diff --git a/aoi_cache_experiment_eval.ipynb b/aoi_cache_experiment_eval.ipynb
index dbe4dde..9e1f54a 100644
--- a/aoi_cache_experiment_eval.ipynb
+++ b/aoi_cache_experiment_eval.ipynb
@@ -65,17 +65,17 @@
      "data": {
       "text/plain": [
        "[{'ttl': '0.5s',\n",
-       "  'data': {'hit_rate': 0.2499719022630842, 'avg_age': 0.2408566463773598}},\n",
+       "  'data': {'hit_rate': 0.458669533255314, 'avg_age': 0.2405818161600988}},\n",
        " {'ttl': '1.0s',\n",
-       "  'data': {'hit_rate': 0.3881665606779017, 'avg_age': 0.4920888885617573}},\n",
+       "  'data': {'hit_rate': 0.6137075818807132, 'avg_age': 0.4914356220831488}},\n",
        " {'ttl': '2.0s',\n",
-       "  'data': {'hit_rate': 0.5381173912695726, 'avg_age': 0.966399936751214}},\n",
+       "  'data': {'hit_rate': 0.7510045829957603, 'avg_age': 1.0028764694071644}},\n",
        " {'ttl': '3.0s',\n",
-       "  'data': {'hit_rate': 0.6224679450442043, 'avg_age': 1.490042165885063}},\n",
+       "  'data': {'hit_rate': 0.8151181771596068, 'avg_age': 1.486159537458237}},\n",
        " {'ttl': '4.0s',\n",
-       "  'data': {'hit_rate': 0.6783420943812974, 'avg_age': 1.9802754170895376}},\n",
+       "  'data': {'hit_rate': 0.8521008724556234, 'avg_age': 1.9920411130528224}},\n",
        " {'ttl': '5.0s',\n",
-       "  'data': {'hit_rate': 0.7175225869007572, 'avg_age': 2.4791552890507336}}]"
+       "  'data': {'hit_rate': 0.877309770620863, 'avg_age': 2.4590330715633857}}]"
       ]
      },
      "execution_count": 4,
@@ -102,7 +102,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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y8d/Xx6fo3btzfh0SYpFXbsIqflhHwdx9bBa3NpeGbh8fH3Xo0EErVqzQsGHDJEk2m00rVqzQuHHjinztZ599poyMDN1zzz1lUCkAAAAAV7l8+eqbjh0/Lp08qRLd/1u1avGOxKpeXUUu8QaK4vLl5RMmTNCoUaPUsWNHde7cWfHx8UpPT8/dzfy+++5TWFiYpkyZ4vC6GTNmaNiwYapZs6YrygYAAADKLatVSky0aM2aMAUGWhQTU/ZnIBuGdP781YN0crLZr7gsFikk5OpHYtWpI5WDLZ5QAbg8dMfFxenUqVN67rnnlJycrHbt2umbb77J3Vzt8OHD8rjicLg9e/Zo3bp1Wr58uStKBgAAAMqthQtzzkL2ktRRU6eaZyG//nrpnIWcnW3OOBe2rDvv8zyHDF2Vr2/xlnjXrq08S7wB13OL4Thu3LhCl5OvXr06X1vTpk1lGIaTqwIAAAAqloULpeHDzVnmvJKSzPYFCwoP3pcuFe9s6VOnSrbEu1q1qwfpunXNpeAs8UZ55BahGwAAAIBzWa3mDHdBc1c5bWPGSHv36vddvB2DdTE3apYkeXjo9527i17mXaeO5O9fOt8PcFeEbgAAAKACu3RJOnhQWrxYOnq06L5nz0pPP134dT+/q286lrPEu6zvEQfcFaEbAAAAKOfOn5f27zcf+/Y5/jopqWTv1aOH1K1bwcE6OJgl3kBJEboBAAAAN2cY5lLvK0N1zvOzZ4t+fXCwuaP3vn1X/6yXXpKio0ulbAAidAMAAABuITtbOny44GC9f7908WLRrw8NlRo3lpo0Mf+Z82jSRKpZ09zcLDLSnPku6L5ui8XcxbxXL6d8PaDSInQDAAAAZeTSJenAgYKD9W+/mcG7MB4eUv36BQfrxo2lKlWK/mxPT/NYsOHDzYCdN3jnLBmPj+debKC0EboBAACAUnTuXMH3V+/ff/X7q319pUaNCg7WkZGSj8/11RYbax4LZp7TbW8PDzcDd2mc0w3AEaEbAAAAKAHDMI/QKmzjsnPnin591aqOS7/zBuuwMHNG25liY6WhQ6VVq7K1dOk2DR7cTjExXsxwA05C6AYAAACukJ0tHTpU+Iz1pUtFv75OnYKDdZMmUo0art8B3NNTiooylJ6epKiotgRuwIkI3QAAAKiULl4s+v5qq7Xw13p4SA0aFBysGzW6+v3VACoPQjcAAAAqrLNnC5+tPnas6Nf6+RV+f3WDBtd/fzWAyoHQDQAAgHLLZiv8/ur9+4t3f3VOoL4yWNer5/z7qwFUfIRuAAAAuLWsrMLvrz5w4Or3V9etW/jGZe5wfzWAio3QDQAAAJdLT7ffX31lsD50qOj7qz09i76/OjCw7L4HAFyJ0A0AAACnMwzH+6uvDNbHjxf9ej8/xxnqvMG6QQPJ27tsvgcAlBShGwAAAKXCZjM3Jyvs/urz54t+fbVq+Y/Xyvl13brcXw2gfCJ0AwAAoNiysszjtAq7v/ry5aJfX69e0fdXA0BFQ+gGAACAg/T0wpeBHz589furIyMLv786IKDMvgYAuAVCNwAAQCVjGNKZM4UH6+Tkol/v71/4/dX163N/NQDkRegGAACogGw2KSmp8GCdklL062vUKDxY163LMVsAUFyEbgAAACexWqXERIvWrAlTYKBFMTHm8uvSkpnpeH913mB94ICUkVH068PCCg/W1auXXp0AUJkRugEAAJxg4UJp/Hjp6FEvSR01daoUHi69/roUG1v890lLK/r+aput8Nd6eTneX503WDdsyP3VAFAWCN0AAAClbOFCafhw897pvJKSzPYFC+zBO+f+6rxhOu+vT5wo+rMCAoq+v9qL/9sDAJfixzAAAEApslrNGe4rA7dkb7v/fmnOHHMJ+P79Umpq0e9Zo0bh51fXqcP91QDgzgjdAAAApWj1auno0aL7XLggff65Y1t4eOEz1tWqOataAICzEboBAACukWGYM9UbN0qbNpmPjRuL99p77pHuvNN+f7W/v3NrBQC4BqEbAACgmI4dswfrTZukzZulc+eu7b3++EcpOrpUywMAuCFCNwAAQAHOnTNDdd4Z7GPH8vfz9ZXatZM6dTIfHTpIgwaZm6YVdF+3xWIuJe/Vy+lfAQDgBgjdAACg0rt4UfrxR3vA3rRJ2rs3fz8PD6llS3vA7tRJat1a8vFx7Pf66+Yu5RaLY/DO2fAsPr50z+sGALgvQjcAAKhUsrKkXbsc78PeudPcdfxKjRpJnTvbA3b79lKVKlf/jNhY81gw85xue3t4uBm4S3JONwCgfHN56J42bZpeeeUVJScnq23btnrzzTfVuXPnQvufP39e//jHP7Rw4UKdPXtWDRo0UHx8vG6++eYyrBoAAJQHNpt55nXeJeI//ihdvpy/b5069nDdubPUsaNUs+a1f3ZsrDR0qLRqVbaWLt2mwYPbKSbGixluAKhkXBq6582bpwkTJmj69Onq0qWL4uPjNXDgQO3Zs0chISH5+mdmZqp///4KCQnRggULFBYWpkOHDqka52gAAFDpGYZ5H3XeJeKbNkkpKfn7Vq1qhuq8ITssrPTPu/b0lKKiDKWnJykqqi2BGwAqIZeG7qlTp2rMmDEaPXq0JGn69OlasmSJPvjgAz399NP5+n/wwQc6e/as1q9fL29vb0lSZGRkWZYMAADcxNmz+QP28eP5+/n6Sjfd5Hgf9g03mPdnAwDgbC4L3ZmZmdqyZYsmTpyY2+bh4aF+/fppw4YNBb7myy+/VLdu3TR27Fh98cUXql27tu6++2499dRT8izkr44zMjKUkZGR+zw1NVWSlJWVpaysrFL8RqUrpzZ3rhGVE2MT7oqxWbGlp0vbtlm0ebNFmzZZtGWLRfv355+W9vQ01KKF1KmToY4dberQwVCrVtLvf1efy2ot+B5uZ2Bswl0xNuGuysvYLG59Lgvdp0+fltVqVWhoqEN7aGiofvnllwJfc+DAAa1cuVIjR47U119/rX379ukvf/mLsrKyNGnSpAJfM2XKFE2ePDlf+/LlyxUQEHD9X8TJEhISXF0CUCDGJtwVY7P8y8626NChYO3bV01791bX3r3VdORIsGy2/CG7bt00NWlyXjfccE433HBejRqlyNfXnqaPHy949tsVGJtwV4xNuCt3H5sXL14sVj+Xb6RWEjabTSEhIXr33Xfl6empDh06KCkpSa+88kqhoXvixImaMGFC7vPU1FRFRERowIABCg4OLqvSSywrK0sJCQnq379/7lJ6wB0wNuGuGJvlk80m/fqrtHmzOXu9ebNF27ZZlJGRP2DXq2eoQwdDHTuajw4dDNWo4Ssp9PeHe2Jswl0xNuGuysvYzFlFfTUuC921atWSp6enTpw44dB+4sQJ1alTp8DX1K1bV97e3g5LyZs3b67k5GRlZmbK58pDMiX5+vrK19c3X7u3t7db/wvMUV7qROXD2IS7Ymy6L8Mwj8/Ke1TX5s1SQf/PUq2a4z3YnTpJYWEWSaW801kZYmzCXTE24a7cfWwWtzaXhW4fHx916NBBK1as0LBhwySZM9krVqzQuHHjCnxNjx49NGfOHNlsNnn8vvvJr7/+qrp16xYYuAEAgOucOWM/pisnZF/xd+2SJH9/8/zrvOdhN2lS+juJAwDgCi5dXj5hwgSNGjVKHTt2VOfOnRUfH6/09PTc3czvu+8+hYWFacqUKZKkhx9+WG+99ZbGjx+vRx55RHv37tW//vUvPfroo678GgAAVHppadLWrY7nYR88mL+fp6fUurXjUV0tW0pe5eqGNwAAis+lf8TFxcXp1KlTeu6555ScnKx27drpm2++yd1c7fDhw7kz2pIUERGhZcuW6fHHH1ebNm0UFham8ePH66mnnnLVVwAAoNLJzJR++snxqK7du837s690442OS8TbtZPKwT6mAACUGpf/vfK4ceMKXU6+evXqfG3dunXT999/7+SqAACAZAbpPXscl4hv22YG7yuFhTkuEe/Y0bw3GwCAyszloRsAALgHw5AOH3a8D3vLFunChfx9q1e3Lw/PCdl165Z9zQAAuDtCNwAAldSpU45LxDduNNuuFBAg3XSTY8hu1IiNzgAAKA5CNwAAlcCFC+asdd6Q/dtv+ft5eUlt2jhudNa8ORudAQBwrfgjFACACiYjw9zoLO992D//bC4fv1LTpo5LxNu1k/z8yrxkAAAqLEI3AADlmNUq/fKL4xLx7dulrKz8fSMiHJeId+ggVa1a9jUDAFCZELoBACgnDMNcEp53ifiWLeYZ2VeqWdNxiXinTtLvJ3ICAIAyROgGAMBNnTjhGLA3bZJOn87fLzDQnLXOex52w4ZsdAYAgDsgdAMA4AZSU+0bneXci334cP5+3t7mRmd578Nu3lzy9Cz7mgEAwNURugEAKGOXL5v3Xee9D3vPnvwbnVksUrNmjkvE27RhozMAAMoTQjcAAE5ktUq7dzsuEf/pp4I3OmvQwPE+7JtukoKDy75mAABQegjdAACUEsOQDh50PKpr61YpPT1/39q1He/B7tRJCgkp+5oBAIBzEboBALhGycmO92Bv3iydOZO/X5Uq5kZnee/DbtCAjc4AAKgMCN0AABRDSooZqvPeh330aP5+Pj5S27aO92E3bcpGZwAAVFaEbgAArnDpkrRtm+N92Hv25O9nsUgtWjjeh926teTrW+YlAwAAN3VNoTs7O1urV6/W/v37dffddysoKEjHjh1TcHCwqlSpUto1AgBQJKtVSky0aM2aMAUGWhQTU/yZ5exsc6OzvPdh79hhtl8pMtJxifhNN0lBQaX6VQAAQAVT4tB96NAhDRo0SIcPH1ZGRob69++voKAgvfzyy8rIyND06dOdUScAAAVauFAaP146etRLUkdNnSqFh0uvvy7Fxjr2NQxp/37H+7B//FG6eDH/+4aEOC4R79jR3PwMAACgJEocusePH6+OHTtq+/btqlmzZm777bffrjFjxpRqcQAAFGXhQmn48PznWyclme3vvmsG5bzLxM+dy/8+QUFmqM4bsiMi2OgMAABcvxKH7rVr12r9+vXy8fFxaI+MjFRSUlKpFQYAQFGsVnOG+8rALdnbCvq7YF9fqV07x/uwb7xR8vBwarkAAKCSKnHottlsslqt+dqPHj2qIG5sAwCUkbVrC949/EoNG0oxMfaQ3bq1ucM4AABAWShx6B4wYIDi4+P17rvvSpIsFovS0tI0adIk3XzzzaVeIAAAV/rlF+m114rX95//lEaMcG49AAAAhSlx6H711Vc1cOBAtWjRQpcvX9bdd9+tvXv3qlatWvr000+dUSMAADpzRpo7V/roI3MTtOKqW9d5NQEAAFxNiUN3eHi4tm/frnnz5mn79u1KS0vTH//4R40cOVL+/v7OqBEAUEllZkpLl0offih99ZWUlWW2e3pKgwdLGzZIZ88WfF+3xWLuYt6rV9nWDAAAkFeJQ/eaNWvUvXt3jRw5UiNHjsxtz87O1po1a9S7d+9SLRAAULkYhrR1qzmjPWeOdPq0/Vr79tJ990l3320e6ZWze7nF4hi8c3Ydj48v/nndAAAAzlDi0B0TE6Pjx48rJCTEoT0lJUUxMTEFbrIGAMDVHDsmzZ5tzmrv2mVvr1NHGjlSGjXK3AQtr9hYacGCnHO67e3h4WbgvvKcbgAAgLJW4tBtGIYsBRxceubMGQUGBpZKUQCAyuHiRemLL8ygnZAg2Wxmu5+fNGyYOavdv7/kVcSfVrGx0tCh0qpV2Vq6dJsGD26nmBgvZrgBAIBbKHbojv19usBisej++++Xr69v7jWr1aqffvpJ3bt3L/0KAQAVimFI69aZQfuzz6TUVPu1Hj3MGe077pCqVSv+e3p6SlFRhtLTkxQV1ZbADQAA3EaxQ3fVqlUlmTPdQUFBDpum+fj4qGvXrhozZkzpVwgAqBAOHDDv0/7oI+ngQXt7ZKQ5o33ffVLjxi4rDwAAwCmKHbpnzpwpSYqMjNQTTzzBUnIAwFWlpJiz2R9+aM5u5wgKMmezR42SevaUPDxcVyMAAIAzlfie7kmTJjmjDgBABWG1mvdnf/ihtHixdPmy2e7hIfXrZwbtYcOkgABXVgkAAFA2Shy6JWnBggWaP3++Dh8+rMzMTIdrW7duLZXCAADly86d5tLxTz6Rjh+3t7doYQbtkSOlsDDX1QcAAOAKJV7Q98Ybb2j06NEKDQ3Vjz/+qM6dO6tmzZo6cOCABg8efE1FTJs2TZGRkfLz81OXLl20cePGQvvOmjVLFovF4eHn53dNnwsAuD6nTklvvCF16GAe5/XKK2bgrllTeuQRadMmM4w/+SSBGwAAVE4lnul+++239e6772rEiBGaNWuWnnzySTVq1EjPPfeczp49W+IC5s2bpwkTJmj69Onq0qWL4uPjNXDgQO3ZsyffWeA5goODtWfPntznBR1hBgBwjowM6auvzFntr7+WsrPNdm9v6ZZbzA3Rbr5Z8vFxbZ0AAADuoMQz3YcPH849Gszf318XLlyQJN1777369NNPS1zA1KlTNWbMGI0ePVotWrTQ9OnTFRAQoA8++KDQ11gsFtWpUyf3ERoaWuLPBQAUn2FIGzdKY8dK9epJw4dLX35pBu6OHaU335SOHZMWLjTv1yZwAwAAmEocuuvUqZM7o12/fn19//33kqSDBw/KMIwSvVdmZqa2bNmifv362Qvy8FC/fv20YcOGQl+XlpamBg0aKCIiQkOHDtWuXbtK+jUAAMVw5Ig0ZYp5X3aXLtLbb0tnz5pLxZ96Stq1y1xCPm6cVKuWq6sFAABwPyVeXt6nTx99+eWXat++vUaPHq3HH39cCxYs0ObNmxUbG1ui9zp9+rSsVmu+merQ0FD98ssvBb6madOm+uCDD9SmTRulpKToP//5j7p3765du3YpPDw8X/+MjAxlZGTkPk9NTZUkZWVlKSsrq0T1lqWc2ty5RlROjM2KLz1dWrTIok8+8dCqVRYZhnkLj7+/oWHDDN17r00xMYY8Pc3+7jIUGJtwV4xNuCvGJtxVeRmbxa3PYpRwetpms8lms8nLy8zrc+fO1fr163XDDTfooYcekk8J1hQeO3ZMYWFhWr9+vbp165bb/uSTTyoxMVE//PDDVd8jKytLzZs314gRI/Tiiy/mu/78889r8uTJ+drnzJmjAM6rAQBJks0m7dpVSytXRmjDhnq6fNn+d7ItW55Wnz5H1L37Mfn7Z7uwSgAAAPdx8eJF3X333UpJSVFwcHCh/UocuouSlJSksBJsT5uZmamAgAAtWLBAw4YNy20fNWqUzp8/ry+++KJY73PHHXfIy8urwHvKC5rpjoiI0OnTp4v8jXG1rKwsJSQkqH///vL29nZ1OUAuxmbF8uuv0iefeGjOHA8dPmzflLJxY0P33GPT3Xfb1LChCwssAcYm3BVjE+6KsQl3VV7GZmpqqmrVqnXV0H1N53RfKTk5Wf/85z81Y8YMXbx4sdiv8/HxUYcOHbRixYrc0G2z2bRixQqNGzeuWO9htVq1Y8cO3XzzzQVe9/X1la+vb752b29vt/4XmKO81InKh7FZfp07J82bZ+4+nnf7jKpVpbg4c/fx7t0tslg8JXm6rM5rxdiEu2Jswl0xNuGu3H1sFre2Ym+kdu7cOY0YMUK1atVSvXr19MYbb8hms+m5555To0aNtGnTJs2cObPEhU6YMEHvvfeePvzwQ/388896+OGHlZ6ertGjR0uS7rvvPk2cODG3/wsvvKDly5frwIED2rp1q+655x4dOnRIDz74YIk/GwAqi6ws85ivO++U6taVHn7YDNyenubxXnPnmudrv/OO1KOHxEmMAAAApaPYM91PP/201q9fr/vvv1/Lli3T448/rm+++UYeHh5auXKlunbtek0FxMXF6dSpU3ruueeUnJysdu3a6ZtvvsndXO3w4cPy8LD/3cC5c+c0ZswYJScnq3r16urQoYPWr1+vFi1aXNPnA0BFtn279OGH0uzZ0smT9vbWraVRo6SRI6U6dVxXHwAAQEVX7NC9dOlSzZo1S3369NG4cePUqFEjtWvXTv/617+uu4hx48YVupx89erVDs9fe+01vfbaa9f9mQBQUZ04YYbsDz+UfvrJ3l67thmyR42S2rVzWXkAAACVSrFD97Fjx9S8eXNJUmRkpPz8/HTPPfc4rTAAQPFdvix9+aUZtJctk6xWs93HR7rtNjNoDxwoufFtUQAAABVSsUO3YRi5x4RJkqenp/z9/Z1SFADg6gzDvC/7ww/NjdFSUuzXunY1g3ZcnFS9uutqBAAAqOxKFLr79u2bG7wvXbqkW2+9Nd+53Fu3bi3dCgEADn77Tfr4Y3P38X377O3160v33mvuPn7jjS4rDwAAAHkUO3RPmjTJ4fnQoUNLvRgAQMEuXJAWLDCDdt6tLgIDpeHDzVntqCjJo9hnUgAAAKAsXHPoBgA4l9UqrVxpBu2FC6WLF812i0Xq08cM2rffLlWp4to6AQAAULhih24AQNn4+WczaH/yiXT0qL39xhvNoH3PPeZScgAAALg/QjcAuIEzZ6S5c81N0TZtsrdXry6NGGHep925sznLDQAAgPKD0A0ALpKZKS1dagbtr76SsrLMdi8v6eabzaB9yy2Sr69r6wQAAMC1I3QDQBkyDGnrVjNof/qpdPq0/Vr79uby8REjpJAQ19UIAACA0lPifW4/+ugjZWRk5GvPzMzURx99VCpFAUBFc+yY9H//J7VuLXXsKL35phm469SRnnhC+uknM4yPH0/gBgAAqEhKHLpHjx6tlJSUfO0XLlzQ6NGjS6UoAKgILl6U5syRBg2SIiKkp56Sdu2S/Pyku+4yl5YfOSK98ooZxgEAAFDxlHh5uWEYshSwk8/Ro0dVtWrVUikKAMorm01at85cPv7ZZ+b52jl69jSXj99xh8SPSwAAgMqh2KG7ffv2slgsslgs6tu3r7y87C+1Wq06ePCgBg0a5JQiAcDd7d8vffyxedTXwYP29oYNzQ3R7r1XatzYdfUBAADANYoduocNGyZJ2rZtmwYOHKgqVarkXvPx8VFkZKT+8Ic/lHqBAOCuUlLM2ewPPzRnt3MEBUl33mmG7Z49JY8S38gDAACAiqLYoXvSpEmSpMjISMXFxcnPz89pRQGAu8rOlr791gzaixdLly+b7R4eUv/+ZtAeNkwKCHBllQAAAHAXJb6ne9SoUc6oAwDc2s6dZtCePVs6ftze3qKFeZ/2yJFSWJjr6gMAAIB7KlborlGjhn799VfVqlVL1atXL3AjtRxnz54tteIAwJVOnTJ3H//wQ+nHH+3tNWtKd99thu2bbpKK+JEIAACASq5Yofu1115TUFBQ7q+LCt0AUJ5lZEhffWUG7aVLzeXkkuTtLd1yixm0Bw+WfHxcWycAAADKh2KF7rxLyu+//35n1QIALmEY0saNZtCeO1c6d85+rVMnM2jfdZc5ww0AAACURLHv6U5NTS1Wv+Dg4GsuBgDK0pEj0iefmGF7zx57e1iYecTXffdJzZu7rj4AAACUf8UO3dWqVStyWblhGLJYLLJaraVSGAA4Q3q6tHChGbRXrjRnuSVzt/HYWHNWOyZG8vR0bZ0AAACoGIoduletWpX7a8MwdPPNN+v9999XGNv1AnBzNpuUmGgG7QULzOCdIzraDNp/+IN5vjYAAABQmooduqOiohyee3p6qmvXrmrUqFGpFwUApeHXX6WPPpI+/lg6fNje3qSJuXT83nulyEiXlQcAAIBKoMTndAOAOzt3Tpo3z5zV/v57e3vVqlJcnDmr3a0bx3wBAACgbBC6AZR7WVnSsmVm0P7ySykz02z39JQGDTJntW+7TfLzc22dAAAAqHyuK3RzXjcAV9q2zQzac+ZIJ0/a29u0MWe0775bqlPHZeUBAAAAxQ/dsbGxDs8vX76sP//5zwoMDHRoX7hwYelUBgAFSE6WZs8279X+6Sd7e0iINHKkGbbbtnVdfQAAAEBexQ7dVatWdXh+zz33lHoxAFCQy5elL74wg/ayZVLOyYQ+PtLQoWbQHjBA8vZ2bZ0AAADAlYodumfOnOnMOgDAgWFI69ebQXvePCklxX6tWzczaN95p1S9uutqBAAAAK6GjdQAuJXffjOP+ProI2nfPnt7/fr2Y75uvNFl5QEAAAAl4uHqAiRp2rRpioyMlJ+fn7p06aKNGzcW63Vz586VxWLRsGHDnFsgAKe6cEGaOVOKjpYaNpSee84M3IGB0v33SytXSgcPSi++SOAGAABA+eLyme558+ZpwoQJmj59urp06aL4+HgNHDhQe/bsUUhISKGv++233/TEE0+oV69eZVgtgNJitZph+sMPpYULpUuXzHaLRerb15zVjo01gzcAAABQXrl8pnvq1KkaM2aMRo8erRYtWmj69OkKCAjQBx98UOhrrFarRo4cqcmTJ6tRo0ZlWC2A6/Xzz9LTT0sNGpibn82ebQbupk2lf/1LOnRISkgwl5ETuAEAAFDeuXSmOzMzU1u2bNHEiRNz2zw8PNSvXz9t2LCh0Ne98MILCgkJ0R//+EetXbu2LEoFcB3OnJE+/dS8T3vTJnt79erSiBHmpmidOpmz3AAAAEBF4tLQffr0aVmtVoWGhjq0h4aG6pdffinwNevWrdOMGTO0bdu2Yn1GRkaGMjIycp+npqZKkrKyspSVlXVthZeBnNrcuUZUTsUdm5mZ0tKlFn3yiYe+/tqirCwzUXt5GRo0yNC999p0882GfH3N/tnZTi0blQA/N+GuGJtwV4xNuKvyMjaLW5/L7+kuiQsXLujee+/Ve++9p1q1ahXrNVOmTNHkyZPztS9fvlwBAQGlXWKpS0hIcHUJQC6rVdq9u6bOnQvTjh1b1aLFGXl62q8bhrR/fzWtWhWhtWvDlJrqm3utUaPz6tPniHr1OqqqVTMlSStWlPU3QGXAz024K8Ym3BVjE+7K3cfmxYsXi9XPYhiG4eRaCpWZmamAgAAtWLDAYQfyUaNG6fz58/riiy8c+m/btk3t27eXZ57/y7fZbJLMZel79uxR48aNHV5T0Ex3RESETp8+reDgYCd8q9KRlZWlhIQE9e/fX97e3q4uB9CiRRZNmOCppCT7GvCwMENTp1rVubOhTz/10Mcfe+jnn+3X69Y1NGKETffcY1OrVq6oGpUJPzfhrhibcFeMTbir8jI2U1NTVatWLaWkpBSZLV060+3j46MOHTpoxYoVuaHbZrNpxYoVGjduXL7+zZo1044dOxzannnmGV24cEGvv/66IiIi8r3G19dXvr6++dq9vb3d+l9gjvJSJyq2hQulu+4yZ7LzSkqyKC7OSxaL/Zqfn3T77ebu4/36WeTl5SnJM997As7Cz024K8Ym3BVjE+7K3cdmcWtz+fLyCRMmaNSoUerYsaM6d+6s+Ph4paena/To0ZKk++67T2FhYZoyZYr8/PzU6orpsmrVqklSvnYApcNqlcaPzx+48zIMqWdPc0O0O+6QqlYtu/oAAAAAd+by0B0XF6dTp07pueeeU3Jystq1a6dvvvkmd3O1w4cPy8PD5SebAZVWYqJ09OjV+734ohQd7fRyAAAAgHLF5aFbksaNG1fgcnJJWr16dZGvnTVrVukXBFRyhiFt2SLNnSvNnFm81xw/7tyaAAAAgPLILUI3ANczDOmnn6R588zHgQMle33dus6pCwAAACjPCN1AJffzz/ag/csv9vaAAOnWW6Xhw6XHHpOOHSv4vm6LRQoPl3r1KrOSAQAAgHKD0A1UQvv3myF77lwp74EAvr7SzTebO5UPGSIFBprtHh5m+M67S7lkPpek+Hg5nNcNAAAAwEToBiqJQ4ek+fPNsL1li73d21saOFCKi5Nuu00q6IjB2FhpwQJzF/O8m6qFh5uBOzbW6eUDAAAA5RKhG6jAjh2TPvvMDNobNtjbPT2lvn3NoH377VL16ld/r9hYaehQadWqbC1duk2DB7dTTIwXM9wAAABAEQjdQAVz8qT0+edm0F6zxr4c3GKRoqLMpeOxsVLt2iV/b09PKSrKUHp6kqKi2hK4AQAAgKsgdAMVwNmz0qJF5j3aK1dKNpv9WvfuZtAePpwdxgEAAICyRugGyqmUFOmLL8wZ7eXLpexs+7VOncyl43fcIdWv77oaAQAAgMqO0A2UI+np0v/+ZwbtpUuljAz7tbZtzaB9551S48auqxEAAACAHaEbcHOXLpkBe948M3BfumS/1ry5GbTj4qRmzVxXIwAAAICCEboBN5SZaS4ZnzdPWrxYSkuzX2vc2LxHOy5OatXKflY2AAAAAPdD6AbcRHa2uQna3Lnmpmjnz9uv1a9vn9G+6SaCNgAAAFBeELoBF7JazWO95s0zj/k6fdp+rW5d8/7suDipa1eCNgAAAFAeEbqBMmazSRs2mEH7s8+k5GT7tdq1zaO94uKknj3FOdgAAABAOUfoBsqAYUibN5tLx+fPl44etV+rXl2KjTXv046Olrz4rxIAAACoMPjfe8BJDEPavt2c0Z4/XzpwwH4tKEi6/XZzRrtfP8nHx3V1AgAAAHAeQjdQynbvNoP2vHnSnj329oAA6bbbzKA9aJDk5+e6GgEAAACUDUI3UAr27TND9ty50s6d9nZfX2nIEDNoDxkiBQa6rkYAAAAAZY/QDVyjQ4fMZeNz50pbt9rbvb2lgQPNoH3bbVJwsOtqBAAAAOBahG6gBJKSzB3H582Tvv/e3u7pKfXta26GNmyYuTkaAAAAABC6gas4eVJasMAM2mvXmhukSea52dHR5ox2bKx53BcAAAAA5EXoBgpw9qy0cKEZtFeuNM/WztGjhxm0hw+X6tZ1XY0AAAAA3B+hG/hdSor0xRfmPdoJCVJ2tv1ap05m0L7zTikiwnU1AgAAAChfCN2o1NLSpP/9z5zRXrpUysy0X2vb1gzacXFSo0auqxEAAABA+UXoRqVz6ZL09ddm0P7qK/N5jubNzc3Q4uKkpk1dVyMAAACAioHQjUohI0NavtwM2l98Yc5w52jSxD6j3aqVuUEaAAAAAJQGQjcqrKwscxO0uXOlRYvMe7ZzNGhg3p99111S+/YEbQAAAADOQehGhWK1SomJ5oz2559LZ87Yr9WrZwbtuDipSxeCNgAAAADnI3Sj3LPZpPXrzaC9YIGUnGy/FhJiHu0VFyf17Cl5eLiuTgAAAACVD6Eb5ZJhSJs2mUF7/nzp6FH7tRo1pNhYM2hHR0tejHIAAAAALuIW837Tpk1TZGSk/Pz81KVLF23cuLHQvgsXLlTHjh1VrVo1BQYGql27dvr444/LsFq4imFI27ZJTz8tNW5sLhGfOtUM3MHB0n33mbuSJydL770n9etH4AYAAADgWi6PJPPmzdOECRM0ffp0denSRfHx8Ro4cKD27NmjkJCQfP1r1Kihf/zjH2rWrJl8fHz01VdfafTo0QoJCdHAgQNd8A3gbLt3m5uhzZsn/fqrvT0wULr1VnMztIEDJT8/19UIAAAAAAVxeeieOnWqxowZo9GjR0uSpk+friVLluiDDz7Q008/na9/dHS0w/Px48frww8/1Lp16wjdFcjevWbInjdP2rnT3u7nJw0ZYi4dHzJECghwXY0AAAAAcDUuDd2ZmZnasmWLJk6cmNvm4eGhfv36acOGDVd9vWEYWrlypfbs2aOXX37ZmaWiDPz2m3l/9rx50tat9nZvb2nQIDNo33abFBTkshIBAAAAoERcGrpPnz4tq9Wq0NBQh/bQ0FD98ssvhb4uJSVFYWFhysjIkKenp95++23179+/wL4ZGRnKyMjIfZ6amipJysrKUlZWVil8C+fIqc2daywNSUnSggUe+uwzizZutG8x4OlpqG9fQ3fcYdNttxmqXt3+mgr+W+L2KsvYRPnD2IS7YmzCXTE24a7Ky9gsbn0uX15+LYKCgrRt2zalpaVpxYoVmjBhgho1apRv6bkkTZkyRZMnT87Xvnz5cgWUg7XJCQkJri6h1J0/76v16+tp3bp6+vnnmjIM88Bsi8VQq1an1bNnkrp1O67g4ExJUjEWPcAFKuLYRMXA2IS7YmzCXTE24a7cfWxevHixWP0shmEYTq6lUJmZmQoICNCCBQs0bNiw3PZRo0bp/Pnz+uKLL4r1Pg8++KCOHDmiZcuW5btW0Ex3RESETp8+reDg4Ov+Ds6SlZWlhIQE9e/fX97e3q4u57qdOSMtXmzRZ595aPVqi2w2S+617t1tuvNOQ7GxNtWp48IiUSwVbWyi4mBswl0xNuGuGJtwV+VlbKampqpWrVpKSUkpMlu6dKbbx8dHHTp00IoVK3JDt81m04oVKzRu3Lhiv4/NZnMI1nn5+vrK19c3X7u3t7db/wvMUV7qLEhKirR4sbnz+LffStnZ9mudO5v3aN9xhxQRkbOs3NMVZeIaleexiYqNsQl3xdiEu2Jswl25+9gsbm0uX14+YcIEjRo1Sh07dlTnzp0VHx+v9PT03N3M77vvPoWFhWnKlCmSzOXiHTt2VOPGjZWRkaGvv/5aH3/8sf773/+68mvgd2lp0v/+Zwbtb76RMjPt19q1M4P2nXdKjRq5rEQAAAAAKDMuD91xcXE6deqUnnvuOSUnJ6tdu3b65ptvcjdXO3z4sDw87Btspaen6y9/+YuOHj0qf39/NWvWTJ988oni4uJc9RUqvUuXpCVLzF3Hlywxn+do0cIM2nFxUtOmrqsRAAAAAFzB5aFbksaNG1focvLVq1c7PH/ppZf00ksvlUFVKEpGhrRsmRm0v/zSnOHO0aSJdNddZtBu1cp1NQIAAACAq7lF6Eb5kJUlrVhhBu1Fi8x7tnM0aGCf0W7fXrJYCn8fAAAAAKgsCN0oktUqJSaa92gvXGjuQp6jXj3z/uy4OKlLF4I2AAAAAFyJ0I18bDbpu+/MGe0FC6QTJ+zXQkKk4cPNoN2zp5TndnsAAAAAwBUI3ZAkGYa0caMZtOfPl5KS7Ndq1JBiY837tKOiJC9GDQAAAAAUC/GpEjMMads2c+n4/PnSb7/ZrwUHS7ffbs5o9+snufHxeAAAAADgtgjdldCuXWbQnjdP2rvX3h4YKN12mxm0Bw6U/PxcVyMAAAAAVASE7kri11/NkD1vnhm6c/j5SUOGmEvHb75ZCghwXY0AAAAAUNEQuiuwgwfNZePz5kk//mhv9/aWBg82Z7RvvVUKCnJdjQAAAABQkRG6K5ijR6XPPjOXj2/caG/39JT69zeD9rBhUrVqrqoQAAAAACoPQncFkJxsHu01b560bp293cNDio42g3ZsrFSrlstKBAAAAIBKidDthqxWKTHRojVrwhQYaFFMjDlTndfp09LChWbQXr3aPFs7R8+eZtAePlyqU6dMSwcAAAAA5EHodjMLF0rjx0tHj3pJ6qipU6XwcOn116U+faTFi82gnZBghvMcnTubm6HdcYfZHwAAAADgeoRuN7JwoTk7bRiO7UePSn/4g+TlJWVn29vbtzdntO+8U2rYsGxrBQAAAABcHaHbTVit5gz3lYE7r+xsqUULc0Y7Lk668cayqw8AAAAAUHKEbjexdq05o30106aZm6MBAAAAANyfh6sLgOn48dLtBwAAAABwPUK3m6hbt3T7AQAAAABcj9DtJnr1Mncdt1gKvm6xSBERZj8AAAAAQPlA6HYTnp7msWBS/uCd8zw+Pv953QAAAAAA90XodiOxsdKCBVJYmGN7eLjZHhvrmroAAAAAANeG3cvdTGysNHSotGpVtpYu3abBg9spJsaLGW4AAAAAKIcI3W7I01OKijKUnp6kqKi2BG4AAAAAKKdYXg4AAAAAgJNUupluwzAkSampqS6upGhZWVm6ePGiUlNT5e3t7epygFyMTbgrxibcFWMT7oqxCXdVXsZmTqbMyZiFqXSh+8KFC5KkiIgIF1cCAAAAACjvLly4oKpVqxZ63WJcLZZXMDabTceOHVNQUJAshR2K7QZSU1MVERGhI0eOKDg42NXlALkYm3BXjE24K8Ym3BVjE+6qvIxNwzB04cIF1atXTx4ehd+5Xelmuj08PBQeHu7qMootODjYrQcaKi/GJtwVYxPuirEJd8XYhLsqD2OzqBnuHGykBgAAAACAkxC6AQAAAABwEkK3m/L19dWkSZPk6+vr6lIAB4xNuCvGJtwVYxPuirEJd1XRxmal20gNAAAAAICywkw3AAAAAABOQugGAAAAAMBJCN0AAAAAADgJoRsAAAAAACchdJehadOmKTIyUn5+furSpYs2btxYaN9Zs2bJYrE4PPz8/MqwWlQWa9as0a233qp69erJYrFo8eLFV33N6tWrddNNN8nX11dNmjTRrFmznF4nKp8pU6aoU6dOCgoKUkhIiIYNG6Y9e/Zc9XWfffaZmjVrJj8/P7Vu3Vpff/11GVSLyuS///2v2rRpo+DgYAUHB6tbt25aunRpka9hXKKs/fvf/5bFYtFjjz1WZD/GJsrC888/ny/bNGvWrMjXVKSxSeguI/PmzdOECRM0adIkbd26VW3bttXAgQN18uTJQl8THBys48eP5z4OHTpUhhWjskhPT1fbtm01bdq0YvU/ePCghgwZopiYGG3btk2PPfaYHnzwQS1btszJlaKySUxM1NixY/X9998rISFBWVlZGjBggNLT0wt9zfr16zVixAj98Y9/1I8//qhhw4Zp2LBh2rlzZxlWjoouPDxc//73v7VlyxZt3rxZffr00dChQ7Vr164C+zMuUdY2bdqkd955R23atCmyH2MTZally5YO2WbdunWF9q1wY9NAmejcubMxduzY3OdWq9WoV6+eMWXKlAL7z5w506hatWqR7zlt2jSjSZMmhq+vrxESEmL84Q9/KM2SUQlJMhYtWlRknyeffNJo2bKlQ1tcXJwxcODA3OefffaZ0apVK8PPz8+oUaOG0bdvXyMtLc0ZJaMSOXnypCHJSExMLLTPnXfeaQwZMsShrUuXLsZDDz2U+5yfnXCG6tWrG++//36B1xiXKEsXLlwwbrjhBiMhIcGIiooyxo8fX2hfxibKyqRJk4y2bdsWu39FG5vMdJeBzMxMbdmyRf369ctt8/DwUL9+/bRhw4ZCX5eWlqYGDRooIiIi39+gb968WY8++qheeOEF7dmzR99884169+7t1O8BSNKGDRscxrIkDRw4MHcsHz9+XCNGjNADDzygn3/+WatXr1ZsbKwMw3BFuahAUlJSJEk1atQotM/Vxic/O1HarFar5s6dq/T0dHXr1q3APoxLlKWxY8dqyJAh+cZcQRibKEt79+5VvXr11KhRI40cOVKHDx8utG9FG5teri6gMjh9+rSsVqtCQ0Md2kNDQ/XLL78U+JqmTZvqgw8+UJs2bZSSkqL//Oc/6t69u3bt2qXw8HAdPnxYgYGBuuWWWxQUFKQGDRqoffv2ZfF1UMklJycXOJZTU1N16dIlHT9+XNnZ2YqNjVWDBg0kSa1bt3ZFqahAbDabHnvsMfXo0UOtWrUqtF9h4zM5OVmS+NmJUrNjxw5169ZNly9fVpUqVbRo0SK1aNGiwL6MS5SVuXPnauvWrdq0aVOx+jM2UVa6dOmiWbNmqWnTpjp+/LgmT56sXr16aefOnQoKCsrXv6KNTWa63VS3bt103333qV27doqKitLChQtVu3ZtvfPOO5Kk/v37q0GDBmrUqJHuvfdezZ49WxcvXnRx1YDUtm1b9e3bV61bt9Ydd9yh9957T+fOnXN1WSjnxo4dq507d2ru3LnX9T787ERpadq0qbZt26YffvhBDz/8sEaNGqXdu3df03sxLlEajhw5ovHjx2v27NmltvkuYxOlZfDgwbrjjjvUpk0bDRw4UF9//bXOnz+v+fPnX9P7lbexSeguA7Vq1ZKnp6dOnDjh0H7ixAnVqVOnWO/h7e2t9u3ba9++fZKkoKAgbd26VZ9++qnq1q2r5557Tm3bttX58+dLu3zAQZ06dQocy8HBwfL395enp6cSEhK0dOlStWjRQm+++aaaNm2qgwcPuqhilHfjxo3TV199pVWrVik8PLzIvoWNz5yftfzsRGnx8fFRkyZN1KFDB02ZMkVt27bV66+/XmBfxiXKwpYtW3Ty5EnddNNN8vLykpeXlxITE/XGG2/Iy8tLVqs132sYm3CVatWq6cYbb8zNNleqaGOT0F0GfHx81KFDB61YsSK3zWazacWKFYXe/3Ulq9WqHTt2qG7durltXl5e6tevn/7v//5PP/30k3777TetXLmy1OsH8urWrZvDWJakhIQEh7FssVjUo0cPTZ48WT/++KN8fHy0aNGisi4V5ZxhGBo3bpwWLVqklStXqmHDhld9TXHGJz874Qw2m00ZGRkFXmNcoiz07dtXO3bs0LZt23IfHTt21MiRI7Vt2zZ5enrmew1jE66Slpam/fv3O2SbvCra2OSe7jIyYcIEjRo1Sh07dlTnzp0VHx+v9PR0jR49WpJ03333KSwsTFOmTJEkvfDCC+ratauaNGmi8+fP65VXXtGhQ4f04IMPSpK++uorHThwQL1791b16tX19ddfy2azqWnTpi77jiif0tLSHP6W8eDBg9q2bZtq1Kih+vXra+LEiUpKStJHH30kSfrzn/+st956S08++aQeeOABrVy5UvPnz9eSJUskST/88INWrFihAQMGKCQkRD/88INOnTql5s2bu+T7ofwaO3as5syZoy+++EJBQUG593FVrVpV/v7+kvL/7Bw/fryioqL06quvasiQIZo7d642b96sd999VxI/O1E6Jk6cqMGDB6t+/fq6cOGC5syZo9WrV+cenci4hCsEBQXl2/MiMDBQNWvWzG1nbMJVnnjiCd16661q0KCBjh07pkmTJsnT01MjRoyQVAnGpqu3T69M3nzzTaN+/fqGj4+P0blzZ+P777/PvRYVFWWMGjUq9/ljjz2W2zc0NNS4+eabja1bt+ZeX7t2rREVFWVUr17d8Pf3N9q0aWPMmzevLL8OKohVq1YZkvI9csbjqFGjjKioqHyvadeuneHj42M0atTImDlzZu613bt3GwMHDjRq165t+Pr6GjfeeKPx5ptvlt0XQoVR0LiU5DDervzZaRiGMX/+fOPGG280fHx8jJYtWxpLlizJvcbPTpSGBx54wGjQoIHh4+Nj1K5d2+jbt6+xfPny3OuMS7iLK48MY2zCVeLi4oy6desaPj4+RlhYmBEXF2fs27cv93pFH5sWw+AcHwAAAAAAnIF7ugEAAAAAcBJCNwAAAAAATkLoBgAAAADASQjdAAAAAAA4CaEbAAAAAAAnIXQDAAAAAOAkhG4AAAAAAJyE0A0AAAAAgJMQugEAqID27NmjOnXq6MKFC64u5bpERkYqPj6+WH27du2qzz//3LkFAQBQQoRuAACcxGKxFPmIjo6+6nWpZMEzx8SJE/XII48oKCio9L+Ym3rmmWf09NNPy2azuboUAAByebm6AAAAKqrjx4/n/nrevHl67rnntGfPnty2zMxM+fj4SJKOHDmizp0769tvv1XLli0lKfdaSR0+fFhfffWV3nzzzeuovvwZPHiwHnzwQS1dulRDhgxxdTkAAEhiphsAAKepU6dO7qNq1aqyWCwObfXr18/9de3atSVJNWvWzG2rUaPGNX3u/Pnz1bZtW4WFheW2HTp0SLfeequqV6+uwMBAtWzZUl9//XXu9Z07d2rw4MGqUqWKQkNDde+99+r06dO51202m/7v//5PTZo0ka+vr+rXr69//vOfudd37NihPn36yN/fXzVr1tSf/vQnpaWl5V6///77NWzYMP3nP/9R3bp1VbNmTY0dO1ZZWVm5fU6ePKlbb71V/v7+atiwoWbPnu3wvQzD0PPPP6/69evL19dX9erV06OPPpp73dPTUzfffLPmzp17Tb9vAAA4A6EbAIAKZu3aterYsaND29ixY5WRkaE1a9Zox44devnll1WlShVJ0vnz59WnTx+1b99emzdv1jfffKMTJ07ozjvvzH39xIkT9e9//1vPPvusdu/erTlz5ig0NFSSlJ6eroEDB6p69eratGmTPvvsM3377bcaN26cQw2rVq3S/v37tWrVKn344YeaNWuWZs2alXv9/vvv15EjR7Rq1SotWLBAb7/9tk6ePJl7/fPPP9drr72md955R3v37tXixYvVunVrh8/o3Lmz1q5dWyq/jwAAlAaWlwMAUMEcOnQoX+g+fPiw/vCHP+SG1EaNGuVee+utt9S+fXv961//ym374IMPFBERoV9//VV169bV66+/rrfeekujRo2SJDVu3Fg9e/aUJM2ZM0eXL1/WRx99pMDAwNz3vPXWW/Xyyy/nhvPq1avrrbfekqenp5o1a6YhQ4ZoxYoVGjNmjH799VctXbpUGzduVKdOnSRJM2bMUPPmzR2+Q506ddSvXz95e3urfv366ty5s8P3rFevno4cOSKbzSYPD+YWAACux59GAABUMJcuXZKfn59D26OPPqqXXnpJPXr00KRJk/TTTz/lXtu+fbtWrVqlKlWq5D6aNWsmSdq/f79+/vlnZWRkqG/fvgV+3s8//6y2bdvmBm5J6tGjh2w2m8M97C1btpSnp2fu87p16+bOZP/888/y8vJShw4dcq83a9ZM1apVy31+xx136NKlS2rUqJHGjBmjRYsWKTs726EWf39/2Ww2ZWRkFPe3CwAApyJ0AwBQwdSqVUvnzp1zaHvwwQd14MAB3XvvvdqxY4c6duyYu9FaWlqabr31Vm3bts3hsXfvXvXu3Vv+/v6lUpe3t7fDc4vFUqKdxiMiIrRnzx69/fbb8vf311/+8hf17t3b4b7ws2fPKjAwsNRqBgDgehG6AQCoYNq3b6/du3fna4+IiNCf//xnLVy4UH/961/13nvvSZJuuukm7dq1S5GRkWrSpInDIzAwUDfccIP8/f21YsWKAj+vefPm2r59u9LT03PbvvvuO3l4eKhp06bFqrlZs2bKzs7Wli1bctv27Nmj8+fPO/Tz9/fXrbfeqjfeeEOrV6/Whg0btGPHjtzrO3fuVPv27Yv1mQAAlAVCNwAA5UBSUlK+megrZ7NzDBw4UBs2bJDVas1te+yxx7Rs2TIdPHhQW7du1apVq3Lvlx47dqzOnj2rESNGaNOmTdq/f7+WLVum0aNHy2q1ys/PT0899ZSefPJJffTRR9q/f7++//57zZgxQ5I0cuRI+fn5adSoUdq5c6dWrVqlRx55RPfee2/u/dxX07RpUw0aNEgPPfSQfvjhB23ZskUPPvigw4z1rFmzNGPGDO3cuVMHDhzQJ598In9/fzVo0CC3z9q1azVgwIAS//4CAOAshG4AAMqB//znP2rfvr3DY8mSJQX2HTx4sLy8vPTtt9/mtlmtVo0dO1bNmzfXoEGDdOONN+rtt9+WZG4+9t1338lqtWrAgAFq3bq1HnvsMVWrVi13M7Jnn31Wf/3rX/Xcc8+pefPmiouLy70fOyAgQMuWLdPZs2fVqVMnDR8+XH379tVbb71Vou84c+ZM1atXT1FRUYqNjdWf/vQnhYSE5F6vVq2a3nvvPfXo0UNt2rTRt99+q//973+qWbOmJPMvJtavX6/Ro0eX6HMBAHAmi2EYhquLAAAApWvatGn68ssvtWzZMleXUmaeeuopnTt3Tu+++66rSwEAIBdHhgEAUAE99NBDOn/+vC5cuKCgoCBXl1MmQkJCNGHCBFeXAQCAA2a6AQAAAABwEu7pBgAAAADASQjdAAAAAAA4CaEbAAAAAAAnIXQDAAAAAOAkhG4AAAAAAJyE0A0AAAAAgJMQugEAAAAAcBJCNwAAAAAATkLoBgAAAADASQjdAAAAAAA4CaEbAAAAAAAnIXQDAAAAAOAkhG4AAAAAAJyE0A0AAAAAgJMQugEAAAAAcBJCNwAAxfT222/LYrGoS5curi5FkvvV4wzR0dGyWCxXfRS33/PPPy9JioyM1C233OLaLwcAqBQshmEYri4CAIDyoEePHjp27Jh+++037d27V02aNKEeJ0tISNCJEydyn2/atElvvPGG/v73v6t58+a57WfOnFHNmjWv2q9NmzZq06aNIiMj1apVK3311Vdl80UAAJWWl6sLAACgPDh48KDWr1+vhQsX6qGHHtLs2bM1adIk6nGy/v37Ozz38/PTG2+8of79+ys6OrrQ1xW3HwAAzsbycgAAimH27NmqXr26hgwZouHDh2v27Nm517KyslSjRg2NHj063+tSU1Pl5+enJ554Irft0KFDuu222xQYGKiQkBA9/vjjWrZsmSwWi1avXn3d9eR15swZ3XvvvQoODla1atU0atQobd++XRaLRbNmzXLo+8svv2j48OGqUaOG/Pz81LFjR3355ZdF1lHS7/7mm2+qZcuWCggIUPXq1dWxY0fNmTOnWN8ZAIDyiNANAEAxzJ49W7GxsfLx8dGIESO0d+9ebdq0SZLk7e2t22+/XYsXL1ZmZqbD6xYvXqyMjAzdddddkqT09HT16dNH3377rR599FH94x//0Pr16/XUU0+VWj05bDabbr31Vn366acaNWqU/vnPf+r48eMaNWpUvvfbtWuXunbtqp9//llPP/20Xn31VQUGBmrYsGFatGhRoXWU5Lu/9957evTRR9WiRQvFx8dr8uTJateunX744YcSfXcAAMoTlpcDAHAVW7Zs0S+//KI333xTktSzZ0+Fh4dr9uzZ6tSpkyQpLi5OH3zwgZYvX+6wQde8efPUqFEjdezYUZL0zjvv6MCBA1q8eLGGDh0qSXrooYfUvn37Uq1HMkPvhg0bFB8fr/Hjx0uSHn744XxLtiVp/Pjxql+/vjZt2iRfX19J0l/+8hf17NlTTz31lG6//fZC6ynud1+yZIlatmypzz77rNjfFQCA8o6ZbgAArmL27NkKDQ1VTEyMJMlisSguLk5z586V1WqVJPXp00e1atXSvHnzcl937tw5JSQkKC4uLrftm2++UVhYmG677bbcNj8/P40ZM6ZU68n5LG9vb4f39vDw0NixYx3e7+zZs1q5cqXuvPNOXbhwQadPn9bp06d15swZDRw4UHv37lVSUlKh9RT3u1erVk1Hjx7NNyMPAEBFRugGAKAIVqtVc+fOVUxMjA4ePKh9+/Zp37596tKli06cOKEVK1ZIkry8vPSHP/xBX3zxhTIyMiRJCxcuVFZWlkPwPHTokBo3biyLxeLwOcXdeby49eR8Vt26dRUQEFDkZ+3bt0+GYejZZ59V7dq1HR45m7OdPHmy0JqK+92feuopValSRZ07d9YNN9ygsWPH6rvvvivW9wYAoLwidAMAUISVK1fq+PHjmjt3rm644Ybcx5133ilJDhuY3XXXXbpw4YKWLl0qSZo/f76aNWumtm3buqSe4rLZbJKkJ554QgkJCQU+rvaXAsX57s2bN9eePXs0d+5c9ezZU59//rl69uxZIXddBwAgB/d0AwBQhNmzZyskJETTpk3Ld23hwoVatGiRpk+fLn9/f/Xu3Vt169bVvHnz1LNnT61cuVL/+Mc/HF7ToEED7d69W4ZhOMx279u3r9TradCggVatWqWLFy86zHZf+VmNGjWSZG6K1q9fv2LVcaXifHdJCgwMVFxcnOLi4pSZmanY2Fj985//1MSJE+Xn53dNnw0AgDtjphsAgEJcunRJCxcu1C233KLhw4fne4wbN04XLlzIPVbLw8NDw4cP1//+9z99/PHHys7OdlheLUkDBw5UUlKSw1Fcly9f1nvvvVfq9QwcOFBZWVkO722z2fIF9pCQEEVHR+udd97R8ePH833uqVOnrlpbcb77mTNnHJ77+PioRYsWMgxDWVlZV/0MAADKI2a6AQAoxJdffqkLFy44bHqWV9euXVW7dm3Nnj07N2DGxcXpzTff1KRJk9S6dWs1b97c4TUPPfSQ3nrrLY0YMULjx49X3bp1NXv27NxZ3ivv9b6eeoYNG6bOnTvrr3/9q/bt26dmzZrpyy+/1NmzZ/N91rRp09SzZ0+1bt1aY8aMUaNGjXTixAlt2LBBR48e1fbt26/6+3W17z5gwADVqVNHPXr0UGhoqH7++We99dZbGjJkiIKCgq76/qVt3759eumll/K1t2/fXkOGDCnzegAAFROhGwCAQuSE4YKO2JLM2d0hQ4Zo9uzZOnPmjGrWrKnu3bsrIiJCR44cyTfTK0lVqlTRypUr9cgjj+j1119XlSpVdN9996l79+76wx/+UOQS62upZ8mSJRo/frw+/PBDeXh46Pbbb9ekSZPUo0cPh89q0aKFNm/erMmTJ2vWrFk6c+aMQkJC1L59ez333HPF+v262nd/6KGHNHv2bE2dOlVpaWkKDw/Xo48+qmeeeaZY71/a9uzZo2effTZf+x//+EdCNwCg1FgMwzBcXQQAAJVdfHy8Hn/8cR09elRhYWFO/azFixfr9ttv17p169SjRw+nfhYAAJUdoRsAgDJ26dIl+fv75z6/fPmy2rdvL6vVql9//dWpn2W1WjVgwABt3rxZycnJDtcAAEDpY3k5AABlLDY2VvXr11e7du2UkpKiTz75RL/88ss1Hfd1NY888oguXbqkbt26KSMjQwsXLtT69ev1r3/9i8ANAEAZYKYbAIAyFh8fr/fff1+//fabrFarWrRooSeffLLA+6Cv15w5c/Tqq69q3759unz5spo0aaKHH35Y48aNK/XPAgAA+RG6AQAAAABwEs7pBgAAAADASQjdAAAAAAA4CaEbAAAAAAAnqXS7l9tsNh07dkxBQUGyWCyuLgcAAAAAUA4ZhqELFy6oXr168vAofD670oXuY8eOKSIiwtVlAAAAAAAqgCNHjig8PLzQ65UudAcFBUkyf2OCg4NdXE3hsrKytHz5cg0YMEDe3t6uLgfIxdiEu2Jswl0xNuGuGJtwV+VlbKampioiIiI3Yxam0oXunCXlwcHBbh+6AwICFBwc7NYDDZUPYxPuirEJd8XYhLtibMJdlbexebXbll26kdqUKVPUqVMnBQUFKSQkRMOGDdOePXuKfM2sWbNksVgcHn5+fmVUMQAAAAAAxefS0J2YmKixY8fq+++/V0JCgrKysjRgwAClp6cX+brg4GAdP34893Ho0KEyqhgAAAAA4DRWqyyJiQpbs0aWxETJanV1RdfNpcvLv/nmG4fns2bNUkhIiLZs2aLevXsX+jqLxaI6deo4uzwAAAAAQFlZuFAaP15eR4+qoyRNnSqFh0uvvy7Fxrq6umvmVud0p6SkSJJq1KhRZL+0tDQ1aNBAERERGjp0qHbt2lUW5QEAAAAAnGHhQmn4cOnoUcf2pCSzfeFC19RVCtxmIzWbzabHHntMPXr0UKtWrQrt17RpU33wwQdq06aNUlJS9J///Efdu3fXrl27CtymPSMjQxkZGbnPU1NTJZk352dlZZX+FyklObW5c42onBibcFeMTbgrxibcFWMTbsNqldejj0qGoXxbkhmGDItFGj9e2TffLHl6uqLCAhX3vx2LYRiGk2splocfflhLly7VunXrijzj7EpZWVlq3ry5RowYoRdffDHf9eeff16TJ0/O1z5nzhwFBARcV80AAAAAgOtTc8cO9Xz22av2W/fiizrTunUZVFQ8Fy9e1N13362UlJQiT8Zyi5nucePG6auvvtKaNWtKFLglydvbW+3bt9e+ffsKvD5x4kRNmDAh93nOWWoDBgxw+yPDEhIS1L9//3KxTT4qD8Ym3BVjE+6KsQl3xdiEyxmGtH+/PL74oljduzZoIOPmm51cVPHlrKK+GpeGbsMw9Mgjj2jRokVavXq1GjZsWOL3sFqt2rFjh24u5Dff19dXvr6++dq9vb3LxQ+X8lInKh/GJtwVYxPuirEJd8XYRJk6ckRatUpaudJ8HDlS7Jd6RURIbjRWi/vfjUtD99ixYzVnzhx98cUXCgoKUnJysiSpatWq8vf3lyTdd999CgsL05QpUyRJL7zwgrp27aomTZro/PnzeuWVV3To0CE9+OCDLvseAAAAAIACnDghrV5tD9lXrlD29pa6dJF++kkqbObYYjF3Me/Vy+nlOoNLQ/d///tfSVJ0dLRD+8yZM3X//fdLkg4fPiwPD/sm6+fOndOYMWOUnJys6tWrq0OHDlq/fr1atGhRVmUDAAAAAApy7pyUmGgP2VeeNOXhIXXsKPXpYz66d5cCA+27l0vmsvMclt+3VouPd6tN1ErC5cvLr2b16tUOz1977TW99tprTqoIAAAAAFBsaWnS2rVmwF61Stq61TE0S1LbtvaQ3auXVLVq/veJjZUWLJDGj3c8Niw83Azc5ficbrfYSA0AAAAAUA5cuiRt2GC/L3vjRik727FPs2ZmwI6JkaKjpVq1ivfesbHS0KHKXrVK25YuVbvBg+UVE1NuZ7hzELoBAAAAAAXLypI2bbIvF1+/XsrIcOzTsKEZsHOCdr161/55np4yoqKUlJ6utlFR5T5wS4RuAAAAAEAOq1Xats0esteuldLTHfvUrWtfLh4TY4ZuFIrQDQAAAACVlWGYm53lhOzEROn8ecc+NWvaZ7L79JFuvNG+wRmuitANAAAAAJWFYZjHduVsfLZqlXTypGOf4GApKso+k926tbnrOK4JoRsAAAAAKrLDh+0bn61c6bg7uCT5+5u7iufMZt90k+RFVCwt/E4CAAAAQEVy4oRjyN6/3/G6j4/Utat9uXjnzpKvr2tqrQQI3QAAAABQnp09a96LnROyd+92vO7hIXXqZA/Z3btLAQGuqbUSInQDAAAAQHly4YK5q3jOfdk//mjeq51Xu3b2kN2rl3mfNlyC0A0AAAAA7uzSJfN87Jwl4xs3mkd75dW8uX3js6goqVYt19SKfAjdAAAAAOBOMjOlTZvsy8XXrzfb8mrUyL7xWUyMeXY23BKhGwAAAABcyWqVtm61z2SvXStdvOjYp149+3LxmBgpMtIlpaLkCN0AAAAAUJZsNmnXLvtMdmKilJLi2KdWLftMdp8+0g03SBaLa+rFdSF0AwAAAIAzGYa0d689ZK9aJZ0+7dgnOFiKjrbPZLdqZe46jnKP0A0AAAAApe3QIceQnZTkeD0gwNxVPGc2u317yYt4VhHxbxUAAAAArtfx42a4zrkv+8ABx+s+Pub52Dkhu3Nnsw0VHqEbAAAAAErqzBnzXuyc2eyff3a87ukpdepkvye7e3fJ3981tcKlCN0AAAAAcDWpqeau4jkhe/t2817tHBaL1K6dPWT36iUFBbmsXLgPQjcAAAAAXOniRfN87JyQvXmzebRXXi1a2EN2VJRUo4ZraoVbI3QDAAAAQGam9MMP9o3PNmww2/Jq3Ni+u3hMjFSnjmtqRblC6AYAAABQ+WRnS1u32jc+W7fOnN3OKyzMPpMdEyM1aOCaWlGuEboBAAAAVHw2m7Rzp325eGKieZ92XrVr23cX79NHatLEvFcbuA6EbgAAAAAVj2FIv/7qeFb2mTOOfapWlaKj7SG7ZUtCNkodoRsAAABAxfDbb44h+9gxx+uBgeau4jnLxdu3N4/2ApyI0A0AAACgfDp2zAzXOfdlHzzoeN3X1zwfO2fJeKdOko+Pa2pFpUXoBgAAAFA+nDkjrV5tn83+5RfH656eUufO9uXi3bpJ/v4uKRXIQegGAAAA4J5SU6U1a+whe/t2x+sWi7lEPCdk9+wpBQW5plagEIRuAAAAAO7h4kXpu+/sIXvLFslqdezTsqU9ZPfuLdWo4ZpagWIidAMAAABwjYwM6Ycf7BufbdggZWU59mnSxL7xWUyMFBrqmlqBa0ToBgAAAFA2srPN2eucjc/WrZMuXXLsEx5un8mOiZHq13dNrUApIXQDAAAAcA6bTdqxw75cPDFRunDBsU9IiH138T59pMaNOSsbFQqhGwAAAEDpMAxpzx57yF692txxPK9q1aToaHvIbtGCkI0KzcOVHz5lyhR16tRJQUFBCgkJ0bBhw7Rnz56rvu6zzz5Ts2bN5Ofnp9atW+vrr78ug2oBAAAA5HPwoDRjhjRypBQWJjVvLo0dK33+uRm4AwOlwYOlV14xl5afPi0tWiQ98oi5KRqBGxWcS2e6ExMTNXbsWHXq1EnZ2dn6+9//rgEDBmj37t0KDAws8DXr16/XiBEjNGXKFN1yyy2aM2eOhg0bpq1bt6pVq1Zl/A0AAACAcshqlSUxUWFr1sgSGGgu7/b0LN5rk5LMe7Jz7sv+7TfH676+Uo8e9pnsjh0lb+9S/wpAeeHS0P3NN984PJ81a5ZCQkK0ZcsW9e7du8DXvP766xo0aJD+9re/SZJefPFFJSQk6K233tL06dOdXjMAAABQri1cKI0fL6+jR9VRkqZONTcve/11KTY2f//Tp81l4jlLxq9cmerlJXXpYt/4rFs3yc+vDL4IUD641T3dKSkpkqQaRZy1t2HDBk2YMMGhbeDAgVq8eLEzSwMAAADKv4ULpeHDzXuv80pKMtsXLJD69pXWrLGH7J9+cuxrsUgdOtg3P+vZU6pSpey+A1DOuE3ottlseuyxx9SjR48il4knJycr9Iqz+UJDQ5WcnFxg/4yMDGVkZOQ+T01NlSRlZWUp68ozAN1ITm3uXCMqJ8Ym3BVjE+6KsQm3YbXK69FHJcNQvruoDUOGJN11l5SdLcsVodxo2VK2mBgZ0dEyevWSqld3fD3jG6WovPzcLG59bhO6x44dq507d2rdunWl+r5TpkzR5MmT87UvX75cAQEBpfpZzpCQkODqEoACMTbhrhibcFeMTbhazR071DMpqdDrFik3PKfVq6dTrVvrdOvWOt2qlTKrVbN33LDBqXUCOdz95+bFixeL1c8tQve4ceP01Vdfac2aNQoPDy+yb506dXTixAmHthMnTqhOnToF9p84caLDcvTU1FRFRERowIABCg4Ovv7inSQrK0sJCQnq37+/vNl4Am6EsQl3xdiEu2JswuUyMmTZuFEeW7cWq3t2fLx8//IXhUsq+v/MAecoLz83c1ZRX41LQ7dhGHrkkUe0aNEirV69Wg0bNrzqa7p166YVK1bosccey21LSEhQt27dCuzv6+srX1/ffO3e3t5u/S8wR3mpE5UPYxPuirEJd8XYRJnJzJQ2bbLvML5+vXT5crFf7tW2LbuNwy24+8/N4tbm0tA9duxYzZkzR1988YWCgoJy78uuWrWq/P39JUn33XefwsLCNGXKFEnS+PHjFRUVpVdffVVDhgzR3LlztXnzZr377rsu+x4AAACAy2RlSZs3mzuMr1olffeddOWy15AQKSpKSkiQUlLyb6QmmRukhYdLvXqVSdlAZeHS0P3f//5XkhQdHe3QPnPmTN1///2SpMOHD8vDwyP3Wvfu3TVnzhw988wz+vvf/64bbrhBixcv5oxuAAAAVA7Z2dLWrfaZ7HXrpPR0xz61aknR0eYO4zExUrNmZqjO2b3cYnEM3pbft1aLjy/+ed0AisXly8uvZvXq1fna7rjjDt1xxx1OqAgAAABwM1ar9OOP9pnstWulCxcc+9SoYYbsnKDdooWUZ+IqV2yseSzY+PHS0aP29vBwM3AXdE43gOviFhupAQAAAPidzSZt324G7NWrzTOzU1Ic+1SrZi4Xj4kxg3br1gWH7ILExkpDhyp71SptW7pU7QYPlldMDDPcgJMQugEAAABXstmknTvty8XXrJHOnXPsExws9e5tXy7eps31hWRPTxlRUUpKT1fbqCgCN+BEhG4AAACgLBmGtGuXfbl4YqJ05oxjn6Agc0OznOXi7dsTjIFyitANAAAAOJNhSL/8Yl8uvnq1dOqUY5/AQKlnT/ty8Q4dJC/+Vx2oCPgvGQAAAChNhiHt3WtfLr56tXTihGMff3+pRw/7cvGOHTkbG6igCN0AAADA9TAMaf9++3Lx1aulY8cc+/j5Sd2725eLd+4s+fi4oFgAZY3QDQAAAJTUwYP2gL1qlePxW5IZqLt1sy8X79LFDN4AKh1CNwAAAHA1hw45zmQfOuR43dtb6trVPpPdtau5hBxApUfoBgAAAK509KjjTPbBg47XvbzMJeI5Ibt7dykgwBWVAnBzhG4AAADg2DHHmex9+xyve3qam53lLBfv0UOqUsUFhQIobwjdAAAAqHxOnLCH7FWrpF9/dbzu4WEe25Uzk92zp3l2NgCUEKEbAAAAFd+pU/Yzsletkn7+2fG6xSK1b2+fye7VS6pa1QWFAqhoCN0AAACoeM6ckRIT7cvFd+7M36dtW/s52b16SdWrl3mZACo+QjcAAADKv3PnpDVr7MvFf/opf5/Wre3LxXv3lmrWLPMyAVQ+hG4AAACUPykpZsjOWS6+bZtkGI59WrSwLxePipJq13ZBoQAqO0I3AAAA3N+FC9LatfaZ7B9/lGw2xz7NmtlnsqOipNBQl5QKAHkRugEAAOB+0tKkdevsM9lbtkhWq2OfG26wz2RHR0t167qgUAAoGqEbAAAArnfxovTdd/aNzzZtkrKzHfs0amTf+CwqSgoPd0mpAFAShG4AAACUvUuXpA0b7CH7hx+krCzHPg0a2EN2dLRUv74rKgWA60LoBgAAgPNdvix9/719ufj330uZmY59IiLsATsmRoqMdEGhAFC6CN0AAAAofRkZ0saN9pnsDRvM4J1XvXqOM9mNGkkWiyuqBQCnuabQnZ2drdWrV2v//v26++67FRQUpGPHjik4OFhVqlQp7RoBAADg7jIzpc2b7buLr19vLiHPq04d+yx2TIzUpAkhG0CFV+LQfejQIQ0aNEiHDx9WRkaG+vfvr6CgIL388svKyMjQ9OnTnVEnAAAA3El2thmyc5aLr1tnboaWV0iIfWfxmBipaVNCNoBKp8She/z48erYsaO2b9+umjVr5rbffvvtGjNmTKkWBwAAADeRnW2ejZ2zXHztWvNYr7xq1rQH7OhoqUULQjaASq/EoXvt2rVav369fHx8HNojIyOVlJRUaoUBAADAhaxWaft2+3LxtWul1FTHPtWrm0d35SwXb9lS8vBwTb0A4KZKHLptNpusVmu+9qNHjyooKKhUigIAAEAZs9mkn36yLxdfs0Y6f96xT9Wq9pAdHS21aUPIBoCrKHHoHjBggOLj4/Xuu+9KkiwWi9LS0jRp0iTdfPPNpV4gAAAAnMBmk3btsi8XT0yUzp517BMUJPXubZ/JbttW8vR0SbkAUF6VOHS/+uqrGjhwoFq0aKHLly/r7rvv1t69e1WrVi19+umnzqgRAAAA18swpJ9/ti8XT0yUTp927FOlitSrl/2+7PbtJS9OmAWA61Hin6Lh4eHavn275s6dq59++klpaWn64x//qJEjR8rf398ZNQIAAKCkDEPas8c+k716tXTypGOfgACpZ0/7cvEOHSRvbxcUCwAV1zX91aWXl5fuueee0q4FAAAA18owpH377DPZq1dLycmOffz8pB497MvFO3aUrtgcFwBQukocur/88ssC2y0Wi/z8/NSkSRM1bNjwugsDAABAEQxDOnDAvvHZ6tXSlSfJ+PpK3bvbl4t37my2AQDKTIlD97Bhw2SxWGQYhkN7TpvFYlHPnj21ePFiVa9evdQKBQAAqPR++80esFetko4ccbzu4yN17WpfLt61qzm7DQBwmRKf8ZCQkKBOnTopISFBKSkpSklJUUJCgrp06aKvvvpKa9as0ZkzZ/TEE09c9b3WrFmjW2+9VfXq1ZPFYtHixYuL7L969WpZLJZ8j+Qrl04BAABUBEeOSB99JI0eLTVsaD4eeMBsO3LEvP+6Z0/pmWekFSvMI74SE6XnnzdDN4EbAFyuxDPd48eP17vvvqvu3bvntvXt21d+fn7605/+pF27dik+Pl4PPPDAVd8rPT1dbdu21QMPPKDY2Nhi17Bnzx4FBwfnPg8JCSnZlwAAACgLVqssiYkKW7NGlsBAcwa6qCO3kpLss9irVpnLx/Py8pI6dbIvF+/eXQoMdOY3AABcpxKH7v379zsE3hzBwcE68PsfDDfccINOX3kERQEGDx6swYMHl7QEhYSEqFq1aiV+HQAAQJlZuFAaP15eR4+qoyRNnSqFh0uvvy7lTDYcP27fWXzVKmnvXsf38PQ0dxTPWS7es6d5rBcAoNwoceju0KGD/va3v+mjjz5S7dq1JUmnTp3Sk08+qU6dOkmS9u7dq4iIiNKtNI927dopIyNDrVq10vPPP68ePXo47bMAAABKbOFCafhwc7OzvJKSpD/8QRowQDp8WPrlF8frHh7m2dg5u4v37CkVMNkBACg/Shy6Z8yYoaFDhyo8PDw3WB85ckSNGjXSF198IUlKS0vTM888U7qVSqpbt66mT5+ujh07KiMjQ++//76io6P1ww8/6KabbirwNRkZGcrIyMh9npqaKknKyspSVlZWqddYWnJqc+caUTkxNuGuGJtwG1arvB59VDIMWa68lhPCly83n1osUtu2skVHy+jdW0bPntKVq/kY03ASfm7CXZWXsVnc+izGlduQF4PNZtPy5cv166+/SpKaNm2q/v37y8OjxPuy2QuxWLRo0SINGzasRK+LiopS/fr19fHHHxd4/fnnn9fkyZPztc+ZM0cBAQHXUioAAECBLFlZavjNN2o9Y8ZV++6++279NniwsoKCyqAyAEBpu3jxou6++26lpKQUeAt2jmsK3QU5f/68PvnkE40bN+6aXn+toftvf/ub1q1bpw0bNhR4vaCZ7oiICJ0+fbrI3xhXy8rKUkJCgvr37y9vb29XlwPkYmzCXTE24RKGIf3yizxWrJDl229lWbNGlrS0Yr00+6OPZNx1l5MLBArHz024q/IyNlNTU1WrVq2rhu4SLy+/0ooVKzRjxgwtWrRIAQEB1xy6r9W2bdtUt27dQq/7+vrK19c3X7u3t7db/wvMUV7qROXD2IS7YmzC6U6elL79VkpIMB9JSY7Xg4Ol329nK4pXRIR55BfgYvzchLty97FZ3NquKXQfOXJEM2fO1MyZM3X48GHFxcVp0aJF6tu3b4neJy0tTfv27ct9fvDgQW3btk01atRQ/fr1NXHiRCUlJemjjz6SJMXHx6thw4Zq2bKlLl++rPfff18rV67U8t/viwIAACh1ly5Ja9faQ/b27Y7XfX2lXr2k/v3NR6tWUqNGZhgvaEGhxWLuYt6rV9nUDwBwqWKH7qysLC1evFjvv/++1q5dq0GDBumVV17RiBEj9Mwzz6hFixYl/vDNmzcrJiYm9/mECRMkSaNGjdKsWbN0/PhxHT58OPd6Zmam/vrXvyopKUkBAQFq06aNvv32W4f3AAAAuC42m7Rtmz1kr1sn5blVTZLUrp09ZPfsKfn7O15//XVz93KLxTF4W37fWi0+vujzugEAFUaxQ3dYWJiaNWume+65R3PnzlX16tUlSSNGjLjmD4+OjlZRt5TPmjXL4fmTTz6pJ5988po/DwAAoEBHjthD9rffSqdPO14PD7eH7L59pZCQot8vNlZasEAaP146etTxfeLj7ed0AwAqvGKH7uzsbFksFlksFnnyN7MAAKA8S02VVq+2B+09exyvV6kiRUebIXvAAKlpU/ssdXHFxkpDhyp71SptW7pU7QYPlldMDDPcAFDJFDt0Hzt2TJ9//rlmzJih8ePHa/DgwbrnnntkKekfQAAAAGUtO1vauNEesr//XrJa7dc9PKTOne2z2V27ls4mZ56eMqKilJSerrZRUQRuAKiEih26/fz8NHLkSI0cOVL79+/XzJkz9eijjyo7O1v//Oc/df/996tPnz7MggMAANczDGnvXnvIXrUq/47iTZrYQ3ZMjFStmktKBQBUbNe0e3njxo310ksv6YUXXtCyZcs0Y8YM3XLLLQoKCtLpK++BAgAAKAtnzkgrVkjLl5tBO89mrJKk6tWlfv3sQTsy0iVlAgAql+s6p9vDw0ODBw/W4MGDderUKX388celVRcAAEDRMjKk776zz2Zv3eq4U7i3t9Sjhz1k33QTy7sBAGXuukJ3XrVr18498gsAAKDUGYa0Y4c9ZK9ZY56hnVerVvaQ3bu3FBjomloBAPhdqYVuAACAUnfsmONRXidOOF6vU8cesvv1k+rWdU2dAAAUgtANAADcR1qalJhoD9q7dzteDwiQoqLsQbtly5If5QUAQBkidAMAANexWqUtW+whe/16KSvLft1ikTp0sJ+X3a2b5OvrunoBACghQjcAAChbBw7YQ/bKldK5c47XIyPtM9l9+kg1a7qkTAAASkOJQ3dhm6VZLBb5+fmpSZMmGjp0qGrUqHHdxQEAgArg3DkzXOcE7QMHHK9XrWqG65yg3bgxS8YBABVGiUP3jz/+qK1bt8pqtapp06aSpF9//VWenp5q1qyZ3n77bf31r3/VunXr1KJFi1IvGAAAuLnMTGnDBnvI3rxZstns1728zGXiOSG7Y0ezDQCACqjEf8LlzGLPnDlTwcHBkqSUlBQ9+OCD6tmzp8aMGaO7775bjz/+uJYtW1bqBQMAADdjGNLPP5sBe/lycyO09HTHPs2a2UN2dLQUFOSSUgEAKGslDt2vvPKKEhIScgO3JFWtWlXPP/+8BgwYoPHjx+u5557TgAEDSrVQAADgRk6cMI/wypnNPnbM8Xrt2uYRXjlBOzzcNXUCAOBiJQ7dKSkpOnnyZL6l46dOnVJqaqokqVq1asrMzCydCgEAgOtdvCitXWsP2T/95Hjdz0/q1csestu0kTw8XFMrAABu5JqWlz/wwAN69dVX1alTJ0nSpk2b9MQTT2jYsGGSpI0bN+rGG28s1UIBAEAZstmkH3+0h+zvvpMyMhz7tG9vD9k9ekj+/q6pFQAAN1bi0P3OO+/o8ccf11133aXs7GzzTby8NGrUKL322muSpGbNmun9998v3UoBAIBzHT5sD9nffiudOeN4PTzcfl52377mEnIAAFCkEofuKlWq6L333tNrr72mA78f+dGoUSNVqVIlt0+7du1KrUAAAOAkqanSqlX2oP3rr47Xq1SRYmLss9lNm3KUFwAAJVTi0P3JJ58oNjZWVapUUZs2bZxREwAAcIasLGnjRnvI/uEHyWq1X/f0lDp3tofsLl0kb2/X1QsAQAVQ4tD9+OOP689//rNuu+023XPPPRo4cKA8PT2dURsAALgehmHOXueE7FWrpAsXHPvccIM9ZMfESFWruqZWAAAqqBKH7uPHj+ubb77Rp59+qjvvvFMBAQG64447NHLkSHXv3t0ZNQIAgOI6fdrxKK8jRxyv16hh3o+dE7QjI11SJgAAlUWJQ7eXl5duueUW3XLLLbp48aIWLVqkOXPmKCYmRuHh4dq/f78z6gQAAAW5fNncWTwnZG/d6njdx8fcWTwnZLdvby4jBwAAZaLEoTuvgIAADRw4UOfOndOhQ4f0888/l1ZdAACgIDabtGOHPWSvWWMG77xat7aH7F69pMBA19QKAACuLXTnzHDPnj1bK1asUEREhEaMGKEFCxaUdn0AACApyfEor5MnHa/XrWsP2f36SXXquKZOAACQT4lD91133aWvvvpKAQEBuvPOO/Xss8+qW7duzqgNAIDKKS1NWr3aHrSvXEkWECBFRZnnZffvL7VowVFeAAC4qRKHbk9PT82fP7/AXct37typVq1alVpxAABUClartHmzPWSvXy9lZ9uvWyxSx4722exu3SRfX9fVCwAAiq3EoXv27NkOzy9cuKBPP/1U77//vrZs2SJr3vM+AQBAwfbvt4fslSul8+cdrzdsaA/ZffqYu44DAIBy55o3UluzZo1mzJihzz//XPXq1VNsbKymTZtWmrUBAFBxnD1rhuucoH3woOP1atXMcJ0TtBs3dkmZAACgdJUodCcnJ2vWrFmaMWOGUlNTdeeddyojI0OLFy9WixYtnFUjAADlT2amuUw8J2Rv2WLuPJ7Dy8tcJp4Tsjt2NNsAAECFUuw/3W+99VatWbNGQ4YMUXx8vAYNGiRPT09Nnz7dmfUBAFA+GIa0e7c9ZCcmSunpjn2aN7eH7KgoKSjINbUCAIAyU+zQvXTpUj366KN6+OGHdcMNNzizJgAAyofkZPMIr5yjvI4dc7weEmIe4ZVzlFd4uGvqBAAALlPs0L1u3TrNmDFDHTp0UPPmzXXvvffqrrvucmZtAAC4l4sXpTVr7LPZO3Y4Xvfzk3r3ts9mt24teXi4plYAAOAWiv1/Al27dtV7772n48eP66GHHtLcuXNVr1492Ww2JSQk6MKFCyX+8DVr1ujWW29VvXr1ZLFYtHjx4qu+ZvXq1brpppvk6+urJk2aaNasWSX+XAAAisVmM4/ymjLF3OSsenVp8GBp6lR74G7fXnrqKXOm+9w5adky6YknpLZtCdwAAKD4oTtHYGCgHnjgAa1bt047duzQX//6V/373/9WSEiIbrvtthK9V3p6utq2bVvsXc8PHjyoIUOGKCYmRtu2bdNjjz2mBx98UMuWLSvp1wAAoGC//Sa99550551S7dpSp07S3/8urVplbo4WESE98ID06afSyZPS1q3Sv/8t9e1rznQDAADkcV3bpDZt2lT/93//pylTpuh///ufPvjggxK9fvDgwRo8eHCx+0+fPl0NGzbUq6++Kklq3ry51q1bp9dee00DBw4s0WcDACBJSkkxA3XOkvG9ex2vBwVJMTH2JeM33ihZLK6pFQAAlDulcjaJp6enhg0bpmHDhpXG2xVqw4YN6tevn0PbwIED9dhjjzn1cwEAbs5qlSUxUWFr1sgSGGiGZE/PgvtmZUk//GAP2Rs3Slar/bqnp9Sliz1kd+4seXuXzfcAAAAVTrk6EDQ5OVmhoaEObaGhoUpNTdWlS5fk7++f7zUZGRnKyMjIfZ6amipJysrKUlZWlnMLvg45tblzjaicGJtwN5ZFi+Q5YYK8kpLUUZKmTpURFibr1Kkybr/dPMprzx55rFghy7ffyrJmjSxX7ENiNGkiW//+Mvr2lREVJVWt6vghjHdcB35uwl0xNuGuysvYLG595Sp0X4spU6Zo8uTJ+dqXL1+ugIAAF1RUMgkJCa4uASgQYxPuoO6GDer08sv5LyQlyTMuTqdat1aV48cVcPq0w+WMoCCdbtNGJ9u106m2bXUpJMR+8bvvnFw1Kit+bsJdMTbhrtx9bF68eLFY/cpV6K5Tp45OnDjh0HbixAkFBwcXOMstSRMnTtSECRNyn6empioiIkIDBgxQcHCwU+u9HllZWUpISFD//v3lzbJGuBHGJtyG1SqvsWMlSVfeYZ3zPOT3HcYNHx8ZPXrI6NtXtn795NGunUI8PBQiwPn4uQl3xdiEuyovYzNnFfXVlKvQ3a1bN3399dcObQkJCerWrVuhr/H19ZWvr2++dm9vb7f+F5ijvNSJyoexCZc6f17673+lpKSr9335ZVnGjZPl99VNhdzpDTgdPzfhrhibcFfuPjaLW5tLQ3daWpr27duX+/zgwYPatm2batSoofr162vixIlKSkrSRx99JEn685//rLfeektPPvmkHnjgAa1cuVLz58/XkiVLXPUVAABl4fRpac0aKTHR/Of27ea92sURESGVg9uJAABAxeTS0L1582bFxMTkPs9ZBj5q1CjNmjVLx48f1+HDh3OvN2zYUEuWLNHjjz+u119/XeHh4Xr//fc5LgwAKprjx+0BOzFR2r07f5+wsOLNdNetW/r1AQAAFJNLQ3d0dLSMImYqZs2aVeBrfvzxRydWBQAoc4cO2QN2YqKUZxVUrpYtpd69pago858hIVJkpBm8C/qzxGKRwsOlXr2cXj4AAEBhytU93QCACsAwzFCdd7n4oUOOfSwWqV07e8ju2VOqXTv/e73+ujR8uNk/b/C2/L6VWnx84ed1AwAAlAFCNwDAuQxD+vln+yz2mjXm8vG8PD2lDh3MgB0VJfXoIVWrdvX3jo2VFiyQxo+Xjh61t4eHm4E7NrY0vwkAAECJEboBAKXLapV27LAH7DVrzI3Q8vLxkTp3ti8V795dqlLl2j4vNlYaOlTZq1Zp29Klajd4sLxiYpjhBgAAboHQDQC4PtnZ0tat9uXi69aZR3rl5e8vdetmD9lduphtpcXTU0ZUlJLS09U2KorADQAA3AahGwBQMhkZ0qZN9pC9fr2UlubYp0oV8z7snHuyO3Y0Z7cBAAAqGUI3AKBoFy9KP/xgvyf7+++ly5cd+1Svbu4SnhOy27WTvPgjBgAAgP8jAgA4unDBnL3OuSd740YpK8uxT+3a9qXiUVFSq1aSh4dr6gUAAHBjhG4AqOzOnTPvw84J2Vu3mpuh5VWvnn1n8d69pWbN7MdyAQAAoFCEbgCobE6dsu8qnpgo/fST4xnXkhQZ6RiyGzUiZAMAAFwDQjcAVHTHjtkDdmKieWb2lW680R6we/eW6tcv+zoBAAAqIEI3AFQ0v/1mD9lr1kj79uXv06qVY8iuU6fMywQAAKgMCN0AUJ4ZhhmqcwJ2YqJ0+LBjHw8PczfxnE3PevaUatVySbkAAACVDaEbAMoTm81cHp4TsteskY4fd+zj5WWei50Tsnv0kKpWdU29AAAAlRyhGwDcmdVqbnSWM4u9dq10+rRjHx8fqUsX+3Lxbt2kKlVcUy8AAAAcELoBwJ1kZZlHduWE7HXrpJQUxz7+/lL37vaQ3aWL5OfnmnoBAABQJEI3ALhSRoa0aZN9ufh330np6Y59goLM+7BzQnaHDubsNgAAANweoRsAytLFi9L339tD9vffS5cvO/apXt2+q3hUlNS2rXmfNgAAAMod/i8OAJzpwgVz9jonZG/aZC4hzyskxB6wo6Kkli3NHccBAABQ7hG6AaA0nTtnbnaWc0/21q3mjuN5hYXZA3bv3lLTppLF4pp6AQAA4FSEbgC4HidPmiE7MdF87Nhhnp2dV8OGjiG7YUNCNgAAQCVB6AaAkkhKss9ir1ljnpl9paZN7QG7d28pIqLs6wQAAIBbIHQDQGEMQzp0yD6LvWaNtH9//n6tWzuG7NDQsq8VAAAAbonQDQA5DEPau9cesBMTpSNHHPt4eEjt29s3PuvZU6pZ0zX1AgAAwO0RugFUXjabtHu343Lx5GTHPl5eUqdO9pDdvbtUtapr6gUAAEC5Q+gGUHlYrdL27faQvXatdOaMYx9fX6lLF/ty8W7dpMBA19QLAACAco/QDaDiysoyj+zKuSd73TopNdWxT0CAOXudE7I7d5b8/FxTLwAAACocQjeAiiMjQ9q40b5UfP16KT3dsU9wsHkfdk7I7tBB8vZ2Tb0AAACo8AjdAMqvixelDRvsy8W//94M3nnVqGHfVTwqSmrbVvL0dE29AAAAqHQI3QDKj9RU6bvv7CF70yYpO9uxT2ioPWBHRUktWpg7jgMAAAAuQOgG4L7OnjXvw865J/vHH80dx/MKD7cH7N69pRtvlCwW19QLAAAAXIHQDcB9nDhh7iiec0/2jh3m2dl5NWrkGLIjIwnZAAAAcFuEbgCuk5RkD9iJidIvv+Tv06yZPWD37m3ObAMAAADlhFuE7mnTpumVV15RcnKy2rZtqzfffFOdO3cusO+sWbM0evRohzZfX19dvny5LEoFKjerVZbERIWtWSNLYKAUE1P8TckMQ/rtN8eQfeCAYx+LRWrd2jFkh4SU+tcAAAAAyorLQ/e8efM0YcIETZ8+XV26dFF8fLwGDhyoPXv2KKSQ/9kODg7Wnj17cp9bWFoKON/ChdL48fI6elQdJWnqVHPW+fXXpdjY/P0NQ/r1V3vAXrNGOnLEsY+Hh3TTTfaNz3r2NHcbBwAAACoIl4fuqVOnasyYMbmz19OnT9eSJUv0wQcf6Omnny7wNRaLRXXq1CnLMoHKbeFCafjw/PdXJyWZ7QsWSMOGSbt2OYbsEycc+3t7S5062UN29+7mudkAAABABeXS0J2ZmaktW7Zo4sSJuW0eHh7q16+fNmzYUOjr0tLS1KBBA9lsNt10003617/+pZYtW5ZFyUDlY7VK48fnD9ySve2eeyR/f3O38bx8faWuXe0bn3XtKgUEOL9mAAAAwE24NHSfPn1aVqtVoaGhDu2hoaH6paANlSQ1bdpUH3zwgdq0aaOUlBT95z//Uffu3bVr1y6FF7DBUkZGhjIyMnKfp6amSpKysrKUlZVVit+mdOXU5s41onKwrFolr6NHi+506ZJ06ZKMwEAZ3brJ6NXLfHTqZAbvvBjTcBJ+bsJdMTbhrhibcFflZWwWtz6LYRQ0fVU2jh07prCwMK1fv17dunXLbX/yySeVmJioH3744arvkZWVpebNm2vEiBF68cUX811//vnnNXny5Hztc+bMUQAzboBkGPJJSVHgyZMKOHHC/jh5UoHJyfI/eVL/3969B9d8538cf53cTyOISySRC9lUQkrEJVhbaUWlYTM1adVYQ8pS3Y1idEfXzJbW7C5t7Q912VGrrFnWpaW767pEqK1LXZo2wapLREpQQ0hCXc75/v4469QhJ6Jyck7i+Zj5Duf7+Xy/5/ON93zbV77fz/frVY3TxJHBg3XsxRdl+Lh91goAAADgcteuXdMvfvELXblyRQ2rmDLp1v87btasmby9vXX+nnmf58+fr/acbV9fXyUlJen48eOVtk+aNEkTJkywf7569aoiIyPVt2/fKn8w7nbr1i1t2bJFzz33nHx9fd09HNR1ZWVSYaFMp07JdOqUdOqUTP/7rFOnZKqoeOSveHLECMWmpDzyfoAfi/MmPBW1CU9FbcJT1ZXavHMX9YO4NXT7+fmpc+fOysnJ0YABAyRJVqtVOTk5GjNmTLX2YbFYlJ+fr379+lXa7u/vL/97b2+VLax78j/gHXVlnHCzmzeloiKpsLDy5eLFqrc3maTwcKl1aykmxvbnnSUqSnr6adtD0yq74m0ySRER8nmY14cBLsR5E56K2oSnojbhqTy9Nqs7NrffBzphwgRlZWWpS5cuSk5O1qxZs1RRUWF/mvmwYcPUsmVLTZs2TZI0depUde/eXbGxsSotLdX777+voqIijRw50p2HAbiW1SqdPes8VH/7beWB+G5NmvwQpO8N1tHR98+9vtvs2banlJtMjt9z53V9s2YRuAEAAIBKuD10Dxo0SN99950mT56sc+fOqWPHjtq0aZP94WqnT5+Wl5eXvf/ly5c1atQonTt3TsHBwercubN27dqldu3auesQgEdnGLYnfzsL1adO2a5mV8VsdgzS9wbrR5lOkZlpey3YuHG2gH9HRIQtcFf2nm4AAAAA7g/dkjRmzBint5Nv377d4fPMmTM1c+bMWhgVUMOuXXMeqgsLpQfNCfH2tt3q7SxUh4T8cOXZFTIzpRde0O3cXOVt3KiO6encUg4AAAA8gEeEbqBeuHVLKi52HqrveWBgpUJDnV+tjoiQ3P1kcG9vGSkpOlNRocSUFAI3AAAA8ACEbqC6DMMWnE+erDxUFxdLFkvV+2jUyHmobtXKdos4AAAAgHqD0A3c7coV56H61Cnp+vWqt/f3t4VnZ8E6OLg2jgIAAACAhyB04/Hy/fe28OzsFvDLl6ve3svLdpu3s1AdGmrrAwAAAAAidKO+sVhs75N2drX67NkH76N5c8dQfXewjoyU/PxcfxwAAAAA6gVCN+oWw5AuXnQeqk+ftj3QrCoNGjgP1a1a2doBAAAAoAYQuuF5ysttAdpZsK6oqHp7X18pOtp5sG7a1LWv1gIAAACA/yF0o/bdvGm7Iu0sWF+8WPX2JpMUHu48VIeH8yorAAAAAB6B0I2aZ7VKJSU/hOh7g/WZM7Y+VWnS5P5QfWeJjpYCAmrnWAAAAADgERC68fAMw/aUb2ehuqhIunGj6n2Yzc5DdevWtvdZAwAAAEAdR+hG5a5dc3y11r3B+urVqrf39paioioP1DExUkgI86oBAAAA1HuEbk9ksci0Y4dafvaZTIGB0rPP1vwc5du3peJi56H6/PkH7yM01PmV6shIyYfyAgAAAPB4IxV5mjVrpHHj5PPtt+oiSf/3f1JEhDR7tpSZWf39GIYtON8dpO8O1sXFtndaV6Vhwx8eTnbv0qqV9MQTj3CgAAAAAFD/Ebo9yZo10ksv2QLz3c6csa3/+GPH4H3livNQfeqUdP161d/n728Lz86uVgcHcws4AAAAADwCQrensFikcePuD9zSD+teeUVatuyHudaXL1e9T5PJdpu3s1AdFiZ5edX0kQAAAAAA/ofQ7Sl27pS+/bbqPmVltqvhd2ve3HmojoqS/PxcN2YAAAAAQJUI3Z6ipKR6/YYOtd1qfidYN2jg2nEBAAAAAH40QrenCAurXr8RI6RnnnHpUAAAAAAANYMJvZ7i6adtTyl39uCyO/Ozn366dscFAAAAAPjRCN2ewtvb9low6f7gfefzrFk1/75uAAAAAIDLELo9SWam7bVgLVs6ro+IuP91YQAAAAAAj8ecbk+TmSm98IJu5+Yqb+NGdUxPl8+zz3KFGwAAAADqIEK3J/L2lpGSojMVFUpMSSFwAwAAAEAdxe3lAAAAAAC4CKEbAAAAAAAXeexuLzcMQ5J09epVN4+kardu3dK1a9d09epV+fr6uns4gB21CU9FbcJTUZvwVNQmPFVdqc07mfJOxnTmsQvdZWVlkqTIyEg3jwQAAAAAUNeVlZWpUaNGTttNxoNieT1jtVp19uxZBQUFyXTv+7A9yNWrVxUZGani4mI1bNjQ3cMB7KhNeCpqE56K2oSnojbhqepKbRqGobKyMoWHh8vLy/nM7cfuSreXl5ciIiLcPYxqa9iwoUcXGh5f1CY8FbUJT0VtwlNRm/BUdaE2q7rCfQcPUgMAAAAAwEUI3QAAAAAAuAih20P5+/trypQp8vf3d/dQAAfUJjwVtQlPRW3CU1Gb8FT1rTYfuwepAQAAAABQW7jSDQAAAACAixC6AQAAAABwEUI3AAAAAAAuQuiuRfPmzVOrVq0UEBCgbt266YsvvnDad8mSJTKZTA5LQEBALY4Wj4vPPvtMGRkZCg8Pl8lk0qeffvrAbbZv365OnTrJ399fsbGxWrJkicvHicfPtGnT1LVrVwUFBSkkJEQDBgzQ0aNHH7jd6tWrFR8fr4CAALVv314bNmyohdHicfLnP/9ZHTp0sL8/tkePHtq4cWOV21CXqG3Tp0+XyWTS+PHjq+xHbaI2vP322/dlm/j4+Cq3qU+1SeiuJStXrtSECRM0ZcoUHTx4UImJiUpLS9OFCxecbtOwYUOVlJTYl6KiolocMR4XFRUVSkxM1Lx586rVv7CwUP3799ezzz6rvLw8jR8/XiNHjtTmzZtdPFI8bnbs2KHs7Gzt2bNHW7Zs0a1bt9S3b19VVFQ43WbXrl0aPHiwfvnLX+rLL7/UgAEDNGDAABUUFNTiyFHfRUREaPr06Tpw4ID279+v3r1764UXXtChQ4cq7U9dorbt27dPCxYsUIcOHarsR22iNiUkJDhkm//85z9O+9a72jRQK5KTk43s7Gz7Z4vFYoSHhxvTpk2rtP/ixYuNRo0aVbnPefPmGbGxsYa/v78REhJivPjiizU5ZDyGJBlr166tss/EiRONhIQEh3WDBg0y0tLS7J9Xr15tPPXUU0ZAQIDRpEkTIzU11SgvL3fFkPEYuXDhgiHJ2LFjh9M+L7/8stG/f3+Hdd26dTNGjx5t/8y5E64QHBxs/OUvf6m0jbpEbSorKzOefPJJY8uWLUZKSooxbtw4p32pTdSWKVOmGImJidXuX99qkyvdteDmzZs6cOCA+vTpY1/n5eWlPn36aPfu3U63Ky8vV3R0tCIjI+/7Dfr+/fs1duxYTZ06VUePHtWmTZvUq1cvlx4HIEm7d+92qGVJSktLs9dySUmJBg8erBEjRujIkSPavn27MjMzZfB2QjyiK1euSJKaNGnitM+D6pNzJ2qaxWLRihUrVFFRoR49elTah7pEbcrOzlb//v3vq7nKUJuoTceOHVN4eLhiYmI0ZMgQnT592mnf+labPu4ewOPg4sWLslgsatGihcP6Fi1a6L///W+l28TFxemjjz5Shw4ddOXKFc2YMUM//elPdejQIUVEROj06dMKDAzUz3/+cwUFBSk6OlpJSUm1cTh4zJ07d67SWr569aquX7+ukpIS3b59W5mZmYqOjpYktW/f3h1DRT1itVo1fvx49ezZU0899ZTTfs7q89y5c5LEuRM1Jj8/Xz169ND333+vBg0aaO3atWrXrl2lfalL1JYVK1bo4MGD2rdvX7X6U5uoLd26ddOSJUsUFxenkpISvfPOO3r66adVUFCgoKCg+/rXt9rkSreH6tGjh4YNG6aOHTsqJSVFa9asUfPmzbVgwQJJ0nPPPafo6GjFxMRo6NChWrZsma5du+bmUQNSYmKiUlNT1b59ew0cOFALFy7U5cuX3T0s1HHZ2dkqKCjQihUrHmk/nDtRU+Li4pSXl6e9e/fqV7/6lbKysnT48OEftS/qEjWhuLhY48aN07Jly2rs4bvUJmpKenq6Bg4cqA4dOigtLU0bNmxQaWmpVq1a9aP2V9dqk9BdC5o1ayZvb2+dP3/eYf358+cVGhparX34+voqKSlJx48flyQFBQXp4MGD+vvf/66wsDBNnjxZiYmJKi0trenhAw5CQ0MrreWGDRvKbDbL29tbW7Zs0caNG9WuXTvNmTNHcXFxKiwsdNOIUdeNGTNG69atU25uriIiIqrs66w+75xrOXeipvj5+Sk2NladO3fWtGnTlJiYqNmzZ1fal7pEbThw4IAuXLigTp06ycfHRz4+PtqxY4c++OAD+fj4yGKx3LcNtQl3ady4sdq0aWPPNveqb7VJ6K4Ffn5+6ty5s3JycuzrrFarcnJynM7/upfFYlF+fr7CwsLs63x8fNSnTx+99957+vrrr3Xq1Clt27atxscP3K1Hjx4OtSxJW7Zscahlk8mknj176p133tGXX34pPz8/rV27traHijrOMAyNGTNGa9eu1bZt29S6desHblOd+uTcCVewWq26ceNGpW3UJWpDamqq8vPzlZeXZ1+6dOmiIUOGKC8vT97e3vdtQ23CXcrLy3XixAmHbHO3+labzOmuJRMmTFBWVpa6dOmi5ORkzZo1SxUVFRo+fLgkadiwYWrZsqWmTZsmSZo6daq6d++u2NhYlZaW6v3331dRUZFGjhwpSVq3bp1OnjypXr16KTg4WBs2bJDValVcXJzbjhF1U3l5ucNvGQsLC5WXl6cmTZooKipKkyZN0pkzZ7R06VJJ0muvvaa5c+dq4sSJGjFihLZt26ZVq1Zp/fr1kqS9e/cqJydHffv2VUhIiPbu3avvvvtObdu2dcvxoe7Kzs7W8uXL9Y9//ENBQUH2eVyNGjWS2WyWdP+5c9y4cUpJSdGf/vQn9e/fXytWrND+/fv14YcfSuLciZoxadIkpaenKyoqSmVlZVq+fLm2b99uf3UidQl3CAoKuu+ZF4GBgWratKl9PbUJd/nNb36jjIwMRUdH6+zZs5oyZYq8vb01ePBgSY9Bbbr78emPkzlz5hhRUVGGn5+fkZycbOzZs8felpKSYmRlZdk/jx8/3t63RYsWRr9+/YyDBw/a23fu3GmkpKQYwcHBhtlsNjp06GCsXLmyNg8H9URubq4h6b7lTj1mZWUZKSkp923TsWNHw8/Pz4iJiTEWL15sbzt8+LCRlpZmNG/e3PD39zfatGljzJkzp/YOCPVGZXUpyaHe7j13GoZhrFq1ymjTpo3h5+dnJCQkGOvXr7e3ce5ETRgxYoQRHR1t+Pn5Gc2bNzdSU1ONf//73/Z26hKe4t5XhlGbcJdBgwYZYWFhhp+fn9GyZUtj0KBBxvHjx+3t9b02TYbBe3wAAAAAAHAF5nQDAAAAAOAihG4AAAAAAFyE0A0AAAAAgIsQugEAAAAAcBFCNwAAAAAALkLoBgAAAADARQjdAAAAAAC4CKEbAAAAAAAXIXQDAFAPHT16VKGhoSorK3P3UB5Jq1atNGvWrGr17d69uz755BPXDggAgIdE6AYAwEVMJlOVyzPPPPPAdunhgucdkyZN0uuvv66goKCaPzAP9bvf/U6//e1vZbVa3T0UAADsfNw9AAAA6quSkhL731euXKnJkyfr6NGj9nU3b96Un5+fJKm4uFjJycnaunWrEhISJMne9rBOnz6tdevWac6cOY8w+ronPT1dI0eO1MaNG9W/f393DwcAAElc6QYAwGVCQ0PtS6NGjWQymRzWRUVF2f/evHlzSVLTpk3t65o0afKjvnfVqlVKTExUy5Yt7euKioqUkZGh4OBgBQYGKiEhQRs2bLC3FxQUKD09XQ0aNFCLFi00dOhQXbx40d5utVr13nvvKTY2Vv7+/oqKitIf/vAHe3t+fr569+4ts9mspk2b6tVXX1V5ebm9/ZVXXtGAAQM0Y8YMhYWFqWnTpsrOztatW7fsfS5cuKCMjAyZzWa1bt1ay5YtczguwzD09ttvKyoqSv7+/goPD9fYsWPt7d7e3urXr59WrFjxo35uAAC4AqEbAIB6ZufOnerSpYvDuuzsbN24cUOfffaZ8vPz9e6776pBgwaSpNLSUvXu3VtJSUnav3+/Nm3apPPnz+vll1+2bz9p0iRNnz5db731lg4fPqzly5erRYsWkqSKigqlpaUpODhY+/bt0+rVq7V161aNGTPGYQy5ubk6ceKEcnNz9de//lVLlizRkiVL7O2vvPKKiouLlZubq48//ljz58/XhQsX7O2ffPKJZs6cqQULFujYsWP69NNP1b59e4fvSE5O1s6dO2vk5wgAQE3g9nIAAOqZoqKi+0L36dOn9eKLL9pDakxMjL1t7ty5SkpK0h//+Ef7uo8++kiRkZH65ptvFBYWptmzZ2vu3LnKysqSJP3kJz/Rz372M0nS8uXL9f3332vp0qUKDAy07zMjI0PvvvuuPZwHBwdr7ty58vb2Vnx8vPr376+cnByNGjVK33zzjTZu3KgvvvhCXbt2lSQtWrRIbdu2dTiG0NBQ9enTR76+voqKilJycrLDcYaHh6u4uFhWq1VeXlxbAAC4H/81AgCgnrl+/boCAgIc1o0dO1a///3v1bNnT02ZMkVff/21ve2rr75Sbm6uGjRoYF/i4+MlSSdOnNCRI0d048YNpaamVvp9R44cUWJioj1wS1LPnj1ltVod5rAnJCTI29vb/jksLMx+JfvIkSPy8fFR586d7e3x8fFq3Lix/fPAgQN1/fp1xcTEaNSoUVq7dq1u377tMBaz2Syr1aobN25U98cFAIBLEboBAKhnmjVrpsuXLzusGzlypE6ePKmhQ4cqPz9fXbp0sT9orby8XBkZGcrLy3NYjh07pl69eslsNtfIuHx9fR0+m0ymh3rSeGRkpI4ePar58+fLbDbr17/+tXr16uUwL/zSpUsKDAyssTEDAPCoCN0AANQzSUlJOnz48H3rIyMj9dprr2nNmjV64403tHDhQklSp06ddOjQIbVq1UqxsbEOS2BgoJ588kmZzWbl5ORU+n1t27bVV199pYqKCvu6zz//XF5eXoqLi6vWmOPj43X79m0dOHDAvu7o0aMqLS116Gc2m5WRkaEPPvhA27dv1+7du5Wfn29vLygoUFJSUrW+EwCA2kDoBgCgDjhz5sx9V6LvvZp9R1pamnbv3i2LxWJfN378eG3evFmFhYU6ePCgcnNz7fOls7OzdenSJQ0ePFj79u3TiRMntHnzZg0fPlwWi0UBAQF68803NXHiRC1dulQnTpzQnj17tGjRIknSkCFDFBAQoKysLBUUFCg3N1evv/66hg4dap/P/SBxcXF6/vnnNXr0aO3du1cHDhzQyJEjHa5YL1myRIsWLVJBQYFOnjypv/3tbzKbzYqOjrb32blzp/r27fvQP18AAFyF0A0AQB0wY8YMJSUlOSzr16+vtG96erp8fHy0detW+zqLxaLs7Gy1bdtWzz//vNq0aaP58+dLsj187PPPP5fFYlHfvn3Vvn17jR8/Xo0bN7Y/jOytt97SG2+8ocmTJ6tt27YaNGiQfT72E088oc2bN+vSpUvq2rWrXnrpJaWmpmru3LkPdYyLFy9WeHi4UlJSlJmZqVdffVUhISH29saNG2vhwoXq2bOnOnTooK1bt+pf//qXmjZtKsn2i4ldu3Zp+PDhD/W9AAC4kskwDMPdgwAAADVr3rx5+uc//6nNmze7eyi15s0339Tly5f14YcfunsoAADY8cowAADqodGjR6u0tFRlZWUKCgpy93BqRUhIiCZMmODuYQAA4IAr3QAAAAAAuAhzugEAAAAAcBFCNwAAAAAALkLoBgAAAADARQjdAAAAAAC4CKEbAAAAAAAXIXQDAAAAAOAihG4AAAAAAFyE0A0AAAAAgIsQugEAAAAAcBFCNwAAAAAALvL/DqH9pkKY0vQAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 1000x600 with 2 Axes>"
       ]
@@ -144,10 +144,244 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "a92dcf86-d0ae-4f5c-937f-aeac45ac0dea",
    "metadata": {},
    "outputs": [],
+   "source": [
+    "details = [k.replace(\" \", \"_\").replace(\"(\", \"\").replace(\")\", \"\").replace(\".\", \"_\") for k in configurations.keys()]\n",
+    "details = [os.path.join(\"./experiments/\",e, \"details.csv\") for e in details if \"_ttl\" in e]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "0ffb1366-83ea-49ab-83ca-945ed993ef3f",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['./experiments/No_Refresh_0_5s_ttl/details.csv',\n",
+       " './experiments/No_Refresh_1_0s_ttl/details.csv',\n",
+       " './experiments/No_Refresh_2_0s_ttl/details.csv',\n",
+       " './experiments/No_Refresh_3_0s_ttl/details.csv',\n",
+       " './experiments/No_Refresh_4_0s_ttl/details.csv',\n",
+       " './experiments/No_Refresh_5_0s_ttl/details.csv']"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "details"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "6e48f78f-15a3-4788-8ac9-6ad1fabbee26",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0.5s</th>\n",
+       "      <th>1.0s</th>\n",
+       "      <th>2.0s</th>\n",
+       "      <th>3.0s</th>\n",
+       "      <th>4.0s</th>\n",
+       "      <th>5.0s</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>obj_id</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>95</th>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>96</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>97</th>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>98</th>\n",
+       "      <td>37</td>\n",
+       "      <td>37</td>\n",
+       "      <td>37</td>\n",
+       "      <td>37</td>\n",
+       "      <td>37</td>\n",
+       "      <td>37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>99</th>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>99 rows × 6 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        0.5s  1.0s  2.0s  3.0s  4.0s  5.0s\n",
+       "obj_id                                    \n",
+       "1          1     1     1     1     1     1\n",
+       "2          3     3     3     3     3     3\n",
+       "3          1     1     1     1     1     1\n",
+       "4          1     1     1     1     1     1\n",
+       "5          2     2     2     2     2     2\n",
+       "...      ...   ...   ...   ...   ...   ...\n",
+       "95         2     2     2     2     2     2\n",
+       "96         1     1     1     1     1     1\n",
+       "97         1     1     1     1     1     1\n",
+       "98        37    37    37    37    37    37\n",
+       "99         4     4     4     4     4     4\n",
+       "\n",
+       "[99 rows x 6 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pd.concat([pd.read_csv(file,index_col=\"obj_id\")['lambda'].rename(f\"{'.'.join(file.split('/')[2].split(\"_\")[2:4])}\") for file in details], axis=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "3e0ddc4a-bede-4921-8ce8-427ef028e19e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "43375"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sum(pd.read_csv(\"./experiments/No_Refresh_0_5s_ttl/details.csv\",index_col=\"obj_id\")['access_count'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e324fbe8-24a6-49e8-96b9-d1a1a49f9644",
+   "metadata": {},
+   "outputs": [],
    "source": []
   }
  ],
diff --git a/aoi_cache_simulation.ipynb b/aoi_cache_simulation.ipynb
index 88eb532..9271c24 100644
--- a/aoi_cache_simulation.ipynb
+++ b/aoi_cache_simulation.ipynb
@@ -24,7 +24,7 @@
     "# Constants\n",
     "SEED = 42\n",
     "DATABASE_OBJECTS = 100 # Number of objects in the database\n",
-    "ACCESS_COUNT_LIMIT = 10   # Total time to run the simulation\n",
+    "ACCESS_COUNT_LIMIT = 100   # Total time to run the simulation\n",
     "EXPERIMENT_BASE_DIR = \"./experiments/\"\n",
     "TEMP_BASE_DIR = \"./.aoi_cache/\"\n",
     "\n",
@@ -130,7 +130,7 @@
     "            self.mu_values = {i: 0 for i in range(1,DATABASE_OBJECTS + 1)}    \n",
     "        else:\n",
     "            self.mu_values = {i: np.random.uniform(1, MAX_REFRESH_RATE) for i in range(1, DATABASE_OBJECTS + 1)}\n",
-    "        self.next_request = {i: np.random.exponential(self.lambda_values[i]) for i in range(1, DATABASE_OBJECTS + 1)}\n",
+    "        self.next_request = {i: np.random.exponential(1/self.lambda_values[i]) for i in range(1, DATABASE_OBJECTS + 1)}\n",
     "\n",
     "\n",
     "    def get_object(self, obj_id):\n",
@@ -178,7 +178,7 @@
     "            obj = self.db.get_object(obj_id)\n",
     "            \n",
     "            # If the cache is full, evict the oldest object\n",
-    "            if len(self.storage) >= CACHE_CAPACITY:\n",
+    "            if len(self.storage) > CACHE_CAPACITY:\n",
     "                if self.cache_type == CacheType.LRU:\n",
     "                    self.evict_oldest()\n",
     "                elif self.cache_type == CacheType.RANDOM_EVICTION:\n",
@@ -192,7 +192,7 @@
     "                self.ttl[obj_id] = 0\n",
     "            self.age[obj_id] = 0\n",
     "            if MAX_REFRESH_RATE != 0:\n",
-    "                self.next_refresh[obj_id] = env.now + np.random.exponential(self.db.mu_values[obj_id])  # Schedule refresh\n",
+    "                self.next_refresh[obj_id] = env.now + np.random.exponential(1/self.db.mu_values[obj_id])  # Schedule refresh\n",
     "\n",
     "        \n",
     "    def evict_oldest(self):\n",
@@ -264,7 +264,7 @@
     "                if env.now >= cache.next_refresh[obj_id]:\n",
     "                    cache.refresh_object(obj_id)\n",
     "                    # Schedule the next refresh based on the object's mu\n",
-    "                    cache.next_refresh[obj_id] = env.now + np.random.exponential(cache.db.mu_values[obj_id])\n",
+    "                    cache.next_refresh[obj_id] = env.now + np.random.exponential(1/cache.db.mu_values[obj_id])\n",
     "        \n",
     "        cache.record_cache_state()  # Record cache state at each time step\n",
     "        yield env.timeout(1)  # Run every second\n"
@@ -279,8 +279,7 @@
    "source": [
     "def client_request_process(env, cache, event):\n",
     "    \"\"\"Client process that makes requests for objects from the cache.\"\"\"\n",
-    "    lowest_lambda_object = max(cache.db.lambda_values.items(), key=lambda x: x[1])\n",
-    "    lowest_lambda_object = [lowest_lambda_object] if isinstance(lowest_lambda_object, int) else lowest_lambda_object\n",
+    "    last_print = 0\n",
     "    while True:\n",
     "        obj_id, next_request = min(cache.db.next_request.items(), key=lambda x: x[1])\n",
     "        yield env.timeout(next_request - env.now)\n",
@@ -289,11 +288,14 @@
     "            cache.get(obj_id)\n",
     "            \n",
     "            # print(f\"[{env.now:.2f}] Client: Schedule next request for {obj_id}\")\n",
-    "            next_request = env.now + np.random.exponential(cache.db.lambda_values[obj_id])\n",
+    "            next_request = env.now + np.random.exponential(1/cache.db.lambda_values[obj_id])\n",
     "            cache.request_log[obj_id].append(next_request)\n",
     "            cache.db.next_request[obj_id] = next_request\n",
-    "        if all(cache.access_count[obj] >= ACCESS_COUNT_LIMIT for obj in lowest_lambda_object):\n",
-    "            event.succeed()"
+    "        if all(access_count >= ACCESS_COUNT_LIMIT for access_count in cache.access_count.values()):\n",
+    "            event.succeed()\n",
+    "        if (int(env.now) % 5) == 0 and int(env.now) != last_print:\n",
+    "            print(f\"[{env.now:.2f}] Client: Least accessed object was accessed {min(cache.access_count.values())} times.\")\n",
+    "            last_print = int(env.now)"
    ]
   },
   {
@@ -323,8 +325,32 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 441 ms, sys: 62.3 ms, total: 503 ms\n",
-      "Wall time: 502 ms\n"
+      "[5.00] Client: Least accessed object was accessed 1 times.\n",
+      "[10.00] Client: Least accessed object was accessed 2 times.\n",
+      "[15.00] Client: Least accessed object was accessed 8 times.\n",
+      "[20.00] Client: Least accessed object was accessed 13 times.\n",
+      "[25.00] Client: Least accessed object was accessed 18 times.\n",
+      "[30.01] Client: Least accessed object was accessed 22 times.\n",
+      "[35.00] Client: Least accessed object was accessed 27 times.\n",
+      "[40.00] Client: Least accessed object was accessed 30 times.\n",
+      "[45.00] Client: Least accessed object was accessed 37 times.\n",
+      "[50.00] Client: Least accessed object was accessed 40 times.\n",
+      "[55.00] Client: Least accessed object was accessed 42 times.\n",
+      "[60.00] Client: Least accessed object was accessed 48 times.\n",
+      "[65.00] Client: Least accessed object was accessed 51 times.\n",
+      "[70.00] Client: Least accessed object was accessed 55 times.\n",
+      "[75.02] Client: Least accessed object was accessed 57 times.\n",
+      "[80.00] Client: Least accessed object was accessed 64 times.\n",
+      "[85.00] Client: Least accessed object was accessed 67 times.\n",
+      "[90.00] Client: Least accessed object was accessed 69 times.\n",
+      "[95.01] Client: Least accessed object was accessed 73 times.\n",
+      "[100.00] Client: Least accessed object was accessed 80 times.\n",
+      "[105.00] Client: Least accessed object was accessed 84 times.\n",
+      "[110.00] Client: Least accessed object was accessed 89 times.\n",
+      "[115.00] Client: Least accessed object was accessed 95 times.\n",
+      "[120.00] Client: Least accessed object was accessed 98 times.\n",
+      "CPU times: user 375 ms, sys: 63.7 ms, total: 438 ms\n",
+      "Wall time: 437 ms\n"
      ]
     }
    ],
@@ -351,106 +377,106 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Object 1: Hit Rate = 0.83, Average Age = 2.60\n",
-      "Object 2: Hit Rate = 0.58, Average Age = 2.52\n",
-      "Object 3: Hit Rate = 0.83, Average Age = 2.41\n",
-      "Object 4: Hit Rate = 0.84, Average Age = 2.40\n",
-      "Object 5: Hit Rate = 0.72, Average Age = 2.47\n",
-      "Object 6: Hit Rate = 0.82, Average Age = 2.39\n",
-      "Object 7: Hit Rate = 0.50, Average Age = 2.74\n",
-      "Object 8: Hit Rate = 0.83, Average Age = 2.43\n",
-      "Object 9: Hit Rate = 0.84, Average Age = 2.51\n",
-      "Object 10: Hit Rate = 0.83, Average Age = 2.58\n",
-      "Object 11: Hit Rate = 0.71, Average Age = 2.42\n",
-      "Object 12: Hit Rate = 0.84, Average Age = 2.53\n",
-      "Object 13: Hit Rate = 0.83, Average Age = 2.55\n",
-      "Object 14: Hit Rate = 0.83, Average Age = 2.50\n",
-      "Object 15: Hit Rate = 0.71, Average Age = 2.52\n",
-      "Object 16: Hit Rate = 0.72, Average Age = 2.78\n",
-      "Object 17: Hit Rate = 0.83, Average Age = 2.50\n",
-      "Object 18: Hit Rate = 0.84, Average Age = 2.49\n",
-      "Object 19: Hit Rate = 0.63, Average Age = 2.56\n",
-      "Object 20: Hit Rate = 0.84, Average Age = 2.52\n",
-      "Object 21: Hit Rate = 0.84, Average Age = 2.48\n",
-      "Object 22: Hit Rate = 0.83, Average Age = 2.49\n",
-      "Object 23: Hit Rate = 0.83, Average Age = 2.47\n",
-      "Object 24: Hit Rate = 0.71, Average Age = 2.55\n",
-      "Object 25: Hit Rate = 0.84, Average Age = 2.38\n",
-      "Object 26: Hit Rate = 0.83, Average Age = 2.58\n",
-      "Object 27: Hit Rate = 0.84, Average Age = 2.42\n",
-      "Object 28: Hit Rate = 0.48, Average Age = 2.58\n",
-      "Object 29: Hit Rate = 0.83, Average Age = 2.44\n",
-      "Object 30: Hit Rate = 0.83, Average Age = 2.60\n",
-      "Object 31: Hit Rate = 0.83, Average Age = 2.44\n",
-      "Object 32: Hit Rate = 0.51, Average Age = 2.55\n",
-      "Object 33: Hit Rate = 0.83, Average Age = 2.44\n",
-      "Object 34: Hit Rate = 0.49, Average Age = 2.62\n",
-      "Object 35: Hit Rate = 0.83, Average Age = 2.41\n",
-      "Object 36: Hit Rate = 0.83, Average Age = 2.44\n",
-      "Object 37: Hit Rate = 0.85, Average Age = 2.38\n",
-      "Object 38: Hit Rate = 0.63, Average Age = 2.81\n",
-      "Object 39: Hit Rate = 0.41, Average Age = 2.51\n",
-      "Object 40: Hit Rate = 0.84, Average Age = 2.50\n",
-      "Object 41: Hit Rate = 0.56, Average Age = 2.57\n",
-      "Object 42: Hit Rate = 0.57, Average Age = 2.68\n",
-      "Object 43: Hit Rate = 0.74, Average Age = 2.40\n",
-      "Object 44: Hit Rate = 0.84, Average Age = 2.49\n",
-      "Object 45: Hit Rate = 0.82, Average Age = 2.45\n",
-      "Object 46: Hit Rate = 0.83, Average Age = 2.52\n",
-      "Object 47: Hit Rate = 0.30, Average Age = 2.94\n",
-      "Object 48: Hit Rate = 0.83, Average Age = 2.60\n",
-      "Object 49: Hit Rate = 0.82, Average Age = 2.52\n",
-      "Object 50: Hit Rate = 0.83, Average Age = 2.50\n",
-      "Object 51: Hit Rate = 0.49, Average Age = 2.35\n",
-      "Object 52: Hit Rate = 0.34, Average Age = 2.17\n",
-      "Object 53: Hit Rate = 0.84, Average Age = 2.54\n",
-      "Object 54: Hit Rate = 0.84, Average Age = 2.58\n",
-      "Object 55: Hit Rate = 0.83, Average Age = 2.42\n",
-      "Object 56: Hit Rate = 0.84, Average Age = 2.53\n",
-      "Object 57: Hit Rate = 0.83, Average Age = 2.38\n",
-      "Object 58: Hit Rate = 0.17, Average Age = 3.00\n",
-      "Object 59: Hit Rate = 0.70, Average Age = 2.51\n",
-      "Object 60: Hit Rate = 0.83, Average Age = 2.47\n",
-      "Object 61: Hit Rate = 0.22, Average Age = 0.60\n",
-      "Object 62: Hit Rate = 0.84, Average Age = 2.62\n",
-      "Object 63: Hit Rate = 0.82, Average Age = 2.41\n",
-      "Object 64: Hit Rate = 0.72, Average Age = 2.43\n",
-      "Object 65: Hit Rate = 0.83, Average Age = 2.58\n",
-      "Object 66: Hit Rate = 0.32, Average Age = 2.78\n",
-      "Object 67: Hit Rate = 0.83, Average Age = 2.48\n",
-      "Object 68: Hit Rate = 0.00, Average Age = 0.00\n",
-      "Object 69: Hit Rate = 0.83, Average Age = 2.46\n",
-      "Object 70: Hit Rate = 0.83, Average Age = 2.56\n",
-      "Object 71: Hit Rate = 0.73, Average Age = 2.65\n",
-      "Object 72: Hit Rate = 0.83, Average Age = 2.49\n",
-      "Object 73: Hit Rate = 0.82, Average Age = 2.43\n",
-      "Object 74: Hit Rate = 0.83, Average Age = 2.48\n",
-      "Object 75: Hit Rate = 0.58, Average Age = 2.73\n",
-      "Object 76: Hit Rate = 0.73, Average Age = 2.58\n",
-      "Object 77: Hit Rate = 0.72, Average Age = 2.49\n",
-      "Object 78: Hit Rate = 0.65, Average Age = 2.56\n",
-      "Object 79: Hit Rate = 0.19, Average Age = 2.56\n",
-      "Object 80: Hit Rate = 0.83, Average Age = 2.65\n",
-      "Object 81: Hit Rate = 0.82, Average Age = 2.45\n",
-      "Object 82: Hit Rate = 0.51, Average Age = 2.56\n",
-      "Object 83: Hit Rate = 0.70, Average Age = 2.72\n",
-      "Object 84: Hit Rate = 0.84, Average Age = 2.47\n",
-      "Object 85: Hit Rate = 0.83, Average Age = 2.32\n",
-      "Object 86: Hit Rate = 0.71, Average Age = 2.60\n",
-      "Object 87: Hit Rate = 0.83, Average Age = 2.64\n",
-      "Object 88: Hit Rate = 0.69, Average Age = 2.43\n",
-      "Object 89: Hit Rate = 0.83, Average Age = 2.51\n",
-      "Object 90: Hit Rate = 0.83, Average Age = 2.54\n",
-      "Object 91: Hit Rate = 0.73, Average Age = 2.26\n",
-      "Object 92: Hit Rate = 0.72, Average Age = 2.32\n",
-      "Object 93: Hit Rate = 0.64, Average Age = 2.51\n",
-      "Object 94: Hit Rate = 0.83, Average Age = 2.51\n",
-      "Object 95: Hit Rate = 0.72, Average Age = 2.37\n",
-      "Object 96: Hit Rate = 0.85, Average Age = 2.44\n",
-      "Object 97: Hit Rate = 0.83, Average Age = 2.54\n",
-      "Object 98: Hit Rate = 0.22, Average Age = 3.40\n",
-      "Object 99: Hit Rate = 0.57, Average Age = 2.32\n",
-      "Object 100: Hit Rate = 0.71, Average Age = 2.35\n"
+      "Object 1: Hit Rate = 0.83, Average Age = 2.36\n",
+      "Object 2: Hit Rate = 0.94, Average Age = 2.61\n",
+      "Object 3: Hit Rate = 0.83, Average Age = 2.37\n",
+      "Object 4: Hit Rate = 0.81, Average Age = 2.33\n",
+      "Object 5: Hit Rate = 0.91, Average Age = 2.44\n",
+      "Object 6: Hit Rate = 0.82, Average Age = 2.43\n",
+      "Object 7: Hit Rate = 0.96, Average Age = 2.48\n",
+      "Object 8: Hit Rate = 0.84, Average Age = 2.15\n",
+      "Object 9: Hit Rate = 0.82, Average Age = 2.61\n",
+      "Object 10: Hit Rate = 0.82, Average Age = 2.59\n",
+      "Object 11: Hit Rate = 0.91, Average Age = 2.54\n",
+      "Object 12: Hit Rate = 0.86, Average Age = 2.43\n",
+      "Object 13: Hit Rate = 0.85, Average Age = 2.64\n",
+      "Object 14: Hit Rate = 0.83, Average Age = 2.28\n",
+      "Object 15: Hit Rate = 0.91, Average Age = 2.51\n",
+      "Object 16: Hit Rate = 0.90, Average Age = 2.49\n",
+      "Object 17: Hit Rate = 0.83, Average Age = 2.54\n",
+      "Object 18: Hit Rate = 0.83, Average Age = 2.52\n",
+      "Object 19: Hit Rate = 0.93, Average Age = 2.49\n",
+      "Object 20: Hit Rate = 0.83, Average Age = 2.56\n",
+      "Object 21: Hit Rate = 0.84, Average Age = 2.55\n",
+      "Object 22: Hit Rate = 0.86, Average Age = 2.29\n",
+      "Object 23: Hit Rate = 0.85, Average Age = 2.68\n",
+      "Object 24: Hit Rate = 0.92, Average Age = 2.58\n",
+      "Object 25: Hit Rate = 0.83, Average Age = 2.70\n",
+      "Object 26: Hit Rate = 0.84, Average Age = 2.55\n",
+      "Object 27: Hit Rate = 0.84, Average Age = 2.73\n",
+      "Object 28: Hit Rate = 0.96, Average Age = 2.54\n",
+      "Object 29: Hit Rate = 0.83, Average Age = 2.98\n",
+      "Object 30: Hit Rate = 0.82, Average Age = 2.40\n",
+      "Object 31: Hit Rate = 0.81, Average Age = 2.57\n",
+      "Object 32: Hit Rate = 0.95, Average Age = 2.48\n",
+      "Object 33: Hit Rate = 0.82, Average Age = 2.29\n",
+      "Object 34: Hit Rate = 0.95, Average Age = 2.56\n",
+      "Object 35: Hit Rate = 0.85, Average Age = 2.45\n",
+      "Object 36: Hit Rate = 0.80, Average Age = 2.46\n",
+      "Object 37: Hit Rate = 0.85, Average Age = 2.45\n",
+      "Object 38: Hit Rate = 0.94, Average Age = 2.54\n",
+      "Object 39: Hit Rate = 0.97, Average Age = 2.46\n",
+      "Object 40: Hit Rate = 0.84, Average Age = 2.63\n",
+      "Object 41: Hit Rate = 0.95, Average Age = 2.44\n",
+      "Object 42: Hit Rate = 0.95, Average Age = 2.53\n",
+      "Object 43: Hit Rate = 0.90, Average Age = 2.32\n",
+      "Object 44: Hit Rate = 0.81, Average Age = 2.37\n",
+      "Object 45: Hit Rate = 0.84, Average Age = 2.45\n",
+      "Object 46: Hit Rate = 0.84, Average Age = 2.49\n",
+      "Object 47: Hit Rate = 0.98, Average Age = 2.40\n",
+      "Object 48: Hit Rate = 0.85, Average Age = 2.44\n",
+      "Object 49: Hit Rate = 0.84, Average Age = 2.64\n",
+      "Object 50: Hit Rate = 0.82, Average Age = 2.62\n",
+      "Object 51: Hit Rate = 0.96, Average Age = 2.51\n",
+      "Object 52: Hit Rate = 0.98, Average Age = 2.35\n",
+      "Object 53: Hit Rate = 0.83, Average Age = 2.74\n",
+      "Object 54: Hit Rate = 0.83, Average Age = 2.54\n",
+      "Object 55: Hit Rate = 0.83, Average Age = 2.57\n",
+      "Object 56: Hit Rate = 0.84, Average Age = 2.62\n",
+      "Object 57: Hit Rate = 0.83, Average Age = 2.48\n",
+      "Object 58: Hit Rate = 0.99, Average Age = 2.38\n",
+      "Object 59: Hit Rate = 0.89, Average Age = 2.43\n",
+      "Object 60: Hit Rate = 0.84, Average Age = 2.16\n",
+      "Object 61: Hit Rate = 0.99, Average Age = 2.30\n",
+      "Object 62: Hit Rate = 0.85, Average Age = 2.32\n",
+      "Object 63: Hit Rate = 0.81, Average Age = 2.54\n",
+      "Object 64: Hit Rate = 0.91, Average Age = 2.31\n",
+      "Object 65: Hit Rate = 0.86, Average Age = 2.50\n",
+      "Object 66: Hit Rate = 0.98, Average Age = 2.44\n",
+      "Object 67: Hit Rate = 0.86, Average Age = 2.21\n",
+      "Object 68: Hit Rate = 1.00, Average Age = 2.15\n",
+      "Object 69: Hit Rate = 0.82, Average Age = 2.19\n",
+      "Object 70: Hit Rate = 0.83, Average Age = 2.38\n",
+      "Object 71: Hit Rate = 0.91, Average Age = 2.30\n",
+      "Object 72: Hit Rate = 0.82, Average Age = 2.62\n",
+      "Object 73: Hit Rate = 0.84, Average Age = 2.47\n",
+      "Object 74: Hit Rate = 0.85, Average Age = 2.21\n",
+      "Object 75: Hit Rate = 0.93, Average Age = 2.32\n",
+      "Object 76: Hit Rate = 0.91, Average Age = 2.56\n",
+      "Object 77: Hit Rate = 0.91, Average Age = 2.46\n",
+      "Object 78: Hit Rate = 0.94, Average Age = 2.57\n",
+      "Object 79: Hit Rate = 0.99, Average Age = 2.34\n",
+      "Object 80: Hit Rate = 0.83, Average Age = 2.40\n",
+      "Object 81: Hit Rate = 0.83, Average Age = 2.29\n",
+      "Object 82: Hit Rate = 0.96, Average Age = 2.45\n",
+      "Object 83: Hit Rate = 0.91, Average Age = 2.42\n",
+      "Object 84: Hit Rate = 0.85, Average Age = 2.41\n",
+      "Object 85: Hit Rate = 0.81, Average Age = 2.21\n",
+      "Object 86: Hit Rate = 0.90, Average Age = 2.43\n",
+      "Object 87: Hit Rate = 0.85, Average Age = 2.51\n",
+      "Object 88: Hit Rate = 0.90, Average Age = 2.58\n",
+      "Object 89: Hit Rate = 0.84, Average Age = 2.44\n",
+      "Object 90: Hit Rate = 0.82, Average Age = 2.24\n",
+      "Object 91: Hit Rate = 0.90, Average Age = 2.64\n",
+      "Object 92: Hit Rate = 0.90, Average Age = 2.32\n",
+      "Object 93: Hit Rate = 0.94, Average Age = 2.51\n",
+      "Object 94: Hit Rate = 0.83, Average Age = 2.57\n",
+      "Object 95: Hit Rate = 0.91, Average Age = 2.34\n",
+      "Object 96: Hit Rate = 0.85, Average Age = 2.22\n",
+      "Object 97: Hit Rate = 0.83, Average Age = 2.79\n",
+      "Object 98: Hit Rate = 0.99, Average Age = 2.24\n",
+      "Object 99: Hit Rate = 0.95, Average Age = 2.49\n",
+      "Object 100: Hit Rate = 0.91, Average Age = 2.49\n"
      ]
     }
    ],
@@ -487,14 +513,6 @@
     "avg_age = {obj_id: cache.cumulative_age[obj_id] / max(1, cache.hits[obj_id]) for obj_id in range(1, DATABASE_OBJECTS + 1)}"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "cd8d0897-2481-47c0-8b5a-87bdab571b90",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": 13,
@@ -534,53 +552,53 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>664</td>\n",
-       "      <td>550</td>\n",
-       "      <td>114</td>\n",
+       "      <td>122</td>\n",
+       "      <td>101</td>\n",
+       "      <td>21</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>58.49</td>\n",
-       "      <td>2.596364</td>\n",
+       "      <td>93.98</td>\n",
+       "      <td>2.356436</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>212</td>\n",
-       "      <td>124</td>\n",
-       "      <td>88</td>\n",
+       "      <td>382</td>\n",
+       "      <td>359</td>\n",
+       "      <td>23</td>\n",
        "      <td>0</td>\n",
        "      <td>3</td>\n",
-       "      <td>83.21</td>\n",
-       "      <td>2.524194</td>\n",
+       "      <td>82.68</td>\n",
+       "      <td>2.607242</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>673</td>\n",
-       "      <td>560</td>\n",
-       "      <td>113</td>\n",
+       "      <td>127</td>\n",
+       "      <td>105</td>\n",
+       "      <td>22</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>84.11</td>\n",
-       "      <td>2.405357</td>\n",
+       "      <td>81.42</td>\n",
+       "      <td>2.371429</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>711</td>\n",
-       "      <td>598</td>\n",
        "      <td>113</td>\n",
+       "      <td>92</td>\n",
+       "      <td>21</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>72.17</td>\n",
-       "      <td>2.401338</td>\n",
+       "      <td>90.98</td>\n",
+       "      <td>2.326087</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
-       "      <td>345</td>\n",
-       "      <td>249</td>\n",
-       "      <td>96</td>\n",
+       "      <td>244</td>\n",
+       "      <td>222</td>\n",
+       "      <td>22</td>\n",
        "      <td>0</td>\n",
        "      <td>2</td>\n",
-       "      <td>82.43</td>\n",
-       "      <td>2.469880</td>\n",
+       "      <td>81.90</td>\n",
+       "      <td>2.436937</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>...</th>\n",
@@ -594,53 +612,53 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>95</th>\n",
-       "      <td>351</td>\n",
-       "      <td>252</td>\n",
-       "      <td>99</td>\n",
+       "      <td>257</td>\n",
+       "      <td>234</td>\n",
+       "      <td>23</td>\n",
        "      <td>0</td>\n",
        "      <td>2</td>\n",
-       "      <td>84.66</td>\n",
-       "      <td>2.373016</td>\n",
+       "      <td>84.89</td>\n",
+       "      <td>2.341880</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>96</th>\n",
-       "      <td>717</td>\n",
-       "      <td>607</td>\n",
-       "      <td>110</td>\n",
+       "      <td>139</td>\n",
+       "      <td>118</td>\n",
+       "      <td>21</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>83.28</td>\n",
-       "      <td>2.436573</td>\n",
+       "      <td>83.46</td>\n",
+       "      <td>2.220339</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>97</th>\n",
-       "      <td>664</td>\n",
-       "      <td>553</td>\n",
-       "      <td>111</td>\n",
+       "      <td>127</td>\n",
+       "      <td>106</td>\n",
+       "      <td>21</td>\n",
        "      <td>0</td>\n",
        "      <td>1</td>\n",
-       "      <td>21.74</td>\n",
-       "      <td>2.542495</td>\n",
+       "      <td>99.45</td>\n",
+       "      <td>2.792453</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>98</th>\n",
-       "      <td>23</td>\n",
-       "      <td>5</td>\n",
-       "      <td>18</td>\n",
+       "      <td>4578</td>\n",
+       "      <td>4553</td>\n",
+       "      <td>25</td>\n",
        "      <td>0</td>\n",
        "      <td>37</td>\n",
-       "      <td>56.91</td>\n",
-       "      <td>3.400000</td>\n",
+       "      <td>95.02</td>\n",
+       "      <td>2.238304</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>99</th>\n",
-       "      <td>181</td>\n",
-       "      <td>103</td>\n",
-       "      <td>78</td>\n",
+       "      <td>482</td>\n",
+       "      <td>458</td>\n",
+       "      <td>24</td>\n",
        "      <td>0</td>\n",
        "      <td>4</td>\n",
-       "      <td>70.62</td>\n",
-       "      <td>2.320388</td>\n",
+       "      <td>90.76</td>\n",
+       "      <td>2.489083</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -649,17 +667,17 @@
       ],
       "text/plain": [
        "    access_count  hits  misses  mu  lambda  hit_rate   avg_age\n",
-       "1            664   550     114   0       1     58.49  2.596364\n",
-       "2            212   124      88   0       3     83.21  2.524194\n",
-       "3            673   560     113   0       1     84.11  2.405357\n",
-       "4            711   598     113   0       1     72.17  2.401338\n",
-       "5            345   249      96   0       2     82.43  2.469880\n",
+       "1            122   101      21   0       1     93.98  2.356436\n",
+       "2            382   359      23   0       3     82.68  2.607242\n",
+       "3            127   105      22   0       1     81.42  2.371429\n",
+       "4            113    92      21   0       1     90.98  2.326087\n",
+       "5            244   222      22   0       2     81.90  2.436937\n",
        "..           ...   ...     ...  ..     ...       ...       ...\n",
-       "95           351   252      99   0       2     84.66  2.373016\n",
-       "96           717   607     110   0       1     83.28  2.436573\n",
-       "97           664   553     111   0       1     21.74  2.542495\n",
-       "98            23     5      18   0      37     56.91  3.400000\n",
-       "99           181   103      78   0       4     70.62  2.320388\n",
+       "95           257   234      23   0       2     84.89  2.341880\n",
+       "96           139   118      21   0       1     83.46  2.220339\n",
+       "97           127   106      21   0       1     99.45  2.792453\n",
+       "98          4578  4553      25   0      37     95.02  2.238304\n",
+       "99           482   458      24   0       4     90.76  2.489083\n",
        "\n",
        "[99 rows x 7 columns]"
       ]
@@ -681,7 +699,7 @@
     "merged = access_count.merge(hits, left_index=True, right_index=True).merge(misses, left_index=True, right_index=True)\\\n",
     "    .merge(mu, left_index=True, right_index=True).merge(lmbda, left_index=True, right_index=True)\\\n",
     "    .merge(hit_rate, left_index=True, right_index=True).merge(avg_age, left_index=True, right_index=True)\n",
-    "merged.to_csv(f\"{TEMP_BASE_DIR}/details.csv\")\n",
+    "merged.to_csv(f\"{TEMP_BASE_DIR}/details.csv\", index_label=\"obj_id\")\n",
     "merged"
    ]
   },
@@ -693,7 +711,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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t8m/E78V76IlvvvkGb731FjIzMx1KxKnPk5ycHPTr1w/x8fFdPm5x7LW1tQCAyspK1NXVYdasWZg1a5bLx6ioqHD7+OpzyB1X59D06dPx9NNPo6SkBP3798eaNWtQUVGB6dOnK/fJyspCfX09kpOTPTouT79L/uCqLQGAgQMHtvu9eK+Brr8mIiIiIiIiIurdGFxFRERERERERAEzbNgw3HTTTZg1axaefPLJdre7y2BksVjcPqZOp/Pod4Cc0aerRFaqN954AxMmTHB5n8jISIefRZaeQBg1ahR++ukn7N27F6effrrL++zduxcAMHr0aJ+fz2q1QqPRYNmyZS7fd+f3xlvJycnYvXs3VqxYgWXLlmHZsmX46quvcPPNN+Obb77x6jG9OU+OPfZYAEBGRoZHz/H999/j1ltvxRVXXIHHHnsMycnJ0Ol0eOWVV5SAs67q7LjFOXvTTTe5DQocP36828cXwX179+51e867OoemT5+Op556CvPnz8cjjzyCH3/8ETExMQ4BcFarFcnJyZg9e7bLx01KSnL4uSe/S+7eV1e/V58jXX1NRERERERERNS7MbiKiIiIiIiIiALq3//+N77//nu89tpr7W4TmYPq6uocfl9QUNBtxyMyUwmSJCE7O1sJPhHl16Kjo3Huuef69bkHDx6MQ4cOtft9ZmamcntXXXLJJXjllVfw7bffugyuslgsmDNnDuLi4nDKKac43Ob8XgDA4cOHMWTIELfPl56eDkmSMHToUIwcObLD+wHAvn37OnwfOyoRGBwcjEsvvRSXXnoprFYr7rvvPnz22Wd49tlnMXz4cLd/508jR47EMcccg59//hnvvfdep8FjCxYswLBhw7Bo0SKH1+Zc/i89PR0rVqxATU2NR9mrOpKUlISoqChYLBavztkLL7wQOp0O3333HW6++WaX9/n222+h1+sdAqeGDh2KKVOm4IcffsADDzyARYsW4YorrkBISIhyn/T0dKxatQqnnHJKQIMQ/elofE1EREREREREf2XaQB8AEREREREREf21paen46abbsJnn32GsrIyh9uio6ORmJiItWvXOvz+448/7rbj+fbbbx3Kny1YsABHjhzBhRdeCACYNGkS0tPT8eabb6Kpqand31dWVnr93BdddBG2bt2KTZs2Kb9rbm7GrFmzMGTIEK8yS5188sk499xz8dVXX+F///tfu9ufeeYZHD58GI8//ni7QJCffvoJJSUlys9bt27Fli1blPfClauuugo6nQ4zZ85sl/FJkiSlFOPEiRMxdOhQvPvuu+2C59R/FxERAaB9gJ1zSUetVqsEwBkMBrfH1x1mzpyJ6upq3HHHHTCbze1uX7lypfLei6xH6te4ZcsWh88cAK6++mpIkoSZM2e2e7yuZlzT6XS4+uqrsXDhQuzbt6/d7Z2dswMHDsRtt92GVatW4ZNPPml3+6effoo//vgDt99+OwYMGOBw2/Tp07F582b897//RVVVlUNJQAC47rrrYLFY8J///Kfd45rN5nafe19wNL4mIiIiIiIior8yZq4iIiIiIiIiooB75pln8N133+HQoUMYM2aMw2133HEHXn31Vdxxxx2YPHky1q5di8OHD3fbscTHx+PUU0/FbbfdhvLycrz77rsYPnw47rzzTgByEM8XX3yBCy+8EGPGjMFtt92G/v37o6SkBKtXr0Z0dDSWLFni1XM/+eSTmDt3Li688EI89NBDiI+PxzfffIO8vDwsXLgQWq13++S+/fZbnHPOObj88stxww034LTTToPBYMCiRYuwZs0aTJ8+HY899li7vxs+fDhOPfVU3HvvvTAYDHj33XeRkJCAxx9/3O1zpaen48UXX8RTTz2F/Px8XHHFFYiKikJeXh4WL16Mu+66C48++ii0Wi0++eQTXHrppZgwYQJuu+02pKWlITMzE/v378eKFSsAyMFsAPDQQw9h2rRp0Ol0mDFjBu644w7U1NTg7LPPxoABA1BQUIAPPvgAEyZMUMrY9ZTp06cjIyMDL730Enbt2oXrr78egwcPRnV1NZYvX47ff/8dc+bMASBnElu0aBGuvPJKXHzxxcjLy8Onn36K0aNHOwTrnXXWWfjb3/6G999/H1lZWbjgggtgtVqxbt06nHXWWXjggQe6dIyvvvoqVq9ejalTp+LOO+/E6NGjUVNTg507d2LVqlWoqanp8O/feecdZGZm4r777sPy5cuVDFUrVqzAzz//jDPOOANvvfVWu7+77rrr8Oijj+LRRx9FfHx8u8xZZ5xxBu6++2688sor2L17N84//3wEBQUhKysL8+fPx3vvvYdrrrmmS6810I7G10RERERERET0V8bgKiIiIiIiIiIKuOHDh+Omm27CN9980+62//u//0NlZSUWLFiAH3/8ERdeeCGWLVuG5OTkbjmWp59+Gnv37sUrr7yCxsZGnHPOOfj4448RHh6u3OfMM8/Epk2b8J///AcffvghmpqakJqaiqlTp+Luu+/2+rlTUlKwceNGPPHEE/jggw/Q1taG8ePHY8mSJbj44ou9fty0tDRs3boVb731FubPn4+FCxdCr9dj/Pjx+Prrr3HzzTe7LL938803Q6vV4t1330VFRQWmTJmCDz/8EGlpaR0+35NPPomRI0finXfeUTIvDRw4EOeffz4uu+wy5X7Tpk3D6tWrMXPmTLz11luwWq1IT09XAtkAORPWgw8+iHnz5uH777+HJEmYMWMGbrrpJsyaNQsff/wx6urqkJqaiunTp+P555/3OgjNFy+++CLOPvtsvP/++/jkk09QU1ODuLg4nHjiifj555+V133rrbeirKwMn332GVasWIHRo0fj+++/x/z587FmzRqHx/zqq68wfvx4fPnll3jssccQExODyZMn4+STT+7y8aWkpGDr1q144YUXsGjRInz88cdISEjAmDFjXJbkdBYZGYnff/8dH3/8Mb7//ns89thjkCQJxx57LN59913cd999CAoKavd3AwYMwMknn4wNGzbgjjvucHmfTz/9FJMmTcJnn32Gp59+Gnq9HkOGDMFNN93UrlRlX3E0viYiIiIiIiKivyqN1NU84kRERERERERERDbPPvssXnnlFZfl8IiIiIiIiIiIiPq6nt/GR0RERERERERER40jR44gMTEx0IdBRERERERERETULVgWkIiIiIiIiIiIuiw3NxeLFy/G/PnzcckllwT6cIiIiIiIiIiIiLoFM1cREREREREREVGXrV27FjNnzsQZZ5yBt99+O9CHQ0RERERERERE1C00kiRJgT4IIiIiIiIiIiIiIiIiIiIiIiKi3oaZq4iIiIiIiIiIiIiIiIiIiIiIiFxgcBUREREREREREREREREREREREZEL+kAfQHezWq0oLS1FVFQUNBpNoA+HiIiIiIiIiIiIiIiIiIiIiIgCTJIkNDY2ol+/ftBq3eenOuqDq0pLSzFw4MBAHwYREREREREREREREREREREREfUyRUVFGDBggNvbj/rgqqioKADyGxEdHR3goyF3TCYTVq5cifPPPx9BQUGBPhwiIr9g20ZERyu2b0R0tGL7RkRHK7ZvRHQ0YttGREcrtm9EdLTqje1bQ0MDBg4cqMQWuXPUB1eJUoDR0dEMrurFTCYTwsPDER0d3Wu+REREvmLbRkRHK7ZvRHS0YvtGREcrtm9EdDRi20ZERyu2b0R0tOrN7ZuILXLHfcFAIiIiIiIiIiIiIiIiIiIiIiKivzAGVxEREREREREREREREREREREREbnA4CoiIiIiIiIiIiIiIiIiIiIiIiIX9IE+ACIiIiIiIiIiIiIiIiIiIiLq+yRJgtlshsViCfShUC9jMpmg1+vR1tbWY+eHTqeDXq+HRqPx6XEYXEVEREREREREREREREREREREPjEajThy5AhaWloCfSjUC0mShNTUVBQVFfkc7NQV4eHhSEtLQ3BwsNePweAqIiIiIiIiIiIiIiIiIiIiIvKa1WpFXl4edDod+vXrh+Dg4B4NoKHez2q1oqmpCZGRkdBqtd3+fJIkwWg0orKyEnl5eRgxYoTXz8vgKiIiIiIiIiIiIiIiIiIiIiLymtFohNVqxcCBAxEeHh7ow6FeyGq1wmg0IjQ0tEeCqwAgLCwMQUFBKCgoUJ7bGz1ztERERERERERERERERERERER0VOupoBkiT/njnORZTURERERERERERERERERERERE5AKDq4iIiIiIiIiIiIiIiIiIiIiIiFxgcBURERERERERERERERERERERUQeGDBmCd9991+f79LTeeEzu9NZjZXAVEREREREREREREREREREREf0lFRUV4e9//zv69euH4OBgDB48GA8//DCqq6u7/Fjbtm3DXXfd5bdj80ewkb+OKTs7G7fddhsGDBiAkJAQDB06FNdffz22b9/u82P3dgyuIiIiIiIiIiIiIiIiIiIiIqK/nNzcXEyePBlZWVmYO3cusrOz8emnn+L333/HSSedhJqami49XlJSEsLDw7vpaL3jj2Pavn07Jk2ahMOHD+Ozzz7DgQMHsHjxYhx77LH417/+5acj7b0YXEV93tcb8nDv9ztgNFsDfShERERERERERERERERERER/eZIkocVoDsh/kiR5fJz3338/goODsXLlSpxxxhkYNGgQLrzwQqxatQolJSV45plnHO7f2NiI66+/HhEREejfvz8++ugjh9udM03V1dXhjjvuQFJSEqKjo3H22Wdjz549Dn+zZMkSnHDCCQgNDUViYiKuvPJKAMCZZ56JgoIC/OMf/4BGo4FGowEAFBQU4NJLL0VcXBwiIiIwZswYLF261O1rdD4mjUaDL774AldeeSXCw8MxYsQI/PLLL27/XpIk3HrrrRgxYgTWrVuHiy++GOnp6ZgwYQKee+45/Pzzz8p9n3jiCYwcORLh4eEYNmwYnn32WZhMJo9er9DS0oK///3viIqKwqBBgzBr1iyH24uKinDdddchNjYW8fHxuPzyy5Gfn+/2+P1B362PTtTNrFYJb648jCaDGXeW1mPioLhAHxIREREREREREREREREREdFfWqvJgtH/tyIgz33ghWkID+48HKampgYrVqzASy+9hLCwMIfbUlNTceONN+KHH37Axx9/rAQ2vfHGG3j66acxc+ZMrFixAg8//DBGjhyJ8847z+VzXHvttQgLC8OyZcsQExODzz77DOeccw4OHz6M+Ph4/Prrr7jyyivxzDPP4Ntvv4XRaFQCpRYtWoTjjjsOd911F+68807lMe+//34YjUasXbsWEREROHDgACIjI7v0Hs2cOROvv/463njjDXzwwQe48cYbUVBQgPj4+Hb33b17N/bv3485c+ZAq22fwyk2Nlb5d1RUFL7++mv069cPGRkZuPPOOxEVFYXHH38cALBixQrceOONLl+v8NZbb+E///kPnn76aSxYsAD33nsvzjjjDBxzzDEwmUyYNm0aTjrpJKxbtw56vR4vvvgiLrjgAuzduxfBwcFdeh88xeAq6tPyq5vRZDADANpMlgAfDREREREREREREREREREREfUFWVlZkCQJo0aNcnn7qFGjUFtbi8rKSiQnJwMATjnlFDz55JMAgJEjR2LDhg145513XAZXrV+/Hlu3bkVFRQVCQkIAAG+++SZ++uknLFiwAHfddRdeeuklzJgxAzNnzlT+7rjjjgMAxMfHQ6fTISoqCqmpqcrthYWFuPrqqzFu3DgAwLBhw7r82m+99VZcf/31AICXX34Z77//PrZu3YoLLrjA5fsEAMcee2ynj/vvf/9b+feQIUPw6KOPYt68eUpw1VtvvYXp06e7fL3CRRddhPvuuw+AnAnrnXfewerVq3HMMcfghx9+gNVqxRdffKEEvH311VeIjY3FmjVrcP7553flbfAYg6uoT8soqVf+bWBZQCIiIiIiIiIiIiIiIiIiooALC9LhwAvTAvbcXdGVMoInnXRSu5/VJffU9uzZg6amJiQkJDj8vrW1FTk5OQDkrFDqrFSeeOihh3Dvvfdi5cqVOPfcc3H11Vdj/PjxXXoM9f0jIiIQHR2NiooKl/ftyvvzww8/4P3330dOTg6amppgNpsRHR2t3L5v3z7cfffdHh+bRqNBamqqcmx79uxBdnY2oqKiHP6mra1NeU+7A4OrqE/bX9qg/NtgYnAVERERERERERERERERERFRoGk0Go9K8wXS8OHDodFocPDgQVx55ZXtbj948CDi4uKQlJTk1eM3NTUhLS0Na9asaXebKKXnXI7QE3fccQemTZuGX3/9FStXrsQrr7yCt956Cw8++KDHjxEUFOTws0ajgdXqOuZi5MiRAIDMzEwcf/zxbh9z06ZNuPHGGzFz5kxMmzYNMTExmDdvHt566y3lPqGhoT4dW1NTEyZNmoTZs2e3+ztvPydPtC+GSNSHZBSrM1exLCARERERERERERERERERERF1LiEhAeeddx4+/vhjtLa2OtxWVlaG2bNnY/r06Ur5OQDYvHmzw/02b97stqzgxIkTUVZWBr1ej+HDhzv8l5iYCEDO0vT777+7Pcbg4GBYLO1jIQYOHIh77rkHixYtwr/+9S98/vnnHr/urpowYQJGjx6Nt956y2UAVl1dHQBg48aNGDx4MJ555hlMnjwZI0aMQEFBgcN9x4wZgz/++MPrY5k4cSKysrKQnJzc7j2NiYnx+nE7w+Aq6rMkScK+UlVwFTNXERERERERERERERERERERkYc+/PBDGAwGTJs2DWvXrkVRURGWL1+O8847D/3798dLL73kcP8NGzbg9ddfx+HDh/HRRx9h/vz5ePjhh10+9rnnnouTTjoJV1xxBVauXIn8/Hxs3LgRzzzzDLZv3w4AeO655zB37lw899xzOHjwIDIyMvDaa68pjzFkyBCsXbsWJSUlqKqqAgA88sgjWLFiBfLy8rBz506sXr3abYCXP2g0Gnz11Vc4fPgwTjvtNCxduhS5ubnYu3cvXnrpJVx++eUAgBEjRqCwsBDz5s1DTk4O3n//fSxevNjhsZ544gnMmzfP7evtzI033ojExERcfvnlWLduHfLy8rBmzRo89NBDKC4u9uvrVmNwFfVZBdUtaGwzKz8zcxURERERERERERERERERERF5asSIEdi+fTuGDRuG6667Dunp6bjrrrtw1llnYdOmTYiPj3e4/7/+9S9s374dxx9/PF588UW8/fbbmDZtmsvH1mg0WLp0KU4//XTcdtttGDlyJGbMmIGCggKkpKQAAM4880zMnz8fv/zyCyZMmICzzz4bW7duVR7jhRdeQH5+PtLT05WydxaLBffffz9GjRqFCy64ACNHjsTHH3/cTe+QbMqUKdi+fTuGDx+OO++8E6NGjcJll12G/fv349133wUAXHbZZfjHP/6BBx54ABMmTMDGjRvx7LPPOjzOqaeeih9++MHt6+1MeHg41q5di0GDBuGqq67CqFGjcPvtt6OtrQ3R0dH+fMkOeneBS6IOqLNWAYDBzMxVRERERERERERERERERERE5LnBgwfj66+/7vR++fn5nd7HYDAgMjJS+TkqKgrvv/8+3n//fbd/c9VVV+Gqq65yeduJJ56IPXv2OPzugw8+6PQ41JyPW5KkdvcRpf06MnLkSHzzzTcd3uf111/H66+/7vC7Rx55xOHnq666Ctdcc41HxwoAu3fvdvg5NTW10+PwNwZXUZ+VUcLgKiIiIiIiIiIiIiIiIiIiIgqslpYWbNiwAeXl5RgzZkygD4f8jGUBqc/aZwuuCgvSAQAMJpYFJCIiIiIiIiIiIiIiIiIiop41a9YszJgxA4888ghOOumkQB8O+RmDq6hPkiQJ+0oaAAATBsYCYOYqIiIiIiIiIiIiIiIiIiIi6nmPPPIIqqur8fbbbwf6UKgbMLiK+qTi2lbUt5oQrNNi/IAYAAyuIiIiIiIiIiIiIiIiIiIiIiL/YnAV9UkZtpKAx6RGITJEDwAwmFkWkIiIiIiIiIiIiIiIiIiIKFAkSQr0IRA58Mc5yeAq6pNEcNXY/tEICZJP4zYTM1cRERERERERERERERERERH1tKCgIABAS0tLgI+EyJE4J8U56g29vw6GqCftU4KrYmC2yFGGzFxFRERERERERERERERERETU83Q6HWJjY1FRUQEACA8Ph0ajCfBRUW9itVphNBrR1tYGrbb7c0FJkoSWlhZUVFQgNjYWOp3O68dicBX1SftLGwAA4/rH4IDt3wZmriIiIiIiIiIiIiIiIiIiIgqI1NRUAFACrIjUJElCa2srwsLCejTwLjY2Vjk3vcXgKupzWoxm1DQbAQDDkiKRU9kEADCYGVxFREREREREREREREREREQUCBqNBmlpaUhOTobJZAr04VAvYzKZsHbtWpx++uk+lejriqCgIJ8yVgkMrqI+p6pRDqwKDdIiIliHEL38RWBZQCIiIiIiIiIiIiIiIiIiosDS6XR+CWiho4tOp4PZbEZoaGiPBVf5S/cXMSTys6pmAwAgISIEGo0GoUHyaczMVURERERERERERERERERERETkTwyuoj6nqlEOrkqMCgEAe+YqE4OriIiIiIiIiIiIiIiIiIiIiMh/GFxFfU51s1wWMDEiGAAQoheZq1gWkIiIiIiIiIiIiIiIiIiIiIj8h8FV1OcomasiHTNXtTFzFRERERERERERERERERERERH5EYOrqM8RmasSIm2Zq4KYuYqIiIiIiIiIiIiIqLeTJAmF1S2wWqVAHwoRERERkccYXEV9TmWTc+YqEVzFzFVERERERERERERERL3Viv3lOP2N1Xhz5aFAHwoRERERkccYXEV9TrUIropyLAvI4CoiIiIiIiIiIiIiot5rbVYlACCjpD7AR0JERERE5DkGV1GfU9UklwVMjJDLAobaygJarBLMFgZYERERERERERERERH1RvtsQVWVjYYAHwkRERERkecYXEV9TpWbzFUAs1cREREREREREREREfVGJosVmUcaAQAVDK4iIiLqM1qMZhwobQj0YRAFFIOrqE8xWayoazEBABJsmauC9fbTmMFVRERERERERERERES9z+HyRhht1Sdqmo0wcj6fiIioT3h8wV5c9P46bM+vCfShEAUMg6uoT6lplksCajVAXLgcXKXTahCk0wAADGZLwI6NiIiIiIiIiIiIiIhcEyUBhcomZq8iIiLqCw6VyZkndxTUBvhIiAKHwVXUp4iSgPERIdBqNcrvRWlAg4k7XYiIiIiIiIiIiIiIept9JY7lhMob2gJ0JERERNQV1bYEKDmVTQE+EqLAYXAV9SlVTXLDnRgZ7PD7EFtpwDZmriIioqNcTmUTCqqbA30YREREdJSqbTZie34NJEkK9KEQUTeQJAkbc6pQ32IK9KEQ+UWbyYJ1WZVoM/k+L1zR0MZSN90swylzVUUDM1cRERH1dmaLFbUt8hp9dgWDq+ivi8FV1KdU2zJXJUaGOPxeBFcxcxURER3NKhracOkH63HNp5tgsXLBk4iIiPzv6cUZuObTTfh4TU6gD4WIusH67Grc8PkWPPvzvkAfCpFffLk+D3/7ciu+2pDv82PdN3snrvl0EzLLGjq/M3WZ2WLFwSPye3tMShQAoLKRmauIiIh6u5oWI8T+q+yKJm7Gor+sgAZXWSwWPPvssxg6dCjCwsKQnp6O//znPw5fSEmS8H//939IS0tDWFgYzj33XGRlZQXwqCmQqpTgKqfMVUG2soBmBlcREdHRa/6OYrQYLahsNKC6mbs7iYiIyP8OlTcCAN5ceQh/Hq4M8NEQkb9l2XaaHyprDPCREPnHgVI5WGd/aX0n9+yc+F7sKarz+bGovezKJhjMVkSG6HHC0DgAQDkzVxEREfV6VY1G5d8NbWal0hTRX01Ag6tee+01fPLJJ/jwww9x8OBBvPbaa3j99dfxwQcfKPd5/fXX8f777+PTTz/Fli1bEBERgWnTpqGtjTsa/oqqbY11grvMVSwLSERERymrVcK8bYXKz0ydT0RERN2h0tbHkCTgobm7UFjdEuAjIiJ/qmiUv+Ol9a0BPhIi/yiska9TRTW+Xa8a20xoNJgBADmVzT4fF7WXUSwHwI3pF43U6FAAQAUzVxEREfV6zhu9WRqQ/qoCGly1ceNGXH755bj44osxZMgQXHPNNTj//POxdetWAHLWqnfffRf//ve/cfnll2P8+PH49ttvUVpaip9++imQh04BUumuLKDIXMWygF4pqmnB7wfLj9o0jtVNBizfd4QltIg6kVFcr6Rnp95nQ04VimrsCyC+TkBarBKWZRxx+Tibcqq5k52OWptzq/8ygQKHyxuxm7vuiagLWoxmZWF5VFo06ltNuPv7HWg1ciMT0dFCBFc1tpnRZPu+E/VlSnBVrW8Bg0fq7WNjLhh2j30lcnDV2P4xSI4SwVXcOPZXUN7QhmUZR2Dl/DwRUZ8kKksJOZXsK9Ffkz6QT37yySdj1qxZOHz4MEaOHIk9e/Zg/fr1ePvttwEAeXl5KCsrw7nnnqv8TUxMDKZOnYpNmzZhxowZ7R7TYDDAYLB/wRsa5EVik8kEk8nUza+IvCU+m84+oyrbAnBsmM7hvsE6DQCgxWDk5+yFf/ywC9sL6rDw7qkYPyAm0IfjV41tJlzz6RbkVbfgwxnHYdqYlEAfEv2FeNq29QYtRjNmzNoEqyRhzb9OR3xEcOd/RD1q9uYCh5+P1Lb4dG4t31+OB+ftwUVjU/De9OOU31c2GnDTl1uQGBmM9Y+d4fXj09GtL7VvagXVLbj+881Iiw7F7/84FXpdQPeadCuzxYrrZ21Go8GMNf88DUlRIZ3/ERH12fbNX0ptC9RhQVp8duMEXPnJZhw80oA5W/Jx84mDAnx0ROQL0a5VNNgDSAqrGjEiOTJQh0Tks4ZWE+pb5XO7ptmImsZWRIV6t+RRVG1fJMyuaPzL9gW6097iOgDAqNRIxIXLn1NZfZtP7/Vfve/WVzyzaC9WZVbi4+sn4LzRyYE+HKI+ge0b9SblTllvD5c18Nwkr/XG9s3TYwlocNWTTz6JhoYGHHvssdDpdLBYLHjppZdw4403AgDKysoAACkpjsEQKSkpym3OXnnlFcycObPd71euXInw8HA/vwLyt99++63D23NLdQA0yDu4F0vL9ii/b6zVAtBi645dkAq5+6GrDpTI7+svf2xEceLR8/5ZJeDLQ1rk1coLp0s37ISl4Oh5fdR3dNa29QaVrUCzUe4WvDL3d5zVj9+V3qTBCKw8ILfVgyMlFDRpsH5HBiIr9nr9mEsK5WvnntwyLF1aovw+twGwWPUobzBg8ZKlCNH5fvx09OoL7Zva/loNJEmH0vo2vDV3BcbFH71tXWkLUN0st+v//fmPo/q1EnWHvta++Ut2AwDoEaGzYNeGPzA1XoOlzTos3XIAiTX7An14ROQHeWW1AORNir+sWodRsewjUN9V3AyolzjmLVmJ/hHePdbGcg0AeQBcVNOCn/+3FEFH716MHmeVgH22Oeia7F2osAKAHsXVDVi6dKnPj/9X7bv1Fbvy5M9+wZqdMOWz+ghRV7B9o95gW4G8lhCmk9Bq0WDLwXws1eQG+rCoj+tN7VtLi2eVLgIaXPXjjz9i9uzZmDNnDsaMGYPdu3fjkUceQb9+/XDLLbd49ZhPPfUU/vnPfyo/NzQ0YODAgTj//PMRHR3tr0MnPzOZTPjtt99w3nnnISgoyO39Xt7/JwADLjjzZIzrb8+w9EvtLmTWV+LYMeNw0eQBPXDER49WowUtm34HAAweOQYXHUW7kT9ak4t9tdnKz1Epg3DRRWMCeET0V+Np29Yb7CqsA3bLZXn3Nkfj9QtPhkajCexBkWLWujxYpSyMHxCN04cn4sM1uYhNG4yLLhrt9WP+b85uoKQCBm0ILrroTOX3y/aVAfvloK2JJ5+JwQkMTqf2+lL7pta6swTI3A8AyJZS8MRFEwN8RN1n0a4SYI/8WkPTRuCic4YH+IiI+oa+2r75y68Zcj9gSEocLrpoCiIOV2Lpd7tQi0hcdNGpgT48IvKBaN9aJD0AudTnwJGcR6O+bfn+cmCvfQPu4DGTcP5o77LWH/49G8iVFwklaHDM5NNwbGqUX46TgKzyJpg2b0REsA63XHkealuMeH3vn2gyaXDetAsQ5GVW4b96360vMFus+OeW3wFIaAlNwEUXnRDoQyLqE9i+UW+yZtE+oLQUJw1Pxh+HKtGAcFx00emBPizqo3pj+yaq4XUmoMFVjz32GJ588kmlvN+4ceNQUFCAV155BbfccgtSU1MBAOXl5UhLS1P+rry8HBMmTHD5mCEhIQgJaV/yIigoqNd8OOReR5+TJEmoaTYCAFJjIxzuFxosn8pmK/g5d1Fhnb2MZn2b5ah5/1YfqsB7f8iBVSenJ2BjTjXKGoxHzeujvqUvXIMaDPZdY7lVzdhd0oQpQ+O9eiyrVcLPe0owZWgC+seG+esQ/7IkScL8HXJmqRunDobJIu8sr2o2+XRe5VY1AwCqm43QaHVKebTqFrNyn+oWM4an9u5zlwKrL7RvarWtFuXfa7OqUNlsRr+jtJ06WNas/PtAWVOf+pyIeoO+1r75i+gHpMaEISgoCMcNSgAA5FW3wGDVIDIkoNNIdJQrqG7GjoJaXHl8f2706CYGC9BksPeHypt8G1MQdabJYMYvu0tx/pgUJEb6v0x1ab3B6Wfv5/7KG40OPxfUtmHcQO/mRai9g+Xy+GRMvxiEhAQjOSgIeq0GZquEeoMVaTHenR9FtS3YXKHBuRod27NeqqyxBRarPJe1/0gj9Ho9r/NEXfBXHZtS71LbIpdMOzE9AX8cqsSR+jYYrRpEcI6AfNCb2jdPjyOgiW1bWlqg1Toegk6ng9UqL/AOHToUqamp+P3335XbGxoasGXLFpx00kk9eqwUePWtJmVBOSEy2OG2EL18HrWZmVK2q47UtSn/rm0xdnDPvuXtlYchScCNUwfh3jPTAQBHnGoCE5FdjdP3f97WQq8fa/aWAvzjhz148X8HfD0sApBZ1oj86haEB+twyfh+SIkOBQBUNLR18pfumSxWFFTLaU4lCahqsn/+FY0Gl/8mOhpUN9nPaasE/Li9KIBH0732ldS7/DcRUUdE/yI5Su5vJEWFIDU6FJIEHCj1bBcfkTckScLd3+3AP3/cg4U7Szr/A/JKg9O0z5E6zpNQ95q7pRBPL87AR6uzO7+zFwpr5HGtTisHahTVelbOwxUxbxgWJJcGzK5o8vHoSG1zbjUAYKytGoVWq0FSlBxQVdHg/dzD80sOYm6ODi/8etD3g6RuIb6nANDYZnb4mYiI+oYq25xqelIkEm1r9LmVzR39CdFRKaDBVZdeeileeukl/Prrr8jPz8fixYvx9ttv48orrwQAaDQaPPLII3jxxRfxyy+/ICMjAzfffDP69euHK664IpCHTgEgFn6jQvUI0escbhM/G0wMruqqUlXAkcgM1tdJkoScSnkC5PZThyItRs5IoQ4kIyJH4vs/PDkSAPBrxhHU23YjdIUkSZi9RQ7Myqti59ofimyTTsOTIxERokeymHz0IfCpoLoZZtuuQfmx7O2jelKTwVV0tBETAWP7y+XCf9xWpOygPZpYrBL2q4IgKhoNPgVkEtFfh7j2J0fbs0eIRdAMBmpSN9pZWIfMskYAwJwtBQE+mqNXg9MQ70g9+wfUvXKr5Pm5wuruCaYQQRoTBsY6/OwNMW944jA5WxWDq/ynsc2E/+09AgC4cFyq8vtk2+axci/HKpIkYVeR3D/5YXsJ5vqwUZC6T5HT95J9SiKivqfatkafGBmC9CR5DSm7sjGQh0QUEAENrvrggw9wzTXX4L777sOoUaPw6KOP4u6778Z//vMf5T6PP/44HnzwQdx111044YQT0NTUhOXLlyM0NDSAR06BIBbDklykkA4Nkk9lg9nS7jbqmDrg6GgJrqpuNqLFaIFGA/SPC0NajNxeNBrMaGzrerAI0V9Bre37f8bIJBybGgWD2YrFu4q7/Di7iuyLIgzM8Q+x4CHaMrHYWdlogNXLoJDsCsfAt3KHgCp1oBUXW+joUm1r626aOhix4UEorW/D2sOVAT4q/8utbEKryYLwYJ0SNMsJbCLyhOgHpKiCq8bZgquYBY+6k3pBfGdhHQ6VcaK+OzQY5ew+eluWn1Jm+KZuVmqbd+yu+YHiWvkcPiVdLmPrbXCVJEnK9+HUEUkAgBxmY/Cbn3eXotVkwfDkSEweHKf83tfNY4U1LWhsMys/P/fzfuwsrPXtYMnvnL+XHJsSEfUtkiQpwVUJkcHKXGNOBftK9NcT0OCqqKgovPvuuygoKEBraytycnLw4osvIjjYXvJNo9HghRdeQFlZGdra2rBq1SqMHDkygEdNgaJuuJ0pmatYFrDLjhyFmavEgC0tOhQheh0iQvSIDpXr/vb0rsyaZiM+XpPt9Q4sop4ivv/xEcG4YeogAMDcrUWQJMfgneyKJnyxLhctRnO7xwAcywnWNBthZLvsMzHBK7LwJUaGQKMBzFapXTlHT4nsfgIzV/UuLUYzPl+bi0q+/34n3tN+sWG46vgBAIA5ft7dbLVK+O/6POwpqvPr43bFvlJ5snp0WjTGD2DGGer9PO0zL95VrJSUoe4hAq5FWUDAnu2PwVUd219ajx+2FbbrP6vVt5rw8ZpsFPtQtqonefKa/KGhzYT/7S0FAAxLjACAgGYfaTaYMWttDsqOwqxO9bb9ZsemRQGQN9z56/OtaGzDa8szMXPJfsxcsh+vLD2IfGYzdim7ohGf/ZmDNtPRv0lUzDuqx5yAvEj31YY87PIhEMZilZT29OThiQCA4ppWrzYh1bWY0GariHCq7bFyK5uOyiy3gTBvm9ymzzhhIDQajfJ7X4OrxBhnYISE80cnw2ix4t7vdyibtMk3TQYzPlqd7XPmOTFXn54kX+PZp+y9DpU1YtbanL/EfG5tsxEfrc52WB/rzXYV1uLH7e3n6umvbX9pPWZvKeiB8ZoZRovcLjhkrmKWT/oLCmhwFVFXiEFRoovMVSF6Zq7yVqlqsrDWy0X63kakGh4YH678rl+sHJRQWtezneXP1ubg9eWHcMt/t7oNRiHqDcT3Pz4iGJdP6I9gvRaHyhtR4DSB8vLSg3jx14P414972nXaG9tMWLLniMPvKjmh5TORYbBfrLzIGaTTIiFCDjRWB0J1RY7TwEf9OOXqQKvGo29BqS/48I9svLT0ID78IyvQh3LUqVIF618/ZSAA4I/MCr8GQW/Nr8EL/zuAxxbs8dtjdlVGsVwScGz/GIztJzLONHT0J0QB9e2mfLy+/BA+Wp3t9j77Surxjx/24O9fb2M22m4kslaKxU7Anrkqp7KJY5oOPL0oA08szMDqQxVu7zNvayFeX34Ib/92uAePzHtPLuz8NfnDz7tK0GayYkRyJP7v0tEAgEU7iwMWePLWysN4eWkm3lp5KCDP351E5qrxA2IBAK0mC+pb/dOmvr78ED5Zk4OvNuTjqw35+GxtLt44Ct9Df/jP/w7ilWWZWLG/LNCH0u3EeLay0eAQqLS9oBYzlxzAU4syvH7ssoY2mCwSgnQaHD8oFjqtBkaL1WFM6ymxqSkhQs7GEKzTwmC29vg84tEoo7ge+0oaEKzT4qqJAxxuS7GVBfQ2a7YSXBUp4bWrxmJYUgTKGwxYvLPEt4MmAMA3G/PxxopD+MDHuQkxV3/xuDQA8tiUASK904u/HsDLSzOx6mB5oA+l2328JhtvrDiEm7/cimZD7x/jPPLDbjy+YC9+P9i9/XLqO8wWK27/ejueWbwPW/JquvW5xPp8VIgeoUH2LPnZlQyuor8eBldRn1Fta7xdZq4SZQFNR39Evb8dUU0S1DabjoqBjdhNM0gVXCXKafV05qpdhXUAgMyyRjyxMOOoeH/p6CRKZcWFByMmLAhDE+TdZAVOqbvFboRl+8rw6Z+5Drep07z3i/FtgozsjjhlrgKAJFs2CW8mjQH7wGdUmpyJQgRRGcwW1LXYF1fKvQzeIt+szZLL1HGA6l9Wq4SaZnuZ6REpUZg8OA4Wq4T524v89jyiNElWRROaAjRBJ3YCj+0fg3EDWM6Lej/xvdndQcY30Ta2GC34eXdpTxzWX06byYIGW2md5Gh75qrk6FAkR4XAKgEHShmo6Y7oN689XOX2PiJ7aCCzG3ZFni3rUEevyVeSJGHuVvk6fP2UQTh9RBL6x4ahoc2MZfuOdPLX/tdmsmDhTrk8+q4+8jl1RYNtT92g+HDE2zZsiLJtvqhvtWcf+9uJg3HV8f0BAJlH2Ga4klkmvy/i+ne0amwzodHWH7ZKQHWzfXwpspoVVLd4PVcm5v8GxIUjRK9Df9vGyqKarr+vIggsLTYUOq0GQ21Z9JiRwXdzbVmrLhibqrQ7gq+Zq/apMldFhuhx1jHJAICqZs5l+MPaw3L/29eNkyJz1TmjUhCk06C+1XTUt399VX613DY7b8o8Gq3Lkvu3WRVNeGxB+03EvUmzwaxsgA5kdlfqXdYcqkSZbe2lu7PFOleWSrcFVxVUN8Nk4bo8/bUwuIr6jEpb4+06cxXLAnpLHWxktFgDtgjoT2LA5hBcZZtgOdKDO86sVslh8WHJnlJ8uT6vx56fqCtqmx07yCLzW6EquMpscdy1+caKTKyzLXQCjmnexYIcy8r5rtQpcxUApETL18JKL4KfJElSJklOTk8AYM9c5VyGjsFxPa+22Yj9tmtHYU3fKBnUV9S2GCE2y8fZJvWvnyKXQZ23rcir8iGuiCxYkgTsD0BAk9UqYb+tLOC4/jEYnRYNjUbe2c9Sk9Rbie9N5pFGtyUoNmbbywFyQrl7iP5AiF6rlFUXRPYqBmq61mayB6hvyHYfiCSu7blVzb1+7N3QZlKOsaPX5KuMknocONKAYL0WV03sD61WgxknyNkl527xX/Czp5bvK1MyOeVUNvWJTAZdIcoCJkeFqDah+T5P8vNuOfvYyJRIvHD5GDw67RgAcuAMF1wcNbaZlE0sR/t4y3mDozpjsrjNl+xpIhvOgDh5zm+Qi3kMz4/VcVOTkpHhLxBg0J2aDWb8YguKn2HLHKyWHC2Cq7r+XZAkScnOOzBCHstFhwYBABrbjq62OxBajGZl07AvGQ4b20yotfWR0pMjcUyqXJaWZet7H6tVUkoiH+3zUZWNBmSWNQIAgnQaLM0ow2drczv5q8DJq7J/HqsPVfSZUobUvdTzIqXdnFTCubJUWnQowoN1MFmko769IHLG4CrqM+yZq1gW0F/Uk6VBOjk1fG1z3y+xUVTroiygbdKwuzsZavnV8oR5aJAW/754FADglWWZ2Jxb7XA/SZLw6Z85WHXg6E+3253mbi3Eyl6cUr+0rhVvrjjkt5IL/lajylwFAAPj5QnFYlXn+Eh9G8xWCcE6La6dNABWCXhgzi7888fdeGDOTiXN+9UTByjBP4GeLP5hWyF+9GNGmp5msUrKgrM6c5V9d6f9/V2fVYV3Vx3uNECkrKENzUYL9FoNThgSZ3sc+RorJvmjbAuqDW3mgJVj+avalFsNsVmutK4NZi5G+Y09Q18QgnRy3/GicWmICtWjuLYV6/20cKwOYNoXgAwvedXNaDZaEBqkRXpSBCJC9Bhm23nPoAjylclixTu/HUZGsX/PJfG9MVqsyKpobHd7m8mCrflymnutBthf2uD3YyB7vyI5OgQajcbhtjG24KoMlhh1Sd32Z1U0uS03K7KpSBJwsJdn9DmiymbU0WvylVgUuGhsKmJtY5FrJw+ETqvB1vwaZLtoE7qTepHC289p1YFy/PPH3cp/ryw72Gvmq0RZwJToUGV84es8iSRJmLNFft+unzIIGo0GaTHygovZKrUrNf9Xl1NpzyxwtG9Gci6ppx6/qheGvc2e5ry50tUmMXcW7SzG0gx7djzxPRDzhyIjQ043ZxPeVViLD37PciiZCAAlda14ZenBPr+A/r+9pWgymDEkIRwnDUtod3uyyMrtxcax4tpW1LeaEKTTIM02BazMZfTSube+ZFt+LYy2+Qhf5jJF3yc+IhiRIXolYJ/BVe6t3F+GWWtzejyTUlWzASaL/JxifaWv+vNwJd7/Pcvte7gxR57/GZ0WjecuHQMAeH254yZifyiqacEryw763I9WX4usEvDjtmJfDy1gftlTiq825PXqTGG+WHOoAh/+4f7c85cj9a0Opdu7O6lElVNlKa1Wg2FJzPIpSRI+X5uL5Z1kXH5jRSaeWrRX2QxLfRuDq6jPEI13kquygLbgqjaWBewSMVkaExakDGZrWoyBPCS/EIO2gQ5lAW2Zq3pwUkIMEkelReP2U4fiign9YLFK+GKdY/aq/aUNeHVZJp5anNFjx3a0ySxrwFOLMvDg3F29ZtLa2du/HcaHq7PxeS/cBWOyWJUSMCJFu6sdn+pdof+5YiyOGxCD+lYTFu0swf/2yh3Ii8alIi4iWGlTAjlZXNVkwBMLM/D4gr1YsKNvDjqrmgwwWyVoNfaAKkBeDAEcJyCfXLQX767KUhaf3REDnkEJ4egfG257HPl6UGmb7B6eHKlcWytYGrBHqQN8LFapx8vZHs2qGtsH6ocF65SyNSL7nq/Ui0aBCGYSzzk6LRp6WxAZM86QvyzZU4r3fs/CA3N3+i3bG+DYX3B1nu4oqIXRbEVyVAguGd8PADCH2av8TvQrUqJC293GdqRjzn1eV5mejGarw3i0twcIljqNnbsje5UkSVixX95kdN0J9owmqTGhOPtYubTT4wv2us1o5285lU3YklcDrQYY218un93Vxd8mgxkPz9uFRTtLlP8++zMXS/b0fIlDV0RZwOSoECUzrq+LMXuK65FZ1ohgvRZX2vpVGo0G6UnM/OOK+v042oOrOspcpQ6o8nauTiz+i/kL8f+iToKrKhra8K/5e/DAnJ3KRjPxPRCZ79N7YMHQYpVw3+ydeOu3w/jzcIXDbV9vyMNna3Px5bq+nQF/daYcqHDNpAHtArcBe+aq6iZDlzcWifZ5ZEokbNMXiA5j5ip/2ai67vsSrCbmFcU8/Vj2KTv19OJ9eHlpppKZraeoA+u9Ka/amzy9KANv/3YYOwtrXd4u+rWnDE/AjVMH4brJ8ibiB+fu6vQa0hVfrs/DZ3/mYvbmAp8eRwRmJ9nmhn/YVtguKLcvaGgz4Z8/7MbMJQfw+bret0biD88s3oc3Vx7G1ryO5+d9NX97MawSoNPK19bunj+uclFZalSqPF767M+cHhuv9TY7C2vx0tKDuHf2Tvx52H1w5tKMMszdWqRku6a+jcFV1GdUKyWrXGSuChJlAXtnUEVvVaqkvA5FXIQ8+Kzp4zXpjWar8rocywKKScOeW6QWg8Sx/WKg0WiUyWLn3fiHy+WfKxu7PpFAsvW2GukGsxVZ5b1z4nZPUZ38/+K6gB6HK7W2oEqtRg62BFwHV6knREKDdPjujql48YqxePqiY/H0Rcfi+UtHK7t9RCBQd+1w90RBtX1H8NOLM3r9ApYrYqdvSnSoEiQBtM9cVdNsRHGtfN/OJgFEScDhSZHKRGZVkwEWq6RM7qdEhfqUnp+8t9Fp4ZKplf2nqllMBDgG6s+wlQZcub/cL2Xz1EGPgdiNK9o6MWmt/jd3B5Ov9trOr4LqlnbZWL1lNFuVhU3A9XkqJr9PHZ6olPP8ZXfJUVeuK9DUmaucieCqrIpGtBo57nbmnK11Q3b770dpXSvUayC9fVHReezs6jX5qrS+DTXNRui1GkwcFOdw2zMXjUJ0qB47C+swc8l+vz+3Kz9skzPennlMMs45NgVA16+dS/aUotlowYC4MDx90bFKkFh3llb0VJvJghaLvACTHBWq2oTmW39/ni3Y9eJxaUr2McBeVq27M//0Ner3I5Dj5Z7gHLhX7lAWUJW5ystzsH3mqjCH37tzuLwJkiRn/9iUU+1wDKJcplIWsLKp27JP/Hm4Qvn+OWd4E6/hUHnPZu/zt0rbZmkRbOksISIEOq0GVsk+9++pDGXeNVr5XbSShZuLl75Sb/yqbzV5/T0ocvqeju1nD646WjPX+MJilVBtW5/ZW1LXo8/t2C639tlgicY2E0ps1x91OT1BkiSlX3vK8ERoNBq8cLm8ibiuxYR7vt/htyz+oi0v8XFNKqdKnuP++ylDERMWhNL6Nqz1c5atnrA5pxpm24Do1WWZvaJ/7E9tJoty7nXn/JvFKinjlqsnyhsbnDfG+FuVi8pSD549osfHa73NOtu6pCQBD83dhUIXGXsNZovSFrjrD1HfwuAq6jNEtoFEF8FVoUpZwL7Z4QsUMVnaLzZMKQVW08fLApbUtUKSgLAgncPiaT8l3X1rjw3cRAdKLEQMt104i2paHDro6om1mi5OJJBMPeDvjQvHLUaz8jn3xskDUQ40NjxY2e2gBFdVtyjH6zxxGR0ahJtOHIy7Tk/HXaen49ZThiLOlvlKZFYK5E5c9YSq0WzFPd/vUErM9hVHnCZ4hSSn1Pnq876zxZFs27mYnhyJhIhgaDWwTWQalMn95OgQn9Lzk3eKa1uQX90CnapkI4Or/MdV5ipAzjA5YWAszFYJC3f6nuVOHZCYU9mEFmPPBn/sK3UfXNXbF/Kp91Nfb+Zu80/Z3Uqna7OrsnNi0vXk4Yk4cVg8hiZGoNlowf/2lvrlGEgm+m3JLjJXpUSHIDEyBFYJOFjWu8vZBYJ470QW2A3ZVe36/M7X9N44blETC2xDEuS+v6vX5CsREDwyJQqhtk1zwpDECLw343hoNMDsLYX40U9tjjsGs0XJdnv9lEFeZ2sTgUa3nDQEd52ejjtOGwpAHrMGehwo2tsQvRbRYXolc5Vz6bauaDKY8cseuS2eoco+Btgz/+Qwc5UD58xVgT4vupMIWFKyIqvLAqozV3l5DhY5ZcTxNHOVeh5OzCeJNq+fLXPVsMRIaDRAXYup2+bq5myxt2vO43jxc66qjGRfJBZjE6Paz+cDcsYNMX/b1azZon0eowquigqVNwyyLKBvapqNOKAqi2uySGj1MtjEPpcof7eOSY2CXqtBbYs9AIbsGlpNEJeFnh6/qzMKShL67OejbjddzakVVLegpK4VQToNpgyNBwCEBunwyU2TkBARjP2lDXh6UYZfrs+ij+XrxlWRuWp0v2hcPXEAAHufsy8R4/rwYB2sEvDAnJ0o7uMlKNXUr6U7x3rrsipRUteKmLAg/P1UeaxxpK6tW/uU1S4qSw1KCMf719vHaz/4qSJAX6I+p+tbTbj7+x3tNqMVVLfAYpUQGaJHiouNbNT3MLiK+oRWowXNtgYpwVVZQJG5SlUWcF9JPZ5cuPeozbhxpL4VTy/O6HDCwGi24tVlmVjophzWEVXmqgTbJHBtHw/uUQd/qNNNp9oCE9pM1h5JvWi1SthvWxgSC5pJUSGICtXDKgH5qow66ok1kV6T7CobDXhqUQay3OzWM5qt2JJrT7PaU4sUn/6Zg683eJae/eCRRmWXur8nDzZmV+GFJQd82k0kdkTFhQcpvxsQJ09KNhrMqLdNShXVts8K506SyHoUwMCcwmr5eC8Yk4qhiREoqWvFw/N296nJ61Kn0gSC6IiLLDv7HIKrOj6/slWZq/Q6rRJoUtFgUD6vlOhQ5TmO1utob7TRtnNuwsBYjEqTJ4j9GVy1v7Qez/28D41/0V28oq1LchGof/0UeTFw3tZCn0qdSZKkBCQG6TSQJOBAqesghPnbi3DHN9uU/55ZnOHz7kh1/2OcKrhKLDiU1rfh719vc3jeO77Zhn/8sBtlfk4hvj6rCq8sPQiTF1k520wWvLos0+EYZ2/xLY0++c5ilRzO5xX7yvwStCwy/gTp5L77wSMNDudNfYsJe23XuVOGJ0Cj0SgL+HO2dm+wxV+NOsjamUajUcqk+XuhZ0dBLZ5enIF6P4zTfthWiC/8XGJCkiR8+EcWft3rvqyb6C+dPzoFwXotyhralEUQQVzTxw+Q2+dABOB2hVhgu/S4fu1e04HSBjyxYK/P45p9ThuSnJ11bDL+ce5IAMC/f9rXrYuMvx0oR02zESnRITjrmCSMs31O2RVNHmdr21dSjz3F9QjSaXCVbRf5xEFxCA3SorLREPDyeKKvnxQVAo1G45fMVb/sLkWL0YJhSRHKAqXgKnOVJEl4//csLN/neZnEXYW1mLlkf6/+vrizaGcxPl6T7TAGVb8fRrNVGW/3Jlar+JzKfHocMTYVfVHRT25sM6FRlX3S03NwfVYVnv9lP+pbTWg2mJU5NOfgqopGQ4ffW/V3cWNOFaxWSekLi41NYcE69LeNw++dvVPpM3tbwtBZWX0bVh+ylwJ0DnIUbXBJXavHmTq/3pDX6xY2q22fkZh3dkUEdbuae/hqQ57L4FpJklQVA1SZq8LkzFUsC+ibTTnVkCRRclHuo3vbVilZ8G3zjKFBOoxMiQLgnz7lwh3F7ca34r9//ri7xzYyHyprxDOLM3yeQ6tTvc89HYjv3L71ls1+LUYznlq0V/XZbu+wX65u412tnW3IkYMhjh8Uh/BgvfL7frFh+PCGidBpNVi0qwTfb/G9PRXXN1/mxy1We3bD4cmRyvzVqoMV7bLn9nYioPmVq8ZhbP9o1LaYcP3nm5XP9smFe/tkf09Qf2e68/s71xZYd+Xx/TEkQd7M0GqydGuf0lVZQEDO+Puv8+Tx2rM/7e+TlUNWZ1bg3z9ldNjfqm024pnFGdhtq04DAM0GM3YVyj9/fdsUJEYG4+CRBjzzU4bD34o2KT050mWJZOp7GFxFfUKNrWRVsE6LqBB9u9tDlMxV9oHzl+vzMG9bEeb4oRPUG73/ezbmbCnE278ddnufF389gE//zMFTizJcLnyUqjNX2Qa54r3uq5zruAuhQTplIN/dKTLFcTQazAjWazEiRZ5Q1Gg0StrHnAr7RLt60r2qj2XV6Qmf/ZmDuVsL8ezP+1zevruozmH3VE/s6qlsNODVZZl4fskBjwIS9x9xDAzz1zGaLFY88sNu/HdDHpbv937SU2SuSoiwd47DgnVKHXfxvXL3/XLFuWxdIBTZdouM7R+Nz/42CcF6LdZnVwV8UaMrxCC8n1PmquRo++SjelIRcNxp5opoc9Jtix3qz6q80b7gYp/gZLvUU8QkwynDE12W5vTVa8sP4ZtNBZh9lPaNOlPV6LosIABcMr4fwoJ0yK9u8al0TUOrWQl2nTo0AYDrCZXqJgOeXpyBVQcrlP9mbynEqoPlXj83IC++NBrMCNZplQVNQN7BPdoWsPdHZoXD8646WIHFu0r8GrwkSRKeWLgXn63Nxcr9XXtNkiThmcX78OmfOQ7H+NzP+1k+OcByKpvQarIgPFiHMf2iYbRYsWhnic+PKxZaR6dFIypED6PZ6nCt3pQrL+6kJ0UogQBXT5J36+4pqkNdHx+/9CaVHWSuAoDxA2IByMFQ/vTOb4cxZ0shfvExE1lNsxFPLsrAi78eVEqv+8PBI414c+Vh/Gv+brdBsOI8HhgfjsmD5eyTG3Mcy1yIvunEQXFIjrJlATvSe7OAiQW2oYkRDq+pvKENt3y1FT9sL8KsP3N8eg6lpFP/aLf3eeCs4Tj72GQYLVZlIaE7/HlILq1y5fEDoNdpkRIdiiTb53TAw89pni2oYdqYVGUDQ2iQDicMkYOO1ge49Ik9O518bCKIpKy+zevgcrFAedXx/dstFtiDq5qV4KKNOdV4+7fDePZnz0uHvL78EL7akN/n5veaDGY8vmAvXl9+SCmrazRblQVSkTW6N463xOf03C+u52E8JbJTTRgotyGVtvkB52AqT7OnvbHyEL7emI9H5u1S3seYsCDEhAUp/46ylYXrKBOGur9fUN2C3cV1MFkkaDT2LNwAcJzturc1r0bpM8/f7numW0DeaGGxSgjWyXPa6vfEYLY4zA/mVXWevaqisQ3PLzmAJxZm+KXUuT+0mSxosi1UustcBdg3jzlnzS6sbsHMJQfwxKK97RaMS+paUdtigl6rwUjVuCdaZK76i24o8pf1SknuJOX75e2ivej/qDdqThgUCwBYnelbWbM2k6XduFr936KdJZi9uWc26by+PBOztxTinQ7WajyhHtscKmvs0dJ8ziVaO8sC2FOWZZRh7tYi1Wdbjgfm7sTqzAqX91e38a7m1NQl552dlJ6Ax6cdA0AO7vRFi9G+YdmX+fEqA2C2SggL0iEtOhQjUqIwfkAMLFYJG3P8X7a7u5TVyxs1tBrgzJHJ+PSmSYiPCEZRTavy2c7bVuRzYHcgFdXY+zN5Vc3KNdCfKhra8PtB+dy/fsoghAbplOzJna0J+KLaRVlA4b4zh+O80SkwWqx4d5VvbWBP21NUh7u/34HvNxfiuw6uFx+tzsbsLYV4cuFeZVyzNa8GZquEQfHhmDI0Hh/eMBEAsGhnicN6vMjiK7L6Ut/H4CrqE0Qq3+gwvcvIzhAXZQFFnfa+GCnrCdEJdJdafsGOYny7Sb4YuFv4UGeuihdlAft45qRiJfgjrN1tabaU90e6sZMhiEniUalRCNLZm1oxuSgWjEwWK/JVkyQiqwbZiQH95twa5LpY8Ba3H2fbWZx5pNGrLBldUVhj/8xE+aWO7LNleRDN1z4X5W688UdmhTIRm+3DApIIqoyLCHL4vT2lfqvt/+0nRNwRE5LVzcaALYarg8FGpkQpmYD6VnCVaKcd2zSRecdkkVDbYnIqC+h+Yrq+1aRMtIoOvVLCscGg7HhKjgpRslaU97FdUH2VJEnKIuwp6QlKEGOxnyazJEnC3uI6AEdv36gz4hrraiIgIkSvLOz6srtMTJjFhAVhkm0h2lWbv3BnMUwWCcekROG1q8fhtBHypJ6vn41o34YlRTj0PwBg1s2T8PrV4/Ha1eMc/rvWFqSy14/nhUizDwB7S+q69Lffby7Awp3F0GqAJy88Fq9eNQ4ajTyZWNcLMzv8lahLr9wwdRAAYO62Qp8zQoqF1pToUIxx8T3coAo8FRIjQ5TgAPUEJvnGnsHS9QLoicPkAJGNOdV+zQSaVSH3YwurfSt9tDGnSimjsj7Lf0EsYlGwzWTFzkLXgWXqoBVxrjofg7ovLbIb9+Zrsr08dZjymlZnVuC+2TuV/qQvwUIOWUfcZK4CAK1Wg0uPSwPQvf14MXYYlRal/E5kQ/Fkc0yL0Yyfd8kBgtdPGeRwm3j/NgQ4uKrSNt8j2s/UmFBoNPKcUbWXmT3EIrDIfKw2KD4COq0GTQazEjQhzpmqJoPH40TRRgQ6OK2rtuZVw2wLWhPHXljTrJQFGZooj8cCme3ZHXG8lY0GWLwMvJMkSdnceNxA+Tsu2krnYCpPM1eJ8erqQ5X4ty0rgHp+QqPReLRJRbQlIhBLlARNjgpx6EP/54qxePPa4/Da1eNw/uiULh1rR6xWCfNs2Zhm2DKQqEsjltc7nhOetH3Ftfa/dw7uDRRxrXC3WVpIcpO5SowjJEnOwqwm2uWRKVFKRQvAHlzVZrL2aFDK0UaZmxieYA+u8iLDqNUqodjWV1dv1Lz8uH4AgCV7S30KPthZUAuD2YrEyOB249zpk+Xv1oYe+D6YLFZszpWDXH7e7dtrUlfcMFkkv24Y6Ixoh1Jt84S9Jbgqy9YGnjYiEa9dPQ6XjE+DJAEPz9vlsK4idJS5yqoKSDrFRXAVAFw+Qc4+WlDd4lM7og50qW0xOSSG6IryVnlBIT05AlpbYPYwWx+iL83Zin7wuP4xiAkPwoC4cCx/+DRlnkrMi2X1oXl7Z+q+R0eZ7H0xf0cxzFYJEwfF4phUedwiNkz4K7umK/bMVe03rGq1Gjx14bEAgNWHKrr1OPypqsmAe7/foXzP5211Pb9lMFuwcKfcV8wsa8Qe2xjevkla3lx74rAEpX+/T/XZZ9vWNNWbYKlvY3AV9QlKcFVokMvbQ/S2soCqzo6ICvck8KGvKappUS7UrlLLZxTX4+nF8iSDKDngauFDPVkaH3l0Za5yFfxhT3nf/Rd3d5PESnCV7YJaUN2iTLYB9qwaJKtqMiCzzD6InOciFbjomM+YMgjRoXoYLdZuH3iqO8qeBEqJEk1njEwC4L+0sOra6tk+ZFoRQZXxTmna1ZOSTQazkkrbVfCis/jwYOi1ckmsQJW7LHLKtCWCifpScJU9w6BjBolgvVb5vA6XNzpMpHYUQCp2b6VGhyLKdk0ViyvlDQZl8jMlOlTJWtFbdr0e7Q6VN6KqyYiwIB2OHxTn98xVJXWtyiTd0dg38kSlmxTWwph+8jXblwBYsXCYHBWilDhyXpCVJAnzbKXMbj1lCKafMAgXj5MXjX39bJRU00ntB+wD4sJx3QkDMf2EQQ7/iSCZfSX1fguWUC9+7u/C+7k9vwYzlxwAIAdW3XNGOmZMGaRM6Pf18tV9XYaqf3vZcf0QHqxDbmUztubVdPKXHVOCUqJDMLZf+++Nq+AqwH597y3lKo4G5Y0iyNp15ip1eTN/TXo3tJmUttPXz3JDdrXq3/5bSFMveLt7XCVAPTpU2QW/KbfaISih0FVwlZ82XfibJElK8EO/2FB7cNWhSuwoqEVUqB5ajZyRyNuysmUNbahuNkKn1SibINxRMkD7MObpjPPYAbCXK/Rk/Pa/vUfQaDBjcEI4ThqW4HCbOCc259YENAujuiwgAATptMqmDW/nScTcm7hWqwXrtRicIL+foo+y0fYdkiTP5p/qWozKeHJLbk2fCpZYn2Vvk0SgQrZq53pKL97MIto6qwTUejlPWNdiQptJ/rxEBqjKRgOsVkmZjxxpy/TuSfY0SZKUEnMAsNNWhsV5/q+zcVRDm0npe1xj22SwZI8cGOm8qSk+IhjXTBqA6ScMwhnHJNleg++f17rsKpTUtSI6VI+/nzIUAFCuCmRzzrjvyRyGeh5gY3bvyGQigjYTI4M7LINjz6btOPegHpc5jyky3JSVjQy1B3E1MnuVV4pqWlBQ3QKdVoOpwxIQ7UPmqvLGNhgtVui1GmXxHwCmDI3HsKQItBgt+GW395lLReDU6SOS2o1z7zkzHQCws6DO4/K+3tpbXIdm23O0GC1Km+KNulbHNrcnSwOKtnmqbUNFbxlniTbwnGOTMf2EQXj7ugmYOCgWDW1m3PP9jnZl5NT9RecysQeONKCuxYTIEL2yUdtZSnQIIkP0sFglFPiw+cO5b+Xt/Gq57WHU8zzKRtk+NGfralyfHB2qzFOdc2wygL41b+/M+Tvj7++v1SrhB9v6mHozh+i/OGef8xd1JkpXG1YBYFhSJKYOjYdVAn7c5p8sn93JbLHigTk7UVrfhmGJEYgM0SO/ugWbctv3oVbsL0etKvB1ri2brqtzeqyLuWDRJrmaq6W+icFV1CeIOulRoa53uYQE2TJXqVL0N9o6/OUNhoCWpXJHkiS8uiwTs9Z2PY2+84SuegGrvtWEe2zRtueOSsbsO6a6XPhwniwVmavcLVplVzThkXm7fF486Uh2RSPu+W6HQ93aruoouEqU1fKlk/Hpnzn4z/8OdDohKhZHnQf59rKA8gXVeXK4KsCZq37YVohnf9rXa8ruiJ0kIjvdgh3FDrs8GttMyvly6vBEl52X7lBYbR8cOT/XL3tK8dSivcrAzWixBz7NOMF/C9glda1Yc9iePltdarKrxGRpXLhjcJV60VIsNsSFBylBOR3RajXKpH0gJovbTBaU2Z5XtAfOwY19gbvMVYB9AlKkwRY/NxrMbicR7TW+7Wloxd+V1rUqk5/JUfaMIL7spK5qMuDBubs6LB8kSRJeX56Jj1Zne/08RwOR3WLqsHgE67XK96+2xeSXkgbqtqqgusXrlP6BMm9rIWYu2e9TZsKqRpG5qv0uKwBug6G6okKVgWecbaIuq6LRYTJvS14NcquaERGsw6W2Hbv261eDT9cHZcDehd1Qo9KiodNqUN1sVNpNX6l3y2c4XfOyKxpx/5ydKKx2nHSqaTbi3tk7YbZKuGR8Gu48bZhym5JhlcFVAaVsHugXg6jQIFw6Xj5/v3cq0yRJEt5blYVXlh306HwW/YSUKPv3RjxXcW0Lcqvk0gEnOgUrdEf51L8yg9miBOEmuynd41DezE+ZoXJVJdILnbKQldW34f45O7HHw/Ghepy8Ja/Gb9ls1VlKNrhZsFZnrhrbPwbRoXo0tpkdJtRFuzcoIVy55jhn4ugt5N318vuXGhOKcf1jlPkYjQZ4b8YE5TV4G8gmsnaNSI5EqCrriCtiHF3VZHQol9NsMOP+OTtx7acblf86KufgjsFswRGnsQPQfnK8oc2EpxZlYP52x00/kiQpZZennzBQySogjE6LRmx4EJoMZmWnc1dZrBLeWJGJd1cd9rqEX4WtPEWyqi+UFmtbjPEyw3dDqzxfFx3mer5OfHbZFY2obzFhr+o74cnmMvWcSavJ4tF8UavRgn/9uCfgZQTV/aFt+bVoM1kcAuFTemkZ9roWo0PAv7o8XVeIAKGEiGD0jwtTMpHWtBiVoNUJA2M9zp7W0GaG0dauqxcUBzrN/4mfZ63NxbWfbsT0zzZhWcYR5XYxH5ccFYILx8obHMS8s/OmJjXxeTmXrvOGWJS7auIADIwPh16rgcUqKWMJ5wV5TwJL1X/jrsqBs615Nbh/9s5uy04jxl8dlQQE1Nm0Hdsh9bjMeYFaBF6NdQqO0Gk1iLRlyWpo860c0/ebC/DUogyv29zuUFLXiofm7sKhMsdNpQaz3O45X588tSG7CtfP2oxrP92Iv3+9DQBw/MBYRIbofSoLKPo+/ePCoFdlhdNoNLjeNkfqS8nf9bZ+2ckuMhANSQhHv5hQGC1WbMvvvvUMwB5MK+avfXlNtc2O73N3zHFLkoT3f8/Cy0vt4zWzxaqMy6YOlcdd3TXOWrm/DE8t2uu23LazXCXri5ylJ1ivxSc3TUJSVAgyyxrxzGJ7CVuTpX35XXWZWLGOduKweIdzUk2j0SgbdH0J7Hfe/Ort9V5krhquCsxIchOUml3RhFu/2qr0i6+ftVkJbO8O5Q2ejdckSVKCIV2VYwTsn293bqbobuJ6OtFW+tTf39+NOdUorGlBVIgeF49PU37fT6nY0z1JJURfMFinRbSbNXoAyubNH7YVep35tKe8sfIQNufWICJYh1k3T8JlE+T5rblb219HRb9NnLtL9pYiv6pZSQpxcroquMop87HVKinrdsxcdfRgcBX1CWJRMdrFTjjAdVlAdYe/uwMtvLG3uB6f/pmDl5dmuix11hHRCUywZS1RT2b+sK0QJXWtGJwQjrenT0BUaBAuVy4M9o6982RpXIT7zFV1LUb8/ett+Gl3KW7/ZhvyXKRb9YdP/8zF8v1luP3rbe1ShHtCkiT7hLWrzFW2SUNvOxltJgteW56JL9fn4bXlmR0ehzLId5O5KreqCVar1C4SP5CZq6qbDHj2p/34bnMB/lQF7QTSBtuizQ1TByElOgQ1zUb8dqBcuX1rXg0sVgmDE8IxMD68SzuLfaEeXKqfy2qV8Pwv+zF3axHm75A7YqUt8m7PxMgQnHlMkrKA7Wsq+R+3FUGSoKQazatq9jooTixWu8tcpc6W50lJQMHd7sOeUFLXCkkCwoN1SlvZEzve/clksSrvXZqLSd5k2wTk77bgqhOGxisDHHfnl1jEGpliL3ciHmf/Efk2vVaDuPBgZYKz3IcA5cU7S7BkTymeWZzhdnJ3S14NPl6TgzdWHEJmWe/M3tATtufLAWgi00FkiF75Tvpjstu5XdzfC/tG7pgtVjy/ZD++2pCP5fvKvHoMSZKUsoBJbnZZiaCO/aX1Xk+gqzNXJUeFIDEyBFZJ3h0piKyDl03op0z8j0yJQrBOi/pWk08lztTZEDwVGqTDCFv/xB/lqdRp9gG5T67OrvfOqiz8uvcIZq1z3GCwYn8ZKhsNGJYYgdevGe+wu13ppzK4KmAsVgn7bWnNxXflxhPlibMle0rxv7323dlfrMvDO6sO47M/cz2akHfIXGXryx040gCD2YInFu4FAEwaHNcuKwozV/mXunRPbLj7QPpT/VzezLlsh7q/MGdLAX7dewT/9/M+V3/qQPRX9VoNokP1aDKYlXK4vlJvztlbXNducdFotirtU0p0KHRaDU5Kl6/n4n2qbzEpi7wD4+zjlqyKJo8XlnqSGI8nRgYjRK+DTqvBeaPkkliPnDMSZx+boixkensueFISUIgI0SsZL9R9+ZUHyvDr3iPYll+r/PfqUs8CO9VKatuPHQCoAqWb0Gq04B/zdmPu1kI8tmAvVuy390k++TMHe4rqEKzTKplw1LRaDU52Oie66s2Vh/DR6hy8uyrL600Jlar2VujnYxmRjjJXAfY5kJzKZmzKtZfuBOwlmzviPGfiSWnABTuLsXBnMZ5enOHwOfWkisY2ZJY1QqORNygZzVZsz69Fji2gND05EknRIcp9e5NNOdUOn5O381RiUTktNhRBOq3y3SpvaFPa1UHx4R5nT6u2LexFhejxwuVjMGWoHOw73im4RrSvR+rbsC2/FlvyavDysoPK7eKcGp4ciQkDYxGmCu50talJSPbT59VmsmD1IXkMf+3kAdBpNcrYWwQ5iv+LxXNPsnioAyRL6lqV4AJ38quacfs32/BrxhH86GVATmeUsuwRrje3CP3j5Pf9cLn9dUqS5DCGVc/tW6wSdtnK9I53cQ0R8yINPm4oemPFIczdWog9fupP+MNHq7Pxy55SfLk+1+H3G7OrsXBnMR5fuBd/ZJa7+Wv33lp5CJtyq7Etv1bJTnqurRSmT8FVIiuki9KxV08agGCdFhkl9V6t3dS3mpBh+2xESSY1jUbTY2V5xeM/ePZwBOk02Ftc73UAfZ3tfRbzQd2xrvXl+jy8/dthzFqbq3zeFY0GWCV5TnDi4FgAcnCcP0uBC68uy8TcrUUeZfgymq0osJ1H6sCElOhQfHzjRADA4l0lSvBHQXUzzFYJEcE6HGOb+1SPF7fbAu2cN+44sweHez+H7JyF0DmA1FPlLbbgKtXrF3O5zhuaf9xehDWHKpV+8abcanzyZ9eTO3hqzpZC/Lr3CJ7tZLyWU9mE8gYDQvRaTBwc5/I+4vX5Wo4xUCRJUuZvL7Jlp/f3GtXcbfJ84hXH90d4sD3IyV6xp3v6lNWqkoAdZaKcNiYVseFBKK1vw9qs3rG+6EpNsxFfrc8HALx57XEYnhyFG2yB+yv2lTnMPeZVNWNTbjU0GuC1a8Yj3ZZ18clF8lzV6LRohzU15/XJ0vpWtJosCNJpurSuRr0bg6uoTxA7iDwpCyhJEiRJcgqu6n2Ltep63z+4KHXmjtUqYZNtweqBs4cDsKeWV5eZufeMdOX9Etlylu4rU3Z5Ok+WJrhZtLJYJTw8b7fSCW1sM+Oub7ej2Yfa4a5IkqRE0Vc3G3Hv9zu6PMlc32pCo+24BrgYtKX5mLmq1BasAQCfr8vDL24GAEU1rahvNSFYp3UIYACAgXFhCNZp0WayoqSuVZkYFqnyvd0R6A+LdpYouwDd7cjuSZIkKROnZ4xMwnWTBwKAco4D6rrG8mB5jCrzR3dSBzoU1rSg3rbL/2BZg/IdmrNFLsVZ1Cx3OMf2j3ZYwPZlcGyxSsrk18PnjECIXgujxYqiWu8mxEXmKufgqoG2CS515irnXaEdSVJ24vb8ZHGRKhhMdPqVif2K5l6189Cd8oY2SBIQpNMgMaJ9MEiy00Tr2H4x6KfsPHd9LogJH3WpEvE4YudjclQItFqN8vu6FpNDxriuqLS1aZlljdjlZheTOvB3novdIX8VYtA13lYyA7B/3/wRXCXaRbFzrydTy/sqp7JZKSni7Q7QZqNFeQx3mavSkyIRGqRFs9GCXC8DyUV7lxwdCo1Gg3H95R1LYmK1rsWIpbYAMdE/A+Sdl8ekyn0GX0oD5lTaF4u6wp+ZH9Vp9o+1vaYM1Y4t0Y91vlaL+5w3JsVhkgiwX5/6evnqviyvqgktRgvCgnTKRPP4AbG4+3Q5w9jjC/biUFkjNmZX4RXVAmZnC3uAKigxOhRDEyIQEaxDm8mKB+bswobsaoQF6fDiFePa/d0gP7aRZP8ckqJCOpwwFf1uf2WGUi9YNBnMDun2xWLPHg8WqEQfZ8LAWJw6Qiyk+WdMo96cY5WAzU6lAkR/J0inQZwtMM05CE2MpxMjQxAWrENKtByAa7FKDgG4vYWYmFcHGrxwxVj8fP8peOgceR5CeY05nmVIcbZPBGx6EFwFqLLQqs6ZjGL5Mc4bnYJPbpwIvVaDZqOlywsLYhylHjsAcinthIhgWKwSHpq3S9nUAAD/+nEPsiuasPZwJd5ccQgA8PxlY9yW1fRlgXdZxhF8ssa+MPb2qsNKcEZXOJcFBHxbjLFapU43Qw5XLU46fyc9mf8Qn7f4bnWWfUGSJGV3OWD/nHqa6O+MTovGWbYyNxtyqlxnrvJDJiR/cg5g8yQIzhXnLMxJqkxd6ts8zZ4mykMmRoUgSKfFd7dPwaL7TsYFY1Id7nfxuDTMvfNEfHrTRHx0g9wuFNW0KpsxlQC3pEgE67VK+Sv5eDrIXGVbyK5qMvqUjWFnQS0MZitSokMw2lYSNc0pyFH8X7Sz+dWdb6ZzDk5Tzzs7azaYcfd3O5T5dk/6a96o6qQsuzBpcBx0Wo3D3FNxrTy3KsavuVXNSobufSX1aGgzIypU7zJAV2Rbb/Qhc1Wr0aKsLfSmQH7RBpY4zfkU236WJODhebu7tDG6sc2kZFV845rx+PSmifjm71Nw+6lyyUoRXOVNJrCO5hLjI4Jx/hg5gMubcf7m3GpYJWBYUoTbwMhTVH2V7tJsMGNXkRzsd+lx/TDN1iZ5O78l1m7EsR8sa/RbNlZAzqr4yjL7pnGxwUq0ISnRoRgcL2/WajSY/Z713GC2IN9Wak+9KcudgupmWKwSIkP0Sjld4YQh8UppafFY2RX2IGax3uJqk/RxA2M7fN50VXC4t/yRuUqSJJS3OR4TAKTY+nLOpQZLbH3a6ZMH4rFpxwDo3jZM9Gv2FnccJCmyHp8wJN5txlp/lWMMlJpmI5qNFmg0wAVj5XYgp7KpXdlKb1U3GbDStmlgxpSBDreJzFXeJKzwhOizuysJKIQG6XDV8fJGk7kBziDbkUU7i2G0WDGufwwutAXCje0fg7H9o2G0WLFop72s4TxbQNsZI5PQPzZMmcvdnCsHaoq5B0GsTxbXtqKuxai0IYMTIhDkJlse9T38JKlPEDtN3JUFDA2yn8oGsxUtRgvMqoFub1xAVE+oLdhR7HE0dmZZI6qbjYgI1uH6KYMcUsu7KjMDyLu4RqdFw2i2YtHOEgDtJ0tFRoD6VpPDgP2d3w7jz8OVCA3S4qvbTkByVAiyKprw2II9ft25kFfVjNL6NmWn9J7iejz38/4uPYfoKCZHyRPWzkTQQZmXwVXOk42PL9iDgy4mwsX5dkxqFIL1js2sXqfFkES5Y59d2aSkI59q23Hn7aSVryRJUiLfge7f0eOJwpoWlNS1IkinwZSh8bhu8kBoNPJEn+hgb7RNzp5iS70pJuYPHmno1tKGRbZ0wmLeXSyEq9+3zLJG7C1pQFGTxuHY/FF26s/DFThS34a48CBcMDYVw5zKTXaV2H0Q55y5yjYILalrVQINuhJhLwa9/kib31WuJnAG2dLtt5rsZT96M9HmpMaEtistArQv2TOuf4xqUrb96yu1fY5aDXBiuj24SkwSmyxye5tk+zk2PAjBtk6/82DdU1Wqv5vnYrKsrsWIZapMRIt2FvfK7A3drbbZqEyOjrEF4wD+K3klZ1SU25xzbIs7YkGzL1D34zbmVCPfi8AnsdM9PFjXLnBH0Gk1ygKHt7tM1WWhANWOJduE5aKdJTCarRidFt1ul/1YH7MvVjcZUNtigkYDDEvsWnCVcm3yw3lhT7OfgONtqdDFa1IHITtfq8U56mqRvbPy1dT9RDDc6H7RyiIXADw27RicMjwBLUYL7vpuOx6YuwtWyd5HKqrtvP2qFEGJtuDeMf3kc0BkK33j2vFK8KGaElzlwXNQ5yqVsqYdT5iqy5v5IzOUc0ZRdbCc+rbOFqjUmy7EYpQnGW48IfpVY2wp/p2DO8Qu9KRIe2CayOq0Pb8WrUaLcp4OipfHpOoA3N6Yadse+GAPNIgM0eO4gbHKa5w0OA4hei3KGwxeZYbN6ELmKkCdhdbeDxDv3bQxqbhwXJqyiNbVYJpCN4u/Go1GOT7RJr161ThMHRqPJoMZd367HQ/Nk9u96ZMH4nqnhQ41MWbdWVjbpUWWrPJGPDp/DwDgjlOH4oapg+TF87m7utwnEoGAKapxhC+LMY0Gs7IBzV3mKvviZJMyXhZZZTwrCyi/xum2hYxdRXVuS6AD8nl14EgDgvVaTBwUiyaDGXd/t73Dv+kO4rWeOjxRCZBZn1XlEAjvr0xI/iYWqMXn5O1YUGxsFNnRxPWlssHgkNXK0+xpysKebd4iRK/DxEFx7cbKWlv2wAvGpuHi8WlKf1QEV6gzVwGO5YnEvKErCRHB0GjkzW6+zN0p16v0RKU9tWfab3P4/6TBcQgL0sFkkTodE5Y6XavczetJkoTHF+7FofLGLvXXvOHpYmxkiB7H2wIdxHGL9n1UWpRyjhywjVXWqzaN6VzMlYgypQ0+fO/V38tiLzcy+ltRTQvybYFwzkEb6kDwxja53fN0Y/SWXLkqwJCEcFw7eSAuGJuGM0YmKYvAyvvpRZCNOnjZFZEp5OfdpV0OQFC3s+6cbMtotb+0oduyIG/Nr4HJImFAXBgGxYcrZUt/2lXiVVCFKNN93AC5JLPRbEVWuX+ChEvrWvHgnF2wWCWE29ZOlOwqtnOqX2wowoJ1SiC2L5m1XSmoboFYtvOkhKk6O7erDSCniMygtuAd5TqbFNluTq2isQ3lDQZoNFDmftxxFdTfVSJzlchY7pxlyhPljQYYLBrotBqlnwvYM1c5Z8MSz3nGMUm48vj+AOSAq+4q0aZ+f+Ztcx9Ms8HWtzilg++rv8oxBoo4z1KjQzEgLhzJUSGQJPu1y1cLdxbDZJFw3IAYZc5E6O7MVeJ6nuhms6qaGA/9nlnhdba27iRJkhLQ6xykJtrvuVvlpAlGsxULdxQ73CayLgrO53RMWJDyXd1X0mDvdyZ1bZ6WejcGV1Gf0HlZQHsgjcFsbRdR726ysr7FhHu/34GfdpV4dVxrDlXg9q+3dXkipM1kwTZb+Z+IYB2qnUqddUQMHKYMlaO81anl5yplZvojIsS+cKjRaJSL2pythTBbrO0mS2Nt760k2dP8rjlUgQ9t6eZfvWo8zjomGZ/cNBFBOg2WZpThqw35XXrdnryuSYPj8P6M46HVAD9sL8KcLuxcEZ19d5l1xGstq2+D1Soho7ge1322Cee9/SfOe/tPXPDuWoeSJs7EZONJwxJw2ohEtJmsuPu79hm2RKCNu0lipXNe3qRMFIpa5p6mW199qAJ3fLPN60kuZ1vzapBb2aykQz9U3uhwXq/LqsRNX2zxe2aA7zcXYNo7a5XP4G9fblHKZIrJkuMHxSE8WI+B8eE4bUQSACifm5gMEmU3BseHIypED4PZqux097c2kwVlto7hlCFyUJxoY9bbgr0ibAPUH7YXqzJXxTj835egzzlb5MWlqyYOQGiQzn5OeTnwEJmrnFO1p0SFIlinhcUqYWueHI3ftbKA8neu0ofJ4t8PluPGLzZ3uVycq9TjQTothtjKKAZi93JXiTbH3Q48ERQljO0f3WH5U9HOjh8Q65AJMtlpEVUEhWg0GmUypbMAuWUZR/C3L7e02z1ZpZq8WrLnSLtFDRFoMiotGv1jw9DQZsbSjCMun2NpxhHc9MWWXrf44A/iujE0McLhsxELsL5OZh2pb0N1sxE6rUYpVdNbFnIb2ky4f/bODktROB/rvC5k/BTsE/sdTwQ4B0N1lZg4EN8r0eb/b+8RnPf2n3j7t8MA5MkG54nBsT4usot2rX9smMsg846I5/bHhoQNSoBDgjLhI16TepFHfa02WazIPCJnz3MVXGUvC9izC6POfthW6NBvufqTjUoWhO62PqsKF7+/TnnuSz5Y1y57TndSgiD6OU5C63VafHD9RPSPDUNBdQtqmo0Y2z8aM06Qxx6dLQSaLFZU264Vot+g7kPfdfowXDK+n8u/FX2SktrWbg2q721WZ1bgtq+2+m0cINjLmrrP2gHIi9YiSGR9lu/noNgcEKST20RxzpgtVoesCz/tKkGrUR531TQbcf/snZi1Vs7koy5HesrwROX4dnUxiMUVi1VS+v7X2q6hzkFb9tKW9vduWGIE0mJCYbRYsb2gxmWJbX9mDfQ3+wKb+0CD0CAdJg+Ry3qI3eieKm9oQ2WjAVoPFreEdKdFLqtVUoKhxbVjuCqQpyuKXHw+gvq69LcTB2PGlEH48IaJSI0ORV5VM+paTDhuQAxmXj6mw6xvgxPC0T82DCaLfWzVGYPZgru/24FmowUnpyfgyQuPxXOXjsbEQbFoaDPjnu93eLxRz2C2KJnh/JW5Siy0hwZpHebl1MQiWUWjQdnoIbJ6VHWhLOAZI5MwOCHcYWzqipgXu2hsKj7722SkRocip7IZj87f02H24v/tLcU93+3wOAirtK4Vt3+9zWFnuyBJkvKdOFkV8JlRUo8WowV62wJpsiqTky9e+vUAHp2/x+tsw2olda3Iq2qGTqvB+bbPqdrLgAQxJhVj1GRlbNmmnG/9YsI8PgerlYW9jgN1nDkH3Io5JxGweXK6fVGso8xVep0WCbaM0r5kG9ugCgYW+imZ9ltt/5ffi/6xYRimLDR3HEwp3m9xrdqYU+3ynP98XS5+3XsEeq0Gz186BkD7LKA1zUbc/vU2r8rLqVWpygh1Rik1a7ue2/ueMUoWiAynMYW7RfpoJXOV/ftcVt+Gv325Bcv3uZ5vcKb+XvZUf1/tx+1F8vyHamF6oyr7Uml9q0NQivj+3HbKECRFheBweROeWZzh0XOJwEN376c/ygK6m0s8cVgCBieEo8lgxvm2cdaF763DctUmPHfEd1r9HXaWHBWKkSmRkCR7RkFvvL48E//6cY/LABUR1CMCJk8aloBB8eFoNJjx067Oy945E3O0seHBGNvPf31FSZJw3+ydqG42Yky/aPz74tEOj+2cbdBfm/2cqedjKxsNnc7f5zi12c5OGWFv4yVJUsYW6cmR7bLB77dtGEpPinRYO3PFHtTf5HX1A/G9FH1Jd9cOk8WKR+btwneb8tvdlmtr+wfGhTn0tcQ1tdloQZMqkFIJXo4JRUq0PK9vtkpel3/uiMUqOY3X7EGSNbbKNGL+Yo0t46qrEp5q/ijH6OzjNdl4cO4uh/epOzhv1nAuD+cLdcWiGVMGtbvded0TkNf7Lv1gvcMcUmcZYN0R1/POgqUBYERKFCYPjoPFKmH+jvb9ZFckScKryzLxyLxd3RYIKGyzlekOC9LhsuMc55ouO64fwoJ0yKlsxjlv/Ynz3vkTVU1GJEWF4GzbZmV11sUgnQYnDGlf5lK03Rkl9fY2LDmiO18W9TAGV1GfINL4Rrnp9ATpNMpuG4PZnrY3IlgHjUbuyLhKN/7d5nws21eGj9dke3Vcn6/Lxe+ZFZi9uWspDncU1MJoSwF96ylDAHQc2a3mPOAR/1+2rwzLMuSBh6vdkpcf3x9RIXpkVzThteWZ7SZL9TqtMlgSOznmb7dH5V5hi3SfNDgeT104CoAcGOMvIj38qSMScfrIJDxqS1v6/C/7saOg1qPH6GzAlhIdCo0GMFqsyCxrxB3fbsPWvBpkVTQhq6IJmWWN+GJdntvHFx3iAXFheH/G8UiICEZhTQt2FjoeX1a5vDg4Oq39DnvA3kncmFOFJoMZOq0Gk2y1pqubDR5l6/pyXR5WHazwujySM7FQffmEfsouNzHolCQJz/2yH+uzq/Cti06+Lz5anY1D5Y3KZ7Auqwp3fivvKhVZqdQ7kG47eQgAefFHDL6mDIlXygVptRqM7ue/BWJXSmzlISOCdTh9ZJLyXAazBdtsk7xPXiR/R37NKEOZbQw6rl1wVYNX2d/K6tuUEhDiu67s6vBi4CFJkvKdjwt3nPDSajUYYAvuEIOarpQFTPYxc5UkSXjx14PYkF2NO77Z3qWMJfb2wHFBaHg3DNK6yxGnnb7O1JmrBsSFITY8WDUp235i2t2uvsTIEKjXgdQZK8Rn2FGA3K7CWjw8bzfWZVVh6V7HiUqRuUqrAVpNFvy82z6xpN4pcsPUQcpCvLvMFN9szMf67Cos2ePZZGhfItqrMU5BC/6azBKPPyI5EpNtQaF5Vc0+7eT1l7lbCvFrxhF88EeW2/uI47/QllZ7wY4ijxcSBU9LUvgaACsm4UXw48TBcQgN0qLVZEFWRROaDGbEhgfhclu/Sk098eLN9UEsuHS1JCAAjE6LgVYjT256s5tSkDcQ2FJjD090yNYoSVK7ckDifT5c3gijxYqoUL3Lfpy9fHVgy+Z8tDrHod+yo6AWn67N6fwP/eDL9bnYX9qgPPe+kgalDFVP6CjDTHxEMD772ySEB+uQGBmMT2+ahOHJcj+4s8D8qiYDJEnOHCc+59NHytep00Yk4nHbmMCV5KgQBOvFZPHRF3jrzhsrDmH1oUrM3+HfUrr2sqadT5iKLAC+llgxmq0osJ0jJ9iuT+KaV1TbCpNFQmiQVlmg+t/eUpgtVjw4dyd+zTiCl5dmYv72ImSWNaKm2YjwYB0mDIz1KojFncpGAyxWCVqNvIlJq5HbW3U2ZCWwVtU302g0qjJw1S7HqiKo6JCfshH4k6vMVa6c4rQY7ikRxDw8OdLjgODhSY6BU3nVzWg2WhAapFXGQ94uyIiFc1EWXe0026LdlCHxePYSeSEyKSoEn/5tEkKDtEiKCsEnN01yW+JE0Gg0Sj/ckzI4ALCnqB65Vc2ICw/CB9cfD71ODmL65KZJiI8IRmZZo8cb9URApk4jKZvrACiZtQ+XNXY5UFXMvbnLWgXI5bnU44vxA2KVDS+dbS5rM9mzvqUnRzh8p1xpMpjxi228MWPKINtnMxHBOi1W7C/HJ3+6v2a/tyoLy/eX4de9nY812kwW3PP9DvyeWYGPVrefT8yvblEys58wJA4p0aEYoeqfDU4IR5BOq8r03OZ1ZviimhZ8vi4PC3YU44UlB7x6DDX7hpwYDFU+J98yV4l2RASTHa5oQqttk2JqTKjH2dMqlYW9zgN11MT3blNONdpMFuW6I/rMx6ZGYURyJGLDgxxKLrmiZN/y8j2pbzEpfSp1IIuSgVpkrhJtcGyoR+2a0WxVMtNdMDYNkSF61LWY2pWd3ZBdhVdt5cCeu3S0Mtdb1WR0yHL0064S/J5ZgfdWuR+jeaIrAXFK+5hdBatVUjLqju0fo4wp9pc2oM1kwXbbPLG7YCBR+aKh1f6afs8sx7qsKnzyZ65Hx64OgujpsoDrsirx5MK9WJ9dhS/W2+ep1W1fm8mqZDgC7N+fCQNj8cmNE6HRAD/tLvWotFZnwWrdGVyl1Wpwy0lDAMgZwrIqmnDwSAM+62SMdaS+FbmVcsDuScM6DtbwtTSgxSrh0z9zsHBnMfa4yNqqZOSx9Re0Wg1uOlEOfnh56cEu90nE+xwXHoRxA/wXnJFf3YLdRXUI1mvx6U2TlICA/aUNsFglZa0ozdYm90RwFdB59YxsVbCUK1OGxCNIp0FJXSsKa1qUjcfpSergKvn74W7DkCuDE+TqBy1G+ybrrpAkSQl6FSUI3QVTb8mtwU+7S/Hy0sx2c132UraOgRkRIXolI5YYi5gtVmVM1y82DDqtBgNsfdvuaMeKalpgtFgRotcqQZL/23sEZosVD83dhWX7ypT5C5NFQv/YsHYZl5z5oxyjmiRJeG9VFpbsKcXjfq7E48x5s4Y/NtjbH1uuRhGk0zhULBJSY+zrniIoftbaXGSU1DvMIX3j5dpeVRcD3C+bIB/j9nzPxuKz1ubi0z9z8NPuUuwu8mwt2FuissZlx/VTyggLUaFBuHayHKSeW9WslE3+24mDHUr63XbKEOi0Gpx9bLLL6gjKJqrS+nYZU+nowOAq6hM6y1yl0WgQYiu/ZjDZM1elRIcqkwHOEf5Wq6QElIgFt64Snc6ullBTp4AWNVrXZVV1uhPGaLZii1MtV7Er9+CRBhgtVozpF+1yx390aBBev2Y8AODzdXn4ZbecrUs9WWpfuJLfD3Hhv9hWd1a4etIAaDXyBcY5S4k3LFZJ2X0jBjz3npGOC8emwmSRcN/sHR5lKnGXyl8I0mmVCe87v92O8gYDhidHYs4dU/H61fJ709ECkH1yIwxxEcH2+rlOGUWUgWOC62hkcSEVg+LBCeFIjbGX5VIP/t0REzn+KHVR12LEr7ZMMTOmDLLv6rPtvNmWX6vskljvZhLTG00Gs7IQ9tWtJ+Dbv09RdpX+68c9qnPCPkg+69hkLHv4NMy5cyrm3DkVc+88EV/eeoLD4/qj7F5H1OeZ+rl2Fdah1WRBYmQIbpwyCOlJEWgxWmCFBnHhQcp3bXRaNLQauVPqTdDR/O1FsFglnDAkTlm49CVzVYvRAoNt4BYf0X6S0nkCxJuygN5mGtqcW6PsgCmubcVDXdi9UGj7Xg5KcDxesUugL6QXdt7p60y9+CnORfuuX8d2SZIktymYg3Rah6xl6owVKZ3spq5sNODe73fCaFuIcQ7KEIOvyyfIk7bqQOKdhbXIqmhCWJAOl0/oh2snD4RWI6dUz65obP9ctsfqjdkdfOWuHJrzLjtv7Vc9fnxEMPrbzil/pab2liTZ+2KldW0wuVjQs1gl5TgfPncEEiNDUNVkxO8Hu7aL2l5GxLPgqgOlDV3enShJkvIdEP2NxMgQ/P6vM5Xr1pw7p2LFI6c7ZCgTjkmNQpBOg7oWk1f9K3u6/K4P2MOC7VkQffmO7SysRZvJiuSoEAxPjsQxqVHQazWobTEhv7pFCXIQC9Xi3Nyn2pnuKuuHkrmqJXABgeoF3ll/m4QXrxgLAPhld6nHJTe8JUkSMmy7bF+6ciy+vGUydFoNthfUKkH93cmq+h6OG+B6MnRs/xise/wsrH70TAyIC/d4Ml4sXCVFhihlfc48Jhmr/nkGvrr1BOh17qcstKrJYn9nV+2tqpsMykKpv6+H4rNwzozpilgA9TUzVEF1MyxWCZEheiX4V3yWok0blhiJ6SIAe1sRXl9xCBuyq5XA8Gd+2qdksJo6NB7Beq1DEIuv5c5FFpGU6FDERwRj3IDYdo9rz1zleI0R45gN2VWuS1bb+qnFvfD8tZfscp+5CrCfC5tzqrsUmNNZtmdXRD++qKYFbSaLqmRUtNJWeJu5yj6Gbz/WmTosAX/86wzMvnMqgvX2NmnCwFisf+JsrH70zA4zfKmJwERPM32J78FxA2MddoqnRIcqpZQ83agnztOYYDhca49NlUt9NhrM2NvFdsWT4CrAcTHh1OGJSLK9ls5Kq+VVNUOS5PJ0SZEhyvyXu+/1kj2laDZaMCwxAlOHym3K8YPiMPNyOTvPmysPKZkT1MwWK/JtAQj7OikNLUkSnv1pH/baAgQLqlva9WHF8U0cHKssuKjHYKKvJsZdbSYrGr3sS6jfi9lbCvGjFxleXT3eqcMTlWxDXmeusrWf4vsh5gf2FNUBkOcgQ4N03Z656riBsYgI1qGm2Yjl+8qU6444Hq1WgwX3nIxV/zzDZR9dTZ19yxubcqthleRF8lTVfKySgbq+Fa1GixI0kxYT5lFpKjlADwi2zXueOEw+/9XnR3FtCx6YsxNWCbhm0gDcdOJgxIQFKd9fdWlAMbd0sKzR5RjNU11ZjJ0wMBbhtuoOmWWNDmNk9SaU7fnyhuXU6NB2wQaCWD9QbyYS86gHjzR49JrUn3FPBlcV1bTgQVuZbQBYsKMYBrMFVqvUru0rVc37HFGCGcMweUg8Trdl/u8s63NFQxsOlzfJVQHcBCl5G1zVarQo7/vAePfXyVtPHoKf7j8Fc+6civdmTADQvoS8MzGnPm5ALGLCO/7e+tonrG81KZ/HBqfrd1WTAQdtfXNRXQQAbjtlKKbYSgh3tTSt+P7Hhgf5NThDnMdDEyIwMD4cw5IiERakQ6vJgryqJnubbWuTB3ZTcJXoo4l2odPgqsqOAxMiQvQ4fqAcKLYuq0rZeDw82bEsoCRJ9nkHD/qfQTqt1+WmAaChzYxmW9bdCQPl53N37RDvcavJgl1Om/hFkNGwxPbtnbgmiT5eeaMBVgnQazXK++uveUVXxGc5LMk+Xpu7tRBvrDyE9dlVCAvS4dObJipzYUsePNVlKVc1f2euqm42KuseSzPK8KmHAbbeEEF8g5wyV4mMab4QbcAxqVFKUJ1akE6r9K+P1MuZvUWm89evGY9/XywnAvD2fa3uQiZKAMq8syfr7uuzqvDa8kzlZ28rCXiivsWkWgd1Xc793xePxoJ7TlLO20X3nYz7zxrucJ9Jg+Px52Nn4p3pE1w+hnrNUGmTklwn4qC+icFV1CeIzFWixrcrIi2muixgdFiQ20CL9dlVSs302hZjl3foSZKk7ArZXVTXpbSSG1U7QuRSZ3In/4ftHU+K7SqstQVvBOOYFLkxFrtyhRlTBrlNRX/huDTce2Y6ANUOMtXfioWr2hYj6ltMSsdOlIoRYsKCMN7FpLK39pXUo6HNjKhQvfJ5aTQavHHtcRiRHInyBgPun72z0ywVHaXyF8SkTUldK6JC9Jj1t0k4eXgiLhhnT3fuboFMyfYVI3ZwtI/8lySpXUfKmegkimCE9KRIhAbplMxsnqTGF5OQ/ih1sXiXvSzXcQNiVLtBqxwyywDy4LbaRRY4b+SqBlNnHZuM00cm4dO/TUKwTouVB8pR22JCZIheOdeEUWnRODk9ESenJ+Kk9IR2HUqx6NddARhFLoKr8qtblJTVpwxPgFarUeowA/KOGPG99GUBWx0Uqn58JVVxRVOXd2CIYMoQvRbhLnaNq8vq6bSaTnevqyllDrzMXCXOvdNGJCIsSId1WVV4c2XnWTokSVIWqZy/h55MTPYWpZ1mrrL/XkwMiB1mYkFMyKpoQmWjAaFBWkwcHNvusZJUj6XOupAc7X7y2GSx4v45Ox12cKmDsKxWe1a0O08bhmCdFvtKGpRBkihvecn4NESHBiE1JlRJsesqe5UYyB2NwVUZboKrxPlbXNvqU1pk54wzIkNWoN9LdQClxSq1O28B+VrRarIgPFiHEclRuM62g2huFxeOxPmTFNXxRMCI5EiE6LVoNJiVXe2eajSY0WaSr+3q72f/2DDlunVyeqLbwIUQvQ4jbf07bz6bnE4mHTvjj4lb9a5njUaD0CD7a/p2U77Sj7164gCH51K+A24Cd+Ij5AnzrmQw9DexwBsTFoTzRqfgxqmDMETZndn1cg9dUdFoQFWTXD7rquMH4JxRKTjH1l7OdZPtz5/yq5vRZDAjRK9VMse4khAZouz8UyayO9k84i4oZXhyZIeBVUJ37ajurTapSkHu88MkrVq57bNQlwtzZ1B8OAbE+Z4Zyh4UGoHBTp+luk27dvIA6LUa7Cioxay18oT4+zOOx7mjkmE0W/GTLVONOnhBCWLxcXOIurQGAJySbg+YEpTANKeSiiIQZF9pvRKgqA6uEv+ubjZ2e5mKripVFtg67vuP6ReD6FA9Gg3mLl0/1EG1nkqKDEF0qB5WSW6TRZ9S3X+yL8h4vttdHsN3PJcwLCnSYbeykBgZ4nKBwx1RuuiAh+Nq5Xvgou2dfsJAaDSebdQD7OdptNMatE6rURbUnReNO+NxcJXq+E8enqBkHnKVYV5NvdNbo9HgpPQEaDTAofJGlxt4xE70GU7ll6+fMgjXTxkISQIenre73ftVWNMCk0Xua2d00rZ+v6UQ83cUQ6uRs+ibrZKyq13YoNpQKajbJ9FXCwu2zwNVeBmsIzbQiHP33z/tU4KXukqdZfSU4YnKpoTOPidXrFZJyfAn2k8x5hTtvBi72sewHW8usAfqdC1zVZBOi6m2c1xkbEhPinA4R2LCgzwKABL9eG9LObrLJi2CGUrr25T2NyJYh+hQvUdBoyKwJjUmFFqtRmlrxIZMkW2ttsWEsf2j8eIVY5XXP8gpswtgz4puNFuR5UN2RWUxtpMxGAAE67WYYguKnL+jCDXNRui1GhyTGqWMU3Iqm/DbAXnu7eThCW7nv+1lAe3XVnEsRrPVo/kg9Wd8pL7VpyAzT4nPqa7FhPEDYpAaHYqaZiN+O1COQ+WNqG42IixIp6wJiD6Kq++byHQ/f3txh8cuMimO6RetrAs4i/YyuEoE7EWF6ju8Tmi1GkwYGIuT0xNx6fh+iAzRo81k7TBzjbK2kt5x1ioAmDI0HjqtBgXVLV4FmKizJztvchbv37GpUQ5tSJBOi49sJYQ9KU2rJsoCxoQFKxmWOgs284TzpnSdU/WHI07n0KBuCsoR378bpsrz2ptza9y+NqtVQk6FyNzkfhwqrrELdxajWVV+t39sGDS2TPpVTUa3Gxvd8TZoH7AHGMeGB2FQvBwY5S7roXos67zWllvlOnMVYB+3iTlbcR1NiQ5VgpgGuli/8hd1P+2aSfJ4bVdhHT6zBTC9ce14XDA2TZkLc7Wp25n6PfdHlinRToqYrjdWZGJdVqXPj+uK/Tsmv+fi2pVV0aiUt/fWvtLOz12xzlta14Y9xfVK5vyrJw7ARbbkGa42BXiiq5mrxKaQzsY7ckCxHPgtrhP7unEj8OJdxTCYrTg2NQoTbBnlnAXrtZg8JF45bycOinMZFDggLtxl1irAvp5eUN2ibFIY5iYgnPomBldRn9Bg67xHhbjviCuZq1RlAWNUwVXOE33q3X2SBNS0dG2xprbFpEQ9m60StubZJ20ziutx9ptrMOWlVZjy0iqc8uof+HqDnMa3vsWk7AYUHT8RJPHj9uIOO8p/2HbYnWyr4Q04ppYX2T868uj5xyjBXIDjZKkoCVbTbMJ+2wVblJpypk7X7CuRlvekYQkOF6rIED0++9skRIXosS2/Fm//drjDx+ks1TAAJd04ALw9fQKG2Trm0aFBiA1vv1tLTZ25CrAHnag7p1VNRrSaLNBo4BD0puZ8IRWdRmWCsZNJGosqYKGjBY3i2hZc+fEG/NDJTlYRxHC9bQLyhCFxCNZpUVovd8SW2qK5o21ptT0tYdAZ9WKKMGFgLF6w7SoFgBOHxbucxO6IknXEDwNPV8RE7KD4cMSpMsD8YFvoF9/rqyYOQJBOPp+d0w2LY/zHD7sx5aVVOPmV3zF/u+PiqMUq4a5vt+OJBXuVoIp12VUoqWtFdKhe6RQDwNDECGg18q6Yyi5OfIpBe3xEsMuJKfX3qX9smEcLnYJYKK1qMnQ5MKTWtqsUAB6fdixes2Xe+2RNDpZldFyqoa7FpOz8HRDn2B6IwXhuX8hcpZRjcd2WqBc/xTlln5RtdRiEit3xJwyJV4KR1dQBVerAD2UXlIsAuZeXHsTWvBpEhujx8DkjADgGYdW3mmC2fe7pyRG4wFbS7YbPN2PKS6vwky2DorpWvLgeLtxZ7BBQa1QFTudUNnkUVFpS14rrPt2ET9Y4ppOXJAlPL87o0uRWd6pvMSkT2c7psdNiwqDXamC0WL3eHa3OeCPOE3d9o+60MbsKV368QfleA+0zLbi6/opjHJ0WDZ1Wo+yGW5dV2W5SfNWBclzywbp25XoBzycC9DotRqV5V15WfE+iQvUelzhy5stn40vmKvVzext0Z7VKWHNInqRSLyCKxxX9jZPTE5UgKnGt3ud0jjqz91G7Hly1o6AWZzn1y3+2tT9doe63aDQaaDQapf1SBzhtz6/BZR+u73J2tY6IAIIRyVHKuSXay0W7itFmaj9R12q04Ob/bsVTizJ8busyXGSH6YyYUGxoM6O+g4xj9mxvngdvq/WG4Kq5Wwtx+YfrO1wYL6huxiUfrMOSPb4F4qkn2wtrWjp8b7vKVWk7dzQaTacZZDwhFirSkyOVjEHis1S3aclRoThnVLLyd3efPgyXHtcPb0+foGSqBpyCq1QZnjsrNdUR5zGgGAevt21EAYByNyUVk6NDMTIlEpJkz/yi7ltHhwYhToxB/XgO7yioxaUfrFfKtHaV1WrPxNhZ5iqdahG/K+dCZ0G1rmg0GlWpkCaX2a/E7VVNBofvx/O/7FeuA1NeWoXLP9qAOts4qL7V/djB35KiQnBsqrworg6WdKejUjgD48OV81G9Ue/bTfm45IN17UpBiWCk6OD21wRvSyZ5Glwljj80SIuJg+KU/lh1J7vZcyod+zbxEcHKJoE1mY4LY7sKa7GnuB5BOo0SxK32/GVjMGFgLOpbTbh39g6Ha6O6T9lRVpsDpQ14Ycl+AMDjFxyLY1Oj2/29nJndsUQUAEwdFq/Md6n7aqLd8GZDktUqKXNyr18zHueOSoHRYsU93+/wKqvm4fImVDXJG3KOHxSLxCjPPidXqpoNMFkkaDT28aVzGynGuWIMW97Y8bxBtYdlvl05Rcm4WAfAfXmpzviaucpd+TURYFbZaFDmnNJiw+R2z4PNdM6lXEW1gw3ZVZjy0iqc+Mrv2FfSgPgIuXyzuoypq76UOpDA27GB2WJV5to7yx4siDZNjBtGpEQhNEiHpKgQpESHQJLkuXP1fV2xlwW0XwfUQYKejLXUAZxWybFs5ZI9pTjl1T8criviv1Nf+wMr9pe5eshOvfjrAewvlT+nT26aZN9YtLVQOXemDotXgmPE517dbITRYoVGAyUj2jmjUmxZnw0djkvWuzkn1bzNXKUOXHYXCOdM6xTw44okScpxd3QeCFGhQcoi+moX2Qs7U9Nsf927Cusc5qNEULKr43AuTfvVxvxOn8tssSpBgXHhQRiSEIHIED0MZmu7Mp9dVewU+AGo5h+KG+ybym19v+4YZ1mtklId47Lj+iE2PAhNBjP22Ma7K/eX4YJ31yp92CMNbWg12YOl3Dl1hBxkJ9p4UX43WK9VrjG7i+qUTayjPSgLCPi2Qde+QSNMyZRY3Wx02cdQjwPUpbYlSbJnrnIRmCGuryJoS9mkq1r/sn+OvlWf+Xl3CS5+fx3yq+z9S3s/LQLJUaE4d1SKcttdpw/DJeM7Xqd0RV2OsbOMlp4QAcvj+sfguskDYJWAB+fu8ipwvDPOa5Mp0SFIjAyBVUK77+++knpc/uF67CjwbLzmSdY1sc57pL5VuWaI9da0mFCEB+tcbgrwRFf7YInKRgqj276LJEl4cO4u1LaYMK5/DF66Us4O79zvWLKnFFd9vMGnMT0gbxL/fos8Zrq+gwQl/hAbHuzQ1vaLCUVEFzbkUO/H4CrqExqUzFUdBFcFieAqqzJ4igkLUhYq1Tt7KxsNWLlfHliI4Ieqxq5NFjg35uuz7B2fD/7IQm5VMyoaDahoNKCkrhXPLzmA5fvKsCm3CpJTCuhzR6UgJiwIlY0GpTPpbFt+Db5cJwdonTc6xeE2EVB104mDOk1hrdNq8MH1x2NYYgSiQ/UYkWJPR2gvC2hwm0VDEDuBN+RU+xxF3lFt92FJkXjpqnEAoJQydMVssSqfSUfBVSfYyk3867yR7d7HznbYH2mXucq2g0O1GCw6Uf1iwhxKBqiFB+sdAq/ERIkywdjJwmFNsxHq+SZ3k9ifr83FrsI6vLos0+WiGyCnyD5kKydzma1ec3iwHscPigUAPLlwLwy2rFbXTh7Y4fN1lbsMGzOmDMLNJw0GAK864UMT5HO7zWTtlkh38Xnb62fLA7JW23sszuP4iGBMnzwAGkg465gkh8c46xh5cajRYEZFowGl9W2YvcUxyOBweSNWHijHD9uL8MYKOVuT2Il75fH9HSbDQoN0yuRKVwd84nyLcxFECTiVLulCSUBAnkDTauSJqK5mPFu4s9he6nRADC47rh/uPG0oAODR+Xs6LIMkvocp0SEO7xNg/75VNRmVBZXeyl6OxfWCc2iQDqPTohETZp8oEteVNpNVSSUOdNzOAvYSDYBj0FaybaBe7hT0uXhXMb7akA8AeOu643CibSeweheWyLAXHapHiF6HW08ZAq3Gft5brBImDIzFRFt7AwBnjExCZIjeVkKsud1jAfL51Fk5uzaTBfd8twNb82vw8epsh0DL3KpmzNlSiAU7ipFX7XlWg+4iFgYHxYe3S2ev02rQP863XWbqjDejbUFDYwf0bHBVflUz7vl+B3YV1uHhebuwr6Qetc1GLMuQJ53FNdHVa3TOujU4IQJnHZMESQIemLNTmdg8eKQBD87dhX0lDfh5V/v+gpgISPBgp5xo17u6kNCVwAR3xvRv32/1RIvRrJQSDFTmqg9XZ2N/aQOC9VqcPtLe1jhfJ08dnoihCRGICNahzWTFofJGpZSCu36nWJDxJrjqu035yHPqlztfcz3hqt9y9UR5d+buojolgOPu73Zgb3G9EnTtD87fAwA4fWQS+sWEoq7F5HIBZ8neUqw9XIm5Wwvx3u9ZPj2/+K5OHhzn8d+EB+uVvq27jQuA+8xVnuoNwVVfb8jHnuJ6/HnY/Q7YFfvLsK+kwePyXe4475bvrHxVV4gJZk8D3SbZzofMMu9LU6oDqAYpC4VymVj1TmgA+PspQ6HVyH2Fx6YdA0AOTpr1t0mICQvCiORIJZMDIPdnxDE+PG9Xp1mQ3XHOXjxxcBxC9FpUNBqUdkEERSS7yEx4sipzTbBO2y57YXdkBXh9eSYySurx3aYCr/6+qkkOitBqgBQPrmmi/NSOgvbBza40tJmU8ugi0MhTIgNSVnmTUmJDfe2IDNEj1fYeizIy1U0GfL0xX7kOVDQasKeoTgn47mjs0B1O6UJ5IufvgbMbVBv1TBYr/sgsx3O/7Me+kgZ8ttax7MlaWxuV7CJeThzTzoK6LmXGVmeN78jJ6YkI/n/23jpOkqte/3+q2nWsx21H1nfWLWuxjRvE2I0AF4t8uUEvTiA4gQtc5JLw42IJcQLEIdnoSrLuOqvjPtM9PdNevz+qzunq6uruahnZyXm/XnnBjtZ0Vx35nOfzPDoe186vgNmgixHtJKsnqf39l80WGza+/9IRWrsZHAngvif2ABBrCEUqBz8mvQ4P3bEEFoMOh9rdMeKRZtn/T+bU8/LBDgTDAi6cUYy71tWrOlqc6hnG0GgQFoMO82X3ptNswOVzSmEx6LBCemYAmdtzBk5IRzujTjaLawrwsw8tQHmeGR1DvoxcGcgcs7yuCCa9jq6be4b9adf9yF62xGGiDXPK8a+COlqZoOc5hCNCQlcPQBbznZG4KtbdJtNmhOIsnKvaB0dxqtcLngN10iIU2Yy0hkgioYhQaprLSvfRiV4fpShieokd00vsiAjitQ6OiPfkrzYuihORKiOjBkcCMTE+me4NBkaCEASA46DJrQSIzplk39AkS1IgY72y9qaGWiyg/CBdyz5PKXiUrzX/vPUM2gZHY+YV8l/rwGjG+4AX94uNhA/eNB+V+RbcKjkUbmnuw9OSqGx1g4sKJ4iQgoisiu3R582g43GLJM56LIHTrSBEBZrJREqZiqu0NEGrkarpp98boM/gYo37k8ulM4AHXzmWtguRfA8aCEew44z4jPqCYbwi7cMuVNR9CYtqCvCVq2YBQMrmZyD2Nc6zGMDzomsjAHz5bweycr9Rez/I/nL3uQH6jCidq9oHR3PWvNw+NIrRYBgGHYdpRVYapbiluReH292474k9ONrpwc+lBnviojfNZUvafD2/Sox/JcjHeCJwII269S4bdVtOBRW3ZtCgK3eBLbAaoZcE1mrjuHy/vLdlkMZI7m8dQrfHDz0nYLrKWlAp+CXOVfIm3VztNZ7Z1YpD7W48JWsOj9uvrRH3a+tmFONL0n4tXbKNY1Qif02+c8M8NBTbMDgSpOviXBEIRehYTOZVjuPoPKYcz/6yTawh/Glr6v2a2DSrwblKFrOsPAeIEWuneT+PBsI0dYDUqFNBakGBcOLo64GRIPZKbqu/vWMx3buf6B6OOcv85aYT2H1uEH9XqfWmw/dfPILm7mE4zHp8YGFlVj9LC3KH5kxF/YzJCxNXMc4LyIKCdJ6oYSaxgEGFuEqawNoGR2mUyN92tyIkHerWu8SBrU9DFJscpXKaTFjdbh82HRW7IP740WV46b61VCjyxaf30Q2NfNNi1PN0ManmBNXl9uHev+5GKCLgugUVuHZ+ecznVzW6sOsb6/HVq2ZruvZ8qxEvfWYttnzlkpgOwwIqrgpSUUoiNfTimgKYDTx6PH6cyGKh4wuG6aYk0cb4klkl4Dhx05hIoNEx5EMoIsCo55Mean501TTs/MZ6/KfksiInWZa4xxftZqXOVSqL0xaVLhA15BNqnHNVChGK8l5Vi7oYDYTxrLTgGEhw6AZEhWRFNmOMQxm5P8lhycbl1dGM+jS7WRORzGHjgevnYvvXL03pxKYGz3NU6JErIZiccwnyswHRQUounPvG1bPw/aVhKlYjXLegAu986WK8dN9a/Oa2xQBEp7HY3xP990NvncQj287g1cOiKHTjihooiS6Q0xOLkHGxKIG1vnzTXZ1mQUQny3hPp/goCOrxh1++chZWNRTBGwjjrkd2xRTK5CQr4NhMeloomMzRgL5gmArfKhI4VwHAs/euwttfupiO5WZDtAhONvLBcATvSQ53iQpm8oNU+QF31LkqOucdah/CV589AAD49MWNuGJuGRVnyTt4ezyxXS2Lawqw9SuX4qX71tL/nvjUyphOEb2OpwIxeTFT2S2drMArCAK+8Y+D9Gs8/hB1jARi59mJjsUDEkcCErIthBDHm8YSO3W8IRu8073eMY8hGgmEcPeju+D2hWDQcfCHIrjrkV34v82nqYByveRGojb/qh2c/uim+XDZTTja6cGXntmPwZEA7npkFy20t6t0txFXP5eGQ+JMHZzIOJco9k8L8t+dziEW6f4stBk1H14omVPuBMcBXW6/atROMt442o2fvyYWQL/3gXmqsaWE1dNd4HmONkD8Y08b/KEI7CY9jQVTUiDFAo4Gw2kVlAVBoJ2fP7l5Pv5nw0IA0a7ddFBbtxQ7TLh8rlio//PWM7jn0V107M5FlyUh2qUYPWASndzEOfIxFbHYE7JY5//ZdCJjJ61ujw+vSd9789J4J5BkaIkg6JHuNWWcmvbfQZodsutizJRwRKCFxmRrHfIaqMWfauVc3wha+keh5zlcOEM8wMnVPCZ3xtUS3QNEBd3JDsJTQdatjSV2FNtNMOp5hCMC2gdHZa5WYpf2ivoivPu1S/GHjy6LcVCbXurA21+6GM99eg14hV3/T26eT12Qv//i4YyuUekkajboaMMOcQalIkGVOUa+9qoqsMRFCiTbg2bCqZ5huu7L9P4g82iJw6zJra5JinE/0ObWNHeRNU2Rzaj5cItA9tGvH+2Gxx+CUc/HCY+o4EUat4lD1PQSO166by0+ItVnyPyQ6eFvpsjdz5IxGghT4XQiIYjoTGJEj8ePP245jc88sRfkLXhubzt1L+oYGsXrUp1qeXH8Aek0KTpHfmisBSquSvE+NpbYsfOb6/FDqXGO7FcC4QhtplSDjBHyv//ui+qxQHKg+tQjOzHsD+G+J/aipX8U1YUWfOu6OQl/Xlmemc6l8v3ESUWMZCLhKvme9bNLpEMqm/T9w3FfM7ci3u3xFxsWYvvXL40Rt6jto7Sy9WTUycao56mACwCN90uHaGSdWE+hB2OhSNp7BjUX5mKFKIrU1nQ8R9fPZA+rRtQ1If217sxSR8z3ZdqMQASnmYiryOs7vyo/zu2N4zgqNtsliatIHcCk19HxKVENQ+lcxXEcnvv0mpi999avXKJad1Wu15SHrpkKuUlts9BqVI3TUWNWmSOmGUa+j5D//8YSe9I9F3WuUokFBNJzrrJKe2jy+oQjAg5JNfP/78NLY15jMsZlFj0XwIDUIEfep6oCK9ZNF9d8pDF2daMreoAuzRHttDEvtna0Qeb6rHZNp3u9aB/ywajjsbS2MO7zBHK/BkKRhM27amQ6v6qN03LIPstl1y6K/tiaOiyfVohhfwh3PbIrrTFN2eBDnuWXD3ZgaDSIynxLjJheyQcWVYLjRHfAVPvswdHoGRiZQ75zw1y47EYc6XDjK8/uz7jJXe39IPWHfa2DAMRkGFJPKHGIa/NQRMjZ3pbM69OKbNDreHqv//twJ+56dCd8QXGNsvVkH870elVTL9Qw6Hh6FgDEjvHk7yU19WTOP0qizlXpN2bKG2Z5novWV1XmD/LekL3Qe6fEtTxpzFlQJKjGUFP3S+ln0mhHWZOu2vlVJpDngKyfBUGIq5EsryvEu1+7FH9U7NfSJZs4RiXy18Rs0GGtNKbmutm0fXAUEUF0aZWvdxLVF0nCgJb9WtvgKAZHgtDzHGaUJm5MIcLbk93D1NFfvhclz1G65yE7zvQjEI6gPM+MaUkc5OSYDTp6zyZK6SFn+DajDlUFVpQ5zXDZjQhHBOr01e320bPnbGofz+5uxZ8k98Cf3bowrrl5LIhxV85Q1M+YvDBxFeO8wD2q3bnKp4gFdJoNNCrggHRQRQ4bNi6v1ixoUUI2rsumiYraY10edHt8eHpXK8IRAUtrC3DxrBLMqXDim9fOwYo6cQFPVNHKDe3qBAW2QCiCex7dhR6PH7PKHPjxTU2qloVFdlNcMTkZZoMurpBZKB1cDYykzqBWKypnwq6zAwiEIihzmhMulO0mfcx7qAZZIFYVWJK+DhzHJbSvTHaATRZiDrOeLgxIdEXvcIAWLWm2coo4gUbZhEr+bnJdvSks14nLGnGXOdLhjhOdvXSgg9oIA1FLbSVRMVjs9crt680GHjcsrMTyukLoeQ4t/aMJ3b3SIVkXLsdxKHGYM7bnlFug5xJBEOJeM/lCSdkNqeM52BIMW9WFVsypcGKt5O4hv4+A6HtDIk+/+c9DVBRK4gfkKA8RtNKf0rkqvtslHUjBK51i8c6zA2juHo6LOtXrePxq4yJU5JlxqteLzz+pHuuW6jnM5SZtrOiUxhyzgaeRpWqYDbq4wizZRJON/P7WQZqzTpyLlJCivo7nYiz7lRbTgyMB3P3oLviCEVw4oxifu2wGgKhTgzcQpvcxEYLKx9yyPDPmVDjpf2qFsFJaHJAJtRRjXDJXn0ffPYtndrWC56Lj6xbZPCWfZw8kcIscT+gBTKX6e5NtIUTN8abYYUKZ0wxBgwtYNgiCgC//7QCOdnrgspvw0n1rMa3IirbBUfz6jWYAolthooPlSESgMcXy2KBSpxm/vWMx9DyHF/Z34Jpfbsa5/hHqRtqhcihD5kktkRTzMhQ4deXAuWpWmQN6nkOfN5BWAVNux54pNpOebvgPpeGcdabXi/ue2ANBEF1Ub5WcLgmzpUhHIHp4C0Rf57/tFsXgcyucCddwdpOevr8DabgOnugeRo/HD5Oex3ULKuh6u8Ptgz+UXtdvonXLBkng9MSOFhpHBKjfh5lCDrWU6/Jbl1WB54D3TvfHxN0e6/Rg97lB6HmOzqOffXIvFQGlwzO7xKaURTXq649kaHGV6qKOP5k9N2Suz6XrTzq09I8gIHVyJxMZEXG+MrY3HUiDw6KafOp6kqui8MCI6IzLceIhqBaUxfx0iUSEmMgvnudQLXXC7jo7AI8vBJ5DTOxficOsekCbZzGoxrHWF9vxsw8tBAD8edtZ/G1Xa9rXqRavEd279yEUjtA1j5rrlzwKTK1RIVcHHoQnZG4Zp3q9tFEtHWiHdwL3VCVzyp3gObGmouV+oHv3DPYWZB8tjytVOhko1/pkT7huRjHmVDhxjeSOvLW5F5GIoHkPnyu07qvJ9ScTThv1PG5aIgpff/DSUXh8ISypLcC0IiuG/SG8sF+MIn16Zysigli/KlXp2+A4ju5l1Rr+EqE1FhAQBVjkvTIbdHCQA5cEtbhwRKBzm3zuFR2oFsNlN+JopwdX/PxtvH28B2YDj4fvWBrTNKaGmlMnca6qksYgtcMbQRDiIlnU9pXJoo5N+vg6XEkWTkhqsVir0nBGkxMMR/CeJEQkIgGLUUedQFLVqZR0qIydRtmhPRAVAsn/fyIRsi8Ypg2PmThXifd49HXKVFxF368MxHBbUjgEEcHMXinWSj4G0wP+BDUMNXGNxaiL2XsXJBhHlOs1suYlz8MRKcY7XTKJceR5jt7DQOxzJF8Hp4qCI4JPeSygvKag5W8izyRxCSevz6meYYwGw7AadbhEqvuT/0jj9Ln+kbTXe+R1r8y3xKxpNi6P7q2KbEbMKnMkdK6qyIudt2uLbFjdWCTFKcbXhck9uaS2IGmsvd2kB1l+peNelajmnAryXh9ud6tGhZLkigqN6xRAFN/8+vZFKHWa0Nw9jC8+tU/ze0T2n0S0R143Eg1/69LqpALCQpuR1uK2phC+Eod9eR2wPM+C39wm1j/+ubcdf5Bc5NNBEAS65pDXdhuKbTAbeCrMLs+L1uJ5nqPjQK7WqUoxDnmWD7a5qUh6uXTe9MSOloSpF2okGuPJ+o7MIcmcf5TU0/QDf9px7O0KkXFxgvr40GiQJg9cPU9059xyshfD/hD+uVdcx60qUR+vSumcRMRVZCyIzgXk+evzBrJqriTN2QdaBzE0EkTvcADuNPZr6UDuj1w0RdO9nPSaZNpMmQp50on8PGuuyrrTFwzTRI7Tvd6EzeMEcq0zpKjcRJB77e0TPQiGBVTmW2LiNDM9OyJ1iNWNrrTO6uTRgGp4FGlVHMfRef+Q9DfLTR4yrX0cbIs2id93SWNcmtFY0aQQhTOmFkxcxZj0+IJhWrB2JnGuMsmcq5QFHjIof+xPOzDzm6/gTN8I7CY9rp1fEY1iS7NQQDaucyvy6AJ5S3MvVZRvkLmtGHQ8fnP7YlosULOApjbs5wZibNh/8q+j2H1uEE6zHg/fuQRW49hlsxJxxdk+Lz18SabmV9rZD3gDuOm3W/G5J/dq/p2kGLSqsSjp5DyvIvnCJxfdpskOgOjGTbY4dZoNdLNDFlAtGq+DdGCXOk20uBYVV2lzrppeYqcxCltPxm7OHpcEhLevqAHHid26agdqiV63+ZV5tNh5TVMF8iwG2EzRuMBUXbapCIYjNN95LBYXpBi48+xATFfVQ2+dxOU/fyttRw7CwEiQbkTIBjNGXJWkUykRavcREH1vPrpqGi3QANHoByWNSaxdj3d5sO7BN/CHzafjPkfEVYkK9g6zAQXS9aVyZFMjWWdOIoiF+nULyuOKz0V2Ex66cwmMeh6vHenC/6n8TcQFLFEBJ9km7ckd57D6R69j5xltmedjRbtsQ5yuyDBqAyz+jHckYdGqhqKEwoVi6TDQZY/tKiXvX583gJnfeBlLv/caWvpHUVNoxS83LKJfazfpaUcnea9JZ4pWB4zo7yQFh3jnKiJaSDQX7DzTjweeF50pvnzlLPzHajFKkoxZ4YiAbbLxMpdxSpmSSsxMxuezWYqrlD8/2wg4Lfzf5tN4fl879DyH396xGNNLHXj4zqX0XiECykTi5lO9XngDYZgNPOpdsaKhZdMK8c1rRWeCtsFRmPQ8fvBBsVNY7VCGbOaLNdyPM0odMOp4uH2htJxEovFmmTtXmQ06Gtm8/bT2cehkitggrTSleV9EIgLu/etueph7/7Vz477GbNBRC/vVMYcl4vqZzEPJipwcx9F5Kp1oQNIAsLyukDr7WY06CALQlobTkdydSNlxtqbRRdcEPAf89JYFAMR7Ll0BlxrdHh+63FK0Z0WsuKk8z0Kjhv+wJTofknXgZXNK8ZObF2BpbQE8vhDueXSXqig5EZGIQOfkjQnWH8nQIq4ia7JMRYlkbdLvDaiKSJ7Yfg4X//TNjIRlWpCvJZIJycn4pozt9QXDuP7XmzHzGy/T/z76x+2q7xPdNzW4VPdGO8/0Y8l3X6U/Z+79r+D375yK+zlqkP1HgdWoucuYuI31ewMZRe51uH0YCYSh5zla9CX3zBvHeui/yT4/Uy6bU4r7JNfir/39AM6keS+oxWsQEcp7p/rQ6fZBEIhAPX6OcZgNWCAJhNXW0rmMtvSHwnhGEpCR5eMhmYi6y+3DJf/9Jr73wuGYA8Vhfwgf/sN2/Mcft2MkEIo7hEiFxaij848W4Xo2e3flPNekIk5XdmUrBSgLq/NhNerQ5w3gaKcn48PfTJHvq5O5QmsVThORLyAK6P/39sW0HvX49haEZWP5h5I4ECZq+EuGOw1xlRLS6JioFtc+OAp/KAKjjo97b+QHzcTd68c3zY+bJ9VQjp+CIOCUdK+QiBC1dVCX24/e4QB0PIfZUg1Q7h5NnimlACsVmeyXAbERk6wV5Y4pK+uLwHPiOprUsbSwr2UQ3kAYBYqGHOL6qqUh9X/fbEbTt/6Fmd94Gd978QiA2LETiJ3vK2RCICIK6hgaxWggjI/8YTs+8oftVFhBnEGNOj5pbTgZpF6j57mMa4ekEajH409rTSV3U12laMojEDGVV3Jplb8+qQ6aE4lrtCDfi8mdSC6dVQK7SQ9fMJJQ1JWMaIxjevWA1VL9S8dzMfeifK8gr5GpQQ5qycGtPxSm/9+g4+ALRpK6vvuCYbpeWyoJPchcQcaHObIGEkJFvgU8B/hDkbSdPRM1cogOheJ9d4FU01HWfKgzi8q8Tdbwv36jOWa9OfMbL+PbUu1E2SiqhOM4+pqmI646l+H8Wueyw2rUYTQYjmkgIUT/3vTu9xKHGb+9YwkMOg6vHOqkLiapIPvPy+eIwpdD7W7sONOP7af7wXNiw0sqtLpWkvtO2QC7or4IX79GTCz5wUtH0haGDI1GEznk7ol6HU/nNCD+Hsq2HqVEeZ/XFEabr4hI+mNrxDreM7taaaKGFteX1TEOPTLnKoXTTqLGRjXs8vSDNMfBDhrXKn5/ovmejC0uuxGXSffYluZePL+vHSOBMOqKrGhIcMmk8b7LQ4SW8c9GzLlDFu9jvyT8iwjiORN5L6sLrTmP1c6pc5WiaYQ0bh5qd6c1jyvxBcO49aFt+PifdsAfCids1iBzlzzq7linByHZ707V3KglEhCI/o3BsPizVyvOW1O9roFQBHf8/j3c9/iemL1iNGIw+VyhpIieuydwrvLFO+CSdTr5mzefiNbwWwdGqQBVKwNeMenAH4rg4pnF+Oz6GWl9fzYw56qpDRNXMSY9ZJDlOMCWRFhE3F38CucqAFSNGooItPB7x8pa2Ex6uslTumKkQm65TFxyfrmpGS39o3CY9bimKTa6z2U34bd3LIHDrMdlc0rjik+kkz8YFqgNu8cXxKPviocjP7llAWqLMncj0AJ5LfZJBdHKfEvSaBmyMXjvdD98wTDue2IPdp0dwN/3tKVUXBP2SBaVK+uST85RVbn6YiMX4ira+a5y2KbWdSf/HtL9Qa8jhUXmqgYXTHoel8wqoR9z0eJi8nuRbNCL7KY4gRsAnOjyYOfZAeh4Dp+5dDoukmJDnlDJdper6uXodTxuXFwJi0GHj62ZRj++OkfRgGf7RhCKCLAadWlvhrXQUGxDmdOMQCiCndLzNDQaxC9eO47jXcN461hmudrk/S11Rq2nXXYTLqgvQmW+JcbxKx2U95H8d9W5bPjVxkWolyIHr1HEghKIYE+t2Pb60W6c6x/Bd188jNePxsYCkQ6sZM/6hTOKYTPqaPZ1OlBXA7f2MXaHJGy6boF6LOT8qnwqqvj95lNxHYepxoOGEvXC5Lun+vC1vx9E2+AoHtse/7yMJ+Rgqj4DFxpSUG0f8kEQBNrpdNGMkoTfs6A6DzajLs7KvMBqpCJOfyiCUESAy27Ew3cuibPQVbqUkQK4FqcgOSUqzlWkMLu8Tixsnuj2xEWDdbl9uEeK0L1mfjk+ta6ezlNEuHywbYh2VgHiBjabzXS2DI0GqdBUnsUuh1gup3sYDIhdj6R4R9wmCTNKxefgbN/YCA62nuzFD18+CgD45rVz6O+fWebAT29ZAIOOwx0ra+A0G+icqTxYPigrXKsd9n/4glrcubIWZgOPB2+ej/WzxfVenzcQI6wNhKLCey33o0HH0867jMRVWThXAcA6ydHwOy8cpgeGqWiWub9kAznAILETqTjW5cHhDjcsBh3+9/bFMOrVt5fXLaiAnudw4+Jo4VlZGJK7k6lBCszpiKu2yjrsAPFggM65aby3bQPSAa8+/oCX5zncfWEDOA742tWzcf2CCrov6cxBfAJ5DhqK7apNFh9dPQ0A8Oi75/DKwQ74gmE8u1sUV2xYXgOjnsf/3rEYNqMORzs91F5dC9tO9eFs3wgcJn1cLLkWtDjykPVBpnGaDrOBrmFa+mOfF38ojAf/dQyne7146UBHRj8/FfLCZKKD8XBEiIl/lkceHWofwv7WIfhDEfrfm8d64g4wIjJx8JrpLvr8nOkbofuu37zRjD5vgP4cbyCMp3dqc2oi4gY1cVAi8q0GGKWxOd29NBAVhdYWWambDVm7EbfnXBUhP3vpdCypLYA/FKHRaFoIhCL0b5M7iMytyEOexQCPP4RNR8SfV5zESZoIXS6dFd8lm0tx1auHu9DvDaDUacIlkvBSfvj2wv4OnOrx4vebT+PRd88CEA/8v/jUPrx9vAdvHOvBl/92QCYo0/5cpiPajq7V02/cqCqw0PsOUD9kaJAdHMjjNMk60qjn6f/ferJ33GMBAW1CJq3C6TqXDVc3lcFu0uO3ty9GqdOMmxZXQc9z2NsyiP/vnVNoGxxFnsWAK+ck3g+QfcChdrfmuTYd5yolqZrLyF6tzmVTdUBYUV+Eb18/F0Y9j09f3IgbJGFUKpSHat0ePzz+EHQ8R/faaq425N6eXmKntYDaIvHahv0hdLn9sa6rWsVVGTg9A8DelkGMBMLUyYaQZzFgvhTVmY57VbTx0RUzlrlSHIwR/rm3DQ++cgwefwj+UAThiACeAy5QNJYWy9bJ8jGG7mEHffjqs/vx1vEevHW8B2ekvQpt3LEbM3Y4v2R2CYodJlw6uyTO8U4rLrsJHCfWl/szcFM1G3gsrlGvqygFrfJ/E+EgiflRkkxckwqlIIiIjqaXOujvTeYcnQjybKfjXAVE407Xzy6JObAvcZqxfFohqgstMe5WakRjAcUxSt6sRZyoks1XpO5q1PP0WSbrzGTudAYdT0Vx6c7rJxPs5ww6Hvdc1AAA1KmQPDudQz5EpDhlQN3J6fI5Zahz2SAIiFlvkufUqOdx5bzU6/y8NMVVovO/eF3pzq86nsPcisTRgEpHoHRYXFOAr10tipR+/85pVWcsJWROnFEabXL+8jP7AQAXzyzRdB1k3t/a3JvUMYtEQ6rNqx9dNQ2XzCpBOCLg34c6U/5OOeS9KHaY4lzK5POV0rW03iXej8c11gdSoXSi4jgONy2pgkHH4cGbF2BOhROXzi6By25C77Afu84OxHx9MmaU2rG4Jh+1RVbMlM2Lyv17OrGA8t+drtuPMh6XinMV871c5H9BQxGNkHz4rZMAgFuXViHRtEeaU3ukPXU7FXSpi+Qy3W+MBEI0shEQ18+JxqxcEBUUZ1+vVM6P9S7RrW0kEMapLBqwXjnYie1n+rHpaDe+/dyhhGLS8jwzimxi1N0RqRajHNcOpWj8PUDnneTCQOU6QpmcpNYUIGfnmX5sbu7Fc/vasVty0RzwBmizTrqmAq4UiVFuWQwqIbqnFOPmSU2PLE3TWY+EIwLue2IP2gZHUVtkxS8+tCit5KdsKbQZsXa6CxV55pT1Tsb5x9hZ4DAYOYJEAjpM+qSDX1RcFT1Ac1rEW/z6BRVY0+jCqHTQZuA5uqHP1LmqQ2a5PKvcid+9fYp2RH9wUaWqne7C6nzs+Pp6eq1yiA37UztbsaW5FxfOKMZz+9oxGgyjodiGy8fBrpAcWpGNRaoJe065E/lWAwZHgvjUI7uoOwoAnOrx0g1rIiIRgSqzU00wqYq1uXSuaukfQSQixNxvUZV7/OL0QNsQ/f1au17rXDbsvf9ymA3Re0FrLCARLLjsRqxpdOH/Np+OETsRW+JLZ5WgxGnGhuU1eONYD/62qxVfuGxmzMHnuSQb3W9fPxdfv2ZOzNevaXThF6+doBEKmS5I5AvwTAtjySCW73/b3YrNzb1YM92F5/a20Y1App0aie6zxz65AhGpYz0TyH0kF/bJXdCK7Ca88tl14DgkLAI2Fosbx44hH4b9oZgsdlKIFATgM0/sxXOfXkOFAzQWMMlh2s8/tBD+UCSjThTqQqTRLcwXDNO/Xb4ZVnLr0ir8/NXj6HL78eaxHqyXjZGpRI6Nss0EoWNoFJ9+bDcd/7ZIBY+xuD+1IHenSBfa9Ts4indP9eN0rxc2oy6hMA8QN5m7vnlZ3PzE8xxe+M816JIdGBfZjKr3QrHDhNO93qhzVYbFVHLPyA+pSTF/TrkTxzqH0Tvsx+EONxX8BUIR3PvX3ejx+DGz1IEHb5oPjhOdMCrzLWgbHMWOMwP0gPHimSXY3NwLjz+Es/0jMRbW4wnZQFfmWxI+g8rNbzr35LO72xAIRTCn3EmLk4RMIju10jY4ik8/tgfhiIAbF1fiwxfUxnz+6qZyXDyzhM6BROwyOBKE2xekXUupXL04jsN3PzAPX79mNswGHQRBgNnAwxeMoHPIh2mKcU7Pc5oP/1wOI451pRcbTWMBs3CuAoDPrZ+BzSd6cajdjXse3YWn7rog5fhL7fWzdK5Kt3BIDu1W1hcmFcf8v4sbcfeFDTHzZH2xHRaDjq7PUxU5iYBGayxgMBzBu6dEsa68CFRdaMWxLo+qmD4RZN1Sn+CA946VtbhxcSUVP1XkW3C614v2QV/WzREHWhMf4ADA2unF+MSaOvx+82l84al9+OjqaXD7QqjMt2CtVEwrcZixsr4Im452Y0tzr+aCMnHAumFRRUbuuckitwFxz0GesWxEidWFVvR7AzjXPxLjWkKEJkD6xXCtyIXaiZxRu9w+2j0KiPvIuZKglqxZltYW4H82LsJdj+zEwTY3DrYNxcxNRzpFsYPNqMPC6nwYdDyd3w61uVFTZMVbkiDpb/dcAIDDTb/ditO9XoQjQso1aiZzNseJe+q2wVF0u32061wrag4NZA9F9vO5crjleQ5rGl3YdXYgLdfKLsmVyqDj4JKJc3U8h1UNRXj5YCee3SNGmyaLtrx1aTVuXFSpKhSmz8nAaFb7KyAaBX/r0moYdTw2He2OEVfJhRYPPH8Ys8qd2H66H68c6oRBx0EQgOf3tVNXGOXeNxlNlXl4dnebJieFZHvQVOglATQRAc9VEaeTtf65/hHaWLKoJh822f5oTaMLbx7rwebm3ujhb4oGqVxC9tXbTvYlfN/JXkXLodVvblscs18rdphw+dxSvHSgEw++Iordb1xcCVOS9USxw4RZZQ4c7fRg28m+pHsHQm6cq5KLq5KNA3esrMXNS6rS2qc2SOsPcqhG1m81hVbMLHXAZtTBGwjjZI83Zj+qFrVt1POoLbLiVI8Xzd3DGPaHqOuq1qhmMv+l63KzJYEYChCdBfa2DGJLcy9uUcQ1J4JEVSkPzojotidJnepIhxtf/psoNLhrXT0+vGoaAMBm1MXFNJL1IsfFCquJWOSZXS1w+6Ju/ie7h9FQbJe5IGW+XnDZTXj3q5cim3M1g45HodWIPm8A3W6/5nmTuKkum1aY8H5Vihrk/75Acmo61O7GgDcQs3f0BcN0vZNOTBqBCIJaB0Zxrn8kJrarqTIP20/342DbEG5ektqdRw6pbabrXFXsMOG9r61XfZ+evGulptob2U8O+0OIRASZiNyEpsp8WhtI9DfJm2aUooRU7nQ1hVa0DoyiZWCEul5pIdmY9/E1dbhzZS2tz5blmcFxojtJr9efVFxn1PP412fXJRTC51kMMfXDRFBxlcZotN7hAEaDYXAc0l4jAuL8vuPMAA60DcU06ADxjkDpsnF5DX7x2gm0DY7inRM9uGhmYuExEOv4v7rRhaOdHirK0Oruu2xaIYw6Hu1DPpzu9dK4OSXElUXpXAWIa+910114/Wg3DranJ3hMdm4iv5eV4gxyNpSrCLWT3fGCnM9fNgP3XNhAz9IMOh63Lq3C/755kn6NlrUQx3F4+u5V4DnE1M3kf/O0ImuMS44WGorteOdEb1ouSoIgRBv1pddUzaUfiH1vCm1GzK1w4mCbG2f6RmDQcfjgogq899Zh1d9DBFsef0iK6pOaQhQNEtWFVuxvHcr4PEQput/c3Ateeo3HIpGE1LVIHKOyuVcr4YiATnfseKHX8ZhT7sTuc4M42DaU8fU/LmvKfnx7C10vKZ8xjuMwtzIPbx/vwcF2NxbVFNDnyWoU16PJxL6CINCIvFR1nGKHCXqeo65YyjMFZVNAmeI+kTd9PLH9HJbUFmDbqT4IgiheTLfWWZTirFMZCwhEz4hPdHlwpMODjiEfjHoe66a78NqRbhxoG6JGJ6n4yb+O4Z0TvbAYdPjdnUszvo+y4c//sRycYkxiTA2YcxVj0kPiHZwpijU0FjBGXBX9nkKbEZX5FlTmW1DijOZHp1LQJqJdZrm8bFoBjSoCYm3ZlZgNuoSDKe1ePEGyu8VJeuPymnEZgJXONak67XipqAxEu4tJfJiWTOSz/SPw+EMw6XkaF5MIYtnaNjhKM57lkAOybKz8y/PFTGi/rEOZEI1GiF+cAqItpT8URoesMJcKizH2XkhllUmIduyZsLyuEHqeQ0v/KJq7h+H2BfHsHrFDnWzwLplVghKHCb3DAbx2JNa1KJkYjOO4OAeKBdX5sBl1GBgJpuV8oCRarBk7QQOxKiUimcekwwYgdadGKByBLxiGLxiOifRJ9HpxHJdVnrjS2SESEeLuaaOeT9pdmWc10MKe0ja7TyYs8PhCuOuRnfBKdtADXnG8LFTZuBM4jsvY4jdd56ozfV5EBLFroThJodKk19FCmHxDEwxHaKdOYucq8b5rGRgRrbF9Qdz96G70Dgcwu9wJo55Hl9ufE/vhTPCHwtS9S9llooVymXMVeW2uX1gZc6CkRqL5SS8d4JL/Et0LpDjeLY2DmRZTqVW2TPRDfpbLbqLxL/LOnu+8cAi7zg7AIUXokr+VCJcBcSwgHS8Xziym1udjGYuXilTiISB+85sMeeeRIAiydUR13HtbSh3C0ncbif6O+I/5gmHc8+gu9HsDmFvhxA8+2KR6X8nnQJtJT9dj8mKP2iGWGuSe5DiOFq7kzjBkjVdoM2o+tM5EfE8OxUqzdK4yG3R46I4lKLAasL91CN/8x8Gk3a2hcARneqWo3Sy7BknR8pQkyEjFZmoPnnqsUs6TOp6jQhibUYe6FCIkcoik9T3Z3zqIYX8I+VZDjOAmleBHjWaVIrASufiIjMMdQ9oEXIIg0HWHLxiOcdQjQpBkz8FXrpqFC+qL4A2E8Zs3xCL0hmXVMff7qjTjnvqG/fiX1BGdbG+TjBrZOlntfuob9iMiiF2I2RyWJnpP5euDTOJstCBfK3S5/arPqnLd2SGb3871ifdIQ7EdlfkWLJDcRpQHGOQQfXldIV0PRp19h/DUjhZEBNEhZEltIRZW58Ok5xEIRzTd6xnP2dJckmp+UkOt21m5dstWMCpH/nppRX5YqZw/yDO1r2UQQPTAJBGJ4hbL88Q9aEBlD6oFf0gcN072DGNzcy84ThRXKZuTguEI3jsliicWVucjFBHwyb/sxE//fQwA8MD18/ANKW6GCBvSiZeir68G8VprljF8ZC1v1PGYURrfjFHsMMFh1iMiAH99TxwHlPMU+fd7p/qpS+R4OleRfXW/N4Ajner76nSE02r7NTJ2k+FXywEwOYR5+3hPzLykNj8BMueqDA4ryForkWhHayxiuvtU+frjYNtQzFjE8xwV7Cn3CInW7dFGiGG6P0nkuqpGOg0PkUh0vUDXYCrxaFHH8b64/YEaXn+IOiKtUTwrJBZQWaci19Hj8eOuR3bBF4xg7XQXvnTlLLpvVAqrgOher8RhiqlvEDEnGX9IfZLM3310P5jePKVEx3NZ11fJ4WIiUbUaSjdVNZI5V5U4zJhRaocgxTHJIXOVxaDLSOgIRMe/E93D1OG+scROhRWZ7JkzbbYCEr9PWmtvxAVDEIDhQCgmorCpKl4sonw2SC2ixGGikb5Do0EMjgRSutNFnem1N3IA8Y4+SuT1WYOOp/WyjkFfXOyV2vfKazry/7QIq4D0navI+rciz5LQ3TgZ5PVVi8tSOgKli9mgw42LRbfDxzW41ssd/+WxWKVOEy6aWazpd1qMOiyuzQeQ3FWQxALmJ5hXifAg3WcyqbhKJlRX3kNkPXmo3a2pPpCMAW+A1qeVLv1Kk4IPLYsKg8vzzCnrmQS1saPIZoRV+vlz03StAhKnHySjX3ITBoDSPPFZLVVx6QfiU0XkIufL55YldRa2m/SwSOug/W2DAEQDCuUZn9p+Wb6m8AXDyR3VvFGHIZ4TTRXIfZxtDUqNbOIY5fR4/LTRSL5Xy2RfKOdkzzDek2JBPyI1k5J7W+0ZI3Xsg1JKBdkv3bBQTOxI9jx3DPnQ542NpU6EjufounJWmSPGLRSQmgKk61O7n+Vj0/P72+H2BbNq/k7lUkvcJeXOVRV5ZhTajAhFBPxhy2kAYiPaklpRrKz1PXvpQAcektzffnLL/KQN/GMJn4N1J2NywsRVjEkP2Vg7UqjKTZL7gT8YxpDkdqVlU5nJ4VkkItDCR3m+BVajnto6L6jOjznASQcySR3ucItq5jY3jDo+rkNjrFAuvLQsOOWFgU+uraPdjVpECWThMFtD4clpNtBoJLUFBxW9FGReEBW7tcQFSNwhSIKNm7yDqW1gFIIgqs7TidQgRIV+2p2rbCY9FtXkAwDW/+wtzP/2vzE4EkRFnhnrpDhAseND3JQ8uSMqMJJHlFRrjGQw6HiskGzdt2YRDZiqaJALyL15sH0Ib5/opdarQHJx1e5zA2j69r8x65uv0P++/vcDkqX12ERGKDvhuj1+BEIR6HgurTgOUnhWLpDJIvaLV8xEicOE413D+NLf9kMQBPR5xc8V2MZGvV/q0F4sBoCTkuVvY0lqV7MN0mb7jWPd9Bk91ulBOCLApOcTirOK7SY4zXoIArDggX+j6dv/xr6WQeRbDfjdnUuwbJo4nm9p7lP9/mz505bTWPDAv6m9tZLdZwfhC0bgsptodFs6EPvnk93DeOWgeDB+m8ZuumygoqgsnauoSEsm+pH/LHpYKG1Kn9rZgkffPQeOA/5nw0LqVkQgY8GmI100dndVg0tWrJtIcVVq98ZUm19AXJd86OFtuPqXm6kAefe5AZzoHobZwOOGRfExKcXEISyDA3FBEPAff96FH+zVxTzbgiDgm/84iP2tQyiwGvDQHUs0H3hVFcQWeyIRAYfbkzv2qEGKgaSbFcjsXiTxgekcdOfKuQoQD5x/tXExeA54elcrHn0vcdG3ZWAUgXAEZgOfUVewnMoCiyjICEViYszUCIQi2H46cyEoEC1qza3ISyl8K0rTuYqM4asaimIOYUgMlTyKNxX04FXjuoWsFzs0xAIKgoA7/u+9mHXHRT99E83doiuLFhGmXsfj17ctokIInkOcUwU5LN1xpj9GOP6d5w/jgh9uonEihL/vaUMwLKCpMi/t6ARCqdMMg07snFQTmhFBjstuykqkTt9T2frubJ83Zh4/2T2ctGBM6Pb4sP7nm/HUqdSlEkEQYsblQChCXZflxO0rZK+10m2zqVL9wIT8LfJnjRx47m0dxFM7xTX+huXi+67jOdoRr2VflrnbJHFcSd8FMZlzFSGXMRNkrm3uHsZIIP59UiO6B4wf15UChGTOVckgInYg/aiOH750BDO/IY4bl/73WwBEN7vqQit9bk/1ejHsD2FfyyC8gTAKbUY8+okVmFnqwOBIEIIgrqlvW1GDj6yahhtla4Z0nKtmlzvBceJznUxwIO5BsxMzkUOcWeUO1QNbjuPovXNCus+U89TMUgeKbEaMBsMp9w5jgXxfTdbrckLhCHVGz/TQak2jC1UF4nu4pLZAVYgW9z3TxWt6cmdLzLxE/lv74Bv0IAQYu1jAcETAPmmtn0uRJWGeLG5KORbNS3DgFnWria33NcoOXcn+JJ15k4yjI4Ewhv2Jx6beYT9W/nATfS/IXlJtDba4pgBmA48ej58+A7/adALLf7AJrx3uivv67af7EYoIqC60xDm4uWzxDakf/9MOeh3Lvv8azvWPoKrAgl9uWJRyPid7PWVtTS4kumFhBT4quV+R+kBPDpyrckW0GUjbPkHupqqcO+TIRQ35VkOc2CBRnCidq/LNGR/gkVrq28d7IAiA0yw2v5B1yeEMhBVEkDeeYyvBbNDR+cE9GoytJ1TEikXaB0dxyX+/hbsf2UW/P+pcZYbVqKfj1VvHe1K60yWKvE/GaCBMhb5am1DJHN06MEqdxpUCvVxCGtjlc0Ayos2pmV1TNMJ1KE7Y256lcxUQFRxvOtId09inBjkzKrAZsbyuCHppnPvQ0mrNQlog+vwnqzUOjoq/S02cCgBzyvPAc6JoJB0X8kSRZQAwvdROnxflPSR3ezydRYQaEN2TVGgQS9UW2ejrle3ZAcdxdM2pNbJXDq21pyHyIXUAl91EDSESO1fFNlfL5/VUtVyO46hoizR8VORb4uYC5bnD0EgQF/70jZg13s0PbYt71ggkBreqwIomqRnoBG0CGJvGeSpez8KBmjRdljpi6w3pxJmrQc7XLplVgm9fPxdXzI2maag54cr3+P5QGMc6xVrPh6RGiNPSfk0NtVjqZJB9a6IanTw+Xc7QSJD+rvI8M3zBCP65tx1bpTVHsvVLIlzUpVa9hkcccOVuchwXjYX95942+rek08jTO+zHF5/eBwD41Lp6XDu/Iu1rZzBSwcRVjEkPda4yJ190yWMB07EmT6WgVaN32I9gWADPRd0Jbl9ZC5tRh89c2qj55yghNuwA8NVnDwAArphXFid6GivsJn2MA5eWBedlc0pR4jDhsjml+PKVs2jhT4ua/5CGwyI58xJMoh5fkNqTZrppI9DFZp/yEISI6czqX98/EnUaKrBmVNAgRaJhfwi+YDjh19GOK+ng99al1TELRI4D7rkoNnrnekkJv/10Py2IdEoRJXqeS6vbh3TUn+rJfFOlZgOca0qdZkwvETv7viY9T0SoQjYuajy7u5VGFAFip9tf3zuHh98+Fd2MZiHiU0O5ySH/W5lvSWujXist4NsUUUfETWV2uRO/vWMxDDoOL+7vwO/ePoUBqSuqyDY2BS/SjXSsy5P0viZocQeJ/mw7VtQVIiIAT+1ohdcfwheeEhfPK+uLEh7UcxyHaxfELqwLrAb8auMiVBdaExYtc0EgFMGvXm/G0GgQv32zWfVrtlAnmKKMxhKykerzBhAIRzC3wjku2d5Kx6loATNT56qoA4jcUUO+Cd7fOohv/OMgAOCzl87AJbPiI3SJcPlkjxeBUARlTjMaim1ZdeHmCrKZTXXYlWjzSzjbP4L3TvfjSIcb9z0hxvGRiNhr51eo2p6TAkyPR91pJRnbT/djc3Mfun0c7ntyPwJSR96j753D07tawXPArzYuTsuRQjkOHu5wwyNFnKZyt5QTFbXEx6ymU3x1OaSDJI82Ic+wP4SRgDjGZRNvJmeN1P0PAN95/hB2ne1X/Toyp9a77FnFSQGiIINEkaVay+1tGcRIIIwimxEzNRzYqnHDwgrkWQyaYkZINILSkj4RiTrsMjnwSNdxk9xrSsGSGqd7vXEF9nP9I/jUI7twpteLjiEfOA4pmzeK7Cb89o4lKLQZsWF5TZzF+4xSO1x2E3zBCHafHQQgjtd/3nYGHUM+vHSgI+brXz/aDQC0qzsTdDxHhZNqrzcRYGQqSiGQdVmLTBD4hFTwJOI6byBMIwGS8dh753C2fwQ7eriUY2PvcABuXwgcJ7qvAeoxyGQMIlO6XHSndEWVH+qT3+8PhamQUW6BT772Xwc70THkQ4HVgCvmltHPJxLdq9GX8ZytfkiQCn8ojP2SCEEe66acN3LZCV3qNKPYYUJEAI50eDR9T/TwLn6vNE2KHiZkF22ZvuhzcCSAP249E/Mxo47H3evqAYi1hTKnGYIgRnZFx8Qi2E2i02dtkRUXzyzGAzfMBSCukX9wYxMuqC9CvcuW1thuM+np+j1ZR3GX24dAOJL2HlTOlfPKUWA14JYkc4f8II7EacrheY66jwFAVUG8O9lYc90CsTHtf988iW0nY+eB1hwIp3mew2fXz4DFoMOnL9FWp1pZX0Sb2tRoGxylAiJBEGgzZGbiqsSxgL947TiOdLhh0vNYXqc9Vksr8v2E0iFLLQKp2+1Dt8cPnhMPtuXInau0uq7KsZn0dA5JdsC/43R/nOPs2uku1fW22aDDMimObPOJXjy3rx3//epx9Hj8+OyTe+PmBbr/VHEliDpXieuvAW8Am6Q1AqE8z4yH71ySMOZczsr6IjjMelw2J3bfNr3UjoZiG5bXFeJHN86PitbinKsmkbhKo7A4xk01ieuEfExUGx/J+6N0vaERaVkIa8j6+B0pSYE0u9W57LAaxRhvpUN6KjJ1xcwVZA/sHg3FXEt9cfRvOtLhxt2P7sLpXi9eOdRJBaPkvSV7ZiLkJ+vlZE3CSmd6LZzqHYYgiHUprQJC0lSxv3UQ4YhY21W6lOSSTJ2rMq2fNhTbYTbw8EoRroSwvOE9i3t+RqkDS2oLEIoIeHpXa9Kvpc5VViPsJj1uXlKFynwLbltRm9bvJOuOrSd7E4oVqXNVgnnVYtTR8ZHMx1pI1ixs0PG4fkEFih0mLFCsl5Ruj9mQbsPSpy9phNOsx7UaYopTcfncMjhMeqyfHV8zTAWZ51sHRhEKRzR9D6kDyGtQxYqGVILSMGB5XSHmlDtxQX0RLqiPd6dUQvZjeyVxlVpTSLViT/7M7lYai03YdXYgobN9v5ecRRmxpjH2msbqbKcxRR1UC53EhVixlpY7siUSlCXCHwrjGWnM2LBMTBv671sXYmF1PmaVOTBNxZGd/L7jXR4cbBtCMCwgz2LAgqo8lOeJ+7XDCaI+tUYCEq5uKkeRzYhblqrvkxoSnN1uO9WHiCC+7p9YK+4nH3rzJM70jUDHc1hRn/56PLVzFYkFjD33J2fFwbD43qxpdFHB1dm+kZTz0D6pVlnnsuFLV8xM+7oZDC1o81NkMCYQ0v2byrmKKHeHRoMISAsdLQWeIpmCVhAETQfZJCKuxGGmm6nrF1TgesVhfSasahCzu0nHysbl1Sm+I3dwHIcCqxHdHj/K88yaihYlDjPe+9ql9PsbS8QCrBZV+YEEnX+JaKrMwwv7O+IW82QxWGgzprxPUiEuNvtiDmfUcrLp10sb7Jb+EZzt80ofy2zj6DTrYdSJ8R29w356GKWEFpWkRfktS6tx3YIKmqes5+MjARqk4sFIQCyITC910MV7VYElLbeAbKOkBEHAyZ6oO9FYsrrRhRPdw/R5+q8rZuGTf9mJ3mE/RgKhmAgfAjng/NXGRbh4Vgme3d2K+/95CA++cpS+rmpdCNkgt+eNRISkds3JUHP8AWLdzuZW5OH+6+bim/84iB+/cpTGRIyVc1Wdy4Yypxmdbh92nhlImYvdnKar2W0ravDe6X48tbMFx7s9ONblQbHDhAdvnp/0+37wwSZ8/erZIFsokyx2USxaHsO7J/sQCkfSEril4tXDXfT9eP1oNzqHfAkzzjN1gil1msFx0cg2LREguUB5/2VaACeH7KPBMDz+EJxmg+zQ10QFxye6h3H3I7sQCEWwfnYp/jPBoRERLh+VOoNWN7rAcVzcAfZ42/QKgkAPUWtTjCkNxXa8iq6EB+Rygdg7J3rxwPOH8ML+dgCJ339S2AmEIxgcCWo6DCE8IXNB3H1uEN954RA+uKgS33n+EADgS1fOSvmsK1GKq8hzsKKuMK1nsEIWi0lIJ1aH4JIEp8TdLxXkMMxu0mu2rNfCXevqcaB1CC8e6MDdj+7Gi/+5Js4ZqznNImUqGkvsONrpwcmeYVyapPhID+obXRkfSC+qKcC+b12u6WsL03CuGgmEsCdBvI18ztX67KfruJmOc5U87u0PH12GwZEAbnloG071ePHhP2wHIM6lWiI7FlTnY9c31ieMUVndWIR/7m3HluZeXNBQhKd3tdLC/ubmXlpE8wXD2Ck5Yqydri3qIhHVhVac7vWitX8UaIj9XDeN0szO7U05fgTDETy9Uyx4fviCWnQO+XCq14uT3d6khzDhiICnpPEtEOHQ6fajxpV4bCRjS3WBFWYDj+Ndw+h2++MEs+S65pQ7cajdHSO6U675ZpQ6YNTxcPtCaOkfRU2RFXvODWI0GIbLHitkJEVHsge4cXFVzB6gMY0Ii94M5+xE8RapiP5NsS6ddpMeRTYj+rwBuOymjKLGktFUmYfXj3bjYNsQltQWpPz6ZM5VHMdhlfQcAdF1UCbUFFqxBX1piT6f3d2GQCiC2eVOPH33BQAAg46j3fGAWITvdPtwoHVIJt4Xx8RpLhve+MJFceO32aDDY59cQf/GdGiqzENz9zAOtrlVBe+ArIkkzT2onDkVTuy5P/ncIR+v5XGaclY3FOH5feJ6aTwjAQkfWFiJt4714B972/Hpx3bj+f9cQ4V8zTkSTt+8pEqTgJlgNeqx6QsXxTQbET71l53YerKPjmHD/hCdQ7Jzroqd1/91qBO/el1sQvnRTU1ZHZ4ngjSeHG5306ggcs80yQ7cSJQMWWs3ltjj3ITI953oHoZPEtqn64xR6jTjVK8XXW4/dR1UQp6dq5vK8ODNCwBEhb1qrG504Z0TvXhqZwvOSnuOfKsBgyNBfOqRnfjn/1tN62fJ9p+kCYscjJHXorbIihfvWwsAMOt5zev1mWUO7Lv/ctWx57XPXwiA1BajjhWCIGTcuDMWRKMcte0T5G6qyZ5np1kU2nkDYdVY1hX1hdDxHM72jaClf4TWHpPNVVohP4s4Z5DDVx0vOkjsODOAA21DmJ6G6LYvi1jAXOA069E77IfHF4xx0dLxHOaUO7Hz7ADu/evumLn3UNsQVjW66HtL9l01hVbsPjeIN4/1AEj+jCvXpVpIp8mQQMZG4mJX6jRn5QSbikzFVZnOr+R92n1uEAfbhuiY0DvsRygiNrxn29S0cXkNdp0dwJM7WnDPhQ2qz6cvGKZNVIXS+POjm5LXGxMxvzIPDpMebl8IB9uG4oRMQOpYQEBc3x3vGsbB9iGsn6NNLBQVu6nPqT+9ZQEiEUH1NWiqzMOus+IY8AEVV3StpHufr6wvwv5vX5Hx75Pz+ctm4LOXTs9oTVVsN8Gk5+EPRdAx5NN07hONFo+Oy2Tu6PP6aa1ZnipCzhrMBh1e+sxa+n3hFH3KxdJ+bG8LcR2Kf49pDWRgFJGIgCekOMz7r52DW5dV47KfvYWOIR/ah0bjatQA0C/FAhbYjFjd4MJv3hDj1lx2Y0KXtWxJp1EoEWTNqpwfp5fYYdLzGPaHcLZ/hDYYauHVw13o9wZiYkHtJj2evWcVOE59/yRGJYtrsGd2iW5MTZV5tDbdMeTDgbYh1YaCA2maU3xsTR0+tqYu4ecTida2yOKmb1xUiR+/fJSepy2oysvozJW4z/claJCMxgLG/mz53+o06zGvMk9q3LOgdWCUztWJIPXghmJ7Ts90GAw57M5iTHrIIKtUsCohzlXkcEvHc5oOIcgmLxCOULVsKlJlmWcDsWEHxG5YLQr1XEIOrtLptOO4aHYssQI92z9CnSzUEARBZquennOV0mUkmbVtulSrbIKHRoO0uKhcYFbkW8BzomMa2dBmunHkOC5G7KeGIAhRO3TZQbjZoIPdpIfdpFe1CCWbUiD6+mX6ukULSenHf4jf58ewPwQdz6FWRc2fS+TFwfpiG9bPLqEFAWWHBiB24p7u9YLngHUzimE36XHnylrcsqQKEQF0Q53r4nt5vpneRz3D/ozfG7UOykhEoC4fZLy7Y0UN/ZsIBWO0GRIPc7U7QRFhplangivmliHfakDb4Che3N8BPc/hf29frOmAyyY9M6JrX3RJNK8yD06zHh5/SJOrkSAImp1/Hpc2sBwH0XFrZ0vM592+IPa3DgLIXFxl0PH0XrAYdDTDfawhv7PL7cNIIOri40qz4GU16uGQ5u9utx+RiCATCJpQnmdGkc0oWvgP+VDvsuFnH1qQtEgify3JPCs/wE43hicXDI0G4ZGK16m6OVN1bJFOJlJ8+Mu2s/AFI5hRasdiKTpWiUmvowW7ZGLZQCgSc38PjgTwotSxe2VVGBwHPPruOXzkDzsQDAu4pqkcd0muGekQFbyIY7PyEFgrpCNNHrtFBL3pFKupc1UKZ9Oh0SC63D4c7xLFe7lyrSJwHIcHb56PGaV29Hj8uOevu+PWV81pjpupSNTJpiRqDz4+a1UiANQS5b39dD+CYQGV+ZY48SIRr3v8IVq8TkbfsB8DI0FwnHjIrYXyNJyryIHb2kYX7CY9qgqs+O0dS2DU8XRsSueQNpkYgjxPW072ikXVHdG4ye2n++m9tfPMQIzTXzaoRfYRolGaWTpXSeNHa/8oOod8eG5vO3qH/XDZTbh0dikVHpKoxUS8fbwnVpiZoktWLrojHcNqIiPyt6+oE58VUmz3BaNuWmQMNOp5zJScjMkaZKvMhU3+/hbZTTGHr8qmnHS6fTM9AI3+3ek1XSRz6STvZ+MYREzIo8DkJHIPaKfuxeoHUXIhcXbOVfEuF/5QGF1uH/1P3ikvCAJdU962vJquZ+XCKiDaxPTe6T7sOTcoXrNsXk3m8pqJ6HxugtdXTraHrVqRz/mJ1hLyj0+EuIrjOPzwxvmYU+5EnzeAex7dRZ1+0xX15hJSS1P+RyIGyRhGDtiNel5zDLQc4s4id65q7h6mTsQfXTUNH1ykXRiWDo3F0UM1Mn6RuaJeikCSO/XQxsCK+PmYODX3ePzw+EMw6vm037diDU5IpAGQCK7tJn3S55Q860c7PRgNhrF2ugv//uw6lDnNONXjxRee2ofOIXENS5pQVjXEr+mUkS7yQz5yHekeXGkZe2qLrOA50PeINDxMCueqNIXFWpunOI6j841avdlhNlAXvq0no7WV9gTOHOmgHAPl93A68UlkPhUFcRPrXOWgMXahaAKAPbbmfa5/BDwH1EsH6+RvJOMCeTbJPO2X1srJ6tjktex0+zS5twOyOlgaYwdxxNkvi3EaS9TEVf5QOGEtTBl9nQlNsoY4AtlflTrNWR+aX9NUDodZj3P9I9iqcJAkkHqqnudonSpT9DoeK6VxdstJ9fooiQVMVqMlc5FWJ6lQOEJft2TvR6KxWcv6zhdMfC8Q1CLBx5NMxeq8JOoAtIsm26noNTouF9mM0PEcBCEqLCepIgYdh7IMGzVIoxIZ59Qc28vzRfFlIBTBywc7caJ7GBaDDjcvrYLdpKfifuKEqGTAS9zbDFhcW0DPYccykaRB4WCZCdQsQTE/6nU8ZpdnlmZA9mDKWFCeT7x/4jiOjmfPSVF3ZB5RG+cIgiDgQJs75uuzJVEDFhmTVje6UGAz4qqmqCN2JpGAQPQ8oDdBrcBDnKsU4ir533qB5EQOxMYrJqNDxTmOwcg1TFzFmPREYwGTq2NJIZFsgJzm5IUGAhGlANqjAdsTuBjlAnl294blNePupEHFVSpFIy2UOc2wGXUIRwTq5KRGS/8o3L4QjDo+ZRwSgVxTS/8oBmWuBcmsbdOlRqWwTYrqRTZjXNHQoOPpAo0cjtVkEU2Yyi7T4w/Rg6907Z6jLi3ioizT1y2Rja1WyOKtttBKM93HihX1hSB7p42SVavae0wgBz3zq/Jp4YDjOHz3A/MwX+puNel5FOe4oCe/j871j2Tx3sR3UA6OBmmBizzfyr/JadardnPnCiJm2ZqgeECIRASc6k3PgcVs0OFGWdH9/uvm0AiETNHxHI2RUlruK/H6Q1j3kzdw++/fS/lzz/WNYHNzLzgO+Pz6GQDEnHb5gd67J0Ub3jqXLeMIECC6gb9uQXnWjn5aKZG52pHiu0nPJ+2oTkSxrGCtvIc5jsNcaTyzGXV4+M4lKdcIq2XiD/LeGnQ8ZpWL8w8ZF8cTIiIqdpjiOuCVpOrYIhvLT62rxyfXRjuUNqZYR5Q6kotlD7e7sepHr+P2379HC8N/3yM6Zcwqc+DKKgH3XSxa0Qz7Q5hRaseDN8/PaO0iP1j2BcPYcSY+AksLpKjcoeJclU4Rj3TpJxPyvHq4C4u+82+s+MEm3P3obgDpz81asJn0ePjOpXCY9dh1dgC/ffNkzOej9vq5ESJEBRmJ13EeXxB7JNt5ZezeWFGUhnPV28cTCzfMBh0VQcidShNB7p/KfEvKZ5VQodG5KhwR6Ny4WnavL6zOx3c/MJf+O9N1uRJyqLevZRCvHOpES/8oHGY9CqwGjATCNEog6kqWWTytnGTd+0SUWJylc1V5nhl6nkMgHMHKH27CF54WD+ZvWVoFg46XRTYlj7QmhVJCqghseVxkVGAcvz4m4z3pRO0c8iESEdAqxTjbjDoUyLrTlVHom2VCJCVkPlw+rZA6CBPkQkktEYdA+gegZO5PNxYwWQRVDRVX5b5YP0+leP38vnY0fv0l/H1PfCQMcQNRcxABxGIvoSSL+1j5nLh9QVz44JtY8YNN9L9Lf/YWPRjbfW4AJ7qHYTbwuCGJgwApQL96uAuhiIDqQktOGpJS/b5kh33KKMyxQn7/JFpLVBdaqQB3rK8nERZpLZtvNWBf6xC+9c9DEAQhIxeTsUYZvUwO2DNxrQKioh25c9VnntiDYX8Iy+sK8fVrZmdzuUmRH6oBojiS7CfkEUhvSxFpB5McbDnNBuriB4hxYenurYk7TneSsfScNJdorRHMKXfSRoqqAgt+uWERSpxmPHSnKOD+9+EurPzhJlz+87fpdavFkZGPkSa/Q+3pRx9mgkmvo814zd3DNKp7ooQ6ctIRFsvdVNXmPCVkL5PIsW01EWbIIqXpIWIW4hrlfSUfe8g6dNvJPgSTRGLd9chOrP7R61RoSFIlJtK5CgDco8E4h075/fulK2fhJsnhj4qr3CQWUHxNlXNEssaHAquBnjOQtV4qMnH3JzVEUiPORlynBTLWu6Wxv3fYjxU/2IR7pH2wktYczPdqwj41R6BMsRh1+KC0jnr47ZOq8WBEXFUg1aKyhTzDLx/oVI2YG5AcgpK5txL3Ra2ikI4hH0IRAUYdn5FjsNztUe01ah0YwZLvvoqvPnsg4c8QBAHHuyZWXJUN6TrSkWdfLu7geY6eJxBxLnGzryqwZuw8p2xUUps/xHMH8Vr++9/HAADXzi+na59oHU19zOqTPQdmg47ua8fyvSTNg6RGmAnJnB217FuUnO3zYktzHzgOuHVZemlDZDzzKlxOSTOM2vPcPuRD7zCJpdaW/JMK0hTQ7fFTU5P2wVGc6hHNBlZIRh/yFIRkLlHJIIkAHn9I9T0k84nDHCtcrSqw0DlHLkyP1kmS1/Cj88TYzouM9zdMXMWY9JBYQKc5eXcAda6SNrfpFHiUnVip6EhgKZkL7CY97rygFnMrnPjQ0vGLBCRc1VSO8jwzrpapk9OB4zgqikjWJU0WDLPKHZoLT3lWA13Myg/CycFYNqImgtpimS7EEqidyfcQQVQ2XTmpnKvIxxM5VCVDuWjMtGuYLNr7hv2as8blpJuxng1OswF3rqxFU2UezZquTuKgsIW6cMQuGs0GHX57xxLMKnPglqVVWUUzJEIu+ooeOqR3T5Oibo+syEfuy3yrIeZZI3/T7HInLSaMFeTg/UDbUIwwUknb4Ch8wQiMOj6hVbUa/7F6GqoLLfjY6jrcubI26+sFogeY8qKlGnvODaKlfxRbT/bRTXEiiEPImkYXPrmuHnkW0XHrnRM99Gu2JDlATYebllSh3mXDp9Y1pP7iHEEOBTy+EL2HXXZTRgUoUvDpdvtpN3uexUAFmbcurUJFnhm/2LBIUzTBqgYXlk8rxE2Lq2JczdLpws016YzBZLyUb34JSifIL185C1c3lWF2uRM3Lk7e7V+SJOZ1cCSAux4VY1S3nuzD/f88GOOUsWFpJTgOuPfCety2ogazyhx4+M6lGUfikbmzdWAUu84OwBeMoNhhwvQ05wpSZCYH0B5fkDrDpOdcFRVXJRIlbD3Zi4ggOtHpeA4mPY9rcxARrUady4avXiUeMr4tGzPkB7C5KmzJO9kS/e3bT/cjHBFQW2QdtwNp0r1LLOkTEQhF8Nw+sRswUaxhOsXRTJzPyJpxaDSIkUBiZ9yDbUNw+0JwmPSYrzik+dCyGtx7UQMq8y24cl5m63IllfkW1LlsiAjAt54TYzw/uKgy6mglzUFE8JVph6KcRK/1s7tb8dKBzpz8Hr2Ox42LK6HjOfpfRZ6Zrgm0xON1u33YdLQbALB+lmjvn0qMFeNcRaNxYwV1I4GoW8KyaQXgONExuc8boHuY6kJrzFwpX7N7fEHsaxXHeDXHiw3LqlGZb8FnL5se97k6lw0cRxwbEq+/YuOWMnOu6kkjFjDmb1IRvVwzvxxlTjOubipP61q0QA6HTnQP0w77X7/eDEEAntqhJq5KXpgtcZixcXk1VtQVUsexTIhGdYj3xD/3tNG5S8dz4DjgbN8I7pacjR57T3Q+vXZ+RVKBObmXyDlYLp7pZBCxX4d0EKBGLhujklFbaMX62SW4fE5pTJymkk+tq0edy4bL5+RmnM2E6kIrfrlhEXgOeHJnCx7bfi7tqPTxoIK6MsY6V6Wq1SWCiHaGpQOXc30jONTuhp7n8OvbFo1p8w8QK45Qvs5XSfPug68cxcG2IbrWJmOIEvn3N1Wmf/g1TVoHE9GxGukKE3mew8dW12FakRUP37mEOoAurM7HT26Zj3yrgc6ZZgOPD1+gvo8mB8EeXwj+UDjteJpsIA0mJ3uGJ6dzlQZhcTI3VTWuW1CBijwzLp5Zovp5+ZqNiBw6cuBcJRcEAbH39NrpLtiMOhzt9OCHLx1V/f5wRMCmI93odPvw1M4W6lKRSe0yV5D50eMLypyrxPfu4pnFqHfZcPuKGty1rj4mDhSI7o+JeF4+Z5n0fNI9KsdFXW60NHIAmcYCKpIVxtm56t1TfRgcCeLN491xe0Z/KIwOhTtrJsyTvS/kfqcxXzkSk334gmkw6nm8c6IXv36jOe7zpLFHnh6RDVfMK4PVqMOBtiH8+JX454m8vsmcq+aUO8FxYnODFgc9Mn9UFVoyqmfL3R7PqDTSbzvZB28gjLeP96h8t8juc4NoGxyF2cBTJ6zziXTqB15/CG9JEaLzq/JjPqdsTJHvBzNF6Z6b6vzqVK/4Hm5cERXPROtoyZ2ryHPwsTV1qMy3jOl5QrHDBIdZj4gA1ftOC9SFWGUvR0VNrdrrwU/uEPdg66YXU0d0rSjXTeT3k3HuZM9wXO3oH3vEutaimgLNjX6pkDcFENdENbOBFXWFuGJuKVY1FGFxTUFmv8uih0Enjjlq0YAkRcqpOMfnOA4fXTUNs8ocMTUBtUYpNdqZcxVjHMjOy5LBGAeoc1UKsZTJEBsLmI64qshuwpm+Ec3OVbnYuCbjW9fNTf1FY8SdK2uzFic0Ftuxv3Uo6QHGAdlBcDrMq3TiXP8IDrYP0Q7UaG547pyrutx++IJhmA26qMV2gqJ6TaE1xj44m42jS9EVqERpZZ0OpBB4qH0IkYiQcfRckc0EHc8hLEV1aYlfkzPeXbgP3DAv5t9q0Y+AeLBEhDSrVIQtlfkWvPLZdWN0ldH76Fz/SBbCt+jBniAI4Dgu6WFZZb4FL8ty3MeKUqcZ00vsONE9jG0n+3BVgsMycogwzWVNy967utCKd750SU6ulUCKlrvODmA0EE64iSGuEoDoLHFbUY3q1wXDETy9Szy0u215DcwGsUPuT1vP4IntLbhIKp5uTiDwS5dcjOXp4jDpYTbw8AUjONwhFiVdGXYWy6MWSoZNcT/r2vkVuHa+dhGL2aDDU3dfEPfxTDqVckV07kq9lnCaDShxmNDt8eNk9zAWyTa25/pHqBPk9BIH9Doe/3v7Ek3XkCiCJBwR8J+P70FL/yhKHCb0Dvvx1M5WcOBwvEt0yrh+QTneef0geJ7DDz7YpPXPTkiZ0wyDTnSe+dtu8VlZ3ZC+aw4pMrt9IXj9Ieo8U+wwpbc2lIpGJDZa7XtJ0f2b18zBx9bUxX0+15DuwMPtboQjAnQ8h55hPzy+EHgOmJajqF0iyBgaDaLPG1CdP7TGm+SSQplzVSQiJCwMbzrShd5h8bovmaV+MFVTaMXOswOaiqOZiNecZvGAatgfQseQL+Gah1ivr6gvUp33vnTlLHzpylmaf68WVjcW4XSvlwqxNyyrwf7WQbywvwNbmnvxH6un0XV6Lt5fUnSUO4YebBuinc33XdJI7+1sePDmBXjw5gWqn9MSj/f0rlaEIwKW1hbgirmleO1oDy08J+KkbE3r9YudmEqxKnGtyrMYUGQ3ocRhQpfbj46h0YQiE7nd/bunRCHjtCKragH30tmlCUWEZoMO1QVWnOsfQXP3cEJnvWF/iMbcpC2uIk0X3gCC4YgmMcR7sr9JzaXzirlluGLu2AhdypxmuOxG9A4HcKTDjYgAHJPEDMo1ny8Ypm4FyQqzP7xxftbXpdyDPrZdLNx/67o5+I/VdWjpH8F1v96M/a1D+K9n9uPVw6IwURkFqaTEaUaxw0Sf97Ees+0mPepdNpzq9eJg2xBd38rJ5d49GTzP4fcfWZby625fUYvbV4zvmlmNdTOK8cUrZuLBV47h288dAi+tf3LlSpkLlM5V7iydq5xmPYw6HoFwBL3Dfrq2WFxTkJUTnFbmyURQynn6Y6vrsPVkH14/2o2P/WkHuj1+cElcAxqK7bSWkInbZKqGj3BEQOtA+jWC+y6djvsujRff3rCwEjcs1HYgSg7GgmEBp3q8dF7LlatmMhpK7HjtSDeOdXroeDw5nKuiTW2k7pIIeQOfln3NrUurcWuSRttFNQWwGHTo8wZwrMuD2eXO6CFiFuIaIgg62umBUcdTcRAgziX/fetC3P3oLvxhy2ksqM6Lu386hkYRksQvj28/h6W14n4103pALnBaJOcqmcicXE+R3YTXv3gR/VryDJ7u9aLfG6D3G6l3yp+7WeXOlPWqmkIrjnZ6VB3zlYQjAk73Zu5cRRjrWEAiViPiHzJe+YIR9Az7Y8bttoFRCAJgMeiyEiVNL4kV9dQX26MxXzn6extL7PjeDfPwpb/tx89fO46myjxcLNtDUueqJGKndCjPs+CntyzAvX/djf/vndNoqsrH9VKDViAUwbBfFBvkJ5lbbSY9GortaO4exqE2N0pmJX8tso1kJm6Pe1sGcaBtCPWKOZPUcrs8flqnUPKE1KR37fyKcXPXzyVqEd6JeGF/O4b9IUwrsmKFYp9boqjBRfeDmZ8xKs9lEiXt1BRasQXiWmVmqQOLpJhZIDp+dLrVnav6R6LOVQBw8cwSbPlKbuvwSjiOQ2OJHXvODeJktxezytIX5VEXYpW9nNwtOtVcDoh1/ad2irXKVHswNeTrJqdZT5/HEocZpU6xRnC43Y2lUhpHJCJQMdeH0nTJSkVDsR1dbj+apfqymtkAx3F4+M6lWf0ejuNQZDOh0+1Dr8cft/ePJlbFy1Q+d9kMfO6yGTEfa5LN1W5fMGGTEXOuYowHzLmKMekhClalPaASEguYSPGajKhzldZYwOw3rlOZBg1xMgcz7HZTKzplu0mQk69i35zKYlspTkpXuS4nVSxgX4Zd5QBQ77LBbODhDYRxqjdaFEv3ddPxHH1mtHTqAeLhxPEuD453eaiN/ER14SaKBTzeNYzeYT/MBj5jRX42kPvoeJeHHsylHQso3RfBsICBEWLVndsuq0yhHZZJogFP5th9JRvqXDaU55kRCEdoPJka8rFIGSHoD0Xv+6d2tqDH44fLbsL6OeIhKLHYfe1IF3adHcD20/042eMFxwEr67NzrpoIOI6jm/qouCqzzmJ5vFKfwsI/l8gPsFNFJmlhaDSYNCpBTrpzV6KoNuLkOKvckXbUammCCJL//vcxvHOiF2YDjz/9x3L81xWiuOPJnVGnjFwXxHQ8RzfaL+7vAJCZ9bTDbIBDmsc7hnwxsV3pYDbo6M9JNCf3SK9buiLjTKl32WAz6jAaDFORCPn7qgutOesKJ4IM+c8HxNeBjGnvnEgc6TVWFNjEey4cEeCR1vvBcIQW+AmPSYXbW6VIODXSKY5Sx800ReHUWj9B9ycgP3AbvzFf/p4tqM7HnAonnaP3tgzi1cNdEARxzMnFvU1c6fq8ARxoHcKB1iHc9cgu+EMRXDyzGJ9dPyPFT8geNet7QHTMPN7lwbFOD3WX3Li8BvUu4pSReC/j9YdoA4boXEVcLGLfb+VYTwp87YM+6nipnAdmlNlh0HEYHAniKWnczdSKX4uwjKwVbUZd2h2xhVYj9DwHQUg8ViqZCHEmgeM4zK2ICqufkEVBKtd8pChrMegyFo9oJc8Snbte3N+BIx1uGPU87QavLrTiVxtFZ6Pn97XDF4xgRqld055Fvt++YBzWl6k6itONNns/cc+FDbhqXhmCYQH+UCSnwulcQA6mOhTOVZk+HxzHxbjIb5FF0o4H85I4V/E8h59/aCGmFVnp3rzeZUvo0Cr//kzi8shzSlz1lHS6fQiGBeh5btwPisjBGAC8KTlx1BRak0ZW5QoSCbTr7AB1iy3MkcAhG4hYORCOYHAkuaPq5iQNfJlg1PNUlP7C/nYcaB2idfBsG4DJuFznssWJh66cV4b/J8XBf/lv+2ldjyBvWGgdGMU/97UDgGrU5HjhkImB+iXns+IE11NoM9K96JvHRCdTg46jsc2lUiMQoM2djrrcpHA3B8T9SCAcgUnPxwmmkuGym6CXiVjGKxaQjP3yeV65p5Kvf7OJ0pNHuJIYqGjMV+7+3luXVeP2FTUQBOC+J/bgjKzBgoirCnNYU726qRx3Xyg9T8/sxxGpfkZeW45Lfa41ryI+SmxwRN11OxfnJskaE092i69XOCKoOmm5fUE8v18cEzIRpUwGEp0lqPG41CSxYXlN3P2vjAHORdOBVucq+XnVxuXVMdcm36OqQZyrxnsOlsfcy/H4gqoRlXKC4Qhdw6mNFzNKxRqqxxdSbbpTpgZsOtKN3mGxrp+ouSkZ1YXRqLt5lXkxrz8RXsmf522nxAZ8h0mPa+fn1tGZrFt3nxvA8S4PtpzM7VpFjsshrfW98bWCaCygtjWlfK4+JEs1khOJCOjMYXwsg5EIJq5iTHrc1Go8hXOV4kAxvVhA4hakNRZwbJ2rzncSLXwIgiBQt5d0xVXk6/eeG4QgCIhEBLRKBdpcxNJwHBd34JbKqUz+e0scpqwON1NFVPZkIZTR63jaabnjTD89AMnkdStNEH2iRkv/CC78yRu4/Odv4/Kfv43d5wYBTLy4SrlwJsXcZdMKJ8S2nLwP26QFrcOsT7tQbdTzdMNP3hsqyEvgVjBeRO3rE8fsZXqAPRZwHKdJECYvLGw9GbXmFwQBG373Lr3vv/73gwCAm5dED/tnljmwuCYfoYiAm367Fbc+vA2AOM7lT4KicSaQTf1hqfCVaWdxdIzxZxxVpIXppeIB9tBokApqM6Xb7cMFP9yEj/1ph6avTzfaI9HcmqkTJBDfNQeIltj/++ZJAMCPb5qPORVO3H1hfUxc8FgVxMhrQRxUMj14J8WkjqHRrGJ15NGAanRJrxsRVYw1PB8VBRDrcipKzfG4ScRo5H470uHGBT/cRMe05u5hcBxwQcP4iYJMeh0VwJPOyU/+ZSdW/mATtp8WBREt/SNUuJGsuy+Ri6UaJzO8h8i6kTRlKPEFw9hxZgAAqBvreHBBQxFIHW+j9BpVF1pRU2hFKCLQOIxcxYc5zQbkSwdT1/16M6779Wa0DY5iWpEVv9iwaEyiltWugVjfk3v6+X3tWP2j13H5z9/GFb94Gy39o3CY9bi6qZyKsXqHAxhKcGhKXPFcdiPyrcaYeUuO8jCjQjY+0c8pYoJMeh1mSDFmrx7uApD5+6F8ltXoU0TlpAPPc1EXRI1NF4liuMcLsp/cdqoPL0hiXhIbJ1/zkfenPN+c1cGgFuR70J+9ehwAcPW8spj14NrpxVTsDIiuc1qui6wP5pQ7x+WQm7y+e6Q9nxx5TCYTV8XDcRx+cssCGjeVS+F0LiAHUx5/CB5fEO5RUdCRjfiQ3JPdHn9OI2m1QA7VAPX9Z57FgIfvXAqrJDpNVrsi32/U8XT8TofyPDMKbUaEIwKOdsZHA9JIpwKLqiPIWEP2dER0Mh6RgEC0cZO8JgVWY1oO12OFSa+jopuuJDWxbo+PiiZW5bAhgTwjv3njJK779WYAYv3InmE8O4GMy4nWvJ+/bCbWzSiGLxjBF57aF/M5peDgGcndY0Kdq6Qm7bN9IzQetyBJLZW42ZGY6GK7ic6zOp6jwgQt9z9Z26Wz16gvtqf1fOt4LqYRIpFbTa6Qi6sEQaBNXkD835lurSMZSlEPEX/kOu7pW9fNxeKafHh8IXz5b/vpxwfGQFwFAP91xUysne7CaDCMzz25F4AojgLEvUuqe0HZfP7nrWew6Luv0lqOnBap1pWNgCf6PsQLGuRNHGrinH/uFRsDppdoawyYjGitHxzpcGNvyyD0PIebFlfFfZ7U4EiDZy6Eb3LXOLtJn/AMlfwOk57HBxfFXpt8j6oGFRmO85iu1ij03qk+LHjg3/jFa8eTfm+X2wdBENdmaudoaCIrLAAAhLtJREFUBh2P2VKs+6Yj3TGf+8Pm01j4wL/xjX8coILFx6WmnFuSNPElg+M4Os/ERwSK/379aDRmlTQN3rCoAlZjbgPIyOv6+PYWXP7zt9HjGTuzASLQ7/XE1lUjEYE69RGnSS2Q11Ap8ib0eQMIhCPgOKCMiasYY8jE70gYjBR4NDpRkVhAQrqxgIA256pQOEIPIZlzlTryhY+airx1YBSDI0EYdByml6Z3ULWopgBWow5tg6PYcWYAXR4fAuGI1MGXm/eDWLGSBS7Nc0/w8+UL4GyLxJqdqzIUypDF20sHxIOEPIsho2Ko3FUmGaOBMD71yC50uf2wGkU76CKbEWsaXROWsU67TQZGYjp6tkxgF738uojjVKYdXsr3hgpTJti5akV9IXQ8h9O9XrQNqm/WMoleGkuWS1a8+1oGVT8/NBrEWakT0WzgMTASpI5Nu88NYs+5QfAc6H0/q8yBj66aFvMzPnfZDFTmW+jXlDnN+Pg4xIuNFWRTT97LTAVR0YNan8y5Kvf3sEmvw0xpM51tNOC7p/sxEghj++l+TS5YmTtXxR6QZ+oECag7VxHXjotmFtO4B47j8JObF+CimcW4cVHlmBXE5K9FvcumGhelBRpbM+iLie1KF1KAUZuTBUGgr5uyU3AsmVtJOnclcZUk8GjI8bipvN/+su0sgmGBRjsU2Yz48MranBeZU0Hcq/q9AQx4A3jreA9Gg2Hc+9fd6Bzy4amdLRAE8dCpNonbRyKhtZJAKELnrGmu9NZ4FSmcq3adHUAgFEGJwzSuouJ8qxGfXFuPC2cU4/qF0XhVsv4h81ou10MfuWAaXHYjvXeaKvPwuw8vHXM3IDn0npbGhN9vPg1AjLQtshlR7DDh85fNgMUoivjyjeI43pzA8am5RzzoJbEY0fWXL2YOUB4uRWO1fEkjuuVjOsdl7jikzbmKiJgzjPKV/e2p6Hb7cGICxJly5tH9UCdGg2FML7Hj7ovqAcS6kL4guW6M1yEQGZfImEMcTuXcfWE9PnJBLZZPK8TNS+MPbNS4eXEVmirz8P8ubszdxSaBiEXfPtETN38S52SnWT8urjfnI3aTHg/fuQQLq/Pj9g0Tjc2kp2KFziFf1s5VQHTc2XyiBwMjQdiMOiyQxdSMJQYdj3subMDFM4uxdJr6cz6zzIFfbliEWWUOfGiZevw7ACydVoBLZpXg7osa0naSBciBW+JowGTzxXhA9nS7zoqi8LkanHtygXJ9NJFCHSWJHIDl/G1XGwBgUU1+wmjeTLh+YQVmlTnousplN+LDF2Qfb3rtAvHn3rxEfX7R8Rx+dqsYwXy00xPj6kHG92XSsxQIZxY3nEvIOcLpXnENVGA1JD0QJ2uvtyWHthKFg+sdK2vRVJmnybEknUaObOpgcoFRIreaXEHGel8wgpM93hj3YPL+038P5M6lkhykk+aisXCuAsRmVRIxvvvcAELSPayMQ8sVOp7D/2xYBD3P4WinB+f6RjAovaYFGtZI5H491DaEbSf78J0XDkMQQJuO5ORiDpHXIeR7HX8oHHOfK8U5giDg8feiDsFj3bAwVlTLavZKRyM5xBX38rmlquP+xTNLwHOiiObRd8/mRIjotOip6USys7F1M4qxbFoBvnj5zLh1OHmeuj3+ODf+SETAwMjkca76x942RATglUOdSb+XmCWU5ZkTNnRdJ0Vy/uiVo9jfOghA3A9+78XDiAjAo++ew6PvnUPrwAjePiHODRuyiOj72Oo6zKt04lbFz7iqqQwGHYd3TvTiobdOoW/Yj38fIjHwidefmbJ+dilmlNpj1hGfWls/Jk0d9KxT4VzlDYSo8DmVqYocNZcvOWQMKrabMhLBMRhaya3kkcEYA8iCJVUsoFkfO/inU+Aptic+PFPS5fEjIoj2wBO5SZzM1BZZoec5jATC6HT74myNyUHwzDIHjXPUit2kx3XzK/DkzhY8vv0cXdBUFlhy1sGmPHCjee4JDnlzKa4qSuFcla1QZq60+doquSNler3FjtTOVYIg4KvPivbGLrsRz//nmkmRdVyRbwHPiQWBnmE/ShxmBMMRvHtKfE0mqote+V5k+t6UOM042umhsTSkM2Cixyun2YD5VXnYc24QW5p7cevS+M0IFQlMAucqIHr4dqjNjUhEiNuMkS6JqgILZpY6sOloN7Y092JeZR7taLlxcRV+esuChL9j7fTiMc+pH0+Ig09I2iFlet+pOVeNldtCU2UeDra5caBtCFc1ZW61TOY2fyiCgZFgUtFJKByhwl2lY0kilMIAINYJkmww04EeiMvGcnIArxTA2kx6/Ok/lqf9O9JBPu5lY0dNiszt2TpXJRE8e/whjEqxLfJOwbFG2bnbPGbOVdEiltcfwnN7xcOhP/7HsgmNLS20GtHSP4p+b4B2IgLie3TPX3fR52pDCnc1cq+1D/oQCkcSriHbBkchCGIsWKIYkURERTTqguLNMvee8S4yf+3q2XEfW91YROcunhNF0bnic5fNwOcuG/v4v2Q0FNuxpbkPzT3DONzuxr6WQRh0HN74r4tU56oSi4DBAIeTPcNYUht/6E7iL8jYQsYBXzACjz9EC4QtCiEtKXi3D47GfU7OvMo8YIcYKTG3wpnxgY7a3KGERkhnGuXrNAMYinPtUoM4Q82rmDiXzqaq2Plyw/IaGpd5qN2NAW8AOh1H40uyKaCng3w9UF9so7FPcjiOwwM3zEv75z7/n2uyvj6tzC53YkFVHva1DuFvu1pxlxR7AyChWxsjlvpiO/7x/1ZP9GWoUpFvgbvTg/YciavIuPOi1Py1or5oXA9CtMxN6+eU0lj3RJj0Ovzho8uyupamSifePt6Dg63xh0W5dIHJBDJPkj3eeDlX5VkMKHaY0OMZOyfjTCl2mHC005NQWByJCNHI4STCvEwodZrxymfX5fRnAsDC6vyUP9dlN6HUaUKX24+T3cNYJAmQyfi+fnYpgmEBe6UGtYmNBRTPEci1pboWUi/1SE4aygaaj6+p09wIJ48QEwQh6Vo/0xh7gOw3BmDUqzuz5BKHWQ+OAwQB1GmQoBSRRaOvs68B07jh9iEEQrKYrzEQk9W7bDAbePiCEbQMjKLOZYs69oyBKLzQZsTimgJsP9OPzc29VIyTp2GNPLcyDxwHtA/5cM9fdyEsjc9qe89kew6tyCPUzvaNYJoUo362b4T+biC+sehA2xAOS3HXNy6uzPj3TzR2qSGnzxtAS/8IdRSXMxoI49k9Yt1kQ4Jxf0F1Pr5y1Sz84KWjeOD5w3RezWZtzHEcSpwmtPSPJk3ZybMY8PTdq1Q/V2QzwqjjEQhH0OX2xUQIun1BKoIZ7/0b2cue6h2mdXlSR2nuHsZIIJTQ1SmVWQIgip3ePdWP14504e5HduGhO5fg04/tRkQQx+STPV585/lDeOtYMQRBrJkka+JLxaWzS1UFurPKnPj29XPx9b8fxE/+dRR7zg0gGBYwvypP9V7Llop8C/79uQtz/nPVILGASucqEmls1PFpibrmVSUXV7WzxCnGOMGke4xJD3WuShULmBPnqtSxgB3SxFzqTKx6fr9j0PGolRaFahEUB7Jw2QCAjSvEBeqLBzroz8plrAD5WQfbhrD9dH/KnN4Cq4Hab2db7ErtXCUJZbJ0riIbn0xfNxKtksy56o9bzuAfe9uh4zn8+rbFk0JYBYj3J7kWssHc3zoIbyCMfKuBRieON/L7CMhCXEVjvsT3hmRaT3QsIBAVrr18oAM7zvRjx5l+GrfT7w3QokV9BkWlsWB6qV0sHvjV89fljkGraIRgH4ZGg3hBOpAbq/i0yYpSZJJpLGCJzLmqd3hsBYJzE3S9BMORuHiDZByQHYS0J3BnI3QM+RCKCDDqeJRqFOYQscvZ/hEEpNg8uRPkjLL0xTXk/ep2+2n3YXMWTk/ZIh/3shG6kjH+XP8IdeHJRFxVRMX38etD0qXuMOthMY5fZA/tUG13IxwRonGqJbkdN2kRq8eL5/e1wxsIo95lwwqVw/7xhIgWB7wB6jCzfnYpnGY99pwbRJfbjyKbEZfPKUv2Y1DiMMGo5xGOCFREr0a0y9eStgCqnIr81H/+1gl2zFQij6tZUJ2fVvfg+UBUZOSlh52XzylLOLeUScvWRKIkpbDRYtTRQzy5i4X8HgKizRqH2t3wBkSBpppLn3yflM09Qsby9iEfvNJhYY/HH+M2kG38rnLtmQwSD52NgDZbKqT4LUB0KbhxUSVKnGbMKLVDEMS4QHl8iZq4biyQ7yM3aoz8m6yQDusnd7SoOrmxSMDzl3LqyjhKx5FULvPJiNY/xLXWZJkTJ4ImmYBASS5ig7JB6RiVSVNHpsgbCCZSqKOE7qMSzH3vnurD2b4R2E16XLsg8waeyYiak4j8Hr1N5rJRPKGxgOLYFAyTxq/k16KsUZc6MxfvVOZbwHGANxCmda5EZBpBDkT3G+V5Yx9hzPMcHFLNcvMJcR9Dzl7ixFU5FITOKHXAqBNFPTvP9EMgDe+23I8HPM+h3hV7f0fj0MZm/CFr4i0ne6k7kBbnKrtJjzpJ4DQ4EpTNz7F7T48vSP+G6izEbvIINXntTHnuo9xbk+YdZdz1+Ui1TDSpxksHOuDxhVBVYElaz/rk2npcO7+cCqvyrYas995kTso0ZYfnORqhpnwP+6T7x2HSZ+TOmQ3VBRYYdaLgsW1wFOf6RqhTXkQAjnTERil3uX3wSEYdqcwSAPHv/tmHFqDeZUP7kA8f+M0WDIwE0VSZhxfvW4trmsoRDAt4TYoNHAsXKcJty2vwoaXViAjAvw93jfnvGy/IWN2ncK4i71M6kYBAdK4+3eulsYJyiMCUJU4xxhomrmJMakLhiCx7NYW4SuGAlE6BJ5WgRQ45IBnrLPPznWQRFHvODQJAxsrrBVV5mFXmQCAUwe/ePgUAMYr6bCGL5fdO9+PWh7fRnN5EG2uO4+j3ZLtxJAe5/SOBOBtWIHqPFmW4iZxeYqdWsQBQleHGiizaexI4V3UO+fCDl44AEN0RJtLlQg2lO9mbku33qoaiCRNNyu8jAKjKVlwldVD2EDeCCY4FBKIHt28c68EtD23DLQ9tw5oHX8fxLg8dKyrzLTnPEs+URMUDwoE2MQJwXmUe3ThvP92Hp3e2wBeMYEapfdyiZCYLyu7OdJ1e6M+RxltvIIxz/aI7SKZCrVTIxSryA8AHXzmKtQ++gZelTvpkyB2kgPhihBJSjKkqsGgec0qdJthNeoQjAs72ia9JNk6QQNRpzB+K0K6hbIq72ULGQI5DVvMGKSy+e7IP4YgAm1GHsgyK48nWh8S5cTwjAQHRzcJi0GEkEMbBtiF6rzUWO3L6e8ihSdvgKP609QwA0Q1qog/7iXtP/0hUXLVhWTV+uXERyKXdtKQqZdGP5zlUF8TGQKuRjRCggsZTxoste4f92C89v5PlILnQZqQC89UNk+Oacgm5p490uPF3qaM4WbGyxBIrOJUjCAKOdIprAHkkp3INJghC3IE4GZ9O94rjeJnTrNqpObPMAb00P2TzfuRbjfQw8VSPFwfbhnDhT97AB36zhc55pHkj0wPQaDRS6ljAbScn1ikWENfcxJ3xqnlldFwhz+I7J3ppfMmGcYwvIfeIQced1539gBixYTPqcKrXi/dk8TT0sDWHe3fG+EK6wHPlXKUUO0zk2DDRkPrY8S4P/KFwzOcmXlwVXe9WFVhyHo+VDPmeZHLFAoqvye6zA6qR8I9JgoIbFlZMmvpGrojWe730Y3J3tWsXlNPGwYl1roodm1Jdi8tuimmqzWafZzboaBMVichTQxCErJqbyH4jmTNLLiFRYtsk5//LJVc/udhEvv7NhbjKoOMxq1zc6xLBQbKYr2xRnmcMeMW5bqzi0Mi8t7W5FwOSiCVf47xKhK75VgN1Gff4Q1S0AEQjGwttxrhnIl3U4mtJIwp5O+TOWYFQBM/tlZxgp4BIJOpIp/5MP7OrFYBYn0h2f3Ichwdvno+ZpeJ9nYt1MZmTsmlslzssyxmgAsPxn4P1Oh7TXJKBQ88wdUEmHJTdi11uHy7+6Zu46n/eQe+wn9ZhUo2PTrMBv/vwEtiMOkQE8Vl56M4lMBt0ePDm+ZhRKo4JhTYjLkvhZJoNokPxXCyQnJmsRh2NLTyfoc5Virqqe1SsQac7LpG5WhCAw+3uuM93UJMMdnbPGFuyFle53W784x//wJEjR3JxPQxGDHL1aapYQJM+G+eqxM4ESujEPMZZ5uc7ap1MgLjheve0uAlbN704o5/NcRxuk9yrSJdYLotMK+uLcOGMYtS7bPS/ey5sSGpP/4k1dVjVUIRLZ5Vk9btdNhMcJj0EATjRFX+YQ52rMlzQ6nU8ZsucmXLljqRk59l+hCIC5pQ78bHV0zL6HWMJFVf1jSIcEfA3aQN0xdzkThdjDTnoBbJxFYvtoOwjbgSTwLlq2bQCXNNUTp+rIpsRHl8Idz2yC3vODQCIPaScDMxTRHDJIR+bV5mHGaV2uOwm+IIR/OK1EwBEG+iJFiKMN0oRaqbFVLtJD5vkBkSKtmPlXEUOsPu9ASqgFgQBz+8TRVW/33w65c841z9CnTaBxDFg8q8H0is2chxHowLI3EoEXZk6QZoNOjip04oPgyMBuhaqnwDnqjnlTtyypAqfWz8jq67GCtnBHyCOK5k8iy4a1asirpKcabLpaM4EHc9hjiQK+KdUqHTZTbTQnSsKbEYqyj3a6YFBx+GmxVU5/R2ZQIraB1qHcKZvBDqew4r6Qlw0swTf/0ATVtYXao7rqFYIrdXIJoaH7BXUxJbP7m6FIIgNA2WTqKPu85fNwNrpLty+8vwvfishByVtg6Pw+EKoLrRgVUNiESd1rlJpFNl9bhBn+0ZgNvBYVJNPP650sejx+OEPRcBz0XFJ2TmbaL1nNujw+ctn4MbFlbggyXVqgYznO8704+5Hd2EkEMbpXi89GMg2flerc5XbF0SbtJdeUJ2f0e/KFXeta8DqxiJ8dn00EoyI2J7f1x6NL1k0fiKnlfWFuGpeGb561exJ5c6SCTaTHtcvFF874lgATHy0GSN7KlScq7ITV5li/j85wHo/UlVgQb7VgGBYwLHOWCcGMl5PlLhK3uQynq5VQGxU2mSKBbxibhl0PIdNR7vxxy1nYj7X7w3g34emjuuEEmW9d9gfos4mNUVWWI163H/dHFw6qwQXzsis7psLlG4YWhq/5sn21aQRKVOUTZ1qtA6Mwu0LwaDjMnJwv3xuKS6oL8JHV03L9DLTgoz3pPZx9XzRla3T7aOi0Jb+UQz7xb9pWhbxWXLI+/KqJK4ay0Nz5f1N7u0C29i4+i6ozofNqMPASJCK1rTWQj6yahpW1BXid3cuxcwyB63tyPefLQNE2J79a0bcXEmzBCAKXsjfAcS6Np/t88IbCMNu0k+4A3YuIM5fas90OBKNQ9VytmA16vG7Dy/B2ukufGKttvpFMjYur8GKusKsnBLJPlVZvyDOZwUT5Dwmj7knkYBEwCsX+r15rBsjgTBaB0bx6cd2U2Grlni4xhIHfnuH+H787s4l1FnaZtLjd3cuxerGInz96tkZNbWmg9mgw0N3itfx1atmxSScnK8QgwhlYpSbOOCmOPNXI1ECBRAVB1aws3vGGJP2nXvrrbdi3bp1+PSnP43R0VEsXboUZ86cgSAIeOKJJ3DTTTeNxXUy3qeQxbrFoEsqbAHinavSKfCQDfqwPwRfMJw055WpX7VBFj5KcdXTO1sgCGJnRjZ50jcsrMQPXjoCX1B0d8plkcls0OHPH1ue1vfctKQKNy3J/tCR5znMrXTi3VP9ONg+RA9QCT1ZHn4AwLxKJ13wZyvg6UrQoU4WN4tq8ieluITce+f6R/D28R60D/mQbzVMuLhK/n5kK3zrcvsgCEI06mUMLLPTRa/j8ZvbF9N/9w37cf2vt+B0rxc/+dcxALG2/5OBRPEMHl+Quk40VeaB4zisaSzCP/a2Y9gfEg/kznPXgUxQFiCz6S4ucZpxutdLY0zHqlPZbNBheqkDRzrcONA6hMp8C071etEpjW+7zg7geJcHM0oTOwMpN3Ttg8ndOzLtPm8osWNf6xA97CfuaZk6QQLi6+z2DaPb44db6nAszzNPyCae5zn85JYFWf8cZWdaphGHyqgaORPlXAWIY86uswN4bp8ormoYoyjVhhI7+iTHkcvnlE2Kw37SLbnpqFhYX1CVRzvdbltRQ8X3WtBy4JGNUwTpJB/2h+D2BanVvyAIeGJ7C4DJ18G7fk4p1o9hN+ZEUuIQGxg8UvPOhmU1STuKiXPVuf6RuP0hEYtc01QRE+FAOobJ+EDun4p8C93Luuwm6HmOxkAkE5nce1Fjen9kAhpL7Nh+uh8/fPkIjcYBxLmrpsgqa97I1G0y9u9OBOlsL3GYJjx2cs10F9ZMj3XIWVFfCB3P0QYvuavVeGDS6/DbO5aM2+8bazYur8bj28/h5YOd+LY3gAKbccLddxjZQ+pgHUM+eiiSK3HV6saiSVk7GC84jkNTZR7eOdGLA21DmF+VDwAYCYTonn6ihIny96mpanzFVY0l0T3YZHKuWlCdj69dPRvffeEwvv/SEcypcFLn3Wd3tyIQjqCpMi9GrDNViMaHi/M6Ec7Ko61uXVqNW5dWT8wFSijXGlrc3OdV5FEBT0mWTTTVhVZsP9OfMEIMyN6JujzPgsc/tTLja0wX+Xiv5zmsaiiC1Si6KrcNjKK+2E5rZzPLHDmLECN1OSLSH8u4J/l5hiAINKov0wSJVBh0PFbUF+H1o900bjFfY+PUktoCPHnXBfTfFfkWuDs9aB8cpfWrXArbicvrwfYhDI4EkG810trU2unF2HNuMMa1mXyuodg2Jeb3ZPWDUz3DGA2GYTXqNDcq1hbZ8MjHV+Tk2tZOL8baDE0MCPLoZznkGSicoEQMueCRCPtuX1GDh98+FdMITeLnAeDdU1HnXK3jxboZxVinIgie5rLhr58Yv3G2PM+Ss/tiMpAoEcDjzzxevKkyD68d6VJthGdn94zxIu0Vzttvv421a9cCAP7+979DEAQMDg7il7/8Jb73ve/l/AIZ729IJ1wq1yoAMBkyd65ymvUwSgXvVNGATP2qDbLwkdtEh8IRPLlTPEzKtnsrz2LANU1Ra8ypVKBtSuCU4wuGqeAw06gt+c8HshDwOKMHzkT4IIdce6ZuKmONPCedHJDduKgqqbByPCCiL44D7ZJIl+gBlx8jgTAVIBIb1slEkd2Eh+5YAqOep4d9DSVjIxLIlKhzVWxk3CHJerYy30I3mKtkMRbXNJVn5bxzviIXmvCc9o47NYodSqHW2Ak7mipFISsZu0jcGEHuuiAIYkeaLxiN6yDiKp10UK/VuSptcZU0t2471YfXDnfhQOugdP2Zj7VyMUA2kQSTCeUmOtOIQyImUnOu6pog5yogOi6RNetYRTjK74PJ0nVPnKvI3JZNpN5Yi6ssRh0tjHfIBJfvne7HqV4vbFPE5v18geM41EvPio7ncEuKpginQdyDRgTgbF/0HnH7gnhhvyhsvG1F7KFhCW0+EJ9NtftHx3Mx48Z47GHIsxwMC7AYdFhZL3aOk7kr6lyV2ZxNHLvI3w2InerKsZPMMRMRO6sFh9mAhTJHrcky7p2vNFXmYW6FE4FQBP+z6QReO9xF3ROm0t79/QZxZWwfijpXZXIoQpCPO5MlJnciIQ0TB9uiMSfEtSrPYshKyJYNMc5V41zjkdcHxkrckCkfWz0NNyysQDgi4NOP7cbLBzrw2uEuPCZFy07VeYSsK872jyAQikxa4azyLEGLm3tTVbTBNdsmmqhjfuK9xoFJXjtVIheszSgVBWHKPdVY/E3Kn6XFiSZTyJhzsmcY7tEQrXlrFTxlApn/SPOF1lhAJVQcI3MeyuXzWeo0Y3qJHYIguldFIgJOdovnPmulpoWeYT8CIXGvPlXqSwT5WYISct/PKXfSuuD5RrnCAZ5A3NsmSlxF9o7/PtyFfm8ANqMOd6ysBQCc6B6GLxhGJCLQOu7HVsc6gTGRzcRChPH93tgzxGgsYPqNvWSuVnOuYqlTjPEibXHV0NAQCgvFYtwrr7yCm266CVarFddccw1OnDiR8wtkvL8hDgpaijXZxAJyHEeLBUqLQiVM/aoNEu3VO+zHbinu681jPehy+1GUo4zijcujBxrEmnUqoJZhDkRtWA06Ls7eOpOfr+O5uGgSrRTZjOA40faWXBdBEARaDJysXXpkU3mk041NR7sBxN5PEwXZqFXkWTLu8JJH0pDDMotBB6txclrJNlXl4fsfmEf/Pdmcq2aUOmDU8RgaDdLCNhAV4cyVucvJDwQ2LJv4+2kiyLMY6L1baDNlVVSQHz6bDTysxrETPyodykjH4HLJuvzZ3W1UTPXgv47hA7/Zgm8/d4h+P7kfyIF1RwrnKmJPnW73ICkqbGnuwyf+shMDI0HoeQ4zyxK7aqVCfihOBNGT9eBbKxajDgWy4memzk6uJLHRJP5KKQIcD+ZVxrpajlWxcrp0H6SKTxtPlC4y2RzEkufvtKwRQEkmEZ5yyH6hXSa4fEISa16/sGJK2LyfT5B7+tJZJSndCDgOqHfFRrECwD/3tMEXjGB6iR2LawpivkcZj3dciviuLoi9f+RNOjVFY7+HmS4b0x+8eT6uXyA6ax5UiKuyda7qG/YjFI7gVM8wLv/527j99+/FfB2ZYybzActqaayrd9mmRHzJRMJxHHXn+9PWM/jEX3bCF4yNyWScfxBXxo5BH63XZSP4ka+jmLhKvdEuuhaZuOdG/j7NU7irjzVlzqij7kSsu5PBcRx+dON8zC53onc4gHv+uhuf+MtOnOr1wmrU4fqFU1NEX+o0wW7SIxwRcLbPO2kjX21GPeTlCE3OVbIaZrZNNGSN997pPowEQqpfc7A9eyfq8UQ+3pPxSik4IeNXLuvB00vtMOiib+ZYOlfVuWzgOTFN5ViXGNFqM+rGtBl3dWPsXjtT51QijpE7D+Va/Ejm6s3NvWgfGsVoMAyDjsPC6nwY9TwEIZpyQdf+53l9iUBew9aBUUQUjeaT/RxECzT6WdEsOjDB4iqydyTnTyvqi1BVYIHLbkQ4IuBIhxvHujzo8wZgMejwlatm4d6LGuj3M4OMiYXcNxEh6oIGiIkgQLzLpBbIc3ayZzhmfg1HBHRJtZgKdnbPGGPSruZWV1dj27ZtKCwsxCuvvIInnngCADAwMACzmQ1UjNxCXHq0ZK8q7XPT7Z5z2U3oGPKldK4iCwxl5AwjFrtJj2vnl+OF/R2499HdeP4/11Dnj5uWVOXEGnhJbQE+fXEjzAZ+SjnEkAXCkQ43QuEI9ApXtSKbKSs73TnlTty5shbl+eaUcZuJ0Ot4uOwm9Hj86HL7YopcrQNiF6tRxyeN0ZpISNY8GWOW1BZg+iS41lUNRbhhYQXWZFFYJu9FIBShFsyT0bVKzi1LqzE0GsTxLg+WTptcB1lGPY+ZZQ4caBui8TmAejdeZb4FX7x8Bob9YSrKeb/BcRxKHCa0DoxmHdsg7xR12bMb91IxT3aQEQpHsO2UaCf95Stn4b7H96BtcBSvHOyEUc/jt2+eBAD8fU8bvnrVbDgtelpIuXxOGbY098UIKdRoyfCQ5MIZxbhmfjnaBqI//+qmsqwKfdTtzu3Hmb6pU/wqz7NgYETcrGcqFiPdzWqx0d1SwTDbuIhMaCy2w2zgqXvTWInhblxciV1nB7BxefL4tPFEXtCzGHRYVJOf8c9aIMXtHO10Y2gkiDxFN/LQSJCuE5TiGK1U5JlxpMNNBZeDIwG8dLATgBhLxxhfPr6mDl5/CP91xUxNX99QbIuJYhUEAY9tj7rwKuelEllsdjgi4J972wAAqxXxc6LoTmw+yfTeSocLGopw4+JKLKjKx3ULKnCgVVzDHGwfgj8Uhlu6zzOdt4tsJvCcWDDt8wbw2Hvn4A9FcLTTgx6Pn65NJ7tzFQDcecE0NPcM444VtVMivmSiuXlxFd491RezbrliblnOYoIY40+ZVAcblTm4ZhsL+Ln1M6DXcRk7N08lyN7yWKcHgVAERj1P9w0T6QpU4jDjk2vrYDXqxz0mmuM4fPmqWdjXMjgpD60tRh3+vw8vwfdfPEKbcTkO+NDS6ikrouc4ToyrbxlEc/dwdG87DmuadOB5DnaTPrrO0SDOK3GYcd8ljfCHIlk7Z180owQuuwln+kbwpWf241cbF8WsLcTG1PPLuUo+3s+TIkLlzlWCIIyJc5VJr8PMMgetu4xlwztx4zrTN4IdZ8RosbGOiZ5Z6oDLbqRNXZnOq0Qc0z5GzlWAKK7609Yz2HqyD5fPLQMATCuywaDjUZ5nxtm+EXQM+VBdaJ1yzlXleRboeQ6BcARdHl/MfTgWosLxplwmoJfT7xXragUTdPZWr2iWXNUgxkjPq8zDm8d6cLBtCH7JLW15XSGMeh5fuHwmguEIrEb9lDozPB/R63gUWA0YGAmid9hP51YyN2fiXFXiMKPEYUK3x4/D7W56ltTtEeswep6bdIJ8xtQj7Tv3s5/9LG6//XbY7XbU1tbioosuAiDGBTY1NeX6+hjvc9w0FjD1otIsiwXkOMCR5iZWi3OVPxSmC13WbZmaH97YhCMdbpzs8eLjf95BF5q5cnThOA5f1Hg4cj5RV2SD3aTHsD+E5p5hzCoTOwPJvZmtUIbjOHxX5hSUKSUOUVzV44kVJJKN9Mwyx6QtnBfajLAZdfAGxKLwZLFrN+l1+J8Ni7L6GWaDDnkWA4ZGgzjSIXZZTTb7fDU+sbZ+oi8hIfMq83CgbQgH24dwzfxyALKNc1XsxvnTl0wf9+ubbJQ6zZK4Krv7jsTVAWMbCQgAsyXr7t7hAF470g2PLwSHWY+F1fm4dWk1fv7acfzvm81olQ4HDToO/lAEf9/Tiktnl2JoNAiDjsOFM4oBiAfrkYigKkjx+IK04yrd7l6zQYff3LY4y782lqjbnY8KCDJ1eppMVOSbcbjDDR3PoaYws7/HYRJjowPhCHqH/aiSHRgQZ5rSCdiw63U8Zpc7sefcIICxE8PlW434ze25vd+yRS6uWlZXGNdckQ5leWbUF9twqseLbaf6cOW8spjPk0J0scMES4bOecSKnDRnPLu7DYFQBHPKnZhfdf4WXs9XZpc78ds7lmj+ejIWkoOB/a1DONLhhlHP48bFlXFfT0TBPR4/3jrejY4hHwqsBlwxN9axV25RPx6H5QYdj5/dupD+e0aZ2P0/OBLEfklopee5jA9ydFLxssvtR+vACP62u5V+7mD7EC6eWQIAdI6ZzOKqYocJ/3u79nuEkRyLMffrFsbEYjboUGQz0ogYPc9l7S77mfVs/0SoLrTAaRbFIMe7PJhXmZe1i2au+Po1cybsd9+5shZ3ShFAk5GqAmta64upQEOxjYqrJmssICA2XpMD3GKNNYXPX56bOnOBzYjf3rEYG3/3Ll7Y34EFVfn45Lpo3at9yId+byBrJ+rxxKniXCUXV7UNjmJQctfOdbNtU2VeVFw1xk40DcV2nOkbwfbTorhKi+tZNnAch9WNLvxzrxg9nqmIhYpjpL1nJCKgtT8z1/RErKgvBM8Bp3u9ePt4D4CoeCoqrhKdnc6HtX866HgOlQUWnO0bwbm+Efp6RyICDrWfX0JJNYjDU583ENNc2O8Va1+FtomJJrYa9ajMt6BNcmRbIzUuNUniqgNtQ/RsirjA6XhuQtctjFhcdhMGRoIx5+7k3D8T5ypAfP83He3GgbYhKq5ql4SBpU7zeRvPyTh/SPvU+95778W7776LP/zhD9i8eTN4XvwR9fX1+P73v5/zC2S8v6HOVZpiAaMFHafZkHaHPTm47UniXNUpKf9Nej4mboahjsNswO8+vBR2kx77W4cQEYAVdYWonyIdC2MFz3OYI1mtk40jEL03J4tQhlhkd3tiOxoOnAfdGhzH0Y2lw6zHNU3lE3xFuYWIUg5LFuNjLUyZ6ijjGYb9IZzqFR1+5p0n9u3jCTlczt65Klowy/ZnpcJs0NHYpIfeEp2pLqgvgo7ncOuyKvCcGO80EghjdWMRvnrVbADA49tbYgSlVQUW8BwQDAsJnTBJvGSB1ZDxJjKXkPerpX+Edh1PheIXKXTVFlkzFvpyHEfvPaX4fiKdq4Do2GM16sY0FmGyUSgrNK9pzD6qkDhFbj3ZG/e5XBwUkfvwvdP9eGZXKx599ywAMYqYueJMfhqkWMC9LYN4ZlcrfvHacQDA1fPKVDtgaSyg24fH3hMdrm5aXBUnAiQW9SY9PyEdlSa9jh54vXlMjMcushuzuifJnP3ItrPUNRAADkriLX8oTJ+pqdK9zmC8X5EfaudZDGw+yyHEiQGI7j0ng3MVg6GE7BdP9kxycZVsv100xjUFNZZNK8Q3rxUP+H/48hFsbY7uOYiT6PRSx5hGzuUSIsTX8RxmSYIw4sbd0j9Kx60ZY/A3yaMTxzruidzfu8+KTrNj7VwFAKsbok63+RmeOdHGHklg0O3xIxCOQMdzOUtgcZoNWFCdDwB4eqe43yGvF3lf2gd96HT7MBIIQ89zqC2afGNDpsjFhIRTvV54A2GYDfx53aiYZzHAIj23nTL3s35pb1c4gedRpKHQZTdiprSPJWPCnnODVAjJIqYnJ2T+ldfJ0zn3V4Oslw/IorRZ4hRjPEn7pOE73/kOZs+ejQ9+8IOw26NFsUsuuQSvvfZaTi+OwXD7iHNVahcq+cFZJl23WpyriPq1It/CCkgaaSi242e3LqD/vm3F5HAImuwoxRyAzLlqkghlyAFSlztWQBC1wnWO+zWlw7QiccPzwUWVGTtSTFbIAdfhDiKuYha42UDu5QNtQxAEAc/uboUgAGVOM7OZVYHEhWQrOlHGAo41ZGO2t2UQQLQbqjzPQl03KvMt+NXGxbhpSRVMeh7Hujx4ZJsolmiqzINex9PnT27FLmeyFZ+JUPZguxsRQVxzae3qncxUSvGv07MUipHoE3kRYNgfos6HJRM0BjRJrkeNJfb31Zo0z2KAQSf+vasasi+ckeLb5uaxEVdVSffh9tP9+OLT+3Cq1wuzgccNi+JdjxiTD3JQcK5/BF98eh/eOCZ2ZydyPCXznjcQxutHuwAAG5bHO/aS6KvaIuuEPb9kr/HGUfFvynaeJWPhc/vaY/5Nip1n+0YQjgiwm/QxzpQMBuP8Qx6Dk00kIEMdssZ7dncbQuHIpNs7MBhAVCh9onsYLZK782S8R8l5gtWog9U4MTGNH76gFjcurkREAP7rmf0IRwQAkDndTO7aqRzi4CQXT5H3vaV/ZEwiAQnE9ddq1GUsPtIKub89fvHwv3AcYsXkMeKZirmouGloFIIg0PmjMt8CvS53yRKkQYm4wjWUiPV1uWszcf6tLbLCkMPfPdFUy+53AnmW55Q7c/o6jzccx9H3sH0oGuk9ILmVTpRzFQDMkPblqxpcdP9M1ksnuofhDYRRaDNidtn5M56+n3DRuqrMuSqNc381yDxzSGZMQYSl5SxxijEOpH3nPvDAA7j77rthtcYumEdGRvDAAw/g/vvvz9nFMRjuUUnBqsHZQcdzMOg4BMNCRgWeYpXDMyVM/ZoZl88tw4M3z8fRDg+unmIOQWOFXMxBIPfmZBHK0O58mXOVIAhUXDXZrXA/fUkjCu1GfObSqRdDQN6bM32iu9JkEeSdr8wsc9D4nOf3d+C7LxwGAHx8Td0EX9nk5M6VtRj2hbKO25SLs8ajy3RehRPP7Ir+Wy7c+OrVs5FnNeDuCxtoLNk188vx7O42bDvVJ36/NOaV55vR6fahY3AUC6WOPjktkyTag0DGC1LknSpinRsXVeJk9zDuyDJCxKXSYUVcq+wmPWxpxlDniusXVOBIhxuXzylL/cVTCJ7n8I1r5qDPG8DciuwLZyvri8BzwKkeLzqGRmMOjHMRw7N+diluXlJFbeo5TnzvJoNrHSM1tUVW3HdJI/a1Rtfj8yqdWF5XqPr1dpOexk5HBGDZtAI0lsRHoqyd4cLtK2pwyaySMbv2VMyrzAN2tFAhflG24ippzo4I4n3+5Stn4QtP76P7gpPd0djZqTDHMBjvZ+SOmZl2mzMS86Gl1Xh021lsP9OPH718FC0DTFzFmHwQAfqRDrFBR8dzYx7VlglkjJoI1yoCx3H4/gea8PrRbrQNjuLt4z24eFbJmAqRxop1M4qxcXkNrpLFqVcViGOTxx/C5hNiw8q8MYg/b6rMw90XNqDONfbNCQ2KBq3CcXCuqsy34GtXz0IoImS8VySNjr5gBIMjwTET565qcOFXrzfTfzcWi/udcplzFRFXTQVXdDlqzlXEhe58epYTUZFnEWsjg9GzHiKuyjSuMhd8fG0dhv0h3HtRI/1YRZ4ZhTYj+qXru6ChKO0kI8b44FI5dyfizEzHO1KDP9HtwWggDItRR0WB7yd3f8bEkfZpgCAIqguYffv2obBQvcjIYGSKR1KwOi3ablWTXodgOJSRuIoM8n3eZOIqSf06xvazU5Fbl8Z3bTMSQxbkh9vdCEcE6HgOfVRcNTmEMuQQRe5c1TY4ioGRIAw6DjPL4g+TJhPzKvPwgw82TfRljAnkvRFErcSEFpKmAiQ+51C7G597ci/CEQFXN5XhE2uZuEqN+mI7fnLLgtRfmIIS5/g6VzXJCoBlTnOMnXdjiR0/u3VhzNfftrwGz+5uo/8mMW0VeRbswWBC56rJdkBSonAQaZwicU0lTnNO7sMilQ6rbkkoM1GuVYAYZfmt6+ZO2O+fSD6yalrOflaexYCmqnzsaxnEluY+3Lykin6OCiELMl/320x6/DQH9yFj4vj85TPT+voSpxmnpejgRCJjk16H70/wGlRZ/M8+yjc6Hl44oxiXzy0FnhZdHPuG/fSARXlYxWAwzj/k3eDMuSr31Bfb8dNbFuCev+7G7zefBgDwnOigz2BMFmoKrbTBGQAq8s2T0p2GOGJMdB3VYtThxkVV+MOW03h8+zlcNLNY5vp//ggybCY9fnhj7BrWbNCh1GlCl9tPGxLm5aAJRgnHcfjKVbNy/nPVUNZExiMWEAA+ta4hq+83G3QoshnR5w2gfWg0J81CaiyuzYfZwMMXjAAA6qXaWYXMuepkD2msmFprf1VxlfQszz2PnuVEEEMJYjDhD4Wpg1vRBMYCludZ8KOb5sd8jOM4zK1w4h1J1LmGRQJOWlw0MUoWCzianXNVqdMEl92E3mE/Dne4saS2IOpcxcRVjHFA86q3oKAAhYWF4DgOM2bMQGFhIf0vLy8Pl112GW699daxvFbG+5CoPaC2go1JigbMJhaw15MsFlBSv07CbhzG1KLOZYfVqMNoMEw3JORgd7IIZaLOVdGFESkOzCh1wKSfWlF75xPKA/+JLiRNBcghZDgiYHqJHQ/evIA5L4wxDpMeFslqPltHDS3MKc8DaXJa3ehK+f4uqS2gXXh6PioopcWIwVHV7xurAlemWI16OGTuS+zgOxa1DqsuybmKxYJODdY0FgEAtiiiASebEJJxfkDWYE6zflI79s4sc0Av6+zNNg62VOY2uWFZDRxmA+pd4kHLwXY3mqfoAQuD8X5EfmDBxFVjw1VN5bjnoughe3meZVIKVxjvXww6HrVF0Wak6oLJuV4mjhgTKQogbJSiojcd7cb+1iH0Dgeg4znMLj//Y6zk+6Wp8DflWQ0xddTxcK7KFTSab9BHm4VyvZ816XVYXifuoSvyzNTNm5gRdAxNXecqMtaRONRIRMChdtEJeCo4VxEBPWkWHRwRz2Z1PJexCGYskb/mTFw1eUkWC5ipCy7HcTRWl5xH0tQp1pDAGAc078x+8Ytf4Gc/+xkEQcADDzyAn//85/S/hx56CJs3b8ZvfvObsbxWxvsQD7UH1OpcJd7SmQzKaodnSjqZcxVjnNDxHI27Odg2hPbBUdoJIT+8mEiIO1KPO+rOQq6ROLgwJgblPcLEVdlDXI0cJj0evnMJ7BMUBfZ+guM4KmYuG4dxz2IUHcoAYM30opRfz3EcdSWZVe6AWRKCkU1ch4pzVTgi4IgUwVQ7iQQbxTL3qqniXJUroh1W0SIAiXibLPMxIztWSxGgW5p7IUiWj6FwBG1SwbSmaPI8q4zJT6XkdPbBRZV0XpiMmA06TC+Nusxm27xB/u5ihwmXzhbjDokTw8G2IdosMtUOWBiM9yMVzLlqXPji5TOxdrq4Rqlz2VJ8NYMx/sj3jZO1GaFIEsWU5U18TWx6qQNLawsQjgj49vOHxI+V2Cf1elErcnHdVPmbGkui4+55Ja6iAqfRqBNzYe7PsdZKQpYZstSKCul393sDtO411RorSG2gx+PHluZenO0fwbA/BJOex/QpsM+pUDSL9tNIQMOkjNybX5UPQJyDJksDKyMeci7V7YnWyWksYBZ7iSbp/X96Vwt8wTAVBVaws3vGOKD5ZPAjH/kIAKCurg6rV6+GXs8OFRljD1WwanWukhbvWmME5RD3gT5vAMFwRLUrjAzQkzFHnjH1mFeZhx1nBrDz7AD+tPUMhkaDmFvhxLJpkyOCtdQZda6KRATwPIcDbeLmaV4VE1dNJMqYr2yjXhjAjYuqcLZvBFfOK0P9FCsOTGa+dd1c7DzTj6W1BePy+77/wXnYfKIP182v0PT1d6ysgXs0iAtnFtOPkWIEyXqX886JHnS5/cizGLB4nP4mLZQ4TDjVI8ZYMeeqWJI5V01kLCAjdyyuLYBJz6PbI0aXTS91oGPIh1BEgFHHo9TB1v0M7Xz64kaUOc2468LsYj3Gg6ZKJz34yFaIv6bRhc+tn4FVjUV0Hz2v0onn9rVjf+sgTnaLcwwTVzEY5z/MuWp80PEcfr1xMR5++ySunFc20ZfDYMTRUGIDRI3QpD3U/tCyarh9Qdy+onaiLwUAsGF5DXaeHcCec4MAzq9IwGTI3/+p4N4DiKKgd0/1Azi/xFXRepSPuqaPhfjxzgtqMTQaxLULok69ToseVqMOI4EwFU5MtfpSnsWADcuq8cSOFnz6sd10zze73An9FHCYVDaLRsVVk/MZuGxOKb5w2QysbEjdIMuYOGolUeLpHi8EQYA/FEEgJMaKZuOItmFZNR7ZdgYH29z42rMHaN2Wnd0zxoO0R3yv14tNmzbFffxf//oXXn755ZxcFINBcI8SBWt6zlWZFHgKrUYajZDIvYpYCzL1K2M8IO5Pj28/h/2tQyiwGvDwnUtg1E+OxbrLbgLHAaGIgIGRAARBwCHJuWqqbKbPV1gsYO6xGHX42tWzsbhm8ghi3g+sm1GMz18+c9w6pJbUFuIz66drLoqY9Dp87rIZMfcFLUYMxjtXPb79HADgxsWTy9GEODAZdTyqC9gaR06RinMVicNVClkZ5ydmg44K10k0IOnyrSq0TMoOTcbkpb7Yji9dOeu8EBzI1+vZxu/qeA6fWT89pgmEHBhuPtGL0WAYep6btM4WDAZDO6VOM0h6diaNjQzt5FkN+NKVs6gzA4MxmZALpifr/F7iNOPr18zBtEni/nZNU3nMQfJUqZ3K3/+mKdJsK7+/J6uwRA1Sjzrd46V1i7F4Ps0GHb54xUzMKotGQHIcFyPALnOap6Tr/7evn4v5VXkYGAnix68cBSA2lUwFqDhP4Vw1WQWGOp7Df146fdIYETDUqS2yQcdz8AbC6HT7qKEKxwF2Y+ZjREW+Bb/auBg8Bzy7pw2CABj1PHWtZDDGkrRP6L/yla8gHA7HfVwQBHzlK1/JyUUxGARPhs5VmRSzeZ6j7lVd7nhx1WggTHOGmfqVMR6QDakgADwH/GrjYlQVTJ6ChUEXXax0e/zoGPKhzxuAjucwS2YLzBh/SmQuGzqeOy8O+BiMqQIpRnR7fAiFI/Tj3W4fNh3pBgAaJzhZIILMOpdtSnTb5RI156puN4sFnGqslmINNjf3AcCYdvkyGJOFubIDvbFwOSXiKm9ArB9Nc9lU3aEZDMb5hUHH07Uj22cyGO9fGoujdT+2ZtaGxajDBxdV0n9PFUGGPEZ9bsXUE1edTwf1RNy044zouuUw68d1rpZHB09Vx1qzQYff3rEEhTYjBEH82FQRShJxntsXgtcfwsDI5BZXMc4PjHqeuled7PbCIznbOUz6rJsZ10x34ctXzqL/Ls8zg+NYgyRj7Em7snXixAnMmTMn7uOzZs1Cc3NzTi6KwQBEwR6xEHVoFFeRxWJJhvEdpEDU7Y53myDxPnaTXrPYi8HIhoZiOxxSh8eXrpyFNdNdE3xF8RRLz1qX24ffv3MaADCz1DGpHFnej1iMOtoNV2QzMtcNBmMccdlNMOg4RASgyxMV5Dy9qxWhiIAltQWYUTq5BKhEuDuDCWPjIOKq/pEAwhGxctblEdeJxSwWcMqwVlpjvXW8G7vPDaBlQBRXVU8iUTuDkWvmlDth1PPgOLGzPNc4zQZMkx22NRRPDtcIBoORPbWF4vOcae2NwWCc/9QX26DnOfBcNPKHkZoNy8RGK6OOx+zyqSGumlZkA8eJf9OcKfI3kZqN2cDDeR4JiYm4qU9yHKoptI6r0EDuXDVVxVUAUJlvwa83LgIpty+ozp/Q68kVdpOeCqme2dUajQVk4ipGljQUi+NBc7cH7lHRwETrmX8qPrWuHtc0iRGlTOzNGC/S9lzLy8vDqVOnMG3atJiPNzc3w2ZjxTJG7hgNhukhllar8a9cOQsX1BfhwhnFGf3OEqcZwBC1TZVD4n3ki0QGYyzR8Rx+c/titA6MYuPy6om+HFVKHCYc6QD+uOUM3jreAwD4zPrpE3xVDEB8bzy+UNYxLwwGIz14nkOp04zWgVF0DI6iMt+CSETAkztaAIiZ8JONDy6uhMcXxHULKib6UiYdBVYDOE50kez3BlDsMKGHOVdNOeZWOHHVvDK8fLAT9zy6ixZ+WGGGMZUxG3T4zW2LMTQaHLP14tzKPJzpE8WKU/mAhcF4v3H/dXOwubl3UjaAMRiM8cFm0uNXGxchEI4g/zyKTZto5lQ48auNi2A36WHNIg5pMlHsMOGnNy+A3ayHxTg1mm1LnWb87NYFsJn00J1HDavKc6vxbhYqz4s6V031xopVjS784aPL0Dnki4lHPN+596IGfO/FI/juC4epE3EhG+MZWdJYYserh7vQ3DOMeqnelivhKsdx+Mkt87GgOg8XzijJyc9kMFKR9gruhhtuwGc/+1n8/e9/R0NDAwBRWPWFL3wB119/fc4vkPH+xT0qulbpeQ4WjS44cyqcmFOR+WJGi3NVuczelMEYa9ZlKBQcL0qd4jNDhFX/7+IGXDG3bCIviSFR6jTjZI93TGJeGAxGciryLGgdGEX7kLie2HqyD+f6R+Aw63Ht/MknYHKaDfj0JUwYq4Zex6PQakSfN4A+rx82kw4ev7hGLWHOVVMGsRizACe6h9HcPUwjwquZuIoxxblsTumY/vymyjy8uL8DABNXMRhTiXmVefTAjcFgvH+5SnKKYKTHVGxqumlJ1URfQs65cfH59zeVOs20OQyIjWwcDyryo+KuhvfB2v+imVNPyPHxNXXY2zKIF/Z3YG/LIAAWC8jIHtLAeLLbC3c9ca7KncDYatTjU+sacvbzGIxUpB0L+OCDD8Jms2HWrFmoq6tDXV0dZs+ejaKiIvz0pz8di2tkvE9x+6KD7HjZlxIHgmTOVRXMuYrBoMhjANbNKMbnL5s5gVfDkEMO/V3MuYrBGHfKpYJSx6AozH58xzkAwAcWVk6ZTs73E0WSSLXXE0C3JLqxGHSwm6ZGpzFDxG7S4+E7l9BIZoA5VzEY2dIkE1+QgiqDwWAwGAwGg8HIPQYdH9MENt7NQnLnqka29j8v4TgOD948HzOlaEyAiasY2UMarZp7hqmpijNHsYAMxkSQtrgqLy8PW7duxYsvvoh7770XX/jCF7Bp0ya8/vrryM/PH4NLZLxfyXX2qhaoc5WauIo4V+Ux5yoGg1ArdcDUFFrxyw0Lzyur5KlOTZFov1xVwMYsBmO8KZOE2B1DPrxxrBsvHRBdOzZM0ohXRnIqJNfSx3ecQ5fkblrqNI2b+J8xfjQU2/GzDy0EABh1/Lh3+jIYU415FXkw6nmYDTwTVzEYDAaDwWAwGGOM/OxqvJuF6lxiLdplN6KYOX2ft1iNYuOZU3IWqmRnC4wsITGhPR4/2gZHAABOC2tYZZy/ZHT3chyHyy+/HOvWrYPJxA4WGGPDkCSuystR9qoWSqSIsy7VWEDxY+X5zLmKwSBct6AC/lAEl8wqQT7L355UfGz1NBTbjZMygozBmOpUSMWsXWcH8OzuVggCcPuKGsytYPEp5yP/eUkjNp/oxYv7O9AjOVfJnRsZU4vL5pTizx9bDg5g7mQMRpbkWQ34038sA89xsLHnicFgMBgMBoPBGFMq8s3Y2yL+//EWV1UXWvGrjYtQkW9mZ8bnOdNcNjxzzyrsbRnE0tqCib4cxnmOw2xAqdOELrefxk0y5yrG+Uz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       "text/plain": [
        "<Figure size 3000x500 with 1 Axes>"
       ]
@@ -762,6 +780,37 @@
   {
    "cell_type": "code",
    "execution_count": 16,
+   "id": "c192564b-d3c6-40e1-a614-f7a5ee787c4e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plotting lambda against access_count.\n",
+    "\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "plt.scatter(merged['lambda'], merged['access_count'], alpha=0.7, edgecolor='k')\n",
+    "plt.title('Lambda vs Access Count', fontsize=14)\n",
+    "plt.xlabel('Lambda', fontsize=12)\n",
+    "plt.ylabel('Access Count', fontsize=12)\n",
+    "plt.grid(alpha=0.3)\n",
+    "\n",
+    "plt.savefig(f\"{TEMP_BASE_DIR}/lambda_vs_access_count.pdf\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
    "id": "00a12eea-c805-4209-9143-48fa65619873",
    "metadata": {},
    "outputs": [
@@ -800,7 +849,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": null,
+   "id": "b07180c3-d739-44a9-a8fd-88f9756c6f2e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
    "id": "adbfeb40-76bd-4224-ac45-65c7b2b2cb7b",
    "metadata": {},
    "outputs": [],
@@ -815,7 +872,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 19,
    "id": "1f550686-3463-4e50-be83-ceafb27512b0",
    "metadata": {},
    "outputs": [],
@@ -835,7 +892,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 20,
    "id": "b47990b1-0231-43ac-8bc5-8340abe4a8b3",
    "metadata": {},
    "outputs": [],
@@ -848,7 +905,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 21,
    "id": "db83cad4-7cc6-4702-ae3a-d1af30a561d2",
    "metadata": {},
    "outputs": [],
diff --git a/experiments/No_Refresh_0_5s_ttl/details.csv b/experiments/No_Refresh_0_5s_ttl/details.csv
index 83de2af..b929c69 100644
--- a/experiments/No_Refresh_0_5s_ttl/details.csv
+++ b/experiments/No_Refresh_0_5s_ttl/details.csv
@@ -1,100 +1,100 @@
-,access_count,hits,misses,mu,lambda,hit_rate,avg_age
-1,664,224,440,0,1,10.38,0.25892857142857145
-2,212,22,190,0,3,32.39,0.36363636363636365
-3,673,218,455,0,1,34.6,0.24311926605504589
-4,711,246,465,0,1,19.13,0.25609756097560976
-5,345,66,279,0,2,31.74,0.24242424242424243
-6,649,206,443,0,1,10.22,0.24757281553398058
-7,137,14,123,0,5,32.45,0.21428571428571427
-8,681,221,460,0,1,34.4,0.2579185520361991
-9,689,237,452,0,1,34.18,0.23628691983122363
-10,667,228,439,0,1,21.95,0.2236842105263158
-11,328,72,256,0,2,34.97,0.2361111111111111
-12,692,242,450,0,1,32.21,0.30578512396694213
-13,683,220,463,0,1,33.62,0.22727272727272727
-14,696,234,462,0,1,20.35,0.2692307692307692
-15,344,70,274,0,2,18.4,0.2
-16,326,60,266,0,2,29.9,0.2
-17,689,206,483,0,1,32.85,0.2524271844660194
-18,691,227,464,0,1,11.87,0.24669603524229075
-19,219,26,193,0,3,34.84,0.2692307692307692
-20,732,255,477,0,1,35.05,0.25882352941176473
-21,739,259,480,0,1,34.55,0.21235521235521235
-22,683,236,447,0,1,35.22,0.288135593220339
-23,670,236,434,0,1,19.94,0.19915254237288135
-24,331,66,265,0,2,34.67,0.18181818181818182
-25,724,251,473,0,1,32.08,0.2589641434262948
-26,692,222,470,0,1,34.18,0.2072072072072072
-27,705,241,464,0,1,8.76,0.23651452282157676
-28,137,12,125,0,5,34.23,0.16666666666666666
-29,672,230,442,0,1,31.7,0.24782608695652175
-30,694,220,474,0,1,33.09,0.2818181818181818
-31,674,223,451,0,1,9.03,0.2600896860986547
-32,144,13,131,0,4,34.63,0.3076923076923077
-33,670,232,438,0,1,7.09,0.24568965517241378
-34,141,10,131,0,4,32.78,0.3
-35,659,216,443,0,1,32.27,0.2638888888888889
-36,691,223,468,0,1,36.91,0.29596412556053814
-37,737,272,465,0,1,14.16,0.22058823529411764
-38,219,31,188,0,3,5.0,0.3870967741935484
-39,100,5,95,0,8,32.77,0.2
-40,714,234,480,0,1,12.5,0.27350427350427353
-41,184,23,161,0,4,7.45,0.30434782608695654
-42,161,12,149,0,4,21.55,0.25
-43,362,78,284,0,2,32.61,0.32051282051282054
-44,696,227,469,0,1,29.98,0.24669603524229075
-45,627,188,439,0,1,32.56,0.3404255319148936
-46,648,211,437,0,1,1.89,0.27014218009478674
-47,53,1,52,0,10,31.51,0.0
-48,676,213,463,0,1,31.35,0.23943661971830985
-49,638,200,438,0,1,32.69,0.27
-50,673,220,453,0,1,12.5,0.22727272727272727
-51,128,16,112,0,5,3.53,0.25
-52,85,3,82,0,9,33.33,0.3333333333333333
-53,747,249,498,0,1,33.0,0.26506024096385544
-54,700,231,469,0,1,35.08,0.24675324675324675
-55,687,241,446,0,1,37.5,0.24481327800829875
-56,720,270,450,0,1,31.3,0.25925925925925924
-57,690,216,474,0,1,0.0,0.2638888888888889
-58,40,0,40,0,17,19.18,0.0
-59,318,61,257,0,2,31.31,0.14754098360655737
-60,674,211,463,0,1,13.04,0.1990521327014218
-61,23,3,20,0,26,35.22,0.0
-62,724,255,469,0,1,32.32,0.2549019607843137
-63,628,203,425,0,1,24.93,0.2315270935960591
-64,345,86,259,0,2,35.1,0.3372093023255814
-65,681,239,442,0,1,4.11,0.2803347280334728
-66,73,3,70,0,10,33.79,0.3333333333333333
-67,651,220,431,0,1,0.0,0.20909090909090908
-68,10,0,10,0,69,33.02,0.0
-69,636,210,426,0,1,32.77,0.32857142857142857
-70,656,215,441,0,1,22.58,0.26046511627906976
-71,372,84,288,0,2,33.48,0.2261904761904762
-72,678,227,451,0,1,33.7,0.2422907488986784
-73,638,215,423,0,1,33.28,0.2930232558139535
-74,685,228,457,0,1,10.45,0.19736842105263158
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-76,344,70,274,0,2,21.16,0.3
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diff --git a/experiments/No_Refresh_0_5s_ttl/hit_age.csv b/experiments/No_Refresh_0_5s_ttl/hit_age.csv
index 7ad3f49..a07638a 100644
--- a/experiments/No_Refresh_0_5s_ttl/hit_age.csv
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@@ -1,101 +1,101 @@
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diff --git a/experiments/No_Refresh_0_5s_ttl/lambda_distribution.pdf b/experiments/No_Refresh_0_5s_ttl/lambda_distribution.pdf
index 0635616..fc35ed3 100644
Binary files a/experiments/No_Refresh_0_5s_ttl/lambda_distribution.pdf and b/experiments/No_Refresh_0_5s_ttl/lambda_distribution.pdf differ
diff --git a/experiments/No_Refresh_0_5s_ttl/lambda_vs_access_count.pdf b/experiments/No_Refresh_0_5s_ttl/lambda_vs_access_count.pdf
new file mode 100644
index 0000000..f4a9cdb
Binary files /dev/null and b/experiments/No_Refresh_0_5s_ttl/lambda_vs_access_count.pdf differ
diff --git a/experiments/No_Refresh_0_5s_ttl/objects_in_cache_over_time.pdf b/experiments/No_Refresh_0_5s_ttl/objects_in_cache_over_time.pdf
index 8225cff..fa84a59 100644
Binary files a/experiments/No_Refresh_0_5s_ttl/objects_in_cache_over_time.pdf and b/experiments/No_Refresh_0_5s_ttl/objects_in_cache_over_time.pdf differ
diff --git a/experiments/No_Refresh_0_5s_ttl/overall_hit_age.csv b/experiments/No_Refresh_0_5s_ttl/overall_hit_age.csv
index a824936..516c754 100644
--- a/experiments/No_Refresh_0_5s_ttl/overall_hit_age.csv
+++ b/experiments/No_Refresh_0_5s_ttl/overall_hit_age.csv
@@ -1,9 +1,9 @@
 ,hit_rate,avg_age
 count,100.0,100.0
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-min,0.0,0.0
-25%,0.1843617845017571,0.21978900255754474
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+75%,0.5339140431552882,0.26880022962112515
+max,0.9713572617066794,0.4423076923076923
diff --git a/experiments/No_Refresh_1_0s_ttl/details.csv b/experiments/No_Refresh_1_0s_ttl/details.csv
index bde224e..11ea0ee 100644
--- a/experiments/No_Refresh_1_0s_ttl/details.csv
+++ b/experiments/No_Refresh_1_0s_ttl/details.csv
@@ -1,100 +1,100 @@
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diff --git a/experiments/No_Refresh_1_0s_ttl/hit_age.csv b/experiments/No_Refresh_1_0s_ttl/hit_age.csv
index 42e1795..115bcb1 100644
--- a/experiments/No_Refresh_1_0s_ttl/hit_age.csv
+++ b/experiments/No_Refresh_1_0s_ttl/hit_age.csv
@@ -1,101 +1,101 @@
 obj_id,hit_rate,avg_age
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diff --git a/experiments/No_Refresh_1_0s_ttl/lambda_distribution.pdf b/experiments/No_Refresh_1_0s_ttl/lambda_distribution.pdf
index dba8a00..0046a3a 100644
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diff --git a/experiments/No_Refresh_1_0s_ttl/lambda_vs_access_count.pdf b/experiments/No_Refresh_1_0s_ttl/lambda_vs_access_count.pdf
new file mode 100644
index 0000000..fe4a186
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diff --git a/experiments/No_Refresh_1_0s_ttl/objects_in_cache_over_time.pdf b/experiments/No_Refresh_1_0s_ttl/objects_in_cache_over_time.pdf
index 1a8b964..084694c 100644
Binary files a/experiments/No_Refresh_1_0s_ttl/objects_in_cache_over_time.pdf and b/experiments/No_Refresh_1_0s_ttl/objects_in_cache_over_time.pdf differ
diff --git a/experiments/No_Refresh_1_0s_ttl/overall_hit_age.csv b/experiments/No_Refresh_1_0s_ttl/overall_hit_age.csv
index 70b7787..39c4173 100644
--- a/experiments/No_Refresh_1_0s_ttl/overall_hit_age.csv
+++ b/experiments/No_Refresh_1_0s_ttl/overall_hit_age.csv
@@ -1,9 +1,9 @@
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diff --git a/experiments/No_Refresh_2_0s_ttl/details.csv b/experiments/No_Refresh_2_0s_ttl/details.csv
index 3320391..fee718f 100644
--- a/experiments/No_Refresh_2_0s_ttl/details.csv
+++ b/experiments/No_Refresh_2_0s_ttl/details.csv
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diff --git a/experiments/No_Refresh_2_0s_ttl/hit_age.csv b/experiments/No_Refresh_2_0s_ttl/hit_age.csv
index a91a067..8aaadb0 100644
--- a/experiments/No_Refresh_2_0s_ttl/hit_age.csv
+++ b/experiments/No_Refresh_2_0s_ttl/hit_age.csv
@@ -1,101 +1,101 @@
 obj_id,hit_rate,avg_age
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diff --git a/experiments/No_Refresh_2_0s_ttl/lambda_distribution.pdf b/experiments/No_Refresh_2_0s_ttl/lambda_distribution.pdf
index a87b9fd..42b8fb4 100644
Binary files a/experiments/No_Refresh_2_0s_ttl/lambda_distribution.pdf and b/experiments/No_Refresh_2_0s_ttl/lambda_distribution.pdf differ
diff --git a/experiments/No_Refresh_2_0s_ttl/lambda_vs_access_count.pdf b/experiments/No_Refresh_2_0s_ttl/lambda_vs_access_count.pdf
new file mode 100644
index 0000000..9b8635a
Binary files /dev/null and b/experiments/No_Refresh_2_0s_ttl/lambda_vs_access_count.pdf differ
diff --git a/experiments/No_Refresh_2_0s_ttl/objects_in_cache_over_time.pdf b/experiments/No_Refresh_2_0s_ttl/objects_in_cache_over_time.pdf
index cb15e69..b8f1277 100644
Binary files a/experiments/No_Refresh_2_0s_ttl/objects_in_cache_over_time.pdf and b/experiments/No_Refresh_2_0s_ttl/objects_in_cache_over_time.pdf differ
diff --git a/experiments/No_Refresh_2_0s_ttl/overall_hit_age.csv b/experiments/No_Refresh_2_0s_ttl/overall_hit_age.csv
index ab804af..a4ea360 100644
--- a/experiments/No_Refresh_2_0s_ttl/overall_hit_age.csv
+++ b/experiments/No_Refresh_2_0s_ttl/overall_hit_age.csv
@@ -1,9 +1,9 @@
 ,hit_rate,avg_age
 count,100.0,100.0
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+max,0.9926313287378179,1.2043010752688172
diff --git a/experiments/No_Refresh_3_0s_ttl/details.csv b/experiments/No_Refresh_3_0s_ttl/details.csv
index 687819c..88ec767 100644
--- a/experiments/No_Refresh_3_0s_ttl/details.csv
+++ b/experiments/No_Refresh_3_0s_ttl/details.csv
@@ -1,100 +1,100 @@
-,access_count,hits,misses,mu,lambda,hit_rate,avg_age
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diff --git a/experiments/No_Refresh_3_0s_ttl/hit_age.csv b/experiments/No_Refresh_3_0s_ttl/hit_age.csv
index 39f01c5..ce3841e 100644
--- a/experiments/No_Refresh_3_0s_ttl/hit_age.csv
+++ b/experiments/No_Refresh_3_0s_ttl/hit_age.csv
@@ -1,101 +1,101 @@
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diff --git a/experiments/No_Refresh_3_0s_ttl/lambda_distribution.pdf b/experiments/No_Refresh_3_0s_ttl/lambda_distribution.pdf
index e490ab6..7eec9e3 100644
Binary files a/experiments/No_Refresh_3_0s_ttl/lambda_distribution.pdf and b/experiments/No_Refresh_3_0s_ttl/lambda_distribution.pdf differ
diff --git a/experiments/No_Refresh_3_0s_ttl/lambda_vs_access_count.pdf b/experiments/No_Refresh_3_0s_ttl/lambda_vs_access_count.pdf
new file mode 100644
index 0000000..668f0f5
Binary files /dev/null and b/experiments/No_Refresh_3_0s_ttl/lambda_vs_access_count.pdf differ
diff --git a/experiments/No_Refresh_3_0s_ttl/objects_in_cache_over_time.pdf b/experiments/No_Refresh_3_0s_ttl/objects_in_cache_over_time.pdf
index 959e1ee..1eb4066 100644
Binary files a/experiments/No_Refresh_3_0s_ttl/objects_in_cache_over_time.pdf and b/experiments/No_Refresh_3_0s_ttl/objects_in_cache_over_time.pdf differ
diff --git a/experiments/No_Refresh_3_0s_ttl/overall_hit_age.csv b/experiments/No_Refresh_3_0s_ttl/overall_hit_age.csv
index 466e8e4..429a6ba 100644
--- a/experiments/No_Refresh_3_0s_ttl/overall_hit_age.csv
+++ b/experiments/No_Refresh_3_0s_ttl/overall_hit_age.csv
@@ -1,9 +1,9 @@
 ,hit_rate,avg_age
 count,100.0,100.0
-mean,0.6224679450442043,1.4900421658850633
-std,0.18900729549961315,0.2559552015594171
-min,0.0,0.0
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+max,0.9951271690040409,1.7263157894736842
diff --git a/experiments/No_Refresh_4_0s_ttl/details.csv b/experiments/No_Refresh_4_0s_ttl/details.csv
index afb44f1..7c25f89 100644
--- a/experiments/No_Refresh_4_0s_ttl/details.csv
+++ b/experiments/No_Refresh_4_0s_ttl/details.csv
@@ -1,100 +1,100 @@
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diff --git a/experiments/No_Refresh_4_0s_ttl/hit_age.csv b/experiments/No_Refresh_4_0s_ttl/hit_age.csv
index 389db7b..3b3c9e4 100644
--- a/experiments/No_Refresh_4_0s_ttl/hit_age.csv
+++ b/experiments/No_Refresh_4_0s_ttl/hit_age.csv
@@ -1,101 +1,101 @@
 obj_id,hit_rate,avg_age
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diff --git a/experiments/No_Refresh_4_0s_ttl/lambda_distribution.pdf b/experiments/No_Refresh_4_0s_ttl/lambda_distribution.pdf
index 4c94b1c..a492fc8 100644
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diff --git a/experiments/No_Refresh_4_0s_ttl/lambda_vs_access_count.pdf b/experiments/No_Refresh_4_0s_ttl/lambda_vs_access_count.pdf
new file mode 100644
index 0000000..f5adee3
Binary files /dev/null and b/experiments/No_Refresh_4_0s_ttl/lambda_vs_access_count.pdf differ
diff --git a/experiments/No_Refresh_4_0s_ttl/objects_in_cache_over_time.pdf b/experiments/No_Refresh_4_0s_ttl/objects_in_cache_over_time.pdf
index 8285b87..a832f6a 100644
Binary files a/experiments/No_Refresh_4_0s_ttl/objects_in_cache_over_time.pdf and b/experiments/No_Refresh_4_0s_ttl/objects_in_cache_over_time.pdf differ
diff --git a/experiments/No_Refresh_4_0s_ttl/overall_hit_age.csv b/experiments/No_Refresh_4_0s_ttl/overall_hit_age.csv
index 4938a7f..5ea9d24 100644
--- a/experiments/No_Refresh_4_0s_ttl/overall_hit_age.csv
+++ b/experiments/No_Refresh_4_0s_ttl/overall_hit_age.csv
@@ -1,9 +1,9 @@
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diff --git a/experiments/No_Refresh_5_0s_ttl/details.csv b/experiments/No_Refresh_5_0s_ttl/details.csv
index c92fbb4..0354ef4 100644
--- a/experiments/No_Refresh_5_0s_ttl/details.csv
+++ b/experiments/No_Refresh_5_0s_ttl/details.csv
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diff --git a/experiments/No_Refresh_5_0s_ttl/hit_age.csv b/experiments/No_Refresh_5_0s_ttl/hit_age.csv
index 782f75e..909eb45 100644
--- a/experiments/No_Refresh_5_0s_ttl/hit_age.csv
+++ b/experiments/No_Refresh_5_0s_ttl/hit_age.csv
@@ -1,101 +1,101 @@
 obj_id,hit_rate,avg_age
-1,0.8283132530120482,2.596363636363636
-2,0.5849056603773585,2.524193548387097
-3,0.8320950965824666,2.405357142857143
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-15,0.7063953488372093,2.522633744855967
-16,0.7177914110429447,2.7777777777777777
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-54,0.8385714285714285,2.5792163543441227
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-56,0.8375,2.527363184079602
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-58,0.175,3.0
-59,0.7012578616352201,2.506726457399103
-60,0.8293768545994066,2.4686940966010735
-61,0.21739130434782608,0.6
-62,0.8383977900552486,2.6227347611202636
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-67,0.8310291858678955,2.478743068391867
-68,0.0,0.0
-69,0.8254716981132075,2.459047619047619
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-71,0.7311827956989247,2.6544117647058822
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-75,0.5771144278606966,2.7327586206896552
-76,0.7267441860465116,2.576
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-80,0.8348484848484848,2.6515426497277677
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+1,0.8278688524590164,2.3564356435643563
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+15,0.9118773946360154,2.5126050420168067
+16,0.8977777777777778,2.485148514851485
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+25,0.8292682926829268,2.696078431372549
+26,0.8439716312056738,2.5546218487394956
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+30,0.824,2.3980582524271843
+31,0.808695652173913,2.5698924731182795
+32,0.9487179487179487,2.484234234234234
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+35,0.8484848484848485,2.4464285714285716
+36,0.8,2.4625
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+39,0.974012474012474,2.463180362860192
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+58,0.9881964117091596,2.381748686096512
+59,0.8878048780487805,2.434065934065934
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+63,0.811965811965812,2.536842105263158
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diff --git a/experiments/No_Refresh_5_0s_ttl/lambda_distribution.pdf b/experiments/No_Refresh_5_0s_ttl/lambda_distribution.pdf
index 0d9140e..c8e92fe 100644
Binary files a/experiments/No_Refresh_5_0s_ttl/lambda_distribution.pdf and b/experiments/No_Refresh_5_0s_ttl/lambda_distribution.pdf differ
diff --git a/experiments/No_Refresh_5_0s_ttl/lambda_vs_access_count.pdf b/experiments/No_Refresh_5_0s_ttl/lambda_vs_access_count.pdf
new file mode 100644
index 0000000..f8fbe44
Binary files /dev/null and b/experiments/No_Refresh_5_0s_ttl/lambda_vs_access_count.pdf differ
diff --git a/experiments/No_Refresh_5_0s_ttl/objects_in_cache_over_time.pdf b/experiments/No_Refresh_5_0s_ttl/objects_in_cache_over_time.pdf
index fa0462e..2a4fb05 100644
Binary files a/experiments/No_Refresh_5_0s_ttl/objects_in_cache_over_time.pdf and b/experiments/No_Refresh_5_0s_ttl/objects_in_cache_over_time.pdf differ
diff --git a/experiments/No_Refresh_5_0s_ttl/overall_hit_age.csv b/experiments/No_Refresh_5_0s_ttl/overall_hit_age.csv
index 668ce47..a594989 100644
--- a/experiments/No_Refresh_5_0s_ttl/overall_hit_age.csv
+++ b/experiments/No_Refresh_5_0s_ttl/overall_hit_age.csv
@@ -1,9 +1,9 @@
 ,hit_rate,avg_age
 count,100.0,100.0
-mean,0.7175225869007572,2.4791552890507336
-std,0.1841955218651161,0.35131346514105605
-min,0.0,0.0
-25%,0.6933831217326363,2.4321113930546847
-50%,0.8266900030111413,2.503781989168563
-75%,0.8338765555190953,2.573372952474587
-max,0.8466757123473542,3.4
+mean,0.877309770620863,2.4590330715633857
+std,0.056767395895691936,0.1482726930083797
+min,0.8,2.148647037787579
+25%,0.8330152671755726,2.3542028879412893
+50%,0.8487028558971006,2.4628401814300958
+75%,0.9138257575757576,2.5551416442865804
+max,0.9970287615878298,2.981981981981982
diff --git a/experiments/README.md b/experiments/README.md
index 6a56d20..e4286c4 100644
--- a/experiments/README.md
+++ b/experiments/README.md
@@ -6,6 +6,8 @@ Explanation for files in each experiment:
 - `hit_age.csv`: Shows hit rate/average age at time of request for each object.
 - `lambda_distribution.pdf`: Lambda Distribution across all objects/discrete
   values of the Zipf distribution
+- `lambda_vs_access_count.pdf`: Displays the access count against lambda,
+  expecting a higher lambda to result in a higher access count.
 - `objects_in_cache_over_time.pdf`: Amount of cache entries at given time.
 - `overall_hit_age.csv`: Cumulative description of `hit_age.csv`
 
diff --git a/experiments/hr_and_age_vs_ttl.png b/experiments/hr_and_age_vs_ttl.png
index b187dfa..d6944dd 100644
Binary files a/experiments/hr_and_age_vs_ttl.png and b/experiments/hr_and_age_vs_ttl.png differ
diff --git a/temp.csv b/temp.csv
new file mode 100644
index 0000000..94624b7
--- /dev/null
+++ b/temp.csv
@@ -0,0 +1,100 @@
+obj_id,lambda,access_count
+1,1,12
+2,3,49
+3,1,15
+4,1,20
+5,2,36
+6,1,16
+7,5,72
+8,1,17
+9,1,14
+10,1,16
+11,2,37
+12,1,17
+13,1,18
+14,1,16
+15,2,33
+16,2,39
+17,1,21
+18,1,17
+19,3,65
+20,1,19
+21,1,20
+22,1,18
+23,1,19
+24,2,34
+25,1,20
+26,1,24
+27,1,22
+28,5,78
+29,1,23
+30,1,18
+31,1,17
+32,4,64
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