Why NBDiff should exist

bugfix-diff.txt

diff --git a/IPythonReviewTime.ipynb b/IPythonReviewTime.ipynb
index 803d4ac..09b5662 100644
--- a/IPythonReviewTime.ipynb
+++ b/IPythonReviewTime.ipynb
@@ -162,7 +162,7 @@
        "output_type": "pyout",
        "prompt_number": 6,
        "text": [
-        "<matplotlib.collections.LineCollection at 0x80e5f50>"
+        "<matplotlib.collections.LineCollection at 0x8f86f50>"
        ]
       },
       {
@@ -170,7 +170,7 @@
        "output_type": "display_data",
        "png": 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l5ubWRxYAAAAAwBnwaVfMyy67TK1atdIvfvELSScO3Nu6dWudhwMAAAAAeOe1\n2I0fP16vvvqqunbt6nGMHQAAAAAgMHgtdpGRkUpNTa2PLAAAAACAM+D1OnZ33323Dhw4oGHDhqlR\no0YnnmRZ9XpWTK5j50/BNS8BAACAc8FZX8fu8OHDatSokdavX+8xnMsdAAAAAEBg8LrFLhCwxc6f\ngmteAgAAAOeCs95i991332n27NnauXOnjh8/7n7R7Oxs/6UEAAAAAJwxr8Vu+PDhmjBhgoYNG+Y+\nKyYXKwcAAACAwOG12J133nn69a9/XR9ZAAAAAABnwOsxdosXL9aOHTs0ZMgQ9wXKJalnz551Hu4k\njrHzp+CalwAAAMC54KyPsfvyyy+1ePFivffeex4XKH/vvff8kxAAAAAAcFa8brHr1KmTvvrqK/c1\n7JzAFjt/Cq55CQAAAJwLvHWikFof+T/dunVTaWmpX0MBAAAAAPzH666YpaWlSkhI0KWXXuo+xo7L\nHQAAAABA4PBa7KZPny7px0sc2LbN5Q4AAAAAIIB4PcZOkoqLi7Vp0yZZlqXk5GRFRkbWRzY3jrHz\np+CalwAAAMC54KyPsVu+fLn69OmjFStWaPny5UpOTtaKFSv8GhIAAAAAcOa8brHr3r27/vd//9e9\nlW7v3r0aMGCAtm7dWi8BJbbY+VdwzUsAAADgXHDWW+xs21bLli3d9y+88EK+dAMAAABAAPFa7K69\n9loNGTJEr7zyihYsWKDrrrtOQ4cOrXX8/Px8XX311erSpYu6du2qWbNmSZL279+vQYMGqXPnzho8\neLAOHDjgfs6MGTMUHx+vhIQErV+/3g9vCwAAAADOHbXuirl9+3aVlJToyiuv1Ouvv64PP/xQktSs\nWTPdcsstiouLq/EFi4uLVVxcrB49eujQoUPq1auXVq1apQULFqhFixZ68MEH9cwzz6i0tFRZWVnK\nzc3VLbfcok2bNqmgoEADBw7Utm3bFBLyY+dkV0x/Cq55CQAAAJwLvHWiWi93cO+992rGjBmSpJEj\nR2rkyJGSpK1bt+q+++7TmjVranxeq1at1KpVK0lSkyZNdPHFF6ugoEDZ2dl6//33JUkZGRlKSUlR\nVlaWVq9erfT0dDVs2FCxsbGKi4tTTk6O+vbt6/G6mZmZ7r9TUlKUkpLi/d0DAAAAgIFcLpdcLpfP\n49da7EpKStS9e/dqw7t37668vDyfXnznzp3avHmz+vTpo5KSEkVFRUmSoqKiVFJSIkkqLCz0KHEx\nMTEqKCgaYuCsAAAgAElEQVSo9lqnFjsAAAAACGY/3Zh18vritan1GLtTj4H7qaNHj3oNcujQIY0c\nOVIzZ85UWFiYx2OWZZ32IudcAB0AAAAAfFdrsevdu7deeumlasNffvll9erV67QveuzYMY0cOVJj\nxozR8OHDJZ3YSldcXCxJKioqcl8+ITo6Wvn5+e7n7tmzR9HR0T//neCcEx7e3P0jQX3fwsObO/32\nAQAAALdaT55SXFysm266SY0aNXIXuU8//VT/+c9/tHLlSrVu3brGF7RtWxkZGbrwwgv1wgsvuIc/\n+OCDuvDCC/XQQw8pKytLBw4c8Dh5Sk5OjvvkKd9++63HVjtOnuJPwTMvTcgIAAAA+IO3TnTaC5Tb\ntq333ntPX3zxhSzLUpcuXXTNNdecdoIbNmzQVVddpe7du7vL2YwZM5ScnKy0tDTt3r1bsbGxWr58\nuZo1ayZJevrppzV//nyFhoZq5syZGjJkyM96E6eOZ8IXfRNyktHr1Cl2AAAAqDdnVewCBcXOn4Jn\nXpqQEQAAAPAHb53I6wXKAQAAAACBjWIHAAAAAIaj2AEAAACA4Wq9QDkA/wgPb67y8lJHph0WFqGy\nsv2OTBsAAAD1h5On+A0nT/Gf4MkomZMTAAAAgYuTpwAAAABAkKPYAQAAAIDhKHYAAAAAYDiKHQAA\nAAAYjmIHAAAAAIbjcgcAjLgkgwkZAQAAnMLlDvwmuE5/T0avU2d5+03wZAQAAKgrXO4AAAAAAIIc\nxQ4AAAAADEexAwAAAADDUewAAAAAwHAUOwAAAAAwHMUOAAAAAAxHsQMAAAAAw3GBcgDwIy6kDgAA\nnECxAwA/OlHqnLmYeXm55ch0AQCA89gVEwAAAAAMR7EDAAAAAMNR7AAAAADAcBQ7AAAAADAcxQ4A\nAAAADEexAwAAAADDUewAAAAAwHB+L3a33367oqKi1K1bN/ewzMxMxcTEKCkpSUlJSVq7dq37sRkz\nZig+Pl4JCQlav369v+MAAAAAQNDze7EbN26c1q1b5zHMsixNnTpVmzdv1ubNmzV06FBJUm5urpYt\nW6bc3FytW7dOd999t6qqqvwdCQAAAACCmt+LXb9+/RQREVFtuG3b1YatXr1a6enpatiwoWJjYxUX\nF6ecnBx/RwIAAACAoBZaXxOaPXu2Fi1apN69e+u5555Ts2bNVFhYqL59+7rHiYmJUUFBQY3Pz8zM\ndP+dkpKilJSUOk4MAAAAAM5wuVxyuVw+j18vxW7ixIl67LHHJEmPPvqo7r//fs2bN6/GcS3LqnH4\nqcUOAAAAAILZTzdmTZ8+/bTj18tZMSMjI2VZlizL0oQJE9y7W0ZHRys/P9893p49exQdHV0fkQAA\nAAAgaNRLsSsqKnL/vXLlSvcZM1NTU7V06VJVVFQoLy9P27dvV3Jycn1EAgAAAICg4fddMdPT0/X+\n++/rhx9+UNu2bTV9+nS5XC5t2bJFlmWpQ4cOmjt3riQpMTFRaWlpSkxMVGhoqObMmVPrrpgAAAAA\ngJpZdk2nqwwwlmXVeFbNmsaTnHo7vmWUzMhJRq9TZ3n7TfBklMzJCQAAzOKtE9XLrpgAAAAAgLpD\nsQMAAAAAw9XbdewAAIEhPLy5ystLHZl2WFiEysr2OzJtAACCGcUOAM4xJ0qdM8filZf7doIsyicA\nAD8PxQ4AEHBMKJ8AAAQSjrEDAAAAAMOxxQ4AgDPELqMAgEBBsQMA4AyxyygAIFCwKyYAAAAAGI5i\nBwAAAACGo9gBAAAAgOEodgAAAABgOE6eAgBAEOPMnQBwbqDYAQAQxEw4cyflEwDOHsUOAAA4yoTy\nCQCBjmPsAAAAAMBwFDsAAAAAMBzFDgAAAAAMR7EDAAAAAMNR7AAAAADAcBQ7AAAAADAclzsAAADw\ngQnX2zMhI4C6Ydm27cyFY34Gy7LkS0zLsuTUdXAk3zJKZuQko9eps7z9JngySmbkJKPXqbO8/SZ4\nMkpm5DQhI4Az460TscUOAAAA9YatikDdoNgBAACg3pwodc5s2SsvtxyZLlAfOHkKAAAAABiOLXYA\nAADAT7DLKExDsQMAAAB+gl1GYRq/74p5++23KyoqSt26dXMP279/vwYNGqTOnTtr8ODBOnDggPux\nGTNmKD4+XgkJCVq/fr2/4wAAAABBKTy8uSzLcuQWHt7c6bePn/B7sRs3bpzWrVvnMSwrK0uDBg3S\ntm3bNGDAAGVlZUmScnNztWzZMuXm5mrdunW6++67VVVV5e9IAAAAQND5cati/d+c2k0VtfN7sevX\nr58iIiI8hmVnZysjI0OSlJGRoVWrVkmSVq9erfT0dDVs2FCxsbGKi4tTTk6OvyMBAAAAcIApWxVN\nyXk69XKMXUlJiaKioiRJUVFRKikpkSQVFhaqb9++7vFiYmJUUFBQ42tkZma6/05JSVFKSkqd5QUA\nAABw9kw5VjEQc7pcLrlcLp9fp95PnnKymZ7u8ZqcWuwAAAAAIJj9dGPW9OnTTzt+vVzHLioqSsXF\nxZKkoqIiRUZGSpKio6OVn5/vHm/Pnj2Kjo6uj0gAAAAAEDTqpdilpqZq4cKFkqSFCxdq+PDh7uFL\nly5VRUWF8vLytH37diUnJ9dHJAAAAAAIGn7fFTM9PV3vv/++fvjhB7Vt21ZPPPGEpk2bprS0NM2b\nN0+xsbFavny5JCkxMVFpaWlKTExUaGio5syZc9rdNAEAAAAA1Vm2bTtzlODPYFmWfIl5ohQ69XZ8\nyyiZkZOMXqfO8vab4MkomZGTjF6nzvL2m+DJKJmRk4xep87y9pvgySiZkdNbJ6qXXTEBAAAAAHWH\nYgcAAAAAhqPYAQAAAIDhKHYAAAAAYDiKHQAAAAAYjmIHAAAAAIaj2AEAAACA4Sh2AAAAAGA4ih0A\nAAAAGI5iBwAAAACGo9gBAAAAgOEodgAAAABgOIodAAAAABiOYgcAAAAAhqPYAQAAAIDhKHYAAAAA\nYDiKHQAAAAAYjmIHAAAAAIaj2AEAAACA4Sh2AAAAAGA4ih0AAAAAGI5iBwAAAACGo9gBAAAAgOEo\ndgAAAABgOIodAAAAABiOYgcAAAAAhqPYAQAAAIDhKHYAAAAAYLjQ+pxYbGyswsPD1aBBAzVs2FA5\nOTnav3+/Ro0apV27dik2NlbLly9Xs2bN6jMWAAAAABitXrfYWZYll8ulzZs3KycnR5KUlZWlQYMG\nadu2bRowYICysrLqMxIAAAAAGK/ed8W0bdvjfnZ2tjIyMiRJGRkZWrVqVX1HAgAAAACj1euumJZl\naeDAgWrQoIHuvPNO3XHHHSopKVFUVJQkKSoqSiUlJTU+NzMz0/13SkqKUlJS6iExAAAAANQ/l8sl\nl8vl8/iW/dNNaHWoqKhIrVu31t69ezVo0CDNnj1bqampKi0tdY/TvHlz7d+/3zOkZVXb0lcTy7Ik\n1dvb+enUfcoomZGTjF6nzvL2m+DJKJmRk4xep87y9pvgySiZkZOMXqfO8vab4MkomZHTWyeq110x\nW7duLUlq2bKlbrrpJuXk5CgqKkrFxcWSThS/yMjI+owEAAAAAMart2J3+PBhlZeXS5L+/e9/a/36\n9erWrZtSU1O1cOFCSdLChQs1fPjw+ooEAAAAAEGh3o6xKykp0U033SRJOn78uG699VYNHjxYvXv3\nVlpamubNm+e+3AEAAAAAwHf1eozdmeIYO38KnnlpQkbJjJxk9Dp1lrffBE9GyYycZPQ6dZa33wRP\nRsmMnGT0OvWgW94Bc4wdAAAAAMD/KHYAAAAAYDiKHQAAAAAYjmIHAAAAAIaj2AEAAACA4Sh2AAAA\nAGA4ih0AAAAAGI5iBwAAAACGo9gBAAAAgOEodgAAAABgOIodAAAAABiOYgcAAAAAhqPYAQAAAIDh\nKHYAAAAAYDiKHQAAAAAYjmIHAAAAAIaj2AEAAACA4Sh2AAAAAGA4ih0AAAAAGI5iBwAAAACGo9gB\nAAAAgOEodgAAAABgOIodAAAAABiOYgcAAAAAhqPYAQAAAIDhQp0O4LO+faVdu047SqEkqXV9pKlZ\na9+mbUJOMvqA5e0/QZJRMiMnGX3A8vafIMkomZGTjD5geftPkGSUnM35uZ9ex7Jt2/bTa9UZy7Jk\nl5RIlZWnHa91mzY6uVjqXxsVFfo2bRNyktEblrf/BE9GyYycZPSG5e0/wZNRMiMnGb1heftP8GSU\nnM15XG2014dKZlmWTlfdzCl2Pr5Z6WzejktSyhk+17eM0tnmdOnMM0q+5jRhXpqQUWJ5exc8GSWW\nt3fBk1FieXsXPBkllrd3wZNRYnl7FzwZJXOW9+nG4xg7Dy6nA/jA5XQAH7mcDuADl9MBfOByOoCP\nXE4H8IHL6QA+cDkdwEcupwP4wOV0AB+4nA7gI5fTAXzgcjqAD1xOB/CRy+kAPnA5HcAHLqcD+Mjl\ndAAfuJwO4AOX0wEkBVCxW7dunRISEhQfH69nnnnG6TgAAAAAYIyAKHaVlZWaPHmy1q1bp9zcXC1Z\nskRfffWV07EAAAAAwAgBcYzdxo0bNX36dK1bt06SlJWVJUmaNm2apJP7vAIAAADAuet01S0gLndQ\nUFCgtm3buu/HxMTo448/dt8PgO4JAAAAAAErIHbFZIscAAAAAJy5gCh20dHRys/Pd9/Pz89XTEyM\ng4kAAAAAwBwBUex69+6t7du3a+fOnaqoqNCyZcuUmprqdCwAAAAAMEJAHGMXGhqqP/3pTxoyZIgq\nKys1fvx4XXzxxU7HAgAAAAAjBMQWO0kaOnSovvnmG3377bd6+OGHnY4TUPbt2+d0hKDw+eefOx3B\nJyNGjNBbb72lqqoqp6PUyoTPpCnLe9asWSotLXU6hleBPj+nTp2qL7/80ukYXgX6fDwp0HOasA6S\nzFifm7IOqqysdDoCEPAaZGZmZjodwim9evXS8ePHFR8fr/PPP9/pOLW65JJL9MEHH6hJkyaKi4sL\nyJPNmDAvR44cqRdffFHHjx9X586ddd555zkdqUbNmzfXokWL9OCDD6qoqEht27ZVixYtnI7lwYTP\npCnLOzs7W/fcc482bNigsLAwderUifl5Bnbv3q0nn3xSc+fOVWVlpeLj4wMuoxT48/GkQM9pwjpI\nMmN9bso6KC4uTnv27FFMTIxatmzpdJwaTZ06VTExMYqMjHQ6Sq1M+L5mQkYpQHPa57Bt27bZDz/8\nsN2pUyd71KhR9rp16+yqqiqnY1VTWVlp//3vf7dHjRpld+zY0Z42bZr9zTffOB3Lgynz8ptvvrEf\neughu2PHjvbNN99s//3vf3c6Uq1KS0vtF1980Y6OjrYvu+wye/78+XZFRYXTsWzbNuMzadvmLO/K\nykp77dq19qhRo+xOnTrZDz/8sP3tt986HasaE+bnV199ZT/00EN227Zt7fT0dPvdd991OlI1JsxH\n2w7snKasg04K5PW5bZuxDjp48KA9d+5c+7LLLrOTk5PtP//5z/bBgwedjuXhpZdesi+//HL70ksv\ntV988UX7wIEDTkeqxoTvayZktO3AzHlOF7uTKisr7dWrV9tt2rSxY2Ji7Mcee8zet2+f07Fq9M47\n79itW7e2w8PD7auuusr+8MMPnY7kwYR5eezYMXvFihV269at7YSEBLtz5872a6+95nQsDz/88IP9\nwgsv2L169bKHDRtmL1myxJ40aZLdv39/p6NVE+ifSROWt23b9ubNm+1f//rXdufOne277rrL7tGj\nh/3AAw84HauaQJ6fx48ft1euXGmnpqbaPXv2tLOysuwbbrjBTktLczpaNYE8H09lQs5AXweZsj43\nZR1k27b93nvv2W3atLHPP/98e+zYsfb27dudjuTBhB+YTPi+ZkJG2w6snOd8sduyZYt9zz332J07\nd7anTJlib9y40X722WftSy65xOlobnv37rX/+Mc/2j179rSHDh1qv/7663ZFRYW9adMmu3379k7H\ncwv0ebllyxb73nvvtePi4uyJEyfan376qW3btl1QUGC3bdvW4XQ/Gj58uJ2QkGA/9dRTdmFhocdj\nPXv2dCiVJxM+k6Ys75PzcdCgQfayZcvcv+JXVlbaHTt2dDjdjwJ9ft577712p06d7DvuuMP++OOP\nPR7r3LmzQ6mqC/T5eFKg5zRhHWTbZqzPTVkHHTt2zF61apV944032pdccon93HPP2UVFRfaKFSvs\n+Ph4p+O5mfADU6B/X7NtMzLaduDlPKeLXc+ePe2rr77a/utf/2ofOXLE47Hhw4c7lKq6+Ph4e/r0\n6XZ+fn61x2bMmOFAoupMmJdXXXWVvXDhQvvw4cPVHlu4cKEDiWr2zjvvOB3BKxM+k6Ys78cee8ze\nuXNnjY99+eWX9ZymdoE+P+fNm2cfOnSoxsdKS0vrOU3tAn0+nhToOU1YB9m2GetzU9ZBHTp0sMeN\nG1fjFtnJkyc7kKg6E35gMuH7mgkZbTswc1q2bdtOH+fnlB07dqhTp05Ox/CqqqpKISEhKisrk2VZ\nCgsLczpSNabMy//85z/65ptvZFmWLrroIjVq1MjpSNUcOXJEc+bM0YYNG2RZlvr166eJEycG1MkL\nTPhMSmYsb0n69NNPtWHDBoWEhOiKK65Qz549nY5Uo0Cen7Zt64033vD4/2b48OEBeRKIQJ6Ppwrk\nnKasg0xYn0tmrIPKy8sDdjmfNH/+fI0aNUoXXHBBtccOHDigZs2aOZDKkwnf10zIKAVmzoC53IET\nmjZtqilTpigpKUk9e/bUPffcE5CnUP7000/VrVs3devWTV27dtUll1yiTz75xOlYHkyYl2+99Zbi\n4uI0ZcoUTZ48WZ06ddLf/vY3p2NVM3bsWOXm5urXv/61Jk+erC+//FJjxoxxOpYHEz6TpizvJ554\nQrfddpv279+vvXv3aty4cXryySedjlVNoM/Pu+++W3PnzlX37t3VtWtXzZ07V5MmTXI6VjWBPh9P\nCvScJqyDJDPW56asg77//nsNGzZMLVq0UMuWLXXjjTfqu+++czqWh3HjxmndunW67777NHXqVK1c\nuVInt58EQqmTzPi+ZkJGKUBzOrKdMEAMGDDAfuKJJ+zvvvvO3rFjh/3kk0/aAwYMcDpWNV27drX/\n8Y9/uO9/8MEHdrdu3RxMVJ0J87Jz584eB1h/++23AbNrxKkuvvhin4Y5yYTPpCnLOz4+3mMXjsOH\nDwfU8SInBfr8vOiii+zKykr3/crKSvuiiy5yMFHNAn0+nhToOU1YB9m2GetzU9ZBycnJ9qJFi+yK\nigq7oqLCXrx4sZ2cnOx0LA933XWXPWjQIHv+/Pn2vHnz7CFDhtgTJ050OpYHE76vmZDRtgMz5zld\n7Lp06VJtWNeuXR1Icno9evSoNiwpKcmBJLUzYV727t3b435VVVW1YYHg1ltvtT/66CP3/Y0bN9qj\nR492MFF1JnwmTVneKSkp9v79+9339+/fb1999dUOJqpZoM/P66+/3s7Ly3Pfz8vLs6+//nrnAtUi\n0OfjSYGe04R1kG2bsT43ZR1UU3Hv3r27A0lqZ8IPTCZ8XzMho20HZs5QZ7cXOmvw4MFasmSJRo0a\nJUlasWKFBg8e7HCq6vr3768777xT6enpkqRly5apf//++te//iVJAbEvvAnzslevXrruuuuUlpYm\n6UTG3r1764033pAkjRgxwsl4bp988omuuOIKtW3bVpZlaffu3brooovUrVs3WZalrVu3Oh3RiM+k\nKcs7PDxcXbp0cf//8vbbbys5OVlTpkyRZVmaNWuWwwlPCPT5WVZWposvvljJycmyLEs5OTm69NJL\nNWzYMFmWpezsbEfznRTo8/GkQM9pwjpIMmN9bso6aOjQoZoxY4bHMh86dKj2798v6cTF4J0WFxen\n3bt3KzY2VpK0e/duxcXFORvqJ0z4vmZCRikwc57TJ09p0qSJDh8+rJCQE4caVlVVuQ94tSxLZWVl\nTsZzS0lJOe0JAN577716TFMzE+blbbfd5jEfbdv2uL9gwQInYlWzc+fO0z5+8h8MJ5nwmTRleb/y\nyivuvy3Lcuc8+d+MjAznwp0i0Oeny+Wq9THLstS/f//6C3MagT4fTwr0nCasgyQz1uemrINiY2Nr\nXeaWZQXE8XZXXXWVNm3aVO0HpvDw8ID5gcmE72smZJQCM+c5XewAAAAAfzDlByYEr3P6rJgmO7m7\nCc7Om2++6XQEn1x//fVOR/DKhM+kKcv78ccfdzqCT9asWeN0hNO64447nI7gE1M+l4G+vE1YB0lm\nrM9NWQcVFxc7HcFDSkpKrTdKHeoDxe4nkpKSnI7gkxdffNHpCF6ZMC83bdrkdASf/OUvf3E6glcm\nfCZNWd69e/d2OoJPAun08lOnTtWXX37pMezOO+90KM3PY8rnMpCWd01MWAdJ0ssvv+x0BK9MWQeN\nHz/e6QhemfADkwnf10zIKDmfk10xgQAzc+ZM3XPPPV6HAfXp6NGj1S6qXNMwp7z88st65ZVXdOzY\nMd1+++1KT09X06ZNnY5lrEBe3sePH1eXLl30zTffOB3FJ4cPH1Z+fr4uuugip6PUaMOGDbryyiu9\nDsOZ+eSTT4wpyjAfW+wM8MYbb+jAgQPu+wcOHNCqVascTFSzoqIirV69WmvWrAm43SMk6U9/+pNK\nS0vd90tLSzVnzhwHE9Xs1APZT3L6RAU/NWDAAJ+GOeH111/XG2+8oddff73a7eQZ/QLJjh07Av6i\nu5J0+eWX+zTMKXfccYc+/PBDLVq0SDt37lS3bt10yy23BMxJNE5avny5+4D6J598UjfddFNA7kIY\nyMs7NDRUCQkJ2rVrl9NRvMrOzlZSUpKGDBkiSdq8ebNSU1MdTuVpypQpPg1z2saNGz1ORlFWVqaP\nP/7YwUS1O3z4sPvvQCx1gf59TTIjYyA6Jy930KRJk9OeWSlQzrZz0vTp0z1OLd2sWTNlZmZq+PDh\nDqby9Je//EVPPPGErr76aknS5MmT9dhjjwXUbhIvv/yyJk+e7L4fERGhl156SXfffbeDqX60ZMkS\n/c///I/y8vI0bNgw9/Dy8nJdeOGFDib70ZEjR3T48GHt3bvXfYpp6cQ/sAUFBQ4m+9GaNWtOe7Y8\np0/T/lO33HKLJk+e7C6dy5YtU3p6esB8YSkqKlJhYaEOHz6sf/3rX+4z5ZWVlXl8eQkElZWV+vrr\nr/XVV1+pZcuWuuSSS/T888/rz3/+s5YtW+Z0PEknylxaWpo2bNigd955Rw888IDuuusu5eTkOB1N\nkjnLe//+/erSpYuSk5M9zkIXCGcdPFVmZqY+/vhj97+NSUlJAfPDzcaNG/XRRx9p7969ev7553Vy\nB67y8nJVVVU5nK66iRMnevwIcsEFF+iuu+7S5s2bHUzl6aOPPtKECRNUXl6u/Px8bdmyRS+99FJA\n/Yhswve1QM8YyD3inCx2hw4dcjrCz1LT3rKVlZUOJKnd73//e23evNldQPbt26fLLrssYP4nlE6c\nhraqqsp9WtrKykodO3bM4VQ/uvzyy9W6dWvt3btXDzzwgHu5h4eHq3v37g6nO2Hu3LmaOXOmCgsL\n1atXL/fwsLAwj9LspJq2eAayI0eOaMyYMe77o0eP1rPPPutgIk/r16/XK6+8ooKCAt1///3u4WFh\nYXr66acdTObpvvvu05o1a3TNNdfokUceUXJysiTpoYceCqhd4Bo0aCDpxAlT7rjjDt1www169NFH\nHU71I1OW95NPPllt2Ol+0HFKw4YN1axZM49hJ/8NclpFRYXKy8tVWVmp8vJy9/Dw8HC99tprDiar\n3anzrkGDBgH3Xejee+/VunXrdOONN0qSevTooffff9/hVJ5M+L4W6BkDuUeck8Xu1C0NNQmEi1ye\nqlevXpo6daomTZok27b13//93x5fqgNBixYt1KRJE/f9Jk2aqEWLFg4mqm7IkCG6+eabdeedd8q2\nbc2dO1fXXnut07Hc2rdvr/bt2+uf//yndu7cqW+//VYDBw7U4cOHdeTIEYWFhTkdUffee6/uvfde\nzZ49OyB31TlVcXGxHnnkERUUFGjdunXKzc3Vxo0bA+YfhpMC/aK7GRkZysjI0GuvvaZf/vKXjmap\njW3bioiI0GeffebeenOqQNn6KUnR0dH6f//v/+ntt9/WtGnTdPTo0YDaOmLC8pZOnH3wp+vJ48eP\nOx2rmi5duuivf/2rjh8/ru3bt2vWrFkBs0tr//79dcUVV+jzzz834iyYHTp00KxZszRx4kTZtq0X\nX3xRHTt2dDpWNe3atfO4HxoaWF+1Tfi+FugZA7lHnJMnTzndRS4lKS8vrx7TeHfo0CE9+eSTeued\ndyRJgwYN0u9+97sav8DUt+eee06S9Nlnn2nr1q3u3UNXr16t7t27a+HChU7G81BZWamXXnrJYz5O\nmDDB/Qt6oHjppZf08ssva//+/dqxY4e2bdumiRMnunMHguXLl2vo0KEKCwvTk08+qc2bN+t3v/ud\nevbs6XQ0t2uvvVbjxo3TU089pa1bt+rYsWNKSkrSF1984XQ0DyZcdFcK7KJs27a6/X/2zjysqnLt\n/58tOJWi1dHMeThqMg+CiAKiInBE7ZioOILzPFQqlppDllaaSFmJAzkiiOaUiIkTJiIIYpIoKFIO\nKYmKDBqwfn/s316y2Wid9+3tefaBz3V1Xe5Ff3yv/ey11nM/931/bysr6da2IgoKCjh48CDW1ta0\nbduWW7duceHCBXr16iVamh4yrzcYx3MSID8/n6VLlxITEwNoDxjnz58vhQmNDmdnZ06fPi1lxrMs\nv/76K9OmTVP7Znv06EFwcDANGzYUrOwpAwYMYObMmUyZMoUzZ86wevVqEhMTCQ8PFy1NZfjw4fz4\n449qVlG3X7O2tkaj0fDWW28JVii/RpnjiEoZ2FXx17Fw4UL1x63rxSj7b2M4BZQNGxsbEhIScHZ2\nVnsHrKysuHDhgmBlT9HpiYuLY968ebzzzjssXrxYmj4h0DasJyYmYmdnp36Ptra2pKSkCFZmnMge\nKIWPrdkAACAASURBVI8cOZLJkyerJZgyUlxcjKWlJZcuXRIt5Q+Rfb2N4TlZnpKSEh49eiSdW+uE\nCRO4efMmfn5+vPDCC4D2UEm2fmRj4O7du0yfPp3vv/8eRVHo1asXq1evlqZPHrT7NqDCvRvIMcPQ\nGDTKilz54b+Z0tJStm7dyrVr11iwYAHZ2dncvn1bmo3B9OnTCQ4O1jPS0CFLk7ju5pMZPz8/IiMj\nsbKyMvibRqMhNTVVgKpnU7NmTWrWrKl+Li4ulu4kVfY+IdCWbvz222/q5/j4eOk2VKDtsVuzZg1x\ncXFoNBpcXV2ZOHGiVCf6ADk5OQwaNIhly5YB2t4hmUqM4uPj2bJlCy1atNAz05Dp/jY1NaV9+/Zc\nv36dFi1aiJbzXGRfb2N4TgL4+/vz9ddfY2JigqOjIw8ePGD69OnMnj1btDSVoqIiXn75ZWJjY/Wu\nyxLYLV++nDlz5lRY/q/RaFi9erUAVRXToEEDtm3bJlrGczGGfZtO44MHD9BoNJiZmYkV9AxkjCPk\neUoLYNKkSVSrVo3Y2FgWLFhAnTp1mDRpkjRDWEeMGAGg18AuG8YQfAYHBwNat0RjwN3dnaVLl1JQ\nUMDhw4dZs2ZNhd+vSGTvEwJtmXCfPn24evUqLi4u3L17V0pDgBEjRmBmZsa0adNQFIVt27YxfPhw\nIiMjRUvTQ/ZA+dChQ4D+Ca+MGIubo+zrbQzPSYC0tDTMzMzYunUrPj4+LFu2DHt7e6kCO9kNp8zN\nzQEq9BaQLZifNWsW8+fPp3bt2nh7e3P+/Hk+++wzPYMs0eicJsui0WgMAnuRnD17llGjRqnukvXr\n12f9+vXSjY6QMY6o1KWYuhKtsqVaNjY2nD9/XrAy40E3ePPYsWMV/r1bt25/q57/BkpKSli/fr1e\nT8aYMWOkeoHl5+dz6NAhrKyspO4T+v3339Uhxu3bt6d69eqCFRlibm5OWlraH14TTVJSElOnTuXi\nxYtYWFiogbKNjY1oaSopKSmcPHlSzXzKpE1HRc9KjUaDu7v73y/mOci+3sbwnASteUpKSgpDhgxh\n8uTJdOvWDWtra6kyyenp6UyaNInbt29z8eJFUlNT2bt3L/PmzRMtzejQ7SF3797N/v37WblyJa6u\nrlKtd9mgo6ioiKioKExNTaVyY7aysmLNmjW4uroCEBcXx6RJk6T6HkHOOKJSZ+xq1KihZ5V79+5d\naWyIy2JlZYVGo9E7ga5Xrx6Ojo7MmzdPaO227vTEGAK4ilwldd/jihUrpHHXMjExYdy4cYwbN060\nlGfy4osv0qBBA+Li4mjbti2mpqb885//FC3LgISEBLKysiguLlbnH+ky4bJgb2/P6dOn6dy5M6DN\njMjmegva0/Ljx49LGygHBwcTGhpK//79URSFYcOGMXbsWKZNmyZamh7G4uYo+3obw3MSYPz48bRs\n2RJra2vc3NzIysqSKvMJMHbsWD755BMmTJgAaPcc/v7+0gV2ffr00dsLaTQa6tWrR8eOHRk/frwU\n5eu6e3n//v0MGDCAevXqSXfYUD7r1bVrVxwdHQWpqRhTU1M1qAOtRplKwXXIGEdU6ozdli1biIiI\nICkpSbV3/uCDDxg4cKBoaXrMmjULU1NThgwZgqIohIeHU1BQQKNGjTh16pTQEsOK+tZ0yNbfMm/e\nPJo1a6bayoeHh5OZmYmdnR1fffXVM7OOfzcyB/I6Fi5cSFJSEunp6Vy+fJkbN24wcOBATp06JVqa\nyrBhw7h69Sq2trZ6zqchISECVRny+uuvc/nyZZo1a4ZGoyE7O5v27dtjamoq1T0UFRVlsEGpV68e\nVlZWUrjSWVlZER8fr5Y35ufn4+zsLJ2ZhrG4ORrDesv+nKwIRVEoKSmRapNqLEZT06ZNIycnB39/\nfxRFYceOHZiZmVGtWjUePnzI5s2bRUskKCiIb7/9llq1apGQkMD9+/fp06ePVCNXylr1l5aWkpiY\nyPTp09VDHBmYMWMGhYWFemOAatWqpZa0yuLALWMcUakDO4CffvpJfaH26NGDDh06CFZkSNmHbflr\nol3AsrKynvv3li1b/i06/gwVlb/oXl6iU+dlkTmQ12FjY0NycjIODg7qb1O28qIOHTqQlpYm3Wlp\neYzlHurduzenT59W+zOOHTuGvb292jQuOhNqZWVFQkICtWvXBrSmNE5OTtIFdsbi5ij7ehvDc1LH\n/v37SUtLo7CwUH0eLViwQLCqp/j4+BASEoKfnx/Jycns3LmT9evXc/DgQdHS9NAFoBVds7Cw4OLF\ni4KU6fPbb79Rv359TExMyM/PJy8vj0aNGomWpVLWqt/U1JSWLVvy/vvv07VrV8HKntKtWze9d3d5\nV0zdyAsZkC2OkOfISBDt2rXDzMxMddTKzs42GC4pmpKSEs6cOUOnTp0AbXmZzqhC9Klf2U3n7du3\nOXPmDNWqVcPR0VGqBxnACy+8wI4dO/Dz8wNg586daumGTJv/77//Xi+Qt7a21gvkZaBmzZp65Qb5\n+fkC1VSMpaUlt27donHjxqKlPBfdPXTnzh2KiorU67I9h37//Xd++uknXn31VUA7U2r48OGcOXMG\nNzc34Rv9wMBAOnXqpJZifvvtt4waNUqopoowFjdH2dfbGJ6ToC3FLCwsJDY2lrFjxxIREaG+y2Xh\n888/Z9y4cVy6dInGjRvTqlUrtm7dKlqWAfn5+XqOstevX1ffPTVq1BApTY+bN29y5MgRvUBe9P1S\nlkuXLhmUrZZ998iALBVUfwbZ4ohKHdiFhISwaNEiGjZsqFeqJdvJ6fr16wkMDOTRo0eAtlds/fr1\n5OfnM3fuXMHqtKxbt47Fixerp7tTpkxhwYIF0gyzBdi6dSvTp09n8uTJgHYo65YtWygsLOTzzz8X\nrO4pMgfyOvz8/Bg/fjz3799n7dq1bNiwgTFjxoiWpcfdu3cxNzfHyclJ3UjL6D64d+9e3n77bW7e\nvEnDhg25fv06HTp0kOb0WcfPP/+sbvIBGjZsyM8//8wrr7wixabqrbfewt3dXR0bERYWhp2dnWhZ\nBhiLm6Ps620Mz0mAH374gQsXLmBtbc3777/P22+/jbe3t2hZerRs2ZIjR47w6NEjSktLpbWWX7Fi\nBa6urmo//NWrV1mzZg35+fmMHDlSsDotCxcu5Pjx41y8eJHevXtz8OBBunbtKlVg5+LiovacP++a\naHSZ7rJBp0yZbpAzjqjUpZht2rQhISFB2lr88ty/f19tFpaNdu3acfr0afW7/O233+jcuTOXL18W\nrMz4OHv2bIWBvIWFBQcOHJCmBzQmJkbPkc7T01OwIn2OHz9uYHkvo/ugtbU1sbGxeHp6kpyczNGj\nR9m8eTMbNmwQLU2PSZMmcf36dQYOHIiiKERFRdG0aVM+/fRTfH19hZfGDB8+3KDHpqJrojEWN0fZ\n19tYnpNOTk5q6W1UVBSvvPIKlpaWZGRkiJam0rx5c7y9vRk0aBDdu3eX7rdYlqKiIi5duoRGo6F9\n+/ZSGKaUxdLSkvPnz2Nvb8/58+f59ddfGTp0KN9//71oady6dYubN28ydOhQtm3bppY3Pnz4kAkT\nJnDp0iXRElXKZ7ojIyPp1KkT69evFy1NDxnjiEod2Hl4eBATEyOV09ezkP3kwsXFhaNHj6qZkceP\nH+Ph4cEPP/wgWNlTCgsLWb9+vcH3KNsGWseDBw8ApAzk58yZw/Lly//wmiiKi4uxsLCQqhn8WTg4\nOJCUlISNjQ3nzp3DxMREun5F0DbZ79q1S82IdenShTfffFOaTWD5XuTi4mKsra2lGxthLMi+3jpk\nPvAEWLJkCVOmTCE2NlatFhk7dixLliwRrOwp+fn57N+/n/DwcM6dO0efPn0YNGiQniuhLFy4cEF9\nh8tY5ujo6MjZs2dxcHAgNjYWMzMzXn/9dSneRd988w1hYWHqmCoddevWJSAgQJqB9PC071j3Lnz0\n6BHe3t7ExcWJlqaHjHFEpQzsVqxYAWgHh166dAlfX1+1tESj0fDWW2+JlGeAMZxcDB8+nB9//JF+\n/foBsGfPHqytrbG2tpbmOx0wYAAdOnRg69atvP/++2zZsoUOHTqwevVq0dKAp79LqLjnT4bvUEdF\nhj6yGUD069eP1atXq/0YstKzZ092797N3LlzycnJoWHDhiQmJkp1KCIzH374IR999BGFhYWqcQpA\n9erVGTduHMuWLROo7inG5CBsLMh+4FmeoqIiioqKqF+/vmgpzyQ3N5dp06axbds2PRt3GXhWmePO\nnTtFS1OZNGkSS5cuZceOHaxYsYIXX3wROzs7Nm7cKFqays6dOxkwYIBoGc9F9ky3zHGEPIXofyN5\neXloNBqaN29Os2bNePLkCU+ePDFw3ZEFY6jRb9OmDW3atFG/v379+qHRaNQyGRnIyMhg586d7Nmz\nh5EjRzJkyBCpXKB0v8v09HTOnj1L3759URSF/fv34+TkJFoeAF9++SVr1qwhMzNTb6Oal5dHly5d\nBCoz5N69e1hYWODk5KRa4MvYY7dnzx5q1arFZ599xtatW3n48CHvv/++aFkqderUeeZzUVfGI5J3\n332Xd999l6CgIGmCuIqQyaXxeci+3jqedeApG/n5+axcuZLs7GxCQ0P5+eefiYuLw9fXV7Q0PY4d\nO8aOHTuIjo7G0dGRiIgI0ZIM2Llzp1rmuHHjRrXMUSbWrFkDwIQJE/D29ubhw4dYW1sLVqVP165d\nGT16NDdu3CA6Opq0tDROnz4tlSdCnz59yM3NZdasWepc17FjxwpW9RSp4wilCkVRFKW4uFi5f/++\naBkV4ujoqCiKonTq1En55ZdflMLCQqVNmzaCVRkfuu+xa9euSmpqqnLnzh2lVatWglUZ0rVrV+Xh\nw4fq54cPHypdu3YVqOgp9+/fV65du6YMGjRIycrKUv/LyckRLc2Ao0ePGvx37Ngx0bIMWLduncG1\nOXPmCFDyfN577z3liy++UB48eKA8ePBAWbNmjTJv3jzRslROnjyp5OXlKYqiKJs2bVJmzpypZGVl\nCVZlvMi+3paWloqiKIqVlZWiKIqSl5endOnSRaSkCvHz81OWLVummJubK4qiKI8ePVKsra0Fq9Kn\nRYsWSr9+/ZRt27ap95CMdOzYUVEURbG3t1fu37+vlJaWKu3atROsSp/S0lJl586dyowZM5SZM2cq\nu3btEi3JAC8vLyU8PFy9d548eaJYWFgIVvVsCgsLldzcXNEy/hBZ4gix49EFM2TIEB4+fEh+fj5W\nVlaYm5vz8ccfi5ZlQPmTi5YtW6pDG0Uzffp0QKux/H99+/YVrE6fsWPHcu/ePT744AP69u2Lubk5\ns2fPFi3LgDt37ujVa1evXp07d+4IVPSUevXq0bJlS8LDw8nJyeHbb79l7969XL9+XbQ0A7p160bL\nli0pLi6mW7duODk5SemSuHPnTrZs2aJ+njx5sjTrXZa9e/cyadIkzMzMMDMzY+LEiezZs0e0LJWJ\nEyfywgsvcP78eVauXEnr1q2l6r2pU6cOdevWrfA/GV0IZV9vXdntCy+8wI0bNzA1NeX27duCVRmS\nmZnJnDlz1DItXfWATJw/f55vv/0Wf39/6tSpI1rOM3F0dCQ3N5exY8fSsWNH7OzscHFxES1Lj0mT\nJvH1119jbW2NpaUlX3/9NZMmTRItS4+cnBwGDRqkujhWr15dKidZ0Ga6lyxZwtixY6lVqxZ3795l\n//79omUZIGMcIddK/s1cvHgRMzMztm7dio+PD8uWLcPe3l66zf78+fMBePPNN/H19aWoqEiaRnHd\nxuntt982+JvwdHQ5dGl8d3d3rl27JljNsxkxYgROTk5687hksXLWsXjxYiIjI1WNgYGBDBgwQP2t\nysDatWsJDQ3l3r17ZGZm8ssvvzBx4kR1kKgs7Nq1i759+2JiYsLBgwd56aWXpDT0efHFF9myZYt6\nqBQeHi7VJtDU1JRq1arx7bffMnnyZMaMGSPV96grS583bx6NGzdm2LBhgHYMy82bN0VKqxDZ11v2\nUi0dNWvWpLCwUP2cmZmpN8dQBh4/fszSpUvJysqiuLgY0L6/Zbp/QL/M0cvLi7y8POnKHI8ePUpa\nWpo65zUgIABzc3PBqvSpU6cOv/32m/o5Pj5emj2ljsDAQBwcHNRe88aNGzNgwADpSphljCMqpXmK\nDgsLC1JSUhgyZAiTJ0+mW7duUrrRFRcXc+DAAbKysigpKVFreGUw0xg3bhw+Pj707NmTunXripZT\nIStWrECj0ehZ3+s+y/I9licpKYmTJ0+i0Whwc3OTLtPUrl07UlNTVavpwsJCbGxspBpvYWNjozZf\n64xeZDJ4uXfvnvrvvLw8+vXrR9euXVm8eDEAL7/8sihpFXLt2jWmT5+uvmi7dOlCcHCwOmBdNG5u\nbnh7e7Nx40ZOnjxJgwYNsLW1lWa9dVT0jpHxvSP7epdFZlOSmJgYli5dSlpaGp6enpw6dYqwsDB1\n5qsMdO7cGTc3NxwcHNSARKPR8OabbwpWZsj58+cN9kIyuTn6+vry+eefq/dJVlYWU6ZMkSrblJSU\nxLRp0/jxxx+xsLAgJyeHyMhIbGxsREtT0blFlzVqs7Gx4fz584KV6SNjHFGpM3bjx4+nZcuWWFtb\n4+bmRlZWlnSnFqA9maxduzZWVlbqQ1cWRo0axcGDB1m5ciXVq1fHy8sLb29vqR4Qs2bNwsbGBh8f\nH72TUkWGJtcyPHz4EDMzM+7du0erVq3UF4NGo+HevXtSbfSbNGlCYWGhGtgVFRXRtGlTwar0qVmz\npt56FxcXS7Xe9vb2enoUReHAgQMcOHAAjUbD1atXBaozpFWrVtIZz5Rlx44dbNu2jQ0bNtCoUSOy\ns7N55513RMsyQPZMmA7Z1xvg1KlT6iZfh0zltwC9evXC3t6e+Ph4AFavXs0//vEPwar0KSwslGZU\nzfMIDAzkwoULWFhY6O2FZAjs+vTpA2gP6Tp06ICTkxMajYaEhAQcHR0Fq9MnMzOTgwcPkp2dTVRU\nFAkJCdI5oBpDphvkjCMqdcauPIqiUFJSIl2tsejo/8+Sk5NDTEwM0dHRpKamYmdnh4+Pj/BBsSkp\nKWzfvp1Dhw5hb2+Pv78/PXr0kC5I7t27NwcOHKBly5YGAYhsG/1+/fpx9uxZevXqBcDhw4dxcnKi\nadOmaDQaKUZIzJo1i/r167Np0yY+//xz1qxZg7m5OUuXLhUtzahYvnw5c+bMYerUqQZ/k2WtjQnZ\nM2HGst7Dhg3j6tWr2Nraqr1CACEhIQJVPSUpKcng4AaetijY29sL0VUR8+bNo3PnzvTu3Vu0lOdi\nbm7OxYsXpTqg03Hs2DG9zzqNugNkd3d3AaoqRle5EhcXx7x583jnnXdYsmQJZ86cES1NxRgy3RUh\nQxxRqQO727dv895770lt+Qrwzjvv4OnpiZeXl2gp/xGJiYkcOnSI9957T7QUQHvDnT59mu3bt/P9\n99+zfPly6QxejIWwsLBn/k2j0UjRE1haWsq6deuIiYkBwMvLizFjxki3KXjy5AlffvklJ06cALSm\nLxMmTJBm4Om+ffvo06dPhWsuw1p36dKFU6dOVWjTL5M9v7Eg+3rr6NChA2lpadLdzzq6dev2XG1H\njx79G9U8nzp16lBQUECNGjXU546M987IkSOZPXs2FhYWoqU8l1u3bpGQkEC1atVwdHSkUaNGoiXp\nYWtrS0pKCkFBQVhZWTF06NAKZ9OKJicnR810Ozs7S5fphqetPqBfBSay1adSB3be3t4EBgaydOlS\nUlNT+f3337Gzs+PHH38ULU2PXbt2MWzYMEpLS6V96BYVFREVFWXQfC3TsNg7d+4QGRlJREQENWrU\nYPHixXTu3Fm0LAOGDRuGu7s7rq6uvP7666LlGC0LFixQ+9UASkpKGD58ONu2bROoypDRo0dTXFzM\nyJEjURSFzZs3Y2pqyrp160RL0yMjI4N//vOfomUYPXfu3CE0NFR6owrZ19vPz4/g4GAaN24sWkoV\nfxPHjh2jb9++NGrUSC3L02g0UlU0rVu3jsWLF6uZpWPHjrFgwQKpEga9e/emSZMmHD58mOTkZGrV\nqkWnTp2k6F8zpkw3aF0xy88ddnR0pF27dgBCZtJW6sCuY8eOJCYm6p1U6E4yZKJly5bs3bsXS0tL\n6coHdXh5eVG/fn0cHBz0ymIqcsv8u1m/fj0RERE8fvyYAQMG4Ofnx6uvvipa1jOJjY3l5MmTxMXF\nkZGRgb29Pa6ursyYMUO0NPz8/IiMjNQbTq5DthdsQEAA7du3Z+7cuTx+/JiBAwdiZ2fHwoULRUvT\nw1jMNNzc3Pjll19wdHTEzc0NNze3Cn8HIikpKeHXX39VAyaA5s2bC1RkiLEYVci+3t26dSMlJQUn\nJye9Tb5sfYHlB5RfuXKF9PR06dz99uzZw4kTJ9SyQV3PmEy0adOGzz77zGAvJEsZM2iNxU6fPs0r\nr7wCwG+//Ubnzp2lMhbLz88nOjoaa2tr2rZty61bt7hw4YLaWiESY8p0A7i6uvLdd9+p5oF5eXn8\n61//4uTJk8I0VerArlu3bkRFRdGzZ0+Sk5OJj49nzpw5HD9+XLQ0Pdzc3Dh69KhewCQblpaW0mU6\ndVSrVg1LS0tatGhh8DcZNwKgNfpITEwkNjaWr776itq1a5Oeni5aFrdu3eK1114jKyurwr/L9IIt\nLS1l6NChWFlZcfToUf71r38xc+ZM0bIMsLe3JyIiQs2OZGZm4ufnx7lz5wQrM+Tx48ckJiZy7Ngx\nvv76ax49eqTn7imSkJAQFi1aRMOGDfWelbK5Ysp4ePgsZF7v8j1NOrp16/a36vgjBg4ciIODA5s2\nbeLixYvk5+fj4uIiRXZER1BQEGfPnmXo0KEoikJ4eDgdO3bko48+Ei1Nj86dO3P69GnRMp6Li4sL\nR48eVQ8bHj9+jIeHh9pTW8V/F+3bt+f8+fN6RnI2NjZC92tyuYT8zaxYsYI+ffpw9epVXFxcuHv3\nLjt37hQty4BWrVrh4eGBj4+POuRUNpt+FxcXUlNTpZspA/onPOXPMWTsz+jRowf5+fl07tyZrl27\nkpiYSMOGDUXLArRZMG9vb3x8fKQtEy1byjFjxgzGjx+Pi4sL7u7unDt3TrpSjk8++YTu3bvTqlUr\nQGuPvXHjRsGqDImLi+PEiRPExcVx//59evfujZubm2hZKqtWrSI9PV09KZcVX19fDhw4IL1Rhezr\nLVsA9ywyMzOJiIggPDwckHNA+YEDB0hJSVEPRAICArC1tZUusLOzs2PIkCH06dNHby8kgyumjjZt\n2uDs7Ey/fv0AbSbU2tpa7cWSad8mM7L3nuuQce5wpc7YgTYzcunSJRRFoX379urDQiZ0pWPlgxAR\ntbvPokOHDmRkZNCqVSvpat+NYdZeWWbOnEliYiK1atVSA5LOnTtTu3Zt0dK4desW0dHRHDp0iPT0\ndDp16qR+t7JsWMqXcpQfayFbKQdoT/l0pTrt27eX0tbZxMQEBwcH5s6dy7/+9S/pNHp4eBATEyPd\ni788xmJUIft6nz59mmnTpvHTTz/x+PFjSkpKqFOnjnTfo4uLC0eOHMHFxYXk5GQyMzPx9/cnISFB\ntDQVa2trjh49qlc+6OHhIcX7uywBAQEVHsbKdBBWfr9W/v0j075NZoyl9xzkmztcqQM7a2trBg8e\nzKBBg2jTpo1oOQZ8+OGH+Pj4CP+R/Bl0pXllH2YgR2lefHw8Bw8eJDY2VtpZexWRl5dHWFgYn376\nKbdv3+bx48eiJelRUlLCmTNn1O+2Vq1aeHl5MXv2bNHSjApjOZm8f/8+cXFxnDx5koSEBExMTHB2\nduaDDz4QqmvFihUApKWlcenSJXx9faWtbDAmZF1vHQ4ODoSHhzNw4EASExPZtGkT6enpLFu2TLQ0\nPYzBtn379u0EBQXh4eGBoigcP36cZcuWMXjwYNHS/iM++ugj5s6dK1pGFX8BxtJ7DpCbm0t2drbe\nrFyRlUGVOrDLyspix44dREREoNFoGDx4MAMHDpSm2T48PJzo6GhSUlKwtbXFx8eHXr168dJLL4mW\nViEpKSnqqYWrq6uUgZOss/bKEhISwsmTJ0lKSqJVq1a4urri6upK9+7dRUt7Lnfv3iUmJoahQ4eK\nlgJo13rRokXExcWpv8kFCxZIV6pnTCeTaWlpnDhxghMnTvDDDz/QvHlzNSAVxaJFi9R/lz8dBzlP\nyHNzc7ly5QpFRUXqNZnKHHXIuN46HBwcSEpK0tvsydq/WN62vaioiKZNmwpWpc/Nmzc5e/YsGo0G\nJycn6Sz6/wwyWPZXFLBrNBpiY2MFqDFejKX3fP78+YSFhdG6dWs9Qx+RlUGVOrAry5UrV1iyZAlb\nt26lpKREtBw9FEUhOTmZ6OhoDh8+THFxMZ6ennh7e+Pk5CRaHgDBwcGEhobq1RmPHTuWadOmiZb2\nXGSbtQfanis3Nzfs7e0rzNrcu3ePl19+WYCyp0ydOhWNRqNnRVyvXj06duyo9haIpmfPnri7uzNs\n2DAURWHbtm0cO3aM77//XrQ0PYzlZLJ169a0b98eV1dX3NzccHJykqJ03ZgqGwBCQ0NZvXo1P//8\nM3Z2dsTHx9O5c2fpNn6yrrcONzc3Dh8+zJgxY3jttddo1KgR33zzjVSmJElJSVy9ehVzc3MsLCz4\n+eefWbJkCdHR0WRnZ4uWp7J79248PDyoX78+oM3WHjt2jDfeeEOwsv8MGQK7xMRE9d+6MVCmpqZ8\n8sknAlUZH0eOHCEwMNCg91y2A+527drx448/SvVsrPSBXdmsnYmJCYMGDZLCov95PHjwgMOHD3Po\n0CFCQ0NFywHAysqK+Ph4tc8qPz8fZ2dnqRzpjGHW3p9BhpfX2LFjSU9Px8/PD0VRiIqKolWrVty7\nd4/WrVuzatUqofqgYqdWKysrqX6TYDwnkyUlJc915hVVBmVslQ2WlpacPXuWzp07k5KSwqVL3Mbc\nlwAAIABJREFUl5g7dy67d+8WLU0PWddbR1ZWFq+++ipPnjzhs88+4+HDh0yaNEma2Xvz5s0jKioK\nW1tbEhISeOONN9i1axfTp09nwoQJqoueDNjY2BgExLJmP5+HDO/GinB0dOTs2bOiZRgdRUVFpKen\no9FopO09//e//81XX30l1QitSu2K2alTJ548ecLAgQOJjIykdevWoiVVSPk5OHfu3KFmzZrSBHU6\nyqahZZy3169fP3XWnkwvVWMkNTWVU6dOYWqqfYRMmjSJrl27EhcXJ82sq169erF9+3YGDRoEQGRk\npBRzespjLK6YfzRuJSIiQshGf/DgwQwePFivsqF///5SVjYA1KpVSzVCKioq4vXXX5dilEl5ZF1v\nHbr+7dq1a0s3mxJg165d6vDne/fu0axZMy5evChF33l5Kjrfl61yyVgoOw6ktLSUxMRE6Qx9jIGI\niAjVC2HJkiUkJyczb9486Vyt3333Xezs7LC0tJRmnmalDuw2bdpE+/btRcv4QwIDA3FwcFDnoDRu\n3JgBAwZINUA0MDCQTp066ZVijho1SrQsPW7cuMGhQ4dEy/iv4P79+zx69Egt3dHNtzI1NZUmaF67\ndi2rVq1i+PDhgPYl++KLL7J27VqpXAh79OjB5cuXpXfFlB2NRoO9vT329va8++67amVDaGioVIFd\ns2bNyM3N5Y033sDT05OXXnpJys2+7Ozbt48FCxYYVGDIcl/XrFlTfRa+/PLLtG3bVtp1dnBw4K23\n3mLy5MkoisIXX3yBg4ODaFkGxMXF0bVr12de8/PzEyFLD3t7e7XP19TUlJYtW7J+/XrBqoyPJUuW\nMHDgQOLi4jhy5AjvvPMOEyZMkMpNFrTjDoKCgrC0tFQTGqLHaFXKwG7z5s0MHz6c/fv3c+DAAb3T\nKhld1IxhDs5bb72Fu7u7alQRFhYmXc+LzLP2jI3Zs2djZ2eHu7s7AMePH+fdd98lPz+fnj17Clan\n5dGjR6Il/CkKCwtZs2aNnsnLxIkTpQmQjQVjqWzQlVwuXLiQbt268fDhQ7y9vQWrMj5mzJjB7t27\n9TZUMnH16lW9w9esrCz1s+gT/fKEhISwZMkStbrB09OTL774QrAqQ6ZOnWpQaln22rvvvitClh6X\nLl0yeHaXNUmq4s+hqxjYv38/Y8eOxdfXl/nz5wtWZUidOnWk85KolIFdQUEBoLWTFx1Z/xlq1qxJ\nYWGh+jkzM1PKE31bW1saNWqkWr5mZ2dL4zAKcPLkSTZu3CjlrD1jY/To0fj4+JCQkIBGo+HDDz+k\ncePGAMKbxH/66Sc6dOjwzB412Uo5RowYgZmZGdOmTVNNXoYPH05kZKRoaUaFMVQ26CgpKeHXX3+l\ndevWKIrC7du3pXpWGgNNmzbFwsJCyqAOUAM33cFx2d592fYdderUYfny5Tx48ACNRoOZmZloSXqc\nPn2aH374gbt377Jy5Ur1O83Ly6O0tFSwOn1cXFwM3j0VXavi+TRp0oRx48Zx+PBhgoKCKCoqkm6t\nAVxdXZk7dy59+/bV25eL3GdUysBu/PjxgNY1r6K0vmwsXLgQb29vfvnlF4YMGaLOwZGJkJAQFi1a\nRMOGDfV6M2Qyqjh48CBgOGtPRk6ePElGRgaBgYHcvXuXR48eqT1Ysrg6KopCgwYNKC4uJiMjg4yM\nDCks21euXEloaChvvfVWhRso2QaUX7x4kbS0NPVz9+7dMTc3F6jof4boMihjqGwA43hW/hlEr/fy\n5cvx8fHBw8NDyrmFW7duxcfHh549e1K3bl3Rcp7L2bNnGTVqlFrGWr9+fdavX0/Hjh0FK9Py5MkT\n8vLyKCkpIS8vT71uZmbGzp07BSp7yq1bt7h58yYFBQWcO3dOHb3y8OFDNZlQxZ8nIiKC6OhoZs2a\nRf369bl165bwQ+OKOHfuHBqNRh1noqNq3IEgKnJQsre3l+pkpbS0lMjISHr06KH+cDp16kSDBg0E\nK9OnTZs2JCQkSDcjrDzGMGtv4cKFJCUlkZ6ezuXLl7lx4wYDBw7k1KlToqWpzJkzhx07dmBubq63\nOd23b59AVVpu3LhBkyZNRMv40wwbNozJkyfTuXNnAOLj4/niiy/YvHmzYGVapk6dqv677IgL3efV\nq1eLkGWAi4sLR44cwcXFheTkZDIzM/H395euJ8NYnpV37twhNDTUoIdtw4YNgpVp8fT0pG7dulhZ\nWell7WSZWxgfH8/BgweJjY2levXqeHl5qWYQsmFlZcWaNWtwdXUFtAfckyZNkq6a5fr167Ro0QLQ\nZr0fPXpEvXr1BKvS8s033xAWFkZiYqJeQFy3bl0CAgLo37+/QHXGSXFxMXfu3FGfP0BVZcOfoFJm\n7J6X1pfNCapatWp8/PHHDBo0CF9fX9Fynknz5s2lK98oT/lZe8OGDZNy1t7u3btJTk5Wm9ebNGmi\nd0opA7t37yY9PV3KkuCxY8fy22+/4eHhgbe3N127dlXdO2VC5x5aXFxMly5daNasmVrCLJOpk+53\n+MMPP5CWlsagQYNQFIXIyEgsLCwEq3uKMVQ2gHE8K0HrIuzm5oanp6c0pgBluXXrFocPHxYt45k4\nOzvj7OzMokWLyMnJISYmhhUrVpCamoqdnR0+Pj4MHDhQtExAa/KhC+oAaZ+Zc+fO5auvvsLExARH\nR0cePHjA9OnTmT17tmhpjBw5kpEjR7Jz504GDBggWo7RYyyVDdWqVWPWrFksW7ZMfT6KThDJd+f+\nDRhDWr8snp6efPrppwwaNEivvEj0kGqAFStWANphtt26dcPX11fKshiAdevWcebMGfU7DAoKwtnZ\nWbrArmbNmnon0Pn5+QLVVEybNm148uSJlIHdd999R2FhIceOHWPXrl288847NGvWDB8fH7y9vaU5\n8XtedlOmDXRAQAAAX375JXFxcVSvXh2AiRMnGpSyi6K0tJTc3FyioqLUyobg4GCpKhuM6VkJWlOf\n5cuXi5bxTP71r39x6NAhvLy8REv5Q/7xj38wZMgQhgwZAmiHWMvg0JyUlASAu7s748ePx9/fH4Ad\nO3aoxlgycfHiRczMzNQy12XLlmFvby9FYKeja9eujB49mhs3bhAdHU1aWhqnT59m9OjRoqUZFatW\nrSI9PV36ygYLCwsURcHT05MdO3bwyiuvCG/zqZSBnbu7O+7u7gQGBqppfZkJDw9Ho9HouVRpNBqu\nXr0qUJUWnQFN8+bNadasGU+ePOHJkyeiZT0T2WftgbZ3Zfz48dy/f5+1a9eyYcMGxowZI1qWHrVr\n18bW1pYePXroGdHIUpZXu3ZtfHx88PHxAbQOdQcPHmTy5Mncvn1bimGxZa3PK+qplI379+/z8OFD\n9UWbl5fH/fv3BavSYgyVDbo1NZZnpa+vLwcOHKB3796ipVTImjVr+PTTT6lRo4Z62CDTuAMdRUVF\nREVFGZS0LliwQLAyraFL2UOkRYsWCVTzxxQXF/P777/z7bffMnnyZKpXry7VIRhoD8ICAwNZunQp\nAG3btmXgwIFVgd1/iLFUNpiamvLxxx+zY8cOXF1dpWihqJSBnY4xY8YQGRmpzuK6d+8e/v7+Upyk\nlSUrK0u0hGeiGwwbERFhUFYSEREhQNGzMYZZewCzZs0iJiaGunXrcvnyZZYsWYKnp6doWXr07duX\nvn376l2T7QVbltatWzN58mQmT54s3Wa6bE9lYGAgT548YdiwYVL1VII2w21vb0+3bt0A7YgLmQZD\ny1zZAFC9enV8fHykGwPzLFatWsWHH34obeAk4+FHRfTr14/69evj4OAg3QiTY8eOARUHnzIyfvx4\nWrZsibW1NW5ubmRlZUnTY6cjJyeHQYMGsWzZMkB738tY1io7rVq1wsPDg969e0td2aBj0KBBWFhY\n4O/vT3Z2tlAtldo8xdbWlpSUlD+8JponT57w5ZdfcuLECTQaDe7u7kyYMEF92cpARUY0FV0TTVJS\nkt68MGPZZFXxn/M8JzqZNqg2NjZqT6XufrG2tpbOuAC0fU1nzpxBo9HQqVMnGjVqJFqSSsuWLQ0O\nF2SpbABt5UV0dDQpKSnY2tri4+NDr169eOmll0RLMyqSkpKee4gk2zgTS0tLfvzxR9EynouXl5ca\nfJbtZyo7okFGFEWhpKREqsCpW7duREVF0bNnT5KTk4mPj2fOnDkcP35ctDSjQndoWNbFXKPRSGOO\ndPPmTRo3bkxSUpLahw7aypY9e/YwcuRIYdrkuRsEYGJioueylJWVJWV53sSJEykuLmby5MkoisLm\nzZuZOHEi69atEy2NgwcP8t1333Hjxg11Dhdoy7RkCjx1yDxrr06dOs/csMgSiPj5+REZGakaf5RF\ntpmA06dPp3HjxgwbNgzQ2o/fvHmTJUuWCFamjzH0VOooLS1VR1xcvnyZy5cvSzHiAuSubAAYPHgw\ngwcPRlEUkpOTiY6Opn///hQXF9OzZ098fHxwcnISLVOPPXv26B0oyjATsHz5YHlkG2fi4uJCamoq\n1tbWoqU8kxs3bkhXqVQRt2/f5r333lP713766Sfp+tdWrFhB3759uXr1Ki4uLuTk5FTNJP0foAvs\ndD4Yso0MGT16NPfu3cPDw4O8vDzVcKh+/fpCgzqo5Bm76Ohoxo0bp25MTpw4wdq1a/H29hasTJ+K\nTu9lOdE/f/48ycnJvP/++yxevFg9Valbty4eHh5SnUYbi8uSzOhOqa5fv27QIKzRaKTqWZX5vinL\nJ598QkZGBjExMcydO5cNGzYwZMgQ6Ux9ZB5xAcZR2QBPT551PHjwgH379nH8+HFCQ0MFKtMnKCiI\ns2fPMnToUBRFITw8nI4dO/LRRx+JlmZUdOjQgYyMDFq1aqXXjyzTc2jcuHFMmTJF6uATwNvbW+1f\nS01N5ffff8fOzk6qjGhERATe3t5kZ2cTFRVFQkICS5YskS6TLDsXLlxgxIgR/PbbbwA0aNCAb775\nBktLS8HKnqIzaYuOjubUqVPymLQplZw7d+4oe/fuVfbt26fcvXtXtJwKsbOzU65cuaJ+zsjIUOzs\n7AQqMmTPnj1KSUmJaBnPpXXr1kpOTo5oGX+KlJQUZfXq1UpISIiSkpIiWo4Bs2fP/lPXROLs7Kxs\n3rxZKS4uVoqLi5UtW7YonTt3Fi2rQg4dOqS8/fbbyttvv63ExMSIllMhbdu2VYqKikTLeCajRo1S\nRowYoRw5ckT5/vvvlZEjRyqjR48WLcuAgIAAvc95eXmKh4eHIDXPxtLSUikuLlY/FxcXK5aWlgIV\n6fPo0SNl8eLFypgxYxRFUZTLly8r+/btE6zKkGvXrinXrl1TsrKylKysLPWzTLz++uuKqamp0rZt\nW8XS0lKxtLRUrKysRMsywMHBQVEURbG1tVWv2djYiJJTIbp75OTJk4q7u7uyb98+xcnJSbAq48PZ\n2VmJjY1VPx89elTa97eOzMxM5fPPP1d8fX2Vjh07CtMhX93h34ypqSkNGzakbt26pKWlceLECdGS\nDPjkk0/o3r276ubZvXt3Pv30U9Gy9NixYwf//Oc/mT17NpcuXRItp0KMxWUpODiYoUOHcvfuXX79\n9VeGDRsmjdukjpiYGINr3333nQAlz2bbtm1ERETw6quv8uqrrxIREcG2bdtEyzJgzpw59OrVi08/\n/ZRPP/0UT09P5syZI1qWAboRF7Jy9uxZvvnmG7p3706PHj0ICwuTbjg5QNOmTZk0aRIAubm59OrV\ni+HDhwtWZYhGo9FzPb1//75UBkmBgYHUqFGDH374AYDGjRvz3nvvCVZlSMuWLbl//z579+5l3759\nPHjwQM8RVwYOHjzIlStXiImJYd++fezbt4+9e/eKlmVAnTp11AwOaIfAy2aeoqtm2L9/P2PHjsXX\n11fq56asFBQU4OHhoX7u1q2b1G0K8NSkbd++fULNzyp1KWZoaCirV6/ml19+wdbWlvj4eDp37kxs\nbKxoaQYUFRWRnp6ORqOhXbt20rlrgbakaPv27YSFhaHRaAgMDMTf3194bbRuflRaWhqXLl2Sfn6U\nlZUV8fHxqrNffn4+zs7OUpSMfvnll6xZs4bMzEzatGmjXs/Ly6NLly5s3bpVoDrjpCKTISsrKynW\nuyz9+/fn/Pnz0o64sLe3JyIign/+858AZGZm4ufnJ3RQ7LOYNWsWDx8+JCkpiaCgICkHGm/fvp2g\noCA9F9Rly5YxePBgscL+Pw4ODiQlJendPzY2Npw/f16wMn2Cg4MJDQ3Vc2MeO3asdKXWxkBSUhJT\np07l4sWLWFhYcPfuXXbu3ImNjY1oaSq9e/emSZMmHD58mOTkZGrVqkWnTp2k+13KzhtvvIGDgwPD\nhw9HURS2bt1KUlISu3fvFi1NDxlN2ip1YGdpacnZs2fp3LkzKSkpXLp0iblz50r3w/n8888ZOnSo\n2q+Wm5vL9u3b1VNfmcjJyWHz5s2sWrUKc3Nzrly5wrRp04S+xBYuXGjgrFQWWVyWdFhZWZGQkEDt\n2rUBbR23k5OTFBv9Bw8ekJubS1BQEMuXL1f77MzMzKSxlddx9epVQkJCDOZHyXISbWxBclhYGGDo\nUia6UVzHkSNHCAwMpFWrVoDWTGXjxo10795dsDItUVFRgPb7UxSFJUuW4OjoiLe3NxqNhv79+wtW\naMjNmzc5e/YsGo0GJycnqVxQXVxcOHLkCC4uLiQnJ5OZmYm/v790WVqZD+qMjaKiIkxMTEhPT0dR\nFNq3b09paalUB935+flER0djbW1N27ZtuXXrFhcuXKBXr16ipRkV9+7d4/3331czX66urixcuFAq\n3waAefPmSWfSVqkDu44dO5KYmKhm62rVqoW5uTlpaWmipelR0SmkbGMZ9uzZQ1hYGFeuXGHEiBEE\nBATQsGFDCgoKMDc3l8Kx7lmz9spfE83KlSsJCwvTO+ENCAhg5syZoqWpZGRk0LRpU2rVqsXRo0fV\nRmfdTEgZsLa2ZsyYMVhaWqqukzpTDRkoHyTrqFOnjjoEXDYKCgrIzs7m9ddfFy2lQmSubAgICNA7\nVCp/yLRx40YRsp7LjRs31IMRnVZZXFBjYmJYunQpaWlpeHp6curUKcLCwvTKt2RA5oM6Y8Pe3t4g\nA1/RtSqq+LuQ0aStUo87aNq0Kbm5ubzxxht4enry0ksvSVf7DlqL8dLSUnVzWlJSwu+//y5YlT67\ndu1i5syZBi/9F154QYqxDAAfffSRQRBX0TXRvPXWW7i7u6vz9sLCwqSbtzdgwAASExPJyMhg/Pjx\n9OvXjyFDhkjVZ1erVi2py53q1atHvXr1CA8PJyUlhZMnT6rzFWUM7Pbu3cusWbN4/PgxWVlZqhuu\nLBlQXWWDriwrNzeXDRs2SFPZoMt4GgvPckGVJbDr1asX9vb2xMfHA7B69Wr+8Y9/CFZlSGBgIJ06\nddI7qBs1apRoWUbFrVu3uHnzJgUFBZw7d049FHn48CEFBQWi5VXxf0DPnj3ZuXOnelh87949/P39\npRvL8eKLL7Jlyxb8/f0B7bzSOnXqCNVUqTN2ZTl27BgPHz7E29tb7b+ShXfeeYfs7GzGjx+Poih8\n/fXXNG/eXO0dE4nuRZWRkYG1tTVeXl6iJRmgm7W3Y8cOdY4UaEve0tLSpCvdyczMpEmTJlJnw3R9\nLR9//DG1a9dm6tSp0g2k37x5M5mZmXh5eak9YSDfAGNj6cGxt7cnNjYWDw8PdZ1lGr5sDJUNAD//\n/DPTpk0jLi4O0AZKwcHBNG3aVLAyfdq1a8eFCxf07h3ZkDmjWJakpCT1oM7V1VW6gzrZ+eabb9i4\ncSNJSUl07NhRvV63bl0CAgKkLGOu4n9HRc9uGZ/n165dY/r06aqJU5cuXQgODhaaJKq0Gbvi4mIs\nLS1VB0ddg7iMLF++nLVr1/Lll18C4OnpyZgxYwSr0jJp0iTS0tJwcXFh/vz5nDlzhgULFoiWpUfj\nxo1xcHBg7969ODg46M3a++yzz0TLM6B///4kJSVJnQ2rUaMG27ZtY9OmTeocM9myyBcvXmTz5s0c\nPXpUbwC4bAOM161bx5kzZ9QenKCgIJydnaUL7KpXr25wuFD2exWNMVQ2gDaDM3ToUCIiIgBtT0Zg\nYCCHDx8WrEwfnQuqrIGd7BnFstja2tKoUSM1AM3OzhY758rIaNu2LbGxsezevZs333xTtJwq/gZM\nTEy4fv26Ohs3KytLqveNjlatWklTtaKj0gZ2pqamtG/fXu+HIxvjxo3Dx8eHnj17MnHiRCZOnCha\nkgEnTpwgNTUVExMTCgoK6Nq1q3SBnY2NDTY2Nrz88sv4+vpK+XAoS7Vq1TA1NWXXrl1MnTpVzYbJ\nxIYNG/j666957733aNWqFdeuXZPOsj0yMpJr165Jl4GviLK/SVl/nxYWFmzdupXi4mKuXLnC6tWr\ncXFxES1LxcvLi8GDB+tVNnh7e4uWZcDdu3cJDAxUPwcEBEh1wDR16lRAW0Zva2srrQvq7t27SU9P\nlzbw1BESEsKiRYto2LChXgBa1WP359m0aROTJ0+mXbt25OXl4e3tLZWRTxV/PUuXLsXV1RV3d3cU\nReHEiROsXbtWtCwDZDRpq7SBHWhrdi0sLHByclJPy0UvSFlGjRrFwYMHWblyJdWrV8fLywtvb2+p\nrH1r1KihvqxeeOEFZK7s3bFjBzNmzGDAgAGMGjVKWgMIY8iGWVhYsGzZMrKzswHtqZVss9esrKzI\nzc3l1VdfFS3luRhLD05ISAhLly6lZs2a+Pv74+Xlxfz580XLUpG5sqEsr7zyCps3b2bIkCEoikJ4\neLhUvWEODg5qWWOfPn2e6ygsEtkzijpWrVpFenq6lH2zxsJXX30FwE8//cTBgwcJCAjg/v37eHh4\n4OPjQ5cuXfSC5iqMH29vb5KSkoiPj0ej0fDZZ5/RoEED0bIMeOONNxgzZgx9+vTRM2kTSaXusTt2\n7JjBNZlc88qSk5NDTEwM0dHRpKamYmdnh4+Pj3Djj9q1a6tzowA963aNRiPUGagiZJ21V5aLFy/y\n1Vdf4eLigr+/P1evXiUiIoKgoCDR0lRkN9IAcHd3JzU1FUdHR72Mg0wadRhDD05kZCR+fn5/eO3v\npmxlg0z38bPIyspi6tSpqumHi4sLISEh0pXmrVq1ihkzZvzhNVHIPldRh4eHBzExMVSvXl20lP8q\nCgoKOHbsGN999x2nT58mKSlJtKQq/kJ69OjBkSNH/vCaaJycnKTzaajUgR1oX7IZGRn07NmTgoIC\niouLMTMzEy3rD0lMTOTQoUO89957QnX80RgDGV1GZZy1Z2zIbqQB2oHK5R9vsh7clJSUcPv2bT0T\nCNk2+hWZ48hgmBMfH8/BgweJjY2VtrLBGKlobWUyL/jmm2/0soiyzVXUmZulpaVx6dIlfH191bJw\njUbDW2+9JVKeUVJ+zE5qaiojRoyQbrZZFf9zCgsLKSgowMPDQy/5ojM31PliyIKMJm2VuhRz7dq1\nhIaGcu/ePTIzM/nll1+YOHGidCcCRUVFREVFGdTwytDLJmPg9izKz9o7e/as3qw9WQK7uLg4Fi1a\nZLDeV69eFazsKbIbaYA2sAsMDKRZs2bqta+//lq6wE72Hhydq+yNGzeYNm2anqusDFkIZ2dnnJ2d\nWbRokVrZsGLFCqkqG8oiuyvm9u3b2bZtG9euXaNPnz7q9by8PGnKCYuLi9m4cWOFVTeykJeXh0aj\noXnz5jRr1ownT57w5MkT0bKMmjfffNPAWGzo0KFSGYtV8b/j66+/Jjg4mJs3b+Lg4KBer1u3LlOm\nTBGorGJkNGmr1IHdF198QUJCAs7OzoDW3vnOnTuCVRnSr18/6tevj4ODg1QDd0E7TPlZ9cS6OTOy\nYAyz9gBGjx7NqlWrsLe3l7ZvQHYjDdDONduxYwchISF0794d0PZqjB8/XrAyfWTvwdG5yu7Zs0d1\nlQUwMzOTyvQD4B//+AdDhgxhyJAhwNPKBpmQ3RXTxcWF1157jZycHN555x299ba2thasToupqSkm\nJibcv39fqjEwZVm4cCEAERERBgcLurWv4j/DGIzFqvjfMWPGDGbMmEFISIhq5CQzMpq0VerArmbN\nmnqp07JlUDJx48YN6TYnOh49eiRawh+iM6SwtLSksLCwwv+nZ8+ef7OqZ1O/fn18fHxEy3gushtp\nADRp0oRvv/0WPz8/BgwYwOzZs0VLqpDmzZtLXf6tc5UdOnSoFBm6ZyFzZUNZZHfFbNGiBS1atMDf\n3x9ra2tpy9xefPFFrKys8PT01DM/k63H7qOPPjII7Cq6VsUfU716demNxar4a2jcuDG7du0yuK4r\nuZZldqGMJm2VOrBzd3dn6dKlFBQUcPjwYdasWaNXeiILLi4upKamSnNaamwYw6y9snh4eDBr1iz6\n9+8vTc12eb777js+/PBDPvzwQ/WaDEYa5WnRogUnTpxgwoQJDBgw4JmBvUhatWqFh4cHvXv3lroH\n58yZM1KXCMtc2VAW2V0xdfz66684Ojpib2/PqFGj8PLykurgs3///vTv319a107ZS5iNkY0bN0o/\nZqeKv4YNGzbwww8/0L17dxRF4dixY3Tu3JmGDRsCSBPY5ebm8vrrr0tl0lapzVNKS0tZt24dMTEx\ngHYO0pgxY6R6OQB06NCBjIwMWrVqpffDkc1xUlYsLCwMZu2dO3dOtKxn0q1btwp/gzIN1pbVSKMs\nY8aM0Sux/eKLL1ixYoU0gYgOXclW+TV///33Bah5Nu3bt6+wRFiWoEQ2855nYSyumKB9R8bExBAW\nFkZiYiIDBw5k9OjRqvOxaAoKCsjOzpZydM358+dVt+DFixergWfdunXx8PCQNhMqM8HBwUyfPl3v\nmkxOrVX8dXh6erJp0yZee+01AG7dusXIkSPV/bosyGjSVqkDu4oeEhVdE43OebLsySQYl3GJSMoH\nHLIFIMaE7hR6x44dDB48WO8UOi0tTQrbX539fY8ePaQucfzwww/x8fExmh6RTp06ceYDs4v5AAAg\nAElEQVTMGdEynsm4ceOYMmVKVWXDX0xKSgobN24kOjqa7t27Ex8fT8+ePfnkk0+E6jKGkSug1enr\n6yuduZQxIrtTaxV/Ha+//jo//fSTuu8tLS3F3NxcOlfMxYsXV2jSJrKXv1IHdsb0kEhJSeHkyZPq\nnKsqK+8/j7HN2rt//z6LFi3ixIkTgDaDt2DBAurVqydY2dNT6AULFrBkyRIpT6GNxf4+PDyc6Oho\nUlJSsLW1xcfHh169eknxHVZEUFAQJSUl0pYIG0tlQ2ZmJjNmzOD06dNoNBpcXFz47LPPaN26tWhp\negQHB7Np0yZeeeUVxowZw7///W+qV69OaWkpbdu2JTMzU6g+Yxi5AjB06FBOnz7NgAEDGDVqlJTZ\nRdnRObWePHkSV1dX9XpeXh4mJibSOZlX8b9nypQpXL58WS1Z37FjB23btiUkJES0ND0aNmxIgwYN\n9EzaRCcPKmVgZ2wPieDgYEJDQ+nfv79qBDJ27Fhp7Pllx9hm7fXv3x8rKytGjhyJoihs3ryZ1NTU\nChuJ/26MJRumQ2d/Hx0dLa39vaIoJCcnEx0dzeHDhykuLqZnz574+Pjg5OQkWp6K7CXCxlLZ0KlT\nJ6ZMmcLgwYMBVOdW2bKh77//PqNGjaJFixYGf0tLS8Pc3FyAqqfoMshlN1HW1tbSBfIADx48YPv2\n7YSFhaHRaAgMDMTf35+6deuKlmYUXL9+nWvXrhEUFMTy5csNnFpNTSu1XcR/Lbt27eLEiRNoNBrc\n3Nz497//LVqSAXZ2dgYmbVWBnQCe9ZCoW7cuNjY20j0krKysiI+PV52/8vPzcXZ2lmbOVRV/LTY2\nNpw/f/4Pr4kgPj6e6Ohojhw5InU27Fno7O/fe+890VJUyps+PHjwgH379nH8+HFCQ0MFKjM+jKGy\noaLgQ5b7uzxJSUnExcVRrVo1unTpIk12FmDUqFH06NGDZcuWsWvXLlavXs3vv//OV199JVpaheTk\n5LB582ZWrVqFubk5V65cYdq0aVUHtP8Bjx49onbt2piYmJCenk56ejo+Pj5VZjT/Rej2FD4+PkaR\n3dYFcUVFRUyYMIFHjx7x448/Ci0ZrZSBnbFhZWVFQkICtWvXBqCwsBAnJ6eqwO5PYkyz9kA7cPmT\nTz5Rs8lxcXHMmjWL06dPC1amj+zZMGOxvw8MDGTjxo3q50ePHtG3b19iY2MFqjJE5hJhkL+y4d69\neyiKwscff0z9+vXx9/cHtBm73Nxcli1bJlihPosXLyYyMlL9Pvfs2cOAAQOkGWtSUFDABx98oGd+\nNn/+fOkcUffs2UNYWBhXrlxhxIgRBAQE0LBhQwoKCjA3N//DipIqnuLg4MDJkyfJzc2lS5cuODo6\nUqNGDbZu3SpaWhV/Ebdu3SI6OppDhw6Rnp6Os7Mz3t7e9OzZU01uyISMJm2VOrCLiooiKCiIX3/9\nVc3aybjRX7lyJWFhYXobloCAAGbOnClaWhX/B6SkpDBixAgePHgAwEsvvcQ333wjZfahLLJlw7y8\nvFT7+7Iujm+//bZAVYbMnz+f3377jTVr1pCbm0vv3r0ZO3as3qwzGZC5RBjkr2xo2bJlhQdMuozt\ntWvXBKh6Nu3atSM1NVUNlAoLC7GxseHy5cuClWlZv349o0eP1rsWFBQkXYA8cuRIRo8ejZubm8Hf\nvv/+e6lmqMqOLjsSEhJCYWEhs2fPljbbXcX/npKSEs6cOaP2zNeqVQsvLy8pZtLK3JZSqQO7Nm3a\nsH//fjp06CBayh+iK4nRlRgZi5NeFf9zdIGdLBmRshhDNkxGI4VnMWvWLB4+fEhSUhJBQUEMGDBA\ntCQDZC4RhqrKhr8aDw8Pdu3apZr55Obm8uabb0qTSfbx8WHo0KEMGzYMgMmTJ1NYWMiGDRsEK9Oi\nO4TNyMjA2toaLy8v0ZKMHjs7O9asWcPMmTNZv349FhYWWFlZVd3jlYS7d+8SExPD0KFDRUuR2qRN\nrmayv5lGjRoZRVAHWrfORo0aUVxcjEajITs7W8q5R1X875k7dy5z5syhfv36gHZDtWLFCj744APB\nyp5iDMOgXVxcSE1Nldb+PioqCtAGxM7OzixZsgRHR0c0Gg27du2SZgCrjtq1a+sZTsXFxfHCCy8I\nVvWUwMBAOnXqpFfZMGrUKNGyDMjPz2flypVkZ2cTGhrKlStXSE9Px9fXV7Q0PczMzLCwsKBXr14A\nHD58GCcnJ6ZOnYpGo2H16tVC9e3atYu+fftiYmLCwYMHeemll6QJ6gAmTZpEWloaLi4uzJ8/nzNn\nzkh18GWMrFq1io8++oh///vfWFhYkJmZiYeHh2hZVfwfkJ6ezqRJk7h9+zYXL14kNTWVvXv3Mm/e\nPNHSAG3LjLOzM4sWLVLbUlasWCFFW0qlzthNnz6d27dv88Ybb1CjRg1Au8mSbUMVEhLCokWLaNiw\noV5JWdUp1X8nFY3cEO2yVB5jyIbJbn8fEBCgV5pX3kSlbN+dDBhDibAxVDYMHDgQBwcHNm3axMWL\nF8nPz8fFxUWazKeOsLCwZ/5No9EwcuTIv09MGe7du6f+Oy8vj379+tG1a1cWL14MwMsvvyxEV3ks\nLCxITU3FxMSEgoICunbtyrlz50TL+q8gPz9fyn6rKv463Nzc+OSTT5gwYQLJyckoioKlpSUXL14U\nLe0PEd2WUqkzdg8ePKB27doGk+xlC+xWrVpFeno6r7zyimgpVfwNlJaWUlRUpNfb8uTJE8Gq9JE9\nGwbaYepgaH8vC8/bOMtGSUkJW7ZsITU1VeoSYWOobMjMzCQiIoLw8HAAaTeoAQEBoiVUiL29vcGB\nyIEDBzhw4AAajUaoaUFZatSooR7EvvDCC9I9f4yRH374gTFjxpCXl8fPP/9MSkoKa9euZc2aNaKl\nVfEXU1BQQKdOndTPGo1GSvdTGdtSKnVgZywbq+bNm0vXnFnF/x1Dhw6lR48ejBo1CkVR2LhxIyNG\njBAtS4+TJ0+yceNGabNhoDWrMAb7+59//plp06YRFxcHaE8qg4ODadq0qWBlTzExMSEuLg5FUaQM\n6MB4Khtq1qxJYWGh+jkzM1Nv4Lto/Pz8iIyMxMrKyuBvMtzjp06dokmTJkI1/BkuXbqk9x1mZmaq\nn2X4Ho2RGTNmEB0dTb9+/QDtQc7x48cFq6ri/4IGDRqQkZGhft65cyevvfba/2vv3qOqLtM9gH+3\nQl6Sbl6OQ0kqVopyUQoZvCIq4KDNuDCvKaB5xLykM11WZaIz1ZiKgnkcR9e4V2YKZ/JCrSASTQ0v\nIHKpEBKKbOF40pkzhYrtoH3+4OxfbvdGK4H3efl9P2u1lvzsj2eBvHu/+33e76OwIvckXksxZSvm\nqlWr8Oyzz2LhwoUufyfh7oDD2rVrATQMgy0rK0NMTIxTy+jSpUtVlkfNKDMzE/v374fFYsGYMWPE\nXbzXYRi09Ph7h9GjRzuFQOzYsQM7duzABx98oLgyZ/PmzcO5c+cwadIk426dpNZ1X19f5OXlie9s\nyM7Oxssvv4zS0lKMGTMGubm5sFqtYu4K/eMf/8CvfvWrRmP4Vf+Ojxs3Dv/85z8RHh6OqKgoDB06\nVNzsWQA3HWOg+vuoo5CQEOTl5TldTZAU4ERNp7KyEnPnzsXRo0dx9913o1evXtixY4e43xuJ11Lk\nrYYtwM/PD0DDTBQHi8XicsdFtZqaGlgsFvj4+KBHjx6w2WziWvKo6Vw7mNPxn1Q6nIZt3boVJ06c\nMFrdnnvuOYSGhorb2F24cMFptEFcXBzWrVunsCL3rl69is6dO7ukIkrZ2OnS2TB27FgMGjQIx48f\nB9DwAUTXrl0VV/WjuLg40QOC33vvPdTW1uLDDz/E7t278Yc//AE9evRAdHQ0oqKixLTeSnsD2hr4\n+PggNzcXAGCz2ZCamqpNAB79PL6+vsjJycHly5fxww8/wMvLS3VJbkm8lmLKE7tXXnkF0dHRIi/W\nu5Oenu6SruPuGelNp8GcOpyG6RJ/P2rUKMTHx2PatGmw2+3YtWsXtm3bhpycHNWlAQCeffZZrFq1\nSuyao1tnQ0REhMvP1t0zVa5fhwYPHozo6GiR65DD559/jszMTGRlZeH8+fPIz89XXRI6derU6AfF\nEufl6uDChQtYvHgx9u/fD7vdjrFjxyI1NVX8KT39dI71HIDbcDFp67nEkDZTbux27dqFrKwsFBUV\nITAwEOPGjcPYsWONeT3SuEtElJaSSE1L8mBOQP4waABITk6G1Wp12nzGxcVhyZIlqktzUlVVhYUL\nFxonOGFhYdiwYYOYk4cBAwbg448/xqBBg0SuOUlJSU4twde/mV6+fLmKslzU1tbiypUrCA8Px4cf\nfmg8//bbbxEVFYWysjJ1xTVC+jrkjs1mMzb21Lrk5uZiyJAhN31G+rp2Pb+WY22Xsp47SLyWYsqN\nnYPdbkdhYSGysrLwwQcfoK6uDmPGjEFUVBRCQkJUl4fMzEy89957SEtLw5QpU4x/MDU1NSgtLUVe\nXp7iCqmlSBrMCehzGqZD/L10Tz/9NLZs2YJLly4ZP28HSScP0jsb1q9fj5SUFJw7dw7e3t7Gcy8v\nL8ydOxcLFixQWN1PI2kdulFrlqR/l9R0+CE3SSTtWoqpN3bX++abb/DBBx/g/fffx5YtW1SXg+Li\nYhQWFmL58uVYuXKl8YmFl5cXwsPDxZ4w0q2RPpgT0Oc0rL6+HufPnzfi7wGIOQlz0CEVEwAmTJiA\njIwM1WU0Spc3fampqaJalhsjfR168cUX4e3t7RQ6dO7cOfzxj39UXBk1tWPHjuHo0aNYt24dli5d\n6vQh9549exie0grp8roo8VqKqTd2ly9fRnJyMs6ePYstW7bgzJkzKCsrw/jx41WX5iQjIwMxMTFo\n06aN6lKoBegymFP6aZgu8ffSUzEdoT5RUVEigwp062yw2WzYtGkTDh8+DIvFghEjRmDevHniZjRJ\nX4cCAgJc7rG4e0b6O3ToEA4ePIi//OUvSExMNJ57eXlh/PjxeOCBBxRWR81B+uuig8RrKaZMxXSI\nj49HcHAwjh49CgDw9vZGbGysuI1dWloannrqKcTGxiIhIUFkUhk1HV0Gc0ofBr1+/XqUl5eLv1gv\nPRXTarUiKysLK1asEBmm4e3tjeDgYGRkZCA4ONips0HS99EhMTERdXV1ePLJJ2G327F9+3YkJiZi\n69atqktzIn0duv322/Hmm29i6tSpABruznfq1ElxVdQccnNzMWHCBMTFxTFt1CSkvy5e69pDFwkH\nMKbe2FVWViI9PR27du0CABFvUtzZsWMHvvnmG+zcuRNxcXGwWCyIj4/H1KlTxUbA0i+nw2BOHU7D\ndIm/79y5M7Zv3+6UitmlSxfVZRl+9atfIT4+HvHx8U5hGq+99pqIMI3AwEAEBgbinnvu0aKzIT8/\n3+lUKSIiQlRUtoP0deitt97C4sWL8dRTTwEAhgwZgrfeektxVdQcevfujdTUVBQVFSEoKAjR0dGi\nA+/o1kl/XXSIj4/H4MGDnVoxExISlNZk6lbMsLAw5OTkICwsDIWFhaisrMTUqVPFte44XLx4Edu3\nb8f69evh5+eHM2fOYNGiRVrc16CfTofBnJKHQesWfy89FfNGJIVpTJ8+HceOHRPf2TBo0CCkp6ej\nT58+ABp+3ydNmoRTp04prsyZDusQmYv0wDtqOjq9Lkq7lmLqjV12djZefvlllJaWYsyYMcjNzYXV\nakV4eLjq0pzs27cPVqsVZ86cwcyZMxEXF4du3brhypUr8PPzM+JWqXWRPJgzPDwc2dnZolqzHHSJ\nv9eN9DANAEZng9VqFdvZkJOTg/j4ePTq1QtAwxuYbdu2YdSoUYorc0/qOvT5559jw4YNqKqqQl1d\nHYCGD24kB/xQ05IWeEfmJC2kzbQbux9++AH//d//jYiICOMTgcGDB6Nr166KK3M1a9YszJ49G8OH\nD3f5u/3792P06NEKqqKmpsNgTp1Ow6TH3ztUVlbiqaeewrFjx2CxWBAWFoZ169ahd+/eqktzIj1M\nw0GHzoarV6+ivLwcFosFDz30kDHYVgId1iGgIShlzpw5GDBggNF+6wijodZJl8A7unVPP/00li1b\nhg4dOiAqKgrFxcVYt24dHn/8cdWlOZF4LcW0d+zatGmD1157DZMnT0ZMTIzqctxy9OsOGDAAtbW1\nbv8fbupaj5qamhsO5pTAUaOPjw969OgBm80Gm82muiy3Xn31VZdNnLtnqk2bNg0LFizA7t27ATSE\nJU2dOhUnTpxQXJkz6WEa13c25OfnO3U2SNrYnTp1Cl988QXq6upQVFQEAJg5c6biqhrosA4BQPv2\n7UX9TKn56RJ4R7cuOzsbq1evxp49e9CzZ0/s3r0bw4YNE7exkxjSZtqNHQCMGTMGa9asweTJk52C\nU+655x6FVf1o/vz5KC0tRVhYGJYtW4YTJ07gpZdeUl0WNZOkpCTVJdyUo8bGTsMkcMTfV1dXY9Gi\nRU7x95I2Ig61tbVOL1YzZszA6tWrFVbknvQwjd27d2PJkiUunQ0dO3YUlTg5Y8YMfP755wgKCnL6\nhFfKxk6HdQgAFi5ciKSkJERGRjqdeA4aNEhhVdScdAm8o1vnaK9+9913ERsbizvvvFPUB0sOEkPa\nTL2x27VrFywWCzZu3Gg8s1gs+PzzzxVW9aPDhw+jpKQEbdu2xZUrVzB06FBu7ExAh8Gckk/DdIm/\n/9e//gW73Y7o6Gi8+uqrRmx7WloaoqOjFVfn6vXXX8fcuXNRVlYGb29vI0xDNd06GwoKClBaWiry\nTcq1pK9Dn376KbZv346DBw86JaEePHhQYVXUnNq1a+f0O15ZWSmqjZmazvjx49G3b1+0b98emzZt\nwtdff4327durLsvgaFnv3bs3Ro4cKepaimnv2Olg4MCBKCwsbPRrap0kD+bUaRh0RkaG6Pj7nj17\n3rDl7YsvvlBQ1c1JC9NITEw0OhtycnIQExMj+gOwSZMmISUlBd7e3qpLuSHJ6xDQkMx7+vRp480U\ntX66BN5R0/jnP/+Ju+66C23btsXly5dRU1OD7t27qy4LgOyQNlNv7Gw2GzZt2oTDhw8bl67nzZsn\npl2rQ4cORiQ20PDplK+vL4CGTwSunYVErUdgYCCKi4tv+kyF4uJiFBYWYvny5Vi5cqXTaVh4eLio\nuUK6xN9LJz1Mo3///i6dDdJGB1xr5MiRKCoqQkhIiHHaIDHNUfI6BAC//e1vsXnzZvzHf/yH6lKo\nBegUeEdNIzc3F19++SW+//57AA3rpJSWdQeJIW2mbsVMTExEXV0dnnzySdjtdmzfvh2JiYli7mOc\nPn1adQmkgOTBnDoNg96xY4cRfx8XFyc2/t5d0lt5ebmYUCfpYRq33XabcVetY8eOkP5Zpbs7bBK+\nj9eTvA4BwP/+7/+ib9++eOSRR0RvkKlp6BB4R01H+l1kB4nXUkx9YhcQEOBy6uXuGVFL0mEwp06n\nYdLj7x977DEEBwfjjTfewKefforLly8jLCxMzMmIdLp0NkRGRiIqKgrR0dGif18cpK9Dhw4dctnE\nc9xB6/bcc8+hS5cuYgPvqOn069dP9F1kyddSTH1i5+HhgYqKCuNNQWVlJTw85HxLOnXq1Og/aovF\ngm+//baFK6KW0LNnT7zzzjuqy7ghHU7DdIm/1yXpTWqYhi6dDVarFVlZWUhKSkJ5eTkGDx6M6Oho\njB49WuTPXPo6dOjQIcTHx6NHjx7Gs82bN3Nj14pJD7yjpjNgwAD84x//EHsXWXRIm93E9u/fb+/R\no4d9+PDh9uHDh9t9fHzsOTk5qssik/vDH/5g/+abb+w2m80+atQoe+fOne1vvPGG6rLcunDhgj05\nOdnu4+Njj4qKsvv6+tpTUlJUl2W32+32mTNn2g8dOuT27z744IMWrqZxv/71r+1XrlyxBwUF2e12\nu72iosL+yCOPKK7KVUREhP1vf/ub3Waz2W02m33btm320aNHqy5LS3V1dfbc3Fz7iy++aA8LC7OP\nGjXKvmrVKtVlOZG+DnXt2tXu5+fn9Jrt+B0iIr2NGDHCfuedd9rHjBljj4mJscfExNjHjx+vuiwX\n+/bts9fX16suw4mpWzEB4OrVqygvL4fFYsGDDz4oKk6VzMkRULBnzx68++67SE5OxrBhw8S0lAGu\np2FxcXFOp2FVVVXKarP/f/x9RUUFAgICEBkZqayWn0KXpDepYRqtobPhwoULyM7OxvTp01WXYpC+\nDg0cOBB79+7FpEmTEBsbi2eeeYbJ0a2c9MA7ajoffvghALgkT0o7kZd4LUVO36ECr7/+OqZPn47A\nwEAADZex//a3v2H+/PmKKyMz02Ewp+Rh0PPnzzfi75ctW4YTJ06Ijr8fO3YsBg0aZNxlSklJEZn0\nJjVM49KlS6pL+EkWLlzY6N9ZLBakpqa2YDU3p8M6dP/99+Pw4cOYN28eYmNjG51jSK2D9MA7ajoj\nR47E+fPnkZ+fD4vFgpCQEHTr1k11WS4kXksx9Ymdu0+bg4KCUFRUpKgiooYL4nv37kX79u2Rl5eH\nf//73xg/fjxOnDihujQtTsN0i7+PiIhATk7OTZ+pJj1MQzqr1er06fO1LBYLZs2apaKsRklehwBg\nzpw5Tm/oN27ciLVr1/K+VSvGwDvzSE9Px9NPP22c0B0+fBirV6/GpEmTFFfmnqSQNlNv7Pz9/VFc\nXGxEttfX1yMgIACffvqp4srI7KQO5tRhGPT17VhS27Nqa2tx5coVhIeHG20nAPDtt98iKioKZWVl\n6oojgsx1aO7cuYiOjkZERATuuOMOpbVQyxo0aBDS09OdAu8mTZok+oM7+mUCAgKwf/9+45TuwoUL\niIiIELeJl3gtxdStmJGRkZgyZQr+8z//E3a7HZs3b0ZUVJTqsohQVlYmcjDn4cOHXU7DpG3sysrK\n4O/vb3xdWVlpfC0p/n7z5s1ISUnBuXPnEBwcbDz38vLCggULFFbm3tNPP41ly5ahQ4cOiIqKQnFx\nMdatW4fHH39cdWlayc/PxyuvvIKqqiqj3VHSv8trSVyHEhISkJmZieTkZHh6ehpjJBxXKqj1Wr16\nNUaNGoVevXoBaOgi2LZtm+KqqDnY7XanKwmdO3cWOaNU4rUUU5/Y1dfX469//avR8jRmzBjMmTPH\naRgiUUtrbDDnhg0bFFbVQIfTsJt9QtazZ88WqeOnSk1NFTN64Uakh2no4sEHH8SaNWswYMAAo1sE\nkPfvUvI65HDx4kVkZ2cjKysLJSUlGDhwIKKjo5UOB6bmxcA7c3j66adRXFxs3OlOS0tDQEAAXnvt\nNdWlAZB9LcWUGztHK8fo0aPFzNwicpA8mFOXYdA60SXprX///vj0008xe/ZsxMbGIjo6WkQqpm6G\nDBmC3Nxc1WXclOR1qDEnT57E+++/jxdeeEF1KdQMHIF3d999N4CGwLudO3cy8K6Vevvtt421ctiw\nYfjd736nuKIfSb6WYsqN3fHjx5GZmYkDBw6wlYPEmTRpElJSUkQO5tThNEy3+PvZs2ejrq4Os2bN\nMpLePDw8xCW9SQ/T0EV2djbS0tIwevRo3HbbbQAa/l1OnDhRcWXOJK9DQMPJzdtvv+3S0irlzRU1\nPQbemccXX3yB7t27o0OHDgAa7qT/z//8j4j3GIDskDZTbuyuxVYOkmbkyJEoKipCSEgI2rVrB6Dh\nDUtGRobiyqg56JT0JjFMQzfTp09HeXk5+vfv79SKKe2ukPR1KDIyEnfddReCg4OdWkV///vfK6yK\nmhMD78wjODgYx44dMz78+u677zBkyBCcPHlScWUNJF9LMXV4CgB06dIF06ZNw7Rp0wD82MpBpEpS\nUhIA18GcEuh2GqYDDw8PVFRUOCW9eXjIXJolhmno5uTJkygrKxPzO90YyesQAFRXV/O12mQYeGce\n9fX1xqYOANq1a2e87kggOaRN5ruHFsJWDpJI8mBOXYZB60SXpLfGwjS4sft5wsLCUFpaiv79+6su\n5YYkr0NAw/expKQEAQEBqkuhFrJq1Sr89a9/xaZNmwD8GHhHrU+XLl2wb98+PProowAaxgp06dJF\ncVU/On36tOoSGmXqVky2cpBEug3mpFt3bdLbQw89ZLS+SaJjmIZEffv2RWVlJXr16uXU4iit9Vb6\nOtSvXz9UVFSI/z7SrWPgnflUVFRg+vTpOHfuHADgvvvuw/bt253C28g9U2/sBgwYgE8++UR1GURO\ndBnMSU3n6NGj+OKLL1BXV2dsnKSdhEkP09DFl19+6TKPyWKx4P7771dUkXvS1yFHkNO1raKAjAAn\naloMvDOPo0eP4te//rXxe11TUwMA4jb0kq+lmLoVk60cJJEugzmpaejS4njhwgX4+fmJDdPQxYsv\nvojt27c7PXv88cddnqkmfR3q2bMnioqKcOTIEVgsFgwbNoxv9Fup0NBQhIaGYsWKFUbg3dq1axl4\n1wq98cYbePLJJ/Hggw8iOjoaUVFRIgO6JF9LMfXG7siRI9i2bRtbOUiUqKgoREZGOg3mjI6OVl0W\nNZOCggItWhylh2no4voukbq6OhQUFCiqpnHS16GUlBRs2bIFEydOhN1ux4wZM/DEE09g0aJFqkuj\nZsTAu9btL3/5C4CGO2yZmZmIi4vDv//9b4waNQpRUVEYMmSI0weg5MrUrZhs5SCpJA/mpKalU4uj\n5DAN6V555RW8+uqrqK2tNWYzAYCnpyfmzp2LP//5zwqrc0/yOuTv74/jx4/j9ttvBwBcvnwZoaGh\n+PjjjxVXRs2FgXfmdOXKFRw8eBBZWVk4evSoyA/CJDH1xg4AWzlIHOmDOalpSZ8X5iA9TEMXzz33\nnMhN3PWkr0P+/v7Iy8tzqi8kJIQbu1aMgXfm4a49fcaMGXjzzTcVVaQPU2/srm/l2Lt3L1s5SDnp\ngzmpaX344YcuzywWi7GBkkJ6mIZOqqur8eWXXxqnDgAwfPhwhRW5kr4OJScnwxts3lYAAB23SURB\nVGq1Or1+x8XFYcmSJapLo2bCwDvzuH7gd11dHQICAlBaWqqwKj2Y+o7d1q1bceLECaOV47nnnkNo\naCg3dqSU9MGc1DQcyW7R0dHo27ev6nJuSnqYhi6effZZpKWlwc/Pz+nUQdrGTvo6tHTpUowYMQIf\nffQRLBYLrFYrBg4cqLosakYMvGv9rm1ZvzYJ09GyTjdn6o0dALRp08btn4lUkT6Yk5qG1WpFVlYW\nkpKSUF5ejsGDBxuzmhwfNkkiPUxDF3v27EF5ebnIWYXX0mEdCgoKQvfu3Y0xIWfPnoWPj4/qsqiZ\nMPCu9Xv++efx/PPPa9OyLpGpWzHZykEScTCn+dTX1+PEiRPGrKb27dsjMjISzzzzjOrSnEgO09BF\ndHQ00tPTxc1lup70dWjDhg1YsWIFunXr5nTyyTt2rRcD78yjoKDghqnLgwYNasFq9GLqjR3Q8I/H\n0coxbNgwtnKQMroM5qTmd+HCBWRnZ2P69OmqSzFID9OQbuHChQCAc+fOoaioCBEREU6nDqmpqSrL\nM+iyDvn6+iIvLw+dO3dWXQq1IAbemUNoaCgKCgqMttuSkhIEBwcbrz8HDx5UWZ5opm/FZCsHSaHL\nYE5qGo43+u5IeqPvEBsbi2PHjhlft2nTBrGxsWLCNKR7+OGHjT+PHz8eQMPPWdo8QF3WIR8fH9xx\nxx2qy6AWxNmF5uHt7Y0tW7bA398fQMP8z+XLl+Ptt99WXJl8pj6xYysHSeQYzJmdnc3BnK2Y1Wp1\naSlysFgsmDVrloqyGhUUFISioiKnZ4GBgSguLlZUkV7mzp1r3KGUdvrljtR1aO3atQCA0tJSlJWV\nISYmxgh5sVgsWLp0qbLaqHlxdqF5+Pn5uSRguntGrky9sWMrB0nHwZwkxejRo7Fw4UKnMI3U1FTk\n5OQorkwPx48fR1ZWFnJycuDp6WmkourQSiZpHUpKSnL6QOT6087ly5erKItaAGcXmseUKVPQqVMn\nzJgxA3a7HW+99RYuXbqEnTt3qi5NPFNv7MLDw5GdnQ1PT0/VpRAZOJjTXPLz8/HKK6+gqqrKmGsm\nMelNepiGTi5evIjs7GxkZWWhpKQEAwcORHR0NB577DHVpRmkr0Pp6eku3y93z6j1YOCdedTW1mLT\npk04cuQIgIZxMImJiWjfvr3iyuQz5caOrRwkGQdzmsuDDz6INWvWYMCAAU4jV6SEkugSpqEru92O\ngoICvP/++3jhhRdUl2OQvg5dX19jz6h1YeBd66Zby7pEpgxPqampgcVigY+PD3r06AGbzQabzaa6\nLDI5DuY0p65du2LChAmqy2iULmEa0jk+UATch6ZI2dRJX4cyMzPx3nvvobq6GosWLTLup9bU1LD7\nxgQYeNe6JSQkIDMzE8nJydq1rEthyhM7B7ZykEQczGku2dnZSEtLw+jRo506ByZOnKi4MmdSwzR0\n4bgbVl5ejvz8fEyYMAF2ux3vvvsuQkJCxLQ4Okhdh4qLi1FYWIjly5dj5cqVxgbZy8sL4eHhuPvu\nu1WXSM2EgXfmokPLukSm3tixlYMk4mBOc5k+fTrKy8vRv39/p1bMbdu2KazqxiSFaehm2LBheO+9\n94zTsJqaGowbN864SyKF9HUoIyMDMTExTr8z1Lox8M68pLasS2TKVky2cpBkTz75JAdzmsjJkydR\nVlYmapaZO9eGaXTs2BG/+c1vsHPnTm7qfqavv/7a6XXG09MTX3/9tcKK3JO+DqWlpeGpp55CbGws\nEhIS0LdvX6X1UPPj7MLWT5eWdclMubHz9vZGcHAwMjIyEBwc7NTKsW7dOtXlkclxMKe5hIWFobS0\nFP3791ddyg198sknTl/X1dXh1KlTiqrR18yZMxESEuKU7CdtZiEgfx3asWMHvvnmG+zcuRNxcXGw\nWCyIj4/H1KlTGbrQyjje7Pfu3RsjR45k4F0r5sjAaKxlnW7O1K2YbOUgiTiY01z69u2LyspK9OrV\nC+3atQMga9zBtWEajtMa4McwDYn3sKQrKCjAkSNHYLFYMHz4cJHJfrqsQxcvXsT27duxfv16+Pn5\n4cyZM1i0aBEWLVqkujRqIpxdaD66tKxLZOqN3fTp03Hs2DG2cpAoHMxpLl9++SWuX4YtFgvuv/9+\nRRW5JzVMQ0f19fU4f/68kewHQFyyn/R1aN++fbBarThz5gxmzpyJuLg4dOvWDVeuXIGfnx+qqqpU\nl0hNjIF35vHQQw+huLjYmFt39epVBAYGory8XHFl8pl6YwfAaOWwWq1s5SAROJjTXNwNgnb3TDXp\nYRq60CXZT/o6NGvWLMyePRvDhw93+bv9+/dj9OjRCqqi5sTAO/N4+eWXkZaW5tSyPnnyZDz//POq\nSxPP9Bs7gK0cJAMHc5qT9EHQDqGhoaLDNHQhPdlP+jrkeJNXUVGBgIAAREZGqi6Jmpkj8C4tLQ1T\npkxxCrwrLS1FXl6e4gqpOejQsi6RqS+X7du3D7/73e8wcuRIfP/998jPz0dmZiZKSkqQnJysujwy\nmYSEBBQVFWHcuHEYNWoUVq1aheLiYtVlUTN55ZVX4OXlhY8//hheXl7Gf926dRM5sNzb2xunTp1C\nQUEBCgoKUFhYiHvvvRcHDx7kpu5nkJ7sJ30dmj9/PtavX49//etfWLZsGVauXKm6JGpmjsC7Dh06\nIDg4GMHBwXj44YcxYcIEvP/++6rLo2YSFBSESZMm4be//S06d+6Ms2fPqi5JC6Y+sWMrB0nFwZzm\nocvdNV3CNKRLSEjAZ599ht/85jfik/0krkP9+/dHSUkJ2rZtiytXrmDo0KFMZzUJBt6Zhy4t6xKZ\nctyBo5VjwIABqK2tdfv/cFNHKnXp0gXTpk3DtGnTnAZzUuvz5z//GdXV1fjyyy9RV1dnPHf3gZNK\nAQEBmDNnjlOYRmBgoOqytOPj4wMfHx/YbDbYbDbV5dyQxHXotttuM97odezY0SV4iFovzi40j/Xr\n16O8vFxsy7pkpjyxS0xMRGlpKcLCwpCTk4OYmBi89NJLqssik7vZYE6Jn+jTrXv22WeRlpYGPz8/\np08m33nnHYVVuZIepqGby5cv4/bbb1ddhgvp61CHDh3Qp08f4+vKykr4+voCkDUmhJoHA+/MITw8\nHNnZ2fD09FRdinZMeWJ3+PBhl1YObuxINQ7mNKc9e/agvLzcmGEnzbVhGkuXLlX+xl53R48exZw5\nc1BTU4OvvvoKxcXF2Lx5M/7rv/5LdWkA5K9Dp0+fVl0CKXTnnXciNjYWtbW1WL9+Pfbs2YPXXnuN\ngXetTK9evRAeHq5Fy7o0pjyxuz6FjnG5JAkHc5pLdHQ00tPTxX7ifPz4cWRmZuLAgQPw9PREZGQk\noqKi2Ib5C4WEhODvf/87Hn30UeN1p3///vj0008VV+aM6xBJw9mF5pGUlAQAHEb/C5jyxK6srAz+\n/v7G15WVlcbXbOUg1b7++mun9gNPT098/fXXCiui5rBw4UIADfeEgoKCEBERYZzaWSwWpKamqizP\nEBoaitDQUKxYscII01i7dq2YMA0dXT+M3MND3kux1HWoU6dOjc5TtFgs+Pbbb1u4Imopu3fvxpIl\nS1zuH3fs2BFbt25VVBU1B8fGTmrLumTyXk1aAFs5SLKZM2ciJCTEaTDnrFmzVJdFTezhhx82/jx+\n/HgA7u80SSIxTEM3Pj4+yM3NBQDYbDakpqaiX79+iqtyJXUdunTpkuoSqIUx8M58pLesS2bKVkwi\n6TiYs/WTPgjaQXqYhm4uXLiAxYsXY//+/bDb7Rg7dixSU1NFpr9xHSIJGHhnPrq0rEtkyhM7tnKQ\ndEFBQejevTvq6upgsVhw9uxZl/Yt0ltCQgKysrKQnJws+u6a9DAN3Xz22Wd46623nJ7l5uZiyJAh\niipqHNchkoCBd+akQ8u6RDyxIxKGgznNR+Ig6OsxTKNpuAvrkhjgxXWIpGDgnfnExsZiyZIlWLBg\nAU6cOIHU1FScPHkSu3btUl2aeNz+EgnDwZzmo8PdNalhGro4duwYjh49igsXLiA5OdkYrF1TU4Mf\nfvhBcXWuuA6RFAy8M59NmzZh8eLFqK6uxr333ouxY8di48aNqsvSAjd2RML4+PjgjjvuUF0GNbOb\n3V174YUXVJTVKKlhGrqw2WyoqalBfX09ampqjOd33HEH/v73vyuszD2uQyQFA+/MR6eWdWnYikkk\nTEJCAj777DMO5mzlkpKSbnh37c0331RdoguGady6qqoq9OzZU3UZN8V1iIhU0aVlXSKe2BEJ4+Pj\nAx8fH9hsNthsNtXlUDNxzOkZNmwYTp06ZdxdW7FiBcaNG6ewssYxTOPWfffdd3jiiSdQVVWFuro6\nAA0bpgMHDiiuzBnXIZKCgXfmoVvLukTc2BEJw8Gc5qLL3TWGaTSNSZMmITExEXPmzDG+jxLnFnId\nIik4u9A8dGtZl4itmETCcDCnubz88stIS0tzurs2efJkPP/886pLc+Lr64u8vDyGadyi4OBgFBQU\nqC7jprgOEZEqurSsS8SNHZEwHMxpPjrcXQsPD0d2drbT6SL9fElJSejatSsmTpyIdu3aGc/vuece\nhVW54jpERKqUl5djzZo14lvWJWIrJpFAHMxpLjrcXevVqxfCw8MZpnGLrFYrLBYL1qxZYzyzWCz4\n/PPPFVblHtchIlJBl5Z1ibhKEwnj4+OD3NxcAA395qmpqejXr5/iqqi56HJ3jWEaTaOqqkp1CT8J\n1yEiUsXT0xOJiYmqy9ASWzGJhLlw4QIWL16M/fv3w263Y+zYsUhNTeXdplZKt7trDNO4NTabDZs2\nbcLhw4dhsVgwYsQIzJs3T1yLK9chIlJFl5Z1ibixIxLG3RBODuZsvXS5u8YwjaYxe/Zs1NXVYdas\nWbDb7di+fTs8PDywdetW1aU54TpERKr07NnTpfVSasu6NNzYEQnDwZzmossgaIZpNI2AgACUlJTc\n9JlqXIeIiPTDO3ZEQnAwpznpdHeNYRq3zsPDAxUVFejTpw8AoLKyUtT3kesQEammS8u6RHJeTYhM\njoM5zUmXQdAM02gaq1evxqhRo9CrVy8ADWEq27ZtU1zVj7gOEZFqiYmJqKurw5NPPmm0rCcmJopr\nWZeIrZhEwnAwp7nocneNYRq3rr6+HikpKZg/fz7Ky8sBAA899BDat2+vuDJXXIeISBVdWtYl4okd\nkTDfffcdnnjiCQ7mNImnnnoKWVlZePTRRwEAgYGBOHTokOKqXH322Wd46623nJ4xTOPnadu2LXbu\n3ImlS5ciMDBQdTk3xHWIiFSR3rIuGb9LRMJwMKf56HB3bcGCBS7BGe6e0Y0NHToUCxYswOTJk3H7\n7bfDbrfDYrFg0KBBqktzwnWIiFSR3rIumbx3D0Qmx8Gc5iL97hrDNJpWYWEhLBYLXnrpJafnBw8e\nVFSRe1yHiEiF+vp6FBcX47PPPhPfsi4RN3ZEwowfPx4bN27kYE6T2LRpExYvXozq6mrce++9GDt2\nLDZu3Ki6LAPDNJpGSkoKFi9ejD/96U8YOnSo6nJuiusQEamgU8u6RAxPIRKGgznNRZdB0AzTuDWB\ngYEoLi7WZhYc1yEiUmXJkiX4/vvvxbesS8SNHRGRQroMgi4vL8eaNWsYpvELTZ06FSdPnkR1dTV8\nfX2d/s5isTDtjYjo/40cOdLtnV5pLesSsRWTSBgO5jQH3e6uMUzj1uzcuRPnz5/H2LFj8c4770D6\nZ6pch4iopenWsi4RT+yIhJk9ezbq6uowa9YsYzCnh4cHB3O2MocOHcLBgwexefNmzJs3z3ju5eWF\n8ePH44EHHlBYnavg4GAUFBSoLkNbc+fORXR0NCIiInDHHXeoLuemuA4RUUvTrWVdIm7siIThYE5z\n0eXuWlJSErp27cowjV/o+PHjyMzMxIEDB+Dp6YnIyEhERUWJDQfgOkRELY0t67eOGzsiYQYNGoT0\n9HSnwZyTJk3CqVOnFFdGzUGXu2sM02g6Fy9eRHZ2NrKyslBSUoKBAwciOjoajz32mOrSDFyHiEiF\nG7Ws6/AhqGrc2BEJk5OTg/j4eJfBnKNGjVJcGTWHgIAAJCYmYtCgQU5314KDgxVXRi3l5MmTeP/9\n9/HCCy+oLsXAdYiIWppuLesSMTyFSBAO5jQfXQZBM0yjaVy9ehVvv/22ywnt9QPLVeI6REQqJCQk\nIDMzE8nJyVq0rEvEEzsiYR555BHk5+erLoNaiC531xim0TQiIyNx1113ITg42DihBYDf//73Cqty\nxXWIiFTSoWVdIm7siIThYE5z0eXuGsM0msaAAQPwySefqC7jprgOEZEkElvWJWIrJpEwhYWFbluz\nOJizdaqqqlJdwk/i4eGBiooKpzANDw++hPxcYWFhKCkpQUBAgOpSbojrEBGpokPLulQ8sSMSwjGY\n86OPPuJgThPR5e4awzSaRr9+/VBRUYFevXoZrbeSYry5DhGRarq0rEvEjR2REBzMaU463F2rr69H\nSkoK5s+fzzCNW+Q4oXW03zpegqXEeHMdIiLVdGlZl4h9NERC+Pn54YEHHkB1dTX8/f2d/k7SJ/rU\ntPLz851+thEREeLa9Nq2bYudO3di6dKlTCe7RT179kRRURGOHDkCi8WCYcOGifqech0iItV0aVmX\niCd2RIJwMKf56DIImmEaTSMlJQVbtmzBxIkTYbfbsXfvXjzxxBNYtGiR6tIMXIeISCXpLeuScWNH\nJAQHc5qTLnfXRo4c6ZLeCTBM4+fy9/fH8ePHcfvttwMALl++jNDQUHz88ceKK2vAdYiIVJPesi4Z\nWzGJhOBgTvPRYRC0I0zjT3/6E8M0mkibNm3c/lkCrkNEpJr0lnXJeGJHJBAHc5qH9EHQDNNoWsnJ\nybBarU6tmHFxcViyZInq0lxwHSIiFXRoWZeKGzsiDXAwZ+sl/e7a1KlTcfLkSVRXV8PX19fp73jn\n4ZcpKCjARx99ZHwSPXDgQNUl/SRch4ioJUhvWZeMGzsiYTiY01x0uLvGMI2mVV9fj/Pnz6Ours74\n2fv4+CiuyhnXISJSxd/fH3l5eejQoQMAoLa2FiEhIdzY/QS8Y0ckzKOPPmoM5pR014qali531xxh\nGh999BHDNJrAhg0bsGLFCnTr1s1p8K60Nyxch4hIlfj4eAwePNipFTMhIUF1WVrgiR2RMBzMaQ66\n3F07fvw4MjMzceDAAYZpNAFfX1/k5eWhc+fOqku5Ia5DRKSSri3rqvHEjkgYDuY0B10GQYeGhiI0\nNBQrVqwwwjTWrl3LMI1fyMfHR4uTT65DRKRSUFAQunfvbrSsnz17VlzLukQ8sSMShoM5zUP3u2sM\n0/jp1q5dCwAoLS1FWVkZYmJicNtttwFo+P1eunSpyvJccB0iIlV0aVmXiCd2RMJkZmYCcB3MSa2L\nbnfXGKZxa2pqamCxWODj44MePXrAZrPBZrOpLqtRXIeISJX169ejvLxcfMu6RNzYEQnDwZzmoNsg\naIZp3JqkpCQAQHp6ukvranp6uoKKbozrEBGpokvLukRsxSQShoM5zUeHQdAM02ga7sJyJAbocB0i\nopamW8u6RNzYEQnDwZwk8e7a3LlzsWDBAoZp/EKZmZl47733kJaWhilTphitjTU1NSgtLUVeXp7i\nCp1xHSKilpaUlOTU/n39jNfly5erKEsrbMUkEqhNmzZu/0ytjy53144cOYJt27YxTOMX8vb2RnBw\nMDIyMhAcHGy8afHy8sK6detUl+cW1yEiakm6taxLxI0dkTAczGkuutxdY5jGrQkMDERgYCDuuece\nxMTEiN8ocR0iIlVeffVVl42du2fkiq2YRAJxMKd56HR3jWEat2769Ok4duwYYmNjkZCQgL59+6ou\nqVFch4ioJenWsi4RN3ZEAtXX1+P8+fPGYE4AHMzZSulyd41hGk3nm2++wc6dO2G1WmGxWBAfH4+p\nU6fCy8tLdWlOuA4RUUsqLi5GYWEhli9fjpUrVzq1rIeHh+Puu+9WXaJ43NgRCcPBnOaiyyBohmk0\nrYsXL2L79u1Yv349/Pz8cObMGSxatEjMRpnrEBGpkpGRoUXLukTc2BEJ4+vri7y8PA7mNImqqioA\nrnfXevbsqagi9/z9/ZGXl4cOHToAAGpraxESEsI3+j/Tvn37YLVacebMGcycORNxcXHo1q0brly5\nAj8/P+Pfg2pch4hIFZ1a1qVheAqRMBzMaS66DIJmmEbT2L17N5YsWYLhw4c7Pe/YsSO2bt2qqCpX\nXIeISJUdO3YYLetxcXGiW9al4YkdkRAczGlOOt1dY5jGL+f42VZUVCAgIACRkZGqS3KL6xARSSG9\nZV0ibuyIhOBgTnPS6e4awzR+ucTERJSWliIsLAw5OTmIiYkRN6sQ4DpEROrp0rIuEVsxiYTgYE7z\n0mEQNMM0bs3hw4dRUlKCtm3b4sqVKxg6dKjYjR3AdYiI1NGlZV0intgRCTNw4EAUFhbe9Bm1DsnJ\nybBarU6tmHFxcViyZInq0pwwTOPWXP87LP13musQEbU0XVrWJeOJHZEQjsGc1dXVWLRokdNgTk9P\nT8XVUXNZunQpRowYYdxds1qtIu+uMUzj1pSVlcHf39/4urKy0vha0ngLrkNEpMr8+fONlvVly5bh\nxIkTIjsbJOPGjkgIb29vBAcHIyMjA8HBwU6DOdetW6e6PGpGQUFB6N69u3F37ezZs2LurjnCNHr3\n7o2RI0cyTOMXOn36tOoSfhKuQ0Skii4t65JxY0ckRGBgIAIDA3HPPfdwMKeJSL+7VlNTA4vFAh8f\nH/To0QM2mw02m011WdqRNpewMVyHiEiV2267zXgd7NixI3hb7OfjHTsiYTiY01x0ubvWWJjG9c/I\nvU6dOrkkTDpYLBZ8++23LVzRjXEdIqKW1qFDB/Tp08f4urKyEr6+vgBktaxLxo0dkUCOwZxWq5WD\nOVu58PBwZGdni7+/xDAN8+E6REQt6WZjDHTpfFCJGzsioTiYs3XTZRC0I0wjLS0NU6ZMcQrTKC0t\nRV5enuIKqTlxHSIi0gfv2BEJc/1gzvz8fKfBnHxD1TrocneNYRrmxHWIiFqabi3rEvHEjkiYWbNm\nYfbs2S6DOQFg//79GD16tIKqqLnocnctIyODYRomwnWIiEg/fIUmEsJut2PPnj0YMGAAamtr3f4/\nfDPV+rz66qs/6ZlqaWlp6NOnD5555hmUlZWpLoeaCdchIiJ98cSOSIjExERjMGdOTg5iYmI4v6UV\n0/HuGsM0Wj+uQ0RE+uLGjkiI/v37uwzmPHXqlOqyqJkUFxejsLAQy5cvx8qVK53uroWHh+Puu+9W\nXaJbDNNo3bgOERHpi+EpREJwMKe56DYImmEa5sB1iIhIXzyxIxKCgznNSZdB0AzTMAeuQ0RE+uLG\njkgIDuY0L8l31+x2O/bu3YuKigoEBAQgMjJSdUnUjLgOERHpixs7IiIBpN5dY5gGERGRHrixIxKC\ngznN6fq7a3FxcU531252gtLcGKZhLlyHiIj0xfAUIiEuXbqkugRSYPfu3ViyZInL3bWOHTti69at\niqr6EcM0zIXrEBGRvnhiR0SkgC531ximQUREpAdu7IiIFNDl7hrDNIiIiPTAjR0RkQK8u0ZERERN\niXfsiIgU0OXuGsM0iIiI9MATOyIiBXh3jYiIiJoST+yIiBQ4ffq06hKIiIioFeGJHRERERERkeZ4\nYkdEpADvrhEREVFT4okdERERERGR5tqoLoCIiIiIiIhuDTd2REREREREmuPGjoiIiIiISHPc2BER\nEd1EVlYW+vbtiwceeACrVq1SXQ4REZELhqcQERHdQH19PR566CHs378f9957Lx555BHs3LkT/fr1\nU10aERGRgSd2REREN5CXl4c+ffqgZ8+e8PT0xJQpU7Bv3z7VZRERETnhxo6IiOgGqqur0aNHD+Pr\n++67D9XV1QorIiIicsWNHRER0Q00NkieiIhIEm7siIiIbuDee+/FV199ZXz91Vdf4b777lNYERER\nkStu7IiIiG7g4YcfxpkzZ1BVVQWbzYa0tDRMmDBBdVlEREROPFQXQEREJJmHhwdef/11REZGor6+\nHrNnz2YiJhERicNxB0RERERERJpjKyYREREREZHmuLEjIiIiIiLSHDd2REREREREmuPGjoiIiIiI\nSHPc2BEREREREWmOGzsiIiIiIiLN/R9KvioFbUpO+gAAAABJRU5ErkJggg==\n",
        "text": [
-        "<matplotlib.figure.Figure at 0x7ff3910>"
+        "<matplotlib.figure.Figure at 0x8e98910>"
        ]
       }
      ],
@@ -292,7 +292,7 @@
        "output_type": "pyout",
        "prompt_number": 8,
        "text": [
-        "<matplotlib.text.Text at 0x80e2b10>"
+        "<matplotlib.text.Text at 0x8f83b10>"
        ]
       },
       {
@@ -300,7 +300,7 @@
        "output_type": "display_data",
        "png": 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0devWgh4YAAAAsotisLMVuzCcwAeJip3R3i4dOtT18jAFfreKXX19Ye/TM9g9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\nQmCC\n",
        "text": [
-        "<matplotlib.figure.Figure at 0x80debd0>"
+        "<matplotlib.figure.Figure at 0x8f7e110>"
        ]
       }
      ],
@@ -336,7 +336,7 @@
       "merge_commits = [\n",
       "    [\n",
       "        commit['parents'][1], # the second parent seems to be the source branch\n",
-      "        commit['committer']['date'] - int(commit['committer']['timezone'])*60*60,\n",
+      "        commit['committer']['date'],\n",
       "        pull_request_number(commit['message']),\n",
       "    ]\n",
       "    for commit in log if is_pull_request_merge(commit['message'])\n",
@@ -369,31 +369,31 @@
         "    <tr>\n",
         "      <th>796a90bdeef377041c353019fdae19aaa72a76d3</th>\n",
         "      <td> 796a90bdeef377041c353019fdae19aaa72a76d3</td>\n",
-        "      <td> 1382845308</td>\n",
+        "      <td> 1380325308</td>\n",
         "      <td> 4294</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>b0d6287174b62de9b89190b868317d12b5bc4ae4</th>\n",
         "      <td> b0d6287174b62de9b89190b868317d12b5bc4ae4</td>\n",
-        "      <td> 1382843422</td>\n",
+        "      <td> 1380323422</td>\n",
         "      <td> 4270</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>07b4962bd787068896f0e2b5dfb977441c7b391a</th>\n",
         "      <td> 07b4962bd787068896f0e2b5dfb977441c7b391a</td>\n",
-        "      <td> 1382821596</td>\n",
+        "      <td> 1380301596</td>\n",
         "      <td> 4278</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</th>\n",
         "      <td> e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</td>\n",
-        "      <td> 1382791407</td>\n",
+        "      <td> 1380271407</td>\n",
         "      <td> 4282</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>68b0f9d2d5f29c540f7873141cb09026c492d0ef</th>\n",
         "      <td> 68b0f9d2d5f29c540f7873141cb09026c492d0ef</td>\n",
-        "      <td> 1382735023</td>\n",
+        "      <td> 1380215023</td>\n",
         "      <td> 4279</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -412,11 +412,11 @@
         "68b0f9d2d5f29c540f7873141cb09026c492d0ef  68b0f9d2d5f29c540f7873141cb09026c492d0ef   \n",
         "\n",
         "                                          merge_timestamp    pr  \n",
-        "796a90bdeef377041c353019fdae19aaa72a76d3       1382845308  4294  \n",
-        "b0d6287174b62de9b89190b868317d12b5bc4ae4       1382843422  4270  \n",
-        "07b4962bd787068896f0e2b5dfb977441c7b391a       1382821596  4278  \n",
-        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77       1382791407  4282  \n",
-        "68b0f9d2d5f29c540f7873141cb09026c492d0ef       1382735023  4279  "
+        "796a90bdeef377041c353019fdae19aaa72a76d3       1380325308  4294  \n",
+        "b0d6287174b62de9b89190b868317d12b5bc4ae4       1380323422  4270  \n",
+        "07b4962bd787068896f0e2b5dfb977441c7b391a       1380301596  4278  \n",
+        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77       1380271407  4282  \n",
+        "68b0f9d2d5f29c540f7873141cb09026c492d0ef       1380215023  4279  "
        ]
       }
      ],
@@ -430,7 +430,7 @@
       "pr_commits = [\n",
       "    [\n",
       "        commit['commit'],\n",
-      "        commit['committer']['date'] - int(commit['committer']['timezone'])*60*60,\n",
+      "        commit['committer']['date'],\n",
       "        len(commit['changes']), # let's sneak in another basic churn metric\n",
       "    ]\n",
       "    for commit in log\n",
@@ -460,31 +460,31 @@
         "    <tr>\n",
         "      <th>796a90bdeef377041c353019fdae19aaa72a76d3</th>\n",
         "      <td> 796a90bdeef377041c353019fdae19aaa72a76d3</td>\n",
-        "      <td> 1382845245</td>\n",
+        "      <td> 1380325245</td>\n",
         "      <td> 1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</th>\n",
         "      <td> e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</td>\n",
-        "      <td> 1382682595</td>\n",
+        "      <td> 1380162595</td>\n",
         "      <td> 1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>68b0f9d2d5f29c540f7873141cb09026c492d0ef</th>\n",
         "      <td> 68b0f9d2d5f29c540f7873141cb09026c492d0ef</td>\n",
-        "      <td> 1382678115</td>\n",
+        "      <td> 1380158115</td>\n",
         "      <td> 3</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>07b4962bd787068896f0e2b5dfb977441c7b391a</th>\n",
         "      <td> 07b4962bd787068896f0e2b5dfb977441c7b391a</td>\n",
-        "      <td> 1382673904</td>\n",
+        "      <td> 1380153904</td>\n",
         "      <td> 1</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa</th>\n",
         "      <td> d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa</td>\n",
-        "      <td> 1379379263</td>\n",
+        "      <td> 1380099263</td>\n",
         "      <td> 1</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -503,11 +503,11 @@
         "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa  d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa   \n",
         "\n",
         "                                          commit_timestamp  churn  \n",
-        "796a90bdeef377041c353019fdae19aaa72a76d3        1382845245      1  \n",
-        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77        1382682595      1  \n",
-        "68b0f9d2d5f29c540f7873141cb09026c492d0ef        1382678115      3  \n",
-        "07b4962bd787068896f0e2b5dfb977441c7b391a        1382673904      1  \n",
-        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa        1379379263      1  "
+        "796a90bdeef377041c353019fdae19aaa72a76d3        1380325245      1  \n",
+        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77        1380162595      1  \n",
+        "68b0f9d2d5f29c540f7873141cb09026c492d0ef        1380158115      3  \n",
+        "07b4962bd787068896f0e2b5dfb977441c7b391a        1380153904      1  \n",
+        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa        1380099263      1  "
        ]
       }
      ],
@@ -549,46 +549,46 @@
         "    <tr>\n",
         "      <th>796a90bdeef377041c353019fdae19aaa72a76d3</th>\n",
         "      <td> 796a90bdeef377041c353019fdae19aaa72a76d3</td>\n",
-        "      <td> 1382845245</td>\n",
+        "      <td> 1380325245</td>\n",
         "      <td> 1</td>\n",
         "      <td> 796a90bdeef377041c353019fdae19aaa72a76d3</td>\n",
-        "      <td> 1382845308</td>\n",
+        "      <td> 1380325308</td>\n",
         "      <td> 4294</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</th>\n",
         "      <td> e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</td>\n",
-        "      <td> 1382682595</td>\n",
+        "      <td> 1380162595</td>\n",
         "      <td> 1</td>\n",
         "      <td> e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</td>\n",
-        "      <td> 1382791407</td>\n",
+        "      <td> 1380271407</td>\n",
         "      <td> 4282</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>68b0f9d2d5f29c540f7873141cb09026c492d0ef</th>\n",
         "      <td> 68b0f9d2d5f29c540f7873141cb09026c492d0ef</td>\n",
-        "      <td> 1382678115</td>\n",
+        "      <td> 1380158115</td>\n",
         "      <td> 3</td>\n",
         "      <td> 68b0f9d2d5f29c540f7873141cb09026c492d0ef</td>\n",
-        "      <td> 1382735023</td>\n",
+        "      <td> 1380215023</td>\n",
         "      <td> 4279</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>07b4962bd787068896f0e2b5dfb977441c7b391a</th>\n",
         "      <td> 07b4962bd787068896f0e2b5dfb977441c7b391a</td>\n",
-        "      <td> 1382673904</td>\n",
+        "      <td> 1380153904</td>\n",
         "      <td> 1</td>\n",
         "      <td> 07b4962bd787068896f0e2b5dfb977441c7b391a</td>\n",
-        "      <td> 1382821596</td>\n",
+        "      <td> 1380301596</td>\n",
         "      <td> 4278</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa</th>\n",
         "      <td> d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa</td>\n",
-        "      <td> 1379379263</td>\n",
+        "      <td> 1380099263</td>\n",
         "      <td> 1</td>\n",
         "      <td> d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa</td>\n",
-        "      <td> 1382669814</td>\n",
+        "      <td> 1380149814</td>\n",
         "      <td> 4131</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -607,11 +607,11 @@
         "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa  d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa   \n",
         "\n",
         "                                          commit_timestamp  churn  \\\n",
-        "796a90bdeef377041c353019fdae19aaa72a76d3        1382845245      1   \n",
-        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77        1382682595      1   \n",
-        "68b0f9d2d5f29c540f7873141cb09026c492d0ef        1382678115      3   \n",
-        "07b4962bd787068896f0e2b5dfb977441c7b391a        1382673904      1   \n",
-        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa        1379379263      1   \n",
+        "796a90bdeef377041c353019fdae19aaa72a76d3        1380325245      1   \n",
+        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77        1380162595      1   \n",
+        "68b0f9d2d5f29c540f7873141cb09026c492d0ef        1380158115      3   \n",
+        "07b4962bd787068896f0e2b5dfb977441c7b391a        1380153904      1   \n",
+        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa        1380099263      1   \n",
         "\n",
         "                                                                      merge_commit  \\\n",
         "796a90bdeef377041c353019fdae19aaa72a76d3  796a90bdeef377041c353019fdae19aaa72a76d3   \n",
@@ -621,11 +621,11 @@
         "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa  d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa   \n",
         "\n",
         "                                          merge_timestamp    pr  \n",
-        "796a90bdeef377041c353019fdae19aaa72a76d3       1382845308  4294  \n",
-        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77       1382791407  4282  \n",
-        "68b0f9d2d5f29c540f7873141cb09026c492d0ef       1382735023  4279  \n",
-        "07b4962bd787068896f0e2b5dfb977441c7b391a       1382821596  4278  \n",
-        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa       1382669814  4131  "
+        "796a90bdeef377041c353019fdae19aaa72a76d3       1380325308  4294  \n",
+        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77       1380271407  4282  \n",
+        "68b0f9d2d5f29c540f7873141cb09026c492d0ef       1380215023  4279  \n",
+        "07b4962bd787068896f0e2b5dfb977441c7b391a       1380301596  4278  \n",
+        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa       1380149814  4131  "
        ]
       }
      ],
@@ -680,77 +680,77 @@
         "    <tr>\n",
         "      <th>796a90bdeef377041c353019fdae19aaa72a76d3</th>\n",
         "      <td> 796a90bdeef377041c353019fdae19aaa72a76d3</td>\n",
-        "      <td> 1382845245</td>\n",
+        "      <td> 1380325245</td>\n",
         "      <td> 1</td>\n",
         "      <td> 796a90bdeef377041c353019fdae19aaa72a76d3</td>\n",
-        "      <td> 1382845308</td>\n",
+        "      <td> 1380325308</td>\n",
         "      <td> 4294</td>\n",
-        "      <td>      63</td>\n",
+        "      <td>     63</td>\n",
         "      <td> 0.000104</td>\n",
-        "      <td>  0.000729</td>\n",
-        "      <td>   0.017500</td>\n",
-        "      <td>     1.050000</td>\n",
-        "      <td>      63</td>\n",
+        "      <td> 0.000729</td>\n",
+        "      <td>  0.017500</td>\n",
+        "      <td>    1.050000</td>\n",
+        "      <td>     63</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</th>\n",
         "      <td> e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</td>\n",
-        "      <td> 1382682595</td>\n",
+        "      <td> 1380162595</td>\n",
         "      <td> 1</td>\n",
         "      <td> e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77</td>\n",
-        "      <td> 1382791407</td>\n",
+        "      <td> 1380271407</td>\n",
         "      <td> 4282</td>\n",
-        "      <td>  108812</td>\n",
+        "      <td> 108812</td>\n",
         "      <td> 0.179914</td>\n",
-        "      <td>  1.259398</td>\n",
-        "      <td>  30.225556</td>\n",
-        "      <td>  1813.533333</td>\n",
-        "      <td>  108812</td>\n",
+        "      <td> 1.259398</td>\n",
+        "      <td> 30.225556</td>\n",
+        "      <td> 1813.533333</td>\n",
+        "      <td> 108812</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>68b0f9d2d5f29c540f7873141cb09026c492d0ef</th>\n",
         "      <td> 68b0f9d2d5f29c540f7873141cb09026c492d0ef</td>\n",
-        "      <td> 1382678115</td>\n",
+        "      <td> 1380158115</td>\n",
         "      <td> 3</td>\n",
         "      <td> 68b0f9d2d5f29c540f7873141cb09026c492d0ef</td>\n",
-        "      <td> 1382735023</td>\n",
+        "      <td> 1380215023</td>\n",
         "      <td> 4279</td>\n",
-        "      <td>   56908</td>\n",
+        "      <td>  56908</td>\n",
         "      <td> 0.094094</td>\n",
-        "      <td>  0.658657</td>\n",
-        "      <td>  15.807778</td>\n",
-        "      <td>   948.466667</td>\n",
-        "      <td>   56908</td>\n",
+        "      <td> 0.658657</td>\n",
+        "      <td> 15.807778</td>\n",
+        "      <td>  948.466667</td>\n",
+        "      <td>  56908</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>07b4962bd787068896f0e2b5dfb977441c7b391a</th>\n",
         "      <td> 07b4962bd787068896f0e2b5dfb977441c7b391a</td>\n",
-        "      <td> 1382673904</td>\n",
+        "      <td> 1380153904</td>\n",
         "      <td> 1</td>\n",
         "      <td> 07b4962bd787068896f0e2b5dfb977441c7b391a</td>\n",
-        "      <td> 1382821596</td>\n",
+        "      <td> 1380301596</td>\n",
         "      <td> 4278</td>\n",
-        "      <td>  147692</td>\n",
+        "      <td> 147692</td>\n",
         "      <td> 0.244200</td>\n",
-        "      <td>  1.709398</td>\n",
-        "      <td>  41.025556</td>\n",
-        "      <td>  2461.533333</td>\n",
-        "      <td>  147692</td>\n",
+        "      <td> 1.709398</td>\n",
+        "      <td> 41.025556</td>\n",
+        "      <td> 2461.533333</td>\n",
+        "      <td> 147692</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa</th>\n",
         "      <td> d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa</td>\n",
-        "      <td> 1379379263</td>\n",
+        "      <td> 1380099263</td>\n",
         "      <td> 1</td>\n",
         "      <td> d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa</td>\n",
-        "      <td> 1382669814</td>\n",
+        "      <td> 1380149814</td>\n",
         "      <td> 4131</td>\n",
-        "      <td> 3290551</td>\n",
-        "      <td> 5.440726</td>\n",
-        "      <td> 38.085081</td>\n",
-        "      <td> 914.041944</td>\n",
-        "      <td> 54842.516667</td>\n",
-        "      <td> 3290551</td>\n",
+        "      <td>  50551</td>\n",
+        "      <td> 0.083583</td>\n",
+        "      <td> 0.585081</td>\n",
+        "      <td> 14.041944</td>\n",
+        "      <td>  842.516667</td>\n",
+        "      <td>  50551</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
         "</table>\n",
@@ -768,11 +768,11 @@
         "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa  d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa   \n",
         "\n",
         "                                          commit_timestamp  churn  \\\n",
-        "796a90bdeef377041c353019fdae19aaa72a76d3        1382845245      1   \n",
-        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77        1382682595      1   \n",
-        "68b0f9d2d5f29c540f7873141cb09026c492d0ef        1382678115      3   \n",
-        "07b4962bd787068896f0e2b5dfb977441c7b391a        1382673904      1   \n",
-        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa        1379379263      1   \n",
+        "796a90bdeef377041c353019fdae19aaa72a76d3        1380325245      1   \n",
+        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77        1380162595      1   \n",
+        "68b0f9d2d5f29c540f7873141cb09026c492d0ef        1380158115      3   \n",
+        "07b4962bd787068896f0e2b5dfb977441c7b391a        1380153904      1   \n",
+        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa        1380099263      1   \n",
         "\n",
         "                                                                      merge_commit  \\\n",
         "796a90bdeef377041c353019fdae19aaa72a76d3  796a90bdeef377041c353019fdae19aaa72a76d3   \n",
@@ -781,26 +781,26 @@
         "07b4962bd787068896f0e2b5dfb977441c7b391a  07b4962bd787068896f0e2b5dfb977441c7b391a   \n",
         "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa  d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa   \n",
         "\n",
-        "                                          merge_timestamp    pr    delta  \\\n",
-        "796a90bdeef377041c353019fdae19aaa72a76d3       1382845308  4294       63   \n",
-        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77       1382791407  4282   108812   \n",
-        "68b0f9d2d5f29c540f7873141cb09026c492d0ef       1382735023  4279    56908   \n",
-        "07b4962bd787068896f0e2b5dfb977441c7b391a       1382821596  4278   147692   \n",
-        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa       1382669814  4131  3290551   \n",
+        "                                          merge_timestamp    pr   delta  \\\n",
+        "796a90bdeef377041c353019fdae19aaa72a76d3       1380325308  4294      63   \n",
+        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77       1380271407  4282  108812   \n",
+        "68b0f9d2d5f29c540f7873141cb09026c492d0ef       1380215023  4279   56908   \n",
+        "07b4962bd787068896f0e2b5dfb977441c7b391a       1380301596  4278  147692   \n",
+        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa       1380149814  4131   50551   \n",
         "\n",
         "                                          delta_weeks  delta_days  delta_hours  \\\n",
         "796a90bdeef377041c353019fdae19aaa72a76d3     0.000104    0.000729     0.017500   \n",
         "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77     0.179914    1.259398    30.225556   \n",
         "68b0f9d2d5f29c540f7873141cb09026c492d0ef     0.094094    0.658657    15.807778   \n",
         "07b4962bd787068896f0e2b5dfb977441c7b391a     0.244200    1.709398    41.025556   \n",
-        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa     5.440726   38.085081   914.041944   \n",
+        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa     0.083583    0.585081    14.041944   \n",
         "\n",
-        "                                            delta_mins  delta_secs  \n",
-        "796a90bdeef377041c353019fdae19aaa72a76d3      1.050000          63  \n",
-        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77   1813.533333      108812  \n",
-        "68b0f9d2d5f29c540f7873141cb09026c492d0ef    948.466667       56908  \n",
-        "07b4962bd787068896f0e2b5dfb977441c7b391a   2461.533333      147692  \n",
-        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa  54842.516667     3290551  "
+        "                                           delta_mins  delta_secs  \n",
+        "796a90bdeef377041c353019fdae19aaa72a76d3     1.050000          63  \n",
+        "e51d4d021c57c846ff1ad439d20b3fcc6b1ebc77  1813.533333      108812  \n",
+        "68b0f9d2d5f29c540f7873141cb09026c492d0ef   948.466667       56908  \n",
+        "07b4962bd787068896f0e2b5dfb977441c7b391a  2461.533333      147692  \n",
+        "d4d6bc63d6c6dd34c5fe1270a90caec2e0208bfa   842.516667       50551  "
        ]
       }
      ],
@@ -819,7 +819,8 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "both_df[['delta_days']].boxplot()"
+      "rcParams['figure.figsize'] = (15, 3)\n",
+      "both_df[['delta_days']].boxplot(vert=False)"
      ],
      "language": "python",
      "metadata": {},
@@ -829,22 +830,22 @@
        "output_type": "pyout",
        "prompt_number": 13,
        "text": [
-        "{'boxes': [<matplotlib.lines.Line2D at 0x83afe50>],\n",
-        " 'caps': [<matplotlib.lines.Line2D at 0x83af450>,\n",
-        "  <matplotlib.lines.Line2D at 0x83af950>],\n",
-        " 'fliers': [<matplotlib.lines.Line2D at 0x83b3890>,\n",
-        "  <matplotlib.lines.Line2D at 0x83b3d50>],\n",
-        " 'medians': [<matplotlib.lines.Line2D at 0x83b3390>],\n",
-        " 'whiskers': [<matplotlib.lines.Line2D at 0x83a9c50>,\n",
-        "  <matplotlib.lines.Line2D at 0x83a9e90>]}"
+        "{'boxes': [<matplotlib.lines.Line2D at 0x9192fd0>],\n",
+        " 'caps': [<matplotlib.lines.Line2D at 0x91925d0>,\n",
+        "  <matplotlib.lines.Line2D at 0x9192ad0>],\n",
+        " 'fliers': [<matplotlib.lines.Line2D at 0x9196a10>,\n",
+        "  <matplotlib.lines.Line2D at 0x9196ed0>],\n",
+        " 'medians': [<matplotlib.lines.Line2D at 0x9196510>],\n",
+        " 'whiskers': [<matplotlib.lines.Line2D at 0x918ddd0>,\n",
+        "  <matplotlib.lines.Line2D at 0x9192050>]}"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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meudI/nuYmuqNHz/e287Lq3lu/Pia7ePHvWvE9yf/fKv4sdGoNy4rq+a41NTaq4pf+/jx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\n",
        "text": [
-        "<matplotlib.figure.Figure at 0x827d0d0>"
+        "<matplotlib.figure.Figure at 0x9139b10>"
        ]
       }
      ],
@@ -863,7 +864,8 @@
      "cell_type": "code",
      "collapsed": false,
      "input": [
-      "both_df[both_df['delta_days'] < 30][['delta_days']].boxplot()"
+      "rcParams['figure.figsize'] = (15, 3)\n",
+      "both_df[both_df['delta_days'] < 30][['delta_days']].boxplot(vert=False)"
      ],
      "language": "python",
      "metadata": {},
@@ -873,22 +875,22 @@
        "output_type": "pyout",
        "prompt_number": 14,
        "text": [
-        "{'boxes': [<matplotlib.lines.Line2D at 0x82f2410>],\n",
-        " 'caps': [<matplotlib.lines.Line2D at 0x82f09d0>,\n",
-        "  <matplotlib.lines.Line2D at 0x82f0ed0>],\n",
-        " 'fliers': [<matplotlib.lines.Line2D at 0x82f2e10>,\n",
-        "  <matplotlib.lines.Line2D at 0x82fa310>],\n",
-        " 'medians': [<matplotlib.lines.Line2D at 0x82f2910>],\n",
-        " 'whiskers': [<matplotlib.lines.Line2D at 0x82f0210>,\n",
-        "  <matplotlib.lines.Line2D at 0x82f0450>]}"
+        "{'boxes': [<matplotlib.lines.Line2D at 0x91e1710>],\n",
+        " 'caps': [<matplotlib.lines.Line2D at 0x91d8cd0>,\n",
+        "  <matplotlib.lines.Line2D at 0x91e1210>],\n",
+        " 'fliers': [<matplotlib.lines.Line2D at 0x91e4150>,\n",
+        "  <matplotlib.lines.Line2D at 0x91e4610>],\n",
+        " 'medians': [<matplotlib.lines.Line2D at 0x91e1c10>],\n",
+        " 'whiskers': [<matplotlib.lines.Line2D at 0x91d8510>,\n",
+        "  <matplotlib.lines.Line2D at 0x91d8750>]}"
        ]
       },
       {
        "metadata": {},
        "output_type": "display_data",
-       "png": 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+       "png": 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s379/cNvy5cuju7s7crlcHH/88RER8dxzz8Xs2bPj8ssvj7POOiu2bNlSczEPYyn/jxLU\nQ35IIT+kkB9SyA9ZGPXtwQsWLIjPf/7zMX/+/Jg+fXosWrQocrlc3HHHHXHJJZfEd77znXjrrbfi\n/PPPj3nz5kXE0G8YXr58eXzta1+LyZMnxxNPPBFf/epXY+7cuTFjxoxYvHjxqIO67bbb4qKLLopc\nLhennXba4DkvvfTSWLp0adx+++3x6U9/OqZMmTJ4zPTp02POnDlxTvlXr0bE3XffHT/96U/jsMMO\ni5kzZ8a3vvWt+lYJRlWIiIh8PmLatNI9lb/zq/L+0ts/DtwWUdpe3lZ6S1jE2WcfuP8ZZ0SU3+F+\nxhmlY3fsGDpH9Tmrle8fbf/Rvg5Vvpv/7LNrO7a832iPW16b4VSOuXq/8cyzci3HmmOt6zHWY450\njso1qd5npLWo5by1jGusrFRnbrS1GO25HW0s49lvrOd4vMeOJ0e1nLN8e7jndDzG+/3faM9j9ViG\nG/94Hq+WbB+s719rfb5rXffxXgvHOq6exxrv+VLyf7DU81pNPVfKeVLX/mCvZ6PquVapGw/m14Zm\ncLBeP82co9SvWfXKFYsVjacT2O7du2PevHmxadOmmDp1ak3HlIrhYtS8Arlc1L5zc5nAQ29ahUIh\n8vl85HK5aJGXEQ1Uzg/UQ35IIT+kkB9S1Pt986hvD54oHn744ZgzZ05cccUVNResAAAANL9Mf9J6\n2WWXDfaulq1cuTKWLVvWkMf3k1YOBj9pBQCAsdX7fXPLvD24HopWAACAxmjrtwdDFob+jhiMn/yQ\nQn5IIT+kkB+yoGgFAACgaXl7sLcHAwAAvOO8PRgAAICWo2iN0k8ha/kYz77N9nHkkdmucSvS00EK\n+SGF/JBCfkghP2Th0KwHkLXx/XS6GN5hCwAA0Dht39PaxtMHAABoGD2tAAAAtBxFK9RJTwcp5IcU\n8kMK+SGF/JAFRSsAAABNS09r+04fAACgYfS0AgAA0HIUrVAnPR2kkB9SyA8p5IcU8kMWFK0AAAA0\nLT2t7Tt9AACAhtHTCgAAQMtRtEKd9HSQQn5IIT+kkB9SyA9ZULQCAADQtPS0tu/0AQAAGkZPKwAA\nAC1H0Qp10tNBCvkhhfyQQn5IIT9kQdEKAABA09LT2r7TBwAAaBg9rQAAALQcRSvUSU8HKeSHFPJD\nCvkhhfyQBUUrAAAATUtPa/tOHwAAoGH0tAIAANByFK1QJz0dpJAfUsgPKeSHFPJDFhStAAAANC09\nre07fQAAgIbR0woAAEDLUbRCnfR0kEJ+SCE/pJAfUsgPWVC0AgAA0LT0tLbv9AEAABpGTysAAAAt\nR9EKddLTQQr5IYX8kEJ+SCE/ZEHRCgAAQNPS09q+0wcAAGgYPa0AAAC0HEUr1ElPBynkhxTyQwr5\nIYX8kAVFKwAAAE1LT2v7Th8AAKBh9LQCAADQchStUCc9HaSQH1LIDynkhxTyQxYUrQAAADQtPa3t\nO30AAICG0dMKAABAy1G0Qp30dJBCfkghP6SQH1LID1lQtAIAANC09LS27/QBAAAaRk8rAAAALUfR\nCnXS00EK+SGF/JBCfkghP2RB0QoAAEDT0tPavtMHAABoGD2tAAAAtBxFK9RJTwcp5IcU8kMK+SGF\n/JAFRSsAAABNS09r+04fAACgYfS0AgAA0HIUrVAnPR2kkB9SyA8p5IcU8kMWFK0AAAA0LT2t7Tt9\nAACAhtHTCgAAQMtRtEKd9HSQQn5IIT+kkB9SyA9ZULQCAADQtPS0tu/0AQAAGkZPKwAAAC1H0Qp1\n0tNBCvkhhfyQQn5IIT9kQdEKderr68t6CExg8kMK+SGF/JBCfsiCohXq9Oqrr2Y9BCYw+SGF/JBC\nfkghP2RB0QoAAEDTUrRCnfr7+7MeAhOY/JBCfkghP6SQH7LQ9n/yBgAAgMaop/w89B0Yx4TRxvU6\nAADAhODtwQAAADQtRSsAAABNS9EKAABA02rbovXBBx+M448/Po499thYs2ZN1sNhguns7Ix58+bF\nggULYtGiRVkPhyZ30UUXRUdHR5x00kmD973yyivxqU99Kj70oQ/Faaed5u/eMaLh8rNq1aqYNWtW\nLFiwIBYsWBAPPvhghiOkmb3wwgvxiU98Ik488cSYO3du3HzzzRHhGkRtRsqPaxC1GBgYiMWLF0dX\nV1fMmTMnvvnNb0ZEfdeftvztwfv374/jjjsuHn744Tj66KPjIx/5SNx5551xwgknZD00JojZs2dH\nb29vHHXUUVkPhQngscceiylTpsSXvvSl2LJlS0REXH311fG+970vrr766lizZk3s3Lkzrr/++oxH\nSjMaLj+rV6+OqVOnxpVXXpnx6Gh227Zti23btkVXV1fs2rUrTj755Ojp6YnbbrvNNYgxjZSfu+++\n2zWImuzevTsmT54c+/bti1NOOSW+//3vx3333Tfu609b/qT1qaeeimOOOSY6OzvjsMMOiy984Qtx\n7733Zj0sJpg2/P8e6nTqqafGkUceecB99913XyxbtiwiIpYtWxY9PT1ZDI0JYLj8RLgGUZsZM2ZE\nV1dXRERMmTIlTjjhhHjxxRddg6jJSPmJcA2iNpMnT46IiL1798b+/fvjyCOPrOv605ZF64svvhgf\n+MAHBm/PmjVr8AUItcjlcvHJT34yFi5cGD/5yU+yHg4T0Pbt26OjoyMiIjo6OmL79u0Zj4iJ5pZb\nbon58+fHihUrvLWTmvT398emTZti8eLFrkGMWzk/H/3oRyPCNYjavP3229HV1RUdHR2DbzWv5/rT\nlkVrLpfLeghMcI8//nhs2rQpHnjggbj11lvjsccey3pITGC5XM51iXG55JJL4rnnnou+vr6YOXNm\nfOMb38h6SDS5Xbt2xdKlS+Omm26KqVOnHrDNNYix7Nq1K84777y46aabYsqUKa5B1Oxd73pX9PX1\nxdatW+MPf/hDPProowdsr/X605ZF69FHHx0vvPDC4O0XXnghZs2aleGImGhmzpwZERHvf//745xz\nzomnnnoq4xEx0XR0dMS2bdsiIuLll1+O6dOnZzwiJpLp06cPfqH/yle+4hrEqN56661YunRpXHjh\nhXH22WdHhGsQtSvn54tf/OJgflyDGK8jjjgiTj/99Ojt7a3r+tOWRevChQvjmWeeif7+/ti7d2/c\nddddceaZZ2Y9LCaI3bt3xxtvvBEREW+++Wb8/ve/P+C3ekItzjzzzFi3bl1ERKxbt27wGwGoxcsv\nvzz4+a9//WvXIEZULBZjxYoVMWfOnFi5cuXg/a5B1GKk/LgGUYsdO3YMvnV8z5498dBDD8WCBQvq\nuv605W8Pjoh44IEHYuXKlbF///5YsWLF4K9ghrE899xzcc4550RExL59++KCCy6QH0Z1/vnnx/r1\n62PHjh3R0dER1157bZx11lnxuc99Lv71r39FZ2dn3H333TFt2rSsh0oTqs7P6tWro1AoRF9fX+Ry\nuZg9e3b8+Mc/HuwPgkp//OMfY8mSJTFv3rzBt+B973vfi0WLFrkGMabh8vPd73437rzzTtcgxrRl\ny5ZYtmxZvP322/H222/HhRdeGFdddVW88sor477+tG3RCgAAQPNry7cHAwAAMDEoWgEAAGhailYA\nAACalqIVAACApqVoBQAAoGkpWgEAAGha/wdB8PbVmD2Q9wAAAABJRU5ErkJggg==\n",
        "text": [
-        "<matplotlib.figure.Figure at 0x83da3d0>"
+        "<matplotlib.figure.Figure at 0x91af190>"
        ]
       }
      ],
@@ -898,7 +900,7 @@
      "cell_type": "markdown",
      "metadata": {},
      "source": [
-      "Based on this, it looks like most review periods are between -4 days (whatever that means) and about two weeks. The median is (I'm eyeballing this) around 1 day. Not bad at all.\n",
+      "Based on this, it looks like most reviews happen within the first five days. The median is (I'm eyeballing this) around 1 day. Not bad at all.\n",
       "\n",
       "If we look closely at the pull requests outside this range, we might see any number of things: pull requests that are large and hard to understand or pull requests that are blocked by some other task. I don't think pandas would help us much: we'd have to use our brains and look for patterns.\n",
       "\n",
@@ -910,7 +912,7 @@
      "collapsed": false,
      "input": [
       "# The data is skewed, so i'll use the spearman correlation\n",
-      "both_df[['churn', 'delta']].corr(method='spearman')"
+      "both_df[['churn', 'delta']].corr(method='spearman')\n"
      ],
      "language": "python",
      "metadata": {},
@@ -930,11 +932,11 @@
         "    <tr>\n",
         "      <th>churn</th>\n",
         "      <td> 1.000000</td>\n",
-        "      <td>-0.001523</td>\n",
+        "      <td> 0.048028</td>\n",
         "    </tr>\n",
         "    <tr>\n",
         "      <th>delta</th>\n",
-        "      <td>-0.001523</td>\n",
+        "      <td> 0.048028</td>\n",
         "      <td> 1.000000</td>\n",
         "    </tr>\n",
         "  </tbody>\n",
@@ -946,8 +948,8 @@
        "prompt_number": 15,
        "text": [
         "          churn     delta\n",
-        "churn  1.000000 -0.001523\n",
-        "delta -0.001523  1.000000"
+        "churn  1.000000  0.048028\n",
+        "delta  0.048028  1.000000"
        ]
       }
      ],
@@ -971,15 +973,19 @@
       "\n",
       "## Threats to Validity\n",
       "\n",
-      "1. Dates are user-system-reported and thus inaccurate.\n",
-      "2. It is 1am on a Friday night.\n",
-      "3. The churn metric only represents the tip (ha) of the pull request iceberg.\n",
-      "4. This analysis doesn't look at how review time changed over time. Can we get a less skewed picture of pull request length by looking at only the period in which the project was funded?\n",
+      "1. It is 1am on a Friday night.\n",
+      "2. The churn metric only represents the tip (ha) of the pull request iceberg.\n",
+      "3. This analysis doesn't look at how review time changed over time. Can we get a less skewed picture of pull request length by looking at only the period in which the project was funded?\n",
+      "4. This analysis doesn't look at actual review time \u2014 the pull request could have been made much later than when the pull request commit was made.\n",
       "\n",
       "## Conclusions\n",
       "\n",
       "1. The IPython folks are very prompt. Send them a decent pull request and they'll probably merge it within a day.\n",
-      "2. The IPython Notebook is pretty cool.\n"
+      "2. The IPython Notebook is pretty cool.\n",
+      "\n",
+      "## Updates\n",
+      "\n",
+      "A previous version of this notebook was incorrectly adding timezone differences to timestamps. After some experimentation, I've discovered that the timestamps provided by `git2json` don't need to be adjusted for timezone unless you want to display it in a human-readable format. Fixing this bug solved the \"time travel\" issue."
      ]
     }
    ],