</title= ><style type=3D"text/css">@page Section_1 { size:612pt 792pt; margin:72pt }= @page Section_2 { size:792pt 612pt; margin:72pt }@page Section_3 { size:595= .3pt 841.9pt; margin:127.6pt 85.05pt 70.9pt }div.Section_1 { page:Section_1= }div.Section_2 { page:Section_2 }div.Section_3 { page:Section_3 }body { li= ne-height:108%; font-family:Calibri; font-size:11pt }p { margin:0pt 0pt 8pt= }li, table { margin-top:0pt; margin-bottom:8pt }.BalloonText { margin-bott= om:0pt; line-height:normal; font-family:'Segoe UI'; font-size:9pt }.Bibliog= raphy { margin-left:36pt; margin-bottom:0pt; text-indent:-36pt; line-height= :200%; font-size:11pt }.CommentSubject { margin-bottom:8pt; line-height:nor= mal; font-size:10pt; font-weight:bold }.CommentText { margin-bottom:8pt; li= ne-height:normal; font-size:10pt }.Default { margin-bottom:0pt; line-height= :normal; font-family:'Times New Roman'; font-size:12pt; color:#000000 }.End= noteText { margin-bottom:0pt; line-height:normal; font-size:10pt }.Footer {= margin-bottom:0pt; line-height:normal; font-size:11pt }.FootnoteText { mar= gin-bottom:0pt; text-align:justify; line-height:normal; font-family:Arial; = font-size:10pt }.Header { margin-bottom:0pt; line-height:normal; font-size:= 11pt }.ListParagraph { margin-left:36pt; margin-bottom:8pt; line-height:108= %; font-size:11pt }.NoSpacing { margin-bottom:0pt; line-height:normal; font= -size:11pt }.NormalWeb { margin-top:5pt; margin-bottom:5pt; line-height:nor= mal; font-family:'Times New Roman'; font-size:12pt }.Revision { margin-bott= om:0pt; line-height:normal; font-size:11pt }.Title { margin-bottom:0pt; tex= t-align:center; line-height:normal; font-family:Verdana; font-size:14pt }.p= aragraph { margin-top:5pt; margin-bottom:5pt; line-height:normal; font-fami= ly:'Times New Roman'; font-size:12pt }span.AsuntodelcomentarioCar { font-si= ze:10pt; font-weight:bold }span.CommentReference { font-size:8pt }span.Emph= asis { font-style:italic }span.EndnoteReference { vertical-align:super }spa= n.FollowedHyperlink { text-decoration:underline; color:#954f72 }span.Footno= teReference { vertical-align:super }span.Hyperlink { text-decoration:underl= ine; color:#0563c1 }span.Mencinsinresolver1 { color:#605e5c; background-col= or:#e1dfdd }span.Mencinsinresolver2 { color:#605e5c; background-color:#e1df= dd }span.Strong { font-weight:bold }span.TextocomentarioCar { font-size:10p= t }span.TextodegloboCar { font-family:'Segoe UI'; font-size:9pt }span.Texto= notaalfinalCar { font-size:10pt }span.TextonotapieCar { font-family:Arial; = font-size:10pt }span.TtuloCar0 { font-family:Verdana; font-size:14pt }span.= UnresolvedMention { color:#605e5c; background-color:#e1dfdd }</style></head= ><body><div class=3D"Section_1"><a id=3D"_Hlk150165641"></a> El =E2=80=9Caula invertida=E2=80=9D como m=C3=A9todo de apr= endizaje en la asignatura de historia en primero de bachillerato de la Unid= ad Educativa =E2=80=9CCombatientes de Tapi=E2=80=9D a=C3=B1o lectivo 2023-2= 024 The =E2= =80=9Cinverted classroom=E2=80=9D as a learning method in the subject of hi= story in the first year of high school of the Educational Unit =E2=80=9CCom= batientes de Tapi=E2=80=9D school year 2023-2024 <table style=3D"w= idth:396.3pt; margin-bottom:0pt; padding:0pt; border-collapse:collapse"><tr= ><td style=3D"width:3.25pt; border:0.75pt solid #000000; padding:0pt 5.03pt= ; vertical-align:top">1</td><td style=3D"width:171.95pt; border:0.75pt solid #00000= 0; padding:0pt 5.03pt; vertical-align:top">Alexandra Sofia Rodr=C3=ADguez Oviedo </td><td style=3D"widt= h:10.5pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:t= op"><img src=3D"data:image/png;base64,iVBORw0KGgoAAA= ANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBl= SsOGwAAA2lJREFUOI21lEtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQi= UhUnFqo4cGIRQUGd+KDY+Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe//= /Wv/aiy1cBV/83NNOPr/VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNN= Z+57RTjDTvqFM1IvNiGXWJvD/9x8yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XLleTd648= Z/863v3nkjWCL59dp/fWSsfzOXNkShKacvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082AAzADZXy= Pj+wL8ehQ1NH700v0N35OAroutW0rxDF6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQt= Z0VEU1QTPtmAkDygiEBTsTxq6hx65fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqF= JrzDF5+Sv+Wvg+y+IEVXaGibsbOO5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52= oNtTMwcBbE0YteeC7we4LinSI9Z03dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg1= 7AAwqpRW9fqayNkiM0tjqDrag67mDCi0ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKrR2zreID= URZTrZ7NTBYdeBPAU+cY59zxCkFlXjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYjFGqkldT= 0J4EkY/ZovBb+klbQ/G1zDYvQntXgWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGA= EQV+Wy87xm/xbwZ1lwewGmCIIhYnCZXjKvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2CV8GrRk= NldbNmKbYU2enC0uV6bkfUNUd8P1ury3ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbrXMoncTV= 99smBH5ZW327igzP3trY2ONCyyQ6FtbRLUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fXp1+BVxd= x2um+HGnuX9egX4dY01U0iVK2R80nMaELy42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJgg= g=3D=3D" width=3D"20" height=3D"20" alt=3D"" style=3D"margin-top:0.45pt; ma= rgin-left:-0.3pt; position:absolute" /> </td><td style=3D"width:166.35pt; border:= 0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><a href=3D"https://orcid.org/0009-0001-= 1552-7660" style=3D"text-decoration:none">https:= //orcid.org/0009-0001-1552-7660</a> </td><td style=3D"border-bottom:0.75pt solid #00000= 0; padding:0pt; vertical-align:top"></td></tr><tr><td style=3D"width:3.25pt= ; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"> </td><t= d colspan=3D"4" style=3D"width:370.7pt; border:0.75pt solid #000000; paddin= g:0pt 5.03pt; vertical-align:top">Unive= rsidad Nacional de Chimborazo (UNACH), Riobamba =E2=80=93 Ecuador</p= ><a href=3D"mailto:sofysro= driguez30@gmail.com" style=3D"text-decoration:none">sofysrodriguez30@gmail.com</a></td></tr><tr><td style=3D"width= :3.25pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:to= p">2</td= ><td style=3D"width:171.95pt; border:0.75pt solid #000000; padding:0pt 5.03= pt; vertical-align:top">Freddy Auqui Ca= lle </td><td style=3D"width= :10.5pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:to= p"><img src=3D"data:image/png;base64,iVBORw0KGgoAAAA= NSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlS= sOGwAAA2lJREFUOI21lEtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQiU= hUnFqo4cGIRQUGd+KDY+Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe///= Wv/aiy1cBV/83NNOPr/VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNNZ= +57RTjDTvqFM1IvNiGXWJvD/9x8yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XLleTd648Z= /863v3nkjWCL59dp/fWSsfzOXNkShKacvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082AAzADZXyP= j+wL8ehQ1NH700v0N35OAroutW0rxDF6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQtZ= 0VEU1QTPtmAkDygiEBTsTxq6hx65fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqFJ= rzDF5+Sv+Wvg+y+IEVXaGibsbOO5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52o= NtTMwcBbE0YteeC7we4LinSI9Z03dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg17= AAwqpRW9fqayNkiM0tjqDrag67mDCi0ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKrR2zreIDU= RZTrZ7NTBYdeBPAU+cY59zxCkFlXjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYjFGqkldT0= J4EkY/ZovBb+klbQ/G1zDYvQntXgWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGAE= QV+Wy87xm/xbwZ1lwewGmCIIhYnCZXjKvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2CV8GrRkN= ldbNmKbYU2enC0uV6bkfUNUd8P1ury3ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbrXMoncTV9= 9smBH5ZW327igzP3trY2ONCyyQ6FtbRLUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fXp1+BVxdx= 2um+HGnuX9egX4dY01U0iVK2R80nMaELy42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJggg= =3D=3D" width=3D"20" height=3D"20" alt=3D"" style=3D"margin-top:0.45pt; mar= gin-left:-0.3pt; position:absolute" /> </td><td style=3D"width:166.35pt; border:0= .75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><a href=3D"https://orcid.org/0000-0001-7= 482-6516" style=3D"text-decoration:none">https://o= rcid.org/0000-0001-7482-6516</a> </td><td style=3D"border-top:0.75pt solid #000000; bor= der-bottom:0.75pt solid #000000; padding:0pt; vertical-align:top"></td></tr= ><tr><td style=3D"width:3.25pt; border:0.75pt solid #000000; padding:0pt 5.= 03pt; vertical-align:top"> </td><td colspan=3D"4" style=3D"width:370.7pt; borde= r:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top">Universidad Nacional de Chimborazo (UNACH), Riobam= ba =E2=80=93 Ecuador<a href=3D"mailto:freddy.auqui@unach.edu.ec" style=3D"text-decoration:= none">freddy.auqui@unach.edu.ec</a></td= ></tr><tr style=3D"height:0pt"><td style=3D"width:14.05pt"></td><td style= =3D"width:182.75pt"></td><td style=3D"width:21.3pt"></td><td style=3D"width= :177.15pt"></td><td style=3D"width:0.3pt"></td></tr></table> <table style= =3D"width:436.35pt; margin-left:0.25pt; margin-bottom:0pt; padding:0pt; bor= der-collapse:collapse"><tr><td colspan=3D"3" style=3D"width:156.4pt; paddin= g:0pt 5.4pt; vertical-align:top"><a id=3D"_Hlk92186133"> </a> </td><td colspan=3D"2" style=3D"width:258= .35pt; padding:0pt 5.4pt; vertical-align:top"> <= p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-size= :10pt">Art= =C3=ADculo de Investigaci=C3=B3n Cient=C3=ADfica y Tecnol=C3=B3gica<= /p>Enviado: </= p>Revisado: </= p>Aceptado: </= p>Publicado:</= p>DOI: </td></tr><= tr style=3D"height:6.55pt"><td colspan=3D"3" style=3D"width:156.4pt; paddin= g:0pt 5.4pt; vertical-align:top"> <= /span> </td><td cols= pan=3D"2" style=3D"width:258.35pt; padding:0pt 5.4pt; vertical-align:top"><= p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-size= :6pt"> = ;</td></tr><tr><td style=3D"width:37.8pt; padding:0pt 5.4pt; ver= tical-align:top"> C=C3=ADtese: </td><td style=3D"width:1.55pt; padding:0= pt 5.4pt; vertical-align:top"> </td><td colspan=3D"2" style= =3D"width:358.55pt; padding:0pt 5.4pt; vertical-align:top"> DATOS REVISTA<sp= an style=3D"font-family:'Times New Roman'">DATOS REVISTADATOS REVISTA</t= d><td style=3D"padding:0pt; vertical-align:top"></td></tr><tr><td style=3D"= width:37.8pt; padding:0pt 5.4pt; vertical-align:top"><img src=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE= BAQEBAQEBAQEBAQEBAQEBAQH/wAARCAAiAEEDASIAAhEBAxEB/8QAHAAAAgMBAQEBAAAAAAAAAA= AAAAcGCAkFBAEC/8QAPxAAAAcAAQMBAwcFEQAAAAAAAQIDBAUGBwgACRETEhQhChUWMVFhcRoiQ= YGxKUJSU1dYZpGTlZeh0tPW4fD/xAAbAQABBQEBAAAAAAAAAAAAAAAIAAIDBAYFAf/EADoRAAIB= AgMDBQwLAAAAAAAAAAECAwQRAAUhBhIxBxNBUbIiIzIzYXF0gZGz0fA0NVJyc4ShscHD8f/aAAw= DAQACEQMRAD8A2krncP0rmf28ebsxaq1F0K4ZPR4YjSfo8nKsiP1ppc7hN+0SXVM+hXbFaLE6Sj= eSXMIrlEp0xQEyrc7D+67DsWb7LF6podn0BtRLFVWVVXtcgpNScWzlo6WcPmozb31ph+gdVsgZM= ki+dg1IX02wIpGMQcnuCHx7dnc7H9H0Ko/+YTfjrQz5Or4Gjckx/pZRfH64ec/b0Sm2mzuSZNs3= yn0uXZfTwRZVtdkkFAd0ySUkU1LA0qRSuWkQSFpN4BtQ7LbdsoGjY3Ps2zfabk8rMwrp55a/Z/M= 2qgW3UnMc9SIzKi2WQoAhBYE3QP4dyZ3zVqFm5k90DM+F1p1C+0HCq3hkhq09B0OdXr761zguHp= CCdUpV2bxwgsSI92VkGT4scwazAs0kV3h1w6+mYvnPbrv3B6g57c92mK5p3J+VlrA5mdfetEgMy= rdbQXa2VhHQqDa31grVqCpa7Ii3QK5M6WB0ArmAliO4Bw5zLTNXy7kahyta8N9ypjJ3Wa5pLqwV= yJRsUGmR4ovEAzsc9X0nbpmnMvkVjNXayTiLlHLCVYu2yqAoQGj8J3+zGxC4XvntG8pU+Pe3yGo= KWJrH0+VaOIp7AwkY4orp9WLO8ZRCIDHOJAXzj3hbxIGKLUE0yiccSykRm9lAAKgaEgBb36b301= t0dNsEvhaZl3jrxsczYZWm57gcbQY9jp0rCwVk5B1xDdJeJz2t2KeRejk7QisykaVJBeuo2TIsL= SNUcSCarpm3K5W62Wd3LXyvMSsHIfjtXaHk/IPONN0LOLnS76FnklmeXVpW0TaUrALsGrhiKzMq= DdEqqiagru0BTKqQrgUO5mnaAdZk/nmmccg6+GVTrPRWUZCSuCZdO3ePitCgJyEO0Q2EqSF0WRj= yzQnTOzfsSOmaKkcBW7R2sUGe87ZlJUrnDah3DW030LxQznXaZMR6kO2i3Wh1zUKujXJV+KozZl= K0nFM2y64uUwkyGMJvaVbeiKgphBfwRbW57ve4Hotxv58LCWneanLvceJmqbjN8bY7LOOc9jd7t= 9XvVc240ZrBoxoxc/Rx9GIxsSL2CdTKyRDt5NJH1WSCpXSaJ0zJmPELX3OtX47Zbk4xld49WWtI= 8c8cv6bPU+VMBFbvYG8znEDNSpHFXlECz9gnVnaj5uykFGYPbQul84IMzKvCIC3ct7emmPMMsOL= 0vn860zi1Zc/vOd02rtqPSbLHQ0XMGkI+PM2vkPMqvZoKk/FVArRF83be2zNGgRigiVsinta7PV= XgXCk8fldTM3YXrMMkxCyLafkuZWpOYmaNn8Xm0WtRp29SPv8ATZayMIZJ23jay/RmSyJhM1kXJ= mjP3VoENyCQAWuAA4Nu4ABva506NAdNeGFiAflIGQfyDXz+9oX/AHejpYfk28F/O0X/AMLm3/M+= jqa1L1t7T5Pn1nq0WKlcDx/c7O50X7aTRxAfIePzQnPh+IgP4fePWhPyddQC0bkkUfr+llE8/Z8= IecAfj9Xw8+f+/HUU4cdv7lLjuIcm8H2jD7I5r3IqHr0UFizPRsakZiuJw5nwLqqxtoucMyVOsD= 0pk1U3S4F9ExDNzeoBiP8A4k8O+RnBJ7bZLGZSQmKlcJSJXsOabhnySLyQLGAKKTmP0XELTqvzO= 9K1cviN3jmouIr2xKMmyQTKR0BBbcbVZBmdNyk5bQ5lTTyZ9tFleaZXPHJzlLUwUdPAkvfYlfm2= urqolCAm1yNbjRsXs9n2V1mwmZVeV1cUOTZXX0VfE8RWeBqqWoKHm3KmRbSIxMbNYE31FsdfvK0= ir6VrfbYz+5xhJeo3fk6lVrRFHcOGpJKDnH1NjpVid0zVbu0AcsnCyQrNnCC6QGE6KpFClMFAOQ= uW5zwb5+WTMuNUESOzLTeC+8SepZg4nJ6brsiWMzDWp9FGaOvLqTKDRV/Ta88D3aWaSDYqrj3F4= 1RkVfU2x5EcTs57iNezJvr7jXMas2XSsjZIllWJaHjZJGVlEGjRZ9G2QY6YZSjFEY5JxHuGB46Y= ZeUjTMbDvVPcU49jnaG41Y821t03sOpXu57Bm1oymY0TQLQ3sFsgqhb4s8TNIVxc0aiwaPl2wpF= LIO2L1wQiINimBms5brjyp5tdxyd5Q6FBYqbtod4Eg2GulxcaEixwSkbrIiyKSVYAgkFTbyggEH= zhSOBAtijeF8wuWuhqZFxk4jQ+D52yy7hjm+xXiV0iOuMtHj88QsCs2rlRZM5N1Ii0ZN5qNQQVk= XL9Y/pvFHsr6xEEnKVzjk1tXKLZsJvCsFkMXvF84K8hXqOgPIS2iwhyVbUNbrIxDaEaWsI8Yl3D= QiqigrMnEkMm8OuV+m2BNqk8+YnCC00W15VE8auOnKG5zVDwKv5aO74pyJouPyU1BRBn0ZH028R= 01EKGmF2DVhGyDySj2zFB63eN2Yl8RyJUX1w04B1/jTkeI7ryLk5qA1DFMA1Gj3KutJJhL1SKpt= 4tt6vs23kyxrB69lbDFM7Y6ZOXMPKLMXDlASsknXlNdZ1xYbqhmY7qqoBdmN7C1yW3jYBbAkker= 13VFZ3YIigszMQFVRqSxOgAGpJ0A1OKbcM903LjN2xKDoczu+EZpSrBentZxz6UZdot4mknq+ha= crd4WZiaS5eydilpuRaoPa2pEx7dtExbR6nJAsusgoCQ1LnZpnLLO5HPNLe0m1LYzzV4hOK5oFI= p11z5jZoW5ydiWMi9pl+Qa2SJexrqJMQVHjZsVyC5wQTXaJtn725DziHwUrNOiscQ3zka4g5+5Q= OqZhGMbq3MthM9ETkoZpJ00q8W2SqiFmC/PplZ2qk/SnoqECyNHiosGjx5MIPg3wmantTlxyW2T= U7bc9XxC5TMjYLlA2S7S14yuXmI+nwB1XVdbvFjpGkHbSfYPDEes4yLQOmuybs1RNO0Eqd8anmA= ZmKHmmANpFTQ24cRfgSb4qJmVA5ZVq4Cy7u8vOC4LIJFFuklDvWFyBe40ONuvSS/gF/q6OvX7oX= +Le/2Zf8AR0dUtxur9R8cWOei+2vz/v79RxJhAPP1fvgD9XgPh+H3dfg4j7Q/H/3gOjo6iHht5v= hhg4N95ezjzKgAen4AA8G+HgPq8h4Hx9nkBEB+4RD9PXWL9QfgH7Ojo6cP4TsLiZeHs7K4+9VV5= lFKfDJdM5QMRW55SkqQwAYiiSmoU8iiahR8gdNQhjEOQwCUxTCUwCAiHR0dXsu+nUv48XvFxz84= +rK30eXsNhQMs+oUo+in8nSKhIv0YuFBF6+rUM7dpAh7qdAE3LhkosQETqqGS9k4emZQ5ieyJzC= MxjM+oTfS05tvSKghNGs7h2aXRrUMlKGdlSQ9l0L8jIrsXBfbP4WFX1A9o3g35w+To667eJ/Kr7= uPGQTx6+np2zi5HR0dHWfHR6v68bnH/9k=3D" width=3D"65" height=3D"34" alt=3D"edi= torial1.png" style=3D"margin-top:46.65pt; margin-left:-1.05pt; position:abs= olute" /><img src=3D"data:image/jpeg;base64,/9j/4AAQSk= ZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/wAARCAAzACsDASIAAhEBAxE= B/8QAHAAAAgIDAQEAAAAAAAAAAAAAAAoHCQEFCAYL/8QALBAAAQQCAQMEAgEEAwAAAAAABAECAw= UGBwgACRESExQxFSFRChYXImFx0f/EABcBAQEBAQAAAAAAAAAAAAAAAAcABgP/xAAkEQACAwABB= QADAQEBAAAAAAACAwEEBQYABxESExQhIggjMv/aAAwDAQACEQMRAD8Af46OjqPtnbT19pzCb3Ye= zssp8LwzHBVLt8gvCWjBDR+prIoY0/2nLOLmcwYCvDinOPLlhEDHmJmiid0Slthq0V1Me9xitSU= gTGtYc+oLWsIkjMymBERiZKZ8REz1zc5NdTHvatCVATGuaYrWpYR5NjDKYEAGI8kUzERH7mepA8= p/Kfx1j1N8+PU3z/HlP+f/ABeqVqbvt8Jr3OVwyOTZdFWkFSA1ux8lxEQLApiVX2xCTvgXlnmVX= UEzOYjji8QbIHErpzhRYY3ubU1cdz7mfxn5uZPlm+VW+wHIZKuEnWdBYIbrix1XNJITi+XabtnP= /H2DCa4mSzrsnjn85GRJPX5E8aeH49UpYvZnnWs29VdmFj36+YWlSo7EFSs7EAawOtmgYzDHrg4= l0GQxXI0i/wCf3WUmex3d4ZlLp2FaEa1N+gNC5cy/FpGV7BJRYvkM+wLOfEKgBInCLiV7yqRlxD= o6iLSG79a8g9b43tTVWSh5Rh+ThsKCNHVYyRCERGmVNuDJ4Jq7msIR4ljXFsYQMQxzXIrFY98uo= vn99F9ivYqPdVtJbWtV2GmxXcBLchyykWKas4EwMCiRISiJiY8TEdJVewi2hVmq5diu9YtQ9Jix= TVHEEDFmMyJAYzBDMT+4nrC/pF/6XpT3nUdtnuK9ymr4RUOQk4zrDWNyoRzG+4+tr/xdBHfZ1n1= kE1WMtLqEQlaDGYiXtgjlmDDinAZbWJb2NOVXJvAuJWlso3TsOOyKp6JkIdfU04shVlf5DY+uGl= ohVRijhvsTEbDJYHPhABhSUkiVGRo16qI/IzIdpbrXuOcXKaupd/YC0g7kbxvkMntHX2FIGlIdn= +FTPiHMynELDHfi1+dAiCtv8MuxIMqZDLVzMOAb+zGPqJZucqr5wj8cu/j8c3roBOZm8rtrX+Cx= xMghX5XJVxuGE1a1i1XW9i5sBMjHd/YzWji8affMvrp09TexqhmN+/xusyfywVAyP1mCj7figX3= elDzUB/GY6YhB7VfCUPS8umI9NY7MGVVKHPnRI8RGyXWSwtamRR5fJGtgPatna0uOAdY6lj0UdK= /4KvGdUTRdrDkVkOQZ1w222OJl+hcNobTMeOHJsiVkVxrmwtCZfxmKBhucQfYVV0ZBNBnOuJ50C= qJIY8nobcZhVdLaX3cReVWu+YenKTbeunFCjkSyVGSUFixW2eK5SHAPLaUBjka2In4yFQzCmj+Y= DQyByGpG+R0MXSFrY1tHXH3NucJXVdWGSfY2B88QoYIIkMk5JZRMzmxQjjwsfLNLI5rI2Mc5yoi= KvWUqdwOe8Xu62dct236c3vZga8vt3crcQ6I/PokbIOvciCZWYAyVW3WcxNmvYSQhGktcF4RySn= laNOtWr5wU4gGZcJrVNLIarzNO6IrgHVon0eDDEbFV6oalqmwU9I58SuT+6O1tyoyPV2yYzf7Gr= szjxXduBRTymB/EZJDAzPcSRzWRSWQ1XMNf0xMUUDMlpXwAkPgaWMUE8dUWlfdVVbcVZg59ZbAi= 2VccLK2UY0A6BhIZY8rVVskBA8sc0UjVVr43tc1VRUXr583cE3tjvJXl/uzbuHxK/Er/ACCvpsW= nWB0cltS4hQ1WHgXbontZM1L9lKlvBFM1pEAx0A0zI5YnMa9RxXxy/wAO4zce8TyiKWDJMb0rrG= jvRiFX5AltV4ZTBnhzfa+6GTDINJ5VVV0S+V89KX+gsdE5nBOXXKaczlG/mAHIKaVwn6WFUKDya= xX6mG1muOsZlEnISlZlMpiZOexWs6NHmXF6lp2lx3FvkeHaaXvKq7bllALA5/XzsKUD4GPUfcWM= ERhk+JUzrBcS2RiV/g+c0NblGJ5NWFVN7RXAsRlfZAGRuingnhlaqepWuV0UzfTLBKjJoXxyxse= 1MbnhwQ2924Nv1O9dE2uRf4mTIUPwjOa90pNrr20Je5G4fmD/AEOiIBJjklBBOsI5K7Iq6R1XYx= zFPIhIdo++vJ5vhGKbGxS+wjN6CsyjFMlriKq9obgWM2vs68pixzDEQSorVRzVRzHt9MsMjWSwv= ZKxj2lHbvuJp8C0mEK40cDSj4buFYn2rX6p/wAGYAfsC7S1kcLZIyJjMpbBLL+VDn3Ac/m9BcEc= 0NuhMux9hMkD6j4mDEGEuRM6xmIyYRPssv8AqqRZHmV/eIHev4l4xqCtxjZ+BzaOy2gFnns6bW+= D/KwPKbkqWQqyt8cDx+NJKYu7OfMeaBbjQxDFEuZHamxt91tc3cV7v+Y8sKkzUmmqm31lpMhWsy= EmyIibm+xI2KjkEtvx5EodBjPueFfSBlHk2boo5rGxaPJJUR9w76/p7K23ySxu+OW5hcUo7AhxI= 2EbKrj7SCjWaaV8o1dldN71iXXwMdHEEPZUhB8cbEQu1NkcsvUjcauwJrDBMgrcr5F7El28+tlG= LhwLG64rGsNIKh9TpGX9lMXLf31f7ixOjCGjx2OX2lacpg00giOubrf50wbp83qP1NHVk5vVOP3= E3LJ0b8+D9UIegKsuW2ZlbrmharqIfopklAHApeyu/WzTVw2wihQzBAadnYpsqVl26Y/x/wBXpc= Vj5mH/ALXVpoc2P5cuPJr6ru7QPbou9/bGx3kTtWhlD0br25iuMcCtBnMh2bl9OSktcOOPO1ENx= SksYULuifDgbMsWOjRpMTrRgrl7Go1qNT6RPCfX0n148frx4+utRQ0NLjVRW0GP1VbSUdMGNW09= PUhD11ZV14cLIBQQARI4RRBRoGMhhHHijiijYjGMa1ETrconj66Au4nP9TuJvnsXxitVSE1svOA= 5NdGn7ycD7+AhthxT9LL/AEGWn6jECpSgBy4DwXO4FiDmUimxaecWNO+QQB3LXrA+0D5KVoVHkE= Kki9BkpmZMzKToVEX76OjrBdbjo6PCJ9J46Ojq6uhERPr9dHR0dXV1/9k=3D" width=3D"43" = height=3D"51" alt=3D"" style=3D"margin-top:3.75pt; margin-left:-5.55pt; pos= ition:absolute" /> </td><td style=3D"width:1.55pt; padding:0pt = 5.4pt; vertical-align:top"> </td><td colspan=3D"2" style=3D"w= idth:358.55pt; padding:0pt 5.4pt; vertical-align:top"><div style=3D"border-= top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; clear:both"><= p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%; padding= -top:1pt; font-size:8pt"> CIENCIA DIGITAL, es una= revista multidisciplinaria, trimestral,= que se publicar=C3=A1 en soporte electr=C3=B3nico tiene como <s= pan class=3D"Strong" style=3D"line-height:115%; font-family:'Times New Roma= n'; font-size:8pt">misi=C3=B3n contribuir a la <= /span> formaci=C3=B3n de profesionales competentes con= visi=C3=B3n human=C3=ADstica y cr=C3=ADtica que sean capaces de exponer su= s resultados investigativos y cient=C3=ADficos en la misma medida que se pr= omueva mediante su intervenci=C3=B3n cambios positivos en la sociedad.</spa= n> <a href=3D"https://cienciadigital.org" style=3D"text-dec= oration:none">https://cienciadigital.org</a>= La revista es editada por la Editorial Ci= encia Digital (Editorial de prestigio registrada en la C=C3=A1mara Ecuatori= ana de Libro con No de Afiliaci=C3=B3n 663) <a href=3D"http://www.ce= libro.org.ec" style=3D"text-decoration:none">www.ce= libro.org.ec</a> </div> </td><td st= yle=3D"padding:0pt; vertical-align:top"></td></tr><tr style=3D"height:23.65= pt"><td style=3D"width:37.8pt; padding:0pt 5.4pt; vertical-align:top"><img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUg= AAAE0AAAAcCAYAAAAk2zLiAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAE= 1VJREFUaIHtmVl4VFW2x3/7nFNThspMCIEQQgIIBBRkaIYWkEFQQbG9Aa+EQRlUtBlaBZtPbMBu= VGznDuA1eMMgiHyIAsokqJhIEpFJgiaoCVAhQAKVpFJVp6rOvg+VFAkCfr7f9XJS+5y19lr/vaa= 9InRdl2fPnSVgGAgBCBAIgiQbH42/hQDZuEbz7wAhkciggGYkpQzKRSDl1feimTwZZG8Simwp4d= ptAVAQIVktXrXY/homrm4i5NUPZUszmtlD0CYpMQIGHVLTUFQFUVl5Vs54bBaj77kbiXH9PRotE= SL4bDJdIhv/aHy2xOu3JJsZKiUGEmkYgEBTlOsbLq41vEkvgTQkhiExBCiKQAjRUg3RwoiW/FIB= KQlII2iPAEUoIV4hQAqJlBJFKOzdtZd/Lv0X6ekd0epdDbRvn0pCQsJvQWsyLiDRdR8ejwevruP= 3+1EUBU1TCQ8Lw2Q2Y9JUhPI7qEmQUqDrOpcvX+ZKrZP6ujqEULDb7URHR2G3R2Exm2h0ebhGJ8= Mw8Pv9XL7sxFlbS63TiTQk9ig7UfYo7NFRWK3WRl3kb0ATQhAIGNTUXKHW6aS2rg5d1wmz2bBHR= RETE43NZkPTtNDeAkFax478/PMvQdCQEiHUkMDmYEkJXreO48w5Thw/TllZGZcuVuNqcGExW7BH= 2WnXLpnumZl0SO9AdEw0iqqFTqr5wSJBGgaXLl6ioKCAY98fxe/3Y7XaMAwDt7uBSHsE/fr/iR6= 39iAqOhpFDXqPbIxNw5A4rzg5duQYBQcLqK+vJ8wWhqIqeL1eFEWh5209GTBoEHHxsaA0BkAoQi= Qet4cffzjFvr1fcOnSJWw2GyaTCY/bQ0AGyEjvyB1D7qBtSjuESQt6umwC30AIgQZNYSFC+afxN= c4rTvbt3sPX+7/C4/EQGxtL69atiYiIQNd1ampqKCr8jvxvCkhNS+X+v4ynU5fOKKoIRmzQxxEy= KPtSVTW5772H1+Nl3LhxDB8+HLPZjKqqOJ1OtmzZwhd79lFaVsp94+8jJj4WTVwN25qaGj7Zuo1= fT5czcMAAsrKyiIuLw2QycfHiRQ4cOMC2bds4efwkUx6ZQuvk1qFYNQBXvZuv93/Jns9307dvX5= 55+hnatm1LWFgYNTU1HD9+nLVr17LynVU8PHkSnbp2QTGrhHJSE1KlpaXyzXfe5s9D/9wYnsE4d= jrreG/V//DD8ROktk9l4sSJjBs3jpiYGCwWC4Zh0NDQwKlTp8j5z384ePAgiqYw5dFp9O7TO5hj= aAIM6l31vPbKv5GG5P333ycjI4P6+noWL15Mp06dmDNnDnV1dRz8+iB/X/R3OqSnMv7B8YSFhwP= gdrvZ+tFWyk6VsWTJEoYOHUpERATV1dXk5+dzzz334PF4KC0tZcb0GXh0L/MXzCM8IhwhBD6fj2= ++/IatH21l/vy/kZ09ifDwcOrq6vD7/URERGAymbhw4QILFy7km/xvmP3UbDqkp4GAwoJDDPvzM= EaNGsXVY5QilAK8bg/vv7uGI4eP0L9vPz7avJk5c+bQpUsXkpKSiIuLIyEhgZSUFIYOHcp7ubm8= 8MI/EIZg1TsrKTlxEimbPDZYVQ8cOEB5eTm5ublkZmYSFhaGy+Xi4MGDfPHFF0gpiYqKYsTIEcy= fN48jh4/gqDgXShOOsw6++uIrxowZw6BBg4iMjOTixYts2LCBV155hcLCQqSUdO/endw1uVyoqm= LXZ7tCKafKUcWnH3/K1KmPMGvWLGw2G+vXr2f8+PGMGjWKRx55hIMHD9KmTRtWrFhB+5T27Ph0B= 676ekLGNLpbi5IlEcgA7PlsD8WFRfTs0YN169eTnpGBzWZDUZRQjmnKMyaTiZiYGGbOmsmKf7+K= 1+Nldc5qrtQ4g+egQIO7ge0ff8rMGTPp2bMnqqricrm4ePEi06dPJysri+LiYgDMZjNjx42jR2Y= PPt32KboeIBCQfPLxJ9TX17Nq1SomTZrE3r17GTFiBEuWLMHhcDBr1ixOnTqFpmnccsstPProo+= z+bDcetxfDkBQVFRNlt/P4YzOxWMxs376dOXPmcP78edq0acOhQ4eYMGEChw8fJjExkeeff56ff= /4ZxzlHs8i8FrTGYlV1vort23dgt9vZvHkz8fHxSCnx+/34/X4Mw2hWKCSBQADDMFAUhQkTJvDE= E09QU13D3l27wB/ACARwOBzofp2p06aiqsGic+bMGbKzs5k/fz5Tp05l/PjxjTlVYLfbGTJkKJW= VVcF9AwEqfiln4cKFLFu2jIqKCrKysigtLWXatGns2bOHrVu30rNnz6BRisLEiRPxeLw4Kh24Gl= ycPv0zw4ePIMoehdfrJScnh9jYWDZs2MDOnTvZuHEjAAsWLACgY8eOxMXFcfbcWQSisQflWk+TS= AH5Bfk0uN089de/0rZtWwKBABcuXKC4uJjCwkLOnDlDIBDA6/VSVlZGfn4+x48fx+l0IoTg6aef= JioqikMFh6i94kQIcDe40RSN1PapwV6q0VsNwwiB33QYTUanp6ej6zqGESAQ8KP7fPTt25eZM2e= yf/9+Xn31VQYNGsQHH3xAVlYWu3fvpqysjLq6OqSUdO7cGSkldbV1eHWdWqeTrt26opk0fD4fFo= uFzMxMkpOTAejUqRNWq5WjR4+i6zoWixnNpOF2e5BG86Zdol3FTOLTdX48WYKmKGRPmoRhGDgcD= ubOnUtJSQkmk4nExERWr15NcXExS5cuDXnH6NGjWbRoEfHx8QwcOJADX+6n8kIV9viYxv4s6JUQ= rKpmsxm73Y6qqkgpadOmTTNVgiAKRaAIJdh0ChHqDxMSEpgyZQqjR4+mqKiIvLw8Fi1aRKtWrRg= 7diwPPvgg7dq1I3ibUEIHFQgEEEIQHh7OsmXL8Pv9xMXFoSgKgUAglHIg2N40XUNa3nNky/B01d= fjdDppm9yW+Ph4fD4fb7/9Nvn5+Tz22GO88cYbJCUl0dDQwMKFC/F4PLzxxhvMnj2buLi4kKjBg= wej6zoXL14ECVHRURiGwQ8//BDyrNatWzN79mzCw8NRVZV33303lLQNw6CkpASr1YqiKKiaSkRE= OCdOnGiKCWpra1m/fj3R0dFkZ2djsVgwmUzs2rWLyZMnM2vWLBRFCVX7mNhYioqK8Hp1hBCsXLm= SxYsXU1JSQk1NDcXFxbjdbgYMGIDZbMbj8eDxeIiMjEQRollwimaehsTtbsDt9tAmLRlFUfD7/R= QXF2O32xk2bBhdunShV69e6LpORUUFY8aMYfDgwfTv3z/kPYqi0K1bNwIBg7raOpCSVq1aEREZw= epVq8nMzMRisRAREUFycjImkwm3202PHj1CYXuh6gL79++nXbt2mE0mpIDUDml8/vnnZGdn07p1= a2pqatixYwd5eXl4vV7S09NZtmwZ8fHxbN68mddff51IeyQJreIxmU107tyJgwe+5sKFKlI7pNK= vXz+2b9/OlClTyMjIoKioiLi4OJ577jl8Ph9HjhzB5WogJaV9s6ZfAUSTpwVxVFUFVVHweDyhML= JYLOi6jtfrJRAIcPr0aXw+H6qqUl9fj8/no7a2lsrKSnRdR0qJy+VCCIHJpKEgsNos/OW/HuDDj= z7ks88+a1FMmvZp+u1yudi48QNKy0q5Z9xYVE1FUQT3jr2HijMVrM3Lw+Vykdy2LWvXruWFF14g= LS2NdevW0a9fP9LT0+nVuzd+I8C9943FYjGjKoLb+/YmgGTJkqW43W6ysrJYsmQJcXFxlJWVMXT= oUHJzc+nduzdnz57lH0v+QcdOHUlsnRi6mzaRFopNICwsnPCIcBwOB36/H5PJRHZ2Nk888QRz58= 4lPT2dffv28eabbzJkyBAKCwuZMWMGVVVVNDQ08PHHH2M2mzl06BCaphEdFR2aEvTt15cTR08wZ= 84chBCMGjWK5ORkHnroIbxeLwB1dXWsW7eO1994nTvuHEpim0QQEkVAq6RERtw1kpyVOVhtVqZN= e4SkpCSGDRtGamoqbdq0wev1snvvHubNncutvXoxZOiQoD8ogpj4WCb890RWvZPDU0/9leXLl5O= dnc2ECRMIBAKoqorVauXHH39k+vTp6F6d+8ePx2y1tJiCAKhPPjX7hcKiQlI7pKJpKke++56ff/= mFMWPGkJKSQlpaGsnJyRQUFIT6oaysLEaPHk1paSnHjh0jMjKS1157jZSUFACWLl3K5SuXGX33a= KKjo4Nep6jcdlsvTpedJicnh6LiIrp3z2T48OH06dOH4uJipj/6KB9u+ZAhw4dw1913YbaaG71Q= oKoKySltkTLAqpWr2bFjB4mJrbFYrZhMZo4dO86zCxbw1ltv0alzJ2bNmolm1lBU0TTCID4hgXZ= t2/H+mvfZsGEDYRHhREZGovt8nHM4ePnll5g3bz6BQIAFC54hPiEWoQQnJ+fOnqND+/akp2cgSk= t/lG++8zaDhw1BSoPi/EOsfHslQ+8cxsaNGzGbzQD4fL7GkDM1qzBGKFQ1TcMwDAoLCxl25zDS0= juy4O8LsIVZr6ZQqeDz6hQVFbF71x4c5xyoioJEYhgB0jMyuPveu0nvnIFmNjWb7V1Nw37dR+mP= P7Hzk52UlpaimTSQAsMwSEpK4s6Rw+nTpy8WixlDbWpjBFIYSAmqVDh/ppKtWz/m5A8n8fl9KEL= B5/MRlxBH//79GDliJBH2CALCQApQpeBQ/iGG3TGEUaNGB8NTSok0JBJBl65dSUpOYteuXXz00U= c88MADWCwWzGZzs4TY6KaqGmpWDcPg/PnzzJ8/H03TuPveuzFbbc2GkMEsYLKY+dPAAfS87VauO= J24PR6EENhsVqJjYjGbtcZ7K82mg1eBM5lMdOvendQOHalz1eNucGMYBrYwG/aISGw2K6oSvGQr= 8mrVE6HppqR12ySmPzaD2ro66uvq8fl9aKpKTEwM0VH2IB5IBKA0zWGbtSOalJJ6Vz0Xqqowm0z= YbGFMmpLNv1e8xtPPPE1iYiL9+/cnIiIiOJBTlFBv1iTI7/fz66+/MnfuXL777jsGDh5It27dqL= 1yhYDfj9I0Gmu8qjV1PlaTBavJEsLFXVePR8rrDx6vIYmCWWiYwiIbv5d43W68bncI5OaNQospb= 7NhaERYGE1TDL+uc+nipav8zfo0V50r5DSipKREDhw0kMjISFRVZex94+jVpw/FRUWsz8vDZg3j= iccf54EHHiA5ORmLxdKin3I6nRw6dIjly//F90e+55auXZn6yDQCRoB3V79L7WXnzSy/Pv3uBPg= m736P94/u2/htfX09eXl5jBo1KuhpNdU11FTXAPDhps0kp6TQ9099sdmsrFvzv7z88sts2bKFQY= MGkZmZSUJCAi6Xi4qKCvLz8zl8+DDOOieDh/yZcfffj81q4/01ayg58QM+3d9CB5PJFGqEGxoaQ= usul4uwsDAMw8Dlct3QXovFgtVqxeVyYbPZCAQC6LpObGwsQghqamrw+Xw35A+mAhuJiYk4nU6u= XLmCqqpERkZSW1uL3++/IW8TadcuVJ2vJOed/zB3/lx69uxB4tN/Y9+efRQUFFByqgSTZkLTNKS= U+Hw+JMEr0EOTH6ZTl05YLVY2rF3Pt998+xvAAKKjo9m0aRPnzp3D5/ORl5fHpEmTePLJJ8nJyW= Hx4sWcPn36hgp37NiRF198kXnz5nHnnXdy6dIlLBYLDz/8MIFAgNzcXHbu3HlT41esWIHf7yc2N= pZFixZht9t56aWXeOqppygrK2uRv64leT3QAv4A5b/8wovLlvL444+TkZHBxOyHGDN2DOccDsrL= y6msrETTNDp37kJKSgrxcXFYrWF4vR7ezVlN/jf56I2917WkaRpms5ktW7Ywfvx4ysvLsVgs5Ob= mcvbsWc6cOXNDhQFsNhtpaWksW7aMU6dOoSgK9913HwsWLKChoYHExESU5v+kuQ4NGjSIDRs2sH= 37djweD5MmTeL48eNMmDCBF1988aagieuBFgTOz/lz5/nnsn8xYtRIRt41gvhWccQlJtDjtlsbi= wBIaWAYwQRc9O23bNq4icrKyptu2gRceHg4drsdTdNYsmQJhYWFdOnSJXSpv6HSQvDTTz+hqioD= Bgxg27ZtREZGUl1djdvtDo2ybkSKovDkk08ycOBAnnvuOdasWUNmZibl5eWMGTOG5cuXt5i4XFf= /665KQEo8DQ3s2PYJB7/8ioyMDDqmdyQxMZGIyAh8uk519WXOnDnDqZISKs850HX9ppsBodlcq1= atQgBVVFRQXV3N+fPnfxc0v9+Py+XirbfeYtOmTbhcLrZv387zzz+PEIJvv/2WI0eO3DCvqarKs= 88+y65duygtLaVz587U1NRw9OhRMjIyuP322ykoKLipDuLkyZOya9euv2usEAJFVdBUDZPJhGEY= 6Lr+m5HK71F4eDj9+/dHURQcDgenT5/G7/czePBgvvzyy9895bi4OGJjYzl79iyZmZk4HA5cLhc= 9evRASsmJEye4fPnyDXVSFIX27dtzyy23UF1dzZUrV/D5fJSXl5Oeno7X6+XXX3+9Lu/OnTsZOX= Ikory8XE6ePPmmija/UF9v/Xrvbiarqc/7I7zXNtbN6Y/Ia95fNpfbXMaN+FesWBGaDv8//UH6P= w/h65aldWKXAAAAAElFTkSuQmCC" width=3D"77" height=3D"28" alt=3D"" style=3D"m= argin-top:-0.3pt; margin-left:-0.75pt; position:absolute" /> </= td><td style=3D"width:1.55pt; padding:0pt 5.4pt; vertical-align:top"> </= span></td><td colspan=3D"2" style=3D"width:358.55pt; padding:0pt 5.4pt;= vertical-align:top">Esta revista est=C3=A1 protegida bajo= una licencia Creative Commons Attribution Non Commercial No Derivatives 4.= 0 International. Copia de la licencia: <a href=3D"http://creativecom= mons.org/licenses/by-nc-nd/4.0/" style=3D"text-decoration:none">http://creativecommons.org/licenses/by-nc-nd/4.0/</a><s= pan class=3D"Emphasis" style=3D"line-height:115%; font-family:'Times New Ro= man'; font-size:8pt">. </td><td style=3D"padding:0pt; vertical-align:to= p"></td></tr><tr style=3D"height:0pt"><td style=3D"width:48.6pt"></td><td s= tyle=3D"width:12.35pt"></td><td style=3D"width:106.25pt"></td><td style=3D"= width:263.1pt"></td><td style=3D"width:6.05pt"></td></tr></table> <table style=3D"width:437= .1pt; margin-left:0.25pt; margin-bottom:0pt; padding:0pt; border-collapse:c= ollapse"><tr><td style=3D"width:74pt; border:0.75pt solid #000000; padding:= 0pt 5.03pt; vertical-align:top">Palabras claves: Aula invertida; m=C3=A9todo; ense=C3=B1anza de historia; estrategia pedag=C3=B3gica.</spa= n><spa= n style=3D"font-family:'Times New Roman'"> </td><td colspan= =3D"2" style=3D"width:4.15pt; border:0.75pt solid #000000; padding:0pt 5.03= pt; vertical-align:top"> </= td><td style=3D"width:321.8pt; border:0.75pt solid #000000; padding:0pt 5.0= 3pt; vertical-align:top">Resumen Introducci=C3=B3n:= el "aula invertida" c= omo m=C3=A9todo de aprendizaje en la asignatura de Historia es una <= span class=3D"Strong" style=3D"font-family:'Times New Roman'; font-weight:n= ormal">estrategia pedag=C3=B3gica que transfiere la instrucci=C3=B3n direct= a, tradicionalmente impartida en el aula, a fuera de ella, generalmente a t= rav=C3=A9s de recursos digitales (videos, lecturas, podcasts, etc.). </span= >Objetivo: = determinar la influenc= ia del m=C3=A9todo de aula invertida en el aprendizaje de Historia en los e= studiantes de Primero de Bachillerato de la Unidad Educativa Combatientes d= e Tapi durante el a=C3=B1o lectivo 2023-2024.Metodolog=C3=ADa: la investigaci=C3=B3n adopt=C3=B3 un d= ise=C3=B1o cuasi experimental con un enfoque cuantitativo, alcance explicat= ivo y corte longitudinal. Poblaci=C3=B3n: estuvo compuesta por 145 estudiantes de primero de bachille= rato y 5 docentes del =C3=A1rea de Ciencias Sociales de la Unidad Educativa= Combatientes de Tapi. Resultados: el an=C3=A1lisis descriptivo de las encuestas a los estudiantes re= vel=C3=B3 que la mayor=C3=ADa disfruta de la materia de Historia y prefiere= m=C3=A9todos de evaluaci=C3=B3n escritos y proyectos. Los estudiantes auto= evaluaron su nivel de comprensi=C3=B3n lectora como bueno o muy bueno y mos= traron motivaci=C3=B3n para profundizar en la materia, considerando importa= nte su aprendizaje. Conclusi=C3=B3n: el estudio concluye que el uso del aula invertida en la materia = de Historia tiene un efecto beneficioso en el aprendizaje de los alumnos, p= otenciando su comprensi=C3=B3n conceptual y habilidades de an=C3=A1lisis hi= st=C3=B3rico, especialmente en el estudio de fuentes primarias. Adem=C3=A1s= , promueve el aprendizaje independiente y el trabajo en equipo, facilitando= la construcci=C3=B3n del conocimiento a trav=C3=A9s de la investigaci=C3= =B3n y el debate. =C3=81rea de estudio general: Historia. =C3=81rea de estudio espec=C3=ADfica:<sp= an style=3D"font-family:'Times New Roman'"> Educaci=C3=B3n. Tipo de art=C3=ADcu= lo: original. <= /p></td></tr><tr><td colspan=3D"2" style=3D"width:77.2pt; border-top:0.75pt= solid #000000; border-right:0.75pt solid #5b9bd5; border-left:0.75pt solid= #5b9bd5; border-bottom:0.75pt solid #5b9bd5; padding:0pt 5.03pt; vertical-= align:top">Keywords:<= span style=3D"font-family:'Times New Roman'; color:#767171"> Inverted classroom; method; history teaching; pedagogical = strategy. </td><td style=3D"width:0.95pt; border-to= p:0.75pt solid #000000; border-right:0.75pt solid #5b9bd5; border-left:0.75= pt solid #5b9bd5; border-bottom:0.75pt solid #5b9bd5; padding:0pt 5.03pt; v= ertical-align:top"> </td>= <td style=3D"width:321.8pt; border-top:0.75pt solid #000000; border-right:0= .75pt solid #5b9bd5; border-left:0.75pt solid #5b9bd5; border-bottom:0.75pt= solid #5b9bd5; padding:0pt 5.03pt; vertical-align:top">Abstr= actIntroduction: the =E2=80=9Cinverted classroom=E2=80=9D as a learning method in the s= ubject of History is a pedagogical strategy that transfers direct instructi= on, traditionally given in the classroom, to outside it, through digital re= sources (videos, readings, podcasts, etc.). Objective: To determine the influence of the inverted cla= ssroom method in the learning of History in the students of the First Bacca= laureate of the Combatientes de Tapi Educational Unit during the 2023-2024 = school year. Methodology: = The research adopted a quasi-experimental design with a quantitative approa= ch, explanatory scope, and longitudinal cut. Population: it was composed of 145 students of the first= year of high school and 5 teachers of the Social Sciences area of the Unid= ad Educativa Combatientes de Tapi. Results: the descriptive analysis of the students' surveys reveale= d that most of them enjoy History and prefer written evaluation methods and= projects. Students assessed their reading comprehension level as good or p= articularly good and showed motivation to go deeper into the subject, consi= dering their learning important. Conclusion: the study concludes that the use of the inverted classro= om in History has a beneficial effect on students' learning, enhancing thei= r conceptual understanding and historical analysis skills, especially in th= e study of primary sources. In addition, it promotes independent learning a= nd work. General area of study: History. Specific area of study: Education. Type of item: original.</td></tr><tr style=3D"height:0pt"><td styl= e=3D"width:85.55pt"></td><td style=3D"width:3.25pt"></td><td style=3D"width= :11.85pt"></td><td style=3D"width:335.7pt"></td></tr></table> <ol style=3D"margin:0pt; paddin= g-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left:32pt; text-ali= gn:justify; line-height:115%; padding-left:4pt; font-family:'Times New Roma= n'; font-size:12pt; font-weight:bold; color:#767171">Introducci=C3=B3= n</li></ol><a id=3D"_Hlk185699730">La educaci=C3=B3n ha sufrido cambios y se han utilizado diferentes para= digmas para adaptarse a las necesidades del tiempo y de la sociedad son sie= mpre innovadoras. Debido a las Tecnolog=C3=ADas de la Informaci=C3=B3n= y la Comunicaci=C3=B3n (TIC) desempe=C3=B1an un papel importante en este =C3=A1mbito educativos = porque rompen barreras de tiempo y espacio, promueven la interacci=C3=B3n y= cooperaci=C3=B3n entre profesores y estudiantes esto es necesario en esta = era de cambio. La instituci=C3=B3n educativa adopta una estructura profesio= nal flexible y din=C3=A1mica, por eso la mayor=C3=ADa de los participantes = en la capacitaci=C3=B3n deben tener nuevas herramientas para mejorar y faci= litar el m=C3=A9todo de estudio La historia, como disciplina que conecta el= pasado y el presente, ha experimentado importantes transformaciones en las= =C3=BAltimas d=C3=A9cadas (Cede=C3=B1o-Escobar & Vigueras-Moreno, = 2020). </a>= Los avances en la tecnolog=C3=ADa y la= s nuevas teor=C3=ADas de ense=C3=B1anza alientan a las personas a encontrar= formas m=C3=A1s efectivas y atractivas de transmitir el conocimiento hist= =C3=B3rico a las nuevas generaciones. En este contexto, el aula invertida s= urgi=C3=B3 como una propuesta innovadora que se espera cambie la forma en q= ue se ense=C3=B1a historia a los estudiantes de primer a=C3=B1o de secundar= ia, como su nombre indica, subvierte el modelo de aprendizaje tradicional, = utilizando una variedad de recursos digitales, como videos, demostraciones = interactivas, lecturas y podcasts, los estudiantes pueden aprender con anti= cipaci=C3=B3n en casa en lugar de que los maestros demuestren el contenido = en clase. De esta manera, el tiempo de estudio se puede utilizar para activ= idades m=C3=A1s din=C3=A1micas y colaborativas como la resoluci=C3=B3n de p= roblemas, la realizaci=C3=B3n de proyectos y el debate.De esta manera, la historia es una materia ric= a en contenidos y tiene muchas conexiones con otras materias, seg=C3=BAn </= span>Aguilera-Ruiz et</sp= an> al. (2017) las aulas invertidas ofrecen = varios beneficios como: <ul style=3D"margin:0pt; padding-left:0p= t"><li class=3D"ListParagraph" style=3D"margin-left:32.33pt; margin-bottom:= 0pt; text-align:justify; line-height:115%; padding-left:3.67pt; font-family= :serif; font-size:12pt">Apren= dizaje activo: los estudiantes se convierten en protagonistas de su propio = aprendizaje y as=C3=AD aumentan su motivaci=C3=B3n e inter=C3=A9s.</= li><li class=3D"ListParagraph" style=3D"margin-left:32.33pt; margin-bottom:= 0pt; text-align:justify; line-height:115%; padding-left:3.67pt; font-family= :serif; font-size:12pt">Adapt= arse al ritmo de cada alumno: Cada alumno puede progresar a su propio ritmo= y profundizar en los aspectos que m=C3=A1s le interesen. </li><li c= lass=3D"ListParagraph" style=3D"margin-left:32.33pt; margin-bottom:0pt; tex= t-align:justify; line-height:115%; padding-left:3.67pt; font-family:serif; = font-size:12pt">Desarrollo de= habilidades: Fomentar el pensamiento cr=C3=ADtico, la resoluci=C3=B3n de p= roblemas, la colaboraci=C3=B3n y la comunicaci=C3=B3n.</li><li class= =3D"ListParagraph" style=3D"margin-left:32.33pt; text-align:justify; line-h= eight:115%; padding-left:3.67pt; font-family:serif; font-size:12pt">M=C3=A1s tiempo interactivo: los pro= fesores pueden dedicar m=C3=A1s tiempo a las necesidades individuales de ca= da estudiante y participar en debates integrales. Actualizaci=C3=B3n contin= ua: Los recursos digitales brindan acceso a la informaci=C3=B3n m=C3=A1s re= ciente y diferentes perspectivas sobre eventos hist=C3=B3ricos.</li>= </ul><spa= n style=3D"font-family:'Times New Roman'">En base a este contexto, se prese= nta el concepto de aula invertida y sus beneficios clave en la educaci=C3= =B3n hist=C3=B3rica. A continuaci=C3=B3n, se analizar=C3=A1 detalladamente = c=C3=B3mo implementar este enfoque en el aula, ejemplos de actividades que = se pueden completar y desaf=C3=ADos que pueden surgir. Por tal raz=C3=B3n e= l objetivo principal del estudio es <a id=3D"_Hlk153400056">determinar la influencia del m=C3=A9t= odo de aula invertida en el aprendizaje de Historia en los estudiantes de P= rimero de Bachillerato de la Unidad Educativa Combatientes de Tapi durante = el a=C3=B1o lectivo 2023-2024</a>. Aula invertida . = El modelo pedag=C3=B3gico del aula invertida (flipped classroom) modifica l= a estructura convencional de la clase. En vez de que el docente imparta la = ense=C3=B1anza en el sal=C3=B3n de clases y los alumnos realicen ejercicios= en casa, se suministra el material (v=C3=ADdeos, lecturas, etc.) para que = los alumnos lo analicen antes de la lecci=C3=B3n. El tiempo en el sal=C3=B3= n de clases se emplea en actividades pr=C3=A1cticas, aclaraci=C3=B3n de int= errogantes, discusiones y trabajos en equipo. = Tendencias. Los estudi= os sobre la inversi=C3=B3n del aula en la instrucci=C3=B3n de la historia r= esaltan los siguientes:<ul style=3D"margin:0pt; padding-left:0pt= "><li class=3D"ListParagraph" style=3D"margin-top:14pt; margin-left:68.33pt= ; margin-bottom:0pt; text-align:justify; line-height:115%; padding-left:3.6= 7pt; font-family:serif; font-size:12pt">Impacto en el aprendizaje </li><li class=3D"ListParagraph= " style=3D"margin-left:68.33pt; margin-bottom:0pt; text-align:justify; line= -height:115%; padding-left:3.67pt; font-family:serif; font-size:12pt"><span= style=3D"font-family:'Times New Roman'">Desarrollo de competencias = </li><li class=3D"ListParagraph" style=3D"margin-left:68.33pt; margin-botto= m:0pt; text-align:justify; line-height:115%; padding-left:3.67pt; font-fami= ly:serif; font-size:12pt">Uso= de tecnolog=C3=ADas </li><li class=3D"ListParagraph" style=3D"margi= n-left:68.33pt; margin-bottom:0pt; text-align:justify; line-height:115%; pa= dding-left:3.67pt; font-family:serif; font-size:12pt">Dise=C3=B1o de actividades </li><li class= =3D"ListParagraph" style=3D"margin-left:68.33pt; margin-bottom:14pt; text-a= lign:justify; line-height:115%; padding-left:3.67pt; font-family:serif; fon= t-size:12pt">Formaci=C3=B3n d= el profesorado</li></ul>Por lo = tanto, el aula invertida es una metodolog=C3=ADa conocida como =E2=80=9CFli= pped Classroom=E2=80=9D que ha tomado relevancia en los =C3=BAltimos a=C3= =B1os debido a que se presenta como una estrategia innovadora en el =C3=A1m= bito educativo, su enfoque se basa por invertir los roles tradicionales de = ense=C3=B1anza y aprendizaje (Alarc=C3=B3n & Alarc=C3=B3n, 2021</sp= an>). Se caracteriza por reci= bir informaci=C3=B3n que deber=C3=ADa absorber durante las clases, asimismo= , trabajar en tareas y ejercicios en casa, por lo tanto, el estudiante se f= amiliariza con el material fuera del aula con recursos en l=C3=ADnea. </spa= n><sp= an style=3D"font-family:'Times New Roman'">Para Dom=C3=ADnguez & Paloma= res (2020) el aula invertida consiste en invertir el proceso de ense=C3=B1a= nza tradicional, ya que en la clase convencional el docente expone los cont= enidos en el aula y los estudiantes realizan las tareas en casa, en el mode= lo invertido ocurre lo contrario. El estudiante accede al nuevo contenido a= ntes de las clases, y en el aula se centra en la aplicaci=C3=B3n de los con= ocimientos, la resoluci=C3=B3n de problemas, discusi=C3=B3n y la colaboraci= =C3=B3n. Los piones Bergmann & Sams (2012) mencionan que esta metodolog=C3=ADa le permite= al estudiante avanzar a su ritmo, y en clase el docente puede ofrecer apoy= o directo y adaptado a las necesidades individuales de cada alumno. = <span= style=3D"font-family:'Times New Roman'">El aula invertida se basa en la ed= ucaci=C3=B3n constructivista, seg=C3=BAn Piaget (1970) los ni=C3=B1os pasan por diferentes et= apas de desarrollo cognitivo y que el aprendizaje es un proceso de construc= ci=C3=B3n activa, entonces, los estudiantes construyen nuevos conocimientos= a trav=C3=A9s de la interacci=C3=B3n con su entorno y la reorganizaci=C3= =B3n de estructuras cognitivas existentes. Por tanto, el enfoque se basa en= la idea de que el aprendizaje no es la absorci=C3=B3n pasiva de informaci= =C3=B3n, sino un proceso activo en el que el estudiante relaciona nueva inf= ormaci=C3=B3n con sus conocimientos previos (P=C3=A9rez & Santiago, 202= 4). Por tanto, la educaci= =C3=B3n tradicional se caracteriza por ser un modelo estructurado y centrad= o en el docente, que supone que la ense=C3=B1anza directa en base a la tran= smisi=C3=B3n de conocimientos desde el docente quien es la principal fuente= de informaci=C3=B3n hacia los estudiantes. Por lo tanto el docente es la f= igura central unidireccional del proceso educativo y es quien contrala la d= in=C3=A1mica de la clase, imparte el contenido y eval=C3=BAa el rendimiento= (Galv=C3=A1n-Cardoso & Siado-Ramos, 2021). La figura 1 representa al proceso del aula invertida. = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; Figura 1<img src= =3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAHwAAAAxCAYAAAAY2M0MAAAAB= HNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAABK9JREFUeJzt2mmoVVUUwPHf07TX= YDlkqby0hLKgMs3KBiko0iwKKbR6zXNR1LekARuQvkRE0AcLKoIyhKw+SIVSIlohGRIV2QAVGA0= 0EBGZ4OvD2rd33u2e++59Xr3vxv7D4Uxrr7WHs9fZe69NJpPJZDKZTCaTyWQymUxmWLAfLsHjDc= o/jb50/Iy3cQtG7pHctYbbMK/q2b5YiyP2em7azAKsx8oG5UdhGZaLSpuDz3HlnsjcHuQkzGh3J= lrBiCbl38QdTcjvxHb8jR34AGsws0m77WYLtrU7E62g2QYnGq9ZRgk3PgNn4dP0/Fg8i2uwOb2f= h9exEecnudnCq5yKDVgl3OtoPIDPhOeZW6L3uBK5uXgFH4lfzQQsxfxC3ufiVfGx3ocDCjaew/F= 4GW9gWrMV0wkcrXGXDjeKyliDD3GvGAsQFdknGhJ6RMMcIBr/a0xM6fowK6W9F8/gKDwlfheL8F= iJ3lpyU7Eah2E6NuEu4YkWpHRTsE405DisSPkjPro+XID90/Orm6iXjmEoDb6s5F2X6HUT0v1F+= gd5leNMjEnXlcHe4fg93Y/BVWJA+GSJXjXkFgsPUM2D+ht8SbqvcIL4CLuEd/wWY9O73lTWYc1Q= XHor6cOfhfsRuFxUaOXYiL+q0u0UFT9Z9PTv8EgdvT015EaIXltN0VZXslHhl4LeXfijrGDDlaE= 0+HhRUfs2qH+ycI3dNd4fnPTtk+634nbRk7rF6Hh6Qf404dKX4AWcIUb97+FQ4Vpr6a0ltwW3it= /EaDF2mCRc/CEp3bviAzwv5edc/VPNMUl2vPgwJqajq4F66RhO1+9q1xeed+El0ZOKPF0iX+G19= G61qCw4R8x5N+Hi9GxUkrsZH4teeiCOTHqfEVO+9elcrbdM7kIxCFyb7F5XyO+cQn7WiYHmUv3j= j5UF2csK1xfVKGemSSoNPpwXbDqCdv/DG6Uy+BpbVyrzv6DbwFF7JpPJZDKZTKYBFuAdsT5+TBv= s7yeWMG+oIzMe9xgYBBkqrdTVcfTgeRHcuEMsVOxt5uMHEd0q41oDgyC7Qyt1tZ1mFzJmiWXVtS= LsuLXlORqcr/CTWDbdUiKzVZRtO77cTXut1NV2mll46RVLksvEfPjXdO7Wv7TYW5Cvjms3GqMu4= 0SxZLpBRMvK7FTYUaKnLIb+c53y7GggfUewz+Ai//IivhfhyodEEOKH9G6VgVuAenA2rkjXb+ET= LBQx5VNEjHqS2P2yEJfi/RLb40RI86Zk8wnRy2vZOTm9K2Naid1j65SnkfQdwe4srf5YuN4lXF6= F2XhYhA8/E5X0qNgmVHGLX4hgxGLcKXpOGfPEb2QbfhNbrcrsDLb3rMxuvfI0kr4jaPVaeqXwZX= HtwWLUZRzkv+HY0XXs1KMZu7Uas5n0w45mGrxLuLIp+iv/GzE1myJc4nLh5mrFtWcaPEZdxkfCn= Vfi4VNxf7JbK37eZWBcu0g9u2XlKepqJt8dzSIDgxgjxbRss5giXZvOlU1+1XHtRmPUZVwmKnmF= mBLeLXp+rfh5byGf1XvM69mtVZ7rq3Q1m+9MJpPJZDKZTCaTyWQymUwmk8lkMplMJpPJ7H3+AcZ= SLtlV/feIAAAAAElFTkSuQmCC" width=3D"124" height=3D"49" alt=3D"" style=3D"ma= rgin-top:70.75pt; margin-left:-87.35pt; position:absolute" /><img sr= c=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAAAxCAYAAACfxeZPAAAA= BHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAABG1JREFUeJzt21uIVVUYAOBvRjM= vWZlpZWpRD+mD4SXMwnnJ7sF0gcgwMimLoofoKbopRAQJRQ89dIGiIKWXlB4qjB7SSroREUKBoE= EPGmZFRFF5evj34eyZc/aZ2TOOovN/cJh9WWuvtYe9zl7/2f8mpZRSSimllFJKKaWUUkoppZSGs= Ba78BGuH0b559Do8Nk1Bn2bgntwd2nb/egbg7ZSarMIyzFJXHS/48Ih6vTgYTxb2jYBdwyjvRU4= vUb/rsF+3FejTkpdTahR9gB+wn/4EefgIPYMUe8CnI3txXoD3w5RZzJewFb8Ncz+7cHPmIivhlk= npa56R1G3gb016/SIO1HzzjMJm8SU7XLML7Y/gX4cws1iIDbEwFldLK8pyi4WA+ljzCu1NROPiD= tL0wq8gy/xGKbV7H9KwzIDG4dZdo32GKQ5QJaLKdFU3Kg1QGC31hRrttYA6cWG4rgzxMC4qCj7u= tYUaz3+xrXF+hx8iPOKei+JgZhSpZHeQW7B8zXKbxJ3j14sKW3fJ+4Ut+MLMXXr5EBp+bCY6hGx= 0HZ8j1/xfqncK3imtN6HnUWbh/CiCOh7apxHGmdGMkCuEBfibyOo28A3WnHLfjFlOoTXDBw8Q5m= EU3Fyh+1N5filR8RNTb/gzxrtpXGo7gBZiR/EN/hJIm7oZoII0KdqfVNPFFOrq4r6i/EB3sSyUt= 1/cVppfR8WiKnSQjwtBsh6XCZ+5p2Px3Fr0d5ZOLOo/6m4U10tpmpX4mUxaFMatRu0xxJri309e= AtzB9Wpeg5yUMQBS0XgvBOvYlap7pNi+rSgWF+Hz0WMcVfxd5q4A30mYooH8ZAYOOtK7V1SHGOV= iEN2iwB+ykj+ESmllFJKKaWUUkoppXR82mDgT7XDTXTslIZ+NGT6ezqqesWzh3e1P73u5liloY9= Fu3VT8NNxrk66ewPniifZW2vUO1Zp6Ee63ZGk4Kfj3GjS3ReK/KlF2IL3RKZsU1Uaeh+2iafn1x= XblmIzLi3Kv43zu5Tv1nad9PfBx+523MEp+FV9S+NYv8hfIi7ihkhBmSouoDuLfVVp6HOLctOKf= XtFesnXxbGWiNjhUZGNW1W+qu066e+djr2tyzkxMAW/qm9pHCsPkF6Rnt68YNaIoLhZrvyuxWpx= ofZrz8taiekGBv7zxCu9N1WUr2q7qt2mjVoDpFNf+rqcEwMHSNW5pBPIaKZYh/FHxb6qNPRekVH= bU/rs1D6n/0frbcVO5avarpP+3qkvO7qc02BV55JOIHUGSPN9itliGjRdpJOfUeybVXx6xDvnnd= LQ5+ABXCyC3mXinfWmZvnb8IZ4d6RT+aq2q9rtlP7e6diLupwTA1Pwq/qWxqnBz0G2lJZXl5b7i= /JVaeirRBr7J+I1W+LdkgbuxXd4CqcU+zqV39yl7brp7+Vjdzsu7Sn4nfqW0hHXHCB1fnZOacyN= JgY5kmYWf/MhXEqDTDZw6pZSSimllFJKKaWUUkoppZRSSimllFJKKaWU0vjwP+GiJvvrzwGzAAA= AAElFTkSuQmCC" width=3D"200" height=3D"49" alt=3D"" style=3D"margin:3.6pt 9= pt; float:left; position:relative" /><img src=3D"data:image/png;base64,iVBO= Rw0KGgoAAAANSUhEUgAAAHwAAABcCAYAAACsstGIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAA= OxAAADsQBlSsOGwAABGRJREFUeJzt2m+oX3UdB/DXnWtuLZebLWXObQZSQVNbS/wLhtIfk62ByK= 2RNfwzi/5BT3ygIYqP9JEgqBOMihRrkQ80xkBHXP+CNKRilIIKBQblEyFHcteDz7nes+P53d89u= 9sY4/2CH/d3zu/z+Z7zO99/557vj4iIiIiIiIiIOCFchmeb1xVHkP9jLFnA8b834LijYpfhJtw4= z3KGxp80zsDVOBVb8PLA/FXYg6sG5FyM0wceZ5yv4G3sPEbxJ41FrfdrsGtg/pexGQ/PM34pnnT= 0Kxy+Y1gFDo0/YS0aH/KB6ebvWtyKuwfkLsb7eAWrsaEn5mLsxqvq4t6hRpJ3sE2NMLepHgd7cQ= i/abZvaLav6omFC/F7/BHnNPuWNMc5gH3NOcwVT00TT2IKX2uVcy+ewaVYN+I69OV+Fo9iIx7HH= 7B+RP5x9xF1UQ/hV2p4n49LsLx5/w01l7etw+9wJj6F57ASfzXbw2/GQXy12V6KB/G5ZvsUdUEn= emJXqor7dFPez1WjOg8PNN9jG+4bE79WNZDlzWdvqAZ8UfP5R7FVf4WPyn1CXc+vN/l3qMZ7wli= mWvF+87+BesRsQzmEPzflzLheDZtd7QqHO81WItWQZi7OBtUg+2K3qAs5Y9LsEH0avq165/1j4r= d0vschXK4a6lPqxm5Nz/cwR+4ivNX6ntvVTeIxMWRIn/FfPK+GoekxsVQv2q163szrL/hS5zxWz= qOs9zrbL6lGt7gp938jYlf48Gi0RPW6Xfinw6eoUfGL8M3Od5lSN3WTavp5FJ/vOfdRudN4tyf+= mDiSCqda8Xn405i4FapnTHX2/xa3NOVMqLn9VnWhlqhKPEvN+x9vciZUT/pEq5xpPI1r8J/W/m7= sq2qYv0SNLOtwO36Kv+EFfFINqXPFr8H3cb6aUr6gpqBL1Zy/B79s9nftH5F7WnOuq5rzXt28Jn= rKOK4uVEPsATXXteepCfxa9Zi2mRurX7T2ne3wYW1mDr5WzZt7zf7r9rNm+zPY0crZ3CpvOX7SO= W5f7KSq2IfwgyZno7pZ29XE7RsTv6I5t73qPmNrE7tJ3fBNqelrtX59uY+1znWy9X7LiDIiIiIi= IuKkcsoC81fhR/gYXl/46Rz18uIo+67Dn1mfaOVFx0J7+P6mjH/gtYWfzlEvLzqGPlrtW947OEd= 83/Ljv9WTpKVmnyxtb+UcHJMfC7B4QOxaXIlvNe/34ItjctarZ+IXqOfd16n137ebz59QS4VD8l= 8ccM7RMaSHb8JdamXngKqMuSoL/q5+iHA9fqh67L9an0+r4XtIfizAkAoftbw3l1HLj12jKnK++= TFPQyp81PJed8my7TL9y49vqhWwNWqIv0cN2d1lzVH5cZx0l/e2m13O6/v1y7n6lx93qF+97lT/= iu1Uy5zd8kblR0RERERERERERERERERERERERERERERERERERERERERERERERERERERERERERER= EREREREREREREnOz+Dy677wVb2+MYAAAAAElFTkSuQmCC" width=3D"124" height=3D"92" = alt=3D"" style=3D"margin:3.6pt 9pt; float:left; position:relative" /><img s= rc=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAJQAAAAiCAYAAAC5r/C8AAA= ABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAAypJREFUeJzt109oXUUUx/HPS1= VSDWpM/6lFUZC2Yiv+w0oNKK21/kGxGyNVMVYputKNFGpVBHXjThAV8T8qiGgXRcWCizYupIsgp= SsXrbhyoaAiCkpcnLm8eY+XNg9JYsz5wvBm3j1n7rlzf/ecGZIkSZIkSZIkSZIkSZIkSRYJ5+PT= Gdpeg49wGPfhhlmKCR7B6Dz4Jv+CFp7ElzOwPV0I6TIsxSZ8PnuhzSsbcfZ8B7EQuQXXmpmgzsK= EEFPD5tkIap4ZxD4pqL5ZidtFyZuJoOBefILrRHbrZlS8jENCrA3byj2mqvZz+R3EWOnvKPYj2I= 2by3gNXscGvIavcHGx/xbPVvF0+/aKax3exHp8iM9wYbF9rorxrvLfxvLch7EHZ0y7QouUFnZiQ= H+CgkvxCt4r/YbV2CsWew2OYTmG8IsQwArsF1lxhbagBvC0tqAexp9CiPB2sb2zzP8EXsIlGMZR= rJrGt1dc+8p8t4lSvhf3V89yVDtDnYcDQnDDeLXYJxU34YLS71dQDZswWc1zh84MNIXrsQTv4gq= cibe0N/ONoOAhbUHBM9qiaOGItmi2ir1fw/4qjm7fXnGN4ntt0ewo92+oBXV3ma9hgxBlrwz9v2= KgD9sxHBeL+wO26Hy5vRjBldV4Ah+LbNPc/x6x0E07hL/xMh4r4yM4OM09Tqv6f1T9KfzaNT4Rt= W+vuA7it5PM0dDCudX4J/w+Q98FTT+C2qm9uKtFSm/pfBG92CO+0KW4CDfiu3JtEo+W64O4SpS5= Fh7Ag+Xai0JkhKjXirKyTuxfbi0+K7Gs2A0JQQ+X8UhpS0QpG6lsu317xbW+2JxT7JeX1mSdv8Q= hBL4Wgtxa/LeIfdzJRL1o6S55LbwvhFYzgssxLl7SF6Kc1Gwuc02I/U4zX7MHatoL4gMYxzfYJU= S3SwhkvLK9Gm9U421V/3G8U417+faK64PKZqzqN8/zVLFfW/kfEKVwt86TbjLHDOk88Z2K7SJDJ= P9h+il5c8l2cRpchlO0y8uP8xlUsnBZhedFmZwUR+7hE3okSZIkSZIkSZIkSZIkSZIkSZIkSZIk= STI3/APh/qZfb7z1lAAAAABJRU5ErkJggg=3D=3D" width=3D"148" height=3D"34" alt= =3D"" style=3D"margin:3.6pt 9pt; float:left; position:relative" />Proceso del aula in= vertida<img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAkIAAAEuC= AYAAABieX28AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzt= vXm4XFWd9f+5BmICEQwBQZQwCG/AljQgSgAj2Mggo+QnEowNAQTEfkUBG1REAUV9lbZxREExgIi= NKIKNGFFBAQUHyBMVURQSnBhUQFGCQO7vj3WOdWrfvU+dU7fq3hrW53nqSQ377LNPJan61t5rrw= XGGGOMMcYYY4wxZrgYmewBGGOMMVV48LTtRjc4e1nt761LL710tBvjMf3NokWLRgCeNtkDMcYYY= 1rx4GnbuZgxXcGFkDHGmJ7GRZDpJi6EjDHG9Cwugky3cSFkjDGmJ3ERZCYCF0LGGGN6DhdBZqJw= IWSMMaancBFkJhIXQsYYY3oGF0FmonEhZIwxpidwEWQmAxdCxhhjJh0XQWaycCFkjDFmUnERZCY= TF0LGGGMmDRdBZrJxIWSMMWZScBFkegEXQsYYYyYcF0GmV1hjsgdgjDFmuOiXIihPJzeDjWeEjD= HGTBj9UgSZ4cGFkDHGmAnBRZDpRVwIGWOM6Tougkyv4kLIGGNMV3ERZHoZF0LGGGO6hosg0+u4E= DLGGNMVBrAIehHwReBHwL8Du0/gudcDTgX2Ljx3PDB/AscwkLgQMsYY03EGsAhaCzgPOBMVH3cD= b53A8x8InAUUt/SfB9w4gWMYSOwjZIwxpqMMYBEEsCbwOPBr4DHgZuCDE3j+JcCmE3i+ocEzQsY= YYzrGgBZBAI+gGZjPAzujmZlvBW3mA1cBNwGviPSxDXAhcATwA2BO5JipwOnAncANwLzC8Y8X7s= 9CM1L5UtkuwGhwWxjpaxvgs8C2wBeAaxnyAsszQsYYYzrGBmcvG2Q35s8BtwEnAP8BvBe4I3vtu= Ugz9Jrs/lKkKXqwcPx7gVcCnwJenDjm1cBGwL8C+wKvAm6JjGUBWqY7KHs8kh13P7ATcEA21vlB= X7OBQ4ArgKOAk4HdgItrvxsDgmeEjDHGmOrcAbyexuzQ7Oz5HZCG51E0A7MpmvEpsgD4BfCrkmO= mopmeVwNvzB7HuAB4X+HxzagI2hJ4LfBu4JeRvhYCv8na/x1pnVLnGApcCBljjDGtmYUKl5ybgS= +h2RfQ9+lhaGYmv90U9DGKig9KjlmBipzfo2KmjFXB4w2AU4B3oGW050b6Wo0KL5PhQsgYY4ypx= mnAXGA6sDnwMhqzO8uAN2SvTwNeCGwRHL8u2ga/RskxB6OZnO8Dz0K71UBF0obA+onHa6OlsrOQ= nukZSIsU9vWM7Lj1sj42yG6DvKRZijVCxhhjTDXOQsXKxWgZ6lzg9uy1FagQ+S9UcHwA+HFw/EV= o+es84LjEMf+LxMzPRlqi44Ed0TLbm7N+VqIlsPzxncAeWdvjC+dbDBwZ9HUFKoJ+jWaj/jtr+z= Pg6jpvxqAwtBWgMcaY4eDSSy9tayfbokWL/B05BHhpzBhjjDFDiwshY4wxxgwtLoSMMcYYM7S4E= DLGGGPM0OJCyBhjjJk4YinyncBJ9G3iQsgYY4yZOGIp8p3ASfRtYh8hY0xX+bc33zj67XPn1/rQ= P+FLew1qcKcZJx/5/77R71valzDkIae9hmeEjDFd49/efKMLGjNIxNLlr0PRGV/MHh+ePd6bain= yf8raT0M5YKPAIspT6OeheI/lyJgxTKLP21wJ/Ag5Yq+dPV+WPh+7vqnAB4Fvo4T7PFttYHAhZI= zpCi6CzIBRTIo/Gi1FbYBS3j+FHKIBLgVeisJM8xT5D6Pk9xjbFO5fDpyR3d80cfxslCf2BpRkf= zgKWT2TxnLbxsB7kPP0ntkxJ2WvnYkcp2ej9PnvofT51PVth2JE9s8eDxwuhIwxHcdFkBlAUuny= q1B0Rh7IuglwC3AX1VLkHyjcXw38LrufOn4emrW5HxVbu6JCqZhEPx/N6qwEHgI+joqbEdLp86n= rW4l0TYcBPwTuLXuT+hEXQsaYjuIiyAwoZenyt6LiY43s+SeIJ79XZWrJ8U8DZkaOKSbRj6B8sZ= w/00i9T6XPp67vflQ8PYSW1Lavdym9jwshY0zHcBFkBpiydPnVwNeAfVHRAZqpqZIiD5p12Rota= W0DnA38R+L4HwOvRwXJVFSAbRT0+T1U1OyVjfXlwPlIf5RKn09d3y5oeWwpcEn2/EDhQsgY0xFc= BJkBZwWNpPhvoRmbuwuvfwMVDo9kj3+AtEIfRknvW6IU+dcg7c4lNHx/zkSFygHAT7LHlySOvwt= 4S/b8NagYekWhzx3R8tXBSEt0GyqUPpWd63wa6fOHovT596ICKHZ9q9AM11KkIbqq5vvW8/T7Nk= RjTA/Qqgjy9nnTKdrZPu/0eVOGZ4SMMePCM0HGmH7GhZAxpm1cBBlj+h0XQsaYtnARZIwZBFwIG= WNq4yLIGDMouBAyxtTCRZAxXcHp8ZOEQ1eNMZVxEWRMx5iHHJwfzh6fN4ljGWo8I2SMqYSLIGM6= xjTgbZM9CCM8I2SMaUm/FEHteMwYU4N5wH8CW6H8rtyteR5wKsoZuxI4l0Y46odQ+vu6yBF6JUq= VPxDFViwAvgscA9yOjAu3KTn2T8gQcToKXb0Mha5+MRvDIuA+lFN2CzJcPBs5Qr8D+C1j88K+n1= 3DBcCxwCEoAHZ/ZNo40HhGyBhTSr8UQcZ0mVjq+zNJJ72nUt5Bxc3PUWbYlagYKqbHlx1bN62+S= nr8nig49tPZ4+tRQfW1kvdjYPCMkDEmiYsgY/5JMfUdlCUGyvPKk95BM0VXo7iNeTSnvE9P9H0B= 8JzC44Ulx1ZJqz8S+Gn2/ErgXcCTwLUoxDXkUeBClE/2A+BlwNfRbNfA4xkhY0wUF0HGNJFKfU8= lvY8ST3lPUUyPTyXEpyhLq6+aHn8z8Hw0s7QhjfDYgceFkDFmDC6CjBlDKvU9lfQ+g3jKe7789S= TS/sDYRPpUQnx+bJ20+qrp8U+hQuoM4GdV35RBwIWQMaaJASuC3oV+mee3KZM7nDFU9Y5JtZsOv= A44uuL56rYvsh4S4+7dxrGDQCz1/T7SSe+plPcDsv6uQJqcrZEeqJge3+rYOmn1ddLjrwWeh4qp= ocE7LIwx/6RbRdBEpc9Hdo09De3G2R+JRx9v0UXo7dJpOt3/3sDFwDvRl2+n2xdZnB1zENKP9A1= On6/MmsBxwMcmeyATiWeEjDHAwM0E5awG/pDdWhVB3fZ26Ub/S9FMRLfaF1mCZiXM4PIK4DuTPY= iJxoWQMWZQi6AY2yDB6LbAF9BSwKbZa0Vvl4Oz5+ajpYSb0JfENmh3zRFod80LsuPuBG5AMz5kf= 34JWI5+YY9E+p+FdvnkS03XoeW7L2aPD88eHxy0A2k+voL8ZzYpPD81MZ5U+xipPqB1MWn6k/3Q= st50tNQ2VHj7vDGm9tJVH3MmMou7AvmznIz8WS5G3i4HI3Hpw2gXzu7Aa7L7S5GIdF+0RPRiZKy= Xe7fsi5bffo9mXY4H1kbajcsj/R+TjeegbGwHICO+fFniUuAepCEptpsJfCQ7/v7smAez14peMv= l4flHSPkasj1tK2pv+5xqGwDgxhWeEjDHDxELgNzT7s0xNtN0BOAttY74TFQjvQ4XFr7I2Re+WN= 2Z9Ff1m7kZ+Mw9F+r8g6y9nFTK12yF7vAkqQMJ289Hs0S9QQVXU68TGU9Y+RqwP02AfZDh4LSpS= JwuHtHYIF0LGmGGijj/L09C26JHC7SZUQOXEvFtSfjMxVgWPb0Vfbmtk53si0m4d4OnBcXmxEht= PWfsYKT8ao/dmIY3oiZ0n8NzzkJN1znnAjRN4/oHFhZAxZpDJze6ehfQPrfxZit4uy1CcwlwkdH= 4hWi5aj4asYFfGerek/GbC/kPvGFCh9jW0JPXnRLvlaJlr5+yaZqMMqUMS4ylrHyPWR2q8w8bzg= BXA39AS5mcn6LwOae0iLoSMMYPMO4FPIn3N39FMR1VvlxVIm/NfwLfQbMCZaInsPFRA/YCx3i3r= EvebCftfTLN3TM43UDzDI9njsN1y4E0okPPc7LrehzRMsfFMLWkfI9bHjkgrlY9jGJdkFiHxeO5= NNRvN0lwJ/AhpwNbO2oai+n3Q3/tc5P9zPfo7XoT+Ps+iUYzHxOrtCu33SPQ3Ffgg8G2kWZuduO= YdUKjrTkhofzmwWaLP2HWnNhP0FMMikDTG9BEd9BEyppM+QnsAL0EF8cZIZH808Bfg/SjZ/d2oO= Hol+uK/FWm/Ds+e+yZygd4Eidj/iDRr/4YK5q1QwXkSmhncFRXWd9AstP8YDU+naTSE9j9FxqG7= oKXcLSP9XY5mLC9Bgau3MzaRHrSTbHtUEN0JnAhsDnwgMcbwulPX0lN4RsgYY4ypz3waYasPobD= Vo9EEwwKaRfWL0Y7DW9Gy2jIkpr8rO/YeGrqtKmL1qkL70UR/K9EM02HAD4kXQdBIvF8OPIYKp0= PRJoDYGMPr7gvhvQshY4wxpj6psFVQAVIU1Y8Cfw0ep6gqVq8qtI/1VzWINTzHE2jJ+NmJMYbX3= RfCexdCxhhjTGtGkOh9Y7QLLxW2Oop0YkVR/Qyk68l3E87KblOQrmgWDRF6SqzejtA+1V/VINac= XGh/KFoOTI0xvO5Uu57ChZAxxhjTmlcCnwOORTMlvyMetgpapiqK6j+C9DJ3IOH0ZUg7c0LWZie= 023Bt0mL1doT2JPrbnOpBrADPR0to66PNB6kxhtedatdTWFhojOk5OiyWPh4JSKt4rlRpW6e/GN= PRbqFR4DNt9gH65X0M0pukdoAZHLo6DtYE/oFmeJ6a5LF0Dc8IGWMGnTrGc1XajtfI7qXA2Yw/4= uhAmrddG9NpZmV/PrO0VZ/jrDFjjJlY8gT4aePsZwmNwFhjOs004A/Z/T8ywAW3CyEzhksvvXS0= nSnh0RtKd0KYIWZk90n7EJ2Flo9uRwXINqgI+RAywFsXuUCvjLQF+aH8J9J3fBzpNGJtTkVblq9= Efi5/i4xlO+AMtKT1DRrBp/ORt8osNFN0beJawrGcT3Ma/NRsHIuQH81bkXblbCSGfQfyucm3So= fn/VZJ2yI7ZOM4F5ny3Yfe0xWJMTyStf8O8s85Cmlrim0c6tp7rGKAi58iXhozTbS7lm5Mj7IAm= d/lH+hnIqHpbPSF/D0aXilh29noC/4NSCh7OPDaoM3GwHuQcHXP7JiTIuPIE+NPRUtaW2bPFxPu= j6YhMg2JjSVcriimxn8YpcZvhzxd9g/6jZ1390TbkE+jrdf/QM7Gy1BRmRrDe4EjkSHfi1HxFrY= xZtLwjJD5Jy6CzAByAfCcwuOFaGalmD4/PdG2mCIP2goMzYGqRVM90EzN1ag4Gg3a5QnwIDfgdW= kk3J9VaDuHxmxRq7EUKZrXHYkE3StRJMSTaKbp91nb2Hmfjoq0sG3IbshJeTkS0F6CzAJfnxjDA= uDnxE328jZGjFeIP5EMjFjfM0IGcBFkBpqiKVyr9Pli21SKfLFNmalekVQCfCrhPqRKon0d47zY= eb+aaBuSMtl7KjGGvjTZmyRCIX6YON9LDIxY34WQcRFkBpnQeK4sfT5sm0qRL7YpM9UrkkqA35i= xCfdbRK6jyljqGOcti5z3VYm2KUKTvdQY+tJkrwfo9cT5JWjZs+9xITTkuAgyA85imo3nziedPh= +2vYuxKfKvCNrcS9pUr0gqMf5zjE24vztyfGwse9CcBl/HOG9F4rzjMdkjMYar6EOTvQhzqJ4gD= +XJ9J8FtgW+gJYhN2VsonyYON+qz2Lq+xz0b+IqNMP4Cqonxs+JXHvYV87jkbZ9R99PaZn2KSuC= vGvMdJK6u8acPt/T9J3JXocMFeskyJcl018OHIJE6dcDJyMt19NpTpSH5sT5Omn3z0X6qw9l95c= iTdYRtE6MD4n19SKkY3srml38euS4vsEzQkOKZ4KMMW0yFCZ7ERZTPUG+LJl+IfAbmgX7UxmbKB= 9SJ+0+F8M/imaANs3OUSUxPiTWV2zWqG/xrrEhxEWQMaZN+tJkr0NRGXUS5MtE9GWC/VCIXrXPU= JCei+G/UHguF6lfgGaRDk4cGxLra6DwjNCQ4SLIGDMOcpO9/DZM1EmQLxPRlwn2w0T5YuJ8nbT7= mBj+YKolxofE+toiMd6+xIXQEOEiyBhj2qZOgnyZiD4l2D+XsYnyxcT5sj7D1PcVjBXD/y/VEuN= DYn3djcw4i2L9vmXYKvqhpW4RZLG06SR9LpbupsndwJjSGdOveEZoCPBMkDHjYrxp82UMjCldgl= 42BDQGcCE08LgIMqanWcKAmNJF6HVDQGMA7xobaPqlCJrEZHIz+GxDc/L5vyOhaDF1/SQkPL0C+= bscjnQTL0dLVsW0+amMTWi/j7GJ67ckzp1njRUJTeliafZPRM4bS4aPJdTvFOnvb9n4TkH+MKch= 0ezr0fbsWD+jjE2sv590En3REHBBdu7xXJsxXcEzQgNKvxRBxnSZMPn8b4xNXT8SiU7PzI65FIl= Kv83YRPpYmnsscT127lgRFJJKs0+lyBeJJdRvneiP7LoWZ88dhXYl7Zbo55nEE+uXkE6iPw2Frc= 5ERc94rs2YruFCaABxEWTMP6liNLcZmgHaIWuzCZrRGWWsyd1KNMtxGIqXuJfmNPU6RnUxUqZ5s= fOGFBPq70bOwXMT/ZUZ+8X6eYj4e3dydu7lwGNoB9GhaEt5J6/NdIfpwOvQ30NV1kOzenu3atgv= uBAaMFwEGdNEymguTHu/FX1Rr5E990ThmKLJXSzNPZWm3sqoLkbKNO+ByHlDYgn17Rj7pZLuY+/= dDUGbYhJ9yHiuzXSHl6JlyToymYET+LsQGiBcBBkzhipGc1ugouBrKIPpz4XjQ9O4WJp7Kk29lV= FdrP+Uad7OkfOGxBLq70r0V2bsl0q6j713m2fnjiXRQzVDwCrXZrrDUrQMWoclDJjA34XQgOAiy= JgoVYzm8rT3b6Ci6JHC8YtpNrlbxdiE9lSaeiujOhhrSpcyzYudNySWUP/jRH+QNvbbJtLPfYn3= 7p6sr1gSPVQzBKxybb3ADshEcSfguyg8dbPstViCeyopHmTIeB0qSPPbKyJ9xFLfpyJh+rdRYT4= 7e77sfCHbAV/JrmOT4LVU0nyRmMA/du7UWHuKgZnaGma6UQRNpKFiZNfYh4ATI01vRf/hJtOEbj= raHTQKfCZ7rpuGe5NFeJ0Teo09Zqho0vRdEv04uA3Nku2ANFInohmxYxib4F6WFD8DLaNuh5YmP= 4uWmt5K6wT5F2Xn3B4Vz3uiHY1PlpwvZCYqdI5BS73notnMT5Wc88Ggj2LqfNm1vjgy1p7TgHlG= qM8Z0Jmgk7PbB2loEdYAPpa93sk16rqGb7E19fEa7nXbdK6d/sPr7KapoOlfhimJfrfsz5gwPBT= GlyXFP4YKkXXRbNiD6IdHFWH/HOLi8rLzhcxHs1G/AB5GxUxOO0nzZefuCyG8C6E+ZkCLINAsxP= 3Bc08Bn8vuL6Eza9TtGL61s6be6TFMRP+dvk4zeIRJ9INOmAxfFIaHwvgykfpTwCfQkuhNNGZaq= wr7Y4L9svOFrAM8PXgu3+mYOmcZZeeOjbXncCHUpwxwERRjBNgWeF7huXCNuki4xp1apy4avh0M= /Al9GE1D/3lH0fIQpNfUZ6Fp4nwr6dSs3zvRjpp5SD/w2ewavgBci35pxcYQG3+Va8zPHV5nnWt= MXWeVazTDx7Am0ceE4aEwviwpfgRpz45CwvNzUHFUVdgfE+yXnS9kOVoWy69jNjKyPKTknEWqCv= xHE2PtOews3ae0o+HpQ/4zu+VsWeGYoulbvsZ9LJpufhdap/5t1vY0VBzsgqaIb6YxE3U5jSnhm= Sh5urimnq+Z54Z7B2WPi+Z6+yJzvdnoQ+YK9OF3Mppmvzgyhtj4wzX6VJvNI9dZ9RrLrrPKNd6C= McPB85Eg/Erg/2XPFYXxx9EQhr8N/T+6GInPc6YhXU/O+9EPpmIfK2iI09cCPoDE789EP0aWoh8= jb0P/T8vOV2Q58CakA1oO/AR5ZS1FGp/YOYvkAn/Q0teNJedeFRlrz+FCyPQyH0TLMyPoS7cK+R= r3WYXnno5mRZ5EszG/Txz7QOH+auB32f3imjpoTT3fEnwB8JzCcUVzvSPRtPdCNGtSNK6bXmP8c= 2guhFJt7kJFUNl1pq6x7DqrXOOgMF5R+HiOdxJ9f/AZNONR5JWRdt/KbiFro5nhI7LHawIHoCIi= 7CfWx23Zny+peL4YX8huMVr1c2l2q3JMaqw9hZfGTD8wir4cfl2hbWyN+6u0v049lfI1dWjWDsT= M9VLGdTGqrNHX0Q5UIb+WsutsdY2DwnhF4eM5fuCM6gaMTgnDF6BZpfXRZETu3/RA2UGme3hGyP= QiU9DSy1roS2EU/VvdAc1QfJPmNeoiy9DU7B3I5O5f0JLR/ehX9lponfr2rH1u+PZw9ngl8jx5A= E1VH4bykY5BnirL0FLXychb5YpgLEVzvQOy8xWN6x5BH3rTC9dWHENs/A/R8LpJXeND2Xs2JXKd= Va7xfjRN/l+J62x1jWb8LKGhHTO9RSgMH0+x+g3gBPQ5BvAltCN2mHSfPYVnhEwv8kEkIPwPNJs= yinZoXIsMu0ITuiIriBvmpQzbioZvZMeej77gf5I9vojGmvq5aHkrX1NfTLPhXsxc7wrixnUHRM= aQGn+Va0wZ01W5xu/QrB0oXuf6Fa5xR3qTOiZ4O9EsCi8Tuc9DX2DLkZ5jhLGi8tS5y8Tm4SaAq= sL/Mr6P/g/lyzmHZI/3q3CsEZ0Uht8HvB2JiLdDs6oPjbNPMw48BWs6RgcNFc2Q00FDxTomeMeg= X+YHIX3U5aho2B+4Hs2OrUTFy7lID7Q2KhD3R6Lx4vGpc38AFZYnIbH5rsjJGZqN6mLmdsdmfdQ= xqJuRjesTqOBbH+3wuQzPQhjjpTFjzECzG9oJsxxtUb4E+BnK0loA/JyGgV0oCk+J3Ivp7KBCJn= Z82bmriM3HI/wv8iia+ToMFUIvQ4WWi6DeY1Id3YcVL40ZYwaZOiZ4Yfu66ezh8alzP5tqYvNOC= v9vRgLdTZHe68/lzU0H6AVH92671g8ELoSMMcNAFRO80Ciubjp7eHzq3Km0+vD4mLndq2jPoO4p= VHydgWalTHfpBUf3brvWDwwuhIwxw0AsHT1Mh19Msyi8bjp7eHzq3CmxebgJYAX1hP+tuBa5s3+= /xjGmmV50dE+J+qu61vdFQnw3sUjVdIwOiqUHwViu1dr+IFxj1+igWHoy09F7LZl9TbTD7WOtGp= ooddLg70X2Frmj+7OQpmw6+jdxOtKmXUo6DX41zeL7rYiL7FOi/txio+haX2f8Q4NnhEwv0mvGc= u2ss7da2++1axxUJjMdvdeS2V+BbBJMe9RJgw+p6uheTIO/ANlX5BQd3d9Iw+x0IfAbmkX9RcPX= Tox/oFnjwdO2884BM4YNzl42mV/QS+gdY7l8nf2IVg1rsoTeucZBpZMmeP107pD9kCj7/yHfKNM= euXg9Fk2xEM2mfBYVK7dH2oS04+h+DiqQ3k1juauqc32nxz8weEbI9Cqhsdw85PvyIxQkujbV1r= bnIDPBuUjzcT1KU16EtjXnszKp9fcq6+ytjPlSfbcyz8uPHer1+3EwmenovZTMfg2aDfifSR5Hv= 1MnDR4aju45uaP7xugz42y0xFWWBp9ydC+K7FOi/pFgDHXHPzS4EDL9wMYo5uLN6FfLbLROvh1a= Z98f/ceP8XbgaLQOfiISEp6ICpbd0C6cDWlOVP9w9jyo6Po5Wse/kubk96PREtg5aO39TuDF6IP= mTBpfgKm+i8T63aDiNRpjus8KetPRPSXqP4BqrvWx8Y8An8/aDDw2VDT9wHw0S7Iye/xx4Gr0Ad= AqbX0x+oVzK/A39KtoKlpvB7in8Lhdk7vXot04KWO+Kn2PJ1He9B+hcZ7pD+qkwZ8VPP5sdouRS= oM/L3i8e+T+Ydmt2FfO1cHxdcb/msh4BhLPCJl+YASZ0OX8Gf1qeoDW5nKjwF+DxzGqJqqnkt/L= jPmq9N3pRHnT24TGecaYScL/CU0vEhrLfQ/N/nwJ+Wy8PHu8M/G09SIz0O6dmcjrZVZ2m4LWyWd= l59mKdKJ6q3T4Jyk35oultcfM8+okypv+JjfOmzbZAzFm2PGMkOlFQmO5e5FQ+RQ0jbsR8CnSa/= NFPoKKnDuAfVDQ5JuBE9C0807IKfgnpBPVW62zn0m5MV9sbf80qpnnVblGkyYUss+heqJ7WXJ9T= Lyfny+VWA9x4zwiY0qN3RjTYUa8fd7EaGf7vNPnTafooKFimDBfJ9E9lR7/LjR7dzQKVX0/8Fu0= 7FlmbpcyzrsmMqYXoVnP4tiNMV3AM0LGmEFmATKqy4XsMVO5PNE9NJTbLftzOfAYKpQORbN7uXj= /ISTePxotd5aZ26WM81JGd+HYjTFdwBohY0zPEZnZaZcwYT5lKncDYw3lUunxEBfvQ7m5Xco4r8= zoLhThG2M6jGeEjDGDTJgw306ie5ge/z1UuOyV9ZGL90cpN7dLGedtHBnTFpGxG2O6gAshY8wgE= ybMr6B+onuYHp8S70O5uV3KOO9ziTGFYzfGdAGLpU2UPhJLt0p57wQ2vxtOei093hjTBTwjZPqd= VinvncDmd8NJr6XHG2O6gAshY1qTm9+Z4SFMjzfGDCht/8JtZ+nEmIpMBU5Fy1H3oV08t6FZmRc= igelvUXbYMWiHz9Ls2H2Qd8vLC/1tjYr+U5A+4zQkRH092gIdO98tSEB7BtJ8fAN4sNDnvOyYTZ= BXzblIZxKO8V7izAfegmYdzkbaldT4Yu9PeJ7bs3FOR94zl6EMtEsT5zfl5OnxxpgBxzNCpheJp= bXHUtgX0JzyPgMZ2h2Hdu58DRUsv8jaLUY7dY5CO39yn5jY+WYiV+pTkcfMloXxbQy8BzlD75n1= eVJijDFiSfPvLxlfSOw82xRevxwVcEYcjwrPfut/OvA69G9kIvtcD/2737uD5zWmZ3EhZHqRYlr= 7G9EMyErGmt5dgHbd5DyGdvysi37RP4g++KHc6C52vpS0Sbh/AAAgAElEQVT5HdlrMUO92BhjxA= z0zikZX0jsPA8UXl8N/C5x7DDSbR1Zlf7nUV9r1A1tWpU+D0T/Pj0jZoYCF0KmF4mltadS2Iumd= 08Bn0AzNTfRvJuszOgudr6U+R3oCyJmqPdAYowhsaT5G0vGF1I1kT5VSJmJZRrwtjaO64Y2rUqf= S9CWf2OGAhdCphcpprU/C6Wu78JY07swwX0ELS8dhczpzqGx7bnM6C52vpT53SGkDfV2jowxRsz= Ub9uS8YXE3gvQTNHWaOluG/TLf9/EGIaFWWi2L1/maRWKujWySPg+sB/6+/4Tsk6YhgrQUaQni/= UPYwNUT0ezLA8h/6Gy/iAdzBrrOxUYG1KnT4DHE/0YM3B0qhD6EPrPHN5uyV6vs+bcjXVx01/E0= to3Z6zp3WKaU95BXy5P0vg3+D7077zM6C52vqnEze+WkjbUq5oUv4KxBnpvLxlfSOo8Z2bXeQDw= k+zxdxJjGBZCHVmZVmwW+jt5P9J+7YWWWcv0V2H/Mf3XucDPke7syhb9lWnTYn3vTmtdWt0+bd5= ohopOrT2fjHaubERj2nUK+tUMjTXngyr0la9hv7NDY2vFPKTTeHiCzmdacw/6cM4p3n9J4f5ns1= vODPQr/4js8ZqoKNgA/Vs8rNA2zHWKne9HkXY538puRW6LjDFFePxVLcZX5Tzh+2G05PmcwuOF6= P98UYuV68h2RUnwd2WPf5C9Vqa/CvvP9V9nFZ6bE4yprL+iNg2kTVu3pO88MPZJNLv1e8ZSt89w= vMYMNJ2aERpFuoUiTyHreKi35jyRni3trt2b3mQBikNYHxX5+fLSA2UHmYGnqCMr04rVETMX9Vf= F/mP6r5tq9FemTYv1/VVa68Xq9lllvMYMDN3SCI2gNfjnFZ5rteacWsOeh6aTf4T8VdYOXvsS0n= Mcl503tt6d0gWEa/ckjg/ZAfm07JSN93Jgs8K5LkSzEj9Av67CPsuOn5qN606UiD0v0ucLIm2Mv= H5mAd9E/16ORu+tY2SGl1BHVqYV+zlaNvs/SCe2RaGflP4q7D+m/9oCzdisW6G/Mm1aO4GxtNHn= FsE1GTPQtJ01FjFUXERjBihnS6R5AAkKl9G8DTlnJioUjkEzS+ciseJXUdrz0cBf0Nr9b9HOntl= Zu+NRcXQJcCyaFfgQWvteCrwIbW8+BK2jX4+W8lZmfd+BRIYPZ8ccGTm+aKQHWprYHhU0dwInIg= 3LMahoeyUqTm5N9PkXVJTFjt8K6V5OQh+Mu6KCsthnrM1bIu/rhDJJWWPGlHEk+hEB+r98MppBA= c2EXJbdPwi4Gn2GHAv8L7IzGAE+nfVzPBJSP45mWD6HLBeK/f8I2AN93q0FfAB9tr0T/SB6I/o/= n+rvb9n43oQKmJ+g2c0L0edG2Pdv0I+nc7J+38bYzytq9jmDxmf5S+l+hI0xk0qnC6F/RctaI9n= 9v1KtEDowa59vXV6Ifj09jH4tnZE9Pxd9WG2OCpvpKKG52E8oUJ2PBJErsuMfzsY6HX3AFQuh1P= HhVPEz0AdIHsa4CfAzVNCtRr8sd0W7Q2J97oVmL2LHP5X1/0r0YflT9AFW7JNImxOYZFwImQGj+= DlhjBlQurU0NoqKnl+3apiRWsNO+bWAxj4zOCa13l2mC6hyfMiq4PETqNB6Cl373wuvxfq8oeT4= mKdN2GesjTGmc+TLZutjY0FjBppOFUJT0I6xtWh8aKwBvBhtQw3X0UNSa9gzifu1jAI/RllM29N= wAv4d8fXuMl1Ace0+tV6eIh/voWiZjayv9WjsyIv1uXnJ8TFPm7DPWBtjTOc4AFkYvA9tLTfGDC= idKoQ+iNao/wPNvoyiWY5r0Zr5a2j4vcQyeZYT92y5lLhfC2iL61uQ98s1qBj6IWP9We6m3EPmC= jT1vTVxf5e7S677+dk51wc+mT13ERJi534csT7vKTk+5mlzVdBnrE3uozMohEL4mIg8ZSYXa2tM= Ha6mMYPr4FpjBphOaoSGiTWBf9DQ+Ez08T1JBzVCMSH8CcgArygQvxzNCF6CZh5vR2aHPSkmN8Y= Y03t0MsxvmJiV/flMGuLliTx+0JmHZsFyb6pdsz9/iXbp5ALxlcC7GGsmVwxRzdsa0w2mI1H1KN= oBBirgizl3xpgexllj9ZkG/CG7/8dJOH4YiAnh6wSxWkxu2qVuSnwszX28afftJNUbY9rEhVB9V= tG8A2yijx8GYkL4fakWxAoWk5v2aMdpvtNO+Ha7N2aCcSFkepGYEP46qgWxQlpM/nk0W2SGi6qJ= 7XVS4lNO+GEafcopPuZ0HxtDbPzGmA7SKY3Qemj7+zL0pdSvtFrbH5Tr7Af+N7sV2T1xPwwfTYW= 2ehv08FFMV8+d3Y9Fie3vQiL732ZtT0PFR26wejMNndrlNMJI8zT3ohN+7uacp9HnAdObot2u/4= pmNV+FCq9D0I7Vo5Db9W7IQiMcQ2z8Mbd7Y0ybdGpGKE+X75WlnnbX2Fut7ffadRpjysnT1R9Fs= zKb0khsPwzZV9ybODaVEl9Mc3+YZrf8C5D1R05RuP9GNEO0EEVj3IysQu6mOcS11fidDm9MB+lU= IbSE6uny3aaba+xL6J3rNMa0pt3E9hRTKU9zh2bn+Zhwv6rTPTgd3piu00mNUJgun0qNT63P58x= BBodzkRHi9cjdeREy1yvOyMTW36uusYeJ7jvRem0/dp1V9QfGmImnbmJ7lZT4dUinuYcu+jHhfp= nTfTiGum73xpiadEssvTHwHmRqtyf6oDgpe207tD6/P/rPH/J2lDa/OUplvzb78wdoHf1V6EMEm= tffP5y9dhoKKJ2JCrHiGvvRNNyZ34s8Zu5EUSBz0dr+SEnfIbG+d29xfcaYiWMFcbf4mMgemp3m= yY49H7nQ/yR7fBFxJ/ylwGIaLvo7EhfuX0Ha6T4cQ2z892DhvzEdo5PO0sV0+UNJp8Y/C83EfJl= mE7x/jgl94LwcuA/ljL0YFVagXUTH01jXj6WwV0mUv5mxie5nALfQWPOP9V28zljfB6Kt36nrG1= icPm+MMabf6NaMUFlqfMoEL2cU+GvwOEUV47zUGnuY6A6t1/ar9D0e/YExxhhjJpBOFULhuvj3S= KfGp0zwcmYgL47cWXhWdpuCdEazKF9/h2pr7GGie5W1/bBNXf2BMcYYY3qIThVCYbr8vaRT41eR= Xp8H+XNshZa39gEuy/o+AWlwdkLOw2uTNs6rkigfpsQvpvXa/mnBdab6Lrs+Y4wxxvQITp83HcM= aIWOMMf2GIzZML7MdmiH8KRKfvxTYb4LOvR5wKg07BWOMMQNIpyI2jOn0zM7L0fbkk1FBMgVFaZ= yIdg52m9xF/KBWDSeIecjq4eHJHogxxgwSLoRMLzID+BjSY11XeP7rqCAaoXw3YSdYQiMIc7LJ3= dKPmOyBGGPMoOGlMdOL7IQcxr8Tee0aVASVJYNXdSffAYnxd0Ip4pcDmxXO1cpFPGQe8KXsHMfR= MOeMuayXJZCHhG7pqUTzolP6nMR4Y8faDd0YM7R0oxCaDrwOOS3nHI8+lKu0BXgB2tW11pgj0qT= OMVnUvWbTYENkqvlYSZttCvcvp2HeCdXdyT+Niqh/IC3QMlSoxEg5lOfMRrsk34BMOA9Hwb8pl/= Uz0U7F2SiB/HvZ2GKEbukx1/PQKf1vifHGjm3l9m6MMQNLNwqhl6I8nuKyWyrVPdYW9AV2AmMND= 4uECfOtkuMnmrrXbBr8Gc3MrFnSJpUMDiowfgbcigqCZcjI8y40q3IPmgXJC4/lqOi6BLmiT4mc= r1UK+Dw0+3I/slDYNTvXfDQjszJ7/HFUmNRJIA+JJZovQGnov2ox3tixK6mWxm6MMQNHNwqhpei= X8XjafhV4pOS4bibMd5s678+wcjsqTHaNvPYCxiZ/5+SFRFV38lXB4yeQN9RTkbatUsCfRsMEtE= jKZX2U6gnkITHX89ApPTXe2LGt3N6NMWZg6WQhtB3wFaS12KTw/CyaU93L2qYS30PtRaiZiJ2jj= l6jTCPxDrRbKeQ69OXzxezx4dnjPWpeM8S1HLFx5u/RoOs57keF7keQO/kMVPy+DOW/5dqdWDL4= vtRzJ4dGivihwMXZc1VcxIsp4D9GGXPbo7+j+WgJKuWyPoPyBPKQolt6zPU8dEpPjTd2bCu3d2O= MGVwePG270XZuQTcz0Rf8HLRctQQVHwDHoC+ufSq03QotHTwdFTjnoC/6L6MvjS3QUsJM5DydL4= 2F50gdszHwTbRMMBO5XZ+ONBXHoS+Fg6hWXEwDPolmKEBfsvPRF1mda35uNoa1s9dXZH3GxkmbY= +1HRpBm5X/Qe/JlVGQWORLpfo5Dy2HHoffxQlSUjqK/g/z+iajQyR+vm/15LPIqejcqUEDC6rxd= rvXaAxXANxPfVr8/+nu+LhjrHujv8w5UIE9HIu28/4WF+wcm3o93Zv1ujZaOb0AzOztm92/Ijv8= yDZ1PbLyxYxehwvsmpJuyTsgYMzR0yln6QCS+zKfaF6IvmTxW4wwaqe6t2oaJ7zehL46LgiEUE+= bDc7w6ccyhaObgjOzxXOBqtGvoQuonxu+MireLkabld2h5pc41xxLs34Vm68Jxbo5+xbczVjOWN= ZFQeg3iy2HGGGMGnE4tja3DWN1GUfi5qmLbmH4hpb0IKZ6jrl7jAdrTSNyKZgvWyPp+ovBa1WuO= aTl+mRgnWM/RSWZlfz6ztJUxxpiBpVOF0HK0HJRrLWYjbc0hjNValLWN6RdS2ouiZiI8R129xs6= 0p5FYDXwN6VL+XHi+zjXHtBy/TYxzFOs5OsU04A/Z/T9O5kCMMcZMHp0shN6EIhHORbMX70Nf1o= tpTnUvaxtLfF8XeEv23DWosLmP5oT58Bx3JY65F2mPTgFuQ8XRp9DsTSox/nRUfKT4BtIhFXe51= bnmFYxNsL8pMU5ajNVUZxXNs3DGGGOGEKfPG2OMMWZoccSG6XcmwlG8l9zA10MhtEVrhv2QeaL/= PxtjTE38wWn6nYlwFO8lN/ADaWSl5ayDNhesnpQRGWNMH9MLH+zG9Dq5G/i0yR4I8qAKw1kvm4R= xGGPMQOAZIdOLVE1Ijzl470PD9Tu/zaE87T3laF7HAb2O43foJF4niR4aztpE3oOyvqqm0RtjzN= AwKIXQi5DBYDv0kv7DiKoJ6QvQjrt8mWgGSqI/DtkXfA19sf+C8rT32PlmooiPU9Fy1JZtjC9GL= MX+/SVja0X4HqSuM3beVBq9McYMDYNQCI0gE8aD2zy+l/QfRlRNSL8A2RDkPIZmPNZF2+MfRIUu= lKe9x843H80s/QK5l3+9jfHFiKXCn1MytlaE70HqOuuk0RtjzNAwCIXQKCpm2sVp8L1HnYT0ooP= 3U8AnkIfTTSiiJRdSryad9h47X10H9KqO3zEn8RtLxlaF4nuQus46afTGGDM0dKoQ2gEJNndCeo= rLUfYWSLNwIXAEMkycQ1yrUKbtKB7/AsZqGv6R9TEf/RK+GH3AQ339Bwx38nsvUDUhPXTwHkHLQ= kchp+5zaGSIPYN02nvsfHUd0Ks6fsecxLctGVtI7Jo3LLRPXWedNHpjjBkaOlUIfRr9Gv4HEm0u= QwUEwHtRgOqdKDn9b4zVKmxGWtsRHv84aU3DH4E9gZ+gLy2or//YGHgPmlXYE30BnpS9VlUHYsZ= HzGF8c8Y6ai+m2cEb9CX/JI1i+n3o3/n5qDj4NQrf/W/0b+uAxPmmUs8BPTa+GCsY6yT+9pKxhb= ymcM3zC+/Bxai4SV3n3Mh5705cy15oKbDMUd0YYwaCTjlLPwP4C40U702An6GCYzXwc/TL80/E0= 9Z3Q7++P4Q+jD+CtgnfgH7VFo/Pz1dMqD8F6UPyMc1C6fTPzs4ftv8m6TT4VEK9k997nxmoOLg2= e7wmKiZuRktXpjrTgYPQzjNjjBlYOjUjtCp4/AT65fsU+lX+98JrMa3Cd0lrO8Ljq2ga1kBC2dW= J9mX6j1RCPTj5vddZADwfLRutQWNZ6IHJHFQfsg7wEpxjZ4wZAjotls71FIeiqXrQTMt6NHZlpb= QKi4lrO8LjY5qG1ejL7gXZ46OAj5a0L9N/pBLqnfze+3wDzQZ+E+m7jkZLrm3Neg4xf0F6vccme= yDGGNNtOl0IPR9tHV4f+GT23EVIp5P7lqxgrFbhHtLajvD4mKZhLtLtfBB9Gd6HdEsk2pfpP1IJ= 9RBPft8Q6yl6hfuQ3ma77PZuNHtnjDHGROmURmhNJJTONUJ16Xdth/UU3WM6sAgVx5+Z5LEYY4w= ZMDo1IzQr+/OZbR7fz9oO6ym6iw0vjTHGdI1OFELTgD9k9//YZh/9rO2wnqK72PDSGGNM1+hEIb= SK5h1g7WBthwlJGV7GzDhD5iCN2FwkdL8eCfIXIaH8Wejfaspss25waRXTzxRboyW/7wP7IcE+y= CpiFP3QWJjdX1TzfTDGGNOCQYjYMINHyvAyFRwa8vbs9c2BE1EhcyIqUnZDppobkg4crRtcWsf0= s8gstGng/ci8cy+0SxJUXOVcTsPXqs77YIwxpgWdKoTWQ19ae3eov17kePQrvFtMB16HvtiGnVT= gaSo4NGQxMvS8FTmZL0Oi+7vQTOM9aDYoFThaN7h0QTbWX2XHVw0y3RW4Jmv/KCrUcor6uNXA7w= qPq74PxhhjWtCpQuhAGssN7TCP9oXWE8V5NEweu4FFwQ1Shpep4NCQUeCvweMYKXPOusGl7Zh+Q= v1/83lBVfV9MMYY04JOFUJL0PJAO0wD3tahcfQzFgU3SBlebkzcjDNkBlp2mpk9npXdpqAA3Vlo= h2IqcLRucGkV088YP0ezV/8naxNey0qkIdoYLZWdDexbMg5jjDE16aRG6PHgcUrMOQ/4EvqyOw6= JSg9ESxYHUy4SrSJKrZoQHxPKpo6dhZY6ikt/+6Dlm9HC7RWkRbYpYW5KFFxnfIPGcuKGl58jHh= wa8hFgK5Q3tw9wGYpvOQHN7O0E/BiF84ZmmztSP7i0iulnHgpb5IdI1P15VASH2XVnZmM5IBvrm= cB3iJuSxt4HY4wxLeiUoSKoUFiG9BzPReLRD2X3lwIvQr/uz0V6m7VRTMX+SIuxC9KDPAvpOaYj= k8bTkfbiUuBKFJ46D+k/tkJfcCehX8q7ImHp9lnfewK3I7fokDrHHgN8DJkmfh3NOPweFTGPouL= nLOBktOtnf7RT6WT0q/7ixPnORsXiMdk1n4tmET41zmsz/cki9O/+060aGmOM6Qzd0qPkYs6zCs= /NQVP8V9Fwi941cmyZSHQBWk6IiVLzZPmVwLtQXEdZQnydYy8AnlM49rHsOtZF3kkPoi+whahIK= 4psp5ecrygKBhVZ65a0r3ptpv/Il+CmZff7wUPLGGNMgbeiZQjQrM3CSJuFaJYj5A6ahaP50hho= J9WRhdduo+Fk/Vy0BLUH8DK0JALSeCxAM1GphPi6xxavD6RfuQgt47wF6U/Ca1mUjT91vtcC7yn= 0uRDtMhrvtZn+40AaS6yLWrQ1xhjTITo1IzSCxKXrZ4+XoeWgO5Bo9F+QBujHwFeRzuFnSKtxF5= rhWBctjUFDJPoA0gUdhmaRbiYtSj0ACU53QUXJ0uzxC9ESUkidY8PrG0Ei16NozlYrimwfQb/wp= 2ftY+dbjnQe12Tv2Wy0nHYf0m+1e22m/7ia9nddGmOMmWTyUMxRGl47e6Bln5uRtiZnfyQMvi5r= A/DO7PHW2eMjkeD0OFRwHIc0RV/JzvFlVGRsjoTEFyAx6g3ZWOYhkfanSRvN1Tn2yML17Yi+sC6= iWSj9PiTKzR8vLNw/MHG+HbN2uS7o/6IZs3Vqjm9DtKy2S+JajTHGGGM6xgyad8KtiZarNpyc4Q= ANjZIZPJ6PCu9ZrRoaY4wxE8HhaAlrfbRMtzGatZqspY110C6y6a0amr4kDyB2IWSMMaYn2Aj5y= izLbqfTMO8zptPkejEXQsYYY8wQkDKfjJl0xowt51DPmHNOpO+yBPoU3UySvw0ZOv4P2nCQm2/G= 3qt2xm6MMWaSceioydkK+DjKGzsYOAfZCZyORPNzkLvyZsBfULzEs9Duu52yPp5Fo/h4GvJfyou= PK7PX8raxvq/K2uyHduidjpZEU8zKzr8V0pB9mIZ1QtlYYueOCfxvQ0XfWshVOj8+9l7lS2lVx2= 6MMUNLJyM2xkunQ0f7IcjVxImlt8cS12fTMLZcRcPYElobcxbT4mN9n0M8gT7FRCTJ/zAby100f= LZi79XCmmM3xpihpZcKoU6GjjrItb+JpbfHEte/C3wCWQ7chNy3byzpNy8GwrT4WN83Ek+gTzGR= SfKjNIT5sfdqNfXGbowxQ0unCqEdkIfOTujL6XK0bJEzDy1H/Ag4DS0D5KRCR8Nw1hGqB5GGQa5= 1wkrLxmomhlh6eypxfTEytpyLZnGKBpep9PYwLT7W97bEE+hTOwO7mSS/DtqhOCs7/6zCWGLvVd= HYs8rYjTHGjJPb0K/U7dHSxNvRr1TQB/830ZT/TGQceHr22kxUAM1Bv6iXoKJnNjJN3BB9Kdyct= Y3pIV6cHbMWMm7Mi5xi1EWqTUjZWM3EkTKfDE06U8aWeYFf1ZiTSN9l5pgpjkUF9BlI6/a6wmup= scTOHZIay36J92ppG2M3xhgzDp6BPmjzvK1NkIh1CnAo+mLImYsEoSPog7lYaCxEXxCvRjt6Uuf= 6dzS78xFULF2Dvng2LrQrFkKpNiFlYzW9Ry8aW+YUc+aMMcb0KJ1aGlsVPH4CFRBPoSLi2YXX/k= xDn7EOmt0pMjUbV8yXJ6aHuB8VUA+hLcOxINIqbWgxVtN7LECuy7mxZb4E9EDZQRNAvhy1Pi6ij= TFmKFgTzQi9BC2NvQklsoOWof4C7IU0EItpJNDPRUXKztlxp2SP34h0QNujwmg+MjE8FO2wWSu7= /2mk+ZmPlhleS+NX+HIa3impNiFlYzW9R68aWzpJ3hhjhoy8EDoW7dx5N1q2yNkDaW/uQFt9i1E= QqdDRWDhrnSDSYpDrDok2McrGaowxxhgzhrwQmtKqoTHGGGNMr9ApjVCegWQDQ2Pa43i0fBvSru= P6esCpwN7jHJcxxpgWTKN5+7IxpjVVnc/3Rrq542r2vxh4HMVyGGOMMcb0DNNQNEjVGdQjqF8Ig= TLNXAgZY0wJvRSxYUyRmLN4yvV7DhLBzwXOB65HRpyLsuPPyo4vc0CPJdKP93wQT5YPnc9nIWF+= cRmrzHG9qvP548Hj2LF1XNeNMcYMMCmNhpl4Ys7i25B2/c7dpQ9CX+6nAB9FTuQz0Q7AjSh3QA8= T6ctcxqueryxZvmj4eQzNy1gpx/W6zudvLfSZOraq67oxxpg+wanz/U/MWbzM9XsE2TZslL22F/= COQttr0Bd8mQP6CPKuyoX/nThf0U8ov70ka1MshMjOlRctKcf1us7nxUIodWxV13VjjBlIBm1pz= Knzg0HMWbzM9XsU+GvhtZRov8wBPUyk78T56iTLF8eWclwfj/N56tgHqOa6bowxA8lEpM/HtBeh= bqJMpxC23QZ9YG8LfAG4loaDdCx1Pkyrh7H6k5hGI6XFKDt/bLzWYNTnx8DraXYWvwsVFbnr98u= RPmcUmXfOolE8zcpuU9Df2ywUd5GTO5kfClycPRcm0n+vA+crS5Z/MjsnqEjZsDDG5Wi5LB/nbD= TjNLNkTCFhn6nr2RnpkZYCl2RjNMYYU5M62ouYbmIv4jqFWNuraCRvr5W9fnhhLMUlh1hafUx/8= iaaNRplWozLS85f59pMOTFn8ZTr94U0lp72Kdw/ERU6+eN1STugpxLpx3O+tUknyxedz48sHLNj= 9nrKcb2q8/miQp+59i12bB3XdWOMMQnqaC9iuokDiOsUYm3nA/fSKHbClO9QexGm1aeS7c+gtZ5= iBM2ipc5f59rMxGMHdGOMMU1MRPp8qL2I6Sa+SlynEGt7I/BoxXHF0upTyfbFayjTYqwuOX+daz= MTjx3QjTHGNLFG6ya12BnpO8q0F8uy1+4Afgn8CwpTvR/pFNZCOoXbE23/gZa11gMeQVP501HRM= UpDe/EwsGt23PfRzMxa2fi+CnwH+BlasruLsXqK85GO6Ls0azGeUXL+OtdmJpZpwB+y+38kvdPK= GGOMqU1Z+nxKe1HUTZTpFMK2l9FYdlpYuH9g1r6ovYil1e/IWP1JTKOR0mK0On+VaxsBPo9mrIw= xxhjT51h7YYwxxpi+w+nzxkw8L0IzpGW8ADlYr9WinR3RjTFmknH6vBkGOuVYnmvJWv1fOYCGz5= AxxhhjzKRRNy2+FevgHw3GGGOMKaFO+nyZ23esHxjrAF7mjn42jRnPgwv9tpvkns+izkei+otpC= OdjbuipflOO6FXfN7ueG2OMMT1I3fT5lNt3rJ+ZxB3Al5N2R4dmo87xJrnnhdA2Wdv/BD6ZvRZz= Q0/1G6bW133fnDxvjDHG9CB10+dTbt8pF/GYA/iepN3RobkQGm+Se14I5cxCXlP55oXQDb2s3zN= oFEJ13zcnzxtjhp5BS583g0Hd9PmU23fKRTzmAH5D0Kbojh7S6ST3NYAH0XXE3NDvL+m36Ihe93= 0r69cYY4YCF0KmF6mbPl90+x5BppUbJPrZiHgq/ObZuWPJ9NCcFj/eJPfVqGh6AVqWOgr4aPZa0= Q39WdnruyT6DRPm675vqX6NMcYYM8nUSZ8vc/uO9ZP3VXQAL3NHh2bH8tRY6iS5vwiJum9Czub5= ElzMDX1Rot+YI3qd983J88YY0yFuo/GBfGHh+QsLz78gcWzREG494FSad8F02jAu1t/T0RfHZuP= sezrSphxd45jYNZuJx+7oxhhj2mZN9IvyXTR/kayJfllvUniuzJhuMc27YCaKF6LdQ+Nlb6S7OK= 7GMYuZnGs2zWyECqFZrRoaY4wZHDqVPv8E8BvgdzSLS58AfouEnyCNwtuI7+QBWELD/2Ui+XGH+= lkKnIKusypLmJxrNg2cTG+MMUPKRIulTyK5T/8AAAw6SURBVEe6jYeQR0rMEO7xwv3w9V0Yu+15= IWMN6CBuLJcyoAvN5soM+mJsB3wFaTM2CV4LjftiFK+5jqGe6QyraN5BZowxZkiY6ELoNODnaIv= vlcAC4EzSXz7h6yNoCSN3yz0b6ZM2Av4V+DDwKlQonIJ2Br0Smes9M9LfxsB7gDcjH5nZwElZm8= XZ46PQLqHdEmOcibxeTkVF3paF154L7A68BumGzqO1IHXTyPVsB/wKCWEtaDXGGGM6RKeWxkBbg= mNC0zWz12JcADynpM/w9ZuzP7cEXgu8Bc2mvBWZyR2JdvzMQ7Mw92ftd030Nx/N1KzMHn8cuBq5= 8s7Lzvd34G4aO21C5iOh9S+yx1+nsc16B+Cs7JYzB3nGpLgrcj0rkf7qSTQ79fvk0aZTTEe7tUa= Bz0zSGI5Hf/83TtL5jTFm4OnkjNBfie+6ahUwuarktdjrG6DZnnegIihmQJcy0gv7S5nNjRI36I= uxDtp1VmRqYRyhcd9NLfqra6hnRKfS4XNeimYcO/ljoS7n4SLIGGO6SicLoVuQCHp39Gv6magIe= CJoVzSmCw3hWj1eGy1bnQU8goz0jmCsAV3KSC/sL2WMN4O4QV9sCW85ynzKjfhmoyLtEOLGfVsE= x4djqmOoZ0Quwu8kufDdGGOMqcwBKPRxBZr5eDNjd1AVjelCQ7hFhcfzI6+fylix9BGMNaDbkbi= xXMyALmY2V2bQF2MhKlw+Bfzf7LrXKfRfNO4LCa+5jqHeoBITjJcJ2GPp8KFIvargvCh8fwfNVg= ithO/XZWP4Yvb48Oxx/u8vPL7smkJh/zbIl+sI4AeMtXuIvWfGGGOM6UNiCeyphPmcYihqLF1+L= 1onrc9EBdCcrK8lNAqhWJ9hQToNpcjn5qFTUPEzkjj+qpJrCpPlr8za7hQZN8TfM2OMMcb0KWEC= eyphPqdYCMXS5Q+gddL6gagYyVlIoxCK9fmSSB870yhmNkObBVLHz29xTWfQKIRG0GxPmeFj+J4= ZY4xpgUNXTS8SE4ynEuZjxETqX6W14LwTwvdbUYGzRtbmiZLjb2xxTUVh/yiN1PgYsffMGGNMC1= wImV4kJhhPJcznAvaiCD8mUs/9mMoE5+MVvoMKtq8B+6JdiDmx47ctuaZQRL9u1i61iy32nhljj= OkBuhEqug9wPRKXbt2irek/YoLxpZQL2GPp8EWRetWk9fEI33PWzo4LCY8vE+WHwv6vZPe/nBh7= 7D3bMdLOGGPMBLOYaqGiVX1gnotErGujL6ojxzE2Y4wxxpiu8y7KC6FpaAdNlUJoNyQiNcYYY4z= pCXZA0/w7oe3Hl9PsMv1WGoVQzO8k9IFJeaIUPXdGkYYjFZpa9FzZBy2HzEWGidcjfccipAs5i4= bWxKGnxhhjjKnFbagw2R6JTN+OtAo5xUIo5XdS3P5c5omyB5phAm2D/iYyoZuJdB2nM9Zz5aLs8= UGoUDoF+Gh2npnZuTcqOfeLae1BY4wxxpgh5Rmo0MhDVzcB/lJ4XCyE8vah30mxEEq1geZC6FCa= l8nmIqO60HNlBIVX5sXOXmg3UM41NBc34bk3pLUHjeku3RDdG2OMGXI6tX0+DEZ9AhUkT0XaVvE= 7qeqJkgpNhWbPlVEUClt8nMKhp73JgTQvYRpjjDHjptM+Qrn/yqHAxdlzVUJFodkHJtVmBM3qbI= yWrlKhqevQ7LkyA80O5Yn0s7LbFLRUNqvF+Bx6OvksAd472YMwxhhjYqyJZlmORUtQ70bFB1QLF= d2RZh+YVJuDaRZLTyEemhp6rlxYOGafwv0TUcGWP147ce5hCz3tBeYBX0Ji9uNQEdxKdF8mam8V= mGqMMca0TV4ITWnV0JgKzEZF7IZod9/NaDavleg+JWqvEphqjDHGtM1GqBAqC4Q0piqvRtYHIa1= E9ylRe9XAVGOMMUNGJzRC04A/ZPf/2IH+jHkaDT1Xijqi9qqBqcYYY4aMThRCq2j+gjFmvPwYeD= 0qZKYifc9GtBbdp0TtVQNTjTHGGGN6gv2RS/l1SBBfRXRfJmoPA09HgM+jmSVjjDGmr0iZ6z0df= dltVqOv49EXqzHGGGNM21RNj+8Ei4kn2r8Q7QoyxhhjjJkw6qTHd4pWifbGGGOMMaV0yln6dLRF= +SHk6QJpA7vQKG8btMNnW+ALwLUoRLXYPkyXB80IUaEdqGC6jubt03PQdv+30rzEFo6vrnHfO0h= vzd6Fsdu4X9Vi7KnX5iAdzFzkpn09EgAvysbuOApjjDFmAimGpqYM7GJGeXlS/H5o58/pwOFZP6= l0eWj2lClrNwMFwG6BdhddQyOV/hial9hi43shnUuj3zXrm2wM7wGeUzL2suu6CL1vB6H3+RTgo= 8hocCb6+8hDZo0xxhjTZYqFUMrALmaU9zTg3sKxi4DXZffL0uWLhVBZuyloK/X2KINsCbB7oe0Z= hX5SRn6dTqPfEhUtT28x9rLXRlCcSV7s7IVmo3KuoXqBZowxxgwlnQ5dLfYbM7CLGeWtBh5N9FO= WLl+13VPAJ4A3Z2P4KXBjoe2qYNzh+DqdRr8Bmr15B5qNKht72WujwF8Lr43WGIMxxhhj6GwhVE= yPTxnYxYzynodmWNZDX/wbZLcR0uny0Gyul2o3mvWzGDgqG885qDgie63YT2x8+9K5NPq1gTORf= ucRNNP0WMnYy65rBtI45YXbrOw2JTvPrMJ1GWOMMabLFNPjYayBXU5olHcZjeWzhYX7Bxb6CdPl= Q3O9VDtQsXMRzct070NF4JGF53ZMjK+ucd/pqFCKcSpjlwz3KRl72XVdGPSR3z8RuLjweHPg6yV= jMsYYY8wAM4PmXWtrAgtoiJaHgemoyDTGGGNMgW5phHqJBcDz0TLRGjSW3h6YzEFNIOsgofpVkz= 0QY4wxxkw8GwHvRbqlZWjpqlWyuTHGGGOMMcYYY4wxxhhjjBk4pkz2ADrMesAJSCD96x7oxxhjj= DFmwlhMPJV+svoxxhhjTA8zaDNCy9A1/Q74VQ/0Y4wxxpgeppPb51MJ79BeunpZf2Wvhan089HW= 8Zto9hMqEibOjwT91Emgjz2/DTJAPAL4QTbWuu+J0+aNMcaYHqUs4b0sQT31Wll/Za9Bcxjrc7P= +8kJiBc0u0BBPnJ8Z9LMV1RPoY89fiYq18bwnTps3xhhjOkynZoQeQ7Mu66IQ0wdpREHMR7MxK1= FI6cdRavtIyWtl/ZW9FrIDmil5FM3mbEpj5ihnXtbf/cDdwK7ZWIrchQqjVwNvRLM+K1EMyGHAD= 4F7s7ax5xcAv6CxzNbOe7IY+BlwK/A3tHx3fza2h4B7snEZY4wxpiKdKoTKEt7bSVdfXdJfqzT5= Ik9DBclI4XZTpE0rg8U6CfSx50cL11x23a1ec9q8McYY04OMoCWcmPh6NlrKyhPUF6Mipuy1sv5= avfbfwGuzx5uhANW5Wf8vRMtfRbZCs0XFxPmNgn4ORTNLa2X3P430P/PRMtVrgddlbWPPr4uW5f= J8s3bekxnAL5HeCFRs/TeNtPlb0AyYMcYYYyaYsoR3qJ+uXtZf2WupVPrrkPbnoMT4w8T5sJ86C= fQ7RJ7/StbXlwvt6r4nVdPm10YFlxPnjTHGmAmi0wnvZf05Tb4aTpw3xhhjWtApjVCnE97L+hv2= NPkqOHHeGGOMmUA6nfBe1p/T5I0xxhhjjDHGGGOMMcYYY4wxxhhjjOkP5gHPHIBzGGOMMcbUYhr= a0dTNImUizmGMMcYYA8RT3rdBMRPbAl8ArkV5X2fTMAA8mHg6e5XUeEinuLc6xwuonihvjDHGGJ= MklfJ+OSpE9kPxFKcDh2fH3EFjtiZMZ6+SGg/lKe6tzlEnUd4YY4wxJsmBNEdejCJDv6eh9PW8G= FlEI5OrWKSMoJmZWS36CzkUOKPweC4qmkYqnAPgGcC/oxmgjyB36mtQ2vvGLa/aGGOMMX1Np5yl= Uynvq4FHKxwfprNXSY2H8qT2VueokyhvjDHGmAGkU4XQMuANjE15fwaaZVkPFS15HMYI8CRKZSf= 7cz0UmVHWX8j3UMGUJ7W/HDgfFT20OMeuKM39+8Cz0HLYLsB2wFLgkuy8xhhjjDEtiaW8X0ZjaW= th4f6BwDuz9luTTmdvlRqft0uluJedo06i/AjweTSLZIwxxhhjjDHGGGOMMcYYY4wxxhhjjDHGG= GOMMcYYY4wxvcv/D7Dg1QveoGWZAAAAAElFTkSuQmCC" width=3D"578" height=3D"302" a= lt=3D"" style=3D"margin-right:9pt; margin-left:9pt; float:left; position:re= lative" />Fuente:= Cede=C3=B1o-Escob= ar & Vigueras-Moreno (2020).Aula invertida. El au= la invertida, tambi=C3=A9n denominada como flipped classroom posee una serie de atributos =C3=BAnico= s que la distinguen de la ense=C3=B1anza convencional. Seguidamente, se exp= one algunas de las m=C3=A1s relevantes de acuerdo con Sol=C3=B3rzano</s= pan>-Barber=C3=A1n (2021).</s= pan><= span style=3D"font-family:'Times New Roman'; font-weight:bold">Distribuci= =C3=B3n de contenido: = intervienen las herramientas como Geneally y Canvas que permiten al docente= subir y organizar materiales de estudio. Los v=C3=ADdeos educativos como Y= ouTube y plataformas espec=C3=ADficas de la instituci=C3=B3n educativa se u= tilizan para compartir v=C3=ADdeos pregrabados.<ol style=3D"marg= in:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left:= 17.3pt; margin-bottom:0pt; text-align:justify; line-height:115%; padding-le= ft:4pt; font-family:'Times New Roman'; font-size:12pt; font-weight:bold"><s= pan>Herramientas de colaboraci=C3=B3n: los foros y chats pueden discutir temas, realizar preguntas y colabor= ar en tareas fuera de clases, tambi=C3=A9n herramientas como Google Docs pe= rmite al estudiante trabajar juntos en tiempo real en proyectos y presentac= iones.</li><li class=3D"ListParagraph" style=3D"margin-left:17.3pt; = margin-bottom:0pt; text-align:justify; line-height:115%; padding-left:4pt; = font-family:'Times New Roman'; font-size:12pt; font-weight:bold">Curs= os en l=C3=ADnea: permite la crea= ci=C3=B3n y distribuci=C3=B3n de cuestionarios y tesis que los estudiantes = puedan completar, de modo que, analizan el progreso del estudiante y permit= e al docente ajustar su ense=C3=B1anza.</li><li class=3D"ListParagra= ph" style=3D"margin-left:17.3pt; text-align:justify; line-height:115%; padd= ing-left:4pt; font-family:'Times New Roman'; font-size:12pt; font-weight:bo= ld">Duraci=C3=B3n de contenido: los softwares de edici=C3=B3n de video como Adobe Premier o CapCut per= miten al docente crear v=C3=ADdeos de alta calidad y si se combina con pres= entaciones ser=C3=A1 visualmente atractiva y din=C3=A1mica. </li></ol>El aula invertida proporciona un entorno para que el estudiante= desarrolle habilidades del siglo XXI, al trasladar el aprendizaje te=C3=B3= rico a casa y dedicar tiempo en clase a actividades pr=C3=A1cticas y colabo= rativas, esta metodolog=C3=ADa despliega el pensamiento cr=C3=ADtico y la r= esoluci=C3=B3n de problemas con la simulaci=C3=B3n y los juegos de roles, m= ismos que permiten al estudiante experimentar diferentes escenarios y tomar= decisiones en ese momento, analiza, eval=C3=BAa y adopta sus estrategias e= n funci=C3=B3n de la retroalimentaci=C3=B3n recibida (Montenegro et<= span style=3D"font-family:'Times New Roman'"> al., 2024). La tabla 1 hace refere= ncia a los m=C3=A9todos de ense=C3=B1anza, t=C3=A1cticas, t=C3=A9cnicas y p= erspectivas que los profesores emplean para simplificar el proceso de apren= dizaje de sus alumnos. Se asemejan a las herramientas que un docente posee = para impartir conocimientos, destrezas y valores, aquellas son: = Tabla 1M=C3=A9todos de ense= =C3=B1anza<table style=3D"margin-bottom:0pt; padding:0pt; border= -collapse:collapse"><tr><td style=3D"width:214.6pt; border-top:0.75pt solid= #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-a= lign:top"> </s= pan></td><td style=3D"width:214.6pt; border-top:0.75pt solid #000000; b= order-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-si= ze:10pt">Caracter=C3=ADstica = </td></tr><tr><td style=3D"width:214.6pt; border-top:0.75pt soli= d #000000; padding:0pt 5.4pt; vertical-align:top">Aprendizaje cooperativo</td><td s= tyle=3D"width:214.6pt; border-top:0.75pt solid #000000; padding:0pt 5.4pt; = vertical-align:top"><s= pan style=3D"font-family:'Times New Roman'">=EF=83=98 </s= pan>Es un enfoque en que los = estudiantes trabajan juntos en grupos peque=C3=B1os para alcanzar objetivos= comunes y realizar tareas educativas.<s= pan style=3D"font-family:Wingdings">=EF=83=98 = ; Fomenta la independencia, y responsabilidad individual y grupal.= =EF=83=98= Interacci=C3=B3n cara a cara y fomenta l= a comunicaci=C3=B3n.</td></tr><tr><td style=3D"width:214.6pt; pa= dding:0pt 5.4pt; vertical-align:top">Clases o aula invertida</td><td style=3D"width= :214.6pt; padding:0pt 5.4pt; vertical-align:top"><s= pan style=3D"font-family:Wingdings">=EF=83=98 = ; Contenido te=C3=B3rico se estudian en casa.=EF=83=98&#= xa0; Estudio independiente.</td></tr><tr><td style=3D"wi= dth:214.6pt; padding:0pt 5.4pt; vertical-align:top">Aprendizaje basado en el pensamiento</sp= an></td><td style=3D"width:214.6pt; padding:0pt 5.4pt; vertical-align:t= op">=EF=83=98= El enfoque se centra en el pensamiento c= r=C3=ADtico y metacognici=C3=B3n a trav=C3=A9s de la reflexi=C3=B3n y an=C3= =A1lisis. </td></tr><tr><td style=3D"width:214.6pt; padding:0pt = 5.4pt; vertical-align:top">Pensamiento de dise=C3=B1o</td><td style=3D"width:214.6p= t; padding:0pt 5.4pt; vertical-align:top">=EF=83=98 = ; En= foque creativo para la resoluci=C3=B3n de problemas.=EF=83=98<s= pan style=3D"width:10.22pt; font:7pt 'Times New Roman'; display:inline-bloc= k"> Comprende las necesidades y experiencias de los usuarios.= = =EF=83=98 <sp= an style=3D"font-family:'Times New Roman'">Genera una amplia gama de posibl= es soluciones.</td></tr><tr><td style=3D"width:214.6pt; padding:= 0pt 5.4pt; vertical-align:top">Aprendizaje basado en proyecto</td><td style=3D"widt= h:214.6pt; padding:0pt 5.4pt; vertical-align:top"><= span style=3D"font-family:Wingdings">=EF=83=98 = 0; Su enfoque se basa en proyectos a largo plazo que involucra investigac= i=C3=B3n y creaci=C3=B3n de productos finales.</td></tr><tr><td = style=3D"width:214.6pt; border-bottom:0.75pt solid #000000; padding:0pt 5.4= pt; vertical-align:top">Gamificaci=C3=B3n</td><td style=3D"width:214.6pt; border-bo= ttom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:top">=EF=83=98</spa= n> Implica la implementaci=C3=B3n de componentes caracte= r=C3=ADsticos de los juegos en escenarios no recreativos, como la ense=C3= =B1anza, el marketing o el =C3=A1mbito empresarial. Su meta principal es in= crementar la motivaci=C3=B3n, el compromiso y la implicaci=C3=B3n de los in= dividuos en una actividad espec=C3=ADfica, convirtiendo labores frecuenteme= nte mon=C3=B3tonas o cotidianas en vivencias m=C3=A1s cautivadoras y retado= ras.</td></tr></table>Fuente: R= odr=C3=ADguez et = al. (2023).= El aula invertida en= la ense=C3=B1anza de la historia. El aula invertida, una t=C3=A9cnica pedag=C3=B3gica que ha cob= rado relevancia en a=C3=B1os recientes, propone un nuevo enfoque para la en= se=C3=B1anza de la historia. En este enfoque el aprendizaje convencional se= transforma, los alumnos adquieren el conocimiento te=C3=B3rico de manera i= ndependiente fuera del sal=C3=B3n de clases, mientras que el tiempo en clas= e se emplea en tareas m=C3=A1s pr=C3=A1cticas, de colaboraci=C3=B3n y de so= luci=C3=B3n de problemas, funciona de la siguiente manera (Tabla 2): Tabla 2=C2=BFC=C3=B3mo funciona el aula invertida e= n Historia?Etapa del aula invertida &#= xa0; Actividades dur= ante la clase<table style=3D"width:470.5pt; margin-bottom:0pt; p= adding:0pt; border-collapse:collapse"><tr style=3D"height:111.35pt"><td sty= le=3D"width:146pt; border-top:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:top">Pre= paraci=C3=B3n en casa </td><td style=3D"width:146.05pt; border-t= op:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:top"><= span style=3D"font-family:'Times New Roman'">-Los alumnos visualizan v=C3= =ADdeos, leen textos o llevan a cabo otras tareas para obtener los conocimi= entos fundamentales sobre un tema hist=C3=B3rico espec=C3=ADfico.</p= ></td><td style=3D"width:146.05pt; border-top:0.75pt solid #000000; padding= :0pt 5.4pt; vertical-align:top">-Es posible que empleen plataformas digitales, libros de texto= o cualquier otro medio que el profesor juzgue apropiado.</td></= tr><tr style=3D"height:112.1pt"><td style=3D"width:146pt; border-bottom:0.7= 5pt solid #000000; padding:0pt 5.4pt; vertical-align:top">Clase activa </td><td sty= le=3D"width:146.05pt; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt= ; vertical-align:top">-El profesor orienta a los alumnos en la implementaci=C3=B3n de los sabe= res obtenidos.</td><td style=3D"width:146.05pt; border-bottom:0.= 75pt solid #000000; padding:0pt 5.4pt; vertical-align:top">-Se llevan a cabo discusiones, recr= eaciones hist=C3=B3ricas, soluci=C3=B3n de problemas, trabajos en equipo y = otras tareas que promuevan el razonamiento cr=C3=ADtico y la creatividad.</= span></td></tr></table>Fuente: N=C3=BA=C3=B1ez-D=C3=ADaz (2021). Sugerencias para la implementaci=C3=B3n del aula invertid= a en historia. Como en= todas las materias los docentes aplican diferentes metodolog=C3=ADas para = una mejor comprensi=C3=B3n por parte de sus estudiantes, la materia de hist= oria no es la excepci=C3=B3n por lo cual es importante abordar los siguient= es pasos: <ul style=3D"margin:0pt; padding-left:0pt"><li class= =3D"ListParagraph" style=3D"margin-left:17.63pt; margin-bottom:0pt; text-al= ign:justify; line-height:115%; padding-left:3.67pt; font-family:serif; font= -size:12pt">Planificaci=C3=B3n adecuada: Es crucial organizar las actividades tanto en el interior como en e= l exterior del sal=C3=B3n de clases para garantizar una transici=C3=B3n sua= ve entre ambas etapas.</li><li class=3D"ListParagraph" style=3D"marg= in-left:17.63pt; margin-bottom:0pt; text-align:justify; line-height:115%; p= adding-left:3.67pt; font-family:serif; font-size:12pt">Variedad de recurso: <sp= an style=3D"font-family:'Times New Roman'">Emplear una mezcla de recursos a= udiovisuales, escritos, tareas pr=C3=A1cticas y herramientas digitales para= mantener la atenci=C3=B3n de los alumnos.</li><li class=3D"ListPara= graph" style=3D"margin-left:17.63pt; margin-bottom:0pt; text-align:justify;= line-height:115%; padding-left:3.67pt; font-family:serif; font-size:12pt">= Colaboraci= =C3=B3n con otros docentes: Colaborar con otros profesores para intercambiar recursos y vivencias= .</li><li class=3D"ListParagraph" style=3D"margin-left:17.63pt; marg= in-bottom:0pt; text-align:justify; line-height:115%; padding-left:3.67pt; f= ont-family:serif; font-size:12pt">Evaluaci=C3=B3n de manera constante: Efectuar evaluaciones formativas y su= mativas para reconocer los puntos fuertes y d=C3=A9biles de los alumnos y m= odificar la instrucci=C3=B3n de acuerdo con ello.</li></ul>Asignatura de historia. </sp= an>Esta asignatura busca prop= orcionar a los estudiantes una comprensi=C3=B3n profunda de los eventos, pr= ocesos y figuras clave que han dado forma al mundo. En el Ecuador la asigna= tura de historia est=C3=A1 dise=C3=B1ada para indagar la historia nacional = y mundial con un enfoque de desarrollo de habilidades anal=C3=ADticas, seg= =C3=BAn el Ministerio de Educaci=C3=B3n (2022) se presenta el curr=C3=ADculo general del cont= enido y los objetivos de esta asignatura (Figura 2). Figura 2Contenido tem=C3=A1tico<img src=3D"data:image/png;base64,= iVBORw0KGgoAAAANSUhEUgAAAkAAAAE0CAYAAADEwYx8AAAABHNCSVQICAgIfAhkiAAAAAlwSFl= zAAAOxAAADsQBlSsOGwAAIABJREFUeJzt3Xl4VOXd//H3BMLuEpA9BEXRUBWohQIC4tKqBZdiWy= qtG6LUrbZVbLFltWLFWh5t6w6iVAO/R9FWRWSpZRHLY8VqlCaAREEIRZaIEkIgmfP743smmQwzy= SSZyZnl87quuZKZOcv3HEjmk/u+z7lBRERERERERERERERERERERESSmc/rAqKUARzjOM4XXheS= Cnw+Xzug1Os6REREvJLoAUjBJ44UhEREJF0lcgDKcByn0usiUp1CkIiIpKMMrwuIoLnCT9NwHOc= A0NbrOkRERJpSIgagDKCD10WkE4UgERFJN4nWBZYBZDmOs8frQtKRusNERCRdJFoLUAuFH0918r= oAERGRppBIASgDyPK6iHTmOE4R6goTEZE0kEgBqAVwmtdFiFqBREQk9SVSADoO6OJ1EaIWIBERS= X2JFIC6Oo6zwOsihM5eFyAiIhJviRSAmntdgADu3be9LkJERCSeEikASWJoDnT3uggREZF4UgAS= ERGRtKMAJCIiImlHAUhERETSjgKQiIiIpB0FIBEREUk7CkAiIiKSdhSAREREJO0oAInAucC9Xhf= hsXPRORCRNKK7L0uqyAKuAi4B+gD/Bl4E/hcor2Pdle4jna1E50BE0ohagCQVZAN/A44FxgGnAr= 8CzgceB1p7V5qIiCQiBSBJdhnAA8CnwH1AMXAIKAR+CpwO3OJVcSIikpgUgCSZfB94D7gfyHRf+= xowFsgDnJDlDwALgTuxVqBe2DiX24BngUXAccC1wINB63UBZgP5wEyObkHqDPzefX+eu12Ak93l= L8Faoj4CHgqqtbZ1ASa4x3crcF7Q6yvdY3Ow1i2AR93nF4fUdrpb+7exQPgfYEbQMURzDk4EpgP= fA0YD/wSeAtoBV7o15gEdojiucPtrBlwPrMaC68PUnIA30nkQEUlJAxzxHPAdINfr/wxhHAN8SX= UQuNB9/RL3ed8I613hvn8K8Jz7/W+pDiVXAtuAJ4PWmQvcDLQEfhC0z5OwcXMzgW5YqLgN635rB= jzjLvcA9sF/AhaChrjbrW3dE4E/ucfZHbg95NhnA78Ieu0bwGWAL+R417k1TMTGRfVyX5vgvh/N= OXjcXWaGe97aA2+4z/u49SwAro7iuMLtrz2wFuiIhc333WOhjvMgIpKSFIASAIkbgI6l9gDUJ8J= 633XfD7RIzKf6wzZgDDUD0Bbgm+73rYC9WAsHQP+gGoIf3d33nwNGBW3rWapbaWpbtyPW0jOC8B= cnnIaFqbbu8zuxgBbKhwWes4Neuwp4Neh5NOdgDhb+Au4Brgt6/kusi7Gu44q0v2B/Bn7ofl/Xe= RARiQl1gUmy+BIYD3yAdbWsdF//1P3aM8J63YGtwA73+aEwy4S+9iBwOdAG6Ie1WATCRmdgKhY0= gh+B7R8M2VZl0Pe1rbsbuBG4CFiBDeAOthHrMhqJdUWVE/7qNgf4KuS1rUDXWo433GvhjiO4tck= Jel7XOQm3v+ZY99ZsrAszsK26zoOISEzoLyxJJi+4j2D/wS53HwMsA/xB77XGWjEepO5L4YMtAq= ZhLSmfYa1M29z39gLnYN05R9zXegH73fdqU9e6m4FfY2HuZaz1alvQ+vOAWUAF8Pc69hX8x80Jw= Po6lm+M+p6TLOAJYAnW3RX6h1hd50FEpNHSrgVowoQJ+Hy+qkdOTg5jx45l2bJlVcvs27ePWbNm= sXTpUs/qLCsrY9GiRdxxxx2e1ZAk/Fh3zBnYGJVsrNvqa9hYlk3YAF6wVpxO1Ow68mGtI52BFu5= rv8JaJvpi3VmLg5b/EAsgd2ODgDsAQ7EP+hbYOJhO7nZbuNvt7D6vbd0+WIjrgLWY7OfoP1DeBf= Zgoa6gjvNyMdZSlA38BBufFO05yMTG5gSOo5n7Xifsd0am+31nt8bajivc/gZjXZovA4exgNYW+= HqU50FEJKU0yRigw4cPO9OmTXMmTZrklJeXO19++aXz0ksvOS1atHD+9a9/OY7jOPPmzXNatGjh= LFmypClKCmvJkiXOiBEjnCuvvLJJ90vijgGqSyfgLqxrrBh4CetaCb4CawHWdbMC62YBu8opMGb= lafe1X1JzLMsubMxNQA/gEeyKp1nA8e7rTwetcw2wPOj5ZXWs2wfrbpuHXXU1JsJxXooNWq7Nci= z0/AMbvBw8/iaac/Bo0PMbQp7fhV1dFngeGJgd6bjC7a8T1pK32q3tJ9jVeu3rcR5ERFJGkw2Cf= uqpp5zp06fXeG3MmDHOM888U/V8+vTpngYgx3GcDz/8UAGo6WVil4Q3C3qtNXZV2LGeVFTTLViL= SW2WU3MQtIiIhEi7LrCAiooKHMehvLycVatWsWLFCvr161f1fsuWNS+wWbduHaNHj2bAgAHMnDm= T0tLSqvcKCwsZP348Q4YMYfHixbzwwgt06NABn8/HoUOHWLhwIT6fj+eff75qnTVr1nD55ZczbN= gwlixZErbGFi1ahH1d4mok1kVzItZt09L9vhIbiO2lrlgI21PLMu2w7qMTOPoSeRERSUBN2gJEy= CW7jz/+eI1lfve731W1AO3YscO54IILnE8//dTZt2+fM2HCBOeee+5xHMdx9uzZ44wcOdLZtGmT= 89VXXzm3336789RTTzm7du1yAKesrMyprKx0pk+f7jz33HOO4zjOZ5995txzzz3OgQMHnMLCQqd= nz57O559/flSdGzduVAtQ0zseuAN4E+tKew1rEfIyjY7ABnvPxG5aGEkrav6//kEty4qIpLWEag= FyHKfJHlOmTKGyspIDBw7w9ttvM2/ePObMmRN22dWrVzNs2DBycnI4/vjjueWWW5g7dy5+v5+33= nqLkSNHcsopp9C2bVsGDhyI4zh07Nix6ph8Ph/dunWr2t769euZOnUq7dq1Izc3l61bt1JYWBh2= 3019XoQvsAHQ52MDmi/B7uVz2MOaVmGDun+DDQqO5BA1L0MPvWJORERcaRmAADIy7NBbt27NoEG= DuPrqq3n++ecjBo/i4uKq77OysmjTpg2O4/DFF1/UWDb4WEJfP3z4MI7jUFlZSV5eHpWVlVWPoU= OHNmnQSbEA1I6jp7NIZg09nsBUHLXddDCRnItNkxFO4FhGRXi/No1ZV0TSREIFoKbg9/spLi6mr= KyMgwcPcvjwYT788EMWLVrEwIEDAQstu3btYu9eu4XJkCFDWLhwIcuWLePQoUP8/e9/58Ybb8Tn= 85Gbm8uzzz7Lpk2bOHjwIEVFRVX76tmzJ4WFhRQXF1NQUMDkyZN5/fXX6d+/P4899hj5+fkcOnS= I9evX11gvYN++fXzxxReUl9fnFjZp6WJsqoVEGKQcCw09ninY/XOSxUpgcoT3ptHwY2nMuiIiTW= 5ARUWFE+/HDTfcUGPsT/v27Z2zzz7bmT59urNnzx6noqLCmT9/ftX7//jHP5yKigpn2bJlzvnnn= +/06dPHmTlzpvPVV19VbfOxxx5zvvGNbzhTp051nnzySeeJJ55wKioqnDlz5jgDBw50Hn30UWfu= 3LnOo48+6uzfv79qexdccIFz9tlnOy+99NJRda5evbqqhhEjRsT9vAQeJO8YoNCpHI4HvuVRLcF= aY5eSj6/neqHHE63nSJ4WoLr8PxreitOYdUUkDSTSVSIDjhw58i+vi2isvLw8ysrKGD++vp93iS= EzM3Mk8AlQ6HUt9XQZNl5nAtayOQtrYVhcyzpN4SJsLqyp2N2PoxV8PPXxJDZw+5V6rpeInsbuy= t2Qf8PGrCsiaSChusC8Hv/S2Iff72f37t3s2bMHv9/veT1JOgaoA9b98x42gec52B2FHWzMCO57= DjA8wjbuxmZDf81dt671e2FjUW7DBjwvwu4D5AOux27Y9ynwMDZLOVgweQ+4FZvTKpKl2I0VG6O= 2OiItfy02eer/UH0zyLrOw4nAdOB72M0R/4ndRbsddvPF94A87N+orroC43AuAca5tTwUVMsxHD= 3O6Tjs32GTu27wvZjqOge1rSsichQFoBg+XnvtNSZOnMjkyZNZsGCB5/UkYQDKxKavWIvdyO8l7= MZ/PYG3g5Y7F/h3LduZid1J+BLsw7qu9e/BrrDqjHVXfQ+7708W1nX1PezeQCOwsHMicKb7/K/u= 96H6u++txu6SHGw48DfgLazLsS6R6ojkm1jr14Xu9vu7r9d1HiZh42f6YtNbjHJrvwubhHYEFkR= GRlFXYDzSOdhVbOdiXZID3PdHcfQ4p3uBz916l1Pzjtd1nYPa1hUROUpCzbGTAB/AjTJq1CgOHa= qe+DrZj8cDZ2GTab7hPp/nPsDuyRPwJfWbHPNAHetfhc0p9i+qJ/ME2IfNaRXwFjampxQLPWdhY= e2PIfvLcl+7EZtG4yFslnOwubnOBX7kfr8UGBj0fjiR6ojk/7AZ4MECTmBairrOw03Y74SPgI/d= 197BukQDc48Fb6+2uq5zt7UKCIzwX0/1fYwWYuc8ME7rDGyaj97Yv8FKLEAG1LavutYVETmKWoD= 0SKQWoK7UHgTi6VCE15tjLQ2zsbnFfFiNN2Lje1Zg9wwKNhxrhdiI3VfojaD3zsJanA5g46x6Aq= dFUV+4OqJxhPp1Bx0MeV4Zsi8n5HltdYXbVrDgc34KFrKCA2hpzcUj7iuadUVEakioFiBJe7uBI= dj0E6HX/jscHdjrc3fmhqyfhQ1cXgL8KWT9zVgXT09sVvPvUt2aciw1Zz8P3lcG9uG9sB6111ZH= fTX2PMarrlIsHLbDwmFobbXtq651RUSOohYgPRKpBeg9rNXg51hXybHYdA6Z2ADes7BujxHYeJ1= HsDEuPvd5Z6qDxxGgO9Zt0qqO9VtiM5SHhpbBbg0vY3eCPgFoC1yBXabeAWvF2E/NPybysRaiIe= 7+crD73fwAeB8b19TXresb2CDsYKHHE6mOr4es19pdp5O7jRZAx6Dn1HEeMoEuQcs3C9pehvt+J= /e15nXU1QK7k3ZwLYFjCtypuqv7vAXW1bYTG8CehXUPdscGSX+/jn3Vta6IyFESqgUoAT6AxVtl= 2JU+v8bGsfwd+xA7gv31/zj24T0N2IB1P63EBuUG7pnz/7DWmFexK5omYyGltvWfAS7HWhCOx65= 8Ahuz8hV2SfmDwBrg29iYnjL3tVzsSqvgO1nmAz/DumrysQHFv8PG+3wJzAD+ALQBHnD3Eyz0eC= ZEqOPlkPUewS6fvwwLCVdjY2wuxgYIv1HHeXgYC2k/wFrgzgJudrftx8LFRPf5HuD5Wup6HBvoP= Arr+grUMhIowcLV4+62Hsf+3X+MDUZf426vELvq7A33XEXa1/461hUROUpC3QfowIEDSX8foGTX= rl27ZL0PkIiISNTUAiQiIiJpRwFIRERE0o4CkIiIiKSdhLoKTERERKQpqAVIRERE0o4CkIiIiKQ= dBSARERFJOwpAIiIiknYUgERERCTtKACJiIhI2kmoy+A7duw43esaREREJPUlVAsQqBUoAfixSS= dFRERSViIFID9QqgDkuQpgh9dFiIiIxFMiBaD9QLECkHe6dOnyC6DU6zpERETiLZEC0E5gf5cuX= abv3LlzutfFpKkvgF1eFyEiIhJviRSAKrAQpG4wD3Tr1m0W7vn3uhYREZF4S6SrwPxACbC5W7du= j3ldTBragnVDfu51ISIiIvHm87qAEC2AM4ARQO8dO3bc7HE9aaF79+6/A14HNqEAJCIiaSDRAlB= zoAeQ6z56b9++XSEoTrKzs58B9gEfAG+g8CMiImki0QIQhAlBQNvPPvvsGk+rSjE9evR4Bgs/hc= CHwDpPCxIREWlCiRiAoGYIOhXoChwLtA0ssG3bNgWiKOXk5MwPeuoHvqQ6/GzC7vuj1h8REUkbi= RqAwEJQd6AL0J7qINQOG7zd9tIrroxZCHr1pYWLAQe7Cqo8Vtv1mJ+aV3VVYpe6bwcK0JgfERFJ= U4l0GXyoCmAr1jrRHWuxOB4LQb0Ap3OXbrHc37HYFBAlWEhIhWvxj1AdcPzYce3ErvZSq4+IiKS= tRA5AAcFBqDPWbVMK9D7vW9/h4MGDMdnJnEdnHwK2Af9xvx6IyYa9VUl1C1AFFniCQ5GIiEhaSo= YAFBA8R1VrICP39L5s37Y1Vts/iLWM7MZaSb6M1YY9VA584nURIiIiiSaZAtBRMjNbcNLJvWO1u= cBNALcCm7GuMBEREUlBiXQnaBEREZEmoQAkIiIiaUcBSERERNJOUo8BkoSTgf2f6ug4znavi0lW= Pp+vFXbbgkr3q4iIxJgCkMRCBtDccZxUuYGkpxzHORT43ufztUBBSEQk5tQFJo2V4ThOpcJPfDi= Ocxg4Af2siojElH6pSmM0dxyn0usiUp3jOLvc86yfVxGRGNEvVGmoDMdxjnhdRJpRS5CISIzol6= k0RAY2LYk0IcdxdqEQJCISE/pFKg3RyXGcYq+LSEduCDre6zpERJKdApDUl1p/vNcc/eyKiDSKf= olKfXUCTvW6iDR3KmoFEhFpFAUgqY/ATQ7/1+tC0pnjOGvQz66ISKPol6jUxylAB6+LEEAtQCIi= jaIAJPV1gtcFCKCfXRGRRtEvUZHkpCAqItIICkAiIiKSdhSAREREJO0oAIlIqmoHXAs8GMd9nAz= MBEY18boNEW5/5wL3xmFfTXHuRRpFAUhEEsEfASfo8SXwPvAXYBzQpgHbvBj4LXBsjGoMZxrwaw= /WjdX+VgKT47Cvpjj3Io3S3OsCRESAn2EfxouwGz1+irUiDMNaLb4P/AjYX49tvoj9kfetGNYZ6= hqgpQfrJvr+muLcizSKWoCaTjN0vkUicYAd7ve7gSNACfAq8D1gAHB7A7Z7KCbV1a7Uo3UTfX9N= ce5FGkwfyPHXDGgNZGNzaLVC513S2/eB94D7gcwolt8M/Am4DWjrvtYZ+D2QD8wDekWxHR9wPbA= aa2F6GDgmwrK1bf84bNzMJqx1qlk99lHbugEnAtOx4Dca+CfwFNYidiV27vKoeVPSSPXWtr9jqD= lOJ5rzU59zGIv1ROJGH8TxdwJwtvsYAXzTfS0TnX9JP8cATwNfB34FnBfleh9h89B1xbrubwf+B= xgErHe/DxcmgmUB47FgMRj7eQy3/7q2fy/wOdAfWI6Fkmj3Udu6AZOw8Tp9gQ+xQcs9gLuAD9xt= +oCRUdRb2/5GUXOcTjTnJ9pzGKqh64nEjcYAxV8z7Bf3IKAyv6jkjr69sr4N7AGK3a9+D+sTaUq= +Rq6XAZyBDeYNHdDbheputHD2AUODnr+Ftc6Gqm37WcClQG+sm24l8Nco93FGHesG3IT9bv4I+N= h97R3gE6DAff5vqqdDiVTviDr2txD73RMYpxPN+Yn2HIZq6HoicaMWiPjriDVDg3v33vyikuX5R= SX/BnLd1/TvIOniS6wl4AOsy2ZllOudgbVkfIZ190zFQlHwo7bwE9Aca3mYDYwlfCCrbfunYCHk= SNDyoeNqIu0jmnUDDoY8rwyp1Ql6HqneY6PYX+g4nWjOTzTLhNPQ9UTiQi1A4TUjurEJ0YgYbvK= LSla5rUGFWEvQYdQaJKnvBfcRrd7Y+J8/AGXAXuAc7Gc08OHeC7tCbG8t28kCngCWYGOKIv1s1r= b9UuAsbDzOgaB1WkSxj7rWbahI9WbUc3/RnJ9oz2Gs1hOJGwWgmgIDlnvGcJu1tvDkF5UsB+jbK= 2sE1UFIIUjSjQ/o7n7fHvgKGy80FPgdsAx41H3/Q6ACuBt4xH1tKHbPoNBtdnYfLbGxJ8cCL2OD= qU9wv34d61IKqG377wA73fcedNfv7n7fDAs5kfZR17ovuvvKxLrbOrnHkOEewyH3+0C3+mHsd3i= kel+pY3+LsDFVnbFQFM35ifYcNvTcizSZZG2CzAX65ReVLPS6kFhyQ9Bm7PLfRGwNygXOcBynPn= +9Sxz4fL6hwNte1xFDfwR+GvLaB8C7WKvBa0B50Hs9sMHCw933fwd8EbL+KHc9gL8BE7CA0BkLA= V2xLplbsDEqwWrb/unAb7BByg9iH+LvYYGiTR37qG3dQCvNo8DN7vc3Yq04gee/xFpT7naf34EN= eI5Ub237+zbwkrudee76dZ2fTlGew8ace5EmoQCUYPr2yhqLDY5OxNYgBaAEkYIBSESkSakLLMH= kF5UsgBpdYiXYAMhECkIiIiJJTQPRElR+UckqrNn6dHSlmIiISEzpQzWBpevl8hMmTMDn81U9cn= JyGDt2LMuWLaux3L59+5g1axZLly71qFJ49tlnGTx4MOeffz6vv/66Z3WIiEj9pMUHarILag3qR= hpMpfHII48wbdo0Jk2aRHl5ORs2bGDMmDFceumlvPvuu1XLvfLKK0ydOhXHcTyp88MPP6RPnz6s= Xr2aGTNmcOWVV7JlyxZPahERkfrRGKAkkU6Xy2dmZpKdnc2OHTto0aIFLVq0YPTo0Xz3u99lw4Y= NDBgwAIDrrruOrVu3elbnmWeeWfX98OHDue666/j44485+eSTPatJEkZr4MfYDQvnxmibN2N3h1= 7TyH3FozaRpJPSLQmpyG0NyiUNJlatqKjAcRzKy8tZtWoVK1asoF+/fjWWadmyZY3n69atY/To0= QwYMICZM2dSWmo3vi0sLGT8+PEMGTKExYsX88ILdiFbhw4d8Pl8HDp0iIULF+Lz+Xj++eertrdm= zRouv/xyhg0bxpIlS2qt1+fzceKJJ8bgyCUFnINNPhrLPzIf4+jw05B9xaM2kaSTsh+eqcwNQcE= Tq6ake++9l4yMDFq1asW5557LfffdR//+/SMuX1xczOTJk3nooYdYvnw527ZtY/bs2ezdu5c777= yTSZMmsXz5cpYtW8b+/fsBKCgoqFp/zJgxTJ8+ver59u3bWblyJXl5ecydO5ebb76Z3bt3h913S= UkJWVlZnHbaabE5eEl2S7F79iTivpqyNpGEpQCUpPKLShYEtQY1KcdxmuQxZcoUKisrOXDgAG+/= /Tbz5s1jzpw5EZdfvXo1w4YNIycnh+OPP55bbrmFuXPnsmbNGkaOHMkpp5xC27ZtGThwYNU6HTt= 2rDomn89Ht27dqt5bv349U6dOpV27duTm5rJ161YKCwvD7nvRokX8/Oc/b7JzIzF3GjAHG2v3JP= APbDqJHwP5wD1U3zdtMHZH43exmwy2DdpOf2zC0dXYzQmDDcduCvgW8B2gD/A0cC12l+jvYDckP= BObqHQJ1Xel74DdqPCiOvbVApiCdZOvdGuNpjaRtKMAlMT69sr6PXCi13XES0ZGBj6fjzZt2jB4= 8GCuvvrqGt1ToRzHYefOnVXP27dvT5s2bapae6J1+PBhAPx+P3l5efj9/qrHsGHDjlr+zTff5OK= LL+a444476j1JGr/GJmk9CfgFFj5+gQWTEcD3sW7nbsC9wM+xOynnYHdjBrtD8x+BXwGXYZOfBm= QD5wI/cvfzGHZH5HFYWPmm+/117javx250OcJd/wpgBtUhLNK+emLTaPQDHnbrrqs2kbSkAJSk+= vbKmodNl7Grqfcd79aNyspKiouLKSsro7S0lPLycvLz81m0aFGN1hu/38+uXbvYs2cPjuMwZMgQ= FixYwNKlSykrK2PFihXceOON5Obm8uyzz7Jx40ZKS0spKiqqcRw9e/akoKCAHTt2UFBQwOTJk1m= 8eDH9+vXjscce44MPPqCsrIx3332XLVu21Kh1zZo19O7dm27dunH48GHWrl2rFqDkdB2wAfg/bD= 6v97GfrcDUNJ9grSvDsRacre7rj2CBxue+txzYiE1D8UbQ9s/CWpEOYIGnJzZdxUbgY3eZK7HZ7= tdis8EXUT1x6VPu8gGR9rUZaykag00t0qKO5UXSlgbBJZmg4PM59stsT1PXEO8P4Jtvvpk5c+YA= 8MADD9C+fXtyc3O58MILue2226r2n5eXx8MPPwxAjx49GD58OIsWLeL+++/njjvu4KqrruL222+= ndevWXH/99Vx11VWMGjWK7OzsGkFiypQp3HTTTYwbN44zzjiDKVOmcM4559C2bVumTJnCxIkTKS= srY+LEiZx11llV673++utcdtllNWp/+umnGTJkSFzPj8SFg03AGvw8HB82j1XAPiysgE322TJk+= UAAyQDGYl1bwQ4Gfe+n5qztoQ4FfR9pX9lYy9JTwG+B0VHUJpKWNBdYEnHDTzFQgAWfz4EtwJdN= VEIucMaRI0eSei6wvLw8ysrKGD9+vNelNFhmZqbmAoutdtgkoZdjP19XAoOAidjVln/HJu7cg12= K/n1sLM2VwPHAQ9j4oeXAd7EWpJ8CdwK3Af8C5rvfb8Lu8F6BjQkahLU2HQN8CgzEWpx+hl2yfr= 9b42xgPfBcLfvKw4Lc/cClWDfdDXXUltQ/zyINpRagJOAGn0rsl2QB1oS+maYLPjUkcxeM4zjs3= r2bQ4cO4ff78fmS9W8AibE/Ar2B/2CDkRe4r2/DZlAfhIWPdliryt1Y6JmPjbUBGyz9Myyo5AMf= Yt1WS7Gf1RnAH7AZ4x/Axvz0xMYD/cStoT32R81YbJZ3sK65Dti4I7Cf/3cj7OvvwJ+wVqonsHs= HDahlee9uoy7isWT97Z82LUBBrT573K+badpWn2C5wBnl5eVJ+xfja6+9xve+9z0AnnnmGcaOHe= txRQ3TsmVLtQCJiDSCWoASWEiXl6etPqnikksuoby83OsyRETEYwpACShooHMx1cHHq1afoyRzF= 5iIiAgoACWcZGj1UQASEZFkl9QBqG+vrIexG3wljfyikmvCvR7m8vaEDD+gACQiIskvmQNQBVCG= XSaaDDd0bE6EOhPg8vZ6UQASEZFkl6wB6DCwE5sZuSOQyHMQNMNuONaVkNaqRLu8PVoKQCIikuy= SNQAVYSHhWCw0JLLu2E3Pgu8em2iXt9eLApCIiCS7ZA1AYMGhyaeBaIBjQl9IhoHOIiIiqSyZA1= CyqMDm+AGo7Nsr6wkS9PL2aKkFSEREkp0CUPztwSZMLMOCTkJf4RUNBSAREUl2CkDxV4nNJ3QAm= 2GOYcMLAAAgAElEQVQ6oa/wioYCkIiIJDsFoPgLjFXqjF29VuJtOY2nACQiIslOAajp7PK6gFhR= ABIRkWSnACT1pgAkIiLJLhnuoCwiIiISU2oBknpTC5CIiCQ7BSCpNwUgERFJdgpAUm8KQAnBX/c= iIiISiQKQ1Fdlp06dZu/atesOrwtJV507d55IckwDIyKSsBSApD4qgN3AHrUCeWovagESEWkUBS= Cpj4+BTGC3ApCndgNfeF2EiEgy02XwUl97gb1du3ad7XUh6ahr164TUQuQiEijqQVI6qsS+C+wu= 2vXrs8UFxdf53E9aaNbt24PYK0/n6MWIBGRRlEAkvrai03m2gVor66wJrUTKAT2eV2IiEiy83ld= gCSlDsCpQB8gF+i4ffv26zytKIVlZ2c/g7W6rQLWodYfEZFGUwCShjoqBH322WfXeVlQKurRo8c= zWPgpAN4CijwtSEQkRSgASWMEh6BT3efNcQfXb9u27RrvSktOOTk5891v/dhtBwLhZxN2FZ5af0= REYkABSBqrA3CK+7UL1UEoA+Dy7/3oer8TmwuWXn1p4d+Cnu6PyUYTg5+aV3X5sYHOG7ExP5tQ8= BERiSkNgpbG2us+AkHov0An93nHDid05MsvY5ZVOrlfv8QCQqqMwN5DdcAJhJ+97le1+oiIxIEC= kMRKcBDKcr/2HTh4OH7Hj9/f+FagFxc8c8D99j1gK1BMaoSg4BagQBgKDkUiIhJjCkASa4Eg9DG= wf+iIC9i3dw/7vyiJxbYPul//C2zHBgSnQgD6HF3aLiLSpBSAJO7adziB9h1OiMWmAn1pO7DwU0= hqBCAREWlimgpDRERE0o4CkIiIiKQdBSARERFJOxoDJJK+ejuOs8nrIpKRz+drjk0MLCJJSgFIJ= M04msG20RzHqQh87/P5mlHzRpYikgQUgETShIJPfDiOUwkKQiLJRmOARNKAwk/8uUFIv1NFkoR+= WEVSnMJP01EIEkke+kEVSW0nel1AulEIEkkO+iEVSV0nOo7ziddFpKmT0e9XkYSmH1CRFKXw4x3= 39gI+r+sQkcgUgERS04leFyD0Qr9jRRKWfjhFUlNvrwsQWqFWIJGEpQAkknp6AS29LkI4Ef2OFU= lY+uEUST0tgJO8LiLdOY7zitc1iEhkCkAiqamF1wUIoLFYIglLAUhEJH4UREUSlAKQiIiIpB0FI= BEREUk7CkAiIiKSdhSAREREJO0oAImIiEjaUQASqelkdPdeEZGU19zrAkQSxMnAKUAmNo3EFuBj= wPGyKBERiQ8FIBHTHDgdODW/qOQnAH17ZZ2KBaAtKAiJiKQUdYGJmJOxm9a1CryQX1SyCeiDtQy= pW0zS2c+IzU0dewAvA8fXsszNwPAY7AtgNvbHS+DRvYHbiWVNkiAUgERMs3Av5heVvALkohAk6a= s9MJLYBIA+wATgi1qWeQxYE4N9AfwS+BXwHNAG2BHleoOpGdJiWZMkCHWBSTI7OYbbivjHgBuC6= NsrayQ2LkhjgySdDAB+gwWXvzdyW8saX069VGCh5wSgLMp1WgF3A9fGqyhJDApAkoxOAXJivM3m= 1NHCk19U8nrfXlmXuU8VgiQVZAKzgG9hrSVvhLzfHAsR64GO2OSunwa9fxpwF/BH4DbsAoLxwBC= s5eWvwDTsZ2U4MBHoAMwElmAtQncBq4BbgZ8C5wH/Bpa6+xjsLtMbeASY5277x8B/gUnAugYef4= sw27oUuAwoAa4AVgM3BtXUBztXs7FgeBxwE7A1wvbWAZOBlcBbDaxT4kABSJJGflHJNQlQQ6A16= DvoSjFJficDv3C/v56jA9BA4P+w/+PPApcDDwe9/2vgGuBVdzu3ul//CIwA1gKPYp815wI/ArKx= IDEQuA/4LvAE8E0saMxw9wP2h84vsTE4bYG/AO8CXYB+WNfc92l4AOoZZlsTgdHA2VhXXWhNM4A= fAC9i5+xO91jnR9jeOuDeBtYncaQAJNIA+UUlS9QaJClgC/A/WAvQ02HeH+8+AjYAT1LdnXQd8A= 0sJJUC72OtIJvd9z9xn/cH7nEfAadhLSwF2M8QwFPUHKg8GPgbsMt9PtT9ugkYA4wDPoriOCPZj= LXS1Lat0JqudOtaCxwEioDW9dieJAgNghZpoPyiklfcK8VOQYOkJTkdAe4A+nJ0609vYBH2/zrw= 2IB1UQU4wFchz8PJAMaGbOstd/mDIcseClkvK+T9bCyUFAO/jbC/aEW7reCa/MCBRm5PEoACkEg= jpevl8hMmTMDn81U9cnJyGDt2LMuWVY9z3bdvH7NmzWLp0qW1bCn+1q5dy3nnncd5553HmjW6mC= cKxwI/4egxKy9ig6G7Yf/X22FjegIhpYP7aIZ1WXXABiC/D9yCBa1WWKtRL2z8THuqeyN8QGd3H= bCxRzcBX8dakoZjXUubgH8CnbCruyLJcGsN1AQ27ulM4AKsRSnctirc2sLVdIz7vL37Xkf34atl= e5KA1AUmEgP5RSWvpFuX2COPPEK3bt0oLy9nxowZlJeXs2LFCi699FLWrl3LgAEDeOWVV5g6dSp= /+9vfPKtz7969lJWV8cYbb7B06VLuvPNO3nnnHc/qSRKLsG6xTtgYH7BuoP91v78cCxF3YC1F/w= G+Ayxw39+GhZZBWIhph42d+QMWCh5wX/8rNm7mMSxwXQL83N1GITbeZyI27qgcuB9Yjg2E7oqNH= boZu1Lt3TDH8SA1xzgFfAWchAW9m8Ns60VgDjYoe0hITXdi4WcL1qr1P+57G4B3ImzvO9gVdG+H= qVE8kjZ/rYoncvOLSgq8LqKp9e2VNQobC+BVEMoFRjmO82C8dzRnzhx27NjBtGnTql774Q9/yMi= RI7n2WruKeMaMGQwaNIiLL7443uWE5ff7yciwxu7i4mKmTZvGU0891ST79vl8Z2AfjCKSYNQFJh= Jj+UUli0mjmydWVFTgOA7l5eWsWrWKFStW0K9fv6r3W7ZsWWP5devWMXr0aAYMGMDMmTMpLS2te= q+wsJDx48czZMgQFi9ezAsvvECHDh3w+XwcOnSIhQsX4vP5eP7556vWWbNmDZdffjnDhg1jyZIl= R9UXCD/bt2/n8ccfZ8qUKbE+BSKShNQFJhIH6XS5/L333su991Zf5fv444/Tv3//sMsWFxczefJ= k5s6dy7HHHsukSZOYPXs2U6ZMYe/evdx555089NBDdO3ald/85jeceeaZFBQU0LlzZwDGjBnDxo= 0bq7a3fft2Vq5cSV5eHtu3b+eiiy7iX//6Fx07dqyx3yNHjtCjRw8AioqKmDt37lHBTETSi1qAR= OIov6hkCdWtQSlpypQp+P1+SktL+ec//8m8efOYO3du2GXXrFnDsGHD6NmzJ1lZWdx6663MnTsX= x3FYu3Yto0aNonfv3rRr145vfvObAHTq1Klq/YyMDLp3r74i+b333mPq1Km0a9eO3Nxctm7dWiM= gBWRmZnLw4EHWrl3LRx99pDFAIqIAJNIE+mAhqEk5jtMkj0AXU+vWrRk0aBBXX301zz33XNhl/X= 4/O3furHqelZVFmzZtcByHkpKSiPsIPZ7y8nIcx6GyspK8vDz8fn/VY+jQoWG30apVK4YMGcJ11= 12Hz+drknOTRho6WWg8Jxltj92V+aII+xsIvBSnfYcT7lhbYoO6T2zCOsSlACQSR317Zc3Hupq3= NvW+4/3hXllZSXFxMWVlZZSWllJeXk5+fj6LFi1i4MCBVYFn165d7NmzB8dxGDJkCAsWLGDp0qW= UlZWxYsUKbrzxRgByc3N59tln2bhxI6WlpRQVFVUdR8+ePSkoKGDHjh0UFBQwefJkFi9eTL9+/X= jsscf44IMPKCsr491332XLli0Ra96xYwebN2+mf//+CkCNE6vJQuM5yehl2I0Xg8fhBfbnw+7XM= zpO+w4n3LGegU0h8mkT1iGulB+gKZ5Ky6vAoCr4gI3/KcDuCNtU5yIXGFVRURHXq8Buuukm5syZ= U/W8ffv25ObmcuGFF3Lbbbdx/PHHk5eXxzXX2FXU//jHPxg+fDhvvvkm999/Pzt37uSqq67i9tt= vp3Vru5HuU089xZw5cxg1ahTZ2dk4jsP48eN55plneOKJJxg3bhwtW7akvLycH//4x7Rt25Y333= yTWbNmUVZWxsSJE7nssstq1Pn+++9z9dVX4/f7GTVqFLfddhs5ObGeSi685s2bp+JVYK2A/4dNF= lrbrO6JYBp2l+rQmzyCXQK/H30Opi39w0s8pWUAcsPPFuxS+CPARuz+IUeaqIRcYNSRI0fifhl8= POXl5VFWVsb48ePrXjhBZWZmehmA6jNRKRw9Wenf3a/fwCbz3I7d32cmNgcYhJ8s9GxsmohgY93= 9B08SutGt5z/A6xFqOPqyPrvJ4GCsBWcCNi/X/2L3EFocsuwk7CaMb7jbDK6zFTalxznY/YW2uM= e1PUItn1Jz4tbrsRak0IlPQydvfRLrjgveN+5yvwJ6AC8DD1E991m4iVYlxtQFJhIjfXtlzQ8KP= 4FWn8Xu900Vfqo0RRdPvB5+v5/du3ezZ88e/H6/5/UkaRfYr7GAcRJ2M8Al7td3sMk7v4/d0Rhs= CodzsclKx2PdNediVy9egt3pOOA32P/pLOyD+wrsJoeBP6h92ISgPuxDfibwHtWThD7s7vsy973= AeuFqqHk5n/k2NjFroPnxH1gIeT3MssFC6wzY427zQyzoRarlQWx+r0Js4tbyMMcUCDC3YJO8Xo= N1FYbuuxs2QerP3X3nYDeVnIHNr5aDBay3sX8riQNdBi8SA0HBx8F+QQYeTR58UsFrr73GxIkTA= ejRowdjx471uKKkdB3RTVQKcBZHT1baEgspFVh4Ko6wn9DJQgOtP6cAV2GtKOUcPUnos9gHfUC4= Gk4Ddofs7wA2cetYLMydh7Xw1JU4Q+sMCLRSP421Rt0SoZargJOpnrg13MSnkSZvDd33cGyakUD= LziPAK9j0IJEmWpUYUwASaYQwY30+pjr4VHhVF5AILRANdskll1BeXl71PJmPxUPRTlQK1ZOVLg= x5fSXWQjEP+7D/d4T1D4U874i1hNyFhZ9srAXlKWyS0NFh1otUQzhrsZaonlgr1r4o1glXZ7DmW= Njy11JL8MSt4Y4p3OSt4fbtw6bLCNjnbtsh8kSrEmMKQCINFCb8JFSrj0JD2gueqPS/1JyotBXV= E5Vuw1qH5mMtIJuA07Gus13YmJU2WGtSIAAFJgv9gqMnC22LdeXcgw0yPgYbMB2YJPRSwk8SGq6= GEqwVJFQlFjymu+uEE1pX6HM/8Dl2JVYR1uX0p1pqqaDmxK3BE58Gjmk98Co2TmgDNhfaZuw8Bu= /7bWxs0CJsDNW33OftqJ5odT8WJFu7tesHOsYUgEQaIGSgc3Dw8bTVJ5gCUNr7I9FPVPopR09WW= oR1kS3F/n/fHbTt2iYLvQC7583NQctfh3UThU4SGixcDetrOb4lwO1YAAnnR0F1bcW65EInWr0E= +D0W0uZSHabC1TKOmhO3hpv49DiOnrz1v+66ofsejZ3Th9z9Pox1w0WaaPWVWs6FNICuApN4ysX= GEPQhiQbc5xeVXBPpvURv9XHlAqMOHjyY1FeBpYI2bdqk4mXwsXQXFiRWNWDdTCyI/DmmFUnaUA= uQSJQS4PL2elELkCS4wDiYj+taMILv0LDgJAIoAEn8fYw1uZ9McrQCnRz6QoRWn49JsC6vUApAk= sDmYGNvZgE76rnuKGzQ8Szs0nWRBlEAknj6GAs9GVhoSGQnY+MlatDl7SJxcUMj1l3M0Tc8FKk3= BSCJpwrsKolk0CP4SSJf3h4ttQCJiESmACTxlhRhIViSDHSukwKQiEhkCkAiZgt2tVrg+4S9vD1= aCkAiIpEpAImYSqoHbFeQ4Fd4RUMBSEQkMgUgEbMFu/nZKdgN4JKy1SeYApCISGQKQCKmwn2kzE= 3rFIBERCJLhvuyiIiIiMSUWoBEUpRagEREIlMAEklRCkAiIpEpAImkKAUgb3Xs2HGM1zWISGQKQ= CIpSgFIRCQyBSCRFKUAlBA+8boAEQlPAUgkNX2iAOQ5P0l8I02RVKfL4EVSzxbgUJcuXSZ7XUi6= 6tKlyxSs9cfvdS0iEp5agERSzxHsrtZ91ArkmSKg3OsiRCQyBSCR1HQE+KRr165ziouLb/C6mHT= SrVu3e7Dw8wk2x5yIJCCf1wWISFxkAr2By4BTd+zYMc7jetJC9+7d5wNLgf8AH6IAJJKwFIBEUl= dv4EygD3Dy9u3bFYLiKDs7ez7W9fgKNqfcIU8LEpFaKQCJpK5AK1AubggCmn322WfXeFpVCurRo= 0cg/BQArwKlnhYkInVSABJJbWFDEMC2bdsUhBohJydnftDTT7HwU4i6vkSSggKQSOoLDkGtgF7u= o1ng/UuvuHJsrHb26ksL/+Z+ewQ4GKvtJqhPgY+x4FOIDX4+7GVBIhIdXQUmkvqOAJuxD+uTsLE= pRVgIygBOaJbRjEp/zBotTgAqgP2kVgD6lJotO59ggWcTFn405kckiSgAiaSHI+5jE/bBfRL2oX= 0ScMbgoSOI1R2DXn1p4UEs/BQA20md8TBHoOo0fUr1pe5q9RFJQgpAIuklOAiB221z3oWjKN6+D= b8/JjcuPgR8AWzDAsLnsdhoAviU6js7B8KQproQSVIKQCLp6UjQ10OtW7fh5N65sdp2CRZ6irCA= VRyrDYuIxIrmAhMREZG0owAkIiIiaUcBSERERNKOxgCJiMSWDzgNwHGcAo9rSRo+n68PNrB8o9e= 1SHpQABIRiRHHcWJ1N4G0Ey4s+nw+3axX4kZdYCIijddV4Sf23HPaxes6JDWpBUhEpBEUfOLLcZ= ydoNYgiT21AImINIxP4afp6FxLrCkAiYg0TFevC0hD6g6TmFEAEhGpv26O4+zwuoh043aHKQRJT= CgAiYjUj0/hxzuBMUEijaUAJCJSP928LkDUCiSNpwAkIhK9qpsciqeO87oASX4KQCIi0euKPnwT= gVqApNEUgEREoncc6gJLBAqh0mgKQCIi0fM5jvNnr4sQQLchkEZSABIRkWTjQ61A0kgKQCIiIpJ= 2FIBEREQk7SgAiYiISNpRABIREZG0owAkIiIiaUcBSESSTWsgy+siRCS5Nfe6ABGRKLUGugOdsN= 9d+4AdQImXRYlIclILkIgki0wgGxgKjMgvKvkQOAULRWoREpF6UQASkWTRGmv9aQ/0BMgvKnkHG= IIFIYUgEYmaApCIJItMoFXQ9wDkF5W84AYhhSAJmA04YR7rvCyqDqOAe2j6z+WBwEv1XOdmYHgc= amlSGgMkIvEUGLcTC7WGm/yiknf69soaDXyMxgaluzuB7dis8b90X2sGjPWsorodC/wW8DdiG4O= BQuCLKJf3AU8B/eq5n8fquXxCUgASkXhoDfTGxuzESiZwTG0L5BeVvNy3V9Y17v4/RiEoXTnALi= wABVQCz3lTTlQWNHL9VsDdwLX1WMcBzgH2N3LfSUkBSERiKr+o5BqP9z8foG+vrBHoSrFUlwnMA= r6FtfS8EWE5H3AGcBDY4r42GLgLC+qPAE9igWAw8CugB/Ay8BCQ425/NvAbbCLWm4CtQdsKXacU= OM3dxx+B29x9jcfGrf0K+CswDRvXdiPwb2Ap0MJ9/8fAf4FJVHffTQZWAm+FHOMU4DLs//oVWEv= QXcAq4FbgemB0mG0edtcfDtzvnp9fA59HqCHLPYb/AK/XcfwJTWOARCQl5ReVrAK+jsYGpbKTgV= 8AZ2If8KHuwkKNH8gPej0QaG4BvgtcAxwPdAPuBX4OfNtd7g5gBnCd+/x64G1ghLutSOuABYnxw= ElunUvcr++4638f6IwFlhlYUAMb5N8F65p62F0u4F6ODj9gwawA+7/+MnAfMA4LQt8EymvZJsAe= t/4PsZAVqYbLgJlBtdZ2/AlNAUhEUlZ+Ucn8oAHSulw+9WwB/gf70H46zPu/xz6oM7AwHDAY+Bv= WTVaE3VqhBGsFeQtr2SnBWobGA1cCnwFrsVakIqyVhlrW8WGhaQPwf1iLyPvuPje7y37ibucp4H= dB9W3GWlzGAD8N2ld9XAFsxLqCo9lmgXtsT2MtRVsiLP8sFngCajv+hKYAJCIpT5fLx9/TTz/N/= fff39S7PYK1NvQlcvcXWCvQ+1R3f2UQ/v+BD+ga9HwfFgoc4ECEbUdaJ7Dfr0LqiORQ0PfZWCgq= xgZGN4QTVEd9ttkc2I217ERaPrjW2o4/oSkAiUhaSJbL5SdMmIDP56t65OTkMHbsWJYtW1ZjuX3= 79jFr1iyWLl3qUaXV1q9fz6uvvup1GcGaYd03bahuiWiOdQV9G1iPjeH5OtayMdxd/m3sSrELsU= HF38LGBrXDuqrau9vr6D58tazjuOt1oPr/Wwf30Qxo635/grudzkHbHApsAv6J3fuqTZTHXYGNT= 8L92p7qsb6RtunHxvuc4b52PfCnetRQ2/EnNAUgEUkrbggagf3CT7gg9MgjjzBt2jQmTZpEeXk5= GzZsYMyYMVx66aW8++67Vcu98sorTJ06Fcfx9nNmz549fPTRR1x88cWe1hHi98CD2OBfP/ZhfAQ= bg/Mu1h00ERvbshgLQf8FtmHdP78E3sNC0RPYB3p7rAXph1i3233ApbWsAzb4uTc2YPhi7Eqvnw= O3Y5eSD8LC2AT39fnAN7AxQue49W3BQvsAd5tTgLMjHPeLwBwgF+uq6unup2Mt2zwMXOKes2Xue= ZhTRw3Bajv+hJbwfXQiEnffyi8qWe51EV7o2yvrm9TvcvmvOY6zIY4lATBnzhx27NjBtGnTql77= 4Q9/yMiRI7n22uqrnGfMmMGgQYM8Cx+VlZU8+uij3HTTTTz99NOUlJQwadKkuO/X5/N9FxvfUhj= 3nUk4d2EBaZXXhTSGWoBEJG25rUFnkoCtQRUVFTiOQ3l5OatWrWLFihX061fzfnUtW7as8Xzdun= WMHj2aAQMGMHPmTEpL7UrkwsJCxo8fz5AhQ1i8eDEvvPACAB06dMDn83Ho0CEWLlyIz+fj+eefr= 9remjVruPzyyxk2bBhLliw5qsYFCxbwgx/8gMzMzKPek5QVGPPzcV0LJjoFIBFJayGXy8fqrtWN= du+995KRkUGrVq0499xzue++++jfv3/E5YuLi5k8eTIPPfQQy5cvZ9u2bcyePZu9e/dy5513Mmn= SJJYvX86yZcvYv9/ue1dQUFC1/pgxY5g+fXrV8+3bt7Ny5Ury8vKYO3cuN998M7t37656f926df= Tq1YsuXYLvNSgpbg42JmgNdn+tpKYAJCJpz715Yq77qJXjOE3ymDJlCpWVlRw4cIC3336befPmM= WfOnIjLr169mmHDhpGTk8Pxxx/PLbfcwty5c1mzZg0jR47klFNOoW3btgwcOLBqnY4dO1Ydk8/n= o1u3blXvrV+/nqlTp9KuXTtyc3PZunUrhYWFVe//5S9/YejQoVWDtW+66SbuvvtuOnToEPdzI56= 5AbuFwMteFxILCkAikvb69sr6M3a1zJd1LdsU4QcgI8N+Pbdu3ZpBgwZx9dVX8/zzzx+1XPDz4u= Liqu+zsrJo06YNX3zxRY3lQo8j9PvDhw/jOA6VlZXk5eVRWVlZ9Rg6dGjVsn/6059qvPfYY49x3= 333sXv3bgUgSQqaCkNE0lbfXlnzgTKsOf9zat6zJax4fwD7/X527NhBWVkZpaWlNG/enI0bN/Li= iy9Wtd4E6ti1axd79uzBcRwGDx7MT37yE6644gqGDx/OihUruOGGG8jNzeX222/n/PPPJzs7my1= bttC1a9eq7fTs2ZOCggI6depEQUEBCxcupFOnTvTr149x48aRm5vLqaeeyoYNG8jKyqJXr14Rz4= sCSkzdDHyEdTdFozU2bYUDzI3D8ilHAUhE0lLfXllPYMFnl/v4GLvpW63i/QF/yy23MGfOHAAee= OAB2rdvz2mnncZFF13ErbfeWrX/vLw8Hn74YQBycnIYNmwYL774IrNmzeKOO+7gqquu4qc//Smt= W7dm3LhxXHXVVYwaNYrs7OwaQWXy5MncdNNNXH/99Zx++ulMmTKF4cOH07ZtWyZPnsxdd93FwYM= HmThxImeddVadx68AFDP1nXH9HGyKiqlxWj7l6DJ4EUmry+CDWn0+xW7/v4Xq1p+yOlb/2pEjR+= J+GXw85eXlUVZWxvjx470upcEyMzN1GXx412I3I4z2Pjz1XT6laAyQiKSNoFafT7HwU0h1AKor/= ABNNwg6Hg+/38/u3bvZs2cPfr/f83qSbAzQP7Huoifd5z9wn48KWa4FdlPBN7EbFua4rwcGD7+L= TVzaNmidwcAibMLWn2B3iJ4EXBS0zHBs/rK3gO8Evd4fm1V+NTYbe6CGKdj/75Xu9mtbPi2pC0x= EUl5Iq8/H7tdtRNfqU0Myd/G89tprTJw4EYDs7GzGjh3rcUVJ5dvAn7FLwQH+gY2heT1kuf7Y/7= Fp7jrbqZ4xfTw20P5+bA6z31I9M/3NWCj6C9YqMwO43N1mNnAu8CP3+6XAQGzqiz8CN2LduA9h8= 3gFz+Q+EpvJfR12r6twy6clBSARSWlhurwKsfBTr+ATkMwBaNSoURw6VD2PZTIfiwcOYDOlj8Xu= gnweNgFr6EncioWfCmzqjWJs+ozAjOlgM6a/goWi4Jnpwebggpo35jwLuMd9BJyGTc+xHOsOxK3= nOGrO/D4OG0wN1ooUbvm0pC4wEUlZbpfXZmAtsALrxmhw+IHk7gJLlYeH1gJfw1pYOmMzn4faBV= yJTa8yD7vJZm0zpkeamT54xvUMLHj5gh5vAccCLUPWa0Hkmd8jLZ+W1AIkIikn1q0+wdRqktYqs= WAxHZu4NJyzsdnel2IzqH8Dm2T0SWycz2pqzpi+HngVm1drAzZB6mYsYJ3gbvN9d3//wWZoPx0L= WPnAH7AJXd/HutPuBHpRPZP7pVTP5B5p+f8CLzTojCQxXQUmIt8CLsDGKSSN/KKSa+gUxtUAAAM= cSURBVMK97rb6bMcGNu8ihuEH+FppaWlSXwWWCtq2bevlVWBtsa6tC6nZShNwFtaq8iBW393YOJ= sL3O+7YWHmYar/T16CjQMqx8YH5WDdbWBjfd5115+EhZkHsG4zsNamn2Hh5kOsYePvwJ+wIPWEW= 8tEdzvhln+aKG4CmmoUgETkbGwKiPbuI9G1AbJCA1AjL2+PlgJQAvA4AGViV2r92YN9SwypC0xE= tgJHsF/srT2upTatsclKTyRkzITb6rMP+ys2pl1eodQFlva+g3VXSZJTABKRz0mO5u8uhLRQxfL= y9mgpAKWtUdiA4llY15EkOQUgETniPhJdjct14znQuTYKQGlrsfuQFKEAJCLJogy78iXw/Xas+6= 6AOLf6BFMAEkkNCkAikiyOYON8NmO/u2J9hVdUFIBEUoMCkIgkizKstWcXNlVArK/wEpE0ogAkI= ski0AIU7u67TUYtQCKpQQFIRKQeFIBEUoMCkIhIPSgAiaQGBSARkXpQABJJDQpAIiL1cMIJJ/xm= 9+7dM72uQ0QaRwFIRKSe1AokkvwyvC5ARESknhxgp9dFSHJTC5CISPQcoFgtQAlhv9cFSHJTABI= Rid5OYL8CkHe6dOkyCbX+SAwoAImIRG8/sLNLly6/2blzpwZCe6MY+NLrIiT5KQCJiNTPfqC4a9= eu84uLi6/xuph00q1bt9/hhlCva5HkpwAkIhI9B2uBKARy1RXWdLp37/4Mdt53ohYgiQGf1wWIi= CQZH5ALDHK/dt2+fbtaguIoOzv7WWAH8FdgIwpAEgO6DF5EpH4CrUAFuC0S2dnZ870tKXW54SfQ= 6qbwIzGjFiARkYY5DmsB6uN+7Qrw2WefqTUoBnr06DGfml2OBcC/PC1KUooCkIhIwwVCUK77fTf= cICSNErjR4Q6qW372o9YfiSEFIBGRxjnOfXSlZhAKUCCqnQP8N+R5MRZ4ClC3l8SJApCISGwEB6= HA18DrEplDdcAJtPzsD/qq8CNxoQAkIhJbgcBzrPvVh1qBahM6r9eX1AxFIiIiIiIiIiIiIiIiI= iIiIiIiIkf5/36WKhVOfl0jAAAAAElFTkSuQmCC" width=3D"576" height=3D"308" alt= =3D"" />Fuente:</= span> Ministerio de Educa= ci=C3=B3n (2022).</spa= n><sp= an style=3D"font-family:'Times New Roman'"> <ol start=3D"2"= style=3D"margin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style= =3D"margin-left:32pt; line-height:115%; padding-left:4pt; font-family:'Time= s New Roman'; font-size:12pt; font-weight:bold; color:#767171">Metodo= log=C3=ADa</li></ol>La presente investigaci=C3= =B3n adopto un dise=C3=B1o cuasi experimental, enfoque cuantitativo alcance= explicativo y corte longitudinal, pues se trata de detallar e investigar l= as caracter=C3=ADsticas del fen=C3=B3meno en cuesti=C3=B3n y establecer las= diferentes causas y efectos, as=C3=AD tambi=C3=A9n describir la realidad d= el lugar donde se desarrolla la investigaci=C3=B3n. Debido que, este tipo d= e investigaci=C3=B3n aumenta la compresi=C3=B3n del tema, y contribuye a te= ner resultados concluyentes y encontrar las diferentes razones por que se d= esarrolla dicho fen=C3=B3meno, permitir=C3=A1 tambi=C3=A9n aumentar y perfe= ccionar las conclusiones del estudio y anticiparse a los diferentes cambios= y obtener nuevos puntos de vista al ser una investigaci=C3=B3n de campo el= an=C3=A1lisis y aplicaci=C3=B3n se dar=C3=A1 lugar en la Unidad Educativa = Combatientes de Tapi con los estudiantes de primero de bachillerato en el a= =C3=B1o lectivo 2023-2024.La poblaci=C3=B3n= de estudio consta de 145 estudiantes de los primeros de bachillerato distr= ibuidos en paralelos =E2=80=9CA, B, C, D, E=E2=80=9D, adem=C3=A1s 5 docente= s del =C3=A1rea de ciencias sociales, en particular que dictan la asignatur= a de Historia. Para tal efecto la muestra fueron 19 estudiantes de primeros= de Bachillerato, distribuidos en los paralelos =E2=80=9CA, B y C=E2=80=9D = y 2 docentes del =C3=A1rea de Ciencias Sociales de la Unidad Educativa Comb= atientes de Tapi.T=C3=A9c= nicas e instrumentos para la recolecci=C3=B3n de datos. la recolecci=C3=B3n de datos es una part= e fundamental en toda investigaci=C3=B3n, pues el estudio de las metodolog= =C3=ADas de aprendizaje requieren del uso de las diferentes t=C3=A9cnicas c= omo es la observaci=C3=B3n directa mediante el uso de una Lista de Cotejo, = que permitir=C3=A1 identificar los conocimientos que poseen los estudiantes en la asignatura de Historia previo a= la aplicaci=C3=B3n de la encuesta la cual contar=C3=A1 con un cuestionario= donde las interrogantes que permitir=C3=A1n identificar las diferentes met= odolog=C3=ADas que utilizan los docentes en el proceso de ense=C3=B1anza ap= rendizaje = de la asignatura de Hi= storia en el primero de bachillerato y= los docentes del =C3=A1rea de Ciencias Sociales. Observaci=C3=B3n Directa: aplicado para observar directamente al docente= que imparte la asignatura de Historia y a los estudiantes dentro de aula p= ara recolectar datos que precisen las metodolog=C3=ADas utilizadas para el = aprendizaje mediante una lista de cotejos. Encuesta: su final= idad es conocer la opini=C3=B3n de las personas acerca de alg=C3=BAn tema, = o bien contar con m=C3=A1s informaci=C3=B3n respecto de un hecho o suceso, = estar=C3=A1 compuesta de entre 15 a 20 preguntas, abiertas y cerradas, las = cuales permitan tanto al inicio de la investigaci=C3=B3n como al final dete= rminar el grado de conocimiento de los estudiantes.La entrevista: es una t=C3=A9cnica de investigaci=C3=B3n cualitativa qu= e consiste en una conversaci=C3=B3n dirigida entre un entrevistador y un en= trevistado, con el objetivo de obtener informaci=C3=B3n sobre un tema espec= =C3=ADfico. Esta interacci=C3=B3n permite explorar en profundidad las perce= pciones, opiniones, experiencias y conocimientos del entrevistado.</= p> <a id=3D"_Toc57614423"></a><a id=3D"_To= c80201716"></a><a id=3D"_Toc80741352"></a><a id=3D"_Toc83138069">T=C3=A9cnicas de proc= edimiento para el an=C3=A1lisis de resultados</a>: se aplic=C3=B3 el programa Excel y SPSS, V.25 adem= =C3=A1s de un an=C3=A1lisis cuantitativo de informaci=C3=B3n mediante el pl= anteo de una Hip=C3=B3tesis Nula y una Alterna aquellas ser=C3=A1n contrast= adas mediante el c=C3=A1lculo de la U de Mann =E2=80=93 Whitney como prueba= no param=C3=A9trica. La encuesta se realiz=C3=B3 mediante la aplicaci=C3= =B3n Forms de Office 365, aquella es una herramienta utilizada para formula= r enc= uestas de opci=C3=B3n = m=C3=BAltiple, abiertas entre otras donde se obtendr=C3=A1n datos de manera= r=C3=A1pida y segura.Pro= cedimiento. En primera= instancia se procedi=C3=B3 a solicitar el ingreso a la Unidad Educativa Combatientes de Tapi a su = primera autoridad como es el se=C3=B1or director de dicha instituci=C3=B3n,= posterior se socializ=C3=B3 el tema de la investigaci=C3=B3n tanto con los= docentes como padres de familia y estudiantes para as=C3=AD continuar con = la firma del consentimiento informado el cual amerita a los estudiantes ser= parte del estudio en cuesti=C3=B3n. <ol start=3D"3" style=3D"ma= rgin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-lef= t:31.25pt; text-align:justify; line-height:115%; padding-left:4.75pt; font-= family:'Times New Roman'; font-weight:bold">Resultados </li></= ol>El an=C3=A1lisis de datos realizado en este estudio= da a conocer sobre las preguntas planteadas a los estudiantes en relaci=C3= =B3n con la asignatura de historia, para posterior fortalecer la misma (</s= pan>tabla 3= ).Tabla 3Estad=C3=ADsticos descriptivos de las preguntas del cuestionari= o aplicadas a los estudiantes <spa= n style=3D"font-family:'Times New Roman'"> </div> <= div class=3D"Section_2"><table style=3D"width:584.6pt; margin-right:7.05pt;= margin-left:7.05pt; margin-bottom:0pt; padding:0pt; border-collapse:collap= se; float:left"><tr style=3D"height:163.65pt"><td style=3D"width:43.05pt; b= order-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding= :0pt 5.4pt; vertical-align:middle"> </td><td style=3D"width:30.3pt; border-top:0= .75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt;= vertical-align:middle">Le gusta la materia de historia</span= ></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= style=3D"margin-right:3pt; margin-left:3pt; margin-bottom:0pt; text-align:= center; line-height:115%; font-size:9pt">=C2=BFQu=C3=A9 m=C3=A9todos de evaluaci=C3=B3n prefiere<= /p></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-= bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">=C2=BFCu=C3=A1l es tu nivel de comprensi=C3=B3n lectora?</= p></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-b= ottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">Te motiva profundizar sobre la materia de historia</td>= <td style=3D"width:47.55pt; border-top:0.75pt solid #000000; border-bottom:= 0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">=C2=BFCu=C3=A1l es tu opini=C3=B3n sobre la importancia de aprender hist= oria en la educaci=C3=B3n?</td><td style=3D"width:49.15pt; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.4pt; vertical-align:middle"><= span style=3D"font-family:'Times New Roman'">=C2=BFCon qu=C3=A9 frecuencia = navegas en internet para investigar temas hist=C3=B3ricos fuera del aula?</= span></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; b= order-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle= ">=C2=BFHas participado en el aula invertida anteriormente?</= span></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; b= order-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle= ">Qu=C3=A9 tan efectivo es el modelo de aula invertida= </td><td style=3D"width:40.25pt; border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= style=3D"margin-right:3pt; margin-left:3pt; margin-bottom:0pt; text-align:= center; line-height:115%; font-size:9pt">Encuentras los materiales previos (videos, lecturas) claros y c= omprensibles.</td><td style=3D"width:44.05pt; border-top:0.75pt = solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; verti= cal-align:middle">Los conceptos estudiados previamente te ayu= dan a desarrollar las actividades en clase</td><td style=3D"widt= h:49.15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000= 000; padding:0pt 5.4pt; vertical-align:middle">Consideras que= tienes m=C3=A1s oportunidades de interactuar con el profesor en el aula in= vertida</td></tr><tr style=3D"height:35.7pt"><td style=3D"width:= 43.05pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00000= 0; padding:0pt 5.4pt; vertical-align:middle">N</td><td style=3D"= width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #= 000000; padding:0pt 5.4pt; vertical-align:middle">19</td><td styl= e=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle">19</td><td= style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75= pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">19</t= d><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom= :0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">19= </td><td style=3D"width:47.55pt; border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= style=3D"margin-right:3pt; margin-left:3pt; margin-bottom:0pt; text-align:= center; line-height:115%">19<= /span></td><td style=3D"width:49.15pt; border-top:0.75pt solid #000000;= border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:midd= le">19</td><td style=3D"width:30.3pt; border-top:0.75pt solid #00= 0000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align= :middle">19</td><td style=3D"width:30.3pt; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-= align:middle">19</td><td style=3D"width:40.25pt; border-top:0.75p= t solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; ver= tical-align:middle">19</td><td style=3D"width:44.05pt; border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4p= t; vertical-align:middle">19</td><td style=3D"width:49.15pt; bord= er-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0p= t 5.4pt; vertical-align:middle">19</td></tr><tr style=3D"height:3= 7.35pt"><td style=3D"width:43.05pt; border-top:0.75pt solid #000000; border= -bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">M</td><td style=3D"width:30.3pt; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:middle">1.32</td><td style=3D"width:30.3pt; border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4p= t; vertical-align:middle">2.11</td><td style=3D"width:30.3pt; bor= der-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0= pt 5.4pt; vertical-align:middle">1.74</td><td style=3D"width:30.3= pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 5.4pt; vertical-align:middle">1.05</td><td style=3D"wid= th:47.55pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 5.4pt; vertical-align:middle">1.16</td><td styl= e=3D"width:49.15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 5.4pt; vertical-align:middle">2.11</td>= <td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0= .75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">1.47</= p></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-b= ottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">2.26</= span></td><td style=3D"width:40.25pt; border-top:0.75pt solid #000000; = border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middl= e">2.26</td><td style=3D"width:44.05pt; border-top:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-ali= gn:middle">1.79</td><td style=3D"width:49.15pt; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:middle">1.16</td></tr><tr style=3D"height:37.35pt"><td= style=3D"width:43.05pt; border-top:0.75pt solid #000000; border-bottom:0.7= 5pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">Des.</td><td style=3D"width:30.3pt; border-top:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-ali= gn:middle">.47</td><td style=3D"width:30.3pt; border-top:0.75pt s= olid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertic= al-align:middle">.93</td><td style=3D"width:30.3pt; border-top:0.= 75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; = vertical-align:middle">.73</td><td style=3D"width:30.3pt; border-= top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5= .4pt; vertical-align:middle">.22</td><td style=3D"width:47.55pt; = border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddin= g:0pt 5.4pt; vertical-align:middle">.37</td><td style=3D"width:49= .15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000;= padding:0pt 5.4pt; vertical-align:middle"><spa= n style=3D"font-family:'Times New Roman'">.73</td><td style=3D"w= idth:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #0= 00000; padding:0pt 5.4pt; vertical-align:middle">.51</td><td styl= e=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle">.93</td><t= d style=3D"width:40.25pt; border-top:0.75pt solid #000000; border-bottom:0.= 75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">.99= </td><td style=3D"width:44.05pt; border-top:0.75pt solid #000000; border-bo= ttom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">.85</sp= an></td><td style=3D"width:49.15pt; border-top:0.75pt solid #000000; bo= rder-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"= >= .37</td></tr></table> </div> <div c= lass=3D"Section_3"><div style=3D"clear:both"><img src= =3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAUDBAQEAwUEBAQF= BQUGBwwIBwcHBw8LCwkMEQ8SEhEPERETFhwXExQaFRERGCEYGh0dHx8fExciJCIeJBweHx7/2wB= DAQUFBQcGBw4ICA4eFBEUHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh= 4eHh4eHh4eHh7/wAARCARfAzMDASIAAhEBAxEB/8QAHQABAQACAwEBAQAAAAAAAAAAAAECCAUGB= wMECf/EAFQQAQABAwIDAwUMBAkJBgcAAAABAgMEBREGByESFzETQVFVkQgUFSJUVmFxkpTR0jeB= obIWIzI2UnR1scEkMzRCYnKCs+EYQ0RGZKIlJzU4ZZPi/8QAGwEBAQADAQEBAAAAAAAAAAAAAAE= CAwQFBgf/xAA0EQEAAQQBBAEDAAcIAwAAAAAAAQIDBBFSBRIUITETQVEiMjRhcYGRFSU1QqGxwd= Ez4fD/2gAMAwEAAhEDEQA/AOgSiyj9Lh8VAAAAgAC/YAFgAFSUWUEkAFgRUQnX3BaKK65imimqq= fREPt7zzNv9Ev8A/wCuUmqIn3LKKZn7PgPpdsXrMRVes3bcT03qoml89pWKok1P9BJVJVigAEos= oACRv5xY+N/hUlUkVAAAASUWUUAECUWUIAAkEnwVJ8AQBQARUk+slaaZqqimPGVhJn7vtiWvKV7= zHxYfvYWqIt0RTH62aw47le5AFYgCSqSiyiAAASEiwgAgAMgAAAIABUqQnxGMs49ACMkY1SynpD= CrqwrlsphEmF8Dfdg2bQXYiOqBEbQLKMoY7AElYNkUkVE2UNG2IqAPldneX0rnal8ZY1SsQgDWy= 2Sikml2i0RvP0I+tunanqtMblJn0zgNht7YYPvKLKOmHPAAAAgAC/YA8+wsB5t37NG0vUNY1C3g= aZiXcrIuTtTRRH7foh7Hw37njWsvGi9rOrWMCuqneLdqiblVM+aJ8I9m7lyMyzY/8lWm+1j3Lv6= kPD58XeuEuVfFPEvDWTruDjxTYtUzVZoriYqyNvHsO2anyZ1XhLV8TVsqzGuaLYuxVlW7E7XexH= nmmfN9Utj+F8/SNS0XGyNFuWqsPsRFumiNuxER/JmPNMeGzys7q/ZTE2ff7/8Ah3YvT+6qfq+mh= uTYu41+uxft1W7tuqaaqao2mJjzPm2q548psfiTHua5oVqm1q1Eb124jam/H+FTVvLxsjEybmNl= Wa7N63VNNdFcbTEx5no4WdRl0bj5+8OTJxqrFWp+HxZ49mvIybdi3G9dyuKKY9MzO0MHYuWePRl= cfaNZuRvRVlU7x9XX/B13a+yiao/DTRTFVcRLaDlPyv0LhjQce9m4OPmapdtxXeu37cVzbmY37N= O/ht4dHKZfGvLnFyK8e9q2jU3Lc9mYiqidvofTnNn5Gm8tdYyMauaLnkJoiqnpMdrp/i0lqqmqq= aqp7Uz1mfTL5XBw6s+arldUvbyMiMXVFNLY3nXxHwPrUcM2MDO07JtUavbryqbU0z/F7TE77eZ1= /n7HLmOHMP8AgzbwaNQm/O04tO3xem/a26fVu8u5eU01cdaLFURMTnWomJjff40Nk/dK6VTmcH4= OFh49qm9fzrdunaiI6zP0Ou5RTh3rVvcz8/dpoqnJt11ahqfTE1TEREzM+HTxfSvGyKYmqqzciI= jeZmmejczQeGuGOXPCPl/g+b9VmiJvXaLHlLt2r6odf1bmrwzVpmTR/BXXqZm1VHaq0yIiOn1tl= PWKq6tW7e4/i1z0+mmN11alqlTj36qYqps3Ko9MU+KXLN23G9dqunfw7VOzdLlNRhRyq0bMu4tr= sxhzcqmbcb7bzL5cGcecE8Z593S9MtU13qbc1VUXceI7VPhLGet1z3TFv1H7/wD0y/s6mdR3fLS= 4opqrnaimZn0R1bCcUcq9KzeeWLpuLajH0vIxvfeRao6RG0zE0x6N9v73qPEWtcCcucDExM6zj4= dFyJizaosxVMxEeP8Ah+tur6xT+jFunumY+Gunp8+++dRDTXT7Fu3n49WpWblOJ5Wny3xZ/k79f= B7fzojln3f0fwetabTqPlrfYnHpiK9uzO++3+Ll+YHMvgvijSMXSNGt1++7mfj1U9qxFMbRXEz1= +p2T3R2Nj2uU9dyjHt01RetdaaIifCXNcy67l21NdM0zvWt/wb6MemiiqKZiWp0Y2RMRMWLkxPh= PZlhct3Lc7V0VUz9MNouDubHCdHDWm4lvh/WMq5j4tq1crs4FNdM1U0xTPWJ9MO8cMavw3x1g5l= inQsmzbtxFNy3m4fkpmJ3229PnbrnV7lqZ77XqP3tdOBTXEdtXtpCO4c4+G8fhXmBqGkYkTGPTM= XLVM/6tNXWI/VDp72bVyLtEV0/EvPuUTRVNMgDYwSUWUUAECUWUIAAkEnwVJ8AQBQARUl+vCtbR= 5SY6+Z8LNublyIhyMREUxTEdIWGi7Xr0oCw5gBVAElUlFlEAAAkJFhABAAZAAAAQJKsSWUADGVA= SqfMm2UJPikg0y369IjJNghOqwQpBMpKLKMtIAIsBISKgAgDGuemySyh8653n6GExLOeiNUsmAy= mEmA0QlSwTG/gKtuN53fUpjanoNsRphsAFfeUWUdMOaAAABAAF+w/boemZes6tj6ZgWpu5ORXFF= FMeeZfiexe5R0/HyuOcrMvU01XMXH/i4mPPVvvP7HNl3vo2aq4+0N+Na+rcin8vcOVfL/TOCNCt= 24tWrupV075OVMdap9EeiIdc5i87tE4az69N03H+FMu3O1yaa9qKJ9G/nl9/dH8YZfDPCNGLp1d= VvK1CvyPlInbsUbTMz+zb9bUqqqqqqaqpmapneZmfGXz/AE7AnNmb9+dw9fLypx4i1abU8tOdul= cUahGk6vi0adlXelqrtb27n0dfCXL67ouocF6td4m4VsVX9Ouz29R0ynwmPPct+ifPMNPqKqqLk= V0TNNVM7xMTtt9L3flpz1+DOHb2BxPTdysjGtf5LdpjebvTpTV+LbmdLm1PfjxuPvDXj5sXP0bk= +4+73/hzWtP1/SrWpabepu2bkfrpnzxMeaXnHO/lRj8V4tzWNHt02NYt071UxHTIj0T/ALX0vGe= BeaOo6Nx/kat2YtadqORvk4lEbUUxPSJpjzS28xb9rJx7eRYriu1cpiqmqPPE+d5l6ze6ddiumf= n/AO07bd23l0TS/n9mY1/DyruLk26rV61VNNdFXjEw/dwln/BfE+nahvtFnIoqmfRG/X9j2X3VP= BmPhZOPxXgWaLcZNXk8rsx41+ar65jaP1PBZ/Y+rxr9OXYir8+nhXrc493X4b3cR6di8XcG5GDT= diLOoYv8Xcjr2e1T8Wf2xLV/M5G8e2cq5btYVi9bpqmKa4uxtVHpfXlnzo1rhLT6NKzLEalg0f5= uKqpiu3HoifQ75HukdP8Am/lfbp/F4dnHzsKqabcbiXp13cbIiKq51LznTeX/ABLwhxbw7ma3iW= 7Fm9qVq1RVTX2t6t99v2Pf+d+XZwcHQczImItWdWs11zPoiYeN8w+cuLxRd0OuzpF+xOmahRlzF= dUfHiImJiOvj1fk5vc3bXG+gWdKxdKuYvZuxcqruVxv08NtpbbmNlZNyiu5TrW9sKL1mxTVFM/h= tFr2oX9P0e5nYmBd1Cq3TFXkbVW1VUfR47vLuKuaGXf4b1KxXwPrVmmvGuUzcrp6Ub0z1no885f= 8+dU0LSbWm6xgzqVuzTFNF7tbXNo807+Ln9W90Vh5GnZNizoF+Lly1VTRNdcbRMx032nwcVHTL1= uvU0d379uirMt10+qtPSeWNU1ck9Mq2mN9Mqn9lTw73Kn6Rr39VqclwzzywtJ4Jx+H7mi37ly1j= VWZuRVTtMzv18d/O8+5S8Z08EcUfC9zDqyrdVuq3VRTO0xv54dePg36bV6mafdXw57mTbm5bmJ9= Q2ezMuzY54YmPdmIrv6VMUTM+eKqun7XQfdQcF8Sa/q2l6homn5OoW7dqq3XRZo7U0TMxPh6Ojz= XmPzQyeIeMNP4i0ixd069g26aaJmqJqmYqmfN026u96N7pC5Rh0UaroM3MiIiKq7FcbVfT1lqt4= OVj1UXaI3MfZsrybN6KrdU6h5fpnBXFmiaxp2oatw/qGFi05lqmq7etTFMTNUbRu2T5+49GXy5x= 8a5O1F3MsUVfVO8PKOYXPLF4m0CnTsfRb9m7Rk2r8VV1R2Z7FUVbdJ8+z8vMvnTZ4q4To0bE0m9= i3qb1u55WqqNo7MT1jafS6LtrLybluuunUxMtdquxZpqppq22CzIwOBOEaZ0nQ7uTbxqKLdNjEt= /Hr8I3mf27sOA+Lb/ABPcy6L3D+oaV73ppmJyY28p2t/DpHht+14xwx7om/iaTZxtY0evJyLVEU= TetVx8fbpvMTPi5SPdJadH/l7K+3T+Lzq+m5Ebiqjc/nbspy7MamKtPPPdQ/pdzd/k1j9yHl7tf= Nfiu1xpxlf16zi141Fy1bo8nXMTMdmnbzOqPqcK3VbsU01fMQ8O/VFVyZgAdTSkosooAIEosoQA= BIJPgqT4AgCgePgP0Ydrt1dqfCEKp7Y3L9GNb8nRHpnxfVFVxTO52ALCACgAkqkosogAAEhIsIA= IADIAABJCCUBGQAGyfBh4sqp8zFrqbKYAGGmzYAaXYAyY/KSjKYSYFQBJZQEhKKgAxSekPnM79W= dc+ZgxqlspSUWUYKEwBKpsztx55Y7bzD6xG0bMqYSqRJVJZtYAMn3lFlHRDngAAAQAPoFIiZnaI= mZew8p9F4t4FvYvHGTp0zo97e1kW4mfKxbnb+Mmnbwj63U+TGRwrj8bYtziujfFidrNVU/xdNzz= TX9G/wD1bnU04+RiRRTTbuWLlEbRERNNVMx/ds8Dq+dVamLU0+p+f3vV6di01x379w6TzJ4U0rm= Zwbb96ZdE3Ijy+Dk09ae1t4T9ExMx9Hj9DUPiPRdS4f1e/peq49VjJs1bVU1U9JjzVRPniW1ebh= ahy31C7qWkWbmXwvfr7WXh07zOHM/95bj+j6Y8HAe6Iy+CNX4DxtVv5Fq5n3bfa0y9YmO3X/sz/= s7+Po6+Dj6Zl12K4tx+lRV/o6s2xTcjvmdVQ1hlFnx+pPP+p9X/AAeDMPthWbmTmWbFqiaq7lcU= 0xHjMzLfHhPDvadwzpuDf/zuPi27df1xTEPBPc5csMi7mWeLtbsTbx6PjYdmuP5c/wBOY9HobH/= rfI9ay6b1yKKfen0HTceq3RNVXzLzL3TFNqeVWZN2Ina9bmn692oHn33bH+604ltU6dhcMWbkTd= uVeXv0x5oifi7/AK4lrhPj4PV6JbmjH3P3lwdSriq96er8oeUdvjvQL2p3NZqwpt35t9iLHb36b= 779qHdf+zZj/Oi590//ALc37kr+YOZP/rJ/dh1Hm1za4z4e4+1HSdMzrVvFsV7UU1WaJ2j65jdw= 13su9l12rNWtOum1Yt2aa66X5+Kfc86rg4FzJ0XWKM+5bp38jcs+Tmr6p3neXmPBnBuq8UcUVcO= 4nk8fMoprqqi/M0xT2fGPBtJyK49v8c8N3ruoW6Kc/EueTvTR0pr36xMR9TqWrcN5OL7oyi5oeb= GmXM7Tq79V2m1TVHa6xMbTEx4RBZ6jftzXauz+lEepSvEtV9tdHxLxLmRwFq/AmThWNWvY1yrLo= qro8jVMxEUzETvvH0uoy9t90jo3ENfEPDuBmalXq+VkW7lOPEWaaJj41PTamI3/AOj9mje5z1C/= p9i9qWtW8fJrmma7VFG/Zp36xv6dnpWeo0U2Ka79Ubn8OOvErquzTbj4eCu8ct+Weucd4OVl6Tk= YlujGuxari9XMTvMb9No9D1j/ALN2B84cmY/3KfwXkRw3rmFXxPpmj8Q1YVrC1ObFX+T0V+U7Mb= RVPapnbpDVkdVoqtzNir3H5bLODVFcfUj1LxrG4KyKOZtngjPyaLd+rLoxrl63Happ3iJ3iOm/i= 7Pzj5TWuAeH8XVLesVZs38mLE0TY7G29NVW++8/0XoHBvL7I1TnHq/EepazN7I0nUrcz2bcUzeq= iimeu0bRG0xHR6RzY4Gs8faFjaZfzbmJTYyYvxVRETM7U1U7df8Aecd7qdVN63qr1ERtvowt26v= Xv7NIt+sq9l4d5MYuqcecQcOVavet29K8l2bkUx2q+3TFXo+l2ufc3YG07cQ5O/8AuU/g9OrquN= TOpqcdODdneoa541vy2Tbs9rszXXFO/o3nbf6XsHHfJS1w3wRd4jo16q/Vbt01+RnG233jfbftO= A5icsdX4D1TBv371GZg3simm3fopmNp7XSmY9Oz3/nf+hPK/q1v91zZedM3LU2avUy6LGLHbXFc= e4acgPceYAAkosooAIEosoQABIJPgqT4AgHnUZUUzXVER53JW6It0RTH63wwrUxHbq/U/SOW9X3= TpABrAFgAFABJVJRZRAAAJCRYQAQAGQAAALCSjIRWJKywqlJkphAGtugAF2ACSAGlgAFJTZQWJY= kstmJpdiT0XZhX6GMkQwnxF2NmHy2IipKaRAZURvJpVojzsl2RshrkSVSVkgARX3lFlHRDRAAAA= gAC/Y3nfd7XyK5u3dEu2eHeI79VzTap7NjIq6zYn0T/ALP9363ihH0dHNlYtGTb7K26xeqtVd1L= +gkVWMrHiqmq3esXaekxMVU1RP8AfDwHnFyUycjJuaxwjT5SKt6rmDNW20+eaN+n6ujrfI/m5d4= aqt6Hr9dd/Sap2tXZnerHn/Gn6PM2e07NxNRw7eZhZFF+xdpiqiuid4mHyNdOR0y7uPj/AEl9BR= VazLftpRY5eca38unGo4dzZuTPZ6xERv8AXM7PZOVnImnCv2dV4uqtXrlE9ujDo600z/tT5/qe9= 0x06r02bMjrORdp7Y9MbXTrVuru+WFq3btWqbVummiimNqaYjpEOu8wuL9M4O4evalnXafKRTMW= LO/xrtfmiH4eY3MTQODMKa8y/TezKqZ8ljW6t6qp+n0Q1K4+4w1bjLWq9R1O78XfazZpn4lqPRE= Men9Mrya+6r1T/uuVmUWY1HuX4OKdczuItdytX1C5Nd/Ir3/3Y80R+pxXnVPS+zopiimKYj4fOz= VNU7ltP7kv+YOZ/XJ/dh4r7oD9K2sf78f3PZfcoZFi1wJmUXL9u3VOZM7VVRE+EO+avwXwJq+oX= NQ1LTcDIyrs713Kr07zP6qnynlRi51dcxuHu/R+vjU07ea+5Cwsm3oWrZtyzMWL1+mm3XMfyto6= 7T6N3atTu26vdGaVaprqmuNFuTMb9I+NV+12jUNa4T4J0DarIxMHDs0z2LNuqOv0RHnmXh3Kniq= rin3QN/W79UWrNeNdos01VbRTRERtHX2/raKorya7mRrUabN02aabcTuXqnFuFYy+dHCld6mJnH= wsm7b3/pdqiP7pl1b3T/GGu8O4+l4eh5t/Aqv1TXcv2atqpj+jv+o53cV2uGeZnCGsU3KbmPbtX= 6L8UVRPxJmmP+v6nddc0/gfmVoWPXlZGPl2Int2rtF2Ka6Jnxj/AKMbcfS+lduU7p1/zLKufqd9= FE6lwXuadb1fXuCcjK1jUcjPv05VVMXL1c1TEbR0+pnyN/8Ar3Hcf/nK/wDF27gPhfROE9Ir0/Q= 6qqseq5NczVXFXX64dM5JX7NrX+Oou3rduZ1yvbtVRHpab1dNyq5VRHqWdFM0xREvN72o5+H7qe= 9i4uXes2cnVbVF+iiram5T2Kek+nxl3/3U+rano/BWnX9Lzr+Hdr1CmiqqzX2Zmnydc7fsh5Lxd= quJpPulb+rZFyJxsbU7d2uqJ3jaKad5bE8b6BwvzA0HHxNRzoqxqbkZFquxepid9pjfrv5pl35O= rddi5VHrUbc1rddNymJ97a/8kOFOJ+NtR1DWZ4jzdOs9qm3kZNFUzcvVRETFP1RGz2fSOWepYGX= j5NXHmtX67VUVTFXhX9Exu4/lDl8N8LcQ8Q8D4ubFEY2XRcx5vXI3u01WqJnrG0TO+7lMvlzw9l= a1Vqs8T61Rcqu+V8nRqMRbid99ttvBpysqq5cn3qn7emyxappojXufv7Ye6Ms26+Wt67XTvVay8= aaJ9G96iGHO/wDQnlf1a3+6vuhcrFucscqm3kWqp99YvSK4n/v6Hw52ZOPXyWyqKL9qqv3tb2pi= uJn+S58aJ3b3+f8AptuTH6f8Gn4D7t80AAkosooAIEosoQABIJPgqT4Aj649ublyI26Q+cdZ29j= kMa35O39M+KtdyrUPrHSNo8IJVJHHvcoAMgBYABQASVSUWUQAACQkWEAEABkAAABAAjNKmMwsjC= WUMdkZ7JsisRdiRZQBSABFACFAEWBJVKvAVKvBgsyjXMs0mEZSiMmMiykwIM6Y2hjRT16voyphJ= ElUlkxRJUBA2EV95RZR0Q0QAAAIAAv2ABYHaOCuPeJuEbn/AMI1G5TYmd6rFfxrc/8ADPTf6XVx= ruW6LlPbVG4bKa6qZ3EvcLHujdeosxTe0HAu3I8avKVRv+pwfE3PfjPVrNVnDnH0uiqNp8hG9X6= qp6w8qnxRyUdLxaJ7u1vqzL1Uamp9s3KyM3Krycu/cv3q53qruVTVVM/XL4g7oiIj05dzM7kSfF= UlRnbvXrdMxbu10bzvMRVsz99ZXyi79uXxGPbH4Zd9UMrlddyZmuqqqfTVO5brrt1dqiqaZ223p= liLqE3Mv36PbjUNbwcXLvVzau36LdczV1imaoierZmnkly7p2mM27TPjvGX/wBWq8TMTExMxMTv= EvvObm7/AOmZHp/zk/i4cvEuXpjsr7YdWPkU2991O5blafc4P5Y8JX7VvVLNGPRVVd2uX+3crqm= PCI3mZ8PM1A4g1i/qmv6jqdFVyz78yrl+aIqnp2qpnb9W+z8F7Iv3Y2u3rlcR1iK65nZ8mGF06M= eqaqp3MssjLm9EREaiFrqqrmaqqpmZ6zM9d1t3blure3XVRP0TsxR6HbTMamPhybmGVVddVfbqr= ma/HeZ67s6cnIppimm9ciI8I7XR8gmIn5haZmPUS+lzIv3KezXdrqp9E1dEuXr1dHYru11UxMdK= p3YJPgvbETs7qvykgKnr7AAJKLKKACBKLKEAASCT4KtFFVdcUx13CZ17fbCtdqrtz4Q/cxooiii= KI8zJXHcq7pElUGtABkALAAKACSqSiyiAAASEiwgAgAMgAAAIElWKSygAYaZwAGlRJUNLLEXZNl= 0gAml2AIuwBJUY1z02ZT4PnV47pMsqYQBgzJRZRFgTbdWVMLEbSSI2hQZ60mxJVJUQAAAH2lHJz= oeq/JZ+3T+KfAWq/JZ+3T+LXGZY5QkY13i40cl8Bap8ln7dP4nwFqvyWft0/ieZY5QeNd4uNHJf= AWqfJf8A30/ifAWqfJf/AH0/inmWOUL413i40cl8Bap8ln7dP4nwHqnyWft0/ivmWOUL413i40c= l8Bar8ln7dP4nwFqnyWft0/ieZY5QRj3eLjRyXwFqnyWft0/ifAeqfJZ+3T+J5ljlDLx7vFxko5= OdC1T5JP26fxPgLVPkk/bp/E8yxyhjOPd4uMHJ/AWqfJJ+3T+J8Bap8k/99P4nmWOSxj3eLjEly= k6FqvySft0/inwDqvySft0/ieZY5QvjXOLjByfwDqvySft0/ifAOq/JJ+3T+KeZY5QePc4uMHJ/= AOq/JJ+3T+J8A6r8kn7dP4nmWOUHj3eMuMSXKfAOq/JJ+3T+KToOq7/6JP26fxPMscoPGu8XFjl= PgDVvkk/bp/E+ANW+ST9un8V8yxyg8e5xcXKOUnQdW+ST9un8U+ANW+ST9un8TzLHKDx7vFxg5P= 4A1b5JP26fxPgDVvkk/bp/E8yxygjHucXGJLlPgDVvkk/bp/EnQNW+ST9un8TzLHKF8e5xcUOU+= ANX+Rz9un8T4A1f5HP26fxPMscoPHucXFjlPgDV/kc/bp/E+ANX+Rz9un8TzLHKDx7n4cVKOV/g= /q8/+Dn7dP4n8HtY+Rz9un8TzLHKDx7nFxQ5X+D2sfI5+3T+J/B7WPkc/bp/E8yxyg8e5xcUjlv= 4Pav8in7dP4p/B7V/kc/bp/E8yxyg8e5xcUOV/g9q+/8Aoc/bp/FynD/L3jDX67tOk6LcyZtRHb= mLtFMRv9MzCTm2OUHj3OLqz92Fa7NPbq8Z8HdrXJfmR5SO3w1ciP6zZ/O/b3Qcw46fwcufeLX5k= jPxucNV3Hva9Uy6HI75PKDmJP8A5cufebX507oOYvzcufebP5jz8bnDn8S/r9WXREd87oOYvzcr= +82vzHdBzF+blf3mz+c8/G5weJf4y6EO+dz/ADF+blf3mz+c7n+Yvzcr+82fznn43OF8S9xl0Md= 87n+Yvzcr+82fznc/zF+blz7zZ/OsZ+Nzg8O/xl0Md87n+YvzcufebP5zuf5i/Nyv7zZ/Ov8AaG= Nzg8S/xl0Md87n+Yvzcr+82fznc/zF+blz7zZ/Onn43OFjEvcZdClHfZ5P8xfm5c+82fznc/zG+= blf3mz+dPPxucHiXuMuhDvvc/zG+blf3mz+c7n+Y3zcufebP5zz8bnC+Je4y6EO+9z/ADG+bdz7= zZ/Odz/Mb5t3PvNn855+Nzg8S9xl0Ed9nk9zG+bdf3mz+dO57mN827n3mz+c8/G5weJe4y6GO+d= z3Mb5t3PvNn869z3Mb5t3PvNn855+NzhfFvcZdCHfO57mN827n3mz+de57mN827n3mz+c8/G5we= Le4y6EO+9z3Mb5t3PvNn86Vcn+Y0R14bufebP5zz8bnB4l7jLoUo753P8AMb5uXPvNn853P8xvm= 5X95s/nPPxucM4xbvGXQpWHe55Qcxfm5c+82fzndBzF+blf3mz+dPOx+cL4t3jLog753Qcxfm5X= 95s/nO6DmL83Ln3mz+dPOxucL413jLoWw753Qcxfm5X95s/nJ5QcxPm5X95s/nXzsfnB413jLoY= 733P8xfm5c+82fzndBzF+blz7zZ/OnnY3ODxrvF0PZNnfe6DmL83K/vNn853Qcxfm5X95s/nPOx= +cL413jLoQ75PKDmL83Ln3mz+dO6DmJ83bn3mz+c87Hn/PB413jLog733Q8xPm7c+82fzpVyi5h= 0xvPDte39ZtfmSc3H5QsY13i6HVLGfB3meU3MH5vV/eLX5k7peYPzer+8WvzMZy7HKGcY9zi6MO= 8d03MH5vV/eLX5jum5gfN6v7xa/Mnl2OUMvoXOMujju/dNzA+b1f3i1+Ze6bmB836/vFr8x5djl= B9C5xdGiOrOno71HKHmHMb/wdr6/+otfmXuh5h/Ny595s/nZRmY8f5oYzYucZdFTZ3vuh5ifNy5= 95s/nO6LmH83a/vNn86+Zj8oTx7vGXREl3zui5h/N2v7za/OxnlFzE+btf3mz+ZPMx+UL49zi6I= O990PMT5u1/ebX5jui5ifNyv7za/MeZj8oXx7nF0Qd77ouYnzcr+82vzB5ljlB49zi5UB8G+oAA= AAADcgAbkADcgAbkAOvok3IAG5AA3IAG5AA3Ie09oG5AA3IAG5AA3IAG5AAAAAA3IAA+uLYu5OT= axrNM13LtcUURHnmZ6NmOXnDtrhvhyxh9mn3zXHlMiuI/lVT/ANNnnPIrhWMnIniPMtb27UzTjR= VHSavCZ/V1e0Rvuou0G0AAbAAABsbAAABsbAAAAAAAAAAAAAAAA+Vyd5+hnXO0PmDEZJsCbQxmG= QDGFWU2BNkZAMRZhATZGQDEmF2AYTGz8eRX2qto8IfryKuzR08ZfimkGExEsZjqzmEBgSymEmA0= w2fTHt9qvfzQx8+3nfus0RRRt6fEGW3RJZTCAxGUxCGxJhFDYxmEZ7JJsYi7BsarAMQAAAAABna= tXbszFq3XcmmJmezTM7RHnXyN7yPlvJV+S37Pb7M9nf0buW4Jz40/iPGrrn+JvT73u+iaa/iz+y= XffemFcuVcC+VtdmLfvqLu8RHlYqnpv/u9kHl13GybVFNd3Hu0U1fyZqomIn6icXJi9Fmce95SY= 3ijsT2pj6npeHl4fFGpatgXLlFGLiZFOViRM9It2527Mf8ADMrl6liZmkZPF1qq3RlYtq5g0UxP= +tMz2KtvoiafYo8z965Plos+973lZjeKOxPamPqYeSu9iqvyVfYonaqrsztTP0vS9Nz7FrRMTjC= 7XRXlWbHvKaap6zXvExVt/uxW/PxTptMY+No+kXLNVzWsj351riIimrrFMz5tpB59j42Rk1TTj2= Lt6qOsxbomqf2P02sO3Tj5fvujMtX7VMTTRFjenrMR8eZmOzHX0S7do2PqFHCGTp2i1xTq9rMqj= Kps1fxtVvaOz2Z8dt+14Mpp1S1w5xFa1q9TXlRhWY2mae3H8bb2iraN9/rB0mzg5t615W1h5Fy3= H+vTamY9sJYxMq/G9jGvXY32+Jbmrr6Oj1f4t63pWRpFrVLmHbs0x/kuTbt2Kaoj43biaJ8+/jL= gtR1ScbhPWb+lTTiU39Voppi1cirs0zTXPxao+qOsA6Fdx79q75G5ZuUXfDsVUzE7/U/Tb0+/by= LUZ2Lm2LVdW01RYmZ2+iJ23l3+xk4tzUdBy825Z9+XtKuRbvXtpjy0VV025q+npT4vwYtjizG1G= xVrN+5TjVZVPS/VE9qevWnfrt9WwOmVYV27mXrWFYyr9NFcxH8TPb2jwmYjfafofKcfIpv+QqsX= Ivb7eT7M9rf6vF6DgYN2/l67k42RqNyv3/VTVj4FdNFzbtT8aapiejk9R8hb4ooixXbt6je0mPe= 1y/VTVPlu1XHWdojtdIjfbzIOj6ToXb0bWcrPxsmzdxMaLlntUzRvPbpp6xMdeky4vPxbNF2zbw= /fdya6ImYu2exPanximImd4+l3vEx+I8bgjiKNduXIoqx6fJ0ZFW9yZ8pR1jfrs+tm7Zp4hxYi7= Zt5lWk004ldzaaabvY+L49N99tt1Hnd3AzrNM1XcLJtxEbzNVqqNo9Pg5TB4evapft2dKpya5jG= m9dm/YmmmJijtTFMxvvvt08N+jteBj8T2OF+Ivhuq95GcSezF+d65ntR1pmfM/TpeXdt69pWPZy= q6PK6LVTTTTcmIqrmxPZj699tgeb04GdVfrsU4eRVdo/lURamZj642cvwpptrIr1S3nY89uxh1X= Kaa42mmqKqY8P1uxaDpWqe8My9lX9YuZcZXYvY2Lcim9G0RMVVVzEzt18Poclq1NujiHUaon41e= iUTVVNUVTVV8XfeYiImfp2NDyyImZimImZ9EPvewc2zb8rew8i3R/SrtTEe2Ydl4Q06NN1nSdR1= ScWnGy4qmxNdUVRFUTMR2o83WHOada1/FydUv8TXqqtLqtVxV5aqJouT/q+T/wCgPPacLMqteVp= xL9VvbtduLczG3p3ZU6fn1Wou04WTVbnwqi1VtP69nbdW1K7Y0XhfFnJrow6rc1ZFNFW3ap8pMT= E7ebbzObt2OKLvGljKwb01aTM0+Srpqj3vFvbw28N/2oPMK6aqK5orpmmqmdpiY2mJYuV4w/nVq= nX/AMVc/elxQAAAAAADl+EdFv6/r2Pp1imfj1b3Ko/1afPMuI2326b+hsByZ4YjRtDjUMq3tm5k= RVPajaaKPNCju2kYGPpmnWcHFtxRZs0RRTH1ed+ogUAAAAAAAAAAAAAAAAAAAAAAAAAY1z02BKt= qpYKoMRlMQxATZQGIylNgTZJhQERdjYE2TzsgGKTttvPmZbPjfr2jswD4XKu1Xv5mDI2BhMMZpf= TZAfKY2R9Zphj2O1O0Azxrfaq7c+EP0lFMU0xEKCJK7EgmyMkBJhjMMgGJKzCAbAA1UAYgAAAAA= Au8oAAAebbzLvPpQAABd59KAC7ybygCxMx5zdAF3n6Zh+3Rr+n2c2KtTxasrHmJiqmivs1U7x4x= 9MPwgOyV6vo2Do+bh6PYzar+ZEUXb2T2Y7NH9GIiZ+j2OtgC7z6ZTzbAATIAyoqiLlM109qmJiZ= p38Y+t2fE1PhXEz7epY+BqMX7VMTTj1TT5Lt+nfffb9TqwD7Z2TdzMy9lXp3uXq5rr+uZ3l8QAA= AAAB+jT8S9nZtnDx6Jru3q4ppiPpB2/lDwvOvcQU5ORb3wcSqK7noqqjrFP9zYiimKaYpiIiIja= HB8E6BY4d4fx9PtU73Ip7V6vz1Vz1mXOsgAAAAAAAAAAAAAAAAAAAAAAAAAAYyylAY7JMMtk2Bi= LsAmyKs9QYizCAmwoDEXZAJhFAY1T2aZl+Wqe1VMvrfneezD5TAMdkmGR4gwJhkkgx2fbHo6dqW= Fumaqtn6YjaNgSYYzDMBgMphiBMIoCIuwDEZJMAgbSA8f7nNb9YYnsk7nNb9YYnsl7nsbA8M7nN= b9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsb= A8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYn= sl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7n= Nb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9Y= Ynsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M= 7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7= nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7m9b9YYnsl2vlty5r4e1SvUdSu2si9RG1jsx0o38Z+= v8XpGxsAAAAAAAAAAAAAAAAAAAAAAAAAAABMAgAAAJsksgTbCYJhlMIKgTCAbIyTbcECY2ASYY1= z2aZZvhdmapB8/HxRlt0TYGMwjNPEGBtv5mUwyt071byDO1R2ad/OymFAYjLZNgQ2gAYzCMyY3B= gLMSgJsKAx3F2AciAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAkwoCCpMAAAACaSYRkCsJhGe3oQGJKzCT0gGFydofNlVO89WOwJMMdpZoDDZGcwm2wM= fHo+1NO0bedhap876gxmBkkwCAAbJMKCMRlMJsKhMQAMZhGaTAMRdpAfvAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAATZQEF2SYAAARQRNnzuTt0= fSqdofGeorFNmUwAxSWWxMAwNt2UsqI2A22joKAgTACGygMRSYBAANkUEYi7AqBuA/aAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAmygILsx= r6QDCud+jHZQGJMLsAxFNgSI3VYhQYi7AITAAmwoCBMAIbKAxGW26TAIC0x2p2jzgm30SP000xE= RGwDIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAACYAYVdWUpMAwmEZpMAxFmEBNiI6qyjbYGIsx6EAABJhGQDEXZNgCYAEFJgEABJfWzRtHa= lhRT2p28z9EdIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAABJAkARJhGSBtEmGWyCsRlMJMAIAEwjI6SDEWY2QA23AEmEZEgxF2QBNlZ2= 43ncGVqnan6ZZgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAABKLKAAAAAAAmyMkESYTZlsgrEZbJMAHSUAJjZGW5MAxCYAElQE26vtRG0M= Lcb9X0AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAA2RQECYQFAAAARQRjsMk2F2xmBlMIDEXZAVJgATYpiZnZkyop26gyiNoAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAABJgU2BAAAAAAEmFBGIyTYVjMCgFMbyzSmNoUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAkAQU2BAAAAABAiOoo= QACgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAABsAJIqTAmwAUiFAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADY2AAAAAAAAAA= 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= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEAmTdwfGvE+m8I6LVq+rTd= jGprponydHaneqdo6Py8I8c8M8VTVRo2o0Xr1NPaqsz0riPTMM4tVzT3RHprm9RFXbM+3Zt4O1D= UbVuZ3GfD3HWsWsPVq7mNa1HIiMe9TFVExFyqIj07R9EtgeS3GGbxtwfOrZ+PZs36MiuxXFreKZ= mmKZ3iJmf6TsyenXce3FyZjUuPG6jbyLk24idw7xvC7uK4p1ixw/w9m6zlUTXaxLc1zTE7b+aI3= +mZhq3pmpczuZuvZ1/Q9Qybdq3VNUURe8nRapmelO8R1nZwPQbc7m7XrhXhfmrw1VqWq6xrVFqx= Rg1xRcuZnbpormqnaZiY2jwnq7dyH4j1TL4V1bUeKuI8TUIx8mIpv03KZotUdiJ2maYjz9QerwO= lV80+Aqb1NqOJcGuqZiI7Ne/X0Ms7mhwNhZl7EyuIMS3es1zbuUzV4VRO0wDuZu4Thnizh7iSi7= Vouq4+Z5L/ADkW695p+txuqcyOCNNybmNmcR4NF63V2arflImYkHbImN9l3eF8zuN9Ty+JuH73C= HF+DiaZlWo8pTXdojys+VmmZjemfRs9BzuZPBulZVen6lr2LazLG1N6iausVbdQdzHBcMcW8O8S= +UjRNWxs2q3G9dNureafrc6AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAigPK/dRfouv/1i1+9DyT3K0/8AzNu/2dd/eoet+6= i/Rdf/AKxa/eh5J7lb9Jt3+zrv79D38Wf7trfN5cf3jQ6Dx9/PnX/7SyP+bU2P9yf+jTI/tK7+5= ba4cffz61/+0sj/AJlTY/3J/wCjTI/tK7+5bdnVf2Gn+Tl6T+31fzdm58WLuRyl161ZiZrmzRO0= eiLlEz+yHl/uRtW02xi6xp2RkWbOVN2m9EXKop7VMxEdN/HrEtgM/FsZuHew8mjylm9bm3XTPnp= mNpeA677nfJjU7t/QNfixj1zNVNuuiYqtx6N4nr+x8o+uesczcrFv8vtbt2MmxcqjFmdqK4mdt4= 9DUuznZNnlLfwrVVVFjJ1mPKxHSKtrUTEe2N3tPCHJLXNMyM6c/iGi5ayMKuxERFVW1UzTMTMTP= 0P3cOcj6LfAeo8N6zqNFV2/lRkY+Rap38lVFMR4T4+APFOGMKJsYU3eXGdqEzXTPvuKsmKa438Y= in4uzsXD3DGkcS8/dZ0XVLNyvCnOyfi03JomNqqtusfU7jg8lOM8Cu1axOMIpx7VUdmiIqp6RPo= 3l2rg3lZn6NzRz+L8rVbV23fvXblFumj40zXM+M+bxB4hgVXOE+P+KMPQ7l2xbx8DKpt/HmeztR= 0mZ8+ztHufuXHC/Gmi6hn675XJv2r0URbovTR2InfrO0+fZ6FpvKK5a5l6nxDnZtnI07Ot3bddj= s7VTFdMRMOqZ/ufNWx8+9Oh8TTaxa6t4pmKqaojzRO09frBwHPPh3S+FuM+E9I0i3XaxLViJopr= rmqYmb9Uz1n6Zfg5gajwvqXG+bZ0zgnJ1nN7UVXq4yb29yqKYiaoponpHh5nfMnkhrOVPD3vjXr= VdWm0zTerqpmqat71VfTefRL6cT8jdSucT39Y4c4gjCi/G9VNVMxVTPniJjxjoDzvkPdvYvO7Bs= UYN3S6LvlqbmJXNe9MRbqmKZ7XXpMR4+ht3Hg8P5dcndc4e4/wuJtS1qxl+QmubkRE9qrtUVU/3= y9wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAABAeWe6i/Rdf8A6xa/eh5J7lb9Jt3+zrv79D1r3UX6Lr/9YtfvQ8l9yt15nXf= 7Ou/vUPfxf8NrfN5f+I0Og8ffz61/+0sj/mVNj/cn/o0yP7Su/uW2uHH38+tf/tLI/wCZU2P9yf= 05aZH9pXf3Lbs6r+w0/wAv9nL0n9vq/m9d2jdqjrvGPMjVOZGo6HoWr5NdyMmuizZoppiIpjzR0= bXQ1Y5df/crkf1m8+UfXPzZvHPNjgTWMWeIb+R2L29UWci3TNN2mNt9p2+mPB6JxfzK1yrV+FMj= QM/TcfB1OxauX7ORcoiZmbm1URv16dY6Pxe68yMP4E0rFqronLm9NUU7/Gijbr+2YeT6hbvWsXl= /Tf37U26pjf8AozlVTH7NgbeapxBo+kY1q9rGqYeDFdO+967FMT9W/mcZZ494Qy65x9O4n0fJy6= qaptW6cqme1MRvt0nwa5abpt3mfzmv6drWfet2KLc9mInfs0UbbUU+jxmXy1HhnC4S54WdDwK7l= zHtUdqmbnjPatTIPUOAOY2rX73Et3ijXdJt4uHERjVUXbe1FU1VRETt9UeLivc/8yLuVl6pY4t4= lsUzVcojEpya6aJqmZmNqfDfzOm8n+HMDii7xppuoeUizFNF6OxO09qm5XMJ7nzgfReKNQ1DJ1W= q9T8G3Ldy12K9vCZnr7AbF5HMDgjGyLuPf4r0e1dt1TRXRVlUxNNUTtMTG7j+YHE2Pc5X65rXDe= rWL9dnGmq1fx7kVxTVvH6mu3GF3l/e4s1SjB0TW8+v3zcqu3LdzpNU1TM7RE+G+7iuBNSv4+l8Y= 6RaiacTJ0m5cqpu0fHiaK6ez9X8qQbA+5r4j1niThHLyNazq8u7ayezRVVERMRtM7dIeqvFPcj/= AMydQ/rf+EvatwUIAAAAAE36+Kz4Ohc3eMK+HtOt4eBdinUMid4n+hRHn/uB30a2d43F3rWv2He= Nxd61r9ibGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8b= i71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcX= eta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71= rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta= /YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7= DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/Yb= GyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2= TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY= 1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGt= neNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7= xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneN= xd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9gbGyYCgAAnnVCR5X7qL9= F1/8ArNn9+Hj3uYsvGwuZVy5lX7diidPu0xVXVtG/ao6Npdf0XTddwKsDVcS3lY1UxVNFcbxvHg= 65PK7gaY68PYn6qHqY2bboxqrFUT7eRk4Ny5k03qfs1v434A4qyeK9WzsLTJzLGRnXrtuqxXFW9= NVczE+Pol23lJxxnct9Oq0DiPhzOtYt3IqvTfpp3miZimJ6bdfCPPD1zuq4MoqicbT8jDnfffGy= rlrr/wAMw+lXL6zat3KMHXdYtRXG3Zv5NWTRH/DcmYdFzqVu7ai1cjcf0/7c9vplyzc+rROp/q5= 3hjibROJMOMrR9QtZNHnimfjUz6Jhr7xPyW4+y+L9Q1fTbuDZov36rlquMyaK4ifqjo9Qs8rox9= Tq1HC1KMHOpo/i8zEtRZqmd4nau3TEW6qZ+mHduH6tapxpsa1bs1X7c7RkWpjs3Y9PZ8Yn0vJu0= UR+pO4evZrr1q5HtrzpHIXjHUtTsXOJ9Ws+96Ko7dUX6r1cx6I38N3ceaHKrWNX4k4bvcO28SjT= tKsW7VUXb3Zq2pr36Rt16fte1UrLS6GsHNjhXTNI44r1PQOMtN0nUuzTVexr96bdVu5t1mKojwn= p02dQ4Qt6pqfNvBt5WpWdXzLkzTOTZuduir+Lq8+0eDYvjLlFwpxTrt3WNRt5MZN2mIrmi7VETt= 9G79vBXLHhLhLUJz9JwKqcrsdmLt25VXNPTrtvPTf6DY6lyW5ca9wrrPEGRrnvX3vqNEUWvI3e3= P8AKqnr0jbpMOoaZyh5icP67dq0PV8S3p12/E3q4vdiqu3v13jaeu0y9e5wcRX+HuDr9eDTdq1D= L/yfEm3403KukVfqeSXNe43wOHMvSNLsaxqV7IibVzIrsX7ldmumY7XYmYmYid+u/h02ddnDqvU= 929OK/m02au3W3yzeTfHml8RZubwtquD5LKuVVRVXXFNUUVVTMRMTE77b+L58P8meO8e7rd7UKt= Nru5+nXcemqMjfe5VVRMb/ABekdJYcAZXMXBz7tdWBxHN6MWum3XmW7k0WoimfNX8Wdp+NEeM+E= dXO4nMDmRbzsjU6uDtRrpu2KbU2qse/NEVUTO1dNMR07Xanf6oba+nV0zMRVE/zaaOpU1REzTMT= /B3XkFwdq/BnDWXgazONN67kdunyFztxtt6doek+Z03lLa1P+C3vvVrWZZzM3Ju5FdrI33t9uqa= opiJ/kxG/g7jEdHDco7app/D0LdffTFX5WAGLMAAAkH5NY1HG0rTb2fl1xRZs0zVM+n6Gr/FWs5= Gva5kajkz1uVT2Kd+lNPmiHf8AnnxVTl5UcOYdc+SsTFWTMeFVXjEfTt0eVpIAIAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAANwAGQAAAAAAAAAA= AAAA/BrOlafrGHVhanh2srHqneaLkdN4Z6VpuDpeJRiYGNbx7FHSmimOkP1yQRVOtbY9sb3o2jw= mOhERttsoMtAAAAAADrPMfiS3w1w5dyoqj31c/i8emfPVPn/VG8uyVTtEz6I3a4c1eI7uv8TXqY= 7VOLi1Tbs0+naf5X1ySOqZF65kX7l+7V2rlyqa66p88z4vmDEAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAf/Z" width=3D"819" height= =3D"1119" alt=3D"Imagen que contiene Interfaz de usuario gr=C3=A1fica &= #xA;Descripci=C3=B3n generada autom=C3=A1ticamente" style=3D"margin-top:-34= .7pt; margin-left:-87.3pt; position:absolute" /><img src=3D"data:i= mage/png;base64,iVBORw0KGgoAAAANSUhEUgAAAUIAAAAzCAYAAADipAFMAAAABHNCSVQICAg= IfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAABjBJREFUeJzt3VuoVFUcx/H/7gZB51UIfJLywc= AH41AQQg+JhISIJRKGkiARJlSUKXkpyVSKSsw0y0S7iFQGXtLECi0viRZU3vJSKpVySk0953jUv= j2s/+A6a/bM3nO80+8DMrPXfQbO3zVrX5aZiIiIiIiIiIiIiIiIiIiIiIiIiIiIiNQHbKGzdk+/= H9gKnAJagXXAaODdpH7NcsALUbutwNCk7sKk73klxtsP2Aa0ASeAZTXKdQNmA7uAY8CaKG8FcNL= HvKor7Sd1RgA/eXungQPApKRMvT7L1D9AtQlFYxOREoAm4GX/w9oI9PD0XcCvwEhgAPAGcAR4L6= lfWM7zAPYCTUn9wcDfwMCS492VExAWJGUGAfs972fgdaDZ8z7z9FnAO/5+WSPtJ331BP4CzgDPA= 48A/xACab+iPkvWH5UzpsNlvi8RKQkY6H9cn0ZpHcDspNxjwPwkrbCcB8IfCTOipTn97yw5zmeB= NUBfYBph9kRcH+hDCMTngLlJ/W6EWRdAd6DZ37d6XmH7OWMa52VO4EGeMEOGMCMu6rNufT9eC0w= t8x2JSBfVCIQ7gIPAQwV1C8t5INwATPfA+WSSXzYQ9k+Ov/Nxb4vS1nnaNzn1x3re2SitYnyZ9n= PaHB61scrTdhOCft8SfRbVbwKO+/d2BPgWGFXm+xKRBtQIhPcQ1sragVVA3xp1C8tVAqG/Xw0cB= npF+TuT8ouAFqBnwbgr65uz/LjZxwHwB2FG1wK85vnzPe9M1Ma/nja/qP0649gWBbND/vlGl+2z= oP4rVDtDslYrIhcoLxBGeZMIM75TwOI6bdQslwTCJsJa4foov9SMMKfPFmB/dDwtChbDgbf9fQd= h7W1J5TiqUwlKS4rarzOOZkLgjQPVm55X2Ge9+p7fB3gC+AQ4GpWpO1sXkQbUC4RRmYWEdbfVBW= 1VlYsDoR8PIpwQmOHHDQdCwomHE8CQKG2Rf45zUdpxT1vM+bPUcVCqSE8CVbVfZyxPEWZ1j0cBr= QMYUqbPevVz+moG9nmZqlmsiHRRXiAkf4a0nvBzs6mRcmkg9LSphMta+jcaCAlnp1uAsUn6vCjI= 9Pe0g368Apjo7894XlNUflyJ9rfSWYd/tg5ga1S3zfM/LOqzqH6Nzz/G82fn5YtIcN1FaKOZ6jW= 6Fn+9uQvlOsmybLyZbTCzVxsZFNDNzGaY2Zwsy6YTzsR+DIwws7VmRmVcSdV9Zva+mbWZ2Q2ENc= rbPa/NzBYVtZ9l2Z1ZZzeZ2X1mdqOZXe+fa4WZHfR2T5bos6h+nq/NrN3MPij1pYlIMeAln2FsA= Hp72gnCWt5zhDWqKYSfsxuTuoXlgJmEM6G9k7pNwC80cE0c8CXVWqP8zZ62jbBO2E4421q5PnKZ= 578FzPX3K8q2nzOeZwhLAa2En7ijCeukR4F7i/osqk9Y92z372k6cDfwOTCn7HcmIgWofWfJEv8= j3EdYmD9GuJ6tV1K/bjngh6T99BKVB4A9SdpHhJ+mzUn6PPLtjcr0AL4iXH7SAWyn8zpiE/CFB5= 5WYHkj7df4DmcBv3t/pwh3iTxaps+i+sAwwn80p/3fHmByvfGIyDUIv4NCRERERERERERERERER= ERERERERERE5LLi/GOdKlYm+aeivIUl2utHuAXs+KUbtYjIRcT5zZfw28B6JPkj/Ha1BUD3Eu0t= Jdxqd7aorIjIVYPwSPh2op3eorxewOYG21ukQCgiV1pDj+HKsmy9mW0xs7vSGaGZPW1mdR/GmqO= 9wfIiIlce4ZFV56jetzhvE6T+/nO6zZ+Ish14OMqfpxmhiFyT/PFPh6LjMSRPSfZHSh0ANhGepj= yWsC/xkcoaogKhiFyzgAl+0mSiH6+h+pmA073MgChtpqdVdpNTIBSRK65Lj+rPsmyKmR0yswc9A= J7LsmxLUuw2f+2I0pb5661d6VdE5FK4kD1LVprZHWb2opnl7WpX2U9jcJR2i792aVtOEZGrCtDN= L7LeXSf/T8I2mZMJ+2psAn6Lyiwn7N077PKNXETkIvKLomfWyR8K7PA9NtoIGyVVts9cnNypMtL= PMH9/+T6BiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiMj/1n9FrJHJxu4OqwAAAABJRU5Erk= Jggg=3D=3D" width=3D"322" height=3D"51" alt=3D"" style=3D"margin-top:-9.2pt= ; margin-left:258.45pt; position:absolute" /> = </div> = ;En la tabla 3 muestra las medias y desviaci=C3=B3n est=C3=A1ndar d= e las preguntas realizadas a los 19 estudiantes. Referente a la pregunta (L= e gusta la materia de historia) se visualiza una M =3D 1.32 y DS =3D 0.47, = demuestra que la mayor=C3=ADa de los estudiantes si les gusta la materia, y= su desviaci=C3=B3n est=C3=A1ndar baja indica una constancia considerable e= n las respuestas. Para la pregunta (M=C3=A9todos de evaluaci=C3=B3n preferi= dos) indica la M =3D 2.11 y DS =3D 0.93, muestra la preferencia por los m= =C3=A9todos de evaluaci=C3=B3n escritos del 47.4 % y proyectos con el 36.8%= , en la desviaci=C3=B3n indica una variedad considerable en las preferencia= s. Seguidamente en la pregunta (Nivel de comprensi=C3=B3n lectora) refleja = la M =3D 1.74 y DS =3D 0.73, los estudiantes indican que su nivel de compre= nsi=C3=B3n va de =E2=80=9Cbueno=E2=80=9D a =E2=80=9Cmuy bueno=E2=80=9D, la = desviaci=C3=B3n presenta algunas diferencias en la autopercepci=C3=B3n de l= a habilidad lectora, pero en general hay consenso en que, es adecuada.</spa= n> En tanto, para la pregunta (motivaci=C3=B3n para profundizar en = historia) muestra la M =3D 1.05 y DS =3D 0.22, la media es cercana a 1 indi= cando que, casi todos los estudiantes est=C3=A1n motivamos y su desviaci=C3= =B3n extremadamente baja refuerza la opini=C3=B3n casi un=C3=A1nime. En la = pregunta (Opini=C3=B3n sobre la importancia de aprender historia) la M =3D = 1.16 y DS =3D 0.37, la media que la mayor=C3=ADa considera que aprender his= toria es esencial, y su desviaci=C3=B3n indica que la mayor=C3=ADa de los e= studiantes est=C3=A1n de acuerdo con la importancia de esta materia en la e= ducaci=C3=B3n. Por otro lado, la pregunta (= Frecuencia de navegaci=C3=B3n en internet para investigar temas hist=C3=B3r= icos) la M =3D 2.11 y DS =3D 0.73, con una media muestra una tendencia a in= vestigar temas hist=C3=B3ricos con una frecuencia moderada, mientras que, l= a desviaci=C3=B3n indica una dispersi=C3=B3n considerable en la frecuencia = de uso de internet, con algunos estudiantes que lo hacen frecuentemente y o= tros que nunca lo hacen. En la pregunta (Participaci=C3=B3n en el aula inve= rtida anteriormente) la media de 1.47 refleja que m=C3=A1s de la mitad de l= os estudiantes han participado en aulas invertidas. Seguidamente la pregunt= a (Efectividad del modelo de aula invertida) la media de 2.26 refleja que e= s =E2=80=9Cefectivo=E2=80=9D este m=C3=A9todo, aunque no necesariamente =E2= =80=9Cmuy efectivo=E2=80=9D, la desviaci=C3=B3n alta indica la considerable= variedad de opiniones entre s=C3=AD y otros que no.En relaci=C3=B3n con la pregunta (Claridad de los materiales previ= os en el aula invertida) la M =3D 2.26 y DS =3D 0.99, las estudiantes menci= onan que son =E2=80=9Cclaro la mayor=C3=ADa de las veces=E2=80=9D, su desvi= aci=C3=B3n muestra la claridad de los materiales es un tema con opiniones d= ivididas, encontr=C3=A1ndolos m=C3=A1s claros que otros. La antepen=C3=BAlt= ima pregunta (Impacto de los conceptos previos en las actividades de clase)= la media de 1.79 indica que a la mayor=C3=ADa les ayuda. En la =C3=BAltima= pregunta (Oportunidad de interactuar m=C3=A1s con el profesor en el aula i= nvertida) la media de refleja que la mayor parte de los estudiantes tienen = m=C3=A1s oportunidad de interactuar.<ol start=3D"4" style=3D"mar= gin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left= :31.25pt; text-align:justify; line-height:115%; padding-left:4.75pt; font-f= amily:'Times New Roman'; font-weight:bold">Discusi=C3=B3n </li= ></ol>El objetivo de la presente investigaci=C3=B3n fu= e determinar la influencia del m=C3=A9todo de aula invertida en el aprendiz= aje de historia en los estudiantes de primero de bachillerato de la = Un= idad Educativa Combatientes de Tapi, tras el an=C3=A1lisis de los resultados, se refleja la signi= ficancia del aula invertida ya que, fomenta la participaci=C3=B3n activa de= los estudiantes, quienes, al tener acceso previo al contenido te=C3=B3rico= , logran un mayor entendimiento de los temas hist=C3=B3ricos abordados. El = estudio de Clavijo-Cortes et </span= >al. (2024) sobre el fortalec= imiento del aprendizaje con la metodolog=C3=ADa del aula invertida, se cent= r=C3=B3 en responder como el m=C3=A9todo puede fortalecer el aprendizaje si= gnificativo, destacando su capacidad para innovar y dinamizar la ense=C3=B1= anza tradicional mediante herramientas tecnol=C3=B3gicas, los resultados co= ncluyen <= span style=3D"font-family:'Times New Roman'">que el aula invertida tiene el= potencial de fortalecer su instrucci=C3=B3n, permite a los estudiantes inv= olucrarse en el proceso educativo y desarrollar competencias profundas en l= a materia. </spa= n>Por otro lado la investigaci=C3=B3n de la implem= entaci=C3=B3n del aula invertida como enfoque pedag=C3=B3gico en la materia= de historia, tuvo como objetivo mejorar el proceso de ense=C3=B1anza-apren= dizaje a trav=C3=A9s de esta metodolog=C3=ADa. El estudio combina el an=C3= =A1lisis sistem=C3=A1tico de fuentes bibliogr=C3=A1ficas con un estudio de = campo comparativo, evaluando el m=C3=A9todo tradicional frente a la clase i= nvertido. Los resultados se=C3=B1alan que el aula invertida promueve aprend= izajes m=C3=A1s significativos, aumenta el inter=C3=A9s estudiantil y hace = que el estudio de historia sea m=C3=A1s din=C3=A1mico (Guerra<= span style=3D"font-family:'Times New Roman'"> et al., 2024). A comparaci=C3=B3n con el presente estudio, se demues= tra que las metodolog=C3=ADas innovadoras como es el aula invertida tienen = el potencial de transformar positivamente la educaci=C3=B3n, de manera que,= incrementa la calidad de aprendizaje como la participaci=C3=B3n de los est= udiantes.<span= style=3D"font-family:'Times New Roman'">En contraste el estudio del enfoqu= e de aula invertida como estrategia en la ense=C3=B1anza de la ciencias soc= iales en bachillerato, esta investigaci=C3=B3n es de car=C3=A1cter descript= ivo, con un dise=C3=B1o de campo y modalidad de proyecto factible, lo que, = se traduce en analizar la realidad educativa y proponer una soluci=C3=B3n v= iable basada en datos recolectados, la poblaci=C3=B3n incluye tanto a profe= sores como a estudiantes de historia, tambi=C3=A9n aborda conceptos claves = como el uso de las Tecnolog=C3=ADas de la Informaci=C3=B3n y Comunicac= i=C3=B3n (TIC), al apr= endizaje invertido y las herramientas tecnol=C3=B3gicas aplicadas (<= span style=3D"font-family:'Times New Roman'; background-color:#ffff00">Anch= undia-Delgado et</span= > al., 2021). Se concluye que, la estrategia n= o solo mejora la ense=C3=B1anza en la asignatura, sino motiva a los estudia= ntes. Por =C3=BAltimo, la investigaci=C3=B3= n de Escobar et <= /span>al. (2024) sobre el mod= elo pedag=C3=B3gico del aula invertida en el proceso de ense=C3=B1anza y ap= rendizaje confirma que, el aula invertida permite variar el orden tradicion= al de la ense=C3=B1a en dos momentos claves: <ul style=3D"margin= :0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left:67= .56pt; margin-bottom:0pt; text-align:justify; line-height:115%; padding-lef= t:4.44pt; font-family:serif">= El docente ense=C3=B1a en clase mientras el estudiante aprende.</li>= <li class=3D"ListParagraph" style=3D"margin-left:67.56pt; margin-bottom:0pt= ; text-align:justify; line-height:115%; padding-left:4.44pt; font-family:se= rif">Posteriormente, el estud= iante profundiza los contenidos y ense=C3=B1a lo investigado reforzando en = aprendizaje.</li></ul>Este enfoque fomenta la c= olaboraci=C3=B3n, profundiza los conocimientos y la autonom=C3=ADa, haciend= o del aula invertida una metodolog=C3=ADa eficaz para el entorno educativo = actual.<ol start=3D"5" style=3D"margin:0pt; padding-left:0pt"><l= i class=3D"ListParagraph" style=3D"margin-left:31.25pt; margin-bottom:0pt; = text-align:justify; line-height:115%; padding-left:4.75pt; font-family:'Tim= es New Roman'; font-weight:bold">Conclusiones </li></ol><ul st= yle=3D"margin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"m= argin-left:16.86pt; margin-bottom:0pt; text-align:justify; line-height:115%= ; padding-left:4.44pt; font-family:serif">El uso del aula invertida en la materia de historia ha probado= tener un efecto beneficioso en el aprendizaje de los alumnos, potenciando = su entendimiento conceptual y sus destrezas en el an=C3=A1lisis hist=C3=B3r= ico, en particular en el estudio de fuentes primarias.</li><li class= =3D"ListParagraph" style=3D"margin-left:16.86pt; margin-bottom:0pt; text-al= ign:justify; line-height:115%; padding-left:4.44pt; font-family:serif"><spa= n style=3D"font-family:'Times New Roman'">El aula invertida promueve el apr= endizaje independiente y el trabajo en equipo entre los alumnos de historia= , facilit=C3=A1ndoles la creaci=C3=B3n de su propio saber mediante la inves= tigaci=C3=B3n y el debate. Aunque el aula invertida plantea retos en t=C3= =A9rminos de preparaci=C3=B3n de materiales y acceso a la tecnolog=C3=ADa, = sus beneficios en cuanto a motivaci=C3=B3n y desarrollo de habilidades la h= acen una metodolog=C3=ADa con gran potencial para la instrucci=C3=B3n de la= historia.</li></ul> <ol start=3D"6" style=3D"ma= rgin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-lef= t:31.25pt; text-align:justify; line-height:115%; padding-left:4.75pt; font-= family:'Times New Roman'; font-weight:bold">Conflicto de intereses</s= pan></li></ol>Los autores declaran que no existe confl= icto de intereses en relaci=C3=B3n con el art=C3=ADculo presentado.<= /p><ol start=3D"7" style=3D"margin:0pt; padding-left:0pt"><li class=3D"List= Paragraph" style=3D"margin-left:31.25pt; text-align:justify; line-height:11= 5%; padding-left:4.75pt; font-family:'Times New Roman'; font-weight:bold"><= span>Declaraci=C3=B3n de contribuci=C3=B3n de los autores</li></ol><= p style=3D"text-align:justify; line-height:115%">Todos autores contribuyeron significativamente en la el= aboraci=C3=B3n del art=C3=ADculo.<ol start=3D"8" style=3D"margin= :0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left:31= .25pt; text-align:justify; line-height:115%; padding-left:4.75pt; font-fami= ly:'Times New Roman'; font-weight:bold">Costos de financiamiento </sp= an></li></ol>La presente investigaci=C3=B3n fue finan= ciada en su totalidad con fondos propios de los autores.<ol star= t=3D"9" style=3D"margin:0pt; padding-left:0pt"><li class=3D"ListParagraph" = style=3D"margin-left:31.25pt; text-align:justify; line-height:115%; padding= -left:4.75pt; font-family:'Times New Roman'; font-weight:bold">Refere= ncias bibliogr=C3=A1ficas </li></ol>Aguilera-Ruiz, C.,= Manzano-Le=C3=B3n, A., Mart=C3=ADnez-Moreno, I., Lozano-Segura, M. C., &am= p; Yanicelli, C. C. (2017). El mod=C3=A9lo Flipped Classroom. INFAD International J= ournal of Developmental and Educational Psychology, 4(1), 261-= 266. <a href=3D"https://doi.org/10.17060/ijodaep.2017.n1.v4.1055" st= yle=3D"text-decoration:none">https://doi.org/10.17060/ijodaep.2017.n1.v4.1055</a><= span class=3D"url"> Alarc=C3=B3n D=C3=ADaz, D. S.,= & Alarc=C3=B3n D=C3=ADaz, O. (2021). El aula invertida como estrategia= de aprendizaje. Conrado, <s= pan style=3D"font-style:italic; background-color:#ffff00">17(80), 152-157. <a href=3D"http://sc= ielo.sld.cu/scielo.php?script=3Dsci_arttext&pid=3DS1990-864420210003001= 52&lng=3Des&tlng=3Des" style=3D"text-decoration:none">http://scielo.sld.cu/scie= lo.php?script=3Dsci_arttext&pid=3DS1990-86442021000300152&lng=3Des&= amp;tlng=3Des</a>. Anchundia-Delgado= , I. M., Anchundia-P=C3=A1rraga, J. D., & Zambrano-Cede=C3=B1o, Z. S. (= 2021). Enfoque de aula invertida como estrategia en la ense=C3=B1anza de la= s Ciencias Sociales en Bachillerato. Dominio de las Ciencias, 7(2), 37= 0-388. <a href=3D"https://dialnet.unirioja.es/servlet/articulo?codig= o=3D8231779" style=3D"text-decoration:none">https= ://dialnet.unirioja.es/servlet/articulo?codigo=3D8231779</a>Basantes Guerra, J., Chicaiza Moreta, M. A., & Miniguano Moya= no, J. C. (2024). Implementaci=C3=B3n del aula invertida como enfoque pedag= =C3=B3gico para fomentar el aprendizaje activo en estudiantes de secundaria= en la materia de historia. Runas Journal of Education and Culture, 5(= 10), e240194. <a href=3D"https://doi.org/10.46652/runas.v5i10.194" s= tyle=3D"text-decoration:none">https://doi.org/10.46652/runas.v5i10.194</a> <= /span>Bergmann, J., & Sams, A. (2012). Flip Your Classroom: R= each Every Student in Every Class Every Day. International Society for Technology in Educ= ation. = <a href=3D"https://www.amazon.com/-/es/Flip-Your-Classroom-Reaching-Student= /dp/1564843157#detailBullets_feature_div" style=3D"text-decoration:none"><s= pan class=3D"Hyperlink">https://www.amazon.com/-/es/Flip-Your-Classroom-Rea= ching-Student/dp/1564843157#detailBullets_feature_div</a>Cede=C3=B1o-Escobar, M. R., & Vigueras-Moreno, J. A. (2020). Aul= a invertida una estrategia motivadora de ense=C3=B1anza para estudiantes de= educaci=C3=B3n general b=C3=A1sica. Dominio de las Ciencias, 6(3), 87= 8-897. <a href=3D"https://dialnet.unirioja.es/servlet/a= rticulo?codigo=3D7539749" style=3D"text-decoration:none">https://dialnet.unirioja.es/servlet/articulo?codigo=3D7539749</span= ></a>Clavijo-Cortes, R. M., Cuzco-Gordillo, J. P., & = Chiquito-Chilan, R. R. (2024). Fortalecimiento del aprendizaje significativ= o en estudiantes de bachillerato t=C3=A9cnico en Inform=C3=A1tica utilizand= o una metodolog=C3=ADa activa que tiene como base el aula invertida. </span= >593 Digital Pu= blisher CEIT, 9(4), 323-332. <a href=3D"= https://www.593dp.com/index.php/593_Digital_Publisher/article/view/2497" st= yle=3D"text-decoration:none">https://www.593dp.co= m/index.php/593_Digital_Publisher/article/view/2497</a>Dom=C3=ADnguez Rodr=C3=ADguez, F. J., & Palomares Ruiz, A. (2020)= . El "aula invertida" como metodolog=C3=ADa activa para fomentar la central= idad en el estudiante como protagonista de su aprendizaje. Contextos Educativos. Re= vista De Educaci=C3=B3n, (2= 6), 261-275. <a href=3D"https://doi.org/10.18172/con.4727" style=3D"= text-decoration:none">https://doi.org/10.18172/con.4727</a> </= span>Escobar Sala= varr=C3=ADa, K. V., Santana Quimis, V. J., Velastegu=C3=AD L=C3=B3pez, L. E= ., & Guzm=C3=A1n Hern=C3=A1ndez, R. G. H. (2024). Aula invertida como u= n modelo pedag=C3=B3gico en el proceso ense=C3=B1anza y aprendizaje. </span= >Explorador Digital, 8(1), 6= -26. <a href=3D"https://doi.org/10.33262/exploradordigital.v8i1.2785= " style=3D"text-decoration:none">https://doi.org/= 10.33262/exploradordigital.v8i1.2785</a>Galv=C3=A1= n-Cardoso, A., & Siado-Ramos, E. (2021). Educaci=C3=B3n Tradicional: Un= modelo de ense=C3=B1anza centrado en el estudiante. Revista Cienciometr=C3=ADa</sp= an>, 7(12), 962-975. <a href=3D"https://doi.org/10.35381/cm.v7= i12.457" style=3D"text-decoration:none">https://doi.org/10.35381/cm.v7i12.457</a><= span class=3D"url"> Ministerio de Educaci=C3=B3n. = (2022). = Bachillerato General Unificado. <a href=3D"https://educacion.gob.ec/wp-content/uploads/download= s/2016/03/BGU1.pdf" style=3D"text-decoration:none">https://educacion.gob.ec/wp-content/up= loads/downloads/2016/03/BGU1.pdf</a> = Montenegro Mu=C3=B1oz, M. E., Bernal P=C3=A1rraga, A. P., Ver= a Peralta, Y. E., Moreira Velez , K. L., Camacho Torres, V. L., Mej=C3=ADa = Qui=C3=B1onez, J. L., & Poveda Gavilanez, D. M. (2024). Flipped Classro= om: impacto en el rendimiento acad=C3=A9mico y la autonom=C3=ADa de los est= udiantes. Ciencia Latina Revista Cient=C3=ADfica Multidisciplinar, 8(3= ), 10083-10112. <a href=3D"https://doi.org/10.37811/cl_rcm.v8i3.1213= 9" style=3D"text-decoration:none">https://doi.org/10.37811/cl_rcm.v8i3.12139</a><s= pan class=3D"url"> N=C3=BA=C3=B1ez-D=C3=ADaz, L. (2021). Aula invert= ida: una metodolog=C3=ADa a implementar en el proceso de ense=C3=B1anza-apr= endizaje desarrollador de la historia. Revista Caribe=C3=B1a de Ciencias Sociales. 10(3), 140-154. <a href=3D"https://www.eumed.net/es/revi= stas/caribena/marzo-21/aula-invertida" style=3D"text-decoration:none"><span= class=3D"Hyperlink" style=3D"text-decoration:none; background-color:#ffff0= 0">https://www.eumed.net/es/revistas/caribena/marzo-21/aula-invertida</span= ></a> <= /p>Piaget, J. (1970). La construcci=C3=B3n de lo real en el ni=C3= =B1o. Proteo. = <a href=3D"https://granatensis.ugr.es/discovery/fulldisplay?docid=3D= alma991000388749704990&context=3DL&vid=3D34CBUA_UGR:VU1&lang=3D= es&adaptor=3DLocal%20Search%20Engine&tab=3DGranada&offset=3D0" = style=3D"text-decoration:none">https://granatensi= s.ugr.es/discovery/fulldisplay?docid=3Dalma991000388749704990&context= =3DL&vid=3D34CBUA_UGR:VU1&lang=3Des&adaptor=3DLocal%20Search%20= Engine&tab=3DGranada&offset=3D0</a>P=C3=A9rez S=C3=A1nchez, L. A., & Sant= iago Garc=C3=ADa, J. (2024). Repensando el aula invertida: =C2=BFinnovaci=C3=B3n o estancamiento? </sp= an>Revista Internacional De Educaci=C3=B3= n Y An=C3=A1lisis Social Cr=C3=ADtico Ma=C3=B1=C3=A9, Ferrer & Swartz</= span>, 2(1), 340-374. <a href=3D"https://doi.org/10.51896/easc= .v2i1.546" style=3D"text-decoration:none">https://doi.org/10.51896/easc.v2i1.546= </a> Rodr=C3=ADguez, J. L., Yang= ali-Vicente, J. S., & Manco Villaverde,= M. E. (2023). M=C3=A9todos de ense=C3=B1anza: estrategias y actitud d= el docente. Revista Venezolana de Gerencia, 28(Especial 10), 1663-1677= . <a href=3D"https://doi.org/10.52080/rvgluz.28.e10.48" style=3D"tex= t-decoration:none">https://doi.org/10.52080/rvgluz.28.e10.48</a> Sol=C3=B3rzano-Barber=C3=A1n, G. M. (2021). T= ecnolog=C3=ADas de informaci=C3=B3n y comunicaci=C3=B3n (TIC) en la educaci= =C3=B3n. Polo del Conocimiento, </s= pan>6<sp= an style=3D"background-color:#ffff00">(3), 2246-2260. <a href=3D"htt= ps://polodelconocimiento.com/ojs/index.php/es/article/view/2504/html" style= =3D"text-decoration:none">https://polodelconocimi= ento.com/ojs/index.php/es/article/view/2504/html</a><img = src=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/= 2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE= BAQEBAQEBAQEBAQH/wAARCABAAHoDASIAAhEBAxEB/8QAHgAAAwEAAgMBAQAAAAAAAAAABwkKCA= QGAAILAQX/xABLEAAABgIABAMBCA4GCwEAAAABAgMEBQYHCAAJERITFCEVCjFBUXeRtrcWGSIjJ= Dg5YXFyc6HB8BcYN0KB0RonUlNVWGeGpbHS1f/EABwBAAIBBQEAAAAAAAAAAAAAAAAHCAECAwUG= BP/EADsRAAIBAwIDBAYHBwUAAAAAAAECAwQFEQASBhMhBzFBUQgiMjdhkRRxc3ahs8EVI0JDgbT= wJzaTpOH/2gAMAwEAAhEDEQA/ALGsJ8xjTPYOTawGM87VJ5ZpBVNuwq9j9p0mxyLpYe1NpFRNyY= wjqYcmEQKCMOV8fu9AAQD1wDzzM25ewXjTX61YcyNbMczjvJc+0fPqrMOY0sm0QrPmEmcs1SP5O= XYlcFKsDKSbu2hlAA3giPURlQ1wKA7E4CH4RzXiz17jB795gw98Pzfz8PFMPuiIvTCWuoh8OUbG= I/41E/X5x6fMA8Svl7KrJwH2wdntqpqia8Wy+m4TTUt2gpajaIKaoiMUoWJIahG3BsSQLtwCN/R= hGCHtKvHGnZdxzcKqCG13Cz/s6GKptctRAW59TTScxd0rSwOu0KCkzArnrjoRlyvebBsdnDPtF1= yzUhWb01uLaxC0viUenX7PHLQVekp8oPWsSmlCyqLgIw7UeyOYLJC4BYy6nh+GpTmn16dBD16dR= 6e9+j4f8B+EPzdOITuTl+UPwT+ZLIX1d2YOLsyj17v1hD1/N0/n+evHBekFw7ZOG+OoaWxW6mtd= NU2OkrZqekUxwNVS1VbHJKsWSkW5IYxsjCRjb6qDJ12/YXe7tfeDpqm8V89xqKe7VFJFPVPzJhB= HTUkiRNKQXk2tKx3SMX69WIwAh3nacw/IWpFRo2JcIyxK5lHKjSVlpC4Ebtnb+o06MURZGWiEnZ= Fm6EzNP3CjZm/VbreSbMXqrcqbwW7hBRuHtLedVn+g1/LsJnPKsHAXuNa2KA+zTZq7QExKwsokV= 3HzHsZlLv1I9nItlU3LJJ6Ri4UaqJLlaEQUSMbm+6L0XxNyMYrrlUCOWwBAEZiPd4QroXe7jIET= Hp2+IUqzMVOgiPRRIDAHUOLDsXv69J42oEhUlGqtXfUqrvK4oxEgsjwTiFZKxJmopfe/LiwM38E= Cfcgn2gHQADhLZ5cUZVVJfJYsAe4jp/nl8NOjU/iOMeY9qpoPKQdv2loePc/yeyrCSY5NzLnOGl= IA2M3tFctlKk3uOWGUpHoyLqdjfaLSBQblcGRaPXjdQpRdAd0+uVxmY/V7E1wzZkuk2SxExzBSd= +yhF2WuOKLMyYsSKSViYWeNCOrTiHdKdV0ZFiRtHHTHvSKQgdAVv7of9NE6wIdOv9Yeg+v/AGfk= jhIHMPzfbU9SOWprshNSsRjp5rJUcnW9nGGEQsEi+frV2I841Mu1SkArjWvyrqPZOV0mp3ssKqx= iqJILIUVOaE9lSzNlgoycKPLwx3DRqwVnulqBISDWJj9pdeX0q+eIRzKNZZmx26fPH7pcjZsyaN= W9iUWcu3DhQiCDdAiiqyxyJplMYxQHmWLcHVCoTstV7Zstgas2WBfLxk5Xp/LdCiJuHkWxuxywl= It/PN3rB63UASLNnKKayRwEpyFMAgEhWtspyepTKGDKjD4t3Tf5Jk8g46hYe0T8rQ2EGtcXlkiW= sbLSrCJuyxW0OWXUbrum7Fk4UIxKYhEXCgdD9ogtT8d7lc5na3C+UH9mjqsrdcyWYzmpyDOOlQf= wczHkZplcPo+Tb+XOV6r4xPL9xxAglUL0ETUMIBOSwAUsSwwe8DoOvn56NWFY5zdhzMCT5fE+Vc= dZNQizppya1Autat6caot1FIj80BJvwZmVAphSK48MVAKYSAYAHpw8h5+wbiNy1Z5VzHi7Grt8Q= VWTW+X+qVJy9SARKKrRtPSzBdykBgEplEkzEKICAmAQ6cSX69YnZ6J87eHwXiW0Wp1QUYywx8il= OPW60hOwEpg+ZvJ4abNHNmDKRRYWBkzesDmZJmSVYMlO0V0zKnFugeqLfm47ObKZQ2PyBbkGNdC= Nsci2rck1Rm3sld5mcQrUMwdzDSXSjqxW4muyDMjNu18QhQim6CqKRVhOcpQCxYhQqtnZ19Y4Ax= nA885/po1TDtbsfEZE1ey/KacbVYBjMm1IKYcuQRyzjVxVKMWatTNBM1qm3zidgIILBHMpuOhxm= WoBIvE1G7ARcp96fN1FzurQ9QMW3fcTZbCM3cJqVt8VK5ebZMx4XHlqfpXK0+xY2BtkaeCqko9j= a8zbRztrGJg4QdRT9JyQ7hq5VFX+53LqwloXy59yHOHpa9Sh8oJYRSsIXSYjJUES0zJKR4sY32d= DxQoCqNpkAd+N5gFATa9gpeGfxATRZjSyP5LOpyW6C18e1n+kLKknR6njF2RvdbLZ2eT8mtFyMQ= XdR7II+PjZJZeQcSUiwZIiq2KK53KzVutQKpVSuSDIB7I3eyCcEZ8D3dR46NUawe4+pNnlmMBW9= nNf56ck102sbDw+YcfSMpIuljgmi1YsGthVcu3KpzARNBumoqoYQKQhhHpxowFAMACUeoCACAgH= UBAfUB693r1D4ePna7OT/Ldm6Gy/qnUTaCk5KbzbNRZxlR9UZOov4A6S5X6J1I21y8ozk0VvKrR= 6zZuKBwBwk4DqdFRI11LnN7pVCq1mps7c3etKvX4autXsn4r2SdtoSNbRqDqQeLgos7fOEmxVXb= lZQ6q651FVDmOcTDkFNuGQxHmHXB/An46NZa1v/GJwF8teK/pzBcUw+6I/7EddflQsX0RNxM9rf= +MTgL5a8V/TmC4ph90R/wBiOuvyoWL6Im4nr2g++/sh+yvP5MmoNcD+6TtS+1sv5kGk58nH8ofg= r9jkL6vLLxdkX+9+sP8ADiE3k4/lD8FfschfV5ZeLsi/3v1h/hwjPSe94VF92bf/AH1z06fR1/2= PW/eCr/sbdpM/OB5cVi3gx9U7biheLRzTiosqWEjJdyVgxudalSoryNaGTU/B4+VI8ZtncI5fCn= HeMZ01eOGaTrzaCUMZUHn44NqMXjLHkLmeIqFYRLHwcR1olmZRbFL7lJjFv5RSVUTjUAACNGrd1= 5NumAEbJkTEChV/tbsbW9TcE3bPdug5ux1yikhFJKIrvkfbDss5YIuutwZ+0nLRn1RdSqK63jOE= /vCSnZ3H7SGS9/pIGsnQf9R+bg/xpHp197qA2b/3xHtHlKBVjEihuhI3YPQ4xkeefq6DPg/NATO= ODuZbs3y0XlFzvQr7fNg2m2cFYYuCfsqwxmE8YxuOphmSRTSiTMY4zBCflHSHiKCLsVlzAPVIEx= L2PbHlX52zppNpPO4+gkozY/XfD8JSLZjmceMo1/NxPhMX4x7GRcKjFpWCqTqDtw2aO3bdlIs5e= SAHgO2rNu7ZdptzfNWtyrqnjGsmtOPckvUXDiBqeQGkazPZ02aCjp6nX5SLkZKNePmzVJV0eNWW= bPlGyKy7dBciKokPz3mAa5MNqkdNHM5YS5ycOWTRKHLWZE8IKr+sp25uA2AC+RApoVUixhEehVh= FAfuwHigeVCFCbSpZyAvgQB3eA6+Hx8tGkZYgsnOCgLRjSFtGjGFwhoqx1KPn7sthKltrEjFNZV= ihKWIZSFsjFmhLN2JFn5X8dHt003SYOEW3oBROeqOpexVH5xmwmwtsxZYYbDttf5jVr18deR9kS= pLDKxDiHO3BJ2d10fpILHSFRuToBBA/aPQOKMePww9oCPxfv+IOLDLuz6iqSMHGcnODnvPj/nTJ= NTm2vUXYWV54kBscXFdgXwMRdMj3IQeR9hkQNgmWqqveAuwedvttySNH8G9Vjh06kEDcY4d6Kcz= Tl37M5HvGjVdG946vJ5BvFrxyVcsDRxVHkqrKRlct9Xn3bd4hM1lbtSaTDQnaomZRVrIgm/kGJa= JcG7+66bEZqyNgDGU3YJDJGKwsg3BhI1qRi45oFUszeozAtJNyUG73wpp0ikl4I/fkTCuQRTKI8= DDCfMsxlm/cPI+msFRbxE3fGhboaWs8qMF9jD4KRKR8W/8AIeUk15P8LVkU1GnmGSP3tM/i+GYS= gN++Qfy1KiNQ6n+Jem1iCR4Y/wDe7RpYFsYc1TbDSTcfGOzuGV0bm8Qwf/QtXoOs1+vPrEunfZG= SyABBZSrhF37MjoivuRK6VQ8FNQ4oiqdc5SZrzJywNssi8tjTGuQOPZJPMWAJ3OaVuxJIOotnOL= wmRslSk8wlWRl35I906aNo6KWFgV15hywljKJAY7cyJq9+POLBKRjaqAB94ABxkgDuyemPL5jRq= LvPOKebPsNiVDD9t0Vx5XK+k6gnvtvHmKKrUbYZWAIYjUnthlZVEUkHPcIv2yDFFFbqBUyJEKUo= YM+1O8w7/ldyD/4X/wDV4sTvnMqxrQN3Klo3I0S8Pb9cHNabsLYz9hfYm1GzQ68y1M58aTSlxBB= BAya4JR6g+KYAS7yfdcMg6m+I37v/AJ4yiokQAbEXIDYGeoOOvtHyI/Tpo183rW/8YnAXy14r+n= MFxTD7oj/sR11+VCxfRE3Ezut34xOAR/61Yr+nMFxTD7oiEBwjrr8qNjD5qib+fTie3aD77+yH7= K8/kyag3wOP9Je1H4y2XH/LCNJ05OP5Q/BX7HIX1eWXi7Iv979Yf4cQmcnIwBzD8FdfgRyD+/Hl= m/y4uyKYo9egh6j/AADr+8f8ve4RnpO+8Ki+7VvHyrbkf1H46c3o6MDwTXDyv9Wf+lbx+mlb86P= 8m5sR+wx99Z9O4WzyPdQtYM7ah2S25jwRjLJNoSy7aYVGwW+qRczLIxTaErSrdgi+doHcJNkFXL= hRIiZygmdZQ5BKY3Xhk3Oj/JubEfsMffWfTuEzcoTma6laf6wz2Ms326ywdwe5OsdpasYikWSxI= KREjEwDRop5+KZLsyLKLsHJBQUWKoQCAY4FKYB4j2u4wnZuzzD7Pf3IP10/tYd5iGDK3oDzG6kt= gtJWq1ps/wAcZhpMQ0fPV/sYWUnDFfRTN07WWdmZFlYZ8Zsk4XW8Ni6I0E5kSAQG9v8AZRk652F= dxIXAevSy8k5qTkuZHNAcKZsSLJYTY2IqhbmE6VAqzYi3sduf2QPZDkK0EBMHjcJr2azO95pPMf= pCmKa9OlgbPPUbHFHj5NoklMI1ODfGdzFjmW7Rd0jHtyFXm596JnKhI+NJ1cKlMicCMBtkaCHuh= 2LiGh/AKkvVo5scB6Cl4eurFqifqHvCToU3UA98OvTjI4OFVj6whYHJyehXGfHp4aNHHO3Os2Uu= Wx1pwJoZgKLyqWoSs1DHlpGvWa6zNqUrrkWUzORcNWJaHRh6yg8TUSaSEg8c+bbi3dKiyM4TbB/= O165sO/1g3Zw7qnshiHG2MnF3tEdG2mEWpNsgrewh5SGkJRi8ZjIXaSQbHdEbIqIKrs3BDoiYfD= +6A3GHuU3sNiTRvc3Y2t7RyyeOXckwsFELaZqMlHaMJZK9dgdvoqQNGMH7xk3mUmx1SvTolaHWZ= NiqrACyRhKVszRi3P3PpwNknDlxjL5R5Cdx3HMrHEEeJsXL2Kocm0kG5Cv2rNx3tHBTJKCdApRM= A9pjB68W7VyUCAgRk7zuySFBOMdPP+oHfnRo96m7R5CntseYfX8I6x65xOX8Z0PYGUoExQ8dO4e= 9ZJt9cypHRkNFXWZNakwnULDIKISM0kkeIF9LkSclctSF7BVXrbmLe6scwfMOR8PYVg7XtXNlyS= GQcYu4hZ1EwRZSah1bcKEeS2xqqXsqSSj2yPdYXnhlXEDC5E3iFZXygOn22ffDr/u89D8XXpn2D= +H5/wCQ4D2s2csVa5c7XaC4ZuuEbjmpyUxnCspWCxg5bxSErLT0NKxqD5ym3VKxSfNYx0KDt2CT= Y6hkEfGBRwkU9wODIAgb91GfEk9FGMeXj9fho02nZHZHmx06va+OsDaxVW7zdsw3C2HNjJ/XXbs= lNym5XVLK1hiVPIkOLVo1QKmcjdRWWOTu9ZFX3gw8HON351tzBjur7260VWgUS8O0SqOYmAnIGb= Thgft2EpPQcgvbbRCy54AzpJxIw4gi7FM6BTLNBdt1Dinmp7lZUyBuhijCmOdpZXX7XObpGO7FG= 5Uqk7YYauScfkNFWTd5Dl5CruY6Vn4Vo1BtGxzPziccgpHuVRFqo5duSKy3uqDKrOcUmZ8wZLeo= Xytl8bw5WzSY428E9fEvX7IrjbPB+ygVTejTyPf7C+/eY7U/BpHGCF3KvrgnAD5A8eucKR5fMDG= jTeNi1Sr+6FcELEEBIs/xEoQQ94SHocgJR9OvXqAgPX4h4q/4kxzqHT3QBrr0/wBnCn1dO+KzuM= MpysQ8RGM/HJJH4dDo189TEOuOy1Hyri68yut+d14Wm5DpVsliR+Lba4eKxldssbLviMklo1BJZ= 0dozVBukqugmooJCHWTKInLSNuDdNQd+qTSanmhXbPBIUuefWCJB7r7fmLoz5/GezFSSblKj3SF= O1TRMJygjINjgoHcZYUx7RfF4ZA94oB+jj0MgmID1KUevxgHQf09A68OfirtnruK7vZ79UWf9lX= ewx1EdsrbNdHgkhFTjmsy1lFXRuxGVB2KNrEEHOdJrhzshp+G7ZdbNBeFuNsvbQNcaO6WtZo5jT= 9YwGpaykkRdx3EB+pCkYAxqR+C5YmI4GyRl61V5j0DUcgwy5nVWQvUIpSLA1cqJKJHIpLt5qMlm= nitlFG7pMaiuRdBVVBZAyaihDNQw1sJv7gdBpD7S4nhtlMZNippDsBrHJx9usEagY/aDqz48bpx= M5Ot26IlVeP4OAZOmzchlAQmVzCHDe39cgpVI6MnDRMgioUSnRexzR2kcpvQwGI4SOU4GD0EDAI= evxcD0+CsUpqLOIqlRFcerG7zSFSIrUZEpx9O9OQrasY7TU9A6nTWKYQ9OoB7+ivPaZW8SxCn4o= por+iKUhqLjS0RulKnfinu1thtNSoViWCTJU0zMSZqeTrrbWns5g4el+kcO1ctmd2DzQUNRVi3V= BwAfpNrr5blTyZACs0b08wXokyEAgbWyD193rwZO0WUk0L9iq6hGJWFhDysjCSiK8TKsJxqwk00= TMJ6vSjOSj2pnka/RZP0DpKNnbYvVVMMU/aM+XQIemKrP69ffyRdP0f8V4ZKbEdYQk0LJEJOYS3= t00kFLXHKFTl5ZugQySDSyqdvg2lqmmcxCknk3yqYiDlBZvIETeplBsVUqKZVzFMqBQBQxCCmQx= ugdxiJmOoYhBHqJSCooJQEAE5xDuFbTNEJWNI9QkJOVjmKtJH3YVpVVUl7vbVEJwSyJkAsemNTy= 1WqERmUANJDkRyHA9ZUZneMnrlGd9vTDt4Y31p5fuqGpMi/ncI4rjK9Z5Judm6tkk8kbFZgYqdo= qsWkxOO3rqPZriQouG7AzZNz2l8cFAKHHu+0L1wfbPpbhuarKHzq3cNHSdkCyTYR4KMK2SqNxGA= B6EQPbCpEbCHlehjgKxgFYe8NmceCHUBAfhDp8/GEknqWJPcST1I78fh8sjx16NSocw3Z/lTS2z= OR6bsNqZl+0ZZx9OBVrRfcer1+sp2dwzYslEHDp00v0I6lwQaqoNkXctHFekSRBHu8FNMAxhy9s= eUDOvNPxtfNSsSXvH2u+MXyVwfJXJ8aakYFCKpzxi5cTcuL6TZkd2C2O0m0dFtpR+uRmr5gAKm3= d+Xs5k8QYompB1LTOM6DLyr9UV30nKVCvv5B4sIAUVnTx1HquHColKUoqKqHMIFAOvpx2Gu06pV= BsozqlZgKy0WUFZVtAQ8fDt1VhAAFVRGObtkzqCAAXvMUTdAAOvGYSgKVAfONvrOSvcOoAwPq+W= jWWMLaI65a9ZkyDnzGNWlIfJWUS2MLnLu7LNyjSQC02Nva5kEIt+8XYsfMTTZFwmLZJPwEyign2= pGEvALzDy4uX5ttk+1ZIuFRibNkYy6Mfc39NvkrFOVZGOSTaAM9H1+WTbElUECJN3CyzdN4YpEi= L9xigHGsdtMtzuDNfMnZSrNbPbJ6qwCasXDD5vynmpOTYQpJWV8iUzwIKvhIjPTxmopuAho18KS= 7cwAuktLF+Cs2VHEtLg8Tzb+/WKvWC1IyVviLNWaq9Wxzd4mfu3sVvM1+bdRyylmzHV6DLWSWWm= Jy9R1EmfKoyqovZFoXd22zLV0ElwnuEVEprFoabmkbJSkPPqXkf+WsAelVFkZBM1QeVvaF11ztz= vstFcIqCmoZq1hSNWVPJB5kaPMsNNHGuP3jTFKlmK7+UIQHCCVXUwZV055a2cqzjGiZAaUqULiF= NHCFEeIZBdQ9uYBXl3kWlQ3MuylmsrLqMX0XJETZSXmzpPW8ks37FVXJz9JHkmctdBs1fnx3NpN= XKrQjR2plO3FQcLPFCJsk0FTTBU1TOlVEk25SHMK51CkTAxjFAQnT9JNmoKYipV5TIM60TaFbCE= wpK1J7Y15KwyUHTrBYivnC6hlptGmRFjt7Uzt1+CWHLNzfR4hMVuuISBvyZr/u00tM2fG862lYl= OOqkygq+lmxICbyBWqdKmGzMajZp2cJDvFbCetIN26rsGp5Kkxkk7WVTssrIwu1qeHrQKhIaTie= kZGikkeSolQJuSSNeWGTeil1fepJLNh1KgIW1qaXiW+GCSar4brVZZUjSGCNy5V0J5hEveA67WA= IAUoScsF1pi9ab6mr7O432buUYu1z0EvBQOPZde2zLNCRl6xWpEYyOaV8jwI1+6bV2Ok3KxDtjC= dBouuqJhT68bvAw9A9R+cR/f8ADws/AWDdhS5xSuuZlptzSaQ+uz/GUfbriheJGLGe8KnslhdJS= jxdKecVSAa2F0+OKjBo9vtshWDVq2QbDwzQCB0D3w+b/LjmrlSQUUsUENbHXEQq800BDQrI7Oyx= RsM7jHFyxIdzDmFlUkAa6S11lRXwzT1FFLRKJ2jghqVKztGiRhpJFPRQ8u/YB/AFJ9YnH//Z" w= idth=3D"122" height=3D"64" alt=3D"editorial1.png" /><a id=3D"_Hlk92188167"> </a>El art=C3=ADculo que se publica es de ex= clusiva responsabilidad de los autores y no necesariamente reflejan el pens= amiento de la Revista Ciencia Digital. <img src=3D"= data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQE= BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ= EBAQEBAQH/wAARCABVAKIDASIAAhEBAxEB/8QAHwAAAgICAgMBAAAAAAAAAAAAAAoICQYHAgQBB= QsD/8QAUhAAAAYBAwICBAcLCAQPAAAAAQIDBAUGBwAIEQkSEyEKFDFRFRYiQXF3thcZNzg5QnKB= obHBGCMoYXaRtfAmVnPRJTI1SFdYdHiGl6bV1tfx/8QAHQEAAQMFAQAAAAAAAAAAAAAAAAIDBgE= EBQcICf/EAD4RAAIBAgUBBAQLBgcAAAAAAAECAwQRAAUSITETBgdBUSJhcZEIFDI2N3aBobG00R= VSdbLE8BYjJkJTZvH/2gAMAwEAAhEDEQA/AH6WcpHSKBHMe9aPmypQOmuzcoOUVCD7DkVRUOQxR= +YxTCA/MOv2cmAWywlHgwJnEOBADAYCiIfPyAgPu8w182rG2c8zYbfklMV5RvVCdkOmc/xas0rF= tXAImE6ZXrBu4Bi9SKbkQRdtl0hAxgMTgxg0+lsKyfdczbOsKZMyHKhOXK001y6npf1ZszNIOms= pKxxHSjdoki3IuqgzSFcUUUyKK96nhlE4hrc/ej3N5h3aUtDmUuc0ebZfX1hooilPLSVUcwiecd= SFnniKFI2syzEhgAUs1xqHu572aPvBqa3L1yipyytoqMVkmqojqaaSMyJCRHIEhkDhnBs0Nrf7r= 4Vbk+rJvdwZnHKENGZQLeKhA5OvTBlUshRDCwsU41pZpNs0YIypEmdjbINW6aSTVJKY8FuRMhQS= EhQKN9HTi6qcXvfs0riyxY2d0bJtfqa9udu4qQTlahLxbCQiop6dodz4ErFvAeTDMyLFZKQRMh4= 5/hEpyFTUT13Bfh6zX9bGQvtXK6tu9H+D+mXeR92B7N+rm5UL9/8Au10R3n923Ylu7Ou7SQ9n6K= hzrLshoa2Cty6P4k0k7JSq/wAZig0QVAkEjajJEz39IMDe+hu7vt92uTvBosikzusq8qr86qKWa= jrn+NokLPNYQPLqmgKWBURyBABYqVAAciLzwHPl/n/P/wC66UpJsYaNfy8m6RZRsYzcyEg9cqFS= btGTNE7h05XUMIFIiggmdVU5hACEKYwjwA674CA88fMPH69QW6mNyfUPYdufn41Q6T42LZyEbrJ= mEiiI2bwa6oqQwCAlOmjJqGKJRAQEPLXCKi5VeLkDy5NsdrDgX8sK074+tfuSzJkmzV3bnd5jDm= GYmUeQ9bc1QEmN1uLNo5FBCxSthMgaVihlOz1tlEwq0f6m2cJtnqz5yQyoRhjsx9XWXYtpOJum/= uTjXyJHLOQj1M6PGTtuqHek4aumyCjdwioUQMmqiodMxeBKIhrPOilhqsZj340FK3xrOZh8ewFi= yOSLkESOWjqZgEmreCVXQVKdNUI+WkWsmmU5TFFdml3BwHAvvkIUgAUocAHAAAeQAABwAAHzAHz= Bq6kdYiEVFNgLkgbk+dwSff8AoK4WO6buUd/MTtU353TKy24mfyvTqOzmsJtMywd+n5RawMq1bH= RW9Tgbg0VcTBlpJGMK8YRjZf1lUGqSyZjCkXUtekTua3z7gbBm9rvDrFprzCsw9JcUU9ixK/xoR= 07knthTnCtV3sRFhLnSRaRoqpJisLQDkOIEBcBNYpvjs9hpGzzczcqjMP69aaxhXIM5X52LXM2k= YiXjq4+csZBkuX5SLpqumRVFQPMhygYPMOdUXdDLd5mbJSm7aybiMyXK+1rGdHpFmbrXGZVk0K+= zTPdXc68aeMAAgKzOMRFcQHg4NkgH/ihps+mkj9NeVGoDcElVsAANiAL/AGnxwYZ65D3h/frzpI= rJ3U/6iG+fPrzHm0p9dKrCyMjIFouPMZoRbCfUgo05wJNWu0u+0yCh23Y6k3LiWjoJgdYES9pSl= VVkxgTCnXcjc2YlkMpOs2jjVnkSoOr4WTzRi2SjzVNCcZKT5X0cxvrt69ajGlcAu1atXDhdPuTS= RUOYpRoYGA9J41Nr6Wax8Psv9vvwYbd5AfYIDoEQD2iAfTpInfvu83ux3UJzdhTC2dMsxzdbKcb= UKBRK1ZVGbQHktHQaEdDxTdQyTdEXci8AqYHUTTBVcRMcpREdayyrmrrNbTUq5fcyXfcPQ4d3ME= YxMncJGOn6w/lE0juSxT5IFJiJOq4bprKkZSJU1HKKK50CnBBUyahTkhbuilgCoNwTcA2sbefhf= f7jD4XICHICAh7+fLRyHvD+/VI2OerM3+9iOd5t/gWDnJNfeOcaq1RioLKMtmV0l02MQZoIiZRp= EyLVZGyy7dETqsI5tKosxWOih4i/9W3h9Xze7crJJYTteYp4Io/rL+FxCzaVuo1Vq8UVMxYrPE0= 2TJJQ6ZDkaJysq4knZEFTgdwKaqgIWFzqvZQraSWIte9tvV43wYeYtzp8xq1jfRRTnlWcFLuoxN= NIXCh37ePcLNCEblAxlzGXImBUQKYVBECAA93Gl/8Apgbu+oznDc5MUndTUbjB4ta49tUuxfTuE= pLHrE1jYTEA3iEST7uDjkVl1GTuRMmxBwYzkhDqlTEG4mLrzpyV/qq1jMmQpneAtnNvi9rgTJJ4= le/WOMk4VC9prV5eAWbt2co9WJKpM0Zg7RfwQImmVyBlC94AbQnRO3bbls3b0rHScuZtyDkKptc= SXqXbwFmnV5KNRk2Nhqjdm+I3UAClcNkHblJJQB5KmsoUB4MOq6NKzfIeyghhe4+Tsp9d97ew+O= DDcHID7B5145D3h7vaHt937B0pNn7CXXblM45dkcVus2Fxq+yPcnVBJGZpxdGx5agvPPla+DKPf= X5o8ZNAizNgbtXbZu4QS7UlUUjlEgQtyTuV6xWw240+ZzzdsqV1ScOq7hIrIM5V8hUy1N4xZH4R= jFXMNJWCL8VMqyQPWreSZTDZByi4IKJVUFhBCWtpeMki9g2/h4eq5v7PXgw9Zo1RPSeu3tplKZU= ZO2RUxEWmRrEA/ssSyXbLs4uwPIpo4mY5osqUiqzZlIqOWyCqhSqKJJEOcpTCIAaR0pv+J/u/X2= /2djCcpg5KP0c/3een6el1+T+26+XH+g0iPH02Of0gub2D9A/u0/R0ufyfu3X+w0j9op/XcXwqf= mn2c+sJ/IVOOMfg3n/VGeDzyI/dW0+EdtwX4es1/WxkL7VyurcPR/Pxyb39Q9l+2dC1UfuC/D1m= v62MhfauV1bh6P5+OTe/qHsv2zoWth95f0L559V6D+hxB+7/AOljJfrFP/PUYcgL+d+kP8NQ16h= uPH+U9k25WlRTdV3LSGKrK/imiBROs7kYBqM+zapFKAiZRwvGERTKAcmOcofPqZRfzv0h/hrgsi= m4SURVIVRJUhk1CHKBiHIcBKchij8kxTFESmKYBAQEQEBAdea6HToYcjSR9ljj0Gx8+bpL7kqlt= f3qY+uuQZJGDotjYTdAtM66N2tIFtZW6ZI+VfnDyRYM5prHDIOBDtaszLuT/IRNw+gwzXh2TZt3= 7DKmOnbN2kRds5b3SuKoLoqlA6aqShJIxDpnKICUxREBDSwm+voG5ElsmWbJWz17WX1Tt0k+nXm= J7JKErz+qSki4M6eNKrLOkxiH1dO4VWUYR8g5jnUOj2MUVH7chFEq+CdEDqQkKBS4nhilD2AXJ1= GAA/RAJ4OA/q4DV44imIfqBCRbSbDjzuRb28cWvgw3Pvvt1VtOxbd8NZssDYis8BZKK7NBy8fLF= amVqkmZIrgWLlcERUKQ4pgp2icCmEvIAPCsfSgaSr7a71VmsKRZSTW20xpWxG/PjH4jMjGWIkBf= lCczcFQAA8x59g6sg2KdOjdphTZ9v9xLkijMYy8Z1xyFexrHJXCuSqMvKfFa1xgoLvmUm4ZxZBe= SjJMyr9dBPtUMoAiVM4l2Z0Yun1uG2pSO5JruSocTBQWUavSoKKboWOv2RGYRjl7WScaOkoZ+9F= BL1SYbEN6yUpFyrHKTv7DgCFKJHIuoP6aEEbaxdDcffex91sGFltkdR3cXjK0pXdmM9LQmVHNUe= rPSwN+rWP5eRrDV8wO/aNZCyTUGlIkTdixdOI1k4Wcimh62ZuKDVVRO9za3ty63dc3E4bnc3WTJ= 7nEcVfIJ7kFCUzxQp6OWq6LooyZHkMwujx7JICjz4jRs0cLKhyUiRxEAHTm4noT7q8WZhkcgbL7= OxmqmtMO5epIoXM1DyLRQeKqqjEjJPF2LSQbsk1haNJZjMEdOmwdrxi3OBjq5PgTZH1oK1m7Elh= yNdcmusfwmRahK3Vq83FN5dmvV2M4xczaLqJC2uBkm6kem4KqxBBb1kgmR8I/f2C48iuupWi3U3= Dj0r8WBPjfYfpgxD/cF59c90PHP9MDFgh83tk6YIce7n36vF9ITKX+Q7Xx4DkM107gePZ/wHav2= /wBft1DfLnTI3hWzqnr7nIPHkU5w8fcVQsglsB7lV27savBPa2tIvQhVpMkp4iSca6MVr6t6wp2= ACaZhOUBtK6wW2DMm7Pa5DYzwhXWllt7TJtcsq8e9mYqCSLEx8VPNXa4PZd00aidNZ82KCJVRVP= 3iJSiBTCDbMpemNx6KDVxZSNPPAHHmOPDBhYmbbSKvRRpy7UFBj2292XNJ9nd2FFagPU2ZlgDy7= fF7ykE3l3mDjz4Abx/R2pymr7Sr5ARzqOC5x2Xpp7Z2RFUQlPUn8LCEgnrlHnxxZqoN3DZquYoJ= Cq2cJFMKiagBmGyfpp2g3TjyRs+3X10lUlrverHPsVoaWhp97XnB0IJxV7TGvI1w7Yi9jJaNFcz= JRYnrTUi7F0BWz0/dTZN9EnqS4VuUqTCUtGT8WqZZqyulCycnQnUrFgoYzckpGysjCSLRcyZUzr= svFftUF+SIPXZCFWOoujrJEXVW1lgx3BHo8WsLXB4N/YLYMOdZG4+59eOQAQ+J9lAPLn2wr3SWH= QcmWta3uZHsL8TeowO3zK0y77AExwaRk3U3q/aHHmbwkD9oefn9OrIem1sm6jeHs2Xuw7mHVofU= KZwTkSpRLaZy+0urI9zm3VcNBh8Ep2GTFBUWzOTIWRO3Im2IdRMyyfjgBsX6UHTI3Vbat0Vwvue= 8dxUJjyy4ivtIWdNLfW5xRy7skpXlEWR2UPIu3ZE3LBm+71jJFSTEgFMcDnIBkLpjSZTIrXVbWs= L3I1WBJOw5P4bnBiuf+Wv1POoBuQtFX25ZCvEY8XPPTNZxtRLZC0KDrtOiHZG6YryMo/hWjxdui= 4ZldvZGQVePHS4iQBKJCE0Vvvw/1Jsb1ejSG+SWucpV5CekGlI+NOT6rfkUZwjFNV+LVrA2ObXY= KGY+GB1l0kElCABCnMYoF1NrJXRS3+4SzbZLHtTlySdZXk5Ven3aq5Ha4+trCBlFzLEhplF5Iwz= xF43SMRq89QcO4554JXBFC+IZBLXmQulZ1gctNGEflFCyZDYRTlR3Fs7nnWv2NtHOlk/CVcs0Za= 1uk2y6iQAmoqiUhzkDtMIhp9WjBXS8SqANrWbgbX8PcOPPgxRto1bp9446jH/RDA/+ZFD/APftG= nerF++vvwYriN7B+gf3afo6XP5P3br/AGGkftFP6QXN7B+gf3afo6XP5P3br/YaR+0U/rtH4VPz= T7OfWE/kKnHGHwb/AJ055/Am/OU+EdtwX4es1/WxkL7VyurcPR/Pxyb39Q9l+2dC1UfuC/D1mv6= 2MhfauV1bh6P5+OTe/qHsv2zoWth95f0L559V6D+hxCO7/wCljJfrFP8Az1GHIC/nfpD/AA1y1x= L+d+kP8Ncteay8D2D8Meg2ITZ56iO0PbLe/ua5uy0zpVzGGYWAsMtX7TJqDESarpFi8FzEQr5mA= LqMnRQT8fxS+EJjkKUxBHSw9ZbpyceW4mN/XT75x9mdLdekDfj7p+z8CuPw8gAPIJK1+7W5cNej= 7XfMOG8ZZaY7javDEyVj6qXtpCO6NKuTxhLVAspxCOcPUZohVzNAelbKuU25SqCmZQqRQEC6uVj= i0K7uw1AG3rNjtYHw232vzzgwzZgbfVtN3MSR4PC2b6ZcLCmmor8WQcuoWzLIop+KuuzgJ9tGSj= 9ugT5bhwwauUUC+axychqRdwvdIx7FEnr7cKxSYNR2iwTmLbPRddizvnBFVUGRX8u6ZtTO100F1= Em4K+MoRFUxCCCZxD5zG4jb/nDp+7ikqXYpU0DkClOoe5Uq8VB48btpJl4wuIWyV96JGrxEoOGy= rddFUiard42dNFQOUgmOztumvGN9/XSiwHkXNGcK5t7aWW705/YrrPVuaskWtfqxGXWtzEI3ia2= RV83NLP0JWUaKm4Qbtm/hKCBlCANHhVTHpY6HsCRY6SPKw3vxb1HBi/Kn3qk5CijTtCt9ZusIR0= sxNMVOdjLFFletypmXaDIRLp20BygVVIyqHjeKmVVMTkADlEcq1VF0dcb4xxVtMfVnFGboHP8AV= hypb5M18rldnaywTknUdXU3cGMbYE035nDBNugqo4AvgKFeEKmIiQ46kNlPqN7H8L2V5Tcjbksc= wtpjVjNpSCYv3tnkYh0QeFGcuhVWM2MU9SEQ8VlIC2dp8h3ol5DlrSblV1NYkX0kHm24ttvtgxN= fWubnmHEuOHjSPyFk/H1Ffv0DumLK4XKvVp28bJqCkdw1bzMiyVcIEVAUzKokOmU4CQTAby1CL7= 7z05P+tDUefZx8X75z+2qBqsjrLYZ2257yRg645L3iUrb+CmLll6vGWOiXO0LWqAlJYZJvPNF4B= uJGbcSrpperPCJuREe4SAA8BVUuwV9SA330k8W4Hu549l8GGFbflfH9HxlO5jnrPHJ40rlWcXWU= t0ec0zFFqrVkMirNs1Ygr00kyMx4dIKRxHIOURKZDxAMXnTG3Devtr3avLSxwDkdrfXFLbxjqyJ= t4awRQxqEwd2lGnOabi44q/rKjB2UAbiqJPBHxAL3EE1a+6fcFtswL0u2m3eXzZAS1ovWyhvXcQ= OUoayNQygxLQm0BCzkQgMWuWMbzixElm7aYdNVm3rBSOBL2mNqoHoVbtNvG1mybhnefcmROOG1x= hcft62tKsJx6EqtEPbQrIkRCFipM5BaketTHFcqQCC5RIJuDcLEWqNnGq6kabD5QuPPc3B8MGHU= tGoj5D33bTMUULGuTshZlgqzRMwMF5TG9ieRdmXa2lg2bMna7lmgxhHb1uRNvIslRCQbNDiC5QA= omA5S6VL1d+nIYxShuip4CYwFATQN7KUBEeAExjVUClL7zGEAAPMRAAEdNBWPCsfDgnBix9Q4Jp= nOPsIUTD9AByP7NQfxF1HtnOdsmtMO4ry+ytORXxpYravJV21sFFBhEll5Ph3JwjNiX1ZJBU497= kvf2CCXeYQKMlcb5exfm2lJ3nEd8q+RKi/TdIt5+py7SXjwcoJ8uGThRqoc7J+2ExQdR7wjd62M= YCuG6YjxpJzo6AH30apf7fLf+FS/+4NOJHrEt7gxqWHrsdwdr3v4e/Bh7EPYH0aNGjTNvb7z/fh= +PmcGPmHG9g/QP7tP0dLn8n7t1/sNI/aKf0gub2D9A6fn6XQgHT9268/6jSIf+o58P2D5D7tdzf= Cp+afZz6wn8hU44w+Df86c8/gR/OU+Ed9wX4es1/WxkL7VyurcPR/fxyb39Q9l+2dC1UfuC/D1m= v8AryxkL9lrlQH9urbfR/jAG8m9c+z7hFm8/m8rlQ+Q+nyHy1sPvL27l888/wDC9Bt47fEcQfu/= IHevkp/7FN97z/8AuHIy/nfpD/DXLXEDlHnz9nv4/u/V8+uWvNcbADyx6DA8eFxe2EePSBvx9yf= UtQP8Stem4tjwB/I02q+X/N6w/wDYGA0o76QN+PuT6lqB/iVr1PTAHX+294fwJh7FErhLM0vOY1= xdSKM/fx61JSipGSqtajoVy6ZqubER2Ri6csjqonXaFXKgconQBQBT1cFGeGLSpb0Re3h6Kj8b3= 8rYrjTnpJDGJSzNtzfoJoFmXWObQ3fnIBAXUYNLEieOBYS/LFMizqR8Hv8AkgJle0Oe4dRwtK71= boKY/TdCoKDbeSogwA4iJStPgq6LGKmA+QE9bVcjwHl3Cb5+R1BvfZvHue/fcGfJj2tnr7IGEdT= Me0Zk6UmXUVCoul1GjNV0m2bjIy8nIvl3TpRBoiU67hNsgmKSKZhum364Dl9tfRF244usjUGdra= Zco1itbQUwTVZ2C2w+RrE/jnIAI9zmL+EU4xYwiPJ2YgA9oFAHT/lrArGzGRdvIbE7+rx8Lnk2w= Y1rts3CWnbh0Lcq2qjSjmDuNu3BWTG8BNM1VG76JVtcfViSb5iukdNZu+bwLOWFk6ROVVo68F0i= YqiRB1FrpfdKtTqARGQ8l3rI0vRKBUrGnVUHULHNJWxWe1rRzealP5+TVFu0aRTORi1nK6qDpZ8= vJFIQUhQVUPurGWJrBlXoJ5JNWmDqTksc7mZbJSzFkkdZyrEQTCtx86uVJMBMZOPh5l5JuB/Mbs= lT8cFHXe6M/VAwhs5ouSML7gFJ+ArFiuf3QqrcYSAe2VBvJvYWLgpuEmY6IKvLolVSgop1FOmce= 9R8Qz9N6ZoX1Y6tAzBJDHcPquSPlWGnYbDz999htgxA7qf7J6jsRztW8TUu5WK6xU7jaJuy8nZm= 0c0fIvJCesUQoySTjEkm5myaUKisUxiiqJ1lAMIlAgBNTrrgATOybgOP6Llc/ez1HbrIbrsJ7v8= AcnUMj4Isb+zVOHxLCVN++ka7OVpZKbZWa1SThsVjPMWDtVMrSVZqA5TSMgYyhkynE6ZwLInrsf= 8ALWyb/uuVz97PSlLE0976rPe/N/Rvfje1/swYnnuk2JY4z50yMGbmLLZ7bE27b7sLq0jWIaGUi= yQUutF4/YWBEk0V0wcPTEO6IVJT1Ry3EUBECiU/ytVOdJXp4Yt39TeaI3JdtutVRxtG017EqVBS= ITUeKWJzYEHRXvwrHvymIiWJbi38AEhAVFfE7/kdrJtjZun/AEP1mrJA7lwfp8MFCIplEyhit8N= tXKvYUAEREqKSh+AARECjpfvojb3Nvmz29ZyT3AWt7SYnIdbqBYCwJ12fscd6/WX84d3HPUKzHS= 8o2XcoTKazNYY8zMwNnKa7lBUUCLoRpOlJpuSHstuRcjgePjt58DwwYvQ3ubD9mQ7ZNvVA3I7gJ= vEGMNtca7qtOtT6ZrcbJ2VWSjItn6m6QexTxSZlxaQBXKMfX48zsxQdrA1MiQfDo1yDtV6MKNLs= 6+Pd/t1Vu7aFknFXbzdNtDmHeTbdqqrHMn5EMYsVBavXREmx1U3iPhFV8YDiBRAcl6+eYEsw5b2= 0WanWB9O4Ws2A2l5x87FtKR8XJuLJap5KVl28ZKtmLlu/XjY2BSckeNUHqaCTRNZNMOAHEavhno= eucTRMnYd0ua2+T1aQk8k4ZWu25u3SuhogVlowSMsSvY0jUkwPqpTIS7pv4HaYJBUOVxrGpCKxe= UFiTaMXAOoXvcbX8duTxgxnfo9OT7VAbpMj4mZyzhakXjF87PycT4igsDz9SfRpImaQQOYCouvU= JKRaLKkIU7huukC3d6ukBNK9HTy6o9T/AO0Zb/wqX1k/QIKiXfjKFbGMduGHMjAgcwCBjog6hQS= MIGABARIBRHkAHnnyL7Axfo5/lRql/t8tf4VL6UdjUeuFQdgLkjk2Gx24wYex0aNGrHBj5hhx8v= p/b/nyH/PGnb+mPug26xezDA2PpfN+MIa6Q1Vex0vWZe5wMZNRrtafmFyoOo989brkUMg4SWAhg= 5FM5TB5DqYqWwDZKimCZNqWAuAAAAT4wqShvL2dxjxRjmH5+RNz5j566T7p47HpAhk19qmC0wMA= gJmePK9Hq+fuWYMWyoD5jwIHAwfMPmOule8vvk7Kd5WV0OVVeUdocqSgrzXw1FNJltUXfoSQaJI= ZZIRpIl1ArKpBXk74537v+6ftX2AzKqzKkzLs/mTVlH8TlgqP2jTqqGWOYuksUTsGBjCi6EWLbC= +KLsldC9zle43e/wCMd3mNp1a42ixWpCIc1U3qzU0/LO5QrI8vA3GfOsm39a8EXZYooqgQFAbp8= imEfIvpJdTba1akclYHsFSlbNFlVRRk8V5B+DZRzHmUTWVZvI65xlWQkmLk7dAXMUoL9BwciZTo= q+GBgYk+9hbIUVwdReEWVcclMJyOKpcsh1VVI/PICiav2yO8HtH2An2lD5i+Y6y2P2T1GsKEVx3= mbczjoyJBIg3h85221xCQcBxzXMpGyBXVezgPDBeLV7A5KTtKYwDYU3fnn8FIMvbPxm+XdFaV8v= 7S9kctNLLTBFToTyZVmRllQqoUlo2J5Oo3GLubuZyiWpFcMjbK6/rGpFbkHauv+MRzs5kMsK5ll= 6pE2tmZRHKgUGwIxWJhLqr7gMKO2FD6i+3e94/Ap0WKWbK9TpRKFU7RRQ9btUKgm4jVSc+M4dzV= RkFETAYhG9ZKUDKDeNjXKuPsv1aOuuM7jAXarSiRVmczXpFtItDd5QOKKwoHMo1dJ9wFcNHJEXL= c4CmskmcBKGlVMRZ6jWS0WnnCuZWhVSim7ic54krso6etjFEpmoTeM3mN45qKhOSqOXtPnAEBER= bnHyHT8Bs4j69Z396xVDIbWMmqqFdPZPDk+Wfw/eBSIUCsrzi2Xiq3FSZHInUUdqx8HBzyIGOpH= 3JB2JVR1vntV2RzsvV0lDT9m8wYkuuUz1VVkU8htxl+YRQ5jloPnRvXwLYKlKgBbE+yOn7V5MEp= qqqqe0FCoCr+1IqenzmFRYEiuopJ6HMCABYVgo5XIJaqJIU4Pu26S+2jehlcMx5ancpR9qCtRNV= KhTrLBxUQMZDLP12igtZGry7j1ox5FfxlAdgmcoJAVMolMY8Yx9Hh2Of61Z+H/wAbVX/4Hq5KlW= S4mTJCZGgWUVZUQ8MZauquX1QsAJ9oeuxKrwicjEqr8gqpBTBTuGRzKNmknOINhk1doB7A492oM= TLCxj6lwttJRleNhsQUYCxU8jg2NioOJ3FIsqBwGW/KupV12BsyncEXsRxtsSMVfbaOkJsp2wWx= jfapRJa53iJcldwlmyZN/GlzAuiB/NOoiMTaRsA0fIn/AJxvIhEGkG6nB27lIwFEJK7wdoGMd62= K2WIMsPrXHVZjbYm5Ir02TYRMsMrDMZZg0TO6kYqYQMzMjMOhWSBoVQ6hUjFXIBTFPKzRpssxIY= kkjgk8cceXGHMQs2+bZMF7A9u9vocBK2FfEkO4tuRLXIX50zsDtuzcxLUbEdyEVCME3MYjGxAH9= TJGrrGDxigK/iFTLQblfF3o+eUbW/tjXOUvjJzKOFnT+Kxs6t8ZAKul1DHVVbQ85Q7C1jCGOYRB= rEgxZJ+xNsTz00Xk2gxWVMeXfGs66fsoS+1SfqEs7ilG6Mo1jrDGOYt44j1XbV61TeJIOTnbHcs= 3KBVikFVBUnJBozD0cjZn8+V9y30BacZ//VIfu05GwBJZ5FJtutiSPG5P2YMLFbxaFtXic7RFD2= OWu7ZRoL2Er0eM1Z/EcyEtfpaSeJOI2ED4u1xw4YpNloZsn3RYGPImeESXXTAgg5juH6VuBt4cX= hiQzbNZHYT+LMXQNBYlo89DQzJdBmzamdKO0ZKuzaii4u0zgQ5F0iFS4KKYiAnHFdsfRV2a7YMh= RmUoZDIGTbnX3Sb+rvcqT0JLx1akUgEEZSNhq5WKvHLySAj4jV3LIyZ2K5SOmINnSSSxLcwDtKA= eXkAfR5aVLNq0BC3oAgsdi17He23gMGNW0DE1Qx7h2pYOZILTNGp9BiMbNWliFCRcSlXiIJGvJt= 5sybZs1eqvYxEU5AStEEHBlFeG6aZgTCoyz+j/AGw+xT0nMsVsw1FtIvFnZICt3eN+BY3xzioZt= HJzdXmpBJqmJuEEVpFwKafaQD9oAGpOdSLcHdsT41qdHw9OyrLLOTbvARJ2tJhlLVkuHxe2cLOs= i3On1huyk13D2FiW4IJvlGKqbRR54rcSPSt1EvVttzcthJFlEDH2i+1i1Ud7lGhNsh2Obir9T8W= 4+qDJxka1Zel7vFDMxjhxZFGsdXIp8WUkJCYmCtlHkXHFEsbnqbszm0+W0eZU+gjMJatKWnLMk0= sdF0etKTIFjVW6kjREvZ0palrjphXjNR2qyylzKsy6YyL8QjpXqqgAPFG9Z1OlEFTVI7qUQS2T0= GqKcWbqErmmUOmntYzHt/xht4yFXpqcreGoJrX8d20swVhkCvNGrVFmoqjYGLJBsuZ+i2R+EWjm= MWinayCCx4/xUETEhKHo8uxkef8ASvPnv8rtVh8ufm5of6vnH+vUbEc+ZssMNlFmtnXI+OrFmC5= xRzwDNKnuatSY++x8hkHIrhaYsEJK2qKNg/BUbBml0KzI1VCPs87FlFY0i7ci6sDZ7zbDQcSsr5= ANbTf42tuquFhgcnqR7W9zNLtFWKGOlq6vT6vB1+ItVxsEzUjepTLayKuWko8QO9Tfxz8kbl8x7= C5xQGBYquCskqKgQLFEJY1DyR07oTLUJHCVmmlenjZXdGliY6lB2xWX9vssrhM8kFRSwQQmZpZD= HISFklVwIoneYNFFGs8qNGrqkigBipOMs2mdJbbRszyorl7E85lOQs6tZlqodC42SDlIkI2aO1O= 7OVtH1eIXB2UWiQIqC6EhAFTuSOIlEvQ259IjbDtgznHbgseT+Vnl5jTWAyDSzWaCkIExrIg5bP= xUZMqpGuTgVNyoLYCvieGcCifxClEB9FBdQ2OLZso2Bmzs9siDO7TKwlZlJGqwdWpuMcKwUdF5B= yLH2JtEqSkmxs2QHkjV4NnIKSQzNihnLeKcsGCS5086wBmOe3R7lGGQvAnaLScXYdjYQaG6kzLC= +yxkZhXLhc2MsDQEG75TG9edVSEcC7bpmZzkzINyJNnSbpEmKn7K51Sw1dVXRimpqal68kzspJk= 0osVL0Q4l6jVDinZivTRg76jGupsnB2uymsmpaaikNVVVVSII4UDACIMxkqjKU6XSSBTNpDdRto= 9IfUFs5DzAPoDRoDyAPn8g89GoxiTXP7p94/X2/wBnbzo0aNGFYNGjRowYBDnyHXHsD3eX6/38/= wANGjRbBjiKRRAOfPjzAR55AeeeQ8w41+geQAHu0aNAFuMGDRo0aMGDRo0aMGDQIcgIe8ONGjRg= xSluWhYKB6iNXd2trJ3GEzLgYlVXhUJ6Tqi9bQoVwQtaiLOYiFFHD6AtaqBI+01pZu3ZzDEy7WQ= cO2LlwxUmXB7YsKZrpEBYr1TgcjMU6z1dvHRM7ZoBgwx9c5pCxjRVEISaYISEPDPmEW5igcIlSj= 5Fgk/iWsUHY1SNGp/n9ZV0uS9lKumqZ6eoOUQx9SCWSIqsM1VTx6FRlVCIYYkZkVWk0BpGZ/Sxr= 7JKOkqc57T01RTQTwDNZZenNDHKC8sdBO5YurM46s8rqrlkj1lY1VbKPem2J7XzOju1saouVV/j= eV2V3YbU8SfEvrRiytSb9JzOKleJygR7V2Yq/ieBJEUkmwpPVlVj7AU2z4eVx1D4tc1x09p8FMQ= NgZNntgsTqUVl6wq1VhHkhYF5U87JHYkZNGiRH0gukDBugw8P1NFNEpo1EJM5zaZozLmdfIYWDx= dSrnfpum6NHqc6GUyOQVsQWJviXx5NlMQcR5bRRiRWSQJTRKHRtIZXso1KQigg3FlA4GNbr7Cdr= a8c1ivucGbsW1dkakZFlabixF7XJKbb2MYiUUaWBE8qyj5xqhJQyUiZyWHckE8aDYTn7t24rwbj= LDKU+jjquFgi2ecf2GZMeRlpVZxKSjlZ8/UTXmH8gs1QcPl3L4zNsok0B47cuQRBZdU5zRqlRmu= Z1cbQ1WY1tRC79RopqqeWNnLBixR3KliQDe19h5CyoMpyullWamy6igmQaUlipoY5FXTp0q6oGA= C7AA2AJtycbg0aNGrDGQx//9k=3D" width=3D"162" height=3D"85" alt=3D"editorial1= .png" style=3D"margin-right:9pt; margin-left:9pt; float:left; position:rela= tive" /> </= p> El art=C3=ADculo queda en pr= opiedad de la revista y, por tanto, su publicaci=C3=B3n parcial y/o total e= n otro medio tiene que ser autorizado por el director de la Revista Ciencia Dig= ital. <img src=3D"data:image/jpeg;b= ase64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/wAARCAB= hAN4DASIAAhEBAxEB/8QAHwAAAgICAgMBAAAAAAAAAAAAAAoICQUHAQYCAwQL/8QAVBAAAQQCAQ= IEAgUECg4HCQAABAECAwUGBwgAEQkSEyEUMQoVIkFRFmFx8BcYGSM5eIGRseEkJSgpMjM4Vlh3o= bbB1homNWeW0fE3dYOHl7KztNX/xAAcAQEAAgMBAQEAAAAAAAAAAAAAAQMCBwgGBAn/xAA6EQAC= AQMDAgMFBgQGAwEAAAABAgMEBREABiESMQcTQSJRYXHwFIGRobHBCDNC4RUjJDJy0VJ0wvH/2gA= MAwEAAhEDEQA/AH+Ojo6Ommjo6Ojppo6Ojo6aaOjrwWRjV7K7sv4Ki9/mifh+Konb8V68u6e351= 7f7O/6/wDr0yPfprno6Ojppo6OjqGXNHnTo3gzgAuabcsjzLW9lnDwzAcaiGMy7LzxmscSleMWU= IIFWV7ZYpLS5sSRwgmSRRRqUeQICTIBJCjkk4A9SdNTN6OlS7H6SvaqaR9UcTQG1ySOQX6y2wRI= Y6JFXyOn+FweKFsjm9lcxnmaxV8qPf28zs9gn0jLJMzzfD8QdxapAGZTk9FjrzmbPOneE25tBa5= SmwOw+NszoEJWVIlkjSTyeRXs83mSzyJf/A/iP+/j9YOmmlujqr3mT4svHTg9tOq1FtrD9yX2S3= GH1ebiGa/x3DLWljqba0uagaCcnIdgYsa2waVRGSTRR18o7YJBnMKfI+SKGybGL8PK8boMnr4yY= QMipqy8CiMZHGXGJahwnDRlRwzERMIZDOxszIp5o2yI5GSyNRHrWQQASCAexIODjvg+uPhprOdH= R0dRpo6Ojo6aaOjo6Ommjo6xtxZQ01TZ3BDJZB6qvMsiGQNY+d8AI8hUzYWyPjY6V0cTkja+RjX= PVqOexqq5KxeHvi48cObW2Z9N6ow3dNFlA2K2+XSG59jeFVdGtbSlVoZULCcf2FlBynPltB3DxL= WpA9jJlkJjVrGySASCQCQO5xwPnpq0zo6OjqNNHR0dHTTR0dHR000dCqie69eL3sja573NYxqK5= znKjWtaiKrnKqqiIjURVVVX2RFXpebxEPGsrNRW1zprikymy7YFdIRXZRtGxjjtMQxE2PzRT1uM= gI5IMoyASRqrOcW92P1hDGQqNeTKUOD6faeztwb2ui2jbtC1XU4DzzMTHSUUJIBnrKgjohjGfZH= tSSN7EUcj4XXmt07tsWzra9zvlYKeHlYIUHm1VXLjIhpYFPVK59T7MaD2pHRedMNK5E79/u7f7f= l8v1+/5e/WpN4bu11x51lk22tpXzMfw7Fg1JNK9NZyzCH/AGAqmrDYqSH21oSrBK8OJUWaeRPM+= OJskrEFMr5x8ws3vSMhv+R+3yLWchxSJXZtd0wQz3KjlbX1NKXX1lfCxU+xAEHBBGido42p7dTy= 4veLFmHwJGhuccK8huOGcDNx7JDcmGSyznExCnpG24htovJYZELXPVpckRksuQgvgiOoLYYsSIE= reNd/DPue1U0FwkrqG/RU0kU11tNoaanuctGrK1THapquL7PPVGESeSsqxeY+AiSMQjaapP4htv= 3OaahSiq7LJURyxW26XMRVNvirGUima5RUsgmhp1lKmVoWmCIGLMoHVrqG3vGH5OZryfpt74DdE= YThuFFFAYbqmYh5eN2GJFER/HBZyJDLFDdWeQDwRPsjIlZJVTtgbRECPChLc1zwt5p6t5qasCzz= BS21mSVzBhM+wE0qGW8wy9fH3kGnRiRvOpy3tlkpLuOCIexGa5rohjoTAhk8OdnBMvjQdUbT1Td= rtDits1YrTWOza6SOxjrxrNFIExfKDBG+gy1GiV0Ydg6MWG4ige9IBjoTQRox8beSe1eKu0qTa+= pL2Squq2Ro9pWTuklocqonyMcdjmSVzJY22FSc1qd2+aMkIhkJ9fOLYDDExbb3L4TbL8RtlWyr2= HFSWyutdG1NaZVjaEzGn/n2i+xnMqViT9YmlqA1VTVRkZzJDK4OrtueJ+7dh7ur6feclVcKO5Va= T3OFpPNEXndCRXWzuGMUlK0IUxxwutNPThQhWSJCP0dEciqiJ9/f+jv15dQz4Vc1NWc1NXC5zgp= Udbk1XGMJn+AllRS3eG3csSq6CZiJG82nNfHLLS3UULBzxmubIkB0BgY8ykd5vdO3bt+Pv/N93/= H2/P1w1crbX2avqrXdKWWiuFDM0FVTTr0SRSqcEHuGU8MjqSsiFXRmRlY9m225UV3oaa426piq6= KriWannhbqSSNwCPiGU5V1YKyOGR1VlI15L8l+72+f4dIDeMvvK53Pz33GARYTkY3qGxH1Lile9= yejXR4oNDDk6xRtRGeqdmMt+S+VyOlkh+Ehe9Yx4mMf4d8l/Qv8AR1+bnz9DKq+cvLuCwa9Jf2y= e4jfLJ3VyiWGf3liE5O6d1Y4Aod8a/JY1aqL2VF6qphl2PqqnHzOPePz192mi+Ffge8Uq/QWvcj= 5E4XabI2vmuL02WZOh+S5DR1mLEX4EFnFi1XWY9Z18SrSDkxAnnGSmEG2UJc8TxxJIBIJlUng8e= Hrjl1UZDS6FgDt6KyBt6sr8ts9lUawrSYjAiEjmySSKT0SIY5PJLG+N/l8r2OaqotiOFXNXkWHY= nf0k0BFNd41R29RMM9r4JqyyrBTAJYHs+y+F4s0To3N+y5ioqeyp12fqkySMSS7c+gJA9OAPQcf= XGGlqvF53fwS1vycxeh5McR8n3tn5GpMbsa7MKbZllh4oWNT5Nl8AFE+sEIhjlmDsBrMxxisV8j= D2RKqpC1G3iZTv7TXH/jvR7h2LdDa61hUYZjBQqHyT2BIoptSI6lx4CGBsp93bvidCCKMJDMSXM= xX+XyJJIxTf6RD/AJcOCfxfMK/332L1tLx6Nn3n5C8GdNDGkwY43T7dk24EcsiC2VuRXUONUU5M= KOSJ8tOKBfNFc9rnRpck+VW+de9vlhvJGT7Wc85wAFPAPbJP6e7WR7D69FP5k6mTk/0kXj4BblC= 4hx+29ktNDI6Ma2urrEMXJLa1eyTNqxysldDFL7ujScxk/kVqyQQvVY2y64f+Lzg/L2i5CXtDpr= LMLj4+6sP2jaD22UU9o/IwwQ7gx1UA8OuHaEVI2okYhBKTRNWZjlj+yqOX64b8s/Cg0PpfHMa3N= xMzzde3yoZT9gZtkmGa7yetmt5yp5I6zE4MgzmNaygqQ3DgDujrgS7OSCSzsIo5yUGGua4w8huE= PIPjpzisuIvG5dDn4toHNQc0MnwvCcUIyES2wXNJ6oZkuI3Vu4yEKYAqV7DVgbE+ZjoUkV0nlmS= NVBxG49oAMWGO6gnj3jOPoCPTt9/4cfr+OtHp9JR1Inz4wbGX3/z9xn/+N1tPT30h/jLn2b1OKb= D1dsbUdTdFjgQZmYfRZbQVZJMrYo5shirVrbavrEc5ElOAAuXQd0fONEO2QiKmnwN+PGl+SPJXZ= GIbw19RbGxqn0xYZDW1F+wh4odzDl+JV8Z8SDEDvSdgZ5kCK56t8k70Vqr5VTvnjq8SNB8XNlaM= n0RggWvAc/xDK5cio6ck6SmmOxy2q4ArEYQ4kpQyphrR8BaDSRjzIMPL6DSFImny6IPM8vDAkZU= 5yOQCPo//AIIwcfL8/r+576cW2TujWOotZ3W4dh5hUY5rehp4rw/KSZ0mAdXktjcC4D4ZJprIiz= fPBDVhgREFWRJA44cM000bHUO5n9I+45VN2WDhGituZlTDTSRQ3trZYriPx6McrUIFrPishKjGl= 7eeH414RXpua6cSCRXRNr28Unb2Vfud/he6uW1LfV5xq6XO8rR8r/NZm4Li+E0OKtJf8yIxY8sv= ZVjkVW+swWZzXSRRuZPvwm/Cz4mZ3xB17u3d2s6zaufbZ+vMgfLkxdm+rxuhFvrGmo6WmrAzhAm= ueHVstbCwJgmsZTrIgRpDARhoG1qkaJ1yAkliqgHHYj5Hn8O2o+vr8dSv4W+Lbr3njlWzdcVGls= twiPENXXmc2hN1lNRaQWtWLOLWFVMDK4ASYcghtgqtIc9zGNav2VcqKkJfCU3pwK2LynNx/jZxB= yjRuxG6yyo6fNLjZ9nl4ktAPZ47HY07aosmaJsppE4MzCkb54mivYi9pXItz2GcLOLvG6r2Ll2j= 9NYlrrI7jXuSUVlbUMRrCi6h4MhrgZVJMIZ6DihYJ1RrGu88Tftdu6Kqn9Hz/wAvK0/1IZ7/AC/= 28w7qQqMsrL1qAuQpOeQBnIBOf+9T6H7vw9f21cryg8djXHGHfmytDXOgM3yuz1vdD0xmQ1uY0N= cDZyEVNdapOMEVVzzwMbHYMhVkkr3K+Nzkd5XJ1pui+kkaILthB8j467YpKaWVjDLOqyTEsgNEj= c5EdNHVEfULCvIi+ZzEsoHqjVRvmd2Rez81Oa/hE6n3tmeN7U40Ue+tvj2XpbGyPF9X4JkLgsiF= ghElrL3JcpuKNbG5BgggFMiBdYIBJD8AVNCUPKPHTvzo5ZeGHvrShePcc+J2V6V3LWXVLZYtl1f= h+A4nSTBJYDxZFVZMmLZdYT2IRdJIZIAySrJkGuIAJI5hh3lrJkkaOFBhkBOAWyAOQMnB7D4YPH= YY50Hyz9D/AKP4/DTqWkd2635Eayxbbup8hhybB8uCUyqsY43jzxvhleMbX2IcqNnAtK0yKYOwC= na2UcmGRi+ZqI5dr9LufRwr6zO4ubtoCSZJq2h3m8qrhkVzvhFu8GxZx0UPmX97gkmroyPSaiNQ= iciXt55XqrEfXzuvQzIOQpwD8vrGo0dcL8vn2/Ov3e/6/wDHrnrhfkv/AJ9vf7vf8fw/P1jpqiT= xsedlzoDXNRx71fbS1eztwVRh2RXwMvon4hrZs0tbO4CZqpKNb5gbGXVBGRd5AqyvuponDmS1pM= a1vCvhnsvmxtqHX+Eo6soaxo9psLOzB5Z6vD6KeZzEInTzM+NubFYp4qSpSaOexninkdJCCGYWN= K3xunZCviAZ+l18Ule3Dtdtxf1/P6C0SYwGsihK77PofXjrn1PJ9n4z4nzL5/N0wn4KWs8Nwjgj= r3J8eGEffbRt8qy/NLaNrHFnW4eRWWMggzT9ll+HpKijCBHDV3owEuPJjjZMcS6TtKku8Hg/4GW= W8WCnhl3Bu4UshuDIsix11xp5atZpz0lXS2UcLU9LAT5f2kdbIS0+eQqm1zeKnjJdbXep5I7Jtl= qmMUKuyM9FQTwUwhi5DI9wqpfPqZ1HX5DBVf2IsSd4z8BeMXFvEwMfwDWdBYXsQrYrnYOV1lff5= zkhMkcbSirC7NGkeJAQ5iK2np466kF9/hq+N75ZJIE+JN4R2A8gcZstm8dsVxzAN40kE5pFLTCC= UWN7QGRr5Zq6zEGbBW1+VOcr31l8kMKHSr8DdSPhlHOr7x+uHNRyKi+6L/X/AOfXLlp37u2z7gj= 3PTXuuluwm82omq6maoStQtmSmrI3crNTSLlTDgLGMGHy2RCvSFz2Nte62FtuT2ehhtnleXBHS0= 0MD0bquI6ilkROuKeMgMJQSzkESl1Z1ZFvhjzNseMdnmfFblZhZ+a8acysD8U2frHKQJ5bjXN04= hwljfUdeX6ZQRIJcaT2tYM4YpJhorammFuhInldQ548DLHjEXR7W1faTbI4s7RQa21nscRFMSuG= uIFOr8cygmJjGQWLRlclefJFBDcwwyOa2A6EsOFsLkZ4ZfGXkzurA93bAx2ePIcXMikyutp3RBV= O0a+vh7UtdmzYmNnISsJYM1xY0kRh9SySkNllEcLIFL/ZWmtebU1TkumcsxqrM1/kuNS4wRj7BI= RwAq9o7Ya9aweBkcdbPTSQil004TYZqwsMQgN8Mo8Tm73Pj1Z7duCy7ksFpraSa8RoPEKzl4xa6= meN440rbenLG6IqPL9rUQipp3ip6pWm6pItJp4JXiusl1sN6udJVJaZCdj3XoJuEUDBpGo69hgi= 2yMwhNKWcwTLJPSssTBJPz2eN/I7aHFfadDtnU93LV3dTKkNlWyySvpMooppI3WOOZECx7WH1Ng= yJqOa7tOGS2CwAmGOGHIjfU4e8qcC5haUx7b+CvQVxfmqcsxmWeOawxDLgYR5LWgPVnbzem0kcy= vJVkaHVRgRjWRrM6KNAzfGrD9I7o2hqKynUkrXmbZBiylq3yKZBV2M8AZat7qjVKDQchzWqqMdI= rUXsnVqHga8iLbVXLFupCTpUwvfNQRSGVz5f7GgzHHhDbjF7aKNyL/ZT4m2tK701Yssds183n+F= gSPa3jnsO1bz2e29bTEn+MWq2R3SGsiQK1zsoiWomgqCAGkMNMz1VK7dUiMjQgBZWKa28G963Da= O6o9qXGRxaLlXvbZqWRvZt92MoghngU56FlnVYKhQel1KSn2o1y6OvyX9C9JX+PTw7yvWfJA/k7= QUpResN2Q077+0DFc4LGdi1NSNSnA2T4WuYKzIwKsK6BJIcxTrGS5jb3eOivdPavfv7/1ff/V3+= /t1g8mxbGc0orPF8xx6kyvGrsSQC5x7I6sG7pLUKZO0ollVWUBIJo0iez4CYJI3fe1e3XA0chjb= qHqMEe8HB+7sNdxaSe4keOvv3jNqPGtN5HrXENx49hFaPR4Zc297b4zk1XjwieQCjsDRBbYK3Bq= RkYFUuUAIsUGKEWYkqOGFI5p4B9Iw2DmedYbiE3F/DgIcpymgx6U2PZV1PKJHc2otc8qOB2KRtl= fA0lZWxukY17mo1XtRe/VxFz4QvhxXtiTaGcXMQHJLkdLLFTZFsDHq5rnL3VBqihy6tqgo09/LC= GFBCxF7Mjant1xSeEN4dWO3NVkFNxtpgrejsgrerMbnO0pXCWNcTGWES2IjOJYJHQEwxytZNFJE= 5WokjHNVWraZIDn/ACjk+5iPd8f2/U6aXK+kQKi84cE7Ki/3PmFfpT/rvsX5/wDonUrvHG435bm= XG/iRyOxSnKtq3WWuq/CtiuChmInqaHJKbGbLGrsiKKN6xVQVuLbAHlve1kE9zWo5PI58jL5N/e= H/AMROUOaBbD3tp2uz7Ma6gDxgK6LybN6eWCirzbCwEAaLjmTUwL2QmWp86TSivJcpDmPmdGyJj= JUwYtjsGNwYf9UBEYwPTQ482jPhSxr5aSANteysKgP+JaaKoTEGljM9f14vM2dZPM5VjzsCLpBz= GCDk8NkAenPYf2OpJ5HwxwfgAD+mkkeHXNPw0cL0rjeE8q+ElFmmzcWjnq5diYxhuNW6ZrUxkPl= rLO+ZY3NOSNkQ4ksddZSMjMhsnBx2riWEmkCw3F8XuSfBHdOiOcGN8NdBGaUNpuOWcXecSS4vR4= 7BfjTYbmAFOxHVF1bPKmClcY5EmZC2Nk6q17lcqNnTk/hJeHVl1wZeWvFvBxjjpnzkR49a5piNX= 6sjlc5R6PFMnpaQJquVV9MOuHjRV/wfl22jpzw/uImgANiVeotO12HAbXxWfCdgDjZNnFmmRYwT= CaPPVTSXmT2koUckNgYxSKt4RjfWVzCGuYxWnkjYEgOGJU8tlRggkY+Q9fh276jSxv0cdU/bc7b= /ADaAtU/lTPMG/n63P9JUVPy+4rp+GIbK7/y3OL9MKcfeBPEvivllpnGg9QV+vsou6KbGbS1EyX= NrmQujnNCspQHDZLklyHG15tcHP60I8ZCLAjGzJG+RjsvyJ4T8YeWB+M2fILVgOxTcOEsQcamLy= DL6RawW2mGIsImNxnIKWMhCZgx3q4tk72emiROY1z0c80ecJB1BQMEYGcYx78fn+Y1Ofazz3B95= /bS3viDcasu2n4UXh/7xw2pMu5NDasAGzEGugeQWLhGfY7jCl5G+KJHSyhY/b4nVxm+RkiiB3BJ= 8iRiilzR9F8ObxusY4ocfaLj/ALo1bl+Y1uCF27cHynBC6RbB9HdWxd2+lv6y/sKqJJKuxsD2gW= QR0vrVsoYM1fDIApZjduEa4wrXWB49rHDqAWpwPFaEXF6HHHyFWQYVAEMgg9Y+W1nOLNgaMnovU= 8gmSViqkz3+ZyrCjMvCg8PLPL0zI7/i5gUNmfI+ctcaNyzCa+SaRyvklbSYZkVDSQvkc5XPfBXx= ue5VVyqqqvULInSUkUsAzMpBAI6j2P3fnx251GtJ8VvFf03zwsdsaz11rvZOIWuMamyfMDD8zZj= La+cGJkdU4UdaS9tCFKWexikRJII4vSZIqyI5GtdQB9H0/wAvG1X7/wBhDPu3t39/rzD1T8Pw/H= v+HTWGi/D94h8arzIck0jpyuwW6yrGy8Rvzhcnzi3fYY6dNCQVWviyHJrceFksw8MizjRQktWNG= sma1XIvq0N4e3D3jJm8mx9G6ZrsDzWalOx6W8FyjOreV9PZTCEGh/CZFlFvXo2eYEV6yoIk7PSR= scrGuejiyIokAVsOuFBIODxkk8fhj46aR7w+31vonn5ldhzX1jc7TxHEtpbSg2bg7nerYXN6W/J= Iau3mHLsKyG5EiyAqtyFRibCEW0CYkrlMhkaORMvmXyx8LDaHHjN8K40cS59XblticWfi2bPwXG= aZlVBXZXS2N9GtjXZJYFj/AFhj4lnXIkQkiSqX6Mjo45Hva2JvbgBw75LZJHmO6tD4hmWWtgiGl= ydst5jd+cOO1GDQ2ttidtRHXEYsbWxCNtZzUFiRIx/TZ7daK/cbvDY/0Y6X/wAe7Y/586z86MlW= KyZUAcOcEjHpnn+wGmq+/o26p+125Cp/301f+41P/V7dMedR748cVdB8UqC+xfQGvRNeUOT3Ed/= e14lzkt0w+3iChrojHzZNc3RMLmBDxQekPNDAqN86xK9VcshOqHYM7MOASTz8dNC/Jf1/o60nyA= 39rLjTrDJNsbYyEegxbHx+7Uc9jrK7tJfN9X4/QAueyW0u7SZqQiBQ+zWpKUS6AAUsmHdbvkvt3= 9l9vx9vl0qr48ujOTJmV4/uom7sc144VYo9XXUNSLLELqi+IZDAUXkQA7nxkw5NOjUDy2ZvlZO6= PHi1Cd9Vpae38OdrW7eO7rXYrrdobRRVTlpJZD0zVZjKsLfRMymFayrGUheYhFwxRZpjFBJ4rxB= 3LcNp7XuF5tlrlutXTqFSNATFSh8g11UqkSPS03+6VIwzMSoYxx9cqfXyWH1l4y+npdy8egXY1y= u0MDYhZFp26NCdkGa62lNIMAbVksSBls8UiSUqjNga2Ia1Ps8etGQy2FMXJFPwufEnuOGGVE6I3= ZFZt0fe5MT8ahQpLbvUuWEysDs7OMF8aGPoSJ4I/wAo6RI/VDJimtgIPjX2A1jVPp7cOw9C7Exz= aersiNxnMcYMaVXniOX054VVELrbEZf3o6rsYPOLYAkNfASO9zHsVfKqXTbL1dqjxXtVXXIfj1W= VOB81MEqmE7v0YNLGPBs8cWJqfldiMUixISeejFUU2NXSTFJ9RX3lsFq7Wx7KvW1bZta0y7L3LF= NcPC66ThLVdZHMlfsa5TyEwQ1lThpBa2qZWagubjFJJM1JXF6WVWPJVp3LcNw3OLdm35YqDxFt8= QkuNvVVSj3hQRIomlpIAyqbitNGq1tuQ/6qKNaqi6KlGVW56C9p8npavIsftALuiuwRbSnt6sqE= 6ts606CMkM4Ewd8kBIhUEjJoJ4nujlje17XKi9+sv1Qh4GmG8vMV1Rkrdu/HUuhXlEQapxPMhD4= 8xEuYDpWXx1BEW+Iimwp5DSonBWEDmHXXrmU8I0HxhFhfcnsn4fr935vw64g3fYItr7juthgulJ= eYbfUGKO4UT9cUykBwr4yq1EQbyqmON5I450kjWRwoY9j7Svs25Nv228z22qtM1bTiSShrEKSRs= CUZkzhmgkKl6d3VGkiKuUGdHZPwT+br4La0Apaywt7QqEKtrAirA8wiRkUAoQcDyCiZpXuayOKG= Fj5JJHORrWtVyqiIq9feqp96p/KqdLY+NB4kVfR0V5w/0jdxF5HewOA3VllSUj4sfpZU/f8AX9c= TA/s64uG+VmUSMcrK+qV1M5khdialb9GydnXXfG4aKw2qJiZ3V6yq6SYbfQq6iorJyOFSNW9hSQ= ZZSkSZdxqneO7Lbs2xVd5uMijykZKSmDAS1tYyMYaaFe5ZyOp2AIjiV5WwqE6Xf5XbRC3ZyT3dt= St96rNtkZPc06q1Wq+nksZYaqRzFRFa6avhHlVqoitV6oqIvfrbHhwV9lY85+MUFUknxUe1KIt7= ou/dgYSEFHPcqfKNgcUyvVfso3v39uoSonb9U/4dX7+Ahxrss53vlfI24r5W4jp+nJx/HTZopWQ= 2OwMrEcPJCI9zfSn+ocZkNJsGo5ZBZ7mjkVPLO3t+iu/6237P8M76rlY6Wi249mokcgtLLNRi2U= MWBjqZ3eMv0g4AZ2AGSOCtk0ldujxBs3QrPU1l/iulY6DCxxRVQuFbISoIRFSNwM4Bcqq/7hhvh= v3p7d/b5fh29v5+3f8Al6rw8T/ldsLhlxeM3TrKtxu1ycfOcUxpgmViGHVChXn1l8VI4cA6unUh= vwkfovQhGN+15mP7p2sPb3+9O3b+b8fb7/v9+/8AL79+qUfH5/g/rP8A1ua5/pvOvzAiAZ0BGQS= ARzg/vj9dfo+Bkge841S1/wBIk5of5jaM/wDDWT/82dZWm+kW8uRbEae81lpO4rGSMUoAWsympI= niRyedkJzcjM9CRW90a9w0zWuVFWNyJ262T9H+49aN3lXclZNxaowTZkmPG66ZRPzTHK6+WpZYQ= ZS45lep8E3wyFOFHcR6Xl9VYYvP38je1pPiHeFRxYzzjPs/IdT6fxLV+1tf4heZrht1gVTHQpZl= 4yFNcEY3b1lesFfZB3wgs9cyUiBSQC5xzR5u0EkE/wBTtAsnQYuxA6h25x8QeM/lxqNSl8PvxD9= W8+tfXF5ioBOHbCwuUEbYGurQyEw2lWzildW3NSdGyFLjG7OQYwcY9BxiRzBCBDg4HfCymRL294= zdFqjmiRw6n0TbXB4+zcI1uudR5wIEK6XM3Y+kdr9SOx6eZIwPr5vnF+sVcR8MvaaJZURi6Pgq7= ZtdX+INqIEQ2Qen2gNkesckEav71Yh3tVMfTwytVUaij5VUUJjH+72qO5jezZHo62XkRzl1Dh3i= YlaQtOEGhMwy6Pd+r8WXdl0I52ePsb52IIHkzpUrJE+taL6xgSvVCvb6uG7Pj7IjcGhCyMoVnXp= 6h7QUj55745x7/XnTTQqfJO/z7J3656gdzs8QLT3ArAK3J9hQWGUZdlMpgmB66oJh4LrJiQI4nG= lkmFI8eloK5xAzLK4mhLkhcUPCHXnlStGWhY76SnsZ5Uzqzi9hUASvco8R2fXxpTI+6+VJiR6QG= GV6J/hOYLC1e3dGIi9kpSKRxlVyPfkAe48k4/M/vpptrqj/AHn4ztFpXmQbxHI0Tb3xoee4bgy5= tDnAYAj5MvZSOZYfUr8eJlawH65ajoFPV0/oKrZYlkRGx04a+OpsPlFya1JoO20LhmK12yb2wqC= sgrcpvTzqxgWPXN02YcQoKMeZ8klWwdWyva1rJXORfM1E66Dyk5zahwTxIbPS9zwg0FnWWQ7Y1v= Qv3JkAjnZxMbdR4wod/JL9WSd7Gl+OgaA74pfKgECI5ns1uaxsGKvGT7BbAYDHbnqBHbn1+7Tj1= /XH7HV0HiPclM44kcSNhb21yBQWeWYpY4WJXh5MKWXTSx5FmNJj5qlDhGAEvdGHYzyQKwqPyTtj= c9HtRzHaG8JHnFtbnZp/Zuf7ZqMQprjDdltw+tgw4CwABmrVxikuVlKisbKzkeUpVjOzzxyxxpE= 2Nvp+ZHPdVF44viFZWlvubgN+xtSrjD4tW3KbGW2sfrn1UZjGwPQSq+H+r1Z8Uz6t83xHm9FVm/= xnZnVb3h6+Ktm/ATXWc69xjUOObFEzXNkzMiyub22qpwJ0oqyk+Bjirxp45IvTrI5/UeqP88z29= ka1qrmsJaEnpHWWBU556SRxwTz3z8+NNPwdHVK/OvxUc14iaf4r7MotRY7mhvIbDW5Ra1VleWwA= +NTLjOKXyiBTBCzSlxpLkco3qEtjejBWOVFc9/lrGX6SXtln2pOL2CIxPdyrmOTN9u/v9p1b2T9= Kovb8F+S1LFI4DKuVPY5A9cdiQffn3aabhX5L93S1OU+L/wAkaTxI4eIYmL6vfriTkjimoVtZ6a= 7dlCY5eZJTU5ZaGNv2g/WkY9hM+Gb4D4dsrY3PGe1HMdPbw4fFY11z7myPC5cPK1dt7E6tL87D5= 7dl9VX+NoVAARfY3cfBVs7215xYUFrWGgxkA/HByQknwySywLWbC/hzxv48+u/9+8Y6zjj9qRXX= lYyRk9j6dj7u3pydNPZp8k7/AIdHR0dUaaF7/cnf83y6wWSY5R5dRW+NZLUgXtBfV5NVc01qNCb= XWdcbC+AoIwQhr4Jx54XujljlY5j2L2VF906zvR1kjMjK6MyOjK6OpKsrKQysrAghlIBBByCNYu= iSKySKro6sjowDKysMMrKchgRwQQQQSPXSVvijeFxkHFK+sNw6drT7/jxenLIWPF6htlqq0Nl+x= T3Hb1JyMWKlejKLIHedB3+WmuXRGJXGXNVWodv7D0VsHHNoavyM3GMwxk1hdeeHJ+9zMRyIQBYD= r3hPrDofMOcASx8BI73xyMVF6/SMyLHKTLKO1xvI6qvu6G8BJrLiotBYTa+zrjIXwFBGCztfDOO= RC90csUjVa5rnIvzXuml4n/hXZJxdvrbcWlKuxyPj1cFSFnV47J7C51OaQ9z5Ku2VEfMXiL5H/w= BpL9/nkCYqVN4rJ4g7K37Z8G/Gak3RSpsbfT08twmgNFQXCvCNTXyBkEf2CvEuY/txU9ETSALWg= dLf6kAz8eeK/hLVbbqX3hs1J46COZaqroqQss9mnVg4raLy8OKMOOt0TmlbLc05xFfFwe8WXj/y= gxWmpc7yKh1DuwcaEXIcNyOwgqqK7PYxrH2eDXh8sYlhXnvX1mUxREV7WSOmFlgNFggtjrDs03x= pbXVHNkmc7V1/i1HBH6sllc5ZSBDKzt3RYnSmtWdzk/wGQJI+ReyRtcqonX5syL7tcndFT3aqd0= VF9l9lT5L7f0/n6+iYsolGoSSQQjE7MSaeSVGp27dmpI5yN9vbsn3e3V95/hb2/W3aWstO4K60W= yeVpXtjUkVa0AZuoxUlU88TpEOVj+0RVEiqAXkkbGarT/EdfqO1x0lxstFdLhFEscdxFTJSiYqo= UTVVMkUivISOqTyZIEYnIWMHhlrxAvG/gvKy51Jw1IPHHOjnr8g3gcHPWGfCytdGQHruqNjjOEf= MxfTflNsMMTC31Fpq9kii3DFpSiijiSDTiSDDDJpSiyypnzkkkzvdLPPPNK58ks00j3SSSPc5z3= qrnKqqqr6P1/T8v19/w6kdxl4o7q5bZ6JgWnsVKtZEmgW/yUyKYXFMSr5ZER9nkVwsboRYmMR74= BIvWsj3MWEAMqRfJ1ufbW09m+FlgqBRCnt1FDH591vFxmjNTVGMEebWVThAccrDTxqkSs3TBCHf= nUu4Nz7q8R73A1YZ7hWTP5NutdDE3kU4cr/lUlMpY88GSV3d3x1TSkKOnC8cePGx+Ue2cY1DrGq= lPvL8pjj7B8ciVeN0UL2La5HeEo1WCVlaO9ZHuevqEkOgAEZMcUNDI/1xf47YPxY0thmmMBGRlT= jIHmsLOSNrDskyIzyTXmR2jkVVkOtTUfKqK5WCjNGBHSMUWCJmnODPBTVvCPWseL4lDDfZ1ewik= 7D2KaJFHcZRZxMd2GGREe6sxyvkdI2opopXMharyipCLAgkqWciJ/s9k+/29vx/R1xL4z+LUviF= co7damkg2ta5WekRwySXOqA6DcaiPOEQIzpRwsS0UUjyPiSVkj698IvDBNjUMlxugjm3JcolWoZ= SHS205Kv9ggf+py3SaqUDpeRAiZjRWfnqk/x+f4P6z/1ua5/pvOrsOqT/AB+f4P8As0/729cr3+= 753nf+b5/o60pF/MT/AJDW6F7j5j9dQb+jU/8AZXKz/wB4av8A/wBbL+mJ+SmW1GB8fd2ZlfTRQ= U+Naqz24sJJVYjPQCxmylWNEerWvkncjYYou/mllkZExFc9EVBThh4iO++CUGeD6UC14azYstHN= f/l1jtteujfj7LCMFK5a3IaFBmuSyIUhJUJWRUiVix+VyP2Fyo8WvmNy7wCfVexMjxHG8Aspx5r= /ABrXGNz47BlKhkRFhQX51hbXtuWAMXDES2rgsBa2cmKCcsQiUYZ0P0SQu8pYY6SV5z6ALzj1+7= v8NMduRz/b8O/1xnpPhbUZuReINxYCAY90w+0qu7mbE1XK0KhHMuz5HduypHEGCQ96/JGNc5e6d= 06lRzG/hvbD27f3Umi/b/4muv09Tb8A7gdnIOwTeZW0MaOxvHabHbLHtMg3YUwNjkNxksHwd3mo= gxLY52UdZjzzaauJlh9G3JvySA5FbUudLCTmN7+N7YfxpNFf/k111Z1hpXAIwI8Z+OeRqB3Ge3r= r2+Pdmd1lPiD5Dix07/q3X2udb4zQwPcrR4B7ql/LQ2dE7+Vsk9llBDZpkarnMHhY5XNijRrYei= +AHE/TmqsLwCu0drHI5KHH6sSyyjJ8Ix69yLJ7hgUKWeQW9nagmFzGWpvrGPi9b4YVJWiiRQiwx= RNX3+kGcPc7TauP8uMOx2wvMGvcOqMO2WVVCzmyYvkWMzmQU95cMha941Rc0RVfVxnK34UUyk9I= qWKQ8Ns3TdGfSI9s601diOBbG0HQbVyPEqWvx52dw7EsMQNyAKoFiAAOu6t+I5RDJeSiwRraWAp= o8FgWshbQBnyvatLIzxReV2AwwHBzgevHr3B4x31PoO3r8/v/AG1Gnh5W11N439RUVAIlZVVXKz= e9dW1oA8QgNeAEuyxhAghYGRwDCijxRwDjwsZFDFGyONjWNaieXO/+Gluv9f2lv/swbroXh1Z+7= a3i56l2g+rbRv2PvXZudvpWGLYtqH5bSZ7fOrWnuGDca0Fx6jIWogqkJEkqjwq/029+53p/fpLr= 3T/2/aW9vfv/AIvBvzfr93VxB6sHv9nYHPvyO+noPmf/AJ0wt44uG4h+5/bpy38lsc/KtLjVkSZ= N9SVq5Akf7I2Kien9c/DfWPk+E/sbyfE+X4f957en9nqGn0dzX2B5fxu3mZlmE4lk5Yu8GjDF5D= jlPckjjrgmLy/DwT2IZMsUPqSPk9KN7Y/O9z/L5nKq2P8AjIYNkewPDu35T4rVl3FtXC4flT68K= F05T6nFM4x2/vZ44md3v+BpgTjpGsa56xjPRqKvSvHhn+K2V4feJbIwK005+ynjed5LX5cJKFmS= YdbUd0NVx0x7JXT45kY9mCcGJWrHF5K+cKcWZ/qlNKRkFCBmp2VcluvgZ5xhexJzqNMz+JNz343= 8IKDCKPPdTU+5s/vQSiMB1igOODh0+PhLABPb2VpbVNzHi9I+aFlfXoBSmz2M4ko4wqQAEzjUl3= fjs6TyOosqG78M3UVhUW4RNdYBTbBx9GECFROhnieseiEkZ5o3qiPjex7F7Pjejmo5NdePFR5tn= uyeNnKR2OWYOuNucbcBhrZle6xAx3JXl3+YHYwXYxwQxIUlbltdONPKMElp6RkgsHcQhsWyde+N= 7xvw3BcQxMrw5dfTFY5jlNSFT1mTYgPXkk1leOGQYIMbqgsuCEyWF5TYCTDCIvVWOYwp7VIklIx= 5at0Fy3LYk6cEFRjGQeP+P3+umof+CTaen4nGnVp4ZKmrvK/cozqz4p5SxVC6tzW2DrJyvJAprR= SK+vd60kMaSzCRzLCx3ZG5zYX8OeN/Hn13/v3jHWK8Gq2gv/FT1HfChMrBbs7e1wNWsc1zK4ey1= RscyEFr44oY3NFjnbA10cUTFbH9mNjezUy2wk/v5438ejXiff8A594x+b+v83Vh/mv/AOufj6j1= 9dNPZdHR0dfDpo6Ojo6aaOvisa4G2CKrbMMU+vOHmEOBNHhLDMGIYsc45I07HwzwzRucyWKVj2S= McrXNVqqi/b0dBwQwJDKQVIOCCDkEEcgggHI1DKrKVYBlYEMpAIIPBBB4II7jVDnKvwJNE7buLH= M9DZKTojJLKaYs7F2163+tiipVkke+uqfiBbPFFnnej5Ias4ylGiRIa+gEZ7LWYV9H75cxHugF2= DpMsBHqjbBbvKoFVnde0jhXYq6Vq9vdWIrlT5Iq9unFe3v37r+j7vv+f8/R2/Oqfr+fv+v8nW3r= J46+Jdiokt8F9FbTRKEh/wAVpYK+eJAAoUVMqfaJAoA6TNLKVACrheNarvHgv4fXmrkrJrO1HNK= xeYW2plo4ZGOOomnjJgQt/UYo4yTyfitboT6PZitXYgXXI3cZmVDDujnIwrWgElDXmvjkbJ8Mfl= 1w2e0eDMiLEVFWU1UarXOcPbDva16MA6j0tq3ROHgYFqPB6DA8Vruyw1VEG2D15vIyN5tkZI6U+= 2sp2xs+Js7Mos8lyI4giRUTttHyp7/P37+/t9/z9u3b/Z1z15LdW/8Ad+9JFbcd7qq6GNuqGiXo= paCFh2aOiplip/MAyPNZGlIJBcjXp9s7F2rtFXFis9NSTSKVlrGL1NbKpwSr1dQ0k3QSATGrLHn= +jIyTo6Ojrx2Ma9aAB20ddKz3W2vtqULsW2ZhGJ7Bxh5Q578dzTHqrJqV5wfqfCGOrLkUwJSRvV= k9CdYVli87/I5vmd37r0dNTqLn7R/hn/oo8dP/AKM69/5f6ytLw84nY3ZC3OPcZ9C0dsDKycKzq= tSYGAeJPG5HxzDFjUUc8ErHIjmSRPY9jkRyL3ROpHdHU5PvP4nTXrjijhjbDDGyKJjUZHHGxrI4= 2InZrWMYjWta1E7I1ERET2TsnWkbjjHxzyHNH7IvtEaguthvtAbt+dWuucSPy51xWKOtbarkRVT= LbLYV/wAIIgRilqQN8MP6MjPRj8u8ujqBx2J/E/X18NNQB55c+NS8FcZwe121hmYZpVbGtbehBC= xMOiPWKWpChMJWzgvbOthUeWKdrI0jWdXPRyPY1ERVpKtfFp8JOxlNsS/D6DtLMj1p3zHaS0Ssp= RTkc9XEFyHSyeaWT3fM9JHorlcqPX5sZb64r8f+T9fQVe+tZ0uya/FjTLDHxbom3GjrDT4WDFkQ= LUWNc9z54I2RuSZ0rUa1PK1qqqrGn9yU8Of/AEV8EX9NlmX9H5Tdl/lRerFMQHtK5bnlW6Qe2Bw= M9u/Pu92mlgPB815e8gfE3rNyYthkGK69wPItm7ayACkDYLjeF1+S1eV1+G4fXOHgHBgRlxkNdX= 1tdBHC59PVWJA0DIQpPTcjvOMXHPJ8yk2LkmiNP3+fynhWsmbXOuMSssrfZ1qQNr7B+QGVM1q40= FowyCEqV6wyDwei9npM7ZvUOitO6Bxr8j9L62xDWmNun+KnrMSpQ6phxisSNTbQiGP4y2OWNrY1= OsiCi3Ma1izK1qIm2OkknWwYZGF6Rzzjvye559+mvCSOOWN8UrGSxSMVkkcjWvY9jk7OY9jkVrm= uRVRWqnZUXsqduo12XDDiJcGk2Vrxf4/WNgZNIQWcbp/ASSyZ5nrJLNPPJQrJNNJI5z3ySOc97n= OVyqqqvUl+jrDJHYkaa6Vc631/kWHw6+yDCMSvMFHACq4MNt8dqbHFoaytiigr6+OhMEmrGBAww= QwiDMGSEeOGJkLGNY1E0j+0f4Z/6KPHRf8A5M69/wCX+pR9HTJHYkffprQuF8WeNOt8kAzHXfH/= AEzguW1TS2VmT4jrPDsev69h4ZFcc0K3qqgQ4VpgBZQRTYZ2IQIRMPKj4ZXsd7iOMPHEvNk2WVo= bTxOxm3g+TJns+t8RlzBMjEIiLFvkyN9S63S4GJghngsvjPjIpoo5WTNexqpvTo6ZOc5OcYzk9v= oaaE9kRPw6Ojo6jTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dNN= HR0dHTTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dNNf/Z" width=3D"222" height=3D"97= " alt=3D"Logo_cicncia_digital CON ISS1.jpg" style=3D"margin-top:0.55pt; mar= gin-left:271.45pt; position:absolute" /><img src=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE= BAQEBAQEBAQEBAQEBAQEBAQH/wAARCAB0AOwDASIAAhEBAxEB/8QAHwABAAIBBQEBAQAAAAAAAA= AAAAkKCAEFBgcLAwIE/8QARBAAAAYCAQIEBAMEBgYLAAAAAQIDBAUGAAcICRESExQhChUxQRZRY= RciMnEjOpGhsfAYGSQ5d7Y0cnN4gYOHkrjB4f/EAB0BAQACAgMBAQAAAAAAAAAAAAAGBwQFAgMI= CQH/xAArEQACAgICAgIBBAMAAwEAAAABAgMEAAUGEQcSEyExCCJBURQVMjNSYXH/2gAMAwEAAhE= DEQA/AL/GMYxjGMYxjGMZ8HDlu0SFZysi3SAQAVV1SIpgI/QBOoYpQEfoACPuPsGMZ98ZthJqIV= ORNKUjlVVDAUiab5qdQ5h+hSkKqJjGH7AUBEc3PGMYxjGMYxmgj2DvjGa4z8AoUwiBTFHt9ewgP= uA9u388/eAQfwe//wAxjGMYxjGM2sZyHKJynlY0hiCIGKZ81AxRKIgICUVQEDAICAlEO4CHb64x= m6Yz4oOEXSRVm6qayRw7kUSUIqmbsIgIlOmYxTAAgICICPuAh9Qz7YxjGMYxjGMYxjGMYxjGMYx= jGMYxjGMYxjGMYxjOpd36K1RyP1zMal3ZTI2/67n141zM1aXUepMH60O/Qk406x490zdALR+2bu= k/LcEAVEi+MDF7lHtrGMZ5tHMLS2tuLHxUXBvS3H+vG1jq0NrcRZn8EQExOGghkpyzK/NnJmr+T= eeIXwt0hXTMcUjeAOxA7j39JcA7AAfkHbPO76oX9by4Of8AELhh/wAzO89EE6hEwExzFIUoCYxj= CAAUoe4mMI+wAAe4iPYAxjP3jOn3PITRDKcGsu9zaubWIqwNjQa98q6MqVyYfCDczBSUK5KsJv3= QSFMD+L28Pf2zkt52dr3WlLl9jX+61em0OAjXExNW+yTUfE16NjGqRl13rqWeOEWSaBEimOJxW7= CAfu9x9sYze3drrTGxxFPeT8M2tc/HS8xCVtxJNEZyXiYBWNQnJONijqg9esIdaYiUpN23RUQYq= ybBNydIztuCnTPKqzXum8f9q2bWjVd3dYipv3cKm1TBVykoUClcvG6QkOB12LMV3iJRIfudEBEh= gASjVd4AdVmvdTH4ifZE3riaOPGjQPDrZ2r9KOX6hmCNpVPsPXr+7bJBm78ozQbpLotWsWkoBXJ= 6vXK8s5RbPVnbdO4YrNwKwCmaWiVCnASiQX7MwHAfqUSeaPcB+ggICA/T7++v21OXY6vY6+G3LQ= mvUbVSK9B/56cliB4UsxdFT8kDOJEIZSGUH2H5Gfqrkeu2muvy04dhFRv1LclCwO4LsdexHM9WY= dN3FYVDFJ+1v2sf2t/yaY0V1MN8cS38JsNa82bZq9i2drSoTes7S6kZd3cDXG9QkHO1upsnLj1C= VpJCvZJzBuWP7qEi1QM9QdMActVbqSZvEmQ3YQ8RCm7CHYQ7lAewh3HsId+wh3H3++YBOOnbwOk= OQcPyjfaapUnuevSxLDXrDITUvIRFesZPAKdjg6W6mlqZETySqZHSEuxgW71B8BZBFZN6AOMz1Q= fsXPiBs8auPLABU8hwkt5YD9BU8sxvAA9h9zdg9h/IciHjXh9rg3Fq2hu7qff2Y7NuzLsJjJ0TZ= l9xFEsssrrEgA6DOT7mRj/12Zl5N5lT53yuxv6Gjg49VkqU6sWvgEXarWhCGWVoYoEaSQ99sIwP= RUH111n9eM4QGzNcjNlrQXynGsJjeAsGFmhhlhP27+AI4HvqxP29/ACPi/TObeIvbxdw7D79/tk= /yvs1yjL8XXwU4/ai4pa95d6Vo7PU+2l99x9PvErQXLutMbtE3mDtUy9e2GIjnKMe8m0Z2HbvE5= dNsk+WF6/9aq68whkbnl65A6L1e/bxeyNw6yocm7MQrWPt95rVdeuDKG8BARay0m0XUE5v3SgVM= RMPsHvlX/4wuaiLD0mKRMQMnHzMU+5PaycMpKLeN37B2ger30SLNnbVRVuukYBASnTUMUe4e/uG= MZJN8OQ8eSHRb4LPX7ty+eOKFdTLu3jhV05WMXb2w0ymVXXOdVQSkIUgCYw9ilAA9gDJuMg5+G4= XTW6KPBUxBHsnRr2gbuAh/SJbi2IU/b29wA3cAH79u/098mTm9jUCtOkWNju1TgXrg5U0GczYoi= MdLKGEClIm3ePEVTmMJgApSkETCIdu/cMYzmQ/Qe35DkeF66nXFDVfKGY4obUu59d3qNi67INbJ= Zkk2tBkXNjYhIN4U9lTXVRhZVBoo2VOE+jGR7gHSCTSQXcmFuWQL5ixOyB+m8anZnTBQjsq6Rmp= yG7AU5VwP5RimEQApgP4TCIAAiI5VX2r0bNvc5OXG+eQW6dq1vSuu7TsCQRpkU1I1uF/m6nAlRg= oCRWj/mcfC1xm9io1qu0K8knskUhxBzEN+xPHptzZ2deOt/qqq2rEllVkR/qIQKjtIXkLIIySFV= WLfk/Qbr1Nt+I+PeNd9sORHyjyabi+hocflloXaXtNsZN7NcqR0Y6lCOval2CpCLctiusJX41Ba= WAlZVspbL35pzT9BdbQ2TsipVGhtWoPPxLKzLROPdImTFRIkYKSiqkq6dFAAZso1N06eKGIi1RU= UOQg9M8NOcWlecdZ2BbtKrzikJQL26o7s9iYJxL+TFGNYSTKws431CzpvCTCLxQIw0gRpIH9E5K= 7ZNVkzIkiFunw9Gr7HQ4CuDzC3qqxrLddOsJWw8BZKbDKPDeYuMTXjLxiEcg5WADqosJFLzO38f= fMP9YUrlP0Gbdsa+PaVB8peOGyGMPHy9iodmXrq9fk4Z85GGlbFFOYyfc156LV+9aKgKMhCOzPG= qJLB6hEG5tdLtdxVtV5b2sSrqgjC1NDIbssblABI4i/ekKuOiRCT0Qzso/blhanxX4i5Nxfd6zh= HkWzybypJbrHi2l2muPD9fsaiXI0npVX20hq2dpYpM8kccm0iPzRiGvWl9vma4J3AfoOMg34n9d= fjtym2lQ9Jx2p9yVDYuwZL5REIrsqtYKwk8SZOZByq6mmFiaySLFq0ZuV1nZ68USJJiYyJffJxS= e5e/6/T6dv0/z+eb6lfp7GIz050niDepZPbpW9Vb1IZVIPqwPRH4IP85R3MeC8u4Bs49PzHRXdB= sZq4tw1rojJnqtI8S2IZIZJYZoWkjkQSRyMpZGAJIPX7xjGZmRPGMYxjGMYxjGMYxjGMYxjPO76= oX9by4Of8QuGH/MzvJcPi0effIzh/wAYNFau0G4tlOZ8k7tZ4PZe0Ki4dRkzG0+oMYd0vr6GsTM= hnNclr6ebMYZRodOQ+UwMo0Zj2cuDEia6mqBHPxfPBxFQTAUb5w6P3KIAIGRnJFYn1AfbxkL4g7= e4dwDt375Y965nVl469Pyg0LWFm0tVuVPJrcT5sto3QFmi4yXgU5RGTQioy9XM71hKLRUQzmXCb= aFQjWnzyySySsbErsU0JKXimM7o4fcFOn9vXp8aWMlwn1xSqdurRVSscpWrnUYeX2VHr2urNXK7= ye2E6Yp2yUtqSzkXqNvO+azKq/p5JEzFby00KqXQbUr/AC35ccxuj7zUj33Kfi9x7kNo7M0PB7S= stnkVtey+sdpxWrH0bHLtZho4d1+fgbSzefJpFd1HQkpDmdwrVmvMSyjiwRrfit1/t0VGM2Fu7q= Z6c4eSE3Goy3+j7oLiHr3ZMRQ2KzMqqFac3K/Tvr3MiwTEGz0qT2dZIuEzlbSj5ECHCsj8KUnOp= dcjmYlaZ9S12VHRnItGwWddi3jVrFNJchdUJyc4rHNBFowUlXhV3x2TYRbtRXFBEfLTL3YzgPRB= 4X8Z9xdejnfx12Hq2LnNM65Dk+2pNGSlLBER9fb0/dkPXq23ZuoWWj5IUYqGVOwQSXerEOkIGWK= oqUpy2u+ffTV6a3EzirsndFb0cemXSuLVlnr6xRWx9pDJsNhWazRNbqCiAO7q6buUCTEo2UdsHL= ddk4aJrkcNzpiIhXn+H0/rKnUl/wC25jf/ACGg8lz+Kb5MDSK1wI4vxT9RCV3hydh71YGyDgC+o= qGq0kCJtniAdzGbuLRaYV0gY4FIZeKN2ETJj4dPyEkaDdkEqRqNkQy/kdU5vsf/AH+v6P32Ouxu= uNAHkWgBAYHdaoFSAQR/n1/r7BH3+PxnD+mpxd1XylpO+zb6h5u6N4GnvZGomNcrlBrQ0i3YP0j= ybJzXp6JXOqCihQJ6g66RFEQMVPuBvFWg+Hpp/UP5v7m5B8YtN8or9pjS9zhqhM8p94Iz8tPbTr= mt6/MT6UdR9TP5aUVGBtOypOTWjXc21IivGx0YvJLOl2zNaEmrjXSbiU6vUNsMnRgbGDSDx09Fw= YiIEdyXqnapFRMJSgYizr05fF+9+6UofXK/vwSIB+3zn6Ah9Neao/t/F1xDKn/TxffZeM6Fp5Gk= 9tvyBEd2ZyYotvaij6LEnr40T6B6HX995bP6jKSa/wAp7WqiLGE1fHnZVUKBJLpacsn0Px3I7E/= jsns/f3khPVH+Gm4Z6e4Q7n5G8WbTvbWPJHjjrmw7kjdiy237Vb3ew3NBj1rLONrgnLORFnLS7B= g9Vj5uqHrx42aFq6M1csSrMFMO+O3xE+/9Y/D02zc1ynFLxy4pm/j8LtXbAsYFlH0ivMUNpsCA2= Va/UAb5zNU2lmnWgrvSuvnk5CQbmbF2pJyKqlwvqm/7tnnj/wB0fkB/b+zKx9v7/pnklOpHyuil= CRQJKG9d1PbI/FYPF5SfyzizWEPKP2/d8xX5p40+/wC94UlPD3ADdrwyjMu4fD59JzinzD4SQ/P= 3nRUCcxOQ3Ke17ImZWx7skZS4NajX67c52jNYiHYP5FVr81fOq+9nH84ql69AZBpGRvoWsYUXET= 3xOnC209NzUVE1NxztdkL0/OR+xm9wR0XbJ2at7LRG+tex8kc59ZTU68dSULTL7XLG6dL1xw7kC= IS8K/WIqk3MxQQtNfC8/wC5H4eewfx7s9//AF52V3D+3+/IqPjZnIE4acSmgrCUXHImZWBDubwq= g219MFFQQ/hEUhcAUBEe4AqPb2EcYzFdh1bLV0wfhluAEXpJ80Y8l+RULtun6zmXTZB8FCr8Rty= /rXPYiDB0kszey0QlIRkZXm74ijNOYlkJJw3eIRizNxOv0vukVxDU4gai3Dyxo0Lyu5N8i9WU/a= m59sciH6uz7KrYNiV5nZloOAPa3cgnWo+vITBIlstDos5F0ZmD547UXMkVDzx+ootZh4FdF5ByZ= 4NRJxT3UrDkN5osQnT8pNpFnTI9+yIuhZpwfngTuqCQN/MECCn39HTUXQC6aT3WOu5NxQ92OlZO= h1B8oJOWPJps1BV1X49woZo1jtqs2bZAxlBFJBqim2RT8KbdJNIpSFYyGnkzuSp9IHqTa+6fm2Z= Gc3B0l+eMHUpdjrHYV1sE654y2x1djwaS9Bt7iXLYW2vIO3w8LJSlWdywtmVfkju2KpX8WsExGn= 1y+H8/0lOoToTlnSYO5bD6ee2LVASMlqJ/eb0/pkPMxaaCOwtUOnB7As5ZEsldFe3UF+5dlH1Kj= 9u0TckrDkFLbdo+HU6QUutH2K+cfbDY16wX1MfN3jkXyCnDw6TdcHpjFfT20nINWxFiFXUL5hER= EomUAfrncHWo1zxRvvTG5B07lK8LFawTpLUKNLR7Mk3a4/abUhG2pDa+jzrpOZq5PLMpHRkXGNn= aCky1fPo927RjXj5YrGYo81uQ/GG68AuLGguJWt6vve58zYqtxPBnUK8xOGgoIpYUzl7t28OWUm= awMKLpOGknstajvFl1lpVuhALkKuuuuzy34S9HzitxG1LRa5LVpxuHbkfRJOsbI23sGasc8+v8l= bmqxbuZeAlZl9Ax9efHeuo+EgiMlyw8AkyYeqduUV3zmkL8PByZc9MzqbuOJ3UG19OUa4XzX8Bp= fT1p2kq+Sl9BK2ydcbGgqnCs371eLrlH3HIWgr2WcRSZe9mPCrLLg0cyyqfpwAoVQhFEzAYhy9y= mKICUxTAAlEBDuAgIdhAQ9hDsIZ+MAylSAQQQQw7BB/II/o5zjkkhkSWJ3jljdZI5EYo8bowZXR= 1IZXVgGVgQQQCCD95Ue4ucVdR8FetdJ0W52VjXaY+p8/a+NhrCsZIsq7voFjo2spSTj+gGSgUD2= ivNVHaya8qdk3FLxunRUTW4iKFEoCHuH5l7dvt7/X79w9/vlOX4kBIjrkzxqaVhB4veVtaPUkkY= YjhSYWMrcnBK8izI08Tk7w0iD4GRG4GXFYQ8sBMJAGwh0ymHLiO4q0dnzEcM1tiJIlCCBYVz3NC= m+mQ+SobEcHMdu4tqRfMBwoh/tAM/SElTqyxXqhohoZkqbPb6SCo6wwWpLaWUBMSidYm+CY/hXX= spEQT7JH0V/b2fV3nPUbDlfjjxT5o3XJ69jdbzjdPjN3Q35lXZWTo57tUbvWIB72K9p42sbT5Ao= itWo5I5HWcRRyHh7gA/njNC/QP5ZrkwzydjGMYxjGMYxjGMYxjOvdqbNrOnaJO7FuJLCpXK4k2W= kiVWp2a8z5iOnaDFII+rU+LmrHKqee5SFRONjHSiKPmOVSkboqqE7Cz8mKBg7D7h+Xt/998Yzzv= Odbm27a+JC4jc59daJ5QT/GPXdk43SV62WXjFvlo2hk6LMyqtnUGEf6+a2FwWMZKtFDFZxbgy/j= EGwLHAxA63+I0qe5dpc2tDdUzjPrfcmz9K6hZawr1g/EOkts1BfX171XcXl5Yt52t3WnQEp+DbM= 3ftlEbE0auYcsklJx0g8ZOjMk3fpFAmQA7eAv8A7Q9/5+2fNVsgsmZJVJNRI4CU6R0yHTOA+wgc= hiiUwCHsICAh+mMZV31t8RrWudNIZaf4H8UOR915dbBiUq63hLjRhhdQacmZhuRjJXnZ2y2790w= QpNQXcLSIembElZ0rRvHotGLp6BkK/vR5o7noy9dXk5Uebsta63X5rTm0aNTNxv8AX9wXre1Jq0= 37W15g5uFNCRcwCydoj4GXMiRqq9K3mS/I1lxkBBM3o+MIOGivN+VxUdGecbxrfL2LVn5px+plP= TpJ+Mw/cx/EP65/QtHMXKhFXDRsuqmPdNVZBFRRMQ+gpnOQTEEPt4RDt9sYzzb+AG0v9Wd8QvyB= 3Vyvouz9P6L5WO97yeu9jXTXFuj2C9P3Ldkdja6sz1snEuH7FpIEZsYuYaqtSSdakXZ2dkYxLhn= IItP6PiAtxTnKvqx8E9t0Kh7jkuM0DW6XT6Le5zWN2qVVvNiZ7HnJu/ydIPZIaOdSkcLKSrEeWX= O1bNZIzAFo71TEiTxx6QrqJjHpkjvGDN2dAe6J3LVuuZEfzSMqmcUx/wCqIYcRca5KkDpi0cEbm= 8aAOGyCxUDB7AZIFEzAmYO/8RAKP65g7OkNjrdhrzIYhfo26ZlUexjFqCSD3C9r2U9/brsd9fkf= nM/V3TrdnrtiIxMaF6pd+It6iX/FsRz/AB+3q3r7+nr7erdd99HrrKZVVcUixSsG63vva58Y9CQ= UrEXuVgWrKVhZbkJaqE8StGv9bTEiwjn8nC0Vva2EfZLKxIDda0tItKGUM3ZLquQic+Ex31rThj= vTmE95QSk1phjs2na5iKO/uFKuzVhPSUVabK5ftWzpvX3KKJm6Eg0VMZ0dAgkWASmN4T+H0lvls= UI/9CZd/f6tkO/5CHun/aGa/L4z7M2YCH39Mh7CH/lh9PbIb4x4KnjjiFHicd8bKOjYvTJb/wAZ= qpcXLUln1aFrFohkMnqXMxDkEhEXpRMvKHPH8k8xv8tk1/8Aq3vV6EDU/wDJW2ENKpFV9xMtWoC= JBGGCGHtAQpd+vYw/dXjmHx5pfDrl7oCwX06O4dicUNqNKTRY+rXGalrC6u1Bn42rtmKkPAP2Ir= y75Qjduis7SUKcf6YqYe+UXOnJxL1Nyh6NnKjhruyzK6M5TSnLyvbi4pxmxqrcIFWw3hjq+AqMf= EeoWgfIJC3dN5OU1w5VXKkwkHDOVWTVLGJkP6cEDszX1u2LsLWENIMZS5atj6a+u7FJNBcIQl5a= yz2uM3KwCfy3rhhDOHx2ZykURZuGS5g8DtIR6ujF+QVi5IzRSRVCqHF+mVdtFpBK19zIbP2lst8= J3b2Wgn6Ms2i6lruqMVGcamd9ESM5abAEqZAkXDMGL6YsDK+yof0IurTqDpe8bJXpudUCPvXEfa= 2hL5fJGkS+xKRaj1m4U66WBzaVGMbIQ8VJieQjbHJTqjV2kkeDmoZ7FuoqSdrA8IlgZ8Rtym291= bNQ0PbHE7SG0pHgpxt2CtXGG3ZymWGJkd87evzRVn67XFOWjjz76kUyBgHSS9gcM2ZBfTTlB4kg= qVqke5RHbbuFx6pd/wCGO169qHZGrYDh9WOTNQk5PWDQtvgrBY9zWbXxa+4k5SZn2EhGMIeCRXK= 8Ri4t64frnVN5aJCI5Kc2jIli0Rj2jFk0YNyFI3Yt2qCDRBMgdiERbJJkRSIQA7FKmQpSgHYAAA= xjPN+d8LKL1I+hrwN40aksHpepDxPr25bZXdEWGu2etWO31Ka2BcbFcaP6+chY+FazTuFQgbNXB= dyRUHLhqaNE6Skn5qNlXpgdcDiq+4ras1DzY2ZFcQeV2iqPWdWbe1xyLI91bJSE5R4hvXC2mAcW= ttGtJVlYm8WnJrNWy53sa9XXZuETE9K5dWMiNGCagKJt26agB2A6aKZDgA+wgBgIBgAfuHf3zid= j1zri4qJLW2j020rICAoK2KsQc4qkIe4CkpJsHRyD39w8Ih7++MZX05jc4aL1CIBnpbRU1YWvAS= Jt9XmucnM/8K3RnQpfXMDao1Vvx40g5QhiTGxLNtyyow1fudoq7R5XKtQnMuRR+7dzCZGvAdHck= dHdS7qCVW37fmbBW9A8Y7m6p/BPjJaNfX+LLtbcEbHq/OOV+yGD+qpRLVpARiCle0PDWd6irDJG= mLYsxipt6zFxZFtkfWIXX9oarsGTCsMavNi+Ysmzdk0Qi0Y1yd2RBFAiSCBCNinEgEKQpPCAl8I= FDtTr031y9/cT7bZtNbZrMPyLo9JsMnB1S1vn567sMa62dnJAqrWIrSQa2JBWKFqq3dSrA0quRQ= p3Mu6EfEGo2W6pamSst5njjs/IqyqhdY3X19RIqBnAfshSqsOwfbr6Jtbxx4c5h5Vpcgn4bDVvX= +PClLPqbFmKjPcrWzOry0bNlkpvLWeKMTQTzQFlnjaFpCHQbt8XPwi05tzTep+RtV+YQvMegKuo= imRtVp1rnJncmtI+QYOJmrOXtWgZNBnMUSTm29lqbyZexoeQ+sca0UduHjZJvkP0Nut4z2BxJqm= peoaF801yG06VhQQvuy9ebBh4HcFQZtATrFzf2Z5XBh4y0N2SBYW4Gl5FoR9KM0p8ihPnR2jTt2= 9fEN1qs0+Gsy3DfcLI1gbqKQD24vGMDWJQxUyHMeNnDxbz1yIAomoJmzXudIxDlDwKAYcONO7j5= Gddfe0lpvY88vpLi1SoNe226q6mKk0XeufPBvVmM5Py7V8rYJZ49MZ0kg9apw6LeMeOmsSk9STc= hgzco17NHW17NevzsEgroksS+zAENNLIiCKMDtmb7IAJAOTbU/po59BTvcl57Xg4TwbRK1nfb61= cobKylaCZYpq+q1ustW5r2ylkZa9WGQ14TYkVZJgVKNy3ijzI19zM63C+xLFXIyZpjqo2egcfPx= EzK5cV8KYyNKxVnYNnJfLYzFgQaWiXATJGcsAmBapnKoj5prdpA7AHYfb8u3t+Xt7j7fl+mQ28c= Oh7xD41bSpG5KfO7jl73r+YJNQD6cucYRgV6DZdmoV3HRFcjCu2bhq6cN3DU6wEVRVOmb90whky= oAIAAD9vb/w+392d+gp7CpXs/wCz+E2bFya0zRN7d/MEJBPqP+WUqo7ICBQD0OhpPPHKvH/KeQc= bPjY7hON6Dh2p41FX3Ff/AB3il1clpBLXj+eUetmCSGWxJ6wtNb+aV09nLHXGMZvso7GMYxjGMY= xjGMYxjGMYxjGMYxjGMYxjGYjc+N9WHi7wt5P8hajHt5W16g0rfbzWWLxIy7FafhYF2vDnfokEp= 1Y9tIi2dP0ynIY7RFYoHL37hlznEr7Rans6k23XN7hGVlpd6rkzUrXX5JLzmE1XbBHrxcxGPEu4= eNu9YOV26gAIGApxEpimABBjIutTaj5IRGpuDG9NYbptl3vFla6fsvLom4NqXScpWzdfbIpTOS2= dPVSpyz2ZqdGtcBZJNrYteRlDhqnEoNGxqoYE4V0ZEsPO1OYu8qHrfRW7KbtrcO17Fc+q7Tdchy= YqMzY4LjDsXSl52/P01/pSIoVo2A4Y2SCiKeieuN7HVdZta0lYIM07X7U9mm61jlrG2teIjPXlP= 1Vq9fbexbfqTTEXFQlI1/YC1ordaIqrdoyoDC3T8dCs5+1oUFjHsEYH1r1E7xyxZS1lPPS7RB8T= BFl0OdCsdQ1zQpN7cjXGodW7WgtzceqM9sdNdxGgrzXthJbFYSFQFWli7sqaT718GihsRzbk2Vd= mZlmwBq6kV3pmM6B4R6joesee3Wkt8Zc7nSkdZX/UNlZzto3DtKTpsa4n+OSs5OWbYkRM3ZaKuz= GJdvHUqia5FlSQLZEiUIpFotGoIY6a15R7yptz6QEghc9822W5Gb5tuv8AcG8bFMWmN0Tylpdop= FrsSc7T9XXq9zM7DNmci0rs9RZv9ndCatotB0WsoMa1MJRBpokem7rb9oXJK7P9n7Wk4rl7Tq7U= +RtEcvKslW9kq1ygyOt0p1dy0rLeerr6SrckZOVaVWWhYx04aMzFaJIpqoLdG1zo36zg4HjfEv8= AknyUtMjw+tsHYeMk/ZJjXjx3qWHhIeQgDVCNjUaA3grBFysQ8aMZGTtcZN2EG8FBoMJZk3aLIO= mMwp5q72snGPqa85N/05khI23UvQ+ibnWWrpAzlmafieQuzVYlZ63KYDLsmr8W7t4j4i+Y2RVKJ= yd/EHMtz7a2pxR40dL3lPW9q7Ru983NuLivQ+QEdbtjXO313b0JyTrqBbsq2pE3NPanW5WLscm2= sdNPTIOAQrjdh8jjG6FeXcRp5HrN066FeeSWwOR172Lcri92jx5DizedeTcVTlqRPaV/Ek5aFK2= 6TSgkpr1riRsMim5miShXyrUyafiKoTzR2qu9OKjQkRx7rNz2fszcOsuI03HW7QOrrsnTxjK7PU= 6GdQet3M3Nw9djJ+4OdcwzlSOp686/VVTV9PKTR5iZaNZFFjK88fuPlJyV6TvMvrDsOW3IDUfIm= jX3e140nQKzsuajtH6t1tpK8OK1Eadm9IqH/ZzcXlggIx+SZsNwrEnZHlgk46RTdoenI3P3/wBI= NHZ2zuRG1dD7L5F8ob5p+E41aT5ZUys3jcWxYy4Qlq5kw5LrKQUrsGBs0XdbfC63YNSwdYTl5r5= c3l385OhENpFdmZhF1prml0hJGgbU1fzX5rb80Cw35yItu3uWXThhNH7AgdKUraAXxd7Oa6dzsP= qOxXZnU15WAhpC5x8BsKNZWSXRcO3URCJOXMK0t8Q/G3Su6LhrbmpxZ26817I2vRsFryIvmo0Kj= PUXaOkBFKcobF/BWCGlYhZKrKrndVGWjE4yVikXjyKcqLx6qkcVjI5NP8zNgv8ApsdSdTbNpkrd= OcTNxcpeLdU2HPLkXsFyhYJ+Wu62e2CSTSRLL2VsjbYevyUqcnrJd3Hg+fHXkXLpdSpC95BTRSx= b+vVKn1y6M4GAg3mxCxyk1b3f4cimMPHSEU5nVpGNqcom2jmyvzisRkZPA7A7gJb+k8BbJXWcit= a8HeDmvuG2onMopKb427Ytp7Mnpt4i/tV8ctZRW43S43F8mk39RM23YcvBPii1atGCKUStGRzZn= HMkGZKm4/Qf5gPv/P8Az7B/L2yo+c7F32kVWJ+hVrIJOgO1mlPynokEqwj+M+ykMPYj26JGfV/9= EfAKsPjHYcl21JZZOTcitSUfkLiOXV6yKGgoliDKliGS/Hf7inV4WaKOT1JVGXuuHve0K5FO9iH= n3dhi73ZZivW+Ntgms8NcH0IwhpdULVHTJnjaXX8FjIuwfLlCVjXRDvot40ekTcJyxdH3lXT9f8= 29L1GEq7bW9T2Se41i2oBNOZRlI3K4MGRK4SPcPkiyDOBZOa/Fxlfh5N9MvGL2amFfmrkZECpYX= RWrRn+mZO7QQSRF3T+aDavGXUUbt/BG2XTsaouUy66pC+EX8awAqYj/ABe4Abv3LhFDyE9T5mGt= MFJFiZuvSsfNQsnGybQXsdKxjpF6wetTNHBl01mzpBJdJUgdyHIUfEHtkbgs2NVaoWQxcdV7n7+= iSnydyIHbtkDNGVboj2P23Y6z0NveM8e8nca53xtooak4m3vEjJWdoYo7UWujj11mzWhZYLMlKO= 7WmrmaORq/Q+EqR2fVeIACHi/X29//AN/x98+mR19NbnTUucnHivXRF2xabSq7RjXNt1NJQE3MR= amzUqaku2aGOZf8P2UqRpWHcAKiSYKOY0y53cc6KWRMvuAD+f8Aj9/78virZhuV4bNdw8M0ayIR= /wCrAEKf6Ze/VgfsEEH7Bz4acj49tuKb7acc3tOSjttNcno3q0oIZJoX9SyEgB4ZV9ZYJVPpNC6= SISjA5rjGMyM0uMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGM2axtpV5Xp5nBPU4= ycdQ0o2hpJZH1KMfKrsV0o56q37h56bR4ZFdRHuHmlTEncPFm84xjKvPFOqMdN8aZLjpys6Um7+= SPNyRVuMZuW+SWkaTtLXvKi9zMvLmR2c85VXOQCnx9JtMe4jVDfjmYgpqhxBfkDWrCpDtI9WaDp= w8YpThZwj4/8brG/j3U7rCkHaWA0U7dPYKNmZiWkrNLQsE9fETduoCvvZhxDQzt0kiu5jWDdwqi= kZQyZc5ewd+/b3/POk+Q9G2JsvTl919q26sdb3K6QbqtMb4+i3M2NVZTAejl5aOi2khFLOZpCKV= dkhjDItEmsodq+VOom2FurwkZkR2VDIyozKikBnYDsIPYhQWP12SAP5PX3mTSgis3KlexaiowT2= YIZ7s6yvDUhkkVJbMqQJLM8cCFpXSGOSVwpWNGYgGhh1f8AlSnyo5pX+XhJD5hQtZm/ZfR1UlCq= NnLGtO3BJiVbmIodI6UtYVZN43XJ7qsTNBN2EvYIuu4f4fp7D9/8/wAvvl2bUnw5nE2pmbSG177= s7bsmUSqvW5nzKmQDtUR8SpgaQqas2QiphERBSwrGEoj3MIj3zGfq7dHjVVB4+x26+I2vi1Z7p5= s6NsaoxjiUklLPRVzis5tHmP3L504mqmt4nT1QTgLmAcPVFlBGIaJGp7Z8X3sq3tvbWH5GZrMkC= SGWb0LD2VfUGPqFPsASElE9VXvrPrj43/U54O1E3CfE/F5t3/r4YKfHaO+ua1NfqBZWL4oZbL2r= Ed4Ns73ZaR6SIti4HkZUEjDETjDqkt26DXMGQO1MqvF8gvxuwUSQK4WSLTYjVRHjlIh1EgAU491= JlOIKE7JmVHuIiJRjl4AcDrfz33KbW9Sm3tYq0DFrTl8vzmvlfsKvGiB0Y5Erckqkm8lZd8AN2D= AzpuZVBJ+7A5kmKoDZ+6V+hl7x0X5zXbVkQZXecLv1ZoksZNEjmVmn01U4JZRRYSJJgIwEWAKqG= BMpEyHOYC9wLIL04ODdY4LceILXLYjOS2HPAlY9q2xAvdSbtztEoLNWi5ykVGDgEPBEQyIlTA7d= ud6qmV2+dCbc1uMf7Q8ensJ1Tj1ERs9H1Mje5mih/hu3Ew9z+QqN9glRlO8g/UofHUXn3V6Wz7c= w2PlbaRcY9o454qNd6dfW7DbyRyo8TpRbUeteJ/dJbdiv7xSQJMuRz8TeiNtHhrteL2xp7mg+Zv= 0BK0sFee6pIrXbhBGVIo6gp9kS8EBdsqBfEg4SMk7YuPA5aLIqk8Q2GESnKmUFBAVAAPGJQECib= sHiEoCJhAoj38ICYRAO3uP1z6FDsHb9f7fYM1ye0NbT1kTQUo2iiZvcoZZZFDEAEqJXf1767Pr1= 2fz/AB14c5x5C5Z5H2UO55jsYdttIa4qrfXV6rX2ZIFPccdmTW0qZtCL7EJs/K0KsyRlVYjGMYz= OyFYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYzb5GMZyzB5GSLdB2= wftlmb1o4TKs3ctXJDpOG6ySgCU6SqRzJnIYBAxTCA+wjm4YwQCCCOwfog/gj+jn6CVIZSVZSGV= gemUg9ggj7BH8EfY/g51zqnVVJ0rQa7rLXcOlA0uqtVmcFDomMokwbru3D06RDHETmL57lU/c5j= G7m9xEfcexsYziqqiqigKqqFVQOgqqOgAB9AAAAD+BnbYsT27E9q1NJYs2ZpLFixM7STTzzOZJZ= pZHJeSSR2Z3diWZiSSScYxjOWdOMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYx= jGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGf/9k=3D" width=3D"236" height=3D"116" = alt=3D"logo_catalogo3b.jpg" style=3D"margin-top:0.85pt; margin-left:13.85pt= ; position:absolute" /> <sp= an style=3D"height:0pt; display:block; position:absolute; z-index:-2"><img = src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAkkAAACICAYAAADzq38MAA= AABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzsvXmYHVd95/05t= d19631vtXpRt3ZZsmVbki0vssGAbbCDDQScTCDvJBmGeSEBhueZQPY8mSEmvAlDWDLBLGExDJuN= ARvLi7zJkrUvLfW+b/f23ZdazvvH7W5JVkuWZZsEqM/z6OmrW3WrTlWdqvM9v61EPB6XuLi4uLi= 4uLi4nIN2oQVCCIQQv8y2uLi4uLi4uLj80pBSIuWFbUXniSQhBKqqYhgGqqqiKMob2kAXFxcXFx= cXl182Ukosy6JUKmHb9rJi6RyRJIRA13W8Xi+qqv7SGuri4uLi4uLi8stGVVV0XSefz2Oa5nlCS= Xn5yq5AcnFxcXFxcflNQVGUC2qfJZEkhEDTNNe95uLi4uLi4vIbhaIoaJp2Xiz2OSJJVVU3WNvF= xcXFxcXlN4pFQ9HLUV6+kouLi8vZSCnJ5krkivYrrlsslEjnLV6vuiJSQjZXJF965X27uLi4vBa= Wy+p3fWsuLi4XxXFsntzbz3Onk9iOXEqZPTvAUUqJIyW9h4b4wf4ZbMoCx5GSxdXkyz8vbn/ht2= cLq8XtO47DiweGOTGZx5FnvpcvW+/sbZ/z/dIX57bFxcXF5VK4YJ0kFxcXFwAkFEs2iu0wn0gzM= FfEKloITaOrJYJPg4GReeZyDum5PAWfj2LRZHw8yWSyRDjiY1VTmNGROI7XR11YY2gqS0tdiEwq= x8B0HikErY0R6sIGM3NpBqfyKLpKd0uUxvoomk8lncnTP5oiU3KoqwnRUullaDRBxpRk8ha1NWH= aawPkswWOD89TkoLW+jA1YYPJqRTDc0U0XaWrNUZFUMe1m7u4uLwS6sc+9rFPwZn0fzezzcXF5W= yk49A7OIceCKJmk/zr42O01AY43TdDApXCXJLHjiWoi3g4dHoWNRTEb+b4xeE5KsIejpyYxDS86= MUsP3phgkwqQ++MyYoqnR/uHiIY8TE/l2TfQIa6kMpDz47g9XuYHIsznhdMj0yRxGDw1CQD8xYB= XfLoC6PU1IR47oV+TsZtwqrDzw/M0NMW5tEnTjFjqhjS4umjs4S9gu88MUxVhZ+5mSQ5xaCl0oc= bXeDi4nI2juOcVwbAdbe5uLhcOhIamqrYsb6eDW1hpuJ5DvUn2Ly2ke0b67m2K4Jj2Rw6NUumaD= MzXyBftNl3ep6WtlpaAg6PH0+xfX0tsaCXHVc00BAzUIRgdi7LxHgCXyzMdRvruX1nB1tWhBFAL= pend6rItg0NXLepie6YyrHJDJqucdXaeratq8UnLaaSOZ45OU8hbzKbKjE/m2IyWUKTNr2jKQLR= ICuqvP/eZ9HFxeVXBNfd5uLi8qrwelVUVaCpCuBgO6AqAkVR8BgLlmhFoaO1gk1tYZTVNfh8Bqq= QFIs2tmmRLzkk42l+sGeYVW0V+H0GHq2IY0sURUERAsu26BvPLsQiAQg0RSmn6qoKRVuiKAKPrq= JpCqoicByJ4TXY3FNF1KdxzfoGAh6FlbUhMpk8+45N0jdT5PduXYlPc01JLi4uF8e1JLm4uFw2m= qrR3RjkyZfGGBxP8PC+GRRNpb0+wMBYEqTkpYNDPHVynlO9E0w7Hu6+uoanXxpneCxJWmpc2VNF= YT5LquQQrQ4xORrn1Hiax58doD9RRAABv4+6gOT5kzP0D8+ypz9Fd10A5WydI8rrtYYFJyfyWMU= SDz3Vz9H+Of7lp30YoQAddT6KpvPvdbpcXFx+xXBjklxcXF4BiWk5VMYCRP0qutdDS6UPRzp4/V= 7Wd1URcko8fTxB98oKVjRE2dRVRUBaPHd8lkBllF0bqjk1kuLKTc30tEaxiiXqmyupUEye741T3= 1RBR12AjpZKVlbpPH90Gi0S5i1b6tEEVFeH2dBZydTEPIdHstx6fSc9DQEsW1JdFSLsVTFtSVtT= jM2dMYaH5jg2nmPL+kY2d1XRGlHZc2iKrOLlzu3NxHyuEd3FxeVclotJEvF4XEK52qTf70fX9X+= 3Brq4uLi4uLi4/HtgWRbZbBbHOWNtdt1tLi4uLi4uLi7L4IokFxcXFxcXF5dlcEWSi4uLi4uLi8= syuCLJxcXFxcXFxWUZXJHk4uLi4uLi4rIMrkhycXFxcXFxcVkGVyS5uLi4uLi4uCyDK5JcXFxcX= FxcXJbBFUkuLi4uLi4uLsvgiiQXFxcXFxcXl2W4pBcYWbbD0ESK6Xj2nHeauLi4uLi4uLj8KqCq= Cisbo1RFfQghXvkHXKJIAjBtyJVAcmkbdnFxcXFxcXH5j4JqgyMFvAod477g1sXFxcXFxeU3Hvc= Fty4uLi4uLi4ul4grklxcXFxcXFxclsEVSS4uLi4uLi4uy+CKJBcXFxcXFxeXZXBFkouLi4uLi4= vLMrgiycXFxcXFxcVlGVyR5OLi4uLi4uKyDJdcTNLFxcXFxcXlNxMpwXIkpiVBgK4KNEVwiYWrf= 2VxRZKLi4uLi4vLBbEdyVjc4vm+IiNzFpoq6KzT2dRqUB1WUZVfX6XkiiQXFxcXFxeXJaSUOM6Z= 97QOzlp8/rE0vRMmBbNcjTroVbm2y8t7twWoDquX/C60XzVckeTi4uLi4uKCbTvMzWXZv2+El14= aIzlfoLI2zEigjdNJDdOWdNfrZAoO4/M2TxzPs6pO45b1fozXQU1IKZf+Ln4GEEKcI8J+mYLMFU= kuLi4uLi6/4WQyBR78zkEe+MoLTE6msCwHkOixKDU3VKJHY9RFVK7u8DCVtChYJRJZybOni+xc7= UNXX1t8kuM4pFMpjh89zL69LzA40Ecuk0HTdWrq6lm7bgMbN2+hobEJTdN+aULpDRZJ8qzPv56m= OBcXFxeX/xhIKUFKpO2UI42FQCgChFL+63IeUkri8Ryfuf8JvvfdAxSLFhUVATo6qghHPCSlj4T= fg1AEN632smmFh0xBRyJ44kSRbMFBylfez8X2XywWef6Zp/nuv32VYnqWns42rtvUSSgcxiyVGB= 8fY89PvsODX/sy195wC+989/uIxmKoqvr6nYgL8DqLJAl2CawM0kxBcRrsAmgBhLcWtDBoflA0/= mOIpsUr+x+hLb/+OI5zntl0eSQXuiaLZthL246Li8tvBI6DUyphTafIHRqi0DuKk8iCR8NYUYt/= /QqMFTWoAR9CdSvfnE0+b/Ltb73Eww8dQQi4594ruO++q2hqjqJpKrNpm//1cJpjYyW+/myW2az= DWNzi6JiFogg66ozLsiJZlkUul6VYKPDwD77Hgeee5C233MjmbTcSiFaRmJslm54nGAqzvaIa6d= gMnzrMd7/5Nf7mk/+d9//Rf6OuvgGP14vX633DxgMRj8clgKIo+P1+dF1/9VuREmkXID+CnH0GO= fkQ5IbBzAMOCBWMMAQ7EfVvQVRsBU8tQr2Mfb0WpCy3xymBNQ9mHIxaMCr5dRBKUkpSqRSJRIJY= LEYoFEJRlnkgSIlTyGCXcijBShTl/KA7KSVzc3Mkk0nq6+vx+/3nLX81ndKyLE6fPk0qlWLjxo0= YhnHeOo5jYyanMXNpPNUtaLrnnH1IKUkmkxw4cICenh5qamqWlkvHKUsrIZZ82cseu4uLy68PUu= IUs8iJk1gTE4x/9hDzD+3HyRbPPAd0FU9XA41/9T6MllqMFTUoYR+Kov46PPZfE1JKenun+fB/+= 78MDMzx3vdeyR99cAehkG9J9Fi25CcH83xjT5q5rI2ulE+bJQWNFRofflOE7kb9VWW4SSnZ/+IL= /N9vfhVNEajS5Lfe/V7aV2/CQXDi4F7sfIqIX0PaRXzhSmLNq/H4QxQy83z3K5/j8MlB/MEQazd= uYddtbyMajb3m82FZFtlsFsdxlr5TP/axj30KyoOLruuv3nwlJbKUQE79FNl7P4z9AHITYBVAWi= BtcCwws5AdhvjzyPQJMGLgrUMoKm94T5USZAnMaUgfgrlHYOpbkHgEfJ3gaebXodiDlJKJiQm++= tWvous6ra2t5wiFRSuMdGwyh37C2GMPkIp0EI1VLiuSTp06xV//9V+zZs0aampqlpbZlkVhegah= a9j5AmY6jeLxIC4iShzHob+/ny9+8YvceOONeL3ec5Zls1kUJNMvPsTxXzyIUtdDOFpxXrtyuRy= f/exnqa6upq2tbWl5KZ1h7qXDONIhfbqfUiaLtyJW7lm/Btf2Nw3LskjMJxmfnGEukcCxbXRNW+= rPrhXRBengpGexnvkG5k//AXQV3213kz85SmlkBpxyPR+tsYLaj96Fd3Ur8//2JNbUPFpFCDXkv= aBVybIsLMv6tbdYm6bNQz8+ys9/doLOrhr+5KM3UlMTOueYFUXQXKES8CjkSpBMFcmls7TGBPft= jLK22UDXlFc1itu2zZc+91m6mit58x13ce31N9O4chUoGkN9J5kdH6KjeSUVNW0Ew7XkZiaIz03= hi1bjD0ZYtXYTq1d3Ux0NsufJ3XR2r6Oisuo1XyvHcTBN85yg8dfmbpMSWYojh7+BHPo6shDn7D= ikZRtsZmDmWWRuFNH+/0D9W0D1vKZmXLh9DlgpyPfB/G5IH4TCKFhJkCYYVYD9xuz73wFFUYhGo= 2iaRj6fP+dCSynJZDJMTEyworUFfDEOjiRono2zov38bQkhqKurI5vNUigUztmOmUzR+9efxltf= h1MogqbS8aH/jB4OX7CTqqpKNBo9I9TOals6neaJJ57gll03E+neRlipIBytWNrf2dYhv9+P3+8= /JwsCKSnMztL3zW/jbWigODaBv6IG4/3vxltVgerxvOqb5+WZFW/Ub1zOpRwfkeCJFw7SO5EjkU= rjOJJo0MOKKj8b13aSLJTY0NGK3+dzz/NvKlIis/NYP/9HzJd+jMwlUTuvxbe2lZbP/mdGPvIl0= o8dQquN0PCX7yV6+9WYk/PYhRK5A/3Ysykid12DZ2UdQjvfMCCEIJPJIKUkGo0uGA8kmLnypEv1= gvjVt1SXSjb79o1SLNrs2NFOZVVg2XvKZyjcusHPFa0Gn/ncUX72i2Ncuaud1bU1ePVXJ5CA8vW= zTK7ccRPta65ALJzLbDbDwOleoppG4fn95CU42SyF5CxzK+sJ1rfjCwTxBiO0dq2noraRg4cO4z= j2Ugza681rEknSyiInHkEOfgVZSmHaDt9+yiFvSm7fqlATUc87eRJAr4DQGpyJnyK89YiKrRe1Q= lxe20zsU88jpr6E8PahkC0LowuHu1zadiU4jqRoSUwbDBUMTaCqr+/FsZ1yZoGiKIhX0WBFUZZm= 21JK8vn80rIjR45w6NAh7rnnHrxtm7nhD7swAmFs28Y0TRRFQdM0LMuiUCgszaSklEszK1VVKSS= T6LXVBDeuwymWiD/zPANffoDwmh6qr9+OdpaV6GwWb75CocDU1BTJZJJIJMLPf/5zDh48QENdHS= HdwR+OMTg0SGAuzsDAACtXrqSiooLjx49TKBTIZDKUSiXGx8cZGxsjGo1SSmewdu2kdlUXidk55= o+fYO/H/gcNt91KxzvfjnqJbmTpONgLx5pMpdB0nUAggOcCQmtR8BWLRTLpNLZlUxGLoaoKiq67= g/irwHEcpmbm+LefPMOLx8c4cvQENh4kAo9SorOjhcdePMIVnQ2sX9n8S2uXBBwpsZzyX9OBnA1= Z0yJpCRImTBUk8ZLNqrDG9koNn+Ze9zcS6diYz34D88XvIwuZhce6QFFVvF3NNN//+4z/5TeIvO= lKom/bihb0YU0my7+1bArDM4gf7SX2nuvRaqPn3aeqqhKJRJibm2NwcJC6ujp8Ph+KosHcwXL4S= GgFKJ5faUu1bTlkMyZCCGprQ2jLCEYoH6JHE9THVBpDNmZ8jly8Gmz78g5fgFAUVN1ACOWciXA8= Hoegj1U7dqD7fAggm5ii/8CL2LaFYGEsEQJFUVHVhUy3N+gyXL5IkjZk+5FDD0ApBVJiO/D9Fxz= iWdixVlATWeZ3QoeqaxHdfwJze5CDX0GEesCIvL6dzXIwnzhB4ZuDqK0SY6OK3m2jROyyatXCEN= 4ERt0ln1xHQjzt8NgRk6d6beazkrBPcH2Pyls2GQS9r0/7S7bJL0afpWAVefOK6/BchqXNcRwOH= jzIwMAAqqoyPT3NiRMniMfjhENBopkRImR4bEIlHK0gkUhgmibvfve72b1795JISqfTzM7O8u1v= fxtVVcnn89TV1PCzmTHe6tmMEQwz2rOSlf0jzH/xK1Ruu/qi8UpSSo4ePcpTTz3FnXfeySc/+Ul= uv/0OfF4f0UiIiT3fw87M8rnH+7nupl2sW7eOT37yk6xZs4bq6mo2bNjAwMAAMzMz3H///bz//e= /nwIEDZDIZ9u7dy3sr3sup3lPs2L4NUVmNdokBfYsWKbtUIjszh2NZiEKeku2QNXT8FTEqKirOc= 1/ats3c7Byl+SS67aCqCjnLRlEVgnW1Szfzr/KD9JdFOpPl+489z6PPHaN/PA1aDLkwRSgKL5Mz= s0Qjfo4d72dqeoq2FW3AL8FqJyW9KYe/PWUynC0xZ0JGquRKFlbexFe0CWSLOMCWtRVsiKh4tVc= ztbm0NsBlzPFe4dxIKcnHc2RnckhnYSYuJb7qIIFKL9mpLPHTcTxRH94KL+H6IMK2cAb6YS4Bug= fa2ihKncxMDhSBv9KPv8KHoijlCUSywPxwmsquGNpZxXRs06KUMfHGvAtNvTTXlpQSe2A/1hP/g= ixkzj9kReBrb2DF5z6IMDQUY5kJkuNQ6Jsg8/QxIm+9EjznT2gURaGqqgpd1zl9+jRVVVXU1tSg= Vm5EzO2D4QNQfzN4Kn9l72+hgKaVBUouVzqngOSFyGZKSEei6wrKZWcMLmQdvsz67vV48fr8TEx= PcWp8kI41GzF0nZmJQWYyBXyB0HkGldeQWHdJXJ5IkrJsRRr/ETI7tDCbLjdWSoHjyPKNLCUSsX= TjldewIHUMOfEIzDwNieeR07uh6fZXZTG5JGwgI7CO6pgnPIgqHXFDJdrt2/HU3Yzqb0JRPJe0X= ylhLu3wpceLnJp0uGG1RkuVwvCszePHLNprVLa0vz7Jgo50OBbvJ1PKsqtlG57LyHIsFot873vf= Y+PGjXR3d/PFL36R97znPYyOjrJr1y0cfvAzVNoTpOaDJJJp/viP/5gHHniAv//7v2doaIgf//j= HHD58mG9961s8+uijhMNhfvd3f5cnn3ySw0eP4g+FeHrPHtauXcvO295M0LTou/8fcUzrgm1aFE= /19fVs2rSJ/v5+hoaGUBSB1+vF7/cxPjpIe22IaDTCHXfcQSgUIp/P8+STT/L7v//7rFq1irq6O= g4fPsyLL75IT08PyWSScDjMddddx/33388nPvEJVrSvZN406f0/XyfU3kakve2iws2aT5Dr60Na= Fo4E1dDxGQbC48M0TbKDw4yn09Q2NqItWKVKxSJjA4N40lmCoQCaBrKQw8kksc0S6bFhVJ8Pb+s= KtPByM4ZfT8ri0TkrgF4sPXzPfqguBkdqmlaOWRuZ4KVTU0zN5VjRUI0iBNliiWjAh6I4GDoMDI= 0R6Wxj/4GjtDS3oChKeTsLM1GxsL2zLe+WZSMX5NZiH1QUBfUSs5ykaSP7EvgfHmNdf4KmuTQN8= RxV8TwVqQKhfAlfyeJQexXf/fM3YTo+bMtiPpkkGomgacs/F8pVjcsZn7Ztk0qliMVi54kFadpY= P+jDmswiYgba9kaUqA/r8WHs8SxCgLapBnswhXpDE0rIwHpiDHwq+vXNFxUeAsCxOfG1AxSFzuq= 7ukkPzjJxKkX7VdWc+OFpWna24qQLjDwVp/sdHWiqwE5Oo3zwQ3DTHYg/+RCKCvv/93NIj59tH7= 3mnH06RYvMVJ78TAYzV0J4VLBBUTSE4pBLmegelaZtzfij3ovqDSkl0i7hTBxCdO9k8dEoAdG8H= ikWnuaqghr0nfVDUEI+/FvakeaZEIuS5ZDJlAh5zhdSi8cQjUbRdZ3e3l4SiQStra34K7agemLQ= 93+g7iaIrgXVKId4OC8L4RAKKApL8lY65X9CPdNJpTzz/ZkGnFnHsc9dtrTd15YCbxgaHZ1V7Nn= Tz/59I9z59nX4/ecn1ZSbKEmnCxw5PI4Qgra2Sry+y0++EkIgnXOPSdU0rt/1Zr70/32aiUce4c= SxY5RKJqMjI7z57XcTfllw9pKsKNuXLrstF+PyR/XiLPbUbtJZi8l5yVwaqsLlF+ABZXGkBsFbB= 4HWcimA9AkozUN+HAYfADMJVg459iCi4c2vf2ySpuKEAlixMMUtayhesRqrpgJZUJGDM2h6lpr6= VqKR882tL8eyYc9Ji6FZh4/cZrCqQUNVwJEad26R+D1nOrssFpHFQjko3edDLAbDOwWw8ws+7QA= oOlIKSlbZfacIUBWBebaal+AUC8hCAaGqCJ8fFOUV22sYBu985zs5cuQI3/nOd0ilUkhZdt8lk0= mOHj7Iqitq0DSNdes2Eo1GCQaDjIyMUCqV0HWdiooKNE3j6NGjtLa2smfPHgDWr19PY2MjH/nIR= 1izZg2xWAwNgZktcPozn6P7v394WZfbokm1v7+fI0eOsH379jPHIR2mJqcYHThNZ9Xqc7ILFgcR= x3FwHAfbtimVSnR2dnLvvfeiKAr5fJ7+/n4Mw+Dx3bvp6e5GIrDyJWzTfEV/tZSSYHcPwuMpP2g= dG6dQxCkWUBLzqFmb/NQMc7ZNrLERx7RIDA0TyWTQDRXdY6BGwiheH8IwyvVZkDj5/Dmzpd8ECo= Uijz+zD8e2iCezXLN5DUPDo0zHU6xorscyS1TEYpzqG0TXNbZu3kgw6OfU0AQDgyMULcHMfApVU= bFtB6eYwi5lKCkx8qbB6MgYL3rTXL/9GsanZ+nrH6SqqopT/SMEfD5u2LaZydkEjXXVIOCpPS8i= BIRCAY6fHqIyFubqzRtobW64pEQVOZSi7cA4f6dlKfzsMDgSmSxBsTwzLF9pCKdNClmLvA1z8Th= /8alP8ck/+zOqqqqW+v7ZZTByuRwvPPc86zasZ252jv/9uc/xV3/z1/h8viWBKQBMB/MfX6IwMo= /i19Fawnj/Yjvm5w9hzeXQV0Sxwzqlzx/CCOuI1ZWU/mEf6p0d6Nc1X3zsEALda6B5NSyhY4R16= re1UkgUKc7nme+bI9ZTTf3qSvSgF0URCEVFiURBVVD8AYTXg6ZraIaKpSkYvjNWGYFA9el4YypC= 1fBWn4kjE0LBLpkoXh1FFUjLxrZsVE29uGEm14sa2I16+58i/K0g1KVz6wgVsXCO4dyYRrUmTOT= eHaiqVs6ULdp86aU5fAN5/kvMj6qcb5Vc/H8gEGD16tX09/dz7NgxmpubqaxcgdHyW4iRB8GogG= Ar9vSzOHMvlj0m5RagRHtQqq5G6H6kdHDmj+LMvYTadBvKghVK2iXs8Z8isyOLVx3hb0CpvQ5hR= JCze7Gn94DiW1gsUGquRYmtQSiXP4wbhsZNN3fx8EPH2LNngH0vjrDzhk48nnOLNZZDCix++IPD= HDkyQSTqY+vVrXi9l79vgaCUz5BPzS3tw3EkKpL7fu8DHNq3l9OnThKNxrj7Xe+irqGJQiZBEbE= 0wSlmkthW6Q3N/bqsI5SAkxthbm6aB35u8509EsuGaADms5KgXyl3mvb7UJrvWvDbqsjsAPL4/w= Q9guj5KHLqF3Dy7yDbB4VpCLyOcQaqApvWUmyuJF8XpaAI8oUC87NxxqdmON47QCZX5Hff+z42b= Yhe/HilJF+SPH7MYm2zSnuthqKUjzVTKD/MkjlJQJcEs9OU9uzGOnYYdB3P9hvwbLkKxDxy7mFk= 4sly56t8E1S+jVQpwPOnLfb223g0QVVIUBGyF6xyEntuhvzzL2Ae2o/w+vDuug1j3QbQLqzgF0s= BfOELX+Duu++mvb2dxx9/fGGZw9jYGFNjw4j1EdKZc83VqqouuZFM08S2bcLhMBs2bODtb387iq= IwNjZGOp3mqquu4mc/+xlXXnklddEYiqIQ2bgOZZmBx3EcisXikunasixKpRKRSAQpJYViicHBQ= XK5PJNT05iWSjabRVVV/H4/K1euZGpqir6+PkqlEt3d3fT29jI1NYVlWRw5cgRd1/nEJz7BRz/2= Ma7csIH6eJrmN91ItH3lBWPeFgcjNRAsi1BVRRECpIrQDdRgEL2yCmlZeDNpCtMzxPv6UYFIwIe= 3rRXF5yvPFJcRYorXBywUuLvA9bqY4F0aLH+FzPmOlAwMjSIck6GxKQ4fPcmW9e2MjU2x+5m9XL= Gmg7HJOKvaGjBtha9/98f8zr23MxtPkcnl0VUPkaAHv9/LzMQ4ycQcploNmkSikM5kSGR8TE5Ps= f/QKSYmp6lLpnn0iefw+Txk0nFeOj7I1o09FEyb2elJdl2/jaGxCR559Cl2bl1HblX7OYH2F0WB= 0hcPolzfiOe+1ZiPDYGmQtrCGc9C0gRb4i1aODmTgiUJ2A65bG5J7Nu2zfT0NKMjIziOw8r2dib= Gx/nSF/6Z377vPlavWcPdv3U3Qgh6e3uRjiSRSNDY2EB9rJxZqt3SgnFNE9ZnDyITRVBAvbcT41= 1rEAqYP+zDOZ3AiXogXUJbW3lJXqBy3xKYmRIjTw7RctNKqtorKM7nCVX7OPwv+xjrqqb77d0L/= XuxT8LCdHhx3F747qydCjCCHnSvSna2iO7VsIsmQlOxcha27SBMsEom0naoWFVFsNrPhUc9Ccn9= yJmfQzEOPX+DCPVg2ZLh4eGFuKFyXGaxWMQwDBRFwePxkE6n8fv9RGMx4gWbz++f5bP757iiPsj= vrY8RNC4smIUoW7vb29sZGxtjeHiIXGqaRt80RuU1qN4qAJyZZ5DZIdTGtwIKMj+Kc/qfEaGVCK= 0VWUrinP4C0ioiNT+y6a2gepClBE7/11Da3l0OCpcWMnkcIqtADyHnXoDsAKLxrQihgtAQRvgi5= +nSUBRBR0c123es5Ic/OMxf/PlPsSyHrVe3Eg77UFWBbUuSyTy7Hz/FP/3j09i25I471tLVVfOa= y6wMvvAjMqeeQEqYmksxN5/Bsh0cRxLfCvU9AAAgAElEQVQMeNCLJqnkAHuGX1qaYChCoWtFDR5= Do1gyySfn3tD8+MuUgRIrM8JLp/J880mHSFBw17WCuRR84wkIBjSIbkA034U0k8ixH4J/BUrDW6= DjD2DipwgtAKpRvsXMDORHXleRJDQN/YpN6PluRuMJDo+OMnC4j/Hjx0jOzGLZ5QDbS31QmjZkC= pKYX6CpZffB3j6LR4/aOIBjSzZXZrj19LdQBk7gve5GnFSS7ANfhNI8+srTkPgJovpOsIvI4c9g= mg57E7/FwwdstnaUg9y//6LF+lYbo6nsuik89gja3hfxXL0d8/RJMp//DJFP/i1aQ9P5V2Uhg61= YLDI3N8fs7Cy9vb0Eg0FCodBCfNEcJ04cR0rJzHyGbFaQSqWYnZ0ln88viZFf/OIXzM7O4vf7Wb= 16NePj4/T29lIoFOg92YsjHd71rnfxr//6r3z7m9/kjjXrcQp56m6+AbGMe0FKid/v57777sPn8= zE6OkowGOTjH/84Pp+PiooKIuEQtb/zYWorQrw7Xp4BWpbFO9/5TgzDIJ1Ok0gk+MAHPkA0GuWa= a65hamoKr9dLrS+AalnUhSN84J57mHxqD2o6T/31Oy5qQSoWi/T19ZHL5QAIh8O0tLSgaRqjo6P= Mzc2V+4gQRMJhampqmDp1ikKxiJrzUiUETU1NSNtmfHwcr9eLrusMDQ1h2zZCUaiqrKShoQEhJW= Y2hxrwMzQ0hKqqhMPhpVinRSFk2zaZTIZAIIBlWeTzeRzHIRaLnROUf3aw41K/F2dcSovrXWxZI= pEgEoks7f9sUbbcvXGpYs22HcxCjvXdbfQPT3HsxAB11VE2r+3kwOETeL1eMtkcJUsyPTlJJpMt= B7vbeaoCGp2rV6MqCsJKUQiFGJ0tx8xIIVCEwDItzFKJ5oYaTvcPcfjoNLlcnk09bWRzOQIehce= f2ktTQx1SFjEtk7raWkzLJJGcJ53NXLpICnuw40VKnz0AlR7UNRX4PrgFtSGEuX+K4lcOYx+cxW= PZyGSBgu0sCIZzZ+Lj4+NMTk7S39fP/n37aG9vJ5fPMzIyQjQW4xtf+xqdXV38w9/fT8/qHjweD= 489+nN+77d/l4iUOKeSWEUgoiMCOtKRWD/sp9SfxvijTaidMewD0yhRLwR1lMbgJR2e5Mw1N0Ll= ysrSkSgejdXvWkts3wSDTwxx6GtHuPYjV+HLTEM2X3ZxXcogKSBYH0YUJhGZDE44iqJrWLqC0CT= SUqDkoKgmmvEKJWGkjcycKpeXmd+LPPGnsOpPEb5udF0nnU4jhFiyEC6mc0ejUSzLwuPxEM9Z/N= O+Gf75YJy5gs1I2iRVci4qkhbxeAxaWpoJeBxycwOcTgtqmldQrfhYuDMRVhJK4+XnjjmN8NYiF= KNsRZp6EgIrUOtvQZ76AjK2HiXcgRRqeaJVHEWoBtKRCH8d6KEz58OMI0pjCD2GqNmJMGKvSyxU= OOzl3e/ZzOjIPC+8MMSffeonXLttJWvX1RMOeYnHcxw6OMbevcPMz+e56aYu3nnPJsLh5RN0LhU= pJY5ZwipkyyEPhQzZdJJC0cSRUMxpgERVVHRdJZsv4jhla1OxxofqGNimjbStNzQu6bJtZXYxw9= Fhh3wJ3roa3r1DIV2ERw9YIDQIrgTVjxz9IXLwq2XLUs0O8DeCt+asLQmQDtJKv65q0JLw4lyGB= wemGM3kSWShFF6JWFuFZ2IIfegkvIqaUB4NYkHBVFJSNCVeA9Y0q9RGFQqm5LvPmSTHZrBOHSf8= tjvwXncT0ixhDfZTfOL7aJEUSu1vIerfV77RS2MUxr7F4anbWdNk8LYrdAQwmXTILfrMs1msIwM= YsQrM3uM401MYV1yJ8Hgv6D4KhULce++9qKrKjTfeSCaToba2lnXr1qGqKtdccw26rnH9pm6qw1= 7+8EYFr8+H1+tl165dFAqFpay49evX8+lPf5pAIICmadi2TTQaZUNtHeg6TbV1vO/ee0kcO8HUN= x7Er+vn+ZgXUVWVtrY22trKwbbr1q1bdiB37M1I6VDvlDPqxsbGuPrqq8nn85w8eZL169cTjUaX= 3G9CCFQhmJiJM/TFr3Ki6qcEp2fwr2xj9R+9H191FcpFYk/S6TTf/Na3UFUFQy8LsWuuuYYdO3b= w+O7HOX36NOFwWUSsWNHK5is2860ffB9N1TAMg7n4HHfddRfr163nZz/7Gc3NzVRXV/OVBx6grq= 62LBZKJe655x7aGhpJDgwRWNnK0NAQq7pXMTA4ULakFQpUVlZiWRbT09MkEgnWrFlDPp9ncHCQV= CpFS0vLUgHN+fl5wuEwpVIJRVHI5XLoC5l4iUSCQDAAsnx8Xo8H07KIRqNkMhkMw0DTNHK5HKZp= oqrqUqbhYmxMTU0N6XQa0zSJRiJkFgqs1dbWvqKLSghBc30lMzM2sUiE992zlYNHj5LN5Lhiw1p= aGusROAyPTqJQ4Obrt6LrGnWVUSqqahgdm0Y5+CxVjS34gzGqG6upaSoxODBIPJmjqqYCn1rAMA= wCfmhrqsWxKgiHfPR0tpErWfR0rmTfoeO0NFYzn87Te7qftWtWs/OaTQjpkM3mLt0L6lVRIx7sX= gfG87BWQVtTjdocQV1djXFdM+azY/j+9nn0TImseX4w6WIs3sjwCBPjY4xPTHDDjTdSW1PLtm3b= UFSVTDqN4ziUSiWu37mTqqoq/vnzn2d2dpawlMgT81iDaTwf2YKoLLtdtPYo2tWNKDEvSlcU56l= x7NgMyoow4lIHsbKhE82v03h1E56QwdRLE6h+Dc1r0HZzB5HmEIe+eQIrPo393z8Mb70D4QikJ4= hUlIVzuXA/c75w90W9eMJFnBMHAAVh2eCYyEIRalsgE0dZuwkloF183JcO0kouuLAtmH8WefrTz= Nd9gh/+8Bds2bKFVCpFb28vV111Fc888wyrV69mzZo1TE5OUtfQyI+PJfny4ThT+bLFvmBLCvYl= dgYpUZ0CVRUx5g0/MwMjzMWTxCqqMRbjjry1EFldPk4tipMeBMdClpLIvi8jancikkdwzBTO6I8= QnR8APYTa8yFwCuUYWaeEM/0kMtSJ8CyMl946CHWDFgRl+bihy0FVFVatquV/fPJN3P/px3nqqT= 5+8vAxHnu0F01TsCybUsnG49G4594r+L33X01LS+w1WrflWRO2crVuRVFJ50pomoJjO2iqSjjkI= 5cvksoWCAe85AompmWiqYti+qyYrjeIyxZJQvUQ8pV98UPTMJOC4VlJIguxiANWurxicCV4qiHY= idQC5TgkO/eyjQlQXpsqfTm2IzmayLB3en5hEFbAHwJ/CKeiFn3tFhoMm2hN7SsfqxB4DXjzBo1= /e8Zk34DJVe0a9VGF6pBk/6DNTNphV7OKfkSCZZXjhhQFLBO5aCWQpTO1NewSUH6fkO2AspDBaJ= 0V8yeFQEqwh/rx3nYnnv/0B6Dp5XiAZTqoEIJwOEw4HD6zjWUyzRb995ZlsUFRlrLYmpqamJmZw= efzcfDgQbZt27YUD7S4HU1VmRsZ4+RffZp8SxNOsYRWKrHq4/8vwRWtaMHl62ycPbu7EKVSiZO9= vSSTSdLp9JK1pbq6eqm9+/bto1gsMjMzs1QNvK2pCf+RYxTic6ROnkANBDEaG/FWVmKEQhe9mct= uxRLvuvd9NDY2cuTIER5//HE2btyIWTLZtm0727dtQ1XVpSxBx5Hc8Y476OjoYM+ePTzyk0dY2b= aSbC5HsVikVCphGAYfeP8HAPjxQz/m6LGjNFfVIBdMydPT0xgeD7lslqmpKWprahkZGSGdTrNu3= Tr6+vqWrpNpmszOztLT08Pu3bsJh8MEAgEOHz6Mbds0NDTg8/kolUpLLs2jR48C0N7ezv79++np= 6WFgYABd1ykWiwDU1tZy8uRJGhoaqKiooL+/n1KpBMDExARDQ0NcccUVJJNJMpkM8XicrVu3UlF= RcdHr6PUYvOnm68hls3g8Xnw+H7U1lTiOxDB02tpasRfcreWyEhqBQIDu9iZWtrUwOp1mfDoJTj= 9N3ZsIV9ZgmyVU6cDJo0TDXjpbIlTEonR11bCup4t8Po9lWhgejUAgiJSSzZs2Lrm7VE0hGAiyc= kUzmWyWaDh8wXTnl6MYGnplkBJT5YL9xxPYJ+dQG0IouoJojWC9OImesfBlTOZLDtI4VyjNJxL8= 65f/hZ41q7nzHXfx5S9+YeGeKJfdOPt+NjwG4XAYn9+PpukLgemg3tyMIhSc43PI65sRikBsrkV= /RwcYKkpnDDtThOfGMe7sRPi0V7Q0SCnJJwsomopiOkwdnoa8SSYhadgcYeipCWrW1lKKF1lxYz= u+2kpEVwfO9AyirRNu2g6GTn46je73ohteCokiXr9+zrvShACKJay6BlTbQsynsL0VqDpQtBGhI= DLgfeX3qy2OFYteP6MO0fguiiUPVVVVHD16lHQ6zbXXXsupU6eYnJyksrKSVCrF888/T3tHBze1= hXi4P8VD/WnyDmgKaJc64EsJqoeSpZBIJjAMD7HFd4gtPMOl0BFKuY6SFAaUkkgrizP2EDK8BhF= YgSME1OzEmX4SkT6N0II4Ez9BbbwDFBVhF2FBLC0dumIg1LIrUmYHkJ4ahLeq7H57jei6Snt7FX= /7d7ezd+8QP//pSU6fniGftwgEdLpW1fKWt6xmzdp6gkHPa8hqO4OUDg3rdtLc1okAOqRkq11+c= wJSMp8tW5iUBat2OBBAWwgH0bRyaZxcNsPhuR8tbpE3IjjpMkWSQA82sKXLoDZa4rmTcN9nbHJF= KJoCHBMSByA7iFK9DaJfh4WL60zthvwkYiHlupx24EX4Gl/HwyqfLlueW7RQ01TaQj521FdwVXW= EloAHn3b+KzmWQ1MFW1ZqDEw7/PNjJruP2zTGFCbnHQ4OO1zfo3H1FQ0wto7cd76GMz2JPTeD1X= eK4H/9EKLqMHLiX8CcQVoZSPwMX9un2Rg0+NoeC0eWcCQ8cdzhmlULgXuhMMaWNuSPvo+TiJN/6= PuYRw8S+vifoTc0XVAoXez/UH4wHj9+nEwmsxTQnUwmqaysJJfLsWLFCqampnjuueeYnp4mnU4z= MzNDT08PsUiEutMDlMwiuf0HUQydUFcnaiiIXvHaZhdSSrLZLKFQiL6+PkZHR8sxAKOj6IaBz+f= Dtm1yuRyJRGKpOGV6dhb7pQPYQ2Oo1THsTIr83n0kjp2g7uorX3GgcGyH2bm5cjzIqVN4fWWXme= 04jAwPcyAQQNd1Ojs7y7U9VAWfz0coFKKnp4dHH32UQqFwJt0fyGazvPDCC5iWxfDwCLfecgvq4= qAsoK6ujlVdXRw6dIh4PE5DfQOKopBOp5eE7tK5FIJQKEQ4HC7XY8pkCIVCS4H1juMsWYnGx8eX= XAuRSITKykqampoW3FsZqquqMQyDQqFAfX09x44fxzRNgsHgkhVJ0zQKxSKRaIRwJMzY6NhSnSz= bfuXiq4qi4PN68Xo8C80XKMqZzwDo+jlV1wFaGmrZtqaJqdl5Dh3tZzheJPn841TUNZNMFTALGR= ob6wmWpli/9lai0RiGrmPoOsFgYGk7i65Cn893zvaFEBiGUc4gY/l7Y1k0BTt2JgZQDmfIfOhRI= j+4G7WjAnssTeE7J1DjBQKpHKmcCQYUCnkOHzxELBYllU4zNTXJm257M6dOnSKXyyOEgmU7jI6O= UVVdtdg1zsm2PbuJSthA395C8X+9iH1rEmk7WN8+CQdnMf7TOkRDEPwaVn8ST0cU9Fd2hQkEvqo= AG//wqqUMQAChCRRNIdpWw/DpEkpDhEBEo4hK/D2foDQdp+qdv0O4IUYyJVH9fq768LUIQPWUh5= Xys3cx61CBjtVMT4/gCIlarWBJgS9ioAUMKjuiZffqK1r3VZRAK1KoSL0S0f2XiJqb8SdzaJrG1= VdfTS6XY3BwkE2bNtHV1bX0fLv99tsp5PM0VFTyP29sRBHj/KA/TZVXIWxcYqajUMjlC4yPL2Z4= tREMBpeKTYroGph5Amfk20tnWGm5G/QICAet50MovrJlSDolHH8DWDnwN5WF0tiDZ66NtxYRXFm= eWEdXQ34IZ/TbLAV21+5CeLbD6yCSoByfFAp52Lmzk+uua6dUtDEtG10vu7s0TbnkMg2XSqSujc= q29ec9om3H4YFvfY9MvoCmKlyzupvrV67FqxtndJCETCqB7vnFQmo9b0gA92WJJAGowVZ6Vlbyq= Xfl+foTDqks3HKFYHgGiqYkYJ5CHv5TaHsvItyDtMeRYz9Cjn4PQl3I6ceQySPlekuBZvDWL7sv= KSWlUonSQrFDj8ezYGq7hDYKgV9XqfZ5uLI6ws76CtrDPnzqmfiPRUuJaZqv+FqWsE/wrm0eVjf= Z7D5mcnjEJuYX/NdbDK7q0NA1D86970OprqX07FMQ8BP66J+ir92IcK5A6jHk9HdB0aHzMxgVt7= AlqmE6gt3HbLwG9DQJdFWwuqIdWzYT3HgFMlJFaffPQQj8996HWlP3mnzRjuMwNDTE1q1befLJJ= 0kmkwSDQXK5HMPDw1RVVZFMJjFNk5deeomurq6l83X4pZfwnRiiODyG6vGC45A+fITUkeOE2lde= wkPuwhiGwcYNG0iNjlMcnKTxmcNox4aofsfbqL1xB6qvPKjOz8/z0EMPsW7dOnp6esj1DXB0eBT= FgUB1LcRi5PqHGfzmg4S7OvBXnv96k7PJ5/M8+J3vkM1lCQaDfPC/fHBBNFj09vUxMzuLx+Ohoq= ICfyBwzm+FoizrD8/nchw+cgTHtskuuLgW72BD12ldsYJoNMqqVatobW1lZGSE9vZ2fD4fzz77L= DU1Naiqis/no76uDgE8/fTTrF+/Hk3T6O/vZ8WKFXi9XkKhEAcOHMDj8dDR0cHwyMiSQPJ6vdTV= 1REMBlnVtYqRkRGCwSD19fV4vV46OjoIh0IcOXJkSUzlcjnCoRChUAN+n5/KykqGhoYIBALnFCd= 9Jc4+5xeyLp6N1+vhlu2bSSZTBP0+BgaGic/kGR+boKq6htamNqLOLDuvuYpVXauWRNClbPvs71= /1naMADb7y33KNV+R0HmnaOKkiub/ag/mjflShEE4XSZrg8Xq56qqreO7ZZ1FUhZaWVrbt2MH3v= vtd1qxdy5vfchsVFTHufMc7eP65Z7nxppu4adcuDI+H7Tu24w8E0DWNzVu2EKuuRL8LZL0f5Zp6= 9Hs7cQpFtNvaUAeTgMBRQcQ8GL+zGmMyi7KhGqkAF6lZVj4hoBoa8bjN8BiYpkRVBI7toHuhrkb= l6b0G1U0OQ6cFW3c4nHg+wETeoDuj0zQn6T0iqW2FhlqVbEahvgnMrE0271AoCQoFQecqQUVIQQ= 8YZGZy2I5ENTSErpKZzVPZVXlpL54VCoQ2Ir1N0PXniOpbQNGIRnXe8Y53LA3iW7ZsOT+ubikmD= 5oiHv7mhgZMOc6KmJfAJQjKxUlcIpEgHA4Ti8Ve9q5Tgdr4JmTDrS9rc1n6qp1/wNIoLgQoHpSG= XUsmR7X7jznX/nhm0qXU3gi1N5x/8S5hHHAciWlamKaDqggMj3bB8hdl66ZAUcQ5llZHguWArgo= cZyGLXZQ9NrL8EV0V2Av1EgE0RVz4xbcLouaMrjkjvsrXSCGRyaIgyBdLpHL5soQ/u07doqgXsv= zvDeKys9vw1OCp2cKO1VNcu8pemJlxlspzIHkYefDj5aA0Wa7zIAAS+5Hz+8sbUg2ofTNovvP3I= yXpTIaHH3mEYydP4vP5uPXmm1nT3b1QC6X8AHAcZymjwbZtnIUZzLqKIF2hNnqiASIe/UzTpMSR= ErkQ0zI0MsLDjzzCLTfdxKqurgsetxACvwHXdKpc3VnuQGcucHkdNRzBd+c7Kdx0F3kLNK9CNgu= aHkFGfpui/z149XJHNKRgaMZmcl7y+zfqmDb8wyNF2qp0bm3dhqIszCp33Ybv5jcv3RCvVcmrqs= rWrVuZn5+nu7t7KeVfSkldXR3RaJSdO3eiaRq7du3i9Ok+du3ahRCCdU0tDDz4UQQC3e/DqK4i0= zfA2Pd+SPWOa/FUnf8euFeDTKYZ+/t/IvuLPchCDoTK7MAQwYJJ02/fjeIxyOfzVFRUMDExQXdH= B9mjx2Emzv/P3nvHyXXVB/vPuWV62ZnZvtoiaVe70qp3S7ZlueJeBAYTB/iZFkJLCLwBYn5JSAi= EYmoIJa+NDQEM2LiCMcbG2LKq1duq7q629+nllvP+cWfXkq1mbMeGzKPPStqZW8+955zv+VZbsR= CREHjd2AMjWKMJBp7dTNPVl54x43YgEOA973kP2WyWO++6a8rXyaW7uPqqq7ngggtQVUfj2NfXh= 2070X+maTI6MoKmaS/kwikOypVVVfz1Bz6Aoig89thjbNy0kRk1jrbU4/FQW1NDLpejqsox99bV= 1U290zNmzAAcjYyu61RVVVFZWemc0zDx+rzU19dPvftjY2MsWLBgKit4ff0LARCGYRCLxQCoqKi= gpsZZjEymUmhrbcWyLNxuN16vl8bGxqnvC4UCmUyG8vJyqqurkVKesjDxiRiGUcwW7wzOTtoJx9= RqWzaariFtu2ieECAlhmli205epUDAz5uvWkNFcAMb9TTx+gimaaNZaabXCNrbVjFnzhyisXIKh= oGqKCcsbCb7B1O52wzTcRDSdQ0hlKlJUrycviRBqwiiqKpT/gAQHh0kZP59A4WfdCBMiUuHtS6J= P6zh0hXWXnwJuq6hqCput5tsJsOSpUsds7ppMjExQXPzTGa1zkLaNtUXXcTE+DjLVqxgbGyMcRx= NRc4sMHBdBS6XTjo9hLw6Qr6QR28P4nbFyBfy+Hwmmf5utDUBbNuHke0jMpSjurr6rLcnBBQKCs= 9vM2motTnSpdDWYnNkLyxaKNA0CIUEbbMFWzbbeAVEggp7t5hssxU8ARgehr5poOZNJlKCY3tNc= qagbrrGju0mFbUK5VGd2hUvDTg55+cwSXA+E7O/QFILQ2Kn87yBoKuCiLeeyQzOLz5u3LDYn3Kc= gien1PevqqJeV9DUM2tIbNsmk8mQyWSIRCL4fL5Ta1WEcga55VRafnFu2o8/ckyVUjI4mOTnP9v= J4GCcSNTPjTfMo2l6FEV5aSDH5D1NypbOV4LuEYNf7SrwjtUe0nnJk/sKTIsqbDxiOWOlanP5XJ= 0NR0wG4uDWYcUMjRUzXOinyj4vBKruYnyoHznbnjIZymIUsJSSedObmD+jkS0dh1na2oKnOEdNt= Z2U5HMZspmsk27nVdRwncgfp0kSAqkHEXU3wugWtNzgKTY68RerqEd+kfQqBIRaETXXcLr13aYt= W9i1dy9vv/lmBoeG2LZjh1M6wrIwLYtwKERvfz+RsjIapk2js6uLZCpFRXk5dbEYB48cZjfQUF/= P4NAQAic5WCqddnxaqqvZsGkTI6OjBIPBc7h35+ZO3w+ch3eo1+bIqE3EI/AokLHBMsGyIWtJZl= SpLJmh4XEJOodtdnRZ2DZEAwoXtGmO6lm86LivEkIIysvLKS8vP+N2lmWxd+8+BgbWs2PHDm5+y= 83En36W3MAQCFA8HjzTakkf7yF96Ag9P/0Fjbe9A833x9XUkpZFYu8Bktt2o7c2w7FOtPpapFAY= +vVvKX/TWnx1NYTDYdra2pxEfYbJ+LadqLVViHgSLRYhNHMGwaaZtL3/XWh+7ylTEpzQGGiaNuV= Y3tzczMaNG7nqqqsAOHjokLNZMUotGAxiGgY7d+6kp7eXjRs3Mn/ePPx+/5SgLhSFbDbD+ueeQ0= qbQ4cPMbd97pQDuVEwONBxgPHxcSKRCHV1dfT09DhtUPRDmhS8UqkUuq5Pmchs23aErNpa4vE4b= rd76t90Oo1pmlOr28lnMOn743K5pnyWJgXjSbOhbdsMDg6SzWbRNG1Kw1ooFKYi9oQQzJo1C5/P= d9rm3HvgsFOQVgpSqTT5gkGsLER1VTm9fYM01NcyMDBETXXl1Mq++3gfqWyWQr7AkgXtVJRHmUj= lWTl/FqmUUztQ11UCwRCV1XXEUzmObd2BEM7kFi76F6mKilDEVPi3IgRHu3qRtkljfR0+r5exeA= KP24Xb7cLncVNVWfEibcApXhEEyrQA0lWsUaUJlKgHe/cw9uNdqLVB8Kq4wz7Onx9Bj6qYukI4H= HLa3e0mn8s5NQeR5HN5PB4Plm3j0jQMw0QvPhuv14tiWng9XvL53NRkblomqq3icrudsUFxtAiy= KBCqmoZLn/RfcoqV29apgyhe2gUENXXwl3+hoqgaF5jSyV9VcCas6U1OjItQYPlKFaMgURSVfMH= J7YYQ6BqOC43lqBUWL3AjJZgGKNLC7VFPeif/WJy5J8AgkqeP/Bt5c9K/VTC/8houbPorlGLeJE= OaKEJBEyoSOJw2+NvdI2SLzaIKwUUVXj7TUuak/TgNkwsGeCGx5J9KSg7Lkjz04B7mza/m1gWLO= XxohB/96HluuWUhli0pFEzqasuwbJuBgQRlZT4qKgIcPepE9TY2RnF5XDy5r8DxkQL7ejUqQwo9= YxZuHWrLYH69xnOH8jy5N0+yAEubdGrKVKrCKqcLflQVhSUrzmP900/Svmw1Hr+ThseybZKZLJZ= tc9niBQghuHrFUnRVZSyZwqPr+Dzu4r2ZdHbsQnP7CJe9Ukfy0/PHO24LDULtMO0GZOc9YJ67Gn= 4KTwWi8VaEt+qUQoAE9h04wKyWFtpmzWJ6YyPNM2bw26eecrQgs2bxxFNPsWTRIjZu3szRY8d4f= vt22ufMYWR0lEAgwOYtW2hpbiaeSLB561baZ8/G5/OxfedO6mpreW7TJmLFye/FPgx/LELA9BoF= n1/g1Z0fw4aC4Qx5BQtqos7A0lSh8N6L3RwftVEENFYolAfPtBp5dTiXF0oIQTgcYuXKFZTHYsh= 0mp577wfLcgZGv49AYz35/kHqb3kzgekNSNt6RaseY3gMaZqo0TLkeBnuGU1QMCgc68bKOn4/Pp= +PRYsWgZRkxieov3kd7lMWgG4AACAASURBVICfkW07MPJ5atZcgCscwhM7e8fx+/1ceOGFhMNhP= B4Pb7riCo4ePYqqqsyfP5+uri7GxseKmiWdmpoaLrjgAjLZLIlEnPNXr2bZsmV4PB6WLllCWVkZ= fr+f888/n0QigQCWL1vOokWL8Hg8yKoKhKoQCoVwu9243W4nhUFV1ZQgk0wmpzRTk/X03G73VGH= fQCCApmmk02kqKiqwLGtK0JvURpmmOSW0ud3uKUEpn88TCAQwi9obXdcJBoNT0W0ulwufz4eqqk= 4KAyGm6vpJKc/qfD8xEWfztj1YpgFCIZXJsLh9Fi6Xzqbnd7Jl+y4y2TyqkOQKJh63i2wui2VJT= NOgr3+AC1YtZW/HYUwjj2la5HN5opEQecNC37aHiUSSxtoqYhVVHDx0iEQqDULBrWtoqoaqqVRX= xqiMRYgns+SyKX7926cJ+n0gBJlcDo/LxfLF87jy8rVnFZIQoMwtx/3udhSfGyXmhTofWnsFgS9= djPRrSL+O6tcRUS+KX0dVBE3Tp78kz9XZ0iq8kERy0ixz5lxZp0vZ8HInDE0XaPrJz3bKZSz00u= 3PFSnh6qsFylk0NS8HgWBm9Hy6k9voGHkKy3a0hXaxWLmUkpF8nP8+/gQrorNZXDYLl6ojERgID= CkRSKb5dG6p9RPUTm9qmwycUBRlKgfTn4qABE4qjvhElhkzYkQiPmbPqeLee3fxwAN78PtdRKM+= Nm7oIpcz8Xg0jh+f4LzzpnPkyAiapjDUlqJ2Vj0jSYsLZrl5an+eaxY6L4aUcHTIJJGVdA6bXD7= PzcbDBju6LIaSsNZ/+rYSisKKVefz5K8fYv/2TSw47xJUzdEUGaaJRGIWtcuTml+rGPE26didmh= jl6d8/xbzlawiXnTnX4SvhFaTLFAhXGdS/DXIDyP5fFyO2zhF3BFH/ZkT1FZzOO18AoWKRwWw2S= 09fH7996imElMxrb6eutpYt27axcN48xsfHGR0b4/xVq9i/fz/pbJYbr72WGTNm0HH4MLFijpmL= 16zhD889N7UyqCgvJxaLkcvlKAu/OqUjhBBUlmlUlL1wH5PIqW2czzUVqiOC6jJlauM3ShdUFIW= 6ujpisRguXSe5aw+KgKa/+v/IdPVgjowQap+Nr6GeuhuuQfP7XtEAIhQFb+M0NFUnu3kXGHnMse= cACC5sRw85mr4THZq9kTK8q5YjAH/DNLLJJGV1dU7kzzlcS8DvnzItCiFoamqivr4eVVVZtmwZS= 5YsmZp8lKJp56qrrnoh/YCqTuUuWr58+dQ5b7rxpin1tXKCSchV74XieSbvRQhxkhZz0gQHp54g= JyfEYDCIpmkEixF8kxnVJ/c5UX3+4mNNFuad/D4cDp90jBP3P3HyPVvyuAVz26iIRRifmEBKC8u= SVFdWECuPUR4JEU8kKeRzWLZdNF2dICDYlhMJVx7lnTdfy+jYKIWCQT6fw+Nxo+s62WyWQqGAz+= ejqqqa9lkNjI+PcbSr15n46mpx6QoBX4BwWZhwuIxEIk4ylSKbyaK7XFO5cyrKY+eWDE8IRyD63= BqKafFBLdaeKmqWT9dpzyWQ4mzfn2mfs/l9vd4IAdoZhJA/7pgCt+ZnZe07SBdG6UnsxLKcckhS= SlJWli8e/Ak/732aem8lX5n31ywsa2YqCSaSmEvjvQ0B2oMutNNEak2a1DVN+5MTjiZRFIHLozE= 8nKKqMsjQUApFcXyMmpvLaW2r5PP/9gSmaVFXF0ZRoKNjmPnzq4lEfTzzbCe9SgUDSY1Up6B/zO= TQgIGUTldordGYO03n8IBB1K/gdSmsmKkzLaridyucyZs6Eo1x5Y0386uHHqS2YSaV9TNRFYVYK= EhuYABjzFmcStvGNgw806bh9rgdc7VRYMOTj1KwVeYvWoLL9SpX6zgBMTY2Jp3GVPD5fGdfVb0Y= aSNzg8iue5DdP3dC/M80zQsF/PWIpnei1N4Auv+02zuq+ON87667CAQC5PN56uvqkEBLczPtbW1= 89847qSgvZyIeZ/7cuezZu5eqqir2HzjA8qVLOdbVhcAxORQKBf76fe+jt7+fe++7j4Zp01AVhY= qKCpLJJG+/+eY/yY7wP4GUEiubxTYMhMtFrq+fnvsfouEvbsYVDqNPZp1+heTHJ+j8jzsZ+PF9W= IkEUgFPQx0zP/V3VF5+EcqZ3s8TJv7XXBVX4pRMmgsn81hNarMmM7mbpslk+QFZrEXl9DnHh2jS= Dwsc/6bJY01q1CaDLCZX9pM5pnL5PPZJGjXHRDnpoOqYTPKOz0jx90kzZqnP/2liS4ux7HE29N7= JsbHNzC6/nIW17+BfD/yEH/c8Sc4uoKDQHmzgK/P/GqE08eHd45R7ND7YGOKicg9+TTnl7PPiRc= SfKlJKDh0a5hc/34muq2SzBldfM4f1zx5lYCBJWZmH+voImbRBPJEhn7OpqQvTPqeKUNjD757ux= DNzFqtm+6kMqew+XmBPj4EQgpYqDbcuWDZd56n9eZJ5m8EJm5E0uHWFRQ0qF89x49FP3365XJa7= v/+fKPkJbnz7u4lWOVHb8c2bSe3bh53PY6fTmKkUlddfT2DuXCSSHc88xv0PPsKt7/0QrbPbz6m= 80LlgmibpYk64SV65kATO5GRlkRM7kV0/gOH1YBdOyu8kFEANQu3ViPq3oQRacJJknOmwzos6Nj= 7O8d5efF4v0+rqSBQT5IWCQSbicXqLYc+V5eUMDA0xNjZGdXU1oWCQnp4eLNumurKSVDpNbdFxt= X9ggEQySW1NjTN4G8ZUor4SZ8e2LMxUGj0YOLesu+eItCVGOs34pucZe3YTalmQqssvJjhrJspp= CoWWKFHifydS2mSMBIfHnmbcnOCnwyP87PjTGLZ50kJpVmAaf9P6UbqyNdxc7WeGXz+tBunPDdu= 2yWYN0uk8Ho8Lr1fnzv+7idlzqpgzp5JQyIttSxKJHF6vjqoq6LpTPy+ftxCailtXUITAsiU5w3= Y0hIoTsKSpTioL03LizcxiYk6XJnDr4oz+XlJKxsdG+d63voZWiHPLbX9FTeMsbNNC5nJwgmZcc= buxpckfHvkpP73vYd79ob9j6Yrz/jiZ5TS8dkISOIISOMmvcv3I+F5IHwIrDVoEgnMQ4Tngir5g= XisJJCVOwSsph1GiRIn/XTgRUZK0keH3I7t4dGgTB1LHyckCqlSpcUe4sHw+11atYpqvEk05tfb= oz5kXj6mdnaOEw14ikdMHYbw0yu3E45xo5n1p+aMTtz3T2D25TXxigv/+wX/R3bGDG268njlL1+= ALhKc00IV8jsHugzz0sx/R0TXEB/7m/zB77rxX3Qz62gpJJUqUKFGixOvE5IRrIzEsk4JtogiBW= 9VRhZOhubTYcnijFc52SmFl2Lj+GR578H6CbsnSZUupbZhJOj7Orh3Pc6izl9kLl3P19TdRXVP7= mlx7SUgqUaJEiRIlSrzhmPRnnBgfZ/OG9WzfsonExCgut4fmtnaWr1pNY9MMPB7PaybclYSkEiV= KlChRosQblklf5Gw2QyqZRNd1AsEguv7aB1mcSkgqecKWKFGiRIkSJd4QTEYU+v0B/P7A6305vL= oJLEqUKFGixKuGZVsUinmdSpQo8T9PSUgqUaJEiTcgtm2zr/Mw37j/LlKZdElQKlHidaAkJJUoU= aLEG5BMPssjG37Hz3//a363/bkpX40SJUr8z1ESkkqUKFHiDYZEksyk2dt1iHQuw2Obn8Ywjdf7= skqU+F9HyXG7RIkSJd4gmJZJ3ig4Nf+EIBoI49J0qiIxLGmTKeQQgEtzob1KpRhKlChxekopAEq= UeI2ZNJNIaYMsRm/8iRbMLPHaIaXk8GA3dz/7SyxpM6N8GrX+CvYcOcjqBUvYdnw/PRODlPlD3H= b+jVSXVbzel1yixJ8VpRQAJUr8D2LbNvlshqGBfvo7j5AYH0Z1ufAGy6iuayBaUUUgGEJV1ZLAV= AKAqD9M50gfu7o78Lk8vHn5Fbz1kqv5t0e+x5ajuwG4pP08XJrrdb7SP19s2yaVSqCqKj5foFie= Q5LP5zDMAn5fAEVxtHiWbZFMThDwh9FKtSX/LCk91RIlXgOkbTPY082ODU+TT6eondFC8+w5KLK= AkBaqlSKb1NFUFa8/8IqqWE86856q1EBJ+PrToswf5K8vfhuff+T7dI30cqD/KCOpCQ70H8OwTO= bWz+Kd599AyBuYqlL/cigYJgOjcQoF84RPJwtzCQQSxEvrc0kpkEI630sxubmzhXT+lcUfceKuU= iCFjZjcBxDCKYQqTiyAPrk5IIUsXssLNcOEEETCfsqC3pfc86SmdqpmGNK5JkUg/ogqbZlMiu/+= 4N8JByO845YP4/F4kdLm4JE9dHYd5LK1N+D1+qe2veu/v8ZfvvVDlMeqznhc27bp7e1FVVWqq6t= RXoXC4IZh0N3dTTgcJhaLlfr7a8DLFJKKRWyLOF3qFAXvprZ+KWf67mznPvG8/zv4c4pkeQXPTE= pOqrT4Bh8IpG1z/OhhnnnsAbw+P4vPW01uaB+ju9ejSBvLBtvIobjdlDUtonH+pai+0Mu+rxOjn= SzLIpVKkUwmqaqqQtM0lBMqaJ84eJ6qGOWpjn2m70/c7tUcmKfMkifx0ppbf26TgW3b7Oo/SHd8= gKgvzFdv/RQjiXGOj/YjhOCDl7ydlupGwv4gPYlBHj/4HK0V02mK1qAq5y5gD40m+Ow3H+TY8WF= sYU0JJQINYasomMUxXSBQQCjOKORULwcUpFSwFQuJhYpalJYEkEeio0gFhFN0FgsQeRQUpFAQNi= iY2EIghYbARKIhpCjOJwJLSmxpo6oKQhGAQNdU3r1uNTdcugiX/sK0JaVkKHmAbd330Fp9NdPKF= rPp2J2MZY6wrPE2qkNzprQ+5/ocevu7UBWVnXs3MTr2VmprGgCBaRoUCvmT+o+UkE4nsCzz9Act= 8qtf/YoPfehD6LrOww8/TGtr6ynfY9u2sW17qm+dTtMspeTRRx/lPe95D62trfzwhz9kxowZ53y= vJc6NcxKSpJSMj4/T19+LoqonLRukdJYRQhSlYnGCICRB2hLLtpyHrahOXxIvfG9bzgshVAVVUU= 6oNlys5WLZSCSqoqAoCjYSVahMb2rC5Xrt05S/Xph2joHUsyTyR1/vS3nFlHsXUhlYxssVlKRlY= fUNUHjwEQrPbUKNRXG9+Qb0ZUtQvJ43nLAkpcSyLIb6e9j0u0dx626WrFpFYfQw/mgNtXPXoLv9= SNsmEx9i+PB2Jjp3kR8fYvry63CHKlBU9ZwrWzup+7N0dnZy//33c88995BMJrnsssu47bbbWLB= gAeFw+KQVq2ma7Nu3j2QySWNjI4VCgZqaGqSUU9tNClzBYBBgytygaZrjUKwo5PN5stks3d3dzJ= 49G4/H86q0YSqX5A97HyeeHnPuEUnUX8OMmoV4XAFURcHvduFzu3Bpfz5mSolk79BRvvzMPVi2R= VvldD576QcIewNYts3qlsUMZEb44EOfpzcxRHkgwmfWvpeGSDUvRwcpJQS9bv7pwzdQEQ1gIsnk= De576Dn2dA/znpvX0tpQjW1bpFJ5Hn9mF89u78TrVfnA2y+mc2Ccex96nvNm13PZxQv4ySNbOdz= Vz/lLZnDT5Uv55j2Pc7hnAhWBpgouWjWLq9bM5z9++Fss2+QDt1xGMBxkYizO1+/6DU3Tq3jH9a= sxTZv/fnAjvcNJbnvLarZuP8xvnts79e6ZtoVpv1h4BssusK3rPtYf+in94920117Jr3f9O5ZlM= Joc4M1LvkbIe2YNz4kUCnl27dnMkoWraZ7ZzsYtT3H91beiKK/8Pdu7dy8jIyNkMhnuvvtubr/9= dvx+/wnPRlIoFFi/fj3f//73OX78OCtXruS9730vM2fOPMmcJ6VkbGyML33pS4yOjtLd3c34+Pg= rvsYSL+WchaRDhw+ya99ufAEfUkrSyTQjw6PEEwkURRCLRSmvLHcEFwS2lGQzWUZHRhkaHAKgqq= aaqupKdF3Dtm0S8QSD/UMkEgk8Xi/T6usIl4VQFAWjYDA6MsbgwCCFgkE0FqGmtgaX20U+naOiv= JxoNHqW6wbblpimRErQNIGmOS+7ZTmfg/O5okxOBs4+AIoiXjIPS+nsa9sSTRPFFOont5VpSizr= BeXHiSiKcz5VPXOnM6wU+4a/z9Gxn4EEWyoUChpCSHTdQkoFy9JRFAtVNZG2C9tWUFQLRSlwLlq= okwTSyc8m7+NFv5/qs3OdnxbV/AMVgWUvT0SSEmtsjPTH/h5rfwda+xzMfQcw//aTeP//T+K+9k= rEGyy6p1AoMNDfx8Edm8jlcyxfczmKmaZmzgX4QuUnOWt7gxHClQ2Mds2gd8fv6N7xW8rnXAyah= 4qKszvkOj4SeZ544gkefPBB+vv7p1aRw8PDfPe73+W8887jne98J+Fw+KRr3LlzJ83NzTzwwAPE= YjEMw0DXdaSURKNRstksO3fuZNmyZaTTaTRNI5PJ0NraisvlIhqNsn79egzDwDAMWltbX7U2TOd= TPLvvSaR0VtJHBw7i0txcsfgGrlj8FsbSBQ70DhEN+plTV4lb1/4sBCVFKFzVej4bj+9mQ+cOOs= d6eeroVtY2LCkKpoIH9/2e/uQIAZeXy5pXsrC2Fe1laEnA6bv+gIuZ9eUYtsmBY0PkLUk2bxDUd= VrqyokGvew+1EV9dSVvvXolHccGkQha6ivwenRciqS83E9zYyXV0QDHuqGxuozWhlpqYmHGk1kW= tDXQ0zfMjj1dXHvRAgBUzU1leYiqWJg+YSE0cCsKDRVl5A0Tty5QhU3ArXHgaC8VERcXLm8nl7f= Yf7gP5RTPWVE0ZlVdynhmiLbqixnLdJM1JLatMJYaw7Dy59w2tm0zMjZId89RVixbi8ft5Tt3fp= 4LVl1BeazytPudq77/1ltv5cc//jG7du3iJz/5Cddeey3Lly+fEn4KhQL3338/t99+O8eOHUNKy= YYNG1i/fj3f/OY3WbhwIZqmTfX9H/zgB+zZswchBJdffjkzZ84853stce6cs5AkJaiajqbp9PcP= sPGZ5/C4PNTX12NZFts3b0N161x82cX4fT4y6SxHDx7BrbtprGsgHA5z9NhR9o+OMn/BPOITcfb= u2suCeQuYXt+Eruts2ryJ6c3Tqaqpoq+nn9GhEea2z0XXdQYHB9mzcw/zFs2byu50psHRtm3Gxk= w2bRph9644+aygscnNRRdXobsUNj47TkdHGktK2lpDrD4/RFW1G9OUbNk0CqrNkiVRPG59ajWTy= 0m6j2d5fssoPV152ub4WLI8RlWlG1UVCCExTZMNz43x5JMpTNNy2k8xABXVVvF6VJpmqly0tpqq= KjdnNEvLSW2bxuGjjezaW4umSua3jxD01zIRn4XuylBZvhNdnA8yhi36UD2PoKgDAORNncGJELW= RCTTVwrYVbASaYp14GjJ5F6m8B121CHszZAoeTFsh7E1P+RjEM14kgjJvptj+5/L2/HFIoPD4k1= hbt+H71lfRzz8POTpK5l++SO6eH+O6bC3ihFXY641lWQwNDTI62M9I73EiFdUEQz4isSY8gQiIk= 01GQgh0l5fypgXYpkHfnifJjnbRNWwQXrUKl9t91sm/UCiwefMmAoEAs2fPZnBwkMbGRo4fP05z= czNbt27l+uuvJxQKveRYpmmiKAq9vb0EAgESiQSKotDf38+SJUtwu91s2bKF5uZmjh49ysqVK3n= yySdZt24dR44cIRgM0tnZyaxZs171iFi35uaa5W9GSPjKg58lZ2TZdmQDa+ddwfSKaYwl0/SNx2= mIhXHrpx/CbNsmkUhMVRc3DAO/30+hUEBVVUzTxOVyoaoqlmWRzWYJhULkcjl0Xcc0TTRNI5lME= olEyOfzFAoFvF4vfr//VRHOJJKMmaczPUzayPPmJVfSUt7IcGoMy7aQvOBv49Fc3DT3YmrDVbRN= a+FwZpiwmaY5UI36Mv1bpIDj/SPc+9CzZE0Yi2cJ+d1IoGdkjP/44RNcccF8rlyzCL/PSyqbP/k= dFs4isioaZOa0GOUhnzNOKIKq8jC3XLOMzduP8MvHt5FMF8cL5FRdLkdcK/5/0lpXPLRl25i2ic= ftZfHc6dSUl/GAvQX1FNocRahML19GfXQ+oPDMoR9iFFxY0qJgKBiWgWlN5peSCFHU1J5iyWZZJ= s/vWI/X62ciPoqu6bjdXrbtfI5LL7rO2UbaLxKKJOIU5uBTUVlZyfve9z4+8YlP0Nvby9e+9jW+= 9KUvUV9fj2EYPPjgg3z605+mq6tryqRn2zabN2/mYx/7GHfccQcLFy4E4Pnnn+eee+4hlUpRXV3= NbbfdRigUOus1/E8gcdpJIFD/DBYwL8MnybEZj42M8dB9D7DuxnXcdNNNhMNhLMuit7eXu35wFw= /e9yA33XwTo6OjlIXLWHfTOh5++GH8fj/ve+/7+I//+BZdnV0cPHAQI2egqRobN27khhtu4C/e/= hf85N6foGgKvd093HTjTfzyl79ECEFLSwstM5vpO95LVWXVGS03UkqSCYPvfLeH+35+nEjEi8ej= 8fDDQ9z7835i5SH27RynvNKPFJKf/2yQ5St9/Ou/zsXnVfjNr5Mc6hzmjjvKqKl2NEfHu3M88tA= QjzwySDyZIRwMcP99fVTVdnHTuiauvKqS8nIV04QNz03wve+OMG+hl4BPIEUWKTWkVMkkJEfvmu= DK6yb4/L+2Ewic4RFManoQ9A5Usv9wPW4NomUV1Nc1ksu1YVgpcrkJPJ6lePVa8vZhDOt3CMXZv= X+inD/sb+OyuTuxEYwngwwnAsyqGUBVLRQhGU4EMWyNRNZDJJAl4c7QOVJJ2JvF68qiazZuzeDQ= QA2xYJJwfddr6xVWNOXaBw6iz52La+UyRDAAHjf6+eeR//b3IZMBn+8NY3LL5/McPtiBV1WwDJO= a+ul4vCFUoWMVCkjLQnW5kLaNncuhFM1TtmEQqpzJWHAP6eFjWEaM4cF+6hqaTnmeE520dd2Fz+= ejsbGJsrIyHn/8cVasWEE2m+W8887j2LFjhMPhKdM1gMvlYsGCBSQSCa666iqSySRutxvDMEin0= /h8PrLZLJdffjkul4tkMsnChQvRdZ3q6mqmTZtGNBpl3759rF27lkgk8oqczl+M46wrcOsehHxB= u5vJp0nnEtREFdy6ilrMI2RYFvppfDYKhQK//e1vSacz2LZFNBpD01QymSxerxdNU3G73cTjcXw= +P9u2bWPFiuUcONDB7Nmz6ezspK2tjYcffoR1626kv3+A3bt3sWDBAi655BLcbvcrv2EJKSPHFz= seYePIIYK6l7fVn8dtc9awt+8gQihIbIQQrGiYx6yqGXz72O/49u4fk7HyvK1+Jf8w+wbUl5EXW= OD4Zrc01fE3t72JVDrPt3/6NLm8iQQiQS+XrZ7P7Jn1iKIJeVJfIoo+gQIFl65yw+VLeNOF8wj7= HNcHW0Aqk2PfkQE6+8axAKUoyMrJP1IACkIWvVzFCdoYAV6vmyVz6vndc4f4xp2/ZXZLDalkhtq= a2CnvR1FUdOFFSolfr8SyvBSsPKPJOH/Y/zMkAsMqIKVNmb+KedMupC7SjK6d/PzSmRTbd24gGC= xj287nEIDH7eH3zzzKiqUXoaoayeQEhpFHSkdITqdTSAm6fvZ3QdM01q1bx3333cfvf/97HnvsM= Wpra3nrW9/K1q1b+epXv0pXVxeqqrJo0SIWLlzIE088QVdXF+vXr+cjH/kIn/zkJwkEAnzpS1/i= 4MGDqKrKbbfdxqJFi07dByyL/mwCw7ZxqSoxlw+fpr9m2lcpJaP5DBvHelgWraPS/cJiwrRtxgo= ZxvNZPKpGlSeAW9NPtlZIiSFtNKGcUnP4evCyHLdN02Lb1m3Mnzuf6667jt7eXvL5PKZpkslkeP= dt7+Zjf/u3dB09BghWLl1JLpfjnnvuoby8nCuvuorlK1by6GOP4tLdvO0tb+Ohhx4imUximiaRS= ISKikqGh0doaGhgZGSESCTCtddeyze+8Q2uvfZatu3cTnmsnBfFUryEjkNZ7r5nkGuvmsEHP1SB= xyvo6MjxkQ/uYfeeCf718zO5dG0Uy4KHHx3mi184zJoL4lxzXZSMoTA85KGQc8xqO3am+Myn9zE= yZHD1dVVcc90cKis0urvz/OLeXr7y5YM89dQw//jPs6is0DFsi1jM4gtfaKau1s1k+IeUgmTS4h= //sZsnnxhl4uPGGYWkSQ2OEDZV5TmuXNvr5G+QLtyuw3jLezAsBdMeJltYjyFzGJaN6iqgucC0F= fZ01qEoKru7G7FsQX3lOMm8l51dDbg1A8t2EQoV6B4KEvWn6Bv1cCBVS1V5gWRO0NFXSzSUpVAQ= CF2hTKZfVQFJ2jb24BBWMgmAEgyixmIIXcPz4b9C5nJYiQT2kWMItxu7UADTBMvRhNnZHNbQEML= nQ41FQQjsRBJ7eATbNBGqghKNopaFEIrqmHHSWSQSYUuQtmMWVRWEoiE8boT28if9bDrF6NAAFW= VhJJJQJEJmbwfHfnAX0cuuIL5zF9VXXEbm4CGyx7pQoiH8s9sYfOCX4PXif9NyCsYEvrI69u/df= UohadJR2zAthifS2JZNzbQm6murCQYD1NTUUFNTQ0tLC9U1Ncyc1Ua6IIkPTRAL+/B73aiqSnNz= M6Zp4vF4plT9Zyt3kcvluO6669B1nUgkwnnnnef4EhY1A2fb37IslKJf4ctFCPC5AwS8YQzLJpM= 3nbpmPYNEAj6mxcIEvZ6XDKqWZTE4OEg8nnA0d7qL2bNnc/jwIcbGxnC5XOTzOfbvP8D8+fM5cK= CDlpYW2tpaSSYTrF+/nsrKSvbu3cMll6xlZGSUo0c7qaubVhQcXjlCCMpcftaUz+bR3u0cSgwwU= ciwPDKDgNvvuH8WfXECLh97k738qGs9/dlxZgaruKJqwcs2uTlIEok0Ozp6yGZM8ukC6AoShfJw= hJuvWYmwv+Bh3AAAIABJREFUJc/vOMzYWApv4MVCgI1pWuw+dJye/lHmNdexsM2HRDIwNMZdP38= abIWWpkoqY6HiGXF8v7EBGylsLJz+Zxd/FEXgd7l4+7VrWDCnmcef2samHUcwbFg09/TmpMmJuD= 7ajq6Vk8oNkswW8LnL6Rrdz86uP5A382iKxjMdj7Bu2UdY0HAhHt3rXJuUHDqyl9qaRm685i/xe= LyAwLZMvnf3l9iz73laW+YxPDLA7r3P0zZrPoVCnl8+cg+tzfMI+INnbXEhBJWVlfzDP/wDBw8e= pK+vj+9973v89Kc/JZvNkiyOga2trXzrW9+iubmZX/ziF9x+++0MDw+zadMm3vWud6HrOvF4nEK= hwLJly3jf+96H1/vSqD+npSVPj3QTUHVsJF5VZ01FI15NJ2eZICUeTUdKyBU1bl7VEaJypoEE3K= qGRJK1DDSh4lU1LCkxbAtL2rgUFUUIspaJAFShkLQN4kYer6Lh010gJdvH++nKJmjzx9g40c3a8= kamqSEyphMs4FV1MmaBJwePsrqikTKXx7Hg2BYuRcWlaq9LyNbLEJIkRj7PQF8/n/7Up/nZz35G= PB4nFArR0dHBvHnzWLt2LZddfjk79u5gxoyZFAoFgsEgDQ0NRU9+KOTzaKqGrum0traybt06Nm7= cyOc//3mmT29CAs1tLZiGIzQFg0EmJiYwDAOQuHS9qDw486B87FgSy7BYfYGHxkYPqgp+n0pbSw= UHj2W47JIYtdVupJQsX1KGrgXYvTfJlVdHpsyLEhgfL/D5f9tNXy9889sLWLLUj9slUBSLmpoQ8= +cHWP3bCj7zySP88O4+PviheiQKqu4jEnHj8ah09xbI5ZxLHhky6O/JMG2ags939glDFLUAHUc0= Nm6qRijQPtsgFGrGKMxHUiAW/SWR8Ftxa0HyZjcJa+vU/q21fURDhxhJ+HBrEkW1WdSYIl1wIWx= BWTDDQDzMosZRPK6C43MlFVJZHxWhBBF/Al2z8LnzjKcC1EQch1ohij5Xk078p7v+s73VBYPkX/= 0N9radICRKeTnuj34Az803ofj9ZO/+b/J3/hA5PIJwuZBuN+rkxG7bGM9vJ/vhj6MuXoDvy59DC= YUwf/xz0v9+B9KyHCGpqQH3338M96Vrkbkcxi8fxkwkUWwJsSiYFjKbRYlGcV++FhF+eZFmUkqS= yQTxsXFioaBzH4ogMmsWowh8M2eQ6TxCprOTfNdRmj72Nxy6/XZc5RXIkQmEPYpbX0NeZpBC0rF= 3D5e+6ZpTXoNlS/Z3jfLoxmNoiqAi2oqnPEI+O0YoFMLj8eDxhcjYXmYuuYJfPH2ERKZAS30ZN5= 4/C6TFww8/jGEYhEIhVq5ceVIUjWVZqEXn8WQySSgUwjAMcrkcHR0dRKNR2tvb0TSNY8eOkc/ni= UQilJWVoSgKlmWRyWQwTRNVVXG5XKRSKQ4dOsSCBQsoLy8/53adxKN7WNl6PmFfjJ7ROPFs1jFl= C6guCxJwu53X8EWCmqIo1NbWEY3GiMfjmKbB6OgoAwODVFdXYxgFvD4fgUCAcDjEkiWLCYVC7Ny= 5i/nz57Fq1SrC4RCNjY14vV7KysLU1Fbj9/tPihx8MS9nlS6lRFdUbq5fQd4yuLvzafLYjBSSVA= gnF5KNnJp8RgoTlLl9zA7V8sHmy1gYaZw6zrme14log2N9I/zw/o2YEmxpURENApL+4RFSmTz11= VG2dnSTKOTx4poy/xf/wrRsNm4/wqadR1AVyYK26QgENZUR3nzZMipiIepqYwS8ruIw4Qyq0rbR= dRVdczE2nsIyLQzTJJXJ4tJVXC6doNfLirkzmF4b4XP/+ShHe8fO6d4qw40sbbqax3b9hGTWZF/= Pbq5b/C5Gk3H29WwlJy0yuR5++ty3CLpjtNYuQlVUpJRMxMe5cNUVxKKVU8K8lJJ1172TjkO7CQ= XLeMsN7+aJ3z/I75/9NYoiaJ+9mIsvuAZNOzeTsxCCCy64gI997GP88z//M4lEgmw2O/V9LBbjc= 5/73JT29tZbb6Wrq4s77riDXC53knN2fX09X/7yl6mrqzvts3cpKjG3jxpPgJju4anhTnK2xZGJ= cY6lxjGxmROqIG+ZTBRyDORTrKloIm7kOZwcxZA2s4IxCpbF4fQY/fkUb53Wzmg+w+ODR4i6fFx= U0cT+5DBCQsLMszRaS8Gy2DDSzYSRY3V5Aw3eMnbFh7i6poVyt49Kjx+PqjGRz/L0SBd9uRRrKx= oxbJvN433kpcXayulsHevHkhZSUVgdqyfq8p5TO7+anLOQJAFbOpFmfr+fvr4+LrnkEgzD4NChQ= 1x66aVUVlYSKYsgLRu/z8f69c8ya9YsGhoaaGtrY2R4hMd+8xsWL1tM57FjPP300yxevJje3l6+= 853v0NXdzQMPP0BNbTXbt25nzZo1DA4Ocuedd3LLLbewb/9+mmbMKE6SZwlNtgWaouP12gjhzOa= qKnGpOVzCRNcmHa4FLh00JYdRsHGMWxYCG6TC2Hie/btNVq+eycKFflTFMb9ZlgLYuFyCVeeFmT= 7Tz4GOPNmsjSIVhMhTyBv80+3Pcu/PxjFNHwoC01Tw+Hx84Svt+P3n0PzF27QtgWFoCNXGlgKJC= ricJAxSQdPcuHQ/pu0Gq5gvRCrkChp9I2Fm1A7i1Y3iYPrCoaWEitD41DOeOm3xl6rwOHZx29rI= KIf7awh5s+iq8RL5SBQ/kIAi5LkFs0kbo38A78UX4vroB8h+/dtk//P/oi5fhvGrx8l94Q5c7/p= L3G++Hqu7m9wXvw4TcaRpQcHAfOoPWEe7sE0T63gvypwgciKO9HgI/ui/EJpG9mvfJPcvX0Bvm4= XSUI9r3fVoCIRpTAkiEuE4grt05Iu1BIqCOIsGJJ/LMzY2QltrM9KWZNMZ8oYgn06R3LUdPRpB+= P1kJhIMPP442ZExYtEI7roapGlRGBnGWx1mNJkiMR4/jY5UUjAs9nSOMDyRwa0rdA0WeHDDcVa1= V7H60hsIxSJoVRZff2AfHrdKVcSLaUoOdo8zEs8Q8Wv09vYyMjJCU1MT3/jGN6b8cBobGxkaGsI= wDGpraxkZGUFVVVRVJRKJMDAwgK7rJBIJVq1aRSKRYPfu3SiKQiaTob6+nr6+Prq6ugiFQni9Xq= LRKKOjowC0t7efwwtxMqqisXbujcxruoL9/XFGk2ksy9Gs5AomqiLIG1nSuSQv9hYByco1S4sBF= MVgC1Vl7uI2R+No2yiKwvlrVyKEYNHK+ShCoX2xE5rdtqAFIQSf+IePoekaTbPqWbJqIaqqEs+N= Q+7kswkcjZfP40cRZ18A2dKmb+IA64/9CMsu0F62gMcv+DuGjTyjuSSGlXbuojjuKopCm6+WR1d= /Ai95dvc8yn3bfoKuuri87cNEfLVnT9kgJsdywbzmBj770RvJGTYP/2YTPSNJbClIZg2+/8Nf8/= EPruOGy1dy+Mgohm04JnBbYouiycx22tC0DSzbwMLRlgd9bhbMqacyWoZAkDVMbCE53pvk9q/eR= 8AtuPFNS6mp8rF9Vx+f/up92Ai6e4dZuaSVTC7HP3/jASYyFrat0j0wwbkMJkIINEXjLSs+SCZv= sPHIE+zr30O44zesbrmejt6DZApOmx4fGeTp/b9hWqyZkLcMIQQXX3gVhmmQL+SmnqeiakxvnEV= TwyyEEMyc3kZjfTOGUUDXXVPh+ecqoDoaTZ33v//9pFIpvva1r5FMJhFCUFNTw7e+9S3e9KY3Tf= n5eb1ePv3pT6NpGl//+tfJZDJIKWloaOCb3/wmK1asOKt2VkqbjvgwBWkxzRdGAZ4cPsY11S2MF= 7I8N3ocv6LRFqpgdrgCXag8O3qIlZE6cpbB/vgwl1TPoC1cwc969tKdidMSiBLz+Lm0cgZj+Qw5= y+SamlkkjDxSQNjlYXGoioxlsDU+gE/V8WgaQd2NQBB2eR3BX3PxpuoWdsYHOZSeYGlZDY3BKJd= VNdOdmSBp5VleVsszI90MZJOU6S/VGL/WvCxNku7S8fl9bN26lXXr1vHoo48ye/Zsli9fzr333s= tNN93Eps2bqKyuoqKqgsREnDu+egfTZ8wglU7zT5/9J2a2NVNRU4E34GHr1i10dXexcuVKfvP4b= 9i9ZzerLjyfcDTErDmt3HXP3axYtpyly5axfsN6EIK5C+dSyOaLvV2ctu9M2r9PRCAJlyWYt0DF= 63nRiyVPdKp11MEA0gbDFqzfMM5HPzqMqhhOXo9irgMJ5NMa+w/YrFipFTVQNhITRZW89ZZ5XH6= FC7ARKGQyJvc90Mdn/n4PMxrnsnJV9Izd3xngiyaNydwlEjRFRSrKCxF0Qjg5RRQx1SwFQ2f7wW= Z84SxDqSiN5YNMZAO4FIuCqRDwZRlLBnGpJj53gXjOR9CdJWu4yBkafleOWDBN73iMiC+FtBWSe= S+DEyb9EyF8botkzk2ZL0U658GtFQCFguViekU/sVDinEM/hNuDWleLvnAB1p792Ps7KHzvv9D/= 4ha8/+ej2Ac60ObPw/vFfyHzwb8j/7uncV1xCeaGzWg3Xo297wDWlm1oLY5KXtE11NpqlKpK3O9= 7N5n3fghjx248TY0Irxerrx9zzz6UWAx7aBiRzyN9PpTKSuTgILYtEU5T4168AFF15jBiRVVJjs= dBqE5ww/Eupi1YxsyPfxzh9SPzeXz106hccyGpzi6qv/NtsGwCzS0oPg/9Hetxxeo49OwutNM4Q= ksgnS1w8PgYE6k8humERQd9Ovu6xiiYFrHQBLuOjaBpgmzepHMghVtXKFg2nQNxymbEaGlp4cor= r2TTpk243W5qa2uxLIvjx4/jcrmorq5meHgYVVUpLy8nFotNmdYaGhpQFIWenh727NkzFTmnqiq= Dg4NomkZrayvRaBTbtjly5AhCiCnty8tFSpuhZJqx1DDzm1qR1TG6R8bpHh4nky/QOTxGPHmABz= b9iIJ57pFMrwWaqnPF4hu4dMHVuLSz+6goQiHsqULBRffYXnpGO8gW4iya/nZympsJ0tjS0dhI6= aRZcas6GgbPHLqTo8NbkQjm1JxPwH1qf51TkclZHO4boiIcIhjwohcKeL0uCqZBf+8ImYLBsZEc= P3pgA1etWcTs9lq27DrCsb5RegfHsKTB6ESart4RJibSSEtlcCTL4eP9TIwnMKWko7Of/uE4oGD= ZFoopyRk2x4dTaLrCwd5x2ltnsvfwGHuODaNIQazMQ3NDlGM9gxzoTzM2nnPGWQmqqpzTUCKEwK= P7uO2iT7Bu+XumotsM06Aq3MLBvn0gJYaAnV27uGLBMEFPGCEEE/ExvvndzwKgay5saROLVnLD1= bdSU13v+FzZNnsPbOP+h+/mI+//R2LRypft3zPZHz7+8Y+zZs0atmzZQkVFBWvXrmXatGkn9ZPJ= bT/zmc9w00038cwzz2DbNhdffPFU0MRZzy8Ebk1jPJej0RvCkpJ4LkPGKBDWPVxRNZOsZfLUSCf= mmM3V1S2M5rNkTIOw7mZF+TQOp8bpy8TpTo0xJ1DOZG1BRQh6c0nKXF4URSHi9pK2jCnBUVccEU= MRAqOYxiFp5fnF8b3UeIPMDVfy/Hg/w7k0MY/P2bY43/VnEuRNg4xpsDI2jWpv8HWJZD1nIck0n= JombbNnc9cPfsBXvvxlPvWpT+F2u4tp3FM89fun2L5zO29+21tIJBLEKv5fe28eJ9dZ3vl+3/es= tXf1vqm71WpJrdXaLHmRjREyNl4wIOOwJmQYk2EguTcsYfmQuQxzySXheiaQST6BXEjImCFgY8c= xcZAB77YsZHmTZO1Sq7vV6rW6u/Y623v/qO62GstS29gszvl+Pq1uVZ2qeuutU+f8zvM+z++pR+= o6Q8NnQMCyFctJJuNkxsYB6O5ZwtjoOHue3Us0GmX9xvUEnsvk2AS2adOzrIdDRw/h+z7pdJq6u= lpyU9N4rl9dEpuRDedGoJAzgeoqlq3zn/5wObV1MWIxbd62oCNmp0MJUNX7hai+giZ9YpEUQgYo= 4c9VZCgFGhJNy848ZtaILYJh6Fy8pWHmg501/QM7AQ/+ZJxDB8tccikLirgooUBWT9ygoVAEyn8= x5B8EBL6P53uIOSNAhW07GJqHkjpHz7SglEYiWqZQ0GirneLg6Q4qFY3aWBlfSqYLEZpT05zJxc= lJk3w5Rtm38HydjroxTmdqUH61WmtwPIWSGsWKSUMix7EzDZiaJBb3yZYi1CWyC4wmKSr79hP81= d/i7d6DvmwJge9BsYy5/Sr8Fw5TuPXjGFs2YX3uU+iL2nCe3I3W3UUwOIi14+24uQLekz/HfOcN= symm1X1DSrRkAmGa+GNjoFR1Gc620RZ3IeIxRDJZrZgMAoQdQUVsJKr6AQcB2BcO8UajUXzPoe9= kH/FUDWNnTlHZcjkNl1wy98WenYpoW9tcFC7a3k45l0EfrUFLtPD83r/jqmtuOPfBQFXNWzcvb2= LdkoY5zyLfr372dSmbWMSio6kGx/NRM8IGQNcEyaiJYZpcddVVc2KoXC7P7UOaps3rWeR5HolEA= ikl2WwWy7KwbXvudd/61rcSiUTI5/Mkk0mmpqaIRqPouo6uV20+Nm/ejOu6RKPROd+lhWJoBul4= HSfPPI6pTbOyvZ2aeC3LWxvxg4CB8Sk8P2Bt10YWNy9BqRnPNSFhpipsdqIVCinE3Ldzbkrnqsc= kzPxWVKOtKngxWXn2eCOlnFl2mn3uF2N+QkpS0TS6trClF6UCImacizvfgeuVyBSGGCucJAhcJD= N2JDPGitXtq0ezipsnVx4jYqZoTi3h8u73VpeMCBALcE3KTBf5xnfvxxQGKgAhFfmiiwoC/ve9j= +MLhaFr7H2+n8MnhvBcKLkO37njIbxAYFsmh/vG6P/uTym7HrGoyTMH+zl6fJBcsXoR+e3vP4Lj= uPgKoraGW5KkI+bMUrTkkSdewAsUlbJLfcLEccF3Pe7duZeSFyAR1EQ1hNAgEJRcf55D9/kQQmD= qJg3JFy9sHM9hccNqDvQfn5vPM5kphjJDdNQtRtd0XNclHovzO+/6COmaelzX4aHH7uNfd36f3/= /AH1etMEoFHn7sPuyZqre3vOlGpHx1fl2RSIQrr7ySK6+8ct7Yz4Wu66xdu5a1a9decNuzUTO5Q= 012nGY7zt6pM2ypbSNqWuhadSlOCkHOrXB981IeGe8n61aIGwa6Jqm3Y1QCj12ZAa5uWMyIU8RT= AU7gUwl8/CCg1U6wOzPI8ngtlmYACsevCiI38HACnzozQsX3GSxlabXjxEyLRdEUu6eGiGkGi+M= 15HyXQAU4gUfeq9AUSXDGKZI0bWK6ifWbnpOUnc7yD9/6B5b0LGHjlk18+c++zNuufRu9vb24rs= vevXt56JGHufyKrfzw+3cyMjyCbduka9J4nke5XAbBXHKaEIJYNIrUdJQKSCSSjI+N4bgOUK1Yq= K+rw3EdfM+j4jg4jgMKent7ed/vvO+845XCJxLxiUb1udJVXddYc1FDdflt7hunsKMQTzoIXDQN= UkmBYXggFIIA26jwtuvjfP4LnejGS63up7M+5c8exJ+x+pcyIJkIMM2qeebssl71PkU6rROL+Hg= L8PCoVvsoerqzSDmGJhTNTRXi8SIVYxzwicX6yZbvIV+x8fwM0poGwNRdrljzAkL4eJ5JIlrE8T= WkqMrHRKTEliWHMbQAKQPKjomhu0TMCm21Y0ihMI2AQsXE1D1iVoW4XcAyfHJFm55mn7JnYBkOE= cOhtWYCIcHzdFLR/IL2q1mCqSkqDzyMGBsj+oXPgGWBlAQjI+jdXRiXbkZuuAgchyCfR6bTuD97= GH9kHO+uewmGzhD0a9Wo0FnXnEIplOejVICMRFGOg//s8yg/qOYiWSYISTA2jmhrRmtoQF/UPk/= cXeiLKYQgkUxS29DA3t27ePu73kVuOsPeR37KFdfeRDxVM7/8f/YPpXCdEpmhI0QaO3liz14yY+= OsXb/xZV5JUc5lOL53J0EQkEomufTSyxgfH+eRxx8hXVNDY2Mjb37zmxkZHeXf7vs30uk0pmUxM= jxM11vfiqDqg2SaJslkklQqRT6fRylFPB6fG2cul8M0zTnD1tmS97OvcqPR6pVfOp0GmOfHNMu5= blsorXWdfPz6zzEwfpKdT/8zO5/5Z67bdDPJaA3tdTUMT+WI2RZRO8ZEfhhLtxnOnqEp1UzRKVC= qlEhGU5SdEtOlSaJmDEu30HUTTWpIIcmXcmSLU3Q0dpPJjRGxYrieg+dXk1ZLlSLpWNWPreyW6G= rqYWhigFxpmnS8jqlCBtuMkIrWki9mScfqznPh9iKB8hgv7CNTPIIUJpd0X49SNpnC6TkBHagAp= QK8wCeYiU8DaEJjY8eNRM0kQhYZLT7JSCGgPraa2uhypDi/UFJCkUrX4pcVrlshVWMRS3lUKi6p= ZIzAV8SjFQxpUXIrWKZkcrpAU0sjXuASz+tIqSOkoN6wCQIfHx9DU9QIg8mJPHX1SQaHRgk8QTw= RI9pkUSlWiEcNFBrFiktmMouQHkuWLCY7OU3E1DF1yeHBDHXpJJatsK0orhPQPzS+sAuul0GXOk= 2pdvzAxJtxxy4oxVh2ck40AWi6TiQSIxZLoJRicddyjhzbPyOmAwYGT2DbMd585Y3ct/P7bNl0F= clEzasa06yz9qxJKzDjs+fNnK/mn57PJ4pmCwl+sdK0EvjoSAquw4Z0C04QMFCc5trmHp7PjpAu= TrMm1cSkU2aknKfFjrM4nsbWdJ6eifAsT9SzLF7Loew4zVaMnFdhslKiTrdxA58l8TRDpRxPjA/= QHknSFk0SERJfBWTdCklpYGsG1zb38OzUMMPFHPZMrtQaKdmTOU1rJIEb+GhC0mbFOZQdY3NtO8= OVAj+fGGRRNMXqmiZ4VUUKvxwLFkmVSoX+vlP0nTzJVW/Zxpq1q9n73NM8+sRjMwfYBBetX8fDD= z7IU3uewvd8urq6uHnHzQwPD2PbNo8++ijHjx0Hqh/mFVdcwerVqykWi5w+fZpcLsfg4CAAsViM= N115Jblcjng8zoEDB3jyySeBqt/Ehappli61ufXWWlavSs2tYVYFy+yONvtb0dZq8cefaMcyFJG= I5Ma3N9DS4pFMgu9L3v+7Ua65polYTMwYTM7fWTVN49YPL+LkiRFiMcGG9VEWdxnUpl+aOyWEYN= nSGH/86RZ6exfQpFJURdfqFcdZtfwUUP0/VHOOQCGlh1KHZuJhAVK6CAGG7tNa+zIJj6oaMGt7m= fuTkfJZfxfn/rYN9yW3zZKIlF9y24IQAvvSLWjvuJ7Sn/7f+AcOYr7zRuT6i6h86x/RVi4n8l8/= j6o4OHfcTZDLY7/lKsr/159hbFiH8eYrkZlJKvf8CO/AobkkUaUCgkoF7+gxQKL3Lp0plYpCoKo= RNykhCJD19WBaSNOkmqEkX9FBORKNsemSy3juqd089+xzbNy4npOH9vHzh+9n/WVvJlVbN89JOw= gC3EqJ6fFB7GQDx/uG2HnPPSxe3ktH1+KXmaZqcvVzzz7L+vXr8X2f2277f3n/+9/PP37nO3zqU= 5/ie9/7HsuXLyeRSPDQQw+xfft2OtJp7r33Xq6//no8z+PRRx8lEongeR5Llixh9+7dNDY2EgQB= LS0tQFUkJRIJzpw5Q1dXF6dOnWLZsmUsXbr0Nek5tRBidoKlrSuI23GePflz9vc/TW/7apa3rcY= 2DGxDpz4Rww88Dg0eIBlJ4fgOxXKe0akh4tEUU/kJNE3n2JmDlCoFljSvwDZtmtKtZAtTjOfGmM= iN0lbXyZnMAIZukS/n8INqOXy2MEVHw2KS0RqmCpM0p9sZGO/j4ODzXNS1ibHpEeLRJIZu8fypp= 2ipbV/Qe1NA2Z3i6Pg/4/pFEnYrG9s+SdJqRCHnBNJcJGkmquSpACk1FqXXkK0c4sDIdyk6o9hG= inRk6YJeWwQBuelpggqgGYyP5RFC4fsBpaKD6yhM00AGHoEG+byL57kMj0wgpcJ1FGW/hKFJTK2= MQENJH9d1kEInCBQT41k8N8D3A7K5Itl8EQLFdE6h6ybujMGvFmicOT2O77lkqS6r+WWP7HQJrQ= C65kHgE3iSX0YlCSGIGEk8z8Lxqs/j+xr58ottRmaTt58/sIdEPEWlUuaJn/+MizdegTbjMr//4= F5W9q6ju3MZiUQNR47tZ+O6yxcU1XFdt9o1IgjQNI2pqSlGRkbo6OiYK3Iol8s899xzdHR0zJnK= znp6zb4PKeU8U0khBGNjY0SjUerq5i+7RjSd7c3d1XOD1Nha34GrAiypsSxRR6DA0jQaInHcwMe= QGqbUiOsmHbEaAqWwNI32WApnpsrMDQJ0KemMp9GEQJeS7c3dlH0PXVQ7Z2y3Y2hC0BGrYW1NE8= bMczbb8apwExJb02mJJOiMpWeivApdSK5tWYqnAiKawdVNS3ACH00IzF+DQIJX0eA2l81x/7/9m= IP7D7Buw3oamxrxvYCB/n7uveceRkdHCWYSK2dLfh3HwTRNDh06NPc8Qgh838e2bVzXpbGxkb6+= vrn7pZSUSiVWrFiB7/tz0apqldv5EUKwZk09q1bVz0VzfmGLs7aVxOOSd7+7EwEYpsbqNUlWrEx= gGBKlTP7w/9iMZekva01vmoJLLkmyeXMCXZe8eVsbUgoM46UnEyEgnTb4/f/YO2NAeaH3Uv2R0g= XO994v3Dto/hP/UhdmrznCsjDWX4S7bi3lv78drXcZkf/2BQof+2MKv/ef0DoXEWSzqHwB+w/+A= 5gmfn8/0f/x59jXvRV/bBz/4GG8nz6I0d5KMDJG/s//OwQK//EnMN7yZrRlS5GmiVjRSzAxgT8w= iNJ0hO+DbaLGx/F9n0CTGIu7kNGFV1Lous6aDZvoWbmKxx/6KbYdYcPmLZx6YT9P/Phelq/fQPO= iLqxIFE3Kqi9RPgdGnP7+Af7xG39NNj/NR97zSSLR6MsedGOxGHV1dXR3d9PZ2ckdd9yB53m+n9= YiAAAgAElEQVQopdi5cye6rpNMJqmpqSGRSNDU1ERbWxuRSGTObK5QKHD8+HE6Ozu599576enpY= deuXdTW1pLJZNi7dy+XX3454zPz8fDDD9PR0UF/fz89PT2vxce9MGYuahprWrh2/U383U/+kv/v= J1/j49d9lsaaHhpTSWqiEQLl0tGwmIgRZXT6DKlYLXE7gSKgJlZHrjTN2q5NVJwy6UQdumagSUl= L7SLikRRxO46Ugpp4HTWxOoLAp+yWMHSLslMkZieqy7QqwNTNOdFUG68jYkWxjAiWbrG++xKMBS= 61aUKjMb6epsRGBiYfYbp4irH80zRGt+JQFUP+TKTB9180lawusWsEgctIfi+FyghSShbXXkNtt= BexgIRxAEO3iMYluYKLUDrJVBzXqTA5mcO2TGpqEuSLBYSCRKwGP/Cq0QoBkZjO1OlxEnU1uCWX= RNLC9xxitsXEZIFEIo7UfNJmAoROoegQjZg4joMIXPKFCkiNdCpK1LZw3AqJVHSmAEUnEo3guR6= BopqfFyj8XGk2QfNVoVAUKi4VV8edOVRWl6rnz1ehkOP4iYMEKuDpZ5/glnf9Ry7d/BZAkJkco+= /UEVb1bsDzXDasvZSdP7uLlb3riUXjFxzD7t27aW5u5oEHHmDbtm288MIL+L7P3r176evr46qrr= uKFF15gdHSUyy67jJ/85Cfouk5PTw/PPPPM3EXWokWL2Lp1KydOnGDv3r0UCgWWLFlCb2/vS0SS= EILI2fukAH3GU8s+63ZNME+ECCGwNX3e/cbM/cY5xIomBDH9xYt+XTt7Xl/c3tJ0LG2+7IieozJ= wNqNPzoiwXycLEklCCFpbW7nmmmsoFApzt7llhzMDQ1UFKDU2bdw0L8JjGAZHjx6lUqlQKBTYtm= 3b3P1CCEzTpL+/nyAIsG2b3t7euYPwbDnx0aNHcRwHpRTXXnstSqm59gjnwzAWrjqFAMt6cXtdl= 7wY6RREIhf+kHT9xW0s6/zTKgTY9vm3MbQ4qxs+Tlfqxgu+9m866cjqlxdkmoZ17Xa0JYuRDfVE= Pv8pnH+6E1wPY9lSEv/7H3D/9ce4Tz2NXl+Hef01GOsvwnl8F9bvvAvj8kvAtpGNjVgf+B385/c= jVq3E2P4m1EQGmUwQ+cwnMK9+CzIRr06+JsEPUJNToBvguviex2zemAJUWxu8ApEkhKAmneY9v/= thvjYwyH1338HJvmO8Y8d70JTHoeee5vk9u0gkEiTTtaRq69GtGE/v+Tk/uusO8tMZbnrv77Fuw= 8XnvSqd9UpSSjE0NISUkmQyiWVZ3HTTTdx5550cOHAA0zTnLijOvlLWdZ1ly5bR3NxMQ0MDLS0t= nDx5kiuuuILJyUlqa2vZsWMHpVKJhoaGuYTsffv20dvbu+D5eLXMup+dnaWrSZ3FTcv44FV/wJ1= P/C8qrsN0sczixvTMwdhiVUfVibi7eemLZZbzmKmyEGflEFVrQ1FqDUII2us6ZwokXnoynn2UQJ= CO1764p8wrQ5xtU7SQyw+BpSdZ23wrrYlLyDmn5krzA+XjKx8vqP52A49ABQQqwFcKX1WjXAlrE= atbfpeU3UV9bA26tBe01IfSqQQKw/fw/QBNN3H8AF3XsKMGsWiEQqkIQlH2fEoVBxlUrQqQAa6v= 0AwNVwUYtoGimpQbCCj5CksJolLDc1wMQ0NT1ZS/qF3taGArnXzFxzAiBKKE6wmCQOD6iorrYRo= gNIFSGo6vkMJEyJdGrl8RCiQGrmfgzkSSNE0ihMnc/iAErS2LuPG695FO1XHR6i08vvsnXLp5G7= 7v89Qzj7Lv4F5OD51C13V836f/9AmOHj/AujVbLjiE7u5u7r77bjKZDA888AA1NTUYhkEymWTz5= s0cOXKEG264gccff5zDhw9z+eWXMzAwwJEjR+jt7SWbzdLe3s6+ffsYGRnhwQcf5H3vex8PP/ww= Q0NDdHR0/HJzFHJORCaTUVAVJdFo9GVbDFxoeevXxRuhb1PIGwff93n26af4n3/+3xg53Y9pR1m= z7mI2b72S9o6OqhFcdoqD+57niQcfZHhoEMuy2Pa2G/nQH/xn4udoITJLEATs2bOHT3/601QqFR= KJBB//+MeZnJzk61//Otdccw25XI58Ps/Y2BhKKb7yla9w++23s3v3bj73uc9x9dVXo2naPF+dc= 3nsnP19HxsbY8+ePVx88cU0Nr7yap5XNH+BR6FcwDYjGJoxb4xBEFCo5LCNCFLqMw2xf7u//7OC= TCmf4ewz2FoLRV9xulIkkxmn3kqRyU3R29ZNf3YYEY3QrAvSVgRNBiTsNqSoHrMXMhenR6b4r39= 9L31DZ1BBtcKOQAABwdkFBmLW10jMRJ2ryetC+dWkdiEAq5r/JwD8qsgLqheLQs50sWfWaPSsPE= EhCJBUy1x8quKSqpskgJTVHEIlq+XFgGHo/N6OK3j7tvWYr+ACeG6eleLg6T7+8zf/nLHpKQDqE= im+8sGPsWXpKjSpMTxymu/98G/53ff8IbXpBhynwt/+/VfYsPZSVq3YwN9956vcdN0H6OlewWxF= wHP7fs7uvQ/zHz7wxzMGlC9PqVTii1/8Ijt27OCf/umf2LFjB/v27aNYLLJu3TrGxsawLItnnnm= G1atXU6lUGB8fp6enh/r6enK5HC0tLTz99NM0NTVx6tQp2tra2LVrF0uWLGHLli2sXLnyFc9NyI= t4XrVA7ewClgWLpJCQkIXh+z4njh7hu9/+Ow49/zTFXA7P92Emny1QAUIpbMumvrmNa258J1ffc= COJZOqCUaTZpWdgzsPI9/25XmyzlViO46Dr+lzLkdko0tlJoq+EsyPArzezpoPneq1f5TheT5RS= VFyHUqVcLZXWdYruKSytjrJSTLgO+WyWlBljupinrbaWofwQwrKp1zVqrBo0qYhY9XhBGUNGkeL= CCwOu6zMxlafizl+eP1fs7cKc/Rmc79EXevaXv//FIJ0glYiQjNmv+rP3A58H9j3DD3c9jO8HvG= 3jFt560SbikWoBwkRmjJ0/u5Prr3nPXDL24FAf9/zr7Wy/6h0cPPwMV29755y7tlKKQjHP7T/4a= 25++4eor2s+7+srpchms0SjUfL5PLZtUygUyOfzBEFAY2MjExMTc0UV+Xx+7rx8dh6g53m4rott= 24yPj6PrOrFYbK76NOTVE4qkkJBfEVVbjByHD+zj548/yvHDh8hOTxGoAN0waWhqZv3FW9i45TJ= a2xfNVZFdiF82ovvbLi7eKPi+z5MvPMNdj+1kdecyahIpNi1fjW1a1VykmRyoWVNKzZjg0Pjt1E= VXo6iwKLUNQ4sQKJ/DE7fTlbqBhNWGocXDz/g8BEFAyXUIAkXENOdFI33fp+KUsSwbbSbvJggCC= oUcplWt4rOt+e0/lFKUykVMw1yw63bIby7nEkmvOHE7JCTkwlRzhVJsuuQyLtp4MflcjlKxSBAE= GIZBIpnCjkTmrhBfiWNvyG8/QghMw2Q4M8aKRUtoqa3nb+65nfU9qxieHCNbzGObFlHTpuRUuP7= STRQqwzTGLiLvTHIscxcxowkpDAqVMwzn9jBVPkZn+mp08Ro03n2DIqUkZp072qJpGtFI7CXbJx= Ivb2MhhHjJY0LeWIQiKSTkdUQIiWla1NZZsHBT5JA3OArmrlbT8SSZ7DRDmVE6sq2MTk2glGJL7= zqePrKf6WKO8WwGqUtqo8tpS13G0cydFL1RdBFFCImt11J0h+YMZkMxHRLy2hCKpJCQkJDXmdlS= /tm8sSAIMHWd7esvxw8CIpbFWzdcQcyKUBNLokvJsvYubNMiW8zR2dxIwd+OIZNYWh1N0c2UvAk= 0YZMwloD0aU++BYkxrwJSvgGS20NCfp2EOUkhISEhrzO+71MuVwiCqlCaEzGadlb1WIDnVT2RCN= Sce7JpmXieRxB4My1PBH5QbTsTzOSo2ZZVbUHhenM2BL4fEItFX+LCHBIScm7CnKSQkJCQXwOap= hF9Bb5bAEGgcJwAKQQR28Tzqo1uDUO+rAmtFaYjhYS8poQiKSQk5GXxg2prCV3X5tr7hLw6Xsmy= l+cpTp8uMThYxvFcVixPMjRUoVzxWbY0Rm2t/bIdAEJCQl47QpEUEvIqmPUiklK+ZkvUQaAouz6= +X+1Cny95jE6Xaa+Pko4vzCLgl8VT1Z5anuuRL1YAxSNPH2Pbxcs4NjDG8s4mEr+EV82vlCBAlb= OoUhZ1VhPTcyGsGCJay8uGaF4NM66Mr2SuymWfTMah4vic6ity0UU1jIwUOXo0z/r1aQZPlznVn= 0cpgWlKYjF9ntt/SEjIa0sokkJCXgWO4/Cd73yHpqYmbrzxxl+66avvBxw/k+fQYBbXUwxPFhme= LGPqGjsuX0QqaqBpr68wKfsBO0dyHMtXuKk2QnZimoamNHUdzRS9gN37T1GXinNyaILFrXVzYkk= pRbnikS9VAIhHLXRNznjQzI+geH5AoeTgBwFCCBIRE10/d87ML1ulFRQnqTz4N7j9z0PgozQTEU= miilMIAtAshJQo30EkmzDe+ilkvOGCTQ1fifGiEBLdMBAL2D+UUhw7lsfzFMVyhbo6C8uSFAoBa= 9bUzHXU0TWDqSmXzKTD8mVxUqlfjYAOCfn3SCiSQv5dcS7H5pdzcT7ftpVKhR/96Ed0dXVxww03= zDN5XOgJq9pqoyoEvEBxfChLb3uCvcemcFy4cUsb1STdl0ZBgkARKDV3whaAlK8sajFvLEDO8/n= GiXGezeRZv2UxT6MzNpjlRL7CJ6IWN2/fACi+8Nf/wic+sJ0NKxYBivGpPD958jBd7fW4jkep4q= FJxUXL2nHcgKa6OIZebYVSdlzuffQAsahN1DJYt6yFxvRLDRDLjsvwWJaOlvSrFqCqlMXtexo/N= 4aoWwyJJoxNO3B+9leIaBL9ohsRhoV76CG8ww8hJs+AmZzr1D4r0maTOGfHMdtXcu51fkHMzXZt= F0JiGDqari+ombRSilLJZ9myOL5vk8m4ZLMuiYSO6yqOHMmzaFGE1tYImi44faZIseSSSp2/j2V= ISMirJxRJIW8ofN/n4MGDTE9Pz90mpaSlpQXDMDh8+DDxeJzly5eTSCSoVCocP36cM2fO0N3dTW= dnJ1JKMpkMR44cAWDlypWkUilc16W/v5/+/v65x/q+T6FQ4PDhw5RKJZYtWzbXGPZ8KAVDE0W+/= 3A/V6xp4KLFaepTFj95ZoRUzMT1PCayFa5a24ShS+RZXbVLjsej+8d46kgGf6bflWVINvSkuaS3= npj9yluP5DyfnSN51tREWFcT5TuDWdYmDDqjBh0xG8M0EBKGx7J86aM3UCi7HO0fo6MlzU92H2Z= Rc5oNy9oAmJguMDKRY2Qix31PHOLmt6yl4nhMF8q01icpVxza6hN0tNRiaJI9B/qRElZ2tzA4Ms= XwRJZU3OafH9zHH+y4nJHJHKWyS0dzmslciXLFJZ2I0N1ef4F3FVSX2RLNmFfeinPsSfA90E30i= 38HihmcvXehsmdAKUZHRti95xhXvelKnnhiF6VSiWQyybPPPY9hGKxbdxH9/f1s3Xo5P/7xToJA= 0dBQz4EDL9A505cvk8lwzTVX88Mf3k00Fuf9738PHZ1dF5z/IFCcOFkkXyiRyZik0waFgk+xGOC= 6PsePO7S1GQwPlzh9uoTnKQxdMj0VkK7xsW0tjCaFhLwOhCIp5A3F5OQkt9xyC4ODgwAzZdEura= 2teJ7H1NQUmqaxfft2/st/+S/84Ac/4Bvf+AaVSgXbtvnc5z7Hli1b+MxnPsNzzz2H7/usWrWKb= 33rW+zatYsvfelLZLNZpJR4nkdHRwcf/OAHefDBBxFC0N3dzV/+5V+ydevWCwglxchkhYf2jRCx= NHoXJTk1VqLieGy7rJ0fPDqIF4AUAk1We7srVX0/+aLHvbsG2Nc3xdK2FKYu6RvJ8W97BvnoDct= 4x2WLMDTJ2R1MfnHZ6xcZKDh8+YUzNEcMPrO8iSlfkZRQQaIQ/HC8SJetc0NtAuUFfP5//gv1qS= h/+pHrOHpqmI29i7DMqjizLYNHnj7Kht4OlAoYnchy/5OH2L6ll3sefI4AeOqFPo4NjPG2rSvRd= Z3v3b+Xay8pk82XWN3TRr5YRqmAvqEJdu07ydVbernzp8/g+Yq2pjSXrFpYx3NhJdC7L6HyyN+h= d6xDS9Sita1Gq+3A6duLyo+jchMoqVGulBkdHcVxXEZHx8jn8ziuy+joKJdddhl9J/s4dOgw0Ui= U+rp6mpqaWLSonb6+U3Qt7mLv3qdJp9McPXqMicwkjusxmZlckEjq6yuQmajQ25vi5IkStq0xMF= Amk3HQNEFHR4TxcZemJoPOzii2XRXNmYzLY49N8KY31WMY2muaUhUSEhKKpJA3GHV1dezcuZNsN= ovneTz11FN8/vOfZ2BggFtuuYU//dM/ZWBggC9+8Yt8+MMfZnp6mi9/+cts27aNO+64g69+9auk= 02mampq47777kFLyyU9+kltuuQXHcbj11lu5+eabeeihh/jSl77Erl27APj+979PY2Mjt912G7f= ddhurV6+mru7lLbbV7L8zDdKzRY9CJeDaTS38/PAYcUtSqXjc/cQAhi657uJWHNfnfz3Qx6rOFH= 4Q0FYf4QvvXUVzbYTDg9P8n3+7l76RIsWyz9BEjgefG2E8W2Zpa5Jt65tpTJ27IkoBjbbBHy5ro= tXWeXSyzNsbY9SbGh1RE10Krqy1OTZVIlsoMTQyxf/zhzcxMV0gFrFY3tXC3oODtDSkMHUNz/Mx= dA3D0EjEIggpyJdcbMvgnW9Zz/27DtK7uJN1y9vZve8kp0ez2IbBZK6MUoqm2jgRSycVj+L5AY3= pBImohe/72JZJb2cji5rTC9ofVOARDB+B7Ch6z+UgNIzVb0VYMWRjD15mEDcziusJfF9RqVR49t= lnKRQKZ4lKgVI+g6dP4/kewyPDNDc34/keyVSSSCRCMpGYazisFJSKRSIRm/qGhgWNU0pBU5NNb= dpmKh2wa9cUx4/lWdxS5pINNpYo4AuNwXGDQU0Qi+mk0waWrVEuu/MEcUhIyGtHWBYR8oZCCEF7= ezsrVqwgEolw9913E4vFaG1t5aMf/Sitra2sXbuWa665hv3797N8+XLe8Y530N3dzYc+9CEaGxs= 5c+YMH/vYx9iyZQtbtmzhE5/4BEePHiWdTvPe976XFStW8O53v5uVK1dy8OBB3vWud7F9+3bWr1= /PrbfeyunTp8lkMgsZ7dxfqajBm9c0YOoa7fUxdu4d4uRInv7RAnc/3s/YdJmnjmS498lBTk8UQ= UGu6LL70DgPPTvCv+05g21orFiUZGiiyJf/aT8nh/N0NSe458kB/sddB5kqOOccha8Uj4zl+H7/= BEGgWJmM0GBptEQMDK3q2Fxv6ayI6cQsg1NnJnjuyCCf+9pdHDk1ytsuX0kiZnHPQ8/z4FPHGBy= dprEuRSxqk45bxGyTS9Z00Xdmkul8iUQsihcIDE2SjEeQUrB8cRPd7fU4rs/DTx+f6Yll0lyfJB= mLcHRggm2be2ltTFN0/HO+j3MS+FDOIeJ1yLpFVPbehT96nMqJp8je9zUKBx7HcbyZajGT2nQtA= 4On0Q2Tjs4OGhsbWb58KZs3b6Zj0SIuu/RSmpqaOH16iEOHDiOFoKmxgcbGRhrq65mammJx92I2= bFjPyhW9ZCYyVXPIC9DWFmF8vMKTT07iOIqaGo1kLMA8+jCn7rmL49/8Jof//ttM734Qz/FIpQz= yeZ/BgRLti0xM8+W9k0JCQl49YSQp5A3J1NQU3/72t5mYmOCzn/0sX/3qV/mbv/kbampq5vKWhB= DEYrG5En7TNOf+H4vF5pbLampq0DQN27ax7WpzTMuyiESq5oCpVApNq+aERKNRgHmJvQtB1wSLG= qqPHZ8uE7F0TENj/ZI0Txwc49BAlideGCcVNVjdmWLXC2NM5R3uenwAXROcyZRoqLHpaIzy5KFx= JrJlNi+rwzYkS1qSnBzOkck51CZe6jYoESxN2Gypi9MVMxFSktQ1CoUyRtRG1yVBoMgWylQqLot= b6xDAhpVdNKTjJKI21162gqmyi6UJDE1jaXczCkH3onqkFHR1NKL8ACUl7a11aFKgpGRVTys9Xc= 0EQiCFYFlXI06giOgaH7hhM1IKmhtrCAKFkpKlXU3oQizcI8h3CUaPom/YgQoU5dEB4muuw3nuf= vxKmWqJfjWa1tTUxM1rtqLcEkJq4LsITWPrJZvQ3CLvefc7wS2hqCbaC9/BTkS56bqr0Q2Tm69/= C0pIzEicJQ0xtFgaPRrnguVyVH2RAJqbTcbHHcplj0LRh1gNRMBKp6G2Dl/GsSMa+bxHXZ2JbUv= GxgRBoF736seQkH+PhCIp5A2H53nce++93H///XzqU5+ipaVlXisIIQRLly6ls7OTiy++eE4k/e= oTX6vjcf2AUsXHD6BaQFUdhxTQ2RijOR3hZ88Oc2QwxyUr6mlIVYVaU02ET+5YQV3S4sdPDfHDx= /o5NJClVPGo2gIJlILulgTL2pPUJs5dBSUFdEVNWmyDo/kKjVGLBgn/eNcuLlvTSVdrLRXHY3gi= R7ZQ4vToFLueO05jbYJ41EIIgYvgQCWgRpdIPIqBoqIgqkn8mbWgekPiuQGTro8uJVL4BAocBJ7= vYaBosQ0yFQ+pBXhKEQQ+QmpoCEoqoMmUdEcW5kulFLiewnMVRtNyvMkzKM1CWFHcocMI5c/5Ig= kBhmmiWxrlo0+iNS+jsu9+tNo29KYeykceJ9L7JiqHH4X6bqymbpw9dyC2/h5yaD9aYw/s+T5aQ= ze0rSJ44SHMpZdipTcsaL8aHa3Q1hahocHC93OAIJ6MMMFGOtfHaajTKTuKiUxAJKJjmpJyuZqw= nct5eJ5CyrCxbUjIa00okkLeUCileP7557ntttu4/vrrufbaazl27BjRaJSPfOQjrF+/nkqlwn3= 33cftt9/O2NjYvD49syaR2Wx2riHpxMQEvu9TKpUolUoAlEolcrkcAOPj43Pb5nI5lFIL65clqr= 5BD+8f5dR4CU0ILFPjlq3tc5vUxAw2Lk3zvQf7UAqu3diCOeMrZJkarXVRWmojXLysljse6WO64= LChp46fPjPMUKZIc63NwYEpamImxnlMByUCTVR/1iZMHh/Lcd3WlRzrH6XvzCSpuEXF8fjx4/v5= 4A1buO+x/aTikepJWYAmYHnMxJ+xJUipqvhCvJh0bkkwBCQ0QTBzuxAChUIpDUGAJQUCDUNKPAV= SVJ2+/ZkVq6gUC15WUgpcF1SkDq1uEZXjezGalxKUcviZwV/YeDa5XSeI1aNZMVTTcgIzirAS+J= E0KpIiSLaAbqM8n6BlTXXfidahzAhB43JEvBYZq8M342DFEVIuqPy/rs5gcLBMsRgwPe3R3h5hc= tLF8ywOnYThSYnvV32X8keLxOM6haJHNCqxohUUcc6VPaGUwvcDfN/DNM1qNWapTDRio2sapXIZ= TdMwDeOcAsvzfXKFAqZhELV/S0xEQ0JeQ0KRFPKGYmpqij/6oz8C4NJLL+Xw4cOMjIwgpeS2227= jC1/4AqdPn+ZrX/safX19NDU1zVsak1LiOA5/8Rd/QSwWQ0rJV77yFdasWUM2m+Wb3/wmO3bs4I= EHHqCvr4/rr7+eO++8k7Vr19LU1MRf/dVf0dXVdd6kbag2NG2qiXDFmmaGJ0t4XoAL6JrENjVWd= KRoq4timxqXr2xk96Fx6lM2Pa0J/AB6F9WQLTjErGpFU1dznPU99aQTFqs6U3z8puX8y65BfrR7= kLa6GNdd3ErUfHnhFtMFH+5K8+h4kW/1TfIHnTVMOxFKp8f57r8+STIeYVV3MxtWdPKhL3ybN29= ewec/fC01iQgCMDVJ05yf0S/m4Mw/saZeEgia3b46vlrjF42v59s3Lrw9igAh0eraEZEkbt+z2G= u3454+jHJKII2ztqyuuUnTIrb8UgDMdGv1OaQgXb8IoRmY6ZaZBwjs1p5q6K+uan2Q2nxT9ZmEx= Ljy/QhNRwi5IBfvWMygu1ty8mSRzs4ohiHp6LAxTUk261GpVF3Ye3vjlMs+8bjO1LTLQ8cOsHPv= AT4f3UZ7fS2BUqTjcQDGJ6fIZLMcHhklWy5zw8b1FCsOX3vkCT52+WZaa2v5we69dLc0c1nPYpR= SnJnI0FiTwjQMiuUyx0bH+cvHnuTGnsXcsHEdhlb1u5ouFAComXmt6pS8ep+ukJDfVEQmk1FQPT= lEo9HXrMVCSMivg1OnTrFx40Zyudy8A3ZDQwPRaJT+/n5s2+baa6/FNE0Mw+C2224jmUwyPT3N7= //+79Pe3s6JEyd45JFHUEqxdetWvv71r/PUU0/xxS9+kYGBAerq6viTP/kT3ve+9/HpT3+au+++= G9d12bhxI1/96lfZtGnTeaNJSsF4tszxoSwNKRtDl9iGpFDxCAIolj0SUQOBIJ0wOZMpUXF9ahI= mEUNjuuCQiBqUHR+FoKnGZnS6jBQCKcD1AoJAIaXA0CV+oGhKR7CM84wJ2DVRYN90iXe31TDl+j= Cd57FnjnH5uiXEE1F+/txxPv5n32XH1Zv4s4/fhG395h4v3JETTHz3s5i9VxDZeAOFJ+5A2HGUE= CjPQeXGkfFaZKKB8lP3UPPOz2J2rH1NT/QK5vLVLritUuzfn6W7O4bnKU6eLMyIJJeVK5OcOFHE= cQLSaZ3OzgiZjMsLp/v47y/sp115DA8PEzUNNN3AtC0KxRJnRkfJOS7CjrCqrYWVjQ0cmsgglKI= 9anNgMocmBTHTwBSCgydPsri1lUXpGo7li1y3bAlPjU+SzWYRlTJ2xKbsuIyPjVKTSBKLRCj5AZ= qhc+slm7h0RW8olEJ+a/E8j0KhMG91IRRJIW8ofN/nxIkTFIvFebfX1tYSj8fp6+sjEonQ2dlJo= VDA933q6+vnXJZHRkaIRCKYpklfXx8APT09mKZJEASMjY0xPDxMfX39XK6T64x7cvkAAAQeSURB= VLqcOnWKcrlMR0cHyWQSOH+Ok1KQyZU5NVrAcX1AoGtVT6Sy46NrgrLrY2iSltook7kKmbxDKmb= QUhthbKpCoeJiGRoVN2DFoiQHTk2haZJkxGAq7yBl9Tm9QFETM2hviJO4QD6PUtVarEfGC+wcK/= CxxbXsniyyrT7G83mXtTGdUrZIXSqGafxmGxj6xWkKj34XZ+wUaDp+YarquhB4CKlD4IGQICV6T= TOJqz+KFqt5Tfu3CaguuS1QJI2MlJme9gDB0FCZTZtSjI9XGBtzWLUqgecpDh3KYxgC25bsOv0c= e04PMgJEMuOcLJapZLOYsThN8Si6UpQVBLqBFrHZmk5yvFjmeGaKYi5La2Mjg9NZ/MkMqeZmorZ= NoVgm57kkE0muaKpjvFzmeLbI+MkTLO7uYmVzE0OTUwzliyQJOD6eQWkaX3z727hu3WsrMkNCfp= WEIikk5DcI3w/wA4UfVJvKyhnTSMfzZ3qiVU+ypiFxvAApq33SLEPi+7PNSMD1fWxTo1ypJiJLA= YEClEKcVQVmmzraAqvCvEDhqoBACaZcn3pTw5gZH/w6ktxfOUoBvovyHc5vJCRA0xH669Pe45XM= VRAoPC/A9xVHj+ZpbbUpFHzGxhza222UAl0XpNMmQkDZcZjK5zENg4pbbbisggCBqAp/pQiCYKb= vm0RKjSAI8IMAKcDxfTQpZ3aYmbEKwdDkJI8dO8nWZT201aSQUuB7PlIKEpEoZdfB8wMCFaAChZ= SSmkSciPXS6smQkN8WQpEUEhIS8luAUopi0aevr0hTk0UioTM8XMH3oa3NmvFFev2E6qyQ0maiY= L8Nojgk5JclFEkhISEhISEhIefgXCIpdNwOCQkJCQkJCTkHoUgKCQkJCQkJCTkHoUgKCQkJCQkJ= CTkHoUgKCQkJCQkJCTkHoUgKCQkJCQkJCTkHoUgKCQkJCQkJCTkHoUgKCQkJCQkJCTkHoUgKCQk= JCQkJCTkH+kI28oOAM2N5JqZLr/d4QkJCQkJCQkJec6SA9qYkNYnIgls0LkgkSSGoTUWIRcO+PC= EhISEhISG/fQggauuvqIf1gkSSEIKobRC1X+XIQkJCQkJCQkJ+ywhzkkJCQkJCQkJCzkEokkJCQ= kJCQkJCzkEokkJCQkJCQkJCzsGcSFJKoZT6dY4lJCQkJCQkJOTXwrk00LxIku/7oVAKCQkJCQkJ= +XeH53kEQTDvtnmRJNd1X7JBSEhISEhISMgbGd/38TzvJbe/JJJUKpXwff9XNrCQkJCQkJCQkF8= Xs9rnXCLpJT5JruuilMI0TTRNA6o+SSEhISEhISEhbxSUUvi+T6VSedng0DnNJD3Pw/M8hBChQA= oJCQkJCQl5Q3KhFKPzOm6HFW8hISEhISEhISEhISEhISEhIXP8/wWorT9uy+wdAAAAAElFTkSuQ= mCC" width=3D"585" height=3D"136" alt=3D"" style=3D"margin-top:49.4pt; marg= in-left:30.45pt; position:absolute" /> <div style=3D"clear:both"> &= #xa0; Renovaci=C3=B3n Cient=C3=ADfica </sp= an>&= #xa0; = P=C3=A1gina= 1 | 17&= #xa0;</div></div></body></html>

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:612pt 792pt; margin:72pt }= @page Section_2 { size:792pt 612pt; margin:72pt }@page Section_3 { size:595= .3pt 841.9pt; margin:127.6pt 85.05pt 70.9pt }div.Section_1 { page:Section_1= }div.Section_2 { page:Section_2 }div.Section_3 { page:Section_3 }body { li= ne-height:108%; font-family:Calibri; font-size:11pt }p { margin:0pt 0pt 8pt= }li, table { margin-top:0pt; margin-bottom:8pt }.BalloonText { margin-bott= om:0pt; line-height:normal; font-family:'Segoe UI'; font-size:9pt }.Bibliog= raphy { margin-left:36pt; margin-bottom:0pt; text-indent:-36pt; line-height= :200%; font-size:11pt }.CommentSubject { margin-bottom:8pt; line-height:nor= mal; font-size:10pt; font-weight:bold }.CommentText { margin-bottom:8pt; li= ne-height:normal; font-size:10pt }.Default { margin-bottom:0pt; line-height= :normal; font-family:'Times New Roman'; font-size:12pt; color:#000000 }.End= noteText { margin-bottom:0pt; line-height:normal; font-size:10pt }.Footer {= margin-bottom:0pt; line-height:normal; font-size:11pt }.FootnoteText { mar= gin-bottom:0pt; text-align:justify; line-height:normal; font-family:Arial; = font-size:10pt }.Header { margin-bottom:0pt; line-height:normal; font-size:= 11pt }.ListParagraph { margin-left:36pt; margin-bottom:8pt; line-height:108= %; font-size:11pt }.NoSpacing { margin-bottom:0pt; line-height:normal; font= -size:11pt }.NormalWeb { margin-top:5pt; margin-bottom:5pt; line-height:nor= mal; font-family:'Times New Roman'; font-size:12pt }.Revision { margin-bott= om:0pt; line-height:normal; font-size:11pt }.Title { margin-bottom:0pt; tex= t-align:center; line-height:normal; font-family:Verdana; font-size:14pt }.p= aragraph { margin-top:5pt; margin-bottom:5pt; line-height:normal; font-fami= ly:'Times New Roman'; font-size:12pt }span.AsuntodelcomentarioCar { font-si= ze:10pt; font-weight:bold }span.CommentReference { font-size:8pt }span.Emph= asis { font-style:italic }span.EndnoteReference { vertical-align:super }spa= n.FollowedHyperlink { text-decoration:underline; color:#954f72 }span.Footno= teReference { vertical-align:super }span.Hyperlink { text-decoration:underl= ine; color:#0563c1 }span.Mencinsinresolver1 { color:#605e5c; background-col= or:#e1dfdd }span.Mencinsinresolver2 { color:#605e5c; background-color:#e1df= dd }span.Strong { font-weight:bold }span.TextocomentarioCar { font-size:10p= t }span.TextodegloboCar { font-family:'Segoe UI'; font-size:9pt }span.Texto= notaalfinalCar { font-size:10pt }span.TextonotapieCar { font-family:Arial; = font-size:10pt }span.TtuloCar0 { font-family:Verdana; font-size:14pt }span.= UnresolvedMention { color:#605e5c; background-color:#e1dfdd }</style></head= ><body><div class=3D"Section_1"><a id=3D"_Hlk150165641"></a> El =E2=80=9Caula invertida=E2=80=9D como m=C3=A9todo de apr= endizaje en la asignatura de historia en primero de bachillerato de la Unid= ad Educativa =E2=80=9CCombatientes de Tapi=E2=80=9D a=C3=B1o lectivo 2023-2= 024 The =E2= =80=9Cinverted classroom=E2=80=9D as a learning method in the subject of hi= story in the first year of high school of the Educational Unit =E2=80=9CCom= batientes de Tapi=E2=80=9D school year 2023-2024 <table style=3D"w= idth:396.3pt; margin-bottom:0pt; padding:0pt; border-collapse:collapse"><tr= ><td style=3D"width:3.25pt; border:0.75pt solid #000000; padding:0pt 5.03pt= ; vertical-align:top">1</td><td style=3D"width:171.95pt; border:0.75pt solid #00000= 0; padding:0pt 5.03pt; vertical-align:top">Alexandra Sofia Rodr=C3=ADguez Oviedo </td><td style=3D"widt= h:10.5pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:t= op"><img src=3D"data:image/png;base64,iVBORw0KGgoAAA= ANSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBl= SsOGwAAA2lJREFUOI21lEtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQi= UhUnFqo4cGIRQUGd+KDY+Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe//= /Wv/aiy1cBV/83NNOPr/VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNN= Z+57RTjDTvqFM1IvNiGXWJvD/9x8yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XLleTd648= Z/863v3nkjWCL59dp/fWSsfzOXNkShKacvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082AAzADZXy= Pj+wL8ehQ1NH700v0N35OAroutW0rxDF6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQt= Z0VEU1QTPtmAkDygiEBTsTxq6hx65fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqF= JrzDF5+Sv+Wvg+y+IEVXaGibsbOO5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52= oNtTMwcBbE0YteeC7we4LinSI9Z03dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg1= 7AAwqpRW9fqayNkiM0tjqDrag67mDCi0ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKrR2zreID= URZTrZ7NTBYdeBPAU+cY59zxCkFlXjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYjFGqkldT= 0J4EkY/ZovBb+klbQ/G1zDYvQntXgWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGA= EQV+Wy87xm/xbwZ1lwewGmCIIhYnCZXjKvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2CV8GrRk= NldbNmKbYU2enC0uV6bkfUNUd8P1ury3ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbrXMoncTV= 99smBH5ZW327igzP3trY2ONCyyQ6FtbRLUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fXp1+BVxd= x2um+HGnuX9egX4dY01U0iVK2R80nMaELy42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJgg= g=3D=3D" width=3D"20" height=3D"20" alt=3D"" style=3D"margin-top:0.45pt; ma= rgin-left:-0.3pt; position:absolute" /> </td><td style=3D"width:166.35pt; border:= 0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><a href=3D"https://orcid.org/0009-0001-= 1552-7660" style=3D"text-decoration:none">https:= //orcid.org/0009-0001-1552-7660</a> </td><td style=3D"border-bottom:0.75pt solid #00000= 0; padding:0pt; vertical-align:top"></td></tr><tr><td style=3D"width:3.25pt= ; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"> </td><t= d colspan=3D"4" style=3D"width:370.7pt; border:0.75pt solid #000000; paddin= g:0pt 5.03pt; vertical-align:top">Unive= rsidad Nacional de Chimborazo (UNACH), Riobamba =E2=80=93 Ecuador</p= ><a href=3D"mailto:sofysro= driguez30@gmail.com" style=3D"text-decoration:none">sofysrodriguez30@gmail.com</a></td></tr><tr><td style=3D"width= :3.25pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:to= p">2</td= ><td style=3D"width:171.95pt; border:0.75pt solid #000000; padding:0pt 5.03= pt; vertical-align:top">Freddy Auqui Ca= lle </td><td style=3D"width= :10.5pt; border:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:to= p"><img src=3D"data:image/png;base64,iVBORw0KGgoAAAA= NSUhEUgAAABQAAAAUCAYAAACNiR0NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlS= sOGwAAA2lJREFUOI21lEtoXVUUhr+197n3nNzbJN6omdTWRmwbikVq4iMxk0ZU2oGgA1FnQcQiU= hUnFqo4cGIRQUGd+KDY+Jp25ouiGCOxElqjhba0URPzsPQmuY9zzj1nLwcnuU1iQ0f+mzXZe///= Wv/aiy1cBV/83NNOPr/VWHunqO5OVNuNlQVjmZCGjCVhcPHR3q8XrsaVNUITu/KSlu7LFeSpNNZ= +57RTjDTvqFM1IvNiGXWJvD/9x8yXB/efizYU/Hy8/0W/aA/Xq43r1P3nOCNIFsW2XLleTd648Z= /863v3nkjWCL59dp/fWSsfzOXNkShKacvfgnMRlXjqqqIrwr5vkihyhxbT+K2ne082AAzADZXyP= j+wL8ehQ1NH700v0N35OAroutW0rxDF6rUUvddaJfdwM9HwqYFSa0GO1SrpfucUVUXEZCQcqQtZ= 0VEU1QTPtmAkDygiEBTsTxq6hx65fWTOy7l0exjKgGrGcjTo2/oKS9EUZ2aPcf/Oo1iTI9UGqFJ= rzDF5+Sv+Wvg+y+IEVXaGibsbOO5hGBSkbUUQdRT9zaQuBhE6Ct2MT7/D9OIIVnw6Ct3csfk52o= NtTMwcBbE0YteeC7we4LinSI9Z03dBNUVxTdu1eI7FcBIjHvPVU1Tjv7nn5sNMXv6WSjyFiIg17= AAwqpRW9fqayNkiM0tjqDrag67mDCi0ARiB6gaTsSEEg4htusj2qGeCIr9dW0JR3PKrR2zreIDU= RZTrZ7NTBYdeBPAU+cY59zxCkFlXjHiI2GY1pZbtRMkC1gZcX9hFV+lBTs98SDWexYjFGqkldT0= J4EkY/ZovBb+klbQ/G1zDYvQntXgWFC5VJ9hSGmRLaRCnCZeqE3x34SXK9XMY8bK+BvZ8JUzGAE= QV+Wy87xm/xbwZ1lwewGmCIIhYnCZXjKvDaQNrfIzkAKXYZl11wR16omfkyHIP0RB/2CV8GrRkN= ldbNmKbYU2enC0uV6bkfUNUd8P1ury3ktQADO05UV6azx1IE/dRULDomjGSVXEFhVbrXMoncTV9= 9smBH5ZW327igzP3trY2ONCyyQ6FtbRLUw2yZ8p+FwARifyCvRDV048rcfXdoT3j5fXp1+BVxdx= 2um+HGnuX9egX4dY01U0iVK2R80nMaELy42O7R39fz/1f8C/hZ5YvjpSKGwAAAABJRU5ErkJggg= =3D=3D" width=3D"20" height=3D"20" alt=3D"" style=3D"margin-top:0.45pt; mar= gin-left:-0.3pt; position:absolute" /> </td><td style=3D"width:166.35pt; border:0= .75pt solid #000000; padding:0pt 5.03pt; vertical-align:top"><a href=3D"https://orcid.org/0000-0001-7= 482-6516" style=3D"text-decoration:none">https://o= rcid.org/0000-0001-7482-6516</a> </td><td style=3D"border-top:0.75pt solid #000000; bor= der-bottom:0.75pt solid #000000; padding:0pt; vertical-align:top"></td></tr= ><tr><td style=3D"width:3.25pt; border:0.75pt solid #000000; padding:0pt 5.= 03pt; vertical-align:top"> </td><td colspan=3D"4" style=3D"width:370.7pt; borde= r:0.75pt solid #000000; padding:0pt 5.03pt; vertical-align:top">Universidad Nacional de Chimborazo (UNACH), Riobam= ba =E2=80=93 Ecuador<a href=3D"mailto:freddy.auqui@unach.edu.ec" style=3D"text-decoration:= none">freddy.auqui@unach.edu.ec</a></td= ></tr><tr style=3D"height:0pt"><td style=3D"width:14.05pt"></td><td style= =3D"width:182.75pt"></td><td style=3D"width:21.3pt"></td><td style=3D"width= :177.15pt"></td><td style=3D"width:0.3pt"></td></tr></table> <table style= =3D"width:436.35pt; margin-left:0.25pt; margin-bottom:0pt; padding:0pt; bor= der-collapse:collapse"><tr><td colspan=3D"3" style=3D"width:156.4pt; paddin= g:0pt 5.4pt; vertical-align:top"><a id=3D"_Hlk92186133"> </a> </td><td colspan=3D"2" style=3D"width:258= .35pt; padding:0pt 5.4pt; vertical-align:top"> <= p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-size= :10pt">Art= =C3=ADculo de Investigaci=C3=B3n Cient=C3=ADfica y Tecnol=C3=B3gica<= /p>Enviado: </= p>Revisado: </= p>Aceptado: </= p>Publicado:</= p>DOI: </td></tr><= tr style=3D"height:6.55pt"><td colspan=3D"3" style=3D"width:156.4pt; paddin= g:0pt 5.4pt; vertical-align:top"> <= /span> </td><td cols= pan=3D"2" style=3D"width:258.35pt; padding:0pt 5.4pt; vertical-align:top"><= p style=3D"margin-bottom:0pt; text-align:right; line-height:115%; font-size= :6pt"> = ;</td></tr><tr><td style=3D"width:37.8pt; padding:0pt 5.4pt; ver= tical-align:top"> C=C3=ADtese: </td><td style=3D"width:1.55pt; padding:0= pt 5.4pt; vertical-align:top"> </td><td colspan=3D"2" style= =3D"width:358.55pt; padding:0pt 5.4pt; vertical-align:top"> DATOS REVISTA<sp= an style=3D"font-family:'Times New Roman'">DATOS REVISTADATOS REVISTA</t= d><td style=3D"padding:0pt; vertical-align:top"></td></tr><tr><td style=3D"= width:37.8pt; padding:0pt 5.4pt; vertical-align:top"><img src=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE= BAQEBAQEBAQEBAQEBAQEBAQH/wAARCAAiAEEDASIAAhEBAxEB/8QAHAAAAgMBAQEBAAAAAAAAAA= AAAAcGCAkFBAEC/8QAPxAAAAcAAQMBAwcFEQAAAAAAAQIDBAUGBwgACRETEhQhChUWMVFhcRoiQ= YGxKUJSU1dYZpGTlZeh0tPW4fD/xAAbAQABBQEBAAAAAAAAAAAAAAAIAAIDBAYFAf/EADoRAAIB= AgMDBQwLAAAAAAAAAAECAwQRAAUhBhIxBxNBUbIiIzIzYXF0gZGz0fA0NVJyc4ShscHD8f/aAAw= DAQACEQMRAD8A2krncP0rmf28ebsxaq1F0K4ZPR4YjSfo8nKsiP1ppc7hN+0SXVM+hXbFaLE6Sj= eSXMIrlEp0xQEyrc7D+67DsWb7LF6podn0BtRLFVWVVXtcgpNScWzlo6WcPmozb31ph+gdVsgZM= ki+dg1IX02wIpGMQcnuCHx7dnc7H9H0Ko/+YTfjrQz5Or4Gjckx/pZRfH64ec/b0Sm2mzuSZNs3= yn0uXZfTwRZVtdkkFAd0ySUkU1LA0qRSuWkQSFpN4BtQ7LbdsoGjY3Ps2zfabk8rMwrp55a/Z/M= 2qgW3UnMc9SIzKi2WQoAhBYE3QP4dyZ3zVqFm5k90DM+F1p1C+0HCq3hkhq09B0OdXr761zguHp= CCdUpV2bxwgsSI92VkGT4scwazAs0kV3h1w6+mYvnPbrv3B6g57c92mK5p3J+VlrA5mdfetEgMy= rdbQXa2VhHQqDa31grVqCpa7Ii3QK5M6WB0ArmAliO4Bw5zLTNXy7kahyta8N9ypjJ3Wa5pLqwV= yJRsUGmR4ovEAzsc9X0nbpmnMvkVjNXayTiLlHLCVYu2yqAoQGj8J3+zGxC4XvntG8pU+Pe3yGo= KWJrH0+VaOIp7AwkY4orp9WLO8ZRCIDHOJAXzj3hbxIGKLUE0yiccSykRm9lAAKgaEgBb36b301= t0dNsEvhaZl3jrxsczYZWm57gcbQY9jp0rCwVk5B1xDdJeJz2t2KeRejk7QisykaVJBeuo2TIsL= SNUcSCarpm3K5W62Wd3LXyvMSsHIfjtXaHk/IPONN0LOLnS76FnklmeXVpW0TaUrALsGrhiKzMq= DdEqqiagru0BTKqQrgUO5mnaAdZk/nmmccg6+GVTrPRWUZCSuCZdO3ePitCgJyEO0Q2EqSF0WRj= yzQnTOzfsSOmaKkcBW7R2sUGe87ZlJUrnDah3DW030LxQznXaZMR6kO2i3Wh1zUKujXJV+KozZl= K0nFM2y64uUwkyGMJvaVbeiKgphBfwRbW57ve4Hotxv58LCWneanLvceJmqbjN8bY7LOOc9jd7t= 9XvVc240ZrBoxoxc/Rx9GIxsSL2CdTKyRDt5NJH1WSCpXSaJ0zJmPELX3OtX47Zbk4xld49WWtI= 8c8cv6bPU+VMBFbvYG8znEDNSpHFXlECz9gnVnaj5uykFGYPbQul84IMzKvCIC3ct7emmPMMsOL= 0vn860zi1Zc/vOd02rtqPSbLHQ0XMGkI+PM2vkPMqvZoKk/FVArRF83be2zNGgRigiVsinta7PV= XgXCk8fldTM3YXrMMkxCyLafkuZWpOYmaNn8Xm0WtRp29SPv8ATZayMIZJ23jay/RmSyJhM1kXJ= mjP3VoENyCQAWuAA4Nu4ABva506NAdNeGFiAflIGQfyDXz+9oX/AHejpYfk28F/O0X/AMLm3/M+= jqa1L1t7T5Pn1nq0WKlcDx/c7O50X7aTRxAfIePzQnPh+IgP4fePWhPyddQC0bkkUfr+llE8/Z8= IecAfj9Xw8+f+/HUU4cdv7lLjuIcm8H2jD7I5r3IqHr0UFizPRsakZiuJw5nwLqqxtoucMyVOsD= 0pk1U3S4F9ExDNzeoBiP8A4k8O+RnBJ7bZLGZSQmKlcJSJXsOabhnySLyQLGAKKTmP0XELTqvzO= 9K1cviN3jmouIr2xKMmyQTKR0BBbcbVZBmdNyk5bQ5lTTyZ9tFleaZXPHJzlLUwUdPAkvfYlfm2= urqolCAm1yNbjRsXs9n2V1mwmZVeV1cUOTZXX0VfE8RWeBqqWoKHm3KmRbSIxMbNYE31FsdfvK0= ir6VrfbYz+5xhJeo3fk6lVrRFHcOGpJKDnH1NjpVid0zVbu0AcsnCyQrNnCC6QGE6KpFClMFAOQ= uW5zwb5+WTMuNUESOzLTeC+8SepZg4nJ6brsiWMzDWp9FGaOvLqTKDRV/Ta88D3aWaSDYqrj3F4= 1RkVfU2x5EcTs57iNezJvr7jXMas2XSsjZIllWJaHjZJGVlEGjRZ9G2QY6YZSjFEY5JxHuGB46Y= ZeUjTMbDvVPcU49jnaG41Y821t03sOpXu57Bm1oymY0TQLQ3sFsgqhb4s8TNIVxc0aiwaPl2wpF= LIO2L1wQiINimBms5brjyp5tdxyd5Q6FBYqbtod4Eg2GulxcaEixwSkbrIiyKSVYAgkFTbyggEH= zhSOBAtijeF8wuWuhqZFxk4jQ+D52yy7hjm+xXiV0iOuMtHj88QsCs2rlRZM5N1Ii0ZN5qNQQVk= XL9Y/pvFHsr6xEEnKVzjk1tXKLZsJvCsFkMXvF84K8hXqOgPIS2iwhyVbUNbrIxDaEaWsI8Yl3D= QiqigrMnEkMm8OuV+m2BNqk8+YnCC00W15VE8auOnKG5zVDwKv5aO74pyJouPyU1BRBn0ZH028R= 01EKGmF2DVhGyDySj2zFB63eN2Yl8RyJUX1w04B1/jTkeI7ryLk5qA1DFMA1Gj3KutJJhL1SKpt= 4tt6vs23kyxrB69lbDFM7Y6ZOXMPKLMXDlASsknXlNdZ1xYbqhmY7qqoBdmN7C1yW3jYBbAkker= 13VFZ3YIigszMQFVRqSxOgAGpJ0A1OKbcM903LjN2xKDoczu+EZpSrBentZxz6UZdot4mknq+ha= crd4WZiaS5eydilpuRaoPa2pEx7dtExbR6nJAsusgoCQ1LnZpnLLO5HPNLe0m1LYzzV4hOK5oFI= p11z5jZoW5ydiWMi9pl+Qa2SJexrqJMQVHjZsVyC5wQTXaJtn725DziHwUrNOiscQ3zka4g5+5Q= OqZhGMbq3MthM9ETkoZpJ00q8W2SqiFmC/PplZ2qk/SnoqECyNHiosGjx5MIPg3wmantTlxyW2T= U7bc9XxC5TMjYLlA2S7S14yuXmI+nwB1XVdbvFjpGkHbSfYPDEes4yLQOmuybs1RNO0Eqd8anmA= ZmKHmmANpFTQ24cRfgSb4qJmVA5ZVq4Cy7u8vOC4LIJFFuklDvWFyBe40ONuvSS/gF/q6OvX7oX= +Le/2Zf8AR0dUtxur9R8cWOei+2vz/v79RxJhAPP1fvgD9XgPh+H3dfg4j7Q/H/3gOjo6iHht5v= hhg4N95ezjzKgAen4AA8G+HgPq8h4Hx9nkBEB+4RD9PXWL9QfgH7Ojo6cP4TsLiZeHs7K4+9VV5= lFKfDJdM5QMRW55SkqQwAYiiSmoU8iiahR8gdNQhjEOQwCUxTCUwCAiHR0dXsu+nUv48XvFxz84= +rK30eXsNhQMs+oUo+in8nSKhIv0YuFBF6+rUM7dpAh7qdAE3LhkosQETqqGS9k4emZQ5ieyJzC= MxjM+oTfS05tvSKghNGs7h2aXRrUMlKGdlSQ9l0L8jIrsXBfbP4WFX1A9o3g35w+To667eJ/Kr7= uPGQTx6+np2zi5HR0dHWfHR6v68bnH/9k=3D" width=3D"65" height=3D"34" alt=3D"edi= torial1.png" style=3D"margin-top:46.65pt; margin-left:-1.05pt; position:abs= olute" /><img src=3D"data:image/jpeg;base64,/9j/4AAQSk= ZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/wAARCAAzACsDASIAAhEBAxE= B/8QAHAAAAgIDAQEAAAAAAAAAAAAAAAoHCQEFCAYL/8QALBAAAQQCAQMEAgEEAwAAAAAABAECAw= UGBwgACRESExQxFSFRChYXImFx0f/EABcBAQEBAQAAAAAAAAAAAAAAAAcABgP/xAAkEQACAwABB= QADAQEBAAAAAAACAwEEBQYABxESExQhIggjMv/aAAwDAQACEQMRAD8Af46OjqPtnbT19pzCb3Ye= zssp8LwzHBVLt8gvCWjBDR+prIoY0/2nLOLmcwYCvDinOPLlhEDHmJmiid0Slthq0V1Me9xitSU= gTGtYc+oLWsIkjMymBERiZKZ8REz1zc5NdTHvatCVATGuaYrWpYR5NjDKYEAGI8kUzERH7mepA8= p/Kfx1j1N8+PU3z/HlP+f/ABeqVqbvt8Jr3OVwyOTZdFWkFSA1ux8lxEQLApiVX2xCTvgXlnmVX= UEzOYjji8QbIHErpzhRYY3ubU1cdz7mfxn5uZPlm+VW+wHIZKuEnWdBYIbrix1XNJITi+XabtnP= /H2DCa4mSzrsnjn85GRJPX5E8aeH49UpYvZnnWs29VdmFj36+YWlSo7EFSs7EAawOtmgYzDHrg4= l0GQxXI0i/wCf3WUmex3d4ZlLp2FaEa1N+gNC5cy/FpGV7BJRYvkM+wLOfEKgBInCLiV7yqRlxD= o6iLSG79a8g9b43tTVWSh5Rh+ThsKCNHVYyRCERGmVNuDJ4Jq7msIR4ljXFsYQMQxzXIrFY98uo= vn99F9ivYqPdVtJbWtV2GmxXcBLchyykWKas4EwMCiRISiJiY8TEdJVewi2hVmq5diu9YtQ9Jix= TVHEEDFmMyJAYzBDMT+4nrC/pF/6XpT3nUdtnuK9ymr4RUOQk4zrDWNyoRzG+4+tr/xdBHfZ1n1= kE1WMtLqEQlaDGYiXtgjlmDDinAZbWJb2NOVXJvAuJWlso3TsOOyKp6JkIdfU04shVlf5DY+uGl= ohVRijhvsTEbDJYHPhABhSUkiVGRo16qI/IzIdpbrXuOcXKaupd/YC0g7kbxvkMntHX2FIGlIdn= +FTPiHMynELDHfi1+dAiCtv8MuxIMqZDLVzMOAb+zGPqJZucqr5wj8cu/j8c3roBOZm8rtrX+Cx= xMghX5XJVxuGE1a1i1XW9i5sBMjHd/YzWji8affMvrp09TexqhmN+/xusyfywVAyP1mCj7figX3= elDzUB/GY6YhB7VfCUPS8umI9NY7MGVVKHPnRI8RGyXWSwtamRR5fJGtgPatna0uOAdY6lj0UdK= /4KvGdUTRdrDkVkOQZ1w222OJl+hcNobTMeOHJsiVkVxrmwtCZfxmKBhucQfYVV0ZBNBnOuJ50C= qJIY8nobcZhVdLaX3cReVWu+YenKTbeunFCjkSyVGSUFixW2eK5SHAPLaUBjka2In4yFQzCmj+Y= DQyByGpG+R0MXSFrY1tHXH3NucJXVdWGSfY2B88QoYIIkMk5JZRMzmxQjjwsfLNLI5rI2Mc5yoi= KvWUqdwOe8Xu62dct236c3vZga8vt3crcQ6I/PokbIOvciCZWYAyVW3WcxNmvYSQhGktcF4RySn= laNOtWr5wU4gGZcJrVNLIarzNO6IrgHVon0eDDEbFV6oalqmwU9I58SuT+6O1tyoyPV2yYzf7Gr= szjxXduBRTymB/EZJDAzPcSRzWRSWQ1XMNf0xMUUDMlpXwAkPgaWMUE8dUWlfdVVbcVZg59ZbAi= 2VccLK2UY0A6BhIZY8rVVskBA8sc0UjVVr43tc1VRUXr583cE3tjvJXl/uzbuHxK/Er/ACCvpsW= nWB0cltS4hQ1WHgXbontZM1L9lKlvBFM1pEAx0A0zI5YnMa9RxXxy/wAO4zce8TyiKWDJMb0rrG= jvRiFX5AltV4ZTBnhzfa+6GTDINJ5VVV0S+V89KX+gsdE5nBOXXKaczlG/mAHIKaVwn6WFUKDya= xX6mG1muOsZlEnISlZlMpiZOexWs6NHmXF6lp2lx3FvkeHaaXvKq7bllALA5/XzsKUD4GPUfcWM= ERhk+JUzrBcS2RiV/g+c0NblGJ5NWFVN7RXAsRlfZAGRuingnhlaqepWuV0UzfTLBKjJoXxyxse= 1MbnhwQ2924Nv1O9dE2uRf4mTIUPwjOa90pNrr20Je5G4fmD/AEOiIBJjklBBOsI5K7Iq6R1XYx= zFPIhIdo++vJ5vhGKbGxS+wjN6CsyjFMlriKq9obgWM2vs68pixzDEQSorVRzVRzHt9MsMjWSwv= ZKxj2lHbvuJp8C0mEK40cDSj4buFYn2rX6p/wAGYAfsC7S1kcLZIyJjMpbBLL+VDn3Ac/m9BcEc= 0NuhMux9hMkD6j4mDEGEuRM6xmIyYRPssv8AqqRZHmV/eIHev4l4xqCtxjZ+BzaOy2gFnns6bW+= D/KwPKbkqWQqyt8cDx+NJKYu7OfMeaBbjQxDFEuZHamxt91tc3cV7v+Y8sKkzUmmqm31lpMhWsy= EmyIibm+xI2KjkEtvx5EodBjPueFfSBlHk2boo5rGxaPJJUR9w76/p7K23ySxu+OW5hcUo7AhxI= 2EbKrj7SCjWaaV8o1dldN71iXXwMdHEEPZUhB8cbEQu1NkcsvUjcauwJrDBMgrcr5F7El28+tlG= LhwLG64rGsNIKh9TpGX9lMXLf31f7ixOjCGjx2OX2lacpg00giOubrf50wbp83qP1NHVk5vVOP3= E3LJ0b8+D9UIegKsuW2ZlbrmharqIfopklAHApeyu/WzTVw2wihQzBAadnYpsqVl26Y/x/wBXpc= Vj5mH/ALXVpoc2P5cuPJr6ru7QPbou9/bGx3kTtWhlD0br25iuMcCtBnMh2bl9OSktcOOPO1ENx= SksYULuifDgbMsWOjRpMTrRgrl7Go1qNT6RPCfX0n148frx4+utRQ0NLjVRW0GP1VbSUdMGNW09= PUhD11ZV14cLIBQQARI4RRBRoGMhhHHijiijYjGMa1ETrconj66Au4nP9TuJvnsXxitVSE1svOA= 5NdGn7ycD7+AhthxT9LL/AEGWn6jECpSgBy4DwXO4FiDmUimxaecWNO+QQB3LXrA+0D5KVoVHkE= Kki9BkpmZMzKToVEX76OjrBdbjo6PCJ9J46Ojq6uhERPr9dHR0dXV1/9k=3D" width=3D"43" = height=3D"51" alt=3D"" style=3D"margin-top:3.75pt; margin-left:-5.55pt; pos= ition:absolute" /> </td><td style=3D"width:1.55pt; padding:0pt = 5.4pt; vertical-align:top"> </td><td colspan=3D"2" style=3D"w= idth:358.55pt; padding:0pt 5.4pt; vertical-align:top"><div style=3D"border-= top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; clear:both"><= p style=3D"margin-bottom:0pt; text-align:justify; line-height:115%; padding= -top:1pt; font-size:8pt"> CIENCIA DIGITAL, es una= revista multidisciplinaria, trimestral,= que se publicar=C3=A1 en soporte electr=C3=B3nico tiene como <s= pan class=3D"Strong" style=3D"line-height:115%; font-family:'Times New Roma= n'; font-size:8pt">misi=C3=B3n contribuir a la <= /span> formaci=C3=B3n de profesionales competentes con= visi=C3=B3n human=C3=ADstica y cr=C3=ADtica que sean capaces de exponer su= s resultados investigativos y cient=C3=ADficos en la misma medida que se pr= omueva mediante su intervenci=C3=B3n cambios positivos en la sociedad.</spa= n> <a href=3D"https://cienciadigital.org" style=3D"text-dec= oration:none">https://cienciadigital.org</a>= La revista es editada por la Editorial Ci= encia Digital (Editorial de prestigio registrada en la C=C3=A1mara Ecuatori= ana de Libro con No de Afiliaci=C3=B3n 663) <a href=3D"http://www.ce= libro.org.ec" style=3D"text-decoration:none">www.ce= libro.org.ec</a> </div> </td><td st= yle=3D"padding:0pt; vertical-align:top"></td></tr><tr style=3D"height:23.65= pt"><td style=3D"width:37.8pt; padding:0pt 5.4pt; vertical-align:top"><img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUg= AAAE0AAAAcCAYAAAAk2zLiAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAE= 1VJREFUaIHtmVl4VFW2x3/7nFNThspMCIEQQgIIBBRkaIYWkEFQQbG9Aa+EQRlUtBlaBZtPbMBu= VGznDuA1eMMgiHyIAsokqJhIEpFJgiaoCVAhQAKVpFJVp6rOvg+VFAkCfr7f9XJS+5y19lr/vaa= 9InRdl2fPnSVgGAgBCBAIgiQbH42/hQDZuEbz7wAhkciggGYkpQzKRSDl1feimTwZZG8Simwp4d= ptAVAQIVktXrXY/homrm4i5NUPZUszmtlD0CYpMQIGHVLTUFQFUVl5Vs54bBaj77kbiXH9PRotE= SL4bDJdIhv/aHy2xOu3JJsZKiUGEmkYgEBTlOsbLq41vEkvgTQkhiExBCiKQAjRUg3RwoiW/FIB= KQlII2iPAEUoIV4hQAqJlBJFKOzdtZd/Lv0X6ekd0epdDbRvn0pCQsJvQWsyLiDRdR8ejwevruP= 3+1EUBU1TCQ8Lw2Q2Y9JUhPI7qEmQUqDrOpcvX+ZKrZP6ujqEULDb7URHR2G3R2Exm2h0ebhGJ8= Mw8Pv9XL7sxFlbS63TiTQk9ig7UfYo7NFRWK3WRl3kb0ATQhAIGNTUXKHW6aS2rg5d1wmz2bBHR= RETE43NZkPTtNDeAkFax478/PMvQdCQEiHUkMDmYEkJXreO48w5Thw/TllZGZcuVuNqcGExW7BH= 2WnXLpnumZl0SO9AdEw0iqqFTqr5wSJBGgaXLl6ioKCAY98fxe/3Y7XaMAwDt7uBSHsE/fr/iR6= 39iAqOhpFDXqPbIxNw5A4rzg5duQYBQcLqK+vJ8wWhqIqeL1eFEWh5209GTBoEHHxsaA0BkAoQi= Qet4cffzjFvr1fcOnSJWw2GyaTCY/bQ0AGyEjvyB1D7qBtSjuESQt6umwC30AIgQZNYSFC+afxN= c4rTvbt3sPX+7/C4/EQGxtL69atiYiIQNd1ampqKCr8jvxvCkhNS+X+v4ynU5fOKKoIRmzQxxEy= KPtSVTW5772H1+Nl3LhxDB8+HLPZjKqqOJ1OtmzZwhd79lFaVsp94+8jJj4WTVwN25qaGj7Zuo1= fT5czcMAAsrKyiIuLw2QycfHiRQ4cOMC2bds4efwkUx6ZQuvk1qFYNQBXvZuv93/Jns9307dvX5= 55+hnatm1LWFgYNTU1HD9+nLVr17LynVU8PHkSnbp2QTGrhHJSE1KlpaXyzXfe5s9D/9wYnsE4d= jrreG/V//DD8ROktk9l4sSJjBs3jpiYGCwWC4Zh0NDQwKlTp8j5z384ePAgiqYw5dFp9O7TO5hj= aAIM6l31vPbKv5GG5P333ycjI4P6+noWL15Mp06dmDNnDnV1dRz8+iB/X/R3OqSnMv7B8YSFhwP= gdrvZ+tFWyk6VsWTJEoYOHUpERATV1dXk5+dzzz334PF4KC0tZcb0GXh0L/MXzCM8IhwhBD6fj2= ++/IatH21l/vy/kZ09ifDwcOrq6vD7/URERGAymbhw4QILFy7km/xvmP3UbDqkp4GAwoJDDPvzM= EaNGsXVY5QilAK8bg/vv7uGI4eP0L9vPz7avJk5c+bQpUsXkpKSiIuLIyEhgZSUFIYOHcp7ubm8= 8MI/EIZg1TsrKTlxEimbPDZYVQ8cOEB5eTm5ublkZmYSFhaGy+Xi4MGDfPHFF0gpiYqKYsTIEcy= fN48jh4/gqDgXShOOsw6++uIrxowZw6BBg4iMjOTixYts2LCBV155hcLCQqSUdO/endw1uVyoqm= LXZ7tCKafKUcWnH3/K1KmPMGvWLGw2G+vXr2f8+PGMGjWKRx55hIMHD9KmTRtWrFhB+5T27Ph0B= 676ekLGNLpbi5IlEcgA7PlsD8WFRfTs0YN169eTnpGBzWZDUZRQjmnKMyaTiZiYGGbOmsmKf7+K= 1+Nldc5qrtQ4g+egQIO7ge0ff8rMGTPp2bMnqqricrm4ePEi06dPJysri+LiYgDMZjNjx42jR2Y= PPt32KboeIBCQfPLxJ9TX17Nq1SomTZrE3r17GTFiBEuWLMHhcDBr1ixOnTqFpmnccsstPProo+= z+bDcetxfDkBQVFRNlt/P4YzOxWMxs376dOXPmcP78edq0acOhQ4eYMGEChw8fJjExkeeff56ff= /4ZxzlHs8i8FrTGYlV1vort23dgt9vZvHkz8fHxSCnx+/34/X4Mw2hWKCSBQADDMFAUhQkTJvDE= E09QU13D3l27wB/ACARwOBzofp2p06aiqsGic+bMGbKzs5k/fz5Tp05l/PjxjTlVYLfbGTJkKJW= VVcF9AwEqfiln4cKFLFu2jIqKCrKysigtLWXatGns2bOHrVu30rNnz6BRisLEiRPxeLw4Kh24Gl= ycPv0zw4ePIMoehdfrJScnh9jYWDZs2MDOnTvZuHEjAAsWLACgY8eOxMXFcfbcWQSisQflWk+TS= AH5Bfk0uN089de/0rZtWwKBABcuXKC4uJjCwkLOnDlDIBDA6/VSVlZGfn4+x48fx+l0IoTg6aef= JioqikMFh6i94kQIcDe40RSN1PapwV6q0VsNwwiB33QYTUanp6ej6zqGESAQ8KP7fPTt25eZM2e= yf/9+Xn31VQYNGsQHH3xAVlYWu3fvpqysjLq6OqSUdO7cGSkldbV1eHWdWqeTrt26opk0fD4fFo= uFzMxMkpOTAejUqRNWq5WjR4+i6zoWixnNpOF2e5BG86Zdol3FTOLTdX48WYKmKGRPmoRhGDgcD= ubOnUtJSQkmk4nExERWr15NcXExS5cuDXnH6NGjWbRoEfHx8QwcOJADX+6n8kIV9viYxv4s6JUQ= rKpmsxm73Y6qqkgpadOmTTNVgiAKRaAIJdh0ChHqDxMSEpgyZQqjR4+mqKiIvLw8Fi1aRKtWrRg= 7diwPPvgg7dq1I3ibUEIHFQgEEEIQHh7OsmXL8Pv9xMXFoSgKgUAglHIg2N40XUNa3nNky/B01d= fjdDppm9yW+Ph4fD4fb7/9Nvn5+Tz22GO88cYbJCUl0dDQwMKFC/F4PLzxxhvMnj2buLi4kKjBg= wej6zoXL14ECVHRURiGwQ8//BDyrNatWzN79mzCw8NRVZV33303lLQNw6CkpASr1YqiKKiaSkRE= OCdOnGiKCWpra1m/fj3R0dFkZ2djsVgwmUzs2rWLyZMnM2vWLBRFCVX7mNhYioqK8Hp1hBCsXLm= SxYsXU1JSQk1NDcXFxbjdbgYMGIDZbMbj8eDxeIiMjEQRollwimaehsTtbsDt9tAmLRlFUfD7/R= QXF2O32xk2bBhdunShV69e6LpORUUFY8aMYfDgwfTv3z/kPYqi0K1bNwIBg7raOpCSVq1aEREZw= epVq8nMzMRisRAREUFycjImkwm3202PHj1CYXuh6gL79++nXbt2mE0mpIDUDml8/vnnZGdn07p1= a2pqatixYwd5eXl4vV7S09NZtmwZ8fHxbN68mddff51IeyQJreIxmU107tyJgwe+5sKFKlI7pNK= vXz+2b9/OlClTyMjIoKioiLi4OJ577jl8Ph9HjhzB5WogJaV9s6ZfAUSTpwVxVFUFVVHweDyhML= JYLOi6jtfrJRAIcPr0aXw+H6qqUl9fj8/no7a2lsrKSnRdR0qJy+VCCIHJpKEgsNos/OW/HuDDj= z7ks88+a1FMmvZp+u1yudi48QNKy0q5Z9xYVE1FUQT3jr2HijMVrM3Lw+Vykdy2LWvXruWFF14g= LS2NdevW0a9fP9LT0+nVuzd+I8C9943FYjGjKoLb+/YmgGTJkqW43W6ysrJYsmQJcXFxlJWVMXT= oUHJzc+nduzdnz57lH0v+QcdOHUlsnRi6mzaRFopNICwsnPCIcBwOB36/H5PJRHZ2Nk888QRz58= 4lPT2dffv28eabbzJkyBAKCwuZMWMGVVVVNDQ08PHHH2M2mzl06BCaphEdFR2aEvTt15cTR08wZ= 84chBCMGjWK5ORkHnroIbxeLwB1dXWsW7eO1994nTvuHEpim0QQEkVAq6RERtw1kpyVOVhtVqZN= e4SkpCSGDRtGamoqbdq0wev1snvvHubNncutvXoxZOiQoD8ogpj4WCb890RWvZPDU0/9leXLl5O= dnc2ECRMIBAKoqorVauXHH39k+vTp6F6d+8ePx2y1tJiCAKhPPjX7hcKiQlI7pKJpKke++56ff/= mFMWPGkJKSQlpaGsnJyRQUFIT6oaysLEaPHk1paSnHjh0jMjKS1157jZSUFACWLl3K5SuXGX33a= KKjo4Nep6jcdlsvTpedJicnh6LiIrp3z2T48OH06dOH4uJipj/6KB9u+ZAhw4dw1913YbaaG71Q= oKoKySltkTLAqpWr2bFjB4mJrbFYrZhMZo4dO86zCxbw1ltv0alzJ2bNmolm1lBU0TTCID4hgXZ= t2/H+mvfZsGEDYRHhREZGovt8nHM4ePnll5g3bz6BQIAFC54hPiEWoQQnJ+fOnqND+/akp2cgSk= t/lG++8zaDhw1BSoPi/EOsfHslQ+8cxsaNGzGbzQD4fL7GkDM1qzBGKFQ1TcMwDAoLCxl25zDS0= juy4O8LsIVZr6ZQqeDz6hQVFbF71x4c5xyoioJEYhgB0jMyuPveu0nvnIFmNjWb7V1Nw37dR+mP= P7Hzk52UlpaimTSQAsMwSEpK4s6Rw+nTpy8WixlDbWpjBFIYSAmqVDh/ppKtWz/m5A8n8fl9KEL= B5/MRlxBH//79GDliJBH2CALCQApQpeBQ/iGG3TGEUaNGB8NTSok0JBJBl65dSUpOYteuXXz00U= c88MADWCwWzGZzs4TY6KaqGmpWDcPg/PnzzJ8/H03TuPveuzFbbc2GkMEsYLKY+dPAAfS87VauO= J24PR6EENhsVqJjYjGbtcZ7K82mg1eBM5lMdOvendQOHalz1eNucGMYBrYwG/aISGw2K6oSvGQr= 8mrVE6HppqR12ySmPzaD2ro66uvq8fl9aKpKTEwM0VH2IB5IBKA0zWGbtSOalJJ6Vz0Xqqowm0z= YbGFMmpLNv1e8xtPPPE1iYiL9+/cnIiIiOJBTlFBv1iTI7/fz66+/MnfuXL777jsGDh5It27dqL= 1yhYDfj9I0Gmu8qjV1PlaTBavJEsLFXVePR8rrDx6vIYmCWWiYwiIbv5d43W68bncI5OaNQospb= 7NhaERYGE1TDL+uc+nipav8zfo0V50r5DSipKREDhw0kMjISFRVZex94+jVpw/FRUWsz8vDZg3j= iccf54EHHiA5ORmLxdKin3I6nRw6dIjly//F90e+55auXZn6yDQCRoB3V79L7WXnzSy/Pv3uBPg= m736P94/u2/htfX09eXl5jBo1KuhpNdU11FTXAPDhps0kp6TQ9099sdmsrFvzv7z88sts2bKFQY= MGkZmZSUJCAi6Xi4qKCvLz8zl8+DDOOieDh/yZcfffj81q4/01ayg58QM+3d9CB5PJFGqEGxoaQ= usul4uwsDAMw8Dlct3QXovFgtVqxeVyYbPZCAQC6LpObGwsQghqamrw+Xw35A+mAhuJiYk4nU6u= XLmCqqpERkZSW1uL3++/IW8TadcuVJ2vJOed/zB3/lx69uxB4tN/Y9+efRQUFFByqgSTZkLTNKS= U+Hw+JMEr0EOTH6ZTl05YLVY2rF3Pt998+xvAAKKjo9m0aRPnzp3D5/ORl5fHpEmTePLJJ8nJyW= Hx4sWcPn36hgp37NiRF198kXnz5nHnnXdy6dIlLBYLDz/8MIFAgNzcXHbu3HlT41esWIHf7yc2N= pZFixZht9t56aWXeOqppygrK2uRv64leT3QAv4A5b/8wovLlvL444+TkZHBxOyHGDN2DOccDsrL= y6msrETTNDp37kJKSgrxcXFYrWF4vR7ezVlN/jf56I2917WkaRpms5ktW7Ywfvx4ysvLsVgs5Ob= mcvbsWc6cOXNDhQFsNhtpaWksW7aMU6dOoSgK9913HwsWLKChoYHExESU5v+kuQ4NGjSIDRs2sH= 37djweD5MmTeL48eNMmDCBF1988aagieuBFgTOz/lz5/nnsn8xYtRIRt41gvhWccQlJtDjtlsbi= wBIaWAYwQRc9O23bNq4icrKyptu2gRceHg4drsdTdNYsmQJhYWFdOnSJXSpv6HSQvDTTz+hqioD= Bgxg27ZtREZGUl1djdvtDo2ybkSKovDkk08ycOBAnnvuOdasWUNmZibl5eWMGTOG5cuXt5i4XFf= /665KQEo8DQ3s2PYJB7/8ioyMDDqmdyQxMZGIyAh8uk519WXOnDnDqZISKs850HX9ppsBodlcq1= atQgBVVFRQXV3N+fPnfxc0v9+Py+XirbfeYtOmTbhcLrZv387zzz+PEIJvv/2WI0eO3DCvqarKs= 88+y65duygtLaVz587U1NRw9OhRMjIyuP322ykoKLipDuLkyZOya9euv2usEAJFVdBUDZPJhGEY= 6Lr+m5HK71F4eDj9+/dHURQcDgenT5/G7/czePBgvvzyy9895bi4OGJjYzl79iyZmZk4HA5cLhc= 9evRASsmJEye4fPnyDXVSFIX27dtzyy23UF1dzZUrV/D5fJSXl5Oeno7X6+XXX3+9Lu/OnTsZOX= Ikory8XE6ePPmmija/UF9v/Xrvbiarqc/7I7zXNtbN6Y/Ia95fNpfbXMaN+FesWBGaDv8//UH6P= w/h65aldWKXAAAAAElFTkSuQmCC" width=3D"77" height=3D"28" alt=3D"" style=3D"m= argin-top:-0.3pt; margin-left:-0.75pt; position:absolute" /> </= td><td style=3D"width:1.55pt; padding:0pt 5.4pt; vertical-align:top"> </= span></td><td colspan=3D"2" style=3D"width:358.55pt; padding:0pt 5.4pt;= vertical-align:top">Esta revista est=C3=A1 protegida bajo= una licencia Creative Commons Attribution Non Commercial No Derivatives 4.= 0 International. Copia de la licencia: <a href=3D"http://creativecom= mons.org/licenses/by-nc-nd/4.0/" style=3D"text-decoration:none">http://creativecommons.org/licenses/by-nc-nd/4.0/</a><s= pan class=3D"Emphasis" style=3D"line-height:115%; font-family:'Times New Ro= man'; font-size:8pt">. </td><td style=3D"padding:0pt; vertical-align:to= p"></td></tr><tr style=3D"height:0pt"><td style=3D"width:48.6pt"></td><td s= tyle=3D"width:12.35pt"></td><td style=3D"width:106.25pt"></td><td style=3D"= width:263.1pt"></td><td style=3D"width:6.05pt"></td></tr></table> <table style=3D"width:437= .1pt; margin-left:0.25pt; margin-bottom:0pt; padding:0pt; border-collapse:c= ollapse"><tr><td style=3D"width:74pt; border:0.75pt solid #000000; padding:= 0pt 5.03pt; vertical-align:top">Palabras claves: Aula invertida; m=C3=A9todo; ense=C3=B1anza de historia; estrategia pedag=C3=B3gica.</spa= n><spa= n style=3D"font-family:'Times New Roman'"> </td><td colspan= =3D"2" style=3D"width:4.15pt; border:0.75pt solid #000000; padding:0pt 5.03= pt; vertical-align:top"> </= td><td style=3D"width:321.8pt; border:0.75pt solid #000000; padding:0pt 5.0= 3pt; vertical-align:top">Resumen Introducci=C3=B3n:= el "aula invertida" c= omo m=C3=A9todo de aprendizaje en la asignatura de Historia es una <= span class=3D"Strong" style=3D"font-family:'Times New Roman'; font-weight:n= ormal">estrategia pedag=C3=B3gica que transfiere la instrucci=C3=B3n direct= a, tradicionalmente impartida en el aula, a fuera de ella, generalmente a t= rav=C3=A9s de recursos digitales (videos, lecturas, podcasts, etc.). </span= >Objetivo: = determinar la influenc= ia del m=C3=A9todo de aula invertida en el aprendizaje de Historia en los e= studiantes de Primero de Bachillerato de la Unidad Educativa Combatientes d= e Tapi durante el a=C3=B1o lectivo 2023-2024.Metodolog=C3=ADa: la investigaci=C3=B3n adopt=C3=B3 un d= ise=C3=B1o cuasi experimental con un enfoque cuantitativo, alcance explicat= ivo y corte longitudinal. Poblaci=C3=B3n: estuvo compuesta por 145 estudiantes de primero de bachille= rato y 5 docentes del =C3=A1rea de Ciencias Sociales de la Unidad Educativa= Combatientes de Tapi. Resultados: el an=C3=A1lisis descriptivo de las encuestas a los estudiantes re= vel=C3=B3 que la mayor=C3=ADa disfruta de la materia de Historia y prefiere= m=C3=A9todos de evaluaci=C3=B3n escritos y proyectos. Los estudiantes auto= evaluaron su nivel de comprensi=C3=B3n lectora como bueno o muy bueno y mos= traron motivaci=C3=B3n para profundizar en la materia, considerando importa= nte su aprendizaje. Conclusi=C3=B3n: el estudio concluye que el uso del aula invertida en la materia = de Historia tiene un efecto beneficioso en el aprendizaje de los alumnos, p= otenciando su comprensi=C3=B3n conceptual y habilidades de an=C3=A1lisis hi= st=C3=B3rico, especialmente en el estudio de fuentes primarias. Adem=C3=A1s= , promueve el aprendizaje independiente y el trabajo en equipo, facilitando= la construcci=C3=B3n del conocimiento a trav=C3=A9s de la investigaci=C3= =B3n y el debate. =C3=81rea de estudio general: Historia. =C3=81rea de estudio espec=C3=ADfica:<sp= an style=3D"font-family:'Times New Roman'"> Educaci=C3=B3n. Tipo de art=C3=ADcu= lo: original. <= /p></td></tr><tr><td colspan=3D"2" style=3D"width:77.2pt; border-top:0.75pt= solid #000000; border-right:0.75pt solid #5b9bd5; border-left:0.75pt solid= #5b9bd5; border-bottom:0.75pt solid #5b9bd5; padding:0pt 5.03pt; vertical-= align:top">Keywords:<= span style=3D"font-family:'Times New Roman'; color:#767171"> Inverted classroom; method; history teaching; pedagogical = strategy. </td><td style=3D"width:0.95pt; border-to= p:0.75pt solid #000000; border-right:0.75pt solid #5b9bd5; border-left:0.75= pt solid #5b9bd5; border-bottom:0.75pt solid #5b9bd5; padding:0pt 5.03pt; v= ertical-align:top"> </td>= <td style=3D"width:321.8pt; border-top:0.75pt solid #000000; border-right:0= .75pt solid #5b9bd5; border-left:0.75pt solid #5b9bd5; border-bottom:0.75pt= solid #5b9bd5; padding:0pt 5.03pt; vertical-align:top">Abstr= actIntroduction: the =E2=80=9Cinverted classroom=E2=80=9D as a learning method in the s= ubject of History is a pedagogical strategy that transfers direct instructi= on, traditionally given in the classroom, to outside it, through digital re= sources (videos, readings, podcasts, etc.). Objective: To determine the influence of the inverted cla= ssroom method in the learning of History in the students of the First Bacca= laureate of the Combatientes de Tapi Educational Unit during the 2023-2024 = school year. Methodology: = The research adopted a quasi-experimental design with a quantitative approa= ch, explanatory scope, and longitudinal cut. Population: it was composed of 145 students of the first= year of high school and 5 teachers of the Social Sciences area of the Unid= ad Educativa Combatientes de Tapi. Results: the descriptive analysis of the students' surveys reveale= d that most of them enjoy History and prefer written evaluation methods and= projects. Students assessed their reading comprehension level as good or p= articularly good and showed motivation to go deeper into the subject, consi= dering their learning important. Conclusion: the study concludes that the use of the inverted classro= om in History has a beneficial effect on students' learning, enhancing thei= r conceptual understanding and historical analysis skills, especially in th= e study of primary sources. In addition, it promotes independent learning a= nd work. General area of study: History. Specific area of study: Education. Type of item: original.</td></tr><tr style=3D"height:0pt"><td styl= e=3D"width:85.55pt"></td><td style=3D"width:3.25pt"></td><td style=3D"width= :11.85pt"></td><td style=3D"width:335.7pt"></td></tr></table> <ol style=3D"margin:0pt; paddin= g-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left:32pt; text-ali= gn:justify; line-height:115%; padding-left:4pt; font-family:'Times New Roma= n'; font-size:12pt; font-weight:bold; color:#767171">Introducci=C3=B3= n</li></ol><a id=3D"_Hlk185699730">La educaci=C3=B3n ha sufrido cambios y se han utilizado diferentes para= digmas para adaptarse a las necesidades del tiempo y de la sociedad son sie= mpre innovadoras. Debido a las Tecnolog=C3=ADas de la Informaci=C3=B3n= y la Comunicaci=C3=B3n (TIC) desempe=C3=B1an un papel importante en este =C3=A1mbito educativos = porque rompen barreras de tiempo y espacio, promueven la interacci=C3=B3n y= cooperaci=C3=B3n entre profesores y estudiantes esto es necesario en esta = era de cambio. La instituci=C3=B3n educativa adopta una estructura profesio= nal flexible y din=C3=A1mica, por eso la mayor=C3=ADa de los participantes = en la capacitaci=C3=B3n deben tener nuevas herramientas para mejorar y faci= litar el m=C3=A9todo de estudio La historia, como disciplina que conecta el= pasado y el presente, ha experimentado importantes transformaciones en las= =C3=BAltimas d=C3=A9cadas (Cede=C3=B1o-Escobar & Vigueras-Moreno, = 2020). </a>= Los avances en la tecnolog=C3=ADa y la= s nuevas teor=C3=ADas de ense=C3=B1anza alientan a las personas a encontrar= formas m=C3=A1s efectivas y atractivas de transmitir el conocimiento hist= =C3=B3rico a las nuevas generaciones. En este contexto, el aula invertida s= urgi=C3=B3 como una propuesta innovadora que se espera cambie la forma en q= ue se ense=C3=B1a historia a los estudiantes de primer a=C3=B1o de secundar= ia, como su nombre indica, subvierte el modelo de aprendizaje tradicional, = utilizando una variedad de recursos digitales, como videos, demostraciones = interactivas, lecturas y podcasts, los estudiantes pueden aprender con anti= cipaci=C3=B3n en casa en lugar de que los maestros demuestren el contenido = en clase. De esta manera, el tiempo de estudio se puede utilizar para activ= idades m=C3=A1s din=C3=A1micas y colaborativas como la resoluci=C3=B3n de p= roblemas, la realizaci=C3=B3n de proyectos y el debate.De esta manera, la historia es una materia ric= a en contenidos y tiene muchas conexiones con otras materias, seg=C3=BAn </= span>Aguilera-Ruiz et</sp= an> al. (2017) las aulas invertidas ofrecen = varios beneficios como: <ul style=3D"margin:0pt; padding-left:0p= t"><li class=3D"ListParagraph" style=3D"margin-left:32.33pt; margin-bottom:= 0pt; text-align:justify; line-height:115%; padding-left:3.67pt; font-family= :serif; font-size:12pt">Apren= dizaje activo: los estudiantes se convierten en protagonistas de su propio = aprendizaje y as=C3=AD aumentan su motivaci=C3=B3n e inter=C3=A9s.</= li><li class=3D"ListParagraph" style=3D"margin-left:32.33pt; margin-bottom:= 0pt; text-align:justify; line-height:115%; padding-left:3.67pt; font-family= :serif; font-size:12pt">Adapt= arse al ritmo de cada alumno: Cada alumno puede progresar a su propio ritmo= y profundizar en los aspectos que m=C3=A1s le interesen. </li><li c= lass=3D"ListParagraph" style=3D"margin-left:32.33pt; margin-bottom:0pt; tex= t-align:justify; line-height:115%; padding-left:3.67pt; font-family:serif; = font-size:12pt">Desarrollo de= habilidades: Fomentar el pensamiento cr=C3=ADtico, la resoluci=C3=B3n de p= roblemas, la colaboraci=C3=B3n y la comunicaci=C3=B3n.</li><li class= =3D"ListParagraph" style=3D"margin-left:32.33pt; text-align:justify; line-h= eight:115%; padding-left:3.67pt; font-family:serif; font-size:12pt">M=C3=A1s tiempo interactivo: los pro= fesores pueden dedicar m=C3=A1s tiempo a las necesidades individuales de ca= da estudiante y participar en debates integrales. Actualizaci=C3=B3n contin= ua: Los recursos digitales brindan acceso a la informaci=C3=B3n m=C3=A1s re= ciente y diferentes perspectivas sobre eventos hist=C3=B3ricos.</li>= </ul><spa= n style=3D"font-family:'Times New Roman'">En base a este contexto, se prese= nta el concepto de aula invertida y sus beneficios clave en la educaci=C3= =B3n hist=C3=B3rica. A continuaci=C3=B3n, se analizar=C3=A1 detalladamente = c=C3=B3mo implementar este enfoque en el aula, ejemplos de actividades que = se pueden completar y desaf=C3=ADos que pueden surgir. Por tal raz=C3=B3n e= l objetivo principal del estudio es <a id=3D"_Hlk153400056">determinar la influencia del m=C3=A9t= odo de aula invertida en el aprendizaje de Historia en los estudiantes de P= rimero de Bachillerato de la Unidad Educativa Combatientes de Tapi durante = el a=C3=B1o lectivo 2023-2024</a>. Aula invertida . = El modelo pedag=C3=B3gico del aula invertida (flipped classroom) modifica l= a estructura convencional de la clase. En vez de que el docente imparta la = ense=C3=B1anza en el sal=C3=B3n de clases y los alumnos realicen ejercicios= en casa, se suministra el material (v=C3=ADdeos, lecturas, etc.) para que = los alumnos lo analicen antes de la lecci=C3=B3n. El tiempo en el sal=C3=B3= n de clases se emplea en actividades pr=C3=A1cticas, aclaraci=C3=B3n de int= errogantes, discusiones y trabajos en equipo. = Tendencias. Los estudi= os sobre la inversi=C3=B3n del aula en la instrucci=C3=B3n de la historia r= esaltan los siguientes:<ul style=3D"margin:0pt; padding-left:0pt= "><li class=3D"ListParagraph" style=3D"margin-top:14pt; margin-left:68.33pt= ; margin-bottom:0pt; text-align:justify; line-height:115%; padding-left:3.6= 7pt; font-family:serif; font-size:12pt">Impacto en el aprendizaje </li><li class=3D"ListParagraph= " style=3D"margin-left:68.33pt; margin-bottom:0pt; text-align:justify; line= -height:115%; padding-left:3.67pt; font-family:serif; font-size:12pt"><span= style=3D"font-family:'Times New Roman'">Desarrollo de competencias = </li><li class=3D"ListParagraph" style=3D"margin-left:68.33pt; margin-botto= m:0pt; text-align:justify; line-height:115%; padding-left:3.67pt; font-fami= ly:serif; font-size:12pt">Uso= de tecnolog=C3=ADas </li><li class=3D"ListParagraph" style=3D"margi= n-left:68.33pt; margin-bottom:0pt; text-align:justify; line-height:115%; pa= dding-left:3.67pt; font-family:serif; font-size:12pt">Dise=C3=B1o de actividades </li><li class= =3D"ListParagraph" style=3D"margin-left:68.33pt; margin-bottom:14pt; text-a= lign:justify; line-height:115%; padding-left:3.67pt; font-family:serif; fon= t-size:12pt">Formaci=C3=B3n d= el profesorado</li></ul>Por lo = tanto, el aula invertida es una metodolog=C3=ADa conocida como =E2=80=9CFli= pped Classroom=E2=80=9D que ha tomado relevancia en los =C3=BAltimos a=C3= =B1os debido a que se presenta como una estrategia innovadora en el =C3=A1m= bito educativo, su enfoque se basa por invertir los roles tradicionales de = ense=C3=B1anza y aprendizaje (Alarc=C3=B3n & Alarc=C3=B3n, 2021</sp= an>). Se caracteriza por reci= bir informaci=C3=B3n que deber=C3=ADa absorber durante las clases, asimismo= , trabajar en tareas y ejercicios en casa, por lo tanto, el estudiante se f= amiliariza con el material fuera del aula con recursos en l=C3=ADnea. </spa= n><sp= an style=3D"font-family:'Times New Roman'">Para Dom=C3=ADnguez & Paloma= res (2020) el aula invertida consiste en invertir el proceso de ense=C3=B1a= nza tradicional, ya que en la clase convencional el docente expone los cont= enidos en el aula y los estudiantes realizan las tareas en casa, en el mode= lo invertido ocurre lo contrario. El estudiante accede al nuevo contenido a= ntes de las clases, y en el aula se centra en la aplicaci=C3=B3n de los con= ocimientos, la resoluci=C3=B3n de problemas, discusi=C3=B3n y la colaboraci= =C3=B3n. Los piones Bergmann & Sams (2012) mencionan que esta metodolog=C3=ADa le permite= al estudiante avanzar a su ritmo, y en clase el docente puede ofrecer apoy= o directo y adaptado a las necesidades individuales de cada alumno. = <span= style=3D"font-family:'Times New Roman'">El aula invertida se basa en la ed= ucaci=C3=B3n constructivista, seg=C3=BAn Piaget (1970) los ni=C3=B1os pasan por diferentes et= apas de desarrollo cognitivo y que el aprendizaje es un proceso de construc= ci=C3=B3n activa, entonces, los estudiantes construyen nuevos conocimientos= a trav=C3=A9s de la interacci=C3=B3n con su entorno y la reorganizaci=C3= =B3n de estructuras cognitivas existentes. Por tanto, el enfoque se basa en= la idea de que el aprendizaje no es la absorci=C3=B3n pasiva de informaci= =C3=B3n, sino un proceso activo en el que el estudiante relaciona nueva inf= ormaci=C3=B3n con sus conocimientos previos (P=C3=A9rez & Santiago, 202= 4). Por tanto, la educaci= =C3=B3n tradicional se caracteriza por ser un modelo estructurado y centrad= o en el docente, que supone que la ense=C3=B1anza directa en base a la tran= smisi=C3=B3n de conocimientos desde el docente quien es la principal fuente= de informaci=C3=B3n hacia los estudiantes. Por lo tanto el docente es la f= igura central unidireccional del proceso educativo y es quien contrala la d= in=C3=A1mica de la clase, imparte el contenido y eval=C3=BAa el rendimiento= (Galv=C3=A1n-Cardoso & Siado-Ramos, 2021). La figura 1 representa al proceso del aula invertida. = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; = 0; &= #xa0; Figura 1<img src= =3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAHwAAAAxCAYAAAAY2M0MAAAAB= HNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAABK9JREFUeJzt2mmoVVUUwPHf07TX= YDlkqby0hLKgMs3KBiko0iwKKbR6zXNR1LekARuQvkRE0AcLKoIyhKw+SIVSIlohGRIV2QAVGA0= 0EBGZ4OvD2rd33u2e++59Xr3vxv7D4Uxrr7WHs9fZe69NJpPJZDKZTCaTyWQymUxmWLAfLsHjDc= o/jb50/Iy3cQtG7pHctYbbMK/q2b5YiyP2em7azAKsx8oG5UdhGZaLSpuDz3HlnsjcHuQkzGh3J= lrBiCbl38QdTcjvxHb8jR34AGsws0m77WYLtrU7E62g2QYnGq9ZRgk3PgNn4dP0/Fg8i2uwOb2f= h9exEecnudnCq5yKDVgl3OtoPIDPhOeZW6L3uBK5uXgFH4lfzQQsxfxC3ufiVfGx3ocDCjaew/F= 4GW9gWrMV0wkcrXGXDjeKyliDD3GvGAsQFdknGhJ6RMMcIBr/a0xM6fowK6W9F8/gKDwlfheL8F= iJ3lpyU7Eah2E6NuEu4YkWpHRTsE405DisSPkjPro+XID90/Orm6iXjmEoDb6s5F2X6HUT0v1F+= gd5leNMjEnXlcHe4fg93Y/BVWJA+GSJXjXkFgsPUM2D+ht8SbqvcIL4CLuEd/wWY9O73lTWYc1Q= XHor6cOfhfsRuFxUaOXYiL+q0u0UFT9Z9PTv8EgdvT015EaIXltN0VZXslHhl4LeXfijrGDDlaE= 0+HhRUfs2qH+ycI3dNd4fnPTtk+634nbRk7rF6Hh6Qf404dKX4AWcIUb97+FQ4Vpr6a0ltwW3it= /EaDF2mCRc/CEp3bviAzwv5edc/VPNMUl2vPgwJqajq4F66RhO1+9q1xeed+El0ZOKPF0iX+G19= G61qCw4R8x5N+Hi9GxUkrsZH4teeiCOTHqfEVO+9elcrbdM7kIxCFyb7F5XyO+cQn7WiYHmUv3j= j5UF2csK1xfVKGemSSoNPpwXbDqCdv/DG6Uy+BpbVyrzv6DbwFF7JpPJZDKZTKYBFuAdsT5+TBv= s7yeWMG+oIzMe9xgYBBkqrdTVcfTgeRHcuEMsVOxt5uMHEd0q41oDgyC7Qyt1tZ1mFzJmiWXVtS= LsuLXlORqcr/CTWDbdUiKzVZRtO77cTXut1NV2mll46RVLksvEfPjXdO7Wv7TYW5Cvjms3GqMu4= 0SxZLpBRMvK7FTYUaKnLIb+c53y7GggfUewz+Ai//IivhfhyodEEOKH9G6VgVuAenA2rkjXb+ET= LBQx5VNEjHqS2P2yEJfi/RLb40RI86Zk8wnRy2vZOTm9K2Naid1j65SnkfQdwe4srf5YuN4lXF6= F2XhYhA8/E5X0qNgmVHGLX4hgxGLcKXpOGfPEb2QbfhNbrcrsDLb3rMxuvfI0kr4jaPVaeqXwZX= HtwWLUZRzkv+HY0XXs1KMZu7Uas5n0w45mGrxLuLIp+iv/GzE1myJc4nLh5mrFtWcaPEZdxkfCn= Vfi4VNxf7JbK37eZWBcu0g9u2XlKepqJt8dzSIDgxgjxbRss5giXZvOlU1+1XHtRmPUZVwmKnmF= mBLeLXp+rfh5byGf1XvM69mtVZ7rq3Q1m+9MJpPJZDKZTCaTyWQymUwmk8lkMplMJpPJ7H3+AcZ= SLtlV/feIAAAAAElFTkSuQmCC" width=3D"124" height=3D"49" alt=3D"" style=3D"ma= rgin-top:70.75pt; margin-left:-87.35pt; position:absolute" /><img sr= c=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAMgAAAAxCAYAAACfxeZPAAAA= BHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAABG1JREFUeJzt21uIVVUYAOBvRjM= vWZlpZWpRD+mD4SXMwnnJ7sF0gcgwMimLoofoKbopRAQJRQ89dIGiIKWXlB4qjB7SSroREUKBoE= EPGmZFRFF5evj34eyZc/aZ2TOOovN/cJh9WWuvtYe9zl7/2f8mpZRSSimllFJKKaWUUkoppZSGs= Ba78BGuH0b559Do8Nk1Bn2bgntwd2nb/egbg7ZSarMIyzFJXHS/48Ih6vTgYTxb2jYBdwyjvRU4= vUb/rsF+3FejTkpdTahR9gB+wn/4EefgIPYMUe8CnI3txXoD3w5RZzJewFb8Ncz+7cHPmIivhlk= npa56R1G3gb016/SIO1HzzjMJm8SU7XLML7Y/gX4cws1iIDbEwFldLK8pyi4WA+ljzCu1NROPiD= tL0wq8gy/xGKbV7H9KwzIDG4dZdo32GKQ5QJaLKdFU3Kg1QGC31hRrttYA6cWG4rgzxMC4qCj7u= tYUaz3+xrXF+hx8iPOKei+JgZhSpZHeQW7B8zXKbxJ3j14sKW3fJ+4Ut+MLMXXr5EBp+bCY6hGx= 0HZ8j1/xfqncK3imtN6HnUWbh/CiCOh7apxHGmdGMkCuEBfibyOo28A3WnHLfjFlOoTXDBw8Q5m= EU3Fyh+1N5filR8RNTb/gzxrtpXGo7gBZiR/EN/hJIm7oZoII0KdqfVNPFFOrq4r6i/EB3sSyUt= 1/cVppfR8WiKnSQjwtBsh6XCZ+5p2Px3Fr0d5ZOLOo/6m4U10tpmpX4mUxaFMatRu0xxJri309e= AtzB9Wpeg5yUMQBS0XgvBOvYlap7pNi+rSgWF+Hz0WMcVfxd5q4A30mYooH8ZAYOOtK7V1SHGOV= iEN2iwB+ykj+ESmllFJKKaWUUkoppXR82mDgT7XDTXTslIZ+NGT6ezqqesWzh3e1P73u5liloY9= Fu3VT8NNxrk66ewPniifZW2vUO1Zp6Ee63ZGk4Kfj3GjS3ReK/KlF2IL3RKZsU1Uaeh+2iafn1x= XblmIzLi3Kv43zu5Tv1nad9PfBx+523MEp+FV9S+NYv8hfIi7ihkhBmSouoDuLfVVp6HOLctOKf= XtFesnXxbGWiNjhUZGNW1W+qu066e+djr2tyzkxMAW/qm9pHCsPkF6Rnt68YNaIoLhZrvyuxWpx= ofZrz8taiekGBv7zxCu9N1WUr2q7qt2mjVoDpFNf+rqcEwMHSNW5pBPIaKZYh/FHxb6qNPRekVH= bU/rs1D6n/0frbcVO5avarpP+3qkvO7qc02BV55JOIHUGSPN9itliGjRdpJOfUeybVXx6xDvnnd= LQ5+ABXCyC3mXinfWmZvnb8IZ4d6RT+aq2q9rtlP7e6diLupwTA1Pwq/qWxqnBz0G2lJZXl5b7i= /JVaeirRBr7J+I1W+LdkgbuxXd4CqcU+zqV39yl7brp7+Vjdzsu7Sn4nfqW0hHXHCB1fnZOacyN= JgY5kmYWf/MhXEqDTDZw6pZSSimllFJKKaWUUkoppZRSSimllFJKKaWU0vjwP+GiJvvrzwGzAAA= AAElFTkSuQmCC" width=3D"200" height=3D"49" alt=3D"" style=3D"margin:3.6pt 9= pt; float:left; position:relative" /><img src=3D"data:image/png;base64,iVBO= Rw0KGgoAAAANSUhEUgAAAHwAAABcCAYAAACsstGIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAA= OxAAADsQBlSsOGwAABGRJREFUeJzt2m+oX3UdB/DXnWtuLZebLWXObQZSQVNbS/wLhtIfk62ByK= 2RNfwzi/5BT3ygIYqP9JEgqBOMihRrkQ80xkBHXP+CNKRilIIKBQblEyFHcteDz7nes+P53d89u= 9sY4/2CH/d3zu/z+Z7zO99/557vj4iIiIiIiIiIOCFchmeb1xVHkP9jLFnA8b834LijYpfhJtw4= z3KGxp80zsDVOBVb8PLA/FXYg6sG5FyM0wceZ5yv4G3sPEbxJ41FrfdrsGtg/pexGQ/PM34pnnT= 0Kxy+Y1gFDo0/YS0aH/KB6ebvWtyKuwfkLsb7eAWrsaEn5mLsxqvq4t6hRpJ3sE2NMLepHgd7cQ= i/abZvaLav6omFC/F7/BHnNPuWNMc5gH3NOcwVT00TT2IKX2uVcy+ewaVYN+I69OV+Fo9iIx7HH= 7B+RP5x9xF1UQ/hV2p4n49LsLx5/w01l7etw+9wJj6F57ASfzXbw2/GQXy12V6KB/G5ZvsUdUEn= emJXqor7dFPez1WjOg8PNN9jG+4bE79WNZDlzWdvqAZ8UfP5R7FVf4WPyn1CXc+vN/l3qMZ7wli= mWvF+87+BesRsQzmEPzflzLheDZtd7QqHO81WItWQZi7OBtUg+2K3qAs5Y9LsEH0avq165/1j4r= d0vschXK4a6lPqxm5Nz/cwR+4ivNX6ntvVTeIxMWRIn/FfPK+GoekxsVQv2q163szrL/hS5zxWz= qOs9zrbL6lGt7gp938jYlf48Gi0RPW6Xfinw6eoUfGL8M3Od5lSN3WTavp5FJ/vOfdRudN4tyf+= mDiSCqda8Xn405i4FapnTHX2/xa3NOVMqLn9VnWhlqhKPEvN+x9vciZUT/pEq5xpPI1r8J/W/m7= sq2qYv0SNLOtwO36Kv+EFfFINqXPFr8H3cb6aUr6gpqBL1Zy/B79s9nftH5F7WnOuq5rzXt28Jn= rKOK4uVEPsATXXteepCfxa9Zi2mRurX7T2ne3wYW1mDr5WzZt7zf7r9rNm+zPY0crZ3CpvOX7SO= W5f7KSq2IfwgyZno7pZ29XE7RsTv6I5t73qPmNrE7tJ3fBNqelrtX59uY+1znWy9X7LiDIiIiIi= IuKkcsoC81fhR/gYXl/46Rz18uIo+67Dn1mfaOVFx0J7+P6mjH/gtYWfzlEvLzqGPlrtW947OEd= 83/Ljv9WTpKVmnyxtb+UcHJMfC7B4QOxaXIlvNe/34ItjctarZ+IXqOfd16n137ebz59QS4VD8l= 8ccM7RMaSHb8JdamXngKqMuSoL/q5+iHA9fqh67L9an0+r4XtIfizAkAoftbw3l1HLj12jKnK++= TFPQyp81PJed8my7TL9y49vqhWwNWqIv0cN2d1lzVH5cZx0l/e2m13O6/v1y7n6lx93qF+97lT/= iu1Uy5zd8kblR0RERERERERERERERERERERERERERERERERERERERERERERERERERERERERERER= EREREREREREREnOz+Dy677wVb2+MYAAAAAElFTkSuQmCC" width=3D"124" height=3D"92" = alt=3D"" style=3D"margin:3.6pt 9pt; float:left; position:relative" /><img s= rc=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAJQAAAAiCAYAAAC5r/C8AAA= ABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAAypJREFUeJzt109oXUUUx/HPS1= VSDWpM/6lFUZC2Yiv+w0oNKK21/kGxGyNVMVYputKNFGpVBHXjThAV8T8qiGgXRcWCizYupIsgp= SsXrbhyoaAiCkpcnLm8eY+XNg9JYsz5wvBm3j1n7rlzf/ecGZIkSZIkSZIkSZIkSZIkSRYJ5+PT= Gdpeg49wGPfhhlmKCR7B6Dz4Jv+CFp7ElzOwPV0I6TIsxSZ8PnuhzSsbcfZ8B7EQuQXXmpmgzsK= EEFPD5tkIap4ZxD4pqL5ZidtFyZuJoOBefILrRHbrZlS8jENCrA3byj2mqvZz+R3EWOnvKPYj2I= 2by3gNXscGvIavcHGx/xbPVvF0+/aKax3exHp8iM9wYbF9rorxrvLfxvLch7EHZ0y7QouUFnZiQ= H+CgkvxCt4r/YbV2CsWew2OYTmG8IsQwArsF1lxhbagBvC0tqAexp9CiPB2sb2zzP8EXsIlGMZR= rJrGt1dc+8p8t4lSvhf3V89yVDtDnYcDQnDDeLXYJxU34YLS71dQDZswWc1zh84MNIXrsQTv4gq= cibe0N/ONoOAhbUHBM9qiaOGItmi2ir1fw/4qjm7fXnGN4ntt0ewo92+oBXV3ma9hgxBlrwz9v2= KgD9sxHBeL+wO26Hy5vRjBldV4Ah+LbNPc/x6x0E07hL/xMh4r4yM4OM09Tqv6f1T9KfzaNT4Rt= W+vuA7it5PM0dDCudX4J/w+Q98FTT+C2qm9uKtFSm/pfBG92CO+0KW4CDfiu3JtEo+W64O4SpS5= Fh7Ag+Xai0JkhKjXirKyTuxfbi0+K7Gs2A0JQQ+X8UhpS0QpG6lsu317xbW+2JxT7JeX1mSdv8Q= hBL4Wgtxa/LeIfdzJRL1o6S55LbwvhFYzgssxLl7SF6Kc1Gwuc02I/U4zX7MHatoL4gMYxzfYJU= S3SwhkvLK9Gm9U421V/3G8U417+faK64PKZqzqN8/zVLFfW/kfEKVwt86TbjLHDOk88Z2K7SJDJ= P9h+il5c8l2cRpchlO0y8uP8xlUsnBZhedFmZwUR+7hE3okSZIkSZIkSZIkSZIkSZIkSZIkSZIk= STI3/APh/qZfb7z1lAAAAABJRU5ErkJggg=3D=3D" width=3D"148" height=3D"34" alt= =3D"" style=3D"margin:3.6pt 9pt; float:left; position:relative" />Proceso del aula in= vertida<img src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAkIAAAEuC= AYAAABieX28AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzt= vXm4XFWd9f+5BmICEQwBQZQwCG/AljQgSgAj2Mggo+QnEowNAQTEfkUBG1REAUV9lbZxREExgIi= NKIKNGFFBAQUHyBMVURQSnBhUQFGCQO7vj3WOdWrfvU+dU7fq3hrW53nqSQ377LNPJan61t5rrw= XGGGOMMcYYY4wxZrgYmewBGGOMMVV48LTtRjc4e1nt761LL710tBvjMf3NokWLRgCeNtkDMcYYY= 1rx4GnbuZgxXcGFkDHGmJ7GRZDpJi6EjDHG9Cwugky3cSFkjDGmJ3ERZCYCF0LGGGN6DhdBZqJw= IWSMMaancBFkJhIXQsYYY3oGF0FmonEhZIwxpidwEWQmAxdCxhhjJh0XQWaycCFkjDFmUnERZCY= TF0LGGGMmDRdBZrJxIWSMMWZScBFkegEXQsYYYyYcF0GmV1hjsgdgjDFmuOiXIihPJzeDjWeEjD= HGTBj9UgSZ4cGFkDHGmAnBRZDpRVwIGWOM6Tougkyv4kLIGGNMV3ERZHoZF0LGGGO6hosg0+u4E= DLGGNMVBrAIehHwReBHwL8Du0/gudcDTgX2Ljx3PDB/AscwkLgQMsYY03EGsAhaCzgPOBMVH3cD= b53A8x8InAUUt/SfB9w4gWMYSOwjZIwxpqMMYBEEsCbwOPBr4DHgZuCDE3j+JcCmE3i+ocEzQsY= YYzrGgBZBAI+gGZjPAzujmZlvBW3mA1cBNwGviPSxDXAhcATwA2BO5JipwOnAncANwLzC8Y8X7s= 9CM1L5UtkuwGhwWxjpaxvgs8C2wBeAaxnyAsszQsYYYzrGBmcvG2Q35s8BtwEnAP8BvBe4I3vtu= Ugz9Jrs/lKkKXqwcPx7gVcCnwJenDjm1cBGwL8C+wKvAm6JjGUBWqY7KHs8kh13P7ATcEA21vlB= X7OBQ4ArgKOAk4HdgItrvxsDgmeEjDHGmOrcAbyexuzQ7Oz5HZCG51E0A7MpmvEpsgD4BfCrkmO= mopmeVwNvzB7HuAB4X+HxzagI2hJ4LfBu4JeRvhYCv8na/x1pnVLnGApcCBljjDGtmYUKl5ybgS= +h2RfQ9+lhaGYmv90U9DGKig9KjlmBipzfo2KmjFXB4w2AU4B3oGW050b6Wo0KL5PhQsgYY4ypx= mnAXGA6sDnwMhqzO8uAN2SvTwNeCGwRHL8u2ga/RskxB6OZnO8Dz0K71UBF0obA+onHa6OlsrOQ= nukZSIsU9vWM7Lj1sj42yG6DvKRZijVCxhhjTDXOQsXKxWgZ6lzg9uy1FagQ+S9UcHwA+HFw/EV= o+es84LjEMf+LxMzPRlqi44Ed0TLbm7N+VqIlsPzxncAeWdvjC+dbDBwZ9HUFKoJ+jWaj/jtr+z= Pg6jpvxqAwtBWgMcaY4eDSSy9tayfbokWL/B05BHhpzBhjjDFDiwshY4wxxgwtLoSMMcYYM7S4E= DLGGGPM0OJCyBhjjJk4YinyncBJ9G3iQsgYY4yZOGIp8p3ASfRtYh8hY0xX+bc33zj67XPn1/rQ= P+FLew1qcKcZJx/5/77R71valzDkIae9hmeEjDFd49/efKMLGjNIxNLlr0PRGV/MHh+ePd6bain= yf8raT0M5YKPAIspT6OeheI/lyJgxTKLP21wJ/Ag5Yq+dPV+WPh+7vqnAB4Fvo4T7PFttYHAhZI= zpCi6CzIBRTIo/Gi1FbYBS3j+FHKIBLgVeisJM8xT5D6Pk9xjbFO5fDpyR3d80cfxslCf2BpRkf= zgKWT2TxnLbxsB7kPP0ntkxJ2WvnYkcp2ej9PnvofT51PVth2JE9s8eDxwuhIwxHcdFkBlAUuny= q1B0Rh7IuglwC3AX1VLkHyjcXw38LrufOn4emrW5HxVbu6JCqZhEPx/N6qwEHgI+joqbEdLp86n= rW4l0TYcBPwTuLXuT+hEXQsaYjuIiyAwoZenyt6LiY43s+SeIJ79XZWrJ8U8DZkaOKSbRj6B8sZ= w/00i9T6XPp67vflQ8PYSW1Lavdym9jwshY0zHcBFkBpiydPnVwNeAfVHRAZqpqZIiD5p12Rota= W0DnA38R+L4HwOvRwXJVFSAbRT0+T1U1OyVjfXlwPlIf5RKn09d3y5oeWwpcEn2/EDhQsgY0xFc= BJkBZwWNpPhvoRmbuwuvfwMVDo9kj3+AtEIfRknvW6IU+dcg7c4lNHx/zkSFygHAT7LHlySOvwt= 4S/b8NagYekWhzx3R8tXBSEt0GyqUPpWd63wa6fOHovT596ICKHZ9q9AM11KkIbqq5vvW8/T7Nk= RjTA/Qqgjy9nnTKdrZPu/0eVOGZ4SMMePCM0HGmH7GhZAxpm1cBBlj+h0XQsaYtnARZIwZBFwIG= WNq4yLIGDMouBAyxtTCRZAxXcHp8ZOEQ1eNMZVxEWRMx5iHHJwfzh6fN4ljGWo8I2SMqYSLIGM6= xjTgbZM9CCM8I2SMaUm/FEHteMwYU4N5wH8CW6H8rtyteR5wKsoZuxI4l0Y46odQ+vu6yBF6JUq= VPxDFViwAvgscA9yOjAu3KTn2T8gQcToKXb0Mha5+MRvDIuA+lFN2CzJcPBs5Qr8D+C1j88K+n1= 3DBcCxwCEoAHZ/ZNo40HhGyBhTSr8UQcZ0mVjq+zNJJ72nUt5Bxc3PUWbYlagYKqbHlx1bN62+S= nr8nig49tPZ4+tRQfW1kvdjYPCMkDEmiYsgY/5JMfUdlCUGyvPKk95BM0VXo7iNeTSnvE9P9H0B= 8JzC44Ulx1ZJqz8S+Gn2/ErgXcCTwLUoxDXkUeBClE/2A+BlwNfRbNfA4xkhY0wUF0HGNJFKfU8= lvY8ST3lPUUyPTyXEpyhLq6+aHn8z8Hw0s7QhjfDYgceFkDFmDC6CjBlDKvU9lfQ+g3jKe7789S= TS/sDYRPpUQnx+bJ20+qrp8U+hQuoM4GdV35RBwIWQMaaJASuC3oV+mee3KZM7nDFU9Y5JtZsOv= A44uuL56rYvsh4S4+7dxrGDQCz1/T7SSe+plPcDsv6uQJqcrZEeqJge3+rYOmn1ddLjrwWeh4qp= ocE7LIwx/6RbRdBEpc9Hdo09De3G2R+JRx9v0UXo7dJpOt3/3sDFwDvRl2+n2xdZnB1zENKP9A1= On6/MmsBxwMcmeyATiWeEjDHAwM0E5awG/pDdWhVB3fZ26Ub/S9FMRLfaF1mCZiXM4PIK4DuTPY= iJxoWQMWZQi6AY2yDB6LbAF9BSwKbZa0Vvl4Oz5+ajpYSb0JfENmh3zRFod80LsuPuBG5AMz5kf= 34JWI5+YY9E+p+FdvnkS03XoeW7L2aPD88eHxy0A2k+voL8ZzYpPD81MZ5U+xipPqB1MWn6k/3Q= st50tNQ2VHj7vDGm9tJVH3MmMou7AvmznIz8WS5G3i4HI3Hpw2gXzu7Aa7L7S5GIdF+0RPRiZKy= Xe7fsi5bffo9mXY4H1kbajcsj/R+TjeegbGwHICO+fFniUuAepCEptpsJfCQ7/v7smAez14peMv= l4flHSPkasj1tK2pv+5xqGwDgxhWeEjDHDxELgNzT7s0xNtN0BOAttY74TFQjvQ4XFr7I2Re+WN= 2Z9Ff1m7kZ+Mw9F+r8g6y9nFTK12yF7vAkqQMJ289Hs0S9QQVXU68TGU9Y+RqwP02AfZDh4LSpS= JwuHtHYIF0LGmGGijj/L09C26JHC7SZUQOXEvFtSfjMxVgWPb0Vfbmtk53si0m4d4OnBcXmxEht= PWfsYKT8ao/dmIY3oiZ0n8NzzkJN1znnAjRN4/oHFhZAxZpDJze6ehfQPrfxZit4uy1CcwlwkdH= 4hWi5aj4asYFfGerek/GbC/kPvGFCh9jW0JPXnRLvlaJlr5+yaZqMMqUMS4ylrHyPWR2q8w8bzg= BXA39AS5mcn6LwOae0iLoSMMYPMO4FPIn3N39FMR1VvlxVIm/NfwLfQbMCZaInsPFRA/YCx3i3r= EvebCftfTLN3TM43UDzDI9njsN1y4E0okPPc7LrehzRMsfFMLWkfI9bHjkgrlY9jGJdkFiHxeO5= NNRvN0lwJ/AhpwNbO2oai+n3Q3/tc5P9zPfo7XoT+Ps+iUYzHxOrtCu33SPQ3Ffgg8G2kWZuduO= YdUKjrTkhofzmwWaLP2HWnNhP0FMMikDTG9BEd9BEyppM+QnsAL0EF8cZIZH808Bfg/SjZ/d2oO= Hol+uK/FWm/Ds+e+yZygd4Eidj/iDRr/4YK5q1QwXkSmhncFRXWd9AstP8YDU+naTSE9j9FxqG7= oKXcLSP9XY5mLC9Bgau3MzaRHrSTbHtUEN0JnAhsDnwgMcbwulPX0lN4RsgYY4ypz3waYasPobD= Vo9EEwwKaRfWL0Y7DW9Gy2jIkpr8rO/YeGrqtKmL1qkL70UR/K9EM02HAD4kXQdBIvF8OPIYKp0= PRJoDYGMPr7gvhvQshY4wxpj6psFVQAVIU1Y8Cfw0ep6gqVq8qtI/1VzWINTzHE2jJ+NmJMYbX3= RfCexdCxhhjTGtGkOh9Y7QLLxW2Oop0YkVR/Qyk68l3E87KblOQrmgWDRF6SqzejtA+1V/VINac= XGh/KFoOTI0xvO5Uu57ChZAxxhjTmlcCnwOORTMlvyMetgpapiqK6j+C9DJ3IOH0ZUg7c0LWZie= 023Bt0mL1doT2JPrbnOpBrADPR0to66PNB6kxhtedatdTWFhojOk5OiyWPh4JSKt4rlRpW6e/GN= PRbqFR4DNt9gH65X0M0pukdoAZHLo6DtYE/oFmeJ6a5LF0Dc8IGWMGnTrGc1XajtfI7qXA2Yw/4= uhAmrddG9NpZmV/PrO0VZ/jrDFjjJlY8gT4aePsZwmNwFhjOs004A/Z/T8ywAW3CyEzhksvvXS0= nSnh0RtKd0KYIWZk90n7EJ2Flo9uRwXINqgI+RAywFsXuUCvjLQF+aH8J9J3fBzpNGJtTkVblq9= Efi5/i4xlO+AMtKT1DRrBp/ORt8osNFN0beJawrGcT3Ma/NRsHIuQH81bkXblbCSGfQfyucm3So= fn/VZJ2yI7ZOM4F5ny3Yfe0xWJMTyStf8O8s85Cmlrim0c6tp7rGKAi58iXhozTbS7lm5Mj7IAm= d/lH+hnIqHpbPSF/D0aXilh29noC/4NSCh7OPDaoM3GwHuQcHXP7JiTIuPIE+NPRUtaW2bPFxPu= j6YhMg2JjSVcriimxn8YpcZvhzxd9g/6jZ1390TbkE+jrdf/QM7Gy1BRmRrDe4EjkSHfi1HxFrY= xZtLwjJD5Jy6CzAByAfCcwuOFaGalmD4/PdG2mCIP2goMzYGqRVM90EzN1ag4Gg3a5QnwIDfgdW= kk3J9VaDuHxmxRq7EUKZrXHYkE3StRJMSTaKbp91nb2Hmfjoq0sG3IbshJeTkS0F6CzAJfnxjDA= uDnxE328jZGjFeIP5EMjFjfM0IGcBFkBpqiKVyr9Pli21SKfLFNmalekVQCfCrhPqRKon0d47zY= eb+aaBuSMtl7KjGGvjTZmyRCIX6YON9LDIxY34WQcRFkBpnQeK4sfT5sm0qRL7YpM9UrkkqA35i= xCfdbRK6jyljqGOcti5z3VYm2KUKTvdQY+tJkrwfo9cT5JWjZs+9xITTkuAgyA85imo3nziedPh= +2vYuxKfKvCNrcS9pUr0gqMf5zjE24vztyfGwse9CcBl/HOG9F4rzjMdkjMYar6EOTvQhzqJ4gD= +XJ9J8FtgW+gJYhN2VsonyYON+qz2Lq+xz0b+IqNMP4Cqonxs+JXHvYV87jkbZ9R99PaZn2KSuC= vGvMdJK6u8acPt/T9J3JXocMFeskyJcl018OHIJE6dcDJyMt19NpTpSH5sT5Omn3z0X6qw9l95c= iTdYRtE6MD4n19SKkY3srml38euS4vsEzQkOKZ4KMMW0yFCZ7ERZTPUG+LJl+IfAbmgX7UxmbKB= 9SJ+0+F8M/imaANs3OUSUxPiTWV2zWqG/xrrEhxEWQMaZN+tJkr0NRGXUS5MtE9GWC/VCIXrXPU= JCei+G/UHguF6lfgGaRDk4cGxLra6DwjNCQ4SLIGDMOcpO9/DZM1EmQLxPRlwn2w0T5YuJ8nbT7= mBj+YKolxofE+toiMd6+xIXQEOEiyBhj2qZOgnyZiD4l2D+XsYnyxcT5sj7D1PcVjBXD/y/VEuN= DYn3djcw4i2L9vmXYKvqhpW4RZLG06SR9LpbupsndwJjSGdOveEZoCPBMkDHjYrxp82UMjCldgl= 42BDQGcCE08LgIMqanWcKAmNJF6HVDQGMA7xobaPqlCJrEZHIz+GxDc/L5vyOhaDF1/SQkPL0C+= bscjnQTL0dLVsW0+amMTWi/j7GJ67ckzp1njRUJTeliafZPRM4bS4aPJdTvFOnvb9n4TkH+MKch= 0ezr0fbsWD+jjE2sv590En3REHBBdu7xXJsxXcEzQgNKvxRBxnSZMPn8b4xNXT8SiU7PzI65FIl= Kv83YRPpYmnsscT127lgRFJJKs0+lyBeJJdRvneiP7LoWZ88dhXYl7Zbo55nEE+uXkE6iPw2Frc= 5ERc94rs2YruFCaABxEWTMP6liNLcZmgHaIWuzCZrRGWWsyd1KNMtxGIqXuJfmNPU6RnUxUqZ5s= fOGFBPq70bOwXMT/ZUZ+8X6eYj4e3dydu7lwGNoB9GhaEt5J6/NdIfpwOvQ30NV1kOzenu3atgv= uBAaMFwEGdNEymguTHu/FX1Rr5E990ThmKLJXSzNPZWm3sqoLkbKNO+ByHlDYgn17Rj7pZLuY+/= dDUGbYhJ9yHiuzXSHl6JlyToymYET+LsQGiBcBBkzhipGc1ugouBrKIPpz4XjQ9O4WJp7Kk29lV= FdrP+Uad7OkfOGxBLq70r0V2bsl0q6j713m2fnjiXRQzVDwCrXZrrDUrQMWoclDJjA34XQgOAiy= JgoVYzm8rT3b6Ci6JHC8YtpNrlbxdiE9lSaeiujOhhrSpcyzYudNySWUP/jRH+QNvbbJtLPfYn3= 7p6sr1gSPVQzBKxybb3ADshEcSfguyg8dbPstViCeyopHmTIeB0qSPPbKyJ9xFLfpyJh+rdRYT4= 7e77sfCHbAV/JrmOT4LVU0nyRmMA/du7UWHuKgZnaGma6UQRNpKFiZNfYh4ATI01vRf/hJtOEbj= raHTQKfCZ7rpuGe5NFeJ0Teo09Zqho0vRdEv04uA3Nku2ANFInohmxYxib4F6WFD8DLaNuh5YmP= 4uWmt5K6wT5F2Xn3B4Vz3uiHY1PlpwvZCYqdI5BS73notnMT5Wc88Ggj2LqfNm1vjgy1p7TgHlG= qM8Z0Jmgk7PbB2loEdYAPpa93sk16rqGb7E19fEa7nXbdK6d/sPr7KapoOlfhimJfrfsz5gwPBT= GlyXFP4YKkXXRbNiD6IdHFWH/HOLi8rLzhcxHs1G/AB5GxUxOO0nzZefuCyG8C6E+ZkCLINAsxP= 3Bc08Bn8vuL6Eza9TtGL61s6be6TFMRP+dvk4zeIRJ9INOmAxfFIaHwvgykfpTwCfQkuhNNGZaq= wr7Y4L9svOFrAM8PXgu3+mYOmcZZeeOjbXncCHUpwxwERRjBNgWeF7huXCNuki4xp1apy4avh0M= /Al9GE1D/3lH0fIQpNfUZ6Fp4nwr6dSs3zvRjpp5SD/w2ewavgBci35pxcYQG3+Va8zPHV5nnWt= MXWeVazTDx7Am0ceE4aEwviwpfgRpz45CwvNzUHFUVdgfE+yXnS9kOVoWy69jNjKyPKTknEWqCv= xHE2PtOews3ae0o+HpQ/4zu+VsWeGYoulbvsZ9LJpufhdap/5t1vY0VBzsgqaIb6YxE3U5jSnhm= Sh5urimnq+Z54Z7B2WPi+Z6+yJzvdnoQ+YK9OF3Mppmvzgyhtj4wzX6VJvNI9dZ9RrLrrPKNd6C= McPB85Eg/Erg/2XPFYXxx9EQhr8N/T+6GInPc6YhXU/O+9EPpmIfK2iI09cCPoDE789EP0aWoh8= jb0P/T8vOV2Q58CakA1oO/AR5ZS1FGp/YOYvkAn/Q0teNJedeFRlrz+FCyPQyH0TLMyPoS7cK+R= r3WYXnno5mRZ5EszG/Txz7QOH+auB32f3imjpoTT3fEnwB8JzCcUVzvSPRtPdCNGtSNK6bXmP8c= 2guhFJt7kJFUNl1pq6x7DqrXOOgMF5R+HiOdxJ9f/AZNONR5JWRdt/KbiFro5nhI7LHawIHoCIi= 7CfWx23Zny+peL4YX8huMVr1c2l2q3JMaqw9hZfGTD8wir4cfl2hbWyN+6u0v049lfI1dWjWDsT= M9VLGdTGqrNHX0Q5UIb+WsutsdY2DwnhF4eM5fuCM6gaMTgnDF6BZpfXRZETu3/RA2UGme3hGyP= QiU9DSy1roS2EU/VvdAc1QfJPmNeoiy9DU7B3I5O5f0JLR/ehX9lponfr2rH1u+PZw9ngl8jx5A= E1VH4bykY5BnirL0FLXychb5YpgLEVzvQOy8xWN6x5BH3rTC9dWHENs/A/R8LpJXeND2Xs2JXKd= Va7xfjRN/l+J62x1jWb8LKGhHTO9RSgMH0+x+g3gBPQ5BvAltCN2mHSfPYVnhEwv8kEkIPwPNJs= yinZoXIsMu0ITuiIriBvmpQzbioZvZMeej77gf5I9vojGmvq5aHkrX1NfTLPhXsxc7wrixnUHRM= aQGn+Va0wZ01W5xu/QrB0oXuf6Fa5xR3qTOiZ4O9EsCi8Tuc9DX2DLkZ5jhLGi8tS5y8Tm4SaAq= sL/Mr6P/g/lyzmHZI/3q3CsEZ0Uht8HvB2JiLdDs6oPjbNPMw48BWs6RgcNFc2Q00FDxTomeMeg= X+YHIX3U5aho2B+4Hs2OrUTFy7lID7Q2KhD3R6Lx4vGpc38AFZYnIbH5rsjJGZqN6mLmdsdmfdQ= xqJuRjesTqOBbH+3wuQzPQhjjpTFjzECzG9oJsxxtUb4E+BnK0loA/JyGgV0oCk+J3Ivp7KBCJn= Z82bmriM3HI/wv8iia+ToMFUIvQ4WWi6DeY1Id3YcVL40ZYwaZOiZ4Yfu66ezh8alzP5tqYvNOC= v9vRgLdTZHe68/lzU0H6AVH92671g8ELoSMMcNAFRO80Ciubjp7eHzq3Km0+vD4mLndq2jPoO4p= VHydgWalTHfpBUf3brvWDwwuhIwxw0AsHT1Mh19Msyi8bjp7eHzq3CmxebgJYAX1hP+tuBa5s3+= /xjGmmV50dE+J+qu61vdFQnw3sUjVdIwOiqUHwViu1dr+IFxj1+igWHoy09F7LZl9TbTD7WOtGp= ooddLg70X2Frmj+7OQpmw6+jdxOtKmXUo6DX41zeL7rYiL7FOi/txio+haX2f8Q4NnhEwv0mvGc= u2ss7da2++1axxUJjMdvdeS2V+BbBJMe9RJgw+p6uheTIO/ANlX5BQd3d9Iw+x0IfAbmkX9RcPX= Tox/oFnjwdO2884BM4YNzl42mV/QS+gdY7l8nf2IVg1rsoTeucZBpZMmeP107pD9kCj7/yHfKNM= euXg9Fk2xEM2mfBYVK7dH2oS04+h+DiqQ3k1juauqc32nxz8weEbI9Cqhsdw85PvyIxQkujbV1r= bnIDPBuUjzcT1KU16EtjXnszKp9fcq6+ytjPlSfbcyz8uPHer1+3EwmenovZTMfg2aDfifSR5Hv= 1MnDR4aju45uaP7xugz42y0xFWWBp9ydC+K7FOi/pFgDHXHPzS4EDL9wMYo5uLN6FfLbLROvh1a= Z98f/ceP8XbgaLQOfiISEp6ICpbd0C6cDWlOVP9w9jyo6Po5Wse/kubk96PREtg5aO39TuDF6IP= mTBpfgKm+i8T63aDiNRpjus8KetPRPSXqP4BqrvWx8Y8An8/aDDw2VDT9wHw0S7Iye/xx4Gr0Ad= AqbX0x+oVzK/A39KtoKlpvB7in8Lhdk7vXot04KWO+Kn2PJ1He9B+hcZ7pD+qkwZ8VPP5sdouRS= oM/L3i8e+T+Ydmt2FfO1cHxdcb/msh4BhLPCJl+YASZ0OX8Gf1qeoDW5nKjwF+DxzGqJqqnkt/L= jPmq9N3pRHnT24TGecaYScL/CU0vEhrLfQ/N/nwJ+Wy8PHu8M/G09SIz0O6dmcjrZVZ2m4LWyWd= l59mKdKJ6q3T4Jyk35oultcfM8+okypv+JjfOmzbZAzFm2PGMkOlFQmO5e5FQ+RQ0jbsR8CnSa/= NFPoKKnDuAfVDQ5JuBE9C0807IKfgnpBPVW62zn0m5MV9sbf80qpnnVblGkyYUss+heqJ7WXJ9T= Lyfny+VWA9x4zwiY0qN3RjTYUa8fd7EaGf7vNPnTafooKFimDBfJ9E9lR7/LjR7dzQKVX0/8Fu0= 7FlmbpcyzrsmMqYXoVnP4tiNMV3AM0LGmEFmATKqy4XsMVO5PNE9NJTbLftzOfAYKpQORbN7uXj= /ISTePxotd5aZ26WM81JGd+HYjTFdwBohY0zPEZnZaZcwYT5lKncDYw3lUunxEBfvQ7m5Xco4r8= zoLhThG2M6jGeEjDGDTJgw306ie5ge/z1UuOyV9ZGL90cpN7dLGedtHBnTFpGxG2O6gAshY8wgE= ybMr6B+onuYHp8S70O5uV3KOO9ziTGFYzfGdAGLpU2UPhJLt0p57wQ2vxtOei093hjTBTwjZPqd= VinvncDmd8NJr6XHG2O6gAshY1qTm9+Z4SFMjzfGDCht/8JtZ+nEmIpMBU5Fy1H3oV08t6FZmRc= igelvUXbYMWiHz9Ls2H2Qd8vLC/1tjYr+U5A+4zQkRH092gIdO98tSEB7BtJ8fAN4sNDnvOyYTZ= BXzblIZxKO8V7izAfegmYdzkbaldT4Yu9PeJ7bs3FOR94zl6EMtEsT5zfl5OnxxpgBxzNCpheJp= bXHUtgX0JzyPgMZ2h2Hdu58DRUsv8jaLUY7dY5CO39yn5jY+WYiV+pTkcfMloXxbQy8BzlD75n1= eVJijDFiSfPvLxlfSOw82xRevxwVcEYcjwrPfut/OvA69G9kIvtcD/2737uD5zWmZ3EhZHqRYlr= 7G9EMyErGmt5dgHbd5DyGdvysi37RP4g++KHc6C52vpS0Sbh/AAAgAElEQVT5HdlrMUO92BhjxA= z0zikZX0jsPA8UXl8N/C5x7DDSbR1Zlf7nUV9r1A1tWpU+D0T/Pj0jZoYCF0KmF4mltadS2Iumd= 08Bn0AzNTfRvJuszOgudr6U+R3oCyJmqPdAYowhsaT5G0vGF1I1kT5VSJmJZRrwtjaO64Y2rUqf= S9CWf2OGAhdCphcpprU/C6Wu78JY07swwX0ELS8dhczpzqGx7bnM6C52vpT53SGkDfV2jowxRsz= Ub9uS8YXE3gvQTNHWaOluG/TLf9/EGIaFWWi2L1/maRWKujWySPg+sB/6+/4Tsk6YhgrQUaQni/= UPYwNUT0ezLA8h/6Gy/iAdzBrrOxUYG1KnT4DHE/0YM3B0qhD6EPrPHN5uyV6vs+bcjXVx01/E0= to3Z6zp3WKaU95BXy5P0vg3+D7077zM6C52vqnEze+WkjbUq5oUv4KxBnpvLxlfSOo8Z2bXeQDw= k+zxdxJjGBZCHVmZVmwW+jt5P9J+7YWWWcv0V2H/Mf3XucDPke7syhb9lWnTYn3vTmtdWt0+bd5= ohopOrT2fjHaubERj2nUK+tUMjTXngyr0la9hv7NDY2vFPKTTeHiCzmdacw/6cM4p3n9J4f5ns1= vODPQr/4js8ZqoKNgA/Vs8rNA2zHWKne9HkXY538puRW6LjDFFePxVLcZX5Tzh+2G05PmcwuOF6= P98UYuV68h2RUnwd2WPf5C9Vqa/CvvP9V9nFZ6bE4yprL+iNg2kTVu3pO88MPZJNLv1e8ZSt89w= vMYMNJ2aERpFuoUiTyHreKi35jyRni3trt2b3mQBikNYHxX5+fLSA2UHmYGnqCMr04rVETMX9Vf= F/mP6r5tq9FemTYv1/VVa68Xq9lllvMYMDN3SCI2gNfjnFZ5rteacWsOeh6aTf4T8VdYOXvsS0n= Mcl503tt6d0gWEa/ckjg/ZAfm07JSN93Jgs8K5LkSzEj9Av67CPsuOn5qN606UiD0v0ucLIm2Mv= H5mAd9E/16ORu+tY2SGl1BHVqYV+zlaNvs/SCe2RaGflP4q7D+m/9oCzdisW6G/Mm1aO4GxtNHn= FsE1GTPQtJ01FjFUXERjBihnS6R5AAkKl9G8DTlnJioUjkEzS+ciseJXUdrz0cBf0Nr9b9HOntl= Zu+NRcXQJcCyaFfgQWvteCrwIbW8+BK2jX4+W8lZmfd+BRIYPZ8ccGTm+aKQHWprYHhU0dwInIg= 3LMahoeyUqTm5N9PkXVJTFjt8K6V5OQh+Mu6KCsthnrM1bIu/rhDJJWWPGlHEk+hEB+r98MppBA= c2EXJbdPwi4Gn2GHAv8L7IzGAE+nfVzPBJSP45mWD6HLBeK/f8I2AN93q0FfAB9tr0T/SB6I/o/= n+rvb9n43oQKmJ+g2c0L0edG2Pdv0I+nc7J+38bYzytq9jmDxmf5S+l+hI0xk0qnC6F/RctaI9n= 9v1KtEDowa59vXV6Ifj09jH4tnZE9Pxd9WG2OCpvpKKG52E8oUJ2PBJErsuMfzsY6HX3AFQuh1P= HhVPEz0AdIHsa4CfAzVNCtRr8sd0W7Q2J97oVmL2LHP5X1/0r0YflT9AFW7JNImxOYZFwImQGj+= DlhjBlQurU0NoqKnl+3apiRWsNO+bWAxj4zOCa13l2mC6hyfMiq4PETqNB6Cl373wuvxfq8oeT4= mKdN2GesjTGmc+TLZutjY0FjBppOFUJT0I6xtWh8aKwBvBhtQw3X0UNSa9gzifu1jAI/RllM29N= wAv4d8fXuMl1Ace0+tV6eIh/voWiZjayv9WjsyIv1uXnJ8TFPm7DPWBtjTOc4AFkYvA9tLTfGDC= idKoQ+iNao/wPNvoyiWY5r0Zr5a2j4vcQyeZYT92y5lLhfC2iL61uQ98s1qBj6IWP9We6m3EPmC= jT1vTVxf5e7S677+dk51wc+mT13ERJi534csT7vKTk+5mlzVdBnrE3uozMohEL4mIg8ZSYXa2tM= Ha6mMYPr4FpjBphOaoSGiTWBf9DQ+Ez08T1JBzVCMSH8CcgArygQvxzNCF6CZh5vR2aHPSkmN8Y= Y03t0MsxvmJiV/flMGuLliTx+0JmHZsFyb6pdsz9/iXbp5ALxlcC7GGsmVwxRzdsa0w2mI1H1KN= oBBirgizl3xpgexllj9ZkG/CG7/8dJOH4YiAnh6wSxWkxu2qVuSnwszX28afftJNUbY9rEhVB9V= tG8A2yijx8GYkL4fakWxAoWk5v2aMdpvtNO+Ha7N2aCcSFkepGYEP46qgWxQlpM/nk0W2SGi6qJ= 7XVS4lNO+GEafcopPuZ0HxtDbPzGmA7SKY3Qemj7+zL0pdSvtFrbH5Tr7Af+N7sV2T1xPwwfTYW= 2ehv08FFMV8+d3Y9Fie3vQiL732ZtT0PFR26wejMNndrlNMJI8zT3ohN+7uacp9HnAdObot2u/4= pmNV+FCq9D0I7Vo5Db9W7IQiMcQ2z8Mbd7Y0ybdGpGKE+X75WlnnbX2Fut7ffadRpjysnT1R9Fs= zKb0khsPwzZV9ybODaVEl9Mc3+YZrf8C5D1R05RuP9GNEO0EEVj3IysQu6mOcS11fidDm9MB+lU= IbSE6uny3aaba+xL6J3rNMa0pt3E9hRTKU9zh2bn+Zhwv6rTPTgd3piu00mNUJgun0qNT63P58x= BBodzkRHi9cjdeREy1yvOyMTW36uusYeJ7jvRem0/dp1V9QfGmImnbmJ7lZT4dUinuYcu+jHhfp= nTfTiGum73xpiadEssvTHwHmRqtyf6oDgpe207tD6/P/rPH/J2lDa/OUplvzb78wdoHf1V6EMEm= tffP5y9dhoKKJ2JCrHiGvvRNNyZ34s8Zu5EUSBz0dr+SEnfIbG+d29xfcaYiWMFcbf4mMgemp3m= yY49H7nQ/yR7fBFxJ/ylwGIaLvo7EhfuX0Ha6T4cQ2z892DhvzEdo5PO0sV0+UNJp8Y/C83EfJl= mE7x/jgl94LwcuA/ljL0YFVagXUTH01jXj6WwV0mUv5mxie5nALfQWPOP9V28zljfB6Kt36nrG1= icPm+MMabf6NaMUFlqfMoEL2cU+GvwOEUV47zUGnuY6A6t1/ar9D0e/YExxhhjJpBOFULhuvj3S= KfGp0zwcmYgL47cWXhWdpuCdEazKF9/h2pr7GGie5W1/bBNXf2BMcYYY3qIThVCYbr8vaRT41eR= Xp8H+XNshZa39gEuy/o+AWlwdkLOw2uTNs6rkigfpsQvpvXa/mnBdab6Lrs+Y4wxxvQITp83HcM= aIWOMMf2GIzZML7MdmiH8KRKfvxTYb4LOvR5wKg07BWOMMQNIpyI2jOn0zM7L0fbkk1FBMgVFaZ= yIdg52m9xF/KBWDSeIecjq4eHJHogxxgwSLoRMLzID+BjSY11XeP7rqCAaoXw3YSdYQiMIc7LJ3= dKPmOyBGGPMoOGlMdOL7IQcxr8Tee0aVASVJYNXdSffAYnxd0Ip4pcDmxXO1cpFPGQe8KXsHMfR= MOeMuayXJZCHhG7pqUTzolP6nMR4Y8faDd0YM7R0oxCaDrwOOS3nHI8+lKu0BXgB2tW11pgj0qT= OMVnUvWbTYENkqvlYSZttCvcvp2HeCdXdyT+Niqh/IC3QMlSoxEg5lOfMRrsk34BMOA9Hwb8pl/= Uz0U7F2SiB/HvZ2GKEbukx1/PQKf1vifHGjm3l9m6MMQNLNwqhl6I8nuKyWyrVPdYW9AV2AmMND= 4uECfOtkuMnmrrXbBr8Gc3MrFnSJpUMDiowfgbcigqCZcjI8y40q3IPmgXJC4/lqOi6BLmiT4mc= r1UK+Dw0+3I/slDYNTvXfDQjszJ7/HFUmNRJIA+JJZovQGnov2ox3tixK6mWxm6MMQNHNwqhpei= X8XjafhV4pOS4bibMd5s678+wcjsqTHaNvPYCxiZ/5+SFRFV38lXB4yeQN9RTkbatUsCfRsMEtE= jKZX2U6gnkITHX89ApPTXe2LGt3N6NMWZg6WQhtB3wFaS12KTw/CyaU93L2qYS30PtRaiZiJ2jj= l6jTCPxDrRbKeQ69OXzxezx4dnjPWpeM8S1HLFx5u/RoOs57keF7keQO/kMVPy+DOW/5dqdWDL4= vtRzJ4dGivihwMXZc1VcxIsp4D9GGXPbo7+j+WgJKuWyPoPyBPKQolt6zPU8dEpPjTd2bCu3d2O= MGVwePG270XZuQTcz0Rf8HLRctQQVHwDHoC+ufSq03QotHTwdFTjnoC/6L6MvjS3QUsJM5DydL4= 2F50gdszHwTbRMMBO5XZ+ONBXHoS+Fg6hWXEwDPolmKEBfsvPRF1mda35uNoa1s9dXZH3GxkmbY= +1HRpBm5X/Qe/JlVGQWORLpfo5Dy2HHoffxQlSUjqK/g/z+iajQyR+vm/15LPIqejcqUEDC6rxd= rvXaAxXANxPfVr8/+nu+LhjrHujv8w5UIE9HIu28/4WF+wcm3o93Zv1ujZaOb0AzOztm92/Ijv8= yDZ1PbLyxYxehwvsmpJuyTsgYMzR0yln6QCS+zKfaF6IvmTxW4wwaqe6t2oaJ7zehL46LgiEUE+= bDc7w6ccyhaObgjOzxXOBqtGvoQuonxu+MireLkabld2h5pc41xxLs34Vm68Jxbo5+xbczVjOWN= ZFQeg3iy2HGGGMGnE4tja3DWN1GUfi5qmLbmH4hpb0IKZ6jrl7jAdrTSNyKZgvWyPp+ovBa1WuO= aTl+mRgnWM/RSWZlfz6ztJUxxpiBpVOF0HK0HJRrLWYjbc0hjNValLWN6RdS2ouiZiI8R129xs6= 0p5FYDXwN6VL+XHi+zjXHtBy/TYxzFOs5OsU04A/Z/T9O5kCMMcZMHp0shN6EIhHORbMX70Nf1o= tpTnUvaxtLfF8XeEv23DWosLmP5oT58Bx3JY65F2mPTgFuQ8XRp9DsTSox/nRUfKT4BtIhFXe51= bnmFYxNsL8pMU5ajNVUZxXNs3DGGGOGEKfPG2OMMWZoccSG6XcmwlG8l9zA10MhtEVrhv2QeaL/= PxtjTE38wWn6nYlwFO8lN/ADaWSl5ayDNhesnpQRGWNMH9MLH+zG9Dq5G/i0yR4I8qAKw1kvm4R= xGGPMQOAZIdOLVE1Ijzl470PD9Tu/zaE87T3laF7HAb2O43foJF4niR4aztpE3oOyvqqm0RtjzN= AwKIXQi5DBYDv0kv7DiKoJ6QvQjrt8mWgGSqI/DtkXfA19sf+C8rT32PlmooiPU9Fy1JZtjC9GL= MX+/SVja0X4HqSuM3beVBq9McYMDYNQCI0gE8aD2zy+l/QfRlRNSL8A2RDkPIZmPNZF2+MfRIUu= lKe9x843H80s/QK5l3+9jfHFiKXCn1MytlaE70HqOuuk0RtjzNAwCIXQKCpm2sVp8L1HnYT0ooP= 3U8AnkIfTTSiiJRdSryad9h47X10H9KqO3zEn8RtLxlaF4nuQus46afTGGDM0dKoQ2gEJNndCeo= rLUfYWSLNwIXAEMkycQ1yrUKbtKB7/AsZqGv6R9TEf/RK+GH3AQ339Bwx38nsvUDUhPXTwHkHLQ= kchp+5zaGSIPYN02nvsfHUd0Ks6fsecxLctGVtI7Jo3LLRPXWedNHpjjBkaOlUIfRr9Gv4HEm0u= QwUEwHtRgOqdKDn9b4zVKmxGWtsRHv84aU3DH4E9gZ+gLy2or//YGHgPmlXYE30BnpS9VlUHYsZ= HzGF8c8Y6ai+m2cEb9CX/JI1i+n3o3/n5qDj4NQrf/W/0b+uAxPmmUs8BPTa+GCsY6yT+9pKxhb= ymcM3zC+/Bxai4SV3n3Mh5705cy15oKbDMUd0YYwaCTjlLPwP4C40U702An6GCYzXwc/TL80/E0= 9Z3Q7++P4Q+jD+CtgnfgH7VFo/Pz1dMqD8F6UPyMc1C6fTPzs4ftv8m6TT4VEK9k997nxmoOLg2= e7wmKiZuRktXpjrTgYPQzjNjjBlYOjUjtCp4/AT65fsU+lX+98JrMa3Cd0lrO8Ljq2ga1kBC2dW= J9mX6j1RCPTj5vddZADwfLRutQWNZ6IHJHFQfsg7wEpxjZ4wZAjotls71FIeiqXrQTMt6NHZlpb= QKi4lrO8LjY5qG1ejL7gXZ46OAj5a0L9N/pBLqnfze+3wDzQZ+E+m7jkZLrm3Neg4xf0F6vccme= yDGGNNtOl0IPR9tHV4f+GT23EVIp5P7lqxgrFbhHtLajvD4mKZhLtLtfBB9Gd6HdEsk2pfpP1IJ= 9RBPft8Q6yl6hfuQ3ma77PZuNHtnjDHGROmURmhNJJTONUJ16Xdth/UU3WM6sAgVx5+Z5LEYY4w= ZMDo1IzQr+/OZbR7fz9oO6ym6iw0vjTHGdI1OFELTgD9k9//YZh/9rO2wnqK72PDSGGNM1+hEIb= SK5h1g7WBthwlJGV7GzDhD5iCN2FwkdL8eCfIXIaH8Wejfaspss25waRXTzxRboyW/7wP7IcE+y= CpiFP3QWJjdX1TzfTDGGNOCQYjYMINHyvAyFRwa8vbs9c2BE1EhcyIqUnZDppobkg4crRtcWsf0= s8gstGng/ci8cy+0SxJUXOVcTsPXqs77YIwxpgWdKoTWQ19ae3eov17kePQrvFtMB16HvtiGnVT= gaSo4NGQxMvS8FTmZL0Oi+7vQTOM9aDYoFThaN7h0QTbWX2XHVw0y3RW4Jmv/KCrUcor6uNXA7w= qPq74PxhhjWtCpQuhAGssN7TCP9oXWE8V5NEweu4FFwQ1Shpep4NCQUeCvweMYKXPOusGl7Zh+Q= v1/83lBVfV9MMYY04JOFUJL0PJAO0wD3tahcfQzFgU3SBlebkzcjDNkBlp2mpk9npXdpqAA3Vlo= h2IqcLRucGkV088YP0ezV/8naxNey0qkIdoYLZWdDexbMg5jjDE16aRG6PHgcUrMOQ/4EvqyOw6= JSg9ESxYHUy4SrSJKrZoQHxPKpo6dhZY6ikt/+6Dlm9HC7RWkRbYpYW5KFFxnfIPGcuKGl58jHh= wa8hFgK5Q3tw9wGYpvOQHN7O0E/BiF84ZmmztSP7i0iulnHgpb5IdI1P15VASH2XVnZmM5IBvrm= cB3iJuSxt4HY4wxLeiUoSKoUFiG9BzPReLRD2X3lwIvQr/uz0V6m7VRTMX+SIuxC9KDPAvpOaYj= k8bTkfbiUuBKFJ46D+k/tkJfcCehX8q7ImHp9lnfewK3I7fokDrHHgN8DJkmfh3NOPweFTGPouL= nLOBktOtnf7RT6WT0q/7ixPnORsXiMdk1n4tmET41zmsz/cki9O/+060aGmOM6Qzd0qPkYs6zCs= /NQVP8V9Fwi941cmyZSHQBWk6IiVLzZPmVwLtQXEdZQnydYy8AnlM49rHsOtZF3kkPoi+whahIK= 4psp5ecrygKBhVZ65a0r3ptpv/Il+CmZff7wUPLGGNMgbeiZQjQrM3CSJuFaJYj5A6ahaP50hho= J9WRhdduo+Fk/Vy0BLUH8DK0JALSeCxAM1GphPi6xxavD6RfuQgt47wF6U/Ca1mUjT91vtcC7yn= 0uRDtMhrvtZn+40AaS6yLWrQ1xhjTITo1IzSCxKXrZ4+XoeWgO5Bo9F+QBujHwFeRzuFnSKtxF5= rhWBctjUFDJPoA0gUdhmaRbiYtSj0ACU53QUXJ0uzxC9ESUkidY8PrG0Ei16NozlYrimwfQb/wp= 2ftY+dbjnQe12Tv2Wy0nHYf0m+1e22m/7ia9nddGmOMmWTyUMxRGl47e6Bln5uRtiZnfyQMvi5r= A/DO7PHW2eMjkeD0OFRwHIc0RV/JzvFlVGRsjoTEFyAx6g3ZWOYhkfanSRvN1Tn2yML17Yi+sC6= iWSj9PiTKzR8vLNw/MHG+HbN2uS7o/6IZs3Vqjm9DtKy2S+JajTHGGGM6xgyad8KtiZarNpyc4Q= ANjZIZPJ6PCu9ZrRoaY4wxE8HhaAlrfbRMtzGatZqspY110C6y6a0amr4kDyB2IWSMMaYn2Aj5y= izLbqfTMO8zptPkejEXQsYYY8wQkDKfjJl0xowt51DPmHNOpO+yBPoU3UySvw0ZOv4P2nCQm2/G= 3qt2xm6MMWaSceioydkK+DjKGzsYOAfZCZyORPNzkLvyZsBfULzEs9Duu52yPp5Fo/h4GvJfyou= PK7PX8raxvq/K2uyHduidjpZEU8zKzr8V0pB9mIZ1QtlYYueOCfxvQ0XfWshVOj8+9l7lS2lVx2= 6MMUNLJyM2xkunQ0f7IcjVxImlt8cS12fTMLZcRcPYElobcxbT4mN9n0M8gT7FRCTJ/zAby100f= LZi79XCmmM3xpihpZcKoU6GjjrItb+JpbfHEte/C3wCWQ7chNy3byzpNy8GwrT4WN83Ek+gTzGR= SfKjNIT5sfdqNfXGbowxQ0unCqEdkIfOTujL6XK0bJEzDy1H/Ag4DS0D5KRCR8Nw1hGqB5GGQa5= 1wkrLxmomhlh6eypxfTEytpyLZnGKBpep9PYwLT7W97bEE+hTOwO7mSS/DtqhOCs7/6zCWGLvVd= HYs8rYjTHGjJPb0K/U7dHSxNvRr1TQB/830ZT/TGQceHr22kxUAM1Bv6iXoKJnNjJN3BB9Kdyct= Y3pIV6cHbMWMm7Mi5xi1EWqTUjZWM3EkTKfDE06U8aWeYFf1ZiTSN9l5pgpjkUF9BlI6/a6wmup= scTOHZIay36J92ppG2M3xhgzDp6BPmjzvK1NkIh1CnAo+mLImYsEoSPog7lYaCxEXxCvRjt6Uuf= 6dzS78xFULF2Dvng2LrQrFkKpNiFlYzW9Ry8aW+YUc+aMMcb0KJ1aGlsVPH4CFRBPoSLi2YXX/k= xDn7EOmt0pMjUbV8yXJ6aHuB8VUA+hLcOxINIqbWgxVtN7LECuy7mxZb4E9EDZQRNAvhy1Pi6ij= TFmKFgTzQi9BC2NvQklsoOWof4C7IU0EItpJNDPRUXKztlxp2SP34h0QNujwmg+MjE8FO2wWSu7= /2mk+ZmPlhleS+NX+HIa3impNiFlYzW9R68aWzpJ3hhjhoy8EDoW7dx5N1q2yNkDaW/uQFt9i1E= QqdDRWDhrnSDSYpDrDok2McrGaowxxhgzhrwQmtKqoTHGGGNMr9ApjVCegWQDQ2Pa43i0fBvSru= P6esCpwN7jHJcxxpgWTKN5+7IxpjVVnc/3Rrq542r2vxh4HMVyGGOMMcb0DNNQNEjVGdQjqF8Ig= TLNXAgZY0wJvRSxYUyRmLN4yvV7DhLBzwXOB65HRpyLsuPPyo4vc0CPJdKP93wQT5YPnc9nIWF+= cRmrzHG9qvP548Hj2LF1XNeNMcYMMCmNhpl4Ys7i25B2/c7dpQ9CX+6nAB9FTuQz0Q7AjSh3QA8= T6ctcxqueryxZvmj4eQzNy1gpx/W6zudvLfSZOraq67oxxpg+wanz/U/MWbzM9XsE2TZslL22F/= COQttr0Bd8mQP6CPKuyoX/nThf0U8ov70ka1MshMjOlRctKcf1us7nxUIodWxV13VjjBlIBm1pz= Knzg0HMWbzM9XsU+GvhtZRov8wBPUyk78T56iTLF8eWclwfj/N56tgHqOa6bowxA8lEpM/HtBeh= bqJMpxC23QZ9YG8LfAG4loaDdCx1Pkyrh7H6k5hGI6XFKDt/bLzWYNTnx8DraXYWvwsVFbnr98u= RPmcUmXfOolE8zcpuU9Df2ywUd5GTO5kfClycPRcm0n+vA+crS5Z/MjsnqEjZsDDG5Wi5LB/nbD= TjNLNkTCFhn6nr2RnpkZYCl2RjNMYYU5M62ouYbmIv4jqFWNuraCRvr5W9fnhhLMUlh1hafUx/8= iaaNRplWozLS85f59pMOTFn8ZTr94U0lp72Kdw/ERU6+eN1STugpxLpx3O+tUknyxedz48sHLNj= 9nrKcb2q8/miQp+59i12bB3XdWOMMQnqaC9iuokDiOsUYm3nA/fSKHbClO9QexGm1aeS7c+gtZ5= iBM2ipc5f59rMxGMHdGOMMU1MRPp8qL2I6Sa+SlynEGt7I/BoxXHF0upTyfbFayjTYqwuOX+daz= MTjx3QjTHGNLFG6ya12BnpO8q0F8uy1+4Afgn8CwpTvR/pFNZCOoXbE23/gZa11gMeQVP501HRM= UpDe/EwsGt23PfRzMxa2fi+CnwH+BlasruLsXqK85GO6Ls0azGeUXL+OtdmJpZpwB+y+38kvdPK= GGOMqU1Z+nxKe1HUTZTpFMK2l9FYdlpYuH9g1r6ovYil1e/IWP1JTKOR0mK0On+VaxsBPo9mrIw= xxhjT51h7YYwxxpi+w+nzxkw8L0IzpGW8ADlYr9WinR3RjTFmknH6vBkGOuVYnmvJWv1fOYCGz5= AxxhhjzKRRNy2+FevgHw3GGGOMKaFO+nyZ23esHxjrAF7mjn42jRnPgwv9tpvkns+izkei+otpC= OdjbuipflOO6FXfN7ueG2OMMT1I3fT5lNt3rJ+ZxB3Al5N2R4dmo87xJrnnhdA2Wdv/BD6ZvRZz= Q0/1G6bW133fnDxvjDHG9CB10+dTbt8pF/GYA/iepN3RobkQGm+Se14I5cxCXlP55oXQDb2s3zN= oFEJ13zcnzxtjhp5BS583g0Hd9PmU23fKRTzmAH5D0Kbojh7S6ST3NYAH0XXE3NDvL+m36Ihe93= 0r69cYY4YCF0KmF6mbPl90+x5BppUbJPrZiHgq/ObZuWPJ9NCcFj/eJPfVqGh6AVqWOgr4aPZa0= Q39WdnruyT6DRPm675vqX6NMcYYM8nUSZ8vc/uO9ZP3VXQAL3NHh2bH8tRY6iS5vwiJum9Czub5= ElzMDX1Rot+YI3qd983J88YY0yFuo/GBfGHh+QsLz78gcWzREG494FSad8F02jAu1t/T0RfHZuP= sezrSphxd45jYNZuJx+7oxhhj2mZN9IvyXTR/kayJfllvUniuzJhuMc27YCaKF6LdQ+Nlb6S7OK= 7GMYuZnGs2zWyECqFZrRoaY4wZHDqVPv8E8BvgdzSLS58AfouEnyCNwtuI7+QBWELD/2Ui+XGH+= lkKnIKusypLmJxrNg2cTG+MMUPKRIulTyK5T/8AAAw6SURBVEe6jYeQR0rMEO7xwv3w9V0Yu+15= IWMN6CBuLJcyoAvN5soM+mJsB3wFaTM2CV4LjftiFK+5jqGe6QyraN5BZowxZkiY6ELoNODnaIv= vlcAC4EzSXz7h6yNoCSN3yz0b6ZM2Av4V+DDwKlQonIJ2Br0Smes9M9LfxsB7gDcjH5nZwElZm8= XZ46PQLqHdEmOcibxeTkVF3paF154L7A68BumGzqO1IHXTyPVsB/wKCWEtaDXGGGM6RKeWxkBbg= mNC0zWz12JcADynpM/w9ZuzP7cEXgu8Bc2mvBWZyR2JdvzMQ7Mw92ftd030Nx/N1KzMHn8cuBq5= 8s7Lzvd34G4aO21C5iOh9S+yx1+nsc16B+Cs7JYzB3nGpLgrcj0rkf7qSTQ79fvk0aZTTEe7tUa= Bz0zSGI5Hf/83TtL5jTFm4OnkjNBfie+6ahUwuarktdjrG6DZnnegIihmQJcy0gv7S5nNjRI36I= uxDtp1VmRqYRyhcd9NLfqra6hnRKfS4XNeimYcO/ljoS7n4SLIGGO6SicLoVuQCHp39Gv6magIe= CJoVzSmCw3hWj1eGy1bnQU8goz0jmCsAV3KSC/sL2WMN4O4QV9sCW85ynzKjfhmoyLtEOLGfVsE= x4djqmOoZ0Quwu8kufDdGGOMqcwBKPRxBZr5eDNjd1AVjelCQ7hFhcfzI6+fylix9BGMNaDbkbi= xXMyALmY2V2bQF2MhKlw+Bfzf7LrXKfRfNO4LCa+5jqHeoBITjJcJ2GPp8KFIvargvCh8fwfNVg= ithO/XZWP4Yvb48Oxx/u8vPL7smkJh/zbIl+sI4AeMtXuIvWfGGGOM6UNiCeyphPmcYihqLF1+L= 1onrc9EBdCcrK8lNAqhWJ9hQToNpcjn5qFTUPEzkjj+qpJrCpPlr8za7hQZN8TfM2OMMcb0KWEC= eyphPqdYCMXS5Q+gddL6gagYyVlIoxCK9fmSSB870yhmNkObBVLHz29xTWfQKIRG0GxPmeFj+J4= ZY4xpgUNXTS8SE4ynEuZjxETqX6W14LwTwvdbUYGzRtbmiZLjb2xxTUVh/yiN1PgYsffMGGNMC1= wImV4kJhhPJcznAvaiCD8mUs/9mMoE5+MVvoMKtq8B+6JdiDmx47ctuaZQRL9u1i61iy32nhljj= OkBuhEqug9wPRKXbt2irek/YoLxpZQL2GPp8EWRetWk9fEI33PWzo4LCY8vE+WHwv6vZPe/nBh7= 7D3bMdLOGGPMBLOYaqGiVX1gnotErGujL6ojxzE2Y4wxxpiu8y7KC6FpaAdNlUJoNyQiNcYYY4z= pCXZA0/w7oe3Hl9PsMv1WGoVQzO8k9IFJeaIUPXdGkYYjFZpa9FzZBy2HzEWGidcjfccipAs5i4= bWxKGnxhhjjKnFbagw2R6JTN+OtAo5xUIo5XdS3P5c5omyB5phAm2D/iYyoZuJdB2nM9Zz5aLs8= UGoUDoF+Gh2npnZuTcqOfeLae1BY4wxxpgh5Rmo0MhDVzcB/lJ4XCyE8vah30mxEEq1geZC6FCa= l8nmIqO60HNlBIVX5sXOXmg3UM41NBc34bk3pLUHjeku3RDdG2OMGXI6tX0+DEZ9AhUkT0XaVvE= 7qeqJkgpNhWbPlVEUClt8nMKhp73JgTQvYRpjjDHjptM+Qrn/yqHAxdlzVUJFodkHJtVmBM3qbI= yWrlKhqevQ7LkyA80O5Yn0s7LbFLRUNqvF+Bx6OvksAd472YMwxhhjYqyJZlmORUtQ70bFB1QLF= d2RZh+YVJuDaRZLTyEemhp6rlxYOGafwv0TUcGWP147ce5hCz3tBeYBX0Ji9uNQEdxKdF8mam8V= mGqMMca0TV4ITWnV0JgKzEZF7IZod9/NaDavleg+JWqvEphqjDHGtM1GqBAqC4Q0piqvRtYHIa1= E9ylRe9XAVGOMMUNGJzRC04A/ZPf/2IH+jHkaDT1Xijqi9qqBqcYYY4aMThRCq2j+gjFmvPwYeD= 0qZKYifc9GtBbdp0TtVQNTjTHGGGN6gv2RS/l1SBBfRXRfJmoPA09HgM+jmSVjjDGmr0iZ6z0df= dltVqOv49EXqzHGGGNM21RNj+8Ei4kn2r8Q7QoyxhhjjJkw6qTHd4pWifbGGGOMMaV0yln6dLRF= +SHk6QJpA7vQKG8btMNnW+ALwLUoRLXYPkyXB80IUaEdqGC6jubt03PQdv+30rzEFo6vrnHfO0h= vzd6Fsdu4X9Vi7KnX5iAdzFzkpn09EgAvysbuOApjjDFmAimGpqYM7GJGeXlS/H5o58/pwOFZP6= l0eWj2lClrNwMFwG6BdhddQyOV/hial9hi43shnUuj3zXrm2wM7wGeUzL2suu6CL1vB6H3+RTgo= 8hocCb6+8hDZo0xxhjTZYqFUMrALmaU9zTg3sKxi4DXZffL0uWLhVBZuyloK/X2KINsCbB7oe0Z= hX5SRn6dTqPfEhUtT28x9rLXRlCcSV7s7IVmo3KuoXqBZowxxgwlnQ5dLfYbM7CLGeWtBh5N9FO= WLl+13VPAJ4A3Z2P4KXBjoe2qYNzh+DqdRr8Bmr15B5qNKht72WujwF8Lr43WGIMxxhhj6GwhVE= yPTxnYxYzynodmWNZDX/wbZLcR0uny0Gyul2o3mvWzGDgqG885qDgie63YT2x8+9K5NPq1gTORf= ucRNNP0WMnYy65rBtI45YXbrOw2JTvPrMJ1GWOMMabLFNPjYayBXU5olHcZjeWzhYX7Bxb6CdPl= Q3O9VDtQsXMRzct070NF4JGF53ZMjK+ucd/pqFCKcSpjlwz3KRl72XVdGPSR3z8RuLjweHPg6yV= jMsYYY8wAM4PmXWtrAgtoiJaHgemoyDTGGGNMgW5phHqJBcDz0TLRGjSW3h6YzEFNIOsgofpVkz= 0QY4wxxkw8GwHvRbqlZWjpqlWyuTHGGGOMMcYYY4wxxhhjjBk4pkz2ADrMesAJSCD96x7oxxhjj= DFmwlhMPJV+svoxxhhjTA8zaDNCy9A1/Q74VQ/0Y4wxxpgeppPb51MJ79BeunpZf2Wvhan089HW= 8Zto9hMqEibOjwT91Emgjz2/DTJAPAL4QTbWuu+J0+aNMcaYHqUs4b0sQT31Wll/Za9Bcxjrc7P= +8kJiBc0u0BBPnJ8Z9LMV1RPoY89fiYq18bwnTps3xhhjOkynZoQeQ7Mu66IQ0wdpREHMR7MxK1= FI6cdRavtIyWtl/ZW9FrIDmil5FM3mbEpj5ihnXtbf/cDdwK7ZWIrchQqjVwNvRLM+K1EMyGHAD= 4F7s7ax5xcAv6CxzNbOe7IY+BlwK/A3tHx3fza2h4B7snEZY4wxpiKdKoTKEt7bSVdfXdJfqzT5= Ik9DBclI4XZTpE0rg8U6CfSx50cL11x23a1ec9q8McYY04OMoCWcmPh6NlrKyhPUF6Mipuy1sv5= avfbfwGuzx5uhANW5Wf8vRMtfRbZCs0XFxPmNgn4ORTNLa2X3P430P/PRMtVrgddlbWPPr4uW5f= J8s3bekxnAL5HeCFRs/TeNtPlb0AyYMcYYYyaYsoR3qJ+uXtZf2WupVPrrkPbnoMT4w8T5sJ86C= fQ7RJ7/StbXlwvt6r4nVdPm10YFlxPnjTHGmAmi0wnvZf05Tb4aTpw3xhhjWtApjVCnE97L+hv2= NPkqOHHeGGOMmUA6nfBe1p/T5I0xxhhjjDHGGGOMMcYYY4wxxhhjjOkP5gHPHIBzGGOMMcbUYhr= a0dTNImUizmGMMcYYA8RT3rdBMRPbAl8ArkV5X2fTMAA8mHg6e5XUeEinuLc6xwuonihvjDHGGJ= MklfJ+OSpE9kPxFKcDh2fH3EFjtiZMZ6+SGg/lKe6tzlEnUd4YY4wxJsmBNEdejCJDv6eh9PW8G= FlEI5OrWKSMoJmZWS36CzkUOKPweC4qmkYqnAPgGcC/oxmgjyB36mtQ2vvGLa/aGGOMMX1Np5yl= Uynvq4FHKxwfprNXSY2H8qT2VueokyhvjDHGmAGkU4XQMuANjE15fwaaZVkPFS15HMYI8CRKZSf= 7cz0UmVHWX8j3UMGUJ7W/HDgfFT20OMeuKM39+8Cz0HLYLsB2wFLgkuy8xhhjjDEtiaW8X0ZjaW= th4f6BwDuz9luTTmdvlRqft0uluJedo06i/AjweTSLZIwxxhhjjDHGGGOMMcYYY4wxxhhjjDHGG= GOMMcYYY4wxvcv/D7Dg1QveoGWZAAAAAElFTkSuQmCC" width=3D"578" height=3D"302" a= lt=3D"" style=3D"margin-right:9pt; margin-left:9pt; float:left; position:re= lative" />Fuente:= Cede=C3=B1o-Escob= ar & Vigueras-Moreno (2020).Aula invertida. El au= la invertida, tambi=C3=A9n denominada como flipped classroom posee una serie de atributos =C3=BAnico= s que la distinguen de la ense=C3=B1anza convencional. Seguidamente, se exp= one algunas de las m=C3=A1s relevantes de acuerdo con Sol=C3=B3rzano</s= pan>-Barber=C3=A1n (2021).</s= pan><= span style=3D"font-family:'Times New Roman'; font-weight:bold">Distribuci= =C3=B3n de contenido: = intervienen las herramientas como Geneally y Canvas que permiten al docente= subir y organizar materiales de estudio. Los v=C3=ADdeos educativos como Y= ouTube y plataformas espec=C3=ADficas de la instituci=C3=B3n educativa se u= tilizan para compartir v=C3=ADdeos pregrabados.<ol style=3D"marg= in:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left:= 17.3pt; margin-bottom:0pt; text-align:justify; line-height:115%; padding-le= ft:4pt; font-family:'Times New Roman'; font-size:12pt; font-weight:bold"><s= pan>Herramientas de colaboraci=C3=B3n: los foros y chats pueden discutir temas, realizar preguntas y colabor= ar en tareas fuera de clases, tambi=C3=A9n herramientas como Google Docs pe= rmite al estudiante trabajar juntos en tiempo real en proyectos y presentac= iones.</li><li class=3D"ListParagraph" style=3D"margin-left:17.3pt; = margin-bottom:0pt; text-align:justify; line-height:115%; padding-left:4pt; = font-family:'Times New Roman'; font-size:12pt; font-weight:bold">Curs= os en l=C3=ADnea: permite la crea= ci=C3=B3n y distribuci=C3=B3n de cuestionarios y tesis que los estudiantes = puedan completar, de modo que, analizan el progreso del estudiante y permit= e al docente ajustar su ense=C3=B1anza.</li><li class=3D"ListParagra= ph" style=3D"margin-left:17.3pt; text-align:justify; line-height:115%; padd= ing-left:4pt; font-family:'Times New Roman'; font-size:12pt; font-weight:bo= ld">Duraci=C3=B3n de contenido: los softwares de edici=C3=B3n de video como Adobe Premier o CapCut per= miten al docente crear v=C3=ADdeos de alta calidad y si se combina con pres= entaciones ser=C3=A1 visualmente atractiva y din=C3=A1mica. </li></ol>El aula invertida proporciona un entorno para que el estudiante= desarrolle habilidades del siglo XXI, al trasladar el aprendizaje te=C3=B3= rico a casa y dedicar tiempo en clase a actividades pr=C3=A1cticas y colabo= rativas, esta metodolog=C3=ADa despliega el pensamiento cr=C3=ADtico y la r= esoluci=C3=B3n de problemas con la simulaci=C3=B3n y los juegos de roles, m= ismos que permiten al estudiante experimentar diferentes escenarios y tomar= decisiones en ese momento, analiza, eval=C3=BAa y adopta sus estrategias e= n funci=C3=B3n de la retroalimentaci=C3=B3n recibida (Montenegro et<= span style=3D"font-family:'Times New Roman'"> al., 2024). La tabla 1 hace refere= ncia a los m=C3=A9todos de ense=C3=B1anza, t=C3=A1cticas, t=C3=A9cnicas y p= erspectivas que los profesores emplean para simplificar el proceso de apren= dizaje de sus alumnos. Se asemejan a las herramientas que un docente posee = para impartir conocimientos, destrezas y valores, aquellas son: = Tabla 1M=C3=A9todos de ense= =C3=B1anza<table style=3D"margin-bottom:0pt; padding:0pt; border= -collapse:collapse"><tr><td style=3D"width:214.6pt; border-top:0.75pt solid= #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-a= lign:top"> </s= pan></td><td style=3D"width:214.6pt; border-top:0.75pt solid #000000; b= order-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-si= ze:10pt">Caracter=C3=ADstica = </td></tr><tr><td style=3D"width:214.6pt; border-top:0.75pt soli= d #000000; padding:0pt 5.4pt; vertical-align:top">Aprendizaje cooperativo</td><td s= tyle=3D"width:214.6pt; border-top:0.75pt solid #000000; padding:0pt 5.4pt; = vertical-align:top"><s= pan style=3D"font-family:'Times New Roman'">=EF=83=98 </s= pan>Es un enfoque en que los = estudiantes trabajan juntos en grupos peque=C3=B1os para alcanzar objetivos= comunes y realizar tareas educativas.<s= pan style=3D"font-family:Wingdings">=EF=83=98 = ; Fomenta la independencia, y responsabilidad individual y grupal.= =EF=83=98= Interacci=C3=B3n cara a cara y fomenta l= a comunicaci=C3=B3n.</td></tr><tr><td style=3D"width:214.6pt; pa= dding:0pt 5.4pt; vertical-align:top">Clases o aula invertida</td><td style=3D"width= :214.6pt; padding:0pt 5.4pt; vertical-align:top"><s= pan style=3D"font-family:Wingdings">=EF=83=98 = ; Contenido te=C3=B3rico se estudian en casa.=EF=83=98&#= xa0; Estudio independiente.</td></tr><tr><td style=3D"wi= dth:214.6pt; padding:0pt 5.4pt; vertical-align:top">Aprendizaje basado en el pensamiento</sp= an></td><td style=3D"width:214.6pt; padding:0pt 5.4pt; vertical-align:t= op">=EF=83=98= El enfoque se centra en el pensamiento c= r=C3=ADtico y metacognici=C3=B3n a trav=C3=A9s de la reflexi=C3=B3n y an=C3= =A1lisis. </td></tr><tr><td style=3D"width:214.6pt; padding:0pt = 5.4pt; vertical-align:top">Pensamiento de dise=C3=B1o</td><td style=3D"width:214.6p= t; padding:0pt 5.4pt; vertical-align:top">=EF=83=98 = ; En= foque creativo para la resoluci=C3=B3n de problemas.=EF=83=98<s= pan style=3D"width:10.22pt; font:7pt 'Times New Roman'; display:inline-bloc= k"> Comprende las necesidades y experiencias de los usuarios.= = =EF=83=98 <sp= an style=3D"font-family:'Times New Roman'">Genera una amplia gama de posibl= es soluciones.</td></tr><tr><td style=3D"width:214.6pt; padding:= 0pt 5.4pt; vertical-align:top">Aprendizaje basado en proyecto</td><td style=3D"widt= h:214.6pt; padding:0pt 5.4pt; vertical-align:top"><= span style=3D"font-family:Wingdings">=EF=83=98 = 0; Su enfoque se basa en proyectos a largo plazo que involucra investigac= i=C3=B3n y creaci=C3=B3n de productos finales.</td></tr><tr><td = style=3D"width:214.6pt; border-bottom:0.75pt solid #000000; padding:0pt 5.4= pt; vertical-align:top">Gamificaci=C3=B3n</td><td style=3D"width:214.6pt; border-bo= ttom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:top">=EF=83=98</spa= n> Implica la implementaci=C3=B3n de componentes caracte= r=C3=ADsticos de los juegos en escenarios no recreativos, como la ense=C3= =B1anza, el marketing o el =C3=A1mbito empresarial. Su meta principal es in= crementar la motivaci=C3=B3n, el compromiso y la implicaci=C3=B3n de los in= dividuos en una actividad espec=C3=ADfica, convirtiendo labores frecuenteme= nte mon=C3=B3tonas o cotidianas en vivencias m=C3=A1s cautivadoras y retado= ras.</td></tr></table>Fuente: R= odr=C3=ADguez et = al. (2023).= El aula invertida en= la ense=C3=B1anza de la historia. El aula invertida, una t=C3=A9cnica pedag=C3=B3gica que ha cob= rado relevancia en a=C3=B1os recientes, propone un nuevo enfoque para la en= se=C3=B1anza de la historia. En este enfoque el aprendizaje convencional se= transforma, los alumnos adquieren el conocimiento te=C3=B3rico de manera i= ndependiente fuera del sal=C3=B3n de clases, mientras que el tiempo en clas= e se emplea en tareas m=C3=A1s pr=C3=A1cticas, de colaboraci=C3=B3n y de so= luci=C3=B3n de problemas, funciona de la siguiente manera (Tabla 2): Tabla 2=C2=BFC=C3=B3mo funciona el aula invertida e= n Historia?Etapa del aula invertida &#= xa0; Actividades dur= ante la clase<table style=3D"width:470.5pt; margin-bottom:0pt; p= adding:0pt; border-collapse:collapse"><tr style=3D"height:111.35pt"><td sty= le=3D"width:146pt; border-top:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:top">Pre= paraci=C3=B3n en casa </td><td style=3D"width:146.05pt; border-t= op:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:top"><= span style=3D"font-family:'Times New Roman'">-Los alumnos visualizan v=C3= =ADdeos, leen textos o llevan a cabo otras tareas para obtener los conocimi= entos fundamentales sobre un tema hist=C3=B3rico espec=C3=ADfico.</p= ></td><td style=3D"width:146.05pt; border-top:0.75pt solid #000000; padding= :0pt 5.4pt; vertical-align:top">-Es posible que empleen plataformas digitales, libros de texto= o cualquier otro medio que el profesor juzgue apropiado.</td></= tr><tr style=3D"height:112.1pt"><td style=3D"width:146pt; border-bottom:0.7= 5pt solid #000000; padding:0pt 5.4pt; vertical-align:top">Clase activa </td><td sty= le=3D"width:146.05pt; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt= ; vertical-align:top">-El profesor orienta a los alumnos en la implementaci=C3=B3n de los sabe= res obtenidos.</td><td style=3D"width:146.05pt; border-bottom:0.= 75pt solid #000000; padding:0pt 5.4pt; vertical-align:top">-Se llevan a cabo discusiones, recr= eaciones hist=C3=B3ricas, soluci=C3=B3n de problemas, trabajos en equipo y = otras tareas que promuevan el razonamiento cr=C3=ADtico y la creatividad.</= span></td></tr></table>Fuente: N=C3=BA=C3=B1ez-D=C3=ADaz (2021). Sugerencias para la implementaci=C3=B3n del aula invertid= a en historia. Como en= todas las materias los docentes aplican diferentes metodolog=C3=ADas para = una mejor comprensi=C3=B3n por parte de sus estudiantes, la materia de hist= oria no es la excepci=C3=B3n por lo cual es importante abordar los siguient= es pasos: <ul style=3D"margin:0pt; padding-left:0pt"><li class= =3D"ListParagraph" style=3D"margin-left:17.63pt; margin-bottom:0pt; text-al= ign:justify; line-height:115%; padding-left:3.67pt; font-family:serif; font= -size:12pt">Planificaci=C3=B3n adecuada: Es crucial organizar las actividades tanto en el interior como en e= l exterior del sal=C3=B3n de clases para garantizar una transici=C3=B3n sua= ve entre ambas etapas.</li><li class=3D"ListParagraph" style=3D"marg= in-left:17.63pt; margin-bottom:0pt; text-align:justify; line-height:115%; p= adding-left:3.67pt; font-family:serif; font-size:12pt">Variedad de recurso: <sp= an style=3D"font-family:'Times New Roman'">Emplear una mezcla de recursos a= udiovisuales, escritos, tareas pr=C3=A1cticas y herramientas digitales para= mantener la atenci=C3=B3n de los alumnos.</li><li class=3D"ListPara= graph" style=3D"margin-left:17.63pt; margin-bottom:0pt; text-align:justify;= line-height:115%; padding-left:3.67pt; font-family:serif; font-size:12pt">= Colaboraci= =C3=B3n con otros docentes: Colaborar con otros profesores para intercambiar recursos y vivencias= .</li><li class=3D"ListParagraph" style=3D"margin-left:17.63pt; marg= in-bottom:0pt; text-align:justify; line-height:115%; padding-left:3.67pt; f= ont-family:serif; font-size:12pt">Evaluaci=C3=B3n de manera constante: Efectuar evaluaciones formativas y su= mativas para reconocer los puntos fuertes y d=C3=A9biles de los alumnos y m= odificar la instrucci=C3=B3n de acuerdo con ello.</li></ul>Asignatura de historia. </sp= an>Esta asignatura busca prop= orcionar a los estudiantes una comprensi=C3=B3n profunda de los eventos, pr= ocesos y figuras clave que han dado forma al mundo. En el Ecuador la asigna= tura de historia est=C3=A1 dise=C3=B1ada para indagar la historia nacional = y mundial con un enfoque de desarrollo de habilidades anal=C3=ADticas, seg= =C3=BAn el Ministerio de Educaci=C3=B3n (2022) se presenta el curr=C3=ADculo general del cont= enido y los objetivos de esta asignatura (Figura 2). Figura 2Contenido tem=C3=A1tico<img src=3D"data:image/png;base64,= iVBORw0KGgoAAAANSUhEUgAAAkAAAAE0CAYAAADEwYx8AAAABHNCSVQICAgIfAhkiAAAAAlwSFl= zAAAOxAAADsQBlSsOGwAAIABJREFUeJzt3Xl4VOXd//H3BMLuEpA9BEXRUBWohQIC4tKqBZdiWy= qtG6LUrbZVbLFltWLFWh5t6w6iVAO/R9FWRWSpZRHLY8VqlCaAREEIRZaIEkIgmfP743smmQwzy= SSZyZnl87quuZKZOcv3HEjmk/u+z7lBRERERERERERERERERERERESSmc/rAqKUARzjOM4XXheS= Cnw+Xzug1Os6REREvJLoAUjBJ44UhEREJF0lcgDKcByn0usiUp1CkIiIpKMMrwuIoLnCT9NwHOc= A0NbrOkRERJpSIgagDKCD10WkE4UgERFJN4nWBZYBZDmOs8frQtKRusNERCRdJFoLUAuFH0918r= oAERGRppBIASgDyPK6iHTmOE4R6goTEZE0kEgBqAVwmtdFiFqBREQk9SVSADoO6OJ1EaIWIBERS= X2JFIC6Oo6zwOsihM5eFyAiIhJviRSAmntdgADu3be9LkJERCSeEikASWJoDnT3uggREZF4UgAS= ERGRtKMAJCIiImlHAUhERETSjgKQiIiIpB0FIBEREUk7CkAiIiKSdhSAREREJO0oAInAucC9Xhf= hsXPRORCRNKK7L0uqyAKuAi4B+gD/Bl4E/hcor2Pdle4jna1E50BE0ohagCQVZAN/A44FxgGnAr= 8CzgceB1p7V5qIiCQiBSBJdhnAA8CnwH1AMXAIKAR+CpwO3OJVcSIikpgUgCSZfB94D7gfyHRf+= xowFsgDnJDlDwALgTuxVqBe2DiX24BngUXAccC1wINB63UBZgP5wEyObkHqDPzefX+eu12Ak93l= L8Faoj4CHgqqtbZ1ASa4x3crcF7Q6yvdY3Ow1i2AR93nF4fUdrpb+7exQPgfYEbQMURzDk4EpgP= fA0YD/wSeAtoBV7o15gEdojiucPtrBlwPrMaC68PUnIA30nkQEUlJAxzxHPAdINfr/wxhHAN8SX= UQuNB9/RL3ed8I613hvn8K8Jz7/W+pDiVXAtuAJ4PWmQvcDLQEfhC0z5OwcXMzgW5YqLgN635rB= jzjLvcA9sF/AhaChrjbrW3dE4E/ucfZHbg95NhnA78Ieu0bwGWAL+R417k1TMTGRfVyX5vgvh/N= OXjcXWaGe97aA2+4z/u49SwAro7iuMLtrz2wFuiIhc333WOhjvMgIpKSFIASAIkbgI6l9gDUJ8J= 633XfD7RIzKf6wzZgDDUD0Bbgm+73rYC9WAsHQP+gGoIf3d33nwNGBW3rWapbaWpbtyPW0jOC8B= cnnIaFqbbu8zuxgBbKhwWes4Neuwp4Neh5NOdgDhb+Au4Brgt6/kusi7Gu44q0v2B/Bn7ofl/Xe= RARiQl1gUmy+BIYD3yAdbWsdF//1P3aM8J63YGtwA73+aEwy4S+9iBwOdAG6Ie1WATCRmdgKhY0= gh+B7R8M2VZl0Pe1rbsbuBG4CFiBDeAOthHrMhqJdUWVE/7qNgf4KuS1rUDXWo433GvhjiO4tck= Jel7XOQm3v+ZY99ZsrAszsK26zoOISEzoLyxJJi+4j2D/wS53HwMsA/xB77XGWjEepO5L4YMtAq= ZhLSmfYa1M29z39gLnYN05R9zXegH73fdqU9e6m4FfY2HuZaz1alvQ+vOAWUAF8Pc69hX8x80Jw= Po6lm+M+p6TLOAJYAnW3RX6h1hd50FEpNHSrgVowoQJ+Hy+qkdOTg5jx45l2bJlVcvs27ePWbNm= sXTpUs/qLCsrY9GiRdxxxx2e1ZAk/Fh3zBnYGJVsrNvqa9hYlk3YAF6wVpxO1Ow68mGtI52BFu5= rv8JaJvpi3VmLg5b/EAsgd2ODgDsAQ7EP+hbYOJhO7nZbuNvt7D6vbd0+WIjrgLWY7OfoP1DeBf= Zgoa6gjvNyMdZSlA38BBufFO05yMTG5gSOo5n7Xifsd0am+31nt8bajivc/gZjXZovA4exgNYW+= HqU50FEJKU0yRigw4cPO9OmTXMmTZrklJeXO19++aXz0ksvOS1atHD+9a9/OY7jOPPmzXNatGjh= LFmypClKCmvJkiXOiBEjnCuvvLJJ90vijgGqSyfgLqxrrBh4CetaCb4CawHWdbMC62YBu8opMGb= lafe1X1JzLMsubMxNQA/gEeyKp1nA8e7rTwetcw2wPOj5ZXWs2wfrbpuHXXU1JsJxXooNWq7Nci= z0/AMbvBw8/iaac/Bo0PMbQp7fhV1dFngeGJgd6bjC7a8T1pK32q3tJ9jVeu3rcR5ERFJGkw2Cf= uqpp5zp06fXeG3MmDHOM888U/V8+vTpngYgx3GcDz/8UAGo6WVil4Q3C3qtNXZV2LGeVFTTLViL= SW2WU3MQtIiIhEi7LrCAiooKHMehvLycVatWsWLFCvr161f1fsuWNS+wWbduHaNHj2bAgAHMnDm= T0tLSqvcKCwsZP348Q4YMYfHixbzwwgt06NABn8/HoUOHWLhwIT6fj+eff75qnTVr1nD55ZczbN= gwlixZErbGFi1ahH1d4mok1kVzItZt09L9vhIbiO2lrlgI21PLMu2w7qMTOPoSeRERSUBN2gJEy= CW7jz/+eI1lfve731W1AO3YscO54IILnE8//dTZt2+fM2HCBOeee+5xHMdx9uzZ44wcOdLZtGmT= 89VXXzm3336789RTTzm7du1yAKesrMyprKx0pk+f7jz33HOO4zjOZ5995txzzz3OgQMHnMLCQqd= nz57O559/flSdGzduVAtQ0zseuAN4E+tKew1rEfIyjY7ABnvPxG5aGEkrav6//kEty4qIpLWEag= FyHKfJHlOmTKGyspIDBw7w9ttvM2/ePObMmRN22dWrVzNs2DBycnI4/vjjueWWW5g7dy5+v5+33= nqLkSNHcsopp9C2bVsGDhyI4zh07Nix6ph8Ph/dunWr2t769euZOnUq7dq1Izc3l61bt1JYWBh2= 3019XoQvsAHQ52MDmi/B7uVz2MOaVmGDun+DDQqO5BA1L0MPvWJORERcaRmAADIy7NBbt27NoEG= DuPrqq3n++ecjBo/i4uKq77OysmjTpg2O4/DFF1/UWDb4WEJfP3z4MI7jUFlZSV5eHpWVlVWPoU= OHNmnQSbEA1I6jp7NIZg09nsBUHLXddDCRnItNkxFO4FhGRXi/No1ZV0TSREIFoKbg9/spLi6mr= KyMgwcPcvjwYT788EMWLVrEwIEDAQstu3btYu9eu4XJkCFDWLhwIcuWLePQoUP8/e9/58Ybb8Tn= 85Gbm8uzzz7Lpk2bOHjwIEVFRVX76tmzJ4WFhRQXF1NQUMDkyZN5/fXX6d+/P4899hj5+fkcOnS= I9evX11gvYN++fXzxxReUl9fnFjZp6WJsqoVEGKQcCw09ninY/XOSxUpgcoT3ptHwY2nMuiIiTW= 5ARUWFE+/HDTfcUGPsT/v27Z2zzz7bmT59urNnzx6noqLCmT9/ftX7//jHP5yKigpn2bJlzvnnn= +/06dPHmTlzpvPVV19VbfOxxx5zvvGNbzhTp051nnzySeeJJ55wKioqnDlz5jgDBw50Hn30UWfu= 3LnOo48+6uzfv79qexdccIFz9tlnOy+99NJRda5evbqqhhEjRsT9vAQeJO8YoNCpHI4HvuVRLcF= aY5eSj6/neqHHE63nSJ4WoLr8PxreitOYdUUkDSTSVSIDjhw58i+vi2isvLw8ysrKGD++vp93iS= EzM3Mk8AlQ6HUt9XQZNl5nAtayOQtrYVhcyzpN4SJsLqyp2N2PoxV8PPXxJDZw+5V6rpeInsbuy= t2Qf8PGrCsiaSChusC8Hv/S2Iff72f37t3s2bMHv9/veT1JOgaoA9b98x42gec52B2FHWzMCO57= DjA8wjbuxmZDf81dt671e2FjUW7DBjwvwu4D5AOux27Y9ynwMDZLOVgweQ+4FZvTKpKl2I0VG6O= 2OiItfy02eer/UH0zyLrOw4nAdOB72M0R/4ndRbsddvPF94A87N+orroC43AuAca5tTwUVMsxHD= 3O6Tjs32GTu27wvZjqOge1rSsichQFoBg+XnvtNSZOnMjkyZNZsGCB5/UkYQDKxKavWIvdyO8l7= MZ/PYG3g5Y7F/h3LduZid1J+BLsw7qu9e/BrrDqjHVXfQ+7708W1nX1PezeQCOwsHMicKb7/K/u= 96H6u++txu6SHGw48DfgLazLsS6R6ojkm1jr14Xu9vu7r9d1HiZh42f6YtNbjHJrvwubhHYEFkR= GRlFXYDzSOdhVbOdiXZID3PdHcfQ4p3uBz916l1Pzjtd1nYPa1hUROUpCzbGTAB/AjTJq1CgOHa= qe+DrZj8cDZ2GTab7hPp/nPsDuyRPwJfWbHPNAHetfhc0p9i+qJ/ME2IfNaRXwFjampxQLPWdhY= e2PIfvLcl+7EZtG4yFslnOwubnOBX7kfr8UGBj0fjiR6ojk/7AZ4MECTmBairrOw03Y74SPgI/d= 197BukQDc48Fb6+2uq5zt7UKCIzwX0/1fYwWYuc8ME7rDGyaj97Yv8FKLEAG1LavutYVETmKWoD= 0SKQWoK7UHgTi6VCE15tjLQ2zsbnFfFiNN2Lje1Zg9wwKNhxrhdiI3VfojaD3zsJanA5g46x6Aq= dFUV+4OqJxhPp1Bx0MeV4Zsi8n5HltdYXbVrDgc34KFrKCA2hpzcUj7iuadUVEakioFiBJe7uBI= dj0E6HX/jscHdjrc3fmhqyfhQ1cXgL8KWT9zVgXT09sVvPvUt2aciw1Zz8P3lcG9uG9sB6111ZH= fTX2PMarrlIsHLbDwmFobbXtq651RUSOohYgPRKpBeg9rNXg51hXybHYdA6Z2ADes7BujxHYeJ1= HsDEuPvd5Z6qDxxGgO9Zt0qqO9VtiM5SHhpbBbg0vY3eCPgFoC1yBXabeAWvF2E/NPybysRaiIe= 7+crD73fwAeB8b19TXresb2CDsYKHHE6mOr4es19pdp5O7jRZAx6Dn1HEeMoEuQcs3C9pehvt+J= /e15nXU1QK7k3ZwLYFjCtypuqv7vAXW1bYTG8CehXUPdscGSX+/jn3Vta6IyFESqgUoAT6AxVtl= 2JU+v8bGsfwd+xA7gv31/zj24T0N2IB1P63EBuUG7pnz/7DWmFexK5omYyGltvWfAS7HWhCOx65= 8Ahuz8hV2SfmDwBrg29iYnjL3tVzsSqvgO1nmAz/DumrysQHFv8PG+3wJzAD+ALQBHnD3Eyz0eC= ZEqOPlkPUewS6fvwwLCVdjY2wuxgYIv1HHeXgYC2k/wFrgzgJudrftx8LFRPf5HuD5Wup6HBvoP= Arr+grUMhIowcLV4+62Hsf+3X+MDUZf426vELvq7A33XEXa1/461hUROUpC3QfowIEDSX8foGTX= rl27ZL0PkIiISNTUAiQiIiJpRwFIRERE0o4CkIiIiKSdhLoKTERERKQpqAVIRERE0o4CkIiIiKQ= dBSARERFJOwpAIiIiknYUgERERCTtKACJiIhI2kmoy+A7duw43esaREREJPUlVAsQqBUoAfixSS= dFRERSViIFID9QqgDkuQpgh9dFiIiIxFMiBaD9QLECkHe6dOnyC6DU6zpERETiLZEC0E5gf5cuX= abv3LlzutfFpKkvgF1eFyEiIhJviRSAKrAQpG4wD3Tr1m0W7vn3uhYREZF4S6SrwPxACbC5W7du= j3ldTBragnVDfu51ISIiIvHm87qAEC2AM4ARQO8dO3bc7HE9aaF79+6/A14HNqEAJCIiaSDRAlB= zoAeQ6z56b9++XSEoTrKzs58B9gEfAG+g8CMiImki0QIQhAlBQNvPPvvsGk+rSjE9evR4Bgs/hc= CHwDpPCxIREWlCiRiAoGYIOhXoChwLtA0ssG3bNgWiKOXk5MwPeuoHvqQ6/GzC7vuj1h8REUkbi= RqAwEJQd6AL0J7qINQOG7zd9tIrroxZCHr1pYWLAQe7Cqo8Vtv1mJ+aV3VVYpe6bwcK0JgfERFJ= U4l0GXyoCmAr1jrRHWuxOB4LQb0Ap3OXbrHc37HYFBAlWEhIhWvxj1AdcPzYce3ErvZSq4+IiKS= tRA5AAcFBqDPWbVMK9D7vW9/h4MGDMdnJnEdnHwK2Af9xvx6IyYa9VUl1C1AFFniCQ5GIiEhaSo= YAFBA8R1VrICP39L5s37Y1Vts/iLWM7MZaSb6M1YY9VA584nURIiIiiSaZAtBRMjNbcNLJvWO1u= cBNALcCm7GuMBEREUlBiXQnaBEREZEmoQAkIiIiaUcBSERERNJOUo8BkoSTgf2f6ug4znavi0lW= Pp+vFXbbgkr3q4iIxJgCkMRCBtDccZxUuYGkpxzHORT43ufztUBBSEQk5tQFJo2V4ThOpcJPfDi= Ocxg4Af2siojElH6pSmM0dxyn0usiUp3jOLvc86yfVxGRGNEvVGmoDMdxjnhdRJpRS5CISIzol6= k0RAY2LYk0IcdxdqEQJCISE/pFKg3RyXGcYq+LSEduCDre6zpERJKdApDUl1p/vNcc/eyKiDSKf= olKfXUCTvW6iDR3KmoFEhFpFAUgqY/ATQ7/1+tC0pnjOGvQz66ISKPol6jUxylAB6+LEEAtQCIi= jaIAJPV1gtcFCKCfXRGRRtEvUZHkpCAqItIICkAiIiKSdhSAREREJO0oAIlIqmoHXAs8GMd9nAz= MBEY18boNEW5/5wL3xmFfTXHuRRpFAUhEEsEfASfo8SXwPvAXYBzQpgHbvBj4LXBsjGoMZxrwaw= /WjdX+VgKT47Cvpjj3Io3S3OsCRESAn2EfxouwGz1+irUiDMNaLb4P/AjYX49tvoj9kfetGNYZ6= hqgpQfrJvr+muLcizSKWoCaTjN0vkUicYAd7ve7gSNACfAq8D1gAHB7A7Z7KCbV1a7Uo3UTfX9N= ce5FGkwfyPHXDGgNZGNzaLVC513S2/eB94D7gcwolt8M/Am4DWjrvtYZ+D2QD8wDekWxHR9wPbA= aa2F6GDgmwrK1bf84bNzMJqx1qlk99lHbugEnAtOx4Dca+CfwFNYidiV27vKoeVPSSPXWtr9jqD= lOJ5rzU59zGIv1ROJGH8TxdwJwtvsYAXzTfS0TnX9JP8cATwNfB34FnBfleh9h89B1xbrubwf+B= xgErHe/DxcmgmUB47FgMRj7eQy3/7q2fy/wOdAfWI6Fkmj3Udu6AZOw8Tp9gQ+xQcs9gLuAD9xt= +oCRUdRb2/5GUXOcTjTnJ9pzGKqh64nEjcYAxV8z7Bf3IKAyv6jkjr69sr4N7AGK3a9+D+sTaUq= +Rq6XAZyBDeYNHdDbheputHD2AUODnr+Ftc6Gqm37WcClQG+sm24l8Nco93FGHesG3IT9bv4I+N= h97R3gE6DAff5vqqdDiVTviDr2txD73RMYpxPN+Yn2HIZq6HoicaMWiPjriDVDg3v33vyikuX5R= SX/BnLd1/TvIOniS6wl4AOsy2ZllOudgbVkfIZ190zFQlHwo7bwE9Aca3mYDYwlfCCrbfunYCHk= SNDyoeNqIu0jmnUDDoY8rwyp1Ql6HqneY6PYX+g4nWjOTzTLhNPQ9UTiQi1A4TUjurEJ0YgYbvK= LSla5rUGFWEvQYdQaJKnvBfcRrd7Y+J8/AGXAXuAc7Gc08OHeC7tCbG8t28kCngCWYGOKIv1s1r= b9UuAsbDzOgaB1WkSxj7rWbahI9WbUc3/RnJ9oz2Gs1hOJGwWgmgIDlnvGcJu1tvDkF5UsB+jbK= 2sE1UFIIUjSjQ/o7n7fHvgKGy80FPgdsAx41H3/Q6ACuBt4xH1tKHbPoNBtdnYfLbGxJ8cCL2OD= qU9wv34d61IKqG377wA73fcedNfv7n7fDAs5kfZR17ovuvvKxLrbOrnHkOEewyH3+0C3+mHsd3i= kel+pY3+LsDFVnbFQFM35ifYcNvTcizSZZG2CzAX65ReVLPS6kFhyQ9Bm7PLfRGwNygXOcBynPn= +9Sxz4fL6hwNte1xFDfwR+GvLaB8C7WKvBa0B50Hs9sMHCw933fwd8EbL+KHc9gL8BE7CA0BkLA= V2xLplbsDEqwWrb/unAb7BByg9iH+LvYYGiTR37qG3dQCvNo8DN7vc3Yq04gee/xFpT7naf34EN= eI5Ub237+zbwkrudee76dZ2fTlGew8ace5EmoQCUYPr2yhqLDY5OxNYgBaAEkYIBSESkSakLLMH= kF5UsgBpdYiXYAMhECkIiIiJJTQPRElR+UckqrNn6dHSlmIiISEzpQzWBpevl8hMmTMDn81U9cn= JyGDt2LMuWLaux3L59+5g1axZLly71qFJ49tlnGTx4MOeffz6vv/66Z3WIiEj9pMUHarILag3qR= hpMpfHII48wbdo0Jk2aRHl5ORs2bGDMmDFceumlvPvuu1XLvfLKK0ydOhXHcTyp88MPP6RPnz6s= Xr2aGTNmcOWVV7JlyxZPahERkfrRGKAkkU6Xy2dmZpKdnc2OHTto0aIFLVq0YPTo0Xz3u99lw4Y= NDBgwAIDrrruOrVu3elbnmWeeWfX98OHDue666/j44485+eSTPatJEkZr4MfYDQvnxmibN2N3h1= 7TyH3FozaRpJPSLQmpyG0NyiUNJlatqKjAcRzKy8tZtWoVK1asoF+/fjWWadmyZY3n69atY/To0= QwYMICZM2dSWmo3vi0sLGT8+PEMGTKExYsX88ILdiFbhw4d8Pl8HDp0iIULF+Lz+Xj++eertrdm= zRouv/xyhg0bxpIlS2qt1+fzceKJJ8bgyCUFnINNPhrLPzIf4+jw05B9xaM2kaSTsh+eqcwNQcE= Tq6ake++9l4yMDFq1asW5557LfffdR//+/SMuX1xczOTJk3nooYdYvnw527ZtY/bs2ezdu5c777= yTSZMmsXz5cpYtW8b+/fsBKCgoqFp/zJgxTJ8+ver59u3bWblyJXl5ecydO5ebb76Z3bt3h913S= UkJWVlZnHbaabE5eEl2S7F79iTivpqyNpGEpQCUpPKLShYEtQY1KcdxmuQxZcoUKisrOXDgAG+/= /Tbz5s1jzpw5EZdfvXo1w4YNIycnh+OPP55bbrmFuXPnsmbNGkaOHMkpp5xC27ZtGThwYNU6HTt= 2rDomn89Ht27dqt5bv349U6dOpV27duTm5rJ161YKCwvD7nvRokX8/Oc/b7JzIzF3GjAHG2v3JP= APbDqJHwP5wD1U3zdtMHZH43exmwy2DdpOf2zC0dXYzQmDDcduCvgW8B2gD/A0cC12l+jvYDckP= BObqHQJ1Xel74DdqPCiOvbVApiCdZOvdGuNpjaRtKMAlMT69sr6PXCi13XES0ZGBj6fjzZt2jB4= 8GCuvvrqGt1ToRzHYefOnVXP27dvT5s2bapae6J1+PBhAPx+P3l5efj9/qrHsGHDjlr+zTff5OK= LL+a444476j1JGr/GJmk9CfgFFj5+gQWTEcD3sW7nbsC9wM+xOynnYHdjBrtD8x+BXwGXYZOfBm= QD5wI/cvfzGHZH5HFYWPmm+/117javx250OcJd/wpgBtUhLNK+emLTaPQDHnbrrqs2kbSkAJSk+= vbKmodNl7Grqfcd79aNyspKiouLKSsro7S0lPLycvLz81m0aFGN1hu/38+uXbvYs2cPjuMwZMgQ= FixYwNKlSykrK2PFihXceOON5Obm8uyzz7Jx40ZKS0spKiqqcRw9e/akoKCAHTt2UFBQwOTJk1m= 8eDH9+vXjscce44MPPqCsrIx3332XLVu21Kh1zZo19O7dm27dunH48GHWrl2rFqDkdB2wAfg/bD= 6v97GfrcDUNJ9grSvDsRacre7rj2CBxue+txzYiE1D8UbQ9s/CWpEOYIGnJzZdxUbgY3eZK7HZ7= tdis8EXUT1x6VPu8gGR9rUZaykag00t0qKO5UXSlgbBJZmg4PM59stsT1PXEO8P4Jtvvpk5c+YA= 8MADD9C+fXtyc3O58MILue2226r2n5eXx8MPPwxAjx49GD58OIsWLeL+++/njjvu4KqrruL222+= ndevWXH/99Vx11VWMGjWK7OzsGkFiypQp3HTTTYwbN44zzjiDKVOmcM4559C2bVumTJnCxIkTKS= srY+LEiZx11llV673++utcdtllNWp/+umnGTJkSFzPj8SFg03AGvw8HB82j1XAPiysgE322TJk+= UAAyQDGYl1bwQ4Gfe+n5qztoQ4FfR9pX9lYy9JTwG+B0VHUJpKWNBdYEnHDTzFQgAWfz4EtwJdN= VEIucMaRI0eSei6wvLw8ysrKGD9+vNelNFhmZqbmAoutdtgkoZdjP19XAoOAidjVln/HJu7cg12= K/n1sLM2VwPHAQ9j4oeXAd7EWpJ8CdwK3Af8C5rvfb8Lu8F6BjQkahLU2HQN8CgzEWpx+hl2yfr= 9b42xgPfBcLfvKw4Lc/cClWDfdDXXUltQ/zyINpRagJOAGn0rsl2QB1oS+maYLPjUkcxeM4zjs3= r2bQ4cO4ff78fmS9W8AibE/Ar2B/2CDkRe4r2/DZlAfhIWPdliryt1Y6JmPjbUBGyz9Myyo5AMf= Yt1WS7Gf1RnAH7AZ4x/Axvz0xMYD/cStoT32R81YbJZ3sK65Dti4I7Cf/3cj7OvvwJ+wVqonsHs= HDahlee9uoy7isWT97Z82LUBBrT573K+badpWn2C5wBnl5eVJ+xfja6+9xve+9z0AnnnmGcaOHe= txRQ3TsmVLtQCJiDSCWoASWEiXl6etPqnikksuoby83OsyRETEYwpACShooHMx1cHHq1afoyRzF= 5iIiAgoACWcZGj1UQASEZFkl9QBqG+vrIexG3wljfyikmvCvR7m8vaEDD+gACQiIskvmQNQBVCG= XSaaDDd0bE6EOhPg8vZ6UQASEZFkl6wB6DCwE5sZuSOQyHMQNMNuONaVkNaqRLu8PVoKQCIikuy= SNQAVYSHhWCw0JLLu2E3Pgu8em2iXt9eLApCIiCS7ZA1AYMGhyaeBaIBjQl9IhoHOIiIiqSyZA1= CyqMDm+AGo7Nsr6wkS9PL2aKkFSEREkp0CUPztwSZMLMOCTkJf4RUNBSAREUl2CkDxV4nNJ3QAm= 2GOYcMLAAAgAElEQVQ6oa/wioYCkIiIJDsFoPgLjFXqjF29VuJtOY2nACQiIslOAajp7PK6gFhR= ABIRkWSnACT1pgAkIiLJLhnuoCwiIiISU2oBknpTC5CIiCQ7BSCpNwUgERFJdgpAUm8KQAnBX/c= iIiISiQKQ1Fdlp06dZu/atesOrwtJV507d55IckwDIyKSsBSApD4qgN3AHrUCeWovagESEWkUBS= Cpj4+BTGC3ApCndgNfeF2EiEgy02XwUl97gb1du3ad7XUh6ahr164TUQuQiEijqQVI6qsS+C+wu= 2vXrs8UFxdf53E9aaNbt24PYK0/n6MWIBGRRlEAkvrai03m2gVor66wJrUTKAT2eV2IiEiy83ld= gCSlDsCpQB8gF+i4ffv26zytKIVlZ2c/g7W6rQLWodYfEZFGUwCShjoqBH322WfXeVlQKurRo8c= zWPgpAN4CijwtSEQkRSgASWMEh6BT3efNcQfXb9u27RrvSktOOTk5891v/dhtBwLhZxN2FZ5af0= REYkABSBqrA3CK+7UL1UEoA+Dy7/3oer8TmwuWXn1p4d+Cnu6PyUYTg5+aV3X5sYHOG7ExP5tQ8= BERiSkNgpbG2us+AkHov0An93nHDid05MsvY5ZVOrlfv8QCQqqMwN5DdcAJhJ+97le1+oiIxIEC= kMRKcBDKcr/2HTh4OH7Hj9/f+FagFxc8c8D99j1gK1BMaoSg4BagQBgKDkUiIhJjCkASa4Eg9DG= wf+iIC9i3dw/7vyiJxbYPul//C2zHBgSnQgD6HF3aLiLSpBSAJO7adziB9h1OiMWmAn1pO7DwU0= hqBCAREWlimgpDRERE0o4CkIiIiKQdBSARERFJOxoDJJK+ejuOs8nrIpKRz+drjk0MLCJJSgFIJ= M04msG20RzHqQh87/P5mlHzRpYikgQUgETShIJPfDiOUwkKQiLJRmOARNKAwk/8uUFIv1NFkoR+= WEVSnMJP01EIEkke+kEVSW0nel1AulEIEkkO+iEVSV0nOo7ziddFpKmT0e9XkYSmH1CRFKXw4x3= 39gI+r+sQkcgUgERS04leFyD0Qr9jRRKWfjhFUlNvrwsQWqFWIJGEpQAkknp6AS29LkI4Ef2OFU= lY+uEUST0tgJO8LiLdOY7zitc1iEhkCkAiqamF1wUIoLFYIglLAUhEJH4UREUSlAKQiIiIpB0FI= BEREUk7CkAiIiKSdhSAREREJO0oAImIiEjaUQASqelkdPdeEZGU19zrAkQSxMnAKUAmNo3EFuBj= wPGyKBERiQ8FIBHTHDgdODW/qOQnAH17ZZ2KBaAtKAiJiKQUdYGJmJOxm9a1CryQX1SyCeiDtQy= pW0zS2c+IzU0dewAvA8fXsszNwPAY7AtgNvbHS+DRvYHbiWVNkiAUgERMs3Av5heVvALkohAk6a= s9MJLYBIA+wATgi1qWeQxYE4N9AfwS+BXwHNAG2BHleoOpGdJiWZMkCHWBSTI7OYbbivjHgBuC6= NsrayQ2LkhjgySdDAB+gwWXvzdyW8saX069VGCh5wSgLMp1WgF3A9fGqyhJDApAkoxOAXJivM3m= 1NHCk19U8nrfXlmXuU8VgiQVZAKzgG9hrSVvhLzfHAsR64GO2OSunwa9fxpwF/BH4DbsAoLxwBC= s5eWvwDTsZ2U4MBHoAMwElmAtQncBq4BbgZ8C5wH/Bpa6+xjsLtMbeASY5277x8B/gUnAugYef4= sw27oUuAwoAa4AVgM3BtXUBztXs7FgeBxwE7A1wvbWAZOBlcBbDaxT4kABSJJGflHJNQlQQ6A16= DvoSjFJficDv3C/v56jA9BA4P+w/+PPApcDDwe9/2vgGuBVdzu3ul//CIwA1gKPYp815wI/ArKx= IDEQuA/4LvAE8E0saMxw9wP2h84vsTE4bYG/AO8CXYB+WNfc92l4AOoZZlsTgdHA2VhXXWhNM4A= fAC9i5+xO91jnR9jeOuDeBtYncaQAJNIA+UUlS9QaJClgC/A/WAvQ02HeH+8+AjYAT1LdnXQd8A= 0sJJUC72OtIJvd9z9xn/cH7nEfAadhLSwF2M8QwFPUHKg8GPgbsMt9PtT9ugkYA4wDPoriOCPZj= LXS1Lat0JqudOtaCxwEioDW9dieJAgNghZpoPyiklfcK8VOQYOkJTkdAe4A+nJ0609vYBH2/zrw= 2IB1UQU4wFchz8PJAMaGbOstd/mDIcseClkvK+T9bCyUFAO/jbC/aEW7reCa/MCBRm5PEoACkEg= jpevl8hMmTMDn81U9cnJyGDt2LMuWVY9z3bdvH7NmzWLp0qW1bCn+1q5dy3nnncd5553HmjW6mC= cKxwI/4egxKy9ig6G7Yf/X22FjegIhpYP7aIZ1WXXABiC/D9yCBa1WWKtRL2z8THuqeyN8QGd3H= bCxRzcBX8dakoZjXUubgH8CnbCruyLJcGsN1AQ27ulM4AKsRSnctirc2sLVdIz7vL37Xkf34atl= e5KA1AUmEgP5RSWvpFuX2COPPEK3bt0oLy9nxowZlJeXs2LFCi699FLWrl3LgAEDeOWVV5g6dSp= /+9vfPKtz7969lJWV8cYbb7B06VLuvPNO3nnnHc/qSRKLsG6xTtgYH7BuoP91v78cCxF3YC1F/w= G+Ayxw39+GhZZBWIhph42d+QMWCh5wX/8rNm7mMSxwXQL83N1GITbeZyI27qgcuB9Yjg2E7oqNH= boZu1Lt3TDH8SA1xzgFfAWchAW9m8Ns60VgDjYoe0hITXdi4WcL1qr1P+57G4B3ImzvO9gVdG+H= qVE8kjZ/rYoncvOLSgq8LqKp9e2VNQobC+BVEMoFRjmO82C8dzRnzhx27NjBtGnTql774Q9/yMi= RI7n2WruKeMaMGQwaNIiLL7443uWE5ff7yciwxu7i4mKmTZvGU0891ST79vl8Z2AfjCKSYNQFJh= Jj+UUli0mjmydWVFTgOA7l5eWsWrWKFStW0K9fv6r3W7ZsWWP5devWMXr0aAYMGMDMmTMpLS2te= q+wsJDx48czZMgQFi9ezAsvvECHDh3w+XwcOnSIhQsX4vP5eP7556vWWbNmDZdffjnDhg1jyZIl= R9UXCD/bt2/n8ccfZ8qUKbE+BSKShNQFJhIH6XS5/L333su991Zf5fv444/Tv3//sMsWFxczefJ= k5s6dy7HHHsukSZOYPXs2U6ZMYe/evdx555089NBDdO3ald/85jeceeaZFBQU0LlzZwDGjBnDxo= 0bq7a3fft2Vq5cSV5eHtu3b+eiiy7iX//6Fx07dqyx3yNHjtCjRw8AioqKmDt37lHBTETSi1qAR= OIov6hkCdWtQSlpypQp+P1+SktL+ec//8m8efOYO3du2GXXrFnDsGHD6NmzJ1lZWdx6663MnTsX= x3FYu3Yto0aNonfv3rRr145vfvObAHTq1Klq/YyMDLp3r74i+b333mPq1Km0a9eO3Nxctm7dWiM= gBWRmZnLw4EHWrl3LRx99pDFAIqIAJNIE+mAhqEk5jtMkj0AXU+vWrRk0aBBXX301zz33XNhl/X= 4/O3furHqelZVFmzZtcByHkpKSiPsIPZ7y8nIcx6GyspK8vDz8fn/VY+jQoWG30apVK4YMGcJ11= 12Hz+drknOTRho6WWg8Jxltj92V+aII+xsIvBSnfYcT7lhbYoO6T2zCOsSlACQSR317Zc3Hupq3= NvW+4/3hXllZSXFxMWVlZZSWllJeXk5+fj6LFi1i4MCBVYFn165d7NmzB8dxGDJkCAsWLGDp0qW= UlZWxYsUKbrzxRgByc3N59tln2bhxI6WlpRQVFVUdR8+ePSkoKGDHjh0UFBQwefJkFi9eTL9+/X= jsscf44IMPKCsr491332XLli0Ra96xYwebN2+mf//+CkCNE6vJQuM5yehl2I0Xg8fhBfbnw+7XM= zpO+w4n3LGegU0h8mkT1iGulB+gKZ5Ky6vAoCr4gI3/KcDuCNtU5yIXGFVRURHXq8Buuukm5syZ= U/W8ffv25ObmcuGFF3Lbbbdx/PHHk5eXxzXX2FXU//jHPxg+fDhvvvkm999/Pzt37uSqq67i9tt= vp3Vru5HuU089xZw5cxg1ahTZ2dk4jsP48eN55plneOKJJxg3bhwtW7akvLycH//4x7Rt25Y333= yTWbNmUVZWxsSJE7nssstq1Pn+++9z9dVX4/f7GTVqFLfddhs5ObGeSi685s2bp+JVYK2A/4dNF= lrbrO6JYBp2l+rQmzyCXQK/H30Opi39w0s8pWUAcsPPFuxS+CPARuz+IUeaqIRcYNSRI0fifhl8= POXl5VFWVsb48ePrXjhBZWZmehmA6jNRKRw9Wenf3a/fwCbz3I7d32cmNgcYhJ8s9GxsmohgY93= 9B08SutGt5z/A6xFqOPqyPrvJ4GCsBWcCNi/X/2L3EFocsuwk7CaMb7jbDK6zFTalxznY/YW2uM= e1PUItn1Jz4tbrsRak0IlPQydvfRLrjgveN+5yvwJ6AC8DD1E991m4iVYlxtQFJhIjfXtlzQ8KP= 4FWn8Xu900Vfqo0RRdPvB5+v5/du3ezZ88e/H6/5/UkaRfYr7GAcRJ2M8Al7td3sMk7v4/d0Rhs= CodzsclKx2PdNediVy9egt3pOOA32P/pLOyD+wrsJoeBP6h92ISgPuxDfibwHtWThD7s7vsy973= AeuFqqHk5n/k2NjFroPnxH1gIeT3MssFC6wzY427zQyzoRarlQWx+r0Js4tbyMMcUCDC3YJO8Xo= N1FYbuuxs2QerP3X3nYDeVnIHNr5aDBay3sX8riQNdBi8SA0HBx8F+QQYeTR58UsFrr73GxIkTA= ejRowdjx471uKKkdB3RTVQKcBZHT1baEgspFVh4Ko6wn9DJQgOtP6cAV2GtKOUcPUnos9gHfUC4= Gk4Ddofs7wA2cetYLMydh7Xw1JU4Q+sMCLRSP421Rt0SoZargJOpnrg13MSnkSZvDd33cGyakUD= LziPAK9j0IJEmWpUYUwASaYQwY30+pjr4VHhVF5AILRANdskll1BeXl71PJmPxUPRTlQK1ZOVLg= x5fSXWQjEP+7D/d4T1D4U874i1hNyFhZ9srAXlKWyS0NFh1otUQzhrsZaonlgr1r4o1glXZ7DmW= Njy11JL8MSt4Y4p3OSt4fbtw6bLCNjnbtsh8kSrEmMKQCINFCb8JFSrj0JD2gueqPS/1JyotBXV= E5Vuw1qH5mMtIJuA07Gus13YmJU2WGtSIAAFJgv9gqMnC22LdeXcgw0yPgYbMB2YJPRSwk8SGq6= GEqwVJFQlFjymu+uEE1pX6HM/8Dl2JVYR1uX0p1pqqaDmxK3BE58Gjmk98Co2TmgDNhfaZuw8Bu= /7bWxs0CJsDNW33OftqJ5odT8WJFu7tesHOsYUgEQaIGSgc3Dw8bTVJ5gCUNr7I9FPVPopR09WW= oR1kS3F/n/fHbTt2iYLvQC7583NQctfh3UThU4SGixcDetrOb4lwO1YAAnnR0F1bcW65EInWr0E= +D0W0uZSHabC1TKOmhO3hpv49DiOnrz1v+66ofsejZ3Th9z9Pox1w0WaaPWVWs6FNICuApN4ysX= GEPQhiQbc5xeVXBPpvURv9XHlAqMOHjyY1FeBpYI2bdqk4mXwsXQXFiRWNWDdTCyI/DmmFUnaUA= uQSJQS4PL2elELkCS4wDiYj+taMILv0LDgJAIoAEn8fYw1uZ9McrQCnRz6QoRWn49JsC6vUApAk= sDmYGNvZgE76rnuKGzQ8Szs0nWRBlEAknj6GAs9GVhoSGQnY+MlatDl7SJxcUMj1l3M0Tc8FKk3= BSCJpwrsKolk0CP4SSJf3h4ttQCJiESmACTxlhRhIViSDHSukwKQiEhkCkAiZgt2tVrg+4S9vD1= aCkAiIpEpAImYSqoHbFeQ4Fd4RUMBSEQkMgUgEbMFu/nZKdgN4JKy1SeYApCISGQKQCKmwn2kzE= 3rFIBERCJLhvuyiIiIiMSUWoBEUpRagEREIlMAEklRCkAiIpEpAImkKAUgb3Xs2HGM1zWISGQKQ= CIpSgFIRCQyBSCRFKUAlBA+8boAEQlPAUgkNX2iAOQ5P0l8I02RVKfL4EVSzxbgUJcuXSZ7XUi6= 6tKlyxSs9cfvdS0iEp5agERSzxHsrtZ91ArkmSKg3OsiRCQyBSCR1HQE+KRr165ziouLb/C6mHT= SrVu3e7Dw8wk2x5yIJCCf1wWISFxkAr2By4BTd+zYMc7jetJC9+7d5wNLgf8AH6IAJJKwFIBEUl= dv4EygD3Dy9u3bFYLiKDs7ez7W9fgKNqfcIU8LEpFaKQCJpK5AK1AubggCmn322WfXeFpVCurRo= 0cg/BQArwKlnhYkInVSABJJbWFDEMC2bdsUhBohJydnftDTT7HwU4i6vkSSggKQSOoLDkGtgF7u= o1ng/UuvuHJsrHb26ksL/+Z+ewQ4GKvtJqhPgY+x4FOIDX4+7GVBIhIdXQUmkvqOAJuxD+uTsLE= pRVgIygBOaJbRjEp/zBotTgAqgP2kVgD6lJotO59ggWcTFn405kckiSgAiaSHI+5jE/bBfRL2oX= 0ScMbgoSOI1R2DXn1p4UEs/BQA20md8TBHoOo0fUr1pe5q9RFJQgpAIuklOAiB221z3oWjKN6+D= b8/JjcuPgR8AWzDAsLnsdhoAviU6js7B8KQproQSVIKQCLp6UjQ10OtW7fh5N65sdp2CRZ6irCA= VRyrDYuIxIrmAhMREZG0owAkIiIiaUcBSERERNKOxgCJiMSWDzgNwHGcAo9rSRo+n68PNrB8o9e= 1SHpQABIRiRHHcWJ1N4G0Ey4s+nw+3axX4kZdYCIijddV4Sf23HPaxes6JDWpBUhEpBEUfOLLcZ= ydoNYgiT21AImINIxP4afp6FxLrCkAiYg0TFevC0hD6g6TmFEAEhGpv26O4+zwuoh043aHKQRJT= CgAiYjUj0/hxzuBMUEijaUAJCJSP928LkDUCiSNpwAkIhK9qpsciqeO87oASX4KQCIi0euKPnwT= gVqApNEUgEREoncc6gJLBAqh0mgKQCIi0fM5jvNnr4sQQLchkEZSABIRkWTjQ61A0kgKQCIiIpJ= 2FIBEREQk7SgAiYiISNpRABIREZG0owAkIiIiaUcBSESSTWsgy+siRCS5Nfe6ABGRKLUGugOdsN= 9d+4AdQImXRYlIclILkIgki0wgGxgKjMgvKvkQOAULRWoREpF6UQASkWTRGmv9aQ/0BMgvKnkHG= IIFIYUgEYmaApCIJItMoFXQ9wDkF5W84AYhhSAJmA04YR7rvCyqDqOAe2j6z+WBwEv1XOdmYHgc= amlSGgMkIvEUGLcTC7WGm/yiknf69soaDXyMxgaluzuB7dis8b90X2sGjPWsorodC/wW8DdiG4O= BQuCLKJf3AU8B/eq5n8fquXxCUgASkXhoDfTGxuzESiZwTG0L5BeVvNy3V9Y17v4/RiEoXTnALi= wABVQCz3lTTlQWNHL9VsDdwLX1WMcBzgH2N3LfSUkBSERiKr+o5BqP9z8foG+vrBHoSrFUlwnMA= r6FtfS8EWE5H3AGcBDY4r42GLgLC+qPAE9igWAw8CugB/Ay8BCQ425/NvAbbCLWm4CtQdsKXacU= OM3dxx+B29x9jcfGrf0K+CswDRvXdiPwb2Ap0MJ9/8fAf4FJVHffTQZWAm+FHOMU4DLs//oVWEv= QXcAq4FbgemB0mG0edtcfDtzvnp9fA59HqCHLPYb/AK/XcfwJTWOARCQl5ReVrAK+jsYGpbKTgV= 8AZ2If8KHuwkKNH8gPej0QaG4BvgtcAxwPdAPuBX4OfNtd7g5gBnCd+/x64G1ghLutSOuABYnxw= ElunUvcr++4638f6IwFlhlYUAMb5N8F65p62F0u4F6ODj9gwawA+7/+MnAfMA4LQt8EymvZJsAe= t/4PsZAVqYbLgJlBtdZ2/AlNAUhEUlZ+Ucn8oAHSulw+9WwB/gf70H46zPu/xz6oM7AwHDAY+Bv= WTVaE3VqhBGsFeQtr2SnBWobGA1cCnwFrsVakIqyVhlrW8WGhaQPwf1iLyPvuPje7y37ibucp4H= dB9W3GWlzGAD8N2ld9XAFsxLqCo9lmgXtsT2MtRVsiLP8sFngCajv+hKYAJCIpT5fLx9/TTz/N/= fff39S7PYK1NvQlcvcXWCvQ+1R3f2UQ/v+BD+ga9HwfFgoc4ECEbUdaJ7Dfr0LqiORQ0PfZWCgq= xgZGN4QTVEd9ttkc2I217ERaPrjW2o4/oSkAiUhaSJbL5SdMmIDP56t65OTkMHbsWJYtW1ZjuX3= 79jFr1iyWLl3qUaXV1q9fz6uvvup1GcGaYd03bahuiWiOdQV9G1iPjeH5OtayMdxd/m3sSrELsU= HF38LGBrXDuqrau9vr6D58tazjuOt1oPr/Wwf30Qxo635/grudzkHbHApsAv6J3fuqTZTHXYGNT= 8L92p7qsb6RtunHxvuc4b52PfCnetRQ2/EnNAUgEUkrbggagf3CT7gg9MgjjzBt2jQmTZpEeXk5= GzZsYMyYMVx66aW8++67Vcu98sorTJ06Fcfx9nNmz549fPTRR1x88cWe1hHi98CD2OBfP/ZhfAQ= bg/Mu1h00ERvbshgLQf8FtmHdP78E3sNC0RPYB3p7rAXph1i3233ApbWsAzb4uTc2YPhi7Eqvnw= O3Y5eSD8LC2AT39fnAN7AxQue49W3BQvsAd5tTgLMjHPeLwBwgF+uq6unup2Mt2zwMXOKes2Xue= ZhTRw3Bajv+hJbwfXQiEnffyi8qWe51EV7o2yvrm9TvcvmvOY6zIY4lATBnzhx27NjBtGnTql77= 4Q9/yMiRI7n22uqrnGfMmMGgQYM8Cx+VlZU8+uij3HTTTTz99NOUlJQwadKkuO/X5/N9FxvfUhj= 3nUk4d2EBaZXXhTSGWoBEJG25rUFnkoCtQRUVFTiOQ3l5OatWrWLFihX061fzfnUtW7as8Xzdun= WMHj2aAQMGMHPmTEpL7UrkwsJCxo8fz5AhQ1i8eDEvvPACAB06dMDn83Ho0CEWLlyIz+fj+eefr= 9remjVruPzyyxk2bBhLliw5qsYFCxbwgx/8gMzMzKPek5QVGPPzcV0LJjoFIBFJayGXy8fqrtWN= du+995KRkUGrVq0499xzue++++jfv3/E5YuLi5k8eTIPPfQQy5cvZ9u2bcyePZu9e/dy5513Mmn= SJJYvX86yZcvYv9/ue1dQUFC1/pgxY5g+fXrV8+3bt7Ny5Ury8vKYO3cuN998M7t37656f926df= Tq1YsuXYLvNSgpbg42JmgNdn+tpKYAJCJpz715Yq77qJXjOE3ymDJlCpWVlRw4cIC3336befPmM= WfOnIjLr169mmHDhpGTk8Pxxx/PLbfcwty5c1mzZg0jR47klFNOoW3btgwcOLBqnY4dO1Ydk8/n= o1u3blXvrV+/nqlTp9KuXTtyc3PZunUrhYWFVe//5S9/YejQoVWDtW+66SbuvvtuOnToEPdzI56= 5AbuFwMteFxILCkAikvb69sr6M3a1zJd1LdsU4QcgI8N+Pbdu3ZpBgwZx9dVX8/zzzx+1XPDz4u= Liqu+zsrJo06YNX3zxRY3lQo8j9PvDhw/jOA6VlZXk5eVRWVlZ9Rg6dGjVsn/6059qvPfYY49x3= 333sXv3bgUgSQqaCkNE0lbfXlnzgTKsOf9zat6zJax4fwD7/X527NhBWVkZpaWlNG/enI0bN/Li= iy9Wtd4E6ti1axd79uzBcRwGDx7MT37yE6644gqGDx/OihUruOGGG8jNzeX222/n/PPPJzs7my1= bttC1a9eq7fTs2ZOCggI6depEQUEBCxcupFOnTvTr149x48aRm5vLqaeeyoYNG8jKyqJXr14Rz4= sCSkzdDHyEdTdFozU2bYUDzI3D8ilHAUhE0lLfXllPYMFnl/v4GLvpW63i/QF/yy23MGfOHAAee= OAB2rdvz2mnncZFF13ErbfeWrX/vLw8Hn74YQBycnIYNmwYL774IrNmzeKOO+7gqquu4qc//Smt= W7dm3LhxXHXVVYwaNYrs7OwaQWXy5MncdNNNXH/99Zx++ulMmTKF4cOH07ZtWyZPnsxdd93FwYM= HmThxImeddVadx68AFDP1nXH9HGyKiqlxWj7l6DJ4EUmry+CDWn0+xW7/v4Xq1p+yOlb/2pEjR+= J+GXw85eXlUVZWxvjx470upcEyMzN1GXx412I3I4z2Pjz1XT6laAyQiKSNoFafT7HwU0h1AKor/= ABNNwg6Hg+/38/u3bvZs2cPfr/f83qSbAzQP7Huoifd5z9wn48KWa4FdlPBN7EbFua4rwcGD7+L= TVzaNmidwcAibMLWn2B3iJ4EXBS0zHBs/rK3gO8Evd4fm1V+NTYbe6CGKdj/75Xu9mtbPi2pC0x= EUl5Iq8/H7tdtRNfqU0Myd/G89tprTJw4EYDs7GzGjh3rcUVJ5dvAn7FLwQH+gY2heT1kuf7Y/7= Fp7jrbqZ4xfTw20P5+bA6z31I9M/3NWCj6C9YqMwO43N1mNnAu8CP3+6XAQGzqiz8CN2LduA9h8= 3gFz+Q+EpvJfR12r6twy6clBSARSWlhurwKsfBTr+ATkMwBaNSoURw6VD2PZTIfiwcOYDOlj8Xu= gnweNgFr6EncioWfCmzqjWJs+ozAjOlgM6a/goWi4Jnpwebggpo35jwLuMd9BJyGTc+xHOsOxK3= nOGrO/D4OG0wN1ooUbvm0pC4wEUlZbpfXZmAtsALrxmhw+IHk7gJLlYeH1gJfw1pYOmMzn4faBV= yJTa8yD7vJZm0zpkeamT54xvUMLHj5gh5vAccCLUPWa0Hkmd8jLZ+W1AIkIikn1q0+wdRqktYqs= WAxHZu4NJyzsdnel2IzqH8Dm2T0SWycz2pqzpi+HngVm1drAzZB6mYsYJ3gbvN9d3//wWZoPx0L= WPnAH7AJXd/HutPuBHpRPZP7pVTP5B5p+f8CLzTojCQxXQUmIt8CLsDGKSSN/KKSa+gUxtUAAAM= cSURBVMK97rb6bMcGNu8ihuEH+FppaWlSXwWWCtq2bevlVWBtsa6tC6nZShNwFtaq8iBW393YOJ= sL3O+7YWHmYar/T16CjQMqx8YH5WDdbWBjfd5115+EhZkHsG4zsNamn2Hh5kOsYePvwJ+wIPWEW= 8tEdzvhln+aKG4CmmoUgETkbGwKiPbuI9G1AbJCA1AjL2+PlgJQAvA4AGViV2r92YN9SwypC0xE= tgJHsF/srT2upTatsclKTyRkzITb6rMP+ys2pl1eodQFlva+g3VXSZJTABKRz0mO5u8uhLRQxfL= y9mgpAKWtUdiA4llY15EkOQUgETniPhJdjct14znQuTYKQGlrsfuQFKEAJCLJogy78iXw/Xas+6= 6AOLf6BFMAEkkNCkAikiyOYON8NmO/u2J9hVdUFIBEUoMCkIgkizKstWcXNlVArK/wEpE0ogAkI= ski0AIU7u67TUYtQCKpQQFIRKQeFIBEUoMCkIhIPSgAiaQGBSARkXpQABJJDQpAIiL1cMIJJ/xm= 9+7dM72uQ0QaRwFIRKSe1AokkvwyvC5ARESknhxgp9dFSHJTC5CISPQcoFgtQAlhv9cFSHJTABI= Rid5OYL8CkHe6dOkyCbX+SAwoAImIRG8/sLNLly6/2blzpwZCe6MY+NLrIiT5KQCJiNTPfqC4a9= eu84uLi6/xuph00q1bt9/hhlCva5HkpwAkIhI9B2uBKARy1RXWdLp37/4Mdt53ohYgiQGf1wWIi= CQZH5ALDHK/dt2+fbtaguIoOzv7WWAH8FdgIwpAEgO6DF5EpH4CrUAFuC0S2dnZ870tKXW54SfQ= 6qbwIzGjFiARkYY5DmsB6uN+7Qrw2WefqTUoBnr06DGfml2OBcC/PC1KUooCkIhIwwVCUK77fTf= cICSNErjR4Q6qW372o9YfiSEFIBGRxjnOfXSlZhAKUCCqnQP8N+R5MRZ4ClC3l8SJApCISGwEB6= HA18DrEplDdcAJtPzsD/qq8CNxoQAkIhJbgcBzrPvVh1qBahM6r9eX1AxFIiIiIiIiIiIiIiIiI= iIiIiIiIkf5/36WKhVOfl0jAAAAAElFTkSuQmCC" width=3D"576" height=3D"308" alt= =3D"" />Fuente:</= span> Ministerio de Educa= ci=C3=B3n (2022).</spa= n><sp= an style=3D"font-family:'Times New Roman'"> <ol start=3D"2"= style=3D"margin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style= =3D"margin-left:32pt; line-height:115%; padding-left:4pt; font-family:'Time= s New Roman'; font-size:12pt; font-weight:bold; color:#767171">Metodo= log=C3=ADa</li></ol>La presente investigaci=C3= =B3n adopto un dise=C3=B1o cuasi experimental, enfoque cuantitativo alcance= explicativo y corte longitudinal, pues se trata de detallar e investigar l= as caracter=C3=ADsticas del fen=C3=B3meno en cuesti=C3=B3n y establecer las= diferentes causas y efectos, as=C3=AD tambi=C3=A9n describir la realidad d= el lugar donde se desarrolla la investigaci=C3=B3n. Debido que, este tipo d= e investigaci=C3=B3n aumenta la compresi=C3=B3n del tema, y contribuye a te= ner resultados concluyentes y encontrar las diferentes razones por que se d= esarrolla dicho fen=C3=B3meno, permitir=C3=A1 tambi=C3=A9n aumentar y perfe= ccionar las conclusiones del estudio y anticiparse a los diferentes cambios= y obtener nuevos puntos de vista al ser una investigaci=C3=B3n de campo el= an=C3=A1lisis y aplicaci=C3=B3n se dar=C3=A1 lugar en la Unidad Educativa = Combatientes de Tapi con los estudiantes de primero de bachillerato en el a= =C3=B1o lectivo 2023-2024.La poblaci=C3=B3n= de estudio consta de 145 estudiantes de los primeros de bachillerato distr= ibuidos en paralelos =E2=80=9CA, B, C, D, E=E2=80=9D, adem=C3=A1s 5 docente= s del =C3=A1rea de ciencias sociales, en particular que dictan la asignatur= a de Historia. Para tal efecto la muestra fueron 19 estudiantes de primeros= de Bachillerato, distribuidos en los paralelos =E2=80=9CA, B y C=E2=80=9D = y 2 docentes del =C3=A1rea de Ciencias Sociales de la Unidad Educativa Comb= atientes de Tapi.T=C3=A9c= nicas e instrumentos para la recolecci=C3=B3n de datos. la recolecci=C3=B3n de datos es una part= e fundamental en toda investigaci=C3=B3n, pues el estudio de las metodolog= =C3=ADas de aprendizaje requieren del uso de las diferentes t=C3=A9cnicas c= omo es la observaci=C3=B3n directa mediante el uso de una Lista de Cotejo, = que permitir=C3=A1 identificar los conocimientos que poseen los estudiantes en la asignatura de Historia previo a= la aplicaci=C3=B3n de la encuesta la cual contar=C3=A1 con un cuestionario= donde las interrogantes que permitir=C3=A1n identificar las diferentes met= odolog=C3=ADas que utilizan los docentes en el proceso de ense=C3=B1anza ap= rendizaje = de la asignatura de Hi= storia en el primero de bachillerato y= los docentes del =C3=A1rea de Ciencias Sociales. Observaci=C3=B3n Directa: aplicado para observar directamente al docente= que imparte la asignatura de Historia y a los estudiantes dentro de aula p= ara recolectar datos que precisen las metodolog=C3=ADas utilizadas para el = aprendizaje mediante una lista de cotejos. Encuesta: su final= idad es conocer la opini=C3=B3n de las personas acerca de alg=C3=BAn tema, = o bien contar con m=C3=A1s informaci=C3=B3n respecto de un hecho o suceso, = estar=C3=A1 compuesta de entre 15 a 20 preguntas, abiertas y cerradas, las = cuales permitan tanto al inicio de la investigaci=C3=B3n como al final dete= rminar el grado de conocimiento de los estudiantes.La entrevista: es una t=C3=A9cnica de investigaci=C3=B3n cualitativa qu= e consiste en una conversaci=C3=B3n dirigida entre un entrevistador y un en= trevistado, con el objetivo de obtener informaci=C3=B3n sobre un tema espec= =C3=ADfico. Esta interacci=C3=B3n permite explorar en profundidad las perce= pciones, opiniones, experiencias y conocimientos del entrevistado.</= p> <a id=3D"_Toc57614423"></a><a id=3D"_To= c80201716"></a><a id=3D"_Toc80741352"></a><a id=3D"_Toc83138069">T=C3=A9cnicas de proc= edimiento para el an=C3=A1lisis de resultados</a>: se aplic=C3=B3 el programa Excel y SPSS, V.25 adem= =C3=A1s de un an=C3=A1lisis cuantitativo de informaci=C3=B3n mediante el pl= anteo de una Hip=C3=B3tesis Nula y una Alterna aquellas ser=C3=A1n contrast= adas mediante el c=C3=A1lculo de la U de Mann =E2=80=93 Whitney como prueba= no param=C3=A9trica. La encuesta se realiz=C3=B3 mediante la aplicaci=C3= =B3n Forms de Office 365, aquella es una herramienta utilizada para formula= r enc= uestas de opci=C3=B3n = m=C3=BAltiple, abiertas entre otras donde se obtendr=C3=A1n datos de manera= r=C3=A1pida y segura.Pro= cedimiento. En primera= instancia se procedi=C3=B3 a solicitar el ingreso a la Unidad Educativa Combatientes de Tapi a su = primera autoridad como es el se=C3=B1or director de dicha instituci=C3=B3n,= posterior se socializ=C3=B3 el tema de la investigaci=C3=B3n tanto con los= docentes como padres de familia y estudiantes para as=C3=AD continuar con = la firma del consentimiento informado el cual amerita a los estudiantes ser= parte del estudio en cuesti=C3=B3n. <ol start=3D"3" style=3D"ma= rgin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-lef= t:31.25pt; text-align:justify; line-height:115%; padding-left:4.75pt; font-= family:'Times New Roman'; font-weight:bold">Resultados </li></= ol>El an=C3=A1lisis de datos realizado en este estudio= da a conocer sobre las preguntas planteadas a los estudiantes en relaci=C3= =B3n con la asignatura de historia, para posterior fortalecer la misma (</s= pan>tabla 3= ).Tabla 3Estad=C3=ADsticos descriptivos de las preguntas del cuestionari= o aplicadas a los estudiantes <spa= n style=3D"font-family:'Times New Roman'"> </div> <= div class=3D"Section_2"><table style=3D"width:584.6pt; margin-right:7.05pt;= margin-left:7.05pt; margin-bottom:0pt; padding:0pt; border-collapse:collap= se; float:left"><tr style=3D"height:163.65pt"><td style=3D"width:43.05pt; b= order-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding= :0pt 5.4pt; vertical-align:middle"> </td><td style=3D"width:30.3pt; border-top:0= .75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt;= vertical-align:middle">Le gusta la materia de historia</span= ></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= style=3D"margin-right:3pt; margin-left:3pt; margin-bottom:0pt; text-align:= center; line-height:115%; font-size:9pt">=C2=BFQu=C3=A9 m=C3=A9todos de evaluaci=C3=B3n prefiere<= /p></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-= bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">=C2=BFCu=C3=A1l es tu nivel de comprensi=C3=B3n lectora?</= p></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-b= ottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">Te motiva profundizar sobre la materia de historia</td>= <td style=3D"width:47.55pt; border-top:0.75pt solid #000000; border-bottom:= 0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">=C2=BFCu=C3=A1l es tu opini=C3=B3n sobre la importancia de aprender hist= oria en la educaci=C3=B3n?</td><td style=3D"width:49.15pt; borde= r-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt= 5.4pt; vertical-align:middle"><= span style=3D"font-family:'Times New Roman'">=C2=BFCon qu=C3=A9 frecuencia = navegas en internet para investigar temas hist=C3=B3ricos fuera del aula?</= span></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; b= order-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle= ">=C2=BFHas participado en el aula invertida anteriormente?</= span></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; b= order-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle= ">Qu=C3=A9 tan efectivo es el modelo de aula invertida= </td><td style=3D"width:40.25pt; border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= style=3D"margin-right:3pt; margin-left:3pt; margin-bottom:0pt; text-align:= center; line-height:115%; font-size:9pt">Encuentras los materiales previos (videos, lecturas) claros y c= omprensibles.</td><td style=3D"width:44.05pt; border-top:0.75pt = solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; verti= cal-align:middle">Los conceptos estudiados previamente te ayu= dan a desarrollar las actividades en clase</td><td style=3D"widt= h:49.15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000= 000; padding:0pt 5.4pt; vertical-align:middle">Consideras que= tienes m=C3=A1s oportunidades de interactuar con el profesor en el aula in= vertida</td></tr><tr style=3D"height:35.7pt"><td style=3D"width:= 43.05pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00000= 0; padding:0pt 5.4pt; vertical-align:middle">N</td><td style=3D"= width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #= 000000; padding:0pt 5.4pt; vertical-align:middle">19</td><td styl= e=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle">19</td><td= style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75= pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">19</t= d><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom= :0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">19= </td><td style=3D"width:47.55pt; border-top:0.75pt solid #000000; borde= r-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"><p= style=3D"margin-right:3pt; margin-left:3pt; margin-bottom:0pt; text-align:= center; line-height:115%">19<= /span></td><td style=3D"width:49.15pt; border-top:0.75pt solid #000000;= border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:midd= le">19</td><td style=3D"width:30.3pt; border-top:0.75pt solid #00= 0000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align= :middle">19</td><td style=3D"width:30.3pt; border-top:0.75pt soli= d #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-= align:middle">19</td><td style=3D"width:40.25pt; border-top:0.75p= t solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; ver= tical-align:middle">19</td><td style=3D"width:44.05pt; border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4p= t; vertical-align:middle">19</td><td style=3D"width:49.15pt; bord= er-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0p= t 5.4pt; vertical-align:middle">19</td></tr><tr style=3D"height:3= 7.35pt"><td style=3D"width:43.05pt; border-top:0.75pt solid #000000; border= -bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">M</td><td style=3D"width:30.3pt; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:middle">1.32</td><td style=3D"width:30.3pt; border-top= :0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4p= t; vertical-align:middle">2.11</td><td style=3D"width:30.3pt; bor= der-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0= pt 5.4pt; vertical-align:middle">1.74</td><td style=3D"width:30.3= pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; pa= dding:0pt 5.4pt; vertical-align:middle">1.05</td><td style=3D"wid= th:47.55pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #00= 0000; padding:0pt 5.4pt; vertical-align:middle">1.16</td><td styl= e=3D"width:49.15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt s= olid #000000; padding:0pt 5.4pt; vertical-align:middle">2.11</td>= <td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0= .75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">1.47</= p></td><td style=3D"width:30.3pt; border-top:0.75pt solid #000000; border-b= ottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">2.26</= span></td><td style=3D"width:40.25pt; border-top:0.75pt solid #000000; = border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middl= e">2.26</td><td style=3D"width:44.05pt; border-top:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-ali= gn:middle">1.79</td><td style=3D"width:49.15pt; border-top:0.75pt= solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vert= ical-align:middle">1.16</td></tr><tr style=3D"height:37.35pt"><td= style=3D"width:43.05pt; border-top:0.75pt solid #000000; border-bottom:0.7= 5pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">Des.</td><td style=3D"width:30.3pt; border-top:0.75pt solid #= 000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-ali= gn:middle">.47</td><td style=3D"width:30.3pt; border-top:0.75pt s= olid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertic= al-align:middle">.93</td><td style=3D"width:30.3pt; border-top:0.= 75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5.4pt; = vertical-align:middle">.73</td><td style=3D"width:30.3pt; border-= top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; padding:0pt 5= .4pt; vertical-align:middle">.22</td><td style=3D"width:47.55pt; = border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000; paddin= g:0pt 5.4pt; vertical-align:middle">.37</td><td style=3D"width:49= .15pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #000000;= padding:0pt 5.4pt; vertical-align:middle"><spa= n style=3D"font-family:'Times New Roman'">.73</td><td style=3D"w= idth:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75pt solid #0= 00000; padding:0pt 5.4pt; vertical-align:middle">.51</td><td styl= e=3D"width:30.3pt; border-top:0.75pt solid #000000; border-bottom:0.75pt so= lid #000000; padding:0pt 5.4pt; vertical-align:middle">.93</td><t= d style=3D"width:40.25pt; border-top:0.75pt solid #000000; border-bottom:0.= 75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">.99= </td><td style=3D"width:44.05pt; border-top:0.75pt solid #000000; border-bo= ttom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle">.85</sp= an></td><td style=3D"width:49.15pt; border-top:0.75pt solid #000000; bo= rder-bottom:0.75pt solid #000000; padding:0pt 5.4pt; vertical-align:middle"= >= .37</td></tr></table> </div> <div c= lass=3D"Section_3"><div style=3D"clear:both"><img src= =3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAUDBAQEAwUEBAQF= BQUGBwwIBwcHBw8LCwkMEQ8SEhEPERETFhwXExQaFRERGCEYGh0dHx8fExciJCIeJBweHx7/2wB= DAQUFBQcGBw4ICA4eFBEUHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh4eHh= 4eHh4eHh4eHh7/wAARCARfAzMDASIAAhEBAxEB/8QAHQABAQACAwEBAQAAAAAAAAAAAAECCAUGB= wMECf/EAFQQAQABAwIDAwUMBAkJBgcAAAABAgMEBREGByESFzETQVFVkQgUFSJUVmFxkpTR0jeB= obIWIzI2UnR1scEkMzRCYnKCs+EYQ0RGZKIlJzU4ZZPi/8QAGwEBAQADAQEBAAAAAAAAAAAAAAE= CAwQFBgf/xAA0EQEAAQQBBAEDAAcIAwAAAAAAAQIDBBFSBRIUITETQVEiMjRhcYGRFSU1QqGxwd= Ez4fD/2gAMAwEAAhEDEQA/AOgSiyj9Lh8VAAAAgAC/YAFgAFSUWUEkAFgRUQnX3BaKK65imimqq= fREPt7zzNv9Ev8A/wCuUmqIn3LKKZn7PgPpdsXrMRVes3bcT03qoml89pWKok1P9BJVJVigAEos= oACRv5xY+N/hUlUkVAAAASUWUUAECUWUIAAkEnwVJ8AQBQARUk+slaaZqqimPGVhJn7vtiWvKV7= zHxYfvYWqIt0RTH62aw47le5AFYgCSqSiyiAAASEiwgAgAMgAAAIABUqQnxGMs49ACMkY1SynpD= CrqwrlsphEmF8Dfdg2bQXYiOqBEbQLKMoY7AElYNkUkVE2UNG2IqAPldneX0rnal8ZY1SsQgDWy= 2Sikml2i0RvP0I+tunanqtMblJn0zgNht7YYPvKLKOmHPAAAAgAC/YA8+wsB5t37NG0vUNY1C3g= aZiXcrIuTtTRRH7foh7Hw37njWsvGi9rOrWMCuqneLdqiblVM+aJ8I9m7lyMyzY/8lWm+1j3Lv6= kPD58XeuEuVfFPEvDWTruDjxTYtUzVZoriYqyNvHsO2anyZ1XhLV8TVsqzGuaLYuxVlW7E7XexH= nmmfN9Utj+F8/SNS0XGyNFuWqsPsRFumiNuxER/JmPNMeGzys7q/ZTE2ff7/8Ah3YvT+6qfq+mh= uTYu41+uxft1W7tuqaaqao2mJjzPm2q548psfiTHua5oVqm1q1Eb124jam/H+FTVvLxsjEybmNl= Wa7N63VNNdFcbTEx5no4WdRl0bj5+8OTJxqrFWp+HxZ49mvIybdi3G9dyuKKY9MzO0MHYuWePRl= cfaNZuRvRVlU7x9XX/B13a+yiao/DTRTFVcRLaDlPyv0LhjQce9m4OPmapdtxXeu37cVzbmY37N= O/ht4dHKZfGvLnFyK8e9q2jU3Lc9mYiqidvofTnNn5Gm8tdYyMauaLnkJoiqnpMdrp/i0lqqmqq= aqp7Uz1mfTL5XBw6s+arldUvbyMiMXVFNLY3nXxHwPrUcM2MDO07JtUavbryqbU0z/F7TE77eZ1= /n7HLmOHMP8AgzbwaNQm/O04tO3xem/a26fVu8u5eU01cdaLFURMTnWomJjff40Nk/dK6VTmcH4= OFh49qm9fzrdunaiI6zP0Ou5RTh3rVvcz8/dpoqnJt11ahqfTE1TEREzM+HTxfSvGyKYmqqzciI= jeZmmejczQeGuGOXPCPl/g+b9VmiJvXaLHlLt2r6odf1bmrwzVpmTR/BXXqZm1VHaq0yIiOn1tl= PWKq6tW7e4/i1z0+mmN11alqlTj36qYqps3Ko9MU+KXLN23G9dqunfw7VOzdLlNRhRyq0bMu4tr= sxhzcqmbcb7bzL5cGcecE8Z593S9MtU13qbc1VUXceI7VPhLGet1z3TFv1H7/wD0y/s6mdR3fLS= 4opqrnaimZn0R1bCcUcq9KzeeWLpuLajH0vIxvfeRao6RG0zE0x6N9v73qPEWtcCcucDExM6zj4= dFyJizaosxVMxEeP8Ah+tur6xT+jFunumY+Gunp8+++dRDTXT7Fu3n49WpWblOJ5Wny3xZ/k79f= B7fzojln3f0fwetabTqPlrfYnHpiK9uzO++3+Ll+YHMvgvijSMXSNGt1++7mfj1U9qxFMbRXEz1= +p2T3R2Nj2uU9dyjHt01RetdaaIifCXNcy67l21NdM0zvWt/wb6MemiiqKZiWp0Y2RMRMWLkxPh= PZlhct3Lc7V0VUz9MNouDubHCdHDWm4lvh/WMq5j4tq1crs4FNdM1U0xTPWJ9MO8cMavw3x1g5l= inQsmzbtxFNy3m4fkpmJ3229PnbrnV7lqZ77XqP3tdOBTXEdtXtpCO4c4+G8fhXmBqGkYkTGPTM= XLVM/6tNXWI/VDp72bVyLtEV0/EvPuUTRVNMgDYwSUWUUAECUWUIAAkEnwVJ8AQBQARUl+vCtbR= 5SY6+Z8LNublyIhyMREUxTEdIWGi7Xr0oCw5gBVAElUlFlEAAAkJFhABAAZAAAAQJKsSWUADGVA= SqfMm2UJPikg0y369IjJNghOqwQpBMpKLKMtIAIsBISKgAgDGuemySyh8653n6GExLOeiNUsmAy= mEmA0QlSwTG/gKtuN53fUpjanoNsRphsAFfeUWUdMOaAAABAAF+w/boemZes6tj6ZgWpu5ORXFF= FMeeZfiexe5R0/HyuOcrMvU01XMXH/i4mPPVvvP7HNl3vo2aq4+0N+Na+rcin8vcOVfL/TOCNCt= 24tWrupV075OVMdap9EeiIdc5i87tE4az69N03H+FMu3O1yaa9qKJ9G/nl9/dH8YZfDPCNGLp1d= VvK1CvyPlInbsUbTMz+zb9bUqqqqqqaqpmapneZmfGXz/AE7AnNmb9+dw9fLypx4i1abU8tOdul= cUahGk6vi0adlXelqrtb27n0dfCXL67ouocF6td4m4VsVX9Ouz29R0ynwmPPct+ifPMNPqKqqLk= V0TNNVM7xMTtt9L3flpz1+DOHb2BxPTdysjGtf5LdpjebvTpTV+LbmdLm1PfjxuPvDXj5sXP0bk= +4+73/hzWtP1/SrWpabepu2bkfrpnzxMeaXnHO/lRj8V4tzWNHt02NYt071UxHTIj0T/ALX0vGe= BeaOo6Nx/kat2YtadqORvk4lEbUUxPSJpjzS28xb9rJx7eRYriu1cpiqmqPPE+d5l6ze6ddiumf= n/AO07bd23l0TS/n9mY1/DyruLk26rV61VNNdFXjEw/dwln/BfE+nahvtFnIoqmfRG/X9j2X3VP= BmPhZOPxXgWaLcZNXk8rsx41+ar65jaP1PBZ/Y+rxr9OXYir8+nhXrc493X4b3cR6di8XcG5GDT= diLOoYv8Xcjr2e1T8Wf2xLV/M5G8e2cq5btYVi9bpqmKa4uxtVHpfXlnzo1rhLT6NKzLEalg0f5= uKqpiu3HoifQ75HukdP8Am/lfbp/F4dnHzsKqabcbiXp13cbIiKq51LznTeX/ABLwhxbw7ma3iW= 7Fm9qVq1RVTX2t6t99v2Pf+d+XZwcHQczImItWdWs11zPoiYeN8w+cuLxRd0OuzpF+xOmahRlzF= dUfHiImJiOvj1fk5vc3bXG+gWdKxdKuYvZuxcqruVxv08NtpbbmNlZNyiu5TrW9sKL1mxTVFM/h= tFr2oX9P0e5nYmBd1Cq3TFXkbVW1VUfR47vLuKuaGXf4b1KxXwPrVmmvGuUzcrp6Ub0z1no885f= 8+dU0LSbWm6xgzqVuzTFNF7tbXNo807+Ln9W90Vh5GnZNizoF+Lly1VTRNdcbRMx032nwcVHTL1= uvU0d379uirMt10+qtPSeWNU1ck9Mq2mN9Mqn9lTw73Kn6Rr39VqclwzzywtJ4Jx+H7mi37ly1j= VWZuRVTtMzv18d/O8+5S8Z08EcUfC9zDqyrdVuq3VRTO0xv54dePg36bV6mafdXw57mTbm5bmJ9= Q2ezMuzY54YmPdmIrv6VMUTM+eKqun7XQfdQcF8Sa/q2l6homn5OoW7dqq3XRZo7U0TMxPh6Ojz= XmPzQyeIeMNP4i0ixd069g26aaJmqJqmYqmfN026u96N7pC5Rh0UaroM3MiIiKq7FcbVfT1lqt4= OVj1UXaI3MfZsrybN6KrdU6h5fpnBXFmiaxp2oatw/qGFi05lqmq7etTFMTNUbRu2T5+49GXy5x= 8a5O1F3MsUVfVO8PKOYXPLF4m0CnTsfRb9m7Rk2r8VV1R2Z7FUVbdJ8+z8vMvnTZ4q4To0bE0m9= i3qb1u55WqqNo7MT1jafS6LtrLybluuunUxMtdquxZpqppq22CzIwOBOEaZ0nQ7uTbxqKLdNjEt= /Hr8I3mf27sOA+Lb/ABPcy6L3D+oaV73ppmJyY28p2t/DpHht+14xwx7om/iaTZxtY0evJyLVEU= TetVx8fbpvMTPi5SPdJadH/l7K+3T+Lzq+m5Ebiqjc/nbspy7MamKtPPPdQ/pdzd/k1j9yHl7tf= Nfiu1xpxlf16zi141Fy1bo8nXMTMdmnbzOqPqcK3VbsU01fMQ8O/VFVyZgAdTSkosooAIEosoQA= BIJPgqT4AgCgePgP0Ydrt1dqfCEKp7Y3L9GNb8nRHpnxfVFVxTO52ALCACgAkqkosogAAEhIsIA= IADIAABJCCUBGQAGyfBh4sqp8zFrqbKYAGGmzYAaXYAyY/KSjKYSYFQBJZQEhKKgAxSekPnM79W= dc+ZgxqlspSUWUYKEwBKpsztx55Y7bzD6xG0bMqYSqRJVJZtYAMn3lFlHRDngAAAQAPoFIiZnaI= mZew8p9F4t4FvYvHGTp0zo97e1kW4mfKxbnb+Mmnbwj63U+TGRwrj8bYtziujfFidrNVU/xdNzz= TX9G/wD1bnU04+RiRRTTbuWLlEbRERNNVMx/ds8Dq+dVamLU0+p+f3vV6di01x379w6TzJ4U0rm= Zwbb96ZdE3Ijy+Dk09ae1t4T9ExMx9Hj9DUPiPRdS4f1e/peq49VjJs1bVU1U9JjzVRPniW1ebh= ahy31C7qWkWbmXwvfr7WXh07zOHM/95bj+j6Y8HAe6Iy+CNX4DxtVv5Fq5n3bfa0y9YmO3X/sz/= s7+Po6+Dj6Zl12K4tx+lRV/o6s2xTcjvmdVQ1hlFnx+pPP+p9X/AAeDMPthWbmTmWbFqiaq7lcU= 0xHjMzLfHhPDvadwzpuDf/zuPi27df1xTEPBPc5csMi7mWeLtbsTbx6PjYdmuP5c/wBOY9HobH/= rfI9ay6b1yKKfen0HTceq3RNVXzLzL3TFNqeVWZN2Ina9bmn692oHn33bH+604ltU6dhcMWbkTd= uVeXv0x5oifi7/AK4lrhPj4PV6JbmjH3P3lwdSriq96er8oeUdvjvQL2p3NZqwpt35t9iLHb36b= 779qHdf+zZj/Oi590//ALc37kr+YOZP/rJ/dh1Hm1za4z4e4+1HSdMzrVvFsV7UU1WaJ2j65jdw= 13su9l12rNWtOum1Yt2aa66X5+Kfc86rg4FzJ0XWKM+5bp38jcs+Tmr6p3neXmPBnBuq8UcUVcO= 4nk8fMoprqqi/M0xT2fGPBtJyK49v8c8N3ruoW6Kc/EueTvTR0pr36xMR9TqWrcN5OL7oyi5oeb= GmXM7Tq79V2m1TVHa6xMbTEx4RBZ6jftzXauz+lEepSvEtV9tdHxLxLmRwFq/AmThWNWvY1yrLo= qro8jVMxEUzETvvH0uoy9t90jo3ENfEPDuBmalXq+VkW7lOPEWaaJj41PTamI3/AOj9mje5z1C/= p9i9qWtW8fJrmma7VFG/Zp36xv6dnpWeo0U2Ka79Ubn8OOvErquzTbj4eCu8ct+Weucd4OVl6Tk= YlujGuxari9XMTvMb9No9D1j/ALN2B84cmY/3KfwXkRw3rmFXxPpmj8Q1YVrC1ObFX+T0V+U7Mb= RVPapnbpDVkdVoqtzNir3H5bLODVFcfUj1LxrG4KyKOZtngjPyaLd+rLoxrl63Happ3iJ3iOm/i= 7Pzj5TWuAeH8XVLesVZs38mLE0TY7G29NVW++8/0XoHBvL7I1TnHq/EepazN7I0nUrcz2bcUzeq= iimeu0bRG0xHR6RzY4Gs8faFjaZfzbmJTYyYvxVRETM7U1U7df8Aecd7qdVN63qr1ERtvowt26v= Xv7NIt+sq9l4d5MYuqcecQcOVavet29K8l2bkUx2q+3TFXo+l2ufc3YG07cQ5O/8AuU/g9OrquN= TOpqcdODdneoa541vy2Tbs9rszXXFO/o3nbf6XsHHfJS1w3wRd4jo16q/Vbt01+RnG233jfbftO= A5icsdX4D1TBv371GZg3simm3fopmNp7XSmY9Oz3/nf+hPK/q1v91zZedM3LU2avUy6LGLHbXFc= e4acgPceYAAkosooAIEosoQABIJPgqT4AgHnUZUUzXVER53JW6It0RTH63wwrUxHbq/U/SOW9X3= TpABrAFgAFABJVJRZRAAAJCRYQAQAGQAAALCSjIRWJKywqlJkphAGtugAF2ACSAGlgAFJTZQWJY= kstmJpdiT0XZhX6GMkQwnxF2NmHy2IipKaRAZURvJpVojzsl2RshrkSVSVkgARX3lFlHRDRAAAA= gAC/Y3nfd7XyK5u3dEu2eHeI79VzTap7NjIq6zYn0T/ALP9363ihH0dHNlYtGTb7K26xeqtVd1L= +gkVWMrHiqmq3esXaekxMVU1RP8AfDwHnFyUycjJuaxwjT5SKt6rmDNW20+eaN+n6ujrfI/m5d4= aqt6Hr9dd/Sap2tXZnerHn/Gn6PM2e07NxNRw7eZhZFF+xdpiqiuid4mHyNdOR0y7uPj/AEl9BR= VazLftpRY5eca38unGo4dzZuTPZ6xERv8AXM7PZOVnImnCv2dV4uqtXrlE9ujDo600z/tT5/qe9= 0x06r02bMjrORdp7Y9MbXTrVuru+WFq3btWqbVummiimNqaYjpEOu8wuL9M4O4evalnXafKRTMW= LO/xrtfmiH4eY3MTQODMKa8y/TezKqZ8ljW6t6qp+n0Q1K4+4w1bjLWq9R1O78XfazZpn4lqPRE= Men9Mrya+6r1T/uuVmUWY1HuX4OKdczuItdytX1C5Nd/Ir3/3Y80R+pxXnVPS+zopiimKYj4fOz= VNU7ltP7kv+YOZ/XJ/dh4r7oD9K2sf78f3PZfcoZFi1wJmUXL9u3VOZM7VVRE+EO+avwXwJq+oX= NQ1LTcDIyrs713Kr07zP6qnynlRi51dcxuHu/R+vjU07ea+5Cwsm3oWrZtyzMWL1+mm3XMfyto6= 7T6N3atTu26vdGaVaprqmuNFuTMb9I+NV+12jUNa4T4J0DarIxMHDs0z2LNuqOv0RHnmXh3Kniq= rin3QN/W79UWrNeNdos01VbRTRERtHX2/raKorya7mRrUabN02aabcTuXqnFuFYy+dHCld6mJnH= wsm7b3/pdqiP7pl1b3T/GGu8O4+l4eh5t/Aqv1TXcv2atqpj+jv+o53cV2uGeZnCGsU3KbmPbtX= 6L8UVRPxJmmP+v6nddc0/gfmVoWPXlZGPl2Int2rtF2Ka6Jnxj/AKMbcfS+lduU7p1/zLKufqd9= FE6lwXuadb1fXuCcjK1jUcjPv05VVMXL1c1TEbR0+pnyN/8Ar3Hcf/nK/wDF27gPhfROE9Ir0/Q= 6qqseq5NczVXFXX64dM5JX7NrX+Oou3rduZ1yvbtVRHpab1dNyq5VRHqWdFM0xREvN72o5+H7qe= 9i4uXes2cnVbVF+iiram5T2Kek+nxl3/3U+rano/BWnX9Lzr+Hdr1CmiqqzX2Zmnydc7fsh5Lxd= quJpPulb+rZFyJxsbU7d2uqJ3jaKad5bE8b6BwvzA0HHxNRzoqxqbkZFquxepid9pjfrv5pl35O= rddi5VHrUbc1rddNymJ97a/8kOFOJ+NtR1DWZ4jzdOs9qm3kZNFUzcvVRETFP1RGz2fSOWepYGX= j5NXHmtX67VUVTFXhX9Exu4/lDl8N8LcQ8Q8D4ubFEY2XRcx5vXI3u01WqJnrG0TO+7lMvlzw9l= a1Vqs8T61Rcqu+V8nRqMRbid99ttvBpysqq5cn3qn7emyxappojXufv7Ye6Ms26+Wt67XTvVay8= aaJ9G96iGHO/wDQnlf1a3+6vuhcrFucscqm3kWqp99YvSK4n/v6Hw52ZOPXyWyqKL9qqv3tb2pi= uJn+S58aJ3b3+f8AptuTH6f8Gn4D7t80AAkosooAIEosoQABIJPgqT4Aj649ublyI26Q+cdZ29j= kMa35O39M+KtdyrUPrHSNo8IJVJHHvcoAMgBYABQASVSUWUQAACQkWEAEABkAAABAAjNKmMwsjC= WUMdkZ7JsisRdiRZQBSABFACFAEWBJVKvAVKvBgsyjXMs0mEZSiMmMiykwIM6Y2hjRT16voyphJ= ElUlkxRJUBA2EV95RZR0Q0QAAAIAAv2ABYHaOCuPeJuEbn/AMI1G5TYmd6rFfxrc/8ADPTf6XVx= ruW6LlPbVG4bKa6qZ3EvcLHujdeosxTe0HAu3I8avKVRv+pwfE3PfjPVrNVnDnH0uiqNp8hG9X6= qp6w8qnxRyUdLxaJ7u1vqzL1Uamp9s3KyM3Krycu/cv3q53qruVTVVM/XL4g7oiIj05dzM7kSfF= UlRnbvXrdMxbu10bzvMRVsz99ZXyi79uXxGPbH4Zd9UMrlddyZmuqqqfTVO5brrt1dqiqaZ223p= liLqE3Mv36PbjUNbwcXLvVzau36LdczV1imaoierZmnkly7p2mM27TPjvGX/wBWq8TMTExMxMTv= EvvObm7/AOmZHp/zk/i4cvEuXpjsr7YdWPkU2991O5blafc4P5Y8JX7VvVLNGPRVVd2uX+3crqm= PCI3mZ8PM1A4g1i/qmv6jqdFVyz78yrl+aIqnp2qpnb9W+z8F7Iv3Y2u3rlcR1iK65nZ8mGF06M= eqaqp3MssjLm9EREaiFrqqrmaqqpmZ6zM9d1t3blure3XVRP0TsxR6HbTMamPhybmGVVddVfbqr= ma/HeZ67s6cnIppimm9ciI8I7XR8gmIn5haZmPUS+lzIv3KezXdrqp9E1dEuXr1dHYru11UxMdK= p3YJPgvbETs7qvykgKnr7AAJKLKKACBKLKEAASCT4KtFFVdcUx13CZ17fbCtdqrtz4Q/cxooiii= KI8zJXHcq7pElUGtABkALAAKACSqSiyiAAASEiwgAgAMgAAAIElWKSygAYaZwAGlRJUNLLEXZNl= 0gAml2AIuwBJUY1z02ZT4PnV47pMsqYQBgzJRZRFgTbdWVMLEbSSI2hQZ60mxJVJUQAAAH2lHJz= oeq/JZ+3T+KfAWq/JZ+3T+LXGZY5QkY13i40cl8Bap8ln7dP4nwFqvyWft0/ieZY5QeNd4uNHJf= AWqfJf8A30/ifAWqfJf/AH0/inmWOUL413i40cl8Bap8ln7dP4nwHqnyWft0/ivmWOUL413i40c= l8Bar8ln7dP4nwFqnyWft0/ieZY5QRj3eLjRyXwFqnyWft0/ifAeqfJZ+3T+J5ljlDLx7vFxko5= OdC1T5JP26fxPgLVPkk/bp/E8yxyhjOPd4uMHJ/AWqfJJ+3T+J8Bap8k/99P4nmWOSxj3eLjEly= k6FqvySft0/inwDqvySft0/ieZY5QvjXOLjByfwDqvySft0/ifAOq/JJ+3T+KeZY5QePc4uMHJ/= AOq/JJ+3T+J8A6r8kn7dP4nmWOUHj3eMuMSXKfAOq/JJ+3T+KToOq7/6JP26fxPMscoPGu8XFjl= PgDVvkk/bp/E+ANW+ST9un8V8yxyg8e5xcXKOUnQdW+ST9un8U+ANW+ST9un8TzLHKDx7vFxg5P= 4A1b5JP26fxPgDVvkk/bp/E8yxygjHucXGJLlPgDVvkk/bp/EnQNW+ST9un8TzLHKF8e5xcUOU+= ANX+Rz9un8T4A1f5HP26fxPMscoPHucXFjlPgDV/kc/bp/E+ANX+Rz9un8TzLHKDx7n4cVKOV/g= /q8/+Dn7dP4n8HtY+Rz9un8TzLHKDx7nFxQ5X+D2sfI5+3T+J/B7WPkc/bp/E8yxyg8e5xcUjlv= 4Pav8in7dP4p/B7V/kc/bp/E8yxyg8e5xcUOV/g9q+/8Aoc/bp/FynD/L3jDX67tOk6LcyZtRHb= mLtFMRv9MzCTm2OUHj3OLqz92Fa7NPbq8Z8HdrXJfmR5SO3w1ciP6zZ/O/b3Qcw46fwcufeLX5k= jPxucNV3Hva9Uy6HI75PKDmJP8A5cufebX507oOYvzcufebP5jz8bnDn8S/r9WXREd87oOYvzcr= +82vzHdBzF+blf3mz+c8/G5weJf4y6EO+dz/ADF+blf3mz+c7n+Yvzcr+82fznn43OF8S9xl0Md= 87n+Yvzcr+82fznc/zF+blz7zZ/OsZ+Nzg8O/xl0Md87n+YvzcufebP5zuf5i/Nyv7zZ/Ov8AaG= Nzg8S/xl0Md87n+Yvzcr+82fznc/zF+blz7zZ/Onn43OFjEvcZdClHfZ5P8xfm5c+82fznc/zG+= blf3mz+dPPxucHiXuMuhDvvc/zG+blf3mz+c7n+Y3zcufebP5zz8bnC+Je4y6EO+9z/ADG+bdz7= zZ/Odz/Mb5t3PvNn855+Nzg8S9xl0Ed9nk9zG+bdf3mz+dO57mN827n3mz+c8/G5weJe4y6GO+d= z3Mb5t3PvNn869z3Mb5t3PvNn855+NzhfFvcZdCHfO57mN827n3mz+de57mN827n3mz+c8/G5we= Le4y6EO+9z3Mb5t3PvNn86Vcn+Y0R14bufebP5zz8bnB4l7jLoUo753P8AMb5uXPvNn853P8xvm= 5X95s/nPPxucM4xbvGXQpWHe55Qcxfm5c+82fzndBzF+blf3mz+dPOx+cL4t3jLog753Qcxfm5X= 95s/nO6DmL83Ln3mz+dPOxucL413jLoWw753Qcxfm5X95s/nJ5QcxPm5X95s/nXzsfnB413jLoY= 733P8xfm5c+82fzndBzF+blz7zZ/OnnY3ODxrvF0PZNnfe6DmL83K/vNn853Qcxfm5X95s/nPOx= +cL413jLoQ75PKDmL83Ln3mz+dO6DmJ83bn3mz+c87Hn/PB413jLog733Q8xPm7c+82fzpVyi5h= 0xvPDte39ZtfmSc3H5QsY13i6HVLGfB3meU3MH5vV/eLX5k7peYPzer+8WvzMZy7HKGcY9zi6MO= 8d03MH5vV/eLX5jum5gfN6v7xa/Mnl2OUMvoXOMujju/dNzA+b1f3i1+Ze6bmB836/vFr8x5djl= B9C5xdGiOrOno71HKHmHMb/wdr6/+otfmXuh5h/Ny595s/nZRmY8f5oYzYucZdFTZ3vuh5ifNy5= 95s/nO6LmH83a/vNn86+Zj8oTx7vGXREl3zui5h/N2v7za/OxnlFzE+btf3mz+ZPMx+UL49zi6I= O990PMT5u1/ebX5jui5ifNyv7za/MeZj8oXx7nF0Qd77ouYnzcr+82vzB5ljlB49zi5UB8G+oAA= AAADcgAbkADcgAbkAOvok3IAG5AA3IAG5AA3Ie09oG5AA3IAG5AA3IAG5AAAAAA3IAA+uLYu5OT= axrNM13LtcUURHnmZ6NmOXnDtrhvhyxh9mn3zXHlMiuI/lVT/ANNnnPIrhWMnIniPMtb27UzTjR= VHSavCZ/V1e0Rvuou0G0AAbAAABsbAAABsbAAAAAAAAAAAAAAAA+Vyd5+hnXO0PmDEZJsCbQxmG= QDGFWU2BNkZAMRZhATZGQDEmF2AYTGz8eRX2qto8IfryKuzR08ZfimkGExEsZjqzmEBgSymEmA0= w2fTHt9qvfzQx8+3nfus0RRRt6fEGW3RJZTCAxGUxCGxJhFDYxmEZ7JJsYi7BsarAMQAAAAABna= tXbszFq3XcmmJmezTM7RHnXyN7yPlvJV+S37Pb7M9nf0buW4Jz40/iPGrrn+JvT73u+iaa/iz+y= XffemFcuVcC+VtdmLfvqLu8RHlYqnpv/u9kHl13GybVFNd3Hu0U1fyZqomIn6icXJi9Fmce95SY= 3ijsT2pj6npeHl4fFGpatgXLlFGLiZFOViRM9It2527Mf8ADMrl6liZmkZPF1qq3RlYtq5g0UxP= +tMz2KtvoiafYo8z965Plos+973lZjeKOxPamPqYeSu9iqvyVfYonaqrsztTP0vS9Nz7FrRMTjC= 7XRXlWbHvKaap6zXvExVt/uxW/PxTptMY+No+kXLNVzWsj351riIimrrFMz5tpB59j42Rk1TTj2= Lt6qOsxbomqf2P02sO3Tj5fvujMtX7VMTTRFjenrMR8eZmOzHX0S7do2PqFHCGTp2i1xTq9rMqj= Kps1fxtVvaOz2Z8dt+14Mpp1S1w5xFa1q9TXlRhWY2mae3H8bb2iraN9/rB0mzg5t615W1h5Fy3= H+vTamY9sJYxMq/G9jGvXY32+Jbmrr6Oj1f4t63pWRpFrVLmHbs0x/kuTbt2Kaoj43biaJ8+/jL= gtR1ScbhPWb+lTTiU39Voppi1cirs0zTXPxao+qOsA6Fdx79q75G5ZuUXfDsVUzE7/U/Tb0+/by= LUZ2Lm2LVdW01RYmZ2+iJ23l3+xk4tzUdBy825Z9+XtKuRbvXtpjy0VV025q+npT4vwYtjizG1G= xVrN+5TjVZVPS/VE9qevWnfrt9WwOmVYV27mXrWFYyr9NFcxH8TPb2jwmYjfafofKcfIpv+QqsX= Ivb7eT7M9rf6vF6DgYN2/l67k42RqNyv3/VTVj4FdNFzbtT8aapiejk9R8hb4ooixXbt6je0mPe= 1y/VTVPlu1XHWdojtdIjfbzIOj6ToXb0bWcrPxsmzdxMaLlntUzRvPbpp6xMdeky4vPxbNF2zbw= /fdya6ImYu2exPanximImd4+l3vEx+I8bgjiKNduXIoqx6fJ0ZFW9yZ8pR1jfrs+tm7Zp4hxYi7= Zt5lWk004ldzaaabvY+L49N99tt1Hnd3AzrNM1XcLJtxEbzNVqqNo9Pg5TB4evapft2dKpya5jG= m9dm/YmmmJijtTFMxvvvt08N+jteBj8T2OF+Ivhuq95GcSezF+d65ntR1pmfM/TpeXdt69pWPZy= q6PK6LVTTTTcmIqrmxPZj699tgeb04GdVfrsU4eRVdo/lURamZj642cvwpptrIr1S3nY89uxh1X= Kaa42mmqKqY8P1uxaDpWqe8My9lX9YuZcZXYvY2Lcim9G0RMVVVzEzt18Poclq1NujiHUaon41e= iUTVVNUVTVV8XfeYiImfp2NDyyImZimImZ9EPvewc2zb8rew8i3R/SrtTEe2Ydl4Q06NN1nSdR1= ScWnGy4qmxNdUVRFUTMR2o83WHOada1/FydUv8TXqqtLqtVxV5aqJouT/q+T/wCgPPacLMqteVp= xL9VvbtduLczG3p3ZU6fn1Wou04WTVbnwqi1VtP69nbdW1K7Y0XhfFnJrow6rc1ZFNFW3ap8pMT= E7ebbzObt2OKLvGljKwb01aTM0+Srpqj3vFvbw28N/2oPMK6aqK5orpmmqmdpiY2mJYuV4w/nVq= nX/AMVc/elxQAAAAAADl+EdFv6/r2Pp1imfj1b3Ko/1afPMuI2326b+hsByZ4YjRtDjUMq3tm5k= RVPajaaKPNCju2kYGPpmnWcHFtxRZs0RRTH1ed+ogUAAAAAAAAAAAAAAAAAAAAAAAAAY1z02BKt= qpYKoMRlMQxATZQGIylNgTZJhQERdjYE2TzsgGKTttvPmZbPjfr2jswD4XKu1Xv5mDI2BhMMZpf= TZAfKY2R9Zphj2O1O0Azxrfaq7c+EP0lFMU0xEKCJK7EgmyMkBJhjMMgGJKzCAbAA1UAYgAAAAA= Au8oAAAebbzLvPpQAABd59KAC7ybygCxMx5zdAF3n6Zh+3Rr+n2c2KtTxasrHmJiqmivs1U7x4x= 9MPwgOyV6vo2Do+bh6PYzar+ZEUXb2T2Y7NH9GIiZ+j2OtgC7z6ZTzbAATIAyoqiLlM109qmJiZ= p38Y+t2fE1PhXEz7epY+BqMX7VMTTj1TT5Lt+nfffb9TqwD7Z2TdzMy9lXp3uXq5rr+uZ3l8QAA= AAAB+jT8S9nZtnDx6Jru3q4ppiPpB2/lDwvOvcQU5ORb3wcSqK7noqqjrFP9zYiimKaYpiIiIja= HB8E6BY4d4fx9PtU73Ip7V6vz1Vz1mXOsgAAAAAAAAAAAAAAAAAAAAAAAAAAYyylAY7JMMtk2Bi= LsAmyKs9QYizCAmwoDEXZAJhFAY1T2aZl+Wqe1VMvrfneezD5TAMdkmGR4gwJhkkgx2fbHo6dqW= Fumaqtn6YjaNgSYYzDMBgMphiBMIoCIuwDEZJMAgbSA8f7nNb9YYnsk7nNb9YYnsl7nsbA8M7nN= b9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsb= A8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYn= sl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7n= Nb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9Y= Ynsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M= 7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7nNb9YYnsk7nNb9YYnsl7= nsbA8M7nNb9YYnsk7nNb9YYnsl7nsbA8M7m9b9YYnsl2vlty5r4e1SvUdSu2si9RG1jsx0o38Z+= v8XpGxsAAAAAAAAAAAAAAAAAAAAAAAAAAABMAgAAAJsksgTbCYJhlMIKgTCAbIyTbcECY2ASYY1= z2aZZvhdmapB8/HxRlt0TYGMwjNPEGBtv5mUwyt071byDO1R2ad/OymFAYjLZNgQ2gAYzCMyY3B= gLMSgJsKAx3F2AciAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAkwoCCpMAAAACaSYRkCsJhGe3oQGJKzCT0gGFydofNlVO89WOwJMMdpZoDDZGcwm2wM= fHo+1NO0bedhap876gxmBkkwCAAbJMKCMRlMJsKhMQAMZhGaTAMRdpAfvAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAATZQEF2SYAAARQRNnzuTt0= fSqdofGeorFNmUwAxSWWxMAwNt2UsqI2A22joKAgTACGygMRSYBAANkUEYi7AqBuA/aAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAmygILsx= r6QDCud+jHZQGJMLsAxFNgSI3VYhQYi7AITAAmwoCBMAIbKAxGW26TAIC0x2p2jzgm30SP000xE= RGwDIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAACYAYVdWUpMAwmEZpMAxFmEBNiI6qyjbYGIsx6EAABJhGQDEXZNgCYAEFJgEABJfWzRtHa= lhRT2p28z9EdIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAABJAkARJhGSBtEmGWyCsRlMJMAIAEwjI6SDEWY2QA23AEmEZEgxF2QBNlZ2= 43ncGVqnan6ZZgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAABKLKAAAAAAAmyMkESYTZlsgrEZbJMAHSUAJjZGW5MAxCYAElQE26vtRG0M= Lcb9X0AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAA2RQECYQFAAAARQRjsMk2F2xmBlMIDEXZAVJgATYpiZnZkyop26gyiNoAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAABJgU2BAAAAAAEmFBGIyTYVjMCgFMbyzSmNoUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAkAQU2BAAAAABAiOoo= QACgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAABsAJIqTAmwAUiFAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADY2AAAAAAAAAA= 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= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAEAmTdwfGvE+m8I6LVq+rTd= jGprponydHaneqdo6Py8I8c8M8VTVRo2o0Xr1NPaqsz0riPTMM4tVzT3RHprm9RFXbM+3Zt4O1D= UbVuZ3GfD3HWsWsPVq7mNa1HIiMe9TFVExFyqIj07R9EtgeS3GGbxtwfOrZ+PZs36MiuxXFreKZ= mmKZ3iJmf6TsyenXce3FyZjUuPG6jbyLk24idw7xvC7uK4p1ixw/w9m6zlUTXaxLc1zTE7b+aI3= +mZhq3pmpczuZuvZ1/Q9Qybdq3VNUURe8nRapmelO8R1nZwPQbc7m7XrhXhfmrw1VqWq6xrVFqx= Rg1xRcuZnbpormqnaZiY2jwnq7dyH4j1TL4V1bUeKuI8TUIx8mIpv03KZotUdiJ2maYjz9QerwO= lV80+Aqb1NqOJcGuqZiI7Ne/X0Ms7mhwNhZl7EyuIMS3es1zbuUzV4VRO0wDuZu4Thnizh7iSi7= Vouq4+Z5L/ADkW695p+txuqcyOCNNybmNmcR4NF63V2arflImYkHbImN9l3eF8zuN9Ty+JuH73C= HF+DiaZlWo8pTXdojys+VmmZjemfRs9BzuZPBulZVen6lr2LazLG1N6iausVbdQdzHBcMcW8O8S= +UjRNWxs2q3G9dNureafrc6AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAigPK/dRfouv/1i1+9DyT3K0/8AzNu/2dd/eoet+6= i/Rdf/AKxa/eh5J7lb9Jt3+zrv79D38Wf7trfN5cf3jQ6Dx9/PnX/7SyP+bU2P9yf+jTI/tK7+5= ba4cffz61/+0sj/AJlTY/3J/wCjTI/tK7+5bdnVf2Gn+Tl6T+31fzdm58WLuRyl161ZiZrmzRO0= eiLlEz+yHl/uRtW02xi6xp2RkWbOVN2m9EXKop7VMxEdN/HrEtgM/FsZuHew8mjylm9bm3XTPnp= mNpeA677nfJjU7t/QNfixj1zNVNuuiYqtx6N4nr+x8o+uesczcrFv8vtbt2MmxcqjFmdqK4mdt4= 9DUuznZNnlLfwrVVVFjJ1mPKxHSKtrUTEe2N3tPCHJLXNMyM6c/iGi5ayMKuxERFVW1UzTMTMTP= 0P3cOcj6LfAeo8N6zqNFV2/lRkY+Rap38lVFMR4T4+APFOGMKJsYU3eXGdqEzXTPvuKsmKa438Y= in4uzsXD3DGkcS8/dZ0XVLNyvCnOyfi03JomNqqtusfU7jg8lOM8Cu1axOMIpx7VUdmiIqp6RPo= 3l2rg3lZn6NzRz+L8rVbV23fvXblFumj40zXM+M+bxB4hgVXOE+P+KMPQ7l2xbx8DKpt/HmeztR= 0mZ8+ztHufuXHC/Gmi6hn675XJv2r0URbovTR2InfrO0+fZ6FpvKK5a5l6nxDnZtnI07Ot3bddj= s7VTFdMRMOqZ/ufNWx8+9Oh8TTaxa6t4pmKqaojzRO09frBwHPPh3S+FuM+E9I0i3XaxLViJopr= rmqYmb9Uz1n6Zfg5gajwvqXG+bZ0zgnJ1nN7UVXq4yb29yqKYiaoponpHh5nfMnkhrOVPD3vjXr= VdWm0zTerqpmqat71VfTefRL6cT8jdSucT39Y4c4gjCi/G9VNVMxVTPniJjxjoDzvkPdvYvO7Bs= UYN3S6LvlqbmJXNe9MRbqmKZ7XXpMR4+ht3Hg8P5dcndc4e4/wuJtS1qxl+QmubkRE9qrtUVU/3= y9wAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAABAeWe6i/Rdf8A6xa/eh5J7lb9Jt3+zrv79D1r3UX6Lr/9YtfvQ8l9yt15nXf= 7Ou/vUPfxf8NrfN5f+I0Og8ffz61/+0sj/mVNj/cn/o0yP7Su/uW2uHH38+tf/tLI/wCZU2P9yf= 05aZH9pXf3Lbs6r+w0/wAv9nL0n9vq/m9d2jdqjrvGPMjVOZGo6HoWr5NdyMmuizZoppiIpjzR0= bXQ1Y5df/crkf1m8+UfXPzZvHPNjgTWMWeIb+R2L29UWci3TNN2mNt9p2+mPB6JxfzK1yrV+FMj= QM/TcfB1OxauX7ORcoiZmbm1URv16dY6Pxe68yMP4E0rFqronLm9NUU7/Gijbr+2YeT6hbvWsXl= /Tf37U26pjf8AozlVTH7NgbeapxBo+kY1q9rGqYeDFdO+967FMT9W/mcZZ494Qy65x9O4n0fJy6= qaptW6cqme1MRvt0nwa5abpt3mfzmv6drWfet2KLc9mInfs0UbbUU+jxmXy1HhnC4S54WdDwK7l= zHtUdqmbnjPatTIPUOAOY2rX73Et3ijXdJt4uHERjVUXbe1FU1VRETt9UeLivc/8yLuVl6pY4t4= lsUzVcojEpya6aJqmZmNqfDfzOm8n+HMDii7xppuoeUizFNF6OxO09qm5XMJ7nzgfReKNQ1DJ1W= q9T8G3Ldy12K9vCZnr7AbF5HMDgjGyLuPf4r0e1dt1TRXRVlUxNNUTtMTG7j+YHE2Pc5X65rXDe= rWL9dnGmq1fx7kVxTVvH6mu3GF3l/e4s1SjB0TW8+v3zcqu3LdzpNU1TM7RE+G+7iuBNSv4+l8Y= 6RaiacTJ0m5cqpu0fHiaK6ez9X8qQbA+5r4j1niThHLyNazq8u7ayezRVVERMRtM7dIeqvFPcj/= AMydQ/rf+EvatwUIAAAAAE36+Kz4Ohc3eMK+HtOt4eBdinUMid4n+hRHn/uB30a2d43F3rWv2He= Nxd61r9ibGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8b= i71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcX= eta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71= rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta= /YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7= DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/Yb= GyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2= TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY= 1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGt= neNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7= xuLvWtfsO8bi71rX7DY2TGtneNxd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneN= xd61r9h3jcXeta/YbGyY1s7xuLvWtfsO8bi71rX7DY2TGtneNxd61r9gbGyYCgAAnnVCR5X7qL9= F1/8ArNn9+Hj3uYsvGwuZVy5lX7diidPu0xVXVtG/ao6Npdf0XTddwKsDVcS3lY1UxVNFcbxvHg= 65PK7gaY68PYn6qHqY2bboxqrFUT7eRk4Ny5k03qfs1v434A4qyeK9WzsLTJzLGRnXrtuqxXFW9= NVczE+Pol23lJxxnct9Oq0DiPhzOtYt3IqvTfpp3miZimJ6bdfCPPD1zuq4MoqicbT8jDnfffGy= rlrr/wAMw+lXL6zat3KMHXdYtRXG3Zv5NWTRH/DcmYdFzqVu7ai1cjcf0/7c9vplyzc+rROp/q5= 3hjibROJMOMrR9QtZNHnimfjUz6Jhr7xPyW4+y+L9Q1fTbuDZov36rlquMyaK4ifqjo9Qs8rox9= Tq1HC1KMHOpo/i8zEtRZqmd4nau3TEW6qZ+mHduH6tapxpsa1bs1X7c7RkWpjs3Y9PZ8Yn0vJu0= UR+pO4evZrr1q5HtrzpHIXjHUtTsXOJ9Ws+96Ko7dUX6r1cx6I38N3ceaHKrWNX4k4bvcO28SjT= tKsW7VUXb3Zq2pr36Rt16fte1UrLS6GsHNjhXTNI44r1PQOMtN0nUuzTVexr96bdVu5t1mKojwn= p02dQ4Qt6pqfNvBt5WpWdXzLkzTOTZuduir+Lq8+0eDYvjLlFwpxTrt3WNRt5MZN2mIrmi7VETt= 9G79vBXLHhLhLUJz9JwKqcrsdmLt25VXNPTrtvPTf6DY6lyW5ca9wrrPEGRrnvX3vqNEUWvI3e3= P8AKqnr0jbpMOoaZyh5icP67dq0PV8S3p12/E3q4vdiqu3v13jaeu0y9e5wcRX+HuDr9eDTdq1D= L/yfEm3403KukVfqeSXNe43wOHMvSNLsaxqV7IibVzIrsX7ldmumY7XYmYmYid+u/h02ddnDqvU= 929OK/m02au3W3yzeTfHml8RZubwtquD5LKuVVRVXXFNUUVVTMRMTE77b+L58P8meO8e7rd7UKt= Nru5+nXcemqMjfe5VVRMb/ABekdJYcAZXMXBz7tdWBxHN6MWum3XmW7k0WoimfNX8Wdp+NEeM+E= dXO4nMDmRbzsjU6uDtRrpu2KbU2qse/NEVUTO1dNMR07Xanf6oba+nV0zMRVE/zaaOpU1REzTMT= /B3XkFwdq/BnDWXgazONN67kdunyFztxtt6doek+Z03lLa1P+C3vvVrWZZzM3Ju5FdrI33t9uqa= opiJ/kxG/g7jEdHDco7app/D0LdffTFX5WAGLMAAAkH5NY1HG0rTb2fl1xRZs0zVM+n6Gr/FWs5= Gva5kajkz1uVT2Kd+lNPmiHf8AnnxVTl5UcOYdc+SsTFWTMeFVXjEfTt0eVpIAIAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAANwAGQAAAAAAAAAA= AAAA/BrOlafrGHVhanh2srHqneaLkdN4Z6VpuDpeJRiYGNbx7FHSmimOkP1yQRVOtbY9sb3o2jw= mOhERttsoMtAAAAAADrPMfiS3w1w5dyoqj31c/i8emfPVPn/VG8uyVTtEz6I3a4c1eI7uv8TXqY= 7VOLi1Tbs0+naf5X1ySOqZF65kX7l+7V2rlyqa66p88z4vmDEAAAAAAAAAAAAAAAAAAAAAAAAAA= AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAf/Z" width=3D"819" height= =3D"1119" alt=3D"Imagen que contiene Interfaz de usuario gr=C3=A1fica &= #xA;Descripci=C3=B3n generada autom=C3=A1ticamente" style=3D"margin-top:-34= .7pt; margin-left:-87.3pt; position:absolute" /><img src=3D"data:i= mage/png;base64,iVBORw0KGgoAAAANSUhEUgAAAUIAAAAzCAYAAADipAFMAAAABHNCSVQICAg= IfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAABjBJREFUeJzt3VuoVFUcx/H/7gZB51UIfJLywc= AH41AQQg+JhISIJRKGkiARJlSUKXkpyVSKSsw0y0S7iFQGXtLECi0viRZU3vJSKpVySk0953jUv= j2s/+A6a/bM3nO80+8DMrPXfQbO3zVrX5aZiIiIiIiIiIiIiIiIiIiIiIiIiIiIiNQHbKGzdk+/= H9gKnAJagXXAaODdpH7NcsALUbutwNCk7sKk73klxtsP2Aa0ASeAZTXKdQNmA7uAY8CaKG8FcNL= HvKor7Sd1RgA/eXungQPApKRMvT7L1D9AtQlFYxOREoAm4GX/w9oI9PD0XcCvwEhgAPAGcAR4L6= lfWM7zAPYCTUn9wcDfwMCS492VExAWJGUGAfs972fgdaDZ8z7z9FnAO/5+WSPtJ331BP4CzgDPA= 48A/xACab+iPkvWH5UzpsNlvi8RKQkY6H9cn0ZpHcDspNxjwPwkrbCcB8IfCTOipTn97yw5zmeB= NUBfYBph9kRcH+hDCMTngLlJ/W6EWRdAd6DZ37d6XmH7OWMa52VO4EGeMEOGMCMu6rNufT9eC0w= t8x2JSBfVCIQ7gIPAQwV1C8t5INwATPfA+WSSXzYQ9k+Ov/Nxb4vS1nnaNzn1x3re2SitYnyZ9n= PaHB61scrTdhOCft8SfRbVbwKO+/d2BPgWGFXm+xKRBtQIhPcQ1sragVVA3xp1C8tVAqG/Xw0cB= npF+TuT8ouAFqBnwbgr65uz/LjZxwHwB2FG1wK85vnzPe9M1Ma/nja/qP0649gWBbND/vlGl+2z= oP4rVDtDslYrIhcoLxBGeZMIM75TwOI6bdQslwTCJsJa4foov9SMMKfPFmB/dDwtChbDgbf9fQd= h7W1J5TiqUwlKS4rarzOOZkLgjQPVm55X2Ge9+p7fB3gC+AQ4GpWpO1sXkQbUC4RRmYWEdbfVBW= 1VlYsDoR8PIpwQmOHHDQdCwomHE8CQKG2Rf45zUdpxT1vM+bPUcVCqSE8CVbVfZyxPEWZ1j0cBr= QMYUqbPevVz+moG9nmZqlmsiHRRXiAkf4a0nvBzs6mRcmkg9LSphMta+jcaCAlnp1uAsUn6vCjI= 9Pe0g368Apjo7894XlNUflyJ9rfSWYd/tg5ga1S3zfM/LOqzqH6Nzz/G82fn5YtIcN1FaKOZ6jW= 6Fn+9uQvlOsmybLyZbTCzVxsZFNDNzGaY2Zwsy6YTzsR+DIwws7VmRmVcSdV9Zva+mbWZ2Q2ENc= rbPa/NzBYVtZ9l2Z1ZZzeZ2X1mdqOZXe+fa4WZHfR2T5bos6h+nq/NrN3MPij1pYlIMeAln2FsA= Hp72gnCWt5zhDWqKYSfsxuTuoXlgJmEM6G9k7pNwC80cE0c8CXVWqP8zZ62jbBO2E4421q5PnKZ= 578FzPX3K8q2nzOeZwhLAa2En7ijCeukR4F7i/osqk9Y92z372k6cDfwOTCn7HcmIgWofWfJEv8= j3EdYmD9GuJ6tV1K/bjngh6T99BKVB4A9SdpHhJ+mzUn6PPLtjcr0AL4iXH7SAWyn8zpiE/CFB5= 5WYHkj7df4DmcBv3t/pwh3iTxaps+i+sAwwn80p/3fHmByvfGIyDUIv4NCRERERERERERERERER= ERERERERERE5LLi/GOdKlYm+aeivIUl2utHuAXs+KUbtYjIRcT5zZfw28B6JPkj/Ha1BUD3Eu0t= Jdxqd7aorIjIVYPwSPh2op3eorxewOYG21ukQCgiV1pDj+HKsmy9mW0xs7vSGaGZPW1mdR/GmqO= 9wfIiIlce4ZFV56jetzhvE6T+/nO6zZ+Ish14OMqfpxmhiFyT/PFPh6LjMSRPSfZHSh0ANhGepj= yWsC/xkcoaogKhiFyzgAl+0mSiH6+h+pmA073MgChtpqdVdpNTIBSRK65Lj+rPsmyKmR0yswc9A= J7LsmxLUuw2f+2I0pb5661d6VdE5FK4kD1LVprZHWb2opnl7WpX2U9jcJR2i792aVtOEZGrCtDN= L7LeXSf/T8I2mZMJ+2psAn6Lyiwn7N077PKNXETkIvKLomfWyR8K7PA9NtoIGyVVts9cnNypMtL= PMH9/+T6BiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiIiMj/1n9FrJHJxu4OqwAAAABJRU5Erk= Jggg=3D=3D" width=3D"322" height=3D"51" alt=3D"" style=3D"margin-top:-9.2pt= ; margin-left:258.45pt; position:absolute" /> = </div> = ;En la tabla 3 muestra las medias y desviaci=C3=B3n est=C3=A1ndar d= e las preguntas realizadas a los 19 estudiantes. Referente a la pregunta (L= e gusta la materia de historia) se visualiza una M =3D 1.32 y DS =3D 0.47, = demuestra que la mayor=C3=ADa de los estudiantes si les gusta la materia, y= su desviaci=C3=B3n est=C3=A1ndar baja indica una constancia considerable e= n las respuestas. Para la pregunta (M=C3=A9todos de evaluaci=C3=B3n preferi= dos) indica la M =3D 2.11 y DS =3D 0.93, muestra la preferencia por los m= =C3=A9todos de evaluaci=C3=B3n escritos del 47.4 % y proyectos con el 36.8%= , en la desviaci=C3=B3n indica una variedad considerable en las preferencia= s. Seguidamente en la pregunta (Nivel de comprensi=C3=B3n lectora) refleja = la M =3D 1.74 y DS =3D 0.73, los estudiantes indican que su nivel de compre= nsi=C3=B3n va de =E2=80=9Cbueno=E2=80=9D a =E2=80=9Cmuy bueno=E2=80=9D, la = desviaci=C3=B3n presenta algunas diferencias en la autopercepci=C3=B3n de l= a habilidad lectora, pero en general hay consenso en que, es adecuada.</spa= n> En tanto, para la pregunta (motivaci=C3=B3n para profundizar en = historia) muestra la M =3D 1.05 y DS =3D 0.22, la media es cercana a 1 indi= cando que, casi todos los estudiantes est=C3=A1n motivamos y su desviaci=C3= =B3n extremadamente baja refuerza la opini=C3=B3n casi un=C3=A1nime. En la = pregunta (Opini=C3=B3n sobre la importancia de aprender historia) la M =3D = 1.16 y DS =3D 0.37, la media que la mayor=C3=ADa considera que aprender his= toria es esencial, y su desviaci=C3=B3n indica que la mayor=C3=ADa de los e= studiantes est=C3=A1n de acuerdo con la importancia de esta materia en la e= ducaci=C3=B3n. Por otro lado, la pregunta (= Frecuencia de navegaci=C3=B3n en internet para investigar temas hist=C3=B3r= icos) la M =3D 2.11 y DS =3D 0.73, con una media muestra una tendencia a in= vestigar temas hist=C3=B3ricos con una frecuencia moderada, mientras que, l= a desviaci=C3=B3n indica una dispersi=C3=B3n considerable en la frecuencia = de uso de internet, con algunos estudiantes que lo hacen frecuentemente y o= tros que nunca lo hacen. En la pregunta (Participaci=C3=B3n en el aula inve= rtida anteriormente) la media de 1.47 refleja que m=C3=A1s de la mitad de l= os estudiantes han participado en aulas invertidas. Seguidamente la pregunt= a (Efectividad del modelo de aula invertida) la media de 2.26 refleja que e= s =E2=80=9Cefectivo=E2=80=9D este m=C3=A9todo, aunque no necesariamente =E2= =80=9Cmuy efectivo=E2=80=9D, la desviaci=C3=B3n alta indica la considerable= variedad de opiniones entre s=C3=AD y otros que no.En relaci=C3=B3n con la pregunta (Claridad de los materiales previ= os en el aula invertida) la M =3D 2.26 y DS =3D 0.99, las estudiantes menci= onan que son =E2=80=9Cclaro la mayor=C3=ADa de las veces=E2=80=9D, su desvi= aci=C3=B3n muestra la claridad de los materiales es un tema con opiniones d= ivididas, encontr=C3=A1ndolos m=C3=A1s claros que otros. La antepen=C3=BAlt= ima pregunta (Impacto de los conceptos previos en las actividades de clase)= la media de 1.79 indica que a la mayor=C3=ADa les ayuda. En la =C3=BAltima= pregunta (Oportunidad de interactuar m=C3=A1s con el profesor en el aula i= nvertida) la media de refleja que la mayor parte de los estudiantes tienen = m=C3=A1s oportunidad de interactuar.<ol start=3D"4" style=3D"mar= gin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left= :31.25pt; text-align:justify; line-height:115%; padding-left:4.75pt; font-f= amily:'Times New Roman'; font-weight:bold">Discusi=C3=B3n </li= ></ol>El objetivo de la presente investigaci=C3=B3n fu= e determinar la influencia del m=C3=A9todo de aula invertida en el aprendiz= aje de historia en los estudiantes de primero de bachillerato de la = Un= idad Educativa Combatientes de Tapi, tras el an=C3=A1lisis de los resultados, se refleja la signi= ficancia del aula invertida ya que, fomenta la participaci=C3=B3n activa de= los estudiantes, quienes, al tener acceso previo al contenido te=C3=B3rico= , logran un mayor entendimiento de los temas hist=C3=B3ricos abordados. El = estudio de Clavijo-Cortes et </span= >al. (2024) sobre el fortalec= imiento del aprendizaje con la metodolog=C3=ADa del aula invertida, se cent= r=C3=B3 en responder como el m=C3=A9todo puede fortalecer el aprendizaje si= gnificativo, destacando su capacidad para innovar y dinamizar la ense=C3=B1= anza tradicional mediante herramientas tecnol=C3=B3gicas, los resultados co= ncluyen <= span style=3D"font-family:'Times New Roman'">que el aula invertida tiene el= potencial de fortalecer su instrucci=C3=B3n, permite a los estudiantes inv= olucrarse en el proceso educativo y desarrollar competencias profundas en l= a materia. </spa= n>Por otro lado la investigaci=C3=B3n de la implem= entaci=C3=B3n del aula invertida como enfoque pedag=C3=B3gico en la materia= de historia, tuvo como objetivo mejorar el proceso de ense=C3=B1anza-apren= dizaje a trav=C3=A9s de esta metodolog=C3=ADa. El estudio combina el an=C3= =A1lisis sistem=C3=A1tico de fuentes bibliogr=C3=A1ficas con un estudio de = campo comparativo, evaluando el m=C3=A9todo tradicional frente a la clase i= nvertido. Los resultados se=C3=B1alan que el aula invertida promueve aprend= izajes m=C3=A1s significativos, aumenta el inter=C3=A9s estudiantil y hace = que el estudio de historia sea m=C3=A1s din=C3=A1mico (Guerra<= span style=3D"font-family:'Times New Roman'"> et al., 2024). A comparaci=C3=B3n con el presente estudio, se demues= tra que las metodolog=C3=ADas innovadoras como es el aula invertida tienen = el potencial de transformar positivamente la educaci=C3=B3n, de manera que,= incrementa la calidad de aprendizaje como la participaci=C3=B3n de los est= udiantes.<span= style=3D"font-family:'Times New Roman'">En contraste el estudio del enfoqu= e de aula invertida como estrategia en la ense=C3=B1anza de la ciencias soc= iales en bachillerato, esta investigaci=C3=B3n es de car=C3=A1cter descript= ivo, con un dise=C3=B1o de campo y modalidad de proyecto factible, lo que, = se traduce en analizar la realidad educativa y proponer una soluci=C3=B3n v= iable basada en datos recolectados, la poblaci=C3=B3n incluye tanto a profe= sores como a estudiantes de historia, tambi=C3=A9n aborda conceptos claves = como el uso de las Tecnolog=C3=ADas de la Informaci=C3=B3n y Comunicac= i=C3=B3n (TIC), al apr= endizaje invertido y las herramientas tecnol=C3=B3gicas aplicadas (<= span style=3D"font-family:'Times New Roman'; background-color:#ffff00">Anch= undia-Delgado et</span= > al., 2021). Se concluye que, la estrategia n= o solo mejora la ense=C3=B1anza en la asignatura, sino motiva a los estudia= ntes. Por =C3=BAltimo, la investigaci=C3=B3= n de Escobar et <= /span>al. (2024) sobre el mod= elo pedag=C3=B3gico del aula invertida en el proceso de ense=C3=B1anza y ap= rendizaje confirma que, el aula invertida permite variar el orden tradicion= al de la ense=C3=B1a en dos momentos claves: <ul style=3D"margin= :0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left:67= .56pt; margin-bottom:0pt; text-align:justify; line-height:115%; padding-lef= t:4.44pt; font-family:serif">= El docente ense=C3=B1a en clase mientras el estudiante aprende.</li>= <li class=3D"ListParagraph" style=3D"margin-left:67.56pt; margin-bottom:0pt= ; text-align:justify; line-height:115%; padding-left:4.44pt; font-family:se= rif">Posteriormente, el estud= iante profundiza los contenidos y ense=C3=B1a lo investigado reforzando en = aprendizaje.</li></ul>Este enfoque fomenta la c= olaboraci=C3=B3n, profundiza los conocimientos y la autonom=C3=ADa, haciend= o del aula invertida una metodolog=C3=ADa eficaz para el entorno educativo = actual.<ol start=3D"5" style=3D"margin:0pt; padding-left:0pt"><l= i class=3D"ListParagraph" style=3D"margin-left:31.25pt; margin-bottom:0pt; = text-align:justify; line-height:115%; padding-left:4.75pt; font-family:'Tim= es New Roman'; font-weight:bold">Conclusiones </li></ol><ul st= yle=3D"margin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"m= argin-left:16.86pt; margin-bottom:0pt; text-align:justify; line-height:115%= ; padding-left:4.44pt; font-family:serif">El uso del aula invertida en la materia de historia ha probado= tener un efecto beneficioso en el aprendizaje de los alumnos, potenciando = su entendimiento conceptual y sus destrezas en el an=C3=A1lisis hist=C3=B3r= ico, en particular en el estudio de fuentes primarias.</li><li class= =3D"ListParagraph" style=3D"margin-left:16.86pt; margin-bottom:0pt; text-al= ign:justify; line-height:115%; padding-left:4.44pt; font-family:serif"><spa= n style=3D"font-family:'Times New Roman'">El aula invertida promueve el apr= endizaje independiente y el trabajo en equipo entre los alumnos de historia= , facilit=C3=A1ndoles la creaci=C3=B3n de su propio saber mediante la inves= tigaci=C3=B3n y el debate. Aunque el aula invertida plantea retos en t=C3= =A9rminos de preparaci=C3=B3n de materiales y acceso a la tecnolog=C3=ADa, = sus beneficios en cuanto a motivaci=C3=B3n y desarrollo de habilidades la h= acen una metodolog=C3=ADa con gran potencial para la instrucci=C3=B3n de la= historia.</li></ul> <ol start=3D"6" style=3D"ma= rgin:0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-lef= t:31.25pt; text-align:justify; line-height:115%; padding-left:4.75pt; font-= family:'Times New Roman'; font-weight:bold">Conflicto de intereses</s= pan></li></ol>Los autores declaran que no existe confl= icto de intereses en relaci=C3=B3n con el art=C3=ADculo presentado.<= /p><ol start=3D"7" style=3D"margin:0pt; padding-left:0pt"><li class=3D"List= Paragraph" style=3D"margin-left:31.25pt; text-align:justify; line-height:11= 5%; padding-left:4.75pt; font-family:'Times New Roman'; font-weight:bold"><= span>Declaraci=C3=B3n de contribuci=C3=B3n de los autores</li></ol><= p style=3D"text-align:justify; line-height:115%">Todos autores contribuyeron significativamente en la el= aboraci=C3=B3n del art=C3=ADculo.<ol start=3D"8" style=3D"margin= :0pt; padding-left:0pt"><li class=3D"ListParagraph" style=3D"margin-left:31= .25pt; text-align:justify; line-height:115%; padding-left:4.75pt; font-fami= ly:'Times New Roman'; font-weight:bold">Costos de financiamiento </sp= an></li></ol>La presente investigaci=C3=B3n fue finan= ciada en su totalidad con fondos propios de los autores.<ol star= t=3D"9" style=3D"margin:0pt; padding-left:0pt"><li class=3D"ListParagraph" = style=3D"margin-left:31.25pt; text-align:justify; line-height:115%; padding= -left:4.75pt; font-family:'Times New Roman'; font-weight:bold">Refere= ncias bibliogr=C3=A1ficas </li></ol>Aguilera-Ruiz, C.,= Manzano-Le=C3=B3n, A., Mart=C3=ADnez-Moreno, I., Lozano-Segura, M. C., &am= p; Yanicelli, C. C. (2017). El mod=C3=A9lo Flipped Classroom. INFAD International J= ournal of Developmental and Educational Psychology, 4(1), 261-= 266. <a href=3D"https://doi.org/10.17060/ijodaep.2017.n1.v4.1055" st= yle=3D"text-decoration:none">https://doi.org/10.17060/ijodaep.2017.n1.v4.1055</a><= span class=3D"url"> Alarc=C3=B3n D=C3=ADaz, D. S.,= & Alarc=C3=B3n D=C3=ADaz, O. (2021). El aula invertida como estrategia= de aprendizaje. Conrado, <s= pan style=3D"font-style:italic; background-color:#ffff00">17(80), 152-157. <a href=3D"http://sc= ielo.sld.cu/scielo.php?script=3Dsci_arttext&pid=3DS1990-864420210003001= 52&lng=3Des&tlng=3Des" style=3D"text-decoration:none">http://scielo.sld.cu/scie= lo.php?script=3Dsci_arttext&pid=3DS1990-86442021000300152&lng=3Des&= amp;tlng=3Des</a>. Anchundia-Delgado= , I. M., Anchundia-P=C3=A1rraga, J. D., & Zambrano-Cede=C3=B1o, Z. S. (= 2021). Enfoque de aula invertida como estrategia en la ense=C3=B1anza de la= s Ciencias Sociales en Bachillerato. Dominio de las Ciencias, 7(2), 37= 0-388. <a href=3D"https://dialnet.unirioja.es/servlet/articulo?codig= o=3D8231779" style=3D"text-decoration:none">https= ://dialnet.unirioja.es/servlet/articulo?codigo=3D8231779</a>Basantes Guerra, J., Chicaiza Moreta, M. A., & Miniguano Moya= no, J. C. (2024). Implementaci=C3=B3n del aula invertida como enfoque pedag= =C3=B3gico para fomentar el aprendizaje activo en estudiantes de secundaria= en la materia de historia. Runas Journal of Education and Culture, 5(= 10), e240194. <a href=3D"https://doi.org/10.46652/runas.v5i10.194" s= tyle=3D"text-decoration:none">https://doi.org/10.46652/runas.v5i10.194</a> <= /span>Bergmann, J., & Sams, A. (2012). Flip Your Classroom: R= each Every Student in Every Class Every Day. International Society for Technology in Educ= ation. = <a href=3D"https://www.amazon.com/-/es/Flip-Your-Classroom-Reaching-Student= /dp/1564843157#detailBullets_feature_div" style=3D"text-decoration:none"><s= pan class=3D"Hyperlink">https://www.amazon.com/-/es/Flip-Your-Classroom-Rea= ching-Student/dp/1564843157#detailBullets_feature_div</a>Cede=C3=B1o-Escobar, M. R., & Vigueras-Moreno, J. A. (2020). Aul= a invertida una estrategia motivadora de ense=C3=B1anza para estudiantes de= educaci=C3=B3n general b=C3=A1sica. Dominio de las Ciencias, 6(3), 87= 8-897. <a href=3D"https://dialnet.unirioja.es/servlet/a= rticulo?codigo=3D7539749" style=3D"text-decoration:none">https://dialnet.unirioja.es/servlet/articulo?codigo=3D7539749</span= ></a>Clavijo-Cortes, R. M., Cuzco-Gordillo, J. P., & = Chiquito-Chilan, R. R. (2024). Fortalecimiento del aprendizaje significativ= o en estudiantes de bachillerato t=C3=A9cnico en Inform=C3=A1tica utilizand= o una metodolog=C3=ADa activa que tiene como base el aula invertida. </span= >593 Digital Pu= blisher CEIT, 9(4), 323-332. <a href=3D"= https://www.593dp.com/index.php/593_Digital_Publisher/article/view/2497" st= yle=3D"text-decoration:none">https://www.593dp.co= m/index.php/593_Digital_Publisher/article/view/2497</a>Dom=C3=ADnguez Rodr=C3=ADguez, F. J., & Palomares Ruiz, A. (2020)= . El "aula invertida" como metodolog=C3=ADa activa para fomentar la central= idad en el estudiante como protagonista de su aprendizaje. Contextos Educativos. Re= vista De Educaci=C3=B3n, (2= 6), 261-275. <a href=3D"https://doi.org/10.18172/con.4727" style=3D"= text-decoration:none">https://doi.org/10.18172/con.4727</a> </= span>Escobar Sala= varr=C3=ADa, K. V., Santana Quimis, V. J., Velastegu=C3=AD L=C3=B3pez, L. E= ., & Guzm=C3=A1n Hern=C3=A1ndez, R. G. H. (2024). Aula invertida como u= n modelo pedag=C3=B3gico en el proceso ense=C3=B1anza y aprendizaje. </span= >Explorador Digital, 8(1), 6= -26. <a href=3D"https://doi.org/10.33262/exploradordigital.v8i1.2785= " style=3D"text-decoration:none">https://doi.org/= 10.33262/exploradordigital.v8i1.2785</a>Galv=C3=A1= n-Cardoso, A., & Siado-Ramos, E. (2021). Educaci=C3=B3n Tradicional: Un= modelo de ense=C3=B1anza centrado en el estudiante. Revista Cienciometr=C3=ADa</sp= an>, 7(12), 962-975. <a href=3D"https://doi.org/10.35381/cm.v7= i12.457" style=3D"text-decoration:none">https://doi.org/10.35381/cm.v7i12.457</a><= span class=3D"url"> Ministerio de Educaci=C3=B3n. = (2022). = Bachillerato General Unificado. <a href=3D"https://educacion.gob.ec/wp-content/uploads/download= s/2016/03/BGU1.pdf" style=3D"text-decoration:none">https://educacion.gob.ec/wp-content/up= loads/downloads/2016/03/BGU1.pdf</a> = Montenegro Mu=C3=B1oz, M. E., Bernal P=C3=A1rraga, A. P., Ver= a Peralta, Y. E., Moreira Velez , K. L., Camacho Torres, V. L., Mej=C3=ADa = Qui=C3=B1onez, J. L., & Poveda Gavilanez, D. M. (2024). Flipped Classro= om: impacto en el rendimiento acad=C3=A9mico y la autonom=C3=ADa de los est= udiantes. Ciencia Latina Revista Cient=C3=ADfica Multidisciplinar, 8(3= ), 10083-10112. <a href=3D"https://doi.org/10.37811/cl_rcm.v8i3.1213= 9" style=3D"text-decoration:none">https://doi.org/10.37811/cl_rcm.v8i3.12139</a><s= pan class=3D"url"> N=C3=BA=C3=B1ez-D=C3=ADaz, L. (2021). Aula invert= ida: una metodolog=C3=ADa a implementar en el proceso de ense=C3=B1anza-apr= endizaje desarrollador de la historia. Revista Caribe=C3=B1a de Ciencias Sociales. 10(3), 140-154. <a href=3D"https://www.eumed.net/es/revi= stas/caribena/marzo-21/aula-invertida" style=3D"text-decoration:none"><span= class=3D"Hyperlink" style=3D"text-decoration:none; background-color:#ffff0= 0">https://www.eumed.net/es/revistas/caribena/marzo-21/aula-invertida</span= ></a> <= /p>Piaget, J. (1970). La construcci=C3=B3n de lo real en el ni=C3= =B1o. Proteo. = <a href=3D"https://granatensis.ugr.es/discovery/fulldisplay?docid=3D= alma991000388749704990&context=3DL&vid=3D34CBUA_UGR:VU1&lang=3D= es&adaptor=3DLocal%20Search%20Engine&tab=3DGranada&offset=3D0" = style=3D"text-decoration:none">https://granatensi= s.ugr.es/discovery/fulldisplay?docid=3Dalma991000388749704990&context= =3DL&vid=3D34CBUA_UGR:VU1&lang=3Des&adaptor=3DLocal%20Search%20= Engine&tab=3DGranada&offset=3D0</a>P=C3=A9rez S=C3=A1nchez, L. A., & Sant= iago Garc=C3=ADa, J. (2024). Repensando el aula invertida: =C2=BFinnovaci=C3=B3n o estancamiento? </sp= an>Revista Internacional De Educaci=C3=B3= n Y An=C3=A1lisis Social Cr=C3=ADtico Ma=C3=B1=C3=A9, Ferrer & Swartz</= span>, 2(1), 340-374. <a href=3D"https://doi.org/10.51896/easc= .v2i1.546" style=3D"text-decoration:none">https://doi.org/10.51896/easc.v2i1.546= </a> Rodr=C3=ADguez, J. L., Yang= ali-Vicente, J. S., & Manco Villaverde,= M. E. (2023). M=C3=A9todos de ense=C3=B1anza: estrategias y actitud d= el docente. Revista Venezolana de Gerencia, 28(Especial 10), 1663-1677= . <a href=3D"https://doi.org/10.52080/rvgluz.28.e10.48" style=3D"tex= t-decoration:none">https://doi.org/10.52080/rvgluz.28.e10.48</a> Sol=C3=B3rzano-Barber=C3=A1n, G. M. (2021). T= ecnolog=C3=ADas de informaci=C3=B3n y comunicaci=C3=B3n (TIC) en la educaci= =C3=B3n. Polo del Conocimiento, </s= pan>6<sp= an style=3D"background-color:#ffff00">(3), 2246-2260. <a href=3D"htt= ps://polodelconocimiento.com/ojs/index.php/es/article/view/2504/html" style= =3D"text-decoration:none">https://polodelconocimi= ento.com/ojs/index.php/es/article/view/2504/html</a><img = src=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/= 2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE= BAQEBAQEBAQEBAQH/wAARCABAAHoDASIAAhEBAxEB/8QAHgAAAwEAAgMBAQAAAAAAAAAABwkKCA= QGAAILAQX/xABLEAAABgIABAMBCA4GCwEAAAABAgMEBQYHCAAJERITFCEVCjFBUXeRtrcWGSIjJ= Dg5YXFyc6HB8BcYN0KB0RonUlNVWGeGpbHS1f/EABwBAAIBBQEAAAAAAAAAAAAAAAAHCAECAwUG= BP/EADsRAAIBAwIDBAYHBwUAAAAAAAECAwQFEQASBhMhBzFBUQgiMjdhkRRxc3ahs8EVI0JDgbT= wJzaTpOH/2gAMAwEAAhEDEQA/ALGsJ8xjTPYOTawGM87VJ5ZpBVNuwq9j9p0mxyLpYe1NpFRNyY= wjqYcmEQKCMOV8fu9AAQD1wDzzM25ewXjTX61YcyNbMczjvJc+0fPqrMOY0sm0QrPmEmcs1SP5O= XYlcFKsDKSbu2hlAA3giPURlQ1wKA7E4CH4RzXiz17jB795gw98Pzfz8PFMPuiIvTCWuoh8OUbG= I/41E/X5x6fMA8Svl7KrJwH2wdntqpqia8Wy+m4TTUt2gpajaIKaoiMUoWJIahG3BsSQLtwCN/R= hGCHtKvHGnZdxzcKqCG13Cz/s6GKptctRAW59TTScxd0rSwOu0KCkzArnrjoRlyvebBsdnDPtF1= yzUhWb01uLaxC0viUenX7PHLQVekp8oPWsSmlCyqLgIw7UeyOYLJC4BYy6nh+GpTmn16dBD16dR= 6e9+j4f8B+EPzdOITuTl+UPwT+ZLIX1d2YOLsyj17v1hD1/N0/n+evHBekFw7ZOG+OoaWxW6mtd= NU2OkrZqekUxwNVS1VbHJKsWSkW5IYxsjCRjb6qDJ12/YXe7tfeDpqm8V89xqKe7VFJFPVPzJhB= HTUkiRNKQXk2tKx3SMX69WIwAh3nacw/IWpFRo2JcIyxK5lHKjSVlpC4Ebtnb+o06MURZGWiEnZ= Fm6EzNP3CjZm/VbreSbMXqrcqbwW7hBRuHtLedVn+g1/LsJnPKsHAXuNa2KA+zTZq7QExKwsokV= 3HzHsZlLv1I9nItlU3LJJ6Ri4UaqJLlaEQUSMbm+6L0XxNyMYrrlUCOWwBAEZiPd4QroXe7jIET= Hp2+IUqzMVOgiPRRIDAHUOLDsXv69J42oEhUlGqtXfUqrvK4oxEgsjwTiFZKxJmopfe/LiwM38E= Cfcgn2gHQADhLZ5cUZVVJfJYsAe4jp/nl8NOjU/iOMeY9qpoPKQdv2loePc/yeyrCSY5NzLnOGl= IA2M3tFctlKk3uOWGUpHoyLqdjfaLSBQblcGRaPXjdQpRdAd0+uVxmY/V7E1wzZkuk2SxExzBSd= +yhF2WuOKLMyYsSKSViYWeNCOrTiHdKdV0ZFiRtHHTHvSKQgdAVv7of9NE6wIdOv9Yeg+v/AGfk= jhIHMPzfbU9SOWprshNSsRjp5rJUcnW9nGGEQsEi+frV2I841Mu1SkArjWvyrqPZOV0mp3ssKqx= iqJILIUVOaE9lSzNlgoycKPLwx3DRqwVnulqBISDWJj9pdeX0q+eIRzKNZZmx26fPH7pcjZsyaN= W9iUWcu3DhQiCDdAiiqyxyJplMYxQHmWLcHVCoTstV7Zstgas2WBfLxk5Xp/LdCiJuHkWxuxywl= It/PN3rB63UASLNnKKayRwEpyFMAgEhWtspyepTKGDKjD4t3Tf5Jk8g46hYe0T8rQ2EGtcXlkiW= sbLSrCJuyxW0OWXUbrum7Fk4UIxKYhEXCgdD9ogtT8d7lc5na3C+UH9mjqsrdcyWYzmpyDOOlQf= wczHkZplcPo+Tb+XOV6r4xPL9xxAglUL0ETUMIBOSwAUsSwwe8DoOvn56NWFY5zdhzMCT5fE+Vc= dZNQizppya1Autat6caot1FIj80BJvwZmVAphSK48MVAKYSAYAHpw8h5+wbiNy1Z5VzHi7Grt8Q= VWTW+X+qVJy9SARKKrRtPSzBdykBgEplEkzEKICAmAQ6cSX69YnZ6J87eHwXiW0Wp1QUYywx8il= OPW60hOwEpg+ZvJ4abNHNmDKRRYWBkzesDmZJmSVYMlO0V0zKnFugeqLfm47ObKZQ2PyBbkGNdC= Nsci2rck1Rm3sld5mcQrUMwdzDSXSjqxW4muyDMjNu18QhQim6CqKRVhOcpQCxYhQqtnZ19Y4Ax= nA885/po1TDtbsfEZE1ey/KacbVYBjMm1IKYcuQRyzjVxVKMWatTNBM1qm3zidgIILBHMpuOhxm= WoBIvE1G7ARcp96fN1FzurQ9QMW3fcTZbCM3cJqVt8VK5ebZMx4XHlqfpXK0+xY2BtkaeCqko9j= a8zbRztrGJg4QdRT9JyQ7hq5VFX+53LqwloXy59yHOHpa9Sh8oJYRSsIXSYjJUES0zJKR4sY32d= DxQoCqNpkAd+N5gFATa9gpeGfxATRZjSyP5LOpyW6C18e1n+kLKknR6njF2RvdbLZ2eT8mtFyMQ= XdR7II+PjZJZeQcSUiwZIiq2KK53KzVutQKpVSuSDIB7I3eyCcEZ8D3dR46NUawe4+pNnlmMBW9= nNf56ck102sbDw+YcfSMpIuljgmi1YsGthVcu3KpzARNBumoqoYQKQhhHpxowFAMACUeoCACAgH= UBAfUB693r1D4ePna7OT/Ldm6Gy/qnUTaCk5KbzbNRZxlR9UZOov4A6S5X6J1I21y8ozk0VvKrR= 6zZuKBwBwk4DqdFRI11LnN7pVCq1mps7c3etKvX4autXsn4r2SdtoSNbRqDqQeLgos7fOEmxVXb= lZQ6q651FVDmOcTDkFNuGQxHmHXB/An46NZa1v/GJwF8teK/pzBcUw+6I/7EddflQsX0RNxM9rf= +MTgL5a8V/TmC4ph90R/wBiOuvyoWL6Im4nr2g++/sh+yvP5MmoNcD+6TtS+1sv5kGk58nH8ofg= r9jkL6vLLxdkX+9+sP8ADiE3k4/lD8FfschfV5ZeLsi/3v1h/hwjPSe94VF92bf/AH1z06fR1/2= PW/eCr/sbdpM/OB5cVi3gx9U7biheLRzTiosqWEjJdyVgxudalSoryNaGTU/B4+VI8ZtncI5fCn= HeMZ01eOGaTrzaCUMZUHn44NqMXjLHkLmeIqFYRLHwcR1olmZRbFL7lJjFv5RSVUTjUAACNGrd1= 5NumAEbJkTEChV/tbsbW9TcE3bPdug5ux1yikhFJKIrvkfbDss5YIuutwZ+0nLRn1RdSqK63jOE= /vCSnZ3H7SGS9/pIGsnQf9R+bg/xpHp197qA2b/3xHtHlKBVjEihuhI3YPQ4xkeefq6DPg/NATO= ODuZbs3y0XlFzvQr7fNg2m2cFYYuCfsqwxmE8YxuOphmSRTSiTMY4zBCflHSHiKCLsVlzAPVIEx= L2PbHlX52zppNpPO4+gkozY/XfD8JSLZjmceMo1/NxPhMX4x7GRcKjFpWCqTqDtw2aO3bdlIs5e= SAHgO2rNu7ZdptzfNWtyrqnjGsmtOPckvUXDiBqeQGkazPZ02aCjp6nX5SLkZKNePmzVJV0eNWW= bPlGyKy7dBciKokPz3mAa5MNqkdNHM5YS5ycOWTRKHLWZE8IKr+sp25uA2AC+RApoVUixhEehVh= FAfuwHigeVCFCbSpZyAvgQB3eA6+Hx8tGkZYgsnOCgLRjSFtGjGFwhoqx1KPn7sthKltrEjFNZV= ihKWIZSFsjFmhLN2JFn5X8dHt003SYOEW3oBROeqOpexVH5xmwmwtsxZYYbDttf5jVr18deR9kS= pLDKxDiHO3BJ2d10fpILHSFRuToBBA/aPQOKMePww9oCPxfv+IOLDLuz6iqSMHGcnODnvPj/nTJ= NTm2vUXYWV54kBscXFdgXwMRdMj3IQeR9hkQNgmWqqveAuwedvttySNH8G9Vjh06kEDcY4d6Kcz= Tl37M5HvGjVdG946vJ5BvFrxyVcsDRxVHkqrKRlct9Xn3bd4hM1lbtSaTDQnaomZRVrIgm/kGJa= JcG7+66bEZqyNgDGU3YJDJGKwsg3BhI1qRi45oFUszeozAtJNyUG73wpp0ikl4I/fkTCuQRTKI8= DDCfMsxlm/cPI+msFRbxE3fGhboaWs8qMF9jD4KRKR8W/8AIeUk15P8LVkU1GnmGSP3tM/i+GYS= gN++Qfy1KiNQ6n+Jem1iCR4Y/wDe7RpYFsYc1TbDSTcfGOzuGV0bm8Qwf/QtXoOs1+vPrEunfZG= SyABBZSrhF37MjoivuRK6VQ8FNQ4oiqdc5SZrzJywNssi8tjTGuQOPZJPMWAJ3OaVuxJIOotnOL= wmRslSk8wlWRl35I906aNo6KWFgV15hywljKJAY7cyJq9+POLBKRjaqAB94ABxkgDuyemPL5jRq= LvPOKebPsNiVDD9t0Vx5XK+k6gnvtvHmKKrUbYZWAIYjUnthlZVEUkHPcIv2yDFFFbqBUyJEKUo= YM+1O8w7/ldyD/4X/wDV4sTvnMqxrQN3Klo3I0S8Pb9cHNabsLYz9hfYm1GzQ68y1M58aTSlxBB= BAya4JR6g+KYAS7yfdcMg6m+I37v/AJ4yiokQAbEXIDYGeoOOvtHyI/Tpo183rW/8YnAXy14r+n= MFxTD7oj/sR11+VCxfRE3Ezut34xOAR/61Yr+nMFxTD7oiEBwjrr8qNjD5qib+fTie3aD77+yH7= K8/kyag3wOP9Je1H4y2XH/LCNJ05OP5Q/BX7HIX1eWXi7Iv979Yf4cQmcnIwBzD8FdfgRyD+/Hl= m/y4uyKYo9egh6j/AADr+8f8ve4RnpO+8Ki+7VvHyrbkf1H46c3o6MDwTXDyv9Wf+lbx+mlb86P= 8m5sR+wx99Z9O4WzyPdQtYM7ah2S25jwRjLJNoSy7aYVGwW+qRczLIxTaErSrdgi+doHcJNkFXL= hRIiZygmdZQ5BKY3Xhk3Oj/JubEfsMffWfTuEzcoTma6laf6wz2Ms326ywdwe5OsdpasYikWSxI= KREjEwDRop5+KZLsyLKLsHJBQUWKoQCAY4FKYB4j2u4wnZuzzD7Pf3IP10/tYd5iGDK3oDzG6kt= gtJWq1ps/wAcZhpMQ0fPV/sYWUnDFfRTN07WWdmZFlYZ8Zsk4XW8Ni6I0E5kSAQG9v8AZRk652F= dxIXAevSy8k5qTkuZHNAcKZsSLJYTY2IqhbmE6VAqzYi3sduf2QPZDkK0EBMHjcJr2azO95pPMf= pCmKa9OlgbPPUbHFHj5NoklMI1ODfGdzFjmW7Rd0jHtyFXm596JnKhI+NJ1cKlMicCMBtkaCHuh= 2LiGh/AKkvVo5scB6Cl4eurFqifqHvCToU3UA98OvTjI4OFVj6whYHJyehXGfHp4aNHHO3Os2Uu= Wx1pwJoZgKLyqWoSs1DHlpGvWa6zNqUrrkWUzORcNWJaHRh6yg8TUSaSEg8c+bbi3dKiyM4TbB/= O165sO/1g3Zw7qnshiHG2MnF3tEdG2mEWpNsgrewh5SGkJRi8ZjIXaSQbHdEbIqIKrs3BDoiYfD= +6A3GHuU3sNiTRvc3Y2t7RyyeOXckwsFELaZqMlHaMJZK9dgdvoqQNGMH7xk3mUmx1SvTolaHWZ= NiqrACyRhKVszRi3P3PpwNknDlxjL5R5Cdx3HMrHEEeJsXL2Kocm0kG5Cv2rNx3tHBTJKCdApRM= A9pjB68W7VyUCAgRk7zuySFBOMdPP+oHfnRo96m7R5CntseYfX8I6x65xOX8Z0PYGUoExQ8dO4e= 9ZJt9cypHRkNFXWZNakwnULDIKISM0kkeIF9LkSclctSF7BVXrbmLe6scwfMOR8PYVg7XtXNlyS= GQcYu4hZ1EwRZSah1bcKEeS2xqqXsqSSj2yPdYXnhlXEDC5E3iFZXygOn22ffDr/u89D8XXpn2D= +H5/wCQ4D2s2csVa5c7XaC4ZuuEbjmpyUxnCspWCxg5bxSErLT0NKxqD5ym3VKxSfNYx0KDt2CT= Y6hkEfGBRwkU9wODIAgb91GfEk9FGMeXj9fho02nZHZHmx06va+OsDaxVW7zdsw3C2HNjJ/XXbs= lNym5XVLK1hiVPIkOLVo1QKmcjdRWWOTu9ZFX3gw8HON351tzBjur7260VWgUS8O0SqOYmAnIGb= Thgft2EpPQcgvbbRCy54AzpJxIw4gi7FM6BTLNBdt1Dinmp7lZUyBuhijCmOdpZXX7XObpGO7FG= 5Uqk7YYauScfkNFWTd5Dl5CruY6Vn4Vo1BtGxzPziccgpHuVRFqo5duSKy3uqDKrOcUmZ8wZLeo= Xytl8bw5WzSY428E9fEvX7IrjbPB+ygVTejTyPf7C+/eY7U/BpHGCF3KvrgnAD5A8eucKR5fMDG= jTeNi1Sr+6FcELEEBIs/xEoQQ94SHocgJR9OvXqAgPX4h4q/4kxzqHT3QBrr0/wBnCn1dO+KzuM= MpysQ8RGM/HJJH4dDo189TEOuOy1Hyri68yut+d14Wm5DpVsliR+Lba4eKxldssbLviMklo1BJZ= 0dozVBukqugmooJCHWTKInLSNuDdNQd+qTSanmhXbPBIUuefWCJB7r7fmLoz5/GezFSSblKj3SF= O1TRMJygjINjgoHcZYUx7RfF4ZA94oB+jj0MgmID1KUevxgHQf09A68OfirtnruK7vZ79UWf9lX= ewx1EdsrbNdHgkhFTjmsy1lFXRuxGVB2KNrEEHOdJrhzshp+G7ZdbNBeFuNsvbQNcaO6WtZo5jT= 9YwGpaykkRdx3EB+pCkYAxqR+C5YmI4GyRl61V5j0DUcgwy5nVWQvUIpSLA1cqJKJHIpLt5qMlm= nitlFG7pMaiuRdBVVBZAyaihDNQw1sJv7gdBpD7S4nhtlMZNippDsBrHJx9usEagY/aDqz48bpx= M5Ot26IlVeP4OAZOmzchlAQmVzCHDe39cgpVI6MnDRMgioUSnRexzR2kcpvQwGI4SOU4GD0EDAI= evxcD0+CsUpqLOIqlRFcerG7zSFSIrUZEpx9O9OQrasY7TU9A6nTWKYQ9OoB7+ivPaZW8SxCn4o= por+iKUhqLjS0RulKnfinu1thtNSoViWCTJU0zMSZqeTrrbWns5g4el+kcO1ctmd2DzQUNRVi3V= BwAfpNrr5blTyZACs0b08wXokyEAgbWyD193rwZO0WUk0L9iq6hGJWFhDysjCSiK8TKsJxqwk00= TMJ6vSjOSj2pnka/RZP0DpKNnbYvVVMMU/aM+XQIemKrP69ffyRdP0f8V4ZKbEdYQk0LJEJOYS3= t00kFLXHKFTl5ZugQySDSyqdvg2lqmmcxCknk3yqYiDlBZvIETeplBsVUqKZVzFMqBQBQxCCmQx= ugdxiJmOoYhBHqJSCooJQEAE5xDuFbTNEJWNI9QkJOVjmKtJH3YVpVVUl7vbVEJwSyJkAsemNTy= 1WqERmUANJDkRyHA9ZUZneMnrlGd9vTDt4Y31p5fuqGpMi/ncI4rjK9Z5Judm6tkk8kbFZgYqdo= qsWkxOO3rqPZriQouG7AzZNz2l8cFAKHHu+0L1wfbPpbhuarKHzq3cNHSdkCyTYR4KMK2SqNxGA= B6EQPbCpEbCHlehjgKxgFYe8NmceCHUBAfhDp8/GEknqWJPcST1I78fh8sjx16NSocw3Z/lTS2z= OR6bsNqZl+0ZZx9OBVrRfcer1+sp2dwzYslEHDp00v0I6lwQaqoNkXctHFekSRBHu8FNMAxhy9s= eUDOvNPxtfNSsSXvH2u+MXyVwfJXJ8aakYFCKpzxi5cTcuL6TZkd2C2O0m0dFtpR+uRmr5gAKm3= d+Xs5k8QYompB1LTOM6DLyr9UV30nKVCvv5B4sIAUVnTx1HquHColKUoqKqHMIFAOvpx2Gu06pV= BsozqlZgKy0WUFZVtAQ8fDt1VhAAFVRGObtkzqCAAXvMUTdAAOvGYSgKVAfONvrOSvcOoAwPq+W= jWWMLaI65a9ZkyDnzGNWlIfJWUS2MLnLu7LNyjSQC02Nva5kEIt+8XYsfMTTZFwmLZJPwEyign2= pGEvALzDy4uX5ttk+1ZIuFRibNkYy6Mfc39NvkrFOVZGOSTaAM9H1+WTbElUECJN3CyzdN4YpEi= L9xigHGsdtMtzuDNfMnZSrNbPbJ6qwCasXDD5vynmpOTYQpJWV8iUzwIKvhIjPTxmopuAho18KS= 7cwAuktLF+Cs2VHEtLg8Tzb+/WKvWC1IyVviLNWaq9Wxzd4mfu3sVvM1+bdRyylmzHV6DLWSWWm= Jy9R1EmfKoyqovZFoXd22zLV0ElwnuEVEprFoabmkbJSkPPqXkf+WsAelVFkZBM1QeVvaF11ztz= vstFcIqCmoZq1hSNWVPJB5kaPMsNNHGuP3jTFKlmK7+UIQHCCVXUwZV055a2cqzjGiZAaUqULiF= NHCFEeIZBdQ9uYBXl3kWlQ3MuylmsrLqMX0XJETZSXmzpPW8ks37FVXJz9JHkmctdBs1fnx3NpN= XKrQjR2plO3FQcLPFCJsk0FTTBU1TOlVEk25SHMK51CkTAxjFAQnT9JNmoKYipV5TIM60TaFbCE= wpK1J7Y15KwyUHTrBYivnC6hlptGmRFjt7Uzt1+CWHLNzfR4hMVuuISBvyZr/u00tM2fG862lYl= OOqkygq+lmxICbyBWqdKmGzMajZp2cJDvFbCetIN26rsGp5Kkxkk7WVTssrIwu1qeHrQKhIaTie= kZGikkeSolQJuSSNeWGTeil1fepJLNh1KgIW1qaXiW+GCSar4brVZZUjSGCNy5V0J5hEveA67WA= IAUoScsF1pi9ab6mr7O432buUYu1z0EvBQOPZde2zLNCRl6xWpEYyOaV8jwI1+6bV2Ok3KxDtjC= dBouuqJhT68bvAw9A9R+cR/f8ADws/AWDdhS5xSuuZlptzSaQ+uz/GUfbriheJGLGe8KnslhdJS= jxdKecVSAa2F0+OKjBo9vtshWDVq2QbDwzQCB0D3w+b/LjmrlSQUUsUENbHXEQq800BDQrI7Oyx= RsM7jHFyxIdzDmFlUkAa6S11lRXwzT1FFLRKJ2jghqVKztGiRhpJFPRQ8u/YB/AFJ9YnH//Z" w= idth=3D"122" height=3D"64" alt=3D"editorial1.png" /><a id=3D"_Hlk92188167"> </a>El art=C3=ADculo que se publica es de ex= clusiva responsabilidad de los autores y no necesariamente reflejan el pens= amiento de la Revista Ciencia Digital. <img src=3D"= data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQE= BAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQ= EBAQEBAQH/wAARCABVAKIDASIAAhEBAxEB/8QAHwAAAgICAgMBAAAAAAAAAAAAAAoICQYHAgQBB= QsD/8QAUhAAAAYBAwICBAcLCAQPAAAAAQIDBAUGBwAIEQkSEyEKFDFRFRYiQXF3thcZNzg5QnKB= obHBGCMoYXaRtfAmVnPRJTI1SFdYdHiGl6bV1tfx/8QAHQEAAQMFAQAAAAAAAAAAAAAAAAIDBgE= EBQcICf/EAD4RAAIBAgUBBAQLBgcAAAAAAAECAwQRAAUSITETBgdBUSJhcZEIFDI2N3aBobG00R= VSdbLE8BYjJkJTZvH/2gAMAwEAAhEDEQA/AH6WcpHSKBHMe9aPmypQOmuzcoOUVCD7DkVRUOQxR= +YxTCA/MOv2cmAWywlHgwJnEOBADAYCiIfPyAgPu8w182rG2c8zYbfklMV5RvVCdkOmc/xas0rF= tXAImE6ZXrBu4Bi9SKbkQRdtl0hAxgMTgxg0+lsKyfdczbOsKZMyHKhOXK001y6npf1ZszNIOms= pKxxHSjdoki3IuqgzSFcUUUyKK96nhlE4hrc/ej3N5h3aUtDmUuc0ebZfX1hooilPLSVUcwiecd= SFnniKFI2syzEhgAUs1xqHu572aPvBqa3L1yipyytoqMVkmqojqaaSMyJCRHIEhkDhnBs0Nrf7r= 4Vbk+rJvdwZnHKENGZQLeKhA5OvTBlUshRDCwsU41pZpNs0YIypEmdjbINW6aSTVJKY8FuRMhQS= EhQKN9HTi6qcXvfs0riyxY2d0bJtfqa9udu4qQTlahLxbCQiop6dodz4ErFvAeTDMyLFZKQRMh4= 5/hEpyFTUT13Bfh6zX9bGQvtXK6tu9H+D+mXeR92B7N+rm5UL9/8Au10R3n923Ylu7Ou7SQ9n6K= hzrLshoa2Cty6P4k0k7JSq/wAZig0QVAkEjajJEz39IMDe+hu7vt92uTvBosikzusq8qr86qKWa= jrn+NokLPNYQPLqmgKWBURyBABYqVAAciLzwHPl/n/P/wC66UpJsYaNfy8m6RZRsYzcyEg9cqFS= btGTNE7h05XUMIFIiggmdVU5hACEKYwjwA674CA88fMPH69QW6mNyfUPYdufn41Q6T42LZyEbrJ= mEiiI2bwa6oqQwCAlOmjJqGKJRAQEPLXCKi5VeLkDy5NsdrDgX8sK074+tfuSzJkmzV3bnd5jDm= GYmUeQ9bc1QEmN1uLNo5FBCxSthMgaVihlOz1tlEwq0f6m2cJtnqz5yQyoRhjsx9XWXYtpOJum/= uTjXyJHLOQj1M6PGTtuqHek4aumyCjdwioUQMmqiodMxeBKIhrPOilhqsZj340FK3xrOZh8ewFi= yOSLkESOWjqZgEmreCVXQVKdNUI+WkWsmmU5TFFdml3BwHAvvkIUgAUocAHAAAeQAABwAAHzAHz= Bq6kdYiEVFNgLkgbk+dwSff8AoK4WO6buUd/MTtU353TKy24mfyvTqOzmsJtMywd+n5RawMq1bH= RW9Tgbg0VcTBlpJGMK8YRjZf1lUGqSyZjCkXUtekTua3z7gbBm9rvDrFprzCsw9JcUU9ixK/xoR= 07knthTnCtV3sRFhLnSRaRoqpJisLQDkOIEBcBNYpvjs9hpGzzczcqjMP69aaxhXIM5X52LXM2k= YiXjq4+csZBkuX5SLpqumRVFQPMhygYPMOdUXdDLd5mbJSm7aybiMyXK+1rGdHpFmbrXGZVk0K+= zTPdXc68aeMAAgKzOMRFcQHg4NkgH/ihps+mkj9NeVGoDcElVsAANiAL/AGnxwYZ65D3h/frzpI= rJ3U/6iG+fPrzHm0p9dKrCyMjIFouPMZoRbCfUgo05wJNWu0u+0yCh23Y6k3LiWjoJgdYES9pSl= VVkxgTCnXcjc2YlkMpOs2jjVnkSoOr4WTzRi2SjzVNCcZKT5X0cxvrt69ajGlcAu1atXDhdPuTS= RUOYpRoYGA9J41Nr6Wax8Psv9vvwYbd5AfYIDoEQD2iAfTpInfvu83ux3UJzdhTC2dMsxzdbKcb= UKBRK1ZVGbQHktHQaEdDxTdQyTdEXci8AqYHUTTBVcRMcpREdayyrmrrNbTUq5fcyXfcPQ4d3ME= YxMncJGOn6w/lE0juSxT5IFJiJOq4bprKkZSJU1HKKK50CnBBUyahTkhbuilgCoNwTcA2sbefhf= f7jD4XICHICAh7+fLRyHvD+/VI2OerM3+9iOd5t/gWDnJNfeOcaq1RioLKMtmV0l02MQZoIiZRp= EyLVZGyy7dETqsI5tKosxWOih4i/9W3h9Xze7crJJYTteYp4Io/rL+FxCzaVuo1Vq8UVMxYrPE0= 2TJJQ6ZDkaJysq4knZEFTgdwKaqgIWFzqvZQraSWIte9tvV43wYeYtzp8xq1jfRRTnlWcFLuoxN= NIXCh37ePcLNCEblAxlzGXImBUQKYVBECAA93Gl/8Apgbu+oznDc5MUndTUbjB4ta49tUuxfTuE= pLHrE1jYTEA3iEST7uDjkVl1GTuRMmxBwYzkhDqlTEG4mLrzpyV/qq1jMmQpneAtnNvi9rgTJJ4= le/WOMk4VC9prV5eAWbt2co9WJKpM0Zg7RfwQImmVyBlC94AbQnRO3bbls3b0rHScuZtyDkKptc= SXqXbwFmnV5KNRk2Nhqjdm+I3UAClcNkHblJJQB5KmsoUB4MOq6NKzfIeyghhe4+Tsp9d97ew+O= DDcHID7B5145D3h7vaHt937B0pNn7CXXblM45dkcVus2Fxq+yPcnVBJGZpxdGx5agvPPla+DKPf= X5o8ZNAizNgbtXbZu4QS7UlUUjlEgQtyTuV6xWw240+ZzzdsqV1ScOq7hIrIM5V8hUy1N4xZH4R= jFXMNJWCL8VMqyQPWreSZTDZByi4IKJVUFhBCWtpeMki9g2/h4eq5v7PXgw9Zo1RPSeu3tplKZU= ZO2RUxEWmRrEA/ssSyXbLs4uwPIpo4mY5osqUiqzZlIqOWyCqhSqKJJEOcpTCIAaR0pv+J/u/X2= /2djCcpg5KP0c/3een6el1+T+26+XH+g0iPH02Of0gub2D9A/u0/R0ufyfu3X+w0j9op/XcXwqf= mn2c+sJ/IVOOMfg3n/VGeDzyI/dW0+EdtwX4es1/WxkL7VyurcPR/Pxyb39Q9l+2dC1UfuC/D1m= v62MhfauV1bh6P5+OTe/qHsv2zoWth95f0L559V6D+hxB+7/AOljJfrFP/PUYcgL+d+kP8NQ16h= uPH+U9k25WlRTdV3LSGKrK/imiBROs7kYBqM+zapFKAiZRwvGERTKAcmOcofPqZRfzv0h/hrgsi= m4SURVIVRJUhk1CHKBiHIcBKchij8kxTFESmKYBAQEQEBAdea6HToYcjSR9ljj0Gx8+bpL7kqlt= f3qY+uuQZJGDotjYTdAtM66N2tIFtZW6ZI+VfnDyRYM5prHDIOBDtaszLuT/IRNw+gwzXh2TZt3= 7DKmOnbN2kRds5b3SuKoLoqlA6aqShJIxDpnKICUxREBDSwm+voG5ElsmWbJWz17WX1Tt0k+nXm= J7JKErz+qSki4M6eNKrLOkxiH1dO4VWUYR8g5jnUOj2MUVH7chFEq+CdEDqQkKBS4nhilD2AXJ1= GAA/RAJ4OA/q4DV44imIfqBCRbSbDjzuRb28cWvgw3Pvvt1VtOxbd8NZssDYis8BZKK7NBy8fLF= amVqkmZIrgWLlcERUKQ4pgp2icCmEvIAPCsfSgaSr7a71VmsKRZSTW20xpWxG/PjH4jMjGWIkBf= lCczcFQAA8x59g6sg2KdOjdphTZ9v9xLkijMYy8Z1xyFexrHJXCuSqMvKfFa1xgoLvmUm4ZxZBe= SjJMyr9dBPtUMoAiVM4l2Z0Yun1uG2pSO5JruSocTBQWUavSoKKboWOv2RGYRjl7WScaOkoZ+9F= BL1SYbEN6yUpFyrHKTv7DgCFKJHIuoP6aEEbaxdDcffex91sGFltkdR3cXjK0pXdmM9LQmVHNUe= rPSwN+rWP5eRrDV8wO/aNZCyTUGlIkTdixdOI1k4Wcimh62ZuKDVVRO9za3ty63dc3E4bnc3WTJ= 7nEcVfIJ7kFCUzxQp6OWq6LooyZHkMwujx7JICjz4jRs0cLKhyUiRxEAHTm4noT7q8WZhkcgbL7= OxmqmtMO5epIoXM1DyLRQeKqqjEjJPF2LSQbsk1haNJZjMEdOmwdrxi3OBjq5PgTZH1oK1m7Elh= yNdcmusfwmRahK3Vq83FN5dmvV2M4xczaLqJC2uBkm6kem4KqxBBb1kgmR8I/f2C48iuupWi3U3= Dj0r8WBPjfYfpgxD/cF59c90PHP9MDFgh83tk6YIce7n36vF9ITKX+Q7Xx4DkM107gePZ/wHav2= /wBft1DfLnTI3hWzqnr7nIPHkU5w8fcVQsglsB7lV27savBPa2tIvQhVpMkp4iSca6MVr6t6wp2= ACaZhOUBtK6wW2DMm7Pa5DYzwhXWllt7TJtcsq8e9mYqCSLEx8VPNXa4PZd00aidNZ82KCJVRVP= 3iJSiBTCDbMpemNx6KDVxZSNPPAHHmOPDBhYmbbSKvRRpy7UFBj2292XNJ9nd2FFagPU2ZlgDy7= fF7ykE3l3mDjz4Abx/R2pymr7Sr5ARzqOC5x2Xpp7Z2RFUQlPUn8LCEgnrlHnxxZqoN3DZquYoJ= Cq2cJFMKiagBmGyfpp2g3TjyRs+3X10lUlrverHPsVoaWhp97XnB0IJxV7TGvI1w7Yi9jJaNFcz= JRYnrTUi7F0BWz0/dTZN9EnqS4VuUqTCUtGT8WqZZqyulCycnQnUrFgoYzckpGysjCSLRcyZUzr= svFftUF+SIPXZCFWOoujrJEXVW1lgx3BHo8WsLXB4N/YLYMOdZG4+59eOQAQ+J9lAPLn2wr3SWH= QcmWta3uZHsL8TeowO3zK0y77AExwaRk3U3q/aHHmbwkD9oefn9OrIem1sm6jeHs2Xuw7mHVofU= KZwTkSpRLaZy+0urI9zm3VcNBh8Ep2GTFBUWzOTIWRO3Im2IdRMyyfjgBsX6UHTI3Vbat0Vwvue= 8dxUJjyy4ivtIWdNLfW5xRy7skpXlEWR2UPIu3ZE3LBm+71jJFSTEgFMcDnIBkLpjSZTIrXVbWs= L3I1WBJOw5P4bnBiuf+Wv1POoBuQtFX25ZCvEY8XPPTNZxtRLZC0KDrtOiHZG6YryMo/hWjxdui= 4ZldvZGQVePHS4iQBKJCE0Vvvw/1Jsb1ejSG+SWucpV5CekGlI+NOT6rfkUZwjFNV+LVrA2ObXY= KGY+GB1l0kElCABCnMYoF1NrJXRS3+4SzbZLHtTlySdZXk5Ven3aq5Ha4+trCBlFzLEhplF5Iwz= xF43SMRq89QcO4554JXBFC+IZBLXmQulZ1gctNGEflFCyZDYRTlR3Fs7nnWv2NtHOlk/CVcs0Za= 1uk2y6iQAmoqiUhzkDtMIhp9WjBXS8SqANrWbgbX8PcOPPgxRto1bp9446jH/RDA/+ZFD/APftG= nerF++vvwYriN7B+gf3afo6XP5P3br/AGGkftFP6QXN7B+gf3afo6XP5P3br/YaR+0U/rtH4VPz= T7OfWE/kKnHGHwb/AJ055/Am/OU+EdtwX4es1/WxkL7VyurcPR/Pxyb39Q9l+2dC1UfuC/D1mv6= 2MhfauV1bh6P5+OTe/qHsv2zoWth95f0L559V6D+hxCO7/wCljJfrFP8Az1GHIC/nfpD/AA1y1x= L+d+kP8Ncteay8D2D8Meg2ITZ56iO0PbLe/ua5uy0zpVzGGYWAsMtX7TJqDESarpFi8FzEQr5mA= LqMnRQT8fxS+EJjkKUxBHSw9ZbpyceW4mN/XT75x9mdLdekDfj7p+z8CuPw8gAPIJK1+7W5cNej= 7XfMOG8ZZaY7javDEyVj6qXtpCO6NKuTxhLVAspxCOcPUZohVzNAelbKuU25SqCmZQqRQEC6uVj= i0K7uw1AG3rNjtYHw232vzzgwzZgbfVtN3MSR4PC2b6ZcLCmmor8WQcuoWzLIop+KuuzgJ9tGSj= 9ugT5bhwwauUUC+axychqRdwvdIx7FEnr7cKxSYNR2iwTmLbPRddizvnBFVUGRX8u6ZtTO100F1= Em4K+MoRFUxCCCZxD5zG4jb/nDp+7ikqXYpU0DkClOoe5Uq8VB48btpJl4wuIWyV96JGrxEoOGy= rddFUiard42dNFQOUgmOztumvGN9/XSiwHkXNGcK5t7aWW705/YrrPVuaskWtfqxGXWtzEI3ia2= RV83NLP0JWUaKm4Qbtm/hKCBlCANHhVTHpY6HsCRY6SPKw3vxb1HBi/Kn3qk5CijTtCt9ZusIR0= sxNMVOdjLFFletypmXaDIRLp20BygVVIyqHjeKmVVMTkADlEcq1VF0dcb4xxVtMfVnFGboHP8AV= hypb5M18rldnaywTknUdXU3cGMbYE035nDBNugqo4AvgKFeEKmIiQ46kNlPqN7H8L2V5Tcjbksc= wtpjVjNpSCYv3tnkYh0QeFGcuhVWM2MU9SEQ8VlIC2dp8h3ol5DlrSblV1NYkX0kHm24ttvtgxN= fWubnmHEuOHjSPyFk/H1Ffv0DumLK4XKvVp28bJqCkdw1bzMiyVcIEVAUzKokOmU4CQTAby1CL7= 7z05P+tDUefZx8X75z+2qBqsjrLYZ2257yRg645L3iUrb+CmLll6vGWOiXO0LWqAlJYZJvPNF4B= uJGbcSrpperPCJuREe4SAA8BVUuwV9SA330k8W4Hu549l8GGFbflfH9HxlO5jnrPHJ40rlWcXWU= t0ec0zFFqrVkMirNs1Ygr00kyMx4dIKRxHIOURKZDxAMXnTG3Devtr3avLSxwDkdrfXFLbxjqyJ= t4awRQxqEwd2lGnOabi44q/rKjB2UAbiqJPBHxAL3EE1a+6fcFtswL0u2m3eXzZAS1ovWyhvXcQ= OUoayNQygxLQm0BCzkQgMWuWMbzixElm7aYdNVm3rBSOBL2mNqoHoVbtNvG1mybhnefcmROOG1x= hcft62tKsJx6EqtEPbQrIkRCFipM5BaketTHFcqQCC5RIJuDcLEWqNnGq6kabD5QuPPc3B8MGHU= tGoj5D33bTMUULGuTshZlgqzRMwMF5TG9ieRdmXa2lg2bMna7lmgxhHb1uRNvIslRCQbNDiC5QA= omA5S6VL1d+nIYxShuip4CYwFATQN7KUBEeAExjVUClL7zGEAAPMRAAEdNBWPCsfDgnBix9Q4Jp= nOPsIUTD9AByP7NQfxF1HtnOdsmtMO4ry+ytORXxpYravJV21sFFBhEll5Ph3JwjNiX1ZJBU497= kvf2CCXeYQKMlcb5exfm2lJ3nEd8q+RKi/TdIt5+py7SXjwcoJ8uGThRqoc7J+2ExQdR7wjd62M= YCuG6YjxpJzo6AH30apf7fLf+FS/+4NOJHrEt7gxqWHrsdwdr3v4e/Bh7EPYH0aNGjTNvb7z/fh= +PmcGPmHG9g/QP7tP0dLn8n7t1/sNI/aKf0gub2D9A6fn6XQgHT9268/6jSIf+o58P2D5D7tdzf= Cp+afZz6wn8hU44w+Df86c8/gR/OU+Ed9wX4es1/WxkL7VyurcPR/fxyb39Q9l+2dC1UfuC/D1m= v8AryxkL9lrlQH9urbfR/jAG8m9c+z7hFm8/m8rlQ+Q+nyHy1sPvL27l888/wDC9Bt47fEcQfu/= IHevkp/7FN97z/8AuHIy/nfpD/DXLXEDlHnz9nv4/u/V8+uWvNcbADyx6DA8eFxe2EePSBvx9yf= UtQP8Stem4tjwB/I02q+X/N6w/wDYGA0o76QN+PuT6lqB/iVr1PTAHX+294fwJh7FErhLM0vOY1= xdSKM/fx61JSipGSqtajoVy6ZqubER2Ri6csjqonXaFXKgconQBQBT1cFGeGLSpb0Re3h6Kj8b3= 8rYrjTnpJDGJSzNtzfoJoFmXWObQ3fnIBAXUYNLEieOBYS/LFMizqR8Hv8AkgJle0Oe4dRwtK71= boKY/TdCoKDbeSogwA4iJStPgq6LGKmA+QE9bVcjwHl3Cb5+R1BvfZvHue/fcGfJj2tnr7IGEdT= Me0Zk6UmXUVCoul1GjNV0m2bjIy8nIvl3TpRBoiU67hNsgmKSKZhum364Dl9tfRF244usjUGdra= Zco1itbQUwTVZ2C2w+RrE/jnIAI9zmL+EU4xYwiPJ2YgA9oFAHT/lrArGzGRdvIbE7+rx8Lnk2w= Y1rts3CWnbh0Lcq2qjSjmDuNu3BWTG8BNM1VG76JVtcfViSb5iukdNZu+bwLOWFk6ROVVo68F0i= YqiRB1FrpfdKtTqARGQ8l3rI0vRKBUrGnVUHULHNJWxWe1rRzealP5+TVFu0aRTORi1nK6qDpZ8= vJFIQUhQVUPurGWJrBlXoJ5JNWmDqTksc7mZbJSzFkkdZyrEQTCtx86uVJMBMZOPh5l5JuB/Mbs= lT8cFHXe6M/VAwhs5ouSML7gFJ+ArFiuf3QqrcYSAe2VBvJvYWLgpuEmY6IKvLolVSgop1FOmce= 9R8Qz9N6ZoX1Y6tAzBJDHcPquSPlWGnYbDz999htgxA7qf7J6jsRztW8TUu5WK6xU7jaJuy8nZm= 0c0fIvJCesUQoySTjEkm5myaUKisUxiiqJ1lAMIlAgBNTrrgATOybgOP6Llc/ez1HbrIbrsJ7v8= AcnUMj4Isb+zVOHxLCVN++ka7OVpZKbZWa1SThsVjPMWDtVMrSVZqA5TSMgYyhkynE6ZwLInrsf= 8ALWyb/uuVz97PSlLE0976rPe/N/Rvfje1/swYnnuk2JY4z50yMGbmLLZ7bE27b7sLq0jWIaGUi= yQUutF4/YWBEk0V0wcPTEO6IVJT1Ry3EUBECiU/ytVOdJXp4Yt39TeaI3JdtutVRxtG017EqVBS= ITUeKWJzYEHRXvwrHvymIiWJbi38AEhAVFfE7/kdrJtjZun/AEP1mrJA7lwfp8MFCIplEyhit8N= tXKvYUAEREqKSh+AARECjpfvojb3Nvmz29ZyT3AWt7SYnIdbqBYCwJ12fscd6/WX84d3HPUKzHS= 8o2XcoTKazNYY8zMwNnKa7lBUUCLoRpOlJpuSHstuRcjgePjt58DwwYvQ3ubD9mQ7ZNvVA3I7gJ= vEGMNtca7qtOtT6ZrcbJ2VWSjItn6m6QexTxSZlxaQBXKMfX48zsxQdrA1MiQfDo1yDtV6MKNLs= 6+Pd/t1Vu7aFknFXbzdNtDmHeTbdqqrHMn5EMYsVBavXREmx1U3iPhFV8YDiBRAcl6+eYEsw5b2= 0WanWB9O4Ws2A2l5x87FtKR8XJuLJap5KVl28ZKtmLlu/XjY2BSckeNUHqaCTRNZNMOAHEavhno= eucTRMnYd0ua2+T1aQk8k4ZWu25u3SuhogVlowSMsSvY0jUkwPqpTIS7pv4HaYJBUOVxrGpCKxe= UFiTaMXAOoXvcbX8duTxgxnfo9OT7VAbpMj4mZyzhakXjF87PycT4igsDz9SfRpImaQQOYCouvU= JKRaLKkIU7huukC3d6ukBNK9HTy6o9T/AO0Zb/wqX1k/QIKiXfjKFbGMduGHMjAgcwCBjog6hQS= MIGABARIBRHkAHnnyL7Axfo5/lRql/t8tf4VL6UdjUeuFQdgLkjk2Gx24wYex0aNGrHBj5hhx8v= p/b/nyH/PGnb+mPug26xezDA2PpfN+MIa6Q1Vex0vWZe5wMZNRrtafmFyoOo989brkUMg4SWAhg= 5FM5TB5DqYqWwDZKimCZNqWAuAAAAT4wqShvL2dxjxRjmH5+RNz5j566T7p47HpAhk19qmC0wMA= gJmePK9Hq+fuWYMWyoD5jwIHAwfMPmOule8vvk7Kd5WV0OVVeUdocqSgrzXw1FNJltUXfoSQaJI= ZZIRpIl1ArKpBXk74537v+6ftX2AzKqzKkzLs/mTVlH8TlgqP2jTqqGWOYuksUTsGBjCi6EWLbC= +KLsldC9zle43e/wCMd3mNp1a42ixWpCIc1U3qzU0/LO5QrI8vA3GfOsm39a8EXZYooqgQFAbp8= imEfIvpJdTba1akclYHsFSlbNFlVRRk8V5B+DZRzHmUTWVZvI65xlWQkmLk7dAXMUoL9BwciZTo= q+GBgYk+9hbIUVwdReEWVcclMJyOKpcsh1VVI/PICiav2yO8HtH2An2lD5i+Y6y2P2T1GsKEVx3= mbczjoyJBIg3h85221xCQcBxzXMpGyBXVezgPDBeLV7A5KTtKYwDYU3fnn8FIMvbPxm+XdFaV8v= 7S9kctNLLTBFToTyZVmRllQqoUlo2J5Oo3GLubuZyiWpFcMjbK6/rGpFbkHauv+MRzs5kMsK5ll= 6pE2tmZRHKgUGwIxWJhLqr7gMKO2FD6i+3e94/Ap0WKWbK9TpRKFU7RRQ9btUKgm4jVSc+M4dzV= RkFETAYhG9ZKUDKDeNjXKuPsv1aOuuM7jAXarSiRVmczXpFtItDd5QOKKwoHMo1dJ9wFcNHJEXL= c4CmskmcBKGlVMRZ6jWS0WnnCuZWhVSim7ic54krso6etjFEpmoTeM3mN45qKhOSqOXtPnAEBER= bnHyHT8Bs4j69Z396xVDIbWMmqqFdPZPDk+Wfw/eBSIUCsrzi2Xiq3FSZHInUUdqx8HBzyIGOpH= 3JB2JVR1vntV2RzsvV0lDT9m8wYkuuUz1VVkU8htxl+YRQ5jloPnRvXwLYKlKgBbE+yOn7V5MEp= qqqqe0FCoCr+1IqenzmFRYEiuopJ6HMCABYVgo5XIJaqJIU4Pu26S+2jehlcMx5ancpR9qCtRNV= KhTrLBxUQMZDLP12igtZGry7j1ox5FfxlAdgmcoJAVMolMY8Yx9Hh2Of61Z+H/wAbVX/4Hq5KlW= S4mTJCZGgWUVZUQ8MZauquX1QsAJ9oeuxKrwicjEqr8gqpBTBTuGRzKNmknOINhk1doB7A492oM= TLCxj6lwttJRleNhsQUYCxU8jg2NioOJ3FIsqBwGW/KupV12BsyncEXsRxtsSMVfbaOkJsp2wWx= jfapRJa53iJcldwlmyZN/GlzAuiB/NOoiMTaRsA0fIn/AJxvIhEGkG6nB27lIwFEJK7wdoGMd62= K2WIMsPrXHVZjbYm5Ir02TYRMsMrDMZZg0TO6kYqYQMzMjMOhWSBoVQ6hUjFXIBTFPKzRpssxIY= kkjgk8cceXGHMQs2+bZMF7A9u9vocBK2FfEkO4tuRLXIX50zsDtuzcxLUbEdyEVCME3MYjGxAH9= TJGrrGDxigK/iFTLQblfF3o+eUbW/tjXOUvjJzKOFnT+Kxs6t8ZAKul1DHVVbQ85Q7C1jCGOYRB= rEgxZJ+xNsTz00Xk2gxWVMeXfGs66fsoS+1SfqEs7ilG6Mo1jrDGOYt44j1XbV61TeJIOTnbHcs= 3KBVikFVBUnJBozD0cjZn8+V9y30BacZ//VIfu05GwBJZ5FJtutiSPG5P2YMLFbxaFtXic7RFD2= OWu7ZRoL2Er0eM1Z/EcyEtfpaSeJOI2ED4u1xw4YpNloZsn3RYGPImeESXXTAgg5juH6VuBt4cX= hiQzbNZHYT+LMXQNBYlo89DQzJdBmzamdKO0ZKuzaii4u0zgQ5F0iFS4KKYiAnHFdsfRV2a7YMh= RmUoZDIGTbnX3Sb+rvcqT0JLx1akUgEEZSNhq5WKvHLySAj4jV3LIyZ2K5SOmINnSSSxLcwDtKA= eXkAfR5aVLNq0BC3oAgsdi17He23gMGNW0DE1Qx7h2pYOZILTNGp9BiMbNWliFCRcSlXiIJGvJt= 5sybZs1eqvYxEU5AStEEHBlFeG6aZgTCoyz+j/AGw+xT0nMsVsw1FtIvFnZICt3eN+BY3xzioZt= HJzdXmpBJqmJuEEVpFwKafaQD9oAGpOdSLcHdsT41qdHw9OyrLLOTbvARJ2tJhlLVkuHxe2cLOs= i3On1huyk13D2FiW4IJvlGKqbRR54rcSPSt1EvVttzcthJFlEDH2i+1i1Ud7lGhNsh2Obir9T8W= 4+qDJxka1Zel7vFDMxjhxZFGsdXIp8WUkJCYmCtlHkXHFEsbnqbszm0+W0eZU+gjMJatKWnLMk0= sdF0etKTIFjVW6kjREvZ0palrjphXjNR2qyylzKsy6YyL8QjpXqqgAPFG9Z1OlEFTVI7qUQS2T0= GqKcWbqErmmUOmntYzHt/xht4yFXpqcreGoJrX8d20swVhkCvNGrVFmoqjYGLJBsuZ+i2R+EWjm= MWinayCCx4/xUETEhKHo8uxkef8ASvPnv8rtVh8ufm5of6vnH+vUbEc+ZssMNlFmtnXI+OrFmC5= xRzwDNKnuatSY++x8hkHIrhaYsEJK2qKNg/BUbBml0KzI1VCPs87FlFY0i7ci6sDZ7zbDQcSsr5= ANbTf42tuquFhgcnqR7W9zNLtFWKGOlq6vT6vB1+ItVxsEzUjepTLayKuWko8QO9Tfxz8kbl8x7= C5xQGBYquCskqKgQLFEJY1DyR07oTLUJHCVmmlenjZXdGliY6lB2xWX9vssrhM8kFRSwQQmZpZD= HISFklVwIoneYNFFGs8qNGrqkigBipOMs2mdJbbRszyorl7E85lOQs6tZlqodC42SDlIkI2aO1O= 7OVtH1eIXB2UWiQIqC6EhAFTuSOIlEvQ259IjbDtgznHbgseT+Vnl5jTWAyDSzWaCkIExrIg5bP= xUZMqpGuTgVNyoLYCvieGcCifxClEB9FBdQ2OLZso2Bmzs9siDO7TKwlZlJGqwdWpuMcKwUdF5B= yLH2JtEqSkmxs2QHkjV4NnIKSQzNihnLeKcsGCS5086wBmOe3R7lGGQvAnaLScXYdjYQaG6kzLC= +yxkZhXLhc2MsDQEG75TG9edVSEcC7bpmZzkzINyJNnSbpEmKn7K51Sw1dVXRimpqal68kzspJk= 0osVL0Q4l6jVDinZivTRg76jGupsnB2uymsmpaaikNVVVVSII4UDACIMxkqjKU6XSSBTNpDdRto= 9IfUFs5DzAPoDRoDyAPn8g89GoxiTXP7p94/X2/wBnbzo0aNGFYNGjRowYBDnyHXHsD3eX6/38/= wANGjRbBjiKRRAOfPjzAR55AeeeQ8w41+geQAHu0aNAFuMGDRo0aMGDRo0aMGDQIcgIe8ONGjRg= xSluWhYKB6iNXd2trJ3GEzLgYlVXhUJ6Tqi9bQoVwQtaiLOYiFFHD6AtaqBI+01pZu3ZzDEy7WQ= cO2LlwxUmXB7YsKZrpEBYr1TgcjMU6z1dvHRM7ZoBgwx9c5pCxjRVEISaYISEPDPmEW5igcIlSj= 5Fgk/iWsUHY1SNGp/n9ZV0uS9lKumqZ6eoOUQx9SCWSIqsM1VTx6FRlVCIYYkZkVWk0BpGZ/Sxr= 7JKOkqc57T01RTQTwDNZZenNDHKC8sdBO5YurM46s8rqrlkj1lY1VbKPem2J7XzOju1saouVV/j= eV2V3YbU8SfEvrRiytSb9JzOKleJygR7V2Yq/ieBJEUkmwpPVlVj7AU2z4eVx1D4tc1x09p8FMQ= NgZNntgsTqUVl6wq1VhHkhYF5U87JHYkZNGiRH0gukDBugw8P1NFNEpo1EJM5zaZozLmdfIYWDx= dSrnfpum6NHqc6GUyOQVsQWJviXx5NlMQcR5bRRiRWSQJTRKHRtIZXso1KQigg3FlA4GNbr7Cdr= a8c1ivucGbsW1dkakZFlabixF7XJKbb2MYiUUaWBE8qyj5xqhJQyUiZyWHckE8aDYTn7t24rwbj= LDKU+jjquFgi2ecf2GZMeRlpVZxKSjlZ8/UTXmH8gs1QcPl3L4zNsok0B47cuQRBZdU5zRqlRmu= Z1cbQ1WY1tRC79RopqqeWNnLBixR3KliQDe19h5CyoMpyullWamy6igmQaUlipoY5FXTp0q6oGA= C7AA2AJtycbg0aNGrDGQx//9k=3D" width=3D"162" height=3D"85" alt=3D"editorial1= .png" style=3D"margin-right:9pt; margin-left:9pt; float:left; position:rela= tive" /> </= p> El art=C3=ADculo queda en pr= opiedad de la revista y, por tanto, su publicaci=C3=B3n parcial y/o total e= n otro medio tiene que ser autorizado por el director de la Revista Ciencia Dig= ital. <img src=3D"data:image/jpeg;b= ase64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEB= AQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQH/wAARCAB= hAN4DASIAAhEBAxEB/8QAHwAAAgICAgMBAAAAAAAAAAAAAAoICQUHAQYCAwQL/8QAVBAAAQQCAQ= IEAgUECg4HCQAABAECAwUGBwgAEQkSEyEUMQoVIkFRFmFx8BcYGSM5eIGRseEkJSgpMjM4Vlh3o= bbB1homNWeW0fE3dYOHl7KztNX/xAAcAQEAAgMBAQEAAAAAAAAAAAAAAQMCBwgGBAn/xAA6EQAC= AQMDAgMFBgQGAwEAAAABAgMEBREABiESMQcTQSJRYXHwFIGRobHBCDNC4RUjJDJy0VJ0wvH/2gA= MAwEAAhEDEQA/AH+Ojo6Ommjo6Ojppo6Ojo6aaOjrwWRjV7K7sv4Ki9/mifh+Konb8V68u6e351= 7f7O/6/wDr0yPfprno6Ojppo6OjqGXNHnTo3gzgAuabcsjzLW9lnDwzAcaiGMy7LzxmscSleMWU= IIFWV7ZYpLS5sSRwgmSRRRqUeQICTIBJCjkk4A9SdNTN6OlS7H6SvaqaR9UcTQG1ySOQX6y2wRI= Y6JFXyOn+FweKFsjm9lcxnmaxV8qPf28zs9gn0jLJMzzfD8QdxapAGZTk9FjrzmbPOneE25tBa5= SmwOw+NszoEJWVIlkjSTyeRXs83mSzyJf/A/iP+/j9YOmmlujqr3mT4svHTg9tOq1FtrD9yX2S3= GH1ebiGa/x3DLWljqba0uagaCcnIdgYsa2waVRGSTRR18o7YJBnMKfI+SKGybGL8PK8boMnr4yY= QMipqy8CiMZHGXGJahwnDRlRwzERMIZDOxszIp5o2yI5GSyNRHrWQQASCAexIODjvg+uPhprOdH= R0dRpo6Ojo6aaOjo6Ommjo6xtxZQ01TZ3BDJZB6qvMsiGQNY+d8AI8hUzYWyPjY6V0cTkja+RjX= PVqOexqq5KxeHvi48cObW2Z9N6ow3dNFlA2K2+XSG59jeFVdGtbSlVoZULCcf2FlBynPltB3DxL= WpA9jJlkJjVrGySASCQCQO5xwPnpq0zo6OjqNNHR0dHTTR0dHR000dCqie69eL3sja573NYxqK5= znKjWtaiKrnKqqiIjURVVVX2RFXpebxEPGsrNRW1zprikymy7YFdIRXZRtGxjjtMQxE2PzRT1uM= gI5IMoyASRqrOcW92P1hDGQqNeTKUOD6faeztwb2ui2jbtC1XU4DzzMTHSUUJIBnrKgjohjGfZH= tSSN7EUcj4XXmt07tsWzra9zvlYKeHlYIUHm1VXLjIhpYFPVK59T7MaD2pHRedMNK5E79/u7f7f= l8v1+/5e/WpN4bu11x51lk22tpXzMfw7Fg1JNK9NZyzCH/AGAqmrDYqSH21oSrBK8OJUWaeRPM+= OJskrEFMr5x8ws3vSMhv+R+3yLWchxSJXZtd0wQz3KjlbX1NKXX1lfCxU+xAEHBBGido42p7dTy= 4veLFmHwJGhuccK8huOGcDNx7JDcmGSyznExCnpG24htovJYZELXPVpckRksuQgvgiOoLYYsSIE= reNd/DPue1U0FwkrqG/RU0kU11tNoaanuctGrK1THapquL7PPVGESeSsqxeY+AiSMQjaapP4htv= 3OaahSiq7LJURyxW26XMRVNvirGUima5RUsgmhp1lKmVoWmCIGLMoHVrqG3vGH5OZryfpt74DdE= YThuFFFAYbqmYh5eN2GJFER/HBZyJDLFDdWeQDwRPsjIlZJVTtgbRECPChLc1zwt5p6t5qasCzz= BS21mSVzBhM+wE0qGW8wy9fH3kGnRiRvOpy3tlkpLuOCIexGa5rohjoTAhk8OdnBMvjQdUbT1Td= rtDits1YrTWOza6SOxjrxrNFIExfKDBG+gy1GiV0Ydg6MWG4ige9IBjoTQRox8beSe1eKu0qTa+= pL2Squq2Ro9pWTuklocqonyMcdjmSVzJY22FSc1qd2+aMkIhkJ9fOLYDDExbb3L4TbL8RtlWyr2= HFSWyutdG1NaZVjaEzGn/n2i+xnMqViT9YmlqA1VTVRkZzJDK4OrtueJ+7dh7ur6feclVcKO5Va= T3OFpPNEXndCRXWzuGMUlK0IUxxwutNPThQhWSJCP0dEciqiJ9/f+jv15dQz4Vc1NWc1NXC5zgp= Udbk1XGMJn+AllRS3eG3csSq6CZiJG82nNfHLLS3UULBzxmubIkB0BgY8ykd5vdO3bt+Pv/N93/= H2/P1w1crbX2avqrXdKWWiuFDM0FVTTr0SRSqcEHuGU8MjqSsiFXRmRlY9m225UV3oaa426piq6= KriWannhbqSSNwCPiGU5V1YKyOGR1VlI15L8l+72+f4dIDeMvvK53Pz33GARYTkY3qGxH1Lile9= yejXR4oNDDk6xRtRGeqdmMt+S+VyOlkh+Ehe9Yx4mMf4d8l/Qv8AR1+bnz9DKq+cvLuCwa9Jf2y= e4jfLJ3VyiWGf3liE5O6d1Y4Aod8a/JY1aqL2VF6qphl2PqqnHzOPePz192mi+Ffge8Uq/QWvcj= 5E4XabI2vmuL02WZOh+S5DR1mLEX4EFnFi1XWY9Z18SrSDkxAnnGSmEG2UJc8TxxJIBIJlUng8e= Hrjl1UZDS6FgDt6KyBt6sr8ts9lUawrSYjAiEjmySSKT0SIY5PJLG+N/l8r2OaqotiOFXNXkWHY= nf0k0BFNd41R29RMM9r4JqyyrBTAJYHs+y+F4s0To3N+y5ioqeyp12fqkySMSS7c+gJA9OAPQcf= XGGlqvF53fwS1vycxeh5McR8n3tn5GpMbsa7MKbZllh4oWNT5Nl8AFE+sEIhjlmDsBrMxxisV8j= D2RKqpC1G3iZTv7TXH/jvR7h2LdDa61hUYZjBQqHyT2BIoptSI6lx4CGBsp93bvidCCKMJDMSXM= xX+XyJJIxTf6RD/AJcOCfxfMK/332L1tLx6Nn3n5C8GdNDGkwY43T7dk24EcsiC2VuRXUONUU5M= KOSJ8tOKBfNFc9rnRpck+VW+de9vlhvJGT7Wc85wAFPAPbJP6e7WR7D69FP5k6mTk/0kXj4BblC= 4hx+29ktNDI6Ma2urrEMXJLa1eyTNqxysldDFL7ujScxk/kVqyQQvVY2y64f+Lzg/L2i5CXtDpr= LMLj4+6sP2jaD22UU9o/IwwQ7gx1UA8OuHaEVI2okYhBKTRNWZjlj+yqOX64b8s/Cg0PpfHMa3N= xMzzde3yoZT9gZtkmGa7yetmt5yp5I6zE4MgzmNaygqQ3DgDujrgS7OSCSzsIo5yUGGua4w8huE= PIPjpzisuIvG5dDn4toHNQc0MnwvCcUIyES2wXNJ6oZkuI3Vu4yEKYAqV7DVgbE+ZjoUkV0nlmS= NVBxG49oAMWGO6gnj3jOPoCPTt9/4cfr+OtHp9JR1Inz4wbGX3/z9xn/+N1tPT30h/jLn2b1OKb= D1dsbUdTdFjgQZmYfRZbQVZJMrYo5shirVrbavrEc5ElOAAuXQd0fONEO2QiKmnwN+PGl+SPJXZ= GIbw19RbGxqn0xYZDW1F+wh4odzDl+JV8Z8SDEDvSdgZ5kCK56t8k70Vqr5VTvnjq8SNB8XNlaM= n0RggWvAc/xDK5cio6ck6SmmOxy2q4ArEYQ4kpQyphrR8BaDSRjzIMPL6DSFImny6IPM8vDAkZU= 5yOQCPo//AIIwcfL8/r+576cW2TujWOotZ3W4dh5hUY5rehp4rw/KSZ0mAdXktjcC4D4ZJprIiz= fPBDVhgREFWRJA44cM000bHUO5n9I+45VN2WDhGituZlTDTSRQ3trZYriPx6McrUIFrPishKjGl= 7eeH414RXpua6cSCRXRNr28Unb2Vfud/he6uW1LfV5xq6XO8rR8r/NZm4Li+E0OKtJf8yIxY8sv= ZVjkVW+swWZzXSRRuZPvwm/Cz4mZ3xB17u3d2s6zaufbZ+vMgfLkxdm+rxuhFvrGmo6WmrAzhAm= ueHVstbCwJgmsZTrIgRpDARhoG1qkaJ1yAkliqgHHYj5Hn8O2o+vr8dSv4W+Lbr3njlWzdcVGls= twiPENXXmc2hN1lNRaQWtWLOLWFVMDK4ASYcghtgqtIc9zGNav2VcqKkJfCU3pwK2LynNx/jZxB= yjRuxG6yyo6fNLjZ9nl4ktAPZ47HY07aosmaJsppE4MzCkb54mivYi9pXItz2GcLOLvG6r2Ll2j= 9NYlrrI7jXuSUVlbUMRrCi6h4MhrgZVJMIZ6DihYJ1RrGu88Tftdu6Kqn9Hz/wAvK0/1IZ7/AC/= 28w7qQqMsrL1qAuQpOeQBnIBOf+9T6H7vw9f21cryg8djXHGHfmytDXOgM3yuz1vdD0xmQ1uY0N= cDZyEVNdapOMEVVzzwMbHYMhVkkr3K+Nzkd5XJ1pui+kkaILthB8j467YpKaWVjDLOqyTEsgNEj= c5EdNHVEfULCvIi+ZzEsoHqjVRvmd2Rez81Oa/hE6n3tmeN7U40Ue+tvj2XpbGyPF9X4JkLgsiF= ghElrL3JcpuKNbG5BgggFMiBdYIBJD8AVNCUPKPHTvzo5ZeGHvrShePcc+J2V6V3LWXVLZYtl1f= h+A4nSTBJYDxZFVZMmLZdYT2IRdJIZIAySrJkGuIAJI5hh3lrJkkaOFBhkBOAWyAOQMnB7D4YPH= YY50Hyz9D/AKP4/DTqWkd2635Eayxbbup8hhybB8uCUyqsY43jzxvhleMbX2IcqNnAtK0yKYOwC= na2UcmGRi+ZqI5dr9LufRwr6zO4ubtoCSZJq2h3m8qrhkVzvhFu8GxZx0UPmX97gkmroyPSaiNQ= iciXt55XqrEfXzuvQzIOQpwD8vrGo0dcL8vn2/Ov3e/6/wDHrnrhfkv/AJ9vf7vf8fw/P1jpqiT= xsedlzoDXNRx71fbS1eztwVRh2RXwMvon4hrZs0tbO4CZqpKNb5gbGXVBGRd5AqyvuponDmS1pM= a1vCvhnsvmxtqHX+Eo6soaxo9psLOzB5Z6vD6KeZzEInTzM+NubFYp4qSpSaOexninkdJCCGYWN= K3xunZCviAZ+l18Ule3Dtdtxf1/P6C0SYwGsihK77PofXjrn1PJ9n4z4nzL5/N0wn4KWs8Nwjgj= r3J8eGEffbRt8qy/NLaNrHFnW4eRWWMggzT9ll+HpKijCBHDV3owEuPJjjZMcS6TtKku8Hg/4GW= W8WCnhl3Bu4UshuDIsix11xp5atZpz0lXS2UcLU9LAT5f2kdbIS0+eQqm1zeKnjJdbXep5I7Jtl= qmMUKuyM9FQTwUwhi5DI9wqpfPqZ1HX5DBVf2IsSd4z8BeMXFvEwMfwDWdBYXsQrYrnYOV1lff5= zkhMkcbSirC7NGkeJAQ5iK2np466kF9/hq+N75ZJIE+JN4R2A8gcZstm8dsVxzAN40kE5pFLTCC= UWN7QGRr5Zq6zEGbBW1+VOcr31l8kMKHSr8DdSPhlHOr7x+uHNRyKi+6L/X/AOfXLlp37u2z7gj= 3PTXuuluwm82omq6maoStQtmSmrI3crNTSLlTDgLGMGHy2RCvSFz2Nte62FtuT2ehhtnleXBHS0= 0MD0bquI6ilkROuKeMgMJQSzkESl1Z1ZFvhjzNseMdnmfFblZhZ+a8acysD8U2frHKQJ5bjXN04= hwljfUdeX6ZQRIJcaT2tYM4YpJhorammFuhInldQ548DLHjEXR7W1faTbI4s7RQa21nscRFMSuG= uIFOr8cygmJjGQWLRlclefJFBDcwwyOa2A6EsOFsLkZ4ZfGXkzurA93bAx2ePIcXMikyutp3RBV= O0a+vh7UtdmzYmNnISsJYM1xY0kRh9SySkNllEcLIFL/ZWmtebU1TkumcsxqrM1/kuNS4wRj7BI= RwAq9o7Ya9aweBkcdbPTSQil004TYZqwsMQgN8Mo8Tm73Pj1Z7duCy7ksFpraSa8RoPEKzl4xa6= meN440rbenLG6IqPL9rUQipp3ip6pWm6pItJp4JXiusl1sN6udJVJaZCdj3XoJuEUDBpGo69hgi= 2yMwhNKWcwTLJPSssTBJPz2eN/I7aHFfadDtnU93LV3dTKkNlWyySvpMooppI3WOOZECx7WH1Ng= yJqOa7tOGS2CwAmGOGHIjfU4e8qcC5haUx7b+CvQVxfmqcsxmWeOawxDLgYR5LWgPVnbzem0kcy= vJVkaHVRgRjWRrM6KNAzfGrD9I7o2hqKynUkrXmbZBiylq3yKZBV2M8AZat7qjVKDQchzWqqMdI= rUXsnVqHga8iLbVXLFupCTpUwvfNQRSGVz5f7GgzHHhDbjF7aKNyL/ZT4m2tK701Yssds183n+F= gSPa3jnsO1bz2e29bTEn+MWq2R3SGsiQK1zsoiWomgqCAGkMNMz1VK7dUiMjQgBZWKa28G963Da= O6o9qXGRxaLlXvbZqWRvZt92MoghngU56FlnVYKhQel1KSn2o1y6OvyX9C9JX+PTw7yvWfJA/k7= QUpResN2Q077+0DFc4LGdi1NSNSnA2T4WuYKzIwKsK6BJIcxTrGS5jb3eOivdPavfv7/1ff/V3+= /t1g8mxbGc0orPF8xx6kyvGrsSQC5x7I6sG7pLUKZO0ollVWUBIJo0iez4CYJI3fe1e3XA0chjb= qHqMEe8HB+7sNdxaSe4keOvv3jNqPGtN5HrXENx49hFaPR4Zc297b4zk1XjwieQCjsDRBbYK3Bq= RkYFUuUAIsUGKEWYkqOGFI5p4B9Iw2DmedYbiE3F/DgIcpymgx6U2PZV1PKJHc2otc8qOB2KRtl= fA0lZWxukY17mo1XtRe/VxFz4QvhxXtiTaGcXMQHJLkdLLFTZFsDHq5rnL3VBqihy6tqgo09/LC= GFBCxF7Mjant1xSeEN4dWO3NVkFNxtpgrejsgrerMbnO0pXCWNcTGWES2IjOJYJHQEwxytZNFJE= 5WokjHNVWraZIDn/ACjk+5iPd8f2/U6aXK+kQKi84cE7Ki/3PmFfpT/rvsX5/wDonUrvHG435bm= XG/iRyOxSnKtq3WWuq/CtiuChmInqaHJKbGbLGrsiKKN6xVQVuLbAHlve1kE9zWo5PI58jL5N/e= H/AMROUOaBbD3tp2uz7Ma6gDxgK6LybN6eWCirzbCwEAaLjmTUwL2QmWp86TSivJcpDmPmdGyJj= JUwYtjsGNwYf9UBEYwPTQ482jPhSxr5aSANteysKgP+JaaKoTEGljM9f14vM2dZPM5VjzsCLpBz= GCDk8NkAenPYf2OpJ5HwxwfgAD+mkkeHXNPw0cL0rjeE8q+ElFmmzcWjnq5diYxhuNW6ZrUxkPl= rLO+ZY3NOSNkQ4ksddZSMjMhsnBx2riWEmkCw3F8XuSfBHdOiOcGN8NdBGaUNpuOWcXecSS4vR4= 7BfjTYbmAFOxHVF1bPKmClcY5EmZC2Nk6q17lcqNnTk/hJeHVl1wZeWvFvBxjjpnzkR49a5piNX= 6sjlc5R6PFMnpaQJquVV9MOuHjRV/wfl22jpzw/uImgANiVeotO12HAbXxWfCdgDjZNnFmmRYwT= CaPPVTSXmT2koUckNgYxSKt4RjfWVzCGuYxWnkjYEgOGJU8tlRggkY+Q9fh276jSxv0cdU/bc7b= /ADaAtU/lTPMG/n63P9JUVPy+4rp+GIbK7/y3OL9MKcfeBPEvivllpnGg9QV+vsou6KbGbS1EyX= NrmQujnNCspQHDZLklyHG15tcHP60I8ZCLAjGzJG+RjsvyJ4T8YeWB+M2fILVgOxTcOEsQcamLy= DL6RawW2mGIsImNxnIKWMhCZgx3q4tk72emiROY1z0c80ecJB1BQMEYGcYx78fn+Y1Ofazz3B95= /bS3viDcasu2n4UXh/7xw2pMu5NDasAGzEGugeQWLhGfY7jCl5G+KJHSyhY/b4nVxm+RkiiB3BJ= 8iRiilzR9F8ObxusY4ocfaLj/ALo1bl+Y1uCF27cHynBC6RbB9HdWxd2+lv6y/sKqJJKuxsD2gW= QR0vrVsoYM1fDIApZjduEa4wrXWB49rHDqAWpwPFaEXF6HHHyFWQYVAEMgg9Y+W1nOLNgaMnovU= 8gmSViqkz3+ZyrCjMvCg8PLPL0zI7/i5gUNmfI+ctcaNyzCa+SaRyvklbSYZkVDSQvkc5XPfBXx= ue5VVyqqqvULInSUkUsAzMpBAI6j2P3fnx251GtJ8VvFf03zwsdsaz11rvZOIWuMamyfMDD8zZj= La+cGJkdU4UdaS9tCFKWexikRJII4vSZIqyI5GtdQB9H0/wAvG1X7/wBhDPu3t39/rzD1T8Pw/H= v+HTWGi/D94h8arzIck0jpyuwW6yrGy8Rvzhcnzi3fYY6dNCQVWviyHJrceFksw8MizjRQktWNG= sma1XIvq0N4e3D3jJm8mx9G6ZrsDzWalOx6W8FyjOreV9PZTCEGh/CZFlFvXo2eYEV6yoIk7PSR= scrGuejiyIokAVsOuFBIODxkk8fhj46aR7w+31vonn5ldhzX1jc7TxHEtpbSg2bg7nerYXN6W/J= Iau3mHLsKyG5EiyAqtyFRibCEW0CYkrlMhkaORMvmXyx8LDaHHjN8K40cS59XblticWfi2bPwXG= aZlVBXZXS2N9GtjXZJYFj/AFhj4lnXIkQkiSqX6Mjo45Hva2JvbgBw75LZJHmO6tD4hmWWtgiGl= ydst5jd+cOO1GDQ2ttidtRHXEYsbWxCNtZzUFiRIx/TZ7daK/cbvDY/0Y6X/wAe7Y/586z86MlW= KyZUAcOcEjHpnn+wGmq+/o26p+125Cp/301f+41P/V7dMedR748cVdB8UqC+xfQGvRNeUOT3Ed/= e14lzkt0w+3iChrojHzZNc3RMLmBDxQekPNDAqN86xK9VcshOqHYM7MOASTz8dNC/Jf1/o60nyA= 39rLjTrDJNsbYyEegxbHx+7Uc9jrK7tJfN9X4/QAueyW0u7SZqQiBQ+zWpKUS6AAUsmHdbvkvt3= 9l9vx9vl0qr48ujOTJmV4/uom7sc144VYo9XXUNSLLELqi+IZDAUXkQA7nxkw5NOjUDy2ZvlZO6= PHi1Cd9Vpae38OdrW7eO7rXYrrdobRRVTlpJZD0zVZjKsLfRMymFayrGUheYhFwxRZpjFBJ4rxB= 3LcNp7XuF5tlrlutXTqFSNATFSh8g11UqkSPS03+6VIwzMSoYxx9cqfXyWH1l4y+npdy8egXY1y= u0MDYhZFp26NCdkGa62lNIMAbVksSBls8UiSUqjNga2Ia1Ps8etGQy2FMXJFPwufEnuOGGVE6I3= ZFZt0fe5MT8ahQpLbvUuWEysDs7OMF8aGPoSJ4I/wAo6RI/VDJimtgIPjX2A1jVPp7cOw9C7Exz= aersiNxnMcYMaVXniOX054VVELrbEZf3o6rsYPOLYAkNfASO9zHsVfKqXTbL1dqjxXtVXXIfj1W= VOB81MEqmE7v0YNLGPBs8cWJqfldiMUixISeejFUU2NXSTFJ9RX3lsFq7Wx7KvW1bZta0y7L3LF= NcPC66ThLVdZHMlfsa5TyEwQ1lThpBa2qZWagubjFJJM1JXF6WVWPJVp3LcNw3OLdm35YqDxFt8= QkuNvVVSj3hQRIomlpIAyqbitNGq1tuQ/6qKNaqi6KlGVW56C9p8npavIsftALuiuwRbSnt6sqE= 6ts606CMkM4Ewd8kBIhUEjJoJ4nujlje17XKi9+sv1Qh4GmG8vMV1Rkrdu/HUuhXlEQapxPMhD4= 8xEuYDpWXx1BEW+Iimwp5DSonBWEDmHXXrmU8I0HxhFhfcnsn4fr935vw64g3fYItr7juthgulJ= eYbfUGKO4UT9cUykBwr4yq1EQbyqmON5I450kjWRwoY9j7Svs25Nv228z22qtM1bTiSShrEKSRs= CUZkzhmgkKl6d3VGkiKuUGdHZPwT+br4La0Apaywt7QqEKtrAirA8wiRkUAoQcDyCiZpXuayOKG= Fj5JJHORrWtVyqiIq9feqp96p/KqdLY+NB4kVfR0V5w/0jdxF5HewOA3VllSUj4sfpZU/f8AX9c= TA/s64uG+VmUSMcrK+qV1M5khdialb9GydnXXfG4aKw2qJiZ3V6yq6SYbfQq6iorJyOFSNW9hSQ= ZZSkSZdxqneO7Lbs2xVd5uMijykZKSmDAS1tYyMYaaFe5ZyOp2AIjiV5WwqE6Xf5XbRC3ZyT3dt= St96rNtkZPc06q1Wq+nksZYaqRzFRFa6avhHlVqoitV6oqIvfrbHhwV9lY85+MUFUknxUe1KIt7= ou/dgYSEFHPcqfKNgcUyvVfso3v39uoSonb9U/4dX7+Ahxrss53vlfI24r5W4jp+nJx/HTZopWQ= 2OwMrEcPJCI9zfSn+ocZkNJsGo5ZBZ7mjkVPLO3t+iu/6237P8M76rlY6Wi249mokcgtLLNRi2U= MWBjqZ3eMv0g4AZ2AGSOCtk0ldujxBs3QrPU1l/iulY6DCxxRVQuFbISoIRFSNwM4Bcqq/7hhvh= v3p7d/b5fh29v5+3f8Al6rw8T/ldsLhlxeM3TrKtxu1ycfOcUxpgmViGHVChXn1l8VI4cA6unUh= vwkfovQhGN+15mP7p2sPb3+9O3b+b8fb7/v9+/8AL79+qUfH5/g/rP8A1ua5/pvOvzAiAZ0BGQS= ARzg/vj9dfo+Bkge841S1/wBIk5of5jaM/wDDWT/82dZWm+kW8uRbEae81lpO4rGSMUoAWsympI= niRyedkJzcjM9CRW90a9w0zWuVFWNyJ262T9H+49aN3lXclZNxaowTZkmPG66ZRPzTHK6+WpZYQ= ZS45lep8E3wyFOFHcR6Xl9VYYvP38je1pPiHeFRxYzzjPs/IdT6fxLV+1tf4heZrht1gVTHQpZl= 4yFNcEY3b1lesFfZB3wgs9cyUiBSQC5xzR5u0EkE/wBTtAsnQYuxA6h25x8QeM/lxqNSl8PvxD9= W8+tfXF5ioBOHbCwuUEbYGurQyEw2lWzildW3NSdGyFLjG7OQYwcY9BxiRzBCBDg4HfCymRL294= zdFqjmiRw6n0TbXB4+zcI1uudR5wIEK6XM3Y+kdr9SOx6eZIwPr5vnF+sVcR8MvaaJZURi6Pgq7= ZtdX+INqIEQ2Qen2gNkesckEav71Yh3tVMfTwytVUaij5VUUJjH+72qO5jezZHo62XkRzl1Dh3i= YlaQtOEGhMwy6Pd+r8WXdl0I52ePsb52IIHkzpUrJE+taL6xgSvVCvb6uG7Pj7IjcGhCyMoVnXp= 6h7QUj55745x7/XnTTQqfJO/z7J3656gdzs8QLT3ArAK3J9hQWGUZdlMpgmB66oJh4LrJiQI4nG= lkmFI8eloK5xAzLK4mhLkhcUPCHXnlStGWhY76SnsZ5Uzqzi9hUASvco8R2fXxpTI+6+VJiR6QG= GV6J/hOYLC1e3dGIi9kpSKRxlVyPfkAe48k4/M/vpptrqj/AHn4ztFpXmQbxHI0Tb3xoee4bgy5= tDnAYAj5MvZSOZYfUr8eJlawH65ajoFPV0/oKrZYlkRGx04a+OpsPlFya1JoO20LhmK12yb2wqC= sgrcpvTzqxgWPXN02YcQoKMeZ8klWwdWyva1rJXORfM1E66Dyk5zahwTxIbPS9zwg0FnWWQ7Y1v= Qv3JkAjnZxMbdR4wod/JL9WSd7Gl+OgaA74pfKgECI5ns1uaxsGKvGT7BbAYDHbnqBHbn1+7Tj1= /XH7HV0HiPclM44kcSNhb21yBQWeWYpY4WJXh5MKWXTSx5FmNJj5qlDhGAEvdGHYzyQKwqPyTtj= c9HtRzHaG8JHnFtbnZp/Zuf7ZqMQprjDdltw+tgw4CwABmrVxikuVlKisbKzkeUpVjOzzxyxxpE= 2Nvp+ZHPdVF44viFZWlvubgN+xtSrjD4tW3KbGW2sfrn1UZjGwPQSq+H+r1Z8Uz6t83xHm9FVm/= xnZnVb3h6+Ktm/ATXWc69xjUOObFEzXNkzMiyub22qpwJ0oqyk+Bjirxp45IvTrI5/UeqP88z29= ka1qrmsJaEnpHWWBU556SRxwTz3z8+NNPwdHVK/OvxUc14iaf4r7MotRY7mhvIbDW5Ra1VleWwA= +NTLjOKXyiBTBCzSlxpLkco3qEtjejBWOVFc9/lrGX6SXtln2pOL2CIxPdyrmOTN9u/v9p1b2T9= Kovb8F+S1LFI4DKuVPY5A9cdiQffn3aabhX5L93S1OU+L/wAkaTxI4eIYmL6vfriTkjimoVtZ6a= 7dlCY5eZJTU5ZaGNv2g/WkY9hM+Gb4D4dsrY3PGe1HMdPbw4fFY11z7myPC5cPK1dt7E6tL87D5= 7dl9VX+NoVAARfY3cfBVs7215xYUFrWGgxkA/HByQknwySywLWbC/hzxv48+u/9+8Y6zjj9qRXX= lYyRk9j6dj7u3pydNPZp8k7/AIdHR0dUaaF7/cnf83y6wWSY5R5dRW+NZLUgXtBfV5NVc01qNCb= XWdcbC+AoIwQhr4Jx54XujljlY5j2L2VF906zvR1kjMjK6MyOjK6OpKsrKQysrAghlIBBByCNYu= iSKySKro6sjowDKysMMrKchgRwQQQQSPXSVvijeFxkHFK+sNw6drT7/jxenLIWPF6htlqq0Nl+x= T3Hb1JyMWKlejKLIHedB3+WmuXRGJXGXNVWodv7D0VsHHNoavyM3GMwxk1hdeeHJ+9zMRyIQBYD= r3hPrDofMOcASx8BI73xyMVF6/SMyLHKTLKO1xvI6qvu6G8BJrLiotBYTa+zrjIXwFBGCztfDOO= RC90csUjVa5rnIvzXuml4n/hXZJxdvrbcWlKuxyPj1cFSFnV47J7C51OaQ9z5Ku2VEfMXiL5H/w= BpL9/nkCYqVN4rJ4g7K37Z8G/Gak3RSpsbfT08twmgNFQXCvCNTXyBkEf2CvEuY/txU9ETSALWg= dLf6kAz8eeK/hLVbbqX3hs1J46COZaqroqQss9mnVg4raLy8OKMOOt0TmlbLc05xFfFwe8WXj/y= gxWmpc7yKh1DuwcaEXIcNyOwgqqK7PYxrH2eDXh8sYlhXnvX1mUxREV7WSOmFlgNFggtjrDs03x= pbXVHNkmc7V1/i1HBH6sllc5ZSBDKzt3RYnSmtWdzk/wGQJI+ReyRtcqonX5syL7tcndFT3aqd0= VF9l9lT5L7f0/n6+iYsolGoSSQQjE7MSaeSVGp27dmpI5yN9vbsn3e3V95/hb2/W3aWstO4K60W= yeVpXtjUkVa0AZuoxUlU88TpEOVj+0RVEiqAXkkbGarT/EdfqO1x0lxstFdLhFEscdxFTJSiYqo= UTVVMkUivISOqTyZIEYnIWMHhlrxAvG/gvKy51Jw1IPHHOjnr8g3gcHPWGfCytdGQHruqNjjOEf= MxfTflNsMMTC31Fpq9kii3DFpSiijiSDTiSDDDJpSiyypnzkkkzvdLPPPNK58ks00j3SSSPc5z3= qrnKqqqr6P1/T8v19/w6kdxl4o7q5bZ6JgWnsVKtZEmgW/yUyKYXFMSr5ZER9nkVwsboRYmMR74= BIvWsj3MWEAMqRfJ1ufbW09m+FlgqBRCnt1FDH591vFxmjNTVGMEebWVThAccrDTxqkSs3TBCHf= nUu4Nz7q8R73A1YZ7hWTP5NutdDE3kU4cr/lUlMpY88GSV3d3x1TSkKOnC8cePGx+Ue2cY1DrGq= lPvL8pjj7B8ciVeN0UL2La5HeEo1WCVlaO9ZHuevqEkOgAEZMcUNDI/1xf47YPxY0thmmMBGRlT= jIHmsLOSNrDskyIzyTXmR2jkVVkOtTUfKqK5WCjNGBHSMUWCJmnODPBTVvCPWseL4lDDfZ1ewik= 7D2KaJFHcZRZxMd2GGREe6sxyvkdI2opopXMharyipCLAgkqWciJ/s9k+/29vx/R1xL4z+LUviF= co7damkg2ta5WekRwySXOqA6DcaiPOEQIzpRwsS0UUjyPiSVkj698IvDBNjUMlxugjm3JcolWoZ= SHS205Kv9ggf+py3SaqUDpeRAiZjRWfnqk/x+f4P6z/1ua5/pvOrsOqT/AB+f4P8As0/729cr3+= 753nf+b5/o60pF/MT/AJDW6F7j5j9dQb+jU/8AZXKz/wB4av8A/wBbL+mJ+SmW1GB8fd2ZlfTRQ= U+Naqz24sJJVYjPQCxmylWNEerWvkncjYYou/mllkZExFc9EVBThh4iO++CUGeD6UC14azYstHN= f/l1jtteujfj7LCMFK5a3IaFBmuSyIUhJUJWRUiVix+VyP2Fyo8WvmNy7wCfVexMjxHG8Aspx5r= /ABrXGNz47BlKhkRFhQX51hbXtuWAMXDES2rgsBa2cmKCcsQiUYZ0P0SQu8pYY6SV5z6ALzj1+7= v8NMduRz/b8O/1xnpPhbUZuReINxYCAY90w+0qu7mbE1XK0KhHMuz5HduypHEGCQ96/JGNc5e6d= 06lRzG/hvbD27f3Umi/b/4muv09Tb8A7gdnIOwTeZW0MaOxvHabHbLHtMg3YUwNjkNxksHwd3mo= gxLY52UdZjzzaauJlh9G3JvySA5FbUudLCTmN7+N7YfxpNFf/k111Z1hpXAIwI8Z+OeRqB3Ge3r= r2+Pdmd1lPiD5Dix07/q3X2udb4zQwPcrR4B7ql/LQ2dE7+Vsk9llBDZpkarnMHhY5XNijRrYei= +AHE/TmqsLwCu0drHI5KHH6sSyyjJ8Ix69yLJ7hgUKWeQW9nagmFzGWpvrGPi9b4YVJWiiRQiwx= RNX3+kGcPc7TauP8uMOx2wvMGvcOqMO2WVVCzmyYvkWMzmQU95cMha941Rc0RVfVxnK34UUyk9I= qWKQ8Ns3TdGfSI9s601diOBbG0HQbVyPEqWvx52dw7EsMQNyAKoFiAAOu6t+I5RDJeSiwRraWAp= o8FgWshbQBnyvatLIzxReV2AwwHBzgevHr3B4x31PoO3r8/v/AG1Gnh5W11N439RUVAIlZVVXKz= e9dW1oA8QgNeAEuyxhAghYGRwDCijxRwDjwsZFDFGyONjWNaieXO/+Gluv9f2lv/swbroXh1Z+7= a3i56l2g+rbRv2PvXZudvpWGLYtqH5bSZ7fOrWnuGDca0Fx6jIWogqkJEkqjwq/029+53p/fpLr= 3T/2/aW9vfv/AIvBvzfr93VxB6sHv9nYHPvyO+noPmf/AJ0wt44uG4h+5/bpy38lsc/KtLjVkSZ= N9SVq5Akf7I2Kien9c/DfWPk+E/sbyfE+X4f957en9nqGn0dzX2B5fxu3mZlmE4lk5Yu8GjDF5D= jlPckjjrgmLy/DwT2IZMsUPqSPk9KN7Y/O9z/L5nKq2P8AjIYNkewPDu35T4rVl3FtXC4flT68K= F05T6nFM4x2/vZ44md3v+BpgTjpGsa56xjPRqKvSvHhn+K2V4feJbIwK005+ynjed5LX5cJKFmS= YdbUd0NVx0x7JXT45kY9mCcGJWrHF5K+cKcWZ/qlNKRkFCBmp2VcluvgZ5xhexJzqNMz+JNz343= 8IKDCKPPdTU+5s/vQSiMB1igOODh0+PhLABPb2VpbVNzHi9I+aFlfXoBSmz2M4ko4wqQAEzjUl3= fjs6TyOosqG78M3UVhUW4RNdYBTbBx9GECFROhnieseiEkZ5o3qiPjex7F7Pjejmo5NdePFR5tn= uyeNnKR2OWYOuNucbcBhrZle6xAx3JXl3+YHYwXYxwQxIUlbltdONPKMElp6RkgsHcQhsWyde+N= 7xvw3BcQxMrw5dfTFY5jlNSFT1mTYgPXkk1leOGQYIMbqgsuCEyWF5TYCTDCIvVWOYwp7VIklIx= 5at0Fy3LYk6cEFRjGQeP+P3+umof+CTaen4nGnVp4ZKmrvK/cozqz4p5SxVC6tzW2DrJyvJAprR= SK+vd60kMaSzCRzLCx3ZG5zYX8OeN/Hn13/v3jHWK8Gq2gv/FT1HfChMrBbs7e1wNWsc1zK4ey1= RscyEFr44oY3NFjnbA10cUTFbH9mNjezUy2wk/v5438ejXiff8A594x+b+v83Vh/mv/AOufj6j1= 9dNPZdHR0dfDpo6Ojo6aaOvisa4G2CKrbMMU+vOHmEOBNHhLDMGIYsc45I07HwzwzRucyWKVj2S= McrXNVqqi/b0dBwQwJDKQVIOCCDkEEcgggHI1DKrKVYBlYEMpAIIPBBB4II7jVDnKvwJNE7buLH= M9DZKTojJLKaYs7F2163+tiipVkke+uqfiBbPFFnnej5Ias4ylGiRIa+gEZ7LWYV9H75cxHugF2= DpMsBHqjbBbvKoFVnde0jhXYq6Vq9vdWIrlT5Iq9unFe3v37r+j7vv+f8/R2/Oqfr+fv+v8nW3r= J46+Jdiokt8F9FbTRKEh/wAVpYK+eJAAoUVMqfaJAoA6TNLKVACrheNarvHgv4fXmrkrJrO1HNK= xeYW2plo4ZGOOomnjJgQt/UYo4yTyfitboT6PZitXYgXXI3cZmVDDujnIwrWgElDXmvjkbJ8Mfl= 1w2e0eDMiLEVFWU1UarXOcPbDva16MA6j0tq3ROHgYFqPB6DA8Vruyw1VEG2D15vIyN5tkZI6U+= 2sp2xs+Js7Mos8lyI4giRUTttHyp7/P37+/t9/z9u3b/Z1z15LdW/8Ad+9JFbcd7qq6GNuqGiXo= paCFh2aOiplip/MAyPNZGlIJBcjXp9s7F2rtFXFis9NSTSKVlrGL1NbKpwSr1dQ0k3QSATGrLHn= +jIyTo6Ojrx2Ma9aAB20ddKz3W2vtqULsW2ZhGJ7Bxh5Q578dzTHqrJqV5wfqfCGOrLkUwJSRvV= k9CdYVli87/I5vmd37r0dNTqLn7R/hn/oo8dP/AKM69/5f6ytLw84nY3ZC3OPcZ9C0dsDKycKzq= tSYGAeJPG5HxzDFjUUc8ErHIjmSRPY9jkRyL3ROpHdHU5PvP4nTXrjijhjbDDGyKJjUZHHGxrI4= 2InZrWMYjWta1E7I1ERET2TsnWkbjjHxzyHNH7IvtEaguthvtAbt+dWuucSPy51xWKOtbarkRVT= LbLYV/wAIIgRilqQN8MP6MjPRj8u8ujqBx2J/E/X18NNQB55c+NS8FcZwe121hmYZpVbGtbehBC= xMOiPWKWpChMJWzgvbOthUeWKdrI0jWdXPRyPY1ERVpKtfFp8JOxlNsS/D6DtLMj1p3zHaS0Ssp= RTkc9XEFyHSyeaWT3fM9JHorlcqPX5sZb64r8f+T9fQVe+tZ0uya/FjTLDHxbom3GjrDT4WDFkQ= LUWNc9z54I2RuSZ0rUa1PK1qqqrGn9yU8Of/AEV8EX9NlmX9H5Tdl/lRerFMQHtK5bnlW6Qe2Bw= M9u/Pu92mlgPB815e8gfE3rNyYthkGK69wPItm7ayACkDYLjeF1+S1eV1+G4fXOHgHBgRlxkNdX= 1tdBHC59PVWJA0DIQpPTcjvOMXHPJ8yk2LkmiNP3+fynhWsmbXOuMSssrfZ1qQNr7B+QGVM1q40= FowyCEqV6wyDwei9npM7ZvUOitO6Bxr8j9L62xDWmNun+KnrMSpQ6phxisSNTbQiGP4y2OWNrY1= OsiCi3Ma1izK1qIm2OkknWwYZGF6Rzzjvye559+mvCSOOWN8UrGSxSMVkkcjWvY9jk7OY9jkVrm= uRVRWqnZUXsqduo12XDDiJcGk2Vrxf4/WNgZNIQWcbp/ASSyZ5nrJLNPPJQrJNNJI5z3ySOc97n= OVyqqqvUl+jrDJHYkaa6Vc631/kWHw6+yDCMSvMFHACq4MNt8dqbHFoaytiigr6+OhMEmrGBAww= QwiDMGSEeOGJkLGNY1E0j+0f4Z/6KPHRf8A5M69/wCX+pR9HTJHYkffprQuF8WeNOt8kAzHXfH/= AEzguW1TS2VmT4jrPDsev69h4ZFcc0K3qqgQ4VpgBZQRTYZ2IQIRMPKj4ZXsd7iOMPHEvNk2WVo= bTxOxm3g+TJns+t8RlzBMjEIiLFvkyN9S63S4GJghngsvjPjIpoo5WTNexqpvTo6ZOc5OcYzk9v= oaaE9kRPw6Ojo6jTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dNN= HR0dHTTR0dHR000dHR0dNNHR0dHTTR0dHR000dHR0dNNf/Z" width=3D"222" height=3D"97= " alt=3D"Logo_cicncia_digital CON ISS1.jpg" style=3D"margin-top:0.55pt; mar= gin-left:271.45pt; position:absolute" /><img src=3D"data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAAEBA= QEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEB= AQEBAQH/2wBDAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQEBAQE= BAQEBAQEBAQEBAQEBAQEBAQH/wAARCAB0AOwDASIAAhEBAxEB/8QAHwABAAIBBQEBAQAAAAAAAA= AAAAkKCAEFBgcLAwIE/8QARBAAAAYCAQIEBAMEBgYLAAAAAQIDBAUGAAcICRESExQhChUxQRZRY= RciMnEjOpGhsfAYGSQ5d7Y0cnN4gYOHkrjB4f/EAB0BAQACAgMBAQAAAAAAAAAAAAAGBwQFAgMI= CQH/xAArEQACAgICAgIBBAMAAwEAAAABAgMEAAUGEQcSEyExCCJBURQVMjNSYXH/2gAMAwEAAhE= DEQA/AL/GMYxjGMYxjGMZ8HDlu0SFZysi3SAQAVV1SIpgI/QBOoYpQEfoACPuPsGMZ98ZthJqIV= ORNKUjlVVDAUiab5qdQ5h+hSkKqJjGH7AUBEc3PGMYxjGMYxmgj2DvjGa4z8AoUwiBTFHt9ewgP= uA9u388/eAQfwe//wAxjGMYxjGM2sZyHKJynlY0hiCIGKZ81AxRKIgICUVQEDAICAlEO4CHb64x= m6Yz4oOEXSRVm6qayRw7kUSUIqmbsIgIlOmYxTAAgICICPuAh9Qz7YxjGMYxjGMYxjGMYxjGMYx= jGMYxjGMYxjGMYxjOpd36K1RyP1zMal3ZTI2/67n141zM1aXUepMH60O/Qk406x490zdALR+2bu= k/LcEAVEi+MDF7lHtrGMZ5tHMLS2tuLHxUXBvS3H+vG1jq0NrcRZn8EQExOGghkpyzK/NnJmr+T= eeIXwt0hXTMcUjeAOxA7j39JcA7AAfkHbPO76oX9by4Of8AELhh/wAzO89EE6hEwExzFIUoCYxj= CAAUoe4mMI+wAAe4iPYAxjP3jOn3PITRDKcGsu9zaubWIqwNjQa98q6MqVyYfCDczBSUK5KsJv3= QSFMD+L28Pf2zkt52dr3WlLl9jX+61em0OAjXExNW+yTUfE16NjGqRl13rqWeOEWSaBEimOJxW7= CAfu9x9sYze3drrTGxxFPeT8M2tc/HS8xCVtxJNEZyXiYBWNQnJONijqg9esIdaYiUpN23RUQYq= ybBNydIztuCnTPKqzXum8f9q2bWjVd3dYipv3cKm1TBVykoUClcvG6QkOB12LMV3iJRIfudEBEh= gASjVd4AdVmvdTH4ifZE3riaOPGjQPDrZ2r9KOX6hmCNpVPsPXr+7bJBm78ozQbpLotWsWkoBXJ= 6vXK8s5RbPVnbdO4YrNwKwCmaWiVCnASiQX7MwHAfqUSeaPcB+ggICA/T7++v21OXY6vY6+G3LQ= mvUbVSK9B/56cliB4UsxdFT8kDOJEIZSGUH2H5Gfqrkeu2muvy04dhFRv1LclCwO4LsdexHM9WY= dN3FYVDFJ+1v2sf2t/yaY0V1MN8cS38JsNa82bZq9i2drSoTes7S6kZd3cDXG9QkHO1upsnLj1C= VpJCvZJzBuWP7qEi1QM9QdMActVbqSZvEmQ3YQ8RCm7CHYQ7lAewh3HsId+wh3H3++YBOOnbwOk= OQcPyjfaapUnuevSxLDXrDITUvIRFesZPAKdjg6W6mlqZETySqZHSEuxgW71B8BZBFZN6AOMz1Q= fsXPiBs8auPLABU8hwkt5YD9BU8sxvAA9h9zdg9h/IciHjXh9rg3Fq2hu7qff2Y7NuzLsJjJ0TZ= l9xFEsssrrEgA6DOT7mRj/12Zl5N5lT53yuxv6Gjg49VkqU6sWvgEXarWhCGWVoYoEaSQ99sIwP= RUH111n9eM4QGzNcjNlrQXynGsJjeAsGFmhhlhP27+AI4HvqxP29/ACPi/TObeIvbxdw7D79/tk= /yvs1yjL8XXwU4/ai4pa95d6Vo7PU+2l99x9PvErQXLutMbtE3mDtUy9e2GIjnKMe8m0Z2HbvE5= dNsk+WF6/9aq68whkbnl65A6L1e/bxeyNw6yocm7MQrWPt95rVdeuDKG8BARay0m0XUE5v3SgVM= RMPsHvlX/4wuaiLD0mKRMQMnHzMU+5PaycMpKLeN37B2ger30SLNnbVRVuukYBASnTUMUe4e/uG= MZJN8OQ8eSHRb4LPX7ty+eOKFdTLu3jhV05WMXb2w0ymVXXOdVQSkIUgCYw9ilAA9gDJuMg5+G4= XTW6KPBUxBHsnRr2gbuAh/SJbi2IU/b29wA3cAH79u/098mTm9jUCtOkWNju1TgXrg5U0GczYoi= MdLKGEClIm3ePEVTmMJgApSkETCIdu/cMYzmQ/Qe35DkeF66nXFDVfKGY4obUu59d3qNi67INbJ= Zkk2tBkXNjYhIN4U9lTXVRhZVBoo2VOE+jGR7gHSCTSQXcmFuWQL5ixOyB+m8anZnTBQjsq6Rmp= yG7AU5VwP5RimEQApgP4TCIAAiI5VX2r0bNvc5OXG+eQW6dq1vSuu7TsCQRpkU1I1uF/m6nAlRg= oCRWj/mcfC1xm9io1qu0K8knskUhxBzEN+xPHptzZ2deOt/qqq2rEllVkR/qIQKjtIXkLIIySFV= WLfk/Qbr1Nt+I+PeNd9sORHyjyabi+hocflloXaXtNsZN7NcqR0Y6lCOval2CpCLctiusJX41Ba= WAlZVspbL35pzT9BdbQ2TsipVGhtWoPPxLKzLROPdImTFRIkYKSiqkq6dFAAZso1N06eKGIi1RU= UOQg9M8NOcWlecdZ2BbtKrzikJQL26o7s9iYJxL+TFGNYSTKws431CzpvCTCLxQIw0gRpIH9E5K= 7ZNVkzIkiFunw9Gr7HQ4CuDzC3qqxrLddOsJWw8BZKbDKPDeYuMTXjLxiEcg5WADqosJFLzO38f= fMP9YUrlP0Gbdsa+PaVB8peOGyGMPHy9iodmXrq9fk4Z85GGlbFFOYyfc156LV+9aKgKMhCOzPG= qJLB6hEG5tdLtdxVtV5b2sSrqgjC1NDIbssblABI4i/ekKuOiRCT0Qzso/blhanxX4i5Nxfd6zh= HkWzybypJbrHi2l2muPD9fsaiXI0npVX20hq2dpYpM8kccm0iPzRiGvWl9vma4J3AfoOMg34n9d= fjtym2lQ9Jx2p9yVDYuwZL5REIrsqtYKwk8SZOZByq6mmFiaySLFq0ZuV1nZ68USJJiYyJffJxS= e5e/6/T6dv0/z+eb6lfp7GIz050niDepZPbpW9Vb1IZVIPqwPRH4IP85R3MeC8u4Bs49PzHRXdB= sZq4tw1rojJnqtI8S2IZIZJYZoWkjkQSRyMpZGAJIPX7xjGZmRPGMYxjGMYxjGMYxjGMYxjPO76= oX9by4Of8QuGH/MzvJcPi0effIzh/wAYNFau0G4tlOZ8k7tZ4PZe0Ki4dRkzG0+oMYd0vr6GsTM= hnNclr6ebMYZRodOQ+UwMo0Zj2cuDEia6mqBHPxfPBxFQTAUb5w6P3KIAIGRnJFYn1AfbxkL4g7= e4dwDt375Y965nVl469Pyg0LWFm0tVuVPJrcT5sto3QFmi4yXgU5RGTQioy9XM71hKLRUQzmXCb= aFQjWnzyySySsbErsU0JKXimM7o4fcFOn9vXp8aWMlwn1xSqdurRVSscpWrnUYeX2VHr2urNXK7= ye2E6Yp2yUtqSzkXqNvO+azKq/p5JEzFby00KqXQbUr/AC35ccxuj7zUj33Kfi9x7kNo7M0PB7S= stnkVtey+sdpxWrH0bHLtZho4d1+fgbSzefJpFd1HQkpDmdwrVmvMSyjiwRrfit1/t0VGM2Fu7q= Z6c4eSE3Goy3+j7oLiHr3ZMRQ2KzMqqFac3K/Tvr3MiwTEGz0qT2dZIuEzlbSj5ECHCsj8KUnOp= dcjmYlaZ9S12VHRnItGwWddi3jVrFNJchdUJyc4rHNBFowUlXhV3x2TYRbtRXFBEfLTL3YzgPRB= 4X8Z9xdejnfx12Hq2LnNM65Dk+2pNGSlLBER9fb0/dkPXq23ZuoWWj5IUYqGVOwQSXerEOkIGWK= oqUpy2u+ffTV6a3EzirsndFb0cemXSuLVlnr6xRWx9pDJsNhWazRNbqCiAO7q6buUCTEo2UdsHL= ddk4aJrkcNzpiIhXn+H0/rKnUl/wC25jf/ACGg8lz+Kb5MDSK1wI4vxT9RCV3hydh71YGyDgC+o= qGq0kCJtniAdzGbuLRaYV0gY4FIZeKN2ETJj4dPyEkaDdkEqRqNkQy/kdU5vsf/AH+v6P32Ouxu= uNAHkWgBAYHdaoFSAQR/n1/r7BH3+PxnD+mpxd1XylpO+zb6h5u6N4GnvZGomNcrlBrQ0i3YP0j= ybJzXp6JXOqCihQJ6g66RFEQMVPuBvFWg+Hpp/UP5v7m5B8YtN8or9pjS9zhqhM8p94Iz8tPbTr= mt6/MT6UdR9TP5aUVGBtOypOTWjXc21IivGx0YvJLOl2zNaEmrjXSbiU6vUNsMnRgbGDSDx09Fw= YiIEdyXqnapFRMJSgYizr05fF+9+6UofXK/vwSIB+3zn6Ah9Neao/t/F1xDKn/TxffZeM6Fp5Gk= 9tvyBEd2ZyYotvaij6LEnr40T6B6HX995bP6jKSa/wAp7WqiLGE1fHnZVUKBJLpacsn0Px3I7E/= jsns/f3khPVH+Gm4Z6e4Q7n5G8WbTvbWPJHjjrmw7kjdiy237Vb3ew3NBj1rLONrgnLORFnLS7B= g9Vj5uqHrx42aFq6M1csSrMFMO+O3xE+/9Y/D02zc1ynFLxy4pm/j8LtXbAsYFlH0ivMUNpsCA2= Va/UAb5zNU2lmnWgrvSuvnk5CQbmbF2pJyKqlwvqm/7tnnj/wB0fkB/b+zKx9v7/pnklOpHyuil= CRQJKG9d1PbI/FYPF5SfyzizWEPKP2/d8xX5p40+/wC94UlPD3ADdrwyjMu4fD59JzinzD4SQ/P= 3nRUCcxOQ3Ke17ImZWx7skZS4NajX67c52jNYiHYP5FVr81fOq+9nH84ql69AZBpGRvoWsYUXET= 3xOnC209NzUVE1NxztdkL0/OR+xm9wR0XbJ2at7LRG+tex8kc59ZTU68dSULTL7XLG6dL1xw7kC= IS8K/WIqk3MxQQtNfC8/wC5H4eewfx7s9//AF52V3D+3+/IqPjZnIE4acSmgrCUXHImZWBDubwq= g219MFFQQ/hEUhcAUBEe4AqPb2EcYzFdh1bLV0wfhluAEXpJ80Y8l+RULtun6zmXTZB8FCr8Rty= /rXPYiDB0kszey0QlIRkZXm74ijNOYlkJJw3eIRizNxOv0vukVxDU4gai3Dyxo0Lyu5N8i9WU/a= m59sciH6uz7KrYNiV5nZloOAPa3cgnWo+vITBIlstDos5F0ZmD547UXMkVDzx+ootZh4FdF5ByZ= 4NRJxT3UrDkN5osQnT8pNpFnTI9+yIuhZpwfngTuqCQN/MECCn39HTUXQC6aT3WOu5NxQ92OlZO= h1B8oJOWPJps1BV1X49woZo1jtqs2bZAxlBFJBqim2RT8KbdJNIpSFYyGnkzuSp9IHqTa+6fm2Z= Gc3B0l+eMHUpdjrHYV1sE654y2x1djwaS9Bt7iXLYW2vIO3w8LJSlWdywtmVfkju2KpX8WsExGn= 1y+H8/0lOoToTlnSYO5bD6ee2LVASMlqJ/eb0/pkPMxaaCOwtUOnB7As5ZEsldFe3UF+5dlH1Kj= 9u0TckrDkFLbdo+HU6QUutH2K+cfbDY16wX1MfN3jkXyCnDw6TdcHpjFfT20nINWxFiFXUL5hER= EomUAfrncHWo1zxRvvTG5B07lK8LFawTpLUKNLR7Mk3a4/abUhG2pDa+jzrpOZq5PLMpHRkXGNn= aCky1fPo927RjXj5YrGYo81uQ/GG68AuLGguJWt6vve58zYqtxPBnUK8xOGgoIpYUzl7t28OWUm= awMKLpOGknstajvFl1lpVuhALkKuuuuzy34S9HzitxG1LRa5LVpxuHbkfRJOsbI23sGasc8+v8l= bmqxbuZeAlZl9Ax9efHeuo+EgiMlyw8AkyYeqduUV3zmkL8PByZc9MzqbuOJ3UG19OUa4XzX8Bp= fT1p2kq+Sl9BK2ydcbGgqnCs371eLrlH3HIWgr2WcRSZe9mPCrLLg0cyyqfpwAoVQhFEzAYhy9y= mKICUxTAAlEBDuAgIdhAQ9hDsIZ+MAylSAQQQQw7BB/II/o5zjkkhkSWJ3jljdZI5EYo8bowZXR= 1IZXVgGVgQQQCCD95Ue4ucVdR8FetdJ0W52VjXaY+p8/a+NhrCsZIsq7voFjo2spSTj+gGSgUD2= ivNVHaya8qdk3FLxunRUTW4iKFEoCHuH5l7dvt7/X79w9/vlOX4kBIjrkzxqaVhB4veVtaPUkkY= YjhSYWMrcnBK8izI08Tk7w0iD4GRG4GXFYQ8sBMJAGwh0ymHLiO4q0dnzEcM1tiJIlCCBYVz3NC= m+mQ+SobEcHMdu4tqRfMBwoh/tAM/SElTqyxXqhohoZkqbPb6SCo6wwWpLaWUBMSidYm+CY/hXX= spEQT7JH0V/b2fV3nPUbDlfjjxT5o3XJ69jdbzjdPjN3Q35lXZWTo57tUbvWIB72K9p42sbT5Ao= itWo5I5HWcRRyHh7gA/njNC/QP5ZrkwzydjGMYxjGMYxjGMYxjOvdqbNrOnaJO7FuJLCpXK4k2W= kiVWp2a8z5iOnaDFII+rU+LmrHKqee5SFRONjHSiKPmOVSkboqqE7Cz8mKBg7D7h+Xt/998Yzzv= Odbm27a+JC4jc59daJ5QT/GPXdk43SV62WXjFvlo2hk6LMyqtnUGEf6+a2FwWMZKtFDFZxbgy/j= EGwLHAxA63+I0qe5dpc2tDdUzjPrfcmz9K6hZawr1g/EOkts1BfX171XcXl5Yt52t3WnQEp+DbM= 3ftlEbE0auYcsklJx0g8ZOjMk3fpFAmQA7eAv8A7Q9/5+2fNVsgsmZJVJNRI4CU6R0yHTOA+wgc= hiiUwCHsICAh+mMZV31t8RrWudNIZaf4H8UOR915dbBiUq63hLjRhhdQacmZhuRjJXnZ2y2790w= QpNQXcLSIembElZ0rRvHotGLp6BkK/vR5o7noy9dXk5Uebsta63X5rTm0aNTNxv8AX9wXre1Jq0= 37W15g5uFNCRcwCydoj4GXMiRqq9K3mS/I1lxkBBM3o+MIOGivN+VxUdGecbxrfL2LVn5px+plP= TpJ+Mw/cx/EP65/QtHMXKhFXDRsuqmPdNVZBFRRMQ+gpnOQTEEPt4RDt9sYzzb+AG0v9Wd8QvyB= 3Vyvouz9P6L5WO97yeu9jXTXFuj2C9P3Ldkdja6sz1snEuH7FpIEZsYuYaqtSSdakXZ2dkYxLhn= IItP6PiAtxTnKvqx8E9t0Kh7jkuM0DW6XT6Le5zWN2qVVvNiZ7HnJu/ydIPZIaOdSkcLKSrEeWX= O1bNZIzAFo71TEiTxx6QrqJjHpkjvGDN2dAe6J3LVuuZEfzSMqmcUx/wCqIYcRca5KkDpi0cEbm= 8aAOGyCxUDB7AZIFEzAmYO/8RAKP65g7OkNjrdhrzIYhfo26ZlUexjFqCSD3C9r2U9/brsd9fkf= nM/V3TrdnrtiIxMaF6pd+It6iX/FsRz/AB+3q3r7+nr7erdd99HrrKZVVcUixSsG63vva58Y9CQ= UrEXuVgWrKVhZbkJaqE8StGv9bTEiwjn8nC0Vva2EfZLKxIDda0tItKGUM3ZLquQic+Ex31rThj= vTmE95QSk1phjs2na5iKO/uFKuzVhPSUVabK5ftWzpvX3KKJm6Eg0VMZ0dAgkWASmN4T+H0lvls= UI/9CZd/f6tkO/5CHun/aGa/L4z7M2YCH39Mh7CH/lh9PbIb4x4KnjjiFHicd8bKOjYvTJb/wAZ= qpcXLUln1aFrFohkMnqXMxDkEhEXpRMvKHPH8k8xv8tk1/8Aq3vV6EDU/wDJW2ENKpFV9xMtWoC= JBGGCGHtAQpd+vYw/dXjmHx5pfDrl7oCwX06O4dicUNqNKTRY+rXGalrC6u1Bn42rtmKkPAP2Ir= y75Qjduis7SUKcf6YqYe+UXOnJxL1Nyh6NnKjhruyzK6M5TSnLyvbi4pxmxqrcIFWw3hjq+AqMf= EeoWgfIJC3dN5OU1w5VXKkwkHDOVWTVLGJkP6cEDszX1u2LsLWENIMZS5atj6a+u7FJNBcIQl5a= yz2uM3KwCfy3rhhDOHx2ZykURZuGS5g8DtIR6ujF+QVi5IzRSRVCqHF+mVdtFpBK19zIbP2lst8= J3b2Wgn6Ms2i6lruqMVGcamd9ESM5abAEqZAkXDMGL6YsDK+yof0IurTqDpe8bJXpudUCPvXEfa= 2hL5fJGkS+xKRaj1m4U66WBzaVGMbIQ8VJieQjbHJTqjV2kkeDmoZ7FuoqSdrA8IlgZ8Rtym291= bNQ0PbHE7SG0pHgpxt2CtXGG3ZymWGJkd87evzRVn67XFOWjjz76kUyBgHSS9gcM2ZBfTTlB4kg= qVqke5RHbbuFx6pd/wCGO169qHZGrYDh9WOTNQk5PWDQtvgrBY9zWbXxa+4k5SZn2EhGMIeCRXK= 8Ri4t64frnVN5aJCI5Kc2jIli0Rj2jFk0YNyFI3Yt2qCDRBMgdiERbJJkRSIQA7FKmQpSgHYAAA= xjPN+d8LKL1I+hrwN40aksHpepDxPr25bZXdEWGu2etWO31Ka2BcbFcaP6+chY+FazTuFQgbNXB= dyRUHLhqaNE6Skn5qNlXpgdcDiq+4ras1DzY2ZFcQeV2iqPWdWbe1xyLI91bJSE5R4hvXC2mAcW= ttGtJVlYm8WnJrNWy53sa9XXZuETE9K5dWMiNGCagKJt26agB2A6aKZDgA+wgBgIBgAfuHf3zid= j1zri4qJLW2j020rICAoK2KsQc4qkIe4CkpJsHRyD39w8Ih7++MZX05jc4aL1CIBnpbRU1YWvAS= Jt9XmucnM/8K3RnQpfXMDao1Vvx40g5QhiTGxLNtyyow1fudoq7R5XKtQnMuRR+7dzCZGvAdHck= dHdS7qCVW37fmbBW9A8Y7m6p/BPjJaNfX+LLtbcEbHq/OOV+yGD+qpRLVpARiCle0PDWd6irDJG= mLYsxipt6zFxZFtkfWIXX9oarsGTCsMavNi+Ysmzdk0Qi0Y1yd2RBFAiSCBCNinEgEKQpPCAl8I= FDtTr031y9/cT7bZtNbZrMPyLo9JsMnB1S1vn567sMa62dnJAqrWIrSQa2JBWKFqq3dSrA0quRQ= p3Mu6EfEGo2W6pamSst5njjs/IqyqhdY3X19RIqBnAfshSqsOwfbr6Jtbxx4c5h5Vpcgn4bDVvX= +PClLPqbFmKjPcrWzOry0bNlkpvLWeKMTQTzQFlnjaFpCHQbt8XPwi05tzTep+RtV+YQvMegKuo= imRtVp1rnJncmtI+QYOJmrOXtWgZNBnMUSTm29lqbyZexoeQ+sca0UduHjZJvkP0Nut4z2BxJqm= peoaF801yG06VhQQvuy9ebBh4HcFQZtATrFzf2Z5XBh4y0N2SBYW4Gl5FoR9KM0p8ihPnR2jTt2= 9fEN1qs0+Gsy3DfcLI1gbqKQD24vGMDWJQxUyHMeNnDxbz1yIAomoJmzXudIxDlDwKAYcONO7j5= Gddfe0lpvY88vpLi1SoNe226q6mKk0XeufPBvVmM5Py7V8rYJZ49MZ0kg9apw6LeMeOmsSk9STc= hgzco17NHW17NevzsEgroksS+zAENNLIiCKMDtmb7IAJAOTbU/po59BTvcl57Xg4TwbRK1nfb61= cobKylaCZYpq+q1ustW5r2ylkZa9WGQ14TYkVZJgVKNy3ijzI19zM63C+xLFXIyZpjqo2egcfPx= EzK5cV8KYyNKxVnYNnJfLYzFgQaWiXATJGcsAmBapnKoj5prdpA7AHYfb8u3t+Xt7j7fl+mQ28c= Oh7xD41bSpG5KfO7jl73r+YJNQD6cucYRgV6DZdmoV3HRFcjCu2bhq6cN3DU6wEVRVOmb90whky= oAIAAD9vb/w+392d+gp7CpXs/wCz+E2bFya0zRN7d/MEJBPqP+WUqo7ICBQD0OhpPPHKvH/KeQc= bPjY7hON6Dh2p41FX3Ff/AB3il1clpBLXj+eUetmCSGWxJ6wtNb+aV09nLHXGMZvso7GMYxjGMY= xjGMYxjGMYxjGMYxjGMYxjGYjc+N9WHi7wt5P8hajHt5W16g0rfbzWWLxIy7FafhYF2vDnfokEp= 1Y9tIi2dP0ynIY7RFYoHL37hlznEr7Rans6k23XN7hGVlpd6rkzUrXX5JLzmE1XbBHrxcxGPEu4= eNu9YOV26gAIGApxEpimABBjIutTaj5IRGpuDG9NYbptl3vFla6fsvLom4NqXScpWzdfbIpTOS2= dPVSpyz2ZqdGtcBZJNrYteRlDhqnEoNGxqoYE4V0ZEsPO1OYu8qHrfRW7KbtrcO17Fc+q7Tdchy= YqMzY4LjDsXSl52/P01/pSIoVo2A4Y2SCiKeieuN7HVdZta0lYIM07X7U9mm61jlrG2teIjPXlP= 1Vq9fbexbfqTTEXFQlI1/YC1ordaIqrdoyoDC3T8dCs5+1oUFjHsEYH1r1E7xyxZS1lPPS7RB8T= BFl0OdCsdQ1zQpN7cjXGodW7WgtzceqM9sdNdxGgrzXthJbFYSFQFWli7sqaT718GihsRzbk2Vd= mZlmwBq6kV3pmM6B4R6joesee3Wkt8Zc7nSkdZX/UNlZzto3DtKTpsa4n+OSs5OWbYkRM3ZaKuz= GJdvHUqia5FlSQLZEiUIpFotGoIY6a15R7yptz6QEghc9822W5Gb5tuv8AcG8bFMWmN0Tylpdop= FrsSc7T9XXq9zM7DNmci0rs9RZv9ndCatotB0WsoMa1MJRBpokem7rb9oXJK7P9n7Wk4rl7Tq7U= +RtEcvKslW9kq1ygyOt0p1dy0rLeerr6SrckZOVaVWWhYx04aMzFaJIpqoLdG1zo36zg4HjfEv8= AknyUtMjw+tsHYeMk/ZJjXjx3qWHhIeQgDVCNjUaA3grBFysQ8aMZGTtcZN2EG8FBoMJZk3aLIO= mMwp5q72snGPqa85N/05khI23UvQ+ibnWWrpAzlmafieQuzVYlZ63KYDLsmr8W7t4j4i+Y2RVKJ= yd/EHMtz7a2pxR40dL3lPW9q7Ru983NuLivQ+QEdbtjXO313b0JyTrqBbsq2pE3NPanW5WLscm2= sdNPTIOAQrjdh8jjG6FeXcRp5HrN066FeeSWwOR172Lcri92jx5DizedeTcVTlqRPaV/Ek5aFK2= 6TSgkpr1riRsMim5miShXyrUyafiKoTzR2qu9OKjQkRx7rNz2fszcOsuI03HW7QOrrsnTxjK7PU= 6GdQet3M3Nw9djJ+4OdcwzlSOp686/VVTV9PKTR5iZaNZFFjK88fuPlJyV6TvMvrDsOW3IDUfIm= jX3e140nQKzsuajtH6t1tpK8OK1Eadm9IqH/ZzcXlggIx+SZsNwrEnZHlgk46RTdoenI3P3/wBI= NHZ2zuRG1dD7L5F8ob5p+E41aT5ZUys3jcWxYy4Qlq5kw5LrKQUrsGBs0XdbfC63YNSwdYTl5r5= c3l385OhENpFdmZhF1prml0hJGgbU1fzX5rb80Cw35yItu3uWXThhNH7AgdKUraAXxd7Oa6dzsP= qOxXZnU15WAhpC5x8BsKNZWSXRcO3URCJOXMK0t8Q/G3Su6LhrbmpxZ26817I2vRsFryIvmo0Kj= PUXaOkBFKcobF/BWCGlYhZKrKrndVGWjE4yVikXjyKcqLx6qkcVjI5NP8zNgv8ApsdSdTbNpkrd= OcTNxcpeLdU2HPLkXsFyhYJ+Wu62e2CSTSRLL2VsjbYevyUqcnrJd3Hg+fHXkXLpdSpC95BTRSx= b+vVKn1y6M4GAg3mxCxyk1b3f4cimMPHSEU5nVpGNqcom2jmyvzisRkZPA7A7gJb+k8BbJXWcit= a8HeDmvuG2onMopKb427Ytp7Mnpt4i/tV8ctZRW43S43F8mk39RM23YcvBPii1atGCKUStGRzZn= HMkGZKm4/Qf5gPv/P8Az7B/L2yo+c7F32kVWJ+hVrIJOgO1mlPynokEqwj+M+ykMPYj26JGfV/9= EfAKsPjHYcl21JZZOTcitSUfkLiOXV6yKGgoliDKliGS/Hf7inV4WaKOT1JVGXuuHve0K5FO9iH= n3dhi73ZZivW+Ntgms8NcH0IwhpdULVHTJnjaXX8FjIuwfLlCVjXRDvot40ekTcJyxdH3lXT9f8= 29L1GEq7bW9T2Se41i2oBNOZRlI3K4MGRK4SPcPkiyDOBZOa/Fxlfh5N9MvGL2amFfmrkZECpYX= RWrRn+mZO7QQSRF3T+aDavGXUUbt/BG2XTsaouUy66pC+EX8awAqYj/ABe4Abv3LhFDyE9T5mGt= MFJFiZuvSsfNQsnGybQXsdKxjpF6wetTNHBl01mzpBJdJUgdyHIUfEHtkbgs2NVaoWQxcdV7n7+= iSnydyIHbtkDNGVboj2P23Y6z0NveM8e8nca53xtooak4m3vEjJWdoYo7UWujj11mzWhZYLMlKO= 7WmrmaORq/Q+EqR2fVeIACHi/X29//AN/x98+mR19NbnTUucnHivXRF2xabSq7RjXNt1NJQE3MR= amzUqaku2aGOZf8P2UqRpWHcAKiSYKOY0y53cc6KWRMvuAD+f8Aj9/78virZhuV4bNdw8M0ayIR= /wCrAEKf6Ze/VgfsEEH7Bz4acj49tuKb7acc3tOSjttNcno3q0oIZJoX9SyEgB4ZV9ZYJVPpNC6= SISjA5rjGMyM0uMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGM2axtpV5Xp5nBPU4= ycdQ0o2hpJZH1KMfKrsV0o56q37h56bR4ZFdRHuHmlTEncPFm84xjKvPFOqMdN8aZLjpys6Um7+= SPNyRVuMZuW+SWkaTtLXvKi9zMvLmR2c85VXOQCnx9JtMe4jVDfjmYgpqhxBfkDWrCpDtI9WaDp= w8YpThZwj4/8brG/j3U7rCkHaWA0U7dPYKNmZiWkrNLQsE9fETduoCvvZhxDQzt0kiu5jWDdwqi= kZQyZc5ewd+/b3/POk+Q9G2JsvTl919q26sdb3K6QbqtMb4+i3M2NVZTAejl5aOi2khFLOZpCKV= dkhjDItEmsodq+VOom2FurwkZkR2VDIyozKikBnYDsIPYhQWP12SAP5PX3mTSgis3KlexaiowT2= YIZ7s6yvDUhkkVJbMqQJLM8cCFpXSGOSVwpWNGYgGhh1f8AlSnyo5pX+XhJD5hQtZm/ZfR1UlCq= NnLGtO3BJiVbmIodI6UtYVZN43XJ7qsTNBN2EvYIuu4f4fp7D9/8/wAvvl2bUnw5nE2pmbSG177= s7bsmUSqvW5nzKmQDtUR8SpgaQqas2QiphERBSwrGEoj3MIj3zGfq7dHjVVB4+x26+I2vi1Z7p5= s6NsaoxjiUklLPRVzis5tHmP3L504mqmt4nT1QTgLmAcPVFlBGIaJGp7Z8X3sq3tvbWH5GZrMkC= SGWb0LD2VfUGPqFPsASElE9VXvrPrj43/U54O1E3CfE/F5t3/r4YKfHaO+ua1NfqBZWL4oZbL2r= Ed4Ns73ZaR6SIti4HkZUEjDETjDqkt26DXMGQO1MqvF8gvxuwUSQK4WSLTYjVRHjlIh1EgAU491= JlOIKE7JmVHuIiJRjl4AcDrfz33KbW9Sm3tYq0DFrTl8vzmvlfsKvGiB0Y5Erckqkm8lZd8AN2D= AzpuZVBJ+7A5kmKoDZ+6V+hl7x0X5zXbVkQZXecLv1ZoksZNEjmVmn01U4JZRRYSJJgIwEWAKqG= BMpEyHOYC9wLIL04ODdY4LceILXLYjOS2HPAlY9q2xAvdSbtztEoLNWi5ykVGDgEPBEQyIlTA7d= ud6qmV2+dCbc1uMf7Q8ensJ1Tj1ERs9H1Mje5mih/hu3Ew9z+QqN9glRlO8g/UofHUXn3V6Wz7c= w2PlbaRcY9o454qNd6dfW7DbyRyo8TpRbUeteJ/dJbdiv7xSQJMuRz8TeiNtHhrteL2xp7mg+Zv= 0BK0sFee6pIrXbhBGVIo6gp9kS8EBdsqBfEg4SMk7YuPA5aLIqk8Q2GESnKmUFBAVAAPGJQECib= sHiEoCJhAoj38ICYRAO3uP1z6FDsHb9f7fYM1ye0NbT1kTQUo2iiZvcoZZZFDEAEqJXf1767Pr1= 2fz/AB14c5x5C5Z5H2UO55jsYdttIa4qrfXV6rX2ZIFPccdmTW0qZtCL7EJs/K0KsyRlVYjGMYz= OyFYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYzb5GMZyzB5GSLdB2= wftlmb1o4TKs3ctXJDpOG6ySgCU6SqRzJnIYBAxTCA+wjm4YwQCCCOwfog/gj+jn6CVIZSVZSGV= gemUg9ggj7BH8EfY/g51zqnVVJ0rQa7rLXcOlA0uqtVmcFDomMokwbru3D06RDHETmL57lU/c5j= G7m9xEfcexsYziqqiqigKqqFVQOgqqOgAB9AAAAD+BnbYsT27E9q1NJYs2ZpLFixM7STTzzOZJZ= pZHJeSSR2Z3diWZiSSScYxjOWdOMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYx= jGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGMYxjGf/9k=3D" width=3D"236" height=3D"116" = alt=3D"logo_catalogo3b.jpg" style=3D"margin-top:0.85pt; margin-left:13.85pt= ; position:absolute" /> <sp= an style=3D"height:0pt; display:block; position:absolute; z-index:-2"><img = src=3D"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAkkAAACICAYAAADzq38MAA= AABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAOxAAADsQBlSsOGwAAIABJREFUeJzsvXmYHVd95/05t= d19631vtXpRt3ZZsmVbki0vssGAbbCDDQScTCDvJBmGeSEBhueZQPY8mSEmvAlDWDLBLGExDJuN= ARvLi7zJkrUvLfW+b/f23ZdazvvH7W5JVkuWZZsEqM/z6OmrW3WrTlWdqvM9v61EPB6XuLi4uLi= 4uLi4nIN2oQVCCIQQv8y2uLi4uLi4uLj80pBSIuWFbUXniSQhBKqqYhgGqqqiKMob2kAXFxcXFx= cXl182Ukosy6JUKmHb9rJi6RyRJIRA13W8Xi+qqv7SGuri4uLi4uLi8stGVVV0XSefz2Oa5nlCS= Xn5yq5AcnFxcXFxcflNQVGUC2qfJZEkhEDTNNe95uLi4uLi4vIbhaIoaJp2Xiz2OSJJVVU3WNvF= xcXFxcXlN4pFQ9HLUV6+kouLi8vZSCnJ5krkivYrrlsslEjnLV6vuiJSQjZXJF965X27uLi4vBa= Wy+p3fWsuLi4XxXFsntzbz3Onk9iOXEqZPTvAUUqJIyW9h4b4wf4ZbMoCx5GSxdXkyz8vbn/ht2= cLq8XtO47DiweGOTGZx5FnvpcvW+/sbZ/z/dIX57bFxcXF5VK4YJ0kFxcXFwAkFEs2iu0wn0gzM= FfEKloITaOrJYJPg4GReeZyDum5PAWfj2LRZHw8yWSyRDjiY1VTmNGROI7XR11YY2gqS0tdiEwq= x8B0HikErY0R6sIGM3NpBqfyKLpKd0uUxvoomk8lncnTP5oiU3KoqwnRUullaDRBxpRk8ha1NWH= aawPkswWOD89TkoLW+jA1YYPJqRTDc0U0XaWrNUZFUMe1m7u4uLwS6sc+9rFPwZn0fzezzcXF5W= yk49A7OIceCKJmk/zr42O01AY43TdDApXCXJLHjiWoi3g4dHoWNRTEb+b4xeE5KsIejpyYxDS86= MUsP3phgkwqQ++MyYoqnR/uHiIY8TE/l2TfQIa6kMpDz47g9XuYHIsznhdMj0yRxGDw1CQD8xYB= XfLoC6PU1IR47oV+TsZtwqrDzw/M0NMW5tEnTjFjqhjS4umjs4S9gu88MUxVhZ+5mSQ5xaCl0oc= bXeDi4nI2juOcVwbAdbe5uLhcOhIamqrYsb6eDW1hpuJ5DvUn2Ly2ke0b67m2K4Jj2Rw6NUumaD= MzXyBftNl3ep6WtlpaAg6PH0+xfX0tsaCXHVc00BAzUIRgdi7LxHgCXyzMdRvruX1nB1tWhBFAL= pend6rItg0NXLepie6YyrHJDJqucdXaeratq8UnLaaSOZ45OU8hbzKbKjE/m2IyWUKTNr2jKQLR= ICuqvP/eZ9HFxeVXBNfd5uLi8qrwelVUVaCpCuBgO6AqAkVR8BgLlmhFoaO1gk1tYZTVNfh8Bqq= QFIs2tmmRLzkk42l+sGeYVW0V+H0GHq2IY0sURUERAsu26BvPLsQiAQg0RSmn6qoKRVuiKAKPrq= JpCqoicByJ4TXY3FNF1KdxzfoGAh6FlbUhMpk8+45N0jdT5PduXYlPc01JLi4uF8e1JLm4uFw2m= qrR3RjkyZfGGBxP8PC+GRRNpb0+wMBYEqTkpYNDPHVynlO9E0w7Hu6+uoanXxpneCxJWmpc2VNF= YT5LquQQrQ4xORrn1Hiax58doD9RRAABv4+6gOT5kzP0D8+ypz9Fd10A5WydI8rrtYYFJyfyWMU= SDz3Vz9H+Of7lp30YoQAddT6KpvPvdbpcXFx+xXBjklxcXF4BiWk5VMYCRP0qutdDS6UPRzp4/V= 7Wd1URcko8fTxB98oKVjRE2dRVRUBaPHd8lkBllF0bqjk1kuLKTc30tEaxiiXqmyupUEye741T3= 1RBR12AjpZKVlbpPH90Gi0S5i1b6tEEVFeH2dBZydTEPIdHstx6fSc9DQEsW1JdFSLsVTFtSVtT= jM2dMYaH5jg2nmPL+kY2d1XRGlHZc2iKrOLlzu3NxHyuEd3FxeVclotJEvF4XEK52qTf70fX9X+= 3Brq4uLi4uLi4/HtgWRbZbBbHOWNtdt1tLi4uLi4uLi7L4IokFxcXFxcXF5dlcEWSi4uLi4uLi8= syuCLJxcXFxcXFxWUZXJHk4uLi4uLi4rIMrkhycXFxcXFxcVkGVyS5uLi4uLi4uCyDK5JcXFxcX= FxcXJbBFUkuLi4uLi4uLsvgiiQXFxcXFxcXl2W4pBcYWbbD0ESK6Xj2nHeauLi4uLi4uLj8KqCq= Cisbo1RFfQghXvkHXKJIAjBtyJVAcmkbdnFxcXFxcXH5j4JqgyMFvAod477g1sXFxcXFxeU3Hvc= Fty4uLi4uLi4ul4grklxcXFxcXFxclsEVSS4uLi4uLi4uy+CKJBcXFxcXFxeXZXBFkouLi4uLi4= vLMrgiycXFxcXFxcVlGVyR5OLi4uLi4uKyDJdcTNLFxcXFxcXlNxMpwXIkpiVBgK4KNEVwiYWrf= 2VxRZKLi4uLi4vLBbEdyVjc4vm+IiNzFpoq6KzT2dRqUB1WUZVfX6XkiiQXFxcXFxeXJaSUOM6Z= 97QOzlp8/rE0vRMmBbNcjTroVbm2y8t7twWoDquX/C60XzVckeTi4uLi4uKCbTvMzWXZv2+El14= aIzlfoLI2zEigjdNJDdOWdNfrZAoO4/M2TxzPs6pO45b1fozXQU1IKZf+Ln4GEEKcI8J+mYLMFU= kuLi4uLi6/4WQyBR78zkEe+MoLTE6msCwHkOixKDU3VKJHY9RFVK7u8DCVtChYJRJZybOni+xc7= UNXX1t8kuM4pFMpjh89zL69LzA40Ecuk0HTdWrq6lm7bgMbN2+hobEJTdN+aULpDRZJ8qzPv56m= OBcXFxeX/xhIKUFKpO2UI42FQCgChFL+63IeUkri8Ryfuf8JvvfdAxSLFhUVATo6qghHPCSlj4T= fg1AEN632smmFh0xBRyJ44kSRbMFBylfez8X2XywWef6Zp/nuv32VYnqWns42rtvUSSgcxiyVGB= 8fY89PvsODX/sy195wC+989/uIxmKoqvr6nYgL8DqLJAl2CawM0kxBcRrsAmgBhLcWtDBoflA0/= mOIpsUr+x+hLb/+OI5zntl0eSQXuiaLZthL246Li8tvBI6DUyphTafIHRqi0DuKk8iCR8NYUYt/= /QqMFTWoAR9CdSvfnE0+b/Ltb73Eww8dQQi4594ruO++q2hqjqJpKrNpm//1cJpjYyW+/myW2az= DWNzi6JiFogg66ozLsiJZlkUul6VYKPDwD77Hgeee5C233MjmbTcSiFaRmJslm54nGAqzvaIa6d= gMnzrMd7/5Nf7mk/+d9//Rf6OuvgGP14vX633DxgMRj8clgKIo+P1+dF1/9VuREmkXID+CnH0GO= fkQ5IbBzAMOCBWMMAQ7EfVvQVRsBU8tQr2Mfb0WpCy3xymBNQ9mHIxaMCr5dRBKUkpSqRSJRIJY= LEYoFEJRlnkgSIlTyGCXcijBShTl/KA7KSVzc3Mkk0nq6+vx+/3nLX81ndKyLE6fPk0qlWLjxo0= YhnHeOo5jYyanMXNpPNUtaLrnnH1IKUkmkxw4cICenh5qamqWlkvHKUsrIZZ82cseu4uLy68PUu= IUs8iJk1gTE4x/9hDzD+3HyRbPPAd0FU9XA41/9T6MllqMFTUoYR+Kov46PPZfE1JKenun+fB/+= 78MDMzx3vdeyR99cAehkG9J9Fi25CcH83xjT5q5rI2ulE+bJQWNFRofflOE7kb9VWW4SSnZ/+IL= /N9vfhVNEajS5Lfe/V7aV2/CQXDi4F7sfIqIX0PaRXzhSmLNq/H4QxQy83z3K5/j8MlB/MEQazd= uYddtbyMajb3m82FZFtlsFsdxlr5TP/axj30KyoOLruuv3nwlJbKUQE79FNl7P4z9AHITYBVAWi= BtcCwws5AdhvjzyPQJMGLgrUMoKm94T5USZAnMaUgfgrlHYOpbkHgEfJ3gaebXodiDlJKJiQm++= tWvous6ra2t5wiFRSuMdGwyh37C2GMPkIp0EI1VLiuSTp06xV//9V+zZs0aampqlpbZlkVhegah= a9j5AmY6jeLxIC4iShzHob+/ny9+8YvceOONeL3ec5Zls1kUJNMvPsTxXzyIUtdDOFpxXrtyuRy= f/exnqa6upq2tbWl5KZ1h7qXDONIhfbqfUiaLtyJW7lm/Btf2Nw3LskjMJxmfnGEukcCxbXRNW+= rPrhXRBengpGexnvkG5k//AXQV3213kz85SmlkBpxyPR+tsYLaj96Fd3Ur8//2JNbUPFpFCDXkv= aBVybIsLMv6tbdYm6bNQz8+ys9/doLOrhr+5KM3UlMTOueYFUXQXKES8CjkSpBMFcmls7TGBPft= jLK22UDXlFc1itu2zZc+91m6mit58x13ce31N9O4chUoGkN9J5kdH6KjeSUVNW0Ew7XkZiaIz03= hi1bjD0ZYtXYTq1d3Ux0NsufJ3XR2r6Oisuo1XyvHcTBN85yg8dfmbpMSWYojh7+BHPo6shDn7D= ikZRtsZmDmWWRuFNH+/0D9W0D1vKZmXLh9DlgpyPfB/G5IH4TCKFhJkCYYVYD9xuz73wFFUYhGo= 2iaRj6fP+dCSynJZDJMTEyworUFfDEOjiRono2zov38bQkhqKurI5vNUigUztmOmUzR+9efxltf= h1MogqbS8aH/jB4OX7CTqqpKNBo9I9TOals6neaJJ57gll03E+neRlipIBytWNrf2dYhv9+P3+8= /JwsCKSnMztL3zW/jbWigODaBv6IG4/3vxltVgerxvOqb5+WZFW/Ub1zOpRwfkeCJFw7SO5EjkU= rjOJJo0MOKKj8b13aSLJTY0NGK3+dzz/NvKlIis/NYP/9HzJd+jMwlUTuvxbe2lZbP/mdGPvIl0= o8dQquN0PCX7yV6+9WYk/PYhRK5A/3Ysykid12DZ2UdQjvfMCCEIJPJIKUkGo0uGA8kmLnypEv1= gvjVt1SXSjb79o1SLNrs2NFOZVVg2XvKZyjcusHPFa0Gn/ncUX72i2Ncuaud1bU1ePVXJ5CA8vW= zTK7ccRPta65ALJzLbDbDwOleoppG4fn95CU42SyF5CxzK+sJ1rfjCwTxBiO0dq2noraRg4cO4z= j2Ugza681rEknSyiInHkEOfgVZSmHaDt9+yiFvSm7fqlATUc87eRJAr4DQGpyJnyK89YiKrRe1Q= lxe20zsU88jpr6E8PahkC0LowuHu1zadiU4jqRoSUwbDBUMTaCqr+/FsZ1yZoGiKIhX0WBFUZZm= 21JK8vn80rIjR45w6NAh7rnnHrxtm7nhD7swAmFs28Y0TRRFQdM0LMuiUCgszaSklEszK1VVKSS= T6LXVBDeuwymWiD/zPANffoDwmh6qr9+OdpaV6GwWb75CocDU1BTJZJJIJMLPf/5zDh48QENdHS= HdwR+OMTg0SGAuzsDAACtXrqSiooLjx49TKBTIZDKUSiXGx8cZGxsjGo1SSmewdu2kdlUXidk55= o+fYO/H/gcNt91KxzvfjnqJbmTpONgLx5pMpdB0nUAggOcCQmtR8BWLRTLpNLZlUxGLoaoKiq67= g/irwHEcpmbm+LefPMOLx8c4cvQENh4kAo9SorOjhcdePMIVnQ2sX9n8S2uXBBwpsZzyX9OBnA1= Z0yJpCRImTBUk8ZLNqrDG9koNn+Ze9zcS6diYz34D88XvIwuZhce6QFFVvF3NNN//+4z/5TeIvO= lKom/bihb0YU0my7+1bArDM4gf7SX2nuvRaqPn3aeqqhKJRJibm2NwcJC6ujp8Ph+KosHcwXL4S= GgFKJ5faUu1bTlkMyZCCGprQ2jLCEYoH6JHE9THVBpDNmZ8jly8Gmz78g5fgFAUVN1ACOWciXA8= Hoegj1U7dqD7fAggm5ii/8CL2LaFYGEsEQJFUVHVhUy3N+gyXL5IkjZk+5FDD0ApBVJiO/D9Fxz= iWdixVlATWeZ3QoeqaxHdfwJze5CDX0GEesCIvL6dzXIwnzhB4ZuDqK0SY6OK3m2jROyyatXCEN= 4ERt0ln1xHQjzt8NgRk6d6beazkrBPcH2Pyls2GQS9r0/7S7bJL0afpWAVefOK6/BchqXNcRwOH= jzIwMAAqqoyPT3NiRMniMfjhENBopkRImR4bEIlHK0gkUhgmibvfve72b1795JISqfTzM7O8u1v= fxtVVcnn89TV1PCzmTHe6tmMEQwz2rOSlf0jzH/xK1Ruu/qi8UpSSo4ePcpTTz3FnXfeySc/+Ul= uv/0OfF4f0UiIiT3fw87M8rnH+7nupl2sW7eOT37yk6xZs4bq6mo2bNjAwMAAMzMz3H///bz//e= /nwIEDZDIZ9u7dy3sr3sup3lPs2L4NUVmNdokBfYsWKbtUIjszh2NZiEKeku2QNXT8FTEqKirOc= 1/ats3c7Byl+SS67aCqCjnLRlEVgnW1Szfzr/KD9JdFOpPl+489z6PPHaN/PA1aDLkwRSgKL5Mz= s0Qjfo4d72dqeoq2FW3AL8FqJyW9KYe/PWUynC0xZ0JGquRKFlbexFe0CWSLOMCWtRVsiKh4tVc= ztbm0NsBlzPFe4dxIKcnHc2RnckhnYSYuJb7qIIFKL9mpLPHTcTxRH94KL+H6IMK2cAb6YS4Bug= fa2ihKncxMDhSBv9KPv8KHoijlCUSywPxwmsquGNpZxXRs06KUMfHGvAtNvTTXlpQSe2A/1hP/g= ixkzj9kReBrb2DF5z6IMDQUY5kJkuNQ6Jsg8/QxIm+9EjznT2gURaGqqgpd1zl9+jRVVVXU1tSg= Vm5EzO2D4QNQfzN4Kn9l72+hgKaVBUouVzqngOSFyGZKSEei6wrKZWcMLmQdvsz67vV48fr8TEx= PcWp8kI41GzF0nZmJQWYyBXyB0HkGldeQWHdJXJ5IkrJsRRr/ETI7tDCbLjdWSoHjyPKNLCUSsX= TjldewIHUMOfEIzDwNieeR07uh6fZXZTG5JGwgI7CO6pgnPIgqHXFDJdrt2/HU3Yzqb0JRPJe0X= ylhLu3wpceLnJp0uGG1RkuVwvCszePHLNprVLa0vz7Jgo50OBbvJ1PKsqtlG57LyHIsFot873vf= Y+PGjXR3d/PFL36R97znPYyOjrJr1y0cfvAzVNoTpOaDJJJp/viP/5gHHniAv//7v2doaIgf//j= HHD58mG9961s8+uijhMNhfvd3f5cnn3ySw0eP4g+FeHrPHtauXcvO295M0LTou/8fcUzrgm1aFE= /19fVs2rSJ/v5+hoaGUBSB1+vF7/cxPjpIe22IaDTCHXfcQSgUIp/P8+STT/L7v//7rFq1irq6O= g4fPsyLL75IT08PyWSScDjMddddx/33388nPvEJVrSvZN406f0/XyfU3kakve2iws2aT5Dr60Na= Fo4E1dDxGQbC48M0TbKDw4yn09Q2NqItWKVKxSJjA4N40lmCoQCaBrKQw8kksc0S6bFhVJ8Pb+s= KtPByM4ZfT8ri0TkrgF4sPXzPfqguBkdqmlaOWRuZ4KVTU0zN5VjRUI0iBNliiWjAh6I4GDoMDI= 0R6Wxj/4GjtDS3oChKeTsLM1GxsL2zLe+WZSMX5NZiH1QUBfUSs5ykaSP7EvgfHmNdf4KmuTQN8= RxV8TwVqQKhfAlfyeJQexXf/fM3YTo+bMtiPpkkGomgacs/F8pVjcsZn7Ztk0qliMVi54kFadpY= P+jDmswiYgba9kaUqA/r8WHs8SxCgLapBnswhXpDE0rIwHpiDHwq+vXNFxUeAsCxOfG1AxSFzuq= 7ukkPzjJxKkX7VdWc+OFpWna24qQLjDwVp/sdHWiqwE5Oo3zwQ3DTHYg/+RCKCvv/93NIj59tH7= 3mnH06RYvMVJ78TAYzV0J4VLBBUTSE4pBLmegelaZtzfij3ovqDSkl0i7hTBxCdO9k8dEoAdG8H= ikWnuaqghr0nfVDUEI+/FvakeaZEIuS5ZDJlAh5zhdSi8cQjUbRdZ3e3l4SiQStra34K7agemLQ= 93+g7iaIrgXVKId4OC8L4RAKKApL8lY65X9CPdNJpTzz/ZkGnFnHsc9dtrTd15YCbxgaHZ1V7Nn= Tz/59I9z59nX4/ecn1ZSbKEmnCxw5PI4Qgra2Sry+y0++EkIgnXOPSdU0rt/1Zr70/32aiUce4c= SxY5RKJqMjI7z57XcTfllw9pKsKNuXLrstF+PyR/XiLPbUbtJZi8l5yVwaqsLlF+ABZXGkBsFbB= 4HWcimA9AkozUN+HAYfADMJVg459iCi4c2vf2ySpuKEAlixMMUtayhesRqrpgJZUJGDM2h6lpr6= VqKR882tL8eyYc9Ji6FZh4/cZrCqQUNVwJEad26R+D1nOrssFpHFQjko3edDLAbDOwWw8ws+7QA= oOlIKSlbZfacIUBWBebaal+AUC8hCAaGqCJ8fFOUV22sYBu985zs5cuQI3/nOd0ilUkhZdt8lk0= mOHj7Iqitq0DSNdes2Eo1GCQaDjIyMUCqV0HWdiooKNE3j6NGjtLa2smfPHgDWr19PY2MjH/nIR= 1izZg2xWAwNgZktcPozn6P7v394WZfbokm1v7+fI0eOsH379jPHIR2mJqcYHThNZ9Xqc7ILFgcR= x3FwHAfbtimVSnR2dnLvvfeiKAr5fJ7+/n4Mw+Dx3bvp6e5GIrDyJWzTfEV/tZSSYHcPwuMpP2g= dG6dQxCkWUBLzqFmb/NQMc7ZNrLERx7RIDA0TyWTQDRXdY6BGwiheH8IwyvVZkDj5/Dmzpd8ECo= Uijz+zD8e2iCezXLN5DUPDo0zHU6xorscyS1TEYpzqG0TXNbZu3kgw6OfU0AQDgyMULcHMfApVU= bFtB6eYwi5lKCkx8qbB6MgYL3rTXL/9GsanZ+nrH6SqqopT/SMEfD5u2LaZydkEjXXVIOCpPS8i= BIRCAY6fHqIyFubqzRtobW64pEQVOZSi7cA4f6dlKfzsMDgSmSxBsTwzLF9pCKdNClmLvA1z8Th= /8alP8ck/+zOqqqqW+v7ZZTByuRwvPPc86zasZ252jv/9uc/xV3/z1/h8viWBKQBMB/MfX6IwMo= /i19Fawnj/Yjvm5w9hzeXQV0Sxwzqlzx/CCOuI1ZWU/mEf6p0d6Nc1X3zsEALda6B5NSyhY4R16= re1UkgUKc7nme+bI9ZTTf3qSvSgF0URCEVFiURBVVD8AYTXg6ZraIaKpSkYvjNWGYFA9el4YypC= 1fBWn4kjE0LBLpkoXh1FFUjLxrZsVE29uGEm14sa2I16+58i/K0g1KVz6wgVsXCO4dyYRrUmTOT= eHaiqVs6ULdp86aU5fAN5/kvMj6qcb5Vc/H8gEGD16tX09/dz7NgxmpubqaxcgdHyW4iRB8GogG= Ar9vSzOHMvlj0m5RagRHtQqq5G6H6kdHDmj+LMvYTadBvKghVK2iXs8Z8isyOLVx3hb0CpvQ5hR= JCze7Gn94DiW1gsUGquRYmtQSiXP4wbhsZNN3fx8EPH2LNngH0vjrDzhk48nnOLNZZDCix++IPD= HDkyQSTqY+vVrXi9l79vgaCUz5BPzS3tw3EkKpL7fu8DHNq3l9OnThKNxrj7Xe+irqGJQiZBEbE= 0wSlmkthW6Q3N/bqsI5SAkxthbm6aB35u8509EsuGaADms5KgXyl3mvb7UJrvWvDbqsjsAPL4/w= Q9guj5KHLqF3Dy7yDbB4VpCLyOcQaqApvWUmyuJF8XpaAI8oUC87NxxqdmON47QCZX5Hff+z42b= Yhe/HilJF+SPH7MYm2zSnuthqKUjzVTKD/MkjlJQJcEs9OU9uzGOnYYdB3P9hvwbLkKxDxy7mFk= 4sly56t8E1S+jVQpwPOnLfb223g0QVVIUBGyF6xyEntuhvzzL2Ae2o/w+vDuug1j3QbQLqzgF0s= BfOELX+Duu++mvb2dxx9/fGGZw9jYGFNjw4j1EdKZc83VqqouuZFM08S2bcLhMBs2bODtb387iq= IwNjZGOp3mqquu4mc/+xlXXnklddEYiqIQ2bgOZZmBx3EcisXikunasixKpRKRSAQpJYViicHBQ= XK5PJNT05iWSjabRVVV/H4/K1euZGpqir6+PkqlEt3d3fT29jI1NYVlWRw5cgRd1/nEJz7BRz/2= Ma7csIH6eJrmN91ItH3lBWPeFgcjNRAsi1BVRRECpIrQDdRgEL2yCmlZeDNpCtMzxPv6UYFIwIe= 3rRXF5yvPFJcRYorXBywUuLvA9bqY4F0aLH+FzPmOlAwMjSIck6GxKQ4fPcmW9e2MjU2x+5m9XL= Gmg7HJOKvaGjBtha9/98f8zr23MxtPkcnl0VUPkaAHv9/LzMQ4ycQcploNmkSikM5kSGR8TE5Ps= f/QKSYmp6lLpnn0iefw+Txk0nFeOj7I1o09FEyb2elJdl2/jaGxCR559Cl2bl1HblX7OYH2F0WB= 0hcPolzfiOe+1ZiPDYGmQtrCGc9C0gRb4i1aODmTgiUJ2A65bG5J7Nu2zfT0NKMjIziOw8r2dib= Gx/nSF/6Z377vPlavWcPdv3U3Qgh6e3uRjiSRSNDY2EB9rJxZqt3SgnFNE9ZnDyITRVBAvbcT41= 1rEAqYP+zDOZ3AiXogXUJbW3lJXqBy3xKYmRIjTw7RctNKqtorKM7nCVX7OPwv+xjrqqb77d0L/= XuxT8LCdHhx3F747qydCjCCHnSvSna2iO7VsIsmQlOxcha27SBMsEom0naoWFVFsNrPhUc9Ccn9= yJmfQzEOPX+DCPVg2ZLh4eGFuKFyXGaxWMQwDBRFwePxkE6n8fv9RGMx4gWbz++f5bP757iiPsj= vrY8RNC4smIUoW7vb29sZGxtjeHiIXGqaRt80RuU1qN4qAJyZZ5DZIdTGtwIKMj+Kc/qfEaGVCK= 0VWUrinP4C0ioiNT+y6a2gepClBE7/11Da3l0OCpcWMnkcIqtADyHnXoDsAKLxrQihgtAQRvgi5= +nSUBRBR0c123es5Ic/OMxf/PlPsSyHrVe3Eg77UFWBbUuSyTy7Hz/FP/3j09i25I471tLVVfOa= y6wMvvAjMqeeQEqYmksxN5/Bsh0cRxLfCvU9AAAgAElEQVQMeNCLJqnkAHuGX1qaYChCoWtFDR5= Do1gyySfn3tD8+MuUgRIrM8JLp/J880mHSFBw17WCuRR84wkIBjSIbkA034U0k8ixH4J/BUrDW6= DjD2DipwgtAKpRvsXMDORHXleRJDQN/YpN6PluRuMJDo+OMnC4j/Hjx0jOzGLZ5QDbS31QmjZkC= pKYX6CpZffB3j6LR4/aOIBjSzZXZrj19LdQBk7gve5GnFSS7ANfhNI8+srTkPgJovpOsIvI4c9g= mg57E7/FwwdstnaUg9y//6LF+lYbo6nsuik89gja3hfxXL0d8/RJMp//DJFP/i1aQ9P5V2Uhg61= YLDI3N8fs7Cy9vb0Eg0FCodBCfNEcJ04cR0rJzHyGbFaQSqWYnZ0ln88viZFf/OIXzM7O4vf7Wb= 16NePj4/T29lIoFOg92YsjHd71rnfxr//6r3z7m9/kjjXrcQp56m6+AbGMe0FKid/v57777sPn8= zE6OkowGOTjH/84Pp+PiooKIuEQtb/zYWorQrw7Xp4BWpbFO9/5TgzDIJ1Ok0gk+MAHPkA0GuWa= a65hamoKr9dLrS+AalnUhSN84J57mHxqD2o6T/31Oy5qQSoWi/T19ZHL5QAIh8O0tLSgaRqjo6P= Mzc2V+4gQRMJhampqmDp1ikKxiJrzUiUETU1NSNtmfHwcr9eLrusMDQ1h2zZCUaiqrKShoQEhJW= Y2hxrwMzQ0hKqqhMPhpVinRSFk2zaZTIZAIIBlWeTzeRzHIRaLnROUf3aw41K/F2dcSovrXWxZI= pEgEoks7f9sUbbcvXGpYs22HcxCjvXdbfQPT3HsxAB11VE2r+3kwOETeL1eMtkcJUsyPTlJJpMt= B7vbeaoCGp2rV6MqCsJKUQiFGJ0tx8xIIVCEwDItzFKJ5oYaTvcPcfjoNLlcnk09bWRzOQIehce= f2ktTQx1SFjEtk7raWkzLJJGcJ53NXLpICnuw40VKnz0AlR7UNRX4PrgFtSGEuX+K4lcOYx+cxW= PZyGSBgu0sCIZzZ+Lj4+NMTk7S39fP/n37aG9vJ5fPMzIyQjQW4xtf+xqdXV38w9/fT8/qHjweD= 489+nN+77d/l4iUOKeSWEUgoiMCOtKRWD/sp9SfxvijTaidMewD0yhRLwR1lMbgJR2e5Mw1N0Ll= ysrSkSgejdXvWkts3wSDTwxx6GtHuPYjV+HLTEM2X3ZxXcogKSBYH0YUJhGZDE44iqJrWLqC0CT= SUqDkoKgmmvEKJWGkjcycKpeXmd+LPPGnsOpPEb5udF0nnU4jhFiyEC6mc0ejUSzLwuPxEM9Z/N= O+Gf75YJy5gs1I2iRVci4qkhbxeAxaWpoJeBxycwOcTgtqmldQrfhYuDMRVhJK4+XnjjmN8NYiF= KNsRZp6EgIrUOtvQZ76AjK2HiXcgRRqeaJVHEWoBtKRCH8d6KEz58OMI0pjCD2GqNmJMGKvSyxU= OOzl3e/ZzOjIPC+8MMSffeonXLttJWvX1RMOeYnHcxw6OMbevcPMz+e56aYu3nnPJsLh5RN0LhU= pJY5ZwipkyyEPhQzZdJJC0cSRUMxpgERVVHRdJZsv4jhla1OxxofqGNimjbStNzQu6bJtZXYxw9= Fhh3wJ3roa3r1DIV2ERw9YIDQIrgTVjxz9IXLwq2XLUs0O8DeCt+asLQmQDtJKv65q0JLw4lyGB= wemGM3kSWShFF6JWFuFZ2IIfegkvIqaUB4NYkHBVFJSNCVeA9Y0q9RGFQqm5LvPmSTHZrBOHSf8= tjvwXncT0ixhDfZTfOL7aJEUSu1vIerfV77RS2MUxr7F4anbWdNk8LYrdAQwmXTILfrMs1msIwM= YsQrM3uM401MYV1yJ8Hgv6D4KhULce++9qKrKjTfeSCaToba2lnXr1qGqKtdccw26rnH9pm6qw1= 7+8EYFr8+H1+tl165dFAqFpay49evX8+lPf5pAIICmadi2TTQaZUNtHeg6TbV1vO/ee0kcO8HUN= x7Er+vn+ZgXUVWVtrY22trKwbbr1q1bdiB37M1I6VDvlDPqxsbGuPrqq8nn85w8eZL169cTjUaX= 3G9CCFQhmJiJM/TFr3Ki6qcEp2fwr2xj9R+9H191FcpFYk/S6TTf/Na3UFUFQy8LsWuuuYYdO3b= w+O7HOX36NOFwWUSsWNHK5is2860ffB9N1TAMg7n4HHfddRfr163nZz/7Gc3NzVRXV/OVBx6grq= 62LBZKJe655x7aGhpJDgwRWNnK0NAQq7pXMTA4ULakFQpUVlZiWRbT09MkEgnWrFlDPp9ncHCQV= CpFS0vLUgHN+fl5wuEwpVIJRVHI5XLoC5l4iUSCQDAAsnx8Xo8H07KIRqNkMhkMw0DTNHK5HKZp= oqrqUqbhYmxMTU0N6XQa0zSJRiJkFgqs1dbWvqKLSghBc30lMzM2sUiE992zlYNHj5LN5Lhiw1p= aGusROAyPTqJQ4Obrt6LrGnWVUSqqahgdm0Y5+CxVjS34gzGqG6upaSoxODBIPJmjqqYCn1rAMA= wCfmhrqsWxKgiHfPR0tpErWfR0rmTfoeO0NFYzn87Te7qftWtWs/OaTQjpkM3mLt0L6lVRIx7sX= gfG87BWQVtTjdocQV1djXFdM+azY/j+9nn0TImseX4w6WIs3sjwCBPjY4xPTHDDjTdSW1PLtm3b= UFSVTDqN4ziUSiWu37mTqqoq/vnzn2d2dpawlMgT81iDaTwf2YKoLLtdtPYo2tWNKDEvSlcU56l= x7NgMyoow4lIHsbKhE82v03h1E56QwdRLE6h+Dc1r0HZzB5HmEIe+eQIrPo393z8Mb70D4QikJ4= hUlIVzuXA/c75w90W9eMJFnBMHAAVh2eCYyEIRalsgE0dZuwkloF183JcO0kouuLAtmH8WefrTz= Nd9gh/+8Bds2bKFVCpFb28vV111Fc888wyrV69mzZo1TE5OUtfQyI+PJfny4ThT+bLFvmBLCvYl= dgYpUZ0CVRUx5g0/MwMjzMWTxCqqMRbjjry1EFldPk4tipMeBMdClpLIvi8jancikkdwzBTO6I8= QnR8APYTa8yFwCuUYWaeEM/0kMtSJ8CyMl946CHWDFgRl+bihy0FVFVatquV/fPJN3P/px3nqqT= 5+8vAxHnu0F01TsCybUsnG49G4594r+L33X01LS+w1WrflWRO2crVuRVFJ50pomoJjO2iqSjjkI= 5cvksoWCAe85AompmWiqYti+qyYrjeIyxZJQvUQ8pV98UPTMJOC4VlJIguxiANWurxicCV4qiHY= idQC5TgkO/eyjQlQXpsqfTm2IzmayLB3en5hEFbAHwJ/CKeiFn3tFhoMm2hN7SsfqxB4DXjzBo1= /e8Zk34DJVe0a9VGF6pBk/6DNTNphV7OKfkSCZZXjhhQFLBO5aCWQpTO1NewSUH6fkO2AspDBaJ= 0V8yeFQEqwh/rx3nYnnv/0B6Dp5XiAZTqoEIJwOEw4HD6zjWUyzRb995ZlsUFRlrLYmpqamJmZw= efzcfDgQbZt27YUD7S4HU1VmRsZ4+RffZp8SxNOsYRWKrHq4/8vwRWtaMHl62ycPbu7EKVSiZO9= vSSTSdLp9JK1pbq6eqm9+/bto1gsMjMzs1QNvK2pCf+RYxTic6ROnkANBDEaG/FWVmKEQhe9mct= uxRLvuvd9NDY2cuTIER5//HE2btyIWTLZtm0727dtQ1XVpSxBx5Hc8Y476OjoYM+ePTzyk0dY2b= aSbC5HsVikVCphGAYfeP8HAPjxQz/m6LGjNFfVIBdMydPT0xgeD7lslqmpKWprahkZGSGdTrNu3= Tr6+vqWrpNpmszOztLT08Pu3bsJh8MEAgEOHz6Mbds0NDTg8/kolUpLLs2jR48C0N7ezv79++np= 6WFgYABd1ykWiwDU1tZy8uRJGhoaqKiooL+/n1KpBMDExARDQ0NcccUVJJNJMpkM8XicrVu3UlF= RcdHr6PUYvOnm68hls3g8Xnw+H7U1lTiOxDB02tpasRfcreWyEhqBQIDu9iZWtrUwOp1mfDoJTj= 9N3ZsIV9ZgmyVU6cDJo0TDXjpbIlTEonR11bCup4t8Po9lWhgejUAgiJSSzZs2Lrm7VE0hGAiyc= kUzmWyWaDh8wXTnl6MYGnplkBJT5YL9xxPYJ+dQG0IouoJojWC9OImesfBlTOZLDtI4VyjNJxL8= 65f/hZ41q7nzHXfx5S9+YeGeKJfdOPt+NjwG4XAYn9+PpukLgemg3tyMIhSc43PI65sRikBsrkV= /RwcYKkpnDDtThOfGMe7sRPi0V7Q0SCnJJwsomopiOkwdnoa8SSYhadgcYeipCWrW1lKKF1lxYz= u+2kpEVwfO9AyirRNu2g6GTn46je73ohteCokiXr9+zrvShACKJay6BlTbQsynsL0VqDpQtBGhI= DLgfeX3qy2OFYteP6MO0fguiiUPVVVVHD16lHQ6zbXXXsupU6eYnJyksrKSVCrF888/T3tHBze1= hXi4P8VD/WnyDmgKaJc64EsJqoeSpZBIJjAMD7HFd4gtPMOl0BFKuY6SFAaUkkgrizP2EDK8BhF= YgSME1OzEmX4SkT6N0II4Ez9BbbwDFBVhF2FBLC0dumIg1LIrUmYHkJ4ahLeq7H57jei6Snt7FX= /7d7ezd+8QP//pSU6fniGftwgEdLpW1fKWt6xmzdp6gkHPa8hqO4OUDg3rdtLc1okAOqRkq11+c= wJSMp8tW5iUBat2OBBAWwgH0bRyaZxcNsPhuR8tbpE3IjjpMkWSQA82sKXLoDZa4rmTcN9nbHJF= KJoCHBMSByA7iFK9DaJfh4WL60zthvwkYiHlupx24EX4Gl/HwyqfLlueW7RQ01TaQj521FdwVXW= EloAHn3b+KzmWQ1MFW1ZqDEw7/PNjJruP2zTGFCbnHQ4OO1zfo3H1FQ0wto7cd76GMz2JPTeD1X= eK4H/9EKLqMHLiX8CcQVoZSPwMX9un2Rg0+NoeC0eWcCQ8cdzhmlULgXuhMMaWNuSPvo+TiJN/6= PuYRw8S+vifoTc0XVAoXez/UH4wHj9+nEwmsxTQnUwmqaysJJfLsWLFCqampnjuueeYnp4mnU4z= MzNDT08PsUiEutMDlMwiuf0HUQydUFcnaiiIXvHaZhdSSrLZLKFQiL6+PkZHR8sxAKOj6IaBz+f= Dtm1yuRyJRGKpOGV6dhb7pQPYQ2Oo1THsTIr83n0kjp2g7uorX3GgcGyH2bm5cjzIqVN4fWWXme= 04jAwPcyAQQNd1Ojs7y7U9VAWfz0coFKKnp4dHH32UQqFwJt0fyGazvPDCC5iWxfDwCLfecgvq4= qAsoK6ujlVdXRw6dIh4PE5DfQOKopBOp5eE7tK5FIJQKEQ4HC7XY8pkCIVCS4H1juMsWYnGx8eX= XAuRSITKykqampoW3FsZqquqMQyDQqFAfX09x44fxzRNgsHgkhVJ0zQKxSKRaIRwJMzY6NhSnSz= bfuXiq4qi4PN68Xo8C80XKMqZzwDo+jlV1wFaGmrZtqaJqdl5Dh3tZzheJPn841TUNZNMFTALGR= ob6wmWpli/9lai0RiGrmPoOsFgYGk7i65Cn893zvaFEBiGUc4gY/l7Y1k0BTt2JgZQDmfIfOhRI= j+4G7WjAnssTeE7J1DjBQKpHKmcCQYUCnkOHzxELBYllU4zNTXJm257M6dOnSKXyyOEgmU7jI6O= UVVdtdg1zsm2PbuJSthA395C8X+9iH1rEmk7WN8+CQdnMf7TOkRDEPwaVn8ST0cU9Fd2hQkEvqo= AG//wqqUMQAChCRRNIdpWw/DpEkpDhEBEo4hK/D2foDQdp+qdv0O4IUYyJVH9fq768LUIQPWUh5= Xys3cx61CBjtVMT4/gCIlarWBJgS9ioAUMKjuiZffqK1r3VZRAK1KoSL0S0f2XiJqb8SdzaJrG1= VdfTS6XY3BwkE2bNtHV1bX0fLv99tsp5PM0VFTyP29sRBHj/KA/TZVXIWxcYqajUMjlC4yPL2Z4= tREMBpeKTYroGph5Amfk20tnWGm5G/QICAet50MovrJlSDolHH8DWDnwN5WF0tiDZ66NtxYRXFm= eWEdXQ34IZ/TbLAV21+5CeLbD6yCSoByfFAp52Lmzk+uua6dUtDEtG10vu7s0TbnkMg2XSqSujc= q29ec9om3H4YFvfY9MvoCmKlyzupvrV67FqxtndJCETCqB7vnFQmo9b0gA92WJJAGowVZ6Vlbyq= Xfl+foTDqks3HKFYHgGiqYkYJ5CHv5TaHsvItyDtMeRYz9Cjn4PQl3I6ceQySPlekuBZvDWL7sv= KSWlUonSQrFDj8ezYGq7hDYKgV9XqfZ5uLI6ws76CtrDPnzqmfiPRUuJaZqv+FqWsE/wrm0eVjf= Z7D5mcnjEJuYX/NdbDK7q0NA1D86970OprqX07FMQ8BP66J+ir92IcK5A6jHk9HdB0aHzMxgVt7= AlqmE6gt3HbLwG9DQJdFWwuqIdWzYT3HgFMlJFaffPQQj8996HWlP3mnzRjuMwNDTE1q1befLJJ= 0kmkwSDQXK5HMPDw1RVVZFMJjFNk5deeomurq6l83X4pZfwnRiiODyG6vGC45A+fITUkeOE2lde= wkPuwhiGwcYNG0iNjlMcnKTxmcNox4aofsfbqL1xB6qvPKjOz8/z0EMPsW7dOnp6esj1DXB0eBT= FgUB1LcRi5PqHGfzmg4S7OvBXnv96k7PJ5/M8+J3vkM1lCQaDfPC/fHBBNFj09vUxMzuLx+Ohoq= ICfyBwzm+FoizrD8/nchw+cgTHtskuuLgW72BD12ldsYJoNMqqVatobW1lZGSE9vZ2fD4fzz77L= DU1Naiqis/no76uDgE8/fTTrF+/Hk3T6O/vZ8WKFXi9XkKhEAcOHMDj8dDR0cHwyMiSQPJ6vdTV= 1REMBlnVtYqRkRGCwSD19fV4vV46OjoIh0IcOXJkSUzlcjnCoRChUAN+n5/KykqGhoYIBALnFCd= 9Jc4+5xeyLp6N1+vhlu2bSSZTBP0+BgaGic/kGR+boKq6htamNqLOLDuvuYpVXauWRNClbPvs71= /1naMADb7y33KNV+R0HmnaOKkiub/ag/mjflShEE4XSZrg8Xq56qqreO7ZZ1FUhZaWVrbt2MH3v= vtd1qxdy5vfchsVFTHufMc7eP65Z7nxppu4adcuDI+H7Tu24w8E0DWNzVu2EKuuRL8LZL0f5Zp6= 9Hs7cQpFtNvaUAeTgMBRQcQ8GL+zGmMyi7KhGqkAF6lZVj4hoBoa8bjN8BiYpkRVBI7toHuhrkb= l6b0G1U0OQ6cFW3c4nHg+wETeoDuj0zQn6T0iqW2FhlqVbEahvgnMrE0271AoCQoFQecqQUVIQQ= 8YZGZy2I5ENTSErpKZzVPZVXlpL54VCoQ2Ir1N0PXniOpbQNGIRnXe8Y53LA3iW7ZsOT+ubikmD= 5oiHv7mhgZMOc6KmJfAJQjKxUlcIpEgHA4Ti8Ve9q5Tgdr4JmTDrS9rc1n6qp1/wNIoLgQoHpSG= XUsmR7X7jznX/nhm0qXU3gi1N5x/8S5hHHAciWlamKaDqggMj3bB8hdl66ZAUcQ5llZHguWArgo= cZyGLXZQ9NrL8EV0V2Av1EgE0RVz4xbcLouaMrjkjvsrXSCGRyaIgyBdLpHL5soQ/u07doqgXsv= zvDeKys9vw1OCp2cKO1VNcu8pemJlxlspzIHkYefDj5aA0Wa7zIAAS+5Hz+8sbUg2ofTNovvP3I= yXpTIaHH3mEYydP4vP5uPXmm1nT3b1QC6X8AHAcZymjwbZtnIUZzLqKIF2hNnqiASIe/UzTpMSR= ErkQ0zI0MsLDjzzCLTfdxKqurgsetxACvwHXdKpc3VnuQGcucHkdNRzBd+c7Kdx0F3kLNK9CNgu= aHkFGfpui/z149XJHNKRgaMZmcl7y+zfqmDb8wyNF2qp0bm3dhqIszCp33Ybv5jcv3RCvVcmrqs= rWrVuZn5+nu7t7KeVfSkldXR3RaJSdO3eiaRq7du3i9Ok+du3ahRCCdU0tDDz4UQQC3e/DqK4i0= zfA2Pd+SPWOa/FUnf8euFeDTKYZ+/t/IvuLPchCDoTK7MAQwYJJ02/fjeIxyOfzVFRUMDExQXdH= B9mjx2Emzv/P3nvHyXXVB/vPuWV62ZnZvtoiaVe70qp3S7ZlueJeBAYTB/iZFkJLCLwBYn5JSAi= EYmoIJa+NDQEM2LiCMcbG2LKq1duq7q629+nllvP+cWfXkq1mbMeGzKPPStqZW8+955zv+VZbsR= CREHjd2AMjWKMJBp7dTNPVl54x43YgEOA973kP2WyWO++6a8rXyaW7uPqqq7ngggtQVUfj2NfXh= 2070X+maTI6MoKmaS/kwikOypVVVfz1Bz6Aoig89thjbNy0kRk1jrbU4/FQW1NDLpejqsox99bV= 1U290zNmzAAcjYyu61RVVVFZWemc0zDx+rzU19dPvftjY2MsWLBgKit4ff0LARCGYRCLxQCoqKi= gpsZZjEymUmhrbcWyLNxuN16vl8bGxqnvC4UCmUyG8vJyqqurkVKesjDxiRiGUcwW7wzOTtoJx9= RqWzaariFtu2ieECAlhmli205epUDAz5uvWkNFcAMb9TTx+gimaaNZaabXCNrbVjFnzhyisXIKh= oGqKCcsbCb7B1O52wzTcRDSdQ0hlKlJUrycviRBqwiiqKpT/gAQHh0kZP59A4WfdCBMiUuHtS6J= P6zh0hXWXnwJuq6hqCput5tsJsOSpUsds7ppMjExQXPzTGa1zkLaNtUXXcTE+DjLVqxgbGyMcRx= NRc4sMHBdBS6XTjo9hLw6Qr6QR28P4nbFyBfy+Hwmmf5utDUBbNuHke0jMpSjurr6rLcnBBQKCs= 9vM2motTnSpdDWYnNkLyxaKNA0CIUEbbMFWzbbeAVEggp7t5hssxU8ARgehr5poOZNJlKCY3tNc= qagbrrGju0mFbUK5VGd2hUvDTg55+cwSXA+E7O/QFILQ2Kn87yBoKuCiLeeyQzOLz5u3LDYn3Kc= gien1PevqqJeV9DUM2tIbNsmk8mQyWSIRCL4fL5Ta1WEcga55VRafnFu2o8/ckyVUjI4mOTnP9v= J4GCcSNTPjTfMo2l6FEV5aSDH5D1NypbOV4LuEYNf7SrwjtUe0nnJk/sKTIsqbDxiOWOlanP5XJ= 0NR0wG4uDWYcUMjRUzXOinyj4vBKruYnyoHznbnjIZymIUsJSSedObmD+jkS0dh1na2oKnOEdNt= Z2U5HMZspmsk27nVdRwncgfp0kSAqkHEXU3wugWtNzgKTY68RerqEd+kfQqBIRaETXXcLr13aYt= W9i1dy9vv/lmBoeG2LZjh1M6wrIwLYtwKERvfz+RsjIapk2js6uLZCpFRXk5dbEYB48cZjfQUF/= P4NAQAic5WCqddnxaqqvZsGkTI6OjBIPBc7h35+ZO3w+ch3eo1+bIqE3EI/AokLHBMsGyIWtJZl= SpLJmh4XEJOodtdnRZ2DZEAwoXtGmO6lm86LivEkIIysvLKS8vP+N2lmWxd+8+BgbWs2PHDm5+y= 83En36W3MAQCFA8HjzTakkf7yF96Ag9P/0Fjbe9A833x9XUkpZFYu8Bktt2o7c2w7FOtPpapFAY= +vVvKX/TWnx1NYTDYdra2pxEfYbJ+LadqLVViHgSLRYhNHMGwaaZtL3/XWh+7ylTEpzQGGiaNuV= Y3tzczMaNG7nqqqsAOHjokLNZMUotGAxiGgY7d+6kp7eXjRs3Mn/ePPx+/5SgLhSFbDbD+ueeQ0= qbQ4cPMbd97pQDuVEwONBxgPHxcSKRCHV1dfT09DhtUPRDmhS8UqkUuq5Pmchs23aErNpa4vE4b= rd76t90Oo1pmlOr28lnMOn743K5pnyWJgXjSbOhbdsMDg6SzWbRNG1Kw1ooFKYi9oQQzJo1C5/P= d9rm3HvgsFOQVgpSqTT5gkGsLER1VTm9fYM01NcyMDBETXXl1Mq++3gfqWyWQr7AkgXtVJRHmUj= lWTl/FqmUUztQ11UCwRCV1XXEUzmObd2BEM7kFi76F6mKilDEVPi3IgRHu3qRtkljfR0+r5exeA= KP24Xb7cLncVNVWfEibcApXhEEyrQA0lWsUaUJlKgHe/cw9uNdqLVB8Kq4wz7Onx9Bj6qYukI4H= HLa3e0mn8s5NQeR5HN5PB4Plm3j0jQMw0QvPhuv14tiWng9XvL53NRkblomqq3icrudsUFxtAiy= KBCqmoZLn/RfcoqV29apgyhe2gUENXXwl3+hoqgaF5jSyV9VcCas6U1OjItQYPlKFaMgURSVfMH= J7YYQ6BqOC43lqBUWL3AjJZgGKNLC7VFPeif/WJy5J8AgkqeP/Bt5c9K/VTC/8houbPorlGLeJE= OaKEJBEyoSOJw2+NvdI2SLzaIKwUUVXj7TUuak/TgNkwsGeCGx5J9KSg7Lkjz04B7mza/m1gWLO= XxohB/96HluuWUhli0pFEzqasuwbJuBgQRlZT4qKgIcPepE9TY2RnF5XDy5r8DxkQL7ejUqQwo9= YxZuHWrLYH69xnOH8jy5N0+yAEubdGrKVKrCKqcLflQVhSUrzmP900/Svmw1Hr+ThseybZKZLJZ= tc9niBQghuHrFUnRVZSyZwqPr+Dzu4r2ZdHbsQnP7CJe9Ukfy0/PHO24LDULtMO0GZOc9YJ67Gn= 4KTwWi8VaEt+qUQoAE9h04wKyWFtpmzWJ6YyPNM2bw26eecrQgs2bxxFNPsWTRIjZu3szRY8d4f= vt22ufMYWR0lEAgwOYtW2hpbiaeSLB561baZ8/G5/OxfedO6mpreW7TJmLFye/FPgx/LELA9BoF= n1/g1Z0fw4aC4Qx5BQtqos7A0lSh8N6L3RwftVEENFYolAfPtBp5dTiXF0oIQTgcYuXKFZTHYsh= 0mp577wfLcgZGv49AYz35/kHqb3kzgekNSNt6RaseY3gMaZqo0TLkeBnuGU1QMCgc68bKOn4/Pp= +PRYsWgZRkxieov3kd7lMWgG4AACAASURBVICfkW07MPJ5atZcgCscwhM7e8fx+/1ceOGFhMNhP= B4Pb7riCo4ePYqqqsyfP5+uri7GxseKmiWdmpoaLrjgAjLZLIlEnPNXr2bZsmV4PB6WLllCWVkZ= fr+f888/n0QigQCWL1vOokWL8Hg8yKoKhKoQCoVwu9243W4nhUFV1ZQgk0wmpzRTk/X03G73VGH= fQCCApmmk02kqKiqwLGtK0JvURpmmOSW0ud3uKUEpn88TCAQwi9obXdcJBoNT0W0ulwufz4eqqk= 4KAyGm6vpJKc/qfD8xEWfztj1YpgFCIZXJsLh9Fi6Xzqbnd7Jl+y4y2TyqkOQKJh63i2wui2VJT= NOgr3+AC1YtZW/HYUwjj2la5HN5opEQecNC37aHiUSSxtoqYhVVHDx0iEQqDULBrWtoqoaqqVRX= xqiMRYgns+SyKX7926cJ+n0gBJlcDo/LxfLF87jy8rVnFZIQoMwtx/3udhSfGyXmhTofWnsFgS9= djPRrSL+O6tcRUS+KX0dVBE3Tp78kz9XZ0iq8kERy0ixz5lxZp0vZ8HInDE0XaPrJz3bKZSz00u= 3PFSnh6qsFylk0NS8HgWBm9Hy6k9voGHkKy3a0hXaxWLmUkpF8nP8+/gQrorNZXDYLl6ojERgID= CkRSKb5dG6p9RPUTm9qmwycUBRlKgfTn4qABE4qjvhElhkzYkQiPmbPqeLee3fxwAN78PtdRKM+= Nm7oIpcz8Xg0jh+f4LzzpnPkyAiapjDUlqJ2Vj0jSYsLZrl5an+eaxY6L4aUcHTIJJGVdA6bXD7= PzcbDBju6LIaSsNZ/+rYSisKKVefz5K8fYv/2TSw47xJUzdEUGaaJRGIWtcuTml+rGPE26didmh= jl6d8/xbzlawiXnTnX4SvhFaTLFAhXGdS/DXIDyP5fFyO2zhF3BFH/ZkT1FZzOO18AoWKRwWw2S= 09fH7996imElMxrb6eutpYt27axcN48xsfHGR0b4/xVq9i/fz/pbJYbr72WGTNm0HH4MLFijpmL= 16zhD889N7UyqCgvJxaLkcvlKAu/OqUjhBBUlmlUlL1wH5PIqW2czzUVqiOC6jJlauM3ShdUFIW= 6ujpisRguXSe5aw+KgKa/+v/IdPVgjowQap+Nr6GeuhuuQfP7XtEAIhQFb+M0NFUnu3kXGHnMse= cACC5sRw85mr4THZq9kTK8q5YjAH/DNLLJJGV1dU7kzzlcS8DvnzItCiFoamqivr4eVVVZtmwZS= 5YsmZp8lKJp56qrrnoh/YCqTuUuWr58+dQ5b7rxpin1tXKCSchV74XieSbvRQhxkhZz0gQHp54g= JyfEYDCIpmkEixF8kxnVJ/c5UX3+4mNNFuad/D4cDp90jBP3P3HyPVvyuAVz26iIRRifmEBKC8u= SVFdWECuPUR4JEU8kKeRzWLZdNF2dICDYlhMJVx7lnTdfy+jYKIWCQT6fw+Nxo+s62WyWQqGAz+= ejqqqa9lkNjI+PcbSr15n46mpx6QoBX4BwWZhwuIxEIk4ylSKbyaK7XFO5cyrKY+eWDE8IRyD63= BqKafFBLdaeKmqWT9dpzyWQ4mzfn2mfs/l9vd4IAdoZhJA/7pgCt+ZnZe07SBdG6UnsxLKcckhS= SlJWli8e/Ak/732aem8lX5n31ywsa2YqCSaSmEvjvQ0B2oMutNNEak2a1DVN+5MTjiZRFIHLozE= 8nKKqMsjQUApFcXyMmpvLaW2r5PP/9gSmaVFXF0ZRoKNjmPnzq4lEfTzzbCe9SgUDSY1Up6B/zO= TQgIGUTldordGYO03n8IBB1K/gdSmsmKkzLaridyucyZs6Eo1x5Y0386uHHqS2YSaV9TNRFYVYK= EhuYABjzFmcStvGNgw806bh9rgdc7VRYMOTj1KwVeYvWoLL9SpX6zgBMTY2Jp3GVPD5fGdfVb0Y= aSNzg8iue5DdP3dC/M80zQsF/PWIpnei1N4Auv+02zuq+ON87667CAQC5PN56uvqkEBLczPtbW1= 89847qSgvZyIeZ/7cuezZu5eqqir2HzjA8qVLOdbVhcAxORQKBf76fe+jt7+fe++7j4Zp01AVhY= qKCpLJJG+/+eY/yY7wP4GUEiubxTYMhMtFrq+fnvsfouEvbsYVDqNPZp1+heTHJ+j8jzsZ+PF9W= IkEUgFPQx0zP/V3VF5+EcqZ3s8TJv7XXBVX4pRMmgsn81hNarMmM7mbpslk+QFZrEXl9DnHh2jS= Dwsc/6bJY01q1CaDLCZX9pM5pnL5PPZJGjXHRDnpoOqYTPKOz0jx90kzZqnP/2liS4ux7HE29N7= JsbHNzC6/nIW17+BfD/yEH/c8Sc4uoKDQHmzgK/P/GqE08eHd45R7ND7YGOKicg9+TTnl7PPiRc= SfKlJKDh0a5hc/34muq2SzBldfM4f1zx5lYCBJWZmH+voImbRBPJEhn7OpqQvTPqeKUNjD757ux= DNzFqtm+6kMqew+XmBPj4EQgpYqDbcuWDZd56n9eZJ5m8EJm5E0uHWFRQ0qF89x49FP3365XJa7= v/+fKPkJbnz7u4lWOVHb8c2bSe3bh53PY6fTmKkUlddfT2DuXCSSHc88xv0PPsKt7/0QrbPbz6m= 80LlgmibpYk64SV65kATO5GRlkRM7kV0/gOH1YBdOyu8kFEANQu3ViPq3oQRacJJknOmwzos6Nj= 7O8d5efF4v0+rqSBQT5IWCQSbicXqLYc+V5eUMDA0xNjZGdXU1oWCQnp4eLNumurKSVDpNbdFxt= X9ggEQySW1NjTN4G8ZUor4SZ8e2LMxUGj0YOLesu+eItCVGOs34pucZe3YTalmQqssvJjhrJspp= CoWWKFHifydS2mSMBIfHnmbcnOCnwyP87PjTGLZ50kJpVmAaf9P6UbqyNdxc7WeGXz+tBunPDdu= 2yWYN0uk8Ho8Lr1fnzv+7idlzqpgzp5JQyIttSxKJHF6vjqoq6LpTPy+ftxCailtXUITAsiU5w3= Y0hIoTsKSpTioL03LizcxiYk6XJnDr4oz+XlJKxsdG+d63voZWiHPLbX9FTeMsbNNC5nJwgmZcc= buxpckfHvkpP73vYd79ob9j6Yrz/jiZ5TS8dkISOIISOMmvcv3I+F5IHwIrDVoEgnMQ4Tngir5g= XisJJCVOwSsph1GiRIn/XTgRUZK0keH3I7t4dGgTB1LHyckCqlSpcUe4sHw+11atYpqvEk05tfb= oz5kXj6mdnaOEw14ikdMHYbw0yu3E45xo5n1p+aMTtz3T2D25TXxigv/+wX/R3bGDG268njlL1+= ALhKc00IV8jsHugzz0sx/R0TXEB/7m/zB77rxX3Qz62gpJJUqUKFGixOvE5IRrIzEsk4JtogiBW= 9VRhZOhubTYcnijFc52SmFl2Lj+GR578H6CbsnSZUupbZhJOj7Orh3Pc6izl9kLl3P19TdRXVP7= mlx7SUgqUaJEiRIlSrzhmPRnnBgfZ/OG9WzfsonExCgut4fmtnaWr1pNY9MMPB7PaybclYSkEiV= KlChRosQblklf5Gw2QyqZRNd1AsEguv7aB1mcSkgqecKWKFGiRIkSJd4QTEYU+v0B/P7A6305vL= oJLEqUKFGixKuGZVsUinmdSpQo8T9PSUgqUaJEiTcgtm2zr/Mw37j/LlKZdElQKlHidaAkJJUoU= aLEG5BMPssjG37Hz3//a363/bkpX40SJUr8z1ESkkqUKFHiDYZEksyk2dt1iHQuw2Obn8Ywjdf7= skqU+F9HyXG7RIkSJd4gmJZJ3ig4Nf+EIBoI49J0qiIxLGmTKeQQgEtzob1KpRhKlChxekopAEq= UeI2ZNJNIaYMsRm/8iRbMLPHaIaXk8GA3dz/7SyxpM6N8GrX+CvYcOcjqBUvYdnw/PRODlPlD3H= b+jVSXVbzel1yixJ8VpRQAJUr8D2LbNvlshqGBfvo7j5AYH0Z1ufAGy6iuayBaUUUgGEJV1ZLAV= AKAqD9M50gfu7o78Lk8vHn5Fbz1kqv5t0e+x5ajuwG4pP08XJrrdb7SP19s2yaVSqCqKj5foFie= Q5LP5zDMAn5fAEVxtHiWbZFMThDwh9FKtSX/LCk91RIlXgOkbTPY082ODU+TT6eondFC8+w5KLK= AkBaqlSKb1NFUFa8/8IqqWE86856q1EBJ+PrToswf5K8vfhuff+T7dI30cqD/KCOpCQ70H8OwTO= bWz+Kd599AyBuYqlL/cigYJgOjcQoF84RPJwtzCQQSxEvrc0kpkEI630sxubmzhXT+lcUfceKuU= iCFjZjcBxDCKYQqTiyAPrk5IIUsXssLNcOEEETCfsqC3pfc86SmdqpmGNK5JkUg/ogqbZlMiu/+= 4N8JByO845YP4/F4kdLm4JE9dHYd5LK1N+D1+qe2veu/v8ZfvvVDlMeqznhc27bp7e1FVVWqq6t= RXoXC4IZh0N3dTTgcJhaLlfr7a8DLFJKKRWyLOF3qFAXvprZ+KWf67mznPvG8/zv4c4pkeQXPTE= pOqrT4Bh8IpG1z/OhhnnnsAbw+P4vPW01uaB+ju9ejSBvLBtvIobjdlDUtonH+pai+0Mu+rxOjn= SzLIpVKkUwmqaqqQtM0lBMqaJ84eJ6qGOWpjn2m70/c7tUcmKfMkifx0ppbf26TgW3b7Oo/SHd8= gKgvzFdv/RQjiXGOj/YjhOCDl7ydlupGwv4gPYlBHj/4HK0V02mK1qAq5y5gD40m+Ow3H+TY8WF= sYU0JJQINYasomMUxXSBQQCjOKORULwcUpFSwFQuJhYpalJYEkEeio0gFhFN0FgsQeRQUpFAQNi= iY2EIghYbARKIhpCjOJwJLSmxpo6oKQhGAQNdU3r1uNTdcugiX/sK0JaVkKHmAbd330Fp9NdPKF= rPp2J2MZY6wrPE2qkNzprQ+5/ocevu7UBWVnXs3MTr2VmprGgCBaRoUCvmT+o+UkE4nsCzz9Act= 8qtf/YoPfehD6LrOww8/TGtr6ynfY9u2sW17qm+dTtMspeTRRx/lPe95D62trfzwhz9kxowZ53y= vJc6NcxKSpJSMj4/T19+LoqonLRukdJYRQhSlYnGCICRB2hLLtpyHrahOXxIvfG9bzgshVAVVUU= 6oNlys5WLZSCSqoqAoCjYSVahMb2rC5Xrt05S/Xph2joHUsyTyR1/vS3nFlHsXUhlYxssVlKRlY= fUNUHjwEQrPbUKNRXG9+Qb0ZUtQvJ43nLAkpcSyLIb6e9j0u0dx626WrFpFYfQw/mgNtXPXoLv9= SNsmEx9i+PB2Jjp3kR8fYvry63CHKlBU9ZwrWzup+7N0dnZy//33c88995BMJrnsssu47bbbWLB= gAeFw+KQVq2ma7Nu3j2QySWNjI4VCgZqaGqSUU9tNClzBYBBgytygaZrjUKwo5PN5stks3d3dzJ= 49G4/H86q0YSqX5A97HyeeHnPuEUnUX8OMmoV4XAFURcHvduFzu3Bpfz5mSolk79BRvvzMPVi2R= VvldD576QcIewNYts3qlsUMZEb44EOfpzcxRHkgwmfWvpeGSDUvRwcpJQS9bv7pwzdQEQ1gIsnk= De576Dn2dA/znpvX0tpQjW1bpFJ5Hn9mF89u78TrVfnA2y+mc2Ccex96nvNm13PZxQv4ySNbOdz= Vz/lLZnDT5Uv55j2Pc7hnAhWBpgouWjWLq9bM5z9++Fss2+QDt1xGMBxkYizO1+/6DU3Tq3jH9a= sxTZv/fnAjvcNJbnvLarZuP8xvnts79e6ZtoVpv1h4BssusK3rPtYf+in94920117Jr3f9O5ZlM= Joc4M1LvkbIe2YNz4kUCnl27dnMkoWraZ7ZzsYtT3H91beiKK/8Pdu7dy8jIyNkMhnuvvtubr/9= dvx+/wnPRlIoFFi/fj3f//73OX78OCtXruS9730vM2fOPMmcJ6VkbGyML33pS4yOjtLd3c34+Pg= rvsYSL+WchaRDhw+ya99ufAEfUkrSyTQjw6PEEwkURRCLRSmvLHcEFwS2lGQzWUZHRhkaHAKgqq= aaqupKdF3Dtm0S8QSD/UMkEgk8Xi/T6usIl4VQFAWjYDA6MsbgwCCFgkE0FqGmtgaX20U+naOiv= JxoNHqW6wbblpimRErQNIGmOS+7ZTmfg/O5okxOBs4+AIoiXjIPS+nsa9sSTRPFFOont5VpSizr= BeXHiSiKcz5VPXOnM6wU+4a/z9Gxn4EEWyoUChpCSHTdQkoFy9JRFAtVNZG2C9tWUFQLRSlwLlq= okwTSyc8m7+NFv5/qs3OdnxbV/AMVgWUvT0SSEmtsjPTH/h5rfwda+xzMfQcw//aTeP//T+K+9k= rEGyy6p1AoMNDfx8Edm8jlcyxfczmKmaZmzgX4QuUnOWt7gxHClQ2Mds2gd8fv6N7xW8rnXAyah= 4qKszvkOj4SeZ544gkefPBB+vv7p1aRw8PDfPe73+W8887jne98J+Fw+KRr3LlzJ83NzTzwwAPE= YjEMw0DXdaSURKNRstksO3fuZNmyZaTTaTRNI5PJ0NraisvlIhqNsn79egzDwDAMWltbX7U2TOd= TPLvvSaR0VtJHBw7i0txcsfgGrlj8FsbSBQ70DhEN+plTV4lb1/4sBCVFKFzVej4bj+9mQ+cOOs= d6eeroVtY2LCkKpoIH9/2e/uQIAZeXy5pXsrC2Fe1laEnA6bv+gIuZ9eUYtsmBY0PkLUk2bxDUd= VrqyokGvew+1EV9dSVvvXolHccGkQha6ivwenRciqS83E9zYyXV0QDHuqGxuozWhlpqYmHGk1kW= tDXQ0zfMjj1dXHvRAgBUzU1leYiqWJg+YSE0cCsKDRVl5A0Tty5QhU3ArXHgaC8VERcXLm8nl7f= Yf7gP5RTPWVE0ZlVdynhmiLbqixnLdJM1JLatMJYaw7Dy59w2tm0zMjZId89RVixbi8ft5Tt3fp= 4LVl1BeazytPudq77/1ltv5cc//jG7du3iJz/5Cddeey3Lly+fEn4KhQL3338/t99+O8eOHUNKy= YYNG1i/fj3f/OY3WbhwIZqmTfX9H/zgB+zZswchBJdffjkzZ84853stce6cs5AkJaiajqbp9PcP= sPGZ5/C4PNTX12NZFts3b0N161x82cX4fT4y6SxHDx7BrbtprGsgHA5z9NhR9o+OMn/BPOITcfb= u2suCeQuYXt+Eruts2ryJ6c3Tqaqpoq+nn9GhEea2z0XXdQYHB9mzcw/zFs2byu50psHRtm3Gxk= w2bRph9644+aygscnNRRdXobsUNj47TkdHGktK2lpDrD4/RFW1G9OUbNk0CqrNkiVRPG59ajWTy= 0m6j2d5fssoPV152ub4WLI8RlWlG1UVCCExTZMNz43x5JMpTNNy2k8xABXVVvF6VJpmqly0tpqq= KjdnNEvLSW2bxuGjjezaW4umSua3jxD01zIRn4XuylBZvhNdnA8yhi36UD2PoKgDAORNncGJELW= RCTTVwrYVbASaYp14GjJ5F6m8B121CHszZAoeTFsh7E1P+RjEM14kgjJvptj+5/L2/HFIoPD4k1= hbt+H71lfRzz8POTpK5l++SO6eH+O6bC3ihFXY641lWQwNDTI62M9I73EiFdUEQz4isSY8gQiIk= 01GQgh0l5fypgXYpkHfnifJjnbRNWwQXrUKl9t91sm/UCiwefMmAoEAs2fPZnBwkMbGRo4fP05z= czNbt27l+uuvJxQKveRYpmmiKAq9vb0EAgESiQSKotDf38+SJUtwu91s2bKF5uZmjh49ysqVK3n= yySdZt24dR44cIRgM0tnZyaxZs171iFi35uaa5W9GSPjKg58lZ2TZdmQDa+ddwfSKaYwl0/SNx2= mIhXHrpx/CbNsmkUhMVRc3DAO/30+hUEBVVUzTxOVyoaoqlmWRzWYJhULkcjl0Xcc0TTRNI5lME= olEyOfzFAoFvF4vfr//VRHOJJKMmaczPUzayPPmJVfSUt7IcGoMy7aQvOBv49Fc3DT3YmrDVbRN= a+FwZpiwmaY5UI36Mv1bpIDj/SPc+9CzZE0Yi2cJ+d1IoGdkjP/44RNcccF8rlyzCL/PSyqbP/k= dFs4isioaZOa0GOUhnzNOKIKq8jC3XLOMzduP8MvHt5FMF8cL5FRdLkdcK/5/0lpXPLRl25i2ic= ftZfHc6dSUl/GAvQX1FNocRahML19GfXQ+oPDMoR9iFFxY0qJgKBiWgWlN5peSCFHU1J5iyWZZJ= s/vWI/X62ciPoqu6bjdXrbtfI5LL7rO2UbaLxKKJOIU5uBTUVlZyfve9z4+8YlP0Nvby9e+9jW+= 9KUvUV9fj2EYPPjgg3z605+mq6tryqRn2zabN2/mYx/7GHfccQcLFy4E4Pnnn+eee+4hlUpRXV3= NbbfdRigUOus1/E8gcdpJIFD/DBYwL8MnybEZj42M8dB9D7DuxnXcdNNNhMNhLMuit7eXu35wFw= /e9yA33XwTo6OjlIXLWHfTOh5++GH8fj/ve+/7+I//+BZdnV0cPHAQI2egqRobN27khhtu4C/e/= hf85N6foGgKvd093HTjTfzyl79ECEFLSwstM5vpO95LVWXVGS03UkqSCYPvfLeH+35+nEjEi8ej= 8fDDQ9z7835i5SH27RynvNKPFJKf/2yQ5St9/Ou/zsXnVfjNr5Mc6hzmjjvKqKl2NEfHu3M88tA= QjzwySDyZIRwMcP99fVTVdnHTuiauvKqS8nIV04QNz03wve+OMG+hl4BPIEUWKTWkVMkkJEfvmu= DK6yb4/L+2Ewic4RFManoQ9A5Usv9wPW4NomUV1Nc1ksu1YVgpcrkJPJ6lePVa8vZhDOt3CMXZv= X+inD/sb+OyuTuxEYwngwwnAsyqGUBVLRQhGU4EMWyNRNZDJJAl4c7QOVJJ2JvF68qiazZuzeDQ= QA2xYJJwfddr6xVWNOXaBw6iz52La+UyRDAAHjf6+eeR//b3IZMBn+8NY3LL5/McPtiBV1WwDJO= a+ul4vCFUoWMVCkjLQnW5kLaNncuhFM1TtmEQqpzJWHAP6eFjWEaM4cF+6hqaTnmeE520dd2Fz+= ejsbGJsrIyHn/8cVasWEE2m+W8887j2LFjhMPhKdM1gMvlYsGCBSQSCa666iqSySRutxvDMEin0= /h8PrLZLJdffjkul4tkMsnChQvRdZ3q6mqmTZtGNBpl3759rF27lkgk8oqczl+M46wrcOsehHxB= u5vJp0nnEtREFdy6ilrMI2RYFvppfDYKhQK//e1vSacz2LZFNBpD01QymSxerxdNU3G73cTjcXw= +P9u2bWPFiuUcONDB7Nmz6ezspK2tjYcffoR1626kv3+A3bt3sWDBAi655BLcbvcrv2EJKSPHFz= seYePIIYK6l7fVn8dtc9awt+8gQihIbIQQrGiYx6yqGXz72O/49u4fk7HyvK1+Jf8w+wbUl5EXW= OD4Zrc01fE3t72JVDrPt3/6NLm8iQQiQS+XrZ7P7Jn1iKIJeVJfIoo+gQIFl65yw+VLeNOF8wj7= HNcHW0Aqk2PfkQE6+8axAKUoyMrJP1IACkIWvVzFCdoYAV6vmyVz6vndc4f4xp2/ZXZLDalkhtq= a2CnvR1FUdOFFSolfr8SyvBSsPKPJOH/Y/zMkAsMqIKVNmb+KedMupC7SjK6d/PzSmRTbd24gGC= xj287nEIDH7eH3zzzKiqUXoaoayeQEhpFHSkdITqdTSAm6fvZ3QdM01q1bx3333cfvf/97HnvsM= Wpra3nrW9/K1q1b+epXv0pXVxeqqrJo0SIWLlzIE088QVdXF+vXr+cjH/kIn/zkJwkEAnzpS1/i= 4MGDqKrKbbfdxqJFi07dByyL/mwCw7ZxqSoxlw+fpr9m2lcpJaP5DBvHelgWraPS/cJiwrRtxgo= ZxvNZPKpGlSeAW9NPtlZIiSFtNKGcUnP4evCyHLdN02Lb1m3Mnzuf6667jt7eXvL5PKZpkslkeP= dt7+Zjf/u3dB09BghWLl1JLpfjnnvuoby8nCuvuorlK1by6GOP4tLdvO0tb+Ohhx4imUximiaRS= ISKikqGh0doaGhgZGSESCTCtddeyze+8Q2uvfZatu3cTnmsnBfFUryEjkNZ7r5nkGuvmsEHP1SB= xyvo6MjxkQ/uYfeeCf718zO5dG0Uy4KHHx3mi184zJoL4lxzXZSMoTA85KGQc8xqO3am+Myn9zE= yZHD1dVVcc90cKis0urvz/OLeXr7y5YM89dQw//jPs6is0DFsi1jM4gtfaKau1s1k+IeUgmTS4h= //sZsnnxhl4uPGGYWkSQ2OEDZV5TmuXNvr5G+QLtyuw3jLezAsBdMeJltYjyFzGJaN6iqgucC0F= fZ01qEoKru7G7FsQX3lOMm8l51dDbg1A8t2EQoV6B4KEvWn6Bv1cCBVS1V5gWRO0NFXSzSUpVAQ= CF2hTKZfVQFJ2jb24BBWMgmAEgyixmIIXcPz4b9C5nJYiQT2kWMItxu7UADTBMvRhNnZHNbQEML= nQ41FQQjsRBJ7eATbNBGqghKNopaFEIrqmHHSWSQSYUuQtmMWVRWEoiE8boT28if9bDrF6NAAFW= VhJJJQJEJmbwfHfnAX0cuuIL5zF9VXXEbm4CGyx7pQoiH8s9sYfOCX4PXif9NyCsYEvrI69u/df= UohadJR2zAthifS2JZNzbQm6murCQYD1NTUUFNTQ0tLC9U1Ncyc1Ua6IIkPTRAL+/B73aiqSnNz= M6Zp4vF4plT9Zyt3kcvluO6669B1nUgkwnnnnef4EhY1A2fb37IslKJf4ctFCPC5AwS8YQzLJpM= 3nbpmPYNEAj6mxcIEvZ6XDKqWZTE4OEg8nnA0d7qL2bNnc/jwIcbGxnC5XOTzOfbvP8D8+fM5cK= CDlpYW2tpaSSYTrF+/nsrKSvbu3cMll6xlZGSUo0c7qaubVhQcXjlCCMpcftaUz+bR3u0cSgwwU= ciwPDKDgNvvuH8WfXECLh97k738qGs9/dlxZgaruKJqwcs2uTlIEok0Ozp6yGZM8ukC6AoShfJw= hJuvWYmwv+Bh3AAAIABJREFUJc/vOMzYWApv4MVCgI1pWuw+dJye/lHmNdexsM2HRDIwNMZdP38= abIWWpkoqY6HiGXF8v7EBGylsLJz+Zxd/FEXgd7l4+7VrWDCnmcef2samHUcwbFg09/TmpMmJuD= 7ajq6Vk8oNkswW8LnL6Rrdz86uP5A382iKxjMdj7Bu2UdY0HAhHt3rXJuUHDqyl9qaRm685i/xe= LyAwLZMvnf3l9iz73laW+YxPDLA7r3P0zZrPoVCnl8+cg+tzfMI+INnbXEhBJWVlfzDP/wDBw8e= pK+vj+9973v89Kc/JZvNkiyOga2trXzrW9+iubmZX/ziF9x+++0MDw+zadMm3vWud6HrOvF4nEK= hwLJly3jf+96H1/vSqD+npSVPj3QTUHVsJF5VZ01FI15NJ2eZICUeTUdKyBU1bl7VEaJypoEE3K= qGRJK1DDSh4lU1LCkxbAtL2rgUFUUIspaJAFShkLQN4kYer6Lh010gJdvH++nKJmjzx9g40c3a8= kamqSEyphMs4FV1MmaBJwePsrqikTKXx7Hg2BYuRcWlaq9LyNbLEJIkRj7PQF8/n/7Up/nZz35G= PB4nFArR0dHBvHnzWLt2LZddfjk79u5gxoyZFAoFgsEgDQ0NRU9+KOTzaKqGrum0traybt06Nm7= cyOc//3mmT29CAs1tLZiGIzQFg0EmJiYwDAOQuHS9qDw486B87FgSy7BYfYGHxkYPqgp+n0pbSw= UHj2W47JIYtdVupJQsX1KGrgXYvTfJlVdHpsyLEhgfL/D5f9tNXy9889sLWLLUj9slUBSLmpoQ8= +cHWP3bCj7zySP88O4+PviheiQKqu4jEnHj8ah09xbI5ZxLHhky6O/JMG2ags939glDFLUAHUc0= Nm6qRijQPtsgFGrGKMxHUiAW/SWR8Ftxa0HyZjcJa+vU/q21fURDhxhJ+HBrEkW1WdSYIl1wIWx= BWTDDQDzMosZRPK6C43MlFVJZHxWhBBF/Al2z8LnzjKcC1EQch1ohij5Xk078p7v+s73VBYPkX/= 0N9radICRKeTnuj34Az803ofj9ZO/+b/J3/hA5PIJwuZBuN+rkxG7bGM9vJ/vhj6MuXoDvy59DC= YUwf/xz0v9+B9KyHCGpqQH3338M96Vrkbkcxi8fxkwkUWwJsSiYFjKbRYlGcV++FhF+eZFmUkqS= yQTxsXFioaBzH4ogMmsWowh8M2eQ6TxCprOTfNdRmj72Nxy6/XZc5RXIkQmEPYpbX0NeZpBC0rF= 3D5e+6ZpTXoNlS/Z3jfLoxmNoiqAi2oqnPEI+O0YoFMLj8eDxhcjYXmYuuYJfPH2ERKZAS30ZN5= 4/C6TFww8/jGEYhEIhVq5ceVIUjWVZqEXn8WQySSgUwjAMcrkcHR0dRKNR2tvb0TSNY8eOkc/ni= UQilJWVoSgKlmWRyWQwTRNVVXG5XKRSKQ4dOsSCBQsoLy8/53adxKN7WNl6PmFfjJ7ROPFs1jFl= C6guCxJwu53X8EWCmqIo1NbWEY3GiMfjmKbB6OgoAwODVFdXYxgFvD4fgUCAcDjEkiWLCYVC7Ny= 5i/nz57Fq1SrC4RCNjY14vV7KysLU1Fbj9/tPihx8MS9nlS6lRFdUbq5fQd4yuLvzafLYjBSSVA= gnF5KNnJp8RgoTlLl9zA7V8sHmy1gYaZw6zrme14log2N9I/zw/o2YEmxpURENApL+4RFSmTz11= VG2dnSTKOTx4poy/xf/wrRsNm4/wqadR1AVyYK26QgENZUR3nzZMipiIepqYwS8ruIw4Qyq0rbR= dRVdczE2nsIyLQzTJJXJ4tJVXC6doNfLirkzmF4b4XP/+ShHe8fO6d4qw40sbbqax3b9hGTWZF/= Pbq5b/C5Gk3H29WwlJy0yuR5++ty3CLpjtNYuQlVUpJRMxMe5cNUVxKKVU8K8lJJ1172TjkO7CQ= XLeMsN7+aJ3z/I75/9NYoiaJ+9mIsvuAZNOzeTsxCCCy64gI997GP88z//M4lEgmw2O/V9LBbjc= 5/73JT29tZbb6Wrq4s77riDXC53knN2fX09X/7yl6mrqzvts3cpKjG3jxpPgJju4anhTnK2xZGJ= cY6lxjGxmROqIG+ZTBRyDORTrKloIm7kOZwcxZA2s4IxCpbF4fQY/fkUb53Wzmg+w+ODR4i6fFx= U0cT+5DBCQsLMszRaS8Gy2DDSzYSRY3V5Aw3eMnbFh7i6poVyt49Kjx+PqjGRz/L0SBd9uRRrKx= oxbJvN433kpcXayulsHevHkhZSUVgdqyfq8p5TO7+anLOQJAFbOpFmfr+fvr4+LrnkEgzD4NChQ= 1x66aVUVlYSKYsgLRu/z8f69c8ya9YsGhoaaGtrY2R4hMd+8xsWL1tM57FjPP300yxevJje3l6+= 853v0NXdzQMPP0BNbTXbt25nzZo1DA4Ocuedd3LLLbewb/9+mmbMKE6SZwlNtgWaouP12gjhzOa= qKnGpOVzCRNcmHa4FLh00JYdRsHGMWxYCG6TC2Hie/btNVq+eycKFflTFMb9ZlgLYuFyCVeeFmT= 7Tz4GOPNmsjSIVhMhTyBv80+3Pcu/PxjFNHwoC01Tw+Hx84Svt+P3n0PzF27QtgWFoCNXGlgKJC= ricJAxSQdPcuHQ/pu0Gq5gvRCrkChp9I2Fm1A7i1Y3iYPrCoaWEitD41DOeOm3xl6rwOHZx29rI= KIf7awh5s+iq8RL5SBQ/kIAi5LkFs0kbo38A78UX4vroB8h+/dtk//P/oi5fhvGrx8l94Q5c7/p= L3G++Hqu7m9wXvw4TcaRpQcHAfOoPWEe7sE0T63gvypwgciKO9HgI/ui/EJpG9mvfJPcvX0Bvm4= XSUI9r3fVoCIRpTAkiEuE4grt05Iu1BIqCOIsGJJ/LMzY2QltrM9KWZNMZ8oYgn06R3LUdPRpB+= P1kJhIMPP442ZExYtEI7roapGlRGBnGWx1mNJkiMR4/jY5UUjAs9nSOMDyRwa0rdA0WeHDDcVa1= V7H60hsIxSJoVRZff2AfHrdKVcSLaUoOdo8zEs8Q8Wv09vYyMjJCU1MT3/jGN6b8cBobGxkaGsI= wDGpraxkZGUFVVVRVJRKJMDAwgK7rJBIJVq1aRSKRYPfu3SiKQiaTob6+nr6+Prq6ugiFQni9Xq= LRKKOjowC0t7efwwtxMqqisXbujcxruoL9/XFGk2ksy9Gs5AomqiLIG1nSuSQv9hYByco1S4sBF= MVgC1Vl7uI2R+No2yiKwvlrVyKEYNHK+ShCoX2xE5rdtqAFIQSf+IePoekaTbPqWbJqIaqqEs+N= Q+7kswkcjZfP40cRZ18A2dKmb+IA64/9CMsu0F62gMcv+DuGjTyjuSSGlXbuojjuKopCm6+WR1d= /Ai95dvc8yn3bfoKuuri87cNEfLVnT9kgJsdywbzmBj770RvJGTYP/2YTPSNJbClIZg2+/8Nf8/= EPruOGy1dy+Mgohm04JnBbYouiycx22tC0DSzbwMLRlgd9bhbMqacyWoZAkDVMbCE53pvk9q/eR= 8AtuPFNS6mp8rF9Vx+f/up92Ai6e4dZuaSVTC7HP3/jASYyFrat0j0wwbkMJkIINEXjLSs+SCZv= sPHIE+zr30O44zesbrmejt6DZApOmx4fGeTp/b9hWqyZkLcMIQQXX3gVhmmQL+SmnqeiakxvnEV= TwyyEEMyc3kZjfTOGUUDXXVPh+ecqoDoaTZ33v//9pFIpvva1r5FMJhFCUFNTw7e+9S3e9KY3Tf= n5eb1ePv3pT6NpGl//+tfJZDJIKWloaOCb3/wmK1asOKt2VkqbjvgwBWkxzRdGAZ4cPsY11S2MF= 7I8N3ocv6LRFqpgdrgCXag8O3qIlZE6cpbB/vgwl1TPoC1cwc969tKdidMSiBLz+Lm0cgZj+Qw5= y+SamlkkjDxSQNjlYXGoioxlsDU+gE/V8WgaQd2NQBB2eR3BX3PxpuoWdsYHOZSeYGlZDY3BKJd= VNdOdmSBp5VleVsszI90MZJOU6S/VGL/WvCxNku7S8fl9bN26lXXr1vHoo48ye/Zsli9fzr333s= tNN93Eps2bqKyuoqKqgsREnDu+egfTZ8wglU7zT5/9J2a2NVNRU4E34GHr1i10dXexcuVKfvP4b= 9i9ZzerLjyfcDTErDmt3HXP3axYtpyly5axfsN6EIK5C+dSyOaLvV2ctu9M2r9PRCAJlyWYt0DF= 63nRiyVPdKp11MEA0gbDFqzfMM5HPzqMqhhOXo9irgMJ5NMa+w/YrFipFTVQNhITRZW89ZZ5XH6= FC7ARKGQyJvc90Mdn/n4PMxrnsnJV9Izd3xngiyaNydwlEjRFRSrKCxF0Qjg5RRQx1SwFQ2f7wW= Z84SxDqSiN5YNMZAO4FIuCqRDwZRlLBnGpJj53gXjOR9CdJWu4yBkafleOWDBN73iMiC+FtBWSe= S+DEyb9EyF8botkzk2ZL0U658GtFQCFguViekU/sVDinEM/hNuDWleLvnAB1p792Ps7KHzvv9D/= 4ha8/+ej2Ac60ObPw/vFfyHzwb8j/7uncV1xCeaGzWg3Xo297wDWlm1oLY5KXtE11NpqlKpK3O9= 7N5n3fghjx248TY0Irxerrx9zzz6UWAx7aBiRzyN9PpTKSuTgILYtEU5T4168AFF15jBiRVVJjs= dBqE5ww/Eupi1YxsyPfxzh9SPzeXz106hccyGpzi6qv/NtsGwCzS0oPg/9Hetxxeo49OwutNM4Q= ksgnS1w8PgYE6k8humERQd9Ovu6xiiYFrHQBLuOjaBpgmzepHMghVtXKFg2nQNxymbEaGlp4cor= r2TTpk243W5qa2uxLIvjx4/jcrmorq5meHgYVVUpLy8nFotNmdYaGhpQFIWenh727NkzFTmnqiq= Dg4NomkZrayvRaBTbtjly5AhCiCnty8tFSpuhZJqx1DDzm1qR1TG6R8bpHh4nky/QOTxGPHmABz= b9iIJ57pFMrwWaqnPF4hu4dMHVuLSz+6goQiHsqULBRffYXnpGO8gW4iya/nZympsJ0tjS0dhI6= aRZcas6GgbPHLqTo8NbkQjm1JxPwH1qf51TkclZHO4boiIcIhjwohcKeL0uCqZBf+8ImYLBsZEc= P3pgA1etWcTs9lq27DrCsb5RegfHsKTB6ESart4RJibSSEtlcCTL4eP9TIwnMKWko7Of/uE4oGD= ZFoopyRk2x4dTaLrCwd5x2ltnsvfwGHuODaNIQazMQ3NDlGM9gxzoTzM2nnPGWQmqqpzTUCKEwK= P7uO2iT7Bu+XumotsM06Aq3MLBvn0gJYaAnV27uGLBMEFPGCEEE/ExvvndzwKgay5saROLVnLD1= bdSU13v+FzZNnsPbOP+h+/mI+//R2LRypft3zPZHz7+8Y+zZs0atmzZQkVFBWvXrmXatGkn9ZPJ= bT/zmc9w00038cwzz2DbNhdffPFU0MRZzy8Ebk1jPJej0RvCkpJ4LkPGKBDWPVxRNZOsZfLUSCf= mmM3V1S2M5rNkTIOw7mZF+TQOp8bpy8TpTo0xJ1DOZG1BRQh6c0nKXF4URSHi9pK2jCnBUVccEU= MRAqOYxiFp5fnF8b3UeIPMDVfy/Hg/w7k0MY/P2bY43/VnEuRNg4xpsDI2jWpv8HWJZD1nIck0n= JombbNnc9cPfsBXvvxlPvWpT+F2u4tp3FM89fun2L5zO29+21tIJBLEKv5fe28eJ9dZ3vl+3/es= tXf1vqm71WpJrdXaLHmRjREyNl4wIOOwJmQYk2EguTcsYfmQuQxzySXheiaQST6BXEjImCFgY8c= xcZAB77YsZHmTZO1Sq7vV6rW6u/Y623v/qO62GstS29gszvl+Pq1uVZ2qeuutU+f8zvM+z++pR+= o6Q8NnQMCyFctJJuNkxsYB6O5ZwtjoOHue3Us0GmX9xvUEnsvk2AS2adOzrIdDRw/h+z7pdJq6u= lpyU9N4rl9dEpuRDedGoJAzgeoqlq3zn/5wObV1MWIxbd62oCNmp0MJUNX7hai+giZ9YpEUQgYo= 4c9VZCgFGhJNy848ZtaILYJh6Fy8pWHmg501/QM7AQ/+ZJxDB8tccikLirgooUBWT9ygoVAEyn8= x5B8EBL6P53uIOSNAhW07GJqHkjpHz7SglEYiWqZQ0GirneLg6Q4qFY3aWBlfSqYLEZpT05zJxc= lJk3w5Rtm38HydjroxTmdqUH61WmtwPIWSGsWKSUMix7EzDZiaJBb3yZYi1CWyC4wmKSr79hP81= d/i7d6DvmwJge9BsYy5/Sr8Fw5TuPXjGFs2YX3uU+iL2nCe3I3W3UUwOIi14+24uQLekz/HfOcN= symm1X1DSrRkAmGa+GNjoFR1Gc620RZ3IeIxRDJZrZgMAoQdQUVsJKr6AQcB2BcO8UajUXzPoe9= kH/FUDWNnTlHZcjkNl1wy98WenYpoW9tcFC7a3k45l0EfrUFLtPD83r/jqmtuOPfBQFXNWzcvb2= LdkoY5zyLfr372dSmbWMSio6kGx/NRM8IGQNcEyaiJYZpcddVVc2KoXC7P7UOaps3rWeR5HolEA= ikl2WwWy7KwbXvudd/61rcSiUTI5/Mkk0mmpqaIRqPouo6uV20+Nm/ejOu6RKPROd+lhWJoBul4= HSfPPI6pTbOyvZ2aeC3LWxvxg4CB8Sk8P2Bt10YWNy9BqRnPNSFhpipsdqIVCinE3Ldzbkrnqsc= kzPxWVKOtKngxWXn2eCOlnFl2mn3uF2N+QkpS0TS6trClF6UCImacizvfgeuVyBSGGCucJAhcJD= N2JDPGitXtq0ezipsnVx4jYqZoTi3h8u73VpeMCBALcE3KTBf5xnfvxxQGKgAhFfmiiwoC/ve9j= +MLhaFr7H2+n8MnhvBcKLkO37njIbxAYFsmh/vG6P/uTym7HrGoyTMH+zl6fJBcsXoR+e3vP4Lj= uPgKoraGW5KkI+bMUrTkkSdewAsUlbJLfcLEccF3Pe7duZeSFyAR1EQ1hNAgEJRcf55D9/kQQmD= qJg3JFy9sHM9hccNqDvQfn5vPM5kphjJDdNQtRtd0XNclHovzO+/6COmaelzX4aHH7uNfd36f3/= /AH1etMEoFHn7sPuyZqre3vOlGpHx1fl2RSIQrr7ySK6+8ct7Yz4Wu66xdu5a1a9decNuzUTO5Q= 012nGY7zt6pM2ypbSNqWuhadSlOCkHOrXB981IeGe8n61aIGwa6Jqm3Y1QCj12ZAa5uWMyIU8RT= AU7gUwl8/CCg1U6wOzPI8ngtlmYACsevCiI38HACnzozQsX3GSxlabXjxEyLRdEUu6eGiGkGi+M= 15HyXQAU4gUfeq9AUSXDGKZI0bWK6ifWbnpOUnc7yD9/6B5b0LGHjlk18+c++zNuufRu9vb24rs= vevXt56JGHufyKrfzw+3cyMjyCbduka9J4nke5XAbBXHKaEIJYNIrUdJQKSCSSjI+N4bgOUK1Yq= K+rw3EdfM+j4jg4jgMKent7ed/vvO+845XCJxLxiUb1udJVXddYc1FDdflt7hunsKMQTzoIXDQN= UkmBYXggFIIA26jwtuvjfP4LnejGS63up7M+5c8exJ+x+pcyIJkIMM2qeebssl71PkU6rROL+Hg= L8PCoVvsoerqzSDmGJhTNTRXi8SIVYxzwicX6yZbvIV+x8fwM0poGwNRdrljzAkL4eJ5JIlrE8T= WkqMrHRKTEliWHMbQAKQPKjomhu0TMCm21Y0ihMI2AQsXE1D1iVoW4XcAyfHJFm55mn7JnYBkOE= cOhtWYCIcHzdFLR/IL2q1mCqSkqDzyMGBsj+oXPgGWBlAQjI+jdXRiXbkZuuAgchyCfR6bTuD97= GH9kHO+uewmGzhD0a9Wo0FnXnEIplOejVICMRFGOg//s8yg/qOYiWSYISTA2jmhrRmtoQF/UPk/= cXeiLKYQgkUxS29DA3t27ePu73kVuOsPeR37KFdfeRDxVM7/8f/YPpXCdEpmhI0QaO3liz14yY+= OsXb/xZV5JUc5lOL53J0EQkEomufTSyxgfH+eRxx8hXVNDY2Mjb37zmxkZHeXf7vs30uk0pmUxM= jxM11vfiqDqg2SaJslkklQqRT6fRylFPB6fG2cul8M0zTnD1tmS97OvcqPR6pVfOp0GmOfHNMu5= blsorXWdfPz6zzEwfpKdT/8zO5/5Z67bdDPJaA3tdTUMT+WI2RZRO8ZEfhhLtxnOnqEp1UzRKVC= qlEhGU5SdEtOlSaJmDEu30HUTTWpIIcmXcmSLU3Q0dpPJjRGxYrieg+dXk1ZLlSLpWNWPreyW6G= rqYWhigFxpmnS8jqlCBtuMkIrWki9mScfqznPh9iKB8hgv7CNTPIIUJpd0X49SNpnC6TkBHagAp= QK8wCeYiU8DaEJjY8eNRM0kQhYZLT7JSCGgPraa2uhypDi/UFJCkUrX4pcVrlshVWMRS3lUKi6p= ZIzAV8SjFQxpUXIrWKZkcrpAU0sjXuASz+tIqSOkoN6wCQIfHx9DU9QIg8mJPHX1SQaHRgk8QTw= RI9pkUSlWiEcNFBrFiktmMouQHkuWLCY7OU3E1DF1yeHBDHXpJJatsK0orhPQPzS+sAuul0GXOk= 2pdvzAxJtxxy4oxVh2ck40AWi6TiQSIxZLoJRicddyjhzbPyOmAwYGT2DbMd585Y3ct/P7bNl0F= clEzasa06yz9qxJKzDjs+fNnK/mn57PJ4pmCwl+sdK0EvjoSAquw4Z0C04QMFCc5trmHp7PjpAu= TrMm1cSkU2aknKfFjrM4nsbWdJ6eifAsT9SzLF7Loew4zVaMnFdhslKiTrdxA58l8TRDpRxPjA/= QHknSFk0SERJfBWTdCklpYGsG1zb38OzUMMPFHPZMrtQaKdmTOU1rJIEb+GhC0mbFOZQdY3NtO8= OVAj+fGGRRNMXqmiZ4VUUKvxwLFkmVSoX+vlP0nTzJVW/Zxpq1q9n73NM8+sRjMwfYBBetX8fDD= z7IU3uewvd8urq6uHnHzQwPD2PbNo8++ijHjx0Hqh/mFVdcwerVqykWi5w+fZpcLsfg4CAAsViM= N115Jblcjng8zoEDB3jyySeBqt/Ehappli61ufXWWlavSs2tYVYFy+yONvtb0dZq8cefaMcyFJG= I5Ma3N9DS4pFMgu9L3v+7Ua65polYTMwYTM7fWTVN49YPL+LkiRFiMcGG9VEWdxnUpl+aOyWEYN= nSGH/86RZ6exfQpFJURdfqFcdZtfwUUP0/VHOOQCGlh1KHZuJhAVK6CAGG7tNa+zIJj6oaMGt7m= fuTkfJZfxfn/rYN9yW3zZKIlF9y24IQAvvSLWjvuJ7Sn/7f+AcOYr7zRuT6i6h86x/RVi4n8l8/= j6o4OHfcTZDLY7/lKsr/159hbFiH8eYrkZlJKvf8CO/AobkkUaUCgkoF7+gxQKL3Lp0plYpCoKo= RNykhCJD19WBaSNOkmqEkX9FBORKNsemSy3juqd089+xzbNy4npOH9vHzh+9n/WVvJlVbN89JOw= gC3EqJ6fFB7GQDx/uG2HnPPSxe3ktH1+KXmaZqcvVzzz7L+vXr8X2f2277f3n/+9/PP37nO3zqU= 5/ie9/7HsuXLyeRSPDQQw+xfft2OtJp7r33Xq6//no8z+PRRx8lEongeR5Llixh9+7dNDY2EgQB= LS0tQFUkJRIJzpw5Q1dXF6dOnWLZsmUsXbr0Nek5tRBidoKlrSuI23GePflz9vc/TW/7apa3rcY= 2DGxDpz4Rww88Dg0eIBlJ4fgOxXKe0akh4tEUU/kJNE3n2JmDlCoFljSvwDZtmtKtZAtTjOfGmM= iN0lbXyZnMAIZukS/n8INqOXy2MEVHw2KS0RqmCpM0p9sZGO/j4ODzXNS1ibHpEeLRJIZu8fypp= 2ipbV/Qe1NA2Z3i6Pg/4/pFEnYrG9s+SdJqRCHnBNJcJGkmquSpACk1FqXXkK0c4sDIdyk6o9hG= inRk6YJeWwQBuelpggqgGYyP5RFC4fsBpaKD6yhM00AGHoEG+byL57kMj0wgpcJ1FGW/hKFJTK2= MQENJH9d1kEInCBQT41k8N8D3A7K5Itl8EQLFdE6h6ybujMGvFmicOT2O77lkqS6r+WWP7HQJrQ= C65kHgE3iSX0YlCSGIGEk8z8Lxqs/j+xr58ottRmaTt58/sIdEPEWlUuaJn/+MizdegTbjMr//4= F5W9q6ju3MZiUQNR47tZ+O6yxcU1XFdt9o1IgjQNI2pqSlGRkbo6OiYK3Iol8s899xzdHR0zJnK= znp6zb4PKeU8U0khBGNjY0SjUerq5i+7RjSd7c3d1XOD1Nha34GrAiypsSxRR6DA0jQaInHcwMe= QGqbUiOsmHbEaAqWwNI32WApnpsrMDQJ0KemMp9GEQJeS7c3dlH0PXVQ7Z2y3Y2hC0BGrYW1NE8= bMczbb8apwExJb02mJJOiMpWeivApdSK5tWYqnAiKawdVNS3ACH00IzF+DQIJX0eA2l81x/7/9m= IP7D7Buw3oamxrxvYCB/n7uveceRkdHCWYSK2dLfh3HwTRNDh06NPc8Qgh838e2bVzXpbGxkb6+= vrn7pZSUSiVWrFiB7/tz0apqldv5EUKwZk09q1bVz0VzfmGLs7aVxOOSd7+7EwEYpsbqNUlWrEx= gGBKlTP7w/9iMZekva01vmoJLLkmyeXMCXZe8eVsbUgoM46UnEyEgnTb4/f/YO2NAeaH3Uv2R0g= XO994v3Dto/hP/UhdmrznCsjDWX4S7bi3lv78drXcZkf/2BQof+2MKv/ef0DoXEWSzqHwB+w/+A= 5gmfn8/0f/x59jXvRV/bBz/4GG8nz6I0d5KMDJG/s//OwQK//EnMN7yZrRlS5GmiVjRSzAxgT8w= iNJ0hO+DbaLGx/F9n0CTGIu7kNGFV1Lous6aDZvoWbmKxx/6KbYdYcPmLZx6YT9P/Phelq/fQPO= iLqxIFE3Kqi9RPgdGnP7+Af7xG39NNj/NR97zSSLR6MsedGOxGHV1dXR3d9PZ2ckdd9yB53m+n9= YiAAAgAElEQVQopdi5cye6rpNMJqmpqSGRSNDU1ERbWxuRSGTObK5QKHD8+HE6Ozu599576enpY= deuXdTW1pLJZNi7dy+XX3454zPz8fDDD9PR0UF/fz89PT2vxce9MGYuahprWrh2/U383U/+kv/v= J1/j49d9lsaaHhpTSWqiEQLl0tGwmIgRZXT6DKlYLXE7gSKgJlZHrjTN2q5NVJwy6UQdumagSUl= L7SLikRRxO46Ugpp4HTWxOoLAp+yWMHSLslMkZieqy7QqwNTNOdFUG68jYkWxjAiWbrG++xKMBS= 61aUKjMb6epsRGBiYfYbp4irH80zRGt+JQFUP+TKTB9180lawusWsEgctIfi+FyghSShbXXkNtt= BexgIRxAEO3iMYluYKLUDrJVBzXqTA5mcO2TGpqEuSLBYSCRKwGP/Cq0QoBkZjO1OlxEnU1uCWX= RNLC9xxitsXEZIFEIo7UfNJmAoROoegQjZg4joMIXPKFCkiNdCpK1LZw3AqJVHSmAEUnEo3guR6= BopqfFyj8XGk2QfNVoVAUKi4VV8edOVRWl6rnz1ehkOP4iYMEKuDpZ5/glnf9Ry7d/BZAkJkco+= /UEVb1bsDzXDasvZSdP7uLlb3riUXjFxzD7t27aW5u5oEHHmDbtm288MIL+L7P3r176evr46qrr= uKFF15gdHSUyy67jJ/85Cfouk5PTw/PPPPM3EXWokWL2Lp1KydOnGDv3r0UCgWWLFlCb2/vS0SS= EILI2fukAH3GU8s+63ZNME+ECCGwNX3e/cbM/cY5xIomBDH9xYt+XTt7Xl/c3tJ0LG2+7IieozJ= wNqNPzoiwXycLEklCCFpbW7nmmmsoFApzt7llhzMDQ1UFKDU2bdw0L8JjGAZHjx6lUqlQKBTYtm= 3b3P1CCEzTpL+/nyAIsG2b3t7euYPwbDnx0aNHcRwHpRTXXnstSqm59gjnwzAWrjqFAMt6cXtdl= 7wY6RREIhf+kHT9xW0s6/zTKgTY9vm3MbQ4qxs+Tlfqxgu+9m866cjqlxdkmoZ17Xa0JYuRDfVE= Pv8pnH+6E1wPY9lSEv/7H3D/9ce4Tz2NXl+Hef01GOsvwnl8F9bvvAvj8kvAtpGNjVgf+B385/c= jVq3E2P4m1EQGmUwQ+cwnMK9+CzIRr06+JsEPUJNToBvguviex2zemAJUWxu8ApEkhKAmneY9v/= thvjYwyH1338HJvmO8Y8d70JTHoeee5vk9u0gkEiTTtaRq69GtGE/v+Tk/uusO8tMZbnrv77Fuw= 8XnvSqd9UpSSjE0NISUkmQyiWVZ3HTTTdx5550cOHAA0zTnLijOvlLWdZ1ly5bR3NxMQ0MDLS0t= nDx5kiuuuILJyUlqa2vZsWMHpVKJhoaGuYTsffv20dvbu+D5eLXMup+dnaWrSZ3FTcv44FV/wJ1= P/C8qrsN0sczixvTMwdhiVUfVibi7eemLZZbzmKmyEGflEFVrQ1FqDUII2us6ZwokXnoynn2UQJ= CO1764p8wrQ5xtU7SQyw+BpSdZ23wrrYlLyDmn5krzA+XjKx8vqP52A49ABQQqwFcKX1WjXAlrE= atbfpeU3UV9bA26tBe01IfSqQQKw/fw/QBNN3H8AF3XsKMGsWiEQqkIQlH2fEoVBxlUrQqQAa6v= 0AwNVwUYtoGimpQbCCj5CksJolLDc1wMQ0NT1ZS/qF3taGArnXzFxzAiBKKE6wmCQOD6iorrYRo= gNIFSGo6vkMJEyJdGrl8RCiQGrmfgzkSSNE0ihMnc/iAErS2LuPG695FO1XHR6i08vvsnXLp5G7= 7v89Qzj7Lv4F5OD51C13V836f/9AmOHj/AujVbLjiE7u5u7r77bjKZDA888AA1NTUYhkEymWTz5= s0cOXKEG264gccff5zDhw9z+eWXMzAwwJEjR+jt7SWbzdLe3s6+ffsYGRnhwQcf5H3vex8PP/ww= Q0NDdHR0/HJzFHJORCaTUVAVJdFo9GVbDFxoeevXxRuhb1PIGwff93n26af4n3/+3xg53Y9pR1m= z7mI2b72S9o6OqhFcdoqD+57niQcfZHhoEMuy2Pa2G/nQH/xn4udoITJLEATs2bOHT3/601QqFR= KJBB//+MeZnJzk61//Otdccw25XI58Ps/Y2BhKKb7yla9w++23s3v3bj73uc9x9dVXo2naPF+dc= 3nsnP19HxsbY8+ePVx88cU0Nr7yap5XNH+BR6FcwDYjGJoxb4xBEFCo5LCNCFLqMw2xf7u//7OC= TCmf4ewz2FoLRV9xulIkkxmn3kqRyU3R29ZNf3YYEY3QrAvSVgRNBiTsNqSoHrMXMhenR6b4r39= 9L31DZ1BBtcKOQAABwdkFBmLW10jMRJ2ryetC+dWkdiEAq5r/JwD8qsgLqheLQs50sWfWaPSsPE= EhCJBUy1x8quKSqpskgJTVHEIlq+XFgGHo/N6OK3j7tvWYr+ACeG6eleLg6T7+8zf/nLHpKQDqE= im+8sGPsWXpKjSpMTxymu/98G/53ff8IbXpBhynwt/+/VfYsPZSVq3YwN9956vcdN0H6OlewWxF= wHP7fs7uvQ/zHz7wxzMGlC9PqVTii1/8Ijt27OCf/umf2LFjB/v27aNYLLJu3TrGxsawLItnnnm= G1atXU6lUGB8fp6enh/r6enK5HC0tLTz99NM0NTVx6tQp2tra2LVrF0uWLGHLli2sXLnyFc9NyI= t4XrVA7ewClgWLpJCQkIXh+z4njh7hu9/+Ow49/zTFXA7P92Emny1QAUIpbMumvrmNa258J1ffc= COJZOqCUaTZpWdgzsPI9/25XmyzlViO46Dr+lzLkdko0tlJoq+EsyPArzezpoPneq1f5TheT5RS= VFyHUqVcLZXWdYruKSytjrJSTLgO+WyWlBljupinrbaWofwQwrKp1zVqrBo0qYhY9XhBGUNGkeL= CCwOu6zMxlafizl+eP1fs7cKc/Rmc79EXevaXv//FIJ0glYiQjNmv+rP3A58H9j3DD3c9jO8HvG= 3jFt560SbikWoBwkRmjJ0/u5Prr3nPXDL24FAf9/zr7Wy/6h0cPPwMV29755y7tlKKQjHP7T/4a= 25++4eor2s+7+srpchms0SjUfL5PLZtUygUyOfzBEFAY2MjExMTc0UV+Xx+7rx8dh6g53m4rott= 24yPj6PrOrFYbK76NOTVE4qkkJBfEVVbjByHD+zj548/yvHDh8hOTxGoAN0waWhqZv3FW9i45TJ= a2xfNVZFdiF82ovvbLi7eKPi+z5MvPMNdj+1kdecyahIpNi1fjW1a1VykmRyoWVNKzZjg0Pjt1E= VXo6iwKLUNQ4sQKJ/DE7fTlbqBhNWGocXDz/g8BEFAyXUIAkXENOdFI33fp+KUsSwbbSbvJggCC= oUcplWt4rOt+e0/lFKUykVMw1yw63bIby7nEkmvOHE7JCTkwlRzhVJsuuQyLtp4MflcjlKxSBAE= GIZBIpnCjkTmrhBfiWNvyG8/QghMw2Q4M8aKRUtoqa3nb+65nfU9qxieHCNbzGObFlHTpuRUuP7= STRQqwzTGLiLvTHIscxcxowkpDAqVMwzn9jBVPkZn+mp08Ro03n2DIqUkZp072qJpGtFI7CXbJx= Ivb2MhhHjJY0LeWIQiKSTkdUQIiWla1NZZsHBT5JA3OArmrlbT8SSZ7DRDmVE6sq2MTk2glGJL7= zqePrKf6WKO8WwGqUtqo8tpS13G0cydFL1RdBFFCImt11J0h+YMZkMxHRLy2hCKpJCQkJDXmdlS= /tm8sSAIMHWd7esvxw8CIpbFWzdcQcyKUBNLokvJsvYubNMiW8zR2dxIwd+OIZNYWh1N0c2UvAk= 0YZMwloD0aU++BYkxrwJSvgGS20NCfp2EOUkhISEhrzO+71MuVwiCqlCaEzGadlb1WIDnVT2RCN= Sce7JpmXieRxB4My1PBH5QbTsTzOSo2ZZVbUHhenM2BL4fEItFX+LCHBIScm7CnKSQkJCQXwOap= hF9Bb5bAEGgcJwAKQQR28Tzqo1uDUO+rAmtFaYjhYS8poQiKSQk5GXxg2prCV3X5tr7hLw6Xsmy= l+cpTp8uMThYxvFcVixPMjRUoVzxWbY0Rm2t/bIdAEJCQl47QpEUEvIqmPUiklK+ZkvUQaAouz6= +X+1Cny95jE6Xaa+Pko4vzCLgl8VT1Z5anuuRL1YAxSNPH2Pbxcs4NjDG8s4mEr+EV82vlCBAlb= OoUhZ1VhPTcyGsGCJay8uGaF4NM66Mr2SuymWfTMah4vic6ity0UU1jIwUOXo0z/r1aQZPlznVn= 0cpgWlKYjF9ntt/SEjIa0sokkJCXgWO4/Cd73yHpqYmbrzxxl+66avvBxw/k+fQYBbXUwxPFhme= LGPqGjsuX0QqaqBpr68wKfsBO0dyHMtXuKk2QnZimoamNHUdzRS9gN37T1GXinNyaILFrXVzYkk= pRbnikS9VAIhHLXRNznjQzI+geH5AoeTgBwFCCBIRE10/d87ML1ulFRQnqTz4N7j9z0PgozQTEU= miilMIAtAshJQo30EkmzDe+ilkvOGCTQ1fifGiEBLdMBAL2D+UUhw7lsfzFMVyhbo6C8uSFAoBa= 9bUzHXU0TWDqSmXzKTD8mVxUqlfjYAOCfn3SCiSQv5dcS7H5pdzcT7ftpVKhR/96Ed0dXVxww03= zDN5XOgJq9pqoyoEvEBxfChLb3uCvcemcFy4cUsb1STdl0ZBgkARKDV3whaAlK8sajFvLEDO8/n= GiXGezeRZv2UxT6MzNpjlRL7CJ6IWN2/fACi+8Nf/wic+sJ0NKxYBivGpPD958jBd7fW4jkep4q= FJxUXL2nHcgKa6OIZebYVSdlzuffQAsahN1DJYt6yFxvRLDRDLjsvwWJaOlvSrFqCqlMXtexo/N= 4aoWwyJJoxNO3B+9leIaBL9ohsRhoV76CG8ww8hJs+AmZzr1D4r0maTOGfHMdtXcu51fkHMzXZt= F0JiGDqari+ombRSilLJZ9myOL5vk8m4ZLMuiYSO6yqOHMmzaFGE1tYImi44faZIseSSSp2/j2V= ISMirJxRJIW8ofN/n4MGDTE9Pz90mpaSlpQXDMDh8+DDxeJzly5eTSCSoVCocP36cM2fO0N3dTW= dnJ1JKMpkMR44cAWDlypWkUilc16W/v5/+/v65x/q+T6FQ4PDhw5RKJZYtWzbXGPZ8KAVDE0W+/= 3A/V6xp4KLFaepTFj95ZoRUzMT1PCayFa5a24ShS+RZXbVLjsej+8d46kgGf6bflWVINvSkuaS3= npj9yluP5DyfnSN51tREWFcT5TuDWdYmDDqjBh0xG8M0EBKGx7J86aM3UCi7HO0fo6MlzU92H2Z= Rc5oNy9oAmJguMDKRY2Qix31PHOLmt6yl4nhMF8q01icpVxza6hN0tNRiaJI9B/qRElZ2tzA4Ms= XwRJZU3OafH9zHH+y4nJHJHKWyS0dzmslciXLFJZ2I0N1ef4F3FVSX2RLNmFfeinPsSfA90E30i= 38HihmcvXehsmdAKUZHRti95xhXvelKnnhiF6VSiWQyybPPPY9hGKxbdxH9/f1s3Xo5P/7xToJA= 0dBQz4EDL9A505cvk8lwzTVX88Mf3k00Fuf9738PHZ1dF5z/IFCcOFkkXyiRyZik0waFgk+xGOC= 6PsePO7S1GQwPlzh9uoTnKQxdMj0VkK7xsW0tjCaFhLwOhCIp5A3F5OQkt9xyC4ODgwAzZdEura= 2teJ7H1NQUmqaxfft2/st/+S/84Ac/4Bvf+AaVSgXbtvnc5z7Hli1b+MxnPsNzzz2H7/usWrWKb= 33rW+zatYsvfelLZLNZpJR4nkdHRwcf/OAHefDBBxFC0N3dzV/+5V+ydevWCwglxchkhYf2jRCx= NHoXJTk1VqLieGy7rJ0fPDqIF4AUAk1We7srVX0/+aLHvbsG2Nc3xdK2FKYu6RvJ8W97BvnoDct= 4x2WLMDTJ2R1MfnHZ6xcZKDh8+YUzNEcMPrO8iSlfkZRQQaIQ/HC8SJetc0NtAuUFfP5//gv1qS= h/+pHrOHpqmI29i7DMqjizLYNHnj7Kht4OlAoYnchy/5OH2L6ll3sefI4AeOqFPo4NjPG2rSvRd= Z3v3b+Xay8pk82XWN3TRr5YRqmAvqEJdu07ydVbernzp8/g+Yq2pjSXrFpYx3NhJdC7L6HyyN+h= d6xDS9Sita1Gq+3A6duLyo+jchMoqVGulBkdHcVxXEZHx8jn8ziuy+joKJdddhl9J/s4dOgw0Ui= U+rp6mpqaWLSonb6+U3Qt7mLv3qdJp9McPXqMicwkjusxmZlckEjq6yuQmajQ25vi5IkStq0xMF= Amk3HQNEFHR4TxcZemJoPOzii2XRXNmYzLY49N8KY31WMY2muaUhUSEhKKpJA3GHV1dezcuZNsN= ovneTz11FN8/vOfZ2BggFtuuYU//dM/ZWBggC9+8Yt8+MMfZnp6mi9/+cts27aNO+64g69+9auk= 02mampq47777kFLyyU9+kltuuQXHcbj11lu5+eabeeihh/jSl77Erl27APj+979PY2Mjt912G7f= ddhurV6+mru7lLbbV7L8zDdKzRY9CJeDaTS38/PAYcUtSqXjc/cQAhi657uJWHNfnfz3Qx6rOFH= 4Q0FYf4QvvXUVzbYTDg9P8n3+7l76RIsWyz9BEjgefG2E8W2Zpa5Jt65tpTJ27IkoBjbbBHy5ro= tXWeXSyzNsbY9SbGh1RE10Krqy1OTZVIlsoMTQyxf/zhzcxMV0gFrFY3tXC3oODtDSkMHUNz/Mx= dA3D0EjEIggpyJdcbMvgnW9Zz/27DtK7uJN1y9vZve8kp0ez2IbBZK6MUoqm2jgRSycVj+L5AY3= pBImohe/72JZJb2cji5rTC9ofVOARDB+B7Ch6z+UgNIzVb0VYMWRjD15mEDcziusJfF9RqVR49t= lnKRQKZ4lKgVI+g6dP4/kewyPDNDc34/keyVSSSCRCMpGYazisFJSKRSIRm/qGhgWNU0pBU5NNb= dpmKh2wa9cUx4/lWdxS5pINNpYo4AuNwXGDQU0Qi+mk0waWrVEuu/MEcUhIyGtHWBYR8oZCCEF7= ezsrVqwgEolw9913E4vFaG1t5aMf/Sitra2sXbuWa665hv3797N8+XLe8Y530N3dzYc+9CEaGxs= 5c+YMH/vYx9iyZQtbtmzhE5/4BEePHiWdTvPe976XFStW8O53v5uVK1dy8OBB3vWud7F9+3bWr1= /PrbfeyunTp8lkMgsZ7dxfqajBm9c0YOoa7fUxdu4d4uRInv7RAnc/3s/YdJmnjmS498lBTk8UQ= UGu6LL70DgPPTvCv+05g21orFiUZGiiyJf/aT8nh/N0NSe458kB/sddB5kqOOccha8Uj4zl+H7/= BEGgWJmM0GBptEQMDK3q2Fxv6ayI6cQsg1NnJnjuyCCf+9pdHDk1ytsuX0kiZnHPQ8/z4FPHGBy= dprEuRSxqk45bxGyTS9Z00Xdmkul8iUQsihcIDE2SjEeQUrB8cRPd7fU4rs/DTx+f6Yll0lyfJB= mLcHRggm2be2ltTFN0/HO+j3MS+FDOIeJ1yLpFVPbehT96nMqJp8je9zUKBx7HcbyZajGT2nQtA= 4On0Q2Tjs4OGhsbWb58KZs3b6Zj0SIuu/RSmpqaOH16iEOHDiOFoKmxgcbGRhrq65mammJx92I2= bFjPyhW9ZCYyVXPIC9DWFmF8vMKTT07iOIqaGo1kLMA8+jCn7rmL49/8Jof//ttM734Qz/FIpQz= yeZ/BgRLti0xM8+W9k0JCQl49YSQp5A3J1NQU3/72t5mYmOCzn/0sX/3qV/mbv/kbampq5vKWhB= DEYrG5En7TNOf+H4vF5pbLampq0DQN27ax7WpzTMuyiESq5oCpVApNq+aERKNRgHmJvQtB1wSLG= qqPHZ8uE7F0TENj/ZI0Txwc49BAlideGCcVNVjdmWLXC2NM5R3uenwAXROcyZRoqLHpaIzy5KFx= JrJlNi+rwzYkS1qSnBzOkck51CZe6jYoESxN2Gypi9MVMxFSktQ1CoUyRtRG1yVBoMgWylQqLot= b6xDAhpVdNKTjJKI21162gqmyi6UJDE1jaXczCkH3onqkFHR1NKL8ACUl7a11aFKgpGRVTys9Xc= 0EQiCFYFlXI06giOgaH7hhM1IKmhtrCAKFkpKlXU3oQizcI8h3CUaPom/YgQoU5dEB4muuw3nuf= vxKmWqJfjWa1tTUxM1rtqLcEkJq4LsITWPrJZvQ3CLvefc7wS2hqCbaC9/BTkS56bqr0Q2Tm69/= C0pIzEicJQ0xtFgaPRrnguVyVH2RAJqbTcbHHcplj0LRh1gNRMBKp6G2Dl/GsSMa+bxHXZ2JbUv= GxgRBoF736seQkH+PhCIp5A2H53nce++93H///XzqU5+ipaVlXisIIQRLly6ls7OTiy++eE4k/e= oTX6vjcf2AUsXHD6BaQFUdhxTQ2RijOR3hZ88Oc2QwxyUr6mlIVYVaU02ET+5YQV3S4sdPDfHDx= /o5NJClVPGo2gIJlILulgTL2pPUJs5dBSUFdEVNWmyDo/kKjVGLBgn/eNcuLlvTSVdrLRXHY3gi= R7ZQ4vToFLueO05jbYJ41EIIgYvgQCWgRpdIPIqBoqIgqkn8mbWgekPiuQGTro8uJVL4BAocBJ7= vYaBosQ0yFQ+pBXhKEQQ+QmpoCEoqoMmUdEcW5kulFLiewnMVRtNyvMkzKM1CWFHcocMI5c/5Ig= kBhmmiWxrlo0+iNS+jsu9+tNo29KYeykceJ9L7JiqHH4X6bqymbpw9dyC2/h5yaD9aYw/s+T5aQ= ze0rSJ44SHMpZdipTcsaL8aHa3Q1hahocHC93OAIJ6MMMFGOtfHaajTKTuKiUxAJKJjmpJyuZqw= nct5eJ5CyrCxbUjIa00okkLeUCileP7557ntttu4/vrrufbaazl27BjRaJSPfOQjrF+/nkqlwn3= 33cftt9/O2NjYvD49syaR2Wx2riHpxMQEvu9TKpUolUoAlEolcrkcAOPj43Pb5nI5lFIL65clqr= 5BD+8f5dR4CU0ILFPjlq3tc5vUxAw2Lk3zvQf7UAqu3diCOeMrZJkarXVRWmojXLysljse6WO64= LChp46fPjPMUKZIc63NwYEpamImxnlMByUCTVR/1iZMHh/Lcd3WlRzrH6XvzCSpuEXF8fjx4/v5= 4A1buO+x/aTikepJWYAmYHnMxJ+xJUipqvhCvJh0bkkwBCQ0QTBzuxAChUIpDUGAJQUCDUNKPAV= SVJ2+/ZkVq6gUC15WUgpcF1SkDq1uEZXjezGalxKUcviZwV/YeDa5XSeI1aNZMVTTcgIzirAS+J= E0KpIiSLaAbqM8n6BlTXXfidahzAhB43JEvBYZq8M342DFEVIuqPy/rs5gcLBMsRgwPe3R3h5hc= tLF8ywOnYThSYnvV32X8keLxOM6haJHNCqxohUUcc6VPaGUwvcDfN/DNM1qNWapTDRio2sapXIZ= TdMwDeOcAsvzfXKFAqZhELV/S0xEQ0JeQ0KRFPKGYmpqij/6oz8C4NJLL+Xw4cOMjIwgpeS2227= jC1/4AqdPn+ZrX/safX19NDU1zVsak1LiOA5/8Rd/QSwWQ0rJV77yFdasWUM2m+Wb3/wmO3bs4I= EHHqCvr4/rr7+eO++8k7Vr19LU1MRf/dVf0dXVdd6kbag2NG2qiXDFmmaGJ0t4XoAL6JrENjVWd= KRoq4timxqXr2xk96Fx6lM2Pa0J/AB6F9WQLTjErGpFU1dznPU99aQTFqs6U3z8puX8y65BfrR7= kLa6GNdd3ErUfHnhFtMFH+5K8+h4kW/1TfIHnTVMOxFKp8f57r8+STIeYVV3MxtWdPKhL3ybN29= ewec/fC01iQgCMDVJ05yf0S/m4Mw/saZeEgia3b46vlrjF42v59s3Lrw9igAh0eraEZEkbt+z2G= u3454+jHJKII2ztqyuuUnTIrb8UgDMdGv1OaQgXb8IoRmY6ZaZBwjs1p5q6K+uan2Q2nxT9ZmEx= Ljy/QhNRwi5IBfvWMygu1ty8mSRzs4ohiHp6LAxTUk261GpVF3Ye3vjlMs+8bjO1LTLQ8cOsHPv= AT4f3UZ7fS2BUqTjcQDGJ6fIZLMcHhklWy5zw8b1FCsOX3vkCT52+WZaa2v5we69dLc0c1nPYpR= SnJnI0FiTwjQMiuUyx0bH+cvHnuTGnsXcsHEdhlb1u5ouFAComXmt6pS8ep+ukJDfVEQmk1FQPT= lEo9HXrMVCSMivg1OnTrFx40Zyudy8A3ZDQwPRaJT+/n5s2+baa6/FNE0Mw+C2224jmUwyPT3N7= //+79Pe3s6JEyd45JFHUEqxdetWvv71r/PUU0/xxS9+kYGBAerq6viTP/kT3ve+9/HpT3+au+++= G9d12bhxI1/96lfZtGnTeaNJSsF4tszxoSwNKRtDl9iGpFDxCAIolj0SUQOBIJ0wOZMpUXF9ahI= mEUNjuuCQiBqUHR+FoKnGZnS6jBQCKcD1AoJAIaXA0CV+oGhKR7CM84wJ2DVRYN90iXe31TDl+j= Cd57FnjnH5uiXEE1F+/txxPv5n32XH1Zv4s4/fhG395h4v3JETTHz3s5i9VxDZeAOFJ+5A2HGUE= CjPQeXGkfFaZKKB8lP3UPPOz2J2rH1NT/QK5vLVLritUuzfn6W7O4bnKU6eLMyIJJeVK5OcOFHE= cQLSaZ3OzgiZjMsLp/v47y/sp115DA8PEzUNNN3AtC0KxRJnRkfJOS7CjrCqrYWVjQ0cmsgglKI= 9anNgMocmBTHTwBSCgydPsri1lUXpGo7li1y3bAlPjU+SzWYRlTJ2xKbsuIyPjVKTSBKLRCj5AZ= qhc+slm7h0RW8olEJ+a/E8j0KhMG91IRRJIW8ofN/nxIkTFIvFebfX1tYSj8fp6+sjEonQ2dlJo= VDA933q6+vnXJZHRkaIRCKYpklfXx8APT09mKZJEASMjY0xPDxMfX39XK6T64x7cvkAAAQeSURB= VLqcOnWKcrlMR0cHyWQSOH+Ok1KQyZU5NVrAcX1AoGtVT6Sy46NrgrLrY2iSltook7kKmbxDKmb= QUhthbKpCoeJiGRoVN2DFoiQHTk2haZJkxGAq7yBl9Tm9QFETM2hviJO4QD6PUtVarEfGC+wcK/= CxxbXsniyyrT7G83mXtTGdUrZIXSqGafxmGxj6xWkKj34XZ+wUaDp+YarquhB4CKlD4IGQICV6T= TOJqz+KFqt5Tfu3CaguuS1QJI2MlJme9gDB0FCZTZtSjI9XGBtzWLUqgecpDh3KYxgC25bsOv0c= e04PMgJEMuOcLJapZLOYsThN8Si6UpQVBLqBFrHZmk5yvFjmeGaKYi5La2Mjg9NZ/MkMqeZmorZ= NoVgm57kkE0muaKpjvFzmeLbI+MkTLO7uYmVzE0OTUwzliyQJOD6eQWkaX3z727hu3WsrMkNCfp= WEIikk5DcI3w/wA4UfVJvKyhnTSMfzZ3qiVU+ypiFxvAApq33SLEPi+7PNSMD1fWxTo1ypJiJLA= YEClEKcVQVmmzraAqvCvEDhqoBACaZcn3pTw5gZH/w6ktxfOUoBvovyHc5vJCRA0xH669Pe45XM= VRAoPC/A9xVHj+ZpbbUpFHzGxhza222UAl0XpNMmQkDZcZjK5zENg4pbbbisggCBqAp/pQiCYKb= vm0RKjSAI8IMAKcDxfTQpZ3aYmbEKwdDkJI8dO8nWZT201aSQUuB7PlIKEpEoZdfB8wMCFaAChZ= SSmkSciPXS6smQkN8WQpEUEhIS8luAUopi0aevr0hTk0UioTM8XMH3oa3NmvFFev2E6qyQ0maiY= L8Nojgk5JclFEkhISEhISEhIefgXCIpdNwOCQkJCQkJCTkHoUgKCQkJCQkJCTkHoUgKCQkJCQkJ= CTkHoUgKCQkJCQkJCTkHoUgKCQkJCQkJCTkHoUgKCQkJCQkJCTkHoUgKCQkJCQkJCTkHoUgKCQk= JCQkJCTkH+kI28oOAM2N5JqZLr/d4QkJCQkJCQkJec6SA9qYkNYnIgls0LkgkSSGoTUWIRcO+PC= EhISEhISG/fQggauuvqIf1gkSSEIKobRC1X+XIQkJCQkJCQkJ+ywhzkkJCQkJCQkJCzkEokkJCQ= kJCQkJCzkEokkJCQkJCQkJCzsGcSFJKoZT6dY4lJCQkJCQkJOTXwrk00LxIku/7oVAKCQkJCQkJ= +XeH53kEQTDvtnmRJNd1X7JBSEhISEhISMgbGd/38TzvJbe/JJJUKpXwff9XNrCQkJCQkJCQkF8= Xs9rnXCLpJT5JruuilMI0TTRNA6o+SSEhISEhISEhbxSUUvi+T6VSedng0DnNJD3Pw/M8hBChQA= oJCQkJCQl5Q3KhFKPzOm6HFW8hISEhISEhISEhISEhISEhIXP8/wWorT9uy+wdAAAAAElFTkSuQ= mCC" width=3D"585" height=3D"136" alt=3D"" style=3D"margin-top:49.4pt; marg= in-left:30.45pt; position:absolute" /> <div style=3D"clear:both"> &= #xa0; Renovaci=C3=B3n Cient=C3=ADfica </sp= an>&= #xa0; = P=C3=A1gina= 1 | 17&= #xa0;</div></div></body></html>