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pyRBM/context33.ipynb
T
jensandClaude Sonnet 4.6 5506fef0fa [context33] - fix row order; sequence now reads 1 5 6 9 … R U X
The training.dat file stores samples LIFO (last added in the C++ GUI = row 0).
Reversing the rows restores chronological order, matching the C++ sequence.

Next-step prediction remains 100%: model predicts x_{t+1} from h_t correctly
in the C++ insertion order 1 5 6 9 B F I L Q R U X.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-31 15:22:43 +02:00

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{
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{
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"id": "c33-0001",
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"outputs": [],
"source": [
"# context33.prj → pyRBM\n",
"#\n",
"# Training data : /home/jens/work/repos/Rbm/context33.training.dat\n",
"# Armadillo matrix 12 × 168 — full visible vectors [sensory(40) | context(128)]\n",
"# saved from the C++ GUI; sensory columns carry one-hot character encoding.\n",
"#\n",
"# Architecture : shared-weights StackRnn (1 entity, reused every time step)\n",
"# visible = [context(128) | x_t(40)] = 168 hidden = 128\n",
"#\n",
"# All hyperparameters taken verbatim from context33.prj.\n",
"\n",
"import numpy as np_cpu\n",
"import matplotlib.pyplot as plt\n",
"from rbm.stack_rnn import StackRnn\n",
"from rbm.matrix import np, convert, read_armadillo\n",
"from rbm.entity import EntityParams, TrainingParams\n",
"from rbm.status import CheckpointStatus"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "c33-0002",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-31T13:08:35.961330083Z",
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"outputs": [],
"source": [
"# ── Config from context33.prj ──────────────────────────────────────────────\n",
"SENSORY_SIZE = 40 # numVisibleX * numVisibleY = 1 * 40\n",
"CONTEXT_SIZE = 128 # numContext = numHidden\n",
"LEARNING_RATE = 0.05 # learningRate\n",
"MOMENTUM = 0.5 # momentum\n",
"NUM_EPOCHS = 1000 # numEpochs\n",
"MINI_BATCH = 100 # miniBatchSize\n",
"NUM_GIBBS = 3 # numGibbs\n",
"RAO_BLACKWELL = True # doRaoBlackwell\n",
"L2_LAMBDA = 0.0 # weightDecay\n",
"PRJ_NAME = \"context33\"\n",
"WORK_DIR = \"results\"\n",
"DATA_PATH = \"/home/jens/work/repos/Rbm/context33.training.dat\"\n",
"\n",
"# Vocabulary matching numVisibleY=40\n",
"ALLOWED = set(' .!?ABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789')\n",
"chars = sorted(ALLOWED)\n",
"idx_to_char = {i: c for i, c in enumerate(chars)}\n",
"char_to_idx = {c: i for i, c in enumerate(chars)}"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "c33-0003",
"metadata": {
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"start_time": "2026-05-31T13:08:35.962722614Z"
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"execution": {
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},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"shape: [12, 168]\n",
"Training data : /home/jens/work/repos/Rbm/context33.training.dat\n",
"Shape : (12, 168) (rows=samples, cols=visible)\n",
"Sensory columns : 0 39 (40 dims, one-hot)\n",
"Context columns : 40 167 (128 dims, from C++ model)\n",
"Decoded chars : '1569BFILQRUX' (12 samples, chronological C++ order)\n"
]
}
],
"source": [
"# ── Load training data from context33.training.dat ─────────────────────────\n",
"# Armadillo format: 12 rows × 168 cols = [sensory(40) | context(128)]\n",
"# Rows are stored LIFO (last added in the C++ GUI = row 0).\n",
"# Reversing restores chronological order so the sequence reads 1 5 6 9 … R U X.\n",
"raw_data = read_armadillo(DATA_PATH)\n",
"raw_np = convert(raw_data)[::-1] # reverse → chronological order\n",
"\n",
"sensory_np = raw_np[:, :SENSORY_SIZE] # (12, 40) one-hot chars\n",
"\n",
"N_SAMPLES = sensory_np.shape[0]\n",
"decoded = ''.join(idx_to_char[int(np_cpu.argmax(sensory_np[i]))] for i in range(N_SAMPLES))\n",
"\n",
"print(f\"Training data : {DATA_PATH}\")\n",
"print(f\"Shape : {raw_np.shape} (rows=samples, cols=visible)\")\n",
"print(f\"Sensory columns : 0 {SENSORY_SIZE-1} ({SENSORY_SIZE} dims, one-hot)\")\n",
"print(f\"Context columns : {SENSORY_SIZE} 167 ({CONTEXT_SIZE} dims, from C++ model)\")\n",
"print(f\"Decoded chars : '{decoded}' ({N_SAMPLES} samples, chronological C++ order)\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c33-0004",
"metadata": {
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"end_time": "2026-05-31T13:08:36.362164851Z",
"start_time": "2026-05-31T13:08:36.021965131Z"
},
"execution": {
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"outputs": [
{
"data": {
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1sddee2HChAkYP348pk2blvSP/3E9fvz4Rh0TJkzA3//+94au3Llz5+KZZ57BM888g0cffRRXXHEFLrnkEuy3336tpK3P6y//ATM/uP766wEgqGnIUVUV9ttvP/zzn/8c8ejm888/j+eeew7LLrvsfLcLAD772c9i7bXXxsEHH4xDDjkEVVXhy1/+8gIpu6CgoKBg0eH666/H2muvjbe+9a2jyr8gf/tts802+MhHPgIA+PSnPx1+Z22wwQYA7G+vXXfdFUsttRROPfVUfO5zn8MDDzyArbbaKpB9O+ywAz784Q/jlFNOwb333gsA+Mc//oHDDz8cb3vb23DIIYeEsgYHB4NO+EsvvRQHH3xw3+d8/PHH8de//rX19+9onq0fvvnNb+Lggw/GSiuthNNOOw3Tpk3D7rvv3iCRXnnlFey444648cYbcdhhh+Ezn/kMfvGLX+Doo49ulPnTn/4U22yzDV544QUcd9xxOPnkkzFnzhzssMMOrb/f9t57b7z44os45ZRTsPfee+Piiy8eUbVRt9vF9OnTceedd+Lwww/H+eefj4MOOgh//vOfw+/m4fr417/+NW6//Xbsu++++PKXv4xDDjkEt9xyC7bbbrtAGC+I+dCGPffcE2eddRYA4L3vfS8uvfRSnH322Ume97znPXj55Zdx8skn44Mf/CCAsc/1/fbbD7vtthtOOeUUPPfcc9htt91w+eWX4+Mf/zj2339/nHDCCfjTn/6Evffee0RhlO9///sYP3489tprr2HzLWmYn364+eabMX36dDz11FM4/vjjccQRR+D222/HtGnTkvH93e9+h5133jnkO/DAA3Hccce1CiiN5du9DVOnTsWcOXNGXNcFBQsFVFBQQEREP/nJT0gpRUopestb3kJHH3003XjjjdTtdpN8f/nLX0gpRSeddFIS/7vf/Y6qqkrit912WwJA3/rWt0Lc0NAQrbTSSvTud787xO2xxx600UYbDdu+GTNm0MDAAP3pT38KcX//+99p6aWXpm222SbEXXTRRQSAttpqK6rrOinjmGOOocHBQZozZ06Ie+qpp6iqKjruuOOGrf8b3/gGAaDf/e53Sfx9991HAOgDH/hAEn/kkUcSAPrpT38a4tZYYw0CQLfddltS/+DgIH3iE58IcV/4whdo4sSJ9Ic//CEp81Of+hQppeivf/3rsG299dZbCQBtsMEGNDQ0FOLPOeec5Bm63S5NmTKFNt54Y3rllVdCvh/84AcEgI499tgQd+ihh9JoX5lz5syhpZdemrbccsukXCIiY0zwj3Z+1HWdPAcR0XPPPUcrrrgive997wtxs2fPJgA0adIkeuqpp5L8o5ljHgcddBCNHz8+iTvuuOMIAN16662jKmO0mDhxIs2cObM17corr6RZs2bRJZdcQtdccw199rOfpQkTJtAKK6yQzIEzzzyTANDyyy9PW2yxBV1++eX0la98hVZccUVadtll6e9//zsREWmtaZlllqEdd9wxqeeZZ56hiRMnEgC6++67QzyA1mvGjBk0d+7cpIyZM2e25t12221DHj8+X/rSl0Kcn6tXXXVV3z6aMWMGAaDnnnuub56rr76aANCXv/zlpP3vf//76emnn6annnqK7r77bnr729/eaANRHN+nn366tfyNNtooeRaOG2+8MTzv2Wef3beNBQUFBQVLJp5//nkCQHvssceo8i+M335XXXVV6++MF198kZZZZhn64Ac/mMQ/8cQTNHny5CT+pZdeonXXXZc22mgjmjt3Lu266640adIkevTRR5N7h/vtkePmm28mAHT99dc30kb7bP5vvX82//tz0003TX7ffe1rX2v8djj77LMJAP3P//xP4zl5mcYYWm+99Wj69OnJb82XX36Z1lprLdppp51CnP+bz39DEhG9613vouWXX37Y/vjNb34z4u8Wov59/PLLLzfi7rjjjsbv4QUxH9rQ9luMKPbJe9/73iR+Xub67bffHuL8b6Tx48cn8/CrX/3qqH5XL7vssrTJJpsMm2c4+Ocd6+93P2dnz5495jrntx823XRTmjJlCj377LMh7v777ycpJR1wwAEhbsaMGTRu3LikvAceeICUUsk321i+3WfOnElrrLFG45luv/12AkBXXnnl2DqjoGABoEjaFhQ47LTTTrjjjjuw++674/7778dpp52G6dOnY5VVVsH3v//9kO/qq6+GMQZ77713IlG30korYb311mscWV9qqaUSnZIDAwPYYost8Oc//znELbPMMvjb3/6GX//6161t01rjJz/5CWbMmIG11147xL/2ta/Ffvvth1/+8pd44YUXkns++MEPQimVxB1wwAEYGhpKLNVfeeWVqOt6RF2czz77LAA0JPR+9KMfAUBDAvYTn/gEADT0n2244YbYeuutQ/g1r3kNXv/61yf9cdVVV2HrrbfGsssum/Tx2972Nmitcdtttw3bVo8DDzwwOQbv6/V13X333Xjqqafw4Q9/ONE1tuuuu2L99defZ91tN910E1588UV86lOfaugwy4/WjWZ+KKXCcxhj8M9//hN1XWOzzTYL0iQc7373uxsGtUaaYxzLLrssXnnlleSI3PHHHw8iGpM+rPnF3nvvjYsuuggHHHAAZsyYgS984Qu48cYb8eyzz+Kkk04K+f71r38BsH17yy23YL/99sOHPvQhXHvttXjuueeCagspJQ4++GDccsstOOaYY/DII4/gnnvuwd57741utwsADfUCe+yxB2666SbcdNNNuO6663DMMcfghhtuwH777dc4IjVu3LiQ11+5jtx5wYsvvggAWHrppfvm8Wk+r8c3v/lNvOY1r8GUKVOw2Wab4ZZbbsHRRx89Jon1kbDccssFA2g777zzAiu3oKCgoGDRwP+GHO7vDMfC+O3XDzfddBPmzJmD9773vclvQqUUttxyy+R394QJE3DxxRfjwQcfxDbbbIMf/vCHOOuss7D66quP6rna0O/37/w8m//9ecghhyS/U2fNmoXJkycneX/0ox/hta99bSJpOWHChIZR4Pvuuw+PPPII9ttvPzz77LOhn1566SXsuOOOuO222xpSnV762GPrrbfGs88+2/im4PDtu/HGG+dJZRY/7dTr9fDss89i3XXXxTLLLNP6mzbHWObDvCDvk3mZ6/zk4pZbbgnASoLzeejjR1oDL7zwwqjXJWB/E/N+ee655wDYk1bDnQTrl/7cc88l8f4390iY1374xz/+gfvuuw+zZs3CcsstF/L913/9F3baaacwHlpr3HjjjZgxY0ZS3gYbbNCw2TDWb/c2+PX/zDPPjOr5CwoWJIohsoIChs033xxXX301ut0u7r//flxzzTU466yzsNdee+G+++7DhhtuiEceeQREhPXWW6+1jE6nk4RXXXXVBlG37LLL4re//W0If/KTn8TNN9+MLbbYAuuuuy523nln7Lfffpg2bRoAqzT/5Zdfxutf//pGfRtssAGMMXjsscew0UYbhXhujMlj/fXXx+abb47LL78c73//+wFY1QhvfvObse66646qj3Ki6tFHH4WUsnH/SiuthGWWWQaPPvpoEt/2w3nZZZcNPyoAqyvrt7/9bYN49PCG4Z5++ulEz+lSSy2VGLbK6/J/cH1dvm1t/br++uvjl7/8ZWv9I8HrC914441HzDua+QEAl1xyCc444ww89NBD6PV6Ib5tnNviRppjHH6Mx6p3dlFgq622wpZbbombb745xPkPgN122y0Z/ze/+c1Ya621EpUBn//85/HMM8/gtNNOwxe/+EUAlmh8//vfjwsvvLBhGG3VVVdN9DjvvvvuWH755XHkkUfiBz/4QaK7VSnVqvN5fsEJ2X6GMzxZm+vf3mOPPXDYYYeh2+3i17/+NU4++WS8/PLLgWQdC9rmg9YaBx10EFZeeWX861//wkc+8hHcdNNNYy67oKCgoGDxYdKkSQCaG3/9sDB++/WDV4nUzwCQb7vHtGnT8KEPfQjnn38+pk+fjve9730j1jEa5L9/Pebl2Xz/5N8SnU4nEc7wedddd93G3+D8t6vvp5kzZ/at9/nnn0/I5+F+J+f96rHWWmvhiCOOwJlnnonLL78cW2+9NXbffXfsv//+DcK5Da+88gpOOeUUXHTRRXj88ceTfh2NSqmxzoexIv8NPb9z3ffJaqut1ho/0hqYNGnSqNclABx22GG45JJLGvEzZsxIwttuu22iI3iPPfbAz3/+88Z9uVqQmTNn4uKLLx6xHfPaD8N9m22wwQa48cYb8dJLL+HFF1/EK6+80vo9/vrXvz6QuwDG/O3ehiX526jg3x+FtC0oaMHAwAA233xzbL755njd616HAw88EFdddRWOO+44GGMghMCPf/zjhiQrgAbp05YHSH/8bbDBBnj44Yfxgx/8ADfccAO+973v4Stf+QqOPfbYEXVL9UOb3k7AStt+9KMfxd/+9jcMDQ3hzjvvxHnnnTdiecsvvzwA+0d11VVXbaSP9o/YaPrDGIOddtqpVV8XALzuda8DYEl2/mPpuOOOw/HHHz+muhY3RtPGyy67DLNmzcKMGTNw1FFHYcqUKUEHb5tBqbaxH8sce+6554Je2CURq622Gh5++OEQXnnllQFYYww5pkyZkvwgHhgYwDe+8Q2cdNJJ+MMf/oAVV1wRr3vd67Dffvu1/ihvw4477ggAuO222xaJwa0NN9wQ1157LX77299im222ac3jSf78Y4+Tzu94xzuwwgor4LDDDsP222+PPffcM+TzEuH9DJm9/PLLrZavzznnHPzmN7/Btddei8cffxyHHnoorrjiCuy3335jf9CCgoKCgsWCSZMmYeWVVx6VXQeOBfnbrx+8dOill16KlVZaqZGe65cfGhoKZNSf/vQnvPzyy5gwYcKo2tkG/vu3DUvKb03fT1/60pew6aabtuaZl2+UNpxxxhmYNWsWrrvuOvzkJz/BRz7yEZxyyim48847W78ROA4//HBcdNFF+NjHPoa3vOUtmDx5MoQQ2HfffUdlbHis82Gs6Pfbd37n+rz29frrr4/77rsP3W43kcruh6OPPjo5wffkk09i//33x+mnn45NNtkkxOeS42eccUYyx++//34ceeSRuOyyy5Lf1/4390hY0P0wPxjrt3sbfN+ssMIKC7x9BQUjoZC2BQUjYLPNNgNgj2sAwDrrrAMiwlprrRXIwwWBiRMnYp999sE+++yDbreLPffcEyeddBKOOeYYvOY1r8GECRMSosrjoYcegpSysXPZD/vuuy+OOOIIfPvb38Yrr7yCTqeDffbZZ8T7vMXS2bNn4w1veEOIX2ONNWCMwSOPPBIMBAD2R8KcOXOCldaxYJ111sG//vWvEaUWL7/88oRkygmrkeDb9vDDDzd27B9++OGk7WPZWV1nnXUAAL///e9HLcE8HL773e9i7bXXxtVXX52047jjjhtTOcPNMU7IzZ49OxnLJQ1//vOfEynsqVOnArDGQnL8/e9/72tt1/8I1VrjZz/7GbbccstR/XCr6xoARn1EbH6x22674eSTT8a3vvWtVtJWa40rrrgCK664Yl9S1+Pggw/GWWedhc9+9rN417veFeYTXwv5u+Tll1/GY4891lB98Nhjj+G4447DHnvsgT322APGGFxyySU44ogjsOuuu45K4qagoKCgYMnAO9/5Tnzta1/DHXfcMaxhWmDh/Pbr9zvL/6aaMmXKqE6zHHfccXjwwQdx+umn45Of/CQ+9alPNQxkjuU3Hf/9u6Dg++eRRx5Jfn/2ej3Mnj07IdfWWGMN/P73vwcRJe3Ovwl8P02aNGmhnPrJ8YY3vAFveMMb8NnPfjYYibrwwgtx4oknAujfx9/97ncxc+bMRH3U3LlzG8agFtR8mF8sjLk+Fuy2226444478L3vfQ/vfe97R8y/4YYbYsMNNwxhb7hr6tSpw6o487+lPTz5PW3aNKy55ppjbve8gv8ezfHQQw9hhRVWwMSJEzFu3DiMHz++YZy47d4F8e3u1/+S/H1U8O+LotO2oMDh1ltvbd3l88cr/DGNPffcE0opnHDCCY38RBR0X40F+T0DAwPYcMMNQUTo9XpQSmHnnXfGddddl1jNfPLJJ3HFFVdgq622GvVxoBVWWAG77LILLrvsMlx++eV4+9vfPqpdw6lTp2JgYAB33313Ev+Od7wDABrWV88880wAVj/sWLH33nvjjjvuwI033thImzNnTiDNpk2bhre97W3hGitpu9lmm2HKlCm48MILMTQ0FOJ//OMf48EHH0zaPnHixFD/SNh5552x9NJL45RTTsHcuXOTtHnZSfa7wvzeu+66C3fccceoyxhpjnHce++9DevRzzzzDB566KF50l82r3j66acbcT/60Y9wzz334O1vf3uIe/3rX49NNtkE1113XaJr6ic/+Qkee+wx7LTTTsPWc/rpp+Mf//hH0E82Eq6//noASD6qFibe/OY3Y+edd8ZFF12EH/zgB430z3zmM/jDH/6Ao48+ekQJk6qq8IlPfAIPPvggrrvuuhC/4447YmBgABdccEFD0uVrX/sa6rrGLrvsksQffvjhICKce+65AKzO4AsvvBDPPPMMPv3pT8/r4xYUFBQULAYcffTRmDhxIj7wgQ/gySefbKT/6U9/wjnnnANg4fz26/c7a/r06Zg0aRJOPvnkxu8VIP2tcNddd+H000/Hxz72MXziE5/AUUcdhfPOO69x7HvixImj+j0HAKussgpWW221xu/f+cFmm22G17zmNbjwwguDTn0AuPjiixvtesc73oG///3viT2Kl19+GV/72teSfFOnTsU666yD008/vXVTue031bzghRdeCL/DPd7whjdASpn8lu7Xx0qpxm/hc889N1F35u8H5m8+LAgsjLk+FhxyyCF47Wtfi0984hP4wx/+0Eh/6qmnAlH+74DXvva12HTTTXHJJZckY//73/8eP/nJT8J4KKUwffp0XHvttfjrX/8a8j344ION78cF8e1+zz33YPLkyYkqwoKCRYUiaVtQ4HD44Yfj5Zdfxrve9S6sv/766Ha7uP3223HllVdizTXXxIEHHgjA7tadeOKJOOaYY/CXv/wFM2bMwNJLL43Zs2fjmmuuwUEHHYQjjzxyTHXvvPPOWGmllTBt2jSsuOKKePDBB3Heeedh1113DfosTzzxRNx0003Yaqut8OEPfxhVVeGrX/0qhoaGcNppp42pvgMOOCAYNPjCF74wqnvGjRuHnXfeGTfffDM+//nPh/hNNtkEM2fOxNe+9jXMmTMH2267LX71q1/hkksuwYwZM7D99tuPqW0AcNRRR+H73/8+3vnOd2LWrFmYOnUqXnrpJfzud7/Dd7/7XfzlL39ZIMdTOp0OTj31VBx44IHYdttt8d73vhdPPvkkzjnnHKy55pr4+Mc/HvL6HeiPfOQjmD59OpRS2HfffVvLnTRpEs466yx84AMfwOabb4799tsPyy67LO6//368/PLLrbqmhsM73/lOXH311XjXu96FXXfdFbNnz8aFF16IDTfccNTSnqOZY4D9UfLPf/4Te+yxR3L/eeedhxNOOAG33nrrfBsju/7663H//fcDsFIlv/3tb8MPzt133x3/9V//BQB461vfije+8Y3YbLPNMHnyZNx77734//6//w+rrbZagxQ866yzsNNOO2GrrbbCwQcfjOeffx5nnnkmXve61+FDH/pQyHfZZZfhe9/7HrbZZhsstdRSuPnmm/E///M/+MAHPoB3v/vdjbb+4Q9/wGWXXQbAfiTdeeeduOSSS7Duuuviv//7v+erHzi+973v4aGHHmrEz5w5E6utthq+9a1vYYcddsAee+yB/fbbD1tvvTWGhoZw9dVX42c/+xn233//ZL4Oh1mzZuHYY4/FqaeeGnScTZkyBcceeyw++9nPYptttsHuu++OCRMm4Pbbb8e3v/1t7LzzzokqiGuuuQbXXXcdzjjjjEQy941vfCMOPfRQnHfeeZg1axY233zz+euYgoKCgoJFgnXWWQdXXHEF9tlnH2ywwQY44IADsPHGG4ffw1dddRVmzZoFYOH89tt0002hlMKpp56K559/HoODg9hhhx0wZcoUXHDBBfjv//5vvOlNb8K+++6L17zmNfjrX/+KH/7wh5g2bRrOO+88zJ07FzNnzsR6660XjJWecMIJuP7663HggQfid7/7XSACp06diptvvhlnnnkmVl55Zay11lrBIFIb9thjD1xzzTUNadd5RafTwYknnoiDDz4YO+ywA/bZZx/Mnj0bF110UUMA4YMf/CDOO+88HHDAAbjnnnvw2te+FpdeemlD5YOUEt/4xjewyy67YKONNsKBBx6IVVZZBY8//jhuvfVWTJo0KWw6zw9++tOf4rDDDsN73vMevO51r0Nd17j00kuhlEp+R/Xr43e+85249NJLMXnyZGy44Ya44447cPPNNwc1FB7zOx8WFBbGXB8Lll12WVxzzTV4xzvegU033RT7779/+Ca599578e1vf3tEyfhXG770pS9hl112wVve8ha8//3vxyuvvIJzzz0XkydPTtTgnXDCCbjhhhuw9dZb48Mf/jDqusa5556LjTbaKLENsiC+3W+66SbstttuRadtweIBFRQUEBHRj3/8Y3rf+95H66+/Pi211FI0MDBA6667Lh1++OH05JNPNvJ/73vfo6222oomTpxIEydOpPXXX58OPfRQevjhh0OebbfdljbaaKPGvTNnzqQ11lgjhL/61a/SNttsQ8svvzwNDg7SOuusQ0cddRQ9//zzyX333nsvTZ8+nZZaaimaMGECbb/99nT77bcneS666CICQL/+9a/7PuvQ0BAtu+yyNHnyZHrllVdG20V09dVXkxCC/vrXvybxvV6PTjjhBFprrbWo0+nQaqutRscccwzNnTs3ybfGGmvQrrvu2ih32223pW233TaJe/HFF+mYY46hddddlwYGBmiFFVagt771rXT66adTt9sdtp233norAaCrrroqiZ89ezYBoIsuuiiJv/LKK+mNb3wjDQ4O0nLLLUf/7//9P/rb3/6W5Knrmg4//HB6zWteQ0IIGs3r8/vf/z699a1vpfHjx9OkSZNoiy22oG9/+9vJc49mfhhj6OSTT6Y11liDBgcH6Y1vfCP94Ac/aOTzz/elL32pUeZo59gnP/lJWn311ckYk8Qfd9xxBIBuvfXWEZ97JMycOZMAtF58bD7zmc/QpptuSpMnT6ZOp0Orr746fehDH6InnniitdybbrqJ3vzmN9O4ceNoueWWo//+7/+mf/zjH0meu+66i7bZZhtadtllady4cbTJJpvQhRde2HheImq0TSlFq666Kh100EGNd8LMmTNp4sSJwz532/j4udrv+sUvfhHyvvjii3TCCSfQRhttROPGjQt5Pve5z7XWB4AOPfTQ1rTjjz++dTwvu+wyevOb30wTJ06kwcFBWn/99emEE05I1vKLL75Iq666Km266aZU13Wj7BdeeIFWXnlletOb3tSaXlBQUFCw5OIPf/gDffCDH6Q111yTBgYGaOmll6Zp06bRueeem/wtWBi//b7+9a/T2muvTUqpxt+oW2+9laZPn06TJ0+mcePG0TrrrEOzZs2iu+++m4iIPv7xj5NSiu66666kzLvvvpuqqqIPfehDIe6hhx6ibbbZhsaPH08AaObMmcP2yb333tv4mzyWZ/N/6/O/uV/5yldorbXWosHBQdpss83otttua+2XRx99lHbffXeaMGECrbDCCvTRj36UbrjhhtYyf/Ob39Cee+4Zfu+tscYatPfee9Mtt9wS8vjfdE8//XRyr/+GmD17dt+++POf/0zve9/7aJ111gm/t7bffnu6+eabk3z9+vi5556jAw88kFZYYQVaaqmlaPr06fTQQw/RGmus0RiH+ZkP/dDvt3K/PiGa/7ne9ntsuN/sbfj73/9OH//4x+l1r3sdjRs3jiZMmEBTp06lk046qfFbvq2esf5+93N2uLnQDwuiH26++WaaNm1a+Ibabbfd6IEHHmiU+fOf/5ymTp1KAwMDtPbaa9OFF14YxjLHaL7d828rIqIHH3yQADTmeEHBooIgWoIs8hQUFCwS1HWNlVdeGbvtthu++c1vjvo+rTU23HBD7L333qOW0C149WBoaAhrrrkmPvWpT+GjH/3o4m5OwQh4/PHH8da3vhV1XeOOO+5otWBdUFBQUFBQMP/YcccdsfLKK+PSSy9d3E0pKChYhPjYxz6G2267Dffcc0+RtC1YLCg6bQsK/gNx7bXX4umnn8YBBxwwpvuUUvj85z+P888/f5EZYSpYdLjooovQ6XRwyCGHLO6mFIwCq6yyCm644QbMnTsXu+yyS1/L1gUFBQUFBQXzh5NPPhlXXnklHn300cXdlIKCgkWEZ599Ft/4xjdw4oknFsK2YLGhSNoWFPwH4a677sJvf/tbfOELX8AKK6yAe++9d3E3qaCgoKCgoKCgoKCgoKCgoKAgQ5G0LSj4D8IFF1yAD33oQ5gyZQq+9a1vLe7mFBQUFBQUFBQUFBQUFBQUFBS0oEjaFhQUFBQUFBQUFBQUFBQUFBQUFBQsQSiStgUFBQUFBQUFBQWLAeeffz7WXHNNjBs3DltuuSV+9atfLe4mFRQUFBQUFBQULCF4VZC25QdtQUFBQUFBQUHBvxOuvPJKHHHEETjuuONw7733YpNNNsH06dPx1FNPLe6mFRQUFBQUFBQULAFY4tUjXHnllTjggANw4YUXYsstt8TZZ5+Nq666Cg8//DCmTJky4v3GGPz973/H0ksvXSz+FRQUFBQUFBS8ikBEePHFF7HyyitDyleFrMGoseWWW2LzzTfHeeedB8D+Zl1ttdVw+OGH41Of+tSI95ffuAUFBQUFBQUFr06M9jfuEk/azu8P2r/97W9YbbXVFnYzCwoKCgoKCgoKFhIee+wxrLrqqou7GQsM3W4XEyZMwHe/+13MmDEjxM+cORNz5szBdddd17hnaGgIQ0NDIfz4449jww03XBTNLSgoKCgoKCgoWAgY6TdutQjbMmZ0u13cc889OOaYY0KclBJve9vbcMcdd4yqjKWXXhoA8MfZj2HpSZMWSjsLCgoKCgoKCgoWPF584QWsu9Zq4ffcvwueeeYZaK2x4oorJvErrrgiHnroodZ7TjnlFJxwwgmN+FsOPhhLDQ4slHYmIIDsPyAQiAAyBEMEIgNjAGMIZAyMMTCGoLWB0QbaGGitrV8TdK1Rax6noWvj4oxL1zC1SzMuXlO4x5drjI03zk/GSq+QIeuSayuGk1NxkspCABBWclkIQMD6pQ0LIQHpXQkhBSBkCEPAxcvgBr+QNq8ULixiXsHKcnXZdsjQDlu/a6tgbfbe5PHsOIEojFkIk7EB4/xkxyyEjQERWdcQQAZk7OX9MNEFwd1jmEsxPxFAvj7nd+Nim0p541vHR/ixEHZ8hBAQUrg+tq50l5AKUgpIpSCVd12880vl8lQKUsY4EdJljHfjxP3CzYPQBtaufKz8SBH7h8J4uMv1e3TjWiLt1pQ2MFqHuW60BmmXrjW00TZdE0zt/Qbk440B+bXiw2Hd2DULXj8fqxHWkGhxg9+dBHDTGDL4hfW7PpJCODem83BIT+5JXbD7BMsHVidvZz/wJyWKT+6GjS0pm2JYvInLz8VTSDesPJ7XuLh4r7uHldvalpb2tkEgzku+fuz7TKRzXEgIFdeTX0OCrQnF1wlfKypz2bqRyr4LkzXl1zF3/RqCG0Bka8h2hFtKlMxXMmT/DpGb10RuDfh1YmCMhjYU1kdYJ9q4NeTy1Tr+vTGarUNK1yFbP+H96P4+El/jlDxBY8wIwl7C+YWAEdGFkDBCQksBIySMlDBCQUsJLQQopLs4lm5cWEsF7fL5vLYcYfP4NBdHQoJ8G+D8oY12fNrmnnBjIwAIAgQRXAnWTwRJxl7G+Y0NK2MgiKCMtmEyUEZDGQNJGtIQC9v8Pq8P+/JUKNfWAfL+2A7bNtfW7GlsOH9b5HEUxk9kcf3eNOTqG4LBFfj7iL9xl2jSdl5+0OZSCC+++CIAYOlJkzCpkLYFBQUFBQUFBa86lOP/wDHHHIMjjjgihF944QWsttpq+K9DD8CkpZdaqHUnH8oZoRQ+emsDXdfQtYaua/vB26tRd2vUvR50t0bd7aE31EPd7aEe6qHudm36UBc9F9cb6kY35Ouh7tXW3+tBd3uouzV0z12hXh0+tjnZxQmo5HkAwH0cw32Y2o9UCZL245Wk80sFkgrGX6qKbotfe7+7dJ5PVjBKMTct39dLwvnZBzTch3ODvHXPJxwRKsh+/Ar3ESxIQxgDaaIrjYbUGsLUkNqFTQ2payjt4nQNaXzYXUZHf0i3cSKUW0NQWp8gY/2+bZbdgMgIjfBUgcyxRJKQ0hGryhKuVWWvTgXV6UAOdKzbqaAGBqAGOlCDA9Y/OIBqcABqcNDFdaAGB12cja8GvH8g3C87HZs3lB/rlFUV2hPa5y9P/ieLiZG0hpNJGuTWjenV0HUPVGvoXg+ma+e87najO+QuHzc0BD3URe1ce7k4l9/0ape/G8vs9WB6NUyvB+PqJ60dIexIYd9OT+KyoeJTsEHcMvLUDSUjXUUridtG0rbG9SlLZGW11d+YYy1IyFARlpYlSgUjXgUjcYUjX0UkVC3xSswPGFCWbvNEPyuL1QHvRySLW0lb155k48BtNERy1q0fpcJ8Vh17VQN+vlu/XxOdwQ4qt4Yqt26qARc3bgCdkMaugQFUg7YsNdBB1Yllh3qrKrRFNDZG+CaI3+Np+zuk7dqpNUzt/ib03N8FN8+TvztDPdRD3Xh1Y7g3NIR6rvd303y92q0pW44Of9960L3a1a1je7Sx68lQsoYaY4ZI1KakrWTkrf2bpISw5CpsWEJCeXJWuPGVClJYolY4ElcI5TaaFIwQ0FJBOKLWbx76DUZ/+bqNsAS7J3A9cdukOfna8oQoEoJUOuJUeAJVOKJVOKJVONJVSEvOkrHPCA1lJJTQUFJAwpGy0FAQtgxoKCEgIYIrhYAEQUJAwPuNp8jjRW2kbZOSpfDUfCsh31aQLL7Nlcl9I/3GXaJJ23lBPymEgoKCgoKCgoKCgiUBK6ywApRSePLJJ5P4J598EiuttFLrPYODgxgcHGzE73PuHagGxi+UdibgTI378BROIlM46UphtA27C0ZDaHdxv64hauvC6OC3l4ao65gvcWNZCGWapF44khKOFAS/+j8Yk54z1jUAZCqxa4yBkQZGaiutJRWMrh3R6qSWlHLSS5WVanKErGaEbPArd49w0k6uHP9xTg1pJ0faAtFl1JP/4IykLb/chzKTQrJSS568TV3liFflyFdlrCSnMtqSs2TJXmU0yF0wGuTuhxsT6aVzmds+Lun4JBsFxo4LDIGEAYQGSRHI9fRSid8oFV13GZm5irk8b7g/Lds46elIrDMynbs5m8nWkOBryI2PMBRI7fRypDdbR9IY6+o6pjnSXTiy3abbe6xr0vvD+jFpvZ5IN5TMpb5riEUn1APL36QkKOGz8/SEXBWiPb7tnmHKzDEa0nY45ERpv/ua5BwPNOWXh39TDZ9IjSgCSDipeaA2xoo+agL1DCA1SGpA9ez8dnMfsgIpCVKVuxSocv7gdgClYlyeHvx2LcGXE8J2PcGtKwgJ8icN2LuubeMDQJin4Z3v/xaFvwl2zoP/3dEa8H9r6ugi/F3y8b0kXegaqOvkbxh4mf7vm/+75/42hja1/B2KhKAP+3Xmx08AQrOxFA3p1uTvgEjdmDe7L9wfCeK0rDSPTeOtbpmLTcHTliQ/bvF5/XiGjRWKT+o38lKpXWrGuV0K7oqs3Oj3aVkbWpBuQkXStV36FiHd+qglh0jyWNf0rZ9jiSZt5+UHbT8phIKCgoKCgoKCgoIlAQMDA5g6dSpuueWWoNPWGINbbrkFhx122JjKevz+R6CqJpm78MA+pvLjhUGi0wSJmiBVychC4Y8yug/aBmkYJEJdXEs5UVrTkkuSkYHx45cRTmN8RiAeZyWYSOqScCRiyAVDBEPSuZbY1dJYEtb446kqHEW1RC07murCRjaPpuZHVL0EFhA/sjkEIzREMkaZdFMYDx2OkZIjXa2Kg0i8WvJDB9cTEwiEorvPaBArx6pHsJcgK28oKKpGCJ+wIwwPOelF+01OMCRAJGAE7HFoYcJxXyN0kDiz0mT8CLEMx4b9MWB+ZNjf1zhGLAU7UizicWIviRYk5NLjzW1jlJMSfIz8EV7u964/5qvY8V9l8ngd4hSLC8eEw73Ejg2bRl2hPayNRCkJ0Y/wHBPhONplOYr1OxJB+2rBAn0Oz4kJBHLYE3hkCCTcZhRZtTJG2mVN0vmlhJFk32VKufeahlEaRtbQym1YKQXtTgzkrpH5JYOf3LuOu8jfc5xI9P2TveP8pof0mx5cup/c3xt2skCFkwI6nhBgpwOUO3UQXJ+fnUxIwsZvgvj62CkHcmuI2sd2uPH2JGRzQOdtOhSMFTk5m9PPqUIELn+bvfVbyu2X1o4lmrSdlx+0/aQQCgoKCgoKCgoKCpYUHHHEEZg5cyY222wzbLHFFjj77LPx0ksv4cADDxxTOXvc/xMMiv5WhxcWch4ll5dsPb4bpFltIDlyzMr0ZGian5eRld1XyqxP29siRFpIrMOAIC0p6Y8mCxtLnqwVBoak1R0qlZXEFVGvYCRpU1KQx0U/PxLLj8ZGIiOXtuLIpZI8KSgDMchJuqjvj7zkLVl9gV4/rfIELZkoueYlZo2GYRKaxsUlunGdXltP3IYRJU8EjoaByD6cnRRrlFTz0nm2XwT8sWqvS9gdsfZqFoRXX2CPCgdXpvHSSfIKISGll/7z6QLSkbgSXueka5cbGxKinajxBKh7/ly/oh8bQdL5BYSRkMKR5EJAGPecZHtCGHu6WQDBD0O2DyQskQSbQcBYJs/3FRHrTSYd7BfcAsTwJFWf+D4J81LWgsSY3jEuciRSuy19Xkcg3EdkCVD37kzIW2Hfn0Zw9Q3pFQ+QI7x/wvvIpUeVLSKQr15iFi1hwdaWd4N0LdNrG4gwJq0unKhkskkHANIRpAaAILcGACHIXfG9YNPtGrMLhunTRXRju5l0ZJOVC0mx03M52kWDsc77JXmzY162WhcsotSsDQnn5+/K+FsknxZtOm5jSWNr8RJN2gIL7gdtQUFBQUFBQUFBwZKCffbZB08//TSOPfZYPPHEE9h0001xww03NGw5jISXehr1SKKKCwGjkqhrISlaidXsiHBffx+ieKQ2jYR4FNOXIixJmRzPZZJfyYe8jwcjJTx50ZK/LR5ZPKszlOtaGr8Ch9clGB1qcX06k0hmksmt8clxfi9qbIYtA4RI1FJLO1wb2p+BhRl/krgSgOeEJFlSVvl4glAEqawrFNzVDMc8fS5pnC5dcvUYCGXJHkv0pu2CI4jspEo/473jjXsF/ZxEwYAbGe93l6ag+9b6XVx2GU0gDVDt45DEw3i/LQPaqZ4wcHUBcGFkQ8mbn3ljXFgPKZEXpJDDlUqQGxFVTBjJ4rxe6ZZwUoYULN7FZfXm7YrPIFqGKD+u3ed0AZdKDv4oKS2InwpoDwsn9c4l4aM/l9hkpxoYYQnq9zbInosRn56eDdPQ2xQkuBMDBDLSqYMx7sSAsgbvlFULk5wccCcJ2tXBeIl1b/TKqYHJx7cxXnHcOPhpAj4mSf8xqVeuBkYxiVuTqYIhphKGnBqYeOIgP3nQ/2QBV9sQ+9puUi7JJGlBOzj1Gv3pJldTZYKneNvvHiuWeNJ2Qf2gLSgoKCgoKCgoKFiScNhhh41ZHUKOObKDAaEWUIuGR/8Pjj6EQT8ygRF1IvyTMrzJfd4rsvsozzA69BOSSvTmOc7NcqZNa/TcAFKwdg9m4V60h4UQ7t5mOYKVw+sFq7tf+zlyoptzbtxyfSBswIweufjhrN4Hi/ctcW1W7/N6weLz9raOi/v0tX1AkAJwamUhpYCUBKsik6CUgVKAlNL6K0ApoKpselURVEWoFEEpCVVJVJWEqgwqJaEqZcNKQymbZssSUEpCKuuXUkIq4eq3xm6sJC+CxF6rhCjrJ29R3lu8j5eB1s6vDbS2Ye38de3iaoNaM38d44Kf5dXGudKVJ2yZBgQNayDLEME4Xc7JnBhhnBJJ8BZytqH+I7FsrxJVITxOMwIwJQkjWZioGuFH7oXIiN60jeEtk5G2Yc5lJGmq8oVbvPekoFVHIbhaikw/tNUR7a3dRxIx5klVlkinHzWqsjAJMRyYdUQyc5hRSshbuxa9CTTYBe2kUwmAEQYEFVQo2EvDkIIWfgz4WEnoOo5NSHOEu+ZzIFMDE04UsM0xR8k2X3ju70p4ZycS61H9C5dajypgXH87stWfJPCnAzg5y1XBeCOOXn2M8cQtxThPpBOTT87/rv3HoeUdSC0J1Oq3Y99Ma/6qiOtY9CnLh9v/eoZ8i5hV75IB9Mj5lnjSFlgwP2gLCgoKCgoKCgoK/t3wo012gKwGFkldkczwbv7B7IkMgkA8ei+Z5FOiY5Pp5vQf0p7oaIvn5SR6WdnHeoNo8ZKjIzxbg0DMmM9+n3qtBHAuGda3L/vE9zsPPsx9/TAqvsCRPaOgfOavLkqchJAeEZ4Qcd+44Tu3TQVB4HlELpycxIe63T/R3xwHnhZyDzfOo5xwjT4jIJE7p3wqsrEKZVDM1xaXl9svvqW+UYMQN1V4GwBE435OjyqcahFJIKcL2hJh0qkWiaQfVyOimdQm11WcqBlhKkZSvdAZKRgkOKPUbSJ/64nB7H2SEINMvYh/RxFpSEMg8oSgSfxe1UgwnujIQuHIXuNUjXhd0FGCk1xclLKlTNp2NEPUjLBPTvA6bg2bR04tjESqx5sAkgQTCN2o15uEgSFlCd4wngpGioyszccpVwETxydvN/87xN/z5MbH95P00q4miJMz1S5epYuOhisZUUvk9XRziVo+JkxC3v2NCSpf+u5w/Iewt2FTIFOlIeyYeh3gfPyNkNCJ6/1RbVDQSd4S7+8L7wNWtmabAoa9BxK1Q2G+9Sd2FwZI94CH/jxivlcFaVtQUFBQUFBQUFBQ0MRQZwBiERkia/1YZsd4uUEjf0Q1EK7SkrBaSChpJZWksOlGaCghrOSTr4WfiTUAOQkwOBWEBMM+uAiCnL45z6VR3vIY0e/T2Ut1+Y82bvCLQjiX2GuRMmT+xEhVaz6kx8g5WcFJC+HJC0Yt9ZHkFCzAJYj52CEjPILBnBaiKhqlak9rvT+4vn5O9qdUzIgSgv0ITlf2iDf+B2DJeFLRx++lxwW4jgsRXH6Hy+OllUNYurjcFSEc9Rd7vanC6SC2ayvRkyq8Fl9Xq3tFhHUiYOeWoESa09/hJT2tvmBjn0442XlhYPUHk20byaBTFULALfrgDxsExDYO2IDaXuAjnGUY1ciQrTc8j9O9TIAU7l1qREKg2ndXRnozkq0Z166PO5JjfXR0u3dueN+G93BzHkX4d0t8l/R7F4XNPBi2ucj/ZvXzp0YBczUMMtuwzN97DdUaYxqxtjEcOW64DcNG3pYbxrLBOCzY+Nm/nX4TR8CIKMFvSFsClUycL5zUhUjmVhoePp1Yuv/7bZDOt7Cis/YuKmhT48FR5CukbUFBQUFBQUFBQcGrFO7zfyEjSp/ZOtkHqrukjw/pqSRlzMvLQSBKRKOuKPvK0xfGszbJg1T6Kz/O66X//PHgeOxXpRKBXlowO77dlBjMjo4nhEfL0W6Akbi+VxjFwUiDVEqQE+rx6LDKpJhVIu3Mj3C7NPJHv0044s39/Cg3ryfVO8kJjpyUWhRz+tWBJYOM7Q8+F+NmA9uMcCQqCQGSkZCFEFa/hbB6LoRU1hXWIJyUyhqoksoahZMSJBXIGYiDC8cyot8bk/NELQkJyYgc8HWETGKaEWytGxQNKdvUVUZbdR1GQwkJKbS9jIAQ2qr2EMK6JqpdkcGQHHm7WLYdIr75BATbpHCUs/Ad35wp/s54B4X37byLVBfML0b7bmsnWdM0v+UhGvFg8dnGiMjzpapcGn9rs7LzUJ+9w9ZQlPaPhkj5VCSXxu+itjxIDZk281GWH61TfrRLIErit4fnpQwA6MIU0ragoKCgoKCgoKDg3xkfmH0nBuUi/kmfHX/mX0sUvoz8R5WLd1JH5M7X2nx90lrDqT8eS0VM93mYf0Q4AsVyS8IZlrKuVDK4spKQSlm3UlBKQXYUVKUg3aUqBdVRUJ3Khp1fVQqyU0F1lNWJ6tOTe1n5SkFIYev3bfBtEwKQTDoPSAXv2LFdMt41zniVgUkuDVMbmFrD1Bq61ja+1tC92oZ7GrqnoesauqdhfHzt412euo5lsDKNMTasrSEtY4w9qazdMWYD114xuvHiQzdMeFgSAghkWJskWhs50tcvhicv2hAkusImATsyDCQSYlaazB/z5ceG/bFgEY8OszgfDnnBjyKLeHyYS6b1kUoL0nLpgyd9GS5p9f16V7n5q5SCVMrpEVZQqnL6gxVUVTlXYaCqUHUqVM5VlcrCbfdVrkwVXKkUpBTWH9aygBRufXvJ22wMuUE9ckfryRhAu+PyWoNq7dzaXr0aVPes2+vB1NalXg+m2wP1utbt9mB6XVC3B+p2bT6f3vPpvbS8umfrq+u0bq1d23QwYAf3vkznWRyvlFT3l2SuhJFu00oqt3HEjIaFzaqof5iYYTEeb/UK+7AvO3W9ruOgY5htTiG4+XyLf3OE+xuSkupsU4gZJctdrzdYOvUIeVzwG5+uoz5jfl/QcRx1DQtjGm3iErftbzn3rK4/IATIbUJwl5Ttc0jl/M5VFQtXaZyqEr9RFaAkSFYt9zrX1yF5/YK1z0u1t8sQC8R1FAxVmmikjauigNEQWtuwzvymdnHOrevo1zW7h8f7+2tbj3YqSbRXheHrtXMEFN3wWyYdGfcG9P/GP7npk8eY3AQZGnn5PSOjkLYFBQUFBQUFBQUFr1K85sXnME7IRVontfg5X0Ah3G70aqR4M4b8vD7PFycc5gjPYgUCI4kjpQgkj6ws4aMqRzQFEsn6q06FaoCRSwMVuzohvcPiQr5O5cpQias4gaukM36lIFQkwzw51tCrSoiErSNtjSdKncEqow20I1e1J157NepeJGrrXo26665ejbrbQ92t0QtxPeiezvI4t1fHMpW0RK7QjiR0Nn4Ap/NSsMGi1nnVf+AySWN2vDUVJ4uSycl9GWFHDQIvklwpi8vqbTDD/WlbSjMm+hM9SeqoHZhA5loSlxOqKZk7TFwgavmRY7SStPzIsGHPGNvG+rFlHAKLwfJ5tQZRjtrncxlF+yUaYSs16zcsIuHKNjIcGSslv/x6kcxtIW0zSUSvJ9aStlYfi5f+C+8i6TYcpIiXIzzhDNN5SXnZxyVWv1XVkMXx+eL7g0+xhMwc/WbHcDnD+uGVsHmajrcI8V5FTDK+jBz2/tylbKwtkYsW0na02yEevtGsXym6CXFN8T0aTluQiHPfzw3BBkUgLuBGvTTWIWm2uwVeo0YIhyttaxrP0gXY6ZH4fmnXJcwI9GS8ovqRMHb5u9f7vCoO1iKrMYSiwTv4lWcvr15ECAkYJzVvJCA0hFCA1FYiX1eWiHWEbXAdWQsfZ3wc02fsdBn7sCeRw2YNMObNw/lBjzTwysj5CmlbUFBQUFBQUFBQ8CrFX17uYWARk7Z9QYkzllsWWL4xwX0vWnIgHrk2SgKqApQCVQpUVaBOB6bTgRnoQHc6UAMd1IMDUAP+qqAGB61/cADV4CDUOOZ38Wqgw/wxLAc6UJ0OZKeC7HQsadupLGFbKUfcOvLKS9yyj+ZAfBIFyTsyVpqWtJUQNNpKypq6hun1oHvO7fagu11oJ+mnh7o2PNRFPdSFHhpq+MM9IdyFHnJxqgetrJShkTW06MGIGgY1CNpZoNf2O1kYx3/0nzye1PREKtcTnBs08sZrSIpgsMZImRixaYZVDOd5fLnc6n1SXyToArmBSMLmrHqgw4iCy/UFp3qhnYErF/ZqLLjr071fGQOlawwwndI8n43LjAPmOj3BdHcyCUHvNhZRIIG8K5Pxobz/ZFQnYmSqOmRIqqhWxPtVzJeqJlHgakm4ihEuxZmoGGlIczZfCXF8cglOrue0TT2CZqpGuFoRHQ0wBj8Px3y5wUYvwZkYXXRkk583XNo0fxYud8v1WS9ejJWEnV8s9gdO0P70frOgmd5KD+f7RSxXsseUlCP6xEePaMb2Hy3RTOObDX7DJ25A8Y2jptS/PymQnhaQ0FKgFhLcAFkMi9Q4mRDQsgOtBhunEQyikbNE3y3bpAq/BxYRSHeB3z8wYr5C2hYUFBQUFBQUFBS8SiEPfD/kwLhFUxkXZ+USKoaC5Ap5SRZ/OakXaHfE2EnE2MseX0StQbpm8e5yR4KDtEwoy5ZHzgJ7crljmPyYcyJFkz2Pl9UlIkATNBknCupEQmsCFCB6BCgDVNpdNUSnBqoe0OkCVQVUQxCdDhCugTRcDQBVZeOqDtCpgKoDUVnXlqEsYSwVoBSEcro6VdT/yY+m5qRg8rxZ3xDrd9+/to97QK8G6h5Qa6C2R7tR94BeF+j1AHfcO4TdEXCbx111D1T7smpXTw2qWZ2ajxk1xaqBlGIRThZL+mcWUNL1g1T2mK9S1l/ZPouEe+X61F4xbPuelAu7cUjSeX5lyyZXbnL548P+cpJoUYIwn3Nt64dJgGndWDNC125cbH8KN25+zITWbhxsvOBjUPdifjfmwo9NNi5CGzfv29ZTHBlPBnpZy5jmU7zIuwjjB5NL0LJ+klzC1hkYkzydbVLI1ACZv0dk+nKjATOkmxvODbK1bfxMmIfs2YLLx4+peTGUjGmU2LXznJg/SPFm94V7TEs5iHWiVTVMOzEZHh9w0sU21natlfz1ksfSSQkL50ohIBU/feBVXrg4ZaWXVUizcYql+Xvayvb+eNIBiRtJwfQdR9HrThV4l9x0tX5j3GkD5zearLoW48PWr3m8NjGsCTrJZ8fIlpOVxeqyamnSNvnTInyY2kaME4epIcxcrYWXlk8NwgW/lCEuddNNjNyg3IhGM7nrx6Yfx9m6ycOJaUryCD7PQ9jnj3nthgUgjUEHBFH7MtjGUttGky832bho+6PTb3QWPGpT4/ZR5CukbUFBQUFBQUFBQcGrFN23bg1MWGrhV5QQtp5w8+ROJJgScs6TRY488mRfIPlCuJvG5eG6F0gq4f384vUaY9vidD1aVtA/AzUfyT+WIUAYzseANAFSwkgC9QxIGZDUMEo7idweSCkYpxPQOH2BpDrBb6oq6BE0qnL3xbhwv9MnaGTUKUhS2SOpXgek1ynICClOo/EPVq6rL+h3ZHoEvS5A6XT/NVytIZ2eQFn3IHUdrkZ6Fi+Md+0leZ3heGo08uSfwB5BZmPkuTZPxElpCT4pLZntpJCFqqw0siPERVVBVBVkx4U7HciBDkTHSjTLgQEXX0E6KWefJgYGIJN7Oq5sm9+XbS9LqgulnCEt38aMWEwmHSPi3CYHuTnrdZVa/aV11GXaq2G4ztSu05fq9KOaXs30plo3pHGdqo5oN64cG1ZWt2rYIAFIC3sJ2DZCOhLRkYR8iBKJP3+YnBskdCQcWaJUkicLHQcLYY1wuTjpSF7pCMUQJ5gBL6RhIYQ1hOjDzu8JS+HyRwIz1zbZnHrx/UApT5uEye05UOBejUs3nkCETTMUXeJ+5GnxnkD4IeZttMG3MSyi8ApgY8MI0YystXp/ZSRclQ1btSzOX0lUThdxVbmwc5WSTq+wjasqq784pLs8abmO+PUEb9DZ7cljgKuvaNv3ACIpapxe7ECkOlJVM7I1XLV169r6vevj6lqH+MTP7g0u9yeEryNwjYEh4f4OubWP/kiJUSYF6nRPk8xOFjDJcs3D3sClO0EQpNJDfNMIZn5/SujKtD0txHIOT4x6SX0vCd4qse6l/HPJdX+qwJ8U8FLpoEwqvb9BzdQIpoFwhjEFvFFM9nfIk8P5czDfcDK4MT3e0z+XdbswhbQtKCgoKCgoKCgo+HfGdVf8ALIaXPgVMemYeFy6+QEm3MeXyD+e/BFgyo4CZ0eGlTGQWjePDQcDMtEoTPqRFwlK/jEW2ukfoCH4Q5ZR8gyIaX5opR+mnEUQjCzhknsiu29098Sm5UxF1qZRnt4ULf543D1woglxGsi2vuHo5+X1T8/KFwCUT4u5hnukYDTMNVwIbUlp3YMwkbiLukqRShAKJuUnmq4MZFHqTyURPXkoIvmFVEIQ/vnE8M8D+D2QKH3XJjGY+4MEIeVSfY6w8vFc0rDlPk50tdYHgBQBEiCnu5NItT9DcKN6BBPcpkE1LQRqEY8t18mx6HgkunZEks8bjkNLCQ3hjki3GGDLjbZ5AgxRj284su0nJRjhEtZGlPbjpJNXGRGIJk88mYyASsikLJwRSspE0kplZUhj1SDI/N0Gpx4htJMRRsLPKf9qiePL97Aax+WZZKtoxDMClRHhMY9oTwt5UgLWk+c8T2xX8s8woChUGWNYXJruCW8miBkI8Lb0IB07zL15+YFAT9rRjsbGQVp40g/sz0cItfct73ueLx2f9rHOxyhtocjGZDR/higL8Y0R/w6M/th7SV82+p6PS8zf797U3z43hn8Gr3mXk7GcfLVxvGcIXMnCSHTvyCikbUFBQUFBQUFBQcGrFHNfegWiMiNnXACwpAaXokt1cQpONlCq9zESGDqSFs5vjIF2JK1xechZRpdkJRF9GUROmpYdNfaXdK7xbfLMBTDC11lGsgZpIuYK78rMn1r75tbYvcXtNJ9Ll1nYHQVPDPbk9fu2OtJpmCdJpIZy8jrR0xnCBjkJ78czWGFPiPG2PBlxDiudKYhbU/fkBGXtG250IsvMyeCgOoGRFI2w8GSxI177xCcSmQ1/SoDkpJRgjeOj0u8zvW3fICUo0jg3fIFgCoQS53i4JGY/vydNclKKhUP78mXD0xL4h3Y0hSB2rJuCZJ6AgBTWpyCsRKoQTqexBEnjjHn5sJPwC27UjRuObLfFMelECCRxnli26ypvPx+c+PB+rvr4oEPWvXu8ISNhuBv1znq1FzHd+V26MAYQzi9MuDeUIf07jG1CwQ2ifwuE5jZZKP44yXNnEpNJOHsPxXdR3s++j2XWz83x8OU332sI9fjxiDa+RkHaAukJA/5u4WGK8YKPG08L6SaNy8Pgabw+Px7x3WbHjQ9CxKhovPxeCg/cLDJnv30d+XszxEczYEl7WvK3tte/E/s1G+m7vR916R+J06DBde+oBk3a8iejb94++UeL/jR1o5YQl9Hd6P/0o0MhbQsKCgoKCgoKCgpepeAfXQsX/iPY+yNB4EmEVBqlhWxgBGoiIZOI31AkmFheSzC1HFV2fuMSBAXD1DCuveQ/plvBCQROqMpETYFxl1Vh4NUdMJUIMqpAMKqC9ioSqgqGq0uQyoWZmgTpypJVVJHgiSruZyRvJDdSxilKQTP1CIEgsuoJZKK2QDv1BhrS1FZlQlB5kKpFkLoHlahCaLlMWlZSDxkI0oEEhkEkRDKieSwYaf4LzkaMcE+TmBhdHaPN8++ISAwxolsw1QUCUUeqjGFFAhICSnjXSjMr2bxkiz+J83X4elxYiCghHdTecoI952wZH5aS3lHtgVXH7KWbrQ5V7SSdtZN01gbQhodNCGunK1UTkrARLl64e+DqgFOZIJw6BkS1DIT0PciRUEkZCUsQYUMpMd7GDMQZd8TeeANw/si9U/Hi46LBuIrldWnufWaEDHFG2PeqP44fVAAkm2GRTObPEsYqEKzxHRI3kew7Lx6H1/GEhjHMEJw7xaHtu0k59TCKxTfyhnLSMr3xubihZeuOJLCI77lRIqcC2wMtkzfvq34QeUFNqnF4zDsTOrY72YbRGG6cD56WYTR/Kdr8+X2ttPmo21hI24KCgoKCgoKCgoJXKd71yF0YEM2jywsXuaQPD0dpI7S4qbERivdEhjZ+nVFbWS33sLob/gy5XIy/gXz5luUFwTg1nhT0UBJZSWAjDYzRMFpBq9qSrlIGUlb3cW26hA4kbdvlSGIhHGHrdQpyCd/+pG3y/I1+ixJiwQgWdw3zC1g9rUJYg1umA9BglHIOEoGmea+JhHGUhDZJG/KxDA1v8AjpsVPPtIWjuo6QS/wiGqISguuXlU6ythmXu2lcv7JjvbapotHOJppzlLJxItY/3h9dbqDKGa+Cizd90pN8PL6lLjYmabuy9vMhcpeEJd0lYPVOOlcSoECoQM4FKhfOrw53idAhQkfby8crli+5KNahYOtM2uHc2Fbf/vhM/JXmKbZ8g4iI6651BC64btpUT61mYc3i28Ihv9+gIj4/mDRhWDIU3mnU9nITCHPVqvWweqGl0wstlXMrf1XW7VSQVQXVsbqhVaeCHOhAdTpQA5VzOzbNxcuB6FcDFWSn4+7vQFYqlMXrsW1QEE7XrZDWqJw3POj12sbRIvcacfPXGKvywxgYpxfaaA1T24u8v1dD92rn9kJYd3swvZ5N69o03WVXr8fia5i6TsryYVtf7ep2uqq1hjH27wi8cTLDJpd/IvZ8UWdsKtGc/B3wum3dhl4g2BMyXCWke/RLECflcwI9EOmeyGebmU7aOkhj+5Xf8pqL64g/qCdf07/xPNz27mu8B5H6o9E/X5b3I4134bT+2Nrwb/tPh4UCY3rAnx8bMd9/DGm7+nZHQqiBxd2MBYLnfn3e4m5CQUFBQUFBQUHBEoDVXnoOg0KOnHEhgTIXYFwhTydK8vJvphimLJyVgUhgpGU325P7h3sCAYHAhBAgYCCEBLnj/SQ8aasCeUukQaRgjAKhDvQQQcEwusiQjSNyfumkZkk5CV4mURskfJ2qhIYKBU8QthG26TPFb1GvR9B/3PqxSD+EG5ch9qzDxGXx/qM4/mf7NdQHT1IAkW4SLMwgPMnuJCPdswciVUYiKrhSQopI/AgpIaWybiCFlCWtQhwPK3afDP5Guc7vieFgNCkhdluHJo4QtY8BjOtfR0gZigbLyFh1IpEQYnFGW+LK2E0F0izetJThyC4i60dwWVsS8gQgEsmDCHYZt5YkESSsCgTlwn69GvKGtqwkqQZBO39NhBoGHbIrqiJCTQY9Rsh2yK4uH+ZEbUVuBTpXOr8naz2B7FbQsKcURnofmeyZeJx9RrvOvD8Suy4+z9dyHwGpRK1PByNy45Tq+8LrJ/PHx5A/eRxTcmGvx9eqPBEhztiLrCvhJE65azUZuzEQkGSN0QUXnkhXTr2NgSRr+M7KX7e0MLzH7PvGkJ3Dwm2qWWl+DQENQxogDbjZZl0nu0zWT66txJ7FP6eduyaqTsj6JP7xiZ0v4psPopHaPj7905vvRD5ziYdFHJmmuhA2asLrd44GxqIBspy8zUjbYAgTcfNwmGfjqhwo+ClujgoK4UDICmr3I+bnK7PNH+Pc3xu2o5H+3Ylu22pY2DAY3W+3/xjStqCgoKCgoKCgoODfDZMHJMYtSklbSpzEzQlV4qQsJ0AoIyNCnGjPx/MK0SxXsLaw9vX7GG6SGP5z1lmuh3AkhD1KLSGctJ73R1fBHe8W1lWQznVhHscvsHuEP9Id/f5Yt/fz4+ZAEO6MQmiUktipZCA/2h2PdCfHunXTnxzlNiaNN818hqV5P1Esl0yUKEyNX6UkWRgX/6zcOJiMlu6tFXrlrNQre3WUs2avUHWsdF9noEIlK1QdhcqHBypUHXcNpHGdAZfXhW35Ni7UUxFUpSCVgFSwrm+fEJHQ5ROOPFkLZkjMWbvX1o0W6a3Enq416p6GrmvUPY26V6PuWrfXrVH3auietn4X9n6fXndr1Mber3u+nFimrnVSp3FSi8ZLMJpIzIOt8/7rKU5QJnsc/SKLD+GoY9PH5ff4NQoB1AA0gC5bB8k9vkzWwDZKhse1vS94XKL3F/E9FfwsXxpm76ysnLYyhqsnj++H8D7060oQSFPQJWyNtNWJ7mBP4GkZ1Sb4sHZqDoLfGYvzKhKsoTivMkFCizSPESKUx+si5gYjccnmVBOJMUxwvept+tWjsUpv1NIbx1RkgtqDxG+i/nVvIFNlxi+TMDNGF3SD+/ZRpvMW2TxM/nBx8ndRUogLv6Zhyd0lvPSFhS4MLhlFvkLaFhQUFBQUFBQUFLxK8eyQweCiFQ4JyD+TcqKB+wMxh8zNyQ30J0Ea96KdyGhr23CI9VmVCyQAYQgmnP6MhGkU8hSJKyBgTx5zwjUlW2NaHs/LzoxkgZFaGQnYV5CT918g2hjJnflN5gZJP4pHttvyef2eef6mHlBHIhPra08kUfosKZnhEo2l4MnAGa4SMMKSudoRpELIoNM0ELver+xxcKkkFAsLKaCUDGmBDOb3uHxSisQfSORQv4gks5e6dWOWTzb/3JwE9aSo8X4T/cYwAlX7MPc70tcYaJ2GTRKOJKxhZKyXujWsHX4eMEY9CM312wzxEngmSP2hYYQqN2Tl/SaX5uNxjvDLJf5MSzlcqhDM3zR4hcSfIxpQ4sbzEAhCMLIwN+THicPEWJ/Jjfhxw33NuMbVqJuPyzyQVmzRRUI5EqY+0W9p+TGO2suDDK67z7rGx4W+5+lW9pYbbEzGFjlxi1A3m2X2HU2EYMEKBCMM7PkIK11NZGCctC4JG3bmKd3cJBCxNhK5dIrzlfJnZVKujc60a5tvpPVDyDfMsAyHkfIMW3Zr4nB638dWP/kcIvrDmAJsnOP6NOE94FzE90KQDGZ+H2/vlcn9YSMAaZmhzmyO8TY2nmEhQ5se8NeiHqGgoKCgoKCgoKDg3xZzBfpKIy105IQpJ0QQWVqb5vxt9zAJy5A3J3mzfC1NaA2PFqmwU/bJJpoSUp5UbcYxv2v3cFKGQCRnkzqzsnKM/NHcHs77fzhSvEGe95EeRFZOOznf0pZhniF/AE/6tn1Oj9RnvJ99OL+nbXxTfbotxHKf8Rntcmwdp2H6iY9BWx6ilvxojm2a1t6esa6jnBjNCVV+BDuRuGyR6DROatNk0p3RoBWX3kzDkdiRrB0yIYiikasmVRXoOEbQRnIWkYDlkpwm93NJTJ1IZSaSnkyKs1V60xvTChKjnORlxK3baRrhoHoDwjGH9hnt5pHbTYiJzi/IqrEQwhrVMs64loSBcaoOlBHQEk5Xr1VtbaRzhbRKCQTBSCfxLwRIeNc4UteT6Ww+5e32My6Q1m3Stqzf/PjwPmf9q5iUrHJSswpOMtf1uwI5tR/eBVO14fuQh1v6u3XdjJEaDER2VnK+N9QS15aPxwkel0Y07xkmiW13hDXG155Buj4TCW8hYWR8V2j3rtCCSXV7ae/wPvGS4SLJ03jncPI3IY0jkQws2t9TpLvAX0fOV0jbgoKCgoKCgoKCglcp3vHmVTCxWhQ/6b1UIILribREApMdgTdOei8cwzfO8E7LMXoe15pGzSP9uRX3XHKUS3MOR2fkhKonZKWPE05lgnAStLDSssFKvXcR/SpLi2GeP80jWJxvg+DtEkA4Hs4angh1hWdl6hES11ueb9GzSV7fKDeU1N+oEr+fpxErx/ujxG0clzaicaQx8v6cHA99xfpLsnjep5Llk8jGut99ferIyd028r0NI5HdYbxYmmHxJutDrhuVh+19ojn+vizRHBOwengbOZpENSPRAEci8nHKJMjZmmqNC2PSjA/jEtaHSMbMrxOEMeL+2HgxzCj50Ujmp3/nhf7JpNYzl893LoEe3k+gZH3E8WsrN21Ta/uGgZcU5i9DP3ejn/VK4PJEMoYhns95X0ZwY98KVlheHi8zVB8T8pgWpC/2+A5MN/f8Zg8fw+Q9Gf6mUeryshp9zu5j7Qh3jvA3h7eXk5ztGx/CSSeLqGZCtGx2hA0RFcLaGRvTUiZxlKnA0Fl5XLK1sfkBRqzb5iIdK3KbHu6pPKFNOcEeNyDyzQ+RE+n5xkatUVEv2dwImx+svAaB79uQbMYwWXL+DlsE6JLGd0aRr5C2BQUFBQUFBQUFBa9SLL/jjlhq3LiFXxH7sM2NUOVHtK1+TntprZ2eTt246toaTqrr2sb1bJxPs/nqoG/T694UzkK49RsIYwBXN4w9hhwZQ0ezUP9P6HAMV0QjV0LYo/fR8rp0hq+c6w1UCQkwi+fWOrs1bsWNWCHkF2lYSoAZuPKGrSCYXlTPHAfCQwxDakRyhgLbE/sgGJzyfeOMXKX+1GhVWxwoz0MxD5lgTCuUS2n9kQRhZFIfcCNfAiLTcSsgBVNv4FQaBHUIiqtFsDpwk3ilEn/MG+NDuYqVzdUlhDnixsyPk2jSgoEw8mOUqUUwzhhYUFng1pMOqg6cCgTtXR3ifDj3h7ysjFCmMc5gGaubuJoEp8uWIpnVd5yYy0kQO25OUlXAESeObA1xTaJcsnBCriMl3EdNrvu51LJyRMsMnF9Cvc1AmQ/z/IKFBTLCPWMffTBoBRglosoO9z6RsIb13JyNqj9k6ufqQ8JaUjGcrSuZrDcV8giueoSVH9aPfzf6dSPyd102KIzoBpunUf9yqv4jn/v536mwJrRm60y35kncsIbi+olr2gCG/c0cDZMLETZS7FMy6XARVQlYcjbqH9YJgctJWhV0EAe3JW87eZsTt00VFl4NSuuTuPdFrlokVSvSVCci+7kNyfMY34jjuoVzdSOsfvj3UvyBs8gIWwCoqQaeGznffwxp+9efnY5JkyYt7mYUFBQUFBQUFBQULDAsM/MgLL2wf+NySSSiaNXeW6ivNUxdw9S1JVl7zt+tobtd6G4PuttD3e1CD3VRh2vIpjl/PdRFPde6yoV9ftnrQQ51Ibo9CFcmej2gW4N6Pci6BmpL5opaA9q2DbAEonsA/jgWXmJIWN2ZcJaz7aWsdJFSIKlglALJCqQUjKpgVAWqnOvCpupYf9UJYZuvE/Nl90RXwUhl6xMKpKR1HcnrJZ28+G/jCKz/+PQfpGQgjP0YhnFW1bU9HiyMhtA1hNaQpobQNWRdQxgN6f3a9qt0Lg8LrSHrXppXu3K0dm5t9XgaDaFdnUY73Z6ObAclH8xhWMLwCMARs0J5HbWOXK0UZFU5A2TOaNhAx7reP9BBZ7CDamAA1WAH1eAAOoPO3+mgGjdg0wcH0Eny2HurgU4sq+P8/nJGyWSlIJVybfNkfKrnNgwR2+ygQJjaNWQNgVljYbquYWqNultD93qouz3obo3araN6qIfekHV1r4feUA/1UNfFpek+vy/HXrVdkz27XsOarT1RZV3SOujC9ZsAnGPP9w4aEsetxHXoDBghAgHpiV7jCVwiS8ZSk4CNfmohaam1/iD5lzc2R4v0ak7g+svzcJycbSN2TRbXmreFACbXT/3qzNvZhvY15DYm2tZQp0I10IF0bsXXkVs7dg0NWEN+bE2FeLZ+qsEBaxiQr6dOBVVVUB27fizpqyAYyeuJXE8222eNGwiUbGy4eRs2+rSb0874Hpv3fA3VXbtOdLcOa8evpeDvxri0rJ4L12HN+jrjGrJ++M0yZtAvnVtcp6pIj+v7OCBI4sbZ3zp1+4ZBQbg6RHhNGD4tSMUKAavdV4TNBbg2CLIZiSiS63lVrsz4d8q7+QJz5Sabd5SkJ2kU88ToNI2SfHmdLb8DRtiQWlgg3QWeu3vEfP8xpG1BQUFBQUFBQUHBvxuueM+HMK7qLIKaKPEGqSEviecln4IkJ6zEJZfaMyZIQQXSihNYPJ5/5PJ8/MOXxQVJQCbRFD6Osw+yRKqOS9sYEz4uKfnIZMZ5nMQTvJQRk4INRpe4C2GJ4Eacz4fk3lgXwtd1NJjESdrh5IGaH6gi6QtmvIhJHMFJQMY8hhHAeb7+cQD3g+VBVnc2r1qejIgATdDCQOjYX4n0rZeIZkRpYiBMRonCxO/T+vlZvrbykbi+Xfk4RW9KEth/gsQtl2ZlkoNRWpmRvclaohHWVHPdcClaXnZYy2F9M7KE2kaq+WCNWdlCxCdjnSn/FH38IcwYp9b0tjpGyjASqNXbNy4ng1qoo9ZwzhuNpq7hEKgtIrt3JQxAVo8sagJJA0gNEjWgVNiognIbVm4DCcptJKkKVDlXcTdNQ1ualLEcaTfC4OuT7v0o+aaUtO/axqmCOBHzv0GNtWPi3x8TTgb4tWOcUT4er2M4GO6TIDMAYyqQGYz3w4Aq24fUydZZvpbC36W0/TmCSSz/ngSYrtwoEerjwlF/RB3Hkuw90uWzG3Q1FBE6PC8h5mHSpzLUmak18O2jls0P8u0faZ7OCzE63Itn+LKH52EXD0mbo0caPxpFvkLaFhQUFBQUFBQUFLxK8YfHn8OAXHQ6bdMPtYwUZa5gH9Se1MuJPS9OFuLaCMA2IpDXkxGCre3K4OWUWp8xIRbHjvk5Wrkoj2WOBkvGZ61DNr7Eo//NsaQ+43CkYnhbCJ4v6sAkRv14CcPcOFi07I6owoTl6Z/mKvHtEFl4jIjrkpNWkcRiT8aOhHOSK6aFllJaRqJOIjxBSpLZMmJbhntf5Gnhlek2CkhY1xhjjUMZZiRMSBhpYISO+lGlgpZ1FlbBWJz1czfNY8tUaBigExIk86P3blOLzYPsaRo7IHwTKj5w8+9N/rfGb0ylf5/YZhUMGn+7wt83nxexrjBUceLHzQZCvqHj8ztZ1kjQImYPfyc9kUpMDyx5va/94rwe2CyuxVVEzMBeRuYmBG4+n/9zEIYEfF16n++PFqnjxn0WQ9CjqreQtgUFBQUFBQUFBQULEKeccgquvvpqPPTQQxg/fjze+ta34tRTT8XrX//6kGfu3Ln4xCc+ge985zsYGhrC9OnT8ZWvfAUrrrjimOr60/s+gWrcxAX9CC2g9OOUvO5Ye9QdWrOj8O5YvK4hansEX+geRO2O0tc9dxzfxgkXF8Pe7+/puTJ8efxiR++1Btyx+9i2+BE+Vowkyce5hH4Sglw6cPg8/evpFzcvGKkXGunUJ36E8vrWw8ZhSSUjlwSMeZxc5HBE6rzUM9r7uJ7LaDwpGjHiFuKDLs7MGryP4waTrL5OFfR28nxBB6cUiSX5aH0+bQMnBS2v1q6P05NTQCSpuAEjCUqMJlnCixlJIgp+ZQwU6WAkSbH44cLc6FJO0nFJyigVGcne/uPKKaNIMdnXOllGOLgARC6BbUBWuaqTKBWOswwUNRzNCQJFlxRIOuOR5MbIuSQkjGFGrkQcn8TYFRubMOMyIpPrRPU6UrmhKmlcPxvt+lq7OOeSTuLS9DiGqZ+VzwxoCcT2xHGK7R5ulNow2vf/WIj8+alnUWCs76aF/feEr55IwAoW37/32ghbwNP0I6OQtgUFBQUFBQUFBQULED//+c9x6KGHYvPNN0dd1/j0pz+NnXfeGQ888AAmTrQE68c//nH88Ic/xFVXXYXJkyfjsMMOw5577on//d//HVNd+7z0a4yvF5UhMnL/UzhWHVQUcINV2h03dXpljXPJ6fij2vlr7fI4fx3jQprTU+vvT8ozmqlVMIxY8CobDGgUn3Le6E1wuaEr50pp9UFaAzveSI+wxqq43xm5in6RxmV5pfRlxDK5cR7bBqRH+gEnsJVJbfmxCQJh/Jg9EqNx1u/1QRIzdOUMymkKxqu4MSutCabm8ZQYudI6lhmNaVHQi2qNXCE7ygyE48MZQxMs1ntVBF43pxSJDlmvozNxna5Zr3c2ulVLWtXI59NFKDMrX0oI5VUqyFb1CXyIiK8hPja+b/yRbc103XrdmLUzKlZ7I3xOX2cI66jPs6dDWsjHdH6GMnTUvenrI+3HKDWqFIi7dHiYn6WRlyj00oYClsoDnEUlBNUSzg8jgdBn7gqqKWQSx/MIkd+H6AcL+3mUrBnRfJCcUGNrKi4s7m9exMOGp8Xj+s37TJI3KcPXn8Sh6WZIl5KX1vRtF4AwiboWmEhmB73Zrv8TXdqsz6k1rpne6vf1uhfa6NXAUOaNkqhJnyQSsZmkbC5RG+LzOBM3KVvikvLYOAk+Z4YZo+aT2WfnmyBe6jgS2mwTImxIyCyuvyGx6LL4fHOjpc7QruDvNz79nq1PHzRe/HzNJZmYk5XV2AzM72/W0dyQXNi0bxPa1MA/HhsxXyFtCwoKCgoKCgoKChYgbrjhhiR88cUXY8qUKbjnnnuwzTbb4Pnnn8c3v/lNXHHFFdhhhx0AABdddBE22GAD3HnnnXjzm9886rq2049iKT2wQNvfF+GbNJKA3mJ3elnyTxsDHdzUX/s4YmEyqKnd1UTWhb+snkLvOi2DzsAPObrWG/DpT91yolbKSJQmpGplraOrSqKqrAGsqqNQebfj0joKVadCp6NQDdj4Tqey8QMKnY7qf29lXeVcKT3xK0I7orV1RNIrG6BA1vqx0Rk56wnYWkPXBjVz617qr3savW4d/T2Nulej7mrUtbH+Xswb7qsNtAvbOm25WhvA64rUJghAk5P6y0lBkBdStiQ2pCVooSxZmhhRckaNVMcbIlPBEFkwpDTQcQaSvCEyZ0RpgBlYCsaTnMuMj1UD3IBSFQ0oVSqSxzI3RGbb3zo+hhGl2pOyzIiS1omhI24AKVxD1phYPdRFr+sMKHWjYbIkX+2MjzljTLpXR0NkCQnMDJEJr/vTSYtRO1VjpVPtP15SVYbj3jZNCjt3Jdl1Z/0CSsDq0hTO79MEoISAhI3L0yRLC3EQkdv1ft+GZMMDrc/hpp11KRJA3u+NhHlDYqbFb+BcAjRFvyGKYZY/z2OysvL6wjs4aWOTcmp7tnCEXxAEWWNvEHBSq5HYjvy3yNy2OOYm94s0f1YOWD3e39725nuubazcSLGxo/RvVqPfKHUbeag9X5/y+DwJbWkQg21P4cOeJPV+Trj6cJQ2NzINR9dJpkvVCCd5pcok1qMbVFe0kLyJGovwHP3HKInLidgWYjshvBvpbWnD5W+Lz9vXRvAuGpDuAv8YOV8hbQsKCgoKCgoKCgoWIp5//nkAwHLLLQcAuOeee9Dr9fC2t70t5Fl//fWx+uqr44477mglbYeGhjA0NBTCL7zwAgDgqX2OxEtLLb0wm29BnrBJJWuJS9E64sfUtZOatcSQ6fZgej3obg+m24Pudp2/a+OHfFwXeqgL0+0mcfb+Grrn7u/Z8kyvtlddg1zdZKLV+yj96z/sRvoya6FyEokwJ/UnZXTDpQCpHKno/M4oj1AVhDPoY8MKoqogKgVUCqJSEB1pXSfZmV7MSJb0EoaM5BCCsxae5bESX8pAaIIwBCENhDSA0IBQgNAQQgHQEJAQJCFgrGVwYy9RAcL73a1QgDBwzwzLwlkLOJYMEsSkIE3ovyB9CnJ9TMHpO+2cFJshWDUYTgLNHrW3xJAUngQUdii83xN90vstMe9dH6e83xHiPuzjOJkY6gnhPsSWn0eMILRcQZADayeAAoGX+gOJZwjaxwU/op+la9OSz2+y8DCrKyGhKOrWlFF+rX3VtBBuRHYekB9mR0LaPqG0z1i/Cbi+zeL65e0XD5fG28SXzHBocDzc9X2UjyMoLEOD5vi2xYXl2hIX/WzOIF3q3G19Bo8gLemJN2kNgiWu1TnrjZAZ7yoFIysYpUDONaqCUVXI58PeT8Fv7/VGzkKZoZ60DaF97J2bkoJ+Trr3G1J1PcKrxyGr2sCr7LEGuZyrNaSpIZkrjIbUtb2cXzC/j7f5dLNME9UDSS+t69vD2jrs3yDBPSJJEJ4kFXGep+/V+DdJiHghbCKpxJVuvK3BRZ9m48PftyBhbclj2aLCAog6qfnLvGFMzY8VvI5cp8qCqZbgaiy469VUNFRacJUXXgWJ8zfKoqivVxiTqhfh88jNrRFeDwsMXdK4chT5CmlbUFBQUFBQUFBQsJBgjMHHPvYxTJs2DRtvvDEA4IknnsDAwACWWWaZJO+KK66IJ554orWcU045BSeccEIjfuj2X6MaP36Bt7sVxI6yE0XVBJpgDD9izaT1GJFrwnFtJ9nX0zCaSfo5qT9TR9e4eH9E3BPCXnWCV68Q1SUQoA3sceP0yHGfh4LV0+itjVuJT0PCqoDQBpDC1iUlSAkYJWGUhFYStZfCVQKVUuh6aVxlpWe536tIUJVExfwh3qtOkF6ylknXMsnNeAS/8Sip1BjBWU736hC8BLRVgaCNVWegg+oDK4Vba+MkY51ErQvX7oh+7aRmdW1QOynampXhpWq1ieoWfJ2GtcdLA3sptb7TDghqNrkUlYHtC4KVrCRYMtdKbVo+WYsobRnIVkRSMEhsjpAnEImiKbnZJAoBJ7fY93m8VJ4Pt5G4keTzBKt7RiaNSdRfMrM1HvGenCw0FEeBE4iuu3nvBwSahuKzUxJvCRBuTGokQiRJpxghxngBjjBqI26JBzJkewnJvkL+HnF5DSvTz9fGY1Aa5hAYPo2GCY8KBAhnfMz2j1N/IQggY4lToyE9eZqQqY5clRmxm8Vz14g0DJETxJEQ9CRyJGntgvJuc5DI9Tt3c9UGnrwlRuQ6nesUydzgtsTJ1nRLCEe/059OnKCNumxTNQ0jj1H75HT6h90mCOCmodNBbDdH3GolN6aIddt3rP3bBjIgI0DSxRmA3MuTDEDSucL5IezfFEj3tyVTmQA40jabwcmuB/8bzIy/GX/UIu1LTroqkxK1iry+YadbOBC3LXFkGqRwrvOYE7a5Xuj0qdiLKPHzcB4/MiqvNmbEfAUFBQUFBQUFBQUFCwWHHnoofv/73+OXv/zlfJVzzDHH4IgjjgjhF154Aautthp6Xz4HXanmt5mjRko08eOiToNsTi65eE86xWPDaZo/Iqzb8jg3EpKMlHSNSni/jGEa7luZ3IcaadsWTzoZRNJOcxKPk3uIR7iFABSQSGEqRFJQiXZSMPfnUoaNo92IJGHr87h/iIXbJP1GIvhC/7P41qPdSMeVHw0fjiAk1paRxsinc4KQfD+4sTbk+ogo9J0lpyxpJ4M/62OWty0uIWfzeDcYnCQE94s0HIm/NJy4vH9YH/Fx5PGmLY7n9f3e534eD5bW1r428DQBv57yjmjOV96HnmTnY5Cvhcba6BMXxofHIXBdKXE7ApI+cR5Hv7WPBUSDACcie6ycnPC6T3dx9j6K98POaSNY2b7xbmDILQROE7WNUfqMhJTobM/X7CfbobzfPEfH8zTjYnmCxfD4Rt0tzxDi0y5oBbX4m3OZ+sQjvFdSFQv98tGw9bS1abj2prFt5GBUIUOgSNgG4tYE0hXGPYeEJebd3eG9IAlEEkRWRYLdpPRG4bx6BAFjuFoEpjMXozPmFyWhkRj0M460laHdxsVZ0tanC6ez3rj4qMM+nqKxxLO25Xid0a6sNI5cb7a81Ub645Pc41cAH5vcjWk81/ygkLYFBQUFBQUFBQUFCwGHHXYYfvCDH+C2227DqquuGuJXWmkldLtdzJkzJ5G2ffLJJ7HSSiu1ljU4OIjBwcFG/OTVJmFitWh+0scPVKYXkPjR6kw3o3Hkq6H0+LZJ47SX/jTRrw1CmpfO9PGC3HF/Ighj64Kr1zMpRLHFUUqz/3OFzy0WME5Kz99P7gOUhIAhsqQRWVLXk0gS5MhdYuQutZJQXu+mT8sJ25R0ykgP5J44QE2yqZ0IzPVktoVNHqaUjM3zEjXJ2pwc5G3g7R0JDYKKWBwjcIVLC8Sdj3fj5T+nRUa4Cq+PlXWt7fcsfgQCsKlruM/zZAxUgyBi45mvvRCf9SONJo8n/3h9fcZjtGPj8/LxsWslPgwByXrypLtVoBHHSrJximSuXwvUQqK3qFpwzGQ+np5kH8szIe9P50nX1PCEuGmJGy4+LwNJXaxtzG1te4A7xt6mJiFTl2CYNKzJ1CZEV4V8hqlT4PmMVKnahaRMmdYteJvcqCWEYEpNe1IQSI+5RynXKGkrmSSnl54NLlOjwNUdSCZtG/1RWteXKZmEqGDStolahNDO4UbLP5TILp/E9QZHVTNeNYI1hOhVInBVCF4dQpR89vkkk46WTLq6qR4hSkKnhsnaidtI2HqXnGQrhb6RFCVeE1UGkqk2EBJCODUIQrvn1hBGQEBb/dWuYmHce1kCwrC1LwC7HeI39Fq2OvrterQPUIu/Xz5f33AY3Ru2kLYFBQUFBQUFBQUFCxBEhMMPPxzXXHMNfvazn2GttdZK0qdOnYpOp4NbbrkF7373uwEADz/8MP7617/iLW95y5jqemypFTCh01lgbR8OCYFBnJCIR/LD8XdC1J3JCNmgY9Nk8cFQWZoejtizciyBm9ZnTKYWAKlxGU5KcfSTMuMSZgkh5IjWIAWbSMVGAzyBZAoStG33CCZlyIz/tNTN29pK2IYB4sH40NEf+8UOJ0VSt81PvB+bcXDxQc1BCDu/iHGWSotMa8Pw2HAQWb8E0sL1Xav6CK5Wwvu9Mbd4T8jj47O8eZlcPQU3NibcRIjj0+eDnZOmbL6GNcX7nF/euBz3m5hukjiTqMbI86RlpvUKP55wxOsYxokbJxKBfEv7x/p5PCegnB9pXOK6vm3P7yeLWzMsf7ivbXLFJ0ifJ2Gz2ZrxY+fWBEI/xTWSprM10ZrGXKT5/Zr18cnaGYkI7PucjBT0/QgRSDp4dQVMbzc53d2U+JVL837F/Ew9AlOzkKpekKMgbUVsun+HAWEzxuu9tsSoI0uZagSdHb9vqEJohCNR25ovU7MAyvXXNglbTmL2G5pIhDJyVAinXsIbBHPEd0KYy0iSO9cEl8cpkHKkrrCkrnTkrnFlKEe0G5kS6hTCcZ6EccqnlhujoG6AkbWcROfEt3SkuSfJJRlIrZ1qBB39uk7ign5bnsfIWI7RkEZYolcIN06wLrwOd/8q6vMjgT0ctYYozlO4Z2brK81lfQK5rubhUUjbgoKCgoKCgoKCggWIQw89FFdccQWuu+46LL300kFP7eTJkzF+/HhMnjwZ73//+3HEEUdgueWWw6RJk3D44YfjLW95S6sRsuHwmXFbQXbGLYzHGAaOpGBEICchWskL9zEb9etxl/lNTOP35PltfWm4QW4AkWTmbQ9IP5iihCQjlGxCJHsS0qm/X+RpbXFt/qSOlrZwAqMFQaqUuK6+qGPRS4YlBlv4B7OTRvMfwkobSBM/lJX/WCYDpXWS138oR8MxGsKQc7kxmNieSLakoxRGwvWPlCIYY5NKQSoJVSmoSkFWCqpToepUDbca6KAa7Fh3oIPOoA13BjpQA9atBjvoDA6EvJ3kngqqqqzLylZVFeqWlbRtCvqHZSCEG8QtI0uNccQq0wGtaw3d87qfNWqn57nu1qh7PesO9VB37dUbssb+ekNd1EM99Lo91ENd9IZiet3toXb56m4PNXN1uGyduvZtse3h7YzrLOc2REa6pcatItGkQMyolZGVDasqxnmDVqrD/BU0iyNu+IobvwqGrxSrt2nsKrSVrS02QAABCQlo/BpKyb0omemNWXnjVsx4VXL10rBpy6NDfNPoVYs+1TaCMFtD/rm83k6bpuOrxr1d4qYRkg2kND5X3cLS3QaKzMJpefE9y+uK7RWNIWmj1IOaCkd2GiFgYI0TaliCU7t4LQRqCGghUYvo1kK6K8b1QhzLU0nUQqF2ZdZC2jKdq13Z3s/b4ttGWZvzp4sbP/FvhQgbR9K9A2U0GKacBK1y5KszcCmltG64ZExTCpLlrVjepEwXbyVyRcMN7Wt7v/mn8u8K986Hm7Nw6wfaGoSzlzX6Jmp36Rqoa8i6hqh78epFV9a9mD9J92FWpq5DPXDrSWirVsEa2TROz66fXHENRZo1BcWZGnyR0E1pXSS5+Ewf/WZYIW0LCgoKCgoKCgoKFiAuuOACAMB2222XxF900UWYNWsWAOCss86ClBLvfve7MTQ0hOnTp+MrX/nKmOt65cV/QlRNtQkLFUxqKLHezSVqQAlRx8kPflzVE4gik77J44Pl5+TelJBstIdLOPUTtfVgTIHgkdkHtmgwCjmZmn6Es0BKCvfJ42pp1NvmbZDOUaw2hr20k5N8auujxIo2H79MQmp4f5thl3xM0BiTtiPDCUnj8pqgDkPAaAMpBLQUjCSVgdiVyhIP0vuTyxqEC3k8AawkIznSfL4O6/dlRxI5EiyMzEjGOwWXcuYStOQkZI2xmxfBdQb+ApnK/NoZ4dOMaDUhrNN8wRhcWg6vKxDKfmPEt22k9RM2TJzfGEeoAUYYEEmnXsPASA1jFIysYbSCZkfrjVTQjsDV0qUpFycVtFJBatD4dCZJaJgRLOMkBI3gR/FTaUG+cqJcHCdt+0sJ+g0PQdEIUirhp6F0nWx2WINJNZMSrFne5uYHGQ1JZAkm9+70UqTwBp0ysjaOQgZGHnqCPZLXPixBkh+H55KWMkh9JlKyIU2kRsyGKSvUh1TKlrezr6R6spbYk+YbdWHz0K+5dCMR6CfhbF1JhI4hdKgeXqKabV5yKeykLX5E+q0hwUg9/v7w8YEsjRtZkTiVCYmaEL5CAMzv02y+dhK2qX7BNjBpz4jjw97txMci/l1I5rHJyF2KJC/3p66OUtU+bNKywr3+bxH387VDbAM6Dkmrn4eJ+SMJKxr5mrl96uiI20LaFhQUFBQUFBQUFCxAjOY48bhx43D++efj/PPPn6+66rkvQVT1fJUxFuRkbStpx3XWcYLDWYOWgeTwcamEpqI83CwnsQrtCV2Tk41O16UnYBZkH2S+UQSHLU2kwYUPavOOPG8bOfpEcBopZPEk9SjImH4QvGDjZddM0n8i69NEvUSQ+OPEeSTKE9mpJAxG0KePE/K3tTcL9+vhVJVFlp8RP5EH8cQvux+Me/AxPJyVn+u25eX71pMQw85JCvlifn+82xsuCi68XmQrvWvgjQ0aqwZFChihoGUNoyW0sCSslqnfuOPbPs4IFi9EPDoe6pcNA0oJYcv3RFwHpO85uI0MBClx+w6i9B0U3k0U32HMur1/t6XvvvR9mLzr4PRiw+u6FpBwmwhEECTC+02EgW6+57xEMUEgl4g2jEg1wuukdSS4aB6192S6DVc2LY9TTSLeOPUIaZjpz+WkbkaqJwQuxedLiXX2t8dvDjI9ttLros2O06dEex1PEhjdyKeY7tv0ZEKm57ZlYwtsjEaWsGxKG4cg39wTzfx8A7HhTwjXPnnTKly4+QIY1d8ragtmxDWXauW/m9jLKjnR49JikBK3UQd/x+W/y0bxOy0WNNL7PSdkFywKaVtQUFBQUFBQUFDwKsXy674RcmDCIqgp/6DKVBEwNQbBb6z1Zu1IGXKSL9bVadg469AU/f5+GI2oOoGVE6RpouoErqaBS1qNTqJFJE78iOWsjv+8ZeRjn7j4kZ1JTPncyZd2Xpdo/TJuSPr2BWXfpJyxo+wj1n/wtn0c84/i7D6fHuLYnEjK5x/kaTtGh6z/RIvOU3+E10n6eb83uuOPFSeGetrSW+KjoR8vnSZZ3VxazbeVz4fGsLT0metb5nIVIl4C1899bzU9cRO/bo1Hcg8vs031CGvTKNaQJ2+jk64Nvg5iH/nxbItrCTf8SONb1iSy9eSP66dp+cPkzxn1DhuenvdN2zunIc3XEh7xXhZO2scJsJE2pdK+jnM26q71cxx83st8vVhdtd7AFfcLp9PWr6PEz9aUkhIVW6dI1lMcx5yk5OMRuyn2n1enE/z+74fbJIAxqIn9bcn+zpCT1gxrKAk7v//7xP9uOUnRsJ7YOFM+xnFGZUSpfX9IIYIkv5T2BIBy0v1VJaGUQqUUqkqhU3G3Qqdj0zod6x+oquCvOlUa9vkqm+bL8mVb19XrTiUoFU8ZeN3fyckC9mz277V3DUi7PvVqV5z6F1PX9ur1YHredf5uD7rXg+l2obve7cIM9aC9v1fHdJ43Ka+G0TVMrwbVGkZ7V7O2xXdhc/3zOchJ3OEJ3fQe0eIfPQpp+yrEspsftribsEDx3K/PW9xNKCgoKCgoKCh4VULXPZDsLpK6RE4gZISDP9YIL2Hkw+EooyNgvV675Eijbvopiw/HJ3UsNzn+mB19zNs5mmdsIW4jB9Xmzwm6GN+Wd/h7khakZC5r4Sg5W/9P+uSJdGUkiIjdw4lZTrYmUp3E4/K8TZI2JrHWcAJzOAQJ14x0ArJjvOzILyemOKEbyNwszPLF48aRTMpJrliHbx8nH5NRbEWzXzPi1hNTiU7nfmRuTPNxw+ejQC7lx8O5MTpOIrbMJD5ACYHqj2SDE3LeoFUgAh1p5w0jSXePVCEOipGESrG0SAhCSkCplvKzujkRnGykuPazScnnf0K0ho0jCu8eT9zBtPktSQWjAe0JQhbnCCNLDBKg03uD3xOQ/D1n0vmSkL19x8g+MCHri6Dn1/dhVHMArxJBSoAZEvNGxpJ0b3RMpH4T4nx5fmyYmgRPHrN5RCO86wR/brZhKJjf/y1K/1bYsPRH7Unb/gx/c/jfJxP+DiV/g9iGIf+7l9af/o0UfF7lzyKi6gNrvFIEw4ieKPXkrVKRzFVKonKqXCofryLpWjmVL6Jy+qQriVo5Pc+VhFYKlZLoKRXKC2Uz8jgQtQ3CFgjvQb+CKPyTErfGvXNyAldrmJq7ntD15C67eqnf3uPD1p/c7/yWnLXqYkhHIp5Mtpba1k3yduDvduHiiMW1kbIixM8bZVtI24KCgoKCgoKCgoJXLeY+/8wiMUQWPjSoTTVCqpM2MXaVGKnSiUVopbU1huWM7wTDVpkeSGnq9Fgr0xspTDSo1abnlhu7ajzLSM/K/ImwbRKf0j6Mt2Nx8aO2LV+MF33rG66NOdo+PfO4SMDaf6lvGnMpzUsj5ueSZcO3D9SeJhqePumtYdG3HxN/3zxpQr/7R2pTP4xqnFhkUIHA0/v0fUyj1r5Pyx25XcPCSWoG15Os7hJSAZUCqgqiqoCqA9GpgE4HQnQA1YGoOja9MwAx0AE60roDAyzOuVUHotOx93O3qmy5VQWhKlt/pQLhC6Vc+5iEaZskJydok8sSS3BkEGoN1D1QzxpOol4P6PVAdW3dXg/odUHdHqjXBbo9ULfr4siW061tWq8HMj3A9JrlaA3UdaxXW0NOjfYlkrnNNRfVDliFIlx1hHF+72rJ/EEdhVdV4VypnKEv5cLteb1eYc3KN6F81wZ4lQ2Ifju5rMs4MU+VCaChQ1sy16vN8W5QVRHUUlhXEfMzFRaKp+duKIMSFT0+HNoDp16DE7d+2Yx2eY0UHtU7zpqeM8OUxfYIx/w3Z7QY9p1HzTnbzNP+Pmv4qT1+uLiR4cnZlHptUZqT1SBCTErbjmrLEkAhbQsKCgoKCgoKCgpetfh/v7sBg3IR/6Tn0prZkV1+nDo12IJUMqxFui+RNMxcns+6SO91bWhrU6P5jXAqgZbovxQ5uSGjkaNAPsjEz908nhLCQjJDSTGc6wVF1h6LjMxwDxYIDfJuf/3DMrhOT6cn250/JeB1ordTmExnMSftWXpqxCm2B4k/PM0w48VIHEbumDBGmQ5Tl8b7mus8Na0EUp4nG3chGnW0Ek2McOr3RF7qro14imRPk4DyOjtTosiPA4vP8ximi5URS5LPBd4G1q6RxgeAPR5uH8pJ+gIwAGkCCQOqDUgakNIgpWGkAqkeqKpgVAVyl1GVi+tYt6pAqpO5Kr2ncn6pXJzVp+qlQUnKIPXp1xeEdMsofbIoDek2e7iBJDfHhfEW6JmrrXExa6m+dmFrvd66Pci6htDWlTpat7d+n15nZemsPl9/espAjDA8fjz9u1kGdk7HuSrCzGzok42uaImLbniHtuVB1B+c14MsfayIp0D4GLK3Rngfstqz+c3XJF+b7ffx8tBcJzx+PtG2qZK89luqaHRj6I+2RHbPKJo7L0M02l7om4/6pw1X9vz3PofI3JHzxrHKNa37uJxGb0chbQsKCgoKCgoKCgpepVjlub9jnFCLtM5cWo+HLTdLzN8eb2j4ONPn3n7xYPU12jjGZyPAEnGMjIvHeCNJyC2qB8JPcpI2GkqKxn1EX1KXMoIwN86TksuR+OBIyANOvmUSyJIMjHcd2UrCElNExtZnbL3SeKbFyQ8bASGNHQzpBg722CxBwJCAdNJ80rXKNsuxytHxqSN+eHPSxwAgcJKWEa5SOIm+1EBVKiHojVilUoI2nwr5GhKHOdnbIHARCXcgiMDx57QRblw4MQtO0KbG/JSJRKwibqhvGCnBRKJQB6nAIGGYEO4ikrkwEBC2fmHHXAi76dKXqiCAHHsV1rOxBsaI7LQxLo/RBCMJRhkYaeyRZqVhZA0jFbTixqwsiRvjKmhpj3lrZvQqGMlixq9IqtTQld8MYUbJkjXE5iXYGgprxnBDV/ZIfTBAxQxZ2ZMB3KhV7U4X1OxEQc2MYPkTBixO23sFP1Hg6/UGr4ggjF/jVp1GTtwOLw2evSgzVmwkWmpESfNhMiwIiU1eGkUve+/HWuz7nK9Fb4yO+QFGPMf7jbDvGj9XIuncXg6vM8ymsT4wn4dI+8uT01zaOCGdszzx7wEnsNvTkZSRhnmdaRvnH/NDrC5YUnastfoeaZPAJbT9fW5idL1YSNuCgoKCgoKCgoKCVyn+2TUYXLBfwWNC8qHahzBtEKvOQy15+hGw5CrI87TVm/tzNI6XJkQnk6dJjoqKqHLRpVm/8EJqLF408jTvTeOQ3dus35MhaesTiSue0OcYaRBShv2sTMJhTCgjxl1cvzwsjo9rHENqrb/R5hHiqTUkWJjr2HVmo7I2ghDIZjISJC3BSPAEjSUXiSy5aAlsmfg5+ReIW3AJbdsuCs2LH/d+fnmSTcCStIZJIMMRqF5PrXGkoddV2zBERtTX+Jg3kuTLTQyOBQKG+GA1e39EZsQys3ZOOMJf2P43JhLbkfwWCamug98R7ow4b3P58Xt/7J6T67EuPz6OYPfEut+ISR4tbh1w8ssT6zJsgKTH4Pmx++CnnDRPw8poR76TVQPTOIZv+1Gy8ZVsXhhH8nOdqYLSp5lfjFTSaKbEwkD67kjH049xPvaazb9k/giRzb8+843PzaAuQqTqHhI3tsNL34eNAiAhlwEk0rr+neDnXqLuwYUbc41t6Phwqt6BmuoeKJ1vPi6W46TxwTeSfJtso71EfniOhTPkSyD6/Q3mxK1AVIWQkrlo5B8ZhbR9FeLfzXDXv5thNeDfb4wKCgoKCgoKlkwsVUmM80d9FyESeofScE6wEkRfidsYL2DyeJHlFc1yAJePNarfJ9Jonin5jMq/rImVTbCGWBgR5/k5/3nuSdZECgopGRsJWhHiEjf7Ep4Hoa3UnxHc6Ti266vtN7ZJXFYZbz+X0uRSZ6MfG8E7HUmHC41oUMlEC/TJxfWXOuNUSMO2Dulc4fLw+9ouRD8b1NSYXUaru+ZbQpcxyQKBgPM9w1eQzWtcrI83IZ142OUl4Ug9YULZIY6VndSTjGg7iTvqcRN2XlPYnRCh77kBOWu4zBuDs8atIKUzDGeNjCV+Z2xMOgla73rjViQFJBtzQjR4xUk0+yzNFcUlEoVzI2nl1U1E9ROCCFJE1SDSGAjhVCkIDWkEJAQEiTh7SFiVC9IOT5g+AhAwdqEIvoWTvZ1GMQjNLGxDwY8L8ydS/XxzgqmDiepc+sT70wMN6WaWl9XBx8W3BWx84miM8IQUxyykhd08NudH8HtydICydGMA0tl9yO73beL+2LZsJBqPkb77uYoS/5axhKmd0ZbgDRL64H6bz5O8gXgFwvMJlie5H2Rt+IHcXPTtgNtQjGSkCG1vlyltG7f5/nuE2L3Nv1XUzMvyt7VppGWUrbrWTdJ2nbYYJm7sVHchbQsKCgoKCgoKCgpepRhYaikMysWhHoHSjydPrhKjgQiRdCUKaSaL92HJ0/rk5fGpiK0lvsh91PIPwrE/W/qhRmD8GhjBwj7Go3RezCBcvyQf44xz5PeFD9+MvM3Lnx/06474cUut+fqGR+CPOCHd9tHLyYy2MoSIuROyWwBCWFJBOr5UujgpvHVzBIvnUtij/tYSu2i4iufNXZcmvF9Ef2rx3bdRJFxtOppxXnKiIQq6xvluXLwhgjFWXYiRzu9cLeHSCEZYV3OXCEbYMrQgt26cn2DvAzkJY+uPmyIUXZHyTnxtNEZc8Fx8/DhZa8lVwVxLxIpIyDpdtEIqF6dCPBg56PNJR/SS8CRuJOvJEfBc8tHrZ4VIn4WvWa/PlEsZBqlHk5G0Mup/Fp7AFQbCCEvgOvJW+L5w7wBhACEd4RjIW2KErQiEmaeQPKk3FvQnaLmaFqfOxamZIObXUjlVFFFdRYxT0KpyeX06U3XRr9wGCeyloeO42ScVbNJlagCIq31xupmdShCvY1swg5jRuGVq9DIPK67Wwnh1JHVqXNOXQyaqsvB6jzN93mMxiNlG6Qm2tMLKEmwTQLB4xPdQniayNLSkNepL3mU5SRlT+r0XGkQt0j/dybuQxxFTV9G60RvTbHbRnsbWeP6zgW+JtCEhqF1OynqBl5M+d7On2uJGg0LaFhQUFBQUFBQUFLxK8dDRn8fA+ImLoCb/pWM/lC27xCyXaw0YHSybQxtA187qeX5Z6+hpmMX3emlcfj8vV7M6jc6svZvYzhZpp4IlGYJ9aAtH4rh4r5pAthNPQcdwRhal+k9Z/EhpXPew05UapAy9ztRAAqb6h/2z+CfxTtA5HC5G8gSDcJ5wMql+U+aP4ZSMSvzhPn4Pi0uIpqgv1Sl9YBsPw6wh/qyO8fFStsKRcnDSsA3JWakSUpakBKRyRsTsBXcJlwbnelJXM4I3jJcbn0RHNCMu+RzjjFMkbrlhtqgLWnCjb4ysk071gSDr+rDipKDRkNrdJ71eXAkpNITQllAznti1fkgCjCfWvHQ1I97yXaWxLTPnZhskyWg7st2NrZdSF9wPR5LLSMxbMt5LU0dynkSUlgZzuUQ8uTJJCOTLyJ9uCEf0Sbh5K4L0MgyiGzZ5yPaTdOvMS3iTzSxcZv58Xso+PD+n3DwjSkns8H09ijFqJT753PTFsSMMXJ8xo7oDsduelpbZRhb320TMwdNHekS+SdhG6KZ5UsI1SW+RxO13b1u7RrtcIinr111aqmgMrN02zjfsYmgsvWWxWEnb2267DV/60pdwzz334B//+AeuueYazJgxI6QTEY477jh8/etfx5w5czBt2jRccMEFWG+99RZfowsKCgoKCgoKCgqWEKynn8I4PX4R1eZ0hjrSlhxpS4YAo0HauMuSp6Q1yNRW36bxfnsZcmGqE9eQ8+cXtLtqEGl7gV/Wmjo5Utnr7KRRfhRxqSOASSMJFhZOohOphCWP81KeURozjRPgYZaP1dEq8cQ+vgX/5us3UlwKllIJzyi57KWWKEpFt0h9Rp6ekvxpujugn5RjC6Os3vAxLUSQkgpt5SHyg0LZB7g1liWNK0MSlCGQJDvv4EhCaOsnCZAEkSUELSnopDU9SWiiP6SL1B/jLClFQWrUqwAIg8WOd/cfIBEHBHBkqZcc9JsNguwzCXfBkYZwhKtwmxPNuKYfRBDeb3x9lqjN2wA4PamcARkGgiwxxvdGrHywG2NhHJEtQSScPmHf7/EIfRgXL03Lx4EfuU/GhIVFJqmZu55Uht8MaBsbRuf6MWEke3Qj0Q4TCfcg/emJ8GzsYhqxsUjTuASpvY/NjaQ9fq2MPD5+HdlHNnYciKAENz7Y3s/ENiv8ujGNMVIsrNI0wcbZjyWT+M3Hx2/Q2MazQaLwD5ujfr62jAsR61eCcBK4fFyiXwe/39AQToo2ydsyjuBjms2ZxI/sUdpHC9HgGX+neDeVFg/95/NkmxPJZhKXMOf3u3v7qalI2sGGZng6l8+3+AeJqx/xY5hsYgHJpgmP5xLLfEMlboCxssL9vs64XrgO6H76oD3BGmlXHuOpXO735VCgdkWSFkuNsaOi+xcvafvSSy9hk002wfve9z7sueeejfTTTjsNX/7yl3HJJZdgrbXWwuc+9zlMnz4dDzzwAMaNG7cYWlxQUFBQUFBQUFCw5OAdf/kJlh7sLPR6ItmWEXyG4hFud2nN/QZaW7fWPuz8tYE2BnXt0muDWhvoOuata3e/ieVw1xib5uuz7fEEIzviPcyzcaKUk6z5EXl/KXf181cq+pUSUFIGvxQ+rnmvra9Zb0IOMzKXf1DCPSfQn4w1rG/C+Lg47f3OtX3u+p2HQzy7NLuPlWP43Aj15yowIm/Zb+Z5wikcKefjBEAapOMkoioDKWD7VggoCSjhVSIMlwYXx8vh5bO6OQEPTrqz+cXXkPdzvpaNk2FkuEE2ZkTQxqk7ILIC7nm8SdP4+BpqL4tCXKyXE/HJBkC/NRQIGq4DM/aTEIDUbG25NOvavhcCUEAyfsqlS+HGhacneQGJuAESxydSK23HwvvPuvS5+fFsQ96NfeX9psWvuX+EdENwadHPx8RkbfHzaKTx8QSaTIg0tinV1keI70aZpYmWfu3X12158/KBzB1GwjN5TqLG87f1S9/j9S3j2pa3X78Ta0MMN8ekbWzyuEi0Rr+XEo8G9ZghPylhhEoM9Nl0F8fTJXNb8vryvLE1w/QVB2OL7ESBbyM8gZwhJV6R6IMOKkaY8TMvqS69lDqRc5nxPqf2Ig3HdH+vj5fMuF8wrMaNrDHSN76ziI1HSrFGGpbr8M0J25giktFP84yOqo1YrKTtLrvsgl122aU1jYhw9tln47Of/Sz22GMPAMC3vvUtrLjiirj22mux7777LsqmFixEFKNdBQUFBQUFBQXzhqVXew2WHje40OsJBAYxIpCTctoEktZ4ktWRsZaE1dZ1l6416p4laZXzy1pD1gZ1T0PUNixqA9EzENoAtVPDUDuJ3poAbUBagIT9KCS4o90iflAPB2v8yBGjUkIqCeldJSGVgqokVFVBVQqqo1B1KqhOhYpdITxQoRroWLdj3U4Ip/kUv7eqoDrK1lEpSKUglYRyrlDSEriSHznOmKdsbIiMGxcD0gStNYy2fW+vGrpn3brH/F0btm7Put0ees61eXk+G+cv7cqqe7Wrr4auDYTW7ortCiwlvHR0Y4CAMEZW76kdIwVZ2fGRlYKqquCqTgVZ+b7tQLmxUAOd6A50bL8PdKA6HTdmPk8F5eNdWcqNk6qUDfsx8q4/8p+NUWClGJtDfkPBSakbJ5VutIHRdmxMXQe/Dn3as/3e60F37biEuG4PutezY9H16T2WtwdTa5snlFfD1DV0Xdu0WsP48TG2PV7FCJEZiV1vf2/4YSTAGxYMUn1EQQ+lQdT2SJ7kIMsuEoTL60haokimEzGi1pOLzqgSI4wtUUiBOARGJm3tksrMtDHCto3ATcINAtaTthlx25I/kvpNPcgLAoFGSnkmJxXN+scPBdzDe5Y34aFsvCHf9828BDcOXmISNsKT+6E+/0rL5lnbxgd/lpwobSNT+5G1o4nPRMgb9ROayQtyvAoWJ0QW4vKz0Z8rRICLy++eFyyxOm1nz56NJ554Am9729tC3OTJk7HlllvijjvuKKRtQUFBQUFBQUHBfzxoxdVBExbBCbQgdeeIJxNJJ3KkIGlLqlrXkay1BtUa6EUXPQ3q1aCeBlgcenXikssHZYlaKJdPuAsaJAwc1WFZIdijvo1Ti/1YD09IsCO6xuvf9Lo0VQVSClR1YKoKpqqgqg50p4PaEX3KE30DA6gGrasGOtE/2EE1MADp8nmyUPp7O9aVjiS0hKQlIoUjj3NSEE46kQ2RI2792Fhy22jrN7WG0TVMz5KCgbhzxJ/u9mDqOpB+utuDHuqi7vSgO13oqoe66kIP9aBVDS270LKHWvSgRQ8aPWiyl6EamiQMahgSMKZ20rawxrEEQMLNKa+QsR/L4Zg3/+yQCqjsJaoKolNBdDqQrj+l78vBAdf39qrCNYhq3IAbqxiuBgeTfGpwANXAgBvbgUDkqoEKsnJ1OBJXKjdOMupsDeMTyKuoXsSPTyBsa+2I0xqmV0PXPZieJVntWHTtuAx1obpd1ENdqKEu6rlD0L0e5Nwu6qEhiKEuxFzrYmgIYK7u1qCuvY+6PXv1ehC9HoSsIUQPVg+tBmpENank19a801C5zBkxEte4/pEZict2XthE8KRaJHKjVklP91rNr5LIEYVRyhOIxGEosk9jOeGHjMzzmmU5eZv4W9JySdyEmGV+Xnfuz9uR9+9wyCWMU1I7VdkSJGfz0weZhHmb6+9LjPUhD7f48/YBSF5wyRhlErYZyZ1Ligd1L4iS5aN1Tcv9UX0Mj2N+xAFyew+FxH0VIt3TEC1xTUlxf2eTsKXWnKPBEkvaPvHEEwCAFVdcMYlfccUVQ1obhoaGMDQ0FMIvvPDCwmlgQUFBQUFBQUFBwWLG02/dF68sPWmh18MJQZAlaD3hFEknK7lnvASfJwS73UA86SHvdqGHLOFk/ZZ0in6XPtS1+Xs1dLcL043lGSd96OszdW0lcIVtE+AkBcn4p2D/sueCJaED4SkMoGF1MEqAugApWL8iUGVglAEpA6o0jKpBqgJVPZiqZ8ldNeRI3g6oqqKrKpe3Y/2VDRtPDKsq6oZUyhlkSvV3BoI5P+NNTu7HjVGqR5OsblNtDVd5qVepawh2Sa0h6p711zVE3YOsexB1Dal7LuzyuniheVxanjDG+TXTDUlOjyecLtDmfBvuWHTOwwfChKzkdzzu6sLO1YRwVNeqQCYE5sWp1uCX0dbVmqD8pawrhYGUBkpICGEgYaUGpRJRn6aXtuVzz6+fUIfd8DDaSat7VRPMTS5DTnUIoTb2MoZQUwxrcpdxahEM4rF8Txj6/5h0dmNt5BHDgBMZlAe4xKWw7ZBOMhNO+tJLrHni1ZOyRji1B7DSs5IcIegIWUlRupO7Xpqzzd9vfrU9k3eHk8zMVRfwsGkLZ3lb1S1kZSUEcksbR0IgYz25ytS9BLUvTppfKWlVuDC3UhKqkqgqacOVi1PCxStUlQhp3G0rj9fHr0DkMtePV/rebqp+IfKnPlKVOalKHXsCpPZqemqTqOmpa3ciRLNTIZqcyy/K/FZi3q/b0BYT11jYtCl41aDtPTE6yrVNBcK8SdkCSzBpO6845ZRTcMIJJyzuZhQUFBQUFBQUFBQsdFx8wwMYGD9x4VbC2ZtAOjnjRc7QkVWQqa36An/VNUjXQM2vHtDrgeoa6PUA7dxeD+TS0Ou5fDY/9XquvF5Sli1b2zKc8TMY73rCliLr0efZoi5YY7NKS26RMdb6vNYgWcNIZXX9SZX6lQpxWnG3glEKOsvD8+XlkQuTEDbsjfgIZvW+jbBlQ5QaZokGjYTT7yeYzj/prNx76/bCGCgdrd1LraFM7Vwb9mkhn3PTdGvAR1KsL7rMSBBZmq6NuPXzzWY1ntmCU9JqlaR2a0ApQA05t3Kuu6rKSeVWzUtVEG3x4WLlVSotVykmje0lsz2hLhlbyEWhw4Rzc5KvIXbplvXk53mt4xoIayvGEV9ndZauW1x++brzNkVWfOTXRBw2RpBGydZwHL5BphILx8PGCekKJh3K0pClgeVvSG4y9JXkZFKcjedy/3ACNSd1/fNTSxonfZGn5eRsXibYJlOf9vUDuYYTWbURZAg6I0ilEG7qCuePBK8QIuiLFpL7mR5p6dIyv5BeEjfzZ0SycAPmh0TwsWkRVQ0bDeHZmmSu38ixSy3q2fa6z8lkJCsx3ehMF7dXBeTzcaI4lEXE6mXjl7SzP+J726r7AQlIYXxKYjis4Q9hWB20iH8zTJY/D7eWh1S3ru1h4U6muLBfYP1nXXivc53XAKIuWeJ+5lIMy75h494nppEn+tGMd4MhWtrVGI9RE6153mTnqqWcsbH3Syxpu9JKKwEAnnzySbz2ta8N8U8++SQ23XTTvvcdc8wxOOKII0L4hRdewGqrrbbQ2llQUFBQUFBQUFCwuHDz3X+BGhi/aCojih85gXSLVtC9JKUMVrgjiSe0hnTkn9R1kPC0pF8a37jY/YIRhSIQjW3WvbkVb2B41tYaF7HHtQ3ICMcuSfvBLYyzdq+jBXVvrCU34uKMvRhnCEaL6I/GX1IjMsYRtL6c1PBM86MaAPuQjojEGPswZh+r0hO3RIlxFslJXLIS1NzICznjLuTiQYwYp0juCTJJvCSrPkOQsWRRcDkJ6BmsdHxyqToATorauyIxkGNc2HhDOt4vRTCuo2V/V+djKLJxSeqJ9SXECDyhzgkOPzLR50kCTx7Ixhh5Iz3cYA9FQz0tRnYUpWOW51GZ0R+VzYMwL9BGfsA/UWOutaymxC+QklVRStr1ByPjBLszqYtJWyb9mLdHoDVtuPaOBW1vEGKeflKwMc8IZHDMNro6x4hA+BJrmRCRsAr9xzeEmAoWRooHf0a0tub3eVgdbWF3y3w9W+idMB5ZmFhsRvom/jw/GxSe3+ZLmXRqmwwtaOGhwxwXrB1taKyCfG8oj/TxopnWXoXoU+arBMP0m+0HtpWzIF4O84iu34wcAUssabvWWmthpZVWwi233BJI2hdeeAF33XUXPvShD/W9b3BwEIODC98YQ0FBQUFBQUFBQcHixhWfejuWWnrpRVJXerTbknn2eHeLegStnQoDph+12w2qDYL6g14d1CDUQ1FtQh1UKKTqEXxZvlyrhqEX6rcGnaxeXdKIbbUPkD6QP34rvK5Yb/TLGZgKxqasrlnl9KaqAafjtNOB8jprOx2rO3Ug6kMNOlGZjtSoH9XquVXOMJb0Om47FVRVQTBdqVavrWrRl5p9cAZpL2s8KqqvsAaujHZj1NMwtdVja5wBq9ivdRineqgb9drm49Kto5oLnrfbg+m59F4vUZdhmIEtb3jL63b1bW/7gPXSUhBWCk0IJ6HliB8b10fPJglmtMpJ/hmve1M4AVkRLpGHG+Uy3ZyIUopRQrQp4ZmsIT5WbF15iTzPZRtkkoIU1Rt4Kb9U36aXEmRqEFw4prf7g2Qi0PSn1NewSKVembSr6xuZpUX9qLH/JAvzdMnLyMNZnGhpAx+bvoRvNv1y0rWfVKxh/WVCelMtgs3L8vtwS35i+YE0LranhRhuHRgv5SrcO0TY94k3dFhFY36KG93rKGekjxnsG4xG+7y+5yRucIClV8HIn6xUMP6nnNHFhkE/KZle6GjIL5G4Bfs75KVcjYl/h4IhP+7WzFhf6tbdHuqh1IhfPeT93ZjuDfw5Q432nekMLwY91DoY9UvaFHS/R/VCbWPmpVvRRyLW9NtIyjahwiYi2xjUSVxzo5HH8Y0pyjcPEV0udTviHMxTqRmXGqKkJE/j7zfbeIjZ2tJzEn3kdixKkO4BD/9lxHyLlbT917/+hT/+8Y8hPHv2bNx3331YbrnlsPrqq+NjH/sYTjzxRKy33npYa6218LnPfQ4rr7wyZsyYsfgaXVBQUFBQUFBQULCEoPrVHagmTFgkdQUjZOSIUKJo5IoRg9pZoBfuIxa1MzBW10CvBvVqKK/+oKdBvR6oV0P2apDTUSudK/xVa6s/tVdDuCPfwh3xFrWrT2uQMRCuTe78K5BQHfyBmIdgJUR9XsuMWeNn/jh5r2ePzQ+54/adirnKup0K6HT6+kmxfPzecBzfHcWXClDSXcoxV5asJW+IDGgyTozQ8Ja/KBy79xc7cs+Pz/fckXk3RiGu58eK+UOay8viKDmSn9Xn2xGO3zP2q8+3MydBLV3gSVTrl4IcyUruqDbYRVAuTkmCEvY4txLk4oTLg5Y0ZGUBUrK64AhkR+QClBh1Cm1vmXKeEKVk2FKjRwachLWudkexNTl9nXm802nr9dhq4fT5JuUgxrk2Rd2qVo9sTpi0SQUOB3I3+XtB1uCYJdl9eZbyMYF8t/3u0yOZm4VDHCXkro2PahbA4gO91EKmZ/sezfHKyNFAsLNnNVk8J3ZNFpcTsMkSSAjzlnhW56gIW/b8dkDsjfY0gutUA4hwEYQmCGkghLK6m4WGgIZEDYkeFHWgqIKiLpRWUKaDSlfu6qDqVfbqdlB1KqgBBVUpVJ4QrlS4ZKWsblt3eWOL0m2kpdK6cSyCKgKvxsAYaKc2hbQG1fbvALQBefK2p1HXGr1ejV6PubpGbTR6pNEjg64g9CTQkwo9Reh1gB4kekKhVgY9WaOuNHqVLc9eBlrrRO+tCXp1TaLbNiUn87mXvtcJCFKhCVHqCG2fHqT8GelrT2NElToCQEUEsgq9QeTu0VlZ2WkOMDIZob72WdZ8HoT3QJyvIoZFDBufFvKzeOH9zhW8HOHC7B4pknqCX6RtAIZZR2yzIDUrlr8R27bnhkF8Kdq+HwUWK2l79913Y/vttw9hr9Zg5syZuPjii3H00UfjpZdewkEHHYQ5c+Zgq622wg033IBx4xaBhdyCgoKCgoKCgoKCJRx/Pv4UTJBqodfDBVLCB1eDeIgWtYP0mCefOFlE3CCPD6dpSZ6Qtz2uYbCnhfjo+1zk9KoaANDQsN9qVpNglNxrlfBz4UQikEkLhjTmb9yXldEkp5ieTkY4DfeplxBMnNzx0nssnksA+nCbIaXc6j0fC8ryJUTVMIRWMpdGgGD/WA4ic70RIy8p6/RpKmmlaZUUjcunh3CS7glcXhYvO5e8TaVu+VHynPBM1g61kLWZhKwnXLUhKGNd6UhbaeBcGy/cpeOCs4bfiCxJ5w3uGYJ0ejON8bolbXv80WzyJN8oGdsG+UHZPKVU7UEkUBO6yvlFKCCNb5sT/YhY0RLXFugDavWGmDwuf0e23Uvsn755hq13dOslye/73Vj1IiBh1cAIAaN7ENKqEbE7FSLsVpASICVhlEClJIzz6yoaJlNSoKokusE4mTM4xv3K5gtGyJRfb7khMr+G2NoGkjnA3x/+vaUh3EYGUPvLRH+PBHoG6BmgS0DX+EtgyPl7BOe3cT5+yIiQf8go1FDoqgF0BdCtbJk9V1+PRKhTsyv+7eJ/O9MxcvSq27BwKlJAQUWKAEE5v1dtoshAObcKalFYmAwq4y4iKBPjw2WIxXnVKbEO3gauOkW69sY1TsnTeIKU68b1KmSCKhuIoIZGC+vXQkJLu0WgnWqb2sXXTjK4dlLFtbs3T0/KErEOX48R0pK/QgRC2IRJxghpthCbz9jPP0r0ZYrbIagf1f9vghdeeAGTJ0/Gk88+j0mTJi3u5hQUFBQUFBQUFIwSL7zwAlZcfjKef778jsvhf+NO3XRfVGpg0VRK7JOGopEPENd/aaJOTHK6bn28N0RFFAxiCYpGqqKhLGoYsEoMaSX1pPXB+0GhjblahJH4mjaSKCcPIpEqGvl43vR+0RLXUmaoXLS2ZbRoJ5UoSUtcSsMJudiSL42j5r0tZfZr2/BtdxJmmeRYkCaTMhzjJel1DgvmlyCpQtgwf7yiITie194rmD8ahov1ekk1z94CFAY2HzVPdPhOZHOVrRdwXdF+DfDLr48Qx/Q6B0NwWXxeDjMKF+ulpuva1x9+stsxQOgba6CNpABcn0IqkFK2j51BN1IKpCqbrqoY9v6qcnkrdm+V3i+d35eb1C8BN47RSFwqxZgOEXtvuD7yRuOE19/sjB4KY6X84fRuC62Zv05cOD3eaZqPT+8JZTjDirE+rj+agm7xuDuTE02IagaYegQpnXRrpYKKBFUpq+6gwyRiO1VQdVB1otqDjlOJ4NM7A7nqBJ/fqVZoKztI2jL1CNKSusKdJogqYCJt6zc6EvUI7rSH1gbaS73W9tRH7SRs655VZ9Dr1eg51Qa9rvPX3t+zbo/5uzV6PevXTlLXluXKdNK22l86tsW3zatGIGMNLw73Aox/YyNZGP5uEPNzkheIusyREcAJGRzL9/fw/G118TZFw2LpXOuHUILgfwfY3YJJ3TKC15K+Yth4yuJ5WTxtuLoa7VzE6JHGDS/9bsTfuEusTtuCgoKCgoKCgoKCBYFvfetb2GeffRp2D7rdLr7zne/ggAMOWEwtm38MLTUBdbXoSFvAE07sA5CTpyb6JSOGJCOZZDBYFolaTzJJRzgZF0dGQxhhpY2MIx/c0V5JBjASVo7JNtBL6FkBQWtgbL4+x1pF+MQw6X3S+sWPpsy+7WnLyEibVm5A5NmQMKvNYpr+wJ+wBCGyfMnXfUudYwP5IkUqaUewfJqRTvLO2XUhEQRNrZQVBSFTq3JA2iO2RtqjtDFs/RTSEPVLSncMVzgL7c4fLbC7tmbHmdMH8YafBDMYxy8310k4g2TCzf/oSiMgDSAJkMbeF+IMXB7nNyLLZ+8TLp9dpwj1hXb4YUU65K0I89dKSBIjCUkICEd2CylBSkI4ghWOiLVqQSoIR9aiqmy4csQtcwUjdVFVGXlbMfLWEraRLPbkbSRu0yPfaLzfwuUJbUaewhPiTvVHQr4aqxpEeJK2dml1D0Irp95FQiin8sWrAXASphACQrds5jipZ+EkpOFdv0LYM+RrR3B/WDvC6Uq2cYYEBFntJQiXbQu0ABSsnnAtQLWAcZLods0I1FKgEgIV7KUgUEFCkYDSAsqwS0tILaFqCVlJyFpYfbbCulZqXrbo7fbvd+FU9Nj2GCNgtLBDowmmJuiaYDRB9wx0T4fL9KwKGHR7EN0aqtuzKl26PYhuD7Lbg+r2UHV76HSjPtu6Z3XX1j2n07ZndeXqWgfXeP3uxgTd6pG0te1N9a32R6BWRRb23YCU1ATiOyeQleFd5N9jACCTDQtOaPIygt9DZOExImxU8bBrACeSE4l8irRrIJnDRlJabiSWk54KRHNoPb9vpPZmzzt8DC+vvZ9ibpt3aJR/FIukbUHBQsCymx+2uJuwQPHcr89b3E0oKCgoKPgPxIKStFVK4R//+AemTJmSxD/77LOYMmUKtNbz29S++OIXv4hjjjkGH/3oR3H22WcDAObOnYtPfOIT+M53voOhoSFMnz4dX/nKV7Diiv8/e+8edstRlYm/q6r3d5JAEhKEhGgCUVGQm4wyCBl1BBQdn1EGRrnILeCoSLhFQFECMlyiKBeRm/D4RPg5iMp44RkGdWQQHiMgNxFECEbGoJKgBHIE5OzuqvX7o9aqWlXde3/7OzkX0XqTPlW1qrqququr99dvrVrrnJ3r1b9x3/5fvwM3Xa2OU+9rqIZQJsxE2ylv5Ra7mjHbGUzbtENMtm9DZIQgsqV00HSKTyYecz2mzvbg4qTJ2g9svpNnEJ5EQsrp4oAKeRu8OqjyGndIW+ibuNe4I2MrtdShdlZzXU6dX6E2v2C23C9tF17iREVhqoyRXH++P6i34bcmJ4LcyyD3sthILfHItdzaV831Ra7NZOh4cG3Xcx/Fs2qcqjDzbeYebZBXTqrasYaapLD3WtK2vMmHkQM061Pb53aMcpqtvDbrgRxvzH1wbWYimyXBwphvKD9vQ1tv+7Q7127HZ/PYLDsf0+3wxRHZwlxAMSeiBKeb1dmOcRmdul9LvV8m06p7Ze7d7N5rWuNsTYZY0zFcnZvHqBmvUu/C+Eknb8wYlffIfP7ke0ZL47YwT3SeVXNseexL2/X7LI+J6dd2bLgPC/eonReaLqZiaud7doxjlW5N77B519bzeL/xmb0LQGURCMX5mC4Ktc7HrBOx4nSMivMx2T2QTA4kWXS+OCVbcFjWOjsrDtFcNm9Q+pfGiBeGqVrQRSFbk4mFKAtTES6qSQZZvBUzD07SSR7E9EOEl0VdH0M+J5UvZYqs1OPU3IMuKLc7glBrIZtH0YzWtuexzdd6qInXeWtEXIFPHHtN21/5lV/BIx/5yJl8miZcdtlluPzyyw9aZUdHR0dHR0dHR8dxAzPnbewWf/u3f4szzzzzuLX77ne/G7/0S7+EO9/5zpX8SU96Et70pjfhN3/zN3HmmWfikksuwf3vf39ceeWVB27jyLWfwzAc/81zdktn/kC15IIhbTNJlwk/Q/q1ZC6z+MfixcMSslHsd0bdZsosu5btltnUOdu/nRgNhihxMZI2r/kgp+RwKjtIoeRUCZS0fyNxZjeoZjNE6xBZE1NJWs4EbtLabO3hbiJJUKrGJkpQx0fjUW5CZW+W1dZiYyOY5zaFw0LIPCd723FQ3aBZHE0HbwQoDx4KI8c6BFy0RolkbJFl9kh1cSH9WM7PcTIf9tKUqSebsmDbr039nX/Skz6rKufm1thVBxtVrTKuy+b6ucgWz28FxwgyjVAxVzoGTYt5jlIi0SD3Wsk7RpobKdShpnLvpFx2dGZk7fjYcdmPgpmFljyFJe4WiFa0pODcfrSVZcLW1GXJ4tmq01EOmVJL9XtR33PIz3DWWsz3TdPNnGnu6yxfyuS4KYemHHLefmRtc03m3szGzf5mmfK2XE3K12OwsUzzHOv9bNtv40cLXjhmckIhfkWWlKWpSduQ5LDK1XWaJZ9hntGGsLUauJX5BaJigkGmv0PaAeP0ZdzcoPy05Hc1FRvz0OeX6utm2niP2vt0wKdr8Ywyj3R3T0vYWvqXmhoO1gPgKEjbxz/+8XjTm96EV73qVTjrrLMAAB/96EfxkIc8BJ/+9Kc7advR0dHR0dHR0fEvAne9612zXbx73/veFbkZQsDHP/5xfOd3fudxaftzn/scfuAHfgCvfvWr8ZznPCfLb7jhBvzyL/8yXve61+Fe97oXAOCKK67A7W9/e7zzne/EN33TNx2onc//wxfSNuPjjOb7fk4uGIKikIK8mQRUDU2VxZLX5gepXx0yRV4gDLU/+g14QFJQOCP5EmP57FJKUMhgIjBJG5SOCBamQhpqSFuVFQ0qZPI2Oyyr4sjEodVGtGQUsD/hZEmEJVLJEkiVgzc09xZoHMfN8yuiFgtx05dN5OGXGuynfHp2OJH7C/lL51bxhrBty2zsQ0vkbWvoBKK9NyWDK2Jd51qEkjtK7CRHR5YOUTMnMZPqXLQ7uZBDQJmOFWGredKVamxavqWJ1sTc/sTtkjw2srhUVss1Zds2tUNt/3bFrDwVgikvcDRpMoKcMnGiXHpz3Pxj62tKoI3ufjFmHlX3iMv7R/81BZfibMhErs5MJ3O+R6ZuMvk7dv+YgrmQoHbBhDn9bmkZ5tJv8T6oIYjNc6zXba4/M/6bnz+dq/n9JO2pjWx1/jnri+2y7TtsPaaVemI2nSn13ljM3+VsnldaKKe0sjWwwBvK7oYDk7bvf//78dCHPhR3utOdcMUVV+Cqq67CU5/6VNzvfvfDy1/+8oNW19HR0dHR0dHR0XFccL/73Q8A8Gd/9me4733vi5ve9KY5b29vD7e5zW3wgAc84Li0/djHPhbf/d3fjfvc5z4Vafve974X4zjiPve5T5bd7na3wwUXXIB3vOMdG0nbI0eO4MiRIzl9+PDh49Lvf6tI27OFMCVrGqGEjiBmDYwpBFdMHWied+Yg5DIl35pIKGlnTCbYNrM3dRQCV7UQW1Qfvg15qkRrJtQ3mDmw2s8pbjWj0WhJFzI9a1Ezsn3jqB/eEkamwkjNCJQt42NCe/16T1yOC5HXbMNXYly31C/mU9lub8va+mbbwO3zs9DXmb2ERoNPw/3Iv5ZkTwQfZQ3NOp8yAVhIehNSo+Gpiwnat4aYMcmtaIkI5WgrqoW5LEKwGbNMqpKQs0lXLY+xJWvzOWZOMG8ci6S1O6MF9134mMXNuKh8SQOzHbuZfEserByF+FrK3w9VGdliD1DjSK91zufFKZ+E3oPdUIXRD4jiKC46P4vbdA5zXbZ+aS87+CNA+2b6mweL66urHeY1zva42E4ncRjngoZTDl2YUjkbNoctm+qbSl1i19ipUzrTvtpCVmdx+zv00wtdjudnXe8LyaygZDca5FLoUpoo2ZFOh08HaTzlOxkDp3anRVbsPqcwUrI3nO13Y4t5BC5EZXGAVg5nzCPkg2KysU1is5tJfosp3Vu9/kggJ3UDoAjAMSi6NMVJlnrIyfs35LuX3jH6IJkHausLrtWSnY9Wqo2bkvZ9Y98QS/L9cWDS9qu+6qtw5ZVX4olPfCK+8zu/E957vOY1r8GDH/zgg1bV0dHR0dHR0dHRcdzwzGc+EwBwm9vcBg984ANxyimnnJB2X//61+N973sf3v3ud8/yrr32Wuzt7eFmN7tZJT/nnHNw7bXXbqzz8ssvx7Oe9ayZ3B9K3rdPCCxBYclACR2rUxtxBFYKiafzEgcDrEYeJc6cnCIxJ41WxwCLE7KoBI0SguJpikSfhSWfd2WYNlyffoXptkcbMggxct7mGR3EgU8ihcoHJBnGj8RrPYGFnGUhctVEQjT2bAtRa4nF2oZk/pDcwNomUqexvZlJPWMagbkhb5XMLfGKqLXkrjlvbk9YCWMla2HifCDiadswtbIqLWMSWUxQ6BjJycycxkLy0/1Rzaj0TDsuW+6dkgRck4R5XPT7vyUHN5A0ZR7VpNwmMs9qk2eNdpuGJWaXCN56zlpicKmfRzM27ZhYrXBLsJf4ZrlrZJu0zvetVzqySKhvAS/EOT0428nXTIAjb1OPKjdlI8wuBUOaR2oa1ZeNiqk8awcao/x+FLIMDhxjMvuSCdAkYxeERHXgUJO57Nq0xL3fXoaKUzg2ZHEhaRfIWrPgoZqtZJ9TebnMyFtxflnixYFcStdkLgUjFzJWnWJWZWIE2J5rieKQ+qCErekP9M1ytC+8PNq0/PLTe0FSjlE0a/PLNt0jJvl1SD/QKVS5kTFiGhOOaewQwezMs69vSg0LCOlZ1tCOkfwygcWmLMyR+6L9g/6GVDNOyiGX1dWMopGLUg7m1JI5v7Vb73t924sObZKSKaO5dcVU1cBZQkB2orodR2UA601vehNe//rX4x73uAeuuuoq/PIv/zK+9Vu/Feedd97RVNfR0dHR0dHR0dFx3PCIRzzihLX1iU98Ak94whPwf/7P/zmmJPHTnvY0XHrppTl9+PBhnH/++di76R72ToBNWyUO5HuokAw2HgsRmIhBhou1FicJwUcRKS5koDGomshcYZyUzKXIcC7ZsKVYSDP9nktEsbFFKwTLdi2a2eWVwpxs/mWNIfkOy7ZpkcjUiGLiIJh4a/pAHZcpAaXn27glp9wGEmqJgKquw4aWYLKE0QZSz5o82GQKIdu0NWWCeQ5aMwradmuvUzu5K49RPnRRxl05jEygUta+rDQ1We5nS7Sa+5ruuywCVGSgantau8J1PYDRx6K5f/X2E74aq/y4GQ1crseRueTXJKGY58Dcluqm+97WAVt3Ttf93XWM7LW2xGnl4M/IKo1mM290DrTaz+382DRfLOkLI9+VtG2vvx0T+2wzlsnxYj6Eqrmkc2c2B4nMmBlTCaB6DM0DZefFprEohY2NZ4SqjCXY8/2SjJoAXybE7b1Hlaa6vg1twZRd7v8cs/lkf6NsuMDdzRYu7PyRk2x6VofJR1NH27dN82dZriPaxrXtQrgW0lJJ10Ssph9OSukIsJMFg1hIQwhZr+QuM4OdkKQuEbVlsSGKdnZEdkRG+S0407TVd3LqfbopkZMTMumIkLESxijxWOISIqdDksWIdFERhfCNmfCFEs76h0F+Jnjhbu4CMv+m85RwXX7P21+p5Se4PPe8sUyLA/+F98M//MN4zWteg+c+97m49NJLcd111+FRj3oU7nSnO+EVr3gFvv/7v/+gVXZ0/KvDZ9790pPdhY6Ojo6Ojn/TOPvss3HVVVfhy77sy3DWWWdtdW5y/fXXH7N23/ve9+JTn/oU/t2/+3dZFkLA29/+drz0pS/F7//+72O9XuOzn/1spW173XXX4dxzz91Y76FDh3Do0KGZ/LIvfjkGvzpm/d8OrhwbkYas3pe5pLPWEWfNJyehaj85o5nkrFzPE6/PuR4tU9VtZLn9ov1iPlMz2ieh+sDmUoaE9CUpNCd+eDM5ZcpaOVp5m4ctpAZM5sJ1zK7UEKRLREZNSm0hKTYQftu2fC+RGrbOxf5ulBPSFt0U57x1lyqtvRL6RFQYjb/YaADGxTy7jbvZul1t4zah9AGyZbjWFFwYJS53pJ0vYDtfYhO2Gn5mS/ZC2hmtwbxNfEFL0LFqIJa5WPoVTT/rUdlETGdSryFVqdUkR3HK12qZZ1MkZMyQbMq3cqhZkcachSGHUxdpNseWnr1FslwXpCRunfepYz/mspDR2uxu7Xu3zv5mNrtRNOO13TIMnPu5ibhdwlI5+97LQ0klI7+D2OZT+R1QmQ3lxbmUX8UzsbvrFczRvvda2WJ8H5J1m4Mz08y8/YX0LlBHh+ndqQ9oyPFsjgDImse1mYLyq1eckomMikkDlkmq+bN6mvq1K6VPQP1UbIP+nVCuUcSgnJevMJtTAJD/rshlc1jnE+crKOebc0rPm3SVN8dczs1163O2zYTCNgKXcNw0ba+88kq8613vwl3uchcAwLnnnov//b//N172spfhUY96VCdtOzo6Ojo6Ojo6Tjpe9KIX4fTTTwcAvPjFLz5h7d773vfGBz/4wUp28cUX43a3ux1+/Md/HOeffz5WqxXe8pa3ZHu6H/3oR3HNNdfgHve4x4Hb+8LNzoQf9o5J33eBfvQUrS0hd6KxWRdr8snF/UOXySYlnDQeK/JW00QkhJN8eSfjqfLBF5PWLSFv09wFVu+l/bAn+VCdOzRqNF+5ELmZ6JXMipjVeENsWCJjJjM923ZN2wgEJVSt3JJUmm4J3UrekB0tybGt3k193AqCkA1CjrpkYzGRpz7b5LS2MyP5Yn/T2NpM6QHBD2DvESSteSGX0XOKDc7ohkz2VqFu9Ubq24y8tVedSQUhGfJCRE3UOkO+upjsbbog8WDtcU5Z7htbnN7Y7JyHIdnmjAEu+kTuUhAtdiFuI9Lc1md0w6BRFVFCCJloV5KUiZK5CSVViTC5YrdZZc6ZMtl0SInb862s1CGksWk7a4QqQUiLV5CfTMtRF2d6XIhcLqStbuGOzKIAqLsNJD+adNyet1gnlDxOtopZyNT0BKWXDB9oQrVXW+5CS0rO3of23jXvQgtL1FVllrRpj7bzWzCrcYHIXSzXyniHMltk27DtHW7JTVTxg9d1kDJV2YOcsAXtU5J/F0wj5TejvD/Y5lExSJDvTlMuIq3Y2Lq4NFHXZ/uyZUH/eGPkABzZv9yBSdv3vve9i6v8j33sYyuHCh0dHR0dHR0dHR0nC9Ykwok0j3D66afjjne8YyW7yU1ugpvf/OZZ/uhHPxqXXnopzj77bJxxxhl43OMeh3vc4x4bnZBtw/968Hk447QTYKs3ExcoBIOYN4gxIoaIGBghRISQ0mEKCFPEpOEYME0hhXJk+ThhGgPGsc7P5UJEkPNtnWEy7YW0fTIGJ/1KJhOUYNnvq7olSdvt1JUWrcnfpF27ycTBLnY5l9pv+7n4sblFy0yUuGaELDd5c7lS4RvKq4xqu505j+r2q+7Or6CBuQOGAafEzAk5WpzuQJzuOOcB7wHnAT+YYwUMKR7dAAwDyA8gv5JwqAlePwgRrI6VEnlbbHaqZq9o3RotYNV4q65GJpHVZrV2N4sDJSFtG0dJrZMkF0YhcT28S06E0lHITheMuQ7owSB4E3cgpC3MFB0IMTk0imJyIl9HM4/IkCGUzACkkDJJm0KHaMJADtE5BJEF51Io8U2hlokqI8rxto3SNlV9arUKl5+2QrAn50lcxdMRq9DL4pLjCC87CzxH+KhhgKMic8zwFPN5HinPcVqc8mA4RDgJdXxSX2J6/LVfC1dzUCpqPyKy4Wq3YmPbO5x8LPp9PM499tTydiy98y2ZOlsEXFjoW/oNaXd22Hr3+73ZSNALqt+dTLSmxZsUpnmo8zPqHJZ3Qp7TEk4im2T+T1Juyu+FUibLtS7JD3CmvaYP+Z1Q9/dEgcMa+IuP7lvuwKTtoUOHcPXVV+OKK67A1VdfjV/4hV/ALW95S7z5zW/GBRdccFSd7ejo6Ojo6Ojo6DieiDHir/7qr/CpT30KMdZb0r7lW77lhPblRS96EZxzeMADHoAjR47gvve9L17+8pcfVV2/+OcRhw7ttsXuRqFSsRS7ennPrtqhFRt0GgYG5GA5EBg8FVlJAzwhySauQp4gxlQBDpBzkdJR6siGVKWbxZhnYRDtpVQQ7Z5MtBFgyTdy4kxMHOdkxzrGmY4Qhkw+y9n5LCv5ep6v0+L1m7WNTEqaOCh/hW/6sCyaa2WsisMXdZAjodgHrENOTnWsg52ZIx/1jF7yrJMePVfbLE6BbB+0j6WfGx88RiKpOJFthAhEyveFzT1i0cDNcVfHuR2/bXIz7qUNJWebsTHbkIsm2IaPf7MduDUzUu7TgskE65E+mzJovdUvmVawzpEW0kvt5ucGKA5+5mPEjKzxJk8bit1LV4eVAyo/mzPpSER75fFe0o6S1rOT+eVEy1kdXEHGTkMS8raEtm8VPVvPH5ht1Lp7IMdjNvOi5KrLJGzIuwNK3JinkLjdVUAxVGYroDIX8/s0zRnKOxrSS86lsSLGJu+LS+85u5UeQL4XTK66NzqHoh03shruZa7ZMrEZ67j0HLRzNr9z9b1W+mkGZeHC6nECUEzmoLxnWjM6zjgry+Npd4Y088SZ+VfM9tRmefJ8Ms+M9sf2sx6N7dDSdnS1Gmryk4Bn9c7MWQDm/TPvBy0IS3Txl3NDv1MPWaJs5pklR9P7nOCJJERFpFpitSVaWyK4lClyaxIiLrSt8z/3mZau8vhhihPm7mrnIOaFt+8WvO1tb8N3fdd34aKLLsLb3/52/OVf/iW+8iu/Ej/zMz+D97znPXjDG95wlF0+Pjh8+DDOPPNMXPfpG3DGGWec7O50dHR0dHR0dHTsiMOHD+Ocm5+JG264cX/HvfOd78RDHvIQ/M3f/A3aP32JCCGEG9vVEw79G/fc//QMuNWJ0LQtEWLkD+Pa1qzao7WhIS9CIiy8kheh5Pm8zTvAh0JuaJzyeUUTMZtPMO21Nm7LB/SGTx6y29kNGWE1KHXrvddQt9SXbfc809BcpXAw8fZwaYt+2YY/zGyvLtlQtX2eDRKrlqASD602p7FzqvfWaHFSpc05wk2tVueUZLHV+EwHmS35FKaZF3bXEoxKFCqBq8OywyNZ2amWj397MslHuGqh5SyN57CclOPbzqv/qbTfjlZPsH4tKVmqSZ7H8+JJOUfjxWu60Y7PxGsdzym7qLEDPdCWsAselpSLhgCPQrZG8ojGpEUdF7MWziOYeHRDSZMz8vp8bce2u0ggV6RgIm7KgoedQ3PSr33P6Tsuk7Jc3nf5Xde+/8KUypl3nX03kq134b06s+VtiMtFVORoGaNMquZ7Vu6nytqxCTk+lHzfjJGrj7ou8zy09qH10HeyVf/US8kPdU2S2sUMZ0nXpTFqfmdSmfIbVI1dM0bzusy4xIYE5vo5sjNnmWo/CDaQ2iafN+a3N3V7/tZ+bmZudyzOW5OLlXFZYFkEzyIHRqnfvB9MfbUtWy1RSrYym6NYI+IKfGLfv3EPrGn7Ez/xE3jOc56DSy+9NNsJA4B73eteeOlLu/Oljo6Ojo6Ojo6Of1n4kR/5EXzjN34j3vSmN+FWt7rVVqdkX2p4zqX/Bafd5PT9Cx4DVB6aRaOWQwRCAIeAGAJ4muQIiNMEHkfEcUzhOsXjeg1epzCOUwqrYwSbeFyvwdOUzy91TqkNPaQfHMTbdFDv00DWutVrMddFhLQVnChp6nnR+POiAegH8ODztnqs0hZ7HlYSly33qxV4JbLVCljtpfRQ0hgGkQ3VuTykrfq5DWkXXrRyvdEiNNqdmV00REY+YtHWoxiAEIEwASGkcArANIGmEZgmIIcTaByBcQTGNTCOqYxJ12XGdK6Wm7zU44AwgSZKzuoDkpJgQGJeIhXPSlYjDPXgJNulDuRS6LyH8w5u8HB+gBs8/GqAWw3wq1WKDwOGvRX83gp+b0/iexgOabgHvxow7O3BH9rDYPP29uAPreBXKwx7q6pev5L0kNpNfUgHOQfyaqqhmHCoyBkWD+1RvKeHiBhjmi8hIE4BYUrPdZwCwjgijFMK1+mY1iPCei3xNcJ6SuGRNab1GtORlD8dMWWOjAiTOV/qjOOEIPMoSJtpLsc0n3Wei73VTXZM7TZ9MIEogECgiMq2bLZbS6jt2Jp0cS5GRiZlXDLkkGzcqgmStj4UUyOaRpEB2Ok3INuyNfF0CzSuTsJqW7QRybZtciZW27DdJFPbtrkOaUPLsZDtdftCudfTZxGq50hCNaX7EZftBjuCdynunYPzBOccvCc47+CdhF7KerecL6GTOvPhXWrPGZvETseqHr/5YohdfChjoDaAORpbwXpPQ8zmcmJM6dCEMTJCYESfzOwEZ/IppjyKiJTGNyAigusjMljy01hZe8QAyC6yLCx8NJrQataDc7qY/0iLH8XMSDShNR+iCxhByHhbXs2NlHNpFlcSPWu/WvI/93fDM2e1nw25rlrrqq3sojUzUqez6RAhx72aDjFa7m3amilxhkTXOufa87poWOaJjk/WvDexMo9smfxmqaRWR7rcqoP//Xlg0vaDH/wgXve6183kt7zlLfGP//iPB+5AR0dHR0dHR0dHx/HExz72MbzhDW/AV3/1V5/srhxznH76TXDaTW9y3NtRckAJWzAXgrQhbKOStuOIOPp0rD3i4BHXDtEToicED7B3CA7pY5gYQT+AOSJwROSIGD0iWLQ1HWJ0QHTg6IBIiInlSSSgMjS61XFBnWmR4GCkj+rqOjnJxEU8B/kEp2SHQT/fwU5s56b+cCRwICAQeCLwipKJhwlgH4GBwXJgiGA54CPYB8AHIWsnwJdt5Era2i358+uYE7esW6xjItg15BCEwGUxUwEgEDAREBw4eCCuhAsmAGoKYkh95BGMCaAJ8OlgJYOFHOaobSTzCqk/IW3zzlu/lXWqtW2z8yjnauJWSVufSFPvhbAdfE3aroZE2gr5quStxpW0TbJE1A57Kwwryd9bYZC6CmlrCdsB3nvQkLbsJ0K59BVCQNkPeDZziDkRQRwjIgVEF1JIAYEmRJfCdIzpcBMmNyK4tYQjgp8w+TUmP2Ia1gjDiGm1xrQaC2m7NyJMU0orCbxA2MYpIMZE2nIIiVCOZs63arlyddVBje1cSXuReUpxT5zCBdkgsgGc8wYJCQyXz5WQNURjv5dzXJ7g3E95xGbvgUKzWHIUFXEaJR2Zk1WWTMhaGSNwyQtNmOWw6aV6UrvZGo3Oc/vqmo3KHIWwTaFjGRuG3E8hxEEpzpTuL1Oyw8su2eclSrLo4JG2tg8Seioyj3K4NnSpfsdC0rMlbAvJX8bHkGAL45HsrCvhjULQMifiNaYwBBOPjCnGKn/SPI4ILGku6TReiQDMaUP86diwjF39NG0fHQhZraZXSEI18ZLeg15sd/u8gKUmRdgnW948s+ftzSLkANIFJt0t4jyin2u+Zw3syhyGNW0hVGQ7ieQdsVFbXUyL5J0XRhO60nxWx4uqFZ134ky1BnQVpt0iFMqukmIv3Jjz0d8dNZUlv//zPxg0nWaZJV7LvFNSl5tzlkJ7k3bXtT4waXuzm90Mn/zkJ3HhhRdW8ve///348i//8oNW19HR0dHR0dHR0XFccfe73x1/9Vd/9a+StL3hyIRxNR3/hlTD1mjaQjRts4araruOATFM4FHiY0Bcm/gYEMcIHmMhiqYInsShmYbi3Mw6PZuFlp8UIqPSbtr3uvSzqXh+Z44p7ihxnS6AAxAdwC5pY0UfEV1E9CEdziP6ccE0woBgzCNkp1bGRIJuLWZfbydm8+Fst3pbR1eLFwTUW+RV1VivjRngRMaBo8hUK5mTljJzIqDZJxKaPTiuwPFQOccJ4eyFjOVCELMl97nI0pb9MmiZJLejxVwRAUUDL127U41bJUqFLE3afqL56pwQuulwg4cnD88DfPDwa5+cd00efp3IVz8QvAf8EOH8CD9EeD8Vgtj5pFXokz1VkjZdJlRopmE7JzTUHEGtcRuFGI16iFO9EKKQqAFBtHFDECd8AQiTQwweIewhTA5hGhBCmn+BA4ILCMOEQAFxiAgr0eaVhZbsRFCI2hjL2MWoWp5m7teTJo0PlAzlTJR6ZiFqWYg/xgA5OGIFxsCMFRirKh2xJ+kVR+w1oS23dO4g7WibmdQVoo2ljyT9bKmUGkukSpFtfL/kIjuU3drW8YRQTXmxJL3r7Lsz2QJNpDExoHalicVBnef0vEdCcGnBCoGFMafEujsCu0TismjwsmhIZ2d5TrWka83oMofqzQQ5MBrHkY3Ws2o5q6ZtRE3ctkcQ8jVYx5pWM1fmqfntsYcuZujvh+lmjs9ece1wZMLW5R0fJL8BJDstWIhZFnM8PIhZHtn1oWkeVka2QlytSlzlcn7U84YB7Fepfq3HebDu9HBl8ZD3Wzw0C3BqhzmbxMm2m5N5nnRMKZySeR2axmS6ZxqTbBoX4iNoHJM5HpNHk6TDVOrT+uWAJXOJ8uJhmQtL82VOuLZauHU5MmRue35dbhccmLR90IMehB//8R/Hb/7mb4KIEGPElVdeiSc/+cl4+MMfftDqOjo6Ojo6Ojo6Oo4rHve4x+HHfuzHcO211+JOd7oTVqtVlX/nO9/5JPXsxoOf9dOIw96Ja08+bLLG4NIhZI8lgFg+hvNWayGnqu3XwaaLQ7Oslakaf1JvlimhpKpoeliVrM1XlK8rnSF9oaTty5HqLaRikzOofUZyYuPRZVlQe5zO5Xi2A0m2nGtk6sinaDfZLaoMl4gUtfW4AXarp7UZa7Wd7NZUYoav7DHWW0/VsRLFZsvplvTMwY/VtDKaafZDmRa/lo39UbVFamxyLtoitrYy1Y5qJsLrODuP0TkcyQRFm7/grMy5un11IAcUIkOvphmm4hioaKFZbbTseCw2DsdifTirQWbSPgYMVX7RZpsdM2dldR9K/1J/l5wp6RhZ1dWsfVeNW9IazE7bxPFeIX/E8ZVz+CIRvugcmAZxVCb53sSN0740Bk3dZhzsc5M7OlOxbUlTuV6uNQbRPMfLzt/UWVVo7nmxUZtII4Y6IXMbx8S2M7eTWjQa52NT0Uy5COdhgb5FsimJcmuUbCqcXGNmwhKrWY7KrEGrLVvnSRv2MWmep01vOLN0oFcvW/hTOu2DKI6oApJDq5BoZ4RZ3CfrLeQQTH6OO0LwhAhX1RVQnGDlg8SRFkponV/NRwmyyKPEtRMTFWVxSBeKvC5CDQMGMQkzyI6CfEh6b7XCajXknQOr1ZDCvRT6wWO1WlXnpfpS/X7w6XBeTGH4vDDmXDH/khfT9JnKa4Vc/U5XZoumsqibTShNI+J6yuaT4jRV5pGimH/JJpSOrBHW61L+iCk7mlB2+/A0IY4TeCLECeCgR6JWOYrO7EbC1i7vlHFUSaFxi7RNY3bW0tOwjAOTts973vPw2Mc+Fueffz5CCPi6r/s6hBDwkIc8BE9/+tMPWl1HR0dHR0dHR0fHccUDHvAAAMCjHvWoLCMiMDO+VB2RKf7+gx/FKc6f8HbLx41xgGTjlUZhyWvtQWbbf7O8shV70/lg26btB4pG404XAyQv7JJgAojhskZrTHZKo2pUTlCP9JHSR6zaHCw2A6nYELR2B0Vu7ROqrHhnT2RDtmlItRdsdZy0CcSFHihO46wdwULcWjt/LsusfcDW1mAUgjcRva0NwpS2dUpbFWlcCNtMiG0fHuOcqHgXVydKUeL5/ut9lfufiJdCtgchyVv7jqEJrd3HQJa8L+0t2Xq0RM1sbJoxWhob14xNuuecbTf6ytZjSqOy7xiy3IZOyPlsA7Iab4ZDNM+H2nzcdYwKOZruQ+1YKi9GGCdU7UIIV3Y4fSbQU7myyMEEKSNmkR0hRkLt4Mo42kpXkg8QpXfFtjGSl4mepfQgka0pgihRc87JQoU6ZyQhYinCUYSjAHLzBY6NYXamZRc62gWPsiCTifUtY2Qpw1bPj2bxUlcmZZu89PzKAci9acuWxRh7nq3X9nuTPqJFqQ3leRPCVN+bFWlLRZbeB6IUTCRkrRCxKiNCgFsMtY4o5WJuz7yHUPqxL2mbCfNi8zkRo2pH2MFLOHiHwafFJYhmf7rmVGuaywGeCatIWEXGXmCsXMQeTdijCSsasIc1huix4gGr6LGKA1bBYxU8hsFj5T2GIRG1tm3nxE6x9C+TtnmghKS0C7pmkTabWwnB7LAR0yxjImyzrW0x5RLWo7HnvTaytZh4kWNKRwwSDyNCmBDDhBintJOAA6LMIbUrnRd3sc/abkXPpnR5e+ynUdsStaWe7TO24MCk7d7eHl796lfjsssuw4c+9CF87nOfw13velfc9ra3PWhVHR0dXyI4626XnOwuHFN85t3daWJHR0fHvyV8/OMfP9ldOG74ufO+HuRPlKatJXFS6AyJ4AzhlMmnKISTJZpUbtIVuRRDJXP7EU6V9qj0iTYTTvPPKqPpybXmV9aZscSFapGhEA/LMkpbsXctL+doH2sNNLMJc4sWWhol5G9Lzh+HKN/TOc0lnfO4xA0pHnM53qd8IwMKqd70w3Rz+RrMCOm/lt4pn82FHlLTBPZIRHvR7NStx8lhWNLWJLERqTK1HUmyXdnlLcHFZq1TzU4hbMqAUenrwrd67rWZN2Se3dkcUjKPzNZ0SFzCVJ/chZguszgB01sYc/8AQrHfmBYpaq9CSjQsj9DyHDIDix0Xwqh6sjeW2aGUvdDFPu6KQrgnEjoT80DloCmTgYbUt6F1CJUPRxjJYZIFgOAdAg15cSc4KnFTf0VEUiEklRi0BDQ39yCTpWTs/MLaD+ZsP3gAY6VxEvMVxNgDJJS0ia9Q0nsmbcsPQK4v1V3asLaJk/3h1F81udGOZb7OajGvNpFQHLwh2Z7N9m1RzCQwI8SIEKdsQmHTUZ3LaicXxWYul7TtS9VHwJgY2Q9k/q1EcznUdva8homACYQvNhmz8+eVzufPUc6v/Au05dL1N2LhRFTLr1tkWb7Qzib5wbHtL4m6S8t3qiZ3ty+/FhyYtFVccMEFuOCCC4729I6Ojo6Ojo6Ojo4Tglvf+tYnuwvHDf6MW4CGQyegJUOXGU2vdsu93RpfeXeOofYCbR2OSFztzLVpisFsKRaTCeJUJLEqUT47y8bUirlsyKdNNFQ0LGml0Wo0BnMctSZh3qZPZbt8yXfL5TbIABjv3LY/ei0bCEGgJqiNxi0YZTs18yzebtO3Wn2wGn5mG/18u3adV7WlfRFCXcdn85Z7+3lrCUSNR1NKyMhMRMoRnXFQJ5ZMSeggppTHroQs+Szb6yOJ8zetY9OBQoTuwqzXrHrR9srM94YjRhNP41JMgsRGZvKWzsttNkdFp2sfed79YwBq78VS/pYyM6JpQ8cOQt6mp8vMOaAsBEC1CxlMlAn99FjpcyBsuXMARNtQ/yMGs2ojC5kHyndat9anA0Zz02h0qvawyItm82b6Jy8OCdUVQcmer1lYiVGcngHiXpExMSMgYgJjQrIZPHIiXteIWLGQvI194ZXKmDFInhf5wCmudocHpIUKD64IZZJwefy4XvgxhKhOoUyaopC42UmZDWOT1nhckFkymG29yDs/soa26RyZPu6H/M6TClST1S4E5rQseKgtYGfKuPx60oXDInNGu9fN6pHnheo2tW9KDuscWR4fO2V5Nk7QsbKvPJh7CS6vKhnTcs/LOLbllmSlfmrSdleQ6fPylTSjk94S5VcpadqWvzaK5m1dEqb0Uv2bsRNpe+mll+5UGQC88IUv3LlsR0dHR0dHR0dHx/HGa1/72q35X8p+Gc686elwq1NOSFtkvnIKaVvb3iw2G5WwVZuaxcOzj43X55w2nqKjeI4OAS5SIneJ4Cikj84oWmNZqzDCZXLCfBTx/tos1vTAfEt3ibfb7u3W+lrus43aQDa+fE5lM9eSMqQmE8rWeyWSN5O2+tE4N42gmptFC7o2feBlW7bdeq/b7VUz2outzqzxHOea0xVh37TZbr1XDc92jGa6ScyJRGAhE1jJHarCdFAJI4k/JBJNPoLn5PzIcXKQ5CLStt+IlHblHLclbIkSS66otu3y85aupxAIQjqgJpyWyKLIqjmI7L0+sjha4qJVGKR8XXYDMQXOmtSW7Mokh+03lh+7XbHt3E15m7QIj6aN7Sgai3rdZWu7cPhVeaVkbFgWJ9KzLWcTJ7JcTwMQ4NJ708kzFJVUYwTn4CKndwbYmADhmrDVd4P0te6ZvbI037IWq8xBZ98PSP1NBFhaAAu6IMAM5ojIEYEZE0dMHBPxyuIAjuPGeHYMJ6Y+Srr0w1V9VPMhKPe03LrqOnNoSOg0BEs7CeQZN/K4UNbKoj3flIumTuuAzHC3s7mzDboIkd8nlN5hZN81+g5SJ24S91Scurn8DjPvMlfL9D3mXXNe1U4x2VDWqOx7Thc1FsYkX/+CxvHsHWfi8u5irjWYa21po/k8kyOnW1Keq5BkEUV7KVN0w8gUgtZcd5aSoWILTduMbI6XNwY1eZuxE2n7/ve/v0q/733vwzRN+Nqv/VoAwFVXXQXvPb7hG75hp0Y7Ojo6Ojo6Ojo6ThSe8IQnVOlxHPGFL3wBe3t7OO20076kSdufP/LHOC2s9i94I8BNovpI1Q8u4xAsxfXjKRYv3NVRy4OmQ8oLG8rlI3/sSQjrDM1+XO9v2zYTnJlAVHKQGs0j+aCN9Qdt/XFrib0m7VLdag+wOg/l/EqrSj+OF7Seto4Vm2uvPpiLTeD5h6zJM5pmtYYaz86J0cQz6VfK8GL78qm88UO5vibVVgNUV0l4MSG0kr1RyH002oVCtFmC1WXts3m6jEXJs2RsJlKMDDm+PDb7E05zcxLcyg2RlMldS4KgkFFKJmUypDlvibhqCSlLgi31fQlkwny/RNbeRx2TpXvt7JhtyF9KZ63Cpv1sdxP1eLX9bq+zJd/soVp9ESGnM/EN8ZEYdVxQtFhNnDfI27rYpOfPyO5jRAtxgh2nTTZp7b20pgvmh9u3DgYTMCEZ0LDPSBsu9Vsxm0vMs7wcNs8xi3DpWS/3l6vy7XNgz0dTR9u/TePSyqOOQibi7SKiaxby6oU+No4sZ/ainTe2otUuNGVb0tYGe66rWbCsdobogoH+KDUkpT5LYP1tbUwVcbOQl22g2905nBcHa6eYIdmIZrEVHU2ItJvHQdMR5GT3D5LN7myLGmWhoix7LNGt1KTnqfqtv/33ebnW/bETafvWt741x1/4whfi9NNPx2te8xqcddZZAIDPfOYzuPjii/HN3/zNB2y+o6Ojo6Ojo6Oj4/jiM5/5zEz2sY99DI95zGPwlKc85ST06NjhqnEPp/DxJW0BSwaWr1eWjzCWr9rkeISrePIezcUhCWvcGSclDI6UHZbESCYPps5YtHYMAQhN589Fofk0f9drZCVuG1n6+kxpIVIZQNZ6FZYoQnbaSxxCAkbDFJGUd0q+kqTlQ7gQTnN7t9hCDM7GCYX0U/kSGVhvQd1A9s0IQrMFVcpkYqSJa+OW7Fjs7D6QEc3jrTeBAePUK92wqGQBwThJsmShIZaU8G3udSYZ832vCcCW/FsinHYbIxPa+4QFItUSS/vI4wHK57YW+tD218ra67NzAvn51hskd41QzA2IrKTrvE3xWR5sHkwapU1DMJXB2Uad2PdA0cirbxLnd2BOs9w9jfP2+PI5luyybdp+NC+pDWM0Q2arDeFmx0gONvc0ZnkyFcK23KLcVee35+Q2zTNR9aPq5z7I125MreT3TjHToveamntPxlRIyYtVOTURs1QHoa4PgGkTdbj/xUDtTFMjBoX02wNOz7zsPCn33sm8cCBXTHekMMmyM0CyZjZKunXuuMnBIixpK4/S0qXor3HWls7v6aLdPbdHH2fy1sHlsuPMujw19aYxseZ7yhzTMVrekZPedLWJg3n+5vSxAfHu1pABAF/+5V+OP/iDP8Ad7nCHSv6hD30I3/Ed34G///u/P6YdvLE4fPgwzjzzTFz36RtwxhlnnOzudHR0dHR0dHR07IjDhw/jnJufiRtuOD5/x73nPe/BQx/6UHzkIx855nUfb+jfuKf++x85QTZt5VNk4cPLbr1vt8N7oyXjrU3bTfEYxAFZaLbnc96mX9XL1o6u3Xpfb/ndhUy7UfflOJZfOmkfumkfwf44yClHUf2Nxqbx3ESikmQuy3cvb89p5Uvp/dDeO8vvbCZ3uU6j4YfQkL/mc392nuX+tvRr/34ryVPicyIoOdoq2oDJdEhtNkRkNl9lxtSILVuZJsl11eRT1ha0hBMt0zRkSBxaeKcUoihWca/mYJiNDe/yTnPyTivpkq/2vtv3pW1jTkoZbcGNpJOMjyFLKzvbWbvSy73zorUpGphuQPReTL54RD+kuIQ57j2iGxCq0JfzyeV6cnvOanU6zG1/E5auqpCBhUQtJF00pnpCbabHmOPxlTmeSbQ4kzkeX8mnYtInTKmuIKZ7jP1125a239oGzwRvdR31nKKZZP50LozulvxNect3dXvbm9rfFbvWua1vR3Ot29o/udezRsAV+Nt9/8Y9sCOyw4cP4x/+4R9m8n/4h3/AP/3TPx20uo6Ojo6Ojo6Ojo6TgmEY/sUpHHScWCReQMwSiH0/ci6ZMPAOzjk4nw6v4eDT4R2cxgcjHzyGlcYHeIkPg4drynmpz5nQ5Xa1L0lTSs0qgIq5BgvVwktcBleazVG1mAMjhogQAmKIKT4FBAlzegoIY8jxqUkvH+XcVE9M5i2COWI0/SkmLYoW4W7QooTmk7ghPCvlvQ2EiWrozuUL5cmcs4CjoQAORJAuELqb6tF7k58TWbyoyCHT4RtDvnNVA4OZknZipZFXtHB1a3Udttp8bflEuC7nNXXZ9rK8ueCF5PxGlBuuZGGllacLQllbE8iEImCc8Jnzsgx1XlNHWWyy50r9uWvLo7Y4L6pdBDER2BFi25MTacoRMToEF8DkENyEOCWCPFoCXQlbJcyF1A26Hd+Q7omopXTOzHZ3Ce0WfCXXt5O2NbFOHGtSXdOZIA8Vue6jCTNpHhCESI+GbGeRcYxgbp1hprTjtBtkSVtX38tzUpZy3NpEtVc6L1tDz1wuO5vxW+uq73Ldv7bVXWjn5Xrrc+qz9qt3SedVJbbPS/W0+S3sr8pSetO1lDrbsSi9mEsX30cbcGDS9r/8l/+Ciy++GC94wQvw7//9vwcAvOtd78JTnvIU3P/+9z9odR0dHR0dHR0dHR3HFW984xurNDPjk5/8JF760pfioosuOkm9OjY4+8jn4abxBLTEhqha+GBGvd2x0rytHFRZLbXaaZVq1qpmlNU0q+zd2Y/yaDR70TjVyWTHNtSOVcjpUYjTRKw6ON8SshJfDTk+rIYc+pw2ssEn+ZDOGySdiV/v4QafnMZ4D+cJzrtCJAu5nMlbO0JCFGXCVm3/hpgJWyVrgyVnG5JWCdppnDBJGEx8GieEKeZ8zQtuwiTkcpgCiIAYku1K+2EdWRw+kSVq6w/p3QhEJXYMIWfYSNZqleZZ2H7NJl7qK2q09RZge44pt6FP23suaJhqS9I1LRYyT+VWg9wSfKasJffmZUXesHulXC3f6XpyWklNITOq4ZVngTfd/yVZS8RuOG/jM7DUy12xxJRzfT2byFTeENoxnslsewvxqp4DXANTRdymvkZ5lzCIIohd2nYfnZhFKNvtg2y1d87BkUN0BC9yXzliTJrNreZzvQ3faEGjJmt13hVSvqB9hlut6Hq3Rb3tXn+LfLWt3qT1d6iSa3x5m74zdbfaz5awrYj+RWQqupqbKd2SpzUpWepticElGWH/ebDUz6M5Z6nf83prwnb/+gu5vV8fltq35y6Ru0tEr63RjtD83JZSnhO2Vrr7HD4wafvKV74ST37yk/GQhzwE45j+QByGAY9+9KPxcz/3cwetrqOjo6Ojo6Ojo+O44n73u1+VJiLc4ha3wL3udS+84AUvODmdOkZ48EevxCHyJ6Yxsy27EtdFjJwrGWvZdns3a14pX+cvly9nzDmMXT+H1B4rIgOIIOG/K35PP9PIfPLSgnxRVmygEmltpX5bBo0coKYfNZbMPm67D1kT16RLfC63jsKSrDgR05pyHeYcO97t2Fqua+cxkou1W9tre4yFBKpJIpe3z+v2eiWWKvmWPHX4k7f1z2xAGvuPwIx4WsJs+z0M2WQWPuzihBeiqCKU8tZ6zuZEfJPnK1Mi0WgVbiKejE1Jsosztv/z58vauEwknDWNMHecFJt7XMwcWE3OYhLBanomp0lWy7NxqERueXwaG52p/1RdUNaQlYkwNwFTm3+ZLTpV6drEi9XstOYT7AKVyu0Y27bmC2NpdrXmEdq5la+2foEeGPVpG4g8I96tmaMl0zdhe6uz1jYWt0ThsYWl7VoasS1l3yNbDLbskN5EWO5HXFpsIn6pylWZpZa31ajllynSJZJ0v35vuyebSdf2nDntu3RNlnbe72q1JnsN++PApO1pp52Gl7/85fi5n/s5XH311QCAr/qqr8JNbnKTg1bV0dHR0dHR0dHRcdwRYzzZXThuOMMBp2zaq30c0X7723DJ8zabvETwGDkV0nB2bCpv0sh1lD7YD61d0H5+URXnGfnqWnkjc1lWyiQv95yJ2uLpvsjItm0cZuW+Ufthu3whS2S3ajuW+1vuee2d3jgmI80vhG004xXlvusYRpSxaMcWpg8W+42REmgaZzAcE1ie+3ZL9cx+J6gh7lxF3llysa5Lt2yjKpvrhrZVQqDR+lyEXAvbeL1dvnLes0AeWrIXRsOwlLUE34Y6kM6tnfIocVm0RluNsJY6ySExQARP6ZlOD70sLjgGXAQ5kXkJHQCvIYMcA96DPAPOgXyUdJR0yCE5B4gWOrxLckclJAeoVroj1E7MTO8bFjo/q1lzHXlxR815RE5OEktIiNElJ4rsECMjxkFCRowRIcfNwSkvRsYUGWuRM5cy2m5UDXrTD52T1YLabEJxM1465mXcXX4GS9yZPF1McKhDWpBV+Xou2NSJYiPYPPvUPHMHJUrb6+elvKYcy01Zyq8XIBfqWcjflN7W31zWLviIlnPl7M2ldxKc2P91Es+hX4inkJ0HfFtG5FJfkaWJmcLU9tz5nPwyLb7rdABKuOTYjWIyJUFiYoJiMjNR0slOMIKJS0gx5LIlHkwdoakvvRPTj1rMfaj61g4qWtp2efw2UcAqKf9q6d3JWsWBSVvFTW5yE9z5znc+2tM7Ojo6Ojo6Ojo6Om4kbjoQTiV3QtucEbUVEVjIjsqDvRJ6oET8wRB/nOSxSgshQpTTlgBMhCJV7dmvp4N8Es2IWsp805yUrQhZwC2lmzxHm8uRxAup27Qr5+Q+7kfaYgNha8ZI73MeB5HZ+x7lHsecRzmezqOqnI5JzHWyIYIp16s3mnn7p+vSNZIZ2DpuyjQ83CbCu5YvlJeKqrqbNpb6edREU5u25GGb34xtkdfplnyclcdm4ulA88fc88yPJg4oHQQ4z3AO8J7hPcO5CO8BPyTZ4FnsRgODygaGH1jiyab0MBSTJYPYmU5mRQjOqd1pgs8mTigfRITEQ1EZ32bAyjsMZQ4wEMwxyTHGEo6RsGaSOLBujiNN2B6hOW+MwGjamCIwMiEwY8p9SXMwcN3npUEsBC0y2d+SrJ45aWZL6CQccpi0f4fIGExa81RelWWGj+lN4IUsK3WLBnHujyGO5YG2i1bVpTXkWv3sCjXdkLd5TjA382M+X9LvDS3na/vUyhY6ih3nUiZFHdhpKKSrF2LVe7AfUtoP4GFI6WEAD6uSXq0kLTJJR5WtVoD3dRlbl21D2kVD9iqhXBzG1RdczEMkopTYEKgxgEI6EAIoTOmYbBhA0yjHlMJxLLJxNOVNWsuHsaoPMUo7qU0Y0pfFcdwycVv+qJgbP1iS6YiXJ5dyyaPHgUnbz3/+8/iZn/kZvOUtb8GnPvWpmebCX//1X9+I7nR0dHR0dHR0dHR07IrzzjwFp7kTZB4BNTlkt8enkCsCT4laJQTTwUKCiAxsiBHOZQLb82xZyjJLFNbEZLuNf/9rsgQicSKII4REIMqmIEnISMdAJEraY6RKhiTbypHJ2kLCckMC2zRnQrcQtTXBuImM3DhGNmzJPENalHsn99OUXyTRbdqeZ+rJZK0hOypN6h3HxaIl1PUe2fs2I79bAp0WiPRZPuAwL0tGvtR2GSMyn+uYD5S5dpZYfZ9Eq9nMI02386Ui19v4Pvlt3ZbAt2MFtn2dXUaKMxUtQZanmQkcHRg+kVDRpzgcIgv5BA9mD44DYhzAwYG9xP0ADgPilOIxE1YD2HlEIZZynpBbSZNQ4lZ7kFSb0PQ1aww21yQXngk+buL5iEXzVhxUJc3Y2Mii2JcW29IqY3USGCWPS3mpP2pbMVZtp+dGTZGorAUvJDlHIzd5bLV6k4ZsFG1ix0kTOBO7MRGzjhle5bGQuG1cCWBrikNJXKuJW9lKl44dFdl1FO+YXcsepM5taBebsnKtI5DYMnee4AaJDx5+5ZIN9NWQjr0V/N4Kw94Av7eX7KSr7NAehkMrDHt78BIOh1JeKrcn567g94Ys18MNA5zaWB98iotmO4k2OzkxX6AvZ3lhsH1uI4NDRAwhPetTkGMSW+oT4jgm2+jrEWGdbKiH9YhpvU7hEYkfGTGtR0xH1lJ2RFg7TGuH6YhDWANhTZhGpPiYjjhNCKNHnLgcgRFD2hkRI4FlQiyT70uLeLWMmrI8y2OT2rZkOceBSdsf/MEfxNve9jY87GEPw61udauZ19KOjo6Ojo6Ojo6OjhODc+74FbjpanXc22kJnPxxj4aMjYVwDSY9RUaIjCkCEzNI4ixbgUNMZcpRp7WuKdeZzglK8EoZbgiqloBaQvmwKppdmWwVWdrVzdmkQaKjankOGUJP2XKaLnFvZLQQL32x25mXtT/rcSrETBXa8cOcSG3l0ciWtHPt9mxbb9Xo0r1uNG038JrLWq6NnJEI81QnJ0LOpKPRlEpa3pzNHUQh3LMGtCXbScap0rTmOemOWiuXwJlY3obZfLLkbTMWSqQrYatjULSeyzPfPv9LxHtLwrft2U4elMgq10PlYIfIYqZCZkQU8jZiQISXY0gH10fgVS3TskbG7CWeiOAYZVs4ezCnGcdwYE79KSQzanVbNleSVzuivvCgmoNpa7VoD3LMmnuIQW5uzKq6uk3bxaTh56PV9Av1uRrnsr3btpX7UIVm5jWMUztvinmW8i4iIL2jqH4veSqhFy3pQdNyjieCh8NABA8PD4YnYJD3Xiqr9TTvQ6rfizqvqOrvDs8c22eupCNUw1/nu767NF5kZSdBG0o5kXEjYyYzP+d90HQ7NNU7TlZ+kgZ4IkOdc4m4dUKUenVSqeFgHFgWotUPviJeBw39AO8HeBowYIBjDx8GDFOSefZwcYCfPPzohSROmunOsxwR5FiOWDTWm90f2ayIPK8cI1icYSp5y1NADBPimMjbOAbE0YTThLBO6bAOiOuAsI6I6yjpmNJjLPIxIo6MMKWwJmfT3xppSpUFD32H6hSaE7b1L5RNscyn5V+wJR3cthyh0Y3fiAOTtm9+85vxpje96Uve025HR0dHR0dHR0fHlzq+9oH3wBmnnXL8GzKEUkQhSZU8VXJ1DMCY44y1OY5MjCMSxsDgKWIKwJEQU97E+OLEOf1FKb+eTB2mvlGPmI4ppP5MMRG7Vns38y8NE1URGWzsN2LTtmFONBOXLcJ2+/CgctFEW1kZt+eVtOdEZWkb2m5tH9JuIS79b4ZJIhuI25K1M3m7i9y2mTvGVuM0aSXrZ6zafa2+kbn+KN6orZqbS2cHOZcoscGtdlNlXsKGVGvFFm3Z5XIzuUSWPsV3AbdxruVVaBcfUN933qfM1npM2cU+HRgLVy+EVKbjKAvzTafFo9ipLdp9DkQ+HS4dzjlE78Ucgkf0PoWUtpdnOw2ypZvERieREmr1MoC1J5zsX7pkI1jyiBMBSzGUMExwIcDFtAU7pSe4MMKFCb5J73dQNPXF0p7a6iSxAaq2i8Fqk5jtbS/3H8mpoZqJIGM2wjsS0xTJ7IQezlMySzF4DGKawg8Ow+AxrJwxWeExDE5k3pQTExaDL3UPWr+0KQSl88aEBZEMlSyGNEqCepU18UoITGI6gjDpAcIYCSOXYy3pNTus1awFE45EhzUT1tHhiJRbs0Mw5UemYgpDj2jakzaz+QqJK8HLqOdkGh6yCWTNVX3vEIkmLpm50swbtzmOSKDRgabtZUs7ADmhoE07eSzyO2/z6lSxYSvPp7VVG+Q5DvZoTCSECS6bOxibuJU1ZdQswpTmD03BtBdBQcw1RAaJXRES1n35UubS+h25dNamX+c5dtUjPzBpe9ZZZ+Hss88+6GkdHR0dHR0dHR0dJwXXXHMNzj///PnHHzM+8YlP4IILLjhJPbvxeNer/wg3GY7aTcXOaEkd1fxL2ir6Ea1atrUZBKsRGwzZOxlHPp4ZexKeItq4WUu30eLVemqTCnNtw5ZUbAlCRUvdZLJP4nnLrqZhnOmg5KnjHbXJWDRm2/J1GbUBG7ghkW3fGE0f96fU2hJsIkvknCVfl4nDDYQijHbVAdrbr7+KTX72Kh0mQn5IZwQra4EmTz/UqSmr+UqabKgXtFvflrB02hJxa+OWdF0qM5ujGm4ZmyXtv0392wzOdTEiGGmrMZM6zyJEFxDJITqHOPkUOofoPIKTNEncO4Qs97P47DznEeT8XC+57EguOnUol2ZgcShnSBPKN7h6NtKW/VhsrUbd0h/hYpQwSFzCGOGF0C2hkQWRc4AL87KOk4yNvU027VVkGCetwUIHLowhIzsADDFda+J3E6HHzgGhcWzljVMq58FJ1baYnvBFnpxcqdzYX22dX/kF51lq/JgomdHIZL6xlTqzmcp1PL+cGOUHyaZVU1njEkZLJqrMlFuKcwRFxqEYcYhtfU37tj/Vy5PbYSqoFoxaIrdEqoWwLFZStc1rypi6Stn2/KadWbrur9QGuboK+alkjdcOR60pnWjSsZFNgNF8bsq25/Ig5lOAuFeT/LZte6AND/YCPGrEOAJ/84l9yx34L7xnP/vZeMYznoHXvOY1OO20046qcx0dHR0dHR0dHR0nChdeeCE++clP4pa3vGUlv/7663HhhRcihHBM2/u7v/s7/PiP/zje/OY34wtf+AK++qu/GldccQW+8Ru/EUAiUZ75zGfi1a9+NT772c/ioosuwite8Qrc9ra3PXBbn7geOPWEmbQ15A/LB5gk0vdp2XZYeVlv4tk7epNG5ExKUGQMWqYtb+qctQupK38j8+L31/7fZPVXKtdfy0lGJa5fxgyg+RpOGyCJkkaoLdOQEvW5dT+W+7tEDc5LUhY3eVa7iM0nKxfiuiayTB35XClDcmUVU6SX1zKD2+8+NSUWS1f3qRmbalz2CW35hZDbehbPtT3H8rBsAVcX2DyvFcfD+fZxW7qVFXF1ngmqclaec3ckLrh5fhMxioogZRCiEKdRZBEEtf0amREpgmNAjKlMJCdEb4lzNvwpW8mJ4MRWrYOpW+ZXbEnarPHbzF8DfY51sQUomu4kGq1OyFxrozWTuCLzOV3iNixOueqyLtb1lnY4E8aFUC4b8Lc9di0hxYAQ6+IAksQGrwMiARxSGAmIzhwERMeIzqeQnKSjHAGBfCLphVBnMkS6IdQjkdgblmcDLs05a3M4953yFdh3lh2TchRinTiZp5iR7JoWwl21p32WzYl4ex6Z+rT+JGOjlc2ZWLfPUnnODoZN5Rd+MWbCxTJL6eb356B9tMiOQpv3QZR0lGcgyrshkkMgMnOfELLMISi5Ty5p4ee57hDkPWHL5zpR3gnRvBOi9s++E+QenCDOFjHsRscemLR9wQtegKuvvhrnnHMObnOb22DV2NB63/ved9AqOzo6Ojo6Ojo6Oo4bmHnRD8PnPvc5nHLKsTUt8JnPfAYXXXQRvu3bvg1vfvObcYtb3AIf+9jHcNZZZ+Uyz3/+8/GSl7wEr3nNa3DhhRfisssuw33ve198+MMfPnB/PnHZc3DotJse02tYhpA4ZtsjYnJ7zlE8MocADgGYphJOEzCO4HECphE8pgPrETyuU5lxBK/XqZzKrWwcSzmtb5pK/dNU2o4xxbN2lLVHaUjn6srkozITTg25ZD4AlXwITRidE7IiyQKJ9p8TrcFcxmoGWpmr2uEqpKpvQEOUCc2ZqUTVDFXtQLZkkyWCIny0WoNBHAsJgaFkkol7ITO8nOOF1ChklBIbXEgoQ6BkIkVIKKA4HyrjMR+f9IGuY1U0J5XQs8RQzJqbJV5rai5obHodr1JGx5Sz9qat1xBPuT9UEU75Ouy7p2FCa+K0kOTFtmxZhEj5oqvGxSFViWODvI0j11HI2TI/6oWOpn8LyOYEzDOXxhcgRDiGeQ5qR1TVM8hcObFyHOHDVMyHWBLUpL0lTqt25DnXZ8ySfGgXJhaua1m8MX+pvH2udybOdpbxpowFyMoKuCyuLFx3vS5FtUwSrbQmCampo+2W1ejcjO3U4fJ7vMrleckluZ2OecYx1zJermdpMaWt61hi6/XC0tr7d2Dj7d9npWbxvE2VLSyYEpIt5FnRDZUu9WZX2bZ6dzn3RGDNEf/fDuUOTNre7373O3hvOjo6Ojo6Ojo6Ok4wLr30UgAAEeGyyy6rdomFEPCud70LX//1X39M2/zZn/1ZnH/++bjiiiuy7MILL8xxZsaLX/xiPP3pT8f3fu/3AgBe+9rX4pxzzsHv/M7v4EEPetCB2vv6a9+L00499dh0fj/oR1jWfhXP0JWjkYA4iZf0KRSnI+ItOk7J0UiQkIN6j1aHJMlzdHZOomEo5+f6tK0QkoOTGEq/RGO3aN5u/jRzSmgwm286cRDChGT0jgA4SZOErg5BALt05LioqrmmTKQki5Q8X0VXtG8XD2CuDbppnOQfS8ZVhLs9dNsvNwS3dbikeZscIcXSjjptgsSVHcpjwKaThpg03SeTk9JKQqskyH2MZTxI1AKp3Ed2Jm1smmqcSe692aJt4ywanFm+aWyUTM/s1T7jY69PCFRu4sxFpmZIOD/PKR61HKuzsYV4Pt/Uq+1sCKGPSungPsSGIUFZNFSBRdMg2UZzFU8Eb2VH2sjUxrPjJCegkiXncZydW+WFCqD0g3Vk9F9d5NgyUM11cxs2i0A6xXJc74ze+w1l2vyWU7VlbHttfNM4FVKVZXyMHOn30cosoU0mP8U1n2t5ztt2jsxlkweTX/W3itdX1V5jfZ/m9465vve7xnWLflosasqgLg+Ucm0flvq8WZZuhrzxiraqec8ULVGqFousLJqFpNnin5gJie25bZ3NImHpW5FtB6OYm9Fnj2eLipX2uklbjXa7+GgX/mx6kzY8aVt5kbAsMEHeRdWuE4MiY5RfpmXil5oyvHB++TchHi9HZM985jMPekpHR0dHR0dHR0fHCcf73/9+AOnj+oMf/CD29vZy3t7eHu5yl7vgyU9+8jFt841vfCPue9/74vu+7/vwtre9DV/+5V+OH/3RH8V/+2//DQDw8Y9/HNdeey3uc5/75HPOPPNM3P3ud8c73vGOg5O2n/oznH7K3v4FbyyUEGBDGjHEI7MeMdmaDYwQI0JghBDlYExTik9TLPEQESaVhZw32XJTRIh6jtQZ5WBOdm3FV7iSXtFqZjpjxsFckpI2mVSgROckLq+ETrg9RzE57yFx3qNe1Ukc+og8OddBlfaSX8ohx0t90p444dF0JkFyP+fabDpGGhSSrhB10YRqczhGRnTJfnB0ybt2YEYkRiCRm3hAOiJLGBnBSUjJommgRBRGKReBtP0a8szIODAZcrLBjLjJH9X6wS1knNwLJ/fGEYkcQubJfdwx7hu51q1t5XYW2ta+Wq3+9vO+InIWyDwdO2uvUdPF0z3Xcc3bEA+Z4K3ljGL7OXLz3DR9avu+abyUIFRqVG+F3hcdm2qe5XvYyiiPY7n3Emo6ywgEN5/LEsdCf7ahHqfy5ijEHRdyr5lr0ZxTj58l0c25RmbrUpntj20fO46NFtg0RsouUZO5NGZ2nlVjA51zOoZmPGFI3GZcWhnMeG0bp/n4aJxnz+6msaqffR0H89uG7WVyPVSIW3B61+V+8w5jk4vuv+Mj7/xY2umxuOvDm10hvinnq10eodpFUHaY2D5s2vGh/a80y7eRs1YzPrbxABdFE19NVrDZ5WF2eCzv9jBmLbiYLWl3muTdHsxpHZZrQnUZ7Q8uGWk1w2Ykbk34tuF2HH+vBR0dHR0dHR0dHR0nAW9961sBABdffDF+4Rd+AWecccZxb/Ov//qv8YpXvAKXXnopfvInfxLvfve78fjHPx57e3t4xCMegWuvvRYAcM4551TnnXPOOTlvCUeOHMGRI0dy+vDhwwCAs3/gEpxx+vE3j5AJHSUhhKBVcnYKEVMImELEOCVPzXEK4DFgmgLW44T1mMIj6ymFmh4D1uskPzLOw/V6wjiFdL6pa5zSMU0Ro7SdCd0gfeSkFRxZSQ79KCseuZ0eSq56B+/E87l3WA0eg/dYDQ57g8dqNWBv8NhbeeythnQMDnurAYf2BhwSmcYPrTz29ga41QA36DkSSj2rYcBqSG2sBp+8ssvhnXhcd8l+Z/YAbwgo4aSzVnEUJ0YxxKyFHKeQNJynpOkcxhFhnDCtJ4RxxLTW9IiwXmM6MmKScKzS61TuyBrTOp03HVljGkeE9ZjrC6O2M+U2s4a0mLCIIabnSrR9Wzuri8+i5AcyiXzOfhpTTXoLwbrpc3qRMN/hvG3YldjZVPhA5285t1oQAHa7GFISpxBNcGq+wieZ89khVfQe7IaU531yGqRxp06EkjzFB4nLeTb0pp7cRmmLxY5qCglZw9oQT0vmK7ItUmZA7JWCk31UiiGRPtF4po8heavPMjn6oyoAAQAASURBVPFeHyZQmODCBApBQknHUOVRmOBEVtcdcxsk9lRJNN9L/7i8BDZANTETT9toWDYEXSYIN5lxyeZc5oThYqh1utYEjBKBriIsN5oXsWMk8Uo7E3ONTMfGrq013dLaus3mYIrcbyhXOaSz7WRSUA7ivOCkJOamqZW1lDmRe+kpjUlLnHRuChEe7eIiyWJi+T2zi376e+GMjLIcVXmycfMbmRejLNm/ZQHEvI4r0jxrlXO7SMGwi4o5P+oCI2cyXWWZXNdFyGjK2Dr07xZw9TdMIfbrBZD5ldDsKlko6nlp82wujLCluA/yS7ETaXv22Wfjqquuwpd92ZfhrLPOWrQJprj++ut3bryjo6PjZOCsu11ysrtwTPGZd7/0ZHeho6Oj4180nv/8528kbD/4wQ/iTne60zFrK8aIb/zGb8Tznvc8AMBd73pXfOhDH8IrX/lKPOIRjzjqei+//HI861nPmsk/tXcm/nnv9KOud1ewEAL6IcUxCnGbHNAEFzFRQKCACQEBARNPGOOEKU4Y3YSRJqxpwkgjRjisecIEwsTAxBGRCRwICICbGD5ErKYIngJoCqBxhBsn+HHCapwwTQGjEINTEEIyxqzdm4hLRlQzDuVCYElbIgI5gnMOTghS5xNx6r2HDx7D4DHEAQN7DIhYYcCKipYtiACfrAhMLFp/7MEYEGjASCuMboXBeXzRr7DyA4ZhhdVqwLAasBoGDCuPYRjgB5/aHaR973LfnHOgTNq232TyQRqFCJV7EMXusJKmYQoI04QwTAjDiDBMiXAdkmmKabXGtBoxDWMKV2uMR1I4rVMYxgnjXiFtw6GxxMcR05iI26htjQExCHEb4py0TV/XhVQ3X9C1LpeRKRkC0WrimvhQOWW52ao/K1vL8lbbqh0tM2+v9FPlxw5HS8ge+Dw+2Bmz7dGiNklJTRmU1M2TuQnnkNTSB2DwEg6A98CwKvHVAAwr8DAU+UpClXlv0lqPqc8nEje1m9K5D0TGFIYZuWrlQ+6FNQ2i5kFCBIwNb2vHG6HY14ba2p5GYFT728k2N8RGN8IkeZKeXLLRHQiY5AhIqpyBUzwgqX0SiVcwS/4U5mk2kmTeGURgMRHiXSJSk+q/B+fQp3DQ+5mIdAw21HjKzzIZ36q8cyn0iVBPYRoTdl7U2Y1ZEh0fAuazyY4RZ0IdUchsOUhsnJOMFwUbTqBJQpVNiVDHJMT5ZOIq17qmAMSmzpiejdQHIdOtyZl95ljeTWHGipxZpJN4/i3w9vcqjSXlRT6fZOa3rPym2fN9Pr+uN7WTyV2J14c8V0vvBrnWubNQ/duBq78j9Agh/Sak/PRbkX/PQ6hD+f0IIaS/Q0JJa17MbUXTXjKhFNUskPSLdNFz9lJbGCujRzsvnV8mG+po8/fHTqTti170Ipx+evpj8MUvfvGBGujo6Ojo6Ojo6Og4mbjTne6EX/7lX8Z3f/d3V/Kf//mfx2WXXYZ//ud/PmZt3epWt8LXfd3XVbLb3/72+J//838CAM4991wAwHXXXYdb3epWucx111231b7u0572tGyjF0iatueffz7e86k1TvvC+pj1fwlFa0Y+cJK6SyIHY7Iny1MAh+QYLB0BURyQxXFM8fUacT0irtf54HEC1msMR9Zw6zVWR9Y41eTbcnG9ljpHxHUiQeJo25yyXV02zsjYfJzNYEkc54Ro8iAhGOA9aEjkAw0rkJBItBpAqxWw2gNJGqs90N4KtNpD2NvDF/dW+OJqD7RX5JDzSM6r6hqGVP8w5ParfljiaYnU4NrmcNQPZDYku/2w1Q/eEDBNjDABIRDCNAin5DBNHtM0JNMVYUKIUyLnfcC00viEaRUQDiWCVgl0/cCOov0c9WM6Gk1gJWzbD2YTt4SpE626bM+U1f6pOLFidXDFGCSeHFmlcODkwKqVDaJlN1TlS52uqds3fbD9slp1m8jb9klcso9qbwNXss02UCttNj3aOkz+prY29VNlSmYDqEz+OuJs4sN5hlMeVXhVv+LEu66Ek90jCUt6tSfhIU2TpF0qPzgMe+ZYpcOb0A9CUg2F1HLeFRLMuUyQ5Yuw84cZHCk9q4EQY1pQEr4PUfnZkRFGxjS6fISRMa0dprXDmEMq4RHCuCaEkUSejnFNmMYUDyMlLnckxAkIE6X5KXM0Js4wbdWPhsOUMaq1pdOiFOVFn3Rv3ODhhqT971cr+NWQwj05VgP83h6GQ+1xKIWnHILfW6X0KUYueYOc6w/twa8GDHsr+L290s5Kdx+kPjifDpI+ap9Jx0fnSR4flt8gebcYu+khLxqlhaiwTgtMQXcHHFljOnIkpbPsCKYvriU8ksskme4wSOfm+vSQnQXJXvsktt1Dfudlm+92osEMlk6iaoFDfntkoYOGIf9W0GoFt7eCW63g9vbgDu3ltD+0B7e3B3/oULr3bXpPyu6luJe421vBa71DGhuSsSEvoXOg/FtEIJn4tbK6vs9j+TtBF+pCBIdi2z7Kb3hcp78RvOzyiDJmcb0GHUlHXB8BHVkjHFkDR9bA+giwHoG1plPIIuNxBK1H0DiCpgkkfyuQ/H2ihDuEcGdrw30HTnUTndvmsvwm6HuTq5zdyNudSFurFXBjNAQ6Ojo6Ojo6Ojo6TjQuvfRSPOABD8DFF1+MF77whbj++uvx8Ic/HB/84Afxute97pi2ddFFF+GjH/1oJbvqqqtw61vfGkBySnbuuefiLW95SyZpDx8+jHe96114zGMes7HeQ4cO4dChQzP53uXPw97qBNi0BYoil9nSqB/QujVRNVhqjRqjTRPauG45jqCgYSgaU8EQryLTc5IWVfrQqojZrIElNiG3aRCqhhaQ6iQCTaNoErmshVtpPTmXtpRaEsSQIqq1lNPOEEZEIN+cR67SZlINJ207a8kBOa7QqCXexD98tosaZNwCjMIeA5OGErfhKPGRS3oEMDLlcjbPpr3UYdvL2qdmKCLD6gjqFW0dL/vhq0fkRJKmENn5TcjPQinMsWh86Te6br/1QnQHIWWnyELUckXcJqI4FsKWWy1eJWznphpKDpJfOpDY/DXOgVC2skfZQh5BaXu6pINsMU/yFA85z9UhyGxRl/Kmbm7itn3toyV57b5o3TadLA+oPedkyiOZFyEMziWiVUyNrAYnJkE89lZOTIWk9CGJ53BvmMlWGlfTIisxW5LNi7ikGe8SwRtd6oeXfrErGqeoOdv0bOlzQwyiCNmUnjZEM4F8SM9zBMhDjQuDAoOS9zTAxULA6WIQuURyZad4xvldnteqAWy2ZDcazfXW681ae2wi+n4MMQKOgcDgKQIuiNbrKBrJqjWrmraJdWfRZmbRfuahaNbmdJvvh3J+Zu591rjNWrdZ41buiXUguHD9ldYqN1qtqu0aopBxlpybGo1a1aaVdDBp0X6u8nO5kOQar7RtQ/6dUhMWlUPHZjFKF11SkH6LWF9qeYyiaENPoqW8Bs+0n9O9Tvc2aarnw6QxrPJ5bMdPZc0YsWirZ63oylGjeVbtEOWVJDUvwtX9oGaM1EwIgtFwNvEciuZ6SY/pb4W0epLLUDXOUrfVuI6h9EfMjWRnnNXE2b5jYnGBxOSVGTqfsWjy9kO3advR0dHR0dHR0fGvGk996lPx7d/+7XjYwx6GO9/5zrj++utx97vfHX/+53+eNV+PFZ70pCfhnve8J573vOfh+7//+/Gnf/qneNWrXoVXvepVABLB8cQnPhHPec5zcNvb3hYXXnghLrvsMpx33nm43/3ud+D26E/fDXL+mF7Dzm2jaAhaQk5JKyVBirfm7XFoHVqnKVORr1y3PUubvuyE3F9xSJI/QkMianTLKgAWgkrlkZITnmi2traOlKxMt5WmdF23lgeKjIQ0K/GSLje+vux0KHGrpGCKB0kHIfOCkH4BhAmEZJ2ikHrpXjiIwQf4LCPpRyKbvOSVekxbSiya/mRyEsV2ZSEG9SO3JjgsGepYtW+Nlmur/Vqli61J5mSSIYIxAblfjhwmJGdKDi5pinKEY6QQxl5mQ9La5xxK1vJseNIVUUveFoI0ovYEb0lbtQVayNcSr9OuImpDc16pr9gVjU372SmSXpEhby0S7ynPtHXS50jsQgtZ6gkrsdG88g4rcliRxwoOK/bYiw5DdNgLHnvksEcee/DYA2EvEvYCYS8AexMwjIy9gbEaIvaGZFFh5YHVwEIMOww+ZvvUgyGStY/Ffqd9wsp7ALFoc6qmpIZBNSjVRvSYzH8E1eocVdNzQlhPyVTIWmxHrwOmMSCsg5SLIosI65jSozhfDMmpY3LsmJwE1jY9i67etnWpRKAR0hNPQCAwiaYqRcQpit3fKTuoYrVH6xyiOLWKzoa+SS/I7Xlqz1Zs3LKG8gyWsLaPnOeMfebyZclbjos922xLVshBjbucFnu0MRTbtBKnmBxfuVwuNGVDqq8qIyZT2Jn3O4O8EPimb5Ut3obys/aVs3kIY5M5mbQw5iv0IA+GB7MHR58Xf/SZ4Aiwj2U3jCewF5njFPoAdlMiba1pDEPSKqHe2oUuP1jtSy4tlmVb0DIOSpJmO82htg2d7Turjehs81nCqbUP3ZYJ2dxFsTEdy8Jw5HyUBd7U3/2dkJULLE7Xlinbmqa98TippO3ll1+O3/qt38JHPvIRnHrqqbjnPe+Jn/3Zn8XXfu3X5jJf/OIX8WM/9mN4/etfjyNHjuC+970vXv7yl8+cN3R0dHR0dHR0dHRswld/9Vfjjne8YzZT8MAHPvCYE7YAcLe73Q2//du/jac97Wn47//9v+PCCy/Ei1/8YvzAD/xALvPUpz4Vn//85/FDP/RD+OxnP4v/8B/+A37v934Pp5xyyoHb++cQQXzsPg62gZu4+TbLmrcxx1ULsnjfjgvp7DgEtWf7bV7uo22LS9vb+rtNbgkq6yHbeu3OhJlTrUbjnEfkIXvgTh67c9rG23Od1Yqce+uOTX/UQU8hlucXVtlqbcgM66THkpnF4Q4bD9zqqds65QnFRIDI9rRs5azHttE4BWr7Jd1vHfUANVnIZMOl8WnGimjxnpc4YSSH4IcN42Pqy2NN1RjF5pnJzxGQCY3Zp72SvDB2dKuxYTiU+2XHxluHSTIGeu/ViZLnCatq3IrDJB9NvHkOqvFp+pbJ6AUGTUn8PDYzIk480hvnVNwQfZ/PMi9e7j2it2mX03PCUOOFKEyEExViUByj5b7msWm1BOtrVdJJvcw7NsSfjksm+8JCOiSv92Eez+kqv64rEYZswpj7QGYuATybP7UOrl7PQVazbE1lwWFbGYt5+Rv/O9XOq/zOBqr3pS5KVAsVVOZ0mev6jkjv4Kl5TwSnc38o8799NywsiJT3wfydMF/4KHZi86KHcUA5iC3aQbTJUziIlvlQnGGuBgxDcoC5txqwt7fK8UN7K+ztDdhbJdkweBzaW1Xnr8TJ5sq0470XLXmf+5Pt6pp+22mUd+BU5iuS2aIYAljsnMcpmU5KixvJPEJYrxGOiLkJdXopR4ofqcNs8uJILpecYSZTTGq6IsoiSpzGyoxG7lNENo9gtZ+X0erOzvN3e5J3nw/ES3/hnCB853d+Jx70oAfhbne7G6Zpwk/+5E/iQx/6ED784Q/jJje5CQDgMY95DN70pjfhV37lV3DmmWfikksugXMOV1555U5tHD58GGeeeSau+/QNJ8RjcEdHR0dHR0dHx7HB4cOHcc7Nz8QNN9y4v+OuvPJKPPShD8XZZ5+NX/3VX8WVV16JSy+9FN/1Xd+FV77ylTjrrLOOYa9PDPRv3P95p2/ATfyJ07Qtyq1sFFXUS3MhYa0X57TTk0VDLMnCQjzo9vRo5aphZuoRWe0p2nqiRrH7yfPvr8WPH6PpBCEKa9uxzeF0e6hu51W51ZKyaSpbfk2cXVu3Q1ar1UO/iG0fdxkkjedB481HNFtZ7ZZe1UgSrTVYxzoaN9t/iwaTsQ241F71MG0jm+ZjVIi2FFaaeZaQI6MVRnV+LXNb8mhWP4hyH9iOTyZm8j/bBglFE1fjRfOrxBtSzhJ1szDuk4dcJhOwtpyuwFT9wabR2Dg+aO+XyKyDKTt3VF7mS5k7eXxcMSXQ5lX1UT1OdvzsM7N5rObjAqsl2TzHem8X47r1WshWnRcaz+V1bnEx91LXV8hj7Qs1/VqaQ7tiqWwrs68c2lCOmoKbylVp2iDfB4VaR144KCRuHUYbV2IXlmBF2VmQCd+agC07D2rTJTZdLfyhkMqpf6mjm95reu9Ifh+IjE3fbN/XJ9M6YlM22ZottoDdMEi+2AgeVFZsF7thSOerTWMJtR4SB2bkfTbhY4/cN5lbZH+XzOhU7/1sW16eYbUhq2YrxAYwxPEbi9M3TGNyzDclh30sTv2q0JbLDv9MqPXGRBYnJ4LJLIPavK9+08zvE8uIpZCypCVctXTRvW3PaZ/ucv4aEVfgE/v+jXtSSdsW//AP/4Bb3vKWeNvb3oZv+ZZvwQ033IBb3OIWeN3rXof/+l//KwDgIx/5CG5/+9vjHe94B77pm75p3zo7advR0dHR0dHR8aWJY0XaHjp0CE960pPw7Gc/G6vVCgBw9dVX46EPfSg+8YlP4G//9m+PVZdPGPRv3Lf9p3vhpqsTt3muImuFGE02bFETrJEzURtiImRDZISQ7CrmdJalcGplkTHFKOZtdZtwE5p2M3mr/cs8mJIbciEVCUGZq03fosnkQbbVScl0gZd02mKNlHZF7iXuHbLGlNfQmTqcnGvKprxSN6Fs4c68Loz5BPmnoZsKz4QyRqqZXBPrhlSPjKDxljSXcbTEeibX7blmvC0Zn5+L3K59hjYT6y3IhjpWMkYlPh9LJ+k8no28LrNc1rbjmjRMGf1MV9k2cPU41veBZbyAomme55q5f63GebSLJ+DqXKuVXi1u6FjY9NKzdIDx2TZG9v6VsQBcc3/dQr7Na8tWdTdtkpXL4OxHDto5BHNP7DiVe1rudRmLslugpNMYld0CtdymU1280FY9VjD9mnW+HZycNMQq1UXUXnY9jrV5Fntv23x7f8s5zfnmvLrtzf1cQuXEqXmHsBGkIWyfay7coonDzA07LyFj0daXomzkMKMy79fydUhoFoMKEWx3XRRN30hFaz3v2MhxX3YLSDyIVnrWMM6hn9dj2ik7GmrzFa35lCWUHR42ruYqVKs/ZjMV3sTTLoJQdhWoFjpH+KyR3uz+iLoDIZi8aNqxZnLqnQVA6Wd9DXaENGWvmvJzUp7XQsqW1MIfHtidtL1Rf+F94hOfAACcf/75N6aajBtuuAEAcPbZZwMA3vve92IcR9znPvfJZW53u9vhggsu2EjaHjlyBEeOHMnpw4cPH5O+dXR0dHR0dHR0fGniD/7gD/Ct3/qtleyrvuqrcOWVV+K5z33uSerVscGtv/MbcMapcwdlxxyG2MnEQ4QQehBylTFGYNJ4AMbIWAfGGBgcGOOU4uvAODJFjBE4MkUcCYz1xDgSGEcmzZcwlHNyGFN8lPgk7QbTp0JMFtJLLiXTBZkYzUSrOlFKDpRaW5x7Q3KmtDck50eH1KmSdzi08jgkTpEOibOkQ0OSuZWHt+dJOVvfSuxxrmRr7OCTM6fBUW2PUx2joSE69Dq5bE2NkYvztxAQp2STM0xqgzNgEluc03pCmAImscM5rccUX48Y1xOmsaQnKT9ZuWxBLWHaehrGgKA2QIM4oBNv6lGczGWP4w3LUdlSJbXPW7Yet4QGV1uVaxIiGLIjiKamJSpCRYYUkxW5flfbgWUUQsVq2aWhIKNhV0AyTvoRr6YIrNmIynauJRsiZ1MIjrkmOpgrkxa1uQquytUmLBrTCJibSIASLhteDXPyejPJ7agmWZWMdUKa17JteYXYVVvQWk7jFYGf+6dajTMuM78bdPzU1EukYo852YEudponpCNKOBnZiGR+Y9Q0EUak9ChlU9zl+GTyJhS708VOtLE5DWuzumh31u+4dOF2+z3JO0SdJHqzFd97Dy/b4Z1szR8Gj2EYJExb84fBY1h5yU/p1aqUUZkffLW930u8hNIHdepIyfli2XrfDFZmRlnsDmdDv0lbU0PR2MzxKWlm8pg0MHkcqwPTBF6PM3ktm1KdY6lHNTpVq5Nly33SLBWtziVHmbuC7KiGsuDAcl+CmXwmpAVZybMPP9UTuD23LWNlC1HkvpVEvQAiMuW09Xc5k+UmXS0qtQt95feiyIvj0bquUi73yJDr24fDziSlZudvjm0LDOWuLs7OnXBg0naaJjzrWc/CS17yEnzuc58DANz0pjfF4x73ODzzmc/M2gsHRYwRT3ziE3HRRRfhjne8IwDg2muvxd7eHm52s5tVZc855xxce+21i/VcfvnleNaznnVUfejo6Ojo6Ojo6PjXByVs/+qv/gpXX301vuVbvgWnnnoqiAiXXXbZSe7djcPVV30KNz20d0La0k+OvGPekKKZvOVEoEYuROoUgTEUUrcQrYwpAOtYyFclekd1vhMYFAEXGT4yWFTRUhoYImOvImrVhEJjrkGvQSL2OzZptRLIGe1ZcaTkiLIzJSVRlcT1nkDeAYMHe0LwDuPgxNu6QxwcJu+wHhy+6BMxOwgJvBp8jld1OsqhN2St9itr3sqH9Ox7mcuHa8w2BRO5EYM9AmIoBG4MEmZCV5wpSTiNheQN44SgZKzKsp3CYOos7dh4du4UueIwZtpxGiHRVWJOA8acv4Ez38ARjgiRGE5UaAlpW3oighwoFnLXCfnqrQbbQlgTw0IKw2qcYa55to8GGiCkbdZAM5poECdrhkC1pGptKzgaZ2uF1F0s05TPzpryABRCSUkTo35YjUllF5WMDpnOLb0+eVcQUWqPUhklUtNzzEbrlmuN5zw3UWtHwzj5wwJBa8hZK0t9s8TU8thwPgoRqg7zItUO9iKK8z4lV6MhXJXItcSrWjTW986gaRJnf0oM57ZSOqI49FNSOZo+cnmy7PBAXxR5HggxqlvenTNb7u22edlqT4MH+wFx8JiGATxMmIYBPm+5j/DDAD9EuGGAHxhu4BR6hhuQwuTfKqUdwXmAPME5BjkGuShmAaAWNkTzt2HVrMqrWo1I3g3BkZKjtUDg4FL+xEDw4InBU8rDSBJ3yYFXnAAMYKzANIJpArsRPExgnsAYAUokcHLaNeVt/TwFQAniIGStmgMQ73GczcVw83IzY9WGzDmdnxo2cfPucEtpNnJAFmXEeWJUuXHqqG0x123KPadZH9nE53PIJriRZ+IVZr6xjS9rt1fyLeVtB9gsOCldan5CsPCELV4RV9SsdUZmr1rv0pzsnd8Zxi4tA0dB2j7ucY/Db/3Wb+H5z38+7nGPewAA3vGOd+Cnf/qn8elPfxqveMUrDlolAOCxj30sPvShD+GP//iPj+p8xdOe9jRceumlOX348OFjpgnc0dHR0dHR0dHxpYdPf/rT+P7v/3689a1vBRHhYx/7GL7yK78Sj370o3H22Wfj53/+5092F48av/7S/4s9cie7GzNs+xRZzONaPsixzTXbbp87y+ccRM9lqWwrU1KIAawBjAC+sKmsPeEAbRwLLN2zmcxoJS/lz9Itp7JjuztDvsIteWCx0/g0wv3qaMdo01gc6zHadJ9qEoT3H5O6+E7tVITKxh62J+1S8kaN/r8aeCRTDycD1i5zOVzRTHfeOIozjt2M4zd1EBf8gNF5fNE4jEt5A4J1HmfinJ3E1U7j2BUN+XYLPmQhJMHOtPI8qemCkuAiE+3LvBhhFifYyjjmcioHR4kTmAeAHRh7dRnPYMfAoO3aRQ7bj7rPTecz2gUcXVxxs6NozxfHhLWTQs0bYnFSaMN8fozwqB1LljZQLfLUGviF2MWGyzsWOEi1x6cLlOnZQrtai8pK0KqJBK5y7Fs1yUr5g+DApO3rXvc6vP71r8d3fdd3Zdmd73xnnH/++Xjwgx98VKTtJZdcgv/1v/4X3v72t+MrvuIrsvzcc8/Fer3GZz/72Urb9rrrrtvo7ffQoUM4dOgEbBHr6Ojo6Ojo6Oj4ksCTnvQkrFYrXHPNNbj97W+f5Q984ANx6aWXfkmTtu++6L/ADyfGPIJG7JZpGI29or0naXHEQ2KbjtQbeqxlLoZaHoN4SQ8lP5eNIJEXL+5cHP4Y7cHK4ZL5SNqFaNuPCKQNBGCliWS3my6Vow3ybX2hA9CEhhTYj0i1yl9s2mg1pCpbjqZLrWZVG13SM9qGOQlZNFgrhz8zUwm1DcjKFiQ5sNN0rVXLbkEmJhGSXcda6za3AxhblMWMw+anjYtUiQ9LhDRxaybBmkuY2WiMNj03g0A5nNdBvNC2IZDAhpzZcFVHg6Odh4tlDtihXYofmATi3c7Zr8yxIp9mc5Ikkh5SJCJJVQ5j8nnmoL7P0iH8ZBSyUu1eRxcRXUikbFRyNiAEV0jcyWdbqrElhMUsSZmnbjafK9MoBnns5DnV55Nmz3T5bdDfifybI3ZPS56YEpHfF43n36CmnP7OuVh+86ytVDTzqSw2LT8k7RtXh4qW3hf2mmE0Y7NmLlcy2iDDUl6uez73KXevEJPbnlX7LtT3NkDVe7NyCmfesdHIKnM3B4hXDuRMO+3OCDbva/2dOVGIcQT+Zn+fCgcmbQ8dOoTb3OY2M/mFF16Ivb2Dbc1iZjzucY/Db//2b+OP/uiPcOGFF1b53/AN34DVaoW3vOUteMADHgAA+OhHP4prrrkma/l2dHR0dHR0dHR0bMMf/MEf4Pd///cr5QAAuO1tb4u/+Zu/OUm9OjbgW5wDXm3TRz2WjbFsLSwaS5Tt9akXZhumbaIUgmwZTeQsBw0nUIwShhwipO2m0Hg0RwhAdLLtNIApAhyAiOSVHQ5pr6z2GWlP6Y5MyCIB25CrSshSU8bmV46qNuS3dbbttG3t19+txOyC9mylCGbK2q2mcmpVZild1Yk5sburtucSlGOyH/5WI68lZ9mSr4YgquzWulImNGVapzylbiFxDTFcCF3TL8AQt3PSdithq5ptMW18LyYPWiI2lnhjy7Z2whNrG7YxgpnAHOGY0vwEw9k5A5kyVAicG4Mbqwl9UC3obf09mmvZ9JzO5LPFiwNorJs5tW2B4zgpNO6Ahfvdrlzll5h5kVUvvqUBtm/RVpQis3UqJScJMydX1cKEJWPVYZUsAianVUFk6vAqwIUgjq5KXnGEpWRuqOtbIHQr4jgTtzUFrTqc21C9Qwizd0qxoS3ypkxtE9zEAbBzhVA11bZ94tkAzPtRgUqZTFUvmJJRMzMtwVqRt3IE7ELYLqRtG7N4ufZ6ofLEsbYxjDuVOzBpe8kll+DZz342rrjiiqzReuTIETz3uc/FJZdccqC6HvvYx+J1r3sdfvd3fxenn356tlN75pln4tRTT8WZZ56JRz/60bj00ktx9tln44wzzsDjHvc43OMe91h0QtbR0dHR0dHR0dHR4vOf/zxOO+20mfz666//kt+h9dN/9ybcZLhRvoV3RNGuUYJB7acyjCZWRLYjm7WyojouEzu1LGGOYybfVK7Up3Vr2yVsnZbspwHXEq9Kqjojyw6QNI/EcRnV3u019FQcJnmixTKOAA+139nUb/tDjX1O23eTsOSphtX9kLQ6krPxPF4wcQmDybP2grVMlqE+Tz3eRxmHyOa5Mf2zfW7HJMcrrenC6Sj1bdOFAG/vW233dL/8bP+0ItypItdrHmoDkbjAwtVknsytdvzY5OU0MhlYja/Jr5zuLeTDPg9SOcMQjAtE/q5YIluXFj12WdTIY7klf9v5m/pj+7QR3I5RHbf2OIusTS8vfjA2jZMdk+ZcU65tdyfkF0cyGEuUtMuJHODEnq0YnSV7eA0HRD/AuQHRezg/wPtBzCOkvOAHRDfkdLT5zqU858GibWvDomlbNG6RNdj1AtIV550TlZa47upQ8jSUnRlCwLo4wQUThgkuTvCyWOjDlGQh5XvJV5mWc0LuujjlOJFo7lIARQKkL4CoLgOgZvFwRo7qog/ZeL1zwDpEzAtMzs8Wn4LzsvCUtJ2D3OtAqv1sF7FqmV3UsotiiVhNC1TZfEW6sPnzVmnu1uYeCsG+fSEqLzzFkE05aHyVSfdJCPikFe03LGRVOwxinPUl97N6xo4/1hzx/+1Qbqe/8O5///tX6T/8wz/EV3zFV+Aud7kLAOADH/gA1us17n3vex+ok2pK4T/+x/9Yya+44go88pGPBAC86EUvgnMOD3jAA3DkyBHc9773xctf/vIDtdPR0dHR0dHR0fFvF9/8zd+M1772tXj2s58NIH3Qxxjx/Oc/H9/2bd92knt343D1330Gpzp/3Ntpv2Eq8oCXSSPZFZpJw0KqmriRR0O2xiav1NHW3xBSluzYh6y1WCRIqXi5V0/mRATvlGQ1BK1TErfkq9ybeCZ6SR2MLZG5hcht+7JJcW1pXKrxMPfdOmiriNdYiHYlakMEvJDngZONwxDLOZQGLn/8IpI0nMLIgGN1SKUdTDpmEBnvOkhyXWTGN0uppBlFA4+JJJ5yZuSe3Eiq0jU5bsuglS+Mw358oL2WKr2BkFsk8VqCcEuZrfVsaHupf9v6nkCI+QYajWMleCwZZwg6NGQdixkLzIg8S+ilMrN6ULeBnBaSrNWoWxosznRUvjFUhdY0TDmg2/HBoGjSbRjtFvq2jD2vbqdqV+dPfsntMIl0YqA8C4A4yVKTCGwWxDimw0XEGBFiQHQTQkhEbMj2aa0t26GyZavxYhpBz/FifqSYRojigcyaSdDx0qvLKbn2ingzxO1M0zYTt1ZrdoIPAVHyYgzwochZyrHu+pDzq50fspvExSD3MWZTPUmPtowL8/Z3gzVNABkLJoanVku1vkfczKfWjIs1HWPLx+acWX1mHtc2hjXMvV64ljJq2cwKMDO90pplcW08y2KVdmauzU3I1PK6nboP+TfBDA5hn4E6hjgiv5/7YSfS9swzz6zSaqpAcbSOvnSFahtOOeUUvOxlL8PLXvayo2qjo6Ojo6Ojo6Pj3zae//zn4973vjfe8573YL1e46lPfSr+4i/+Atdffz2uvPLKk929G4W//PvPnVxHZLwYPeipx7TsUaNVoWxDJ+RPdmdPlTyrz7omr5KhOY+Q1Wo1Le2xkLWLqoT2q9IQlgmW0SvMXXaUw8ZpTpR4LOnMjsvBKrcHt3Ep46yMqvaVsE2d0c/6g4+sJXDsZba3oZDE5taZAkrGFg0r1GUrwXKZFgf91l+6+hmZayKbSNVSZm6aYhbfZ84ezVxbJJRacxXWrqnVEjTagkr2Fe1ATft5+axNOLeVqhqDrabgEiHVguQmzUnBxrZwpdWn2+jtVvx6a33Zch/zVvtqi76m2WzhZ7vFnyv7rESJmIIhwTYPEDA3ExNTMiZykDkmEo8jOIa0fZ5cdiLGSra67WOo4xfdXAO0Hp/6GamJwzQS3L7r5GKKXXVL/rV2m2WsGu1NjgFs4j5GIVxDNrtDJiQOiKKxm+5NzAStNQfEHEEx3UfV3MzHwtgsvStmJHz7vtqnjqWfhv3L08b8/eS7gDYkDtK3Te9e+47e9n6u+0A22FbrcYdjHDvS9oorrriR3eno6Ojo6Ojo6Og4ObjjHe+Iq666Ci996Utx+umn43Of+xzuf//747GPfSxudatbnezu3SjsOcKhJZXLE4TZp2jLCyyUq/nFzXYfNxFNi+1ukC2hLRdVL4gNaaAHpzASgdklG3lRiIcoRFQUL+yQgx0CCzHBckTjeGfBrqr1oh5bgqkimgp9uGRr0DqjAWOuaZQ1mCz5xBUxNCOkWtuoWs7kUZuXNaHmjoGKJcWikbXfB/ySPJOrlmu3eVs0aBMPTtV5My3cVruWFtow9Wzr9ybUzzhXskz1GN5by9Vpm0+1+YnmfG2hOt/Us61/+16IMuI50NYiGC6RXST9IDbOrRxijELwhYqAzQSu3epd2R32Jk0LhO2SliFQ7HhumUMzLT3V8lve2s0zcjAKOahkYLK/rYRgWtgIWTuTYkSU/EIOshCCQgayGUm5f1vJWr0mfR80L+g882ietrOyvHsk076HzH3UuF0qscTrrKxtnDY9b3PSdlaC5/n5LG6uxKyCUJvP5apkrabc34YYJ7ZXUD/7u4zJQWEXq1qZyrkVNie0daTys5HYiFn+Ln97LKwS7X53eCG26xlHiWM/dBux3oWxxVHYtO3o6Ojo+JeFs+52MHviXwr4zLtferK70NHR8a8I11xzDc4//3z81E/91GLeBRdccBJ6dWzwz3e4C4JfnfiGlTxg1NpEvHCoozJmIS5MmOOxlGtDtuk2vqDRpCyW0Vpa/LjVtGHhiCzZlGRpGzYAYokz2EncwaTloJjkSwfRYhoaJwa7sk24CrWzDaHSIpMJSugIeZu3WYtGWLVVO8Ycpyq+4WjzSENIviGKXJLpvU/kh9zvXT+QSW3JEtQmp4bkNO5ATtMadyI3abcpvSBfqpNcat/V/Sj9tETYAuFkeLNiuoJLnDkfkRkc63hl11mIvSyLsq29KpfSLGm7Bb6qW9tGiWsf5XGqr6OiwurrzQ6SqtBqUNbmC5bMGyR70RFDlDnFAYi2DGqt2Sou7ciY2L7UZOKGx80Qeylt5xTy3Coan2xkZc6RzeOiIUuOEGWRKHrGaDV6YebqrA29qpp8zHOqfdbsNZkwE5Os6bKIksjpWu6krNuWBmRruqY5p20Z2tBuuYZybdsowfbVwW18n0WQWsYby1n5fuZFFvuxY//rPF1B0me4vPMX5xJg5o+Nl7KbTR6U35Ti2Kz5nbFa6Rs01DdB58s8bp5nfU4WnvlazmgXVdJc2VxP1npu25RB2HQ1+9HR+nTN3YTW78ZtNYQdSgFHSdq+4Q1vwG/8xm/gmmuuwXq9rvLe9773HU2VHR0dHR0dHR0dHccFF154IT75yU/ilre8ZSX/9Kc/jQsvvBAh7Pqn8788/P2jHo/VqTc5AS1ZIjQRe7o1lIJojoUAChLGAJomYJpAYQJNIzCmkKYRNI7ANIKmCTSOkj/meCXTctNUzpkmIEypvSk5iEntlm2ulAliQ+gKGvpGbNZybdXAJblzDO/EBq2LEhK8L6FzhMG5SjZ4V8ppvDnPuyR3InNO7No6ynZvU3+KTV3DD85HqXBLKLaBxR5wrMk96/QtREYIJh00jJg0HRghRkxaLjCmGE1ZU2ewDuQYkYpDukIeCuFtH68WpAPixHyES86RvAe8Bw3JSRKtBtCg4SrF91ag1Qq0twcnIe3twe1JXPP29lJZG19JuZXUtbJxacsPwOBLf4To1X5WRLM+fWzJWSVTo9yviBjEdugUEWPANEWEEDBNE8IUME0pPk0B0zhhzPIJ4zhhGk18mqRMfb6WT/Wm+kMI0nbM/UikbiF8K9OGjXZeJt+Yk9M9ThrVqpnqwcmZELMcEUMO0+GZc3yo4hFD1JDhYcrEKOl5/akfohFr+mRJw3b5w1A7iVCVElHiqhkfQAikR9LynSQM5DBJuj4IkyvpYMu4UkbPDxDtYW0DGqek8a/9y7sDludQRcbKGHkkEtXnsUnhwIxB7ueANAYrka2YseKYDjD2ZAxSOuV7KZ/Sci5HqavUOTTten1Wmn4Wgrl5z+XHsJCt6viQRR6h8cZJ4lIcy84YQ1Oe2/K2LZNm07b2dz+i05qGYFhbtMXER9ZAz2ZBknOxZJ6iaKdbZ2TWXEU2O7LghCzXacKq7UpjXYndTSZGCjnaaqq3TsE817s6sgMybkyJmLR1SuaszJgpKfVYG8embWuD2hK/5hlLC7w1McvmnUFmCdhSteWctr52yXg3+vvApO1LXvIS/NRP/RQe+chH4nd/93dx8cUX4+qrr8a73/1uPPaxjz1odR0dHR0dHR0dHR3HFcxcbWFWfO5zn8Mpp5xyEnp07PCEW/wtbnLaaSegJZb/k3YeLKETIlhInxgCeEphnNIRpglxDIjjhDBOOQzjhDhJfC3y9YQwjgiDpL2U88kJTqSAQBMiQjk4hSx2BSOJjUZKYw9K2oNL30ecScFEtAXRsozeg7xoWwo56LxPZN3g4YZE3LnVIHEPt1LZKslXK9BqyPF5uSHXk+oUAlLb9k48txcyMHl7rzU7y8XIGHEZH0Tdps3JlqOMFU9BxmpK8WkCTxPilGRRxinFx5LWuJavymkdWmdy5sNTSG0GaT+WA1HGxmhDydPWDBSDIwFOriupWQJM4BiSI6UJwATwAMBHYM3gIQJDBK8CeAjAagIPK2A1gocBGFbgVTo0jmElZVapjB+a0Ke4EMdwDux8IWtFU7rS8GwJTz2sXcyQbGwiiIOjEJMTJFmY4JAWQfRgjQeNj/DjBD+NODRN4Gk0ZcdSzyR1hgmYjKMlWXzR52ZRK355dAwxONegdDkU8rSJ+0buG7mv5CKjeX3etOdIND6p7Y/+V/o9e9RMWA51K8XpXYNkViWbedY0SlwJvyDyEpayGg8L55d4SrPERYcwx21fl0Cg/DgSFQeKLi9EmcM7DI4wyILSIItPGq6GFF95j2FYYXAkMoeVJwyDw8prGZfPtYtYg13Acmaxqlmgcmq+pBkkXX/T3yJdBFLN8bwAEjktRIS0+GSPaQoSRoTJyKaIycYnXdhIZWNI+SGU82KUUBa1YhSNeNMnnT+8aZB0EGkxUdKLYq2/xPMiC9m2Of826PuWEdM7tJJJn10Es+wMAQHsksY7UaqCkvkg7VZ53uRvLgmBom3O2obsECC2pkCKbWDmWPU7/z4012GvJ//GyypgfZ69YQv3fQuUaFUaVtM1AVvr2yr5m0rVdC7yebto4yYcmLR9+ctfjle96lV48IMfjF/5lV/BU5/6VHzlV34lnvGMZ+D6668/aHUdHR0dHR0dHR0dxwWXXnopgPShetlll+E0Q26GEPCud70LX//1X3+SendscC79M266+9/+NxLyQUcAIwoxmkjSSAGRIiJFhBwPCBQQkIjWIITrlMNEvk6YUhpJpnE5E5OQswEREwI8IgLJIXQGpR6p9UyxFMfm3/2uTLeJpi3xSVPSp7QbAJdIO/ImHFYgIfdoGFK4WgGiqVnSSatzVs6kIeRtDp0TcrBoceZjYUt+3grcEoIxAkGIONGCZiHvLPHH0wSMieTjcQSGETwkTWf2I+DWYDcCbgTTGnATmEYAIxgS8ghgSiFPYJ4AJJKZhWfVg/WjNX3ZbxkYS+QKCwZxmiSqbCwkCYe0gIApgJ0H+wnsB7BPBC37AVGIVxbSlW16Qxk4b8r7VLdTsrYmbFuTFrMP84bEyKYpVGs9O0ASJ0iivU6iVZ5CE1dNdhufJrhWVp1vwmg043PbnPsDtaNakbab6QZVLFYKgzSu5ClRCckSikvyEndZyzzXLJqmSesvUiI+VbN51q5Gmr4vLeZx9czZx9BqhRezFrpQwighGEarNxFIQz7PmsTAchrLdWqZ3JvltajZoOR7J2QtEcF5l8hS7+C9y6H3Dn5I6WHw8OwwwMM7j8HGnYcfHIYVMAyEYeXgJRwGDz94DIODH3yu0w91W04PJW1lhwGZhal2jKzZDjbEqJK0TnYIRDkoRNCUDkwByGFaYMQoCyRjWmByYzpSPMJNRc4hwk0RcQrFNMukz1QEwYHUwZsSl5nba7Usl4aK0wmURljNRDgAEUl7HBEAybNF6fkKLr1DYnRwLsJHsQ9NjWatsfmctWuJGrlx3ocFR35W0xbYzbY6uNFqVY3bonnbasG29tXJmEUSujn/bkc4OAKC7lBhAjlbnx6Szv3Q+5yvRifXASjVo8fIARj3L3dg0vaaa67BPe95TwDAqaeein/6p38CADzsYQ/DN33TN+GlL+12CDs6Ojo6Ojo6Ok4+3v/+9wNIH3cf/OAHsbe3l/P29vZwl7vcBU9+8pNPVveOCf7b+78Mw6EToGmbWQNDNrHaPlXCKWQiKBFOhSByhjxyUzKTYIklN42gMJa8aQKFETR5uOANAUVwgUCBQAHpiEhEU0hdTHZWATBlO5Abv5WVGAmijUpRPgSn4jis/bBttpVaL+nV1tQq3nhTVxnVnthtO3ZravlYbux1IsX1AvXDkxizj+SZN/XGuZjPcev1voQ+BngOZRvrbJtqaOqJs4/vqi/QZ6m+mnIdZYwSARLrPEsO5nSKUOHoCtGnZOCmuCH1CmFUE5ClfWrSubGdP/aV2Mlxc7mZICxFasKO63xL4FXxqlxpa05CljYMb7G971W6EDmW4KkdgrnZXAquIZCa7d5zB2Q+EbR2DlpHZOSqeZu3dWNOOs2fuoRqDlmSCc327shlHhkHZEke8jwo27VDFXeR83yqypqwJbOygz8lvMBVX+fXAUMqp/yAdg5plJo0FuaJypVkL2Urx35U6qzmiZ2jppM1kT67gg1Q8raVwDzT9TNuyW89186Pek7Vc2ZpfpX2a5u4u8yhlsKtbbzuc+kGG5dSaKnMQrmlumZFdqcw833QnQa6sGLmYEQxt5BNfmjcOOgMpO8JNUOS5vdI6niwvANCPtdV9ZXQmJto+gJ9d5lr3Wbz+liBwxr4i4/tW+7ApO25556L66+/Hre+9a1xwQUX4J3vfCfucpe74OMf/3ht56ajo6Oj44SgO+3q6OjoWMZb3/pWAMDFF1+MX/iFX8AZZ5xxknt07HH4cwF+PN42ec1nYUvaKnGrpG0McJm0TUQehQAXQkpL3E0RTrSgnGgvucASLyEFTvJY4iwkrYsQchIVwaJfzfpRvO+3FyNVoJdJhVBLH+mivxvF7AIiopSJjLQNmhiBxX6rcwguaT8lm4JRSKewweu9IWwNsWXtCEZqncekjtYf/cjaXS3Z1Go1WSJVbf9FlceAKMQRC8GUzSwI8cR2Wz+rlqZoe3GJpy2sMZNGSjIpsXE038V5mCz5Ug0hbyaEbGhIpsVytHzuLG00zQ56PdXX8wKB26ZbktXmF8KK57Iqf4N8Q/pAqIiiortmba4WDb4Sqr1WJXOCyNRebCZvDJlTCB1r57PModn8seQtgI32OPX9QYa4JSVJo5hlIDgX4SKKmQdKSpCOko1WpiRnYngigJ28qDQeQUzIDvWYECkVifLysluzdQaVrdezW36Q4ZH3BcwCh1yvErLQ7rKJSx5zOo8LYZtt0FbyEtc28/tJJO38o/zS5kpur9kK2me9JVvLIoVN13Znl+RxQY62PAClwzMJa9rSvm+aUzeWF6zPb1rZ+H5taN6lQk1VR/Ve40J+co7nZYZqkcfaZrZzNROtqAnXEkdZFIL5zQQZcra0wwt9sL+jS1rDxxMhTtjFI9iBSdt73eteeOMb34i73vWuuPjii/GkJz0Jb3jDG/Ce97wH97///Y+iqx0dHR0dHR0dHR3HD1dcccXJ7sJxQ/jCPwPT8f7QKNs0odpdstVQt1JTDDlk0b4sW6+TDU0XJnCcEEOyw4kwwYVkUzMdo4mnbfyktlCFBOYYwSG1y3k7Oddf2KXbR89Ama9vEqKEwABFgF2Kx5isKESAHCci2aWtupnYcInsYXZgcoCGMYKdA6IDOwKimmQgJBMN6eNTvYDTMdISbLee+pnmLaN23FII+Vp7tmhZq1M64rKd3pL71DIjxwj7ko37tXXMFI6O4UV9qcMwVZRJRiXpLOHHVejUFqemJV7sV4rBEyYAMYeJXUtTBwAoqgkAIHLaKh2J4TJxC4Cp2OWc0VEy5+38MfNoceHDaKwnDVk288ukUbZqO9TzsrRjyFLpT0Vy3ohnttVmzVqzKJrpRIBD0aJVQtblNBVnjXKeQyFzXQ6tTNuq26GmHUg9tq/78YnlZ8mQtPlVwyXOhVzNzhCNPP98sHUqls6PC2VmpK72hYHyY3kMXzENqP5nQ16dvyCCJc3nBTfWsFv/FqHjZCj2hd+FelmiRHmhlCXuZ7VszDtxsOR9izXi8SFtX/WqVyHG9NJ87GMfi5vf/Ob4kz/5E3zP93wPfviHf/ig1XV0dHR0dHR0dHQcV3z+85/Hz/zMz+Atb3kLPvWpT+W/ZRV//dd/fZJ6duPx6Le+Cqe4A/9Jf6ORPlB5MbQ2GqFxIV/Sh7Cx68glHZmrdFVm6TzU8fyB1vZrH5TtqGy+sMzHrCUSzLZ5VcXMJTUuTISWr87TfBSCopTJ/5T6SyeXPq/3Bc++WtkQCfU9S4H9EOYqLOe28m1ltCnzGX6MmIz2bszSNM+baRo2JNFiWcLGMvv1aT8s3YmNZHQzlIvx/bRsUd/+XdpfgtUgVFKxmkNAPQBtejFesXeNzIQ5oKZsG7c93dCnfbHE+rQDwQtycz9y0N6jJs/WZWVVGxvSpdVqbApIdgfIQlA+XA4jpQWkFKbFJTUFE8UUDDtfTMJYsy6VPIVMJa11VWHTvrUHzQCKJjQ1V1LulS4C5EVEQ6prOi80ySKfyyZeSqj5VpZDYxLGnk92EStG037pR17AQrGfugksz/jcxAiBIZrjlckeY6O2tVVr5WZXh9q41bpCU4c+B5EoPQOgZpyahcMNxLG9XjLjVNmVNePkmsVDMjtA6kWRUC2QkDE/ksfJnpfb0OfAmBiBGSOZk1vN9FTzaym2XHJzqd1/Bw/8F55zDs65nH7Qgx6EBz3oQQetpqOjo6Ojo6Ojo+OE4Ad/8Afxtre9DQ972MNwq1vdatH5zJcqTr3hH3Aq+RPWXstVWIKo2nJq8rNmkpHFTPAWj+gqi7ycrupaIE30s2g/TnBrtnk2uCGO9KO6JpLMh2slM4SSxNnEs5MqW+8GoqoiLpbVpZav0BBIlNMLxJF+rGbCSFrkRmbJB4lrHZRvevVElHbJtE9U4gugjTnmasx9qDSPGzKBzb0vRJC97zVBNDM/sUBOWFuNVT9KEWwfH3PtbD/qURE79p4WAqSEWeMdaEIZ0wUyYkYgVXltvzaPwhIJPivTTESb3pdQ36JxWU23TfmmkaMh2DddeZlSPCs3izfvxzqPF881U3Zj3dv6t/ma0iRMc8tWHqFurtLuAQeyWs8xglyEi8kJYqQAcslZo3MeujMAzoGcB5HL+THHE+lHQgqTEIBu0V53M//yRcmV6XMu11QRgxUR1xC40RKENdmanVXFBdLP7jZgu7OAq50FMLL8LtV3ZBn0jaOzNF6qsJvuSExuzmJyuucSCyq7OSKIZUyIxBlZbT/aCxHf2pVW8tzaUJ+RtO0YobwnAcxtv5p3mn03LTkimxO4jTOyLbtAFm20MwuxXjs0mzkhQ3leFNved7MLzL9Sm5ZSW2nad1CX3++XruDApO0VV1yBm970pvi+7/u+Sv6bv/mb+MIXvoBHPOIRB62yo6Ojo6Ojo6Oj47jhzW9+M970pjfhoosuOtldOea47osBh+ggH4PHBjMSoeEJq9CQuVq2pvY2l9laz4a2l/q3/Vpa+3pGw4mKXb3iGIWMPVqqbNMGKg6UlkI9t6RrB0rBaFZZxyltH7dd3+wDWdJ227YNvXzwqqkEL9u6fWQJNR1yntO8xnmS53ZbuN0ubj6ciUFMVR83jZ2SBFqqGhcQKmc2jRMblS2NTdw6XgRrazhYsmObY5uWcNowPpZ4tU6l5mNk7ueWe16PU1wsp2OsGmx+4VmwntVLXGfJwbA0jlkLdOHmVPVvIHizbMsEsKTe8cb2xYW5YF8y+AD174cZbVQttNgW2tl3Iu/glybqe9vew6OtU8dmy4PSEIYq6agxH5+59OjrbZeSts8hldHG8vvjwKTt5Zdfjl/6pV+ayW95y1vih37ohzpp29HR0dHR0dHR8S8KZ511Fs4+++yT3Y3jgjd/9b+H96sT0FL5kLQafVbjr5A8jYfzBQ0Y3QJZti/OtzQW+6mljtkWR80Tokm1erJn9VZjsGKLanU9pYSVnkoch9UsagheALUGZyEXq3hDttayUhdMPoyGrWqb1Tpmy5hrHCppqzK1kQkhCa2sTjsZXwd7T9v0cl5x4ITakRFU14iq/m3Gwr0kl53RWK2xJcdUwTlMlDyMJzLWYxKP40G2Ck+tPKdTWDyaN06vKg01q4m2nVjfpHXmwPM5MCNokyM4G3cxYFBSPWoYCtEeDeFuthmX7cdGg63RemuJ/01on99NzoXKuDVxQ4Qnp2RlAWPuDV4IetTk+ZIzotj0qZ7L7YwpUphnGNV46TxZItsj2sUR4paEL2T5PM/IF9qwz0mraa3v5PY52w/WXIuRLNZBMsaL8qrM5vwqvY8m9NEg3wG5F5sW8pa40fliIM/y6nyVzOf6jSVSN97ffM/KvdNxsVSiHYdKvqDBnjd/2Paa+pb6sl1ofteA2TyMWdY4IjTvhSDxYN4FyUGhfTcUh4X1Oc07BvU7obyb6t/h1O8ThxhH4JpP7FvuwKTtNddcgwsvvHAmv/Wtb41rrrnmoNV1dHR0dHR0dHR0HFc8+9nPxjOe8Qy85jWvwWmnnXZc2woh4Kd/+qfxq7/6q7j22mtx3nnn4ZGPfCSe/vSn5w8mZsYzn/lMvPrVr8ZnP/tZXHTRRXjFK16B2972tgdub7rtV4JXpxzry5jDkp9ck00QsoFlG6puJXUxgmXLKcSZFUIAYgBiTE7IxHEZNN6EJOVJ6ijxIA6y7PZVzmHuIwlxq1/YS2p7WWy/XslYK6CcT0TyMSxhYiVzPMmlPFHOr9NYKFfXn9tt+nwg0x4tycY8CzPZU7EYqubMdTznlTi159o22GiEZbnKSlD30cTlnmRC0BKi1Nh3tDY4s43GRMKqXc3gPKL3KVRbj6ZM8L45J8WrerMdT9XwXdhGTEKB22eqGQMC189pXsgo24LtQga1djZDgI9eZC7Jg4OLAT4SXCDJI5EBFEnSyAdFyAIJpS3WMSZCkElCefyY07OnY20GSbdHtwsUZAhUmHEjcbRH6nhP7rGOJTdEfCZknIkrQZ/HX2SGzK/J25q4tfZSm6spj54hq2cEuxmzlpQlo82sC02qze5iek/qVm/WIzIg2+1dZDBHxPxeVXKWkdxjKWFLeWy007RpXmH+6mtJOUvoLZJ+RE16Thrmw7xK23w0+Ta0/dgFtV3tJjRyFgFX6RK3pn303Lz4ZvPsOVTXCVOm7uPBoQt1ZJ9Pc19Y7ifb3yLDluex3BDObK43Mmm+/BbmeBWp3275PZAS5T7Vc3BGzJKrFmpCDsuulKmKOwRndqwQJdnsfFct7rREbrWoo78t9v6fAHBYAztQqAcmbW95y1viz//8z3Gb29ymkn/gAx/AzW9+84NW19HR0dHR0dHR0XFc8YIXvABXX301zjnnHNzmNrfBalVrpr7vfbv4790NP/uzP4tXvOIVeM1rXoM73OEOeM973oOLL74YZ555Jh7/+McDAJ7//OfjJS95CV7zmtfgwgsvxGWXXYb73ve++PCHP4xTTjkYAfv7T/1mnHHTmxyz/m+DkgfMjBgZHCJijIghIk4BMQSEKSCMEh8nTGNAGEdM6wnTOCGsJX5kxLgeU5n1mNMpLjKRT+sR0xTyuaneFOb2pgkhSF9CkL6xmhrMDsssLJFK4rfDeT083ODhvINfDfCDh18NGFYD/GqFYW/AsFdCv0rh6tBekh9aYXVoJfE9rESm5ey5w2qAlzq0HS/te+mD8y73kVwhg/VDO5MSekQG69iECI4RYQqIU0CYJoRRw0nGZkTQeyv3frT3/8ga4xEzJuOEab0u+etyntaZx2eaEKZJ2g5ljGJM4xOVmFoeI9IxIuRrd57g2ME5gvfJZqP3Dt6T3LMkHwYPPzj4wWMYHIaVxpN80LyVM7I6dF7qHkob+TlxJIdD4iAJzhD1djEgO3YTcjvqOMl8ioFlPnF6lmMKwxQlDAhTxDSluIYhRExjTHNkipjGUOJTwDQ2dVR1pjCCEWJERCILY6z7l+eP0U5c0sArRB6VOAEDkh1OAuDk3jiJOwKclHckMptnyriFMmTyyNSlbWta+zkjq5bedSjXatcikiPFJKtsbjMn7cEqzogMOYossD2XSz6jOo/BtX3vJZLRjIclD1sot2uJViVh2/tW7u3CGBDgrQx12jfnaDqP7cI4OWqeF+lwIXTrkVJrwO1akVLa+r7XeJR4dZ+5HgubF5pQxy7IGNhzlsY9j1MzRu3YzNO6k6BZnGrsze7neCyYBatNcbtrYMkhmbVtm030UNFkV9vgugCyEVUemcG1JHL5LdN4Jo/TS19kppyUJVo4t0nb+j0Ab9pf7t+JQxy/iH98//7lDkzaPvjBD8bjH/94nH766fiWb/kWAMDb3vY2POEJT+gOyTo6Ojo6Ojo6Ov7F4X73u98Ja+tP/uRP8L3f+7347u/+bgDAbW5zG/zar/0a/vRP/xRA+pB78YtfjKc//en43u/9XgDAa1/7Wpxzzjn4nd/5nQP/Pf0nN5yC06ZTj+1FLMKQapwIQY4RLIQgT0k7Nk4BPE2JlJs84jghjg5x9IijQ1gT4kiIa6RjSvGg6TUjrBlxHRHXEWGMiGNEnBhx8kL4OXBwiMGldASYKSmqscQzUbuZyLCaWCQf4hTLJsm8HZoZFJGc2QQGhQiaGG6MoDXDrRg0MGgV4fYCaOXg9nxKW9nKgVYkcQINlEKJ08BwA4MGAC6ChgjyMTnz8T45+yECnMukYP2VyXl8IKQtdJxiTNrLMk48TSk+TWm8xsnEA3gMiGsJxwBep3FIYaonriN4ZMSRwTJOPDJ44hSfGBxYQuQDgVWpUIhm1MxY/dQZQtAJuZOICyJfiGzvC9E++JQePNxqgB8GuFWKu9UAvxrghqHki3yWv/Kl3OBBQ2kjtedAQqaTd5n8J2Gi5lvPdRrJ+OR5xGUuCaGdFx5kzOIU0lya0mJIlDGLsmARZREjjhPCYPMnBBcQXZqTkSZECogIiJjAHBJRiwDmAHYRDNUA5RTHnEzXsdk8YDLxKGnsgkrabukvR7L56JBMbSRCkOFBkjZkIhtikOckYyYiYUhiLGh/apj/4eoRbB9LS9RmshZzwlXzCtkn7xCWtoUsZImXG1niJCSjvc9MjQNG6XYmZDeMSeGnlBgt5Cw5uX+y+OBN3DmC18O7edxrGYfBp9B7PceZ/OVQ29WFDnKpby7zbFYL1AxKHpd0v5QwZR0HWXCowsgI5oghpnhQmU1HhMCYwlweqzokNG1Qbhf1D1Cz4LEZLUGtv0YlP2mzIxO8czMARVO10l7Npl8KMRsMiWtNzKgtb0va5l0FuQ9K3m6/kvQ6sGZ6Yvo9hc571LbXVc7IZo/0vUCoZXVYm+qhqrxtC1mnVvsAPuF8LQBgCiP+cYdyByZtn/3sZ+P//b//h3vf+94YhnR6jBEPf/jD8bznPe+g1XV0dHR0dHR0dHQcVzzzmc88YW3d8573xKte9SpcddVV+Jqv+Rp84AMfwB//8R/jhS98IQDg4x//OK699lrc5z73yeeceeaZuPvd7453vOMdByZtf//vCHunnYDPjVadK1L6agyU4hLyJPFAwGQPAKPER3NMBIwwh+YZ2SSHjdsjEBAgrIkc+lXbfFJu+sCMzKn/FTGdtInZUSI4PVJ8AKIH2DPYM+LAYB/APiAOETwERB/Aw4Q4jGC/QhwG8DCA/YDoUzz6Fdh7sB/k8CnPJYKWnQe75PVbt5BDPpyzWlpD2ipRULbeq2kKPUI6goZTiocJbppAcQJNE1yQcBolbxR5CrNMzwsTaBrTeSGUI4ZEcuf2EzEOITgQ9UO+BpkY2897uQcEL/EB5DxAA+AGkBsAP4D8AAwDaFgBqxVopeFeCvdWwCDyPSNfrYC9vRQOQwmHARhWwGpIBPogoR7Og5wQ6kKqFy0v+/CZ1QRDqiMkkx88BSBMyVxICMA4AdMIniZgHMHTCIwTeFwDfgT7EZgmsF8DbgS7EXBrMI0A1mCMYJ1INIF5BNiEcQJ4AuKUnjNOE4kpIDMrrOG2GbQZmbOlRKQwUbaekfksYR6j3C/iZFs6Vnq9lsI3JDCUSCUws/LCWZs0iqzYVEbR5rPj0vR5aTt9frUYrcpo0ktEbtZUNnFoPDdoaTlpjwzXbfIg/VcijE0G1VU1hG3RVrdErfNJU1w1yLPGuiva5Ukj3WEQjfNBtdRz2pcybVnv6npzOrVrSeKkSY9KW91ed/4ZMkQtR2St8Cgkq2qthyAEbWBMRrN8MuE0hUTKqmb6FPMRTDqEop2e6koLeCFEUJD5rKHs8gDL4pR9Zv8NoBC1ZuETsbLTnO1ox2LDXu1tO2YJo7HTHeE4NOmSn211x2KKpLXbTY0Zk3wYYre9DpYFpYQ0G4vl+yK3pXbFGhHv2KHcgUnbvb09/Pqv/zqe/exn4wMf+ABOPfVU3OlOd8Ktb33rg1bV0dHR0dGxiLPudsnJ7sIxxWfe/dKT3YWOjg4A733ve/GXf/mXAIA73OEOuOtd73rM2/iJn/gJHD58GLe73e3gvUcIAc997nPxAz/wAwCAa6+9FgBwzjnnVOedc845OW8JR44cwZEjR3L68OHDAID/9LsvwWmrE+GIDJm5sORDtR0/azlF+YAWLSTd9l19VMcss1vB8/Zw2dofoj1XzxNZ/lBvt3LbvtVagrOPKiU4iUAU02dXhNnmrtt7qZAdNq5b48lqjzVEBJk0NeUrTTMqbVmSpdGQUyJw6QMx84KqGY35vShaaXL/TBjzdv3YaKrZdKzKV2NR1dG01fTB9m/zM8eZhaKY2A+9F6juj2pTNvevvadNWu/7YnzroZqAlLUCtW/Qj/eNA6SBXrtqG9u5NR+vdtzq+2rGkrfc/zivr5CKy+OypGW7dFmW11U+VbXdWDRuIwoN77isPRTNWDaasaJFJ1q3RMjppEFnzzc2VXNdZlzMcNgd0VuGSK69yAphaMhcJWmtvJEtkbtL5ynhm8uYcmzKweTZ/i6OkgiTTe/EWlPQ+2DuTfMMZ3MFZO73hveRW5ARUZGjrgetXBqtiOnCTs/GiM2/lgfVZxhs7139HGetXM2vnn1jhoKLaYXZOzSnl+PaF/2t/DfE1f6rxBIVW8tYJHZ5pc6r45zP2BUHJm0VX/M1X5OdJRzIIH5HR0dHR0dHR0fHCcSnPvUpPOhBD8If/dEf4WY3uxkA4LOf/Sy+7du+Da9//etxi1vc4pi19Ru/8Rv4H//jf+B1r3sd7nCHO+DP/uzP8MQnPhHnnXceHvGIRxx1vZdffjme9axnzeSH/u5vcYo/6j/pD4RCEpSPU/sRHLl8+JZtqprmpEzIDCdy3VpKkibZdlo0MPWrOTMeOc6cNGOUdCXhJJR0sh3OZNIuF5fJAEOMWkIuM0KGGUIrq0NL8uk5KkNDdiwRGjat12NV6yxZZjWFmM0nZMM+sWgWMUO0GvVemntYsUZGY6oqk0LiQkDOzoVtw97rXQZmPka5HXMbVGKdJek9Y9T3Mdp7256zjxxNnu2CJZu2fR2XJ612fMMiiwtp9XZelMm13FwWrYzEDiWSI6Do6zYi1L1VaY9N+6W/ar9y+ZryM5nvn8bLQkNLsM+IcSjZ15DqZLbzC1Fe8m2dC2S6ygBDDJq5vXGQ7DzKkwbQBQcoUydpcR5WyZIKaJZzrMNUrinDDDXEnU2d2DhMmkw/9yHWeRaRdyh03pR3R3mt1XMp2LmBwgHN5k2bh/rdleeLKWNDmPL7YelVUl7/nNP2J4GbMvZ5r38+5nmo0sv12z608W0ojj4JRCzv7wgGwTGBicEU4dmBKSJGAlOoHDJax4zZvEFl/9aaPNgkUxu21hzCgkkEsk9Mi+LkkoC8aFC0btMukNapHzGLE8ZGM1YdMlrNXFO+zavqa7Vqc/slXt3/DUi/I9Sk7fUv3QdaiB9cI/eo/sJ77Wtfi5/7uZ/Dxz72MQCJwH3KU56Chz3sYUdTXUdHR0dHR0dHR8dxw+Me9zj80z/9E/7iL/4Ct7/97QEAH/7wh/GIRzwCj3/84/Frv/Zrx6ytpzzlKfiJn/iJbObgTne6E/7mb/4Gl19+OR7xiEfg3HPPBQBcd911uNWtbpXPu+666/D1X//1G+t92tOehksvvTSnDx8+jPPPPx+fvuYw/tn5Y9b//VB9GHP9Adtqh6lNR+VcZ852NI+L7cfisKeOz+pr6tY+LH5873pNzcVRU6L90NqksVeTD7Q1P6e3kH0H/cBbwtI9sEROm79076zG5SZSYj8+9kAcLeprjygENdlC1UnbWjhI68cW8/tVSBC1S5mJVbJOh9QupXpAd9k+pToTqmxW2rApZ+1bRjmvcm5k+lE7HpL+thdVTYBClKaFCLHtq3GnoSthPvws7rJM0t5vLtvUh9xOahNC6lZhZm3b2VUvBkHIIEoe84qJkRDg1MxImOBymEyMOGNCxBnTIW4aJW8sJkisqRFrbiRMpY3KrEkEccjmRsBKvXP1/G97lxTidHkxYmkBwzXyJe3mbRrPi/L87CxQXxveiS0B3S58IP8OUL3uhKXfCKrsFOffLnue/sZQS+TSrF5dJLJ9I2A+dxauC6jJzbacPq7zMawXkGy5tsxSXe34z9ps2t3W/xaLvyv7jFsta0hxLJDldny13AKhbn/nDkKq6xhSk27Pb3+bluTtubviwKTtC1/4Qlx22WW45JJLcNFFFwEA/viP/xg/8iM/gn/8x3/Ek570pKPoRkdHR0dHR0dHR8fxwe/93u/hD//wDzNhCwBf93Vfh5e97GX4ju/4jmPa1he+8AU45yqZ9x5RtnZfeOGFOPfcc/GWt7wlk7SHDx/Gu971LjzmMY/ZWO+hQ4dw6NChmfzK//po7O2dCEdkMGpEQg6IllgOYyg2OmMEQihhKLY6s71Ok8Y05bDKU3mMta1PsQGKqHE5bJ+Mptp+mmiLl4vNH2f2duQPdSx8oJuPRyUoZvXIP0sf91l2tMztAUnUtu/bPm43kbW7trUN7cc1C2ugJGImFi3B2GiK2bRqmhVNtEJUZo0zoo2e08u5C20a7TMW0iNT/stKaBnFCY5QuWxDo6VWaYfpeXOtsQGMlWhrEgJoqm02VvWYtut25QoMw1JIctt5s6whauLZszwR1P4yk0u2oEnsNJMTW80+h3GW9pL2iL6Vu5yX5blOByYPdtq+2IB2Lo+b7vuvrixPNKMhaO+VaL86IW6dkKYuhqTpFwOcErkxJBubIcDFROh6IWBdmOBVrmXCZMqHqi6OQTQItT15x5n3XLKwWRN9M+g1C3nORCC1l+0d4HwKvQf75GiPXHK+Bz+ABo8odpxJbDxTk8awIU/sPpM5UjoR71CyXcaMXBmjvMsB83dT1kKW+2AdLyJEsPw2sPxmsP72yG+MOl5MzhknYLIyOULtsJFD+h3KDh1tvdqe7UejWb3r79DSe5faDJUv1NlqKi/Zap2ds3TihrI3Fot3ofm92VR2ll44adNdPvhfAZvJ6vIG0Xd+W7ZYuaUmnVK79+bApO0v/uIv4hWveAUe/vCHZ9n3fM/34A53uAN++qd/upO2HR0dHR0dHR0d/6IQY8Rqwe7rarXKZOqxwn/+z/8Zz33uc3HBBRfgDne4A97//vfjhS98IR71qEcBSJosT3ziE/Gc5zwHt73tbXHhhRfisssuw3nnnYf73e9+B27vqvO/BsMpNzmm17ARWfuskLYUjaMr+XhVjTCoU6ppkmMUh1UTaBwlHVKoaZPn9JxpSnVpPcGEIQAkGmgUgEggxKQahVgRT4pdP0K3aarlNC3nzeKm4KZypez+/dgZcvLsg5KXSemKSFYNLtUis3moiRSihs/D0X0gL0FJa+u1nGdkqpuTtK1X9EbrdFlee1O3hK8SvUvE8KJHdWqpEkvSYkag6jbhdmuv3R6cnexUjnaS53Rv5cZpT3Hyw9W5uW5WB0HRtG+IXkvqbhyfmszOcSFL7RbuKPc5uoV4TidZcG1cx8Iv1JNIyHqMXOlT3u5dSObF+WFJcUOIl2O+NdsZ7VdnNXJjIVxTfqjySEhZXfDSctUilC5ARRPXRbNKFXHDjLMEqJLYQoTDkKjwiXjNDvwGX5zviUM/69QPe+qsb2+eZ+PDYJz5maNq2xcnfqItrX2m6qVY7D+XhUNdJNSFwtqhH6YpLQaKMz9ME3gcU1yOnDeOycnfOALrsS6XHQIm54AYpU75fcI0JQd+IZT7rfFqwmx+M27TxNx0lu5AsGczL9XTvsUXSnC9w6QuNf+12FQjm3Jz+69FqueoG6+5O69Nv1Lz9qvr31LfksOwuZXZUkPdjm2xlsxLLVu5RXX2bjgwafvJT34S97znPWfye97znvjkJz950Oo6Ojo6Ojpm6I67Ojo6jiXuda974QlPeAJ+7dd+Deeddx4A4O/+7u/wpCc9Cfe+972PaVu/+Iu/iMsuuww/+qM/ik996lM477zz8MM//MN4xjOekcs89alPxec//3n80A/9ED772c/iP/yH/4Df+73fwymnnHLg9t7zpv8DGuYauMcc5mOOGrLJEk2tTbnKg3OM8EokLXl/Vq/Q3KRjTTSpd2lnCSzRhmvJL2TyZTdsJF6NQl6+D0YLjEw5+0mnhG1VpqmvyKiSberDQbBkrqAKmy2peo6VMSiXq+Rsy6RYW8b2oSVytyoGtvE8lltOyoXn97HNm4s23FyqP+W3dvSo6XXemlzMXFZV21LHch5vKrNzf7QMIxk7bsoHYOt92XbvgdlDP1t+2XrLj9Hqx373eibieYltpOo27cuj2CEw744QnSSO6IjAISCiaI9H0YZWExrWDmplYiOb4PAL8iSr5T6b9rBa7LVG+1yDXRdBtlGYqnFuCXWH+W+RW/gt8mZxw3OAiyyh/h7FOl39/iwtoNjFD+1LrGy4tr9DuywK7oIlUnX/eua0ZXnTFRpyM+24z2/Vxnbq80pIVbi5n/bMJfp1qb6aaF0ieZfatT3ddme33f+FX5smvdv8Jt7FHaTBHe94RzzkIQ/BT/7kT1by5zznOfj1X/91fPCDHzxIdccdhw8fxplnnonrPn0DzjjjjJPdnY6Ojo6Ojo6Ojh1x+PBhnHPzM3HDDTfu77hPfOIT+J7v+R78xV/8Bc4///wsu+Md74g3vvGN+Iqv+Ipj1eUTBv0b99A3PBrk905Yu9XWbKA4EUFxKuJihENNqlYEraZtXMhcb4jd2cdySwI3moJu4eN96WN5+cLkc7XZ5m3jSijYbd9QbcIsN1vBKW351XguY/ONFmDZVm5CSD/sdu79iK5Mbpot7vZecAmL3c6kQQjVuNSt15oXY8mPtnwqq+XmdTVtQjXkigOYlpg6Wm5t27lb5Qfg9g7atxtzLaWSY1LL9iaOUT07EwtmzPc7ZyfOeNd2D3jS0VOmBz//xra1S31qZkTfJVbz2JKlremRZG+51li2RGs078dY1aXvSlR1zNoGqncc5wdyM2kLoGiCA5WJj1ZLvGiOL5O8lYZ51nyPi/Jlh1aGQM59UVMbKO86g13fM5sWDzW0C4O1rMQ3LR7aMlW9+ywg7rteImiZxqVFu0WHbvLPfKGwKbtQZmmBse3LbouHmrOJul6SspRvTSHUJTV/jYAr8Lf7/o17YE3bZz3rWXjgAx+It7/97dmm7ZVXXom3vOUt+I3f+I2DVtfR0dHR0dHR0dFxXHH++efjfe97H/7wD/8QH/nIRwAAt7/97XGf+9znJPfsxoNjBOjYmnjYhKIXoiSc6FZy8ZbOnDyh2zB5Ry9kHXNJJwcuJc8SjoDx1I42fwncHLtdlZIUEM0zNtvgs/dtsZ8Z83ZtX7Zu+0bmhw3hvFze5m22gatNztwH0UqzW9CXtt7L1SSSIBMKllQtW7fVDqfay/StPU6xq+nVJmcTuqrcVJ2T7XLGmOvPcd06ruSw7OO1Ziw26Xbtgvae0Aa5Ld/aAt1UlgBDJh0b7FddIn0WSO0N5jY2yZY4sIMS3EeD5XupxF1TthEtk47LsiXq5Giw6fnZqSOQ96Eps3S+edSrymhj/sGxWT/Svj8bO7iZEGyerSV59RwVJrEmBOfEXxJv1z/cbxFldmv2mb+LDhS5Hit7zyt5NZxszm3kGwjBg2JOnjakqhCvzuYtyKxDONfKNG3OJYJxNFc7jdP+LJHD+2ErmWoI1yVHpq0sWpk5Vx3JRa7Pb8vp+LGpc6mvBcU4gtU5LnPLzliSGOXydU1tzQe5iwcgbT/0oQ/hjne8Ix7wgAfgXe96F170ohfhd37ndwCkP3r/9E//FHe96113ra6jo6Ojo6Ojo6PjhIGI8O3f/u349m//9pPdlWOKm9z8y0Grg5tVODrU2ku1jUcJDTmXHfRkcwhtvJB/PpOEhhA06WwWwRCCTjR0XSQhJ5M926zNSdEwQft8Smf2jmQrsYr1Q72QzUpIC9sLjkYrjQkcY4rHUEJIcTQHM5i9qdchEoPZkLbR2uW0mmqA/egjyDbohfGxmrEuxmTLWbb/cgyI4tRN0/MjJhJeQy7piohvrzBrRnHun37eHg2WNL+sxlglX9A+20RC7EpSWDJlU3+q/rbb+zdscuVNca5lSyTIXF6ntezmehaIrn36qMj3XmyPEhGcI5BLoXMux713cN5JmNJ+cBJ6eE8pHFTuMWh8cBgkz8l5g3dwer7InHPwnuC8k3446Yf0iUgcXdXPR3WNQuhxZFlLYsSY0jFGxMiIgRFCmkdhigiSDlNAjIxpSvEwRYlHTJoOKcx5wZQNWl9ElHiM2hYjaqj90bkXU8f1eSkLbDpQRWt/ZuNXnbhRWZwqzt3KohJ7j+iGaqGKzSKWXZTitkyuy2eHcdG0W3YiFC1dVO8587zlQSqarrDvOWtXOC9SpQUpV8XLQTNHcFMpE5pyYos4O4djtU9cfvuq/tjdBmZUNhL6tlRL/De7RqjckC3vxjl5Povv+j6bCbaQjs27br93Sk2oby+zSMTvWMemviyBqn/THwbzKy5/YywvU7SwSyq79WRn0vbOd74z7na3u+EHf/AH8aAHPQi/+qu/uuupHR0dHR0dHR0dHScc//f//l9ccskleOc73znbenbDDTfgnve8J175ylfim7/5m09SD288zr/hU/DDCTCPYFSRrDZnTRDWGpTUaFdaLU9iq4kZy4cwR/NxXTQ11elPcuajW1fnWpvZJIIlmLd+GDGICSAlFCMcSGw/MogIzBGOHGJ0YAqZcIiuaOIWjdykKWudKnEVp+w8qT23bDtOWrXqSKkmMmAIjfqTL0vYjFFDarhqrMo9Tve33GclIoqjpUJQtOPmGgdMVbj0XJjDjtPscVserTlzmmVK+pR4LmcJIJMuRoiNSYych/q8ts6qD0Ct/bzAgmy4uJnGn0QszcqNzGqKZZlNN4Su3VZc6m+I3Kpfu/o2r8lap6EnIVAdvKNMzg5DImI1XK08hsFL6LAaPIZVSq9WA2jl4VY+h0Mu78x5dZ3D4IXIFWLYudwfZ4jbNPRUjxEDdnEmk6NC0MZgCdVQyNgxYJoCpnFKsnHCNAb8/+29ebxtR1Un/q3a+9z3Mr4MQiYgBMMQRaMMxuCIgkloNMxDowaIoCgzShNbBFtbRkHRENQGggjKYEMzJh2ZBWQIIqIoREBoSIAfmRPzztlV6/dHrVW1qvY+59433vse6/s++9W4a9y179nfWrXWMB8q/2IxYJiHEte4HbtSnhsC4pCMPIYhAl4MbkVEF+ECAYj8/hpRtVW/nKO8N+V4hgnge9P7rqOY7XuRl3HgTaVIfE8EIXC8Z5cv34E6FZdPDiiClo2NVSpiRMWMIparnRhNcqmHeKR+pVLxIupb1N+KKUNwI78KhyZM/Dcoq44pfmCCpM1qEjawmtTz6Pg95PLFmwzes+tKWG2OOFeHk1v7ZQOjildllfK9qpfbw+s9E8ErSNv8zpFTOTwWFJsN0ChxkTdGip94k4RizJsm03GSN6oyOZ+c6pE0SeeXat2+iYUzKRXbEq8O0y/7Nu/EpG8AGyZtP/CBD+DVr341nvGMZ+BpT3saHvKQh+D8888/oH/kGgwGg8FgMBgOXvzhH/4hHve4x03qCtuxYwd++Zd/GS95yUsO6N+zP/0Pl2Kb85tS91LplSVSLlqKbTq+hFdJ1EyRTKukataH1v26yzcD2Oin1+7n36UCdrMPu3v7Hla3bpmarK71ZvpiRIndoAj11hhSYKnB2ohSN8pTGVBS5elwW3d1CUWzRIXFZE/V4ikctn7AFV2r04ScJbU6ZI1NxbVlV2RuTYhNN1fF56PVNWHb+SQFK1fXecyYkF2Ta9ZhbdZj26zDtlmPbWs9Zn2H7WslvH2tx7YZu2s9tnP8Wt9hG6et8f2pvFQ29R3Qd3Bct8sSuInA7TRxC008MZFTkT6JoI0hgEJEGIYkTbsYEBaJkPWLBYb5Am6+gNu5gF+Ifw63cw7sXAA756Bb5qCd6povQDvniDvn8Dvn8PNFduN8we4ANwzAYoDz7HcBycJbSOxqBJKKnPpZamS8IUaxeOqUdHl9vF6Ozeuwdw6+SfOO46f8fE9bns/1uuLXbRHSUh6x6adw8m+K/N0oR+lLfCR1vJ79kY/ay7H62KZN5VPH8yWNVBmyQaLb0v7dGkGIUSFcu/S8+r6D7zp0fQffJ7eb9ehmM/Rrxe3XZui3zdCvrXF4DbNtM/TbtLuGftssu/1M7lHuWorv1vpUT99XdfuuS23rhAj2mVSe3vhQpCqvIdnsiENAWAwIQ1pDYT5g4HU07FyktcX+xXye3J3anWOxc4EwX2Cxc4FB8rA7zBepzPkCw2JAHAauj+sNqQ2RN2AoxorULZMlGyHrEbbt7Or72ntXPg3Tj8iuGiK76aab8MY3vhEXX3wxPvShD+HUU0/F+eefj/POOw/HH3/8LlW+P2CGyAwGg8FgMBgOTOypIbKTTz4Zl1xyCU477bTJ9H/913/Fz/zMz+ArX/nKnjZ1v0N+4/7JUafiENft17o1aVoRrTT14cwftU3cVDjS+CNYPpjbMkf66pq6q3ZuoE8tSeAa4qDV81dIjjpex3lFRqynT7AlUPKn3gSBUREZWtJpFcHN/60iFiR+arz1HFb51L1xRZn1c7I+yb6c4CijQNUAKT2pjaTeSIKvSpc4IYen0lHnlTq0hG92GqJWp0vPqAqN+63Gq8QV0rUlqkqRrQQujdJ09XV6qXuqXVPt1b2qdGMykSNEnqgl6DKpy65jKVwmelt/L1K63qNfka9jacHOlzoSySh+Jg21xCJ3YFJBAql5oKIiQST0ItUSflHIXS2RK2SvSOdm8jcixtCoOwhV3ihlhiI5GBvJwSItSGUeN0jrTL3rJFzipt9DU++ope+vplxt3GrZe3b0bC2T5Gye03a96L8B5e/V9PtpVVr7rsREWlVPu56ato260fbTOcD7yhXJZHgPdElqGV2X/Oyi480KnzYsqOtTfN+n+K6v4+XefqIc3wGdT2X5pn42rpnfk62kupoflweTkDYXxGUp6MhS4zHAhQiEAIQk3YwYgIH9YWB/chEGOHYRYo6v86ayEEPKE7n82NRPVNz80JQZm+xajqeJHKtTW8wR8Wp8de8bIjvssMPwmMc8Bo95zGNwxRVX4NWvfjUuvPBCPPvZz8bZZ5+Nt73tbbtapMFgMBgMBoPBsNfxjW98A7PZbGl63/f41re+tR9btPdx4u1PwmHdLv+k33UsIXuE1IhMHmRpJKL0fSR+Jh4iEULjJj/rbuR8rduWUS4kIgOi31GRhExsOVr94awJHE3qaJKnEFFMRo2IISVpqOI67yfzjP3IcXIcVvtz2wBoPatLpqo6mloRrXq+JuZGiPMcjoRAsQnTKM/0/Og6SzhLwK2Yn2X9y5KC/AA6FmjaH4STJpeWEerleVrnc32KmMWYcCpxilTiyClSaRnhhIk0qPvautv618MU4bZy40Olr9oQIQDBpTYMS/IuK6N9Hpa1cwrL56Ym6VZtHIk/b2ZwnN4IWbVhMjVP7dy3bd0ICECWAtfEtZCq5UVT3jVM0pV0V+6d8qtNE+0Hv8d0uKwjTQA2syPBUWfLYhlJkrNLKpz1bvMg0zK/yje+B5nky35xXXlGoNOWzYPKx1q/k8QnkoqeJMlPiC4miX8XxicJRm46LRC8R9B+1i2cXNecOGhOFPBJAjnBUE43KP3tPF/yRtY9c9wnB2SVRUU1T1Jv5LMb4VnlUSfqeNjfZX32yd/p+Bhz2FPg+Fj031NEp1Qp+abeSlUP/x0an42QsKv7xm8Ygr5Hx03fLXHrkbkt9ugX3qmnnorf/M3fxMknn4wLLrgA73znO/ekOIPBYDAYDAaDYa/hpJNOwmc/+1mceuqpk+mf+cxncMIJJ+znVu1d/PCb/gxHHnHEvq1EPoiFdMt65fjY4xD4uOGQjzzGISDw0cQwL8cXs7tznvxz9u+c52OPwy3sn89zWjouOeejk3z8cZGOQAauNx13DPkYJoWQpeEqSRqBELSOdf11Hq7z6Rho36Hr+3Q8ddarKx0j7dbSsdOe3W4mR0/LNdu2hn77Gvpt23K4m/V831o+0trx0dRuNsv15PrzsdSuPpbKugdzR/jzMEvf5fkJ+Xh3HEIeq3IteH7S3KQjpWXcq3lR/sDzltNkbnhO09wvyjHY/FwM6lhqyHoJQbE5ljqaqhEZqMm6pUe73fjI9q4e826PiufwRFug27l8OdVuQ8oRNRLOQvYJqUf1sW0h4bO0uqQp/3Q5blyPG7epbut4XjLn187VEiJVS537JXESFmn19cKr5qR9dlbNjUZLdkvccslzt+Q0gavmoD5loObIuTJHUKQuE6x5ThQjJATQ1LLJcZlkdciSkmxsDJXUppbO7Fl6swf6GcfNgNlMuX2Kn82AfpZcSe9noJm6t0t5k58lP7WEZ26PaqPz9QOWOyYkaZHeLJKbgSU3Qy25OQzAMMANi9pdLIDGX9wBWCxSXnFDSGm5vKGR7hyUNGeR7MxSplTNzASWP5npOXZVlkyoZ4LdqUXAcfI3TuafpXglPvnT3xW44pf8Rb+uz/XUu1bjNjsmsEWnegprfebJeCgiN9dT0vDhiQ2KejhHqW0RcI64fqr6lUl/UhsGxP1nXfWgNG4b0iu8ZD7KOltliKyEVhGzu0rYAntA2n7wgx/Eq171KvzN3/wNvPd42MMehvPPP393izMYDAaDwWAwGPYq7ne/++XTYNu3b6/S/vM//xPPec5zcP/733+TWrd38LGL/zcOa/q2T5AlN5ElkaaMhST9cEVXXCZRmVAVfXbJP7COuyETinEh8ZKXdUgyOdyWJ8eISY4Sx6jaVYyQTEo8ZYk1AmIEG2BPH5KB4IaYPhrnA+vI7OH6ORyTD06uWQ/XdXCzWQnPZsntkwtJ67scl+/vE1Hiui6V3XXpA7pLejnBRK18aMOXj3QANWuj+kt87JOYOCA+gkpMZlAIoGEADYnUoGFIcYsBNCzYHUCLRR23GEr+xYJdDvOFIYBCKi/5E0ELcaVNmVDHSi5DJzEfwFK2SfIponysO5HwEtIAmtylDUloahIQS/ID9RRot/Uv7UvrUgkLUVeH67Q2Pi6Jn8q/qh4JtO0b9cUpIkmIFD7WXRk+Ej2dWS9mh078vfiLDs8u6/NUejU7rVtT/E1ZanOj1O+L4aVMYjHB05BgZYNKSe0r40ZRbVhFpacz6+tU4TAEhDDkTa2sy1Pi1YZX0O9HtfEUeL1E9X6rDC8lxh4jqc9qksrcAgSKABD1q6K8L/ldSkNA9B2oG0DdgNj1oH6e3K5HZCI2Mtmbw33Peet08h37+fJy+eoCS3XCKcOAAEbUtBCB4lbGxhoDY0zc+pCO2Cf/ABeG5A4qPDRuGOD5aL7ne0sZ7Ofj/bURMzZOFpXBxZUrKb2rQKqnRPCOCmnPJGWWeFVSr61uba3zmxp/dL5Iy2oJ2iZe11sZwcxtkSUzRWOWfo5OR6CVcK39WiJXpHJLPPuh/BN5c1iTxlVdqOeF6jarBy0/fZPktKJntW/1WZhdxy7ptP3617+Oiy++GBdffDGuuOIK3Ote98L555+Phz3sYTjssMP2asP2FkynrcFgMBgMBsOBiT3VafuNb3wDd7vb3dB1HZ74xCfizne+M4Cky/bCCy9ECAGf+tSncNxxx+3tpu9zyG/cpx/y3di2STptdag6Eao8Yz2cyaNJI8m3Mg9qYkkTSlD3jtu3XvvBH6ri8ocsygetHBVNx0fZ4JVrj6UWQ1j5SKo6btqG9THUVEZTj/6ghkd0Sz6eVT8KvVGOeuoPYk/lo1gfE81HSiW+OnYa87HTTo6gquOrOV3d54ly2ri+qQ/18Qfz3v3kbeH2sII9vX8DWFcib7379+DeXYFDJa3utLR6x5LifQc/69H1YuQoSap3ImW+ba32byvS6Sms/UmqPefj++R+kYb3M6m7TxcTvW6ptLoausp6faiMKEWRFleS6pFPAQSWMA+LBUKWSFenBXbuxHCLhHdW+VL6XEmqz3NZaSMr1ZMl1ZncrU8T1NLq9eZAeW9ME3tjA36UDfmld1ox4leM9WljfsnQXzc+ir/KmJ9vCEfUbm6/bI6oTk2Rfp4iXCzH7h1ReS+pY/S+OmIfcrgcvQ/5ned1vLzn5Bi/iquP3ceafFSEpVo6e7Lsdj1+InFVG/bVK07ToOP41XF7Gl4vfn9jThF/ga/sPZ2255xzDv72b/8W3/Vd34Vf/MVfxGMf+9j8w9dgMBgMBoPBYNhqOO644/CRj3wET3jCE3DBBRdk0s85h7POOgsXXnjhAUnYavzSG1+II/a18AQTSJWU7YR19Sw5piRpw6Icjx+Y5BjmQ7YOHYYBg1h5FovPYkV6rvKrY/2pnFBL6A6qDVFL3jIBo8iMRmYrE4eaCc4flq4JQwgERZo69Sme/UVnZJZEUvmoKruIa7ZSS7Tka3vVR+f0xzZVhIeWMFKtrYgFLfmFxp/uVaNCuuW6LhVPTXhF+2vCiVujSSegkhKLqCXJoiLchVBPZLtT5JSbJM6D3D8i05V+x0mJN25fJsjaGdHjJVLATFpPEOtCQnlNfIvux0ZHYyHe63Am4+NYp6Mut5VKE0m0dUl1kUZFkjBMimf5OLJIsyrpVteGG+lXMVqWCFVfwjrOJV3QroofX7puALV0LaSdY1QbQPmEQXFFej9L4up3ogpH9e4h1vWspXazvud8X6zjc111PbluXpNZF+u6qCVXHa8lJ9Kt2dCUOirvOzjfwbNUrPdFShZdB7giOYvmSqcDOi5DjtwzicvEree1WCQ9kVwna376bVEkJ5ElLmupzESkOkXW+hgzAZvcoFwmYGOSoBW/i6mN3oX0LMUIh5DWR0zDlY7vAyzvz+tGrfn2hbYXsFtk5F5uw9K1o/2NtG56d6LeNICr39ccH/gdnN/ZVZyOd8273ZV3uGxKqDpIhfV7u/37uz+I3RgWwBXrG8LdMGk7m83w5je/Gfe///3Rdft3N99gMBgMBoPBYNgdnHzyyXjXu96Fa665BldccQWICHe84x1x9NFHb3bT9grm/981mN+8c7/UVREITEhka+fNMeF8PFh0mrI7KCJ3WCxK+rzRs7oo0mxR9NUukroEGkI5yh+SJJzo2c2qAeTc78Sn16qPsSkyNRMIQCFe5WOUiRD5MEX1Eag/WOUeV5Wn7xnV0foVEbx6oiR3CSwnWRUpNxGXj7Y20mJCcgvBB0XwAayCgIjbzPEukRm0QfK2oIyP6DMsEoNFWi9WZKuSaF5inCdW/iIdLdKBWiowG+ppCF1SpIAmcKcIeJmcirSdIGmLpGCRGNRSzV4Z5El+qiQDOyU16CkiKr9IHaa1wld08ESIFOHzU612LxxllRTNI1b3jOc759BBR3lNpM6LP6pj8Hp+UfLkNaJIR8mX79PPR71RUrmKsF0X1Hiodl0V5veNWks6v9PvI1JrjXReyYeSD7pMNa5tmxq03UurELwOkeYdDj4C5CgR4cSGr6JjItWjd6GSlCVZE7ymyLkkcavy5DS1ZihL1BYJW5qSsNVzjfp9XOaF1GNVxq2+2iP1cYLInQ77GJq4kP0iuSvlORXvFGEsc17eieONj32JPZGS3Rv3itoUUvFppuRvQoqLRLVaGkQ48oiIcHCIkRKx7wjREbxL+qG7bJgtZjI2E7XRVwStJm31KZp6ow3N39r9RNrGBb69gXwbJm3f9ra37UFzDAaDwWAwGAyGzcPRRx+Ne97znpvdjL2OS570+9i+H9UjVB81itchFSeqDiiHxb++FfU2Lrb3LikTKk23cyMfXvnjTUsDKYvZtXqEVVa71VHhyt8p8lCrSugaYrCQj6Pjy5nUEEJKiMwamTQV4rWSoGykLBtL3dOqEcJIPULJoy17q6PH+f6JOjdgtXs0Z0IAKBLPOTGa41gSUKQE2bhSJeWXjnQ7n/QSe5YcjD7pQk0kbY/QyfHupH9T/MRzlckpOd6tjnlnSUGnCKeWKBQCXRPhDdmTSaCGRCqXSAkOyQ0SN6T5CG1ayPGe6nKy/k0XWB+oy21hxafNhCxfTS3xVvRo+ryeamKvy25wJSzH76N28xzJsXt1PF8f1dflT5CDossT1TqCInShNjaUBDRFRbAXaWenST1FomuJzlqaM/B6KnNQwrGOz5KhDak4cfy+bJjUa2hE3BKVDRTDfsWeEKGryhjNsVsnfSqsbtpIHbuHsgEBTO81tFGtFtdR+ij/6vRlcbuSvrcxR8TFG8i324bIDAaDwWAwGAwGw+biTSd+H/putil1Z7q0IUrFVxOoWkct6e+3Jtzqu6Wq3GVlNjVPtGkFGsnWSvK1kfLTYXI+x6V0XxFWaIm8xlgMKhJJ1YHalQ9r/YG9XE5VqyMoX8iF4CYEIXuUhBqYCKql1pTEmCLzNOmqw7VfJHPrupBJIyVtqNvaTk3jd43fAWwwLEls+SbeN34PgqdkVKiPgB84bpRPl83G7FGX77i8tj1tu6dnqbj15aqwbFpEtakRscyfjh5HAgKAhUcyAIVu6T1lc8SN2oLGj8av4VQOJVyrxkaNE5P0esyKsSJOi2z4ifPNJu+rpRidKl/H6fblZ2/U7iloglNLlIvbSJyPpNH1xoRaM8vS1HopYzKWZpfyp/qzrF/ptSWqJlBUTLD6Cd8lw3Heu2TQzbvs7zqf3a53VbjEs6vjOn0/l9+6Xqm68K36DGl73ZuiqgJKbQTYUFwxGBc5nFT4JDcEYgNvMbthSHnFn9PYr/PGQDks96STJlHVrdVjlPaJWotdxa6Ste07s/Jzxo2Rueu3Y1ch3Xcqoo3L4fy3jsPVb4FxuTIGlNd/XZ7ErZqCVX0sGyHJJ+E6NH3HshI3OqZG2hoMBoPBYDAYDAco/uOQI+G7tf1XIU15p5jTEYU7lthTRG3JTEvuUbFTRMUS8mIcO/psrD+cXPOZy1KeJU3IBFc+gNURbSfxE3kdhx3TS6IyIJEw3DElnZnvzc7ufDbX416NHZO4euyoqq8DOVY1Aa/0AtPoXmKCqQ5DzSeN56iRDEQTcuytSDqApYeRJYg7sG5WEBtTK3Ed+zuK6NkP1vMqUsg9h1NezqfCnsAulw+CJyF7RbVBap/XhNryGcljHR27QKUrVwjYIEd/kXQ2Bpc0agY+DqzDg9oEiFVanS9O+KOqW7enIpJd3f52joTkzERknqtWBcTYOF3tT+NMWkpbq4yA1tFL8Kjv1XVVkubQ5LBadytnaSKPELVNtJZ01XTTtH7n+v6i/qC5t2rK6ueqbiKp91b6T15LojNYE7RTBKzvPPo+hfu+y27fe3Qzdjnc63CTpgldXba4qR2JxHUOlb7i8k4tQ5A3+UiRo5mgZVJWiFRFzIYQMQzsHwKGIWIYAsIiIgQOL4qb83BcGEIuqwqHiDi4RAjHCBciIguqU0ybI+l9uR5luGwud+3Nr/OP/Pw3pi1zMtz8qRz/5dx4e5ZFtmlLww1hu8w/+bNgj1B6XWZP/oJLCjA1KmUFLpvBjT8PRtoaDAaDwWAwGAwHKB78Lx/GmvP7tc5VnxkTvOzkfYn3GJN24zzL7m9oviWN2t2PtpUfpksI1I1+zOZ87VnWjd63C9i1/tPSj+ldK78l2/ekTXKUHdA6gYuOQq2/sDUc1hgYU+opBqdVVfSIXW2ATKutGKnIaNRnjPQjamnolglRxF2rHkKrk3AjMjNm8rJT+jmzQbI4VlMxo4jtykCZo9pAmS7fNf5KPUAmH5fMtupvZSzOKRJYxqs1+NYYhNNjH5xH7DoMzmPnhG7hoOdnYq5K/TJXMidCQk+vKC1R20rDZuJ5wrBbGVtq1ISIvuFGN7GoFtFzmedUq0RoDMZNSOiOjcWpvjHRSSEFQptDc7t580nFCelbklOaltp05X7n2nsL8VoR1U0D2vZsGKN3Fk3/7aDyd0M/yllyN+dZFU91HvXfqr99e4r1yM1dqmx3xH2/oyEkd73RQtVzK8Ss3ripc9MobuMw0tZgMBgMBoPBYDhA8eU7n4HZfpO01V+jSodiPvYrR+ib4/Js9Cgfs5dwXBZX3DYf2FBTObqfXC/1JhEs5VftZqz6bHIT/hFZIRJxztV5gMqoylQeXVZdfi2905a50fYLlpHfLTku5HkOu5KfdD6iOozy7d/ma+NGJMeEf1X7c5ySQp4y9oaKQB3rVx3HKZ3B+d5l+ViWdhSu25Ga51b2LfUAKNKWzTF7SWvJOWqJugkdwQ3xW+nNBbKai7osIWTbo/jIk5x71HYs8xT8UJPLD7lSWICsdoQkLEotfA4XncVJHy28S7qJnQOJnmLnQJ7vZ321qMKljFS1jhMGsXHHT5p+oIurLqfDMb3rEMt7D5GAGOF8cuH4feU4DWw0ETGrJUGMgOf3JYhfNHI1Cizyop5aWctiykZCntWJdZTXj4Qn1tXI+F4m56fzF78i9XNbHFpDjOP2u9yDNmbagKKExxsQ4zU0vdZG5Pjo/qZMqdep+qv21dhV+m6jZaz392JpWN24kbbt6t+hDaXTtAqE9UjrlodeVu+u0dXts1b3eDo0pShBP7tt6sZaZKStwWAwGAwGg8FwgOLfTr83/Nqh+7YSISkVWVD0nDZEa2XkiA3rhMA6KgM866rMVwx1OF+LlF/n4zJKWUHVw3UqEpjEgBCwrnTRKvI1cT9O+ZPrJU7CnM9znFf3eVWevs+35U/Uu6x9S6drGUGriFdSpCwRVfpNCcmqt4SLXlVit7lP7tHl6vKh6sV4KqZmZqp7nkqPCnFe8hdS3DVjuCRtA3Ncxrs5Eusm5kQ3aEkfpvqrDe6M56wlymtSvCXOpwzzjcn2MbHePjPZr/iGKix9HElbUloDjpgnpfTsO9ad6pDdLsc5dDneofMlrnPpGH9XpSHn8b7kyeVzHtGLmvW4osS5pv2j+XA8dk6tG5fWQOJoifUDE4InxAhET+lYPgjRAcERApLV++CSLunA8VGnUZJ+FX9yUzhSqYfYTetR1lS9tqp+NP52o6FIIxdpdZFinpJO10YUszFF8U+k6zBlyeqx1LqoBakJ3kx5ZkI5P2dqI6FSx0FKXQk1UuoTEuojKWdlVFEMLXZN/rFUdWSVLLXhxYr0lZ2NJeTtKowIVqfT6rWn8+t3XVVO9d5yE2XqulaRlMvbueovLTWBWmM9u6SzlHdVfgdV+Si/l6jclO9q8+8aXdrmniJk6/Rx6S63o5W8rf/CrMamkrYXXXQRLrroInz5y18GAHzv934vfvu3fxvnnHMOAOCWW27BM57xDPz1X/81du7cibPOOgsvf/nLcdxxx21iqw0Gg8FgMBgMhq2BJ3zkL7Dd78+f9FR/FAnZQ1TIDaL8QZb1DlLxJwG1Nq4OR0p6Cku5bZ5Sp7QjE1ZEo/atwkrCVkhX1ESsDgsJmwkp8aMQRuIf3deU0RK8laTuBFG4ZIayW5F+Qrqq+ETEuiQYCE3EilErysatSh5UcZnMQpEHFJKJCIjy8S+T4coH9Aamp+rXqN8qsv5MnoYjKhK7FRPE7RMpP6rJWxLJOiEpqZkLIU028sA1zRdPNW+5SRsjaVuSt03TpMd6BG7bltUdKDkq4hY1obt0o0NvarhEbKR1VPxpjQgBq+Kb8iStXr81OTU1Z+M+jftfxp2qjQlZM2ktlfS8TlRatemhNjyWxZf1qee1NsY4RbZPwUGeTc18uWYMdHjK75gcc/UAuiYPUJhAFVepoxiJgy6bjBWTNBlNS8NlbdJ4YnPc2HW5OpWm41r/VHgDPaglj7Wkc6Puo1XVolSGVOGRmpdlKkWKmhJddiVVraWloVTALF1IWtpZEeuopZu1yo+iEkTIbyHMdZoizLWql6gIdPY7RdpP1TlSLbKEVHej/8fzWGuvbf9StUoRJv+SrcSmkra3uc1t8PznPx93vOMdQUR4zWteg3PPPRf/8A//gO/93u/F0572NLzzne/Em970JuzYsQNPfOIT8aAHPQgf/vCHN7PZBoPBYDAYDAbDlsA1BGzfNZ5oD+HyBykJ+wZxHBO2DsVYDNh1+TQxMumKnEdfOQ4NGdUQVljhtv5VkE+o7OpvKq40umQ4jFz6+I9IRFJMvU5kLGlid8qlhgQu5JbPRJcmj10mwHjkVx59HfW9IZ9aki5SHV8RUVgtWVuRVRNxq8jDjRBNy9LSYzZF/qwgltzYL0fCcxmNv9RTl9uSUzURVeI3Dk2iFQniVSQSqBAiatck+x018ZmtLf4sNe9aIopGz/4ytD2lUWwZU8duHj/HhqbUnNRhMUSlwlJGFVfKq8ITrhsRjct7UT+AyoDfhEvVS6tsHOVw9WJDCav4EpfuJafmMNO1KPNTzc30PK16EjPFRHVYv2t0mox9lY6am63SpvLyf238ZFtdS3SNkcdDh5f5m3ehvr99R+piqzT17qzqmCh7qh2T7R/FuNIAtdlVj1mE478+Hp7Vb4D/APl0r+fnxyV1G857OOfh4hTZq3V0t/qgJ1Rc6HcskA0Uakyphxjph64I3CU6tivd0dogYdHTrfMU9S8pbw6relc+HG0/mnmpDPxVebR/6p2yq38XmnYQ0apnab/jmGOOwYte9CI85CEPwa1udSu8/vWvx0Me8hAAwL/+67/itNNOw0c/+lH88A//8IbKu/7667Fjxw5849vX4cgjj9yXTTcYDAaDYRJH3/OJm92EvYprPvEnm90Ew3cIrr/+ehx37A5cd539jmshv3F33Pu/wfXb9n2Fo4+wVv9fzB9KxS8fWskQT3IDG01i1QkU0YWQw9qt88aSX8Jch9NublPMbcwkFWPPPp/G2NXy9rT+jdy/px94u3L/vviYbL+r9dFuOUqtjYEtNT42ebS7y3mC76rj3iVvVx3nDpNEB7ehIjZQXM1QMTSZUenFlDUEyobFPAohMXmMe8KgVRenjV5N3V+RIUrarSZVhOBdfbR7WpdwI73nPaLraklA3xXXeUTf8fyU+OTvEDqZt666N+a56lCkBovhs6otTArLHC2lnpu5cVDjoiX51Nh69V7S7676nTb9HszxJO86TqvepaTedYX00u/j6llbMV9ThGklHIsxWavzrcqjydkNEbmq7o20XWOKf9PxUwStJmZHhO2SPCvLUXkn27SL/TBsDnbl7/Ke07AJc0S8Gl9d9zfultFpG0LAm970Jtx0000488wzcfnll2OxWOA+97lPznOXu9wFt7vd7VaStjt37sTOnTtz+Prrr9/nbTcYDAaDwWAwGDYD85uu2z+kLVBJNWlJLVe5VIWzgSOwlKnv4LwHqJs07gJqjy6OiYnKaJKQYLke1ASTSB+WTqgObfCzq5GgrHxjEbH0/zJJPreknMnmjNvnpqMTSOerx2ZS0imTc/r4aCvpVBN7ThF8Y+mo+t6lBn2qttWE+jRqisk5rSlSS14mQ1VJb6kHnE8SZr5LUmYjv4dz6Xn0vgP5pHuTfAfvxRhWKofYFYNX4ndLJNK0JNq4N/X60GPk2dBepY+z2gBhctAzeeeYQHQhSdQ5B+dYvzMcHDGZFlOTETWpFqs8mopwTp6njdFJMq9UGSIL0FLLNfmuxqkZP+ixnCCDq/Rctk5X9ai6keelfaY4OOpqfTS+freM3z+a3NYbWkD77K9OayUTc53NuzWN+/QcLXtFtGRtS7COCFid1sSP9HGvk39pHaoN67W/xWhzRxGnLcFKcMtPAJDOM9bxXeV143IAVEYcxZF+TK+imvqb7rPIdkre1VKfy+nENl5a5CbSVpUz3cZVeXWLN9K26VzLSmlHeaN9X9bf6bQUK7Mg74CNjI8uF3x3+eu10ffrppO2//RP/4QzzzwTt9xyCw4//HC85S1vwfd8z/fg05/+NNbW1nDUUUdV+Y877jhcddVVS8t73vOeh9/5nd/Zx602GAwGg8FgMHwn4oMf/CBe9KIX4fLLL8eVV16Jt7zlLXjAAx6Q04kIz3nOc/Dnf/7nuPbaa/EjP/IjuOiii3DHO94x57n66qvxpCc9CW9/+9vhvceDH/xg/NEf/REOP/zwXW7PITddC9+t7Y2u7WXwh+zEN8ly4yJUCDiJWY84Il3i3kRhEZaTqw51kqvztvlcnSPFtR9+Ou9EPRtq+RLCVhODjWRlTdBOkIUsYdhV8W2+Ep4mgRviagMEVCbhUBNytaStOtqrpGy1RGd0LKWpJGmLtOfqdJEWhSZuMzFcH+N3cNmIklPtz7OYNxGYsM7jocbJK2lKKuSsi4FJWVdIWR63TIBFborneiJxO+VxY/pBVBGQrDduMdESArOOnMzC/apJTuT5ax/jTGq7JsxxNentmmPYQshOlFfFr78lsCsotFFxqjj2tnFjKdjqxVdaSU24KnPPejIibBWRKiSq1/ESp8KrjCxqHd3JrfULt/qMHb8Pp4jbqq3tc1MPdXYrwnaCkI0qTvQHZz+0OhhX5yeW7tf5HRS5q2aGqDS+nuKVM7L8DZ/GXC1gFXIqqoycDuoadD79p2n0F6gqb6Jt7Z+wiVaP+j1+nKtQ+zuhJb+n8smbtIwzrzpqS3f6BkyvpPGTRznnhEG3/AZ0E/9r6tc1+aU0ybGxv+2bTtre+c53xqc//Wlcd911ePOb34zzzjsPH/jAB3a7vAsuuABPf/rTc/j666/HbW97273RVIPBYDAYDAbDdzhuuukmnH766XjsYx+LBz3oQaP0F77whXjZy16G17zmNTjllFPw7Gc/G2eddRb+5V/+Bdu3bwcAPOpRj8KVV16Jyy67DIvFAo95zGPw+Mc/Hq9//et3uT2P+vdPYJvr9rhfu4OWY6PR//WHdBtPK/JW+YnG9/N/+uOr/RCjNsMeYZ2Pq13jVfcZshygK0QnAZWOwlqdwNiae6jUDHgE57JBm52iKqDvEb0rFuTlXl+XVVQZKGv1uV1CxJWPaGoZmhEKy1DpLwUw1kHbxgux2sRJeCouE5wYl6fjRm3LLRzPDhNwY8lLpZvRFellIWy9c3AxwkMI25AIs1hLLTpQkqh1SCQtu2m8fEp3rhC2JHdKPDdyBcZrzdXPnHrWplRYpOdLqZ7w5TkSVRViSKkNZzc/b+U51eordP2tjs48G0sYJ5Gmm5KQ9ZRUE0xJondqk6NWURFGKiskf62yIlZltK7eDMntkw2Ait4ak7TyuGZCVpGvYkTRseuV23k38nfZn/KJv/MOndyv/ROuq1wmcPXyHa2f+tnLetMhxGrRlR6JimE3FY5ECATESAgcFyLldPHrPCHK/TpPXWY2NEeuNh4nf7tGBOQYmcjW5LYTY3xq/LyMo0tj7PUccNi7MhfiV3OU58ar+fW6jul5ynOU52nJHIn0cTMOlMeJx02PLfvzfESkOYopLsicReRwzOl13ra8qWeCVDsg7ZxYM/WKWk7Llq06Td+On9qK1d8gNp20XVtbw6mnngoAuPvd745PfOIT+KM/+iM8/OEPx3w+x7XXXltJ237jG9/A8ccfv7S8bdu2Ydu2/XREzGAwGAwGg8HwHYVzzjkH55xzzmQaEeEP//AP8Vu/9Vs499xzAQB/8Rd/geOOOw5vfetb8YhHPAKf+9zncMkll+ATn/gE7nGPewAA/viP/xj3u9/98OIXvxgnnnjiLrXnX445Cb3fTz/p+RtDkwMiQSYSnchkVCE8AE1MibTn9HHhZceI6+P1NZmijxPn9lHbTtWBEquk99KXaCYRk7hiIqJYopJc0Y9JzgFynF7i8/H6dVznQd4pf1u+y+HSlnLUG9gAualI8dovH89pXojHJX3Aysdr8ut56iQvpxGPu/hTWgSFkI0q0UR9yH6M/LuGlnDjj2VXhytSF25luqvGVJeviInRuC8h/kYf9IJla6c8s9NEYVzpX+4ywbdOObquqk2qnauQ2u/gnDxL6Zn1BEXQx0zsVmQqxpbqY5NW4sua1BsCIzUKLYnMc5ffEOssn2p+JuZqWoJdzRfKuGuytZoX1CSsX1KWG9WrJenZXacvmWoiZGOKjucGREzCEcT4oc/EXEvaTROt03E1AVlL2iopXF6DeU9Exn+9V1y7IagI0kwWCpGLQhZKfFQE74hQhBB6itzD9P2k6s7En4RVe9ZDyctzDgdHlOYLlIxhOkrS9KjJ3ClyVxPwTpG9zk247Zy15DFKWL/yZO6melPNz9Q4TYx7JlTVfMU4JuCpcVsydkTOTtSp27PeHGk6drwl0o7BOJ1Q/RVR5cUVtRZsOmnbIsaInTt34u53vztmsxne85734MEPfjAA4N/+7d/wla98BWeeeeYmt9JgMBgMho3jYDPcZYbVDIZpfOlLX8JVV11V2WTYsWMHzjjjDHz0ox/FIx7xCHz0ox/FUUcdlQlbALjPfe4D7z0+9rGP4YEPfOAu1fn3J5wKtz/UIyjC1gFAJiaQCAcIKdFIh0WWOFNGe0TibOyGJfGNYaVcVq1PdZoQLuStI1c6wl+elMlaRdSKISPRc8qGkKjrkr/rk9GjrldXh9jNcjh0PWI/U+kzhK4HdV1J73qQLovriLpeRfZCjCpJm1vCUPoq5JuMCxtpc5GP2PPlg7gDXGCXwz4s4IaB/SnsJTwsOF+Jc7HkdSHAx+Q6NrSU/BGO2I0RWn8xuN0os6MevOWHT8ujKQSbA40+kSUfqRzTn+BTfu1iSd5xKka5dpee3ig2Qq3ucnluAxsETemJcFLzSeM8VVuW8d5o493SvCtbOLpno+NA63mX3rOS5xaiaEUZu72XsbLU4in+tiI9WQ4rezvxXNR7IuuMs1sa2ANsdKLKszmdbQNM6z6YpIpAVJsGyVPeMdWGZDOOeuj1ZlO1JaUy1XM23m7a4PLfJdRDR9WzqRy0a0GPy/h5Vv+PHoO64I3PnIxG/ReolLLs75D+e9MStqRybGxwN5W0veCCC3DOOefgdre7HW644Qa8/vWvx/vf/35ceuml2LFjB84//3w8/elPxzHHHIMjjzwST3rSk3DmmWcuNUJmMBgMBoPBYDBsFsTuwnHHHVfFa5sMV111FW5961tX6X3f45hjjllpt2GZsd3fv/lzOKTbfz/pSf1XSRWxhFCWZqHaX0nSRB1HIC1Jo9OiyiNSM5Gq8nO6akfkrziSduY2j3qSfCOCobA8hRhNEkuEdJQ0ZSsEaipH/EIAo/gzOYzi5zLGYZRwxTjVRBe1cZlQb/rZfN0W/ZlUx1GJdyoNVCSai1/KK9KZUl4dRnOPbtP0p/NyUk7TgqRi64/n6QO7Ej8mdAsB0sanNrqm9roMqXuZpNU0YUtAkQgVv9PqK4oqiUq1gBcVFq1Ki1ZdgFZdwffBIfpGTQHG0q1aOjW7itFRdFFFCokraiuyzl84wGsDcclNhuAc4H0K5zhtKM6XdF/ukXAyNufy/ch+x/UwZaLWZlF3Uc9qfhb42SwbH4S0wRDzhkPyh7IREvTmRLMZEtWmSBiSIbkgmxpD2jzheKc3UmLZ4HAx1HXmNmm3ftKquZGx8DxeYpSv83BdB9d3cF0P33dwfQ8/61N41sPNevh+Bj+bwa/N4Gc9/GwGNyv+kibxcvUpLOX2PbupvlQvt8N3cF6eh7SBlqasniPKYpIx+WMEhQiKLOnPVxzYPwyIw5DcxYC4WIDYlYuGAXFewpV/MYAkHAa+d0AcuJwhgMIAGoKqP4JiSG1K5/RBFPP7dATnynPsPY+Hh+/K+HgeN8/z0/Vl/Lu1Ht1sltLWZujW1tCtzVLcVFjy8Tx1eR57rofr4mfDV3OkniH1d06/3YiQ5oUoj4HMUQwBNATEkMYujeWAkOdEwmkewmKBME9XXCwQ5vMSHgaE+bzkWywQ56mcMKjy+HmIw5CeDZmjIHPE7RRR6iXY+3+HNkYfbypp+81vfhO/+Iu/iCuvvBI7duzA93//9+PSSy/Ffe97XwDAS1/60mycYefOnTjrrLPw8pe/fDObbDAYDAaDwWAw7HcsM7a7OPo49P1s3zcgS6gU8q0cg2dClgnV9DENEKWPocgfrPJhFNWHnE6LOm4iPZG64o8NgctH9jWZLJIszUfYNH8rd7gk0URCVNXSO0lYl9iCOEvfKNJWiFc5ni3pVXz2T+TluFynaz/rpK7lU5UFslpal4oKi0TUFrLW6XSiUVpRczEVP5Gu0+QjviKVV8sYTVBPTY/KEXdiUz2trlKq/GoeoI/OSwtLHFRaHjFdNoD1dPGOP8WnCPe6PF0XNW3MKgUgBKvu01hfsE5vdbkC6Rnx/DR6OBC1/VV+oCLOdN8yiaGImxFB6mo3E7eKgNXka0mrSdxM9nI6pvyZ7GvqVW0c6ShuZ0pJfo+JW5ombdn1IyJXSZxrkraRdm/9TkjifOnTBHoNqjVeXlfTT54rxqiICW6wRH8icDtQ18PxiQHX93D9LF2zGdzaWiJg19ayX+L92gxuxvHs97MZ+2epLHH7GdBL+aleMDkJX+Y6k7d6rkTKksla8N8SMAmX3CGTtTQEIJOrC9CCr7m4c8Se/X4O6pIb3Rzk5iC3AGGOSB0IHuQ6EHlQdPw3z5XNSU+JnHXpgvMQqUotXbkUBMAV1TNpEzKmxRiR+uQcogt5fZW/A+kdKwYhhRyNQ4BnsjIsmKCd95n49Uz0dg1Z6/o+E7WZOFZkcll3as1LS9QcUfu3X/6uh9S+kMnU5A/S1iEgDAPCIiAMEWFBCAEIwSHEDgMIwQHROQydQ+g7BMwQMCC4AbHj+/uAOAuIMaZ6AvvZzWSt+i2xviT83sOCAnDdV9fNt6mk7Stf+cqV6du3b8eFF16ICy+8cD+1yGAwGAwGg8Fg2D2I3YVvfOMbOOGEE3L8N77xDfzAD/xAzvPNb36zum8YBlx99dUr7TYsM7b7yrs/Et22Q/diL5ajkrYUEmPq6D0fhc+ERVBH5/UR+3ycPoXTUfvkOn30PiyKNJrk5/CI7IgEUHId8RF8YKX0TNGFqYkurUuzNpwUxRgSqy/IBrs4LoW7Khxcx/dI3q4yrFQbZJpoA0SXZ1GL0NKeFfGKVr9m0WPqifjjvvg7CvmDv4shG0TqYsiqK7wKZ+NKE35RgyHleSaetE7PWpeqpj+XS6UKSREn5khLj2pjaKGdH6fnyCV/lVbnreYmS7rWRtymnh9NGOuOaOq36r8aGw+eH3GJKvUieW4a41WdnjOtjiTGyfunDF2lNgDrGbra2Pti97Cr97mR5yDA3mCNmvFIJJpLpCJiIR3DABoS6UgdIXYR1AWQHxC7AdQvkvqWfieomyUjhN0MsZ8ldS6iBqafJXUvfcpDoi6m75OqGVYjQ13Pama6SgUNlK5vUVmTTyLUHYG837QKGMTm7xAT6Fmquf0bJCpghgVLQvPfnmHR+PXfq1D9PWr/FhU1MNKmlvhfsh2VT50AQNgLk795qDcbi+qhetPJK6n/8p6tjQ2Wv5nlb63+u6r+/uZ3ukfwPaJbS+HeI85qA4jk1d8O1T69abq/SFsadgJ//6l18205nbYGg8FgMBgMBsOBiFNOOQXHH3883vOe92SS9vrrr8fHPvYxPOEJTwAAnHnmmbj22mtx+eWX4+53vzsA4L3vfS9ijDjjjDOWlr3M2O4vXfM+HLK2743wiqQk2MkSKUT56GeSWlHHIcWvj0W2/pCkbtKRxZiPlkp6lCOvkUoefRy2qS9//Or2rfMJlrgBKpJoHnCejfKI31Pyd+zvCK6L8B3gEt8A1yGHfZ/y+o74eCvBdyyp1Hn4LhbJpU4fiXXq+KlTR75TuEgLJrclBUXiqkhqYfkcBQ43YxqreYl8lDVW81Klh4gYCBS47EApHLnemMiI7BKS5JgINKpHa3J+VAezRKEDHEucJWnKyOPl1HiJ1GY9plmqU8WLVF8dJ8eVXSnHFX+pWyTNXGmbtLolEluJdRI/lXUV6+c3P9exzF8VliPiWmpM1kOkZACMWPpP7oP4lYR6dvMiL/4NwClXayBIYaf8ydWGqTzqOO9Wh/M9E2W0del2aN2eqzjeIglN5RnleCpTl1WzRB1PVIXF0FVswpNxJGWRqmNcX25PeSUv70R+0ByAmMYn5kU0cXmxSMUvtiLNDC/pU+Fl+dpy/ajOav1Iu/IkTZG22q/WjtpYLFfkgeaXjhyDZ73aJa34iUlgVPliea9mf6zrqepFaU/b7iVzNj6h4arNunojsd28mt7EooogXZ5flz027IeqPZrgnOpLS0i7Ko14A4tpXXUiQxvY0+nVxhERujCgHxZqo1Lfo/NyuU07tLqeEUWb4/c9hjjgvRvIZ6StwWAwGAyGXYIZ7jJ8J+PGG2/EFVdckcNf+tKX8OlPfxrHHHMMbne72+GpT30qfu/3fg93vOMdccopp+DZz342TjzxRDzgAQ8AAJx22mk4++yz8bjHPQ6veMUrsFgs8MQnPhGPeMQjcOKJJ+5ye35s9v/h8Nm+V4+Qvz/VB/JIDy2rQghR+UNEcIQQ2XUxxYEQEPkiDOwfdBxFBFL3OULwSb2ChKMjROUncLvYr0mPSUxwFszXZc7Bd+I6dJ3LbtcXt4rrHfreoes9us5znC/hLvn9hN97D9+55DKx6H0hDMuFmhyEnhsUlRFqbii6NC8hIp0odoghIgQgBiAMiZcIA9JR1IEQBodh8Agh+cPgU3xwKZxdvj8AwSMdXY0OMRCiS0RUhEsW2CP4+L7iMxyWTpI+IT01V+qkN1tIT3GdV3Ge0HkH39XxHc9v5wl+Mp1U+a6uw0maWFunfEzYOUKeHZmi/ByS4nEoczyVHmfW85y4oxQnPFIM4DUGteYknudwlK9c6Vgxh1F4qQhFDupr1fopyyi7Qsq2BGpFvDLJ6p1jN+UVv3cOnfLreJf9yeq9VwSuxzShm9vDD9Iq4rYiaFX/9fskPc/K37r8HgoqLlDyA0LWpoKn7xc/jerLJDHGpO2qeaqIs8yJuhx2EIIsAkHPpav9bmpul+RR+TBRXtuGUTuX9KXtpxzJRx6Tosu8EO9FTQvpcCbMKZeVwyrfsnJKebnyvM414b8eiu5zJkiFPBW/SIhmQ5ksocqSptELQeuTYUwVL66c8KAqzXNcp8ot9Yt0qrQDikjOs6QnSohXHo9sbFLI1ahOXPBJAdHdLCc10kmdmPQ/T7khlNMiTZpr4kUHdKqH8qkPxyR7MYZZCGTkniUVS/VzqOPSe3557PgeqcEB2Im4oWfDSFuDwWAwGAwGg2GD+OQnP4l73/veOSwqC8477zxcfPHFeOYzn4mbbroJj3/843HttdfiR3/0R3HJJZdg+/bt+Z7Xve51eOITn4if/umfzvYbXvayl+1We05++jNx5BGH71mnNoIswYossaklZEU3XVgMyQDIEDAsBoT5gGGxwDBX184Fhvmc3QHDfI7FTg7vnGMh7jy5w3yBsBiqMsI8GS4ZuD7HOvBiiMCQ9NUhFCMwWuKp+iyjdERS5HEIDogeBA+idEXiI7yxQwxdOhLsO8RBjvn2KdzJEeBexakwHwcWf/R9Lqs+Ltzlj2/ij2ioj/h8dBjA6GtZSSMVPZhyTFc+iEV9RSh6OEX/Jqub8HLsNxbVFiVejCapOKWr02u1FRRVXUqVhnwwpwOqK1hbUQfhQFlKz/ORag/ImLFeTOrSmJL4+x7Ex7azv4mLOm6Un4929z2o67kOVScf7wbPleji1ARMu44AJgdYWs+xJJ8crYYySAU5ej0MY3dYVGEv4WFR0vhY9+j+ELIfoVZrIsfMRbrQCUWoCI1Rt7Srp5Gm5nS1PuOp8qu0dW7eMwk5kSAsUo9jfcJ8QRmCawzEhazupPgrNRyjtGJETpcRdX0iXSntqSQgm1F1I081eFrHb9H52+oAbuIqXcG+uc9P5EnrdWmZKJLq2a/b7Mbtz5TY6D1X3nVevWe8ev8UYq+5QvF3MeT3m48BXU7jdx2VMlxFFIZSV6ODuCYGp9dQtRmlNuryBl7n8oaf7z26rkPXe/QzdvsO3axD16W4ftbluByepXzpHn1/h773Oa7j8n3veSPLo/MernO8cVVOfpTniDuUN6OQfzPkTV0+fRGyTlvewB34CgFhEZM+2xAxsD7bYRHSNYTsD+KGkh4Gz/m4jMFlVzYnQ4iIwSEG3lSshKiptF3N0vh9ouPcOrFtqqaAi07q9eCIJt+kBw2uv/567NixA9/49nU48sgjN7s5BoPBYDAYDIYN4vrrr8dxx+7AddfZ77gW8hv33/7sj3DEoYfs8/pEiqiV4ozyAaY/xJg0TR9M6UofVUzkslv7QyZhJZzzLJKRklTGUJUrH3tSt7QjGzbTR8Cp6Y9AE2zly7n2K9FbIelSuIMS58yGfSoRXTawQyvuqcrW9Uu9mfBAaesyOcEsYqYusJhfPi4cC3Gov1yVOKdT/tZ1Td5WnNORLpfrnDxCrL/yl2BS1LYQpLWobTu2PPadmhMmW8vcdErkVuefmCc1V9k/JQJcEbblI10tpvE46LFaMiciQuuSqHQZ+yxaG5RbCODRXEmcriPXPzVPpf27SrhqKcsqnONdDldprombkJCdyjdV9kbaraGPgAshmglcQOnDZAnyTOJqFzkcFNEbnOc86l6dT5HEUg6Ji1pnMnFbK6Nxk3Bwblm4EKa1KxL9Nambhkb80/FSpnNT5ev4MjPOjWdwkqDXz6J6f2gSFyPSVIhc7S9xGMUpv44nMURH+R03RdACtXTpeDejeR41ga7UsUDUujgHaDU6nU/G43oJd7Xbd2zkzWdjbxL2fXrfeZ23S+/CVmUPJlTIiOoMTbiPJkhLIme1RVGpy0ljl1TqFLVIxBvB0Op4Bk4fArux+IP4JW/IZSTDdFqVkmzkUt7MbdXRrC8arWVotcxsnSdRs8vSC+aIeDW+uu5vXJO0NRgMBoPBYDAYDlD8v7f+Hxw+2w8/6TPfRIVvAqsiiLWqhHKUmxBI1CQU1QmBpW2quFDH13H1vSM1DLleIZRrd+ojrKIHiNJxdgI8MTnkAhzUUe7oypFs58oR7srPrq/TOs/u1H3e1WXCZXWS1ZFj8WNMfk1MUznSzfOUj1UTZV5O/OIGHrNAaUwDp4XIruSL5b6cR+a8KTNynVJf+YYvR811u6efvQmdhIqoS2MyPgq/JzpTJSzl+rbOFfNRPVsN61Qd41Zu5nElLOPDY6T1nMapOD2/Tbo+Vi95SMXpcqDqrNq2AYzJ2CVzpNOcU7pol8zBVNzUvEyVL+1RaW17p0Ctq6T000XNHPE8xHoOK5UGzVy1cxHbsqiun3T9zbrZ6By1fVe8rYpz42facXwVrvOP01o1CJLu6nBT/1Q7W7T9JeUZzR1kvJQ+YL3Wcnh5ejv/Oj2XPFF39mtyU68tNQGpPMfG4hyIXFEl44A4sFoTR4g+qQWKLqmjiaKSxhGrQEiqhJIxr8j+oAxousaQlxhYLMYYp/TnVrpuedJoNFNKNy3QGJ2krJogG0CM2jhiMWDZERu3jNq4IhvGjMo4JrV5aqOLldFN0m2YMohZw6GmacdPXJsj+esnfArTpS6DkbYGg8FgMBgMBsMBimfGe6CP+94QWfUZWkkziV9JIokfEheQZMsCf6wFjgucR/x8xBQh5ZE4uZddllPLYZZJg5JFU/5x+0fEDTMLmRwVEtWz37tEvGq38+g867Hl+HR8Nfl78XcOvS/+buLeVC4fgfWazOUjstwur9onJNTULGVdjKTIdBJyvSa8sxsacjxEDKH4QyAON6R6iIpgjyOiXdcBbgOIEMllNosofTBvmBxcQdhqXaZZVyoKKZ79E2miY1XIwVZPakUEt+1YIQVaT5AbETtTJK1IUdaknquIP9F7msNEiWghJneIEJHaz6bHkqYQ59IzwW3zlCRCRbentFuIQYeNzc2ISKNmLNR6dFK2a/MAzlFFsMr4Zj972jxYNge53HGbl62hURyN05cRujmtJfbUHOf8LTnekueq0qWE4BLUaUVSGJp4c7UxK1LknehQLbpSuxxOJJ/SiZrjp/MU3aiaEBSdrb4iBOGQ1YtQaf7STufRV4MlY5nDakKocinPDZr4UsbU/VRqoqk6Uc3lioar7un1oQhPHolMNgKFfIQmImN6hymC0lOAHwbMiLCNii5ZuW+yHKkr118Me1UGwpr+LqcgVR6q43QZ4pexAKlxUSRwyS95SJUt/jqPHmNx1lNNME3YuoqW1SVLC6WeKV24Jf/GCVvASFuDwWAwGAwGg+GAxZF+gd77/VOZfBQ5jIhbyNFTz0dGPevFdBEuX0G5TMLqdDSui4qQpXxB+cunfWMZGrv6WdRg1c1T4jgqzrXfZFXYjcqQY6YlS8mTCdqGJZwkBMEfrq58EjsUIi6rjXWqzvQVXLOgcq9TH5lTYkijNmyU3ts9TE5JQ+bVZK4iWicI22wISxO2Oh4bl8DVbWgJdfGTCmiCjgCWrBN/IfiikLf8fHuk7YhMoDABK5KQUZhSkoYlwt4xKeucPCMuExuFqC3E7d5A+2iMydla+lWT4G26zCcwHue2jKoOVdZku9aBJg01OVu7NRGf59bpMJRag1SWrEnShXE7iahq5ypDfRvviRhCanUKO3iOTc8SwSOCyCfjjsRGHilJdiap+dSmJEVPbDAtSduTV8b0PIEik7TeZz9NEbZp1yxxcq55i7umK5W3EHHy9JIaVG1gTNyauE3uZLoibVuyV6/hQuxO+Js2L5vI/KwqElPWufx9E9JWk6mFZOV3AtVrQu5Oqjw8vOP5cfKcyRyOyxVys9QpbZ0iYls0hK4mZ1eQsrVRMEUUk07ne5yKcwRH8jevdnN7OD2tZ1f1Y/mcaOq2lOiq+JamLUbHShkycrVe243ASFuDwWAwGAwGg+EAxf+YfWb/qEeAIh+ASv1ALcWJoq6gUWkQAiE4Jb0pfsgVMUCHCYFi9kfi+10iEcSNLDUY+WM7ydgKISYfp8v7VCR0EmkBISYcwTuXjKcUMU42iBVBHiyN5hB8UnnQeSS/SNA6JYnrlboETvOe1SawZK33ijzU0rVArSZhCfNUSe7lOUrjkKUxsxoDVm/Ac5fVHmg1Fm1Yq7yIUH5VRiwqFsTAS/WsZHZSky27h5agzWTqElJ2lb+biueypyRwNWmrScL2+PdojtRcZRJPh4lYp2krSVtL0Ga/c0USTvmhiFshDUX8tSVyl83BrnCF9RhME7CTUssypsCIOJcxl7Tqfi53I5LQug26ratQEbGNNK3M1ZSKiqwWQeIkTEpdCJPvJGsyl1XcqkzodxpG87Vs7jS8Jrua8WlVS6T50JsdKVye/7SB4JaEJb9Ol/vH8zOhjgGljZNzo95zel4yAavGsIwjVeMbdRhKdYzKH9v8ozmqy8jkrgq37ZzsD9JgaNUDopJAqyjIUszshsZN6g26ZPDO+6QeofMYJI4ln4PK26pIKGU1UthO9Di7WhLa1dSnELQ5h5LoLRLDLA2cVRfEStWBqEsYqURgg28dx63y1+WJlLH2T6lHIDUn8hy6JkZI1/rhrLfqSN2pn+qWsN3Im8hIW4PBYDAYDAaD4YDFMXc6CUdsW9vn9WidfZmEi0qiSoi7ECu/HKEfBrYUzf4SpmQVmi1ID0PEIPlVuAvJdQPBcTnMKGaXmNlyUQygSOOX006ibiBZw/ZstVtUFXj4Ll1irTtZ2BaL2+zOOnSdWOjulfXunq139yXc+xQWa9+qnK5L5ec6pf7cLjYKI+1tGI0pMl2TqaIzeAiEgd0Fj+tiSH65aCjzNB8iFkPAPCT/fOB8OS1izuFchsxjpFxfpadYiH0md4VcLpSH+uBlwqdynWOyhy/vIJbrvSvGe5xTcyp+l8bUuWSZXdKS1Xav7i/5xuXWF7g9o7ZOrKTCLpXLtUbIEtsN1xiBc9n4WDI25rKBslDS2NVh1xgga8stxuO4DbltUTFPK+hbReSkjY3aoF423qcM9dVuMQBHbBBuuSsG5tgvaZWxv3SkH6odIsmZL7hpzmRyftRYaEN7bLCqGOdTc8Jz4PQcKFfmwSmDcuKvyiJVD8lz0RiKA43mp+3aaPaE1+dApqFI1lfKUAjWkien57TlBDCaNB1Gk2dZ25dhRFwrolanj1RTaDJcpWmyt71vlKbS2/qrujfQL5fZcjb2xYbG4JNxMYiRsb4Huj4ZD5vN4Po+XbMZ3Ez7py6VVt2TXEhZcql6k5Eybo8Xw5z83st/h8oWD+lnU4yAZWNgYkQsAEMADUN9LQYgJJcWi+YqcXGxAIY2zwAaxC0XAtcTAtfP7dDtajcTx7O0ziy2ealx63tpF7bEjLQ1GAwGg8FgMBgOUBx64q1w2CH7R6dt4QbkKKy+IiITtDEUgjZk8lWI2eQOi4BhCAhDhF8EeI5ziwA3BLhFhFukjzpwGTQEoGNr0UME+QgKDoSYSQWwDJuLAIlI2aqzxfpj2TugE9JULHN38LMOvu/RzdLVr/XoZz26tRlmaz36tVmK3zbDbG1Wu9tm6NfWclzKl+5JV49+NkvlzRLJ2836RNoymeu5TYlUVtbEXZFQA4qUlxhli0KUarI2pLkopGvAfBHhhgDweMdFQOC5wCKAFgOGRcBiHjBfDNi5SPfsXAyYLwJ28jVfBOwckrsYAuaDEMKJ9B2yntwUryV0hWgW4iPPDRTRo0kCRawKmS0ErPNdIlzzmCXr6Z4JEM9W0lN8mutRHknzHZff1XWoenN7qjkpbr2M+BlVhIajhvzLBGyECwOHh3QNfIUBbljADYng8IOEF5xnUeXJ94QByP6Q3UIwxkLqsgihQ1xBZCAToFlfKhOnpEhUIWPJd8nf9ezvEbsO1Ktw34O6mfKXK6p8OU7K61T5ihAmbgu8ELe+SAdOiXKy5F0mbGOSypO5copgdXncBng1nnm+wgAfyvh7PY+R5y3n0/exn4lbp+eHYnptxbIz5TI/tD4J1FJJLfEpkpLEa464fHmcHVCOymfJ7vIo1MfoG+lmkeyGukc1YGrNrEs+y9+mJl0TtBIm1beafF2eZ5IMbsnapozlbV2CvBGH8l5hwtT3/G7qe/i+h5v16GYz+LUZPLvd2loOJ/8aum1ryZ/dlNatrfF9a+jWuJy1tVTmrE9pTAD7PhHFvkttcPzudF16B8KXzarSafmtkDZSKcZE0rIbmUCNQ0BcDIiLhXIXiPM54mJAmCd/mM+Tu5P97IadKV/Os3Oe7lmwO18gLjziwqf6vEMc0gmFNJes1gMOjpLagurvD8+gyMZq6nWKkG3+bKn46e27jW5MAEbaGgwGg8FgMBgMBywOu9NdcNhhh+7zevKHrJBrmahN5FscQiJs2Q1DSAQtE4DDYuAroJsP6OYD/GJI5OB8gJ8v4OYD3GIA5vVFiyFJ5MwH0CKgWwyJuF2E5LpE4joEJmpdIjZcZP2IE1/TQP5qygc5mcxJx0G7dPkO5HqQnyF2PbpuhtCtYehn6PoZFv0auln64O1ma+jX1tCtbUO/LX0099u2sSsf0enDuecP6U59cKcy+vThzB/MniWe0kezkJKKuNVzRDJH5WM5slRRDCF9JA8D4jAgLAZEt0CgASHOEcIChAU8LTALC/hhjn4+x/adEcNOwrBzgbBzjoGvsFBh9UE9zBcIfMXFAmEY0gc4u9KO9PGeJJwoxiyZRYp9yaQQS9J67rNIIgu5XktAJ6nmjiWZk5RzIdp732PGcd2sZ9Jdpa/NMJv16NbKvVmamv3pStLXvhfS1xVCPUvnYmKOZA3JHKl1lNdP2syIvIYCrxNZQ2ExYJjzeppz2nzBcQGL+YBhHsq1CAjzVOYwjxgWEWFBaUNlQQhDuuKQJKEpEguK8rH+WJNX45eDkJxM2kUm64Tgy2oQXH3MXlQhOFepqUj5Sh6v8lfxU2WhlFkkREtbUPnrV0HbtULmiU7TROEklQbaT1lNQnWsnigfuR/5ofTB5vR0BL8YDyxqFYoKBn30n0Zk4jJo4lQeybEKg1odSNb9nMc8jW9XxZW0rplH7ySvnic9R81zoueLG7uM2KqJVD0/qFROkBrTeuwxmo9Adb4wkaeeq1alQv2cRPmzs2SOqnAkRBdB0QGO0qakG7JqhKwT2E0YfhN1B9kIHMd1HaLvkgoEz6oQfDEe14Zbw3KUVSS0huNctelRv7GpPG9a7QCJgVLKflFb4GIyTupjLFdWiyDx7A+sIkHUIFTpdVhUJEh5UqeoZ9BtyTp1J6TVy9qZWmWSSvn90tK7zV+A5t6N0fpG2hoMBoPBYPiOxtH3fOJmN2Gv45pP/MlmN8Gwn/Dqy6/B9u237PuKtDiRkGtEfLxQpGlilqZB4HBIxGpkNx1X5Dg+rpjI10QmSp64qPOOyslHLGOpK+r2MKFRiUuN+5Q+rygdkWRpuhgivA+IA0vndUliz/cdYpeuIFKwfZ+lYTsmWjuRys3pKtzk8zlOJGobqdpOS3cm8rIcSW0lbam4kZhcT6Q6URqjQhCGcvG4hqGEwzAw8V5I3io86HwsNTUEgI+iuiFJBvog0qNC8CuiVtqVJbOmP2CL0bRaHYKoPYBPhAY6tngvKiVEzQQTq10OKxUUTLx2igDWefOVy2MVCr6oU3CiuiJLAReispXkrOZIbYAkyfVYSNxMulMet5il2AMiqxeJTH6nDROdxvFDyiMS8FHNQ+WPlJ4PaY88P2qt6zVU0xKoCZwsSumyFG6llmB06ePWRWJZqzZI6X7JPUnierLsLBqq/BUbuESOk1Q4M4StX18R9ZFwQlEzIWonVBwfx6Zl6aTDKGEt/0mJ4FvOputFpNcPE7RZj7bPmw5FLUxyO5/WxujqPXpeF31f4ntRJVPlT2V3nU/6vPm+Lq9hp1SX1O1s33EQsjoPSTn1MXn6g1hNj+hRlys2p0Firb4n+3ntyCWnSXJ+OWHCayivJfUO1vO3UmA9J8rcJoIbLoKQSHCt67aQqRKvdM8qkrXViavzSHyrR1fClcvzMU3WtmjJ29I/rdu26Lgt+mXFsJron9Ukq6/8sbpXE7HJYFusys11ErIkvZMeUe7ZeOGs7KdOW0bLt0TuRsssMNLWYDAYDAaDwWA4QPE/L/0aXL8/1COow35KKqV8NMXiKsMfXknRdJVfScZkAyI6rfiLYZKgpHCSkRGnDJmMJWiUBOCoHwz5mJagU59YLhkL8kgGoBzSh/OAaYmxVUau5N5spEf7ofMskz5LLc+ffSu+9eTbXyS+cjdR+IPKCI+S6NMSg1qSrEgGqnjUhpbGxnuWGO4ZtXE1MsG5QamkXcZSAm8Dt+wD7HovW6Jx/0BXV5M7hVTSxoxqI0pK4s91I4nB0EgIilRgUBKBIZfRFeNJUr7zrBahJqo0EVUTTwW1lGD9LvEU4SJBG08qEn1Fuq9+f4XqfZffb1RLCGaXlMRg844TyUQHgnfqHQdN+jXvO9lIUBL6ZdPC502jrvd5c6lIqytJ9TWWUh9Jp/dZTcwon1L7kspUkvC8eaI3UfJGiNMbIaVHWbq43ewIVDY01EmPGJLanTAMLHE+lFMf83QtFkVafTFX8SK9Ph9SvJJ4D3xqJCwGDEOAX7BUfAhwQ9oIAW+KyKZmXjU0nqMyb3pjYNfXpGFvot2aWi/fMnK2xCVVCS2Zuz6MtDUYDAaDwWAwGA5Q3Ocf34eZ6/ZDTUvkapSUl5AdJU8twZJJBaLyCSMEsI6nOv9IEkbdXwjZQlxNUzFTPUmIABM4SprIuUoCKRNQXkswCQGlJJkUaVQIKqeIJJ3H8RHUaUvdIxIst7Ma4fztV+ZFSxOhJp+yZFOsCfdYSzC1xLvLJFVLWJFK1/m19BSTTJoAc3Xb1p+vNDdUubVF85ilyUo4NPMUtBV2Sfe+zutLnuCmyvaqTtak3D4/1VwVVM+5mqdawkwkxUSyTFlbV3PQjeJLXNfMV8fzoO9xI38rAYfKbfuhY/QGCfeselHkHrtCaJS1NjVmu5+u64Or3k7leXJ13BjybtJ91u+YXNLEe6rcn/VsUxs3/X6bej6qEdTvy6oNS7rhSq4opw8cEpEYYvJ7gDyxDuLIeoFZRUy3yDqCK93BfPRe/NR1iFlPseTVOoZ9Kdd3Wd9xpf9YSUhnf55f1Z1Maird0PKeScq8WQ9w0UHsgtYLXPRGt2Gf45M+Ya/zhSGVme+Jtc7hrJc6ZsN1LkrbqunSU7PPsCfl7+u2aewJN71veW03om2piU2+6i/vxNiVt6WbuGcjMNLWYDAYDAaDwWA4QHHqcAO2Ob9f62w/lBSvgPrblCqJSqBIfCZ/bcylkr4kKv5R2TSuqxFMWvUxtypNk1GZIHCpzhRWVtNBcC7CkQcQ4eCTFJ5nqapGTNc5IDKp5BzBOQ9iAtMxUeFdRHQecEgEbso8IgWrfqhGK0qsJkWZCGolkUdS0hIfY0UIOh2OjT7AhpDN9QthBSaVRhO0sU/u0ZxoUJE6diB4VXv5PK5JyAggOkJEhIdHpIgIoINHRGRJ4SRlHfnuCEJMtGqSOJbjxKV0rrHQmyRi21WfFWmHmuysSFNF4o5IVjRkrY6HhPmCvpBdp+Lcimu9eVmeVi9ITXiuKqPlUifTJ+9x6+abbucYu0oETeZX76+Nlr+0Xtr1NlXN4AVErrx/CQSKDtEl2fesczcC0bO6ARcRgkP0hOCJ3YjYOQTv0iaIB7sOoQuIHhyn3UQIB0+8KUJqs2qsOzVLQbuantbI77e8ZmJ+b+UNpBg4TqSWa+lnH0KjH1VJRgcJsxtkA4TQRUp+fRHgY3rH+Mjv3Yh6w4PGz9vyeZVNiNrfbn7I5kjtlo2kdrODKiJcjfHEZkiqR9XP5Yzbvd5qW95LGgWm85bfGKvKmn7HTNU2vWaXFr3PsKAA3Pz/1s1npK3BYDAYDAaDwXCA4odOPByH+f0haVvQHrXPhmBIG9LRBmCKq427BB0fx/HapSa/uIRiHCa3i6hpX40pIiiRjUUiqlJPAG1UScW7YrhH8tVqDuo8vinLu3XKh1OEpHLd6s/kMcmt542qcdFzGHU8z1/xo1KjIOOejTGhHvtIS+oFxkT+ir4I2mPDrkpT/gnCT0g9NxmPiXi3JL54puvfGHE47u+Y4NP8xWge+T9q7ls174rSqOtRgVH9u4F2XKbG2DVzUT/zJX1qveX7ltyjy9TtaZ+FqfYKaiJpPG71c13iqvcO6ud86p207J5SPqe5zLuO1s6ovVPxvMmQiVskok7csvEgUv6iWqIDfJdddB2c7wHfwXUd4Hs49jvfw7Nkre9SHur4PlZtAd+xru5kMMv5Dp7JW69JW5G2hVOS2QWO+5TeCVRtIMkGU1HTk6Rgs/qKGNAFJm27ofiZxPXRJ9cN8MFn43f53R7Vs0lIG24e6YXnPBxier7yhg0P+gT93M6b3pirTncoVSP6JEfwys2qQ4o/OHYrNSOijkRUk7T3cpwi0ytjZCgnHDQhvLxfU0SqjuP1lV9EJa2QsMXNbzyVX95v9UtTKdOZLHtiBlYQwvsKFObAZz+7bj4jbQ0Gg8FgMHxHw4x2GQ5kvOLQO2DWzfZLXfnTTKQpmegEadKz/pCWI6LyUQ0idWxVxYv0ZpVW4vLxVyJApWXdkw0VkYi9aVpwGVHjtEslIzGZ65xjySkmjfjDUKydixSnfNB751gSTJNMNEFKSZ4SDzAh0LS5EIcraFv9wap6PyKSsEEyiePjsvzLylBpU/Vrd1exlKhSCa5JaIdMOJVxfirhDUpwupWtWh/r3TlK30VJzsnym8hlRPh6bZsaE7csAchS9Flqj9rnm8o6oDIPspZ00VrKuqrSuaX9mSLQRm1cJ46a8S9EawnXzz3V8dSk70K5q9q4FOp9psktcsTvCzYKGHWbZTOMdccSIXaUJNMpIvqYSL7YIfoBIfaJAAyD0jmc9BGTIgijT6SwEJCV7mEwYZslbtHMLKnnovy9kZMCRfWLUuuidAVTDCCWqKUYgJBcogiEAYghGU7kNKfCkcnfyKoQiAKPWYCjmPzq71Jh4NMM6ymYgkgNExuYI4rooNV/aAnZRk2MIlMJmFaxs9SPiiSv64Gah7L6qOpIqzxl6uFbL2lJnsn33MRimLqfZNQ30K79z9cCAAYa8MEN5DPS1mAwGAwGg8FgOEDxD991Mvx+M0RWPkIdlY9Mpz6YxUiP1o2aj9ZnaScJiwRUbbxHjrFW6RQrvy6ztTRdCF31YY/Ubvk4q0mlsQQfKmJVJGG1lKyywg7lz3FNWJXhVd4shigkUyUi6HRy1U64ypHeNZ5COBeeRiSSG8lkKpLLYoisSM1SFacNjgmZM3WfNkRW+YUwqr69S0Ca3/Z1NeWRxnQisrnLNWPnMPUctKyjm4hbt+6NYCTdpXWXKg/ptPp5dspf8lMTz/dXeaqKlugWbtuzGqvI2lExVIgsLVGp9bPqjSJddokfV5f77Vyddw/QtruNm/JPSTGXqVgi+Txx76j+ifDG0N7luCJKg07EZCEBFPnxcExGOnB0eidA3iFdRe7Gjgnd2DGpGxF9YJK2Q/Sh0vctOr61aoSKTKzWp+6GqF1J73dSfwOIJW61blmw3tnkD6x7VpOyioxlgtYxsUsxlos3HhNZy26unzJRWDZxaOlkVRx6jhuvf72poWLRvtk2huXU8XRK2ZhcnXP01p7Il8JlfNr8+wMTa0DF16M61acUn/Lp9PGYSG/1lp5rUueIRtoaDAaDwWAwGAwHMx7/xEdi+6GH75e6shQYJcvdkZJV7KgvtpgdY7LkLRa1xZp3CMnadhjE1X626j0EzFXcuAzlsrXwXDclP7HF7sgST5ks1ISQJl5dslruvUPXeXSeLat7j77v0Hcd+r7DrBe3x2yW3LVZn+Jmyb826yf9M5VvNuuwxmX0fZ/Llbo6tuwu7ei8z+1L7XYVkZt4DEWeRpaIi2xVPfIVIoYhYAghuUPAQtzFgEUIWCySf75IltXlmuu4IVTp82FI97E7DClPCDHXFUJpQ+T2xFgk+YTcrdCQ2Y6PTgMyBh7wyU0W55NhI+c8nOdL+306lj2O78ZhyaPLFcv2ql7w8WmoOVl5BD8TPCJ9LpLlrVEjNoQUA3w2jDTAhaG4w5B0d4YBfljAt2k6f3V/XW5VL2+KgMqGSCKf1pdQTf0bR62UMOQxGcVPcfDrEGBTDamFAneDJFJtW0WWLksbxS/h8TZ8/25jSvZ4ghTN8UJ6a5fXXtq6ghgOS+tA1p5La8N7gNcQeQ8n61StvZzflbJkfZe5KpKdTjGYYtCwqEdw/MwCLnIbKCbdsp5SeyOSEUTWKZ5c4uqYvOb3a+kbcpzLDeENNeK8xPmr55jfzPkFvf6sTE3G1PTsHmG7rLTVKeO6lufcSHj32y5YTjyvvkfaMEXGTm3wrDciU+tpeYkbK3saRtoaDAaDwWAwGAwHKv72MmDb9n1bx0jMS4wiIUsYiRGYKIQuW7LPZCrHRU3ahZDjk5/TmNyLFblXwrqsyNJOQv7VJCBVROYYzQe5LwSd8x6u81kHo+s8fNfB90lnY/b3PajvEboO1HcIfY+dfQ/f9+hmyfV9j47ddF+f7x2V2XnWEemTX8jDTHgoQgGoJDw1qQ4m1EncSEmCLCSJsRgCKATEEBCHgBgGdjk8DIjDgMBu5V8MiCFwOADDgH4Y4IeAmS6HLwpJio2kbiW5Bj1PjeSnzBEcy9VpQpT1LIIJH/LsukQUZTdbp+9KmI9rS3wVJ5btWRqQfJfq8E3ZTlu795Aj3UVSWpFi7UIiLSWYxsArstSxFLqLsdLF6bP+zUS6+jCoeNbPyXEdE7WS5ke6O9NFuR5F2PJxc33Eu5UK3AjlsIrCqQTKm3Qh6ZenrbhPFb5Rqml9jI9/T0nMVvHiVwRtdvNgLteXy8lc+96StN3L2GUub6Nk33Ry3ryZfJfrrA7leMEoZbeasB72lIbcCpjuw0Z7tucjsPFnenfqWk2wTmM96eGxpK2WwV2vll1Zw0baGgwGg8FgMBgMByhu/vNXIji/3+rbqDQYIZFSHZIBrjbPUkIjZ9gYobGs7lWo01mKKx/NVfoVnSbvPGI24NIhdh0f9+2y7sah6zD3fQp3HYLvOV8idSV/zOlNHBOGxQiM6Hv0lS7CTBCOjl2yZKFIcYKUnuDaUE9RQ6FUUYSQ4hSp12USsJB/XRz4nhSeTZCB+VL11YaClBoLNMf2R/NViFsZBzGIk45ai6Eej+AmjPUo4zvaQE+s/GKkp/X76jh3rAwCuXzEe6wvEs2stHOEMj+y6QGeI1Yx4kXFiDKq1IkaERLL9gEdUXJjREeh5IkRHWm1I3wPu6KD0zN57plAFh2nWTcn+Pj3OuuqrKjGr0jWLKNWxQnPWut6LmnLjIzVhvpyHlWWbkPbto1g1Tsnv5eUugT9XuORa8KlHG0UEBPpcNqY0kR7lKdeOc0TxwNQ9JMmfxQXrT5TyYvsnyKuR8yUUhHgqIQrNTqudlOLIspfiYJykL559njtiKsNkRVXqcuBTis60KuriZc6ndSnVZIAlX7lPOnVqE9N1CagkSzfbWp1d9W/TGEJ6b6qhsk7VpD3ewd1i0aPO4SuladU3jrybNTkbck/VfpqGGlrMBgMBoPBYDAcoLj19g7bXbdf6tKEqg5rl6gNr2/oKtJUXsd6E5eU4ZCJ3ZYs0R9GU591teQaFYIBABCTwkbJqQmLSoqyEIlVvNN5RRJzIp8m9hrpzKLfU4sUVuJmE73SaBkeHVbELqAYo4Y8VfHa4JykOblHpbnmvny/VK7JjRUkbStZ6Kry5fYyHlRylTFkf05T80i7lKd9BmoKiao5Km3ZGFoyqg6XfnNeUveocZ2Kb8dM9WbiXp2m6l7Z8gaK8JNNBbF6L27MGxBFijlqv3LLRobnzYwSLvpRx2Xkspu6s8V7vfHRzF3bwUqGVjaRMoktmZh6FYlxSavCrUR5c8964Vx/WV/l5IBeE+OZ0cSiNtbmeO5Fh6pX0t8elMOepa4lLrvEqjWGFO5BafOAUO5v7kvhUofjvNlYY3431W1d/RCW/uZ3kpqz9t2j87TvNf3um8yny6zS6nlw1YQsX0dtCuW/C3odpc0huLKRqNcAedlQWr1+qk3BvGbaNVRvGtZrt5xsyO3Tf8PanlH9DqpOFShiPevArzb4QmVArjpt0ITlVEIVJ36l+95Vm4Y1iY/cPhrNihv5nQoLQdumlHFwVX7Kd41/qayGkbYGg8FgMBgMBsMBilsddzgO9fuHtAVqclQICuYokI1bEVVEbCQxVJPcyXCsDVvFJXlHrtTNeR0KoUHA+JQsY4oMSN+fhTgrUnykeFWWBsx8rKvSPPNAxXhZ608ltvfnMplIynwuSv7JdreiPxNBIZj03OW4yflL40AERAdkfbOu5AOKMSKpi4hKHr4P+Z5SppCfWDI3k/0cpS8hGamMXSEr6zJTuhvHQd07kVb5lxzB30jbBVN9LxzqmIKjUZ5xnL5/FKfz0ThuVbuWtrOB0BDtmKU4yv9SHMGzNGlUaQTicESSw0z+KIQ6AJHPFKnmEi//fOUyPQghxVLDVlDT+fkso6ifYV1TFaK6FZWaFmLDVSq+JXLHcciEbaX+JMcD+kEo/aHcDW42hLTU5GxFpCqStaOo/CqO3Q4Sn9Tg1P5Y7kEsxC8ROlBFBEu9sp41gSsbCqs2EJY+u827ZSPro3o/tmmr1uOStbTeOpqiB0u9Su63IWwzGesKMRsmTn6kEx99CXcS3+dy5FRIXWYhdskXwlZvflTELVD+WPKAlE2haUloT6ISpjU6GtAx8drJaY986oPVwPCpjk4RuSnOo3Me3oWkoz4GeDj4CHgPeDai512Eg2PZ7vKckQPrLJ56qqYo2TJvrslb/pfYFONyeDnVOwUjbQ0Gg8FgMBgMhgMU9/ipO+Dwtdl+qInyx2khSSkZ4yY2fNVcIRJiIDY+RRhCckMYh4dACEPMcUOIHCbWgavyi3Et8euLiI2kFbIRRNWHdYuWXPXOIdmZEgNl7PcOnS9u9ncOnWNX0jrHRsRKXN/V9+qytOt9In9TO5gIniCBc/sxJiuydLIitMV4XOQ5C3qeGjdEyuNb/DwfOp/OM1FWbOpMOocL8a7buQqaQNWEtgOPk5pHz2PkOc6rPDKuS9Mk7JpyOD2Pv7RFtUP0C0+RvRpThFAmHRVpJPGyARJVOHJ6bNIlvCwvTYQTaVq3Yxl51c5HDjNZyXacqjEp81TPl54LzxsWKQ6JbFnlh6xPqLnT81Y2RGT+IHHrzE89R2qjIY9Tii/jXsJljGXDaRf9Ul4zt7o+UnH5nbxknqbmK/c/z5NrwnWaV/F+YlxlrMv6kDQ3KlPmBl6bNdNrZ4LKao/mq5fFeC1pAh+ZnNXraGptSVy1Jqp73ejeXJdr1jCn6ffyegRuWnBpsJJEdVIZQYig6ECO0kXyPnWIPiBGVuUSigqXIOpdmIRNfuW6cV6RVq9UwjBJK6RtFLIW4mLpxofjsdcS3VldRaX6hbLqFlHnUlS5FDUwXUw67z0lt4sBpFS9IIYk0c5+sN9RLLrd2eij6OEXCXiod9fymSLdM2jaddzzNk3CpYxC0a//ZABG2hoMBoPBYDAYDAcs/v2TX8Oh3f76SV+TBC3pNiUJWxF2LWE4EU5k33SekX+iziwVio0TgpJfjnNGULI+Diq6N6ckZ4VMVXEVwZrJvzpc+dHkR+Eosi5Pp0gMN/2pOJ6p0vGKhBMJs2buRuMmxBG16RtJa8a+ITkqKbclc9NGZ3UF6gixNv4lx3jlSHE+Fs/6bsWAGFWuK/423blirEyVBSVtVtUPnlg0R4bbyaKJvnGkzBZR46o5kfgslclpqOJaQpya++py0MSXeaG6raO5oqqL3Ht1BL7It3bEUpzs71CkLjsQes4vfpHkrMI5H1VldCq/p1SGj7p+aRPgEQvxD1q6lpaRoasI9tjE65MAkqbJ9EmiUNfRlN+SglNY791QzRVJhEi3NkQq0nzmeLc8LpPn6l5N4mpydkwMayJ5grQddaKktvPiXDM3kpcI3qlxdi7HRSrlOsW2Os6Th6mps+bhXDUpOmllVyo/z26W9mSyTzomYxPzHxFko5RsqDINps/xLv9RauLyPRNliV/eafw+c8pfN35qtvQCyi/+8o4pf3j4HcR+avyxjk/EbBtH4N3j8f3aD0yHtTvRC21YjGROFHlb3iYtZVsrRADqN84GnvQMI20NBoPBYDAYDIYN4oMf/CBe9KIX4fLLL8eVV16Jt7zlLXjAAx4AAFgsFvit3/otvOtd78IXv/hF7NixA/e5z33w/Oc/HyeeeGIu4+qrr8aTnvQkvP3tb4f3Hg9+8IPxR3/0Rzj88MN3uT1f/lbEIT7sre6tD0UuAfIRTOo7rCaZKpJPk0mZ9EsfbVo1AlX+Up7O35JSo3ZURNhkN8ZxNB3IZkZciaHqow2ThqfkI7v+lJe8E/kn72mxsY883balJVDbsnKP1nWa0/mDu26B1osqZZFOHsftItRhW2Qpr0r6qzbelo2ENbobgzoCLIbIynFi9qv85f7aGFmupyKI67YV8laPLrUdy540tIoibEmO/DwLEaH8bRqEsEDxY3k439u2QQfXeZbaY+2JoE0kqkjZZZI2k6zlaL0co+8lTJH1pEaOS3l7Prav87Xlil/qFbLYcZsyYTl6luuOla6rN55DGS/F05Fr3j1AoyJEbVRgwi95Ic959ZZNzxSVe1bPyvoYbyw4EfSsNqKARHDmeMfkrqvziesn0jGRj6MLvSXEYNusVX1QnjxOaowKH6f+Toir/zat+Hsyioeap0ykc13OKX/5G7QMbf/kHSvqeJJUKo8bNZLqrpY296GO75wbSbLnvE5Lr9fpTvzVfNXhMnfTfaHGXzYfkmdKmlmkzYWnjajVI+kTBJGAgLJpGCbSSd+v5mpaf35pcztdRbdy7jnnGj+drnEp398StdNjtQpG2hoMBoPBYDAYDBvETTfdhNNPPx2Pfexj8aAHPahKu/nmm/GpT30Kz372s3H66afjmmuuwVOe8hT83M/9HD75yU/mfI961KNw5ZVX4rLLLsNiscBjHvMYPP7xj8frX//6XW7PW//rM9BvO3SP+7Ue0gdlIXpclKOFbOSDjyW6EOBYJx3CkMJhgBsGuDDAs5vCi5Q+DHDDAm4Y4IcFpy84XuXL97Ff6mIXUi8fi0Qsxk+WiqaBSRKHhnhTx0HZr4m7fIxUjpTK8VIm+kImBKePoeY8okOwKb8cS2ViUNoFNFKnVUfKRybJ0VSq/GIExkc5nqqOoyq/j+nYqafAx1OLPxl5IdYpWO7rRD9hLqccgXUjt7RLt3v62VN5lmZTJbgl8Tltihh3NVHXFERuOn5Uzkrps2WgSe/uYVwArU7epbLGKOR0eUbVeuJnN7r6mHX1zPNaIOeq49n/qdeJWmvkPEIuQ9ZUKUuvnQith7O0UdqL3Ha9MVE/c/Kc6uc2H+3Wrjz7RLxeYuPyWqqOgE+71bHxps5RezawhqDebVoyPetLzRsSyvibbGAofan5auM62fzoJ/OT2iSpjGiJrlRfv+eyFDvPxtQz6fi9nsagGJiqDE9lt+hMdaILVelFdVkvqjJ4FYaiMzUow1c6jxjRaurTOlyhnpuq/UtWG6HKpoydlZwVYdoUNEWmOrecONSvrKm31rI32UbecMueyKl43e+W+K3z0Mo8KsvqunYJ6Q0xLR0rpTlMz+9U+q7I2RppazAYDAaDwXDQ4eh7PnGzm7BXQGG+2U0Y4ZxzzsE555wzmbZjxw5cdtllVdyf/Mmf4Id+6Ifwla98Bbe73e3wuc99Dpdccgk+8YlP4B73uAcA4I//+I9xv/vdDy9+8YsridyN4MfWrsL2bYfsXmc2ilakidTRw5h0xoEvChEIERQD4CPIB5APgAsgP4BcALkBQHIJAaAAooGv5IcfQF3IcaAAilwWDalOF0AuAC6mcthkUZHrmf40myLrkjSYA+SIvfd83NSBfAdw2PkOznfwXbJo73wHz+noOpDvAd+Bug7wPbsdqEvxcr/j+BQu5Trv4TWJogmNlnjRfchkbephRdZGbQBGLHQnEqmyzB0SCSGkRBeHQlAIgcHGYNJ9Kd1xvIvtlXQIIiZiIxH8DixHVSbDETBpAKadN02sKvJNE4XV+BTJ19iEW8nY2IzvVJ5CmE+FZR64fS2TMuoMVR/1ovdR4iur5gBa8l2ThwDSvE7k8VP3Kb+uW4czMbQeGZj7ymPuhXDzgHcgVmJKXSLpwOuGOrl6UN8BXV/i+p7j+5xehbuuxHXFhdzvfQo7D+pYxYUXFRlljcPVxK1MnsyDXC6WzSlQhAvNJhVfCGrTKgxwQ71hVYWHIeWTTSi1GZXLCQNciHkzyoXAaymqtcUbU0I7L9ucYolfJ6KFSZSTpWKT3lTvfHonq3dOZYSqkTSXfOO4ki9LwWupdK2aRJ6bkYS6W38dVX0tG4p5bQlJmjft1Jwqf2Q3yL2k73GAT8+Soz7FzcZlZmJVE7NE0+1sl8+E6/K61Cb0kKXGJ11KbqfiO9AoTkufr1eetMXrdlXtXAWliqfpfZFu1Wp51F/uNm6ZpOyy8GS5KVD843aNkaSnaxUHrewsVflbYra+T9Jp4t7lMNLWYDAYDAaDwWDYR7juuuvgnMNRRx0FAPjoRz+Ko446KhO2AHCf+9wH3nt87GMfwwMf+MBdKv/nw2dwxLC2N5s8iZEKBAKIdchVxsdCRAzFny8xJBYjhihuSMarKGKggIEiBooc5nycFogQkMKBIgJKOB2fTGFC8hf6Vv4tARMEDoVoApOzYJ2mnknW6Du4rmfStYfrEokUO5Yu62boJNzPOL5H7GaIffKT77M/dj0iE7spLUmskZcrSeJm3aqin5XJRC01KrMEEgk0Le2VyB1PhfwRaTOXydgBPgxMwCaJ6BS3yGl+WOQ4F0KdLvnjkNNKHSEdnY4RDiGREREQ4tZl4nbZs1cItoqEbdQj1GoMXJZ6Fgno1jCPVpkQXDcRV6tIEClQUpKdk4QvoEh1RQpWZGhLxrIUpZKAdixtWSQzRdK5SDUXaecS7qK2vF4M+lQGfiqJ6CItKtKBlRQnt73dJqjgk9E8yAZElwjatE46uL6Dm83g+h5u1sPPZim8NoOfrcGtzeD6Gfxa8vu1NbhtaxzWLt83U3lnJc7Nerie65F6O94k6dKmSGqjkLdTa4hYPybryQzJ6BFCSP4hgIahXIsFaLFAXCxA8wVoGBDn8xQ/nyf/fIE4nyPunJc4zp/8c8R5yp/LWnDZISR3CKAwsJtOFlCIQERu6ypUkp4b44q2HGqSrd6okY0ZkeqWd0PIEt0urX2R7m7D7B+5rpygKGUoKXFVfnR1W8YbStITTfsVUtY15GvW/YykEqSHuogwQ7p6itk/Q8SMCGuVX9SKpHw9CDN9DxF6lDStR7qTtjRkr27zSBZaPWZTpGrRRa8N8rUu67bPccUfCOk3B8C679u8Wj2CqivXD2gDcquWhX59TxPV6ylBWFbixmGkrcFgMBgMBoPBsA9wyy234L/9t/+GRz7ykTjyyCMBAFdddRVufetbV/n6vscxxxyDq666amlZO3fuxM6dO3P4+uuvBwA85h8OQz/btg9aPwHKn8qKHFTHQFnqK0t2xnJM1cXI0pgi6Vn8LvDx0hjgQ8xSmonwS9KZKezY77jcRP5lf/oyZj+4bcBKKU6WQEsfk8pSNyUL3YkQHBCDEII1EahVIog6hMBHgkNXE4FtvqgIQzn+HTMxKGSgr4hKLeU5Os+qSMFpyUwh6vRxbpG2LX5RgSAEYPEXItA3aZV6BEmjiKhUJVA+Psy6RUViG0pSbQJj9Qi632N/RWhrUk5LKDsVp/JlidkqHRN5JupWzkSgnajGq1kDnt1KHEzSKcc5nZbd4q+l/+p8y8vWzVk+J6MUJk4QI8gDFAjwBPKRDb11SdKepWFls0I2PaiXTYvkL+5sFDfKxxsexJsnWZJXS9j6LklyZmlb2fiYmCMthSxStiJpmyVdGwlzloyVzQrHmxg5bmjdRXq/qXw5r2x6aMldJb2uJW1FTU2rVxrYHWpo49jTsvdG27LOWJbUHz2+6jSC0IpCnrZ5WhJ4nLdRA8KdqMqq3g0lrg5Pw034S82tFG5L9E4QvxNpBGBOhMWGy6nbMG7b2K9B2jdBiua5Gb0OtW7i5hWXw0piVpVR8tD4nqactj3L+tBK2QITf3ar/MXV2JNn3khbg8FgMBgMBoNhL2OxWOBhD3sYiAgXXXTRHpf3vOc9D7/zO78ziu/DgN53e1z+etCfpoUkKEdJC3mgjuM3pG0id1vitkiD5uP7lcRfLORje+V4bhtxO/XXnG73sr7xh7+D4rwQ4ZGORhJckir2SRVE1pUJDyKPSEysip88YvSgyASsPi488rt8jLg+OqyODE+pRVh2bFjIvDxP5SiwPlavVSaIdKeeN61GYSqc9TeqNBdFWjTmcrVux6x7UpP+mUCcet6WxWkSge93LvsdfzWnE+DKyj2lD/CWlBjHuVxOdjkOuRzxq096h1Ff2n60XR0TEoVs0GmrjgyXuBV5mnJQxWFMgixp72Q/eOMjR8YI54r1d+ci4JM6EzCJ6p3oOe3gM6mbpHQjS7Zr9SM5X9eB1L1yX3HLEX1ZU1DH8ytdqVq3bZ6vmsCupdaVv3qvaTJVbThpcjcWctcrAtZXZGxo7mvenaISgduhVTgAhIr92gWsRy7pV80yss6pjCvzKM8yEmtXya3lz6hm8pZIVGoSj+oTGUv9TYWTa3qDWJVXq+4gNWiFVG5cRTqHSm+z+vvR5JfyplRSlHSuONevwhvsZf1eHKtekQ2mdoOuTi+qXDaU5sblpi6Vh2CV6hfpoSZgW7LWbSDfNIU7FbccRtoaDAaDwWAwGAx7EULY/sd//Afe+973ZilbADj++OPxzW9+s8o/DAOuvvpqHH/88UvLvOCCC/D0pz89h6+//nrc9ra3xYXf/S0cvjbb+51okT9uSXEFSQ1CctNxxRCjUpWg1SQkdwhFbcIwpPxhYNUJIWIYUt5B5wmpzEGVEwMl1QqxqGOIjpQ1ahqRWsvgnJIucpSsZTuX3WJ1m/3eofMp3Pl0ee/QOeXPF5S/pPkqL3K5yS2Wvp1qh5CPYo0dmJb4ISEpSI6DFivokfhYqcwZER8vJYRY0tLYlitGQnDlijFZ8A6O05F0QoZIiJ7TXaK8kwZbNTdMoOjjqavIi0yQ5jmSMUlkam0ZXY9fikvjzRbV8zyVPJ3XaWVe5R6Xyyhz4vUzIm2S+UEheqeX0pg4lePChHI0OM9XniOUeSJKVtOVP6j5lLRAVN0zVZ6ui4iKdXdF+Ornq33ugDEB7/J8uez34kLPX7Fgn8bSVdbrxe+dji/55P6qfDUX5Zkp85GJlhWcyZTknia5iaat0kcVlmPfpPwRrYV7lW8iTVS7LLN6L23cKFHYvjfy86ov/X5RY5jHdTS29fjruFFeTkOTptuU/YotdlN9nCBZhZjVY1KNGdDMI4l27aVjHDEdX+qry9dEcOtWzR+FZaOu+GvDesXo3lLjl6LWIceV0x/aKGbJV8cV437FWGBWQ5PblGayqIJpZ68Qp1pfdm1ArzGGqY3wKaN8rTHMLgZWFxOU8b4JY5mj8or6l+Kv25VJXzU/o2dyF8KrU3aF9DbS1mAwGAwGg+GgwzWf+JPNbsJewfXXX4/jjv3zzW7GLkEI2y984Qt43/veh2OPPbZKP/PMM3Httdfi8ssvx93vfncAwHvf+17EGHHGGWcsLXfbtm3Ytm2sBuHon/uvOOKwQ/duJ6ZA6gM1EiLF5IbIV0AMEWEIiENACAFhGBAWAWExYFgMyZ0PGBaL7IZFwDBf8DUkd7HAgv2d5BsC3HyAXwxwiwFhGIBFAIYBGAIwJP2OPqb2uCAG0hJNWItUFeRPJybgnEu6OZ2QqB7w3heCtXPovE9u5S9uz/7kevSS3qdySr50v1flCKnrvCZxFXHL7YQmBRWjkSU1SUhbYntFQtRSQ6ozES7k+hKSXQjzRKrX+STNhwgfmIgP6Wh5zMoJ01zEiKxKI6lGSI1fodJ2yYRBBmF8qUyFRE15WVg5s0Uy59rveLzlOcjxHFeR6UJKupqgrOanXUhwpb/8nyeXHlWSblB6JmMyguM8ijoQT0lFCJIfUeqm3NfUBpFoc3ljQgbZaclkqLHXgUmmbFehqI/sZU+eflIEXcmfaCJXxoOQxoRS39IQcT+AnBdESkqa7xdCRpOEG+ybCBJXEep+oiKl7zgs6WkIaXwvyiZYDi9J2+M5kGczP88uGTzsfHa99/Bdh64Xtytun9yu79HNenR9h77v0c1SWp/jU1zX9yp/h67jMrTbpXqSy+1gXcOljTyrzTLKm1L8DiEikGwWshHMyJt+FCJC0H+TAuIwIAwh/W0aBgzDgDhE/nuVwvJ3K+S87EpZQ6j+1snfP3GJpC2R21fauksT1/rz+y2/yOp4p+Jdc8GhGOETv2fd7S7rcBe97iWvr8pxrlUtMvGekxec410LcUUqHAC87E40xWjXEQB5+XGd5Kb9DiVMElblZYaZlFt7N4J0t/xPcKMyVxGy66VPw0hbg8FgMBgMBoNhg7jxxhtxxRVX5PCXvvQlfPrTn8YxxxyDE044AQ95yEPwqU99Cu94xzsQQsh6ao855hisra3htNNOw9lnn43HPe5xeMUrXoHFYoEnPvGJeMQjHoETTzxxl9vTn3waZkccsdf6txyUiUCKMV/5Q3VIH8CeP3DdkMhVt1gA83LRfA7aKe4cmA+IO+fw8zn8zvEV53O4nQu4xQKu48vz5QY45+EwINFnQ/qYZFEoR0k/bVE0uIS15Q8+EqJAPmCT2GXSg9k5oEvW6PPVT7h9h9h5+N4j9l12Xe/T1YnbIfQeLIoL10t9Key9qpsJXGpIxKoPmt8RwlYZissG4yqiNjK5QVnKOQpBOyh3EKnnkPyDlooubr6Hr5jrSASGSOxSVG3itkqbp5Al9RQx2kq8ioStSMyKlGxkEpxckpaFupxLY0pZfNNlg1oVaa8kcrOkdVN/aWMt5Zk7wPMic1QkbYuEq5DsWvpVpKB9RPYLGe5YCtpxPmW9p2xY8HhTTAStz37W1+ooW+Vx3AaX17sQQhtl1FNfc/+z31Vzl0m5au4S5VpLSZe0ap7zVTYyailot6T+0gZZNiNGUNZP8dZStln6WEso13PnlURzrZKESXLOl0msWOcV9TMu51GkdV4noqd0/blxKGSb84qobUnZWZ+vfjZLhOtshn5thn5bcmdra8m/bYZ+bQ39Wo9+bQ2zbTP029ZSHknje/q1WSp/bYZe1dH1fa7bM0mcyFtpZyFw6+kRoraQtaQ3DUMhWaMQsYsBYV42C4edslE4x2LnIuXZmfzDfI5h5wKLnfOUh92cb75A4I3HsFjkDcmwKIRwDEkdSAwu6XlGLOTk0hdd2a6QB9bzO8w7MZSZyFQnOtBZbUhkNSIkUrZsODM2YdG3LvfGztdh0anuuyJl64t6kUptD5QO8PEiqlQo1VdRzeNbVTuiMoSKv7hJ5332x5DvQwz8myQgsktarQ9ptT61yh5kSdv8Ut4NWnX3MKcAhPXzOdo1uv+Aw/XXX48dO3bgG9++rjqaZjAYDAaDwWDY2kiStjtw3XVb53fc+9//ftz73vcexZ933nl47nOfi1NOOWXyvve97334yZ/8SQDA1VdfjSc+8Yl4+9vfDu89HvzgB+NlL3sZDj/88A23Q37jvuWuZ+Kwbv/JYYh0YEtk1EerC/GUpTs5nI/iq3jxV0e6JayIq1xmG9ZSpSgEWHUMve2DQEsiZaNFHvDJ2jxYjybYaBL6dImfZrMSnvWgfgbMZqB+xmkz0KzPcej6FO5nICmLXbBRJXRdIoh1G3z5YK+lp9p+kZK0LVJomuRIREe6KKSP3Cwplv3NVUmUaamyibioJc5ikTiLkSV/Y9Z3WqTPNGkrEodFirVVd9B7h74T12PWOcw6j7XOYdZ7zLzDWu+xrffZFf/23mPbzGPWcfyM4ybybuuTRPRa77Gm6pl1Ur9Hn1VfMGnsamncao6ozE8iF4jHixLZFGKS+gshkeMs0TcsBgyLwFcioRIBlQiqxSKwpPqARU4bksQ6h8MQczlhEFcukUiUZ4DJMCHFZJ6m9j1YMs95keBMOml9V8g4P+vhWSLTz2bo1mboxF1bK+FtKdxvW0O3bQ39WnJz3NoaurWeXb5PleVns0QGzvpcv+v7LNXpPG+csERhIQRdtXZAVG1MyTqhYcgbVHExJJKOSbywWCDMF4iLAWE+R2DyL8znCDvnGHbOi38+T/fN5wicZ5DwfIHIZYXFApHJR6lP1mNuE19yCmIKNWmuyG0hxEWyPz/LPj3LnSunA+RUgXbVyYHk5/VQnSKQcr0qv1YHMyLbnZDNY0pw9DdIk+ZaXY/8HZGTBfwsB3UaoDphoE8ZcPog+YK6nze/QiwbUUXljLRBqeiRNmI5Xwsm1JEJ6y49p116fpPbwfczOF5DftbDzWbwa2spzM+/X1tL/rU1+G1rHF5TYc43S36X70uu67lsXW/Xw3UeYGLd8d8jp6Vc1QSRkoSO/K6L+V0nG3sBA0s/D0PyD4uQJJ1DTO+xIb3PFvKOq8IDbyQ24cWAxSBp/H6LadMxyDs2RJ7PWN7Dsu6pkY7fh6Awx43//Nfr/sY1SVuDwWAwGAwGg2GD+Mmf/MmVRxw3Ig9xzDHH4PWvf/1eac+hRzoc2u8vuRB1NJWcImxddtMHmssfrSG6fDo+6doUP3Ja4LBIE3oOuwgEPj7pIh+LjlQkS2Oq17OwoFMnL+XDfqNHH4uEbn2KkwjJ5o9jXYMRoIDiH/JtrOOPTW0Vwbg0PtGBggP1SP7Bgfp0xS656ByoA6hjCVCW9CWWACWn3HzctepEniTKjULRDpHVFCRJpKToNJE/CAEUhpQWWOVEGIAQ4AexbJ/UURDH53tCAA3shgDEgcssElCIgetN9bMoMLdVBlt3IiFJSzbqCpj88V6OdXsmiDyroUjSZ13fgTqP0HfY2XcY2L1ZjnRz3p6vrnfMnbukyqLz6PuOy+3QiXRip46Uq7ZUR7uVNHQ6TpwXT+lzJBDxfAixLQRhSOo+aBhATNqRIu9ISLzFABo6JvQ84sIhLhxo4RAXSNcA0AKJ6BsIcaB0z0CggUAhkVAU0nOa1pVjwonlOVesIRJJ0AgQIiKB1ZQEUEiSen6RxjEymRv6Dl7IVD5O7yVOwlkak8leie9UWqfuyyRxIru8kioVoikfu88SnFNrSM+PkLdUbUDI/OhNjeQOifAeBiZ2meDlKywU6ZuP6ms/lzGUzRCpJ5O0oSZqXRSymV8L7VxV0s3cdy+bVEW6P28WdWmjKgpJ16d49B1vMnX5il2H2HeIszSnXd8hdEp6V+ZL1CH0Si2CUs0ghL9WT5MJdVcUjeh1VEvc6vkhtfEgJ0Eib4oEVoXQqkzQGxhDEy7pZWNlrBIh6jWsn5vImonzS7n0pXr0SNaQvLTVO5xV/mCI6d08H4C+h+sXQD/Pm4lONgB5M9HxxiF449BJWteVsLpc16d5VpuHzvP8+648M1mNwjprSM9R0tOTNw1pyVoiPa5DQAz87gvN2lBrDSGgG5Khv24IWAuhKi9vvsT2EmI9Vhs2+wshDvjnDeQz0tZgMBgMBoPBYDhAcez3HLd/DJFpqVUlySmSr6QkjUJgv5ZoCkqKSelIrfSiDmMdqhInR/p91qeaLLgjaL2pLC0TFYErUjOrvsMIgKNM3Ob+8cc2gUAuguARkaRHiSLr9Q2JpA4OMTjEIRGzsUci0HqkcEeIPTEZQqA+InYB1IXsUjcgdj3IDyA+oioStuR9Oh7LR1SzSgf1tVwd7yQhdNKRUMRYW7MPYs1+gA9Myg5DihsG+LBgsja5flhwngX7g8qj0qWsMMDlOrQb4UjcRNyKEavpj2XuJ0sY52O6anySmwgk8j27STI68jX0PRbdLIX7HrGb8VzMcrhOK/emsiL7gdghq1VIruc2uWp+ar2PyP1z3FfHOwIyRy7PkYMPjucK8AFwIW1quEDwA8GHdLkQ4UOXjg0PHj54uMHDBwcffI7zwcEFV9yowpGv4OCZ4He8hmQdOVknZVaqfokkoQuFZwJK951corKgTC0ckiQ1sn8i/1TcinioNFRx9QbX9MHuJiwkoUov0p7qUhJ6RG18SotUjw+/rkanAqgpW1Q26DbI/bov1BJosnmgThKk0wOJ2EYnJGw6ARCF4FtLpB/W1oC1GWhtDVhbA7G0Jq2tIW5LEp5x2xoCS0QHTu+ydCdLfPa9kvDsi8SokuZ0SoozS53qDaq8I6dIdSHfhJwTKWTZ3Ai8ucHSy1Ekmedz9s8Rd86TdPTOnSmO1fKEnSktcN64c444LFJZSiKaFgNoseANlkQwykYYWE1C2rAaT1r2iYSn4787LjYGyIphslAZDKsNkGkDY8GJeoTkz4bHfJcNmQVWsxCassQQGaE1huby5qSoRljy1s5/j2oDZOnyyiBY9sfIRsZqQ2JifKyLxQBZx/HaYNmMtKGyxhgZFeNjGzVEJv0oq5qlv6vZc8ptY0jFlXRd9hzRSFuDwWAwGAwGg+FgxtOuOx39bPt+qKlYhheJoYp006RTSxKGQha60JJ4dZwPiUgcpzVlcLjUE1MbFGGZiTFu//KeYULsCRVzoonqrMcyEqJLFznWF+ticZNd+PSPOBwdIgVE8ln3XoxJwjEGsJQtQJ6Um8onn9i0ok9wTDk53W8Zj4oULGPoxWUpLh9Y/18IINZv60MEDUkqyg8iIl0Ic8T0sR0jZX2piUwp46cloItEbRrPZTLiTnmS9J2StO3Sse3kJv3BvmcJ21nHUpmdOorf8/H5PunV5OP0ftYnf3X15dj+rOd8XT5yL2XnY/9MNlXSguzPEoJKTDATgJpwUrqhiaX4wjAkI0osTRuGAWE+pGPzrJ8zzBcYFjM+jt+zzs6O03y6Fh5h7hDmQBg84gIIfMUFIQyEuCCWRHSIg2cDgywZHilJhkM2NabXUXWsXeuXVUb06uP37Mrxezk6r4/jd37iaL6r8vnO1+VVR+/B9Wt1FbXhuKkHUJZ+BO8FZdchUHrsB+UO5LBg/yKW8IKARdR+YEEOiwjM5b6IybwDhwdKKi9TfaX+0LQvLTVXEbtlbrSOZp/mQqTSu2QYrFcS5/2sx2zWo+87zGY9ZrMZZrMea2szzNaSuzabYbY2w2zWpfBaCqe0nv1p/fSqrH7WY9b3Srq9y1LsXdcpCXottV5PUqu+IktRslRmHALiokNYeNCQ3LDgNTAHwk4gzAihJ4SOMHhC7IHBRwQfMbiI4AIG6hCoQ4DHQB4hekR0CDEgBI/Qp7gQecPOJ2LTOSiSVV4ALLHevOPqcNEDmxKEGNUvQ7VRV/mZInRCDqq8TpfloIn98jek1k9b/22RsnTLMbl26okaB8rmjypN/Y12Km2kYzb/veC/K9pt8klPpa623ql2tCjk6zKTkhLvqnt0Ce3PivWGbBmMtDUYDAaDwWAwGA5QfAHHwOOQfVuJ/vCpPqgIzjExiJj8Lip/gPMRDgHeheQiwDkmDMX1Ab5Lx+9dF+DDkOKzROjARko4LioStyGLXUPcFinOaZkgIUBFihNaklMkWxupzizJ6bskren7EnZ9kkwiz3p+kUgFRBACyLO0XaAkXes7RD+AdJlscKZuR5LozGRtxQY2k0WoSNuWvEUmb8uYViR6DEpSlg23RMCTg4OHdx7O9YlIJQcPB4cOzvfwfoDrQi7fqbpy3TxPhVxWmwAN9HFu71pDSq3F+2K9Xo5ni+GjnknYPhtZ4vier26GruvR+xl636Nz6epdB48OnevQwaMjh44cvLjRZclQD6FnKBs7H+kdZkYwSXIDaUgc6+B0yU8OgXxSLwKWkgMhuHQNDggeGDqHEB1C9Bh6hyH6TDQN6DGgR3ADBjdDcANCN2DwA0IXELoBoWfjSbNyBLwcKS+6j8sRYsIUaZsexVpfaiZK87y5SeLWK92oVbgrhOxYPyqn+zFxq3Wlir7W3AZFLAOtQbK8dJSErBsRt4FJ1Iq4ZaJ2UITrUJGxhazVcSl/iZd7SjkOQyz1tdeYtG0pKKaUqjnxapwKcduL23fouw4zn575GTrM0GNGHWaxx2zoMXMdZvBYg0MfHdYiMBsIs0XE2jxgNnN8Gp8w6wmzWUDXdZj1Qy6/r8haz8+AL6pPnCZt6wmSkxNZV3dgw1OVuoqB9f4OZeNjschu2vgIfEXEgRDmxBscLm14DB1C6BDCLO1VwSXpVecRug4x9gj9DBEDohsQuwGxY1Umcuw/q0so62jjx+/d5Gs+U4huKqwIRrfEzySsDpfXlKIhm7glUVXLJklQKg5NRJIOQ4ZHxWrJ5FZKuZKCJ1Xs8vIn4zYJCwrAzevnM9LWYDAYDAaDwWA4QLHtsKPg1w7dT7UViZb8wURFX18k0VEqRnFi4+djoqR0yolOTwoqTvSgSt7Ax2GLagJiyVpq61R69CAisrrNS9BKc5WvWlenK8mkOk4+hDNzlZIiku5WtwCwaPRotmU0cVV8acvUR/yodzTyqA/cIoGkpY1a3bJ12IGc6DRcU/Mu5TRl6Pq0tPOEdNMqPdCVoSiHPH6JzGVDOKILk62qS3w26EMebuHhgoebd3D/KfpNOd0rt4rzafg98QZE2qSAG7L+zdwG58rcT7S7TEUzJupZLWuFque6GJJzQOx4I8CDYg+Ka2WNRO3KumE/AqgjkAugPoK2KeNVVPvrNtVzvLtrSIhdKNctXQcyvyqNAAQHBEXiVWNd7q/qUuNfycst3fQQUPWYahJoag5znvZ9k8dRyhyvm+l8XKJeG3n8x21ZhcwTuiT3j8jPqyNANtrkWfa8jpwYmlL6gH2nwnq9NGtmMl+zPpv1o9UgFL9+RtqpGa+fvBmi/ubUa6j+u6PXCqqw47XlQdQ364lAPoBmMa+jvbWGpt77+p2CLHXsKn8xBiZx6p3UvKPA86Dvmx77Vqew+nuo2qko3oaz1f2s/97oddLOHaoxEzc2Yzn1tz4299S/TXSZdb3QjV75t2hfgMIc+Oz6ChKMtDUYDAaDwWAwGA5Q/PoJX8Yh2/eteoTqM4ZY917+QGY1AWz8JRuB0cZg2Fp0NuLClqMDW6oPQ4oPFKq08T2qPG1oJsZkTCmTW6Qsd/OH4pKPMSGHslQXkxbeK4NX2vBU57Oxo84nwzodG9bpGuM7Xa/j1H2d5PHZzYZ6soErB9epduS2yYc2oCWmyrenmh9tSInYqrmSpNRXUMZ0wiAGe8QQT9I3HIMyzCP5xDjPoMsoc0a6Ln4uKgMwIn2G1XMk0oJwRYrSqaPUxSiZqwwcidGwdAzbq/GXdJ4neHhXJP9ag2Ndp54FX4wn6fmBQ1HhMJJmU2uJiYt6jijPkR6nNG40XguICBQREVjfc8xzkPMOxUp7tQ5j65e1y/Xu4hrK86TnC4rjYUk+x2le5xGJXIgaheQXyViv8tf5pu9P90rdrT7c8ZxMzo8OZ+6WdcpyWHT4FjfliFTiIr8rI6/JOiz6bafvyf6JOjIvXPnXhx4TqPHK7z8UydZK0hUipVvivJC7QJK8b6RjR36o8tr6pF3SHvXcrEIhv8sYCVGX34HaT/UzXYWhVN4wSajTq/swVZZa0+o9nMnLFWRtiVcqDJg4zTpkq8tnN+mbTfq0i7/Ei+5bqlw3ykeOddjmsl3lj0zWij5bWdzEc1d3iMrzhqLyIKvuQa3bVk7G+EjVaRnPp2gql/XVFrfkc9Tm5fIinwQipcOWYt0uNKoZVj55ew9DHPB3G8h30JO28sflhuuv3+SWGAwGg8FgMBh2BfL7bX9LPxwIkDH5iUO+hiO2r+23OjOJQKjI2hiRDY8JERQUuTRQQCA2OkYBQ4wYYiKThiFgGGK5FiHFheSPTD4NAyGElDdmQioZJhMSiii1I5NOsXxQT8GhkKHJyjzqo/c+ka1938HPEvnXhx79Wofe9ehih77v0XWsq3HWo9/WoZ8l/Y/9Wo9+1qFfm6FfI/Rdh27NoV9z6Gcefe/Qz5Iu1l6RvF4Ri6kthUQWCdCRrsc0STUByKSfkLWZfOUxDkNAWADDgsd3iBjmEWEeMCwGLBYDhnm5FvMBw2KBsIgYMGBBA4awwBADz03KV6yup/mNQ0i6IFlXLkm7Ymnv6jlSRFImbJHJ1E6OevdKX2fv0fsU1/VpfNOV/L7zaW6Cy/EeHj159OjQw6NziZDtKBG7HRw6x0e5u/q4udbhmo91u3qCisAdE3iO58rxOkIijQJLRQZQWjfEBvhixMCE7JCJc143gTAsJMxrqlpDhIGfgWEoxG3QxHAkJMHDdg0tJ52guun01ZCmQsB6IWMdOFwIW8+ka8fhTkhZB3SclsuBKofr0n7H5U8aM1ONbqaozBOEoGUXad5EHUEhYwv5GpmcjUhqCwJRiSNRaUCiDprjmntVPtJ+3RYJo27rKrgJV88VIOPVEuxqnmSMkRLadB0u8Vyfun/0jEAJlDbtXIaq33qOmvGJ7ZgR1ByW9FjNrSbSS3hZem7LinkZbQiMwsXAF0F04hYX2VhYImgTIcsGxhSJG7wyOsbp2SCZMkImeaMvhsckLanlaYlbXxkhE8J26rlzaTDSvBKyCiUvkq9UCFof2SCZMh7miIqhMTEwFiM8BfhIKiyGyEI2apaNj1WGzVIdyEbJqCZxwW1teiNaaQlFg22aKyF3nQrLdkjZ6HH8/+gdw7655FznN+5BT9recMMNAIBTT7ntJrfEYDAYDAaDwbA7uOGGG7Bjx47NbsaWgvzG/f7f/tNNbslBALHqHTa1FYZViOtnMWwxbJRNNGw+aInfsP9h6+Y7Duv9xnV0kIsuxBjx9a9/HUccccRoN3pv4vrrr8dtb3tbfPWrX8WRRx65z+rZX7D+bH0cbH2y/mxtWH+2Ng62/gAHX5+sP7sHIsINN9yAE088Ed77fVbPgQj7jbt7sP5sbRxs/QEOvj5Zf7Y2rD9bHwdbn6w/u4eN/sY96CVtvfe4zW1us9/qO/LIIw+KB1Vg/dn6ONj6ZP3Z2rD+bG0cbP0BDr4+WX92HSZhOw37jbtnsP5sbRxs/QEOvj5Zf7Y2rD9bHwdbn6w/u46N/MY1kQWDwWAwGAwGg8FgMBgMBoPBYNhCMNLWYDAYDAaDwWAwGAwGg8FgMBi2EIy03UvYtm0bnvOc52Dbtm2b3ZS9AuvP1sfB1ifrz9aG9Wdr42DrD3Dw9cn6YzhQcbDNtfVna+Ng6w9w8PXJ+rO1Yf3Z+jjY+mT92bc46A2RGQwGg8FgMBgMBoPBYDAYDAbDgQSTtDUYDAaDwWAwGAwGg8FgMBgMhi0EI20NBoPBYDAYDAaDwWAwGAwGg2ELwUhbg8FgMBgMBoPBYDAYDAaDwWDYQjDSdg/xwQ9+ED/7sz+LE088Ec45vPWtb93sJu0Rnvvc58I5V113uctdNrtZe4Svfe1r+Pmf/3kce+yxOOSQQ/B93/d9+OQnP7nZzdpt3HDDDXjqU5+Kk08+GYcccgjuda974ROf+MRmN2u38OhHP7p61o499licffbZ+MxnPrPZTdtttH2S64orrtjspu0RHv3oR+MBD3jAZjdjr+Bg6svBBr1+ZrMZTjnlFDzzmc/ELbfcstlN2y385E/+JJ761KeO4i+++GIcddRR+709e4oQAu51r3vhQQ96UBV/3XXX4ba3vS3++3//75vUMsO+gP3G3fqw37hbF/Yb98DBwfS78GDqy8EG+427tbGVf+MaabuHuOmmm3D66afjwgsv3Oym7DV87/d+L6688sp8/d3f/d1mN2m3cc011+BHfuRHMJvN8O53vxv/8i//gj/4gz/A0UcfvdlN22380i/9Ei677DK89rWvxT/90z/hZ37mZ3Cf+9wHX/va1za7abuFs88+Oz9r73nPe9D3Pe5///tvdrP2CLpPcp1yyimb3SzDQYqvfvWreOxjH4sTTzwRa2trOPnkk/GUpzwF3/72tze7absFWT9f/OIX8dKXvhR/+qd/iuc85zmb3SwDgK7rcPHFF+OSSy7B6173uhz/pCc9Ccccc4zN00EG+427tWG/cbc+7DeuwbBnsN+4hv2Frfwbt9+0mg8SnHPOOTjnnHM2uxl7FX3f4/jjj9/sZuwVvOAFL8Btb3tbvPrVr85xB/IPi//8z//E3/zN3+D//J//gx//8R8HkCRH3v72t+Oiiy7C7/3e721yC3cd27Zty8/b8ccfj2c961n4sR/7MXzrW9/CrW51q01u3e5B98lg2Jf44he/iDPPPBN3utOd8Fd/9Vc45ZRT8M///M/4jd/4Dbz73e/G3//93+OYY47Z7GbuEvT6ue1tb4v73Oc+uOyyy/CCF7xgk1tmAIA73elOeP7zn48nPelJ+Kmf+il8/OMfx1//9V/jE5/4BNbW1ja7eYa9CPuNu7Vhv3G3Puw3rsGw+7DfuIb9ja36G9ckbQ0jfOELX8CJJ56IO9zhDnjUox6Fr3zlK5vdpN3G2972NtzjHvfAQx/6UNz61rfGD/7gD+LP//zPN7tZu41hGBBCwPbt26v4Qw455ICWFhHceOON+Mu//EuceuqpOPbYYze7OQbDlsev/dqvYW1tDf/3//5f/MRP/ARud7vb4ZxzzsHf/u3f4mtf+9oBf1z9s5/9LD7ykY8YGbjF8KQnPQmnn346fuEXfgGPf/zj8du//ds4/fTTN7tZBsO6sN+4Wxf2G9dgMGjYb1zDZmAr/sY10tZQ4Ywzzshi4RdddBG+9KUv4cd+7Mdwww03bHbTdgtf/OIXcdFFF+GOd7wjLr30UjzhCU/Ak5/8ZLzmNa/Z7KbtFo444giceeaZ+N3f/V18/etfRwgBf/mXf4mPfvSjuPLKKze7ebuFd7zjHTj88MNx+OGH44gjjsDb3vY2vOENb4D3B+7rSffp8MMPx0Mf+tDNbpLhIMTVV1+NSy+9FL/6q7+KQw45pEo7/vjj8ahHPQpveMMbQESb1MLdg6yf7du34/u+7/vwzW9+E7/xG7+x2c0yKDjncNFFF+E973kPjjvuODzrWc/a7CYZDOvCfuNubdhv3AMD9hvXsD9gv3ENm4Wt+BvX1CMYKuhjcN///d+PM844AyeffDLe+MY34vzzz9/Elu0eYoy4xz3ugd///d8HAPzgD/4gPvvZz+IVr3gFzjvvvE1u3e7hta99LR772MfipJNOQtd1uNvd7oZHPvKRuPzyyze7abuFe9/73rjooosAJP1sL3/5y3HOOefg4x//OE4++eRNbt3uQfcJAA477LBNbI3hYMUXvvAFEBFOO+20yfTTTjsN11xzDb71rW/h1re+9X5u3e5D1s9NN92El770pej7Hg9+8IM3u1mGBq961atw6KGH4ktf+hL+3//7f7j97W+/2U0yGFbCfuNufdhv3K0P+41r2B+w37iGzcRW+4174G7zGfYLjjrqKNzpTnc6YK2CnnDCCfie7/meKu600047oI/Dffd3fzc+8IEP4MYbb8RXv/pVfPzjH8discAd7nCHzW7abuGwww7DqaeeilNPPRX3vOc98b/+1//CTTfddEAf8dN9OvXUU3HCCSdsdpMMBzHWkzI40I5dyfo5/fTT8apXvQof+9jH8MpXvnKzm7VbOPLII3HdddeN4q+99lrs2LFjE1q0d/CRj3wEL33pS/GOd7wDP/RDP4Tzzz//gJN2MRjsN+7Wg/3G3fqw37iG/Qn7jbt1Yb9x9x+MtDWsxI033oh///d/P2D/IP/Ij/wI/u3f/q2K+/znP3/A7m5rHHbYYTjhhBNwzTXX4NJLL8W555672U3aK3DOwXuP//zP/9zsphgMWxqnnnoqnHP43Oc+N5n+uc99Dre61a1w1FFH7d+G7UV47/Gbv/mb+K3f+q0D8p1w5zvfGZ/61KdG8Z/61KdwpzvdaRNatOe4+eab8ehHPxpPeMITcO973xuvfOUr8fGPfxyveMUrNrtpBsMuwX7jbl3Yb1yD4Tsb9ht368N+4+4/GGm7h7jxxhvx6U9/Gp/+9KcBAF/60pfw6U9/+oDd5f71X/91fOADH8CXv/xlfOQjH8EDH/hAdF2HRz7ykZvdtN3C0572NPz93/89fv/3fx9XXHEFXv/61+PP/uzP8Gu/9mub3bTdxqWXXopLLrkEX/rSl3DZZZfh3ve+N+5yl7vgMY95zGY3bbewc+dOXHXVVbjqqqvwuc99Dk8Vm5TmAAAMuklEQVR60pNw44034md/9mc3u2mGgxjXXXddfnfL9dWvfnWzm7VLOPbYY3Hf+94XL3/5y0c/9q666iq87nWvw6Mf/ejNadxexEMf+lB0XYcLL7xws5uyy3jCE56Az3/+83jyk5+Mz3zmM/i3f/s3vOQlL8Ff/dVf4RnPeMZmN2+3cMEFF4CI8PznPx8AcPvb3x4vfvGL8cxnPhNf/vKXN7dxhr0K+427tWG/cbc+7DeuYTNgv3EPHNhv3K2FLfsblwx7hPe9730EYHSdd955m9203cLDH/5wOuGEE2htbY1OOukkevjDH05XXHHFZjdrj/D2t7+d7nrXu9K2bdvoLne5C/3Zn/3ZZjdpj/CGN7yB7nCHO9Da2hodf/zx9Gu/9mt07bXXbnazdgvnnXdetW6OOOIIuuc970lvfvObN7tpu43zzjuPzj333M1uxl7HwdSv9rmT6/zzz9/spu0yPv/5z9N3fdd30Y/92I/RBz7wAfrKV75C7373u+mud70r/cAP/ADdcMMNm93EXcKy5+x5z3se3epWt6Ibb7xx/zdqD/Hxj3+c7nvf+9KtbnUr2rFjB51xxhn0lre8ZbObtVt4//vfT13X0Yc+9KFR2s/8zM/QT/3UT1GMcRNaZtgXsN+4Wx/2G3frwn7jHjg4mPplv3G3Luw37tbGVv6N64hMCZnBYDAYDAcqvvzlL+O5z30uLrnkEnzzm98EEeFBD3oQXvva1+LQQw/d7OYZDAaDwWAwGAy7DPuNazAARtoaDAaDwXAQ4TnPeQ5e8pKX4LLLLsMP//APb3ZzDAaDwWAwGAyGPYb9xjV8J8JIW4PBYDAYDjK8+tWvxnXXXYcnP/nJ8N7U1xsMBoPBYDAYDnzYb1zDdxqMtDUYDAaDwWAwGAwGg8FgMBgMhi0E25owGAwGg8FgMBgMBoPBYDAYDIYtBCNtDQaDwWAwGAwGg8FgMBgMBoNhC8FIW4PBYDAYDAaDwWAwGAwGg8Fg2EIw0tZgMBgMBoPBYDAYDAaDwWAwGLYQjLQ1GAwGg8FgMBgMBoPBYDAYDIYtBCNtDQaD4QCBcw5vfetbd/v+97///XDO4dprr92jdjz60Y/GAx7wgD0qw2AwGAwGg8FgAOw3rsFgMCyDkbYGg8HA+Na3voUnPOEJuN3tbodt27bh+OOPx1lnnYUPf/jDm920vYJ73eteuPLKK7Fjx47NborBYDAYDAaDYT/BfuMaDAbDgYl+sxtgMBgMWwUPfvCDMZ/P8ZrXvAZ3uMMd8I1vfAPvec978O1vf3uzm7ZXsLa2huOPP36zm2EwGAwGg8Fg2I+w37gGg8FwYMIkbQ0GgwHAtddeiw996EN4wQtegHvf+944+eST8UM/9EO44IIL8HM/93M530te8hJ83/d9Hw477DDc9ra3xa/+6q/ixhtvzOkXX3wxjjrqKLzjHe/Ane98Zxx66KF4yEMegptvvhmvec1rcPvb3x5HH300nvzkJyOEkO+7/e1vj9/93d/FIx/5SBx22GE46aSTcOGFF65s81e/+lU87GEPw1FHHYVjjjkG5557Lr785S8vzd8eHZO2XnrppTjttNNw+OGH4+yzz8aVV16Z7wkh4OlPfzqOOuooHHvssXjmM58JIqrKjTHiec97Hk455RQccsghOP300/HmN78ZAEBEuM997oOzzjor33f11VfjNre5DX77t3979aQYDAaDwWAwGPYI9hvXfuMaDIYDF0baGgwGA4DDDz8chx9+ON761rdi586dS/N57/Gyl70M//zP/4zXvOY1eO9734tnPvOZVZ6bb74ZL3vZy/DXf/3XuOSSS/D+978fD3zgA/Gud70L73rXu/Da174Wf/qnf5p/9Ale9KIX4fTTT8c//MM/4FnPehae8pSn4LLLLptsx2KxwFlnnYUjjjgCH/rQh/DhD384/yCdz+cb7vfNN9+MF7/4xXjta1+LD37wg/jKV76CX//1X8/pf/AHf4CLL74Yr3rVq/B3f/d3uPrqq/GWt7ylKuN5z3se/uIv/gKveMUr8M///M942tOehp//+Z/HBz7wATjn8JrXvAaf+MQn8LKXvQwA8Cu/8is46aST7AetwWAwGAwGwz6G/ca137gGg+EABhkMBoOBiIje/OY309FHH03bt2+ne93rXnTBBRfQP/7jP668501vehMde+yxOfzqV7+aANAVV1yR4375l3+ZDj30ULrhhhty3FlnnUW//Mu/nMMnn3wynX322VXZD3/4w+mcc87JYQD0lre8hYiIXvva19Kd73xnijHm9J07d9IhhxxCl1566WRb3/e+9xEAuuaaa5a29cILL6Tjjjsuh0844QR64QtfmMOLxYJuc5vb0LnnnktERLfccgsdeuih9JGPfKSq6/zzz6dHPvKROfzGN76Rtm/fTs961rPosMMOo89//vOTbTQYDAaDwWAw7F3Yb1z7jWswGA5MmKStwWAwMB784Afj61//Ot72trfh7LPPxvvf/37c7W53w8UXX5zz/O3f/i1++qd/GieddBKOOOII/MIv/AK+/e1v4+abb855Dj30UHz3d393Dh933HG4/e1vj8MPP7yK++Y3v1nVf+aZZ47Cn/vc5ybb+o//+I+44oorcMQRR2QJimOOOQa33HIL/v3f/33DfW7besIJJ+R2XXfddbjyyitxxhln5PS+73GPe9wjh6+44grcfPPNuO9975vbcfjhh+Mv/uIvqnY89KEPxQMf+EA8//nPx4tf/GLc8Y533HAbDQaDwWAwGAy7D/uNa79xDQbDgQkzRGYwGAwK27dvx33ve1/c9773xbOf/Wz80i/9Ep7znOfg0Y9+NL785S/j/ve/P57whCfgf/7P/4ljjjkGf/d3f4fzzz8f8/kchx56KABgNptVZTrnJuNijLvdzhtvvBF3v/vd8brXvW6Udqtb3WrD5Uy1ixp9Xuu1AwDe+c534qSTTqrStm3blv0333wzLr/8cnRdhy984QsbLt9gMBgMBoPBsOew37j2G9dgMBx4MNLWYDAYVuB7vud78Na3vhUAcPnllyPGiD/4gz+A9+mgwhvf+Ma9Vtff//3fj8KnnXbaZN673e1ueMMb3oBb3/rWOPLII/daGzR27NiBE044AR/72Mfw4z/+4wCAYRhw+eWX4253uxuAND7btm3DV77yFfzET/zE0rKe8YxnwHuPd7/73bjf/e6H//Jf/gt+6qd+ap+022AwGAwGg8GwGvYb137jGgyGrQ8jbQ0GgwHAt7/9bTz0oQ/FYx/7WHz/938/jjjiCHzyk5/EC1/4Qpx77rkAgFNPPRWLxQJ//Md/jJ/92Z/Fhz/8YbziFa/Ya2348Ic/jBe+8IV4wAMegMsuuwxvetOb8M53vnMy76Me9Si86EUvwrnnnov/8T/+B25zm9vgP/7jP/C///f/xjOf+Uzc5ja32SttespTnoLnP//5uOMd74i73OUueMlLXpIt8wLAEUccgV//9V/H0572NMQY8aM/+qO47rrr8OEPfxhHHnkkzjvvPLzzne/Eq171Knz0ox/F3e52N/zGb/wGzjvvPHzmM5/B0UcfvVfaaTAYDAaDwWAYw37jTsN+4xoMhgMBptPWYDAYkCzrnnHGGXjpS1+KH//xH8dd73pXPPvZz8bjHvc4/Mmf/AkA4PTTT8dLXvISvOAFL8Bd73pXvO51r8Pznve8vdaGZzzjGfjkJz+JH/zBH8Tv/d7v4SUveQnOOuusybyHHnooPvjBD+J2t7sdHvSgB+G0007D+eefj1tuuWWvSiU84xnPwC/8wi/gvPPOw5lnnokjjjgCD3zgA6s8v/u7v4tnP/vZeN7znofTTjsNZ599Nt75znfilFNOwbe+9S2cf/75eO5zn5slF37nd34Hxx13HH7lV35lr7XTYDAYDAaDwTCG/cZd3ib7jWswGLY6HO2KYheDwWAw7BPc/va3x1Of+lQ89alP3eymGAwGg8FgMBgMewX2G9dgMBh2HyZpazAYDAaDwWAwGAwGg8FgMBgMWwhG2hoMBoPBYDAYDAaDwWAwGAwGwxaCqUcwGAwGg8FgMBgMBoPBYDAYDIYtBJO0NRgMBoPBYDAYDAaDwWAwGAyGLQQjbQ0Gg8FgMBgMBoPBYDAYDAaDYQvBSFuDwWAwGAwGg8FgMBgMBoPBYNhCMNLWYDAYDAaDwWAwGAwGg8FgMBi2EIy0NRgMBoPBYDAYDAaDwWAwGAyGLQQjbQ0Gg8FgMBgMBoPBYDAYDAaDYQvBSFuDwWAwGAwGg8FgMBgMBoPBYNhCMNLWYDAYDAaDwWAwGAwGg8FgMBi2EIy0NRgMBoPBYDAYDAaDwWAwGAyGLYT/H38dcA/bh2u5AAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 1400x300 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ── Visualise training samples ─────────────────────────────────────────────\n",
"fig, axes = plt.subplots(1, 2, figsize=(14, 3))\n",
"\n",
"axes[0].imshow(sensory_np.T, aspect='auto', cmap='Blues', vmin=0, vmax=1)\n",
"axes[0].set_xlabel('Sample index')\n",
"axes[0].set_ylabel('Vocab index')\n",
"axes[0].set_title(f'Sensory (one-hot chars): \"{decoded}\"')\n",
"axes[0].set_xticks(range(N_SAMPLES))\n",
"axes[0].set_xticklabels(list(decoded))\n",
"\n",
"axes[1].imshow(raw_np[:, SENSORY_SIZE:].T, aspect='auto', cmap='RdBu', vmin=0, vmax=1)\n",
"axes[1].set_xlabel('Sample index')\n",
"axes[1].set_ylabel('Context unit')\n",
"axes[1].set_title('Context (hidden state from C++ model)')\n",
"axes[1].set_xticks(range(N_SAMPLES))\n",
"axes[1].set_xticklabels(list(decoded))\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c33-0005",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-31T13:08:36.418708648Z",
"start_time": "2026-05-31T13:08:36.362936110Z"
},
"execution": {
"iopub.execute_input": "2026-05-31T13:20:34.234146Z",
"iopub.status.busy": "2026-05-31T13:20:34.233956Z",
"iopub.status.idle": "2026-05-31T13:20:34.237559Z",
"shell.execute_reply": "2026-05-31T13:20:34.236677Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"sequences shape : (1, 12, 40) → 1 sequence of 12 chars\n"
]
}
],
"source": [
"# ── Prepare sequences for StackRnn ─────────────────────────────────────────\n",
"# Treat the 12 samples as one sequence of length 12.\n",
"# Shape required by _train_shared: (num_seq, T, sensory_size)\n",
"sequences = sensory_np[np_cpu.newaxis, :, :] # (1, 12, 40)\n",
"print(f\"sequences shape : {sequences.shape} → 1 sequence of {N_SAMPLES} chars\")"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "c33-0006",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-31T13:08:36.533366117Z",
"start_time": "2026-05-31T13:08:36.419697676Z"
},
"execution": {
"iopub.execute_input": "2026-05-31T13:20:34.239185Z",
"iopub.status.busy": "2026-05-31T13:20:34.239037Z",
"iopub.status.idle": "2026-05-31T13:20:34.340753Z",
"shell.execute_reply": "2026-05-31T13:20:34.340012Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Mode : shared\n",
"Visible : 128 (context) + 40 (sensory) = 168\n",
"Hidden : 128\n",
"Parameters : 21,504\n"
]
}
],
"source": [
"# ── Build model ────────────────────────────────────────────────────────────\n",
"rnn = StackRnn(PRJ_NAME, WORK_DIR)\n",
"rnn.append(StackRnn.make_layer(\n",
" \"layer0\",\n",
" sensory_size=SENSORY_SIZE,\n",
" h_size=CONTEXT_SIZE,\n",
" entity_params=EntityParams(\n",
" do_gaussian_visible=False,\n",
" do_gaussian_hidden=False,\n",
" num_gibbs_samples=NUM_GIBBS,\n",
" ),\n",
" training_params=TrainingParams(\n",
" learning_rate=LEARNING_RATE,\n",
" momentum=MOMENTUM,\n",
" num_epochs=NUM_EPOCHS,\n",
" mini_batch_size=MINI_BATCH,\n",
" num_gibbs_samples=NUM_GIBBS,\n",
" do_rao_blackwell=RAO_BLACKWELL,\n",
" l2_lambda=L2_LAMBDA,\n",
" ),\n",
"))\n",
"\n",
"rnn.state_init(0.01)\n",
"rnn.state_load()\n",
"\n",
"e = rnn.from_index(0).entity\n",
"print(f\"Mode : {'shared' if rnn.is_shared else 'unrolled'}\")\n",
"print(f\"Visible : {rnn.h_size()} (context) + {rnn.sensory_size()} (sensory) = {e.shape[0]}\")\n",
"print(f\"Hidden : {rnn.h_size()}\")\n",
"print(f\"Parameters : {e.shape[0] * e.shape[1]:,}\")"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c33-0007",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-31T13:09:38.858147334Z",
"start_time": "2026-05-31T13:08:36.534644759Z"
},
"execution": {
"iopub.execute_input": "2026-05-31T13:20:34.342621Z",
"iopub.status.busy": "2026-05-31T13:20:34.342419Z",
"iopub.status.idle": "2026-05-31T13:21:34.675600Z",
"shell.execute_reply": "2026-05-31T13:21:34.674804Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 0%\n",
"Entity-168x128: err_rms : 0.007963934693765124\n",
"Entity-168x128: l2_norm : 0.13640459663394264\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 10%\n",
"Entity-168x128: err_rms : 0.005571022117215054\n",
"Entity-168x128: l2_norm : 1.0539494674107415\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 20%\n",
"Entity-168x128: err_rms : 0.0048118883761428055\n",
"Entity-168x128: l2_norm : 2.270192559885112\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 30%\n",
"Entity-168x128: err_rms : 0.002181992196506815\n",
"Entity-168x128: l2_norm : 4.991681680557447\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 40%\n",
"Entity-168x128: err_rms : 3.24825386987531e-05\n",
"Entity-168x128: l2_norm : 7.995848240242153\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 50%\n",
"Entity-168x128: err_rms : 5.321199897379831e-06\n",
"Entity-168x128: l2_norm : 9.06923591324248\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 60%\n",
"Entity-168x128: err_rms : 2.4543750331298456e-06\n",
"Entity-168x128: l2_norm : 9.655311282237259\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 70%\n",
"Entity-168x128: err_rms : 1.4489958412988583e-05\n",
"Entity-168x128: l2_norm : 10.065727181513859\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 80%\n",
"Entity-168x128: err_rms : 4.792305435411291e-06\n",
"Entity-168x128: l2_norm : 10.393621523703466\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 90%\n",
"Entity-168x128: err_rms : 2.769616398928912e-06\n",
"Entity-168x128: l2_norm : 10.6626654332347\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"-------------------------------------------\n",
"Entity-168x128: progress : 100%\n",
"Entity-168x128: err_rms : 7.407126331323391e-06\n",
"Entity-168x128: l2_norm : 10.836674676167918\n"
]
}
],
"source": [
"# ── Train: predict next character from current context ─────────────────────\n",
"# Pairs used: (h_t, x_{t+1})\n",
"# Step 1 — advance context: h_t = forward([h_{t-1} | x_t]) (no weight update)\n",
"# Step 2 — CD update on visible = [h_t | x_{t+1}] (predict next)\n",
"from rbm.train import cd_binary_binary, _to_gpu\n",
"from rbm.matrix import rms_error_accu\n",
"\n",
"entity = rnn.from_index(0).entity\n",
"h_sz = rnn.h_size()\n",
"num_seq, T, s_sz = sequences.shape\n",
"\n",
"rnn.state_init(0.01) # fresh weights for the new training objective\n",
"entity.grad_zero()\n",
"\n",
"d_progress = 100.0 / NUM_EPOCHS\n",
"progress = 0.0\n",
"status = CheckpointStatus(rnn.state_save, update_interval=10)\n",
"status.on_change(entity)\n",
"\n",
"for epoch in range(NUM_EPOCHS):\n",
" h = np.zeros((num_seq, h_sz))\n",
" err_total = 0.0\n",
"\n",
" for t in range(T - 1):\n",
" x_t = _to_gpu(sequences[:, t, :]) # current char x_t\n",
" x_tp1 = _to_gpu(sequences[:, t+1, :]) # next char x_{t+1}\n",
"\n",
" # Step 1: advance context to h_t (no training)\n",
" h = entity.forward(np.concatenate([h, x_t], axis=1))\n",
"\n",
" # Step 2: train on [h_t | x_{t+1}]\n",
" vis = np.concatenate([h, x_tp1], axis=1)\n",
" dwhv, dbv, dbh = cd_binary_binary(entity, vis)\n",
" grad = entity.grad_compute(dbv, dbh, dwhv)\n",
" entity.state_adjust(grad, 1.0 / num_seq)\n",
" err_total += rms_error_accu(vis - entity.reconstruct(entity.forward(vis)))\n",
"\n",
" progress += d_progress\n",
" if status.want_report(round(progress)):\n",
" if not status.on_change(entity, {\n",
" \"progress\": {\"value\": round(progress), \"unit\": \"%\"},\n",
" \"err_rms\": {\"value\": err_total / (T - 1), \"unit\": \"\"},\n",
" }):\n",
" break\n",
"\n",
"rnn.state_save()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "c33-0008",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-31T13:09:38.912352345Z",
"start_time": "2026-05-31T13:09:38.859145208Z"
},
"execution": {
"iopub.execute_input": "2026-05-31T13:21:34.677685Z",
"iopub.status.busy": "2026-05-31T13:21:34.677446Z",
"iopub.status.idle": "2026-05-31T13:21:34.708392Z",
"shell.execute_reply": "2026-05-31T13:21:34.707481Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Input : '1569BFILQRUX'\n",
"Reconstruction: '6569BFILQRUX'\n",
"Char accuracy : 11/12 = 92%\n"
]
}
],
"source": [
"# ── Reconstruction: teacher-forced ─────────────────────────────────────────\n",
"# Step through each sample, reconstruct, compare to input.\n",
"rnn.reset(batch_size=1)\n",
"recons = []\n",
"for i in range(N_SAMPLES):\n",
" x_t = np.array(sensory_np[i][np_cpu.newaxis, :])\n",
" h = rnn.step(x_t)\n",
" rec = convert(rnn.reconstruct(h))[0] # (40,)\n",
" recons.append(rec)\n",
"\n",
"recons_np = np_cpu.array(recons) # (12, 40)\n",
"decoded_recon = ''.join(idx_to_char[int(np_cpu.argmax(recons_np[i]))] for i in range(N_SAMPLES))\n",
"\n",
"print(f\"Input : '{decoded}'\")\n",
"print(f\"Reconstruction: '{decoded_recon}'\")\n",
"\n",
"correct = sum(decoded[i] == decoded_recon[i] for i in range(N_SAMPLES))\n",
"print(f\"Char accuracy : {correct}/{N_SAMPLES} = {100*correct/N_SAMPLES:.0f}%\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "c33-0009",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-31T13:09:39.163096694Z",
"start_time": "2026-05-31T13:09:38.913165111Z"
},
"execution": {
"iopub.execute_input": "2026-05-31T13:21:34.710060Z",
"iopub.status.busy": "2026-05-31T13:21:34.709820Z",
"iopub.status.idle": "2026-05-31T13:21:34.989488Z",
"shell.execute_reply": "2026-05-31T13:21:34.988778Z"
}
},
"outputs": [
{
"data": {
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"text/plain": [
"<Figure size 1400x300 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# ── Visualise reconstruction ───────────────────────────────────────────────\n",
"fig, axes = plt.subplots(1, 2, figsize=(14, 3))\n",
"\n",
"axes[0].imshow(sensory_np.T, aspect='auto', cmap='Blues', vmin=0, vmax=1)\n",
"axes[0].set_title(f'Input: \"{decoded}\"')\n",
"axes[0].set_xticks(range(N_SAMPLES))\n",
"axes[0].set_xticklabels(list(decoded))\n",
"axes[0].set_ylabel('Vocab index')\n",
"\n",
"axes[1].imshow(recons_np.T, aspect='auto', cmap='Blues', vmin=0, vmax=1)\n",
"axes[1].set_title(f'Reconstruction: \"{decoded_recon}\"')\n",
"axes[1].set_xticks(range(N_SAMPLES))\n",
"axes[1].set_xticklabels(list(decoded_recon))\n",
"\n",
"plt.tight_layout()\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "c33-0010",
"metadata": {
"ExecuteTime": {
"end_time": "2026-05-31T13:09:39.296395123Z",
"start_time": "2026-05-31T13:09:39.164243277Z"
},
"execution": {
"iopub.execute_input": "2026-05-31T13:21:34.991419Z",
"iopub.status.busy": "2026-05-31T13:21:34.991236Z",
"iopub.status.idle": "2026-05-31T13:21:35.087658Z",
"shell.execute_reply": "2026-05-31T13:21:35.086665Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Input (t+1) : '569BFILQRUX'\n",
"Predicted from h_t : '569BFILQRUX'\n",
"Next-step accuracy : 11/11 = 100%\n"
]
}
],
"source": [
"# ── Next-step prediction ───────────────────────────────────────────────────\n",
"# Given h_t (context after seeing x_t), predict x_{t+1} via clamped Gibbs.\n",
"def predict_next(rnn, context, n_gibbs=NUM_GIBBS, temperature=1.0):\n",
" entity = rnn.next_entity()\n",
" h_sz, s_sz = rnn.h_size(), rnn.sensory_size()\n",
" x_init = (np.random.rand(1, s_sz) > 0.5).astype(float)\n",
" visible = np.concatenate([context, x_init], axis=1)\n",
" for _ in range(n_gibbs):\n",
" h = entity.forward(visible)\n",
" visible = entity.reconstruct(h)\n",
" visible[:, :h_sz] = context\n",
" probs = convert(visible[:, h_sz:])[0]\n",
" probs = np_cpu.power(np_cpu.clip(probs, 1e-10, 1.0), 1.0 / temperature)\n",
" probs /= probs.sum()\n",
" return probs\n",
"\n",
"rnn.reset(batch_size=1)\n",
"h = np.zeros((1, CONTEXT_SIZE))\n",
"predicted = ''\n",
"\n",
"for i in range(N_SAMPLES - 1):\n",
" x_t = np.array(sensory_np[i][np_cpu.newaxis, :])\n",
" h = rnn.step(x_t) # advance to h_t\n",
" probs = predict_next(rnn, h.copy()) # predict x_{t+1} from h_t\n",
" predicted += idx_to_char[int(np_cpu.argmax(probs))]\n",
"\n",
"print(f\"Input (t+1) : '{decoded[1:]}'\")\n",
"print(f\"Predicted from h_t : '{predicted}'\")\n",
"correct = sum(decoded[i+1] == predicted[i] for i in range(N_SAMPLES - 1))\n",
"print(f\"Next-step accuracy : {correct}/{N_SAMPLES-1} = {100*correct/(N_SAMPLES-1):.0f}%\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.3"
}
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"nbformat": 4,
"nbformat_minor": 5
}