Repository: aidotse/PASEOS (language: python)

Issue:
Check config only contains permitted values.
# Feature
## Desired Behavior / Functionality
Currently it is possible to set any value in the cfg without an error being raised. Ideally, users should be warned if they set a value that doesn't do anything.

## What Needs to Be Done
Validate config file during creation of paseos against default cfg to check all parameters present are also in the default cfg and hence valid. Otherwise throw error.

## How Can It Be Tested
Modify cfg erronously and check error is raised.


Discussion / hints:

Fix patch:
diff --git a/examples/Learning_example/learning_example.ipynb b/examples/Learning_example/learning_example.ipynb
index f67be607..3b74ad3c 100644
--- a/examples/Learning_example/learning_example.ipynb
+++ b/examples/Learning_example/learning_example.ipynb
@@ -49,7 +49,7 @@
    "source": [
     "# Speed up simulation\n",
     "paseos_cfg = paseos.load_default_cfg()  # loading paseos cfg to modify defaults\n",
-    "paseos_cfg.sim.time_multiplier = 1000\n",
+    "paseos_cfg.sim.time_multiplier = 1000.0\n",
     "        \n",
     "# Power consumption when training and communicating\n",
     "power_consumption_in_watt = 100\n",
@@ -81,7 +81,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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DKVOmIDY21u71r7nmGgDA7t278b///c8n1yCEEOJdr732GmJjY3HlyhWMGDECa9euxeXLl02vV1VVYevWrZg8eTLuuusui2M7deqE7Oxs7N+/3yKhPX36NO655x40NDRAJpNh3LhxFscZ7xcbNmxwq80dAPzf//0fkpOToVarMX78ePz000+mh6MHDx7E2LFjTQUEW4qIiDB1UJg7dy5yc3NN+/7222+4+eabcfjwYYSHh9s8Pjo62jSL7P3337cq5OiNaxBixU/9aAkJWI6apnOc803M33rrLdO+ALiIiAguJCSEA8DFxcVx27dvt9tMfOfOnXZjeP/99zkAXKdOnexe21GjckfHG//uo0ePtntuR7FxHMfNnj3b9DrDMFxMTAynUCg4AFx6ejqXnZ3NAeDGjRtn9xr26PV6bsaMGabzy2QyLiYmhmNZlgPA3XnnnVxWVhYHgMvKyrI6/s4777T4nkRHR5uOHTBgAPef//zH7r/NxYsXufj4eNOxcXFxXKdOnbhOnTpx+/bt88o1CCGEuK61+/aRI0e41NRUq3tTRESExfv12LFjLY4zf814vzHex43nWbFihdX1PvzwQ9M+CoWCS0pK4jp16sQNHz7cpb/XoUOHuOjoaNO5wsLCTDFHRkZyn376qd17/eHDh7nw8HDT6yqViouMjOQAcHK5nFu/fj3XqVMnDgD3/vvvW137pZdesjg2JSWF69SpEzdt2jSvXYMQczQSS4hIPPzww/jqq6+QlpaGiIgI6HQ6JCUl4Z///Cd+/fVX9OnTR+gQfWLFihXYunUr0tLSEBkZCbVajZ49e2LZsmX47rvvTGX27Y2YOiKTybB+/XqsX78eQ4cORWhoKHQ6Hfr374+3334bGzdudHj8hg0bsHLlSlx77bVQqVTQ6/Xo06cPFi9ejJ9//tlub1wAiImJQX5+Pu68804kJSXh8uXLOHfuHM6dO2ex5seTaxBCCPG+fv364ffff8cbb7yBsWPHIi4uDrW1tTAYDOjevTvuvvtufPLJJ6ZCRUbff/89srOzMXLkSKSkpJiWq3Tr1g333nsvDh06hNmzZ1tdb/r06fjwww8xYsQIhIWF4cKFCzh37pzLvVIHDhyIY8eOYdasWUhKSoJOp0NUVBSysrJw5MgRDB482O6xAwYMwMGDB5GRkYG4uDgYDAZERkYiIyMDe/fuxYwZMxxe+5lnnsGqVaswcOBAKBQKFBcX49y5cxbFCT29BiHmGI6jGtaEEPEaPnw49u7dixdffNE0PZgQQgghhAQvGoklhIjWrl27TJWLjetHCSGEEEJIcKMklhAiqEcffRQffPABysrKTEUoampq8M4775iqRKanp2PQoEFChkkIIYQQQkSCphMTQgR13XXXmcrtq1QqhIWFoaamxpTQ9urVC99//73d/rmEEEIIISS4UBJLCBHU9u3bsW3bNhw8eBDl5eW4fPky2rRpg969e2Py5Ml48MEHERYWJnSYhBBCCCFEJCiJJYQQQgghhBAiGbQmlhBCCCGEEEKIZFASSwghhBBCCCFEMiiJJYQQQgghhBAiGZTEEkIIIYQQQgiRDEpiCSGEEEIIIYRIhlzoAIhr2rdvj/r6enTs2FHoUAghJKicP38e4eHhKCsrEzoU4gV0PyWEEOF4ek+lkViJqa+vh1arFToMQggJOlqtFvX19UKHQbyE7qeEECIcT++pNBIrMcYnxidOnBA4EkIICS69e/cWOgTiRXQ/JYQQ4Xh6T6WRWEIIIYQQQgghkkFJLCGEEEIIIYQQyaAklhBCCCGEEEKIZFASSwghhBBCCCFEMiiJJYQQQgghhBAiGZTEEkIIIYQQQgiRDEpiCSGEEEIIIYRIBiWxhBBCCCGEEEIkg5JYQgghhBBCCCGSQUksIYQQQgghhBDJoCSWEEIIIYQQQohkUBJLCCGEEEIIIUQyKIklhBBCCCGEECIZlMQSQgghhBBCCJEMSmIJIYQQQgghhEgGJbGEEEIIIYQQQiSDklhCCCGEEEIIIZJBSSwhxIKmuAQXcnLAaTQO9+M0GlzIyYGmuMRPkRFCCCESUlcB5C8D1k8EVo/lf89/ld9OCPGIXOgACCHioSkuwfnMTGhLS6Err0DyyhVglEqr/TiNBsWz56AuNxf1u/LRcf16KJOTBIiYEEIIERltI/DNAuCXjYBBa/namZ1A3itAv3uA8UsARYgwMRIicTQSSwgxqV6zGtrSUgBAXW4uimfPsRqRNU9gAUBbWorqNav9HishhBAiOtpG4KMpwJF11gmskUELFHwAfHQHvz8hxGWUxBJCTNpnZyMiPd30dctEtmUCCwAR6elon53t91gJIYQQ0flmAXBuj3P7ntsDfPu0c/vS1GRCLFASSwgxYZRKJK9cYTORNdTX20xg7U05JoQQQoJKbTk/hdgVRzc4TkS1jcD2x4HlvYDcf/HTkYsP8b/nvsRv3/EEoG3yLHZCJIbWxBJCLBgTWfOEtS43F38MGGixHyWwhBBCiJmj6+1PIbbHoAWOrAdGzbN+zTg12dHIrnFqctVpYPpmQBHq2vWN6ir4KdCFPwOaOkAZAaSOAPpnAhEJ7p2TEB+ikVhCiBVbI7Lm7CWwVNmYEEJI0Cr82c3j7CSpnkxNdnb6MY30EomikVhCiE2MUomkZUutRmABIGnZUpsJLFU2JoQQErQ0dd47zt2pySOeBHa/6lxlZHD+G+klxMtoJJYQYhOn0aBk/lM2XyuZ/5TVaCtVNiaEEBLUlBHeO87dqcnrbnW+MvJXT/qmCBUhfkBJLCHEiq0qxOZsJalU2ZgQQkhQSx3u5nEjrLe5OzW55pxz+53b4/pI75GPqBoyEQ1KYgkhFuwlmz0KDiNs2DDTtpZJKlU2JoQQEjDcaWnTLxOQKVy7jkzBF09qyd2pyS7hXNxdxxehIkQEKIklhJjYS2CTV66A7lINNIWFFvvX5ebi/EMPo/SFF8BpNKZ1tGxcnMU+fwwYSAksIYQQ8fOk0FFkO+C6u127Xr97bFf/dXdqsq+dtj1DixB/oySWEGJS+uxzdpPN6jWrobtwweqYhn37cHnTZ6YR15L5T0FfVWX3GkxICBLmz6cElhBCiLgYW9o4u6ZU22j9+k1LgE42pgfb0mnE3wWWbHB3arKv1RQKHQEhAKg6MSHkb5riEjQcOGD6OiItzWK0tH12NnTlFQ7XyZ4eeyP0ly45vA7X1ISL778PsDLE3j/L95WJqfcdIYQQZ7jT0mbCKsvtilBg4lvAZ5lA6S+wPWWXASI7AJ1HAuorgCLEepd+mUDeEteLO/matsH+a3S/JX5ESSwhBABfXVhX0bzWp+Vt1zhV+PS48ZYjrUol8Pe6WPMElo2Nhb662uo6bGwsNGVlaMjP922LHW0j/4HEmTYDtj5AEEIIkQZvJE/utrQZ82zzNRzddyxwQG0pkLeYX2dr615knJp8ZJ1rMfmapoGP2fzflu63RAA0nZgQCdIUl+BCTo5VC5uWOI0GF3JyoCkuafWcLasL1+flWVUXtjlV2E4MthJY4/aG/HwAPmyx440pYYQQQsTNk/WrLbnb0sZY6MiZ+469c7S8FxmLSl08CygjnTtPdCeXQnebXm35b9t4ie63RBCUxBIiMZriEpzPzETNx5/Y7MVqZCzSVPPxJzifmWk3kTUmxAAcVhcuevwJi6nE5sWbnMHGxlptC09LQ/vsbJeSbae4MyWMEEKIdHj7YaW7LW0K/77XuHLfseXcHuDr+ZZJeWE+oKl14mAG0NS7f213GP9t/zvEtfvtjid8GhYJHpTEEiIx1WtWQ1taCsB2v1bAusqwvRHPlgmxpqQE8rg4hKelmfYxVheuz8szbQsdMgQRo0Y5HTMbGwtVz55W2xkAnFbrVLLtNHenhFHvO0IIkQ5vP6x0t6WNps69+44tRz9yfSQXAMABDfYLKvpUXblr+x/7FNj6oHOj44Q4QEksIRLTctpvy0TWXpuc9tnZVudqmRCfnTQZNZs2gQGfqNqjPX8el7dudTpmfXU1GvZYf9ioy8vDX7fdbjvZdrVHn3H/teM8mxJGCCFE3HzxsNLdljb1Ve7dd2xysW+rVB37lKYWE49REkuIxDBKpcNpv/b6vNpqadMyIeaa+CejdXl5aPrlF5vXZ9u2tdlqx1nho0Yh4u+RXiYkBLqS5pHXiPR0tJ8/x7U1Ti3XRF06615ghR5MAyOEEOI/nq5ftcXdljaXzrp/3wlmtJSHeIiSWEIkyF4i+8eAgU4nsPbOY8Sp1TaP0V+86FHsnMEAtm1bsAkJpqTZFOuri8F8epfza5waLrpXSMMWd6eSEUII8S9P16/a0i8TkCncOy9xDy3lIR6gFjuESJQxAW058mrUWgLr7Hm8zda04rBhw/hYv53n2hqnteOAqj+9E1j1aX7aMqsEWAWg0wIGDfW5I4QQsfFk/ao9Ym1pE8iMo+Oj5gkdCZEgGoklRMKMvVttSVq2tNUEFuCLO5UtXoykZUtN03z9TZmSAkZ9yfU1Tt5KYAG+TUDxIeDcz8CZPOD8z+63aiCEEOI77q5fbe24m5YAnUa4d27inr98//CcBCYaiSVEwoy9W20pmf+Uw5FYTXEJKlatRGPBEehKS6G7UAaDTuf9IOVywMF5Izqr0D7lILD2Cy8VxvAR4zTmqtPA9M2AIlToiAghJDilDucfMLp8XCsJqiKUf3//9ml+qquY70mB4txe/gHx+CWAIqT1/esq+NHywp/5kXWaLRW0GI7jgqQUWmDo3bs3AODEiRMCR0KEZqsKcUv2phTXHy5A8YMPwtDQ4OswWyUP06FjWjVUbfRCh+K8ATOBCauEjoL4Gb3/Bhb6fkpYbTmwordrSaZMAcz93flEZ8sDwPFN7sVHXNdphOMHxNpGvq3SLxttf99lCqDfPc4nw0Rwnr4H03RiQiTIXhudHgWHHbbfAfgR2KKHxJHAAoCuQY4z3ySgtlSBC4ejoKljhQ6pdVSMghBChFFXwVcnDo9z7bh+97SewBpbtb1/MyWw/uaoWrG2sfUijuZFH6l1T1Cg6cSE+JGmuATVa1ajfXa2w/WqnEaDssWL0eaWW3Hlqy8t9reZwKalgY2Lhe5SjVWRJmMiaxyRrV6zGlx9KwmsQgFofTiNSq4HdGbJKsegOD8OAIP6UhU6pldDGSHikVmDFljeE0geAtzyKtCuF7+dpjkRQohvtDYS50inEfwInS/OTbzn6AZg8EPAH19Z3kebaoDSo86dw5gM02ypgEfTiSWGpj9Jl6a4BOczM6EtLXVYOdgiSWVZQK+32P9CTg5qPv7EtH9EWhr0jY1oPHAATFgYOm/ZAmVSolWiGznhVrChYdBrtWjcuxe68nK//L1tkYfqoGu0/wwtuls9Ogy87MeIPNS2C5AyBDi+maY5BTB6/3WsoKAAP/zwAw4ePIgDBw6gtLQUKpUKTU3uFUOrqanBokWLsG3bNpSVlaF9+/aYOHEicnJyEB0d7XG89P2UEONInLPV642cee9199zENxgZwBk8O4erU8eJIDx9D6YkVmLopitdVsmnjUTW0TpX4/7aisrmZNgsgTViExIQmZaGdgueQtFj/0TDvn2QxcaCa2gA12g2xUapBMymGYuFPFyHbjdXgJHArGKXtbbmh4gavf86NnHiRHzxxRcW29xNYqurqzFs2DCcOnUKXbp0wcCBA3HixAmcOHEC3bp1w/79+xEbG+tRvPT99BNvzFDZ/rhrrW8iE4FB9zt3DVfPTaQh/Xlq3SNylMQGGbrpShen0eD8Qw+jYd8+0zbzRNZmAqtSAWq11f7aikpUv/sutBUVqM/Ls3m9sKFDoT53DvoLFwCZDDB4+GTTDxiZAZ3HV0qryJOrqCiUZNH7r2NLlixBQ0MDBg0ahEGDBqF9+/ZuJ7GZmZn48MMPMXnyZHz66aeQy/mZG48//jj+85//IDMzE+vWeZZ40PfTx9wtxNMy6WWVwPl9ro3OORqJMz9/4yXgwq8A6KNwwOkyBsj8XOgoiAOUxAYZuulKl6a4BOcyM6ErLbXYHpGejqRlS1Ey/ymbI7BsTAz0ly6ZvpYnJaHLls0ofeZZh5WJJYfhkDK6ChHtA3w9Ek1zkix6/3UNwzBuJbFlZWVISkoCy7IoKipCu3btTK+p1WqkpKTg4sWLKCkpsXjNVfT99CFXpugaZ6gA3l2X2nIkjta9BpfkQcCsH4WOgjhA1YkJkYjqNautEliAL7z0x4CBdhNS/aVLYOOaqzDqSkrw59BhgZXAAgDHoLY4TOgofM+gBY6sFzoKQkTrm2++gcFgwKhRo6ySVJVKhQkTJkCv1+Obb74RKELSqm8WOL/G9Nwe4Ot5rVefdVWh2fWdqW5LAosyQugIiI9RdWJC/KR9djZ05RVuJZ/6qiqrqcWBJiKpEe37SaiYkycK9/AjBL6oZkwVkonE/frrrwCA/v3723y9f//+WLt2rWk/IjK15fxopyuOboDXp/Rq6pr/7EpSTQJD6gihIyA+FtRJrNQqKRJp01ZUQh4Xh/C0NLvrWB0K4ASWVemRNPRSYBZzskV9hS8mYmta25mdQN4rrlczdjRVzt1zEiKA8+fPAwCSk5Ntvm7cbtyvNcYpay399ddf6Nq1qxsREoeOrndjtNMHK9uqTgPlvwNhsa4n1UTaZAr+wS0JaEGdxL700ktWlRTd1bKS4sSJE3HixAm8/vrr+Prrr71SSZFIl3l7nbChQ0VbGVgoejWLkn0xYEMNiOtZJ+4esd5Q/RdQUmD/dWPT9qrTzlUzdmb9mavnJEQgdXX8CFpYmO3lBeHh4Rb7EZEp/FnoCHhNl4C3hvFJLE0hDi7t+wgdAfGDoE5ihw0bhr59+1pUUnTXnDlzcOrUKbuVFOfOnetxJUUiLZriElSvWY322dmoXrMa2r/Xwzbs3y9wZOJUV8onVfWlKnS6oTqwE9mmGuf2c7Zpu6vrz6gRPBExY71JhmEcvu4se0VD7I3QEg9pRPZwoaFa6AiIv5UeAZb3spx9REttAk5QJ7ELFizwynnKysqwYcMGKBQKvPnmm6YEFgCWLVuGTz75BBs2bMDSpUs9qqRIpMN85FVXXoGkZUvdXg8bbHSNclSdjEDioCBZH9uaoxuAMc/av8m6u/7M0TkJEVBkZCQAoL6+3ubrDQ0NAICICCrcIkpUUIeIgXH2UcUfQFQicGKbdZsmWmojaVSd2AuokiJpyXzktS43FyXzn0Liy/+2qDJM7LM9/hKkWqtm7M76M6qQTESsY8eOAIDi4mKbrxu3G/cjIpM6XOgISKALc2F5XtE+4Lct9vsMG5Pdj+7gl+YQyaAk1gucqaRovh8JfO2zsxGRnm76ui43F2fumMJXGSYOycN0iO0psuloQit0MFXY3fVnjs5JiID69u0LADhy5IjN143br732Wr/FRFzQL5MvrEOILyQPBhp9MFPLuNSGSEZQTyf2Fm9XUgSomqLUMUolkleuQPHsOaYpxLqSEoBlAX0Ar/X0CIc2KY2I71sb2Oth3eFojZm768/Etm6NkL+NHz8eMpkMu3fvRkVFBRISmqe9q9Vq7NixAzKZDDfddJOAURK7ItsB193Nrz90FiOzP1JGCMD/H+kzFYjpDBQf9M01CtYBoTHA0EdouY0E0EisF1AlRWKLMZE1H5GlBNax8MRGSmBtcbTGzN31Z7RujQjsjTfewNVXX43s7GyL7R06dMBdd90FjUaDRx55BDqdzvTaU089hcrKStx9990eFWMkPnbTEqCTk306U4YBYfG+jYdIH2cAjm8B9v3XlxcB9qzgi0LteALQutdyk/gHjcR6gbcrKQJUTTFQGBPZ0zfdzI/EeiB04EA0Hj8ewP1iGVw40BaK8CqEJ1A7BAuOmranDueLU3jznIS44auvvsJLL71ksU2j0WDo0KGmr59//nnccsstAICqqir88ccfuHDhgtW5Vq5cif3792PLli24+uqrMXDgQJw4cQK//fYbunbtihUrVvj2L0M8owjlW3l9+zRfSM7Wun2Zgi+oo9fx6xYJaQ2nAzS1vr8OtaSTBBqJ9QKqpBjcNMUluJCTA85O31dtRSVCr7nGo2vIoqLQeKQggBNYIwZlh6OFDkJkZMC10+y/7M76M2oET3ygsrISBw4cMP0C+Ie45tsqKyudOldcXBwOHTqEf/7zn9BoNNi2bRsuX76Mxx57DAcPHkQcFckTP0Uo38pr7u9A+vNAlzFA8iD+9/Tn+e1pzwDHPhU6UkJso3WyokYjsV5AlRQDl3mvV0aptPm6sZVOXe5OhAwcgOTFi037aopLcG7GDOhsjDS4wnA5ONrNXAkDEsdfFDoMkTEAH9wCZH0JxHS03euu/TVA6VHnT9nvHlrvQ7xu5syZmDlzptP7L1q0CIsWLbL7ekxMDF5//XW8/vrrngdHhBORAIyax/9qKX+Z69XVCfEnakknWpTEegFVUgxMLXu9Jq9cYZXImrfS0ZWXo+6rr3Guqhqd3nsXjFKJqnff8TiBDSanOgA/tm2DZ2suCR2KuNScA1ZdC8R1By6etfOhjwHgxNKFTiP4fniEECK0P38UOgJCHDO2pLP1EIYIiqYTe0HLSormqJKidLXs9Vo8e47VlOF28+ZZ9X5tPHAARY8/AUN9PfTl5X6LNxAM+AuYsQPgqLaTDRxQ9aeDUQtjAmuny65MAQyYCUzfQg3dCSHC0jYC2x8HivcLHQkhraOWdKJESawLqJJicLHV69U8kVWfPYu/brvdZu/X+rw8nP7HONTtyvdbvFJmvtK3viQUZUejBItF+jggsb/t9WcTVlECSwjxnroKfkrw+onA6rH87/mv8tvt0TYCH01xrQUPIUKilnSiFNTTiamSInHEVq9XYyKbMGc2zk7NANfUXH5dFh0NQ02N6Wt9dbW/Q5YsFQCZSg+DmoUiTIfYq+mG4ZGy43zSSmt4CCG+oG0EvlkA/LLRenbImZ1A3iv82vvxS6wfnH2zgC+YQ4hUUEs6UQrqkViqpEhaY6vXa11uLs5MuM0igQXDIGLUKAEiDBwGNQtlGy06pldTr1hPGdfwEEKIt5mPpNpb3mBsUfLRHfz+RrXlfOJLiJRQSzpRYjh3mpgSwRj7xNrrI0t8g9NoLEZkbVIoED5oEOr37vVfYIFEoUPXcZTAek2XMUDm50JHEVDo/Tew0PfTTdsfd20q8ICZ/FIGgJ96nPsvn4RFiE/IFDSzyUc8fQ8O6pFYQmyx1feVUSqRtGyp4wO1WkpgPaFlwSoogfUaWsNDCPE2d0ZSj25oXiNb+LP3YyLEl8Lj+ZlNjtZ5E0FQEkuIGWNbnZqPP7Eo4sRpNCiZ/5TA0QU6Bqe2t6eWgd5Ca3gIId52dL3rfV3NlzfQwzUiBiEuFI+sLQVyXwKW9wJ2PAFom1o/hvgFJbGEmLHVVsdQX9/6VGLiFZxehrM/xAsdRmCgNTyEEG9zdyTV2KKEHq4RMWBYgHExBbK3zpsIhpJYEtRaTh221Vbn9LjxFgksE0ItSryF+7u3qXFhvoHhED+wRrB4AoZMAfTPFDoKQkigcXck1Xhc6nDvxUKIuxovApzBvWPP7QG+fdq78RC3UBJLgpatqcOMUomE+fMhT0oy7WfRB1Yms6xKTNzGsAZ8Mk2L7/oxmHs/g/NxwMK7Wbzek57Ue+yayVSEghDifYow944zjsD2yQDAeC0cQgRhvs6bCIaSWBK0bE0dVp8tRNH990NXUmJ7xNVg9uROqfRTpNJlv/Q5hzVZOmzrEoY141mUJLCY94ActR0MuPfyFT9GGKCOb6G1O4QQ79I2ApcK3TvWuLxh92twdGcgRBKojZ0oUBJLgpatqcPnZ80yJbaORlzZuDjArHoxsc3+83YGt25RgtXzH2ZG1Tdg6pVarC0rR5KOKhR7jNPR2h1CiHd9swCoOef6ccblDbXlwC8bvB8X8Z62XYSOQDqM67yJYCiJJUGLUSqRvHIFwoYNM23TlZTwCWorLKYYE7ckXAZm/mBAWn0DVlZU4YXqS5TAehut3SGEeIM7rXWM+t3DL284uh4w6Lwbl9Ai2glyWZ+NZV86DyQP9tXZAwtV2hYcJbEkqDUcO47GX36x2EYJqn9wAJo6qrG8ogoKoYMJZAUfAD8uovU7hBD3udNaBwCiOwHjl/B/DqQesYwcjdfOwLt9PsZJ1bV+uyz3d/bqs1XFnA6QhwDXTnO9em+woUrbgqP/oSRoaYpLUPTQg+Aaabqlr3EA/vkAoDF7x2EA3L5DDpb6wvrenhXU444Q4j53E9A2iYDi7/oSkh+5YoDIRGhHPo1/X70F1xbcjJd3lmHi5bnYqEuHhmN9H8Hf2aueY6DhfPQRvjAf+G0rcPWt4FxMZA0cgwrOhR6sUkZt7ARHSSwJWtVrVoOrbxA6jKDAAHj+U0DZsqK9QYbTX7Vz6wE/cRH1uCOEuMvdBPT8vuaHZ1Ifubo2A02P/4bpp9Pw3tF6aP+u6aCGEs/oZuF69RtYqs1Avr4PjhlScdbQDmcN7XDM0BmFBu9OO2YZDu/pbsVSbQb26HujkmsDA+fF8VmDFji5HQ3yGADNI8CtkTEcmrggKHpJbexEQS50AIQIpX12NnTlFRY9YIkdCgWgdT/TVLNAgp2iw/omFmd/iEfXmyvdPj9xgXGd7IRVQkdCCJEKTxLQgg/4iunhsV4LRwjcb1vxmvZuHDhbb/P1KkThTf1EvKmfaPXaesVipKLcq/H0kZ1FpjbbdL04XEYGuxNDZScRwTSiM1OGGMb90W8OQLi2GuVcNNoxNc4dwwEdZZUwgIEskKtQ951GbexEgEZiSdAyFnYKT0sTOhTx8yCBBQBVi3pNR7oAl4ztBhkO7QfWeHR+4iLqcUcIcUXqcM+O19S6355HJBiDFqrj7lVXjmC8P/ul5TmNSXSmNhsPap7Eb4ZUj85vHNdtiyvQO5mPMsHSArj6DM1oEgFKYknQ0hSXoCQ7G+o//xA6lKByrCuwbAqLf/6fDOfjgK2TtWAStPhXbAxK5L5fU0RAPe4IIa7pl0mFfgAMZk66dVwdF+rlSGyfUwUNXpa/h72qxzCS/c0r11EwBrAuJqcycLii6uCV64vS+b1U+V8EaDoxCUqa4hIU3nUX9JU0hdWRRgUQ6sX1qlciONza/wLym+KQHx6GeQ/IAMjxgy4R1XI5doeGUq9YfzmzCxg1T+goCCFSENmObydTe0HoSATl7ojqAUNPjGKPezWW/YaeFl+roME65RIMlbmXaHvbsYa2KEUPTGXzfFdNWUhHNwBjnrWcVlxXARxZxxdC09Tx0/BTR/DrZ2n6sdfRYzUSlKrXrLZKYNm2bQWKRry0Xr7z6MPDIeMYqxtatZx/nlaqkOP9qDZWxxkCeGmNYIoPUqViQojz2iQKHYHg3B1R3aRP82r1Yg3HYpN+jMW2hfJ1GCo76XQRJl8LY9RYqp2GckO00KH4hvmMJm0jsP1xvgtA7r+AMzuB4kP877kvUXcAH6EklgQUTXEJLuTkgNNoHO7Xbt48MLGWRSb0Fy/6MjRJauPgn7FloWFnxJQ3YMvhrtgTYvuDQFp9AxZUX2q+Bgcc06dCFpCPcQWmawLWTaB1PYSQ1tVVAA10j2w5+umsSkRjs34UAOcr/dpiPHazfjSq0NzKJh41mMLmAxDPutQOqMZe1WNoL6sROhTfOZvP30M/msKPwNprtUDdAXyCklgSMDTFJTifmYmajz9B8ew5dhNZTqNByfynwFVX+znCwMHB/TePAYUNeHKrHmyLShFp9Q1YXlEFBfhec7/ou2CE+nXUINLTcIk9xQdpXQ8hxD7zEaZLZ4WORlC2Rj9dkaPLwn5DT4+STIbhE+kcnWV7lww2D0pGXMtwOsguiS4mr6v4HfhmAV/13xnG7gDEKyiJJQGjes1qaEtLAQB1ubk2E1lOo0Hx7DnUVsdD5vdgjRszpAaehkUi26dOjhllUdin74Ol2gwMVr+Jidp/oRRxPqnqSMwc+YgqFRNCrDkzwhQE7I1+ukoNJbI0C7BRl253arGeY6C30+9Vw7HYqEtHlmYB1LDsxTrEh+tgtRwLDed6uiCWac0+VV/pepFE6g7gNVTYiQSMln1fjYls8soVYJRKmwksExICronWKLjrUjgw+wEGr67hEF9r/XpNGBDdAFS0AcpigGvPNb828DRw73d6vDWyD/YW34O9dt6OfFHVkZjhdMDGacC93wCKEKGjIYSIhSsjTAHM3uinO9RQ4hndLCzXTbXo6VrHhWK/oadppNfea/aSaF887OU4/u/+mX40AA53y3eatrV2DCCeac2+52K2blxLS4UVPUZJLAkYxr6v5omqMZFNWrYUJfOfskhg5UlJ0JWUCBWu5FVEAXNnyaBnGTCc7SlD0Q1AUSzwSgaLi5H86OvA082vh+gYNJXcCUdvRb6o6khaKD3Cr9WZvhlQ0EMDQoJebTnwy0ahoxCchpNhsz4NObpMq9FPTxh7ur6pn2jzdUev2eKLh70tk/cusrJWKx8HT+LqocI9lMR6AU0nJgHFmMhGpKebttXl5uKPAQMtEtiI9HR0+Pe/AJb6khZ0BS6FuXbMpfDmBHbuNgPi6uzvezGS/6VnGbw2mcXhbvz26kjg01EyhKasRljn5ZCF2l5v5e2qjsQOWqtDCDE6uj5opxAbp8H+ou+C69X/xTO6WV5NYH3hgJsFp/R2mt+0nLrszFRoDcfigiHGrTiCjsbBhybiNEpiiSQ5qkJsK5E1F5GejuSVK1D73XeAPsCLDrSioCvAMUBMg2vHxdQDs78w4Mmtegw61TyVpiIKmDlbZkpUAaBvITB3mwGsnjMlst/1Y/DCdBaV0Qzk4UVgQyoQ1uldm4msK1Udg2INji/RWh1CCMD3uQxSxhHIadoXPFoD60/uPOzVcCzuC12JpdoM5Ov74IihG/L/rktxvfoNq+TdOBX6evUbdo+5gFgHVyQmygihIwgINJ2YSI6xCrG2tBS68grTmlfz16vXrEaHnEU4ZaOAU+LL/4a2ohKGJjWgUADawH3afEUFtFHbfz2lEki40vz1pTDnE1rzacEAcKg7g+WTZH8nqvwIrTHBHXSKw9xtBtPra8Zb32wZhkNI+21oODvX6rUcXRZNZfIHWqtDCAGCdqRIw7HYrB/t9enDvmZ82OvKutUthjRUqLpglz7epanLjqZCUw0LJ6WOEDqCgEAjsURyHFUhNm+zcyr9BpvH/3XTzTh7zz24sm1bQCewl0MtE9iTSUBVi241CVcA9d+PsiqiHCewl8L539U2Hn2ZJ7AAP3V4+SQZDnVvvpMOOsVh5g+Ou8satDEAdFbbnZ3KtFU3HFqaeuyZQirkQkjQC6CRInszdHQcgwuGGBw1dHU4AikVzrbwMY40L2Vm4mSZjYqMHnB3WnNQkSmA/p4XCSM0EkskyFEVYvME116Cqr90yV+hCirKrFihMclsWwtM3GdATB1nGklV6fgEdukk4N8f8V/bElPP7/fyVAb3/cjh2kJ++6+psEhgjYyJrHFEtiIK2D7U8XMzReQf4Np/CXXZRKvXnKnqWIUoNEHp1NNoYkeQjsAQQsykDgfO7BQ6Cq8oDe2Gz2t7oY/srNPVfqXI+LB3oXw9prC7bPZotRxp9v4D3036NDwh3xL4/WE90e8eICJB6CgCAsNxtIpMSnr37g0AOHHihMCRCMtWu5yI9HR+CvENY4EWa2VVgwdD99df0FdX+ztUwbUcJQUAVs9ZTPcF+AQ14bLlca/fJsPj2y33O9SdwarbGDz4LQeO4/D2raxVAmuO1fMjsNuHylAZ7TirNGii0XD+QXDatm78TXkqaLBOuaTVqcfEji5jgMzPhY5ClOj9N7DQ99OB2nJgRe+AKe6kgxybdKMkN03YXXG47HKbHm95Wf4ePUi2RxkJJPYDuozmR2ODPJn19D2YkliJoZtuM1uJrCOqIUOgPnIkoKYQG+B4TcClcOCfD8ugUVrvZZ7IquWWI7Dmia+thNdWYuwJXV1XGLSx0FSneZTAGqmgcfg0mjiQ/jytibWD3n8DC30/W7H9ceDIOqGj8KoDhp7I/LviLvENepDsJJmCH5UdvyRoe7R7+h5Ma2KJZLVWhbjlI0D1gQMBlcDqGds/wBVmD1lj6oEntnNg9dbPqozTfc/H2U9gzfdzdX2rKwzaWKjLJnslgQUsqyj+V3sbDPSozjm0VocQYnTTEqBT4BSg4QAMkZ3EQsV6oUMJaM7UsNByLH7Rd8ElLtzP0YmIQQsUfMD3aNc2tro7sUZJLJE0RqlE0rKlNl9rM2GCn6Pxncsqy6/VLMCaJWbGoksVUcBLd1onnMYWNy3pWQZLprKmxNfeCGvLRNaZ9a3O0mvaQFM90ivnaqkKUVimvxOf6McAoBY8rWrfR+gICCFiEpUsdAReY7yrTZHtQhwuO9yXeKa1djzD1G9govZfWK27RehQhUc92t1G04klhqY/WXI0pTgiLQ3ay5ehPnpUgMicxwF22o03O9IFiFa1RZeTF61eM65RnZHLmdad2poC/F0/261tACC+hsNt+w344EbHU4RdWd/qCoOmDXSNXaCp/IfXRmPN0fQmFzByoP/0oJ7iZA+9/wYW+n46oG0EPpwEnN8ndCQ+sVSb4VJbGeIb8ajBz6p/0rIfmQKY+3vQrZGl6cQkaLW2JrYuLw/qX3/1c1SuY8Anso70PwM0GBpwuBv/tf7v/NE4cqpRyrBmPGtKLF0dOa2M5hPc1ta4Gnu8ejOBBQCZ8gqUUb8grONbYBTWibqnnJneRFOO/8bprKc41VUA+cuA9ROB1WP53/Nf5bcTQsTJk5/bbxYEbAILgB5oioSxvy0Q5DOljD3aiUtoJFZigv3Jsaa4BNVrVqPdvHkomf+UVXXipGVLrbYHksPdgIvhwO5rZBjxOyfYyKkvaS5fB3XpnT47v72qjZ/rh+Mx+RdUDMpcv+kAwwK/bLRdpTTIClME+/tvoAnY76e2kU9C3f25rS0HVvQCDHb6rQWAI4ZumKx5UegwCGimlEkQdgbw9D2Y+sQSydAUl+B8Zia0paWo/eFH6KuqTK9FpKcjeeUKMEolEl/+N/4cNdqqzY5gFAr+EaPu7w8ECjl0nB5ynePnR9URwNnOIYhsAHr81QQAGHiaH309ncTgSs8kjIi5CruKd4EBA87GeK5x5FRafPtcrQpReFM/0eZUMvM+tA/Iv0YME+Q9U49ugMPvh7EwRdVpYPpmQBHqr8gIIbZoG4GPpvDr7Oxp7ef26PqATmABoI6j9yqxsOxvmwcl472ikZJCPdpdRtOJiWRUr1kNbWkpANhMYLUVlSh59jn8dcut4klgAUCrBaNQmH2tQ15vDlXR1j9+h7sBP/QB8nszeGEGi6W36vDfe6KtCjXd+wOHjeM3YunIpegQ3sFmAitV8tBzPplS7Cxjkrtad7NgMYiHk/+vqDAFIeLwzQLHCay5lj+3xunH+/7rm9hEZL+hp9AhEDPGQlCrdbcKHYpwlBFCRyA5NBJLJKN9djZ05RUWU4XZuDgkLVsKbUUlzs2YAd2FCwJGaB/X2Fw+/VB3BmvG8Qnsw18C1xQBsbX2KwOXaauwfJLMVKipIgr4YiiDbV9NwfDE4bhQL86/s7tkyhooY/OhLpsoaByb9Gl4Qr6FphY76+gGYMyzQVeYghDRqC3npxC74uhH/Ifn37YAtWXw9UwYMdBwLDb9XbGeiMs1srNChyCc1MBpZ+UvNBJLJMNWX1h9VRVK5j+FqrffEm0Ca64qElgxiS+gpGcZ/Pd2OV6YzuK7frYTWCNjoabv+jHIuZsvrFTdVI3tZ7b7+W/ge9ranlCXCf80lgpOuIgKUxAirKPrba+BdcSgA/a9AdRegFQTWD3H3zdbe582vr5ZPxpViHK8MxFEBBOk/VKpR7tbKIklkmIrka3LzcXlzVts7Cy+QkYcB8TUWt5pzSsDyxn7kyOM61sb4yJ9HaZgtLU90VR8D8QySSRHl4X9hp5i/K8kToVOTmMkhHhf4c9CR+AXl7gIi56jI9UrnXqfZhh+GnGOjpIFsQratcr97qFZTG6gJJZIDqNUImH+PDAhrVRDFeHwWXwdcNt++0ULdFzrxTTqdIG5+N+giYG6/GaIJYEFnGvNQ8xQYQpChBMkP3/v6W7GZM2LyNRm4039RJQivtX3aQ3HYqMuHVmaBVBD6eeIibMOeGGtsvGjn659P77ib5skj8/pUyHRfKVw4jJKYokkXVy/HlxTk83XwkeN8nM0ztPIga8G0bBeS5xBBpnyEsI6rhG0qJMtxoIT16vfwFJtBvboe6OSayPGZyTCq/yDesgSIpQgKAyj4WQ217O2fJ/O1/exGK29Xv0GntHNogRW5Dbp0zx+YGwccU+regpNd20BHtgJyMTzcNzKkP8LihZ1vkBJLJGkdvPmgY2Ls/kaI5MhTKSJrFIHPH6qC0YnjxY6FFFhZPzotLGokxgZqxZP1z6LQeq3MUK9CucN8UKHJS7qK8CZnUDuS8DyXsCOJwCt7YdNhBAvSx0udAQ+t1mf5nA9q/F9OlObbTFaS2tgpcHTWhTmI+7FdRye3nociGwHhIv0Xi1TAIPuEzoKyaIklkgOp9GgZP5TFm12zNXl5UEt0ub14Wlp6Pfyf5AQloCRSSOFDkd0DNpwqMvGCx2GU0oQjxs1y3DB0FboUMTJ2Ivyozv43pWEEN/ql8l/KA5QBw3daT1rEHClFkUNF46jhi52R9y3/1KCylq1eO9BtBbWI5TEEknQFJfgQk4ODPX1KJ49x6rNTkv66mp/huc0tb4J9317Hz778zOcqBZnoi0kmaIeqvZfCx2G09RQ4iP9WKHDEDfqIUuI7xh7u66fCHx6DxAWK3REPnPGkETTgYOAM7UojCOuQ9T/xSTNv+yOuBs4YNPhIterdvtDpxG0FtZDIp4kTghPU1yC85mZ0JaWovaHHy1GYCPS05G0bCmKHvsnGvbtEzBK5+h278f0Mr5dzsUmca39FAtGJq3pp9RP1gnUQ5YQ79I2At8s4PvCivEDug9MZnfjVd00mhocBIxrnJfrpiKD3YmhspOIYBpRx4Viv6EnNunHOP3/YP+ZajzKKgHU+zZopzFAZAeg80h+CQ6th3UbJbFE9KrXrIa2tBQArBLY5JUroK2ohPrUKbvHKzp1grakBNC1XvnXV2rCgOgG/s+DTnGY+YMBa8ZTtVtbGLYBgA5SeXsyruG5W74THCfKzk7CM/aQHTVP6EgIkT5tI/DRFH6WQxBRMnpksDvxpn6i0KEQPzGucfbke16n1gEd+gJn8rwWl2c4oLYUyFsM7FoCRLQH2nQAVG2A1BF8v1h64OsUmk5MRK99drZFX1iAn0KctGwpGKUSFa+9Znd9LABoi4sFTWABPoG9FM7/uSIK2D6UfvTskUechqr9l0KH4RLqJ+sE6iFLiHd8syDoElijobKTQodAJCZCJQf+8W+hw7CNM/AJbUkBFUV0A32SJqLHKJVIXrnCIpHVV1XxxZ1qalD700+OT6AXxzTPmHqgKBbIuZtFZTRlO+Y4DtA1dAQAGDTR0FSLs7q0PdRP1glB0sOSEJ+qLeenEAepCEakBXqIaA3sFAO0vwYIlch6cSqK6DRKYokk2Epk63Jz8efQYYBGI2BkrrkYyf8ilhgGMKgToLk0FA3nHwSnlV7F35Z9Cs8a2gkdkrgEQQ9LQnzu6PqgWQNrSx0XKnQIRGJ2/VmJJq0euPcboUNxDRVFbBUlsUQwxorDnFkSamsbp9HgQk4OtBWVVoms1PQtBGb+YBA6DFFi5HVQl90qyQTWnHENTxFHa1ospI4QOgJCpK/wZ6EjENR+Q0+hQyASc+R8DXJ2/A4k9ACuvVPocFxzdANfgZzYREksEYSx4nDNx5+gePYccBqNzW2cRoPi2XNQ8/EnfIXiikrEP/ao0OG3TmZ7urBaDnw5mKYS26KI/B9CkjeAL+okfTTtrYWqP2mNDyGeCuJp+RqOxSb9GKHDIBK0uaCI7xc7YSUQEi10OM4zFkUkNlESSwRhXnG4LjcXxbPnoOrddyy2FT3+BIoff8LUE1ZbWoqK117D2SlTBYvbKWGhePmRdvi+L3Cwjwq/pja/pNIBtx7kBAtNbAzaMGhre5i+VkSelFxRJ3to2lsLxz6lNT6EeCoIp+Vzf98yN+tHU3sd4hatnuP7xSpCgdiuQofjGiqKaBclsUQQLSsO1+XmQl9RifC0NNO2+rw81OXlmb6OGD0Ktbm5gEHE03EZBt9lp+OXyCqsvlmOV2/V45UMFoe686OvVJnYkkzRAICBtvZqANIs6mTPAZr2Zo3W+BDimdThQkfgdwzDTyPO0WUKHQqRsP1nqvk/qNoIG4irgnj2RWvo0zQRhM1CTXl5YACEDh5stX/4yJFo+O0EoFb7MUo3cBxu/bIcCfLmdZ16lsHySTJ814+hysQ2KCL/BwDQXBos2aJOtmzSp1GlYltojQ8h7uuXCcgUQkfhNxqOxUZdOrI0C6CGUuhwJC0+Irj//erUfy9VktqDoOrTQP6rdN+0gZJYIhh7iWzjwYNW+9bv3g1DdXXzBrncHyG6RXvgMLI+qQSrb542rGcZrBlPCaw5gzbM9GdF5P/AyGvBaSX2hNSBSkRjs54fVeZoBnkzWuNDiPsi2wHX3S10FD5VYmiLfH0fLNVm4Hr1G3hGN4sSWA91jY/AV4+PwJDOgfGQ2B3VdRp+XazUHgQ1XqL+sXZQEksEZSuRbY0sOhpgxT3CNegUh7nbDFAZxB2nkGSKBhi0zeu7Amk9rFGOLgv7DT3B0LMLS7TGhxD3jV0ERARmCy8Nx+J2zb+Rqc3Gm/qJtAbWS/6qrMONK/LRoNGhfZsQe7UnA9r5iw0YtvgnZP9QAd21dwkdjuuof6wVSmKJ4BilEknLljq9vywkRJTTiqvCgcPdmr8edIrD9O+l08PW5zg56v76J7S1zWtFZYo6UyIbSOthjdRQIkuzABt16TS12Byt8SHEPdpG4NMZQF2588cw4v+oJ+XiTQyAm65pDwUr7szwcqMOx0uuoOxKEwwcH3ew0Rk4fHzwPLIuTIaho5PTipMHi2vklmpLmIj/nY0EPE6jQcn8p5zeX1dW5sNo3HeuPbDydlnQFnGSo5Up3owOEZ3fhrr8H9aJrCYGDefvD5j1sObUUOIZ3Sxcr34DS7UZyNf3wRFDN1zigq/KqEkQVlglxCu+WcB/iHUFJ+JiiH+TcvGmOwd3xFvTB2Dv0zdg/rgeGNk9Dv06RmNk9zjMH9cDE/slCh2iTcG8yuXncw14LmIRMGCm/QRVpuBfz9ohvin8VFsCAMBwHK3WkpLevXsDAE6cOCFwJN5h7ANrbKMjdYe6M1h1G4MZuRy2D5UF1RpYuUwOnaH1Hq96TTQa/pqNkORPoYg8adquuTQU6rKJPoxQXB5lP8d8xSahwxBG+vPAqHlCR+GyQHv/DXaS+37WlgMrevPTCiWG42B3WYWGY7FZPxo5ukzJrX0d0rkt1t03GCEK+zNtmrR6ZK09iANnL/oxMtIahgEOPjMW8cxlvk5D4R5+lpAyAkgdAfTPBCIS+J21jcC624Bi65otgpHofdScp+/B4q2OQwKerQQ2Ii0NnMGA+vx8ASNzTXU4EFvP/3nQKQ5PbAeWT5JBL/KpRd7mTAILAKyyBiHJn6KpeBrwdyIbiFOJW7NJn4Yn5FugZPRCh+JfMgX/4YAQ4pqj6yWZwAJ8wlBg6I5d+msxUPYnIphG1HGh2G/oiU36MZKbQqxgGUwZkIKFE3o5TGABIETBYt19g5Gz43dsLiiCVk9jR2LAccCMNQfw+aPDETJqnuOEUBEKZG0H/p0IQCQzGwr3SD6J9RQlsUQQdhNYQFIJLACwBn4t7MDT/NeDTnGY+YMBa8YH/hrI4YnDUVBegCZ9c7U8hUyBa2KvwdHKoxb7xobEorqJrzCtiDwJrv23aCq+B1z7L6GpHhWQU4kdMVYvvlu+0+EoRcDpd0/z021CiPMKfxY6ArdYjbRK/LndtclRWJM1CPGRKqePCVGwWDy5D+beeBXmfPoL9pyu8mGExFn/K6vFjDUH8OH9Q1p9GAEAYJWAXiTVgam2BK2JJcIoW7zYMoFNTwebEI/6vDzTtpBBg8ConL9JCCW6EYhobC7qFCxrYduq2mL56OXYeOtGyMzeSrQGrVUCm5aShq8nfY20lDQA5kWc5FCXTQy6BNbIlerFAbHwo9MIYPwSoaMgRJok+KE1X39NwLXJOXnhitvHxkeqsHxaX9EXgQomhwovIeOdfZix5gAmvfkzZqw5gP/uPM234zHSNgIfTRFPAgtQbQlQEksEEnv/LMgT+NGY8LQ0JK9cgbgHH4IikS+AEDpkCNTHjoETYRViW64u4X//4ToGOXcHRz/Yi+qLWLBnAVIjU7H59s0IYUNs7peWkoblo5cjTBmG5aOX447uU3EV91TQJq7mnKlerOVYlHPREh+plfEFMqZvARS2/58QEvTqKoD8ZcD6icDqsfzv+a82F3CR2IdWDcdirvZRyU0Vbo1Wz2HT4SK3j0+IDMGUAckuHdM1PkIUiW/X+HCX9pdKK59jxZex+1QVjp6vwe5TVVj23R+4/pWfkL31OJq0evcKqvla6gihIxAcTScmgmg8fhy6an5qqfE9TpmchI7r16Pq3XdQv+dnySSwRgNPA4e6AxcjhY7Et2KUMbikuQQAyCvKw9xdc7F89HL8OOVHjPjU+k11ycglULB89T8Fq8Ci619A0yA9rQ/6m7F68XLdVGSwOzFUdtJqvVgtQrFQvh5T2F3SXEM7+AHgZufbaBESVLSN/IfkXzZar3k9sxPIe4Wfhp8yhP9a5IzLI6TYLsdZ+89U49Ex3Vrf0Y6FE3rjTGW9U8WejMWjapt02HS4CPvPVKNOrUNlrRrFl/zXL3RI57Z4Z8YAPPRhgdNx6/QGFJyv8X1wPqDV8+14qsvO452qjSJrScQAfTKEDkJwVJ1YYiRXTdGG+sMFOD9jhsX8yIj0dCSvXAEAkqtWfCUUaGN2H/muHxPQ62Gv73A95Kwc+cXNa5enXDUFVY1VyCvKs9rfOBJrTGTNVdaqMeXtvThX3eDDiANHHC6bEt0Bsj8RzkjkQU/H4cB9XwsdhccC4f2XNBPF99M4TdGZUZ7kwUDpEcDJInpC2m/oiSzNgoCZQtxSv47R2PaIk31G7WjSOn6Y21rxqBlrDmD3Ke+trZUxgMFGRtAyDmfintQvCQCwuaDY5jmlRLSdBAbMBCasEjoKj1B1YiI5ZYsWWS3wq8vNRfHsOWDjYiWVwAJ8AnspHIipl9Z62P4J/VGjrsGZy2dcOm7vhb2Y2HUi0lLSkFeUhw5hHVBcW4z9F/bb3N98tLZlIhsfqULbcCUlsU6qQhTe1E/Em/qJ+Ejxb4xgJZJM1ZwVOgJCxMmVaYpiau9hh55j8Kl+jCTb5bgiQuX5x2fzYk/mI6wRKjmGdolFxsAUh8Wj6tTee5ihYBnseGwEfvpfRatxtBb37dcl4slNvwZMS6EhspOt7ySEoxuAMc8GdaFESmKJ33X+9BOcHjce+irLJ4h1ubkIGzYMCAkBmkS0eN4GPQDz56Ix9cD5OGDJVOmshy28XIg149bgkZ8ewYX6Cy4dm1eUhy8nfomVoSutEti0lDQsGbkEC3YvMI3MOkpkvfFhIBiFSWUUFuDX9Gkb+TYFhBBebTk/hTiAHDT0wDO6WUKH4XNDu8R67VzxkSo8Oqaby9OTvXnvnDIgBVd3aIOrO7RxOg57cWdvPRYwCSwARDD+m7LtEoOW728bxG12pDFkRAKKLDwc3b77FmxcnNVrDfv2iT6BBSwTWIAfgZVSAgvwhZke+ekR9EvoZ7Fd1uJtIS0lDXum7UFbVXMhphpNDaZ+NRWVDZVWCezy0csRpuCLOBmrEQPNiaxWb7nma0hnKvDkjjpOQgmhQQes7GNdqIaQYCbhvq/2hDAaoUPwOQXLIGNgitBheO3eOaRzWyyc0Msr56qobcJnHhS9EiNR32vPSqslpbdREksE4SiRlZKCrsD3fSHZisTGEdjEcL4qtIpVwWDWyNuYlEaFROGbyd8gNiTW4thdxbus9jUv4mQrkV1yyLLFSsagFFFUXZSaA4aeQofgmvpKvihN7kvA8l7AjicArfgfWBHiMxLt++pIZ6YcKgR2IjtlgONpvv7i6b1TwTK4a3BHrLtvsHM9Up2w6VARdIbW95MSUd9rK34XOgJBURJLBKO7VIPw0aPBxnpvWo6/MRzw/jhpJrDm1o5fi67RXaHWN09RbZmUhinD8PWkr00Jrzl7xZtaJrKJ4Ym495p7LfZxp90AATbp0+y25RE9gxYo+AD46A5+mjEhwUiCfV9bE83UY6F8vdBh+Iw3Ry095c69MzZCiZHd4zB/XA/sffoGLJ7cx2sJLACvFpoSC1Hfa+urgnpmEyWxRBCa4hKcz8zElS1boLzqKqHDAQC4U0Cv/xng/u+k0fKEZVgMbDfQaruMkSEpIgn/veG/pgTVXlIapgzDl5O+NCWlCaEJuLXLrXarDwPNiey0HtOwdvxaJEUkWe2zcEJvmlbsokpEY7N+FACrOmnScW4PTTMmwUtifV+dNYXdhThcFjoMr/LFqKU3uHLvHNK5LX5ekI4P7x+CR8d088lo8vmLgVekUdz3Wo5fFxukKIklfqMpLsGFnBxwGg2q16yGtrQUANC4b5/AkfGcHUvVtLh/DfoTUGrEP39Gz+kRwoYgRhlj2hatjMZj/R4DACRFJGHt+LWY1mOa00np+pvXY/HIxXb3NT/muaHP2UxgAb7a4br7BuOuwR1parELcnRZ2G/oCUbK/2Q0zZgEq1TPWrQ4FCbcUh0lo0cGK/5+tvbIGD7h69cx2qejlt7gzL3Tnwl4o1YaD/VdJep7baGT1c0DEPWJlRhR9LVrQVNcguo1q9E+OxuM0nZJfU1xCc7NmAHdhQtQ9uoFNDWBSUiAer/ttixidv8/Gby6hkOM2QPH83HAvAekV2X31i63YvHIxUKHYaGyVm2zbP+p8jp8/kuJV64RruR73dlocSc5KmiwUL4eU9hdUDIB8gGi0whg+mbRVTMW4/svcZ/g38/acmBFb98Ud0odBXAG59v3eFm+vg8ytdmCXNtTdw3uiMWT+wgdhsvs3Ttba9XjTcMW/4QLlwPzIWQSKpCvmgOWEdkHh+RBwKwfhY7CLdQnlgjKOC1YW1oKXXkFkleusJnIVr37DnQX+CJCmt//Xoh+xkZ/0uhooKbGdwG7QCsDFDYGWB/+Fpj9IIOV73GIqQf0DPDeOOlNakhLScOL178odBhW7JXtb9LqceFyo0el+82bttc26bDpcBFW/PAndBLuxq6GEs/oZmG5biq+UD6HJFm10CF57twe4NunJd/InRCHItsB190NHFnn/XN3GQ0Me5T/OTqynk9o/Ui0bUlaIaY1r65yt1WPN3VsGxawSexEdq/4ElggYJclOIOSWOIR82nBdbm5KJ49xyqR5TQa6CsqnTuhSBJYwHYCCwCDTnF47CsGsx9g8NJHHN4bJ8MfHaWVxCaGJzqcMixGxmlTOTt+x+aCImhtDKMak9RHx3TFF7+UOnwiHaJg8eiYbvho/7mAuOlWIQp/cYlIQgAksQA1cifB4aYlQPVf3h8x/fl14PBaICYViEwErhR79/ytaOCsR/4YALG4jGnsTgyRnUQE04g6LhT7DT2xST8GVYjya4zmzB9wim3KsJSM7B4XUD1izQ2RnRQ6BNsS+wH5y4C/dgKXCgFtA6AIA6JTgW7pQP/MgL2P0nRiiRF8+lMLnEaD4tlzUJeba9oWkZ5uSmRtvS41h7sBq25n8fh2Awadav5xOdSdwfJJMugltoZTxaqwZcIWdIrqJHQobvPmtKlp7+wLmJvuo+znmK/YJHQY3pP+vKgauYvt/Zd4RjTfT20jP2J6dEPA9I0tj+iFeTErTe/PwzuFo1vBvzCq4Xubyx40HIvN+tHI0WVCDdvLkrytQ1QIuiVE+H3KbSCrqG3C9YtzJT27yZ6tyhfQX3Za6DBsYOCwNCkjB/pPB8YvARQhfovKGZ6+B1MSKzGiuemasZfIJi1bipL5T1luT0uDpqoKmt9+EyJUtxzuBrw2mX8yO3ebNBJZBgw4G29qieGJePfGdyWdwHrbG7mn8Or3fwodhlfEowY/q/4ZOGtjO48GsrYLHYWJGN9/iftE9/2sq+Cn/hbuAdRXgKpT/O9SJJMDc0/yI0DaRuCjKU6NNu839ESWZoHPE1kZA+Q/NQbJMWE+vU4wyt56DB8fLHL5uIRIFSpq1a3vKJD1isUYxR4XOgz3ibDWhKfvwdKaA0lEiVEqkbxyBSLS003b6nJz8ceAgRYJbHhaGpJfX4UuGzdAee21QoRql9rB7KGBp/nkFQCWT5LhUPfmhHXQKQ4zfxBfZWJbCSwAbLt9GyWwLWQMSoE8QN4Jxd0KwA0lR6iPLAkeEQn8zIPMz4F210g3gQUAg6659cc3C4Bze1ptY8dxwFDZSb/0mTVwwJObfkVTgFbTFZI7LfOGdG6LH+aMwl2DO0ImrjEBkwOGnkKH4BljrYkAEiAf3YjQbCWyVvuY7dv5/bX+CcwJegZYcC+DX1Obtx3vxI/AGhmTVT3LWCSyFVHA9qHS+TFasHsBtPrAmK7mLQmRIZg6MEXoMLxG1K0AXKWpDbibLiGtqi0HftkodBQeO7BzO7L+sx26IxsAtN7Gzvie5a8+swfOXkTOjt99fp1gY972p7UHxHJZc/ufqDAlFk/ug68eHynKRHaTPg0GToSBueLohoDqxy6dT99E9BilEknLltp9vS4vD8Wz58BQX4+S+U/5MTIHlEosfbQ9SuNZvHZnCHb1AvJ7M3h5GovXJrM2k1VjIvtdPwY5d7OojJbOm1peUR7m7ppLiWwL7jw5Fis1lMjSLMBGXTr0Ur/hAgF30yWkVUfXB8TaWIW+HteU7YAcOpeO82ef2c0FRagU8RRWqQpRsFg8uQ/2ZY/F/HE9MKRzW3SICkF0mAIdokIwpHNbzB/XA/uyrfvv9uzQBtMGie/BciWicZzrLHQYnjFom2dIBABaEysxolvDY8bZIk5sXBz0VVV+iso+ebt26Pr1VyjSVSHjyww06Bqs9mH1/Ajs9qEySSWr5lIiU9A1uivyivJM29JS0iRXndjXmrR6h5WPpehjxYsYxv5P6DA8J5ICT2J+/yWuE+33c/1E4Ix/kjhfytfzvVbdWUfozz6z88f1ELQtDbHWpNUja+1B0RVdTEYF8lWzRTlS7LQuY/glCyJAa2KJKLhShVgMCWzo0CHo9sP30Ico8WrBqxYJbLQyGkoZX1RCzzJYM15ao60tdY/ujnkD5iEtJc20jUZkrRmfHO99+gb8X1rXVqe+SYGKcW0ERLQKvdx+hBAx09QJHYFX7Df0dLtfrD/7zO4/EyBtyQKI+ZRkhYgKZxYjAZ9Jve5EgLy/AJTEEi+wV524R8Fhh2tkhXRYXoxGRoe5u+ZajFAmhicirWMaNAaNYLF5U4QiArlFuXjwhwdtJrJLDi0RLDaxio9UYcH4q3HnYPFNZ3JGHC7jUfZzrFcsRnfGv70hfSaAbrqEtErmnxYzvqThWGzSj0Ed514lVHePc+ta6gB52BdgQhQsFk7ohVv6JIpq5PMF3X3SrjuhjBA6Aq+hJJZ4xFGfWFl4OBLmzwcTIq6+VJVtgH9dX4YhG4dYJLCjkkdh223bcO7KOcFi84YoZXPD+Dot/+G/tL4UH578EMtHLzclsonhibj3mnuFCFESpLZOVgUNXpa/h72qxzBfsQmj2OOIZJqEDss7AuimS4hd2kZg++NA0T6hI3GbcXRqs340qhDldkXX/X6sBBuhkvvtWsR5xinFn/9SAjG1nTXWnThtSBQ6FPekjhA6Aq+hJJZ4pGzxYpsJLKPknyRfXL8OXJO4Pki3qQfaXbRui8NxHJ7a/RSOVhwVICrvuSbuGsSGxFpsS0tJw4JBC6BgFVg+ejmm9ZiGtePXIikiSaAoxU+s05lsUUGDdcoluFu+M3B6xJoLoJsuITYZe6keWQdw4mvb5iyG4RPQHF0mAL6iq4Zz0MPOBuMorr8M7RLb+k7E73J2nBDdmlijNmhAR6Zc6DBcJ1MA/TOFjsJrKIklHom9fxYUifzTqJYJLAC0z84W3ZRilR54bQ2HxErLD/u7S3ZjV/EugaJyXofwDohWRtt9/efSn1Hd1LzGp2URJwWrwHNDn6ME1gnm62RHdIsTOhy7FsrXYajspHTX6DgSYDddQmz6u5eqlGk4Fht16cjSLIAa/OcAV3pXtxzF9QcFyyAjgFqsBYqK2iZsLhDvcpgMNk+aD4z73cP3ow4QlMQSjyiTk9Bx/XpE33WnVQILNPePDR0yRKAIbWM54JUPOCg10nriPTxxOLpGd0WNpsap/Uclj6IqxF4QH6kS7fqXeNRgCpsPAKKN0SMBdtMlxIqE+8JWcW2Qr++DpdoMXK9+A8/oZpkSWCNne1e3HMX1hykDUhAfqfLb9YhzNh0Sd5eAIbKTQofguk4jgPGBVQeFFgIQjymTk9Bh4UKH+2iLivwUjfNCdMDy1QY88RADvcinixodLjsMtcGyp12UIgqXtbYbwzMBUWNXHMRa/EOyT4SdEYA3XUKsSLQvbA0XhuHq162S1paMawgXytdjCrvL5vuVhmOxWT8aObrMVs/nLUM6t8XCCb38ci3iGrFOIzbyZ/VsjzFyoP90/l6qEFeNGk9REkt8ylj4SVdaKnQoNiVcBmb+YMCa8a6t2RFKywR2ZNJIcByHPaW2p6HtKt6FJYeW4Lmhz/kjvIAm1uIfknwi3CqGH4G9+bWAu+kSYqXwZ6EjcIsOrNMJpxpKPKObheW6qchgd2Ko7CQimEbUcaHYb+iJTfoxfp1CPGVAChZO6IUQhTTu/cFGrA+NjfxZPdttqjbA0EeBQfcF7GwmcX4qI5KkKS5B9ZrVaJ+dbZpW3LLwExsbC321eHqyVUQB24dKc1b9iES+2I29BBbg189SBWLvGNK5LXafEr7HcUuSeiLsNA748zvgcglf1Kl/ZsDehAmRaguptqhDHC67lHxWIQpv6ifiTf1E3wVmR3SYAg+M7IKMgTSFWOzE+tDY6IChJ0axx4UOwzaZgn8IHIAjry1J89M7ER1NcQnOZ2ai5uNPUDx7DtRnz+JCTg7aZmY1F35KS4Oyp//K5jtypAvwfV8g524WldHSnHK7p3QPdpfsdrhPxzYdkRBKH/69IWNQiiirFEviibA76iuBMzuB3JeA5b2AHU8AWnFVOifEKyTaQkrGcMhgdwodhtM6x4Xj0THdKIGVALG3t3On6rZfdBkDzP0dmLAq4BNYgJJY4iXVa1ZD+/eU4brcXJydNBk1H3+CimXLkLJmDaIzMqCrr0fjHuGrL9aEAcsnybD6Zjk69RiExHCJ9vpqYVTyKBy4+4CpDywAHLhwAHN3zYVWL731VmKTEBmCKQOShQ7Dirt9GCXFoAUKPgA+uoNvRUJIIOlwndARuG2ohJYziH10jzQT60NjI5eqbvshHpPJ7wbVrCVKYolXtGylY+wNW5ebi4olS9B09iyaDh0SKjwL0Q3AjFz+beV41XGU1pda9VUVg390+ofTcY1IGoGVaSsRpgjD8tHLLRLZvKI8SmS9ZOGE3qJ7QizaJ8K+cG4P8O3TQkdBiJeJtwpra6S0nIH6wUqHWB8am3O66rZ/wglKlMQSrzC20rHVE7YuL080CSwANCiAPb34txW1ni+UZN5XVQwYMLisvux0XOZViBWswmYiu+QQVXn1VIiCxbr7BuOuwR1F85TYlSfCAeHoBqCuQugoCPGeC78KHYHbpLKcgfrBSs/CCb0xKDVG6DDsMlbd3qhLt/sg2e/35PxXgfxlwPqJwOqx/O/5rwbsPZOSWOI1jFKJhPnzIE9KEjoUh8K0wOM7DIiv4cDqOdz/rR7xNeL69M+Bw4GyA6av24Y4Hv3bXbIbc/LmmEZbWyayieGJVODJS0IULBZP7oO9T9+A+eN6YGT3OESGCDtNzdknwgHBoAWOrBc6CkK8R6KFnQC+r6sUUD9Y6QlRsEiNCxM6DIeMVbevV7+BpdoM5Ov74IihG/boe6PEEOv/e/LBd4Dcf/H1JIoPBXxdCUpiiddoiktQdP8s6EpKwMbFOX0cEx3tu6DsiL8CTNqrx9xtBow7ymHhRnEksrb6uo5KHoXesb0ttl0Xdx3ah7e32LareJfFtGFjIjutxzSsHb8WSRHifrggNfGRKjw6phs+vH8IHhrVRdBYnHkiHFAKhV9bT2xramrCwoULcdVVVyEkJASJiYm47777UFxc7NJ5UlNTwTCM3V//+9//fPQ3EIBECztpOBab9GOEDqNV1A9Wmipqm/D5UXG2Z2zJWHU7U5uNyZoXcZ5LQJJMRDP8ArSuBK1yJ15jXtxJX+V8KxKupsZHETl27Vkg4QqfuCZcBm7bL3y/2HGp4yCXyXGw7CAqGiowKnkUGDDIL8k37TOkwxC8dcNbAIDZebORX9z8mnH96/LRy6FgFVCwCuoR6wcZg1Kw6qdT0OqFexBiqw9jNFOLSPA3rDqEIA61SGAugWWEf2DjEQmPXAWypqYm3HDDDdi7dy86dOiA22+/HYWFhXj//ffx5ZdfYt++fejatatL58zKyrK5PSrKPz1F/SJ1OD9iIhEcBzAMsFk/2m+9Xd3BAJg6MAUv3t6b+sFK0KZDRYLeU92VhApMY/OEDsM2Y12JCauEjsQrKIklXtM+Oxu68gqLvrBipWaBhCvNXx/qzuCDG4WfmFCjrsGbN7yJisYKvP/b+zBwBnz252em19NS0kwJKgCsTFuJlw++jOLaYuy/sB9A8/pXSl79x1iE4uODRUKH0mofxjhcRga7E9fLTuBqWRFicUV605AlOnIV6F5++WXs3bsXw4YNw/fff4+ICP77tHz5cjz55JO47777sGvXLpfO+cEHH/ggUpHplwnkLeFHSySAYfhpxDm6TKFDseva5Ci8eU9/JMeIezoqse/A2YtCh+AyFTT4WPlvcT8oProBGPNsQFQxFv5TOwkYjFKJpGVLXZpKLBSVvvnPh7ozWD5JBr0ICvXsv7AfSw4tQVJEEp4b+hzu73O/qQVQywQW4KcMLxy2EG/e8CatfxWYGCsX22JMcqdrn8VA9dsYoV6F84Z4ocNyTeoIoSMgLWi1WvznP/8BAPz3v/81JbAAMHfuXFx77bXIz89HQUGBUCGKV2Q74Lq7hY7CKRqOxUZdOrI0C6CGUuhwbBrUKQbbHxtBCazE1al1QofgsoXydegoqxQ6DMcCqK4EJbHEaziNBiXzn3JpKrHQhE5gZS1+BMPkYRYJaFJEEtaOX4tpPaZZJbDmaP2r8MRYudgZJYjHjZpl2KhLh1YK62llCqC/eEeAgtWePXtQU1ODrl27ol+/flavT5kyBQCwY8cOf4cmDTctATqJ++GMnmNwq/plPKObJdoEFgDSrpb+CBORXl/feNRgCpvf+o5iECB1JSiJJV7BaTQonj1HElOJjX5NheAjsAYYTCOtYfIwvDn2TasE1Dgqay+BNTKuf6UEVjgtKxcP6dxWEj3ijOtph6nfwDFDKgARt+sJj+efIgdoywCp+vVXvk1M//79bb5u3G7cz1nLli3Dww8/jCeeeALvvvsuKitFPsrhLkUoMH0zEJkodCR2sQyHsay4R9KplU7gkMLMJnMZbB6UjL7V/UQhQOpKBH0SS5UUvaNs8WJJJbAA8OodrOBTiFmGxUvXv4RpPaZh6+1bMaDdAEHjId5hrFz86UPDcOdg6XygYsDhaoZf1yvadbK1pQHdMkCqzp8/DwBITk62+bpxu3E/Zz311FN455138Prrr+Ohhx5Camoq1qxZ49I5evfubfPXX3/95dJ5fE4RCgy6T+goHBoqOyl0CA5RK53AkTEoRVKzmoaI/GfDQoDUlZDWWL2XUSVF72lzy62o2fQZoNeDCQkB1yT+D5aPbzcIPhKr5/T4/vz3VIQpgC2c0BtnKuslUaRCUk+SjS0Dqk7zI1iKUKEjCmp1dfyT/bAw2+sQw8PDLfZrzW233YYxY8ZgwIABiI+Px5kzZ7B27VqsWrUKs2bNQmxsLCZOnOiV2EXlqpv4Po8iFcH4vz1HZIgctU2tr4+kVjqBRUwFE50hxM+G2wKkrkRQJ7FUSdE7NMUlKFu0CNDzH365piZAJgMMBmEDa8WgUxzmbhM2kR2dPBoLBi0Q5NrEP4xrZdOW5aHsirgf7kjqSbJRgLUMkCru7/nnjJ0hfM7F+emvv/66xde9e/fGa6+9hh49euChhx7CggULnE5iT5w4YXN77969bW4X1J/fCB2BQ3Wcfx8WTeyXhJwJvfDKt39gc4HtlisKlsGUASlYOKEXtdIJMO4+BFawDLolRODkhVofRWbN3z8bbguguhJBO52YKil6h6a4BOczM6E5fdqyKrHIE1gjYyLLCtSLjINYFx4SbwpRsJg+tKPQYbRKUk+SzR3dQGtkBRYZGQkAqK+vt/l6Q0MDAFjca90xa9YsJCQk4M8//8TZs2c9OpcoFf4sdAQO7Tf09Nu1okMVWDntOkSFKS1qDYzsHod+HaMxsnsc5o/rgb1P34DFk/tQAhuAnCmYKGOA9m1C0DclyuL/xLr7Bvt1WcwBP/5seKTXbQHRXgcI4pFYZyopHjt2DDt27MCAAbRO0Z7qNauhLS0FAJtVidnYWBgMBnCXLvk7NKcJOSKbX5xPPV2DRMagFKz66ZSom7erOYneEowtA0bNEzqSoNWxI/+Qxl49CeN2437ukslk6Nq1KyoqKnDhwgV07tzZo/OJjogLrmg4Fpv0Y/x2vdomLSpr1aY1rsZaA4+O6ea3GIjwjAUT5954FTYdLsL+M9WoU+sQoZJjaJdYZAy0vw56yoAkfHa4xC9xbtKn4Qn5FvEvyfltK6AIA25+FVCECB2NRyT6icVzvqyk+Ndff0GlUqF3796YNGkS4uMl1oPRBe2zs6Err7Bb1ElfXe3niGyraAMkXGn+ulEB/JkE9C3kvx50isPMHwxYM973T3JjQ2LRM7Yn9pTsoZ6uQUQK63t0Ur4lFO6hJFZAffv2BQAcOXLE5uvG7ddee63H17r090NRT0d1RUmEBVc4ji/0tlk/GlXwX30PPQdsOlxESSsB4N5DjJdu74PCygYcOuf7gZRKRGOzfhTulu80/cyIEwcc/RC4eFby9SSCdjqxmCspAtKppsgolUheuQIR6elCh2JBbZaLVrYBXrpLhkPd+XeUBiXwcoYMr2Swpm0VUcD2of75cahuqgbLsJhy1RTq6RpkFk7oLeq2AQpIr7m8iYhHsILB8OHDERUVhb/++gtHjx61en3z5s0AgFtvvdWj65w4cQJ//PEHwsLCcPXVV3t0LlFKHS50BFYYBjhviEeOzv/r6PafEceDcCJNIQoWH84agrsGd4TcDx/xcnRZ2G/oKeIE1oyxnoSEBW0S64tKilu3bsW5c+fQ0NCA3377DXPnzoVarcasWbPw+eefeyVuMTImsuFpaUKHYqLS86OvP/YFFt3DorytDMsnyfBdPwbz72fxR0d+6rBxW87dLCqj/feus6t4F1iGpQQ2yDizvkdISkbCSawIR7CCiVKpxGOPPQYAeOyxxyzWxi5fvhzHjh3DiBEjMGjQINP2N954A1dffTWys7MtzvXdd9/ZrEdx7NgxTJ06FRzHYdasWVAqlT762wioXybAiO+j2TkuAWr4/9+7Ti3h9yQiCsbpyPuyx+L/0rr6tHe7GkpkaRZgoy4dGk4Ca7QlXk9CwnPHPCPmSoqAxKopgk9kU15fhaLHn0B9Xp7Q4QDgpw9HNTC4yNcbgZ5lrKYL29rmL3d0v0OQ6xJhma/veTf/L7y3WzzFaSRTXdGWAGkZIGXPPfccfvzxR+zduxfdu3fHyJEjce7cORw4cACxsbF4//33LfavqqrCH3/8gQsXLlhs37dvH3JyctCpUyd07doV8fHxOHv2LI4cOQKdTofRo0dj8eLF/vyr+U9kO+CaKcDxTUJHYiGcUQty3QhV0H5MJR6orFXj00PnceDsRYv1s/cN74yaBo1Pl/WoocQzullYrpuKDHYnhspOIoJpRDemBG3EVjxR4vUkxPe4z0+okqL3MUolkl4R9oPF4W78LyOhqw87MvPbmdDqtUKHQQQSH6nCs7f0wtSB4hmNLzB0FzoE9wRQywApCwkJwc6dO/H8888jLCwMn3/+OQoLC5GVlYWjR4+iWzfn1rKNGzcO9913H9q0aYNff/0VW7ZswenTpzFixAi89957+Omnn+zOopKcugogfxmwfiKweiz/e3RHgLVdqEYoQj3gGtolVpDrEmlq0uqRvfUYrn/lJ7z6/Z/YfaoKR8/XYPepKiz77g9c/8pP0Bs4DOoU4/NYqhCFN/UTkanNxmTNi/jFINK13YV7hI7AbUH7iIsqKXqfob4ef906QbDrNykZvDaZfy4zd5sBg07xias/iza5okHXgLm75mL56OVQsAqhwyECeen2Psg9WYnqeo3QoaATUyZ0CO7pd0/AtAyQutDQULz44ot48cUXW9130aJFWLRokdX2YcOGYdiwYT6ITkS0jcA3C4BfNvKjIebO7BQmJgf82VrHSMEyyBiY4vfrEmlq0uqRtfagw56yWj2HTYeLMSg1BlMHJuPzoyV+6xhwwNATo9jjfrmWSyRcTyJoR2KpkqLrNMUluJCTA05j/WHbUF+P0+PG22yz4y8Rfa6DQqYwrXUVomiTuRhV60/68orysOTQEt8HQ0TrSpMWlxuFH5GPRw1uZQ8IHYbrOo0AxtPPEJEQbSPw0RTgyDrrBFaE/N1ax2jKAPutUwhpKWfHCYcJrLlDhZcgl8lMvYf9UXBxkz4Nek58tTCkXE8iaJNYqqToGk1xCc5nZqLm409QPHuORSLLaTT467bbBU1gAUBXcBT3fMev2xGyaBMAXN/helwTd43FtpFJI9EhvAMAQPX3VDFqsUM2HSqCziD8dPcMNk/8/e3MyRTAgJnA9C2S73VHgsw3C/jKoCJnLA3i79Y6ADCkc1ssnNDLr9ck0lVR24TNBbZnVtqzuYBfF/vomG4Y2T3OF2FJg4TrSQRtEkuVFF1TvWY1tKWlAIC63FxTIstpNCiePQe6Ev80k7blSBf+95YjrsaiTf5OYAHg94u/Y3fJbtPXaSlpWDVmFb6a9BWm9ZiGLRO2YFqPadRihzj95NjXhshOCh2Cc0JigPTngbm/AxNWUQJLpKW2nJ9CLAEMw08j9mdrHbkMuGtwR6y7bzBCFOJaAkTEa9OhIpenBfNTi/lE1h/34Qw2Dywj/ANrCxKvJxG0a2IBqqToivbZ2dCVV6AuNxdAcyLLxsWattkji4mB4ZLvGk0bZMD3fYEvrhcmYbWlRl1j+nNaSprFutfnhj5n8TsJbmJpIREhtqqJ9rByyVZSJARH10tiCrGeY/CpfgxydJl+aa0TqmDx8OguuHtIJ5pCTFzmbhK6/0w1Hh3TDTUNvq9JIcoHxRKvJxG0I7EAVVJ0hbEXbER6umlbXW4utEXFkLdv38rBDPB3NWhfGHgaiDFrpSMm0cpoLBmxhAo3EbvE0kJCMu116qsk3deOBCHzCsQ/v97q7kI7b4jHSPUqPKOb5bfesDqDgRJY4jZ3HwbXqXWoadDg9wtXvByRNdE9KA6AehIM52pDVCIoY59Ye31kfc04fbi10VchHOrOr4PVs+IYjTUa0mEI3rrhLUpkiU1v5J7Cq9//KXQYeJT9HPMV4upNadeIOcDYRX6/rNDvv8S7fP79dFSBWIQ4DjjNJWKyZhFq4f9iL/PH9cCjY0TahoSI2ow1B7D7lOt1WUZ2j0NpTSP+qrTdbtOb1isWi6M6sUwO9JvOJ7ACL8fx9D04qEdiietsjcha7iBcAinWnrAHLhygCsTEroxBKVCI4MHLJn0aNJxE1qDtWQnseALQNgkdCSG2SawCMcDfvrvLSvGecgVU8H/Lr/1nqv1+TRIY3K0u3CUu3C8JLMC32BGFdn2A8a8InsB6AyWxxGWMUomkZUttvtZ5yxYwfp46fSm8+c/GnrBiopKpML3XdKHDICKVEBmCKQOShQ4DlYjGZv0oAM1VScWLAwo+AD66g08WCBEbiVQgbonjgKGyk1goX+/3a4ulPgCRHnceBitYBicv1PooImuieVB84Sjw7dNCR+EVlMQSl3EaDUrmP2XztcrXX0enDz8EQvz3hCemvjmRFaonrCNqgxqvHX4NWr00nsYT/1s4obdf+tS1JkeXhf2Gnk5NqBBFontuT8DcjEkAkVAF4paMP/tT2F2Iw2W/Xlss9QGI9LjzMHjKgBT8WeG/JFZUD4qPbgiI2hLi+rRPRK+1NbF1eXkonDoVaGry+dTiijbNf46pB87HQZCesPaoZM0FKvKK8jB311xKZIlNIQoW6+4bjLsGdxQ0DjWUyNIswEZdut0nxhpOhnIuWsiVA5aOfhQQN2MSQCRSgdgRJaNHBrvTr9cc2iXWr9cjgcWVh8HGPsQanX9n7rnyoNinDFrgyN+zLcwLz60ey/+e/6ok7quUxBKn2UpgI9LSED5qlOWOhr/fFHz4qKk6AnjpLhkOdeffCSqigCVTxZHAjkwaiSlXTcHm2zcjLSXNtD2vKI/WxhK7QhQsFk/uI/j6WDWUeEY3C9er38BSbQby9X1wxNAN+fo+WKrNwPXq/2KUeiV+1XcRNE4Tgw7YOI3WxxLxKPxZ6Ai8YqgfW4IoWAYZA1P8dj0SeMwfBtu7jypYxqIPsVLu3zTImQfFfnM2H9j+OLC8F5D7L+DMTqD4EP977kv8dpHXnqDqxBIjRHVMTXEJqt59B/qKStTl5Zm2y2Jj0f3778AoFCh6/AnUm73mSzoAcx6SobytDKyeXwO7fajM5wmsglEgUhWJi02O+5FN7DYRLw1/CQCg1Wsxd9dc5BXlITE8EWvHr0VSRJJP4yTSVVHbhCH//glSeFOORw32qx6BCGpS8TqNAKZvBhS+axVE1YkDi8++n6vH8h8GJe6IoRsma170y7XuGtwRiyf38cu1SOCrrFVj0+Ei7D9TjTq1DhEqOYZ2iUXGwBSLNk7TV+/HntPCFBSLw2V8plyEzrJyQa4PRgZwToxE+/DeStWJiU9piktwPjMTlzd9ZpHAAoChuhrFT84DACS/9ipkbf2zpk8OICOf/8HTswzWjPfPCCzDMK0msACwq2gXGjQNAAAFq8Dy0csxrcc0SmBJqzYdKpJEAgvw63squBihw2h2bg+wso+kpkKRAKX0f3saX/BX7+iESBWeHt/DL9ciwSE+UoVHx3TDh/cPwbZHhuPD+4fg0THdrPoQP3OLcBWDqxCFS4gU7PpOJbCAqGtPUBJLHKpesxra0lK7r9fn5eH8Y/9EyZPzYLjYeoLnLb2K4PdWOhqDcy0HLqkv4eZtN1skss8NfY4SWNKqA2f99zPkijhcxqPs51ivWIytyhewXrEYj7Cfo0rIG7At9ZWSmgpFAlTqcKEj8Ir9fmoJUlGrxoMfFqBJq/fL9Qgx6tUhCl3jw1vf0Uf89aDIYyItBEVJLHGofXa2VU9YNtay+EJDfr7VKK2vxdYBT27V20xkWT2H+7/VI77Gv0muQqYw/bm6qRqTdkyiQk7EJWJrMaGCBi/L38Ne1WOYr9iEUexx9Jedxij2OJ5SbEJv5rzQIdpn0FIbHiKMfpmA2f1AijQci036MX673oGzF5Gz43e/XY8QAGjS6tE3JUqw64umd2xrzAtBiQglscQhRqlE8soVFomsvrraKpEVwsDTwNxtBotEltVzmLvNgHFHOSzc6PtENjak+d9Ba9BaJLKldaVUkZi4REwtJlTQYJ1yCe6W74SSsT1CIhPLelhHRDwVigSoyHbAdXcLHYVbjFVSNutHowr+/XC/uaAIlbVqv16TBK8mrR5Zaw9i6xH7sw19TTS9Y51RKL6+15TEklbZS2TFYNApvrAT0JzADjrF34UTLgO37fdd+fTRyaPx9aSvLSoQaw1ahLDNPXKpIjFxhRh6xRotlK/DUNlJ4fvZeYNIp0KRAHbTEr4gisQwDD+NOEeX6fdra/UcNh0u8vt1SXDK2XFC8CU8Fr1jBY3ECZo6oSOwQkkscYqtRFYMKtsA24fKrBJYADjUncEHN/rmv/jo5NFYkbYCYcowLB+93CKRbdI3ITEiEQCQGJ6Ie6+51ycxkMCTMShF8BY7AF95eAqbD8Dn7Z79Q6RToUgAU4TyFT0HzJTM1GIDB2zUpSNLswBqKAWJYf8ZcTwgJ4GtorYJmwuKhQ4DAN87tsDQHaK/1YqwYB0lscRpjFKJ+DlzhA7DQmlb4EoYbCawyyfJoPdBQtA+vD2WjlwKBct/MDFWIDYmsonhiXjnxneoIjFxWUJkCKYMSHb7eBnjnSm+GWye3SnEkiXCqVAkwClCgQmrgLm/A+nPA13GAMmD+N9HPw106Cd0hBbe0t2GZ3SzBEtgAfHVBSCBadOhImj9XBzUHjWUyNdLoL1UqvhmllASS1qlKS7BhZwcGOrrUfTww4LF8VsKUNQWuGhWSK5vIfDha3q/JbAAUFZfhvm751usdW3ZSie1TSpVJCZuWTiht9vTijmOH03x1BDZSc9PIjYinApFgkREAjBqHpD5OTDrR/738t+BC0eFjsxEw7F4X3+T0GGIqi4ACVxCTyNuaYDslNAhOCZTAP39v8SgNZTEEoeMfWJrPv4Ep8eNh66kRLBYkqqBlIuAngV+TbW9j68TWKP84nzMzpttlchS4ko8FaJgse6+wbhrcEfIXRxW9dZz5QgmAKv5inAqFAlCDReBVf2A/20XOhIAwhZysmVoF+GLRpLAJ7YRf9Hfc/vdwz+MExlKYolD5n1i9VVVgsYSw7ddRfwVoDLK9of712/zXQIrYyx/XGwlsoR4Q4iCxeLJfbAv+wbMHtsd7duE2F0v44sKwZLpXecKEU6FIkGm4SKwqi9w6YzQkZgIWcipJQXLIGNgitBhkCAgthF/Ud9zO40AxouzQCklscShdvPmgY2LEzoMC5fCgZg622NOj2832Owd6w0GzoAO4R0stuUX5+Plgy/75HqExEeqMHvsVdj/zA04+OxYzB/XAyO7x6Ffx2iM7B6H/0vr6pMkVjK965wl0qlQJMis+QegviJ0FCYajhW8kJO5KQNSEB+pEjoMEgTE1AkAEPE9NzIRmL4FUIS0vq8AxPUogohO+auvCj4C21JMPTDgL9uvDTrFVyn21ZTiYYnDUN1YjV3Fu0zbmnRNXr8OIS3FR6rw6JhueHRMN9O2N3JPQeeDLlKb9Gl4Qr4lcIo7iXQqFAkiZb8B1f5f92bggM/1I1DItcNA2Z+IYBpRx4Viv6EnNunHiGIKMcAnFQsn9BI6DBIkMgalYNVPp0RT3Em099xB94s2gQVoJJbYYSzm1DYzE4pEvl2M2EZkAX4N7IwnWRzq3pywGhNZb4/IhsnD8OC1D2JF2gqMTh4NAEgIS8Bj/R7z6nUIcZavilNY9K4Txz3efSKeCkWCyPfPCnbpJijxjn4CMrXZmKx5EZnabLypnyiKBFbBMrhrcEesu28wQhSs0OGQIOFpJwBvq0Q0tumHCx2GJQnMYKIkllgxL+ZUsexVpKxZjei77kS3774VVZ9YYxEntZL/3ZeJbIfwDvh0wqdIikiCglVgRdoKTOsxDetvWk+FnIhgfFmcIkeXhf2GntLuEztgpqinQpEgUvqLIJeVMcDd8lysUy6BChpBYjAXHaYwLYeYP64H9j59AxZP7kMJLPE7TzoB+IbIbrYSmMFESSyxYl7MqS43FxXLXkX77GzIwsORtGypIDFVRlp+XREFiynDetZ2IjvzB8/nWnYI74CvJn2F1Dappm1UiZgIrUmrx4Ua31U0VEOJLM0CbNSlQ8PZ/oApkplYtkV24Ht0UgJLxEBdK9ilOQ4YKjuJhfL1gsVg9MDILtj2yHB8eP8QPDqmG62BJYIx7wSgsLP8TC4DusZH+Dy9jEcNJrEi6mUukRlMlMQSK+2zsxE2bJjp67rcXBTPngNDfT1K5j8lSEwyDlD/vYJbLQdenspg5g8GxNc0f4pumchWRAHbh3r+X3xo+6FQsAqPz0OItzRp9chaexBlV9Q+vY4aSjyjm4Xr1W9gqTYD+fo+OGLohnx9HyzVZmC17hafXt8jbbsIHQEhvNpygBNurZtxNsUUdhficFmwOGQMqPowERVjJ4C9T99gVThx/rge2Jc9Fj89ORo/zh0FX3ZuzGDzxLEeViaX1AwmKuxErGgrKqE5d85iW11uLk6PGy9YkafYOuB4JyC6DnhtEoN7dvEjrf3O6JFzN4vKaMsR2Zk/GLB9qMy03RPFdcXQ6rWUyBLRyNlxwq/N2qsQhTf1E/GmfqLF9vWKxX6LwWVXSoHVY/n+sKkj+LU9Ip8aRQLUUeFHQAFAyeiRwe60+jkmJNjZKpxobvWesz6deTREdtJ3J3fF9f8Exi4SOgqn0UgssVK9ZjV0f08nNufLBLbWier+fc4B5THA9DwOg07x7yYJl4Hb9ltOGdazDNaMZ72SwALAofJD+PeBf3vlXIR4qqK2CZsLioUOA4DIG7RfOgsUHwLO7ARyXwKW9wJ2PAFoqZo48bPCn4WOwGSogB+WDRyw6XCRYNcnxB0VtU34zMf/b0VzLxVo7b67KIklVtpnZ/u9gFOkk/UmBp7mfxkd6s7ggxt9/994x5kdOH3pdOs7EuJjmw4ViaYtgKgbtLdk0AIFHwAf3QFoRfKBgQQHTZ3QEZgI/WF5/5lqQa9PiCuatHrM+uCwT1rZmRPNvbT8N0k96KUkllhhlEokr1whqkrELQs7Ac3ViX3RD7YljV6DO3bcgXOXz7W+MyE+5M9pxK0RbYN2R87tAb59WugoSDBRRggdgYnQH5Z9WVGdEG8qutiAsct34ViJ79eRi+ZeWl8JvNYDeC8dWD8RyH8VqKsQOiq7KIklNhkT2ZB+1wkdCgAgvkVhx19T4bcE1sjAGfBE3hN+ux4htojpQ+AmfZrdysWidnSDqG/MJMCkiqf/436BPyxHqKgUCxG3Jq0e2VuPYdSynSi+5J+ZC6K6lzbVACUFkliKQ0kscUhbLr4Per+mAq9ksH5NYAFAxaqwcsxKv16TkJbE9CGwEtH4Sj9U6DBcZ9ACR8RRbIcEgX6ZgEz4woAajsUm/RhBYxjaJVbQ6xPiiLHy/8cHi8D5cdVOJaKxWT/Kfxd0hYiX4lASS2ziNBoUz54DvY0CT/5yxE6HjFfv8H8CCwA3dLzBolcsIUIQV3N2oJBrJ3QI7ikUUU8+Etgi2wHX3S10FNisH40qRAl2fQXLUIsdImr+rvxvcW1dFmo5Ebe1EeFSHEpiiRVjAluXmytYDEc7AwY7/zsf324A6+fCNu3D2uPx/o/79ZqE2JIxKMVuY3YhDJCdEjoE94io2A4JAjctATqNEOzyBg54Q3e7YNcHgFuvTUR8pErQGAixR+jK/2oo8auhq2DXd4rIluJQEkuslC1eLGgCCwC9z1tWITY36BSHudv8l8h2ieqCD276AEkRSX65HiGOJESGYMqAZKHDMBG62qnbRFRshwQBRSgwfTMwYCYA/z+EkjHARFbYVj9J0SIeZSJBTwyV//cZegt6/VaJbCkOJbHESuz9syDv0MFqOxMWhpD+/f0Sg1Lf/OdD3RnMnC3DpfDmbf5KZONC4/Dm2DcpgSWisnBCb9FMKxa62qnbUoUbFSNBShEKjH8FUNkot+8HQvaIBYDNBSWCXp8QR8RQ+V9UBZ7sEdFSHEpiiRVFQjyUqalW27mGBjSdOOHXWNQscCWEw9zPDYipt3zNH4msjJEhITTBZ+cnxB0hChbvzBiABBFMzRNNawBXyBRA/0yhoyDB6JsFgPqKIJcWetZE+ZUmVNaqBY2BEHvEUPlfEsUSRbQUh5JYYqVs8WI07Ntn+poJNxsCVfv3BqTSAzccB64ttP36oFMcZv7guy7UFQ0VmLtrLrR6rc+uQYg7lnz7P1SI4AOhJJ4ct9TvHiCCHk4RP6stB37ZKNjlhZ41wQHYdLhI0BgIsUcslf9FXyxRREtxKIklVmLvnwVFYiIAICI9Hd1/+hFsrDjL4ldEAduHev+/cQjbvHYnryiPElkiKkIXoDAn6tYAtnQaAYxfInQUJBgdXc+vKROI0D1iAWD/mWqhQyDEJrEs0RF9sUQRLcWhJJZYUSYnoeP69Yi+604kr1wBWVgYQnqLa7H54W7AD9cxyLmbRWW094tkNOmbEBvSnLjnFeXh/376P0pkiSiIoQCFuRxdFs4b4oUOo3WJ/YHpWwAFFZghPlRXAeQvA9ZPBFaP5X/PfxX4a6dwMckU+E55o3DX/5sYpmwSYotYKv8LPe3fIZEtxRHH2DkRHWVyEjosXGhqt1Ofny90SCaHujNYPknm816x1U3VaKtqi4tqfrH/gQsH8MLeF7B45GKfXpeQ1oihAIU5NZS4W/MsdqnmgGXEk1xbCYmiBJb4jraRX/P6y0brEdczOyFEVWKTfvdAezIeaGwQLgaIZ8omIS0ZK/9/fFDYKe9CT/t3SGRLcWgkljgkhnY75vyVwBoZE1hCxESMoxnFSMCn+jQAACfWPFZEBSlIgNE2Ah9NAY6sczBlWKAfDGUkmsa+jIv1wq+hH9pFnEuTCAHEUflftMUSRbgUhx6JERNNcQmq16xG28wsXFy/Du2zs9HmlltRs+kzQK9v/QQ+drgbvJbAMmAgZ6z/+8shhw62E4TB7Qdj0dBFMBh8V0iKEGdEhcihdPERpM4A+Pp/bo4uC11kZYK38rBLRAUpSID5ZgFwTjytJ8zpE/sha/0x1KmFvY8rWAYZA1MEjYEQR0IULNbdNxg5O37H5gLby3YY+PZx1Bf66/GkfBNkws9s5jEyfgrx+CWim8lESSwBwCew5zMzoS0txeVtn4NraoKuvALyuDhRJLAA4OksxRBZCK6Pvh69wnshVmn/abBCpoC2xZP0cEU4OkV2wpnTZzwLghAvuLe3EjeluD6iUdWgx7EKNXada0KTzvu3YTWUyNIswEL5ekxh86BkRPbAR0QFKUgAEbjqcGt+bOqBA4XCzyqaMiAF8SJoC0aIIyEKFosn98HcG6/CpsNF2H+mGnVqHSJUcgztEovb+ibiP7mnsOmwb4orPiL/QjwJLACkDAEmrBI6CpsoiSUAgOo1q6EtLQUAcE1NAIC63FyEp6UhIi0NdXl5AkbHG/AX8ORWPV6bzLo8GhsiC8GMDjPQPaI7olRRULEqMIxz55AxMihZJRgh1zMRYiY+UoXIEIVLx3DgkKw1IDVGiavaKvHe0Ss+S2Sf0c3Cct1UZLA7MVJ2DP1kpxHCCDwFmpEBf+UCf37Lj8imjuCfLotofQ+RKIGrDjvCyRRYWNRf6DAwqFMMFk7oJXQYhDgtPlKFR8d0w6Njulm9xvooy4xHDaaw4qlBAwCoPi10BHZREksAAO2zs6Err7Ba/1qflwdV376ATAaIYBrtwNPuJbLXR1+P7hHd0S6yHeRt5JApZaYaG52jOqOqsQq1mlqr4yKVkUiKTIKMoeXjRFxKLjXgYoPG+QM4DuHaJoQqLwMARncKwXd/+a4KYhWi8KZ+It7UT8RW5Qvozwh8I+QMwLmfm78+sxPIe4UvVCHCaVJEQgp/bn0fgZxIuBVlhVFCh4HO8eEIUUisnzQhNviyxV0GmwclI47Zjyb1VXzFdRE+8KUklgAAGKUSMZmZqNu1y2r6sPrXXwWKincpDIgxK6g48DRw3/cGvHeT8zfEXuG9EKWKgryNHGxo83FdorsgVB4KlUKFPy7+YXVccptksDK68RLxSYoJh8YA1Dtb5IkBGFU4ACBao8W1CSqfJrHmRFtt0aAFCj4Aqk4D0zcDCpHGScRNrAXDOo3Acv39AK4IHQm2HS3B/HFX03RiInm+bHE3RJT1JDhg/5vA2EVCB2KFhpcIAH5NbMkjj4hm/euViOb/mjENfCJrLqGGA+vkm4gMMsQqY6FiVfwIrJmKhgroDDr8VfOXzWNL6kpg4IQfgSakJZmMQefYcMSEKV06jlGEIEQhQ1wY67cbwG+Gzn66kpvO7QG+fVroKIhUia5gGAP0mwFM34JLGnF8zNPqOWw6LGzrEkK8wZct7kTbI3bPSmDHE4C2SehILHj87nbx4kV8+OGHWLJkCdatW4fy8nKH+3/xxRd48cUXPb0s8bLqNathaBC2f5xRQTcGjzzEt9MximkAKto079O3EJj5g3PJJcvwI6kMw1i16avT1OHPS39CZ7A9mlWrqUVxbTElskSUZDIGKrmLb+MMY1rf7eqhrlJBg5fl72GW/EvfXsgbjm7gp0wJjO6pEpQ6XOgImiX2B544Btz+BqAIQaiIpvDuP1MtdAiEeOySK8t4XCTaWUvg+FlLH93BtxMTCY8+wmzduhVdunTBzJkz8cwzz+C+++5Damoqnn32Weh0tpOCzz//HDk5OZ5clvhA++xsRKSnCx0GACClgkNMHd9Ox5jIVkQBL91l+fX2od75BM6ZNbWUy+To0bYHIpWRpm2UyBIxE2PPWIBPYNcpl+Bu+U7xVSm2xaAFjqwXNAS6p0pUv0xA5lqhNZ8ITwAYBtjxOJD/KlBXIar3BzHFQoi7apt89/9YtD1ijUQ2a8ntLOD48eO46667cOXKFfTo0QNTpkxB//79oVar8corr2DUqFG4eFH4ku7Ekqa4BBdycsBpLJ8kMUolEubPAxMifHGThCvA0vcNiLvM4VIYh/zeDHLuZlHeVoblk2T4rh//dWW0d6vDMQyDrtFdIZfJkRyZTIkskQSDLxvWeWChfB2Gyk6CE2l8NhUK1+eT7qkSFtkOuO5uoaMA6iuAkgK+aFnuS+CW98Jd5a9BBd+NHLkiQkVlWAhxZJM+DRpOPLMnbBLJrCXAgyR26dKl0Gq1eO655/D777/j008/xaFDh5Cfn4+uXbti//79GDlyJEr/bttChGfsBVvz8Sconj3HKpG9uH69qb2O0EI1wPOfGPCPX4Gri5s/BetZBmvGez+BBfgR2YoG/gdTxshsJrJl9WVevy4hnhBVP7m/mbcJcLKTlTgIWKCH7qkSd9MSwOx+IQaMQYu72FysUy4RRSI7tIvrva0JEZvIEN89jKlENDbrRwGAeB8Ai2DWkpHbSeyuXbvQrVs3q7U4I0aMQEFBAW6++WacPHkSw4cPx+nT4u0xFEzMe8HW5eZaJbLt5s0DGyuOm4yGBRL4TiBIuAzctt/3I6AMwyA2tPnv3zKRVcgUiAuN83kchLhCjKMbomwT4AwBC/TQPVXiFKFAYj+ho7DCccBQ2UkslAv7oVMuY5AxMEXQGAjxBleLKboqR5eF/Yae4n4ALOCsJXNuJ7EVFRXo18/2G3ZkZCS2b9+Oe++9F+fOncOoUaNw/Phxt4Mk3tFy3at5IstpNCh+ch701eIovKA0+/x7qDuDD270fYVFjuNQXl9uMWXYmMjGhMQgNSoVSta3b17BJi0tDQzDoLCw0ONzffnll3jmmWcwduxYREVFgWEYjB8/3vMgReKPP/7AihUrcOedd6JLly5gGAYMw0Bde5EvWiYi4mwT4ITUEYJdmu6pAaDLKKEjsGJ8a5jC7kIcLgsWR6/ENtRehwSEIZ3b+vT8aiiRpVmAjbp08U4tFklbMbcf4cfGxqLBQTVbmUyGNWvWoG3btnjttdcwZswYfPXVV+5ejngBo1QieeUKFM+eg7rcXADNiSzbNgb1eXnCBmjDoe4Mlk+SQc/650O6ce1rcmQyZAyfOMsYGRIjEv1yfeK+6dOn4/Jl4T6k+dpbb72FVatWWW1XsDLEqBS4WC/8dEEj0bYJcESmAPpnCnZ5uqcGgH6ZQN4SfrqdyCgZPTLYnXhTP1GQ60eKcMYIIe7IGJSCVT+d8lmvWIBPZJ/RzcJy3VRksDsxVHYSEUwj6rhQyKDHCPZ3n13bKSJpK+b28FbXrl1x8ODBVvdbtmwZ/v3vf+PixYv4xz/+gaNHj7p7SeIFxkS25Yjs5c1bBIzKtoooYH064/MENlwRbrX29fSl01Dr1D69LvGuO+64A8uWLUNeXh527NghdDhe16dPHyxYsABbtmzB+fPn0alTJ9NriVGhCBfRh0TxtglwoN89QESCYJene2oAEEuBJzuGCjhDokErweUFhNiQEBmCKQOS/XKtKkThTf1EZGqzMVnzIjK12ZijfUz4go5Nl0XRM9btJDY9PR1VVVX49ttvW903Ozsbb7/9Nurr62kKlAjYSmTF5lI4vxb2+U8MiK/x3U9ruCIcHdt0tCripDVocebyGWj0ro9uVdaq8UbuKcxYcwCT3vwZM9YcwH93nkZlLSXFvrRmzRrMmzcPo0ePRkSEOJ4SetP999+PV155BZMnT0ZKiuXaMpmMQefYcLQNV7ZshSwI0bcJaKnTCGD8EkFDoHtqgLhpCf//SYSEnCEhxrX7hLhr4YTePp9WbE8lonERbQS5tknpEVH0jHU7ib3tttvAcZzTTdYffPBBfPLJJ5DL6Y1MDBilEknLlrayk3Afh2Pq+d99WdRJIVOgY5uOkDEyyBgZkiKSIJc1//80cAZUNVY5fb4mrR7ZW4/h+ld+wqvf/4ndp6pw9HwNdp+qwrLv/sD1r/yE7K3H0SSCJ9KFhYVgGAZpaWlobGzE008/jU6dOkGlUqFbt25YsmSJRf9cc7///jvuuecedOjQAUqlEklJScjMzMQff/xh93rvvvsu+vTpg5CQECQlJeGf//xnq1N/CwsL8dBDDyE1NRUqlQrx8fGYMmUKjh075tHf3V1qtRpxcXEICwuzG/uuXbvAMAzGjh3r5+j4RDY5JgzdEoSvkCqJNgEAP4V4wExg+hZAIWx7MbqnBghFKDB9M///Sgy9Y80IOUOCKhOTQBKiYLHuvsGIjRCmTsr/DCIokiaCnrFuJ7H9+/eHVqvF7t27nT5mypQpKC4uxpkzZ9y9LPESTqNByfynWtlJ6PkKvi3qpJI3F5kwcAaU1JVAZ2huYh2pjET78PZOnatJq0fW2oP4+GCR3XUSWj2Hjw+eR9bag6JIZAFAo9HgH//4B95991307NkTY8aMQUlJCZ5++mk8//zzVvv/9NNPGDhwIDZu3IjExETccccdSEhIwIcffoiBAwfafD+YN28eHnroIZw6dQrp6ekYNmwYNmzYgDFjxkCttj06vWfPHvTt2xfvvvsuIiIicNttt6F79+7YunUrhg4dip07d3r936I1KpUKWVlZaGxsxIYNG2zus3r1agDAAw884M/QLIQqWYQqhE0gzdsEiErH4UDyIKDLGCD9eWDu78CEVYInsADdUwOKIpT/fzX3d2D000BkB0AEcyT2CzRDQsFSZWISeEIULHp1EGZE9Dd0FuS6VgTuGetRdsCyLFjWtQ9L8fHxFmu5iP9xGo1FcSexuhQOrLrNd2ti6zR1KK4tht6gR3FtMWo1tabXIpWRFsWdWpOz4wQOnL3o1L4Hzl5Ezg6BF+X/bd++fWAYBn/++Se+/fZbfPvtt9i9ezfkcjlWrFiBurrmCnT19fW455570NjYiLfeegsFBQX4+OOPcfToUSxfvhx1dXW4++67LRLTvXv34rXXXkPbtm1RUFCAr7/+Gps3b8apU6eg1+uxf/9+q5iuXLmCqVOnorGxEZ999hl+++03fPbZZ9i7dy++//576PV6zJgxAxqN/wsZPfTQQwCA9957z+q1mpoabN68GbGxsZg4caJpu3HU25VfqampHsXZMTbMo+O9IUeXhRouXOgwmiX2B+77Gpj1I5D5OTBqnqBrYG2he2qAUUXyrShqLwAQ9qGwgQM26ccIcu0pA1KoMjEJSEJMKY7HRTzIfu3369okcM9YmocUZGwlsBHp6UhathTnH3kUjQcOCBidpZh64IntHJZP4nyWyNZqavG/i/+z2OZqAltR24TNBcUuXXdzQRHm3niV4Dd2mUyG1atXIy6uuf/twIEDcdNNN2HHjh04fPgw0tLSAACbNm1CeXk5Ro4ciYcfftjiPHPmzMGGDRtQUFCAbdu24c477wQAvP322wCAJ598Er179zbtHxsbi2XLlmHcuHFWMa1duxZlZWXIzs7GlClTLF4bO3YsHnnkEaxcuRJffvklJk+e7JV/B2ddddVVGDNmDHbu3ImCggIMGDDA9NpHH32EpqYmPPLII1Cpmr+vERERyMrKcuk65t8Pd6jkLGLClLjUIFzFYjWUeF83DnMUWwWLoRkDTF0ndBAk2HyzgJ9yJwIX0QZViPL7dYd0bouFE3r5/bqE+EPGoBSs/PFP6Hyz6s2mnaELIOP8eMHWFO7hHwoLgJLYIGIvgU1euQKMUglVp06iSmIBYNApDnO3GfzWZodhGLQLb2dKYA2cAWX1ZYgLjbPbI3bTIftTiO3R6jlsOlyER8d08zhmT6SmpuKqq66y2m7cduHCBdM24zTHe+65x+a5pk+fjoKCAuzevduUxO7Zw3+Ay8jIsNr/H//4B9q2bYuLFy1HsH/44QcAsBjNNDdixAisXLkShw4d8nsSCwAPP/wwdu7ciffee88iiTWOzs6aNcti/7i4OHzwwQf+DBEAkBQdiiuNWugFXBawUT8Wj8q/gJIRePp8v+lATEdhYyDBpbYc+GWj0FGY+HsNnYJlMGVAChZO6IUQgZc3EOIrbUIUaBuuQoWfCncOw28I5+r9ci2nCdgz1jeLDYkolS1ebDeBBYDYBx+EPFEc/VDVZo9XBp3iMPMH/zx14jgO1Y3VMHAGlNaV4vyV87jUdAmFlwvtVip2dhpxS/vPVHsSqlckJ9suE2+s7ms+Nbi0tBQA7E51NW437mf8M8MwVtV0jTp2tE4sCgsLAQBDhgyxOdXWODpbVeV80S1vmjRpEtq1a4eNGzeivp6/mRw8eBDHjh3DiBEj0LOnOCrzymQMVAph3+LN18YKlksrwoGbXxXo4iRoHV0vqn6xew29W9/JQxEqFtd3jcX8cT2w9+kbsHhyH0pgSUDL2XHCbwksACxWrhbB6voWBOwZSyOxQST2/lmo35UPbWmpVQILAMrkJHRavx7V774LbUUF6vPyBImzIhJ4eRqDe3bxCWxFFLB9qH8+jMtlciSEJVitkdUatKhqrEJihHWSX6fWWW1zhrvHeRPjRgXq1o5x55zm9Hp+1G7q1KkIC7O/tnPIkCEeXcddCoUC9957L1555RVs2rQJ9957r8OCTlVVVZg3z7WpNnFxcXj1Vc8TL5mAFcaNcnRZ6CIrE65HpbYe2PE4MOF1URRw+n/23jwuynr9/3/eswECuQAugIprmWUpmpQbmtlqpSGVmlueY7+Wk1q5nE8dpNPJsETzdOp8zb3UVMxOtltumKKIlmvuqIiIoCD7DDP3749pRpZhmWHmvu/R+/l48NC55577fQHDvO/r/b6u10vlJiH9V7kjsGMUtR7th9VpYETPNuquq8pNxbkrRXyRel7SMcME+Tc/qhEhn6WYmsTeRBjCw2izYgW5ixfRcubMSglsxXNavR2PpaiIU488SvmlS5LH2bwAxv8s8v5TGp7bbE1gLzeR5ma83FLOqbxTlVSKoXalYlf977zNNy/0z136M2fOOHz+7NmzALRq1cp+rFWrVqSnp3P+/Hk6dqxeOn3u3Llqx8LDwzl27Bhvvvkm3bp1c0fobuevf/0rCQkJfPrpp4wYMYIvvviCxo0bM2LEiGrnFhYWsny5c/2Ybdu2dUsSG+Cjk32xpAwDY43TWat/m7u0MqnoHlgD+Res1id6+WxGVG4iSq7KHQGiaHXKSzIP8Gg/bLfwJmoCq3JTUWoyM/LT3ZJXGGlQUC8sWG3EeoyRb3jZRlaRBUN4GK3i4hwmsDZs9jtSJrCmKnPfXenwxnoLyx6QLoG1UTWBDTAE1Cr05Ko6nbf55vXr1w+gRnsZ23HbeWDtXwVYt25dtfM3bdpUrR8WsHusfvXVVw2K15O0a9eOIUOGsGvXLt566y0KCgoYPXo0fn7VE6SIiAhEUXTqy1ZS3VCa+svjYVeVMgxMNL2OSU7vWAV42qncRJTW7oMtBYJgtdWJL/fsTea+c3mKUdxXUZGC+I2HybhaIvm4FqWlbd1Hyaryr7CfhorciEYj5ya9ILn9zpTxlftgwZrITt1gQeukaJI7CTAE0Dqwda1KxbG9WqN3UnTKG33zYmNjadGiBcnJySxcuLDScwsWLCA1NZXw8HCGDRtmP26zpElMTOTo0evlpFeuXGHaNMc+xZMmTSIkJIR3332XpUuXIlZZ6iwqKmLFihVkZDinCO2IWbNmIQgC48aNc/q1NoXm+fPnA9UFnZSAXqtBr5XmYz6YfF7SfsUK/Wy+NPyDFfrZvKj9imCsN/OXacKXZvnKjgDZPe1UVKTCKGpZVT6IscbplOH5xayktPNclrA3UEVFLlxxpHAXF0QFbX607QsPJcgagnfVM6p4FFsCW7xrl+RjL1jkeEXFJuq0+CF5dnD0Gn2dVjvNA32JiQxn9Z7690Z4o2+ev78/K1euZOjQoUyaNImFCxfSuXNn/vjjD/bv34+/vz+rVq2qZC/Tt29fJk+ezPz58+nevTuDBw/Gz8+PzZs306ZNG6Kioqp5xTZt2pQNGzbw+OOPM2HCBOLj47njjjvw8fHh3LlzHD16lKKiIvbv319JmOqf//wn3377LWD1mgVISUkhKirKfs6GDRsqlTtbLNbSHL1e7/TPY+jQoYSFhXHhwgV69erF3Xff7fQ1nGHfvn28+OKL9sc25ehHH33UHv/EiROrJdPN/A1culbqsbh8MBKnW06Mdns1FeL+2oNM1q0nyTyA2eXP0E6TWcNVJMLmaSeTHYDKTUJhNpik2aUxiRoOWyIowA9/oYxC0Y8USxfWmgdKaqljMovE/HcnsT1bE9vT++Y3FZX64oojhbuYaZzIKp93kV3uIjAURq+XXWfCrUnskSNHmDNnDtu3b+fixYsYjY7VXAVBoLxcflEblcpkzZ4tSwILlRPYq/5wuiVEnkJSUaeq6DV6gv3q59cZN7Qrpy8X1Uup2Jt98+6//35SU1P517/+xebNmzlw4ADBwcGMHj2aN998k1tvvbXaaxITE7n11lv56KOP2LRpE0FBQcTGxjJ79uwabXT69OnDwYMHSUxM5Ntvv2Xz5s1otVpCQ0N57LHHGD58OLffXvlneOrUKXZXsYjKz8+vdKyi2jLA77//DsBzzz3n9M9Cq9XSv39/Vq9e7VDQyd1cu3at2vcH1uTWxkMPPVTt+Wb+BrKvlSHi/knXByPLDQm1ijYZBDMjdZsZrE2juSB/iSW7PrL+22OMrGVQ9UGdU70MU4nVG/a3VZIpEy8sf4z3zc9IMlZdnM0t5v0fjzH/5+OqvY7KDYurjhTuYBd3cA0/GlNi73mXhcZhsiewAIJYtVbPRXbt2sXgwYMpKbGuPgYFBdltOhxRkziMSu107WqVyT98+LDbr23MuMDZMWMoz6xht0QQPO6TYQEmvgIlflrGbbK4RdRJL+j5e/u/075xewwtDAia+l3PX+9Pm1va1LkTa6PUZCZ+4xGS0hyv0qm+ecrCYrEQFBREz5497d60zlBcXExoaChms5nMzEwCAwM9EKV7OH6pgFKTdZdUFC2Yr2RyIruQt7bkYmyATsS7uk8ZqdtS52Qq62RbExq9tZ/noYR6T8ae/Pytijqneh63/j5NJfB5jLX3WkKSzV15zvR/ko5ZX3q3a8byCfeo853KDcWwj39l/7k82cYP4Qq7fP6GTpBR5Kn9QBjzVYMv09DPYLftxM6cOZOSkhImT57Mm2++SbNmrondqMiHzWLn8rx5FKWmYs6u0Dum0YDF838wGmDOMnjl/8NhCbHWLLotua2LIlMRGQUZtYo6VcRXr2X28DuZ+kBn1u49T8rpXArLygnw0RHVPkgtsVIY+/fvJy8vj7ffftul1//nP/8hPz+fl156SdEJLIDFA4tPIeQRo90O1J2gKi6BBetOWdoyyDmpSNVidU71Mr6fLnkCC3C35hQ+GCXpe3WW3WeuEL/xCLOH3yl3KCoqbkNuZ4nLNOPesgX87DONWyiWZ36V0VanIm77Tezdu5e7776bxMREd11SRQZMWVkUbN6MWFKln0eCBNZGcAEO+2C1ZpGpGyz0OiHS/bSZ+JFajyeyBcYCpxJZgJBAH14a2JGXBla3lFFRDpGRkdVEo+oiNzeX6dOnk5WVxffff09gYCAzZ870UITuw2xxfxIbq91arQfWK7GpFg/9UO5IKqHOqV5EwSVrCbEMBAqlxOlW8Pdy5QnLgVXwaeoDndUFXJUbht7tmpF8IkfWGC7TjLvKFjFb+/94Vr9N2sFlttWpiNuaDQ0Gg0MfSBXvwZhxgfOT/lo9gZUYM/Btr8rJacUEFqB5PjyeIk1ibUtkLaLC/LlUJKegoIDFixezadMmevTowTfffENYWJjcYclC71r6YL0OBaoWq3OqF7F/hWQ9sI6I0W6zq4ArDZNZZO3e+oseegJRFLFYLOqXF365qePRrbjiSOEpEs1PY5Tauk5mW52KuG0ntm/fvhw8eNBdl1ORgdzFixCLiuUOAy3w3BaRxGEiZq1QLYEFSO0ksOwB9ws+CYLg8EOzwFhAVlEWoQGhbh9TxXuweb56G1qN4Pbd2ABB3sUut6JA1WJ1TvUi0n+VdXiDYCZWu4WPzU/KGkdNpJzOlbwyyWw2k5ubS0FBQY2CaCregcFgIDAwkKCgILRa+furXXGk8BSXaUKSuT8jdVukGVABtjoVcVsW8O6773L+/Hnmzp3rrkuqSEzLmTPRKWRXqdcJa+LqY3ScwCYO02B2w0qYVmP9QNRr9DT2aUwjXSOH5zmjVKyiojQa+zlvIVQXhaKyekgbTLr0/Yy1oc6pXoSxUO4IalUIl5vCMmmVs81mM+fOnSM3N1dNYG8AjEYjubm5nDt3DrNZGS0scUO70rudMnQK4svHcrbRHZ4dRKOHyHGKsNWpiNt2Yvft28f48eOZNm0aGzdu5IEHHiA8PByhho7jMWOUUU+tch3BYKDD1//j5OAHMF+9Knc49Doh8tncyh9Y7kpgNYKGxj6NadGoBZeKLxHkF8SloksUmYoqnafX6Gmkb0TzRs0xaJUnnKGiUh+CA3y4XFBW94lOsNvShf7aG2inUAGJSEXUOdWLMNSsGi0VSq6MkFoIJzc3l9LSUrRaLS1atMDf3x+NRh6rPpWGYbFYKCoq4tKlS5SWlpKbm0vz5vKXsvrqtSyfcE+tjhRScXe7lrR47kdYPAByT3pmkEnboYXyrCHd9skybtw4eynm9u3bSU5OdnieKIoIgqBOuAql/Goeoo8yBRjcuQMriiItGrVAq9HS0r8lGQUZFBgL7M8HGALsu69q8qri7ei1Gpo2MnC12H27EmvN0byqW39jiDuBIhKRiqhzqhcR0QdOS1TOVwNKroyIah8k6XgFBda5vEWLFjRu3FjSsVXci0ajsf8OMzMzKSgoUEQSC9cdKV6M7sDIT1M4f1XahSQBeOaeNlbbRozgH+K5JPbYdzd2EvuPf/yjxhViFe8hd+FCLFlZko9rxtoLWxsLHndPAgsgInIi7wQdm3QkszCzUgIbaAh0So1YRcUbCGviR1m5haIy9ySyFXtxFOkD6ywKsQywoc6pXkT3MbA1QVZxpxRLF9nGrg29ViC2Z2vJxhNF0V5C7O/vL9m4Kp7F9rs0Go32hTul8PHWk5InsAAiEGC6gnbHXNi3BAouem6w9B2K0oyw4bYkdtasWe66lIpMGDMuUJSWJsvYWiD7Fmh+DcwCaB1UZvzta4vbdmIBzBYzx64cq3RMTWBVbmTcPe3Hl4+lvSZL0f149UJBlgE21DnViwhsAXePhH3LZRleFOErcx9Zxq6LmEhp/dErCu+pJcQ3DhV/l0pKYrMLSklKy5B8XB+MxOmWE3NkO/qjElRDKazdxob6F64CWBPYc2PGYDp1CmT64M8ItiayjhJYuC72pPVQ74GawKrcyGTml1BkdK/AShkGxhqns6p8kPQy/+5EQZYBKl7KwwlW5U4ZEAR4Wfc/ycYL9K3f/kfvds2IG6q8EkQVFXexNlX6flgfjCw3JDBSt0W6dh6FtdvY8Ei3/cWLF9m5cyeZmZkIgkCrVq247777aNWqlSeGU3EDuYsXYcrMtD6wyOOH2uN05cdlOpgxTsPIbaJdndiWyDZkR1ZAQKT6h05YQJiawKrckJjMFq4We6bUsQwDfy+fSGL5CGK1W/iL7juaCspctXWIwiwDHKHOqV6A3g9GJ8EPM2Df5yBKq8gbo91GYvkIcvB8D6hBqyG2Z2s27M9weAOv1wrERLa29urpvXhxS0WlDnafuSL5mHG65URpjkrbxhPaXaKBnMOtSezly5d55ZVXWL9+PZYqiZBGo+Gpp57i3//+NyEhIe4cVsUNtJw5k/JL2RRu3izpuFcbwZmW1RNYAJ9yeChNJHGYppLNTkMTWY1Gg9lSffXqQuEFdSdW5YbkapHR4/62OTTmY/OTCMAb+rUeHcstaPTWHdiHEhRlGVARdU71QkTRWrcvsViplF6xuUVGzuYWsfm1aL7+PZOU07kUlpUT4KMjqn0QsT2lLSFWUZELqe2jQsgjRrsdkFqHQj715dpwWxKbn59P//79OXbsGH5+fgwZMoSIiAgAzp49y08//cTatWv5/fffSUlJURXjFIZgMBD2/hyO9+mLWFoq2bhNi8F02fFzqZ0Elj1gTVQdJbLjNllY/JDzq7yOEliAAmMBGQUZaiKrcsMh5USrSNVirQ+0vgfKS61lURF9rT2wCi4hVudUL8NUAp/HwFn5/IajNEclSWLBugP18dZTzB5+Jy8N7CjJmCoqSkNq+6hY7VZ55tbM36Qfsx647af/3nvvcezYMUaMGMFHH31UbWU4JyeHl19+mbVr15KQkMC7777rrqFV3MSlDz6QNIG10byg+rGqdjpVE9nsxvB1VMMSTX+9P3qtHpPZZPeHVRNZlRsRi4SLqIpULTaXwS2hMHyh3JHUG3VO9TK+ny5rAgsQpDfii4ZSkzQtQUlp55n6QGd111XlpqV3u2Ykn8iRbjy5RBRvdGGnDRs20Lp1az7//HOHpU3BwcF89tlntG7dmvXr17trWBU3EvT8RAQ/+b3mavKDtSWyP3YXiB+p5XKTht0d6zQ6wgLCaHNLGwINgfbjtkTWIsrTG3wzER0djSAIpKenN/ha33zzDX//+98ZPHgwjRs3RhAEHnrooYYHqSAsFgvz58/nzjvvxM/Pj5CQEEaMGMGRI0dqfZ1G4kQyvnwsKZYuykhgbRxYA1/+FUzSL9S5gjqnehEFl+C3VXJHQa7JIFkCC2Ayi6zde16y8VS8j23bthEfH8+jjz5KSEgIgiBw2223yR2W23ji7jC3q/7XRoAgvZUPoFhhJ7clsWfPnqVPnz7o9foaz9Hr9fTp04dz5865a1gVN2LKykKUSdTJRvYt1NrratYKLH6o4QksYN9p1QgawgPDqyWyWUXS++WquM7o0aOZPXs2v/zyC9euXZM7HLcjiiJPP/00U6ZMISMjg0cffZSuXbuyfv16evbsye7du2t8rdQlTzbV4sPmNpKOWycH1sDnT1lLPxWOOqd6EftXyOoRa0MOr9iU07mSj6niPbz66qvMmjWL7777jpwc6XYspeLjrScl7RYtFGXaaFKYj7oNt93Z+Pn51esNmpOTg58CdvtUKmPMuMD5v/wFyspkjeO9WPf5wNZGgCGAlv4t7Y9tiWxGQQYFxgL0Gj3BfsGuXbww2+oXmP6rtQTDS3rwvJ2nnnqKLl260KtXLwoKChg6dKjcIbmVpUuXkpSURKdOnUhOTqZFixYArF+/npiYGEaNGsUff/yBTlf9Y72pv4FLBWUeF3eqSBkG/AV5P08ccnaHVUF26IdyR1Ir6pzqRaT/KncEWERYax4o+bhSC9sojcsFZaxJPcfuM1dUcSsHDBkyhNjYWHr16kVwcDA9evSQOyS34S6P2GDyeVq7hd6aowQIJRSKfqRYurDWPLCa2vhuSxf6aw82eEzn0CjOR92G25LYyMhItm3bRlpaGpGRkQ7PSUtLY+vWrURHR7trWBU3kbt4EWKJ/LsTI7dauOJv4X/3uWe3tSbKyqvfXNsS2ayiLIL9gjFoDc5d1FRi7Yv6bVX1VfnTW2Dre4pXQ/VmFi9ebP//1q1b5QvEQ8ydOxeAOXPm2BNYsCbvjz/+OF9//TX/+9//eOqpp6q9Vq/V0LSRnitFRsniBWgmKHRHfP9KGPh/il5UUudUL0IB/WImdJLY61RF6ioPpVBqMhO/8TBJadVthpJP5DD/5+OqzRDW+cqGO9qGlERDPWJ9MBKnW06Mdns1sab+2oNM1q0nyTyA+PIxlGG9H5VFOFEQIOl5KC9R3KaM28qJp0yZgslk4v777yc+Pp4TJ05gNBoxGo2cOHGCWbNmMXjwYMxmM1OmTHHXsCpuouXMmegU4DnY8yQM+R3iVpoJyfPcrpHJYnJYLqwRNIQGhLqWwH4eY92BramszGKCtGWKKGdMT09HEASio6MpKSlhxowZtG3bFh8fHzp27EhCQkKNu3ZHjhxh1KhRtGrVCoPBQFhYGGPGjOHYsWM1jrdw4ULuvPNOfH19CQsL45VXXiE/P7/OGCdNmkRERAQ+Pj6EhIQQExPDgQMHGvS9u0pZWRnBwcE0atSoxti3bduGIAgMHjzYrWOfOXOGI0eO4Ofnx6OPPlrt+ZiYGAA2btxY4zVCG/vhf5PecFbDYoJ9K+SOolbUOdWLUEC/WK54iyzjRrUPkmVcOSk1mRm7ZA+r99ScxJjMIqv3nGPskj2UmuRVak9NTUUQBPr06VPjOfHx8QiCwDvvvCNhZN5NQzxifTCy3JDASN2WGhNSg2BmpG4zyw0J+GBdgLYJJ4LVzUsSRDOkb4eMVOuGzOZ/wtxbFaEx4bYk9pFHHuFf//oXhYWFvP3229x22200atSIRo0acdttt/HPf/6TgoIC3nnnHR5++GF3DaviRgydOkk+5rU/q+DKqtxbN78GT+x07we/gIDwp9JMg8qFHeGMMqWtnFEBGI1GhgwZwsKFC+nSpQsDBw7kwoULzJgxg7feeqva+b/88gs9e/Zk1apVhIaG8tRTT9G8eXM+++wzevbsSXJycrXXvP7660yaNIkTJ04waNAg7r33XlauXMnAgQMpq6F8fceOHdx1110sXLiQgIAAHn/8cTp16sSXX35JVFQUW7ZscfvPoi58fHwYO3YsJSUlrFy50uE5ixYtAuAvf/mLW8f+/fffAbjjjjsc9kjaSrRs5zlCoxFoF+RPs0ZOLtA0ALlurOtFurxKsnWhzqleRETNyYFUZIlNJR9TrxWI7dla8nHlJn7j4XonMLvPXCF+Y+3Ce56mV69eREZGsnPnTg4fPlzteYvFwtKlS9FqtYwfP16GCL2ThpTSx+mWE6U5WmciKopW66w43fVFV0UIJ4oWq8bEh3dByVXZwnCrh8jMmTNJSUlh9OjRREREoNfr0ev1RERE8Nxzz7Fr1y5mzpzpziFV3ETW7NkUb98u+bgnQuHnbnA8rPpzzYpA24BSDUeIoohG0BAWGOb8bmtNuKJMuX+ltXdWZnbt2oUgCBw/fpwffviBH374geTkZHQ6HfPmzaOw8HqZXFFREaNGjaKkpIRPPvmEtLQ0Vq9ezf79+0lMTKSwsJCRI0dWSkx37tzJ3LlzadasGWlpaXz33XckJSVx4sQJzGYzKSkp1WK6du0aI0aMoKSkhHXr1nHo0CHWrVvHzp07+emnnzCbzTz33HMYjdKWxgJMmjQJgE8//bTac3l5eSQlJREUFMSTTz5pP27b9Xbmy+YHasMm3BMeHu4wLtvxugR+NBqBsKaN0EjkHvW9+R5pBnIFBZSA1oU6p3oJ3ceApBql1WkpuL4r5CoxkTdf36crfZBJaee5XCCvPoBt7rIttFbkp59+4uzZszzyyCOEhVlvxpYtW+b0vDVu3DgpvyXZcbWUPoQ8YrTW++26ElHb8zHabQRjrQCzCSf+1vxJ0NQs/CcJhVnwn96yVRe6vbasZ8+eLF++3N2XVfEwQc9PpGjbdkyZmZKOG3kKrvpD06Lqz/U8CeM2WVj8kHv6ScQ/NeQsooX8snz89f5uua5LypS2csb+r7snBhfRaDQsWrSI4ODru9I9e/bk4YcfZuPGjezdu9feb7d27VouXbpEv379eOGFFypdZ8qUKaxcuZK0tDQ2bNjAM888A8B///tfAF577TW6du1qPz8oKIj333+fBx98sFpMS5YsISsri5kzZ9rLZG0MHjyYF198kfnz5/PNN98wfPhwt/wc6kvnzp0ZOHAgW7Zsqdar+Pnnn1NaWsqLL76Ij8/1G7uAgADGjh3r1DgVfx+AfTGhUaNGDs/39/evdF6dSFSGtNT8MJN036AVpNRvrCd556ylUArvT1fnVC8gsAX4B0PRZdlCaClcJZh8yfpie7RpQtzQ2yUZS0m40gdpsyJ6aWBHD0VVNyNHjuT111/ns88+47333qs0RzmqIOrYsaPT81bfvspUsPUUrnrExmq3Ot3TahDMxGq38LH5SQCMGAh7biEUnYT/3ud0DG6l8BJsfFUWH3a1QUoFAEN4GG1WrCD7w/kUp+zGfFm6ybhiAnuwLZTprQlsdmP4Osr9W0ZaQUuLRi3qPrG+uKpMmb5D9iQ2IiKCzp07VztuO3bx4kX7MVup8KhRoxxea/To0aSlpZGcnGxPYnfssJZsxsbGVjt/yJAhNGvWjCtXKu8gbNq0CaDSbmZF+vbty/z580lNTZU8iQV44YUX2LJlC59++mmlJNa2Oztx4sRK5wcHB7Ns2bIGjWnrTxbcVT8k0aaRtX+nH0/rpK/yqJPCS9b+9NFJoFfVfVUaSFBnWZNYjUClm1xPcyAjn/iNRyoJF90MSr2u9kGmnM6VNYn19/dn1KhRfPLJJ5UWmrOzs/n6668JDQ3lkUcesZ/ft2/fmy4pdZbYXq2Z//Nxyp10puytOerSeFGao/a/76b+Buvf1P7vXLqW2zm4Doa8I7nYk0RFZSregCE8jPD336fV7NkeHacooOa1k5ZXYMUgDT92F4gf6RmFYrNo5lTeKYcKxS7halmiAsoZaypPDQiwCpVULA3O/HOXvmqpqw3b8cwKu/mZmZkIgkDr1o77ptq0qe4jalMw7N27t8OSJdvurFyec8OGDaNFixasWrWKoiLrCsyePXs4cOAAffv2pUsX93s1BgZaPYxt41XFdtz2e6uNcrMFKe2g/1E+gXzR8Q6y7CioP13FyykvljsColy8OXaFcst14aK8YiMzvzzAfe/9wgc/HSf5RA77z+WRfCKH9388xn3v/cLMLw/KLnDkDlztg1SCFZGtgqpiO8yyZcswmUxMmDABrfbmVVF2heaBvtwe6nzlQ4DgWultxdflFxutJeoKsPcCrD2yMoglurwT2759ewRB4Oeff6Zdu3a0b9++3q8VBIFTp065OrSKB7EUFXHh5Zc9OoZ/Yc0f5iEF8Giq6LYS4powWUycyj9FxyYdG94b66oypQIULV3Z2avrNQ3dLTSbrTc6I0aMqLF8FqxJrhzo9XrGjx/Pe++9x9q1axk/fnytgk45OTm8/rpzO+7BwcF88MEH9se2ZD8jw3Evlu24o0WBilgsIicuS7t4UoaBJeUPMUX/paTj1huF2O2oc6oXU3AJsqT2bqyOqzfHDWH3mSsMmbed7Fp6Pm1KvacvF7J8wj1ebTnjah+kEqyIunXrZhdGPHXqFB06dGDx4sUIgsDzzz9f6dwdO3Y47J+tjb59+1arRLrRceX3Wii6VvlT8XVmEWuJugI2Q+zIUF3o8l+VbbfEZDJVeqyiTIwZF8hdvIiWM2ciGBwnbZaiIk4OeRCxVD7J7INtYdkD0hQIiKJIdnE24YGOdyPrTUQfq+y406/zrlKd0NBQwGr34oizZ88C0KqCVVOrVq1IT0/n/PnzdOxYvZTKkRBReHg4x44d480336Rbt27uCN3t/PWvfyUhIYFPP/2UESNG8MUXX9C4cWNGjBhR7dzCwkKnexrbtm1bKYm96667ADh06BAmk6maQvG+ffsA6vx5ZeSVUG6WcBv2T1aZBzNZ96W8aoo1oZD+dHVO9WL2rwCL/DttZaI8iVJtCWxFbEq9s4ff6eGIPIerfZBKsSJ64YUXSElJYfHixTz44IMcP36cIUOGVKuwOnnypEu9+DdbElviQnXBbksX+mudX/RKsVSu8ko5nctLOgW1wsiQULucLVgsFiwWi713zva4vl8q0mHMuMC5MWPIW/0FGZOnIDpQdRWNRk49NhRzbq4MEV6nzINCa4KDRkCN4IaEufsY5xXiNHqrWbQX0a9fP4Aa7WVsx23nwXWhh3Xr1lU7f9OmTdX6YQG7x+pXX33VoHg9Sbt27RgyZAi7du3irbfeoqCggNGjR+PnV31CiYiIQBRFp76qJjDt2rWjS5culJSU8O2331YbIykpCYDHHnusxphNZgv5xdIrOnsFCrDbUedUL0YhJX0mL5A5UYJSb0OI7dUavda51TglWRHFxsbStGlTli1bxieffAI4riAaN26c0/NWQ7UfvBFXdmLXmqMxis5VIxhFLWvNAysfKy2CvHSnx/cYMlQXqj2xNwG5ixfZVYcLN292mMhmvfMvyiuI+NjQNGkiRYh2ep6EqRssbrfWgevqxDYCDAG09G/Z8AsHtoC7Rzr3mu6jZC9fdJbY2FhatGhBcnIyCxdWVqFbsGABqamphIeHM2zYMPtxm6x/YmIiR49e79e6cuUK06ZNczjOpEmTCAkJ4d1332Xp0qV2USMbRUVFrFixosbSWmeYNWuWy9YAtv6i+fPnA55fgZ46dSoA06ZNIzv7uj3Tl19+yddff027du1qFMMCuFpklEqUuBrjtd8rcxfWhpJKslS8D4W8fwwov+fUptTrrTQP9CUm0rnqLSVZEfn5+TFmzBguXrzImjVrCAkJ4YknnpA7LK8lso3z/sxWwcP+APXyiQVIMg+opjz+QvFCq8q+UpChulBNYm8CWs6cScCgQfbHVRNZ0WjEeL76pOLfrx+CnzT2E+YKN7i9TogeS2RtBBgCaB3Y2j07sQAPJ0Dbev4Bt+0LDyW4Z1wJ8ff3Z+XKlfj5+TFp0iR69uzJyJEj6dGjB6+++ir+/v6sWrWqknR/3759mTx5Mjk5OXTv3p3HHnuMESNG0KlTJwCioqKqjdO0aVM2bNiAv78/EyZMoF27djz22GM89dRT9OrVixYtWjB27Nhqwk7//Oc/iYqKIioqihdffBGAlJQU+7GoqKhKasuAfQeranlufRg6dKjdU69Xr17cfffdTl/DGSZMmMCwYcM4ceIEt912GyNGjGDgwIHExMTg6+vL559/Xuv3IaewyFDtLtnGrhcK6E+/USgtLSUuLo7OnTvj6+tLaGgoEyZMcGnRKS8vj8mTJ9O2bVt8fHxo27Ytr776Knl5ee4PvCEo5P1jEJy0epOJlNPyVnw1lLihXendrlm9zu3drpnirIhsi8tg3XF1Zf6rL4sWLbLPv7YF7rNnz1aal23tMN5GqcnMtuOuKZLHl48lxdKlXj6xKZYuxJdXrtwLIY/+xZtcGtsjyFRd6LYk9sSJE6xYsaJav9yePXu49957CQgIoGvXrvzvf/9z15Aq9UQwGAifP89hImspKiJj8hSKd1W+yfTv1w8EAfPFLEli1IpWSx0bvU6IjNvkmRI5f72/exNYsFp0jE6CyHE1lxZr9NbnR69XvDdlTdx///2kpqby7LPPkpGRQVJSEllZWXZ7nYqlxDYSExP55JNP6NixI5s2beLXX38lNjaWLVu2VEp4K9KnTx8OHjzIa6+9hp+fH5s3b+ann37i2rVrPPbYY6xZs4bbb698Y3Dq1Cl2797N7t277bu++fn59mO7d++upLYM8PvvvwPw3HPPOf2z0Gq19O9vXU11VI7lbjQaDevWrWPu3LmEhobyzTffcPDgQYYNG8bevXu5777aveIsMlq1hgh58g1eH1rLIxJWG944p5aWlnL//ffz9ttvU1hYyBNPPEHr1q1ZunQpPXr0cEp8Kjc3l3vuuYcPP/wQnU7Hk08+SWBgIAsWLKBXr17kytz6UomIPnJHALguGCM1SlDqbQi+ei3LJ9zDs/e0qbG0WK8VePaeNooUsurSpYtd48LTFUQZGRn2+fe3334DrJ8TFefla9eueTQGTxG/8TD7z+e59NoyDIw1TmdV+aAaS4uNopZV5YMYa5xOGZW1bJ7WbkUrKujvSKbqQkGsWqvnIi+88AKLFi3izJkzdjuNy5cv06lTJ65du4YgCIiiiE6nIzU11S5UouIcXbt2BeDw4cNOv1Y0GsmYPIXCzZtrPMf37rsxX7uGISyUomTp+sQu3NWK6YMv8erXIr1OiGQ3xm0WO3pBz9/b/532jdtjaGHAoDPQsWlH9yaxFSnMtgrFpO+wlpkZAqxlFj3GeF0J8Y2MxWIhKCiInj172r1pnaG4uJjQ0FDMZjOZmZl2GxylcvpyIYVl5YiiBfOVTE5kF/LWllyMErRTnvQZjU5QcN/m7U9AbN32AA35/HUWb5xT//GPf/DPf/6Te++9l59++slu+ZSYmMhrr71G//792bZtW72uNWbMGD777DOGDx/OmjVr0OmsvWd/+9vf+Pe//82YMWNcEp6piNt+nwWXYF5Xq0iYjMwxxUrmE9sQ+nUK5rPnPbNwZLFYOHbsGAC33norGo1nCw4vF5Sxdu95Uk7neo037s6dO+nTpw8DBgxg69atcodTL6T+vdZFdkEpfd7bjMkNFYPB5BOr3UKU5igBQgmFoh8pli6sNQ+sVkJs4wu/94gSDzR4bLegNcCM8y5tzjT0M9ht74IdO3bQrVu3Sn6QS5Ys4dq1a7z22muUlJSwYcMGzGYzc+fOddewKk7gaEe2KqVHj2I6fVrSBBag2FSMWSvw4eMC54Lh349pPOIRC1Z7nawiD+4wBzS3Kp2O+Qom/mz9t//ragKrMPbv309eXh5vv/22S6//z3/+Q35+PmPHjlV8AgvyWjyUo6ydiGoc3WhdfFIQ3janmkwm/v3vfwPWv42KnsVTp06lW7dubN++nbS0tDqvlZWVxcqVK9Hr9Xz88cf2BBbg/fffJyQkhJUrV3Lp0iX3fyOu4IougptxJPyiVJSi1OsOQgJ9eGlgRz57vjcbXuzDZ8/35qWBHRWbwAK8++67ALzsYTvFG5m1qefdksAC5NCYj81PMsY0k+HGtxljmsnH5idrTGABgnQKah0IjZStutBtSezFixdp27ZtpWPff/89Pj4+xMXFYTAYeOKJJ4iKiiIlJcVdw6o4iWAwEPb+nJpPKJNHNbDTkXxe+9LM5P9ZaJMDr3xjISTPM/WPgiBgES0YzapS681MZGQkoihy77331vs1ubm5TJw4kccee4wZM2YQGBjIzJkzPRil+2jqb2iwh6+rXBadN4SXFJmM2mvD2+bUHTt2kJeXR4cOHejevXu152NiYgDYuHFjndf6/vvvsVgs9O/fnxYtWlR6zsfHh6FDh2I2m/n+++/dE7w7eDgBfJtIPmxtwi9KRElKvTcTO3fu5Pnnn6d37958++23REZGMnz4cLnD8lp2n6nurCAlPgG3yDp+JToNlm1otyWxpaWl+Ppez8TNZjN79+4lKiqq0opsREQEFy5ccNewDeZmE6EQjUYuvOFYFVYOyips0PQ8af0CaJ4Pj6d4pvxQFEXyy/JJz09XE1kVpygoKGDx4sVs2rSJHj168M0339jFnZSOXquhsZ8HPaxqwAcjGtl0kZ1AATY7FfG2OdXWX96jRw+Hz9uO286T6lqSofeD3i9IPqwgQJqlUzXhF6lo5GS/p5KUem8mjh8/zpIlSzh69ChDhw7lyy+/lL0k15uRs69bAwTdXnNFpaQIOlntIt32Dm7dujV//PGH/XFycjLFxcUMHFi5vKWkpAR/f393DdsgbjYRivr0xEqNTw2OAKmdBJY94NkPWJPFRE6J86blKjcvNs/XsrIyUlNT7cJO3oKPTvqbljjdcsI0uXVaCciOQmxSbHjbnHrunNXqITzcsf2I7bjtPKmuBda+K0dfzszx9aLnBOc9w93AncIp4nQr8EH6Rdln72nt1Uq9Nws239dr167x9ddf06ZNG7lD8mrkbM9pFxKAf9R4QAG+dT1Gy9oq57Y7mvvvv58DBw7w4YcfcuDAAd58800EQajmP3Xw4MFKPT5y8u6777Jz507uvfdejh8/zpo1a9i9ezdz587l8uXLTJgwod7XmjJlCidOnGD48OEcO3aMNWvWcOjQIV555RVOnjxp93iUEmPGBS7GxyMajQ4T2IBBg7g1bS8B0dGSx1YbByIgcZgGs5OG4ioqKrVTJPHqcQh5xGi3AyjbJxYUY5Niw9vm1MJC6yJAo0aNHD5vS7Rt50l1LUmRqTfWIFgYqdvMckOC5Ins8exCr1bqVVFxhfou3HiCs7lFXDb5gF8T2WIAFGEX6balhJkzZ7J27Vp7siaKIk8//XQlxcTDhw9z6tQpRTST1yVCsXz5crsIRWRkZK3XqkuE4osvvmDlypXMmTOnWn+PpzBmXODcmDGYMjMxXcxCAAorqNAFDBpE+Px5AIoq9DsQAbNjtZIlsBZRwYqpKipuRmqbnVjtVgxCDeUWSkMGo/ba8LY51WZ0UFPftTNGCO68FtSsfGlTxnQrDydA7ik4K215uihClOYocboV/L3cs7YpFSksK8dXr2X28DuZ+kBnr1PqVVFxhdherfnwlxNuE3dyhkaWAnQfdQfLVcnHBqzVJt1HWRNYme0i3ZbEhoeH89tvv/Hpp59y+fJlIiMjGTduXKVz9u/fzxNPPEFsbKy7hnWZ+ohQHDhwgI0bN9aZxNpEKAYOHFijCMWSJUv4/vvvq/1MPEXu4kWYMjMBKKoioV4xgc2YPKXa83KR3ViaBFZAQEREp9HRvJGqGKxy86CReDe0t+aotAO6ikxG7bXhbXOqTaG7qKjI4fPFxcUAlRaMpbiW5Ng8wze+CgfXWUXDJMCW78dot5FYPkIykSeD9npBn02p96WBHSUZW0VFLpoH+hITGc7qPeclHdcHI5t8ptHUkifdoE3bgX+wIu0i3VrUHRYWxqxZs2p8fvTo0YwePdqdQ7qM1CIUS5YskVSEouXMmZRfyq7W/xoQHV0pga30vI+PbOrEAHOGC55PYAWBdk3acbX0KsF+weg0OjILMwn2C8agNdR9ARUVLybAR0dBqXTlhgFCiWRjNQiZjNrrwpvmVFuPXU2iiLbj9enFc+e1JMdUAt9Ph0NfSpbAVsQgmInVbpHML9YgQ5+9iooSiBvaleQTOWRclW6ee0/3KS2EPMnGA+CWUBj/nbRj1pOb9tNHySIU0HAhipo8YUVANJmqJbC6sDBZE1iAaV+KaD1cmiGKIuevnbcnsBkFGVwtvaoqFavcFEhts1Mo+kk2lssooK/nRsBW5rxv3z6Hz9uOd+vWTdJrSYqpBD6PgX3LwSKfj2OUhBUQxnK1JUfl5sRXr6VNM8d9+54ghDwe1+6UbDw7V9OlH7OeuF1eq7i4mL1793Lx4kXKakmKxoyRt3TrZhChsCWyFRPWoq1bORbZs9J5AYMGEfruvzj12FDMOfKp9TbPh6kbLB4XdbKpEpdbyikwFlQ6FhoQ6rFxVVTkRq/V0NRPz2WJxttt6UJ/7UGJRnMWASLHKqKvpza8ZU7t06cPjRs35tSpU+zfv79am05SUhIAjz32WJ3Xeuihh9BoNCQnJ5OdnU3z5td3ycvKyti4cSMajYaHH37Yvd9EfSnMtiaq6b9aVa1tZXaXj0neC+sIKSsgjGY1iVW5eSkolU4sMVa7Fa0gg4qNqVj6MeuJW5PYf/zjH8ybN8/er+IIURQRBEH2CVfJIhTgPiEKR4lsRQIGDSLs/TlceGOa5Ans1Ubw+vMCs1eINM+3Hut1QvR4IqsRNJgsJgorWGoEGgJp6d/SI+OpqCiJVo39uOy8DbZLrDVHM1W3Tp6Jty4CWsDQD+WOola8aU41GAy8/PLL/Otf/+Lll1/mp59+si/gJiYmcuDAAfr27UuvXr3sr/noo4/46KOPGDZsGLNnz7Yfb9WqFc8++ywrV67kxRdf5IsvvrALJk6bNo3Lly8zevRoWraU+DPbVir826rqO62nt0gbSy1IWQEhp9WIiopclJrMxG88zMEL+ZKNKZvGhF663WZncdunz5w5c3jnnXfQ6XQ89thjdO7cWZmiC39yM4lQCAYDYe/PqbYDCxD67r+49MEHsnjHNi2GF78T+b0NtCiAbunW455OZC2ipVoCGx4Yjka4aavrVW4iNBpB+XY3UmCWt32iLrxtTgV48803+fnnn9m5cyedOnWiX79+nD17lt27dxMUFMTSpUsrnZ+Tk8OxY8e4ePFitWvNnz+flJQU1q9fz2233UbPnj05fPgwhw4dokOHDsybN0+qb8uKrVRYATutdZFi6SLZWFHtgyQbS0VFCZSazIxdsofdZ65IOq5sGhNNIuQZtx64LYn99NNP8fPzIzk5uUaBIyVxM4lQiEYjF96Y5vC5EwOiabtqFUXbtlvVjCUWd4r8s8W3WA9Hw6DLBevjXidExm2ysPghz3rKBRgC1ARWRcVDyFb+VB/0yu7X9bY5FcDX15ctW7Ywe/ZsVq1axVdffUXTpk0ZO3Ys//znP53ysw0ODiY1NZW4uDi++uorNmzYQIsWLXj55ZeJj4+nWTOJfRq/n+4VCaxR1LLWPFCSsXQagdie8nsUq6hISfzGw5InsCCjxkTHQXWfIxNuu3M/f/48AwYM8JrJ9mYRoRCNxhpLiQHEsjLSn3mGsH//m8axI/Dp3FniCK00MkFENvweYX2c3Ri+jvJ8YqnX6NUEVkaio6MRBIH09PQGXefSpUssXryYYcOG0blzZ/z8/GjSpAkDBgxg+fLlLpX0K41jx44xb948nnnmGdq3b48gCAiCQFZWltyh1YiiLXbMyvav9bY51Yafnx9vv/02J0+epKysjKysLJYtW+YwgZ01axaiKLJs2TKH12ratCkLFizg3LlzlJWVce7cOf79739Ln8AWXLKWECsY20dcknmAZPY6FlEkcdNxSk3K/ltSkZe8vDwmT55M27Zt8fHxoW3btrz66qvk5eXJHZrTZBeUkpQmUT9OFXZLWGFhR9Apzn6uIm67e5e8N6WBVBWhqEpDRCgqIqcIhaME1j86Gv9+fSufaDKR/swzlJ08SdlB+URY/EyQ3UTgx+4C8SO1XG7i2ZpHvUZPsF8wFtFCZmGmqk7sxbz22mtMnDiRb7/9lpCQEJ588knuvPNOduzYwbhx44iNjcWs8KSlLj755BOmTp3KmjVrOHPmTIOuJVU5saItdoqyrQI9CsXb5tQbmv0rZFUbrg+CAHmiP100Z1mhn82L2q8IxrP9ehYRVu85x9gle9REVsUhubm53HPPPXz44YfodDqefPJJAgMDWbBgAb169SI3N1fuEJ1ibep5TB520ahxbHM0RtGz1YnV6DFakfZzNtyWxD7zzDPs2bOHq1evuuuSHsUmQgHw8ssvV+pnrU2E4rbbbmPmzJmVrmUToTAajbz44ouUl19XK7OJUIwcOVLSmxJHCWzAoEG0XvAhrf/zHxr1rZ7Ilu6rnsxLyYEIWDJEw+KHPJ/AAhi0BrSCVrXZuQEICgoiISGBrKwsfv31V1avXk1ycjIpKSnccsstJCUlsXjxYrnDbBB33nkn06dPZ/369Zw7d462bdu6fC2NRFmssi12RNi3Qu4gasTb5tQbmvRf5Y6gVmy31E2EIrprTtFfe5Bp+rXs9HmZd3WL8MGz89ruM1eI33jEo2OoeCdTpkzhxIkTDB8+nGPHjrFmzRoOHTrEK6+8wsmTJ5k6darcITqFHGXENi7ThCRzf+B65YVHEXQwOF6CgVzHbUnsrFmzuP322xk+fHi9vUzl5s0336R37952EYqnn36aqKgoXnvtNZdEKDp06GAXoXjmmWe48847WbBggSwiFFmzZ1dLYMPnz0MwGBAMBtp87CCRlZGj4TA7VutRa52qFJmKOJl3sprNjitcKLzAOynvYDLXvlpvMpt4J+UdLhRecGkcFcd8+OGHTJs2rVqZYa9evZgxYwYAq1evliM0t/H888/z3nvvMXz4cKd6Cx2hk0jcSZbyJ2dIV26PozfOqTcsRmnt8WrDdvN6WQwkT7SqP9f0p2wQzIzUbWa5IcHjiWxS2nkuFyhbLM0jFGbD9vdhxZOwaLD13+0fKLrKQyqysrJYuXIler2ejz/+2K4wDvD+++8TEhLCypUruXTpkoxROkdhmXSWOo6ILx9LiqWLNNVUYjl8McoqaqdQ3JbEPvLII1gsFrZv385tt91Gp06dGDhwIIMGDar2df/997tr2AZhE6F46623aNSoEV999RXp6emMHTuW/fv307Fjx3pfyyZC8corr2A0GtmwYQP5+fm8/PLL7Nmzh+DgYA9+J9UJen4i+lCr52nFBNaGYDDQ+sP5ksZUG+eDkCSB1Wl0+Ov97Y/LLdc/kFy12blQeIEJP0xgzbE1TN02tcZE1mQ2MXXbVNYcW8OEHybImsimp6cjCALR0dGUlJQwY8YMe79Kx44dSUhIqLGP9MiRI4waNYpWrVphMBgICwtjzJgxHDt2rMbxFi5cyJ133omvry9hYWG88sor5OfXXuqWnp7OpEmTiIiIwMfHh5CQEGJiYjhw4IBT36utZz0zM9Op11WlrKyM4OBgGjVqVGPs27ZtQxAEBg8e3KCxPI0gCDRtZKj7xAYiS/mTM5Qod5fTG+fUGxaDclShBQGuiY3YZr6bJkJRnTsyoghRmqPE6TxbdWAyi6zde96jYygKUwl8/TdIvB02v2O1WMpItf67+Z/W4xtfBVOp3JGSmpqKIAj06dOnxnPi4+MRBIF33nnHbeN+//33WCwW+vfvT4sWLSo95+Pjw9ChQzGbzXz//fduG9PTyG0pVYaBscbprCofJM3cenYH/DDD8+O4iNt+G1u3brX/32w2c+rUqRpXj2vyU5UDmwjF22+/Xee5s2bNYtasWTU+bxOhWLBggRsjdA1DeBhtVqwgd/EiWs6cWSmBhT/LjV97XaboKpN9Cyx9UJob3XJLOSIiOo2uUgKr0+gICwhzSeRp6aGlZBZZE6St57cyddtUEgckotfq7efYEtit57cCkFmUydJDS3kz6s2GfDsNxmg0MmTIEA4fPsw999xDly5d2LZtGzNmzKCgoKDahPbLL78wdOhQSkpK6NGjB9HR0fzxxx989tlnbNiwge+++45+/fpVes3rr7/O3Llz8fHxYdCgQTRq1IiVK1fy66+/4uPj4zCuHTt28Oijj3Lt2jW6du3K448/zoULF/jyyy/57rvv+Pbbbxk4sH4KnKdPnwYa3mPo4+PD2LFjSUxMtPtXVmXRokUA/OUvf2nQWFLQqrEvwYE+ZOZ7bvfEVv40UqccD81KlF6TO4Ia8dY59YYkoo9ifGBFEW4RihmmtVYR1PWrtz0fo91GYvkIj4o+pZzO5aWB9V/891rqY7dkMUHaMsg5CaOTZFVD79WrF5GRkezcuZPDhw/TtWvXSs9bLBaWLl2KVqtl/Pjxbhv3999/B6hRnK5Hjx4sWbLEfp430LtdM5JPuFax5y7KMPD38okklo9gpPZnJuh+oIng2OLTLexfCQP/T5G9sW7biT1z5ky9v2w3lSqexRAeRqu4OIcJ7Pm/vUpRhZskubjqB1P/4hk/2JooNhVXSmDBmtxeKnatpGV6r+lEt462P7YlsrYd2aoJLEB062im95ru0njuZNeuXQiCwPHjx/nhhx/44YcfSE5ORqfTMW/ePAoLr5fRFRUVMWrUKEpKSvjkk09IS0tj9erV7N+/n8TERAoLCxk5ciRlFSyadu7cydy5c2nWrBlpaWl89913JCUlceLECcxmMykpKdViunbtGiNGjKCkpIR169Zx6NAh1q1bx86dO/npp58wm80899xzGI11l8eZTCY+/vhjAJ544okG/7wmTZoEWO1PqpKXl0dSUhJBQUE8+eST9uO2XW9nviIiIhoca22IIpzNLSJHgvK/+PKx9rJH5aFc1Wp1TlUQ3ceARl/3eRJgS0qdta4yCGZitZ5NxH87n8d/tpy88cuKnbFbUshOlm3usi20VuSnn37i7NmzPPLII4SFhQGwbNkyp+etcePGVbruuXPnAAgPD3cYk+247TxvILZXa/QS3q/WRg6NaSVcsVZkeHIgiwlSPvHkCC7jtp3YhoiMqEhHjQmsXg8m6dUX5d5AsO3I2pSKXUGv1ZM4ILFSompLZBP6JTA9eXq1BLbqTq1caDQaFi1aVKncvWfPnjz88MNs3LiRvXv3Eh0dDcDatWu5dOkS/fr144UXXqh0nSlTprBy5UrS0tLYsGEDzzzzDAD//e9/Aat6cMXV36CgIN5//30efPDBajEtWbKErKwsZs6cSUxMTKXnBg8ezIsvvsj8+fP55ptvGD58eK3f31tvvcXRo0dp165dtZhdoXPnzgwcOJAtW7aQlpZGZGSk/bnPP/+c0tJSXnzxxUo7zAEBAYwdO9apcTzdfmAyWygsk0ZNtAwDS8sfZIr+S0nGcwpfaaxIXEGdUxVEYAu4eyTsWy53JA0iSnOUj81Peuz6BaXlvP/jMeb/fJyYyNbEDb0dX72C2wlcwRW7JQXsZI0cOZLXX3+dzz77jPfee6/SHOWogqhjx45Oz1t9q+is2BbBGzVq5PB8f3//Sud5A80DfYmJDGf1HvlL50PI4yntdqDmvni3sSMRSq7AQwmg9/X0aPVG3uJuFUmpdQdWhgQWoEkx/Pu/Fl55AYwG6f1aOzTpQHZxNsF+wRi0rvcI1pTI9l7Vu9J5SkpgASIiIujswBvYdqyiiFlycjIAo0aNcnit0aNHk5aWRnJysj2J3bHDulodGxtb7fwhQ4bQrFkzrlyprPa3adMmgEq7mRXp27cv8+fPJzU1tdYkdvXq1cyZMwdfX19WrVpV40TqLC+88AJbtmzh008/rZTE2nZnJ06cWOn84ODgGn0w5cBktmC2SLsDuco8mFd1G9A4uXvkcfyayh2BirfwcALknqr/DpwCkcryymQWWb3nHKcvF7J8wj03ViLrit2SxWRVQu8vXwuXv78/o0aN4pNPPqm00Jydnc3XX39NaGgojzzyiP38vn37VktKncWmq1FTu4O3+rfHDe3K6ctFsioVA8Rqt2IQJLS2Ukh5fEXcnjUcOnSIyZMn06dPH2699VamTZtmf+7XX39lwYIF1W5aVaQha/ZsxzuwFdAGBaGt0oDvaZoWWRNZg9Ei6bgAmYWZtPRv2aAE1oYtka1YWlwRpSWwUHOZT0CAVcikYmmwTRipplJX2/GKAkqZmZkIglCjmm6bNm2qHUtPTwegd+/eDkuWbLuzOTk196Vs2rSJcePGodFoWL16NVFRUTWe6yzDhg2jRYsWrFq1ym7NtWfPHrstV5cuylbkvVokrY1UMPnEardS7v7ppuFEKEehvSbUOVUh6P2sN2+R40Djnev/Ulte3ZDWO67aLSlACd1WjVSxHWbZsmWYTCYmTJiAVuvexYbAwECAShaWFSkuLgau3294C756Lcsn3EO3cHkreXprjko/qELK42249ZN4zpw5vPnmm3afVEEQKt1oFhcXM2XKFHx8fOz1+SrSEfT8RAp/2Ux5tlX6XdOsGZYqNz/m3Fy0QUEej8UMFPnBLX8uDDctgsRFFl6dJEjaH1tgLCCjIIPwwHCXRJ2qotfqSeiXUG0HFiChX4KiElhwTRCmrtc0VGTGbLauLI4YMaLW3dPevav/jAF2797NsGHDMJlMLF68uMYdXVfR6/WMHz+e9957j7Vr1zJ+/PhaBZ1ycnJ4/XXnVuCDg4P54IMP3BJvVYoksgjwwUicbjkx2u3SrhbXF40eeoyRO4paUedUhaH3g6Efwvm9kH1I7micJkUGy6uktPNMfaAzIYGORfy8DlftlhRg09StWzeioqLYsmULp06dokOHDixevBhBEHj++ecrnbtjxw6H/bO10bdv30qVSLZF6oyMDIfn2447WsxWOr56LY395L2fk6qyohoKKI+34bYk9n//+x8zZsygQ4cOzJ07lz59+hASElLpnMGDBxMcHMxXX32lTrgyYAgPIzQxkfN/+QtiSUm1BNaGOTfX47FosSayeY2sJcUAzfNh3CYLix+StvTInYmsyWxierJjwabpydMVtxPrDKF/WjadOXPG4fNnz54FoFWrVvZjrVq1Ij09nfPnzzu0rHIk6BAeHs6xY8d488036datm1MxHj58mEceeYSioiISExPdqrRYkb/+9a8kJCTw6aefMmLECL744gsaN27MiBEjqp1bWFjI8uXO9dK1bdvWY0msFJXEPhhZbkggSo6V4vrSfZQiJuGaUOdUhVJwCbIPyx2F0xhFLWvN9VN0dyc2650bRrXYVbslhdg0vfDCC6SkpLB48WIefPBBjh8/zpAhQ6pVWJ08edLpeQsqt9PY7O327dvn8FzbcWfneaUgt2es1JUVdiwmSPkYDP7WygRjofX9HdHXujAs4bzqtvquefPmERAQwKZNm3j88ccJcrCbJwgCt956K8ePH3fXsCpOcu3bbxBLlGFc3LTEqpJ6+Rbr4+zG8HWUPCWHBcYCzl07h0V0vaTZkQpxRaqqFnsbNuuclStXOnzedryixY6tp2bdunXVzt+0aZPDMkibx+pXX33lVHzp6ekMGTKEK1euMGvWLKZMmeLU652hXbt2DBkyhF27dvHWW29RUFDA6NGj8fOrPqlEREQgiqJTX7aSak+gkaDQIU63nCjN0To9LGWjbV+rQIWCUedUhbJ/BUpWta6K7W8wyTzAo/Y6tZFy2vML45IRUbPXau2vU0brQmxsLE2bNmXZsmV88olVcdZRBdG4ceOcnreqaj889NBDaDQakpOTyf6zAtBGWVkZGzduRKPR8PDDD3vs+/UkcnvG7pahssLOjvmK8Ed2W8awf/9+7r333jqtIcLCwiqJxahIS8uZMwkYNKjSMcFXPqWxpiXW24FNdwvEj9RyuYl0pcRaTeUd3yJTEZmFmTWcXTs12ejsHrm7VvsdbyI2NpYWLVqQnJzMwoULKz23YMECUlNTCQ8PZ9iwYfbjtt2hxMREjh69vit35cqVSr19FZk0aRIhISG8++67LF26tJr4Q1FREStWrKhUopSdnc0DDzxAZmYmr732GnFxcfX6nmbNmuXQGqA+2PqL5s+fD1QXdFIaJrOF7GulGC2e7T0PIY8Ym2KiMpwIKqNvBKPXK0ph0RHqnKpQXO2JlAlBsJYRx5fLVzov946VW3HFbklBrQt+fn6MGTOGixcvsmbNGkJCQtxiP+eIVq1a8eyzz2I0GnnxxRftbREA06ZN4/Lly4wcObLBHu5y0btdM1nHX2uOxijKJZpWw0KezR/586esfsoexm1JbHl5eb3UPy9fvozB0HARHRXXEAwGwufPq5TIiqWl1QSepKT5NbAISJrA6jQ6zBb39OnVlMAmDkikkb5RNbEnb01k/f39WblyJX5+fkyaNImePXsycuRIevTowauvvoq/vz+rVq2qJN3ft29fJk+eTE5ODt27d+exxx5jxIgRdOrUCcCh4FLTpk3ZsGED/v7+TJgwgXbt2vHYY4/x1FNP0atXL1q0aMHYsWMr9QZOmjSJkydP0qhRI3Jychg3bly1L0d9qZY/Ezq9C+//oUOH2j31evXqxd133+30NZxh3759REVF2b9sicujjz5qP+aoh8liEcm4WswfWQVkXSvFWO7ZJFZyxURn0fkoPoEFdU5VLArobXSGy+ItjDVOpwz53iNy71i5FZvdkjMorHWhYuvBuHHjXJr/6sv8+fPp0KED69ev57bbbuOZZ57hzjvvZMGCBXTo0IF58+Z5bGxPI7dn7GWakGTuD6C8qieJBKDclsR26NCBtLQ0uyiLI4qKivjtt9+4/fbb3TWsigs4SmTlstgBKNGDnxFC8qT5K9QKWsot1VeG/fX+hAaEOn29hNSEWn1gHakWbz2/lYRUZZczOuL+++8nNTWVZ599loyMDJKSksjKyrLb61QsJbaRmJjIJ598QseOHdm0aRO//vorsbGxbNmypVLCW5E+ffpw8OBBXnvtNfz8/Ni8eTM//fQT165d47HHHmPNmjWVPkeuXr0KWIVuli9f7vArKSmp2ji///47AM8995zTPwutVkv//tYJxFE5lru5du0au3fvtn8ZjVaV4X379tmPVRXQsFhEzuQWcaXIKJmdgSyKic6gd4/VkqdR51SFopDexvpy1NJW1gQWIKq958UiJeXhBGtLQn1QYOtCly5d7BoXnq4gCg4OJjU1lVdeeQWj0ciGDRvIz8/n5ZdfZs+ePR73RPckNs9YOYkvH0uKpYsyq572r4TC7LrPawBuS2JjYmLIyMjgrbfeqvGct956i6tXr/L000+7a1gVF7EnstHRssYhYu2F7X9Y5O3PzZIksmax+k1hoCGQNre0cUnYafwd4wn1t04INdnoVE1kQ/1DGX+HZ0SH6oOtT3OrI89grGW2oig6LLPt2rUrq1atIisrC6PRSGZmJp999hm33nqrw2sJgsALL7zAoUOHKCsrIzMzk08++YQmTZqwdetWRFF0WDIZGhrKBx98wNGjRykuLqagoIBjx47xxRdfEBsbW2n3yXYdZ/pMLRYL27dvZ/DgwfZk1BmKi4v57rvvCAgIsHvueZLo6Og6v8dZs2ZVek1mfolkasQ2ZFNMrC9NI+SOoF6oc6pCcbUnUibkUCSuiF4rENvTscWa11LJbqmGXUyN3vq8AlsXdu7cSWZmJgMGDHDoE+9umjZtyoIFCzh37hxlZWWcO3eOf//73zRrJm85rjuIG9qVO8NukW38MgyMNU5nVfkgGUuLa8Dmj+xB3JbEvvbaa3Tp0oWEhAT69+9vV9Y8ffo0H330EYMHD2b+/Pl069bN3kumIj+ih/vj6kIA2v5ZFRpUAE9vlz4eP71fg5SJwwLCWPLQEp6+9ela1YdtiezTtz7NkoeWEBYQ1pCwVRrI/v37ycvL4+2333bp9f/5z3/Iz89n7Nixdj88JWEyW7haLH2FRZmo8NLBds4vWMiBOqcqFFd6ImVCLkXiisREtr5x7HUqYrNbmnoEBr0F7QdCeC/rv4Pesh4f+qHiEliAd999F4CXX35Z5ki8H1+9lkG3yVsqXoaBxPIRrCy/XxL3AafwsD+y2+42/P392bJlC+PGjeOHH37g11+t4gfbt28nOTkZURS5//77WblyZY0lhCrScvGddyjavl3uMCpRphF5/gczX0dpJOuRLSsvo9xSjkHreslVWEAYb0a9Wed5eq2+XuepeJ7IyEinS2xzc3OZPn06WVlZfP/99wQGBjJz5kwPRdgwrkpYQmwjmHxaCY6tuxTDyV+gz6vWm1AFo86pCsXWE7nPefsRqZFTkRiswjdxQ2/wUveA5tD/deuXgtm5cyeLFy/m0KFD7Nmzh8jISIYPHy53WDcE+87lyTa2zY99hHY7eiVqUXhYQ8CtS+bNmzfnu+++4/fff2fTpk2kp6djNpsJDw9n8ODB9O7d253DqTSAsjPpFG1TVgKb1sGqVtzzpEj302bJ1IotooWckhyX+mFVbi4KCgpYvHgxBoOBHj16MHfuXLu4k9KQUhHUNpHGaLcrW9QJIGMPLH0ERq5RlNiKI9Q5VaE8nAC5p6ziJQqlQPSVTZFYrxWIiWxN3NDb8dUrrMTxJuX48eMsWbKEwMBAhg4dykcffYRGI4+l4Y2GXOrbXuHH7mENAY/Ufd111112k2MV5VF2Jp0zw4ZZVYltaDQgY2lxWgdo4tOEDkfyAGieD4+nWFj8kOcnwABDAC39vVPiXUVabL3E3oBUZUVeMZFWJXMfJHaB7qOtoisKLPmriDqnKgxbT+QPM6ziJRblKc3/Zukgi6CTRoBHu4WqCazCsKn0q7gfudS3K/qxK1LYCTzuj6wuw9xkiEYj5yZOVFQCe7CN9V9bAgtwIAKWPSDN21PA+tdvES1kFmZiNBslGVdFxZNoJJrUKk6kXoWlXFI/O5UbjJp6Itv2sf6/5d2yhrfL0lWWcS0ifLX/AmOX7KHUpPCqDBUVNyCHX6zi/dhBEn9kty8fpKens337di5evEhZWZnDcwRBqFVxUcVzZM2eTfmFC5UPyizu1DIPQq5VPpbVGMwS+W8VGAvIKMhARKTQWEihsZCIxhEN6pFVUZGbAB+dx8ucvGIirQubn93QD+WOxCHqnKpwqvZEmkrg++mQnixbSEoQdNp95grxG48we/idssahouJpYnu15sNfTmAyS7eSq3g/dpDEH9ltSWxpaSl/+ctfWLVqFUCtJXfqhCsfQc9PpGjbdkyZmWiDgzHn5MgdUrUEdm9HWPqgtGVIBcYC+/9NFpPaI6vi9TT1N3CpoMyj5c9eMZHWh/0rYeD/KapHVp1TvRBTCXw2DM7tkmV4W1nhEUtbWcavSlLaeaY+0FlSdWKhwmqaxWJR+z5vECwVNlsEha2Y2vxiV+85L9mYivdjl8gf2W1J7PTp01m5ciXNmzdn1KhRdOjQAX9/f3ddXsVNGMLDaLNiBbmLF9Hi9de58MY0CjdvljssOwfawtzhWo/vwuo0OsotjnepAg2Bao+sitej12po2kjPlSLPlccrfiKtLzY/OwUpjKpzqhfy7euyJbBwvRribu1pdmpeJsk8gPjyMbL0xgKYzCJr957npYEdJRtTEAQMBgNGo5GioiIaN5ZPnVnFfRQVFQFgMBgUl8SC1S/29OUidp9xrzp/MPk8rd1Cb81RAoQSCkU/UixdaCJ4VvW3bgTAwcKqRm/dgZVIa8JtSeyaNWsIDg7mt99+o2VLNQFQMobwMFrFxQEQPn8eGZOnKCaRzfeXpoy43FKOv96fIlNRpeP+ev8GecaqqCiJ5oE+FJaWYzR7pmUgQLiBeknTdygqiVXnVC+j4BL8vkruKOwYBDMjdZtpr7nIWON02RLZlNO5kiaxAIGBgeTm5nLp0iXAalel7sh6JxaLhaKiIvvvUome7GD1i/1gxF1M+mwvRy4W1P2COqhN8b+/9qAC/GBFuO9vkHXQaqNjCLCKOPUYI2lFk9uS2MLCQh588EF1svUyBIOBsPfncCyyp9yhANDzD7i1u4VjbTw/4ThKYNvc0kZNYFW8HotFJDO/hKvFJo+WExeKyvZadQoP+9k5izqnehkpn4Aor75EVUQRojRHidOt4O/lE2WJQQ77kaCgIIqKiigtLSUzM1Py8VU8g6+vL0FBQXKHUY1Sk5n4jYdJSstwS19sfRT/pRJurJVTW+D/k9dmzG136127drWvlKh4D6LRSMZrytl98LPA/62xEJIn7TJToCFQTWBVbggsFpEzuUVcKTJ63A5ot6WLR68vKR72s3MWdU71Mo58JXcE1bBVXcZotxFMviwxyGE/otVqadOmDUFBQRgMqkCjt2MwGAgKCqJNmzZotcqybSo1mRm7ZA+r95x3m7BTfRX/ZXcEuHQQCrNlDcFtny6vv/46o0aNYufOndx3333uuqyKBxGNRjImT6Fo61a5Q6mEbzk8s9XMv5+UbvILDQhVE1iVG4LM/BKKJNr9WGuO5lXd+htD3MnDfnbOos6pXkZxrtwR1IhBMBOr3cLH5iclHzuqvTw7Z1qtlubNm9O8eXNEUfQaf2+VygiCoMgeWBvxGw+7tQ/WGcV/RfxYZNaScFuWMGLECDIyMnjiiSd45ZVXGDx4MGFhYTW++dq0aeOuoVVcwJbAKqUXtir3nICWuRaygqRJLE/nnaZj045qIqvi1ZjMFq4WmyQb7zJNSDL3Z6Rui7IN1+tCAj87Z1HnVBV3EqU5KnkSKwDbj18GILZna0lViivFofBESMU7yS4oJSktw63X9DrFf5m1JNx6x96tWzeaNm1KfHw8/fr1o3379rRr167aV/v27d05rIqTOEpgtU2byhhRdXzK4fUvpesvMllMZBRkYFFYT9ONTnR0NIIgkJ6e3qDrXLp0icWLFzNs2DA6d+6Mn58fTZo0YcCAASxfvvyGWYW3WCzMnz+fO++8Ez8/P0JCQhgxYgRHjhwB4KoEJcRViS8fS4qli/cmsCCJn50rqHOqF9FIeb16FZFDhE3E6hf7/o/HuO+9X5j55UFKTV50g66iUgtrU91XQmzD6xT/ZdaScNtO7DfffMPw4cMpLy8nJCSEtm3bqnYACiVr9uxKCawuLIzyCxeuPw4NRR8RQcnOnXKEB0CZFt5/yvO7ooIg2G/6C4wFnLt2Tu2N9UJee+01Vq5ciV6vp1evXkRGRpKRkcGOHTvYvn0733zzDV988YXi+mmcQRRFnn76aZKSkmjSpAmPPvooOTk5rF+/nm+//ZYtW7YQ0r6r5HGVYWCscTpxuhXEaLd51yoySOZn5yzqnOpl3P4E/Dpf7ihqRG4RNpNZZPWec5y+XMjyCffgq/fez2IVFcDtdjrghYr/MmtJuC2JjYuLQxRFli5dypgxY9TSDQUT9PxEirZtx5SZScCgQTR/43XOPz/R+jg6GhFk75Mt14LFw/JrgiDQvnF7souzKTBaJdGLTEVqIuuFBAUFkZCQwMSJE2nWrJn9eGpqKoMHDyYpKYnFixfz17/+VcYoG8bSpUtJSkqiU6dOJCcn06JFCwDWr19PTEwMo0aN4pvte2WJrQwDfy+fSGL5CGK1W7hPc5jbNOdpxjVlqCg6QmI/O2dR51QvI+pF+PVDHHonKoAUhYiw7T5zhfiNR5g9/E65Q1FRaRCeUN4uE6UXQmsQMmtJuO0u/ejRo/Tv35+xY8eqk63CMYSH0WbFCpo8+wzh8+fh066d9XFsbLUE1q9PH8njMwvgb4S4VWaPqhSLosiV0iuIVW46ikxFZBVlOXUtY8YFLsbHIxqNtY9pNHIxPh5jxoVaz1Nxjg8//JBp06ZVSmABevXqxYwZMwBYvXq1HKG5jblz5wIwZ84cewIL8NRTT/H4449z6tQpNv/wrVzhAZBDYz42P8lo0//Rs+y//Lf8cVnjqURgKIRFQvuBMOgtmHoEhn6oyAQW1DnV6whsAd1i5Y7CIUZRy1rzQLnDsJOUdp7LBWVyh6Gi0iA8obxd7r69Rc+jAC0JtyWxwcHBBAQoy6JApWYM4WG0iotD+FN+3hAeBlpN5R1YHx/Kjkpbn1+mA+2fOWXzfHg8xdqjqjWLPP+De5PaAEMA5ZZyCqvU9Os1eoL9gut9HWPGBc6NGUPe6i/ImDylxkTW1ouct/oLzo0ZI2sim56ejiAIREdHU1JSwowZM2jbti0+Pj507NiRhISEGnsrjxw5wqhRo2jVqhUGg4GwsDDGjBnDsWPHahxv4cKF3Hnnnfj6+hIWFsYrr7xCfn7tlg/p6elMmjSJiIgIfHx8CAkJISYmhgMHDjj1vd51110ADfYLLCsrIzg4mEaNGtUY+7Zt2xAEgcGDBzdorKqcOXOGI0eO4Ofnx6OPPlrt+ZiYGAC2//KDW8d1lmDyeUn7FSv0s/nS8A+e1f0iazyVKMgEnR88u9oqRKHAHtiKqHOqF6LRyx1BJWwf4UnmAeTQWN5gKmAyi6zde17uMFRUGkSPNk3cfk090vsqu4wCtCTclsTGxMSQkpLCtWvX3HVJFYkJen4imkaNrh8oK8Nyxf01/7XhU+HvN7WTwLIHNGjNIlM3WHhwv+i23dkAQwACgr2MGMBf709T36ZENI7AoK2/t1zu4kWY/kyQCjdvdpjIVhXTMmVmkrt4UYO/j4ZiNBoZMmQICxcupEuXLgwcOJALFy4wY8YM3nrrrWrn//LLL/Ts2ZNVq1YRGhrKU089RfPmzfnss8/o2bMnycnJ1V7z+uuvM2nSJE6cOMGgQYO49957WblyJQMHDqSszPFq/I4dO7jrrrtYuHAhAQEBPP7443Tq1Ikvv/ySqKgotmzZUu/v8fTp0wC0bNmy3q9xhI+PD2PHjqWkpISVK1c6PGfRIuvv9C9/+UuDxqrK77//DsAdd9yBXl/9RrlHjx4A/HHkkCy7dj4YeVf3KTt9XuYN/Vr6aw/SQ3OSpkKR5LHUytkd8MMMuaOoF+qc6mUUXIIDa+SOohKCYC0jji9XlvI2QMpp5VoSqajUh7O5xW6/pkHwkiS2SVtFaEm4LYl95513aN++PcOHD+fMmTPuuqyKhBjCw4hYvx6hYiIrE3s7CSQOs749p26w0OuENXGtuDvbEAqNhZUSWACj2UiwX7BTCSxAy5kzCRg06Pq1qySyjtSgAwYNouXMmQ34DtzDrl27EASB48eP88MPP/DDDz+QnJyMTqdj3rx5FBZe36UuKipi1KhRlJSU8Mknn5CWlsbq1avZv38/iYmJFBYWMnLkyEqJ6c6dO5k7dy7NmjUjLS2N7777jqSkJE6cOIHZbCYlJaVaTNeuXWPEiBGUlJSwbt06Dh06xLp169i5cyc//fQTZrOZ5557DmMdpdsAJpOJjz/+GIAnnniiwT+vSZMmAfDpp59Wey4vL4+kpCSCgoJ48skn7cdtu97OfEVERFS69rlz5wAIDw93GJft+Plz52jaSNrdIB+MLDckMFK3xTtEnfavlN2gvT6oc6qXsX8FWKSzt6oLo6hlVfkgxhqnU4Zzc5oUeKKfUEVFKrILSvnmwEW3X1duAbZ60zRCEa04biu+fuyxx9BqtWzZsoVbb72ViIiIGj3tBEHgl18UVGamYscQFkqjnj0p2r5dthhMWpj/uPV9UzGBheu7sx4Z12IipySH0IBQp14nGAyEz59XKVG1JbJh78/hwhvTqiWw4fPn2Uu55USj0bBo0SKCg6+XT/fs2ZOHH36YjRs3snfvXqKjowFYu3Ytly5dol+/frzwwguVrjNlyhRWrlxJWloaGzZs4JlnngHgv//9L2BVD+7a9bpyblBQEO+//z4PPvhgtZiWLFlCVlYWM2fOtJfJ2hg8eDAvvvgi8+fPt6u31sZbb73F0aNHadeuXbWYXaFz584MHDiQLVu2kJaWRmRkpP25zz//nNLSUl588UV8fK77IQYEBDB27Finxqn4+wDsiwmNalhgsqnWFhYWEtrYj7JyC0US3STG6ZYTpTnqPT6xFpPsBu31QZ1TvYz0X+WOwE6mpRkjjHFcIETuUGrEE/2EKipSsTb1POUW92u27LZ0ob/2oNuv63ZM7t+FdgW3fYpsrdBLWV5ezsmTJzl58qTDc1WRCmVizLjA+RdewFjD700q9GYYv8nCLSVCtQQ2cZgGs9Yz759AQyAt/V0rOa0pkT0W2bPSeUpKYAEiIiLo3LlzteO2YxcvXl9ptJUKjxo1yuG1Ro8eTVpaGsnJyfYkdseOHQDExlYXPBkyZAjNmjXjSpWS9U2bNgFU2s2sSN++fZk/fz6pqam1JrGrV69mzpw5+Pr6smrVqhoTQGd54YUX2LJlC59++mmlJNa2Oztx4sRK5wcHB7Ns2bIGjWnrT67PZ6dGI9AuyJ/M/BKuFptq7G3WueHvKIQ8YrTb/4ytwZeTDpkN2uuDOqd6GTL7JVYkVHOFV3QbmFGuXDX2qPbK9tVVUakNT9jrAKw1R/Oqbr3yq5pkttax4bYkVi138m5s4kSmzEwEX1/E0lJZ47n/AFS0KvB0AhtgCCA8MLxBtjqOEtlKYygsgYWay1NtgjIVS4NtwkhVS11t2I5XFFDKzMxEEARat27t8DVt2rSplsSmp6cD0Lt371pjz8nJqfG5TZs2MW7cODQaDatXryYqKqrWaznDsGHDaNGiBatWrWLu3Ln4+/uzZ88eDhw4QN++fenSxf1WFoGBgYC1pNsRtuO235tGIxDetBEtbrFwtchIYVk5FhE0AjTSa8gt0OCOP6VY7VblT7aOUFDCURPqnOplKOSmzsYI7TY+KH9aUYJONvRagdiejucEFRVvwFPl8JdpQpK5PyN1W5Rd3SSztY4NtyWxbdu2ddelVGSgojiRWFqKtkULBI2G8ovur/l3Fk8nsAAC7rm2YDAQ9v6cajuwAGHvz1FUAguu7eDU9ZqG7gqZzdakaMSIEbXuntaU5O7evZthw4ZhMplYvHhxjTu6rqLX6xk/fjzvvfcea9euZfz48bUKOuXk5PD6687t+gUHB/PBBx/YH7dp0waAjIwMh+fbjtvOs8eq1dD8Fl9s+oEWi8iFq0WUmSyUlTe8FKq3Rlr1crehsITDEeqc6mVE9IHT9Rec8zRaQWS89nveNz8jdyjViIlsTUigT90nqqgogMsFZaxJPcfuM1coLCsnwEfHlaK6NTlcJb58LO01WUQpeX699RG5IwDcmMSqeDctZ86k/FK2fQfRfOkSvnffTfmlS2BpuJBSQ1jwuGcTWIACYwEZBRkN3o0VjUYuvDHN4XMX3pimuJ1YZwgNtfYK17RDdPbsWQBatWplP9aqVSvS09M5f/48HTt2rPYam2BRRcLDwzl27Bhvvvkm3bp1cyrGw4cP88gjj1BUVERiYiLjx4936vX15a9//SsJCQl8+umnjBgxgi+++ILGjRszYsSIaucWFhayfPlyp67ftm3bSkmszSbo0KFDmEymagrF+/btA6j152WxiJzJLaKw1H2Tb4BQ4rZrSYpCVpFVbiC6j4GtCYoSd3pEu1txSWzvds2IG3q73GGoqNRJqclM/MbDJKVlYDK7v/+1JsowMNY4nTjdCmK025RZ7XTsO2gh/9+xZxRyVLwOU/ZltMFBBPwp4gNQ+ttvkiSweX5gquWd+LevLWg99AHiq7uurmZLZC2ia9+zIxXiitRkv+Mt9OvXD6BGexnbcdt5YO1fBVi3bl218zdt2lStlBiwe6x+9dVXTsWXnp7OkCFDuHLlCrNmzWLKlClOvd4Z2rVrx5AhQ9i1axdvvfUWBQUFjB49Gj+/6sqCERERiKLo1JetpLrieF26dKGkpIRvv/222hhJSUmAVQyoJjLzS9wu9uQ1SooVUYBBu8oNSGALuHuk3FFUIkhQjj2TXivw7D1tWD7hHnz1WrnDUVGplVKTmbFL9rB6z3lJE1gbZRj4e/lE7iv7iDmmWK6KCqseSt8hdwRAA5JYjUaDTqfj+PHjAGi12np/6XTqBrCSsPXD5q9dhwg06n2PpOM3KYFrtdwL9zph9Yn1RCJbZi4j0BBof1xgLCCrKMvp69Rko3Nr2t5a7Xe8idjYWFq0aEFycjILFy6s9NyCBQtITU0lPDycYcOG2Y/bLGkSExM5evR6acyVK1eYNs3xjvWkSZMICQnh3XffZenSpdWEiYqKilixYkWl0trs7GweeOABMjMzee2114iLi6vX9zRr1iwEQWDcuHH1Or8iNrXj+fPnA9UFndzN1KlTAZg2bRrZ2dctYr788ku+/vpr2rVrV2PptMls4Wqx+3eIdlvc3//rcRRg0O4IdU69AXg4Adqqu/wVaeynY/LgTuyccT+zh9+pJrAqXkH8xsMeE29yhhwa87H5SRaVK6N8145CdCVcnvnatGmDIAj2srbWrVurColeSsV+2KKtW2XpJA9yrFdjx5bIurs3VhRFREQCDYEUGAvQa/QE+wXX/cKK16ghgbWVDtdkv+NtpcX+/v6sXLmSoUOHMmnSJBYuXEjnzp35448/2L9/P/7+/qxataqSvUzfvn2ZPHky8+fPp3v37gwePBg/Pz82b95MmzZtiIqKquYV27RpUzZs2MDjjz/OhAkTiI+P54477sDHx4dz585x9OhRioqK2L9/v12YatKkSZw8eZJGjRqRk5PjMCmt2mcKYPmz0qBqeW59GDp0KGFhYVy4cIFevXpx9913O30NZ5gwYQLfffcdGzZs4LbbbuP+++8nJyeHbdu24evry+eff17j93G1yFijSnFD8BolRRuGQEUYtDtCnVNvAPR+MDoJvnvd6keM9Ds4FckVb5F1fID8knIuXStTe2BVvIbsglKS0hzrT0hNMPk8rd1CP80BuzijIlCIroTLSWzVcreqj1W8h6r9sHjgZre+XG0ETSvYT+UEQnCB9f+eSmQLjYUEGAJo6tuUYL9gDFrnEsus2bNr9YGtKZHNmj2bVvXcMVQK999/P6mpqfzrX/9i8+bNHDhwgODgYEaPHs2bb77JrbfeWu01iYmJ3HrrrXz00Uds2rSJoKAgYmNjmT17do07h3369OHgwYMkJiby7bffsnnzZrRaLaGhoTz22GMMHz6c22+/3o9x9epVAIqLi2vsP63aZwrw+++/A/Dcc885/bPQarX079+f1atXOxR0cjcajYZ169bx4YcfsmTJEr755hv8/f0ZNmwYb7/9diUfXpO5sipxWblnkkyvUVK0EdpdEQbtjlDn1BsEvR8IWuROYAG+Ndeu8C4VSWnnmfpAZzWRVfEK1qbKU0JcER+MxOmWE6PdrsxFYoXoSgiiJ5bn4EAIjwAAnUVJREFUVTyG7Ub18OHDLl/DmHGB3MWLaDlzpj3RqqufUwry/aBxBZ2Y3yPg/ac0vPq1WMkv9sfuAosfqn9Jkl7Q8/f2f6d94/YYWhgQaljKCjQEuiTsVNGeqDYbnYo/Y31oKG1WrMAQHubUWCruw2KxEBQURM+ePe3etM5QXFxMaGgoZrOZzMxMuw2OnFgsYp3+sKJowXwlkxPZhby1JRdjA9vefTCy3JCgbCVFGwNmwsAZLr/cHZ+/KsrBI7/Pgkswr6vsAk9mUaB32ceKsdh548FbeWlgdXE/FRWl8dzi3SSfqNnCz9Mofk7V6GHqEbe05TT0M1gVdrrJsCVceau/qNSbadst1P6pQCsVFW+zKyawqZ0E3ovVYjRoSBymIbWTNfHMbgxfR3nmbetqP6whPIw2K1bQ5Nlnai0Rtv2Mmzz7jJrAKoD9+/eTl5fH22+/7dLr//Of/5Cfn8/YsWMVk8CeyS3iiodKh2vCpqS4qnwQRlHh/W6nfgGTlyoqq3gH+1fInsACbLTcq5gEFiDldK7cIaio1AtPecDWlzjdcqI0R+UsiqwdBelKuFxOvH379gYN3L9//wa9XsU1Kva/OurN9OvUkcI/n5cCR3uiB2/zI/Fxo71k2Ky1+sSO22Th6ygNl5t4pmbRlX5YG4bwsHqVBgsGg9eVEN+oREZGOp3s5ebmMn36dLKysvj+++8JDAxk5syZHorQOTyhPlxfbEqKieUjiNVu4T7NYXpr/kCvtDKojD3wwwwY+qHckVRDnVNvENJ/lTsCAE5ZWtX6vK3XrrfmKAFCCYWiHymWLqw1D/RI8it3YqCiUl8CfOQTygshjxitdS5QZHtO276K0pVw+TcVHR3dINEJs1lhNzc3CVX7X22JbNj7c7jwxjQKtzXsRqq+iDhOYP2jowmb8QzmbS9XOm7WOldC7Az+en8MWoNL/bAqNxcFBQUsXrwYg8FAjx49mDt3LmFh8u+oe0p92FlsSoofm59khX42/bUH5Q6pOvtXwsD/U8xKsg11Tr1BUIhqZy/NcXDwlqit166/9iCTdetJMg8gvnwMZbhvPpQzMVBRcYbe7ZrJVk4cq92qzB5YAH0jeGalonQlXP5UGTNmTLUJNzc3l2+++QZBEOjevTtt2rQB4Ny5c/z222+Iosijjz5KUFBQw6JWcZmaRIZOPf4E5RcuSBdHDcctca/y6i+jJYsDwGg2EhoQqiawKnVi83xVGp5SH24Iuy1dlJnEWkywbwX0f13uSCqhzqk3CApR7QwQqpfN16fXziCYGanbTHvNRcYap7stkY1qr75HVbyD2F6t+fCXE7KIO/VWah8sgKkYvhhlVWDXK8Mj3uUkdtmyZZUeX7x4kaioKB544AH+/e9/07lz50rPHz9+nFdffZXff/+9mqWGirSYsi+jDQ4iIDqawq1bASRNYGsj9YVnGeNXxlf3eq5suComi4mckhxCA6TtB1ZRcRdKLNVTtP1O+g7FJbHqnHqDENEHTm+ROwoKxeo3mRV77Wrb9BdFiNIcJU63gr+XN9z/Wq8ViO3ZusHXUVGRguaBvsREhrN6z3nJx3a0+KQozu5QVEuO2xRyZsyYgdls5n//+1+1yRagc+fOfPnll5jNZqZPn+6uYVWcxCbslL92HSIQEB0td0iVuONYKQ/8JjJrpZmQPGlWwWxqxGXlZWQWZpJRkGH/v9FslCQGFZWGYJF5EzaYfF7SfsUK/Wy+NvwfWw1TWGuIpwDrjbTCNonh0iEwlcodRa2oc6qX0n2MVb1TZlIsXSo9dqbXzvZ8jHYbweQ3OJaYyNaqvY6KVxE3tCu92zWTfFxHi0+KY/9KKMyWOwrAjUnsjz/+SL9+/fD1rblW2s/Pj379+vHjjz+6a1gVJ6ko7FS0dSvm4mLHJ+rk7V8JuQZP7mqg90c9aaRvxNXSq5zKP8XV0qvkl+Xb/5+en64msiqKRy4DdB+MvKv7lJ0+L/OGfi39tQfppjlDhOYS7TSXCBKs/YGKE6gougyfP6VopWJ1TvVSAlvA3SNlDUHU6PmSgZWOudJrZxDMxGobtqvcu10z4obeXveJKioKwlevZfmEe3j2njbotdJNYLurLD4pEltLjgJwWxJ77do1cnLqboTOycmhoKDAXcOqOEnLmTMJGDTI/rhkzx7HJ5ZLW55Y7kCzqWmhiNYNPQlm0Tpxi6Lo0H++8E8hjoo9hbb/20qNVVSUjFOiKaKI+OcfQnkD1ols/XUjdVuUWTJcF7ayKIWizqlezMMJVhVPmRC6j2Jg5B2Vjrnaa9dQr8rlE+7BV69w6y0VFQf46rXMHn4nO2fczxsP3kq/TsE0a+TZKou15mjlW9WBtSVHAbgtib3jjjvYtm0bycnJNZ6zY8cOtm7dyh133FHjOSqexSbs5K+wMmKdg3vgnifhhS0NF5WwYCHXmEuZuQyL0bm79kBDIC39WzY4BhUVT9LU31BvZVvRVEqpyUJOsZmG1Doo3suuPiioLKoq6pzqxej9rOInkeOkLy3+0wLj/4vuUElA0dVeu4b06PnoNGoCq+L1hAT68NLAjnz2fG92zryfXm2bemysyzQhyWy1S1P03KoQFXa31YxOnz6dESNG8OCDDzJ27FhGjBhBmzZtEASBs2fPsm7dOlasWIHFYlH7dxSA0qr7HGHy0TFi1kr+syO2wdc6UnSENo3a4HvNWpqnMWjq/CHoNXpCfENABIsoTWmziooraAVo4qvlSnEtpe+iiGgqxVKUT16xkQPZZS6Pp3gvu/qiUKViUOdUr0fvZxU/Gfh/1vdY+g7I2AtGD+6adx8Nj8wFvS9f/3aiUuGRq712DenR6xp6i8uvVVFRIr56LZ9N7M2AOVu4VOD6HFob8eVjaa/JanAVhEdRiAq725LYp556igULFvDGG2/w//7f/2PhwoWVnhdFEYPBQGJiIk899ZS7hlVxEtFotNrr/KlKrFSKDfDl9J5knfzALdfbmbeTDn4dAGhsbIyP1qfWnSsBASNG/rj4R53nqqgoAVEE0WzGUsN6i4hIqclCXrGRPy6Xse2s68JGivaycxYFKhWDOqfeMAQ0t76/+r8O29+Hze94biyNzu7huPvMlUpPuWp5VVUgyhm6hTd2+bUqKkrFV68ltKmfx5LYMgyMNU4nTreCGO02Zc61EfK1S1TEreo9L7/8MkOHDmXx4sX8+uuvZGZmIooioaGh9O3bl/Hjx9OuXTt3DqniJFmzZ9v9YQECBvSncNt2GSOqTr4fvPSiBqNpL2SB1iwybpOFr6Nct90ptZTy2cXPuK/JfdzufztBhpo963SCjnLxek9wM59mtApo5dK4KipSIQig12rILCjlarHRYSlSTrGZA9nWBLa03PVaJUV72TmLQsqiHKHOqTcY3cfA1gRrBYAnSFsOmb9h9m1C74xWHKU/OVgTSVcsr4yilrXmgXWfWAOnLhe5/FoVFSXjlA6FC5Rh4O/lE0ksH0GsdgvPaTfRSnO1TnssSdDooccYmYOw4vbfQtu2bXn77bfdfVkVNxH0/ESKtm3HlJlJQHS0I50j2RF8DPzleyNrBwhcCYSpGyz0OiHS/bSZ+JHaBiWym69sZvOVzQgI6IS63/79w/uT0DsBvVZ+ywQVlfrQBbhcUMb6fRnsOXOForJyDpzPw2ShQT2wFVG8l50zKKQsqibUOfUGwqZcvG+5hwYQ4eJvaIGXgb/6rCXJPID48jH2XruRui318okVBEgyD7Anwa5w5OI1Sk1mtS9W5Yajd7tmJJ/wvOhnDo352Pwki82PsNyQoIwS4+6jrBUmCkBeHxUVyTGEh9FmxQpyFy7ElJ1NkQLLim/JMzIgD7pkmMlqBt3Srceb58PjKRYWP9TwCVFExCTWvhoe3Tqa9we8b09gTWYTCakJjL9jPGEBYQ2OQUXFU7Ro7MeLAzvx4p+bKB1mfuu2BBa8xMuuviikLErlJuHhBMg9ZVXH9jAGwcxI3Wbaay4y1ji93r12gmAtI44vb9huS26hkbFL9qgKxSo3HLG9WjNv03HcYKBRLyqWGD+j3SybrZ5NOE4puE2dWMV70DcPoTwnp1ICGxAdjX///vIF5YDm164nsACpnQSWPSDNWzbIN4iEvgmVEtip26ay5tgaJvwwgQuFFySJQ0WloWQXlLp9ovUKL7v6IGgUUxalcpMgsXKxKFptcuJ0K+w3wqvKB9Vo42EUtawqH8RY43TKaLg7wO4zV4jfeKTB11FRkZvLBWV8tPkEzy3ezaTP0vAzSLsPaCsxPiTK0UKisX5mjV5v77tXAmoSe5NhF3aq2Bf7Z1lx0XZl9cZWJLWTQOIwDWaJTKdzS3OZvmM6JrPJnsBuPb8VgMyiTJYeWipJHCoqrmKbcId/vNPt1/YaL7u6uHOEYsqiVG4ibMrFU49Aq7s8OpStbDhGu41g8u03wveVfcQcUyzbzXeyz9KR7eY7mWOK5b6yj/h7+US3JLA21qSe44+L19x2PRUVKSk1mZn55QHue+8XPvjpOMkncth/Lo/CsvK6X+wBromNpB1Q5wuTD1g/sxSUwIJaTnzTUU3YyZbAKrCs2IbUCayNree3MnnrZAQEtmVssx+Pbh3N9F6qpYWKMik1mYnfeJiktAxMHqp1cqa/TrEEtIChC+SOQuVmRhThkjS7lAbBTKx2Cx+bnwSu99rZHnsSiwiPLEjm6V5tiBt6u1parOI1lJrMjF2yp5rat5wESq1J0aIrNGkt7Zj1RE1ibzIqCTsNGoQ2OIj8teuqnecfHY0AFG7dirZlS8w5OVAu/arTwdt8SXzcJHkCa2N7RuXd6ejW0SQOSFSFnlQUiZQTrld42dVEQEt4abfiVpVVbnAKs62iTum/WlWxi3I8p1TsgCjNUUmSVkdYRFi95xynLxeqPbIqXkP8xsOKSmBDyON24ay0g/oo1+9ZTWJvMuzCTosX0XLmTEzZlyne8SumzEwEX1/E0lICBg0ifP48AC6+8w6mc+cpzsqSJd6lfY2YtcqoelcTWBWlI/WEe9YSQi/hD7SCEnXOHSBorCXEQxeoCayKdJhK4Pvp8NsqSZPWqgQKxbKNbcPWIzt7+J1yh6KiUivZBaWs23te7jAqMdZvO3pRYt9YBYsfKiM7UJEUQ3gYreLiEAzWnhe/yEgax46g3YYNNHn2GcLnz0MwGKxfCBSnpMgW64x1FrRmkcYGeU3TqyawJrOJd1LeUQWeVBRDdkEpSWkZkozlg5HlhgSe1m2vM4F15FcrKT63QPuBMOgteO0YDF+oJrAq0mEqgc9jrDuwMiawAO2ELHwwyhoDQFLaeS4XlMkdhopKraxNPU+5O2X93UBf3TFpBxR0ihY/VJPYmxhjxgXOjRnDtY0bMefkYggLrZTcikYjxvNVVqE00r5lmudbfWILS/IkHbcqCf1UpWIVZbM29bzHemCrEqdbTpTmaJ0JqiL6ZZu1hzFfQf/XVREnFen5frokdjr1oYlQRJxuhdxhYDKLrFXYDpeKSlWk8IF1Fn+hVNoBg9oret5Uk9ibmNzFizBlZgJQuHkzGZOnIBqvr9JmzZ5N8a5dlV9kkWZZqmL3ba8TIlM3WHdkPYmemsuEpyerSsUqykaqCTeEPGK01l7xuhJU2RNYgIu/w8ZXwSTx5K+iUnDJWkKsIGK02+jMeV7SfsUK/Wy+NPyDFfrZvKj9imDyJYsj5XSuZGOpqLjCuSvyl99Xxcdf4v7UK2esvfwKRU1ib2JazpxJwKBB9sdVE9lmY8Yg+MpTdmcUILvC36oUiWyzRs1qfM6mVDxl6xR7AguqUrGK/Njk//dI1Asbq92KQZC4J6dBiJC2DD5/ylraqaIiFftXyF5CXBWDYOY7nxm8oV9Lf+1BemhO0l97kGn6tez0eZl3dYskKTmWy55ERaW+lJiUNc/ptQJBtw+q+0R3YjHBPvmrN2pCTWJvYgSDgfD58xwmspaiIrLf/wCxVJ7di0YiNL8GZRWkx3qdEBm3yXM7wZeKL9X6/PaM7dWsdlShJxU5sakRr95zHqlaT3t7oxoxWEs6f5ghdxQqNxPpv8odgUN0NfSxGwQzI3WbWW5I8HgiG+Cj6oqqKBs/hSlox0S2xr/ns4DEJU7pymiHcISaxN7k1JTIHovsWclPVi58yiH7T02nYgPsuN3zf7z9wvoxIHxArecMCB+gJrAqsiOH/H+A1B517mT/SkWXRqncYBgL5Y7AaUTRasXj6d7ZqPZBHr2+ikpDadOskdwh2OndrhlxD7WDr14EyZas/0TBn2NqEqviMJFVCgci4I3xAtmNoZER/vaNSEieZ/+ABUFgTr85RLeOrvGckEYhagKrIitSqhFXpFD0k3xMt6Hw0iiVG4jCbKsPrJdh62OP0W7zWI+sXisQ27O1R66touIuurdpIul4weTzhvYLthimcMDneQ74PM8WwxTeDfyS5bER+P78d3lE4i4fgxVPwvYPFLcIrCaxKoA1kQ17f47cYVTC794oUv4WzcvfWlWKAULyRR5P8ay41PaM7byR/AZNfZo6fL5lo5ZMvHOiR2NQUakLKdWIK7Lb0kXyMd2KgkujVG4ATCXw9d8g8Xa4ekbuaFzGIJiJ1W7xyLVbN21EoK9aTqyibKQq2vXBSILuv+z2eZGX9F/TTnOJW4QSbhFKaKe5xEhTEj4f3ma16ZKDsmtwegts/qf1c01BQolqEqsCWO10LrwxTe4w7GiaNaP1vHlM2WjthbWR2klg2QOef9tuz9jOhpMbHD4X0TiC5n7KlRxXufG5XFDGOhl2YQHWmqMxisrqFXIKBZdGqXg5CvKEdQdRHup/P51TxNgleyhVmHCOigpY59ePNp9gdarnbaB8MLLCMLtOz3UlCP0D1s81BQklqkmsCqLRSMbkKYrogbVhuXKFk48+RtGWrfZjqZ0EEodpMGs99+fcslHLOs9JuZjC1G1TMZm9/yZFxbuwKRHf994vnM2VR/7/Mk1IMvcHqNMnVpEYAuSOQOVGRUGesO7Ak/3vu89cIX7jEY9dX0XFWSrOrx/8dJy8Ys/f48XpltNbc8zj47gdhQglqknsTY6jBDZg0CBuTdtLo3vvlTEysORe95FL7STw4eMC4zZZPNoTm1PiuIepb2hfWvm3sj/een6rmsiqSEpFJWI5yogrEl8+lhRLF2X4wDpLRF+5I1C5EVGgJ2xD8XT/e1LaeS4XlHl0DBWV+iDH/Gr1XN9W94lKRQFCiWoSexNTUwLb/I3XufTBBxjCwmSM7jq2BPbVr0Ue3C8S/7mZl7821+kZqzWLPP+D2amkt1ys7l3XL6wfGo2Gi0UX8dVe981VE1kVKZFDibgmyjAw1jidVeWDMHlTabFGDz3GyB2Fyo2IAj1hG0qKh/vfTWaRtXs9X7KpolIXcsyvVs91z2q8eBQFCCWqSexNTNbs2Q4T2HPjxpO3+gtM2dkEDOgvY4RW/vOoNYG19cYGF0D/wyJTN1hqTGS1ZuvzD+4XiVvlXCJbkX5h/RAEge0Z2wEoNZcSGhBqf37r+a0kpCa4dG0VlfqSXVDKOoXd7JVh4D/lT3BJbCJ3KPWn+ygIUPvZVTyAQj1hXcUoallrHujxcf677RTPLd7Nf7acVHdlVWRBLqV/r/Vcr4jMQolqEnsTE/T8RPSh1oQsYNAgwufPI+fjTyi/dAmAou3bEUXw79dPzjD5fx9ZKok72eh1wnEia0tgba9pno/LisYioj2BBYhuHc2GoRvs9juh/qGMv2O8S9dWUakvK1POUq6gBVsfjLyr+5TtPpMJ1+TW/QIl0LYvPKQuOKl4iBtEMMzW555kHkAOjT0+XkFpOckncnj/x2Pc994vzPzyoCr4pCIpUir9B5PPS9qvWKGfTQ/NcUnG9Cgyf+6pGuc3MYbwMNqsWEHu4kW0nDkTwWBA8POtdE7R9u1omjWTKUIrPtUrfO3YElmb4FPVBBYapmi848L1Vabo1tEkDkhEr9WTOCCRhNQExt8xnrAAZZRdq9y4rJFAJbG++GBkuSHBY8qlbkejt+7APpQAet+6z1dRcYUbRDBMEKxlxPHl0pfdm8wiq/ec4/TlQpZPuAdfvRe1Kqh4LTtPeX4h1gcjcbrlxGi3YxBuoEUamT/31J3YmxxDeBit4uIQDAYAWr35Jv7R0ZXOsVxRRh+ejb0drV82bImsj9FxAusOReN7Wt5jT2AB9Fo9b0a9qSawKh4nu6CUS9eUU2YXp1tOlOaowpWJBWjbBwa9BVOPwNAP1QRWxbNE9JE7Ardw0dKUscbplGGQLQZVuVhFSo5lFXj0+raF35G6LTdWAguyCyWqSaxKJQSDgdYLPsS/v/y9sI4o1cHn0QJzh2tJ7XQ9Me11QuSzuWaPJLAA5wuUsxOmcnOxNvU8SskXrWqK1vJ6RSsTdx8F47+D/q+rPbAq0tB9jHXX38v5zPyArAmsDVW5WEUKsgtKuVJk9OgY3rHw6wIKEEpUk1iVaggGA7qWLeQOwyG+5TB7hUizAkgcpqmUyFbE3Z6yF4su8thXj5F+Ld0t11NRqS9KUSQGm5qiF6wkZx2SXfpf5SYjsAXcPVLuKBqEKMLP5ki5wwBU5WIV93K5oIyPNp/gucW7Gfbxr3Yxsf9sPuHRRWKvWfh1BQUIJapJrIpDgv86CcHPsx5xzlBR08bPaBVqMmsFFjzu+C284HH3JbA2MgszeXrj01wovODW66qo1EZhWS1N4RLjNWqKF3+DuV1g46tgKpU7GpWbhYcTrAJiXoogwGBtmtxh2Ek57SWicSqKpdRkZuaXB7jvvV/44KfjJJ/IYf+5PLuY2PJd5zw6vtcs/DqLQoQS1SRWxSGG8DDCP/kENMpYOqr4Rs1uDN/cYxVx+tvXjiVb//Z1zfY7DaG4vJilh5baH5vMJt5JeUdNbFU8RoCPcvT3AoQSuUOoP2I5pC2Dz58CkxfFreK96P1gdBJEjvPa0mIlCbYpaQFPxfsoNZkZu2QPq/dIpz5cFa9Z+K0vGr318230ekXoTCjn7khFUYhGI1eWLAGLsor4jVqrZc5bqy1kNYNu6Y7Pq6pa7C76h/dneq/pgDWBnbptKlvPbyU5I5klDy1RhZ5U3E7vds1IPpEjdxgAFIrKqc6oN2d3wA8zrOJOKiqeRu9nfa8N/D/Yt8Lqo2gshNyTUHJV7ujqREkLVUpawFPxPuI3Hpa9HUdJf08uERgKjcOsKsQRfa09sArSmVB3YlWqIRqNZPztVYq2b6/7ZIkx/FmV0fxazQmsjZp8ZBuCKIrM3jObs/ln7QksQGZRZqUdWhUVdxHbqzV6N5fGu8puSxe5Q3CN/SvVHlkVaQlobhUWG/MVTPwZ7n1J7ojqhZIWqqLaB8kdgoqXkl1QSlJahtxhKOrvyWna9oW/7bd+fo35SpFCiWoSq1IJWwJbuHVr5ScM8qsVuoK7E9nkC8msO76OpzY+ZU9gweoha9uhVVFxJ80DfYmJDJc7DADWmqMxil7o3WgxWXfFVFTkwkvUi1MUslCl1wrE9mwtdxgqXsraVPlKiCvitQu/oT0UUzJcG2oSq1KJrHf+VS2B1YWG4n//IHkCcgFHPrLjNjnunXWVMvN16X9frS+v9XzN7iGrouJu4oZ2pXe7ZnKHwWWakGRWpv1WnaTvkDsClZsZL1AvNopa1poHyh0GADGRrQkJ9JE7DBUvRe4yYhtrzdGYvG3hV9DByDWKT2BBTWJVqmAuKa702D86mo4/fE/rhAQa3XuvTFHVn98jYO5wbSUf2ezG8HWU597qpeZSPj/yuceur6Liq9eyfMI9PHtPG9lLi+PLx5In+ssag0sYC+WOQOVmR+Hqxd+Y7yWHxnKHQe92zYgbervcYah4MUoQBfPByBTdOjS4dxPF4/QYrbiy4ZpQk1iVSjR/dTK65tY3r390NK0XfIhgMCAYDLT5f/8lYJCyd2SzmwiYtdavxGEafuwuED9Sy+Umnrvx792qt1pKrOJxfPVaZg+/k82vRdO6qXx9NmUYOCO2lG18lzEEyB2Bys1ORfViQXm3X+mivP7wGgGevacNyyfcg6/ey3avVBSF3KJgPhhZbkhgpG4LWkH+suZ606StIqxz6ovyPkVVZMUQHkbbVato8uwz9gTWhmAwED5/HrowZSrw7u0IS4Zcf0ubtQKLH/JsAgtw7to5sktU0RgVafh460nOX5VX8dAkeqFqaIRyd8BUbiJs6sUv7FBcIttTc1zW8YP8fYgberuawKo0GLnbb+J0y4nSHEX0ovwVgKYRXlFGbENZn6AqisAQHkaruLhKCawNwWCgzaJPwUdZvSppHaxlxO6006kvF4suqsrEKpKQXVDKur3yKi76YOQO4YysMTiNRm+1BlBRUQotukL35+SOohJy24FcLixj7JI9lJrMssah4v3IqeofQh4xWqu7h6AMY4H6Yyqu+xwFoSaxKk5jCAuj0d13yR2GYqjoHaui4knWpp6nXEbvZh+MrDL8i0Yao2wxuMRdT3tNj4/KTYTCemSVYAey+8wV4jcekTsMFS9HTlX/WO1WDIKXLsR4WduNmsSq1Igx4wIX4+MRjZVvWLPe+RfFu/fIFJVjIk/Ba1+a3eoJW18EvG2pTcWbuFxQxkebT/Dc4t38d9spWWOJ0y0nUnNC1hhcIvc0mLzcdF7lxqNij6wC7HeUYq+TlHaeywVldZ+oolILcUO70qNNE8nH7a05KvmYbsPL2m7UJFbFIcaMC5wbM4a81V+QMXmKPZEVjUaM58/LHJ1jep6UJ5HdlrGNqdumYjKbJB1X5cam1GRm5pcHuO+9X/jgp+Mkn8ihsEy+1d2KJVJex7md8MMMuaNQUamOrUd26hGIngmBrUCGhVEl2euYzCJr9yrzPkPFe/DVa+nXKVjyceUuy3cZL2y7UZNYFYfkLl6EKTMTgMLNm8mYPAVLUREZk6dQvGuXzNFd52oVp4+eJ2HqBkuNiazWLPL8D2ZC8tyb6G49v5WEVO9RdFNRNqUmM2OX7GH1HmUYtoOXl0gB7F8JhaoAm4pC8QmEM8lQcBGQ/m9eKfY6NlJO58odgsoNwL5zeZKPqYSyfJfoPsrr2m7UJFbFIS1nzqxkp1O4eTMnH3yIws2b7ce0wdKvcFWlaREUVtGf6nVCZNym6r5cWrPI1A0WHtwvErfKvYmsTtAx/o7xbrueys1N/MbDijFrt+HVJVIAFhPsWyF3FCoqjvl+OpzdIdvwctvrVGX/uTyGffwrzy3ezX+2nFTLi1WcwtaG89v5PMnH3q2QsnynaNvXq6x1bKhJrIpDbHY6FRNZc06O/f/a4OBKj9FL1M+jr27tEVBFY8aogx96YN9x1ZpFJn5Xzsy1ZnqdsCauzfPh8RT3GVCvemQVYQHKtB5S8S6yC0pJSpNXgdgRXlsiVZF0+ZIEFZUaKbgEv62SNYT7NMoSUyosK2f/uTyST+Tw/o/HuO+9X5j55UFVuVilVqq24RSUlksew1pzNEbRW2yiBGtP/uj1XmWtY0NNYlVqxFEia6NSAgtgkqgf1FT3B5KhHGatEnlwv8islWZmrjEz5Hfoln79nNROAssecN/bf/3J9W67lsrNzdpU5ZQQV8RrS6QqYiyUOwIVlersX2GtFJCR3pqjzNF9gg/KVB43mUVW7zmnWvCo1IhS2nAu04Qkc38A5fvEtrnP2pPvhQksqEmsSh3UlsiCMkqKHdH4z02jkGvQ7Wzl51I7CSQO07jNU7ZVo1Y8c+szPPm/J0m7lOaWa6rcvCitjNiGV5ZIVcXL7AO8jZ07d/LII4/QrFkzAgICuOeee1i+fLnT11m2bBmCINT49cwzz3ggepkozLb2a8uMIECsLpnPDP9SbCILqgWPSs0oqQ0nvnwsKZYuyveJ7ej43t5bqF6bqaJSBcFgIOz9ORyL7FntuQ7fbOTEoPsRi73DIHlvR9yawAKEBobyzLfPUGYu4/kfn2fxg4vpFtyNd/e8S2l5KS93f1ktNVapN4Vl0pc/1YevzPfxmm4tGqVPyrXhZfYB3sSGDRsYMWIEFouF/v37ExwczC+//MK4ceP4/fffSUxMdPqad911F3fffXe1471793ZDxDJjKrH2wf62SvZd2IrcozlBnG4Ffy+fKHcoNZKUdp6pD3QmJNBH7lBUFILS2nDKMDDWOJ043QpitVvQCQrckvVCNeKqqEmsSp2IRiMX3pjm8LkLM2Zi6NiRsgMHJI7KefZ2hLnDtW5NYIFKu69m0czbu94mPDCc7RlWO5I9WXtY8fAKNZFVqRcBPsr8WH5J9z/vTmBvgAlbqVy9epXx48djNptZv349w4cPB+DSpUv07duXefPmMXToUAYOdM7C5cknn2TWrFkeiFhmTCXweYysQk61MUK7lcTyEYpSK66IzYLnpYEd5Q5FRSEosQ2nDAN/L59Ie+EiUVoFCiN6oRpxVdRyYpVaEY1GMiZPqaRKXJGirVu9IoEF+PAJ9yewjmjq09SewAJkF2ez+OBi3kl5hwuFFzw+vor82JQRn1u822mFzd7tmkkQoXN4tUesjRtgwlYqixYtIj8/nyeeeMKewAK0aNGCOXPmALi0E3vDIrMScV3oBQux2i1yh1ErqgWPSkWUUkbsCIOgnEoLO03aeqUacVXUJFalRhwlsAGDBnFr2t4ae2SVzBvrzTX6x7qTtOzKfbHdgrtxqfgSa46tYcIPE9RE9gamqjJi8okcpxU27+/SXHE7nl7vEeul9gHewjfffANATExMteceffRRfH19+fnnnyktLZU6NOWhACXi+hClcEutvGIFJgYqsqHUNhxQoiiiBsZ967ViThW56ZNYVYjCMTUlsOHz56Hx969V7EmpdEuHmWulSWQrciDngH1nNrMok6WHlko6voo01EcZsTaFTVsC/PhHv2JRVlWU93rEavRebR/gLRz4sxqnR48e1Z4zGAzccccdlJaWcuzYMaeum5aWxhtvvMGkSZOIi4tj27ZtbolXVhSgRFwflG6pda1U+T9DFelQahsOQJqlk9whVCZyDDRpLXcUbkG5v3UJUIUoaiZr9myHCaxgMADXVYtrKzVWIt3SYeoGi9vFnepLdOtopveaLvm4Kp7HGWVEm8Lm7OF3AtcTYKWWRCn9hhafW+Del+BcitVGxxBgFXHqMUYtIfYw165dIy8vD4Dw8HCH54SHh7N3717OnTvHXXfdVe9rf/PNN/ZdXoC3336bAQMGsGbNGlq0aFHv63Tt2tXh8VOnTtGhQ4d6X8ctpP8q7XguorzdIxWVmundrhnJJ3LqPlFifDDSX3tQ7jCuc4NVJd20SawqRFE7Qc9PpGjbdkyZmdUSWBs21eITQx7Ekus9/Sm9ToiyJLK9W/UmcUAieq1esjFVpMEVZcSKCptKsgZwRLGocBXQ4E4QPUPuKG5KCguve+82atTI4Tn+/v7Vzq2NVq1aMWvWLJ544gnat29PSUkJe/bsYdq0aWzbto1HH32U3bt3o9VqG/4NSI2XeBWnKNxSy9/HC3/3Kh4jtldrPvzlhOLEneJ0y4nUnEAUkd9uJ3KcNYG9gaqSbtokti4hiuHDh5OYmOh0EnujYAgPo82KFeQuXkTLmTOrJbBwXbXYWxLYvEbQ5E8noF4nRMZtsrD4Iekmwt+zfyezMJO2jdvaj5nMJhJSExh/x3jCAsKqPVbxDlxRRrQpbI7oGa4oawBHBHrDTqyKy8TExHDo0CGnXrNixQruueceRLHu9319zqnIgw8+yIMPPmh/fMstt9gXlSMjI0lLS2PNmjWMHDmyXtc7fPiww+M17dB6FFe9irU+YK5bGM4dmEQNa83Kvve5cLWEUpMZX72azKpA80BfYiLDWb3nvNyh2KkoiCh7AqvRwcD/u6ESWLiJe2JVIYq6MYSH0SouzmECC9VLjpXOqVZWmx2A7MbwdZS0b/9ScykTfpyAyWzt5TGZTUzdNtUu+JR+Lb3SY1UAyntwdRc15XSuIq0BKhJCHrcLZ+UOo3ZU/9cGkZ6ezrFjx5z6Kv7TGzwwMNB+neIa/MJtxwMCXEzg/iQgIIC//e1vAPz4448NupZsRPRx7XW3hLo3jlpYZ45WrL2OjfyScuI3HpE7DBUFETe0q6LU/RUliGgph30r5I7C7dy0SawqRNFwgp6fiD5Uuom1oUSegiv+8GN3gfiRWi43kX5pLLskm//vl/+PYmMxU7dNZev5rYBV8GnSpkmVHqsCUN6Dq8qIhWXl7Dyl7EqGWO1W9EqZiB2h+r82mL179yKKolNf0dHRgHWXtHFja8KTkeG4osB2vE2bNg2OtVMnq0jKxYsXG3wtWeg+xvqedQaNHro+4Zl4qlAq6ogv946/p3V7z9fLtkzl5qCgtJyo9s1oeYsydhsVJ4iYrlxbL1e5KcuJVSEK92ArOT43aRKmU6fkDschZTo41VrP7WdMZDeG/90nT/Jakd0Xd/Pg+gfJM+bZjwX5BpFZmGl/rApAeReuKiP66bUcyMhzbzBuJJh8RmgVvhCn+r/Kzl133cX27dvZt28ft99+e6XnTCYThw4dwsfHh1tvvbXBY129ehVo+K6ubAS2gLtHwj4nXBC6j4LeL8LO/3hc2Xh3yAgsF31AwdUhNsotIs8vT2XtpHvVsuKbgMsFZaxJPcfuM1coLCsnwEdHVPsgHr8rlI+3niQpLUNRVU2KE0T0kn58Z7gpd2I9KUSxf/9+8vPzycrK4uuvv+a2226zC1GYzQrezXARQ3gYrT/6CHyUKfySHq7n3eFm++5rThNlvOWrJrC5pdd346JbR5M4IBGT2cST/3uStEtpDq6goiRcLWEqLCunsEx5nws+GHlX9ym7fF4mQnNJ7nBqxrfJDaW06K08+uijACQlJVV77ptvvqG0tJT7778fX9+G75CsX78egMjIyAZfSzYeTrCqhNYHm5poYAvoOsyzcQkaBox7m50z7ueNB2+lX6dg7mrdGK3SjKsrcCAj36FlmcqNQ13+6/3nbKnV2k4uFKfw7Wo/voJRxh29C8TExHDbbbc59bVnzx6gfiITrghRxMXFcffdd3PLLbfQokULhg4dSmpqKp07d7YLUdSXw4cPO/xSyi5sRa6sWA5lyizpuTXdxOT/WVj2gAZdWCgiIlqzyPM/mAnJU8YHXk0J7CMbHuFU3ime//F5NZFVOLG9WqN3Uulap4Ejmdc8FJHr+GBkuSGBkbotyi4jBgjqcMMJVXgjEydO5JZbbuF///sfX375pf14dnY206ZNA2Dq1KnVXmebmy9cqNz/v2DBgmoLyCaTifj4eNatW4efnx/jxo1z/zciFXo/GJ1kVQutqbTYkcdxs/aejetua1VDSKAPLw3syGfP9+b2VrdgVppxdRV2n7nC8I93qqXFNyD18V9X6rtzt9IUvm9A7QivLSe2CVE4Q01CFLfcUl3Z0t1CFC+//DI//vhjvdUUvYmg5ydSuHUb5QrtUep5Ev71bRM2jA8l+1omUzdY6HVCpPtps2y9sY6omsDakluzaOafKf/kqye+kjdAlRpxRRnx9tDGHMjI92BUrjFb9ylRmqPKsASoC1WVWBE0a9aMJUuWEBsbS0xMDAMGDCA4OJiff/6ZvLw8/va3v3H//fdXe51tDjeZKpfIvvrqq8yYMYPbb7+dtm3bUlpaym+//UZmZia+vr58/vnnhIV5uXq73g+GfmhVDN23wtqvVpfH8fndnounzX3wyAeVDrliHSYXRy5e455//cyInq15+4muannxDYLS7edqY605mld165Uh7nSDakd4bRK7d+9el19rE6LIz88nIyOjWg8PqEIUzqBvHoIhIkKxSSxA+8O5RH+SywDBmtQCNM+Hx1OktdmpjYR+CdUSWLCWG696eJWMkanUh7ihXTl9uaheE27vds0UV6Lng5H3dJ/ypPZXwAsSWLghV5a9laeeeort27fzzjvvkJKSgtFopEuXLrz00kuMHz/eqWv94x//YNeuXfzxxx8cOXIEURQJDw9n0qRJTJkyxS29tYohoDn0f936VRumErjknA1SvdDooPtoh/6RSldOr4oIrN17njOXC/lsYm81kfVyvGkRxRGXacK35iiG6X6VO5QbVjvCa5PYhqIKUbiPrNmzKd61S+4w6iSyivZUaieBZQ8op6J+ypYpHLt6rFoC+92w72hkcNy7raIcfPValk+4h/iNR0hKc3zzp9cKxES2Jm7o7Tz7aYoMUTrGVkIcpTQ1xdq4QVeWvZk+ffrw/fff1/v8mtp24uPj3RXSjYGpBD6PgaLL7r2uoIFJydCi+kI+uG4dJjepZ68Sv/EIs4ffKXcoKg3A2xZRHJEu1l/Q1WPY+upvQJRzBy8xqhCF+wh6fiI6L7LaAWsCmzhMg9nJPkZPsvPizkoJrAYNi4YsUhNYL8JXr2X28DsrCaN0b9OEfp2CeePBW9k5435mD78TX73WZUVjdxNMPmsNb9tLiL2GG3RlWUWlGt9Ph7MesMcQLXDsuxqfdtU6TAms23tO7ZH1crx1EaUi92pk9DJ21Fd/g3HTJrGqEIX7MISH4df97mrH/fv3p3PKLrRBQdIHVQtKTGAdYcHC69tf50LhhbpPVlEUFYVRNrzYh8+e781LAzsSEmhV8b5cUEaZySJrjDYF4p0+L3GX5jTgJSXEcEOvLKuoVOL/b+/O45uq0v+Bf27WbiylZWtL2UXEDZFNEUrVUUdBRERFLSrMOCPKpiiMX6zMOFZE2fTrT0ccpY4LCIrId2Rc2EWUTUV0oCwF2lJaCoXuSZPz++OSNmmWptlubvJ5v14O09zk5kna5vS555znqTgF/BjE7SQeekeGy4U2X9Rb5aXFNqUVdXhtQx4eePt73PH6t3jg7e/xvxsPMdENY2erTUqH4Ld0KcCrJ7yR2APInAvM/FXedx+hCSwQxcuJWYgicITJBMuZsw63xQ8fjrRFC1H4xJOwlJW5eWTo/XiRHgvHWMM+gQXkpcSHyw/j4fUP4583/xOpCZH58xNNas0WzP3sF6zeXQAlC34aYcIHhr9jgCZPuSB8odHLM7Au9u8RRaS9ucHtDeuhd+Tg7u2wNe908J47yHYcKcOkYd0x7/P9LnuIbs07jcVfH2zY4sE9tOGlola9KwFs4pToFZvYtfk99hEiamdigcZCFDfddBN+/PFH/Pvf/0bPnj3xz3/+E0uWLGnRuZ599lkMGzYMJSUl+OKLL7BhwwbExcXhkUcewY8//oixY8cG6VUor+meWG1SEtIWLcSp+S+hctMm5QJz4ZVR6khggcbWO0VVRXjnl3cUjob8VWu24IG3v8fHu5RPYP/PMEddCaykBVqnAmmDgDZdgLrwa01EFBT5QS4K46F3pC+tw8LJ+Rpzs+1ZzBaBD384zl6zFFC2lU6tUR36J/dwYSrSRO1MrA0LUfgvadJknFvzGUSNfMXJUlaGwllPQYptMlOi1QIWZQeJqWutqlhKbC+jSwaeHvi00mGQn+Z9vh878882f8cgss3A9tKEbyVxl4QFOF8o/3f8W2DTi5yRpegQ7D9IPVT49qV1WDg5db4Wxee9Wy78/dEzLAalsNKKOqzYeRzfHz2Dyrp6lFWqc6m34oUSPVyYijRRn8RSYGgSEmCpaVw2UblhA+KGDoW2fXtYSkshJSdDnFZ+WdLAPIGZn6onkdVAg+eHPg+9Vq90KOSHkopafLxL+VYB2brl6pqBdcdqBna/C5w+BNy/Su65SRSJgvkHqasK35UlwJ7l8gywqRLPa/S4I64KVrMJBsmMShGLHda+WGkZidNoE7zYAsDbBNZm1e4TmHnjRQ21Cyg0as0Wt0u+1Shbt1zZXutR1HouqpcTU2CUvb0MllLnzevV330HY69eaDPuTqBSueUNpa2Bn7s1fm1LZLUq+LC0worb196OapMCS1IoYFbuPIF6JdcQA2iPcozTblE0hoA7tg1YP1vpKIiCp9u1wTu3Rgfs/KecuJprgLVTgYWXABueB45sBAp2Qnt8OwZZf8IQ7W+4SnMIw7X78JR+JbYbH8MLumUwQv3Fd2zMFuFQDIqCr9ZsaXbJt5r0wXGM124CoFACG2Wt55jEkt86zZmDhMxMl8eqv/sO51athqitDXFUjdqfB4rbyFWJbdSUyJbVlmHCFxOUDoP8EA6tAsZrN8EgReCer73vy3+EE0Wi/lnyH6bBUF8DbM4BXr4YWNBLnoH1soiUQbJggm4DlhvmR1Qiu+NI+BSijAbzPt8fFuOjv2x7YP9tnAOdpODflVHWeo5JLPlNMhiQtniR20RWaSVtgHdu0mLhHRqnRPbBr5Rtc+KJ5sKvpwQJf7r8TwpHQ/4Ih36Lg5XanxNsVjOwJ1fpKIiCo1VH4MpgX8S0+LT3VghgiOY3ZOsi5/fvxxPlbMETIvI2G/XPfNv2wE7QbYRWyQQ2ClvPcU8sBYQtkS2YPgOVGzYoHU4DiwQ8f3fj/teFd2gw81MrBuYJlLQB1g4J3+s4Vlihk3SoF/VYtHsRLmt/GdvshLmmhSkSjDoM6ZEEg1b5n7MEJUr9h0r+tqhpKUBR6IbngP2fhl1VbttyyXHazVhYf1fY75H1RkVtPfYeLwfAFjzB9v6OY6gP33kEAEAyzuFu7UYM1vyGBKnG5Z5wxffAQgJSrgQkDbD8Nnkffbdh8rLiCJ+VZRJLAWNLZE9MnYaqMGitYwWQcydw606B/xtoxa07Bb4YAKSUCpxqA/z9Hi1K27r/xNFa5JnatUM0Hu8XLBIk1At5Bs/WZud/hvwPzBYz5u+cj4cufYhJbZjwVJgiXPosVooILn4URS0FKAp9/VzYJbD2DJIFE7RfY6nlTqVDCThbC54jpZVY/vAgJrIBtGJn+M7CGmFCtm45xmm3OG3DGa7dh+m61VhlGYH/rb+9odaEMgksAAigaK/jTUc2RkUVfyaxFHCSCI9LaxoAU/4NJFYLZOwTMNYDN+wFbEPQ1M8s+NuDsaiRnPcAaS2iYca2/xEL5k3wnPAGg0BjMpSSkIL7L7kfZosZMzfPxKYTm7C1YCv+efM/mcgqzFaYItz39Xxv7Yvh2n1KhxEcUdRSgKJMxSngxw+UjqJZD+vW403LKNTBoHQoQRFNLXjcrSgaf3WXgFVuLqnwvv1RqHnTIse2J/wO7dbwrTURBVX8lV/jRhFDmEwomDoNlZvDpwJq4oWivsYLWxLtr6H2KgZmflTjVNzJPoEFgA7ngNE7lEvM9Ro9iiqL8Mf//BGPfvMoNp3YBKBxdpaUpZbCFCstGTCJCJ1FiKKWAhRl9uZ6XWxJSW2lqojaG+vKqt0nfNojW1pRh9c25OGBt78P6/22tWYL5nzyM6558Ru8/OVBbM07jb3Hy7E17zQW/OcArnnxG8z5ZB9qzf4nbe/vOBaAiIPDfnlwc2JdTIKEnQiu4s+ZWAqIhgQ2DJYRt8QV+XDoG9s0gQXkqsbv3qjc9R7zhT9gTlafxMnqkw23Z3TJwNMDn1YqLIJ8NXnVbuX7v3qjFG2xyjIcE3QbFdy7EwRR1lKAokz+t0pH4LVI2hvritkiMO6N7WgXb/BqdrK5bSbhtN/WmxVFgVpaXWu24N3t+T5GGlz2regiZowE5Cr+I5+JuD2ynImlgCh+/u9OCWx8Rgb67N4VtlWLbWztdowm1wmsLcENJxldMrBwxELotUFqvUBeWblTXb3t5tVPxA5r38ganKOspQBFGRXt9zZIFozXblQ6jKA6Vlbt1eykN/1PbUnhxH/+EJDZTX+0ZEWRbWl1S9jPRl/74gacq1G+Yr8rEduKLkKr+DOJJb8JkwmmE44b9OMzMtBl6RJo4uPl9jsZGcoE56WBeQLvvWJRRQI7Im0EkmOTUVLD3phKKq2ow8cqmYW1d8za3qtlUqoQhS0FKMqobL+3p32EkchdIhrspDCQfFlR5O3SaldLlMuqwrevcMS2ogPkKv4Rhkks+a04JwfV333X8LUtgZUMcoEHyWCAtkN7pcLzSbgmsNelXoeDZw9i1cFVeHj9wyisLFQ6pKhTa7Zg+oq9GPzC1zhWVq10OF5LQSm+MszC3botKpqJdROoRg8MeBC4f3XEVl0kAgB0u1bpCFokolt5eWCfiAYzKQwGX1YUmS0CK5vp8erNbHS4ieifXxWt6vAWk1jyW9KkydCnpAAAEjIzHRLYhvs89DAkY2Cq2gXSnh6ub186OvwSWADYX7YfJ6vkfbEs7BR65dUmXPfSRqzZWwSrOsZkpKIUnxn+B98apyFdU6p0OC2Tfg2QORfoMRJIGyj/mzkXmPkrMGoJE1iKfP2z5Is2KtEZZ2BE+M60BZMtEQ1WUhgsvhYm3HGkzONxtRQ9tBfRrehUtqrDG0xiyW+GtFSk5+ai7b33IG3xIqcEVphMKFmwAKKu8Spj3NCh6L52LTQKztDu7gl0P+X62KzVFqeqxeHgTG3jgJASn8LCTiFg28sz4a0duPr5r8OuoqQ7RpgwX/cGthqn4QrNERXNvtrplQkMfxLIWgNM/lr+d/iT3ANL0aNVR+DKCUpH4bXOmjP4yjALqVDZBbMAsCWiwUoKg6Wyzrf9qZ4ep6aih/a+t/ZVOoTgicAq/qxOTAFhSEtF5+xsl8eKc3JQuWFDw9cJmZlIW7wIpsIiWE8r86H9SxegRzGQWOX6+OX5wJyVFuSM14bljGxSTBI+Hf0pCzsFga1H3vbDZThQXIEzVSaE3+UMz7zpcxf2WHWYSHbLfKDssNwqQwXSNaXYYpyOFZaRmFefFbG9Y115a+sRmOp9a8nnazLprwSjb6mAp8d9sOO4apYQ21tpycA03erIK+4UoeMpZ2Ip6JouN05bvAgAcPzBBwGrMv1XLznhmMCejXdeWnx5vtx+JxxnZPUaPUpq3Rd2KqwsxPM7nofZ4rmHmdlixvM7nnfYW+vPY9WsaQGK7YfLUKbCBBZoWZ+7sMWqw0QyfSxw/yp5H7ikjrkHrSQwQbcByw3zo2p5cXm1GdUm3xIgX5NJfw3u3s6nxw3pkeTy9lqzBf/89qg/ISnG1ooOgLrHz6YidDxlEktB13S5MQAcf+RPqD/lZi1vCNj/4J+NB06k6HDVEef72drvhFsiW1xdjLvW3oX88/lOxworC/Hw+oex4sAKzNw8020yaraYMXPzTKw4sKKhSJQ/j1UzNRagcCci+tyx6jCRI32svA/8id+AEbOBVilwW/gsTAghVyvO1kVea49gcJcUBtv4gV2gb+GKM71Wwviru7g8Nu/z/Thfq8yscjLOYYp2DXL1OfjE8Cxy9Tl4VLsGyTjn9TkirhVdBI+nTGIpJGzLjSWDwamasZLK44AjnYDL8xo/cHf1kvfL2gzME3jwK2VmjD2ptdRi+sbpTre/88s7KKoqAgBsOrHJZTJqS0I3ndgEoLFIlD+PDXf2ferueP1bPPD29/jfjYdQWlGnygIU7qi6zx2rDhN5ltABGDlHTmafPCgXOus+AohLVjoyJ7YkYJx2c4uSiGjkKSkMtg6tYjBuQFqLHjNuQBe0b+VcrFOpvbBGmPCC7i1sNz6GWfqVGK7dh6s0hzBcuw9P6Vdiu/ExvKBb5tWqgIT4BPyjy0vY33kshKTiNCkKxlN1rEuhiJI0aTIqv9mA+hLl+5y2rQYGHG78uk4HvD9Cwn2bG2fjyloBa4eE5wfZnEFznG57euDTOFV9qiHJtCWjC0cshF6rd0pCASCjS0ZDkSh/HhuOas0WzPt8P1btLnCaZd2adxqLvjqgmkrD3hiq2a90CN7TxwEd+8lVE7sNk/fsROCSJ6KgSOggFzobOgX417iw3TNrkCwYr92I1y1jlA4lbCXFG7Fy1wmMv9p1chhs2aP64UhplVcXc9MSY3G8rAp3vP4tEow6DOmR1BC3L5WZ/eVNDQiDZMEE3Qb00JzERNPTHvdpn681Y/49w9EefYCFawGE3ySGE0kDpA8FLKaoGk8lISJq1XfE69evHwBg/34V/aHahKmgEMcmTJCTWL0eMHveexlqZW21SCpvnMna0hd4bYz76z1aizxTu3aIBqVtQ7v+JLNLJtrHtccDfR/Ae7+9h6cHPu022UxJSMHikYsxfcP0htlWQE5CbUkq4DzTarvP/Ovm4+mtTzvdbv/YcGNbJhwps6zNaY1K7Db+GXq1zMT+6Vug06VKR+G1SPj8pUYR8/1cOxXYs1zpKDzaYrkMWWbni67kSK+VMG5AF2SPugQxem1DocHvj55BZV29U9IYSPIF31+xarfrRFRz4c8bVxd9bXEfL6vCt4dDW7DzBd1bmKDbCCE8b6GxHf+gPhN/qZ/s8ZyzbuqDKdpPgQ3PBzjaIBnwoLzdQGX8/QxmEqsykTDonpw3D+UffqR0GC6dT9CgdaXjVbddvYBXxrquUqy1yHtmB+YJlLQB5k3QhjSR1UgaWIUVBq0BJoupIakEgJwfcpB3Ng8/lv7o9vH295+/cz4euvQhpCakukxk3T023BJY+0H/16LzKKuKjqIiRpiw1TgNHSQVLdtr2xWY8r28308FIuHzlxpFxPez4hSwqB9gDa+LwU3ttfbAHSaVJARhYGDXRHRrH481ewtdJpRNk91AKq2owzvfHsX/7TuJM1UmWK0CtfVWWLxYspRg1KKyLnQXUdujHN8aH2/RFhqT0OKautdwGm3c3ue63sl4T58DHNkYiDCDq+sw1S4Z9vczODzXSFJE6zRnDnSpqY436pVPhCxaySmBBYCrD7muUmyfwAJAh3PA6B2hXXZiFfLzmSxyorbpxCZM3zQdMzbNwMcHP8bPp392+9iU+JSGBLZpkSa9Vo+FIxYio0uGy8eGYwLbtLrw1rzTUZPAAsBLujfVlcACQPkxYP1spaMgUq+9uWGfwAJAD6k4qqoU+2vnsbP4eJfzFhgbs0Xgwx+OY+I/f0CtOXBJY63ZgoVfHcBbW4/gWFk1KmrrUWWyeJXAAghpAgv4VgPCtrzdk8q6esBU6UdkISJpgDH/T5UJbCAwiaWQkwwGpC97C1KM3S9dGCwptk9Sd/WS/7NpWqW4aQILADt7S3j3RuV/pbYUbMHmgs0AGpNcVwZ3HoyiyiK3RZr0Wj3mX+e6ot386+aHXQIbKdWFfdEe5RilDY9iaS22932gUvn98USqlP+t0hF4pY1UHTFViiUABp3yYz0AfH/0DOZ9/mtAzqXGcXSwj73Qbftn3VUzTtFVyHtLw52wAvtWKh2FYsLjt5CijrF7d3T/9BPoLvSPDSdn44HFt2vwylgtdvZuXBpsS2SNJtcJ7MI7NC6XHIerTw99ijs/v9Np3+zMq2aisLIQ876bh6e2POXysXesvQP55/PDpldsJFUX9sVD2i8a9iupjtUM7ImMP26JQk4Ns0UX3KXiKsWtYnS4rncyZt3UBz88cwOmZvZq/kEhsmr3CZRW1Pl9HjWOowlSjU+PayVVe6xmvPTkfUBteWCDDZb88CzoFgpMYkkxhtRUxPQOn4HAJrEKmLZWTlAX3qFxSmTfe8XSbAKrtQhMWm9B+/LQXM1MivGtv1ydpXHgi9HGoKiyCFM3TcWDXzyIVQdXNczoNlVUWYRxa8fhT1//SfFesUqV9A8nv9f+oHQI/oniQZjIL2qYLbpA78UyznDVq0MC3ps0GFNG9kL7VkafeqsGi9kisHLXCb/OodZxtFL4Vk+hu1SMCbqNbpcia0U9ULQX4d6LGYCqLmQFGpNYUkzx839H5eYtSofh0sA8gT9u0OG2i8Zg+bhElLjZ/+8ugZ35qRU37RXI/iA0iWxZrX/VADvHd0atpRYA8P3J71FcXexwfETaCGy7e5tDslxnqcMPxXLyVFRVhGX7lrk8d2FlIZ7f8TyqTdUeZ219ndVVoqR/uGknnVc6BP9E8SBM5Jdu1yodQYt4aoMSzgxaxz+XfemtGkw7jvj3N4Bax9HvrX19elxbqQrNlbUVdv8b1lR0ISvQmMSSIoTJBNMJ/64cBpMAcPvkl1BRfRYTV51FBzcroP73VsllAqtksSdf9GrbC8PThrs9bhVW/OXbv3hMlkurS2G2OO5tLqwsxEPrH8KKAyswfOVwt7O2tmrIvszqqm35UzBIahhoPYniQZjIL/2zAE341CdoTk+pUJVLinfmn8GcT/Y5FFHKHtUPg7u3UzCqRpV19X49Xq3j6EpLBkyiZdWZbcmrp3Y8gCrmYGXdhikdgWKYxJIiinNyUP1d+BaikQAcnT0TVy/d4LB0uKlFb1lhMMlJqsFkxZI3nZcah0Oxp+ZsLdyKjnEdkRLveo/y1sKt2FLgedZ8c8FmzNw8syGRNVvMmPL1FJysOgmgcemyffEo2/3cFZfyhr+DdySob+EgHnaieBAm8kurjsCVE5SOwmupmjPYbnwML+iWqapasVUAH/5wHNe/shkT3tqBO17/Fn/I3YWhPZMwpn+q4kuLD56qwIgFGzFiwUaMenUbHnj7e/zvxkNe75VV6zhairZYZZEvwDc7s+pl8qoqGj1wVZbSUShGp3QAFJ3aZU1E+epPAJPzIKZNTobl9GkFonKUVG5BUrnn+yRWAa++YcWTDwu8/E+BxKrGY2oq9tQ+tj0mXTYJEy+ZiLGfj21o2dNSm05swqPfPIqUhBSUVpfi8LnDTveJ0cZg5lVysvvst89jV0Eeis37Go7r6y6F9uztKK2o86qZe4KRH2MViEUiqpq/YziK8kGYyG+3zAfKDgPH1LG33CBZMEG3AT00JzHR9DTqYFA6JK8VltegsLyxmNDWvNPQaYAbL+mE/+wvhpedaAKuqs6Cqrpqh9u25p3G4q8PetVPVs3j6Lz6ieihKW52qbokyYlsRCWx/e8DEjooHYViwn+KiCKOMJlQsmCBywQWgJzAGpQb1Dwt/rWNTxa7D8HEKuDtVx0T2JI2UE0Ca9MhtgN0Wh3aGNw3APfGjpM78EneJ9hauNXl8VpLLR7fMBPXvPMA1h39xCGBNVf0xZkj9+DNzccx+IWv8dSqn5vtgRcuy7mUVA4VL8eN8kGYyG/6WOD+VcCAB1WztFgIeX9sJLTdqbcCX/yiXALribf9ZNU8jtbBgImmp/FBfabbpcUmocVPlh6RlcB2HQbc7LoNYrRQ76UXUq3inBxUbtjg+U5uEtxQ8HRlx/b5pxVAnQ4wuliBczYemDlZXQlsaU0ppm+ajo5xHVFaUxqU59Br9DBb5aXGP5z6Fmjyt5a5oi9qC+6D7WPJKoCVu07gaGkl3ps8uOEqcmlFHVbsPI7vj56Rl0CF4R8OoVYuWikdgm84CBMFhj4WGLUEGPmM3LIqfxtQuBuoC8+ib7Zk4m7tRrxbfxMOoouyAUU4Wz/ZnLGXuTw+fmAXLPkmT5XFnQA5kf1L/WQsrL8L47UbMUTzGxKkGlSKWOyw9sVKy0gs1L+udJiBodHLF39vng/oY5SORlGciaWQS5o0GfoL/WHjMzKQkJGhbEA+OBcLzJjk+tiMP2hgMqjvV2tLwRYUVBRAH4Qr+e1i2uGLMV8j3uJ6ADVXXOyQwNrbeews5n3+K2rNFsz55GcMzfkaL395EFvzTmPv8XLsPVEe8HjVxtcKjYrR6OVZo/tXR/0gTBRQCR2A4U8CWWuA9n2UjqZZWkng38bZqtsjq0ae+smGW7VlX51GG7xuGYMs8xyMNf0VWeY5eN0yBqfRxueesmEjsTuQOReY+at8wYpjJ5NYCj1DWirSc3PR9t570GXpEqQtXYKEzEylw2qRNjXA62+6Pjbl/wS0Kr2a+d3J7xpmSwOpW+tuePnLQyivdv1HSm3hvfC0MOTDH45j5IKN+PCHE6gP/2LPIedLhUZFJPbgIEwUCpUlQJXytSW8oZMEJug2YLlhPhPZIGqun2z2qH4Y2C0xhBGFlq89ZcNGYjf5AhW33zRgEkuKMKSlonN2NiSDAZLBgLTFi1SXyLozME9us6OWRLa1oXXQn2NPyR6sr5wEfasDLo/HpH4EwHN1xJPnvauyGI1K0RbrLEMANF+hUVGJXTkIEwWTuQZYOxVYeAlw9qjS0XgtkvbIhjNP/WRj9Fp0S44LYTShpboVS02xn7oTJrEUFiSDAakLXlI6DJ9NflyDnb0b98AOzBNY8qalof2OO1qLwKT1FrQvVy7zOG9Sfs+UvtVviEl7H80lsuTMCBNe0L2FUdodAMK88iIHYaLgMdcA/xoH7FkOBGFFTTDZPrfGaTerso+sWpx1sxoKAEoqarFmb1EIowkdCfKKJYsI5wGyGeyn7oRJLIUFYTKh4IknlQ7DZ39eDywZLTkksh3Oye133CWyWos8Y3vTXoHsD5RNZMMBE9mWM8KE5Yb5mKDbCL3kuYpzWOAgTBQ8XzytmjY77hgkC8ZrNyodRsSqqHU/vq7ceUK1hZ2aIwD0TVFpAUQb9lN3wiSWFCdMJpyYOg1VmzYpHYrPBuRZMW2twJLREkrsOtQkVgELlzkvLbYlsAPz5Ns7nANG74i+zZ7miothrri44Wsmst5JxjlM0a7BJsMMDNH8Ft5LiO11GaJ0BESRqeIU8OMHSkcREM31+yTfHT9TjRELNuKl9f91KvL0/dEzCkUVGqMs30ArqWWwbIL91F1iEkuKcpfAJowYjvhwrlpsMKD31i3QDR/acNPAPIFpawVmPSThbHzjXTucg8Me2aYJLADs7C3h3Ruj69fRak5AbcE9qC24H+aKxr0q+la/wdhpnYKRhR9b0vov/d+xy/gn/GB8FLP0K9FZcxZAmC8htnf4G3nJIxEF1t5c1S0hdkf1VWTDmBDAsbJqvL7p8IVe7D+h1mxBrdmC/UWRvYz7ouq9SofgO/ZTd4l9YkkxwmRCwfQZzglsRgbSli4BABRMn9F8T9lQ02jQ+5uvcSrWhGmZBbjnpNSQkA7ME3js/yRM/4OEBe8IdLgwJtiKPS0drcHUtc4J7MI71NVXNhA0+krEpK1AbcF9cnudtPehb/UbrKa2MJUNVzo8xSXjHO7TfoV7tBvRUToLTST8eBT8AKyfLVcmJqLAyf9W6QgCJhEVyNXnOPX5PI02zT+YvCb3Yi/A4ZJKQJJwpioyLoK4081yTOkQfMN+6m5JQqhmIRoB6NevHwBg//79Ckfiv5Pz5qH8w48cbrMlsJLBACB8lxonZGYid0IHfHR4FbQWgSc+seDqQ43Ht/ST8P9u1TjNuDYVjQmstT4GGl1tw9fmir4XesQCxk7rYCobDmFup1R4ijPChGzdctyl3aKOfa4tpdHLLXZUeFU5kj5/KcK+n8tuAAp2Kh1F0JiEFqssIzCvPgt1MCgdDqlMe5Tjh5gpkBCGKY+kA4SLLVQavTwDe/P8iG1H5+9nMGdiSTFJkyajavMWmIuKEDd0KAxduqDT/zzTkMDahGN6V7lhAx5MGocOx2Kw8spqGJtcwLzkuEC7CmDhHe4T2WhMYAGg6tAsxKSugr6VvO9J3+o3iE7rUFc8BnXFY5QNLsCScQ53azdisOY3r2YVbIWaInpPmNUM7MmVW+0QUWBEeNE0g2TBBN0G9NGcwATTM0xkqUUm6deHZwILANdOBQzxQP42uYK/IUEu4nRVliov9oYSk1gKKVNBIcreXoZOc+bAkJaK9Nzchq/tk1dhMuHk88/DfKIA1d99p2DEbmg0MB06jGF7KzFoD2BochEtuUIu1PT2zVosHa3Be684z6h9OEKKugQWAGJSV6G24G4gbUXELh+2zaaO026Bocls6nDtPkzXrXY5q5CtW95QqEk1+1x9kb+NSSxRIHW7FjgS+VV9B2jysM7wF9xmeoGJLDXLNhbfq92kdCjuFe0FstZwTPRBdFWSIUWZCgpxPCsL5R9+hILpMyBMJhjSUtE5O9spgS2YPgPnVn7skMBqEhOVCNs1qxW1e+UiAU0TWADY1Qt490YNtBaBqWtdVx2e/bFz1eJoIFcgXoHagrthOjsE1cf/GFHLh+3b3jRNYG1sswrLDfNhhNy3rz3KMU67BUCEJ7AA+8USBVr/LHn5YRTorSnCB4a/N3x2ErliPxaH7SwswPHQD0xiKWTK3l4Gc5HcSLtyw4aGRNaeLYFtWswpITMTvb/+CnFDh0ItXFUhtte0anEki9HGID3m6oavbYlsXfFtEZXAAo6zqZ4IIbeS2GSYiUe1a/CQdr3bpDfiRPjSR6KQa9URuHKC0lGEzABNHrJ1uUqHQWFsniFXHouVDqQ5HA99xiSWQqbTnDlIyMxs+LppIusqgY0bOhRtx49H2uJF0MTHo8trr4bXjKwbVx8CXn3DdQJr337HVrU40hPZWkstzlVrnHrCxvd8GTEpH0DSR0Z/upbMptqOd9acwVP6lfiTbm2QowsjbNpOFHjDnkB4VpEIjnHazUhGZLeFoZZLMOqQPTIJd+u2AlDBbwTHQ58xiaWQkQwGpC1e5DKRtVZVOSWwCZmZSH/zDXT+6zxIBoNcqfixx2E9e1aJ8Ju1q5f8n01ilev7PP4nDXb2bvxYtU9ktRaBSestaF8eeUltlTgKSI4z7xpDOfRtfkZc1zciIpEdr93k82xqRLTQ8QabthMFxy8rgfCfdwoYg2TBeG3k7wOmlumf3hYPxW6FpIa+yS0ZDytLgC0LgNwxcjXy3DHAlpfl26MUk1gKKXeJ7IEBVzslsGmLFzXsla07ehSHbvl9eBZ5uqA8Dlh8uwYlHlrZSQLI+tqK3EzJKZF96D8WzPzUipv2CmR/EFmJbGtDa9RrS6FPOOLyuEZ/HoakLSGOKvAGR3JV4UBh03ai4IigXrHeiuhK7uSTIT2S1PO74M14aK4B1k4FFl4CbHheLuBWsFP+d8Pf5Ns/nwaYaz2fJwIxiaWQc5XI2muawJoKCnF03DjUFxaGMswWu+FnYPpnVrw01v2U2oDDwO9+AuZ+6JjIlrQGOp1Dw/LjDufk6saR4rzpvMfj5soeqCu+LUTRBE+CVKN0COGNTduJgicKC8TwM5fs6bUSxl/dRR2/C96Mh+Ya4F/jgD3L5fZ0rljNwO53gX/dKd8/ijCJJUVIBgNSF7zk8ljqgpccqhWXvb0Moqo6VKH55epDwLMfNT+D2uE8cPt3VpyNE9jaFyhuB1ye33h8Z28J794YPb+eWsMZSHrPia4aVAuj0iGEKQkY8CBw/+qIbdpOpLgoLBBTKWKdbmsdw+6R0WrcgC5o38oY3r8LGr334+EXTwPHtnl33mPbgPWz/Q5PTaLnr2QKK8JkQuGsp1weK5z1lEPV4qYFocJday8vhNlmZQflOSewC+/QRFUPWY2hPCKWE7eRXGyEJqDzFcCoJUxgiYKp27VKRxByrVHl0GpnTP9UPHxtdwUjIqV0SYxF9qhL5C/C5XchsTvQYySQNlD+N3MuMPNX78bDilPAjx+07Pn2vh9Ve2SZxFLIuWujY9O0arFt1labnBzKMIPOVvjJaNdnNhoTWACor+yl+uXE7VGOftIxpcMIT7HhX1GcSPWiqFeszZXaIw39tu/on4rFd1+JCUPSoVfZGJqMc5iiXYNcfQ4+MTyLXH0OHtWuibrqy/5819LbxSFGr5W/6J8FSGGQ4sQnA1lrgMlfy/8Of9L7mhB7c90vIXbHagb2RE/rqTD4DlM0cZXAJmRmos/uXR7b75x6+WVYTp8OebyhtKsXPCawkVy5WGMoVf1y4oe0X0AjBe5701yfWVVhCwGi4IuyXrFAY7/t/223AjljLwMAdGgVg3ED0hSOzDtGmPCC7i1sNz6GWfqVGK7dh6s0hzBcuw9P6Vdiu/ExvKBb5jDbHKk6t4nB1qdHIsGobdHjbBcAZpXMbqzau/c9IL59cAJtCX+WNftanCrfy+XHEYBJLIWMuwTW1gPWXfsdYTIhadJk6FNSACDiZmRtPOU/WovwuXJx+3I5+W2uF62SSbLGcA6xactV3Wbn99ofAnq+5vrMqgZb6hCFzi3z5YIxUcL2OXl97deIqStruD17VD8M7BreK0CMMGG5YT4m6Da6bc1mkCyYoNvQMNscybonxyMtMQ6Xp7X16v5NLwBcad7rWLW38lRwA/aGPxdwfS1OpYaiVgHCJJZCpjgnx2MbHXftd4pzcmBIS0V6bi7a3nsPeq77POSxh8KAw8ATnzgnm7YE1pfKxe3L5aT3pr2NvWhd8SdJDgSrOQHamFOIS/+HKhNZI0xIkSJ7pYDP2FKHKHT0scD9q+TCMVG0tFhqsowyRq9Ft/bxCkbUvGzdcgzR/NbsqhvbbHO2LrKXiR4/U41aswXX9Exq9r7eXABQnL8XcH2dxQ3nolYBxiSWQsZ+NrVpAmvTNJHVp6QgadJkAIAhLRWd5sxB0ew5oQ08hK4+5JjINk1ggZZVLh69w4oOF7bUDMxzncj6kyQHghCARi9fOVRjgSfbYBq2A6mS2FKHKPT0sXLhmJm/yoVkmhaW+fN3jbenDoB/OxHDSP42uajNlgUwvTMaE36eFLZ7S9ujHOO08ljX3Kob2/Fx2s1h9zoCqeBsDeZ9/ivGD+zS7J5mby8AKMrfC7i+FqeKou07khBh/SNATfTr1w8AsH//foUj8Y2poBBlby9DpzlznBJYe8JkQnFODpImTYYhLbXhtoKp01C5aVOIog2ukjbAE5O1mPaZBVcfcjy2qxew5HYtpq51TmBbUvjJXRL83kgJt+4UeC9TwrS1wu1zaC0CD35lxdohGpS2Df4fOuaKvqgtuA+AelokvKB7CxN0GyFEBC0B9pdGLw/gN8+PqIrEav/8JUf8fl6QeztwZJPSUfgvvj1QU+6yGI5JaLHKMgLz6rNQB/d/e4TKFO0azNKvbPHjXjKPx+uWMYEPKEzotRK2z74eC786gA9/OOHyPu1Rjm+Nj4f3heOuw5xb6FSWyP1e87+Vl/waEuSE86os18luxSlgUb+WFXfS6OWLVypZ/eTvZzCTWJWJ1kG3uYrGamPSAn94XEJNrBZai8ATnzgnsk35WrnYVSJbp5OrIp+Nb6yS3PQ57B9X0gaYN0Eb1ERWWAwwn78SprIMCHO7oD1PIKliMA0VQzyQNsjzoKxy0fr5G6n4/byg+BfgjTBpSRJkO6x9MdH0tOKJbK4+B8O1+1r8uC2Wy5BljtzVaAAw66Y+mDSsOyb+8wd8f9R5e5GvFwBCwtUFXHON3O/1xw9cJ6SeLvqunSonvt4a8KC8CkMl/P0M5nJiCnuRlsACgMECTP1c4A9fWNCuAnhlrBY/X+R+UPWn9Y5FKz92Z+/Gx9ra+niTwALBX2IsBFBfkwpD4g+q2hc7XruJCaxN2qCWtxAgIuV1uhRI6q10FEEXTntLEyQvG8oH6HHhzr7F0O++ux8xH96Jf/XZhj/0T3BaWjxY85tCUXrQKsV1D1hzDfCvcXIi6m5G1WoGdr8L/OtO+f72WlKoLQq37zCJpbDXtCCUNtGx4mDc0KFodfvtgF5dRSwGHAZu/FHgufct6GvtiJdG1aM8zvV9l472r3esq0TW3tl4YMloyWUCC7RsH64vhCUW+oSjANS1LzYsB1OlRNE+HKKIM+lLQGpZaxO1sW33uFu7ESlQthBfpYgN6ePClasWQ71NvwFHNkK/6Xk8c+BO/Dzg35h9Yzdc1zsZ/dPbonNsvdJhO4ppC0zd6/oC7hdPA8e8bHlzbBuwfrbjbd4UatPo5eNNly9HASaxFPbsC0LpUlNhOXu24VhCZibSFi1E9bZtgLmFTaHDRPvzwHN5l2H2OgPaVru+z9S1VnQ8Y/WrVY5FK2HpaNe/8olVwLS1AkaT6wTW11lgb2l0jVcfzRV9UVd8W9CeK5Ai9ap4i7GNDpG6xbUDugxROoqQ0EoCHxn+pmjLmu+tfX163A4fHxeOvKowbDUj9uf38KfjT+G9rMvx6aPXondap9AG2pwhf3adPFackpcQt8Te9+W9s/aaK9TWdPY3iqinegpFLVt7nbK3l6Fd1kScmDQJ5qKihgrHR+4YC0tZWfMnCmfbduLSslq3hwfmCVx+VMBYDyRVWHAmHvjsGuc9qvazqP2PWBz2sWotAlPXul8SPDBP4L1XHAeSUCSw9iymtqg79Xuo5aMp0q6K+4xtdIjUr9dI4Pi3SkcREumaUqzU/xXnEI8EqQaVIhY7rH2x0jISp9Em6M+/0pKBabrVLdqOYhJarLSMDGJUoWVfYdhTUUQBQDq2Dfh8GpDcGzibH6oQvSABVz/s+tDe3JYVZQLk++/JlWd1m0roIN/u6liU4kwsqYIhLRWds7Nh7N6toV9s2uJFAABN69YKR+c/a5njHtDdPYEHntC63Md69SHgdz8B2e87zrZ62sfqaolwc0KdwAoBaA3liEt/WzV7Yn29mh5RonAfDlFE6p8VVb1lr9AewXDtPlylOYTh2n14Sr8S242P4QXdsqDP0paiLVZZhgOAV31iAWCVZURIEuxQaFGLoQv/ip9XABueB84eDW5wLZHS3/0F3HwfLwjle7n8mJjEkvrYEloAKJg+A7V797q8n65zZ0ClCW7f40DPIqvHfawdzgO3b5ev4nrax+ruWNMkuSl/9+G2lG0gU9Oe2JWWDJhEZO8jcyuK9+EQRaRWHYErJygdhaIMkgUTdBuw3DA/6InsvPqJ2GHt61Wf2B3WvphXHzlbNnwpihiWHezOHgM2vui8BBiQ2+j4wtfHRSEmsaRaTQs+2ZOMRtSfPAmcPx/iqAIjzgxkfygw8xMLXrsVKHGTi7erAuJqrFjypsXlPlYAbve41hkkLBkt4Wy863NPXWttdv9tMJgrLlbNntiWXE2PDBKQfm3U78MhilgtqYYaoUJVxbgOBkw0PY0P6jPdXgw1CS0+qM8Mi7ZAgRQxRRFryoDNOcArfeXlzma7bWGGBN/O6evjohCTWFIt+4JPmiYVi0VdnRIh+c0+D5IADDwELPmHQAc3ufjVh4B3F1vR4VzjbfbLgB/8yn2RJq1FYNpa4dBmx97APHkGN9SJ7CWWM0iGm6DCkLdX0yPCgInAw/9mGx2iSOVNNdTwnBMLGNtn+TjtZiTjnOc7+6kOBvylfjKuqXsNL5nHY4vlMuyx9sIWy2V4yTwe19S9hr/UT46oBBaIwKKIot65TU43H3svs9K/1yQhomP+IFKwObsjU0Ehyt5eho5PPokTjz2O6u++UzqkoNvXFajTywlsU2YN8NRDEgo7yFd125cLZH9gQYdzjrOzD39pRYdygSvyGx97Nl6uUlyna9x/C4R2b2wncz3eLT6F9mZ5/8+8+qyQD97JOIe7tRsxWPOb1wU/jDAhW5eLu7UboZUi9CO167CoXzrMz9/Iwu9nMypL5CIz+dvkJY6GBPkP7MMbgGPRUQDqJfN4vG4Zo3QYqtPcOJqrz8Fw7T6lwwyOAQ/Kq5QqTgGL+rWsuJNGL69yipKLxP5+BjOJVRkOuu4Jkwknpk5D1aZNSofiNytcL5Mwa4CZf9CgIlaegXWlTgfMeliD4iT5DO3LBUbvsDb0eX3iE4tTAryzt7y0+IENAusGScjaIELeZgcABlfX4P+dKoXt+v8Oa9+QLaOSE9HlGKfd4nKvjklom02s++A4vjDOhiaSJio0ern68M3zozqBBfj5G2n4/fTRmyOAkz8qHUVIbLFchizzHKXDUA1vx9FikYiZ+tUKRBgC9ono2qnAnuXeP9aWAEcJfz+D1dHHgsgLksEAfYfIuHrlbp2/3grcsdWK/sfcP9ZYD/zPCiumPSLBopVQ2lbC2zdrGwo8uUpgbQnq2zfLty28w7EY1MA8gQe/suLtm4NbxOj7uFjM7JCMhSWnobPbl/SX+slBfV5bv7ohHvbp2Ap+9NCcxETT02iFGocrzSahhwRL5Cy0a5UCDJwk93+NkqvCROSF2uAusQ0nbaUKpUNQjZaMo7utvWESGhgk923/VMu+Tc4t84Gyw8AxLyoOs9J/i3FPLEWUpD/+Ua5KHMEyf4Xbfaw2Hc7BYT+ruxY7u3rB5QyrRSs5VEYuaQOsHRK8j4u29Y1XbDfFx2F+UmJI9yXZ96vzxFbwY53hL9hufAyz9CsbWjQM0f6GwdqDkbE31tgaeHQ7974SUVS7TMrHQt3rQa9UHAlaMo4O0OThuOgYmsCUYGuT480ec1b69xmTWIoo+g7tYejWTekwQkZ4SJgG5gnMWWlBWqlz9eKfu0n48grglbHahgRWaxGYtL6x96wtkf1PfwnzJmhR2jZ42Vm5Toukenkjboq5Hg+da6xkZZAsGK/dGLTn7oPjGK/dBMCLfnUXjvfWFLW4PYCq1J0Hvn5O6SiIKBzFREavUm9IEjBWtw0/GydjhnZl0C+oqlWL+r5eON5DUxzkqBRk3yZHHysvEZ75q1zZv8dIIG2g/C8r/fuFy4kpYgiTCQXTZ0RFcSeb5moIXZ4PLFzmuFzH1f5W+5na/kcsDUmrvMTYuyXE9ntvPe2d1Vrkpclrh2gcEuMynQ4pZjPeLC5Bar1jgjhE85vb4hruCkh8bRmAG7W73RaWsO3duVu7KXKLMflj7/vAyGc4E0tEjmITm79PhDFK9ZimX4M/69ZilSVDkaKD4SoZ57BQ/3qLL+xqEMHjrqs2OQkd5NVNw58MfTwRikksRQRbAmvfNzY+IwOiphrV3/+gYGTh5Ww8sGS01JBkaqCBZLE4LDXucA4YvaNl+1/tqyC3q7S6LQLlLlm2KdLr8Uq7RCwsOQ37hTeuyvF7KiAxXLsPs3Qrna4ID9fuw3TdanxqGYZummIM1hzw+jVGHft9PURENt2uBY4Eb3VMODNIVofaCNGcyDZXxCmqsU1OSDCJJdVzl8BKAKqiLIEV8NzBL7FKnpn92z3AqXbOCSwgz9TaKhk3ZT/b2q4CDf9/9I7GXrUD8wSe+MSCM/HAZ9fIBaWe/MSKhWMk3LcZbpPlxhnaWMxPSsT/lJ1teN5KEesQhzcFJNwtaTJIFtyt2yy/X6L5pU9RLX8bk1gictQ/C9jwdyCSZ9I8ECEsOhgsrlYw/WztDg2ASzVHm20v580YHLU0erkgIgUdk1hSveKcHJcJbKVdq52EjAwIICLa73jiTT7W4RzwyjIrfuhtRUy9Y7/Zn7oB5fGNX9sv/QXQMNva+YwFvYuAWLM887pktIR2lY0Jqu2cVx2yoHUdYKgHXnlbQGv3N48tWZaEgMYKzPrEgqsOAQMPW5CeWQnYbQ/ZYe3r8BrsC0j4koTaHscEthn2+3qIiACgVUcgPhmoKlU6EkXYFx1cWH+X2/7hgaTVSLBY/b9o0NwKpqZsq5eatpfzdwyOaP3v4zacEGFhJ1K9pEmToU9JAQAkZGZC36GDYwKbmYm0pUvQZekSJGRmAgA0ycmAJnp//A0WYNh/nRPY7ueMuPFHecmvwWTFzE+tuGmvvFR4/GZLw2zr5cfkBBaQE9dpawWWjJawq5fj8yRXyQksAIcENq+HvOTYCIG3Ck7hlZUmXHUhlnbnAd0vcQ33NQktVlpGNnzdkgIS7nDQ9ZKrfT1ERO37Nn+fCGeQLPjY8Bwe1a4JesGntMTY5u/UDNvs6QTdxhYt/7W1xVlumA8jTAEZgyMW2+SEFGdiSfUMaalIz81F2dvL0GnOHJhLSlG1bRvMRUVyArt4ESSDfPUwbfEinHz+eZhPFERNAag9PYDupzy35dl3kRElcSZckV8HQE5MX31DNDymwzngp+4SdvUSTn1mbfef/plottAUIO/L/en6OtxZWYeHzp6H2NIalYWN+28TUmvQqf+5hiu8qywjHK50j9du4v6bUOG+HiJypcdwIH+L0lEorrvmFJ7SrMRM/Wp8gWtwyNweAzR5zS7HbQm9VsLvL+2E/7f5iF+x+jN7ar+EulAkcwxuSqOXZ2Bvns8qwyHEJJYigiEtFZ2zsxv+v31Sa0tgbSynyxwTWI0GsEZgw20Av/Y2oI0hHolVZz3ez2Spw/LrNWhb1bgk2D7prTYA6/sL3LvV/TlcJbeuJFYB/b6Jw639i1Cyoy0qCxuvMCek1iDtmrOQLuS0O6x9Ma/ecW/JYO7BCQ3u6yEid/pnAZteBKz1SkcSFnSwYBS2Ak1agbpbjtsS4wZ0wUPDuuONzUfc7kJ2V6XflkD7O3tqv4R6t7V3y08QSdp2BRK7AeZqebVSt2HyWMklxCHHJJYikn1Sa6/p/lldairqCwsbvta0awd9t26o27MnJHEG2yV5JsCuSbtJKy8lbmrAYWD6Z1a8dpsGi94SDgmsABBnAl5613FJsD/6HhE4cqSzw232CaxVAD9be2Cm+U9Og76rSsUUBNzXQ0TutOoIXHkfsGe50pGEPdtyXF8qGg/u3g7Zoy5BjF6Ljq2NKD5f53C8uT2utgS6WCQGZPbUIFmQLpX4fR7VapUCTPmBs61hIno3BVJUarp/Nn3ZsoavdampiB88OGIS2KbqdK4TWJurDwHvLrY6LTu2XbS1T2B39wRKWrc8hrPxrm9PSKl1mIHVSMCV2iPYZJyJF3TLYLRPxAWvvQUd9/UQUXNumQ+kD1U6ClWwX47rDb1Wwr2D0rH84UGI0csD490Duzjcx5s9rrYE+mHdev9egJ3WWnPAzqU6AycxgQ0jTGIpqtiWGre99x6kLV4EY/duDV+nL1uG6l27lA4xaIx2q75KWgPnmvkcNrlpE2tLRDucb3kM7vblpg5tTGDtNS0oAQBmLiAJHo0eGPAgcP9qDtRE5Jk+FnjgU6D/A/CuNn70sl+O27QIVFpiLK7pmYT+6W1xXe9kzLqpD7bPvh45Yy9rSGAB4L4hXR0eZ7/H1RMhgLaSh6IYLdSqlQ9XsJWScpU8rgUCt9iEHf41SFGn6VJj29cn582DpTTyWwacbxeD4+1qm93D6m7WNrFKXn7sjbPxwIw/aDDl/4RDL9qmDn+fiF5Dz7hMZG1XsFfq/4pziMeVGi8331LL9BgJjP0HlxATkff0scDtrwGD/wy8OQwQLagvodEBVguiqd+sQbJggvZrLLXcCZ0GuOvq9Iblws3p0CoGl6e2wc+F51q0xzXgFYRNVZAvWqjg+zZhhfzvPzKA84Ue79osbrEJO5yJJbqg05w5iBsa4Uuj9Hp06HuVQwJrCuKnQGIVMOX/BF67FTgb5/5+9QUxKNieCOEicbYNwFdoj2C4dh9aSbXBCTaaafRMYInId536XZiRbYFL7wxOLGHuj4b/YPYNXfHdnBucZlvdqiwBvs7G6vop+Nk4CVuN05SrEFxbDlUksJCAPReWbydf5N+puMUmLDGJJbpAMhjQ5bVXoU1MdHOHCFguZTaj9tvtDV+ejQcMQS7MPDBPYPE/BBKrnY+V2HUdqCyMdZvIUpDxCjMR+euW+fIf+97oOgxI7A51JEOBlSAq8afzS9G+lbH5O5trgDWPAi/3BrYthv5cPlpLNYiRonhfqtcEsOFvwMJLLiTePmqVwi02YYpJLNEFwmRC4aynYDnrph1NcxtP1Eaj8dg7NpBcJrCtga9GmxCf2lhtmImsAniFmYgCQR8L3L9K3lfvbh+i/b77E9+HMrrw8vMK4JM/AuUngC0LgNwxwLIb5H+3vCzPvJprgHdHAz++r3S06mY1A0V7fX88izmFLe6JJbqgafsdbXIyLKdPKxhRkNn3xtXrALPv/f5MGqC8ZzI65DX/fu1LB04mAqWXm/Dn78xIvqISJUBDv9jKwlgU77Wi89XnPJ+I/MPm7EQUaPpYYNQSYOQz8lLO/G2AqdJ1P01TpbKxKu3nFcDPK+E0G31ko9yDN7ErUMYaEIqSNCzmFMaYxBJdkDRpMqo2b4G5qAgJmZlIeeHvODgkwvfIAoBeD5j9W5pksAIdDpV5dd+TicDuIQbM/Vc9zlfFo6bIiC4Z8mMrC2Ohj6tH0sVR/sdNMBlbA9dOY3N2IgqehA7A8Cfl/9wxJIQunrDlZoWX1cwENhwkdOI4Gca4nJjoAvv2O6kLXkLRX55xc0fvG5Wrgp8JbAMvllvv6wq8P1LCjHcF6qvka2jmah3OHExA2jVn0bZXFdIzy2BI4HrioEkdIP9hyYGZiJTU7VqlIyDyrHVnpSMgD5jEEtkxpKWi05w5KJz1lMPSYgcmU2iDiiAdy4ClbwrE1NklzpJAq7RqSFqg89XnmMAGWzcvC68QEQVT/6zA9fAkCgajinriRiEmsUR2hMmEgukzHBLYhMxMXLTjO2iTkx3vHAnVikOsQyXQpsb+FgEICSc2J6OqhH/MBB2btRNRuGjVEbhygtJRELnHi75hjUks0QXuEljb0mKnIk+RVq24GYF+tXJZqQsXAoSEgq3tYKr0ol8e+Y6tdIgonLSkLQ9RKPGib9hjEkt0QdPqxAmZmUhbvAinXn7Z4XYpJjoruQZy3tmKph8+AlazFsc3JDGRDRa20iGicGPflkdirVEKI7zoG/aYxBJdkDRpMvQpKQAaE1jJYHC8PSMDMZddqmSYEcH+g8d+RtZcrUPZf1mxMuDi27NZOxGFJ1tbnotvVToSIhkv+qoCk1iiC+yrE9sS2Ka3a5OSULNzl8PjtBcSXGq5pjOyuvh6dOrP/rAB1/FSJrBEFJ7MNcDqPwC/faZ0JBTtNHp5VQAv+qoCk1giO4a0VHTOzm5IYO1v7zRnDsxFRQ63x2dkoOubb0TtEmN/2X8AaWMs6HlzCSSuJg48FqcgonBkrgH+NQ7Yt1LpSChqSUDXa4HMucDMX+VVAUxgVYEbEIi8VJyTg+rvvmv4Oj4jA12WLkFxTg5Eba2CkamfNsaCXreeYreFYGBxCiIKV188DRzbpnQUFM0GTJQTV1IdzsQSeanpntkuS5dAMhjQac4cJGRmKhydmgl0uvoME9hgYXEKCrKqqiq89957ePzxxzFo0CAYjUZIkoQXX3zRr/OuW7cOI0aMQJs2bdC6dWuMGDEC69atC1DUpLiKU8CPHygdBUUz7n1VNSaxRF5yt2dWMhiQtngRE1mfSTj5fTulg4hMaYM4QFPQ5eXlISsrC6+99hp27twJk8nk9zmXLl2KUaNGYfv27bjmmmuQmZmJnTt3YtSoUVi6dGkAoibF7c0FrGalo6BoxL2vEYHLiYlawLZntilbInvolt+jvrBQgcjUTECfaIKpUgtDgkXpYCJLr+s5QFPQtWrVCpMmTcKgQYMwcOBArF69Gn//+999Pt/BgwfxxBNPwGg0YuPGjRg6dGjD7ddccw2eeOIJ3HLLLejdu3egXgIpIf9bpSOgSBabCAx4CIAAin4ETJWAIUGuEXFVFlcoRQAmsUQBIhkM6PL/XsfRMXcAVqvS4aiIhLqSWBz5jx49bipjIhtIx3coHQFFgZ49e2LZsmUNX3/2mX9VZpcsWYL6+npMmTKlIYEFgIsuugjPPPMMZs6ciaVLl+LVV1/163lIYaZKpSOgSJbUC7jBedKBIgeXExMFiDCZULp4CRNYHwmzDqd/Y4/YgOIfiaRCtn2v48aNczp21113AQA+//zzkMZEQWDg5z0FEX++Il7UJrEsREGBJEwmFEyfgcoNG5QORdXMFVoITsQGDgdxUpny8nIcP34cANC/f3+n42lpaUhOTsaxY8dw7hx7Sqtat2uD/xwxbYP/HBSe2Fou4kXtcmJbIYpAWrp0KaZNmwadTocbbrgBRqMRX375JUaNGoUlS5Zg6tSpAX0+Cg9MYAOnuiQGRT+0RerQcqVDiQwcxEllbAlsYmIi4uPjXd4nLS0Np0+fxvHjx3HZZZc1e85+/fq5vP3w4cPo2bOn78GSf/pnAZvmB7e4kz4GqNUA4AqpqMLWclEhamdibYUo3nzzTezZswfPPPOMX+ezL0SxZcsWfPHFF1izZg1+/PFHJCUl4YknnkBeXl6AoqdwUpyT4zGB1SYnhzAa9bPUS0qHEBk4iJMKVVbKS+Dj4uLc3seW3NruSyrVqiNw5YTgPkdFMZjAhrFgzZS36w4YWwfn3BQ2onYmloUoKFDaZU3EuU/XQNTWNtwmxcRA1NYiITMTqQteQuGspzhT6yV9DP/gcKLRA5eOBX5e4f1j2B+WvDRu3Dj88ssvLXpMbm4uBg0aFPBYhBAAAElyfzHLdh9v7d+/3+Xt7mZoKYRumQ+UHQaObVM6ElLCkD8DFSeBve8Hdkb+9EHgX3cC968C9LGBOy+FlaidiQ00FqKIXmdylzsksAmZmej+6acN/WQ18fFIXfASpBi2OmlOQkoNOl3FfW5O+t8HjFoiN2b3Bhu4Uwvk5+fjwIEDLfqvuro6KLG0atUKgFy3wh3bcyckcM+36ulj5URjwIPyxTpXNHogxXl/NKmcRg9c/bA8ts38FUjsEdjzH9sGrJ8d2HNSWGESGwAsRBHdkiZNhj4lBYCcwKYtXgRj927onJ0NyWCAMJlQOOsph0SXnCWk1CDt2rOQtEpHEmZsCam3f+yxgTu10K5duyCEaNF/GRkZQYklPT0dAHD27Fm3iWxBQYHDfUnl9LGNiUzmXKDHSCBtoPxv5lz59ntXuP/cI3WyXy2U0AHoH4Sl5XvfBypLAn9eCgtRu5w4kFiIIroZ0lKRnpuLsreXodOcOZAMhoZjLos+SRLQwuVwkU+gw5XnmcA2dfndwKiljQmp7Y+9kc8Ae3KB/G1s4E4RpW3btkhPT8fx48exd+9eDBvmuPqgoKAAp0+fRnp6Otq0aaNQlBQUCR2A4U/K/7ly5QRgz/LQxkTB4Wq1UDAKfVnN8ljp7meKVI0zsQHAQhRkSEttmHm1cZXAapOTHRNYu/tHNwmnf2mldBDhpV0PxwTWnu2Pvaw1wOSv5X+HP8kEliLCrbfeCgBYtWqV07GPP/4YAHDbbbeFNCYKA7fM935LBYUnT6uFWnWUL9wGWj73W0cq1c7EshAFhbumVYu1ycmwnD7d8LUuNRXdP/oQR+4Y63B7tKo8ZYCwgLOxNmeOsDAFRbSLL74YAPDNN98gNTW14fZp06bhH//4B9544w3cc889GDJkCAC5Nd7f//53aLVatqyLRrYtFetnuy8EpNED8e2BiqLQx0eeJXYDJn0l///vXgXyv3VeSYQgrFIzcfIoUqk2ibUVomgJFqKgUEqaNBlVm7fAXFQEXWoq6gsLG47Z9s4W5+R4TGC1KSmwFEXHYGyt0+HwF+2RnnEGhgSL0uGEB1thilFLlI6EyKM77rgDJ0+eBNC4Z/X111/HmjVrAACdO3fGp59+6vAY2xhuNjsmI3369MGCBQswc+ZMXHfddbjxxhthMBjw5ZdfoqamBgsXLkSfPn2C/IooLHmzpWLPcmDD80pHSk1ZLcDXzwE/r3S+AHFkI7ApB7AGoTuBgX93RyrVJrG7du1SOoQGTQtRuNoXy0IU0cd+r2y7rCycmDQZ5qKihgRWMhjQLivLqT2PbcZW17kzDGlpqI6SJBYAzJV6HPs6CV1vKGMia7P3ffkPNi4VpjC2d+9eHDt2zOG2EydO4MSJEwCArl27tuh8M2bMQK9evbBgwQJs3boVADBgwADMmjULo0ePDkzQpF6e9s8GY28l+e/cCeDH990ft9YH53m7cQl6pOKe2ACwFaIA5IG8KRaiiF62vbLG7t2Rnpvb0HbHtnf2TG6uU3ueXv9Zjzbj74KhWzdU//CDUqErpr5Wh5J93B/bwFaYgiiM5efne6xmnJ+f7/QY27Fu3bq5POeoUaOwZcsWVFRUoKKiAlu3bmUCS81r1VEuAkWk0V9YpkyRiElsgLAQBTXHVfEnV+15NPHxkLRaVH/3nVKhKk5i8WZHLExBROQ9FoEiwLGND0UcJrEtdPHFF+Piiy9God3+RkAuRKHVavHGG29gx44dDbezEAV5Ylty3HSG1j65hT76euNJ+gjMYlulAMbWvj2WhSmIiLxnKwLVKkXpSEgprtr4UESJ6iT2jjvuwJAhQzBkyBAsW7YMgFyIwnbbHXfc4fSYAwcO4MCBA24LUdTV1eG6667D73//e4wZMwZXXHEFysrKsGDBAhaiIJdczdAa0lKR9sb/gxQTA5id9/XEDR2K1rffHpEJriamHp2vOqd0GIEnLEDqAN8ey8IUREQto48FBj6sdBQUap7a+FBEUW1hp0BgIQoKZ4Uzn3DYL2tjXxiq05zZOHjdcJeJripJVvS+tSQy2+xUlgBX3itXYWwpFqYgImq5sCnyJCEo7WOcnkYDXDsN2L8GOHs0+M+nNEkDpA8FLCbHCtVcQhwVojqJdVVoojnN9XsdNWoURo0a5WNERI06Pfccjj/wAGD3M2efwAKAtm1b9N7wDfKGj3C4nypJAheNKYYm8iaXLxCAxSJfJW7JH1QsTEFE5Btbkac9y71/jKQBRABbvVx+NzDyf4B9K+X6BoW7gLqKwJ3f3mV3ATc8Bwz+M7DwEkAEqeJvuLgqiy3oolhULycmChemgkKcnDcPwmRquC3+6gFIWbgQ0MnXmhIyM5G64CUU5+TAVCDvyRYmE4rmPuucwOrUd32qVXo1tEalowiyX1a3vGomC1MQEfmuJUWeug4DrghgZePL7wbG/gNITJfbAWWtkWdKgyGhIzBqqfz/W3UE2nUPzvOEC+55jXpMYokUZiooxPGsLJR/+BEKps9wSGTb3HIzeq5fj7b33oPUBS+hcNZTKP/wIxzPykLd0aM4MXUaqjZtcjyhwQDUq+/qa/UpI0Skt4atOAlc92TL/qDiIE1E5DtbkacBD8LtUh/7fZS3vhyYysZpgxqTSnv9s9zH4auETsCUHxr3gFacAs7mB/Y5QknSAJKbi/Hc80oXqG+6hijClL29DOaiIgBA5YYNKJg+w2HJsCEtFZ3mzEHB9Bmo3LABAGAuKkLB41NhOnTI4VzapCRYyspC+wICxFKrw4ltiegy7Gxk7okFAAh5Sdn9q4D1s4G977teWqzRyzOwN8/nIE1E5C99rLzsdOQzct/t/G1y1Xd3+yib+4z2Rs/rXX9++7LE2R1JIy8hHrXU8bn25obBPmA/XJXl/feKopYkmtvkSWGlX79+AID9+/crHAkFijCZHBJUwHHvq7vjHWbNwvGJE1FfUgIA0KWkoP5CMqwYjQaw+reXKD6lBl2ujeBEtsdIeUkZIBd74iCtGvz8jSz8flKzKkuAt3/nW5Ek+8/6psw1wL/GAcda2gNcAuKTgfZ9gR4j3I8VuWN8KyLYnEvvBDpc4jhmdRkM7HwLqA7QBfSuwzjLGiX8/QzmTCyRwiSDAWmLFzkkqrYZWdsSYncJbtcPPkDJksXQxsah3UMP4cSkSTAXFUGKiYGorW34NyQztLGxSHnhBVR9tx2mI0dQs2u3T6epKorFyT1WpAyMwDY7gGPP14QO8j6p4U8qFw8REbmW0EFOGn1JYj3197YtcfY02ytp5GXCrTvLPcZbcoEzWL3F9XGux6wT3/ufNHMFErUQk1iiMOAukT0w4GqH+zWtTmxIS0XaggUNx9Nzc1H29jK0y8rCmdxcJN47ASf+/GfUFxYG/0XU1KDqu+3o/D//g4Kp/hWuEGYpQEGFIfZ8JSJSD18/s5t7XEuXOAfyuX3100fA9c86x9XtWt+S2NapQPJFXIFEPmFhJ6IwYUtkEzIzXR5vmsC6YkhLRefsbBi7d0enOXNQunixQwKbkJmJPrt3QZea6vA4bVISYPS/NLAp/xgKpk5DZdNiU3biO9YgIaXG43lEBOew7PlKRKQi3a718XFeftbbVuRkrQEmfy3/O/xJ/xI6X2NujtUsJ9xN+VKsSqMH/rgpMK+XohKTWKIwIhkMSF3wkstjqQte8pjA2vO0z1YTH4/0ZcsgxTQu17GUlSH2skv9Cx5AzQ8/eExgAaDqVCwE4DaRlbRWdLgsSD30lMaer0RE6uJrgqbkZ30wKiDb5LvYx2srVtUSbB9HfmISSxRGhMmEwllPuTxWOOsph/Y7nhTn5LjdRwsAxu7d0P3TTx1mZH3dw4oYL/au6DSI79SYtFYVuUlkJYEuI8pgSIjQXjsctImI1EWNCZovMXvL3X7blvbjZfs48hOTWKIw4Wr21J6t2JM3iWzSpMnQp6QAcL8M2di9G3p98W8kZGT4HrRGA9TWOt0cN3QodBeeX5eaij7fbkGX+y9BQqpjIquNtTbcJumsSB95GvEdVNwWwBMO2kRE6qTGBK0lMbeEu/22Le3Hy+JN5CcmsURhwN3y3z67dznskfU2kTWkpSI9Nxdt772n2X20lhrH2VBtSgp6bfjGu8Dt2unYlicnZGYi/c030PXC8/f64t/QtEmCNHE10m7UNSSt+rh6JPetRNo1Z9G2VxV63Fyq3gS2VQoHbSKiSKXGBM2bmH3haa+vrVjVzF+BzLlym6G0gfK/mXPl20ctCY/3h1SPfWJVhn3tIo+vfWLtk1NTQSHK3l6GTnPmeExYhcmE4pwceaa2Q3uXM7/xw4dD0mia3dtqz9a39kzucs8x5I6ByNuI4r1tkHRxZeQsG86cK+9/Ys/XiMbP38jC7yf5RI39vU/9CvxnDlD0I1Bb7vt5JA3wxIHwfZ2kKv5+BjOJVRkOupHn5Lx5KP/wo4avXS3/dZXItr33HnTOzoapoBDHs7JgLiryWMHY/hz6lBTEDLgKFZ+v8zt+bXIyev1nPTTx8c3fecsCYMPzfj9nWNHo5avLHNQjHj9/Iwu/nxTxzDXAF08DP37guhdtS11+NzD2H/6fhwj+fwZzOTGRwrzZv9q0/Y4+JQVJkyYDAMreXgZzUREA98uNmybB5qIiSJAanjc+IwPxw4c7xaZNSmo2fsvp094XnQpmxUSlKF3Ag4iIqClzDfCvccCe5YFJYBM6AqOW+n8eogBhEkukMG/3r9oS2bb33oP03FwY0uTKwp3mzPG4b9bdcuSUvz/f+LyvvAxJ4/xxYCkr8+o1eF10KpgVE5UQLgU8iIiI7H3xNHDMRTscXyR0Aqb8wL2sFFaYxBKFAUNaKjpnZzfbB1YyGNA5O7shgbXdZj9LCzQmldaqKo/7aW3Pe+rll1u0B9aVyg0bUJyT0/wdg1UxsaUkDdx+BEo6IPki9RTwICIisqk4JS8h9pekkZcQT/sJiG3r//mIAkindABE5D9bImufsFZu2IADA652uJ+75cpJkyajavMWeV/tiOGo3LzF7XNpk5NhOX0aUkwMhF17HSkmBu2yJjYfrK1i4vrZwN73A7PMqTmSBkgfClhMjkU4AM8FOtRYwIOIiKLb3lzfxtbE7kB8Msc6UgUWdlIZFqIgTzz1mvVU9Am4UOH4H/+AuaQEVW5mZRMyMpD6yss49fLLaJeVhZIFL3usmtwsV0lil8HA2aPAL6sBa71352nOgAflsv5EfuDnb2Th95MiVu4Y4MjGlj+ux0gga02goyFyiYWdiKiBZDAgdcFLLo+lLnjJY3Kp79Ae9adPu01gAUAAkPR6dM7OhrF7d5fLmL1aUmyT0AEY/qQ8aE7+Wv535By5+uHM34CU/t6fyx3uWyUiomhiqgzt44gUwCSWKIIIkwmFs55yecxTBWFXM7hxQ4dC17mzw/2qNm1yKODkqWqy3xI6AA994fv+We5bJSKiaGRICO3jiBTAJJYoQnhaSgx4334HkJcFp7/5Brq+9x7ajh+P+IwMt+dxVzU5IGz7Zwc86L7IkqQDUq4Cuo8A0gbKy6Ey58q9W0ctYQJLRETRpdu1Pj4uDIouEnmJe2JVhnt4yBV3iWjqgpdQOOspj/tWT86bh/IPP3J73N352957DzpnZwfzZTlikSVSGD9/Iwu/nxSxKk4Bi/q1rLiTRi9f/OV4SiHCPbFEUc5dApu2eBE08fFu2+/YZlKTJk2GPiXF4XFN984Gddmwt1ztnx3+JAdcIiIie770ZO9/H8dTUhUmsUQqV5yT43Gm1V0fWVsBJkNaKtJzc9H23ns8VhYO6rJhIiIiCpyW9GRnAURSISaxRCoXiJlUQ1oqOmdnN9saRzIY0Dk7mwksERFROPOmpgQLIJKK6ZQOgIj8Y5tJLXt7GTrNmdPsTGpxTg6SJk1mIkpERBTJ9LFygcORz7CmBEUcJrFEEcA2k9oc20wqERERRQlbTYnhTyodCVHAcDkxERERERERqQaTWCIiIiIiIlINJrFERERERESkGkxiiYiIiIiISDWYxBIREREREZFqMIklIiIiIiIi1WASS0RERERERKrBJJaIiIiIiIhUg0ksERERERERqQaTWCIiIiIiIlINJrFERERERESkGkxiiYiIiIiISDWYxBIREREREZFqMIklIiIiIiIi1WASS0RERERERKrBJJaIiIiIiIhUQxJCCKWDIO+1atUKZrMZPXv2VDoUIqKocvjwYej1elRUVCgdCgUAx1MiIuX4O6ZyJlZl4uPjodfrlQ6jweHDh3H48GGlwwhLfG/c43vjHt8b95R+b/R6PeLj4xV7fgqscBlPlf65Dmd8b9zje+Me3xv3wum98XdM5Uws+aVfv34AgP379yscSfjhe+Me3xv3+N64x/eGIhF/rt3je+Me3xv3+N64F0nvDWdiiYiIiIiISDWYxBIREREREZFqMIklIiIiIiIi1WASS0RERERERKrBJJaIiIiIiIhUg9WJiYiIiIiISDU4E0tERERERESqwSSWiIiIiIiIVINJLBEREREREakGk1giIiIiIiJSDSaxREREREREpBpMYomIiIiIiEg1mMQSERERERGRajCJJSIiIiIiItVgEkteqaqqwnvvvYfHH38cgwYNgtFohCRJePHFF/0677p16zBixAi0adMGrVu3xogRI7Bu3boARR1a27dvx+9//3u0a9cOCQkJGDRoEJYvX97i87z77ruQJMntf/fcc08QovdPbW0tsrOzcdFFFyEmJgYpKSl4+OGHUVBQ0OJzlZeXY/r06ejatSuMRiO6du2KadOmoby8PPCBh0Cg3ptu3bp5/Ln473//G6RXEBy7d+/Giy++iLFjxyI1NRWSJCEmJsbn80Xazw1FHo6jzeM4ynHUFY6jrkX7OKpTOgBSh7y8PGRlZQX0nEuXLsW0adOg0+lwww03wGg04ssvv8SoUaOwZMkSTJ06NaDPF0yffvop7rrrLlitVgwfPhzJycn45ptv8OCDD+Knn37CwoULW3zOK664AldeeaXT7YMHDw5AxIFTW1uL66+/Htu3b0fnzp1x++23Iz8/H++88w7WrVuH7777Dj179vTqXGVlZRg6dCjy8vLQo0cPjBkzBvv378fSpUvx73//Gzt27EBSUlKQX1HgBPK9sZk4caLL29u0aROIkEPmb3/7Gz777LOAnCvSfm4oMnEc9YzjKMdRVziOuhf146gg8sKhQ4fEpEmTxJtvvin27NkjnnnmGQFA5OTk+HS+AwcOCJ1OJ4xGo9i+fbvD7UlJSUKn04mDBw8GKvygOnPmjGjTpo0AIFavXt1we3FxsejVq5cAIDZs2OD1+d555x0BQGRnZwch2sCbO3euACCGDh0qKioqGm5/5ZVXBAAxfPhwr8/1wAMPCABi7Nixwmw2N9z++OOPCwAiKysroLEHWyDfm65du4pI+sh+8cUXxbPPPis+//xzUVxcLAAIo9Ho07ki7eeGIhPHUfc4jnIcdYfjqHvRPo5GzneSQio7O9uvwffRRx8VAMS0adOcji1cuFAAEI899pifUYbGSy+9JACI22+/3enYJ598IgCI2267zevzqWnwNZlMom3btgKA2LNnj9Pxyy+/XAAQu3btavZcJ0+eFBqNRuj1elFcXOxwrLa2VrRv315otVqnY+EqkO+NEJE3+Dbl6+AbaT83FD04jjbiOMpx1BWOoy0TbeMo98SSImz7dcaNG+d07K677gIAfP755yGNyVeeXsutt96KmJgYfP3116itrQ11aEG3bds2lJeXo2fPnujfv7/Tcdt74s338osvvmhYRtaxY0eHY0ajEaNGjYLFYsEXX3wRmOCDLJDvDbkXaT83RN7iOBoZOI66x3E0NNT6c8MklkKuvLwcx48fBwCXH0ppaWlITk7GsWPHcO7cuVCH12I///wzAOCqq65yOmYwGHDppZeitrYWBw4caNF5d+/ejVmzZuGRRx5BdnY2Nm/eHJB4A+mnn34C4Pq1299uu1+ozhUOgvV6FixYgD/96U+YNm0a/vGPf6C0tNS/QFUu0n5uiLzBcdQ7HEd9P1c44DgaGmr9uWFhJwo528CbmJiI+Ph4l/dJS0vD6dOncfz4cVx22WWhDK9Fzp8/31C1LS0tzeV90tLSsGvXLhw/fhxXXHGF1+det26dQ4XJv/71rxgxYgRWrFjhdKVMKbbvpafXbn+/UJ0rHATr9Tz11FMOX8+YMQNLly7FpEmTfIhS/SLt54bIGxxHvcNx1PdzhQOOo6Gh1p8bzsRSyFVWVgIA4uLi3N7HNijb7huu7ONz93pa+lo6d+6M5557Dnv37sW5c+dQXFyMtWvX4uKLL8bmzZtx6623wmKx+B98ADT3vWzJaw/kucJBoF/P6NGj8cknn+DYsWOorq7GL7/8gpkzZ6Kurg6TJ0/GmjVrAhK32kTazw2RNziOesZxNDI+DzmOhoZaf244Exslxo0bh19++aVFj8nNzcWgQYMCHosQAgAgSVKz9wkFf94bb+Js6Wu56aabcNNNNzV83bp1a4waNQojR47EgAEDsHv3bqxYsQITJkxo0XmDobnvZUteeyDPFQ4C/XqWLl3q8HW/fv3wyiuvoE+fPnjkkUfw9NNPY8yYMT7FqmaR9nND4YvjqHscR33HcdQ9jqOhodafGyaxUSI/P7/Fe0mqq6uDEkurVq0AyI3fm3vuhISEoMRgz5/3xvZabLe1bt3a7X39fS0JCQmYOnUqHnvsMfznP/8Ji8G3ue9lS157IM8VDkL1eiZPnoy5c+fi4MGDOHr0KLp37+7X+dQm0n5uKHxxHHWP46jvOI66x3E0NNT6c8MkNkrs2rVL6RAapKenAwDOnj2Lqqoql/t5CgoKHO4bTP68N61bt0abNm1w7tw5FBQU4JJLLnG6TyBfS+/evQEAJ0+e9PtcgWB7TbbX2FRLXnsgzxUOQvV6NBoNevbsiZKSEpw8eTLqBt9I+7mh8MVx1D2Oo77jOOoex9HQUOvPDffEUsi1bdu24Rdh7969TscLCgpw+vRppKeno02bNqEOr8VsRSb27NnjdMxsNuOXX36B0WhEnz59/H6us2fPAgifq2GeXrv97ZdffnlIzxUOQvl6wu3nIpQi7eeGyBscR30Xbp+XHEfd4zgaGmr9uWESS4q49dZbAQCrVq1yOvbxxx8DAG677baQxuQrT69l3bp1qK2txfXXX4+YmBi/n2v16tUAgAEDBvh9rkC49tpr0aZNGxw+fNjlH1K298Sb7+XNN98MjUaDrVu3oqSkxOFYXV0dPv/8c2g0Gtxyyy2BCT7IAvneeLJ//34cOHAAcXFxuPjii/06lxpF2s8Nkbc4jvqG46h6Pg85joaGan9uBJEPsrOzBQCRk5Pj8X59+vQRffr0EQUFBQ63//e//xVarVYYjUbx3XffNdx+8OBBkZSUJLRarfjvf/8blNgDraysTLRu3VoAEKtXr264/dSpU6JXr14CgPj666+dHufuvVmyZImoqKhwuM1kMonnnntOABCxsbFOj1HSM888IwCIa665RlRWVjbc/sorrwgAYtiwYQ73f/XVV0WfPn3E7Nmznc513333CQDizjvvFGazueH2qVOnCgDi/vvvD94LCYJAvTfr168Xu3btcjr/Tz/9JPr27SsAiKlTpwbnRYQIAGE0Gt0ej6afG4oOHEcbcRzlOOoOx1HvRds4yiSWvDZmzBgxePBgMXjwYJGamioAiC5dujTcNmbMGKfHABAAxNGjR52OLVy4UAAQOp1O3HLLLeL2228XsbGxAoBYuHBhCF5R4KxatUpoNBohSZLIyMgQ48aNE23btvX4oejuvbENsAMGDBBjx44Vv//970VKSooAIGJiYhwG+HBQU1MjBg8eLACIzp07i/Hjxzd8nZSUJPLy8hzub/vDbeLEiU7nKi0tFT179hQARM+ePcXdd98tLr300oavS0tLQ/SqAiNQ743t9q5du4rMzExx9913i0GDBgmdTicAiBEjRoiqqqoQvjL/rVu3ruGzw/aeSJLkcNu6desa7h9NPzcUuTiOusdxlOOoKxxH3Yv2cZRJLHmta9euDQOGq/+6du3q9BhPg68QQqxdu1Zcd911IiEhQSQkJIhhw4aJzz77LLgvJEi2bdsmbr75ZtG2bVsRFxcnBgwYIP75z3+6vb+79+bZZ58VN954o+jSpYuIjY0VMTExolevXuKRRx4J26vq1dXVYu7cuaJnz57CYDCIjh07iokTJ4rjx4873dfTh6gQQpw5c0Y8/vjjokuXLsJgMIguXbqIxx57TJSVlQX5VQRHIN6b7du3i4cfflhcdtllIikpSeh0OtGuXTuRkZEh3nrrLVFfXx+iVxM477zzjsfPEwDinXfeabh/tP3cUGTiOOoZx1GOo65wHHUt2sdRSYgwbf5DRERERERE1AQLOxEREREREZFqMIklIiIiIiIi1WASS0RERERERKrBJJaIiIiIiIhUg0ksERERERERqQaTWCIiIiIiIlINJrFERERERESkGkxiiYiIiIiISDWYxBIREREREZFqMIklIiIiIiIi1WASS0RERERERKrBJJYoDD344IOQJAmbNm1yuL1bt26QJEmZoBQmSRK6deumdBhOTp8+jWXLluGPf/wjrrzySuh0OkiShI8++kjp0IiICBxTXeGYSmqnUzoAIiI127ZtG/7whz8oHQYREZHqcUwlbzGJJVKRb775BmazWekwFPHbb79Br9crHYaTjh074tFHH8XAgQMxcOBAzJ8/H++9957SYRERUTM4pnJMJfViEkukIj179lQ6BMVcfPHFSofg0tChQzF06NCGrzUa7tIgIlIDjqnhh2MqeYs/GUQKWr16NQYNGoTY2Fh07NgRWVlZKCoqcnt/V/t38vPzIUkSMjIyUFVVhZkzZ6JLly6IjY3FVVddhc8//7zhvh9//DEGDRqE+Ph4dOzYEVOnTkVNTY3L56qsrMRf//pXXHbZZYiLi0Pr1q0xYsQIrFmzxum+9jHU1NRg9uzZ6Nq1K4xGI3r16oX58+dDCOH0uBMnTmDKlCno06cP4uLi0K5dO/Tr1w+PPPIIDhw44HBfT/t3/v3vf+PGG29EYmIiYmJi0KdPH8yePRvl5eVO933uuecgSRLeffdd7Nu3D6NHj0ZiYiLi4+MxYsQIbN++3eVzEBFReOOYyjGVooggIkW8+uqrAoDQarUiMzNTjB8/XnTu3Fl06dJF3HbbbQKA2Lhxo8NjunbtKpr+2h49elQAEEOHDhWDBw8WycnJ4rbbbhMZGRlCo9EIrVYrvvrqK7Fw4UKh0+nE0KFDxZgxY0RSUpIAICZMmOAUW3FxsbjkkksEAJGamipGjx4tbrjhBhEfHy8AiJycHLcxDBs2TCQmJoqbbrpJ3HTTTSImJkYAEM8884zDY06cOCGSk5MFAHH55ZeL8ePHi9GjR4srrrhCSJIk3nnnHYf7AxBdu3Z1ivWFF14QAIROpxPXX3+9uPvuu0VaWpoAIC666CJRXFzscP/s7GwBQEyZMkXExcWJiy66SNx5553iiiuuEABETEyM2LdvXzPfPfcmTpwoAIgPP/zQ53MQEVHLcEzlmErRhUkskQKOHj0qjEajMBqNDoNqVVWVuPHGGwWAFg+4AERGRoY4c+ZMw7F33nlHABC9evUS7dq1E1u2bGk4VlhYKDp06CAAiMOHDzuc85ZbbhEAxFNPPSVMJlPD7YcPHxY9e/YUWq1W/PTTTy5juO6660RpaWnDsZ07dwqdTifi4uJERUVFw+22ge+VV15xen/y8/PFoUOHHG5zNeD+8MMPQqPRiFatWonvv/++4fba2lpx1113CQDirrvucniM7XkBiPnz5zscmz59ugAgHnjgAaeYvMUBl4gotDimckyl6MMklkgBc+fOFQDEH/7wB6dj//3vf4UkSS0ecLVarcjLy3M4ZrFYRPv27QUA8eyzzzo914wZMwQAhyu0e/fuFQDENddcI6xWq9Nj1qxZIwCIxx9/3CkGjUYjDhw44PSYUaNGOb2eP//5zwKA2Lt3r9P9XXE14GZlZQkAYu7cuU73P3XqlIiNjRUajUYUFBQ03G4bcIcNG+b0mNOnT7u9Ou0tDrhERKHFMZVjKkUf7oklUsC2bdsAAOPHj3c61qdPH/Tv37/F5+zWrRt69erlcJtGo0HXrl0BADfeeKPTY2xFLU6ePNlw21dffQUAuP322132zxs2bBgAYOfOnS5juOiii5xut91m/zwDBgwAAEyZMgUbN25EfX29h1fn2tatWwEA9913n9OxDh064He/+x2sVqvLPTm/+93vnG5LSkpCUlKSQ5xERBTeOKZyTKXowySWSAG2QhPp6ekuj7u73ZPU1FSXt8fHx7s9bjtWV1fXcFt+fj4A4Omnn4YkSU7/JScnA5AbkjeVlpbmMoaEhASn53nwwQcxfvx4bN++HZmZmWjTpg1GjBiBF198ESUlJc29XADy+yhJUsMfFU3Zila4KuzhKVaTyeTV8xMRkfI4pnJMpejDFjtEChAXqgq6uirrq+bO5e1zWSwWAMB1112HHj16uL2fbeD15TkAQKvVYsWKFZg9ezY+++wzbNy4ETt27MCWLVuQk5OD//znPxgyZIjX5/PEVVyBfO+JiEg5HFM5plL0YRJLpICUlBQcPHgQx44dQ+/evZ2OHz9+XIGoZLarqePGjcPUqVOD/nz9+/dH//798dxzz+H8+fOYN28eFi5ciGnTpuH777/3+NiUlBQcPXoUx44dQ58+fZyOHzt2DADQuXPnoMRORETK45jaiGMqRQsuJyZSgG0PzMcff+x07ODBg/jxxx9DHFGjG264AQBc9q4LttatW+OFF16AJEnYt29fs/e/7rrrAADvv/++07HS0lJ8+eWX0Gg0uOaaawIeKxERhQeOqa5xTKVIxiSWSAEPPfQQDAYDcnNzGwopAEBNTQ2mTZsGq9WqWGxDhgzB9ddfj40bN2LGjBmorKx0OG61WvHll182FNLw1XvvvYdffvnF6fb169dDCOHVHqYpU6ZAo9FgyZIl2LVrV8PtJpMJjz/+OKqrqzF27Fi3e5uIiEj9OKZyTKXow+XERAro0aMH5s+fjxkzZmDkyJHIyMhAcnIytm7dCo1Gg9tuuw3r1q1TLL73338fv/vd77B48WLk5ubiyiuvRPv27VFYWIgDBw6gtLQUixYtarj67YvVq1cjKysLPXv2xGWXXYbY2Fjk5+djx44d0Gq1eOGFF5o9x6BBg/C3v/0NzzzzDIYOHdrwPn777bc4ceIEevfujddee83nGL1lv8/o8OHDAIC5c+di8eLFAICrrroKr7/+etDjICKKRhxTOaZS9GESS6SQ6dOnIzU1FfPnz8e2bdvQqlUr/O53v8NLL72EZ555RtHYOnbsiB07duCNN97AihUrsHPnTphMJnTu3Bn9+/fH7bff7rKVQUvMnDkTaWlp+Pbbb7F161ZUVVUhNTUV9957L5588kmvWyL85S9/wRVXXIFFixZh586dqKmpQXp6Op566inMnj0biYmJfsXpDVf7jA4dOoRDhw4BAGJiYoIeAxFRNOOYyjGVooskbCXdiIiIiIiIiMIc98QSERERERGRajCJJSIiIiIiItVgEktERERERESqwSSWiIiIiIiIVINJLBEREREREakGk1giIiIiIiJSDSaxREREREREpBpMYomIiIiIiEg1mMQSERERERGRajCJJSIiIiIiItVgEktERERERESqwSSWiIiIiIiIVINJLBEREREREakGk1giIiIiIiJSDSaxREREREREpBpMYomIiIiIiEg1mMQSERERERGRavx/iBv9b6vKFpYAAAAASUVORK5CYII=\n",
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",
       "text/plain": [
        "<Figure size 960x720 with 2 Axes>"
       ]
@@ -224,962 +224,7 @@
    "outputs": [
     {
      "data": {
-      "application/javascript": [
-       "/* Put everything inside the global mpl namespace */\n",
-       "/* global mpl */\n",
-       "window.mpl = {};\n",
-       "\n",
-       "mpl.get_websocket_type = function () {\n",
-       "    if (typeof WebSocket !== 'undefined') {\n",
-       "        return WebSocket;\n",
-       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
-       "        return MozWebSocket;\n",
-       "    } else {\n",
-       "        alert(\n",
-       "            'Your browser does not have WebSocket support. ' +\n",
-       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
-       "                'Firefox 4 and 5 are also supported but you ' +\n",
-       "                'have to enable WebSockets in about:config.'\n",
-       "        );\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
-       "    this.id = figure_id;\n",
-       "\n",
-       "    this.ws = websocket;\n",
-       "\n",
-       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
-       "\n",
-       "    if (!this.supports_binary) {\n",
-       "        var warnings = document.getElementById('mpl-warnings');\n",
-       "        if (warnings) {\n",
-       "            warnings.style.display = 'block';\n",
-       "            warnings.textContent =\n",
-       "                'This browser does not support binary websocket messages. ' +\n",
-       "                'Performance may be slow.';\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.imageObj = new Image();\n",
-       "\n",
-       "    this.context = undefined;\n",
-       "    this.message = undefined;\n",
-       "    this.canvas = undefined;\n",
-       "    this.rubberband_canvas = undefined;\n",
-       "    this.rubberband_context = undefined;\n",
-       "    this.format_dropdown = undefined;\n",
-       "\n",
-       "    this.image_mode = 'full';\n",
-       "\n",
-       "    this.root = document.createElement('div');\n",
-       "    this.root.setAttribute('style', 'display: inline-block');\n",
-       "    this._root_extra_style(this.root);\n",
-       "\n",
-       "    parent_element.appendChild(this.root);\n",
-       "\n",
-       "    this._init_header(this);\n",
-       "    this._init_canvas(this);\n",
-       "    this._init_toolbar(this);\n",
-       "\n",
-       "    var fig = this;\n",
-       "\n",
-       "    this.waiting = false;\n",
-       "\n",
-       "    this.ws.onopen = function () {\n",
-       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
-       "        fig.send_message('send_image_mode', {});\n",
-       "        if (fig.ratio !== 1) {\n",
-       "            fig.send_message('set_device_pixel_ratio', {\n",
-       "                device_pixel_ratio: fig.ratio,\n",
-       "            });\n",
-       "        }\n",
-       "        fig.send_message('refresh', {});\n",
-       "    };\n",
-       "\n",
-       "    this.imageObj.onload = function () {\n",
-       "        if (fig.image_mode === 'full') {\n",
-       "            // Full images could contain transparency (where diff images\n",
-       "            // almost always do), so we need to clear the canvas so that\n",
-       "            // there is no ghosting.\n",
-       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
-       "        }\n",
-       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
-       "    };\n",
-       "\n",
-       "    this.imageObj.onunload = function () {\n",
-       "        fig.ws.close();\n",
-       "    };\n",
-       "\n",
-       "    this.ws.onmessage = this._make_on_message_function(this);\n",
-       "\n",
-       "    this.ondownload = ondownload;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._init_header = function () {\n",
-       "    var titlebar = document.createElement('div');\n",
-       "    titlebar.classList =\n",
-       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
-       "    var titletext = document.createElement('div');\n",
-       "    titletext.classList = 'ui-dialog-title';\n",
-       "    titletext.setAttribute(\n",
-       "        'style',\n",
-       "        'width: 100%; text-align: center; padding: 3px;'\n",
-       "    );\n",
-       "    titlebar.appendChild(titletext);\n",
-       "    this.root.appendChild(titlebar);\n",
-       "    this.header = titletext;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
-       "\n",
-       "mpl.figure.prototype._init_canvas = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
-       "    canvas_div.setAttribute(\n",
-       "        'style',\n",
-       "        'border: 1px solid #ddd;' +\n",
-       "            'box-sizing: content-box;' +\n",
-       "            'clear: both;' +\n",
-       "            'min-height: 1px;' +\n",
-       "            'min-width: 1px;' +\n",
-       "            'outline: 0;' +\n",
-       "            'overflow: hidden;' +\n",
-       "            'position: relative;' +\n",
-       "            'resize: both;'\n",
-       "    );\n",
-       "\n",
-       "    function on_keyboard_event_closure(name) {\n",
-       "        return function (event) {\n",
-       "            return fig.key_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    canvas_div.addEventListener(\n",
-       "        'keydown',\n",
-       "        on_keyboard_event_closure('key_press')\n",
-       "    );\n",
-       "    canvas_div.addEventListener(\n",
-       "        'keyup',\n",
-       "        on_keyboard_event_closure('key_release')\n",
-       "    );\n",
-       "\n",
-       "    this._canvas_extra_style(canvas_div);\n",
-       "    this.root.appendChild(canvas_div);\n",
-       "\n",
-       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
-       "    canvas.classList.add('mpl-canvas');\n",
-       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
-       "\n",
-       "    this.context = canvas.getContext('2d');\n",
-       "\n",
-       "    var backingStore =\n",
-       "        this.context.backingStorePixelRatio ||\n",
-       "        this.context.webkitBackingStorePixelRatio ||\n",
-       "        this.context.mozBackingStorePixelRatio ||\n",
-       "        this.context.msBackingStorePixelRatio ||\n",
-       "        this.context.oBackingStorePixelRatio ||\n",
-       "        this.context.backingStorePixelRatio ||\n",
-       "        1;\n",
-       "\n",
-       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
-       "\n",
-       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
-       "        'canvas'\n",
-       "    ));\n",
-       "    rubberband_canvas.setAttribute(\n",
-       "        'style',\n",
-       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
-       "    );\n",
-       "\n",
-       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
-       "    if (this.ResizeObserver === undefined) {\n",
-       "        if (window.ResizeObserver !== undefined) {\n",
-       "            this.ResizeObserver = window.ResizeObserver;\n",
-       "        } else {\n",
-       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
-       "            this.ResizeObserver = obs.ResizeObserver;\n",
-       "        }\n",
-       "    }\n",
-       "\n",
-       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
-       "        var nentries = entries.length;\n",
-       "        for (var i = 0; i < nentries; i++) {\n",
-       "            var entry = entries[i];\n",
-       "            var width, height;\n",
-       "            if (entry.contentBoxSize) {\n",
-       "                if (entry.contentBoxSize instanceof Array) {\n",
-       "                    // Chrome 84 implements new version of spec.\n",
-       "                    width = entry.contentBoxSize[0].inlineSize;\n",
-       "                    height = entry.contentBoxSize[0].blockSize;\n",
-       "                } else {\n",
-       "                    // Firefox implements old version of spec.\n",
-       "                    width = entry.contentBoxSize.inlineSize;\n",
-       "                    height = entry.contentBoxSize.blockSize;\n",
-       "                }\n",
-       "            } else {\n",
-       "                // Chrome <84 implements even older version of spec.\n",
-       "                width = entry.contentRect.width;\n",
-       "                height = entry.contentRect.height;\n",
-       "            }\n",
-       "\n",
-       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
-       "            // the canvas container.\n",
-       "            if (entry.devicePixelContentBoxSize) {\n",
-       "                // Chrome 84 implements new version of spec.\n",
-       "                canvas.setAttribute(\n",
-       "                    'width',\n",
-       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
-       "                );\n",
-       "                canvas.setAttribute(\n",
-       "                    'height',\n",
-       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
-       "                );\n",
-       "            } else {\n",
-       "                canvas.setAttribute('width', width * fig.ratio);\n",
-       "                canvas.setAttribute('height', height * fig.ratio);\n",
-       "            }\n",
-       "            canvas.setAttribute(\n",
-       "                'style',\n",
-       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
-       "            );\n",
-       "\n",
-       "            rubberband_canvas.setAttribute('width', width);\n",
-       "            rubberband_canvas.setAttribute('height', height);\n",
-       "\n",
-       "            // And update the size in Python. We ignore the initial 0/0 size\n",
-       "            // that occurs as the element is placed into the DOM, which should\n",
-       "            // otherwise not happen due to the minimum size styling.\n",
-       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
-       "                fig.request_resize(width, height);\n",
-       "            }\n",
-       "        }\n",
-       "    });\n",
-       "    this.resizeObserverInstance.observe(canvas_div);\n",
-       "\n",
-       "    function on_mouse_event_closure(name) {\n",
-       "        return function (event) {\n",
-       "            return fig.mouse_event(event, name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousedown',\n",
-       "        on_mouse_event_closure('button_press')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseup',\n",
-       "        on_mouse_event_closure('button_release')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'dblclick',\n",
-       "        on_mouse_event_closure('dblclick')\n",
-       "    );\n",
-       "    // Throttle sequential mouse events to 1 every 20ms.\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mousemove',\n",
-       "        on_mouse_event_closure('motion_notify')\n",
-       "    );\n",
-       "\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseenter',\n",
-       "        on_mouse_event_closure('figure_enter')\n",
-       "    );\n",
-       "    rubberband_canvas.addEventListener(\n",
-       "        'mouseleave',\n",
-       "        on_mouse_event_closure('figure_leave')\n",
-       "    );\n",
-       "\n",
-       "    canvas_div.addEventListener('wheel', function (event) {\n",
-       "        if (event.deltaY < 0) {\n",
-       "            event.step = 1;\n",
-       "        } else {\n",
-       "            event.step = -1;\n",
-       "        }\n",
-       "        on_mouse_event_closure('scroll')(event);\n",
-       "    });\n",
-       "\n",
-       "    canvas_div.appendChild(canvas);\n",
-       "    canvas_div.appendChild(rubberband_canvas);\n",
-       "\n",
-       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
-       "    this.rubberband_context.strokeStyle = '#000000';\n",
-       "\n",
-       "    this._resize_canvas = function (width, height, forward) {\n",
-       "        if (forward) {\n",
-       "            canvas_div.style.width = width + 'px';\n",
-       "            canvas_div.style.height = height + 'px';\n",
-       "        }\n",
-       "    };\n",
-       "\n",
-       "    // Disable right mouse context menu.\n",
-       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
-       "        event.preventDefault();\n",
-       "        return false;\n",
-       "    });\n",
-       "\n",
-       "    function set_focus() {\n",
-       "        canvas.focus();\n",
-       "        canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    window.setTimeout(set_focus, 100);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var toolbar = document.createElement('div');\n",
-       "    toolbar.classList = 'mpl-toolbar';\n",
-       "    this.root.appendChild(toolbar);\n",
-       "\n",
-       "    function on_click_closure(name) {\n",
-       "        return function (_event) {\n",
-       "            return fig.toolbar_button_onclick(name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    function on_mouseover_closure(tooltip) {\n",
-       "        return function (event) {\n",
-       "            if (!event.currentTarget.disabled) {\n",
-       "                return fig.toolbar_button_onmouseover(tooltip);\n",
-       "            }\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    fig.buttons = {};\n",
-       "    var buttonGroup = document.createElement('div');\n",
-       "    buttonGroup.classList = 'mpl-button-group';\n",
-       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            /* Instead of a spacer, we start a new button group. */\n",
-       "            if (buttonGroup.hasChildNodes()) {\n",
-       "                toolbar.appendChild(buttonGroup);\n",
-       "            }\n",
-       "            buttonGroup = document.createElement('div');\n",
-       "            buttonGroup.classList = 'mpl-button-group';\n",
-       "            continue;\n",
-       "        }\n",
-       "\n",
-       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
-       "        button.classList = 'mpl-widget';\n",
-       "        button.setAttribute('role', 'button');\n",
-       "        button.setAttribute('aria-disabled', 'false');\n",
-       "        button.addEventListener('click', on_click_closure(method_name));\n",
-       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
-       "\n",
-       "        var icon_img = document.createElement('img');\n",
-       "        icon_img.src = '_images/' + image + '.png';\n",
-       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
-       "        icon_img.alt = tooltip;\n",
-       "        button.appendChild(icon_img);\n",
-       "\n",
-       "        buttonGroup.appendChild(button);\n",
-       "    }\n",
-       "\n",
-       "    if (buttonGroup.hasChildNodes()) {\n",
-       "        toolbar.appendChild(buttonGroup);\n",
-       "    }\n",
-       "\n",
-       "    var fmt_picker = document.createElement('select');\n",
-       "    fmt_picker.classList = 'mpl-widget';\n",
-       "    toolbar.appendChild(fmt_picker);\n",
-       "    this.format_dropdown = fmt_picker;\n",
-       "\n",
-       "    for (var ind in mpl.extensions) {\n",
-       "        var fmt = mpl.extensions[ind];\n",
-       "        var option = document.createElement('option');\n",
-       "        option.selected = fmt === mpl.default_extension;\n",
-       "        option.innerHTML = fmt;\n",
-       "        fmt_picker.appendChild(option);\n",
-       "    }\n",
-       "\n",
-       "    var status_bar = document.createElement('span');\n",
-       "    status_bar.classList = 'mpl-message';\n",
-       "    toolbar.appendChild(status_bar);\n",
-       "    this.message = status_bar;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
-       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
-       "    // which will in turn request a refresh of the image.\n",
-       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_message = function (type, properties) {\n",
-       "    properties['type'] = type;\n",
-       "    properties['figure_id'] = this.id;\n",
-       "    this.ws.send(JSON.stringify(properties));\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.send_draw_message = function () {\n",
-       "    if (!this.waiting) {\n",
-       "        this.waiting = true;\n",
-       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    var format_dropdown = fig.format_dropdown;\n",
-       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
-       "    fig.ondownload(fig, format);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
-       "    var size = msg['size'];\n",
-       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
-       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
-       "        fig.send_message('refresh', {});\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
-       "    var x0 = msg['x0'] / fig.ratio;\n",
-       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
-       "    var x1 = msg['x1'] / fig.ratio;\n",
-       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
-       "    x0 = Math.floor(x0) + 0.5;\n",
-       "    y0 = Math.floor(y0) + 0.5;\n",
-       "    x1 = Math.floor(x1) + 0.5;\n",
-       "    y1 = Math.floor(y1) + 0.5;\n",
-       "    var min_x = Math.min(x0, x1);\n",
-       "    var min_y = Math.min(y0, y1);\n",
-       "    var width = Math.abs(x1 - x0);\n",
-       "    var height = Math.abs(y1 - y0);\n",
-       "\n",
-       "    fig.rubberband_context.clearRect(\n",
-       "        0,\n",
-       "        0,\n",
-       "        fig.canvas.width / fig.ratio,\n",
-       "        fig.canvas.height / fig.ratio\n",
-       "    );\n",
-       "\n",
-       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
-       "    // Updates the figure title.\n",
-       "    fig.header.textContent = msg['label'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
-       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
-       "    fig.message.textContent = msg['message'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
-       "    // Request the server to send over a new figure.\n",
-       "    fig.send_draw_message();\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
-       "    fig.image_mode = msg['mode'];\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
-       "    for (var key in msg) {\n",
-       "        if (!(key in fig.buttons)) {\n",
-       "            continue;\n",
-       "        }\n",
-       "        fig.buttons[key].disabled = !msg[key];\n",
-       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
-       "    if (msg['mode'] === 'PAN') {\n",
-       "        fig.buttons['Pan'].classList.add('active');\n",
-       "        fig.buttons['Zoom'].classList.remove('active');\n",
-       "    } else if (msg['mode'] === 'ZOOM') {\n",
-       "        fig.buttons['Pan'].classList.remove('active');\n",
-       "        fig.buttons['Zoom'].classList.add('active');\n",
-       "    } else {\n",
-       "        fig.buttons['Pan'].classList.remove('active');\n",
-       "        fig.buttons['Zoom'].classList.remove('active');\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Called whenever the canvas gets updated.\n",
-       "    this.send_message('ack', {});\n",
-       "};\n",
-       "\n",
-       "// A function to construct a web socket function for onmessage handling.\n",
-       "// Called in the figure constructor.\n",
-       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
-       "    return function socket_on_message(evt) {\n",
-       "        if (evt.data instanceof Blob) {\n",
-       "            var img = evt.data;\n",
-       "            if (img.type !== 'image/png') {\n",
-       "                /* FIXME: We get \"Resource interpreted as Image but\n",
-       "                 * transferred with MIME type text/plain:\" errors on\n",
-       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
-       "                 * to be part of the websocket stream */\n",
-       "                img.type = 'image/png';\n",
-       "            }\n",
-       "\n",
-       "            /* Free the memory for the previous frames */\n",
-       "            if (fig.imageObj.src) {\n",
-       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
-       "                    fig.imageObj.src\n",
-       "                );\n",
-       "            }\n",
-       "\n",
-       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
-       "                img\n",
-       "            );\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        } else if (\n",
-       "            typeof evt.data === 'string' &&\n",
-       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
-       "        ) {\n",
-       "            fig.imageObj.src = evt.data;\n",
-       "            fig.updated_canvas_event();\n",
-       "            fig.waiting = false;\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        var msg = JSON.parse(evt.data);\n",
-       "        var msg_type = msg['type'];\n",
-       "\n",
-       "        // Call the  \"handle_{type}\" callback, which takes\n",
-       "        // the figure and JSON message as its only arguments.\n",
-       "        try {\n",
-       "            var callback = fig['handle_' + msg_type];\n",
-       "        } catch (e) {\n",
-       "            console.log(\n",
-       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
-       "                msg\n",
-       "            );\n",
-       "            return;\n",
-       "        }\n",
-       "\n",
-       "        if (callback) {\n",
-       "            try {\n",
-       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
-       "                callback(fig, msg);\n",
-       "            } catch (e) {\n",
-       "                console.log(\n",
-       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
-       "                    e,\n",
-       "                    e.stack,\n",
-       "                    msg\n",
-       "                );\n",
-       "            }\n",
-       "        }\n",
-       "    };\n",
-       "};\n",
-       "\n",
-       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
-       "mpl.findpos = function (e) {\n",
-       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
-       "    var targ;\n",
-       "    if (!e) {\n",
-       "        e = window.event;\n",
-       "    }\n",
-       "    if (e.target) {\n",
-       "        targ = e.target;\n",
-       "    } else if (e.srcElement) {\n",
-       "        targ = e.srcElement;\n",
-       "    }\n",
-       "    if (targ.nodeType === 3) {\n",
-       "        // defeat Safari bug\n",
-       "        targ = targ.parentNode;\n",
-       "    }\n",
-       "\n",
-       "    // pageX,Y are the mouse positions relative to the document\n",
-       "    var boundingRect = targ.getBoundingClientRect();\n",
-       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
-       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
-       "\n",
-       "    return { x: x, y: y };\n",
-       "};\n",
-       "\n",
-       "/*\n",
-       " * return a copy of an object with only non-object keys\n",
-       " * we need this to avoid circular references\n",
-       " * https://stackoverflow.com/a/24161582/3208463\n",
-       " */\n",
-       "function simpleKeys(original) {\n",
-       "    return Object.keys(original).reduce(function (obj, key) {\n",
-       "        if (typeof original[key] !== 'object') {\n",
-       "            obj[key] = original[key];\n",
-       "        }\n",
-       "        return obj;\n",
-       "    }, {});\n",
-       "}\n",
-       "\n",
-       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
-       "    var canvas_pos = mpl.findpos(event);\n",
-       "\n",
-       "    if (name === 'button_press') {\n",
-       "        this.canvas.focus();\n",
-       "        this.canvas_div.focus();\n",
-       "    }\n",
-       "\n",
-       "    var x = canvas_pos.x * this.ratio;\n",
-       "    var y = canvas_pos.y * this.ratio;\n",
-       "\n",
-       "    this.send_message(name, {\n",
-       "        x: x,\n",
-       "        y: y,\n",
-       "        button: event.button,\n",
-       "        step: event.step,\n",
-       "        guiEvent: simpleKeys(event),\n",
-       "    });\n",
-       "\n",
-       "    /* This prevents the web browser from automatically changing to\n",
-       "     * the text insertion cursor when the button is pressed.  We want\n",
-       "     * to control all of the cursor setting manually through the\n",
-       "     * 'cursor' event from matplotlib */\n",
-       "    event.preventDefault();\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
-       "    // Handle any extra behaviour associated with a key event\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.key_event = function (event, name) {\n",
-       "    // Prevent repeat events\n",
-       "    if (name === 'key_press') {\n",
-       "        if (event.key === this._key) {\n",
-       "            return;\n",
-       "        } else {\n",
-       "            this._key = event.key;\n",
-       "        }\n",
-       "    }\n",
-       "    if (name === 'key_release') {\n",
-       "        this._key = null;\n",
-       "    }\n",
-       "\n",
-       "    var value = '';\n",
-       "    if (event.ctrlKey && event.key !== 'Control') {\n",
-       "        value += 'ctrl+';\n",
-       "    }\n",
-       "    else if (event.altKey && event.key !== 'Alt') {\n",
-       "        value += 'alt+';\n",
-       "    }\n",
-       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
-       "        value += 'shift+';\n",
-       "    }\n",
-       "\n",
-       "    value += 'k' + event.key;\n",
-       "\n",
-       "    this._key_event_extra(event, name);\n",
-       "\n",
-       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
-       "    return false;\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
-       "    if (name === 'download') {\n",
-       "        this.handle_save(this, null);\n",
-       "    } else {\n",
-       "        this.send_message('toolbar_button', { name: name });\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
-       "    this.message.textContent = tooltip;\n",
-       "};\n",
-       "\n",
-       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
-       "// prettier-ignore\n",
-       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
-       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n",
-       "\n",
-       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n",
-       "\n",
-       "mpl.default_extension = \"png\";/* global mpl */\n",
-       "\n",
-       "var comm_websocket_adapter = function (comm) {\n",
-       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
-       "    // object with the appropriate methods. Currently this is a non binary\n",
-       "    // socket, so there is still some room for performance tuning.\n",
-       "    var ws = {};\n",
-       "\n",
-       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
-       "    ws.readyState = comm.kernel.ws.readyState;\n",
-       "    function updateReadyState(_event) {\n",
-       "        if (comm.kernel.ws) {\n",
-       "            ws.readyState = comm.kernel.ws.readyState;\n",
-       "        } else {\n",
-       "            ws.readyState = 3; // Closed state.\n",
-       "        }\n",
-       "    }\n",
-       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
-       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
-       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
-       "\n",
-       "    ws.close = function () {\n",
-       "        comm.close();\n",
-       "    };\n",
-       "    ws.send = function (m) {\n",
-       "        //console.log('sending', m);\n",
-       "        comm.send(m);\n",
-       "    };\n",
-       "    // Register the callback with on_msg.\n",
-       "    comm.on_msg(function (msg) {\n",
-       "        //console.log('receiving', msg['content']['data'], msg);\n",
-       "        var data = msg['content']['data'];\n",
-       "        if (data['blob'] !== undefined) {\n",
-       "            data = {\n",
-       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
-       "            };\n",
-       "        }\n",
-       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
-       "        ws.onmessage(data);\n",
-       "    });\n",
-       "    return ws;\n",
-       "};\n",
-       "\n",
-       "mpl.mpl_figure_comm = function (comm, msg) {\n",
-       "    // This is the function which gets called when the mpl process\n",
-       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
-       "\n",
-       "    var id = msg.content.data.id;\n",
-       "    // Get hold of the div created by the display call when the Comm\n",
-       "    // socket was opened in Python.\n",
-       "    var element = document.getElementById(id);\n",
-       "    var ws_proxy = comm_websocket_adapter(comm);\n",
-       "\n",
-       "    function ondownload(figure, _format) {\n",
-       "        window.open(figure.canvas.toDataURL());\n",
-       "    }\n",
-       "\n",
-       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
-       "\n",
-       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
-       "    // web socket which is closed, not our websocket->open comm proxy.\n",
-       "    ws_proxy.onopen();\n",
-       "\n",
-       "    fig.parent_element = element;\n",
-       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
-       "    if (!fig.cell_info) {\n",
-       "        console.error('Failed to find cell for figure', id, fig);\n",
-       "        return;\n",
-       "    }\n",
-       "    fig.cell_info[0].output_area.element.on(\n",
-       "        'cleared',\n",
-       "        { fig: fig },\n",
-       "        fig._remove_fig_handler\n",
-       "    );\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
-       "    var width = fig.canvas.width / fig.ratio;\n",
-       "    fig.cell_info[0].output_area.element.off(\n",
-       "        'cleared',\n",
-       "        fig._remove_fig_handler\n",
-       "    );\n",
-       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
-       "\n",
-       "    // Update the output cell to use the data from the current canvas.\n",
-       "    fig.push_to_output();\n",
-       "    var dataURL = fig.canvas.toDataURL();\n",
-       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
-       "    // the notebook keyboard shortcuts fail.\n",
-       "    IPython.keyboard_manager.enable();\n",
-       "    fig.parent_element.innerHTML =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "    fig.close_ws(fig, msg);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
-       "    fig.send_message('closing', msg);\n",
-       "    // fig.ws.close()\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
-       "    // Turn the data on the canvas into data in the output cell.\n",
-       "    var width = this.canvas.width / this.ratio;\n",
-       "    var dataURL = this.canvas.toDataURL();\n",
-       "    this.cell_info[1]['text/html'] =\n",
-       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.updated_canvas_event = function () {\n",
-       "    // Tell IPython that the notebook contents must change.\n",
-       "    IPython.notebook.set_dirty(true);\n",
-       "    this.send_message('ack', {});\n",
-       "    var fig = this;\n",
-       "    // Wait a second, then push the new image to the DOM so\n",
-       "    // that it is saved nicely (might be nice to debounce this).\n",
-       "    setTimeout(function () {\n",
-       "        fig.push_to_output();\n",
-       "    }, 1000);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._init_toolbar = function () {\n",
-       "    var fig = this;\n",
-       "\n",
-       "    var toolbar = document.createElement('div');\n",
-       "    toolbar.classList = 'btn-toolbar';\n",
-       "    this.root.appendChild(toolbar);\n",
-       "\n",
-       "    function on_click_closure(name) {\n",
-       "        return function (_event) {\n",
-       "            return fig.toolbar_button_onclick(name);\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    function on_mouseover_closure(tooltip) {\n",
-       "        return function (event) {\n",
-       "            if (!event.currentTarget.disabled) {\n",
-       "                return fig.toolbar_button_onmouseover(tooltip);\n",
-       "            }\n",
-       "        };\n",
-       "    }\n",
-       "\n",
-       "    fig.buttons = {};\n",
-       "    var buttonGroup = document.createElement('div');\n",
-       "    buttonGroup.classList = 'btn-group';\n",
-       "    var button;\n",
-       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
-       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
-       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
-       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
-       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
-       "\n",
-       "        if (!name) {\n",
-       "            /* Instead of a spacer, we start a new button group. */\n",
-       "            if (buttonGroup.hasChildNodes()) {\n",
-       "                toolbar.appendChild(buttonGroup);\n",
-       "            }\n",
-       "            buttonGroup = document.createElement('div');\n",
-       "            buttonGroup.classList = 'btn-group';\n",
-       "            continue;\n",
-       "        }\n",
-       "\n",
-       "        button = fig.buttons[name] = document.createElement('button');\n",
-       "        button.classList = 'btn btn-default';\n",
-       "        button.href = '#';\n",
-       "        button.title = name;\n",
-       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
-       "        button.addEventListener('click', on_click_closure(method_name));\n",
-       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
-       "        buttonGroup.appendChild(button);\n",
-       "    }\n",
-       "\n",
-       "    if (buttonGroup.hasChildNodes()) {\n",
-       "        toolbar.appendChild(buttonGroup);\n",
-       "    }\n",
-       "\n",
-       "    // Add the status bar.\n",
-       "    var status_bar = document.createElement('span');\n",
-       "    status_bar.classList = 'mpl-message pull-right';\n",
-       "    toolbar.appendChild(status_bar);\n",
-       "    this.message = status_bar;\n",
-       "\n",
-       "    // Add the close button to the window.\n",
-       "    var buttongrp = document.createElement('div');\n",
-       "    buttongrp.classList = 'btn-group inline pull-right';\n",
-       "    button = document.createElement('button');\n",
-       "    button.classList = 'btn btn-mini btn-primary';\n",
-       "    button.href = '#';\n",
-       "    button.title = 'Stop Interaction';\n",
-       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
-       "    button.addEventListener('click', function (_evt) {\n",
-       "        fig.handle_close(fig, {});\n",
-       "    });\n",
-       "    button.addEventListener(\n",
-       "        'mouseover',\n",
-       "        on_mouseover_closure('Stop Interaction')\n",
-       "    );\n",
-       "    buttongrp.appendChild(button);\n",
-       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
-       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
-       "    var fig = event.data.fig;\n",
-       "    if (event.target !== this) {\n",
-       "        // Ignore bubbled events from children.\n",
-       "        return;\n",
-       "    }\n",
-       "    fig.close_ws(fig, {});\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._root_extra_style = function (el) {\n",
-       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
-       "    // this is important to make the div 'focusable\n",
-       "    el.setAttribute('tabindex', 0);\n",
-       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
-       "    // off when our div gets focus\n",
-       "\n",
-       "    // location in version 3\n",
-       "    if (IPython.notebook.keyboard_manager) {\n",
-       "        IPython.notebook.keyboard_manager.register_events(el);\n",
-       "    } else {\n",
-       "        // location in version 2\n",
-       "        IPython.keyboard_manager.register_events(el);\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
-       "    // Check for shift+enter\n",
-       "    if (event.shiftKey && event.which === 13) {\n",
-       "        this.canvas_div.blur();\n",
-       "        // select the cell after this one\n",
-       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
-       "        IPython.notebook.select(index + 1);\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
-       "    fig.ondownload(fig, null);\n",
-       "};\n",
-       "\n",
-       "mpl.find_output_cell = function (html_output) {\n",
-       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
-       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
-       "    // IPython event is triggered only after the cells have been serialised, which for\n",
-       "    // our purposes (turning an active figure into a static one), is too late.\n",
-       "    var cells = IPython.notebook.get_cells();\n",
-       "    var ncells = cells.length;\n",
-       "    for (var i = 0; i < ncells; i++) {\n",
-       "        var cell = cells[i];\n",
-       "        if (cell.cell_type === 'code') {\n",
-       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
-       "                var data = cell.output_area.outputs[j];\n",
-       "                if (data.data) {\n",
-       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
-       "                    data = data.data;\n",
-       "                }\n",
-       "                if (data['text/html'] === html_output) {\n",
-       "                    return [cell, data, j];\n",
-       "                }\n",
-       "            }\n",
-       "        }\n",
-       "    }\n",
-       "};\n",
-       "\n",
-       "// Register the function which deals with the matplotlib target/channel.\n",
-       "// The kernel may be null if the page has been refreshed.\n",
-       "if (IPython.notebook.kernel !== null) {\n",
-       "    IPython.notebook.kernel.comm_manager.register_target(\n",
-       "        'matplotlib',\n",
-       "        mpl.mpl_figure_comm\n",
-       "    );\n",
-       "}\n"
-      ],
+      "application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n    if (typeof WebSocket !== 'undefined') {\n        return WebSocket;\n    } else if (typeof MozWebSocket !== 'undefined') {\n        return MozWebSocket;\n    } else {\n        alert(\n            'Your browser does not have WebSocket support. ' +\n                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n                'Firefox 4 and 5 are also supported but you ' +\n                'have to enable WebSockets in about:config.'\n        );\n    }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n    this.id = figure_id;\n\n    this.ws = websocket;\n\n    this.supports_binary = this.ws.binaryType !== undefined;\n\n    if (!this.supports_binary) {\n        var warnings = document.getElementById('mpl-warnings');\n        if (warnings) {\n            warnings.style.display = 'block';\n            warnings.textContent =\n                'This browser does not support binary websocket messages. ' +\n                'Performance may be slow.';\n        }\n    }\n\n    this.imageObj = new Image();\n\n    this.context = undefined;\n    this.message = undefined;\n    this.canvas = undefined;\n    this.rubberband_canvas = undefined;\n    this.rubberband_context = undefined;\n    this.format_dropdown = undefined;\n\n    this.image_mode = 'full';\n\n    this.root = document.createElement('div');\n    this.root.setAttribute('style', 'display: inline-block');\n    this._root_extra_style(this.root);\n\n    parent_element.appendChild(this.root);\n\n    this._init_header(this);\n    this._init_canvas(this);\n    this._init_toolbar(this);\n\n    var fig = this;\n\n    this.waiting = false;\n\n    this.ws.onopen = function () {\n        fig.send_message('supports_binary', { value: fig.supports_binary });\n        fig.send_message('send_image_mode', {});\n        if (fig.ratio !== 1) {\n            fig.send_message('set_device_pixel_ratio', {\n                device_pixel_ratio: fig.ratio,\n            });\n        }\n        fig.send_message('refresh', {});\n    };\n\n    this.imageObj.onload = function () {\n        if (fig.image_mode === 'full') {\n            // Full images could contain transparency (where diff images\n            // almost always do), so we need to clear the canvas so that\n            // there is no ghosting.\n            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n        }\n        fig.context.drawImage(fig.imageObj, 0, 0);\n    };\n\n    this.imageObj.onunload = function () {\n        fig.ws.close();\n    };\n\n    this.ws.onmessage = this._make_on_message_function(this);\n\n    this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n    var titlebar = document.createElement('div');\n    titlebar.classList =\n        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n    var titletext = document.createElement('div');\n    titletext.classList = 'ui-dialog-title';\n    titletext.setAttribute(\n        'style',\n        'width: 100%; text-align: center; padding: 3px;'\n    );\n    titlebar.appendChild(titletext);\n    this.root.appendChild(titlebar);\n    this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n    var fig = this;\n\n    var canvas_div = (this.canvas_div = document.createElement('div'));\n    canvas_div.setAttribute(\n        'style',\n        'border: 1px solid #ddd;' +\n            'box-sizing: content-box;' +\n            'clear: both;' +\n            'min-height: 1px;' +\n            'min-width: 1px;' +\n            'outline: 0;' +\n            'overflow: hidden;' +\n            'position: relative;' +\n            'resize: both;'\n    );\n\n    function on_keyboard_event_closure(name) {\n        return function (event) {\n            return fig.key_event(event, name);\n        };\n    }\n\n    canvas_div.addEventListener(\n        'keydown',\n        on_keyboard_event_closure('key_press')\n    );\n    canvas_div.addEventListener(\n        'keyup',\n        on_keyboard_event_closure('key_release')\n    );\n\n    this._canvas_extra_style(canvas_div);\n    this.root.appendChild(canvas_div);\n\n    var canvas = (this.canvas = document.createElement('canvas'));\n    canvas.classList.add('mpl-canvas');\n    canvas.setAttribute('style', 'box-sizing: content-box;');\n\n    this.context = canvas.getContext('2d');\n\n    var backingStore =\n        this.context.backingStorePixelRatio ||\n        this.context.webkitBackingStorePixelRatio ||\n        this.context.mozBackingStorePixelRatio ||\n        this.context.msBackingStorePixelRatio ||\n        this.context.oBackingStorePixelRatio ||\n        this.context.backingStorePixelRatio ||\n        1;\n\n    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n        'canvas'\n    ));\n    rubberband_canvas.setAttribute(\n        'style',\n        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n    );\n\n    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n    if (this.ResizeObserver === undefined) {\n        if (window.ResizeObserver !== undefined) {\n            this.ResizeObserver = window.ResizeObserver;\n        } else {\n            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n            this.ResizeObserver = obs.ResizeObserver;\n        }\n    }\n\n    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n        var nentries = entries.length;\n        for (var i = 0; i < nentries; i++) {\n            var entry = entries[i];\n            var width, height;\n            if (entry.contentBoxSize) {\n                if (entry.contentBoxSize instanceof Array) {\n                    // Chrome 84 implements new version of spec.\n                    width = entry.contentBoxSize[0].inlineSize;\n                    height = entry.contentBoxSize[0].blockSize;\n                } else {\n                    // Firefox implements old version of spec.\n                    width = entry.contentBoxSize.inlineSize;\n                    height = entry.contentBoxSize.blockSize;\n                }\n            } else {\n                // Chrome <84 implements even older version of spec.\n                width = entry.contentRect.width;\n                height = entry.contentRect.height;\n            }\n\n            // Keep the size of the canvas and rubber band canvas in sync with\n            // the canvas container.\n            if (entry.devicePixelContentBoxSize) {\n                // Chrome 84 implements new version of spec.\n                canvas.setAttribute(\n                    'width',\n                    entry.devicePixelContentBoxSize[0].inlineSize\n                );\n                canvas.setAttribute(\n                    'height',\n                    entry.devicePixelContentBoxSize[0].blockSize\n                );\n            } else {\n                canvas.setAttribute('width', width * fig.ratio);\n                canvas.setAttribute('height', height * fig.ratio);\n            }\n            canvas.setAttribute(\n                'style',\n                'width: ' + width + 'px; height: ' + height + 'px;'\n            );\n\n            rubberband_canvas.setAttribute('width', width);\n            rubberband_canvas.setAttribute('height', height);\n\n            // And update the size in Python. We ignore the initial 0/0 size\n            // that occurs as the element is placed into the DOM, which should\n            // otherwise not happen due to the minimum size styling.\n            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n                fig.request_resize(width, height);\n            }\n        }\n    });\n    this.resizeObserverInstance.observe(canvas_div);\n\n    function on_mouse_event_closure(name) {\n        return function (event) {\n            return fig.mouse_event(event, name);\n        };\n    }\n\n    rubberband_canvas.addEventListener(\n        'mousedown',\n        on_mouse_event_closure('button_press')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseup',\n        on_mouse_event_closure('button_release')\n    );\n    rubberband_canvas.addEventListener(\n        'dblclick',\n        on_mouse_event_closure('dblclick')\n    );\n    // Throttle sequential mouse events to 1 every 20ms.\n    rubberband_canvas.addEventListener(\n        'mousemove',\n        on_mouse_event_closure('motion_notify')\n    );\n\n    rubberband_canvas.addEventListener(\n        'mouseenter',\n        on_mouse_event_closure('figure_enter')\n    );\n    rubberband_canvas.addEventListener(\n        'mouseleave',\n        on_mouse_event_closure('figure_leave')\n    );\n\n    canvas_div.addEventListener('wheel', function (event) {\n        if (event.deltaY < 0) {\n            event.step = 1;\n        } else {\n            event.step = -1;\n        }\n        on_mouse_event_closure('scroll')(event);\n    });\n\n    canvas_div.appendChild(canvas);\n    canvas_div.appendChild(rubberband_canvas);\n\n    this.rubberband_context = rubberband_canvas.getContext('2d');\n    this.rubberband_context.strokeStyle = '#000000';\n\n    this._resize_canvas = function (width, height, forward) {\n        if (forward) {\n            canvas_div.style.width = width + 'px';\n            canvas_div.style.height = height + 'px';\n        }\n    };\n\n    // Disable right mouse context menu.\n    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n        event.preventDefault();\n        return false;\n    });\n\n    function set_focus() {\n        canvas.focus();\n        canvas_div.focus();\n    }\n\n    window.setTimeout(set_focus, 100);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'mpl-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'mpl-button-group';\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'mpl-button-group';\n            continue;\n        }\n\n        var button = (fig.buttons[name] = document.createElement('button'));\n        button.classList = 'mpl-widget';\n        button.setAttribute('role', 'button');\n        button.setAttribute('aria-disabled', 'false');\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n        var icon_img = document.createElement('img');\n        icon_img.src = '_images/' + image + '.png';\n        icon_img.srcset = '_images/' + image + '_large.png 2x';\n        icon_img.alt = tooltip;\n        button.appendChild(icon_img);\n\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    var fmt_picker = document.createElement('select');\n    fmt_picker.classList = 'mpl-widget';\n    toolbar.appendChild(fmt_picker);\n    this.format_dropdown = fmt_picker;\n\n    for (var ind in mpl.extensions) {\n        var fmt = mpl.extensions[ind];\n        var option = document.createElement('option');\n        option.selected = fmt === mpl.default_extension;\n        option.innerHTML = fmt;\n        fmt_picker.appendChild(option);\n    }\n\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n};\n\nmpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n    // which will in turn request a refresh of the image.\n    this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n    properties['type'] = type;\n    properties['figure_id'] = this.id;\n    this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n    if (!this.waiting) {\n        this.waiting = true;\n        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    var format_dropdown = fig.format_dropdown;\n    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n    fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n    var size = msg['size'];\n    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n        fig._resize_canvas(size[0], size[1], msg['forward']);\n        fig.send_message('refresh', {});\n    }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n    var x0 = msg['x0'] / fig.ratio;\n    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n    var x1 = msg['x1'] / fig.ratio;\n    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n    x0 = Math.floor(x0) + 0.5;\n    y0 = Math.floor(y0) + 0.5;\n    x1 = Math.floor(x1) + 0.5;\n    y1 = Math.floor(y1) + 0.5;\n    var min_x = Math.min(x0, x1);\n    var min_y = Math.min(y0, y1);\n    var width = Math.abs(x1 - x0);\n    var height = Math.abs(y1 - y0);\n\n    fig.rubberband_context.clearRect(\n        0,\n        0,\n        fig.canvas.width / fig.ratio,\n        fig.canvas.height / fig.ratio\n    );\n\n    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n    // Updates the figure title.\n    fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n    fig.rubberband_canvas.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n    fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n    // Request the server to send over a new figure.\n    fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n    fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n    for (var key in msg) {\n        if (!(key in fig.buttons)) {\n            continue;\n        }\n        fig.buttons[key].disabled = !msg[key];\n        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n    }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n    if (msg['mode'] === 'PAN') {\n        fig.buttons['Pan'].classList.add('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    } else if (msg['mode'] === 'ZOOM') {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.add('active');\n    } else {\n        fig.buttons['Pan'].classList.remove('active');\n        fig.buttons['Zoom'].classList.remove('active');\n    }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Called whenever the canvas gets updated.\n    this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n    return function socket_on_message(evt) {\n        if (evt.data instanceof Blob) {\n            var img = evt.data;\n            if (img.type !== 'image/png') {\n                /* FIXME: We get \"Resource interpreted as Image but\n                 * transferred with MIME type text/plain:\" errors on\n                 * Chrome.  But how to set the MIME type?  It doesn't seem\n                 * to be part of the websocket stream */\n                img.type = 'image/png';\n            }\n\n            /* Free the memory for the previous frames */\n            if (fig.imageObj.src) {\n                (window.URL || window.webkitURL).revokeObjectURL(\n                    fig.imageObj.src\n                );\n            }\n\n            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n                img\n            );\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        } else if (\n            typeof evt.data === 'string' &&\n            evt.data.slice(0, 21) === 'data:image/png;base64'\n        ) {\n            fig.imageObj.src = evt.data;\n            fig.updated_canvas_event();\n            fig.waiting = false;\n            return;\n        }\n\n        var msg = JSON.parse(evt.data);\n        var msg_type = msg['type'];\n\n        // Call the  \"handle_{type}\" callback, which takes\n        // the figure and JSON message as its only arguments.\n        try {\n            var callback = fig['handle_' + msg_type];\n        } catch (e) {\n            console.log(\n                \"No handler for the '\" + msg_type + \"' message type: \",\n                msg\n            );\n            return;\n        }\n\n        if (callback) {\n            try {\n                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n                callback(fig, msg);\n            } catch (e) {\n                console.log(\n                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n                    e,\n                    e.stack,\n                    msg\n                );\n            }\n        }\n    };\n};\n\n// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.findpos = function (e) {\n    //this section is from http://www.quirksmode.org/js/events_properties.html\n    var targ;\n    if (!e) {\n        e = window.event;\n    }\n    if (e.target) {\n        targ = e.target;\n    } else if (e.srcElement) {\n        targ = e.srcElement;\n    }\n    if (targ.nodeType === 3) {\n        // defeat Safari bug\n        targ = targ.parentNode;\n    }\n\n    // pageX,Y are the mouse positions relative to the document\n    var boundingRect = targ.getBoundingClientRect();\n    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n\n    return { x: x, y: y };\n};\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * https://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n    return Object.keys(original).reduce(function (obj, key) {\n        if (typeof original[key] !== 'object') {\n            obj[key] = original[key];\n        }\n        return obj;\n    }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n    var canvas_pos = mpl.findpos(event);\n\n    if (name === 'button_press') {\n        this.canvas.focus();\n        this.canvas_div.focus();\n    }\n\n    var x = canvas_pos.x * this.ratio;\n    var y = canvas_pos.y * this.ratio;\n\n    this.send_message(name, {\n        x: x,\n        y: y,\n        button: event.button,\n        step: event.step,\n        guiEvent: simpleKeys(event),\n    });\n\n    /* This prevents the web browser from automatically changing to\n     * the text insertion cursor when the button is pressed.  We want\n     * to control all of the cursor setting manually through the\n     * 'cursor' event from matplotlib */\n    event.preventDefault();\n    return false;\n};\n\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n    // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n    // Prevent repeat events\n    if (name === 'key_press') {\n        if (event.key === this._key) {\n            return;\n        } else {\n            this._key = event.key;\n        }\n    }\n    if (name === 'key_release') {\n        this._key = null;\n    }\n\n    var value = '';\n    if (event.ctrlKey && event.key !== 'Control') {\n        value += 'ctrl+';\n    }\n    else if (event.altKey && event.key !== 'Alt') {\n        value += 'alt+';\n    }\n    else if (event.shiftKey && event.key !== 'Shift') {\n        value += 'shift+';\n    }\n\n    value += 'k' + event.key;\n\n    this._key_event_extra(event, name);\n\n    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n    return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n    if (name === 'download') {\n        this.handle_save(this, null);\n    } else {\n        this.send_message('toolbar_button', { name: name });\n    }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n    this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n    // Create a \"websocket\"-like object which calls the given IPython comm\n    // object with the appropriate methods. Currently this is a non binary\n    // socket, so there is still some room for performance tuning.\n    var ws = {};\n\n    ws.binaryType = comm.kernel.ws.binaryType;\n    ws.readyState = comm.kernel.ws.readyState;\n    function updateReadyState(_event) {\n        if (comm.kernel.ws) {\n            ws.readyState = comm.kernel.ws.readyState;\n        } else {\n            ws.readyState = 3; // Closed state.\n        }\n    }\n    comm.kernel.ws.addEventListener('open', updateReadyState);\n    comm.kernel.ws.addEventListener('close', updateReadyState);\n    comm.kernel.ws.addEventListener('error', updateReadyState);\n\n    ws.close = function () {\n        comm.close();\n    };\n    ws.send = function (m) {\n        //console.log('sending', m);\n        comm.send(m);\n    };\n    // Register the callback with on_msg.\n    comm.on_msg(function (msg) {\n        //console.log('receiving', msg['content']['data'], msg);\n        var data = msg['content']['data'];\n        if (data['blob'] !== undefined) {\n            data = {\n                data: new Blob(msg['buffers'], { type: data['blob'] }),\n            };\n        }\n        // Pass the mpl event to the overridden (by mpl) onmessage function.\n        ws.onmessage(data);\n    });\n    return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n    // This is the function which gets called when the mpl process\n    // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n    var id = msg.content.data.id;\n    // Get hold of the div created by the display call when the Comm\n    // socket was opened in Python.\n    var element = document.getElementById(id);\n    var ws_proxy = comm_websocket_adapter(comm);\n\n    function ondownload(figure, _format) {\n        window.open(figure.canvas.toDataURL());\n    }\n\n    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n    // web socket which is closed, not our websocket->open comm proxy.\n    ws_proxy.onopen();\n\n    fig.parent_element = element;\n    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n    if (!fig.cell_info) {\n        console.error('Failed to find cell for figure', id, fig);\n        return;\n    }\n    fig.cell_info[0].output_area.element.on(\n        'cleared',\n        { fig: fig },\n        fig._remove_fig_handler\n    );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n    var width = fig.canvas.width / fig.ratio;\n    fig.cell_info[0].output_area.element.off(\n        'cleared',\n        fig._remove_fig_handler\n    );\n    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n    // Update the output cell to use the data from the current canvas.\n    fig.push_to_output();\n    var dataURL = fig.canvas.toDataURL();\n    // Re-enable the keyboard manager in IPython - without this line, in FF,\n    // the notebook keyboard shortcuts fail.\n    IPython.keyboard_manager.enable();\n    fig.parent_element.innerHTML =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n    fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n    fig.send_message('closing', msg);\n    // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n    // Turn the data on the canvas into data in the output cell.\n    var width = this.canvas.width / this.ratio;\n    var dataURL = this.canvas.toDataURL();\n    this.cell_info[1]['text/html'] =\n        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n    // Tell IPython that the notebook contents must change.\n    IPython.notebook.set_dirty(true);\n    this.send_message('ack', {});\n    var fig = this;\n    // Wait a second, then push the new image to the DOM so\n    // that it is saved nicely (might be nice to debounce this).\n    setTimeout(function () {\n        fig.push_to_output();\n    }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n    var fig = this;\n\n    var toolbar = document.createElement('div');\n    toolbar.classList = 'btn-toolbar';\n    this.root.appendChild(toolbar);\n\n    function on_click_closure(name) {\n        return function (_event) {\n            return fig.toolbar_button_onclick(name);\n        };\n    }\n\n    function on_mouseover_closure(tooltip) {\n        return function (event) {\n            if (!event.currentTarget.disabled) {\n                return fig.toolbar_button_onmouseover(tooltip);\n            }\n        };\n    }\n\n    fig.buttons = {};\n    var buttonGroup = document.createElement('div');\n    buttonGroup.classList = 'btn-group';\n    var button;\n    for (var toolbar_ind in mpl.toolbar_items) {\n        var name = mpl.toolbar_items[toolbar_ind][0];\n        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n        var image = mpl.toolbar_items[toolbar_ind][2];\n        var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n        if (!name) {\n            /* Instead of a spacer, we start a new button group. */\n            if (buttonGroup.hasChildNodes()) {\n                toolbar.appendChild(buttonGroup);\n            }\n            buttonGroup = document.createElement('div');\n            buttonGroup.classList = 'btn-group';\n            continue;\n        }\n\n        button = fig.buttons[name] = document.createElement('button');\n        button.classList = 'btn btn-default';\n        button.href = '#';\n        button.title = name;\n        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n        button.addEventListener('click', on_click_closure(method_name));\n        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n        buttonGroup.appendChild(button);\n    }\n\n    if (buttonGroup.hasChildNodes()) {\n        toolbar.appendChild(buttonGroup);\n    }\n\n    // Add the status bar.\n    var status_bar = document.createElement('span');\n    status_bar.classList = 'mpl-message pull-right';\n    toolbar.appendChild(status_bar);\n    this.message = status_bar;\n\n    // Add the close button to the window.\n    var buttongrp = document.createElement('div');\n    buttongrp.classList = 'btn-group inline pull-right';\n    button = document.createElement('button');\n    button.classList = 'btn btn-mini btn-primary';\n    button.href = '#';\n    button.title = 'Stop Interaction';\n    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n    button.addEventListener('click', function (_evt) {\n        fig.handle_close(fig, {});\n    });\n    button.addEventListener(\n        'mouseover',\n        on_mouseover_closure('Stop Interaction')\n    );\n    buttongrp.appendChild(button);\n    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n    var fig = event.data.fig;\n    if (event.target !== this) {\n        // Ignore bubbled events from children.\n        return;\n    }\n    fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n    // this is important to make the div 'focusable\n    el.setAttribute('tabindex', 0);\n    // reach out to IPython and tell the keyboard manager to turn it's self\n    // off when our div gets focus\n\n    // location in version 3\n    if (IPython.notebook.keyboard_manager) {\n        IPython.notebook.keyboard_manager.register_events(el);\n    } else {\n        // location in version 2\n        IPython.keyboard_manager.register_events(el);\n    }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n    // Check for shift+enter\n    if (event.shiftKey && event.which === 13) {\n        this.canvas_div.blur();\n        // select the cell after this one\n        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n        IPython.notebook.select(index + 1);\n    }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n    fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n    // Return the cell and output element which can be found *uniquely* in the notebook.\n    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n    // IPython event is triggered only after the cells have been serialised, which for\n    // our purposes (turning an active figure into a static one), is too late.\n    var cells = IPython.notebook.get_cells();\n    var ncells = cells.length;\n    for (var i = 0; i < ncells; i++) {\n        var cell = cells[i];\n        if (cell.cell_type === 'code') {\n            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n                var data = cell.output_area.outputs[j];\n                if (data.data) {\n                    // IPython >= 3 moved mimebundle to data attribute of output\n                    data = data.data;\n                }\n                if (data['text/html'] === html_output) {\n                    return [cell, data, j];\n                }\n            }\n        }\n    }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n    IPython.notebook.kernel.comm_manager.register_target(\n        'matplotlib',\n        mpl.mpl_figure_comm\n    );\n}\n",
       "text/plain": [
        "<IPython.core.display.Javascript object>"
       ]
@@ -1258,7 +303,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3.10.6 ('paseos')",
    "language": "python",
    "name": "python3"
   },
@@ -1272,11 +317,11 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.10.6"
   },
   "vscode": {
    "interpreter": {
-    "hash": "7148ca98b4bc5b9a0cc0620a9891cc313cafe70c4a658144d5498dd944104066"
+    "hash": "cec805858b69cacb2b7ad611a1d16c309b9d5c2fd3283013a8f0cd0423ba3fc5"
    }
   }
  },
diff --git a/paseos/__init__.py b/paseos/__init__.py
index a39802be..59f88cfb 100644
--- a/paseos/__init__.py
+++ b/paseos/__init__.py
@@ -1,5 +1,6 @@
 from loguru import logger
 from .utils.load_default_cfg import load_default_cfg
+from .utils.check_cfg import check_cfg
 from .paseos import PASEOS
 from .actors.base_actor import BaseActor
 from .actors.actor_builder import ActorBuilder
@@ -29,6 +30,8 @@ def init_sim(local_actor: BaseActor, cfg=None):
     logger.debug("Initializing simulation.")
     if cfg is None:
         cfg = load_default_cfg()
+    else:
+        check_cfg(cfg)
     sim = PASEOS(local_actor=local_actor, cfg=cfg)
     return sim
 
diff --git a/paseos/resources/default_cfg.toml b/paseos/resources/default_cfg.toml
index 71341754..41faf6ef 100644
--- a/paseos/resources/default_cfg.toml
+++ b/paseos/resources/default_cfg.toml
@@ -1,14 +1,8 @@
 [sim]
-start_time = 0 # [s] Start time of the simulation in seconds after MJD2000
-dt = 10 # [s] Maximal Internal timestep used for computing charging, etc.
-activity_timestep = 1 # [s] Internal timestep at which activities update, try to charge and discharge etc. 
+start_time = 0.0 # [s] Start time of the simulation in seconds after MJD2000
+dt = 10.0 # [s] Maximal Internal timestep used for computing charging, etc.
+activity_timestep = 1.0 # [s] Internal timestep at which activities update, try to charge and discharge etc. 
 time_multiplier = 1.0 # [unitless] Defines how much real time passes 
 
 [io]
-logging_interval = 10 # [s] after how many seconds should paseos log the actor status
-
-[power]
-
-[comms]
-
-[radiation]
+logging_interval = 10.0 # [s] after how many seconds should paseos log the actor status
\ No newline at end of file
diff --git a/paseos/utils/check_cfg.py b/paseos/utils/check_cfg.py
new file mode 100644
index 00000000..c858075a
--- /dev/null
+++ b/paseos/utils/check_cfg.py
@@ -0,0 +1,105 @@
+from dotmap import DotMap
+from loguru import logger
+
+
+def check_cfg(cfg: DotMap):
+    """This function validates that all required entries are in the config.
+
+    Args:
+        cfg (DotMap): Run config you intend to use.
+    """
+    major_categories = ["sim", "io"]
+    _check_for_keys(cfg, major_categories)
+    _check_entry_types(cfg, major_categories)
+    _check_value_ranges(cfg, major_categories)
+    logger.debug("Config validated successfully.")
+
+
+def _check_for_keys(cfg: DotMap, major_categories: list) -> None:
+    """Checks that all required keys are present in the config"""
+    required_keys = [
+        "start_time",
+        "dt",
+        "activity_timestep",
+        "time_multiplier",
+        "logging_interval",
+    ]
+    # Check only expected categories are there that are expected
+    for key in cfg.keys():
+        if key not in major_categories:
+            raise KeyError(f"Found unexpected category in cfg: {key}")
+
+    # Check required keys are there
+    for key in required_keys:
+        key_found = False
+        for category in major_categories:
+            if key in cfg[category]:
+                key_found = True
+        if not key_found:
+            raise KeyError(f"CFG missing required key: {key}")
+
+    # Check no other keys are there (to e.g. catch typos)
+    for category in major_categories:
+        for key in cfg[category].keys():
+            if key not in required_keys:
+                raise KeyError(
+                    f"CFG Key {key} is not a valid key. Valid are {required_keys}"
+                )
+
+
+def _check_entry_types(cfg: DotMap, major_categories: list) -> None:
+    """Check that all entries in the config are of the correct type"""
+    # fmt: off
+    integer_keys = [] # noqa
+    float_keys = ["start_time","dt","activity_timestep","time_multiplier","logging_interval",] # noqa
+    boolean_keys = [] # noqa
+    string_keys = [] # noqa
+    list_keys = []
+    # fmt: on
+
+    for key in integer_keys:
+        for category in major_categories:
+            if key in cfg[category].keys() and not isinstance(cfg[category][key], int):
+                raise TypeError(f"{key} must be an integer")
+
+    for key in float_keys:
+        for category in major_categories:
+            if key in cfg[category].keys() and not isinstance(
+                cfg[category][key], float
+            ):
+                raise TypeError(f"{key} must be a float")
+
+    for key in boolean_keys:
+        for category in major_categories:
+            if key in cfg[category].keys() and not isinstance(cfg[category][key], bool):
+                raise TypeError(f"{key} must be a boolean")
+
+    for key in string_keys:
+        for category in major_categories:
+            if key in cfg[category].keys() and not isinstance(cfg[category][key], str):
+                raise TypeError(f"{key} must be a string")
+
+    for key in list_keys:
+        for category in major_categories:
+            if key in cfg[category].keys() and not isinstance(cfg[category][key], list):
+                raise TypeError(f"{key} must be a list")
+
+
+def _check_value_ranges(cfg: DotMap, major_categories: list) -> None:
+    """Check that all values in the config are within the correct range.
+    This throws runtime errors as ValueErrors are caught in training to avoid NaNs crashing the training."""
+
+    # fmt: off
+    positive_value_keys = ["dt","activity_timestep","time_multiplier","logging_interval",] # noqa
+    positive_or_zero_value_keys = ["start_time"] # noqa
+    # fmt: on
+
+    for key in positive_value_keys:
+        for category in major_categories:
+            if key in cfg[category].keys() and not (cfg[category][key] > 0):
+                raise RuntimeError(f"{key} must be a positive integer")
+
+    for key in positive_or_zero_value_keys:
+        for category in major_categories:
+            if key in cfg[category].keys() and not (cfg[category][key] >= 0):
+                raise RuntimeError(f"{key} must be a positive or zero integer")


Test patch:
diff --git a/paseos/tests/default_cfg_test.py b/paseos/tests/default_cfg_test.py
new file mode 100644
index 00000000..f1205da8
--- /dev/null
+++ b/paseos/tests/default_cfg_test.py
@@ -0,0 +1,17 @@
+"""Tests whether the default cfg passes validation."""
+
+import paseos
+import pykep as pk
+from paseos import load_default_cfg, ActorBuilder, SpacecraftActor
+
+
+def test_default_cfg():
+    """Load default cfg and check it."""
+
+    # Need some actor to init paseos
+    earth = pk.planet.jpl_lp("earth")
+    sat1 = ActorBuilder.get_actor_scaffold("sat1", SpacecraftActor, pk.epoch(0))
+    ActorBuilder.set_orbit(sat1, [10000000, 0, 0], [0, 8000.0, 0], pk.epoch(0), earth)
+
+    cfg = load_default_cfg()
+    _ = paseos.init_sim(sat1, cfg)
diff --git a/paseos/tests/operations_monitor_test.py b/paseos/tests/operations_monitor_test.py
index bc25c586..4da86ba7 100644
--- a/paseos/tests/operations_monitor_test.py
+++ b/paseos/tests/operations_monitor_test.py
@@ -27,7 +27,7 @@ async def test_monitor():
     cfg.sim.dt = 0.1  # setting lower timestep to run things quickly
     cfg.sim.activity_timestep = 0.1
     cfg.io.logging_interval = 0.25  # log every 0.25 seconds
-    cfg.sim.time_multiplier = 10  # speed up execution for convenience
+    cfg.sim.time_multiplier = 10.0  # speed up execution for convenience
     sim = paseos.init_sim(sat1, cfg)
 
     async def func1(args):
diff --git a/paseos/tests/thermal_model_test.py b/paseos/tests/thermal_model_test.py
index 972d61ea..2c9977b0 100644
--- a/paseos/tests/thermal_model_test.py
+++ b/paseos/tests/thermal_model_test.py
@@ -37,7 +37,7 @@ async def test_thermal():
     cfg.sim.dt = 5.0  # setting higher timestep to run things quickly
     cfg.sim.activity_timestep = 1.0
     cfg.io.logging_interval = 10.0  # log every 0.25 seconds
-    cfg.sim.time_multiplier = 200  # speed up execution for convenience
+    cfg.sim.time_multiplier = 200.0  # speed up execution for convenience
     sim = paseos.init_sim(sat1, cfg)
 
     # Initial temperature is 0C / 273.15K
diff --git a/paseos/tests/time_multiplier_test.py b/paseos/tests/time_multiplier_test.py
index 97d136eb..9866cee9 100644
--- a/paseos/tests/time_multiplier_test.py
+++ b/paseos/tests/time_multiplier_test.py
@@ -23,7 +23,7 @@ async def test_activity():
     # init simulation
 
     cfg = load_default_cfg()  # loading cfg to modify defaults
-    cfg.sim.time_multiplier = 10
+    cfg.sim.time_multiplier = 10.0
     sim = paseos.init_sim(sat1, cfg)
 
     # Initial power is 500