{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Relation proie- prédateur ou hôte -pathogène selon Lotka et Volterra\n",
"\n",
"*Notebook d'Alix Helme-Guizon, à partir d'un Notebook d'Olivier Ricou (EPITA) issu de l'excellent MOOC [«Python pour les scientifiques»](https://courses.ionisx.com/courses/EPITA/002-001-002/2014-FALL/course/)*\n",
"\n",
"Public visé : BCPST1, Préparation à l'agrégation et au CAPES. **À simplifier pour le lycée.**\n",
"\n",
"*Vous pouvez écrire dans ce ficher (ou sur papier) et sauver ce ficher entier avec vos réponses en utilisant File/Download as/ (PDF ou python).*\n",
" \n",
"\n",
"\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ces équations s'appliquent à une \n",
"* une population de proies n'ayant qu'un seul prédateur et une cette population de prédateur n'ayant pour source de nourriture que cette proie.\n",
"* une population d'hôtes parasitée par un parasite spécifique.\n",
"\n",
"Prenons d'exemple célèbre est celui du **lièvre à raquettes d'Amérique et du Lynx du Canada.**\n",
"![An image](https://images.math.cnrs.fr/local/cache-vignettes/L492xH350/arton1144-84fc7.png?1605704237)\n",
"L’évolution des populations de lièvres et de lynx, leurs prédateurs, en fonction du temps t, a été modélisée par Alfred Lotka et Vito Volterra au début du xxe siècle. Ce modèle a été repris par l’écologiste canadien Crawford Holling qui en a proposé une version plus élaborée : elle contient notamment un nouveau terme qui rend compte de la mortalité des prédateurs. \n",
"\n",
"## 1. Établissons les équations qui contrôlent les effectifs de ces deux populations\n",
"\n",
"\n",
"On rappelle que l'équation logistique de l'effectif N d'une population est \n",
"$$\\frac{dN}{dt} = rN(t)*(1 - {N}/{K})$$\n",
"\n",
"### 1.1. Équation de l'effectif de la population de proie, noté H (pour Herbivore).\n",
"Sachant qu'il s'agit d'une proie, très chassée par ce prédateur (puisque c'est sa seule source de nourriture), comment pensez-vous qu'il faut modifier cette équation ?\n",
"\n",
">1. Il n'y a rien à modifier, car cette équation rend compte de la mortalité par prédation dans le terme *r*\n",
"2. La capacité biologique du milieu n'est jamais atteinte, donc on peut supprimer le terme N/K;\n",
"3. Il faut modifier *r*, car cela représente la différence entre natalité et mortalité en absence d'interaction avec une autre espèce, donc sans prédateur"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
">*Vos réponses ici*"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
">Exprimez l'accroissement d'effectif du à la natalité de la proie et à sa mort **de vieillesse ou de maladie.**\n",
"\n",
">*votre réponse : * $\\frac{dH}{dt} =$"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"La proie meurt (1) si elle rencontre le prédateur, **et** (2) si le prédateur est assez habile pour la tuer.\n",
"Appelons «P» l'effectif des prédateurs. \n",
">Comment pourriez-vous exprimer simplement et mathématiquement la probabilité de rencontre entre la proie et son prédateur ?\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
">*votre réponse :*"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Appelons $\\beta$ la probabilité que le prédateur tue la proie, **sachant** que la rencontre proie-prédateur a eu lieu.\n",
"> Exprimez la mortalité de la proie causée par la prédation\n",
"\n",
">*Votre réponse :*"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 1.2. Équation de l'effectif de la population de prédateurs, noté P.\n",
"Soit $\\gamma$ le taux de mortalité individuel des prédateurs, indépendemment de tout problème de nourriture.\n",
"> Exprimez les variations d'effectifs de prédateurs dus à là vieillesse et à la maladie\n",
"\n",
">*Votre réponse :*\n",
"\n",
"La nourriture des carnivores contrôle très fortement leur fertilité. on appelera $\\delta$ la probabilité que la consommation d'un lièvre donne naissance à un petit lynx. \n",
"> En réutilisant l'expression que vous aviez établi pour la probabilité que le lièvre soit tué par le lynx (et donc consommé par celui-ci), exprimez l'augmentation d'effectif obtenu par la reproduction des lynx :\n",
"\n",
">*Votre réponse :*\n",
"\n",
"> Regroupez les deux éléments pour estimer la variation des effectifs de la population de lynx.\n",
"\n",
"\n",
">*Votre réponse :*\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 1.3. Analyser et critiquer les équations de Lotka et Volterra\n",
"\n",
"Dans l'excellent MOOC [«Python pour les scientifiques»](https://courses.ionisx.com/courses/EPITA/002-001-002/2014-FALL/course/) d'Olivier Ricou (EPITA), j'ai trouvé ce Notebook, que j'ai modifié pour vous. Il présente le modèle proies-prédateurs ainsi :"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Les équations de Lotka-Volterra permette de simuler l'évolution de populations\n",
"de proies et de prédateurs. Elles sont :\n",
"$$\\frac{dH}{dt} = (\\alpha * H - \\beta \\; H*P)$$\n",
"\n",
"$$\\frac{dP}{dt} = - P(\\gamma - \\delta \\; H)$$\n",
"\n",
"Où $H$ représente le nombre de proies herbivores et $P$ celui des prédateurs. On note que :\n",
"\n",
" * $\\alpha$ représente la capacité de reprodution des proies\n",
" * $\\beta$ représente l'appétit des prédateurs\n",
" * $\\gamma$ représente le taux de morts de faim chez les prédateurs\n",
" * $\\delta$ représente le taux de reproduction des prédateurs bien nourris\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
">Comparez ces équations aux vôtres, et montrez que ces équations répondent bien aux contraintes données dans les parties 1.1 et 1.2.\n",
"\n",
">Critiquez cette la validité biologique de cette présentation des équations de Lotka et Volterra. Comparez en particulier vos coefficients et ceux utilisés ici, et le fonctionnement d'une équation par rapport au fonctionnement d'organismes biologiques.\n",
"\n",
">Pourquoi dit-on qu'il s'agit **d'équations différentielles couplées ?** Savez-vous résoudre mathématiquement ce type d'équations ?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## 2. Visualiser les solutions de deux équations différentielles couplées\n",
"\n",
"Cliquer sur la flèche située après Entrée pour exécuter le code Python de la cellule, directement dans le Notebook."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline \n",
"#installer matplotlib si cette bibliothèque n'est pas déjà installée.\n",
"#Vous pouvez le faire directement en ouvrant la console ou par cliquer sur CMD direct Prompt dans Anaconda\n",
"#taper «conda install matplotlib»\n",
"from matplotlib.pyplot import * #importer la bibliothèque permettant de tracer des graphiques mathématiques sous python"
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [],
"source": [
"a = 3 # on choisit le paramètre $\\alpha$ et on le stocke en variable globale\n",
"b = 2 # on choisit le paramètre $\\beta$ et on le stocke en variable globale\n",
"c = 3 # on choisit le paramètre $\\gamma$ et on le stocke en variable globale\n",
"d = 0.3 # on choisit le paramètre $\\delta$ et on le stocke en variable globale\n",
"#n'oubliez pas d'éxécuter, ou les paramètres n'auront pas ces valeurs !"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 2.1. Tracer les courbes qui montrent l'evolution du nombre de proies et de prédateurs dans le temps"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pour tracer les courbes des effectifs des proies et des prédateurs en fonction du temps, on ne va pas résoudre mathématiquement ce système de deux équations à deux inconnues, mais découper le temps en moments élémentaires. À chaque instant, on peut calculer $\\frac{dH}{dt}$ et $\\frac{dP}{dt}$ et les intégrer. \n",
"la fonction f renvoie deux valeurs qui sont $\\frac{dP}{dt}$ et $\\frac{dH}{dt}$. \n",
"puis on intègre cette fonction (avec `odeint`) en lui donnant le temps défini par t et H(0) et P(0), c'est à dire les populations de proies et de prédateurs initiales au temps 0."
]
},
{
"cell_type": "code",
"execution_count": 122,
"metadata": {},
"outputs": [
{
"data": {
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d8Qoq9PFWlCGyxDjnjzz2CdR18sTX8atJSlnXxb4nyNbHa67pBG0oabrjA9SAcKvx+63AGnl8latKYK4QQngaS0KIHJR+VXRzfPdqt3fRh74Mfm6ZBneyfYjxszuZeks1aoLeWSK+97YKY99T6DDCPOlsW3dMRhkzt0gpn3RvNFbgfKEr2d0PaPfPrq6lC3UdvP/+iIdMMaiHiedDv5UT7zn08NARqmzrBagwsT94bI9D5Sv4SyUQI4QY4GkYGImvg+j6gebPeeZ0sr0zfQEVqvManbOnF+fr6v62obxwnkiv9325JhXG35/bxef17SeV8gvgC8PDdRIqX+dvQohSKeUL3RwfVLiNt6enL7h1tKvrVuAlQzMqD6AzejPGdNajxX1ub2Pc+/74oiOV9G6cOgP1f71ISun2IiF86wPjy1jXQufjQDadXz/va4CUshFVgvmXQvW8OQ+Va/c2yhvhE1LKN4E3jTFlHir35TkhRIGUchV9u+/98VzqLYGSxV1Y5APgIyHEuV4ejmtQRuUFnt5twyDtiUCNg50ipWwWQjwPfFUIMRh1T+vpKAwBwblnvo5fJ+h9D5/15ZprOkGH3mm6xHD7Pw1cIoQ4BTWR+Z/Xbh+jVqcv8dp+k8fnXVFg/Jzqtf2iTvbtzYq9p0xnCCGGeG2/CbVC2udy4sYDei1wmRAi3r1dqMaPF3rt/g5qlXWolHJ9J69tvp7e+Ok9Efmaj8e51rMKjlCV4xagVqJAPYSOANd57ZeE8jSukieWKb3e6/1VKIN5uce2ArzuuRDiDJQedYdEXUfv7/0VVM6FJ73xCrpx6+gNXtsvR4X0dafDvvApkCKE8Nbv4/p5SCn3oAprTOtCX9YbYXQ90ZVufuEV0tMZfbkm76CMXmsXsp8wuZFSOqWUazCqqQEzuzn+B6iQy1FdXR+PfVsBehmStRo1eT9Oh4UQCzgx3OkdVFGDyi5kKOjF+brSBRcqeb1LfNSRT4EzhUfzTMMwvdr7sMbP3owrXV1XX8a6Ak4cB8biZziVlLJUSvkEKq9kXCdhwb4cq9UwFt3eBXc1sr7c94+BiUIIb92+CXXtP/VXXj/o7TOyx3FUSrkJVfgjF1huLJK2f4z6X20fbwydubEnAX3UcV/Ge0/+i3p2/BDlUXrB65nWl7lEVzL5Mn75g9/XXNM52qMUvUw2Vvu9OeAVbvM/1MPiOdRKmndc+1Ooyc2TQpWH3QacjKrqslRK+VE3MqxDTcb/bMhSjar+cnIn+25DTfy+gSpC4OpmQPkVyvPwqRDi16hKQdejqsvcI6Ws7eLvfOXnqOpRy4QQf0ENuD9ChcG1eziklCuEEI+hSqyehJoENaJWqk4Gtkkp/+nDeXejSjj/wTBgqlAT4MU+yp8DvC6E+DeQhrpuLagVPKSULiHEPagY8XeMWPQ41EMlnc6bW15mhFwuAyahQuS2oHKV3DwN/Ma4N5+hKg19i+NDwU5ASlknhPgc+KEQogI10ToNVVGtxmv37cbPO4QqqdoCHJIq986bZaiH1wNCiFRgBWoC9ytUhaunu5PLB55CVcp6SgjxU9QkYAkqZt2brwHvGWFET6AM1kxUnshMKeWVvTifE6WbD6IWxX6EqmT1y178bV+uyQuo/7elQoiHUAsKdtRE6nTgTSnl60KIr6O8GO+iKvTF07FS3+W4IaUsEEL8ArhfqLym91Fjx0CUx65RSun+ju6J+Y+EEO8Z12SrlPKEsEApZbUQ4s/Az4QQ/0GtLOehCl54h679DWU0fi6E+CtGwRNUQZWzgb8Yhl93VAL/FEIMQ4W5LUGFyvxTeuTAdUNvdeS3qMWnT4z/uSbUmO1dznol6jr+nxDiV6h7dj0dobiedHVdfRnrnkblMv0DFfo0HBWGeVy4Z3cIIdagjJethuwTUBPC9kUc47l0CHhSSnlLN8f6NUpHP0aFK6UD3+H4PK2/4f99/ytqgv2uob+FqGfSnah7vre337uXzBOdV4P+jN4/Iw+gnvvXC1WCugE4KqU86nlAKeUuYzH1I9S1OUtKeRj1v303yiv3GGoB5Qf0Poqitzruy3jvKfd6IcRWVKVHwYm9k/oyl3D/j3xHCPEkSo/2+Dh++UNfr7nGG+lj9QfUgyPX4/0c1OBxh6/H0q/+f9F91TsJfKWTv1lhfPZMF8fMBP6JCtOzoyawv8OrDC+dVDkCxqAmZLWosql/R00Yjqtgg8qFeRk1oLg4vqqcxKuKGio87S3UBLoVlTh+i9c+i+ikOhCdVLDp5npeiDIEWlEPvh9hVBLrZN9bUStQDajJyn6Mfg69vGf5HtsmoOKQ61CD90vG/+YJ16KT47m/9w2oksRlqAfL553JgirgsRr1wGxAPQwXeO1zn3HMmcZ1rzdkew7I8do3FngANTluQnmbpnnrB51XPxyKii2vMo7/Hsog60y3voPKiXB43k+8qt4Z2+JRITsFqNC0o6hqVOmd6PA7nVyj5XhU6urm2rvld1+fV1AJwSfoG8oweRGV79GGikf/GPhaD+fIN453D6o8dzFKPzdilJbt5L5ld3Kc3l6TE747ahHu+6j/u2bj++5ClXMebewzDxVSU4DSvwrjWBf2ciy7GFUyu9b4+wLUGHGml679G6XjLrqp8mbsL1ALAEXGNduCmih19h2TUAsBu419a1AT5wfpueT/ctTk7jTUglGLcX3vx6PCl8e9/EEXx+mVjqA8xauM85SgSvh/1ft6GLq4EmXclBnXbgYnVvTq9rrSi7HOuNY/pGMyvg5lSB93remmihtqUWcdajxoMY71IJDlsc9k4+9/38M9OR+V63jYuJ+lqEnnyV779eq+0/mYNAy18FRh3K/dqEmsZ1XRLu85vo3vXb0WeVyXbp+Rxn7XoP532zzPj1d5cI/xbRfKMB3poQu7Pe7PvagFkW7/F/3Q8U7H+14c390KZUcXn/dmLpHf2TlR86AjqIUE72dZb8avE66xly480sVnfbrm+nX8SxgXtdcI1YT0MSnl00KIQSiPwA5gLCoJ99c+HVCj0fQrQohFqDCPK6WU3tUK/T3mfShPxQApZX/G2mu88FhB/6GUsqskaI2JCNVQNVtKOdlsWSIdIcSdKMNwlPSo/KfRaDS9wZ8cpcmoUApQ+QfbpZQLULHVtwRILo1Go9FoNJq+cjpqEVcbSRqNxmf8yVGy0RHreBYdPWh203l1EI1Go9FoNJp+R/Yun0+j0Wg6xZ/QuzWosJ13UTkS86SUW4QQ84BXpJS5gRdTo9FoNBqNRqPRaPoPf0LvfoSqRLIceF5KucXYfhEdIXkajUaj0Wg0Go1GE7b45FEyShEPQ1Ues0qPxmJGAnGTlLIs0EJqNBqNRqPRaDQaTX/iq6FkQZUbnCSl3Bc0qTQajUaj0Wg0Go3GRHwq5iBVA8p9qAZWYWEoGV6wIag+HhqNRqPRaDQajSa6SUE1UO7WY+RPMYfzUc2rviGl3N7T/mYjhBiKaiCn0Wg0Go1Go9FoNAC5Usoj3e3gj6FUDSSivFFtqI7a7UgpM30UMqgIIVKB2uLiYlJTU02VxW638+GHH3L22Wdjs9lMlUUTHmid0fiK1hmNr2id0fiK1hmNr4SSztTV1ZGXlweQJqWs625ff/oofdcfocwmNTU1JAylxMREUlNTTVcSTXigdUbjK1pnNL6idUbjK1pnNL4Srjrjs6EkpXwyGIJoNBqNRqPRaDQaTajgTx8lhBCjhBC/FUI8L4TIMbadK4SYFFjxNBqNRqPRaDQajab/8dlQEkKcBmwD5gKXAcnGR1OBXwVONI1Go9FoNBqNRqMxB388Sn8AfialXIwq5uDmU2B+QKTSaDQajUaj0Wg0GhPxx1CaArzeyfZyVH8ljUaj0Wg0Go1Gowlr/DGUaoDBnWyfAXRbi1yj0Wg0Go1Go9FowgF/yoM/BzwghLgSkIBFCLEQ+DPwVCCF02iinb2l9Xx0RNC44QgXz8glKc6ff1mNJnBsKKxi9cEqcjMSWDJlMDarXzWBNJqAIKXks73lbDtcy4TBqZw5IQchhNliaaIYp0vy/vZjHCxvYPaITOaN1MFW4Yw/s66fAk+gvEcC2AlYUQbUbwMmmUYT5fz784P87r1dSGnl7aId/OfLAp7+ylyGpieYLZomCpFS8qu3d/LEyoL2bU+uLODxW+eQlhA+PTE0kUObw8Vdz2/i/R3H2redPXEgj14/UxvwGlOobbZz+xPrWF9Y3b7tlgX5/PLCidqAD1N8HkmklHYp5fXAWOAq4AZgvJTyRimlM9ACajTRyJubj3D/0l1ICWPTXOSkxHGwopE7n9mA3ekyWzxNFPKP5QfajaSzJuSQEh/DxqIa7n11K1JKc4XTRCW/eHM77+84RqzVwuKJA4mNsfDhzlL++P5us0XTRCEul+TOZzewvrCalLgYzpqQgxDwxMoCnl5daLZ4Gj/xe8lFSnlASvmKlPIlKeW+QAql0UQztU12fvHmDgDuOCWfb0508dIdatV+y+FaXlhXbLKEmmijsLKRhz5Sw/zvLp3Cf26ezbNfmUuMRfDe9mMs31tusoSaaOPT3WW8sK4Yi4DHbprFv286iYevnQHAf788xJ5j9SZLqIk2nllTyIr9lSTYrLz4tfn85+bZ/HTJBAD+9P4eKhpaTZZQ4w+9MpSEEA8KIZI8fu/yFVxxNZrI55FP91HbbGfcwBS+d+ZoAIamJ/D9s8eqzz/Zp71Kmn7l/nd30eZ0ccqYbK6dkwfA1Nx0blmQD8DfPtJrZZr+w+F08dt3dwJw28IRLBqXA8A5kwZx7qRBuCQ88ul+M0XURBm1zXYeXLYXgHvPG8/EIakA3LpwBJOHplLf6uCJFQUmSqjxl956lGYANo/fu3pND7B8Gk1UcaSmmSdXKhf9j5eMJ8Yjzv6a2cMYkBJHaV0r728/1tUhNJqAsrGomg93lmK1CH5xwfFx9l9fNIrYGAtbimvYerjGPCE1UcV7249xoLyRjEQbd5015rjPvm0sLi3dVkJZXYsZ4mmikOfXFlHTZGd0TjLXzx3Wvt1qEXzrdKWTz6wppNWhM1TCjV4ZSlLK06WUNR6/d/U6I6jSajQRzjOrC2lzupg3MpPTxg447rPYGAvXzlED8MsbDpshniYKedxYBb10xlDGDEw57rPs5DjOn6K6RTy/VoeEavqH/604BMBN8/NJjT++kMikIWnMHJaO0yV5daPuWKIJPm0OV7u36I5TRx63wAmweOIgBqfFU9Nk5+NdZSZIqOkLuiyMRhMitDqcvGjkH926cESnFXIumzEUgBX7K3S8sybolNa18N62EoD2MDtvLp+ZC8D720tw6JBQTZDZVFTNpqIaYq0Wrp83rNN9rjxJhYe+veVof4qmiVLe3XaUY3UtDEiJ4+LpQ0743GoRXGI8u9/arHUy3OhtjtJrvX0FW2CNJlJ5b9sxqhrbGJwWz5njczrdJz87iSlD03C6JJ/s1itTmuDy/NoiHC7JScMzmDw0rdN95o3MJDMpluomO2sOVfWzhJpow1097MJpQ8hJie90n3MmDcIiYGdJHUWVTf0pniYKecHwpt84bzhxMdZO9zlv8iAAvtxfQZtDLyiFE731KNX68NJoNH7g9iZdO2fYCa57TxaNUyF5X+yr6Be5NNGJlJLXjNClG+YN73K/GKuFMwzD/vN9uvqdJng0tzn5wMjPvG5uXpf7ZSbFMmdEJgCf7tELSprgcbi6iTWHqhACrpiV2+V+k4ekkZ0cS0Org/WFekEpnOhtjtKtvX35cnIhxI+FEOuEEPVCiDIhxBtCiHFe+zwhhJBer9W+nEejCXXK6lpYfagSULkg3XGqkbv05b5yXC7dv0YTHLYcrqWoqokEm5WzJw3sdt+TR2cDKiRUowkWy3aV0tjmJC8zgZnDMrrd95QxapxcdaCyP0TTRClvGqF080ZkMaSbZvAWi2h/dn+2Ry8ohRNm5yidBjwKzAMWAzHAh+5S5B68Dwz2eC3pTyE1mmDz7rYSpISZw9LJy0zsdt/peekkx8VQ3WRnx9G6fpJQE228uVl5kxZPHEhibEy3+y4YnQXAjqN1VDW2BV02TXTy5ialkxdPG9ppDqcn80cpnVx1sFIvKGmCgpSS1w2d7GmBE2gvY6+9nOFF908/AyHEJqBXI42UcmZvTy6lPNfrPLcCZcAs4HOPj1qllLoesiZieWerSpi/cNqJiaDe2KwW5o/KYtnOUj7fV86U3M5zRzQaf3G6JO8aOtlZcrI3OSnxjBuYwp7SelYdqOT8qYODLaImyqhttvOZ0dj4khk96+TUoWkkx8VQ22xnZ0ldlzl2Go2/7C9rYH9ZA7FWC+dOGdTj/qeOycYiYG9pA2V1LeSkdp5jpwkteutRegN4s5evvuAeybwDOBcZoXl7hRD/FkJ0numu0YQhx2pb2FBYjRCwZErvJpinjFGhTjqsRBMMNhfXUFbfSkp8THsIU08sNMLvvtThd5og8NnechwuyeicZEbnpPS4f4zV0p6npMdJTTD4cGcpAAtHZ51Qpr4z0hNjGWu0WNhYVB1U2TSBo1ceJSnlr4ItiFB+9AeBL6WU2z0+eg94GSgERgC/AT4RQsySUp5QH1kIEQfEeWxKAbDb7djt9mCJ3yvc5zdbDk1osWyHWrmflptGZoL1OP3oSmemDVWD7ebiGlpb27BYug9D0UQPgRhnPjJ08tQx2QjpxG7vuUninOFp/G8FrC+o1GNcmBEOzyb3OHn62Oxeyzk3P51Pdpfx5f5ybpnfdfEHje+Eg84Em/e3K508c/yAXl+H6Xlp7D5Wz7pDlZw5LjuY4oUcoaQzvsggpAyN2F0hxKPA+cDJUsouu2kKIQajjKZrpJQnlCMXQtwH/NJ7+3PPPUdiYve5HxqNGfx7t4Xt1RaW5Dk5J7d3/49OCfeutdLmEvx4moNBWrU1AeSBLVaONgluHO3kpAG908m6Nvj5hhgEkj/McRLfeZVcjcZnnBJ+ts5Kk1Nw1yQHo1J793eF9fDg9hiSYiT3n+Skh7QmjabXVLfCfRvVePfrWU5SY3v3d2vLBM8esDIiRfLdyT0vQGmCQ1NTE9dddx1AmpSy22Tv3uYoVQFjpZQVQohquslXklJm+iKscfyHgYuAU7szkozjlwghCoExXezye5Rnyk0KcPjss88mNbWXo2uQsNvtLFu2jMWLF2Oz9eym1UQ+rXYn967/FHBxxwULmTTkeB3tTmeeK1nL+sIa0kZOY8nMnhNJNdFBX8eZozXNHF31BRYB377yTDISezkDAP6x/3NKalsYOnkec0f4/CjQmESoP5vWHKqiafV6MhJt3HnVYqy99KC32p38fecnNDpg+sLTGdpNVTKNb4S6zgSbZ9cWw8ZdzBiWwTWXzOn1302oaOTZh1ZwpNnKWWcvJjbG7Jpq/Uco6UxdXe8LYfXKUAK+B9Qbv3/XR3m6xAi3exi4FFgkpTzUi7/JAvKAks4+N8LxWj32B8Bms5l+Y9yEkiwac1l5qIZmu4uBqXFMG5bZZSWnznRmxrAM1hfWsO1oPdfM1fqkOR5/x5nPD6hytzOHZZCT5l2AtHum56VTUnuMnccaOHls9yXFNaFHqD6bPt+v0pZPH5dDfFzvDXebzcb4wSlsP1LHzmON5A8wd7E0EglVnQk2Xxo6eeaEgT59/zGD0khPtFHTZGdfRTPT89KDJGHoEgo648v5e5uj9GRnvweAR4HrgIuBeiGEu2xIrZSyWQiRDNwHvIoyjPKB3wEVwOsBlEOjMYVPd6syoWeMz+mx3K030/MygENsLq4JvGCaqOWTXSpB+YwJvtfMmZqbznvbj7GlWPce1wSOjwydPHOC78b3lKHpbD9Sx9bDtb0ulqPRdEebw8WqA6pozam9LHbjRgjBjLx0Pt1Tzqai6qg0lMINv31+QogcIcRkIcRUz5ePh/kGqtLdcpQh5H5dbXzuBKagquntBZ40fs6XUtZ7H0yjCSeklHxiGEqnj/N9Ujp9WDoAu4/V09ymY501fae5zclKo0LYmeN9n5ROy1OFS7XxrgkUhZWNHCxvJMYiOHWs78nv04z2CVsP1wRYMk20sqmomsY2J1lJsSeEy/eGqbnpALoPYpjQ29C7doQQs1AGywTAewlcAr1O4ZVSdruELqVsBs7xVUaNJhw4WNFIUVUTsVZLe2llXxiSFk9WUiyVjW3sLa1nml6Z0vSRNYcqaXW4GJqewNiByT7//ZShaQgBR2qaqWxoJSs5ruc/0mi6wV1uftbwDFJ6UYLZG3efuW1HanG5pK4Qqukzn+9T/bxOHpPtlz5NGKyMq10l2lAKB/zxKD2O8uosAEaiSna7XyMDJ5pGE9l8uU9NAE7KzyApzuc1C4QQjB+syoTvPqYHXE3fWWFMSheOzvI5FBQgJd5GfpbKa9pVop3+mr7j1smT/VhMAhg7MIW4GAv1LQ4Kq5oCKZomSvl8r39hd24mGobSvtIG7E5XwOTSBAd/DKURwD1SyjVSygIpZaHnK9ACajSRSsek1P9eCuMHuVem9KRU03dW7Fdhd33RyXEDtfGuCQxOl2wPBV04xj+dtFkt7U0+9xzT46Smb1Q2tLL9qMrBPMVPnczNSCA5LoY2p4uD5Y2BFE8TBPwxlD4GpgVaEI0mmnC6JKsPqgnAglFZfh9n/CA9AdAEhqrGNnYaoSALRvXBUNI6qQkQO4/WUdNkJyUuhqlD0/w+jjaUNIHiy/0VSKmevTmp8X4dw2IR7c9uHX4X+vge7wNfAZ4UQkwGtgPHtbeVUr4VCME0mkhm+5Fa6locpMTFMKUPEwB3rPPuY3VIKf0Kl9JoAFYaVZzGD0phQIr/uUXtxnupnpRq+oY7P2nuyCxirP73m3Hr5F6tk5o+stLwup861r+wOzcTBqeyvrCaXSV1XDJD90EMZfwxlBYAJwPndfKZT8UcNJpoZcWBwEwARuckYxFQ3WSnrL6VgX6ucGk07rC7vniTAMZ6TEqdLtnr5qAajTcd+Un+e92hQye18a7pK2sLVP+kvjbUdi9y7tQepZDHnxna34GngcFSSovXSxtJGk0vWNmeC9K3CUC8zcqIbJU8v1uHlWj6gNuj1FedzM9KIi7GQovdRZFOntf4SYvd2T4pPdnPXBA37ry5QxWNtDp0KwWNf5TVt3CoohEh4KThfTWU3Lmc+rkd6vhjKGUBf5VSlgZaGI0mGmixO1lnTAD6kjTvZrw7/E6vTGn8pLiqicLKJqwWwdyRfTOUrBbBGKO0+B5d0EHjJxsLq2lzuBiYGseoAb6XqvdkYGocqfExOF1SJ89r/GbdoWpAGd5pib6XqvdkdI7S6fL6Vmqb7T3srTETfwyl14DTAy2IRhMtbCqqodXhYkBKHGNy+jYBABibo1am9pc19PlYmujEXVhkWm4ayX6Uqvdm3EB37pxeLdX4h9ubNG+kf6XqPRFCtBcZ0XlKGn9ZF6CwO1CtFAYZofIHyvWzO5Tx54m4F/i9EOJkYBsnFnP4eyAE02gilbWHAjcBABiVo0Lv9GCr8Rf3BGDOiL55k9y4PUoH9Oq9xk/c4+Ts/L5PSkFVY1xXUM3uY/VcHJAjaqKNNW6dDIChBOrZfayuhf1lDcwclhGQY2oCj79V7xqA04yXJxKVw6TRaLqgfVKaH5iB0R2WcqC8UVe+0/jFugIVUjJnRIB1Uns5NX5gd7rYVFQDwJwATUpHGzp5SBvvGj+obba394abEyDjffSAZFbsr9TjZIjjs6EkpRwRDEE0mmjA7nSxoVBNSgO1KjUiOwkh1EBe2dhGdrL/pZ010YdngvKsPiYouxk5QHk5D1U04nJJLLryncYHth+ppdnuJD3R1m7g9JURbkOpQhtKGt/ZUFiFlJCfleh3/yRv3HlKOhoktPG/LrFGo/GZHUfraLY7SUuwtecW9ZV4m5XcjARAr+BrfGd9gUeCckLfEpTdDMtMJMYiaLY7KalrCcgxNdGD2+t+0vDMgBnZI43qoIcqlfGu0fjC2kNur3tgFpOgw/Ou84tDG20oaTT9yLpD7glARkBX2T3D7zQaX3DnggRyAmCzWhiWlQjAQb1aqvGRjklp4PI2hqQnEGu10OZwcaSmOWDH1UQHaw+pgjeByuOEDo9SUVWTLlsfwmhDSaPpR9yVnAIVduemw1DSk1KNbwTDUIIOndTlmDW+4HLJdo9SoAo5gCpbP9ww3nX4ncYXmtucbDtSCwQuPwlgQEocKfExuCQUVOiec6GKNpQ0mn7C5ZKsD8IEADpyQrShpPGFuhY7uwKcoOxG66TGH/aVNVDbbCfBZmXy0LSAHjs/uyN3TqPpLZuKq7E7JYNS48nLTAjYcYUQepEzDNCGkkbTTxwob6C6yU68zcKUAE8A9GCr8YcNhdVICcMDmKDsRnuUNP7g9rrPHJ6OzRrYKcpIbShp/MDdaHb2iMyAV5UdYehkYaX2KIUqfnUWFEKkA3OAHLyMLSnlU30XS6OJPNwTgOl56cTGBGcCcKS6mTaHK+DH10Qm6wLcq8aTUdqjpPGDYOqke1J6UBtKGh9YW+DOTwq8TrrDQQsrtU6GKj4bSkKIC4FngSSgHtU7yY0EtKGk0XSCewIQ6BAnULHOCTYrzXYnh6ubGBmgkrqayKajp1cwJqVKB0tqW2ixO4m3WQN+Dk1kIaUMsk66PUraeNf0DrvTxcbCGiA4OpmfpXSyQBtKIYs/y85/Af4HpEgp06WUGR6vwGuRRhMhuJt6BrqQA6hY546VKe3C1/RMi93JlmKVoBwMncxItJESr9biiqq0Tmp65nB1MyW1LcRYBDOGBa7inZsRhpfzcHWzrjKm6RWePb3G5AR+AVI/t0MffwylocDfpZT6rmo0veRITTNHapqxWgQzgzABAO3C1/jG1sO1tDldZCfHkW/oTiDRxrvGV9wVGCcPTSMhNvAeyAHJcSTHxSAlFGmd1PSCtYcC39PLE7dHye1514Qe/hhKHwAnBVoQjSaScYfdTRqSSlKcX6mBPdLhwtcTAE3PtIc4jcgIeIKym+GZ7kRlbbxresatk3OD4OEEZbzrPCWNLwRbJ9MTbaRqz3tI48+M7V3gT0KIicA2wO75oZTyrUAIptFEEmuDVBbck+GGoaQHW01vWBvEpHk3w7RHSeMD/TFOjshOYtuRWl35TtMjqqeXu/lx8Iz3/Owkth5WOjl2YEpQzqPxH38MpX8bP3/RyWcS0Bm7Go0Xwazk5MYd5qSTQjU94XRJNhQaOXNB1El3SF+hNt41PVDR0NpeSv6k/OCEJ4NH5TtdjVHTA3vL6qlttpMYa2XSkNSgnWd4ljKUtOc9NPHZUJJS6rrDGo0PVDe2sa9MPZRnB3EC4DaUiquacLok1iDEU2sig10ldTS0OkiJi2HC4OBNAIYZoXdFegKg6QF3M+5xA1NIT4wN2nl03xpNb3F73WcNzyAmwD29PMlvX+TUOhmK9OnOCyEC26FQo4lA3DHOo3OSyUqOC9p5BqclYLMK7E5JSW1z0M6jCX/cE4CZwzOCalC7jffD1c04nK6gnUcT/qxtb+oZvMUkgLzMBEDppEbTHf0RngwdYfPaoxSa+GwoCSGsQoifCyGOAA1CiJHG9t8IIW4PuIQaTZizrh/i7gGsFkFeps4J0fRMRyGH4OrkoNR4YmMsOFySozUtQT2XJrxxN/UM9jjpHiOP1qrm3BpNZ0gp2w2lYI+T7R6lCv3cDkX88Sj9FLgFuAdo89i+DfhKAGTSaCKKte3JoMFdKYWOynfaUNJ0xXFNPYM8AbBYBMPcxnuVXi3VdE59i52dR+uA4OvkgOQ44m0WpFRtGzSaziiqaqKsvhWbVTA9Lz2o53J7lI7W6v5eoYg/htJNwB1SymcBzzu6FRgfEKk0mgihqc3BjiNGU88gr5QCHZNS7cLXdMGhikYqGtqIjbEwNTct6Ocbnqnj7zXds7GoBpdUYXGD0xKCei4hOox3XSFU0xVrDG/StNx04m3BrVGWnRxLUqwVKaG4ShvvoYa/DWf3d3Esmy8HEkL8WAixTghRL4QoE0K8IYQY57WPEELcJ4Q4KoRoFkIsF0JM8kNujabf2VRUg8MlGZIWT25G4Jt6epOvK99pesDtTZqem05cTPCLlLpLhOuCDpqu6I+qoJ7kZXQUvtFoOqNdJ4Ps4QR3c26dpxSq+GMo7QBO6WT7lcAmH491GvAoMA9YjKrC96EQIsljn3uAu4FvAbOBY8AyIYQuNq8Jedb042ALMFxXdNL0QH8lzbvR4aCannD3T5rTX4ZSpjaUNN2ztp/Ck93kZ2vPe6jiTx+lXwFPCyGGogytywwv0E3ABb4cSEp5rud7IcStQBkwC/hcqHbx3wXul1K+ZuxzM1AKXAf8yw/5NZp+o79XSod7hJRIKVH/QhpNB/1VXMRNu0dJT0o1ndDqcLK5uAbovwUlHXqn6Y7SuhYKK5uwCFUavD/QXs7QxWePkpTybeBqYAmqweyvgQnAhVLKZX2Uxx0wX2X8HAEMAj70OH8r8BmwoI/n0miCSpvDxabi4Hb19iY3IxGLgKY2J+UNrf1yTk34cKy2haKq/p0ADPeoxCil7JdzasKHrYdraXO4yE6OZWR2Us9/EADchlJxtZ6Uak7EXe1uwuBUUuN9yijxm9xMdysFrZOhhj8eJaSUHwAfBFIQw3v0IPCllHK7sXmQ8bPUa/dSYHgXx4kDPJvVpADY7XbsdnvgBPYD9/nNlkPTP2wurqHF7iI9wcbw9Di/7ruvOiNQJZmP1rZQUFZPRnzwc1A0oUV3OrNqfxkA4welEG/tn7FoYLINi4Bmu5Oj1Y3kpASvl5jGP8x8Nq3eXw7AzGHpOByOfjnn4FQ1+S2qbNLPYz+J5PnM6gMVAJw0PL3fvt+QVNVkOZJ1MpR0xhcZ/DKUgsQjwFTg5E4+816GFJ1sc/Nj4JfeGz/88EMSE4OfTN8bli3rq+NNEw58fEQAVnLjW3n//ff6dCxfdCZRWgALb3+6ipIBegU/WulMZ149qHQjW9aydOnSfpMlPdZKVavg5aUfM0Jnl4YsZjyblu5SOpnUVMLSpUf75ZytToAY6locvPLWUhJDaSYUZkTifOaT7VZAYKk8xNKlB/vlnKXNADEUVNTz7rtLieSo+VDQmaam3nvuQmJ4EEI8DFwEnCqlPOzx0THj5yCgxGN7Did6mdz8HuWZcpMCHD777LNJTU0NkMT+YbfbWbZsGYsXL8Zm6x93rsY83nxmE1DO+XPGs+TkfL+O4Y/OfNG6g/0bj5A5bCxLTh/l13k14Ut3OvOPR1YCDVxx2nTOmzyo8wMEgeeOrWPNoWpyx01nyfQh/XZeTe8w69nkdEl+uvFTwMHN5y1k0pD+e0b/cedyKhraGD/rZCYPNXduEI5E6nympslOyapPAfjapWeQldw/HvBWu5Pfbf6YNpdg3qKzyEqK7Zfz9iehpDN1dXW93tdUQ8kIt3sYuBRYJKU85LXLIZSxtBijop4QIhZVLe9HnR3TyGFqT85wJ7PbbDbTb4ybUJJFExxcLsmGohoA5o3K7vP99kVn8rPdzetatZ5FMd46U9tkZ29ZAwDzR+f0q24Mz0pizaFqjtS2aZ0MYfr72bT3aC0NrQ6S42KYkpeJ1dJ/y+jDMhOpaGijpL6NGVon/SbS5jNbjqj8pJEDkhiUkdxv57XZbAxMjaO0rpVj9XYGpfdPvp4ZhILO+HJ+f8qDB5JHgRtQFezqhRCDjFcCgFSZv38DfiKEuFQIMRl4AmgCnjNHZI2mZ/aVNVDbbCfBZmXy0OA39fQkT1d00nTC+sIqpIQR2UkM6Oc8IV1lTNMZ7qT5mcMz+tVIAj1OajrHXRZ8bj8VYPJEV74LTfpsKAkhrEKI6UIIf0oofQNV6W45KrTO/braY58/ooylfwDrUQ1vz5ZS1vdBbI0mqLgH2xnD0rFZ+3c9QvcI0XTG2vay4P1T7c6TPF1lTNMJ69r7J/W/TmrjXdMZa/u5pYcnepwMTXwOvRNC/A3YJqX8rxDCSkep7iYhxAVSyuW9PZaUssclJMOrdJ/x0mjCAvdg219lwT1xTwBK6lpodTiJi9GV7zT939PLk2HaeNd4IaXsaH5s5qRU66TGoKnNwfYjtYA5z+68jAQAiqua+/3cmq7xZ6n7CmCL8fuFqF5H41Fen/sDI5ZGE75IKdsnpWYMtllJsSTYrEgJR2ta+v38mtCjuc3JNmMCMHdEVr+f320oHatrocXu7Pfza0KPgsomKhpaibVamJaX3u/n18a7xptNRTU4XJKh6QnkZvR/lWTdSyk08cdQyqajGt0S4GUp5V7gv8CUQAmm0YQrxVXNHKtrwWYVzMjr/5ASIYQOK9Ecx6biauxOycDUOPIyE/r9/JlJsSTGKuP9SI1eLdXAmoOVAEzPSyfe1v9e77z2SWkzTpduo6CBNYfMC08GyDU8Soer9RgZSvhjKJUCE42wu3OBj4ztiYBeKtREPWsOqQnA1Nx0EmLNCXvTicoaT9YcdCcoZ7VXAu1PtPGu8cbM8GRQjbltVoHDJSmp1RNTDR6RIP3vdYeOYg5HqptxaeM9ZPDHUHoceAnYjmr66u4cNRfYHSC5NJqwxewJAOiwEs3xhIJOtq/ga53U0LF6b5ZOWi2iPbxK54Ro2hwuNhapnLk5I8zxKA1Oi8dqEbQ5XZTW67D5UMFnQ0lKeR/wFeAxYKHRtwiUN+kPgRNNowlP3NXFzJ2UupNC9aQ02vGcAJhR8taN9ihp3ByubuJITTNWi2DWcHMmpaALOmg62HakllaHi8ykWEYN6L/+SZ7EWC0MSY8HtPEeSvjVcFZK+Uon257suzgaTXhTWtdCYWUTFoGpEwA9KdW42Xq4pn0CMDrHnAkAaJ3UdOAuCz55aBpJceb1vXdXGdM6qXGHzM/OzzAlPNlNXkYixVXNFFc1mbrYqunArxFKCHEmcCaQg5dXSkp5WwDk0mjCEneI08QhqaTGm9d5un1SWtmElNLUgV9jLu0hTvmZ5k4AMt2TUr1SGu24x0kzPZyg+9ZoOvDM4zQTladUqXUyhPA59E4I8UvgQ5ShlA1keL00mqilPRck39zB1h17X9/qoLbZbqosGnMJhfwkOD5vTrXH00Qrnsa7meRl6NA7DTicLtYbXs65I8023nUvpVDDH4/S14FbpJRPB1oYjSbc6ZiUmrtmkBBrZUBKHOX1rRRXNZOeGGuqPBpzCKUJgNt4b2h1UNNkJyNJ62Q0UlbfwsHyRoQwp9GsJ+3Guy7HHNXsOFpHY5uT1PgYxg9KNVUW7eUMPfypehcLrAy0IBpNuFPd2Mae0nrA/AkA6JwQDewsUROAlBCYAMTbrAxMjQO0TkYz6w6pwiLjB6WSlmheeDJ0rN6X17fqRshRjDs/ac6ITKwWc8PU3QtKujpo6OCPofQf4LpAC6LRhDvuBOXROclkJceZLI02lDQdHs7Z+eZPAEDrpAbWGpNSs/OTANISbKQYxSQO6xX8qCVU8pOgw3gvqWuhzeEyWRoN+Bd6Fw/cIYQ4C9gKHJcAIaW8OxCCaTThRqjkgrjRLnzN6oOhkTTvJi8jkXUF1dpQimLM7p/kiRCC3MxEdpXUUVTVxOicFLNF0vQzTpdsb+lhdngywIDkOOJtFlrsLo7WNJOfnWS2SFGPPx6lqcBmwAVMBmZ4vKYHSjCNJtxoH2xDYAIAHaVvdaJydOJyyXYvZyhMSkH3rYl2appCKzwZPMdJnacUjew+Vkd9i4PkuBgmDjY3PBkM4z1DL3KGEj57lKSUpwdDEI0mnGlodbDjaB0QOhMAHeYU3ewra6C22U5irJXJQ9PMFgfwTJ7XOhmNrC+oRkoYNSCJASnmhyeDNt6jHXfY3azhGcRY/fEdBJ68jAT2lzVo4z1E6JNWCCFyhRBDAyWMRhOubCysxumS5GUmMCQ9wWxxABiWpSYAR6qbcbp0OeZoY22BSpqfNTwDW4hMANw6qY336GRtu4fT/FwQN+0eJW28RyXuQg6hEHbnRofNhxb+9FGyCCF+IYSoBQqBIiFEjRDi50KI0HgaazT9TKj0T/JkYEo8sVYLDpekpFavTEUb6wxDyexeNZ64PUpHa1qwO3WicrSx5mDoFHJw0+FR0mNktOFySY/mx6Hz7Nb9vUILfwyb+4FvAfei8pJmAj8Bvg38JnCiaTThw6oQnABYLIJcY7VUr+BHF1LCukLDUAohnRyQHEdsjAWnS1JS02K2OJp+pKHVwXYjPDmUdFKv3kcv+8oaqG6yk2CzMjU3NMKTwaPprO7vFRL4YyjdDHxFSvlPKeVWKeUWKeU/gK8CtwRUOo0mDGhodbCluAaABaNDZ1UKdPx9tFLWAhUNbcTGWJiWl262OO1YLKI91Ekb79HFBiM8OTcjdMKToWP1vr7FQW2TvYe9NZGEO+wulMKTQfdSCjX80YxMYHcn23cbn2k0UcW6giocLsmwzMT2AS5U0AUdopN9tapn0vS8dOJtVpOlOR5d0CE6Wbm/AoAFo0JrMSkh1kq20fdO62R0sSbE2ie4cedyVja20djqMFkajT+G0hZU6J033zI+02iiilUH1KpUqE0AwMOFr+Pvo4p9dcpQWjgq22RJTkQb79HJyvZxMvR0smOc1DoZLUgpPQo5hNazOzXeRlqCDdDGeyjgT8PZe4B3jYazqwAJLADygCUBlE2jCQtWHlArpfND0FDSk9Low+WS7R6lhSEWCgod4aBaJ6OH2iY724/WAqE5TuZlJLKpqEZPSqOIPaX1VDS0EW+zMC0vdPKT3ORlJlB7xE5xVTPjB5nf3yma8dmjJKX8DBgLvA6ko8LtXgPGSSm/CKh0Gk2IU9PU1t4/aX6IrUqBzlGKRnaX1tPoECTGWpmam262OCegdTL6WHWwEilhdE4yA1PjzRbnBNweJW28Rw8r9itv0pwRWcTFhFZ4MuhFzlDCH48SUsqjwE8DLItGE3asPljVPgHICckJwPGxzklxfv3La8KI1Ubc/ezhGcTGhE6Cshs9AYg+Vh0IzfwkNx3lmHWIcrTgzplbGPI6qcdJs+nVrEkIMRXYLqV0Gb93iZRya0Ak02jCgFCfAKTG20hPtFHTZKe4ukm78KOAlYahNH9UaCUou3Eb7zVNdupa7KTG20yWSBNsVoRwfhLoEuHRht3pYo3RP2nh6BDXSW0omU5vl5c3A4OAMuN3CYhO9pNA6PkwNZogsTKECzm4GZaZSE1TLUWV2lCKdOxOF+uNRrPzQqySk5vkuBiykmKpbGyjuKqJSUNCLz9AEzjK6lrYX9aAEDBvZGjqpHv1/nB1My6XxGLpbHqjiRS2Hq6hodVBeqKNiYND85mojffQobdxGSOAco/fRxo/vV8jAy2gRhOqlNe3ss+YAIRSV29vdPJ89LD1cA2NbU6SYiQTBqWYLU6X6NXS6MG9mDR5SBrpibEmS9M5g9PjsVoEbQ4X5Q2tZoujCTLu/KT5I7NC1ihub6NQ1YyU0mRpopteGUpSykLZcaeGA0eMbe0v4IjxmUYTFaw6qAbbiYNTyUgKzQkAeA64elIa6bgnAGNSQ3tVXBvv0cPKEA9PBrBZLQxOUzmmepyMfFa485NCNOwOYEh6PEJAs91JRUOb2eJENf5k+n5K541l04zPNJqoINTzk9y0J4VW60TlSMc9KR2TFtorkMN0lbGoQErZbrwvCOFJKXiOk1onI5mmNgebimqA0DaU4mKsDDYKROlx0lz8MZQEKhfJmyyg0acDCXGqEOJtIcRRIYQUQlzi9fkTxnbP12o/ZNZoAk4oN1D0RFcZiw6a25xsLKwBYGzIG0q6ylg0UFzVzJGaZmIsgtn5GWaL0y26OXd0sK6gmjaniyFp8eRnJZotTrfkZrpz5/Sz20x6XStYCPGa8asEnhBCeAbyWoGpwEofz58EbAEeB17tYp/3gVs93msfpMZ0Dlc3UVjZhNUimB2iSfNuPEPvdKJy5LK+sIo2p4tBqXEMiHeYLU636Byl6GCF4eGcMSydxNjQbk2gyzFHB+6y4AtGZyNEaD8Lh2UmsvZQFUWVWifNxJeRq9b4KYB6wHPZpQ1YDfzbl5NLKd8D3gO6U9hWKeUxX46r0QSbz/caE4C8dJJDvDeRO1G51UhUDsWGj5q+4/Zwzh+ZiRA+Off7nWGZHVXGnC6JVRvvEUm4eN1BVxmLFtzG+8LRoR0yDzocNFTo9QxPSnkrgBCiAPizlLK/nsSLhBBlQA3wGfBTKWVZP51bo+mUL/apIpCnjh1gsiQ9405UPlzdTHFVkzaUIhR3gvL8kVlQUmyyNN0zOC2BGIugzemitK6FIekJZoukCTAulwyLpHk3OvQu8qlubGPH0ToAFoaB8T4sS+dyhgI+L4VLKX8VDEG64D3gZaAQVX78N8AnQohZUspOa3gKIeKAOI9NKQB2ux273R5kcbvHfX6z5dD0DYfTxZdu9/3IjKDez0DpTF5GAoermzlUXs+0oaFbNlrjH1WNbWw7opz+c4ansqUk9MeZIenxFFU1c7CsjgFJoe2VjXSC8WzadqSWqsY2kuKsTB6cFPL6OChFVS4tqW2mqaUVm9WfFO7oIRznM1/sLUVKGD0giYwEa8jLPtjQyeKqppCXtTeEks74IoPwpz67EOIK4CpgGHBcXWQp5UyfD6iOKYFLpZRvdLPPYJTRdI2U8rUu9rkP+KX39ueee47ExNBO3NOEB4fq4W/bY0iMkdx/kpNwiBp64YCFVWUWzs11cl5eaCf6a3xnQ4XgqX1WhiRKfjTNabY4veIfOy3sqbVw3Sgnc3O0TkYaHxwWLC22MiXDxVfGu8wWp0ekhB+usWKXgp/PcJCtHe8Rh/s5eOogF5ePCH2drG2DX2yIQSD5y1wn2nYPHE1NTVx33XUAaVLKuu729XkZTwhxF3A/8CRwMaoQwyhgNvCoz9L6gJSyRAhRCIzpZrffAw96vE8BDp999tmkpprbgdlut7Ns2TIWL16MzWYzVRaN/zz08X7gIIvGD+KC86cF9VyB0pmizw6y6qP9JGTnsmTJlABKqAkFlr+6DSjh/JkjWHzGiLAYZ1Y5drJn3WEy8saw5MzRZosT1QTj2fT0f9YCNVx5yiSWzM4LyDGDzcMHVnCgvJFR0+ayMMTbPphNuM1npJT84S9fAC3ctHgWp4VB2LyUkvu3fEyrw8XUBYsYnhnei/2hpDN1dd3aRsfhT7zDncAdUsrnhRA3A3+UUh4UQvyazvsrBQwhRBaQB5R0tY8Rktfq8TcA2Gw202+Mm1CSReM7Kw5WAbBo3MB+u4991ZnhA1S43ZGaVq17EYbLJfliv9LJ0yd06GSojzP52ckAHKlpCWk5o4lA6Uxdi51NxSoU9PTxg8Lm/g7LTORAeSMldW1hI7PZhPo442ZvaT0ltS3ExlhYOGYgNpvVbJF6RV5mIvvLGiipa2P0wDSzxQkIoaAzvpzfH0feMDrKgDdj5AABTwPX+nIgIUSyEGK6EGK6sWmE8X6Y8dmfhRDzhRD5QohFwNtABfC6H3JrNH2mtsnOluIaAE4ZG/rJoG50L6XIZdexOioaWkmMtXLS8NAuVe+Ju6KT1snIY+X+CpwuycjspPZqcuGALlsfuXy2RxVgmjcyi4TY8DCSQOUXgy4yYib+GErHUM1lQeULzTN+H4EqHe4LJwGbjBeokLlNwK8BJzAFeBPYiwr12wvMl1LW+yG3RtNnvtxfgUvCmJxkBqeFT6Uut6F0rK6FFnt45LBoesdne9UEYMGoLGJjwieIvcN41xOASOMzo31COFQF9aSjHLPWyUjDPU6GQ8idJ3qR03z8Cb37BLgQ2Aj8F/irUdzhJKDTAgtdIaVcTvfG1Tl+yKfRBI3P94ZPWXBPMhJtJMVaaWxzcri6mdE5yWaLpAkQ7pXScJ0AVDS00tzmDKtVXk3XSCnbx8lw00m3R6moMrT7kGl8o7HVwdpD7pD58NRJ3UvJPPxZfrwDVcwBKeX/AbcAu1CV5r4RMMk0mhBDStneP+mUMeETdgcqV08PuJFHQ6uDDYXVQPgZ72mJNlLj1Vqd1snI4UB5I0dqmom1Wpg7MnxCQQHys9UYWahX7yOK1QcraXO6yM1IYGR2ktni+ESH8a510ix8NpSklC4ppcPj/UtSyruklH+XUrYFVjyNJnTYU1rP0doW4mIszB0RfhWRhun4+4hj5f4KHC5JflYiw7PCawIAMCxLTwIiDXeI05wRmSTGhld/rOGZ6n+opslOTZOezkQKyz287u4CX+FCvjGuF1Q24k87H03f6dUoJoSY2tsDSim3+i+ORhO6fLyrDICTR2eHZZjQML0yFXEsD9MQJzd5GYlsP1Kn4+8jiOV71Dh5ahgVu3GTEGtlUGo8x+paKKhsYnpibM9/pAlppJQs36t0ctG4HJOl8Z3hxmJSfYuD6iY7mUlaJ/ub3i73bAYkPRdrkED4zSA1ml7w8a5SAM6YEH6DLXi48PWkNCKQUvLp7vCdAIBOVI406lvsrD5YCcCZEwaaLI1/DM9K5FhdC4WVjUzPSzdbHE0fKahsoriqGZtVMD8Me2PF26wMTounpLaFQxWN2lAygd4aSiOCKoVGE+JUNrSyySgLfsb48J6U6opOkcGOo3WU1LaQGGsNywkAdBjvh3WOUkTwxb4K7E7JiOwkRg0Iz4Ix+VlJrDlURUGF1slIwL3AOTs/k+S48AoFdTM8K5GSWmW8zxqeYbY4UUevtEZKWRhsQTSaUGb5nnKkhImDU8OqLLgnnj1CpJRhF6utOR7PUND4MGme6I32KEUWbp0M18UkgOHugg668l1E8JFhKJ0Vph5OgBHZSaw+WEVBhdZJM/DZvBZC3NTd51LKp/wXR6MJTT4xQpzODNOwO4Bco3FdQ6uOdY4EImEC4GkoaeM9vHG6JJ/uCf9x0p08f0gbSmFPTVMb6wpUVdBwHieHtxd00AtKZuCPH/Ihr/c2IBFoA5oAbShpIoo2h6u9L0g4r5TG26wMTI2jtK6VoqombSiFMaV1LWw7UosQcHoY6+SQ9ASEgBa7i/KGVnJS4s0WSeMnm4urqWpsIyU+htn54VUW3BO3oVSoJ6Vhz/I95ThdknEDU9orbIYjnpXvNP2PP+XBM7xeycA44Evg2oBLqNGYzPqCKupbHWQlxTItN91scfqELhEeGbhDnKblpjMgJc5kafwnNsbCECOUVetkePPRro7CIjarPy0aQwN3lbGqxjZqm+0mS6PpC8vcXveJ4buYBB39vQ5V6BLhZhCQ0UxKuQ+4lxO9TRpN2POxEXZ3+vgcLJbwDg3Sle8iA3eC8uKJ4RtO4iYv020o6SIj4cwnhqF0VhiH3QEkxcW0Lz7oVgrhS5vDxWdG/6RwDruDjv5e7hLhmv4lkMs+TmBIAI+n0ZiOlJJlO9Wk9MwwDnFyoz1K4U9zm5Mv91cA4Z0L4kYXdAh/iqua2FNaj9Uiwranlyf5hldJ5ymFL2sOVdLQ6iA7OS7sI0Hc/b1Ah9+ZgT/FHC7y3gQMBr4FrAiEUBpNqLCrpJ6iqibiYiycGgETgLwMPSkNd1bsr6DV4WJoegLjBqaYLU6f0YZS+OMuLDJreAbpEdCkdXhWEusKqinUVcbClo92uovdhH8kCKjwu2N1LRRUNDJzmC4R3p/4U8zhDa/3EigHPgG+31eBNJpQ4v0dxwA4dewAksK0B4Mn7lhnXWY0fPnA0MnFEwdGRJW49nBQHeYUtry3XenkOZMGmSxJYBiRrauMhTNSyvacuXAPu3OTn2WUCNc62e/4PPOTUoZvlqZG4yPvby8B4LzJkTEBGJmtmkAerW2hqc1BYmz4G3/RhN3p4kNjpfTcCNHJ4bqiU1hTVt/CuoIqIJJ0UvdSCmd2HK3jSE0z8TYLC0dnmy1OQMh3G+96kbPf6dMsSRjLmTJMynA4nU5cLpdp57fb7TgcDuz24CbjWSwWrNbwbEAZShwob2BvaQMxFsGZ4yNjVSojKZbMpFiqGts4WN7I5KFpZouk8YFVByqpbbaTnRwb1iWYPRk5QE0AyupbqWuxkxpvM1kijS98uKMUKWFabhpD08OzGbc37nLMB/WkNCxZuk0tcJ4xPoeE2MiYC+Vr4900/DKUhBC3A98Dxhjv9wF/k1L+J4CyBRSn00lxcRltbebZdHa7ndLSRg4dKsdmC95kIDZWkJeXo42lPuIOcZo/Kou0xMiZvI0akERVYxsHyhu0oRRmuEOczp40CGsExN0DpMbbyEmJo6y+lYPljUzPSzdbJI0PvG/o5LmTB5ssSeBwG+9VjW1UNbbpnnNhhJSy3VA6L4J0coQRDXLQKBEeCWHX4YI/xRx+gzKSHgZWGZvnA38VQuRLKX8WQPkChsvloq1NYrVmEBNjTriRxWLHZssiLm5A0Awlh8NBW1s1LpdLG0p95ANjAhBJgy3AqAHJrCuo5kC5XpkKJxxOFx8axvuSCNTJsvpWDpQ1aEMpjKhubGPVwUogcsKTARJjYxiansCRmmYOlDeQmRQZ3ttoYGdJHQWVqgBTODeI9yY/OxGLUCXCy+tbyUnVzbn7C38shm8AX5VSPu+x7S0hxFaU8RSShpKbmJiYoHpzenv+YMrgdAbt0FHDkZpmthyuRYjI6FXjiXu19EB5g8mSaHxhbUEVlY1tZCTamDsysiZuo3KSWHWwUutkmLFsVylOl2TC4NT2HIpIYVROsjKUyhoiJsw1Gnhvm1pMWjQuMgowuYmLsTIsM5GCyib2lzVoQ6kf8acwgxVY38n2DfQx50mjCRXc3qTZwzPbmw9GCqMGGC587VEKK9whTosnDsRmjayaOm6d1IZSePF+u9c9crxJbkbpBaWwwzPsbsmUyPK6A4zOUePkfq2T/Yo/T9tnUF4lb+4Anu2bOBpNaPDO1qNA5FRx8qTDUGrA5QqLOixRj8sl2/OTzovkCUCZngCEC3Utdr7YVw5EpqGkdTL82FNaz8GKRmJjLJwZIWXBPXE/u7VO9i/+eoBuF0KcDaw23s8D8oCnhBAPuneSUt7dR/k0mn6nuKqJjUU1CAEXTI28SWluRgI2q6DV4eJITXN7HxtN6LK+sJry+lZS4mNYOCoyyt164p4AFFY2YXe6Is5jFol8uKMUu1MyakASYyKg8bE3HV5O7XkPF5ZuVd6k08YOIDmCwu7cjMrRnncz8EeTJgMbjd9HGT/Ljddkj/3CZqn6iitg1arjt9lsMGAALF4M99wD6el9O8fcuTB3rpXzz+/bcTTB560typu0YFRWRMYBx1gt5Gclsa+sgQPlDdpQCgPe2HwEUA09Y2Miz4gYlBpPYqyVpjYnRVVN7ZNUTejypqGTF08farIkwcHtUSqubqLF7iTeposjhTJSSt5tD7uLPA8naC+nWfjTcPb0YAhiNpMnw+9+1/HeboetW+GBB2D7dnjzTehLNcb//hfi450cONB3WTXB5a3NylC6aNoQkyUJHqMGJLOvrIGD5Y0sGme2NJruaHO42uPuL4nQSanFIhg5IIntR+o4UNagDaUQp6y+hRX7KwC4eHpkjpNZSbGkJdiobbZzqKKRCYNTzRZJ0w07jtZxoLyRuAgNu4MOQ6m0Tvec60/6tDQphMgVQkTEkzslBWbN6njNmwd33AHf+hZs2AAbN/Z8jO6YPBmGDw+MrJrgsftYHXtK64m1Wjh3UuSF3bnRle/Ch8/2llPTZCcnJY75o7LMFido6FCn8OGdLSW4JEzPS2d4VmRVu3MjhNAr+GHE65uUh/OsiQMj1oBw95wDOKB1st/w2VASQliEEL8QQtQChUCREKJGCPFzIUTExYRMm6Z+Hj6sQvS+/W346ldh3Di48Ub1WV0d3HcfLFgAI0fCGWfACy8cf5y5c+H73+9w3be0wG9/CyedBCNGwFlnKa+VJ9u2wVVXwfjxMHYsXH113w02Tfe4vUmnjRsQUU1mvdFVxsIHd9jdhdOGREyT2c7QOhk+vGmEJ18Sod4kN7ryXXjgcLraQ+YvjVCvuxttvPc//uQo3Q/cDtwLrAAEsBC4D4gHfhoo4UIBd6hcfr76+dZbcMEFKpTO6YTmZrj0Uigvh+9/X3mN3n9f/V5WBnfddeIxpYSvfAXWrVP7jR0L770Hd94JbW1w5ZVQXw/XX6+Mr8ceU9sfekhtW7MGUnUUQMCRUrYPtpEaTuJmVPtgq1fvQ5n6Fjsf7SwFIjfszo02lMKDQxWNbCmuwWoRnD81wsdJXWUsLFhxoJLy+lYyEm2cNm6A2eIEldE5yaw8UKk97/2IP4bSzcBXpJRveWzbIoQ4AvyDMDWUpASHo+N9TY0q8PDQQzBzJkydqrZbrfCnP0Gikf/+5JOweze88QbMnq22LVqkjvXQQ8rrlJFx/Lm+/FLw6afwj3/AxRd3/E1TE/z+98rw2rsXKivh9ts7jjt6NDzzjDKitKEUeDYW1XC4upmkWCtnjo/MGGc37lWpioZWKhtayUqOrF5RkcIHO0ppdbgYmZ3E5KGR/U/fvlJa2oCUEtGXpFBN0HAXcVg4Ojviesx5MzpHh4OGA29s6vC6R3rFTO1R6n/80ahMYHcn23cbn4Ulq1crb5D7NW2a8vBMmQL//GdHIYe8vA4jCZQxlZvbYcy4uewyFV7XWajcihUCIVS4ncPR8Tr7bCgtVYbX+PGQlQW33AL33gsffggDB8LPfgZDI3th2TRe3XgYUJXFEmIju8JRclwMw4xqd3uO1ZssjaYrPCuLRbrhMCI7iRiLoL7VwdHaFrPF0XSClLI9PDnSw+7g+J5zDqfLZGk0ndHY6mhvfHzJjMifHI3Wnvd+xx+P0hbgW4B3UNm3jM/CkilTVIU7UEZRXJwySJK9ii8N8PLq1tScuA0gJ0f9rKs78bOaGoGUKuSuM0pLVfGH115TXqm33oKnn4aEBGWA/frXEB95VatNpbnNydvGBOCKk3JNlqZ/GDcohaKqJnYfq2fB6MjrzRPulNZFfmUxT2JjLIzOSWb3sXp2l9QxND3BbJE0XmwsquFgRSPxNgtnT4rMEsye5GUmkmCz0mx3UlDZ1L6arwkdlu0spdnuJD8rkRl56WaLE3TcOlhY2ajL1vcT/hhK9wDvCiHOAlah+iUtQDWcXeLLgYQQpwI/BGYBg4FLpZRveHwugF8CdwAZwBrgm1LKHX7I3S3JyR2FG3whPR0OHTpxe6lKKyCzEx9baqokKQlefrnzY7rzoUaPhocfVrlQmzbBq6/CU08pj9c3v+m7rJqueX9HCfWtDvIyE5g3InIri3kyYVAKy3aWsvtYJ9a8xnRe2XAYl4SThmeQnx2ZlcW8GT8oRRlKx+ojtsRvOPPSumIAzp8yJCIbenpjtQjGDUphc3ENu0rqtKEUgrgjQS6ZEfled4ABKXFkJNqobrKzr7SBKblpZosU8fgceiel/AwYC7wOpKPC7V4Dxkkpv/DxcEl0eKg64x7gbuPz2cAxYJkQImTagM+bpyrirVt3/PbXXlNNa6dPP/Fv5s6VNDaqvKhp0zpeu3fDgw8qw+idd5SXq6xM5UWddJLKX0pLg6NH++WrRRUvr1eD7RUz87BEcGUxT8YNUjkvOvQu9HC5JC+tV5PSq2fnmSxN/zHe6FWzq0Qb76FGY6uDd7aqh0806eSEwWq6oReUQo/iqia+NLzul82IjkgQIQQTh+hxsj/xa0lISnmUABRtkFK+B7wHnLASYHiTvgvcL6V8zdh2M1AKXAf8q6/nDwRXX60KOtx+O/zgB8rb8+GHqjz43Xcrw8aNlJKSJrj8bAfz5sVw223wne/AmDGweTP85S9w2mnKCzV7NrhccNttqpdTcrIKwaurgyU++e00PVFc1cTKA5UIAZfPivwYZzfjjQnA3tIGnC4Z0aWnw43VhyoprGwiOS6G86dGbj8vb8YPUjqpjffQ492tJTS2ORmZncTs/Iye/yBCmNBuvGudDDVeWl+MlHDy6GyGZSX2/AcRwoRBqazYX8lObSj1C34ZSkKIDFSJ8Amo0LtdwONSyqoAyjYCGAR86N4gpWwVQnyGCvXr1FASQsQBnqV4UgDsdjt2ux2LxX7C37hcKsbTbnd2K1Bn+8XEKKPogQes/PnPgvp6GDUK/vhHJ1ddJbHb3bLH8Nm+CtYMsjJxSg3/+18Wf/mLhYcftlBZqQo13Habi7vucmG3K2PpyScFf/6zhe9/X9DcDOPGSf75Txdz5nQc1xv397R3tYPmBF5cWwjAgpFZDEy2hdS1c8sSDJmGpsYSF2Oh2e7kYFkt+RHaODIceWFNEQAXTB2ETUif7n8wdSbYjM5WeUkHKxppaGohTsff9wu90ZkX1imdvGzGEByeJWIjnNHZagK+q6QuLP+ngoXZ44zD6WoPBb1y5pCoujdjc9SzeufR2rD63mbrjCe+yCCklD4dXAhxGvAmUAesNzbPQoXhXWSE5vmMEELikaMkhFiA6tM01PBgufd7DBgupTyni+Pch8prOo6nnnqK+nqJzZZFTIw5sdXP7hfsrrFwfp6TeUEKv3c4HNjtlQwcmGTa9wwnXBJ+tdFKTZvg5jFOZmb79v8Q7vx5q5XiRsFtY51My4qu7x6qNDng5+utOKTg+1McDIuitAgp4afrrTQ6BD+c6iBX2+4hwbEm+P2WGCxIfjXLSWqs2RL1H80OuHedepb+7iQHSZHbhzys2F4l+PceK0kxkl/PchIT2VXBj+NII/xxawwJVsnvZzuJgtSsgNPU1MR1110HkCal7NY1589M+lHgJeAbUkongBDCiuqh9Cgw2Y9jdof37E10ss2T3wMPerxPAQ4vXryYyspW4uIGYLOZM9IdiDnI7tXFOFMHc8YZE4JyDrvdTmtrOSNGmPc9w4nP91VQs3ojqfEx/PDaM0NuBdtut7Ns2TIWL14clPv5Wct2ijcdJWnoGJacMTrgx9f4ztOri3DI3YwfmMzXrpzvc4JysHUm2LxQuo7Vh6rJHj2NJVFQ7jcU6Eln/vD+HqCQ08fncM0lM/pfQJN5eN/nHKlpYdjUecwdEbZdUAKK2ePMm89sAsq5ek4+F503rt/PbyZtDhd/3fExzU6YsfB0hoRJhVCzdcaTus5KUneBP4bSKOByt5EEIKV0CiEeBG7y43hdccz4OQgo8dieg8pT6hQpZSvQ6n7vnmTYbDZsNpfx05wb5E5U3l/WGFQZXC6bqd8znHhurSricPmsXJITQ7fmerDu58Qhaby26Sj7ypq0voQAUkpe3qgc6NfMGUZsrP9L9+E6BkwYksbqQ9VaJ02gM51psTt5fbN6BF8zZ3hU3pMJg9M4UtPCvvImTh6rqzF6YsY4c6y2heV7ywG4bl706aTNpnp87T5Wz97yZoYPCK9m5KHwbPLl/P44KzeicpO8mQBs9uN4XXEIZSwtdm8QQsQCpwErA3iefmOckahcUNlESw/5UJrgU1zVxCd7ygC4cd5wk6Uxh/FG5Ttd0Sk0WF9Yza6SOuJtlqhontgZE9p1UifPhwLvbC2hqrGNIWnxnD6uk6aBUUB75Ttd0CEkeHl9MS4Js/MzGJ0TMkWQ+5WJukJov+GPR+nvwENCiNHAamPbPOCbwL1CiKnuHaWUW7s7kBAiGfCM9xkhhJgOVEkpi4QQfwN+IoTYB+wDfgI0Ac/5IbfpDEiOJTFG0uRQnb4nDtH1783kmdWFSAmnjMlm5IAoSgTxwF35rrCqicZWB0lR0BsllHliRQEAl84YSnpiFCWCeDBel2MOGaSUPLmyAIAb5g8nxhpFiSAetFe+0zppOnani2fWqAJM180dZrI05jFhcCpsOqINpX7An1nR88bPP3bxmaQjj6inhI+TgE893rtzi54EbjHOkYDKf3I3nD1bShmWyzpCCIYkSvbXCfYc04aSmbTYnbxo9Km5aX6+ucKYSHZyHIPT4impbWH7kVrmjoyOZruhSEltM+/vUBHHNy/IN1cYExmTk4JFQEVDG6V1LQxMDd2Q2EhnY1EN247UEhtj4ZrZUT4pRZWtdzhdUWswhgJLt5VQWtfKgJQ4zp8yxGxxTGOC9ij1G/78t4/o4TXS42e3SCmXSylFJ69bjM+llPI+KeVgKWW8lPI0KeV2P2QOGQYbpf53l2rlNpO3thylpsnO0PQEzhifY7Y4pjLV6Oy95XCNuYJEOc+sLsTpkswdkdkeEhmNJMRaGTtQeZW2FNeYK0yU4/YmXTRtCJlJ0enhBBiWmUhirJVWh4uDFY1mixPVPG543W+YO5zYaCp158UEr2gQTfDw2aMkpSwMhiD9hZn9H+x2OwPj7Einld1HqoNSSz6a+lv4i5SSp1YVAHDDvOFR32h1am46H+woZcvhWrNFiVpa7E6eX6s8nLdEsTfJzfS8dHYfq2fL4RrOnjTIbHGikrK6FpZuU0Ucol0nrRbB5CFprC2oYktxTbshr+lfNhVVs7m4hlirJarD7gCykuMYlBrPsboWdhytY46uxhg0oiYhwWKxEBsraGurxmlSHQW73c6AmEpwWtlXUk1D0zBsQXDhx8YKLJboXWnpibWHqth+pI7YGAtXz84zWxzTmZ6XDsBW7VEyDc+E+cUTdVWtaXnpvLCumC3F2ng3i2fXFOFwSWYNz2DyUB0mPi1PGUpbD9dy5Un6uWEGTxgezgunDWFASpy5woQA0/LSOLajhS3FNdpQCiJRYyhZrVby8nJwuVymyWC32xk7LIn0qngaWh24khMYEYQQG4vFgtUaWv2AQol/fX4QgCtm5UZ1OIkb9ySouKqZqsY2fU36GSkl//3yEBDdCfOeeIaDulwSS5R7ffub5jYnT69WwSPRnC/nydTcdEAvKJlFaV0L725VHs5bF+abK0yIMC1PRYNs1joZVKLGUAJlLJltQMTaYpiUm8Hagmp2lzYxJU8nz/cne47V88nuMoSAr57SYxpdVJCWYGNkdhIHKxrZcriG08dFd85Wf7N8bzm7SupIirVy3ZzoDidxM3ZgCvE2C/UtDg5VNjIqSqtSmsVL64upamwjLzOBJZN16CPANMNQ2lVST5vDFdX5MWbw+IoCHC7J7Hzt4XTj1kmdyxlc9H+6CUwZqrxIm7Ry9zv/+vwAAOdNHsSI7CSTpQkdprnD73SoU7/zz0+VTl43d1jUlgT3xma1MNmoCqonAf2L3eniMcPrfscpI7WH0yAvM4GMRBttTpcuXd/P1DbZecbwcH79tFEmSxM6TDE874erm6lsaDVZmsjF5xFQCJEnhMj1eD9HCPE3IcQdgRUtcplhTEo3FlabK0iUcbSmmbc2HwXga6fqwdYTd6iTDivpX9YXVLG2oAqbVXD7ydrD6YnbeNeGUv/y7tYSjtQ0k5UUq3NxPBBCMEWv4JvCk6sKaGh1MH5QStRXqfUkNd7GqAFqwXerLsYUNPxZKnoOOB1ACDEIWAbMAX4nhPhFAGWLWGYMSwdgb2k99S2Br3yn6Zz/fXkIh0syb2Rm+yRMo3DH3285XIuU0lxhooh/LlfepMtn5jIoTfcL8sT9P7pZTwD6DSllu07edvII4m0619UTd+GbjUU1psoRTTS2OvjfCpXDeefpoxFC5yt64h4nNxXphfdg4Y+hNBlYa/x+FbBdSrkAuA7VJFbTAzkpceRmJOCS6KpO/URFQyvPrikC4GvadX8Ck4akEmMRVDS0cqSm2WxxooLdx+r42MiXu+NU7U3yZro7J+RoHa0Ok0qVRhnL91awp7Se5LgYbpg33GxxQo7Z+RkArCuoMlmS6OH5tUXUNNnJz0rk/CmDzRYn5Jg5TOnkBm0oBQ1/DCUb4A6GPAt4y/h9N6C1uJe4lXujVu5+4V+fHaDZ7mRabhqLxg4wW5yQI95mZdIQlTu3vkDrZH/w8Cf7AVgyeTAjdbGCE/DMCdlxVOeEBBsp4WGPfLm0BJvJEoUeM4ZlYBEqJ+RYbYvZ4kQ8rQ4n//5C5ct9/bRRUd/zsDNm56uy4BsLa7A7zavqHMn4YyjtAL4uhDgFWAy8b2wfAlQGSrBIZ6YRfqcNpeBTVtfCU6tUIuj3Fo/VrvsucPdhWKtXS4POjqO1vLu1BCHgW2eMNluckEQIwUnGJGDtIa2TwWZbtWDbkToSY63aw9kFyXExTBhsLCgVap0MNs+vKaK0rpVBqfFcOnOo2eKEJGNykklLsNFsd7JTLygFBX8MpR8BXwOWA89LKbcY2y+iIyRP0wPuCcCGgmocehUgqPxj+QFaHS5mDkvnNO1N6pLZelLabzz44V4ALpg6pH3ipTmRuSO0TvYHLpdkaZGaDty2cATZybqZZ1ecNFxFg2jPe3BpbHXwyKfK6/6tM0YTF6Pz5TrDYhHtOqlDQoODz4aSlHI5kA1kSylv8/joMeDrAZIr4pkwOJXU+BjqWx3sLNGrAMGipLaZ59aq3KTvnz1Oe5O6wW0o7S9r0KVGg8jGomo+3l2G1SL43lljzBYnpJk7QvWZW1dQhdOli4wEi6Xbj1HSLEiJj9H95XrAvcipJ6XB5fEVh6hoaGN4ViJXz9bVF7vDrZPaeA8O/jZIEMAsIcTXhBApxrY2oCkwYkU+VotgjjEJWHVARywGi4c/2U+bw8WcEZksGKWb+3ZHRlIsYweqXJl1esANGn/+YA8Al88cqnOTemDikFSS42Kob3GwSy8oBQWH08XfP1G5SbcvzCctUecmdYc7RHlnSR21TbpqbTCoaWrjX0Yvr7sXj8Wme3l1y5wRHR4ll15QCjj+9FEaDmwD3gQeBdyxTPcAfw6caJHPvJFqwF19UBtKwWBvaT0vuL1JOjepV7gnAWsOaZ0MBiv2V7DyQCU2q+CuM7U3qSesFsFJRqWxNTr8Lii8vOEwhyqbSIqR3Dx/mNnihDwDU+MZNSAJKWGVfnYHhf/77CD1Lapv0oVTh5gtTsgzZWg6CTYrlY1t7CmtN1uciMMfM/0hYD2QAXjWEX4dODMQQkUL80e5w0p0nlIw+N3SXbgknDNpIHNHam9Sb1gwKhuAL/dVmCxJ5OFwuvjNOzsBuH7ucHIzEk2WKDyY2+551zoZaOpa7O0ezrNzXSTHxZgsUXiwcLQaJ1dqnQw4R2qaeWKl6pv0w3PGYdGV7nokNsbCXGPhfcV+rZOBxh9D6WTgt1LKNq/thYAuS+IDEwalkpZgo6HVwdYjup9SIPlsbznL95Rjswp+fN4Es8UJGxaMysIiYF9Zgy5/G2BeWFfM7mP1pCXY+I72JvWaU8aoSemqA5W0OfSCUiB59NP9VDa2MTI7kVMG6pCd3tK+oKQnpQHnd0t30WJ3MXdEJmeMzzFbnLDh5NFaJ4OFP4aSBeis/EguoH1+PmCxCBaOVquln+0pN1mayMHhdHH/u2rl/ub5+eRnJ5ksUfiQnhjLFKPR5xf7tE4GitpmOw8uU5XuvnfWGDKSYk2WKHyYODiVrKRYGtucup1CACmsbOTxLwsAuPfcceg0kN4zf6RaUDpY3qgXlALI6oOVvLu1BIuA+y6apMPlfeBkY0FpzcEqvaAUYPwZGpcB3/V4L4UQycCvgKWBECqaWDRWrZgs36snpYHi+XXF7C1tID3RxrfP0Cv3vnLqGL0yFWj+/vE+qhrbGJ2TzPXzhpstTlhhsYh2r5I23gPH75fups3p4pQx2Swam222OGFFWqKNKUPTAPhc62RAcLokv3pbLXBeN3eYbpvgI+MGppCdHEuzXS8oBRp/DKXvAacJIXYC8cBzQAEq7O5HgRMtOjhtnKqFsfVwjS7JHADK6lv44/u7AfjeWWN1BSc/aHfh76vQJZkDwL7Sep5cWQDAzy+YqCs4+cEpY9Q4+flebbwHgs/2lvP+jmNYLYKfXzBRr9z7waJxapHz091lJksSGTy/tohdJXWkJdj4/uJxZosTdggh2sdJrZOBxZ8+SkeB6agKd/8CNgH3AjOklPru+MjA1HjGD0pBSr2CHwh+884u6lscTM1N4wa9cu8XM4dnkBIfQ2VjG5uLa8wWJ6xxuST3vrYNh0ty1oQc3fDYT9wepW1Haimr06FOfaGpzcFPX98GwE3zhzN2YEoPf6HpjDMnKEPp873lOtSpj3gucN69eKwOTfYTd07XR7tKTZYksvBraVNK2Syl/J+U8ltSyjullP+RUjb3/JeaznCvTH28S9uZfWH5njLe3nIUi4DfXToFq66W4xc2q4XTDZ1ctlMPuH3h2TWFbCisJinWyq8vnmy2OGFLTmo80/LSAfhIj5N94m8f7eNwdTND0xP4wdl65d5fJg9JY0BKHI1tTtbq0vV94r63dlDX4mDy0FSun6tL1PvLaeMGEGMRHChvpKCi0WxxIoZeGUpCiIt6+wq2wJHI4okdLvxWh9NkacKT5jYnP39zOwC3LhzBZCN+XOMfiycOBGDZzmMmSxK+lNQ288D7qvTyD88Zx5D0BJMlCm/ONnTyQ62TfrP9SC3/+UI18vzNJZNI0uXA/cZiEZwxTq/g95X3tx9j6TYVBvrA5VOJ0aHJfpMab2svE651MnD0ViPf8Hq93sW21wMoW9QwIy+Dgalx1Lc6WLlfN7Dzhwfe301xVTOD0+K5e/FYs8UJe04bNwCbVa1MHSxvMFucsENKyS/e3EFDq4PpeencOD/fbJHCnnMmKUNp5f5KGlodJksTftidLu59bSsuCedPHcwZ4weaLVLY4w6/+3DHMVw6n9Nnapvt/MJY4Pz6aSOZNEQvcPaVM8e7F5S0oRQoemUoSSkt7hdwNrAZOA9IB9KM3zcC5wZHzMjGYhGcM2kQAO9tLzFZmvDjy30VPGEky//usil6lTQApMbbmGc06X1vu17B95WXNxxm2c5SYiyCP1yuw0ADwagByYzMTqLN6dLJyn7w94/3sf2ISpb/5YUTzRYnIjh17ACS42I4WtvCpmJdacxXfv32TsrqWxk5IElXqA0Q50xWc8l1BVWU6nzOgOCPj/NvwHeklB9IKeuklPVSyg+Au4G/B1S6KOJcQ7mX7SzF7tSJob2ltsnOD17eAsAN84a159Zo+s4FUwcD8NbmoyZLEl4UVjbyq7d2APC9xWMZP0iXuQ0EQoj2cfKtLVonfWF9QRWPfrofUPmbOSnxJksUGcTbrO1hyu9s1YucvvD2lqO8uvEwFgEPXD6VeFtn7Tk1vjI0PYFZwzOQEt7VOhkQ/DGURgG1nWyvBfL7JE0UMyc/k+zkWKqb7Hyueyr1ml+8tZ1jdS2MyE7iJ0smmC1ORHHupMHEWi3sKa1n97E6s8UJCxxOF997cTONbU7mjMjk66eNMlukiOLi6UMBVbilpqnNZGnCg/oWO997aTMuCZfNHMr5xgKIJjCcP0Vdz6XbSnT4XS85XN3ET4zKi986fTSz8zNNliiyuND4H397q15QCgT+GErrgL8JIdpHWyHEIOAvwNpACRZtxFgt7ZOA1zYeMVma8OCldcW8ufkoVovgwaumkRirQ+4CSVqijUVGny/tVeodD3+yn41FNaTEx/DgVdN0yF2AGTcohQmDU7E7Je9u06ulPSGl5Jdv7qC4qpncjAR+ddEks0WKOE4Zm01KfAylda2sPKBzjHvC4XTx3Rc2U9/iYMawdO46U4fcBZolUwdjEbCpqIaiyiazxQl7/DGUbgNygEIhxH4hxH6gCBgM3B5I4aKNy2YqQ2nZzlJqm+wmSxPa7Dha217l7ntnjWHGsAyTJYpM3Mb765uO6OazPbB8Txl//2QfAL+9ZDK5GYkmSxSZXDJ9CACv6wWlHnlubRGvbTqCRcCDV00nJV434A40cTFWLpqmdPKl9cUmSxP6/O2jfawvrCY5LoaHrp6hq9wFgZyUeBYajeNf3qB1sq/403B2PzAVuACVk/QwcD4wxfgsYAgh7hNCSK9XxGaWTxycyvhBKbQ5Xby1RU8CuqK22c43ntlIq8PFGeNzuHPRaLNFiljOnJBDRqKNktoWlu/RCfRdUVzVxHde2IyUcN3cYe0GpibwXDJjKFaLYH1hNftK680WJ2TZVFTNfUau3I/OHc+cETq8KVhcPTsPgPd3HNOLnN3w/vYSHjFy5e6/dDLDsvRiUrC4ZrbqR/Xy+sM4dN57n/C34ayUUn4opfy7lPIhKeUyKWWwlpt3oLxV7teUIJ3HdIQQXHmSGnCfWV1E8C5p+OJySb7/0haKqprIzUjgwaumYdHhTUEj3mbl8pm5ADy/tshkaUKT5jYnX3t6A7XNdqbnpeuKYkFmYGo8Zxod6J9do3WyMyoaWrnz2Y3YnZJzJw3ijlNHmi1SRDNlaJpa5HS4eGOzXuTsjL2l9dz9kiq8dPvJI/RiUpA5a2IOmUmxHKtr4TOd994nwsHn6ZBSHvN4RfQdv2JWLgk2K3tK61mju32fwB/e381Hu0qJtVr4x/UzSU+MNVukiOeaOWpl6pPdZRypaTZZmtDC5ZL88JUt7CypIyspln/eMJO4GF29KdhcP284AK9tPExzm27S7UmL3ck3ntlASW0LIwck8acrpyKEXkwKJkIIrjXGySdXFeiiDl7UNtm546n1NLU5WTAqix+fN95skSKeuBgrl81QxuhTqwpNlia8CYfs9zFCiKNAK7AG+ImU8mBXOwsh4oA4j00pAHa7HbvdXJe4+/zdyZEYAxdNG8yL6w/zxIpDzMrTpYXdPLe2mMc+V7f+D5dNYsLAJNPvabDpjc4Em+EZccwbkcHqQ9X874sD3HvuONNkCTX++MFe3tlaQoxF8NDVU8lOjDFdJ0NBZ4LNvOFp5GUkUFzdzIvrCrl+Tp7ZIoUELpfk7pe3sq6gmpT4GB69Zhrx1p51IRp0JthcNHUgf/pgDwfLG/l4VwmLxg4wW6Sg0ludabU7uf3JDRRUNjEkLZ4Hr5yCdDmxu/QCR7C5dvZQ/rviEJ/tLWfn4WrGDEw2VZ5QGmd8kUGEcniXEOI8IBHYCwwEfgaMByZJKTstLyOEuA/4pff25557jsTE8IiHPdoID2yNQSD56XQnAxLMlsh8dlULHtttwYVgSZ6Tc3JDV28jkR3Vgsd2W4mzSn4100lCOCyxBJkvjgleOaS8RzeMdjJ7gNbJ/uTzEsGrBVay4iQ/neHEqp0mvFlo4ZOjFqxC8o0JLsakaZ3sT14vsLC8xMLYNBffnKjzQlwSnthrYUuVhQSr5K5JToYkmS1VdPHfPRa2VlmYn+PimlFaJ900NTVx3XXXAaRJKbvtfxLS0x0p5Xseb7cJIVYBB4CbgQe7+LPfe32WAhw+++yzSU011ztjt9tZtmwZixcvxmbrvvrQ6paNfLa3gj3W4dy8JLpLuq4rqObepzbgwsWlM4bwwKWToiaUxBedCSbnScknD69kf3kjFekT+NqpI0yTJRT4YEcpr61W8fbfPXM031wUOjkgoaIzwWZRm4NP/vIFlU12LMNmsmTKILNFMpXHVxbyyao9ADxw2RQuNqoD9oZo0ZlgM7W6mS/+9iV7ay0MmTKP6XnpZosUNHrSGSklv3l3N1uqirFZBf+++STm6oIi/c7ASdVc8591rK+08sBNixicZl6z6VAaZ+rqet8b0mdDSQgxE7BLKbcZ7y8GbgV2AvdJKYPWBVBK2SiE2AZ0WXhfStmKCtNzywuAzWYz/ca46Y0sd505hs/2VvDG5qN8d/E4hqZHp1tpc3ENdzyziWa7i9PGDuCBy6cRGxMOqXWBJRT09+uLRvODl7fw3xUF3LxwRNSWGl62s5TvvrQVl4RrZufxnbPGhqThHgo6E0zSbDZuXpDP3z7ax6PLD3Lh9Nyo7Vv11KoCfveeMpJ+eM44rpg93K/jRLrOBJsROTYunTGUVzYc5pHlh3jytjlmixR0OtMZKSV/eH83T69Rpan/evV0Th470Azxop65owYwJz+TtQVVPPZlAb+9xPx6aKEwzvhyfn9mnP8CxgIIIUYCLwBNwJXAH/04Xq8x8o8mABHfaXDW8Ezmj8zC7pQ8+OFes8UxhR1Ha7npv2toaHUwf2QW/7pxVlQaSaHCJdOHMHJAEtVNdv73ZYHZ4pjCJ7tLufPZDThckoumDeH+S6eEpJEULdy6cARpCTb2lTXwxqborDb2/NoifvGmKgN+56JR3LlolMkSRTffPmM0Vovgs73lbCiMvoJMUkoeeH8P//pM5RP/5uJJXDC1995NTWARQnD32WMBeHFdMYerdQNaX/Fn1jkW2Gz8fiXwuZTyOuAW4PLAiKUQQvxZCHGaEGKEEGIu8AqQCjwZyPOEKj8yKsO8tukwO4/23k0YCawvqOKax1ZT1+Jg5rB0/nPzScTbdDUxM4mxWvjeWWrA/fcXBymrbzFZov7lgx3H+PozquTy+VMG8+BV06LWgxEqpCXY+PppyjB4cNleWuzRlSD+5MoCfvL6NgC+cvIIfnjOOG24m8zwrCSunKVaKvz6nV1RVQHP7Un6v88OAPDriydx4/x8c4XSMG9kFgtHq4X3B97fY7Y4YYc/hpLw+LuzgKXG78VAdiCE8iAXeB7YA7wGtAHzpJRRUetwel46F0wdjJTwq7d3RE1fpU/3lHHDf9dQ3+Jgdn4GT9w2h6S4kE6nixrOnzKYqblpNLQ6eOC96BlwX1hbxDee2UCbw8W5kwbxt2um647yIcItC/IZlBrPkZpm/rn8gNni9AtSSh5ctpdfvrUDKeHWhfn89PwJ2kgKEe5ePJakWCtbimuipq+S3eniR69ubfck/eqiSdykjaSQ4cfnTUAIeHvLUdbq1jM+4c+Tfj3wMyHEjcBpwLvG9hFAaaAEA5BSXiOlHCKljJVSDpVSXi6l3BnIc/QrlftIbimBxnLopdHzo3PHE2+zsOZQFa9sOBxkAc3nlQ2H+eqT62mxu1g0bgBP3TaX1CjNhQk69maoOgiVB6Cpqlc6abEIfn3xZISAVzcejvgBV0rJI5/s497XtuGScNVJuTxy3Qxs2kgKDi11UHVI6WRL77zoCbFWfnbBBAD++dkBCioagymh6didLn76xnb+/vE+QE3Kf3HBRG0kBYvmajVOVh2Ett7pVk5qPHeePhqA3y3dRXVj0FK3Q4KmNgd3PLWel9YfxiLg95dN4eYF+WaLFZlICY0VULEfaorUc7wXTB6a1t7r6+dvbKfNoSvg9RZ/lum/CzwLXALcL6Xcb2y/AlgZGLEiE+s73+HMw2th148gLg2GzoBxS2D8+ZCW2+nf5GUm8t2zxvKH93Zz/9JdnDZ2ADmp5lUtCRZOl+SB93e390m6cNoQ/nJldBZuCCrle2Hjk7D/IyjfffxnCZmQvxBGnQETL4HEzisUTc9L55rZeTy/tpgfvrKFpXedEpEevxa7k3tf3cobm48C8M3TR/GDs3VoU8A5vAG2PAf7PlQPfk/S8mDYPBi9GCZcALGd1xY+f8pgXhxTzBf7KvjhK1t44Y75ERkWWd3Yxjef28jKA5UIAb+5eDI3zPOvcIOmC6SEg8th60tw4BNoOHb855mjYPgCGHM2jD0XYjpvev6VU0bwxqYj7Ctr4Nfv7OSvV08PuuhmcKSmmW8+v4UdR+uIt1l45NqZnDVRF24IKE4H7H0Ptr4IhSuhybM7joCs0eq5Pe48yD8FrJ0/j39w9jg+2H6MPaX1PPLJPu4+W/dE7A296qMkhLgLeExK2SKEGAYcllK6vPaJB5xSSvM7SXkghEgFamtra00vD+568mKcRWuxOb2T6YRS8LlfhxGngtdEzO50ccmjK9hxtI6TR2fz1G1zsETQJKCmqY3vvbiZT/eUA3DXGaP57lljI+o7+ovdbmfp0qUsWbKkb1Viaoph2c9hx+vHb49JAIsV2hqO326Ng4kXw/xvwpDpJxyursXOuX/9nKO1LVw7Zxi/v8z8SjqB5EhNM197ej3bj9QRYxH88sKJYRNrHzCdCTZlu+D9e9Wk1BNbIiDA7rV6H5sMU66EBd+GrBMLFhRXNXHu3z6nsc3Jj84dzzcirKjB7mN1fPWp9RRXNZMUa+XBq6dzzqTAlEQPG50JNkWr4b0fQcnm47fHJoN0gd3r2Z2YBTNugPnfguScEw63qaiay/+5EpeEh66ZzsXThwZP9n7Gbrfz1+fe4/nCeKqb7GQmxfKfm09i5rAMs0WLLHa9Ax/9Eir3H789LhUcreBsPX57ai7Mvh1m3dLpYufSbSXc+exGrBbBi3fM46T8/ivZHkrjTF1dHWlpadCLPkq9NZQcwBApZZkQwgkMllKWBUTaIBNKhlK7kpxzFraaQ2qCsPtdKPJwxA1bAGf9Uq2ierC/rJ4LHv6SFruLuxeP5a4zu6yQHlasK6jiO89v4mhtC3ExFv585TQunKYr5LgJyMCy+Xl49/vGxFOoVdBpV8PwkyEpWxnmbU1QthMOfAq73oJjWzv+fvwFcPpPYODx/by+3FfBDf9dA8ADl0/h6tnD/PyWocWHO47xo1e3tj/8/3H9TOaNzDJbrF4TSg+jTnG5YMVf4dPfg8sOlhiYfDlMvgLyZkOCMdFqqYOjG6HgS9j2MlQXqO3CovY942eQcbw35aX1xdzzylasFsGTt87h5DGBTpvtf6SUPLe2iN+8s5MWu4u8zAT+c9Nsxg1KCdg5Ql5ngo2jDZb9Atb8U723JcL065RnfcgMiEtWnqbmaji8Dg59Dtte6fA2xSTASbfByd89wWD6y4d7ePiT/STYrLzxzYUBvW9m4XC6eOSTfTz08T4kgqm5afzfDbMYEqVtTIJCSy288z3Y/qp6n5AJM2+E8RfC4KkQE6d0sqEMjqyHve8ro6rZCIePS4WFd8Hcbyj99eCu5zfx1paj5KTE8c63T+63KKVQGmeCYSgVoRq5LgUOAScBFZ3tK6Us6my7WYSkoeStJBX7YM2/YNPT4DAqiY09D879HWR2NLJ8aV0x97yqJrAPXzsjrA0Ku9PFP5cf4G8f7cUlIT8rkUeum8nkoWlmixZS9GlgcTnh/R/D2n+p98Pmw5I/waBeeH+ObITV/1QTVIwxYsYNcOZ9kDygfbeHPtrHXz/aS6zVwgtfmxfWq4nNbU5+8+5OnlujhrDJQ1P5vxtmkZuRaLJkvhFKD6MTaGuC174Ku99R78eeB+c9cILBcwJSKoNp5d9ViB4or+e8r8Mp34f4NGM3yfdf3sJrG4+QlmDjzW8uJD+783C9cKC6sY17X9vKBztU+u+pYwfw0NXTyUjqPNzLX0JaZ4JNYyU8fw0cXqvez7gRzvoVJPWwOOJ0KF384i9qogoQmwKLfgRzvtYekud0SW55fC1f7KtgRHYSb9y5kLTE8L3GRZVNfO+lzWworAbgshlD+N1lU3VV2kBSXQjPXQ3lu0BYYeF34OTvQXwPc1h7C+x4DVY+AmWqZQBJA+CMnyu9tqhUhsZWB5f9YyV7Sus5aXgGz311Xr+kOYTSOOOLodTbK/Nb4G/AQdSsaR3KYPJ8FRg/Nb6SPQbO/zN8eyPMvFn9Y+x9Dx6dB8sfUMoPXDU7j6+cPAKA77+8hfUF4ZlIv/1ILRc/soIHlykj6ZLpQ3jnrlO0kRRIHK3wym0dRtLpP4Vb3u2dkQQwdCZc/m/45hqYdKnatukZeGQWrHlMTRJQPUPOmTSQNqeLrz65nn2l9UH4MsHny30VnPvQ5+1G0tdOHclr31gYdkZSSNNSC89cpowkayxc+He49vmejSRQXs8Rp8D1L8Mdn6kQZWcrrHgIHj5Jre5LiRCC3106hel56dQ227ntyXVhWcZeSslbW46y+K+f8cGOUmxWwc/On8ATt8wOuJEU1dQegcfPU0ZSfBpc+yJc/EjPRhKoPJDxS+ArH8ENryrPU1s9fPgz+OcClQcKWC2Ch66ZwZC0eA5VNHLz42tpaHUE+YsFHqdL8tSqApb8/Qs2FFaTHBfDDaOd/OHSSdpICiQlW+E/ZykjKWUw3P6hijLqyUgCsMUrT+jXv4TL/wsZI1TxsLfvgv+drY4NJMXF8H83ziIlPob1hdXc9fwm7E5d3KEremUoSSkfQ5X+noYqD74YmOn1mmH81PhL2lC46O9w52oYcZqaCCz/Hfxzfvug++MlEzhrwkDaHC5u/t9aVh2o7OGgoUNdi53fLd3FxY+uYGdJHemJNv569TT+evV0kiOwGIBpOB3w8i2w8w2w2NSAedo9KhfJVwaMgyufgNs+hEFT1WT3vR/CY4ugeB0Wi+DBq6YzeWgqlY1tXPvvNewvCx9jqby+lbtf3MwN/11DYWUTg1Ljeeb2ufx4yQRdSCSQNFfDUxdD0SpVyObmt2HWzSfkY/aKIdPhprfUpDZrNDSWwau3wzOXQ9Uh4m1WHrtxFkPS4jlY3si1j62mrC58jKWiyiZufWIddz2/iYqGNsbkJPP6nQv5yikjdd5mIKk9DP87Fyr2QOpQuH0ZjDvX9+MIAaPPgq98Ahc/qlbwK/cpfXzxRqg9QmZSLP+7dTbpiTY2F9dw+xPraG4Ln55f24/Uctk/VvCLN3fQ0Kradrz9zfnMHiB1cZtAUl2g9KaxDAZOga98DLkn+X4ciwWmXAHfWgfn/E7l2B1eB4+dBkvvgZZaRmQn8c/rZxFrtfD+jmPc/dIWHNpY6pRezwSklPVSyu3ArcAKKeWWzl7BEzWKGDAWbnoTrvgfJA9SZUmfuRxevgVrYyl/v3Y6J4/OprHNyS2Pr+WjnQGtyh5wHE4Xz64p5PQ/Leexzw/idEkumDqYZd87jUtn5OqBNpBICe/dA3uWQkw83PCKGjD7yrC5cMdyOP9BiE+H0m3w38Xw9ndJctXzzO1zmTg4lYqGVq55bHXId6RvbnPy8Mf7WPSnT3lt0xGEgJvnD2fZ3adGRF5LSOFoVRPGo5tU8vstb5+Qg+kzQqhJ7TdWKm+pNQ4OfAz/mAdfPEhOkpXn75jHkLR4DpQ3ctW/VnGgvKHn45pITVMbv3lnJ2c+uJzle8qJNRo8v3PXydrbHmiaa+CZK6C2SIW33/a+WhTqCxaLCk/+9gaY900VGbLrLXh0Dqx8hPEDEnnqtjkkx8Ww5lAVVz+2KuQN+CM1zXz/pS1c+MiXbDlcS0pcDL+5eBIv3DGf3AydjxRQGis9jKTJcOu7avG8L1htqiDTt9bBpMtUQZK1/4JH5sCO1zl5dBb/vGEmNqvg7S1H+epT66lvCal6bCGBz0umUsonpZStPe+p6RNCqATnb61TyXjCoiqWPTKbxC1P8J+bZnLm+BxaHS6++vR6HvxwD84Q6wDucLp4ZcNhFv/1c376+nYqG9sYOSCJx2+ZzSPXzWRASpzZIkYeX/4V1v8XEHDZv2HkosAd22JV1XS+vQGmXw9I2PA4PDKb9H2v8+ztc5g0JJWKhjaueWw1L6wtCrkmyc1tTp5YcYhFf/6UvyzbS2ObkylD03jtGwv41cWTSdE9uwKLywVvfhMKvlD5Gze9CYOnBe74MXHKW/qNlSocz9ECH/8K/u8Uhjdu44U75jM0PYGCyiYueWRFSC4q1TbZeeijfZz2p+X898tD2J2SU8cOYOl3TuE7Z40hLkaHNQUURyu8eENHaNNNb0F6AAvRxKep/OKvfQ55c1VF0Q9/Co+dxlTXHp68bQ4ZiTa2Hq7l4kdXsKmoOnDnDhCldS3c/+5OTv/zcl7deBgpVcuOj79/GjfOz4/I0vum0tak8uQq96uWCNe/0p53GRBSh8CVj8ONb6jy9g3HVNTJs1dy5qBmHr1uJnExFj7dU87l/1zJoQjvRecrvS3mUAWMlVJWCCGqac/uPhEpZf/VGuwFYVHMoTcc3QzvfFetygIMPQn7kgf59TorT68uBGDOiEx+f9kURg1I7vIw/UFdi53XNhzmfysKKKpS5VQzEm1858wxXD9vuG7W6QM+6cyWF+H1O9Tv5/0R5n4tuMIVfAnv3K1CVwDyT6H5nD9x98dNvLddVYNaPHEg918y2fTeXxUNrby4rpj/fXmISqP549D0BO45dxwXTh0SUSFNoZQwy0e/gi8fVJXtrn9Z9foIFlKq3jcf/ASajFpDs26hYt5PuPPVg6w1cjqvnTOMHy8Zb3oj6+KqJp5ZU8izq4vac1bGD0rhx0smcNrYAT38dWAJKZ0JJlLCa3fAtpdUONKt76kKYsHC5YLNz6iKes2GQTTzJopn3sMtLx7gQHkjVovgzkWj+PYZY0wP991f1sB/vzzIqxuO0GaEYc0dkcm9541nhlehnqjRmWDjdMBLN6ookPh0lZPUV+9md9hb1ILqlw+Cs01VbFz0I7bk3cBXn9lCWX0r8TYL9547npvm5wf02RhKOhOMqnc3Ay9IKVuFELfQvaH0pG/iBpeIMZRAVTFb9x/4+DcqaVRYYf6dvJ1xM/e8dYBmu5NYq4WvnDKCO04dSXpi/yX9SinZfqSO59YW8camIzTbVfx1VlIsXz11JDfMG67zkPyg1zpzcLkKJXHZVU+Pc+7vHwEdbbDqYfjsj2o13xqLXPAd/iUv4c+fFOFwSVLjY/jGotHcsiCfhNj+Wx2XUrLqQCXPrS3igx3HsDvVsJWbkcDXTxvFFbNyIzIJOWQeRuv/p8rbAlz8D5hxff+ct6lK9R3Z+JR6nzQAx+Lf8dvCiTyxSi0qDUyN47tnjeWKWbn9unDjcLr4dE85z64p5LO95bgfv+MHpfDN00ezZMpgU1brQ0Zngs3Hv1ZV6oQVrn9J5Rb1B42V8NEvVEEcgIRMmhbdx08OTuaNLWpRaUR2EvecM45zJw/q13D05jYnS7eV8OK64vbFBIDZ+RncefpoFo0d0Kk8UaMzwURKNUZueFyFD9/8Vt/DkntLxT517oIv1PucSVSe/gDf/tLGSiP3fWpuGveeO54FowMTjh5KOhNwQymciShDyU3dUdUUb9db6n1aHuWn3s89Wwe3N21NirVyw/zhXDt7WNDK40op2XG0jne3lbB0WwmFlR3N+MYOTObGecO5fFYuibHaQPKXXunMse2qclNrnapQd/n/2suA9htVh2DpD2H/MvU+YwRF83/DN9dksO1ILQADUuK4cd5wrpmdFzQPk8PpYl1BNR/sOMYHO45RUtuRAzAtN42b5udz0fQhEe3VDImH0d4P4fmrVUz8oh/Donv7X4bClfD2dzs8nqPOYNPUn3P3srr20JLhWYncsiCfy2bkBq1kc6vDycr9lby3vYRlO0upburIAThlTDY3zc/nzPE5pno1Q0Jngs36x1VUBsBFj6ieNP1N4Sp4927Vsw5g2Hw+G/Njvv9ZGxUNytM9YXAqty7M56JpQ4K2kFPfYuezveV8uKOUT3eXUW94NC0Czhg/kK+dNpLZPTQijQqdCTaf/wk++S0g4KqnYOJF/Xt+KWHLC8oLb/RfkrNu5aW02/j1R0dpNAqOzBmRyS0L8jl74kBi+vDsDCWdCaqh1FXDWSFEFlAmpQypJdqINJTc7Hkflv4AaosBkBMu5PNRP+QPK+rYVdJx3+fkZ7J44kAWjRvAqAHJfj+Q7U4XB8sbWVdQxaqDlaw5WNk+uAPExVg4a+JAbpw3nLkjMnWRhgDQo87UHob/LIb6ozB8IdzwmioRagZSKuP9vR9BfQkArkmX8d6Qu/j9l9Ucrm4GIMYimD8qi3MmDWLBqCxGZCf5rSttDhd7jtWz5lAlaw9VsbagihqPiWhyXAwXTx/CtXOGRU1CvOkPo6Ob4PHzVYPj6derSmBmjQWONlj5EHz2J1VFNCYe+8K7edZyEQ9/frg9DDMuxsKicQM4e+Ig5o/KYnBavN862dzmZMfRWtYcqmLNoSo2FFS1TzgAMpNiuXJWLtfOCd4ilq+YrjPBZu+HKgdEOuG0H6kG2mbhtKsedcv/oP5HLDG0zf4G/xJX8I8Vx9qjMZLjYjhrQg6LJw5i9ogMclL8H9frW+xsKqphfWE16wuqWF9Q3R5aB5CXmcDVJ+Vxxaw8BqX17jwRrzPBZtOz8Oad6vfz/gRz7zBPlqYqWPbzDo9nUg51i37Ng0en8OzaovZojKykWM6eNIizJuRw0vBMnxeXQklngm0ouYBBnRhKQ4ADUsqQKoUS0YYSQFujGnBXPaoeArHJuBZ+j08zruTpDaXHhXcApMTFMGloKuMHpTIkPZ7BaQmkJ9qIt1mJi7Fgd0pa7E4aWh2U1bdSWtvC4eomdh+r52B543GDK0C8zcLp43JYMmUwZ4zPIUmH1wWUbnWmuUaVty3fBdnj4PYPICEEGr621MGnv1PVdaQL4lJxnP4z3ok9j2fWHGZ94fHJy5lJsUzLTSM/O4m8jESGpMeTFBdDYmwMMRaB3emizeGiptlOeX0rZfUtHCxvZF9ZAwUVjTi8ipikJ9pYPGEg504exMLR2REZXtcdpj6MqgtVNcSGUhh5uspLsobAJKrygAozOfSZep+WR8tpP+flljk8u7aY3ceOL2k/MDWOqbnpjMhOIjcjgYGp8STFxpAQayXGImhzumi1u6huaqOsvpWyuhYOlDeyr6yeoqomvB+rOSlxnDt5EOdOHsSc/Mw+rcoGg1CawAScUDLcPak9rBaV3M2XU3NpPPN+nq6ezNOrizhS03zc7vlZiUwYnEp+dhLDMxPJSIolJS6GxLgYXFLidEma25xUNbZR2djG4eomDpQ3cqCs4YRjgQr1O3viQBZPHMjMYRk+L6BGtM4Em30fwXNXqTnbyd+Ds+4zWyJFwZdqnKzYq97nn0L5gp/z5KF0nl9b1L6w5GbswGQmDE5lWGYieRlKJ5PjYkiMteKUEodT0mx3UtnQSkVDK0eqmzhWXMAjXzvXdJ0JiqEkhLjL+PWvwM8Bz1qrVuBUIF9KOcNniYNIxBtKbo5tUwp+eJ16n5oLZ/7i/9u78/ioqvPx459nZrJAVkgg7KuAIAiKCLiAG25fbbWta23dWqt289tv1bb6U1v9Vm37tdZWW7uptbUurXUFEfcFRNkUZEcW2SEhZE9mOb8/njtkMiSQgSQzE57363VfM/fOnZkzk5M757nnnOeyecA5vLp0O68v386Ha8uoDx1cnvycTD9j+hUweUgxk4cWMbZ/gWVlakct1plQvaYSXfeuppD/xqy2zdzUFjYv0jq5eYGul4yG0+7gs4JJzFy6ndeXbeOTTbtpOMg6mZ8dYMKg7hw7WJcxfQtSriHakZLWgKkpg7+crteQKRmtE+Vbc5HEjuIcLPk3zLodKjbqtn4TcGf8nE99I3j10628sWI7y7ZUHnQG0eLcTCYM6s7Ewd2ZOKSIESV5KZ0wpNM2enet0x736u2pFbjHWvGKXpuuXC92zfAziZx2Jwtri5m+eCuz15SyfGvFXsF3ovp378IxA7tzzKBuTBxcxNAeB96TD524zrS32MD9yIvh/D+kRuAeFaqH9x/QYYHhekBg7CUET7qFD3ZmMWPJVj5YU8pnB5gZrzjbMeeWM5JeZ9orUFrr3R0IbARir5bWAKwDbnPOzU20wO0pNlDKyckhEkneBbWCwSAzZszgrLPOap9KEoloQ+CNuxobAr3Hwsm3wtCTCUUcq7ZXsXhTOWt3VrOlvI6tFXVU1oWoD0WoD4YJ+H10yfCTnemnR04WJQWZ9C7owrCeeYzolUffwi6t/sH3+Xz4/RZEHYxmf4wiYfjXlbD0+Y7J3HQwImGd1P/GnXqxWoCBJ8C0n0K/Y6gPhVm6uYIlmyvYWFbD57tq2FZRT3V9iJqGMOGIIzPgI8Mv5Gdn0CMvix55WQwsymFYz1yGleTSK//Ah0l1RklpwDRU6wVlN36kJ2mufvXgrwHSXoK1MPt3mvkp6P3YH3G+zqXqMYKahhBLNlWwZNNuNu6qZeOuGrZX1lPbEKYmGCIcdmRl+Mn0+yjokkGP/Cx65mUxqCiHYSW5DC/Jozg3vS590CkbvVXbNXDftTY1A/dYDTXw7q+0gRoJarKJcZfqMMHC/uyuDbJwwy7W7KhmfWk1G8pq2F0bpLIuRG1DGJ8PAj4fWQEf3XMy6Z6TSa/8bA7rmcvQnrkMKc6hqI3rZKesM+1t52p45Eyo3qGX7rj0GQh0XNKthJRv0OQni5/R9UAXmHy9Jovq2p3SqnoWbCjnsx1VrC+r4fOyGirqQlTVBaltCOP3Cxk+H1kZfopzMynKyaQ4N5OqzWu488p2agMnoL2H3r0JfMk5l3rJ/5sRDZTKysqoq96NCzfs9zntJRgK8vbbbzN16lQyAu1YSUJ1sOgJnbza4DUE+oyFY6+B/pM67OyF+DPp2bu/BUsHYa8fI+fgxe9pRi9fhmZuas+Uy22lpkwbpnMf9s5SAYefAyf+D/Q9Orll62Q6vAETDsGTl8KqmR2T3ratVGzRk0qL/oEmchUYc4E2TosPS3bpOlSna/TW7YZH/0tHWhQOgKtehfzeyS7V/u1YAa/doamiAfyZcMzVOjwrrySpRYvX6epMeyv/XIfKV2yEXkfCFS+nbuAea+N8vQ7Yhjm6npkHk67VC9kmONQ/lepMIoFSwhNKnHMnH2jBkikSieDCDXTL9RMIJGceTTDkoygvgx6FWe0bKJEFp10Hx12o6cQ/eQoqP4bXvw29j9Lr6ww6Xi9i205CoRC7qhqIRCIWKLUV5xrTHosPvvKX9AiSALp2h9Pv1Lr35t3w8RM6Nn/5SzD0VJjyQxh4XLJLaRIVDum1u1bNhEA2XPp0egRJoA3n8x6ESdfBW3drXVz8NCz5F4y5EI77LvQanexSmkQ1VMM/L9UgKaeHXmQzHYIk0P+dS/4Jn3+oZ/PXvQtzf6+98uMu1TpZNDTZpTSJqtoOj5+nQVLxcPjaf9IjSALoN157Y5e/rMfJbUt0WN7ch/X3/NhvQW7HXvetoyUcMYjIv4B5zrl74rbfCBzrnLugrQrXHgKBQPIiWWl8//YNlDwFveC0W2HyNfDhnzQN5PZF8OJ1enXmYy6HkV/QLtV2Ed7/LqZ1nNOLFs5+QNfPfQBGfTG5ZToQBf20cXr89+Dd+7Rbf83rugyYDBOvhcP/K/XmEZi9RYOkJf/W3s0LHoMBE5NdqsT1Gg0X/0Pn1L11D6ycAZ88qcuQk+G472gwb8M7U199JfzjQtgwW898X/bv9Aws+h8Ll7+o18d78391SOv8R2DBYzDqPA2YrCc+PVRsgcfPh9LVUDBAA/ectrkuUYcRgZHnwIiz9YTSW/fA9k81YHr/ATjyQu1h6jky2SVtFwfSpTAVeLmZ7a+gCR1MqsnpCSffAt94DY65Uue1lK2BV2+DP56sV2iOTiQ1qcdF8L1yY2OQdOa9ybkGSFvqMQK+9DB8dz6Mv1KHmGyYA89cDvcfqQfgqh3JLqVpSUO1Xk0+GiRd+DcYcWayS3Vw+oyDS5+Eb76pc5bEB5+9qUlTHpoMc/8ItWkx4vzQVF2qDdINsyErX4Ok3mOTXaoDJwJDT4arZ8EV02HY6ZpF9NNn4U8n62/3wr/r/CaTmsrW6pykHcs06dLXn0vduZut4fPptZ6ufU+P+X2P0aH0Cx+HhybB41+CZS9qCvxO5EACpVw0eUO8IJAmfYmdwIGkwMktgak/gmve0gtA5vfVH/65D2tK32cu17MFobr9vpTpIPWVTPzsfvwLHgVEe5ImXZvsUrWd7oPh3Pvh+5/AlBt1qEzlZp07ct9IeOoyWD690x1401rVdnj0HJ1H4c+Cix6Hw89OdqnaTt+j4YJH4XsLYeJ1kJGjDZ0ZN8L/HQ7PfksvZtvJL9aeVnashD+fqj0v2YXw9efTs3ezOSI6VP6rz8C178ORF+mJpc0L4Plvw32Ha5rxTQusTqaSDR94yUTWQbdBevmOdOzdbI7PpyNavvm6zv8b+QU9sbTmdf3Nvm+UjoDZuTrZJW0TB5LM4SPgRefcz+K23wGc65wb33bFO3jRZA47d+6kvqpU5wfFD7179ytQOifuiRmQ3QN6TYORN0FmYeve8KNrYdtbMOUFyB/e5KFgKMgbr7/BKaeeokPv1j8FC38A0z6AnP6te/1wPSy9GwqPhP5fat1zWhIJwerXdFz+utnohGZ07OzQaXqGeOBkPWOcoGAwyI7yenr0GZz0SXtpa+cq3FOXITuW4wLZyHm/h9EH+TdPdaF6+PQ5vQbTpvmN27sW6UT7I74E/Sbogdo0q10nzK6fDf+6Si8o3KUbXPIkDJjUtu+RamrLdZ7n/Md0uElUwQD9fxz9Zeg1Jq2H5qXSJOuELXtJL9xZt1sTN1z6dKcdArRH9U49iz/vEShf37i9aJgGUmO+oieh2lFa15n25JwOk5x+k2YwLBmtvZt5vZJdsvZVthbmP6qJxKpjLrPad7z+bh9xPsGuPVOmzrR31rsvAP8GngDe8DafClwCXOCcey7RArenVgdKoUoY+/PGbZEglH8CS++FwiPgxOf3/0NYsRLePB0mPQIle+e8aJNAqfpzmDUJjroPBl7Uuue0RsUmWPKsDqWp3NK4PbsQhp0GQ07RBlFm664kb4HSQXAO5v0FZt4KoVpqM7qRcdlTBAZ2kjOkrbV1CXz8T/jk6aYH3twSHSs98hwYNCV106smSbs0YEINmrXw7Xv1IolFw3TSefGwtnn9dOCcnrVf8KgeKxtiLiVYdBiMPBeGnaGBvD+9Lrydlo3ehmp49VZNdADQfyJc/ET6zf84GJGInsVf9IT28MaOBikZAyPO0t7e3uPaPJBPyzrT3qp2wIvfhxXe7JRRX4QvPgRZucktV0cKB2HlTE06tXqWDhf1RPpNZAnDGHnZL8jIbl1bsr20d9a7F0TkPOAnwFeAWuAT4DTn3NuJFzdFBPKge1xnWPEkCFXD8l/BrgV7Px4vuydMew+69mu/craX/L46QXTyt/VM/orpWtlrSmHxv3TxZ2gjYPBUGDwFug1O67OoKWnrYh1Gsf59ACKDp/J2zpc5tc8hOHG312jo9b9w2k9hzRva87lyJlRt0zN28x+BrAIYMkUn3Q85CboPsTrZ1tbP0QsH71im62MuhHN+fWj9+IPWq37jdTnrF7DqVT2xtHKmTtR+79e6ZBfCYafpnJIhJ6VcWue055wOEX/lx7D7c9123PfglP936J008flg2DRd6ir0e/nkKVj7DmxbrMs7v4C8PjD8DK2Pg06EnKJkl7xziYQ1MHjjTm0z+TLglFvh+O8fer9H/gw9iTnyHKjcptd7/PRZ2DAH38a5HJaxGny/TnYpE3JAp72ccy/TfEKHzqebNxm0ZiN8ejd06Q2ROtj+DhQdC5Mfh3AdLPsVbHoO6kshdygM/y70i8lK5iL4Vv2WKXWPEJheAz2nQnEzPQSbX4E1D8PuT7VXq2t/GHKlLtHeJNCeqOX3wRne9X13zoVlv4DyReDLhl6nwejbIMs7ILbUezVzIhRPhvH36/rz/eHw/wH/XOhfBj3Ogco82P4sZJSB/1X4bBZ8EoD6vho49Zug3avFw9s15XinVrpGs8B9/ISegQl0gVNvIzz+aupnvJLs0iWXPwDDT9cl1KCNgOUv6tyl6u06eXTZi7pvwQAYMlV7P/sdq2f6bZjegdm6ROeKrZyh612L4cx7dFjPofbjHy+ji54tHvVFzbS24hVY+YoOZa4r1xTjS/6l+xYN09T3g06Agcen92TuZFv7rqYo9k4kUTAAvvCb9LlMQnvKztcU4uMu1cQWq17Vno3Vb+i8z+jJJdDepsEnap3sNwFyeya37OkqEtHv+K17NSgF6HmEJirqNSa5ZUsFeSUw8Rpddm8ivORZVi1bxag0+/04oEBJRArR3qQhwK+cc2UicjSwzTm3qQ3Ll3yVa/Q2Z5DebnoB+p4DE/+iQ1Ccg7nfgLKPNMDIGw5bZsC86yHSAAO8bOmf3oVvzV/Y5D+bQUd/mcC2VzTwirX1Nfjwahhytb5WuBY+exQ+uRUKRuu8pGP/DB9+A4Z/H/p4E6h3fgDvXww9ToAJf4CGclj2S3jvAjjpZfAnmP57xW90Xlb+4dClD2x7DepDMOhmKN8BW9+BwlWwaxOs2AkrvIZUVj6UjIKeo6D74ZB9GPQaeABf+iEiEoY1b2rK1+UvNXZRjzoPTr8LCvtD0JIYNBHI1KGgw06D/7oPNi/UzGRr3oLP58LuDTp2f+Hjun92YWMw32uM9lIV9LeGfktCDdrY//BhTU0MevLjqK/BaXfo9bBMU1l5cOQFuoRDsGme9jKtnqXBZukqXRY8pvvn9YY+R+lwqD5HabY9a6i2rKFae+7mPaIJDECTGRz3XTjxh5DZNbnlS0U5RTDuEl2CdXo9plWz9Hb70sbepg8e0v0L+msSk77jdek1BrILkvsZUllNmV7aYt5fYcdy3ZZVACf/GCZ8wy5v0ZyCvkSOvZZ1O6czKtllSdCBXEfpSOA1YDcwCPgzUAacDwwEvt6G5etATpMbRAXLYeccWPkb6Ha0BikA4odxv4SAd3De/g5sfxOOeaixB6nkJAjVaNKFfufr8L01fyUy+CrWbJnEwJ5Toc9pULtVnxtVuQr6fwWOjMmT0f0YmD4aSj+AogkaMAHkDIRC7/7SuyFvKEx+TMsH0P1oeP1k7UkackViX0W3o2D4txvXP71LP/8R323ctuqPUFMOtbnaMNi0EOorNNPLhg8g7KAS6FYIfUZrb1OPEXpbPFwPzIfimf5wUCfEr5ypXdIVGxsfG3Y6TLkJ+k9IXvnSic8P/Y7RZcqN2qBaPwfWvg0b52mjqq5cG6yrZzU+L6sASo7QoKnH4ZqJqPtQHX56KNbJhhpNqbz0BVj2QmMKbPFp0H7yTw6tuUgHwx/Q3swBk+C02/W73PABrHtPe0G2fKxzQFds0eHNUXl99PjY43DoMVxvi0ccukOk6io0YF8xQ3vq6r0pBP5MOPrrcMIPrGeutTKyG4fngWatXPeu9sxvmKsN/d2f67L0+cbn5feDnodrYoweI/V+96HQpTApHyPpqnbo70i0Toa95M9Z+XDsNTDp+kP3/7WTO5AepfuAR51zN4lIZcz2GWiCh/RU+gG8EN/74dNemqN+2XgGumv/xiAJYMd7gOhQt9hAq/fpsPFZqFgO9TvABXG9psGWmK+s77lNA6Vh1+ltqAaq10LVZ7DrY90WaaFnIVQLZQv0uc6B88rQdSDkDdNALtFAKf/wpuvFx8HSn8O750PvM6HkVBh2TdN9IkHYuRK2LYVtn8LmxVCzwgue5ugSK9AFug3ULEXxS35fHeaTZhOi9+KcZifa8jFs/FCvtr5xHjTE1IHsQhh7sf74lxyRtKJ2Cpk5jb1NoEHp1sWaMnjTfK2XO5ZD/W4NDDbMbvr8QLbOu+s+RDNGFfSD/D5aH/P7aBIJn7/jP1dbck4bRJsXab38fK4u0R990M955IX64184IGlF7RS6dNMJ9SPO0vX6Kq2TWxZpb+jmhbBzlQ6NqtysvaOxsgv1b9BtIBRGlwHa25zbS18/3YP7SFgzt235WBvun8+FrZ80/T3tNhjGXwHjvgq5PZJW1E4ht6dmahz9ZV2vr9Tjwab53rJAT+BFl9WvNX1+diF0G4S/cCAjy8LIwlLoPkB7SvN6a51M9x77cAjKPtOTwBvn6W/I1sXsyQwMeo2ucZfB2Ius962TO5CW6ATgW81s3wSkb/7DgjEw7l69LwK+LOjSFzLiJixnxR2kG3YBDl5qmgp8j7ptENSzYS6zO9rN4smOG25RXwaLboYtr2gZcgbrPCho+foIwXIgAqse1CWeL7v55+1L/Gccdh0EcmD9k7DkTljyMw2mxtwBPU703idDx+b2PELTOAeDUFoFGfWwaw3sXKGB1I6VOvE5VKuN1mi39V5Esxfl9NQDe26J3nYt0oNSl0K9zfZuu3TTMzsdFVw5B8FaTUlbtU3PEldugcqtsHuTDrXZsUJ7NOJ1LdaJtcPP1F6kjAP4G5n982d4w0liEmGEGrQubvtUf/h2rtKLL+9apxmjdixrTFoQT/xaD/N769+wa5EORevaXe93id5200QHmbkavAWyOuTj4pz2qlVspVv1GmTVTKjdCbvWw661+hnLPtM6Gy+/Hxx2qjaeBp2Q/gFhqsrK1UsuDJzcuK2+Uk8w7Vyhx4wdK/R++QY9fmwt18ChOb6AHiPzShqPkTk9veNjYdPjZHRbVl7HNWSdg2CNnjCq3ApVW/W2covWxZ2rdH5muH7v5xYdptktR5ytGe3SPSBMVVl5Ol9p8ImN22rL9bd5+1LY7t3uWKFzQuvKYcsifFsWMRxg+ktNX8+fqUF8Xi+tlzk99JjY0pKZAxldO+6Y45z+z1Xv8OrkNu1l2/251snS1ZrqurmT073HambLUV+wOUiHkANpVdbR/IVlRwA7Dq44zROR64Ebgd7Ap8ANzrl32/RNArmNiRsSkZGvQcTxzzT/eM4gTbAASP3Opo81xF3lfd63oWoVHP+kDrnzZ2lAsX4fHXWBPEBg6Deh33l7Px6dn7TnhzHc9PFwdcuvHSU+7ZUacgXU74Str8PKB2DuNXD2x+BrIdOQPwN6DYf+cRnbwiE9g1i+XhsD8UvVNp2vU71Dl9hrl+yPP0sDj0AXnXCd0UV7CqL3/VleIOzXzyU+bQBH77uIHiDDDdojEfbuR0LaCK2v0GEh9RVNz3i2/OVp70S/Y3WIWP9j9boK1hBNjkCmN1dpjPbkRYVD3g/lGij9TIOKik1QsVkbdRWbdU5i9Mx/InwZ2hjIyvMCp2xtTPgzdPFleOsBvfUFvN7hSPNLOKiNz4Zq77YGgtW6HqojA5gCsLKl8gR0OE10joxlC0yurDy9OGr8BVIbqvV4uCt6nFyv9bJ8A+zeCLVlegw6kDoZ6KLHyYyuEMgmEOjCidV1+Hf9yWu0BuKOk/7G+4h3jAzq+4eDjevhBm2E1lfqMbK+skl64Bb5s3ToYf+J3nKs9qKZ5OhS2DiENFZ91Z56GN65hvWL3mZQAfiqvOC3plTrwO4NuiRiz+90js47i97PyPbqX0DrYJNb71gZCenxORLSHsqIdz9Up3WwoVrT+UdvW1MnA100MOp3jM5xHTCp818LyTTrQAKl54HbRORCb92JyADgHvT6Sm1KRC4C7geuB95He7NmiMgo51yC/4ntoHgSrP4D4KDbuMbt65+CzdPh6F97QU82smU6MLVxn62zmr5W2Ycw6DLocXzjtm3RS1V5/9jxWeUycqFwDFStbhrohWvhw29BySl64dtAnm6v2dyYmKJy9d7BWnPe+QIUjtO5U1nFev2mUCUsvh2CVZCV4ARvf0DnhbR0lepIWA+4Vdsbz/ZUbdOldpee7arb7S3e/eg1TcL13tnJZs6atwvRs7jRYQf53m3RUJ2L1X2oTTZOB/6ABrTdB8NhzTweCWvQXrEJKrZoI7WmVCf11nj3o9tqd+0JWvS5Qa+elnfIR3GBbGolh+zi/vhye+pwrW6DGpfiYR3Xy2UOXGaOBrQtXTw11KB1Mnps3HOs3N54bKwtb3obHWIZqtXFm48mQHeA6tXt81n8WV6vV7SnoZcOISweofWxcICdPEoHWbk6RLzkCCLBIItLB9L/7LPxRa+jFKr3RljEjLKoKfN+t5tZ6sobg5ZQnS61rWiTtIXMvKajVaK/20WH6XKozlk1ezmQQOmHwHRgO9AFeBsdcjcHuKXtirbHD4C/OOf+7K3fICJnANcBP26H90tMyalQNAnmXgUjvg+5w7QHadn/aQrwaBAx4gZ8S3/BsMB2ZEcAdry9d6BUeBR8/h9NnJDdG8rmwcrfAqLzlkB7sEDnRuUN06QNo34Ec74G876jySNcGFY/DLsWaplAgy9/F1jyUxh1M4SqNL14RuH+P2PRZA0Gs4o16Kvbqq9fNDnxIKk1fH7vANYTGN2654SD2tMTrNYsP6FaHRoXrNWDb7BGt4frvTPzzZyxj4Q1EG1ydj+j8cx/Rlcd3pedr7dZeTq8yg6mnZ/P39jAa+0c8nAo5ixmtc5Nq6/SxsSeXsuQd+v1WkZv9/R2xi6it76A1sXokJU9t12hazEhyWTWjBmcHduAMZ1PIFMTGrQ2qYFzjWfY9xwb9TZUV8X8D95j/NhRBCINjcfD2GOjizRmet3TExpoPEb6vGNmVl7McTJPl4yu1mN5KAhkNc41bo1onYz2igdr43rKa/TxaA+Ri+ktioS94XHStJcpeoz0+bWXKjM3Zii0dz8r305gmlY7kAvOVgAniMgpwNGAD1jgnHtt389MnIhkAuPR3qpYrwLHtfCcLCD2dGke6FWkg6EgwZBPT5/F8HtnNMKhfadibnG/CX/Ft+L/8K34LTSUQnYJkSFXERn2PYjuO+RaXCSTXit+j/+j14l0G48bdQv+xbcSDAd1v7G/xL/kduRjjTddzhAiY36Ob9N/YOdcfV/JxjfkG/jWPwHbXiM0bR50Pw6Z+Dd8K3+DfHgN+DJwBWOITPo7Lv9IfW3pgoz/Pf7l98Lcq6FLP8LDv49v47/BRfZ8pgwgHAkTif2Mw27Ahx/f+idhxa8hkI8rOY3wyJsbP18c/a6DBDsyvXVmvi4dKRzWpZ1Ev78O/R5N2wnk6NKBv8lWZ0zLApDVTZcYwWCQrctraRg+DdcewXWoNcOUTTppu+NMIDm/3XZ87HCp9NuUSBnEtZQkIHYnkTJguHNup4j8Ffi+c65yf887WCLSB00ScbxzbnbM9p8AlzvnRjTznDuA2+O3/+1vf8MFKynKyyAQSPNsamkgFApRWhkkp6DEvm9jjDHGGJMSampquPTSSwEKvA6gFrW2BZuJJnDYCVwO3EyT9G3tLj6ak2a2Rd2NpjCPygM2Tps2jfrqUnoUZpGRpOEooWCId955hylTphDI6NzBQzAYZEd5PT16D07a990ZBINBZs2axbRp0+x7NK1idcYkyuqMSZTVGZOoVKozFRX7jI2aaG1rfQ7wnIjMR4OUB0SktrkdnXNXtfrd928nmqYtPtVIT2BbC+9fD+zJNSreuOiMjAwigQwyvCWZAhmBpJeh3TnICETIyMhI+j9EZ2Dfo0mU1RmTKKszJlFWZ0yiUqHOJPL+rZ2FfhmawCF6UaECoFsLS5txzjUA84FpcQ9NA2bv/QxjjDHGGGOMOXit6lFyzm0DfgQgImuBrznnStuzYDHuAx4XkXloz9Y1wADgDx30/sYYY4wxxphDTKsCpdhkDsCbQEO7liqGc+4pESkCbkMvOLsEONs5t76jymCMMcYYY4w5tLR26F00mQNoMofs9ilO85xzDznnBjnnspxz451z73Tk+xtjjDHGGGMOLamezKHNVFRU0FBTSXagIWmTyILBILW1tVRWViZ9Ilt7CwaDVFbVk1VR0ek/a3sKBoPU1NRQYd+jaSWrMyZRVmdMoqzOmESlUp1pj6x3lwH/DQxF03IX0MG9SgchD2DIkCF0zYL8dCl1J1BRBzX1+9/PGGOMMcaYDpYH7DNqatUFZ5s8QZM5HNOByRwOimh+8D5A9WEl9C0pIDNZZamuJ2flVt4d3osTc7KoTlY5Osq23TSs3sYmIJLssqSxPGAj0I+OvXaZSV9WZ0yirM6YRFmdMYlKtTqTB2x2+wmEEg6U0pmI+Gn9vKz2kAeUAkWkRiVpbxHnXDjZhUhnIpIP7KYVV482BqzOmMRZnTGJsjpjEpWudaa1Q+8QkenAJc653d76LcCDzrlyb70IeNc5N6o9CtoWvEZ70hruIhLy7oacc8FklcMYY4wxxhizb4n0rpwBZMWs3wx0j1kPACPaolDGGGOMMcYYk0yJBEqyn3Wzf/XAT71bY1rD6oxJlNUZkyirMyZRVmdMotKyzrR6jpKIRIBezrnt3nolMNY595m3XoJOivK3V2GNMcYYY4wxpiMk0qPkvCV+mzHGGGOMMcZ0Kq1O5oAOtXtURKJdZtnAH0QkmuY6q/mnGWOMMcYYY0x6SWTo3SOt2c85d+VBlcgYY4wxxhhjkuyQuo6SMcYYY4wxxrRGMi++esgRketFZK2I1InIfBE5MdllMqlJRH4sIh+JSKWIbBeR50TE0u+bVvHqjxOR+5NdFpPaRKSviPxdREpFpEZEFonI+GSXy6QeEQmIyF1eO6ZWRD4TkdtExNqSBgARmSIiL4rIZu836Ly4x0VE7vAerxWRt0TkiCQVt1WscncQEbkIuB/4X+Ao4F1ghogMSGa5TMqaCjwITAKmofMJXxWRnKSWyqQ8EZkAXAN8kuyymNQmIt2A94EgcBYwCvgfoDyJxTKp62bgWuA7wEjgJuBG4LvJLJRJKTnAx2gdac5NwA+8xycAW4FZIpLXMcVLnA296yAiMhdY4Jy7LmbbMuA559yPk1cykw5EpAewHZjqnHsn2eUxqUlEcoEFwPXArcAi59wNSS2USVkicg9wvHPORjeY/RKRl4BtzrmrY7b9G6hxzn0teSUzqUhEHHC+c+45b12AzcD9zrl7vW1ZwDbgZufcw8kq675Yj1IHEJFMYDzwatxDrwLHdXyJTBoq8G7LkloKk+oeBF52zr2W7IKYtPAFYJ6IPOMN8V0oIt9MdqFMynoPOFVEhgOIyFjgBGB6Uktl0sVgoBcxbWHnXD3wNincFk4kPbg5cMWAH42aY21DK40xLfLOwtwHvOecW5Ls8pjUJCIXoydkjkl2WUzaGAJchx5ffg4cCzwgIvXOub8ltWQmFd2LnrRbLiJhtF1zi3Pun8ktlkkT0fZuc23hgR1cllazQKljxY9zlGa2GRPvd8CR6Jk7Y/YiIv2B3wCnO+fqkl0ekzZ8wDzn3E+89YXexOrrAAuUTLyLgMuAS4FPgXHA/SKy2Tn3WDILZtJKWrWFLVDqGDuBMHv3HvVk78jamD1E5Lfo8JgpzrmNyS6PSVnj0ePJfO2ABPRs7xQR+Q6Q5ZwLJ6twJmVtAZbGbVsGfDkJZTGp75fAPc65J731xSIyEPgxYIGS2Z+t3m0v9NgTldJtYZuj1AGccw3AfDR7WaxpwOyOL5FJdV4Kzd8BXwJOcc6tTXaZTEp7HRiDnuGNLvOAfwDjLEgyLXgfiL/swHBgfRLKYlJfVyASty2MtSVN66xFg6U9bWFvDv9UUrgtbD1KHec+4HERmQfMQdP3DgD+kNRSmVT1IDq84YtApYhEeyN3O+dqk1csk4qcc5VAk/lrIlINlNq8NrMPvwZmi8hPgKfROUrXeIsx8V4EbhGRDejQu6PQVM9/TWqpTMrwMq8eFrNpsIiMA8qccxu8a/v9RERWAauAnwA1wBMdXdbWsvTgHUhErkdzyPdGGzX/bameTXO8tJrNudI592hHlsWkJxF5C0sPbvZDRM4B7gaGoWd873PO/Sm5pTKpyLvWzZ3A+ehwqc3AP4GfeSNnzCFORE4C3mzmocecc1d4yaluB74FdAPmAt9O5RN6FigZY4wxxhhjTBwbV2qMMcYYY4wxcSxQMsYYY4wxxpg4FigZY4wxxhhjTBwLlIwxxhhjjDEmjgVKxhhjjDHGGBPHAiVjjDHGGGOMiWOBkjHGGGOMMcbEsUDJGGNMpyYiJ4mIE5HC/ey3TkRuSOB1B3mvO+4gixj/uleISHlbvqYxxpjEWaBkjDEdyGtY72t5NNll7Oz2EYhMAP7YwcVpF95nbK5+ZSe7bMYYky4CyS6AMcYcYnrH3L8I+BkwImZbbccWx0Q553YkuwxtrIKmdQvnXF2SymKMMWnHepSMMaYDOee2Rhdgt25qsm2KiMwXkToR+UxEbheRPSe1vF6Bb4nISyJSIyLLRGSyiBwmIm+JSLWIzBGRoTHPuUNEFnnP+9x73jOxQ9G84Wkfes8vF5H3RWRgS59DRPqKyFMisktESkXkeREZFPP4oyLynIj8UES2ePs8KCIZ+3jNaDmvEpENIlIlIr8XEb+I3CQiW0Vku4jcEvOcvYa/iUiht+2kZt7jJOARoCCml+UO77EmQ++8x64TkRkiUisia0XkgpbK7z1nlIhM98q+TUQeF5Hi/TznCu/z1ojIf4CiZvY5d1/1ogVN6pZXv/ZVjiIR+aeIbPTKslhELonb5y0ReUBEfiEiZd7f5I64fe7wPk+9iGwWkQf2U05jjElJFigZY0yKEJEzgL8DDwCjgG8BVwC3xO36/4C/AeOA5cATwMPA3cAx3j6/i3vOYcCFwLnAmd5zH/TeNwA8B7wNHAlMRoeguRbK2RV4E6gCpgAnePdfEZHMmF1PBoZ6t5d7n+WKfX4Juv9ZXhkvAa4CXgb6AVOBm4G7RGTSfl6nJbOBG9Delt7e8qt97H8n8G9gLPq3+aeIjGxuRxHpjX6Hi9C/w5lACfB0Sy8uIhOBvwIPoX+TN4Fb4/Zpbb2Ilysi673A5yUROWo/+2cD84FzgNFoHXjcK2Osy4FqYCJwE3CbiEzzyvoV4L+9Mg4DzgMW7+d9jTEmNTnnbLHFFltsScKCNnbLY9bfAX4ct89lwOaYdQfcGbM+ydt2Vcy2i4HamPU7gBDQL2bbmUAY6AV0915jaivLfRUaoEnMtkygBjjdW38UWAf4Y/Z5GnhyH697B9oAz4vZ9gqwFvDFbFsO/Mi7P8gr+7iYxwu9bSd56yd564XNfe8xz1sH3BD3Xf8+bp8PgIeae290GOXMuP37efsMb+EzPwHMiNv2ZKL1opnXneTtMxY4EfiX9/cZlmAdfRn4Vcz6W8C7cft8CNzj3f8BsALISPb/ly222GLLwS42R8kYY1LHeGBC7NAywA9ki0hX51yNt+2TmMe3ebeL47Zli0i+c67C27bBObcxZp856KiCEc65t0WTSMwUkVnAa8DTzrkt+yjnYUCliMRuz0Z7hKI+dc6FY9a3AGNaeM2odc65yrjPEnbOReK29dzP67SVOc2sj2th3/HAySJS1cxjQ4GVzWwfCfynmfc4M+51W1Mv9nDOfYAGdQCIyPvAAuC7wPeaK7yI+IEfoXPn+gJZ3lIdt+sncetbaPx7PIP22H0mIq8A04EXnXOh5t7TGGNSmQVKxhiTOnzA7cCzzTwWOwk/GHPf7WPbvoZXu9hb59yV3lySM9GG8l0iMs1rcDdXzvnAV5t5LDYhQjDuMbefMrX0nH29TjSAio3YWpwH1UaaHZKIlulFdHhgvJaCTmlhe/zrtqZetMg5FxGRj9DhcC35H3TY3A1o4F0N3I/2FsZq8e/hnPtcREYA04DT0CGFN4rIVOdc/POMMSalWaBkjDGpYwHaw7O6HV57gIj0cc5t9tYno0HGnl4O59xCYCFwt4jMAS4lplcirpwXAdtjeqySJRqY9UbLDi33+EQ1oD0yrTEJnQ8Wu76whX0XAF9Ge8Va24Oy1HvN+PeMf92DqheiXX/j2Pd8oROB551zf/ee40MDq2WJvJdzrhZ4AXhBRB5Eh0qOQT+HMcakDQuUjDEmdfwMeElEPkeHMEXQ5ApjnHO37vOZ+1cHPCYiPwTy0cQATzvntorIYOAatHG7GU0pPZymAUKsfwA3As+LyG3ARmAA8CXgl3FD/NqVc65WRD4AfiQi64Bi4K79PG0dmujgVOBjoKa54WueC0RkHvAe2oN2LHB1C/s+CHwTTfjwS2AnOkTxYuCbccMQox4AZovITWhCjdNpOuwODqBeiMjtaJC7Cv17fw8NlL7dQtkBVgNfFpHjgF3ofKNeJBAoicgVaBA6F50T9TU05f361r6GMcakCst6Z4wxKcI5NxPNODYN+Aht6P6AtmlkrkaHbk0HXgWWANd7j9UAh6PZ3Vai2c5+h2bSa66cNWi2uw3eay5DM7d1QbPJdbSr0OF284DfEJc1Lp5zbjbwB+AptEfqpn3sfjsa6HyCZnv7qnNuaQuvuxk4Hg0UZqLf8W/QNPCRFp7zAfANdO7QIjRQuitunwOpF4Xo33EZ+vfuC0xxzn24j+fcifb6zESTNmxFg7dElKPB4vvod3YqcK5zrjTB1zHGmKQT51oaam2MMaYz8K5zc55zblySi5JWRMQB5zvnnkt2WYwxxnQ861EyxhhjjDHGmDgWKBljjDHGGGNMHBt6Z4wxxhhjjDFxrEfJGGOMMcYYY+JYoGSMMcYYY4wxcSxQMsYYY4wxxpg4FigZY4wxxhhjTBwLlIwxxhhjjDEmjgVKxhhjjDHGGBPHAiVjjDHGGGOMiWOBkjHGGGOMMcbEsUDJGGOMMcYYY+L8f3yXvpFah/HBAAAAAElFTkSuQmCC\n",
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