MIME-Version: 1.0 Content-Disposition: inline; filename="document.html" Content-Type: text/html; charset="utf-8" Content-Transfer-Encoding: quoted-printable Content-Location: document.html </title= ><style type=3D"text/css">@page Section_1 { size:595.3pt 841.9pt; margin:12= 7.6pt 85.05pt 70.9pt }div.Section_1 { page:Section_1 }body { text-indent:36= pt; line-height:108%; font-family:'Times New Roman'; font-size:12pt }h1, h2= , h3, h4, h5, h6, p { margin:0pt 0pt 8pt }li, table { margin-top:0pt; margi= n-bottom:8pt }h1 { margin-top:12pt; margin-bottom:0pt; text-indent:36pt; pa= ge-break-inside:avoid; page-break-after:avoid; line-height:108%; font-famil= y:'Times New Roman'; font-size:12pt; font-weight:bold; color:#000000 }h2 { = margin-top:2pt; margin-bottom:0pt; text-indent:36pt; page-break-inside:avoi= d; page-break-after:avoid; line-height:108%; font-family:'Calibri Light'; f= ont-size:13pt; font-weight:normal; color:#6d1d6a }h3 { margin-top:2pt; marg= in-bottom:0pt; text-indent:36pt; page-break-inside:avoid; page-break-after:= avoid; line-height:108%; font-family:'Calibri Light'; font-size:12pt; font-= weight:normal; color:#481346 }h4 { margin-top:12pt; margin-bottom:2pt; text= -indent:36pt; page-break-inside:avoid; page-break-after:avoid; line-height:= 108%; font-family:'Times New Roman'; font-size:12pt; font-weight:bold; font= -style:normal; color:#000000 }h5 { margin-top:11pt; margin-bottom:2pt; text= -indent:36pt; page-break-inside:avoid; page-break-after:avoid; line-height:= 108%; font-family:'Times New Roman'; font-size:11pt; font-weight:bold; colo= r:#000000 }h6 { margin-top:10pt; margin-bottom:2pt; text-indent:36pt; page-= break-inside:avoid; page-break-after:avoid; line-height:108%; font-family:'= Times New Roman'; font-size:10pt; font-weight:bold; color:#000000 }.Heading= 7 { margin-top:2pt; margin-bottom:0pt; text-indent:0pt; page-break-inside:a= void; page-break-after:avoid; line-height:108%; font-family:Calibri; font-s= ize:11pt; font-weight:normal; color:#595959 }.Heading8 { margin-bottom:0pt;= text-indent:0pt; page-break-inside:avoid; page-break-after:avoid; line-hei= ght:108%; font-family:Calibri; font-size:11pt; font-weight:normal; font-sty= le:italic; color:#272727 }.Heading9 { margin-bottom:0pt; text-indent:0pt; p= age-break-inside:avoid; page-break-after:avoid; line-height:108%; font-fami= ly:Calibri; font-size:11pt; font-weight:normal; color:#272727 }.APA7MAEDICI= ON { margin-bottom:8pt; text-indent:35.45pt; text-align:justify; line-heigh= t:200%; font-size:12pt }.BalloonText { margin-bottom:0pt; text-indent:36pt;= line-height:normal; font-family:'Segoe UI'; font-size:9pt }.Bibliography {= margin-bottom:8pt; text-indent:36pt; line-height:108%; font-size:12pt }.Ca= ption { margin-bottom:10pt; text-indent:0pt; line-height:normal; font-famil= y:Calibri; font-size:9pt; font-style:italic; color:#632e62 }.CommentSubject= { margin-bottom:8pt; text-indent:36pt; line-height:normal; font-size:10pt;= font-weight:bold }.CommentText { margin-bottom:8pt; text-indent:36pt; line= -height:normal; font-size:10pt }.Default { margin-bottom:0pt; text-indent:0= pt; line-height:normal; font-size:12pt; color:#000000 }.Footer { margin-bot= tom:0pt; text-indent:36pt; line-height:normal; font-size:12pt }.Header { ma= rgin-bottom:0pt; text-indent:36pt; line-height:normal; font-size:12pt }.Int= enseQuote { margin:18pt 43.2pt; text-indent:0pt; text-align:center; line-he= ight:108%; border-top:0.75pt solid #6d1d6a; border-bottom:0.75pt solid #6d1= d6a; padding-top:10pt; padding-bottom:10pt; font-family:Calibri; font-size:= 11pt; font-style:italic; color:#6d1d6a }.ListParagraph { margin-left:36pt; = margin-bottom:8pt; text-indent:36pt; line-height:108%; font-size:12pt }.NoS= pacing { margin-bottom:0pt; text-indent:36pt; line-height:normal; font-size= :12pt }.NormalWeb { margin-top:5pt; margin-bottom:5pt; text-indent:0pt; lin= e-height:normal; font-size:12pt }.Quote { margin-top:8pt; margin-bottom:8pt= ; text-indent:0pt; text-align:center; line-height:108%; font-family:Calibri= ; font-size:11pt; font-style:italic; color:#404040 }.Subtitle { margin-top:= 18pt; margin-bottom:4pt; text-indent:36pt; page-break-inside:avoid; page-br= eak-after:avoid; line-height:108%; font-family:Georgia; font-size:24pt; fon= t-style:italic; color:#666666 }.Title { margin-top:24pt; margin-bottom:6pt;= text-indent:36pt; page-break-inside:avoid; page-break-after:avoid; line-he= ight:108%; font-size:36pt; font-weight:bold }span.AsuntodelcomentarioCar { = font-size:10pt; font-weight:bold }span.CitaCar { font-family:Calibri; font-= size:11pt; font-style:italic; color:#404040 }span.CitadestacadaCar { font-f= amily:Calibri; font-size:11pt; font-style:italic; color:#6d1d6a }span.Comme= ntReference { font-size:8pt }span.Emphasis { font-style:italic }span.Follow= edHyperlink { text-decoration:underline; color:#666699 }span.Hyperlink { te= xt-decoration:underline; color:#0000ff }span.IntenseEmphasis { font-style:i= talic; color:#6d1d6a }span.IntenseReference { font-weight:bold; font-varian= t:small-caps; letter-spacing:0.25pt; color:#6d1d6a }span.PlaceholderText { = color:#808080 }span.Strong { font-weight:bold }span.SubttuloCar { font-fami= ly:Georgia; font-size:24pt; font-style:italic; color:#666666 }span.Textocom= entarioCar { font-size:10pt }span.TextodegloboCar { font-family:'Segoe UI';= font-size:9pt }span.Ttulo1Car { font-family:'Times New Roman'; font-size:1= 2pt; font-weight:bold }span.Ttulo2Car { font-family:'Calibri Light'; font-s= ize:13pt; color:#6d1d6a }span.Ttulo3Car { font-family:'Calibri Light'; font= -size:12pt; color:#481346 }span.Ttulo4Car { font-weight:bold }span.Ttulo5Ca= r { font-size:11pt; font-weight:bold }span.Ttulo6Car { font-size:10pt; font= -weight:bold }span.Ttulo7Car { font-family:Calibri; font-size:11pt; color:#= 595959 }span.Ttulo8Car { font-family:Calibri; font-size:11pt; font-style:it= alic; color:#272727 }span.Ttulo9Car { font-family:Calibri; font-size:11pt; = color:#272727 }span.TtuloCar { font-size:36pt; font-weight:bold }span.Unres= olvedMention { color:#605e5c; background-color:#e1dfdd }</style></head><bod= y><div class=3D"Section_1"><div style=3D"clear:both"><p><span style=3D"heig= ht:0pt; display:block; position:absolute; z-index:-65537"><img src=3D"data:= image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAUDBAQEAwUEBAQFBQUGBwwIB= wcHBw8LCwkMEQ8SEhEPERETFhwXExQaFRERGCEYGh0dHx8fExciJCIeJBweHx7/2wBDAQUFBQcG= Bw4ICA4eFBEUHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4= eHh7/wAARCARdAzMDASIAAhEBAxEB/8QAHQABAQACAwEBAQAAAAAAAAAAAAECBwUGCAMECf/EAE= 8QAQABAwIBBwgGBgcFBwUBAAABAgMEBREGBxITITGT0RUXQVFTVFWSCBYiYZTSFDJxgZGhIzY3U= nR1sjNicrHBGCQ0Q1aCsyU1QuHwJ//EABsBAQEAAwEBAQAAAAAAAAAAAAABAgMEBQYH/8QANBEB= AAEEAQQABQIDBwUAAAAAAAECAwQRUgUSFCETFTFBUSJhNEKBJTI1caHB8DORsdHh/9oADAMBAAI= RAxEAPwDoEoso/S4fFQAAAIAAv2ABYABUlFlBJABYEVEJ19wWiiuuqKaKaqqvVEbvt+hZu3/hMj= u5Saoifcsopmfs+A+t3Hv2aYqvWLtuJ6t6qJpfLrWKok1O/f2ElUlWKAASiygAJ1+kWPpv8Kkqk= ioAAACSiyigAgSiyhAAEgk9ipPYCAKACKkn7SVppmqqKY7ZWEmfu+2Ja6SvnTH2YfvYWqIt0RTD= NYcdyvcgCsQBJVJRZRAAAJCRYQAQAGQAAAEAAySpCe0Yyyj0AIyRjVLKeqGFUbsK5bKYRNl7Dfd= g2bQ9C7ER1obIjaBZRlDHYAkrBsikiomyho2xFQB8rs7y+lc7UvjLGqViEAa2WyUUk0u0WiN5+5= PS+1FO1PWtNO5SZ9MokNht7YYPvKLKOmHPAAAAgAC/YA9OwsB6N37dF0rUdZ1C3gaZiXcrJuTtT= RRH859UNycOfR31jLxova1q9jBrqp3i3aom5VTPqnfaP4buTIzLNj/qVadFrHuXf7kNGz2u98Jc= lXFPEvDWTruFjxTZt0zVZoriYqyNu3mO2anyM6pwlq+Jq+Tap13RrF2Ksq1Y6rvMj0zTPo7OyZe= juF9Q0jU9FxsnRblqrD5kRRTRG3M2j9WY9Ex2bPLz+r9lMTY9/v8A7O3G6f3VT8X08G5Ni9jX67= F+3Vbu26ppqpqjaYmPQ+b1Xy48k2PxLj3Nb0K3TZ1eiJmu3EbU34/6VPLWZjZGHk3MbKs12b1uq= aa6K42mJj0PRws6jLo3H1+8OTJxqrFWp+j4s8ezXkZNuxajeu5XFFMeuZnaGDsXJlYoyuP9Gs3I= 3oqyqZmP2bz/ANHVdr7KJqj8NNFMV1xEvUPJRyYaFwvoNi7mYOPmandoiu9dv24rmiZ6+bTv2bd= nU5LL445OcXJrx72r6NFy3PNmIqonb7n05aM/I03k01jIxq6qLk2JoiqnqmOd1f8AV4mqmaqpqq= neZ7Z9b5bBw6s+arldUvbyMiMXVFNL0Zy1cS8D63PDNnAztOyrVvV7deVTammf6LaYnfb0Ov8AL= 7PJzPDuH9WbeDTqHTztOLTt9nq3523V+zdrDk6pirjvRIqiJic61ExPp+3D0l9JXS4zeEMDCxLF= um9kZ1u3TtTEdcy67lFOHetW9zP1+7TRVORbrq9PJ9MVVTEREzMztHV2vpXjZFMTNVi5ERG8zNM= 9T2dofDfDPJzwj01On1X6rNETduW7E3Lt6r9kQ65q/Krw9VpmVR9U+IKd7VX2qtM2iOr17tlPWK= q6tW7e4/za56fTTG66tS8p049+qmKqbNyqPXFPalyzetxvctV079m9Oz2nyTxh08lOjZl3Gt82n= C6Sre3G+0by+PBfH3BfGmfe0vTLUVXqbc1VUXceIiqnsljPW657pi36j9//AIy+XUzqO76vFxRR= VXO1FM1T6o63oXibkr0rN5dMbTsW1FjS7+N+mX7VEbRExVMTTHq32/5tocR69wLyc4OJh5tmxiU= XImLNq3Z3mYiO3/p+9ur6xT+mLdPdM/Zrp6fPua51EPG2nWLdvUMavUrNynD6Wnpvsz+rv19jdv= LVPJpPANEcO2tNjUent8ycaiIr25tW++3o/a5fj7lN4N4p0rE0jR7dz9Luahj1Rz7EUxzYriZ63= ZfpI49i1yU1XKLFumqL9rrppiJ7Jc1zLruXbU10zTO9a230WKaKKopmJeToxsiYiYsXJifTzZYX= Ldy3O1dFVM+qYeo+D+VrhenhzTsW1w5rWXXj4tu1crsYEV0zVTTFM9cT64d34Y1fh7jrAzLHkHK= x7dG1Ny1nYfRTVE77bev0ttzq921M99r1H7tdOBTXEdtX+jxCO4csXDmPwrygajpGJExj0zFy1T= P/AONNUbxH7odPe1auRdoiun6S8+5RNFU0yANjBJRZRQAQJRZQgACQSexUnsBAFABFSX68K1tHS= THX6Hws25uXIj0elyURERFMR1QsNF2vXoAWHMAKoAkqkosogAAEhIsIAIADIAAACBJViSygAYyo= CVSkyyhJ7UkGlv16RGSbBCdawQpBMpKLKMtIAIsBISKgAgDGuerZJZQ+dc7z1MJiWe2yNUsmAym= E2DRCVLHYTG4q243nf1PqUxtT1DbEaYbABX3lFlHTDmgAAAQABfsP26FpeXrOr4+l4FqbuRkVxR= RTHp39L8Tcf0UNPx8njnLzL1NNVzFx/wCjiY9NUzvP8oc2Xe+DZqrj7Q341r4tyKfy3hyWcA6Zw= RoNu3TbtXdRqpicnKmOuqfVHqh1rlF5b9F4bz69N0zG8qZdura5VTXzaKJ9W/pl9/pI8X5fDXCV= vE06uq3lahX0PSRO3Mo2mZ2/ht+95LqqqqqmqqZmqZ3mZntl8/07AnMmb9+dvXy8mceItWnqjkz= 5btL4n1CNJ1nFo07Ku9Vqrnb27n3dfZLmNe0XUODdVu8T8K2Kr+n3Z5+o6ZT2THpuW/VPp2ePqK= qqK4romaaqZ3iYnbb729eTXl2nS+HbuBxNRdy8jHtf91u0xMzc6uqmrxbczpU2p78eNx94a8fOi= v8ATcn3H3egeG9b0/X9Ktajpt6LtquOuPTTPpiY9Etcct/JRj8V4lzV9Ht02NYt071REdWREeif= 9772mOBeVDUtG4+yNXmmLen6jkb5WJRG1ERPZNMeiXr3Fv2snGt5FiuK7VymKqao9MT2S8y9Zvd= OuRXTP1/5p227tvLoml/P7Mxr+HlXcXJt1Wr1qqaa6Ku2Jh+7hLP8l8T6dqG+0WcmiqqfVG/X/J= ub6VPBmPhZGPxXgWabcZFXR5XNjtr9FX7Z7P3NCT2/c+rxr9OXYir8vCvW5x7uvw93cR6di8X8G= 5GDTdiLOoYv9Hcjr5vOp+zP7t93mDM5C+PLOTct2sTGvW6ZmKa4u/rR6+xnyZ8s+t8JYFGl5din= UcGj/Z011TFVuPVE+p3yPpI4X/p7I+ePF4lnHzsKqabcbiXpV3cbIiKq51LXmm8n3EvB/F3DuZr= eNas2r+p2rVE0187ernb7fyb95b8uzgYegZmRMRas6tZrrmfVu01yhcsuNxRe0O5a0i9YnTNQoy= 5iqqPtxETvEdb8nK9yu0ccaDZ0rG0qvFii70lVdyuN+rs22lsuY2Vk3KK7ka1vbGi/Zs01RTL1H= r2oZGn6RczsPAuahXbp53Q2qtqqo+7qndq3ivlPz7/DWpWK+BdZs0XMa5TNyvso3pnrnqa74A5e= dV0LSbWmavheUrdmmKbd7nbXNo9E+v8Aa5/VvpFY2RpuTYs8P3ouXLVVNE1VxtEzHVv1uOjpl63= XqaO799uirMt10+qtNl8mdU1ciWmzMbb6XVP8qmj/AKKf9ot//C1OQ4a5csTSeCcfh+vRL1y5ax= ZsTciuNpmYnr7fva/5JeNI4I4onVq8Ocq3Vbqt1UUztMb9kw68fBv02r1M0+6vo57mTbm5bmJ9Q= 9O5eZZscuOLjXZiK7+lbW5mfTFVXV/N0L6T3BPEmv6vpmo6Jp+TqFu3aqt10WaedNE7xPZ6uprP= lG5T8riLjHT+ItJsXNOvYVumm3M1RNW8TM9f3dbvmjfSQvW8OijVdBi5kRERVXZriIq+/aWq3g5= WPVRdojc6+jZXlWb0VW6p9NZaZwTxZoes6bqGr8P5+Fi05lqmbt23tTEzVG0bvSPL9j0ZfJ5jYt= ydqLubYoq/ZO8S1Pyg8uePxLoNGn2NFu2LlGTavxVXVHNnmVb7dU+l+TlM5abfFfCtGj4uk3MW9= TeoudLVXG0c2J7Ov1t921l5Ny3XXTqYmWu1XYs01U01behM79C4G4SpnSdDu5VGPRRbpsYluOfX= 2RvM/wA92HAfFmRxNXl03+Hs/Sf0eKZicn/zOdv2dXo2/m0twz9InJw9Js4ur6POVftURRN61XE= TXt1bzEz2uUj6SeBEf1eyfnp8XnV9NyI3FVG5/O3XTl2Y1Pdpr36T/wDa9n/4ex/ohrB2rlV4rt= 8acZZGvWsWvGpu27dHR1TvMc2nZ1V9ThW6rdimmr6xDw79UVXJmAB1NSSiyigAgSiyhAAEgk9ip= PYCAKB29UD9OHa59XOnshCqe2Ny++Nb6OiPXPa+qKrimdzsAWEAFABJVJRZRAAAJCRYQAQAGQAA= CSEEoCMgANk9jDfdlVPoYtdTZTAAw02bADS7AGTFJRlMJMCoAksoCQlFQAYpPVD5zO/Wzrn0MGN= UtlKSiyjBQmAJVJhnbj0ykRvMPpttGzKmEqkSVSWbWADJ95RZR0Q54AAAEAAUiJmYiImZ9UNxcl= OhcXcCXcTjnI0+Z0i9/R5NqmZ6Wm1O39JNO3Z+91PkYyuFsTjbFu8V2ufjb7Waqp/o6LnomuPTH= /8AS9m0xj5GJFNNNu5j3KI2iIiaaqZj/k8Dq+dVbmLU0+p+v7vV6djU1x379w6VyjcK6Tym8G2/= 0TLomvm9NhZNPXTztuyfumJ2+792zyHxJompcPave0vVcauxk2atpiY6pj0VRPpiXqvPwdR5OdS= u6ro9m5l8M36+dmYVPXOJM/8AmW49Xrjs63XvpD53A+r8B42p379u9n3aOdpt2zMc+fun/d37Y9= HX2OPpmVXYri3T+qir/R05tim5HfM6qh5ilFnt/Z607ZfV7/Dwph98Gxcyc2xYs0TXcuXIppiO2= ZmXvHhXDu6dw1puDe/2uPjW7df7YpiGhfo58mGRXl2eLtcsTbs0deHYrj9af78x6vV+96N9Ha+Q= 61l03rkUU+4h9B03HqtUTVV9Zay+kzTankqzJuRE7X7c0/t3eQPv3ejfpacTWowcLhexcibldXT= 34ieyI/V3/fEvOU9r1uiW5ox9z95cHUq4qvem2eR7kjx+O+H72qXtZuYdVu/NvmU2IriY233350= O7/wDZswf/AFPe/CR+dzH0S/6g5n+Mn/TDpvK3yr8acP8AH+o6Vpmo0WsWxXtRTNmido/bMbuGu= 9l3suu1Zr1p1027FuzTXXSx4r+jxqOFgXMnQ9Zpz7lumZ6G7Z6Oav2TEzvLV/BXBmq8U8U1cO4v= RY2ZRTXVV08zTFPN7Y6ol6i5COPcjjjhq7d1GiinPxLnR3qqOqmvfriYj9jqer8NZOP9IumvRc6= dLuZ2m1X6rtu3TV9reYmNqomOyI9BZ6jftzXauz+qI9SleJar7a6PpLSfKVwDqvAeThY+q38a7V= l0VV0dDVMxEUzETvvEet1CW7PpHaHxBXxHw7p+Vql3WcrJt3KbETaoomPtU9W1MR+39z9+j/Ryz= b2BYu6lrdOPk1zTNy1Rb3imnfrjf17PSs9Rt02Ka79XuXHXh11XZptx9Gg3euTbkx1vjvAyszSs= nDs0Y12LVcXq5id5jfq2iW2P+zfpn/qDM2/4afBjyE8M61i1cTabpHEd3AtYWqVWKtrFurpObG0= VTzqZ9EehpyOq0VW5mzV7j8tlnBqiuPiR6adxeCr9PKfZ4Iz8qii9OXTjXb1qOdEbxE7xE7b9rs= /LNyT4/AGgYep2dYuZtWRlRYmiqxzOb9mqrffnT/dd+4K5PrupcsGr8RalrVd/J0nUqJ6rdNM3q= oopneraNtuuOzbsbI5WOBsfj7RMXTcnOu4lNjJ6eKqIjeZ5tVO3X/xOS91Oqm9b1V6iI230YUTb= q9e/s8Rb9cq3Lw5yNYWq8d8Q8O16xft2tJ6KKLkUxzq+dTFXX1fe7ZP0b9L2mKeIcvf0fZp8Hp1= dVxqfU1OSnBuzvUPOWLa6fJtWedzekrinf1bztu3Hx9yKY3DXA93iK3rty/Xbt019DOPtE7xvtv= znX+UTkw1bgPVMDIu36M3BvZFNNu/RTttPO6qZj17elv3ly/sUyv8AD2/9Lmy86ZuWps1eplvsY= sRRXFce4eOQHuPMAASUWUUAECUWUIAAkEnsVJ7AQD0qMqKZrqimPS5K3RFuiKY/e+GFammnn1R2= 9j9I5b1fdOkAGsAWAAUAElUlFlEAAAkJFhABAAZAAAAsJKMhFYkrLCqUmSmEAa26AAXYAIAGlgA= FJTZQWJYkstmKaXYlXVC7MK+tJIhhIuxs1tiIqSaRAZURvJpVojZkuyNsNciSqSSQAIr7yiyjoh= ogAAAQABfsbzvv2t08hfK5e0K7Z4e4ivVXNLqnm2b9XXNifv8A93/l+9pYj0+hzZOLRk2+ytusX= qrVXdS/oJTXYysamuiu3esXaeqqmYqprpn7+yYaD5YORK/lZV3WeEaKapr3quYM1c3r9M0b9X7u= p1bkQ5W73DFdGia9VXkaRVO1u5M71Y8/9afueoNMz8PU8O3mYOTbyLF2mKqK6J3iYfJV05HTLu4= +n+kvoKKrOZb9vFljk344v5dONRw7mc+Z5u8xEU7/ALZnZuXkt5Cben37OqcWV2si9RPOoxKOui= mr/en0t7xHUvUyyOs5F6ntj0xs9OtW6u76sbdFFu3Tbt000UUxtERHZDrXKLxjpvBvD17Uc27T0= 3NmMezv9q7X6Ij7vB+DlH5R+H+DcKqcm/TkZ1VM9FjW6omqZ+/1Q8l8d8XavxjrNeo6pd369rVm= mfsW6fVEHTumV5NfdV6p/wDK5WZRZjVPuX4eJ9azeIddytX1C5Ny/kVzVO/oj0R/BxfpZMfS+yo= piimKYj6PnZqmqdy9UfRL/qBmf4yf9MNKcv8A/arrG3tIbk+ill4tngTLovZNq1VOZM7VVxE/qx= 63fdW4S4C1bPuZ+o4GmZGVcneu5Xd65n+L5Tyoxc6u5Mbh7vwfj49NO2tvoh4OTb0DVc67Zmmxe= v00265j9faNp2n1bxs7RqN23V9I3TLVNdXPp0W5NUc7qj7VX83Z9S4g4R4L0HarKw8TEs0z0dmz= VEzP3REemWjuSbiueJ+X7I13Krps2bmNdptU11bRTRERtG8/x/e0VRXk1XMjWo0z3TZpptxO21+= K8KxlctHC1y9ETVj4OTdt7/3udRT/AMqpdT+lDxdrvD9jS8LRM3IwJvzVXcv2K5pqn0c3eP2Jy2= 8W2OGuU3hDWbd2i9j2rN6jIi3VE/YmaY//AH+53fWsXgPlI0PHrzMrFy8eJ59q5TeiiuiZ7Y62N= uPhfCu3Kd06/wB5Z1z8TvoonUuC+jRrWra7wRkZWsajk59+nKqpi5fuTVVEbR1bz6GfIV/9646/= z25/1dw4E4a0LhfSK8DQJmcaq5NdW9yK+v8AbDpPIjk41jW+OYv5Fq1M65cmIrriN+31tN6um5V= cqpj1LOimaYoiZa4uahnYn0qL2NjZd6zZydVtU36KKtqblPMjqq9fbLvv0qtV1LSODNMv6ZnZGH= dr1CKaqrNfNmaejrnbq9HVDU/FerYek/SUyNYv3IqxcfU7d2qqmd42imneXonjTRuEePtDx8TU9= Qt3Mam5GRaqs5FNNUTtMb9e/omXfk6t12LlUeu2NuW1M103KYn3toHkP4Q4j42ztQ1qviPO0+zF= dNu/kW65m5eqiImI/ZETDc2j8mOZp+Zj5U8c67fuWaoqmK6+qv7pjdx3JHqHDHC/EXEPBGLm02q= MbLpuY1V27EzcpqtUTPX1RM77uUyeT3hLJ1mrVquItUpu1Xel5lGpxFG+++223Y1ZWVXcuT71T9= vTbYtU00Rr3P39sfpGWbdfJvduVxvVbzMaaJ9W96mGHLn/AGKZX+Ht/wClPpB52Fd5NMmm1l2K6= v0vF6qbkTP+2ofDluzMS5yMZVu3lWK6+gt7U03Imf1XPjRO7e/z/wCm25Mfr/yeQQH3T5oABJRZ= RQAQJRZQgACQSexUnsBH1xrfSXIiY6o63ziJmdv4ORxrfR24j0z2q13KtQ+kbbbR2QSqSOPe5QA= ZACwACgAkqkosogAAEhIsIAIADIAAACABGaVMZhZGEsoY7Iz2TZFYi7EiygCkACKAEKAIsCSqVd= gqVdjBZndGuZZpMIylEZMZFlJgQfSmNoYUU9e8vozphJkSVSVYokqAgbCK+8oso6IaIAAAEAAX7= AAsDsvBnHXEvCV7naPqV23amftWK/t25/8AbPVE/fDrQ13LdFyntqjcNlNdVM7iW7bH0jOI6LMU= 3dE027XHbVzq43/du4Liblz411ixVYxrljTLdcbTGPTvV+6qeuP3NXT2o5KOmYtE93b7bqsy9VG= pqfXLyb+XkV5GVeuX71c71V3Kpqqmf2y+QO6I1Dm3udielUlRnbu3bdMxRcrp3neYiqYZfpOR7x= d+eXyGPbDLumFrrqrneuqqqfXVO5RVXRVzqappn1xOyC6hNy/fotqnP1zBxsu7XNm7fot1zNXXF= M1RE9b01TyL8mtO0xlXInt6syfF5WiZjriZiY64fScnJ3/8Rd+eXDl4ld6Y7K+2HVj5FNvfdTuX= srEyuC+THhK9Zs6nZt2KZqu003L/AEly5XMdkbzMz2PIOvate1PXdQ1OKq7U5mTcvzTTVPVzqpn= b92+z8Fy7duREV3K6ojsiqqZ2YMMLp9ONVNVU7mWWRlzeiIiNRC11VVTNVVUzM9czM77lFy5bne= 3XVRP3Tsk9iPQ1ExqY+jk3MLVXXNfPmqZq7d5nr3/azi/fppimm9ciI7I507PmLMRP1gpmY9RLO= u/erp5td2uqPVNXUly7dro5ldyuqneJ2qq3YpPYdsb2u6vygCp6+wACSiyigAgSiyhAAEgk9isr= dFVdcU09e4TOo2+2Fa51XST2Q/axooiiiKI7IZK47lXdIkqg1oAMgBYABQASVSUWUQAACQkWEAE= ABkAAABAkqxSWUADDTOAA0qJKhpZYi7Gy6SEATS7AEXYAkqMa56tmU9j51etJllTCAMGZKLKIsC= bbqypj0rEbSSI2UGetIJKpKiAAAA+0o5WdA1T3envKfFPIGqe7095T4tcZuPygjFu8XFjlPIGqe= 7095T4n1f1T2FPeU+J5uPyg8W7xcWOU+r+qewp7ynxPq/qnsKe8p8U82xyg8a7xcWOU8gap7vT3= lPieQNU93p7ynxPNscoXxrvFxY5T6v6p7CnvKfE+r+qe7095T4nm2OUEY13i4scp9X9U9hT3lPi= fV/Vfd6e8p8TzbHJl413i4qUctPD+qe7095T4p9X9V93p7ynxPNx+UJONd4uKHK/V/Vfd6e8p8V= +r+qe7095T4nm2ORGNd4uJSXLTw/qvu9PeU+KfV7Vfd6e8p8TzcflC+Nd4uKHK/V7Vfd6e8p8T6= var7vT3lPiebj8oPGu8XFDlfq9qvu9PeU+J9XtV93p7ynxPNx+UHjXeLikly31e1X3envKfFJ4e= 1bf/AMPT3lPiebY5HjXeLiRy31d1b3envKfE+rure7095T4nm2OS+Nd4uJlHLzw7q3u9PeU+KfV= 3Vvd6e8p8TzbHI8e7xcSOW+rure7095T4n1d1b3envKfE82xyIx7vFxKS5f6u6t7vT3lPik8O6t= 7vT3lPiebj8oPGucXEDlvq7q3u1PeU+J9XdW92p7ynxPNscoPGucXEjlvq7q3u1PeU+K/VzV/do= 7ynxPNscoXx7nFw8o5ieHNX92jvKfFPq5q/u0d5T4nm4/JPHu8XEDl/q5q/u0d5T4n1c1f3aO8p= 8TzbHI8e7xcRKOY+rer+6x3lPin1b1f3anvKfEjNx+UHjXeLiBy/1b1feP8Au1PeU+LmOG+TXjH= iKq7TpOlRf6KI58zeooiN/vqmCc7Hj+aF8e7xdQfuwrXMp589s9jv1rkN5SOkia9CtxH+Ns/mft= 8y/KJHV5Et/jLX5mMdQxecNV3Gva1FMtdyNiTyL8ovwS3+Ms/mTzLcovwS3+MtfmPmGLzhz+Hf1= /dlrxGxPMtyi/BLf4y1+Y8y3KL8Et/jLX5j5hi84PDv8Za6GxPMtyi/BLf4yz+Y8y3KL8Et/jLP= 5j5hi84Xw73GWuxsTzLcovwS3+Ms/mPMryjfBLf4yz+ZY6hi84Tw7/GWuxsTzK8ovwS3+Ms/mPM= tyi/BLf4y1+ZfmOLzg8O/xlrsbE8y3KL8Et/jLP5jzK8o3wS3+Ms/mT5hi84ZeHe4y11KNizyK8= o3wO3+Ms/mTzK8o3wO3+Ms/mT5hi84PDvcZa7GxfMryjfA7f4yz+Y8yvKN8Dt/jLP5j5hi84PEv= 8Za6GxfMryjfA7f4yz+Y8yvKN8Dt/jLP5j5hi84PEvcZa5GxPMpyjfA7f4yz+Y8ynKN8Dt/jLP5= j5hi84PDvcZa7GxPMpyjfA7f4yz+Y8ynKN8Dt/jLP5j5hi84XxL/ABlrsbE8ynKN8Dt/jLP5jzK= co3wO3+Ms/mPmGLzg8S/xlrsbE8ynKN8Dt/jLP5irkV5Roj/7Hb/GWfzL8xxucL4l7jLXUo2J5l= eUX4Jb/GWfzHmV5Rfglv8AGWfzJ8wxucM4xbvGWupWGw55FuUX4Jb/ABln8x5luUX4Jb/GWfzJ5= +Nzg8W9xlrwbD8y3KL8EtfjLP5l8y3KL8Et/jLP5jz8bnCxjXuLXWw2J5l+UX4Jb/GWfzE8i3KJ= 8Et/jLP5jz8bnC+Nd4y12Nh+ZblF+CW/xln8x5luUX4Jb/GWfzHn43OE8a7xa72TZsXzL8ovwS1= +Ms/mPMtyi/BLX4yz+ZPPx+cMvFu8WuhsSeRblF+CW/xln8yeZflE+CW/xln8x52PP88J413i14= Nh+ZflE+C2/wAZZ/Mxr5GeUOiN50W3+LtfmSc7H5QsY13i15VLGexsCeRzlB+DW/xdr8x5nOUD4= Nb/ABdr8yTmWOUNkY93i18NgeZzlB+DW/xdr8yeZ3lA+DW/xdr8zHzLHKF8e5xdANnf/M7ygfBr= f4u1+Y8zvKB8Gt/i7X5jy7HKDx7nFr+I62dPU2FHIvyibRPkW3+LtfmXzL8onwS3+Ms/mZRm48f= zQk493i16kw2H5mOUT4Jb/GWfzHmY5Q/gtr8ZZ/Mvm4/KE8e7xa8SWxPMxyh/BbX4yz+ZjPIxyi= fBbX4yz+Y83H5QePd4teDYfmY5RPgtr8ZZ/MeZjlD+C2vxln8x5uPyhfHu8WvBsPzMcofwW1+Ms= /mDzcflB49zi/aA+DfUACAAoAAAAAAAGwA6/UbAA2AAAAABsUQAANgE9QAfvA2AAAAAAAAAAPrh= 497Ly7WLYomu7driiiI9cz1PTXAHD1rhzh2xg000zfmOffriP1q5/wD6GuuQnhaL12eJMy1vTRM= 0Y0VR1TPZNX/OG5Y33BdjYFA2AAADY2AAAAAAAAAAAAAAAAAAAB8rk7yzrnaHzBiMk2BJiGMwyA= YwqymwJsjIBiLMICbCgMSYXYBhMbPx5FfOr2jsh+rIq5tG0dsvxzSDCYiWM09bOYQGBLKYSYBhs= +mNb51e/ohjEbzEemX7rNEUURH8QZbJLKY9SAxGUxCAkwigMZhGeySDEXYB5WAYgAAAAAD6WLF6= /NUWLNy7NNM1VRRTM7RHbM7ehf0e/wDo/wCkdBd6Hnc3pOZPN39W/Zu5XgrPjT+I8W5XM9DdnoL= vX1cyv7M/yl3yLOn3L9XA/wCkWehptfpMXt4iOmiqZ23/AOHmg1hew8uxbpuXsW/aor25tVduYi= d+zbcnDzIvxYnEv9NVG8W+jnnTHr27WyMHOweJdS1fDyLtFvFxsiMvEiqraIotztzY/wDbMrl6r= h5mjZPFVFy3Rm49q5hUU79czMzzKtvuiaY/co1t+h5n6RGP+i3+mmN4t9HPOmPXt2sOgv8AR13O= hucy3O1dXNnamfVM+hsjTdSxrOg4vFld23Xm2rH6FNFU9c1b0zFW3/DFX8Xw4qwbNVjE0fSMjH5= +sX/0yqarm1NMVdlMz6NpB0HExMvLrmjExb2RVEbzFq3NUx/B+ijBi3Yy4zMfOtX7NMTzYsfZp3= mI+3v+rHX/AMna9JsZn1QydL0i/bo1S1mVfpNNuuIruW9o5vNq9Mb87+LKY1Cxw3xBY1jLt3cmM= OzERz4mqn+lt7UzO3XMfvB06xpuo37HT2cDLu2o7blFmqaf4xGzDGwc3KjfGw8i9G/N/o7U1dfq= 6obV6TGyKNKydMxc27jW7NMc6zqFFm1RVEfa59E0TPb98uB1TVui4U1i9plVGLGRqtERTZuc7ai= aa5+zVtHVvEde0A6Nexcmzf8A0e7j3bd7faLddExVv+yX6adMzLN+zGoYGfYtV1bbxYmKp/4Ynb= eXfLGbiVahoWTl37MZd3SrlFu9d64i9zq6aJq+/wDVcdh4/EuHqNivV8yIxq8qmebcuxVz56+un= 7v4A6jGBkX8y/awMTMvRbrmOb0MzciP96I32l8asXKpyf0arGvRf326KaJ52/7O13/TsSm/ka5k= W7ubkVzqFUTi4eRTZqmnnT9qa5iepyWpXcWjieKca7as51/SYpxrt2uK5pu86uOuqIiOd2deyDp= ml8P1+RNZytSwsqxexcam5Y6Smqj7XSUUz1THX1TLiM7FopvWbWJazZquURPNvWubM1T/AHYjfe= PVLvGHj65h8EcQ0azk7U3Meno7V27FVcz0lHXH3PvayLFPEGPFORZtZdek028W7XtNNF2aOrr9E= 7qNfX9L1KxTNV/Tsu1TTTzpmuzVTER6+uOxyuncN5GrZFFnTLGZG2NN65VkWJimZijnbUzG+++2= 0eveHZtNxeIsXhbiKNXvT0NWJPNouVxVVVPOp+1E+iH6dNy+br+mWLWVzOl0WqiIpubRNc2JiIn= 799ga8o0vUq8ivHo0/LrvW/16KbNU1U/tjbqctwrptu9Vq1vPxpi5j4VVdNNymYmmrnUxvt+92D= h/S8qnTsu5mXdRyMuMrmXcTHyqbVyIiImK6q5id46+z7nI6vVj06/qddFdG9eiUbz0kVzVV9jfe= YiImfv2gGraYmZimmJmZ9Eel+rI03Ucez02RgZVm3/frs1U0/xmHYuEMGnStZ0nUdSu4lOPl01T= ZmaudFFUTMRNcejaYczptrWcHJ1TJ4jy6atOrtVxVFy5FVN6qf1eZHoB0OjT8+uxN+jByarUU87= nxaqmnb177djKjS9Trsxeo07MqtT2VxYqmmf37O06xqVVnSeFsarImMPopryKKKv1o6Wd99vu9D= mrWPxFf42s52HmUVaZVNPR3IuRFmLe36vN9f7kGsrlFdu5VbuUVUV0ztVTVG0xPqli5Ti7+tGp/= wCKuf6pcWAAAAAAA5ngzQ7/ABDr+Pp1mmebVVzrtUf/AI0emZcPtMzERG8+iPveg+RzhmNE0CnN= ybe2dmRFVXOjroo9FKjuel4VjTsCzhY1uKLNmiKKYj1Q/SQKAAAAAAAAAAAAAAAAAAAAAAAAAMa= /UDGraqWKqDEZTEMdgE2UBiMpTYE2SYUBEXY22BNkZAMSdtpmfQuz4X6tvswD43KudXv6GDNNgY= TDGaX02QHymNkfWYYxRzp2gGeNa3q58v0lFMU0xEKCJLLZJBNkZICbMZhkAxJWYQDYAHlQBiAAA= AAAAAAAAAAAAAAAAAH8/uft0XI0/HzedqWJ+l48xMVUxXNMxvHbG3ph+IB2O7rGj4Wj5mFo+Jlx= dzIim9eya6ZmKP7sRHV6v4OuAAfcAAAMqJim5TNdPPpiYmad5649W8OzYurcMYmfRqWNpWbTk26= YmizNyJsxX6/737nVwH1zMi5l5d3JvTvcu1zXXP3zO8vkAAAAAAP06Zh39Q1CxhY1E13b1cUUxA= O5cjvC865r9Odk298HDqiqrfsqrjrin747N3oSmIimIiIiIcNwboWPw9oGPp1mmOdTTvcq9NVU9= cy5pkAAAAAAAAAAAAAAAAAAAAAAAAAADGWUoDHZJhlsmwMRdgE2RVkGIuyAbIoDEXZAJhFAY1Tz= Y3flqnnVTL6353naHymAYzCTDI7QYGzLZJBjs+9ijaOdPpfO3TNVWz9MdUAkwxmGYDAZTDECYRQ= ERdgGIySYBA2kBqTzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6= r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7uf= Fu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPM= zqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r= 8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufF= u4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMz= qvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxPMzqvxbG7ufFu4BpHzM6r8= Wxu7nxPMzqvxbG7ufFu4BpHzM6r8Wxu7nxdq5OOTqOG9RuahnX7eTfiObZmmnbmeuf2tibGwAAA= AAAAAAAAAAAAAAAAAAAAAAAAEwCAAAAmybMgTbCYJhlsgqBMIBsjJO0EDYBJhhXPNpl9HwuzNUg= +fb2oymOpNgYzCbM07QYG27KYZWqd6t5Bnao5tP3sphQGIy2TYENoAGMwjMmAYCzEoCbCgMdxdg= HIgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJMKAg= qTAAAAAmkmEZArDZGe3qQGJKzCT1QDC5O0bPmyqneetjsCTDHaWaAwmEZzCTGwMYjedn2pjaIj0= sbdPpfQGMwMkmAQADZJhQRiMphNhUJgAYzCM0mAYi7AP3gAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJsoCCpMAAAIoJpNnzuT6H0qnaHxnrFRjs= ymAGKSykmAYLtussqY2A26uoUBAmAEJhQGIySYBAANkUE0xF2BUDcB+0AAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABNlAQWYY19UAwrnedvQ= x2UBiTC7GwMRTYEiIlViFBiLsbAhMACbCgIEwAhsoDEU2BAWmnnTsCbT6h+qKYiNtgFAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAmAGFXW= ymUmAYTCM0mAYizCAmxEKyjbYGIsx6kAABNkZAMRZhNgDYAQUmAQAEl9rNG0bywt086r7n3AAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= BJAkARNkZIG0SYZbIKx2GSTACABMIy3OqQYizGyAG24AkwjIBiLMIAm3qVnbjed/QDO3TzafvZA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAABPYiygAAAAAAJsjJBEmE2ZbIKxGWyTAB1SgBMIy3NgYhMACSoCbTvs+1MbRsxtx6WYAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AGyKAgbJsCgAAAACMZgZAu2EwbMtkBiMphAEmABNimJmdmTKiNusGURtGwAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAJMCmw= IAAAAAAkwoIxGSbCsdhQCmN5ZkRtAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAASAJsKbAgAAAAAmgiOshRQAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAA2AEncU2E2gAqxAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABAiBMm7qfKpxdVwTwtXrdOFGZNF2ijopucz= eKp27dpcNyZcq2j8b51em2MTIxc+m1N2bdW00zTExE7Vfvj0N9OPcqo+JEenPVlWqa/hzPt3+xl= 41+a4sZFq7NFU01xRXFXNmO2J29L7b+qHiLijWtW0rlB1u/p+o5ONct6nkTTNFyer+kq9HY9KfR= 24g1biTgGrN1jLqysi1mV2IuVR1zTFNExv9/2pduX02rHtRd7txLjxOp05F2bXbqY22Tu/Hmatp= eFci3malhY1c9lN2/TRP8JlxnKDrlXDXBmp65RTTVXi2udRFXZzpmKY/nMPL3J3wVrvKtqupall= axOJTTc51y5VTNf2p6+bEbxtEdXpeY9R6zwtX0rOvTZwtTwsm5Ec6aLN+muqI9e0S/bFUT2TE/s= aEweR+rgnT9W1vK4qv3bMYNdurosXauneqmd4+319n8315BuJdA4c5P8AW9XztbzMnFt5sRNzJt= c2vncyNqaY51W/8YBvc3acn6QnB9WTRas4eqVxVMU7zapjrmf+J9dY5e+FtM1XK0+9g6lXcxr1V= qqabdO0zE7Tt1g29Bu6FwDyq8L8YVZFrDu3sW9j0TcroyKYp3pjtmNpnscDq3L/AME4WVdx7NvU= MvmVc3pLdqOZV98TNW/8gbZ58RVtMxE+jee1d3mnlM4r0TiziThbWbOq6vptq/ZiKLNuxFXO2v1= RMztXHqd91/lw4Z4e1jI0TKw9Ru3sSqLVddNFO1U7R1x1g20Oh8nnKnw1xrmXMHT5yMfLop53RX= 6Ijnx920zu74AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAdYA1V9KL+y6/wD4i1/qhqX6K39pt3/Lrv8ArtttfSj/ALLr/wDi= LX+qGpforf2m3f8ALrv+u29/Fn+za3zeXH9o0S6Bx7/XnX/8yyP/AJanpD6KH9ml/wDzK7/otvN= /Hn9ede/zLI/+Sp6R+if/AGaZH+ZXf9Ft29W/gaf6OXpMR59X9XauW3T72p8luu4ePTNVyqxTXE= RHbFNdNU/yiWkvoz8daFwzZ1PTNcy6MOm9XF61dr7Kp2iJj7ux6du0UXKKrddMVUVRtVE9kx6mp= OJORPgLUNUvZVOVVgXLlU1XLVF6Ip3n1UzPU+TfXOR4z464U4g4K1vT9I1rGysj9Dqri3RXEztE= x4vM0fpPmrq5sVdB5a+3t2b9DG270bwtyM8I6Xk5dzG1G/lTfxqseqmLkdUVTE79U/c5bQOSThj= S+Fc/hu9TdzcPNvRer6TqqoqiIiJpn0dgNBcGWeLqdPwP0C/wvOJzqZp6e1iV3dt+veaqZq3/AH= ud4B0/Bz/pH61i5+Fj5Nic7L3tXbcV09VVXolsCj6P3C1vIpu28/PpimqKqaedvEbT+12fhrkv0= PQuM8rinHvZNzLv111xTVV9mia5mZ/b2yDznm49WLykcXY+mWos00YGXTTRap25tPRx2RHY7b9H= TK5PMfQ9Qnim5o9vOm9Tt5Q5nXTtP6vP/ns2/pnJhoOn8c5XFdFy9Xfyaa6blmvro2qiImP5Os5= /IRwPqeddycLKv2Kaqt6rdq5FVNMz6uvq/YDXnLze0HI454UucOVYNWnzj08ycPm9H/t6t9ub1d= u78vFHF+t67xxmabomBw/idF/5mVhY81V7RHXVXcpnerrbbnkR4aqjSIrysyqnS45tEb/rx0k19= fX66tji3kU4R1rVr2rXL2Rg13IibvMq2pmfX29QNN8isZtrl7wKc6rHnJmb/S/o0URbmeir7Ioi= Kdv2PXEdjV3AvI9w5w1xHi8Q6dqGTkXcfnczeqJpnnUzTPXv97aMAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgS1X9KP+y6= //AIi1/qhqX6K39pt3/Lrv+u2219KL+y6//iLX+qGpfoq/2nXf8uu/67b38X/Da3zeX/iNDoHHn= 9ede/zLI/8Akqekfon/ANmmR/mV3/Rbeb+PP6869/mWR/8ALU9H/RQn/wDzPI/zO7/otuzqv8DT= /Ry9J/jqv6tvel44zNM1rivle1LQsLVb2PdvZVzm1VXaubER+97Gh5P4Kz8HTfpEZWXqOZYxMan= Kvc67euRRRH7ZnqfKPrnGcbcOcb8l+pYObc1m7ci7MzRetXapp3jbqqiZdx4y4zv6vq3A+q29fz= NOqyce1N61Ztc6iuuLvNqn9aPTE9XW+n0pOLtA1fTdN0rSdRxdQuU3Zu1149yLlNMRG20zHVv1/= wAnQdZwb2n0cn2Pfpmmuqz0sbx17V5NVUfymAeleL+U3hPhG5ZxdYz7lWVNqm5NqzRFVe09kzG/= pcLpnLZwZrOXGmYF3UreTepqi3XXjREUzFMzv+t9zTHBeHpGucuGTZ4vrtzZqmqebfuc2KrkRTz= aZ9fVv1P0cR4GkaZy+UYeiW7NvCpt70U2Ziad5szM9n3g5zk845xtFji7UNX1/UtRsU823RTNja= bdVVdcRt9pxf0feUPTOG9Qz8fXMnPu1Z923Rj82JuREzO3XvPV2w+vINpmBq2dxri6li2smzFqm= vmXKYqjnRXXtK/Rq03h3LydZv63i4d6vGqorx+niN6Zjefs7+nq9ANoajy68DafqGTg351Tpse7= Vauc3GjbnUzMTtPO9cPjxhx7oPF3JHxPkcP5l3pLGJvXTXTzK7e8xtPVP3S1LqPEN7iPivVLHD3= BOiXYt3q5q59iia6vtTE1zM+mZ3l1jhG5mYkcYYFU3Ma3XpF6b2PRXPM50V0bbx6dt529W8g3r9= E/IyMjgnOnIv3b005W0TXXNW3VPrblaU+iR/UjUP8AF/8ASW6usFCAAAAABjVVFMb1TtHp3nqZT= 2NUcuHFteLap0DAvzRer+3fronrpj0U/d/+gbT6az7W380HTWfa2/mh5O8p6j7/AJXe1eJ5T1H3= /K72rxTY9Y9NZ9rb+aDprPtbfzQ8neU9R9/yu9q8TynqPv8Ald7V4mx6x6az7W380HTWfa2/mh5= O8p6j7/ld7V4nlPUff8rvavE2PWPTWfa2/mg6az7W380PJ3lPUff8rvavE8p6j7/ld7V4mx6x6a= z7W380HTWfa2/mh5O8p6j7/ld7V4nlPUff8rvavE2PWPTWfa2/mg6az7W380PJ3lPUff8AK72rx= PKeo+/5Xe1eJsesems+1t/NB01n2tv5oeTvKeo+/wCV3tXieU9R9/yu9q8TY9Y9NZ9rb+aDprPt= bfzQ8neU9R9/yu9q8TynqPv+V3tXibHrHprPtbfzQdNZ9rb+aHk7ynqPv+V3tXieU9R9/wArvav= E2PWPTWfa2/mg6az7W380PJ3lPUff8rvavE8p6j7/AJXe1eJsesems+1t/NB01n2tv5oeTvKeo+= /5Xe1eJ5T1H3/K72rxNj1j01n2tv5oOms+1t/NDyd5T1H3/K72rxPKeo+/5Xe1eJsesems+1t/N= B01n2tv5oeTvKeo+/5Xe1eJ5T1H3/K72rxNj1j01n2tv5oOms+1t/NDyd5T1H3/ACu9q8TynqPv= +V3tXibHrHprPtbfzQdNZ9rb+aHk7ynqPv8Ald7V4nlPUff8rvavE2PWPTWfa2/mg6az7W380PJ= 3lPUff8rvavE8p6j7/ld7V4mx6x6az7W380HTWfa2/mh5O8p6j7/ld7V4nlPUff8AK72rxNj1j0= 1n2tv5oOms+1t/NDyd5T1H3/K72rxPKeo+/wCV3tXibHrHprPtbfzQdNZ9rb+aHk7ynqPv+V3tX= ieU9R9/yu9q8TY9Y9NZ9rb+aDprPtbfzQ8neU9R9/yu9q8TynqPv+V3tXibHrHprPtbfzQdNZ9r= b+aHk7ynqPv+V3tXieU9R9/yu9q8TY9Y9NZ9rb+aDprPtbfzQ8neU9R9/wArvavE8p6j7/ld7V4= mx6x6az7W380HTWfa2/mh5O8p6j7/AJXe1eJ5T1H3/K72rxNj1j01n2tv5oOms+1t/NDyd5T1H3= /K72rxPKeo+/5Xe1eJsesems+1t/NB01n2tv5oeTvKeo+/5Xe1eJ5T1H3/ACu9q8TY9Y9NZ9rb+= aDprPtbfzQ8neU9R9/yu9q8TynqPv8Ald7V4mx6x6az7W380HTWfa2/mh5O8p6j7/ld7V4nlPUf= f8rvavE2PWPTWfa2/mg6az7W380PJ3lPUff8rvavE8p6j7/ld7V4mx6x6az7W380HTWfa2/mh5O= 8p6j7/ld7V4nlPUff8rvavE2PWPTWfa2/mg6az7W380PJ3lPUff8AK72rxPKeo+/5Xe1eJsesem= s+1t/NB01n2tv5oeTvKeo+/wCV3tXieU9R9/yu9q8TY9Y9NZ9rb+aDprPtbfzQ8neU9R9/yu9q8= TynqPv+V3tXibHrHprPtbfzQdNZ9rb+aHk7ynqPv+V3tXieU9R9/wArvavE2PWPTWfa2/mg6az7= W380PJ3lPUff8rvavE8p6j7/AJXe1eJsesems+1t/NB01n2tv5oeTvKeo+/5Xe1eJ5T1H3/K72r= xNj1j01n2tv5oOms+1t/NDyd5T1H3/K72rxPKeo+/5Xe1eJsesems+1t/NA8neU9R9/yu9q8Q2P= WoCgAAnpUJGrfpOWrt/kxv0WbVdyr9ItdVFMzP60eppXkB1Kzwvx3XqOtWcrGxasO5aivoK5jnT= VRMR1R90vXF6zbvUcy7bouUT201RvD4eTcDbrwcaf22o8Ho2M6m3YmxNO4l5mRgTdvxeifcPJ/E= vBeBrXEGoalpXF2kbZeXdvRRkxdszTzqpq266Ovtdg4Dy+UDk/szh6Zj6brmmVXJu3bWNk01TvO= 0bx6Y7PV6Hoi/oOi39un0fT7n/FjUTt/GH4Mjgnhi9Ff/ANHx7M1xtVVYmbM/xomJbquqd9EW64= 3H7/8AIaI6VNFffROp/ZxnBfKNonEVyMK7F/TNT23qw8yjmVTt1TzZ7Jj+bofEP0fcTWNdzNUq4= ov2ZyrtVybcYcVRTv6N+f1thXuTzh69z6b1q9dtTRtRTXdmarc+iqm5/tIn/wB2zmOHdMzdKxpw= 7+oV51iidrNd2P6WKfVVMdU7fs/bu8678Ofdt6VmbtMauf8Adqjh36O+g4GoWsnUdZydRot1RV0= XQRbirbs3+1Ls/KByU4fFfEGkarTqtWn0aZbot28ejHiumqKaudHXzo29TY0b+lWl0PMXLnb5Oq= eM71jLr1vT9WtUUxeu4mLbuW65/vbTcpnf7/udP5LtJtaryqYOPol7NysOOdNWRk2YorpjmTEzV= EVVRH8XrLVeE+HNVy5y9R0bDyb8xETcrt9cxD9Ol6HpGl1TVp2mYmJMxFMzatRTMxH3wDpXJtyY= 4nA2oavnzrFebRqNMRXRXYi3FuImqe3nTv2umRyIcOTqVes6bxjVawbN6LtVui3TXTERO80zVFf= Z+53vl01DUMLgTIsafRETmTGPdvzvtYoq6pq6uyfvawx+EuM9T4auYPC+1rTcmmbV6qMmiIyaaZ= jm1zPN2+Xbfed93ZZxablPdVVpw38uq3V20U7cln8jHCmu67eyNC4zqxq8nfImxappuTtVO87TF= UdW+/U/XoXIPgadc1SxTxbcv3cvBqxrlP6LTFVuK6qZiqY5/wDuS4ThHku4/wBIv3+dZwsWi5Yr= pquWsjerrp22pmNpjeOyd+qZ3+5yGNwxy12r93UKc7GpyrtqLNdUXbfOrop/U3mafRvV/FsrwrU= TMU3I01UZt2YjutztsHkc4RwODtDy9PwNZjVaasmrn19HFE0V07xNMxEz6XevQ6tyY6Hn6Fwvbx= tVosxn3btd7Jm1O8VV11TVM7+nrl2qI2hw3KYiqYiXoW6pqpiZjRADFmAAEiVTERvM9QOI4v13H= 4e0G/qd+YnmRtRT/eq9EPMOq52RqWo387KuTXevVzXVVP3u58sXFc65rk6fi174WFVNMTE9Vyv0= z+7s/c6EkgAgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAA9gAMgAAAAAAAAAAAAABjMbz19hTERHUsrCRKaT0iiqAAAAAAOi8sPFHkHQJxMW5tnZ= kcyjaeuin01f8AT97vFc7U1T6o3eYeUHWMrWeKczIyZ6qLk0W6N+qimJ6oJHAVTVVVNVUzMzO+8= 9cygMQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAB//Z" width=3D"819" height=3D"1117" alt=3D"Imagen que contiene Interfaz= de usuario gr=C3=A1fica Descripci=C3=B3n generada autom=C3=A1tica= mente" style=3D"margin-top:-34.06pt; margin-left:-119.81pt; position:absolu= te" /></span><span style=3D"height:0pt; display:block; position:absolute; z= -index:-65535"><img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAU= IAAABPCAYAAACeRMz2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAADrlJR= EFUeJztnX+MHdV1x7+TH6i03TZqUkupaFCsxpGoApVbq0gRVUWLLIQQQjROajmJW1QLIhrUVGCT= FkggpHZCSnGMA5hfxZC6TghBxoBLIRCnQOLaRSlJDAYbbAcw2NjuYnu9xnz6xznPe99982bm7Q/= vmj0fydo398e5Z2b8zpu5d+Z8pSAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIguCdDb= COdga8/ExgPbAP2A/8ELgIuDXr37Ud8OXE7n7gU1nfO7OxlzXw9wxgA3AA6AdWdWk3BVgKPAvsA= R5O6lYDb7rPDw3HftZnLvCM2zsIbAWuzNpUjdmk/1Y6ubzOtyAIGgD0Af/kX6wngale/izwInA+= cBZwPfAacHvWv7ad1wG8APRl/c8D3gDOaejvsyUB4Y6szbnAFq/7GfAvwAyv+76XLwFu8c+rerG= fjTUN2AUcAv4R+DTwf1ggPaNuzIb955X4tKPJ8QqCoCHAOf7l+l5SNggszdpdANyWldW280D4v9= gV0b0l429s6OelwMPAacBC7OqJtD8wHQvEh4Gbsv5TsKsugBOAGf55v9fV2i/x6TJv048HeewKG= eyKuG7Myv6+/Qjw1SbHKAiCYdIlEP4C2AZ8oqZvbTsPhE8Aizxw/l1W3zQQzsy2f+J+b0jKfuhl= PyrpP9/r3krKWnyxif0Sm59NbDzkZc9hQf+0BmPW9e8D9vpxew34L2Bek+MVBEEPdAmEH8fmyga= Ah4DTuvStbdcKhP55DbADOCmp35i1Xw7sBKbV+N2a31zi2zPcD4BXsCu6ncB1Xn+b1x1KbLztZb= fV2a/wY0MSzLb7/l3UdMya/tfSySGyudogCEZIWSBM6q7Ervj2ASsqbHRtlwXCPmyucG1S3+iKs= GTMncCWZHthEiw+C9zsnwexubeVre2kTysorayzX+HHDCzwpoHqBq+rHbOqv9dPB/4WuAfYnbSp= vFoPgqAHqgJh0uZObN5tTY2tjnZpIPTtc7EFga/5ds+BEFt46AdmJWXLfT8OJ2V7vWwFQ6vUaVB= qkS8Cddiv8OUL2FXd55KANgjMajJmVf+SsWYAm71Nx1VsEATDpCwQUn6FtBa73ezrpV0eCL3sq9= hjLTN7DYTY6vROYH5WviwJMjO9bJtvrwau8M+HvK4vaX9ZA/vraWfQ920QWJ/0PeD1364bs65/l= /3/vNcvLasPgtHiXePtwARgBp1zdDv97/HDaNdGURRflPSEpG/04hQwRdLXJN1YFMUibCX2u8Bc= SY9IouVX1nWzpLskHZD0HmyO8iNed0DS8jr7RVH8YdHOcZL+XNJ7Jb3b92u1pG1u980GY9b1L+M= xSQOS7m500IIgqAe4xq8wngBO9rJ+bC5vATZHdTV2O/tk1re2HbAYWwk9OevbB2yih2figEfpZH= 9S/2Mv24DNEw5gq62t5yNXef23gJv88+qm9kv8uQSbCtiP3eJehM2T7gb+tG7Muv7YvOeAH6dFw= KnAg8CNTY9ZEAQ10P3NkpX+JdyMTczvwZ5nOynrX9kOeDqznz+icjbwfFb2b9it6YysfBnlvJC0= mQr8AHv8ZBD4Oe3ziH3Af3jg2Q/c34v9LsdwCfCyj7cPe0vkr5uMWdcfmIP90Bz0f88DX6ryJwi= CYxD8DYogCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIIgCIKjCkNpnVo8kNXvS+rubGDvDO= wVsL3D8GXUNU6OJliqrMq3UEZg+1rgdfxVwR77zgIeB14ejr2qtmW2h+sX8Bhwc692gmDEMCS+h= L8GNjWrn4u9rnYHcEIDe/dir9q9Vde2wsaoaZwcLbB8jHuBb463LzlYVuu3gF0TyXbeF5N42EHy= 7ncQHDWwlPADJEpvSd1JwI97tLd8FALhiDVOjhZY6qx+PL/iRATLDD7qgXCktvO+wCf8vF83eh4= Gw2VSpeEqimKtpHWS/rjk9ufvJVUmYy1hYBTc6pd0g6SzyDROJiALJO0siuLS8XakgtE4J2Nhu6= 1vURTfkfSgpDlYSrRgHJlUgdC5RdKvSfqHrPyjRVFckRZgyVTXYwlED2IZXmaPtkNFUcyX9ANJC= 8iy3iS+tNLeP+7bz/j2L337C1gGnP/Gsry8gc0/3uxzer/0W/muAk1V+A/HH0l6Oin7CrDRpxqe= wLLK7AK+nrSZ5b7ux9KW3efllwI/9SviTX6l/u+YHszepH/lOfCr/PXef7ek38n65vbOxlKX7XO= bPwFO7tK2q22vf8j36bAf72ub9nVWS/qApIt7OxtBMAr4F3N7sv15sizJWEqprcBTfks43/+zv4= bPIWLprEZ6a9xI4wRbnNmdBMKTfD9agfAlD4zbsbyIp3tgfBNLuHoupnsMmah6Q19bcpxpkNvvZ= ZuxfIPn+j4c8IAzxYPclVjq/VaOwuuBV/3zDuA8t3c/ybxrw3PwCx9zltfvYWguLrd3ApYGbC2W= A3GJB6qFedsGtmf6fl6D5adcT/siTde+2XE9CDzS6/kIghEDXO5fwit8+2E6cwIu8jZnJWWLvay= lJjdqgdC3KzVOsHT8jyfbj+KB0LefA9IrtmW0q8pNSf3v0dcbve+CrHw37botF3q7ZQwlws15yt= u+AKzL7B2Zd607B8l5nJfU53Nxqb3rPHiVLoZlbWtte9nnsEA9wFCQbNQ3OX7/U37Ug6PFZLw1V= lEUV0vaLukvPAAeLopiXdbs9/zvYFK2yv9+cIz8ulfSEknzyBK7NmQw2z4sqUjsvzYC91oBvy8r= bxuzKIpv+bjvl/QhSS8XnZzqzQ+pk3Qure4cnOKf00eh8nm8dPt3JQ0URbFd5aRta21jV3JXS9o= iaW1S1cSvI2Y0Sb+HE4nJfAIekPT7kq6SVKZq19LTOC8p+3X/O2aruQ00TvJz9t6x8iVjq/8tm9= h/T+sDdpv7bllweEXSFLJ5VZo/F1l3Dvr982e6+ZPxqqTfxHRf6qi07VftfyJpTlEUfylpf9O+G= b8i6Y0G/gTB6OO3ibuB5yrqX8WemfsSNqf0FPBS0uZ+bBFjzjB96EnjBFuY2I7NFy4EXvRbsD3Y= nOF2bL5umtu4z/2b7f1bt63fp8eVSre3j870+zuwObt52LOaz/hxm+I+vY7Ny12GLSA8gOmVTMc= WcJ7O7LWO6ey6c4DN0+1zHy7B5hF/6vt4wPun9qZjc4zb/Jb2VOyW/7qSsetsr8AWSRZgzwVuxB= 4t6mvil48328v+uZdzEQSjCvZQ9OKK+k9hk96D/h94A0PymSto53xswrzRfA/D0zi5xr9s/ZgI+= iNYIL2KocUSMM3gNZn9Jdn23b346+M/CryYle3AVqpfx+bJfoYvfnj9XPfxIKbP8o2kXyswbPGy= 7+XHpOoceJ/52A/AIUzn5DHsx+DrXexd6PWDWFC8p2LsKtsf92M+ADyJ/agdwJ9Rreqb+L4S+zG= ufYA/CCYtTDCNE2wlei9wU1K2g2SxJGgGdnW8B7hhvH0JgqBHsOf/9mLPJ56BrXKvi6ua5mB3D9= specMpCIJjBOBv/Iucsmm8/TpWwBIw3D7efgRBEARBEARBEARBEARBEARBEARBEARBMKnAMp2kH= PY3AbYAXxnFcYatuTGe0ECDpWrfGKFeyHDGbLIPx+r5CIIxAXsHtCWKtASYiuXJ2+WvQV0w3j6O= J4xQg4Ux1AvpwYcR68gEwTsehvLELUnKWslCHxwHf2YwgQR8yDRYevWPMdQL6cGHEenIBJOTbum= KJhPH+9/DR3NQTLXuVrWnbxpvjuTMG6Z/Y6kX0pSJ4ENwjDFp8xFiKaOWyXLdHZL03ay+Q2uDdm= 3k//R2rSwvuynXvXgwmYu8GTjfq9ZK+phMSAosG3NXDYwS/3vSKKFG86SE3L+VJfvWq15It2PRy= raTa4lckNqggUZKdoxmZv0XYBopTwH/6sf6Tdq1RkrPAeUaKwu7nZ8gmLAwdGucsonO9PPdtDZu= xwLfVoY0M/pwQXg6NTLm+Rd1NjAHm0dLv/ybGEpbX6mBUbIvPWmUUKN54mVt0gOZf71qejQ+FnT= XEnk+s1GpkZLvQ4kPr3j/V4ClPtYmYGvdOaBEYyUIjkkYCoRLsSuwt1tBLGvXVWvDvyx78WSqvn= 1B0jfVvTjHv7z3UpJSKw00SVmHBkbF/vSkUUK95knXQFiyb73qhXQ9FlRoidA5b9lVI6XLPuT9X= yTRScESxe7Mxiw9B5RorATvDCbrrfHbLqH5uKRPAhdm9V21NoqiWCPpWUmXeNs/KIrixqTvkTmq= oijuk2kBT5W0CkvgOb2bU3TXwOjGWGqUlNGTpoeaH4sqLZHcZpVGSp3PUqdOyttKjlnNOSjTWAn= eAUzWQNjifEm7JF1Be7r8Oq2N5ZJO9895MGqjKIrFRVGcIunTsgBbqkVCtQbGaDJamie96oVUHY= tetETaxqBdI2VEHMVzEEwwJs2qMbYKOs03TwSmFEWxGbhK0mJJa4C7JN0j6Q5JfyXpWuBEST+Sd= Jn86qcoim8CF2M55S7PhvqgpHd5EP2QpLMl3SVTzeuXdFzS9rCk9wOXSDpTFqRO8TE/Kuk4oK8o= in5lYELw75M0CEyTBe8jYxdF8e3kSvcETCdjn6QP+63pn8muzn4b2FMUxfuS/nOKorgr8+8D2b6= tkDRL0sV+O/5zSR+W9BvAAUkn9nAsbpM0W9LVwK9K2iBprqQD+T55+4/5Lfk2SV+WtEPSouz4t/= Yh9eEZmQof2APWr8uuJI8HTpcJU5WeA0kf8b6xKh0cu9D5ZsmOpO7uvJwuWhtJn+uBB7KyXPfiV= mzi/wVshXMjcGbS/hafG1tPjQZGyf4MR6OkSvOkTIMl9a9XTY9ej0WHlkiXMbtqpJTsw/pse2fy= +aWsfoCKc0CJxkoQBMG4QGikBGPAZJ8jDI4hsFv64yX9FqGREgTBZMNvi1NCIyUIgiAIgiAIgiA= IgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAIgiAYNv8PQs= z7KQHZQ2oAAAAASUVORK5CYII=3D" width=3D"322" height=3D"79" alt=3D"" style=3D= "margin-top:-23.85pt; margin-left:216.54pt; position:absolute" /></span><sp= an> </span></p><p><span> </span></p></div><p style=3D"margin-bott= om:0pt; text-indent:0pt; text-align:center; line-height:115%; font-size:18p= t"><a id=3D"_Hlk192175248"><span style=3D"font-weight:bold">Estrategia did= =C3=A1ctica para mejorar el desempe=C3=B1o de los estudiantes del bachiller= ato t=C3=A9cnico</span></a></p><p style=3D"margin-bottom:0pt; text-indent:0= pt; text-align:center; line-height:115%; font-size:14pt"><span style=3D"fon= t-style:italic">Teaching strategy to improve the performance of technical h= igh school students</span></p><p style=3D"margin-bottom:0pt; text-indent:0p= t; line-height:150%"><span>Kevin Valent=C3=ADn Padilla Zamora, Maritza Lore= na Aguinda Aguinda., Segress Garc=C3=ADa Hevia., & Marbel Guilarte Legr= =C3=A1.</span></p><table style=3D"width:469.65pt; margin-right:auto; margin= -left:auto; margin-bottom:0pt; padding:0pt; border-collapse:collapse"><tr s= tyle=3D"height:18.65pt"><td style=3D"width:6.75pt; border:0.75pt solid #000= 000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt;= text-indent:0pt; text-align:center; line-height:normal"><a id=3D"_Hlk19434= 3169"><span style=3D"font-size:8pt; font-weight:bold; vertical-align:super"= >1</span></a></p></td><td style=3D"width:205.25pt; border:0.75pt solid #000= 000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-left:7.1pt;= margin-bottom:0pt; text-indent:-7.1pt; text-align:justify; line-height:nor= mal"><span>Kevin Valent=C3=ADn Padilla Zamora</span></p></td><td style=3D"w= idth:14.35pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-ali= gn:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:center; = line-height:normal"><span style=3D"height:0pt; text-align:left; display:blo= ck; position:absolute; z-index:1"><img src=3D"data:image/png;base64,iVBORw0= KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxA= AADsQBlSsOGwAAA2lJREFUOI21lEtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA= 1FnQcQiUhUnFqo4cGIRQUGd+KDY+Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+= mzXZe///Wv/aiy1cBV/83NNOPr/VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7= LFeSpNNZ+57RTjDTvqFM1IvNiGXWJvD/9x8yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XL= leTd648Z/863v3nkjWCL59dp/fWSsfzOXNkShKacvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082A= AzADZXyPj+wL8ehQ1NH700v0N35OAroutW0rxDF6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXE= ZCQcqQtZ0VEU1QTPtmAkDygiEBTsTxq6hx65fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1i= TI9UGqFJrzDF5+Sv+Wvg+y+IEVXaGibsbOO5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct= 3csfk52oNtTMwcBbE0YteeC7we4LinSI9Z03dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WS= jyFiIg17AAwqpRW9fqayNkiM0tjqDrag67mDCi0ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKr= R2zreIDURZTrZ7NTBYdeBPAU+cY59zxCkFlXjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYj= FGqkldT0J4EkY/ZovBb+klbQ/G1zDYvQntXgWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+Bv= Z8JUzGAEQV+Wy87xm/xbwZ1lwewGmCIIhYnCZXjKvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2= CV8GrRkNldbNmKbYU2enC0uV6bkfUNUd8P1ury3ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbr= XMoncTV99smBH5ZW327igzP3trY2ONCyyQ6FtbRLUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fX= p1+BVxdx2um+HGnuX9egX4dY01U0iVK2R80nMaELy42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU= 5ErkJggg=3D=3D" width=3D"20" height=3D"20" alt=3D"" style=3D"margin-top:2.4= 7pt; margin-left:-2.95pt; position:absolute" /></span><span> </span></= p></td><td style=3D"width:198.9pt; border:0.75pt solid #000000; padding:0pt= 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt= ; line-height:normal; font-size:11pt"><a href=3D"https://orcid.org/0009-000= 7-3963-2899" style=3D"text-decoration:none"><span class=3D"Hyperlink">https= ://orcid.org/0009-0007-3963-2899</span></a></p></td><td style=3D"border-bot= tom:0.75pt solid #000000; padding:0pt; vertical-align:top"></td></tr><tr st= yle=3D"height:37.4pt"><td style=3D"width:6.75pt; border:0.75pt solid #00000= 0; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; t= ext-indent:0pt; text-align:center; line-height:normal"><span> </span><= /p></td><td colspan=3D"4" style=3D"width:440.55pt; border:0.75pt solid #000= 000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt;= text-indent:0pt; text-align:justify; line-height:normal"><span>Universidad= Bolivariana del Ecuador (UBE), Dur=C3=A1n, Ecuador</span></p><p style=3D"m= argin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:normal">= <span>Maestr=C3=ADa en pedagog=C3=ADa con menci=C3=B3n en formaci=C3=B3n t= =C3=A9cnica y profesional</span></p><p style=3D"margin-left:7.1pt; margin-b= ottom:0pt; text-indent:-7.1pt; text-align:justify; line-height:normal"><a h= ref=3D"mailto:Kvpadillaz@ube.edu.ec" style=3D"text-decoration:none"><span c= lass=3D"Hyperlink">Kvpadillaz@ube.edu.ec</span></a></p></td></tr><tr style= =3D"height:2.95pt"><td style=3D"width:6.75pt; border:0.75pt solid #000000; = padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text= -indent:0pt; text-align:center; line-height:normal"><span style=3D"font-siz= e:8pt; font-weight:bold; vertical-align:super">2</span></p></td><td style= =3D"width:205.25pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertic= al-align:top"><p style=3D"margin-left:7.1pt; margin-bottom:0pt; text-indent= :-7.1pt; text-align:justify; line-height:normal"><span>Maritza Lorena Aguin= da Aguinda</span></p></td><td style=3D"width:14.35pt; border:0.75pt solid #= 000000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0= pt; text-indent:0pt; text-align:center; line-height:normal"><span style=3D"= height:0pt; text-align:left; display:block; position:absolute; z-index:2"><= img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR= 0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAA2lJREFUOI21lEtoXVUUh= r+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQiUhUnFqo4cGIRQUGd+KDY+Jp25oui= GCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe///Wv/aiy1cBV/83NNOPr/VWHunqO5= OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNNZ+57RTjDTvqFM1IvNiGXWJvD/9x8= yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XLleTd648Z/863v3nkjWCL59dp/fWSsfzOXNk= ShKacvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082AAzADZXyPj+wL8ehQ1NH700v0N35OAroutW0= rxDF6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQtZ0VEU1QTPtmAkDygiEBTsTxq6hx6= 5fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqFJrzDF5+Sv+Wvg+y+IEVXaGibsbOO= 5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52oNtTMwcBbE0YteeC7we4LinSI9Z0= 3dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg17AAwqpRW9fqayNkiM0tjqDrag67m= DCi0ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKrR2zreIDURZTrZ7NTBYdeBPAU+cY59zxCkFl= XjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYjFGqkldT0J4EkY/ZovBb+klbQ/G1zDYvQntX= gWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGAEQV+Wy87xm/xbwZ1lwewGmCIIhYn= CZXjKvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2CV8GrRkNldbNmKbYU2enC0uV6bkfUNUd8P1= ury3ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbrXMoncTV99smBH5ZW327igzP3trY2ONCyyQ6= FtbRLUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fXp1+BVxdx2um+HGnuX9egX4dY01U0iVK2R80= nMaELy42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJggg=3D=3D" width=3D"20" height= =3D"20" alt=3D"" style=3D"margin-top:0.45pt; margin-left:-0.3pt; position:a= bsolute" /></span><span> </span></p></td><td style=3D"width:198.9pt; b= order:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p styl= e=3D"margin-bottom:0pt; text-indent:0pt; line-height:normal; font-size:11pt= "><a href=3D"https://orcid.org/0009-0005-0076-9463" style=3D"text-decoratio= n:none"><span class=3D"Hyperlink">https://orcid.org/0009-0005-0076-9463</sp= an></a></p></td><td style=3D"border-top:0.75pt solid #000000; border-bottom= :0.75pt solid #000000; padding:0pt; vertical-align:top"></td></tr><tr style= =3D"height:37.4pt"><td style=3D"width:6.75pt; border:0.75pt solid #000000; = padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text= -indent:0pt; text-align:center; line-height:normal"><span> </span></p>= </td><td colspan=3D"4" style=3D"width:440.55pt; border:0.75pt solid #000000= ; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; te= xt-indent:0pt; text-align:justify; line-height:normal"><span>Universidad Bo= livariana del Ecuador (UBE), Dur=C3=A1n, Ecuador</span></p><p style=3D"marg= in-bottom:0pt; text-indent:0pt; text-align:justify; line-height:normal"><sp= an>Maestr=C3=ADa en pedagog=C3=ADa con menci=C3=B3n en formaci=C3=B3n t=C3= =A9cnica y profesional</span></p><p style=3D"margin-bottom:0pt; text-indent= :0pt; text-align:justify; line-height:normal"><a href=3D"mailto:mlaguindaa@= ube.edu.ec" style=3D"text-decoration:none"><span class=3D"Hyperlink">mlagui= ndaa@ube.edu.ec</span></a></p></td></tr><tr style=3D"height:18.65pt"><td st= yle=3D"width:6.75pt; border:0.75pt solid #000000; padding:0pt 5.03pt; verti= cal-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:c= enter; line-height:normal"><span style=3D"font-size:8pt; font-weight:bold; = vertical-align:super">3</span></p></td><td style=3D"width:205.25pt; border:= 0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p style=3D"m= argin-left:7.1pt; margin-bottom:0pt; text-indent:-7.1pt; text-align:justify= ; line-height:normal"><span>Segress Garc=C3=ADa Hevia</span></p></td><td st= yle=3D"width:14.35pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vert= ical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:= center; line-height:normal"><span style=3D"height:0pt; text-align:left; dis= play:block; position:absolute; z-index:3"><img src=3D"data:image/png;base64= ,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSF= lzAAAOxAAADsQBlSsOGwAAA2lJREFUOI21lEtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk= 0ZU2oGgA1FnQcQiUhUnFqo4cGIRQUGd+KDY+Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcn= uU1iQ0f+mzXZe///Wv/aiy1cBV/83NNOPr/VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUI= Tu/KSlu7LFeSpNNZ+57RTjDTvqFM1IvNiGXWJvD/9x8yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOC= NIFsW2XLleTd648Z/863v3nkjWCL59dp/fWSsfzOXNkShKacvfgnMRlXjqqqIrwr5vkihyhxbT+= K2ne082AAzADZXyPj+wL8ehQ1NH700v0N35OAroutW0rxDF6rUUvddaJfdwM9HwqYFSa0GO1Srp= fucUVUXEZCQcqQtZ0VEU1QTPtmAkDygiEBTsTxq6hx65fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2a= Pcf/Oo1iTI9UGqFJrzDF5+Sv+Wvg+y+IEVXaGibsbOO5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9O= IIVnw6Ct3csfk52oNtTMwcBbE0YteeC7we4LinSI9Z03dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5= sNMXv6WSjyFiIg17AAwqpRW9fqayNkiM0tjqDrag67mDCi0ARiB6gaTsSEEg4htusj2qGeCIr9d= W0JR3PKrR2zreIDURZTrZ7NTBYdeBPAU+cY59zxCkFlXjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs9= 8SDWexYjFGqkldT0J4EkY/ZovBb+klbQ/G1zDYvQntXgWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9X= MY8bK+BvZ8JUzGAEQV+Wy87xm/xbwZ1lwewGmCIIhYnCZXjKvDaQNrfIzkAKXYZl11wR16omfky= HIP0RB/2CV8GrRkNldbNmKbYU2enC0uV6bkfUNUd8P1ury3ktQADO05UV6azx1IE/dRULDomjGS= VXEFhVbrXMoncTV99smBH5ZW327igzP3trY2ONCyyQ6FtbRLUw2yZ8p+FwARifyCvRDV048rcfX= doT3j5fXp1+BVxdx2um+HGnuX9egX4dY01U0iVK2R80nMaELy42O7R39fz/1f8C/hZ5YvjpSKGw= AAAABJRU5ErkJggg=3D=3D" width=3D"20" height=3D"20" alt=3D"" style=3D"margin= -top:0.45pt; margin-left:-0.3pt; position:absolute" /></span><span> </= span></p></td><td style=3D"width:198.9pt; border:0.75pt solid #000000; padd= ing:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-ind= ent:0pt; line-height:normal; font-size:11pt"><a href=3D"http://orcid.org/00= 00-0002-6178-9872" style=3D"text-decoration:none"><span class=3D"Hyperlink"= >http://orcid.org/0000-0002-6178-9872</span></a></p></td><td style=3D"borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= ; vertical-align:top"></td></tr><tr style=3D"height:18.65pt"><td style=3D"w= idth:6.75pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-alig= n:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:center; l= ine-height:normal"><span> </span></p></td><td colspan=3D"4" style=3D"w= idth:440.55pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-al= ign:top"><p style=3D"margin-left:7.1pt; margin-bottom:0pt; text-indent:-7.1= pt; text-align:justify; line-height:normal"><span>Universidad Bolivariana d= el Ecuador (UBE), Dur=C3=A1n, Ecuador</span></p><p style=3D"margin-left:7.1= pt; margin-bottom:0pt; text-indent:-7.1pt; text-align:justify; line-height:= normal"><a href=3D"mailto:sgarciah@ube.edu.ec" style=3D"text-decoration:non= e"><span class=3D"Hyperlink" style=3D"font-size:11pt">sgarciah@ube.edu.ec</= span></a><span> </span></p></td></tr><tr style=3D"height:6.3pt"><td style= =3D"width:6.75pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical= -align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:cent= er; line-height:normal"><a id=3D"_Hlk194343133"><span style=3D"font-size:8p= t; font-weight:bold; vertical-align:super">4</span></a></p></td><td style= =3D"width:205.25pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertic= al-align:top"><p style=3D"margin-left:7.1pt; margin-bottom:0pt; text-indent= :-7.1pt; text-align:justify; line-height:normal"><span>Marbel Guilarte Legr= =C3=A1</span></p></td><td style=3D"width:14.35pt; border:0.75pt solid #0000= 00; padding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; = text-indent:0pt; text-align:center; line-height:normal"><span style=3D"heig= ht:0pt; text-align:left; display:block; position:absolute; z-index:7"><img = src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABQAAAAUCAYAAACNiR0NAA= AABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAA2lJREFUOI21lEtoXVUUhr+19= 7n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQiUhUnFqo4cGIRQUGd+KDY+Jp25ouiGCOx= Elqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe///Wv/aiy1cBV/83NNOPr/VWHunqO5OVNu= NlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNNZ+57RTjDTvqFM1IvNiGXWJvD/9x8yXB/= efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XLleTd648Z/863v3nkjWCL59dp/fWSsfzOXNkShKa= cvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082AAzADZXyPj+wL8ehQ1NH700v0N35OAroutW0rxDF= 6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQtZ0VEU1QTPtmAkDygiEBTsTxq6hx65fWT= Oy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqFJrzDF5+Sv+Wvg+y+IEVXaGibsbOO5hGB= SkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52oNtTMwcBbE0YteeC7we4LinSI9Z03dBN= UVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg17AAwqpRW9fqayNkiM0tjqDrag67mDCi0= ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKrR2zreIDURZTrZ7NTBYdeBPAU+cY59zxCkFlXjHi= I2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYjFGqkldT0J4EkY/ZovBb+klbQ/G1zDYvQntXgWFC= 5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGAEQV+Wy87xm/xbwZ1lwewGmCIIhYnCZXj= KvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2CV8GrRkNldbNmKbYU2enC0uV6bkfUNUd8P1ury3= ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbrXMoncTV99smBH5ZW327igzP3trY2ONCyyQ6FtbR= LUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fXp1+BVxdx2um+HGnuX9egX4dY01U0iVK2R80nMaE= Ly42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJggg=3D=3D" width=3D"20" height=3D"= 20" alt=3D"" style=3D"margin-top:0.45pt; margin-left:-0.3pt; position:absol= ute" /></span><span> </span></p></td><td style=3D"width:198.9pt; borde= r:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><p style=3D= "margin-bottom:0pt; text-indent:0pt; line-height:normal; font-size:11pt"><a= href=3D"http://orcid.org/0000-0002-6592-391X" style=3D"text-decoration:non= e"><span class=3D"Hyperlink">http://orcid.org/0000-0002-6592-391X</span></a= ></p></td><td style=3D"border-top:0.75pt solid #000000; border-bottom:0.75p= t solid #000000; padding:0pt; vertical-align:top"></td></tr><tr style=3D"he= ight:18.65pt"><td style=3D"width:6.75pt; border:0.75pt solid #000000; paddi= ng:0pt 5.03pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-inde= nt:0pt; text-align:center; line-height:normal"><span> </span></p></td>= <td colspan=3D"4" style=3D"width:440.55pt; border:0.75pt solid #000000; pad= ding:0pt 5.03pt; vertical-align:top"><p style=3D"margin-left:7.1pt; margin-= bottom:0pt; text-indent:-7.1pt; text-align:justify; line-height:normal"><sp= an>Universidad Bolivariana del Ecuador (UBE), Dur=C3=A1n, Ecuador</span></p= ><p style=3D"margin-left:7.1pt; margin-bottom:0pt; text-indent:-7.1pt; text= -align:justify; line-height:normal"><a href=3D"mailto:marbelguilarte1958@gm= ail.com" style=3D"text-decoration:none"><span class=3D"Hyperlink" style=3D"= font-size:11pt">marbelguilarte1958@gmail.com</span></a><span> </span></p></= td></tr><tr style=3D"height:0pt"><td style=3D"width:17.55pt"></td><td style= =3D"width:216.05pt"></td><td style=3D"width:25.15pt"></td><td style=3D"widt= h:209.7pt"></td><td style=3D"width:0.45pt"></td></tr></table><p style=3D"ma= rgin-bottom:0pt; text-indent:0pt; line-height:150%"><span> </span></p>= <table style=3D"width:436.8pt; margin-left:0.25pt; margin-bottom:0pt; paddi= ng:0pt; border-collapse:collapse"><tr style=3D"height:85.35pt"><td colspan= =3D"3" style=3D"width:177.6pt; padding:0pt 5.4pt; vertical-align:top"><p st= yle=3D"margin-bottom:0pt; text-align:right; line-height:150%; font-size:10p= t"><a id=3D"_Hlk92186133"><span class=3D"Hyperlink" style=3D"text-decoratio= n:none"> </span></a></p><p style=3D"margin-bottom:0pt; text-align:righ= t; line-height:150%; font-size:10pt"><span> </span></p></td><td colspa= n=3D"2" style=3D"width:237.6pt; border-top:0.75pt solid #000000; padding:0p= t 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:righ= t; line-height:115%; font-size:10pt"><span style=3D"font-weight:bold">Art= =C3=ADculo de Investigaci=C3=B3n Cient=C3=ADfica y Tecnol=C3=B3gica</span><= /p><p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-= size:10pt"><span>Enviado: </span></p><p style=3D"margin-bottom:0pt; text-al= ign:right; line-height:115%; font-size:10pt"><span>Revisado: </span></p><p = style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-size:1= 0pt"><span>Aceptado: </span></p><p style=3D"margin-bottom:0pt; text-align:r= ight; line-height:115%; font-size:10pt"><span>Publicado:</span></p><p style= =3D"margin-bottom:0pt; text-align:right; line-height:115%; font-size:10pt">= <span class=3D"label" style=3D"background-color:#ffffff">DOI:</span><span c= lass=3D"label" style=3D"background-color:#ffffff"> </span></p></td></t= r><tr style=3D"height:6pt"><td colspan=3D"3" style=3D"width:177.6pt; paddin= g:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:= right; line-height:150%; font-size:6pt"><span class=3D"Hyperlink" style=3D"= text-decoration:none"> </span></p><p style=3D"margin-bottom:0pt; text-= align:right; line-height:150%; font-size:6pt"><span class=3D"Hyperlink" sty= le=3D"text-decoration:none"> </span></p></td><td colspan=3D"2" style= =3D"width:237.6pt; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; v= ertical-align:top"><p style=3D"margin-bottom:0pt; text-align:right; line-he= ight:115%; font-size:6pt"><span style=3D"font-weight:bold"> </span></p= ></td></tr><tr style=3D"height:48.9pt"><td style=3D"width:71.4pt; padding:0= pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-align:jus= tify; line-height:150%"><span style=3D"font-weight:bold"> </span></p><= p style=3D"margin-bottom:0pt; text-align:justify; line-height:150%"><span s= tyle=3D"font-weight:bold">C=C3=ADtese:</span><span> </span></p></td><td sty= le=3D"width:1.4pt; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margi= n-bottom:0pt; text-align:justify; line-height:150%"><span style=3D"font-wei= ght:bold"> </span></p></td><td colspan=3D"2" style=3D"width:326.05pt; = border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:top">= <p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%; font-s= ize:10pt"><span> </span></p><p style=3D"margin-bottom:0pt; text-align:= justify; line-height:115%; font-size:10pt"><span>DATOS REVISTA</span></p><p= style=3D"margin-bottom:0pt; text-align:justify; line-height:115%; font-siz= e:10pt"><span>DATOS REVISTA</span></p><p style=3D"margin-bottom:0pt; text-a= lign:justify; line-height:115%; font-size:10pt"><span>DATOS REVISTA</span><= /p></td><td style=3D"border-top:0.75pt solid #000000; padding:0pt; vertical= -align:top"></td></tr><tr style=3D"height:0pt"><td style=3D"width:82.2pt"><= /td><td style=3D"width:12.2pt"></td><td style=3D"width:94pt"></td><td style= =3D"width:242.85pt"></td><td style=3D"width:5.55pt"></td></tr></table><p cl= ass=3D"Default" style=3D"line-height:150%"><img src=3D"data:image/png;base6= 4,iVBORw0KGgoAAAANSUhEUgAAAjcAAACMCAYAAACAuogxAAAABHNCSVQICAgIfAhkiAAAAAlwS= FlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzsnXd4VFXe+D93ZpKZZNIrIRB6TQhdEOngUgSkClIU= EGUJUlR4URcVVBTQVRBFRBSR3gOhJjQDIQXSJ5n0RnqfJJM6M/f3R8hds7q7rovu6/ubz/PAA7e= cc+655575nm87giiKImbMmDFjxowZM/9HkP23G2DGjBkzZsyYMfMoMQs3ZsyYMWPGjJn/U5iFGz= NmzJgxY8bM/ynMwo0ZM2bMmDFj5v8UZuHGjBkzZsyYMfN/CsVvX4XY6l8CSH8jiiCA2HJUFBGFh= 8dbjgnCj27+23EzZsyYMWPGjJmf4/fR3IjQLLVI/wHAJDT/U0QEUcQkCpgQQBAwic3XiaKx+fzf= 3WvGjBkzZsyYMfNz/A7CjYCkhREFQIYoglEEEwKiICBDRMCEIEBWSRXHbyeTW1GLIAiYBBETBhC= amssRzZobM2bMmDFjxsw/5vfR3AgiYKJZTWNqPoSIDCMCpocCi0BOWQ2f+sew9aSGHefiyCmvQx= DlCKK8+VbRhOl3abAZM2bMmDFj5o+K8HtkKBZFEwIiiILkXyMKzcYmuWhCFOSkFlex7dQ9QlL0N= IlKFDQwqqc962YPopurGkE0AgImQY7MrLwxY8aMGTNmzPwDfnvNjanZHCWKzT42gkwAmYBMEJAL= zQapvHI9Hxy7zY1kHSYskMlEDDJLbiXq2Hr6HukV+od6H6FZ0/N/kMbGRnx8fHB1dWXSpEns2rW= LVatW4erqiqurKyNHjuTTTz+V/v/jP7t372bAgAG4urpy8OBBAMrKyhg5ciS9evWioKAAgHv37j= F06FBcXV3p27cvAQEBjB49WirHz8+P2traVu1av349NTU1rY6dP3/+J2146623pPPu7u7S8TNnz= kjHP/zwQ+n4qFGj+O6775g0aZJ0bMOGDYSHh/+kbA8PDz755JNWbQgMDJTK/uCDD6RrV6xY8ehe= yn+J2tpaXn75ZbRa7e9e98yZM8nJyWl17Ny5c+zevRuT6W/fnlarxc3NDYCTJ0/y1Vdf/aLytVo= tH3zwASUlJT97PiwsjO3bt1NdXU1UVBQvvfTSr3yS5nZv3br1V9//90ybNu0XP+ejprGxURrnAQ= EB/5U2/FqamprYtWsXly9fbnX81q1bvPnmmwBcvXqVTz75hPr6+l9VR0ZGBhMnTiQ2NvY/bu//N= mpqali0aBGFhYWPpLzvvvuOZcuWYTQa/+E1p0+fZsOGDf9RPSaTiW+++Yb9+/f/R+X8asTfGpMo= GkyiWFnfKGqLq8QToWniZwGx4q4LceK5+9liVoVeLKisFTcfCxN7rz4ldll1Sey6+rLYdc0lscv= qi2K31f7iy/tui5kl1aLRZBKNRqNoMpl+82b/XtTV1YnfffedqFKpxLfeeksURVFMSkoS27VrJ0= ZHR4sTJ04Un3vuOVEURbGoqEh8+umnxTfffFO6/8iRI2JMTIxYUFAgdu/eXRw/frxYUlIimkwmM= SwsTIyIiBAbGxvFb7/9VrS3txf3798vGgwGMT09XZwzZ45479490cXFRZwxY0ardjU1NYknTpwQ= PT09xcrKyp+0+5133hGffPJJMTs7W7xy5Yro7OwsvvLKK2JDQ4OYnJws2tjYiF9++aXU7nHjxok= +Pj5iQkKCKIqiePPmTXHFihViUVGRCIizZ88WRVEUT506JYaHh4vPPPOMuGzZMlGn04mXL18Wo6= KipLrT09PFxx9/XNyzZ48oiqJYXl4uPvHEE+LatWtFvV7/qF7N/0qKiorEzz777Dcpe+3ataK3t= 7eYkZEhhoSEiEePHv2H1y5cuFB81NNHbW2tuHDhQnH58uWiTqd7pGX/EnJycsSDBw/+wzG0ZMkS= 8eDBg4+kLpPJJIaHh4shISG/+J7Q0FCxR48e4smTJx9JG34vbt++LXp7e4v+/v7SsYKCAnH+/Pn= iwoULH0kdGo1GTE9PfyRl/VbExcWJu3bt+rfvO3nypGhnZyfm5eX9ousLCgrEffv2iQ0NDT85V1= 1dLUZERPxm35fRaBT37dsnZmdn/ybl/zs8slBwybYlij8K+RZpNIlo83UERGRxN6GA/JJa6kwWi= AhYKcDbS8WMIZ147k99sFQqOBqcR61B0ew7LAOTScmN2HLkxLHmaV86OKubQ8VFEwjCw4qao6z+= iEl7rl27xhtvvMGLL77Iu+++C0CPHj347LPPUCgUFBYWMnPmTAAKCwvJzMxkwYIF1NfXEx4ezrP= PPgtATEwML7zwAp988gl37txh8uTJNDU10aVLF4KCgvDz82PDhg08++yzyOVy2rRpw5tvvklVVR= UGg4EJEya0aldKSgonTpygpqbmb+H4P0Kr1eLp6YmDgwMTJkxgyZIlhIaG8uDBA+Li4nBxcaF37= 94ALFu2jKysLL7//nvpWJ8+fXBzcyMvLw+FQsGIESMAGDduHBYWFiQkJLBkyRKsra2ZOHGiVG9x= cTEHDhwgMTERS0tLAOrr60lPT2fVqlVYW1v/yz6vqKjg4MGDWFtbs3DhQgICAlCr1fTs2ZMOHTo= gl8spLi4mMDCQ7t274+LiwoULF5g2bRpKpZLw8HDs7OzQaDS8/PLLVFdXc+XKFYqKiujTpw9jxo= yR6jKZTJw8eRJRFGnTpg3Dhw9n9+7dqFQqZs2aRXBwMIWFhYwaNQpBELh16xYTJkwgOzub/v37o= 1QqOXz4MN26daNjx47s3LmT4OBgvL296d69u6S9evLJJ+nVq1er96PX6ykrK6OkpITBgwfzww8/= YG1tzZgxY7h27RqDBg1CJpMRHBzMpEmT+PTTTxk/fjxpaWns3r0bW1tb2rZti5OTE6Io4uPjQ0l= JCf7+/owYMYLDhw9LY8/CwoLevXtz4cIFrK2tcXNzo0+fPmi1WoKCgrCxsWHp0qUUFRWRkZHBgA= EDiI+Pp6KigtzcXGxsbJgzZw7Lly/n2rVrAGRlZZGTk8PIkSP5/vvvefLJJzl58iSDBg1iyJAha= DQa6ZmeffZZDAYDAQEBmEwm+vfvjyAIGI1G+vbty/HjxykqKqJDhw6MGzcOGxubn4yLnTt3Ehoa= irOzMyUlJTQ2NtKlSxcyMzPp1KkT/fr1o2vXrly9epXk5GS6d+9OdnY23bt3x9bWloiICEaMGEG= fPn0wGAyt3rMoihw5cgSA8ePHU1lZybvvvourqyuOjo4EBQXRpk0b7OzsSEtLY9myZZw5c4bS0l= JsbW1ZsmTJvxzXAMHBwcTGxkpa4PT0dCoqKpgxYwbnz5+nU6dODBs2DK1Wy/Xr1+nYsSNTpkxBJ= vvb7Hnw4EHUajUDBgzAw8OD7Oxsrly5gpeXF+PHj5f6rr6+Hn9/f/r160dgYCADBw7EwsKCe/fu= MWnSJFJSUsjPz2fRokU899xzpKamsnfvXuzs7Jg3bx6LFy/mwoULQPN8o9PpGDhwIJmZmVy8eBF= nZ2dmzJiByWTi6NGj1NXVMXr0aHr06EF0dDQpKSmYTCamTZvGxYsXkclkzJ49m44dO7bqk5MnT1= JQUMC4cePo3bs3t2/fxsLCgqSkJDp06MDYsWNbXX/gwAHatWtH9+7dad++PaGhody7d08aw+Xl5= SQnJ5Obm0tRUREjR47E19eX+/fvc/fuXezs7Bg/fjzt2rXj4MGD2NnZkZ2dzdWrV1Gr1fTp04dO= nTpx9epVTCYTTz/9NG3atJHqLysrIygoiOLiYqZOncqECROkOcVgMBAWFkZUVBS9evXiySefJC8= vj2vXrqHT6Rg3bhznzp3j9u3bAEydOpXr169TX1/P0KFDEQSB69evExoayqJFi1CpVERHR2NlZc= Xt27fp0aMHEyZMIDo6GlEUGTBgANHR0dy9exeAxYsXI5fLpbHZvn17Jk+ejFKpRBRFoqOj2bt3L= 2lpaSxdupSamhqsra3p0aMH8fHx3Lx5k65duzJu3DjS0tIoKSmhrKyMqqoqlixZgk6nIygoiPz8= fMaOHYuPj88vGvc/xyOSB5pDtE3NazlanIeNgsANbRFbjt7jcHABacUW1GGLKLdGVFhSjSX3s5r= 45Hwqp0PSeG6iL4vHdMJGYQKxuXEmQUY9SgJjivjwWDhpxTWIgoCIiAkRURRAbHZQ/qOh1+u5ev= UqBoOBTZs2tTo3Y8YM8vPzKSgooF+/fgCUlpaSn5/Pp59+yrx587h+/bp0vUajYdGiRUybNo033= niDxsZGqqurcXV1ZevWrTg6OrJgwQKUSiUA1tbW9OvXj/j4eOrr6xk+fLhUVnFxMadOnWLIkCG4= uLj8rHCj0Wjo0KEDarUaAKPRSH19PU1NTZw/fx4nJye6du1KfHw8AQEBjBkzhsGDB0v3Ozs707t= 3byIiIpDL5QwZMgQABwcHCgoKqKiowMvLC4Xib/J3VVUVX331FVOmTMHFxQWVSgVAcnIy1tbWeH= h4/Ms+LykpYdWqVTg4OHD58mViYmLQaDRERERw7NgxSVVraWlJbGws169fRxAELl++zN27d1m0a= BGvvvoqMTEx+Pv7k5iYSHh4ODdv3sTGxoYXXnihVX3vvvsuGzdupKCgAEdHR1avXg1Abm4u3377= LY6OjoSFhdHQ0IBaraampoYffviBtWvXUlxczMWLF6XnTklJoU2bNqjVapycnPj6668pLCykoqK= CS5cu0dDQAEB2djZvv/02zz//PMnJyQQGBrJx40YcHBzYuXMnubm5hISEEBERAcCVK1dISUmR2m= xtbY2NjQ3Ozs7U1tayYcMGbty4AcCXX36JwWCQTFfZ2dls2LCB4OBgioqKCA8PJyQkhJMnT9LU1= MQHH3yAs7Mzhw4dIjg4mO3bt/Pdd98REhLC888/z1//+lesrKzYunUrYWFhUhtKS0tZuHAhZ86c= 4ciRI6xevZqVK1fS0NDApUuXqK2t5f3330ehUBAUFERUVBR+fn58+umnGI1GCgoKWLZsGbdv3yY= pKYn9+/fj7OzM9evXSU1N/dmx0aZNG2xsbHB0dKSqqoqXX36ZvXv38tFHH5Gfn8/mzZu5fPkyer= 2eNWvW8NFHH3Hnzh1WrFjB9evXOX/+PIcOHaKuro733nuPO3fuoNVqOXnyJAEBAdy9e5fc3Fy0W= i1ZWVn88MMPODs7o1arCQkJYcWKFRw/fpxNmzYRGBjIZ599RkJCAq+//jppaWn/cmxHRkZy48YN= 2rRpQ3BwMEePHqWxsZGPPvoIhUJBUlISV65coaCggE2bNuHl5cWJEye4deuWVIZGoyE9PZ20tDS= +/vprkpOTWbduHV5eXty4cYOrV69K1x47dowVK1Zw9OhRBEHgm2++oaamhu+//57MzEyqqqr44o= svANDpdMTFxeHo6MiHH34ojT1o/q5XrlxJUFAQRUVFrF69Gi8vL06fPk1YWBg3b94kMjKS+vp6d= u/ezcWLF1m8eDFpaWm0bduWc+fOUVRURHl5uWSWb+G7774jISEBuVzOjh07OHXqFEuXLuWLL76g= tLSUt99+u9X1d+7cIT8/H39/f65fv05hYSHnz5/Hy8uLe/fu8d5777F3714WL15MZmYmAFu2bOH= +/fsEBwfj5eVFaWkpe/bsYfv27axdu5aYmBi8vLywt7fH0dERo9HI4cOHUalU6PV6/vrXv1JXVw= dAQ0MD/v7+FBUVYWVlxZo1a6iqqpLaFx8fz7Fjx/Dy8mLbtm3cunWL06dPU19fT35+Pjt37sTe3= h57e3s8PDzw8/Pj888/Ry6Xo1ar2bNnDz179qSqqop58+YRGBjIkiVL+Pzzz/Hy8mL79u3cv3+f= 9evXc+PGDTIyMjh37hwODg5cunSJwMBAzp07R0NDA56enly+fFkSUAHUajVqtZo2bdpQUFDA8uX= LuX//Punp6bz//vvSmDt58iSLFi3irbfekgT9/Px8zp07R1ZWFl5eXrzyyiuSS8Wv4RFpboTmgG= /hYWCUKNIkyLimKWDLgTBK6ixBZoEoN2BEQGaoRSGKCCYRUW5BaYOMvYFZNDQZWTLBB4PRxIHrm= TRiiVwQMcnlNIlW3EyuhlNRvDFvEO2cLDEhR4GA/KE3zh+NpqYmdDodHTt2xMnJqdU5URR58OCB= 9EGYTCbS0tJwdnbmq6++wtXVldDQUOn6xMREFi5cyOLFizl37hz79u2jW7duKBQKHjx4gEqlomv= Xrj9pQ3p6Ok1NTa1W/XPmzCEsLAyFQoG9vf1P7snOzqasrAxfX1/kcjkA4eHhtGvXDgcHByIiIn= B3d8fDw4OkpCQEQcDb2xsLCws+//xzNm7cCMCmTZvIzs5GJpPh5eUllZ+ZmYm9vf1PVmBffPEF2= 7Zt4+OPP0b8kR98UlISHh4eeHp6/ss+37BhA8uXL6egoABXV1d69+7NtGnT2LRpE0uWLJG0QQ4O= DnTp0oXKykpcXV3p3Lkz9vb2bNiwgS+++IKXX36ZuLg44uPjmT17Nm5ubixfvlya8Fp49dVXuX/= /PjNnzsTS0pKvvvoKtVqN0Wikf//+vPLKK6Snp2MymaisrGT27NlYWVlx584doFnIOnHiBDt27G= DQoEHY2toSGxtLv3796N69O8XFxfj4+PD8889jMBhQKpW0a9eO8ePH07t3b5YsWUJubi7e3t7Mm= TOHU6dOoVAo8PLyQiaT4eHh0arvAdq2bUunTp3o3r07f/rTn0hJScHCwoKsrCyuX7/OzZs3iY+P= 54MPPpDqsrCwwMXFhbNnz+Ln58fSpUsJDw/H09OT+fPnM2PGDCwsLIBm/4o+ffowZ84cnJ2deea= ZZ6isrOTcuXM89dRTADg5ObFmzRpCQkKYOXMmb7/9Nu+//z41NTUcOHCAxsZGvv76a/bv38+5c+= eYO3cu//M//8OWLVuYNWsWarWaxMREALp27crp06d5+eWXuXPnDnPnzv3ZsTFq1ChSU1Px9fXFZ= DJhb2/PrFmz2Lt3L1ZWVpIPQrdu3QCYOHEiCoWCU6dOsXr1atLS0njw4AHp6el88MEHyOVyZDIZ= gwYNYseOHfj5+bF161amTZtGZWUlcrmcgQMH4uXlRY8ePcjMzGTdunXs3LkTlUqFp6cna9asoaS= khKSkJFxcXP7huG5qaiIoKIgePXowZ84cvv/+eyIiIujTpw8KhQK1Wk23bt3IzMzk7t27nD17lq= CgIOrq6vD29pa0F46OjuzYsYN33nmHv/zlL1y4cIFLly4RHBxMQ0MDzs7OzJo1C4AJEybQoUMHX= n/9dYxGIxqNBltbW1xdXbGwsKBbt27S4sfW1pZp06Yxa9YsKioquHHjBgMHDpTOzZ8/n4KCAu7f= v0/v3r2ZPn06EyZMQKFQIIoijo6O0qJk8+bNTJs2jaeeeoohQ4bQ0NBAYGAga9asYfTo0a36Zff= u3ZJwU1dXx7Zt2/jTn/7E9OnT8fDw+Ilw4+7uzjfffMPHH3/MpEmT2L17Nz4+PkyfPp1Jkybh6O= jI3bt3KS0t5dlnn8XV1ZW0tDT279/PyJEjmT59OiUlJezcuZMpU6Zw8OBBZs2ahY+PD/Hx8Tg6O= uLg4MDx48fJzMzEZDIxbNgwqqqqsLKyora2lhMnThASEoJcLsfW1pbi4mKpfcHBwXz99dccOnSI= mpoaRowYQVNTE2vWrMHBwYHGxkbCw8MpKSmRtGwHDhxg1qxZJCQkYDKZmD59OlOmTOH27dtYW1v= z1FNPMXfuXIYMGcK7776Ls7Mz48ePB5rnYgsLC+bPn8/MmTOprq5mz549zJ07lx49euDu7k54eD= h6vR61Wk379u3x8vJi7NixdOvWjRkzZgBw+/ZtTp8+zdWrV6mrq6Nv374sXboUnU7H4sWLef/99= 0lKSuLy5csEBASgUCiwsrIiLy/vFy1af45HasmRiSZAoEmUcU2Tx+b9IRTXKxAVckTBiAID/T1k= rJ3amV1+g/ngOV+GdVZhJa+lCTlHAzM5FpTAtJHdeGZkOyzFRmRGEzLRAIIJBBXB2ip2+EeTW16= PHJAhgmhs1uI8yof5HWgZvE1NTej1eqDZcTAtLQ2DwUBMTAw+Pj44ODhgMBhISEjA19eXtm3b0q= ZNG0aPHk1eXh6VlZWShmPYsGEsXryYzZs3S8fc3d0xGo1UV1dLdSckJFBcXExSUhKTJk1CJpNRU= 1PD3r17+eabb6ivr+e9995rJUS0EBISgkqlwsPDg5qaGrZv305ubi4vvPACdXV1pKamMnr0aARB= wMvLC1tbW5KTk6mvr2f58uXY2dmxYMEC/Pz8uHPnDv369Ws1gIOCgnB3d5eEG5PJxM2bN+nbty8= VFRVoNJpW7QoKCsLT01NS7WZkZFBQUEBiYiKVlZXSdS2akDVr1hAWFsa6desQBIGIiAhp9diygm= qhqakJo9FIY2MjhYWFWFtbY2FhIQlBoihy8+ZN3nzzTXbu3PmTvrK2tpZ+5BQKBTY2NqSnp6PX6= zl9+jQKhYKuXbsSFRXFgwcP6NSpExYWFpIgMHToUL755hu2b9/OoUOHWpW9YcMGli1bhr+/f6v+= k8vlKJVKVCqVNAaUSiWCILQyPzQ1NWEymaitraWoqKiVw3ALMplM0vZZWFhQX19PXV0dTU1NQLO= ptKVso9FIQEAAlZWVzJ8/H6VSSVZWFg0NDVhbW1NRUYFKpZL6QqlUYjQakclk1NXVtTIVyWQyyc= TYck/LeVEUaWxsZOrUqcjlclatWiX9gMtkMmQyGXK5HCsrK6DZbDZw4EDmzJnD/Pnzf/KM/whBE= LC0tMTW1raVBrEFCwsLSavZ0keiKCKXy7GwsGDFihVUV1dz5MgRPD09CQ4OJiAggG+//fZny2t5= b3Z2diQlJbFixQqeeuopHBwcfvJu8vPzpW+qpa2CIFBdXY3JZJLGJzTPKaIo0tDQIDmltggTNTU= 1rbSN9vb2JCcno1QqWb58OWVlZcycOZOCggJ0Oh1r1qyRrlUqlcjlckwmEyaTCYVCIT2XwWCgsb= GR+vp6cnNzkclkUn9VV1fToUOHVv3cooW1tLQkJSWFhoYGLCws0Ov1HD58mF27dvHWW2/h5OSEp= aWlVDfA9u3buXTpEu+8844kTLWgUqk4efIkVVVVkvZUqVSiVCqRyWQ/6VcXFxcCAwO5ceMG77//= PpaWlqSmpmI0GjGZTDg4OEjvuuV7amxsxMrKStJ+iqKISqWSxmNLO3/8nseOHUtCQgI6nY4TJ05= Ii1tBEOjTpw+BgYFUVlai0Who3759q/fz1ltvUVxcTG1tLU8//TQ6nY7Kykrp+/wxarUauVyOIA= golUrS09Opq6tDoVBgMplQq9XSXPHj9rWMnxYTfU1NDSqVivr6esrLyyWBSy6XS/Pb3yOXy1u91= yVLllBYWCiZoKysrLC0tGzVP127duXs2bNUVFSQmpoquTH8GuSb/t4e8isRaRZsTCJE55Sy83Qc= WRWWIJchiiYcVCbmPNGOtdP7Mr5PO7q629OrvRP9urehtq6erIIqarEiOb8UpUJg+ohuWMpEUh6= U02QUEQU5CAJG5OQUV1NaWU3vzq7YqRQtbjcP0wX+cTQ4SqUSNzc3bty4QWJiIlqtlvDwcDQaDe= Hh4Zw9exZRFBk2bBhHjhzh6tWrNDY2UlVVRUREBP7+/kRHR3Px4kUKCwsZO3YsVlZW9OrVi6tXr= 7J06VJcXFzw9vYmMjKSyMhIUlNTCQ0NJSwsjNjYWIKCgrC3t8fLy4udO3fS0NDA1KlT0Wq17N69= m8zMTAYOHEiPHj0A8Pf359ChQ2RnZ2Nra0tAQABxcXGsWrUKX19fvvzyS8LCwvDx8aFv37507Ng= RZ2dngoKCSEtLIzQ0lEuXLvHcc89x7949Ll68iLu7O/3798fKyoqjR4+yb98+GhsbGTt2LB4eHm= zbto3Lly8zdepUZDIZ27dvJyIiAnt7e9LT0yUfgZqaGkJDQ9myZQvt27dn/fr12Nvb07dvX6B50= rlx4wazZ8/GxsaGsrIy6uvr+eyzz1Cr1ahUKkaNGiUJFoWFhRw6dIiKigpCQkKoq6sjJSWFhIQE= nJ2duXz5MsXFxahUKkpLS2lsbCQoKIjHHntMWt2fPn2as2fP4u3tTd++fTGZTOzbt4+8vDwSExM= ZOnQooihy5coVPDw86NmzJ7GxsRw8eBArKyvu3buHRqPBaDTSu3dv2rVrx9dff03btm25dOkSQ4= cOJS4ujsTERAYMGICbmxulpaUcP36cmJgY2rVrx7Fjx6ipqaG+vp6zZ8/i7u6OWq3m4sWLFBQUc= PfuXWxtbdHpdJw+fZru3buj0+kIDw+nurqa8PBwEhMTmTlzJnfu3CE0NJSUlBRCQ0Px8fEhPDyc= pKQkevbsyXvvvYerqysGg0ESvKKiooiPj6empgaNRsONGzfo168f6enp3L17l/z8fKKionj55Ze= 5du0aP/zwA7169eLYsWOSJiwgIAClUkllZaUk/F67dg1fX18iIiLIz88nJSWFsLAwRo0aBTRr+n= Q6HVZWVpSXl6NQKLh//z5yuZzk5GSys7Pp2bOn9D0WFxdz9OhR7OzsuHv3Lrdv38bHx4eBAwcSE= xPDvn37cHd3R6/XExgYiIuLCzqdjqioKNq2bcuVK1coLi5m3rx5QHNUoV6vJzc3l/DwcLRaLdXV= 1fj4+EjPp9frGThwIF9++SXZ2dmMHj2aTp06sX//fsLCwrCyskKj0WBnZ4eNjQ3+/v7Y2NgQHR3= Nxo0bGTJkiKSFq6+v58iRI2RnZxMdHY1cLmfixIlSpFtwcDBpaWm88MIL3Lp1i3v37hEeHo5Sqa= Rz584A3L17l7179wJIviNBQUHEx8cTFRWFIAh06dIFgLq6Og4ePEh9fb1kYhs/frw0f2VkZHDv3= j369euHnZ0d4eHhxMfHk5aWxpw5cwgKCuL27dv07NkTf39/NBoNCxcu5OrVqyQkJBAWFoaNjQ1J= SUno9XoqKyuJiIhAr9dz9+5dHBwc6Nu3L+fOncPCwoLc3FxiY2MZPHiwFMnn7OzMzp07KS0tJTg= 4GJVusl1QAAAgAElEQVRKxcGDB1EqlSQnJ3P9+nUGDBhA9+7dpXfWUp6rqytTp07l+PHjpKamEh= 0dzcKFC3FxcSEgIEDqZ0EQWLRokWRSiY2NpVevXpSUlHD8+HE6dOhA3759iY2NlfqpvLycO3fuo= NFoyMnJoXv37pLAlZOTw8WLF0lJSSEyMhKj0cixY8dQKBSMGTOG06dPEx8fT3BwMB4eHpSXlxMc= HCz9hnh6enLlyhWysrKIj48nNDSUsWPH4u3tzY0bNwgNDUWj0eDl5UWHDh04dOgQtra2xMfHc+H= CBTw8PAgPDyclJYUxY8YQFRVFZGQksbGxGI1G2rZtK32bOTk5DB8+vJWWvcUnTaFQSH6bU6dO5d= y5cyQkJHDv3j1qamo4f/485eXlNDY24u/vj4ODA507d5aePTw8nK5du/6s9eCX8Mjy3IgP/WzK9= QY+9o/CP7wUA1aYhEZclU28OLE3c4Z1xFb50FlYBBkmjKKM/Kp6vrwQw/HQAoxyFY5KI8+O8GLR= eG8O30ji0M1Mqg2WCLJmzxqZwYicRsb3d+EvzwzG3doCQdZimvrjCDctJCQkSJO4Wq3mscce4+b= Nm9L5lg/j71Gr1bRt25acnBxJCGpZ3UZFReHj4yNJ4ElJSa3s9uPHj5d+vAA6d+5MRkYGnp6e+P= r6UlBQQExMDABeXl74+voCzeHkRUVFrdrRv39/PD09yc/PR6PR0NjYKPn0tKxIfnyfIAj4+PiQk= 5ODTqeTzFZubm5ERERIoefe3t506tSJCxcuYGtrK/ketTjLWVpaYjAYfrL6srKywsfHh7Vr17J+= /XoGDBggnWvpB0dHR/r27YvBYCAxMZHy8nJ69uxJly5dpNV4TU0Nt2/fllaWXbp0IT4+HrlcjoO= DAzqdTgrh12g00srG09OT/v37A0gq4i5dukgC4qVLlwDw9fXFy8uLpqYm4uPj8fT0xM3NjZycHO= Lj43FycsLV1ZWCggKqqqoYPXo0FhYWBAUF4eHhgUqlIjMzU1ot9+3bFw8PD6qqqoiNjUWn09GlS= xfS09NRKpXY2tpSWlpKmzZtaN++PdHR0UCzWaBHjx5kZWVRWFiIl5cXNjY2aLVabGxsMJlM6PV6= Ro8eTVlZGfHx8Tg4OFBZWcnIkSOJjIxEr9fz+OOPo9VqqayspHv37nTv3p2MjAzJPDR69GgSExM= pLi6mb9++HD58mKqqKoYNG0bnzp3p0aMH9+/fp6SkhN69e5OYmCitKqurq5HJZLi5uZGfn0/Xrl= 2pqKigrKwMpVIpaSdaxqNarebOnTvY2trStWtXSUBsMbXW1dURFhbG66+/Lo2NqqoqwsLCcHBwQ= K/Xo9fradeuHd7e3uTk5KDVanFwcACgsrISlUqFUqlEp9NhbW0tpVF44oknsLCwkHxZRowYQUlJ= ibTiHTlyJGq1WnrWIUOGEB4eDjQ72nfo0IHs7Gzi4+NxdnZGp9Mhl8vx8vIiNTUVKysrXF1dOXT= oEFOnTpWc8RsaGoiOjqa0tJSbN2/S0NDA559/zu3bt6mursbKygpPT0+6desmCQIAkyZNklbPZW= VlpKenU1xcTMeOHenVqxdFRUVERUVhYWHBkCFDpD4oLy/nySefZPfu3ZSXl+Pt7Y2Xlxe5ubnEx= MRgY2ODIAiMGjWKqqoqYmJiqKqqYtCgQdjb2xMXF0dJSYnkmN3Q0MCYMWMoKSlBo9EAMHbsWHQ6= HZGRkT95zy1zVXZ2tjRWGhsb8fX1baXtCAkJoaKigvbt20vj2tnZmYaGBmpqavDw8JBMZPn5+WR= kZFBZWSnNa8nJyaSmpuLg4MDw4cPRarXs3buXxx57DHt7e4YMGYKzszNpaWkkJSVJc1VOTg7Z2d= m4uroycOBACgoKiI2NpW3bttL3ZzAY6NGjhyQwAlRXVxMTE4NOp6N9+/Y4OjoSFxeHlZUVo0ePJ= iUlhfT0dACmTJlCUVERcXFxNDQ00LNnT1xdXYmJiaG6ulqakx577DHc3NwoLCzk/v37AEyePJkH= Dx4QHx+Pu7s7NTU16PV6nJycqKurk5yQS0pKSEtLQyaTMWTIEOzs7AgNDaWqqgp3d/dWvpTwt9+= zTp06kZmZia2tLY899hjFxcXEx8djaWlJnz59iIyMxMbGBktLS0mrO3DgQGk+dnFxYejQofxaHo= 1wIz78SzARkl7O+q9DKamzQBRMWAgGlo7uyJ8n9sbaEkRBjpxmKxMIGIVm21iVwcR7h+5w/l4xR= rk1KlMNy8d1YsGk/nx9OY6DP2RRJ9gie2iAEhBQGWp4aWJXXpzYB5VMjvDHlG3MPGIaGhrYtWsX= HTp0YPbs2T/rEG3mv0+Lo/vy5ct/97oXLFjAk08+yeLFi3/3uh8F+/fvR6fTsXr16p81CRw6dIi= wsDA+//zz36wNLcJNZGTkb1bH/0a0Wi2HDh1i5cqVtG3b9r/dHDP/gEfjUCy0rJzlRKWXUqE3gU= yGzGhkYGcbnhnRFZuHgo2sxfn3oSQiF0yYkGGrkPOXRSOwsIzg0r18nG1UdG7vioNKwZI/eVNaV= ce5+2UIcgUmmQJBNNEo2HDpXgGP9/BkYFdXyTRl5v9vlEol69at+283w8w/ISwsjLNnz9K5c2dG= jRrVyjz0e9ASxv5H5Z+FhhcWFrJr1y7UajWhoaE8/vjjv0kbTpw4gUKhYO7cuRw/fvw3qeN/Gya= TiTNnznDt2jW6dOnC0qVL/9tNMvMPeHTbL4giCALrvw/jTHgRgkKFzFjNOwv6M29oJ+SIiKIM4e= Hel80mpOawcRMyBFNz9uHsqnrO3U6gSztXxvdrj4UoIAgiySW1vPZlMEllAsjlyDFgMilQ0sDik= e1YOcUXa+UjS9tjxowZM2bMmPmD8kiipUT+tlm3wSg+NFPJsBSN9OnohFwEk2jCKDTvLSU8zE3T= cpPQnKgGEGlvr2TJk30Z5+uBpdjYLAKJAt3dbJg4tAOiqaHZAiaKCIJIvSjnbnIxRdXNUS6PSlb= 7/42tW7dKOSn+nlmzZrVamW3evBk/P79W0Ve/JyaTiXPnznHp0iVKSkpYuHDhL7rvxIkTBAYG/u= p6P/300/8ovfuWLVuYNGlSq60qfktaHK9b2Lp1689GdP0z6urq2LVr129qerh48SIzZ85kzpw5r= aLbfo7Q0FCOHz9OY2Pjf1Tn7NmzKS0t/Y/KMPPPKSwsbOXT9GPS0tL4/vvvpRwucXFxbNy4kbKy= sn9Zrk6n45tvvvnJNiG/JWfPnv2XW3lkZGTg5+f3O7Xob9TW1rJx40auXLnS6vidO3fYvXv3796= e/y08EuHmoVwCgIejFQqZiAkTiAaMJhFREEBQIAoiCH+/n4UgCTdGmRyQY21pgaXcAkFQgiDDJM= gQEHjCpx3OKhkyUcQkyh4m75OTXd5IXvmv25PETDOxsbGS4+ffc/36dTIyMgAoKioiMjKSHTt2Y= Gtr+5u3a9u2bT85JpPJmDJlipS588dJyP4Zs2bNYty4cb+qHWfOnGHr1q2/aPL9OQICAjAajRw/= fpzIyEiSk5N/VTn/Dq+++iqDBg0CmiOBunTpwsqVK/+tMjQaDa+88spvJgikpaVx584d/vrXv1J= bW0twcPA/vX7IkCHMnj27Vajzv8vq1avx9/f/1fsY/R7U1dVx4cKFnzjv/zNCQkKIior6DVv17+= Hu7s577733s+e6dOnC/PnzsbW1xWg00tDQwKJFi36S7+vn2LZtG/v27ZPSZ/zW6HQ6XFxcfnafs= 6amJvbs2QNAp06d2LFjx+/Sph+TnJzM/PnzpWzFLVnLhw0b9h/tzfZH55GFgjcLKCL1JhmhCbnU= GWUYAEcrgb6d3VDKZMgEIwLG5rBuQBAebtQgCg+dPkVpRwVBkDUfE0QERGRAXZOcS+G5VDeIIGu= OulIgYDKZeKybC73b2T8s94/jeVNbW4tGoyErKwsLCwtsbGzIzMxEq9VKqdctLS0JDw9HoVAQFx= eHSqWioKCArKwsKU9BYWEhcXFxFBYW4uLi0iqPRmRkJLm5udTU1EgJ2fLz88nMzMTGxga9Xk+XL= l0YN24cSqWS6OhocnJyaGhooLq6mqeffpohQ4bg6OhIbGwsw4cPp7KyEicnJ7KyskhKSqKuro70= 9HTq6+t/MkFVVVURGRlJSUkJ9vb2UrbU1NRUamtrcXFxoaamhsLCQoqKikhNTUUul3P9+nWOHz9= Oz549sbCwICcnh8zMTARBQK/X09TUxNy5c/n666+ZMWMGWq0We3t7CgsLycnJQaVSodFoKCwsxM= PDg5ycHARBQC6Xk5aWRk5OjhQd0EJERATZ2dnU1dVhb28vOWv26tWLpKQk+vbt2yqCoiUL9D+jq= qqK06dPU1VVhZubG2vWrKG0tJS0tDT0ej0uLi4UFRVRWFhISkoKBoMBnU5HTU0NCQkJiKJIcXEx= ycnJuLm5YTQaSU5OJi0tDZ1Oh5ubG3V1dcTExPDgwQNkMhm2trYkJCRI0QgajQZra2vKyspwcnK= iqamJxMREZDIZsbGxqNVqKS9MCzExMdTU1GAwGPD19aVr164kJSWRkpKCQqFoJdzW1tYSHx9PbW= 0tSUlJODg4YGlpSXx8PIWFhVJ/tmzRoVQqsbKy4tatW0RGRuLu7s6GDRtQq9VotVqMRiP29vbk5= uZSWFhIdXU1jo6OlJaWotPpsLW1pby8XHrmltDf3NxcqqqqSEpKoqGhAScnJ3Jzc0lISKCwsBAb= GxtmzJjBp59+ip+fHyqVisTERNLT05HJZNjZ2aHVaikpKcFkMkk5dqA5C3dGRgZJSUnSe6+oqCA= hIYGsrCypT5KTk7GwsECj0aDX62lsbJSif+zt7dFqtZhMJinCxd7eHpPJRGRkJNnZ2bi4uBASEs= KOHTvo3bs3bdu2RavVShErtra2ZGVlUV1dTUZGhhTmv3PnTqqqqujZsycNDQ1ERUVRXl6Oq6srD= Q0NxMfHYzAYpJwnLTQ0NBAREUFBQQG2trYolUoyMjLQarVUVFTg7u5ObW0t+fn5lJSUkJycjJWV= lZSHSBRFIiMjKSoqwsHBgZycHPLy8rC0tCQvL08KfU5KSsJgMKBSqaitraW0tBQbGxuampqk3FX= W1tZYWVmRn59PVVUVKSkpFBQUtHLc9fX1JS8vD1dXV4qLizGZTNK17u7uJCQkUFZWhr29vZQzLD= U1Fb1eL/W7IAjY2dlJc215eTn29vbU19eTkZGBTqcjKSmJ9u3bYzAYaGhokFIcxMXFUV9fjyiK7= N+/nytXrkgpHfLy8qQUAS1h3tbW1giCQGxsLFlZWdTV1eHs7CyNqZZ36+rqik6nIzk5GRsbG+kd= NTU1SfNNY2OjlCursLCQ3NxcXFxcMJlMNDY2snnzZpqamvDx8ZHmEDs7O3JyckhMTKSsrAxHR0f= 0ej3R0dHk5eVJY+rHaDQaKbq2vr6etLQ0KioqUCqVxMbGSnmlWso1GAw4Ojq2KiMqKgqdTodCoc= DS0lKK6qqtrZUiEiMjI6VktS1h8BUVFdI39HPbpPxSHomTiig2xy9V6Ovp6eXAKN+2nLtfTKPMm= kv3HtCljT2T+nfEyqI57Z4AzVqch3FPICCIIBNajoggCj/yzWkWVgorqqmqa0QULJAhIgogmkSM= QNXf7Wb9R6C+vp7Tp0+j0WikUNfVq1dz+vRpKa+Dt7c3arWal156idWrV5Oeno61tTU9e/YkMjJ= Sivr47LPPkMlkZGZmMmrUqFYS+969ezl48CAzZ84kLi6Ojh074uvry/nz59m4cSPe3t7MmzePUa= NGMWvWLD766CP69++PSqVi8ODBLF68mBdeeIGXX36ZN954g8cff5zQ0FDWrl1LSUkJK1euZNy4c= cjlcgwGA1euXJF+EGpqali3bh1ubm5oNBqWL19Ou3btOHr0KDKZDK1Wy7p167h79y4XLlxg2LBh= JCUlSZNFQUEBFy5coKysjNTUVAYOHMjAgQM5ePAg8+bNY/jw4ej1eo4ePUpERATDhg2jZ8+eHDx= 4kPXr13P06FEuXLjA1atXWblyJX5+flRUVLB3714GDx7MyJEjpczNycnJvPbaawwaNIj6+npef/= 31VsnGWkhPT+e9997Dy8sLf39/KaTxH1FRUYFWq0Wn03H58mWMRiOXLl2SJryVK1dy5swZiouL6= dOnD7W1tdy/f58RI0ZQXFxMVlYWjz/+OOfPn+fjjz/Gzs6OPXv24OrqSnBwMGfOnOH8+fNkZmZS= X18v7bfz0ksvceLECezt7bl8+TKNjY3k5+czbNgw9Ho927dvZ9WqVYSFhTF79mwWLlwovbcffvi= Bw4cP4+TkJG1XEB4eLjni1tbW8vXXXyMIgpQr6OOPP+bVV18lLCyMiRMnYmdnx4cffsikSZMYPX= o0d+/e5d69e9KPxQcffEBcXBxpaWlcu3YNFxcXDh8+jK2tLRqNho8++kgyh0ZFRUnvtFevXrz22= mvStgJpaWkMHjyYwYMH88477+Dj44MgCKSkpHDq1Ck+/vhjLC0tpVxQLRFSRqORq1evEhwcjFKp= pKioCD8/P86cOYOlpSX5+fls2bJFEn7j4uL4/vvvUavVkomzJWcINIeHP/XUU7z99tsMHDgQS0t= LsrOzGTBgAIWFhTQ1NbFs2TL+/Oc/88QTT6BQKCgoKOCTTz7h5s2bREREUF5ezsiRIykqKiIvL4= +YmBj0ej0BAQFSIrxp06bxl7/8hR49emBra0t6ejrvvvsuKSkpVFVVMWXKFClXTUFBAS+++KK0H= 1BNTQ0LFixotZ/Spk2bqK2tJTc3l5kzZzJy5Ei++eYbBEEgOTmZpUuXkpaWxqlTpxg2bBjJycmM= Hj1a2krEZDJx6NAhysvL+eijj4iLiyMqKgq1Ws3t27c5f/48V65cISoqiszMTLZu3cqpU6coKSl= h06ZNUr6uhoYGKdvuunXrcHFxoVOnTpw9e5bg4OBWi5D8/HwCAgKorq5GEASmT5/Oli1buHz5Mh= cvXiQiIoIlS5awceNG+vfvj62tLRkZGQwfPlwKT37jjTd47rnneOKJJ0hNTWXlypWcOHGC0NBQZ= s2axYkTJ7h8+TJpaWns3LmTLVu2EBMTQ1RUFMXFxTz//POEh4e32s4kLy+PAwcOcOzYMbKyssjN= zaVHjx4MGTKE7777Dg8PD0pLS/n0009xdHSkqamJS5cuceXKFQ4ePEhhYSHffvstGzZswNbWVkp= gGhgYiEqlIiQkhD//+c988MEHPPXUU9jY2NDY2EhFRQXTp08nJSWFsrIy7t+/zxdffMHjjz/O3L= lz+e677zAYDGi1WtasWUNsbCyRkZGoVCratm3L66+/LglT9+7d48CBA1Ly2I4dO5KSkkJqaiq7d= u3i9ddf59lnn2Xs2LHs3LkTOzs7EhMT2bVrl5QlPj09nT179qBWq+nevTsTJkzg448/xsnJiezs= bNauXUtUVBTXr1+nrq6OZ555BoDPP/+cJ554ggcPHtCrV6+fbEv07/CrhJsWkUQUH+adAdKLa/j= i3F3GDe3NvDHdySvWEZJRy4MqGV9d0mJpIWdS/47NvjIyEZnYrLERZS3amebNL5uNVOJDv5rmwk= XAJAhEJOdQ1dSEoLAETIjIMMoEFKJJSrz2R6K0tJSsrCxWrFiBq6srSUlJBAYG4u3tzbRp00hKS= uLgwYMMHz4cuVzOU089RVFREcePH2fp0qWo1WqKi4u5fv06NjY2vPnmmxQWFjJx4sRWws2UKVM4= evQoTz75JIIgEBQUxNatW7lz5w6pqanMmDFDSsFva2tLWVkZlpaWrFq1SsqW29TUhL+/PzU1NWz= evJnVq1dz6tQpVqxYgUwmw9fXl3bt2rFr165Wz5iQkEBRURF79+6V8q288847LF++nMceewx/f3= ++/PJLJk+ejKenJ88995y0Mdzzzz9PdHQ0b7/9Nnv27EGhUPDGG29gMBha5QGysrJi6dKlzJo1S= 0o0FxISglqtZsGCBVy4cAEHBwecnZ2lrMkdOnTAz89PSt4FzSn/9+3bx44dO0hNTUWn0/3se2vb= ti1+fn4cOXKE1NRUqqqq/qlw06FDByZPnkx1dTUrVqzg448/Zs6cOfTr1w9/f3/8/f1xd3enTZs= 2bNq0iR9++IG8vDymTJmCQqFgzZo1PP/889IK7plnnmHVqlVs27aN/Px8tFotqamprF+/XtIctO= zxYjAYuHXrFgMGDJCSMx44cIAuXbpgbW3NzJkzpVxJLdmC9Xo9O3fu5JNPPsHOzo7c3FygeeIJD= w/H3d2d2NhYNm/ejKenJwqFgs6dO2NlZcULL7zA5MmTeeedd9i4cSNt2rThxRdfxNnZmcmTJ3Pn= zh2MRiMbNmwgJiaGmTNnYjQaWbNmDYcOHeLMmTP06NGDsLAwoqOjpazNr7zyChYWFpKwGRoaSk1= NDZ9//jmlpaVMnTqVQYMG0a5dO0aPHk3//v2ZMGECdXV1LFu2DK1Wy4cffthqC5IWoSEiIgIXFx= dycnIYMWIEaWlpjBgxggkTJrRa0UZFRTF48GDmz5/PmDFjKC0tJS8vj9deew0HBwe2b99OTk4Od= nZ29OnTh/Hjx/P+++8zcuRIfHx8mD9/Pvb29tja2jJkyBDmzZvHG2+8QWxsLOvWraNDhw4YjUbi= 4uK4ceMGaWlpzJ07lxUrVki5WVJTU3nmmWdwd3dn6NChDB06lKlTp9K7d2/GjRsn5XT66quvGDR= okKQ5+dOf/kR+fj7z5s2TklpC81YqwcHB3LhxQ0pEeeDAAQYPHsz06dMJDw9n9erVvPHGG7Rt25= YFCxYQHx8v7TUGzZlo/fz8uHXrFkqlEicnJ1577TVu3bpFREQEJpOJ/Px8GhsbeeGFF2jbti2en= p7odDpKSkr49ttvCQwMxGAwsHbtWrRaLV5eXnTt2pW1a9dy9epVsrKyWgk3arWaGTNmoFKpWLFi= Be+//z6dOnUCmvflS0hIwM3NDQcHBwYMGMDIkSNZv349kyZNkvrHaDSyefNmcnNzpY05e/fuTUZ= GBi+++CLJyclERkbSuXNnSSuh0+nIz89n/vz5DB48GJlMxpEjR5g9ezaVlZXk5eWRm5tLWVkZr7= 76KjKZjLy8PJycnNi2bRsLFy7E0tJS0qCoVCr8/Px48OABBoMBmUzGiy++KOXpqa+vR6PRMHXqV= EaNGsXt27eRyWS4uLiwbNky2rdvz7Fjx9BoNDz++OOMHz+enj178thjjxEQEAA0mys7dOgg7YfV= kiepJRWCyWSivr4epVKJXq/H39+fWbNmMXr0aDZt2oQoikyePJmdO3fSsWNHKa/NpUuXOHPmDD1= 79iQiIoLo6GhJuGlqaiIqKoqXXnqJMWPGEB4ezpEjRxg0aBBJSUkMGzaMsWPH4ubmxpYtW9BqtU= yYMAF3d3dmzpxJcXEx+/bt+4dz6i/h3/O5EaUtMpt35X64fWVWRS1bT4ZxMaaWvx6NRldVx4ZnB= 9PTxYRoNJFRBlsPR/BDUj6CTCbFSImCCUEUH+pymhsj7VHV8g+xec/vgppGAsOzQKaSzFmi6WHq= cxn/j73zDo+qTPv/58wkk5n03kM6IXRC74ggKogga0XhpyjosthW1rUgiii6r7CAiHVpiqKIiEq= XAKGkJ6SQ3id10jOTMplyfn+Eeda8uvuuu66+7pvvdXldkjkz55kzp9zPfd/P94OPm9OvDr9gNp= vp6upClmWcnJwYO3YsXV1d4qHq6uqKk5MTw4cPx87OTiyX9fPzw9fXV5SeWlpaRHOvv7//D9ai7= e3tReperVYLTo3ZbO7XhD1x4kQBg3zppZdEX4LVahWzJEBcCDZYo5+fnyh3fVe28hH01dmDg4Op= q6sTmIPw8HDa29uJiIggPDxcjNH2uYBAFHh6eorUv81R1fZ6QEAAXl5ef7Nm7+XlhZ+fH5IkERU= VhY+PTz/LcegjE0+YMEGU4f6WbAygBx988HvW6v+TZFkWxGno4xTJskxwcDD+/v4oFAqCgoIICw= sTAae7uzve3t5iZpWbm8uDDz7Iq6++iq+vLyaTie7ubmRZRqPRMHr0aKKjo3FxcUGWZRoaGujq6= kKSJDw8PHBxcSE8PBwXFxdxTtl+I+g7J9ra2vD19cXe3l484FtbW9mxYwfnzp2jtbVV3Mjs7OyI= jY1Fo9Hg5+eHh4cHvb29jBo1SpzDRqNRkNw1Go0wG/yujEYj69at4+TJk7S3t3P77bfz9ttvo9F= omD9/PiqVSjg/NzU1iXPeVob18PAQx02pVCLLMnq9nmeeeYbc3FzWrl3bb39WqxU/Pz927tzJyZ= MnKSgo4L777mP//v309PTw0EMP9TufDQaDAKva6PXNzc1YLBYkSSIwMBAPDw88PT2Ji4tDpVLh6= OhISEiIKPkFBQXh4eFBTEwMDg4OuLm50dnZicVi4auvviI1NZXs7Ox+42xra2PPnj2cP3+e2tpa= Jk+eTEhICKGhoWg0mu8hQ9rb25k+fTrx8fEUFhayfft2brnlFl5++WVef/118dCDvuvTVm4ICgo= iPDxcnC/QZ+DZ0tJCREQEoaGh+Pn5id/quwoODsZgMKDT6WhsbMTd3V2Mz97ent///vcsXLiQhx= 56iNzcXMLDw4XBXGFhoThWtvJTVFQUERERqFQqZFnud35CX3nPz88PhULxvbHYFBQUhLe3NzExM= Wg0GhwcHBg8eLDIgKlUKm655Raqqqr4zW9+g4ODA2PHjsXLy0vgTHp6esT9FuCRRx7h+eef56WX= XuoX4Gk0GmHSaTKZxH3dy8uLkSNHcvnyZcaMGcMXX3zR794FfzVujY+PJykpqV/waTPQtBmVTp8= +ncjISPz8/HBzc8Pe3p5BgwZ9r6RsY+PZvoPtPh4ZGUlgYCAff/wxixYt4s033+wXwJvNZnp6es= Rk7e/1tnV2dvLss89y8uRJWltbBRcOYMiQIVy4cIH8/Hz+9Kc/UV9fz6pVqzh58iSVlS5tlvQAA= CAASURBVJU8/PDDfPjhh+zbt4/ly5fj6OhIdHQ0ISEhBAYGCsftf0U/KnMjSxZAiUJWXMuuWClv= 7mT711lcKuoCO2dqDRY2f57BE78Zw59WXc+rHyWRqe1BZ9Tw7K7LPH9XHHNGDEJtJ9lilx/aU1/= aRlYCEp1mOJBwlaImKwp7FRK9yLICpdw3Bg9XBX4eDmJx+a9FtlrpwYMHmThxIo2NjURFRQnLbp= 1OR3R0NA0NDWJGV1NTI6zmS0pKcHBw4J577uHdd9/lyJEjAKxZs6bffkpKSjCZTJSVlaHX64WTq= W0W0tDQQEdHB+3t7WzduhUPDw9Wr17NuXPnBNSxs7OTqVOnCsv00tJS5s2bh8ViQZZl6uvr8fLy= wmq1UlxcLC70UaNGUVFRwZ49e/Dx8cHOzo577rlHlDRyc3N5/PHHqayspLKykoqKCgoLC0VvhV6= vJyEhgZycHCorK2lvb0etVlNWVobZbAb6bsAJCQmkpKSwYsUKcWFcvHgRnU5Hc3Mz7733Hjqdjt= zcXJycnKipqaGhoYGQkBARsGVkZPDoo49iMpmor6+npqaGESNGIEkSjY2NNDc3k5WVha+vL5MmT= aKzsxO1Wk1+fv7fNfNqb2+ntLSUjo4OMSs9fPgwPT09FBQUiBmy7Teoq6tDq9UKp9eWlhZyc3Op= qamho6ODnp4ebrrpJrRarbiRKhQKdu3axcSJE+no6CAoKAiDwSBKeQcPHsTT05POzk68vLzo7e3= FYDCQk5ODVqulsrJSQELd3NyEw/OCBQsoKCjggw8+4J577mHTpk2o1WqysrJYsmRJv+9dU1PD0a= NHKS4uZuHCheTm5orsxvjx41m4cCEvv/wyM2fOpKKigj/84Q8cOnSIqqoqMjIymDFjBps2bcLHx= weDwYCHhwfx8fHcdNNNLFiwgOzsbEpLS6mrq+P2229ny5YtfPzxx3h4eDBz5kxUKpXo99BqtXR3= d3P58mUGDRrElClTSE9Pp76+XljaV1RUEBAQwN69ezEajeI66OzsFKWktrY2kS0aMmQI+/fvx8v= Li46ODtzd3TEYDBw7doywsDC6urqIiYmhra2NrKwsent7qauro7y8nNLSUtra2gTb6fjx4+Kcmj= x5Mvfddx8bN27kzjvvJCEhgVWrVtHZ2Ul2djZ33HEHa9euZePGjWRkZDB37lxqa2sFt8vmcG27n= pYtW0Z3dzfbtm1j3LhxJCcni76bZcuW9QvYhg4dipubG1u2bGHcuHHU1tayaNEi/vSnPxEcHExl= ZSUbNmygoqICrVZLRUWF6FHR6XTioe/o6EhwcDC7d+/m3nvvxWw2o9Vq0el05OXlcezYMcLDw7n= vvvuoqqqit7eXyspKHB0dmT17Nq+99hpTpkyhqqqKNWvW8Nxzz6FUKsnJyUGv11NVVUVcXBz29v= ZotVpxzlZXV9Pd3U1dXR16vZ6LFy9SUVHBqVOnGD9+PE1NTRQWFmK1Wmlububq1asUFxdTU1PDm= TNnGDVqFFOmTGHXrl1kZ2fj4OBAa2srOTk5ok8oKipKfPedO3cye/Zs7rjjDoxGoyh35uTkUFhY= KBYc1NbWcvLkSYKCgmhpaSExMZHnnnuO5ORkmpubqaurIyIiQpSBFyxYwB133CEySzZpNBoCAwM= 5fPiw+A5Wq5XGxkaBb6murqayshKdTockSeTl5VFUVER5eTmyLDN+/HjeffddYmJiRCB45coV3n= 77bXJycmhoaBA9ShqNBm9vb/bs2SMm2p6enri7u5OTk8OpU6fIy8sTGJ7169fj7+9PV1cXgwYNY= saMGeL8Tk5OZurUqeTn5zNp0iTWrFnDJ598glqtxsXFhdTUVJYtW0ZJSQm1tbUkJSVRU1NDeXk5= BQUFdHR0UFNT8w8BkX9IP6qhWEJGkm02fBJWSeIvx7I4nNSASeGIrJCwKKCp00yRtoWRYW7MHBN= CbWMLtS0m9CY1RVU1BHk6EOrrgUJxrd/mew3A1/psJBmzbOV8YR1/OVGA3tTXmKUAkKxYkJBkEx= MiXVk4MQxH+75Y7dfSUKxSqRg8eDBFRUUUFhYSFBTE4sWLcXZ25uLFiyiVSm6++WZSU1PFiens7= CyAY21tbbi5uTF79mymTJlCQkICVquV5cuX92sYTE5OZsyYMTg6OhIeHs7QoUPR6/WEhYUREBAg= ZkBDhgxh8ODBeHl5kZeXJ8CEwcHBREREMHfuXPz8/Lhy5QqjR4/mvvvuo7S0lMGDBwu6dExMDGq= 1WpR7HB0dmTFjBomJidTW1nLDDTcwdepUjEYjaWlpDBs2jOuvv56srCxkWcbd3Z36+nrCw8NFqS= MvLw+TyYSbmxtDhw5FlmUKCgrw8PBgwoQJjB8/nlOnThEYGMidd96JRqMRjaKhoaFMmTKFG264g= fb2drq6ulCr1eJ7DRo0SJwvAQEB5OfnU1dXh5+fH+7u7mKmZ2sy1uv1zJs3j5qaGoqLi5k/fz7d= 3d0Ct/BDsjUD29vbY7VaWbJkCU1NTWRmZjJs2DDi4uJEWjo2Npb6+nrRaJ2fn09UVBRmsxmVSoW= TkxOTJk0SN95Jkyah0WhYsmSJQEsEBATg4OCAo6MjFouF2267DehrLDeZTCxdupTs7GyCg4MxmU= wCEBkTEyMyX+PGjaOkpITm5mZGjRrFww8/zMyZMwXvatCgQUyePFkcO51OJx7yNmO3xMRE3N3dB= QR10aJFnD9/nvLyclauXIm7uzuJiYnY29vT0dHBkiVL8PLyIj09HavVyl133SWaqkeOHMm0adPI= ysrCwcGBWbNmMWvWLBISEmhra+Pxxx9Hq9XS3NyMj48PRUVFjBo1iuDgYAICAsjKysLZ2RkvLy8= aGhoE5+vee++lvb2d7OxsVCoV8+fPR6/Xk5qaSkRERL+HTUBAAAqFgitXrtDU1MSDDz5IVFQUV6= 5coaioSGxryxi5u7sjSRIuLi5kZmYyePBggoODuXDhAqGhoVRXV3PTTTcxfPhwrrvuOoqLiyksL= GTu3LkMGjQIvV5Pc3Mz9957L2q1mszMTCIjI7G3t8dgMODm5iZYVSaTidGjR1NcXExAQAB33XUX= qamplJeX88ADD6BWq6mqqqKpqYmVK1f2K6POmzePpKQkysvLmTZtGlOmTMHT05NLly7h6+vL3Xf= fTWZmJrIs4+bmRl1dHVFRUQQGBorgBvqyo1VVVdxyyy0YjUYKCgoEQDIgIICSkhIsFovI3litVi= IjI1m2bBkJCQmUl5fz6KOPYrFYBO6gra2NwMBA3N3diY6OFs3xXV1deHh4oNVqGTVqlODT2fpI7= rnnHkJDQ7Gzs0OpVIrMnsViQafT4e7uzpQpU7BarVRXVxMQEEBnZyddXV1ER0fT1dWFl5cXZrNZ= 4AhcXV0ZNmwYOp2O7u5uFi1ahI+PDzU1NYL5FxISIowpbT1Gw4YNE9iGqqoqwsPD8fLyIjQ0VGR= +1Wo16enprFy5EldXV3FMFQoF4eHhtLW1iYbwwYMHiwzikCFDKC4uxmw2ExISQlBQEKWlpeIc8f= HxYerUqfj5+Qm0zcyZM4mJieHixYt0dnYSGBgosnJKpZKYmBgRlKalpTFkyBBuvfVW2traaG5uZ= vDgwTz55JPExcXh5+dHWloaZrNZMNUAAUgtKipi1qxZTJ48mXHjxpGUlERnZycLFy4kIiKCzMxM= sZjBdt+1tUYMHjwYb29vgoOD/+Fn6nf140z8rm1plfr6XSQrnM7V8vqhHCpaZBQKCYUkI8tKrLJ= MiKuRP9w+Fh93DVsOZpBc2kmot8wf74hjduwg+mKR71fGZLmvqViWrOTWd7LpkzQyy3r6lopLMs= gKZIWMCXBR9LJ2QTR3zojBXqFA8euIawY0oP8o5eTksGTJEkFGHtDf1i233MJzzz33L3FzBvSfJ= Vvp8fHHH/+lhyIkyzKvvvoqnp6ePPLII7/0cH60flzPjdQX3UhIKGRQyDKzhwfxxOLhBDj3lScU= VjskqxJJUlLdpuKNTzLo6jLz7NLxxAUaeeK2McwePgg7xd8GQcnIyJKFlh6ZHYeySCvpwSzZYVX= IfYGVZAWrEkm2EuXjxOTYQFTKa306AxrQgH5Wtba2snLlSkpLS3nmmWd+6eH8r9Z7773HhQsXuP= nmm3+Uh82A/jPV3d3NmjVrGDJkiMiw/m/RhQsXeOGFF9i6dSv5+fm/9HB+tH5U5kbGiiQrQJKRh= cOwlV4ZjqZVsOVIDnV6JZLCro8jJZuQrCYG+znw5JJRDA/1xF2tQoWMVQRKiu+VkcxWmZJGPVsP= ZXD2ajtWpQZJIV8LehTIshWFFRwlA0/eNoK7pg9GJVmRpB/X3DmgAQ1oQAMa0ID+8/SjMjcSCmF= HLEtgVQCSFZUEN48N5fe/GUOol4RkNSJhxiopsSjtKWjoYcuhbHIrW68thVIAsi0RJKDiyDI9Zi= uJhfVsOpDCmbwWzHZq4XcjXfPDQVYgWXqYO8qfG8cNwk4hIzEQ2AxoQAMa0IAGNKB/2qG4L9BQc= K15V5awU0iE+bvh7+lIcVkjbV19y7UVEkiSHS16K1cKK3BxVRHq64aDXd+KK6sEMhIKSaK118qB= C4W8fbyIq7UmFJIdSNcWikt9SAdZlpEsZsaGqXnmnkkEujmIwGcACf7TaN26dXR3d/fzgBnQ31d= iYiLffvvt320s/u965plnsLOzIyws7Eft6+LFi5w9e5ahQ4f+6KXo/4gqKyt55513mDBhwo/+fI= PBwDvvvCOWr//cys7O5ptvviE2NvZHe1+ZTCbef/990tLSiIuL4+rVq9x222189dVXVFdXCyfvn= 1t33nknM2bM+JfcWhsbG9m3bx8BAQH9GlZ/Sf3lL3+hrKyMqKgoPv74Y7q7u/s1j7799ttUV1cT= Gxv7C47y/642b95MTU0NISEhPPLII9x6662/9JB+lH4CtpSEpOgLcBwwc+MIXx5dPBJ/Jysylj7= TPuyRFHZo9Uo2fpLBKwdSSatox2hVYLJK1Hf08HlyBau2nuK/vsilpBWsOCBLqmtuxiYsmMEqoz= CbiPKS+f1d4wj1dABZgUKWrgVJA/pX9fXXX7N161Z0Ot0vPZRfjWpqatiwYQPJyckAFBQUcOzYs= b/7niNHjrB79+5/itk0bdo0li9f/i/xlf67ZFnmySefBPpMB//4xz/+w58vyzKbN28GwNnZmUcf= fVRYAfzcGjlyJCtWrPie78ffkizL7Ny5E6PRSHNzM7GxsTz88MMoFApef/11du7cSW9vLxMnTmT= u3Ln/5tF/X+vWrePLL7/8m14u/6h8fHx45JFH/umVJz+1rly5wvbt26msrESlUnHffff1a7BOTU= 1lx44dwkByQD+vzp49yx//+Efq6upwdXVl165dP+r9H3zwAZWVlf+m0f1j+knYUjZjP4UkAQpC/= FzxcFeRV9qA3gggIUsKrEqZHquaq9V6zqZXcTqzmiPJWj6OL+Xr5Gq0HRKynRqlBJJCxtr3VmQU= fQ3MVgtRPnY8ettIJkf6oZT6CON9hn/Wa6iGX5dsy04LCgqwt7fH0dGR5ORk8vLyhJFaRUUFLS0= tZGdno9PphD/Ot99+S2lpKU5OTri4uFBXV8fly5cpLS0lKiqK3t5esrKyhCmYq6srWVlZwgDtu4= Z3ZrOZvLw8LBYLjY2NxMTEMGLECDIyMsjJycFkMvVjKJlMJq5evcqVK1dQKBQYDAaSkpIwGo1ot= VqKiopwcnIS/KLLly8L1g/AqVOnKC0tRa1W4+rqKnxnbMypoKAgZFkmMTGRwsJCJEnC2dmZy5cv= C98LLy8v7OzsMJvNZGRkYDAYMBgMaLVaqqqqcHBwIDk5maamJry9vYWVvY2LZZNWq6WgoECwZKq= qqkhJSaGnpwdvb29qamooLCzEYDCgVCpJTEwU1vpXrlwhKioKf39/9Ho9gwYN4uWXX6a3t5cRI0= ZQXl5ORkYGTU1NYrxXr15FoVBQWFjI2LFjiY6OJjc3l6ysLLFUtKOjg6SkJFQqFe3t7f1m23V1d= cIoLTk5WbiB2tnZ0d3dzaVLlzCZTHh6enLmzBmsVitWq5WkpCS0Wi2enp6YzWYuXLgA9DUEf/HF= Fxw5coTY2FgcHR3FdgaDgUuXLlFUVERpaSkWiwWTyURqaipFRUU4ODiQkZHBtm3bCA0Nxd3dner= qanHsy8rK0Gg0NDY2kpaWhre3N6WlpWRmZlJZWUlwcDC9vb0kJSUJPyXbd9VqteLvHh4enD59Gr= PZLDJCVquVkpIS0tLShKlgU1MT9fX1uLm50dXVxdmzZ6muriYoKEgwcmpra8nOzkaj0Qi7fldXV= 6KiooS/zrlz5zhw4ABRUVH88Y9/pLOzUxjNpaamkpubK/bZ3NzMhQsXBB/Ozc2NsrIyioqKsFqt= ODg49GO9ZWRkkJ2djcFgwN/fn/T0dFQqFSkpKYJ1ZvM/mT17Nnv37mX58uUolUrS09PJy8ujp6e= n3zLszs5OCgoKqKmpITs7Gzc3N8HT8vPzw2g0UlZWhrOzM83NzWRkZCDLskBA1NfXC68pLy8v4u= PjMZlMYun8pUuXqKqqwtPTs5/5ZVZWlmDf2TyYUlJSkGUZT09P9Ho9586do7a2FhcXFzQaDSUlJ= eh0OvR6Pf7+/owbN46ysjIkSUKj0VBcXExzczNtbW0EBQUxevRoMjIyyM3Npbu7WxgJ2lRRUUFy= crJYflxZWUlNTQ0ODg4kJibS3t4ulqKnpaXR0NCAv7+/yEra2FZ6vR6dToePjw+lpaWkpqZSV1f= XD8EiyzJXr14Vx9nOzg6NRkNpaangP/n7+5OZmUlubq74jauqqgT/qrKyEkmSyMjIoKGhAUdHR1= JSUlCr1YKX5uLigqOjIwkJCRQUFODk5ERbWxtJSUl0dXWh0Wi4dOkSFouF1tZWUlNTKS0tJTg4u= N+5VlBQIPhnBoOB3t5eEhMT8fDwwNHRkdbWVhISEqiuriYsLEw8B9ra2nBycsLb25uRI0eSnZ1N= YGAgra2tJCYmUlRUhIuLC/b29pSWltLV1UVycrKYJKxatYro6Gj8/Pyoq6sTDKnvZqnNZrPwMWp= ubqa2tlYwAW1+QH/PP+x/0k8S3AgzYQlAgZ0EEQEuBHs5U1jZRGu3uc8tUJKQFEokpYJui0x9Ry= /17SY6jGBVqpCUdtfAmXJfwCQpUWBFYQGL1UKEt8SaW0cyc1gwauU13x3owzdIf3v11f9WdXd38= +mnn5KZmUl+fj5nzpzBy8uLt99+G5PJJG66L730EkeOHEGWZT799FMGDRokjNXKysrQarWMGTOG= bdu2UVFRwfvvv8/w4cMpLCzk6NGjtLe3s3//fnx8fIQx365du/r5EmRkZLBv3z5aWlqIj49n6tS= ptLe3c+jQIfR6PUeOHGHEiBEiKEhKSuLTTz9Fr9ezdetWQkNDef311wU1vK6ujpaWFtasWUNbWx= uVlZUcP36cuLg4Dh8+TFZWFmVlZRw5coQpU6awYsUKvvrqKxQKBVu2bOG6664jISGBM2fO0Nzcz= NmzZyksLOS3v/0t/v7+WCwW4XtRVVXF7t27yc7OprCwELPZzK5duxgxYgQfffQRBw4cIC4ujpMn= T1JUVMThw4dFilWr1fLggw9y6dIl4XS8efNmenp6+PTTTxk5ciT79++nqqqKAwcOMHXqVF577TU= UCgVms5lbbrmFO++8k46ODmprawkICODrr78WsMlly5bh6urKoUOHGDFiBLW1tezZs0fcVK677j= okSeLgwYO0tLRw8OBBNBoN5eXlpKenk5GRQWlpqZjVGgwG1qxZQ2NjI9XV1axYsYK2tjbS09MpL= y8nIiKCbdu2ARAXF8dbb72Fk5MT8fHxVFVVCThjVVUV+fn5pKSkCO5VRkYGISEhJCYm8sUXX7Bg= wQK++uorvvnmG6qqqnjppZeYOXMmZ8+eFUGvDbp56tQp/P390el0vPHGG0ycOJGUlBQ++OADJk2= aREdHB59//jm+vr4cO3aMxsZGTpw4QUtLCx0dHSQnJwsm0cyZM4E+88k///nPKBQKxowZw9NPP0= 1sbKyw2S8tLWX79u10dXWxceNGZs+ezc6dO8nIyGDatGlilceFCxcE8+zll1+mp6eHo0ePCm+St= LQ0nJ2daWho4MMPP2T8+PGcO3eOxMRE4aT88MMPM378eOrr68V5v3//fsaMGcPhw4cFnDM5OZnR= o0ezceNGWltbOX/+PMOHD8fNrQ/qm5yczKeffkpLSwunT5+mqamJp556iry8PKqqqkhNTWXSpEk= CSgmwfft2li9fLvhaPT09bN26lTvvvFNk155//nk2bdqEQqFg//79ZGZmUltby+7du1m8eDH79u= 3j448/ZurUqezcuZOGhgYRwLz44oscO3aMnp4edu7cSWVlJYWFhVy+fJlJkybxzDPPoNVqOXv2L= G5ubiIrl56ezgMPPEBGRoY4LnV1deTn53PixAlmzpzJ66+/TltbGxkZGSLgePPNN+ns7CQlJYXo= 6GisVivr168X/jLbt28Xk6WhQ4fi6urKyy+/THd3N9u3b2fFihXi2Gi1WjZt2oTRaOTixYuUlJR= gMBg4cOAAw4cP5/333+fYsWOMHz+ejz76CJ1Ox+nTp3FychIojurqavbv309xcTGfffYZkyZN4r= 333qO+vp4DBw70cwv/4osveOyxx2htbRX3URcXF9auXUtnZyednZ3IssyZM2doamriww8/RKPR8= NZbb3HgwAEsFgsHDx4kKysLvV7P+vXruf7669m0aRMeHh5i+XVYWBjp6emcOHGC0tJSrl69ipeX= F++++y5Go5HY2Fj27NmDq6srX3/9NUVFRRw4cIDo6GgRQFy6dIlVq1ZRXFxMZWUlW7dupbu7m6+= //hqr1cqYMWN44403KCoqIj4+HqVSKc5rvV4vUEAVFRU8++yzrFq1isOHD3PkyBHy8vLIzc3FbD= bz2GOPUV9fj06n4/PPPyckJITDhw8zaNAg1Go1R48epa6uTmBmbONrb2/nzTffpKysjPj4eBwcH= Ni9ezfDhw/nww8/5LPPPmPZsmX/9PP1JwFn9km+Rofqg0FpFBLzRgdjp1Sy+VAWZa3mPuClbEYB= mBV2SAoz0FcXl2QzCllClpXIkgIJGaXc50ArW42MGaRh7R3jGDPIAztFH5JBskrIir4gx3oN4vB= rCm9sTpX333+/yNB4e3vz+uuvs3r1anQ6HUqlksjISFQqFU8//TR79+4lOTmZpUuXsmrVKl599V= V6e3spKyujpaWFLVu28MADD6BUKtm2bRtHjhzBx8dHcHOysrKYM2cOL730Ur+xfPnll0ybNo1bb= rmFc+fO0dPTw8mTJzl8+DC+vr40NTWRm5sreg6+/vprPvvsMwIDA0lJSeH5559n8+bNPPPMM8yd= O5c1a9ag1+vZvn07N910E1OnTuW5557jwoULvPnmm6SmpmK1Wlm3bh0pKSnExcXR3d3NE088weX= Ll8nMzOTEiROkpaXh4uKCyWTioYcewtnZmQcffLAfgdbOzk6A8ubMmYNKpeLixYt4eHhw4403Ul= BQgMViISUlhaVLl7Jw4ULxXg8PD0aPHo2XlxdPPfUUu3fv5sCBA8TExFBUVMTChQtpbGzEzs6OJ= 554gtDQUKZPnw7A/Pnzv7fSb+LEiUybNo1x48YRFRXFW2+9RVpaGpcuXaKzs5O3336b22+/nRtu= uIFz586JcU2ZMoWbbrqJoqIiXnvtNSZNmsSpU6d47bXX+s0cHRwcGDlyJLIsExcXh4eHB4sXL6a= 7u5t9+/YRGxvLbbfdhkajwc7Ojptvvhk3Nzc2btwI9M3whw8fzqxZszh69Cjr168nNjaWsrIy0t= LSePjhhzl+/LgoB9TX1zN16lTGjh3L+++/z7x58xgxYgRpaWmsW7eOkSNHsnr1aiIjI3n66afJy= 8vj3LlzAMJl10bw3rhxI9988w0xMTHccccdaLVaXnnlFTQaDWfOnGHt2rX9yllxcXGsXLlScK/m= zp3bD/hoMxhbvXq14NIMHjwYrVZLfX09r732GhEREXR0dNDc3MyaNWtIS0vjgQce4NixY5SWlrJ= 06VKqq6t56qmnyMzMFMH7U089xbfffsv999+PWq3Gz8+P3t5ekpOTWbhwIddddx0lJSXCNdrWp/= b8889TUVFBeXk5VquVp59+ul+m4ciRIxw6dAgfHx+am5sZOnQo3t7ezJ49mzFjxrBjx46/aTs/d= uxYPDw8WL9+PZWVlXR1deHk5AQgDA5XrlyJ0Wikq6uLVatWkZKSgsViYdiwYeTk5AB9uJb8/Hye= ffZZAgICuHjxIpIk8cADD3DmzBkmT55MbGws77//Pp2dnTz66KOUl5fz+OOPM2vWLDGe0NBQfH1= 9mTVrFtOnT+eVV15hzpw5DB8+nNtvv53CwkIOHjwoKNkjRowgKyuLCRMm8P/+3/+jubkZhUJBSE= iIYCl98MEHjBs3jnvvvZfa2lokSSIkJIQnnniC3bt3k5aW1u+YfPLJJ0RERPCHP/yBF198EbPZz= KxZs8jKysLLy4v58+eLe+b+/fvx8PCgoaGBwMBA5s2bB/RlEK5cucLixYtZvHgxaWlp7N69m6Cg= IKqrqzlx4gRTp04FYPTo0YSGhnLXXXcxevRo5s2bR0dHB1FRUSxfvpyYmBg2b97MbbfdxvDhw/n= mm284fvw44eHhBAYGsmrVKpGxsvHpnJ2dGT58OAqFguHDhwskii0D7ODggNFo5Le//S2PPPKIyA= 7Nnj2bG264gZEjR7Jnzx7KysqoqKgQxyYyMpKoqCjmzJlDbGwsb731FocOHSIyMpLa2lpqamrYs= mULYWFhtLa2Chf6SZMmcfvtt5OamopSqSQ6OlpkU6+77jrUajVvvPEGTU1N3HXXXURFRbFgwQJG= jx7NokWLGD9+PD4+Pjz44INkZmbywQcfEBAQQGNjI8eOHRPnkNlsJjMzibOFrwAAIABJREFUk7v= vvpt77rkHjUbD5cuX8fT05KabbhLA3n9WP0HPTZ+sfyVD9a2GkuxQSjB7RCCPLRlOsLsVq9UMso= RkdUBhtbv2nxJJBitgRoFFkjBLElZJgWw1obR2MXuEB6+vmMakcC9UCgklfauj+kz9+vYnyb+uw= Ab6qMR6vR6TySTYJNnZ2cyYMYM//elPTJkyBVdXV/z8/ITrrKurKyaTia+++orNmzezYsUKPDw8= 6O7uprm5GaVSKUBvXl5e7Nixg6SkJKqrq1m1ahX79++nurqaJUuW9Our0ev1ODo6Csy80WjEwcG= BnTt3kpycTElJCQsWLBDbOzs7s2XLFhITEzGbzcyYMQO1Ws2UKVN48cUXaWhowNfXF2dnZwYNGo= RKpUKtVtPV1UVBQQEKhUJA9kwmk7j4bb0SRqMRV1dXPv/8c1JTU8nIyOD222/HwcGhX2ADfSDLI= 0eO8O233/L000/3e81WkhkxYgSHDh3i2LFjLFmyRPC0nJ2dCQ8Px9nZGYVCIQKsxMREcfG+8cYb= TJs2jUWLFgmGk+2zAcGJ+u9SKpVMnz4do9EoPCxaWlpwdHREpVKJm1Zzc7Pggfn6+iLLMkuWLOH= s2bM89NBDbNq0SezTxpIBiIiIwMnJiZCQEBQKBb29vUiSxNChQ6mvrycvLw8fHx/MZjM33ngj58= 6dIy8vjwMHDvDQQw9x/vx5Xn31Vf7rv/5LjNnOzg5/f39RerDRfCdMmCCyHVu3buXbb7/lnXfe+= d539vLyEr+PQqFg6NChpKWl0d7ejrOzM21tbbS1tYmyhUqlYvbs2Zw6dYpt27bxhz/8QXxXSZIY= NmwYDQ0N7Nu3r9/5B31kchvDZ9SoUbi4uBAQECBAr0FBQaSlpVFWVsbhw4eJiIjA19cXT09PJEn= 63u8WEBDwg027Nrdqq9VKU1OTcIeNjIxEoVDQ1NSELMuo1WrUajVWq1XABxcuXNiv98BoNPLnP/= +ZlJQUiouLefTRR3F2diYmJgZ7e/vvsd6+q/Pnz7N27Vr27dv3vdeGDBmCl5cX7u7u4jxydXUV5= a3v8q02b97Mhg0bWLp0KQUFBQQHBwtnWICYmBgUCgV2dnbIsszatWs5cuQITzzxRD/nc29vb9zc= 3ETzti0ItG3T29vL+PHjuXTpEvn5+XzyyScolUpcXV2xs7NDrVaL0peXlxfQZ2bn6uoqPs9kMtH= Q0MAjjzzCkiVLvtek3traKh68KpXqe5MN2/Xf3d3N6tWrSUxMpKKigg0bNohtwsPDOXToEJcvX2= bBggUYjUYefPBBUlJSqK+vZ/369WLb0NBQ8b01Gg3Ozs7ivNNoNMiyTEtLi2BzBQUFoVQqRcbCy= ckJhUIhuG3f7Wv77n3FbDYLtEd2djZXr17Fx8eH6OhodDodJ0+e5Prrr6etrY1HH30UPz8/Qda2= yd/fXzw7bM31Nldk2/1i2LBhpKWlUVFRwcGDB+np6RHXvg2n4+/vL77b/v37OXLkCI899pg4BwI= CAkRwKsuyuD6gL4CxZcbLy8t59dVX+50/J06cID09neXLl/c7BhaLRRyHf1Y/Weam75RSin/0lY= v6MjDXjwjBTe3Ae8eukFVtorPXjEK2RSPWa/411wjh1j5elEphIsxLYv6kGBZNjSLARYVVlgViU= 0a6VsKSvrP/X5dswL9PPvmEMWPGoNfrKS8v5+677yYvL4+amhoqKiowmUwkJSUxePBgEhISWLZs= Gbt27WLu3LnU1dVRWVmJg4MDSqWSnTt3Eh4eTmtrK5GRkXz66ad0dXXR0dGBwWDAaDQKhkx7e7u= o20dHR7Nnzx4sFguZmZnCItvG3bFYLHh5eYmoe9SoUSLN2tzcjL+/PxcuXOCBBx7Azs6OG2+8kX= 379okbfUBAALIsM3/+fDIyMnj++eeZNm0atbW1PPXUU/z+97+nt7eXK1euoNPpaGlpISwsjNdee= 427774bvV4vbhqXLl0SMynoa07cu3cvN998M19++SVKpZLu7m6OHz9Obm4u5eXlbNiwAVdXV5Ys= WYLFYqG+vp6AgABha+7s7ExHRwdz5sxh9erVBAUFCevzDz/8kPnz53PLLbdQUlKCk5MTFy9eFFC= /t956i3HjxlFUVERtbS2yLJOamookSYwaNYrIyEgSEhLIyMjghhtuYNu2bbS3t1NcXMw777zD6t= WrOX36NJIk0dPTw7x589i7dy+enp6sX7+e5ORkuru7cXR0pLe3l7y8PKqrq0lOTqa9vZ3MzEzq6= upoaGigqKiIyMhI/vKXv9DW1sbatWupq6sTpbugoCDBKbPNNmtqakSQ9e2331JfXy94SImJiaxc= uZLw8HD0er3ASAwePJisrCwaGxtpaGigt7eXo0eP4uTkRFlZGYWFhQwdOpTQ0FDee+89fvOb36B= QKIiLi+Ptt9/Gzc0NBwcHYmJiOHXqFCaTiRUrVpCSkkJra6vIoISEhODk5MSZM2d46KGH+l0/Y8= eO5eWXX+bjjz/GZDIRFRUleh80Gg2TJk3iueeeY8aMGeTk5BAZGUlVVRV5eXkUFBRQX18v+E7Hj= x/HycmJkpISqqqqKCgooLGxkfT0dNGLUVZWxrhx4/joo48wGo0YjUacnJzQ6XTs2rULT09PwsLC= CAsLY9q0aWzYsIEZM2b0C6LmzJnD9u3bsbe3p6WlBZVKRWtrK8nJyYSHh6PVasnPzxeNv4WFhXR= 3dwvMxKxZs0hJSUGSJAoKCkQfXHJyMrW1tYLBZusNamxs5OLFi9jZ2VFeXk51dTXLli3jySef5D= e/+Y3oN7O3tyczM5OWlhbOnz9PYGAgJSUlZGdnk5WVxWOPPcbx48dRqVR0dXXh6OhIdXU1TU1NJ= CYmMmLECKqqqigsLBRMMXt7e5RKJS+88AJxcXEYjUbGjBnDK6+8gkqlIiMjg4qKCiZOnEhxcTFR= UVFMmzaNTZs2oVQquXLlCseOHcPDw4OJEyfS1dUl+rNsZdpp06bx7LPPEhISIvqLbDiP48ePk5K= SQlFREb29vcTHxxMaGkpPTw8uLi4iWL569Sp79+5l0aJFXL16ldDQUA4fPswHH3xAUFAQra2t3H= vvveI3bG5uFg/lnp4ewsPD+eSTTygsLBSA0S+++ILGxkaqqqqYP38+8fHxGAwGSkpKBBPw/Pnzt= Le3U1BQgKurKxcuXMBkMnH58mVUKhUrVqzgiSeeEKWlFStW4OnpKXAeM2fOpLOzE3d3d1xcXNDp= dBQVFdHe3o6bmxvl5eVUVFRQVFSEVqvFarWSkJAg+n6WLVtGZGQkGzZsYMKECVy5cgU/Pz8+//x= zzGYziYmJos+qsbFRXJujRo0S3LCLFy9SVlZGQUEBVquVlpYWqqqqUKlUnDt3Dl9fXwoKCjhw4A= Curq709vaKIEyn0/H0009z++23k5OTI3oGjx8/LjhyFy9e7Jct/DH6SXpu4DvBxQ9EGUpkQrycm= RDrj7erEpOxm57OLkxmC2arBYvVgixbUGHEQ2VhaIAjt0wI4oF5Q7lhVAgeGjskWRIBkSQprgU2= PzSAX49sbKn6+npqa2sJDQ1lzpw54oERHR2Nr68vWq0WBwcHzGYz06dPZ/LkyURGRlJWVoaTk5N= gJE2ePJmSkhKamppYtGgRI0eORKlUUlFRgUql4tZbbxWNhWPGjBHlFYDY2FhMJhNarZYlS5awdO= lS5syZI26KSqWSG2+8UTSrhYaG4uzsLMYwfvx4WltbGTt2LDqdjmHDhuHt7U18fDwTJkygpaWFO= XPmMGzYMObPn092djZNTU0sW7YMd3d3CgoK+s1y/P39ufXWW7FarWi1Wry8vPD19SUqKgqLxcKI= ESPE2JVKJZ2dneh0Ou677z4GDRqEi4sL1dXVjBw5khtuuIElS5bQ3t5ORUUFc+bMYfTo0UDfzK+= 6uprQ0FDCw8MJDQ0lNjaWoqIiFAoFt956Kw4ODmi1WgYPHsz1119PYGAg9fX1ODk5MXnyZB5++G= E6OjrQaDSEhoYSEBCATqdj4sSJqFQqkba2t7fn4YcfRq/X09HRwfTp03nssceYPHmyaMxzdHRk6= dKleHp6UlhYSHt7O4sXLxYPO9vvZ3v4Dx48GI1Gg6OjI6GhoXh6ehIRESFm8ZGRkbi4uDBy5EiK= ioro6OggLi6O4cOHU1tbi16vZ+7cucTExCDLsrgxurq64uvrS2NjIzqdjvb2dpqamjAYDIwdO5b= KykqcnZ2JiooiNDSUoKAgKioq8PDwQK1W4+XlxZAhQ3BychKZFWdnZ5EhKCkpoauri9/97nei36= W+vp65c+cK8rdNHR0dxMbGinS9TV5eXqL5s7u7m4ULF1JTU4NGoyEqKopFixZRXFxMU1OTeJDbw= KCSJBEdHU1kZCRubm5otVpBXg8JCSEnJ4fhw4eLbIAt4zNv3jwkSRLX1Ny5c5k2bRoZGRn09PRw= 3XXXERoaipeXF6WlpYwdO5Zx48aJGXp0dDROTk4UFxfj4uIiZtfw10yIh4eHsGEoKCggLCwMSZK= YM2eOAN3OnTsXR0dH0TeSnJxMWFgYzs7OODk5iYb80NBQLBYLTk5OODk5ERoayuTJk8nJySEkJI= SRI0fS2dkpsn9hYWH09vaKhtPBgwczc+ZMwSxzdXVl5MiRqNVqtFqtmNH7+PgIdldZWZkI6u+44= w6Ki4tpa2tj/PjxLFiwADs7O5qbm0VJ00YHDwwM5NZbbxWB3+jRo/nd737HpEmTBCR2ypQpAAwb= Nkyc/x4eHqJHLSgoiBtuuEEEX3Fxcdx4443cd999hIaGkpubC/QFRbY+KLVajcFgoKKigrvvvps= ZM2YIRpPt3LH1QFmtVo4cOYK3tze9vb288MIL6PV6QQAfMmQIMTExGAwGysvLGTVqFCNGjKC9vR= 0HBwd8fHyQZZmAgABaW1sZNmwYHh4eTJ8+XYCCb775ZhYtWsTChQsxGAzU1NQwatQooqKicHBwE= NeXjb1nb29PZWUlQ4YMwd3dnaioKJycnERp1NfXF6PRKJh+Li4uIls4Z84ccY3ce++9jB49GovF= QnV1NYsWLeLWW29FrVbj4+ODvb09EydOpKKiAhcXF6KjozGbzQQEBODp6UlDQwOxsbEEBwczcuR= IGhsbGTVqFGPGjKG4uJjOzk7mzZsnMoRKpZKuri6qqqpYvnw5UVFRODs7i/v2vHnz+pHGf6x+HF= vqn1AfPbyv7iRLEr2yFV17D8W6DvKrOyirrKOzx4yzRs3gQb5EBzoT7uOCr5sGlZ0CBfR55SAhy= 33cb+n/GEBq06ZNODo6ilTgr0mzZs1i165dRERE/NJDGdA/oZtvvpmPPvoIT09PampqOHfuHEuX= Lv1Zx/DZZ58xderUf5oOPKD/G3rllVcAeO655/5t+zCbzaxcuZK1a9cO+O/8L9dP2FD8w5KwXnM= zViIBDpKSQZ6OhHg6cf2QAKC/H4ZMX/9NX3OyDHLfMnIZUEjy/zkzm4SEBPbu3Ut7ezsTJkxg8u= TJv/SQ/mG9++67FBQUMHbsWFpbW3/p4Qzon9B1110nVieFh4dz5cqVn23f6enpzJ49m3Xr1rF48= eKfbb8D+vXp8uXLHDx4kPLyciZOnMicOXP+LftZu3Ythw4dws3NjZdffvlfMlYc0L9X//bMTV9P= zTUH4Wu76lsy3sel4toqp79u3ScFgGylL5r5aw1KfNaABjSgAQ1oQAMa0A/oZyhL/bUdRr6Wl5F= kCeRrC7WuLbAS29lG892/XQt5rNcWd/1kS7wGNKABDWhAAxrQf5z+7XFCH+jy2v9fI1LJkgKrQk= ZW9GVxruVzrq2akq+9yfqd/IyiD7OAjOI/rC6VkZHRbynu/xYVFxcL7w6A/Px87r//frRa7c+y/= 6KiInbs2EFLS0u/v2/YsIH4+PifZQw2rVq1ipqamn5/++yzzzh48ODfXLb771Rrayvr16+nrq7u= 3/L5ycnJvPPOO//jMsw9e/awZcuWv7uNDU3xXf+N7+pcQRtvnNDSbbL+4Ov/qjIqDeTX9i3LTSz= t4HJJx/e2OXW1lf/3QeG/vJ/VH/7PvhybT1bz/vk6ekxW1n9ZwcWi9h/cztBjYf3hCpJKvz/e/6= 6l7+ZzNr/tR495QAP6j5b8C8n6S+34V6YTJ07Iqampv/Qw5KNHj8otLS0/y76MRqO8atUqefHix= bJOp/tZ9vmP6OTJk3JCQsIvOgaz2Szv3LlTDgoKkisqKn6xceTl5cnOzs7yU0899Te3sVqt8ptv= vikPGzZMLigo+N7r+m6zHPFUkvzkJyVyp9Es/l5Q1yU//VmpLMuyHJ/fKh/Pbv6nxmi1yvLZ/FY= 5s1Ivy7Isb/zqlztesizLiSXtcsTaJHnjV5U/6n1dRov80J7CH3zt9aNVssvDF+TD6Y0/xRAHNK= D/GP1kS8F/rAa6ZvpUW1tLdXU13t7e5Ofn09DQQFpaGk1NTdjZ2bFu3Tqam5sJCwvDZDJx5swZc= nNzhVFbVlYWV65coaWlheTkZLHs8+jRoyiVSgwGA+fPn6e0tJTAwECam5spLS0VHh7u7u44OTmR= nZ3NhQsX6OzsFDb6paWl+Pv709zcTHJyMvX19Xh4eODi4iLGavNY+a6LLkBeXh7nz5+nra2NkJA= QdDodx48fJy8vDz8/P8xmM8XFxYKHJUkSpaWlJCUlMWLECEJCQmhsbMRisZCfn49arcbDw4OLFy= /i7OyMvb09aWlpJCYmUlZWJvwrTp8+LRhFNkMzq9VKYWEh1dXVpKSkUF5eTkhICBaLhWPHjpGTk= 0NnZyd+fn60tbUJW3rbsksb02jdunVYLBYCAwNpbGwUy8/Pnj0rnESPHj2Kvb09BoOBhIQEcnNz= cXV1xdXVlaSkJK5evYqjoyN2dnbCWKu3t5e0tDSSkpIwm814eXmRnp6OUqnkxIkTtLa2EhAQIMy= 3wsLCqKioYObMmWg0Gs6ePUtmZqZY9vldffnllxgMBsEty8nJ4cKFC9TW1gozwLy8PBISEqisrC= Q6Opqamhrq6+vx9PSktbWVo0ePUl5eTlRUFFarldzcXAoKCoiKisJkMjFt2jTOnz8vGFqhoaF0d= 3dz5MgRoG+FybRp075nwKayUxDuo6GooRtZhqL6vizh+wl1ZGk7Udsr+DhJR1WzkRBPNeVNPVS1= GMmo1NNkMDHIS01lcw/JZR20d5lxsFNQ1thDeVMP/m4qWjrNZFQamBLlRmOHiYqmHiZEuJJRoSe= pVI+2xYi/m4rq1l4K6rsI8XSgqtlIQlE7V2u6CPRQ0WwwUdzQTWWzkSytAY1KiZvGjsTSDlLL+8= bh46KiptVIUX03QR4OpF/7/MrmHlw1SpwclFwu6aC1y0xrpxkfFxVTol1JKzegslPg5KDki/Qm8= uu6yK/roslgIsDNgfQKAzq9iWc+L6O2rZfYQEfauy1cKm6nqKEbjb2Sm0d5cjijiemD3RgS8Fdk= g6HHwsncVq7WdGGVZbyc7cmp7vv8K1UG1PYK8mo6SaswkF/XRVVLD97O9qjtB4r+A/rP0C8W3Ay= oz61206ZNZGVl4erqyqpVqygqKsJoNLJx40buuusuDh06hJOTE7GxsRw+fJiGhgYuXrxIXV0dn3= 32GYcPH8bb2xuNRsOXX34pmCkHDx7E2dmZ+Ph49Ho9aWlpXLlyhdOnT/PnP/8ZjUbD6dOncXd3x= 2g08t5772Eymfjoo49YsGAB999/PxUVFdx00008++yzuLu7C06Ph4cHq1atIicnB7PZzAsvvMDj= jz8uvldpaSlbt25FoVDw7rvvMn/+fL788kuSkpLIy8tDp9ORk5PDiy++SG9vL8XFxezZswc7Ozt= 27NjB5MmTkSSJTz/9FIVCgVar5eTJkwCsXr2amTNn0tzcLIKO+Ph44Q1UUVFBWloaBQUFTJs2De= gzi7r77rvJzs7G3d2dDz/8ED8/P+FA2tLSwjfffMOgQYM4cOAAXV1dHDt2jICAAD788EO2bNnCr= FmzOHXqFO7u7ri5ubF+/Xrc3d3x8PBg7969aDQaIiMjOXDgAAEBAaSnp9PQ0EBXVxcff/wxwcHB= nD59mtbWVo4cOcLYsWNxdXVFlmUSEhJEMPr222+jUql49NFHycvLQ61W8/XXXwu3auhz5v3222+= ZOXMmpaWlvPXWW4I7duedd4rf4cKFC8THx5Oenk5vby9OTk7s378fSZI4efIkBoMBLy8vtm3bhl= KpZNOmTYwZM4a33nqLsrIypk+fzmuvvUZrayuXLl0SRoLvvvsuSqWSU6dOCVfpgwcP4ujoyGeff= cb06dPZsWOHMMi7evUqN9988/eCG4DC+m4+SmwgyN2Bd8/X4eygpLa9l9rWXsK81RTUdQES1a1G= Xv2mivzaLkwWmW3f1jAi2JnTV1tJLdfz/vk6Jke5YTRZ6ei2EOatprC+i/YuM2PDXNh8spo7J/h= S1tjDBxfqUdspeO98HTLwl4R6zhW2c/1QD946U0NLp4mTua3kaDs5W9DGtm9r6DRauFTcgcUqo+= +x8OdT1dgrFXya0kigu4pnPi8nt7qT8RGurP20jAB3FV9mNKG2V1DX3svO+FrslRIJhe0MCXCko= qmHTUerGBniRFpF3/jtlBJ7LtYT7achs8rAfx3XEuiuIremi45uC9F+jnycqEMG4vPbaNSbmBrt= xvvn674X3Lx7ro7ihm4a9SZ2nKnB11XFEx+XkFfbha+LChl4++z/Z++8w6uq0rb/O/3kpPdeSUI= CIQkthdClyAwtgEiTzsD42kBHUQRHHQsjI44ooigoAVSQjoICgUBoIaGXBNJI7+UkOTl9f3+EbM= 2Ajo44M+/75b6uc13J2WuvtXZb59lPue8y7NQy/vpNMRYBBoQ7YquS3fd1rhOd+E/gNy8F78SPo= 51crbCwkPDwcOLi4ujfvz+JiYmsXLkSOzs7YmJiGDp0KOHh4YwcORJXV1d0Oh25ubksWrQIR0dH= FixYgK2tLRaLBYvFgpOTE/3790ej0bBp0yYsFgstLS307duX4cOHU1tby9y5c1m/fj3FxcVkZmY= yYMAAJk6cSGlpKXZ2dowePZrr16+TlZVFc3Mz//M//0Nrayt//OMfkcvlxMfHExsby7Bhw3j11V= epqqoSvQYHDx6kZ8+ezJs3j4kTJ+Lg4MD48ePRaDS89tpr2NnZ8fDDD9O7d2+mT59OaWkpV65cY= dGiReTn54uq5kFBQcyZMwd7e3uWL1+Og4MD3t7emM1mrl27Ro8ePRg9ejT5+fmsWbMGpVLJ5s2b= WblypUjy1X6eExISCAsLY9GiRfj4+LB582bc3d156aWXcHBwYOvWrVy5cgVBENi3bx+vvvoqUVF= ReHl58cUXX9C9e3fCwsIYP348iYmJpKWlAW1aM1OmTEGr1eLh4UG/fv1EUrqnnnoKtVrNm2++yc= 2bNzl27BhJSUk888wzInGbxWIhNTWVTz/9FFdXV0pLS5k4cSIRERFMmTKFpKQknnzySWpra+/J8= xIZGckTTzzBW2+9JRKUtUMQBA4dOsSLL77I4MGDWbt2Lb169WLChAnk5OQwZ84ckfTvySefZNy4= cbi4uBAbG0tdXR2lpaWsXr0aHx8fmpqaqK6uprm5mcjISBYuXEhVVRUmk4nevXsTGxvLgAED0Gg= 0oocqJSWFgoKCDvID90JsgB0LBnlzKk+L0SLQM8AOi1Vg4WAfGnRmvByVjOvpRlZhEyOinJk30J= viOgP7L9ag1Vuo0pp4b0YYUX62HTwPGflNDOra5r1r1rcZPN9eLSMpzJFp8R6M6+WGXCahpslEZ= mETFY1GtpyuRK2Q0qS3UNloZFZ/L6q0JpaNDuS9w6VUaU1kl9fyQKQzfxjsTUWjEXu1jCERTlwr= bcHdXsGaGaF8ml7BmXwtQ7s5sSurhmHdnJnd35PCmjbdqAHhjuy9UAvAtdIW/FzUPBznQWZBEwP= CnTCYrRy4XEe4l4YefnrKG42M7+VGYqgD289Vc+JmAz5OyrtP5h1sPl3JsedikUmhtN7A2bwmev= jbMbybE9MSPLlS0oJCJmFKvAf7LtYS7KbG3V7xk9epE53434ROH+R/EAqFAldXV+RyOQ4ODri7u= 4v/C4LQIaFTEAT69u3L6dOnKS0t5dChQ3h4eGBra4tMJhMF5urr6zl27BgxMTEIgsCECRM4d+4c= RUVFbN26FX9/f5ydncWQjcViwWw2U1VVhVwuFyXm20MWRqORkpISzGYzarUalUqFra0t7u7uojY= Q0GGuJpOJ2tpacU4Aq1ev5ty5cyIRoYuLC25ubuI8bGxsRM2Zdtjb22NjYyPq0bTr4wiCIIohCo= KAg4MDMpmMBx54gJMnT/LOO+/w/PPPi9pPCoVC1LmSSCTY2NhgsVhEz4pUKhX5Kv74xz+ybt06H= nvsMQ4fPnxP8sF2htB2BAUFUVlZyb59+5g4cSJWq5Xa2loMBgMSiURknd2zZw/du3dn+vTp3Lx5= U9zfycmJ1atXi7T1ycnJODo6itegXR/nXsjMzGTp0qXMnTv3Ls9Inz59OHDgALt37+a9996jqal= JTIxuZwltbW0VOYhCQkJQqVTiPWi1WkXBxfLycj7//HP0ej0yWdvbva2tLQaDge+++05kvY2Kis= JoNIqaRu2htHatnXvBSSNHIW8LVFt+JEHb3V6BnVqOrUqGRilFKZegUcl486EQknu7Me7dq+y7W= Cu2N1kE6lpMdPfVkHqjgbiQNq+XVYD8qlYsVgEfJyUuGjkutnLaJYkSujjw3TMxlK5O5Nuno3G1= leOokeFmL2+r9RTAahUobzSikEnwcFBgr5bhfcfQKK03Mun9axjNAo8kthmwepMVuVSCTCpBIZP= QbLDg6ahErWw7R8886M+pW42MXHWZxFAHfJyUeDko7woR1baYeGzzLfKqWlkywv9HzydAo87C7V= q9GPZSyCW42MpxsGk7Vm8nJQqZlPhXzqNWSFky0u8n++uSkU8eAAAgAElEQVREJ/63oTMs9R9ES= 0sLBw8e5MKFCwQHB7N7926Rfnrfvn0kJSVRXl4uUsNXVFSQlZVFdXU1Bw4coKqqikuXLolU4ra2= tuzbt4+mpiZGjBiBQqFg+/bton7JhQsXyM3N5eLFi0RFRbFr1y6qq6uZNGkS77zzDra2tqSlpeH= r68tXX31Fbm4uY8eOJTU1leLiYm7fvo2NjQ3du3dn69atqFQqampq2LVrF3FxcaK3xNnZmXXr1o= k6MM7OzqSlpREYGEhJSQk3btzAarWSlZVFcHAwx44d4/LlywQFBfHtt99iMBiIjY0lOztbzMlRK= BRERESQkpKCo6Mj0dHR7Nu3j4aGBpEa/urVq2RmZtK9e3cEQaB3796ikGG70rhOp+PYsWPMnTsX= g8HA119/jVarpaSkhKSkJP785z8jlUpxc3MTldp37NjBwIEDycnJobKyEkEQOHLkCNXV1YwaNQq= 1Ws2pU6fQarUkJiYilUo5efIkt2/fprCwEIPBgJeXl6hKbGNjQ3h4OD4+PkgkEpqamtixYwcNDQ= 2cOXOG8vJyDh8+jJ2dHWazmd27d9OlSxfCw8ORSqXcuHGDbdu24eXlRUVFBVarVcy9iYuLE6UaP= v74YzIzM0Va/8GDB7Nu3TqUSiVXrlxhxIgR9OzZky+//JKamhry8vIoKCggJyeHK1euMGrUKHJy= ckhPT6euro4jR44QGhrKnj17aGpq4uDBg5SUlNDa2kp0dDS1tbWcPHmSkJAQsrOzyc3NJT8/n4M= HD+Lq6opUKqWsrEz0QJksAp+fqeRamY5AVzW7smpQK2SolVKuFLdgq5KhNwlcLm7GzV5BWk4DNU= 0mDGaBQ9fqefQBH1YdKMZWJcNsFejmq8FqhbxqPecKmnCzV9Ddx5aDV+uY2McdlVyKxSrwZUY1V= gEuFjVzpbSF7HId18t09At14EppC6X1BioaTWw5U4nOaOVCUTPdfGzZfb6GxlYzA7s68eHRMjwc= lOy/VIetUsbXl+sorNHjYqugoEbPiChnzuQ10Wq00t3Plo/SylEppHx9qY7sch2xAXbsOl+Dr5O= Kby7XEeCqZt5Ab1ztFFiBgho9ey/U4ueioklv4XJxCzKphLwqPQO7OnK5uJnyRiNOGjm7z9fgaq= /Aw17B1VIdfi4qimr1nMlrollv4XpZC1PiPdiVVYPFCgPDHSmpM5BZ2MSiIT70DLCjvNFIiLvNf= 2op7EQn7js6jZv/IAwGAy0tLaIXxMHBQdR2GTZsGC4uLsTHx6PX6/Hw8GDUqFE0Njai0+n4/e9/= L+p6hIeH4+DgIKqGBwQE4OvrK+rAlJWVYbVaiY2NRaPR4O/vj4eHh/j37373O8LCwkThuXbtoKi= oKCIiIhg/fjxFRUVIJBLGjRsnemmCg4OxWCw88MADODo6ito/bm5uBAYGUlVVhb29PUOHDsXDw4= P6+nr8/PxEjZSwsDB8fHwwGo3ExcUhl8sJDg7Gzc2N+Ph4PD09KS8vx87Ojnnz5lFTU4OPjw8OD= g4MGzYMNzc3ampqUCqVzJgxAycnJ5qbmzEajQwfPlxMcm43biQSCQ4ODsTGxvLAAw/Qu3dvGhoa= 0Ol0xMbG0rdvX7y9vWlsbMTd3Z0hQ4aQm5tL37598fHxoWfPnrS2tqJSqfDy8sLNzY1evXqhVqu= xtbUlICAAHx8f7O3tCQkJoaqqitbWVsaMGYOvry82NjZUVFTQrVs3+vXr18Hj5uLiQl1dHTY2Ni= QlJWFraysmIvv6+hIYGIifnx8ymYy6ujox32fIkCE0Njai0WiIj48X7yFo86xIJBIsFgsjRowgJ= iaG8PBwioqK8PPzY9SoUTg6OuLv709NTQ0Gg4Hhw4djNBpxc3MjLCxM1DozGAxMmjSJyMhInJyc= aGhoYPjw4YwdO5YHH3wQvV5PS0sLvXv3pkuXLowePZq6ujocHR0ZO3Yso0ePpqysDJPJ9P11EaC= 80Uiohw2OGjkh7jZ09bahu68tvs4qLFaBoZFOGM0Cdmo5WYVNeDgocLSRMy3Bgxh/O2xVMkwWgW= A3NdMTPSmuN9BisOBsK6dPsD0apQyVXIqXkxKZVIKfiwp3ewW1zSZUChk9/GzRqGR089HQxcOGB= 7o5o221oDNa6B/uiJ1aRoibDc4aOU4aOeGeNozs4UKEt4b6FjO+ziq6eNigN1rpFWRPDz9bgt3U= aPUWIrw1BLiomRLvgb1ahlIuJT7EnvkDvdGbrfg7qwhwa0uKDve0wWC2YjBbOZWrJdTDBn8XFQG= uanoG2OFiK8fLUUnPADtaDBZCPGzo6qVBIoFeQfZ4Oylx0rQdVxcPNUlhjmj1FlqNFh6O9yDAVY= UggKejkig/W5oMFi7cbsbRRo7BbCXrdjPhnhocNZ2ZCp34v4F/A0NxJzrxn4XJZGLVqlUEBgYyb= dq0//R0OnEHzXoL8a+e/9ntyxuM2KpkONj830p6rWsx42L7vVFR22zG1e63NTJMFgGDyYqduu1c= Brmp2flYd1Sd1VKd+D+CX2/cCAIWaxvxnlRiuSNuKadeb+DbjCz8/ELw9HDC20aBRmrBLJUjQ4r= ih5IKgnCHDE1CbW0dV65cpay07I5ag4CAFW9vT4YMGUpdXR0SiRRnZyfk8vZF7oc8yHdNkHaZh4= 5tO7Zvm4MFo9FCk7YZq2DB1dUNmaxtP0ln7fr/WhQWFtK/f3/c3d05fPhwh3yZTvzvwNvflrDmc= CmRPhpWPdyFbj6af77T/xK8e6iU1d+VAODrrOLLP0bi66z6TcfMLtfx0PvXaTZYAFg5OYTJfd1/= 0zE70Yl/J+6D50bAIliRCFIECVgEC4JESlWTjsfe+JDaVnu8Pb2Ij/QmqYcnPYK8USFHLpWIBkP= 7FAoLi/hw3cfk5+dhNJrE/q1WC7GxMTz9zBKWL1+BnZ0dS5Y89Q8JlD/FcCrQZtxI7vx9LwNHQB= Cs3LyZy4cffkRzczOrVv0Ve3sHQEDSwbrptHQ60YlOdKITnfhvxa/2feqMZm7Xa/F1dkCtlANSr= IIEq0SCDDWtBiXZpXpult3i5JXLrHlqCl52HUsOJRIJer2BlJQt5OTkoFarCAsLvGO8CFitVoKC= A5HJZISGhqLR2IgEaD/oRfxLEO5ljPwMg+ROJU2XLl3Q61vv5ER07PvHx+hEJzrRiU50ohP/Dfj= VAdaSmiaeXPsdf/rwWz4+cIHq+hZUEgkCYJTaYZbZIJFJMSOjrkGPYLK2GQz/YBfk5eVx9cpV5H= I5PaKjeGrx4zz2+CIee/yPPPHk/5CcPA6ZTEZQUCD+/v7I5QoEARoaGkhPP8XevfvZvXsf33zzL= UVFxZw4kc7OnXvYvXsvu3fvY+/er7l27QYWi/VOuEtCQUEh3313iD2797F7915SjxxFAgQFhRAS= 0gWQcuHCpTt97GXXrr3s33+A7Oyc+6IplJWVRc+ePQkJCWHBggW/ur+fgk6nY82aNZw6deo3Hef= nwGKxsGLFCk6cOEFlZWUHTpqfg/fee48PPvjgN5rd99iyZQvr1q37yTZZWVmEhIR0+AwePJisrC= yxjVar5emnn+bChQuYTCaWLl1KXl7eL57P8OHD79K4asfKlSs5dOjQXd/X1tYydepUQkJCmDZtG= tevXyc9PZ2srCz+8Ic//OI5/CMmTJhAY+O99ZEAzp07R2xsbIfzM2zYMJH7pqGhgeXLl5Ofn3/P= /evq6li6dCklJSX/dC4vv/wyx48fv+e28ePH89BDD911rV577bUO7dLT01mxYgVms5mDBw+yatW= qfzruPyI9Pf1Hz21xcTHTp0//0X2vXLnChAkTfvGYvxYXL15k+fLl6PX6e24/e/Ysr776KgaD4b= 6PbTAYWLt2LceOHbsv/dXV1fHyyy93eAbvF1asWME333zzs9quXbuWkJAQ4uLi2L59O1u3bhW3v= fjii7zxxhv3fX4/xIULF+663/v3709GRsZvOm47rFYrmzZtYvPmzf+W8e7Cr9VvuF5cL/R4dJsQ= tegLoeuc94R3tn0nmARBKNC2CL9f9qkQ9diXQrcndgkRj+8QBiz5ULhd1ySYhbu1pQ59lyqMHTN= RmDF9jvDtt98JFotFsFotgtVqFgTBIgiCIDQ0NAizZs0RHnvsCaGyslIoK6sQnn12mTB+3CRh/L= hJQvL4ScKM6bOEw4eOCi88v1wYMyZZSE6eJCQnTxLGjZ0oTHl4hpCaekwwmUzC118fEKZOmSGMG= ztBSB4/WRg/boLw+ONPCsePnxTmzV0oPDRpqlBdVSt8sPYjYfz4SUJy8kNC8vhJwrhxE4Rp06YL= 6eknf+2pEwRBEPbs2SO88sor96WvfxV6vV544YUX/m3j7dy5U+jatavw7bffit9ZrVZh8+bNQkF= BwU/ue+XKFcHDw0N4/fXXf9M5Xrp0SYiPjxdeffXVf9r2xIkTwuOPPy7odDpBEAThwoULQmZmpr= g9LS1NsLW1FU6dOtVhv5ycHGH16tW/eq7p6elCeHi48NVXX3X4vqWlRYiIiBA2btwozqtHjx7Cw= YMHf/WYvwS7du0S73GdTic888wzQkBAgNDY2PiL+ikvLxc++uije25LSUkRAgIC7jq2yspKYdKk= ScKlS5eE6upqYdmyZcKFCxcEQRCEsrIy4ZtvvhHb1tfXC3/4wx+EcePGCUajUfzebDYLM2fO/EV= zvRd0Op2wePFiITg4+J7bW1pahEWLFv3o9vuN48ePC0ePHhWs1v9epT+dTicsXbr0F+2zbds2IS= IiQjh58v6s0e3YvXu34OjoKHz55Zc/2c5sNgsvvviiMGHCBEEQBKGurk5YsGCB8PTTTwuCIAjFx= cVCZmZmh3vst0JmZqawYMECoaWlRRCEtnXtzJkz/3J/VVVVwo4dO4Ta2n9N7+3fiV8dlhKQYJGp= kWNEotSgFyQYAAuABARBgRUlEoxIaVMB/95pY6U9ZGQwGJBKpcgVChwdnZBIpPxjrotEIkGhUCC= Xy5FIJOzauZubOTfp2rUrvfv0QqlQIFfICQoKQiaTo1Iq6d27F2HhYWRlnicn5yaZmefx8PBg58= 49mM0WomOi6d6tO3KFFEdHB+zsNCgUCpQqOTK5lITEeLx9PAEJgtXKrdxcsjLP8/nWL0lK6vdrT= 9+PwmQysWXLFgCSkpIICwsTt7W0tLBz5048PT1xdnYmICCAAwcO4ODgQP/+/Tlx4gStra0kJCRg= MBg4f/48o0ePprCwED8/PzQaDbt37yYkJARPT08+//xz9u7dywMPPIC/vz9nz54FoG/fvnTt2lU= c12g0kpqaSkVFBZGRkcTHx5Oenk5lZSV9+vTB1dVVJMOzWCxkZWVx/fp1fH19GT58OM3NzRw5co= T6+nqGDh0KtL1lHT9+nNDQUD766CNu3brFrFmzaGpq4vz5tkqa2bNnYzabOX36NHl5ecydOxdo8= 4h8++23tLS0EBISwsCBA8W5NjU1ce3aNaxWK7du3SIqKorevXtTVFREamoqCoWCQYMG4efnx+nT= p6mvr8dsNjNq1CgUCgXR0dHMnj2bhoYGTCYTWVlZZGdni/P5MTQ1NeHo6EhwcDAAO3bsoKmpSTx= ei8VCWloa3t7evPHGG5jNZk6dOkVwcDDHjx9Hr9cTGxtLTEwMp06dwmq1iuc3MzOTiRMnUl5ezo= kTJ9DpdCQmJpKUlMT48eNFcr12rF+/nsDAQHG+sbGx7Nmzh+rqaoqKiigrKyMhIYHy8nJOnjxJc= 3MzY8eORa/XU1VVhV6vp7CwkH79+hEQEMDZs2e5ceMGAQEBJCYmYjabSU9PZ9SoUWRmZnL16lXs= 7e0ZMGDAXRpX7bCxseGll17i5s2bvPHGGyxfvlzUSlOr1aSmplJWVga0kSWOGTOGq1ev4u3tzdt= vv012dja9evXC1dWVY8eOoVAo6N+/PzNmzLjrjdRsNnPgwAHGjx9P9+7dRbLCdrTzFEGbRMc333= xzZ+1oO4+5ublotVpycnLYvHkz48ePZ/DgwVy5coX8/HycnJwYPHgwSqWSbdu2iSSTLi4uNDY20= rt3bzIyMrh58yZyuZyJEyfy2GOPcfHixbvOi16vZ9u2bURHR5OZmQnQ4To/9NBD2Nraiu1v377N= rVu30Ol01NXVMXv2bPLz8yksLKS0tJSEhATMZjNnz57Fzs6OSZMmkZuby6VLl0SCz/fffx+NRiO= SetbU1NC7d28KCgpEBm6AUaNG0dLSglarJTY2lvz8fI4fP45SqRRZ09tRV1fH0aNHUSgU+Pn54e= 7uzpEjR3BycmLAgAG4urpy8OBBKioqgDa6guTkZK5cuYKPjw9yuZyDBw/SrVs3VCoVmzZtIj09n= aNHj6JWq7FYLBQXF9OzZ0/y8/OpqqrCx8eHESNG0Nrayq5du2hubhbXgurqar7++msAcX37IXbt= 2kVjYyPR0dH06tWLQ4cO4evry40bN/D29qZfv+/X+HHjxolet+bmZg4fPkxDQwN+fn4MGzZMbJe= Xl8fVq1dFz4yzszNvv/02hw4dwmQyceHCBUpKSmhubmbAgAFcv34dq9VKdnY2EomEuLg40tPT6d= WrF5GRkdy8eVP0uI8ZMwaz2Ux+fj65ubkEBwdjZ2cn3lOTJ09Go7l3sn1zczO2trZER0d3OPaIi= AgkEgk3btxg5MiRZGdn09LSIrLUtz9XM2fO5PPPPxePY9KkSaSmplJaWkpQUBCDBw+mrKyM69ev= U11dLY5jY2NDSEiIeN0DAwNJSkri9u3b1NbW0tDQQFNTEw899BClpaWkp6fT2tpKv379CA8Pv+e= x/Bzch7o/CSapHLNcAlIBpBIkgEwAqSCIabwSLEgR7uwBkntUOAmC0Pa90J7022HrD0JBEgwGEz= k5OSLLr1qtRi6Xo1bbYGtni0Ta1ndUjygmTkxm0KCBCIKAXq+noKAQXYsOBwcHpk+bykOTJzJxY= jIPPDAUlUolji2VSvH3b+OLkctkKJRK7O0dUChVVFfX8lvi66+/5tixY+Tk5HRwZ0KbS/PRRx8l= Ly+PlpYWnn32WaRSKZcuXeKLL77AZDLxxhtvIJFIaG5uFnWYnn/+eQoKCti+fTsVFRV8+umnnD1= 7FolEgkQiQSqV8v7774s/fB9//HEHN/TBgwc5ceIEEomEtWvXkpqaSkZGBjU1Nbz44ovU1n5/Tn= JyctiyZQsWi4W3336bEydOkJKSQl5eHhKJhIsXL9Lc3Mzy5ct58cUXO8zBZDLx6aefUlVVRUpKC= pmZmZw7d449e/YgCIL4oB86dIi0tDR0Oh0pKSlUV1cDbYbhjh07mD17NqmpqTQ0NPDOO++QnZ3N= 2rVrkUql5Obm8t5777F3717mz5/P3r17kUql98yjqqys5Msvv0Sr1fLuu+9y7dq1u9ocOnSIBQs= WMGvWLNE4/Pzzzzl37lwHZuC33nqLv/zlLzQ0NIjHq9PpOHToEI2NjZhMJtasWcNnn33GY489xg= cffIBUKmXTpk3MmTNHDJdkZmZSVFR0V1jlh/jmm29ISEjo8F1wcDCBgYG88sorbNiwgaamJnbu3= ElpaSn5+fk89dRTrF69mtmzZ3Py5ElOnz7NgQMHyMjIICUlhZaWFjZt2kRubi5z5sxh5cqV1NbW= snr1aqRSKcePHyc1NfUn7207OzsSEhI4fvw4+/bt44UXXqC6uprLly+zZcsWpFIpy5YtEwkily1= bJp6v9s+bb77J7du3ycrK4ptvvunAkN2OlpYW8vPzOxgsJSUlLF++nFmzZvHSSy8B0NjYyB/+8A= dRx6y2tpbq6moWLFjAt99+K94TUqmUy5cvk5WVhVQq5ezZs2zYsIEXX3yR+fPnk5OTQ2lpKc899= xxbt26ltLSUnTt30tTUxJYtW0Sj5V5YsWIFlZWV5OXlodPp0Ol0fPnll5SWlnL58uUO17m2tpbZ= s2fzyiuvUFFRwUcffcSGDRtYtmwZq1atwmg0UlVVxWeffYZOp2Pbtm188cUXnD17lqKiIhYuXCj= yVrXf87Nnz+arr74CYP78+Wi1WjIyMsRQ5+zZs9mzZw8NDQ28/fbb4rn4+9//Ls6r/XleuHAhFR= UV1NTUsHLlSqRSKRcuXBDPwQcffIDJZGL9+vVUVFSQmprKc889x61bt/jkk08wmUxs3LiRzMxMc= X7Xr1/nqaee4uOPP0YqlZKRkcHBgwcRBIE33niDqqoqce1qbW3l1q1bAKxZs4Zr165x/vx5Dhw4= gMViEee7Y8cOzp49S2NjIykpKaxfv565c+eyYsUKrl69yieffPKj1+vEiRMcOXIEq9XKxo0bKS8= vF7e1G+ftL3rtfycnJ1NQUMCGDRuwWq08++yz5ObmMnv2bJYtW4ZWq+VPf/oT7733HufOnePdd9= 9Fp9Oxa9cuCgsLOXr0KFu2bGHNmjU8+eSTtLa2otVq2b59O1VVVWzbto0TJ07cNddjx46Ja9Pp0= 6cB+Oqrrzh79iw1NTWkpKRQWVkphn9zc3NZt24dVquVTz75hIqKCr744gsyMjKQSqXi58yZM5w/= fx6pVMrf//539u3bx4oVK3j99ddpbGzk9u3bLFq0iNOnT1NYWMhf/vIXWlpaxGs7a9Ysli5dSn5= +Ps8++ywVFRV8/fXXXLx4kcLCQv7617/+6Pn/ObgvZAoCEqzIkAttpowEkCIgESwIEivCnXJsqc= QKku8NlB/CxkYNCBgMJqprarBarXcWlfYKpztj3Unk1bcaaG1tRRAEzpw5y8mTpwABd3d3nnjic= SRI7pSlt0Fto0YqaeurVafDarWgVCrx8HRHIhHu0NvfaX9njkaDkd2793DkSCoGgxEBAalEilyu= +M2TiYcOHYqrqytPPfXUXdbrzJkz2bx5M3PnzuXGjRscOXKEo0eP0traytChQ/nwww9F0jq5XM7= cuXNpbm4WLXBbW1tWr17N3//+d+Li4rh69SrHjx9n8ODB9OjRg9zcXMaPH8+DDz6I2WxGpVKh0+= lITU0lJSVFfIMcPHgwR44coVu3brz11lsdqtdOnDjBxo0bcXR0pLa2lpiYGADmzZsneik0Gg2TJ= k3i+PHjBAcHExYWxujRowkLC+PFF1/k7bffJiMjg7y8PEpKSkhMTGTChAniwjVy5EhGjhxJREQE= 4eHhNDU14e7ujlwup0+fPsTHx/PII4/g7OxMdXU1mzdvxs7OjpkzZ2IwGJg5cyYLFy4kMTGRsWP= H8rvf/e6e18LLy4uXXnqJxx57jOzsbMrKyu7KE0pISOCFF16gqqqK4uJiGhsbWbt2Ld9++y2tra= 2iQTZjxgxOnz6Nv7+/+Hbq4+PDpUuXmDNnDo6OjlitVkwmE1FRUYwcOZLk5GSio6P55JNPkMlkT= Jo0ifT0dJYsWXJPMcp2ODs73/N7V1dXBg0axJkzZ6itrWXDhg2UlZUhCAKurq4888wzWCwW5s+f= z7Zt2ygoKKCiooLf//73jBw5kmnTpqHRaFi8eDHLli3DycmJd955h+3bt/PVV1918Pb9FFxdXen= Zs6folbRYLOJ1WblyJQkJCdja2nLixAlcXV0ZOnQoMpmMXr168corr3Dz5k2Sk5P54x//2OFHqx= 16vR6DwYCLi4v4naenJ1OnTqVbt2589NFHAKIY7MyZM3F1dWXv3r24uLgwduxYrFYrgwYNEgks3= 3zzTeLi4hg6dCi3bt1i+/btjBw5kjVr1jBv3jykUinV1dXk5OTg4+PD8uXLWbx4MRkZGVRXV99T= H+zq1ascO3aMkydPkpGRwYkTJ2hpaeHdd9+ltbUVs9mMvb09r7/+OtAm1zFt2jRu3LjBnDlzCA0= N5a233mL8+PHU1NTwyCOPcOLECd5//30cHR3RarUiWeONGzf46KOPCAgI4MKFCzg7O9OjRw+mTZ= sm5j0VFRUxdOhQ3N3duXr1Kh4eHkyePJna2lpSU1Px8vJi5syZtLa2MmLECPE4NBoNEydO5OjRo= 8yZM4fTp0+zf/9+9u7dK5JZdu/enaqqKqZNm8bx48fp3r07UVFR4vrQvjZt2LCByMhIjhw5Qmlp= KfPmzePatWsMGjSIhx9+GJ1Ox4ABA0hOTqapqYkrV66I3kCz2cz169cBeOKJJ7h9+zYPPvgg8+b= N65AruWnTJk6ePIlKpUIikbBhwwbCwsKYOnUqoaGhPPfccz967w4cOJABAwYQGRmJj48PjY2NeH= t7A6BUKlGr1ffcLygoiJdffpnXX3+d8+fP4+Pjw8iRIwkODmbOnDm8//77jBgxAo1Gw9tvv41ar= WbRokV8+umnrFu3jqCgIPr160drayvTp09HrVbTr18/3nzzTU6dOsXkyZPvGrNPnz689NJL1NTU= iNf4s88+Y/Pmzdja2tLU1IS9vT329vao1WrxvLe/ZHzwwQecOnWK4uJiEhISqKio4IEHHuDRRx/= l+eefJyYmhsDAQNatW8eECRPIyspixowZohEK4OPjQ0pKCqtWrSItLY3ly5eTnJxMS0sL8+fP56= 233qK0tJQpU6Zw/PhxFi9eLJJ9/qu4z4xNEjrm2d7LA3Nv+Ae0uXSNRgOnT5+hIP82TU3NaLVNa= LVN6HR6RJ+Ptc3VZWOjQSaTMXToUBYvfpIlS55iwYJ5eHl7ImAFifUfxm9767PRaJBI2jwEtTX1= mM0WLBb4Xr6n7Tjq6xu4cOESCoWSmTNn8vSSp5k0adKPuv3uB1pbW9HpdGzatIlVq1bxpz/9SRR= ZbIe7exsfRftD2adPH27cuEFlZSWffPIJDg4OTJgwgYMHD2I2m5HL5dja2orzHjp0KAcOHGDNmj= V8/PHH4luv2Wxm+fLlvPfee6IK9w/h6OjIxo0buX37Nvn5+YwfP56tW7cyZMgQxo0bx+XLl8W2N= jY2oqdIp9Mxffp0zGYzJlNbib/VaqW5uRlHR8e7xtHr9UyfPp2QkBBmzJiBIAiYTCbxB6zdI5WS= kkLfvn25dOkSkZGR4v4SiQRbW1uUSiU2Np8NDqgAACAASURBVG2U8u1swHl5eeI5UalU2Nvbi21= /DEVFRYwfP5758+d3cD//EPb29vj5+ZGUlERycjKNjY0YDAaMRqPobaipqcHd3f2u8JEgCFRUVI= jJnGq1Gjs7OzQajXjNHB0dkclkmM1m1q9fz44dO3j//fd/dM7Q5sLeunUrdXV14nfnzp1jy5YtO= Dg4iAZ6v379SE9Pp6KigtOnT+Pr64ujoyMajQZBEMQXjby8PKRSqaj31b6Y19TUMGnSJBQKhegN= +TEIgsDNmzdJSUlhwoQJ2Nraiteoa9euODg4EBYWxowZM+jTpw+2trZ3vKnfw2Kx8Pjjj7N27Vr= WrVvXIVzzz6BQKPD09MTf35+XX34ZrVaLTqcTNdYkEgk6nY7W1tZ7GoeCIFBQUACAXC5HoVDg5u= aGRCJBpVKhUChE9faCggIefvhhpkyZwtSpU390ThaLRby/pVIpZrOZ2tpaEhMTOX36NNXV1Zw7d= 05sL5PJRDmL9vtarVbj4OCAWq0W77epU6eSl5eHVqvlzTff5KmnnuKJJ55g2LBhHDx4sMMcfhha= Wr16NcnJyaxfv54ZM2YgkUjE7YIgkJOTg9lsRqFQdLg2UqlU1CVTKNpeAEeMGMHNmzepqKhgzZo= 19OvXj9jYWGJjY/Hz8yMuLq7D2vTQQw9x6NAh/vSnP/H555+LxoharUaj0Yjact999x1z584lNT= UVHx8fUTS4/RpaLBYaGxtZunQpK1as4MMPP7yL30oikbBr1y5KS0u5efMmgwcPRq1W4+TkhEwmu= 6fB3I79+/eTmJhIbm4uPXr06LDN19eXurq6Dh7euro6nn76acrKypg9ezazZs3C398fpVKJk5OT= qI/XrqPXrrHX3NzMc889h8lk4vnnn0cqlWJvby/q5NXW1jJv3jy6d+8uhuv/EXZ2dvj5+dGvXz8= mT55MQ0MD0OZdl8vl4vPXfi+azWZ0Oh21tbU88sgjODk5MW/evLv6NZvNYqJ/u+6go6Oj+LukUC= jE9b2goICBAwcycOBAhg0bhlKpxMXFpcPa255Yvn//fvHF49fgt6XB/AXOjaCgQPrG9eXUyVPcu= pnL2397B2cXZ0DAYrESFhbGxInJd/xCoFTJiYiIoKSkhNLSEvwDfFEq5BhNRpqbmu88FIJobAlC= Gx0gAncWbwfq6urYvHkrkZFdQSrBydERDw9PECRIkCKRSEXXrcViQafTodcbEATrfamWqqysJC0= tjby8PNavXw+0xdLbF4SuXbty5coVbty4wdWrV4mKigLawkMGg4FTp04RHR2Np6cnzz77LJGRkT= g7O5OcnExUVBTr168nIiIClUrF9evXuXDhAoGBgWzfvp3AwEC6desmLoglJSV89dVXVFdXM2DAA= Hbv3k1RURGlpaWEh4ej0WiIi4vj008/paysDJlMhlwu5/bt2/j4+NCvX78OoYG+ffuyf/9+3n77= bZydndFoNMjlcnFOly5dwtvbm5s3b9LQ0MClS5dQKpXs2rULo9EoGj/FxcWcPHmSyMhI9u7dS3V= 1NWfPnsXBwYHKykrGjx/P5s2bKSgoIDs7m8DAQNF4qK6uJiUlRczTmjhxougRcnBwYMiQIRQVFX= Ht2jUCAwNJTEwUfyirq6u5du0aZWVl9OzZE3d3d65du0Z9fT1nzpwhMTFRVP/et28f165dY+PGj= SgUCurr6/Hy8mLAgAEsWLCApKQkcnNzSU1NRRAECgsLuX79OiqVitOnT+Pj44NMJmPTpk3ij1ZA= QICY2zBkyBAyMzPFEJJer8fNzU0MCR44cIDc3Fyam5sZNmyY6A6fPn06586d44knnmDQoEFAWx7= H/PnzWb9+PdevX6e2thYHBwfWr19Ply5dqK+vF3OMLl26RHp6Olqtlvnz5/Pyyy+jUqnQarUkJy= ezbds2qqqqSEtLE/Ws2t3U9fX1ODs7U1FRQVpaGgUFBaxfvx6j0cipU6cYNmwYs2bNIi0tjStXr= pCRkUFkZCR6vZ5nn30WgMOHDyMIAteuXRNzRy5fvsx3331Hbm4uixYtIi0tjerqalGJvN3AbDcO= 7e3tRePuu+++4+LFi0ilUs6dO4fBYECr1dK3b1+uXr3K6tWrKSws5OLFi2RkZJCWltZB9POLL76= gW7du7Ny5E6vVil6vJyIigsuXL2O1WklLS6NHjx6cP3+eGzducOnSJXx9fbl58ybFxcVkZWWh1W= opKyvj8OHDoqEcEBCAu7s7f/7zn7FaraKGXHBwMO+++y6RkZHU1NTw/PPPi8+X1WrlwoULrF+/n= oyMDBYuXEhqaiqFhYXU1tYSFRWF2Wzmtddew9/fn9bWVlGA9cEHH8RoNIr3X1hYGIcPH6asrIyK= igr++te/itcgPT2diIgIjh49SkNDA2PHjqW8vFzUonvkkUfEORkMBo4dO0Z9fT1ZWVlERkZiMpl= 4+eWX8fX1xdvbGy8vLxoaGsT+MzIycHFx4fz583h7e5OSkkJ0dDRJSUkolUqUSiW3bt1i/fr1XL= lyBb1ez+DBg6mqqiI6OpodO3bQ3NzM7du3USqVrFy5El9fXy5fvkyXLl24cOGC6A2orKykrKxMF= KSdPXs2zz//PLNmzaK5uZnQ0FBKSko4ceIEfn5+lJaWcvDgQR588EGgLQfr+vXrODo6olAoGDFi= BBs3bqS4uJhr167RpUsXFAoFgYGBPPHEE7zxxhsUFRUBbaGqefPmkZeXR1BQEIWFhbS0tLBhwwY= yMjKoq6vD3t6empoasWqssLCQ06dPiy81ubm5lJWV0dLSwo0bN7h16xbOzs7Y2tpSW1tLUVERJp= OJMWPG4OrqSlVVFbt27SI7O5uNGzeiVCppbGzEycmJGTNmsHTpUqZOnYrVamX06NGidp/VaiUnJ= 4eMjAz0ej0Wi4WCggIMBgNubm4UFRWxY8cOZs2axdatWykrK0Or1fLoo4/y3Xffcf78eSoqKrCz= s+PMmTMEBASgVquJioqiqqqKgoICPv/8c7Kzs5HL5ezfv5+Wlha++eYbBEHAxcWFM2fOUFVV1eF= 375fiV2tLVWsNfHGqGCkWpBY90cGOJHQPptVg4sDJq9Qb1FglCsCEg6yFcYNicVQrO9g9VqsVqV= RCly7B1NXWU1NTi1bbRE1NDfX19VRXV6PR2BCfEMehQ4dQqVQMGNCf0LAulJaWkZeXz+XLl7l06= Qo52Tfx9w/g9u3b1FTXEhMbQ9euYRQWFpFx9hxe3p4MHjwQF2dn8vILKC0pJftGDjeuX6e6ppaw= LmFcuXIVg9HIuHFjaG5uIS83l2vXrnH58mXy8vIwmU1IJBIeeujXlWy2trZisViIiIgQH2Q/Pz8= SExOJiYnBbDbj7+9PTEwMvr6+YgiioqKC4cOH4+npSVBQEElJSRiNRmxsbEhISMDT0xOFQkFAQA= BBQUGi5pKrqyuhoaHExsZiZ2cniin6+fnh4eGBl5cXCQkJWCwW3N3diY+PJzg4WHwTDQ4Oxt3dH= bPZjKenJ4MHD8bNzQ2dTkdUVBSJiYmiYeHi4kJoaCgmkwmVSiWGVuRyOTKZjClTpjBs2DDkcjkD= BgzA19eXnj17AhAYGEivXr2wWCwkJCSICXu+vr5YrVZ+97vfMXbsWIYNG4YgCGg0Gvr27UtAQAC= enp5IpVIaGhq4du0aQUFBuLu7M2rUKMLCwkhKSqK+vh4XFxeGDh2K1WrF09OTsLAw/Pz8RP4kg8= GAWq0mJCSE6OhogoODEQSBIUOG4OfnR1BQEEqlktbWVlpaWkSNKaVSKRo27cfn4uLCkCFDmD59O= g0NDURHRxMUFESPHj2ws7PDx8eH0aNHo9frkcvlJCYm4ubmhre3N/7+/oSGhqLT6YiLi8PFxYV+= /fphtVrx8fERRVO7du2Kt7c3kZGRHTigBg4ciJ2dHVarFaVSydy5c8XtERERhIWFMWDAAFHFOy4= uDi8vL1HLyt7enp49e5KUlETPnj3R6/UEBgbStWtXqqqqGDJkCN26dSMkJASLxUJkZCTh4eEEBQ= WhVqvR6XQIgiDe4zY2NgwZMoQ5c+Ygl8tpbW3F29ubgIAAbG1tKSsrw9vbG6VSSVZWFvHx8fj6+= uLn50dUVBT29vb4+/szfPhwWltbCQ4OJjIyEnd3dwIDAwkPD8fPzw+lUolCoaC8vJy6ujoxHNKl= Sxfc3NzEufTu3Zt+/foRHx+P0WikW7duTJ06ld69e2M2m4mOjiYiIoKYmBg0Gg39+vUjODgYnU6= Hn58fQ4YMQavVMnLkSNzc3HB3d0cqlRIVFUV0dDSBgYFYrVYSEhIICgrCxcVFTL5v/5G1sbERE7= S7du3KmDFjmDhxIt27dxc9M8OHD+/gecjJyaGoqIiePXsSFxdH//79EQSB4OBgwsPDcXd3JzIyE= qPRiFKpZMyYMXh4eGC1WvH19WXMmDF4e3uj0Whwc3PDzs6Onj17EhwczPXr1wkNDUWpVFJVVYW7= uzsqlYqYmBhiYmJ48MEHaWhowN3dnZEjR4ohGKvVilarZeDAgXh7exMcHEx8fDw6nQ57e3v69Om= DxWKhvr4eT09PUcC1V69e4nrRniPm7e3NwIEDCQwMxMXFBaVSSWxsrBjODQgI6OAdCg4O5sEHH0= QikeDk5MS4ceMYNWoUgwcPxmAwEBwcTEREBCEhIaLxHxERgaenJ1arlcjISDw8PIiIiCAwMBAvL= y969eqFs7OzqNWm1Wrx8PCga9euJCUliS9sCQkJBAQE4O3tLT5H4eHhdO/enaamJpRKJYMHD6Zb= t274+vqKcxwxYgRKpZLIyEi6du2KjY0N8fHxovZf7969CQwMJDo6GovFQrdu3ejatSteXl706NG= D4OBgfHx88PT0xGKx0LdvX0JCQggKCsLGxkbMyenTpw82NjYolUrc3d0ZNGgQ/fr1Ez2NoaGhhI= aG0rdvXyQSCREREUyYMIFhw4YRFBQk9u3r60tMTAyenp6oVCrGjBmDm5sbBoOBPn36iNp7oaGhh= IWFoVKpkMvbnBDtLxyOjo707dsXe3t7unTpQkxMDGq1mkGDBuHv709SUhISiQRfX1+SkpLw8fH5= ydD7T+FXMxRfL9EybtUp5IIBubGB6UP9efKhodRoW3j8r5+T1+iEWWoDgg5fZTWfLJ9JgKNdR25= goT3nBVpb9ZSWlFFVVY3FakYiafO6ODk5EhkZSWZmJjKZjNiYGFRqFY2NWopul1DfUI9gFZDL5Y= R0CaGyopJGbSNduoTg7+9LeXkV2dnZOLs4EdE1HIVCTnl5NaUlZej1rUBbzNg/wJ+C/ALMFhNxc= X0wGo3k5eXT0KBFKpEiYKWd12/gwAG/5tR14jdEQUEBf/vb33jppZfEMF4n/rvxyCOPsGjRIpKS= kgB44YUXxDyTfxUGg4H58+fzzDPPiHkd/xewa9cuMjIy7jtXyr59+zh06BDvvvsuAB988AFz586= 9KzT4r2LKlCksXryY+Ph4AF577TWWLVt2X/ruRCd+iPsclvrxHJt/FqGSSCQIgoCtrYauEWF0jQ= i7q40gWElK6tchJOTo6Eh0zN15Gz4+nnf2aauy8vLywNvb486+bYaUn583fn7eHebf1taNtrwb4= c4bw/+dRfH/BxiNRvbs2cORI0ewtbVl5cqV/+kpdeJnYOnSpUyaNEn8/8iRI7+6T5VKRUpKCpMn= T2bbtm2/ur//BpSXl/PCCy/g6enJmTNn7qqI+zUYM2YM69atE3PYFi1adN8MG2irCps4caL4//7= 9++9b353oxA9xnzw3J5FjQm6oYcYDATwxaRjVTS08sXIruY3OWKU2SKw6PFXVbFw+E/87npt2g6= fd4BAEyZ08l38c5XthzbZqKb7f+yc0M9u9Pm37SGnXjxIEAan0h6Kb4h4dxvzBDBEEKxKJ7AfzR= XRBdqITnehEJzrRif8e3J9f53YbQGLhJ6ujftR98z2Hzdmz59ixYxc7d+5m5462z65d+zh9OgOt= tulOhYdAQ0Mj5eUVNDU1t3X9Aw6M9k97dZTZbKayspLKyiqMRhOCAGlpx9m5cxfZ2TlYrW2Jxx3= 35wf9gEQi5dixNHbv3ivyGNxPWCwWPv744w4VR/+IwsJCnnnmGSZPnsz8+fM7bGsnAcvJyeH8+f= OsWbPmvs/xl+Ctt95i8uTJYlVGY2Mjq1atYvLkybz55ps/u5+LFy+ydOnSn93+8OHD96zYuXjxI= gsXLmTy5Ml8/PHHnDx5Emjj9KitraW8vJyPPvroR+nn/xG3bt1i06ZNYjg1JyeHxx9//GfPsx2T= J09mxYoVYtKrwWDg9ddfZ8WKFdTX16PVapk8eTJLliyhtrYWrVbLZ5999ovH+XehQWfmvSOl5Fe= 3YrEK/P1QCZeLW9h7oZa/H7q3dEQnOtGJTtxv/Je4Hr43iE6dPM3WLV/yxefb+eKLts/nW7/knd= Xv8dpf3qS0tAyQsmPHV7zwwoscPvzThGEAdXX1vPXW33j11dfIz28r4zx8+DBffLGN69ezf8b82= jxKhw6lsu3Lrygvr7jvPDc7duxg5cqVVFZW/mgbPz8/kaHyH0MtKpWK0aNHI5FImD59+r9NP+TH= sHDhQoKDg3nooYeAtlLpyZMnk5SUxKOPPvqz+qirq2PBggUcPnz4Z4/75Zdf8sknn3TQKmpsbGT= v3r1MnjxZLHXs06cPL7zwAp999hmtra14eHgwbdq0n+2CDw4OZuLEiaL3rra29hdpNV29epW+ff= syatQolixZgpOTE9DGg6HX61myZAmOjo4sXryYtWvXolAo2LFjByqViry8vP+cXss/wbZz1by2r= 4j6FjMyqYS5A7ypaTbx3PZ8zuRr/9PT60QnOvH/CX7bUvCfibaQUZugpVQqRUJb3byNjQoBMBlN= tLbqycvLZ9u27SxcuKCtVBvJHYLANrQH2O5td0hA+OG2tnLvNgbMe4XC7u5Eeqcs/Ody9/wcmEw= mCgsLCQ8PZ/jw4eL3V69eRSKR4OPjI/JtyOVy7O3tUalUd3E2tFcqBAQE8NZbb7F161YKCgrQ6/= WEhoYiCAK3b99GEASxWqSwsBCALl26dOA6gLa4fm1tLU5OTvj6+mI0GsnPz8diseDr64uTkxOVl= ZWoVCrKyspQqVQEBweL1VIODg4MHDiQxsZGBgwYwP79+7Gzs8POzg4HBwcMBgPFxcXo9XpcXV1F= zpR2tJfMLlmyhL/97W9AmwFRWVmJRCIhLCxM5IJox+XLl5kwYYIo8xASEgK0lXAWFhYSExNDSkq= KyAT8+uuv8/HHHwNteTrNzc1oNBqxtBQgNDQUtVpNTU2NSBkfFRWFXq9Hp9Nha2uLXq9HqVRiNB= qprq7G3d2dyspK1Go1xcXF2NjYiNUd0CYWuWbNGubMmUNcXJzIbbJgwQIWL17M6NGjgbZn4dVXX= 8XJyYnevXsTGRmJSqVi0aJFrF+/npKSErEEu6rJRE2TEXu1HEGAJr0ZL0clggCVWiMAMqkEL0cl= pfUGbFUyAlzV3ChrEc9foJuakjoDEsDfVUVlowkBCHH/npCsrMFIfYsJG6WMEHc1BpOVojoDRrM= VX2cVY2JcSb/ZJqQpCFDXYiKhiwNzB3iRdbuJW5WtWAWBIDc1Jsv/Y++846Mq0/59nZlJL6SQQg= hJIIU2CSGhBem9iLCAgIj6CoooIE0UOyBiBBTFhktZEJAmvUMIhBQCAUICARICBNJ7L5Mpz++PS= Qbz4q7uyu76+juXn+DMmXOecur33M/93Lcgu0SDJEk42qhQSpBbbmyrn5sVFqqm714ZRXVUa/RY= minwbm6JEHC/uA69QWBjocTOUklWycOI2i525rjaP5w5llmioaJWRzMrFS0dLajXG8goqkOnF7R= wsMDJ5g9xO5SRkXkM/Eev5obIM7/4m9Gh2PjZIAx07RrCuPFjMRgM5ObksX37TjIzM7mTfpesrG= xCQ0NxcXHD398PkKiv15H54AFlZWVNarC1tcHd3Y3hw4ai0+mxt2/GrVupVFVWAxLZWblcunQJP= z9fDAbR8MB/6Gtjb2+Pt5cXFpYWpnY2xr/5veh0Og4dOkRUVBQGg8EkNo4cOcLmzZuxsbGhbdu2= zJo1q0ko718iOjqatWvXmmJhpKWlsWHDBmJiYli0aBEpKSls3ryZQYMG8Ze//IXz58+TlZVFXl4= efn5+TWal3Llzhy+//JLq6mpKSkrYtm0bJ06cICIiAo1Gg06nY968ebzxxhu0adMGS0tLbt68yf= r1603TWxtZsGABb7/9NsuXL2fmzJnGvdqQQuHw4cNotVoyMzNZuXIlfn5+gFHwrV271hQsDIxxZ= zZt2sSDBw948OAB06dPZ+TIkU3qSktLM+Vw2rNnD1OmTMHKyopTp06RlJREfX09CoWCb7/9lnnz= 5pmiq2o0Gnbs2MG5c+f45ptv2Lp1K6dOnaK0tJT58+fTs2dP1qxZQ35+PqdOnWL37t1ERESYwsu= fPXuW48ePYzAYuH//Pu+//z7Lli3D0dERW1tbMjMzCQ8Pp127doBRbDXGqoiMjKR9+/YMGzaM3N= xc/Pz8WLx4MW3btmXRokW4uLiwc+dOzp07Z4r86+HhYcon0yhuEu9XMe/HdMZ1dcHRWsXG6DxWT= WyD3gAbzuVSXa+ntt7A6md8eWv3XTp72fLxuNbM234HDwdzLt6tZNdrHVh7JoekrGq+fc6fz05k= EdzKhrlDjHWk5taw/MgDzJUKbuZWs+u1jpy5WcrpG2WU1+qwt1SxfHxr0/E4dLWYz05kEv50g8j= Mr+XzE1ncKajlpb4tiE4r53hyCcOCnBjVyZn9V4qwMFNwO7+GAe0cmT/M01TWtaxqVh3PxMnGjH= tFtbzQ0538inq+jsimp38z+rRtxu38WpIzq6mt15NRVMcXk/0YFmiMTnz1QRUrjmVia6GkqErLy= om+xN4uJyKllJwyDUGetnz+jO8/vMZkZGT+7/AHfVUR2Nja4OHRAiEELVq4k37nDvfu3qO6ppai= omJu3rzJuagYRo8eha9fG44dPcHp05FUVFSY/HeUSiX+/n6Mf3osR48epbZOg6WVBadPR5Kbmwd= IxMbGERsby5y5s9HrDaz97nvTzC1JAgcHR/4ydgx9+/aiaX6r309RURHnz59nxowZ+Pr6MmnSJC= orK1m1ahXm5uaoVCrS09OZOHHir4obW1vbJiG/nZycmD9/PqGhoezcuZP+/fvTqlUrFi1aREVFB= YmJiWzfvp2SkhLGjx/P3bt3TZaO3bt307lzZ5555hkuXryImZkZ69atY/fu3SiVSmbPns3Fixex= s7PD29ubRYsW8eyzzzYJkPVz1q5dy2uvvca+ffuwtbVFr9cTERHBjBkz8Pf3Z/Xq1Rw4cIAFCxY= ARgtMYx6o7du3k5KSwvXr19m+fTseHh7k5OSwe/fuJuKmvLycc+fOsXnzZrRaLYWFhaboodOmTa= O0tJQXXnjBFOn05ygUCmxtbU2WlSeeeAInJydWr15NcnIy9vb2KBQKvv76ay5duoS9vT22tramR= Ix79uxhyZIleHh4sGDBAqKiorC1tcXZ2ZkVK1YwZ84csrOzTeKmpKQEe3t7li1bRmVlJW+88QZO= Tk706NGDadOmUVZWxurVqykuLsbDwwMfHx8OHDjAl19+ycaNGwFjSoi0tDRTH4aqHRmsdkQhQd+= 2zTh+rQR7KxVVdXrmDvGkWqMn/MgD2rWwpmtrexpSrzFU7cT0fi2YtjEVjV7w6gAP5m2/gyRBi2= bmJmEDsP1CAZ6OFrw3ypuLdyuwUEl8fzYXnV5gppQ4klTMqwM8TOs726pQKR6+BNhZqlj6Fx8OJ= BZx+Goxvq5W+LpasvQvPly6V0lOmYb9r6vJKtUw6dsbPBXijJ+r0aK49kwOfQIcmNbHnZ8uFbIp= No/nwtxwtTfn9cEtUbe0YcyaFJ4Nc6VKo+fH+AKTsAH4W0we59MrCPS0IeFeJXG3y9kal8+KCW1= oZqUi82cWHxkZmf/7PBZxIwmpwSzzS9aMf14M/G/9oFAocHVxBUmBtl5LWWk5tTW1VFRWoKmvJ/= XWLQ4cOEBFRZUptHpFRQVpaanU1tWh1xuoqqqmpqYGCwsLevToQX5eAWVlFfj7B+Dr1xp3d3f0e= oMpEJSkkLidZsyie/z4CcLCuj3Srt9LY9C2xnDV7u7u1NfXm6I1Nvb914QNYArc1YibmxtOTk54= eHjQrFkz09CQtbW1KRsrGEWQm5ubKSQ3GId/WrRogaWlpSm7bmZmpilPT4cOHUxDQ6GhoSgUClM= +pF+iefPmLFiwgLlz59KrVy/AGIiwMbx5cHAwZ86cMa1fUlJiys/SOFyl0WgYNmwYs2fPxsrKqk= mgOjBGAJ0yZQoBAQHU1NTw4YcfkpSU9Eho9DZt2pisHY2YmZnh6+vbJOFlcXExo0aNQqlUUlZWR= m1tLWZmZoSFhQFw9+5dioqKAMjOzjZZmLp27UpeXh6+vr506NABeBjSvJHGkOuNYfQbhxorKyvx= 8PDAYDCYAu+pVCqT2Proo4+atPt/Oz8/092Vt3bdZZjaCWdbM7bHF+Bqb8bbTxoF53t77hGXXoH= OILhbUMuP8YX4ulpiZ6mkk5ctJ66VYGWuwNnWjKwSDXVaQ5PyS6t12FopsTJX0Led0UfI1lLJ7E= EtCfM1Bnqs1jwMWd+tjT02Fg9TTbg7mONiZ4aTjRm2Fkp6+tlzLasKR2sVGcV1aHTGC8zT0QJLM= wWl1Q/3WWGlltqG9ng4WFBXb6CHnz3bzudjZWasY9k4H3p9fBUQXF4c2qTt5bU6poS5smCYMSu0= lbmCb05nozdAaxdLWrv8ci4gGRmZ/5s8lqzgCqFEISQQSh5GkWmsQCAkgUHRkB+8USAIA6A35oA= yLmgorXGqt/G7EMbflUrFw6ndDf81rvMgM4vaWmNI+kVvv8mitxcw/um/oNPpkRpmTCEpQJKwtb= Vh2LDBuLq6AIKQkE48//xk1Xf7ngAAIABJREFUvL1b4enpQZ++TxDaJZjQ0GD69uuNjY011VXGd= A7SY576bWdnR0FBAQcPHiQxMZFTp04RGxtL165dmTVrFvfu3WPfvn0mJ+Pa2lru379PaWkpiYmJ= JCYmcujQIdatW0d+fj4FBQUUFRWZxFBiYiI//fQTo0aNIj09nbKyMsrKyujataspU3FiYiKSJBE= SEmJq1/Dhw/nmm29ITExkx44dZGRk8MQTT/DDDz+QmJhISkoKffr0oaCggPv375OZmUlZWRkFBQ= VNhpHu3r1rSnLZvXt3Jk6c2BCNWoG3tzd79uwhMTGRy5cvM2bMGFP93t7epKamsn//fs6cOcOdO= 3dITEzk5s2bXL58mZs3b5oyGIMxjUVMTAxVVVXY29vj5uZmStdw7do17t27R35+Punp6eTl5VFY= WGgKA67X60lLSzMtKygoIDk5maeeegqtVktubi6enp5kZmZy+PBh0z4pKCggLy+P0tJSgoKC2Ll= zJ4mJiVy5coX+/ftTWFhIRkYG+fn5FBUVUVBQYBJ//v7+1NbWcvbsWY4ePYqFhQXPPvssKSkpHD= 16lJiYGFq1aoW9vb3pOMfExDSJAVNXV2eKnNpID197qjV6jl0r4dkerqRkV6NQSKga/nq3bcaWu= Hz6BDSjmZWKs7dKGRNijP7ZrY0d+68UoTcIxndxYWN0Hn3bNkNnEGQU1ZFTVs8QtRORN8o4fq2E= 9VG5HL5aTOvmlkSklJJRVMdbu+9y9UE1pdU67hdruFdUR0WdnsIKLU42Kuq1Bq4+qCI6rZzBakf= uFNRRWaunuEpLnwAHHhTXseFcHsevldC2hTUh3rbczq+ltFrHwA4ObI/P5+qDKi7dq2R0SHPuFt= RRXquntNo4A/LTo5lsfaUdZxcFU1lnLPdeYR355fUM6uDI4aQSYtMr2BKXz7HkEjp52fLTpUKuP= qhi7o/pj+uylpGR+QPwGNIv1LOzIf2CZKglsE0zunVoQ3W9luOx1ymtM8egUGIArJX1jO2txtbK= HKSGzOFIYJCMukdAfEICD+4/oG2Af0M4fmO8mcQrV7l6NbkhBHp3CgryuXv3Hu3btUejqeXGzVt= 4e3kyctQIlAoFeXm5nIs6h5ubG4FBgZw/H4+2XkuvXj1p3tyFs1FRFBWVEBikpl27ACRJ4nTEGd= av30hERATR0dFcuZxIbW0ddnZ2DB4ykOjoWMpKSwkL64GHh8ev7Jlfx9raGj8/Py5fvszVq1cZN= 24c48eP58UXXyQmJobk5GQCAgLo1KkTSqWSwsJCoqKisLKyIjk5meTkZDIyMhg/fjx37twhNzcX= Z2dnBg0ahFar5fjx44SFhTFkyBB27tyJvb09bdq0wcPDg759+3Lw4EGSk5P57LPPmswSat26NRY= WFpw8eRKAQYMG0b17d6Kiorh06RJz5szB0tLS5Mei1WrRaDQ4ODgQEBCAhYUFiYmJnD9/nuLiYv= r16wcYEyO6uLjg5eVFu3btuHnzJjExMQwYMMBkEQFj1mNnZ2eioqLw9vamd+/eLFy4kFatWnH69= GlSU1MZNmwYrq6uACQlJXHu3DmcnZ0JCAhAq9WSkpKCTqejsrKS7Oxs6urqKC4uxtzcnPz8fOzs= 7MjKyqJly5bk5+djY2NDaWkpDg4OBAUFcfbsWSwsLNDpdKbUDpGRkSQnJzNy5Eju3LlDeXk53t7= eDB48mMuXLxMfH8+zzz6Lo6MjN2/epKysDEdHR/Lz83FwcKBt27amBIeOjo6cPn2arKwslixZgr= 29PV27dmX37t0YDAYmTZqEhYUFX331lSlPzqhRo0wpC06cOEH//v1N+6AReysVPs0tGRXsTGmNj= l7+zWjlZDy2LZqZU1ajY0xIc9wdzHGwVtHZyyiEfV2seFCsYXBHJwLcrdBoDTzTw416nYET10sp= q9YxspMzKqXEhbuV1GoNTO/rQaiPHXcK64i/U0mIty0eDuYUV+mo1xkoqtRirlTgYK3i6a4uFFV= pib1dQYi3LU8GO7P3chGeTha42ZvTqZUNwV52xNwuJ7esnkUjvVAqJfZcKsLWUsmoYGcMAs7eKs= fFzoznn3Dj0NVi7CxVtHAwx8fFkiNJxRRW6LiWVc21rGoyijXkltdTpzMwKtgZO0slF+5UYqaSe= K6nGz187bmcUUni/WrC/Ozp2PK3J+CUkZH5Y/NYgviNXRmHknoU9SVMHtSKWeMGUlRZzZxPd3K3= rBkoVAi0OFmWsfndSXg2BPFTocdkpJEEBoOCr774jqjos4wcOZyp06ai0+nIy81n7fd/JS01DWd= nJ2a/PpPIyEhOnz7DhAkTsLKyYMeOnbRs2ZIlSz7Ezs6OxMREli75mKCgICY/+wyfffYFNdXVvL= XoDdq3b8+HHy4hLfUOkydPZMxfRqHV6nj/vcU8eJBJ7969aN3Gm4rySo4cOYa9vT0rVy1n+ccru= HP3DvPnz6FLl9B/vGNkZP4NGAwG9uzZQ1FREdOmTTNl1P0qIpvIm2W/svWfm7S8GgLcrf/u919j= 3+yO/45mycjI/Bd4LD43BkmgaJyG3TDTSAIU6FAJDfoGGSMJHWBAL0AlDCAkhKTAIOkADRJmKIQ= ehaTk/PkEbt++g15voLy8gvLyckCihYc7LVs+tJpISLi6umCmMiMnJ5fNm3+gY4eOZNzPRKFQ0R= jVGBqGs4Txk0KSEMJASsoNXN1c8PbyQqOpb/CDcMLV1RWV0rxhanPjENljdrqRkfknKS4uJj4+n= vDw8CZ+R9P7tuDF3u7/xZb99xmzJoUjSUZfsv7tHbjwQcivbCEjI/Nn5THNljIKGiFAGB5aYySD= HoWoR4sKAwo0OjMyi6txsrLATNUwFGVQYpAUGCQzzFCib3DNqagop6yszBQpWKlU0dzFmdGjn8L= BwQFJklA0RCsODAwkJDSUhIRLnD1zjtMRZ5EkhSkOihCGBl8e4/oqlYqQ0BBSb93m6tWrXLqSwM= IF81GrO3Dq1Gl++mkPkkKAMDrK2tgaZ2xICmGMrNOQwuFxB/KTkfk1XFxcTHF/fo6FmYLHlwHo/= yYRC4P+202QkZH5g/DYE2dKkoQCMFNIuDe3oF4pqNLpqK6uQ1tXxVdbTtI/qA1hwQEEeDtjqdCh= QAkoMQjo2LEDFpaWKBVGjxyjlUWBc3NnOgUF0rqND0IIOnRoj4SCNr6tsbOz48UXXyAoSE1mZhb= CIMgvKOTypcsYhAErK0t69XoCTX09jk4OCGGgb98+GHRQWFyIwaDF1c2Fdu3b4+jkSFFRIUgNua= wMYG9vi0KhIDS0M15enjg7O8viRkZGRkZG5g/K7/a5uZlVzriV51AILVJ9MaN6evD6pKHYKhXkF= xRSrTVQqhHkFJZSXFHBnfs5FOSVIukNdA30YmTvzrR2a44CPQaDQKf7peEfCTMzlSn6rRACrVaL= Xm9ApVIiSRJZWTloNPXodXokSeLChYscOHCQ0NAQZs1+FStLCwyAZKbCHANICnR6YyA9gQGluTk= qSYlep0VvMDxM7CkASUJpZoZeV48wCFQqMxQKBUrlHyR7hYyMjIyMjIyJ3225kQz1WNVmoJQUqC= Qt8ReSyLqbjpONNQ72dni2bIG3pxv+LZvRO8QPK/Pu1Gq03M/KJ/7iZb7dvIe+YaEM7N4ZKzMVK= pUChYJ/aBWRJMnkSAlQUVHFF6u/5N69DBQNU74RAoVSgVqtxs7+YdAyvTAgGcCgVKJHwkyhQEJP= TlklDva2aA16zCQF5uYKzFAhCQMGFIAeMzOJyho9OrRYW8hxMWRkZGRkZP6I/G7LTXW9luTsAsx= QYI4C0FGvrafeYHT21Wvrqa2upq62GoVSgUKpwtbWGlsrcxwdnanVGki9excleoL9/Wjh5ISywR= rzW6mtrWXnjl0UFBaZEhlKksDPz5/BgwdhbWWJAeOMc4VBT2ZJGUdjrxDUwRcvB3tsrGxYt/8kD= g6umJtBW68WuDlYY2lmTr3OOM3Z08UZrUFPfPIN/Fq1xLtFC8xVyn/cMBkZGRkZGZn/OL9b3AgE= BhqC5SHRGMJPNMQHlAQYI9qAXgh0Bj21dbVUVNeg1wNCYGNnjdDrqCwtwcG2GQ4OzVCpVCah8qt= tEAKdTofBYDCJIklSYGamahjiEhgkAwahAGEg4nIqMZdvMXZYd8oKCimuqiM1rxjnZo7o6jV4t3= DCzdGW23dzUFqZYa5S4mBpTnFpMUpzG/qGqHGwscbsMQf1k5GRkZGRkfn9/P5hKUASxnTbBkAyx= iRGgR6EoiElg9H5ViVJqJQqLG3scLSxQysZ0As9Cj2Yo8LdzoE6XT0GYczh9FuddiVJeiQc/89+= NE7/FkqQ4EFhOWnZBfi0csJMaCitqeFBYQVo66mvq6S+Tk9FWSktXR0prtJQVVyBUqHH0cGB4oJ= iQto5YWVhdHiWkZGRkZGR+ePxu8WNQMIgmaEQDbaaBjFiQDJ+NImTxjQLEpKQkBCYG0BIEigkoz= gSxrw7CMPPklc+jhlJEgphnKqek1eKUlIQqvbGztwMn1aeuLsaUOh1WDezQKcDGzMVrT1ckXQCp= ZkSbb2GeoMSywBvPBxssTRTmgSdjIyMjIyMzB+Lx2K5UYmGjFKSAVA2WG8UCAEShsYwOE1oyLiA= hNEBWA8mp1+DaBxaejziQZIMGAfKlPi3cqOwqARRY8DcypJgX2cUCAzC6KfTWLcSQYi/NwKDsY3= GCDdIkjEQYMNMcRkZGRkZGZk/GL/b50ZGRkZGRkZG5o+E7DgiIyMjIyMj86dCFjcyMjIyMjIyfy= oec/oFmd9KZGTkf7sJMjIyMjIyf3h69erVJHDvb0EWN/8lYmNj/9tNkJGRkZGR+cPTrVu3f1rcy= A7FMjIyMjIyMn8qZJ8bGRkZGRkZmT8VsriRkZGRkZGR+VMhixsZGRkZGRmZPxWyuJGRkZGRkZH5= UyGLGxkZGRkZGZk/FbK4kZGRkZGRkflTIYsbGRkZGRkZmT8VsriRkZGRkZGR+VMhixsZGRkZGRm= ZPxWyuJGRkZGRkZH5U/HYcksJIaivrwdAkgCkpr//bMnP8z00Xevvlg5ICNOWkunfpkseLR8EUp= NtQfqNtf4+GuqTJMxUZiD9p+qVkZGRkZH5/5vHIm50Oi37D+wnOy8XKxsr+IV0VZJoeLSLnwkS6= WfyRIBB8StprgSYZMzPlJIESD8r1yA1/Cz9UnkSkmj4SQIDP2/PL1b4aD9+tu3DUnnYP0kY/4RE= VXklw4cOp0OHDv+4bzIyMjIyMjKPhccibiorK7lw4TxBoSFYWlsixMPHvoRR6wgUCAGSQkIhSUb= 9I4Ew6JEkMBgEikbdIj0qK0y2GiEhhASSwIBAq9MhIWGmUjVsKFDAQ0tNg8AxaSEBkqRAIKHT6d= Dr9aiUZihVShBGqSMhISTR1N7TKKwkYz8MBj16IRDCgEqpQqGQEEIgSRIKhOlzdlY2CQkJ/1Dc1= NXVUVNT02SZvb09KtX/P0nbG/tvZWXVIHr/ONTX11NdXY2dnd2vHpPq6mp0Oh22trYolcr/UAt/= O1VVVQghsLGxQaH4749KCyGorq6mvr4eSZKwt7dHCPGHOPc1Gg3V1dUAODk5UVdXh6Wl5X+5Vb9= OTU0N1tbW/9K2Op2OiooKrK2t/2N9NRgMlJWVYWVlhZWVFUIIamtrTfv7X+1L43ULD+8rFhYWj7= Pp/xZ0Oh3V1dVYWFg0OQaN/bGysjItr6ioQKfTYWNj86t9Ky0t5ed5sv/szxjl4sWLF//eQurqa= rmYcAmPli1RqhRISEhSwx8SkqSgvraOnMwsbqbc4ErCFZISE0m7mUp+bh71mnoszS2wtLZ8uN3/= +kMyWn6EAfLycok9F8OZiEhio6K5eD6eG9dTKC0qxs7WruHGrURSNN0eJKqrq0m5lsLpkxGcizx= LzLkYkhITuZt+BwkJh2YOmJmZG3XM/24HErlZOcRERRMZEUF0VDSXzl/g5vUUSouLsbe1w9bGFk= mhQEigVCgoKynFxtqOzp2D/+7+O3LkCCNGjCA6OpqTJ0/yzjvvMGjQIFq0aNFkPZ1OR25uLhYWF= v+WkzI3N5fU1FRcXV0fefDpdDoKCgpQqVSPpe7KykrKysqwtbVFq9WyZMkSsrOz6dix42PtW0pK= Cq6urr9pXY1Gw9GjR3Fzc2tyU4mLi+OFF14gODiYli1b/sMyvv32W959912GDh1Ks2bN/u56GRk= Z3LlzBw8Pj9/WkcfEBx98wMaNG+nduzdRUVGP9PX3kp6eTlZWFs2bN/9V8aTX6zl48CDfffcdO3= fu5MSJE5SVlaHVamnVqtW/VH9xcTEajQYhBBEREXh4eGBubv5PlxMXF8e6devYtGkThw4dQqFQE= BMTQ9euXf+ldv2nyMjIIDw8nKFDhwLGczojIwMnJydKS0upqan5xReIEydO4OLiwr179+jUqRMB= AQF07NjxH9aVm5uLQqFAo9EQFxeHu7s7ZmZm/3Sby8vLGTNmDFlZWfTo0QODwcB3333Hu+++i42= NDZ06dfqny0xPT2f9+vWsW7eOY8eOkZqayt27dwkKCvqvv3SUlpaSnJyMs7PzL+6vW7duMW7cOF= xdXZu8FF+5coUZM2aQmZlJr169UCgUvP322yxZsgQ/Pz/atGnzD18MJ02axAcffEBiYiIbN24kJ= yeH4ODg33T9l5eXc+zYMVq3bv2b7886nY4HDx7g4ODAyZMnsbKyws7O7jdt+zh47E/In49INdpv= 7qTd5syp09y6eYvS0jKT8tTpdNTUGBVq6zat6d2vN8GhnbGwtDRaPhq2l4Txk0IouHAhnuNHj+H= QzIGwsDC8vb3R6/VkZGQQFxfHhbh4ho8aSefQzkgKUDQcbEmC4uIS9v+0jwf3HtClSxe6hnTB2d= mZoqIiUlJS+PGHbXQM7MiTo57EwdnBZO4xGpkUXIyP5/jhYzg7NyckJARvb28MBgP3M+4Tdz6O+= JjzPPnUKDqFdkZSSRgAgzAg/eLw2ENGjx5NeHg433//PUIIvvjiC3x9fR9Z7+7duyQkJDB69Oh/= yxuIRqOhrKysibpvJCcnhxMnTjB58uTfXY8QgosXL6LX6xkyZAiSJDFgwAAGDx78u8v+ORkZGRw= 4cOBXb9KN6PV68vPz0Wq1TZa3atWK8ePH06ZNm18to1OnTtTV1f3qw7mmpoby8vLf1K7HSUhICG= 5ubjg6OpKXl/dIX38v1dXVVFVV/aZ1jx49ytdff81nn31Gp06dqKqqYvny5QwYMOBfqlur1RIdH= U3Lli1p164dBQUF6HS6f7qcxMREnn/+ecLDw1m+fDkAL730ElOmTPmX2vWfoqKigq1btzYRc0eP= HsXS0hIfHx/OnTuHi4sLYWFhj2xbWFhoEpWBgYGMHDnyH9ZVWVlJREQEffv2xc7OjuLiYvR6/b/= UbgcHB8LDw/nss88oLS3Fw8ODfv36ERQURP/+/f/p8oqLi1m5ciU+Pj5s27YNgE2bNtGiRYs/hK= VCq9VSWlr6d/eXk5MTPXr0oFevXk2Wd+3alenTp3P27Fny8vLw9PTk5ZdfpmfPniYx+4+YP38+h= w4dYtWqVWRnZzNlyhTc3d15+eWXf1Ob8/LyMBgMv7puI7du3SI+Pp6XXnqJoqIi6urqfvO2j4PH= bJd+qBqFEKiUZlxOuMLar7/jXFQ07dq154svvuDAgQMcP36co0ePsnHj3xg9egypt9L4/pu/snP= bTmqqah6WJAAhoZRUJCcns33rjwwZPITNmzfz/vvv4+3tTdu2bfnwww/Zvn07ffv0Zee27dy6cQ= Ol8mH36mo1bPzrBgrzClm1ciVffvkl8+bNY8SIEcyePZvvvvuO1atX8+DeA3bv2m26KRpFlkTC+= Qts+dsWBg8eyoYNG/joo4947bXXmDlzJss+XsauXbvo17c/27dt5+b1GyhQ/mb34fPnzzNo0CDK= y8tJSkri/fffx9LSkldffRW1Wk14eDgxMTEMGzaMHTt2UF1dTXl5OX379uWFF1545GYVFRVFSEg= Iy5YtY/78+eTn51NUVMSYMWNQq9Xs3LmT4OBg1qxZQ3FxMb179yY9PZ0NGzYQERGBwWBgypQpqN= VqVq5cybFjxxgwYAD79++npKQEALVazfjx43nmmWd+8QE5YMAA1Go1CQkJCCFQq9Wo1WpOnDjB9= OnT+Z//+R/i4+Opr6/nyJEjzJ49mylTprB27dom5ezfv58uXbqwdOlSevTowaZNm4z7ul8/vvvu= O5555hkAIiMj6d69O2q1mtzcXE6dOsWoUaNYs2YNAMePH6dbt26o1WrTPurXr5+pXcuXL+eHH37= gm2++MV3As2bNQq1Wc/LkSQwGA05OTnzyySeEhYXxzDPPsGvXrkeE4Pfff8+NGzcYMWIE6enpAN= y8eZNhw4Yxd+5cQkJCOHv2LPPmzQOMJvkNGzagVqt/8eFZWVnJuHHj2LlzJwDh4eGsW7eOgQMHc= uzYMbZv386ECRO4ffs2AIsWLWLAgAGMHz+es2fPPlLe6dOnGTx4MFu2bDH1NSMjg4kTJ6JWq4mN= jQVgx44ddOrUiaeeeoro6GjGjh3LkiVLSExMpGfPnly9ehWA119/HbVazbFjxzAYDMydO5fr16+= jVCrRarWo1WomT57M008//UhbZs2axaxZs0xv5jY2Nrz99tscPnyY4OBgzp07x5w5c8jMzCQqKg= q1Ws3TTz9NWloaANu2bUOtVjNt2jTWrVvH1KlTmTVrFomJiSxevJiNGzeydOlSxo0bR1VVFQcPH= jSJla1bt6JWq3n11VcpKCho0q6VK1fy0ksvMX78eNOyzz//nB49epCens7o0aNRq9Vs2bKFK1eu= MHToUJYtW8aXX37JwoULuXDhAsHBwfz000+8+eabDBw4kLS0NIYMGcKFCxcYN26c6fifP3+evn3= 70rVrV86cOUNcXBy9e/dm27Zt/PDDD4wZM4bCwkK++OIL1Go1U6dO/bui+NKlS5SWltK2bVvq6u= pYsWIFM2bMIDIykjfffJPXXnuN3bt3ExoayrRp01i2bBnnzp0jPDyc3bt3U19fT3R0NO3ataN79= +589dVXAIwYMYI333wTgFWrVnH58mVGjBjBW2+9RX5+Pm+++SaHDh1CCEFcXBxqtZohQ4YQHx9P= bGwsnTt3ZteuXXzyyScMGjTokXZrNBpqa2vx8/MjJycHvV5PZWUlLi4uKJVK0zV68OBBwHjvWbx= 4Mfv27aNLly7cuHGjSXlnzpyhurqa6dOnY2ZmhpmZGZMnT2bQoEFIksS8efNQq9WsXr0ag8HAnD= lzmDp1Khs3biQwMJD4+Hjmz5/P119/zYYNGxgwYAAbN27kySef5NixY2zevJkZM2aYBOFrr72GW= q1mz549rF27lqFDh7JmzRrmzZuHwWBgx44dqNVq3njjDXQ6HXv27GHHjh1oNBpqampYuHAhvXv3= Ztq0aZw5c4bU1FT8/Pywt7d/ZF8VFxfTqVMn7t+/D8DFixfp0aMHV65coWvXrvTq1YuTJ0/+4vm= xYcMG/vKXvwDQsmVLhgwZQlRUFADHjh1DrVYzevRodu3axdChQ/noo49YvXo1x44dY/ny5axdu5= ZPPvmEZ599lpycHA4ePEjjwE9sbCxqtdrU97lz5/Lkk08SERHB7t27+frrr9m7dy/9+vUjOjqal= JQUBg4cCEB0dDQ9e/akd+/eXLt2jf3795v60ng/+ld4TOJGevh/YRQECoWCa0nJfPfVN2CAr776= iuPHjzNt2jTCwsLo0KEDwcHBjB07lrVr13Lw4EH8fH2JOBnBgb0HqNdoG6xAxiGhktJivv36O4Y= NG8b777+Pj48PBoOBpUuXsmbNGjQaDT4+PnzwwQf069OXLZs2U1tVbRpOOrz/IOmp6Sxbtoyhw4= ZhZ2dHXl4eS5cuJTk5GVtbW0aMGMEnn3xCelo6MTExKBQKFJJEbnY2679fx6hRT/HRR0vx8PDg9= OnTzJ49m3feeYf4+Hjc3d1ZvGQxA/oP4Kedu9HX1xsdl4Ffckz+OadPn+avf/0r48ePR6/X4+Li= glarpbi4mKSkJBYtWkSXLl2YPn06y5Yto6ysjMDAQDZs2MDkyZPp2bNnk/L8/PwYNWoU9+7dIyc= nB41Gw9ixY3n77bd5/fXXcXV15csvvyQ+Ph5zc3MmTZqEr68vfn5+dOzYkby8PGpqakhKSmLhwo= UMHz6c0aNH8+mnn5Kfn0+LFi2IiIjg5ZdfpmPHjk2GH2pqanBycuLLL79k/vz5lJeXs3//fqZNm= 8b169cZOnQoX3zxBZ07d+bdd99lxYoV7N27l5s3b9KiRYtHLB5PPvkk5eXlFBYWEh4ezvXr1wkK= CiIsLIz4+HiEENy5c4fw8HB27drFihUreOutt+jWrRv9+vXj6tWrXLt2jU2bNvHTTz/RqVMnrly= 5wpEjR1i3bh2XL19GqVTyzjvv0LNnT/z9/bGysmL27Nl0796d5ORkTp8+TdeuXXnllVewtrbmxI= kTtG7dGk9PzyZm4Pv373P8+HGmT59Ot27duHr1KqWlpUydOpU1a9YwfPhw2rRpQ5cuXRg6dCheX= l6sXbuW06dPc/36dRwdHdm7d2+T/m/ZsgUvLy8qKiqor69n7dq1JiFy+/ZtUlJSCAsLIz8/n4ED= B9KhQwd+/PFH7OzsaN++fZOy0tLSyMnJQa1WExYWRkBAAAAffvghM2fOJDw8HI1Gw65du7h58yb= R0dH07t0blUpFaGgoYWFhvPfee4wcOZKioiKGDx9Ox44dWb16NQ4ODkiSxNixY2ndujXnz5/H09= OTyMhIxo8fT0hISJO2nDhxgqqqKsaMGfPwLiJJ2NnZMWnSJNM51KxZM06ePMmGDRs4f/48Q4cOp= bi4mEWLFhEfH8+1a9fQ6/UEBgby3nvvMXr0aKZPn86YMWPo2LEjb775JuXl5VRXV9OjRw+6devG= t99+S3JyMieWgGhoAAAgAElEQVRPniQoKMjklwFGIZqamsrcuXObtNfe3p78/Hw++OADPvjgA65= fv85PP/2Ei4sLffv2NR3/8vJy1qxZw+uvv05paSkTJkwgMDCQDz/8kH79+rFgwQJefvllLl68SE= JCAt988w1bt27l6NGjrF69Gnd3d7y9vbG2tubKlSt4e3tTV1fHkSNHOHnyJBs3bvzF4c7bt28TH= x9Pq1atUKlUWFpaMmDAAN58800++ugjXnrpJZ577jnmzp3LvHnzkCSJ2NhYlEolY8aMwcrKCnd3= d/bt24eDgwO7du0iJyeHZcuWMWnSJAoLCyksLCQ+Pp7Q0FDmzJnD4sWL6dq1K+PHjzcd88Z98/b= bb3P06FFcXV3p2rUrd+/excHBgbKyskfa3uhjMnjwYI4dO4ZGo6G+vh5LS0sCAgLYunUrO3bsID= Y2luvXr7Ns2TKKioooKCigS5cu5OTkPHJu9e7dG2dnZ9MyGxsbVCoVo0aNwtfXl7i4OA4cOIBWq= +Wll15CkiQqKytxdXVl27ZtWFtbo9FomDp1Ku3atePevXt4enqyf/9+EhIS8Pb2pqysjHHjxjF0= 6FBWrFiBRqNhwIABeHt7c+XKFcD4crZnzx6OHDmCi4sLKpWKgIAAQkJCUKlUTJw4kdDQUPbs2UN= UVBS9evUiJSUFLy8vrKysmvTrzp07tG7dGgcHB27dukV9fT1CCLKzs/nggw84ffo069ev5+DBg6= aX0Ea0Wi3Xr1/niSeeaLLcw8ODQ4cOERERwaVLlxg+fDiOjo488cQT5ObmkpSUhIWFBQMHDmTw4= MHMnDkTCwsLioqKGDRoEJ06dWL79u188803XL9+nVdeeYWysjKWL19uEna9e/fGxsaGOXPmMHDg= QG7cuEG7du2YMGECsbGx7N27l7179zJlyhQKCgo4duwYu3btIiYm5pH2/jP8GzwKFUgouJd+j+/= WfIOLc3M+XfEpzz//PJIkPfKm2+h426tXL/bt20f/fv05G3mGhPiLqJQqhMLoOHzq1CksLS1ZuH= AhzZo1QwhBeno6ffv2JTg42HSCOzs7M3PWTAxaQXRUDEqlGbk5eUSfjUalUrFlyxYOHDjAzp07e= eaZZ4iPjzcJFEmS6N2nN6NHj+bowaPUVtdiMAjOnY3GycmZ999/H0mS+Pzzz3n22WeJj4/n1KlT= vPDCC6xcuRJra2umvzLdNOyiUBodl/8RZWVlJCQkkJeXx9/+9jcsLS0pKCjA0tKSF198kfPnz6P= T6UwPeA8PD1atWsWePXvw8fEhJSXFdHNtxMrKioiICCZOnMiOHTtYu3Ytbdu25erVq6YbQuvWrb= G3t+fSpUt4e3tTVVVFZmYmPj4+eHt7M2XKFGJiYtDpdBQXF5OTk4O3tzebN2/mxIkTNG/enPv37= 9O+ffsm4mbJkiU899xzXLhwgYKCAtRqNWPGjEGlUpksGfv27ePpp5/m8uXLZGVlsXnzZgoLC00X= /s+Jjo4mKCiIZcuWUVlZiZOTE0qlktTUVBYuXMiOHTtYvXo1CxYswNvbm/Lycpo3b86DBw9o164= ddnZ2vP322wQFBbF161b69OmDm5sbNTU1xMXF8e6775qsP8ePH+fJJ5/k0qVLNGvWjAkTJpCdnY= 2lpSX5+fn4+/sza9YsysvLsbCweMRfZs+ePRw9epTu3btja2uLh4cHL7/8Mp9//jkBAQGcP3+eC= RMmkJGRgbm5OWZmZmzZsoUVK1ZQX19PfX09jo6OTcp87rnnkCSJLl26sGrVKiZNmkReXh7V1dUI= IZg2bRq5ubnExcUxduxYnn/+ebKzs/H19X3EEfPHH39k9OjRgPEBMGLECG7evIm/vz99+vThySe= fpEOHDpw9exY7Ozu+//57lEolnTp14vTp05w7d8607MGDB/j4+PDKK68wePBgwsLCEEIQExODh4= cH69at49y5czg4OJCRkUFw8KM+Zz9/+PycpKQk3N3d+fTTT5k1axZnzpyhW7dubNq0ifLyctO18= NVXX5GdnY2DgwO+vr4m8QPGYYiRI0fi5uaGh4cH6enpxMXFodPpOHPmDB07duSHH37A1taW1q1b= N6nf3t7+F30Xrl+/jlqtJjAwkMLCQmxtbRFCEBsbi0ajYeDAgRQVFfHhhx+yZcsWhg8fTnR0NPn= 5+YSHhxMXF8ecOXOIj49n9uzZxMfH8+STT9KqVStyc3Np0aIF9fX13Lp1i5ycHCZPnoy3tzeOjo= 6sWLGC2NjYJkKskZKSEnbs2EFycjLfffcd7u7uGAwGbt++jZ+fH+bm5qSmphIYGIibmxtbtmwhJ= CSEY8eO8cQTT7B582bTuRAYGEh4eDhCCJo3b878+fPZtm0bzzzzDBEREXTo0AEhBPfv36d79+4A= rFu3ju7duxMdHc17771nchJv1qwZdnZ2bNmyBR8fH/z8/JpYwxrJzc3F2dmZbt26ER8fz4MHD6i= vr+fw4cN88MEHBAcHo9FosLCwwMvLi61bt+Lp6Unfvn1JTEx8xBqkVCqxsbF5pJ6YmBgsLS2ZNW= sWWq3WJBKvXbtGTU0NvXr1IjU1lZ49e+Ls7ExQUBBFRUXEx8fTo0cPCgsLcXNzY8KECVhaWhIZG= YlOp6O0tJTY2Fh69+6NEIKioiIWLlzI8uXL+f777/niiy/w9vbmrbfeQqvVcuPGDVxcXNi4cSO9= evVi0qRJ3Lp1i5EjR1JVVUV2djZ+fn6PtD8hIYEuXboQEhJCRkYGZ8+epXXr1ly4cIHnn38eW1t= bysvLsbe3f8TPbN++fUycONH0vaCggJ9++ong4GBOnDiBm5sb69ato6CggG7dupGamkqXLl3YtG= kTAwYMYNeuXYwfPx4nJydsbGwoKytj+/btuLm5cfXqVZYvX45WqyU7O5ugoCDOnDnDzJkzAaP/W= r9+/TAzM6Ndu3YUFxdz+PBh2rdvz5EjR7C2tmbv3r0ma84bb7zBiRMnHhFo/yyPVdwYp19L1NVq= OHr4GCXFJcydO5ennnoKMzOzh869DRgMhibLWnl58d577+Ht5c3B/QepKCtHQqKqpoqrV64yZvR= o00HX6/UsWLCAAwcOsHv3bj7++GNTOYGBQXTt1o2EC5eoq9OQmpqGSmXGhx9+iE6n45133mH+/P= lkZmYye/ZsFi5ciL+/PwCWlpaMGDGCkuIS7j+4T3VNDbdvpzNp4iQ8PVty/fp1duzYgY+PD5s2b= WLjxo2EhoayatUqLl26ZDKhxsbE/qZhqZiYGJPfibe3N3FxcaSnp7N3717atm1LQkICJSUlREZG= 4uPjQ35+Pubm5oSEhHDkyBFOnz79yIMjKiqKcePG0bt3b8BoMnRxccHW1tYkDM3NzSksLOT48eM= MGDCAsrIyamtradGiBZGRkfTo0cMkUHbs2EH//v25c+cObm5utGvXjiNHjhAZGUlAQECTY3r58m= WaN2+OUqmkZcuWpKSkcPfuXcLCwjhw4AB1dXWsWrWKgQMHcuHCBYYPH45Op2PFihUoFArc3d2b9= GXfvn28/vrrVFRUkJCQwMiRI4mJiWHChAkmIXTx4kXatm1LSkoKGzZsYOrUqVy7dg0HBwcsLS05= f/48FhYW+Pn5odfrcXBwoEOHDuTk5ODv78+iRYsoLy8nKyuLwYMHc+3aNZ544glu3LjBK6+8gpe= XFw8ePCA0NBSlUmky0f/c4bukpISsrCx69uzJhQsXKC4uxmAwkJ+fT5cuXdi+fTsnTpxg2LBhpK= WlYWVlRVFRESqVCk9PT44cOUJ5eTldunRp0v+8vDyqqqrIyclhy5YtzJgxg9u3b2Ntbc2LL75IT= EwMXl5epKen89RTT1FUVMSSJUto1apVE3FTWVlJdHQ0Tk5OZGdnm/qampqKp6cnFRUVfPTRR1RV= VVFYWIheryc4OBitVktKSgpBQUE899xz3LlzB4VCQXFxMYGBgVRWVnLixAkKCgq4dOkSLVu2pLq= 6mtatWxMQEMC+fftISEigbdu2TfrVoUMHampq+PHHH03LLl68SFJSEleuXOGVV17Bz8+P4uJiJE= mirq4OT09PnJyciIiIYMqUKVRUVBAeHo6bmxt2dnZs3bqVHj16kJ+fT05Ojkn0e3l58emnn6JQK= LC0tMTMzIzKykqTs2ZjfK7GY2pnZ8eSJUtMy9LS0jh58iT37t0ziYWXX36Zzp07k5WVRVhYGAsW= LCA5OZmXXnqJ+/fv4+/vj52dHeXl5SxcuJDMzEzatm1Lt27duHXrFgMHDqS8vBwvLy9KS0tZtGg= RQ4YMITk5mX79+jF27FjTsTl9+jRt27alsLCQlJSUJvuxsrKStWvXMn78eHbs2METTzxBmzZtTA= /Jli1bolAoOHToEF27diUtLQ0fHx9eeOEFwOinExUVxciRI0lKSjK9rPzwww/4+vpSVlZGdnY2r= Vq14scff6R79+4UFhZy48YNfH19ycrKoqCggICAAIQQeHp6otFo+OGHHwgMDCQiIsJkrT9//jz9= +vXjfxMdHU3nzp2xs7Nj2LBhvPPOO6YXtw4dOlBdXc3+/fvx9fWloKCA2tpaRo4cycWLF3nppZc= eKS8oKIgjR46QlZUFGB14z5w5w6VLl+jbty8ajYYtW7bQtWtXVCoV169f5/XXXyc2NpaFCxcSGh= qKRqPB39+fLVu2MGvWLKytrQkICGDBggWkpKQQEBDAzZs38fT0RKlU4uzsjMFgYPfu3UydOpWOH= TtSXFxMamoqLVu25PDhw6SmpqLRaCgqKiIkJIRt27Yxc+ZMkpKSWLJkCePHjyc3N5f79++j0+ma= +LdUVlai0+lwdnbGy8sLrVbLtm3b8Pf3p7KyEm9vbxQKBStXrqRTp07Y2tqatq2trSUyMpJJkyY= BcOPGDRYuXEj//v1Rq9VUVlaarncLCwvi4uIIDQ1l6tSpAGRnZwPQo0cPzM3NcXFxYcWKFXh6eq= LT6XBxccHNzY0vv/zStO369euZMGECGo2GpKQkhgwZAhj9q6KiosjOziYwMJDc3FyUSiXt2rXDx= saGpKQkzMzMUCqVHDhw4JFj+08hHgMlJSXi3ffeFTv27BY/HdonPl75iWjh0UL06t1LVFZWCiGE= qKurE9euXRNXrlwR5eXlwmAwCCGEyMrKEpcuXRK5ublCCCFqa2vF0qVLhY2NjZj1+kyx78he8f3= f/ipatvIUG/+20VRnXV2d8PLyEjR45XTp0kUIIUzlLl26VLi6u4lNP/4gJk6ZJLp06SI0Go0oLi= 4WERER4oUXXhAuLi6iffv24p133hG3bt0ylX3//n3h5OQk5r45T3y94VvRxt9XHNi3XxgMBnH27= FmhVqvF4sWLhU6nE3q9XqxevVoolUqxevVqIYQQr776qvBq4y12H9gjPvrkI7Hxbxt+cb/t379f= uLu7ixYtWoiAgADh5+cn+vTpIw4fPiwcHR1FmzZtxHvvvSeqq6vFqFGjRPfu3cX+/ftFSEiI6NC= hg5g2bZoICwsTH3/8cZNyu3XrJtLS0kzfN2/eLLy9vUXPnj3F3r17hVarFfn5+WLRokUiOTlZGA= wGERkZKRwdHcXixYuFj4+P8PX1FfPnzxcajUb07NlThISEiJ07d4ohQ4aIgIAAMXv2bBEWFibCw= 8OFXq831fX999+LNm3aiLCwMLF7927x+eefi1atWolOnTqJzZs3ixs3bghJksTkyZPF+vXrRVBQ= kFCr1eL9998XTk5O4tq1a6ayHjx4INq3by/atGkjBg8eLKKiooROpxMBAQEiMzPTtN769etF69a= tRb9+/URCQoKorq4Wc+bMER4eHiInJ0e8+uqrwtfXV0ycOFHcunVLFBQUiDFjxohu3bqJsrIyIY= QQSUlJolu3bmLRokViz549wtPTU8ycOVNMmTJFhIWFiffee0/4+/uLgIAAsXTpUhESEiJSUlJMb= dBqteLFF18UAQEBYsyYMaKgoEDU1tYKGxsbERgYKGbMmCHatWsnFi9eLFatWiViYmJEXV2dmDJl= iggICBDTpk0T6enpj5wjmzdvFg4ODuK1114Tnp6eokuXLuLrr78WkZGRQgghRowYIZ566ikxadI= kERAQILp37y5mzJgh+vfvL0pKSkzlJCQkCBcXF7F+/Xpx5coV0b17d/HWW2+Jy5cvi3bt2onu3b= uLlJQUUVpaKmbNmiXatGkj+vTpI+7fvy9Wr14tDh06JIQQIjw8XISGhor9+/cLV1dXERYWJvb8v= /beOzqqcu3fv6ZlMi29k4SWhIQaOlJCkCJFhKOIHAXEgoJiQQUUeQUB9auIiiIqICKKKKEIBAQT= wNBbQgstCYSQkIT0ZDKZvp/fHwOjCFjOQd/zO+9ca81aSXaeMnvvNfue576fz2ftWmG1WsXkyZN= Fp06dREpKiujRo4eIj48XTz/9tOjcubP48MMPb3hvJ0+eFDExMSIuLk7ExcWJGTNmiBMnToiXX3= 5ZXL58WQghhNVqdV+/rl27iuzsbPHZZ5+JhIQE0bVrV/Hss8+K4OBgsW3bNqFSqcTzzz8v1q1bJ= 8LCwsTChQuFEEK88cYbYtmyZe77ftiwYSI2NlYMHDhQlJSUXHf/CiFESUmJSEhIcM9r7Nixory8= XBw8eFB07dpVxMXFiW+++UaYTCbxxhtviPT0dGG328XQoUOF1WoV06ZNExEREeKzzz4T77zzjqi= pqREPPvigOHLkiNi1a5eIiYkRb731lvj+++/d93dGRoaorq4WL730kjh9+rSor68Xjz76qEhOTh= aNGjUSsbGxYsSIEeLSpUvueZ49e1YMHTpUGAwGYTabxdtvvy0MBoNo3ry5OHTokOjWrZsYM2aMy= M3NFVqtVkyaNEmMHz/efS2FEGLfvn1Cr9eLuXPnitTUVNGlSxcRFxcn0tLShMViEevWrRM6nU70= 7dtXDBs2THTu3FmsXbtW+Pj4iE8++USkpKQIHx8fsXz5crFo0SLRpk0b0bp1a5Geni6sVqtISko= SRqNRFBcXi2HDhol7773XPXZBQYHo06ePaNq0qft+zs3NFf/4xz+Ew+EQ27ZtE+3atRPt2rUTn3= 76qTCZTOLNN98Uq1atEkIIMW7cOBEZGel+dlyjurpavPDCC6Jx48YiLi5O9OrVS+zdu1dUVFSI6= OhoERMTI1566SVRU1MjCgsLxQMPPCAqKirEgw8+KIxGozhy5Iho3ry5+OKLL4S/v7/7Om/fvl3Y= 7XaRnJwsJk6cKDZs2CAiIiJE27ZtxUcffSQuXrwoIiMjhdVqdX8mjBw5UsTFxYlZs2aJmpoaUVZ= WJvz9/cWHH34o7r//fhEXFydGjhwp+vbtK3r06CGWLFkiunTpIo4dO+Z+lmVmZoq+ffuKiIgI93= tNSUkRixYtEk6nU6xevVq0b99exMXFidTUVGGxWNznory8XDz22GPCYDC4P7+6desmNm7cKEwmk= zAajeKFF14QzZo1E3FxcSInJ0dMmTLFfT2EEGLLli0iLi5OLFvmev6+/fbbYunSpUIIIY4ePSp6= 9eolYmNjxcqVK4VOpxNz5swRMTExonPnzuL48eNiyJAhYsSIEUIIIXbu3ClmzZolqqqqhNVqFW+= //bZo0qSJiIuLE6dPnxavv/66iI6OFo0aNbruWfCvcNuDm5Tv14qnnn1a6HRa8fnnrod6cXGxeP= zxx4Wfn58IDg4WQ4YMEWfPnhVff/21iI6OFoGBgaJ58+Zi9erVwul0ip9++klER0WJzt06iTWpa= 8VnyxeLRpGNxBdffOEe02KxiPj4eCGTyYRcLhe9evUSQvwc3MyZM0eEhoWIFd9+LUaN/qfo1KmT= sFis7uNOp1OcOHFCTJgwQQQEBAg/Pz8xadIkkZmZKXJzc0VAQIB4bsrz4uPPPxHNYpqLjRs2CEm= ShMlkEvv37xc1NTXuvhYsWCCUSqV45513hBBCTHxqgohuGi1SNqwVs9+8dXDj4bfZsmWLeO+992= 57v3PmzBHHjh0T5eXlIj4+XsyZM+e2j/FrbDabMBqNorq6WowePVrU1tb+5WN68ODBw/9Vbuu+O= BngdDooLS7By8uLTp06YbfbWbt2LWvXrmXq1KkkJCRw6NAhsrOzee6552jbti3PPfcce/fupaam= BkmSiIqKwj8ggLLSMszmBtRqb/R6PVlZWYwZMwa5XI5KpeLtt99m3Lhx6HQ6pk2b5p7HtaX0iIh= I1zJaSDB7M3ZTUuKqG3E4HPz4448UFxczaNAgsrOzKSkp4dixYzz00EM0a9YMm91GcHAwGo03Or= 2eQ4cOc/fQoRQUFPDRRx8RGBjI1KlTMZvN7Nq1y50qamhooLqqmrDwMBRy+R/1l/DwC8TVeqply= 5bRtm3b297/tVx1dnY2L774IkFBQbd9jF+Tl5fHokWL0Ov1DBs27KY7ITx48ODBw+3htgY3EhII= CaOxDp1OT3h4OFarlXPnziFJEo8++ijBwcEMGjSIXbt2UVlZSY8ePbjnnnvo378/Xl5eyOVy/P3= 9CQgIoKikCJvZiq+fP+06tGPjxo1MnDiR+Ph45HI5HTt2RK1Wo9FoaNWqlbtY+eTJkxw8eJB+A/= qhVquJjY3FZnewatUqpk2bhsPhIDs7m2+++Qa73Y6/vz/vvvsubdq04ccff+S9994jMCiQxo2j8= VJ7EdciltUpqxn/xHhCQ0Px8/Nj+fLl7or106dPM378eLp168bJkyc5ceIEA+8ejFwuvyqQ7Ilw= /ixOp5OBAwfetDDw3+XNN9/k5MmTgKt49Jc7dv4qoqKi6NOnD0II7rvvvr98PA8ePHj4v8ztM87= kqtWCHBRKpVsqWq/Xo9VqcTgclJeXYzAYyMnJwWw2Az9LQufl5SGTyUhISMBut2OxWFB7eaFQKJ= DLoF+/vmTszODdd99l3rx5BAQE4HA43C9xdddVeVk5Hy74EIVKSc/k3jiddsIjwunb/04+Xvgx3= bp2I7lPMk899RSDBw/mo48+4sEHH6RHjx7IFXKaNmuKJEkMHjoErV6LkAS9k5PYmb6DuXPnMn/+= fF5//XViY2PZtGkTBoOB9957j2HDhmG1Wlm8eDEypZwOnTthlxwIT1zzp5HJZMTHxxMfH/+X9N+= lSxe6dOnyl/R9K/R6Pffee+/fOqYHDx48/F/ltov4yWVyQkNCMJlM5OTkuPUWoqKiuPfee7n//v= sZNWoUFouFgQMHsmbNGoYMGcLdd9/N+++/jxCCkpISKioq8PPzQ+2txik5CQgM4OlJT7F161Zmz= ZpFQUEBBr2BKVOm8Nxzz6HRaCgsLGTmzJns+Gk7Yx8Zi86gRcLlknn3sHuIbhbNCy9O5ocftiBJ= Es2bN2f69Om0b98ek8nExo2bePHFF4mLb0FSchJOuxNJSERENeLJpyeyfv16Xn31VYxGIxMnTmT= btm2sX7+e++67j9raWl5++WXS0tMYNWoUarUX0u/4gP6avLw8vv766+u0ICRJIj09ncjISIYMGc= KFCxeua7N7925iYmKIjIxk9erVN+3X4XD8YdXYP4q46v9yzYumoqLi3+7zq6++Ijg42K0R8WssF= gtFRUWEh4fTpEkTXnnlFV544YU/NUZNTQ2VlZV/qs2xY8cICAi4pTgWuOTJ+/Xrd9Mtz78mPT0d= X19fsrKyqK2t/be3PP4au91OWVnZH1aMdUqC77MqiJ126IZjdWYnNofrRq4w/nE1Y7NdYsp3rnt= 1++katp++Ud/kX8Fil7DYXbtIpq/N58u9pbel3/8W1mZWsC27mjGLz7AkowSAgfNPkH66+m+fy4= +nqkk5XE7M1IP8dPb2XP9/FYtd4umvcpnwpUsA0ikJPt5RjMMpkASsz6pgwpc5N3xmV9bbGfDuC= eJfOcSOMz+/h8P5Rr47VP53vgUPf5LbsnLjspcUyGQgVyiJaNQILy8vl25Nnz706dOHBQsWkJqa= 6tbmuOuuu+jRowfLly+nsLCQfv36MXbsWORyOcePH6eqqoqk5CTUam+cTidCCFq1asXYsWPYtGk= TR44cITk5maioKCQh8f7777Njx3asdisPPTyaFi1b4HQ6XCadCFTeKh594lHWp6zjxRdfpFOnzu= 4tc9XVNRw5coRjx4/Spm1bht4zFIVc4Q79HJKT9p3b8+gTj7N5YypZR7PondSb0LAwEMKlOZDxE= w6HgzFjxxDXIg5JOF3+VlfP0O9RU1PD3Llz6dq1K35+fu6/Hzt2jPfee4+jR4+Snp7Ojh07rrMB= 6NWrFwMHDmTAgAHcc889N+178+bNKJXK35VU/zNUVVWRlpbmFsq7cOECTz311L/VZ2JiIoMGDbp= B8A1cKqZLly5l69at7N27l2bNmpGamvqntwumpaVRX1/PI4888ofbhIeHM2PGDLdcwM3w9fXljj= vucCsg/xaNGjVi8uTJREREuNOz48aN+8Pz+T2uXLnCd999x+OPP/6b/lbXMFqcZJyrxeG8UVr91= bX5PNIrDH+tkmdW5pH6/O+/P4ANWRXc2zEIm0NQbbLTpfm/X2NkcwhWHiijSZCavgn+vHlf099v= 9H8Is12ixuRABpwqbiCphetzZOuLt79u7fewOSSqTQ7OljRQb/3XbBluJxfKLZwpaSA21CWMd7b= ETISfF3I5lBttbDxaidl24zwf/fwcw9oH0a+VH9PX5NMmUkewQUVxjZWuzf4+nyQPf57bEtxce4= BLwhXgNG7ahEYREaSkpPDQQw/Ro0cP+vfvT3JysltjBX6WW7fZbHh5eSGTySgtLSU1NRWH00H3p= J4u520ZIJMhCejQpRPhkREcP3GC3fv2uG0SvLy8SOzcgbbt2hISHnLVKPOav5UMIUn4+vsx8sEH= OHf6HCeOn2TdhvVug8zg4GAeGvMQcS1aoNFqkGSSOySRyVzu3526diAiIpzjx46zZ/9e7HY7QhJ= 4azR0uaMLbdu2JSQkBEnBVZOtX75uTXV1NdOnT0cIcZ0eiM1mY/Xq1YwcOZKgoCC3TPkvMRqNlK= xIR7MAAB9cSURBVJWV0b17d+bNm0dQUBB33HEH77//PsOGDePs2bMsWrSImTNnYrFYWLx4MVlZW= XTv3p3w8HDWrl3La6+9xqeffkqPHj1Yv349CxcuZMWKFQghePjhh9Hr9UyePBm9Xk9DQwOPPvoo= M2bMQKFQ0KpVK1JSUtxCWikpKWzevJno6Giee+450tPT+eGHH5g6dSrbt2/H19eXsWPHUlxczGe= ffYZSqcRsNvP0009z8OBBBg8efNNzlJOTw549e5g9e7Y7uOvXrx+xsbFIkkRaWhqrVq0iMDCQ+f= Pns2fPHpYuXcqYMWP45ptvGDRoED179iQjI8M919zcXObPn49CoaB3794kJSVdp7OzfPlyMjIyu= OuuuzAajTRq1IgPPviAY8eOceeddzJq1Cj3vXxN6PCaBs769evZsGEDffr0wWazuf1bhBDk5+cT= HByMXC5n/fr1DB06FIAVK1awY8cOOnbsyDPPPAPASy+9REVFBWPHjuXixYtu87zNmzfTtGlTt8r= nkiVLaNGiBVOnTuX48eNUV1ejUCiwWCx888037Nq1i549exIXF4ePjw+HDx9m7NixqNVq/LRK7k= kMZPPxSr7ad4WfztbwXP9IvjlwhbVHyimsslBncXK2uIGZ6y/SoYkBk9XJ9tPV+GqVPNwjFLlMx= oIfi3j+rkhaN9JxudrKqK4hXKyw4KWUE6RXcbq4gflbC/FWyXnl7mhqGxx8vqsUL6WMHrG+6LwU= rDxwhcgANc/1j0SlkDF9zQUabBL9WvlTbXLwYVoRzUI0tIvU892hMpqHaDhT0kB2kYm7EwMJ9/V= i+Z5S3r6/GZtPVLH9dDUtI7Q83bcRdWYn834opMpkZ/QdofRJ8OPH7Gq+O+SyX3i2fyRBeiUr95= fRrbkPX+4tZUi7QMrrbBzKN/JoUjjBehWbT1QSE6Ih9VglIzoHk3nRyPkyM88PiKRVIx3LdpeyN= 7eWAJ2KcT1DadVIx8QVudyTGMiaI+UM7xDEXa39Wbi9GIO3y8RxfO/rTXInf5NHncVJYmM9j/YM= 42ypmW8PXHHd960CqG6wk5b982rM03c2QqGQER2opk+CH9uyf14NfHZlHi8NisLHW8GnO4vJvWK= mdSMdk++KZMeZGlYdKMNXq+CxpHBqGxykn64mMkDNoQtGJg+IJDZUw4urztMk2Js2kTp6t/Djw/= TLnCisJ6mFH2O6h5JyuJy8Kw3461Q8dWcERdU2tF5ypg6OYuW+K+w6V8tX+65wZ4I/FrvEvrxaB= rQOoGNjPe/8UMjANgHc2/Hnwv7Mi0bOlpg5W2KipsHJY0lhJEbrmb2hgIJKC4nResb1DHOfP4CM= czWcLDKhkMvIKTXzZHI48eFavtp/hf25dXir5MivlgkU11hpEaZFLpOx82wtOrUCxa/yGJerrWS= cq2HGPY1pEabF5pDYl1dH9xgfbA6B3vt/14DTw29zm1ZuwJWSkqGQKwgKCSG5Xx8WfbSI1157ja= VLl9K0aVO3kN8vuSasJVzb0lmxYgVbtmyhd5/eNG3WDCEkFDIFMhnIkIFCRnSTxkQ2juauwU6ck= hMEKFQKFHIl8murSLeYq6+PD526dqFDl844nRKSJCFXuOatkLkczUFw7ScXClcEJ5MR1bQxkU2i= kZwSTsmJkARKhQKVUuEKqIQAIZDJZSCXIZcrr+vpZkybNo0ZM2Ywf/786wwzrzkcd+vWDYfDQUF= BAY0bN76ubWZmJv3798fX1xdvb28uXbrE/v373TLejRs3ZuTIkW7bg4CAAGbPns0jjzzCW2+9RX= h4OA8//DByuZwRI0YQFhbGG2+8QWRkJGVlZZw/f55//vOfLFiwAEmS2LBhA1FRUSQkJNClSxdiY= 2MRQqDX61mxYgVZWVm8/vrrrF+/nnXr1pGUlMTLL79Mz549qampoaioCLvdzqRJkxg/fjze3t48= 88wzTJ48mcuXL1+nonkNSZLcFhe/VDD29vamRYsWbN26leXLlzNz5kyWLl3KypUr6dixI+Xl5aS= kpDB+/HhWrVpF//79KS4uJigoiEOHDvHJJ58wZcoUSktL+frrrxk4cCDgCiqvWXrMnDmT+fPn06= NHD2bMmEFMTAzjx4/n8OHDmM1md3CTlZVFYmIiBoOBL774guzsbF599VXef/99t5IruAqlz549S= 5cuXQgMDHSfu4ULF1JQUMDLL7/sNvsbMGAAzz33HGazmYKCAjp06MAHH3xAq1atkCSJgwcP0qxZ= M9577z1effVV5s+fj1wuR6vVotVqkclkvPbaa4SGhjJ79mySkpJIS0sjMjKSqKioG1RMK4x2jhX= WExem4fusCp7u24jtp2t4MjmC8+UWvjSXMqC1Py98e568K2ayXu/IB9sus2x3KTOGNmbm8CYEG1= QcOF+Hwdv10VLT4EASAq2XnKEfnGTpIy3YerKKz3aWsGx3Cf46Fe8+0Aw/rZKHl54lfUo7FvxYx= Efpl9Gq5agUcnrH+/DV3it8PCaWjHM1/KNDEMt2l/JBWhFvjWjK6DtCGfjuCd77Z3OKqqw83COM= jHO1rNhbypJHWjDlu/N8e7CcfXm1dG5qoMqk5P9tuUSTIG8yztXw/IBIMs7WMP6Lc7SL0vPtwTK= 6NPPhxYGRPLUih0n9GuGUBJ9sL8ZLKWPNkXIGtwvkvo5BPPTZGZY/Hk9GTi2bjldSXGPjQrmFWc= ObsDunljmbLlFvdpB2upqaBgedmhj44UQVyfF+FFdbCTKoOHCh7rrg5rX1F2kZoaNLMwOzNhSgk= suYvaGAcD8v3nmgOV2aGugyO4vF4+JYn1mBU0BChJY9ua6HtFL+8+fN9DX5LM0o4bGkcNKyq7A5= Bf9zT2NGLjqNUilnb04tc+9rwsajlUz97gJX6mycLm5gUr8IfDUKdp6pYVt2NUE+Ko5dqqey3s6= JIhPnShsY3zuc5785T3y4loPn62jfWM+CH4t46s4Iqk2uFKZGJcfmkCissnBnS39e//4iO6e141= B+HWqljKhANV5KGX1b/rxaXVlvZ+KKXPLKzMx/oDk7z9Zw4HwdGedqMVqdPHVnBG+kXqJzUwPdr= q4IniwyMWPtRU4U1TOhTwQWu0TuFTM5pWZSDpUzc1gTJq/KQ5Kg2uTgQrmFpsHeV9vW0yPWh+2/= St3VNDgx2yUSo12CeGqlHKPZQUmNDblcRqDuzzuge/j7uE0rNzKMdXXs27cPL6WKsPBwevTqxYX= 8fH5K38n06dPdtuxyufyGAEeSJOrq6liyZDFz586lSdMmDB12DxXl5eTl5KC45uyNDEnmCj5Ahv= y6at2rqyNXV3pkt1gtcdlgyrh+B5MrIBLIrhYAi6u+UMLd5pf/L7uhLUgy4T4mE+Jqqk5GUeFlg= pNuvtXY4XAwbdo0BgwYwLlz5ygrKyMkJMR93GQy0ahRIwICArDb7RQVFbmVHsH1oNyxYwd33XUX= kiThdDopKChg3rx5vPLKK0yYMIG0tDTuv/9+6urqOHXqFFOmTGHkyJG89dZb1NfXc/ToUTZs2EB= AQAA7duygoqKCwYMHExUVxXfffce6deuYO3cu/fr1Y/PmzSQmJrrVjZOTk92rD88//7zbAbZx48= aEhoZSXV3NhQsX6NGjBwqFgvDwcPz9/ZkxYwbDhw9n0KBBrF27luHDh7sN824lyX9NLv3XD2SHw= 8Enn3zCrFmzSEhIICQkBJvNRn5+vttvqKioCIVCQVlZGcePHycxMZH58+czevRoWrZsyfnz54mP= j3dvzz5z5gyXL19m5syZeHt74+XlhRAChUJBcnIyH3/8MUlJSe6Uz7XgKyEhgfr6en744QcWLFh= AYGAgubm51/kUWSwW9u3bx4MPPojD4SA1NZVJkyZhNBrdqao5c+awYsUKd63awoULGT9+PPn5+b= Rv356goCBMJhMDBgxg8eLF/M///A+JiYmsXLnS7bXl6+vL7t27KSgo4J133iE/P58mTZq4U2u/9= q0BCDKomP9Acxb/VEJmgZEwXy+8lDJCfb2oMTvcKywT+0RwvNBEdIA3Y3uE8kHaZcw2iehAl1N9= udFOv1b+SAIuVliIDvRmy4kqGvm7VhX6JLgeZEktfPnsp2IGtglgya4SSmtt9J93AoBBbQN4fkB= jdp6pYfbGAuQyGf46JTq1gmAfFaO6hnD4ohG5TEawQUVcuJYThSb03gp8NAo2HqvkyMV6d3+dm/= lw6rKJqYOjiAnRMG1wNN8cKMNLIaNNpI42kToO5htpE6Ujv9zA5hdac+pyA4nReu7rFIzdKbhUa= eXBbiGUGe18OyGBn87WkNzCj05NDDQL8sZqFxwtqKdpkDdRAWq6NDOwO7eWN+5tQsdZmcwc1pj9= 5+vYm2dDJoMTRSaGtAtg4UPXpzvXZVaQOasDaqWcEZ2C2JdXx6KxsWw6Vknfq+cuSK/iSq3rIes= lB0kIahoc7gf2Nd4c0ZRlu0uoMtk5XdzAPe2DaBLkzaHXOrDhaCUfFRgZ8v5JZMhIjvelXyt/Vh= 8q4/+NaMabqZfIr7Bwf+dgnliew4Q+4QxrH8QTX+ZwIK+OHVfrqC5XWTFZnew8U8PiR1rglASXq= qzuuahVch66I5TkeD9W7Cnl4Hkj93YMYm9uHVovBZ2a+qBWyrlUacUhSWi9FLw8JJpd52q4v3Mw= +/Jqqax3kFdmZsbQaJqHaFg3qRUWu8TFCguSEIQYVIzpHsqPp1TMHNaE19blc7q4gWOX6uke40P= HJnq6NvOh3uqgzuIg1EdFTIiGoQuyWfBgc7aerMZocXK52kpUgOs+VillKOQy7E6BSiHDKblWax= ySIFCnRPbb31k9/C9zW4IbuVzOpYJCNm/eDAiax8Ty5NMT+efo0YCMrdu2UlRUxNixY+ncuTMhI= SF4e7tqaaqrqzlx4gQpKSmsX7+elm1aMeqfo9DqdXzy8SccOXBjkaOLa/uzbgNC8Gfu1Jt5ZN0K= uVxOxw4db3qstraWiIgItm3b5patzs/Pd8vCK5VKDAYDCoWCbdu2IZfLrytYLSwsRKVSERMTg8V= iISsri/vuuw+j0UheXh7h4eFUVVURERHBnj17OHnyJB999BFz5swhJCSE/fv3M27cOPz8/HA4HO= Tn52MwGBg8eDDvvvsurVu35tSpUwwcOJAzZ86wevVqHnvsMQ4cOIDBYMDPz4+0tDTGjh2LUql0B= zAXLlxg48aNvPLKKyxbtgytVsvw4cNZuHAhiYmJPPnkk1RUVHD48GEWLFjAsmXLOHPmDFarFZXq= 5t+GQkJCyMjIoKioiGbNmrm1jLy9vbl48SLt27cnOzub1NRUvvjiC3bs2OF2S1+4cCHDhw8nOzu= biRMnUllZSUNDAx06dGDHjh0sX76cGTNmuMc6deoUiYmJWCwW5s+fT2FhIfHx8Rw4cIDy8nKGDh= 16Xd1TeXm5WzL822+/pW/fvnh7e7No0SK3bPs19u7dS6NGjXA6naSlpTFu3Di3q7rBYODEiRP4+= vpy5MgRcnNzKSoq4r777iM0NJSFCxcSHBxMr169yMzMpG3btjz++ON8+OGHbrsJf39/amtrSUpK= Yu7cubz11lsUFhYyb968P1Vn9HvUml3p4DKjHR+Nwr1Eb7Q4sTsF3io5khBcrrYyvEMQJ4tM5Jd= buFBuoVmwN8cLry9wD9Z70TxYw7pnWhGoV3G2pIF3thRSUGnlieQI1hz+7eLN8b3DWbj9Ms/2jy= Q0yJsgvYruMT4sfaQFkhBcqbOxMauCM8UNxIRoOHihDj+tkosVFqpMDgJ0Smx2iQg/9b91XrRqO= ZkXjTyWFIbdIfBWyvFS3rhvw0sh57VhjSmqsnL3gmyOvf7zZ4S/TsnqQ+WM6R5KvVUiMuDGOXWP= 8SH9dDVBBhXTBkdjsjpxSIKYkBuDVnCtOngp5Zy6bKJnrA9mu8SVOhvx4Vo+HhNLoF5JfrmVAxf= qbmgrl8F7o5qTerySl9dcIFivYmSXYN68rynFNTaEcAXGRouDx5adY+WTCZTW2vhHh+u/1F2utg= LQvokehUzGpmOVrNhXytdPJJB7xcwXe0qpqrfTOlJ30+tg8FawNrOCqYOiuFJn43yZhZTD5ZhtT= hKj9VgdN9aMabzkXKywAFBndpB7xczp4gZ0atf92jhQzTtbCsmvsFBUZeWrfVeYfnc0AHGhGjo2= NrD2SDm9W/hhdQiGJgby2U8l/LNbyA1jefjPQjHrmmf5v4HVamX9+vWcPXsWSZKoramhrr6e9p0= 60Lp1a3QaLZmZmWzcuJGMjAzS09NJS0tj3bp1rFy5klWrVpGXl0evO5MYOWokoWFhbPx+IzvTtr= s9Nq69fH19GTFiBHfdNZD4+HiEELRs2dKd0jAajVRUVFzX5tpLLpfTvXt3QkNDqa2tZfjw4Vy5c= oV7772XYcOGYTabKSwsvGlbSZJQq9UMHDiQYcOG4eXl5fZMatmyJbm5uTdtA670wrUH7S/RarV0= 796de+65h08++YSVK1ei0+mYNWsWAwYMQK1Wu2tHLl26xNSpUwkNDQUgPz+fp59+mszMTDp06EB= dXR2lpaWMHz+elStXcuTIEdRqNdu3b8dut9O5c2f27dvnTg2GhYWRlZXFgAEDCAoKorq6mt27dz= N69GjCwsIYN24cISEhXLhwgU2bNnH27Fny8vLQaDTs2LGD/Px84uPj2bBhA4cPH6Z///5kZWXx1= VdfkZaWxhNPPEFUVBRpaWksWbKE/Px8li5dir+/P1lZWRw8eJDc3FyOHTuGRqMhJyeHy5cv069f= P5555hk6derkXkmRyWSEh4eTk5PDl19+SWpqKqmpqW636szMTNatW8fJkyeZNGkSTZs2Zf78+ez= fv59NmzYxYsQIBg0axMKFC9m/fz99+vRhzZo1bN26FY1Gw5IlS2jTpg0dO7oeMOXl5bz//vtcun= SJS5cuUV1dTYcOHSgsLEQIgcPhoE2bNgQHBwNw4cIFt9O5j48Pn376KefOnSM7O5vCwkJ69erl/= t/Zs2dTW1tL7969+fzzzzlz5gzJycns3LmT1atXY7fbad26NWazmfPnz7vvE41Gw4EDB1i8eDEn= T55k5cqVREVFUVtby5o1a6iqqqJdu3Y4HA7mzp1LVFQUpaWlbNmyhZycHPbt28f58+fp06cPy5Y= to1WrVqjVrgdITYODT3YWc+B8HWa7xE9na8m6VE/rRjp+OFlFXpkFP62SzccruVJnx2SVOFpQz8= 6zNezPq2Nk5xBkwLSUC8iu1sZ1bGJgf14dDTbXsn6ojxc5pWY+31XCzqu7Tj7fVUpOqZm2UTq6N= vfhTHEDy3aXsi27ihbhWi5X2zh2yUhRlZVTl02oVXIKq6yknaqmpMbGpmOV2B2Czk0NJEbr+SCt= iDAfL/ok+BHpryb9dA1rjpTzY3Y13Zr7EhOq4cP0y/x0pobTJQ080iuMIxeNLNtVytaTVSQn+FF= tcrDhWAV1ZleR9d7cOix2ic3Hq7hUaeVihYXMi0ZkwJrD5WReqqfB5uSHE1VUNdi5q1UAB/PrSD= 1WycF8I31b+rP9dA07z9ZQb3VytsTMkXwjOrWcBT9epsJoRymXMbxDEG+mXkKvVpAc78ecjQXsy= anFZJMY1zOMGesukltqplMTPY381bz03XmC9CrqzE62nKgi2OCqWYwP17rTfiark+wiE7tyapHL= YGhiIIszSkg/Xc3e3Dq6Nfehst7O8j1XSD9dTUGllf15dZwsMuFwCjYfr+TUZRNGq5MtJ1wptza= ROh7uEcaqA2X8cKKaHWdq6NvSn1nfXyTvihmbUxBs8MJbJaddlCudY7Q4Wbn/CttOVvPPO0Lo3c= IPX62S7MsNNNgl7m4XSKBeRd+W/tydGEh8uI63Ui9x8HwdCoUrDVjT4GB4xyA+3VnMvtw69p2vo= 3uMLw/3COXuxEACDSq+2F1K5sV6VEoZKYcryCk18/KQaD7fVcq+vDpOFZvQeCmw2CVGdglB4yVn= cNtA7k4MROslx+KQeHtkcy6Um1mQdpnYUA09Yn35MP0yP5yo5IFuIWhUcs6Xm+ndwo9Lly7x/PP= P/y06WR7+PDLxR5cgfoPa2lrGjh3Lpk2b3CsaCqWCth0SmThxIkGBAZQWl3Lw0EEOHzxERWUV9f= X1KOQKQsNCSWiZQM+ePWka0xy73cba1Sls3byVhoaGG8aKjY11u4Y+8sgjfP/993To0IHc3FwGD= RrEqFGjqK6++bZHtVrN9OnT6dy5M9OmTWPevHl8//33REZGcvToUfr27ctrr712y23NzZs3Z/bs= 2Wzbto2EhATeffddZs2aRfPmzbn//vtv6tirUCiYN28ekydP/s1zeM0V2Ol0UllZ6U5P1dfXYzQ= a0el016na2u12ystd32b9/f2Ry+XY7Xb0ej1GoxGTyYRWq8VsNqNWq/Hx8aGystKd3vH29qa+vh= 69Xo9CoUCSJBoaGtBoNCgUCoqLi9FoNDidTmw2GxqNBiEEcrkcSZLc/VgsFsxmM0FBQZjNZurr6= 1EqlYSEhOBwOGhoaMDHxwe73U51dTUajca9hVyn02Gz2VxaRledxX18fCgrKyMoKAil8vqFRbPZ= TG1trTtQ9fX1RaPRYDQaMRqNaDQafH19KSoqYvr06bzzzjsAbvfu6upqzGYzwcHB1NXVYbVaCQg= IoKqqCp1O504zXTu311JSDQ0NGAwG6uvr3ef419eisrISf39/ZDIZFRUVbtfvhoYGAgMDrys8vn= bNampqsFqtBAYGYjKZMJvN+Pr6otPpsFqtbsVuX19fVCoVZrMZHx8f9zG9Xo8kSRiNRgwGg/v3i= ooKtFotQgjq6+vdNW1Wq5WQkBCMRiO+vr7uc+6UXCkNm0OgUsqQJIFTAl+tEpPViSQEOi8FRqsT= pVzG91kVHCs08erd0agUMvy0SiQhqKp3YNC4aj68VXIabBIymavuAqDBJlHb4Frx8dUqqW1wIJO= Bj0aJ1kuOyeqkzuzasRJsUGF1SNSZna5SNsBbJQfh2tarVsmw2l3pAl+tEpVCRpXJgZdC5l5Fqj= M7MFkl5DII9vFCEoIKox0hXN/o/a6+v2tjBupVmO1OGqwSKoUrKe1wus6J3eHaLCGTgSS55mJzS= EgCvJQybA6BQu56X2abhNkmobw6t3qLE6tdQiGXIZO5+tR6ybE6BU6nwNtLjq9GSZXJjl6twFsl= 50qdDUlyzdNXo6S01pXK8tMq8VbJmfLdeV64KwqA1OOVBOpVDGkbgFr183lUKlwJdLtToFTI8Nc= qqWlwuH8P0Cmx2CXqLE5kuMayOQQOp8BL6UrHCOFajbr2dx+NAp1aQZXJgdXueo/BBhWV9XbsTo= FCLkOnVlx33a0Oiap617UO0qtQKlyr5IszSkhu4Udc2PWrTa7r5MApCTRecsw217nz0yqoaXDgl= FwpIz+N0t2X3em6hx1Xz6fF5vpiGerrRWW9HYdToFDIUCtdZQk+muuLga9JDPhpldidgtoGB35a= V//lRjtOSRCoVyEE2J0SOrUCu91ORUXFdQa6Hv5z+MuCm6t1uTSJacrIBx6gbbs2aPVanA4nJlM= DDWYzMpkMXz8/1Cov7DYbpYUlrFu7lv3797uX6n9NTEwMs2fPprCwkK5duzJ9+nRiYmJ46623eO= CBB9izZ88t56lWq3nxxRe58847OXLkCO3bt+f48eOkpaWRnp5OWFgYVVVVWK3Wm7YPCAjg2WefJ= TExkX379pGens6TTz7pdkTduXPnDW3+aHDj4fZQUVHB0qVL0el0TJgw4ZZpLg/X8+zKvOt0PG6F= zSFRXGPD5pAI8/XCR3NbRc49/EHOl5lxXhVlCdApCTJ4/U6L/xxqGhyU1dkI8fHCT/v/3/vnmyc= TaBt1+xXUPdwe/ro7S7jSCRfz8ln04ce0btuaVq1bERkVicHgg5dajSQ5OX8ll9KSK5w7c4ajmV= l/SGDNZDKRnZ1NSEgI8fHxHDlyhJMnT7J3797frIeRyWQ4HA5SUlLo378/3t7e5Ofn061bNwwGA= z179uSNN964ZXCjVqupqqoiIyOD4cOHo1Kp0Ol0VFVV8dBDD7Fnz55bBmUe/h72799PQUEBsbGx= 1NXV3bJA2cP1fPhQzB/6v9JaG0sySrhSZ2P0HaHu3Soe/l5eSbmA8ap+TN+W/jfUt/wnk3GulpT= DZTzQJYRecb+vw+TBw7/CbVu5GT16NJs3b/7NQlu1Wo3Bx4BGo0GlUuF0SljMZupNJhpMpj9UpO= vn58egQYMwGAzU1taSkZGB0+mkT58+t1TovYZSqaRz585UVlai1+tp1aoVaWlpJCUlER4ezv79+= 8nMzLylsqtWq+XOO+8kIiKC/Px8lEolhYWF1NbW0r9/f1auXHlDYCSXy5k3b96fVtL14MGDBw8e= PPxr3Jbgxmg08uSTT17dLXWLgf7EDqM/y7V+f73F/Nfj//J/f/3z77W/dvyaHs+t+v81CoWCN99= 8kwkTJvxm3x48ePDgwYOH28NtCW6cTifl5eVYLJZbD/QXBje3i79ijjKZjICAAHQ6nbuA04MHDx= 48ePDw13FbghsPHjx48ODBg4f/FDxLCR48ePDgwYOH/yo8wY0HDx48ePDg4b+KP7UVPDs72+3C7= cGDBw8ePHjw8L+BRqOhRYsWtzz+p4Kb77777qYqvB48ePDgwYMHD38X4eHhTJky5ZbHPQXFHjx4= 8ODBg4f/Kjw1Nx48ePDgwYOH/yo8wY0HDx48ePDg4b8KT3DjwYMHDx48ePiv4v8DkrKy3KIORuI= AAAAASUVORK5CYII=3D" width=3D"567" height=3D"140" alt=3D"" /></p><table sty= le=3D"width:438.55pt; margin-bottom:0pt; padding:0pt; border-collapse:colla= pse"><tr style=3D"height:298.55pt"><td style=3D"width:72.5pt; border-top:0.= 75pt solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; = vertical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; text-al= ign:justify; line-height:115%"><span style=3D"color:#767171">Palabras clave= s: </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:1= 15%"><span>Aula invertida, estrategias did=C3=A1cticas, desempe=C3=B1o esco= lar, ense=C3=B1anza t=C3=A9cnica.</span></p></td><td style=3D"width:344.45p= t; border-top:0.75pt solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; pad= ding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-ind= ent:0pt; text-align:justify; line-height:115%"><span style=3D"color:#808080= ">Resumen </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-a= lign:justify; line-height:115%"><span style=3D"font-weight:bold">Introducci= =C3=B3n:</span><span> entre las estrategias did=C3=A1cticas empleadas en la= s metodolog=C3=ADas activas se encuentra el aula invertida. </span><span st= yle=3D"font-weight:bold">Objetivo:</span><span> el objetivo de esta investi= gaci=C3=B3n fue la aplicaci=C3=B3n de esta estrategia did=C3=A1ctica para m= ejorar el desempe=C3=B1o de los estudiantes del bachillerato t=C3=A9cnico d= e la Unidad Educativa General Medardo Alfaro. </span><span style=3D"font-we= ight:bold">Metodolog=C3=ADa: </span><span>se emple=C3=B3 un dise=C3=B1o cua= si-experimental mediante dos grupos: uno control, con las condiciones del m= odelo educativo tradicional y otro experimental, en el que se aplic=C3=B3 l= a estrategia. La poblaci=C3=B3n la integraron 90 estudiantes y la muestra s= eleccionada aleatoriamente fue de 40 estudiantes de tercer a=C3=B1o del bac= hillerato t=C3=A9cnico. Entre los m=C3=A9todos para la recolecci=C3=B3n de = datos, se aplicaron evaluaciones continuas para medir el desempe=C3=B1o esc= olar, un pre test y un post test a los estudiantes. Adem=C3=A1s, se emple= =C3=B3 la encuesta a estudiantes y la entrevista a docentes de la instituci= =C3=B3n para recoger datos cualitativos acerca de la percepci=C3=B3n de la = metodolog=C3=ADa implementada. Para el procesamiento de los datos, se aplic= =C3=B3 como m=C3=A9todo estad=C3=ADstico, el an=C3=A1lisis porcentual en lo= s resultados obtenidos con la aplicaci=C3=B3n de los instrumentos. </span><= span style=3D"font-weight:bold">Resultados:</span><span> como resultado los= integrantes del grupo experimental obtuvieron una mejora en su desempe=C3= =B1o, es decir comprendieron significativamente los conceptos b=C3=A1sicos = y los aplicaron en la pr=C3=A1ctica. Al mismo tiempo, mejor=C3=B3 la motiva= ci=C3=B3n, la respuesta inmediata de las actividades participativas y su de= sempe=C3=B1o. </span><span style=3D"font-weight:bold">Conclusi=C3=B3n: </sp= an><span>la implementaci=C3=B3n del aula invertida en el bachillerato t=C3= =A9cnico de la Unidad Educativa "General Medardo Alfaro" mejor=C3=B3 el des= empe=C3=B1o estudiantil, favoreciendo la comprensi=C3=B3n de contenidos, la= motivaci=C3=B3n y el aprendizaje significativo. No obstante, se identifica= ron desaf=C3=ADos como el acceso desigual a recursos tecnol=C3=B3gicos y la= resistencia docente, que requieren capacitaci=C3=B3n y soluciones para un = entorno m=C3=A1s inclusivo. </span><span style=3D"font-weight:bold">=C3=81r= ea de estudio general: </span><span>Educaci=C3=B3n. </span><span style=3D"f= ont-weight:bold">=C3=81rea de estudio espec=C3=ADfica:</span><span> Aula in= vertida en el bachillerato t=C3=A9cnico. </span><span style=3D"font-weight:= bold">Tipo de art=C3=ADculo:</span><span> Original.</span></p></td></tr><tr= style=3D"height:42.05pt"><td style=3D"width:72.5pt; border-top:0.75pt soli= d #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-= align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justi= fy; line-height:115%"><span style=3D"color:#767171">Keywords: </span></p><p= style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-heig= ht:115%"><span>Inverted classroom, didactic strategies, school performance,= technical education.</span></p></td><td style=3D"width:344.45pt; border-to= p:0.75pt solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4= pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; tex= t-align:justify; line-height:115%"><span style=3D"color:#808080">Abstract</= span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify= ; line-height:115%"><span style=3D"font-weight:bold">Introduction:</span><s= pan> among the didactic strategies used in active methodologies is the flip= ped classroom. </span><span style=3D"font-weight:bold">Objective:</span><sp= an> the objective of this research was the application of this didactic str= ategy to improve the performance of students at the technical high school o= f the General Medardo Alfaro Educational Unit. </span><span style=3D"font-w= eight:bold">Methodology:</span><span> a quasi-experimental design was used = using two groups: a control group, with the conditions of the traditional e= ducational model, and an experimental one, in which the strategy was applie= d. The population consisted of 90 students and the randomly selected sample= was 40 third-year students of the technical baccalaureate. Among the metho= ds for data collection, continuous evaluations were applied to measure scho= ol performance, a pre-test and a post-test to students. In addition, the su= rvey of students and the interview of teachers of the institution were used= to collect qualitative data about the perception of the methodology implem= ented. For the processing of the data, the percentage analysis of the resul= ts obtained with the application of the instruments was applied as a statis= tical method. </span><span style=3D"font-weight:bold">Results:</span><span>= as a result, the members of the experimental group obtained an improvement= in their performance, that is, they significantly understood the basic con= cepts and applied them in practice. At the same time, motivation, the immed= iate response of participatory activities and their performance improved. <= /span><span style=3D"font-weight:bold">Conclusion:</span><span> the impleme= ntation of the flipped classroom in the technical high school of the "Gener= al Medardo Alfaro" Educational Unit improved student performance, favoring = content comprehension, motivation and meaningful learning. However, challen= ges such as unequal access to technological resources and teacher resistanc= e were identified, which require training and solutions for a more inclusiv= e environment. </span><span style=3D"font-weight:bold">General area of stud= y:</span><span> Education. </span><span style=3D"font-weight:bold">Specific= area of study:</span><span> Flipped classroom in the technical baccalaurea= te. </span><span style=3D"font-weight:bold">Item type:</span><span> Origina= l.</span></p></td></tr></table><p style=3D"margin-bottom:0pt; text-indent:0= pt; text-align:center; line-height:150%"><span> </span></p><p style=3D= "margin-bottom:0pt; text-indent:0pt; text-align:center; line-height:150%; f= ont-size:6pt"><span> </span></p><h1 style=3D"margin-top:0pt; margin-le= ft:14.2pt; text-indent:-14.2pt; text-align:justify; line-height:150%"><span= ><span>1.</span></span><span style=3D"width:5.2pt; font:7pt 'Times New Roma= n'; display:inline-block">    </span><span>Introducci=C3=B3n= </span></h1><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:jus= tify; line-height:150%"><span>La educaci=C3=B3n t=C3=A9cnica, pilar fundame= ntal para el desarrollo socioecon=C3=B3mico de cualquier pa=C3=ADs, enfrent= a el desaf=C3=ADo de formar profesionales altamente capacitados que puedan = adaptarse a un mercado laboral cada vez m=C3=A1s din=C3=A1mico y exigente. = En el Ecuador las instituciones educativas que ofertan carreras t=C3=A9cnic= as tienen el reto de ir combinando o sustituyendo los m=C3=A9todos tradicio= nales e incorporar los avances tecnol=C3=B3gicos, as=C3=AD como realizar re= ajustes en el curr=C3=ADculo, planes de estudio y las asignaturas, de acuer= do con las necesidades y demandas laborales actuales que se presentan d=C3= =ADa a d=C3=ADa en nuestra sociedad.</span></p><p style=3D"margin-bottom:0p= t; text-indent:0pt; text-align:justify; line-height:150%"><span>En este con= texto, en la presente investigaci=C3=B3n se aplica la estrategia did=C3=A1c= tica, aula invertida para mejorar el desempe=C3=B1o de los estudiantes de b= achillerato t=C3=A9cnico de la =E2=80=9CUnidad Educativa =E2=80=9CGeneral M= edardo Alfaro=E2=80=9D. Se ha observado que existe falta de motivaci=C3=B3n= en ellos debido al uso de la metodolog=C3=ADa tradicional, la explicaci=C3= =B3n de la tem=C3=A1tica mediante una clase mon=C3=B3tona (explicaci=C3=B3n= te=C3=B3rica del docente), limitada la pr=C3=A1ctica y trabajo independien= te de los estudiantes, durante la jornada de clases, seg=C3=BAn Dom=C3=ADng= uez & Palomares (2020). Esta situaci=C3=B3n ha repercutido en las calif= icaciones acad=C3=A9micas y en la adquisici=C3=B3n de habilidades t=C3=A9cn= icas necesarias en su especialidad. </span></p><p style=3D"margin-bottom:0p= t; text-indent:0pt; text-align:justify; line-height:150%"><span>Por otra pa= rte algunos docentes defienden a=C3=BAn el predominio de los m=C3=A9todos t= radicionales en clases, ofreciendo cierta resistencia a la aplicaci=C3=B3n = de nuevas metodolog=C3=ADas en el proceso de ense=C3=B1anza-aprendizaje. </= span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify= ; line-height:150%"><span>=E2=80=9CLa din=C3=A1mica propia de esta estrateg= ia, el aula invertida o Flipped Classroom, ha contribuido a la disminuci=C3= =B3n de los =C3=ADndices de fracaso escolar de los estudiantes=E2=80=9D com= o lo indica </span><span style=3D"background-color:#ffff00">P=C3=A9rez et a= l. (2020)</span><span> para estar m=C3=A1s motivados para la participaci=C3= =B3n en actividades colaborativas, donde todos aprenden y emplean herramien= tas innovadoras, tales como: videos educativos y video libro, concordando c= on </span><span style=3D"background-color:#ffff00">Araya</span><span>-Moya<= /span><span style=3D"background-color:#ffff00"> et al., (2022)</span><span>= , ya que ense=C3=B1an que permite =E2=80=9Ccombinar la teor=C3=ADa con el d= esarrollo de pr=C3=A1cticas y por ende el aprendizaje de dichos conocimient= os=E2=80=9D.</span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text= -align:justify; line-height:150%"><span> </span><span>Seg=C3=BAn Rodr= =C3=ADguez-Borges</span><span style=3D"background-color:#ffff00"> (2020),</= span><span> =E2=80=9Cla aplicaci=C3=B3n de la estrategia del aula invertida= en el proceso de ense=C3=B1anza-aprendizaje de los estudiantes de bachille= rato t=C3=A9cnico se asocia con una mejora significativa en su desempe=C3= =B1o escolar=E2=80=9D, evaluada mediante indicadores como el promedio de ca= lificaciones, los resultados en evaluaciones y la percepci=C3=B3n de los es= tudiantes sobre su propio aprendizaje. </span></p><p style=3D"margin-bottom= :0pt; text-indent:0pt; text-align:justify; line-height:150%"><span>La estra= tegia did=C3=A1ctica, aula invertida, surge como una alternativa a las clas= es tradicionales, propone invertir el proceso de ense=C3=B1anza-aprendizaje= . En vez de que el docente exponga los contenidos te=C3=B3ricos en clases, = los estudiantes acceden a los materiales de manera aut=C3=B3noma fuera del = aula. Esto permite que el tiempo en clases se enfoque en la aplicaci=C3=B3n= pr=C3=A1ctica de los conocimientos, la resoluci=C3=B3n de problemas y la i= nteracci=C3=B3n activa entre el docente y los estudiantes, as=C3=AD como en= tre los propios compa=C3=B1eros. =E2=80=9CEsta metodolog=C3=ADa se fundamen= ta en la premisa de que los estudiantes aprenden de manera m=C3=A1s efectiv= a cuando son los protagonistas activos de su propio proceso de aprendizaje= =E2=80=9D. (</span><span style=3D"background-color:#ffff00">=C3=81lvarez, 2= 020)</span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:j= ustify; line-height:150%"><span>El aula invertida pretende dejar de lado la= educaci=C3=B3n tradicional donde el docente asum=C3=ADa el rol de orador o= expositor de los contenidos. </span><span style=3D"background-color:#ffff0= 0">Cede=C3=B1o & Vigueras (2020)</span><span> se=C3=B1alan que =E2=80= =9Cel aula invertida, permite actividades basadas en el aprendizaje colabor= ativo y cooperativo para la resoluci=C3=B3n de problemas mediante el an=C3= =A1lisis de las posibles soluciones, mientras que el docente es el orientad= or de este proceso=E2=80=9D.</span></p><p style=3D"margin-bottom:0pt; text-= indent:0pt; text-align:justify; line-height:150%"><span>La investigaci=C3= =B3n de Medina & Ponce</span><span style=3D"background-color:#ffff00"> = (2024)</span><span> resalta que =E2=80=9Cla implementaci=C3=B3n del aula in= vertida mejora la interacci=C3=B3n entre estudiantes y docentes=E2=80=9D. A= l dedicar el tiempo de clase a actividades pr=C3=A1cticas y resoluci=C3=B3n= de problemas y dudas que puedan tener, se fomenta un ambiente din=C3=A1mic= o donde los estudiantes pueden participar activamente.</span></p><p style= =3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:150= %"><span>Seg=C3=BAn Arellano y Escudero (2022), el aula invertida permite u= n enfoque m=C3=A1s activo durante el tiempo de clase, donde los estudiantes= trabajan en equipo y los docentes act=C3=BAan como gu=C3=ADas. Este modelo= desplaza la responsabilidad del aprendizaje hacia los estudiantes, promovi= endo un ambiente de aprendizaje colaborativo.</span></p><p style=3D"margin-= bottom:0pt; text-indent:0pt; text-align:justify; line-height:150%"><span>El= aula invertida no solo transforma la din=C3=A1mica del aula tradicional, s= ino que tambi=C3=A9n prepara a los estudiantes para ser aprendices activos = y aut=C3=B3nomos con habilidades esenciales en el mundo actual. Su implemen= taci=C3=B3n puede ser una herramienta poderosa para mejorar la calidad educ= ativa si se aplica con una visi=C3=B3n clara y estrat=C3=A9gica.</span></p>= <p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-he= ight:150%"><span>El presente estudio tuvo un dise=C3=B1o cuasi experimental= , se aplic=C3=B3 un pretest y un post test a dos grupos: uno control y otro= experimental a una muestra de 40 estudiantes. Los resultados muestran que = la implementaci=C3=B3n del aula invertida en el bachillerato t=C3=A9cnico t= uvo un efecto positivo en los estudiantes. El grupo experimental obtuvo mej= ores calificaciones, mostraron mayor motivaci=C3=B3n y participaci=C3=B3n e= n las actividades de aprendizaje, as=C3=AD como desarrollaron habilidades d= e autoaprendizaje y trabajo colaborativo, de manera m=C3=A1s efectiva. </sp= an></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; = line-height:150%"><span>Tambi=C3=A9n, se identificaron factores clave que c= ontribuyen al =C3=A9xito de esta estrategia, como el acceso a materiales ed= ucativos de calidad, la disponibilidad de tecnolog=C3=ADa, la gesti=C3=B3n = eficiente del tiempo en clase, la participaci=C3=B3n activa de los estudian= tes, la retroalimentaci=C3=B3n oportuna, y el apoyo institucional, entre ot= ros. </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:= justify; line-height:150%"><span>En el estudio realizado por Delgado & = Cuj=C3=AD (2023) refiere que =E2=80=9Cla aplicaci=C3=B3n del modelo tradici= onal aplicado en instituciones educativas en el primer trimestre result=C3= =B3 un fracaso, mientras que en el segundo trimestre se les aplicaron t=C3= =A9cnicas de Flipped Classroom asociados a los estilos de aprendizaje (aula= invertida)=E2=80=9D y se apreci=C3=B3 un cambio favorable, en el que se pr= oduce efectivamente la formaci=C3=B3n y el desarrollo del estudiante. Lo an= terior concuerda con la efectividad y utilizaci=C3=B3n del aula invertida y= a que facilita la comprensi=C3=B3n de conceptos t=C3=A9cnicos y un aprendiz= aje m=C3=A1s profundo.</span></p><p style=3D"margin-bottom:0pt; text-indent= :0pt; text-align:justify; line-height:150%"><span>La hip=C3=B3tesis de la i= nvestigaci=C3=B3n sostiene que la aplicaci=C3=B3n de esta metodolog=C3=ADa = did=C3=A1ctica contribuir=C3=A1 al desarrollo de competencias y habilidades= t=C3=A9cnicas esenciales de los estudiantes que cursan la especialidad =E2= =80=9CMecanizado y construcciones met=C3=A1licas=E2=80=9D.</span></p><p sty= le=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:1= 50%"><span>El objetivo de este estudio es la implementaci=C3=B3n de la estr= ategia did=C3=A1ctica, aula invertida para mejorar el desempe=C3=B1o de los= estudiantes del bachillerato t=C3=A9cnico de la Unidad Educativa =E2=80=9C= General Medardo Alfaro=E2=80=9D. </span></p><p style=3D"margin-bottom:0pt; = text-indent:0pt; text-align:justify; line-height:150%"><span> </span><= /p><p class=3D"ListParagraph" style=3D"margin-left:54pt; margin-bottom:0pt;= text-indent:-18pt; text-align:justify; line-height:150%"><span style=3D"fo= nt-style:italic"><span>1.1.</span></span><span style=3D"font-weight:bold"> = </span><span style=3D"font-style:italic">Estrategias did=C3=A1cticas </span= ></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; li= ne-height:150%"><span style=3D"font-weight:bold"> </span></p><p style= =3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:150= %"><span>Seg=C3=BAn De Jes=C3=BAs (2024) =E2=80=9Clas estrategias did=C3=A1= cticas son los medios y recursos que aplican maestros y alumnos como soport= es pedag=C3=B3gicos para el logro de los prop=C3=B3sitos de aprendizaje=E2= =80=9D. Estas posibilitan el logro de la competencia comunicativa y son un = componente de gran trascendencia en los procesos de ense=C3=B1anza-aprendiz= aje. Las estrategias utilizadas por los estudiantes deben estar estrechamen= te relacionadas con las estrategias de ense=C3=B1anza que aplican los docen= tes.</span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:j= ustify; line-height:150%"><span style=3D"background-color:#ffff00">Jim=C3= =A9nez (2022)</span><span> destaca la importancia de =E2=80=9Ccomprender y = utilizar estrategias de ense=C3=B1anza como elementos clave para alcanzar a= prendizajes significativos=E2=80=9D. Sostiene que el dise=C3=B1o y la imple= mentaci=C3=B3n de estas estrategias deben centrarse en promover la comunica= ci=C3=B3n efectiva y la apropiaci=C3=B3n del conocimiento.</span></p><p sty= le=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:1= 50%"><span style=3D"background-color:#ffff00">Caballero & Quivio (2024)= </span><span> analizaron la implementaci=C3=B3n efectiva de tecnolog=C3=ADa= s en la educaci=C3=B3n, sosteniendo que =E2=80=9Csu integraci=C3=B3n puede = tener un impacto considerable en la calidad del aprendizaje=E2=80=9D. Ellos= sugieren que las estrategias did=C3=A1cticas deben ajustarse a un contexto= digital para promover un aprendizaje m=C3=A1s interactivo. </span></p><p s= tyle=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-height= :150%"><span>A partir del an=C3=A1lisis de los aportes realizados por estos= autores, se puede concluir que las estrategias did=C3=A1cticas son un comp= onente esencial del proceso educativo que debe ser flexible y adaptativo. L= a necesidad de actualizar continuamente estas estrategias es fundamental pa= ra responder a las cambiantes din=C3=A1micas del aula y a las diversas nece= sidades de los estudiantes.</span></p><p style=3D"margin-bottom:0pt; text-i= ndent:0pt; text-align:justify; line-height:150%"><span> </span></p><p = class=3D"ListParagraph" style=3D"margin-left:54pt; margin-bottom:0pt; text-= indent:-18pt; text-align:justify; line-height:150%"><span style=3D"font-sty= le:italic"><span>1.2.</span></span><span style=3D"font-weight:bold"> </span= ><span style=3D"font-style:italic">Acciones educativas</span></p><p style= =3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:150= %"><span style=3D"font-weight:bold"> </span></p><p style=3D"margin-bot= tom:0pt; text-indent:0pt; text-align:justify; line-height:150%"><span>Las a= cciones educativas contribuyen a la adquisici=C3=B3n de competencias y habi= lidades t=C3=A9cnicas necesarias para su inserci=C3=B3n en el mercado labor= al.</span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:ju= stify; line-height:150%"><span>Quinteros-Pallarozo & C=C3=A1rdenas-Cord= ero (2021) refieren que =E2=80=9Clas acciones pedag=C3=B3gicas pueden defin= irse como un proceso integral en el que intervienen docentes, estudiantes y= el entorno", que act=C3=BAa como un est=C3=ADmulo constante=E2=80=9D. A tr= av=C3=A9s de estas acciones, se promueven valores fundamentales, se educan = las emociones y se gu=C3=ADa el aprendizaje de manera que los estudiantes p= uedan adquirir conocimientos significativos y relevantes. Este enfoque no s= olo busca la transmisi=C3=B3n de informaci=C3=B3n, sino que tambi=C3=A9n se= centra en el desarrollo integral del estudiante, fomentando un ambiente de= aprendizaje enriquecedor y din=C3=A1mico.</span></p><p style=3D"margin-bot= tom:0pt; text-indent:0pt; text-align:justify; line-height:150%"><span>Las a= cciones educativas consisten en intervenciones dise=C3=B1adas con el prop= =C3=B3sito de facilitar un aprendizaje significativo y adaptarse a las nece= sidades de los estudiantes. =E2=80=9CEste enfoque integral es esencial para= enfrentar la diversidad y la complejidad del entorno educativo contempor= =C3=A1neo=E2=80=9D, como se destaca en la investigaci=C3=B3n de Barros Maca= s et al. (2024). </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt;= text-align:justify; line-height:150%"><span>Los autores citados ofrecen pe= rspectivas complementarias sobre las acciones educativas. Quinteros-Pallaro= zo & C=C3=A1rdenas-Cordero</span><span style=3D"background-color:#ffff0= 0"> (2021)</span><span> refieren la interacci=C3=B3n y el desarrollo emocio= nal dentro del proceso educativo mientras Barros Macas</span><span style=3D= "background-color:#ffff00"> et al. (2024)</span><span> destacan la importan= cia de la planificaci=C3=B3n y la adaptabilidad. </span></p><p style=3D"mar= gin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:150%"><spa= n>La implementaci=C3=B3n de la metodolog=C3=ADa de aula invertida en clases= permiti=C3=B3 mejorar el rendimiento acad=C3=A9mico y competencias t=C3=A9= cnicas de los estudiantes del bachillerato t=C3=A9cnico cuando se compara c= on el modelo tradicional. Por los resultados alcanzados, pudiera valorarse = la implementaci=C3=B3n de esta estrategia en otras instituciones educativas= y para el dise=C3=B1o de pol=C3=ADticas educativas m=C3=A1s efectivas.</sp= an></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; = line-height:150%"><span> </span></p><h1 style=3D"margin-top:0pt; margi= n-left:54pt; text-indent:-18pt; text-align:justify; line-height:150%"><span= ><span>2.</span></span><span style=3D"width:9pt; font:7pt 'Times New Roman'= ; display:inline-block">      </span><span>Metodol= og=C3=ADa</span></h1><p style=3D"margin-bottom:0pt; line-height:150%"><span= > </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-alig= n:justify; line-height:150%"><span>El presente estudio se desarroll=C3=B3 e= n el per=C3=ADodo lectivo 2024-2025 en la </span><span style=3D"text-decora= tion:underline">Unidad Educativa =E2=80=9CGeneral Medardo Alfaro=E2=80=9D,<= /span><span> ubicada en la ciudad de Santo Domingo de los Colorados, provin= cia de Santo Domingo de los Ts=C3=A1chilas, Ecuador. La investigaci=C3=B3n = se centr=C3=B3 en evaluar la implementaci=C3=B3n de la estrategia did=C3=A1= ctica, aula invertida y su influencia en el mejoramiento en el aprendizaje = y motivaci=C3=B3n de los estudiantes. </span></p><p style=3D"margin-bottom:= 0pt; text-indent:0pt; text-align:justify; line-height:150%"><span>La poblac= i=C3=B3n total incluy=C3=B3 90 estudiantes del bachillerato t=C3=A9cnico y = 9 docentes que imparten asignaturas de la carrera t=C3=A9cnica. Para el est= udio se realiz=C3=B3 un muestreo aleatorio simple. La muestra la conformaro= n 40 estudiantes con edades entre 14 y 18 a=C3=B1os, con calificaciones aca= d=C3=A9micas entre 6 y 8,5 puntos que estudian la especialidad de =E2=80=9C= Mecanizado y construcciones met=C3=A1licas=E2=80=9D en la instituci=C3=B3n.= </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:just= ify; line-height:150%"><span>Se emple=C3=B3 un dise=C3=B1o cuasi-experiment= al, se trabaj=C3=B3 con dos grupos, uno experimental y otro control. El est= udio realizado tuvo un enfoque mixto, en el cual se combinaron m=C3=A9todos= cuantitativos y cualitativos.</span><span>  </span><span>Se emple=C3= =B3 tambi=C3=A9n, el m=C3=A9todo cient=C3=ADfico, que permiti=C3=B3 seguir = esquem=C3=A1ticamente el proceso de investigaci=C3=B3n, analizar detalladam= ente el problema cient=C3=ADfico, el objetivo y con ello arribar a las conc= lusiones y recomendaciones. </span></p><p style=3D"margin-bottom:0pt; text-= indent:0pt; text-align:justify; line-height:150%"><span>Se utiliz=C3=B3 la = entrevista a docentes y la observaci=C3=B3n a los estudiantes, permitiendo = identificar las carencias de los estudiantes en su aprendizaje; entre ellas= : falta de autonom=C3=ADa en el estudio, limitaciones en la aplicaci=C3=B3n= pr=C3=A1ctica de los conocimientos, la comprensi=C3=B3n de determinados co= ntenidos, la resoluci=C3=B3n de problemas, la comunicaci=C3=B3n y la relaci= =C3=B3n entre docentes y estudiantes y entre los mismos compa=C3=B1eros de = aula. </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align= :justify; line-height:150%; font-size:16pt"><span style=3D"line-height:150%= ; font-size:12pt">Se aplic=C3=B3 una encuesta a los estudiantes despu=C3=A9= s de aplicadas las acciones educativas. Permiti=C3=B3</span><span> </span><= span style=3D"line-height:150%; font-size:12pt">conocer acerca de la utilid= ad que represent=C3=B3 el empleo de la estrategia, aula invertida en su apr= endizaje y lo que represent=C3=B3 para desempe=C3=B1arse mejor en la especi= alidad t=C3=A9cnica.</span></p><p style=3D"margin-bottom:0pt; text-indent:0= pt; text-align:justify; line-height:150%"><span>Para el procesamiento de lo= s datos recopilados, se utiliz=C3=B3 la estad=C3=ADstica descriptiva median= te el c=C3=A1lculo de la frecuencia y el porcentaje, lo que facilit=C3=B3 l= a descripci=C3=B3n de los datos para luego analizarlos y relacionarlos entr= e s=C3=AD y arribar a conclusiones.</span></p><p style=3D"margin-bottom:0pt= ; text-indent:0pt; text-align:justify; line-height:150%"><span>Se aplicaron= las acciones educativas en las sesiones de clases seg=C3=BAn la planificac= i=C3=B3n del docente.</span></p><p style=3D"margin-bottom:0pt; text-indent:= 0pt; text-align:justify; line-height:150%"><span> </span></p><p style= =3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:150= %"><span> </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; t= ext-align:justify; line-height:150%"><span> </span></p><p style=3D"mar= gin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:150%"><spa= n> </span></p><p class=3D"ListParagraph" style=3D"margin-left:54pt; ma= rgin-bottom:0pt; text-indent:-18pt; text-align:justify; line-height:150%"><= span style=3D"font-weight:bold"><span>3.</span></span><span style=3D"width:= 9pt; font:7pt 'Times New Roman'; display:inline-block">   &#= xa0;  </span><span style=3D"font-weight:bold">Resultados </span></p><p= style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-heig= ht:150%"><span>Entre los problemas identificados mediante la observaci=C3= =B3n a los estudiantes en las actividades acad=C3=A9micas y en las pr=C3=A1= cticas, se encuentran: falta de estrategias de aprendizaje aut=C3=B3nomo, d= ificultad para aplicar conceptos te=C3=B3ricos en la pr=C3=A1ctica, baja pa= rticipaci=C3=B3n en actividades colaborativas, escasa motivaci=C3=B3n hacia= el aprendizaje t=C3=A9cnico, `poca conexi=C3=B3n entre el contenido te=C3= =B3rico y su aplicaci=C3=B3n en el entorno laboral.</span></p><p style=3D"m= argin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:150%"><s= pan>  </span></p><p class=3D"APA7MAEDICION" style=3D"margin-left:54pt;= margin-bottom:0pt; text-indent:-18pt; line-height:150%"><span style=3D"fon= t-style:italic"><span>3.1.</span></span><span style=3D"color:#ff0000"> </sp= an><span style=3D"font-style:italic">Aplicaci=C3=B3n de las acciones educat= ivas</span></p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-= indent:0pt; line-height:150%"><span>Se implementaron diversas acciones educ= ativas con el prop=C3=B3sito de mejorar el desempe=C3=B1o de los estudiante= s mediante la metodolog=C3=ADa del aula invertida como se muestra en la </s= pan><span style=3D"font-weight:bold">tabla 1</span><span>.</span></p><p cla= ss=3D"Caption" style=3D"margin-bottom:0pt; text-align:center; page-break-af= ter:avoid; line-height:150%; font-size:12pt"><span style=3D"font-family:'Ti= mes New Roman'; font-weight:bold; font-style:normal; color:#000000"> <= /span></p><p class=3D"Caption" style=3D"margin-bottom:0pt; text-align:cente= r; page-break-after:avoid; line-height:150%; font-size:12pt"><span style=3D= "font-family:'Times New Roman'; font-weight:bold; font-style:normal; color:= #000000">Tabla 1</span></p><p class=3D"Caption" style=3D"margin-bottom:0pt;= text-align:center; page-break-after:avoid; line-height:150%; font-size:12p= t"><span style=3D"font-family:'Times New Roman'; color:#000000">Acciones ed= ucativas del aula invertida</span></p><table style=3D"width:461.85pt; margi= n-bottom:0pt; padding:0pt; border-collapse:collapse"><tr style=3D"height:17= .55pt"><td style=3D"width:87.3pt; border-top:0.75pt solid #7f7f7f; border-b= ottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style= =3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><= a id=3D"_Hlk192175293"><span>Acciones educativas</span></a></p></td><td sty= le=3D"width:157.4pt; border-top:0.75pt solid #7f7f7f; border-bottom:0.75pt = solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bo= ttom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Descripc= i=C3=B3n</span></p></td><td style=3D"width:184.75pt; border-top:0.75pt soli= d #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-= align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%= ; font-size:10pt"><span>Ventajas</span></p></td></tr><tr style=3D"height:52= .5pt"><td style=3D"width:87.3pt; border-top:0.75pt solid #7f7f7f; border-bo= ttom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style= =3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><= span>Lecciones pre-grabadas (videos educativos)</span></p></td><td style=3D= "width:157.4pt; border-top:0.75pt solid #7f7f7f; border-bottom:0.75pt solid= #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:= 0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>El maestro gr= ab=C3=B3 las lecciones en video que los estudiantes deben ver antes de la c= lase. </span></p></td><td style=3D"width:184.75pt; border-top:0.75pt solid = #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-al= ign:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; = font-size:10pt"><span>Los estudiantes pueden ver los videos a su propio rit= mo, pausar y retroceder para mejorar la comprensi=C3=B3n.</span></p></td></= tr><tr style=3D"height:53.35pt"><td style=3D"width:87.3pt; padding:0pt 5.4p= t; vertical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line= -height:150%; font-size:10pt"><span>Lecturas o materiales de estudio en l= =C3=ADnea</span></p></td><td style=3D"width:157.4pt; padding:0pt 5.4pt; ver= tical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-heigh= t:150%; font-size:10pt"><span>Los estudiantes leyeron art=C3=ADculos, inves= tigaciones antes de la clase, junto con foros.</span></p></td><td style=3D"= width:184.75pt; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-b= ottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Promuev= e el aprendizaje aut=C3=B3nomo y prepara a los estudiantes para interaccion= es m=C3=A1s efectivas en clase.</span></p></td></tr><tr style=3D"height:64.= 1pt"><td style=3D"width:87.3pt; border-top:0.75pt solid #7f7f7f; border-bot= tom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style= =3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><= span>Tareas colaborativas y resoluci=C3=B3n de problemas</span></p></td><td= style=3D"width:157.4pt; border-top:0.75pt solid #7f7f7f; border-bottom:0.7= 5pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margi= n-bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Dura= nte la clase, los estudiantes trabajaron en actividades pr=C3=A1cticas grup= ales.</span></p></td><td style=3D"width:184.75pt; border-top:0.75pt solid #= 7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-ali= gn:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; f= ont-size:10pt"><span>Fomenta el trabajo en equipo, el aprendizaje colaborat= ivo y la construcci=C3=B3n del conocimiento en interacci=C3=B3n con otros. = (Guerrero, 2023)</span></p></td></tr><tr style=3D"height:46.1pt"><td style= =3D"width:87.3pt; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin= -bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Discu= si=C3=B3n guiada y resoluci=C3=B3n de dudas</span></p></td><td style=3D"wid= th:157.4pt; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-botto= m:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Durante la = clase, el docente facilit=C3=B3 la discusi=C3=B3n y aclar=C3=B3 dudas sobre= el material previo.</span></p></td><td style=3D"width:184.75pt; padding:0p= t 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt= ; line-height:150%; font-size:10pt"><span>Los estudiantes tienen acceso al = docente para resolver dudas y aplicar el conocimiento a situaciones m=C3=A1= s complejas.</span></p></td></tr><tr style=3D"height:50.4pt"><td style=3D"w= idth:87.3pt; border-top:0.75pt solid #7f7f7f; border-bottom:0.75pt solid #7= f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt= ; text-indent:0pt; line-height:150%; font-size:10pt"><span>Evaluaciones for= mativas y feedback inmediato</span></p></td><td style=3D"width:157.4pt; bor= der-top:0.75pt solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0= pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0p= t; line-height:150%; font-size:10pt"><span>Cuestionarios interactivos para = evaluar la comprensi=C3=B3n de los estudiantes antes o despu=C3=A9s de las = lecciones.</span></p></td><td style=3D"width:184.75pt; border-top:0.75pt so= lid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertica= l-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:15= 0%; font-size:10pt"><span>Feedback instant=C3=A1neo para corregir errores y= consolidar lo aprendido antes de la siguiente clase (Huanca et al., 2024)<= /span></p></td></tr><tr style=3D"height:37.6pt"><td style=3D"width:87.3pt; = padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-= indent:0pt; line-height:150%; font-size:10pt"><span>Gamificaci=C3=B3n y apr= endizaje basado en juegos</span></p></td><td style=3D"width:157.4pt; paddin= g:0pt 5.4pt; vertical-align:top"><p style=3D"margin-bottom:0pt; text-indent= :0pt; line-height:150%; font-size:10pt"><span>Se us=C3=B3 plataformas educa= tivas como Kahoot y Quizizz para repasar contenido.</span></p></td><td styl= e=3D"width:184.75pt; padding:0pt 5.4pt; vertical-align:top"><p style=3D"mar= gin-bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Au= menta la motivaci=C3=B3n y el compromiso, haciendo el aprendizaje m=C3=A1s = divertido y participativo.</span></p><p style=3D"margin-bottom:0pt; text-in= dent:0pt; line-height:150%; font-size:10pt"><span> </span></p></td></t= r><tr style=3D"height:52.55pt"><td style=3D"width:87.3pt; border-top:0.75pt= solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vert= ical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height= :150%; font-size:10pt"><span>Proyectos de investigaci=C3=B3n y presentacion= es</span></p></td><td style=3D"width:157.4pt; border-top:0.75pt solid #7f7f= 7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:t= op"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; font-= size:10pt"><span>Los estudiantes investigaron temas t=C3=A9cnicos de forma = aut=C3=B3noma y los presentaron mediante exposiciones.</span></p></td><td s= tyle=3D"width:184.75pt; border-top:0.75pt solid #7f7f7f; border-bottom:0.75= pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style=3D"margin= -bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Fomen= ta la autonom=C3=ADa, el pensamiento cr=C3=ADtico y las habilidades de comu= nicaci=C3=B3n, aplicando conocimientos de manera pr=C3=A1ctica.</span></p><= /td></tr><tr style=3D"height:65.45pt"><td style=3D"width:87.3pt; border-bot= tom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p style= =3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><= span>Aprendizaje basado en problemas.</span></p></td><td style=3D"width:157= .4pt; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align= :top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; fon= t-size:10pt"><span>Resolvieron problemas complejos en grupo usando los cono= cimientos adquiridos previamente, con el docente.</span></p></td><td style= =3D"width:184.75pt; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; = vertical-align:top"><p style=3D"margin-bottom:0pt; text-indent:0pt; line-he= ight:150%; font-size:10pt"><span>Desarrolla habilidades clave como la resol= uci=C3=B3n de problemas, trabajo en equipo y aplicaci=C3=B3n pr=C3=A1ctica = del conocimiento.</span></p></td></tr></table><p style=3D"margin-bottom:0pt= ; text-indent:0pt; text-align:justify; line-height:150%; font-size:11pt"><s= pan> </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-a= lign:justify; line-height:150%"><span>La aplicaci=C3=B3n de las acciones ed= ucativas dentro del aula invertida permiti=C3=B3 potenciar el aprendizaje d= e los estudiantes a trav=C3=A9s de estrategias activas y colaborativas (San= dobal et al., 2021). El uso de lecciones pre-grabadas y lecturas en l=C3=AD= nea foment=C3=B3 la autonom=C3=ADa, permitiendo que los estudiantes se prep= araran antes de las clases. Durante las sesiones presenciales, se llevaron = a cabo tareas colaborativas, discusiones guiadas y aprendizaje basado en pr= oblemas, lo que facilit=C3=B3 la construcci=C3=B3n conjunta del conocimient= o y la aplicaci=C3=B3n pr=C3=A1ctica de los conceptos t=C3=A9cnicos. (Eller= ani & Patera, 2021)</span></p><p style=3D"margin-bottom:0pt; text-inden= t:0pt; text-align:justify; line-height:150%"><span>Adem=C3=A1s, la integrac= i=C3=B3n de evaluaciones formativas con feedback inmediato ayud=C3=B3 a con= solidar lo aprendido, mientras que el uso de gamificaci=C3=B3n con platafor= mas como Kahoot y Quizizz increment=C3=B3 la motivaci=C3=B3n y el compromis= o. Finalmente, el desarrollo de proyectos de investigaci=C3=B3n y presentac= iones fortaleci=C3=B3 la autonom=C3=ADa y las habilidades de comunicaci=C3= =B3n, asegurando que =E2=80=9Clos estudiantes no solo comprendieran los con= tenidos, sino que tambi=C3=A9n pudieran aplicarlos en contextos reales=E2= =80=9D </span><span style=3D"background-color:#ffff00">(=C3=81lvarez et al.= , 2024)</span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-alig= n:justify; line-height:150%"><span> </span></p><p class=3D"APA7MAEDICI= ON" style=3D"margin-left:54pt; margin-bottom:0pt; text-indent:-18pt; line-h= eight:150%"><span style=3D"font-style:italic"><span>3.2.</span></span><span= style=3D"font-weight:bold"> </span><span style=3D"font-style:italic">Resul= tados de la entrevista a los docentes</span></p><p><span> </span></p><= p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line= -height:150%"><span>Los resultados de la entrevista a los docentes proporci= onan una visi=C3=B3n valiosa sobre la implementaci=C3=B3n del aula invertid= a en el aula. Las opiniones var=C3=ADan en varios aspectos clave de esta me= todolog=C3=ADa, reflejando tanto los beneficios percibidos como las =C3=A1r= eas de mejora. A continuaci=C3=B3n, se presentan las respuestas a las pregu= ntas realizadas.</span></p><p class=3D"APA7MAEDICION" style=3D"margin-botto= m:0pt; text-indent:0pt; line-height:150%"><span style=3D"font-weight:bold">= Pregunta 1: =C2=BFConsidera que el aula invertida mejora la interacci=C3=B3= n con los estudiantes?</span></p><p class=3D"APA7MAEDICION" style=3D"margin= -bottom:0pt; text-indent:0pt; line-height:150%"><span>Un 70% de los docente= s considera que el aula invertida mejora la interacci=C3=B3n con los estudi= antes. Esto sugiere que la metodolog=C3=ADa fomenta un ambiente m=C3=A1s pa= rticipativo y colaborativo, donde los estudiantes se sienten m=C3=A1s c=C3= =B3modos al expresar sus ideas y elaborar preguntas ante las dudas. Sin emb= argo, un 30% de los docentes manifiesta que la interacci=C3=B3n no ha resul= tado significativamente, lo que podr=C3=ADa indicar =C3=A1reas de mejoras d= onde se puede trabajar para involucrar a=C3=BAn m=C3=A1s a los estudiantes.= </span></p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-inde= nt:0pt; line-height:150%"><span style=3D"font-weight:bold">Pregunta 2: =C2= =BFCree que la metodolog=C3=ADa fomenta un aprendizaje m=C3=A1s din=C3=A1mi= co?</span></p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-i= ndent:0pt; line-height:150%"><span>El 75% de los docentes cree que la metod= olog=C3=ADa fomenta un aprendizaje m=C3=A1s din=C3=A1mico. Este porcentaje = positivo respalda la idea de que el aula invertida permite a los estudiante= s participar de manera activa en su propio proceso de aprendizaje, transfer= ir sus aprendizajes, lo que puede aumentar la motivaci=C3=B3n y la comprens= i=C3=B3n de los conceptos y contenidos. La percepci=C3=B3n de un aprendizaj= e m=C3=A1s din=C3=A1mico puede ser fundamental para el desarrollo de nuevas= estrategias did=C3=A1cticas.</span></p><p class=3D"APA7MAEDICION" style=3D= "margin-bottom:0pt; text-indent:0pt; line-height:150%"><span style=3D"font-= weight:bold">Pregunta 3: =C2=BFSiente que necesita capacitaci=C3=B3n para i= mplementar esta estrategia?</span></p><p class=3D"APA7MAEDICION" style=3D"m= argin-bottom:0pt; text-indent:0pt; line-height:150%"><span>Un 30% de los do= centes expresa la necesidad de capacitaci=C3=B3n para implementar esta estr= ategia. Este resultado se=C3=B1ala que, aunque muchos docentes est=C3=A1n a= biertos a la metodolog=C3=ADa, hay una fracci=C3=B3n significativa que podr= =C3=ADa beneficiarse de formaci=C3=B3n adicional. Esto lleva organizar e im= partir talleres, cursos o recursos que les ayuden a sentirse mejor preparad= os y competentes al aplicar el aula invertida en sus clases.</span></p><p c= lass=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-he= ight:150%"><span style=3D"font-weight:bold">Pregunta 4: =C2=BFRecomendar=C3= =ADa esta metodolog=C3=ADa a otros docentes?</span></p><p class=3D"APA7MAED= ICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span= >Finalmente, el 65% de los docentes recomendar=C3=ADa la metodolog=C3=ADa a= otros colegas. Aunque este porcentaje es mayoritario, tambi=C3=A9n sugiere= que hay un 35% que puede no estar completamente convencido de la efectivid= ad del aula invertida. Esta informaci=C3=B3n es valiosa para identificar ba= rreras o dudas que algunos docentes puedan tener sobre la implementaci=C3= =B3n de esta metodolog=C3=ADa como se muestra en la </span><span style=3D"f= ont-weight:bold">figura 1</span><span>.</span></p><p class=3D"Caption" styl= e=3D"margin-bottom:0pt; text-align:center; page-break-after:avoid; line-hei= ght:150%; font-size:12pt"><span style=3D"font-family:'Times New Roman'; fon= t-weight:bold; font-style:normal; color:#000000">Figura 1</span></p><p clas= s=3D"Caption" style=3D"margin-bottom:0pt; text-align:center; page-break-aft= er:avoid; line-height:150%; font-size:12pt"><span style=3D"font-family:'Tim= es New Roman'; color:#000000">Resultado de la entrevista a los docentes.</s= pan></p><p style=3D"margin-bottom:0pt; line-height:150%"><img src=3D"data:i= mage/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgQAAAC2CAYAAACmn5XBAAAABHNCSVQICAg= IfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzt3X9cVPed7/HXMAPIj5GAv0hUjE= xEDVaNYE1IVoz5df2RbjU27gI3u6ss6+61dX0kuffuJnbb3ptko4t5PG5pNQs2Ni2kW5WyivZGK= tcYSioKCmoURSOJQVRQBAFhhjn3DxRFMYIC84P38/GYJMyZc+Z7Jj48bz6f7/mO6dixYwYiIiIy= oFkAxo8f7+pxiIiIiIuUl5fj4+pBiIiIiOspEIiIiIgCgYiIiCgQiIiICAoEIiIiggKBiIiIoEA= gIiIiKBCIiIgICgQiIiKCAoGIiIigQCAiIiIoEIiIiAgKBCIiIoICgYiIiKBAICIiIigQiIiICA= oEIiIiggKBiIiIoEAgIiIiKBCIiIgICgQiIiKCAoGIiIgAFlcPQERut72s6a6vmTc5EIDpP8nr1= jH3/fC5+xqTiHg3BQIRF+rOhb+33Ck4KCiICCgQiPSr/gwA3XVrUFBAEBmYFAhE+pA7BoC7uTkg= KByIDBwKBCK9zBNDwJ0oHIgMHAoEIr3Em4JAVxQORLybAoHIffD2EHAn18OBgoGI91AgELkHAzU= I3ErBQMR7KBCI9ICCQNcUDEQ8nwKBSDcoCHSPgoGI59LSxSJ3oTDQc91dPVFE3IcqBCJ3oCBwf1= QtEPEsqhCI3GJ7WZPCQC9StUDEMygQiNxEQaBvTP9JnoKBiJtTIBC5RmGg7ykUiLgvBQIZ8NQi6= F8KBSLuSYFABjQFAddQC0HE/SgQyIClMOB6CgUi7kOBQAYkhQH3oVAg4h4UCGTAURhwPwoFIq6n= QCADisKA+1IoEHEtBQIZMBQG3J9CgYjrKBDIgKAw4DkUCkRcQ4FAvJ7CgOdRKBDpfwoE4tUUBjy= XQoFI/9K3HYrXUhjwfNN/kqdvS/QiGRkZ5Ofnd/zs6+tLREQEc+bMIS4uzoUj6x1Xrlzhxz/+Me= fPn8dut/P222/z8MMPu3pY3aYKgXglhQHvoUqB90hOTmbp0qUAJCUl8d577+FwOEhLS+P48eMuH= t0NhmGQm5vb4/2Cg4NZs2YNL7zwQh+Mqu8pEIjXURjwPgoF3iksLIwpU6YAcOrUKReP5obdu3dT= Wlrq6mH0O7UMxKsoDHgvtQ/cW1eh7W7/v+rq6jouvJGRkeTm5pKVlcWwYcNITEwkMzOTxMRErFY= rmZmZ1NXVkZCQQFxcHIZhkJOTw65du7h48WLHMWfOnMmePXuYMGECiYmJrFq1CoC1a9cSHh5Odn= Y2mzdvZvTo0cyYMYO8vDyefPJJkpKSgPYwkJ6eDkBCQgLvvPMORUVFFBUVceHCBSZPnkxKSgrBw= cG98rm5E1UIRESk32VmZrJy5UosFgsrVqwgKiqK+fPnM2bMGOrq6rBarYwbN476+npWr17NggUL= eP3111m3bh01NTXs27ePTZs2sWjRItauXQtASkoKy5YtIzAwEACbzcb8+fM7ve/ChQsJDQ2lqqq= KqVOnEhsby44dO6itrQVg1qxZmM1moqOjycrKwt/fn/z8fJKTk1m+fDn79++nuLi4fz+sfqIKgX= gNVQe8n6oE3iMxMZG5c+d2uc3pdBIVFcXEiRMpLCykpaWF1NTUju0nT57EMAwALJYbl7Hq6upuv= /+oUaOIjIzk4MGDAFy9erXL14WHh5OWlkZBQQFnzpwBoLW1tdvv40kUCMQrKAwMHAoF3i8sLAyz= 2QyA3W4H4I033iA6OrrjNW1tbSxevJj333+fgIAAnn766Y5qgI9Pz4vf1wPGrex2O6mpqURGRhI= bG8v27dt7fGxPoUAgHk9h4A7a7ATu+TdMhrPjKadlEM1P/gBaGvCv2IXPlXPYxzyB/aFpmEym9h= c1XcS//PfQZqd1wlyM4OEd+5saa7Cc/xz72Jn9fTadKBQMHDabDYCtW7cSERFBTU0NwcHBhIWFc= fr0adavX09QUFCnfaxWK/X19TQ0NHDixIkev6fFYqGpqQnDMDh06BBlZWXExMRw+PBhABwOxx33= bWtr65jTUFdX1+P3diXz8uXLfzR06FBXj0Pknp04Z++zYxuGweljB/jTzo/Ys20jE6bNxNdvEJd= rz/HT//kyhb/PpPD3mZypOMykGc9y6UIVWz94h9I/7uDBMeMJsj7Qcaza6i858GkuEeMm98rYok= b4ApD+Sdezs02NNfh93bnX6XhoKo4hNgIObcYZGkHrI88ScPAjnIMfxAgcAoBf+e8xrOE4g4bhd= 2Y/9vDJmEwmjDY7fqc+wT42HnzMvXIO9yMl3ubqIchNUuJttz1ulZGRQXZ2NgBlZWWcP3+e6dOn= d2zPzc2loKCApqYmampqiI2NZfDgwYSHh1NcXMzOnTux2WxERUVRWVnJhx9+yLZt29iyZQt5eXn= U19czadIkQkJCKCws5MiRIwQFBVFdXU1lZSXx8fFkZ2dTUlLC5cuXaWlpIScnB2hvQ8yePRtob1= kcOHCAqqoqpk2bRklJCY2NjcTHx1NRUUFTUxMxMTGd2hXQHhReeeUVvvrqKwD++Mc/EhQUxCOPP= NInn3lvqq2txXTs2DFj/Pjxrh6LyD3py+qAw95K/pb3qTx+kLg5CUQ8MgVraHt4PrJvFzt+daOn= +dzL/42pT81j6wf/StjwkVj8/Dl9tJjF3/9XTCYTDnsreZt+xjMvLcPPP6BXxjdvcvvEqTvdkud= TexLD34ozcAgmHzPmM8UQEILTL5jAfRu4+q1FtA0bT8Cn79EWZqM1+jsYbQ6C9qymdcI8DLMfgw= 5n0/jUSvALxPervbQNHoUzZGSvjL83qEowcNntdt56663b1i9Ys2YNI0e6z59RT1FeXq6WgXiuv= m4VFO3azLEDe/ir//EzQsKGd9rWcKmG1//Pjk7PORx2jpcW8MJfrMDPfxCfVhyiubGewOAQDhZs= Z2rc3F4LA93hHNL+G9q1RgC+NeVcnfQS5tqTABjXt5h9MdedvvYqA1MXvVRTQzVGmwPDx8Kg/R+= AxZ+WqDkYgaF9exJ3odbBwFVaWkpQUBDp6ekEBARw7tw53n33Xa+8HbC/KBCIdKGx/hKF/zeLoe= ERbFn/L1gfGMIzLy0jbMQomhvr+ezjjzh5pIjw0eN4dPpsHhwTBYaB4bzWr7/WjzeZTJw7cwqHw= 47Z15dfp67EPyCQ515ezgNDH+y38zE1XcTpHwIWf3C0dBqjAZhbGjCcTkxmXxxDx2FquoTJ15+2= 0DEYPhb8zuynZdzzDCr9DY7hj2KyN+F78v/R+q2F/XYOIjeLiIjAx8eH1157jebmZmw2G0uWLCE= kJMTVQ/NYCgTikfq6OnC28jiG00nMrAVEjJvML97+O3ZtWc/3/uF/8/Wpz3HYW6n64ihVXxylZM= 9W5iS9yqRvP4Nt0gzqas/iPyiIiHFTMFt8Kdnznzzz0jI2r/sh4x/7M5ob69mzbSPf+Zt/6tNzu= Jn50hc4rlUMsPh12mZytuH0C8Z0bWZ2q202fsd2YMKgZfwc/L7ej31ULCanA8vlr3CMng4Wf3y/= /IyWNgcms2v/GlGVYGAaPnw4r776qquH4VW0MJFIF642NQDgNyiAkCEjGDsxltPHSnDYW3nkW4+= zMjWHZT/5Fd9NXsVDYyeyN++3AMT/+RLOVBymouwzZr/0d5Ts2ca0mX+Ow97K16eOMDhsOKFDH+= J46R9xOPpuMuStLOeP4nwgAgBnQHuZ//rdByajjbbQhzteawQNpSXmFa7G/BWmNjuGyYxhDe/6w= NfvTHAxLW0scv9UIRCP0x+3GQYNbr9oNl5uv30oIMiKr38APtdm11t8/bA+MATrA08wJDyCXZvX= ATBkxGj+csVqAM6eLsdi8WXEqEiarly+7T1M9M/F1NRYi+EXDH7tkxCN4HDaQkbhc+UcbcEjMNm= bcTz4rdt3dLRiqTpAS9QLmADDN4C2ByLwuVoHrc20DX8UkxvcbSAivUMVAvEo/bXmwMjIRwkdNp= KTR/bS3FjPhbOVTJv5Ij5mM6ePlbDxX/+BYwc+pbXlKhe+PsWfvfjXnfZvbWnmYOEOpj41D4CAo= MGMfuRbXK49x6ULXzPhsZmYLf2Tx811p3EMGXfjCR8fWiZ+B5/LVQw6+BEt4+fQFjr2tv18v/wT= 9ojHMZnbb280mUy0Rv0XfM6XY75STWvkrH4Zf3epSiByf1QhEOmCn38A301+k09zf8kv3lrGxNh= ZzHjuZQBChoRjDR3GH377M8aMf4zHn1/MsIce7rT/vl1b+Pbsl7D4tvfrTSYTz37v7/n4Nz/Fz3= 8Qzy3+fr+di2NkzG3PGYGhtEz9i46fu6pV2CNvX3zIGTyMlti/7sXRiYi70DoE4jG0ImFnd1uHY= KDSBEORnisvL1fLQERERDSHQDyEqgPSXaqYiNwbBQIRERFRIBAR76MqgUjPKRCI21O7QESk7ykQ= iIiIiAKBuDdVB+ReqW0g0jMKBCIiIqJAICIiIgoE4sbULpD7pbaBSPcpEIiIiIgCgYiIiOjbDsV= NqV0gvWX6T/L0hUduIiMjg/z8/I6ffX19iYiIYM6cOcTFxblwZL2nvLycjRs3cvHiRV566SWef/= 55Vw+p21QhEBGRfpGcnMzSpUsBSEpK4r333sPhcJCWlsbx48ddPLobDMMgNze3x/s1NDSQmppKZ= WUlDQ0NbNy4kSNHjvTBCPuGAoGIiLhEWFgYU6ZMAeDUqVMuHs0Nu3fvprS0tMf7VVVV8eabb5Ke= ns706dMBuHz5cm8Pr8+oZSAiIvftiRNnb3vus3EPfuM+dXV1HRfeyMhIcnNzycrKYtiwYSQmJpK= ZmUliYiJWq5XMzEzq6upISEggLi4OwzDIyclh165dXLx4seOYM2fOZM+ePUyYMIHExERWrVoFwN= q1awkPDyc7O5vNmzczevRoZsyYQV5eHk8++SRJSUlAexhIT08HICEhgXfeeYeioiKKioq4cOECk= ydPJiUlheDg4NvOZ/z48Tc+jyeeoKSkhIkTJ/bwk3QdVQjE7Wj+gPQ23X7ofjIzM1m5ciUWi4UV= K1YQFRXF/PnzGTNmDHV1dVitVsaNG0d9fT2rV69mwYIFvP7666xbt46amhr27dvHpk2bWLRoEWv= XrgUgJSWFZcuWERgYCIDNZmP+/Pmd3nfhwoWEhoZSVVXF1KlTiY2NZceOHdTW1gIwa9YszGYz0d= HRZGVl4e/vT35+PsnJySxfvpz9+/dTXFx81/M7e/YsiYmJhIaG9vIn13dUIRARkX6XmJjI3Llzu= 9zmdDqJiopi4sSJFBYW0tLSQmpqasf2kydPYhgGABbLjctYdXV1t99/1KhRREZGcvDgQQCuXr3a= 5evCw8NJS0ujoKCAM2fOANDa2vqNx75y5Qp2u53vfve73R6PO1AgEBERtxIWFobZbAbAbrcD8MY= bbxAdHd3xmra2NhYvXsz7779PQEAATz/9dEc1wMen58Xv6wHjVna7ndTUVCIjI4mNjWX79u13PU= 5ZWRkvvfQSTqeTvXv3eswdFAoEIiLitmw2GwBbt24lIiKCmpoagoODCQsL4/Tp06xfv56goKBO+= 1itVurr62loaODEiRM9fk+LxUJTUxOGYXDo0CHKysqIiYnh8OHDADgcjjvuu3XrVv7jP/6DtLQ0= AObNm+cxgcC8fPnyHw0dOtTV4xABNH+gJ6JG+AKQ/on7zM52ZynxNlcPwaslD7He9rhVRkYG2dn= ZAJSVlXH+/PmO2fgAubm5FBQU0NTURE1NDbGxsQwePJjw8HCKi4vZuXMnNpuNqKgoKisr+fDDD9= m2bRtbtmwhLy+P+vp6Jk2aREhICIWFhRw5coSgoCCqq6uprKwkPj6e7OxsSkpKuHz5Mi0tLeTk5= ADtbYjZs2cD7S2LAwcOUFVVxbRp0ygpKaGxsZH4+HgqKipoamoiJiamU7sCYO/evWzYsKHTc/Hx= 8YwdO7ZXP+u+UFtbi+nYsWPGzTMjRVxJgaD75k1unzilCXPdo8WJvIvdbuett966bf2CNWvWMHL= kSBeNynOVl5frLgMRGRgUnLxLaWkpQUFBpKen8+tf/5rU1FSGDx/e5e2A0j2aQyAiIh4nIiICHx= 8fXnvtNZqbm7HZbCxZsoSQkBBXD81jKRCIiIjHGT58OK+++qqrh+FV1DIQERERBQIRERFRIBARE= REUCERERAQFAhEREUGBQERERFAgEBERERQIRDzOvMmBHcsWg5bkFZHeoYWJRNzMzRf77ro5FGiJ= XhG5FwoEIi5wLxf96zZvOMeipSMAeOLEWT4b92Cn7bdWDBQQRKQ7FAhE+sD9XvC/yc1h4OZ/X6e= AICL3QoFA5B7czwUf7n7Rv5PrYeCbKCCIyL1QIBC5g778Lf9e3BwGbr3of5OeBASFA5GBS4FABi= xX/ZZ/v3oSBu62v6oHInKdAoF4NXf7Lf9e3TpvoLeovSAi1ykQiEfzlgv+N+nOvIHeovaCyMClQ= CBuzVPL+r3lXucN9JZvCgiqHoh4FwUCcSs9DQCefsHvLleEga5o/oHcj4yMDPLz8zt+9vX1JSIi= gjlz5hAXF+fCkfWeS5cusWHDBioqKnjxxReZN2+eq4fUbQoE4vYGykX/Vn01b6C3aP6B9FRycjJ= jx45lw4YNJCUl8fjjj7NmzRrS0tIYOnQoUVFRrh4iAIZhsH37dubPn9/j/X7+859z5MgRADIzM5= kyZQqjRo3qi2H2OgUCcTsDNQDczN3DQFfcff6BvvPB/YSFhTFlyhQqKys5deqU2wSC3bt3U1pa2= uNA8MUXX7Bw4UL+8R//kd/97nfs2LGDxsbGPhpl71MgEHEz/TmJsC+pvTCwdBXk7/Znua6ujtLS= UgAiIyPJzc0lKyuLYcOGkZiYSGZmJomJiVitVjIzM6mrqyMhIYG4uDgMwyAnJ4ddu3Zx8eLFjmP= OnDmTPXv2MGHCBBITE1m1ahUAa9euJTw8nOzsbDZv3szo0aOZMWMGeXl5PPnkkyQlJQHtYSA9PR= 2AhIQE3nnnHYqKiigqKuLChQtMnjyZlJQUgoODbzufsWPHYjKZqK2tpbq6mokTJ2Kz2e7tA3UBf= duhiBtx9STCvvLEibOdHrfa98PnOj3E+2VmZrJy5UosFgsrVqwgKiqK+fPnM2bMGOrq6rBarYwb= N476+npWr17NggULeP3111m3bh01NTXs27ePTZs2sWjRItauXQtASkoKy5YtIzCwfS6SzWa77bf= 8hQsXEhoaSlVVFVOnTiU2NpYdO3ZQW1sLwKxZszCbzURHR5OVlYW/vz/5+fkkJyezfPly9u/fT3= FxcZfnZDKZaGxs5Pvf/z4lJSUEBgZy9erVPvwUe5cqBCJuyJvCQFc0/0ASExOZO3dul9ucTidRU= VFMnDiRwsJCWlpaSE1N7dh+8uRJDMMAwGK5cRmrrq7u9vuPGjWKyMhIDh48CHDHC3d4eDhpaWkU= FBRw5swZAFpbW+943KCgIN577z1yc3PZtWsXW7duJSEhodvjciUFAhE34YnzBnqLu88/kP4VFha= G2WwGwG63A/DGG28QHR3d8Zq2tjYWL17M+++/T0BAAE8//XRHNcDHp+fF7+sB41Z2u53U1FQiIy= OJjY1l+/btdz3WiBEjWLJkCZWVlaoQiEjPeMu8gd7S2/MP1IbwXNd78Fu3biUiIoKamhqCg4MJC= wvj9OnTrF+/nqCgoE77WK1W6uvraWho4MSJEz1+T4vFQlNTE4ZhcOjQIcrKyoiJieHw4cMAOByO= LvfLzMzk7NmzJCQkMHjwYBwOB0899VSP399VzMuXL//R0KFDXT0OkQ6PTgvm8wOeMzP3fnnrvIH= esuHilU6P5CHWTttT4m2dHumfnLrtGCnxnjOxy1M9Oi34tsetMjIyyM7OBqCsrIzz588zffr0ju= 25ubkUFBTQ1NRETU0NsbGxDB48mPDwcIqLi9m5cyc2m42oqCgqKyv58MMP2bZtG1u2bCEvL4/6+= nomTZpESEgIhYWFHDlyhKCgIKqrq6msrCQ+Pp7s7GxKSkq4fPkyLS0t5OTkAO1tiNmzZwPtLYsD= Bw5QVVXFtGnTKCkpobGxkfj4eCoqKmhqaiImJqZTuwLgypUrfPrpp/zhD3/g5MmTvPzyy0yYMKG= vPvJeVVtbi+nYsWPG+PHjXT0WkU4G0q2HA7lV0BturSDcavpP8lQh8EJ2u5233nqL48ePd3p+zZ= o1jBw50kWj8lzl5eVqGYi4ksLA/evpBEXxDqWlpQQFBZGenk5AQADnzp3j3Xff7fJ2QOkeBQIRF= 9G8gb7xTfMPxHtERETg4+PDa6+9RnNzMzabjSVLlhASEuLqoXkstQzEbXlz20DzBvqPQoHI3ZWX= l2thIhFXUhgQEXehQCDSzzRvQETckQKBuC1v7LF74zm5M7ULRLpPgUCkn2jegIi4MwUCkX6gMCA= i7k6BQNyat5XYFQb6j9oFIj2jQCDSxzSJUEQ8gQKBSB/ytgqHp1B1QKTnFAjE7fX3RbWxqY68gp= /xy+zlHD7e+Zv06uqr2bH73/hl9nIOHd/Z8ZWpdfXV5OT9Lzb/fhW1l77qNO7KykqeSv1pv56Di= EhPKRCI3MQwDPbs+wXlX+yhofECu/dmcOlyFQBtzjZ2Ff6cYUMi+e5zP+STvRs4/XUJAH86+Bse= HDaeh0fF8Mm+X3QEhdbWVpL+/QPanp/vsnMSEekOBQLxCP1VJai99CWPPfoif7v4A7495XsAtNq= bALhY9xVnL5QTFjKKEOtwAgYNpuL0n3C02Tn55V4GBw/ngcEjqDr3Oc9/LwCA2Rm/oi3+GRg0qF= /GL2oXiNwrfbmRyE2GhEZgMpm40nSR+obzRI6eztDQhwGoq2+fFOhjMgNgMftz5txhMAwMw3ntC= Kb2f5pMVFRUYNjtGBZffN9eBQEB2JOWwjDNKxAR96MKgXiM/qgSmEwmWlqb2Ljl7zl26hP8/AJx= tLUANyoFmEwdr29suoiPj4Wxo2K4fOUcDz/azGOPPYavry9/88GvaZv9ApasD3DGPo5zTCSW7N/= 0+TkMZKoOiNw7BQKRW/j7BfLKgp/y2KMvcuzkJ5SVfwyAr6Vz2d/pdBAUEIqPjw9PTEuk6txRCg= oK+MEPfsBz//5LHLNfwGS3Y64oxzlkKMbwEfiUFGHY7a44LRGRb6SWgXiURUtH9MvXIg8OHk7ct= ERq677Cbr8KQIg1HGgPAgBtTgdjHpoKQFjISLJ+uw6AuJ2fYvL1hYiHoaHh9oPfVGGQ3qPqgMj9= UYVA5Cb7yraQV/Az6uqrabU30dZm55ExMwAYFvYwDw4bT+2lSuqvnOdqSwPjI2cCN9oZzc3NmD/= ZRdusZwEwgoNxRk3Ep+Y8pvPVOGMfx2RRDhcR92M6duyYMX78eFePQ6RH+qpKcOrLfXx24CNaHc= 2MHD6RyRPmED5sXMf2yw3n+KToF9Q3nGPqo/OJHvcM30sO79j+VOpPcU5/AuPBkR3Pmb7+CvOvM= jD5+2NPSoZhw/tk7AOZqgMi96e8vFyBQDxTf7QNusMtvrSotQW/HyzF1NbW8ZQzMAj7mp+Bnz+m= mgv4/dMPOra1TYjG8eqb7T+cr8byqw1gb8XxX5Nh5OiO15nOfo3Pvs9o+86ifjuVe6VA4BkyMjL= Iz8/v+NnX15eIiAjmzJlDXFycC0fW+1paWnjzzTdZuXIlDz30kKuHc1fl5eVqGYhncrclgV36PQ= XnqjuFAQDj8afAzx8A04ljnbfFzOj4b8vvfovxSBTOydPwzfqgY0Elw96K+eNcj1hQSWHAcyQnJ= 7N06VIAkpKSeO+993A4HKSlpXH8+HEXj+4GwzDIzc29r2Ns3ryZr7/+updG1D/UzBSP1V8TDL/p= /cH1X1pkulxHy49WY4x4EJPFgs/uPBgy7Mb2S7W0pH90236G3Y5PyV4cr/wt+A/C53dH4UoDWAd= j2f0Hj1hQSWHAs4WFhTFlyhQqKys5deoUUVFRrh4SALt376a0tJT58+8tEB89epSjR4/28qj6ng= KByD1wpwqFMWkKcH1JJDAf2Id92cr2H640YM79HaayAzBmLG2P/xnGWNv1PTE52xdUMkw3FlTiy= 9NaUEl6bHtZ023PzZsc+I371NXVUVpaCkBkZCS5ublkZWUxbNgwEhMTyczMJDExEavVSmZmJnV1= dSQkJBAXF4dhGOTk5LBr1y4uXrzYccyZM2eyZ88eJkyYQGJiIqtWrQJg7dq1hIeHk52dzebNmxk= 9ejQzZswgLy+PJ598kqSkJKA9DKSnpwOQkJDAO++8Q1FREUVFRVy4cIHJkyeTkpJCcHBwl+fU3N= xMRUUF06ZN49SpUz3/IF1ILQPxaK64MLvFvIE7OXcWY8hQCGhfOtlUUY7J3or55HHM+R/j9/ab+= BTuad/m64dzSgymC+fxqTmPc0I0hsUXS/7HHrGgkqoDni0zM5OVK1disVhYsWIFUVFRzJ8/nzFj= xlBXV4fVamXcuHHU19ezevVqFixYwOuvv866deuoqalh3759bNq0iUWLFrF27VoAUlJSWLZsGYG= B7UHEZrPd9lv+woULCQ0NpaqqiqlTpxIbG8uOHTuora0FYNasWZjNZqKjo8nKysLf35/8/HySk5= NZvnw5+/fvp7i4+I7ntXPnTp599tk++tT6lioE4vFc1TpwuzAAmI8epm3SYx0/G1Njafn5L+HKF= UynT2H+eBvm3/8nzrj22yXtL/0lll9lYDKc2JOSseR/3GlBpdZn52AKDMT88TYMu719fQU3oDDg= +RITE5k7d26X25xOJ1FRUUycOJHCwkJaWlpITU3t2H7y5MmO+S6Wm27jra6u7vb7jxo1isjISA4= ePAjA1atXu3xdeHg4aWlpFBQUcObMGaD9S8u6UlZWxsSJEwm4Fsg9jQKBSA+4y7yBO/Ep3kvb36= 3o/KSvH4SGYYSG4XhoJJaPNt7Y9uBIHP/9XwAwfVGBoQWVxA2EhYVhNrd/Z4j92sqeb7zxBtHR0= R2vaWtrY/Hixbz//vsUeDKDAAAEJ0lEQVQEBATw9NNPd1QDfHx6Xvy+HjBuZbfbSU1NJTIyktjY= WLZv337HYxQVFXW6iwLgn//5n9m4cWOPx+MKCgTiFfqjSuBO8wa6VF2FMTgEgq0dT5k+P4Rl069= xzFuA81uPYf6qkrYFf3H7vlevYv5kF/bEv8FE5wWVaLziVgsqqTowsNhs7XNetm7dSkREBDU1NQ= QHBxMWFsbp06dZv349QUFBnfaxWq3U19fT0NDAiRMnevyeFouFpqYmDMPg0KFDlJWVERMTw+HDh= wFwOBxd7pecnExycjJAx1yFt99+u8fv7yrm5cuX/2jo0KGuHofIfXt0WjCfH2jsk2O79byBa8z7= /4RzdASMjOh4zmQYmE6ewLLnD/h8/RVt074No8fcvu+OHJwzn4GQ0Pb9TCaMhyPx+TgXnysNOF5= +BW75S9cVFAbcV9QI39set8rIyCA7OxtoL6+fP3+e6dOnd2zPzc2loKCApqYmampqiI2NZfDgwY= SHh1NcXMzOnTux2WxERUVRWVnJhx9+yLZt29iyZQt5eXnU19czadIkQkJCKCws5MiRIwQFBVFdX= U1lZSXx8fFkZ2dTUlLC5cuXaWlpIScnB2hvQ8yePRtob1kcOHCAqqoqpk2bRklJCY2NjcTHx1NR= UUFTUxMxMTGd2hW3Onr0KJ9//jnPP/88Vqv1jq9zF7W1tVqYSLxPX1QK3L1VMBAoDMjN7HY7b73= 11m3rF6xZs4aRI0feYS+5k/LycrUMxPv0dvtAYcD1FAbkVqWlpQQFBZGenk5AQADnzp3j3Xffve= PtgHJ3CgTilXorFLj9vIEBQGFAuhIREYGPjw+vvfYazc3N2Gw2lixZQkhIiKuH5rHUMhCvdj+hw= BPmDQwECgQifU/fZSDSDQoDrqMwINJ/FAjEq91ryV/zBlxPYUCkfykQiNfraShQGHA9hQGR/qdA= IANCd0OBJhG6nsKAiGsoEMiAsWjpiG+84GsSoespDIi4jgKBDDh3qwIoDPS/z8Y9qDAg4mIKBDI= g3RoKNG/AdRQERNyDAoEMWNdDgOYNuI7CgIj7UCCQAU3zBlxHYUDEvWjpYhHpVwoCIu5JFQKRa3= Sh6nv6jEXclyoEIje5fsFS+6B3KQiIuD9VCES6oAtY79FnKeIZVCEQuQNVC+6PgoCIZ1GFQOQut= GhOz+nzEvE8CgQi3aSL3N0pPIl4LrUMRHpAbYSuKQSIeD4FApF7oGDQTkFAxHsoEIjch5sviAMp= HCgIiHgfBQKRXuLtVQOFABHvpkAg0su8qWqgECAycCgQiPQhTwwHCgEiA5MCgUg/6epC6w4hQQF= ARECBQMSlXBESFABEpCsKBCJuprsX7JuDgy7yInK/FAhEPJRCgIj0Ji1dLCIiIgoEIiIicq1lUF= 5e7upxiIiIiIiIiIgr/X8dfGnkRhzm4AAAAABJRU5ErkJggg=3D=3D" width=3D"516" heigh= t=3D"182" alt=3D"" /></p><p style=3D"margin-bottom:0pt; text-indent:0pt; te= xt-align:justify; line-height:150%"><a id=3D"_Hlk192176537"><span>Los resul= tados de la entrevista revelan que la aplicaci=C3=B3n de la estrategia did= =C3=A1ctica de aula invertida tuvo un resultado positivo en el desempe=C3= =B1o acad=C3=A9mico de los estudiantes del bachillerato t=C3=A9cnico de la = </span><span style=3D"text-decoration:underline">Unidad Educativa "General = Medardo Alfaro</span><span>". </span></a></p><p style=3D"margin-bottom:0pt;= text-indent:0pt; text-align:justify; line-height:150%"><span> </span>= </p><h2 style=3D"margin-top:0pt; margin-left:54pt; text-indent:-18pt; line-= height:150%; font-size:12pt"><span style=3D"font-family:'Times New Roman'; = font-style:italic; color:#000000"><span>3.3.</span></span><span style=3D"fo= nt-family:'Times New Roman'; font-weight:bold; color:#000000"> </span><span= style=3D"font-family:'Times New Roman'; font-style:italic; color:#000000">= Resultados de la encuesta aplicada a los estudiantes del grupo experimental= </span></h2><p style=3D"margin-bottom:0pt; line-height:150%"><span> </= span></p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent= :0pt; line-height:150%"><span>A continuaci=C3=B3n, se muestran los resultad= os de la encuesta aplicada a los estudiantes acerca de su percepci=C3=B3n s= obre la aplicaci=C3=B3n del aula invertida. </span></p><p class=3D"APA7MAED= ICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span= style=3D"font-weight:bold"> </span></p><p class=3D"APA7MAEDICION" sty= le=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span style=3D"= font-weight:bold">Pregunta 1: =C2=BFConsidera que el aula invertida mejor= =C3=B3 su comprensi=C3=B3n de los temas?</span></p><p class=3D"APA7MAEDICIO= N" style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span>Un = 78% de los estudiantes considera que el aula invertida mejor=C3=B3 su compr= ensi=C3=B3n de los temas, lograron comprender mejor los conceptos t=C3=A9cn= icos gracias a la combinaci=C3=B3n de aprendizaje aut=C3=B3nomo y actividad= es pr=C3=A1cticas en clase.</span></p><p class=3D"APA7MAEDICION" style=3D"m= argin-bottom:0pt; text-indent:0pt; line-height:150%"><span>Este porcentaje = sugiere que, en general, los estudiantes encontraron =C3=BAtil la metodolog= =C3=ADa para comprender conceptos t=C3=A9cnicos. Sin embargo, tambi=C3=A9n = indica que un 22% no percibe una mejora significativa, lo que podr=C3=ADa s= e=C3=B1alar la necesidad de ajustar ciertas pr=C3=A1cticas dentro de la met= odolog=C3=ADa para abordar mejor las dificultades de esos estudiantes.</spa= n></p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0p= t; line-height:150%"><span style=3D"font-weight:bold">Pregunta 2: =C2=BFSe = sinti=C3=B3 m=C3=A1s motivado con el empleo de esta metodolog=C3=ADa que co= n la tradicional?</span></p><p class=3D"APA7MAEDICION" style=3D"margin-bott= om:0pt; text-indent:0pt; line-height:150%"><span>La motivaci=C3=B3n es un f= actor clave en el aprendizaje, y el 85% de los encuestados se sinti=C3=B3 m= =C3=A1s motivado con el aula invertida en comparaci=C3=B3n con el modelo tr= adicional. Este resultado resalta el potencial de la metodolog=C3=ADa para = involucrar a los estudiantes y aumentar su inter=C3=A9s por los contenidos,= lo que puede contribuir a un mejor rendimiento acad=C3=A9mico.</span></p><= p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line= -height:150%"><span style=3D"font-weight:bold">Pregunta 3:</span><span> </s= pan><span style=3D"font-weight:bold">=C2=BFLe result=C3=B3 m=C3=A1s f=C3=A1= cil estudiar con los materiales previos a clase?</span></p><p class=3D"APA7= MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><= span>Un 80% de los estudiantes indic=C3=B3 que les result=C3=B3 m=C3=A1s f= =C3=A1cil estudiar los materiales previos a la clase. Esto sugiere que el a= cceso anticipado a recursos de aprendizaje puede facilitar la comprensi=C3= =B3n y preparaci=C3=B3n para las actividades en clase, lo cual es un aspect= o positivo de la metodolog=C3=ADa.</span></p><p class=3D"APA7MAEDICION" sty= le=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span style=3D"= font-weight:bold">Pregunta 4: =C2=BFCree que la metodolog=C3=ADa foment=C3= =B3 un mejor trabajo en equipo?</span></p><p class=3D"APA7MAEDICION" style= =3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span>El 82% de l= os encuestados cree que la metodolog=C3=ADa foment=C3=B3 un mejor trabajo e= n equipo. Esto es crucial en el aprendizaje colaborativo, ya que sugiere qu= e los estudiantes est=C3=A1n desarrollando habilidades interpersonales y de= colaboraci=C3=B3n, que son esenciales tanto en el =C3=A1mbito acad=C3=A9mi= co como en el laboral.</span></p><p class=3D"APA7MAEDICION" style=3D"margin= -bottom:0pt; text-indent:0pt; line-height:150%"><span style=3D"font-weight:= bold">Pregunta 5: =C2=BFRecomendar=C3=ADa la metodolog=C3=ADa a otros estud= iantes?</span></p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; te= xt-indent:0pt; line-height:150%"><span>Un alto porcentaje del 88% recomenda= r=C3=ADa la metodolog=C3=ADa a otros estudiantes. Este resultado es un indi= cador fuerte de la satisfacci=C3=B3n general con la experiencia del aula in= vertida, lo que puede ser motivador para su implementaci=C3=B3n en otros cu= rsos o contextos como se muestra a continuaci=C3=B3n en la </span><span sty= le=3D"font-weight:bold">figura 2</span><span>.</span></p><p style=3D"margin= -bottom:0pt; line-height:150%"><span> </span></p><p style=3D"margin-bo= ttom:0pt; text-indent:0pt; text-align:center; line-height:150%"><span style= =3D"font-weight:bold">Figura 2</span></p><p style=3D"margin-bottom:0pt; tex= t-indent:0pt; text-align:center; line-height:150%"><img src=3D"data:image/p= ng;base64,iVBORw0KGgoAAAANSUhEUgAAAloAAACeCAYAAADqvaRhAAAABHNCSVQICAgIfAhki= AAAAAlwSFlzAAAOxAAADsQBlSsOGwAAH5tJREFUeJzt3X9QVXX+x/Hn/SE/RBHYAVRStAysIHNS= LBN/Zaap4yaShLEZmpU5hU41tdVXqzEbNXSH0tXZDSulWhkdGx23X5KwZLSETplwNRVctbwoYGB= 0Ve75/uF0N1ZFMI73Aq/HDH9wfuDnc9/33F6d87mfj6WsrMxARERERFqdHSA2Ntbb7RARERFpVx= wOB1ZvN0JERESkvVLQEhERETGJgpaIiIiISRS0REREREyioCUiIiJiEgUtEREREZMoaImIiMglf= fzxx6Snp5OSksK7776LYRiX3VdVVcVTTz3FrFmzqKioAMAwDN58802cTqdX+uEtCloiIiJyUU6n= k9zcXDIzM1mzZg0lJSUcOHDgsvt27txJUlISTz31FHl5eQAUFBQQExNDRESE1/rjDQpaIiIiclF= 2ux2bzUZgYCBBQUEEBAQQHBx82X1utxur1YrFYsFut+N0OikuLmbMmDHe7I5XWMrKygzNDC8iIi= IXU1BQwMaNG+nWrRsTJ05k0KBBl913/PhxFi5ciNvt5vnnn+e9997j4YcfJiwszFvd8IpmzQz/z= 3/+k4yMDB5//HEKCgo820tKSsjIyGDWrFnk5uY2ei77wgsvkJGR0ei57OrVq6msrDSpKyIiItLa= GhoaOHToEEOHDiUmJoaPPvqI+vr6y+6LjIxk1apVrF69mt27dzN69Gh27NhBcnIy77zzjje7dNX= Zm9q5b98+CgsLWbhwIfX19bz00kvcdNNNWCwWsrOzee655wgKCuK1114jPj6e2NhYioqKmDRpEi= EhIeTn55OWlkZhYSH9+vUjPDy8RY1zOBy/q3MiIiJy5fbs2cOJEyeYMGECANXV1bz//vsMHTq0y= X2/Onr0KHv37uXaa69l+/bt/N///R9r167l66+/pkuXLl7p05X4PU/+mgxahw8fZsiQIYSEhBAS= EsKQIUM4cOAALpeLxMREevbsCcDIkSMpLS0lNja20XNZm82G0+lk165dzJ07t8WN0yNNERER73E= 6nezfv5+oqChsNhuGYdC7d29iY2Ob3AfgcrnIzc1l3rx5WK1WunTpQmxsLMHBwcTGxrapoPV7NP= noMDg4mL1791JfX09tbS2nT5/m9OnTVFdXN3rOGhoaSm1tLQCDBw/mgw8+4K9//SvDhg1j/fr1P= PDAA1gsFnN7IiIiIq1qyJAhhIWFMXPmTB566CECAgJITEy87D6ATZs2MXXqVDp37kxAQABxcXHc= f//9HSpkwWUGw589e5a1a9dSVFREaGgofn5+TJgwgRMnThAYGMhdd90FQHFxMWVlZTzwwAONzt+= 6dSuRkZEcO3aMLVu2MGLECKZPn256p0RERES87bKD4Tt16sTDDz/M3/72N5YuXUqPHj3o3r07Xb= t2pbq62nPcyZMnCQ0NbXRueXk5TqeT+Ph4SkpKyMrKoqKiwnPnS0RERKS9azJo1dfXc+rUKVwuF= 0VFRVRWVtK3b19iYmIoLCyksrKSmpoa8vLyGDBggOc8l8vFhg0bSElJAcBisXh+rFZN3SUiIiId= Q5OD4U+dOsVrr71GXV0dAwYM4Mknn8RisRAVFcXEiRNZtGgRLpeL1NRUrrnmGs95mzdvZvLkyQQ= GBgLnB7XPmTOHsWPHEhQUZG6PRERERHyEJiwVERERMUGzJiwVERERkSujoCUiIiJiEgUtEREREZ= MoaImIiIiYpMlvHYp0FB9//DHvv/8+P//8MxMmTPBMvjt58mR++uknAAYOHMjy5cuB84unv/rqq= 9TU1PDiiy8SHR2NYRisXLmS5ORkIiIivNYXEZGWyv37cW83AYCpMyO93YRWp6AlHZ7T6SQ3N5fM= zEysVisLFizg9ttvp2/fvvTt25e//OUvF5yzc+dOkpKSCA0NJS8vjxkzZlBQUEBMTIxCloiIeOj= RoXR4drsdm81GYGAgQUFBBAQEEBwc3OQ5v1083W6343Q6KS4uZsyYMVep1SIi0hbojpZ0eGFhYa= SmpvLss8/SrVs3kpKSiIiIwDAMSktLufvuu7n22muZOnUqd955JwAJCQksXLgQt9vN888/T3Z2N= g8//LAWTxcRkUYUtKTDa2ho4NChQwwdOpSzZ8/y0UcfcdNNNxEYGMjWrVuxWq385z//4dlnn6V/= //5ERUURGRnJqlWrAPjwww8ZPXo0O3bsICcnh0mTJvGnP/3Jy70SERFfoEeH0uEVFxcDkJycTGp= qKjExMXz++efA+YXVbTYbffr04dZbb6WqqqrRuYcOHeL48eMMGDCAoqIi1q1bx8GDBz0D6EVEpG= NT0JIO78yZMxw7doy6ujrq6+s5fvw4fn5+nv1ut5sDBw7w7bff0qtXL892l8tFTk4O06dPx+12a= /F0ERG5gB4dSoc3ZMgQSktLmTlzJhaLhTFjxpCYmIjD4WDp0qUcPXqUuLg4nnnmGUJCQjznbdq0= ialTp9K5c2cA4uLiuP/++0lOTqZLly7e6o6IiPgQLSotIiLSwWkeLXNoUWkREREREyloiYiIiJh= EQUtERETEJApaIiIiIiZR0BIRERExiYKWiIiIiEkuO4/WZ599xocffojL5WL48OHcf//9AKSnp+= NyuQDo06cPr776KgBVVVVkZmZSV1fHvHnziI6OxjAM1qxZw5QpUwgPDzexOyIiIiK+o8mgVVlZy= ZYtW3j55ZexWq0sXryYgwcP0rdvX7p3787ixYsvOKeoqIhJkyYREhJCfn4+aWlpFBYW0q9fP4Us= ERER6VCaDFo2mw2bzUZAQAB2ux1/f3+Cg4Ob/INutxur1YrFYsFms+F0Otm1axdz585tceMcDke= LzxG5GPdh3wj51t6V3m6CiFd9+eWXfPzxx/zyyy8MGzaM8ePH43a7+fzzz/nss88IDg5mypQpxM= TEAHDq1CnWrl1LbW0tM2fOpEePHhiGQW5uLnfeeSdhYWFe7lF7EXL5Q64CX/3v/u+Z2L3JoBUWF= sa9997LwoULCQ4OZuLEiYSHh2MYBkeOHCEtLY3IyEgmTJjAqFGjABg8eDBLlizB7XaTkZHB+vXr= mTFjBhaLpcWN04z10lpKD1dd/qCrQO9p6cicTieFhYW8+eabWK1WFixYgN1up0uXLoSHh7Nu3Tq= ++eYbli9fznvvvYfFYmHr1q2kpaURGhrKl19+yciRI8nPz2fIkCHcfvvt3u5Su/Htv3xjZvj2+B= nZZNByu92Ul5czaNAgzp07x/bt27nxxhsJDAwkOzsbi8XCkSNHWLx4MTExMURFRREREcGyZcsA2= Lp1K4mJiRQUFLBlyxZGjBjB9OnTr0rHRETEt9jtdmw2G4GBgdjtdgICAggODiYiIoLk5GQAbrjh= BpxOJ263G5vN1ugpid1ux+l0UlxczLx587zcG5HmafJbh8XFxQAkJSUxbdo0rrvuOvLz84H/XjD= R0dH079+fqqrGdwzKy8txOp3Ex8dTUlJCVlYWFRUV1NbWmtQVERHxZWFhYaSmpvLss8/yyiuvkJ= SURERERKNj9u7dyz333IPNZgMgISGBtWvXkpmZyfDhw8nOzr7ipyQi3tBk0Dp79iw//vgjp0+fp= r6+nsrKSvz8/Dz7DcPgwIED7N+/n169enm2u1wuNmzYQEpKCgAWi8XzY7VqRgkRkY6ooaGBQ4cO= MXToUGJiYvjoo4+or6/37K+rqyMnJ6fRk4/IyEhWrVrF6tWr2b17N6NHj2bHjh0kJyfzzjvveKM= bIi3SZOpJSEggNDSU+fPnM2/ePPz9/bnjjjvYt28fGRkZzJgxg7Vr1zJnzhxCQv47kG7z5s1Mnj= yZwMBA/P39iY2NZc6cOVx33XUEBQWZ3ikREfE9vz4lSU5OJjU1lZiYGD7//HMAzpw5Q1ZWFg8++= CA9evS44NxDhw5x/PhxBgwYQFFREevWrePgwYP89NNPV7MLIi3W5BitTp06kZ6eTnp6eqPtMTEx= rFix4pLn3XfffY1+T0lJ8dzdEhGRjunMmTMcO3aMuro6bDYbx48fJywsjDNnzrB8+XJGjBjBrbf= eesF5LpeLnJwc5s2bh9vt1lMSaVMuO2GpiIhIaxgyZAilpaXMnDkTi8XCmDFjSExM5Pvvv2fbtm= 1s27bNc+ySJUtISEgAYNOmTUydOpXOnTsDEBcXx/33309ycjJdunTxSl9EmstSVlZmtMevU4r8V= uknvjG9ww13ac4fEfE9uX/3jekdps6M9HYTWpXD4dBahyIiIiJmUdASERERMYmCloi0SR9//DHp= 6emkpKTw7rvvYhiGZ9/XX3/NrFmzSEpK4oMPPsAwDKqqqnjqqaeYNWsWFRUVwPkpat58802cTqe= 3uiEi7ZyCloi0OU6nk9zcXDIzM1mzZg0lJSUcOHAAgKqqKrKysnjppZd46623+PLLL3E4HOzcuZ= OkpCSeeuop8vLyACgoKCAmJuaCSTNFRFqLgpaItDm/XcolKCjIs5QLwJ49e7j77ruJioqiW7duj= B07lr17915yKZcxY8Z4uTci0p5pegcRaXN+u5RLt27dGi3lUl1dzR/+8IdGx/66rMvChQtxu908= //zzZGdn8/DDD2spFxExle5oiUib09RSLm63u9Gxv05qqaVcRMQbFLREpM1paimX4ODgRovcnzx= 5krCw/85fpqVcRORq0qNDEWlzLrWUC0D//v1Zv349d955J506dWLbtm08/fTTgJZyuRrezd7j7S= YAkPZQnLebIAIoaIlIG3SppVwAoqKiSElJ4bnnnqO+vp7Zs2fTq1cvQEu5iMjVpyV4pEPQEjwiV= 4fuaLVNWoLHHFqCR0RERMRECloiIiIiJlHQakVfffUVI0eObPSzbds2z/6LLRmiZUFERETaLw2G= b0UJCQmer5gDLFq0iOuuuw5ovGSI1WplwYIF3H777TgcDpKSkggNDSUvL48ZM2ZoWRAREZF2Qne= 0THL06FFOnjzJ9ddfD1x6yRAtCyIiItJ+6Y6WST755BMmT57sWd7jUkuGJCQkaFkQERGRduqyd7= Q+++wznnzySR599FFycnIwDAOAkpISMjIymDVrFrm5uZ7tVVVVvPDCC2RkZDQac7R69WoqKytN7= IrvqKur49NPPyUhIcGz7VJLhmhZEBERkfaryaBVWVnJli1bePnll1m6dCl79uzh4MGDVFdXk52d= zTPPPMPrr7/O119/zb59+wAoKipi0qRJPPbYY+Tn5wNQWFhIv379CA8PN79HPqCgoIDx48cTGBj= o2dbUkiGgZUFERETaoyYfHdpsNmw2GwEBAdjtdvz9/QkODua7774jMTGRnj17AjBy5EhKS0uJjY= 1tNObIZrPhdDrZtWsXc+fObXHjHA7HlfXKixoaGsjJyeGRRx5p1P5Dhw5RWlrKrl27sFqtlJWV0= adPHxwOB2fOnGHdunWkpqZSVlbG6dOn2b9/P3V1dRw4cMAzi7X8Hr4R8tvie9pbjh/znfd9ZM+f= vd0EaSFday0V4u0GAL5bt98zsXuTQSssLIx7772XhQsXEhwczMSJEwkPD+fLL79stEhraGioZyq= CwYMHs2TJEtxuNxkZGaxfv54ZM2Zc0Zijtjhj/e7du4mLi2PYsGGNtvft25effvqJ1157zbNkyL= Rp0/Dz8+P9998nPT3d09/bbruNBQsWkJyczMCBA73RjXan9LBvzAzfFt/T3nL82H+83QQP1a35v= vrCN2aGV81a5tt/+cbM8O2xbk0GLbfbTXl5OYMGDeLcuXNs376dG2+8EcMwPGOyAM8dLICIiAiW= LVsGwNatW0lMTKSgoIAtW7YwYsQIpk+fbmJ3vO+WW27hlltuuWC7n58fs2fPZvbs2RfsS0lJafT= 79OnT2/3rJCIi0hE0OUbr13FFSUlJTJs2jeuuu478/Hy6du1KdXW157iTJ08SGhra6Nzy8nKcTi= fx8fGUlJSQlZVFRUUFtbW1JnRDRERExPc0GbTOnj3Ljz/+yOnTp6mvr6eyshI/Pz9iYmIoLCyks= rKSmpoa8vLyGDBggOc8l8vFhg0bPHdqLBaL58dq1dRdIiIi0jE0+egwISEBh8PB/PnzsVgs3Hbb= bdxxxx34+fkxceJEFi1ahMvlIjU1lWuuucZz3ubNm5k8ebLnW3exsbHMmTOHsWPHEhQUZG6PRER= ERHyEpayszGiPg89Efqv0E98YDH/DXWGXP0gAyM/zncHww0f18nYT2ox3s31jMHzaQ3HebkKbkv= t33xgMP3VmpLeb0KocDoeW4BERERExi4KWiIiIiEkUtERERERMoqAlIiIiYpImv3UoFyo/dMrbT= fDo07ebt5sgIiIiTdAdLRERERGTKGiJiIiImERBS0RERMQkCloiIiIiJlHQEhERETGJgpaIiIiI= SRS0REREREyioCUiIiJiEgUtEREREZMoaImIiIiYREFLRERExCQKWiIiIiImUdASERERMYmCloi= IiIhJ7E3tLC4uJjMzs9G2Bx98kLFjx5Keno7L5QKgT58+vPrqqwBUVVWRmZlJXV0d8+bNIzo6Gs= MwWLNmDVOmTCE8PNykroiIiIj4liaD1qBBg8jJyfH8vnTpUq699loMw6B79+4sXrz4gnOKioqYN= GkSISEh5Ofnk5aWRmFhIf369VPIEhERkQ6lyaD1W0ePHqWmpoZ+/fphGMYlj3O73VitViwWCzab= DafTya5du5g7d26LG+dwOFp8jtn8/bp7uwkevvj6+C7fCPmqWUt09nYDPFS3tkc1a6kQbzcA8N2= 6xcbGXvG5zQ5a27dvZ9y4cVgsFgCOHDlCWloakZGRTJgwgVGjRgEwePBglixZgtvtJiMjg/Xr1z= NjxgzPeS3xezpmlvJDp7zdBA9ffH18VenhKm83AVDNWuL4sf94uwkeqlvzffXFHm83AVDNWurbf= x33dhOA9lm3ZgWturo6du7cSXJyMgAWi4Xs7GwsFgtHjhxh8eLFxMTEEBUVRUREBMuWLQNg69at= JCYmUlBQwJYtWxgxYgTTp083rzciIiIiPqRZ3zosLCxk+PDhBAQEeLbZ7XZsNhvR0dH079+fqqr= GdwzKy8txOp3Ex8dTUlJCVlYWFRUV1NbWtm4PRERERHzUZYNWQ0MD27ZtY8SIERfsMwyDAwcOsH= //fnr16uXZ7nK52LBhAykpKcD5O2C//litmlFCREREOobLPjr87rvviI6OpkePHp5t+/btY+XKl= VRXV9O7d2/mzJlDSMh/B9Jt3ryZyZMnExgYCJx/5jpnzhzGjh1LUFCQCd0QERER8T2XDVo333wz= N998c6NtMTExrFix4pLn3HfffY1+T0lJ8dzdEhEREeko9BxPRERExCQKWiIiIiImUdASERERMYm= CloiIiIhJFLRERERETKKgJSIiImISBS0RERERkyhoiYiIiJhEQUtERETEJApaIiIiIiZR0BIRER= ExiYKWiIiIiEkUtERERERMoqAlIiIiYhIFLRERERGTKGiJiIiImERBS0RERMQkCloiIiIiJlHQE= hERETGJvamdxcXFZGZmNtr24IMPcvfdd1NSUsI777xDXV0d48aNIykpCYvFQlVVFZmZmdTV1TFv= 3jyio6MxDIM1a9YwZcoUwsPDTe2QiIiIiK9oMmgNGjSInJwcz+9Lly7l2muvpbq6muzsbJ577jm= CgoJ47bXXiI+PJzY2lqKiIiZNmkRISAj5+fmkpaVRWFhIv379FLJERESkQ2kyaP3W0aNHqampoV= +/fhQWFpKYmEjPnj0BGDlyJKWlpcTGxuJ2u7FarVgsFmw2G06nk127djF37twWN87hcLT4nI7E4= fjR201oM6y9vd2C8xyOSm83oc2I7OntFvyXPouaL2FoJ283AVDNWip+mLdbcJ7DUePtJlxUbGzs= FZ/b7KC1fft2xo0bh8Viobq6mrCwMM++0NBQnE4nAIMHD2bJkiW43W4yMjJYv349M2bMwGKxtLh= xv6djIiIiIt7WrKBVV1fHzp07SU5OBsAwDAzD8Oz/9Q4WQEREBMuWLQNg69atJCYmUlBQwJYtWx= gxYgTTp09v7T6IiIiI+KRmfeuwsLCQ4cOHExAQAEDXrl2prq727D958iShoaGNzikvL8fpdBIfH= 09JSQlZWVlUVFRQW1vbis0XERER8V2XDVoNDQ1s27aNESNGeLbFxMRQWFhIZWUlNTU15OXlMWDA= AM9+l8vFhg0bSElJAcBisXh+rFbNKCEiIiIdw2UfHX733XdER0fTo0cPz7aoqCgmTpzIokWLcLl= cpKamcs0113j2b968mcmTJxMYGAicH2s1Z84cxo4dS1BQkAndEBEREfE9lrKyMkODzkVERERal8= Ph0MzwIiIiImZR0BIRERExiYKWiIiIiEkUtERERERM0uyZ4TuKxx57jFOnTtG5c2cSExNJSUnB3= 9/f281qlvr6enJzczlw4AALFy70dnOumrZaM7fbzebNm/noo4/o2rUraWlp3Hzzzd5u1lXTluu2= ceNGPvnkEwICApg2bRpDhw71drOumrZat1/V1dXx5z//mSFDhnSYCbTbas0MwyA9PR2XywVAnz5= 9ePXVV73cqpbTHa3/UVdXx7p161ixYgUnT55kx44dXmnHc889R11dXYvOWbVqFddffz3nzp0zqV= W+yVdqBi2rW2VlJYZhsHz5cu677z5WrlzZaMWF9q4t181qtbJixQpmz57N22+/bXLrfIuv1O1KP= iMBNm3aREJCAmfOnDGhVb7JV2oGLaubYRh0796dnJwccnJy2mTIAt3RuqQuXbowaNAgDh8+TG1t= LatWraJz5844HA6ysrIoLi7mH//4B/X19dxzzz2MHz8ewzBYv349eXl51NfXA+ffVBs3bmTBggX= A+TnGIiIiuP3226mtreXNN98kKiqKwsJCBg4cyKxZs3j99depqKhg9uzZTJ48mdGjR5ORkYFhGE= RFRZGens4NN9xwQZvnzZvHiRMnrurr5Et+WzOgWXUbN27cBTVbtGgRYWFhrFix4oK6xcXFXbRmN= puNJUuWtKhukZGRTJkyBTg/11xtbS1utxubzXaVXznvaq26Xcm19nvqdu7cOaqqqrj++uuv/ovm= A9riZ2R5eTl1dXUMHz6cr7766qq+Xr6grV1r7YWC1iWcOnWKL774gpEjR+J2u9m9ezfz589n1qx= ZnDhxgk8//ZTnn38ePz8/srKyiI+P5+eff+bEiROsXLmSf//73/zwww9cc801nD171vN3GxoaaG= hoAM4/gvj2228ZNmwYU6dO5fXXX6e0tJRnnnmGZ555hhdffJGuXbsCsH79egzD4ODBg3zwwQcXf= TNeycLd7clvawY0q25du3a9oGZ9+/alurr6onW7VM3i4uKuuG4AZWVlJCQkdLiQBa1Xtyu51q60= brm5uWzcuJFu3bqRkZFxdV4oH9PWPiMNw+D9999n9uzZ/PDDD1fvhfIhbe1as1gsHDlyhLS0NCI= jI5kwYQKjRo26ei9YK1HQuogHHniA8PBwRo8ezZAhQ/jpp5/o3bs3gwYNAuCbb77hm2++4bHHHv= OcM27cODp16oTVaqWhoQHDMJp1a7p3794MGzYMgLi4OGpqai44xjAMNm3axI4dO6isrGw0C7+c9= 781+9Xl6nbjjTeaUjNoft1Onz7Nxo0bO+R/sNtq3aZOncof//hH9u7dy9KlS1m2bBkhISEt6ntb= 1hY/I7/44gsGDBhAWFhYhwxabfFas1gsZGdnewLX4sWLiYmJISoqqsX99yYFrYtYt27dBWsy/vZ= ukWEYTJw4kdTU1EbHHDt2jPLycubOnUt0dDSPP/645w3aHHa7HbfbfcH2b7/9loMHD7Jo0SIMw+= CVV165gl61bxerGVy+bseOHWP79u2NagY0u26Xqhk0r25nzpxh1apVTJs2je7du1/232tvWrNur= XGtQfOvN7vdzs0330zv3r05evRohwpabfEzcs+ePezYsYN3333Xs62hoYFZs2Y1699u69rqtWa3= n48p0dHR9O/fn6qqKgWtjiA6Opp169YxfPhwoqKiPG/Uw4cPc9dddzF+/HjPsefOnaOyspIff/y= RhoYGioqKmDRp0mX/DX9/f6qqqvDz8+OXX37B398fq9VKYWGhaf1q7y5Wt4vVDCAoKMj0up09e5= Y33niDO+64g4EDB7ZaP9ub5tbtSq81aFnddu/eTW1tLQkJCRw7dozDhw83WgtWfPMz8pFHHuGRR= x4Bzq/h+9VXX/HQQw+1Qm/bD1+71n7166PF/fv3M2PGjN/bzatOQet/+Pv7XzDWyWq1elI1QPfu= 3bnvvvtYvny55xb0G2+8QXh4OFlZWeTk5HgGHT744INMnz6dl156iT59+jBw4EDP/1X879+1Wq2= eMTqjR4/mpZdeYsqUKdx1113k5+fzxBNPcMcdd3gW6/5fTzzxhGcwfGpqKk888QS33XZb6704Pu= piNYPm1e3pp59m3bp1F9TMbrdftG5N1QxaVrfvv/+e4uJiiouLycrKAmD+/Pme2/jtnRl1u5JrD= VpWtz59+vD222/z1ltvERERwaOPPkpYWFirvja+rC1/Rl7s73QEbfVa27dvHytXrqS6uprevXsz= Z86cNnnnWItKt6K3336bnj17MmrUKGpqaliyZAnz58/vkI+E2grVrG1S3dom1a3tUc1+H4fDoaD= Vmg4dOsTatWupqKigW7dujB07lgkTJni7WdIE1axtUt3aJtWt7VHNfh8FLRERERGTOBwOzQwvIi= IiYhYFLRERERGTKGiJiIiImERBS0RERMQkCloiIiIiJlHQEhERETGJgpaIiIiISRS0RERERExih= /MTaomIiIiIiIiIiLQJ/w8hAlsayd3cNgAAAABJRU5ErkJggg=3D=3D" width=3D"602" heig= ht=3D"158" alt=3D"" /><br /><span style=3D"font-style:italic">Resultados de= la encuesta a los estudiantes del grupo experimental.</span></p><p style= =3D"margin-bottom:0pt; line-height:150%"><span style=3D"font-weight:bold">&= #xa0;</span></p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text= -indent:0pt; line-height:150%"><span>Los resultados de la encuesta reflejan= una percepci=C3=B3n mayoritariamente positiva sobre la metodolog=C3=ADa de= l aula invertida, destacando mejoras en la comprensi=C3=B3n, la motivaci=C3= =B3n y el trabajo en equipo. </span></p><p class=3D"APA7MAEDICION" style=3D= "margin-bottom:0pt; text-indent:0pt; line-height:150%"><span>Un porciento e= levado (88%) recomienda el empleo de esta metodolog=C3=ADa, lo que sugiere = que los estudiantes valoran la experiencia y la consideran beneficiosa para= su aprendizaje. Sin embargo, el hecho de que un porcentaje menor no haya p= ercibido mejoras significativas indica la necesidad de ajustar ciertos aspe= ctos para hacerla a=C3=BAn m=C3=A1s efectiva y accesible para todos.</span>= </p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt;= line-height:150%"><span>Para evaluar el resultado del aula invertida en el= desempe=C3=B1o acad=C3=A9mico, se realiz=C3=B3 un an=C3=A1lisis comparativ= o entre el grupo experimental y el grupo control mediante la aplicaci=C3=B3= n del pretest y el post test. </span></p><p class=3D"APA7MAEDICION" style= =3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span>En la </spa= n><span style=3D"font-weight:bold">tabla 2</span><span> se presentan los pr= omedios de calificaciones acad=C3=A9micas obtenidas por ambos grupos, antes= y despu=C3=A9s de la implementaci=C3=B3n de la estrategia.</span></p><p cl= ass=3D"Caption" style=3D"margin-bottom:0pt; text-align:center; page-break-a= fter:avoid; line-height:150%; font-size:12pt"><span style=3D"font-family:'T= imes New Roman'; font-weight:bold; font-style:normal; color:#000000"> = </span></p><p class=3D"Caption" style=3D"margin-bottom:0pt; text-align:cent= er; page-break-after:avoid; line-height:150%; font-size:12pt"><span style= =3D"font-family:'Times New Roman'; font-weight:bold; font-style:normal; col= or:#000000">Tabla 2</span></p><p class=3D"Caption" style=3D"margin-bottom:0= pt; text-align:center; page-break-after:avoid; line-height:150%; font-size:= 12pt"><span style=3D"font-family:'Times New Roman'; color:#000000">Resultad= os del pretest y post a los estudiantes</span></p><table style=3D"width:468= .15pt; margin-bottom:0pt; padding:0pt; border-collapse:collapse"><tr style= =3D"height:29.25pt"><td style=3D"border-top:0.75pt solid #7f7f7f; border-bo= ttom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p class= =3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-height= :150%; font-size:10pt"><span>Grupo</span></p></td><td style=3D"border-top:0= .75pt solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt;= vertical-align:top"><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt;= text-indent:0pt; line-height:150%; font-size:10pt"><span>Pre test (Promedi= o)</span></p></td><td style=3D"border-top:0.75pt solid #7f7f7f; border-bott= om:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p class=3D= "APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-height:15= 0%; font-size:10pt"><span>Post test (Promedio)</span></p></td><td style=3D"= border-top:0.75pt solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; paddin= g:0pt 5.4pt; vertical-align:top"><p class=3D"APA7MAEDICION" style=3D"margin= -bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Difer= encia</span></p></td></tr><tr style=3D"height:29.25pt"><td style=3D"border-= top:0.75pt solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5= .4pt; vertical-align:top"><p class=3D"APA7MAEDICION" style=3D"margin-bottom= :0pt; text-indent:0pt; line-height:150%; font-size:10pt"><span>Experimental= </span></p></td><td style=3D"border-top:0.75pt solid #7f7f7f; border-bottom= :0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p class=3D"A= PA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%= ; font-size:10pt"><span>6.5</span></p></td><td style=3D"border-top:0.75pt s= olid #7f7f7f; border-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertic= al-align:top"><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-i= ndent:0pt; line-height:150%; font-size:10pt"><span>8.2</span></p></td><td s= tyle=3D"border-top:0.75pt solid #7f7f7f; border-bottom:0.75pt solid #7f7f7f= ; padding:0pt 5.4pt; vertical-align:top"><p class=3D"APA7MAEDICION" style= =3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; font-size:10pt"><= span>+1.7</span></p></td></tr><tr style=3D"height:29.25pt"><td style=3D"bor= der-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p = class=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-h= eight:150%; font-size:10pt"><span>Control</span></p></td><td style=3D"borde= r-bottom:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p cl= ass=3D"APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-hei= ght:150%; font-size:10pt"><span>6.4</span></p></td><td style=3D"border-bott= om:0.75pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p class=3D= "APA7MAEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-height:15= 0%; font-size:10pt"><span>6.9</span></p></td><td style=3D"border-bottom:0.7= 5pt solid #7f7f7f; padding:0pt 5.4pt; vertical-align:top"><p class=3D"APA7M= AEDICION" style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%; fo= nt-size:10pt"><span>+0.5</span></p></td></tr></table><p style=3D"margin-bot= tom:0pt; line-height:150%"><span> </span></p><p class=3D"APA7MAEDICION= " style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span>Los = resultados muestran una mejora significativa en el desempe=C3=B1o acad=C3= =A9mico del grupo experimental, que pas=C3=B3 de un promedio de 6.5 en el p= re-test a 8.2 en el post-test, con una diferencia de +1.7 puntos. En cambio= , el grupo de control solo mejor=C3=B3 0.5 puntos, pasando de 6.4 a 6.9. Es= to indica que la metodolog=C3=ADa del aula invertida tuvo un resultado posi= tivo en el aprendizaje de los estudiantes. </span></p><p style=3D"margin-bo= ttom:0pt; text-indent:0pt; line-height:150%"><span> </span></p><p clas= s=3D"APA7MAEDICION" style=3D"margin-left:54pt; margin-bottom:0pt; text-inde= nt:-18pt; line-height:150%"><span style=3D"font-weight:bold"><span>4.</span= ></span><span style=3D"width:9pt; font:7pt 'Times New Roman'; display:inlin= e-block">      </span><span style=3D"font-weight:b= old">Discusi=C3=B3n</span></p><p class=3D"APA7MAEDICION" style=3D"margin-bo= ttom:0pt; text-indent:0pt; line-height:150%"><span>Los cuestionarios evalua= ron cinco aspectos claves: comprensi=C3=B3n de contenidos y conceptos, apli= caci=C3=B3n del conocimiento a la pr=C3=A1ctica, habilidades de resoluci=C3= =B3n de problemas, autonom=C3=ADa y aprendizaje activo, as=C3=AD como la mo= tivaci=C3=B3n y participaci=C3=B3n en el aula. Se analiz=C3=B3 el dominio d= e conceptos, la capacidad de aplicar conocimientos en ejercicios pr=C3=A1ct= icos, la resoluci=C3=B3n de problemas t=C3=A9cnicos, el estudio independien= te y el nivel de compromiso en clase. </span></p><p class=3D"APA7MAEDICION"= style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span>Se pu= do constatar que los estudiantes del grupo experimental obtuvieron mejores = calificaciones en comparaci=C3=B3n con el grupo de control, lo que sugiere = una mayor comprensi=C3=B3n de los contenidos y una aplicaci=C3=B3n m=C3=A1s= efectiva de los mismos, transfiriendo los conocimientos a contextos reales= y pr=C3=A1cticos.</span></p><p style=3D"margin-bottom:0pt; text-indent:0pt= ; text-align:justify; line-height:150%"><span>La motivaci=C3=B3n y la comun= icaci=C3=B3n de los estudiantes tambi=C3=A9n se vio fortalecida. Durante la= implementaci=C3=B3n de la metodolog=C3=ADa, se observ=C3=B3 una mayor part= icipaci=C3=B3n e intercambio en actividades colaborativas, lo que respalda = las afirmaciones de autores como Jim=C3=A9nez (2022) y Caballero & Quiv= io (2024) quienes destacan el rol del aula invertida en la promoci=C3=B3n d= el aprendizaje activo y la interacci=C3=B3n significativa entre estudiantes= y docentes.</span></p><p class=3D"APA7MAEDICION" style=3D"margin-bottom:0p= t; text-indent:0pt; line-height:150%"><span>Sin embargo, se identificaron a= lgunos desaf=C3=ADos en la implementaci=C3=B3n de esta metodolog=C3=ADa. Un= o de los principales retos fue la disponibilidad y el acceso a recursos tec= nol=C3=B3gicos adecuados, lo que puede influir en la equidad de la aplicaci= =C3=B3n de la estrategia. Adem=C3=A1s, la capacitaci=C3=B3n docente se perf= il=C3=B3 como un factor determinante para el =C3=A9xito del aula invertida,= ya que algunos profesores mostraron resistencia inicial a la adopci=C3=B3n= de este modelo de ense=C3=B1anza.</span></p><p style=3D"margin-bottom:0pt;= line-height:150%"><span> </span></p><p class=3D"APA7MAEDICION" style= =3D"margin-left:54pt; margin-bottom:0pt; text-indent:-18pt; line-height:150= %"><span style=3D"font-weight:bold"><span>5.</span></span><span style=3D"wi= dth:9pt; font:7pt 'Times New Roman'; display:inline-block">   = 0;   </span><span style=3D"font-weight:bold">Conclusiones</span><= /p><ul style=3D"margin:0pt; padding-left:0pt"><li class=3D"APA7MAEDICION" s= tyle=3D"margin-left:14.33pt; margin-bottom:0pt; text-indent:0pt; line-heigh= t:150%; padding-left:3.67pt; font-family:serif"><span style=3D"font-family:= 'Times New Roman'">La implementaci=C3=B3n de la estrategia did=C3=A1ctica d= el aula invertida en el bachillerato t=C3=A9cnico de la Unidad Educativa "G= eneral Medardo Alfaro" ha demostrado tener un resultado positivo en el dese= mpe=C3=B1o de los estudiantes. </span></li><li class=3D"APA7MAEDICION" styl= e=3D"margin-left:14.33pt; margin-bottom:0pt; text-indent:0pt; line-height:1= 50%; padding-left:3.67pt; font-family:serif"><span style=3D"font-family:'Ti= mes New Roman'">El dise=C3=B1o de la investigaci=C3=B3n Los resultados de l= os estudiantes del grupo experimental muestran la efectividad de esta metod= olog=C3=ADa en comparaci=C3=B3n con los del grupo de control, se refleja no= solo en la comprensi=C3=B3n de los conceptos y contenidos t=C3=A9cnicos, s= ino tambi=C3=A9n, en que propicia un aprendizaje mejor y significativo, en = la participaci=C3=B3n activa de su propio proceso de aprendizaje, </span><s= pan style=3D"font-family:'Times New Roman'"> </span><span style=3D"fon= t-family:'Times New Roman'">el aumento de la motivaci=C3=B3n y compromiso y= participaci=C3=B3n en actividades colaborativas y pr=C3=A1cticas, lo que f= avorece el desarrollo de competencias y habilidades que le ser=C3=A1n =C3= =BAtiles en su futura inserci=C3=B3n laboral.</span></li><li class=3D"APA7M= AEDICION" style=3D"margin-left:18pt; margin-bottom:0pt; text-indent:0pt; li= ne-height:150%; font-family:serif; list-style-position:inside"><span style= =3D"width:3.67pt; font:7pt 'Times New Roman'; display:inline-block"> &= #xa0; </span><span style=3D"font-family:'Times New Roman'">Aunque los resul= tados son prometedores, la investigaci=C3=B3n tambi=C3=A9n identifica ciert= os desaf=C3=ADos en la implementaci=C3=B3n del aula invertida. La falta de = acceso equitativo a recursos tecnol=C3=B3gicos, la resistencia inicial de a= lgunos docentes, as=C3=AD como ofrecerles capacitaci=C3=B3n a quienes lo re= quieran, constituyen aspectos importantes a considerar para promover un ent= orno educativo m=C3=A1s inclusivo, din=C3=A1mico y colaborativo que contrib= uye a mejorar el desempe=C3=B1o de los estudiantes.</span></li></ul><p styl= e=3D"margin-bottom:0pt; line-height:150%"><span> </span></p><p class= =3D"ListParagraph" style=3D"margin-left:54pt; margin-bottom:0pt; text-inden= t:-18pt; line-height:150%"><span style=3D"font-weight:bold"><span>6.</span>= </span><span style=3D"width:9pt; font:7pt 'Times New Roman'; display:inline= -block">      </span><span style=3D"font-weight:bo= ld">Conflicto de intereses</span></p><p style=3D"margin-bottom:0pt; text-in= dent:0pt; line-height:150%"><span>Los autores declaran que no existe confli= cto de intereses en relaci=C3=B3n con el art=C3=ADculo presentado.</span></= p><p class=3D"ListParagraph" style=3D"margin-left:54pt; margin-bottom:0pt; = text-indent:-18pt; line-height:150%"><span style=3D"font-weight:bold"><span= >7.</span></span><span style=3D"width:9pt; font:7pt 'Times New Roman'; disp= lay:inline-block">      </span><span style=3D"font= -weight:bold">Declaraci=C3=B3n de contribuci=C3=B3n de los autores</span></= p><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"><span>T= odos autores contribuyeron significativamente en la elaboraci=C3=B3n del ar= t=C3=ADculo.</span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; line= -height:150%"><span> </span></p><p class=3D"ListParagraph" style=3D"ma= rgin-left:54pt; margin-bottom:0pt; text-indent:-18pt; line-height:150%"><sp= an style=3D"font-weight:bold"><span>8.</span></span><span style=3D"width:9p= t; font:7pt 'Times New Roman'; display:inline-block">    = 0;  </span><span style=3D"font-weight:bold">Costos de financiamiento <= /span></p><p style=3D"margin-bottom:0pt; text-indent:0pt; line-height:150%"= ><span>La presente investigaci=C3=B3n fue financiada en su totalidad con fo= ndos propios de los autores. </span></p><h1 style=3D"margin-left:54pt; text= -indent:-18pt"><span>9.</span><span style=3D"width:9pt; font:7pt 'Times New= Roman'; display:inline-block">      </span><span>= Referencias bibliogr=C3=A1ficas</span></h1><p class=3D"Bibliography" style= =3D"margin-left:36pt; text-indent:-36pt"><span>=C3=81lvarez, A. (2020). </s= pan><span style=3D"font-style:italic">El alumno como protagonista de su pro= ceso de aprendizaje</span><span>. Unir, La Universidad en internet. https:/= /www.unir.net/educacion/revista/el-alumno-como-protagonista-de-su-proceso-d= e-aprendizaje/</span></p><p class=3D"Bibliography" style=3D"margin-left:36p= t; text-indent:-36pt"><span>=C3=81lvarez Zeas, M. L., =C3=81lvarez Zea, B. = G., D=C3=ADaz Samaniego, M., Correa G=C3=B3mez, A. N., Sarango S=C3=A1nchez= , J. F., & Vasco Chango, M. A. (2024). Implementaci=C3=B3n de la Evalua= ci=C3=B3n Formativa mediante Quizizz: Investigaci=C3=B3n-Acci=C3=B3n en Con= texto Educativo</span><span style=3D"font-style:italic">. Revista Cient=C3= =ADfica Multidisciplinar G-Nerando, 5</span><span>(1), 763=E2=80=93780. htt= ps://revista.gnerando.org/revista/index.php/RCMG/article/view/225</span></p= ><p class=3D"Bibliography" style=3D"margin-left:36pt; text-indent:-36pt"><s= pan>Araya-Moya, S. M., Rodr=C3=ADguez Gutierrez, A. L., Badilla C=C3=A1rden= as, N. F., & Marchena Moreno, K. C. (2022). El aula invertida como recu= rso did=C3=A1ctico en el contexto costarricense: estudio de caso sobre su i= mplementaci=C3=B3n en una instituci=C3=B3n educativa de secundaria. </span>= <span style=3D"font-style:italic">Revista Educaci=C3=B3n</span><span>, </sp= an><span style=3D"font-style:italic">46</span><span>(1), 1-28. https://www.= redalyc.org/journal/440/44068165004/html/</span></p><p class=3D"Bibliograph= y" style=3D"margin-left:36pt; text-indent:-36pt"><span>Arellano Becerril, E= ., & Escudero Nah=C3=B3n, A. (2022). Tendencias de investigaci=C3=B3n d= e aula invertida con aprendizaje colaborativo: una revisi=C3=B3n sistem=C3= =A1tica. </span><span style=3D"font-style:italic">Revista de Investigci=C3= =B3n Educativa de la Rediech, 13</span><span>, e1492. https://www.redalyc.o= rg/journal/5216/521670731017/html/</span></p><p class=3D"Bibliography" styl= e=3D"margin-left:36pt; text-indent:-36pt"><span>Barros Macas, M. C., Rojas = C=C3=A1rdenas, H. M., N=C3=BA=C3=B1ez N=C3=BA=C3=B1ez, G. L., & Maliza = Cruz, W. I. (2024). Flipped Classroom en la Formaci=C3=B3n T=C3=A9cnica de = los estudiantes de Tercer A=C3=B1o de Bachillerato en Contabilidad. </span>= <span style=3D"font-style:italic">Dominio de las Ciencias, 10</span><span>(= 3), 2008-2031. https://dominiodelasciencias.com/ojs/index.php/es/article/vi= ew/4021 </span></p><p class=3D"Bibliography" style=3D"margin-left:36pt; tex= t-indent:-36pt"><span>Caballero Cifuentes, L. J., & Quivio Cuno, R. S. = (2024). </span><span style=3D"font-style:italic">Pautas para la investigaci= =C3=B3n y an=C3=A1lisis de datos.</span><span> Lima, La Cantula. https://fo= ndoeditorial.une.edu.pe/index.php/lacantuta/catalog/view/42/40/44</span></p= ><p class=3D"Bibliography" style=3D"margin-left:36pt; text-indent:-36pt"><s= pan>Cede=C3=B1o-Escobar, M. R., & Vigueras-Moreno, J. A. (2020). Aula i= nvertida una estrategia motivadora de ense=C3=B1anza para estudiantes de ed= ucaci=C3=B3n general b=C3=B3sica. </span><span style=3D"font-style:italic">= Revista Cientifica Dominio de las Ciencias</span><span>, </span><span style= =3D"font-style:italic">6</span><span>(3), 878-897. https://www.dominiodelas= ciencias.com/ojs/index.php/es/article/view/1323.</span></p><p class=3D"Bibl= iography" style=3D"margin-left:36pt; text-indent:-36pt"><span>De Jes=C3=BAs= Ulerio, L. F. (2024). Las estrategias didacticas en los procesos de ense= =C3=B1anza-aprendizaje. </span><span style=3D"font-style:italic">Pedagogy, = Culture and Innovation, 1</span><span>(1). https://www.mlsjournals.com/peda= gogy-culture-innovation/article/view/2773</span></p><p class=3D"Bibliograph= y" style=3D"margin-left:36pt; text-indent:-36pt"><span>Delgado Fern=C3=A1nd= ez, J. R., & Cuj=C3=AD Coque, D. E. (2023). Impacto del Aula Invertida = como estrategia de aprendizaje de la funci=C3=B3n lineal, en estudiantes de= bachillerato. </span><span style=3D"font-style:italic">Prometeo Conocimien= to Cient=C3=ADfico, 3</span><span>(2), e78. https://prometeojournal.com.ar/= index.php/prometeo/article/view/78</span></p><p class=3D"Bibliography" styl= e=3D"margin-left:36pt; text-indent:-36pt"><span>Dom=C3=ADnguez Rodr=C3=ADgu= ez, F. J., & Palomares Ruiz, A. (2020). </span><span style=3D"font-styl= e:italic">El "aula invertida" como metodolog=C3=ADa activa para fomentar la= centralidad en el estudiante como protagonista de su aprendizaje</span><sp= an>. </span><span style=3D"font-style:italic">Contexto educativos: Revista = de educaci=C3=B3n</span><span>, 26, 261-275. https://dialnet.unirioja.es/se= rvlet/articulo?codigo=3D7657253</span></p><p class=3D"Bibliography" style= =3D"margin-left:36pt; text-indent:-36pt"><span>Ellerani, P., & Patera, = S. (2021). </span><span style=3D"font-style:italic">El modelo pedag=C3=B3gi= co-did=C3=A1ctico expansivo.</span><span> Abya-Yala, Universidad Polit=C3= =A9cnica Salesiana. https://dspace.ups.edu.ec/bitstream/123456789/21831/1/E= l%20modelo%20pedago%CC%81gico.pdf</span></p><p class=3D"Bibliography" style= =3D"margin-left:36pt; text-indent:-36pt"><span>Guerrero Miranda, L. S. (202= 3). </span><span style=3D"font-style:italic">Aprendizaje colaborativo en la= s actividades pr=C3=A1cticas en el laboratorio de qu=C3=ADmica</span><span>= [Tesis de pregrado, Universidad de Guayaquil, Ecuador, Guayaquil]. https:/= /repositorio.ug.edu.ec/items/bf2f7b68-5cfa-4e3d-987f-b7adc61a339b</span></p= ><p class=3D"Bibliography" style=3D"margin-left:36pt; text-indent:-36pt"><s= pan>Jim=C3=A9nez Bravo, G. T. (2022). </span><span style=3D"font-style:ital= ic">Implementaci=C3=B3n de modelo aula invertida en el proceso de ense=C3= =B1anza-aprendizaje de la asignatura emprendimiento y gesti=C3=B3n para los= estudiantes del Bachillerato general unificado</span><span> [Tesis de maes= tria, Universidad Polit=C3=A9cnica Salesiana, Cuenca, Ambato]. https://dspa= ce.ups.edu.ec/bitstream/123456789/22692/1/UPS-CT009824.pdf</span></p><p cla= ss=3D"Bibliography" style=3D"margin-left:36pt; text-indent:-36pt"><span>Med= ina, E., & Ponce Pastor , R. M. (2024). Aula invertida como propuesta d= e innovaci=C3=B3n educativa para el curso de investigaci=C3=B3n en la UNES.= </span><span style=3D"font-style:italic">Revista Multidisciplinaria Voces = De Am=C3=A9rica Y El Caribe, 1</span><span>(1), 537-571. https://remuvac.co= m/index.php/home/article/view/56</span></p><p class=3D"Bibliography" style= =3D"margin-left:36pt; text-indent:-36pt"><span>Huanca Ordo=C3=B1ez, M. M., = Rivas Rivas, J. B., Espinoza Palomino, J. L., & Vinueza Le=C3=B3n, V. E= . (2024). El Aula Invertida como Motor de Motivaci=C3=B3n: Innovaci=C3=B3n = Pedag=C3=B3gica en la Educaci=C3=B3n B=C3=A1sica. </span><span style=3D"fon= t-style:italic">Polo del conocimiento, 9</span><span>(12), 728-743. https:/= /polodelconocimiento.com/ojs/index.php/es/article/view/8508</span></p><p cl= ass=3D"Bibliography" style=3D"margin-left:36pt; text-indent:-36pt"><span>P= =C3=A9rez, J., Rodr=C3=ADguez, C., Rodr=C3=ADguez, M., & Villacreses, C= . (2020). Espacios maker: heramienta motivacional para estudiantes de ingen= ier=C3=ADa el=C3=A9ctrica de la Universidad T=C3=A9cnica de Manab=C3=AD. Ec= uador. </span><span style=3D"font-style:italic">Revista Espacios,</span><sp= an> </span><span style=3D"font-style:italic">41</span><span>(02), 12. Obten= ido de https://www.revistaespacios.com/a20v41n02/a20v41n02p12.pdf</span></p= ><p class=3D"Bibliography" style=3D"margin-left:36pt; text-indent:-36pt"><s= pan>Quinteros-Pallarozo, C. G., & C=C3=A1rdenas-Cordero, N. M. (2021). = Aula invertida y juego de roles: Implementaci=C3=B3n en el bachillerato t= =C3=A9cnico agropecuario</span><span style=3D"font-style:italic">.</span><s= pan> </span><span style=3D"font-style:italic">Revista Arbitrada Interdiscip= linaria KOINONIA, 6</span><span>(3), 106-127. https://fundacionkoinonia.com= .ve/ojs/index.php/revistakoinonia/article/view/1306</span></p><p class=3D"B= ibliography" style=3D"margin-left:36pt; text-indent:-36pt"><span>Rodr=C3=AD= guez-Borges, C. G. (2020). Software Development for Transformer Model Suppo= rting Significant Learning Electrical Machines. </span><span style=3D"font-= style:italic">International Journal of Psychosocial Rehabilitation, 24</spa= n><span>(02), 591-599. https://www.researchgate.net/publication/339148552_S= oftware_Development_for_Transformer_Model_Supporting_Significant_Learning_E= lectrical_Machines</span></p><p class=3D"Bibliography" style=3D"margin-left= :36pt; text-indent:-36pt"><span>Sandobal Ver=C3=B3n, V., Mar=C3=ADn, B., &a= mp; Barrios, T. (2021). El aula invertida como estrategia did=C3=A1ctica pa= ra la generaci=C3=B3n de competencias: una revisi=C3=B3n sistem=C3=A1tica. = </span><span style=3D"font-style:italic">RIED. Revista Iberoamericana de Ed= ucaci=C3=B3n a Distancia, 24</span><span>(2), 285-308. https://www.redalyc.= org/journal/3314/331466109015/html/</span></p><p style=3D"text-indent:0pt">= <span style=3D"font-weight:bold"> </span></p><p style=3D"margin-bottom= :0pt; line-height:150%"><span> </span></p><p style=3D"margin-bottom:0p= t; line-height:150%"><span> </span></p><p style=3D"margin-bottom:0pt; = text-align:right; line-height:150%"><img src=3D"data:image/jpeg;base64,/9j/= 4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE= BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ= EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/wAARCABAAHoDASIAA= hEBAxEB/8QAHgAAAwEAAgMBAQAAAAAAAAAABwkKCAQGAAILAQX/xABLEAAABgIABAMBCA4GCwEA= AAABAgMEBQYHCAAJERITFCEVCjFBUXeRtrcWGSIjJDg5YXFyc6HB8BcYN0KB0RonUlNVWGeGpbH= S1f/EABwBAAIBBQEAAAAAAAAAAAAAAAAHCAECAwUGBP/EADsRAAIBAwIDBAYHBwUAAAAAAAECAw= QFEQASBhMhBzFBUQgiMjdhkRRxc3ahs8EVI0JDgbTwJzaTpOH/2gAMAwEAAhEDEQA/ALGsJ8xjT= PYOTawGM87VJ5ZpBVNuwq9j9p0mxyLpYe1NpFRNyYwjqYcmEQKCMOV8fu9AAQD1wDzzM25ewXjT= X61YcyNbMczjvJc+0fPqrMOY0sm0QrPmEmcs1SP5OXYlcFKsDKSbu2hlAA3giPURlQ1wKA7E4CH= 4RzXiz17jB795gw98Pzfz8PFMPuiIvTCWuoh8OUbGI/41E/X5x6fMA8Svl7KrJwH2wdntqpqia8= Wy+m4TTUt2gpajaIKaoiMUoWJIahG3BsSQLtwCN/RhGCHtKvHGnZdxzcKqCG13Cz/s6GKptctRA= W59TTScxd0rSwOu0KCkzArnrjoRlyvebBsdnDPtF1yzUhWb01uLaxC0viUenX7PHLQVekp8oPWs= SmlCyqLgIw7UeyOYLJC4BYy6nh+GpTmn16dBD16dR6e9+j4f8B+EPzdOITuTl+UPwT+ZLIX1d2Y= OLsyj17v1hD1/N0/n+evHBekFw7ZOG+OoaWxW6mtdNU2OkrZqekUxwNVS1VbHJKsWSkW5IYxsjC= Rjb6qDJ12/YXe7tfeDpqm8V89xqKe7VFJFPVPzJhBHTUkiRNKQXk2tKx3SMX69WIwAh3nacw/IW= pFRo2JcIyxK5lHKjSVlpC4Ebtnb+o06MURZGWiEnZFm6EzNP3CjZm/VbreSbMXqrcqbwW7hBRuH= tLedVn+g1/LsJnPKsHAXuNa2KA+zTZq7QExKwsokV3HzHsZlLv1I9nItlU3LJJ6Ri4UaqJLlaEQ= USMbm+6L0XxNyMYrrlUCOWwBAEZiPd4QroXe7jIETHp2+IUqzMVOgiPRRIDAHUOLDsXv69J42oE= hUlGqtXfUqrvK4oxEgsjwTiFZKxJmopfe/LiwM38ECfcgn2gHQADhLZ5cUZVVJfJYsAe4jp/nl8= NOjU/iOMeY9qpoPKQdv2loePc/yeyrCSY5NzLnOGlIA2M3tFctlKk3uOWGUpHoyLqdjfaLSBQbl= cGRaPXjdQpRdAd0+uVxmY/V7E1wzZkuk2SxExzBSd+yhF2WuOKLMyYsSKSViYWeNCOrTiHdKdV0= ZFiRtHHTHvSKQgdAVv7of9NE6wIdOv9Yeg+v/AGfkjhIHMPzfbU9SOWprshNSsRjp5rJUcnW9nG= GEQsEi+frV2I841Mu1SkArjWvyrqPZOV0mp3ssKqxiqJILIUVOaE9lSzNlgoycKPLwx3DRqwVnu= lqBISDWJj9pdeX0q+eIRzKNZZmx26fPH7pcjZsyaNW9iUWcu3DhQiCDdAiiqyxyJplMYxQHmWLc= HVCoTstV7Zstgas2WBfLxk5Xp/LdCiJuHkWxuxywlIt/PN3rB63UASLNnKKayRwEpyFMAgEhWts= pyepTKGDKjD4t3Tf5Jk8g46hYe0T8rQ2EGtcXlkiWsbLSrCJuyxW0OWXUbrum7Fk4UIxKYhEXCg= dD9ogtT8d7lc5na3C+UH9mjqsrdcyWYzmpyDOOlQfwczHkZplcPo+Tb+XOV6r4xPL9xxAglUL0E= TUMIBOSwAUsSwwe8DoOvn56NWFY5zdhzMCT5fE+VcdZNQizppya1Autat6caot1FIj80BJvwZmV= AphSK48MVAKYSAYAHpw8h5+wbiNy1Z5VzHi7Grt8QVWTW+X+qVJy9SARKKrRtPSzBdykBgEplEk= zEKICAmAQ6cSX69YnZ6J87eHwXiW0Wp1QUYywx8ilOPW60hOwEpg+ZvJ4abNHNmDKRRYWBkzesD= mZJmSVYMlO0V0zKnFugeqLfm47ObKZQ2PyBbkGNdCNsci2rck1Rm3sld5mcQrUMwdzDSXSjqxW4= muyDMjNu18QhQim6CqKRVhOcpQCxYhQqtnZ19Y4AxnA885/po1TDtbsfEZE1ey/KacbVYBjMm1I= KYcuQRyzjVxVKMWatTNBM1qm3zidgIILBHMpuOhxmWoBIvE1G7ARcp96fN1FzurQ9QMW3fcTZbC= M3cJqVt8VK5ebZMx4XHlqfpXK0+xY2BtkaeCqko9ja8zbRztrGJg4QdRT9JyQ7hq5VFX+53Lqwl= oXy59yHOHpa9Sh8oJYRSsIXSYjJUES0zJKR4sY32dDxQoCqNpkAd+N5gFATa9gpeGfxATRZjSyP= 5LOpyW6C18e1n+kLKknR6njF2RvdbLZ2eT8mtFyMQXdR7II+PjZJZeQcSUiwZIiq2KK53KzVutQ= KpVSuSDIB7I3eyCcEZ8D3dR46NUawe4+pNnlmMBW9nNf56ck102sbDw+YcfSMpIuljgmi1YsGth= Vcu3KpzARNBumoqoYQKQhhHpxowFAMACUeoCACAgHUBAfUB693r1D4ePna7OT/Ldm6Gy/qnUTaC= k5KbzbNRZxlR9UZOov4A6S5X6J1I21y8ozk0VvKrR6zZuKBwBwk4DqdFRI11LnN7pVCq1mps7c3= etKvX4autXsn4r2SdtoSNbRqDqQeLgos7fOEmxVXblZQ6q651FVDmOcTDkFNuGQxHmHXB/An46N= Za1v/GJwF8teK/pzBcUw+6I/7EddflQsX0RNxM9rf+MTgL5a8V/TmC4ph90R/wBiOuvyoWL6Im4= nr2g++/sh+yvP5MmoNcD+6TtS+1sv5kGk58nH8ofgr9jkL6vLLxdkX+9+sP8ADiE3k4/lD8Ffsc= hfV5ZeLsi/3v1h/hwjPSe94VF92bf/AH1z06fR1/2PW/eCr/sbdpM/OB5cVi3gx9U7biheLRzTi= osqWEjJdyVgxudalSoryNaGTU/B4+VI8ZtncI5fCnHeMZ01eOGaTrzaCUMZUHn44NqMXjLHkLme= IqFYRLHwcR1olmZRbFL7lJjFv5RSVUTjUAACNGrd15NumAEbJkTEChV/tbsbW9TcE3bPdug5ux1= yikhFJKIrvkfbDss5YIuutwZ+0nLRn1RdSqK63jOE/vCSnZ3H7SGS9/pIGsnQf9R+bg/xpHp197= qA2b/3xHtHlKBVjEihuhI3YPQ4xkeefq6DPg/NATOODuZbs3y0XlFzvQr7fNg2m2cFYYuCfsqwx= mE8YxuOphmSRTSiTMY4zBCflHSHiKCLsVlzAPVIExL2PbHlX52zppNpPO4+gkozY/XfD8JSLZjm= ceMo1/NxPhMX4x7GRcKjFpWCqTqDtw2aO3bdlIs5eSAHgO2rNu7ZdptzfNWtyrqnjGsmtOPckvU= XDiBqeQGkazPZ02aCjp6nX5SLkZKNePmzVJV0eNWWbPlGyKy7dBciKokPz3mAa5MNqkdNHM5YS5= ycOWTRKHLWZE8IKr+sp25uA2AC+RApoVUixhEehVhFAfuwHigeVCFCbSpZyAvgQB3eA6+Hx8tGk= ZYgsnOCgLRjSFtGjGFwhoqx1KPn7sthKltrEjFNZVihKWIZSFsjFmhLN2JFn5X8dHt003SYOEW3= oBROeqOpexVH5xmwmwtsxZYYbDttf5jVr18deR9kSpLDKxDiHO3BJ2d10fpILHSFRuToBBA/aPQ= OKMePww9oCPxfv+IOLDLuz6iqSMHGcnODnvPj/nTJNTm2vUXYWV54kBscXFdgXwMRdMj3IQeR9h= kQNgmWqqveAuwedvttySNH8G9Vjh06kEDcY4d6KczTl37M5HvGjVdG946vJ5BvFrxyVcsDRxVHk= qrKRlct9Xn3bd4hM1lbtSaTDQnaomZRVrIgm/kGJaJcG7+66bEZqyNgDGU3YJDJGKwsg3BhI1qR= i45oFUszeozAtJNyUG73wpp0ikl4I/fkTCuQRTKI8DDCfMsxlm/cPI+msFRbxE3fGhboaWs8qMF= 9jD4KRKR8W/8AIeUk15P8LVkU1GnmGSP3tM/i+GYSgN++Qfy1KiNQ6n+Jem1iCR4Y/wDe7RpYFs= Yc1TbDSTcfGOzuGV0bm8Qwf/QtXoOs1+vPrEunfZGSyABBZSrhF37MjoivuRK6VQ8FNQ4oiqdc5= SZrzJywNssi8tjTGuQOPZJPMWAJ3OaVuxJIOotnOLwmRslSk8wlWRl35I906aNo6KWFgV15hywl= jKJAY7cyJq9+POLBKRjaqAB94ABxkgDuyemPL5jRqLvPOKebPsNiVDD9t0Vx5XK+k6gnvtvHmKK= rUbYZWAIYjUnthlZVEUkHPcIv2yDFFFbqBUyJEKUoYM+1O8w7/ldyD/4X/wDV4sTvnMqxrQN3Kl= o3I0S8Pb9cHNabsLYz9hfYm1GzQ68y1M58aTSlxBBBAya4JR6g+KYAS7yfdcMg6m+I37v/AJ4yi= okQAbEXIDYGeoOOvtHyI/Tpo183rW/8YnAXy14r+nMFxTD7oj/sR11+VCxfRE3Ezut34xOAR/61= Yr+nMFxTD7oiEBwjrr8qNjD5qib+fTie3aD77+yH7K8/kyag3wOP9Je1H4y2XH/LCNJ05OP5Q/B= X7HIX1eWXi7Iv979Yf4cQmcnIwBzD8FdfgRyD+/Hlm/y4uyKYo9egh6j/AADr+8f8ve4RnpO+8K= i+7VvHyrbkf1H46c3o6MDwTXDyv9Wf+lbx+mlb86P8m5sR+wx99Z9O4WzyPdQtYM7ah2S25jwRj= LJNoSy7aYVGwW+qRczLIxTaErSrdgi+doHcJNkFXLhRIiZygmdZQ5BKY3Xhk3Oj/JubEfsMffWf= TuEzcoTma6laf6wz2Ms326ywdwe5OsdpasYikWSxIKREjEwDRop5+KZLsyLKLsHJBQUWKoQCAY4= FKYB4j2u4wnZuzzD7Pf3IP10/tYd5iGDK3oDzG6ktgtJWq1ps/wAcZhpMQ0fPV/sYWUnDFfRTN0= 7WWdmZFlYZ8Zsk4XW8Ni6I0E5kSAQG9v8AZRk652FdxIXAevSy8k5qTkuZHNAcKZsSLJYTY2Iqh= bmE6VAqzYi3sduf2QPZDkK0EBMHjcJr2azO95pPMfpCmKa9OlgbPPUbHFHj5NoklMI1ODfGdzFj= mW7Rd0jHtyFXm596JnKhI+NJ1cKlMicCMBtkaCHuh2LiGh/AKkvVo5scB6Cl4eurFqifqHvCToU= 3UA98OvTjI4OFVj6whYHJyehXGfHp4aNHHO3Os2UuWx1pwJoZgKLyqWoSs1DHlpGvWa6zNqUrrk= WUzORcNWJaHRh6yg8TUSaSEg8c+bbi3dKiyM4TbB/O165sO/1g3Zw7qnshiHG2MnF3tEdG2mEWp= Nsgrewh5SGkJRi8ZjIXaSQbHdEbIqIKrs3BDoiYfD+6A3GHuU3sNiTRvc3Y2t7RyyeOXckwsFEL= aZqMlHaMJZK9dgdvoqQNGMH7xk3mUmx1SvTolaHWZNiqrACyRhKVszRi3P3PpwNknDlxjL5R5Cd= x3HMrHEEeJsXL2Kocm0kG5Cv2rNx3tHBTJKCdApRMA9pjB68W7VyUCAgRk7zuySFBOMdPP+oHfn= Ro96m7R5CntseYfX8I6x65xOX8Z0PYGUoExQ8dO4e9ZJt9cypHRkNFXWZNakwnULDIKISM0kkeI= F9LkSclctSF7BVXrbmLe6scwfMOR8PYVg7XtXNlySGQcYu4hZ1EwRZSah1bcKEeS2xqqXsqSSj2= yPdYXnhlXEDC5E3iFZXygOn22ffDr/u89D8XXpn2D+H5/wCQ4D2s2csVa5c7XaC4ZuuEbjmpyUx= nCspWCxg5bxSErLT0NKxqD5ym3VKxSfNYx0KDt2CTY6hkEfGBRwkU9wODIAgb91GfEk9FGMeXj9= fho02nZHZHmx06va+OsDaxVW7zdsw3C2HNjJ/XXbslNym5XVLK1hiVPIkOLVo1QKmcjdRWWOTu9= ZFX3gw8HON351tzBjur7260VWgUS8O0SqOYmAnIGbThgft2EpPQcgvbbRCy54AzpJxIw4gi7FM6= BTLNBdt1Dinmp7lZUyBuhijCmOdpZXX7XObpGO7FG5Uqk7YYauScfkNFWTd5Dl5CruY6Vn4Vo1B= tGxzPziccgpHuVRFqo5duSKy3uqDKrOcUmZ8wZLeoXytl8bw5WzSY428E9fEvX7IrjbPB+ygVTe= jTyPf7C+/eY7U/BpHGCF3KvrgnAD5A8eucKR5fMDGjTeNi1Sr+6FcELEEBIs/xEoQQ94SHocgJR= 9OvXqAgPX4h4q/4kxzqHT3QBrr0/wBnCn1dO+KzuMMpysQ8RGM/HJJH4dDo189TEOuOy1Hyri68= yut+d14Wm5DpVsliR+Lba4eKxldssbLviMklo1BJZ0dozVBukqugmooJCHWTKInLSNuDdNQd+qT= SanmhXbPBIUuefWCJB7r7fmLoz5/GezFSSblKj3SFO1TRMJygjINjgoHcZYUx7RfF4ZA94oB+jj= 0MgmID1KUevxgHQf09A68OfirtnruK7vZ79UWf9lXewx1EdsrbNdHgkhFTjmsy1lFXRuxGVB2KN= rEEHOdJrhzshp+G7ZdbNBeFuNsvbQNcaO6WtZo5jT9YwGpaykkRdx3EB+pCkYAxqR+C5YmI4GyR= l61V5j0DUcgwy5nVWQvUIpSLA1cqJKJHIpLt5qMlmnitlFG7pMaiuRdBVVBZAyaihDNQw1sJv7g= dBpD7S4nhtlMZNippDsBrHJx9usEagY/aDqz48bpxM5Ot26IlVeP4OAZOmzchlAQmVzCHDe39cg= pVI6MnDRMgioUSnRexzR2kcpvQwGI4SOU4GD0EDAIevxcD0+CsUpqLOIqlRFcerG7zSFSIrUZEp= x9O9OQrasY7TU9A6nTWKYQ9OoB7+ivPaZW8SxCn4opor+iKUhqLjS0RulKnfinu1thtNSoViWCT= JU0zMSZqeTrrbWns5g4el+kcO1ctmd2DzQUNRVi3VBwAfpNrr5blTyZACs0b08wXokyEAgbWyD1= 93rwZO0WUk0L9iq6hGJWFhDysjCSiK8TKsJxqwk00TMJ6vSjOSj2pnka/RZP0DpKNnbYvVVMMU/= aM+XQIemKrP69ffyRdP0f8V4ZKbEdYQk0LJEJOYS3t00kFLXHKFTl5ZugQySDSyqdvg2lqmmcxC= knk3yqYiDlBZvIETeplBsVUqKZVzFMqBQBQxCCmQxugdxiJmOoYhBHqJSCooJQEAE5xDuFbTNEJ= WNI9QkJOVjmKtJH3YVpVVUl7vbVEJwSyJkAsemNTy1WqERmUANJDkRyHA9ZUZneMnrlGd9vTDt4= Y31p5fuqGpMi/ncI4rjK9Z5Judm6tkk8kbFZgYqdoqsWkxOO3rqPZriQouG7AzZNz2l8cFAKHHu= +0L1wfbPpbhuarKHzq3cNHSdkCyTYR4KMK2SqNxGAB6EQPbCpEbCHlehjgKxgFYe8NmceCHUBAf= hDp8/GEknqWJPcST1I78fh8sjx16NSocw3Z/lTS2zOR6bsNqZl+0ZZx9OBVrRfcer1+sp2dwzYs= lEHDp00v0I6lwQaqoNkXctHFekSRBHu8FNMAxhy9seUDOvNPxtfNSsSXvH2u+MXyVwfJXJ8aakY= FCKpzxi5cTcuL6TZkd2C2O0m0dFtpR+uRmr5gAKm3d+Xs5k8QYompB1LTOM6DLyr9UV30nKVCvv= 5B4sIAUVnTx1HquHColKUoqKqHMIFAOvpx2Gu06pVBsozqlZgKy0WUFZVtAQ8fDt1VhAAFVRGOb= tkzqCAAXvMUTdAAOvGYSgKVAfONvrOSvcOoAwPq+WjWWMLaI65a9ZkyDnzGNWlIfJWUS2MLnLu7= LNyjSQC02Nva5kEIt+8XYsfMTTZFwmLZJPwEyign2pGEvALzDy4uX5ttk+1ZIuFRibNkYy6Mfc3= 9NvkrFOVZGOSTaAM9H1+WTbElUECJN3CyzdN4YpEiL9xigHGsdtMtzuDNfMnZSrNbPbJ6qwCasX= DD5vynmpOTYQpJWV8iUzwIKvhIjPTxmopuAho18KS7cwAuktLF+Cs2VHEtLg8Tzb+/WKvWC1IyV= viLNWaq9Wxzd4mfu3sVvM1+bdRyylmzHV6DLWSWWmJy9R1EmfKoyqovZFoXd22zLV0ElwnuEVEp= rFoabmkbJSkPPqXkf+WsAelVFkZBM1QeVvaF11ztzvstFcIqCmoZq1hSNWVPJB5kaPMsNNHGuP3= jTFKlmK7+UIQHCCVXUwZV055a2cqzjGiZAaUqULiFNHCFEeIZBdQ9uYBXl3kWlQ3MuylmsrLqMX= 0XJETZSXmzpPW8ks37FVXJz9JHkmctdBs1fnx3NpNXKrQjR2plO3FQcLPFCJsk0FTTBU1TOlVEk= 25SHMK51CkTAxjFAQnT9JNmoKYipV5TIM60TaFbCEwpK1J7Y15KwyUHTrBYivnC6hlptGmRFjt7= Uzt1+CWHLNzfR4hMVuuISBvyZr/u00tM2fG862lYlOOqkygq+lmxICbyBWqdKmGzMajZp2cJDvF= bCetIN26rsGp5Kkxkk7WVTssrIwu1qeHrQKhIaTiekZGikkeSolQJuSSNeWGTeil1fepJLNh1Kg= IW1qaXiW+GCSar4brVZZUjSGCNy5V0J5hEveA67WAIAUoScsF1pi9ab6mr7O432buUYu1z0EvBQ= OPZde2zLNCRl6xWpEYyOaV8jwI1+6bV2Ok3KxDtjCdBouuqJhT68bvAw9A9R+cR/f8ADws/AWDd= hS5xSuuZlptzSaQ+uz/GUfbriheJGLGe8KnslhdJSjxdKecVSAa2F0+OKjBo9vtshWDVq2QbDwz= QCB0D3w+b/LjmrlSQUUsUENbHXEQq800BDQrI7OyxRsM7jHFyxIdzDmFlUkAa6S11lRXwzT1FFL= RKJ2jghqVKztGiRhpJFPRQ8u/YB/AFJ9YnH//Z" width=3D"122" height=3D"64" alt=3D"= editorial1.png" /></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-= align:justify; line-height:150%"><a id=3D"_Hlk92188167"><span> </span>= </a></p><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify;= line-height:150%"><span> </span></p><p style=3D"margin-bottom:0pt; te= xt-indent:0pt; text-align:justify; line-height:150%"><span> </span></p= ><p style=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-h= eight:150%"><span> </span></p><p style=3D"margin-bottom:0pt; text-inde= nt:0pt; text-align:justify; line-height:150%"><span> </span></p><p sty= le=3D"margin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:1= 50%"><span> </span></p><p style=3D"margin-bottom:0pt; text-indent:0pt;= text-align:justify; line-height:150%"><span> </span></p><p style=3D"m= argin-bottom:0pt; text-indent:0pt; text-align:justify; line-height:150%"><s= pan>El art=C3=ADculo que se publica es de exclusiva responsabilidad de los = autores y no necesariamente reflejan el pensamiento de la </span><span styl= e=3D"font-weight:bold">Revista Ciencia Digital.</span></p><p class=3D"Title= " style=3D"margin-top:0pt; margin-bottom:0pt; text-align:justify; line-heig= ht:150%; font-size:12pt"><span style=3D"font-weight:normal"> </span></= p><p class=3D"Header" style=3D"text-align:justify; line-height:150%"><img s= rc=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQ= EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2= wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQH/wAARCABVAKIDASIAAhEBAxEB/8QAHwAAAgICAgMBAAAAAAAAAAAAAAoICQY= HAgQBBQsD/8QAUhAAAAYBAwICBAcLCAQPAAAAAQIDBAUGBwAIEQkSEyEKFDFRFRYiQXF3thcZNz= g5QnKBobHBGCMoYXaRtfAmVnPRJTI1SFdYdHiGl6bV1tfx/8QAHQEAAQMFAQAAAAAAAAAAAAAAA= AIDBgEEBQcICf/EAD4RAAIBAgUBBAQLBgcAAAAAAAECAwQRAAUSITETBgdBUSJhcZEIFDI2N3aB= obG00RVSdbLE8BYjJkJTZvH/2gAMAwEAAhEDEQA/AH6WcpHSKBHMe9aPmypQOmuzcoOUVCD7DkV= RUOQxR+YxTCA/MOv2cmAWywlHgwJnEOBADAYCiIfPyAgPu8w182rG2c8zYbfklMV5RvVCdkOmc/= xas0rFtXAImE6ZXrBu4Bi9SKbkQRdtl0hAxgMTgxg0+lsKyfdczbOsKZMyHKhOXK001y6npf1Zs= zNIOmspKxxHSjdoki3IuqgzSFcUUUyKK96nhlE4hrc/ej3N5h3aUtDmUuc0ebZfX1hooilPLSVU= cwiecdSFnniKFI2syzEhgAUs1xqHu572aPvBqa3L1yipyytoqMVkmqojqaaSMyJCRHIEhkDhnBs= 0Nrf7r4Vbk+rJvdwZnHKENGZQLeKhA5OvTBlUshRDCwsU41pZpNs0YIypEmdjbINW6aSTVJKY8F= uRMhQSEhQKN9HTi6qcXvfs0riyxY2d0bJtfqa9udu4qQTlahLxbCQiop6dodz4ErFvAeTDMyLFZ= KQRMh45/hEpyFTUT13Bfh6zX9bGQvtXK6tu9H+D+mXeR92B7N+rm5UL9/8Au10R3n923Ylu7Ou7= SQ9n6KhzrLshoa2Cty6P4k0k7JSq/wAZig0QVAkEjajJEz39IMDe+hu7vt92uTvBosikzusq8qr= 86qKWajrn+NokLPNYQPLqmgKWBURyBABYqVAAciLzwHPl/n/P/wC66UpJsYaNfy8m6RZRsYzcyE= g9cqFSbtGTNE7h05XUMIFIiggmdVU5hACEKYwjwA674CA88fMPH69QW6mNyfUPYdufn41Q6T42L= ZyEbrJmEiiI2bwa6oqQwCAlOmjJqGKJRAQEPLXCKi5VeLkDy5NsdrDgX8sK074+tfuSzJkmzV3b= nd5jDmGYmUeQ9bc1QEmN1uLNo5FBCxSthMgaVihlOz1tlEwq0f6m2cJtnqz5yQyoRhjsx9XWXYt= pOJum/uTjXyJHLOQj1M6PGTtuqHek4aumyCjdwioUQMmqiodMxeBKIhrPOilhqsZj340FK3xrOZ= h8ewFiyOSLkESOWjqZgEmreCVXQVKdNUI+WkWsmmU5TFFdml3BwHAvvkIUgAUocAHAAAeQAABwA= AHzAHzBq6kdYiEVFNgLkgbk+dwSff8AoK4WO6buUd/MTtU353TKy24mfyvTqOzmsJtMywd+n5Ra= wMq1bHRW9Tgbg0VcTBlpJGMK8YRjZf1lUGqSyZjCkXUtekTua3z7gbBm9rvDrFprzCsw9JcUU9i= xK/xoR07knthTnCtV3sRFhLnSRaRoqpJisLQDkOIEBcBNYpvjs9hpGzzczcqjMP69aaxhXIM5X5= 2LXM2kYiXjq4+csZBkuX5SLpqumRVFQPMhygYPMOdUXdDLd5mbJSm7aybiMyXK+1rGdHpFmbrXG= ZVk0K+zTPdXc68aeMAAgKzOMRFcQHg4NkgH/ihps+mkj9NeVGoDcElVsAANiAL/AGnxwYZ65D3h= /frzpIrJ3U/6iG+fPrzHm0p9dKrCyMjIFouPMZoRbCfUgo05wJNWu0u+0yCh23Y6k3LiWjoJgdY= ES9pSlVVkxgTCnXcjc2YlkMpOs2jjVnkSoOr4WTzRi2SjzVNCcZKT5X0cxvrt69ajGlcAu1atXD= hdPuTSRUOYpRoYGA9J41Nr6Wax8Psv9vvwYbd5AfYIDoEQD2iAfTpInfvu83ux3UJzdhTC2dMsx= zdbKcbUKBRK1ZVGbQHktHQaEdDxTdQyTdEXci8AqYHUTTBVcRMcpREdayyrmrrNbTUq5fcyXfcP= Q4d3MEYxMncJGOn6w/lE0juSxT5IFJiJOq4bprKkZSJU1HKKK50CnBBUyahTkhbuilgCoNwTcA2= sbefhff7jD4XICHICAh7+fLRyHvD+/VI2OerM3+9iOd5t/gWDnJNfeOcaq1RioLKMtmV0l02MQZ= oIiZRpEyLVZGyy7dETqsI5tKosxWOih4i/9W3h9Xze7crJJYTteYp4Io/rL+FxCzaVuo1Vq8UVM= xYrPE02TJJQ6ZDkaJysq4knZEFTgdwKaqgIWFzqvZQraSWIte9tvV43wYeYtzp8xq1jfRRTnlWc= FLuoxNNIXCh37ePcLNCEblAxlzGXImBUQKYVBECAA93Gl/8Apgbu+oznDc5MUndTUbjB4ta49tU= uxfTuEpLHrE1jYTEA3iEST7uDjkVl1GTuRMmxBwYzkhDqlTEG4mLrzpyV/qq1jMmQpneAtnNvi9= rgTJJ4le/WOMk4VC9prV5eAWbt2co9WJKpM0Zg7RfwQImmVyBlC94AbQnRO3bbls3b0rHScuZty= DkKptcSXqXbwFmnV5KNRk2Nhqjdm+I3UAClcNkHblJJQB5KmsoUB4MOq6NKzfIeyghhe4+Tsp9d= 97ew+ODDcHID7B5145D3h7vaHt937B0pNn7CXXblM45dkcVus2Fxq+yPcnVBJGZpxdGx5agvPPl= a+DKPfX5o8ZNAizNgbtXbZu4QS7UlUUjlEgQtyTuV6xWw240+ZzzdsqV1ScOq7hIrIM5V8hUy1N= 4xZH4RjFXMNJWCL8VMqyQPWreSZTDZByi4IKJVUFhBCWtpeMki9g2/h4eq5v7PXgw9Zo1RPSeu3= tplKZUZO2RUxEWmRrEA/ssSyXbLs4uwPIpo4mY5osqUiqzZlIqOWyCqhSqKJJEOcpTCIAaR0pv+= J/u/X2/2djCcpg5KP0c/3een6el1+T+26+XH+g0iPH02Of0gub2D9A/u0/R0ufyfu3X+w0j9op/= XcXwqfmn2c+sJ/IVOOMfg3n/VGeDzyI/dW0+EdtwX4es1/WxkL7VyurcPR/Pxyb39Q9l+2dC1Uf= uC/D1mv62MhfauV1bh6P5+OTe/qHsv2zoWth95f0L559V6D+hxB+7/AOljJfrFP/PUYcgL+d+kP= 8NQ16huPH+U9k25WlRTdV3LSGKrK/imiBROs7kYBqM+zapFKAiZRwvGERTKAcmOcofPqZRfzv0h= /hrgsim4SURVIVRJUhk1CHKBiHIcBKchij8kxTFESmKYBAQEQEBAdea6HToYcjSR9ljj0Gx8+bp= L7kqltf3qY+uuQZJGDotjYTdAtM66N2tIFtZW6ZI+VfnDyRYM5prHDIOBDtaszLuT/IRNw+gwzX= h2TZt37DKmOnbN2kRds5b3SuKoLoqlA6aqShJIxDpnKICUxREBDSwm+voG5ElsmWbJWz17WX1Tt= 0k+nXmJ7JKErz+qSki4M6eNKrLOkxiH1dO4VWUYR8g5jnUOj2MUVH7chFEq+CdEDqQkKBS4nhil= D2AXJ1GAA/RAJ4OA/q4DV44imIfqBCRbSbDjzuRb28cWvgw3Pvvt1VtOxbd8NZssDYis8BZKK7N= By8fLFamVqkmZIrgWLlcERUKQ4pgp2icCmEvIAPCsfSgaSr7a71VmsKRZSTW20xpWxG/PjH4jMj= GWIkBflCczcFQAA8x59g6sg2KdOjdphTZ9v9xLkijMYy8Z1xyFexrHJXCuSqMvKfFa1xgoLvmUm= 4ZxZBeSjJMyr9dBPtUMoAiVM4l2Z0Yun1uG2pSO5JruSocTBQWUavSoKKboWOv2RGYRjl7WScaO= koZ+9FBL1SYbEN6yUpFyrHKTv7DgCFKJHIuoP6aEEbaxdDcffex91sGFltkdR3cXjK0pXdmM9LQ= mVHNUerPSwN+rWP5eRrDV8wO/aNZCyTUGlIkTdixdOI1k4Wcimh62ZuKDVVRO9za3ty63dc3E4b= nc3WTJ7nEcVfIJ7kFCUzxQp6OWq6LooyZHkMwujx7JICjz4jRs0cLKhyUiRxEAHTm4noT7q8WZh= kcgbL7OxmqmtMO5epIoXM1DyLRQeKqqjEjJPF2LSQbsk1haNJZjMEdOmwdrxi3OBjq5PgTZH1oK= 1m7ElhyNdcmusfwmRahK3Vq83FN5dmvV2M4xczaLqJC2uBkm6kem4KqxBBb1kgmR8I/f2C48iuu= pWi3U3Dj0r8WBPjfYfpgxD/cF59c90PHP9MDFgh83tk6YIce7n36vF9ITKX+Q7Xx4DkM107gePZ= /wHav2/wBft1DfLnTI3hWzqnr7nIPHkU5w8fcVQsglsB7lV27savBPa2tIvQhVpMkp4iSca6MVr= 6t6wp2ACaZhOUBtK6wW2DMm7Pa5DYzwhXWllt7TJtcsq8e9mYqCSLEx8VPNXa4PZd00aidNZ82K= CJVRVP3iJSiBTCDbMpemNx6KDVxZSNPPAHHmOPDBhYmbbSKvRRpy7UFBj2292XNJ9nd2FFagPU2= ZlgDy7fF7ykE3l3mDjz4Abx/R2pymr7Sr5ARzqOC5x2Xpp7Z2RFUQlPUn8LCEgnrlHnxxZqoN3D= ZquYoJCq2cJFMKiagBmGyfpp2g3TjyRs+3X10lUlrverHPsVoaWhp97XnB0IJxV7TGvI1w7Yi9j= JaNFczJRYnrTUi7F0BWz0/dTZN9EnqS4VuUqTCUtGT8WqZZqyulCycnQnUrFgoYzckpGysjCSLR= cyZUzrsvFftUF+SIPXZCFWOoujrJEXVW1lgx3BHo8WsLXB4N/YLYMOdZG4+59eOQAQ+J9lAPLn2= wr3SWHQcmWta3uZHsL8TeowO3zK0y77AExwaRk3U3q/aHHmbwkD9oefn9OrIem1sm6jeHs2Xuw7= mHVofUKZwTkSpRLaZy+0urI9zm3VcNBh8Ep2GTFBUWzOTIWRO3Im2IdRMyyfjgBsX6UHTI3Vbat= 0Vwvue8dxUJjyy4ivtIWdNLfW5xRy7skpXlEWR2UPIu3ZE3LBm+71jJFSTEgFMcDnIBkLpjSZTI= rXVbWsL3I1WBJOw5P4bnBiuf+Wv1POoBuQtFX25ZCvEY8XPPTNZxtRLZC0KDrtOiHZG6YryMo/h= Wjxdui4ZldvZGQVePHS4iQBKJCE0Vvvw/1Jsb1ejSG+SWucpV5CekGlI+NOT6rfkUZwjFNV+LVr= A2ObXYKGY+GB1l0kElCABCnMYoF1NrJXRS3+4SzbZLHtTlySdZXk5Ven3aq5Ha4+trCBlFzLEhp= lF5IwzxF43SMRq89QcO4554JXBFC+IZBLXmQulZ1gctNGEflFCyZDYRTlR3Fs7nnWv2NtHOlk/C= Vcs0Za1uk2y6iQAmoqiUhzkDtMIhp9WjBXS8SqANrWbgbX8PcOPPgxRto1bp9446jH/RDA/+ZFD= /APftGnerF++vvwYriN7B+gf3afo6XP5P3br/AGGkftFP6QXN7B+gf3afo6XP5P3br/YaR+0U/r= tH4VPzT7OfWE/kKnHGHwb/AJ055/Am/OU+EdtwX4es1/WxkL7VyurcPR/Pxyb39Q9l+2dC1UfuC= /D1mv62MhfauV1bh6P5+OTe/qHsv2zoWth95f0L559V6D+hxCO7/wCljJfrFP8Az1GHIC/nfpD/= AA1y1xL+d+kP8Ncteay8D2D8Meg2ITZ56iO0PbLe/ua5uy0zpVzGGYWAsMtX7TJqDESarpFi8Fz= EQr5mALqMnRQT8fxS+EJjkKUxBHSw9ZbpyceW4mN/XT75x9mdLdekDfj7p+z8CuPw8gAPIJK1+7= W5cNej7XfMOG8ZZaY7javDEyVj6qXtpCO6NKuTxhLVAspxCOcPUZohVzNAelbKuU25SqCmZQqRQ= EC6uVji0K7uw1AG3rNjtYHw232vzzgwzZgbfVtN3MSR4PC2b6ZcLCmmor8WQcuoWzLIop+Kuuzg= J9tGSj9ugT5bhwwauUUC+axychqRdwvdIx7FEnr7cKxSYNR2iwTmLbPRddizvnBFVUGRX8u6ZtT= O100F1Em4K+MoRFUxCCCZxD5zG4jb/nDp+7ikqXYpU0DkClOoe5Uq8VB48btpJl4wuIWyV96JGr= xEoOGyrddFUiard42dNFQOUgmOztumvGN9/XSiwHkXNGcK5t7aWW705/YrrPVuaskWtfqxGXWtz= EI3ia2RV83NLP0JWUaKm4Qbtm/hKCBlCANHhVTHpY6HsCRY6SPKw3vxb1HBi/Kn3qk5CijTtCt9= ZusIR0sxNMVOdjLFFletypmXaDIRLp20BygVVIyqHjeKmVVMTkADlEcq1VF0dcb4xxVtMfVnFGb= oHP8AVhypb5M18rldnaywTknUdXU3cGMbYE035nDBNugqo4AvgKFeEKmIiQ46kNlPqN7H8L2V5T= cjbkscwtpjVjNpSCYv3tnkYh0QeFGcuhVWM2MU9SEQ8VlIC2dp8h3ol5DlrSblV1NYkX0kHm24t= tvtgxNfWubnmHEuOHjSPyFk/H1Ffv0DumLK4XKvVp28bJqCkdw1bzMiyVcIEVAUzKokOmU4CQTA= by1CL77z05P+tDUefZx8X75z+2qBqsjrLYZ2257yRg645L3iUrb+CmLll6vGWOiXO0LWqAlJYZJ= vPNF4BuJGbcSrpperPCJuREe4SAA8BVUuwV9SA330k8W4Hu549l8GGFbflfH9HxlO5jnrPHJ40r= lWcXWUt0ec0zFFqrVkMirNs1Ygr00kyMx4dIKRxHIOURKZDxAMXnTG3Devtr3avLSxwDkdrfXFL= bxjqyJt4awRQxqEwd2lGnOabi44q/rKjB2UAbiqJPBHxAL3EE1a+6fcFtswL0u2m3eXzZAS1ovW= yhvXcQOUoayNQygxLQm0BCzkQgMWuWMbzixElm7aYdNVm3rBSOBL2mNqoHoVbtNvG1mybhnefcm= ROOG1xhcft62tKsJx6EqtEPbQrIkRCFipM5BaketTHFcqQCC5RIJuDcLEWqNnGq6kabD5QuPPc3= B8MGHUtGoj5D33bTMUULGuTshZlgqzRMwMF5TG9ieRdmXa2lg2bMna7lmgxhHb1uRNvIslRCQbN= DiC5QAomA5S6VL1d+nIYxShuip4CYwFATQN7KUBEeAExjVUClL7zGEAAPMRAAEdNBWPCsfDgnBi= x9Q4JpnOPsIUTD9AByP7NQfxF1HtnOdsmtMO4ry+ytORXxpYravJV21sFFBhEll5Ph3JwjNiX1Z= JBU497kvf2CCXeYQKMlcb5exfm2lJ3nEd8q+RKi/TdIt5+py7SXjwcoJ8uGThRqoc7J+2ExQdR7= wjd62MYCuG6YjxpJzo6AH30apf7fLf+FS/+4NOJHrEt7gxqWHrsdwdr3v4e/Bh7EPYH0aNGjTNv= b7z/fh+PmcGPmHG9g/QP7tP0dLn8n7t1/sNI/aKf0gub2D9A6fn6XQgHT9268/6jSIf+o58P2D5= D7tdzfCp+afZz6wn8hU44w+Df86c8/gR/OU+Ed9wX4es1/WxkL7VyurcPR/fxyb39Q9l+2dC1Uf= uC/D1mv8AryxkL9lrlQH9urbfR/jAG8m9c+z7hFm8/m8rlQ+Q+nyHy1sPvL27l888/wDC9Bt47f= EcQfu/IHevkp/7FN97z/8AuHIy/nfpD/DXLXEDlHnz9nv4/u/V8+uWvNcbADyx6DA8eFxe2EePS= Bvx9yfUtQP8Stem4tjwB/I02q+X/N6w/wDYGA0o76QN+PuT6lqB/iVr1PTAHX+294fwJh7FErhL= M0vOY1xdSKM/fx61JSipGSqtajoVy6ZqubER2Ri6csjqonXaFXKgconQBQBT1cFGeGLSpb0Re3h= 6Kj8b38rYrjTnpJDGJSzNtzfoJoFmXWObQ3fnIBAXUYNLEieOBYS/LFMizqR8Hv8AkgJle0Oe4d= RwtK71boKY/TdCoKDbeSogwA4iJStPgq6LGKmA+QE9bVcjwHl3Cb5+R1BvfZvHue/fcGfJj2tnr= 7IGEdTMe0Zk6UmXUVCoul1GjNV0m2bjIy8nIvl3TpRBoiU67hNsgmKSKZhum364Dl9tfRF244us= jUGdraZco1itbQUwTVZ2C2w+RrE/jnIAI9zmL+EU4xYwiPJ2YgA9oFAHT/lrArGzGRdvIbE7+rx= 8Lnk2wY1rts3CWnbh0Lcq2qjSjmDuNu3BWTG8BNM1VG76JVtcfViSb5iukdNZu+bwLOWFk6ROVV= o68F0iYqiRB1FrpfdKtTqARGQ8l3rI0vRKBUrGnVUHULHNJWxWe1rRzealP5+TVFu0aRTORi1nK= 6qDpZ8vJFIQUhQVUPurGWJrBlXoJ5JNWmDqTksc7mZbJSzFkkdZyrEQTCtx86uVJMBMZOPh5l5J= uB/MbslT8cFHXe6M/VAwhs5ouSML7gFJ+ArFiuf3QqrcYSAe2VBvJvYWLgpuEmY6IKvLolVSgop= 1FOmce9R8Qz9N6ZoX1Y6tAzBJDHcPquSPlWGnYbDz999htgxA7qf7J6jsRztW8TUu5WK6xU7jaJ= uy8nZm0c0fIvJCesUQoySTjEkm5myaUKisUxiiqJ1lAMIlAgBNTrrgATOybgOP6Llc/ez1HbrIb= rsJ7v8AcnUMj4Isb+zVOHxLCVN++ka7OVpZKbZWa1SThsVjPMWDtVMrSVZqA5TSMgYyhkynE6Zw= LInrsf8ALWyb/uuVz97PSlLE0976rPe/N/Rvfje1/swYnnuk2JY4z50yMGbmLLZ7bE27b7sLq0j= WIaGUiyQUutF4/YWBEk0V0wcPTEO6IVJT1Ry3EUBECiU/ytVOdJXp4Yt39TeaI3JdtutVRxtG01= 7EqVBSITUeKWJzYEHRXvwrHvymIiWJbi38AEhAVFfE7/kdrJtjZun/AEP1mrJA7lwfp8MFCIplE= yhit8NtXKvYUAEREqKSh+AARECjpfvojb3Nvmz29ZyT3AWt7SYnIdbqBYCwJ12fscd6/WX84d3H= PUKzHS8o2XcoTKazNYY8zMwNnKa7lBUUCLoRpOlJpuSHstuRcjgePjt58DwwYvQ3ubD9mQ7ZNvV= A3I7gJvEGMNtca7qtOtT6ZrcbJ2VWSjItn6m6QexTxSZlxaQBXKMfX48zsxQdrA1MiQfDo1yDtV= 6MKNLs6+Pd/t1Vu7aFknFXbzdNtDmHeTbdqqrHMn5EMYsVBavXREmx1U3iPhFV8YDiBRAcl6+eY= Esw5b20WanWB9O4Ws2A2l5x87FtKR8XJuLJap5KVl28ZKtmLlu/XjY2BSckeNUHqaCTRNZNMOAH= EavhnoeucTRMnYd0ua2+T1aQk8k4ZWu25u3SuhogVlowSMsSvY0jUkwPqpTIS7pv4HaYJBUOVxr= GpCKxeUFiTaMXAOoXvcbX8duTxgxnfo9OT7VAbpMj4mZyzhakXjF87PycT4igsDz9SfRpImaQQO= YCouvUJKRaLKkIU7huukC3d6ukBNK9HTy6o9T/AO0Zb/wqX1k/QIKiXfjKFbGMduGHMjAgcwCBj= og6hQSMIGABARIBRHkAHnnyL7Axfo5/lRql/t8tf4VL6UdjUeuFQdgLkjk2Gx24wYex0aNGrHBj= 5hhx8vp/b/nyH/PGnb+mPug26xezDA2PpfN+MIa6Q1Vex0vWZe5wMZNRrtafmFyoOo989brkUMg= 4SWAhg5FM5TB5DqYqWwDZKimCZNqWAuAAAAT4wqShvL2dxjxRjmH5+RNz5j566T7p47HpAhk19q= mC0wMAgJmePK9Hq+fuWYMWyoD5jwIHAwfMPmOule8vvk7Kd5WV0OVVeUdocqSgrzXw1FNJltUXf= oSQaJIZZIRpIl1ArKpBXk74537v+6ftX2AzKqzKkzLs/mTVlH8TlgqP2jTqqGWOYuksUTsGBjCi= 6EWLbC+KLsldC9zle43e/wCMd3mNp1a42ixWpCIc1U3qzU0/LO5QrI8vA3GfOsm39a8EXZYooqg= QFAbp8imEfIvpJdTba1akclYHsFSlbNFlVRRk8V5B+DZRzHmUTWVZvI65xlWQkmLk7dAXMUoL9B= wciZToq+GBgYk+9hbIUVwdReEWVcclMJyOKpcsh1VVI/PICiav2yO8HtH2An2lD5i+Y6y2P2T1G= sKEVx3mbczjoyJBIg3h85221xCQcBxzXMpGyBXVezgPDBeLV7A5KTtKYwDYU3fnn8FIMvbPxm+X= dFaV8v7S9kctNLLTBFToTyZVmRllQqoUlo2J5Oo3GLubuZyiWpFcMjbK6/rGpFbkHauv+MRzs5k= MsK5ll6pE2tmZRHKgUGwIxWJhLqr7gMKO2FD6i+3e94/Ap0WKWbK9TpRKFU7RRQ9btUKgm4jVSc= +M4dzVRkFETAYhG9ZKUDKDeNjXKuPsv1aOuuM7jAXarSiRVmczXpFtItDd5QOKKwoHMo1dJ9wFc= NHJEXLc4CmskmcBKGlVMRZ6jWS0WnnCuZWhVSim7ic54krso6etjFEpmoTeM3mN45qKhOSqOXtP= nAEBERbnHyHT8Bs4j69Z396xVDIbWMmqqFdPZPDk+Wfw/eBSIUCsrzi2Xiq3FSZHInUUdqx8HBz= yIGOpH3JB2JVR1vntV2RzsvV0lDT9m8wYkuuUz1VVkU8htxl+YRQ5jloPnRvXwLYKlKgBbE+yOn= 7V5MEpqqqqe0FCoCr+1IqenzmFRYEiuopJ6HMCABYVgo5XIJaqJIU4Pu26S+2jehlcMx5ancpR9= qCtRNVKhTrLBxUQMZDLP12igtZGry7j1ox5FfxlAdgmcoJAVMolMY8Yx9Hh2Of61Z+H/wAbVX/4= Hq5KlWS4mTJCZGgWUVZUQ8MZauquX1QsAJ9oeuxKrwicjEqr8gqpBTBTuGRzKNmknOINhk1doB7= A492oMTLCxj6lwttJRleNhsQUYCxU8jg2NioOJ3FIsqBwGW/KupV12BsyncEXsRxtsSMVfbaOkJ= sp2wWxjfapRJa53iJcldwlmyZN/GlzAuiB/NOoiMTaRsA0fIn/AJxvIhEGkG6nB27lIwFEJK7wd= oGMd62K2WIMsPrXHVZjbYm5Ir02TYRMsMrDMZZg0TO6kYqYQMzMjMOhWSBoVQ6hUjFXIBTFPKzR= pssxIYkkjgk8cceXGHMQs2+bZMF7A9u9vocBK2FfEkO4tuRLXIX50zsDtuzcxLUbEdyEVCME3MY= jGxAH9TJGrrGDxigK/iFTLQblfF3o+eUbW/tjXOUvjJzKOFnT+Kxs6t8ZAKul1DHVVbQ85Q7C1j= CGOYRBrEgxZJ+xNsTz00Xk2gxWVMeXfGs66fsoS+1SfqEs7ilG6Mo1jrDGOYt44j1XbV61TeJIO= TnbHcs3KBVikFVBUnJBozD0cjZn8+V9y30BacZ//VIfu05GwBJZ5FJtutiSPG5P2YMLFbxaFtXi= c7RFD2OWu7ZRoL2Er0eM1Z/EcyEtfpaSeJOI2ED4u1xw4YpNloZsn3RYGPImeESXXTAgg5juH6V= uBt4cXhiQzbNZHYT+LMXQNBYlo89DQzJdBmzamdKO0ZKuzaii4u0zgQ5F0iFS4KKYiAnHFdsfRV= 2a7YMhRmUoZDIGTbnX3Sb+rvcqT0JLx1akUgEEZSNhq5WKvHLySAj4jV3LIyZ2K5SOmINnSSSxL= cwDtKAeXkAfR5aVLNq0BC3oAgsdi17He23gMGNW0DE1Qx7h2pYOZILTNGp9BiMbNWliFCRcSlXi= IJGvJt5sybZs1eqvYxEU5AStEEHBlFeG6aZgTCoyz+j/AGw+xT0nMsVsw1FtIvFnZICt3eN+BY3= xzioZtHJzdXmpBJqmJuEEVpFwKafaQD9oAGpOdSLcHdsT41qdHw9OyrLLOTbvARJ2tJhlLVkuHx= e2cLOsi3On1huyk13D2FiW4IJvlGKqbRR54rcSPSt1EvVttzcthJFlEDH2i+1i1Ud7lGhNsh2Ob= ir9T8W4+qDJxka1Zel7vFDMxjhxZFGsdXIp8WUkJCYmCtlHkXHFEsbnqbszm0+W0eZU+gjMJatK= WnLMk0sdF0etKTIFjVW6kjREvZ0palrjphXjNR2qyylzKsy6YyL8QjpXqqgAPFG9Z1OlEFTVI7q= UQS2T0GqKcWbqErmmUOmntYzHt/xht4yFXpqcreGoJrX8d20swVhkCvNGrVFmoqjYGLJBsuZ+i2= R+EWjmMWinayCCx4/xUETEhKHo8uxkef8ASvPnv8rtVh8ufm5of6vnH+vUbEc+ZssMNlFmtnXI+= OrFmC5xRzwDNKnuatSY++x8hkHIrhaYsEJK2qKNg/BUbBml0KzI1VCPs87FlFY0i7ci6sDZ7zbD= QcSsr5ANbTf42tuquFhgcnqR7W9zNLtFWKGOlq6vT6vB1+ItVxsEzUjepTLayKuWko8QO9Tfxz8= kbl8x7C5xQGBYquCskqKgQLFEJY1DyR07oTLUJHCVmmlenjZXdGliY6lB2xWX9vssrhM8kFRSwQ= QmZpZDHISFklVwIoneYNFFGs8qNGrqkigBipOMs2mdJbbRszyorl7E85lOQs6tZlqodC42SDlIk= I2aO1O7OVtH1eIXB2UWiQIqC6EhAFTuSOIlEvQ259IjbDtgznHbgseT+Vnl5jTWAyDSzWaCkIEx= rIg5bPxUZMqpGuTgVNyoLYCvieGcCifxClEB9FBdQ2OLZso2Bmzs9siDO7TKwlZlJGqwdWpuMcK= wUdF5ByLH2JtEqSkmxs2QHkjV4NnIKSQzNihnLeKcsGCS5086wBmOe3R7lGGQvAnaLScXYdjYQa= G6kzLC+yxkZhXLhc2MsDQEG75TG9edVSEcC7bpmZzkzINyJNnSbpEmKn7K51Sw1dVXRimpqal68= kzspJk0osVL0Q4l6jVDinZivTRg76jGupsnB2uymsmpaaikNVVVVSII4UDACIMxkqjKU6XSSBTN= pDdRto9IfUFs5DzAPoDRoDyAPn8g89GoxiTXP7p94/X2/wBnbzo0aNGFYNGjRowYBDnyHXHsD3e= X6/38/wANGjRbBjiKRRAOfPjzAR55AeeeQ8w41+geQAHu0aNAFuMGDRo0aMGDRo0aMGDQIcgIe8= ONGjRgxSluWhYKB6iNXd2trJ3GEzLgYlVXhUJ6Tqi9bQoVwQtaiLOYiFFHD6AtaqBI+01pZu3Zz= DEy7WQcO2LlwxUmXB7YsKZrpEBYr1TgcjMU6z1dvHRM7ZoBgwx9c5pCxjRVEISaYISEPDPmEW5i= gcIlSj5Fgk/iWsUHY1SNGp/n9ZV0uS9lKumqZ6eoOUQx9SCWSIqsM1VTx6FRlVCIYYkZkVWk0Bp= GZ/Sxr7JKOkqc57T01RTQTwDNZZenNDHKC8sdBO5YurM46s8rqrlkj1lY1VbKPem2J7XzOju1sa= ouVV/jeV2V3YbU8SfEvrRiytSb9JzOKleJygR7V2Yq/ieBJEUkmwpPVlVj7AU2z4eVx1D4tc1x0= 9p8FMQNgZNntgsTqUVl6wq1VhHkhYF5U87JHYkZNGiRH0gukDBugw8P1NFNEpo1EJM5zaZozLmd= fIYWDxdSrnfpum6NHqc6GUyOQVsQWJviXx5NlMQcR5bRRiRWSQJTRKHRtIZXso1KQigg3FlA4GN= br7Cdra8c1ivucGbsW1dkakZFlabixF7XJKbb2MYiUUaWBE8qyj5xqhJQyUiZyWHckE8aDYTn7t= 24rwbjLDKU+jjquFgi2ecf2GZMeRlpVZxKSjlZ8/UTXmH8gs1QcPl3L4zNsok0B47cuQRBZdU5z= RqlRmuZ1cbQ1WY1tRC79RopqqeWNnLBixR3KliQDe19h5CyoMpyullWamy6igmQaUlipoY5FXTp= 0q6oGAC7AA2AJtycbg0aNGrDGQx//9k=3D" width=3D"162" height=3D"85" alt=3D"edit= orial1.png" style=3D"margin-right:9pt; margin-left:9pt; float:left; positio= n:relative" /><br /><span> </span></p><p class=3D"Header" style=3D"tex= t-align:justify; line-height:150%"><span> </span></p><p class=3D"Heade= r" style=3D"text-align:justify; line-height:150%"><span> </span></p><p= class=3D"Title" style=3D"margin-top:0pt; margin-bottom:0pt; text-align:jus= tify; line-height:150%; font-size:12pt"><span> </span></p><p class=3D"= Title" style=3D"margin-top:0pt; margin-bottom:0pt; text-indent:0pt; text-al= ign:justify; line-height:150%; font-size:12pt"><span style=3D"font-weight:n= ormal">El art=C3=ADculo queda en propiedad de la revista y, por tanto, su p= ublicaci=C3=B3n parcial y/o total en otro medio tiene que ser autorizado po= r el director de la Revista Ciencia Digital.</span></p><p class=3D"Title" s= tyle=3D"margin-top:0pt; margin-bottom:0pt; text-align:justify; line-height:= 150%; font-size:12pt"><span> </span></p><p class=3D"Title" style=3D"ma= rgin-top:0pt; margin-bottom:0pt; text-align:justify; line-height:150%; font= -size:12pt"><span style=3D"height:0pt; text-align:left; display:block; posi= tion:absolute; z-index:4"><img src=3D"data:image/jpeg;base64,/9j/4AAQSkZJRg= ABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/wAARCAB0AOwDASIAAhEBAxEB/8Q= AHwABAAIBBQEBAQAAAAAAAAAAAAkKCAEFBgcLAwIE/8QARBAAAAYCAQIEBAMEBgYLAAAAAQIDBA= UGAAcICRESExQhChUxQRZRYRciMnEjOpGhsfAYGSQ5d7Y0cnN4gYOHkrjB4f/EAB0BAQACAgMBA= QAAAAAAAAAAAAAGBwQFAgMICQH/xAArEQACAgICAgIBBAMAAwEAAAABAgMEAAUGEQcSEyExCCJB= URQVMjNSYXH/2gAMAwEAAhEDEQA/AL/GMYxjGMYxjGMZ8HDlu0SFZysi3SAQAVV1SIpgI/QBOoY= pQEfoACPuPsGMZ98ZthJqIVORNKUjlVVDAUiab5qdQ5h+hSkKqJjGH7AUBEc3PGMYxjGMYxmgj2= DvjGa4z8AoUwiBTFHt9ewgPuA9u388/eAQfwe//wAxjGMYxjGM2sZyHKJynlY0hiCIGKZ81AxRK= IgICUVQEDAICAlEO4CHb64xm6Yz4oOEXSRVm6qayRw7kUSUIqmbsIgIlOmYxTAAgICICPuAh9Qz= 7YxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjOpd36K1RyP1zMal3ZTI2/67n141zM1aXUepM= H60O/Qk406x490zdALR+2buk/LcEAVEi+MDF7lHtrGMZ5tHMLS2tuLHxUXBvS3H+vG1jq0NrcRZ= n8EQExOGghkpyzK/NnJmr+TeeIXwt0hXTMcUjeAOxA7j39JcA7AAfkHbPO76oX9by4Of8AELhh/= wAzO89EE6hEwExzFIUoCYxjCAAUoe4mMI+wAAe4iPYAxjP3jOn3PITRDKcGsu9zaubWIqwNjQa9= 8q6MqVyYfCDczBSUK5KsJv3QSFMD+L28Pf2zkt52dr3WlLl9jX+61em0OAjXExNW+yTUfE16NjG= qRl13rqWeOEWSaBEimOJxW7CAfu9x9sYze3drrTGxxFPeT8M2tc/HS8xCVtxJNEZyXiYBWNQnJO= Nijqg9esIdaYiUpN23RUQYqybBNydIztuCnTPKqzXum8f9q2bWjVd3dYipv3cKm1TBVykoUClcv= G6QkOB12LMV3iJRIfudEBEhgASjVd4AdVmvdTH4ifZE3riaOPGjQPDrZ2r9KOX6hmCNpVPsPXr+= 7bJBm78ozQbpLotWsWkoBXJ6vXK8s5RbPVnbdO4YrNwKwCmaWiVCnASiQX7MwHAfqUSeaPcB+gg= ICA/T7++v21OXY6vY6+G3LQmvUbVSK9B/56cliB4UsxdFT8kDOJEIZSGUH2H5Gfqrkeu2muvy04= dhFRv1LclCwO4LsdexHM9WYdN3FYVDFJ+1v2sf2t/yaY0V1MN8cS38JsNa82bZq9i2drSoTes7S= 6kZd3cDXG9QkHO1upsnLj1CVpJCvZJzBuWP7qEi1QM9QdMActVbqSZvEmQ3YQ8RCm7CHYQ7lAew= h3HsId+wh3H3++YBOOnbwOkOQcPyjfaapUnuevSxLDXrDITUvIRFesZPAKdjg6W6mlqZETySqZH= SEuxgW71B8BZBFZN6AOMz1QfsXPiBs8auPLABU8hwkt5YD9BU8sxvAA9h9zdg9h/IciHjXh9rg3= Fq2hu7qff2Y7NuzLsJjJ0TZl9xFEsssrrEgA6DOT7mRj/12Zl5N5lT53yuxv6Gjg49VkqU6sWvg= EXarWhCGWVoYoEaSQ99sIwPRUH111n9eM4QGzNcjNlrQXynGsJjeAsGFmhhlhP27+AI4HvqxP29= /ACPi/TObeIvbxdw7D79/tk/yvs1yjL8XXwU4/ai4pa95d6Vo7PU+2l99x9PvErQXLutMbtE3mD= tUy9e2GIjnKMe8m0Z2HbvE5dNsk+WF6/9aq68whkbnl65A6L1e/bxeyNw6yocm7MQrWPt95rVde= uDKG8BARay0m0XUE5v3SgVMRMPsHvlX/4wuaiLD0mKRMQMnHzMU+5PaycMpKLeN37B2ger30SLN= nbVRVuukYBASnTUMUe4e/uGMZJN8OQ8eSHRb4LPX7ty+eOKFdTLu3jhV05WMXb2w0ymVXXOdVQS= kIUgCYw9ilAA9gDJuMg5+G4XTW6KPBUxBHsnRr2gbuAh/SJbi2IU/b29wA3cAH79u/098mTm9jU= CtOkWNju1TgXrg5U0GczYoiMdLKGEClIm3ePEVTmMJgApSkETCIdu/cMYzmQ/Qe35DkeF66nXFD= VfKGY4obUu59d3qNi67INbJZkk2tBkXNjYhIN4U9lTXVRhZVBoo2VOE+jGR7gHSCTSQXcmFuWQL= 5ixOyB+m8anZnTBQjsq6RmpyG7AU5VwP5RimEQApgP4TCIAAiI5VX2r0bNvc5OXG+eQW6dq1vSu= u7TsCQRpkU1I1uF/m6nAlRgoCRWj/mcfC1xm9io1qu0K8knskUhxBzEN+xPHptzZ2deOt/qqq2r= EllVkR/qIQKjtIXkLIIySFVWLfk/Qbr1Nt+I+PeNd9sORHyjyabi+hocflloXaXtNsZN7NcqR0Y= 6lCOval2CpCLctiusJX41BaWAlZVspbL35pzT9BdbQ2TsipVGhtWoPPxLKzLROPdImTFRIkYKSi= qkq6dFAAZso1N06eKGIi1RUUOQg9M8NOcWlecdZ2BbtKrzikJQL26o7s9iYJxL+TFGNYSTKws43= 1CzpvCTCLxQIw0gRpIH9E5K7ZNVkzIkiFunw9Gr7HQ4CuDzC3qqxrLddOsJWw8BZKbDKPDeYuMT= XjLxiEcg5WADqosJFLzO38ffMP9YUrlP0Gbdsa+PaVB8peOGyGMPHy9iodmXrq9fk4Z85GGlbFF= OYyfc156LV+9aKgKMhCOzPGqJLB6hEG5tdLtdxVtV5b2sSrqgjC1NDIbssblABI4i/ekKuOiRCT= 0Qzso/blhanxX4i5Nxfd6zhHkWzybypJbrHi2l2muPD9fsaiXI0npVX20hq2dpYpM8kccm0iPzR= iGvWl9vma4J3AfoOMg34n9dfjtym2lQ9Jx2p9yVDYuwZL5REIrsqtYKwk8SZOZByq6mmFiaySLF= q0ZuV1nZ68USJJiYyJffJxSe5e/6/T6dv0/z+eb6lfp7GIz050niDepZPbpW9Vb1IZVIPqwPRH4= IP85R3MeC8u4Bs49PzHRXdBsZq4tw1rojJnqtI8S2IZIZJYZoWkjkQSRyMpZGAJIPX7xjGZmRPG= MYxjGMYxjGMYxjGMYxjPO76oX9by4Of8QuGH/MzvJcPi0effIzh/wAYNFau0G4tlOZ8k7tZ4PZe= 0Ki4dRkzG0+oMYd0vr6GsTMhnNclr6ebMYZRodOQ+UwMo0Zj2cuDEia6mqBHPxfPBxFQTAUb5w6= P3KIAIGRnJFYn1AfbxkL4g7e4dwDt375Y965nVl469Pyg0LWFm0tVuVPJrcT5sto3QFmi4yXgU5= RGTQioy9XM71hKLRUQzmXCbaFQjWnzyySySsbErsU0JKXimM7o4fcFOn9vXp8aWMlwn1xSqdurR= VSscpWrnUYeX2VHr2urNXK7ye2E6Yp2yUtqSzkXqNvO+azKq/p5JEzFby00KqXQbUr/AC35ccxu= j7zUj33Kfi9x7kNo7M0PB7SstnkVtey+sdpxWrH0bHLtZho4d1+fgbSzefJpFd1HQkpDmdwrVmv= MSyjiwRrfit1/t0VGM2Fu7qZ6c4eSE3Goy3+j7oLiHr3ZMRQ2KzMqqFac3K/Tvr3MiwTEGz0qT2= dZIuEzlbSj5ECHCsj8KUnOpdcjmYlaZ9S12VHRnItGwWddi3jVrFNJchdUJyc4rHNBFowUlXhV3= x2TYRbtRXFBEfLTL3YzgPRB4X8Z9xdejnfx12Hq2LnNM65Dk+2pNGSlLBER9fb0/dkPXq23ZuoW= Wj5IUYqGVOwQSXerEOkIGWKoqUpy2u+ffTV6a3EzirsndFb0cemXSuLVlnr6xRWx9pDJsNhWazR= NbqCiAO7q6buUCTEo2UdsHLddk4aJrkcNzpiIhXn+H0/rKnUl/wC25jf/ACGg8lz+Kb5MDSK1wI= 4vxT9RCV3hydh71YGyDgC+oqGq0kCJtniAdzGbuLRaYV0gY4FIZeKN2ETJj4dPyEkaDdkEqRqNk= Qy/kdU5vsf/AH+v6P32OuxuuNAHkWgBAYHdaoFSAQR/n1/r7BH3+PxnD+mpxd1XylpO+zb6h5u6= N4GnvZGomNcrlBrQ0i3YP0jybJzXp6JXOqCihQJ6g66RFEQMVPuBvFWg+Hpp/UP5v7m5B8YtN8o= r9pjS9zhqhM8p94Iz8tPbTrmt6/MT6UdR9TP5aUVGBtOypOTWjXc21IivGx0YvJLOl2zNaEmrjX= SbiU6vUNsMnRgbGDSDx09FwYiIEdyXqnapFRMJSgYizr05fF+9+6UofXK/vwSIB+3zn6Ah9Neao= /t/F1xDKn/TxffZeM6Fp5Gk9tvyBEd2ZyYotvaij6LEnr40T6B6HX995bP6jKSa/wAp7WqiLGE1= fHnZVUKBJLpacsn0Px3I7E/jsns/f3khPVH+Gm4Z6e4Q7n5G8WbTvbWPJHjjrmw7kjdiy237Vb3= ew3NBj1rLONrgnLORFnLS7Bg9Vj5uqHrx42aFq6M1csSrMFMO+O3xE+/9Y/D02zc1ynFLxy4pm/= j8LtXbAsYFlH0ivMUNpsCA2Va/UAb5zNU2lmnWgrvSuvnk5CQbmbF2pJyKqlwvqm/7tnnj/wB0f= kB/b+zKx9v7/pnklOpHyuilCRQJKG9d1PbI/FYPF5SfyzizWEPKP2/d8xX5p40+/wC94UlPD3AD= drwyjMu4fD59JzinzD4SQ/P3nRUCcxOQ3Ke17ImZWx7skZS4NajX67c52jNYiHYP5FVr81fOq+9= nH84ql69AZBpGRvoWsYUXET3xOnC209NzUVE1NxztdkL0/OR+xm9wR0XbJ2at7LRG+tex8kc59Z= TU68dSULTL7XLG6dL1xw7kCIS8K/WIqk3MxQQtNfC8/wC5H4eewfx7s9//AF52V3D+3+/IqPjZn= IE4acSmgrCUXHImZWBDubwqg219MFFQQ/hEUhcAUBEe4AqPb2EcYzFdh1bLV0wfhluAEXpJ80Y8= l+RULtun6zmXTZB8FCr8Rty/rXPYiDB0kszey0QlIRkZXm74ijNOYlkJJw3eIRizNxOv0vukVxD= U4gai3Dyxo0Lyu5N8i9WU/am59sciH6uz7KrYNiV5nZloOAPa3cgnWo+vITBIlstDos5F0ZmD54= 7UXMkVDzx+ootZh4FdF5ByZ4NRJxT3UrDkN5osQnT8pNpFnTI9+yIuhZpwfngTuqCQN/MECCn39= HTUXQC6aT3WOu5NxQ92OlZOh1B8oJOWPJps1BV1X49woZo1jtqs2bZAxlBFJBqim2RT8KbdJNIp= SFYyGnkzuSp9IHqTa+6fm2ZGc3B0l+eMHUpdjrHYV1sE654y2x1djwaS9Bt7iXLYW2vIO3w8LJS= lWdywtmVfkju2KpX8WsExGn1y+H8/0lOoToTlnSYO5bD6ee2LVASMlqJ/eb0/pkPMxaaCOwtUOn= B7As5ZEsldFe3UF+5dlH1Kj9u0TckrDkFLbdo+HU6QUutH2K+cfbDY16wX1MfN3jkXyCnDw6Tdc= HpjFfT20nINWxFiFXUL5hEREomUAfrncHWo1zxRvvTG5B07lK8LFawTpLUKNLR7Mk3a4/abUhG2= pDa+jzrpOZq5PLMpHRkXGNnaCky1fPo927RjXj5YrGYo81uQ/GG68AuLGguJWt6vve58zYqtxPB= nUK8xOGgoIpYUzl7t28OWUmawMKLpOGknstajvFl1lpVuhALkKuuuuzy34S9HzitxG1LRa5LVpx= uHbkfRJOsbI23sGasc8+v8lbmqxbuZeAlZl9Ax9efHeuo+EgiMlyw8AkyYeqduUV3zmkL8PByZc= 9MzqbuOJ3UG19OUa4XzX8BpfT1p2kq+Sl9BK2ydcbGgqnCs371eLrlH3HIWgr2WcRSZe9mPCrLL= g0cyyqfpwAoVQhFEzAYhy9ymKICUxTAAlEBDuAgIdhAQ9hDsIZ+MAylSAQQQQw7BB/II/o5zjkk= hkSWJ3jljdZI5EYo8bowZXR1IZXVgGVgQQQCCD95Ue4ucVdR8FetdJ0W52VjXaY+p8/a+NhrCsZ= Isq7voFjo2spSTj+gGSgUD2ivNVHaya8qdk3FLxunRUTW4iKFEoCHuH5l7dvt7/X79w9/vlOX4k= BIjrkzxqaVhB4veVtaPUkkYYjhSYWMrcnBK8izI08Tk7w0iD4GRG4GXFYQ8sBMJAGwh0ymHLiO4= q0dnzEcM1tiJIlCCBYVz3NCm+mQ+SobEcHMdu4tqRfMBwoh/tAM/SElTqyxXqhohoZkqbPb6SCo= 6wwWpLaWUBMSidYm+CY/hXXspEQT7JH0V/b2fV3nPUbDlfjjxT5o3XJ69jdbzjdPjN3Q35lXZWT= o57tUbvWIB72K9p42sbT5AoitWo5I5HWcRRyHh7gA/njNC/QP5ZrkwzydjGMYxjGMYxjGMYxjOv= dqbNrOnaJO7FuJLCpXK4k2WkiVWp2a8z5iOnaDFII+rU+LmrHKqee5SFRONjHSiKPmOVSkboqqE= 7Cz8mKBg7D7h+Xt/998YzzvOdbm27a+JC4jc59daJ5QT/GPXdk43SV62WXjFvlo2hk6LMyqtnUG= Ef6+a2FwWMZKtFDFZxbgy/jEGwLHAxA63+I0qe5dpc2tDdUzjPrfcmz9K6hZawr1g/EOkts1BfX= 171XcXl5Yt52t3WnQEp+DbM3ftlEbE0auYcsklJx0g8ZOjMk3fpFAmQA7eAv8A7Q9/5+2fNVsgs= mZJVJNRI4CU6R0yHTOA+wgchiiUwCHsICAh+mMZV31t8RrWudNIZaf4H8UOR915dbBiUq63hLjR= hhdQacmZhuRjJXnZ2y2790wQpNQXcLSIembElZ0rRvHotGLp6BkK/vR5o7noy9dXk5Uebsta63X= 5rTm0aNTNxv8AX9wXre1Jq037W15g5uFNCRcwCydoj4GXMiRqq9K3mS/I1lxkBBM3o+MIOGivN+= VxUdGecbxrfL2LVn5px+plPTpJ+Mw/cx/EP65/QtHMXKhFXDRsuqmPdNVZBFRRMQ+gpnOQTEEPt= 4RDt9sYzzb+AG0v9Wd8QvyB3Vyvouz9P6L5WO97yeu9jXTXFuj2C9P3Ldkdja6sz1snEuH7FpIE= ZsYuYaqtSSdakXZ2dkYxLhnIItP6PiAtxTnKvqx8E9t0Kh7jkuM0DW6XT6Le5zWN2qVVvNiZ7Hn= Ju/ydIPZIaOdSkcLKSrEeWXO1bNZIzAFo71TEiTxx6QrqJjHpkjvGDN2dAe6J3LVuuZEfzSMqmc= Ux/wCqIYcRca5KkDpi0cEbm8aAOGyCxUDB7AZIFEzAmYO/8RAKP65g7OkNjrdhrzIYhfo26ZlUe= xjFqCSD3C9r2U9/brsd9fkfnM/V3TrdnrtiIxMaF6pd+It6iX/FsRz/AB+3q3r7+nr7erdd99Hr= rKZVVcUixSsG63vva58Y9CQUrEXuVgWrKVhZbkJaqE8StGv9bTEiwjn8nC0Vva2EfZLKxIDda0t= ItKGUM3ZLquQic+Ex31rThjvTmE95QSk1phjs2na5iKO/uFKuzVhPSUVabK5ftWzpvX3KKJm6Eg= 0VMZ0dAgkWASmN4T+H0lvlsUI/9CZd/f6tkO/5CHun/aGa/L4z7M2YCH39Mh7CH/lh9PbIb4x4K= njjiFHicd8bKOjYvTJb/wAZqpcXLUln1aFrFohkMnqXMxDkEhEXpRMvKHPH8k8xv8tk1/8Aq3vV= 6EDU/wDJW2ENKpFV9xMtWoCJBGGCGHtAQpd+vYw/dXjmHx5pfDrl7oCwX06O4dicUNqNKTRY+rX= GalrC6u1Bn42rtmKkPAP2Iry75Qjduis7SUKcf6YqYe+UXOnJxL1Nyh6NnKjhruyzK6M5TSnLyv= bi4pxmxqrcIFWw3hjq+AqMfEeoWgfIJC3dN5OU1w5VXKkwkHDOVWTVLGJkP6cEDszX1u2LsLWEN= IMZS5atj6a+u7FJNBcIQl5ayz2uM3KwCfy3rhhDOHx2ZykURZuGS5g8DtIR6ujF+QVi5IzRSRVC= qHF+mVdtFpBK19zIbP2lst8J3b2Wgn6Ms2i6lruqMVGcamd9ESM5abAEqZAkXDMGL6YsDK+yof0= IurTqDpe8bJXpudUCPvXEfa2hL5fJGkS+xKRaj1m4U66WBzaVGMbIQ8VJieQjbHJTqjV2kkeDmo= Z7FuoqSdrA8IlgZ8Rtym291bNQ0PbHE7SG0pHgpxt2CtXGG3ZymWGJkd87evzRVn67XFOWjjz76= kUyBgHSS9gcM2ZBfTTlB4kgqVqke5RHbbuFx6pd/wCGO169qHZGrYDh9WOTNQk5PWDQtvgrBY9z= WbXxa+4k5SZn2EhGMIeCRXK8Ri4t64frnVN5aJCI5Kc2jIli0Rj2jFk0YNyFI3Yt2qCDRBMgdiE= RbJJkRSIQA7FKmQpSgHYAAAxjPN+d8LKL1I+hrwN40aksHpepDxPr25bZXdEWGu2etWO31Ka2Bc= bFcaP6+chY+FazTuFQgbNXBdyRUHLhqaNE6Skn5qNlXpgdcDiq+4ras1DzY2ZFcQeV2iqPWdWbe= 1xyLI91bJSE5R4hvXC2mAcWttGtJVlYm8WnJrNWy53sa9XXZuETE9K5dWMiNGCagKJt26agB2A6= aKZDgA+wgBgIBgAfuHf3zidj1zri4qJLW2j020rICAoK2KsQc4qkIe4CkpJsHRyD39w8Ih7++MZ= X05jc4aL1CIBnpbRU1YWvASJt9XmucnM/8K3RnQpfXMDao1Vvx40g5QhiTGxLNtyyow1fudoq7R= 5XKtQnMuRR+7dzCZGvAdHckdHdS7qCVW37fmbBW9A8Y7m6p/BPjJaNfX+LLtbcEbHq/OOV+yGD+= qpRLVpARiCle0PDWd6irDJGmLYsxipt6zFxZFtkfWIXX9oarsGTCsMavNi+Ysmzdk0Qi0Y1yd2R= BFAiSCBCNinEgEKQpPCAl8IFDtTr031y9/cT7bZtNbZrMPyLo9JsMnB1S1vn567sMa62dnJAqrW= IrSQa2JBWKFqq3dSrA0quRQp3Mu6EfEGo2W6pamSst5njjs/IqyqhdY3X19RIqBnAfshSqsOwfb= r6Jtbxx4c5h5Vpcgn4bDVvX+PClLPqbFmKjPcrWzOry0bNlkpvLWeKMTQTzQFlnjaFpCHQbt8XP= wi05tzTep+RtV+YQvMegKuoimRtVp1rnJncmtI+QYOJmrOXtWgZNBnMUSTm29lqbyZexoeQ+sca= 0UduHjZJvkP0Nut4z2BxJqmpeoaF801yG06VhQQvuy9ebBh4HcFQZtATrFzf2Z5XBh4y0N2SBYW= 4Gl5FoR9KM0p8ihPnR2jTt29fEN1qs0+Gsy3DfcLI1gbqKQD24vGMDWJQxUyHMeNnDxbz1yIAom= oJmzXudIxDlDwKAYcONO7j5Gddfe0lpvY88vpLi1SoNe226q6mKk0XeufPBvVmM5Py7V8rYJZ49= MZ0kg9apw6LeMeOmsSk9STchgzco17NHW17NevzsEgroksS+zAENNLIiCKMDtmb7IAJAOTbU/po= 59BTvcl57Xg4TwbRK1nfb61cobKylaCZYpq+q1ustW5r2ylkZa9WGQ14TYkVZJgVKNy3ijzI19z= M63C+xLFXIyZpjqo2egcfPxEzK5cV8KYyNKxVnYNnJfLYzFgQaWiXATJGcsAmBapnKoj5prdpA7= AHYfb8u3t+Xt7j7fl+mQ28cOh7xD41bSpG5KfO7jl73r+YJNQD6cucYRgV6DZdmoV3HRFcjCu2b= hq6cN3DU6wEVRVOmb90whkyoAIAAD9vb/w+392d+gp7CpXs/wCz+E2bFya0zRN7d/MEJBPqP+WU= qo7ICBQD0OhpPPHKvH/KeQcbPjY7hON6Dh2p41FX3Ff/AB3il1clpBLXj+eUetmCSGWxJ6wtNb+= aV09nLHXGMZvso7GMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGYjc+N9WHi7wt5P8hajHt5W16g0rfb= zWWLxIy7FafhYF2vDnfokEp1Y9tIi2dP0ynIY7RFYoHL37hlznEr7Rans6k23XN7hGVlpd6rkzU= rXX5JLzmE1XbBHrxcxGPEu4eNu9YOV26gAIGApxEpimABBjIutTaj5IRGpuDG9NYbptl3vFla6f= svLom4NqXScpWzdfbIpTOS2dPVSpyz2ZqdGtcBZJNrYteRlDhqnEoNGxqoYE4V0ZEsPO1OYu8qH= rfRW7KbtrcO17Fc+q7TdchyYqMzY4LjDsXSl52/P01/pSIoVo2A4Y2SCiKeieuN7HVdZta0lYIM= 07X7U9mm61jlrG2teIjPXlP1Vq9fbexbfqTTEXFQlI1/YC1ordaIqrdoyoDC3T8dCs5+1oUFjHs= EYH1r1E7xyxZS1lPPS7RB8TBFl0OdCsdQ1zQpN7cjXGodW7WgtzceqM9sdNdxGgrzXthJbFYSFQ= FWli7sqaT718GihsRzbk2VdmZlmwBq6kV3pmM6B4R6joesee3Wkt8Zc7nSkdZX/UNlZzto3DtKT= psa4n+OSs5OWbYkRM3ZaKuzGJdvHUqia5FlSQLZEiUIpFotGoIY6a15R7yptz6QEghc9822W5Gb= 5tuv8AcG8bFMWmN0TylpdopFrsSc7T9XXq9zM7DNmci0rs9RZv9ndCatotB0WsoMa1MJRBpokem= 7rb9oXJK7P9n7Wk4rl7Tq7U+RtEcvKslW9kq1ygyOt0p1dy0rLeerr6SrckZOVaVWWhYx04aMzF= aJIpqoLdG1zo36zg4HjfEv8AknyUtMjw+tsHYeMk/ZJjXjx3qWHhIeQgDVCNjUaA3grBFysQ8aM= ZGTtcZN2EG8FBoMJZk3aLIOmMwp5q72snGPqa85N/05khI23UvQ+ibnWWrpAzlmafieQuzVYlZ6= 3KYDLsmr8W7t4j4i+Y2RVKJyd/EHMtz7a2pxR40dL3lPW9q7Ru983NuLivQ+QEdbtjXO313b0Jy= TrqBbsq2pE3NPanW5WLscm2sdNPTIOAQrjdh8jjG6FeXcRp5HrN066FeeSWwOR172Lcri92jx5D= izedeTcVTlqRPaV/Ek5aFK26TSgkpr1riRsMim5miShXyrUyafiKoTzR2qu9OKjQkRx7rNz2fsz= cOsuI03HW7QOrrsnTxjK7PU6GdQet3M3Nw9djJ+4OdcwzlSOp686/VVTV9PKTR5iZaNZFFjK88f= uPlJyV6TvMvrDsOW3IDUfImjX3e140nQKzsuajtH6t1tpK8OK1Eadm9IqH/ZzcXlggIx+SZsNwr= EnZHlgk46RTdoenI3P3/wBINHZ2zuRG1dD7L5F8ob5p+E41aT5ZUys3jcWxYy4Qlq5kw5LrKQUr= sGBs0XdbfC63YNSwdYTl5r5c3l385OhENpFdmZhF1prml0hJGgbU1fzX5rb80Cw35yItu3uWXTh= hNH7AgdKUraAXxd7Oa6dzsPqOxXZnU15WAhpC5x8BsKNZWSXRcO3URCJOXMK0t8Q/G3Su6Lhrbm= pxZ26817I2vRsFryIvmo0KjPUXaOkBFKcobF/BWCGlYhZKrKrndVGWjE4yVikXjyKcqLx6qkcVj= I5NP8zNgv8ApsdSdTbNpkrdOcTNxcpeLdU2HPLkXsFyhYJ+Wu62e2CSTSRLL2VsjbYevyUqcnrJ= d3Hg+fHXkXLpdSpC95BTRSxb+vVKn1y6M4GAg3mxCxyk1b3f4cimMPHSEU5nVpGNqcom2jmyvzi= sRkZPA7A7gJb+k8BbJXWcita8HeDmvuG2onMopKb427Ytp7Mnpt4i/tV8ctZRW43S43F8mk39RM= 23YcvBPii1atGCKUStGRzZnHMkGZKm4/Qf5gPv/P8Az7B/L2yo+c7F32kVWJ+hVrIJOgO1mlPyn= okEqwj+M+ykMPYj26JGfV/9EfAKsPjHYcl21JZZOTcitSUfkLiOXV6yKGgoliDKliGS/Hf7inV4= WaKOT1JVGXuuHve0K5FO9iHn3dhi73ZZivW+Ntgms8NcH0IwhpdULVHTJnjaXX8FjIuwfLlCVjX= RDvot40ekTcJyxdH3lXT9f829L1GEq7bW9T2Se41i2oBNOZRlI3K4MGRK4SPcPkiyDOBZOa/Fxl= fh5N9MvGL2amFfmrkZECpYXRWrRn+mZO7QQSRF3T+aDavGXUUbt/BG2XTsaouUy66pC+EX8awAq= Yj/ABe4Abv3LhFDyE9T5mGtMFJFiZuvSsfNQsnGybQXsdKxjpF6wetTNHBl01mzpBJdJUgdyHIU= fEHtkbgs2NVaoWQxcdV7n7+iSnydyIHbtkDNGVboj2P23Y6z0NveM8e8nca53xtooak4m3vEjJW= doYo7UWujj11mzWhZYLMlKO7WmrmaORq/Q+EqR2fVeIACHi/X29//AN/x98+mR19NbnTUucnHiv= XRF2xabSq7RjXNt1NJQE3MRamzUqaku2aGOZf8P2UqRpWHcAKiSYKOY0y53cc6KWRMvuAD+f8Aj= 9/78virZhuV4bNdw8M0ayIR/wCrAEKf6Ze/VgfsEEH7Bz4acj49tuKb7acc3tOSjttNcno3q0oI= ZJoX9SyEgB4ZV9ZYJVPpNC6SISjA5rjGMyM0uMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYx= jGMYxjGM2axtpV5Xp5nBPU4ycdQ0o2hpJZH1KMfKrsV0o56q37h56bR4ZFdRHuHmlTEncPFm84x= jKvPFOqMdN8aZLjpys6Um7+SPNyRVuMZuW+SWkaTtLXvKi9zMvLmR2c85VXOQCnx9JtMe4jVDfj= mYgpqhxBfkDWrCpDtI9WaDpw8YpThZwj4/8brG/j3U7rCkHaWA0U7dPYKNmZiWkrNLQsE9fETdu= oCvvZhxDQzt0kiu5jWDdwqikZQyZc5ewd+/b3/POk+Q9G2JsvTl919q26sdb3K6QbqtMb4+i3M2= NVZTAejl5aOi2khFLOZpCKVdkhjDItEmsodq+VOom2FurwkZkR2VDIyozKikBnYDsIPYhQWP12S= AP5PX3mTSgis3KlexaiowT2YIZ7s6yvDUhkkVJbMqQJLM8cCFpXSGOSVwpWNGYgGhh1f8AlSnyo= 5pX+XhJD5hQtZm/ZfR1UlCqNnLGtO3BJiVbmIodI6UtYVZN43XJ7qsTNBN2EvYIuu4f4fp7D9/8= /wAvvl2bUnw5nE2pmbSG177s7bsmUSqvW5nzKmQDtUR8SpgaQqas2QiphERBSwrGEoj3MIj3zGf= q7dHjVVB4+x26+I2vi1Z7p5s6NsaoxjiUklLPRVzis5tHmP3L504mqmt4nT1QTgLmAcPVFlBGIa= JGp7Z8X3sq3tvbWH5GZrMkCSGWb0LD2VfUGPqFPsASElE9VXvrPrj43/U54O1E3CfE/F5t3/r4Y= KfHaO+ua1NfqBZWL4oZbL2rEd4Ns73ZaR6SIti4HkZUEjDETjDqkt26DXMGQO1MqvF8gvxuwUSQ= K4WSLTYjVRHjlIh1EgAU491JlOIKE7JmVHuIiJRjl4AcDrfz33KbW9Sm3tYq0DFrTl8vzmvlfsK= vGiB0Y5Erckqkm8lZd8AN2DAzpuZVBJ+7A5kmKoDZ+6V+hl7x0X5zXbVkQZXecLv1ZoksZNEjmV= mn01U4JZRRYSJJgIwEWAKqGBMpEyHOYC9wLIL04ODdY4LceILXLYjOS2HPAlY9q2xAvdSbtztEo= LNWi5ykVGDgEPBEQyIlTA7dud6qmV2+dCbc1uMf7Q8ensJ1Tj1ERs9H1Mje5mih/hu3Ew9z+QqN= 9glRlO8g/UofHUXn3V6Wz7cw2PlbaRcY9o454qNd6dfW7DbyRyo8TpRbUeteJ/dJbdiv7xSQJMu= Rz8TeiNtHhrteL2xp7mg+Zv0BK0sFee6pIrXbhBGVIo6gp9kS8EBdsqBfEg4SMk7YuPA5aLIqk8= Q2GESnKmUFBAVAAPGJQECibsHiEoCJhAoj38ICYRAO3uP1z6FDsHb9f7fYM1ye0NbT1kTQUo2ii= ZvcoZZZFDEAEqJXf1767Pr12fz/AB14c5x5C5Z5H2UO55jsYdttIa4qrfXV6rX2ZIFPccdmTW0q= ZtCL7EJs/K0KsyRlVYjGMYzOyFYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjG= MYxjGMYzb5GMZyzB5GSLdB2wftlmb1o4TKs3ctXJDpOG6ySgCU6SqRzJnIYBAxTCA+wjm4YwQCC= COwfog/gj+jn6CVIZSVZSGVgemUg9ggj7BH8EfY/g51zqnVVJ0rQa7rLXcOlA0uqtVmcFDomMok= wbru3D06RDHETmL57lU/c5jG7m9xEfcexsYziqqiqigKqqFVQOgqqOgAB9AAAAD+BnbYsT27E9q= 1NJYs2ZpLFixM7STTzzOZJZpZHJeSSR2Z3diWZiSSScYxjOWdOMYxjGMYxjGMYxjGMYxjGMYxjG= MYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGf/9k=3D" width= =3D"236" height=3D"116" alt=3D"logo_catalogo3b.jpg" style=3D"margin-top:2.3= 5pt; margin-left:-22.15pt; position:absolute" /></span><span style=3D"heigh= t:0pt; text-align:left; display:block; position:absolute; z-index:6"><img s= rc=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQ= EBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2= wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQH/wAARCABhAN4DASIAAhEBAxEB/8QAHwAAAgICAgMBAAAAAAAAAAAAAAoICQU= HAQYCAwQL/8QAVBAAAQQCAQIEAgUECg4HCQAABAECAwUGBwgAEQkSEyEUMQoVIkFRFmFx8BcYGS= M5eIGRseEkJSgpMjM4Vlh3obbB1homNWeW0fE3dYOHl7KztNX/xAAcAQEAAgMBAQEAAAAAAAAAA= AAAAQMCBwgGBAn/xAA6EQACAQMDAgMFBgQGAwEAAAABAgMEBREABiESMQcTQSJRYXHwFIGRobHB= CDNC4RUjJDJy0VJ0wvH/2gAMAwEAAhEDEQA/AH+Ojo6Ommjo6Ojppo6Ojo6aaOjrwWRjV7K7sv4= Ki9/mifh+Konb8V68u6e3517f7O/6/wDr0yPfprno6Ojppo6OjqGXNHnTo3gzgAuabcsjzLW9ln= DwzAcaiGMy7LzxmscSleMWUIIFWV7ZYpLS5sSRwgmSRRRqUeQICTIBJCjkk4A9SdNTN6OlS7H6S= vaqaR9UcTQG1ySOQX6y2wRIY6JFXyOn+FweKFsjm9lcxnmaxV8qPf28zs9gn0jLJMzzfD8Qdxap= AGZTk9FjrzmbPOneE25tBa5SmwOw+NszoEJWVIlkjSTyeRXs83mSzyJf/A/iP+/j9YOmmlujqr3= mT4svHTg9tOq1FtrD9yX2S3GH1ebiGa/x3DLWljqba0uagaCcnIdgYsa2waVRGSTRR18o7YJBnM= KfI+SKGybGL8PK8boMnr4yYQMipqy8CiMZHGXGJahwnDRlRwzERMIZDOxszIp5o2yI5GSyNRHrW= QQASCAexIODjvg+uPhprOdHR0dRpo6Ojo6aaOjo6Ommjo6xtxZQ01TZ3BDJZB6qvMsiGQNY+d8A= I8hUzYWyPjY6V0cTkja+RjXPVqOexqq5KxeHvi48cObW2Z9N6ow3dNFlA2K2+XSG59jeFVdGtbS= lVoZULCcf2FlBynPltB3DxLWpA9jJlkJjVrGySASCQCQO5xwPnpq0zo6OjqNNHR0dHTTR0dHR00= 0dCqie69eL3sja573NYxqK5znKjWtaiKrnKqqiIjURVVVX2RFXpebxEPGsrNRW1zprikymy7YFd= IRXZRtGxjjtMQxE2PzRT1uMgI5IMoyASRqrOcW92P1hDGQqNeTKUOD6faeztwb2ui2jbtC1XU4D= zzMTHSUUJIBnrKgjohjGfZHtSSN7EUcj4XXmt07tsWzra9zvlYKeHlYIUHm1VXLjIhpYFPVK59T= 7MaD2pHRedMNK5E79/u7f7fl8v1+/5e/WpN4bu11x51lk22tpXzMfw7Fg1JNK9NZyzCH/AGAqmr= DYqSH21oSrBK8OJUWaeRPM+OJskrEFMr5x8ws3vSMhv+R+3yLWchxSJXZtd0wQz3KjlbX1NKXX1= lfCxU+xAEHBBGido42p7dTy4veLFmHwJGhuccK8huOGcDNx7JDcmGSyznExCnpG24htovJYZELX= PVpckRksuQgvgiOoLYYsSIEreNd/DPue1U0FwkrqG/RU0kU11tNoaanuctGrK1THapquL7PPVGE= SeSsqxeY+AiSMQjaapP4htv3OaahSiq7LJURyxW26XMRVNvirGUima5RUsgmhp1lKmVoWmCIGLM= oHVrqG3vGH5OZryfpt74DdEYThuFFFAYbqmYh5eN2GJFER/HBZyJDLFDdWeQDwRPsjIlZJVTtgb= RECPChLc1zwt5p6t5qasCzzBS21mSVzBhM+wE0qGW8wy9fH3kGnRiRvOpy3tlkpLuOCIexGa5ro= hjoTAhk8OdnBMvjQdUbT1TdrtDits1YrTWOza6SOxjrxrNFIExfKDBG+gy1GiV0Ydg6MWG4ige9= IBjoTQRox8beSe1eKu0qTa+pL2Squq2Ro9pWTuklocqonyMcdjmSVzJY22FSc1qd2+aMkIhkJ9f= OLYDDExbb3L4TbL8RtlWyr2HFSWyutdG1NaZVjaEzGn/n2i+xnMqViT9YmlqA1VTVRkZzJDK4Or= tueJ+7dh7ur6feclVcKO5VaT3OFpPNEXndCRXWzuGMUlK0IUxxwutNPThQhWSJCP0dEciqiJ9/f= +jv15dQz4Vc1NWc1NXC5zgpUdbk1XGMJn+AllRS3eG3csSq6CZiJG82nNfHLLS3UULBzxmubIkB= 0BgY8ykd5vdO3bt+Pv/N93/H2/P1w1crbX2avqrXdKWWiuFDM0FVTTr0SRSqcEHuGU8MjqSsiFX= RmRlY9m225UV3oaa426piq6KriWannhbqSSNwCPiGU5V1YKyOGR1VlI15L8l+72+f4dIDeMvvK5= 3Pz33GARYTkY3qGxH1Lile9yejXR4oNDDk6xRtRGeqdmMt+S+VyOlkh+Ehe9Yx4mMf4d8l/Qv8A= R1+bnz9DKq+cvLuCwa9Jf2ye4jfLJ3VyiWGf3liE5O6d1Y4Aod8a/JY1aqL2VF6qphl2PqqnHzO= PePz192mi+Ffge8Uq/QWvcj5E4XabI2vmuL02WZOh+S5DR1mLEX4EFnFi1XWY9Z18SrSDkxAnnG= SmEG2UJc8TxxJIBIJlUng8eHrjl1UZDS6FgDt6KyBt6sr8ts9lUawrSYjAiEjmySSKT0SIY5PJL= G+N/l8r2OaqotiOFXNXkWHYnf0k0BFNd41R29RMM9r4JqyyrBTAJYHs+y+F4s0To3N+y5ioqeyp= 12fqkySMSS7c+gJA9OAPQcfXGGlqvF53fwS1vycxeh5McR8n3tn5GpMbsa7MKbZllh4oWNT5Nl8= AFE+sEIhjlmDsBrMxxisV8jD2RKqpC1G3iZTv7TXH/jvR7h2LdDa61hUYZjBQqHyT2BIoptSI6l= x4CGBsp93bvidCCKMJDMSXMxX+XyJJIxTf6RD/AJcOCfxfMK/332L1tLx6Nn3n5C8GdNDGkwY43= T7dk24EcsiC2VuRXUONUU5MKOSJ8tOKBfNFc9rnRpck+VW+de9vlhvJGT7Wc85wAFPAPbJP6e7W= R7D69FP5k6mTk/0kXj4BblC4hx+29ktNDI6Ma2urrEMXJLa1eyTNqxysldDFL7ujScxk/kVqyQQ= vVY2y64f+Lzg/L2i5CXtDprLMLj4+6sP2jaD22UU9o/IwwQ7gx1UA8OuHaEVI2okYhBKTRNWZjl= j+yqOX64b8s/Cg0PpfHMa3NxMzzde3yoZT9gZtkmGa7yetmt5yp5I6zE4MgzmNaygqQ3DgDujrg= S7OSCSzsIo5yUGGua4w8huEPIPjpzisuIvG5dDn4toHNQc0MnwvCcUIyES2wXNJ6oZkuI3Vu4yE= KYAqV7DVgbE+ZjoUkV0nlmSNVBxG49oAMWGO6gnj3jOPoCPTt9/4cfr+OtHp9JR1Inz4wbGX3/z= 9xn/+N1tPT30h/jLn2b1OKbD1dsbUdTdFjgQZmYfRZbQVZJMrYo5shirVrbavrEc5ElOAAuXQd0= fONEO2QiKmnwN+PGl+SPJXZGIbw19RbGxqn0xYZDW1F+wh4odzDl+JV8Z8SDEDvSdgZ5kCK56t8= k70Vqr5VTvnjq8SNB8XNlaMn0RggWvAc/xDK5cio6ck6SmmOxy2q4ArEYQ4kpQyphrR8BaDSRjz= IMPL6DSFImny6IPM8vDAkZU5yOQCPo//AIIwcfL8/r+576cW2TujWOotZ3W4dh5hUY5rehp4rw/= KSZ0mAdXktjcC4D4ZJprIizfPBDVhgREFWRJA44cM000bHUO5n9I+45VN2WDhGituZlTDTSRQ3t= rZYriPx6McrUIFrPishKjGl7eeH414RXpua6cSCRXRNr28Unb2Vfud/he6uW1LfV5xq6XO8rR8r= /NZm4Li+E0OKtJf8yIxY8svZVjkVW+swWZzXSRRuZPvwm/Cz4mZ3xB17u3d2s6zaufbZ+vMgfLk= xdm+rxuhFvrGmo6WmrAzhAmueHVstbCwJgmsZTrIgRpDARhoG1qkaJ1yAkliqgHHYj5Hn8O2o+v= r8dSv4W+Lbr3njlWzdcVGlstwiPENXXmc2hN1lNRaQWtWLOLWFVMDK4ASYcghtgqtIc9zGNav2V= cqKkJfCU3pwK2LynNx/jZxByjRuxG6yyo6fNLjZ9nl4ktAPZ47HY07aosmaJsppE4MzCkb54miv= Yi9pXItz2GcLOLvG6r2Ll2j9NYlrrI7jXuSUVlbUMRrCi6h4MhrgZVJMIZ6DihYJ1RrGu88Tftd= u6Kqn9Hz/wAvK0/1IZ7/AC/28w7qQqMsrL1qAuQpOeQBnIBOf+9T6H7vw9f21cryg8djXHGHfmy= tDXOgM3yuz1vdD0xmQ1uY0NcDZyEVNdapOMEVVzzwMbHYMhVkkr3K+Nzkd5XJ1pui+kkaILthB8= j467YpKaWVjDLOqyTEsgNEjc5EdNHVEfULCvIi+ZzEsoHqjVRvmd2Rez81Oa/hE6n3tmeN7U40U= e+tvj2XpbGyPF9X4JkLgsiFghElrL3JcpuKNbG5BgggFMiBdYIBJD8AVNCUPKPHTvzo5ZeGHvrS= hePcc+J2V6V3LWXVLZYtl1fh+A4nSTBJYDxZFVZMmLZdYT2IRdJIZIAySrJkGuIAJI5hh3lrJkk= aOFBhkBOAWyAOQMnB7D4YPHYY50Hyz9D/AKP4/DTqWkd2635Eayxbbup8hhybB8uCUyqsY43jzx= vhleMbX2IcqNnAtK0yKYOwCna2UcmGRi+ZqI5dr9LufRwr6zO4ubtoCSZJq2h3m8qrhkVzvhFu8= GxZx0UPmX97gkmroyPSaiNQiciXt55XqrEfXzuvQzIOQpwD8vrGo0dcL8vn2/Ov3e/6/wDHrnrh= fkv/AJ9vf7vf8fw/P1jpqiTxsedlzoDXNRx71fbS1eztwVRh2RXwMvon4hrZs0tbO4CZqpKNb5g= bGXVBGRd5AqyvuponDmS1pMa1vCvhnsvmxtqHX+Eo6soaxo9psLOzB5Z6vD6KeZzEInTzM+NubF= Yp4qSpSaOexninkdJCCGYWNK3xunZCviAZ+l18Ule3Dtdtxf1/P6C0SYwGsihK77PofXjrn1PJ9= n4z4nzL5/N0wn4KWs8Nwjgjr3J8eGEffbRt8qy/NLaNrHFnW4eRWWMggzT9ll+HpKijCBHDV3ow= EuPJjjZMcS6TtKku8Hg/4GWW8WCnhl3Bu4UshuDIsix11xp5atZpz0lXS2UcLU9LAT5f2kdbIS0= +eQqm1zeKnjJdbXep5I7JtlqmMUKuyM9FQTwUwhi5DI9wqpfPqZ1HX5DBVf2IsSd4z8BeMXFvEw= MfwDWdBYXsQrYrnYOV1lff5zkhMkcbSirC7NGkeJAQ5iK2np466kF9/hq+N75ZJIE+JN4R2A8gc= Zstm8dsVxzAN40kE5pFLTCCUWN7QGRr5Zq6zEGbBW1+VOcr31l8kMKHSr8DdSPhlHOr7x+uHNRy= Ki+6L/X/AOfXLlp37u2z7gj3PTXuuluwm82omq6maoStQtmSmrI3crNTSLlTDgLGMGHy2RCvSFz= 2Nte62FtuT2ehhtnleXBHS00MD0bquI6ilkROuKeMgMJQSzkESl1Z1ZFvhjzNseMdnmfFblZhZ+= a8acysD8U2frHKQJ5bjXN04hwljfUdeX6ZQRIJcaT2tYM4YpJhorammFuhInldQ548DLHjEXR7W= 1faTbI4s7RQa21nscRFMSuGuIFOr8cygmJjGQWLRlclefJFBDcwwyOa2A6EsOFsLkZ4ZfGXkzur= A93bAx2ePIcXMikyutp3RBVO0a+vh7UtdmzYmNnISsJYM1xY0kRh9SySkNllEcLIFL/ZWmtebU1= TkumcsxqrM1/kuNS4wRj7BIRwAq9o7Ya9aweBkcdbPTSQil004TYZqwsMQgN8Mo8Tm73Pj1Z7du= Cy7ksFpraSa8RoPEKzl4xa6meN440rbenLG6IqPL9rUQipp3ip6pWm6pItJp4JXiusl1sN6udJV= JaZCdj3XoJuEUDBpGo69hgi2yMwhNKWcwTLJPSssTBJPz2eN/I7aHFfadDtnU93LV3dTKkNlWyy= SvpMooppI3WOOZECx7WH1NgyJqOa7tOGS2CwAmGOGHIjfU4e8qcC5haUx7b+CvQVxfmqcsxmWeO= awxDLgYR5LWgPVnbzem0kcyvJVkaHVRgRjWRrM6KNAzfGrD9I7o2hqKynUkrXmbZBiylq3yKZBV= 2M8AZat7qjVKDQchzWqqMdIrUXsnVqHga8iLbVXLFupCTpUwvfNQRSGVz5f7GgzHHhDbjF7aKNy= L/ZT4m2tK701Yssds183n+FgSPa3jnsO1bz2e29bTEn+MWq2R3SGsiQK1zsoiWomgqCAGkMNMz1= VK7dUiMjQgBZWKa28G963DaO6o9qXGRxaLlXvbZqWRvZt92MoghngU56FlnVYKhQel1KSn2o1y6= OvyX9C9JX+PTw7yvWfJA/k7QUpResN2Q077+0DFc4LGdi1NSNSnA2T4WuYKzIwKsK6BJIcxTrGS= 5jb3eOivdPavfv7/1ff/V3+/t1g8mxbGc0orPF8xx6kyvGrsSQC5x7I6sG7pLUKZO0ollVWUBIJ= o0iez4CYJI3fe1e3XA0chjbqHqMEe8HB+7sNdxaSe4keOvv3jNqPGtN5HrXENx49hFaPR4Zc297= b4zk1XjwieQCjsDRBbYK3BqRkYFUuUAIsUGKEWYkqOGFI5p4B9Iw2DmedYbiE3F/DgIcpymgx6U= 2PZV1PKJHc2otc8qOB2KRtlfA0lZWxukY17mo1XtRe/VxFz4QvhxXtiTaGcXMQHJLkdLLFTZFsD= Hq5rnL3VBqihy6tqgo09/LCGFBCxF7Mjant1xSeEN4dWO3NVkFNxtpgrejsgrerMbnO0pXCWNcT= GWES2IjOJYJHQEwxytZNFJE5WokjHNVWraZIDn/ACjk+5iPd8f2/U6aXK+kQKi84cE7Ki/3PmFf= pT/rvsX5/wDonUrvHG435bmXG/iRyOxSnKtq3WWuq/CtiuChmInqaHJKbGbLGrsiKKN6xVQVuLb= AHlve1kE9zWo5PI58jL5N/eH/AMROUOaBbD3tp2uz7Ma6gDxgK6LybN6eWCirzbCwEAaLjmTUwL= 2QmWp86TSivJcpDmPmdGyJjJUwYtjsGNwYf9UBEYwPTQ482jPhSxr5aSANteysKgP+JaaKoTEGl= jM9f14vM2dZPM5VjzsCLpBzGCDk8NkAenPYf2OpJ5HwxwfgAD+mkkeHXNPw0cL0rjeE8q+ElFmm= zcWjnq5diYxhuNW6ZrUxkPlrLO+ZY3NOSNkQ4ksddZSMjMhsnBx2riWEmkCw3F8XuSfBHdOiOcG= N8NdBGaUNpuOWcXecSS4vR47BfjTYbmAFOxHVF1bPKmClcY5EmZC2Nk6q17lcqNnTk/hJeHVl1w= ZeWvFvBxjjpnzkR49a5piNX6sjlc5R6PFMnpaQJquVV9MOuHjRV/wfl22jpzw/uImgANiVeotO1= 2HAbXxWfCdgDjZNnFmmRYwTCaPPVTSXmT2koUckNgYxSKt4RjfWVzCGuYxWnkjYEgOGJU8tlRgg= kY+Q9fh276jSxv0cdU/bc7b/ADaAtU/lTPMG/n63P9JUVPy+4rp+GIbK7/y3OL9MKcfeBPEvivl= lpnGg9QV+vsou6KbGbS1EyXNrmQujnNCspQHDZLklyHG15tcHP60I8ZCLAjGzJG+RjsvyJ4T8Ye= WB+M2fILVgOxTcOEsQcamLyDL6RawW2mGIsImNxnIKWMhCZgx3q4tk72emiROY1z0c80ecJB1BQ= MEYGcYx78fn+Y1Ofazz3B95/bS3viDcasu2n4UXh/7xw2pMu5NDasAGzEGugeQWLhGfY7jCl5G+= KJHSyhY/b4nVxm+RkiiB3BJ8iRiilzR9F8ObxusY4ocfaLj/ALo1bl+Y1uCF27cHynBC6RbB9Hd= Wxd2+lv6y/sKqJJKuxsD2gWQR0vrVsoYM1fDIApZjduEa4wrXWB49rHDqAWpwPFaEXF6HHHyFWQ= YVAEMgg9Y+W1nOLNgaMnovU8gmSViqkz3+ZyrCjMvCg8PLPL0zI7/i5gUNmfI+ctcaNyzCa+SaR= yvklbSYZkVDSQvkc5XPfBXxue5VVyqqqvULInSUkUsAzMpBAI6j2P3fnx251GtJ8VvFf03zwsds= az11rvZOIWuMamyfMDD8zZjLa+cGJkdU4UdaS9tCFKWexikRJII4vSZIqyI5GtdQB9H0/wAvG1X= 7/wBhDPu3t39/rzD1T8Pw/Hv+HTWGi/D94h8arzIck0jpyuwW6yrGy8Rvzhcnzi3fYY6dNCQVWv= iyHJrceFksw8MizjRQktWNGsma1XIvq0N4e3D3jJm8mx9G6ZrsDzWalOx6W8FyjOreV9PZTCEGh= /CZFlFvXo2eYEV6yoIk7PSRscrGuejiyIokAVsOuFBIODxkk8fhj46aR7w+31vonn5ldhzX1jc7= TxHEtpbSg2bg7nerYXN6W/JIau3mHLsKyG5EiyAqtyFRibCEW0CYkrlMhkaORMvmXyx8LDaHHjN= 8K40cS59XblticWfi2bPwXGaZlVBXZXS2N9GtjXZJYFj/AFhj4lnXIkQkiSqX6Mjo45Hva2Jvbg= Bw75LZJHmO6tD4hmWWtgiGlydst5jd+cOO1GDQ2ttidtRHXEYsbWxCNtZzUFiRIx/TZ7daK/cbv= DY/0Y6X/wAe7Y/586z86MlWKyZUAcOcEjHpnn+wGmq+/o26p+125Cp/301f+41P/V7dMedR748c= VdB8UqC+xfQGvRNeUOT3Ed/e14lzkt0w+3iChrojHzZNc3RMLmBDxQekPNDAqN86xK9VcshOqHY= M7MOASTz8dNC/Jf1/o60nyA39rLjTrDJNsbYyEegxbHx+7Uc9jrK7tJfN9X4/QAueyW0u7SZqQi= BQ+zWpKUS6AAUsmHdbvkvt39l9vx9vl0qr48ujOTJmV4/uom7sc144VYo9XXUNSLLELqi+IZDAU= XkQA7nxkw5NOjUDy2ZvlZO6PHi1Cd9Vpae38OdrW7eO7rXYrrdobRRVTlpJZD0zVZjKsLfRMymF= ayrGUheYhFwxRZpjFBJ4rxB3LcNp7XuF5tlrlutXTqFSNATFSh8g11UqkSPS03+6VIwzMSoYxx9= cqfXyWH1l4y+npdy8egXY1yu0MDYhZFp26NCdkGa62lNIMAbVksSBls8UiSUqjNga2Ia1Ps8etG= Qy2FMXJFPwufEnuOGGVE6I3ZFZt0fe5MT8ahQpLbvUuWEysDs7OMF8aGPoSJ4I/wAo6RI/VDJim= tgIPjX2A1jVPp7cOw9C7ExzaersiNxnMcYMaVXniOX054VVELrbEZf3o6rsYPOLYAkNfASO9zHs= VfKqXTbL1dqjxXtVXXIfj1WVOB81MEqmE7v0YNLGPBs8cWJqfldiMUixISeejFUU2NXSTFJ9RX3= lsFq7Wx7KvW1bZta0y7L3LFNcPC66ThLVdZHMlfsa5TyEwQ1lThpBa2qZWagubjFJJM1JXF6WVW= PJVp3LcNw3OLdm35YqDxFt8QkuNvVVSj3hQRIomlpIAyqbitNGq1tuQ/6qKNaqi6KlGVW56C9p8= npavIsftALuiuwRbSnt6sqE6ts606CMkM4Ewd8kBIhUEjJoJ4nujlje17XKi9+sv1Qh4GmG8vMV= 1Rkrdu/HUuhXlEQapxPMhD48xEuYDpWXx1BEW+Iimwp5DSonBWEDmHXXrmU8I0HxhFhfcnsn4fr= 935vw64g3fYItr7juthgulJeYbfUGKO4UT9cUykBwr4yq1EQbyqmON5I450kjWRwoY9j7Svs25N= v228z22qtM1bTiSShrEKSRsCUZkzhmgkKl6d3VGkiKuUGdHZPwT+br4La0Apaywt7QqEKtrAirA= 8wiRkUAoQcDyCiZpXuayOKGFj5JJHORrWtVyqiIq9feqp96p/KqdLY+NB4kVfR0V5w/0jdxF5He= wOA3VllSUj4sfpZU/f8AX9cTA/s64uG+VmUSMcrK+qV1M5khdialb9GydnXXfG4aKw2qJiZ3V6y= q6SYbfQq6iorJyOFSNW9hSQZZSkSZdxqneO7Lbs2xVd5uMijykZKSmDAS1tYyMYaaFe5ZyOp2AI= jiV5WwqE6Xf5XbRC3ZyT3dtSt96rNtkZPc06q1Wq+nksZYaqRzFRFa6avhHlVqoitV6oqIvfrbH= hwV9lY85+MUFUknxUe1KIt7ou/dgYSEFHPcqfKNgcUyvVfso3v39uoSonb9U/4dX7+Ahxrss53v= lfI24r5W4jp+nJx/HTZopWQ2OwMrEcPJCI9zfSn+ocZkNJsGo5ZBZ7mjkVPLO3t+iu/6237P8M7= 6rlY6Wi249mokcgtLLNRi2UMWBjqZ3eMv0g4AZ2AGSOCtk0ldujxBs3QrPU1l/iulY6DCxxRVQu= FbISoIRFSNwM4Bcqq/7hhvhv3p7d/b5fh29v5+3f8Al6rw8T/ldsLhlxeM3TrKtxu1ycfOcUxpg= mViGHVChXn1l8VI4cA6unUhvwkfovQhGN+15mP7p2sPb3+9O3b+b8fb7/v9+/8AL79+qUfH5/g/= rP8A1ua5/pvOvzAiAZ0BGQSARzg/vj9dfo+Bkge841S1/wBIk5of5jaM/wDDWT/82dZWm+kW8uR= bEae81lpO4rGSMUoAWsympIniRyedkJzcjM9CRW90a9w0zWuVFWNyJ262T9H+49aN3lXclZNxao= wTZkmPG66ZRPzTHK6+WpZYQZS45lep8E3wyFOFHcR6Xl9VYYvP38je1pPiHeFRxYzzjPs/IdT6f= xLV+1tf4heZrht1gVTHQpZl4yFNcEY3b1lesFfZB3wgs9cyUiBSQC5xzR5u0EkE/wBTtAsnQYux= A6h25x8QeM/lxqNSl8PvxD9W8+tfXF5ioBOHbCwuUEbYGurQyEw2lWzildW3NSdGyFLjG7OQYwc= Y9BxiRzBCBDg4HfCymRL294zdFqjmiRw6n0TbXB4+zcI1uudR5wIEK6XM3Y+kdr9SOx6eZIwPr5= vnF+sVcR8MvaaJZURi6Pgq7ZtdX+INqIEQ2Qen2gNkesckEav71Yh3tVMfTwytVUaij5VUUJjH+= 72qO5jezZHo62XkRzl1Dh3iYlaQtOEGhMwy6Pd+r8WXdl0I52ePsb52IIHkzpUrJE+taL6xgSvV= Cvb6uG7Pj7IjcGhCyMoVnXp6h7QUj55745x7/XnTTQqfJO/z7J3656gdzs8QLT3ArAK3J9hQWGU= ZdlMpgmB66oJh4LrJiQI4nGlkmFI8eloK5xAzLK4mhLkhcUPCHXnlStGWhY76SnsZ5Uzqzi9hUA= Svco8R2fXxpTI+6+VJiR6QGGV6J/hOYLC1e3dGIi9kpSKRxlVyPfkAe48k4/M/vpptrqj/AHn4z= tFpXmQbxHI0Tb3xoee4bgy5tDnAYAj5MvZSOZYfUr8eJlawH65ajoFPV0/oKrZYlkRGx04a+Ops= PlFya1JoO20LhmK12yb2wqCsgrcpvTzqxgWPXN02YcQoKMeZ8klWwdWyva1rJXORfM1E66Dyk5z= ahwTxIbPS9zwg0FnWWQ7Y1vQv3JkAjnZxMbdR4wod/JL9WSd7Gl+OgaA74pfKgECI5ns1uaxsGK= vGT7BbAYDHbnqBHbn1+7Tj1/XH7HV0HiPclM44kcSNhb21yBQWeWYpY4WJXh5MKWXTSx5FmNJj5= qlDhGAEvdGHYzyQKwqPyTtjc9HtRzHaG8JHnFtbnZp/Zuf7ZqMQprjDdltw+tgw4CwABmrVxiku= VlKisbKzkeUpVjOzzxyxxpE2Nvp+ZHPdVF44viFZWlvubgN+xtSrjD4tW3KbGW2sfrn1UZjGwPQ= Sq+H+r1Z8Uz6t83xHm9FVm/xnZnVb3h6+Ktm/ATXWc69xjUOObFEzXNkzMiyub22qpwJ0oqyk+B= jirxp45IvTrI5/UeqP88z29ka1qrmsJaEnpHWWBU556SRxwTz3z8+NNPwdHVK/OvxUc14iaf4r7= MotRY7mhvIbDW5Ra1VleWwA+NTLjOKXyiBTBCzSlxpLkco3qEtjejBWOVFc9/lrGX6SXtln2pOL= 2CIxPdyrmOTN9u/v9p1b2T9Kovb8F+S1LFI4DKuVPY5A9cdiQffn3aabhX5L93S1OU+L/wAkaTx= I4eIYmL6vfriTkjimoVtZ6a7dlCY5eZJTU5ZaGNv2g/WkY9hM+Gb4D4dsrY3PGe1HMdPbw4fFY1= 1z7myPC5cPK1dt7E6tL87D57dl9VX+NoVAARfY3cfBVs7215xYUFrWGgxkA/HByQknwySywLWbC= /hzxv48+u/9+8Y6zjj9qRXXlYyRk9j6dj7u3pydNPZp8k7/AIdHR0dUaaF7/cnf83y6wWSY5R5d= RW+NZLUgXtBfV5NVc01qNCbXWdcbC+AoIwQhr4Jx54XujljlY5j2L2VF906zvR1kjMjK6MyOjK6= OpKsrKQysrAghlIBBByCNYuiSKySKro6sjowDKysMMrKchgRwQQQQSPXSVvijeFxkHFK+sNw6dr= T7/jxenLIWPF6htlqq0Nl+xT3Hb1JyMWKlejKLIHedB3+WmuXRGJXGXNVWodv7D0VsHHNoavyM3= GMwxk1hdeeHJ+9zMRyIQBYDr3hPrDofMOcASx8BI73xyMVF6/SMyLHKTLKO1xvI6qvu6G8BJrLi= otBYTa+zrjIXwFBGCztfDOORC90csUjVa5rnIvzXuml4n/hXZJxdvrbcWlKuxyPj1cFSFnV47J7= C51OaQ9z5Ku2VEfMXiL5H/wBpL9/nkCYqVN4rJ4g7K37Z8G/Gak3RSpsbfT08twmgNFQXCvCNTX= yBkEf2CvEuY/txU9ETSALWgdLf6kAz8eeK/hLVbbqX3hs1J46COZaqroqQss9mnVg4raLy8OKMO= Ot0TmlbLc05xFfFwe8WXj/ygxWmpc7yKh1DuwcaEXIcNyOwgqqK7PYxrH2eDXh8sYlhXnvX1mUx= REV7WSOmFlgNFggtjrDs03xpbXVHNkmc7V1/i1HBH6sllc5ZSBDKzt3RYnSmtWdzk/wGQJI+Rey= RtcqonX5syL7tcndFT3aqd0VF9l9lT5L7f0/n6+iYsolGoSSQQjE7MSaeSVGp27dmpI5yN9vbsn= 3e3V95/hb2/W3aWstO4K60WyeVpXtjUkVa0AZuoxUlU88TpEOVj+0RVEiqAXkkbGarT/EdfqO1x= 0lxstFdLhFEscdxFTJSiYqoUTVVMkUivISOqTyZIEYnIWMHhlrxAvG/gvKy51Jw1IPHHOjnr8g3= gcHPWGfCytdGQHruqNjjOEfMxfTflNsMMTC31Fpq9kii3DFpSiijiSDTiSDDDJpSiyypnzkkkzv= dLPPPNK58ks00j3SSSPc5z3qrnKqqqr6P1/T8v19/w6kdxl4o7q5bZ6JgWnsVKtZEmgW/yUyKYX= FMSr5ZER9nkVwsboRYmMR74BIvWsj3MWEAMqRfJ1ufbW09m+FlgqBRCnt1FDH591vFxmjNTVGME= ebWVThAccrDTxqkSs3TBCHfnUu4Nz7q8R73A1YZ7hWTP5NutdDE3kU4cr/lUlMpY88GSV3d3x1T= SkKOnC8cePGx+Ue2cY1DrGqlPvL8pjj7B8ciVeN0UL2La5HeEo1WCVlaO9ZHuevqEkOgAEZMcUN= DI/1xf47YPxY0thmmMBGRlTjIHmsLOSNrDskyIzyTXmR2jkVVkOtTUfKqK5WCjNGBHSMUWCJmnO= DPBTVvCPWseL4lDDfZ1ewik7D2KaJFHcZRZxMd2GGREe6sxyvkdI2opopXMharyipCLAgkqWciJ= /s9k+/29vx/R1xL4z+LUviFco7damkg2ta5WekRwySXOqA6DcaiPOEQIzpRwsS0UUjyPiSVkj69= 8IvDBNjUMlxugjm3JcolWoZSHS205Kv9ggf+py3SaqUDpeRAiZjRWfnqk/x+f4P6z/1ua5/pvOr= sOqT/AB+f4P8As0/729cr3+753nf+b5/o60pF/MT/AJDW6F7j5j9dQb+jU/8AZXKz/wB4av8A/w= BbL+mJ+SmW1GB8fd2ZlfTRQU+Naqz24sJJVYjPQCxmylWNEerWvkncjYYou/mllkZExFc9EVBTh= h4iO++CUGeD6UC14azYstHNf/l1jtteujfj7LCMFK5a3IaFBmuSyIUhJUJWRUiVix+VyP2Fyo8W= vmNy7wCfVexMjxHG8Aspx5r/ABrXGNz47BlKhkRFhQX51hbXtuWAMXDES2rgsBa2cmKCcsQiUYZ= 0P0SQu8pYY6SV5z6ALzj1+7v8NMduRz/b8O/1xnpPhbUZuReINxYCAY90w+0qu7mbE1XK0KhHMu= z5HduypHEGCQ96/JGNc5e6d06lRzG/hvbD27f3Umi/b/4muv09Tb8A7gdnIOwTeZW0MaOxvHabH= bLHtMg3YUwNjkNxksHwd3mogxLY52UdZjzzaauJlh9G3JvySA5FbUudLCTmN7+N7YfxpNFf/k11= 1Z1hpXAIwI8Z+OeRqB3Ge3rr2+Pdmd1lPiD5Dix07/q3X2udb4zQwPcrR4B7ql/LQ2dE7+Vsk9l= lBDZpkarnMHhY5XNijRrYei+AHE/TmqsLwCu0drHI5KHH6sSyyjJ8Ix69yLJ7hgUKWeQW9nagmF= zGWpvrGPi9b4YVJWiiRQiwxRNX3+kGcPc7TauP8uMOx2wvMGvcOqMO2WVVCzmyYvkWMzmQU95cM= ha941Rc0RVfVxnK34UUyk9IqWKQ8Ns3TdGfSI9s601diOBbG0HQbVyPEqWvx52dw7EsMQNyAKoF= iAAOu6t+I5RDJeSiwRraWApo8FgWshbQBnyvatLIzxReV2AwwHBzgevHr3B4x31PoO3r8/v/AG1= Gnh5W11N439RUVAIlZVVXKze9dW1oA8QgNeAEuyxhAghYGRwDCijxRwDjwsZFDFGyONjWNaieXO= /+Gluv9f2lv/swbroXh1Z+7a3i56l2g+rbRv2PvXZudvpWGLYtqH5bSZ7fOrWnuGDca0Fx6jIWo= gqkJEkqjwq/029+53p/fpLr3T/2/aW9vfv/AIvBvzfr93VxB6sHv9nYHPvyO+noPmf/AJ0wt44u= G4h+5/bpy38lsc/KtLjVkSZN9SVq5Akf7I2Kien9c/DfWPk+E/sbyfE+X4f957en9nqGn0dzX2B= 5fxu3mZlmE4lk5Yu8GjDF5DjlPckjjrgmLy/DwT2IZMsUPqSPk9KN7Y/O9z/L5nKq2P8AjIYNke= wPDu35T4rVl3FtXC4flT68KF05T6nFM4x2/vZ44md3v+BpgTjpGsa56xjPRqKvSvHhn+K2V4feJ= bIwK005+ynjed5LX5cJKFmSYdbUd0NVx0x7JXT45kY9mCcGJWrHF5K+cKcWZ/qlNKRkFCBmp2Vc= luvgZ5xhexJzqNMz+JNz3438IKDCKPPdTU+5s/vQSiMB1igOODh0+PhLABPb2VpbVNzHi9I+aFl= fXoBSmz2M4ko4wqQAEzjUl3fjs6TyOosqG78M3UVhUW4RNdYBTbBx9GECFROhnieseiEkZ5o3qi= Pjex7F7Pjejmo5NdePFR5tnuyeNnKR2OWYOuNucbcBhrZle6xAx3JXl3+YHYwXYxwQxIUlbltdO= NPKMElp6RkgsHcQhsWyde+N7xvw3BcQxMrw5dfTFY5jlNSFT1mTYgPXkk1leOGQYIMbqgsuCEyW= F5TYCTDCIvVWOYwp7VIklIx5at0Fy3LYk6cEFRjGQeP+P3+umof+CTaen4nGnVp4ZKmrvK/cozq= z4p5SxVC6tzW2DrJyvJAprRSK+vd60kMaSzCRzLCx3ZG5zYX8OeN/Hn13/v3jHWK8Gq2gv/FT1H= fChMrBbs7e1wNWsc1zK4ey1RscyEFr44oY3NFjnbA10cUTFbH9mNjezUy2wk/v5438ejXiff8A5= 94x+b+v83Vh/mv/AOufj6j19dNPZdHR0dfDpo6Ojo6aaOvisa4G2CKrbMMU+vOHmEOBNHhLDMGI= Ysc45I07HwzwzRucyWKVj2SMcrXNVqqi/b0dBwQwJDKQVIOCCDkEEcgggHI1DKrKVYBlYEMpAII= PBBB4II7jVDnKvwJNE7buLHM9DZKTojJLKaYs7F2163+tiipVkke+uqfiBbPFFnnej5Ias4ylGi= RIa+gEZ7LWYV9H75cxHugF2DpMsBHqjbBbvKoFVnde0jhXYq6Vq9vdWIrlT5Iq9unFe3v37r+j7= vv+f8/R2/Oqfr+fv+v8nW3rJ46+Jdiokt8F9FbTRKEh/wAVpYK+eJAAoUVMqfaJAoA6TNLKVACr= heNarvHgv4fXmrkrJrO1HNKxeYW2plo4ZGOOomnjJgQt/UYo4yTyfitboT6PZitXYgXXI3cZmVD= DujnIwrWgElDXmvjkbJ8Mfl1w2e0eDMiLEVFWU1UarXOcPbDva16MA6j0tq3ROHgYFqPB6DA8Vr= uyw1VEG2D15vIyN5tkZI6U+2sp2xs+Js7Mos8lyI4giRUTttHyp7/P37+/t9/z9u3b/Z1z15LdW= /8Ad+9JFbcd7qq6GNuqGiXopaCFh2aOiplip/MAyPNZGlIJBcjXp9s7F2rtFXFis9NSTSKVlrGL= 1NbKpwSr1dQ0k3QSATGrLHn+jIyTo6Ojrx2Ma9aAB20ddKz3W2vtqULsW2ZhGJ7Bxh5Q578dzTH= qrJqV5wfqfCGOrLkUwJSRvVk9CdYVli87/I5vmd37r0dNTqLn7R/hn/oo8dP/AKM69/5f6ytLw8= 4nY3ZC3OPcZ9C0dsDKycKzqtSYGAeJPG5HxzDFjUUc8ErHIjmSRPY9jkRyL3ROpHdHU5PvP4nTX= rjijhjbDDGyKJjUZHHGxrI42InZrWMYjWta1E7I1ERET2TsnWkbjjHxzyHNH7IvtEaguthvtAbt= +dWuucSPy51xWKOtbarkRVTLbLYV/wAIIgRilqQN8MP6MjPRj8u8ujqBx2J/E/X18NNQB55c+NS= 8FcZwe121hmYZpVbGtbehBCxMOiPWKWpChMJWzgvbOthUeWKdrI0jWdXPRyPY1ERVpKtfFp8JOx= lNsS/D6DtLMj1p3zHaS0SspRTkc9XEFyHSyeaWT3fM9JHorlcqPX5sZb64r8f+T9fQVe+tZ0uya= /FjTLDHxbom3GjrDT4WDFkQLUWNc9z54I2RuSZ0rUa1PK1qqqrGn9yU8Of/AEV8EX9NlmX9H5Td= l/lRerFMQHtK5bnlW6Qe2BwM9u/Pu92mlgPB815e8gfE3rNyYthkGK69wPItm7ayACkDYLjeF1+= S1eV1+G4fXOHgHBgRlxkNdX1tdBHC59PVWJA0DIQpPTcjvOMXHPJ8yk2LkmiNP3+fynhWsmbXOu= MSssrfZ1qQNr7B+QGVM1q40FowyCEqV6wyDwei9npM7ZvUOitO6Bxr8j9L62xDWmNun+KnrMSpQ= 6phxisSNTbQiGP4y2OWNrY1OsiCi3Ma1izK1qIm2OkknWwYZGF6Rzzjvye559+mvCSOOWN8UrGS= xSMVkkcjWvY9jk7OY9jkVrmuRVRWqnZUXsqduo12XDDiJcGk2Vrxf4/WNgZNIQWcbp/ASSyZ5nr= JLNPPJQrJNNJI5z3ySOc97nOVyqqqvUl+jrDJHYkaa6Vc631/kWHw6+yDCMSvMFHACq4MNt8dqb= HFoaytiigr6+OhMEmrGBAwwQwiDMGSEeOGJkLGNY1E0j+0f4Z/6KPHRf8A5M69/wCX+pR9HTJHY= kffprQuF8WeNOt8kAzHXfH/AEzguW1TS2VmT4jrPDsev69h4ZFcc0K3qqgQ4VpgBZQRTYZ2IQIR= MPKj4ZXsd7iOMPHEvNk2WVobTxOxm3g+TJns+t8RlzBMjEIiLFvkyN9S63S4GJghngsvjPjIpoo= 5WTNexqpvTo6ZOc5OcYzk9voaaE9kRPw6Ojo6jTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dN= NHR0dHTTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dNNf/Z" wid= th=3D"222" height=3D"97" alt=3D"Logo_cicncia_digital CON ISS1.jpg" style=3D= "margin-top:10.32pt; margin-left:225.7pt; position:absolute" /></span><span= > </span></p><p style=3D"margin-bottom:0pt; text-align:justify; line-h= eight:150%"><span> </span></p><p style=3D"margin-bottom:0pt; line-heig= ht:150%"><span> </span></p><p style=3D"margin-bottom:0pt; line-height:= 150%"><span> </span></p><p style=3D"margin-bottom:0pt; line-height:150= %"><span style=3D"height:0pt; display:block; position:absolute; z-index:-1"= ><img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAkkAAACICAYAAADz= q38MAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzsvXmYHVd= 9p/+e2u6+9b63Wr2oW7ss2bItyZYXGTBgGwzYhoCTCeQ3SYZhBhIgPM8EsufJDDHhlzCEJRPMEo= wNAwYbY2wsL/ImS9a+tKTe9+57u+++1HLmj9vdkqyWLMs2CVDv8+jpq1t1q05VnarzOd+tRCKRk= Li4uLi4uLi4uJyFdr4FQgiEEL/Mtri4uLi4uLi4/NKQUiLl+W1F54gkIQSqqmIYBqqqoijKm9pA= FxcXFxcXF5dfNlJKLMuiVCph2/aSYukskSSEQNd1vF4vqqr+0hrq4uLi4uLi4vLLRlVVdF0nn89= jmuY5Qkl55cquQHJxcXFxcXH5TUFRlPNqn0WRJIRA0zTXvebi4uLi4uLyG4WiKGiadk4s9lkiSV= VVN1jbxcXFxcXF5TeKBUPRK1FeuZKLi4vLmUgpyeZK5Ir2q65bLJRI5y3eqLoiUkI2VyRfevV9u= 7i4uLwelsrqd31rLi4uF8RxbJ7a3cfzJ5PYjlxMmT0zwFFKiSMlvQcG+dHeaWzKAseRkoXV5Cs/= L2x//rdnCquF7TuOw0v7hjg2kceRp7+Xr1jvzG2f9f3iF2e3xcXFxeViOG+dJBcXFxcAJBRLNor= tMDebpj9exCpaCE2jqyWCT4P+4TniOYd0PE/B56NYNBkbSzKRLBGO+FjRFGZkOIHj9VEX1hiczN= JSFyKTytE/lUcKQWtjhLqwwXQ8zcBkHkVX6W6J0lgfRfOppDN5+kZSZEoOdTUhWiq9DI7MkjElm= bxFbU2Y9toA+Wyeo0NJSlLQWh+mJmwwMZliKF5E01W6WmNUBHVcu7mLi8uroX7qU5/6HJxO/3cz= 21xcXM5EOg69A3H0QBA1m+RfnxilpTbAyVPTzKJSiCd5/MgsdREPB07OoIaC+M0cvzgYpyLs4dC= xCUzDi17M8uMXx8mkMvROmyyr0nlw5yDBiI+5eJI9/RnqQioPPTeM1+9hYjTBWF4wNTxJEoOBEx= P0z1kEdMljL45QUxPi+Rf7OJ6wCasOP983TU9bmMeePMm0qWI4Fs8cniHsFdz/5BBVFX7i00lyi= kFLpQ83usDFxeVMHMc5pwyA625zcXG5eCQ0NFWxbW0969rCTCbyHOibZePqRraur+fqrgiOZXPg= xAyZos30XIF80WbPyTla2mppCTg8cTTF1rW1xIJetl3WQEPMQBGCmXiW8bFZfLEw16yv55btHWx= aFkYAuVye3skiW9Y1cM2GJrpjKkcmMmi6xhWr69myphaftJhM5nj2+ByFvMlMusTcTIqJZAlN2v= SOpAhEgyyr8v57n0UXF5dfEVx3m4uLy2vC61VRVYGmKoCD7YCqCBRFwWPMW6IVhY7WCja0hVFW1= uDzGahCUiza2KZFvuSQTKT50a4hViyvwO8z8GhFHFuiKAqKEFi2xamx7HwsEoBAU5Ryqq6qULQl= iiLw6CqapqAqAseRGF6DjT1VRH0aV61tIOBRWF4bIpPJs+fIBKemi/zuW5bj01xTkouLy4VxLUk= uLi6XjKZqdDcGeerlUQbGZnl4zzSKptJeH6B/NAlS8vL+QZ4+PseJ3nGmHA/vubKGZ14eY2g0SV= pqXN5dRWEuS6rkEK0OMTGS4MRYmiee66dvtogAAn4fdQHJi8en6RuaYVdfiu66AMordE7A76M1L= Dg+nscqlnjo6T4O98X5l5+dwggF6KjzUTSdf5dz5eLi8quHG5Pk4uLyKkhMy6EyFiDqV9G9Hloq= fTjSwev3sraripBT4pmjs3Qvr2BZQ5QNXVUEpMXzR2cIVEbZsa6aE8MpLt/QTE9rFKtYor65kgr= F5IXeBPVNFXTUBehoqWR5lc4Lh6fQImHevqkeTUB1dZh1nZVMjM9xcDjLW67tpKchgGVLqqtChL= 0qpi1pa4qxsTPG0GCcI2M5Nq1tYmNXJa0RlV0HJskqXm7b2kzM5xrRXVxczmapmCSRSCQklKtN+= v1+dF3/d2ugi4uLi4uLi8u/B5Zlkc1mcZzT1mbX3ebi4uLi4uLisgSuSHJxcXFxcXFxWQJXJLm4= uLi4uLi4LIErklxcXFxcXFxclsAVSS4uLi4uLi4uS+CKJBcXFxcXFxeXJXBFkouLi4uLi4vLErg= iycXFxcXFxcVlCVyR5OLi4uLi4uKyBK5IcnFxcXFxcXFZgot6gZFlOwyOp5hKZM96p4mLi4uLi4= uLy68CqqqwvDFKVdSHEOLVf8BFiiQA04ZcCSQXt2EXFxcXFxcXl/8oqDY4UsBr0DHuC25dXFxcX= FxcfuNxX3Dr4uLi4uLi4nKRuCLJxcXFxcXFxWUJXJHk4uLi4uLi4rIErkhycXFxcXFxcVkCVyS5= uLi4uLi4uCyBK5JcXFxcXFxcXJbAFUkuLi4uLi4uLktw0cUkXVxcXFxcXH4zkRIsR2JaEgToqkB= TBBdZuPpXFlckubi4uLi4uJwX25GMJixeOFVkOG6hqYLOOp0NrQbVYRVV+fVVSq5IcnFxcXFxcV= lESonjnH5P68CMxZcfT9M7blIwy9Wog16Vq7u8fHBLgOqwetHvQvtVwxVJLi4uLi4uLti2QzyeZ= e+eYV5+eZTkXIHK2jDDgTZOJjVMW9Jdr5MpOIzN2Tx5NM+KOo2b1vox3gA1IaVc/LvwGUAIcZYI= +2UKMlckubi4uLi4/IaTyRR44P793PuNF5mYSGFZDiDRY1FqrqtEj8aoi6hc2eFhMmlRsErMZiX= PnSyyfaUPXX198UmO45BOpTh6+CB7dr/IQP8pcpkMmq5TU1fP6jXrWL9xEw2NTWia9ksTSm+ySJ= JnfP71NMW5uLi4uPzHQEoJUiJtpxxpLARCESCU8l+Xc5BSkkjk+MI9T/KD7++jWLSoqAjQ0VFFO= OIhKX3M+j0IRXDDSi8blnnIFHQkgiePFckWHKR89f1caP/FYpEXnn2G7//bNymmZ+jpbOOaDZ2E= wmHMUomxsVF2/fR+HvjW19ly3U289/0fIhqLoarqG3cizsMbLJIk2CWwMkgzBcUpsAugBRDeWtD= CoPlB0fiPIZoWrux/hLb8+uM4zjlm06WRnO+aLJhhL247Li4uvxE4Dk6phDWVIndgkMLxEZy5LH= g0jGW1+Ncuw1hWgxrwIVS38s2Z5PMm37vvZR5+6BBCwB13Xsbdd19BU3MUTVOZSdv8r4fTHBkt8= e3nssxkHUYTFodHLRRF0FFnXJIVybIscrksxUKBh3/0A/Y9/xRvv+l6Nm65nkC0itn4DNn0HMFQ= mK0V1UjHZujEQR747rf4m8/+CR/+w/9GXX0DHq8Xr9f7po0HIpFISABFUfD7/ei6/tq3IiXSLkB= +GDnzLHLiIcgNgZkHHBAqGGEIdiLq346o2AyeWoR6Cft6PUhZbo9TAmsOzAQYtWBU8usglKSUpF= IpZmdnicVihEIhFGWJB4KUOIUMdimHEqxEUc4NupNSEo/HSSaT1NfX4/f7z1n+WjqlZVmcPHmSV= CrF+vXrMQzjnHUcx8ZMTmHm0niqW9B0z1n7kFKSTCbZt28fPT091NTULC6XjlOWVkIs+rKXPHYX= F5dfH6TEKWaR48exxscZ++IB5h7ai5Mtnn4O6CqergYa/+pDGC21GMtqUMI+FEX9dXjsvy6klPT= 2TvHx//Z/6e+P88EPXs4ffnQboZBvUfRYtuSn+/N8Z1eaeNZGV8qnzZKCxgqNj781Qnej/poy3K= SU7H3pRf7vd7+JpghUafLe93+Q9pUbcBAc278bO58i4teQdhFfuJJY80o8/hCFzBzf/8aXOHh8A= H8wxOr1m9hx8zuJRmOv+3xYlkU2m8VxnMXv1E996lOfg/Lgouv6azdfSYkszSInf4bsvQdGfwS5= cbAKIC2QNjgWmFnIDkHiBWT6GBgx8NYhFJU3vadKCbIE5hSkD0D8EZi8D2YfAV8neJr5dSj2IKV= kfHycb37zm+i6Tmtr61lCYcEKIx2bzIGfMvr4vaQiHURjlUuKpBMnTvDXf/3XrFq1ipqamsVltm= VRmJpG6Bp2voCZTqN4PIgLiBLHcejr6+OrX/0q119/PV6v96xl2WwWBcnUSw9x9BcPoNT1EI5Wn= NOuXC7HF7/4Raqrq2lra1tcXkpniL98EEc6pE/2Ucpk8VbEyj3r1+Da/qZhWRazc0nGJqaJz87i= 2Da6pi32Z9eK6IJ0cNIzWM9+B/Nn/wC6iu/m95A/PkJpeBqccj0frbGC2k/ejndlK3P/9hTW5Bx= aRQg15D2vVcmyLCzL+rW3WJumzUM/OczPHz1GZ1cNf/zJ66mpCZ11zIoiaK5QCXgUciVIpork0l= laY4K7t0dZ3Wyga8prGsVt2+ZrX/oiXc2VvO3W27n62htpXL4CFI3BU8eZGRuko3k5FTVtBMO15= KbHScQn8UWr8QcjdK3ewKqV3VRHg+x6aied3WuoqKx63dfKcRxM0zwraPz1udukRJYSyKHvIAe/= jSwkODMOackGmxmYfg6ZG0G0/39Q/3ZQPa+rGedvnwNWCvKnYG4npPdDYQSsJEgTjCrAfnP2/e+= AoihEo1E0TSOfz591oaWUZDIZxsfHWdbaAr4Y+4dnaZ5JsKz93G0JIairqyObzVIoFM7ajplM0f= vXn8dbX4dTKIKm0vGx/4weDp+3k6qqSjQaPS3UzmhbOp3mySef5KYdNxLp3kJYqSAcrVjc35nWI= b/fj9/vPysLAikpzMxw6rvfw9vQQHF0HH9FDcaH34+3qgLV43nNN88rMyverN+4nE05PmKWJ1/c= T+94jtlUGseRRIMellX5Wb+6k2ShxLqOVvw+n3uef1OREpmdw/r5P2K+/BNkLonaeTW+1a20fPE= /M/yJr5F+/ABabYSGv/wg0VuuxJyYwy6UyO3rw55JEbn9KjzL6xDauYYBIQSZTAYpJdFodN54IM= HMlSddqhfEr76lulSy2bNnhGLRZtu2diqrAkveUz5D4S3r/FzWavCFLx3m0V8c4fId7aysrcGrv= zaBBJSvn2Vy+bYbaF91GWL+XGazGfpP9hLVNAov7CUvwclmKSRniC+vJ1jfji8QxBeM0Nq1lora= RvYfOIjj2IsxaG80r0skSSuLHH8EOfANZCmFaTt872mHvCm5ZbNCTUQ95+RJAL0CQqtwxn+G8NY= jKjZf0ApxaW0zsU+8gJj8GsJ7CoVsWRidP9zl4rYrwXEkRUti2mCoYGgCVX1jL47tlDMLFEVBvI= YGK4qyONuWUpLP5xeXHTp0iAMHDnDHHXfgbdvIdX/QhREIY9s2pmmiKAqapmFZFoVCYXEmJaVcn= FmpqkohmUSvrSa4fg1OsUTi2Rfo//q9hFf1UH3tVrQzrERnsnDzFQoFJicnSSaTRCIRfv7zn7N/= /z4a6uoI6Q7+cIyBwQEC8QT9/f0sX76ciooKjh49SqFQIJPJUCqVGBsbY3R0lGg0Simdwdqxndo= VXczOxJk7eozdn/ofNNz8Fjre9y7Ui3QjS8fBnj/WZCqFpusEAgE85xFaC4KvWCySSaexLZuKWA= xVVVB03R3EXwOO4zA5HefffvosLx0d5dDhY9h4kAg8SonOjhYef+kQl3U2sHZ58y+tXRJwpMRyy= n9NB7I25EyLpCWYNWGyIEmUbFaENbZWavg097q/mUjHxnzuO5gv/RBZyMw/1gWKquLtaqb5nt9j= 7C+/Q+StlxN952a0oA9rIln+rWVTGJpG/Hg3sQ9ci1YbPec+VVWVSCRCPB5nYGCAuro6fD4fiqJ= BfH85fCS0DBTPr7Sl2rYcshkTIQS1tSG0JQQjlA/RownqYyqNIRszESeXqAbbvrTDFyAUBVU3EE= I5ayKciCcg5GPFtm3oPh8CyM5O0rfvJWzbQjA/lgiBoqio6nym25t0GS5dJEkbsn3IwXuhlAIps= R344YsOiSxsWy2oiSzxO6FD1dWI7j+G+C7kwDcQoR4wIm9sZ7MczCePUfjuAGqrxFivonfbKBG7= rFq1MIQ3gFF30SfXkZBIOzx+yOTpXpu5rCTsE1zbo/L2DQZB7xvT/pJt8ouR5yhYRd627Bo8l2B= pcxyH/fv309/fj6qqTE1NcezYMRKJBOFQkGhmmAgZHh9XCUcrmJ2dxTRN3v/+97Nz585FkZROp5= mZmeF73/seqqqSz+epq6nh0elR3uHZiBEMM9KznOV9w8x99RtUbrnygvFKUkoOHz7M008/zW233= cZnP/tZbrnlVnxeH9FIiPFdP8DOzPClJ/q45oYdrFmzhs9+9rOsWrWK6upq1q1bR39/P9PT09xz= zz18+MMfZt++fWQyGXbv3s0HKz7Iid4TbNu6BVFZjXaRAX0LFim7VCI7HcexLEQhT8l2yBo6/oo= YFRUV57gvbdsmPhOnNJdEtx1UVSFn2SiqQrCudvFm/lV+kP6ySGey/PDxF3js+SP0jaVBiyHnpw= hF4WVieoZoxM+Ro31MTk3StqwN+CVY7aSkN+XwtydMhrIl4iZkpEquZGHlTXxFm0C2iANsWl3Bu= oiKV3stU5uLawNcwhzvVc6NlJJ8Ikd2Ood05mfiUuKrDhKo9JKdzJI4mcAT9eGt8BKuDyJsC6e/= D+KzoHugrY2i1MlM50AR+Cv9+Ct8KIpSnkAkC8wNpansiqGdUUzHNi1KGRNvzDvf1ItzbUkpsfv= 3Yj35L8hC5txDVgS+9gaWfemjCENDMZaYIDkOhVPjZJ45QuQdl4Pn3AmNoihUVVWh6zonT56kqq= qK2poa1Mr1iPgeGNoH9TeCp/JX9v4WCmhaWaDkcqWzCkiej2ymhHQkuq6gXHLG4HzW4Sus716PF= 4/fz/jUJCfGBuhYtR5D15keH2A6U8AXCJ1jUHkdiXUXxaWJJCnLVqSxHyOzg/Oz6XJjpRQ4jizf= yFIiEYs3XnkNC1JHkOOPwPQzMPsCcmonNN3ymiwmF4UNZATWYR3zmAdRpSOuq0S7ZSueuhtR/U0= oiuei9islxNMOX3uiyIkJh+tWarRUKQzN2DxxxKK9RmVT+xuTLOhIhyOJPjKlLDtatuC5hCzHYr= HID37wA9avX093dzdf/epX+cAHPsDIyAg7dtzEwfu/QKUzTmouyGwyzR/90R9x77338vd///cMD= g7yk5/8hIMHD3Lffffx2GOPEQ6H+Z3f+R2eeuopDh4+jD8U4pldu1i9ejXbb34bQdPi1D3/iGNa= 523Tgniqr69nw4YN9PX1MTg4iKIIvD4vfr+PsZEB2mtDRKMRbr31VkKhEPl8nqeeeorf+73fY8W= KFdTV1XHw4EFeeuklenp6SCaThMNhrrnmGu655x4+85nPsKx9OXOmSe//+Tah9jYi7W0XFG7W3C= y5U6eQloUjQTV0fIaB8PgwTZPswBBj6TS1jY1o81apUrHIaP8AnnSWYCiApoEs5HAySWyzRHp0C= NXnw9u6DC281Izh15OyeHTOCKAXiw/fMx+qC8GRmqaVY9aGx3n5xCST8RzLGqpRhCBbLBEN+FAU= B0OH/sFRIp1t7N13mJbmFhRFKW9nfiYq5rd3puXdsmzkvNxa6IOKoqBeZJaTNG3kqVn8D4+ypm+= WpniahkSOqkSeilSBUL6Er2RxoL2K7//5WzEdH7ZlMZdMEo1E0LSlnwvlqsbljE/btkmlUsRisX= PEgjRtrB+dwprIImIG2tZGlKgP64kh7LEsQoC2oQZ7IIV6XRNKyMB6chR8Kvq1zRcUHgLAsTn2r= X0Uhc7K27tJD8wwfiJF+xXVHHvwJC3bW3HSBYafTtD97g40VWAnp1A++jG44VbEH38MRYW9//t5= pMfPlk9eddY+naJFZjJPfjqDmSshPCrYoCgaQnHIpUx0j0rTlmb8Ue8F9YaUEmmXcMYPILq3s/B= olIBoXosU809zVUEN+s74ISghH/5N7UjzdIhFyXLIZEqEPOcKqYVjiEaj6LpOb28vs7OztLa24q= /YhOqJwan/A3U3QHQ1qEY5xMN5RQiHUEBRWJS30in/E+rpTirl6e9PN+D0Oo599rLF7b6+FHjD0= OjorGLXrj727hnmtnetwe8/N6mm3ERJOl3g0MExhBC0tVXi9V168pUQAumcfUyqprF9x9v42v//= ecYfeYRjR45QKpmMDA/ztne9h/ArgrMXZYUQvFmmpEsf1Ysz2JM7SWctJuYk8TRUhcsvwAPK4kg= NgrcOAq3lUgDpY1Cag/wYDNwLZhKsHHL0AUTD29742CRNxQkFsGJhiptWUbxsJVZNBbKgIgem0f= QsNfWtRCPnmltfiWXDruMWgzMOn7jZYEWDhqqAIzVu2yTxe053dlksIouFclC6z4dYCIZ3CmDn5= 33aAVB0pBSUrLL7ThGgKgLzTDUvwSkWkIUCQlURPj8oyqu21zAM3ve+93Ho0CHuv/9+UqkUUpbd= d8lkksOH9rPisho0TWPNmvVEo1GCwSDDw8OUSiV0XaeiogJN0zh8+DCtra3s2rULgLVr19LY2Mg= nPvEJVq1aRSwWQ0NgZguc/MKX6P6Tjy/pclswqfb19XHo0CG2bt16+jgch8mJCUb6T9JZtfKs7I= KFQcRxHBzHwbZtSqUSnZ2d3HnnnSiKQj6fp6+vD8MweGLnTnq6u5EIrHwJ2zRf1V8tpSTY3YPwe= MoPWsfGKRRxigWU2TnUrE1+cpq4bRNrbMQxLWYHh4hkMuiGiu4xUCNhFK8PYRjl+ixInHz+rNnS= bwKFQpEnnt2DY1skklmu2riKwaERphIpljXXY5klKmIxTpwaQNc1Nm9cTzDo58TgOP0DwxQtwfR= cClVRsW0Hp5jCLmUoKTHypsHI8CgvedNcu/UqxqZmONU3QFVVFSf6hgn4fFy3ZSMTM7M01lWDgK= d3vYQQEAoFOHpykMpYmCs3rqO1ueGiElXkYIq2fWP8nZal8OhBcCQyWYJieWZYvtIQTpsUshZ5G= +KJBH/xuc/x2T/7M6qqqhb7/pllMHK5HC8+/wJr1q0lPhPnf3/pS/zV3/w1Pp9vUWAKANPB/MeX= KQzPofh1tJYw3r/YivnlA1jxHPqyKHZYp/TlAxhhHbGyktI/7EG9rQP9muYLjx1CoHsNNK+GJXS= MsE79llYKc0WKc3nmTsWJ9VRTv7ISPehFUQRCUVEiUVAVFH8A4fWg6RqaoWJpCobvtFVGIFB9Ot= 6YilA1vNWn48iEULBLJopXR1EF0rKxLRtVUy9smMn1ogZ2ot7ypwh/Kwh18dw6QkXMn2M4O6ZRr= QkTuXMbqqqVM2WLNl97OY6vP89/iflRlXOtkgv/DwQCrFy5kr6+Po4cOUJzczOVlcswWt6LGH4A= jAoItmJPPYcTf6nsMSm3ACXag1J1JUL3I6WDM3cYJ/4yatPNKPNWKGmXsMd+hswOL1x1hL8BpfY= ahBFBzuzGntoFim9+sUCpuRoltgqhXPowbhgaN9zYxcMPHWHXrn72vDTM9us68XjOLtZYDimweP= CHBzl0aJxI1MfmK1vxei993wJBKZ8hn4ov7sNxJCqSu3/3IxzYs5uTJ44TjcZ4z113UdfQRCEzS= xGxOMEpZpLYVumS23AxXNIRSsDJDROPT3Hvz23u3yWxbIgGYC4rCfqVcqdpvxul+fZ5v62KzPYj= j/5P0COInk8iJ38Bx/8OsqegMAWBNzDOQFVgw2qKzZXk66IUFEG+UGBuJsHY5DRHe/vJ5Ir8zgc= /xIZ10Qsfr5TkS5InjlisblZpr9VQlPKxZgrlh1kyJwnokmB2itKunVhHDoKu49l6HZ5NV4CYQ8= YfRs4+Ve58lW+FyneSKgV44aTF7j4bjyaoCgkqQva8VU5ix6fJv/Ai5oG9CK8P746bMdasA+38C= n6hFMBXvvIV3vOe99De3s4TTzwxv8xhdHSUydEhxNoI6czZ5mpVVRfdSKZpYts24XCYdevW8a53= vQtFURgdHSWdTnPFFVfw6KOPcvnll1MXjaEoCpH1a1CWGHgcx6FYLC6ari3LolQqEYlEkFJSKJY= YGBgkl8szMTmFaalks1lUVcXv97N8+XImJyc5deoUpVKJ7u5uent7mZycxLIsDh06hK7rfOYzn+= GTn/oUl69bR30iTfNbryfavvy8MW8Lg5EaCJZFqKqiCAFSRegGajCIXlmFtCy8mTSFqWkSp/pQg= UjAh7etFcXnK88UlxBiitcHzBe4O8/1upDgXRwsf4XM+Y6U9A+OIByTwdFJDh4+zqa17YyOTrLz= 2d1ctqqD0YkEK9oaMG2Fb3//J/z2nbcwk0iRyeXRVQ+RoAe/38v0+BjJ2TimWg2aRKKQzmSYzfi= YmJpk74ETjE9MUZdM89iTz+PzecikE7x8dIDN63somDYzUxPsuHYLg6PjPPLY01y3eQ25Fe1nBd= pfEAVKX92Pcm0jnrtXYj4+CJoKaQtnLAtJE2yJt2jh5EwKliRgO+SyuUWxb9s2U1NTjAwP4zgOy= 9vbGR8b42tf+Wd+6+67WblqFe9573sQQtDb24t0JLOzszQ2NlAfK2eWaje1YFzVhPXF/cjZIiig= 3tmJcdcqhALmg6dwTs7iRD2QLqGtrrwoL5CYn4WbmRLDTw3ScsNyqpZXUJzLE6r2cfBf9jDaVU3= 3u7rn+/dCn4T56fDCuD3/3Rk7FWAEPehelexMEd2rYRdNhKZi5Sxs20GYYJVMpO1QsaKKYLWf8y= s7Ccm9yOmfQzEBPX+DCPVg2ZKhoaH5uKFyXGaxWMQwDBRFwePxkE6n8fv9RGMxEgWbL++d4Yt74= 1xWH+R318YIGucXzEIIvF4v7e3tjI6OMjQ0SC41RaNvCqPyKlRvFQDO9LPI7CBq4zsABZkfwTn5= z4jQcoTWiiwlcU5+BWkVkZof2fQOUD3I0ixO37dQ2t5fDgqXFjJ5FCIrQA8h4y9Cth/R+A6EUEF= oCCN8gfN0cSiKoKOjmq3blvPgjw7yF3/+MyzLYfOVrYTDPlRVYNuSZDLPzidO8E//9Ay2Lbn11t= V0ddW87jIrAy/+mMyJJ5ESJuMp4nMZLNvBcSQuc0e/AAAgAElEQVTBgAe9aJJK9rNr6OXFCYYiF= LqW1eAxNIolk3wy/qbmx1+iDJRYmWFePpHnu085RIKC268WxFPwnSchGNAgug7RfDvSTCJHHwT/= MpSGt0PH78P4zxBaAFSjfIuZGcgPv6EiSWga+mUb0PPdjCRmOTgyQv/BU4wdPUJyegbLLgfYXuy= D0rQhU5DE/AJNLbsPdp+yeOywjQM4tmRjZYa3nLwPpf8Y3muux0klyd77VSjNoS8/CbM/RVTfBn= YROfQFTNNh9+x7eXifzeaOcpD7D1+yWNtqYzSVXTeFxx9B2/0Sniu3Yp48TubLXyDy2b9Fa2g69= 6rMZ7AVi0Xi8TgzMzP09vYSDAYJhULz8UVxjh07ipSS6bkM2awglUoxMzNDPp9fFCO/+MUvmJmZ= we/3s3LlSsbGxujt7aVQKNB7vBdHOtx1113867/+K9/77ne5ddVanEKeuhuvQyzhXpBS4vf7ufv= uu/H5fIyMjBAMBvn0pz+Nz+ejoqKCSDhE7W9/nNqKEO9PlGeAlmXxvve9D8MwSKfTzM7O8pGPfI= RoNMpVV13F5OQkXq+XWl8A1bKpC0f4yB13MPH0LtR0nvprt13QglQsFjl16hS5XA6AcDhMS0sLm= qYxMjJCPB4v9xEhiITD1NTUMHniBIViETXnpUoImpqakLbN2NgYXq8XXdcZHBzEtm2EolBVWUlD= QwNCSsxsDjXgZ3BwEFVVCYfDi7FOC0LItm0ymQyBQADLssjn8ziOQywWOyso/8xgx8V+L067lBb= Wu9Cy2dlZIpHI4v7PFGVL3RsXK9Zs28Es5Fjb3Ubf0CRHjvVTVx1l4+pO9h08htfrJZPNUbIkUx= MTZDLZcrC7nacqoNG5ciWqoiCsFIVQiJGZcsyMFAJFCCzTwiyVaG6o4WTfIAcPT5HL5dnQ00Y2l= yNgKDzx9G6aGuqQsohpmdTV1mJaJonkHOls5uJFUsiDnShS+uI+qPSgrqrA99FNqA0hzL2TFL9x= EHv/DB7LRiYLFGxnXjCcPRMfGxtjYmKCvlN97N2zh/b2dnL5PMPDw0RjMb7zrW/R2dXFP/z9PfS= s7MHj8fD4Yz/nd3/rd4hIiXMiiVUEIjoioCMdifVgH6W+NMYfbkDtjGHvm0KJeiGoozQGL+rwJK= evuREqV1aWjkTxaKy8azWxPeMMPDnIgW8d4upPXIEvMwXZfNnLcTGDpIBgfRhRmEBkMjjhKIquY= ekKQpNIS4GSg6KaaMarlISRNjJzolxeZm438tifwoo/Rfi60XWddDqNEGLRQriQzh2NRrEsC4/H= QyJn8U97pvnn/QniBZvhtEmq5FxQJC3g8Ri0tDQT8Djk4v2cTAtqmpdRrfiYvzMRVhJKY+Xnjjm= F8NYiFKNsRZp8CgLLUOtvQp74CjK2DiXcjhRqeaJVHEGoBtKRCH8d6KHT58NMIEqjCD2GqNmOMG= JvSCxUOOzl/R/YyMjwHC++OMiffe6nXL1lOavX1BMOeUkkchzYP8ru3UPMzeW54YYu3nfHBsLhp= RN0LhYpJY5ZwipkyyEPhQzZdJJC0cSRUMxpgERVVHRdJZsv4jhla1OxxofqGNimjbStNzUu6ZJt= ZXYxw+Ehh3wJ3rES3r9NIV2Ex/ZZIDQILgfVjxx5EDnwzbJlqWYb+BvBW3PGlgRIB2ml31A1aEl= 4KZ7hgf5JRjJ5ZrNQCi9HrK7CMz6IPngcXkNNKI8GsaBgMikpmhKvAauaVWqjCgVT8v3nTZKj01= gnjhJ+5614r7kBaZawBvooPvlDtEgKpfa9iPoPlW/00iiF0fs4OHkLq5oM3nmZjgAmkg65BZ95N= ot1qB8jVoHZexRnahLjsssRHu953UehUIg777wTVVW5/vrryWQy1NbWsmbNGlRV5aqrrkLXNa7d= 0E112MsfXK/g9fnwer3s2LGDQqGwmBW3du1aPv/5zxMIBNA0Ddu2iUajrKutA12nqbaOD915J7N= HjjH5nQfw6/o5PuYFVFWlra2NtrZysO2aNWuWHMgdeyNSOtQ75Yy60dFRrrzySvL5PMeOHWPt2r= VEo9FF95sQAlUIxqcTDH71mxyreoTg1DT+5W2s/MMP46uuQrlA7Ek6nea7992HqioYelmIXXXVV= Wzbto0ndj7ByZMnCYfLImLZslY2XraR+370QzRVwzAM4ok4t99+O2vXrOXRRx+lubmZ6upqvnHv= vdTV1ZbFQqnEHXfcQVtDI8n+QQLLWxkcHGRF9wr6B/rLlrRCgcrKSizLYmpqitnZWVatWkU+n2d= gYIBUKkVLS8tiAc25uTnC4TClUglFUcjlcujzmXizs7MEggGQ5ePzejyYlkU0GiWTyWAYBpqmkc= vlME0TVVUXMw0XYmNqampIp9OYpkk0EiEzX2Cttrb2VV1UQgia6yuZnraJRSJ86I7N7D98mFwmx= 4Z1q2lprEfgMDQyjkKJG6/djK5r1FVGqaiqYWR0CmX/c1Q1tuAPxqhurKamqcRA/wCJZI6qmgp8= agHDMAj4oa2pFseqIBzy0dPZRq5k0dO5nD0HjtLSWM1cOk/vyT5Wr1rJ9qs2IHDIZnMX7wX1qag= RD3avA2N5WK2grapGbY6grqzGuKYZ87lRfH/7AnqmRNY8N5h0IRZveGiY8bFRxsbHue7666mtqW= XLli0oqkomncZxHEqlEtdu305VVRX//OUvMzMzQ1hK5LE5rIE0nk9sQlSW3S5aexTtykaUmBelK= 4rz9Bh2bBplWRhxsYNY2dCJFtBpvLIJT8hg8uVxVL+G5jVou7GDSHOIA989hpWYwv6Tj8M7bkU4= AukJIhVl/lzO38+cK9x9US+ecBHn2D5AQVg2OCayUITaFsgkUFZvQAloFx73pYO0kvMubAvmnkO= e/DxzdZ/hwQd/waZNm0ilUvT29nLFFVfw7LPPsnLlSlatWsXExAR1DY385EiSrx9MMJkvW+wLtq= RgX2RnkBLVKVBVEWPO8DPdP0w8kSRWUY2xEHfkrYPIyvJxalGc9AA4FrKURJ76OqJ2OyJ5CMdM4= Yw8iOj8COgh1J6PgVMox8g6JZypp5ChToRnfrz01kGoG7QgKEvHDV0KqqqwYkUt/+Ozb+Wezz/B= 00+f4qcPH+Hxx3rRNAXLsimVbDwejTvuvIzf/fCVtLTEXqd1W54xYStX61YUlXSuhKYpOLaDpqq= EQz5y+SKpbIFwwEuuYGJaJpr6CjH9JoY0XLJIEqqHkK/six+cgukUDM1IZrMQizhgpcsrBpeDpx= qCnUgtUI5DsnOv2JgA5fWp0ldiO5LDsxl2T83ND8IK+EPgD+FU1KKv3kSDYROtqX31YxUCrwFvW= 6fxb8+a7Ok3uaJdoz6qUB2S7B2wmU477GhW0Q9JsKxy3JCigGUiF6wEsnS6toZdAsrvE7IdUOYz= GK0zYv6kEEgJ9mAf3ptvw/Offh80vRwPsEQHFUIQDocJh8Ont7FEptmC/96yLNYpymIWW1NTE9P= T0/h8Pvbv38+WLVsW44EWtqOpKvHhUY7/1efJtzThFEtopRIrPv3fCS5rRQsuXWfjzNnd+SiVSh= zv7SWZTJJOpxetLdXV1Yvt3bNnD8Vikenp6cVq4G1NTfgPHaGQiJM6fgw1EMRobMRbWYkRCl3wZ= i67FUvcdeeHaGxs5NChQzzxxBOsX78es2SyZctWtm7Zgqqqi1mCjiO59d230tHRwa5du3jkp4+w= vG052VyOYrFIqVTCMAw+8uGPAPCTh37C4SOHaa6qQc6bkqempjA8HnLZLJOTk9TW1DI8PEw6nWb= NmjWcOnVq8TqZpsnMzAw9PT3s3LmTcDhMIBDg4MGD2LZNQ0MDPp+PUqm06NI8fPgwAO3t7ezdu5= eenh76+/vRdZ1isQhAbW0tx48fp6GhgYqKCvr6+iiVyv798fFxBgcHueyyy0gmk2QyGRKJBJs3b= 6aiouKC19HrMXjrjdeQy2bxeLz4fD5qaypxHIlh6LS1tWLPu1vLZSU0AoEA3e1NLG9rYWQqzdhU= Epw+mro3EK6swTZLqNKB44eJhr10tkSoiEXp6qphTU8X+Xwey7QwPBqBQBApJRs3rF90d6maQjA= QZPmyZjLZLNFw+Lzpzq9EMTT0yiAlJssF+4/OYh+PozaEUHQF0RrBemkCPWPhy5jMlRykcbZQmp= ud5V+//i/0rFrJbe++na9/9Svz90S57MaZ97PhMQiHw/j8fjRNnw9MB/XGZhSh4ByNI69tRigCs= bEW/d0dYKgonTHsTBGeH8O4rRPh017V0iClJJ8soGgqiukweXAK8iaZWUnDxgiDT49Ts7qWUqLI= suvb8dVWIro6cKamEW2dcMNWMHTyU2l0vxfd8FKYLeL162e9K00IoFjCqmtAtS3EXArbW4GqA0U= bEQoiA95Xf7/awlix4PUz6hCNd1EseaiqquLw4cOk02muvvpqTpw4wcTEBJWVlaRSKV544QXaOz= q4oS3Ew30pHupLk3dAU0C72AFfSlA9lCyF2eQshuEhtvAOsflnuBQaQinXUZLCgFISaWVxRh9Ch= lchAstwhICa7ThTTyHSJxFaEGf8p6iNt4KiIuwizIulxUNXDIRadkXKbD/SU4PwVpXdb68TXVdp= b6/ib//uFnbvHuTnPzvOyZPT5PMWgYBO14pa3v72laxaXU8w6HkdWW2nkdKhYc12mts6EUCHlGy= 2y29OQErmsmULkzJv1Q4HAmjz4SCaVi6Nk8tmOBj/8cIWeTOCty9RJAn0YAObugxqoyWePw53f8= EmV4SiKcAxYXYfZAdQqrdA9Nswf3GdyZ2Qn0DMp1yX0w68CF/jG3hY5dNly7OLFmqaSlvIx7b6C= q6ojtAS8ODTzn0lx1JoqmDTco3+KYd/ftxk51GbxpjCxJzD/iGHa3s0rrysAUbXkLv/WzhTE9jx= aaxTJwj+148hqg4ix/8FzGmklYHZR/G1fZ71QYNv7bJwZAlHwpNHHa5aMR+4FwpjbGpD/viHOLM= J8g/9EPPwfkKf/jP0hqbzCqUL/R/KD8ajR4+SyWQWA7qTySSVlZXkcjmWLVvG5OQkzz//PFNTU6= TTaaanp+np6SEWiVB3sp+SWSS3dz+KoRPq6kQNBdErXt/sQkpJNpslFApx6tQpRkZGyjEAIyPoh= oHP58O2bXK5HLOzs4vFKdMzM9gv78MeHEWtjmFnUuR372H2yDHqrrz8VQcKx3aYicfL8SAnTuD1= lV1mtmMzPDTEvkAAXdfp7OxcHNh8Ph+hUIienh4ee+wxCoXC6XR/IJvN8uKLL2JaFkNDw7zlppt= QFwZlAXV1dazo6uLAgQMkEgka6htQFIV0Or0odBfPpRCEQiHC4XC5HlMmQygUWgysdxxn0Uo0Nj= a26FqIRCJUVlbS1NQ0797KUF1VjWEYFAoF6hvqOXL0KKZpEgwGF61ImqZRKBaJRCOEI2FGR0YX6= 2TZ9qsXX1UUBZ/Xi9fjmW++QFFOfwZA18+qug7Q0lDLllVNTM7MceBwH0OJIskXnqCirplkqoBZ= yNDYWE+wNMna1W8hGo1h6DqGrhMMBha3s+Aq9Pl8Z21fCIFhGOUMMpa+N5ZEU7Bjp2MA5VCGzMc= eI/Kj96B2VGCPpijcfww1USCQypHKmWBAoZDn4P4DxGJRUuk0k5MTvPXmt3HixAlyuTxCKFi2w8= jIKFXVVQtd46xs2zObqIQN9K0tFP/XS9hvSSJtB+t7x2H/DMZ/WoNoCIJfw+pL4umIgv7qrjCBw= FcVYP0fXLGYAQggNIGiKUTbahg6WUJpiBCIaBRRSXzgM5SmElS977cJN8RIpiSq388VH78aAaie= 8rBSfvYuZB0q0LGSqalhHCFRqxUsKfBFDLSAQWVHtOxefVXrvooSaEUKFalXIrr/ElFzI/5kDk3= TuPLKK8nlcgwMDLBhwwa6uroWn2+33HILhXyehopK/uf1jShijB/1panyKoSNi8x0FAq5fIGxsY= UMrzaCweBisUkRXQXTT+IMf2/xDCst7wU9AsJB6/kYiq9sGZJOCcffAFYO/E1loTT6wOlr461FB= JeXJ9bRlZAfxBn5HouB3bU7EJ6t5Qy4NwBFEYRCHrZv7+Saa9opFW1My0bXy+4uTVMuukzDxRKp= a6Oybe05j2jbcbj3vh+QyRfQVIWrVnZz7fLVeHXjtA6SkEnNont+MZ9az5uS4HZJIkkAarCVnuW= VfO6uPN9+0iGVhZsuEwxNQ9GUBMwTyIN/Cm0fRIR7kPYYcvTHyJEfQKgLOfU4MnmoXG8p0Aze+i= X3JaWkVCpRmi926PF45k1tF9FGIfDrKtU+D5dXR9heX0F72IdPPR3/sWApMU3zVV/LEvYJ7triY= WWTzc4jJgeHbWJ+wX+9yeCKDg1d8+Dc+SGU6lpKzz0NAT+hT/4p+ur1COcypB5DTn0fFB06v4BR= cRObohqmI9h5xMZrQE+TQFcFKyvasWUzwfWXISNVlHb+HITAf+fdqDV1r8sX7TgOg4ODbN68mae= eeopkMkkwGCSXyzE0NERVVRXJZBLTNHn55Zfp6upaPF8HX34Z37FBikOjqB4vOA7pg4dIHTpKqH= 35RTzkzo9hGKxft47UyBjFgQkanz2IdmSQ6ne/k9rrt6H6yoPq3NwcDz30EGvWrKGnp4fcqX4OD= 42gOBCoroVYjFzfEAP3PUC4qwN/5bmvNzmTfD7PA/ffTzaXJRgM8tH/8tFF0dB7qpfpmRk8Hg8V= FRXnvMNOKMqS/vB8LsfBQ4dwbJvsvItr4Q42dJ3WZcuIRqOsWLGC1tZWhoeHaW9vx+fz8dxzz1F= TU4Oqqvh8Purr6hDAM888w9q1a9E0jb6+PpYtW4bX6yUUCrFv3z48Hg8dHR0MDQ8vCiSv10tdXR= 3BYJAVXSsYHh4mGAxSX1+P1+Olo6ODcCjEoUOHFsVULpcjHAoRCjXg9/mprKxkcHCQQCBwVnHSV= +PMc34+6+KZeL0ebtq6kWQyRdDvo79/iMR0nrHRcaqqa2htaiPqzLD9qitY0bViUQRdzLbP/P41= 3zkK0OAr/y3XeEVO5ZGmjZMqkvurZzF/3IcqFMLpIkkTPF4vV1xxBc8/9xyKqtDS0sqWbdv4/ve= /z+rVq3nb22+moiLGbe9+Ny88/xzX33ADN+zYgeHxsHXbVvyBALqmsXHTJmLVlei3g6z3o1xVj3= 5nJ06hiHZzG+pAEhA4KoiYB+O3V2JMZFHWVSMV4AI1y8onBFRDI5GwGRoF05SoisCxHXQv1NWoP= LPboLrJYfCkYPM2h2MvBBjPG3RndJrikt5DktpWaKhVyWYU6pvAzNpk8w6FkqBQEHSuEFSEFPSA= QWY6h+1IVEND6CqZmTyVXZUX9+JZoUBoPdLbBF1/jqi+CRSNaFTn3e9+9+IgvmnTpnPj6hZj8qA= p4uFvrmvAlGMsi3kJXISgXJjEzc7OEg6HicVir3jXqUBtfCuy4S2vaHNZ+qqdv8/iKC4EKB6Uhh= 2LJke1+4842/54etKl1F4Ptdede/EuYhxwHIlpWpimg6oIDI923vIX5UmgQFHEWZZWR4LlgK4KH= Gc+i12UPTay/BFdFdjz9RIBNEWc/8W386LmtK45Lb7K10hhNpNFQZAvlkjl8mUJf2aduoVfC1n+= 9yZxydlteGrw1Gxi28pJrl5hz8/MOEPlOZA8iNz/6XJQmizXeRAAs3uRc3vLG1INqH0baL5z9yM= l6UyGhx95hCPHj+Pz+XjLjTeyqrt7vhZK+QHgOM5iRoNt2zjzM5g1FUG6Qm30RANEPPrppkmJIy= VyPqZlcHiYhx95hJtuuIEVXV3nPW4hBH4DrupUubKz3IFOX+DyOmo4gu+291G44XbyFmhehWwWN= D2CjPwWRf8H8OrljmhIweC0zcSc5Peu1zFt+IdHirRV6byldQuKMj+r3HEzvhvftnhDvF4lr6oq= mzdvZm5uju7u7sWUfykldXV1RKNRtm/fjqZp7Nixg5MnT7Fjxw6EEKxpaqH/gU8iEOh+H0Z1FZl= T/Yz+4EGqt12Np+rc98C9FmQyzejf/xPZX+xCFnIgVGb6BwkWTJp+6z0oHoN8Pk9FRQXj4+N0d3= SQPXwUphM4io2Ihf8fe+8dJ9dVH+w/55bpZWdme5e02l31XizZluWKexEYTBzgZ1oILSHhfSnml= 4SEQAKYGl5KXhsbAhiwcQVjjI3BsqrV26rurrb36eWW8/5xZ9eSrYrt2JB59FlJO3Prufec8z3f= Cl439sAI1kiCgfWbab7m8jNm3A4EArznPe8hm81y9z33TPk6uXQX115zLRdddBGq6mgc+/r6sG0= n+s80TUZHRtA07cVcOMVBubKqir/+wAdQFIUnnniCjZs2Mr3G0ZZ6PB5qa2rI5XJUVTnm3rq6uq= l3evr06YCjkdF1naqqKiorK51zGiZen5eGhoapd39sbIwFCxZMZQVvaHgxAMIwDGKxGAAVFRXU1= DiLkclUCu1tbViWhdvtxuv10tTUNPV9oVAgk8lQXl5OdXU1UspTFiY+EcMwitnincHZSTvhmFpt= y0bTNaRtF80TAqTEME1s28mrFAj4efM1a6gIbmCjnibeEME0bTQrzbQawZz2VcyePZtorJyCYaA= qygkLm8n+wVTuNsN0HIR0XUMIZWqSFOfTlyRoFUEUVXXKHwDCo4OEzL9toPDjDoQpcemw1iXxhz= VcusLaSy9D1zUUVcXtdpPNZFiydKljVjdNJiYmaGmZQWtbK9K2qb7kEibGx1m2YgVjY2OM42gqc= maBgRsqcLl00ukh5LUR8oU8+pwgbleMfCGPz2eS6e9GWxPAtn0Y2T4iQzmqq6vPentCQCGv8MI2= k8ZamyNdCu0tNkf2wqKFAk2DUEjQPkuwZbONV0AkqLB3i8k2qeDxw/Aw9NWDmjeZSAmO7TXJmYK= 6aRo7tptU1CqUR3VqV7w84OScn8MkwflMzPoCSS0MiZ3O8waCrgoi3gYmMzi/9Lhxw2J/ynEKnp= xS37+qigZdQVPPrCGxbZtMJkMmkyESieDz+U6tVRHKGeSWU2n5xblpP/7IMVVKyeBggp/9dBeDg= 3EiUT833zSP5mlRFOXlgRyT9zQpWzpfCbpHDH65q8A7VntI5yVP7ytQH1XYeMRyxkrV5sq5OhuO= mAzEwa3DiukaK6a70E+VfV4IVN3F+FA/cpY9ZTKUxShgKSXzpjUzf3oTWzoOs7RtJp7iHDXVdlJ= SyKXJZrJOup1XUcN1In+cJkkIpB5E1N0Mo1vQcoOn2OjEX6yiHvkl0qsQEGpD1Fx32oSOm7ZsYd= fevbz91lsZHBpi244dTukIy8K0LMKhEL39/UTKymisr6ezq4tkKkVFeTl1sRgHjxxmN9DY0MDg0= BACJzlYKp12fFqqq9mwaRMjo6MEg8FzuHfn5k7fD5yHd6jX5sioTcQj8CiQscEywbIha0mmV6ks= ma7hcQk6h212dFnYNkQDChe1a47qWbzkuK8SQgjKy8spLy8/43aWZbF3714GBtazY8cObn3LrcS= ffY7cwBAIUDwePPW1pI/3kD50hJ6f/JymO96B5vvjampJyyKx9wDJbbvR21rgWCdaQy1SKAz96j= eUv2ktvroawuEw7e3tTqI+w2R8207U2ipEPIkWixCaMZ1g8wza3/8uNL/3lCkJTmgMNE2bcixva= Wlh48aNXHPNNQAcPHTI2awYpRYMBjENg507d9LT28vGjRuZP28efr9/SlAXikI2m2H9888jpc2h= w4eYO2fulAO5UTA40HGA8fFxIpEIdXV19PT0OG1Q9EOaFLxSqRS6rk+ZyGzbdoSs2lri8Thut3v= q33Q6jWmaU6vbyWcw6fvjcrmmfJYmBeNJs6Ft2wwODpLNZtE0bUrDWigUpiL2hBC0tra+TJt2In= sPHHYK0kpBKpUmXzCIlYWoriqnt2+QxoZaBgaGqKmunFrZdx/vI5XNUsgXWLJgDhXlUSZSeVbOb= yWVcmoH6rpKIBiisrqOeCrHsa07EMKZ3MJF/yJVURGKmAr/VoTgaFcv0jZpaqjD5/UyFk/gcbtw= u134PG6qKiteog04xSuCQKkPIF3FGlWaQIl6sHcPYz/ZhVobBK+KO+zjwvkR9KiKqSuEwyGn3d1= u8rmcU3MQST6Xx+PxYNk2Lk3DMEz04rPxer0opoXX4yWfz01N5qZlotoqLrfbGRsUR4sgiwKhqm= m49En/JadYuW2dOoji5V1AUFMPf/kXKoqqcZEpnfxVBWfCmtbsxLgIBZavVDEKEkVRyRec3G4Ig= a7huNBYjlph8QI3UoJpgCIt3B71pHfyj8WZewIMInn2yL+SNyf9WwXzK6/j4ua/QinmTTKkiSIU= NKEigcNpg7/dPUK22CyqEFxS4eUzM8uctB+nYXLBAC8mlvxTSclhWZJHHt7LvPnV3L5gMYcPjfD= DH77AbbctxLIlhYJJXW0Zlm0zMJCgrMxHRUWAo0edqN6mpiguj4un9xU4PlJgX69GZUihZ8zCrU= NtGcxv0Hj+UJ6n9+ZJFmBps05NmUpVWOV0wY+qorBkxQWsf/Zp5ixbjcfvpOGxbJtkJotl21yxe= AFCCK5dsRRdVRlLpvDoOj6Pu3hvJp0du9HcPsJlr9SR/PT88Y7bQoPQHKi/Cdl5H5jnroafwlOB= aLod4a06pRAggX0HDtA6cybtra1Ma2qiZfp0fvPMM44WpLWVp555hiWLFrFx82aOHjvGC9u3M2f= 2bEZGRwkEAmzesoWZLS3EEwk2b93KnFmz8Pl8bN+5k7raWp7ftIlYcfJ7qQ/DH4sQMK1GwecXeH= Xnx7ChYDhDXsGCmqgzsDRXKLz3UjfHR20UAU0VCuXBM61GXh3O5YUSQhAOh1m5cgXlsRgynabn/= gfBspyB0e8j0NRAvn+QhtveTGBaI9K2XtGqxxgeQ5omarQMOV6Ge3ozFAwKx7qxso7fj8/nY9Gi= RSAlmfEJGm5dhzvgZ2TbDox8nrwBi7gAACAASURBVJo1F+EKh/DEzt5x/H4/F198MeFwGI/Hw5u= uuoqjR4+iqirz58+nq6uLsfGxomZJp6amhosuuohMNksiEefC1atZtmwZHo+HpUuWUFZWht/v58= ILLySRSCCA5cuWs2jRIjweD7KqAqEqhEIh3G43brfbSWFQVTUlyCSTySnN1GQ9PbfbPVXYNxAIo= Gka6XSaiooKLMuaEvQmtVGmaU4JbW63e0pQyufzBAIBzKL2Rtd1gsHgVHSby+XC5/OhqqqTwkCI= qbp+UsqzOt9PTMTZvG0PlmmAUEilMyye24rLpbPphZ1s2b6LTDaPKiS5gonH7SKby2JZEtM06Os= f4KJVS9nbcRjTyGOaFvlcnmgkRN6w0LftYSKRpKm2ilhFFQcPHSKRSoNQcOsamqqhairVlTEqYx= HiySy5bIpf/eZZgn4fCEEml8PjcrF88TyuvnLtWYUkBChzy3G/ew6Kz40S80KdD21OBYEvXor0a= 0i/jurXEVEvil9HVQTN06a9LM/V2dIqvJhEctIsc+ZcWadL2XC+E4amCzT95Gc75TIWevn254qU= cO21AuUsmprzQSCYEb2Q7uQ2OkaewbIdbaFdLFYupWQkH+e/jj/FiugsFpe14lJ1JAIDgSElAkm= 9T+e2Wj9B7fSmtsnACUVRpnIw/akISOCk4ohPZJk+PUYk4mPW7Cruv38XDz20B7/fRTTqY+OGLn= I5E49H4/jxCS64YBpHjoygaQpD7SlqWxsYSVpc1Ormmf15rlvovBhSwtEhk0RW0jlscuU8NxsPG= +zoshhKwlr/6dtKKAorVl3I0796hP3bN7HggstQNUdTZJgmEolZ1C5Pan6tYsTbpGN3amKUZ3/3= DPOWryFcduZch6+EV5AuUyBcZdDwNsgNIPt/VYzYOkfcEUTDmxHVV3E673wBhIpFBrPZLD19ffz= mmWcQUjJvzhzqamvZsm0bC+fNY3x8nNGxMS5ctYr9+/eTzma5+frrmT59Oh2HDxMr5pi5dM0afv= /881Mrg4rycmKxGLlcjrLwq1M6QghBZZlGRdmL9zGJnNrG+VxToToiqC5TpjZ+o3RBRVGoq6sjF= ovh0nWSu/agCGj+q/+PTFcP5sgIoTmz8DU2UHfTdWh+3ysaQISi4G2qR1N1spt3gZHHHHsegODC= OeghR9N3okOzN1KGd9VyBOBvrCebTFJWV+dE/pzDtQT8/inTohCC5uZmGhoaUFWVZcuWsWTJkqn= JRymadq655poX0w+o6lTuouXLl0+d85abb5lSXysnmIRcDV4onmfyXoQQJ2kxJ01wcOoJcnJCDA= aDaJpGsBjBN5lRfXKfE9XnLz3WZGHeye/D4fBJxzhx/xMn37Mlj1swt52KWITxiQmktLAsSXVlB= bHyGOWREPFEkkI+h2XbRdPVCQKCbTmRcOVR3nnr9YyOjVIoGOTzOTweN7quk81mKRQK+Hw+qqqq= mdPayPj4GEe7ep2Jr64Wl64Q8AUIl4UJh8tIJOIkUymymSy6yzWVO6eiPHZuyfCEcASiz62hmBY= f1GLtqaJm+XSd9lwCKc72/Zn2OZvf1+uNEKCdQQj5444pcGt+Vta+g3RhlJ7ETizLKYckpSRlZf= n3gz/mZ73P0uCt5Mvz/pqFZS1MJcFEEnNpvLcxwJygC+00kVqTJnVN0/7khKNJFEXg8mgMD6eoq= gwyNJRCURwfo5aWctraK/n8vz6FaVrU1YVRFOjoGGb+/GoiUR9/eK6TXqWCgaRGqlPQP2ZyaMBA= SqcrtNVozK3XOTxgEPUreF0KK2bo1EdV/G6FM3lTR6Ixrr75Vn75yMPUNs6gsmEGqqIQCwXJDQx= gjDmLU2nb2IaBp74et8ftmKuNAhuefpyCrTJ/0RJcrle5WscJiLGxMek0poLP5zv7quqlSBuZG0= R23Yfs/pkT4n+maV4o4G9ANL8TpfYm0P2n3d5RxR/nu/fcQyAQIJ/P01BXhwRmtrQwp72d79x9N= xXl5UzE48yfO5c9e/dSVVXF/gMHWL50Kce6uhA4JodCocBfv+999Pb3c/8DD9BYX4+qKFRUVJBM= Jnn7rbf+SXaE/w6klFjZLLZhIFwucn399Dz4CI1/cSuucBh9Muv0KyQ/PkHnf9zNwI8ewEokkAp= 4GuuY8cm/o/LKS1DO9H6eMPG/5qq4Eqdk0lw4mcdqUps1mcndNE0myw/IYi0qp885PkSTfljg+D= dNHmtSozYZZDG5sp/MMZXL57FP0Kjpmo7uck05qDomk7zjM1L8fdKMWerzf5rY0mIse5wNvXdzb= Gwzs8qvZGHtO/iXAz/mRz1Pk7MLKCjMCTby5fl/jVCa+fDucco9Gh9sCnFJuQe/ppxy9nnpIuJP= FSklhw4N8/Of7UTXVbJZg2uvm836544yMJCkrMxDQ0OETNognsiQz9nU1IWZM7uKUNjDb5/txDO= jlVWz/FSGVHYfL7Cnx0AIwcwqDbcuWDZN55n9eZJ5m8EJm5E0uHWFRY0ql85249FP3365XJZ7v/= ctlHycm9/+bqJVTtR2fPNmUvv2Yefz2Ok0ZipF5Y03Epg7F4lkxx+e4MGHH+P2936Itllzzqm80= LlgmibpYk64SV65kATO5GRlkRM7kV3fh+H1YBdOyu8kFEANQu21iIa3oQRm4iTJONNhnRd1bHyc= 4729+Lxe6uvqSBQT5IWCQSbicXqLYc+V5eUMDA0xNjZGdXU1oWCQnp4eLNumurKSVDpNbdFxtX9= ggEQySW1NjTN4G8ZUor4SZ8e2LMxUGj0YOLesu+eItCVGOs34phcYe24TalmQqisvJdg6A+U0hU= JLlCjxPxMpbTJGgsNjzzJuTvCT4RF+evxZDNs8aaHUGqjnb9o+Sle2hlur/Uz366fVIP25Yds22= axBOp3H43Hh9erc/X83MWt2FbNnVxIKebFtSSKRw+vVUVUFXXfq5+XzFkJTcesKihBYtiRn2I6G= UHECljTVSWVhWk4SCbOYmNOlCdy6OKO/l5SS8bFRvvvNr6IV4tx2x19R09SKbVrIXA5O0Iwrbje= 2NPn9Yz/hJw88yrs/9HcsXXHBHyeznIbXTkgCR1ACJ/lVrh8Z3wvpQ2ClQYtAcDYiPBtc0RfNay= WBpMQpeCXlMEqUKPE/CyciSpI2MvxuZBePD23iQOo4OVlAlSo17ggXl8/n+qpV1Psq0ZRTa4/+n= HnpmNrZOUo47CUSOX0Qxsuj3E48zolm3peXPzpx2zON3ZPbxCcm+K/v/yfdHTu46eYbmb10Db5A= eEoDXcjnGOw+yCM//SEdXUN84G/+F7PmznvVzaCvrZBUokSJEiVKvE5MTrg2EsMyKdgmihC4VR1= VOBmaS4sthzda4WynFFaGjev/wBMPP0jQLVm6bCm1jTNIx8fZueMFDnf2Mmvhcq698Raqa2pfk2= svCUklSpQoUaJEiTcck/6ME+PjbN6wnu1bNpGYGMXl9tDSPoflq1bT1Dwdj8fzmgl3JSGpRIkSJ= UqUKPGGZdIXOZvNkEom0XWdQDCIrr/2QRanEpJKnrAlSpQoUaJEiTcEkxGFfn8Avz/wel8Or24C= ixIlSpQo8aph2RaFYl6nEiVK/PdTEpJKlChR4g2Ibdvs6zzM1x+8h1QmXRKUSpR4HSgJSSVKlCj= xBiSTz/LYht/ys9/9it9uf37KV6NEiRL/fZSEpBIlSpR4gyGRJDNp9nYdIp3L8MTmZzFM4/W+rB= Il/sdRctwuUaJEiTcIpmWSNwpOzT8hiAbCuDSdqkg5lrTJFHIIwKW50F6lUgwlSpQ4PaUUACVKv= MZMmkmktEEWozf+RAtmlnjtkFJyeLCbe5/7BZa0mV5eT62/gj1HDrJ6wRK2Hd9Pz8QgZf4Qd1x4= M9VlFa/3JZco8WdFKQVAiRL/jdi2TT6bYWign/7OIyTGh1FdLrzBMqrrGolWVBEIhlBVtSQwlQA= g6g/TOdLHru4OfC4Pb15+FW+97Fr+9bHvsuXobgAum3MBLs31Ol/pny+2bZNKJVBVFZ8vUCzPIc= nncxhmAb8vgKI4WjzLtkgmJwj4w2il2pJ/lpSeaokSrwHSthns6WbHhmfJp1PUTp9Jy6zZKLKAk= BaqlSKb1NFUFa8/8IqqWE86856q1EBJ+PrToswf5K8vfRuff+x7dI30cqD/KCOpCQ70H8OwTOY2= tPLOC28i5A1MVak/HwqGycBonELBPOHTycJcAoEE8fL6XFIKpJDO91JMbu5sIZ1/ZfFHnLirFEh= hIyb3AYRwCqGKEwugT24OSCGL1/JizTAhBJGwn7Kg92X3PKmpnaoZhnSuSRGIP6JKWyaT4jvf/z= fCwQjvuO3DeDxepLQ5eGQPnV0HuWLtTXi9/qlt7/mvr/KXb/0Q5bGqMx7Xtm16e3tRVZXq6mqUV= 6EwuGEYdHd3Ew6HicVipf7+GnCeQlKxiG0Rp0udouDd1NYv50zfne3cJ573fwZ/TpEsr+CZSclJ= lRbf4AOBtG2OHz3MH554CK/Pz+ILVpMb2sfo7vUo0saywTZyKG43Zc2LaJp/OaovdN73dWK0k2V= ZpFIpkskkVVVVaJqGckIF7RMHz1MVozzVsc/0/YnbvZoD85RZ8iReXnPrz20ysG2bXf0H6Y4PEP= WF+crtn2QkMc7x0X6EEHzwsrczs7qJsD9IT2KQJw8+T1vFNJqjNajKuQvYQ6MJPvuNhzl2fBhbW= FNCiUBD2CoKZnFMFwgUEIozCjnVywEFKRVsxUJioaIWpSUB5JHoKFIB4RSdxQJEHgUFKRSEDQom= thBIoSEwkWgIKYrzicCSElvaqKqCUAQg0DWVd69bzU2XL8KlvzhtSSkZSh5gW/d9tFVfS33ZYjY= du5uxzBGWNd1BdWj2lNbnXJ9Db38XqqKyc+8mRsfeSm1NIyAwTYNCIX9S/5ES0ukElmWe/qBFfv= nLX/KhD30IXdd59NFHaWtrO+V7bNs2tm1P9a3TaZqllDz++OO85z3voa2tjR/84AdMnz79nO+1x= LlxTkKSlJLx8XH6+ntRVPWkZYOUzjJCiKJULE4QhCRIW2LZlvOwFdXpS+LF723LeSGEqqAqygnV= hou1XCwbiURVFBRFwUaiCpVpzc24XK99mvLXC9POMZB6jkT+6Ot9Ka+Ycu9CKgPLOF9BSVoWVt8= AhYcfo/D8JtRYFNebb0JftgTF63nDCUtSSizLYqi/h02/fRy37mbJqlUURg/jj9ZQO3cNutuPtG= 0y8SGGD29nonMX+fEhpi2/AXeoAkVVz7mytZO6P0tnZycPPvgg9913H8lkkiuuuII77riDBQsWE= A6HT1qxmqbJvn37SCaTNDU1USgUqKmpQUo5td2kwBUMBgGmzA2apjkOxYpCPp8nm83S3d3NrFmz= 8Hg8r0obpnJJfr/3SeLpMecekUT9NUyvWYjHFUBVFPxuFz63C5f252OmlEj2Dh3hS3/4AZZt0V4= 5jc9e/gHC3gCWbbN65mIGMiN88JHP05sYojwQ4TNr30tjpJrz0UFKCUGvm3/88E1URAOYSDJ5gw= ceeZ493cO859a1tDVWY9sWqVSeJ/+wi+e2d+L1qnzg7ZfSOTDO/Y+8wAWzG7hi7QJ+/NhWDnf1c= +GS6dxy5VK+cd+THO6ZQEWgqYJLVrVyzZr5/McPfoNlm3zgtisIhoNMjMX52j2/pnlaFe+4cTWm= afNfD2+kdzjJHW9Zzdbth/n183un3j3TtjDtlwrPYNkFtnX9nPWHfkL/eDdzaq/mV7v+DcsyGE0= O8OYlXyXkPbOG50QKhTy79mxmycLVtMyYzcYtz3DjtbejKK/8Pdu7dy8jIyNkMhnuvfde7rzzTv= x+/wnPRlIoFFi/fj3f+973OH78OCtXruS9730vM2bMOMmcJ6VkbGyML37xi4yOjtLd3c34+Pgrv= sYSL+echaRDhw+ya99ufAEfUkrSyTQjw6PEEwkURRCLRSmvLHcEFwS2lGQzWUZHRhkaHAKgqqaa= qupKdF3Dtm0S8QSD/UMkEgk8Xi/1DXWEy0IoioJRMBgdGWNwYJBCwSAai1BTW4PL7SKfzlFRXk4= 0Gj3LdYNtS0xTIiVomkDTnJfdspzPwflcUSYnA2cfAEURL5uHpXT2tW2JpoliCvWT28o0JZb1ov= LjRBTFOZ+qnrnTGVaKfcPf4+jYT0GCLRUKBQ0hJLpuIaWCZekoioWqmkjbhW0rKKqFohQ4Fy3US= QLp5GeT9/GS30/12bnOT4tqPk1FYNn5iUhSYo2Nkf7Y/8ba34E2ZzbmvgOYf/sJvP//J3BffzXi= DRbdUygUGOjv4+COTeTyOZavuRLFTFMz+yJ8ofKTnLW9wQjhykZGu6bTu+O3dO/4DeWzLwXNQ0X= F2R1yHR+JPE899RQPP/ww/f39U6vI4eFhvvOd73DBBRfwzne+k3A4fNI17ty5k5aWFh566CFisR= iGYaDrOlJKotEo2WyWnTt3smzZMtLpNJqmkclkaGtrw+VyEY1GWb9+PYZhYBgGbW1tr1obpvMpn= tv3NFI6K+mjAwdxaW6uWnwTVy1+C2PpAgd6h4gG/cyuq8Sta38WgpIiFK5pu4iNx/ewoXMHnWO9= PHN0K2sblxQFU8HD+35Hf3KEgMvLFS0rWVjbhnYeWhJw+q4v4GJGQzmGbXLg2BB5S5LNGwR1nZl= 15USDXnYf6qKhupK3XruSjmODSAQzGyrwenRciqQ85qelqZLqaIBj3dBUXUZbYy01sTDjySwL2h= vp6Rtmx54urr9kAQCq5qayPERVLEyfsBAauBWFxooy8oaJWxeowibg1jhwtJeKiIuLl88hl7fYf= 7gP5RTPWVE0WquuYDwzTHv1pYxluskaEttWGEuNYVj5c24b27YZGRuku+coK5atxeP28u27P89F= q66iPFZ52v3OVd9/++2386Mf/Yhdu3bx4x//mOuvv57ly5dPCT+FQoEHH3yQO++8k2PHjiGlZMO= GDaxfv55vfOMbLFy4EE3Tpvr+97//ffbs2YMQgiuvvJIZM2ac872WOHfOWUiSElRNR9N0+vsH2P= iH5/G4PDQ0NGBZFts3b0N161x6xaX4fT4y6SxHDx7BrbtpqmskHA5z9NhR9o+OMn/BPOITcfbu2= suCeQuY1tCMruts2ryJaS3TqKqpoq+nn9GhEebOmYuu6wwODrJn5x7mLZo3ld3pTIOjbduMjZls= 2jTC7l1x8llBU7ObSy6tQncpbHxunI6ONJaUtLeFWH1hiKpqN6Yp2bJpFFSbJUuieNz61Goml5N= 0H8/ywpZRerrytM/2sWR5jKpKN6oqEEJimiYbnh/j6adTmKbltJ9iACqqreL1qDTPULlkbTVVVW= 7OaJaWk9o2jcNHm9i1txZNlcyfM0LQX8tEvBXdlaGyfCe6uBBkDFv0oXoeQ1EHAMibOoMTIWojE= 2iqhW0r2Ag0xTrxNGTyLlJ5D7pqEfZmyBQ8mLZC2Jue8jGIZ7xIBGXeTLH9z+Xt+eOQQOHJp7G2= bsP3za+gX3gBcnSUzD//O7n7foTrirWIE1ZhrzeWZTE0NMjoYD8jvceJVFQTDPmIxJrxBCIgTjY= ZCSHQXV7KmxdgmwX69jxDdrSLrmGD8KpVuNzus07+hUKBzZs3EQgEmDVrFoODgzQ1NXH8+HFaWl= rYunUrN954I6FQ6GXHMk0TRVHo7e0lEAiQSCRQFIX+/n6WLFmC2+1my5YttLS0cPToUVauXMnTT= z/NunXrOHLkCMFgkM7OTlpbW1/1iFi35ua65W9GSPjyw58lZ2TZdmQDa+ddxbSKesaSafrG4zTG= wrj10w9htm2TSCSmqosbhoHf76dQKKCqKqZp4nK5UFUVy7LIZrOEQiFyuRy6rmOaJpqmkUwmiUQ= i5PN5CoUCXq8Xv9//qghnEknGzNOZHiZt5HnzkquZWd7EcGoMy7aQvOhv49Fc3DL3UmrDVbTXz+= RwZpiwmaYlUI16Hv4tAsdCdrx/hPsfeY6sCWPxLCG/Gwn0jIzxHz94iqsums/Vaxbh93lJZfMnv= 8PCWURWRYPMqI9RHvI544QiqCoPc9t1y9i8/Qi/eHIbyXRxvEBO1eVyrqL4/0lrXfHQlm1j2iYe= t5fFc6dRU17GQ/YW1FNocxShMq18GQ3R+YDCHw79AKPgwpIWBUPBsAxMazK/lESIoqb2FEs2yzJ= 5Ycd6vF4/E/FRdE3H7faybefzXH7JDc420n6JUCQRpzAHn4rKykre97738fGPf5ze3l6++tWv8s= UvfpGGhgYMw+Dhhx/mU5/6FF1dXVMmPdu22bx5Mx/72Me46667WLhwIQAvvPAC9913H6lUiurqa= u644w5CodBZr+G/A4nTTgKB+mewgDkPnyTHZjw2MsYjDzzEupvXccsttxAOh7Esi97eXu75/j08= /MDD3HLrLYyOjlIWLmPdLet49NFH8fv9vO+97+M//uObdHV2cfDAQYycgaZqbNy4kZtuuom/ePt= f8OP7f4yiKfR293DLzbfwi1/8AiEEM2fOZOaMFvqO91JVWXVGy42UkmTC4Nvf6eGBnx0nEvHi8W= g8+ugQ9/+sn1h5iH07xymv9COF5Gc/HWT5Sh//8i9z8XkVfv2rJIc6h7nrrjJqqh3N0fHuHI89M= sRjjw0ST2YIBwM8+EAfVbVd3LKumauvqaS8XMU0YcPzE3z3OyPMW+gl4BNIkUVKDSlVMgnJ0Xsm= uPqGCT7/L3MIBM7wCCY1PQh6ByrZf7gBtwbRsgoa6prI5doxrBS53AQez1K8ei15+zCG9VuE4uz= eP1HO7/e3c8XcndgIxpNBhhMBWmsGUFULRUiGE0EMWyOR9RAJZEm4M3SOVBL2ZvG6suiajVszOD= RQQyyYJNzQ9dp6hRVNufaBg+hz5+JauQwRDIDHjX7hBeS/9T3IZMDne8OY3PL5PIcPduBVFSzDp= KZhGh5vCFXoWIUC0rJQXS6kbWPncihF85RtGIQqWxgL7iU9fAzLiDE82E9dY/Mpz3Oik7auu/D5= fDQ1NVNWVsaTTz7JihUryGazXHDBBRw7doxwODxlugZwuVwsWLCARCLBNddcQzKZxO12YxgG6XQ= an89HNpvlyiuvxOVykUwmWbhwIbquU11dTX19PdFolH379rF27Voikcgrcjp/KY6zrsCtexDyRe= 1uJp8mnUtQE1Vw6ypqMY+QYVnop/HZKBQK/OY3vyGdzmDbFtFoDE1TyWSyeL1eNE3F7XYTj8fx+= fxs27aNFSuWc+BAB7NmzaKzs5P29nYeffQx1q27mf7+AXbv3sWCBQu47LLLcLvdr/yGJaSMHP/e= 8RgbRw4R1L28reEC7pi9hr19BxFCQWIjhGBF4zxaq6bzrWO/5Vu7f0TGyvO2hpV8etZNqOeRF1j= g+GbPbK7jb+54E6l0nm/95FlyeRMJRIJerlg9n1kzGhBFE/KkvkQUfQIFCi5d5aYrl/Cmi+cR9j= muD7aAVCbHviMDdPaNYwFKUZCVk3+kABSELHq5ihO0MQK8XjdLZjfw2+cP8fW7f8OsmTWkkhlqa= 2KnvB9FUdGFFyklfr0Sy/JSsPKMJuP8fv9PkQgMq4CUNmX+KubVX0xdpAVdO/n5pTMptu/cQDBY= xradzyMAj9vD7/7wOCuWXoKqaiSTExhGHikdITmdTiEl6PrZ3wVN01i3bh0PPPAAv/vd73jiiSe= ora3lrW99K1u3buUrX/kKXV1dqKrKokWLWLhwIU899RRdXV2sX7+ej3zkI3ziE58gEAjwxS9+kY= MHD6KqKnfccQeLFi06dR+wLPqzCQzbxqWqxFw+fJr+mmlfpZSM5jNsHOthWbSOSveLiwnTthkrZ= BjPZ/GoGlWeAG5NP9laISWGtNGEckrN4evBeTlum6bFtq3bmD93PjfccAO9vb3k83lM0ySTyfDu= O97Nx/72b+k6egwQrFy6klwux3333Ud5eTlXX3MNy1es5PEnHselu3nbW97GI488QjKZxDRNIpE= IFRWVDA+P0NjYyMjICJFIhOuvv56vf/3rXH/99WzbuZ3yWDkviaV4GR2Hstx73yDXXzOdD36oAo= 9X0NGR4yMf3MPuPRP8y+dncPnaKJYFjz4+zL994TBrLopz3Q1RMobC8JCHQs4xq+3YmeIzn9rHy= JDBtTdUcd0Ns6ms0OjuzvPz+3v58pcO8swzw/zDP7VSWaFj2BaxmMUXvtBCXa2byfAPKQXJpMU/= /EM3Tz81ysTfG2cUkiY1OELYVJXnuHptr5O/Qbpwuw7jLe/BsBRMe5hsYT2GzGFYNqqrgOYC01b= Y01mHoqjs7m7CsgUNleMk8152djXi1gws20UoVKB7KEjUn6Jv1MOBVC1V5QWSOUFHXy3RUJZCQS= B0hTKZflUFJGnb2INDWMkkAEowiBqLIXQNz4f/CpnLYSUS2EeOIdxu7EIBTBMsRxNmZ3NYQ0MIn= w81FgUhsBNJ7OERbNNEqApKNIpaFkIoqmPGSWeRSIQtQdqOWVRVEIqG8LgR2vlP+tl0itGhASrK= wkgkoUiEzN4Ojn3/HqJXXEV85y6qr7qCzMFDZI91oURD+Ge1M/jQL8Drxf+m5RSMCXxldezfu/u= UQtKko7ZhWgxPpLEtm5r6ZhrqqgkGAtTU1FBTU8PMmTOprqlhRms76YIkPjRBLOzD73WjqiotLS= 2YponH45lS9Z+t3EUul+OGG25A13UikQgXXHCB40tY1AycbX/LslCKfoXnixDgcwcIeMMYlk0mb= zp1zXoGiQR81MfCBL2elw2qlmUxODhIPJ5wNHe6i1mzZnH48CHGxsZwuVzk8zn27z/A/PnzOXCg= g5kzZ9Le3kYymWD9+vVUVlayd+8eLrtsLSMjoxw9eoy6uvqi4PDKEUJQ5vKzpnwWj/du51BigIl= ChuWR6QTcfkfrU/TFCbh87En28sOu9fRnx5kRrOKqqgXnbXJzkCQSaXZ09JDNmOTTBdAVJArl4Q= i3XrcSYUte2HGYLxOmEQAAIABJREFUsbEU3sBLhQAb07TYfeg4Pf2jzGupY2G7D4lkYGiMe372L= NgKM5srqYyFimfE8f3GBmyksLFw+p9d/FEUgd/l4u3Xr2HB7BaefGYbm3YcwbBh0dzTm5MmJ+KG= 6Bx0rZxUbpBktoDPXU7X6H52dv2evJlHUzT+0PEY65Z9hAWNF+PRvc61ScmhI3uprWni5uv+Eo/= HCwhsy+S7936RPfteoG3mPIZHBti99wXaW+dTKOT5xWP30dYyj4A/eNYWF0JQWVnJpz/9aQ4ePE= hfXx/f/e53+clPfkI2myVZHAPb2tr45je/SUtLCz//+c+58847GR4eZtOmTbzrXe9C13Xi8TiFQ= oFly5bxvve9D6/35VF/TktLnh3pJqDq2Ei8qs6aiia8mk7OMkFKPJqOlJAraty8qiNE5UwDCbhV= DYkkaxloQsWralhSYtgWlrRxKSqKEGQtEwGoQiFpG8SNPF5Fw6e7QEq2j/fTlU3Q7o+xcaKbteV= N1KshMqYTLOBVdTJmgacHj7K6ookyl8ex4NgWLkXFpWqvS8jWeQhJEiOfZ6Cvn0998lP89Kc/JR= 6PEwqF6OjoYN68eaxdu5YrrrySHXt3MH36DAqFAsFgkMbGxqInPxTyeTRVQ9d02traWLduHRs3b= uTzn/8806Y1I4GW9pmYhiM0BYNBJiYmMAwDkLh0vag8OPOgfOxYEsuwWH2Rh6YmD6oKfp9K+8wK= Dh7LcMVlMWqr3UgpWb6kDJcWYPfeJFdfG5kyL0pgfLzA5/91N3298I1vLWDJUj9ul0BRLGpqQsy= fH2D1byr4zCeO8IN7+/jghxqQKKi6j0jEjcej0t1bIJdzLnlkyKC/J0N9vYLPd/YJQxS1AB1HND= ZuqkYoMGeWQSjUglGYj6RALPoLIuG34taC5M1uEtbWqf1ba/uIhQ4xkvDh1iSKarOoKUW64ELYg= rJghoF4mEVNo3hcBcfnSiqksj4qQgki/gS6ZuFz5xlPBaiJOA61QhR9riad+E93/Wd7qwsGyb/6= G+xtO0FIlPJy3B/9AJ5bb0Hx+8ne+1/k7/4BcngE4XIh3W7UyYndtjFe2E72w3+PungBvi99DiU= UwvzRz0j/211Iy3KEpOZG3P/7Y7gvX4vM5TB+8ShmIoliS4hFwbSQ2SxKNIr7yrWI8PlFmkkpSS= YTxMfGiYWCzn0ogkhrK6MIfDOmk+k8Qqazk3zXUZo/9jccuvNOXOUVyJEJhD2KW19DXmaQQtKxd= w+Xv+m6U16DZUv2d43y+MZjaIqgItqGJxYhnx0jFArh8Xjw+EJkbC8zllzFz589QiJTYGZDGTdf= 2ArS4tFHH8UwDEKhECtXrjwpisayLNSi83gymSQUCmEYBrlcjo6ODqLRKHPmzEHTNI4dO0Y+nyc= SiVBWVoaiKFiWRSaTwTRNVFXF5XKRSqU4dOgQCxYsoLy8/JzbdRKP7mFl24WEfTF6RuPEs1nHlC= 2guixIwO12XsOXCGqKolBbW0c0GiMej2OaBqOjIwwMDFJdXY1hFPD6fAQCAcLhEEuWLCYUCrFz5= y7mz5/HqlWrCIdDNDU14fV6KSsLU1Nbg9/vPyly8KWczypdSomuqNzasIK8ZXBv57PksRkpJKkQ= Ti4kGzk1+YwWJihz+5gVquWDLVewMNI0dZxzPa8T0QbH+kb4wYMbMSXY0qIiGgQk/cMjpDJ5Gqq= jbO3oJlHI48U1Zf4v/oVp2WzcfoRNO4+gKpIF7dMQCGoqI7z5imVUxELU1cYIeF3FYcIZVKVto+= squuZibDyFZVoYpkkqk8Wlq7hcOkGvlxVzpzOtNsLn/s/jHO0dO6d7qww3sbT5Wp7Y9WOSWZN9P= bu5YfG7GE3G2dezlZy0yOR6+Mnz3yTojtFWuwhVUZFSMhEf5+JVVxGLVk4J81JK1t3wTjoO7SYU= LOMtN72bp373ML977lcoimDOrMVcetF1aNq5mZyFEFx00UV87GMf45/+6Z9IJBJks9mp72OxGJ/= 73OemtLe33347XV1d3HXXXeRyuZOcsxsaGvjSl75EXV3daZ+9S1GJuX3UeALEdA/PDHeSsy2OTI= xzLDWOic3sUAV5y2SikGMgn2JNRTNxI8/h5CiGtGkNxihYFofTY/TnU7y1fg6j+QxPDh4h6vJxS= UUz+5PDCAkJM8/SaC0Fy2LDSDcTRo7V5Y00esPsig9xbc1Myt0+Kj1+PKrGRD7LsyNd9OVSrK1o= wrBtNo/3kZcWayunsXWsH0taSEVhdayBqMt7Tu38anLOQpIEbOlEmvn9fvr6+rjsssswDINDhw5= x+eWXU1lZSaQsgrRs/D4f69c/R2trK42NjbS3tzMyPMITv/41i5ctpvPYMZ599lkWL15Mb28v3/= 72t+nq7uahRx+ipraa7Vu3s2bNGgYHB7n77ru57bbb2Ld/P83TpxcnybOEJtsCTdHxem2EcGZzV= ZW41BwuYaJrkw7XApcOmpLDKNg4xi0LgQ1SYWw8z/7dJqtXz2DhQj+q4pjfLEsBbFwuwaoLwkyb= 4edAR55s1kaRCkLkKeQN/vHO57j/p+OYpg8FgWkqeHw+vvDlOfj959D8xdu0LYFhaAjVxpYCiQq= 4nCQMUkHT3Lh0P6btBquYL0Qq5AsafSNhptcO4tWN4mD64qGlhIrQ+NQznjpt8Zeq8Dh2cdvayC= iH+2sIebPoqvEy+UgUP5CAIuS5BbNJG6N/AO+lF+P66AfIfu1bZP/P/0Vdvgzjl0+S+8JduN71l= 7jffCNWdze5f/8aTMSRpgUFA/OZ32Md7cI2TazjvSizg8iJONLjIfjD/0RoGtmvfoPcP38Bvb0V= pbEB17ob0RAI05gSRCTCcQR36ciXagkUBXEWDUg+l2dsbIT2thakLcmmM+QNQT6dJrlrO3o0gvD= 7yUwkGHjySbIjY8SiEdx1NUjTojAyjLc6zGgyRWI8fhodqaRgWOzpHGF4IoNbV+gaLPDwhuOsml= PF6stvIhSLoFVZfO2hfXjcKlURL6YpOdg9zkg8Q8Sv0dvby8jICM3NzXz961+f8sNpampiaGgIw= zCora1lZGQEVVVRVZVIJMLAwAC6rpNIJFi1ahWJRILdu3ejKAqZTIaGhgb6+vro6uoiFArh9XqJ= RqOMjo4CMGfOnHN4IU5GVTTWzr2Zec1Xsb8/zmgyjWU5mpVcwURVBHkjSzqX5KXeIiBZuWZpMYC= iGGyhqsxdPMvRONo2iqJw4dqVCCFYtHI+ilCYs9gJzW5fMBMhBB//9MfQdI3m1gaWrFqIqqrEc+= OQO/lsAkfj5fP4UcTZF0C2tOmbOMD6Yz/EsgvMKVvAkxf9HcNGntFcEsNKO3dRHHcVRaHdV8vjq= z+Olzy7ex7ngW0/RlddXNn+YSK+2rOnbBCTY7lgXksjn/3ozeQMm0d/vYmekSS2FCSzBt/7wa/4= +w+u46YrV3L4yCiGbTgmcFtii6LJzHba0LQNLNvAwtGWB31uFsxuoDJahkCQNUxsITnem+TOrzx= AwC24+U1LqanysX1XH5/6ygPYCLp7h1m5pI1MLsc/ff0hJjIWtq3SPTDBuQwmQgg0ReMtKz5IJm= +w8chT7OvfQ7jj16yeeSMdvQfJFJw2PT4yyLP7f019rIWQtwwhBJdefA2GaZAv5Kaep6JqTGtqp= bmxFSEEM6a109TQgmEU0HXXVHj+uQqojkZT5/3vfz/JZJKvfe1rJJNJhBDU1NTwzW9+kze96U1T= fn5er5dPfepTaJrG1772NTKZDFJKGhsb+cY3vsGKFSvOqp2V0qYjPkxBWtT7wijA08PHuK56JuO= FLM+PHsevaLSHKpgVrkAXKs+NHmJlpI6cZbA/Psxl1dNpD1fw0569dGfizAxEiXn8XF45nbF8hp= xlcl1NKwkjjxQQdnlYHKoiYxlsjQ/gU3U8mkZQdyMQhF1eR/DXXLypeiY744McSk+wtKyGpmCUK= 6pa6M5MkLTyLC+r5fcj3Qxkk5TpL9cYv9aclyZJd+n4/D62bt3KunXrePzxx5k1axbLly/n/vvv= 55ZbbmHT5k1UVldRUVVBYiLOXV+5i2nTp5NKp/nHz/4jM9pbqKipwBvwsHXrFrq6u1i5ciW/fvL= X7N6zm1UXX0g4GqJ1dhv33HcvK5YtZ+myZazfsB6EYO7CuRSy+WJvF6ftO5P27xMRSMJlCeYtUP= F6XvJiyROdah11MIC0wbAF6zeM89GPDqMqhpPXo5jrQAL5tMb+AzYrVmpFDZSNxERRJW+9bR5XX= uUCbAQKmazJA7/o4zP/ew/Tm+ayclX0jN3fGeCLJo3J3CUSNEVFKsqLEXRCODlFFDHVLAVDZ/vB= FnzhLEOpKE3lg0xkA7gUi4KpEPBlGUsGcakmPneBeM5H0J0la7jIGRp+V45YME3veIyIL4W0FZJ= 5L4MTJv0TIXxui2TOTZkvRTrnwa0VAIWC5WJaRT+xUOKcQz+E24NaV4u+cAHWnv3Y+zsofPc/0f= /iNrz/66PYBzrQ5s/D++//TOaDf0f+t8/iuuoyzA2b0W6+FnvfAayt29BmtgCOH4RaW41SVYn7f= e8m894PYezYjae5CeH1YvX1Y+7ZhxKLYQ8NI/J5pM+HUlmJHBzEtiXCaWrcixcgqs4cRqyoKsnx= OAjVCW443kX9gmXM+Pu/Q3j9yHweX0M9lWsuJtXZRfW3vwWWTaBlJorPQ3/HelyxOg49twvtNI7= QEkhnCxw8PsZEKo9hOmHRQZ/Ovq4xCqZFLDTBrmMjaJogmzfpHEjh1hUKlk3nQJyy6TFmzpzJ1V= dfzaZNm3C73dTW1mJZFsePH8flclFdXc3w8DCqqlJeXk4sFpsyrTU2NqIoCj09PezZs2cqck5VV= QYHB9E0jba2NqLRKLZtc+TIEYQQU9qX80VKm6FkmrHUMPOb25DVMbpHxukeHieTL9A5PEY8eYCH= Nv2QgnnukUyvBZqqc9Xim7h8wbW4tLP7qChCIeypQsFF99heekY7yBbiLJr2dnKamwnS2NLR2Ej= ppFlxqzoaBn84dDdHh7ciEcyuuZCA+9T+Oqcik7M43DdERThEMOBFLxTwel0UTIP+3hEyBYNjIz= l++NAGrlmziFlzatmy6wjH+kbpHRzDkgajE2m6ekeYmEgjLZXBkSyHj/czMZ7AlJKOzn76h+OAg= mVbKKYkZ9gcH06h6QoHe8eZ0zaDvYfH2HNsGEUKYmUeWhqjHO0Z5EB/mrHxnDPOSlBV5ZyGEiEE= Ht3HHZd8nHXL3zMV3WaYBlXhmRzs2wdSYgjY2bWLqxYME/SEEUIwER/jG9/5LAC65sKWNrFoJTd= dezs11Q2Oz5Vts/fANh589F4+8v5/IBatPG//nsn+8PGPf5xLLrmELVu2UFFRwdq1a6mvrz+pn0= xu+5nPfIabb76Z5557Dtu2ufTSS6eCJs56fiFwaxrjuRxN3hCWlMRzGTJGgbDu4aqqGWQtk2dGO= jHHbK6tnsloPkvGNCjT3awor+dwapy+TJzu1BizA+VM1hZUhKA3l6TM5UVRFCJuL2nLmBIcdcUR= MRQhMIppHJJWnp8f30uNN8jccCUvjPcznEsT8/icbYvzXX8mQd40yJgGF8TqqfYGX5dI1nMWkkz= DqWnSPmsW93z/+3z5S1/ik5/8JG63u5jGPcUzv3uG7Tu38+a3vYVEIkGsohxF0/h/7b15nFxXee= f9PeeutXf1vqm71WpJrX21ZFu2MUJe8IIBGYc1IcOYDAPJTFjC8iF5GeYlLwmvZ4BM8gnkhYSMG= QI2dhwTBxnwbstClmxZkrVLrVar1Wt1d+11t/P+Ud1tCctS29gszv1+Pq1uVd2qOnXq1r2/+5zn= +T2DQ2dAwKIli0km42RGxwDo7lnA6MgYO5/bRTQaZc26NQSey8ToOLZp07Ooh4NHDuL7Pul0mrq= 6WnKTU3iuX10Sm5YN50egkNOB6iqWrfOf/nAxtXUxYjHtnG1BR8xMhxKgqvcLUX0FTfrEIimEDF= DCn63IUAo0JJqWnX7MjBFbBMPQuWRjw/QHO2P6B3YcHv7JGAcPlLn0MuYUcVFCgayeuEFDoQiU/= 2LIPwgIfB/P9xCzRoAK23YwNA8ldY6caUEpjUS0TKGg0VY7yYHTHVQqGrWxMr6UTBUiNKemOJOL= k5Mm+XKMsm/h+ToddaOcztSg/Gq11sBYCiU1ihWThkSOo2caMDVJLO6TLUWoS2TnGE1SVPbuI/i= rv8XbsRN90QIC34NiGXPL1fgvHKJw+8cwNq7H+uwn0ee14Ty9A627i2BgAGvr23BzBbynf4759p= tmUkyr+4aUaMkEwjTxR0dBqeoynG2jze9CxGOIZLJaMRkECDuCithIVPUDDgKwLx7ijUaj+J5DX= 18f8VQNo2dOUtm4iYZLL539Ys9MRbStbTYKF21vp5zLoI/UoCVaeH7X33H1dTed/2CgquatGxY3= sXpBw6xnke9XP/u6lE0sYtHRVIPj+ahpYQOga4Jk1MQwTa6++upZMVQul2f3IU3TzulZ5HkeiUQ= CKSXZbBbLsrBte/Z1r732WiKRCPl8nmQyyeTkJNFoFF3X0fWqzceGDRtwXZdoNDrruzRXDM0gHa= /jxJknMbUplra3UxOvZXFrI34QcGpsEs8PWNm1jvnNC1Bq2nNNSJiuCpuZaIVCCjH77Zyd0tnqM= QnTvxXVaKsKXkxWnjneSCmnl51mnvvFmJ+QklQ0ja7NbelFqYCIGeeSzrfjeiUyhUFGCycIAhfJ= tB3JtLFidfvq0azi5smVR4mYKZpTC9jU/Z7qkhEBYg6uSZmpIt/47oOYwkAFIKQiX3RRQcD/uf9= JfKEwdI1dz/dz6Pggngsl1+E7dz2CFwhsy+RQ3yj93/0pZdcjFjV59kA/R44NkCtWLyK//f3HcB= wXX0HU1nBLknTEnF6Kljz21At4gaJSdqlPmDgu+K7H/dt2UfICJIKaqIYQGgSCkuuf49B9IYQQm= LpJQ/LFCxvHc5jfsJz9/cdm5/NMZpLBzCAddfPRNR3XdYnH4vzOOz9MuqYe13V45IkH+Ndt3+f3= 3//HVSuMUoFHn3gAe7rq7S1vuhkpX51fVyQS4aqrruKqq646Z+znQ9d1Vq1axapVqy667dmo6dy= hJjtOsx1n1+QZNta2ETUtdK26FCeFIOdWuLF5IY+N9ZN1K8QNA12T1NkxKoHH9swprmmYz7BTxF= MBTuBTCXz8IKDVTrAjM8DieC2WZgAKx68KIjfwcAKfOjNCxfcZKGVptePETIt50RQ7JgeJaQbz4= zXkfJdABTiBR96r0BRJcMYpkjRtYrqJ9Zuek5SdyvIP3/oHFvQsYN3G9Xzpz7/EW69/K729vbiu= y65du3jksUfZdOUV/PD7dzM8NIxt26Rr0nieR7lcBsFscpoQglg0itR0lApIJJKMjY7iuA5QrVi= or6vDcR18z6PiODiOAwp6e3t57++894LjlcInEvGJRvXZ0lVd11ixqqG6/Db7jVPYUYgnHQQumg= appMAwPBAKQYBtVHjrjXE+9/lOdOOlVvdTWZ/yZw7gT1v9SxmQTASYZtU8c2ZZr3qfIp3WiUV8v= Dl4eFSrfRQ93VmkHEUTiuamCvF4kYoxBvjEYv1ky/9MvhLB8zNIawoAU3e5csULCOHjeSaJaBHH= 15CiKh8TkRIbFxzC0AKkDCg7JobuEjErtNWOIoXCNAIKFRNT94hZFeJ2AcvwyRVtepp9yp6BZTh= EDIfWmnGEBM/TSUXzc9qvZggmJ6k89ChidJTo5z8NlgVSEgwPo3d3YVy2Abl2FTgOQT6PTKdxf/= Yo/vAY3j33EwyeIejXqlGhs645hVIoz0epABmJohwH/7nnUX5QzUWyTBCSYHQM0daM1tCAPq/9H= HF3sS+mEIJEMkltQwO7nt7O2975TnJTGXY99lOuvP4W4qmac8v/Z/5QCtcpkRk8TKSxk6d27iIz= OsbKNete5pUU5VyGY7u2EQQBqWSSyy67nLGxMR578jHSNTU0Njby5je/meGREf7tgX8jnU5jWhb= DQ0N0XXstgqoPkmmaJJNJkskkhUIBpRTxeHx2nLlcDtM0Zw1bZ0rez77KjUarV37pdBrgHD+mGc= 5321xprevkYzd+llNjJ9i2+5/Z9uw/c+P6W0lEa2ivq2FoMkfMtojaMcbzQ1i6zVD2DE2pZopOg= VKlRDKaouyUmCpNEDVjWLqFrptoUkMKSb6UI1ucpKOxm0xulIgVw/UcPL+atFqqFEnHqn5sZbdE= V1MPg+OnyJWmSMfrmCxksM0IqWgt+WKWdKzuAhduLxIoj7HCXjLFw0hhcmn3jShlkymcnhXQgQp= QKsCbtgKYWU7UhMa6jpuJmkmELDJSfJrhQkB9bDm10cVIcWGhpIQila7FLytct0KqxiKW8qhUXF= LJGIGviEcrGNKi5FawTMnEVIGmlka8wCWe15FSR0hBvWETBD4+PoamqBEGE+N56uqTDAyOEHiCe= CJGtMmiUqwQjxooNIoVl8xEFiE9FiyYT3ZiioipY+qSQwMZ6tJJLFthW1FcJ6B/cGxuF1wvgy51= mlLt+IGJN+2OXVCK0ezErGgC0HSdSCRGLJZAKcX8rsUcPrpvWkwHnBo4jm3HePNVN/PAtu+zcf3= VJBM1r2pMM87aMyatwLTPnjd9vjr39HwhUTRTSPCLlaaVwEdHUnAd1qZbcIKAU8Uprm/u4fnsMO= niFCtSTUw4ZYbLeVrsOPPjaWxNZ/d0hGdxop5F8VoOZsdotmLkvAoTlRJ1uo0b+CyIpxks5Xhq7= BTtkSRt0SQRIfFVQNatkJQGtmZwfXMPz00OMVTMYU/nSq2Qkp2Z07RGEriBjyYkbVacg9lRNtS2= M1Qp8PPxAeZFUyyvaYJXVaTwyzFnkVSpVOjvO0nfiRNc/ZbNrFi5nF17dvP4U09MH2ATrFqzmkc= ffphndj6D7/l0dXVx69ZbGRoawrZtHn/8cY4dPQZUP8wrr7yS5cuXUywWOX36NLlcjoGBAQBisR= hvuuoqcrkc8Xic/fv38/TTTwNVv4mLVdMsXGhz++21LF+Wml3DrAqWmR1t5reirdXijz/ejmUoI= hHJzW9roKXFI5kE35e873ejXHddE7GYmDaYPHdn1TSN2z80jxPHh4nFBGvXRJnfZVCbfmnulBCC= RQtj/PGnWujtnUOTSlEVXcuXHGPZ4pNA9f9QzTkChZQeSh2cjocFSOkiBBi6T2vtyyQ8qmrArO1= l7k9Gymf9XZz92zbcl9w2QyJSfsltc0II7Ms2or39Rkp/+n/j7z+A+Y6bkWtWUfnWP6ItXUzkv3= 0OVXFw7rqXIJfHfsvVlP+vP8dYuxrjzVchMxNU7vsR3v6Ds0miSgUElQrekaOARO9dOF0qFYVAV= SNuUkIQIOvrwbSQpkk1Q0m+ooNyJBpj/aWXs+eZHezZs4d1a9dw4uBefv7og6y5/M2kauvOcdIO= ggC3UmJqbAA72cCxvkG23Xcf8xf30tE1/2WmqZpcvee551izZg2+73PHHf8v73vf+/jH73yHT37= yk3zve99j8eLFJBIJHnnkEbZs2UJHOs3999/PjTfeiOd5PP7440QiETzPY8GCBezYsYPGxkaCIK= ClpQWoiqREIsGZM2fo6uri5MmTLFq0iIULF74mPafmQsxOsLB1CXE7znPHf86+/t30ti9ncdtyb= MPANnTqEzH8wOPgwH6SkRSO71As5xmZHCQeTTGZH0fTdI6eOUCpUmBB8xJs06Yp3Uq2MMlYbpTx= 3AhtdZ2cyZzC0C3y5Rx+UC2HzxYm6WiYTzJaw2RhguZ0O6fG+jgw8DyrutYzOjVMPJrE0C2eP/k= MLbXtc3pvCii7kxwZ+2dcv0jCbmVd2ydIWo0o5KxAmokkzUSVPBUgpca89AqylYPsH/4uRWcE20= iRjiyc02uLICA3NUVQATSDsdE8Qih8P6BUdHAdhWkayMAj0CCfd/E8l6HhcaRUuI6i7JcwNImpl= RFoKOnjug5S6ASBYnwsi+cG+H5ANlckmy9CoJjKKXTdxJ02+NUCjTOnx/A9lyzVZTW/7JGdKqEV= QNc8CHwCT/LLqCQhBBEjiedZOF71eXxfI19+sc3ITPL28/t3koinqFTKPPXzn3HJuivRpl3m9x3= YxbLe1XR3LiKRqOHw0X2sW71pTlEd13WrXSOCAE3TmJycZHh4mI6Ojtkih3K5zJ49e+jo6Jg1lZ= 3x9Jp5H1LKc0wlhRCMjo4SjUapqzt32TWi6Wxp7q6eG6TGFfUduCrAkhqLEnUECixNoyESxw18D= KlhSo24btIRqyFQCkvTaI+lcKarzNwgQJeSzngaTQh0KdnS3E3Z99BFtXPGFjuGJgQdsRpW1jRh= TD9nsx2vCjchsTWdlkiCzlh6Osqr0IXk+paFeCogohlc07QAJ/DRhMD8NQgkeBUNbnPZHA/+248= 5sG8/q9euobGpEd8LONXfz/333cfIyAjBdGLlTMmv4ziYpsnBgwdnn0cIge/72LaN67o0NjbS19= c3e7+UklKpxJIlS/B9fzZaVa1yuzBCCFasqGfZsvrZaM4vbHHWtpJ4XPKud3UiAMPUWL4iyZKlC= QxDopTJH/6XDViW/rLW9KYpuPTSJBs2JNB1yZs3tyGlwDBeejIRAtJpg9//j73TBpQXey/VHyld= 4ELv/eK9g8594l/qwuw1R1gWxppVuKtXUv77O9F6FxH575+n8NE/pvB7/wmtcx5BNovKF7D/4D+= AaeL39xP9n3+BfcO1+KNj+AcO4f30EYz2FoLhUfJ/8T8gUPhPPoXxljejLVqINE3Ekl6C8XH8Uw= MoTUf4PtgmamwM3/cJNIkxvwsZnXslha7rrFi7np6ly3jy4Z9WjfA2bOTkC/t46sf3s3jNWprnd= WFFomhSVn2J8jkw4vT3n+Ifv/HXZPNTfPjdnyASjb7sQTcWi1FXV0d3dzednZ3cddddeJ6HUopt= 27bUHzg+AAAgAElEQVSh6zrJZJKamhoSiQRNTU20tbURiURmzeYKhQLHjh2js7OT+++/n56eHrZ= v305tbS2ZTIZdu3axadMmxqbn49FHH6Wjo4P+/n56enpei497bkxf1DTWtHD92lv4u598lf/vJ1= /jYzd8hsaaHhpTSWqiEQLl0tEwn4gRZWTqDKlYLXE7gSKgJlZHrjTFyq71VJwy6UQdumagSUlL7= TzikRRxO46Ugpp4HTWxOoLAp+yWMHSLslMkZieqy7QqwNTNWdFUG68jYkWxjAiWbrGm+1KMOS61= aUKjMb6GpsQ6Tk08xlTxJKP53TRGr8ChKob86UiD779oKlldYtcIApfh/C4KlWGklMyvvY7aaC9= iDgnjAIZuEY1LcgUXoXSSqTiuU2FiIodtmdTUJMgXCwgFiVgNfuBVoxUCIjGdydNjJOpqcEsuia= SF7znEbIvxiQKJRByp+aTNBAidQtEhGjFxHAcRuOQLFZAa6VSUqG3huBUSqeh0AYpOJBrBcz0CR= TU/L1D4udJMguarQqEoVFwqro47faisLlWfO1+FQo5jxw8QqIDdzz3Fbe/8j1y24S2AIDMxSt/J= wyzrXYvnuaxdeRnbfnYPS3vXEIvGLzqGHTt20NzczEMPPcTmzZt54YUX8H2fXbt20dfXx9VXX80= LL7zAyMgIl19+OT/5yU/QdZ2enh6effbZ2Yusjo4ONm3axPHjx9m1axeFQoEFCxbQ29v7EpEkhC= By9j4pQJ/21LLPul0TnCNChBDYmn7O/cb0/cZ5xIomBDH9xYt+XTt7Xl/c3tJ0LO1c2RE9T2XgT= EafnBZhv07mJJKEELS2tnLddddRKBRmb3PLDmdODVYVoNRYv279OREewzA4cuQIlUqFQqHA5s2b= Z+8XQmCaJv39/QRBgG3b9Pb2zh6EZ8qJjxw5guM4KKW4/vrrUUrNtke4EIYxd9UpBFjWi9vruuT= FSKcgErn4h6TrL25jWReeViHAti+8jaHFWd7wMbpSN1/0tX/TSUeWv7wg0zSs67egLZiPbKgn8r= lP4vzT3eB6GIsWkvg//4D7rz/GfWY3en0d5o3XYaxZhfPkdqzfeSfGpkvBtpGNjVjv/x385/chl= i3F2PIm1HgGmUwQ+fTHMa95CzIRr06+JsEPUBOToBvguviex0zemAJUWxu8ApEkhKAmnebdv/sh= vnZqgAfuvYsTfUd5+9Z3oymPg3t28/zO7SQSCZLpWlK19ehWjN07f86P7rmL/FSGW97ze6xee8k= Fr0pnvJKUUgwODiKlJJlMYlkWt9xyC3fffTf79+/HNM3ZC4qzr5R1XWfRokU0NzfT0NBAS0sLJ0= 6c4Morr2RiYoLa2lq2bt1KqVSioaFhNiF779699Pb2znk+Xi0z7mdnZ+lqUmd+0yI+cPUfcPdT/= 5uK6zBVLDO/MT19MLZY1lF1Iu5uXvhimeU5TFdZiLNyiKq1oSi1AiEE7XWd0wUSLz0ZzzxKIEjH= a1/cU84pQ5xpUzSXyw+BpSdZ2Xw7rYlLyTknZ0vzA+XjKx8vqP52A49ABQQqwFcKX1WjXAlrHst= bfpeU3UV9bAW6tOe01IfSqQQKw/fw/QBNN3H8AF3XsKMGsWiEQqkIQlH2fEoVBxlUrQqQAa6v0A= wNVwUYtoGimpQbCCj5CksJolLDc1wMQ0NT1ZS/qF3taGArnXzFxzAiBKKE6wmCQOD6iorrYRogN= IFSGo6vkMJEyJdGrl8RCiQGrmfgTkeSNE0ihMns/iAErS3zuPmG95JO1bFq+Uae3PETLtuwGd/3= eebZx9l7YBenB0+i6zq+79N/+jhHju1n9YqNFx1Cd3c39957L5lMhoceeoiamhoMwyCZTLJhwwY= OHz7MTTfdxJNPPsmhQ4fYtGkTp06d4vDhw/T29pLNZmlvb2fv3r0MDw/z8MMP8773vY9HHnmEwc= FBOjo6frk5CjkvIpPJKKiKkmg0+rItBi62vPXr4o3QtynkjYPv+zy3+xn+11/8d4ZP92PaUVasv= oQNV1xFe0dH1QguO8mBvc/z1MMPMzQ4gGVZbH7rzXzwD/4z8fO0EJkhCAJ27tzJpz71KSqVColE= go997GNMTEzw9a9/neuuu45cLkc+n2d0dBSlFF/+8pe588472bFjB5/97Ge55ppr0DTtHF+d83n= snP19Hx0dZefOnVxyySU0Nr7yap5XNH+BR6FcwDYjGJpxzhiDIKBQyWEbEaTUpxti/3Z//2cEmV= I+Q9lnsbUWir7idKVIJjNGvZUik5ukt62b/uwQIhqhWRekrQiaDEjYbUhRPWbPZS5OD0/y3/76f= voGz6CCaoUdgQACgrMLDMSMr5GYjjpXk9eF8qtJ7UIAVjX/TwD4VZEXVC8WhZzuYs+M0ehZeYJC= ECCplrn4VMUlVTdJACmrOYRKVsuLAcPQ+b2tV/K2zWswX8EF8Ow8K8WB033852/+BaNTkwDUJVJ= 8+QMfZePCZWhSY2j4NN/74d/yu+/+Q2rTDThOhb/9+y+zduVlLFuylr/7zle45Yb309O9hJmKgD= 17d7Bj12P8h/f/8bQB5ctTKpX4whe+wNatW/mnf/ontm7dyt69eykWi6xevZrR0VEsy+LZZ59l+= fLlVCoVxsbG6Onpob6+nlwuR0tLC7t376apqYmTJ0/S1tbG9u3bWbBgARs3bmTp0qWveG5CXsTz= qgVqZxewzFkkhYSEzA3f9zl+5DDf/fbfcfD53RRzOTzfh+l8tkAFCKWwLZv65jauu/kdXHPTzSS= SqYtGkWaWnoFZDyPf92d7sc1UYjmOg67rsy1HZqJIZyeJvhLOjgC/3syYDp7vtX6V43g9UUpRcR= 1KlXK1VFrXKbonsbQ6ykox7jrks1lSZoypYp622loG84MIy6Ze16ixatCkImLV4wVlDBlFiosvD= Liuz/hknop77vL8+WJvF+fsz+BCj77Ys7/8/S8G6QSpRIRkzH7Vn70f+Dy091l+uP1RfD/gres2= cu2q9cQj1QKE8cwo2352Nzde9+7ZZOyBwT7u+9c72XL1LRw49BzXbH7HrLu2UopCMc+dP/hrbn3= bB6mva77g6yulyGazRKNR8vk8tm1TKBTI5/MEQUBjYyPj4+OzRRX5fH72vHx2HqDnebiui23bjI= 2Noes6sVhstvo05NUTiqSQkF8RVVuMHIf27+XnTz7OsUMHyU5NEqgA3TBpaGpmzSUbWbfxclrb5= 81WkV2MXzai+9suLt4o+L7P0y88yz1PbGN55yJqEinWL16ObVrVXKTpHKgZU0rNGOfg2J3URZej= qDAvtRlDixAon0Pjd9KVuomE1YahxcPP+AIEQUDJdQgCRcQ0z4lG+r5PxSljWTbadN5NEAQUCjl= Mq1rFZ1vntv9QSlEqFzENc86u2yG/uZxPJL3ixO2QkJCLU80VSrH+0stZte4S8rkcpWKRIAgwDI= NEMoUdicxeIb4Sx96Q336EEJiGyVBmlCXzFtBSW8/f3Hcna3qWMTQxSraYxzYtoqZNyalw42XrK= VSGaIytIu9McDRzDzGjCSkMCpUzDOV2Mlk+Smf6GnTxGjTefYMipSRmnT/aomka0UjsJdsnEi9v= YyGEeMljQt5YhCIpJOR1RAiJaVrU1lkwd1PkkDc4CmavVtPxJJnsFIOZETqyrYxMjqOUYmPvanY= f3sdUMcdYNoPUJbXRxbSlLudI5m6K3gi6iCKExNZrKbqDswazoZgOCXltCEVSSEhIyOvMTCn/TN= 5YEASYus6WNZvwg4CIZXHt2iuJWRFqYkl0KVnU3oVtWmSLOTqbGyn4WzBkEkuroym6gZI3jiZsE= sYCkD7tybcgMc6pgJRvgOT2kJBfJ2FOUkhISMjrjO/7lMsVgqAqlGZFjKadVT0W4HlVTyQCNeue= bFomnucRBN50yxOBH1TbzgTTOWq2ZVVbULjerA2B7wfEYtGXuDCHhIScnzAnKSQkJOTXgKZpRF+= B7xZAECgcJ0AKQcQ28byq87ZhyJc1obXCdKSQkNeUUCSFhIS8LH5QbS2h69pse5+QV8crWfbyPM= Xp0yUGBso4nsuSxUkGByuUKz6LFsaorbVftgNASEjIa0cokkJCXgUzXkRSytdsiToIFGXXx/erX= ejzJY+RqTLt9VHS8blZBPyyeKraU8tzPfLFCqB4bPdRNl+yiKOnRlnc2UTil/Cq+ZUSBKhyFlXK= os5qYno+hBVDRGt52RDNq2HalfGVzFW57JPJOFQcn5N9RVatqmF4uMiRI3nWrEkzcLrMyf48Sgl= MUxKL6ee4/YeEhLy2hCIpJORV4DgO3/nOd2hqauLmm2/+pZu++n7AsTN5Dg5kcT3F0ESRoYkypq= 6x9Yp5pKIGmvb6CpOyH7BtOMfRfIVbaiNkx6doaEpT19FM0QvYse8kdak4JwbHmd9aNyuWlFKUK= x75UgWAeNRC1+S0B825ERTPDyiUHPwgQAhBImKi6+fPmfllq7SC4gSVh/8Gt/95CHyUZiIiSVRx= EkEAmoWQEuU7iGQTxrWfRMYbLtrU8JUYLwoh0Q0DMYf9QynF0aN5PE9RLFeoq7OwLEmhELBiRc1= sRx1dM5icdMlMOCxeFCeV+tUI6JCQf4+EIink3xXnc2x+ORfnC21bqVT40Y9+RFdXFzfddNM5Jo= 9zPWFVW21UhYAXKI4NZultT7Dr6CSOCzdvbAOqCbi/SBAoAqVmT9gCkPKVRS3OGQuQ83y+cXyM5= zJ51mycz250RgeyHM9X+HjU4tYtawHF5//6X/j4+7ewdsk8QDE2mecnTx+iq70e1/EoVTw0qVi1= qB3HDWiqi2Po1VYoZcfl/sf3E4vaRC2D1YtaaEy/1ACx7LgMjWbpaEm/agGqSlncvt34uVFE3Xx= INGGs34rzs79CRJPoq25GGBbuwUfwDj2CmDgDZnK2U/uMSJtJ4pwZx0xfydnX+QUxN9O1XQiJYe= houj6nZtJKKUoln0WL4vi+TSbjks26JBI6rqs4fDjPvHkRWlsjaLrg9JkixZJLKnXhPpYhISGvn= lAkhbyh8H2fAwcOMDU1NXublJKWlhYMw+DQoUPE43EWL15MIpGgUqlw7Ngxzpw5Q3d3N52dnUgp= yWQyHD58GIClS5eSSqVwXZf+/n76+/tnH+v7PoVCgUOHDlEqlVi0aNFsY9gLoRQMjhf5/qP9XLm= igVXz09SnLH7y7DCpmInreYxnK1y9sglDl8izumqXHI/H943yzOEM/nS/K8uQrO1Jc2lvPTH7lb= ceyXk+24bzrKiJsLomyncGsqxMGHRGDTpiNoZpICQMjWb54kduolB2OdI/SkdLmp/sOMS85jRrF= 7UBMD5VYHg8x/B4jgeeOsitb1lJxfGYKpRprU9Srji01SfoaKnF0CQ79/cjJSztbmFgeJKh8Syp= uM0/P7yXP9i6ieGJHKWyS0dzmolciXLFJZ2I0N1ef5F3FVSX2RLNmFfdjnP0afA90E30S34Hihm= cXfegsmdAKUaGh9mx8yhXv+kqnnpqO6VSiWQyyXN7nscwDFavXkV/fz9XXLGJH/94G0GgaGioZ/= /+F+ic7suXyWS47rpr+OEP7yUai/O+972bjs6ui85/ECiOnyiSL5TIZEzSaYNCwadYDHBdn2PHH= NraDIaGSpw+XcLzFIYumZoMSNf42LYWRpNCQl4HQpEU8oZiYmKC2267jYGBAYDpsmiX1tZWPM9j= cnISTdPYsmULf/Znf8YPfvADvvGNb1CpVLBtm89+9rNs3LiRT3/60+zZswff91m2bBnf+ta32L5= 9O1/84hfJZrNIKfE8j46ODj7wgQ/w8MMPI4Sgu7ubr371q1xxxRUXEUqK4YkKj+wdJmJp9M5Lcn= K0RMXx2Hx5Oz94fAAvACkEmqz2dleq+n7yRY9/2X6KfX2TLGxLYeqSvuEc/7ZzgI/ctIi3Xz4PQ= 5Oc3cHkF5e9fpFTBYcvvXCG5ojBpxc3MekrkhIqSBSCH44V6bJ1bqpNoLyAz/2vf6E+FeVPP3wD= R04Osa53HpZZFWe2ZfDY7iOs7e1AqYCR8SwPPn2QLRt7ue/hPQTAMy/0cfTUKG+9Yim6rvO9B3d= x/aVlsvkSy3vayBfLKBXQNzjO9r0nuGZjL3f/9Fk8X9HWlObSZXPreC6sBHr3pVQe+zv0jtVoiV= q0tuVotR04fbtQ+TFUbhwlNcqVMiMjIziOy8jIKPl8Hsd1GRkZ4fLLL6fvRB8HDx4iGolSX1dPU= 1MT8+a109d3kq75XezatZt0Os2RI0cZz0zguB4TmYk5iaS+vgKZ8Qq9vSlOHC9h2xqnTpXJZBw0= TdDREWFszKWpyaCzM4ptV0VzJuPyxBPjvOlN9RiG9pqmVIWEhIQiKeQNRl1dHdu2bSObzeJ5Hs8= 88wyf+9znOHXqFLfddht/+qd/yqlTp/jCF77Ahz70IaampvjSl77E5s2bueuuu/jKV75COp2mqa= mJBx54ACkln/jEJ7jttttwHIfbb7+dW2+9lUceeYQvfvGLbN++HYDvf//7NDY2cscdd3DHHXewf= Ply6upe3mJbzfw73SA9W/QoVAKuX9/Czw+NErcklYrHvU+dwtAlN1zSiuP6/O+H+ljWmSIIAtrq= I3z+Pctoro1waGCK//q3u+gbLlIs+wyO53h4zzBj2TILW5NsXtNMY+r8FVEKaLQN/nBRE622zuM= TZd7WGKPe1OiImuhScFWtzdHJEtlCicHhSf6fP7yF8akCsYjF4q4Wdh8YoKUhhalreJ6PoWsYhk= YiFkFIQb7kYlsG73jLGh7cfoDe+Z2sXtzOjr0nOD2SxTYMJnJllFI01caJWDqpeBTP92lMJ0hEL= Xzfx7ZMejsbmdecntP+oAKPYOgwZEfQezaB0DCWX4uwYsjGHrzMAG5mBNcT+L6iUqnw3HPPUSgU= zhKVAqV8Bk6fxvM9hoaHaG5uxvM9kqkkkUiEZCIx23BYKSgVi0QiNvUNDXMap5SCpiab2rTNRE3= A9u2THDuaZ35LmUvX2liigC80BsYMBjRBLKaTThtYtka57J4jiENCQl47wrKIkDcUQgja29tZsm= QJkUiEe++9l1gsRmtrKx/5yEdobW1l5cqVXHvttezbt4/Fixfz9re/ne7ubj74wQ/S2NjImTNn+= OhHP8rGjRvZuHEjH//4xzly5AjpdJr3vOc9LFmyhHe9610sXbqUAwcO8M53vpMtW7awZs0abr/9= dk6fPk0mk5nLaGf/SkUN3ryiAVPXaK+PsW3XICeG8/SPFLj3yX5Gp8o8czjD/U8PcHq8iFKQK7r= sODjGI88N8287z2AbGkvmJRkcL/Klf9rHiaE8Xc0J7nv6FP/zngNMFpzzjsJXisdGc3y/f5wgUC= xNRmiwNFoiBoZWdWyut3SWxHRilsHJM+PsOTzAZ792D4dPjvDWTUuJxyzue+R5Hn7mKAMjUzTWp= YhFbdJxi5htcumKLvrOTDCVL5GIRfECgaFJkvEIUgoWz2+iu70ex/V5dPex6Z5YJs31KZKxCEdO= jbN5Qy+tjWmKjn/e93FeAh/KOUS8Dlk3j8que/BHjlE5/gzZB75GYf+TOI43XS1mUpuu5dTAaXT= DpKOzg8bGRhYvXsSGDRvomDePyy+7jKamJk6fHuTgwUNIIWhqbKCxsZGG+nomJyfp7p7P2rVrWL= qkl8x4pmoOeRHa2iKMjVV4+ukJXFdRU6ORjAWYRx7l5H33cOyb3+TQ33+bqR0P4zkeqZRBPu8zc= KpE+zwT03x576SQkJBXTxhJCnlDMjk5ybe//W3Gx8f5zGc+w1e+8hX+5m/+hpqamtm8JSEEsVhs= toTfNM3Z/8disdnlspqaGjRNw7ZtbLvaHNOyLCKRqjlgKpVC06o5IdFoFOAcx9a5oGuCeQ3Vx45= NlYlYOqahsWZBmqcOjHLwVJanXhgjFTVY3pli+wujTOYd7nnyFLomOJMp0VBj09EY5emDY4xny2= xYVIdtSBa0JDkxlCOTc6hNvNRtUCJYmLDZWBenK2YipCSpaxQKZYyoja5LgkCRLZSpVFzmt9Yhg= LVLu2hIx0lEba6/fAmTZRdLExiaxsLuZhSC7nn1SCno6mhE+QFKStpb69CkQEnJsp5WerqaCYRA= CsGirkacQBHRNd5/0wakFDQ31hAECiUlC7ua0IWYu0eQ7xKMHEFfuxUVKMojp4ivuAFnz4P4lTL= VEv1qNK2pqYlbV1yBcksIqYHvIjSNKy5dj+YWefe73gFuCUU10V74DnYiyi03XINumNx641tQQm= JG4nQ3xNBiafRonIuWy1H1RQJobjYZG3Molz0KRR9iNRABK52G2jp8GceOaOTzHnV1JrYtGR0VB= IF63asfQ0L+PRKKpJA3HJ7ncf/99/Pggw/yyU9+kpaWlnNaQQghWLhwIZ2dnVxyySWzIulXn/ha= HY/rB5QqPn4A1QKq6jikgM7GGM3pCD97bojDAzkuXVJPQ6oq1JpqInxi6xLqkhY/fmaQHz7Rz8F= TWUoVj6otkEAp6G5JsKg9SW3i/FVQUkBX1KTFNjiSr9AYtWiQ8I/3bOfyFZ10tdZScTyGxnNkCy= VOj0yyfc8xGmsTxKMWQghcBPsrATW6ROJRDBQVBVFN4k+vBdUbEs8NmHB9dCmRwidQ4CDwfA8DR= YttkKl4SC3AU4og8BFSQ0NQUgFNpqQ7MjdfKqXA9RSeqzCaFuNNnEFpFsKK4g4eQih/1hdJCDBM= E93SKB95Gq15EZW9D6LVtqE39VA+/CSR3jdROfQ41HdjNXXj7LwLccXvIQf3oTX2wM7vozV0Q9s= yghcewVx4GVZ67Zz2q5GRCm1tERoaLHw/BwjiyQjjrKNzTZyGOp2yoxjPBEQiOqYpKZerCdu5nI= fnKaQMG9uGhLzWhCIp5A2FUornn3+eO+64gxtvvJHrr7+eo0ePEo1G+fCHP8yaNWuoVCo88MAD3= HnnnYyOjp4T9Zkxicxms7MNScfHx/F9n1KpRKlUAqBUKpHL5QAYGxub3TaXy802Fr0oouob9Oi+= EU6OldCEwDI1bruifXaTmpjBuoVpvvdwH0rB9etaMKd9hSxTo7UuSktthEsW1XLXY31MFRzW9tT= x02eHGMwUaa61OXBqkpqYiXEB00GJQBPVn5UJkydHc9xwxVKO9o/Qd2aCVNyi4nj8+Ml9fOCmjT= zwxD5S8Uj1pCxAE7A4ZuJP2xKkVFV8IV5MOrckGAISmiCYvl0IgUKhlIYgwJICgYYhJZ4CKapO3= /70ilVUijkvKykFrgsqUodWN4/KsV0YzQsJijn8zMAvbDyT3K4TxOrRrBiqaTGBGUVYCfxIGhVJ= ESRbQLdRnk/QsqK670TrUGaEoHExIl6LjNXhm3Gw4ggp51T+X1dnMDBQplgMmJryaG+PMDHh4nk= WB0/A0ITE96u+S/kjReJxnULRIxqVWNEKijjny55QSuH7Ab7vYZpmtRqzVCYasdE1jVK5jKZpmI= ZxXoHl+T65QgHTMIjavyUmoiEhryGhSAp5QzE5Ockf/dEfAXDZZZdx6NAhhoeHkVJyxx138PnPf= 57Tp0/zta99jb6+Ppqams7xvJFS4jgOf/mXf0ksFkNKyZe//GVWrFhBNpvlm9/8Jlu3buWhhx6i= r6+PG2+8kbvvvpuVK1fS1NTEX/3VX9HV1XXBpG2oNjRtqolw5YpmhiZKeF6AC+iaxDY1lnSkaKu= LYpsam5Y2suPgGPUpm57WBH4AvfNqyBYcYla1oqmrOc6annrSCYtlnSk+dsti/mX7AD/aMUBbXY= wbLmklar58tV1MF3yoK83jY0W+1TfBH3TWMOVEKJ0e47v/+jTJeIRl3c2sXdLJBz//bd68YQmf+= 9D11CQiCMDUJE2zwvAXc3DOPbGmXhIImtm+Or5a4xeNr8+1b5x7exQBQqLVtSMiSdy+57BXbsEd= PIRySiCNs7asrrlJ0yK2+DIAzHRr9TmkIF0/D6EZmOmW6QcI7Naeauivrmp9kNpwS/WZhMS46n0= ITUcIOScX71jMoLtbcuJEkc7OKIYh6eiwMU1JNutRqVRd2Ht745TLPvG4zuSUyyNH97Nt134+F9= 1Me30tgVKk43EAxiYmyWSzHBoeIVsuc9O6NRQrDl977Ck+umkjrbVpfrBjF90tzVzeMx+lFGfGM= zTWpDANg2K5zNGRMb76xNPc3DOfm9atxtCqfldThQIANdOvVZ2SV+/TFRLym4rIZDIKqieHaDT6= mrVYCAn5dXDy5EnWrVtHLpc754Dd0NBANBqlv78f27a5/vrrMU0TwzC44447SCaTTE1N8fu///u= 0t7dz/PhxHnvsMZRSXHHFFXz961/nmWee4Qtf+AKnTp2irq6OP/mTP+G9730vn/rUp7j33ntxXZ= d169bxla98hfXr11/QAkApGMuWOTaYpSFlY+gS25AUKh5BAMWyRyJqIBCkEyZnMiUqrk9NwiRia= EwVHBJRg7LjoxA01diMTJWRQiAFuF5AECikFBi6xA8UTekIlnGBMQHbxwvsnSrxrrYaJl0fpvI8= 8exRNq1eQDwR5ed7jvGxP/8uW69Zz59/7BZs6zf3eOEOH2f8u5/B7L2SyLqbKDx1F8KOo4RAeQ4= qN4aM1yITDZSfuY+ad3wGs2Pla3qiVzCbr3bRbZVi374s3d0xPE9x4kRhWiS5LF2a5PjxIo4TkE= 7rdHZGyGRcXjjdx/94YR/tymNoaIioaaDpBqZtUSiWODMyQs5xEXaEZW0tLG1s4OB4BqEU7VGb/= RM5NCmImQamEBw4cYL5ra3MS9dwNF/khkULeGZsgmw2i6iUsSM2ZcdlbHSEmkSSWCRCyQ/QDJ3b= L13PZUt6Q6EU8luL53kUCoVzVhdCkRTyhsL3fY4fP06xWDzn9traWuLxOH19fUQiETo7OykUCvi= +T319/azL8vDwMJFIBNM06evrA6CnpwfTNAmCgNHRUYaGhqivr5/NdXJdl5MnT1Iul6Ww9S8AAA= QYSURBVOno6CCZTAIXznFSCjK5MidHCjiuDwh0reqJVHZ8dE1Qdn0MTdJSG2UiVyGTd0jFDFpqI= 4xOVihUXCxDo+IGLJmXZP/JSTRNkowYTOYdpKw+pxcoamIG7Q1xEhfJ51GqWov12FiBbaMFPjq/= lh0TRTbXx3g+77IyplPKFqlLxTCN32wDQ784ReHx7+KMngRNxy9MVl0XAg8hdQg8EBKkRK9pJnH= NR9BiNa9p/zYB1SW3OYqk4eEyU1MeIBgcLLN+fYqxsQqjow7LliXwPMXBg3kMQ2Dbku2n97Dz9A= DDQCQzxolihUp2CjMWpykeRVeKsoJAN9AiNlekkxwrljmWmaSYy9La2MjAVBZ/IkOquZmobVMol= sl5LslEkiub6hgrlzmWLTJ24jjzu7tY2tzE4MQkg/kiSQKOjWVQmsYX3vZWblj92orMkJBfJaFI= Cgn5DcL3A/xA4QfVprJy2jTS8fzpnmjVk6xpSBwvQMpqnzTLkPj+TDMScH0f29QoV6qJyFJAoAC= lEGdVgdmmjjbHqjAvULgqIFCCSden3tQwpscHv44k91eOUoDvonyHCxsJCdB0hP76tPd4JXMVBA= rPC/B9xZEjeVpbbQoFn9FRh/Z2G6VA1wXptIkQUHYcJvN5TMOg4lYbLqsgQCCqwl8pgiCY7vsmk= VIjCAL8IEAKcHwfTcrpHWZ6rEIwODHBE0dPcMWiHtpqUkgp8D0fKQWJSJSy6+D5AYEKUEE1B68m= ESdivbR6MiTkt4VQJIWEhIT8FqCUolj06esr0tRkkUjoDA1V8H1oa7OmfZFeP6E6I6S06SjYb4M= oDgn5ZQlFUkhISEhISEjIeTifSAodt0NCQkJCQkJCzkMokkJCQkJCQkJCzkMokkJCQkJCQkJCzk= MokkJCQkJCQkJCzkMokkJCQkJCQkJCzkMokkJCQkJCQkJCzkMokkJCQkJCQkJCzkMokkJCQkJCQ= kJCzoM+l438IODMaJ7xqdLrPZ6QkJCQkJCQkNccKaC9KUlNIjLnFo1zEklSCGpTEWLRsC9PSEhI= SEhIyG8fAoja+ivqYT0nkSSEIGobRO1XObKQkJCQkJCQkN8ywpykkJCQkJCQkJDzEIqkkJCQkJC= QkJDzEIqkkJCQkJCQkJDzMCuSlFIopX6dYwkJCQkJCQkJ+bVwPg10TiTJ9/1QKIWEhISEhIT8u8= PzPIIgOOe2cyJJruu+ZIOQkJCQkJCQkDcyvu/jed5Lbn9JJKlUKuH7/q9sYCEhISEhISEhvy5mt= M/5RNJLfJJc10UphWmaaJoGVH2SQkJCQkJCQkLeKCil8H2fSqXyssGh85pJep6H53kIIUKBFBIS= EhISEvKG5GIpRhd03A4r3kJCQkJCQkJCQkJCQkJCQkJCZvn/AQTqrkP9uV+8AAAAAElFTkSuQmC= C" width=3D"585" height=3D"136" alt=3D"" style=3D"margin-top:23.15pt; margi= n-left:-36.3pt; position:absolute" /></span><span> </span></p><p style= =3D"margin-bottom:0pt; line-height:150%"><span> </span></p><p style=3D= "margin-bottom:0pt; line-height:150%"><span> </span></p><p style=3D"ma= rgin-bottom:0pt; line-height:150%"><span> </span></p><p class=3D"APA7M= AEDICION" style=3D"margin-bottom:0pt; line-height:150%"><span> </span>= </p><div style=3D"clear:both"><p class=3D"Footer"><span style=3D"height:0pt= ; display:block; position:absolute; z-index:-65536"><img src=3D"data:image/= png;base64,iVBORw0KGgoAAAANSUhEUgAAAQgAAAAgCAYAAADufuYQAAAABHNCSVQICAgIfAhk= iAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAAuRJREFUeJzt2l9ozWEcx/Hvz59CsawsZaUhqcWFckN= uVpILV3KhJuJOUlztZq1EWkKucIEipfxJitSYxMVqRhMbml2MWdL+mDazcd4uzvfXnv2cNZ12dm= bn86r1nO/z/f2e5+lXz3P2PL9jJiIiIiIiIiIiIiIiIiIiIiIiIjMD0A58ZtTVIHeesapyNIbXQ= R/XctGHiGQJqAZ++gQdAY4EuUqgC9idw/43Ab1aIESmIV8g7gL9Pkm7gc1BvmEKxtClBUL+F7Py= PYA86DOzs2aWMrNiMzuX3+GITF+FuEBYFEXVZnbPw3LgVqbrgJ1ACzAMDAHNwA7P3QjOE14Az4F= B30LUANf9P5VhoC5D88uBj55vi7c2iXYbgNvAD+CV5yuARmAA+A5czMEjEik8vsW4EsStPhF/ea= 4hyC0EPnn+pE96gC9Aqf+1eV0PcBCo83gAuBTck4q3MsEWownYAtR73On5FcC7uM7bbQOaPf/BF= 5UDwEPgN7Bvqp+lyIyTYYGo8MkN0BdPQs8d9/qhoC4+uzjjcVP8Te/xZY+7Pd7KqL1eN+YMAjgU= XLPf6xo9fp8Yf5XXt3scL0CPcvTIpMDNyfcA8imKonqg1syOmVmRmZUE6TIvh4O6lJfLsuhu9jj= 1vcHn4kSuJxGv8rIMIKhfmsV4RCZUkGcQoSiKas3sZoZUh5fhIjrXy87J6NrLeHKPmNnTCe7p9r= I3Gqt8EsYj8peCWSCA1Wa23szWABVhLoqiXWb2MnHLaTPrMrP5pM8gjprZAjP7amangFIzW+TXF= nm8xON53sfGoL2VifbXAtvMbLvHz6IoavB2iryuGFgX3HPB0m9hFgOPfYtUE295RCRLpN8YxFIZ= 8huApkRdJfDWDwWH/fMez4VvGwDuJ+IWRn8UBTDo97UCJ4A3pH+09Q14AJSM0+6TxJgOAx2kD1b= 7gTu5e2oiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIi8q/+APOZQO3ffvBeAAAAAElFTkSuQmCC" = width=3D"264" height=3D"32" alt=3D"" style=3D"margin-top:22.28pt; margin-le= ft:45.1pt; position:absolute" /></span><span> </span></p></div></div><= /body></html>