diff --git a/examples/TimeSeriesLSTM.ipynb b/examples/TimeSeriesLSTM.ipynb
index b8f86925..6fdb3811 100644
--- a/examples/TimeSeriesLSTM.ipynb
+++ b/examples/TimeSeriesLSTM.ipynb
@@ -20,16 +20,16 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "--2023-02-11 16:24:56-- https://raw.githubusercontent.com/jbrownlee/Datasets/master/airline-passengers.csv\n",
- "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 2606:50c0:8001::154, 2606:50c0:8002::154, 2606:50c0:8003::154, ...\n",
- "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|2606:50c0:8001::154|:443... connected.\n",
+ "--2023-02-11 16:28:25-- https://raw.githubusercontent.com/jbrownlee/Datasets/master/airline-passengers.csv\n",
+ "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 2606:50c0:8000::154, 2606:50c0:8003::154, 2606:50c0:8002::154, ...\n",
+ "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|2606:50c0:8000::154|:443... connected.\n",
"HTTP request sent, awaiting response... 200 OK\n",
"Length: 2180 (2,1K) [text/plain]\n",
- "Saving to: ‘airline-passengers.csv.3’\n",
+ "Saving to: ‘airline-passengers.csv.4’\n",
"\n",
"airline-passengers. 100%[===================>] 2,13K --.-KB/s in 0s \n",
"\n",
- "2023-02-11 16:24:56 (28,2 MB/s) - ‘airline-passengers.csv.3’ saved [2180/2180]\n",
+ "2023-02-11 16:28:25 (31,9 MB/s) - ‘airline-passengers.csv.4’ saved [2180/2180]\n",
"\n"
]
}
@@ -178,7 +178,7 @@
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "b0c41dfea5bd4cbe91ebf7efcbcf0674",
+ "model_id": "591aa4bfce744f54b6862a7b843fb1c0",
"version_major": 2,
"version_minor": 0
},
@@ -204,3808 +204,6 @@
{
"cell_type": "code",
"execution_count": 10,
- "id": "ddd413fe",
- "metadata": {},
- "outputs": [
- {
- "data": {
- "image/svg+xml": [
- ""
- ],
- "text/plain": [
- ""
- ]
- },
- "execution_count": 10,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "# Display sample\n",
- "built_dataset.samples[0].draw(img_type=\"svg\")"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 11,
"id": "77a350e4",
"metadata": {},
"outputs": [
@@ -4013,318 +211,318 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 0 Loss: 6.083160490000402 Mean loss: 0.06083160490000403\n",
- "Epoch 1 Loss: 2.2840650084958822 Mean loss: 0.022840650084958822\n",
- "Epoch 2 Loss: 1.4858856718724218 Mean loss: 0.014858856718724217\n",
- "Epoch 3 Loss: 1.1878093438444064 Mean loss: 0.011878093438444063\n",
- "Epoch 4 Loss: 1.0768520829935488 Mean loss: 0.010768520829935489\n",
- "Epoch 5 Loss: 1.0123350387217116 Mean loss: 0.010123350387217116\n",
- "Epoch 6 Loss: 0.9656553714956269 Mean loss: 0.009656553714956268\n",
- "Epoch 7 Loss: 0.9324729977460346 Mean loss: 0.009324729977460346\n",
- "Epoch 8 Loss: 0.9022516771087317 Mean loss: 0.009022516771087317\n",
- "Epoch 9 Loss: 0.8790322979991856 Mean loss: 0.008790322979991856\n",
- "Epoch 10 Loss: 0.8534107807542335 Mean loss: 0.008534107807542334\n",
- "Epoch 11 Loss: 0.8324739065199404 Mean loss: 0.008324739065199404\n",
- "Epoch 12 Loss: 0.807513596480301 Mean loss: 0.008075135964803009\n",
- "Epoch 13 Loss: 0.7868600054668282 Mean loss: 0.007868600054668282\n",
- "Epoch 14 Loss: 0.7617469762882513 Mean loss: 0.007617469762882512\n",
- "Epoch 15 Loss: 0.7385103699472664 Mean loss: 0.0073851036994726635\n",
- "Epoch 16 Loss: 0.7092846216249051 Mean loss: 0.0070928462162490515\n",
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- "Epoch 18 Loss: 0.6464659471068225 Mean loss: 0.0064646594710682246\n",
- "Epoch 19 Loss: 0.6116479375864817 Mean loss: 0.006116479375864817\n",
- "Epoch 20 Loss: 0.5738761583275848 Mean loss: 0.005738761583275848\n",
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- "Epoch 32 Loss: 0.32543222524656923 Mean loss: 0.0032543222524656925\n",
- "Epoch 33 Loss: 0.3160366080328809 Mean loss: 0.003160366080328809\n",
- "Epoch 34 Loss: 0.3079445370904387 Mean loss: 0.0030794453709043867\n",
- "Epoch 35 Loss: 0.30088264406091886 Mean loss: 0.0030088264406091885\n",
- "Epoch 36 Loss: 0.2945482716354868 Mean loss: 0.002945482716354868\n",
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- "Epoch 39 Loss: 0.2788925951147424 Mean loss: 0.002788925951147424\n",
- "Epoch 40 Loss: 0.2748177983640656 Mean loss: 0.002748177983640656\n",
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- "Epoch 46 Loss: 0.25620322431117626 Mean loss: 0.0025620322431117626\n",
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- "Epoch 53 Loss: 0.24033816531522745 Mean loss: 0.0024033816531522745\n",
- "Epoch 54 Loss: 0.2384912918492733 Mean loss: 0.002384912918492733\n",
- "Epoch 55 Loss: 0.23671779926293116 Mean loss: 0.0023671779926293115\n",
- "Epoch 56 Loss: 0.23500316361053725 Mean loss: 0.0023500316361053726\n",
- "Epoch 57 Loss: 0.23333313790789803 Mean loss: 0.00233333137907898\n",
- "Epoch 58 Loss: 0.23169491912773862 Mean loss: 0.0023169491912773863\n",
- "Epoch 59 Loss: 0.2300783620904086 Mean loss: 0.002300783620904086\n",
- "Epoch 60 Loss: 0.22847710697762427 Mean loss: 0.0022847710697762426\n",
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- "Epoch 71 Loss: 0.21334944095874855 Mean loss: 0.0021334944095874856\n",
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- "Epoch 81 Loss: 0.20574144958590843 Mean loss: 0.0020574144958590843\n",
- "Epoch 82 Loss: 0.20519517607491758 Mean loss: 0.0020519517607491757\n",
- "Epoch 83 Loss: 0.204670684603382 Mean loss: 0.00204670684603382\n",
- "Epoch 84 Loss: 0.2041636662069527 Mean loss: 0.002041636662069527\n",
- "Epoch 85 Loss: 0.20366992626157315 Mean loss: 0.0020366992626157316\n",
- "Epoch 86 Loss: 0.20318541338629365 Mean loss: 0.0020318541338629364\n",
- "Epoch 87 Loss: 0.2027062307098171 Mean loss: 0.002027062307098171\n",
- "Epoch 88 Loss: 0.20222862818392587 Mean loss: 0.002022286281839259\n",
- "Epoch 89 Loss: 0.20174897644495168 Mean loss: 0.0020174897644495166\n",
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- "Epoch 91 Loss: 0.20076933836761576 Mean loss: 0.0020076933836761577\n",
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- "Epoch 103 Loss: 0.19249113081415486 Mean loss: 0.0019249113081415486\n",
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- "Epoch 106 Loss: 0.18893570169672097 Mean loss: 0.0018893570169672097\n",
- "Epoch 107 Loss: 0.18816446384864324 Mean loss: 0.0018816446384864324\n",
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- "Epoch 110 Loss: 0.19598815927830862 Mean loss: 0.001959881592783086\n",
- "Epoch 111 Loss: 0.19019711408727544 Mean loss: 0.0019019711408727543\n",
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- "Epoch 115 Loss: 0.17754927472814208 Mean loss: 0.0017754927472814208\n",
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- "Epoch 124 Loss: 0.15362313662330648 Mean loss: 0.0015362313662330648\n",
- "Epoch 125 Loss: 0.1507173054258388 Mean loss: 0.001507173054258388\n"
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+ "Epoch 62 Loss: 0.24015198612730096 Mean loss: 0.0024015198612730095\n",
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+ "Epoch 64 Loss: 0.23272635130473782 Mean loss: 0.002327263513047378\n",
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+ "Epoch 67 Loss: 0.22527972711373448 Mean loss: 0.0022527972711373447\n",
+ "Epoch 68 Loss: 0.22353749966425981 Mean loss: 0.0022353749966425984\n",
+ "Epoch 69 Loss: 0.22200551402122554 Mean loss: 0.0022200551402122553\n",
+ "Epoch 70 Loss: 0.2206242104845903 Mean loss: 0.002206242104845903\n",
+ "Epoch 71 Loss: 0.21935768770290523 Mean loss: 0.0021935768770290523\n",
+ "Epoch 72 Loss: 0.21818299290192464 Mean loss: 0.0021818299290192462\n",
+ "Epoch 73 Loss: 0.2170832747880538 Mean loss: 0.002170832747880538\n",
+ "Epoch 74 Loss: 0.21604487825180313 Mean loss: 0.0021604487825180314\n",
+ "Epoch 75 Loss: 0.21505641862342847 Mean loss: 0.0021505641862342847\n",
+ "Epoch 76 Loss: 0.2141084583896326 Mean loss: 0.002141084583896326\n",
+ "Epoch 77 Loss: 0.21319325515469714 Mean loss: 0.0021319325515469713\n",
+ "Epoch 78 Loss: 0.2123044903394485 Mean loss: 0.0021230449033944852\n",
+ "Epoch 79 Loss: 0.21143701857387207 Mean loss: 0.002114370185738721\n",
+ "Epoch 80 Loss: 0.21058667971229067 Mean loss: 0.002105866797122907\n",
+ "Epoch 81 Loss: 0.2097501846081654 Mean loss: 0.0020975018460816543\n",
+ "Epoch 82 Loss: 0.20892505656191063 Mean loss: 0.002089250565619106\n",
+ "Epoch 83 Loss: 0.2081095940721001 Mean loss: 0.002081095940721001\n",
+ "Epoch 84 Loss: 0.20730281999808942 Mean loss: 0.002073028199980894\n",
+ "Epoch 85 Loss: 0.2065043945897857 Mean loss: 0.002065043945897857\n",
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+ "Epoch 87 Loss: 0.20493362729760697 Mean loss: 0.00204933627297607\n",
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+ "Epoch 112 Loss: 0.18926794561879703 Mean loss: 0.0018926794561879704\n",
+ "Epoch 113 Loss: 0.18879876157425932 Mean loss: 0.0018879876157425932\n",
+ "Epoch 114 Loss: 0.18834279669555534 Mean loss: 0.0018834279669555534\n",
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+ "Epoch 116 Loss: 0.1874707888983872 Mean loss: 0.001874707888983872\n",
+ "Epoch 117 Loss: 0.1870543087323777 Mean loss: 0.0018705430873237768\n",
+ "Epoch 118 Loss: 0.18664996120448468 Mean loss: 0.0018664996120448469\n",
+ "Epoch 119 Loss: 0.18625644233648053 Mean loss: 0.0018625644233648054\n",
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+ "Epoch 121 Loss: 0.18549299196910551 Mean loss: 0.001854929919691055\n",
+ "Epoch 122 Loss: 0.1851162337331781 Mean loss: 0.001851162337331781\n",
+ "Epoch 123 Loss: 0.18473628953972737 Mean loss: 0.0018473628953972736\n",
+ "Epoch 124 Loss: 0.18434658486947458 Mean loss: 0.0018434658486947459\n",
+ "Epoch 125 Loss: 0.1839390466178675 Mean loss: 0.001839390466178675\n",
+ "Epoch 126 Loss: 0.18350406735446725 Mean loss: 0.0018350406735446725\n",
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+ "Epoch 128 Loss: 0.1825061592355457 Mean loss: 0.001825061592355457\n",
+ "Epoch 129 Loss: 0.1819175022152493 Mean loss: 0.001819175022152493\n",
+ "Epoch 130 Loss: 0.1812508170923714 Mean loss: 0.001812508170923714\n",
+ "Epoch 131 Loss: 0.1804928184945482 Mean loss: 0.001804928184945482\n",
+ "Epoch 132 Loss: 0.179632380834296 Mean loss: 0.0017963238083429601\n",
+ "Epoch 133 Loss: 0.17866366499831146 Mean loss: 0.0017866366499831145\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Epoch 126 Loss: 0.14895697766636043 Mean loss: 0.0014895697766636044\n",
- "Epoch 127 Loss: 0.14882017999683764 Mean loss: 0.0014882017999683765\n",
- "Epoch 128 Loss: 0.15011007733618287 Mean loss: 0.0015011007733618286\n",
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- "Epoch 131 Loss: 0.14376499782897112 Mean loss: 0.0014376499782897112\n",
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- "Epoch 133 Loss: 0.15047429676666596 Mean loss: 0.0015047429676666596\n",
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- "Epoch 201 Loss: 0.11358885362828214 Mean loss: 0.0011358885362828214\n",
- "Epoch 202 Loss: 0.10063435613182822 Mean loss: 0.0010063435613182823\n",
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- "Epoch 204 Loss: 0.1036726490302544 Mean loss: 0.001036726490302544\n",
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- "Epoch 207 Loss: 0.09836754939826567 Mean loss: 0.0009836754939826567\n",
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- "Epoch 209 Loss: 0.1009500571614545 Mean loss: 0.001009500571614545\n",
- "Epoch 210 Loss: 0.1213533513147023 Mean loss: 0.001213533513147023\n",
- "Epoch 211 Loss: 0.1001639038618272 Mean loss: 0.0010016390386182721\n",
- "Epoch 212 Loss: 0.11246077738658453 Mean loss: 0.0011246077738658452\n",
- "Epoch 213 Loss: 0.10676459906063875 Mean loss: 0.0010676459906063874\n",
- "Epoch 214 Loss: 0.11501875218568439 Mean loss: 0.0011501875218568438\n",
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- "Epoch 217 Loss: 0.10156188681893441 Mean loss: 0.001015618868189344\n",
- "Epoch 218 Loss: 0.09422111132922581 Mean loss: 0.000942211113292258\n",
- "Epoch 219 Loss: 0.09789595305217748 Mean loss: 0.0009789595305217747\n",
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- "Epoch 225 Loss: 0.10901518415386335 Mean loss: 0.0010901518415386336\n",
- "Epoch 226 Loss: 0.10223555076419197 Mean loss: 0.0010223555076419198\n",
- "Epoch 227 Loss: 0.1091480621155891 Mean loss: 0.001091480621155891\n",
- "Epoch 228 Loss: 0.1003731089883593 Mean loss: 0.001003731089883593\n",
- "Epoch 229 Loss: 0.10825074000352475 Mean loss: 0.0010825074000352475\n",
- "Epoch 230 Loss: 0.09794348918057849 Mean loss: 0.000979434891805785\n",
- "Epoch 231 Loss: 0.10449357070418688 Mean loss: 0.001044935707041869\n",
- "Epoch 232 Loss: 0.09778684574190152 Mean loss: 0.0009778684574190152\n",
- "Epoch 233 Loss: 0.10646128196840761 Mean loss: 0.0010646128196840762\n",
- "Epoch 234 Loss: 0.10197685273767754 Mean loss: 0.0010197685273767754\n",
- "Epoch 235 Loss: 0.09574424243710178 Mean loss: 0.0009574424243710178\n",
- "Epoch 236 Loss: 0.09799143209907854 Mean loss: 0.0009799143209907853\n",
- "Epoch 237 Loss: 0.09739274446061073 Mean loss: 0.0009739274446061073\n",
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- "Epoch 240 Loss: 0.0954098455837166 Mean loss: 0.000954098455837166\n",
- "Epoch 241 Loss: 0.09944375177783467 Mean loss: 0.0009944375177783466\n",
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- "Epoch 250 Loss: 0.09171480532400897 Mean loss: 0.0009171480532400896\n",
- "Epoch 251 Loss: 0.0946808402910875 Mean loss: 0.0009468084029108751\n",
- "Epoch 252 Loss: 0.09149382783573408 Mean loss: 0.0009149382783573408\n",
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]
},
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"text": [
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+ "Epoch 299 Loss: 0.10966639497011618 Mean loss: 0.0010966639497011618\n"
]
}
],
@@ -4347,23 +545,23 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 11,
"id": "2248561a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
- "[]"
+ "[]"
]
},
- "execution_count": 12,
+ "execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
+ "image/png": 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\n",
"text/plain": [
""
]
@@ -4385,7 +583,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 12,
"id": "1e2bf200",
"metadata": {},
"outputs": [],
@@ -4404,13 +602,13 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 13,
"id": "e4e0025d",
"metadata": {},
"outputs": [
{
"data": {
- "image/png": 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\n",
+ "image/png": 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unpy4ZVp7o8zzGIUyBom7y2YmajISlI1R3Lv6YjzwZjNrK8zqF4Z5lOlLq4t8i8pAebD36BTt0OKu0WhGxNTXRpepEI/DisNqyrm4h/oCWEUKi8vX3+bJ1By1upS1PQGklLT1Rql1GII6yC0jhMDi9KqdMYZD7usIkUpLZnvTo1vtADYXLqHG0BXS4q7RaKYYR6SdPmsxQgiKPXa6+uKGuPtz0n9XV6e6j6egv82bQ7dMMJYkHE9RYzf6cRUNOW7PhDCO0XJv6Fb95YkI2L2jX2B14kCJeiZ6Z7LR4q7RaAYoKlKbQV6yk5izVB3y2Onoi4EjL2eWu79bFepxegfE3WO3qFBIqxuSEUiP30d9sFf5xMusGXEfGrLo8BjuoPjYYt0busOYBDjT4SzF3YVdGpZ739ERdx3nrtFoBnjggf63vZEExbKHPq+KDS/x2Gj2R6Eid26ZXn8XoJKGZeiPlrENKtiRjYAOQ6sh7iUmw73jHCrubq+xP0bLvbE7TEW+U8XIO7Jwy1hdWMM9gLbcNRrNFNPc1o5XRLD5KgEMt0zG5x6AdHrC9wgZScPyfcX9bR67hVA8RdqaKbU3ftdMW0CJu08Y4n2I5e71qV8M8dDYvqwausPUFrqUrz5Lt4wpFcVqFnSHclOUezS0uGs0mgG+9CW1AZ1tBwBwF1cDUOSx0RWKk7bnARImsLIzQzSorFl3/tAQRYCYcKiGCUyqZtwynnRARd9Y7EOO5/vUfUPGOLJlQNyDWU6ouhGJMAUuW38is8lGu2U0Gs0Ar77a/zbQ3gSAr2wWoCz3VFoSNnnwgHLNOPKH6SR74n1KVIVjaJw7QAS7ikKfgOXeGohS6LZhifYcZrUDlPjySEgzkaCfgmGuH45IPEVHMEZNoRP2ZCnuVifEwxS6bXRrt4xGo5lKIt1K3D3Fqq5ppgB0UBrukhz43ZNhv3ozyG/tdajMkGEylvv4xf1gb5TyPIfKi+M8XNxL85z04SSeGUcWNPao8dQUOAzLPbsJVRKRo2q5a3HXaDTDkuo1Sh97ywHllgHoThurOnMxqRoLkMLcnzkRGMgMKTPVmMaftbG1N0p5vgMi3cNa7mV5dvqkk0Q4exdTQ5cS99leCcisJ1RJhCl0WbXlrtFophZLqI2ocPRbpiWG5d6ZzJ3lbooHiJk9KhWkQcYt09dfam8ClnvAEPdw12Ex7gD5Tish4RxTTvdMjHut2wjRzHJCFZmixCX6LXcpJdHE5KUi0OKu0WgGqK6G6mrSaYkz1kHIVtIvvBm3THvcmJScoLjHk2kcqT7i1qHi6B1UJBsYt1smlkzRFYobbpmeYd0yQgjiZhdiDKGQDd1h3DYzPpORBCxbtwxQ4kzjjyRIpSW9kQSLv/YP/vhqfdb3Hgt6QlWj0Qxw990AdASiFNNDwlXWfyjfacVsErTlSNz9kTheIqRsQ8UxY7n3poz7jDO/THtALRqq8Joh1jusWwYgYfHgSWT/WRq7w9QUuhAZd5E9i0llI6d7iS2JlGoNQZPhuy/Nc2R977GgLXeNRnMYjd1hyuhB5JX3t5lMgiK3jZaImvCcqLj3hBLkiRDykGiTjM+9N2XcZ5zinlnAVG3PJA073C0DIG1ebKns79EfBhk1XDljsNwL7coN0x2KD7h3Cl0jXjYRtLhrNJoBPvUp+NSnaOwOUS66sfmqhhwu9thpD6VUzHh0bMm2DqU7pCx3cUg4pdumxL0nYYj7ON0ymQVMlTbjeucIwY52L/Z0dveQUg5dwGRcPyoZcbeqzJA94QFxr9HirtFoDqNtC9x+Fjz+xdz0t3kzbN5MZ0c7DpHAU1I95HCRx0ZnKJ6TzJA94Th5IoTZNVTczSah8svEAbNt3JZ7ZgFTsdlwn4zgljE783DLCJH46JObHcEYsWSa2iLXQMqCrKJlVISRz6JWp3aH4jR2hyly2/rdULlGi7tGM1PZeCf85hxo2QQHXs5p13F/CwDW/Moh7SUeO53BWE4yQ3aH4uQRxjYo3W+G/uRhNve4Lff9nSG8DguupPElNIJbxubKwyVitPceHnIZTaSo6xz4cjkw2Noeh+WeyemecctMltUOWtw1mpmJlPDk16DqBFh8KfS157b7QCbGvWJIe7HXTmdfDJkDyz0YCOARUWy+8sOOeTIFO6zjr6O68UA3q2sLEBGVv2a4aBkAh8cHQFd392HH/vvR7Vx820v9IYvbmtVnXlzuHbDcbVmIuzGh6jUPWO797p1JQou7RjMTCXdBLMA239lQugRCHRNKjXso5tBB9cY7VHiL3DZiyTQp28TT/iYC6h6WvGHE3W5RBTtsrnGJe284we6DfayZVQC9zSBM4Ckb9lyXkW64p6dzSHt7MMr9G5qIJFJsNUR9S3OAYo9NhVfGgkrYTVnIqGG529JRXDYzHcEYLf6oFneNRjOUVNd+AH66KUEHPpBpCHUe+aJsWLgQFi7EETV+CRwi7plY96jZM2FxTwfb1JthRLe/1N44i2RvbFBW+JrZheBvAG8lWGzDnuvNV+Le6/cPaf/9P+tJGJkvNzeqY1ube1lWlY8QQk0oZ5uK2PC5YyQP29bSSyottbhrNJqh+Jt2AbAnWcpvNxmWbV/bxDu+/Xa4/XZssW5iJudATnWDYq8S95BwT1jcRUgV6sBdctgxj31QTvcsV6hKKUmlJQBv1PdgMQlW1figtxF8NSNe5zYs977AgFsmGE1w92sHuHhZBVU+J5sa/UTiKfa0B1leZUwAxwLZTabCQHqFhEoetsX4JTAtfO5CCLMQYpMQ4lFjf44Q4nUhxF4hxF+EEDaj3W7s7zWOz56ksWs071j62vaSloKzT1rDG52GRRo8mJO+02mJK+knYvUddqzIre4VxK3EbQI53a0RQ9yHsdw9/aX23Fnnlvm3P27ko3dvBGBjfQ/HVeXjtJmV5e6rHfE6YVjfocBA2t8/r28kGE3y0TPnsarGx+YGP9tbA6QlLOsX9yyThsEQcS9w24gm1HOrLZoG4g7cAuwYtP894MdSyvlAD3CT0X4T0GO0/9g4T6PR5JBk5z7aKOAjZy+lomq2auzLgbjffDOBf/84BQRJ2A+PCy8xLHe/dClX0ASSejlinaQR4C4+7Fie04o/nECOwS2zoy3AU9sP8tT2g2xu8it/eyoJgRbIH9lyzwh0OOjvb9q7awtXFTWxvDqfVTU+mv0Rnt+lXFVDLPdsxd1iV37/RIRCl4rft5qF8t1PElmJuxCiGrgE+K2xL4BzgPuNU+4CrjTeX2HsYxw/1zhfo9HkCGvgAE2UUeq1k1diLDTKhVtm9246D7RSKAKkHIeHDha5bQgB3UlDlCbgmnEluolYfGC2Hnas0uckkkgRNzmydstkapN+7q9vEU+mOXF2AQSaQaaOaLlnBDoW8vc3nd/+O74T/jpEA6yq9QHw5zcaKXLbqMg3Pnu2hTpA5eexqoLfBcavn+oCF2bT5Eljtpb7rcDngcxvsCLAL6VMGvtNQGYpWxXQCGAc7zXOH4IQ4mYhxAYhxIaOjo7xjV6jeYeSF2mix16FySQoKfTRK12kAjkQd6Db6qRQBBHuw8XdYjZR5LbTnphYfplYMkVBuoeoffjwxOoCNQHZl7ZnVYkpHE8SjqdYVeOjN6LCDU+YVaj87ZCVuKeiQeLJNFJK7PEeHDIKW+5jWWU+ZpOgIxgbmEyFsU2ogppUTYQpdClxn0x/O2Qh7kKIS4F2KeXGXN5YSnm7lHKNlHJNScnhEyoajWYE4iF8qW4iHiVYlfkO2mUBMX9rTrrvtrgoJIjZM/zfZanXTltsYuLuDycoEX7ijuHvkRF3fzK7FaoZq/19a2tZO6eQhWUe5ULyN6gTshB3j4zQ2huhoy+GVxrupjd+h9NqUnHtDHLJgLLcx1KJKlOww7Dcawud2V87DrKx3E8FLhdC1AN/RrljbgN8QojMutlqoNl43wzUABjH84GuHI5Zo3lHk+qqU28K5wBQ4XPSIfNzZrn7bTZcIoY9bwRxz7PTFDUmcccp7t2hOCX0knaXDnu82qes2p6EBVJx5TsH6OuAW1dAy+Yh53f2qeRgxV4bv7vxRP70r+uMD2NY7vlD0ygMwWQmZXbiERGaeyI0dkfII0TKbIf2bdD0hoq6YdBkajqlflGMyXJ3QSLUPyk9mWGQkIW4Sym/JKWsllLOBq4DnpVSvh94DrjGOO0G4CHj/cPGPsbxZ6WUMqej1mjewfQYYZDO0vkAVOQ7aMeHKRerVFetIlyjBNfpG37RT6nXTkNoYpkhe/piFItexAgLi/KcFrx2C53xTGZIYzVo21vgPwC7nxhyfsZyL/bY8dgt/fH4+BvAU35YYezDsHvxEqapJ0JTT5h8ESI07xK1SGnD7zh9QQl2i4nVhv99TKkHMlidkIhQZIxtysX9CHwB+IwQYi/Kp36H0X4HUGS0fwbIUUYjjUYDEGjdDUBh9SLAEHdZgC3aodISTIRbbyWxZjkAFs/hUSwApV4HB0LGj/Zxinsg0INTxLHmDy/uQgiqCpzUx40Jy17DMdBzQL22bBpyfsZyzwhnP/4DR3bJGJjchRSIEE09YRq7QuQRxlk8C1ZeB2/dywUvXc3bF9VRakQLEVC5d0bMNDkcRsz+CbMK+NaVyzhn8fCfPVeMKR2ZlPJ54Hnj/X5g7TDnRIH35GBsGo1mGBId++mVLmqqVAyD12ElYC7Amo4aC2vG4AcehmRfZnHRCOKeZ6d3gkWyoz1KHO2+ihHPqS5wsbXDmNTtqYPyZUqsAVreVF9kxuRml1G6LuPy6Ke3EarWjDoe4Sqi1NLDEz0R3ESxihS4C+DEz0PhXMSW+7A/9SUoWwjzz4Mt96vQxnnnZP+hrU7oa8dsEnxg3azsrxsneoWqRjPDsPQeoJHyASsSSLoM3/VEXTMf+ADseku9HyGLYqnXThILKYtr3OKeNPLKuAorRzynusDJxqBP7XQb8wwZy73v4ID1jLLcvXYLDqt5oIN0Cnqbjrg6tR9nAcXmPpr8Ebq7jWfo8KncNif/B/zLk+AuhddvV/2+/ReYd+5h6RmOiDGherTQ4q7RzDA84Ua6bJWYBsdIZ0QmOMFJ1aYmzBhx5SOIe4lXxXknrF5Vvm4cpINKQIdLGpahusBJa8xO2lEA3SqXDv4DA9kdB7lmuvriFHkOsdqDbZBOZuWWwVVEvuyjuSdCn9/I0eP0DRy32GDNh2HPk/DmH1T8/KrrR+93MOPMkzNetLhrNDOJVJKi5EHC7qHWqD2TNjcHq1StlhgpzMpyHYbML4aY2Ttuy90UMqxjz/DRMjAQDhn11iq3DCjLfeGFYLIo14xBZ19sGH+7EQaZn424F+JO99LaGybeZ+SYOdS9dcKHwWSGxz+v6qYuumT0fgdjxLkfLbS4azQziFRfOxZSiENC+5yFaj8ZmFisexpwmSJErXkjprLNpCAImcafPMwa6SCFacQc66B87gC9jmrllokFIdINJQtVmuPmAXHv6otTfKjlns0CpgyuIswyhVtGBmLcD/1yy6uAJZer0MxlV4F1jKkDbNoto9EcG/Q2wX03DBR1yEWX7UqwHAVDfdWFRSXEpJVQV/Nwl2VNwOzAZ+ojbhs5CsRhNZPvtKrkYeMUd0e8i4C54Ii50Kt8ynI/aK5Qz7JrrzrgmwWVq5VbxogO6godYrnHw7DnKeP8bHzu6kumQATJF8aiqcFumQynfFwVEDnhw6P3eSgZt8wEkq2NBS3uGs1ksecp2P73w8L2JkKwowkAe8HQwtWVPhcd5BP3T8zn3nXiKRSK4LB5ZQZT6rXjTzvHLe6eRBd91iPfw+ey4raZOSBLVX6Y+n+qAwWzoGq1KvPXU0cqLekOxSnORMrsfwF+uhq23AfHf2Agl/qRMOYXCgiShyHuw7mlqk6Ar7RA5aqsPucQMuNIRsd+7TiYnMqsGs07HCklIjMJ2Dsxa3ow4W4l7t5DCldX+By0Sx/VE5xQ7f7oxyn83Z+RriOH6pXm2enqckJqfOKen+ohZj9ynLcQguoCF7vixkrZ/c+rV99s5XMHeOjjJB3FnMgKir3HqbYX/heEGT78OMw6JbsBGcWzC0x9+EwRJAKRbVKwbLEaufET4f6ye5OJttw1mhzz+JZWTvr2MyQ6DXEPNOWs72SvEu+CsqHiXpnvpEP6MIfGEQo5aOFTV1+MQhHANEJemQylXgftcYey3EdZOJVOS3a1DbimookURfhJOEfPKVVd4OTtsOEiOvBPsHmUEJcuhTlnQl871n1P8BHLYxS57crl0boZFl2UvbBDv+U+2xGl0h5FOPKzK583FgZVYzoaaHHXaHLM5kY/7cEY4Ta1kjSXlrsMttElvZTkD1327rSZaTeX4Y00jc2ne+el8ORX+3e7f3gbPvpGzCuTodRrpy1uP3JO93A37HyMp3cc5IJbX+SNfQfh5R9z4MmfUUTvERcwZagqcLKl1wEWhxJF3yy1cMls5f5lv6D9hpfpqL2E1abdFLmt0LVHjadqdfbPAPpXmi7MS1DliA3vb58omdDSQfH5k4kWd40mx7T0RgGJI2iE4gVyJ+6WcDvdogCb5fA/3R7XbGwylv39UgloeBXeuEMJMRBKRjALiSN/5BBFgNI8Bz3pUVapPv8d+PP1NDWp57D++Ufg6W+w6I2vYxMpauYuGnWI1QVOeqNpUj7DTVSgXus7Q3zur2/x8+f20pq3nCIRpCLdOjC/UXn8qH0PweEDYeLqJU7WlJkmvMp3WKpOUK9NG3Lf9zBocddockyrP0IJfuzSmDjLoeXujHYQsAw/ERnxqiyRdO3JrjN/g1rkk4zAprtVHw61MMoyqlvGTuBIKQjSKdiucgmmDm4HoKderXy9Kvlt7ljwC6yrPzDqECuNiJmI2whnNER+fZ36Mnpq+0H2O5YBUOx/S4m71QXFC0ftewgmEzgLsMf9WGK9I8b4TwhvmQrLbFqf+76HQYu7RpNjWnujrPP5Aehz1+bU5+5JdhG2D5/zRRapLJF07s2qL2mEFnZJL+F//ordrX7eKDQWQw1TqGMwpV47AY4g7g2v9S+osnfvotBtY65spFfksSk5ixPPvGT0TI1ARb4S9x67ER1kWO6vG+Le0hvl4WYvQenE1bZRiXvFSrXYaKy4iiDcpaJwJsMtA1B9IjS+MTl9H4IWd40mh6TSkrZAlIsq1WKVzeZlSvxi46812k86TUG6h4RzeJeJt7iaoHSSbN+VVXexg2pO4EfJ9+AKN3Pnnb+mXPrVwRFSD2QozXMQPJLlvu1vYHGCPY+Cvn2cPK+I4x1t7ExVsqDUO7ToxRGo9KmFQm0Wwz+fsdzruzhxdgEmAS/s7WK7aSGi4VVofVvFwI8HZ6FyT0X8k2O5A1SvhWCLitufZLS4azQ5pD0YJZWW1NBGCjOP+g1fcQ787qlQFxZSpD3D52Op8DnZJyuIH8xO3KMH99ArXRSd8RFaZSHXR+7lEy5jmb9r+F8HGY5ouWdcMgvOR5YdR2W8nmqfg3k0sjtdzdUnVJNtWeVSrwOzSbDDslSJb8UKWvyqoMaFyypYM6sQKWGvfSl07FAuprH62zO4CiHSoz7PZFnuNSeq16bJt961uGs0OaTFr/zspYkWYp5q9icMkcyBpebvUBOTlvzho0wq8p3sl5WYu7Nzy9C5lzpZzsnzy/Gf+S2Wm+qodbyqjo1iubvtFtI2w/o+VNwbXoVQOxx3FRHfQhaIRha5gtiSfcxZeuKY0t2aTYIyr53NyVr4Qh3kV/NGvXLJnDSnkPOXqlj5Zs/ygYsmIu6BZkjFJs9yL1uuIn+OgmtGi7tGk0Nae5U7Ji/aiKloLi2Z2vA5sNyD7aqPQ1MPZKj0OdifrsAebs2q7qi1t446WUFZnp0l57wfzvqyEmqbJ6u8Kb4C47MdKu67HlcCtvACOpxzyRNhloZVhMhpp5yGxz62tZMVPiet/oFVna/XdeOxW1hSkdcv7v7CFeqgPQ8K546p/36chuUOk2e5W2xQseqoTKpqcddocogSIYkjcAB76XyC1hIkIicRMxFjdaqnePh6oGV5DvZLw6rv2nfkzhJRXJFW6tPllOYZQn7m56GjBDqzk4XKonwi2IeIezieZOf2zbSYK8HmpsGiolxqWp9UJ5QsyarvwVTkO/q/NEFFyqyZXYDZJJhd7Ob6tTWctny+soqr14x/8dHgXyuTZbmDcs20vgXJ2OTdAy3uGk1OaemNUGULI2IBRNE8akt89JoKchIxk/CrjI++suHF3WE10+UwQgZHC4fsqUMgabFUDVjSQsC2angzO8u3tshFQLqQET8Auw8GueynL5PoaWJnOI+DgSg7k2qsrqaXwF0yahTOcFT5nLT0RpFS0tUXY297H2vnDGST/M67V3Dx8gq4/k9wxS/G3H8/rkEZKicjzj1D9VqVWbL17cm7B1rcNZqc0uqPstpj/LQvmMP8Ug8tsnD8lnvbVvjBIujcQzrYRkC6KCnwjXh6wjeHNGL0cEgjDDLoHi4dbnaTnTWFLnqli1if+rzfeHgbPeEE8+29tMlCXtvfxZ6QnS7yETIFJYuz6vdQKvIdxJNpukJxNjf6ATihdpislb5alZZ3vAy23CfLLQNQcxKs+sCk55fR4q7R5JDW3ghLHUYln8K5zC/1cCBZQHq84r7vGehrg413Ygm30ykKsVtGjuEu8vloFyWjW+6G2yaeN07/NFBb6CKAm1jIj5SSbS0BLl1agDPRQ5elhFf3ddHYHaHZOltdUDp2lwwonzuoL863mnoxCVhePQmW9eDc8pPplvGWwZU/h7LjJu8eaHHXaHJKsz/KInObykpYMIt5JW5aZREy0Dxqgq1hySynf/s+XNE2ei0jF7cAqMx3sE9WQOdo4r6XbvLx+o7c35GoLVRumVTYT1sgSm8kwep8lRTLXTyLV/d30eQP0+Oepy4Yp7hXGguZWnojvN3kZ0GpF5dtEhLaDrHcR85nP1PQ4q7R5IhYMkVnX4xZqQNQNB8sdsMtU4Q5ERpf7vPmN5VFGWpnbmwnYduR0wJU+JzsTpYju/Yc8ctEdu9jvyynLO+QqJhLL1VbFlT5nARwYYr1sqM1AMBit8r+WF47nwNdYZp6IkQLjVQA45hMBZXOGFRah7ebelkxGVY7HD2f+1FCi7tGkyMO9qroh9Lo/n4rdVaRm3YxznDIcLcqCL3u3/stydHS5FbkO6iX5Yh4CEIdw5+UTiM797A/Vd5fD7Wfz31ObVlgs5hI2fKwJILsaFWiPsvqB2DhAuVflxIC866Ad/0/qFmbVb+HUuS2YbOYeONAD92h+OSJu8MHCBVOOZ70BdMMLe4aTY5o6Y3gJIon3KTyjQNWswmZZ+RFGavfPeOSqTkJuewaAKTnyAUuKvKdqnIRqLqjhxLthT9fjynUwXq5+HDLfYyYnD6cqSA7WwNU+Zw4wyqiZ+7c+fhcVgDKS0tUebpxCqYQgsp8B8/tVLnqV1T7JjTmETFblMU+mf72o4gWd40mR7T2RpgvWhDIIf5lV7ERkTJGyz2VKQBdsZKehdeSloJ0wZEnQCvyHTRmxL2nfujBRATuuAD2Ps2eE7/J/akzDhf3s85SW5bY3AWYSVPf2s6SCq/6jM5CTHY3JxnhijUFE48Kqch3Eo6nsJoFiyu8o18wXlxF4Jz5LhnQ4q7R5IwWf5RFJlXAOmO5A5SU15KWglRv9kUa/rG1jWee+Qd+Zy1+6eKjz6Y4I/5jfKuO7A8vz3fQRKlaONUz1HKXrW9Dxw6Sl/yEzWVXA4KyvNEzMx4JZ54S8O6uDhaX56lfJ/nql8oVq6pYUOrpT9s7ETJ+9yUVeUeMFpoweZUwQu6emYauoarR5IgWf4Tl1hYw26FwTn/73HIfHeTj7DhAtlU532zo4Uaxnxf6FvOl7z5LIpXmB+99FyfMPnJCL6vZRL7Hg58SCg5xy2x56w1WAH9pr8LvMOYHvBNzy3h9aj7BLUPKot7fDPk1AFy8vEItLsoBmYiZSfO3Z7ji5yCODZv32PgUGs00oNkfYZm1GUoWDfEvzy/10CYLifVk75bpbmukUnRTu+xUagpc3PnhtVyxqiqrayt8TtpE+RC3TDCaYPOmN4hJC7/dkqStN0qew4LTNjEruKBQTfDmEVKWe2DAcs8lGct90vztGQpmga9mcu9xlNCWu0aTI5p6IsxNN0DpeUPa5xS7eVUWUN3XlnVfzs4tABy/7hyeGEuhZ1Sse72/lCU9W/rbfvjkbk5LNOB311LXHSO4tW3Ck6kAxcXKv19kiTA7D5V4K2/4xGYTYWW1jzyHhZPnjj19wTuVUS13IYRDCLFeCPGWEGKbEOKbRvscIcTrQoi9Qoi/CCFsRrvd2N9rHJ89yZ9Bo5lypJQEetopSHUetljH67Dit5bgjGQn7lJKyvu2kcYE5SvGPJaKfCe7YsWqElI8xP6OPv7waj2rXB0Uz15GgctKZ19seHG/9lq1ZUl+gXITLcxPY+lTkTLkDZ/7ZiIsq8rn7W9cQE3h5C7ZP5bIxi0TA86RUq4EVgEXCiHWAd8DfiylnA/0ADcZ598E9BjtPzbO02imBW/Ud9MTiue8365QnNqkURB70GRqhqS7HFe6L6tUvO3BGMvlbvye+WD3jHkss4pc7EsavvmeA2w80INFJiiKt2AuXcTVq5X4lg43mfof/6G2LBFGDpYTy80DOesnwS2jGTujirtUZGqEWY1NAucA9xvtdwFXGu+vMPYxjp8rsi27otFMIrFkivf/5nU+9qc3keNJBXAEmnoiLDIZ4jbMMntzRvACraP2Vd8RZKVpH9Gy8RWdmF/q4YA04uF76tjb0cc8c4dK3lW8kOvWqtDMivxhLPdwWG3ZYldTxGfU2AZCPfO0uE8HsppQFUKYhRCbgXbgKWAf4JdSJo1TmoDMv2gV0AhgHO8FDnOUCSFuFkJsEEJs6OgYYSWdRpNDGrvDxFNpXtnXxd83Tzy/+mCaeyIsFI2krB7IP9wt4SpWk3R9nQ2j9tXduIN8EcY+68RxjWWIuHfXsa+9j3X5RjKz4gXML/Xw6w+ewAfXzT784osvVlu2WGyqVmrUDwEj1HMSfO6asZOVuEspU1LKVUA1sBYYX+7OoX3eLqVcI6VcU1Jy5CXVGk0uqOtUFmmxx863Ht1BbziRs76besIsMjUhS5eovOiHUFA+G4CulvpR+5JGCbb8BWObSM1Q6rWTtucTMXuU5d7exyqnYUAVLQDgguPKKR/Och8PjnxVfKJxvcrZbplY7LwmN4wpFFJK6QeeA04GfEKITLRNNZAxhZqBGgDjeD7QlYvBajQToa5TeRd/ev3xzI9u4d7Hn8lZ303dStwt5cOnca2oUStL+zoOjNqXp3MzIZxYysZnQwkhmFfqpc1UTqqrjobuMAtMLcpdMg4f/qiUL4P6l2DvU1AwZ/TzNUeFbKJlSoQQPuO9Ezgf2IES+WuM024AHjLeP2zsYxx/Vubawak59jm4De59H4RyZxfUdYYodNs4uTjCH63f4ZydX89Z34GuZgoIDjuZClBdVkxAuohnEete2beNevuiCSWvmlfiYV+yhFTXftISKhJNULxg3P0dkff9FT61FT70EFz9m8m5h2bMZGO5VwDPCSHeBt4AnpJSPgp8AfiMEGIvyqd+h3H+HUCR0f4Z4Iu5H7bmmMbfAHdfDbv+D1o35azbus4Qc4rd8Oy3sBFnYWIX8uD2nPTt7N6p3oyQs9xuMdNpKsYUPPKEqoyHmJWqp9M39hDIwcwv9bAnUYw50IiZFHmhOiheOKE+R8RkUgt/5p4FBbMn5x6aMTPqIiYp5dvAYdP2Usr9KP/7oe1R4D05GZ3mnUe4Wwl7yJgADPfkrOu6zhDXVXfDW39mT9WVzGp6hOTrd+K6/H8n1K+UEl/fPmUqjWC5A4TsJTiiB4c91vLwf+M+8CzW4y7FRYrYOCNlMswv9fBIehZmmeQh29cwJ/qyE/cbb5zQfTXTB51+QDO9ePH7qgTcNb9T+5HunHQbiiU5GIhxTfdvwFlA96nf4On0CVi3/RWS44x7f/BmeOa/6QknmJNuIGIrBPfIuV8S7goKkp2HhWGur+smtvFP5HdtwvXi/wDgmH3S+MZkoMR9HV9LfoRisxFbX7Zs9AtvvFEL/DGCTj+gmT6Eu2HjXbD8PbDICMcL58bnXt8VIo8QNf71cNaXmFNTwS9TZ3FxbD3segyOu3JsHaYSsO3vYLHTPO9mFpkaCfsWcqT8h5b8Soo6/bT3hijzqYnNrc29fObOZ3lZtHK3/Tpa+9IUiiBnVg9XuDp7agqcWM0W/pg8h5a57+aOCxxQdcLoF3ZmQiaPnKBMM/3Rlrtm+rD+N5AIwam3DBROCOfGcq/rDLFQGOl4K1dT4rHzlm01fmspvPXnsXfYuRtSMYgFSOx8ggWiadQaoc7iWsxC0tRQ39/2tYe2staqilWfe/F7+KP1Gr6V+iDVE8yBbjGb1PwCMKe0IDthB7jmGrVpZjxa3DXTg3gIXv8VLLwQygy/tbMwZ26Z+s4QizO51suWqnDBsnw2m1dA6+axd9j6tno126ne9mvcIoazavkRLymomAVAZ4tKxSulZM/BPq4oagZhpmLJydxx44l88cLFOKwTz1k+r9RtvE5C+KNm2qPFXTM92PwniHTzWuWHuPDWFwnFkqoqTo4s9/2dIVbbW8Ce3788fkGZh82xMgi2jr14detbYHUhV72f0uA2AFzVRxb3wjIl7t76f8Dz36O3biN9sSQL4jtUrLjNzYmzC/m3M+eN/QMOw/wSJerztbi/I9Hirpke7HiEROFCbn7ews62IDvbAqoafY4s97rOEEstTepXgbGCdH6pl60xo+pO556s+4omUnTtXc9e02z+ZdOgsnclR150ZPLVkEZwStvd8Py3sT/yMSwk1ZdD9fiKRx+JsxaXsrwqn6UV2ZYI0RxLaHHXTD2xIPLAKzweX0kkkQJgb3ufcsvkKBSyvqOPWckDQ0IVF5R62CeNPCgdu7LqR0rJu3/+MrbO7WxKzKJ0yWn0OSpIeqvAMYqIugr5aeX3+JTz/8FlP8HZs5NPWh7EkgxBTe7FfXVtAY984jTcdh038U5E/6trpp79zyPSCe7pWsw3rjyObz6yXYl7jix3fziOM9KG09E34M9HuWUaZCkpYcXcmZ24dwRjhA/uwWuPcPUlF/GeE46H3bdBLJjV9bHaM3m0fj8/WHE+vc/cysdDxsLu6vElCcs5//7vUz0CTY7Qlrtm6tnzJGHhoqdoFe9bW8vcYjf7OkLKco/3jT8O3WBnW3BQ4eqB3C/leQ6cdjud9mro2J3dUNv7OE6o/DCmylWqceEFsDy7CJM5xW6SaUlTb5xHC2/AJKRKtjVdVna+971q08x4tLhrphYpkXue4sX0ck5ZWGEkvfIYlnuBOmeC1vv2lgCLM2GQg8IVhRDML/VQRxVkY7m3vk1dcxvLTHVIkxVKjhz6OBxzS1QES11niP9LrGGPdRHMO3fYTJJTQmOj2jQzHi3umqnl4FZEsJVnkis5bb5aODO/xENjT5i4zafOmWDEzI7WACtsTZBfA0bloAyLy728FS1D9tRDIjpyJ5174NdncNnLV3KRZYP6krDYxjyWOcUqcmV/Z4gDPVF+O/8XcOUvxtzPpPHBD6pNM+PR4q6ZWvY8CcBLchUnzS0EVFy2lNAaNxbyTHCV6vbWAMdZmofN+7K0Mo9t8QqETEP3vpE72fogAL3SxWxaERUrxzWWApeVfKeVHa0BDgZiVBXnTyj7o0YzElrcNVOHlLDlfnZbFlJVMwevwwoMxGfXhY2iDxNwyyRSaeoO+qlKNg6ZTM2wpCKPvdlEzGx7EGpP5pr097iv+itwxn+OazxCCOaWuHlxtyqeMatIF3zWTA5a3DVTR+N6aN/OnZHTOXX+QC6TuSVuhIA9QcPtMQG3zL6OPpak92CWSRjG2l5c7mWfrEQiVEqB4Ti4HTp20rfgMtrDaQKLroGCWeMe05xiN+3BGAC1hVrcNZODFnfN1LHx9yQtLh5KndLvbwdwWM3UFLjY5jcidcdquUd7YdM9kE6zozXAeeY3kSYLzDvnsFO9DivlRT66LOUji/u2B0GY2FWorl9Q5h3beA5hrpHzBWBWkfsIZ2o040fHuWuy5untB1lY5qV23z0qfG+smRQHE+mBbX9jY/6FyLiHVTW+IYfnl3rY2RlRxZfHarlvfQAe/TS4CtneMotrzZuQtacgHPnDnr6kPI899ZUUD+OWSSRTRDbch7v2VLYHVc7HBRNczp+ZVPXaLRS4rBPqK+d89rNTPQJNjtCWuyYr6jtD3PzHDfz26U3wxFfgjd+Or6NoL7RthVd+BskoP+w6hbMXl2KzDP2vOL/Uw/7OENJVqL4IxkL3fvW6/nY6G3ezQDRhWnTRiKcvrczjldhcOLhV5ZIfxLMvPEde+ACPpU9m78EgbpuZigkWls5ka6wtciGmSwhkhssuU5tmxqMtd01W3P6SqsVZ3PikSnXbN3xFoZFo641iNUHRHaeDXy0C6i5YyfrWav609vDc5fNK3MSTaRK2fGxjtdy7VdZF9j3LycKwjBddOOLpSyry+HLybD5t+zum138NF6vKTFJK6jb8A4Dv7q2Gjnbml3knLMizi5WffVpOpu4yfr0sWjS149BMGG25a0alPRjl/o1NmE2CtcGnVGMwe3GPxFOc/YPnufLbfwL/AbZXXwfvf4DPW7/E7CIX6+YWHXbNonKVpyUg8rL2uf9zbyf/fvdG0t31ULkaabZxrXwCv3suFM4d8bqllXl04KOu/ALYfE9/hsj1dd3M6ttM0FFJwlNFsz8yYZcMgMtm4ZIVFZy3pGzCfeWcf/s3tWlmPFrcNaNy5z/rSaTSfOpEF2vZTspRALFeSESyuv5Ad4hIIsXNc1S8+mf3reTbe6p4uiHNdWtrMZkOt4SXVHixmU10pNxZ+9yf2n6Qx7e2kujcD9Unstl7FgCJee864nWV+Q7ynVYec12p0h1sutv43HWcZN6Jc8EZfP0yFUa5aIKTqRl+/r7VvHt1dU760miGQ4u75ogEowkefG0Hly0t5CrLK5iEpHHudcbBtqz6qO8MA3CxrwFp81C5cDW3v7gfq1lwzQnDC5zdYmZJZR6NUUfWlnuzP0IhQezpMA812PjqwTOJmj2UnPz+I14nhGBJhZeneyuh9mR4/Vc0dwfZu+NNCglimXMqlyyv4PYPnsB719ZkNRaNZqrRPnfNEXngn9t4Wn4U9/44mKxsTC+gzbKU2aD87oVzRu3jQJcq0Ozr2oSoOoGfv+9EPnHvJmoLXRR77CNed3yNj/0bbEhzDyKdBtORbZHmngiX1MSgAx5usFGycC3WG5pgmF8Gh3JcZT53v3aA5PUfw/LXD7DvuT9yotirDs46FSEE7zqufNR+NJrpgrbcNSMSS6bY9OpTeEQUseI6xJLL+J3tfewIGhOB2VruXWGqXCnM7dug5iQcVjO/+dAavnbp4StGB7Oqxkd7yqNSA0T9o96npTfCCpey8pctW8Vt7z0ecxbCnrlXLJlmZ/5pULKEBbtv50zbTqSn/Ij+eo1muqItd82IPLSphbnR7UirCXHx98HuIXDH62zyt6sTsoyYaegOcW5eI/jTYypKsarGxwvSmMCM9Kj87iMQiiXxhxPUCrWs/9PXnAe27GPIM3H2m5oCLDv9M1Q8+K+UcgAx+6rpk7HxaPDVr071CDQ5QlvummFJpyW/enEfpzvqVMItuxLZhWVe3uw0qRWfY/C5n2Q1Ys+r12Q9hllFLpJ2n9oZZVK1xa8md8vTreApB9vYwgyrC5wUuW1sbvDjn3spB9KlmEnDrFPG1M+M57zz1KaZ8Whx1wzL28291HUEWc4exCBre2GZh0gCUs6SkS33VBL2Pg3pFLFkipbeCEuSO1SNUWdB1mMQQlBSVqF2hptU7W2Gupegu46WblUJqTDWnNU8wHD3WlXjY3NjD5ub+/hp6iqkMMGcs8bc14xm82a1aWY8Wtw1w7L7YJAFohlrsm9I8eZMXpWQrWhky33PE3D31fDC92jqieCQUar7toyrlFxljfJ3xxo2Dj0gJdzzHrjrUvjJKo77x3swkcYVahp3VaNVNT72dYR4aU8nD6TPJPTxrVA8f1x9zVg+9Sm1aWY8WtyPFVIJaNkMe55WwjdB9rX3sdZsRIsMstwzi3i6RcHIlnsmR8sL3yOy6T7usn1PfUksu3rM45g/fxFPpU7AvP6XEPEPHGh+E9q3wam3wBmfp7h3K++xvISprxUKxm65A6yq9QHw1w2NLCj14CmqGlc/Gs10QIv7scCep+G7tXD7mXDP1f0FMCbC3vY+TnfWgatoSLSI12GlyuekJZU3suXetQ9cxVC2nGWvfJrjxV76Lv0NzDt7zONYUe3jx8mrscQD8NqgikWb/qCSip3+OTjrS7Ta5/BFy70I5Lgt9xXVPgAC0eRhicw0mpnGqOIuhKgRQjwnhNguhNgmhLjFaC8UQjwlhNhjvBYY7UII8RMhxF4hxNtCiNWT/SHe8az/NTh8cPUdkF8LL35/7NZ7oFWtzDSu29fRx0p2K1fKIdEia2YXsLXXCeFO9YvhULr3QckiuPYuDrhX8Gk+i2f12K12gEK3jS7vIt7yngmv/kJNrMbDsOUBlZXSkQcmE/c5rqWAgLponOKe77Qyz6hxuqom+7kBjWY6ko3lngQ+K6VcCqwDPiaEWAp8EXhGSrkAeMbYB7gIWGBsNwO/zPmoNQPEQ7D/BVh6BSy/Bk67BZregLoXx9bP89+Bhz4GjeuJJlL4u9spTzQM6yd/19JyGhIq9wt97Yf31bUXiuZB0Tz+q/iH1BefMaFkW4vL8/iluFalBrj7auRLP4R4kC/WreAL978NwP3RE2m3GatdxzGhmiEj6itrhk8PrNHMFEYVdyllq5TyTeN9ENgBVAFXAHcZp90FXGm8vwL4g1S8BviEEBW5HrhGZS0MbH8aUjFic438Kas+oEIBX/pB9h3Fw/01Qll/O/VdIa41Paf2h3GlnLmohG5hxJz3HeKaifZCqAMK5wFwoCvMrMKJFaRYXOHl2a4iklf/DvwHEC/9gLp0GQ92zeaBN5vo7IvREkzw0tzPwnHvVrnmx8kVqyo5c2FJznLIzDi+/W21aWY8Y/K5CyFmA8cDrwNlUspW41AbkElxVwU0DrqsyWg7tK+bhRAbhBAbOjo6xjpuDfDdx3fyf/f/noB0cuqfIwSjCbA64JRPKMu99a3sOtrxCMSDykrf/nda923ho5ZHCNacBVUnHHa6x26hvFqVmZOH+t0z+dCL5pNMpWnsDk84te2S8jziqTT7S8+n58Mvc2fyAl6e80nu++gpJNOSu16pJ5WWxOacB+/5/YQWHZ2xsIS7/mUtFvM7dDrqlFPUppnxZP0/WAjhAR4APiWlDAw+JqWUwJicvFLK26WUa6SUa0pKxm9pvZN5alsr77K9RVvJqXRG4PEthtAuvkS9tr6dXUeb71F+6it/BekkJ7x4E4WiD+t5Xx/xkhWLVb7v9paG/jYpJdu2vAnA1fcdZNV/P0UyLZk9wVJyiyuUFb2jNcArrYJvJG/guHPfz8rqfOaWuLnrlXoAqgqcE7qPBnjlFbVpZjxZibsQwooS9nuklMbvdw5m3C3Ga8b52gwMTp1XbbRpckhTTxhX9zaK0t0sOO1q5ha7uX9jkzqYXwPCDD31o/bz7GsbSNe9iFx5vYrpnn8eebFWXjCdhGPW4VZ7hlNWLgHgQP1A5aK/bmziyZdeIY1gweLlXLumhn8/ax7vOm5iecvnFnuwmgU724K8vLcTr93Ciqp8hBBcvrKSQDQJQJVvYhWSNMCXv6w2zYwnm2gZAdwB7JBS/mjQoYeBG4z3NwAPDWr/kBE1sw7oHeS+0eSIN7bv46OWR5AIxIJ3cfUJ1ayv76ahKwxmC/hqoKfuiH2k0pK6p3+DCcmbBUYZulM+SVB4eKLsI0e8tqwgj16RR3f7gAfu6e0HOc7Rgciv4bvvXcvXL1vKFy5cjM9lm9BntVlMzCvxsLM1wD/3drJuXlG/2+TylZX951X6tOWu0WTIxnI/FfggcI4QYrOxXQx8FzhfCLEHOM/YB3gM2A/sBX4D/Efuh/0OZ8v9XPDMBVxsXg8nfxzcxVx1fBVCwANvGtZ7wZxRLffntjZweeIxnk+v4raNMQBSs89gTeK3uKqWjTqMhKuUivBuon/6IPLOy9i4v53FtnZE0byJfsLDWFKRx+t13TR0hzltfnF/+9wSD8ur8vG5rLhsOg+eRpNh1L8GKeXLwEgzVOcOc74EPjbBcWkG8/KtMO8cqFgBgHz2WzSli/nbnG/whQveDSir9dR5xTy4qYlbzl2AqWA2bH9o5D6B+mfv4DwRoGv5R3lxQwfbWnrx2q3EkmnmZ1FOzlFQycrQiyT3tiDSUS5MzKfc0gxFp0/0Ex/G4nIvf9ukvHunDhJ3gP+6bClNPdlVhdJo3im8Q0MCZhDhbnj6v+Cft6r9QAuip46/JE5n3rKh6XOvOr6Kxu4IW1t6Vax3pLu/Huih7Grt5ezu+2j3LOG8i67GbTPzzUe286W/qUnYbMTdfe7n+Yn5Q3xh1l84mL+Sz1nuw5YMqhj3HLO4QsXVl+c5+hcaZVgzu5Arj9epAjSawWhxn8ak0xIOblM7+56DdAoOqEiG19OLOXX+0MLSpy9QFu2r+7oGVmke6prp2ge7/sGeh77LPFMrrrM/Q77bxgfWzWJ9XTf72kPccu4CTpg1+gpNMed0Wo/7V57YH+O39g9RIPrUgaLcJ9taUq4iZk6dXzyhBVGaUbj1VrVpZjzaSTlN6eqLcdb3n+e+VW+xBJQV3rqZ+L4XSeAiVrSUivyhE4ilhlX76v4u/m2hsUqzpx4qVg6c9Kf3QtceLgW6bVUUrlJunc+8ayGXrKjguMr8rKsXAZy9qJR71zfym4YKrik5iUXB1yelclGJ187n3rWQ85ZOLPJGMwqrVk31CDQ5Qov7ZJOMQyKkcrYcoZLQoWxq8BOMJWnds5ElNg/E+0jsfpqOrc+yO72QL1+6fNjrTp5XxN/ebCaRvw4rDLXc4yHo2sP/2S7i0fQ6vv+Rq1RkDaogdSZx1lg4dX4xNrOJeCpN48nfYlHyxUkRdyEEHz9nQc771RzC00+rV12wY8ajxX2SSKUl6Vgflp+tRoSMJQAn3AiX3ZbV9Vuala+8oG8vsdqV2FJ9dL56D1XJRnqWXcuyxaXDXnfy3GLufq2BLZ2S1a4i6B4UDtm+E4CH+xZz5fXvxVM68awQbruFk+YW8tKeTlYsXwHe7MvoaaYh3/qWetXiPuPR4j4JtAeinPujFzgz/hI/s7WzdfaNLMuLwMY7YcllMH/0P5ytzb2UuC0sTDayM70Gd14e81tvB2DZKRePeN26uerXwav7ulhdMHuI5f766y9xElA0dxUXLiufwCccysfOns/xtQWUevUiIo1muqAnVCeB53d3EIwm+WTpW3SKQv61+WJiF98KxQvhkU9DrG/UPrY093LF7CRuEeMfnUV8f5/KeCit7qE+9EMo8thZVObltf1dRqy7stx//txetm16lZiw85X3X5TTScl1c4v4zPkLc9afRqOZOFrcJ4F/7u1ktjvJguBrRBdeTmswyUNbuuCyn0BvA7z4v0e8vj0QpT0YY51b5Yp5JVjGs6HZpKweVc/UbD3i9SfPK2JDfQ+p/Fngb6QnGOaHT+7iFG871vKluJ32nH1WjUYzPdHinmOklPxzbyc3l2xDpOJUnf5BjqvM41cv7iNdsw4WXAA7HztiHxl/+2JTIxLBQfsc3n/yfMzvvQsu+H+jjmHd3CIiiRT1shRkije3bCEtYZ5swFR2XE4+p0ajmd5on3uO2XUwSGdfnHMKXgbfLETVCfzbma188t5NPLXjIBdUrVZl8OIhsA2fLXFLcy9CQHl0P6JgNk/cfBFeuwVM2QnzaQuKsVtMvNDuZh6wd9dW5jjysEY7oWxpDj+t5pjj17+e6hFocoS23HPMy3s68RGkrPM1VRBaCC5eVk55noO/b2qG8uWAhPYdI/axtbmXucVuLB3boew48p1WTGOIPffYLZy7pJT76lTCLtm4nquq/OpgqRZ3zRFYtEhtmhnPO1fc0ym1tH+stUZH4ZV9XVzhq0PIFCxSmRYtZhMnzS3kzYYeZMYt0jZyrvUtzb2srTCrWqTjFOPLV1ayM+Shoeg0rk89zLkuIzWvdstojsQjj6hNM+N554r7Y/8J/zsHvjsL7r0eEhNPPJVIpXltfxcXePeDxQkVq/qPra4t4GAgRgulYM+Htq3D9tEejCICLXyu5TMgTLDg/HGN5axFpXjtFj7Zfhn5IszS/b8DV9GEStBp3gH88Idq08x43nHi/uzOg/zwD/eT3vA7DhSdDksvg12PwRu/nXDfmxv9hOMpjktug+o1YBnIY766VuVqebPBr1wzbVuGXty1j+Sfrqf9ZxfyiP0r+GIt8P77oWZ8i4IcVjPvOq6czYkanrWeiUjF1K8AnZdFo3lH8I4S90QqzRfvf5vT9v2IAG4ua/4gW9d8W6XTfelHEA2M3slgogFofrN/d31dN24i5Pl3QO3JQ05dXOHFYTXxZkOPEveD2yCd7j8eev33iN3/IBYJkSxbifmmJ4YtTj0WLl+lClnsWPxxMFmOGB+v0WiOLd5R4v741jZWhl/hJLEN+/lfQ9p9/OqFfXDOV1Virtd+ObYOH/0U/OZsWP8bADYe6OHSwiaETEPtuiGnWs0mVlT7DMt9mco3YywwqusM0fTG/7FJLiTwvv+j4j8eVedMkNPmF/PJcxdw+dmnwc3Pwxmfm3CfGo1mZvCOEvc/vLyXr9jvQxYvxLnuI7xvXS2PbWnlgGMxLL4UXv2ZmmQdhZ8+s4fP3P4IctvfwVkIj32O9D9/wob6bt7l3q985cO4U1bXFrC9pZdY8cCk6q62IDf94nEWyDqqTriEs0fIGTMezCbBZ85fSE2hS/1acI6exlej0RwbHPvibkTDvNXop7L5CWbLJsTZXwazhZtOnYPFZOI3L+2Hs78MsQCsv/2I3UUTKW5/cT9LG+4hJSH24adh6ZWYnvoalyX+wYr0dihfAXbvYdeurvWRSEm2xMuVm6RtC3e9Ws/q5FuYkFSsvmRSHoFGkzV//KPaNDOeY1vcU0m4+93w+u384Z/7uMX6IKmSJbDkCkDlP3/36ir+uqGJXu9CWHSxcs3EgiN2+cS2NogF+IDtBR5NncQtT/iRV/+WppIz+B/L7ynu2QSzThn22tVGAYyNTWEoXgRtW9nc4Ocyzy5w+KByVa6fgEYzNmpq1KaZ8RxT4p5Ipfnjq/Uc6AqphmQEzDZ4/D+5ace/ME+0YD7ri2Aa+NjXra0llkzz9I6DcPpnIepX2RsHEw+rLwrggY1NfM79OI50mMTaj/GPbW08tbOLnxZ+hS1iISKdPGwyNUOxx05toYuNB3qg+gRk3Qs42jdxfHITzD0TTOZJeCoazRj4y1/UppnxHFPi/vDmFr720DbO/eEL/NdDWwlIB1x3L+vn38JCGogWLoYllw+5ZmV1PpX5Dh7f2qrCF+ecCa/8DBJRdYK/AW5bCT9ZRfDZH/HB+i9xQ+oBWHoFV118MfNK3Hzn8Z28fCDMXbP/F87/H1h4wYhjPGVeEa/u6yJx1leJOUq50/Jt8uLtKmJHo5lqfvlLtWlmPMeUuN+7voHZRS6uPbGGu19v4D//+hZSCL7cfi6fKvwFjhv/NsRqB1Xh56LlFby4u5NgNKEiSvra4C/vB38j/Ok6SMbAV4v3xW9yhultuk79L7jmTixmE1++eAl1nSGa/RGWzquFUz8JlpGzLp69uJRgLMkbHWYeWnYbKQxrfe7Ewh41Go1mMMeMuO8+GGTDgR7ef9Isvn3Vcj5/wSKe2HaQL/9tK3vb+zjjlNMgr3LYay9eXk48lebZne0w5wy49Mew/wX4ySro2AnX3knyQ49yo/M2bin5DUXnf6b/S+KcxaWcPFcVql4ze/QyeqcZZeme29nOC135fMbxTbjkh1AwK2fPQqPRaI4Zcb93fQM2s4mrT1BFLT5y+lzWzink3vUNeOwWLl05ckm542sKKMuz89iWVtWw5l/gw4+r4hqX/BDmncODm5p5vqeEq88ZOlkqhOA7717Ov581j+VV+aOOM1OW7tmd7Wxu8OOetRpO/Mj4P7hGo9EMwzEh7tFEigffbOaCZeUUutWSf7NJ8KNrV+JzWbnuxBpctpGzG5tMgouWVfD8rg5CMTVxSs2J9NzwAsnjbyCRSvPTZ/ewvCqf85YcHoc+u9jNFy5cjDnLzI3nLC5lX0eIlt4oq2p8Y/68Go1GMxrHRD73Hz21m95IguvXDg3hqi5w8fIXzsFlHT0K5ZIVFdz5Sj1PbGvj3auraQ9GOev7z1OR7+CkuUU0dkf45o3H5aQ83TmLS/nmI9sBtLhrphf33z/VI9DkiBlvuf/y+X3c/uJ+PrCutt/3PRiP3ZJVLvQ1swqoLXTxwJtNAPx1QxPheIq0hD+93sDKGh9nL8rN6tFZRW7mlrixmATLsnDlaDRHjeJitWlmPDPacv/z+ga+94+dXL6ykv++fNmErGohBO9eXcVtz+yhqSfMn99o4OS5RfzxprU8se0gy6ryclpU+ubT57KzLYgji18VGs1R48471euNN07lKDQ5YEaL+5KKPN59fBXfu2bFmCoVjcTVq6u59ek9fP7+t2nsjvCfFyzGYjZxyYqRJ2PHy3Vra3Pep0YzYbS4HzOM6pYRQvxOCNEuhNg6qK1QCPGUEGKP8VpgtAshxE+EEHuFEG8LIVZP5uBX1vj40XtXYTXnxrtUU+hi7ZxCXtnXRYHLygXHleWkX41GoznaZKOKdwIXHtL2ReAZKeUC4BljH+AiYIGx3QzMuKVu16xWoZTXnFCN3aJdJhqNZmYyqrhLKV8EDs2DewVwl/H+LuDKQe1/kIrXAJ8QIvc+jUnkspWV3HTaHD5y+typHopGo9GMm/H63MuklMaKH9qAjP+iCmgcdF6T0dbKIQghbkZZ99TWTh//s9Nm5muXjq8otUaj0UwXJjyhKqWUQgg5jutuB24HWLNmzZiv12g0k8Bjj031CDQ5YrwzkQcz7hbjtd1obwYGrySqNto0Gs1MwOVSm2bGM15xfxi4wXh/A/DQoPYPGVEz64DeQe4bjUYz3fnFL9SmmfFkEwp5L/AqsEgI0SSEuAn4LnC+EGIPcJ6xD/AYsB/YC/wG+I9JGbVGo5kc7rtPbZoZz6g+dynl9SMcOneYcyXwsYkOSqPRaDQTY8bnltFoNBrN4Whx12g0mmMQLe4ajUZzDCKUm3yKByFEB3BgnJcXA505HM5kMlPGOlPGCXqsk8FMGSfMnLFO1jhnSSlLhjswLcR9IgghNkgp10z1OLJhpox1powT9Fgng5kyTpg5Y52KcWq3jEaj0RyDaHHXaDSaY5BjQdxvn+oBjIGZMtaZMk7QY50MZso4YeaM9aiPc8b73DUajUZzOMeC5a7RaDSaQ9DirtFoNMcgM1rchRAXCiF2GTVbvzj6FUcHIUSNEOI5IcR2IcQ2IcQtRvuwtWenA0IIsxBikxDiUWN/jhDidePZ/kUIYZsGY/QJIe4XQuwUQuwQQpw8XZ+pEOLTxr/9ViHEvUIIx3R5ptO5LnIW4/y+8e//thDib0II36BjXzLGuUsIccHRGudIYx107LNCCCmEKDb2j8oznbHiLoQwAz9H1W1dClwvhJguJZSSwGellEuBdcDHjLGNVHt2OnALsGPQ/veAH0sp5wM9wE1TMqqh3Ab8Q0q5GFiJGu+0e6ZCiCrgk8AaKeUywAxcx/R5pncyM+oi38nh43wKWCalXAHsBr4EYPx9XQccZ1zzC0MjjhZ3cvhYEULUAO8CGgY1H51nKqWckRtwMvDEoP0vAV+a6nGNMNaHgPOBXUCF0VYB7JrqsRljqUb9QZ8DPAoI1Go6y3DPeorGmA/UYQQBDGqfds+UgXKThajMq48CF0ynZwrMBraO9hyBXwPXD3feVIzzkGNXAfcY74f8/QNPACdP5TM12u5HGSL1QPHRfKYz1nJn5Hqt0wohxGzgeOB1Rq49O9XcCnweSBv7RYBfSpk09qfDs50DdAC/N9xHvxVCuJmGz1RK2Qz8AGWttQK9wEam3zMdzFjrIk8H/gV43Hg/7cYphLgCaJZSvnXIoaMy1pks7tMeIYQHeAD4lJQyMPiYVF/ZUx6HKoS4FGiXUm6c6rGMggVYDfxSSnk8EOIQF8w0eqYFwBWoL6RKwM0wP9mnK9PlOR4JIcRXUO7Pe6Z6LMMhhHABXwa+PlVjmMniPq3rtQohrChhv0dK+aDRPFLt2ankVOByIUQ98GeUa+Y2wCeEyBRzmQ7PtgloklK+buzfjxL76fhMzwPqpJQdUsoE8CDqOU+3ZzqYGVMXWQhxI3Ap8H7jiwim3zjnob7c3zL+tqqBN4UQ5Rylsc5kcX8DWGBEINhQkykPT/GYADUbDtwB7JBS/mjQoZFqz04ZUsovSSmrpZSzUc/wWSnl+4HngGuM06Z8rFLKNqBRCLHIaDoX2M40fKYod8w6IYTL+L+QGeu0eqaHMCPqIgshLkS5EC+XUoYHHXoYuE4IYRdCzEFNVq6fijECSCm3SClLpZSzjb+tJmC18f/46DzToznhMAkTGBejZsz3AV+Z6vEMGtdpqJ+1bwObje1ilC/7GWAP8DRQONVjPWTcZwGPGu/nov449gJ/BezTYHyrgA3Gc/07UDBdnynwTWAnsBX4I2CfLs8UuBc1F5BAic5NIz1H1OT6z42/sS2oCKCpHOdelL8683f1q0Hnf8UY5y7goql+poccr2dgQvWoPFOdfkCj0WiOQWayW0aj0Wg0I6DFXaPRaI5BtLhrNBrNMYgWd41GozkG0eKu0Wg0xyBa3DUajeYYRIu7RqPRHIP8fwB3MyLu3B7/AAAAAElFTkSuQmCC\n",
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]