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UgEPj5+QUEBBiNRpQGDCfoXQYAAACuimXZgICAtLQ0Zxsb44SzMPOLZh49ehT9zQBJBgAAAODaM5lMTjhTmXOuJ+OcZQWAJAMAAAAjiJOPZXfylTFZlhUIBHiKwNVhnAwAAAC4GH5sjMFgQFEMgMlkevbZZ1EOgCQDAAAAcLVjjFwuj4uLk8lkKI0BEIvFFosFo/8BSQYAAADgqiorK9NoNGq12gnPrdhYXFhXyFpZImKt7KaDm5yzDF9++WW9Xm+1WvE4gUvDOBkAAABwDS4xYN1oMqbsTDEkG2T5Mu1yrVgoRqkCDBG0yQAAAIALYBgmKCiosbHRyc9TKpZmBmdSMq0JWuP8MaaxsRHrzACSDAAAAMAQxhh+bIyvr6+Tn6qZNafsTKELFL89nu9m5sx8fX01Gk1oaCjCDCDJAAAAAAy+qKiouLg45xwb0yPGRJVGTRk/hXbQDZ43bDyw0fnLVqFQaDSaqKgoDJsBl4NxMgAAAODsXGUsR1RpVMbCjAhdhOlZU31z/VP6pz5VfuoSJezk6/MA9AptMgAAAOC8AYb/wVWGpJdHlx87e0wmkRFLUrH0Xsm9rlLUfIyxFTgAkgwAAADAAOn1+vT0dIZhXOicLect62vX/3XRX/mXcybNcdqJmC/V0dGhVqtTU1ORZwBJBgAAAOCKkkxxcbFEInGhc97y7y1SsdTvRj/+ZfjM8B3f7KhorHCJk/f09CwsLFyyZIlcLsfjBy4B42QAAADAGVmtVnd3d9c656CioLyQvMDJgW5uF6tYJospqCjo6BNHBe4CV7kKlmUFAgGeQHB+aJMBAAAAJ2IymViWJSKXizGMmTFZTIGTA7u/KRaKk+YnZXyc4UIXYosxrtW1D5BkAAAAAK5dGGCYoKAgnU7niidfbCyO84+79P3kwGQDYzCaXGzBFqPRGBQUhDEzgCQDAAAAcPkYwy9/qVQqXfH8Sw6VKKW9n3nB0oLEHYmudTlSqVSj0eTm5uLJBCQZAAAAAHtSUlJcYvnLXh3/4bhYKJaIJL1+Gjg5UCqWFtYVutZFKRQKl+vjByMKRvwDAADANWaxWIRCoXMO8T9y5Mj27ds7Oztnzpy5bNmy7Ozs0aNHjxkzJi0trfvZFhuLJSKJTCK7WMFy61nFYq1ssj45cHJgX+02zsxqtZrNZm9vbzyr4FTQJgMAAADXEsMwCQkJ5JRD/Ds6Oh555JH09PQlS5bExsbu2LHjp59+ysrKqqurq6mp+c1VmBlbjOmVwF1QuKyw5FAJY2Zc7h7V1dXdcccdRqMRjysgyQAAAABcjDFyufyxxx5z2jPcvn17a2urQqF4++23GxsbZ8+eTUT+/v4DO1rB0oLtX293udsUGBio0WhCQ0MRZgBJBgAAAIDol7ExMpnMOU/P09Nz0qRJEydObG5u3rVrl9Vq7XUzM2t2cLkYX2/fto42V7xTCoVCo9EkJibioQXngVFcAAAAcM2Ul5e7xHlOnDhxwYIF48aN4xslvvvuu1tuucX2aUVjha+3r4OH8vb0bmxrdHx7pwozCoUCDy04D7TJAAAAwNXGMIxrrbqo0+muv/56hUKh1+vPnTvX2dl566232j4tOVQiFUsdPNSyGctcbkbmS28fnmFAkgEAAICRGGPkcnmPEfNOG2Dc3Nzc3Ny++OKLVatWTZw48bnnnhOLxS+99JJtfgLGzDBmpq/5ly8lEUnEQrGuQee6dzA3NxcDZsAZYBZmAAAAuHrMZnNAQEBmZqaLLn95qZy9Oed+Ope9OPs3FSw3e1Usk8UkL5Hve3SfSCByxUtuampatGhRVVWVVCrFIw1IMgAAADAiNDY2siw7bGrAJovpvnfuq46r9vb0djzJEFHdybqX9rz0eujrk8dNdtEwU1NTs3LlSjzSgCQDAAAAwxw/uEIikQyni0rZmTJ1/NTkwOSeFSy3y1exjCajqlJVH1/v0iVgNpsZhkHjDFwTGCcDAAAAVyPGuMrYmH7RNehi/GIGtq9ULJVJZPk1+S5dAkajEevMAJIMAAAADOcYk5mZGRMTM5yuS9+kl4qlYqF4wEfIXpy9vna9yWJy3UKQyWT8opkmkwmPOlxl6F0GAAAAQysjI2PmzJnDZoi/japSFTw1WCnt5boc6V3Gq2isKDlUUh5d7tJFodfrWZaNjIzE0w5IMgAAAABOjbWyk16bdGrNKYG74EqSDBFFlUZlL852xbUyAa4t9C4DAACAIWE2m4fx8ImKxgqFj6LXGNNfBUsLtn+9fRiUCcMwGDADSDIAAADg8jEmPT3dYrEMy6uznLes/Wzt3+R/G5Sj8SNtXHq0DM9qtRYWFqampmLMDFwd6F0GAAAAgy8/P18qlcpksuF5dTX5Leda8kLy+qxgufWvinX8h+MP/O8D+x7dNwwKR6/X7969Ozs7G78FgCQDAAAA4FyCioLyQvICJwcOVpIhosQdif43+SfMS0DxAjgIvcsAAABg0DAMYzAYhvc1tnW0mVmznRgzMMNgRuYejEYjhs0AkgwAAAC4RoyRy+XDPskYTcY4/7hBP6xIIEpbkJbxccZweh6wzgwgyQAAAIBrxJi4uDi1Wj28r7ShtSHGb0iW+FRKlYyZMTDDJApGRkZqNJrc3Fz8dgCSDAAAADivioqKkRBjiMjMmiUiyRAdvGBpQcrOFNbKDo+yUigUPj4++O2AIYIR/wAAAHBFTCaTWCweIRdr7bK+vOfl54Ofv0wFy23gVaxdx3YV1hVuCt8kEoiG00NCRCPnOYGrA20yAAAAMHAMw6Snp4+c6y37suz2ibcP6Vcsmb7ksTmPxW6NHU7lZjQaAwICMAEAIMkAAACAs8QYuVyenJw8ci659Eip341+Q/0tCh+FSCDSNeiGTbkpFAqNRhMaGoowA4MIvcsAAABggHQ6HcuySqVyhFyvmTXPemPWdynfuY9yv0wFy+1Kq1gmi0leIq+Prxe4C4ZNAer1+sbGxhEVfQFJBgAAAODaK6wrPPT9oYKlBZevYLkNQhWrsK5w8rjJy2YsQ8kD9Aq9ywAAAKB/GIbR6XQj8MJLDpUMxUoyfUmYl1B3sm5YluTevXvxewRIMgAAAHC1Y4xcLmdZdsRduJkxWUyBkwPxDFy5LVu2YMAMIMkAAADA1WM2m+VyeWZm5sgZG2NTbCy+mg0yvMDJgfk1+cOvMFNTUzH6H64cxskAAACAo86cOfPtt99KpdKRduHHfzgepg376OGPvD29HapguQ1OFauL6/qfHf8z7+Z5j815bJgVaVNTk8ViGYHPEgwitMkAAADA5TEMk5+fP2HChJFZ9Xxpz0vxc+MdjDGDWVFzG1W4rHDr0a36Jv0wK1IfHx/+WSouLkbjDCDJAAAAwFDFGLlcbjabR+bls1ZW36SP9I28VidQsLQgZWcKax2eY5PEYjF6mgGSDAAAAAxVjImLi1Or1SOzBAyMwdfbVywUX6sTkIgkcf5xWbuzhmXx2hbNNJlM+HUDJBkAAAAYNGazOT4+fsTGGLrqky/3Kjkw2cAYjKbh2XDBhxmLxYJfN+gXjPgHAAAA6FN4ZPgHlR+IvEQHDxycNm1aR0eHj4/PvHnz3n//fXd39z4rWG6DX8WqOV6TsjNl36P7cFMAeGiTAQAAgF6YzeaMjIwRXgg6ne6OiDuUFcqkp5KSkpKsVusnn3xy5MiRbdu22YkxQyRwcqCvt2+xsXgYF3hOTg4GzACSDAAAAFxRjElPTw8JCRnh5bDsD8u2sdsygzOfeOIJDw+P9vb2r776Sq1W19fXX5PzeT309ZrjNf/+/t/DtcBXrFhRWFiYmpqKMTPgCPQuAwAAgJ6MRqPFYlm4cOEIL4ecvTnnfjqXvTj7zTfffOSRRwQCARG1t7f/6U9/2rx581XuXWajNqjVMvUwLna9Xk9ECoUCv4lgnzuKAAAAAHrAeoW80iOlmgiNTqdzd3fnYwwRjR07dsGCBdey9jbKnbWyAnfBcC12ZBhwEHqXAQAAwEUMw2BsjI3JYiKiRkPjF198sWrVqv3799fW1hJRQ0PD9ddff/XHydgETg7Mr8kfCbcgJycH3cwASQYAAAAuH2PkcvnMmTNRFLyG1oYbam+IjY1dt26dm5vbAw888OWXX7q5uT3++OOrVq26hicmk8hKDpUwZmbY3wKpVJqbm4tHEZBkAAAA4DIxJjMzU6lUojR4RpNxy9+3cL9oaWlRqVQcx33++efX9sTcR7nnheQl7kgc9rdAoVBYLBbMZgZIMgAAAGBPdnY2Ykx3lvMWsVDcr1242zhyI3IjjjhyI+7vQzXoX+GjEAlEugbdsL8LqampeBShz1SPIgAAABjJzGazyWTy9fWVSCQoDRtrl3WUW7//4OvW5Pabl2fchu4M3wp767FtjwnHCJfNWDaMb4SPjw//w65du/z8/MRiMR5OsEGbDAAAwMjFMExAQAAGVV+q7Muy2yfefoUHKS4Zwm5RwjFC3Qrdc9XPGU0jovOV1WoNCAhATzNAkgEAAICLY2Pi4uJkMhlKo4eSQyVScT+momZZa2FhXY837/l26usL9ut0DWYzO0TnqYnQqCpVI+GOKBQKjUYTGhqKMAM216nVapQCAADAyCQSiTAO4VImi2ntZ2ufD37ekQ5mLGstK/tSpaocPfq60AafUdZfe5SNfWj05LPjZhfeWPyasXBXnYm1eHt7ikSDuQ6MWCj+6v++amxrDJwcOOzvi4+Pz7x588RisUgkwlMKRDSEC9ACAAAAuKL8mvyWcy15IXn2NzMYmJKSQ3p9k0wmycwM9mW9KZFISyQhN7cUjvtldxNRMXXmXzg2xryRrWu9tz09faFUOmjjPVgrO+uNWYcTDwvHCHHvAEkGAAAAhi2GYVJSUrRarW3ReughqCgoLySvr1aOtraOl17ao9M1+Pp6x8X5R0b6ikQCaiJ6mKiKSERE5ObWWxVLT1RC333xw1Ojq4ysSaHwiYiYqVD4XPkJ6xp07qPcV9y+YoTcoIqKColEIpVK8ayOcBgnAwAAMLJijFwu9/f3R4zpS2Nbo5k19xpjTCZLfn7NokWaqVPH19fHV1fHKZXSi73FiomqL8aYPimItHTrpnHlFN3o9cQfO2YX5NV5ea2Njd1aV3fySs45xi+mobVh5NwjPz8/DJgBwizMAAAAI4fZbOaH+GOUrB26Bl307OjflhtbUdFYUnKosbEtJsZvzx6Vt7fnb/YpJPIjcjAbyoiOkkeNu3yjRP5vyU9RP3/sdywxcYe3tyffRCORDGQQiPsod9bKCtxHRED18fHhR/9XVVWhZWYkQ+8yAACAkcJqtTY0NKDmZwdjZqJKo6rjqi1toz788D/ffnuOiAQCd19fb6lU3EvGqCAyEs0j+u2aLr33LrsUS9RAVEPURv85ceYotTWNP2MWXpzoTCQSBAZODgyc7OCZP/3R0wVLC7w9vUfKzWIYkUiE0f9IMgAAADDM63wpKSnl5eUoCvtW6laZG0VHSqaKxcJXX71v4cIp9kKIiiiESNlbBcut/1UsM1EF0UYiM1ESUQwxZnN+fk1JySHbiBr7854ZGEPW7qzquOqRdtdUKlVSUhIi+giEcTIAAADDP8bI5fKIiAgURV8slvOFhXX+czfojFv96N7q6rh9+x61F2PMRLFEEb3HmAESESmJ9hGVEx0imkWSLFF+qqK5OSkiYmZl5VfTpq0PDX23sLCur9VpZBKZRCQpNhaPtNsXHR2NYTMjE9pkAAAAhn+MyczMVCqVKI1Lsay1oqLxtdf2zZt384zw05/+UFkefbmWK5YolCiNSNF3BcvtiqtYLJGOaD1RPFHMxbkE9PqmysqvDAYmOnp2ZKTvpVM5myym0HdDqx6qEgvFI+o+6vV6lUpVX18vFovxVCPJAAAAwPCoqbMGg0GhUKAoLqn7NpWWHqmoaFQofDIzg319vWO3xkbMjIjxi7nMnjlECiK7XZkGIcnw2oieI6ogkhHFXcxOJpOlsLCusvIrs5m9dCrnYmPx7pbdmgjNSLuhBoMhMDAQk/IhyQAAAAAMT7bVYKRScV71IdgAACAASURBVHT07JgYP4HAnYjMrHnWG7Oak5ovM/2XkchAlHy5CpbboFaxWKIKohKiRqJ4oieJhEREDGPmW2lqao4nJc1PTg7kB9LYXw8HYNjAOBkAAIBhiJ9wmWVZFIUNw5hzcvbaVoOpqnpIqZTyMYaIdA26SN/Iy8SYGqKUQR0b4yABUQxRFVE10Tmi+4j0REQSiSghYV5V1UPNzUlEZBtI81zAKyk7U1jrSLz7GDAzoqBNBgAAYLixWCzPPvusUqkc4bM5tba2f/ppS0NDK/9SJBL4+d149923enqO7rEla2WDioLKo8slIknvxzISVRBNJlrp0Loxg9wm0/PCiD4kavrlpS+RH5EfEVFT05nGxrampjMtow98dHrrQ2Ofu2PWLb6+3j4+E0bITW9qasrNzRUKhenp6d7e3vjfAEkGAAAAXAzDMBKJZMRefk3N8ZKSQ3V1J9esCYqJ8bvs9nu/3bvjmx3Zi7N7/zif6BBRfwaeDG2S6aGCqJTITFRA1O2e65v0TSePu38p5bufOTiV83B5AGqkUinGzCDJAAAAALiGxsa2kpJDOl2DWCyMi/Pv3nnMvg37NyyZvsTX27eXzzKIWKK8flaw3K56FUtPlEjkSxRH9MucBWqDWi1TE5HZzPIjavT6psDAyWvWBC1ZMh0PDLg6jJMBAAAYJhiGCQgIMJlMI/DaDQYmIGBjVFTp+PEe/GowCQnzHIwxRNTW0dZ7jFERje93jLk2FETNRElElUSTiDKIGHIf5c6PlhGJBDExflrt8rNn05KS5q9d+1lAwEa12mA0DuenhWXZoKCgkfkbMUK4owgAAACGR4yRy+VxcXEjaj0NlrXqdA2lpUdY1qrRRFy6vsoVKSYKvhbj+68wzyiITETFRHJaoliS8WNG3tLfRDGFwkeh8DEaTRUVjSpVZa9TOQ8PAoEgMzMzNzc3NzcX/0UMS2iTAQAAcHn8TGVxcXFqtXqEXLJe36RSVU6a9Nru3S1JSfOrq+MGOcaYiRhXizE2YqJ0omYKnBlo2Gkw/tlIjT03kUrFarWsvj6+ujrO3/+m9etrf//7t3S6BrN5WM14plAoLBYLwzD4XwJJBgAAAJyRSCTSaDQjIcaYTJbExB2TJr22fn1tcPDUU6fWaDQRV9iYoG/S+0z47RFMRFEuG2O6SybNnzUqsYqiiIKIiokuySm2qZwLCpZWVn5lm8qZYczD45lRq9WOz37R0dExd+5ct27effddIjp9+vSUKVOam5sv3cXORwPecnDpdDo3N7fw8HCr1Wp7c//+/TqdztVvLkb8AwAAuDCz2Ww0GmUy2XC9QJa1NjS0Go2m48d/ICKhcIxMJvH19RYKxwzK8a1d1qCioA9iPxALxRczTDGRO9FKoito47kGI/77VvZl2favt2+4c4Pw30JqILISCYlkRH69zyhtm8qZb58RiQQ+PhNcfSpnlmU3bdq0YsWKy3a/7OjoiIiIePPNN6dNm9be3h4XF5ebm3tpFvr5558zMjJeeOGFy86Q5viW/Uvger1MJnPkmJs3b37kkUf4ny9cuPDXv/712WefLSoqmjRpUkxMjGv/B8EBAACAa2pubpZIJNXV1cPy6g4f/j4mpkwkyklI2L5v33dD9C2aeo2yQnnxRTXHyTju7CAc1tmqWNrD2piymF9fn+K4BI4Tc5yS4/Zd9jE7W1DwhUKxRSTKiYkp02oPd3ZecMUnqqqqSiwW19fX29+svb19yZIlx44du1h0Wm1RUVFra+vtt9/e2dlZW1s7ZsyYBx98cOfOnUTk5eVVU1Nj+ygyMpKIVq9ezXEc//OUKVPq6+t7bBkZGRkUFNTa2jp27NjVq1fzW4aFhV24cIHjuNra2hUrVixbtsz25vLly/lDtbS0xMbGLlu2LCwsLCoqysvL67333uPPp66uznYJ/AH5M8nMzLSdEn85tpP5wx/+0ONsw8LCfv75Zxe6p+hdBgAA4KqtMfzYmOHXIGMwMCpVpUpVGREx8+zZtIKCpYGBk4fou0qPlEbPjiYiqiBaS1ROJBqGT0uMX4yZNeub9Bdfi4kKiJqJgolSiGYRFfbS8Yxn637W3JwUETGzsvKr3//+LVfsfqZQKDQaTWho6ACGzTz++OMWi4WI/vWvf3388cdhYWEikSgqKurkyZM5OTkWi6W9vT0xMdHLy6u1tVWv16elpYWFhXEcN2fOnFOnTnXfkojefffdmJiYiRMnrlu3zs/Pb82aNfyWmzdvbm9vv/fee8vKytLS0jiOu+666zZv3lxWVtbe3u7t7T116lStVpuWlrZt27bg4OCTJ09+9dVX/Pl0dnbyp6rT6aZPn85HMoPBsGTJkpKSktdee43/dNasWfzJTJ8+feLEifzZajQa2zkcOnTIhe4p5i4DAABwSfzYmOEUY2yrwUgkorg4/4KCpY5PozwwJovJaDIqfBRkJCohKu+9t9XwULC0IPTdUJlEJnD/5SIFREoiJVEj0Xqi+4heJQq088gJYmL8YmL8mprOvPbavrVrPxOJBBERMyMjfQd5uoWhDDNVVVX9WjT28OHDoaGh77777sqVK4nomWeeWbRoUXNzc2PjxVkU+I/Gjh2r1+sNBsPYsWNnzpx56NChsLAwIiovL79w4cJbb71l25KIPD09L1y4cPr06XHjxjU2Nq5atYo/1OrVq8eOHfvJJ5+8+uqrgYGBRBQdHd3R0XHixInp06ePHTu2pqZm/fr1/Ec33HBD9/M5cODAxXBeWsp/taenZ1hY2Ndff+3u/uvv0W233Wb7efHixfzZdj+HoKAgF3qq0SYDAABgj20E8Jo1a06cOOHh4dFj4KwjTp8+PXv2bDt77d+/38PDY+rUqSx78Q/j//rXvy572GETY3btOjZr1hu21WCqq+McX9TyShQbi5VSJRFR8TCPMUQkEUmiZ0fn7M3p5TNfogKivF/aZ3KI7C7B4uMzoaBgaXNzkkYTQUQqVeW0aevz82tcohykUmm/fnO3bdvGJwfeli1bPvvss3/84x/79++3s6O/v395ebn9v0SsXbuW79O1Z88evq+UreXEprS0dMaMGS+88EJ7e3tUVNSlx7Gdz4YNG/h3oqOjs7Ky+P9JDh06NGPGDEeu1HYOISEhrvRYo5MxAACAfbYu8hzH5ebm2jrQOy4yMnLKlCl8J/i+NtizZ09mZmZRURH/jYcPH+5rbIyvr++pU6dcsSSVyoruLzs7L2g09QrFliVLNh89errHxl3l5UNxDrte32XyMHHEVVCFNEH68V0fZ/w+g3N4qFFtbe3YsWMv+ww4ZxXryX89ecc/7jh6+ijHcWc7zybrkzmO0yfrO892chx3tPxo59lO/SN6Lp3jxBwXw3FVHMdxXT5dHHG2f10+Xb2OpdHFvmgbSHP2bKf9W3/N5eXl9Tpgpr29fc6cOd2rynq9nuM422iTzZs3jxkzhoiamprmzJnj5eUVGxvLfxQZGRkeHs5vGR8fbztObW1tjy05jjt8+DD/y959WAv/Dj8Ux9ZKw3FccHBw91Pi33z99de9vLwyMzP5jW1RpMcB+YExtk/5C/Ty8vL19bWdrW2sDhEdPHjQhf5LQZIBAABwKIrwVYF//etfA9id/3uq40kmKSmpr43/+Mc/ZmVluWIZvvHGfqHw5f37j3McV15+lB/Nr1RWVFV90/sOa9ZwlxucPQDNa5uTxckmD5Oa1LMfn50sTjasNvQr05rNZluyda0kU3+qXlooXfj2ws4LnbJiWf2peo7jTtWfKpYVd57t/Cjto2JZ8an6X0KyluMUHLec6x5jLv7r43798GmtVnuYv7MKxZaCgi+am8/abv0bb+x3oqKorw8ODnbO3xR+xL+d/y4ASQYAAKAftFptWFjYt99+W1NT0z1+ENHatWu7zx3E/z319ddf57pNB3Tu3LmoqCiGYS6dZchWdxkzZsyUKVM6Ozu1Wm33P6/24OD8S04YYyZMWEuknjHj72JxbmSk7rJTYP08d26XXD74p5LJGW4wJIuT1aROnJxouMHQr8fANtGTnXvktEmGDzPiXPGftv2JjzE8PszkS/J/jTE2/+tokulxv6qqvklI2C6R5C9a9Pb48dlE6gkT1jpPmMnMzNRoNE54g86fP8835thabMAOrCcDAABweRcuXOC7iyQkJPDDZzds2HDw4MEpU6Z8+OGHcrn822+/TU1N9ff3/+ijjwwGw+TJk3/++Wd+A4PBsGjRoiNHjmRnZ2/evNm2Za9ftHXr1nHjxo0bNy4/Pz8yMjI6Orr7p/n5+Wazme/ZYrFY+tXj/9qOTdDpmGPHfrxwocvLy+Opp24nOmh/B+Hnnyd//LG1q2uTn1/b8uWDeCoyg2ze3nmbJm46Zzon8BY8cfaJ3GdzHdzXYDCMHz8+ICDAYDBMnz59ypQpfW2ZlZXF99txNud+Olf4XaHvbb4hF0JsQ/8ZA3Nh34UbPW8cGz/W/ZLhSeosdc93Mnu+IywrSz5y5MKoUUVSaVtYWPePjMZp27YxHEejR4+aPv2/YmIkRMZrWwhNTU1CoZBfWEYikSiVSvwX56oQ5gAAABzR2tr63HPPdf+bLv9X+bq6Or4hhf9r/caNGzs7O3Nzc20bcL/0Lqupqem+Za9/8ud30Wq1mzdv7mszFxUerhUKX7733hK+x5E9nZ1dEyZwRBxRl7s7t38w/5D/Y86PyeJkww0GNakfuf2RZ/7rGZPJ1N82mVWrVtkfKuOcVaxDpkOiHJGuQXfqx1OyYtnZzrOnj55+c96beVPyjtce/yD+A76b2W/Li+u67rfjZIS/HSdz9iz38MNdHh4X79e4cdxvB3ElJVWFhLwjFL4cHq51uV/5W2+99cyZMz3evGzfQlubrf2Gu2uIbwR+5ZVX+JcDG/7nDJBkAAAAHLVv374eNRUimjRpUvcRt/yAYJVKxXUbd8t75ZVXum+p1Wq9vLxs9aTa2tqMjAxb8pk0aZIj1SCNRuNCo/8lkvyzZztlsuJLx/d31yWT8dXii5VjoXAQB8zo39Qbdhk4jsuX5Ncb6p8SP/W079OOV235cTKxsbH2hzE4YZJpPtvs/Yq3rkHHv6w/Vf947OOF0kLNPRq+U9m+vH2n6k/pInW/2S3p4rj/vn4luMDALl/f39wvmcz2eXr6Lq32MH/rr30JNDfn5eVd4UH42Tsum2R6jLN30MaNG6/O8Bg+Za1bt45/qrVaFwuZSDIAAADXXm1t7XffXdHq9VVVVfySdi6kuflsYOCm+nqHA9jZs5xMxg3N0KCUp1L+dvPffvrxJwe312q1AoHA5eYuO3r6qKxY1ny2+WJUPt2+KXDTrvRdF+wMVTrLcUqOe6vvg+blcTIZd/Rorx92dl6IjNRlZ+9xmqeuWSKRZGZmXuFx+PZVR9pkurfKOn7kq59kkpKSHLkcJBkAAAD4TYxZsWLFzz//fIXHiY+Pd7kJAPiWmX6Hmd+2iQ2Kzh87A6MD696qG+QKljMlmfpT9YGbAm0xhuO4rQ9t/W6f3Qi9j+MCOU7TV6l1cgoFl5zM9VED5sNqeflRl44xfBMcwzArVqxYtmwZP1uxLcksX76ciPj2Gf53edmyZUFBQd3nceaTjMViGTt2bFhY2F//+ld+KH9mZuaWLVv4dhvbQfiXaWlptplCTpw4ERsbu2zZsi1btvDn0/0469atCwsL27x5s+0gLS0to0ePLioq6n4ODz744IkTJy79z4fvXWZ/fhEkGQAAABha33zzTVVVlcud9gDDzDffDPqZlBeXr39w/XBNMvWn6vkhMfzLH0/9uEWx5Zsqu8WYyXGBHGcnhqxZw/X9yO3b951UWtiPO3sVCqG+Pjs7u7978R3J8vLy+EzCB5u2tjZbm0x7e/uSJUsOHz7Mx4Y9e/a88sorzzzzzKUT3Gm1WtsE63zysTXG8gc5duyY0WiMioqqr6/n97LNGNE9aXQ/DsMwtqkUbQdJS0vjz+2DDz6IjY3ds2ePVqttaWnp9QItFsvzzz/PByQvLy9XHCqDJAMAAADXMsxUVTkcTjo7ub/9bSjO5Mk/PHl0UBsQnCTJfPN/33SPMfWa+g2+G+zFmKMcF8hxmXYPmp7Ovf56Xx9qNPUyWfGlK2O6Ir75xTYsin9pSzLHjx8fM2YMHwBaW1v5bd55552QkBBbFOkx50dLS8uGDRs2b9784Ycf8o2xfNsIfxB+m48++sg2su7BBx/sMSKr+3Hef/99/qPuBzl8+PDq1atbW1uff/552yKYPSYtsKmqquLbgvgFNF1xipHr1Go1JnADAAAYBoqLi7ds2XLnnXcKhUKXOGGBwD0mxq+u7uSxY2d9fb0vv4O7O40bR4WFJBKRWDyIZ/J/Hv93cOPB69quu3nezW6j3K78gFlZWde8itXQ2rDr2K51IessX1qMxcZju46JJKL/zv1v716LmiX6B1Ez0fNE4b0drrGRNm2iXbtIoaAVKy79/ODBUxs3HpBIRC++eK+n52hneMDMZnNOTk5XV9e0adMGsLvBYHjnnXcmT55cVlYWFBT09ddfv/POO21tbZ999tltt9328ssvR0VFtba28qlm+/btQUFBH374oVAoLC0tbWlpMRgMX3755eLFi6+//vrRo0cLhcIPPvjgz3/+85tvvrlgwYLJkyer1eoXXnghPj6eP8j8+fNLSkpuueWWRYsWLViwQCaTXX/99Z999tnvfve72267jT+l7sf5/PPP77rrrh4HeeCBB06ePPniiy/m5uaWlZXddNNNQqHwxhtvfP/992fPnn399dfbru7EiROnT5/29fW9cOHCtm3b6urqAgMD586d61r/6WE9GQAAgOFDr9erVKqqqirXWWqGiGjLln97e3sqFD6O7qBSUXAwDd4yINbz1t+n/z6Lsjw4j5C8kEGoYLld4ypWsbF45392Ft1XVB5dLhQLQ/JCBCJB388NUQrRB0S93gGWpZQUMplIoyGRiHqPOW3FxcacnCXO81AxDCOXy+Pi4kbaX+1fe+21P/zhDz3C2/79+zmOmz9//jC72FH4Tx8AAGDYUCgUGo3GZDK51mnHxPitX19bXOzwgokaDe3eTfn5g3UC7mPc8+7Jy+PyzIy5saLR1R+DYmPx7pbd2uXaT575ZH7S/AhNRJ8xhiVKIVpPVN1HjGlro6Ag8ven8vK+YozBwKhUlampdztVIZjN5vj4+JEWY2bNmuXl5dUjxpw4ceLVV191ufYWh/5kgDYZAAAAcAYqVWVw8FSl0uHWpJQUGj+eBq+qGrsmNuzWsM7SzghNhLcjvd3sVLCuXZuM2qBuOddSEFywM2XntMXT7lx5Z5+bGolURHFEyX0f7rHHKDWVfH37+rywsK609Eh5ebTITpsPwNBAmwwAAMAwtHfvXqPR6FrnrNFE7N7d0o+Wmbw8IhrEJJP3RN7fvvvbvbn3bo3damWtrnjf1QY1Ef3V469FQUVTg6faizE5RIlE2r5jjNlMsbG0bFlfMYZlrYmJOw4d+r66Os55YgzDMBkZGfgfAEkGAAAAXJVYLA4NDXXRMJOfX+NwzV1NRJSYODiFNl0cf2P833f8fX7S/B2JO1zupifuSCQLBZQE1K6vjauOk9pp3conOkdUTdRXW0tNDcnlFBFBkZF9xBw2KqrU3/+mgoKlzlMCZrNZLpfPnDkT/wOMEOhdBgAAMDy56Oh/IkpJ2Tl+vIdaLXN0h8JCEov7qnP3V8DqAE2EpqW4ZX7SfLF0gDOkXf3eZRWNFS0ftbj/w31B2gKp/R56xUSNRDl9b5CTQ5WVpNWSRNLr521tHffd905eXohMJnGqJ0etVkskEuXgTQUBSDIAAABwbTQ1NQmFQvGgTlh8dRgMDMOY+zFmRqcjIlqxgtzdr/CrTYwp8R+JT9//tHWvdWH6wlHuA+nAcjWTjLXLuvXTraatJvl8uW+k7xjhmN63O06kI7IQSYmWEV1aTmfO0JtvEsvSwoW0pM9ZyGpqjn/6acvjj891woEx33777ZQpU/CLjyQDAAAAw0dGRkZ0dLRrNc4YDExJySGNJsLRHSoqqKSEtFoSXGkN2/y9OeiVoKoVVbWv1EaXRztzkrFYLGkr06a3TP/znj/3mWFYoiwiA1E5UV+plmUpMZHy8vqaoIx+GRgjEgnyBmOi6kHEMMzatWvz8vIEAsw6MLJgnAwAAMDwFxwcHBoa6lqzM8tkkuDgqSpVpaM7REZSfDzFxhLLXuFXi24SZc7MrPuhTiQR1Tg+aOeqa/y0UX27eu5tc9fUr+kzxjQSyYnGE+3rO8Y0NlJoKD36qJ0YYzJZQkPfDQ6e6oQxRi6X33TTTYgxSDIAAAAwDPHrzOTm5rrWaSuV0v6FGYWC4uNJLiez+Qq/OubxmIbDDYuzF39V+dXxmuPOVjJW1rrj6R1vrXor8r3IVa+u6nO7GqJYogKi9L6PVVxMKhVlZ9PChX1tYjSaoqJKs7MX96O/31WMMSNw+UvguaMIAAAARkiYccUBM3zVWaWqLChYKhC4O3KdJBZTVJSdlRwdrSRNcLdarRGaiNKo0rjqOIHTDAv54fgPJfeX1PnWpexNkYr7jhYmojeI9hH1deJ8jzIiqqqyU1Y6XcP69bVa7XKJRORsj4dIJEpLS0tISMAv+MiENhkAAICRwuUmMbOFmeDgqbGxW1kH13iRSikvj6KiyGK5ku9dOH1hTm6OSCIKzgyudLxdaIhZWWvVmir9g/qUv9uNMXoiOVFm3zHGaKSgIAoOJo3GTowxGJjKyq+qq+OcMMbwSQYxBkkGAAAARorY2FiXW2dGqZTGx8+Njd1qtXb1I8wUFl5Rkrl7YemPpUwD4xvp6yQDZtoa20rkJfWB9W8kvNFnjDETqYjWE+0j8unjQDU1lJhIWi3ZnbCYZa1lZV9qtcsdag27isxmc1RUFHvFA6LA1WHuMgAAgJHFaDTm5OSIxeL09HTX6m/W1HRm+/avExLmOVqxNhjIaKSVK8nbe4Df2ND09NtP/+2hv/nN9du/Yf8Px3+459l7+hxb372CNahzl3W0dTRWNP5w/Icfr//x4IyD8jnye6be09v1EhmIBEQKor5aaxiGyspIJCKl0s6M1ceP/6DTNbCs9fHH595441hnizHp6ekxMTEymQy/zkgySDIAAAAjTkVFhUwmE4lErnXax4//8PDD5eXl0Y4uZsIwFBtLBQU00J51pmOmoIKgo5lHBUIBY2B2Z+2Oq467mklmb87eI6VHlhYsbfBuWPvZ2vLocpGgt7uWQ8QSqe0eS62m3btJqyW7CVana9i48YBWu1wsFjrhM8CybFNTk5+fH36LAb3LAAAARqLIyEiXizFENHnyuLy8kKioUrPZsZ5FEglVVVFKCg20Q514ujjJOynj5QwiksgkU4OnMgbmql3v3py9P5376dF9jzZ4N2w8sLHPGFN8uRhjMlFQEBFRdbX9GJOSsrOy8quqqoecM8YQkUAgQIwBJBkAAAAgl1tnRioV82HGZHJsQL9IROXllJJCBsPAvjE5LdnAGoy7jUQkU8uuWpLZm7P3vOX84uzFZU1lGw9s1C7X9hJjzEShRLvtzrNcUUFyOeXlkd2pilnWGhVVOnXqeCccGEO/TLiMsTGAJAMAAAAXJSUludw6M7YwwzCOrRvDh5m1a0mvH9g3Fvx3QWJFIv+zQCQwM+YhvUCLyfJu6Ls/nftJppYVG4srv6rULtcK3C/pUKcnCiJKItL0MUeZ1UqJiVRSQvv2UWCg/S8tLKyLi/NPTg50wjtuWzcGy18CkgwAAABcpFAoLBaLy81mJpWKtdrlKlVl/8LMxo3U1DSArwtUBErHSAvXFRLR7Stur1RVWh2cErr/jMXGEnnJ/KT5i7MX/7vt37tbdvcSY1iiFKL1RNVEir6PlZtL/v6OLK1jMDBmMxsZ6eu0MSYzM1Npd6Y1GIEw4h8AAGCkYxhGJBK54rAZhjGrVJUaTYSjq52wLKnVlJMzgO8yf28OeiWo+olq8XRxTX7NuZZzIXkhfVawBjTi32KyVKoqhWJhSF4IvxBnsj45X5HfczsTUShRHFGy3cMVFxPD2O9RxissrKus/Kq8PNoJO5UREcuyBoNBoVDgVxWQZAAAAGA4xTCzSlXZj4m2ysrIYqEB/XW/eEPx7pbdmlc1RFQaVeof5+/bRyPGAJKMsdj42drPQvJCfBQXV4FRG9QyiUwmkfXcVEmUTmSn+cRspsREEgjorbfsTLXMS0zcQUR5eSHOGWMAkGQAAADg8tRqtcViSU1Nda11ZsxmtrjYGBPj52iYqaggo5GWLKGFC/v7XblFuXf63vnfC/7bylo/ffFTT2/Pu568a5T7qCtJMq0NrY0VjTf63eij8HEXuBNRRWOF0WTsGWOMRHoilmhl30te7t1Lu3aRQEDLlpHdCb7a2jp0uoa2to5ly2bMm3ezU95Wc35+/l133XX//ffjdxOQZAAAAOAy9Hq9SqWqrq729fV1odNmWWto6Lt5eSFSqcMZLCODPDwc6Xx1ad5T/7JXXWHd94e+X1qwdGBJhjWzO1N2WllrhCaCzzCslU3ckRg8NVgpVXar1BOlEBFRHlFf3egsFnrgAZJKKTv7st/b1HTm4YfLNZoIX19v57yhJpMpKCgIY2PAPoz4BwAAgF8pFIry8nKJROJapy0QuJeXRycm7tDrHR7Qz9f4+59kRHNFTAPD/zwvYZ6VtRqLBzJfQpO+qSioaGrw1OXa5bYYE7s1tmeMqSEKIgom0vQdY/gLSUpyJMYQUX5+TVXVQ04bY4hILBZrNBrEGLAPbTIAAAAwTLCsNTZ2a3z8XIXCx9F91GpqaSGNxvFvaTQ2ZmzOKF9Xzr+0staioKKHP3rY09vz1wqW3TYZvinGYrJEaCKEv/SI42NM/Nx4hU+3oe16oiyiciKxvcumrCyaOpUSEhwpopSUnRERM/tRRADOCm0yAAAAl2U0MgAAIABJREFU0IvCwkKXm5pZIHDXapdv3HigHy0zajUFB1NFhePf4iv1JaKKkou7uAvcl2uXN+gaHNz9TNMZvinmoaqHuscYeYm8Z4xpJNIR7bMbYxiGQkNp/HhHYozZzIaGvuvvf5PTxhiGYQICAlxrqVZAkgEAAADnsmTJktDQUNcNMzqHowUplWQ0Un8Wjy94siClIYW1XNzF29e7o63DkR1ZM/txxsdx1XFSpbT7+8XG4oKlBb+JMflEsUT254vW6SgqirKzKT39sl9tNJrk8pLs7MUJCfOc896ZzWa5XB4REeFaE04AkgwAAAA4Fx8fH41GExoayjCMK4aZysqvjEaH/7QfGUmxsY6HGfF0cZJ3UsbLGb++IxVfdrTM8ZrjRUFFi/66SPjbOdYYM2NmzVLxL9mGXy6mxW5rDMuSSkWVlVRdTYGBlz3hiorGlJSd5eXRgYGTnfbGFRYWxsXFqfs/cglGLIyTAQAAgD6ZTCbX/QN5YWFdYOBkR2cza2oinY4kElqxggSCy25uPW998c0X3Ue7Pxv/LBFxXVzt32s72jruefYed4F793EyPxz/obGisaOtY9zkcX4xfmOEY2wHaeto2/LvLUT02JzHhF1C0hMZiYREkX3Ps0xE771Hx47RsmUkldo/ya4u7v33jzY0tPr6ekdG+jr5ijFms9kVl2cFJBkAAABw6ipmUFCQVquVXq7q7GxUqsqZM29IT3d43Ri9ntaupfJycqxKrXpaFTw1WPmkkn+pDddyXdyD2x+Mcosq58qPvn/05BcnGQMToYnwvmSiMKPJmLgjUbtcKxFJ6DjRA0TxRMrL3AlSqejRR2nZMkdOLz+/RiwWxsT4OfM9YhgmNDS0vLzctSb+BmeA3mUAAABwGSKRKC8vLzQ01OWGYms0EefO/aRWGxzdQaGgvDyKiiKz2ZHNsxOz1x9bbzp2sVjkL8i/P/T93uy9UpKyZtaQafAY7/Hovkd7jTEpO1OqHqqSiCREROlEmsvFmJoaCgqiuDgHY4zRaDKbWeePMXK5PDo6GjEGkGQAAABgSCgUCo1Gs2HDBpc78+zsxUTUjzAjlToeZsTTxUnTkzIKLg6YEUvFf9z6x89e+YyICv0LZ/9x9sLemoP0TfqUnSnl0eUigYgaiYKIHiOyX5NXqyklhaqrKTLSkYvQ6RoSE3ekpt7tzLeGH+KPsTFX07ZtDo0f0+l0bm5ub7/9Nv9yxYoV4eHhYWFhbn1Ys2YNkgwAAAA4dZh58sknXfHM1WoZEWVkfNy/MFNc7Mi2yieVjdbG403H+Ze33HXL0oKlRPS7kN/d89w9l27fdKZp44GNF2NMMZGKKI9I1vcXmEwUFEREtG8fOTZmKSPj48rKr6qr44TdxuQ4IZFIpNFoEGOuZox5/PHtoaHvXjbMxMTEtLa2PvXUU3v37iWijIyMf/7znzfeeOOxY8daW1tvv/32zs7O999/PyoqqrOzs7293WAw8FsiyQAAAICTct3R/2q1bPx4D5Wqsh9hhogcm7etILJg+5fb+Z9ZM3tg4wEiOvPNGStrvXTjYmOxdrlWxIoolGg3URWRnbnHmppILqe8PHKsus+y1qio0vHjPbTa5U4+vp8nk8nwa3U1Y8z331tMJosjYYaI8vPzs7Kympub+ZdFRUXTpk2zfbrsl16Onp6eYWFhaWlpq1at+tOf/tTR0TF37lw3N7fw8HCr1YokAwAAAM6CZdlZs2a53DozRJSevjA4eGpFRaOjOyiVFBtLDlypNFhqOmjiY0xpVGlIXggRheSFXDovc7Gx2O9GP8EuAQURJRFpiET2ypqysmjfPkfmWSYihjHL5SVxcf79mOHgGnnxxRex/OVQKC42urll9fovIkL3/fcWfjOTyRIQsLHXzaZNW287mlAofO+995YtW2Y/kHR0dHzwwQeff/55W1vbxo0bX3nllSeeeILjuOuuu27z5s1Der3uuOUAAADgOIFA8MEHH+Tm5gqFQrVaLRQKXejklUqpTteg0zWsWHG7u/vl/p4rEtFHH9GWLaTXk1Jpv2fXnHvnbNJtCqTA5drlQrFQT/pMaWb3NhkDYzAwBilJI/dH0s1EXxDZKTmjkbZvJyLKznZwFrV//vPIyZM/lpdHi8VOfUesVuuLL74oFoux/OUQPeFKZe8TDJpMltzczzduPEBE8fFzU1PvduRRmThxYmlpaUFBwWuvvXbpp2az+cUXX3R3d09NTe3q6vrpp59GjRplMpluueUWIoqOjh7q1agwCzMAAAAMBMMwEonEFc+8oqKxpORQP/pfmc0UFUVpaaRQ2NkqanVUnH9cZFwkEXVfT4aI1AY1Ealr1FRJ9AGRt93vSkwkgYAKChxZ1oaXkrJzwYJbV6y4HU8O2Md3KrvsIkunT5+eNm1ae3v7nj17Fi5cqNfrZTKZQCCwvT9lypSUlJSUlBQvL68DBw7cdNNNixYtam5u/s9//uPh4bFo0aKDBw+GhYW9//777u5D2HCCJAMAAABXxGq1DmllZSjo9U0bNx7oX5hRqSg+3k6YYRqYUE1ofVa9QCjonmQSdyTexN2kfklNMqJMIjvxpKaGUlIoKYliYhy8ELOZjY3dGhLyu+TkQCcvc5ZlBQ5nMwBHYJwMAAAADJzZbH722Wdd7rQVCp/4+LmxsVtZ1rERySIRabW0cSPp9X1tIvGTxHnFZa3N6v6mqlLlf8xf/bSa8oiy7caYnBzKyCCNxvEY09jYFhr6blLSfOePMQzDzJo1a6j7GsFI8//t3X18VNWBP/47GiU8qAHFIlKeRIHiA0hBQFHYsjW0y8OsWhLBAq4/HrRWICjV4iZuqdKCGlaroCKoBEJfaKJb19EftGGDClFqRCy4ZWGgQlOC61iTMEI03z+mnbIIGBRoBt7vl6+XmZNz7z1z7uXF/XDPucc8GQDgy8vIyIjFYuXl5d27d0+5MBMEwcCBT7300siMjHo8K0hPD5YsCcLhoFWr4CBfdvvvtq8+bfWIc0bUBXVBKPjZmJ9d1eyqMVVjgtcPObM/CIK5c4OPPgpeeqn+I8pKSqJ33rliwYJhXbqc1fBjzMCBA3Nzcw0q48gyugwA+Eo2bdrUv3//DRs2ZNRvbnqDUl5eMXnyyy+9NPIw3lmcl3ewdyKXn1M+dvjYZnualT5Z+qdmf7ox68YXL38xGPPFoST41a+C2bPr3+y5c99cuvTdoqIR9cpgf1e1tbUXXXTRtGnTxowZ4w8LkgwA0LBUVFSk7quoyssrVq9+f8KEb9Z3g+LioKIimDDhQDdWQXmr8sGjBv9gzQ/y++b/Z6v/7DW51xfs7c47g9Wrg//4j6Deb4ErLt748sv/8+ij33V5cIIzTwYA+KqS96mxWCzlGt+9e6tYLB6N1rvlw4cHb799sMcy3Su6/+LFX0z/1vTbX72910eHjDHRaNC3b3DGGcFvflP/GBOLxUtKoqkSYxLXgxjDUeKZDABwZFRVVU2dOrVZs2ZTp05NrZvXqqo9Tzzx2yAIxozpXt/xWiUlQUlJcMUVwaBBybLdTXY/1e2pWHosc1NmpFNkwKgBfcZ/bi7+Z58FL7wQlJcHGRnBtdcGbdrUs5EbN+5KLOs5YcI3G/6gslgslp+fX15evnDhwlQcdogkAwCccCKRyMSJEzds2JByr9yNRmNjxz6/YMGw9u3rfec9c2bw3nvBggWJT+Gl4dyrcru36p54C3P+6vxJfSbtv8mMGUGbNsFhThrJz1+9cuXWBQuGNfwMk9CjR49hw4blHeTJFUgyAEBDFIvFUvSf4aPRWDi8dMGCYV+4dODfLFwYrFyZDDN/ucEKHeQWa+7cYNeu4HDeWx2P106c+GJGRvqDD16dQj1pbgySDACQqqqqqprVe/pHQ4ph8XB46YMPXn14YSY9fd91YA6QZBJra7ZqFTz0UFDvhUSrqvYMGbJk9OhLxoxJjZdcCzAcS2b8AwBHxYwZM8rLy1Ou2RkZ6UVFIyZPfrmioqq+24wZE6xfH8TjB62wenXQt28wenTw6KP1jzFBEOTnr77vvm+lSoyJRqN9+/YtLi528SPJAAAp7Kabbho8eHDqhpnEOwAOI8xkZx84zMycGUyeHPzmN8Hw4YfVjMLC9enpaX36tEmJTovFYgMHDhw9evTww/yaIMkAAA1Lp06dFixYEA6H44d4WNGAw8xZZzWJRDbV/9sG48cHgwcHsVgQBE8mCquqgoEDg48+Cl5/PTjMMVd5eSXPP//epEl9UqXHCgsLR48ebYr/8aGmpqZnz56hUGjVqlWJkrKyskaNGg0dOrS2tjbxcfr06fvWTLj33nsTH5M1EyZMmBAKhVq0aLFly5YgCMLhcGgfOTk5X66d5skAAEdRPB5PvMQs5abNfPZZ3eLF70SjsaysCzt1alGvbd5/P1i0qO7Pf667777QHXeEzjgjuP76oH37+h80FosXFq6vqKgaMKD9gAHtU6KjEmd2z549p556qgu+4TozCP53n48tguCDQ1WvrKycN2/emjVrFi5ceNpppy1cuHDFihUFBQVpaWl79+594IEHTj755ClTppx00kk1NTWjRo1avHhxenr6T37ykwkTJtx2221PP/102l8HUhYUFARBMHLkyO3bt48fP37KlCkff/zxlVde+cQTT9x6662ffvppWVnZwIEDv8R38kwGADiKEjFm48aN559/fmqNNDvppNCoURdPndrv9tv//4UL69fyxOuV//3fTwqC4N//PRg37rBizOrV7w8eXNCnT5u8vAGpEmOi0ehFF11UUlIixjR0/3vIjwfSqVOnkSNH3nvvvdFo9JJLLjn55JP/mrdj7dq1i8fjW7duTZRs3bq1cePGoVBo9OjRn9/PsmXLvvGNbwRBcO65537zm9988cUXhw0b1rx588RvmzZt+uVijCQDABwLXbp0WbBgweDBgysqKlItiaUtWXLNypVb6xtmFi1K/L+utrbu9dfrf6DCwvV33rmiqGjEYbwzrQHEmIEDB+bm5g4YMMBFflwaOnTounXrPvroo44dOyYLV6xYkZ2dfffdd2/fvj1R0q5du927dx9sitQll1yyc+fO5Mdu3bodsX9ucIYAgGMgMzNzwYIFy5YtS7mWp6enLVgwrF5hJh6vu+++UHV1EAQn1dYGq1fX8xCRyKbnn3/vpZdGtmqVSgPwxo4dm5ubO+YwV/kkhTRp0uTyyy8vKyvbt/CDDz7Yu3fvO++8U1RUtG95QUHBfm+uKysre+aZZ77zne+UlpYmPs6bN+9LP4H5PPNkAIBjp7a2Nu1wXkPcwG7cn7/ssnMnTPjmwSrUDRwYKin528f27UNbtnzhbmOxeF5eSX5+Zsp1SHISFCngtCDY973izYLg44PWramp6d+//29/+9v58+cPGTLk8ccfv/fee6urqwcMGPDBBx+8//77a9euXbNmTXZ2dqLknXfeadu27XvvvTdp0qR58+Yl99O8efO1a9d26NBhwoQJ8+bNS34MgqCysvLcc88955xz3nvvvS99FUkyAMCxFo1G2x/OBJKGY+LEF0eM6PaFk1gOsDLmQbsiNnbs848++t0uXc5KlU6oqqpKS0uTYfi7M7oMADimysvL+/btm4rrzARB8Oij3y0piR6pvZWURMPhpQ8+eHUKxZggCGbPnl1YWOhK5u/OMxkA4FjbtGnT7Nmz27Rpk1iSIrVEo7GFC8v79GmTmdnpoDdYX/RM5le/+u8339zRvn1GVtaF6empNNxu7ty5sVjsRz/6kcsYSQYAIPXk569+++0/LVgw7HCTTDxeO3hwwYgR3Q4x36YhMzcGSQYA4C93xlVVVWeddVbKtXzhwvKVK7ceMMwcIsnMnLmqT582qbJcTFI0Gs3IyMjIyHDF0nCYJwMA/D2Vl5fPnDkzFVs+Zkz3q65qN3bs8/XfJBLZFARBKsaYgQMHmhuDJAMA8Dd9+vSpqqpK0RcAJMLM4MEFtbWffWHl/PzVc+asmTSpTyrGmNGjR0+YMMHlSoNidBkA8He2adOmG2644fXXX0/R9kcim3btqhk16uK/3WD939Fl8Xjt5Mkvp6enPfjg1Sn37cLh8CWXXJKXl+dCRZIBADjezJjxX1On9ku+hWzfJBOLxcPhpak7xR8aLKPLAICGIhaLpegws6ysC8PhpbFYfL/y8vKKgQOfuu++b6VijIlGo7FYzGVJg5WmCwCAhpNk5s6d26xZs6lTp7Zq1SqFWt6pU4tHH/3u3LlvZmSkX3zx14Lg/3vjje0bNuyqqdn7m9+MzshIT7kTkZ+fH41Gf/7zn7ssabCMLgMAGpZIJDJnzpyXXnopFRt/110rZs9+be/ez0499eQnnhh6ww0Xp+K3GDt27FVXXTVmzBhXIw2Z0WUAQMOSmZmZojFm4MCnHn30zb17PwuCYM+eT++9tzRFT8GCBQvEmOPTM88EzzzzhbVqamp69uwZCoVWrVqVKCkrK2vUqNHQoUNra2sTH6dPn56sHw6HQ6HQk08+OWrUqNBBtGjRYv369YndJsyaNUuSAQCOQ/F4POXmzPzmN6OvvLJdkyanBEHQpMkp//qvV6VW+6PRaDQade0dx3+ogkmTgkmTgnj80BWbNGkSiURuueWWOXPmJKLLe++9N3To0Oeeey4tLS0IgvLy8tNPPz1RubCwsGPHjnV1ddu2bYtGo5s3b965c+c3vvGN3bt379y5c9y4cdnZ2Z9++ukjjzwSi8VKS0vD4fDu3bvr6uoSu5JkAIDjTUVFxeDBg1MuzDz/fNagQR2DYM+gQR2zsy9MoZbHYrGBAweuXr3atXfcevjh4JNPgk8+CR5+uD7Vu3fvHovF/vCHP1RXV//v//7vKaeckiivqanZvHnzySefnAg5HTt2XLx48ZYtW/Ly8latWtWhQ4fkHlq2bDljxowgCNavX9+mTZsrrrhivz/jkgwAcBxq3779ggULUjTMBEHN889npVaz8/Pzc3Nzs7KyXHspbOHCIBQ66H+33x5UVwfV1cHttx+0zj45pFmzZv/yL//y8MMPb9++vU+fv63oWl1d3b179927d//hD38IgqB3797r1q276KKLQqHQtm3bPt+oF1544ZJLLkl+3Lp1a+PGjUOh0C233HIEkkwIgBOMv+5JCZmZmQsWLJgzZ04Ktj0/5VrcrFkzc2NS3pgxQV3dgf+bNSto2vQv1Zo2DWbNOnC1LVv23d/QoUPXrVv30UcfdezYMVm4YsWK7Ozsu+++e/v27YmSli1bVlVVVVdXFxcXf75RQ4cOffvtt5Mf27Vrt3v37uHDh3/1r5sWBIHXlwEADTbMZGZmBkEQi8Xi8XhqvZo5JSQ7durUqXrjuBWPB7/5TfDNfRY1Ki0NpkwJTjrw+Ky9e/cuWrTo1Vdf7dy586RJk0pLS4uLi995552nn376k08+Wb58+a5du95+++077rjj1ltv7dChw9KlS88444wgCDp27FhdXZ2fn19ZWfnQQw/dcsstixYteuedd5599tkdO3a8++67e/fu3bBhw0MPPbR48eJ77723RYsWt95665eeMOMtzABACohEImPHjn3rrbdSIsyEQqlxixWNRgcOHDh+/Pgf/ehHrjFSjiQDAKRMmFm+fPns2bMlmSMYY0aPHp2Xl+fqIhWl6QIAICVkZmZ6R/ARVFxcLMaQ0jyTAQA40jdYIbdYcNR5CzMAkGLKy8tT7tXMDa0DdQKSDADAsRaNRlNxnZmG03tGlHF88OgTAEg9mzZtmj179hVXXDFq1KiGeIPVUEeXRSKRuXPn5ufnt2/f3lWEJAMAQGokGTieGF0GAKS28vLyiooK/XAI0Wi0pKREPyDJAAA0IBUVFSmxyMzfMcYMHDjQC6yRZAAAGpbMzMyqqiovADhEjMnNzR0zZoze4DhjECcAkPI2bdr0q1/9atKkSQ3lBqvBzJMpLCyMx+NiDMclz2QAgJTXqVOnhhNjGpSsrCwxhiAIJr88ORaPJX6O18YnvjjxEJVramp69uwZ+qtZs2YVFhaGQqEnn3wymZA7dOhw8cUXh0KhVatWJTecMGHC0KFDa2trJRkAgMMTiUQMM0uIRqPr16/XDyQM6zws+9nseG08CILsZ7OvPu/qQ1Ru0qRJaWlpOBzevXt3XV1dWlpaVlbWzp07f/jDHyZyS1ZWVmFh4YoVK2655ZY5c+Yko8tZZ5313HPPpaWlHZsvlea8AgDHjU6dOs2ePbtZs2ZTp05t1arVidkJsVgsPz8/Go3OnDnTJXFCKa8oL95YfLDfnhw6uf+C/ulp6Y1OblReUV5ecYDMn5GeManPpOSFNGPGjLS0tAsvvDBR8sgjj6xfv37lypXTpk1LlPTu3Xv9+vXPPvvsiBEj3nrrrUaNGh3L7yvJAADHVZKZO3duJBKJRCIn7Kiq1atXt2/fPi8vz/Vwouneqnv3Vt0PemG8v/rOFXemp6XfdtltmZ0yv3BvGRkZ06dPz87OvvHGGxMlp5566ve///3CwsJp06Z973vfS5Tk5eUNGzasd+/eFRUV7dq1O5bf1+gyAOB4k5mZeSJPDjnBvz4HFI1FJ788eck1S5Zcs+Selfds3LWxnhsWFBQUF/+f5zxZWVmnnXbaf/3XfyU+NmnS5PLLL//JT37SokWLY/ylJBkA4PhUXl5+Qs2ZiUaj+fn5zjsHNPnlyY9+99FWzVplpGcsuWbJF87479+/f1FRUefOnU866aTf/e53oVDo7LPPzs7OTsyTycvLO++88zIzM7Ozs5988slbbrllzZo155xzzk033fTP//zPx2zGv7cwAwDHp02bNvXv3/+ll17q3r37MT70sX8LcywW69Gjx+jRow0q48QhyQAAx61IJDJ27NhjH2aOfZJJBBgxBkkGAOD4CTNBEGRmZh7Lgx77JLNs2bJrr73W6UaSAQA43qxatapTp07H5tXMxyzJxGKxN998c9CgQc4vJyAz/gGAE0JVVVWPHj0qKiqOm28UjUZ79Oix7wrrcELxTAYAOFFEIpHly5fPnj37qN9gHf1nMtFodODAgab4cyKzMiYAcKI4xrNljqpYLDZ+/Pgf/ehHTisnLM9kAACO9A1WyC0WHHXmyQAAJ5yZM2em7qKZy5YtcwZBkgEATkTdu3cfPHhwKoaZaDT6q1/9yhkESQYAOBFlZmaWlpbOnTs3tcJMNBqdMWPGzJkznUGQZACAE1SnTp3mzp3bvXv3FGpz+/btn3jiiWOzJA4nspqamp49e4b+atasWUEQVFZWduvWLR6PH3CTcDgcCoXuu+++bdu2HaJaQmVlZbNmzYYNG7ZvYVlZWaNGjQ7rJRaSDABwolu0aFFDbl40Gp04ceKhbw3h0F6e/HI8Fn9+7PNBEMRj8Zcnv3yIyk2aNCktLQ2Hw7t3766rq0tLSwuCoGXLlu+++256evrn6xcWFnbs2LGurm716tVnn332waolFRUV7dq1q1evXlu2bEkWvvHGG9XV1Yf1yFGSAQBOdKtWrWqww8wS68Z87WtfO/StIRzaJaMvWRpeWr6wPB6LLw0vvWT0JfXfNrGebGVlZdu2bbt27dqiRYstW7YMGzYsma47duy4ePHiLVu2PP/88x9//HHimUxZWdkPf/jDxLOdG264oV27dsn648aNS09Pv+iii5KHKCsrmzJlynnnnVdbW1v/hllPBgA40U2dOrV///4vvfRSQxtsFovFLH9J/ZUvLE88dTmEnzX/WRAE83rMO+BvM9pn3LbltsTPW7dubdy4ceKHIAh+8YtfhEKhefPmRSKRDh063HXXXcl03bt373Xr1nXo0OF73/te27Ztq6qqqqurJ06cuGXLlrVr1z711FNNmzY977zz3nzzzSuuuOJvOSQtrUOHDsk9fPLJJ2VlZQ899NDkyZMlGQCAeunUqdOSJUsyMjIaWsPS09OnTZs2YcIE54j66D6me/cxB03j8Vj8Z81/1n5A+xFFI9IzvvgRX7t27V599dXs7OzExzvuuGPdunW9e/d+6qmntmzZUllZuW/lli1bVlVVzZ8//7LLLlu3bl3Tpk0fffTR4uLiDh06dOnSpXPnzs8/v3/EOuuss/Yr6d27965du+r/fY0uAwAIBgwY0L59+waYZMQYjojEoLIgCK5+8Oql4aXxWH2nXRUUFBQXF+9bMn78+FGjRn39619PlpSVlT3zzDNBEDRt2nT79u312W1eXt7evXsLCwv3K//ss8/q/6VO9rASACBp9uzZzz333MUXX9ysWbMvvZN77rnnq9xixWKxmTNnFhYWfuc73wmFQk4KX93G4o39pvY7vc3pXYZ36ZTZafPyzWdfePbBKu/duzcxJOydd97p16/fBx988OKLL5522mmxWOzMM8/85je/ee655/br16+mpubxxx+/9NJLTzrppE2bNhUXFzdu3Lhr164ffPDBmWeeuWnTpg8//LBNmzYbNmxo1qzZjh07qqurX3vttZ49e/7yl7/ctWvX5s2bhw4dmpaW9vjjj3/00UfPPPNMSUnJiBEj6j8lLFRXV+fUAgAkRSKRsWPHvvXWW1/6fceh0Je/xUpM8Tc3BiQZAIDDVlJS0r179y89c+arJJlYLFZcXDxmzBhnASQZAIBje4MVcosFR50Z/wAABzZ27Nhjts5MNBoNh8P6HCQZAICvasSIEYMHDz4GYSaxbsywYcP0OdSfR58AAAeVmP1/uItmHu7osry8vPbt25sbA5IMAMAR8yVm/x9uktm4cWOXLl10NRwWo8sAAA5lwIABiRizaNGiioqKI7jnWCy2cOHC2tpaMQYkGQCAo+Wss87q0aPHkQoz0Wi0R48eQRCkpaXpW/gSjC4DAKivSCRSUlIyc+bML7jB+qLRZRUVFX379s3NzTU3BiQZAIBjIRqNtm/f/ismmSAISkpKBgwYoD9BkgEAaDA3WFbGhKPPPBkAgMMTj8f79u375daZmTnYmI/qAAAU6ElEQVRz5pF9bQBIMgAA1Et6enpubu6XWDQzGo2uXr26VatW+hAkGQCAv4PMzMzS0tJFixbFYrF6bhKPx/Pz8/Pz8/UeHBEGcQIAHOkbLPNk4OjzTAYA4CuJxWLTp08/2G+j0WjXrl03btyoo0CSAQBoQDIyMnbt2nXAOTPRaHTgwIEjRozo0qWLjoIjy6NPAICvatOmTf3793/99dcTS80kRpfF4/GuXbuOHj06Ly9PF4EkAwDQEJWXl3fv3v0vN1h/nSdj+UuQZAAAUucGy4x/OPrMkwEAOGJqa2snTZoUBMFNN920Z88eHQJHj38wAAA40jdYnsnA0eeZDAAAIMkAAABIMgAAKSfxLmbgqDKIEwAASD2eyQAAAJIMAADA0ZemC1JIKBTSCcARYWgxACl/b+wvMwAAIOUYXQYAAEgyAAANUjgcDoVC/fr1q0/lysrKOXPmHL3GVFZWtm3bdsuWLfXfpKys7LrrrqutrXUqQZIBAE4gRUVFubm5v/jFL+pTedy4cXv27PmKR1y7dm08Hj9gYcuWLbdt29ahQ4f67Oexxx774IMPJk6c+MknnziPIMkAABxUQUFB69atv+JONmzYUM/CQ6ipqYlEIk2bNo1EIs2aNXNqQJIBAE5QiWFa06dPD4VCOTk5eXl5nTt3fu2116677rohQ4aEQqGhQ4cmB3ElxqQlShIbXnnllYmtkuXhcLhz587JComd5OTkFBcXt27desaMGaFQKBQKtWvXLh6PJwrXrFnTrVu3xBObxCFycnL22zzRgBdeeKGoqKh169abN29OVE4MkNu3Yc4pkgwAwHHu008/ffXVVzdu3BgOhz/88MPly5d/97vfnTJlygMPPPC73/3uoYceqquru/jii5966qkgCB5++OHmzZvn5ub++c9/vu+++xIbLly4MLFVdXX17t27c3Jymjdv3rdv32SFhx566MMPP3zjjTf+4R/+YceOHdOnT3///ffvvvvuZs2a/fGPf/z2t7+9Y8eO//7v/z7ttNOCIJg+ffpll11WW1u7Y8eOu+66a9/NEznn8ssvD4fDO3bs6Nix43vvvffQQw/dcMMNs2bNSjZs9uzZTisnJuvJAAAnkJNPPnnUqFFvvPHGJZdcsmfPnvPOO++iiy5at27dNddc89xzz7Vp0yYIgnfffbd///67du3atWvXjTfeeMUVVyS2raysfOONN84999zEVp999lmi8Oabb07USVRo06bNnj17zjrrrMaNGwdBkJeX99vf/va5557bvn17EARNmjQJguCaa64pKioKguDCCy+cNm3a1KlT4/H4zTffvGzZsuTmiYOeeeaZycZ37ty5TZs2p512WjQa3bdhcIKqAwA4AQwfPjwIgr59+yZ+mD9/fm5ubhAEU6ZMueaaa3r27Hnqqacm7o6mTJmSm5vbt2/f5FaJ+omfH3jggUSdJUuWJH5I7nC/Pf/TP/1T8+bNs7Ozk/ddbdu2ffDBB5OFU6ZMSR7i85snfltdXX3ppZc2b968S5cuid9eddVVyYMmSpxcTkxWxgQACMrKymbNmrVkyZK0NCNWIDWYJwMAnOj27t07ceLEZcuWPf3003oDUoVnMgAAQOrxTAYAAJBkAAAahvfff/8o7Xnt2rXJVVyqq6sffPDB3bt3f75aQUFBXl7ekiVLEm85OyJNXbt27RfuDSQZAIBUVVNTs3LlyqOx57179/70pz9NJpmmTZtOnjw58cLl/Xz66ad5eXnZ2dknnXTSEWlqTU3NT3/6U0kGJBkA4Lj1wgsv3HTTTWvWrLn++uuHDBkS+qtZs2aVlZVdd911icKcnJwgCCZMmDBy5Mi1a9fu+6uCgoJwOJzYKicnp7KyMrGru+++u6ioqHXr1lu2bAmCoLKyslu3blu3bt1vn3l5eaNHjx45cmRiq6FDhz7zzDOhUCgjIyMej5eVlTVq1Chx0M83NScnp7CwMBQKbdu2LdGGdu3axePxF154oaio6JRTTklWWLVqVbJhtbW1icpDhw5NBi04nnkRNQBw/CkvL3/yyScvvfTSIAhKS0sThdXV1bNmzUoW7ty58xvf+Mbu3bufeuqpJUuWPPvss02bNk3W/8d//Md9V3RJ3DiVlpb+8Y9/DIfDu3fvTi5Tk1glZr991tXVPf744/s1oK6u7oknnti8eXNubm5paemSJUtKS0v3a+qaNWvuvPPOurq63Nzcp556KrFczPDhw+fPn19eXh4Oh6PRaLJCJBJJbLh169bE3hLlFpnhROCZDABwHDr//PNPPfXUSCSSnZ3dp0+fIAjKysqaN2++a9euZGHTpk07d+4cBMGf//znm2++uUePHr/+9a+vvfbaRP3TTz+9W7duQRA0adJkyJAh9957b2KrM888c98DFRQU9OzZc+zYsfvtMwiC/RqQaMNtt90WBMEdd9xx22233Xzzzeeee+7nm5pUUVFxwQUXBEFQVFR04403nn/++ft9zaZNmyY2bNOmzcaNG/v37x8Khe655553333XNcBxT5IBAI5/eXl5M2bMqK6u7tq16+d/26tXr0ceeeThhx/etzA9Pf2ee+6Jx+NBELz99tvJfPIV2/DMM88EQbBo0aJXX3318wfdz8qVK4uKig5RYeTIkfu+bCD58Of+++930jn+eSwFABx/qqurO3To0KVLlyAIpkyZkpubm7jzOeOMM66++uogCObPn58onDJlyrXXXhv8dWTXqaeemqgZiUSGDx+e+Hn+/PmJn6dMmbJnz55LL720efPmmzdvTgzlCoJg7Nix++1zyZIlydutxCi1ZBvatm372GOPJQ5UWlq6X1N37tyZGOQWBMGmTZuSA9vmz5+fGOf2gx/8IFmhtLQ00bBIJJIYhJas7BrguGdlTACAvygrK5s1a9aSJUvS0tL0BjRwRpcBAARBEOzdu/ett97q1q3bO++8ozeg4fNMBgAASD2eyQAAHNihl2eprKxs27btli1bKisr58yZk/yYrDBjxox9Px5QYqsPP/xQb8Ph8kwGAOAA1q9fX1ZWduONN9Yn8PTr1+/2229Pljz22GPf//7309PTdSMcPZ7JAAAcwK5duxJruXyhgoKC1q1bJz/W1NREIhEdCJIMAMDfQV5eXv/+/XNycgoLC0OhUCgUateuXTwe79q1a+KHysrKbt26JRacCYIg+fGFF14oKipq3br1XXfdlfhtcpTaa6+91qNHj7Vr1yaPkthq69at11133ZAhQ0KhUE5Ojs4HSQYA4MsnmdLS0vvvvz8rKyuxQM0FF1xw4403Ll68+NJLL128ePG4ceOqqqqS9ZMfu3btGg6Hd+zY8etf/zoIgsLCwpycnLq6uksvvfTyyy//6U9/uu9alomtioqKli1bNm3atJ07d0YikWQ6Ag7Bu9IBAA6lpKTkzTffrK6urq6urq2t/eyzz4qKioIgyMrKGjVqVLJaQUFB4uP555+fKPnBD34QBMHGjRtfeeWV5cuXJ9NR9+7d99tq7NixZWVlffr02bNnT+fOnfU5SDIAAF/Sww8//Oyzz5aWlpaUlNxzzz2JwubNm2dmZu7atWv+/Pnbtm0rKir68Y9/fNppp73yyiu///3vEx9/8pOfbN26tXXr1ueee+5bb711//33h8PhBQsWBEHQs2fP8vLykpKS5FF+/vOfFxUVZWRkLFmyZNCgQcl93n///U4BHJp3lwEAAKnHPBkAAECSAQAAkGQAAAAkGQAAQJIBADhRVVdXP/jggx9++OEh6qxdu7a2trY+Nffz5JNPnn/++bW1tfoZDsa7ywAAjoq9e/eOGDFi8eLF6enph7ttTU3NqFGjfvnLX6alWTMDDswzGQCA/6OsrOy6667r3LlzTk5OYWFhKBQKhULt2rWLx+PhcLhfv36VlZXNmjUbOXJkt27d4vF4WVlZWlpaKBQaOnRobW1tcpObbrqpqKiodevWa9asSdQMgqBr166hUCgnJyd5oCFDhvTr12+/AzkLIMkAAByGmpqaiRMnLlu2rLi4OBKJDB8+vK6urrq6+oILLvjjH/9YUFCQlZXVsmXLBx544IMPPqiqqgqCYPPmza+99tqgQYPmzJmTlpaWlZWV2KR169bhcHjHjh0zZ85M1CwsLMzPz6+uri4pKXn55ZcTB5o2bVo4HN7vQE4ESDIAAIehSZMmkUgkOzu7Y8eOnTt3DoKgrKysefPma9euTfx27969lZWVp59++nPPPdezZ88gCIYOHTp8+PDGjRt//etfT+wkscmePXsSHwsKChI1ly5devbZZzdp0mTIkCHbt29PHKhPnz7nnHPOfgcCvpCRlwAAB5Wbm7thw4bq6urx48cnSjIyMn72s5/NmDHjs88+S5S88MILq1evbtu2beJjXl7eb3/72+rq6gULFmzZsmXfvY0YMWL58uU9evR4++23Bw0adOgDAZIMAMBhGDduXHFxca9evYqKihIlp5xyShAEy5cvf++99y677LJQKJSenp6Xl1dUVPTjH/+4V69e7dq1C4Jg/vz5N954YxAE//Ef/3HKKaekp6e3b9++devWmZmZiZr3339/165d77jjjvnz519xxRXhcLi4uHjQoEFPP/30ypUr9z1QVlZWUVHRihUrrr76amcEDsi7ywAAvpKSkpIrrrhiz549ixcvvummm3QISDIAACmgsLBw48aNjRs3HjduXPPmzXUISDIAAAAH5t1lAAD7q6ys/Nd//df6V54zZ84ROW5ZWVmjRo2SS8q89tpr+70zAJBkAAAOqmXLlv/2b/9Wz8rjxo1LvnA56bHHHqutrT3c4953330rVqwYO3bs4sWLgyA4+eSTO3To4HSAJAMAcOQVFBS0bt1635KamppIJPLV91xZWal7QZIBADiUxMiukSNHrl27NjFgrKys7Lrrrps+fXooFMrJycnLywuFQl//+tdzcnIKCwtDodCqVauSmydKQqFQu3btli5dWlRUNH369HA4nCjMyclJJJNrrrkmUZI40H5tuPPOO7/1rW8tWLDg+uuvLywsvPjii50XkGQAAA7lP//zP1esWDFkyJDdu3ePGzeuurp64sSJy5Yt69ix486dO+fNm9e2bdvq6urs7OxGjRplZWXl5ubuu3lWVlZdXV11dfUFF1xwxhlnhMPhrKysjh07JgpLSkpefvnlzMzMM844Izc3t7S0NHGg/drQu3fvTz75ZOvWrR9//PGGDRvmzZvXokULU2VAkgEAOKjMzMy33377xRdf3L59e0FBQbt27SKRSHZ29ve///2mTZt++9vfvv766/fb5Nlnn01OhikpKZk9e/asWbMSYSYIgp07d1ZWVtbW1jZp0qRXr17xeDwSiQwePHjfAx2wJevXry8qKrr77ru7dOnyyCOPPPzww84OfF6aLgAACILg97///ZQpU/bs2TN+/Pif//znr7zyyrJly4qLiwcNGrRt27aioqIf//jHvXr1ikQimzdvvu+++4IgKC0tTUtLmzFjxiuvvPLtb3/7nnvuSezqyiuv/NrXvvbrX//6448/PuWUU4IgmD9//rBhw8Lh8J/+9KeJEycmD1RYWHjzzTf/z//8T3IhmrKysuLi4nvvvTcIgo8++ujWW28tLS11duDzrCcDAPD3VFZW1rp16zZt2ugKOCxGlwEA/D1jzKxZs/Z79RlQH57JAAAAqcczGQAAQJIBAACQZAAAACQZAABAkgEAAJBkAAAAJBkAAECSAQAAkGQAAAAkGQAAQJIBAACQZAAAACQZAABAkgEAAJBkAAAAJBkAAABJBgAAkGQAAAAkGQAAAEkGAACQZAAAACQZAAAASQYAAJBkAAAAJBkAAABJBgAAkGQAAAAkGQAAAEkGAABAkgEAACQZAAAASQYAAECSAQAAjg9pQRCEQiEdAXBCqaur0wkApLSQv8wAAICUY3QZAAAgyQAAAEgyAAAAkgwAACDJAAAASDIAAACSDAAAIMkAAABIMgAAAJIMAAAgyQAAAEgyAAAAkgwAACDJAAAASDIAAACSDAAAgCQDAABIMgAAAJIMAACAJAMAAEgyAAAAkgwAAIAkAwAASDIAAACSDAAAgCQDAABIMgAAAJIMAACAJAMAACDJAAAAkgwAAIAkAwAAIMkAAACSDAAAgCQDAAAgyQAAAJIMAACAJAMAACDJAAAAkgwAAIAkAwAAIMkAAACSDAAAgCQDAAAgyQAAAEgyAACAJAMAACDJAAAASDIAAIAkAwAAIMkAAABIMgAAgCQDAAAgyQAAAEgyAACAJAMAACDJAAAASDIAAACSDAAAIMkAAABIMgAAAJIMAAAgyQAAAEgyAAAAkgwAACDJAAAASDIAAACSDAAAIMkAAABIMgAAAJIMAAAgyQAAAEgyAAAAkgwAAIAkAwAASDIAAACSDAAAgCQDAABIMgAAAJIMAACAJAMAAEgyAAAAkgwAAIAkAwAASDIAAACSDAAAgCQDAAAgyQAAAJIMAACAJAMAACDJAAAAkgwAAIAkAwAAIMkAAACSDAAAgCQDAAAgyQAAAJIMAACAJAMAACDJAAAAkgwAAIAkAwAAIMkAAABIMgAAgCQDAAAgyQAAAEgyAACAJAMAACDJAAAASDIAAIAkAwAAIMkAAABIMgAAgCQDAAAgyQAAAEgyAAAAkgwAACDJAAAASDIAAACSDAAAIMkAAABIMgAAAJIMAAAgyQAAAEgyAAAAkgwAACDJAAAASDIAAACSDAAAgCQDAABIMgAAAJIMAACAJAMAAEgyAAAAkgwAAIAkAwAASDIAAACSDAAAgCQDAABIMgAAAJIMAACAJAMAAEgyAAAAkgwAAIAkAwAAIMkAAACSDAAAgCQDAAAgyQAAAJIMAACAJAMAACDJAAAAkgwAAIAkAwAAIMkAAACSDAAAgCQDAAAgyQAAAEgyAACAJAMAACDJAAAASDIAAIAkAwAAIMkAAABIMgAAgCQDAAAgyQAAAEgyAACAJAMAACDJAAAASDIAAIAkAwAAIMkAAABIMgAAAJIMAAAgyQAAAEgyAAAAkgwAACDJAAAASDIAAACSDAAAIMkAAABIMgAAAJIMAAAgyQAAAEgyAAAAkgwAAIAkAwAASDIAAACSDAAAgCQDAABIMgAAAJIMAABAfYV0AcAJqK6uTicAkNL+H/8zbO3SBCqdAAAAAElFTkSuQmCC)
3 USING THE SC-METHOD TO ASSESSING
EFFECTIVENESS OF MARINE
NAVIGATIONAL SIMULATORS FOR
TRAINING RIVER SHIPMASTERS
A detailed analysis of evolvents of "the Safety
Cube" allows detecting individual features of
navigational simulators which are used in training
centers for training navigators. Knowledge the
differences and shortcomings of navigational
simulators from different manufacturers may help
decision makers (managers of shipping companies,
leaders of basins, etc.) to plan effective teaching
and/or retraining of crew for the operation vessels
in specific inland water basins.
In particular, using the above evolvents can be
convincingly argued that in modern navigational
simulators the transport infrastructure facilities
such as vessels and hydrotechnical constructions
(waterworks) are presented to a limited amount
and does not fully reflect the real diversity of
existing types of vessels and waterworks of the
Russian Federation inland waterways. Also, a
number of simulators, which was originally
designed to prepare the skippers of marine vessels
are absent or are not modeled in full amount
typical parts of inland waterways (rifts, canals,
etc.).
Table 4. Percentages of implementation the transport
infrastructure facilities of RF inland waterways in
navigational simulators with standard kit
Navigational
simulators for
RF training
centers
Percentage of implementation the transport
infrastructure facilities in navigational
Vessels
nical
constructi
e parts of
the inland
In total
«NTPro» 55.5% 20% 64.3% 53.6%
«MARLOT» 22.2% 20% 50% 35.7%
«MASTER» 44.4% 0% 57.1% 42.8%
«RNM» 22.2% 60% 35.7% 35.7%
«Riv.Sim. 2.5» 22.2% 0% 35.7% 25%
Except qualitative assessments, using evolvents
of "the Safety Cube", there is possibility to obtain
quantitative expert estimates. For example, in
Table 4 shows the percentages of implementation
the transport infrastructure facilities of RF inland
waterways in navigational simulators with
standard kit, obtained from the results of statistical
processing the information from the evolvent XZ.
For clarity, the data of Table 4 can be
represented graphically by plotting values of the
calculated parameters on the axes of the polar
coordinate, as shown in Figure 2.
The data in Table 4 allow confirming with
quantitatively mentioned above qualitative
conclusion about the absence of a complete list of
transport infrastructure facilities in modern
navigational simulators which are used for training
and retraining shipmasters and navigators for
inland waterways
On average over all navigational simulators in
Russian training centers, are able to simulate only
38.6% of objects from inland water transport
infrastructure! In turn, officials of shipping
companies which are responsible for the safety of
navigation can make a reasoned conclusion about
the low efficiency of use of modern marine
navigational simulators for training river
shipmasters, intended for testing skipper’s skills in
different shipping conditions on inland waterways.
Figure 2. Percentage of implementation the basic groups of
the transport infrastructure facilities in navigational
simulators with standard complectation
4 CONCLUSIONS
Thus, the SC-method as a variation of methodical
apparatus "the Safety Cube" really allows
implementing a way of evaluating the effectiveness
of the navigational simulators for training
shipmasters to control vessels on inland waterways
in Russian Federation. Thus, the introduction of
SC-method will contribute costs optimization to
simulators, will increase the quality of training
navigators by rules for necessary adaptation and
eventually will decrease the number of accidents
and crashes on the inland waterways.
485