diff --git a/trackinglosses_endVelo_momEff.ipynb b/trackinglosses_endVelo_momEff.ipynb
index 38d7e7e..7e36ecb 100644
--- a/trackinglosses_endVelo_momEff.ipynb
+++ b/trackinglosses_endVelo_momEff.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -38,18 +38,15 @@
     "\n",
     "# selektiere nur elektronen von B->K*ee\n",
     "allcolumns = file.arrays()\n",
-    "found = allcolumns[\n",
-    "    (allcolumns.isElectron) & (~allcolumns.lost) & (allcolumns.fromB)\n",
-    "]  # B: 9056\n",
-    "lost = allcolumns[\n",
-    "    (allcolumns.isElectron) & (allcolumns.lost) & (allcolumns.fromB)\n",
-    "]  # B: 1466\n",
+    "found = allcolumns[(allcolumns.isElectron) & (~allcolumns.lost) &\n",
+    "                   (allcolumns.fromB)]  # B: 9056\n",
+    "lost = allcolumns[(allcolumns.isElectron) & (allcolumns.lost) &\n",
+    "                  (allcolumns.fromB)]  # B: 1466\n",
     "\n",
     "electrons = allcolumns[(allcolumns.isElectron) & (allcolumns.fromB)]\n",
     "\n",
-    "notelectrons = allcolumns[\n",
-    "    (~allcolumns.isElectron) & (allcolumns.fromB) & (~allcolumns.lost)\n",
-    "]\n",
+    "notelectrons = allcolumns[(~allcolumns.isElectron) & (allcolumns.fromB) &\n",
+    "                          (~allcolumns.lost)]\n",
     "\n",
     "print(ak.num(found, axis=0), ak.num(lost, axis=0))\n",
     "print(ak.num(notelectrons, axis=0))\n",
@@ -58,7 +55,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -70,12 +67,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 2000x800 with 3 Axes>"
       ]
@@ -91,13 +88,13 @@
     "endVeloP_lost = ak.to_numpy(lost[\"p_end_velo\"])\n",
     "trueP_lost = ak.to_numpy(lost[\"p\"])\n",
     "\n",
-    "endVeloP_notelectrons = ak.to_numpy(notelectrons[\"p_end_velo\"])\n",
-    "trueP_notelectrons = ak.to_numpy(notelectrons[\"p\"])\n",
+    "endUTP_found = ak.to_numpy(found[\"p_end_ut\"])\n",
+    "endUTP_lost = ak.to_numpy(lost[\"p_end_ut\"])\n",
     "\n",
     "stretch_factor = ak.num(trueP_lost, axis=0) / ak.num(trueP_found, axis=0)\n",
     "\n",
-    "nbins = 100\n",
-    "vmax = 200\n",
+    "nbins = 80\n",
+    "vmax = 150\n",
     "\n",
     "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20, 8))\n",
     "\n",
@@ -111,8 +108,8 @@
     "    vmax=vmax,\n",
     "    range=[[0, 20000], [0, 20000]],\n",
     ")\n",
-    "ax0.set_xlabel(f\"True $P$\")\n",
-    "ax0.set_ylabel(f\"EndVelo $P$\")\n",
+    "ax0.set_xlabel(f\"True $P$ [MeV]\")\n",
+    "ax0.set_ylabel(f\"EndVelo $P$ [MeV]\")\n",
     "ax0.set_title(f\"found P\")\n",
     "\n",
     "a1 = ax1.hist2d(\n",
@@ -127,8 +124,8 @@
     "    vmax=vmax * stretch_factor,\n",
     "    range=[[0, 20000], [0, 20000]],\n",
     ")\n",
-    "ax1.set_xlabel(f\"True $P$\")\n",
-    "ax1.set_ylabel(f\"EndVelo $P$\")\n",
+    "ax1.set_xlabel(f\"True $P$ [MeV]\")\n",
+    "ax1.set_ylabel(f\"EndVelo $P$ [MeV]\")\n",
     "ax1.set_title(f\"lost P\")\n",
     "\n",
     "plt.suptitle(\"Momentum at Creation and EndVelo\")\n",
@@ -138,12 +135,69 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2000x800 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "nbins = 80\n",
+    "vmax = 150\n",
+    "\n",
+    "fig, ((ax0, ax1)) = plt.subplots(nrows=1, ncols=2, figsize=(20, 8))\n",
+    "\n",
+    "a0 = ax0.hist2d(\n",
+    "    # endVeloP_found,\n",
+    "    trueP_found,\n",
+    "    endUTP_found,\n",
+    "    density=False,\n",
+    "    bins=nbins,\n",
+    "    cmap=plt.cm.jet,\n",
+    "    cmin=1,\n",
+    "    vmax=vmax,\n",
+    "    range=[[0, 20000], [0, 20000]],\n",
+    ")\n",
+    "ax0.set_ylabel(f\"EndUT $P$ [MeV]\")\n",
+    "ax0.set_xlabel(f\"EndVelo $P$ [MeV]\")\n",
+    "ax0.set_title(f\"found P\")\n",
+    "\n",
+    "a1 = ax1.hist2d(\n",
+    "    # endVeloP_lost,\n",
+    "    trueP_lost,\n",
+    "    endUTP_lost,\n",
+    "    density=False,\n",
+    "    bins=nbins,\n",
+    "    cmap=plt.cm.jet,\n",
+    "    cmin=1,\n",
+    "    vmax=vmax * stretch_factor,\n",
+    "    range=[[0, 20000], [0, 20000]],\n",
+    ")\n",
+    "ax1.set_ylabel(f\"EndUT $P$ [MeV]\")\n",
+    "ax1.set_xlabel(f\"EndVelo $P$ [MeV]\")\n",
+    "ax1.set_title(f\"lost P\")\n",
+    "\n",
+    "plt.suptitle(\"Momentum at EndVelo and EndUT\")\n",
+    "plt.colorbar(a0[3], ax=ax1)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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gY27k8ZdF+c3O1xMxNs4Yna8COCXq567+r487Ge8ArvfQQXn8x8BSh2a97n0SZ8v5nqI6fPgwDh8+jFqthoWFBRw9ehSJRALz8/PYvXu3o+7MzExoDR1G3MmYiIiAd6Oxm3Gzy1f/fRlAf4KMvfrw9Y1HO9/YBH729f62p1tdZxPXNA2PP/44VldXMT4+Dl3Xcf/99+P06dMhNi8co54Ti4iIKOj0lPXot24/wwM3dc+ePXjwwQfx4IMP4sSJE0gmk5iYmEAmk8H73id7rO7q9Tqy2SwAIJfLOY4ZhoFSSWZzbSgWi4jH43ZZBjfruo5yuWyXK5UKstksNE1DvV6HYRhIJBKOc7zUISKiwRDJiSf+4i/FE2ui/Joo/0CUZaoFSc7hyHAEVWoH6/zLrrXCdN1O4PqAn/pup/frMzyMtvpy+vRpHD9+HNVqFdVq1W7wn/7pn3o6v1QqIZ/Po1AoIJVKOY7VajXUajXkcjlHks9qtYqFhQXHjVlaWkIqlXIk+mw+XqvVEIvFUC6X7emjiYkJrK2t2a/rpQ4RERE19Osz3I/AHZxnn30WuVzO0TOLx+PIZDI4fPiw5+vE43HE4/G2S8tLpRLK5bLjxgBouTEAsLKygmKx2PF10uk04vG4IzYmk8kgnU7bXxQvdYiIiIbKDgTfqe9K+6f79RnuR9cxOE888QTe/va3wzAMFItFmKaJqakplMtlfP7zn/fVuVFJpVItNwYAjh07hmQyaZcLhQJWV1eRTCaxtCS3rWwMn5VKJRiG4Xh+cnISQKPn6KUOERHR0LG2Mg7y6KKDFNZnuF++RnA2NjaQzWbtjoBpmohGo0ilUpifn+9rgs16vY5KpYLp6Wn7uWKxiHq9jkKhgEKhgEwmg5WVFbuHuLq6CgAtOzJbIzXFYtE+5laHozhERFsr8knxxEOfEU/ImBjVx508fkGU3yzKMqZH1pcxPPL4ZfFvH1idlCA6jOD41c1nuF+eR3Duv/9+7N27FwsLC1hfX8eBAweQz+extraGo0ePtu3cPProo101yovjx49D13VHrzCfz8M0TZTLZaRSKTs42IrAtv5t15O0jnup49X58+exsbHR9ePixYueX4uIiLbCZQCvB3hc6mtrL5rAxpXuH+dD6uB08xnul69kmwCwd+9ezM/P2yuKzp4921K3Xq+jVqshm83iox/9aFcNU1lZWcGRI0faHtN13U4Omkwm7V5gtVoFAIyPj7c9r16ve6rj1aFDhzzXbefhhx/GI488EugaRETUS18A0H510MDZCWR/CHysvtUN6e4z3C9fg1WapiEajeLzn/+8HXcjra01hu1qtRrOnTvnu0FeWHEyVqerk0QigUQigUqlAgB2VLbVRknTNE91vDp58iRuv/12z/WlsbGxrs8lIqJ+eB+A96L7KarvAXgq/Ga1swOY3wc80P7vd09OXwQOyU2dfer2M9wvzx2cRCKB48eP+7r4XXfd5btBXpRKJWia5qmz0bz23qrfaRSm+ZpudbzatWtXy+7ORETkX+SXxBOf/Zp44q2i/LziivKPWLlvzc2iLPe9kb0E+akv60+IslX/prat65WxHUCQP513db006ZpuP8P98tzB6TSU5KZXuaiOHTvma9M9awWU9a+cz7PKsVjMUx0iIqKhY62iCnqNgLr9DPfLc19MLpv2Ympqyv7/xoZMXNa9QqHgucNVLBbtjlY0GoWu6y1r7K3e4fT0tKc6REREQyfoEvEwVmGh+89wvzx3cKztl7vl5XwvAbyFQsHuhDSrVCqIxWJYWFhw1B0fH3f0FJeXl1EqlRwjNLlczrHDopc6RETUO5FvX3Y88NnPOh+4LB7Pi4e0Jh4XxEN+it8oHqrryfpvFA9Z//qrjy1I7tQj/fgM92Ng7mylUrEDjo4fPw7DMBCPx1s6FMeOHWs7iqJpGsbHx5HNZlEsFqHrOgzDaAlisnJaZDIZaJqGWq2GTCbj2NvGSx0iIqKhEsZOxh2GRfr1Ge5HxGy3FKqNt7/97XjooYfarpxSsRJwvfaaTG62PVk90eZcVkRE5F3k22IDvFs/J2rIIN8XFFdUbcwnyaBlWV+VTFM1fmC9v5cBfKKnnxf2Z9I7AP0fBbzWPwCx5zEUn2+eR3Cq1SpmZma6fqF2+SmIiIiIesFXB4f8mZqawo03tpu7BWZnZzE7O9vnFhERDabIvxJPfFouA5cfVzLORi5kkVt0yLL83SxHaH4gynLZ99tE+UVRbm7vnwH4c3Hcmg2R1+0hj0HCi98DFr/f/tiFkHYy7gfPHZwDBw70sh3b0okTJwZ+CI+IiHrt564+mjmnqPrCYwzO7Fsbj3Yq54HYN0NtVc8MTJAxERER9dCA7IPTLyHsSUhEREQ0WDiCQ0REfRd5UDzx6a+IJ+SqKLGqqiXXk/w4a59PsPP1JNXH40sBr78FRmwEhx0cIiKiURDGTsRD1GvgFBURERFtO776YhsbG3YKA13Xceedd/aqXURERBSmHu5kPIg8d3DOnTuHyclJR36miYkJFItF3HrrrT1pHBERbQ+RXxdP/KfPiCfc9pEBWvex8bszsTwud0KWx2UMjWyPs75p/qajHIkswMkZM2Sa9wOwdhnu0zJxxuC0l8lkUK1W7dwSlUoFL774ImKxGF599dVetnFocaM/IiJqbPLn3Ljwttv+EwDgwgVVx4y65bmDY01N7d+/336uUqkgHo/jySefxL333tuL9g01bvRHRETAzwC42/HMc881j+DE+tMMjyM4i1Vgsdb+2IXNUFvUU547OJqmOTo3QCPr9vLyMkqlEjs4RERki/yxeOI/fVE8cb0oyykjFdWUkqQ67kyeaZoPO8qRyMdE/esUx2XohrO91+q/omhXiHbC207G/7TxaKeyDsRKobaqZzyHC+3du7ft8/F43BGXQ0RERLTVPI/grKysYN++fYjH44jH49i9uxHwtWfPHrz22ms9ayARERGFgEHGneXzeeTzeQCNKSvDMBCPxzExMdGTxhEREVFI2MFpLxqNYnp6GtVqFc888wyq1Sqq1ard4XnXu96F6elpxONx3H777QCAJ554Avfdd19PGk5ERIMjckw88S9l6gUZM/MjUd5Q1H+z4rhK+xWt18jUD6rznTFDpun8rItEfttTq/rKYwyO8hpDwnMHJ5fLYWZmxi5/4xvfwLFjx1AqlVCpVLC6uopyuQyg0RmanJzE6uoqOzhERETUd547OM2dGwA4ePAgDh48CKCxCWCpVEKxWLSXkxeLRUQikXBbS0RERN3hFJV/e/bswdTUFKampgAAZ86cQbFYxEMPPRTG5YmIiCgodnCCO3DgAFKp1MiP4HAnYyLariKfEk988HnxhIypUcXYvFWUXxLl74uyat8cmcrhx6L8Q1FW7Wsjvayo3/y7/88ByJgki2p/nv5b/Ctg8a/bH7sweM3tqKeJz+W01qjhTsZERNTYyfhgh2OvAFjqTzM8juDM3t54tFP5ARA7HmKbeqinHRwiIiIaEFxFRURE5BR5Vjzxwc+KJ24W5bOiLKfrfyDKcspJluUUlaTKFi5fT6aKkFNWcsrMOSXVmsrhKXH8Q+L4b4vjjezjjVxUfRrBGTHs4BAREY0CBhkTERHRtsMOjj9nz55FPp9HrVbD+Pg43va2t2FmZsbOVUVERETUb4E6OI8++igymQxM03Q8/zu/8zt44okn8IEPfCBQ44iIaGtEPimemP2aeEJ+fMhl4qqYGHm+ahm3jImRy8BVZAyQ8/VlTI0UiSyI8sdFjR+K485l460xO1ZMziuurxsqBhl788wzz2Bubg66riOdTmNychLRaBT1eh2nTp3Cgw8+iAMHDth5qYiIiGgLcYrKm1wuh3w+33avm4MHD2J6ehrz8/N47LHHAjVwmHGjPyIiAr6O2267TTz36tV/5chVD3ns4Cx+DVj8evtjF/rY3KAC9eXcNvKLRqNBLr0tcKM/IiIC3oXnnnva8YxzikrOB26t2Z9uPNqpvALEHu9ve7rVdQcnFosp69RqtW4v71mtVoOmaT1/HSKi7Szyx+KJWZlaQMbYvFGUZUyMXGjijFExzQecry/2iWlNYfAy3Mn6MgZIcg5FyBgb05wT9eX7lfvqyJie3xTXl+/P2oenj4uZOUXlzfr6Or75zW/ine98Z8uxs2fPIp1O+x7FqdfryGazABpTYO3I/Fa6rqNcLtvlSqWCbDYLTdNQr9dhGAYSiYTjnLDqEBERDY0BDDLu5SBF1x2co0ePQtM03HHHHfY0TL1eR6lUQq1WQzQaxZkzZzxfr1QqIZ/Po1AoIJVKta2ztLSEVCqFiYkJ+7l4PG7/v1arIRaLoVwu222amJjA2tqafc2w6hAREdE1/Rqk8KrrDk40GkWpVMLMzEzLG9F1HSsrK772wonH44jH464ZyFdWVlAsFjseT6fTiMfjjriXTCaDdDptd0zCqkNENMzG1kR27/efFTVkNKl76gI15xSWnBIC3izKMjWDcwqqddm1vJ4k349M1eCc0mqdUvKn85SUfL3XA72OLz2courXIIUfgd6q1fM6c+YMKpWK/dyBAweCXLatQqGA1dVVJJNJGIbR8mat0SPZ2ZqcnATQuLHT09Oh1GEnh4iIhk4POzj9GqTwY4fvM9o4cOAApqamMDU15ejcbGxsuJzlT7FYRL1eR6FQQDqdxt69e1Eqlezjq6urANAyl2fdqGKxGFodIiIi8q55kGJpqTW5qDVIYRiG4/nmwQW/QungdNJNgzrJ5/MwTRPlchmpVMqem7NWaln/dgpsrtVqodXx6vz589jY2Oj6cfHiRc+vRUREW+EyGtNM3T4u9a+pO0N6dCGMQQq/PA9W3XHHHb4vXqlU8NGPftT3eW50XUc+n4dhGEgmk8hkMlhZWUG1WgUAjI/L7cAb6vV6aHW8OnTokOe67Tz88MN45JFHAl2DiAgAIs+KJw7LTUhLorxflGUMydtEWS4jV6VSkDExcsS//SapFpkKQVW/lTPmRhXTI5eNX4uxOQngCz5fe4vsBC6awEW5ot6H811u9JfP55HP51GpVJDP57G0tATDMFCtVqFpWqiDCxbPHRzTNO04G6/c5uKCSiQSSCQSdpusoKW1tfY/VJqmhVbHq5MnTwZKVTE2Ntb1uURE1A+HAPwsZBD0uXPzns4+ffp04D+G/cj+CfCxp9X1eiXIIIVfnjs48Xgcy8vLOHjwoOeLf/jDH/bdID8Mw7CHuKyOR6eboGlaaHW82rVrF7OqExFta9ddfTg7OF5/9+/atSv8JnWyE5j/P4AH/vfuL3H674BDqgVrHnQzSOGX5w7OkSNHfHVugEZEdK9ZAUjWv3IYyyrHYrHQ6hAREQ2dHcDYG4AgcwO7/M4EuvA7SOGX5w5Op87NxsYGVldXceeddwJoZBmPRCK48847fXeI/CoWi3YnKhqNQtd1FItFzM1dmyu1bt709HRodYiIBl3k8+KJu2WMjIx52S/KL4qynDqQ17tZcb1vibL8pJQxMTLVgd+YG5k6QcbQhDAM4UK9j4414vNKT9vhYA02Bb1GiPwMUvgVaBXV/fffj7179+Kuu+6ynzt8+DCq1Srm573NPzbr1HOrVCqIxWJYWLj2DVkoFDA+Pu7Y4XB5edneSdmSy+WQy+XswKWw6hAREVH3Og1SNAsyuNB1X+yhhx5CPp9HNBptCSaemZnBXXfdhSeffBL33nuvp+tZkdUAcPz4cRiGgXg8jmg0Ck3TMD4+jmw2i2KxCF3XYRiGXd9ibTyYyWTsqOxMJuPYICisOkREREOlx8k23QYpZmZmcOTIEXtmpNMgRSwWc+SnCjK40PVbLRQKKBQKuOeee9r2rAzDwNGjRz13cKzIatlpARo9O69r4K00Ef2oQ0RENDR62MHp1yCFH12/VU3TcM899wBovxz81KlTXa1bJyIi/yIyt+FDXxFPyNxOMoZFtcGJal+bH4jyBVF+o+K4U9BcUK3XkzE87q+njgFScc91td30c5DCq0DJNi2maTqOfeMb30ChUHAk1BpFU1NTuPHG9oFws7OzmJ2d7XOLiIio//4cgOxwWgLsuufXDnS9E7HjGkOi6w7O/Pw87r77buRyOXsE5+zZsygUCshkMohEIn1ZJj7ITpw44UgaRkREo+hnAHRaVfwKgPDSGrnyuIpq8Wlg8Y/bH7vQx8wSQXnu4Jw+fdqxK+/BgweRzWZx3333oVKpoFAoALg2mpPJZEJP00BERA2RT4knHvqceEIu4/5pUf6i4hXkyIL8uJBTMJKcslIt636zo2Sa9znKrcu6ZXvk9eWUmur1nVNIqikpVWoH1ZSUdX5jlXCfOjgezb6/8WinUgViv9Hf9nTLcwdnZmYGp06dcjyn6zpWV1dx5swZlMtlnDlzBpqmIR6PY8+ePaE3loiIiLrU41VUg8bzWy2Xy9i3bx/m5+eRSqUc21AfOHAABw4c6EkDiYiIKAQjFoPjuam6ruPo0aN48cUXsX//fhw5cgTPPivT0xIRERFtPc8jOPPz85iamsLMzAwef/xxnDhxAnNzczhz5kzbUR0iIgpP5L+JJz74l+IJuQz8raIsV/G8Q5RlzIosq5aRO1M5+I+hcbZfVd80HxD15bJyZwyRXPYt+Y+5+Zji+MfFFWSMj9XePqZqGLEpKs8jOFNTUy3l1dVVnDp1yh7Vufvuu/GHf/iHoTeSiIiIAroupMeQCDybpmkaHn/8caytrSGVSuHee+/Fvn378B/+w3/A2bNnQ2giERERBWbF4AR5DFEMTmh9sSeeeAK5XA7nzp2DaZo4evQo1tfX8dhjj4X1EkRERESeBOrgbGxsIJvNYmlpCfV6HaZpIhqN2jE5o75UnDsZE1G33vijV51P/Mq6qCFjZGQMpNwHR246KvdpkTE2NyteT3Ieb41pkdeT++RIch8e5/n+Uyc4taZmcI+xUV/Prf7X8Y53nGl75MKFC+jbZIfHGJzFQuPRzoWLobaopzx3cD7zmc/YuadOnz6NbDbr2NxP0zRkMhnMzMz0pqVDiDsZExER8C4899zTbY80NvqL9acZHmNoZv9l49FO5W+A2L8OtVU947mDk81msba2hpWVFZRKJXvH4ng8jkwmg8OHD/eskURERER++NroL51O2x2bRCKBXC7HDf6IiEIS+dumwk+dEkc3RFlOSZ1VXP1boiyze/9QlOUUlpwycp5vmvc7yq3LtuX1VKkT5MeTnCJTfXw526vKTq6esgo2pdX5OJeJ94qvt2qaJubm5jA/Pz/y8TVERERDZcR2MvbcwdE0DZVKhZv5ERER0cDz3MHJ5/Ps3BAREQ0rTlG15zeI+NFHH0UikcD+/fv9tomIaCS0LAX/Z29qKrwsasvUCzImR8a4SOOK46pUDJIzhqY1NYGMsVHF9MiPI7/tUXG2pzXVg2pZ+PWK47L98v05WTE8jVVUS4prhySMnYiHaCdjT01dXl7G0pL3L0C9XketVsPa2hp+53d+p+vGEREREXXDUwdncnIS6XTa98VXVlZGuoPDjf6IiAj4+tXHNbfddgxAY6O/vvEYZLz4KWDxv7Q/duH1UFvUU546OAcPHkQikcDx48ft5373d38XAPDggw+2Peehhx7Chz/84RCaOLy40R8REQHvuvq45rnnmqeo+rTRn8cYnNl/03i0U/kWEHt/qK3qGc+zablczlGu1WqueabS6TSSySROnZJ7ORARjabIt0Vcxq0y/cKXmv4vY2bkPjaSrC9jRmTMjhxdljEjqpiTl0T5VkfJND/kKLfGuLjvw6Peh+Y3Fdd3fry1xtyEva+N/Dj1F5PTFyMWZOx5RbvfDf1qtRoqlYrvBhEREREF1fWWPaZp4gtf+ELbYxsbG0in09A0reuGERERUYiuC+kxJLpu6tGjR6FpGu644w4YhgFN07C2toZyuWyvuMrn86E1lIho2LwZ33Y+cestoobMqP3mpv/LbOBvE2WZukBOQUmqVAmqZehyisV9GXgkIkMY5MeNe3Bta2oFmXrBfQqpdQprQXE991QOrdd3n9KSx6Vrr9e/VA3mDsAMOMVkbsedjKVoNIrV1VVkMhnMzc0hEokAgJ2ram5uDvfdd184rSQiIiLyIdBgk6ZpWFlZwZkzZ1CtVnHmzBlomobJyUnmqiIiIhogmzuBzYBTTJtDFGQcymzagQMH2gYhP/roo/joRz8axksQERFRAFdC6OBcGZUOzqOPPopisYi1NTkX3FCpVEa6g8ON/ohGS+RvxRM/VRdPfFOUXxPlCx3+D7TG3Mhl1qplyHLZt7yePH6zKMtl4fL1ZTxR+999nahiVqTW1BA/FMdlzI1M/dBdaoVr13ePuXHG9HwVwNfkFT29LnWv6w7OkSNHsLKy4lrHissZVdzoj4iIgHdffTSzOjavAOhPLqrNnRFc3qn+XM4/bmLpcbPtsde3207G7aysrCCdTrtu9jcoOxnXajUuWSciopG2uXMnNq9TL4O67yONRzunK1dw6F3DMerU9YIvXdeV+ank7scq9XodmUwGmUym7fFCoYBYLIZIJIJYLIZSqdS2XiQScTySyaTjeKVSQTKZRCaTQTqdRqFQaLmGlzpERETUW7Varavzuh7ByeVyOHbsGG6//faOdcrlMu68805P1yuVSsjn8ygUCkilUi3HFxYWUCwWkU6nUa1WsbCwAMMwUCwWEY/H7XpLS0tIpVKYmJiwn2s+XqvVEIvFUC6X7emjiYkJrK2t2a/rpQ4RUeQT4ol/L/eueVmUXxDld7hc/euiLH9dyxgamaqhfWxkZ84YldZUCzKmxRkj5H3fl07HZUyNHCWQ7XNP1WCac4Ha4/fjsXVfHvd9grbClZ07sbkz2EY2V3ZG0CluqF6vI5vNAmg/wFEoFJDNZlGpVKDrOnK5nOPz2SLDW3RdR7lc9t3Wrjs49XodlUoFjz76KKLRaNs6uVwOL7wgf6Dbi8fjiMfjHeN2Tp06hWKxaJePHDmCWCzWcoNWVlYc9aR0Oo14PO6IjbFGaazOi5c6REREw2QTO7AZMJnUZofn+zVI4UfXHRyrF+bWmQgryLhUKrX0BnVdh67rjqGrQqGA1dVVJJNJGIbRcpPr9Xrba01OTgJo3Njp6WllHXZyiIho2GxiJy73qIPTr0EKP7ru4KRSKZRKJRw5cqTt8ddee81O2RCUW++tOXi4WCyiXq+jUCigUCggk8lgZWXFPn91dbXlHAD2SE2xWLSPudVhB4doNL0Nf+184t+/RdR4UZR/JMr7Rfn7otw8rSRTJ8i6KqopK/ds4qopKXm+Ktt367SG/Pj5Idw566uzfbunelBnDw+aysE5Raa+n9tXWIMUfgVaJm4YhmuW8TvuuKPby3tSq9Ucgc75fB75fB6VSgX5fB5LS0swDAPVahWaptk3stOUWq1W81THq/Pnz2NjQ5UfprOxsTGMjY11fT4REfXaZbSLSWn93S/XV1vlSz1oU3tXsBObAff3vdLFOWENUvjV9Tvds2dP23QMZ8+exfj4OHbv3o2DBw92e3mlQqEATdPa9vB0XUc+n4dhGPZKqJWVFVSrVQDA+Lj8y6ahXq97quPVoUOHPNdt5+GHH8YjjzwS6BpERNRLXwZwsuXZPXuO9r8pCpvYgR9d3IFLF9vvcePFD8+Ht7+d30EKvzx3cJ599ln7/24ro9bX15FIJHDu3DkYhoFPfvKTvhvlRTabVW40mEgkkEgkUKlUAMAOWuq087KmaZ7qeHXy5EnXVWYqHL0hIhp07wXwnpZnz52bd5T37Pl9UcOaovoegKfCb1YHn8z+A37/Y3LqtP+6GaTwy3MHJx6PIxaLYX6+8UVrN/Vijdqsrq7CMAzk8/medHAymQyWl5c9dTYMw7D3y7HqdxqF0TTNUx2vdu3ahd27d3uuT0SD5afxJUe5GvkpUeMroiw/OFRxL/J481SHTC3wZlGWv4NlqgSZakFOo8gYEJmqwfnxoI5ZUZHXk8u85TJxuQxdxvT4I2NoWmNqbhWv9yFR330ZeGvMjddUDje1bW8vXMFOpOd349cekGk2vHv+9I/xLw/53YKgVTeDFH75WhB/6tQp3HPPPQAac2V33nkn9u7di1gs1hJQnM/nu2qQijVk5ScFgrUCyvpXxtFY5Vgs5qkOERHRsLmCHbhu7DrctPv6rh9v2BU8R7ffQYpOMyoqnjs4siFTU1NYXV2FaZooFostSTU1TXMNQO6GtZuwDDhy691Z6+6BRuCwrustS9CsEZ7p6WlPdYiIiMi/IIMUfnnuiu3du7ft85qmYf/+/b7O6cQtgLdUKiGbzSKdTjtGi8rlsj2qMjMzgyNHjmBurjFUWCgUMD4+jkQiYddfXl5GLBZz5KfK5XLI5XL2yikvdYiIiIbJZewIvA/O5e4zPLkOUnTq8DQPUvgVeKwprM38rKhpADh+/DgMw0A8Hkc0GkWlUoFhGADQ9o2ur68DaKx8ymazKBaL0HXdjgNqZm35nMlk7KXjmUzGEejkpQ4RbT9ja864lktv+nlR47OiLPemeZso+93rpLm+jMGRMTJypafc5+V+R9l/KgTVPi7y40O1b8z14ri/GJ7W15f3xy95vz6keD0Z0+Tct6d1HyD31BVWTFGlUkEs1pvFONIVXBfCMvFOW/31Z5DCj+CTaSGxoqbbxe7oug7TVC9r87r7oa7ryuAmL3WIiIiof4MUfnju4NRqNbz00kttOxrtnl9fX+868pmIiIjCdSWEXFRXOkxR9XOQwivPHZz19fWOEc/dbMBDRERE/RNOss1g2cj7ydcUlZceWLOw4nOG1dTUFG68Ue570TA7O4vZ2dk+t4iImv0EzjjKl/bJ31mfE+X9ovwdxSvIGBzVvjjNZRnzIc+VZWdMijpmRcb0BKOKOWltjyTvhWyvKubGb64pVW4r+fEo9xly57ze1/GOdzi/155//u+v/q81zUOveE22ubL4GgqL7ZdmX7zQTbKGreG5g6Prup2s0qu77rrLd4O2kxMnTvhaCkdERNvRu/Dcc087nrnWAXoFQDiJqcOSnN2H5Oy+tsf+pnIBvxqr9rlF3fHcwbF2MPaj26VdREREFK5wkm0Gm+LqJ8/vdGpqyvfFuzmHiKhX4nD+Ff3dyHtFjbOiLKeY5DTFTyrO/6Eoy2kYef3mEd/nFXUleW3V1If7lJU6dYKcApJTUH6XyPubglK939Zl6qrr+fvg95u6Qt2e3tvEzhBicIangzM80UJEREREHg3MPjhERETUO71cJj6I2MEhIiIaAVwmTkS0TUS+LeIsbn2/qPEZUZZxIPtFWcbFyJicW0X5jaIsl2bLOJKXm/4vY0TkuTLGRRXvI1M7yPqyrXKZsDzu1JrawX3ZtZWqoFN9v8vOVfVbz5cxMb1dri3fr6WRqmGwVlFtF+zgEBERjQCv++CorjEs2MHpIW70R0REwNdx2223tT1y4YLf1Wbd4zJxCg03+iMionYb/VkaU1SxPrfH3WcXX8ZnF19ue+zSdtzJmIho0Ml9blpjbmQMjSou5UVRlnEw8g+Y74ty++3uO7/+hktdGR8kUzmoYnJUZDyR/HiQ+8y47/uiirlp1X60+9rrucfMqGJ4VO1trf/b4rh7zJBqjyPV9frBa5DxL87egl+cvaXtsRcrG/g/Y6fCblpPsINDREQ0Aq6EsNEfp6iIiIhooGxiRwhBxlwmTkTUcx/Af3eUn4n8oqjxRVGW0zgyzkCVcVtOQcmyrK/K2C2nkZpfX54rlzE7p5T8p06Qv/5VHwfBgmHV2brdl2mrp4jcs4P7XUYefBl7f5ehUyt2cIiIiEbAZgirqLhMnIiIiAbKqMXgDM9kGhEREZFHHMHpIW70RxSu96LoKP9ZZErU+Loou8W4tCvLOBNZfrPP8yVVegS3azupl0HL3z3Osjq1gvuybVXqiNYYFr8xQU7qZeAy5kWe/3Fx/gOK850xM0GWnS8uLuIjH3lEnP8HbV+nl5iLikLDjf6IiGh2dhYf+cirHY6+AqA/uai8pmooLb6AZxerbY9durAZdrN6hh0cIiIissVn34747NvbHjtbWccjsWLbY4OGHRwiIqIRwFxUREQDYhbOuIk/i8i/KmUqhe+I8k2irIqhkakVVKkWZByJTL3gHqfiL52CMyZGFXOiinHxf76Ke8yOOubHX+qF1uvLmB+/+9C4x9y0vp5qHxxVKov+G7UYnOFpKREREZFHHMEhIiIaAaO2Dw47OEQ0MFqXgd8nalRE+WuivFuUfyTKr4myaspITmnJ1A4yo7ecppEZuuU0SeeM4K3LmFWpDuSSc9USd5lmQvL38aCegvLLfUpNnY1bTjn5TfUQLJu419QQlUoFsVh/VlFdCWGK6soQTfywg0NERDQCLntcJq66xrBgB6eHuNEfEREtLi5icXGx7bELF4IlMaXO2MHpIW70R0REbn/QNqaoYn1ph9dl4n+2+C38+eJftT324wvDkxWdHRwi2jKRmul8YuKnRY1vibKMkXmHKJ9VvKKMoZHLuGUci6wvj8sR2pdEWf6KlWW5DP1t9v/UqRNU8UMyvke+F1UMj+qDzLnEXr3s3B9VzIvf1BSt11ct81a9H3n/nF8PdWoJ6/gritcJj9dl4u+ZvR3vmb297bHvVH6AT8SOhdyy3hieaCEiIiIijwZqBKderyObzQIAcrlcy/FKpYJsNgtN01Cv12EYBhKJxJbVISIiGhZcJr5FSqUS8vk8CoUCUqlUy/FarYZYLIZyuWzHtUxMTGBtbc2u3886REREw2QTOwKvgnLbybhfgxReDUwHJx6PIx6PIxKJtD2eTqcRj8cdQbuZTAbpdNrudPSzDhH5dxBfdT4x8U9FjRdEWcaoyL1b5D43MgZGpmJ4qyirVrCo4l7k60kyxkf+ypVxLs2pJ1T72sh9V+bgpjWmRJ6v2ndHcn/9SGRB1He2vzUm5eOiHCwGRgqe+sHf+ar2W+f3cx+cXurXIIUfQxGDU6/XUSqVYBiG4/nJyUkAwNLSUl/rEBERDZvNq6uogj3ajwDF43GsrKx0fG23gQM/dfwYig7O6uoqAEDTNMfz1k0oFot9rUNERDRsrBicII9uYnC2anBhYKao3NRqNQBANBrteLyfdbw6f/48NjY2PNeXxsbGMDY21vX5RETUWxcvXsTFixfbHHndUer0WXD+/PketKqzyxcvY/PiZtfnXzp/yfc5XgYOrGNudfxOUw1FB6darQIAxsfH2x6v1+t9rePVoUOHPNdt5+GHH8YjjzwS6BpEW+k+OHdvPX293OxMxtzI3E3y51DWl/mVZH35oSL3gnHfK6U1DkbGBKniZGTZuTeNad7vKDvjNlS5lBZE2RnDoj7/t0VZni/vjYxnUsUvqWJu/OZ6kuT785b7qRNVjE3nfWy+AOCk8vp79vxWkOaF4gp24MvZr+LPPvalvr5uvwcXLEPRwZmYmAAArK3JXy4Nmqb1tY5XJ0+exO233+65vsTRGyKiQfdeAO/BuXPzjmf37Mk6yp2Pfw/AUz1rXbNN7MBPz/88Jh/4ma6v8YPT38N/O/SUr3P6PbhgGYoOjtWp6PQGNU3rax2vdu3ahd27ZXZjIiLaPq4DcF2b3/VvcJQ6H7+hR+1qtYmdwNgYdgb443nHLtWoZ6t+Dy5YhqKDYwUZySEqqxyLxfpah4jaewjOYf4nx8W0weUvijP2i/Jroix/RckPCTltoop5e5soy1+mctpFTpk5tS6tfkrUkMvI5Xb+cilx87SL84OkdQpJNWXknD5TT/nIVA/Oey+nkKRI5DHFcffXV7dP8vfxpZoSUy/79rdMXLav9Wt9Xdt621G/BxcsQ7GKKhqNQtf1lhVMpVIJADA9Pd3XOkRERMPmSgjLxLtZRbVVgwsD1cFxm2NbXl5GqVRyvPlcLodcLmcHJfWzDhER0TCxkm0Ge/jvNmzV4MLAjI1VKhXk83kAwPHjx2EYBuLxuN2h0HUd5XIZmUwGmqahVqshk8k4lo31sw4RERFdoxqkiMViqNVq9nRTu8EFVR0/IqZpmr7PIleNrbed200TbUe/i193lOcivyJqnBXlmxRXlHElMjWDahm2DICUcSXy+M2irFqmLtsjUzGolqnL1Azy/V473nlZskUuUXePoWl9bSfVMu7W8+W9dP97WcYrSaoYl9b37x4jpIrp8Rtzo142L7kvY792/VcALPX088L6TEqWfwP/WP/JQNf6+8p3sBL7jy3ttQYplpaWEI1Gsby87BiksOpYeaZqtRoMw2gZOPBSx6uBGcEhIiKi3ullsk1d15HP5+2ZmE513NI5eK3jFTs4PTQ1NYUbb2y/pG52dhazs3LTMyIi2n6+jttuu0089/dX/3UfWaPusYPTQydOnOAUFRHRyHsXnnvuacczcoqqH6yVUCrPLZ7E84tfbnvs8gXV1NzgYAeHiDz7DRx1lH8/8nuihoyJOSvKMkblK4rjcgRUXl/GwMh9clQxOTLmRv7ylvvkqP7abr9J2TUybmTOUW5Ov6COIZF78Kj2kXGPIVHH+LinZmhtj0wloYrpcVLH5Dwmys59goKmbpDk18ov//v8hO/K1VVUKj81eyd+avbOtsdeq3wbn41l2x4bNAO1TJyIiIgoDBzBISIiGgGbHkdwVNcYFuzgEFFHRbzXUf79yNOixvOKsmpZuJwGkVNEqlQNMju4aopJktnInddTpyc4Jp55UZRV0zByWmWu6Zjf1AaqZeFyOk+W5bJmOeUkp5hUU1Zy+s3fMm9JPWUl2+d+vqTOHi5TZcjpTn/XszSWcPcnBufK1c36gl5jWLCDQ0RENAJ6uUx8EA1PS4mIiIg84ggOERHRCNi8mmwz6DWGBTs4PcSN/mjY/Boed5Sf+gm5F8YLoizjMGRcgjyuSr3wVsX1ZOoDSS77dl9mbpr3OcoyzsLv0uZWzlQQpnm/6/VVcSROflMxuMfEqGJaWlMhOJeBS63H/cbcqGJq/MXctL4/uYzdX4yOn2Xfi4uLWFxcdDz3/PP93+iPMTgUGm70R0RE7f6g3YqN/ryqLX4eZxY/3/bY5oVLfW5N99jBISIiGgFel4nfOvsLuHX2F9oeq1dq+HLsobCb1hPs4BAREY2ATewMYRUVp6iIaAjchm84ys9HPixqfFFxhbOirNreX6ZikL+CZH1VzI2k+pV2q+K4eyoIdRyKPN+5D4+fvWDU+66oYjfc74X/mJug+/L4rS/35XFPvSC/Fqr2+03l0NpeVRoR9/Ot1+/nPjijhh0cIiKiEXAlhFVUDDImIiKigcJUDUS0bX0czpUcz0f+H1HjL0VZbuevmjL6SVH+mijLYXxZlsP+7bdZ6ExO28gpM2cqBvW0g1Pr0mSZ6kGSy+IlZ3uDZJxWTTmpl6AHa0vQ7N1Bp5Ba03SoXk9OablnCw/6/sLObt6NUVsmPjxdMSIiIiKPOILTQ9zoj4iI2m30Z7lwwT04OUyjlouKHZwe4kZ/RETk9gdtYxVVrC/t8Jqq4XuL/wPfW/yfbY9duXAx7Gb1DDs4RNvY/4tfcZT/r8h/VZwhY26+IsoyzkH+9SnrS3Kps7yeaumtLMsYmDVFWVK9nvwVKe+PM8ZGnX7A+1Jqv8ucVcu8W9siY3Lc36sqRkWV1kKd6kC1rFy1JN89fqrXMTDdp/V4JeymBPZPZv8F/snsv2h77Hzlb/GtmNxOYjCxg0NERDQCRi3ImB0cIiKiEXAlhGXiV4YoBmd4WkpERETkEUdwiLaRFfySo3xv5ISoIfe5kfvWvCDKMkZGFTMjqWJo3irKL4uyjHmRcQ2y/s2iLGN+ZKoIGaPTOXUC4CWdgd84DHn82uv7T43gd88g97b4fe+qr1XrvjOqmBxJfu/Jjy+/++Co9gVyUsU0qb/Wzq+PFdPUz1QNmyFMUTEXFREREQ2UUVsmPjwtJSIiIvKIIzg9xI3+qNd+A0cd5d+P/JGoIZdtPy/KcopGphZQTTHJKS45TXBWlOUUkRzWl9McqmkJ+fOlOl9Oafldmqw67p4qwjQfUJzvZ9M31bVV02X+prRUUzSqZeSSaoqt36ki1FNQ3b9+u43+brvtKQD93ugveLJNTlERAG70R0REg7PRH5eJExER0bbjdZn4ucVP49zip9seM7mT8WCq1WrQNG2rm0FERDSw9sz+MvbM/nLbYxcrz+E7sek+t6g7Q9fBMQwDpVKp7bFisYh4PG6XI5GI47iu6yiXy3a5Uqkgm81C0zTU63UYhoFEIuE4x0sdon75E7zPUf79yOdFDbnMW/6Iv0OUN0RZxqjIZdZvFGW57FzGwMj4Ank9uaxbxujI9snr7RZlGUMkybgTeX+8bq9vUcUIOdsbiXzc9bizfc5r+0+9IPlbVq1KpRB8Cb37vfK7jNxvqorW9rnHQ6lifCKRx0T9+8Vx91Qb/XAZO7Az4BTT5R6tTerFAMRQdXBqtRpqtRpyuRyi0aj9fLVaxcLCgqNzs7S0hFQqhYmJCfu55uO1Wg2xWAzlctmOk5mYmMDa2hpSqZTnOkRERMPgCq4LHGR8xeX8MAcgwjBUHZxSqYRyuezo3ABo6dwAwMrKCorFYsdrpdNpxONxRxBwJpNBOp22Oy9e6hAREY26MAcgwjJUHZxOnYpjx44hnU7b5UKhgNXVVSSTSRiG0XJevV5HqVRCLpdzPD85OQmgcfOnp6eVddjJISKiYdHLXFRhDkCEZag6OO3U63VUKhVMT18LeioWi6jX6ygUCigUCshkMlhZWbFv8urqKgC0zPdZIzXFYtE+5laHHRzqtTP4CUf5F97+iqih2udFxsTIfXAkGQOz3+frSarUCT/wWV/GAMmYG9U+OPJ85z5ArXEZ7nEordxjeOReNVLz66ljPtxjOlpTI8y5HlfF5Kjvjfu+OmHvM9P6+jI1hPs+QPJ6qn18/MYktdr6j9tN7MCOHu1kHNYARJiGfifj48ePQ9d1R68xn8/DNE2Uy2WkUik7OLhWqwGA/a/saVqsoTZVHZXz589jY2Oj68fFi8OzHI+IaDRdBvC68vc58LrjYT1//vz5LW19L6kGINLpNPbu3dsxbieore9SBrSysoIjR460PabrOvL5PAzDQDKZtEdyqtUqAGB8XP612lCv1z3VUTl06JCHd9DZww8/jEceeSTQNYiIqJdOAvgC9uz5LV9n+a0fhitXduLyhcswL17q+hqXf/i657qdBiDy+TwqlQry+TyWlpZgGAaq1epor6KSrFiafD7vWi+RSCCRSKBSqQCAHdi0tia3qW/QNM1THZWTJ0/i9ttvV9brZGxsrOtziYioHw4B+FmcO/ega609e37XUbbqnz59OvAfw15tbu7A67/zSVz8rd/ry+t1MwARpqHu4JRKJWia5qmz0bx8zarfaRSm+ZpudVR27dqF3bvlPh1E7r6CSfv/P3eniLl5UcZJyBgV2SGXcRHucRat58uy/H52z73Uev6bfb6eJOMoVHuZyJgcGfPjnv+oNe5Dld8p2L46za/nN5eUKuam9bXcY3L8x8y451QKem/V+8ao9un5mGvZL3VMkuRs3549//Hq/2RcXW+Nzf07jP37tLpiB5vf/Gv8Q/wDynrdDkCEaag7OMeOHfO16Z61Asr6V8bRWOVYLOapDhER0bDYvLwT2PmPgJv+UdfXuPIG+UdMe90OQIRpqIOMC4VCx+EvqVgs2pHc0WgUuq63LFOzbvD09LSnOkRERMPiyuZObF4O9riy6W0VVrcDEGEa2hGcQqFgd0KaVSoVzMzM4MiRI5ibm7Prjo+PO2728vIyYrGYY3voXC7n2KTISx2ioP5GLMX+uZvOXitcOAsnOeX0dcXVZaoDOWWjWmYtp6RUU1xymuKtoiyXlbsvLW497pySUy91lu9HtQzdSb1M3P2vWbks3E86AXVqBvf37n9KSN4rv9w/TtRTTP6mpPynOnB+L7VO0blPMfl9PdWydut4I5v4kq9rd2tzcwfMywH3wdn0Ni5SKBQ870zcPAARpqHt4Bw7dqztKIqmaRgfH0c2m0WxWISu6zAMo2Ue0NoWOpPJQNM01Go1ZDIZx5p8L3WIiIjomqADEGEZ2g5Op2jraDTqeYdEXdeVUdte6hAREQ26zcs7ceXHwUZwvIwABR2ACMvQdnCIiIjIO/PKTpibAT/2r6g7OGEMQISBHZwempqawo03to8xmJ2dxezsbJ9bRAPha84suu94t9x06y+b/i/jIuRSShljs1+UX1Q0Rhflb4myXLYtY2xkTIt8fZkaQi4TlzE5MmZHtWxcFfehirOQP5/yevL+y+PO++F32bp73Id7zIhqWbZsq9+YG7/LqFXLptWpJFSpGCTVFgjuMT2t8VB+Y3qc3M5fXFwE8Afi9a2yv60EyDt2cHroxIkTLXOQREQ0WmZnZ/GRj7za4egrAPoTZIzLOwAvQcb/3yeBTz3e/tjrqo714GAHh4iIaBRs7vTWwfmVf9d4tPNXFeCfh7+kuxeGeh8cIiIionY4gkPUa3/jjLmJvPt7osJnRPknm/6v2qdmnyjLmJu3ibKMiZExMHJfF9XeKM4YINP8BUc5Ejkr6sv3I38FyZgb2R73VBWqOI/WuA053C7b43y91pie3xZlf3upuKVXUKUWUMesqGJQ3OOR/MfEOAU9X30973sKtXv9oKki/O+b0z6VRD/3wcFmBLgcUddTXWNIsINDREQ0CjYRPKZ5M4yG9AenqIiIiGjb4QgOUcgex685yvdPm6LGWVF+hyg3p0f4jjimWrYsl1nLZeWq1AsydcG4KLunWohEHhPH5ZSTKvu4fH1/v6Japw3cr6+edlAlFgz657Bziqx5miTosmVJtSy7tX6wKSUVr6kMvLbH75RVa3vkMnf36cetvn9dGbERHHZwiIiIRsFlBO/gDNG2Pezg9BA3+iMiokZSXGdi3NtuOwYAuHChj/vKXIY6X66XawwJdnB6iBv9ERER8K6rj2uee645m3hsC9rkorDYeLRzkRv9EY2MP8H7HOX7b/qCs8IFGYci0yvIpdtuXhNluUxcHt8vyrItPxBlGcMjl3XLEUkZoyKv74zhMc37HWV16gS/MTlyKe4Drq/Xuoxcdb779v6RyMfF9WT7Va79eex/GbLkviTef4yI+71Xxaio2hs0JkcVc+P3+q1DFTL1RbAYm2vfS68Euo4vV+AthuYDs41HO/+rAvybAeuQdcAODhER0SgYsSBjLhMnIiKibYcjOERERKOAq6iIyM2vwZll96k7ZMyNKqZGtTdNcxyLXPKwX5RlPI+Mu5DH5fVudpRM8z5HWR1TIn+FuP/2C546wf36rXuZ+N275OOirNp7RRWH4YxRUqdH6JyqQZ1aQN4r571Un+/kN/WBOkbF/eNGvp7/mBn39qnrB7sf3b5+I8j4k76u3TVOURERERENN47gEBERjYIRG8FhB6eHuNHf9rCxOeYoP3XdRVHji6L8ZlH+S8VxuRS7+bhc9i2nnGT2cPn9Jsvu2cEjkScU58sppPbf353JXzlyykv1eu7X87udfyvVb//OU0peXk817eJv6bF7tuvWtgRLhaDif0rL3/GgU1bq6/n7WqnvX/P35ldx2223tW1HXzf6YweHwsKN/oiICHg3nnvus22PDORGf9sEOzhERESjwOsIzucWgT/psJPxJe5kTERERIPEay6q+Gzj0c6ZCjA/HCNO7OAQSYsRR3HPRy6JCjIORsa1qJaJyzgTGZNzocP/gdbUCnIK9GVRlm2V58u2yN9+8s89Wd89NYMqVYHfpc+qZeCt5K84+bVS/bZ3X3odNG6kNdXFtfst43t6vUw67OupBI+pUS079xuT4y/VQ9DX2xKbCB5DM0QxOFwmTkRERNsOR3CIiIhGAVdRERER0bbDDg7RiFlwxtxEHjFFBRnH8hVRVsXUyDiVs4oGNdeXv41uFmWZ9kHGwMjzZcyHKvWCU2tciEy9IK/nvm9Oa8zNW0XZGVPkP+ZFXt/vPj7y/qliemSMjmrfnc4xSvLehr1vjd/zW19fts99T6CgMSqt+9TIeCz34+rre0+j0a7+UMTgjBh2cIiIiEYBR3AoLNzJmIiIFhcXsbjYfl+Zvu5kzGziFBbuZExERG5/0A7kTsYnF4Evddjo78fc6K/varUaNE3b6mbQEPiHizsd5V2/KWJuLsuYGUnG5Kj8SJRVcR27m/4vY2Zk7ilJ/vKR+7zIsrz+blGWMTAfV7yefC9+c1XJ67nvq6OOCfL7eqpfie4xN63cY6BM8wFH2RnX4WVHtmZ+9wxyry+1xhO5/ynvN15Kdb46xsXZnuC5t5z3X3X/hoLXKaqfnW082vm7CvDogHXIOhjCr1BDJOIMDNV1HeVy2S5XKhVks1lomoZ6vQ7DMJBIJBznhFWHiIho4G1RDM5WDUAMZQdnaWkJqVQKExMT9nPxeNz+f61WQywWQ7lctqeIJiYmsLa2hlQqFWodIiIiuiaMAYgwDGUHZ2VlBcVisePxdDqNeDzuiH/JZDJIp9N2xySsOjQECs4ftl1JuQxcNSX1giirpiXkFNZLoqz6sWuehpHLpuWUj2yLXHYsl5XL82Xb/C0bV0+5qKaM5J+T8mvhPp0XfKmzPN/9z1vVUmE176kr5JSQesm5+xRN69fS35SO32XXKq3Luv1NWUn+p6CCpgHxd7/Dvn9d8ZqLSnUNF2EMQIRl6FI1FAoFrK6uIplMYmlpqeV4vV5HqVSCYRiO5ycnJwE0bn5YdYiIiIbGZkgPFysrK8jn85ibm7MfzYMEbgMHYRu6Dk6xWES9XkehUEA6ncbevXtRKpXs46urqwDQMt9n3cxisRhaHSIioqFhxeAEebh0cMIYgAjT0HVw8vk8TNNEuVxGKpWy5+9qtRoA2P9Go9G259dqtdDqqJw/fx4bGxtdPy5evKh8DSIi2kqXAbyufHT6PX/+/Pkta3nYwhiACNNQxuAAjRuSz+dhGAaSySQymQxWVlZQrVYBAOPjcnlpQ71eD62OyqFDh5R13Dz88MN45JFHAl1jJJVF6oWWmJvvi7KMmZFLgX8gyvsU15M/VvJ7SE6Cy7iM5rgWtyXk7WJeHhPH7xfH3bejb22rfG8y5kfGIahiblQBAH5TI7jHJPmPqwgal+EUZPv+1teW99b9Xqna3v/UD36XpQdNheAvXsvv612r/2UAJ5Wt2bPnt5R1em4TwOsXgc0Afzxf6Nwhy+fzyOfzqFQqyOfzWFpagmEYqFar0DQtlIEDP4a2g2NJJBJIJBKoVBo5eazAprW19oGjmqaFVkfl5MmTuP3225X1OhkbG+v6XCIi6of3AngPzp2bdzy7Z09WcZ718ftdAE/2oF1tbAL4chb4s2CdWZUgAxBhGvoODgAYhmEPg1kdj043StO00Oqo7Nq1C7t3y43TiIho+7gOwHVtfte/wcN5ANDnP2TfMw+86wF1vU6+fxr4r95mJ7oZgAjTtujgANeClKx/5VCXVY7FYqHVISIiGhqXAZhjwI4Anaodu3xV9zsAEaZt0cEpFov2ErNoNApd11EsFjE3d23PCusGT09Ph1aHBsSiiLnJq/a5OSvKMo7jK6L8ZlF+Ge5UW4XKOBK3H0MZ/+Nv+/hI5ClxXKZmkOR7c987pZW/PDWqOBB1DIz82vndrt89/YA6rsQ9Bsjv3ihur6eOCXHfJ0cdw+L+cSBjgOSeQCr+94FRtUcVM3NZcdydel8g9+t5/d5u5KL6pK+2dc3DMm9P1/DJzwBEmIZqFZWVlGxh4doPWqFQwPj4uGMXxOXlZZRKJcdNzOVyyOVydnBTWHWIiIiovU4DEM16NXAwVCM4mqZhfHwc2WwWxWIRuq7DMAzk83lHPWtb6EwmY0duZzIZxy6JYdUhIiIaCj3MRVWpVDAzM4MjR47Ysx6dBiBisZgjP1WvBg4ipmnK8XwKyBppat6KmkL0NTEl9aD4Fv7y8+IEOY0glz7L+vI3gFxGrsqQ7Z4R2zQ/5Ci3Ti2MN9WVy7xV2bz9Zq+WS4/lMm45nea+zFs95SKnyPxl41Yvbfb7N5t7dvCgS6n9T4uo0jG4UaWZUE2Z+L23/qaAws4u3ircJf5B36/Kta/1KwA+2dPPC+szCYky8I8DvsbfV4BC6+dbvV5HMpnE6uoqJicn7QGI5jQNze2xclHVajUYhtGTgYOhGsEhIiKiwRONRj1v1KfrOlZWVnrcInZwempqago33tj+r/3Z2VnMzs72uUVERNRvi4uLWFxcFM++evXfoNkvfehDss1Bwg5OD504cYJTVEREI67dH7RyiqovtmgV1VZhB4cG3+dFzM2/EDE3LWEcZ32+gBxlk3EZcpm5e4xN6/Wc5dY4ms5Ljd3icxrkn1Oy7EwD0frazj/n/C/L9rcsujUtheS+7FtSL/t2j7GRx/3G3KjqB0l/EPayZlV8T/DUCP2len/Bl8331pYtE/cyAvO/FhuPttfwtxXEVmIHh4iIiK75qdnGo53XKsAfD8dGt+zgEBERjYIeLhMfROzgEBERjQIGGRNtsRkRc/OnMuZG7ltzVpTlPjf7RPkFnw1qn/n2GhmjI+s70x/42YumNSbG7z4p7jEzUmtb5PkyZsdfqoXW15MxKu6/ff3HtKj20VkQZXl//e2toooLUX89Lzcd8xf/E3SfG7/70AS9nl/+9yTy9/HW6/slbXUM0ChgB4eIiGgUXEHwKaYrYTSkP9jBISIiGgWXEXyKiVNUBHCjP88+LqaknhRTUqacApJUS6XllNVuUZapGCQ55SSvJ8mM3M6lyK3TQPLH8Fo6A/Uw/K2K15ZTPjIzunwv/paNBx+295ut/GZR9vu9Ickpu2BTUv5f3/unhd9UCkHTTPjn/nHS6ymZ4Kkewr1+c/12G/1FIn9w9X9D1GMYMuzg9BA3+iMiovYb/VkdolcALPWnIVxFRURERNuO11VUf7cIfIcb/REREdF28r/NNh7tbFSAr3OjP6L25DLwr8mYm6+JE2TMjFwmLuMw5J8o7xDlF0VZxtjIOBX5en7J2Ai5TFwuFW5OZ6CKUXnJZ1tkjI67SOQJ8Yx7e1pTQahSM8hUCv6WdbfejzeKsvvrq+Mq5DLvrVv67HcZc5DXahx3XzLf62Xhquv7fT1V/aDL5LttTyNVQ5+mqLiKioiIiLYdxuAQERHRtjNiy8R3bHUDiIiIiMLGERzqPbnPzdMi5ua78oSzoixjcN4qyjLmRsbkyL1eZJyGrP8txfX9csaBtMaRyDiU5r2T3PdpkVr3bZExMXJfph8ori/vnSpG5jFRX8bAyHikOXG+v3125PtrjW+S11OlulC9P1XqhfDiUoLGhASt38r9T/ewUxP0OnWE//uxDT4umYuKiIiIth0GGVNYuJMxERG128nYcuHC8OwrM2zYwemhkd3J+EkxJZUVU1KvfkWcILN7v12UZX2ZnkAulZZjsHKa5G2K46p0BXLaR5VtXLWUu/M0lCobt9Q6/eW8tpzCUZ3fOoUk37skp7zkdKCzPcGXPrsvuQ+aOkK9lFreb9X1nVrbd+31g6dikPfevW2ty579ZYL3vww92JSZ32Xf/Z/Su8btD9rGMvE+7SvjdRXVa4uNRztXhqdDxg4OERHRKPC6imrPbOPRzoUKcHY4NvrjKioiIiLadjiCQ0RENAq4iorIp8+LmJuPyZibs+IEuSx7vyh/x1FqjQM5JurfLMryJ1C+nmyP/Il3Boa3Ln1WkXEoMtDc+28Y9bJm5xLz1nv126IsY0ZkW2TqBRlHIe+Nqn3BUiWofkWp4lTU3FNP9Hqpdqtrr9/PGBEv1wt6r1XxUWHfS7f4Ji/X83s/w14m3xMjtoqKU1RERES07XAEh4iIaBQwFxURERFtO+zgUFi27UZ/bxUxNz8QMTctPwBnRVnGzLjvq9C694pM3aBK1SC5x53IuJHWvVZkHIuMuZHvx/k9oN5fpPn6ch8b97gFdRyFbLv8/pRtl2kkJH+pDST1Xi/+9gHyW7/1/HD3YglSv/Xe+UuVsNUxH8FjgtzTYvi/9+7fG0FjntzOX1xcxG233db2WF83+gsjQJhBxgSM8EZ/RERkG5iN/ry6sAi83mGjP5Mb/Q2kWq0GTdO2uhlERET9twkgoqwF3DDbeLRzuQL8cMA6ZB0M5SqqQqGAWCyGSCSCWCyGUqnUtl4kEnE8ksmk43ilUkEymUQmk0E6nUahUGi5hpc6REREA8+KwQnyYAxO7ywsLKBYLCKdTqNarWJhYQGGYaBYLCIej9v1lpaWkEqlMDExYT/XfLxWqyEWi6FcLtvTSBMTE1hbW0MqlfJcZxR8LeLs8r/7RhFzc/l5ccZZUZZxHidFWeZykjEy7jEtrfvoqPahUX3bq/aCkdxjilR70/iZ1FbvO+Mvl1LrvZDxQv5yPfndSyXsvUb8CxZQEPz9+Mud5actqtfyu+eP31xTfvnPZRXs/fi11TFN210vZliGroNz6tQpFItFu3zkyBHEYjHkcjlHB2ZlZcVRT0qn04jH444YGWuUxuq8eKlDREQ0FDYBmMpa7hQb/RUKBWSzWVQqFei63vLZbImIP5x1XUe5XA7YOKeh6uCUSiXkcjnHc7quQ9d11Go1+7lCoYDV1VUkk0kYhtHSGanX622vNTk5CaAx+jM9Pa2sw04OERENjcvwFoPjxqWDFNYMS1iGqoPjdgOah7aKxSLq9ToKhQIKhQIymQxWVlbs81dXV1vOAWCP1BSLRfuYW51t28F5SkxJ4TXn8QuqVAMboiynsOSU1PdFWU4pvVWU5TLwr4vyG0VZTkPIKS/VUmfVFvVySszfFJg7eS25bFu23bkUtnUYX5XawXsqgUZ9uewcPo8Hm+YIOm3S63QIftvTXD/oEnTVMuuggt6LXk+JhT192OspsO0grBmWsAxVB6eTWq2GdDptl/P5PPL5PCqVCvL5PJaWlmAYBqrVKjRNs0d7otFox+t5qaNy/vx5bGzID3vvxsbGMDY21vX5RETUWxcvXsTFixe7Pv/8+fMhtkbB6yoqNx1GcMKaYQnTUK6ialYoFKBpWtubpOs68vk8VlZWADTiZwCgWq0CAMbH5UhCQ71e91RH5dChQ9izZ0/Xj2w2q3wNIiLaOtlsNtDv+UOHDvW3wWbARwfxeLxjkHCnGZZ0Oo29e/d2XAkd1NCP4GSzWbsD00kikUAikUClUgEAe95vba39jreapnmqo3Ly5EncfvvtynqdcPSGiGiwzc/P44EHHlBX7OD06dN97uRcvProlr8RJ78zLGEa6g5OJpPB8vKyp5tiGIbdS7TqdxqF0TTNUx2VXbt2YfdumVZg8Kzglxzl6V/7W1FDxODgi6IsO4FvFmUZUyNjeGRciazvHkPjP2YmWHqBVn7TC8il2HMd6rXyH8cgY3J6G/PS6+35W+s7Y3zCjkMJ+n7CjNkJ/rUPdi/8bgHQa72OgfH6sxM0lGDXrl1dn9udLID+fK28zLAYhmHvNacarPBraDs4Vq/PTyoEawWU9a+Mo7HKsVjMUx0iIqLhMg+g+xEn4DQAbyNO3cywhGkoY3Cs3YTlqiq3G2QtXQMagcO6rrdEcVsjPNPT057qEBERDZcxNBIWd/vwNuLkd4alUzhIEEM3glMqlZDNZpFOp7G0tGQ/Xy6X7VGVmZkZHDlyBHNzjaH/QqGA8fFxJBIJu/7y8jJisZhj98RcLodcLmevnPJSh4iIiK4JMsMSpqHq4FQqFRiGAQCOoCXL+vo6gMbKp2w2i2KxCF3XYRgG8vm8o661a2Imk7GXjmcyGcdcoZc6w+h9+BNH+YuR3xI1XhRlVaqEl0VZtTT+h6Ks2lfGnd/t7mXchipmRx1rIO+He/tU3GIZ/MY9yPr93r4+aNyGKm5EtY9P8Jig/l6vuRw0piXstg/7+UFt9euH4zJaYyC7uUZnbjMsnTo8zTMsYRqqDo6u6zBN9T7TXjcQ0nVdOT/opQ4REdHgszJmBr1Ge2HNsIRlqDo4RERENHjCnGEJCzs4PTQ1NYUbb2w/fTE7O4vZ2dm+tOOmjXVH+cKed4kafyTKchn2/Y5yJPJxxSvKKSjJfVm1/2Xa7vxnuHZfHtrraRm36wfNPr2VUy5e6rfeG39/bfZ7GiFoOoUwrx32Mu2gqRXCFvbPYT8tLi5icXGx7bELF2QIQC/1booq7BmWMLCD00MnTpzwFWRFRETbj9sftJVKpY/bjmwi+BTVZhgN6Qt2cIiIiKjJEwCe7HDs9X42JBB2cIiIiEaC1ymqD159tPOXAO4KrUW9xA7ONhSR2zea/108IZdh+/s2ME33XTBbYwHe6Hp+a8yNeyqF1tdzj9kJGjvgd/t//7ET3rfQDxof1Otl4kHjHrZ6+39pmJYGD1NMSjd6Ge80Onq/THyQDOVOxkRERERuOIJDREQ0EhhkTERERNvOaE1RsYOzDUQiXxPPnHSUWrezV8WsuMd5tNYPlg7ALebEG+cPXK9jDYK2N0h7ev/eerudfq/jKIY9zqSXRi2Ghd8L7YzWCA5jcIiIiGjb4QhODw3KTsZERLR1RmEn40EUMb3srUy+WDtTlstl7mRMREQd9ePz4tpuyf8FwDs8nHH86qOdiwBeGYrPN47gEBERUZPpq492ngfwr/vYlu6xg0NERDQSRmuKih0cIiKikcBVVERERERDjSM4REREI4FTVERERLTtcIqKiIiIaKhxBKeHuNEfERFxo7+twQ5OD1y6dAkA8OlPfxrvfve7t7g1o+3ixYvIZrOYn5/H2NjYVjdnpPFrMTj4tegvtz9ov/rVr+I973mP/bnRW5yiooCsb9T+fMOSm4sXL+JjH/sYLl68uNVNGXn8WgwOfi0GR38/L6wRHNXjjwD82w6PbB/aGQ6O4BAREVGTX7j6aKcG4ME+tqV77OAQERGNBMbgEBER0bZzGcE7KMPTwWEMDhEREW07HMEhIiIaCZyiIiIiom1ntJaJs4PTQ7/6q7+Km266qe0xbvRHRDQa3Db6+9GPftTn1owOxuD00Kc+9Sk899xzbR9+Ozedfji6Eea1huF6YRvk9zvIbeuFQX+/g/y1Ddsg37utvt7s7GzHz4JPfepTobbLndd9cNwewzNFxQ7OkBjkX5SDfr2wDfL7HeS29cKgv99B/tqGbZDv3TBcrz+sKSrV41kAH+vwWOp7q7vFKSoPKpUKstksNE1DvV6HYRhIJBJb3SwiIqIe+Pmrj3b+DsDv9rEt3WMHR6FWqyEWi6FcLkPXdQDAxMQE1tbWkEqltrh1REREXo3WKipOUSmk02nE43G7cwMAmUwG6XR6C1tFRETkl9cpKrfH8KyiYgfHRb1eR6lUgmEYjucnJycBAEtLwzMXSUREo45BxnTV6uoqAEDTNMfz1mhOsVjse5uIiIhIjTE4Lmq1GgAgGo26Hpdef/11AMA3v/nNQK9/ww034IYbbgAAXLhwAZVKJdD1LGFea9Cvd/78eQDA6dOnsWvXrlCuOcjvd5DbNmpfi7Cvx6/FYF7v0qVLuHTpUtfXsT4nrM+N3voego/AvBpGQ/rDpI7m5uZMAGa5XG45BsDUNK3teU899ZQJgA8++OCDDz48PZ566qmefZa99NJL5k033RRaW2+66SbzpZde6ll7w8IRHBcTExMAgLW1tbbH5dSV5f3vfz+eeuopvOUtb8Eb3vCGrl+/eQSHiIgGT9ARnNdffx3f/e538f73vz/EVjndcssteP755/Hqq+GMvrzpTW/CLbfcEsq1eokdHBdWB6Zer7sel970pjfhgx/8YK+aRURE5Mstt9wyFJ2SMDHI2IW1WkrG2ljlWCzW9zYRERGRGjs4LqLRKHRdb1ktVSqVAADT09Nb0SwiIiJSYAdHYXl5GaVSyTGKk8vlkMvlOq6uot7qtHqNiBr4M0IEREzTNLe6EYOuORdVrVaDYRht0zQwZ1VvRCIRR1nXdZTLZbvs5b6HVWdU1Ot1ZLNZAI0OvdTPez7qXxfV1wLgz0g/FQoFZLNZVCoV6LqOXC6HeDzuqMOfjwGx1cu4totqtWoCziXlmqaZ+Xx+C1s1/PL5vJlKpcxcLmc/mu+xl/seVp1RUSwWzUQiYQIwU6lUy/F+3vNR/7qovhamyZ+RfsrlcmY8Hjfz+by9jQgAs1gs2nX48zE42MEJSTweN+PxuOO5fD5vsg8ZjLyn7Y6r7ntYdUZNpw/Vft5zfl0a3Do4/Bnpn0Qi4SiXy2UTgOO+8OdjcDAGJwTMWdUbhUIBq6urSCaTbe+hl/seVh1q6Oc959dFjT8j/VMqlVqmCHVdh67rdswTfz4GCzs4IWDOqt4oFouo1+soFApIp9PYu3evvYIN8Hbfw6pDDf285/y6qPFnpH/i8XjHvc+s5/nzMVjYwQlBtzmryF0+n4dpmiiXy0ilUnYAnXU/vdz3sOpQQz/vOb8uavwZ2Xq1Wg3JZNL+P8Cfj0HBDk4IqtUqAGB8fLzt8U47IZM3uq4jn89jZWUFAJDJZAB4u+9h1aGGft5zfl2848/I1igUCtA0zV5Vy5+PwcIOTgi6zVlF/iQSCSQSCTsjsJf7HlYdaujnPefXxT/+jPRXNpu1O5UAfz4GDTs4Ieg2ZxX5ZxiG/QPt5b6HVYca+nnP+XXpDn9G+iOTyWB5ednx3vnzMVjYwQkBc1b1l3W/vdz3sOpQQz/vOb8u3ePPSG8tLS3BMAw7oNfCn4/Bwg5OCJizqn+KxSLS6TQAb/c9rDrU0M97zq9Ld/gz0luFQgEA2u5ezJ+PAbPVG/FsF9aGT9Vq1X5O0zQzl8ttYauGV7lcNnVdd9y/lZWVls3OvNz3sOqMkvX19Y6by/XznvPr0vlrwZ+R/isWi6au62Y+n3c8UqmUvXswfz4GB3NRhchrzipSq9frSCaTWF1dxeTkJHRdh2EYLX81Ad7ue1h1RkGlUkE+n8fS0hKi0SiWl5cRj8cdy1H7ec9H+evi9rXgz0h/VSoV12mf9fV1+2eEPx+DgR0cIiIi2nYYg0NERETbDjs4REREtO2wg0NERETbDjs4REREtO2wg0NERETbDjs4REREtO2wg0NERETbDjs4REREtO2wg0NERETbDjs4RERDIpPJIBKJIBKJYO/evdi7d2/HciQSack0vVWWlpYcbUsmkzAMAxMTE0in06jX667n12o1RCIRTExMIJPJIJPJoF6vo1AoIJlM2te1koy6WVhYsOvHYjEsLS15eg+lUgkTExOOc63Em80KhQJisZhdp1KpoFarIZPJIJ1O2/dB9Z4pBFubCouIiLxKpVJmPB4319fX7efi8bgJwFxZWbGfs5IwlsvlLWhle6lUqiVpaLVaNQGYmqY53pNk1bMSWkqappkATACu15F1m5NUemElPnVri2maZj6fN6PRaNtjc3NzntpJwXEEh4hoiOTzeUfi03Z0Xcfc3Fx/GuSRNZpkGIb9nKZpiMfjqNVqKJVKXV87Go3a9ySbzXasVyqVoGmaXR4fH/f9OtZ9XVlZ6VivXC5jfn6+7bF9+/b5ek3qHjs4RERDwjAMxwe0m3Q6rewI9ZPVgZHZzq02BplOGx8ftzsUblNOuVwOmUym69cBYL9OqVRCpVJpW+f48ePM6D0A2MEhIhoSiUTCc11N06BpGgqFAgzDQKlUsmNh0uk0CoWCHQ9ifVCXSiU7piWZTDquV6lUHLEzfjoK1vU1TWvpdFnHdF33fL12EokENE1DvV5v28mp1Wqo1WotHSzZFtV7jEaj9teh3WhRoVBAPB4fqM7lyNrqOTIiIupeuxgcy8rKih1zkkqlzLm5OVPXdVPXddM0r8XFNMfqWPEuiUTCfq5cLpvxeNxxXYh4GjdW3Imsb8UKaZrmer4qBicej5vVatXM5/Mdr5dKpezz0SZex897tNojr2GapqnrulksFju+l1wuxxicPuEIDhHRNpVIJOyVRdFoFLlcDuVyGeVy2X5OaheXMjMzg1wu57huNBrF0tKSp9VA1vSUFX9jrYA6fPgwotEoisWi37fWViqVQjQabYnpqdfrKJVKrtNGft6jFTsEOEdxvIwSUf+wg0NEtI1ZnZg77rijq/NrtRoqlQqy2SySyaT9sKyurrqeX6/X7WmoY8eOIRaLIZlMolgsIpfLYX193XNckRdWJ6a5s7K0tOQ6vdfNe7Smr5qnw3K5XMfgYuq/67a6AURE1HvdxoRYnRO3VUNurJEUXde7voYf8/PzWFhYsIOAdV1HPp+3R63a6eY9xuNxaJqGWq2GpaUlpFIpHD9+HGfOnAn8HigcHMEhIqKOrNVN3a5ysqafjhw5Elqb3MggYC9Bv92+R2sUJ5fLoVAoYHJyksHFA4QdHCIi6siaPmq3ay8A5f41nZaHh2ltbc1RtqaJCoWCvYOwm27fY3PMz8zMjKedlKl/2MEhItoG5Ie8F9amc80jF9b/rcBaq2OSyWRa9n1RpTmwgm6j0WjgZeAqzYHAuq7b7dY0TfnaQd5jc8yNn2X81Hvs4BARDTHZIZGs59sdtz74M5mMvU9OPp8H0Bi1MAzDsXuvFSC8sLAAwzBQrVZdR2askY/Jyclu3ppnVkeqmTV9JPeyaa5ndQqDvEcrqJkb+w2grV6nTkRE/hWLRXsfGwBmNBo15+bmHPmVmvfB0TSt7T4yuVzOjEaj9vmm2cjXNDc359gfJ5fLKa/VzMrHZLVNVd9Np31wVlZW7H2AotGomcvlHMeb97Wx2qTrun3PdF13XNPve7SkUinPea24D07/REzTNLeob0VERKRUq9UwMTGBfD4/9CMlCwsLyGQyWF9fZ0Byj3GKioiIhoKXTQUH3WuvvbbVTRgZ3AeHiIiGQjabtTsI8/PzQzMCUqvV7NgmVdAyhYdTVERERLTtcIqKiIiIth12cIiIiGjbYQeHiIiIth12cIiIiGjbYQeHiIiIth12cIiIiGjbYQeHiIiIth12cIiIiGjbYQeHiIiItp3/H8eGjDfL/ROeAAAAAElFTkSuQmCC",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -156,11 +210,12 @@
     "a0 = plt.hist2d(\n",
     "    trueP_found,\n",
     "    endVeloP_found,\n",
+    "    # endUTP_found,\n",
     "    density=False,\n",
     "    bins=nbins,\n",
     "    cmap=plt.cm.jet,\n",
     "    cmin=1,\n",
-    "    vmax=200,\n",
+    "    vmax=150,\n",
     "    range=[[0, 20000], [0, 20000]],\n",
     ")\n",
     "plt.xlabel(f\"True $P$ [MeV]\")\n",
diff --git a/trackinglosses_energy.ipynb b/trackinglosses_energy.ipynb
index b6806f2..beeb1af 100644
--- a/trackinglosses_energy.ipynb
+++ b/trackinglosses_energy.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17,7 +17,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [
     {
@@ -53,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [
     {
@@ -197,7 +197,7 @@
        "<Record {all_endvtx_types_length: 7, ...} type='{all_endvtx_types_length: i...'>"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 57,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -208,7 +208,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [
     {
@@ -236,7 +236,7 @@
        "<Record {lost: True, rad_length_frac: ..., ...} type='{lost: bool, rad_leng...'>"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 58,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -273,7 +273,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 124,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -349,7 +349,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 125,
    "metadata": {},
    "outputs": [
     {
@@ -387,7 +387,7 @@
        "<Record {event_id: 0, lost: True, ...} type='{event_id: int64, lost: bool, ...'>"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 125,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -407,7 +407,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 126,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -425,7 +425,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 127,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -460,7 +460,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 128,
    "metadata": {},
    "outputs": [
     {
@@ -497,7 +497,7 @@
        "<Record {event_id: 1, lost: False, ...} type='{event_id: int64, lost: bool,...'>"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 128,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -513,7 +513,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 129,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -527,7 +527,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 130,
    "metadata": {},
    "outputs": [
     {
@@ -574,7 +574,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 131,
    "metadata": {},
    "outputs": [
     {
@@ -615,7 +615,7 @@
        "<Array [-3.61, -33.8, -133, ..., 8.82, 12.8, -17.8] type='19848 * float64'>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 131,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -640,7 +640,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 132,
    "metadata": {},
    "outputs": [
     {
@@ -703,7 +703,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 133,
    "metadata": {},
    "outputs": [
     {
@@ -733,8 +733,9 @@
     "        if ntuple[jelec, \"brem_vtx_z\", jphoton] <= 770:\n",
     "            tmp_velo += ntuple[jelec, \"brem_photons_pe\", jphoton]\n",
     "            tmp_velo_length += 1\n",
-    "        elif (ntuple[jelec, \"brem_vtx_z\", jphoton]\n",
-    "              > 770) and (ntuple[jelec, \"brem_vtx_z\", jphoton] <= 2700):\n",
+    "        elif (ntuple[jelec, \"brem_vtx_z\", jphoton] > 770) and (\n",
+    "            ntuple[jelec, \"brem_vtx_z\", jphoton] <= 2700\n",
+    "        ):\n",
     "            tmp_richut += ntuple[jelec, \"brem_photons_pe\", jphoton]\n",
     "            tmp_richut_length += 1\n",
     "        else:\n",
@@ -750,11 +751,16 @@
     "    energy_emissions.field(\"neither_length\").integer(tmp_neither_length)\n",
     "    energy_emissions.field(\"downstream\").real(tmp_neither)\n",
     "\n",
-    "    energy_emissions.field(\"photon_length\").integer(tmp_neither_length +\n",
-    "                                                    tmp_richut_length +\n",
-    "                                                    tmp_velo_length)\n",
+    "    energy_emissions.field(\"photon_length\").integer(\n",
+    "        tmp_neither_length + tmp_richut_length + tmp_velo_length\n",
+    "    )\n",
     "\n",
-    "    if (tmp_velo == 0) and (tmp_richut == 0):\n",
+    "    # if (tmp_velo == 0) and (tmp_richut == 0):\n",
+    "    if (\n",
+    "        False  # (tmp_velo >= 0.5 * ntuple[jelec, \"energy\"])\n",
+    "        or ((tmp_velo == 0) and (tmp_richut == 0))\n",
+    "        or (ntuple[jelec, \"energy\"] - tmp_velo < 3000)\n",
+    "    ):\n",
     "        energy_emissions.field(\"quality\").integer(0)\n",
     "    else:\n",
     "        energy_emissions.field(\"quality\").integer(1)\n",
@@ -768,7 +774,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 134,
    "metadata": {},
    "outputs": [
     {
@@ -802,7 +808,7 @@
        "<Record {lost: False, energy: 5.09e+04, ...} type='{lost: bool, energy: flo...'>"
       ]
      },
-     "execution_count": 16,
+     "execution_count": 134,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -813,7 +819,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 135,
    "metadata": {},
    "outputs": [
     {
@@ -823,16 +829,16 @@
       "found:  41978\n",
       "lost:  8523\n",
       "50501\n",
-      "VELO energy emission, eff:  0.19057048375279698\n",
-      "RICH1+UT energy emission, eff:  0.1271657986970555\n",
-      "Neither, eff:  0.513494782281539\n",
+      "VELO energy emission, eff:  0.18201619769905547\n",
+      "RICH1+UT energy emission, eff:  0.12653214787825984\n",
+      "Neither, eff:  0.5226827191540762\n",
       "total efficiency:  0.8312310647313914\n",
       "efficiency:  0.8312310647313914\n",
       "\n",
       "found in velo/(found + lost in velo)\n",
-      "VELO energy emission, eff:  0.8275150472914875\n",
-      "RICH1+UT energy emission, eff:  0.7901082677165354\n",
-      "eff von e die nicht strahlen:  0.8435090915005041\n"
+      "VELO energy emission, eff:  0.848831840428479\n",
+      "RICH1+UT energy emission, eff:  0.794479671764267\n",
+      "eff von e die nicht strahlen:  0.8345505706788074\n"
      ]
     }
    ],
@@ -880,7 +886,8 @@
     "\n",
     "eff_rich = num_rich_found / denom\n",
     "\n",
-    "eff_other = ak.num(electrons_found[electrons_found.quality == 0], axis=0) / denom\n",
+    "eff_other = ak.num(electrons_found[electrons_found.quality == 0],\n",
+    "                   axis=0) / denom\n",
     "\n",
     "print(\"VELO energy emission, eff: \", eff_velo)\n",
     "\n",
@@ -908,7 +915,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 136,
    "metadata": {},
    "outputs": [
     {
@@ -929,21 +936,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 137,
    "metadata": {},
    "outputs": [],
    "source": [
-    "energy_emissions = energy_emissions[energy_emissions.energy >= 5e3]"
+    "# energy_emissions = energy_emissions[energy_emissions.energy >= 5e3]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 138,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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qraLKczGvhIqMEQIAYE0FQSDf9xP/WK/X65I+LZIufcr112q1RoKfqLUoz3IbCAVBsOoqAABwK5MGN+/u7kr69nnX6XRUKBRk27ZKpVIuB0YnyVQgFA3ksm071fGWZWljYyPxK0o6Fbm6v1qtLuItAACwdEm5f6L1PqNlsAzD0Ndff61yuawgCLSzs6N2u73EWmZTZsYIdbtdOY4j13VH+jDHCYJAQRCo2WyOLO7a7/fVarVGRsq3223VajWVSqV42+X9AACso6hL7Oof/9K3wVH07AuCQIZhyPM8ua6rarWqer2e6pl7l2UmECqXyyqXy9rY2Eh1fLfbVa/Xu7bC/dUgSPrUHOh53ryqCgBAJhiGIdM05ft+HOhETk9PVSgU4kCn2WzG44UqlYocx1G9Xr92Hpml10StVrsWBEnSycnJSLeX67o6PT1VtVqlCRAAcOdEY3+iwdHSp2Cm2Wzq+Pg4fla+fPlyZHxsGIYyDCMOgqKWI8dxFASBXNdd3ptYocy0CM1DGIbyfV97e3vxNs/zFIahXNeV67qybVudTmeqrrHz83N9+PBh5nptbm5qc3Nz5vMBAAlytKq77/txa47v+2q1WnGDQDT25+nTp7IsKw5sOp3OyGyy3d1dWZalSqUi6VNX2eXFW6Mp9y9fvpT07WyzVbi4uNDFxcXM55+fn6c+dmM4HA5nfqUF2NjYiG/GtNrtthzHSVyVN/ohilqF+v3+jQmjpslDMMmzZ8/0/PnzW5cDAON+lfArBnfJ8+fP9eLFi1uX0+v1bswDeKdahDqdjp48eZK4zzRNOY4jy7JUrVbjlqE03rx5owcPHsxcL1qDAABI7/DwUF9++eXM5797904PHz5MdeydCYSidVNuakmqVCqqVCpT5U/Y2trS/fv3b1tFAACQwm2HlGxtbaU+dm0HS1/V7XZHBn1NYlmWBoPBEmoFAACy7M4EQicnJ/EAsDSijJsAACC/7kzXmOu6iYOkk3ieNzLNEAAA5FOmWoQmJXEKgkClUikxe6bruioUCtdGhkezvi4vMOe6rorF4lStRwAA4G7KTCDk+368xtjLly/luu5IYBSGoQaDQWKwdHJyMpI7KGIYhorFohqNhizLkm3bKhQKK82NAAAAsiNzeYSyJGpRSpOHAACWYdp8QeQXQh5N8/zOTIsQAADAst2ZwdKL9PjxY927dy9x3/7+vvb395dcIwAA8u3o6EhHR0eJ+z5+/Ji6HAKhFF69ekXXGAAAGTKpIWKaJbLoGgMAALlFIAQAAHKLrjEAwFpalxlx61LPvKJFCAAAzJXv+2q326uuRioEQgAArJEoAXG1WlWpVBpZPWHVgiBQtVrVzs7O2iQvpmsMAIA14fu+Hj16pLOzM0mSbdvq9/srrtW3DMNQp9PRxsbGqquSGoEQAABrotFoqFgsxt83m80V1uZuIBBKgYSKAIAs8H1/1VXIDBIqLhEJFQEAq9Rut+V5noIgkCRVq1VJUr1eV7lclvRpcfJocfEoYLJtO97vuq6ePn2qMAzjNbi63a4cx5HruqpUKup0OgrDUC9fvpTjODo8PFShUJBt2/J9Pz7msuh1I6VSaeHXQyKhIgAAuVGr1dTpdGQYRjwOp9PpxEGO7/v6/PPPVa/X1Ww25XmeqtWqLMuKB1NXKhXt7e2NlFsul691rw0GA3meJ9/35TiOPM/T8fGxarWaXNcdGZwdBIE+//xzVatVOY6zNgOkLyMQAgBgzT19+lS7u7sjvRe1Wk2macq27bglqVAoXDv38pgj6dOA5ydPnkiSLMtSs9mUaZpxkON5Xnysbdva3d2NAzJJOjg4mNv7WgYCIQAA1lgQBPJ9P3EIR71el6SZW2qSAqfBYBC/ruu6sixrprKzgkAIAIA1NmkA9e7uriTFLULzFJVpGMbcy14mAiEAAO6AMAyvbYtadK52f81DFAhFLUTrikAIAIA1FnWJdbvda/ui4GgRM7milqBerzf3speJQAgAgDUxGAyutcAYhiHTNBUEwbUusNPTUxUKBdVqNUnSd7/7XUmjXWXR/5NalCaJut3a7XbiudOWtyrkEUqBhIoAgCzrdDra2dlRvV6PZ3WFYahms6nj4+O4iyxqPYryDQVBELfodLtdWZYlz/NSdXcVCgUdHByo1WrFa4sZhhEPzA6CQK1Wa2GzyOaVUHFjOBwO51WpuyZKyBQlngKAVXv+fLHHI5uinD7Riu61Wk3VanVk2noYhnHCxKjbql6vX3t+tVotNRqNuJxms6lSqaRKpRJPm3/69Kl8348Dm93dXdm2Hb9+s9mMA5x2u61ms6kgCGSapjqdjizLUqVSUb1eX8lg6mme3wRCExAIAcgaAiHgZtM8vxkjBAAAcotACAAA5BaBEAAAyC0CIQAAkFsEQgAAILcIhAAAQG6RUDEFEioCAJAt80qoSCCUwqtXr8gjBABAhkxqiIjyCKVB1xgAAMitOxkIXV10DgAAIEmmusbCMIzXP2k2m6nP29jYGPneNM14ETnpUxNZo9GQYRgKwzBeAwUAAORbZgKhbrcrx3Hkuq5qtVrq89rttmq1mkqlUrzt8iJ0QRBcW2+kVCppMBhM9ToAAODuyUwgVC6XVS6Xr7Xu3KTT6cjzvLH76/W6yuXyyGBn27ZVr9cJhAAAyLm1HiPkuq5OT09VrVbVbrev7Q/DUN1uV5ZljWzf3d2VpMRzAABAfqx1IOR5nsIwlOu6qtfr2t7eVrfbjfefnp5KkgzDGDkvah2a1JIEAHfB8+fXvwB8KzNdY7NwHEeO48j3fTmOo3a7Lcuy1O/3ZRhGPHusUCgknp92dtn5+bk+fPgwcz03Nze1ubk58/kAAOTJxcWFLi4uZj7//Pw89bFrHQhFTNOU4ziyLEvValW2bavT6ajf70uSisVi4nlhGKYq/+HDh7eq37Nnz/ScP8MAAEil0WjoxYsXS3mtOxEIRSqViiqVinzfl6R4JtlgMEg8/mqX2Thv3rzRgwcPZq4XrUEAAKR3eHioL7/8cubz3717l7oR404FQpJkWVY8TigKdMa1/KQNhLa2tnT//v251A8AAEx22yElW1tbqY9d68HS40SzwqJ/r44Fir5Puw4JAAC4m+5cIOR5nur1uqRPg6RN07w2OyxqMdrb21t6/QAAQHZkqmts0uDlIAhkWZYcx1G5XJbv+3r69KmePHmig4MDSZ/yChWLxZHlM46Pj7Wzs6MgCOKusGazqWazOXY2GYDxxo37Zz4AgHWUmUAomgIvSS9fvpRlWSqXy3GwEoahBoNBHCwZhqFisahGoyHP82SaZhwoXRatO2bbdjyl3rZtskoDAIDsBELRFPirgczl/WdnZ/H3hUIhdUJE0zTV6XTmUk8AAHB33LkxQgAAAGllpkUoyx4/fqx79+4l7tvf39f+/v6SawQAQL4dHR3p6Ogocd/Hjx9Tl0MglMKrV69GVq8HAACrNakhwvf91Cly6BoDAAC5RSAEAAByi0AIAADkFoEQAADILQIhAACQWwRCAAAgtwiEAABAbpFHKAUSKgIAkC0kVFwiEioCAJAtJFQEAAC4JQIhAACQWwRCAAAgtwiEAABAbhEIAQCA3CIQAgAAuUUgBAAAcotACAAA5BYJFVMgszQAANlCZuklIrM0AADZQmZpAACAWyIQAgAAuUUgBAAAcotACAAA5BaDpQEgZ54/n247cJfRIgQAAHKLQAgAAOQWXWMpkFARAIBsIaHiEpFQEQCAbCGh4i0FQbDqKgAAgBXLVCAUhqFs25Zt26nPcV1XOzs72tjY0M7OjrrdbuJxGxsbI1/VanVe1QYAAGsqM11j3W5XjuPIdV3VarVU57RaLXmep3q9rn6/r1arJcuy5HmeyuVyfFy73VatVlOpVIq3Xd4PAADyKTOBULlcVrlc1sbGRupz3r59K8/z4u+fPHminZ0dNZvNkUCn0+mMHAcAACBlrGtsGt1uV81mc2SbaZoyTXNk/I/rujo9PVW1WlW73V52NQEAQIatbSBULpdlGEbivsvbPc9TGIZyXVf1el3b29tjxxEBAIB8yUzX2LwEQaB6vR5/7ziOHMeR7/tyHEftdluWZanf748NpK46Pz/Xhw8fZq7T5uamNjc3Zz4fAIA8ubi40MXFxcznn5+fpz72TgVCruvKMIzEwdamacpxHFmWpWq1Ktu21el0UpX78OHDW9Xr2bNnes4iPgAApNJoNPTixYulvNadCoQajcaNwU2lUlGlUpHv+6nLffPmjR48eDBzvWgNAgAgvcPDQ3355Zczn//u3bvUjRh3JhCybVvHx8epurssy5pqnNDW1pbu379/m+oBAICUbjukZGtrK/WxaztY+rJo3M80y2Ds7u4usEYAAGAdrH0g5LqupOsJEid1fUVJGAEAQL5lKhAKw3DsviAIVCqVRrq0ut2uGo2GpE+tQtFXvV7X6elpvOhaq9WKz3FdV8ViUZVKZWHvAwAArIfMjBGKprdL0suXL2VZlsrlsgqFgqRPQdJgMIiDJd/3ZVmWJCW27pydnUmSisWiGo2GPM+TaZqyLCt+HQAAkG+ZCYSi6e3jghTTNOPgJvp+OBzeWC5LawDA7MZl/iAjCO6KTHWNAQAALFNmWoSy7PHjx7p3717ivv39fe3v7y+5RsBy8Fc/gKw6OjrS0dFR4r6PHz+mLodAKIVXr15NNTUfAAAs1qSGiGiyVBp0jQEAgNwiEAIAALlFIAQAAHKLQAgAAOQWgRAAAMgtAiEAAJBbBEIAACC3CIQAAEBukVAxBTJLAwCQLWSWXiIySwPIA5ZUwTohszQAAMAtEQgBAIDcIhACAAC5RSAEAAByi0AIAADkFoEQAADILQIhAACQW+QRSoGEigAAZAsJFZeIhIoAMuP96+Tt3//JEisBrB4JFQEAAG6JQAgAAOQWgRAAAMgtxggBYLFNALlFixAAAMgtAiEAAJBbdI0BmM7712N2/GR5dQCAOSEQSoGEigAAZAsJFZeIhIq4896/Tt5Okj4AGUVCRQAAgFsiEAIAALmVqa6xMAzVaDQkSc1mM9U5vu+r0WjIMAyFYSjLslSpVKY+BgAA5E9mAqFutyvHceS6rmq1WqpzgiDQzs6Oer1ePIanVCppMBjEZaQ5BgAA5FNmusbK5bI6nc5U59TrdZXL5ZGBzLZtq16vT3UMAADIp8y0CE0rDEN1u91rXWi7u7uSpHa7rb29vRuPoVUIAKY3blkWlmvBulnbQOj09FSSZBjGyPao5cfzvHjfpGMIhADcae9fX99GWgQgtraBUBAEkqRCoTB2f5pj0jg/P9eHDx+mrmNkc3NTm5ubM58PAECeXFxc6OLiYubzz8/PUx+7toFQv9+XJBWLxcT9YRimOiaNhw8fTl/BS549e6bntBdjHb1/veoaAMihRqOhFy9eLOW11jYQKpVKkqTBYJC43zCMVMek8ebNGz148GD6Sv47WoMAAEjv8PBQX3755cznv3v3LnUjxtoGQlEQM65VxzCMVMeksbW1pfv3709dRwAAML3bDinZ2tpKfWxmps9PK5r5dXWcT/T9zs5OqmMAAEB+rW0gVCgUZJqmPM8b2d7tdiVJe3t7qY4BAAD5lalAaNLg5SAIVCqV4iBGko6Pj9XtdkdafJrNpprNZjxTLM0xALD23r9O/gIwUWbGCPm+L8dxJEkvX76UZVkql8txsBKGoQaDwUiwZJqmer2ebNuWYRgKgkC2bY/kBkpzDAAAyKfMBEKmacpxnDgYStp/dnaWuP2mpTnSHAMAAPInU11jAAAAy5SZFqEse/z4se7du5e4b39/X/v7+0uuEQAA+XZ0dKSjo6PEfR8/fkxdDoFQCq9evRpZvR4AAKzWpIYI3/dTp8ihawwAAOQWLUIAgLlJWlaRpRaRZbQIAQCA3KJFCACwEuNaimhBwjIRCAEAForABllGIATkDA8lAPgWgRBwRxHwAMDNCIRSIKEigDvl/evk7d//yRIrAdwOCRWXiISKAABkCwkVAQAAbokWISBv3r9edQ2Au+fvnl/f9uOEbcgcWoQAAEBu0SIEAPjk/evr2xhAjTuOFiEAAJBbtAgBAPKN8T25RosQAADILVqEUiChIgAswPvXY3b8ZHl1wNoioeISkVARAFaLlepxFQkVAQAAbolACAAA5BaBEAAAyC3GCAHLwhRdAMgcWoQAAEBuEQgBAIDcomsMAJApTInHMtEiBAAAcosWoRTILA0AQLaQWXqJyCwNAEC2kFl6ToIgWHUVAADAimSuRcj3fTUaDRmGoTAMZVmWKpXKxHMsy1K3203c53meyuVy/P3GxsbIftM01ev1bl9xYEUYWAoAs8tUIBQEgXZ2dtTr9eKuqFKppMFgoFqtNvacIAjUbDZVKBTi7f1+X61WayQIarfbqtVqKpVK8bbL+wEA62XsYqz/MWEHCUyRIFOBUL1eV7lcHhmPY9u26vX62ECo2+2q1+uNBEGSrgVBktTpdOR53tzrDQDIvvFB01KrgYzJzBihMAzV7XZlWdbI9t3dXUmfWnOS1Gq1a0GQJJ2cnKharcbfu66r09NTVavVsWUBAFJ6/zr5C1gzmQmETk9PJUmGYYxsj1qHpmnJCcNQvu9rb28v3uZ5nsIwlOu6qtfr2t7eHjuuCAAA5ENmusai2VtJrTuX96fx8uVLmaY5UpbjOHIcR77vy3EctdttWZalfr9/Lfi66vz8XB8+fEj9+ldtbm5qc3Nz5vMBAMiTi4sLXVxczHz++fl56mMzEwj1+31JUrFYTNwfhmHqsjqdjp48eZK4zzRNOY4jy7JUrVZl27Y6nc7E8h4+fJj6tZM8e/ZMz5naAwBAKo1GQy9evFjKa2UmEIpmcg0Gg8T9N7XaRKKxRo7jTDyuUqmoUqnI9/0by3zz5o0ePHiQ6vWT0BoEAEB6h4eH+vLLL2c+/927d6kbMTITCEWBzriWn7SBULfblWEYqY6flH/osq2tLd2/fz/V6wMAgNu57ZCSra2t1MdmJhCKZoddHQsUfZ82VfbJycmNCRiTXhcAcHc8/08/ub7x+0uvBtZAZgKhQqEg0zTleZ4ODg7i7VGLzeUZYJO4rps6U7TnearX69NXFgCQ7P3r69u+/5PllwGklJlASJKOj4+1s7OjIAjirq1mszmSNToIAlmWJcdxriVMdF03Dqgu831fT58+1ZMnT+Igy3VdFYvFqVqPgFVjzD0AzFemAqFo3S/btmUYhoIgkG3bI1mlwzDUYDBIHEt0cnKS2HJkGIaKxaIajYY8z5NpmnEwBQAA8itTgZD0KRiaNJ3dNE2dnZ0l7ht3XqFQYGkNAABwTWYySwMAACxb5lqEsujx48e6d+9e4r79/X3t7+8vuUZYmL97nrydVasBIFOOjo50dHSUuO/jx4+pyyEQSuHVq1fXBmADAIDVmdQQ4ft+6rQ7BELItpy20DA7DLji/etV1wB3FGOEAABAbtEiBNxV71+vuga4C96/XnUNgIWiRQgAAOQWgRAAAMgtAiEAAJBbBEIAACC3GCydAgkVAQDIFhIqLhEJFQEAyBYSKgLLlJTY8Y4ndQRwx/F7TRJjhAAAQI7RIgQAyLXn/+kn17f9ePn1wGoQCOHuWMN1ycauKfb+dfpCvv+TW9cDwBLN43fVuDJuW24O0TUGAAByixYhrKdp/hpalDVsgQJy7f3rVdcAGUQgBMzZuO6u5/9xqdUAcAtju63HHc/ne23RNQYAAHKLFqEUyCwNAEC2kFl6icgsDQA58/518nZmaWbGvDJL0zUGAAByixYhAAAWgIkT64FACFiSpOy1+v4cCn7/eg6FALizspBuJMPoGgMAALlFixAAYLHev151DYCxaBECAAC5RYsQsErvX6+6BgCm8f71qmuAOSMQSoGEigAAZAsJFZeIhIoAAGTLvBIqEgjh7mOVeADAGHd6sHQQBKuuAgAAyLDMtQj5vq9GoyHDMBSGoSzLUqVSSXXuxsbGyPemaarX682lbNxBi0oy9v71YsoFAMxdpgKhIAi0s7OjXq8Xj8kplUoaDAaq1WoTz22326rVaiqVSvG2crk8l7IBAJhkYZnjsXCZCoTq9brK5fLIwGTbtlWv128MVjqdjjzPW0jZAADgbsrMGKEwDNXtdmVZ1sj23d1dSZ9afMZxXVenp6eqVquJx92mbAAAcHdlpkXo9PRUkmQYxsj2qAXH87yxLTee5ykMQ7muK9d1Zdu2Op1O3DV2m7Il6fz8XB8+fJjhXX2yubmpzc3Nmc8HACBPLi4udHFxMfP55+fnqY/NTCAUzfAqFAoT9ydxHEeO48j3fTmOo3a7Lcuy1O/3ZRjGrcqWpIcPH978BiZ49uyZnj9/fqsyAADIi0ajoRcvXizltTITCPX7fUlSsVhM3B+G4Y1lmKYpx3FkWZaq1WrcMnTbst+8eaMHDx7c+Prj0BoEAEB6h4eH+vLLL2c+/927d6kbMTITCEWzvQaDQeL+q91ak1QqFVUqFfm+P5eyt7a2dP/+/dSvj/WVOPND0vOfvV5mNQDcYWN/z/x4ufXIstsOKdna2kp9bGYCoSgYGdc6M00gJEmWZanb7S6kbEAa/8sMALA+MhMIRTO4ro7Xib5Pu2ZIUpmLKBspsLQFACDjMjN9vlAoyDTNa7mAoladvb29qcrzPE/1en0hZQMAgLshMy1CknR8fKydnR0FQRB3VzWbTTWbzXjGVxAEsixLjuOoXC7L9309ffpUT5480cHBgaRPeYWKxeLI8hlpygYAYG7ev57q8KTJxUw4XrxMBULR2mC2bcfT3m3bHsnxE4ahBoNBPN7HMAwVi0U1Gg15nifTNONAadqygXEYDwQAd1OmAiHpU8DS6XQm7j87O4u/LxQKE5fWmKZsAACQL5kLhJADSYOoGUANANeNm3SybHd48guBUAqPHz/WvXv3Evft7+9rf39/yTUCACDfjo6OdHR0lLjv48ePqcshEErh1atXI6vWYwGy8lcPAKzK+9errsFamdQQ4ft+6tQ4mZk+DwAAsGy0COH2aM0BgIVg2Z/Fo0UIAADkFi1CuPP4iwoAUsphCz8tQgAAILdoEQIAYM3Q0j0/BEJYS0m/BPgFAACYFoFQCiRUXA+sBwYA+UFCxSW6MwkV73CKdABAvswroSKBEHKLFiQAALPGAABAbtEihEyj1QYAsEi0CAEAgNyiRQjJg6gZQA0AyAFahAAAQG4RCAEAgNyiaywFEioCAJAtJFRcojuTUBEAkDt3dV2yeSVUpGsMAADkFi1CAADcEeRemx6BEDKBDy8AYBXoGgMAALlFIAQAAHKLQAgAAOQWY4QwnaTlOKbEeCAAQFYQCKVAQkUAALKFhIpLREJFAACyhYSKAAAAt5T7QCgIglVXAQAArEjmusZ831ej0ZBhGArDUJZlqVKp3Hie67pqNBryfV+maarZbKpcLl87bmNjY+R70zTV6/XmVv87Yw6DogEA2ZU0cWXd1x+bRaYCoSAItLOzo16vF4/JKZVKGgwGqtVqY89rtVryPE/1el39fl+tVkuWZcnzvJFgqN1uq1arqVQqxduSgiUAAJAPmQqE6vW6yuXyyMBk27ZVr9cnBkJv376V53nx90+ePNHOzs61VqFOpzNyHAAAyLfMBEJhGKrb7arZbI5s393dlfRta85VSeeYpinTNEfG/7iuq9PTU1WrVVmWNTGwwnTICwQAWFeZCYROT08lSYZhjGyPWoc8z0sMXiZ1bV0uy/M8hWEo13Xluq5s21an06FrDMizcWPhfjxmO4BRSZ+hNfv8ZCYQilpvCoXCxP3TlFev1+PvHceR4zjyfV+O46jdbsuyLPX7/WvB11Xn5+f68OHDVK9/2ebmpjY3N2c+HwCAPLm4uNDFxcXM55+fn6c+NjOBUL/flyQVi8XE/WEYpi7LdV0ZhpHYgmSaphzHkWVZqlarccvQJA8fPkz92kmePXum58+f36oMAADyotFo6MWLF0t5rcwEQtFMrsFgkLj/plabyxqNxo3BTaVSUaVSke/7N5b35s0bPXjwIPXrX0VrEAAA6R0eHurLL7+c+fx3796lbsTITCAUBTrjWn7SBkK2bev4+DjV8ZZlqdvt3njc1taW7t+/n+r1AQDA7dx2SMnW1lbqYzMTCEWzw66OBYq+T7NmSDTuZ5p1waLXxahxM8HymGwLAHB3ZWaJjUKhINM0r+X5iVps9vb2Jp7vuq6k67PIJnV9RUkYAQBAPmUmEJKk4+NjdbvdkVahZrOpZrMZzyYLgkClUmmkS6vb7arRaEj61CoUfdXrdZ2ensar0LZarfgc13VVLBZTLd8BAADupsx0jUnfrvtl27YMw1AQBLJte2T2VxiGGgwG8Vgi3/dlWZYkJbbunJ2dSfo0G63RaMjzPJmmKcuy5DjO4t8UAADIrEwFQtKnYGjSjC/TNOPgJvp+OBzeWC5La8wHWaQBAHdJprrGAAAAlilzLUJZ9PjxY927dy9x3/7+vvb395dcIwCLlJT/lJyoyIN1mjF8dHSko6OjxH0fP35MXQ6BUAqvXr2aako+gPwYFyAROAGLNakhIpoklQZdYwAAILdoEVp3d2DlXyBz3r++vu3vErZJ0vufjClk3HYAWUKLEAAAyC1ahABgWZJacCVacZF56zSIeloEQiA3EHJr2T/7Yx8mP15qNQBcQiB0F437qxPIs8TPxU9Sn77QoImWImBlCIQA5MLSW3+eL/XlAMyIQCgFEioCAJAtJFRcIhIqAhlEdxKQayRUBAAAuCVahNbFHAZAMzsMuTD2s/KTJVYCwLogEAKAjGLANbB4BEIAMi8padvzny29GtN5/zobZQALlNTTsG55sRgjBAAAcosWIQCZQVcQgGUjELqDGBSNTEkavMwUd+DuWrPUFgRCANbSXVoEkj9egNUhEEqBzNJACvNY4+7969uXASAXyCy9RIvILH1xcaFGo6HDw0Ntbm7OtWws3r/97rf6P/6v/1X//X/3P+kP/+A7q64OLknbusI9XH/cw/V3m2chmaXX3MXFhV68eKGLi4tVVwUz+N3v/lVv3v0v+t3v/nXVVcGMuIfrj3u4/rLwLCQQAgAAuUXXWNZMOc6CQZZYR0yTB5AVtAgBAIDcIhACAAC5RdcYgOV7/3rVNQAASbQIAQCAHKNFKAUSKgKzY0A/gEUgoeISLSKh4rSmeZj8n//3/6b/8N/+jwupx6LKXsc6L9I6Xo//4X8+W7s6LxKflcWXu0jreJ0XWfY05Y5d/ubHc6yQSKiICd7+P//72pW9jnVepHW8HutY50XiOi++3EVax+u8yLLX8R6mlbkWId/31Wg0ZBiGwjCUZVmqVCpzOW/WsgEAwN2UqUAoCALt7Oyo1+vFXVGlUkmDwUC1Wu1W581aNgAAuLsy1TVWr9dVLpdHxuPYtq16vX7r82YtGwAAzMHfPb/+9Z8bK62SlKEWoTAM1e121Ww2R7bv7u5KktrtdmLLTZrz9vb2Zip7FZhhAwDA8mSmRej09FSSZBjGyPaoBcfzvJnPm7XspfjPjdHoGAAALE1mWoSCIJAkFQqFiftnOW/WsqM8BL7v6/z8PPGYNL7zne/oO9/5zsi2qLx3/+9/0da9b/f986//cebXifzbv13MpZxllr1udf7tv3762fgv3/x/+s5/nZxj6jbW7XosstxFlb2u93DdrvMiy13kPVzH67zIsudRbr3531zbFt3Dd+/eaWtr69vtv/2tfvvb3878Wv/4j5/qmiqf0DAjDg4OhpKGvV7v2j5JQ8MwZj5v1rJ/+ctfDiXxxRdffPHFF19r+PXLX/7yxvgjMy1CpVJJkjQYDBL3X+3Wmua8Wcv+4osv9Nd//df64z/+Y/3RH/3R+MrfIKlFCAAAJLtti9C//Mu/6J//+Z/1xRdf3HhsZgKhKBgJw3Di/lnOm7Xs733ve/rTP/3TMTUGAADrLjODpaMZXFfH60Tfj0uVnea8WcsGAAB3W2YCoUKhINM0r83g6na7kqS9vb2Zz5u1bAAAcLdlJhCSpOPjY3W73ZGWm2azqWazGc/4CoJApVIpDmLSnpfmGGCZxs1WBDBffNYwyca/z5zKjMvrgQVBIMuyRpId+r6vR48e6fj4eGSdsJvOS3vMMoRhqEbjUzbNq0kex2GdtGy4zX3Y2NgY+d40TfV6vUVUM/cWuWYhloPP2npbq+fcjfPKMFee5w0rlcpQ0rBWq6U6p9/vD6XR6f+GYQwdx1lUNZHgNvfBcZxhrVYbNpvN+CspnQNub9b7xOcsO/isrbd1e84RCK3IND8g5XJ5WC6XR7Y5jjMkjl2u29yHq+dhcWa9T3zOsoPP2t2wLs+5TI0RwnXRWmqWZY1sv7xOGhbvNvfBdV2dnp6qWq1yvxZs1vvE5yw7+Kzlz6o/fwRCGZfpddJy5Db3wfM8hWEo13VVr9e1vb09Mtgf87PINQuxHHzW8mfVnz8CoYybdZ00zNdt7oPjOBoOh+r1eqrVavEgQO7d/C1yzUIsB5+1/Fn1549AKOP6/b4kqVgsJu4fly0b8zWP+2CaphzHUafTkSTZtj23+uGTWe8Tn7Ps4LOWP6v+/BEIZdys66RhvuZ5HyqViiqVinzfn0vd8K1FrlmI5eCzlj+r/vxlZq2xdeH7fuq/LgzDkOM4t3q9WddJQ7JZ79+874NlWYxdWIBFrlmI5eCzlj+r/vwRCE0paamORWKdtPma9f4t4j5EZWJ+FrlmIZaDz1r+rPrzR9dYxrFOWjbM+z54nqd6vT63+uGTRa5ZiOXgs5Y/K//8LTxTEa45Ozsbm2iq3+8PDcMYep4Xb+v1ekNJw36/H28zDGPYbDaXUl98kuY+XL1/vV5vaJrmyDGdTid1kjFMb5b7lPY8LAeftfW3Ts85usaWzPf9eNzJy5cvZVmWyuVyPG0wDEMNBoORvtJonRzbtuN10mzbXsk6aXmW5j5cvX+GYahYLKrRaMjzPJmmKcuybj12DOPNcp/Snofl4LO23tbtOZe5RVcBAACWhTFCAAAgtwiEAABAbhEIAQCA3CIQAgAAuUUgBAAAcotACAAA5BaBEAAAyC0CIQDIkKvrLQFZdZuf1Sz9nBMIAUBGtFot+b6/6moAqQRBoFarNdO51Wp17Grzy0YgBAAZ4LquvvnmG1UqlWv7Wq2Wtre3tbGxoY2NDVmWFX+VSqV4Oz7hei1HuVyWJLXb7anO831fhmHES25EVnbfFr6aGQBgorOzs6FpmhOPqdVqQ0nDg4ODa/uiRSzxLa7X8pimOTw7O0t9fK1WG1lw9eq+Zd83WoQAYMVs21a9Xp94zOnpqSTJsqxr+wzDiP86xydcr+Wp1+uybTv18d1ud+z1X8V9Y9FVAFix7e1tnZ2dTTwm6hIY9ys7DMNrXQ15xvVaru3tbX399dc3XlPXdeV5Xrw6/VWruG+0CAHACrmuK8MwJh7T7XYl6dpfw67rxv/nof4trtfyGYahly9f3njcycnJ2NbPVd03AiEAWCHP825s7u90OpJGuwvCMNTJyclC67auuF7LVy6X5XnexGPCMFQQBDJNM3H/qu4bgRAArNDp6alKpdLEY6K/lE9OTrSzs6NSqaTt7W396Ec/WkYV1w7Xa/lKpdKNuYFevnypJ0+ejN2/qvv2hwstHQAwURiGKhaLE/cHQaBCoaBerxdve/ToEQN+E9yl6+W6rt6+fatms7nqqtyoWCzeGAg5jqOvvvoqcd8s961er6tUKumbb77Rj370o8TUE2nQIgQAKzQYDCaOe4jGXVx+GBQKBZXL5WtdDK7ramNjQ9vb2/Ff19KnB0q1WtX29vZIwkbXdeO8LdHMn+jhcnUcR1T2xsbGxCR6YRjKtu34q1qtTnxAhmEY//Wf9mtS0slprlfSdbNtO85dc7nel9//5TEr0qe8ONVqVdVqNX7PlmWN5NcZd/3a7fa1exaGoVqt1tySDo577TAMVa/Xtb29Hb+ny/e/Wq3G+Xyi48aN7zEMY2JdgyBQsVgc+7M+7X2rVqsqFAo6ODhQs9lUo9EY+Zmfytwn5AMAUisUCmNzqgyHw2GlUhlKGjqOM7J9XN4W0zSH5XL52vZxuVsMw7h2/NnZ2bXXi+paq9XG1tVxnKFpmsN+vx9v6/V6Q0lT5Zm5jWmvV0RXctcYhnEtZ03S+z84OLj2nofDT/fh6vVOOv/s7GwoadhsNq/VyTTNidc74nnesNfrTTxGUmJZnU5n5LUvH+M4zsi963Q6Y39WPc8bFgqFsa9/cHAw7HQ6Y/dPc9/6/f5Q0sg1bzabiT/3aRAIAcAKGYYx8QFRKBRuDCQuP5xqtdq1B1K/3x9WKpVr5016CF99vejhM66u0UPzakAwHF4PMhZp2usVfS9pZHv0YI4kvf+Dg4Ox77nT6YzUYdz1i147KZApl8upAqFJAcpw+G0wmnRMrVYbqf/l/5fL5ZFgcNI17XQ6E5Md3pQIcZr71ul0hlfbcaLrOEvATdcYAKyQYRhju46CIFAYhonLEUTa7fbI+Ts7O9e6KGzb1vHx8bVzo66EaGxFGIbxtquvF3WdJI3DCIJA9XpdtVptbCqAZSyyOcv1khTPdoq6ZaLrcHBwEB9z9f37vq9Wq6Vms5n4niuVykgdxl2/TqejQqEwtttuHqJZV0ljbYIgGKn/5f93u92R+k7qwh0MBmPv/aQEilEdprlvb9++vXZcNM5uMBiMfZ1xGCwNACtkmqbevn2buC96eCY9YKKxOO12eyQZY3Ss7/syTVOu68qyrMQHTPSAdBwnfvhHA1Wv8jxv7MM6yiqcNKg3Gs8zaUD4vMxyvaLzCoWCbNuOH8rNZlO1Wi0+5ur7j97z5WBpkijYqlarI9tvChLm4WpAE5k0lT0KiJMyPCfp9Xpjy3IcR4eHh2PPnfa+TZpgcDWwS2XqNiQAwNz0er3EboNmszmUFH9FY39M0xwahhFvv9rlFXV3RV0wSV1ikctjVs7OziZ2w2hMF1q0b1zXR/Q+JnXdzMNtr5fjOBO7qa6+/0KhcOP6cJPOHw5v7m6cR9fY5fd3VbPZHDu2KOr2S8swjLF1mNQtNst9azab17p/o+6/pG7Km9AiBAArFP0VHbXgRA4ODlK3NlxWKBRUKBQUBEHcdZPE932FYRj/xV8oFKbO+Jv0Pq5qNBoql8sLb/WY9XpFs5X29vbia+c4zsgSEGne/yTjzp+13Kv36fT0VMViMU5IGHEcJ167K+k13r59O/aaTdNSFXVZJR3fbrcnrqM3y31LmqEWdYlN3RokusYAYOVs27728L2N3d1dnZyc6MmTJxPHbUijY1bGBWWTxrFE3UpJXRXRVO2rD+gs8TxvZGxKrVZTq9UauRdJ7393dzcOMq66uh7WuOvX6XQmjosZ5+rPSXQPxo0Bkq4HCJO6kMIwlO/7qX8em83m2EVXJ+UOmlV0HS+/h6s/s9NgsDQArFitVlMQBHMbUBz9xTzpL+2Tk5PEB0c0Tuayca0D1WpVpmnq8PDwWg4X13V1cnKiXq+X6XW9rr63qPXicq6gpPffbDbjfD9Xy7u65ta46zdu7M48Ra97Na9UvV4fO24nKafPONHP7eXxVJf3TcodNCvDMFSpVEbu0cnJycyJJ2kRAoAM6HQ6qlarN67XlMbOzs61QbmXtVqteBBz9Jd8EATyfV+DwWDkgRIFRoPBIA4SBoNBfL5hGHHAVa1W4yCsVCqNHXidFfV6Pc5oHLUuGIYh0zT19OlTGYahk5OTOOPx5RYI0zTV7/dVr9d1cnISP/Cj2XOR6PoVCoW41SIIgvi6+76f2Drjuq663a4Mw7jVgGrDMOR5Xvx6hmGoWCzKcZzEAMV13fhY13VVq9UmBjL1en1sy5HjOBO7xW6j0+moXq+r1Wrpm2++Ub1en/kabQyHY9a6BwAsVRAEcl13prEuyK9JXWOL1Gq1VKlUxnaxVavVTHeLRgiEAABYY1fHJGE6BEIAACC3GCwNAAByi0AIAADkFoEQAADILQIhAACQWwRCAAAgtwiEAABAbhEIAQCA3CIQAgAAufX/Axrb/ZEEkTWNAAAAAElFTkSuQmCC",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -954,40 +961,35 @@
    ],
    "source": [
     "# energyspektren angucken von velo und rich\n",
-    "diff_found = (\n",
-    "    ak.to_numpy(\n",
-    "        energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
-    "            \"velo\"\n",
-    "        ]\n",
-    "    )\n",
-    "    - ak.to_numpy(\n",
-    "        energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
-    "            \"rich\"\n",
-    "        ]\n",
-    "    )\n",
-    ") / ak.to_numpy(\n",
+    "\n",
+    "velo_found = ak.to_numpy(\n",
+    "    energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\"velo\"]\n",
+    ")\n",
+    "rich_found = ak.to_numpy(\n",
+    "    energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\"rich\"]\n",
+    ")\n",
+    "energy_found = ak.to_numpy(\n",
     "    energy_emissions[(~energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
     "        \"energy\"\n",
     "    ]\n",
     ")\n",
-    "diff_lost = (\n",
-    "    ak.to_numpy(\n",
-    "        energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
-    "            \"velo\"\n",
-    "        ]\n",
-    "    )\n",
-    "    - ak.to_numpy(\n",
-    "        energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
-    "            \"rich\"\n",
-    "        ]\n",
-    "    )\n",
-    ") / ak.to_numpy(\n",
+    "\n",
+    "velo_lost = ak.to_numpy(\n",
+    "    energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\"velo\"]\n",
+    ")\n",
+    "rich_lost = ak.to_numpy(\n",
+    "    energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\"rich\"]\n",
+    ")\n",
+    "energy_lost = ak.to_numpy(\n",
     "    energy_emissions[(energy_emissions.lost) & (energy_emissions.quality == 1)][\n",
     "        \"energy\"\n",
     "    ]\n",
     ")\n",
     "\n",
-    "xlim = 1\n",
+    "diff_found = velo_found - rich_found  # / energy_found\n",
+    "diff_lost = velo_lost - rich_lost  # / energy_lost\n",
+    "\n",
+    "xlim = 20000\n",
     "nbins = 80\n",
     "\n",
     "plt.hist(\n",
@@ -1012,8 +1014,8 @@
     ")\n",
     "# plt.xlim(-20000, 20000)\n",
     "# plt.yscale(\"log\")\n",
-    "plt.title(\"emitted energy difference ratio\")\n",
-    "plt.xlabel(r\"$(E_{VELO} - E_{RICH1+UT})/E_0$\")\n",
+    "plt.title(\"emitted energy difference\")\n",
+    "plt.xlabel(r\"$(E_{VELO} - E_{RICH1+UT})$ [MeV]\")\n",
     "plt.ylabel(\"a.u.\")\n",
     "plt.legend()\n",
     "plt.show()"
@@ -1021,12 +1023,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 139,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1039,11 +1062,9 @@
     "# number of brem vtx with E>x*E_0\n",
     "\n",
     "number_velo = ak.to_numpy(\n",
-    "    energy_emissions[energy_emissions.quality == 1][\"velo_length\"]\n",
-    ")\n",
+    "    energy_emissions[energy_emissions.quality == 1][\"velo_length\"])\n",
     "number_rich = ak.to_numpy(\n",
-    "    energy_emissions[energy_emissions.quality == 1][\"rich_length\"]\n",
-    ")\n",
+    "    energy_emissions[energy_emissions.quality == 1][\"rich_length\"])\n",
     "\n",
     "plt.hist(\n",
     "    number_velo,\n",
@@ -1082,7 +1103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 140,
    "metadata": {},
    "outputs": [
     {
@@ -1091,7 +1112,7 @@
        "' \\nphoton cut = x*E_0\\neffs, all photons included: x=0\\nfound in velo/(found + lost in velo)\\nVELO energy emission, eff:  0.8446167611094543\\nRICH1+UT energy emission, eff:  0.7961586121437423\\neff von e die nicht strahlen:  0.7954674220963173\\n'"
       ]
      },
-     "execution_count": 20,
+     "execution_count": 140,
      "metadata": {},
      "output_type": "execute_result"
     }