From 4277d6a2b5068a239ccf92443bd20e9c1df22756 Mon Sep 17 00:00:00 2001 From: Nikhila Ravi Date: Wed, 26 Aug 2020 22:27:07 -0700 Subject: [PATCH] Update latest version of site --- css/main.css | 2 +- css/prism.css | 2 +- docs/assets/architecture_overview.png | Bin 133103 -> 0 bytes docs/assets/architecture_renderer.jpg | Bin 0 -> 135287 bytes docs/assets/texturing.jpg | Bin 0 -> 57787 bytes docs/assets/transformations_overview.png | Bin 67258 -> 0 bytes docs/assets/transforms_overview.jpg | Bin 0 -> 180942 bytes docs/assets/world_camera_image.jpg | Bin 0 -> 100076 bytes docs/assets/world_camera_image.png | Bin 63883 -> 0 bytes docs/batching.html | 4 +- docs/batching/index.html | 4 +- docs/cameras.html | 115 + docs/cameras/index.html | 115 + docs/cubify.html | 69 + docs/cubify/index.html | 69 + docs/datasets.html | 73 + docs/datasets/index.html | 73 + docs/meshes_io.html | 4 +- docs/meshes_io/index.html | 4 +- docs/renderer.html | 39 +- docs/renderer/index.html | 39 +- docs/renderer_getting_started.html | 42 +- docs/renderer_getting_started/index.html | 42 +- docs/why_pytorch3d.html | 4 +- docs/why_pytorch3d/index.html | 4 +- en/help.html | 2 +- en/help/index.html | 2 +- en/index.html | 7 +- en/users.html | 2 +- en/users/index.html | 2 +- files/bundle_adjustment.ipynb | 217 +- files/bundle_adjustment.py | 46 +- ...zation_with_differentiable_rendering.ipynb | 628 +- ...imization_with_differentiable_rendering.py | 59 +- files/dataloaders_ShapeNetCore_R2N2.ipynb | 541 + files/dataloaders_ShapeNetCore_R2N2.py | 301 + files/deform_source_mesh_to_target_mesh.ipynb | 489 +- files/deform_source_mesh_to_target_mesh.py | 29 +- files/fit_textured_mesh.ipynb | 940 ++ files/fit_textured_mesh.py | 580 ++ files/render_textured_meshes.ipynb | 172 +- files/render_textured_meshes.py | 71 +- help.html | 2 +- help/index.html | 2 +- index.html | 7 +- js/codetabs.js | 12 +- js/scrollSpy.js | 6 +- sitemap.xml | 2 +- tutorials/bundle_adjustment.html | 8900 +---------------- tutorials/bundle_adjustment/index.html | 8900 +---------------- ...ization_with_differentiable_rendering.html | 2955 +----- .../index.html | 2955 +----- tutorials/dataloaders_ShapeNetCore_R2N2.html | 614 ++ .../dataloaders_ShapeNetCore_R2N2/index.html | 614 ++ .../deform_source_mesh_to_target_mesh.html | 8791 +--------------- .../index.html | 8791 +--------------- tutorials/fit_textured_mesh.html | 849 ++ tutorials/fit_textured_mesh/index.html | 849 ++ tutorials/index.html | 4 +- tutorials/render_textured_meshes.html | 2699 +---- tutorials/render_textured_meshes/index.html | 2699 +---- users.html | 2 +- users/index.html | 2 +- 63 files changed, 6646 insertions(+), 47801 deletions(-) delete mode 100644 docs/assets/architecture_overview.png create mode 100644 docs/assets/architecture_renderer.jpg create mode 100644 docs/assets/texturing.jpg delete mode 100644 docs/assets/transformations_overview.png create mode 100644 docs/assets/transforms_overview.jpg create mode 100644 docs/assets/world_camera_image.jpg delete mode 100644 docs/assets/world_camera_image.png create mode 100644 docs/cameras.html create mode 100644 docs/cameras/index.html create mode 100644 docs/cubify.html create mode 100644 docs/cubify/index.html create mode 100644 docs/datasets.html create mode 100644 docs/datasets/index.html create mode 100644 files/dataloaders_ShapeNetCore_R2N2.ipynb create mode 100644 files/dataloaders_ShapeNetCore_R2N2.py create mode 100644 files/fit_textured_mesh.ipynb create mode 100644 files/fit_textured_mesh.py create mode 100644 tutorials/dataloaders_ShapeNetCore_R2N2.html create mode 100644 tutorials/dataloaders_ShapeNetCore_R2N2/index.html create mode 100644 tutorials/fit_textured_mesh.html create mode 100644 tutorials/fit_textured_mesh/index.html diff --git a/css/main.css b/css/main.css index 3f2fe622..357fc4b7 100644 --- a/css/main.css +++ b/css/main.css @@ -1 +1 @@ -a,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,em,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,object,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{border:0;font:inherit;font-size:100%;margin:0;padding:0;vertical-align:baseline}body{color:#24292e;font-family:-apple-system,BlinkMacSystemFont,Segoe UI,Helvetica,Arial,sans-serif,Apple Color Emoji,Segoe UI Emoji,Segoe UI Symbol;font-size:16px;line-height:1.5;-ms-text-size-adjust:100%;-webkit-text-size-adjust:100%;word-wrap:break-word}*{box-sizing:border-box}b,strong{font-weight:600}em,i{font-style:italic}[type=checkbox]{box-sizing:border-box;padding:0}a,a:hover{color:#812ce5;text-decoration:none}a:active,a:hover{outline-width:0}a:not([href]){color:inherit;text-decoration:none}p{margin-bottom:1em;margin-top:0}h1,h2,h3,h4,h5,h6{color:inherit;font-weight:600;line-height:1.25;margin-bottom:16px;margin-top:1.5em}h1{font-size:32px}h2{font-size:24px}h3{font-size:20px}h4{font-size:16px}h5{font-size:14px}h6{font-size:13.6px}ol,ul{margin-bottom:1em;margin-top:0;padding-left:2em}ol ol,ul ol{list-style-type:lower-roman}ol ol,ol ul,ul ol,ul ul{margin-bottom:0;margin-top:0}ol ol ol,ol ul ol,ul ol ol,ul ul ol{list-style-type:lower-alpha}li{word-wrap:break-all}li>p{margin-top:1em}li+li{margin-top:.25em}img{border-style:none;box-sizing:content-box;max-width:100%}img[align=right]{padding-left:1.25em}img[align=left]{padding-right:1.25em}table{border-collapse:collapse;border-spacing:0;display:block;margin-bottom:16px;margin-top:0;overflow:auto;width:100%}table tr{background-color:transparent;border-top:1px solid #dfe2e5}table tr:nth-child(2n){background-color:#f6f8fa}table td,table th{border:1px solid #dfe2e5;padding:6px 13px}table th{background-color:inherit;font-weight:600}table td,table th{color:inherit}blockquote{color:#6a737d;font-size:16px;margin:0 0 16px;padding:0 1em}blockquote>:first-child{margin-top:0}blockquote>:last-child{margin-bottom:0}code{background-color:rgba(27,31,35,.05);border-radius:3px;color:inherit;font-family:SFMono-Regular,Menlo,Monaco,Consolas,Liberation Mono,Courier New,monospace;font-size:85%;margin:0;padding:3.2px 6.4px}pre{margin-bottom:16px}pre code{background-color:transparent;border:0;display:inline;font-size:85%;line-height:inherit;margin:0;max-width:auto;overflow:visible;padding:0;white-space:pre;word-break:normal;word-wrap:normal}kbd{background-color:#fafbfc;border:1px solid #d1d5da;border-bottom-color:#c6cbd1;border-radius:3px;box-shadow:inset 0 -1px 0 #c6cbd1;color:#444d56;display:inline-block;font-family:SFMono-Regular,Menlo,Monaco,Consolas,Liberation Mono,Courier New,monospace;font-size:68.75%;line-height:10px;padding:3px 5px;vertical-align:middle}hr{border:1px solid #dfe2e5;box-sizing:content-box;margin:1.5em 0;overflow:hidden;padding:0}hr:after,hr:before{content:"";display:table}hr:after{clear:both}body{background-color:#fff;min-height:100vh;text-rendering:optimizeLegibility}@media only screen and (min-width:736px){body{display:flex;flex-direction:column}}article:after,article:before{content:"";display:table}article:after{clear:both}article>:first-child{margin-top:0}article>:last-child{margin-bottom:0}article iframe,article p img{display:block;margin-left:auto;margin-right:auto;max-width:100%}.anchor{display:block;position:relative;top:-80px}.hash-link{line-height:1;margin-left:-20px;opacity:0;padding-right:4px;transition:opacity .3s}.hash-link:hover{opacity:1!important;transition:none}.hash-link .hash-link-icon{vertical-align:middle}.button{border:1px solid #812ce5;border-radius:3px;color:#812ce5;display:inline-block;font-size:14px;font-weight:400;line-height:1.2em;padding:10px;text-decoration:none!important;text-transform:uppercase;transition:background .3s,color .3s}.button:hover{background:#812ce5;color:#fff}h1:hover .hash-link,h2:hover .hash-link,h3:hover .hash-link,h4:hover .hash-link{opacity:.5;transition:none}blockquote{background-color:rgba(255,229,100,.3);border-left:8px solid #ffe564;padding:15px 30px 15px 15px}.wrapper{margin:0 auto;max-width:1100px;padding:0 20px}.wrapper blockquote>p:first-child{padding-top:0}.center{display:block}.center,.homeContainer{text-align:center}.homeContainer .homeWrapper{padding:2em 10px}.homeContainer .homeWrapper .wrapper{margin:0 auto;max-width:900px;padding:0 20px}.homeContainer .homeWrapper .projectLogo img{height:100px;margin-bottom:0}.homeContainer .homeWrapper #project_title{font-size:300%;letter-spacing:-.08em;line-height:1em;margin-bottom:80px}.homeContainer .homeWrapper #project_tagline{font-size:200%;letter-spacing:-.04em;line-height:1em}.projectLogo{display:none;pointer-events:none}.projectLogo img{height:100px;margin-bottom:0}.projectIntro{margin:40px 0}.projectTitle{color:#812ce5;font-size:250%;line-height:1em}.projectTitle>small{display:block;font-weight:400;font-size:50%;line-height:1em;margin:.7em 0 1.3em}@media only screen and (min-width:480px){.projectTitle{font-size:300%;margin:.3em 0}.projectLogo img{height:200px;margin-bottom:10px}.homeContainer .homeWrapper{padding-left:10px;padding-right:10px}}@media only screen and (min-width:736px){.homeContainer .homeWrapper{position:relative}.homeContainer .homeWrapper #inner{max-width:600px;padding-right:40px}}@media only screen and (min-width:1200px){.homeContainer .homeWrapper #inner{max-width:750px}.homeContainer .homeWrapper .projectLogo{align-items:center;bottom:0;display:flex;justify-content:flex-end;left:0;padding:2em 100px 4em;position:absolute;right:0;top:0}.homeContainer .homeWrapper .projectLogo img{height:100%;max-height:250px}}@media only screen and (min-width:1500px){.homeContainer .homeWrapper #inner{max-width:1100px;padding-bottom:40px;padding-top:40px}.wrapper{max-width:1400px}}.mainContainer{flex:1 1 0%;max-width:100%;padding:40px 0}.mainContainer .wrapper{text-align:left}.mainContainer .wrapper .allShareBlock{padding:10px 0}.mainContainer .wrapper .allShareBlock .pluginBlock{margin:12px 0;padding:0}.mainContainer .wrapper .post{position:relative}.mainContainer .wrapper .post.basicPost{margin-top:30px}.mainContainer .wrapper .post .postHeader{margin-bottom:16px}.mainContainer .wrapper .post .postHeaderTitle{margin-top:0;padding:0}.docsContainer .wrapper .post .postHeader:before,.docsContainer .wrapper .post .postHeaderTitle:before{content:"";display:block;height:90px;margin-top:-90px;visibility:hidden;pointer-events:none}.mainContainer .wrapper .post .postSocialPlugins{padding-top:1em}.mainContainer .wrapper .post .docPagination{background:#812ce5;bottom:0;left:0;position:absolute;right:0}.mainContainer .wrapper .post .docPagination .pager{display:inline-block;width:50%}.mainContainer .wrapper .post .docPagination .pagingNext{float:right;text-align:right}.mainContainer .wrapper .post .docPagination a{border:none;color:#fff;display:block;padding:4px 12px}.mainContainer .wrapper .post .docPagination a:hover{background-color:#f9f9f9;color:#393939}.mainContainer .wrapper .post .docPagination a .pagerLabel{display:inline}.mainContainer .wrapper .post .docPagination a .pagerTitle{display:none}@media only screen and (min-width:480px){.mainContainer .wrapper .post .docPagination a .pagerLabel{display:none}.mainContainer .wrapper .post .docPagination a .pagerTitle{display:inline}}@media only screen and (min-width:1024px){.mainContainer .wrapper .post{display:block}.mainContainer .wrapper .posts .post{width:100%}}@media only screen and (max-width:1023px){.docsContainer .wrapper .post .postHeader:before,.docsContainer .wrapper .post .postHeaderTitle:before{content:"";display:block;height:200px;margin-top:-200px;visibility:hidden;pointer-events:none}}.fixedHeaderContainer{background:#812ce5;color:#fff;min-height:50px;padding:8px 0;position:fixed;width:100%;z-index:9999;transform:translateZ(0)}@media only screen and (min-width:1024px){.fixedHeaderContainer{flex-shrink:0}}.fixedHeaderContainer a{align-items:center;border:0;color:#fff;display:flex;flex-flow:row nowrap;height:34px;z-index:10000}.fixedHeaderContainer header{display:flex;flex-flow:row nowrap;position:relative;text-align:left}.fixedHeaderContainer header img{height:100%;margin-right:10px}.fixedHeaderContainer header .headerTitle{font-size:1.25em;margin:0}.fixedHeaderContainer header .headerTitleWithLogo{font-size:1.25em;line-height:18px;margin:0;position:relative;z-index:9999}.fixedHeaderContainer header h3{color:#fff;font-size:16px;margin:0 0 0 10px;text-decoration:underline}@media (max-width:480px){.headerTitle{font-size:17px}.headerTitleWithLogo{display:none!important}}.promoSection{display:flex;flex-flow:column wrap;font-size:125%;line-height:1.6em;position:relative;z-index:99}.promoSection .promoRow{padding:10px 0}.promoSection .promoRow .pluginWrapper{display:block}.promoSection .promoRow .pluginWrapper.ghStarWrapper,.promoSection .promoRow .pluginWrapper.ghWatchWrapper{height:28px}.promoSection .promoRow .pluginRowBlock{display:flex;flex-wrap:wrap;justify-content:center;margin:0 -2px}.promoSection .promoRow .pluginRowBlock .pluginWrapper{padding:0 2px}.promoSection .promoRow .pluginRowBlock iframe{margin-left:2px;margin-top:5px}input[type=search]{-moz-appearance:none;-webkit-appearance:none}.navSearchWrapper{align-items:center;align-self:center;display:flex;justify-content:center;padding-left:10px;position:absolute;right:10px;top:10px}.navSearchWrapper:before{border:3px solid #e5e5e5;border-radius:50%;content:" ";display:block;height:6px;left:15px;position:absolute;top:50%;transform:translateY(-58%);width:6px;z-index:1}.navSearchWrapper:after{background:#e5e5e5;content:" ";height:7px;left:24px;position:absolute;top:55%;transform:rotate(-45deg);width:3px;z-index:1}.navSearchWrapper .aa-dropdown-menu{background:#f9f9f9;border:3px solid rgba(57,57,57,.25);color:#393939;font-size:14px;left:auto!important;line-height:1.2em;right:0!important}.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--category-header{background:#812ce5;color:#fff;font-size:14px;font-weight:400}.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--category-header .algolia-docsearch-suggestion--highlight{background-color:#812ce5;color:#fff}.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--subcategory-column .algolia-docsearch-suggestion--highlight,.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--title .algolia-docsearch-suggestion--highlight{color:#812ce5}.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--subcategory-column,.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion__secondary{border-color:rgba(57,57,57,.3)}input#search_input_react{background-color:rgba(0,0,0,.2);border:none;border-radius:20px;color:#fff;font-size:14px;font-weight:300;line-height:20px;outline:none;padding-left:25px;position:relative;transition:width .5s ease;width:170px}.navSearchWrapper:before{left:24px}.navSearchWrapper:after{left:35px}input#search_input_react:active,input#search_input_react:focus{color:#fff;width:220px}.navigationSlider .slidingNav .navSearchWrapper .algolia-docsearch-footer a{height:auto}@media only screen and (max-width:735px){.navSearchWrapper{width:40%}}input::-webkit-input-placeholder{color:#e5e5e5}input::-moz-placeholder{color:#e5e5e5}input:-ms-input-placeholder{color:#e5e5e5}input::-ms-input-placeholder{color:#e5e5e5}input::placeholder{color:#e5e5e5}.hljs{padding:1.25rem 1.5rem}.gridBlock{padding:0}.gridBlock>*{box-sizing:border-box}.gridBlock .fourByGridBlock img,.gridBlock .threeByGridBlock img,.gridBlock .twoByGridBlock img{max-width:100%}.gridBlock .gridClear{clear:both}@media only screen and (max-width:735px){.gridBlock .fourByGridBlock{flex:1 0 26%}}@media only screen and (min-width:736px){.gridBlock{display:flex;flex-direction:row;flex-wrap:wrap}.gridBlock>*{margin:0 12px}.gridBlock>:first-child{margin-left:0}.gridBlock>:last-child{margin-right:0}.gridBlock .twoByGridBlock{flex:1 0 40%}.gridBlock .threeByGridBlock{flex:1 0 26%}.gridBlock .fourByGridBlock{flex:1 0 20%}h2+.gridBlock{padding-top:20px}}@media only screen and (min-width:1400px){.gridBlock{display:flex;flex-direction:row;flex-wrap:wrap}}.alignCenter{text-align:center}.alignRight{text-align:right}.imageAlignSide{display:flex;flex-flow:row wrap}.blockImage{max-width:730px}.imageAlignSide .blockImage{flex:0 1 500px;max-width:500px}@media only screen and (max-width:735px){.imageAlignSide .blockImage{display:none}}.imageAlignSide .blockContent{flex:1 1}.imageAlignBottom .blockImage{margin:0 auto 20px;max-width:730px}.imageAlignBottom.alignCenter .blockImage{margin-left:auto;margin-right:auto}.imageAlignTop .blockImage{max-width:80px}.imageAlignTop.alignCenter .blockImage{margin-left:auto;margin-right:auto}.imageAlignRight .blockImage{margin-left:40px}.imageAlignLeft .blockImage{margin-right:40px}.container .gridBlock .blockContent p{padding:0}.container .wrapper .alignCenter h2{text-align:center}.container .wrapper .imageAlignSide h2{text-align:left}.container .wrapper .imageAlignSide p{margin:0 0 40px;max-width:560px}.highlightBackground{background:rgba(153,66,79,.7);color:#fff}.highlightBackground a{font-weight:800}.container.highlightBackground .wrapper h1,.container.highlightBackground .wrapper h2,.container.highlightBackground .wrapper h3,.container.highlightBackground .wrapper h4,.container.highlightBackground .wrapper h5,.highlightBackground a{border-color:#fff;color:#fff}.lightBackground{background:#f7f7f7}.darkBackground{background:grey;color:#fff}.darkBackground a,.darkBackground code{color:#d6b3b8}.container.darkBackground .wrapper h1,.container.darkBackground .wrapper h2,.container.darkBackground .wrapper h3,.container.darkBackground .wrapper h4,.container.darkBackground .wrapper h5{border-color:#fff;color:#fff}.container.paddingAll{padding:40px}.container.paddingBottom{padding-bottom:80px}.container.paddingLeft{padding-left:40px}.container.paddingRight{padding-right:40px}.container.paddingTop{padding-top:80px}@media only screen and (max-width:735px){.container.paddingBottom{padding-bottom:40px}.container.paddingTop{padding-top:20px}}@media only screen and (max-width:1023px){.responsiveList .blockContent{position:relative}.responsiveList .blockContent>div{padding-left:20px}.responsiveList .blockContent:before{content:"\2022";position:absolute}}.navigationSlider .navSlideout{cursor:pointer;padding-top:4px;position:absolute;right:10px;top:0;transition:top .3s;z-index:101}.navigationSlider .slidingNav{bottom:auto;box-sizing:border-box;left:0;position:fixed;right:0;top:0}.navigationSlider .slidingNav.slidingNavActive{height:auto;padding-top:42px;width:300px}.navigationSlider .slidingNav ul{background:#ffaf00;box-sizing:border-box;color:#fff;display:flex;flex-wrap:nowrap;list-style:none;margin-top:50px;padding:0;width:100%}.navigationSlider .slidingNav.slidingNavActive ul{display:block}.navigationSlider .slidingNav ul li{flex:1 1 auto;margin:0;text-align:center;white-space:nowrap}.navigationSlider .slidingNav ul li a{align-items:center;box-sizing:border-box;color:#812ce5;color:inherit;display:flex;font-size:.9em;height:auto;height:50px;justify-content:center;margin:0;padding:10px;transition:background-color .3s}.navigationSlider .slidingNav ul li.siteNavGroupActive>a,.navigationSlider .slidingNav ul li.siteNavItemActive>a,.navigationSlider .slidingNav ul li>a:focus,.navigationSlider .slidingNav ul li>a:hover{background-color:#812ce5}.languages-icon{width:20px}#languages-dropdown{pointer-events:none;position:absolute;width:100%}#languages-dropdown.visible{display:flex}#languages-dropdown.hide{display:none}#languages-dropdown-items{background-color:#812ce5;display:flex;flex-direction:column;min-width:120px;pointer-events:all}#languages li{display:block}.navPusher{left:0;min-height:100%;padding-top:100px;position:relative;z-index:99}.singleRowMobileNav.navPusher{padding-top:50px}.navPusher:after{background:rgba(0,0,0,.4);content:"";height:0;opacity:0;position:absolute;right:0;top:0;transition:opacity .5s,width .1s .5s,height .1s .5s;width:0}@media screen and (min-width:1024px){.navPusher{display:flex;flex-direction:column;min-height:calc(100vh - 50px);padding-top:50px}.navPusher,.navPusher>:first-child{flex-grow:1}}.sliderActive .navPusher:after{height:100%;opacity:1;transition:opacity .5s;width:100%;z-index:100}@media only screen and (max-width:1024px){.reactNavSearchWrapper input#search_input_react{background-color:rgba(242,196,178,.25);border:none;border-radius:20px;box-sizing:border-box;color:#393939;font-size:14px;line-height:20px;outline:none;padding-left:38px;position:relative;transition:background-color .2s cubic-bezier(.68,-.55,.265,1.55),width .2s cubic-bezier(.68,-.55,.265,1.55),color .2s ease;width:100%;height:30px}.reactNavSearchWrapper input#search_input_react:active,.reactNavSearchWrapper input#search_input_react:focus{background-color:#812ce5;color:#fff}.reactNavSearchWrapper .algolia-docsearch-suggestion--subcategory-inline{display:none}.reactNavSearchWrapper>span{width:100%}.reactNavSearchWrapper .aa-dropdown-menu{font-size:12px;line-height:2em;padding:0;border-width:1px;min-width:500px}.reactNavSearchWrapper .algolia-docsearch-suggestion__secondary{border-top:none}.aa-suggestions{min-height:140px;max-height:60vh;-webkit-overflow-scrolling:touch;overflow-y:scroll}#languages-dropdown{left:0;top:50px}#languages-dropdown-items{background-color:#812ce5;display:flex;flex-direction:row}}@media only screen and (min-width:1024px){.navSearchWrapper{padding-left:10px;position:relative;right:auto;top:auto}.reactNavSearchWrapper input#search_input_react{height:100%;padding-top:8px;padding-bottom:8px;padding-left:38px}.navSearchWrapper .algolia-autocomplete{display:block}.navigationSlider{height:34px;margin-left:auto;position:relative}.navigationSlider .navSlideout{display:none}.navigationSlider nav.slidingNav{background:none;height:auto;position:relative;right:auto;top:auto;width:auto}.navigationSlider .slidingNav ul{background:none;display:flex;flex-flow:row nowrap;margin:0;padding:0;width:auto}.navigationSlider .slidingNav ul li a{border:0;color:hsla(0,0%,100%,.8);display:flex;font-size:16px;font-size:1em;font-weight:300;height:32px;line-height:1.2em;margin:0;padding:6px 10px}.navigationSlider .slidingNav ul li.siteNavGroupActive a,.navigationSlider .slidingNav ul li.siteNavItemActive a,.navigationSlider .slidingNav ul li a:hover{color:#fff}}@media only screen and (max-width:735px){.navigationSlider .slidingNav ul{overflow-x:auto}.navigationSlider .slidingNav ul::-webkit-scrollbar{display:none}.reactNavSearchWrapper .aa-dropdown-menu{min-width:400px}}@media only screen and (max-width:475px){.reactNavSearchWrapper .aa-dropdown-menu{min-width:300px}}.docMainWrapper .wrapper{padding-left:0;padding-right:0;padding-top:10px}@media only screen and (min-width:1024px){.docMainWrapper{width:100%}.docMainWrapper>*{margin:0 24px}.docMainWrapper>:first-child{margin-left:0}.docMainWrapper>:last-child{margin-right:0}.docMainWrapper .mainContainer{min-width:0}}.edit-page-link{float:right;font-size:10px;font-weight:400;margin-top:3px;text-decoration:none}@media only screen and (max-width:1023px){.edit-page-link{display:none}}.docLastUpdate{font-size:13px;font-style:italic;margin:20px 0;text-align:right}.docs-prevnext{margin:20px 0}.docs-prevnext:after{clear:both;content:" ";display:table}.docs-next{float:right}.docs-prev{float:left}@media only screen and (max-width:735px){.docs-next{clear:both;float:left}.docs-next,.docs-prev{margin:10px 0}.arrow-next{float:right;margin-left:10px}.arrow-prev{float:left;margin-right:10px}.function-name-prevnext{width:200px;display:inline-block;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}}.hide{display:none}.collapsible{cursor:pointer}.collapsible .arrow{float:right;margin-right:8px;margin-top:-4px;transform:rotate(90deg);transition:transform .2s linear}.collapsible .arrow.rotate{transform:rotate(180deg)}@media only screen and (max-width:1023px){.docsNavContainer{background:#fff;left:0;position:fixed;width:100%;z-index:100}}@media only screen and (min-width:1024px){.docsNavContainer{flex:0 0 240px;height:calc(100vh - 50px);position:-webkit-sticky;position:sticky;overflow-y:auto;top:50px}}.docsSliderActive.docsNavContainer{box-sizing:border-box;height:100%;-webkit-overflow-scrolling:touch;overflow-y:auto;-ms-scroll-chaining:none;overscroll-behavior:contain;padding-bottom:50px}.docsNavContainer .toc .navBreadcrumb{background-color:#f1f1f1;box-sizing:border-box;display:flex;flex-flow:row nowrap;font-size:12px;height:48px;overflow:hidden;padding:8px 20px}.docsNavContainer .toc .navWrapper{padding:0}@media only screen and (min-width:1024px){.docsNavContainer .toc .navBreadcrumb{display:none}.navBreadcrumb h2{padding:0 10px}.separateOnPageNav .docsNavContainer{flex:0 0 240px}}.navBreadcrumb a,.navBreadcrumb span{border:0;color:#393939}@media only screen and (max-width:735px){.anchor{top:-144px}}@media only screen and (min-width:1024px){.toc{padding:40px 0}}.toc section{padding:0;position:relative}.toc section .navGroups{display:none;padding:48px 20px 60px}.toc .toggleNav{color:#393939;position:relative}.toc .toggleNav .navToggle{cursor:pointer;height:32px;margin-right:10px;position:relative;text-align:left;width:18px}.hamburger-menu{position:absolute;top:6px;width:100%}.line1,.line2,.line3{width:100%;height:3px;background-color:#393939;margin:3px 0;transition:.4s;border-radius:10px}.docsSliderActive .hamburger-menu{top:12px}.docsSliderActive .line1{position:absolute;top:50%;transform:rotate(-45deg)}.docsSliderActive .line2{display:none}.docsSliderActive .line3{position:absolute;top:50%;transform:rotate(45deg)}.toggleNav h2 i{padding:0 4px}.toc .toggleNav .navGroup{margin-bottom:16px}.toc .toggleNav .subNavGroup{margin-bottom:0}.toc .toggleNav .navGroup .navGroupCategoryTitle{color:#393939;font-size:18px;font-weight:500;line-height:1.2em;margin-bottom:8px;margin-top:0}.toc .toggleNav .navGroup .navGroupSubcategoryTitle{color:#393939;font-size:14px;font-weight:500;line-height:1.5;margin-bottom:0;margin-top:0;padding:4px 0}.toc .toggleNav .navGroup .navListItem{margin:0}.toc .toggleNav .navGroup h3 i:not(:empty){box-sizing:border-box;color:rgba(57,57,57,.5);display:inline-block;height:16px;margin-right:10px;text-align:center;transition:color .2s;width:16px}.toc .toggleNav ul{padding:0 8px}.docsSliderActive .toc .toggleNav ul{padding-left:0}.toc .toggleNav ul li{list-style-type:none;padding:0}.toc .toggleNav ul li a{border:none;color:#717171;display:block;font-size:14px;padding:4px 0;transition:color .3s}.toc .toggleNav ul li.navListItemActive a,.toc .toggleNav ul li a:focus,.toc .toggleNav ul li a:hover{color:#812ce5}.docsSliderActive .toc .navBreadcrumb,.tocActive .navBreadcrumb{border-bottom:1px solid #ccc;margin-bottom:20px;position:fixed;width:100%}.toc .toggleNav .navBreadcrumb h2{border:0;flex-grow:1;font-size:16px;font-weight:600;line-height:32px;margin:0;padding:0}.docsSliderActive .toc section .navGroups{display:block;padding-top:60px}.tocToggler{cursor:pointer;height:32px;line-height:32px;margin-right:-10px;padding:0 10px}.icon-toc{box-sizing:border-box;display:inline-block;line-height:normal;position:relative;top:-1px;vertical-align:middle}.icon-toc,.icon-toc:after,.icon-toc:before{background-color:currentColor;border:1px solid;border-radius:50%;box-sizing:border-box;height:4px;width:4px}.icon-toc:after,.icon-toc:before{content:"";position:absolute}.icon-toc:before{left:-1px;top:-7px}.icon-toc:after{left:-1px;top:5px}.tocActive .icon-toc{border-radius:0;height:16px;transform:rotate(45deg);width:3px}.tocActive .icon-toc:before{border-radius:0;height:3px;left:50%;top:50%;transform:translate(-50%,-50%);width:16px}.tocActive .icon-toc:after{content:""}@media only screen and (min-width:1024px){.docMainWrapper{display:flex;flex-flow:row nowrap}.docMainWrapper .wrapper{padding-top:0;padding-left:0;padding-right:0}}.onPageNav{display:none;margin-bottom:40px}.onPageNav::-webkit-scrollbar{width:7px}.onPageNav::-webkit-scrollbar-track{background:#f1f1f1;border-radius:10px}.onPageNav::-webkit-scrollbar-thumb{background:#888;border-radius:10px}.onPageNav::-webkit-scrollbar-thumb:hover{background:#555}.onPageNav a{color:#717171}.onPageNav .toc-headings>li>a.active,.onPageNav .toc-headings>li>a.hover{font-weight:600;color:#812ce5}.onPageNav ul{list-style:none}.onPageNav ul li{font-size:12px;line-height:16px;padding-bottom:8px}.onPageNav ul ul{padding:8px 0 0 20px}.onPageNav ul ul li{padding-bottom:5px}@media only screen and (min-width:1024px){.toc section .navGroups{display:block;padding:8px 0 0}.navBreadcrumb h2{padding:0 10px}}@supports ((position: -webkit-sticky) or (position: sticky)){@media only screen and (max-width:1023px){.tocActive .onPageNav{background:#fff;bottom:0;display:block;left:0;overflow-y:auto;-ms-scroll-chaining:none;overscroll-behavior:contain;padding:0 20px;position:fixed;right:0;top:148px;z-index:10;margin-bottom:0}.tocActive .singleRowMobileNav .onPageNav{top:98px}.tocActive .navBreadcrumb h2,.tocActive .navToggle{visibility:hidden}.tocActive .onPageNav>.toc-headings{padding:12px 0}}@media only screen and (min-width:1024px){.separateOnPageNav .headerWrapper.wrapper,.separateOnPageNav .wrapper{max-width:1400px}.separateOnPageNav .toc{width:auto}.separateOnPageNav.sideNavVisible .navPusher .mainContainer{flex:1 auto;max-width:100%;min-width:0}.onPageNav{align-self:flex-start;display:block;flex:0 0 240px;max-height:calc(100vh - 90px);overflow-y:auto;position:-webkit-sticky;position:sticky;top:90px}.onPageNav>.toc-headings{border-left:1px solid #e0e0e0;padding:10px 0 2px 15px}.tocToggler{display:none}}}.blog .wrapper{max-width:1100px}.blogContainer .posts .post{border-bottom:1px solid #e0e0e0;border-radius:3px;margin-bottom:20px;padding-bottom:20px}.blogContainer .postHeader{margin-bottom:10px}.blogContainer .postHeaderTitle{margin-top:0}.blogContainer .postHeader p.post-meta{margin-bottom:10px;padding:0}.blogContainer .postHeader .authorBlock{display:flex}.blogContainer .postHeader .post-authorName{color:rgba(57,57,57,.7);display:flex;flex-direction:column;font-size:14px;font-weight:400;justify-content:center;margin-right:10px;margin-top:0;margin-bottom:0;padding:0}.blogContainer .postHeader .authorPhoto{border-radius:50%;height:30px;overflow:hidden;width:30px}.blogContainer .postHeader .authorPhoto.authorPhotoBig{height:50px;width:50px}.blog-recent{margin:20px 0}.blog-recent>a{float:left}@media only screen and (max-width:735px){.blog-recent{height:40px}}.blogSocialSection{display:block;padding:36px 0}.blogSocialSection .blogSocialSectionItem{padding-bottom:5px}.fb-like{display:block;margin-bottom:20px;width:100%}.more-users{margin:0 auto;max-width:560px;text-align:center}.productShowcaseSection{padding:0 20px;text-align:center}.productShowcaseSection.paddingTop{padding-top:20px}.productShowcaseSection.paddingBottom{padding-bottom:80px}.productShowcaseSection h2{color:#812ce5;font-size:30px;line-height:1em;margin-top:20px;padding:10px 0;text-align:center}.productShowcaseSection p{margin:0 auto;max-width:560px;padding:.8em 0}.productShowcaseSection .logos{align-items:center;display:flex;flex-flow:row wrap;justify-content:center;padding:20px}.productShowcaseSection .logos img{max-height:110px;padding:20px;width:110px}@media only screen and (max-width:735px){.productShowcaseSection .logos img{max-height:64px;padding:20px;width:64px}}.showcaseSection{margin:0 auto;max-width:900px}.showcaseSection,.showcaseSection .prose h1{text-align:center}.showcaseSection .prose{margin:0 auto;max-width:560px;text-align:center}.showcaseSection .logos{align-items:center;display:flex;flex-flow:row wrap;justify-content:center}.showcaseSection .logos img{max-height:128px;padding:20px;width:128px}@media only screen and (max-width:735px){.showcaseSection .logos img{max-height:64px;padding:20px;width:64px}}.nav-footer{background:#20232a;border:none;color:#202020;font-size:15px;-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale;font-weight:400;line-height:24px;padding-bottom:2em;padding-top:2em;position:relative}@media only screen and (min-width:1024px){.nav-footer{flex-shrink:0}}.nav-footer .sitemap{display:flex;justify-content:space-between;margin:0 auto 3em;max-width:1080px}.nav-footer .sitemap div{flex:1}.nav-footer .sitemap .nav-home{display:table;height:72px;margin:-12px 20px 0 0;opacity:.4;padding:10px;transition:opacity .15s ease-in-out;width:72px}.nav-footer .sitemap .nav-home:focus,.nav-footer .sitemap .nav-home:hover{opacity:1}@media only screen and (max-width:735px){.nav-footer .sitemap{display:flex;flex-direction:column;margin:0 2em 3em;width:calc(100% - 4em)}.nav-footer .sitemap>div{margin-bottom:18px}}.nav-footer .sitemap a{color:hsla(0,0%,100%,.6);display:block;margin:2px 0;padding:3px 0}.nav-footer .sitemap a:focus,.nav-footer .sitemap a:hover,.nav-footer .sitemap h5>a:focus,.nav-footer .sitemap h5>a:hover{color:#fff;text-decoration:none}.nav-footer .sitemap h5,.nav-footer .sitemap h6{margin:0 0 10px}.nav-footer .sitemap h5,.nav-footer .sitemap h5>a,.nav-footer .sitemap h6,.nav-footer .sitemap h6>a{color:#fff}.nav-footer .sitemap h5>a,.nav-footer .sitemap h6>a{margin:0 -10px}.nav-footer .fbOpenSource{display:block;margin:1em auto;opacity:.4;transition:opacity .15s ease-in-out;width:170px}.nav-footer .fbOpenSource:hover{opacity:1}.nav-footer .copyright{color:hsla(0,0%,100%,.4);text-align:center}.nav-footer .social{padding:5px 0}.tabs{border-top:1px solid #cfcfcf}.nav-tabs{display:flex;border-bottom:4px solid #e0e0e0;width:100%;padding:0;overflow-x:auto;white-space:nowrap;max-height:100%}.nav-tabs::-webkit-scrollbar{display:none}.tabs .tab-pane:focus{outline:none}.tabs .nav-tabs>div{font-size:14px;line-height:1.14286;padding:12px 16px;text-decoration:none;display:block;cursor:pointer}.tabs .nav-tabs>div.active{border-bottom:4px solid #812ce5}.tab-pane{display:none}.tab-pane.active{display:block}.tab-pane>pre{white-space:pre-wrap}.tab-pane>pre>code{margin-top:0;border-radius:0;box-shadow:none}html body{font-family:Montserrat,sans-serif;overflow-x:hidden}.fixedHeaderContainer{background-color:#222}.fixedHeaderContainer header .headerTitleWithLogo{display:block;color:#fff}.fixedHeaderContainer header .logo{height:50px}.fixedHeaderContainer header a:nth-child(2){position:absolute;right:0}.fixedHeaderContainer header a:nth-child(2) h3{font-size:14px}.fixedHeaderContainer header a:nth-child(2) h3:before{content:"v: "}.navigationSlider{margin-right:80px}.navigationSlider .slidingNav ul{background:#222}.navigationSlider .slidingNav ul li a{color:#c7d4fd}.navigationSlider .slidingNav ul li a:focus,.navigationSlider .slidingNav ul li a:hover{color:#fff;background-color:inherit}.navigationSlider .slidingNav ul li.siteNavGroupActive>a,.navigationSlider .slidingNav ul li.siteNavItemActive>a{background-color:inherit}.homeContainer{background:linear-gradient(#812ce5,#ffaf00);padding:25px 0}.splashLogo{display:block;margin:0 auto;width:65%}.projectTitle{color:#fff;font-variant:small-caps;font-weight:300}.promoSection .button{border:2px solid #fff;color:#fff;font-size:19px;margin:10px}.promoSection .button:hover{background:inherit;border:2px solid #fff;color:#fff}.landingPage{padding:0}.productShowcaseSection{padding:45px 20px 30px}div.productShowcaseSection{color:#6c6c6c;padding-top:40px}#quickstart{padding-top:80px}.productShowcaseSection>h2{font-variant:small-caps;font-weight:360;margin:0;padding:0;color:#5b1861}.productShowcaseSection p{font-weight:360}# Subtitles for key features .productShowcaseSection .blockContent>div span p{font-size:18px}.productShowcaseSection div.container{padding:10px 0 40px}.productShowcaseSection img{height:100px}.gridBlock .fourByGridBlock img{max-width:200%}.productShowcaseSection li{padding:10px 0}.productShowcaseSection pre{margin:10px 0}.productShowcaseSection code{background:#fff}.container .wrapper .alignCenter h2{color:#222}div#quickstart{background:#efefef}div#quickstart ol{margin-bottom:0}.nav-footer{background-color:#222}.nav-footer .sitemap a{color:#c7d4fd}.nav-footer .sitemap a:hover{color:#fff}.social{text-align:center}a,a:hover,p a,p a:hover{color:#4872f9}.imageAlignTop .blockImage{margin-bottom:20px;max-width:200px}.tutorialBody{margin-top:-20px;color:#6c6c6c}.tutorialBody h1{margin:0}.tutorialBody h1,.tutorialBody h2,.tutorialBody h3{color:#222}.tutorialBody pre{font-family:IBM Plex Mono,monospace;font-size:14px;margin:0}.tutorialBody .input_prompt,.tutorialBody .output_prompt{color:#8b0000;font-size:12px}.tutorialBody .highlight{background:#f3f4f7;padding:10px 20px;border:1px solid #d3d3d3;border-radius:3px}.tutorialBody .cell{margin:20px}.tutorialBody .output_stderr{background-color:#fdede9}.tutorialBody .anchor-link{color:#d3d3d3}.tutorialBody iframe{width:100%;height:100vh}.tutorialButtonWrapper,.tutorialRuntime{margin:20px}.colabButtonWrapper,.tutorialButtonWrapper{float:left;margin:5px}.colabButtonWrapper img{padding-right:.25em}.colabButton{width:24px}.tutorialButtonsWrapper{display:flex;align-items:center;padding-bottom:15px}.tutorialButton svg{height:15px;margin-right:5px}.tutorialButton:hover{color:#4872f9;background-color:inherit}.wrapper{max-width:1400px}@media only screen and (min-device-width:360px) and (max-device-width:736px){.fixedHeaderContainer header a:nth-child(2){position:absolute;right:150px}.promoSection .button{font-size:12px;margin:3px}.inner h2{margin-top:0}.splashLogo{width:90%}.headerTitleWithLogo{display:block!important}.blockContent>div span p{margin-bottom:30px}.productShowcaseSection div.container{padding-top:0}.productShowcaseSection>h2{padding-bottom:20px}}@media only screen and (max-width:1023px){.fixedHeaderContainer header a:nth-child(2){position:absolute;right:200px}}.highlight .hll{background-color:#ffc}.highlight .c{color:#60a0b0;font-style:italic}.highlight .err{border:1px solid red}.highlight .k{color:#007020;font-weight:700}.highlight .o{color:#666}.highlight .cm{color:#60a0b0;font-style:italic}.highlight .cp{color:#007020}.highlight .c1{color:#60a0b0;font-style:italic}.highlight .cs{color:#60a0b0;background-color:#fff0f0}.highlight .gd{color:#a00000}.highlight .ge{font-style:italic}.highlight .gr{color:red}.highlight .gh{color:navy;font-weight:700}.highlight .gi{color:#00a000}.highlight .go{color:grey}.highlight .gp{color:#c65d09}.highlight .gp,.highlight .gs,.highlight .gu{font-weight:700}.highlight .gu{color:purple}.highlight .gt{color:#0040d0}.highlight .kc,.highlight .kd,.highlight .kn{color:#007020;font-weight:700}.highlight .kp{color:#007020}.highlight .kr{color:#007020;font-weight:700}.highlight .kt{color:#902000}.highlight .m{color:#40a070}.highlight .na,.highlight .s{color:#4070a0}.highlight .nb{color:#007020}.highlight .nc{color:#0e84b5;font-weight:700}.highlight .no{color:#60add5}.highlight .nd{color:#555;font-weight:700}.highlight .ni{color:#d55537;font-weight:700}.highlight .ne{color:#007020}.highlight .nf{color:#06287e}.highlight .nl{color:#002070;font-weight:700}.highlight .nn{color:#0e84b5;font-weight:700}.highlight .nt{color:#062873;font-weight:700}.highlight .nv{color:#bb60d5}.highlight .ow{color:#007020;font-weight:700}.highlight .w{color:#bbb}.highlight .mf,.highlight .mh,.highlight .mi,.highlight .mo{color:#40a070}.highlight .sb,.highlight .sc{color:#4070a0}.highlight .sd{color:#4070a0;font-style:italic}.highlight .s2{color:#4070a0}.highlight .se{color:#4070a0;font-weight:700}.highlight .sh{color:#4070a0}.highlight .si{color:#70a0d0;font-style:italic}.highlight .sx{color:#c65d09}.highlight .sr{color:#235388}.highlight .s1{color:#4070a0}.highlight .ss{color:#517918}.highlight .bp{color:#007020}.highlight .vc,.highlight .vg,.highlight .vi{color:#bb60d5}.highlight .il{color:#40a070} \ No newline at end of file +a,abbr,acronym,address,applet,article,aside,audio,b,big,blockquote,body,canvas,caption,center,cite,code,dd,del,details,dfn,div,dl,dt,em,embed,fieldset,figcaption,figure,footer,form,h1,h2,h3,h4,h5,h6,header,hgroup,html,i,iframe,img,ins,kbd,label,legend,li,mark,menu,nav,object,ol,output,p,pre,q,ruby,s,samp,section,small,span,strike,strong,sub,summary,sup,table,tbody,td,tfoot,th,thead,time,tr,tt,u,ul,var,video{border:0;font:inherit;font-size:100%;margin:0;padding:0;vertical-align:baseline}body{color:#24292e;font-family:-apple-system,BlinkMacSystemFont,Segoe UI,Helvetica,Arial,sans-serif,Apple Color Emoji,Segoe UI Emoji,Segoe UI Symbol;font-size:16px;line-height:1.5;-ms-text-size-adjust:100%;-webkit-text-size-adjust:100%;word-wrap:break-word}*{box-sizing:border-box}b,strong{font-weight:600}em,i{font-style:italic}[type=checkbox]{box-sizing:border-box;padding:0}a,a:hover{color:#812ce5;text-decoration:none}a:active,a:hover{outline-width:0}a:not([href]){color:inherit;text-decoration:none}p{margin-bottom:1em;margin-top:0}h1,h2,h3,h4,h5,h6{color:inherit;font-weight:600;line-height:1.25;margin-bottom:16px;margin-top:1.5em}h1{font-size:32px}h2{font-size:24px}h3{font-size:20px}h4{font-size:16px}h5{font-size:14px}h6{font-size:13.6px}ol,ul{margin-bottom:1em;margin-top:0;padding-left:2em}ol ol,ul ol{list-style-type:lower-roman}ol ol,ol ul,ul ol,ul ul{margin-bottom:0;margin-top:0}ol ol ol,ol ul ol,ul ol ol,ul ul ol{list-style-type:lower-alpha}li{word-wrap:break-all}li>p{margin-top:1em}li+li{margin-top:.25em}img{border-style:none;box-sizing:content-box;max-width:100%}img[align=right]{padding-left:1.25em}img[align=left]{padding-right:1.25em}table{border-collapse:collapse;border-spacing:0;display:block;margin-bottom:16px;margin-top:0;overflow:auto;width:100%}table tr{background-color:transparent;border-top:1px solid #dfe2e5}table tr:nth-child(2n){background-color:#f6f8fa}table td,table th{border:1px solid #dfe2e5;padding:6px 13px}table th{background-color:inherit;font-weight:600}table td,table th{color:inherit}blockquote{color:#6a737d;font-size:16px;margin:0 0 16px;padding:0 1em}blockquote>:first-child{margin-top:0}blockquote>:last-child{margin-bottom:0}code{background-color:rgba(27,31,35,.05);border-radius:3px;color:inherit;font-family:SFMono-Regular,Menlo,Monaco,Consolas,Liberation Mono,Courier New,monospace;font-size:85%;margin:0;padding:3.2px 6.4px}pre{margin-bottom:16px}pre code{background-color:transparent;border:0;display:inline;font-size:85%;line-height:inherit;margin:0;max-width:auto;overflow:visible;padding:0;white-space:pre;word-break:normal;word-wrap:normal}kbd{background-color:#fafbfc;border:1px solid #d1d5da;border-bottom-color:#c6cbd1;border-radius:3px;box-shadow:inset 0 -1px 0 #c6cbd1;color:#444d56;display:inline-block;font-family:SFMono-Regular,Menlo,Monaco,Consolas,Liberation Mono,Courier New,monospace;font-size:68.75%;line-height:10px;padding:3px 5px;vertical-align:middle}hr{border:1px solid #dfe2e5;box-sizing:content-box;margin:1.5em 0;overflow:hidden;padding:0}hr:after,hr:before{content:"";display:table}hr:after{clear:both}body{background-color:#fff;min-height:100vh;text-rendering:optimizeLegibility}@media only screen and (min-width:736px){body{display:flex;flex-direction:column}}article:after,article:before{content:"";display:table}article:after{clear:both}article>:first-child{margin-top:0}article>:last-child{margin-bottom:0}article iframe,article p img{display:block;margin-left:auto;margin-right:auto;max-width:100%}.anchor{display:block;position:relative;top:-80px}.hash-link{line-height:1;margin-left:-20px;opacity:0;padding-right:4px;transition:opacity .3s}.hash-link:hover{opacity:1!important;transition:none}.hash-link .hash-link-icon{vertical-align:middle}.button{border:1px solid #812ce5;border-radius:3px;color:#812ce5;display:inline-block;font-size:14px;font-weight:400;line-height:1.2em;padding:10px;text-decoration:none!important;text-transform:uppercase;transition:background .3s,color .3s}.button:hover{background:#812ce5;color:#fff}h1:hover .hash-link,h2:hover .hash-link,h3:hover .hash-link,h4:hover .hash-link{opacity:.5;transition:none}blockquote{background-color:rgba(255,229,100,.3);border-left:8px solid #ffe564;padding:15px 30px 15px 15px}.wrapper{margin:0 auto;max-width:1100px;padding:0 20px}.wrapper blockquote>p:first-child{padding-top:0}.center{display:block}.center,.homeContainer{text-align:center}.homeContainer .homeWrapper{padding:2em 10px}.homeContainer .homeWrapper .wrapper{margin:0 auto;max-width:900px;padding:0 20px}.homeContainer .homeWrapper .projectLogo img{height:100px;margin-bottom:0}.homeContainer .homeWrapper #project_title{font-size:300%;letter-spacing:-.08em;line-height:1em;margin-bottom:80px}.homeContainer .homeWrapper #project_tagline{font-size:200%;letter-spacing:-.04em;line-height:1em}.projectLogo{display:none;pointer-events:none}.projectLogo img{height:100px;margin-bottom:0}.projectIntro{margin:40px 0}.projectTitle{color:#812ce5;font-size:250%;line-height:1em}.projectTitle>small{display:block;font-weight:400;font-size:50%;line-height:1em;margin:.7em 0 1.3em}@media only screen and (min-width:480px){.projectTitle{font-size:300%;margin:.3em 0}.projectLogo img{height:200px;margin-bottom:10px}.homeContainer .homeWrapper{padding-left:10px;padding-right:10px}}@media only screen and (min-width:736px){.homeContainer .homeWrapper{position:relative}.homeContainer .homeWrapper #inner{max-width:600px;padding-right:40px}}@media only screen and (min-width:1200px){.homeContainer .homeWrapper #inner{max-width:750px}.homeContainer .homeWrapper .projectLogo{align-items:center;bottom:0;display:flex;justify-content:flex-end;left:0;padding:2em 100px 4em;position:absolute;right:0;top:0}.homeContainer .homeWrapper .projectLogo img{height:100%;max-height:250px}}@media only screen and (min-width:1500px){.homeContainer .homeWrapper #inner{max-width:1100px;padding-bottom:40px;padding-top:40px}.wrapper{max-width:1400px}}.mainContainer{flex:1 1 0%;max-width:100%;padding:40px 0}.mainContainer .wrapper{text-align:left}.mainContainer .wrapper .allShareBlock{padding:10px 0}.mainContainer .wrapper .allShareBlock .pluginBlock{margin:12px 0;padding:0}.mainContainer .wrapper .post{position:relative}.mainContainer .wrapper .post.basicPost{margin-top:30px}.mainContainer .wrapper .post .postHeader{margin-bottom:16px}.mainContainer .wrapper .post .postHeaderTitle{margin-top:0;padding:0}.docsContainer .wrapper .post .postHeader:before,.docsContainer .wrapper .post .postHeaderTitle:before{content:"";display:block;height:90px;margin-top:-90px;visibility:hidden;pointer-events:none}.mainContainer .wrapper .post .postSocialPlugins{padding-top:1em}.mainContainer .wrapper .post .docPagination{background:#812ce5;bottom:0;left:0;position:absolute;right:0}.mainContainer .wrapper .post .docPagination .pager{display:inline-block;width:50%}.mainContainer .wrapper .post .docPagination .pagingNext{float:right;text-align:right}.mainContainer .wrapper .post .docPagination a{border:none;color:#fff;display:block;padding:4px 12px}.mainContainer .wrapper .post .docPagination a:hover{background-color:#f9f9f9;color:#393939}.mainContainer .wrapper .post .docPagination a .pagerLabel{display:inline}.mainContainer .wrapper .post .docPagination a .pagerTitle{display:none}@media only screen and (min-width:480px){.mainContainer .wrapper .post .docPagination a .pagerLabel{display:none}.mainContainer .wrapper .post .docPagination a .pagerTitle{display:inline}}@media only screen and (min-width:1024px){.mainContainer .wrapper .post{display:block}.mainContainer .wrapper .posts .post{width:100%}}@media only screen and (max-width:1023px){.docsContainer .wrapper .post .postHeader:before,.docsContainer .wrapper .post .postHeaderTitle:before{content:"";display:block;height:200px;margin-top:-200px;visibility:hidden;pointer-events:none}}.fixedHeaderContainer{background:#812ce5;color:#fff;min-height:50px;padding:8px 0;position:fixed;width:100%;z-index:9999;transform:translateZ(0)}@media only screen and (min-width:1024px){.fixedHeaderContainer{flex-shrink:0}}.fixedHeaderContainer a{align-items:center;border:0;color:#fff;display:flex;flex-flow:row nowrap;height:34px;z-index:10000}.fixedHeaderContainer header{display:flex;flex-flow:row nowrap;position:relative;text-align:left}.fixedHeaderContainer header img{height:100%;margin-right:10px}.fixedHeaderContainer header .headerTitle{font-size:1.25em;margin:0}.fixedHeaderContainer header .headerTitleWithLogo{font-size:1.25em;line-height:18px;margin:0;position:relative;z-index:9999}.fixedHeaderContainer header h3{color:#fff;font-size:16px;margin:0 0 0 10px;text-decoration:underline}@media (max-width:480px){.headerTitle{font-size:17px}.headerTitleWithLogo{display:none!important}}.promoSection{display:flex;flex-flow:column wrap;font-size:125%;line-height:1.6em;position:relative;z-index:99}.promoSection .promoRow{padding:10px 0}.promoSection .promoRow .pluginWrapper{display:block}.promoSection .promoRow .pluginWrapper.ghStarWrapper,.promoSection .promoRow .pluginWrapper.ghWatchWrapper{height:28px}.promoSection .promoRow .pluginRowBlock{display:flex;flex-wrap:wrap;justify-content:center;margin:0 -2px}.promoSection .promoRow .pluginRowBlock .pluginWrapper{padding:0 2px}.promoSection .promoRow .pluginRowBlock iframe{margin-left:2px;margin-top:5px}input[type=search]{-moz-appearance:none;-webkit-appearance:none}.navSearchWrapper{align-items:center;align-self:center;display:flex;justify-content:center;padding-left:10px;position:absolute;right:10px;top:10px}.navSearchWrapper:before{border:3px solid #e5e5e5;border-radius:50%;content:" ";display:block;height:6px;left:15px;position:absolute;top:50%;transform:translateY(-58%);width:6px;z-index:1}.navSearchWrapper:after{background:#e5e5e5;content:" ";height:7px;left:24px;position:absolute;top:55%;transform:rotate(-45deg);width:3px;z-index:1}.navSearchWrapper .aa-dropdown-menu{background:#f9f9f9;border:3px solid rgba(57,57,57,.25);color:#393939;font-size:14px;left:auto!important;line-height:1.2em;right:0!important}.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--category-header{background:#812ce5;color:#fff;font-size:14px;font-weight:400}.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--category-header .algolia-docsearch-suggestion--highlight{background-color:#812ce5;color:#fff}.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--subcategory-column .algolia-docsearch-suggestion--highlight,.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--title .algolia-docsearch-suggestion--highlight{color:#812ce5}.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion--subcategory-column,.navSearchWrapper .aa-dropdown-menu .algolia-docsearch-suggestion__secondary{border-color:rgba(57,57,57,.3)}input#search_input_react{background-color:rgba(0,0,0,.2);border:none;border-radius:20px;color:#fff;font-size:14px;font-weight:300;line-height:20px;outline:none;padding-left:25px;position:relative;transition:width .5s ease;width:170px}.navSearchWrapper:before{left:24px}.navSearchWrapper:after{left:35px}input#search_input_react:active,input#search_input_react:focus{color:#fff;width:220px}.navigationSlider .slidingNav .navSearchWrapper .algolia-docsearch-footer a{height:auto}@media only screen and (max-width:735px){.navSearchWrapper{width:40%}}input::-moz-placeholder{color:#e5e5e5}input:-ms-input-placeholder{color:#e5e5e5}input::-ms-input-placeholder{color:#e5e5e5}input::placeholder{color:#e5e5e5}.hljs{padding:1.25rem 1.5rem}.gridBlock{padding:0}.gridBlock>*{box-sizing:border-box}.gridBlock .fourByGridBlock img,.gridBlock .threeByGridBlock img,.gridBlock .twoByGridBlock img{max-width:100%}.gridBlock .gridClear{clear:both}@media only screen and (max-width:735px){.gridBlock .fourByGridBlock{flex:1 0 26%}}@media only screen and (min-width:736px){.gridBlock{display:flex;flex-direction:row;flex-wrap:wrap}.gridBlock>*{margin:0 12px}.gridBlock>:first-child{margin-left:0}.gridBlock>:last-child{margin-right:0}.gridBlock .twoByGridBlock{flex:1 0 40%}.gridBlock .threeByGridBlock{flex:1 0 26%}.gridBlock .fourByGridBlock{flex:1 0 20%}h2+.gridBlock{padding-top:20px}}@media only screen and (min-width:1400px){.gridBlock{display:flex;flex-direction:row;flex-wrap:wrap}}.alignCenter{text-align:center}.alignRight{text-align:right}.imageAlignSide{display:flex;flex-flow:row wrap}.blockImage{max-width:730px}.imageAlignSide .blockImage{flex:0 1 500px;max-width:500px}@media only screen and (max-width:735px){.imageAlignSide .blockImage{display:none}}.imageAlignSide .blockContent{flex:1 1}.imageAlignBottom .blockImage{margin:0 auto 20px;max-width:730px}.imageAlignBottom.alignCenter .blockImage{margin-left:auto;margin-right:auto}.imageAlignTop .blockImage{max-width:80px}.imageAlignTop.alignCenter .blockImage{margin-left:auto;margin-right:auto}.imageAlignRight .blockImage{margin-left:40px}.imageAlignLeft .blockImage{margin-right:40px}.container .gridBlock .blockContent p{padding:0}.container .wrapper .alignCenter h2{text-align:center}.container .wrapper .imageAlignSide h2{text-align:left}.container .wrapper .imageAlignSide p{margin:0 0 40px;max-width:560px}.highlightBackground{background:rgba(153,66,79,.7);color:#fff}.highlightBackground a{font-weight:800}.container.highlightBackground .wrapper h1,.container.highlightBackground .wrapper h2,.container.highlightBackground .wrapper h3,.container.highlightBackground .wrapper h4,.container.highlightBackground .wrapper h5,.highlightBackground a{border-color:#fff;color:#fff}.lightBackground{background:#f7f7f7}.darkBackground{background:grey;color:#fff}.darkBackground a,.darkBackground code{color:#d6b3b8}.container.darkBackground .wrapper h1,.container.darkBackground .wrapper h2,.container.darkBackground .wrapper h3,.container.darkBackground .wrapper h4,.container.darkBackground .wrapper h5{border-color:#fff;color:#fff}.container.paddingAll{padding:40px}.container.paddingBottom{padding-bottom:80px}.container.paddingLeft{padding-left:40px}.container.paddingRight{padding-right:40px}.container.paddingTop{padding-top:80px}@media only screen and (max-width:735px){.container.paddingBottom{padding-bottom:40px}.container.paddingTop{padding-top:20px}}@media only screen and (max-width:1023px){.responsiveList .blockContent{position:relative}.responsiveList .blockContent>div{padding-left:20px}.responsiveList .blockContent:before{content:"\2022";position:absolute}}.navigationSlider .navSlideout{cursor:pointer;padding-top:4px;position:absolute;right:10px;top:0;transition:top .3s;z-index:101}.navigationSlider .slidingNav{bottom:auto;box-sizing:border-box;left:0;position:fixed;right:0;top:0}.navigationSlider .slidingNav.slidingNavActive{height:auto;padding-top:42px;width:300px}.navigationSlider .slidingNav ul{background:#ffaf00;box-sizing:border-box;color:#fff;display:flex;flex-wrap:nowrap;list-style:none;margin-top:50px;padding:0;width:100%}.navigationSlider .slidingNav.slidingNavActive ul{display:block}.navigationSlider .slidingNav ul li{flex:1 1 auto;margin:0;text-align:center;white-space:nowrap}.navigationSlider .slidingNav ul li a{align-items:center;box-sizing:border-box;color:#812ce5;color:inherit;display:flex;font-size:.9em;height:auto;height:50px;justify-content:center;margin:0;padding:10px;transition:background-color .3s}.navigationSlider .slidingNav ul li.siteNavGroupActive>a,.navigationSlider .slidingNav ul li.siteNavItemActive>a,.navigationSlider .slidingNav ul li>a:focus,.navigationSlider .slidingNav ul li>a:hover{background-color:#812ce5}.languages-icon{width:20px}#languages-dropdown{pointer-events:none;position:absolute;width:100%}#languages-dropdown.visible{display:flex}#languages-dropdown.hide{display:none}#languages-dropdown-items{background-color:#812ce5;display:flex;flex-direction:column;min-width:120px;pointer-events:all}#languages li{display:block}.navPusher{left:0;min-height:100%;padding-top:100px;position:relative;z-index:99}.singleRowMobileNav.navPusher{padding-top:50px}.navPusher:after{background:rgba(0,0,0,.4);content:"";height:0;opacity:0;position:absolute;right:0;top:0;transition:opacity .5s,width .1s .5s,height .1s .5s;width:0}@media screen and (min-width:1024px){.navPusher{display:flex;flex-direction:column;min-height:calc(100vh - 50px);padding-top:50px}.navPusher,.navPusher>:first-child{flex-grow:1}}.sliderActive .navPusher:after{height:100%;opacity:1;transition:opacity .5s;width:100%;z-index:100}@media only screen and (max-width:1024px){.reactNavSearchWrapper input#search_input_react{background-color:rgba(242,196,178,.25);border:none;border-radius:20px;box-sizing:border-box;color:#393939;font-size:14px;line-height:20px;outline:none;padding-left:38px;position:relative;transition:background-color .2s cubic-bezier(.68,-.55,.265,1.55),width .2s cubic-bezier(.68,-.55,.265,1.55),color .2s ease;width:100%;height:30px}.reactNavSearchWrapper input#search_input_react:active,.reactNavSearchWrapper input#search_input_react:focus{background-color:#812ce5;color:#fff}.reactNavSearchWrapper .algolia-docsearch-suggestion--subcategory-inline{display:none}.reactNavSearchWrapper>span{width:100%}.reactNavSearchWrapper .aa-dropdown-menu{font-size:12px;line-height:2em;padding:0;border-width:1px;min-width:500px}.reactNavSearchWrapper .algolia-docsearch-suggestion__secondary{border-top:none}.aa-suggestions{min-height:140px;max-height:60vh;-webkit-overflow-scrolling:touch;overflow-y:scroll}#languages-dropdown{left:0;top:50px}#languages-dropdown-items{background-color:#812ce5;display:flex;flex-direction:row}}@media only screen and (min-width:1024px){.navSearchWrapper{padding-left:10px;position:relative;right:auto;top:auto}.reactNavSearchWrapper input#search_input_react{height:100%;padding-top:8px;padding-bottom:8px;padding-left:38px}.navSearchWrapper .algolia-autocomplete{display:block}.navigationSlider{height:34px;margin-left:auto;position:relative}.navigationSlider .navSlideout{display:none}.navigationSlider nav.slidingNav{background:none;height:auto;position:relative;right:auto;top:auto;width:auto}.navigationSlider .slidingNav ul{background:none;display:flex;flex-flow:row nowrap;margin:0;padding:0;width:auto}.navigationSlider .slidingNav ul li a{border:0;color:hsla(0,0%,100%,.8);display:flex;font-size:16px;font-size:1em;font-weight:300;height:32px;line-height:1.2em;margin:0;padding:6px 10px}.navigationSlider .slidingNav ul li.siteNavGroupActive a,.navigationSlider .slidingNav ul li.siteNavItemActive a,.navigationSlider .slidingNav ul li a:hover{color:#fff}}@media only screen and (max-width:735px){.navigationSlider .slidingNav ul{overflow-x:auto}.navigationSlider .slidingNav ul::-webkit-scrollbar{display:none}.reactNavSearchWrapper .aa-dropdown-menu{min-width:400px}}@media only screen and (max-width:475px){.reactNavSearchWrapper .aa-dropdown-menu{min-width:300px}}.docMainWrapper .wrapper{padding-left:0;padding-right:0;padding-top:10px}@media only screen and (min-width:1024px){.docMainWrapper{width:100%}.docMainWrapper>*{margin:0 24px}.docMainWrapper>:first-child{margin-left:0}.docMainWrapper>:last-child{margin-right:0}.docMainWrapper .mainContainer{min-width:0}}.edit-page-link{float:right;font-size:10px;font-weight:400;margin-top:3px;text-decoration:none}@media only screen and (max-width:1023px){.edit-page-link{display:none}}.docLastUpdate{font-size:13px;font-style:italic;margin:20px 0;text-align:right}.docs-prevnext{margin:20px 0}.docs-prevnext:after{clear:both;content:" ";display:table}.docs-next{float:right}.docs-prev{float:left}@media only screen and (max-width:735px){.docs-next{clear:both;float:left}.docs-next,.docs-prev{margin:10px 0}.arrow-next{float:right;margin-left:10px}.arrow-prev{float:left;margin-right:10px}.function-name-prevnext{width:200px;display:inline-block;white-space:nowrap;overflow:hidden;text-overflow:ellipsis}}.hide{display:none}.collapsible{cursor:pointer}.collapsible .arrow{float:right;margin-right:8px;margin-top:-4px;transform:rotate(90deg);transition:transform .2s linear}.collapsible .arrow.rotate{transform:rotate(180deg)}@media only screen and (max-width:1023px){.docsNavContainer{background:#fff;left:0;position:fixed;width:100%;z-index:100}}@media only screen and (min-width:1024px){.docsNavContainer{flex:0 0 240px;height:calc(100vh - 50px);position:-webkit-sticky;position:sticky;overflow-y:auto;top:50px}}.docsSliderActive.docsNavContainer{box-sizing:border-box;height:100%;-webkit-overflow-scrolling:touch;overflow-y:auto;-ms-scroll-chaining:none;overscroll-behavior:contain;padding-bottom:50px}.docsNavContainer .toc .navBreadcrumb{background-color:#f1f1f1;box-sizing:border-box;display:flex;flex-flow:row nowrap;font-size:12px;height:48px;overflow:hidden;padding:8px 20px}.docsNavContainer .toc .navWrapper{padding:0}@media only screen and (min-width:1024px){.docsNavContainer .toc .navBreadcrumb{display:none}.navBreadcrumb h2{padding:0 10px}.separateOnPageNav .docsNavContainer{flex:0 0 240px}}.navBreadcrumb a,.navBreadcrumb span{border:0;color:#393939}@media only screen and (max-width:735px){.anchor{top:-144px}}@media only screen and (min-width:1024px){.toc{padding:40px 0}}.toc section{padding:0;position:relative}.toc section .navGroups{display:none;padding:48px 20px 60px}.toc .toggleNav{color:#393939;position:relative}.toc .toggleNav .navToggle{cursor:pointer;height:32px;margin-right:10px;position:relative;text-align:left;width:18px}.hamburger-menu{position:absolute;top:6px;width:100%}.line1,.line2,.line3{width:100%;height:3px;background-color:#393939;margin:3px 0;transition:.4s;border-radius:10px}.docsSliderActive .hamburger-menu{top:12px}.docsSliderActive .line1{position:absolute;top:50%;transform:rotate(-45deg)}.docsSliderActive .line2{display:none}.docsSliderActive .line3{position:absolute;top:50%;transform:rotate(45deg)}.toggleNav h2 i{padding:0 4px}.toc .toggleNav .navGroup{margin-bottom:16px}.toc .toggleNav .subNavGroup{margin-bottom:0}.toc .toggleNav .navGroup .navGroupCategoryTitle{color:#393939;font-size:18px;font-weight:500;line-height:1.2em;margin-bottom:8px;margin-top:0}.toc .toggleNav .navGroup .navGroupSubcategoryTitle{color:#393939;font-size:14px;font-weight:500;line-height:1.5;margin-bottom:0;margin-top:0;padding:4px 0}.toc .toggleNav .navGroup .navListItem{margin:0}.toc .toggleNav .navGroup h3 i:not(:empty){box-sizing:border-box;color:rgba(57,57,57,.5);display:inline-block;height:16px;margin-right:10px;text-align:center;transition:color .2s;width:16px}.toc .toggleNav ul{padding:0 8px}.docsSliderActive .toc .toggleNav ul{padding-left:0}.toc .toggleNav ul li{list-style-type:none;padding:0}.toc .toggleNav ul li a{border:none;color:#717171;display:block;font-size:14px;padding:4px 0;transition:color .3s}.toc .toggleNav ul li.navListItemActive a,.toc .toggleNav ul li a:focus,.toc .toggleNav ul li a:hover{color:#812ce5}.docsSliderActive .toc .navBreadcrumb,.tocActive .navBreadcrumb{border-bottom:1px solid #ccc;margin-bottom:20px;position:fixed;width:100%}.toc .toggleNav .navBreadcrumb h2{border:0;flex-grow:1;font-size:16px;font-weight:600;line-height:32px;margin:0;padding:0}.docsSliderActive .toc section .navGroups{display:block;padding-top:60px}.tocToggler{cursor:pointer;height:32px;line-height:32px;margin-right:-10px;padding:0 10px}.icon-toc{box-sizing:border-box;display:inline-block;line-height:normal;position:relative;top:-1px;vertical-align:middle}.icon-toc,.icon-toc:after,.icon-toc:before{background-color:currentColor;border:1px solid;border-radius:50%;box-sizing:border-box;height:4px;width:4px}.icon-toc:after,.icon-toc:before{content:"";position:absolute}.icon-toc:before{left:-1px;top:-7px}.icon-toc:after{left:-1px;top:5px}.tocActive .icon-toc{border-radius:0;height:16px;transform:rotate(45deg);width:3px}.tocActive .icon-toc:before{border-radius:0;height:3px;left:50%;top:50%;transform:translate(-50%,-50%);width:16px}.tocActive .icon-toc:after{content:""}@media only screen and (min-width:1024px){.docMainWrapper{display:flex;flex-flow:row nowrap}.docMainWrapper .wrapper{padding-top:0;padding-left:0;padding-right:0}}.onPageNav{display:none;margin-bottom:40px}.onPageNav::-webkit-scrollbar{width:7px}.onPageNav::-webkit-scrollbar-track{background:#f1f1f1;border-radius:10px}.onPageNav::-webkit-scrollbar-thumb{background:#888;border-radius:10px}.onPageNav::-webkit-scrollbar-thumb:hover{background:#555}.onPageNav a{color:#717171}.onPageNav .toc-headings>li>a.active,.onPageNav .toc-headings>li>a.hover{font-weight:600;color:#812ce5}.onPageNav ul{list-style:none}.onPageNav ul li{font-size:12px;line-height:16px;padding-bottom:8px}.onPageNav ul ul{padding:8px 0 0 20px}.onPageNav ul ul li{padding-bottom:5px}@media only screen and (min-width:1024px){.toc section .navGroups{display:block;padding:8px 0 0}.navBreadcrumb h2{padding:0 10px}}@supports ((position: -webkit-sticky) or (position: sticky)){@media only screen and (max-width:1023px){.tocActive .onPageNav{background:#fff;bottom:0;display:block;left:0;overflow-y:auto;-ms-scroll-chaining:none;overscroll-behavior:contain;padding:0 20px;position:fixed;right:0;top:148px;z-index:10;margin-bottom:0}.tocActive .singleRowMobileNav .onPageNav{top:98px}.tocActive .navBreadcrumb h2,.tocActive .navToggle{visibility:hidden}.tocActive .onPageNav>.toc-headings{padding:12px 0}}@media only screen and (min-width:1024px){.separateOnPageNav .headerWrapper.wrapper,.separateOnPageNav .wrapper{max-width:1400px}.separateOnPageNav .toc{width:auto}.separateOnPageNav.sideNavVisible .navPusher .mainContainer{flex:1 auto;max-width:100%;min-width:0}.onPageNav{align-self:flex-start;display:block;flex:0 0 240px;max-height:calc(100vh - 90px);overflow-y:auto;position:-webkit-sticky;position:sticky;top:90px}.onPageNav>.toc-headings{border-left:1px solid #e0e0e0;padding:10px 0 2px 15px}.tocToggler{display:none}}}.blog .wrapper{max-width:1100px}.blogContainer .posts .post{border-bottom:1px solid #e0e0e0;border-radius:3px;margin-bottom:20px;padding-bottom:20px}.blogContainer .postHeader{margin-bottom:10px}.blogContainer .postHeaderTitle{margin-top:0}.blogContainer .postHeader p.post-meta{margin-bottom:10px;padding:0}.blogContainer .postHeader .authorBlock{display:flex}.blogContainer .postHeader .post-authorName{color:rgba(57,57,57,.7);display:flex;flex-direction:column;font-size:14px;font-weight:400;justify-content:center;margin-right:10px;margin-top:0;margin-bottom:0;padding:0}.blogContainer .postHeader .authorPhoto{border-radius:50%;height:30px;overflow:hidden;width:30px}.blogContainer .postHeader .authorPhoto.authorPhotoBig{height:50px;width:50px}.blog-recent{margin:20px 0}.blog-recent>a{float:left}@media only screen and (max-width:735px){.blog-recent{height:40px}}.blogSocialSection{display:block;padding:36px 0}.blogSocialSection .blogSocialSectionItem{padding-bottom:5px}.fb-like{display:block;margin-bottom:20px;width:100%}.more-users{margin:0 auto;max-width:560px;text-align:center}.productShowcaseSection{padding:0 20px;text-align:center}.productShowcaseSection.paddingTop{padding-top:20px}.productShowcaseSection.paddingBottom{padding-bottom:80px}.productShowcaseSection h2{color:#812ce5;font-size:30px;line-height:1em;margin-top:20px;padding:10px 0;text-align:center}.productShowcaseSection p{margin:0 auto;max-width:560px;padding:.8em 0}.productShowcaseSection .logos{align-items:center;display:flex;flex-flow:row wrap;justify-content:center;padding:20px}.productShowcaseSection .logos img{max-height:110px;padding:20px;width:110px}@media only screen and (max-width:735px){.productShowcaseSection .logos img{max-height:64px;padding:20px;width:64px}}.showcaseSection{margin:0 auto;max-width:900px}.showcaseSection,.showcaseSection .prose h1{text-align:center}.showcaseSection .prose{margin:0 auto;max-width:560px;text-align:center}.showcaseSection .logos{align-items:center;display:flex;flex-flow:row wrap;justify-content:center}.showcaseSection .logos img{max-height:128px;padding:20px;width:128px}@media only screen and (max-width:735px){.showcaseSection .logos img{max-height:64px;padding:20px;width:64px}}.nav-footer{background:#20232a;border:none;color:#202020;font-size:15px;-webkit-font-smoothing:antialiased;-moz-osx-font-smoothing:grayscale;font-weight:400;line-height:24px;padding-bottom:2em;padding-top:2em;position:relative}@media only screen and (min-width:1024px){.nav-footer{flex-shrink:0}}.nav-footer .sitemap{display:flex;justify-content:space-between;margin:0 auto 3em;max-width:1080px}.nav-footer .sitemap div{flex:1}.nav-footer .sitemap .nav-home{display:table;height:72px;margin:-12px 20px 0 0;opacity:.4;padding:10px;transition:opacity .15s ease-in-out;width:72px}.nav-footer .sitemap .nav-home:focus,.nav-footer .sitemap .nav-home:hover{opacity:1}@media only screen and (max-width:735px){.nav-footer .sitemap{display:flex;flex-direction:column;margin:0 2em 3em;width:calc(100% - 4em)}.nav-footer .sitemap>div{margin-bottom:18px}}.nav-footer .sitemap a{color:hsla(0,0%,100%,.6);display:block;margin:2px 0;padding:3px 0}.nav-footer .sitemap a:focus,.nav-footer .sitemap a:hover,.nav-footer .sitemap h5>a:focus,.nav-footer .sitemap h5>a:hover{color:#fff;text-decoration:none}.nav-footer .sitemap h5,.nav-footer .sitemap h6{margin:0 0 10px}.nav-footer .sitemap h5,.nav-footer .sitemap h5>a,.nav-footer .sitemap h6,.nav-footer .sitemap h6>a{color:#fff}.nav-footer .sitemap h5>a,.nav-footer .sitemap h6>a{margin:0 -10px}.nav-footer .fbOpenSource{display:block;margin:1em auto;opacity:.4;transition:opacity .15s ease-in-out;width:170px}.nav-footer .fbOpenSource:hover{opacity:1}.nav-footer .copyright{color:hsla(0,0%,100%,.4);text-align:center}.nav-footer .social{padding:5px 0}.tabs{border-top:1px solid #cfcfcf}.nav-tabs{display:flex;border-bottom:4px solid #e0e0e0;width:100%;padding:0;overflow-x:auto;white-space:nowrap;max-height:100%}.nav-tabs::-webkit-scrollbar{display:none}.tabs .tab-pane:focus{outline:none}.tabs .nav-tabs>div{font-size:14px;line-height:1.14286;padding:12px 16px;text-decoration:none;display:block;cursor:pointer}.tabs .nav-tabs>div.active{border-bottom:4px solid #812ce5}.tab-pane{display:none}.tab-pane.active{display:block}.tab-pane>pre{white-space:pre-wrap}.tab-pane>pre>code{margin-top:0;border-radius:0;box-shadow:none}html body{font-family:Montserrat,sans-serif;overflow-x:hidden}.fixedHeaderContainer{background-color:#222}.fixedHeaderContainer header .headerTitleWithLogo{display:block;color:#fff}.fixedHeaderContainer header .logo{height:50px}.fixedHeaderContainer header a:nth-child(2){position:absolute;right:0}.fixedHeaderContainer header a:nth-child(2) h3{font-size:14px}.fixedHeaderContainer header a:nth-child(2) h3:before{content:"v: "}.navigationSlider{margin-right:80px}.navigationSlider .slidingNav ul{background:#222}.navigationSlider .slidingNav ul li a{color:#c7d4fd}.navigationSlider .slidingNav ul li a:focus,.navigationSlider .slidingNav ul li a:hover{color:#fff;background-color:inherit}.navigationSlider .slidingNav ul li.siteNavGroupActive>a,.navigationSlider .slidingNav ul li.siteNavItemActive>a{background-color:inherit}.homeContainer{background:linear-gradient(#812ce5,#ffaf00);padding:25px 0}.splashLogo{display:block;margin:0 auto;width:65%}.projectTitle{color:#fff;font-variant:small-caps;font-weight:300}.promoSection .button{border:2px solid #fff;color:#fff;font-size:19px;margin:10px}.promoSection .button:hover{background:inherit;border:2px solid #fff;color:#fff}.landingPage{padding:0}.productShowcaseSection{padding:45px 20px 30px}div.productShowcaseSection{color:#6c6c6c;padding-top:40px}#quickstart{padding-top:80px}.productShowcaseSection>h2{font-variant:small-caps;font-weight:360;margin:0;padding:0;color:#5b1861}.productShowcaseSection p{font-weight:360}# Subtitles for key features .productShowcaseSection .blockContent>div span p{font-size:18px}.productShowcaseSection div.container{padding:10px 0 40px}.productShowcaseSection img{height:100px}.gridBlock .fourByGridBlock img{max-width:200%}.productShowcaseSection li{padding:10px 0}.productShowcaseSection pre{margin:10px 0}.productShowcaseSection code{background:#fff}.container .wrapper .alignCenter h2{color:#222}div#quickstart{background:#efefef}div#quickstart ol{margin-bottom:0}.nav-footer{background-color:#222}.nav-footer .sitemap a{color:#c7d4fd}.nav-footer .sitemap a:hover{color:#fff}.social{text-align:center}a,a:hover,p a,p a:hover{color:#4872f9}.imageAlignTop .blockImage{margin-bottom:20px;max-width:200px}.tutorialBody{margin-top:-20px;color:#6c6c6c}.tutorialBody h1{margin:0}.tutorialBody h1,.tutorialBody h2,.tutorialBody h3{color:#222}.tutorialBody pre{font-family:IBM Plex Mono,monospace;font-size:14px;margin:0}.tutorialBody .input_prompt,.tutorialBody .output_prompt{color:#8b0000;font-size:12px}.tutorialBody .highlight{background:#f3f4f7;padding:10px 20px;border:1px solid #d3d3d3;border-radius:3px}.tutorialBody .cell{margin:20px}.tutorialBody .output_stderr{background-color:#fdede9}.tutorialBody .anchor-link{color:#d3d3d3}.tutorialBody iframe{width:100%;height:100vh}.tutorialButtonWrapper,.tutorialRuntime{margin:20px}.colabButtonWrapper,.tutorialButtonWrapper{float:left;margin:5px}.colabButtonWrapper img{padding-right:.25em}.colabButton{width:24px}.tutorialButtonsWrapper{display:flex;align-items:center;padding-bottom:15px}.tutorialButton svg{height:15px;margin-right:5px}.tutorialButton:hover{color:#4872f9;background-color:inherit}.wrapper{max-width:1400px}@media only screen and (min-device-width:360px) and (max-device-width:736px){.fixedHeaderContainer header a:nth-child(2){position:absolute;right:150px}.promoSection .button{font-size:12px;margin:3px}.inner h2{margin-top:0}.splashLogo{width:90%}.headerTitleWithLogo{display:block!important}.blockContent>div span p{margin-bottom:30px}.productShowcaseSection div.container{padding-top:0}.productShowcaseSection>h2{padding-bottom:20px}}@media only screen and (max-width:1023px){.fixedHeaderContainer header a:nth-child(2){position:absolute;right:200px}}.highlight .hll{background-color:#ffc}.highlight .c{color:#60a0b0;font-style:italic}.highlight .err{border:1px solid red}.highlight .k{color:#007020;font-weight:700}.highlight .o{color:#666}.highlight .cm{color:#60a0b0;font-style:italic}.highlight .cp{color:#007020}.highlight .c1{color:#60a0b0;font-style:italic}.highlight .cs{color:#60a0b0;background-color:#fff0f0}.highlight .gd{color:#a00000}.highlight .ge{font-style:italic}.highlight .gr{color:red}.highlight .gh{color:navy;font-weight:700}.highlight .gi{color:#00a000}.highlight .go{color:grey}.highlight .gp{color:#c65d09}.highlight .gp,.highlight .gs,.highlight .gu{font-weight:700}.highlight .gu{color:purple}.highlight .gt{color:#0040d0}.highlight .kc,.highlight .kd,.highlight .kn{color:#007020;font-weight:700}.highlight .kp{color:#007020}.highlight .kr{color:#007020;font-weight:700}.highlight .kt{color:#902000}.highlight .m{color:#40a070}.highlight .na,.highlight .s{color:#4070a0}.highlight .nb{color:#007020}.highlight .nc{color:#0e84b5;font-weight:700}.highlight .no{color:#60add5}.highlight .nd{color:#555;font-weight:700}.highlight .ni{color:#d55537;font-weight:700}.highlight .ne{color:#007020}.highlight .nf{color:#06287e}.highlight .nl{color:#002070;font-weight:700}.highlight .nn{color:#0e84b5;font-weight:700}.highlight .nt{color:#062873;font-weight:700}.highlight .nv{color:#bb60d5}.highlight .ow{color:#007020;font-weight:700}.highlight .w{color:#bbb}.highlight .mf,.highlight .mh,.highlight .mi,.highlight .mo{color:#40a070}.highlight .sb,.highlight .sc{color:#4070a0}.highlight .sd{color:#4070a0;font-style:italic}.highlight .s2{color:#4070a0}.highlight .se{color:#4070a0;font-weight:700}.highlight .sh{color:#4070a0}.highlight .si{color:#70a0d0;font-style:italic}.highlight .sx{color:#c65d09}.highlight .sr{color:#235388}.highlight .s1{color:#4070a0}.highlight .ss{color:#517918}.highlight .bp{color:#007020}.highlight .vc,.highlight .vg,.highlight .vi{color:#bb60d5}.highlight .il{color:#40a070} \ No newline at end of file diff --git a/css/prism.css b/css/prism.css index d783edb5..2a84ffb1 100644 --- a/css/prism.css +++ b/css/prism.css @@ -1,5 +1,5 @@ /** - * Copyright (c) 2017-present, Facebook, Inc. + * Copyright (c) Facebook, Inc. and its affiliates. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. diff --git a/docs/assets/architecture_overview.png b/docs/assets/architecture_overview.png deleted file mode 100644 index 898d689abc0298ffe0e979f8761c5d6accc91b8c..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 133103 zcmeFZbzhWg*FOvh(p}Qs2m+E)(%qfXg3{ffk|NzH-QA5KE!_+$4HDAL@9^60xbJ<$e~2@~%sEG`wZ5@VLX;FFQIQCdprD{orKQAFprGJBLqR=aM1TRW-0<2Hf&ZW# zRU}2A%7%$|z!O9}DQ!n6D2&u!|Db7y_?|;S2}4PXy;O69{*eaf7du55n4s09EYj3W zldH>@6ZIHc`K62spEw2_q9um17$Nxil24ou4rfQl<)Ury=Y2Rwb5~XKkArXg?F)@t zLf+{dFMbZYwy}n`x3}Zt!;(WmBM3vmVE94(_0Y}?Mp@te_#4Upc=h)iU@?SOR^0#n zAwR!CY~dBVtEZ;W|Gd`kPm$Xl5&z>G{(RW6fkw;{7ALiu-X)JMYom$~|Nd~y75Lr$Rc z>sUS3?SuI*a|PSO`(K9qf7|na+w*_X^Pd3xzvw~uzvLziYLA%f6>bF-LIa_H5{HFB zgWZ=Y^C2&ae#BB=r(;-ew-G68D0Wi8kI}CDYF@1$!mN zi+cGLGY{p}V>W?$n$aR}{Ca&NJihs^gk-dmn?Oyv8tdtIqinf5z7iD$NzQqtUC?~M@6loxMRTPPSdIkEZri~L;ct!IR_2>kiI z=jLo?u|FoiFO}v^EWL6`9rd5E3&9uW!94~2VU^&o-MOF|t+21=mWiKkYD?yFzl@9+ zf~kLd-;Y3ib8$a^k$pfHPR4P?*L3VtPfGHl-F7lar5jnl$?c{1{_+kpwDC@KcNO$l zsaVWQQAt{bRI#1j2+~gk0$#)4cG}w7^00d)r;?ue{0Or&Bn%M8b=c~^=)WAPHXF%2 zedk^sgi3n3JtmsF$Nl>D&UKkSiduTSH3;T;!mHs5m5riim;Dyct?=Z&i(bf62>lnh z-v?1x3?ztP`r|O@k9Bf_5m3hF_9@pT! zNFas8q7q!T4Sf{1FSNj8-@v_@yVqwK+=jxsEPp00%19_d9!d;BQPDrJ??Oz+M84wT zQfu=;?-X{=r%Da23MC^F#;XDg?rfXwSAAclRhO-1zp81qyL>XUGUAj@VQKw}u;;R- zxEE(|yDuWUNUu_J+3}_8&18wm6kAC7)(G2fVECt&iNe9l5JOtobUkrG6sk6Hj;_^h$Bh|Xg!dW9RHLF|JYqokMWy(seP-k&{J10zkqiTccK*;O3 z&(=b>#_B?ZV{$clr+PD^&CdFyZt-hyW%j_+KPm(HEyyV}w@Dn7e?0G~MnJiAdtF>d zQe!@N7&tCZIGdus(Cj)BFI%K$83q~lxnuM^T=L%4h1$Pr7fQmKMFB^Sjm#hRa|OZsO9Lx2Z0Y!xbr z;&-H^i<8^7-6CR9$8sQ7|F}Uvko-jW>bX^8s}i3{-ZwUoi}2*j#Lt8dUyo&*4c{JG z;^-RWmBu+9-U}fGQ08bQxgfqF7Z-Pbs&2&*N@`}IT%(29JOGker9(;JfcpW8HIa@$ zd_>e%7W_gmj=or6sA>TgUh6;{s52uL$}d*F4nSoK)t|JbGZpMhCrt^ z>aRuNNBq#*VZS$BTB=)5>glorAEQ>Ng3GK`;c>QGY0`@}62SHspuvmYI=h9hCFeVc~``A{IBhzrC8P zGAq_^cF7R*-UPMM^^aO9Rk zTQku=&Clf6@)7{G@9eE^EQ4b_SQE%5Pu_bW(KkuqX_0@zGvQ0@U}NJkc)lYrvcdSL zM6Z=UCmpsw+;3(0lD>}m#(jUe76FTh1*;=N3#%90@$p`thsApI^UHy^Q*9qjFnNE~ zJpLfR1&dT6*Ynk`AW%=F()i>{@M}&d;S;HX(ED#BmTs?}qIO56EA;BMxV@~j+&FzM z9vaJva{$7|DHY{E*C1aRhc#Dx5INx{+tl}A%m-q%AJTOvDn;lmwr45+m?Hq7Eov}Ew02I1ON;D}llYvig3zE>4~A&2R_^a^ zWI&1DsU8uWXpGyNDSv1ml`Z;`$YwHMch}pX<`Far?|gO+vCZIf-UYj(A@3b*x!80D z=Bit3Rr_|1T}Y_?^;lM6e}0A!A-9d+>Rz^F#A9^Q5?v-^y-bk+^O5wl7p^vO3Q6qZ z6P`ya{^PqZuVh-TcZ+Y%_Z;E7RQ2u?w z+pZX>#*M7eN(5* z9cw#@N`r*Ya=UOPg%_n|0x2D@+N_v*@k6HZcNY97j0ff6b`PETxyb`qsBs=SbS$2C zyD}ahn8i0DMCmj_;NWDXBORz!X&j(F$D*7i7P2*L(H~8dr#_U-$!)Vh4~fZ>Pw9yuYgfr7?;4!@ z)cLze{SRqt6)YAr4~t>j+o7{K&3F8YObMGG@t!iO=E;5k8lrBff$NZ)`G{F&a3^r; zy|mMhS^MMl{^N;Ev`-$C+D7~HwR~mK;GA$|8IKhmUo89DCKqgFiU#dMeMGC1OMWh$ zBy@k7O^vQ% zK+7_B8NM+J!cr%&f-c?;zj4{0sr=Wv34g^xAVLmDAz+vCc-F?@G@IjkxC9EKyu&Xf)Q*7V`TD$f>(4PKs)UDNAO0S zAPrMdHkTh-*i2gEfy&%D+HaTJ?v7Twx$&D^oZA4oH>jY-+ z?34>uUV+c+z{^x~ywTAjAWi_BKJc-pQ#~PX(CNCAVgL2zejT!u7+f$xv~(u$0XCe~ zvHtIG-!rZh=fI~iMd63pw%=)pAB$TtO06ip(oCa|>M?Qvu&fHyxEP-?NjMcY`SoZ~ zS|X&$EGovQx^Rvv5Fz+c-dZ?~B)nFAQrxp<8cOs96*5ggg}`|H8uv`oG_3N^L;5ut}zi&5?+ zw=OHJ+pnI7t#qEKCPb9tT^f@-t_P_xKB*&;-ZrxpFR^1>OduhX1hOiXLv*PBo;twl z2ps;R$ggKBGE2C6!U(driyUl?o=TUo?M@Zvr-GE$Ybf z;cbcwj%OdjQ5_MxO;rArQ2NV9X`_FZ&8U-aHy4M4P9jl;8#N+ElIxeM_kyLgjB%BL z#@Skxn(OP|K~982!l^ievYJBo5uuYb<#M>cbx->k#h=NPqz!0MnHnnAcIQ>3g(_HYIC6d6UyQ4pV7j#Hy}W;2212tZ)gYZwhMA5>cmfwC1i zs7Wb-gTX+cg zzsbix-m#DZlo-!L*5ZH4On;zWH&`G8M9iAwA^z(W+1Ubke$d)pg7&Y0tY8A7!*86T zP5p0)sr8pzb8%nA_a_AVYao7-z!o|Rwl0T|O6* zr#dxd`pqD1jYA-i%2RR2``eQd4vXOe^%AYhHVI9-Pa}j1+pWkR`&K@*eo;vSaUF2NhK3YpQ-mSo+}Hfw=Gx5lK51VE;^?>U7{U? zPSysH5izgB>D~-$Z0i{DKaa{d zSBb*+gD>H^N%3$&29;!Zfx>VqFQ+JEAc9PYtF=3V%rH4Tsoh!^GVmwcprExo*_3Z3 z*dYOs;f;XjIf}iI3+faEFrdl(yPJzUo3iM754t*=X{rTg%^lyQ3Qa)@{A4c!iCd*se?pK) z%=<6^NqoP&gQI=enaBsJR@LKcFea$(F~;m}N3T#VPH{HglmNW2HJqkv>0D;X?{*}- z0{|a`VTh)o_Zg_n(VAh=?5{ffNCiBeB#Gv_Xs&h!fSO=(!s%11;po~o`r_{DYkI6%P1xOM4F9UK_5h@-XI)XNm zL6!E+oy1rqX{GOj57PuS81@u^UQ@-IgO?)X9iY;`W!lE4p400~2pW!FX!C|JMrVE) zS9xx_tz2uRj)dg3QVH;$eTQA3U%<;Ur9``bcg1X6}d6DGGp3|2X~+ z62?G-g<;D=3sNTd#n**lu_E2OL13)2ie^feSmLl6=vgvgdQA4CF%XixaFI*rZ!D}Z zA0osK>Q>=yd${*RBs-3ZV$x)p7$_>CWltNm)owC%WOLqC15#9Pu|ccHP=?SlF;UcY zg>g61MEjZvz<)p3rxs2vNv&nyOcl{Yo?dL0Xi;E(oZlwM*z`~8FVc~ z8=N)!6Ykk52%AT+qdTc_Ps(KZY7xBQ$#|6eE69lvUwv8a`#=oNkbWeTw<0I45?;Dx~r#3#G-e=!`D1=CQ-A0TXqeyQ2f)JVdtI@?B2R}jx(Bh zdDjVhs8>BmYU*sxb}!9jQquR5qtBcAN4lHHVe z(NGJ_E-{uyggHD|CRn;MeGI!;@*FXZXVSC*eD)a2>Qk0iKa-36kH_Pg8_Aq+iWG{} z3V&GrxnpiD&`Fkwe9`wCMgyT{Eak)?!*YjbynPXMMA0l#xH}N5$i!(m`q_Vc#MwKS zPvz+B%7-%3syjWlx(2mOsI-MS)r-R*I|+1%?4Xo^5}+RM*VT zh?)JAL;3o2$1K69s4(2Y=k83ikfLh%Svz?@v1riC)9Pr!k;3E+nJ$gK3N>^RO=-YP z1kaOX^RTOSDj<&=nQI3to2M)qXyuci+@Pg}U#$j_{iwm68c7#urhWA(>jS^{?D@%p z@>`~u-|o&VrrX`wOzsPMRhXt>XD-_%J%@IF3t4W>&ax_-Wv>(Y!S8FJnpF9gXqKlh zX!5#x=LYhvX}5W~J3>uV>c+fBF8bUTi4G0CCUi9P1*dovXhpiuCSAu*tSA$MyFpl& z6wret#ut4O5XF!S(3)x)Po*A3&$>aLNTY`R^~K4j&cE#_TG=2@nL<# z9g;Z*RvIcyI2=_e_B7JkG!B-6x0aD$iGKH~q)Q1)pl0~qH)=PEMAp2S8TKNtW`1S1 zM$Y+ingB1YyzN>h-`818T#&Wx=HSJgpVk5IS#d0JLQ&pEj_6|&hucE3lJg&PCU^0< zo9uI!>oJN>Ik{$o@kse}XJ2+78h`N#SrS4T@wm81Di!A}SqlqOH_AuY6aCGHZN=DQ zpz`F3X7H3E^1C81{wA#NM1`%o0gsV~axQLLzX3F7SATr0y7n7I?hi;?adHNp)47;! z0Ark}O=H41D~5(`Re0{=+(t@|0Dcn71J$q3+$6^w&gCfVop6A^(O z)dVqk-nz)4QiVc#Nj5|0IW)?yPn6=JeG+SX775l-#6~$%Q6junHpesxeWF3*>|fOD zcMT~tor)vuo8(9YbTax&i0Kf$?_W4>hN-`7f73rOvoKI5R!&{TJ%(rjmllVUr5M^I zS13kMjEndOMioxPP+t6Vide4n20xKOvZV;$`7T$}6w zTb*@~1|hy09ugMd3(e0gWpap4`YjOqh*Qt$b$iE9yNr>TDvMK=l<57EgGg*zxaph_GpHtSk%;B?7A zXo;7-PqRhp-pn%P!;!LLx-cc%T>+^uPe@` zb!~S>%YDeB<30%TN)L}lr~yw_(DS^+0ONEbhP0G4=Ow*d$?hOSGKj$GOl-mzKBs3|5LKpfsJQx_yxHBTs(3*DW@w2>EvYZR?4v2TxR zB8aPuqF3wW8HAS}GP>NI9xk_w2BFbb8@Bs+JQ_vs+|=Nhyr7X+Da+60)-2H)D|-rv zg7627NKrS4z1e_~U`LW%A*sjJxS4J*SLu^V_J!J^O2S=NM*VPcqm*n824Y!6-JH|M z{~?ieus9)d8U8>kF0YsJj*UZC=B=+|+@_OY+UH+gIEzDhnmb11Y+xy_o8XEL;b7QZ zX!smGqmsMvPR98(PVD~0dOtXlcwetz>47S_5GI_6Nc=r(WWpl^k(N9uNx#L7t-z2f z&Nj!8pa@RA_ez+(e6-N5mrr9PT-<+i`+4(QCQu{HCQ()C%m!k6)^#yk&R~iTMSf{} zC~PqMUo^fbkJ{dSX5{v-i~dgSy;l-PJv)8WuAm1Mn_)cD@{P^K1%0b!(^tl*#=V+RSRweX*ay8ZrKS7GY)7elG z^T(4G=Db zgjADhX)Lg77y6bd^@)a5eLR=Z`jg_RkF=%*l=$)voRlxO#33qV|D4~dv@n_WP`<|1 z*0jajyV!!5nd`=}bB^llAcnhmON-=ElN1F#LrZZ7PDWeTaryNCH6fFbKL4!73Xx|8!N1iVr9a?~1RSl9jeTq(6^3N;QT%`}HB3JC99AP&8furqa4qF@F@ zsrSk$JkNY6xz4d-+=D^$Ngt2_^~xvtij6mdm@{LTtJV;-b#?wJE&^e`kGH-|DSQt^ z6JG*57O|moQ65ulOeQa&q~oxiDl4P-KH_*4c71`JIUC-p(`M`mk$J@{Fe<c|SfbQ9s%DBSdimQ{Y1pA=yRo=R2w5<2fG<1tQ9f<(DRw)w> zLkyXcL7WTedlSX`K>5XNvB^2pb*$uSa9s?V#B|m81)k-|#+GQyvR7 zT!>sQSS627Uhi};@k%$3p(wd2`L?ns=Uiu-Fl%>PUW-_`Pp*Ta#5x~&{XgW5KP0XX zxgDz?HcPatL9Lx-lj?+}raYb_-F|b>3>1?-+-*=loR>z*^1dxO368R; z){j`zEBCCTOUgoU9;XGLiO@wI9tbpu$d^UB0#V-pzX^b?AJ=L}IwXuyk}Az! zj(a(ox9=BP+$Z?ntj+3;=>nBtu~3z+Hw%Ag%>Kz0eU#`lzO|J1e_3a+=MDC2fi23j z2EMmHgE01PdkheM@Co;+q{s9vUpU+NlM78C?M$F;VQ4Scq^3b z-jYN{d7?G@6ls(eVV)JdDw`=cOprw@d|Gs}5Xd)6nNPYqQ6{>l!NuS}nDvAO$uCQ; zyGQvm0ywCF-zdm>?K%dvwvVpAK8$qUdB21*S$Vh=t6#8KGJxA+mI#w>+2|J)p z9cmsPos`}xOksf8pk=n`ZGw`nzDrV5TvXq;B#sm=>s>7|w0{YjP%tAj80N}qc!JF^ zBqLl)wXg_l25OueiK0O=rWaAb-&~Z*sVKEJ|lx(IqMx9 zGG93>5k{{ToSR;mllh1mmPbq zY(o6tREzsbpizd?pZ!aJ&k6KSYT31P{tK+W2Ij^}#(g*$hmftJDp8*KF2SQ6K)EXYe!d zWg{;iPIpud4Grm_^$r)Cff?Acbt=LJs~6LuDpU?1ahuM+@zJK@T=DVKh;%mrkMCqu z9=@L z&0;t;G80i=w--|}onIUH!2XZm`S7%Pop&b-fiwyP^-^Li47*1#(a#Trj@zA=@tvt) zn;Bk<(D{{RpFA0PTv06@~6{jw(Siy8ix=RjvB%Tove0 zsFsly?#M;#>+adV@j=gkZJ1j@qJZ{gg~pNi61JWYu^jUv;vt$wggV25IwKwG@vGB` zG19*})X1UygF)E9^v2LBzFV_B0zC;p9bRm9Esxm%B+Fr~=M%62>{aLrvPNra_kY>E zoNuO?RdRx}x&Q-Hl07*&sm3d~ngKZz;8_*!DvOaepnw8>`}yn9jym{p3_E3*~=oX2It1m4(OiT%)TnLp6byrxS`BdcT~@aKb6lu|n1SBK6|DY$jwp z=21HNMRs;K@C-T`YXdA zBh&B!*Em-u4ge(vYsQD`y>h+{3d3|z-+(GF32Xr}0i;Vz=7KV{(-}kGvmbLD-q)wV z>ULlI#O=f*o>XV;%p@DBk}K1X_!=~xEP0&_frbl4$E)KF6?)_D&^ShQ#-a5uk9fNt zMrb&&lgv+dr(`EC75x(uyu8%P^myM)mw+zb5KO8-b;j0g`?VgB2rC`Hv^Nm8pLM6f zN8c-Pce?F;P}RgzyEYjBuMa-!I0%?OIGb@PH5ggwLs9!AP&wLmf;q_oZ5qnzZ;@Z-gzRZXZ|$zP>I~<%WhP@)?5qK}u-E zJmk4uVP*m>IyF-8DmwKx)*Fc*_{w!^i>QfqI91et$bb{(4LUnQcwDX)M1XfIHPvwQ zY=t~t_S^IZEki{ok^9O(F?}5o>xnkbt6qveR!4;Ee~_jMx+AQvuVseq1|orvOMqYp zBvEH3v(>wc<%i=z)*FEK_q$wJiWmes*PrO3K*oie0aQ+)Omx~A7w2qtJ+#p^v;^HS zKyohX{NDX>$T9)AE{wjw#|XV;>=)&t1*TWU8#5akmF+OOg$Db58K4WWm_!20XOJmK zKgtI5_C7_91$`R*#@&^%#0X*zFzBS><0d#!sk%q``KpZXh`BYS(3atRV_!{stx$C* zl`ntE!Hu@+Wa|5AOpPRMG7oA@COP?2?eco|yI@;+y!bqRWOiKN<-^qQN5^hNApJ4pOh*s~jFmy~G(91({7(i&}>t0b# zW$&+|sY(hm%TbQ@3OB3dW%UnWhz_$8>jIa;*5RC@80m!}DL9d;3IL6q??bj`2i6Np z(K31B2U5j2B1i@7)TORK??IE@>N^ur2Xc&lMEV3$6)cnwQIEL+;kw4A@Lo92Q-lqx&6BXlk&vk}h z)UJA0yKAfA+jxC5W%#r7=9=kzX4!eY(&tkuR8kz3e*(STESfpVqo^3=jluCRb!s~R zGeb6Do!>Zf0)M-4DiRyDaeUMsmnu!G)ai-1Wv>!5uj6K_kZ;@D=S~uNpk3hjrx9l* z7Sau)a!*q&79XY~&~C0)M(v51Cb%f5!Uq#rA)AqbezF*DN5R1rt5wSP2G9jm*B(dD zF_d|-=r+>V-p>nM#HowZ!U(qAUy$zXDRm@J!fl18lBQ8%KihntU0ZX9C0yuMnT3vOeA5azznq7u~ z$^sUj5z(YO6c;p8A3HO)10;rny8-&~eu2eDQ5inh(pZ6Bu>+WeCUCqvQt`}5CW5>e z!QWs{@hJWI*+)jxHfbj@Z?1IB;e31)7ZEK@4L&NFFk>fi2RAl8_wNy6ZB>kI^Y3a$J%&HR4Ge5F9{S1Wr#94{P0& zLOOq;y|ts1DETqA+t+6COBRy?c-CP=zjuNp^!XVR2tXG>-mTnY3P#tQ zEa{EduzTZv2_;4Yzv1=eV;+(3NZc?m z;X*TZ*+arMio$qyd`Z5F;}X(sn%;^b9micUb)HlkKY)rvB6T<sgq1%~x2&;_g85{2*XTHrPlk_{ zjx1)o+?4{~gWGW;^IxWQZRvh$-e=nL7Y;_a&2|=y_8rHl&5zQ>M&KuxLWt-0Jbzmp z=LFweE>}k<2&R%NN&|Z7`eNuJl6f@Z4N-*P&OBUr<8}0bc`#oaNvTpc+#%_<$f&w!_Npsa5LBi=F=9T9`z?3!ei~=L4P(1OJ zRE;jwGg`>kXONt-z-nYj5!_D!O!24ARHN5LRPT`kyg7FRcVFvCKY3Y5l!u*UqSx-D zAEXVlKfyB5+q+d-zobI1M-VoPYme+NrLe+~flp-|M2XbQdLT|^-28M?eL2Q`y2WUTR zT3eY9Hn18V=*iXA2T9&9fp!Z`+E>HnSJ&d7h?qi|%HKBz5%>pJt{_zJw0{f7p%Wig z0?zwVy{#eLTHjPbi$A^BTcDGrsbwSlO4dRdL{!EmU`84EHzd$E`v8a{d>)QG5EkxL z0XLl)QE5MdH4ubu)!4>e+lc5wU=fBwMzctvRwM?tsf$l6Xs2ahzX--JZqa(AO`E)*Js?$GV4|y+5)T4*mz-^v8}|M!mx#awBN`^=c~CXmOB%XsSl$=+LjO zqN~T%{C_dv6-HPbROoi1vMTLw*uPfAKs2}*i?^QE%RHb1Q!tePG*$hHxjF~{kuta- zTcaH%pd0|edc)*N6&z*MB2Ze0<@7^{N?{Mn|n& zYplhX3HKUz_e`vu@u#u90mUh^ehEA*8b0J%-rtR$3t=Fve22d^&!q>hI^4F9e%EU# z{_}4E?4CyBZweUoJ$G=~INaNEUS=J5|JuMl`*9y}X6tDY)*wWv2}P`dKLjc{o^GG( z&EFlsQ4t*iS)^iZ@*yZ3#}~(*yUv3%52U*irnBL8$)bMZy#o8qE<&eN$MaYofh;qR z!0qhT1lWIrzyr~hsEBrEo&^hm66!F7OHTps-G}=2cEu-WlH6rt!Z)N9HwKELygN{P z&pH)?u(FCdC0FcfNle=Q-my;z{9a*As}c|b30e0%n+1u}3xftrgY3~P6PL3=`b#GwgUJ6)TP;+<0{V+S3^2xEdzdc)~@_I4;CjZRI$ zSZj9AQ8*rljFy|Zi^BSO5h&0%An4E3Bp}}-e-p?)zLe%jDJXk*#I5o@VZ;>%b`Th zLJ~qsY&yD+GHD=fS*U@OD?PNYuYfX{ zkoS|`7Y5(9?G0*bW3Hu$6jqdA{S#z_DL3;?1R%YKYy2My_l z?C`=yyr|nJ7Icdxv{|TVJkYIO`-&*L&klQ%i3ogSVi>;Uc{Xyy?M8>r2=&58OkH8DovZ^rjvDP zzcTMv%U^WV_eie1+u!nuRD`DZ-f^0)AaF9PoStDI6T=~G7}mQ_&2enW#4!*6Muj2w zo)$QMm)J*$)a0k{IpK8NuCU)%uHrMY0#h3q2WJ8NAM1%HKbb@YQ>k zzu5vp)YA2hMg+RxFTR9Q9@?(__I@Ftye0bdq!2sLhfP1pP(F$G0Wx=3gZOp3a0l{f z*-A}Oz;?OGq?0a#Ou*sCee2B?()!Km37dA6Ia(q#_){ntZLsSntX}Y@HGK*liZJl_ zu9gUI>Zg5ryi+5CZ7&%T}2}`uV*(4l6TvvEgSv>E4Xh?Zr@gX&mEXrF8v_7 z_Fl699;=RVD2skejxW))br=cVIX7|}XHvcGqQNs)qjTapYCE9C)a!-FRP{X*2a+!F zg70j3^TqIu`E)BVBA5-VjxT;J6@MLSx9RyvG-H}4n{f`Xa0<5#C+=Ia+`w%OB&l-r z8=WhMCFMM=?hPTI2ahNb4O-AAK~9WtdF3e}zJdTh%EBq;2iGgx;PQ6yr^22qS~~v| z8(JS=t_%1cw4e~F=1Z5>%U0)^+j27LWNqJ&wUK?NIasW&pVO816{zAixOJmA_?k-; zcubHrL)>~SCjQ-ShwkMwS~5m|QB0$dBrKFZwUArb+cVSfHIfH$x?R0Z`pOma&m?Gs z&!w(P=UowNCb>?wO81;0If%*>Zwn*C-9W3NKCkQf?Jch%k+W#V((%Sfv1J^Sq50iB zs(P`ebPU(oJm+2nsbJnWI7htcGF`{+adjC_PfylMn{YY0y0`P!kdS2#(}76ltKymR zMJ46v9BGvtIhOKVnL(2RW$q%iV!ig4X_%rCZyGq6W@KQM3-@z3rDJG6WgIOF8Q2~^ z;dR`4<~*Ds0NM^8<#KkhZ^(jMkgnEzM4eN}U*5Jo@-%F6yZSiN<^?qEDjFsXp0|b3 zfx)*Bn&%57!UT|^Kg82+w5U8v;-}|m=7JunDiHc_Hjg` zQW;B+(aFdU(`C?~j9YZB+XEqn&-Xy2Qw&i^kY6lGlf_UyF)pW^TDh~g*J7dIC+Du3 zZ#kryuOn-G(o#jeSV=Y{Z-@w$;Hna3T^tl2Q$}&ldWIa%tpbWL0=kY{53p$+WIZdeNHH zcH1tHX%gtT1_0*ls8{wHm&ZDzs`gNEkMjdE+QFUKa31G-&R5?zP~Xh>KI~sW>fb*2 zOhw0*=b|X06epAuPTDFB)|C=+S<~O$C1kjMBI8(6PD3AIXq?fa@C|%|)^gl1b3$=6 z^+9jt=%=^bll+d%=)F+bb)C5j`>@xc6(pU=NmL(JUT=Pf?U5&*sFHWA4hHwXq2IZE zy`3{8BKcxUXqdC;>AE*}Miqk7{$oDd_t6c?!BTVaH+oWm+g>A|Z(0vxLQ&G)0Vnu! z5RIYvx$l){Cdpj-I)y}xaq7X=Br)-c;{^sBCa=aVgjv_T*VaRp<#*!cA*Ul&W{}c2 zY0xU^RtW25#xM*A?Fp0Vq0#q6HOawj(rf}x9{lwI{X*03DJG42@BGqza$q9waxP0p zS);pHHft~?lzvO)9PG2FlINU@p0quU_d&E<8i<{DHk+X?(4{L)#etjB%^5+T;t(tL zJRiX3ql%Oo2}YcMXobrNMz=S5kNz>aOqg6QeLR}i0bMJpc=;H1PPU;lD~SqLMC8@{ z57uRysmYpDUhlf{Lm`Q75{Prs{RT=Q(WhjtCjvGNg|7r>Yi(wX*UoDlaI8?cPYd^A zl-CsRe6CmD`!Yk9W{&}TNG68sljRGq(@56#Yp?56R*Rtw7I@;Gh(HDhtZMO0i(H$& zvqCE_o9POR40QRJZ`vG5AFh+0?^jz^(~cx^I}gur^n^cb#S}1XfIIKO-Nv`!glLfh z?!ll;<1*_VZIKA+Vki*57^^Xe`Bumt$D-n~zgw%(=Jg7Fd$Ij>8|99Hyl$mwz@6uX zu6Sum9U=E_3@feIPl+#BRs~kRcV`Ij_%LVx2mx9vlK0e3snRw~AFDSARBJ z!-K2ZVvTR#K6?4kQki@|^U%(&2}^B}W^1~HC8Xuk zzNys7z#8I+eQF{C#v8=|s$Qqm9H*q{>o3+rMYX$g>o446-_%bJ%@bUZU27#B*WzRc z`DXdPsDIFFGv=KDm&OJ*ZIN0oXfe~?XgA4h{D?M{1lM&&-O5hQ|qXCE0nUa0!) zIGAzSF7O{^LxW6apPKp=nIP`D)shwoi%!MsV~ZFyi^XJTD)@-L6rsb>G0_uz#?LiH zNp&ec^J>KoPYcfvy)S*PLN{3T8(yC^-Ue-8307_No%erLbl4o8Ycumy*Vx&IxY{hW z%;jmPfZX8y{IgWySeM49CY_j4!Yo{m z(ROZLZXG0d6=a&cnJUagpdCz_Gk8xyLQn|kmXaEoy{Zg4(v$&M}v zSNIx6_F_zJx_1GK=HpC(zV${G*l9?Kk!&$`KxV04ZI-hvNHidN?lWtjqX+S_e?Z1o zT8}mKotv;#5_*HW{M3+{j-;tnIbY)EZFil`yh^LfCpgDVG665suJeo>oPq*__a3cH z=hvoRXRlHBQUVb0u7YtsLzp_b`h zT+f=`Ug0^zDkEEdIFoJL&z`%k>G5VyC;tsxDyL$do8ruo-Sz5I8 zbyvjRp!%g`?}*{Ehp;OS^{-}t!y1_Um1yq-t|6GK^16QH)b> zI5rjH$WXfj_Js-*zf*_E%XbSXXT7fM)OER2E3kVRV@ZmPH^4fv{8~9XNf#nIsgb9K z0`Y=u(w07A=#oH<*D%Iq@Q|%q?=R5>9=-4-Mr8T*5kasre^5s^GJYJ*vV|#XJ+rqDRgmK-Z%MAU(K(?luAYF zH=C%d8Q$II4w1`>*_P@HT z+I*ya`r7S3^7#@ACDMfceuJ$vT=QKy4Vt>_{{5SHwzHGjWK5swpbP-17b6M1E;gQ9 z9R3tYy{8{5KoYVOfO9O@bUGsrvdy#EXvtcP65y1db627#A1qa_Q!0|q4@(VC$GBFu z0DXU7CJ29G2&W>~!m_VNOE@n5KQLXZ!DcmI7B1u`0(#WJ(#u9#{lSNy=j?(^B3<;> z=EM1B^(~F7P36|j{^W1=n8GN(xY5v)x2sK5*3mTTVimnEQ7ALM8eUh9Ub zN-Qm;@<3EoJE`$+#sfPjfPGjthv*%RfMAeG?eDQ!plHzqwvAR=gN($lnb*GoK2UdE zMYAqR6z`!bO0Y3WWCqf}g4V*hNJotBL4lOH%V_0$1>7%M1oHj4?fPy+CcwCp{|;1B z7^*#9TD9Y0_&yq!jn!g{;#WNqq3Z!sr|vM|(EX+J&+P@x2TEeI!CA}vBum^>thEN{Nr)oN$&0694o8Uhx zUN}7Xm?{PLVMZ%G3-I-3!gYc#Pnw``o&eG!NL6Euh~+joI$s`>>wh*{EuA17T=n*M zzT7)5pp!Ow&-^|uLdY;q*`=^o-#n3!PV|(uT&iUC7)qJj7>>bu-790InoOk>SmS8< z)PI)3s2C%QCo<}Z1ywSWPhySKLHWnGE`$qRE$8?(`n+brQ`UE77rR$YJlC6z-1-(H znJm859Woo8RCuq#nMq~+Hr{nC)f-i3P@AnK;b#r9hX>ii6*F>lzK8q4t6X6e-S7tFgFyR#~OoJ zeIRrq#*iY$`d?uan6?liVV*8mup^33dOQCSmhy?&_{8Ifu}sinv#naL@oh|B99N;~ zHeO7q;%!e$Cu3?`l;S_w>hj^%eFKU5nM?P44}FEjYSF=2Vwjb>)QcTKcDhvIW?e%3 z{Jb=ZK1}TR4@^Meh{5O8t&?cgdpyJCKThl?e>~r4KiEX#@_C$m#E??y^f`SPUr%zS z<$8FjvFmKM9Itp8Sna1?e$U;8ce8#yEdIgo*VzH?Di@pJU2}yCu?^>1;3Wvg1__p!c#^ z)F@W7)?L|r+DqZt`Eag&)UrovCE+gGmR!|xITAyyYq8s%uK>_3x%^_4+IZPcszf$% zT4pHFrpa?f8CFbW^GSC3YLN+xzI$nm*ZZID!| z)@?0AqfR7~NyrK}Is_=+FEAn#C`sQgACr$$?jXi%Gv6jCk@XjESiM|NnQfMg>(S<$>gbd>Jd%Iv9GDq5_vw9)sl!l3F!g zpTVW4jXTrjF<0nz;&v@^)=J`bGS_B7mHHciU}=Qr;E$`TPh*bKXipN0%E~=bJ3M3h zzr=@@?*YIE2l7B+bhJ4F=#SnUZr7S7*Oh6o?cqh5aI>~9H{O3=K*k#hC;pDB;#$8^ zoqTCaTDHViDwt0F*sRhSOQtXPCsXQ5Rjl?DaK_NN;be7LT6lwiqrg|TgZ*1)cpTZq z`|@zSC4T#Cz9Sy=f`~KY)sqTi1R0I>_PE{b={qC*x!+P|U)wkBiQo>D-pxG5)Zfl? zeS@6K=~eg0p+uA!e}mtS$DcR}_Pj&$i1WE)!|AqrZdT>EArUYSD6&sb04mM-LSa8r zRLZDLuw#?WYBrn3Ury#jHJW$RA?4LmWiRQ+n_29{ z*?#^sh6|@GZ^>KBp;*tmWeu!(%l#QfMG6|1{u8PaHR19=BVwmynQBbR2BX*MA_?j_ zQYBJ=JFv<-;D6hLus?jrVJ;qR^}7tfNjfEyPyKs7REfdspr6z0QQukRM5i*osQ$PI z$?Dc6qXOOFbTEGI)Ck+?JVw@UwTiP~>$pGj1483$;ll?5C@HI7SaDs<7bPtOrE{3d zX}C`o%{lz0md9%8R8rZVsW%}Zm?;d4prT6>xm)YeXB>@>49;UTp2`la#?Y%N$dbmC zU(W|5lOl!3296u-%Zn288e_S*Snl>vR_6{;hGh9|K5lL;4y09Q)kSYp7CtORO>wML zt8CPZOCjeHcl#eb(?Jl5!o{ImkU=Zhw9V^N0gn!#ZUd7(y{Swlr``$yGnG=yLh9x! z&Fo4Qv&TGM{B5|W%nE6ofiZ+~U(Ob<&87QpJ-+Wz@YL3k4M>~mmY&ut4YQ+B-PEZ%dqx)SdLrb?zQ*V1HcXaF76D@_$xbl_qZsac|mn zwiMpMrb=#QAjZnaM+2YJ*?Dm6;J`?)OnlQ4;o)Mnn0PRxO1Jc3=sv^i?qaF(@U`9T z+(Ny%^!R*ka2%DRAfds0zT-!IsFT^$r?6&?k5!Taxf?i3d)^UD#y` zt4DbVjRIc=51rbUc4d0wtHnFnz4z-9J|)f^D=N9j*s;}c77x2yjBVfInot6<1qk^XR}-@d-=hOh|jZ8BB$ik zF+$U^?!~)Zp<5`uEEnmoQZLmB*@$yEmRLXCqw5FxqY`=WYL}80hRgE~ z!K(UkZZfv=Vc~f4*}9X!y{6sNvuCIWJ|5GJ5p!nD#6%{acz&#dk}=byQGK$k@sfl6 zCy~Y&h1qrf_k^^CBx_@^5K7Te&f2uw;)9X2O&Ng%sVqx`m~Wh_`TP9E$iSr zqC;=nI4 zS~JVG$+Rk#Dt10hE^k}@#c{aKC%|E~%8iDGH3fF-={DFK?1Wp5BRfuHPN$cOGbZI# z>tO6DE@Ji$H|_(G~yQf z@)s^*(CU)T2s9C$CaVI~mOCnk=l;yx_w8(cx1r@_dX=(;G$yl3jbdMbnEY(Tf8O#dv}0&xI&{4IvXLdkBU=KIVC@H^)p?@$`` z5VqStx(ruE_56yR2wuc0)e=h+yCcg!qfkY+=MJb@blMtXe1;-1=8cPFQ^X?Xi>LSL zQ{`ba(7fL_@xJf3ivLiS#XpP%p5puH5ezVX`yrCRcCOWEyDbz@J)O;0tm@_ata9v^SNhEEnY;6$lVMJosMJPSY9e~9Ju%r-Km&CorP6qI zjY$3621_L1e&`mL$V9Til+&)_4TZ<*GJDkZd33)SAQ$X=I#D1G+D}k@KG-VJF0t?J z?T1n)BXynM`3goS($hMD@&gX=NyRFPj$1inPlhD*Tr&YFtvS74LXTxK*W|J|VFE~u z;VmG52&${&6%>*%goX^^?Jb>@3UwgqjF153+%oixO}E2eo}^883%SVe8wp0hoQd?O zr}ZUJ^clO*t=|GVDki0>h@K?zB54{tI8U+wI5eK!FRHxi)t9c5Cmm%vsykk7HpGC7 zum+^g@DUb5qayfL$HPn}k{&o=26`9-CSvs_W6^g=mqii1>~huW{DDPkKk)jno1`&X zZJy;S$55H$Bxa|rhCA%JRSeE8GRbriz^Lq*d*H{oE1mY^Cl>QUZTi1Eo&pi3snhK% z+(mwt&VTJ;+KbY^PPe_mW;JWPaRkF(x!&TtDJCiOSJ)f)o@xAklb)#UN7_F9Zbt&7 zi2>7*1aEKB=+{dP!Qruhzu>G5MkX4k3)QPFa_^dYlUeyeR5!kDCus&TmR*Y_**A?P zvm`^MQvrKk=r-fEP>zHRcsaOIGMlky{}Yryj3#RtDio zt)enTuS%!YX|OpYKpjk@lnloupBDkq?UCMK@q%>n`xcY`^6C4G>JqRS@klRCfQHF_ z^~RLAH3Ky?NyC}U|Bbd6+HcDtn=92g7L`1)ES~n|6_JCD915&TT7XIX0+ib6UMri> z3uajdg883=;z|()Z{@Z8nBU_DJuD_?yY+D7x!momcYDQryAHs2^Ya6BT3e}Z<=C+z zS;>#W2_T4f;RLWyI+@B@DR;k|KGzjUeyf%Uu+HLc=p^tb96cohu60 zYc>_7){8ih#`OE#?E9v}U9H|E(yTX~Q|YVhG~4I#<@KH>li#YSLDEF?=E|T)&_btN z^-ZDPa<$?(@i>Q!!E_%v>EV1)C3{mA;=fs>gulRvdjf^YxlJcO%TyOV3!_xR~E-D~gP8O9pk^mT>$?A~4e2HGgBIzWFADdSxy6>-xCtEKFT?_5%R&RUN>gOW4u@SWcK#u(pZ=&S7_Y&=5 zwY1Kr%%QHKyYhFXs1U5ddS2TU1sDe>;syzbNrQe(roAZm|2UzPZGH)x{4`rOJ*^wmjl%JHUw0b(NmZBQG zzi8es4X~LNZj)uXn*H>kY%1(q<@DE3yl5A#xPEupe>BGu@TRl9N@Gh^Xm@D_SUA&} ztqhYac1OV7PA3Fj`^kkiS!EH6I<{(OF&k}ZMW5PjHk_B2)&rm^EvM0T^=qLztKBM# zVBphy@q{wc4Gr5xyWH1_e!N z-Jdxg&W_`2vG*m0!0g<@;FPv3_bbpHJebZk{62?$%pxoCWB3hXGzO#$FROO6wdev?><53ZSAA`qTtKWOm5dkaW z4~+~;9A^Q>nY+`Yi89N4m4CSpGcN{@jSvgJ&~rV|7JHz~j#16lnQ!c)l3c5E}?80vV8j z>oCJazYQ)Gx`bM}W9{@ek$1-ZpMTCDNfw#v0GXFRJv&HyWa64J5AWe81WDP$t|HDN(-lV|=ytgO`y4m_ zbbV}ViH%7O`#hmbL6TfAZmp?P zUtr%jc*(gJQpa+zCy7!zl!qOztve23uNJ&WD7~OdEaDR8GA#Su0A{^{x z9PAKvDw1&vWrQXRnF}b+)@brXSs-SdWo&z4oxz8(3K{p;-5V{3QeeC){UL!smOc>P zdlpj2A&B-<s5BBAW##?8=Wicfd||O!e@^Mu zy7~sG-Rw~ow^~LQk$-eOUtO6=ggU+ZFIG~aJr&W31YW80Kc+Ld5=1bXE8WJL+Jh@HC zu$Y&6$|L4-=z+mO(XPmfeBJM6^Xb9bh{v1#FJtG(+U50?gF{1Ik?ty8h8}O<|74tR z{&wppLlFOo-D}09DZ%$cOq|ezm{1zrQKq+-@K0}7FgRYE;2gp}nruABg=5}VNm=Fu zLrm3(ZVJjG!uXl*lVsZQ#pJS-=%AF5k}G6IayIrqhZ6e2X_1=W-J?`)gl%PdtrX(m znOO~IRH3Kk{+38(Yqm&i4DC!>UbSG^{i@Bn6LH6g5jG(f0RIRDsVD@Sia4Vw;%ukY zXu%7S?oG+tN&UlSv3v9U#2Q5RrCV;^wlxpNmgeb>JKp)3&+i%!OE1@S4xOB$C0-Q5 zq$7V@B-RmYcnk}C4dItoBV%CTmk``#yKHW!fW|+!XU9%%wo%#he+DNWNo6JnR>+wO z1lS|FBm1E`)2<15UR?<`VwRvDzcJlMDrAoV4|ks!OaZTAvjxpFdXu|}kZ$N)i@oMa zi@o|an`bN6z^Dm@hraha!q`cAI&jNQNQkq!5zqZ@hge-l_|Q<1+jw_J=?{O2$)>|; zeNSv$7=f`cEd zVxX;{72}SOiLL*KBkZcjU1pY z1@eF*h&gR=eI?_7#d)#Niu{yO(+LO@DmO({x~;}m7Ley+gHmP8hwiL4wgdaOqlf*| z5NA^>yPMq2q_K&nr*ERvse-*MDc9NcqGHBZDcF1a38vzx6667S?_n)J-Ht7{7RhH0 zhk`O*V=nCGIz|WexI&x}Z|Db*@%{W|KTDS5;gUUdU=Xe!xYy=d4vzijKMm<{5`lk* z*R&I74>rJLA`v&SDC=RI(fWcX`TWOj+l!~yCZa2*s4^tNKo*};kCs+G89F$G*I+#$ z2M1R83_o>VivBb^)CD1q3NESUwhtey>UdW?R2ZDNvOqKb9@V$+$B!S9Fb*s`D|Kdv zd_@uFYx$HfLi}}xqn6MlO=n~L_kL1h~ zzK1I${AW3Gfh||*vYoG#g;x2NFP$$elno90K_hgIy5_0KYTdZXWpls=F^#}~W1DNL z=6#b&eT%}}r7&NfX?KuC?=t(-f+8FmeRIn_rOAB#e0HpKN2O7xoZ*@e@7!pKODrWZ z^`c;Gh^e@Ku(JC*?14bD)4}D?R%eBH{1@$fi6n`uW61bWBl}P8VAf-rC>M0@Uknl} zdo}HOZfX^JFb8l0`dtR<(+tmjGr#_%QmRU&#;{5reb1wuG?4tyMtR)0W4@FxxdWm1 zO;hOQhpBA{aG%qHggfWt{YyE;fyUS0wVtzRyfRpsG zaOn>DD)V5qPDQ$Eb4Mq5DG>T_p;B0_GBW)I$5V++##C1*j_1H{tf&~_GBD7^&FVAJ zm!hW>ypO#~hyBu6x9}$pJfl688ol0TZ%L4t$Nks)41l#!KGFvp?Mn7JIl^LLGUu3g zA;V2Hfl{ihpvn|#sUg_zrq4WGT&RI5vj4_TNk#^lkd_)AeR;ZPWw=pmxk`0^e~Qoh z%lInQo1||LxFaK|pvNlqJ5;U7g0dQhS$}kIM%a`#xK&I!K^2{hITdjjI6;G7ZOj&6 zJSx;TW-J#QUl40TFxcVP;9bO6Sv#xny=r2ht7<(5+iKConVBzNAHNYcMvAhZvQjT) z-5{YOB9K4BUSI6}{fD&t$XKDAp?LHB0V=-Hh^FERp?^az^mkWNTKD zR~kbFP9id#pRXlFT9L>JJQvR0{WGsMq&4_rI0mo&XszBo z;!k$eU#=L3;8yY2sm*J4I348pJ4J<>n#&~Vlx-2w-+wpTAH(6-y4^lezembvGL_oC zdy>cIWb*o`(gtZ>IBg)DED2(BAueG?qRzV(g$JB-m;HOr3t< zNxP#jijw{>O)BS*0T12T)=;Ml7AFfIpYL89EwV6{zQ`B{{yw|q%F0gecm)X!y|S`$ zTtEhXU3&~f6fbU0J2V7TUwD;Xr$diEcL~Er@uVq}%{uPynI<2r?1Cm2Es}+uWZ}LA zZ`eFRCR-t7t%atP%}wt7C)TpEB<0BRtDeG=Jj{P(dX&FGC#06!x1RLvjtC)jh3|!d zCnxDtgORm50`*saH`#Y%RI644*{eB^&cp5~BsR;6_29ZOblTGSz3u7!3^^1>IAqgJ z`B!#l`(M}A+WHFW%{6P>F}A$%YK0MGX?HuW{2VgaVE8CSqsqLWuD&hd9YNzZ6h<9p zxJoO+-sY9W5rG-R_T_$Eo|%)W#Qe!xB$o+>6n}84$^aa3A*;z|y?g3Z=T+UXi;IO* zvEG*LA|f?VuQtW#1fSvCG@TQ|d;pDZOt+Vr(P-V}v20p&(udyJrjd*JF=VseJ~_2k z)dR7X8Ti+@9x|p%FGfjumvQ0Dq8|{s+(c$i(y<1v>F51Zu?Hm$$kkjQm0wn@!QA})@o$IfKxKAjM2eh=R zK}?T2DGaQRMsURf^bdg$!_U+K(9Z$!R!7Isiv-;wM|wcv=SUF16yB~tHhMrRTpq?O zZPH3r0cR`T=<*@43zZQA2{0_?0*t$pxJv@<0aBM}W|oUpL4Buc^rwqekPu-B`6E2R zx_-j`7E!S15^dG1%~sWWJEYsh@LmJUxPEZDVja#{@9n65p)!;0*}Oh%ys$CY*^*Oa zSO}3YwzXKEr)<`>8p+o+;<52mCcBZM8*$<-zcnEngY0yag_Raynmp!@VG%>USos=9G3c;ps9vAY~JZ|N0EV_K7ST$~sH@>lH_Y zz}$Sl8#v(X>919`1AoFyJ}1!ii_+aGKL;H7ScY&dzobEIjzBC37;SVk+r>(7-+D{S zkAAT{e} z&}A|vPp}uf$;{q_`^WXPw;$TIyM0~y_hARcCIlhJbU}#!B07?^W09DJ?7uf~O_HQc zU9H~P+8&YwZ_QxV?Em_3gE2ZysnTl5vf9Mc8aV%=DCP9)&8q`~ ze$N=*QwAO{x0;!n%gXW)qu|XcXevbHDBLZ~BOA!st2QNg67GJq$MoK5*eZy1_rKY8BomUAfi*n`Um%?07V=`(+r33-(Nvls0ND+`j^O1RE~qAWF?+;>!31&ipI4 zt1Z7to74S3&bJg8rD)CO%x3$k+p9z9yd0t_XrDutwbgBQ5W0<{aQD}9t_GJ3)+B7{ zV!x7+krE)fyHJnMi*%3QdjL|&oAA=B&u(CbQ6i;8g;wQIxJiP7btop){$c{cbR6nC zqxp0ubJpPccy{#23Qd=nNI)*roui9OhWci-X90f$k?wfMO6#85-|$ly-tp1Bt|1#O zX2}m2Y@XEvIf@d$#|K)zU58#Ej08b{2X}1kN$T_)Ctn$|AV0K2l2;Ms1Don}GPgt(=K)_l0 zyxI-Ag!u&IwoHC6qMZ#G144pYgF_GZ-b{o0&;!H!)}xuRBDJJ4OVpo#R&?p0!tTyY zRl2-6t-reNJ(+Z)J7Z&myC+v@H<)NzMuJN;#uI-nBL!2G^H;`I^bIuk5FwO?-XX&~ z)>I!#rooPbL_w_~FeEtg8(Zr8iY>$CdZAESN7d(dvC#&{L^GD)lC!0ot=mE(a1@=& zK08k)E6gDu_9MSoRyKn@q{%RQxMPx_-UvLqIr4*Dzsz+5e+*V6f5n%8ve8BMxq}Znnp^$8->O8b~ZTFcSjPEG%;}fyD~y3biiqi z7f?IY5hD3{Sgu@YXt4Oj6_4wb!t3PfUhFqpsj_^b5~XmK?(Q zSK160hKoRS|IvHQj@JzKSsHQW$V5lR+NFgPqU5}y{k|DkW*kFiSfoMEUGY|raZ{my z{qdd}BXO?YfxVgQPHhADeuVKY$z+#`_LY%7#=-Of#P1R}Mf*Al%K{vOQhd-DilhQ% z(de}b-%;Wm!3x&mZqP)=Nx(!1n~??fyJWf9=+m3+H_IBIjK@_~lw7io%hZ&R!uGO; zg-t*n2@f5nI2L9XR}VXL1`GU`j5?ywJkK{4CqJkp>Q%Q?HaW-%E=9tz1XYs~Nc*@_|HM6?sxDA_LI!v)XdN^dfcENwONZNAtv zoyz#08JHBpnwAQ^NiLJE(4?(V@YBJ?VUWl+rXxAZoOBzS>R1%qIKiLCmP~0~U0**p zKK_SgrNgIa(GqEESF`9geNOioZ-nm%eZi^iQIX zBNT$S>4tN&^L-xIqVnP1ckw@lMqylt-#C{*n@`DOvKmfi&AK0LN%p=P_P5EVwHoi< ztRq$Lil6tjM)_1go^iJLj1?R+=$hNjHJQ@BPvSQ9X%yKSUh%-M6lFO8(ynH+MWMF3 z$6?dv?sWDezCQP?2_8+?%1C$!FpdGM~X7e*2Q%A=V1?a3oW2S z!#k>*uM>C9>vawp6v~P=?-5Fw>hlhlXjq4LqTR7M6eg)9f|Wuo|v!tWcbMT2X54fd!r| zs6-|gv^%lh;%2jk3!F#l&k0rN_qwtd+L$4i!=+W`Jc>wmZaR@xRZ)@Y-S}BmB$DT7 zfk^lKDVn}X6xT>cC1)E&+uk_dAS`wFdU>qDJZj7tFh>Qe!DpKO#q`CEdoo^9fGJ?V zo0fQSh%ffhZCd(5q7qorXcWq|o>{Geqi%wJJ_*cu>A^XE10y4N$f;^Q)9?MSk4fbv zyAQh7$UHJ3H(*pC182xqkr6Sz*w?U;NZKp>EpB@C>B-G5 zqLk0;x^}B~5@O!s|78KFs5B}%oS7`tYh512j(I}!X0jpvk9kHul~4lAb@r z^oeXmytM7??3R!rq6Fn1u_PBn&df9lEhw-&{xA1UcB^Ha4WuJ*2To_C#H~WT4!1+J zjZ~JDmh22?*T2a(il!RsYLAS}(7dk`UKcd3M4hv_0#I1+>m;j_%1!w@?sO8)Vj}Tx%63d7P=;{KiP?Y(^aIARAQy)k9nc6sSX-`U@{R`tEUU~MELS9pOO9^ z(;SPz6`M0R+OSu2e!8+_TVGro6V9BkA{&&H=!etH*5-ZNVQHema*wMYB|*V}x@&ky zpJPbojY0J*%+Yc?UZ+yCS%msb&ofn1Xg*juia}0r*V-OLx;;FVP#BU!q+1Y+b~Y#S z&ieCUe0j!Z`o>uplW`ck3zZ7cVSt8?7Zgjb$d)_p)J+_h5bVEmRA6``Fol9F+BNbQ zlSekUrUeIwWx+tf-!E6vYJN9JObS|c!YOwrrqj2-Z6vx67{Is&iQVV$d4z&ZAf#Gp z+;rxq1PbwOL4Y~^C4cT<+^vSu!@z(GcL{z7z;$M|-XMGf4tv<~LPfcDTxi)wnm`c% z{|aSaDnJd-WqEXb<$!EPdg6l4AIu27Y@4g7Rt@QEREEq@cM0YF zc#HL}`_=iwR`MU`T#}k*?iV1U?oUp95U|#On~#IxJhTR8HsJ;nd7BKg=ci0Ns5El0 z$)JI?HI3bYfh-7K5(X6+_I<6eD=gR-xfDvRmy0YfFV~CpP9yqtIrSAKHVMzBYCR>) zK15-$?H1R>`+Rxej)nW5p->d9%lJh$XOA0T;77iYc@?L)0>jdOGr)g?2+{z&njQW1 z5KE9D2syevVCKv0)CNTZhCEFyiwcnh`)3prlUlumkXlVu3E_%+@-!r5xtcisHt8VO z!Ls3^6@XD6kZrwW^l6J8N; zR-?`20lLeET)lr&hh`zbDl@Wg|`=4EPhj| zh^#hUNlibXpnt8^uMJg|UGJ4Ld6}S`C-X6)$t>>F zEH!wby;Y0z5I&_CWHHECE#*^cU1hDiy?cLA2sOmawtb6h1hU@2P*Td&mj6U5s{+T= z#$>x+?VwQi|3T`O>s!*+2~GcWc)rK&&${!< zV7BC4arm-14vmoU*PQgSw!S3q-mfD0T_tr2UAFpEFKsVoY$y;MqRov zB%6fR|NrW{qK<%KVq_CVoTE))0!L7b7fg4rvKi_sS123wsi(NvZNm(EpguTnok4to zTz9C3HK5k(c_cWNA_ZlR1N!mvt=d?mz}? z#?*k?mZ%0~C8I|V5?e9#cjW$enD$#Hrkm`$YcJf#$HCcrTGv$Zd+Wx zBtbpk_f4bQB^82kR*uZA7Igk+r~J?B%_;G(8G4Zin+`wi`M+1hfkfOeu-r$`PNHYzE;2ZK@$8S(aI5w}mh zz|in)rb*9^Cr7*4@{6|^^6J7+K7mkN4BlS&Qj)Zq+VYZ6_Aia>3yIjkeKN|J9;&?8 zD?V@dS!(1>BZ<%5lAqr1+~*g65!M;_zA_Iv@ca}kdcy`$>8mk6vD`9=SgsR=OJ;(; zJ*0te^~Sg#X>M~oM>UqPn9nCcohL;4S_1%2oxYW1;Tu1I78jgiv%wZlu~X=^#&r?0 zgeuoCjwhw2(Wlr|N-AJ$%|Q~F_`*O0AD}n;U3_wuanR54+z|e!Td5;54}QTgIEZvN?CICQb!&mjTE1ExY?H*l$8Yl z#Ub{fn#*07wF#e4tP#NG_eAXrsab+C%4GDVJ@*{$@M${V3fBJ`5%gATO*YDh4c=63 z!AwR{IZ<)!gar;h=-w9hfJ$3sQJOfCh#O=nQ$gkc+7u7u&PQ#(se)U$$``9wg9S0KiviOAjAN__VLb| zpj0c@zO;P1Bt3nr>f9@jd~ONFV`C-?xXl)XAW78Tt2Ly zqj)L@{Tp$6*_HjD{cHDIoDC$BEUJ&3ezrV&0~6Bl1KA3HIEUKnA9~e-n;DP7RUz8L z_gvCbRBWY5vh*F#3KCjT1vMiIT0mod@eKAI>?h(0D}ys0D;_KyRxu&ic0$N_xA#Yf z{i=5@D5G*aqRsyTGGEZ#V{-pq|7I{IGN|9lGk==5Kj<6l3-=tw^xMm(NF~s%TyOgG z+Sdt{uppCm0pFnxlTc}o>nPDj{o&q&k}AQ2%|~?Rw{+<7bPJF}1ra8Bk_tIf=SHQe=x{&?Em|PT zjlnc?K7y&@COy@0dIBcX)h8rX;b(ko<$^EGw z%KNgFty}LASze*@C0gviHB4(t51^tCbNqzi$}v7tt5qBn?1w_aVH^1@_*5TebirMi zUzqzD8!P?|#I)v$j0#o~%W2S8jb4k@?O`MKIv*;z<-yi&&iBuPxz~XsJ&Ds}p}fzk(?-C7s|c<{Xet;^AY->TW(d z-^i3^B<{T<4d!HJOB?9PbLIWC<6s%IgDFMN$Vi1YgI>TV=!$BfWJw}XlJXPN6R&6t z1y@jAufZIpV-S3fC)gC+vv9wxa35c3oo@keGz8EP0e*lS`Ib6G3CQ5B_hx)T39Z9` zMf~|Q2gTd*6TSXICvW!1e}-rMvB!n3=MlZ3Q=D>dw8|zn%y%W6d`fyhi_mhhL zk_j!_aV+9BM4-fMO$VuSsK4(Qk^AL+l5(A5ucV+|*AI}}H!o(>eHv-S8-HaxuFj5` zQ*C#V`};oNBH_Ey@+a!t)7)x%$TR<<#_sPF3IQcjAYa6POI8&B%c0GgcIu_-GfTQi zcZ6Gne$UVew=b}FMcs4B#i4M^=Q7Q7WO16Esp>bvwK33g|1zp9kQ0`#1P5L`32v6k zbZs8q3P4mWRTkSGPkKMsik7G+J?Y{M1+5XZ$r?TB1R#hB5x^7Z#0m{4TRjo7WMz@X zjTWwI!?Oaeh||kh+gt(ds4Q%+!~lB@)0cyZRK5@Raw7+v5rG`C{=E!E9)aV*gdy*A z*<<4l&cUH31chy{8`yoWmxS!sTxhB4A!AxaQ4_(~Cl@{qbHBHGoPf$f(2 zH}w&w2zGb#-}~|Jf;}>O{Bl0NfF{Gn{r0!~av&|3g6t+t6GoW$eErT%Lz#}lR;nmA z>9Ij-u#Xtre6*BTt|}_)gV0HdMs~|DdBibbdo?S(<(=FQg-G%fg8%ORnw9ZFz0o@9 z<>fwgC6Mzr){CGU&wF)j0`(G5%15o#ANPHJ#D*(}I}Hzu3(B-RTu$*?IZ;V6Y&MteTGxf#(I)P) zZCA7xyZMoSXf&>b1X{*g1rYiG)3HPSGd(_?bP?^}`mRe9IA$tD@il)<&PrWyT6!Dr zRYS%h;rrMNsmBbW(+v#z=Gf(^$Irn@B8)a?qyyX5w@47KNUF_n63+qC`U4Q0MRmzp zb`8-%Q-ADyP(p)6n~PUqW-7&bz^)%E?tJgEYsPC>vxojz zdd}5^RtCb?;TOvxBDTurQdzSdM8=a@%nt3>2+Hc}hlbGGhke%fko z>%5R*5|zB!;p;ShQ8|IcyYC1+A^hZDt=HA|4FIErRzVwus<%4NAlG_tz#?O9UYnw{ zyQ02|ZUb5cVJNc8sFgyF;kIg}R-^gioJj}3_b7#OAcmO0=A>Y@xtv*U)qBlYvRUr6AEdLQ2IzglYlO$;K2h#qR{Tsf>fy1!`(L=VmG z%r1_`Jl>_~7iyRQdfc@=bMT8e8+Z^faBuMQ2oY&{b#3EVlS~ zTnuZjQbYR2lLb*_|A_b%JM!_Qk^WhyznXZ+) zI39+G(*3FW*&a z@ueKtfJV{ZC)pvDmm+kuk(sJ)qpJt(jNIlMta`qxkP5;43JEYl`ez*3%~grqAxOe` z!x_o+xuaaRJM);C*-t#KFSYa&jr^S}74sjT`5tbL09D3H@+oH3}3!DpJHDCOJ*b) zMs@9sjJJpnU4L}9Dmj&`exlpVEmg?&|N6VL{buo3I01LZyZ~26NX{pO3uP+oJly|v3a8B_GR+Kb0OsQTKTYe5HFGp+Y3Vlvzmf~` zNF;5;M7D2vYH#vPniTqS1OW~hY8tn2E5snQzTCU5OrN`RHL1O~Frk{!L0#6$)LJEN z3Isfchs()UzsJ&`x-l&;5 zTOXWdN@37m-6_x{M)!LQ2AawMcZAr$TKq;^t{u0H_%fti+jI>(o(9m*{{Gewr+2g? zuR1^Gyga(%lT0W##-Oz+EdgB(TYPR`S>6c;wwHr?H-jRA8;G8OlYZ0~GI#2~+C$ur)KskQ9Y z)y)ICdQ42=5mCR`JEkhdR9?`1cz;vZl!DN}&d`#*@dxraAJYD1SATEk-xq`&WCogK z`#R%xF!bRq5w928v)6b8JA*t!7)gW|Y5FIV)zaqF(gnby8W|e{XzbMbG75<#fjC!f z{sy7r2nR&EI^oZDfpz1Y-LWEg75jtQJ+pT6wSu`(b%51@s82PD#bAu17B4_?D~t+q zS?loG8oa=MF9959U0?45J}k;xZeKM0+(pXz240WTvWnKP+ukIQIF2*?p7)1$-*#gH zMd@NAq6SLi9q3Ga@cHfECybKLg3rZ9^G`mBG#*XKD@mcHs{qADzw#t(j&trlr8|}- z1?Y#ApRQ`rMaNY6{~q=~Ped|PQ0=N*PKPb~kS%?M=gYyG&F>DaKj{iWkhxRDVIy}w z0!x@FOVAykJ1*Qrz5C23wnW_(P-~rXZ+r$$OpHE0Su?=t2@9*^lWLo-Lq0vq-`1BP zBvJ`}^CPFPW~eTs0Xnk_j!NQ~i457-Cu;^O6_g`6NPPKlQu=@kHZj&}{Zi~+S`>yC zX5DDnPYWfYw2aa9DQQrjmDeolJufI;z3yzy+eTKF$BM#&te@MkA<-dG{g1L< zDYvi{vnW8%AQ0FIlx54-&a9n|ii*~RM3+j7{60m67Dos=7yd?3X9@!gi;II3u6Ewv z@*)}`2(a9=NEHhdTiKe){x!%p_V*(ueV`HvVI==Jo<;ppC`nFEhEDIcjsSL|GfLzg zr;{mai+%Z?JkEH(I`MhKtL^f!$==Y=a5#p56KF$K)dB?Ejof$O5CJ|-fv2mxQYz+D zl$_Ix@%2i4TVgQD`SU7|GjjCUk}bU1%lj8J8p*s`KY1a|$q@ik2%j!x?;}+ZZ|(yNz62OdC;~&C5fxN)G7F6~2@* zUNnc$FbQR%kwoQqZBD)-i#xKm%3-7jHBB6x#vSv>^_J`NF_jiyA@LUjRx316=*<8h6)uriqi-Pv(+g)=G zHYcECi1;oyp7jv=%mW^Q*@*;GH!Ba=?LHuP0sePe3skfL{#KgvQT|`9{rCH{$Ue;% z+bsQpIbMIr-X)#kiHd!J@P$KI`)NcbA=W8=ub|H5@Cd%kVI6=TKp_FP#Y@zU%%aS& zezNrbn)7-G;#}e5BBj^378+FkMTx(^24?XO132m~kgN}#?al47aw6TQ3POj=t__-X zztVGzx^~Ax-=0+IehZF0O@%slDEoV^I2({jFUiVos*A+`U88@8FoZ{RM6xP@MD%*I zS!mi0j1fbLxR9`lrQVOqg|GP_z7O)$iC%(+R_FDLe&1pK zJt^Wuz@?ESmL`7``>*fjmH2csQMEeuVa!vL|E;eJ%`IrXJGk|G8d_lJn})fCYHLju zr<8}J$y|YN>Y83<8nj*RTgxs((G_YRjBS@0IREgTfDt`iY()4R6;AJGN*`r;nj&Ij zciD|#cyuDuZ4R6q<+EqAP6F+d2>yPQlmX#^dYXH z0ntK2e_lXH;XS@rSE-gn$CJ0WA`Sl3{K!wIrWGSbg)f!bb?=8v2uQF9o?ur7#AnrH zF2C(@&6#%eqw;(NWyb%j8tdg=k8kQ65__(;!)84{s@oXUfhxt`UmL<*;m1r~H z!1G@Z3)SCObmMol6~OvA3d!;LP-VGX`+EajtUG+U$+Um>g+CUTb-G2)Gw2$hwKt9Fn*qlD`*|Ku?v0{Yj+!80p#2IgR6fP6>jMb% zV@%KlM-N*2bCr!QTPT6t&I^^=fD9%k=QNW$H4Sj=Po^`IO}S4oRd}iNS&{bzw6p+& zRJF29d!+~U1lXrknD92taUk-vmCzRM=0uzkiEiaX<~)NQ+uN(!<@Zyi8dJeeTa>ct zY)c<5ucI+#I^*QFN`ERe{CGvsNaL{Kw*}wCL}CX3L;yTIbnNHDyB!&lUTnr@CQF}@ z7q;g%w-1<4+%tba{ns4-TCz!4PfoTDJ6l5@njqu1uCXQ{vtITt|3yV%MV z-^cCc8DPy3UZmJVA_Q0I%p0p!%-aUbnyFk&t#GKR&2^+ye%9koORHY*i2T6v+z*$g z-O@IR!(wd$-pLaVPNGuCOkW1~#c0N^f8Uz<$=e4^D0BM4#`Co4XyzNwmG6H{`79C= z`(v&meVOy$99$gpYu~@ldaj@%Uub6})n>J6u2rUVh%*{`#@Hux5*7~pUiUAMAu3o7 z4<6m^vFlPr1IG`dUgP)5C;ny!#w-`RT}!oM^{ux)uYUOT%LwXGbb{bet;l@ZK&-X; zGoKO=gfS}oH=*9bBNj$|JmT)N6Qd6aZmh~)|86{nz75`dVv78e!U<2r+Sr#_MopmS zy{0XvLq&VeE>M|YF|5XfjK}Ux_?*P<{gk07s1zSb!3fXu(eh`MGccQj@EzAfYDTRB zV1)GTCB%vV>d?TW#UYD>!fvM>1olx?^>Oa+FDNQ13buL$JDQH9#51=v5WJeYpDJ2h zstij+O1awiMwpzn?ss=??DysplE_%f^! z%c0`ePeS@HSEJYzViZ2qtvx*Rm1=McbBdQt?xNbkq~aRgDci@h(yyK4jS(jD3?7QjH)nrFs}bV|2dF7r}pT>7Ae3}@=7JI{>wKV2c7(5MSWnsmH zaE6)DlnJQf_tS@euknD4Z7an&y8xcm*ZdYFOH6+Xw-v1zT)Ct;(rwD zJY3+tMQsAxYQ0gdf>WhaQN*1-x2mgGfNX*_tt>-bZPy1BeG*GP+@}2}{=tCKyZ8IZzMcrEj8o@eFHRGh zMnUkICfA`$uSm%g`|=MmI_4%UsEi9xKpeh&@xsjlY>S*!2t{LC0j+@AAm8XBW$0Ad z5HSYgCGnI_X<;e=XHYWK-`vu0He(d%)=bP+!i{lv{GLQ}v3g@6fa6Kqj5 zG4^jFeR?Yfv~6{(+9v#j`hmPDxKN6LOqI5Q34Dip#@nH~$5Ng=M?U&Zo!r;o`MZ!^ zcgcA44>ARozc#)^MqHgG|AMj?uX?W)Z&FPxXt1a2kYOJ0E0QP3Z-P#&QQ0k&7T$Fp zzQ{Tq-}dV7^g(bpM{QF0X)HmczSEOJ- zPA9)gzdEKXWOBM+$K}xOXAzh7P9l!Om*!gW&SGaGLj!#*TyN@al~19a4~yC70$RlZ z5td7RxXCiO?Ce?FZ0}-N|4<~E1)k#YWM=dZ6@`2b{wR(N^(dd0{FXZ3_=wv%{W9+pF=ideX?5PlX#5gH*(M#;!(Ifb=^;jw^in93qpd( z%y$x#1-X2l1(mw*dnMde9#FE^J06DKD!D!03Vp+>+9)8c+&1l=Np)Kqe&HP<67bP& z_uxvH=8nSGDUzJ#uq!xTMb>L_drqCq#irM%ND8gBZ~WuPclrIwN~65os{XOjTJWQf zB>^B~aQRzq`;S9nMzeXaB&nfcY%KmyGecX)i{o#Im~>~2O8&3mhqxd5S-3YpFQ{YF zQNVYEiC|fqkd&Cw0K&lHHP5EXD^d)@z+ZAtfaK*VEo^=D3xW{xbZ({8inWR)oelNT zf_x5_r;s%i6)N~7gCkpOp&Muy8&XNqbw;`ygOR7e4ESmPEFw4*#4cf3MKj+nmuWI% z=68YNx`s#~CnAzP97`A%5XhPjLL&wNDZ&KOSLY)p#scmJc7g@x+3qXGUX{xuAo=Je8 zc{W|;`H1_A^b7G`s;VOR#Piqtgz0()U@}*o{^E5$ZuLI;hXB0PU;p9A?mwnu|7iv0 z0{i(KS)bNqAikm-s=*C4Za6hv5Y?YoSdhy%{ig2c~{AN2+^5HcRDnv|Dm3rUa%pm~(5yVA!Ob#H+_2SO9A1AHmk7?%&F22YYCK+&TN(lGeOztI7F_RM8KqFFP3@m6atBW0wfL@aP93hi$ z1dM!?%TIj8as0&~?{bk9pa5VQ$O$B8Gqm9rO=rvXs2bJP4GK)8w!@O?$?`Fq@Z5me zu0Bfg!lO?{8NpDWPZZsjFZs|}#l^&tk2%1$ioPnWDsNq5YljU1+^@^wsO^GtSL@>Q zT(xmrIP=#?)pvQj@yhPnMb=7Mrypo4%Mx;bC`c~37w;4$LUgs=f=X4=2EzQtQ2o9u z8;bFc6;YAA{7D*tVq6M-B5Przf3;L;L4AD^Cmm1pE6Q8azE*wF8>iCA`#V4o`+NuJ z<17eQueP|5ITOz^R8!MTsRv_&(m}9CALdx);R1z(6kA z3bqT?iM_z+;Hums5HqrLy%2R%4i+Rn!|WDdg6NC0C&YFmQ-ILymxLOZN_VPqY(@wG-zga;i;8GDc1&o1l>LzFs&8gxC-27e0s zf*6o=*yr zVf>eugNgmU9ASJ+YLT#OsuPRA)N17z6=SK4xiPlo)lwZ~n2uJ#|i9auvzBoT!2`DSTa23gzM5~f(LLkOGs7PgWJ>(+|UI7Zw)92N8 zwu@=$&5>`uQg_>k&v6fFPZvL;ekee!BkviIS1IDco74pa+8}Vmxdn+S)D>+)&*1(= zZ7kmP*tnw&{!+B}y2pCi8g6FWkrI?7Ht2dBxr-F+C8;c80gP%%cH>~7W^bB!>?Z5( zbh9(rs>$Ty{6`kU4ASTqiKZf8=Huhnnr8Qvu4U)_l2))as$v}7rO0#QPX!N_4CGp; zIgEnaf?&tF2#Y!{@r_(+PDg7FHfG?PfnaTt0%1EHNkc6(ezx=Ai?ELNJGz>YqA-au zFRu)6@~U_V%t~}bRE=+mmaS-WlrMJZB9 zDS@eXJj!JMt_MsE`Lnt|qtLDQM=)k2*(YRWn*RPsQo8VoF9qN5{2-7vAkYNkT|{7C z-cF@B3P9@6IZZCvMt1Vz%};;Tu1otiQSmSi7_b4r<>J(ZcB{}&irGAU|!H^(N1&|r4GH946`W|fLU6_wd_1!As z>~qe!|2*w|a$7$$4pG1tAicbn3ng(W!{_jL@AsyuS%|CWBuFimLHAv-{wmL14sVEX zge=gp5?FRX^(#weT%Ii1U1{N*U)WtV96in!!jvpCPf@yoH+MMJMQsx~@Yf#h0~_k&)}bkS+U%`REirZiDV8 zauFo-n3U(3RZnf9@R^R{x?<;C^x;@*-RAwgW}-1V+VXNEL8yL@!N^ny{3L^JA54rd z@|>f^8%TQN9tD(KiFWH<&U@w<*w{QS9Y_t5fYwh>jMw8Nz-vSuiLqV%02Hg@H!B== z81!lW5QvD5wCme>)Zf3zV{V>*&00a&?!O^vKJlN=&3=WIvl}cJ{&~5-?+buF$ma!y z@7<5LBVwT9fO-acPPQGWIYZvy;W%=YDU$4bpZQ#m*#kCO-ab>*q}T64VehQ8KEP8I za2GDx_yn4=WqN|)8QAUVMft{yT`$7kSbkhRL81|0HTUsL4%2dF`(U~Ail$2G#A?RJ zsZblqN&QZD1B`i_<*zCtv3Gs5%#~&Ul*4xUnG$PgNY+;Z$Q9t;5^QoWeJxfxkdiN~ zw7CbA6oQ0cksX5Sq3&_#Ml7wz*aU)QKUNtav&QvYXk1-dIl6L#ZDbkdHu^<0zdW+^U?frCKKPF%@yQR7L zCLAmcB%<3OLMQAq7CH0(}bl5|jWa0`NaxHTwpKTo|rwn9!l|(d% zSb&i&tZQm+?QKqUY`nn9D26D7q~{oPs&;oGuBmb@y)uoG$+S^%L3?!!MC#|yeG>9j z#3t|DMrvf!>u-SJE#yvQk6L%38Y;usORI=W0fNEP|Y|}(5b>^g^;Wq#o+pcYYV2t z3_t(?0(@A)2vt`GMaIWk2B4(h@=nCg8&q7F^17lWJ*<114VA%usa_1XrI?9F2+zaZUl9Xj7FtI0}2dGaQ$FnfyHMJ z!@ZN+b>EjNy+#a~0E6!vhGa|2Qv?<7Sb8@niT2ntAOrz9oKX$CcgOL`?K+yy>?eCC zyMd_XSf2?*Z23aw$y(F4apP+ubkB&+U%XQvBwLLsz9nRr-B0T*#wHW>d9|(d>uAt4{6)?j>y+ES!x1AvpWgf$zB%!tf)Dj4M)P!` zfSK61+N00nBS6Ku!_8+aS6iUb=nAmMH__noGS3ytZZi@g!P@H~iJ{DH-n#^hGyq@<#2wr#RVvF}yol-9!?WPeC z)ZKn#)TtlVd52DfHADzi8?=+oXFQAiJiv;hOIGNr#Xt7iqv(g;#Dt`+% z0PRSI_$4Gr=TDu6HrX$e%n%69@IHj~7|#p_dkwEscx-mXuKnsc;^(>4@i3*Y2BbQlWiRa-DQu3u~`OxZ!Deqpc0bS>}^KKKjbd z8Ri*p7Hu+v?jf@h?39U^;AEs4&HYA`!TWPe+6ledN{MC^O_3EB%KQ7qv()>to8G1) zx#QK=XmH_pMze7A?%`fc;SkW|jZtlR$I{VsvWP>-0nTEvib>U0yW(lK3y7_F$cn_C z=u;eA9zu~anXl3hK`yVbipU3VkbJ=#aeGNpxFtzFML)?^RPFt--JC!j2$j&n24umB zfli459r*8hv3g3`D#PdFRuBL)Z_X9c7C-|tgBT5XbNQVMg7)B$3F46vQFy(zJB^ri zVDY0I2-Ld`jS(seDF5TuY(P^4VK%7K?3!|BD&K(Kz`|6eU;iDFhG09hMZL~a{f-`G zOwK+pN-~8^igt%^l2Wjjf-q6NGoqHZ&F0w0 zDKSf&_9wp((iC09?Q}^g_6>bM+?7Z*))xt^m5GwyaU6R;K0F~A&zwzuaS3ua-YWS3 zfJakxK)p3(8->Syczy*pbx8bXAG~=T=7|Uhr$0;@t}{=YawqWv(qn@LYC)9VkAEOD z8MpvWNU}FnpiR~IO0#XBiFTuHXy3!lNt2C!EL$6Ozl~YQFzEMSzsd7&^qU^U!;hMe zV~^uyv#9_KutY*UNk60fQ}N#@VT7Ej6!ba0fA@>;=KemS#}h1f(f89|I0j%%Ev;gj zbPNAKH{BncS-HXEcnjLiWsLb61DOgDI0$15hSUghZe1pMr6`cPyxFa8d<+a&Z>K(C z(d9?7u_dd2M_IwLSfr`iw1Yoftbk6leT~o;+O} z$}KJ^*CMg)InH<=wX9{?qB!$NjIJ~>XWvR<~3uw^vht=B#FOSwO9Mct(MSX(NP zNt1;Ab&v4}E6N+$%S$mW)g>8~Z@6?O9){`1w^j&_w{&CAs28|Fl)ae*mIr^%?=g^W zMQYTGY1jJHD`{u)b%MA4&hNk40MH6VWq1eh4mRF`e!h8+%~1(?T~T@7t&odyxH3*# zql+R8xg5dj4|!ajc#EpgM+j_%yI0fH-;joX9-ETLb3O!dRK^4!9@0%rfvrMB)C3*p=h5W8BuZwz() z&%)id0gv%3xpvF6^E7-ZzeUJE9m-0_bf-_Ub{OVgXYk)0`I{R7WjX4NQc{BHG|OwA z#0)wW5wG<~oG4k;$Zop|<%-#xnIx1(#^-PG<=B?4wePOAVrQ`(z4(5Y&HH?`!f_(< zKmw(+lX5R#hytS7`6pZlQ4Do`$3iOHvXV}y{{)8; zObhA1q(nscjKRzM;%CAxP+4$nK?2ETRXGqK8q+iP?8r8a#QEwFjsy4WL5W_NS}@ zyDZr(R`5d=aw)Zf;fM2It79OzZ^M8p7VPNCmFXD|ldk^>V-!P^({S2L_`5~4elc#a zCOwUXm-M|H@ohMheT$TeYR)l5u#D^_F3Ky>g91&BiINrVZ8{d%ioFiw1@=)eM{cSQZI-!z zGqW%1j->?6ed{U1?anGN{N?XaH+YI>Qhj={5*rjmgs?7law4$fL(X44HY#~)Jv#bxsS=Ta#$K>Ue=g?wa}5(&uo$FC)pK#)|nXS158msk)_ z1mG|rrEzmZvHrcEEYp`oH7+dq7@!!c;cRlIz>eg3fdkUCi~5O;@xnUsW)gn2G?50!E6H!J*q z9cxI^(;E09Zyqv3J4!j$$}P!Zt5iXQy8gWJ&gXuySKy)aCUM z+kj`0<4p{r-T<-X$*AP~_Z0wS)MyAkzmbo#Y-oVJI2OyKnqvGcmCHET#Cq9;;t_2? z8dln(fC$hwITKdc7Wa>;uV+ynDu6I}7s!3}u8V^FWO1}@vWt(0-{%oN8F5V(qC7gC z5Ges^cPS&+QQ$=;?B!ezI#C~o0wNHlBl(;Tn^sXYCrh0rB6j;f#OPN{{q!w-9L%tQ zpR~w3{|*ViOtD)0I*1;tAY0;;&WDdc#ini|Mx#`)y&TOWlR_W-S{VKTw}-h`=J7Ky zs8?isjQrKxfM@Th_05n6I;NDDhh~%?9faYkkP6HHv5BJPuIL zK(NKXycYQq<$AKVzqb(JlP{xj5&HIcM|aJfF)B3fY7v`a1ckh+`#@I?RcBc#(29RTH-HyU1C>E zR4EKXtnIi23Nz#w+LP`9EG7D!_r7d0Aw@!fa|JW``@5)zq8ys8qVnMiJfQ39uDGHW z|LUWo-EY)nvr^A(odmj$UA{LcLN%-le1)C0jgz_E)=MNK$uZdV;Y*q>?YNG6f5KV& zME5G$pK{O6h-#6PlJb9^-qWO>iX7AN`$k}lXgVEhy4VWR?O2Jb+Ub6v1&?BasY=5X zXbc!WDB!}!1&H8IfU5lAw?BZwAhflr5m#90$@0P_cb^SS{AX+3N>vDr0DjX}w$EJ$ zF~ZSMXpMto>vq9MjV!dX2)~9hBZMCg+YuLHkx5b@0J5kw{lvNIjdHvwB4S6t<2Y5K z(HtzZaM{#2+Vs@NSTE(>Ilgi|S4}3pk*vmO9ZjcF%QI~F6v&XZ>iK72-JGM|(q@Ti z;%)2Xx^G`{!ke9X$R-SV66MdEvDO74NCr?aFzx`LRB-8XNecRkMvR?23s&TN^{axg z2tDbbCcL6m@V&~z1yxT%jr4qAFCzFzm0$nMQmIx#8w6v-S_y=hgs|#c~j?yy*CUv;d4IEVag3IN7uN-Z%($M{I4DJZ22?E?*CJVl@=uMr# zpts)3XW4x^JOEeiafMn(U0OsrA{~7#dq(4b`28(_X(;@%Xp)vLb93-EV77g^VUPi8 z6~IpJ@W9zTIhg4KYs$VSsc!$mhIlH#<grU za5Au0$10T}W4LYWdA&%_X`u2w`)8wrCW0IRPuh?4D28A~B{hsggy~8vy!ZS2^P)H& za4L!Fo-TF=3%;j6F!377)rJo}U2V)(3)e-3D9-M>C*RKlj2#mZB3@#t4}H)!xP^^y|5^r-63;-}pU82k)Nj6ls!tFm3HG|& zWykw8gYlY=x}N-W#65t>?u)h};ixtMdQbcN3_eudHW$DoJ#A1SD~_N3-BghjBUBNo-!KY zkR5)u*kU$d0u6V~gOq41;PPYkzF7XrFKG|Pq$l`2=5jPWnt|{J|Bz|aiG+?UKdrsO z2@tz#yTYxc?KbxNcr+hLgza2@VRJ-+MUdg4rZzWfQwDK=!Z+eC*s{uf`;mAh0v|F!3nz5}Ni7%x36c45xLWw^OMsj682tNl%m2Sw4 zUXSl%%?W}LX)ZFhgR#V`;u)=PVm_D$a3NsePw@~ZxYqp|Om~6eQklr*sZy?V)BRPQ z7#n9KXE^`>g>0e#P$*KIU^FbN5z&B$0n0OUd#);>Bv0@oc;~B1PWAW?vXU=`q$IBi zv|u$Q#6@(_iGkx4mgDp3C%_y(D)pFcQI5}*mr+sWU5;*o5K$T|E!7kl$kYRg3(J(0RexQjp>$C_ zqQW%Nsxe!DlVv2SDJvy#ev`vT-S4XfY4V|DHd`Z~Bmipn7_^#UI=*4yhMJ46)@!w& z@5fptNs+{2i=7Q9oi-oSajF?K7~sCXOs=K(3@&;*=q}M|B~VBe%Vj2oDW)h&&Xapy zcancsCwaKn)+b%M@y3=CbJ0RnlFY9cy}o+Mw0#-An2?=G5*l^qzi|J#yXG|6dGipJ zp2NDERiXB9kvcgtvJ-qS-7*%VIafaSjQo>xb+R;B4$3JKcBW*~)_PSofRHA$)(mlH zH7)@&+#h1?!}<>Yk1pEF&l~8(P;j}h$$yil;KZI%yG7mT7y${09?b3Jm!EEI?*Jov zp-|MT8j9O2e0#i3;B>+5JEQ)=hCqZY5wl|9MML*TvWtx#n}k98&yflJ1l>BLS^`18 zlivJ_(%h7cz7rS@#9O1Xva(aUR+cQq*;(jtUeQ5nTfnhN=l@zJsn-d&&uJj#WlDuF)h~P4efJ{l5zeS8B z<>?k{tDPhz`N6#GhJZ;`^5tsg!;apmDsmg4F|^-#n$}ta)=6@Nxcu zaDfr8k;lJJa^v8Jak007sha+!8llIZ?`0zPvp6&&nSUx{PQSR{0wB)0Sz2qfRPg(Q z&bLwz+t$SsC=&8TE|`@@QZ)&;MVfUQ^p^QUL>mHb>s5>nho|L+232ducTC>pno`DF zZQvP)+bRA-M$eC=Z&+Naj%1Q)=f1U*v1Im@2V^Tgmb$;i+p8{6PPgdsVc@V6?e>1a z;>YfXy%CdFEc$_3k)`&ESgK&}LUy*ZUPPCfOs+lEc^;H15D{dz)z6pDmHXbE!{pP| zego=sSDTFpjT-$v!rqgWA`7Q6uVZ?F7SB(VC@yj>d*)>;gg)~l?LlE%TLf~35Kbh zWMXi13b~D^a}^qdg`pcTxxujN^I31Y{i5<$v-F0e-owWtq+!~wdPhm7Cz>%_J0DqE zeOO$A?!qG*c8j@rwjgRn^KKMV@gIeK7x3k9*7><0*(Ut5Inu6b)hkpvi=6mAK>g&M#<9gfSP^b^w zsvC%0zbs7&_AcmGZxHtZSc7greaK;M5@T7|CqlgS>sLadNe)a-_uZaUrWwU7^IK?I zx|deH@iia$(l>?fEfU>}#U^Jzq>E`E3lgeynuSFQKf837g|?wX?jbz-*AUA7KJj_j zs4+M+2F1QbmaCFZ9w_Zcr3e`)rkTvyUtkV^6l+MX@PF?m61NxlO}chdzgvERgDFS^ zjtbZdQZauG1&iW&eHk8;3SvlG3du!6Axn#AZm{Cfc}w^#<@@^hEF9k`E;B)!1iw`E489*DHg zi9T`p9KpgdKv`W6d!dEq*rh5E;@@4*PYwKQ^pcz&@ub(8h_GmA!+TcS$1?%Z7WyZc~&(ORjO>(#>=sBh+Jpw)Z45?>z$pY!2n)kp)-XNV3|Q zQ7Tig{S|c>MTmdgRUqT_sHwExx4m2?ny`qKK|Wt%2d$5 zYoIs{^g&Jhpt#q7=Ca2bkMUYR_>sj8534RzSIb~C>@kSuIpTV1TjaxSn(6V^g@;JYpxZAoYf_#C7WU+rl7-55b{kjdtcX^5f z-Jsms7tBL8YBXv==szmL>Kt?**sq>=a85!{g6;IXg}9TuIi(N|gpIUi6+-Ot8b;F(yuy4Xj5CUOA|Q@R}@_;tjc62d5ZkWLo_*T zUb5!HWP-2h6z^mT_dEY}Q9of-A9PJ+ng2H?5!RDSeEPJ~Ja~bnmB~?ET)w%*bvB4( z4OTwf8jh{dsI;|OQE$&sXB{mW#bPv$r{A3v$FaiG>&9Ab)iVRPU*YzYgk=B=WM^5K zzOh(w&bWS#xj0_`wqDSRWcD!0GRN-UR|a2u|sjkPwO1x}OQ9K*3Z{(>kBsbU^NoPVLE19Ls;$YX|vwpJ(#dV?D*?XxRwuO$>$PaUk%5%vQU-*#h3f5%v44L6ng^2IwP19 z8uSnJ2ZiUCUuR;f2v}LxV$R>M7N|uQ4GeR!$jM8GK$-$m%}}s!|11_8BRgM#S>r|S zkw3D01X>(ws~*k^)!KO8>=_r-OC3HJ2bT-Ls(7odDN6gnegDo?M||N72DocNKRxm8 znCHjh3*=~^h{LejOj)X{GDg0_CDbQee8MitisHaA52%rdm7kzXt**5(?%$2mt4eUr> zW$c$7&ehy(NrYoh8f@HWre{{IVhk{J`#f=fpD7KOn?YXTsP%R^TH)d3ao!F3M%SZX zYy2Xg*hVS)X(DP#ds%yQp|Ynq(71h3r;gonKCSx;q}35etwGPDR%NAxBn(v&BM_L#Oy= z>14yfqR;L;fl|EELo89PwRw0+FIfm@;}Lj!PZk=H8}fXE`j2be@Bb{T`JXo5)rwQp2+OpAgM+%M~kC&6aJS((kNZG$6Z7}oAL1^aZ=F388C_$#0d4x)}Dn6 z%j0stSBrxi0T{$7pl!9>eQEXm8MP=xY=9**BmQM9dMn@W9Kc^cZG6| znkKW|oK+r|leMmj4DG9+2ZXGT#xwL=ktHc5mY8bdzqi9x^q~GEMgyNix0}OzV0a_HEkoO-%IH9>otP9hp&~$I?nfm>Q{PXO$#^b2IHd>JD{fj5*YIx!_3yAJKqSiQ`HEiJ<@?fQ zen*Ps7BH5vgzWz&+x`!y1KTz>GJYL%o#XlWRtKMoit^#|va|ECcFZno9}yoZJ?RJb z@s2KHo{*%_MTRtBatu?n#7*`+RWV^0d!t3bk)E=OGN1}e>dlxy4uT2rBZrdk*MyKu z_+Mv2{EGenj+j_9&$5vg+}ldyW(+K=Ae|6}hO6#(A<5B{Ex|28tkSp?#fAXJcg;E^!OG0&f^JywUG1N)Y9ouwWR_qX!tOfX%T zal0;drrzFAkNTa`L;^$THNZH8rZz$owh&=-(5)NE&Y`l54iD@4pl`_W(h5v_!+zPE zIANS}vCQ0TnZ?{9BF{8!vWjpGK&x)DO<`|P!7g1w+WoY!2!|km9&ip9;8UlU_Qv-+ zI;Dai*^uf9O;@7VwDwo!Vlg^sp7K*uO~&J>OCrE76zp#-r(3vauijkJs+Ut6bZ}Au ziW`ddug-mAjVFWa|L5Fef(drX{;bX5FwQ2?s8G5ccoaQ)<=o>>p4OW8B$JVmK@G)F z?J3;pDTYjnZQS>iD&&y1iB1Bscd5RN7thD#@RV6N;m~ojUQBokz-9??#K#XZ-xBfZ z)@A*;m}Mh})ViCLzKt5wVG%ID;NFIma!*M(KLqyERtFUH42skPM_c?;JAIlu<*WE| z%&@w3GTfg4sz6*(6qkf0U|ee%Xxn-tfw_{>baT9>qOKm&8CU@f4O9Pt2KOjUoe%?- z4p@}ne}(5W=-PY)l=+Zd-`}z%`VE@Qi~Og*w5u|;4BDL2+mm!TJ#PODmPIln)WP3x zkS8W4oUEhY`t`K=JIz_Do&C}-o@Sg4KA=-oR8?kUXT>Z}@kzC?^FH*nEu8jD)HMGf&O&y zzbNQ`U3K2nyIMQDlZ{0b8eWi>**+fb&+yi#YL?ApmZQ$J$k*lh5COkU1lsP6_dSLg z5Bjg$3**-_Gm8zUAZoqjRB5)`RAo~oopd{z$yiiek`)_KX>4*h+p6QHX+BnUAbH?+ zvbI{G!60tXt_;w;s~aJDifORyL9ijPZkVTHQUrz^{`s2ys%iflRiNfKJahNMu=cv;Mu7&$%&FPkZ|9ol&uNXFx zyD3}v@6P%~ArSkn1aL)W^R(Ko)v67ZOA!F(uZ;fbbBs@+_lxaRM3+Cw3a*M+alJNj zuM6h+`ML9(Xss_03$$1DlK)ZqK_q_-m~qX~lya{oc54hB09pVF&=llQ37AIQxvR@B z2k&u+^&W{b0~h@##IrK@IPm21srtE{kIM4$h}G%4)s~&{;#X*3j>5-muoI|2-IB!3 zCvA^g<7bgbrN_X<5=SECg#jus&1u zq0}I1`>;HwZFj$%^FllSM;HSn{i%MTNX!ZQ$^UyUw}a*3Y2De)me{bz%Q2r1$t^%) zHCKsYKg||h$L}_qQC4A=j#(~3`+pdFtA@DNEm#y9cZc9Ef#4e4NpP3o7Tkktu zR4TA(aF=zJPyogZ;F@E*m*tE{_EMC{Fi!W@FoXcNQh3g=>K|tlb{%mff?lr%J|hit z!1?};cp>*l1S#QNJTOr4JQFhd`&9UXkNsnDeWVzvkSR`~TkM^U7D6H3Adn3sjpkaD zU%fBnDaZminenn3iTx_C4gQ0{sQymGkf)Oou0r=5l%mUGWq%J`wXZPm7#D z$>Fzu8XO%RUG)R6&!{bGSy~SknyDw0~uZO&j&Ckzb zjRl|s=bf2M-Z$%FpZc1}lLg64WJd6KM>9m=7-Q^*_v9H-6IY|n!F2H@##nqP1xP9q zijXgI?zH6RKNB&25m17BCo9eBs;a@Xpvak-9K&|Ux>;LAON*qaKZyI`N^2y_vWs*9r=MYoOtuai{!9brA(y&?}MG14QKo=0tF& z8OFx$p~PDSDFu!AhXg1qB0Tdyil1SKgA(a8zSdd_{Wz)2(ve%BQ>ZBW?8n*)?p~X$ z!D5b@r)XAfbRe_#%iR~04+VzTVnxwkmH66xv^{{{$iw446peU)JSz>OR7UNea~78a zH2hJ?$o`GULY5A%(Mg%j=atSB=2R<#u8kq~KESc&r?}MFMns3t;n8A^A;y_Nw5F|H zt?6c}YZmBF+imDiv5IERlyBcq6=_psLkC=qAl=smcxxd_b z5khz%Dw78;f(^v(#x3C@iwjl5FwF&8*$=Y#@x0G-z);Z#$bG`j5P7~%v8E6VXHA`f zBbj6x*cX1{F8Ajn*_t~r^etWJJdPierIf+8yxQlz#(=?fd%oUD~_wdbMt)u^ktLG zmko!hA(YeCqFxs1AU%s+;txh08`olW3Ab&xvLz1Q+48da)0@eJAZbxM7`4&mSqqmw zvHL$Q4p9fp^*j!GavFVuF56KAtjb8>c_z)4COed-@poA)x}DKo_|ufy<535bLelM~ z59x86W?d)k!6Yb7mc|&6|Fpl4IU>Yx9PTFPH%AL{h7uTMlmlq6de;`?4yLm!A4Y3^ zE8Lviw_E7|3*=?&_zZ->HkX65&8|s>iIEXmrE?3_+$>%PgATVC8*WZcPHyf!mTOH! zR8+va>9g-(3~^ea3a3M%@_&YCj9@c$TlSS9)Qb-LxMsimnXb02wDD&Qiw8HAS}|P@ zCr&#sy%V2`@>7as_hgk4bGIim;Ti~<+^u;>e1lV)=|0WdEI3*ohKo-cOuRId*;kAnhLozgkg|v@m7>I9ArRExE^Pa@iil`(3JT<-Vka{mViffc}++@A#v?! zH(NUa*7jS>APY=ADvPkXa;!0?(bUR*bIE%hFed5WGcX0p({49~jkAvMTgbjo)_)&s|7@m@oWFQ&U!l*~ax; zY;AsCb#{^)FPht_L{M9e7LyfP%Oq!c9 z-y6*1x)b94NtV2!@Chxn4qk#D$yfXl55;-UH)cA`uNP}JAqNMsb^x&a#oBtO&f|j04mbZSa+St&&csCUKdVcL63`X z8WpXhhqI;UYi&s#*&OC0HN<>;cK?nJV}eEGje2Ikdkv7% zDkq$^txIUr{*ddmi%kA$hqd53VKsW6r}$erEx@o%hxKV8`JN#mZpF3(HLuxy zw{u3@uZ#*rLsauOYS{uE90*AfYMt75F|7i>)0Z-4u{@mg@2%Tp|N4Mapn;Dx)FDmN zD+`f&JViZH99=2hK!Xa@JNvw&O2y9Rf|F6PO+e@fvt8Amjb`3(Po4fr)e;f6&6r_( zz{fknDfc_^p4c4;X>{&s_UXBW6;C7jRRp0ezo)~bd^X2!d69W}<*zLQmf zB`#Zh=MzbSgX&6ni+g6ps~anm*)M%}XeV;W0HbeG((fu}?0R7>Ia^yp)8O?PKn*%b zacs=j!&!ssS20@-T|U>!+KS>s1g?+vD)w*3RbXJok8Z(^sgi`tq7o9~#*kVodmN|t zs^3fa8NF|hpYK(+0gE4PcccS9m_Kl1lg{2^CRlt8-K;?(gn1XaCkSez1$$BX2;IaP zI$s6xK`;nv9smC@mTrR3;aMPhFFRmNTz%=>bnPjYTx25UGT-HD_v0Bh9Hp@z&cCFX zB!xe=Hfd+QdsmLFy%@OX-d5&eq`0Db{js-Qr7(1*(sMTJNd!H^bN-fmiJt3<4?Cnj zclv^O;%PZ5KK7>18!QKhKA{LEU$eHJGfUw-xUbQ>R)RdHgj5&-!#-STwzjf zi9ZQ@-6MwFdtW-rksJy~9vA1AZ!NW%_GjcuyKwbTTwV0^vFDh!*6=7Ah(o*dP2JN% z{i&_}l?VWa5hF~D&uf+o(;p#aZwSeT`)`ilupPs*5NqoQEBZu(d_>b-VK!)05)L3% zSF+ikO27h4X|IRxXEw@VjwW*jCYuVnmDOtu(9nrG+)scrL5sWT2F1{YU*4eoToj;yY9_#d8DWgoJ291H#&}jo>!7( zNTlo<+Geq&0`O>T^2kV2v_QK7oVNj@zH%D zCadzAnlLjelh;5qoIK8dzZxzs$P4~)6qL3Z+qS;Ytk98)e!+*C=_z#WwPn0D<`z); ztVUUiIYmj+$0C=;GG1em&r&9ai#oBwzw)F>6WI<#qjkYMWwus68?yfhSmL0PfyAoF z%tGlf2LdS{uKZ(6Y~+I8SL*7N{z#%*OYJaR-m!O*{V`>=yF^PeY*PU2c5i}#O$Nc< z%uly=gtViH5l24XPv5_G*}PWsKTcPFy)_MrN7cuM&cI=yWQr+JBxED}b$l!# zvY8cxHi*&pNUtL{|98i-Eqv^1*5Qlm+g z_9wD2c#+)*AtLVm>Be&S@A@_v%2bqumy4Whkq-(Kw zw&V;4O$TJ+^hF(lpG00+Ow5rEE^0q~rUj$=A?R{Byu}HvD|AYdJ{906S@DO}5!dVZ zy_al6ys}`Y>y-B28w4bq=h89}`;`O;9{z502LjMX0(-qm)h6T?{FZ!}EgK^%b@F_C z#90PlR(0v}Os|3q&NdvKy=X)EwX2kpsXo|f|q(q|fPLq0|$K2bq0dpmMj%><7}G}t(Xlqh7?(|v{n980b? z+gVKJjJFu-wK>D_pnrA}JyNE*g0vKP>*-}HqcNVIo&v|tUQrQ^HrEnsq~mgJbMt;B zv8B}Ja1uSn8#XBO){HMFO9>9^qI(_g=Kzu-vw)VD7xWj)=%%MgJ9OPz8T>ic$#P_z zf9IV0Yo-GMMGlN16%vUT#8Wjez+gFFrh(Iu`|H;sTbIt~bLzuVS?|<+5DP<70+SX zOm0i7heJ2~dY$$czWV22z?B5u?_t9SDhTiz6XT}8xt9x%iAYIGBR@DTuPEglc6VNS z;B0$-l2MlfkSSx@t+{Pt%m;3TW27HwZ7}6rn8{AtmYTh`)dtR6z_+oNSdU-9k?ZbD zFf(3=Y%B+w{0~c%V)uZTDahsZO6r}mlC1{~Gy!+Xd}2w0Ju1ynUO?56U>Bqd=--bum@ zL~&Y7K(PI@yu7@qPRr8L2*f`a1&OxGe&u(CNP{&=Ncq1wy1R$%fmCQL>l+$OZ`TOV zv~Q2*`wWAtSLg;Mweyhc&jNDgqA($4+pAU)5F^@R;O$!ZM6>f)h8v^=V@Wq_{C z+PZhGjk;!)562V3*my)78MRm2r(5eLF7DQ)&lolAeKHu}ESrc#TAM}uC#qnWa(?j% zl8*`>z3(p)3IfH^T)FW{zk57@I@3|zrAbCce~awkKbR|q;;}JB@9`9oH=BP{@&|HP z@Sb{PLTxE!zx-pH$`B44PXi*u6!PjYYKhI87t;oZ?$hNo&%nCe_cBA`GsD+q)zu&5+vSf5g0%5vmlpZAl&Je_CikM8U{p4_b zTV1X}2UKc!v|M3t_+G`|rz;5FGV8CIVUpe|XjntU(96VpjZIC!8EI;2dg)F2jtRv#?gO~0|R{tcd5wE*0y#W`5jiR>^s9BBq?lW-AnnEm1C-(DWV2}`q!BMa9%Ec zF#VN@WEMyo406IC<%d;6tNr1Z3iW82x+}+MY4>WDN&qCXqxG~14{jBafo z6U{vL-1Fy$<0BN|qpe4TBxqzI?+zm-HK6gm$7j%J$Nf=TNu=wklu@Rxh-9dZeY5ii z1p(*HIVTxi(6B+0ub{7T&{$pv#woZ9e&i~H!{bbJnYa6VzT)Q6RPeGlD6Tk#_Sld0 zY@=h$(0G~FokdsEcwmjNFf4k&fMyD^(n4_O*@L;{CuM057!z6o!T=oBettgJ^ae{7 zH7c4=S`pWO-pc9hS&3{Q)U#e8wX*LccRGtPDmR ziVQeGBk^!)u~|fiN0-Oyd8_B8f`EX)q8{w&=$OW4fT)9G93bkR&WWiQ2vQC11qDhd zD4_kBrmB{-e9p|wEURlAd&D%Z%J$P+Sy`!Bfo7G5#y;@D))9y}- zI!C6wRtB^7b<$qPg**>ZVqt7O0T#43{ZSP?q4oOh?mrFaJvzgbsI=lpRdb6_uAsI9 zl0N)PZSZS-WZ- zmkaX7k0BfBSMNe%3i9q}x1=mNo)K=(&t^y&jA#OT!haSZ4~sthBu;Ckgv^+%&fIOR zd*6cz@6fArkR?U;Vf~`OFwN1P*ZaoRY>q{xrG-$}7Fj%YnBu+o-GY2egxnwQ3iBy1 zbU!1!00KOi+ax-LZ-5zMfmGCAfP=p`ALdXB>k}1GF$kKnkFu0p0UjQ{HsA44MHCS= z*>n?sm;I+;#yFe-jc$v*g1o$$3XiQa|3B8?|GtcWXuNn4B#0PwM|K*(TYZ1y%1%d_ z+C{15tjfXjZnE!_kq#R-=Xf2pAl=1w6y|^~ntPzL)P(*I&4O0FQsLAQr1tv zPvbo~a&TC8W;Y>4I=7gdTolq=naa-N?eSOx%CYCm(|ea+qPD9SV=ylif9_7R-n-Dr zsUc{g)WM@u;!jP^-#sOuPPNiNXdyB^`1O?(vyd#_$CkDg7! z_HQ`W|9&zUBn>5EO{GoNLnQR)roRCmG|!sT6|QdzC|wP@HN|HE%wCiqln9zEnvJLZ zX^Y<)fQHBNMjRdywkj`z)0k}&d14#t51by){$y_4QanHvEmZ0x?EwQA%GA__0Rd1R zj&oJIX$^cIGN@r(0yIL#9s0wuB*M_qkdXt6`}+HX(R_cO=?9m!wzr?HwE?5}$e%y! zw1r0=uhGf=aY4mX|K40ym7DSSTKm=p+6 z@SN6p(J;eemm-8&oxMpQFe6X^<>xj;UmQz~4xM$lovr{EcwZVUmgQ0-90E>|J`7+^ zW<=gA3<1&v=%aw&ru+qwqG}@(%_e?pTl&WJq+pN7BcNC#Xw4qy&!SV6c1L0tZ?9o4 zh5~?cS%B)<9gQq->=VYijU5~&i=TpBV4qkix;-7)9-Q|^j5l#$Lyh9J{eGaD4VGyD z5szw^OP~sbF`R7YxycMp1bD=1Y3F>kQpNrKeSqxW*Hwx?58ES=QqRoEG4SybTs?sM z#`ZuaOcUb6lZ;Oe`KWmFQw>po#lFM10MV8Hr4g?D1cXeEVyHrtPfR#FxF_b3a= zgmU)0x{kwdZ8|zS#BY5MaEaZUR20N82tKsIdZphqtGq6^rSdftMg@Zz6U*fVHO_0%ZWLRRbf^MHbn_7&Kl*y%5d%N2GzqUtXKg6(d4(L##XUrGY?_J{}0m%EH^fg86?jgu%||W9xjRLv@8;q z6vc=23(KHBn-Jn@(m2-Sb3MB_+GElgOa8YY{lEK;5RgEJMS~OD3&cegtIH~r7j)Q= zp5lKtCd~iZGzVKK%CMOOScMP{(Z)i)tALF6oMdROzTj(ax^5j{5BJT~l5N0Lk{AK( zuliW=Ws-d(A|k^1=Pr?suH8y)le0M?379b{% zeZ$w}>AMGF^eqXgzsS~5PvP(LpQVCwRn?l~^~TTTFG+LO>N3asXu1HW6@UNB38B;t zU@Wn>$#0H!I80*=r3Y4_UYGMJjX%aERjA{U$A_Q&zrPUI1b8?M{k&7IMUIq5+qnL@bvx1knrlB;serzI6NK>Td+J9<`Div2OwAxy$JgxToOFo@; z?8lrMofzq}Nora=(&u7%q`dIIJuIIpicDj$w-hCYMO4X```?15U; z3ZW}3D~nHLU<=+m*jamEsxkPksi|pgy-p!AnY90(03gY{a9|zFVEMyLU73qgjE-Ru zKY0AMy#mfMWz_^ZP*-1LPf1>--r3TjM9?3!)h1I`>(8u!2lg@+9Bh`)(>+#5s@piP zEt*NMxBIyarQo~Xk#@?89#4&_D|?}Kz-0q&Z@#h*Z+L`<|OR)(_6DybhB0#~&}9C92ezV20m5PPbks`~Wu>>aR4ve4)}E&}9V z20VwLlK5yo)V|C0tc^%{dObUTaLidt_9>b8?z0!FqhB~QrLRYe=NAG667nCSNj}q} z6Y~XR91JF~4E>!9YmOX_xFH?#HcvRPBg8y!9X!Gl<6e*!xCUO4o`h!yUV(rO)-<<9 zKNu7`V|$%ALO#r-UP3-DYpd>dXmBE}-1b_1%4w!Q+(Nvmj3S$yOzulH@q(SSaO|@; z2D?ygdR}~TvY^k!FXCxl9a;hZhj+D!j)U=AFrz7Iy|kz#dXBQxId&mQMdHFVwdT(= zcj$ptKFgPoEz{qZFL6mZT-KIOFWd76lZGtmoDa8IE#AM$JG@z;t8s|9=k>h#VhGmjLFOzPOn!m4iW}Vg@(pg;qeBwL7p=5J>k=p+w`M( zb={>;HE0{D$xmPUr+yfaNu;qD5)jbWjthAu&n=D@CZs$}iG6oF6>|P{Q9f%i(UVjb z3y!tptf(toTXO#O4h?$umzYlmS0W9NIS(kq@t}RKhGg*$hg<$`JqHIgg-TIuNY;Dg zU6ADrASKIQ+vKog6KsFvuk1d-Wf1YX2%lFkzvApEojRvk7_T%w4B#Cc@z<2l78C2S z_{K}6Y?Qy$ZY5xCR4dv!oFb>C-*GFYEgM5*O+AP%;B)b&KBE9n)Hu^4o zK!NyH?U_KcQu{}oP1?kSL_y79Ub*T|Ri)(m;{rMXZxtF($UH$^Z9YX zE}*HSlXACC1{eU7*(M<1#^C#y9|+DDuDHBPZ*^I<_ls4f{MbH54-2U=wp>7F^_|@x z+UU*2%YK{P(d=MjG27dGDOrOR_8X2>2Qmt)m>nG+5o5X#L-->HV`t*%&^rI4p;Cu` z?pbzX^;eS40W|Zp&8}BRa-rH7{RIIYt`m|5p3h7Y@X~^b-S{*~YDm@arusg7jB( zaV@?{(xqPI;UnhbMbdNjVBMX{L!6Sw=<>`qT{c_t+0vMuPYI)U+k40I9FJa=rN5&w zGM3GZc(>ZKh=}jy-@Kpo7p(A1y2O``xf&U1wY9Y3S@u>J_=Eo@p{cq4{1CGAdw3T2 zKGcz@4B!K|ZwSh`(*Idf8Q6JBWEtCIr6a$NX>&K;Wa9rV%P6|AM7f}Oi*I!oVzby% zy;u5O_T#Z&UiCXjK-q5=M{Z5%P~EH+OW=^*1Yu<41a#+Gf!x2M3~pq=`mG93icgiy zr>HY-sTOJ~M5{i%`e$9F2>d?T-{Y+QayWx2;cMe9fctA`687`tg)l*L*!TMuRVA$~ z1!8+r7Sfkq9goUDg?+QPSMB7v+cXk(q270S$h53qFlHmRiYb2 zq)m}rbicRCYzbRT?`YY%2rjqC(`~k0xTbj$F!EM%cl+@w3W1>zMU}I_NOduN zK5vYRB5|*~ZhZ-9&-Ia*8b{&-KYvqPhj*Mgqkg9kw1GVF>xq!(6U5m5_t{V4H@{K< zjrOMGp3eu-hE)DuAsTtq3~sj*VN~eg0*aQ9oQTsT`nQH%zJ0_FMqOmo1B&I^Vh^(i zlL}SLSl~d|Tx@kD?xtF+Ml&5uM*VD38MNat-lcI}_aA-wRq=NSRR@nn||NJjyr z1@k=>HHJ}lmp4f1A!5N;Z zHGZ+Z@&OG&j#mZTmfy-%8cL*75p%52j?B!LAzl&qkYCemvx^dq5!Qef^E|^-o9z@5 z)6sm&2XzcTvQ);+;PK~;l1Q?5hg-SLr_$_1s>IOVWdtlH)#~Z?I@$ujV|>P^WK6%_ zRzG6a(#`!obMvW`qM`en7$8PVW8+1Pm?K=(DO6&@5&W zoX(XxV&y62^ty`ttdU+3LG1rs^67uYCNK^!19gU-2=^ZP-koCp*PVXY*`P=x8!tF( zVB3Fz%3eyU7~4#_o3<1gKI;3bmQ&hQMjeKpI?BA9I^8T171~E~_mSDy%mmj>SiYi}qTBBI4nTnY#QRN3?Z3vzN8cX*+QA93 zVdi)f1rc|-cQ%&1$dIUWlG+*a zXHC9yHDdBRm6N^$y<3VcaYdk8ypJQ_b{}QjWh&i!CW7vCDN+fTB;k()LAOszZL!P} z{a1F33lAF03uw&K9M6uwqq@5j0@(ggm<$<|zN^S3BH7e{ohS-OS$I`eY8Eqen+Yu- z!%MW|a4X4-U9fkXeCAE!+)nIi~+wBr3NedU&J1UOo?QndT3T zUox&l}1SGuhH0f~W$X*`o1x<Lw*^e8tOds<=Kl{G`J@3FdeF+A zd3m1Kjo*Z4Whsr{ERnn(K7cLqoP@Z9azyW6|6%AmOaM!SvVFw+dvW~(D2W2XITl2Q z+>X>hLyaq(+y^`lQiWbT~#8zN}}W5fT!XogXa7 z=(OpbRISoWh_?*`@zyF@hFVHWr3I~XNI)`ZTvW$ou)r7F(&DON*P_2HVMsL8)4-;G z;-9;(APwZ@nDIZ(kpyZljK9CVG0zb4@1C^q zkB`qiGpv!*h4b%^vafc9PJgK)L80_>ReOVTji0HX6!T;I9dU#ED|^ZA zcvj1)0LB~6iSy4VU$IO}fKK(N#ZmTL<3Sf6tSf6j>_~DllUN2H@+I2D^GxkqX{WZU zpO%YJYlTdVLXZwhErZN)wTtCIrSyWpkcEto0jMN5(i9-LtbnxFnF`)B+!OAplWShE zio|+GL{F#RcR=qkxE81A;p~1~jRuJS4u367oUVOs=Nq73_q)2<0wlFYOk%$Qc#hM@ z!pY0cesz2VV4WEReXmaR%y9pCA5(?8VU0yLC&emicH>>ga8FpGIel8Q#8acCr+59;+2p`UXf_Pf1SGDz%5Wy5n{LS7rwP`-`oqmp+E> zFM;<23+>*62AX--4zw4$A7u@BG3o_- zNjln7)Ku3ReDOADxaYnBjY4TrQIDwGpNa2bab&Lx4@p-b1o)dT+pZ#350%!>oXb>_}jTy{6R6*^j~yso%hFS>Ki3K1rN#&Doo zKs>3{0N~04Z#iRtAYX0YKgkANUs>%8Es|X)OQ2JPy!o2!Om%^qQx0X8Nz0+xe!fz@yi&m}_;H373kuo?KADN>_3@dv zK4AKfSaN_~UE1=uo$y8#DPww3_}E^*Fe~4#i~#)>EKlOC zlO-!vH`EoJx5YF#reaKH`$KqK*b}j$3TUnixbDBn3O=-2X#Ehh#W~@92t$ekbOqBu z{0980INTl}7`qO6*!xR-`M;8JE9=Us!GuO94K_3ub*Eh@QCK7EmUY&4LkMt+>!jtvKAe-uouu$nQ-@J^DWZ5moHo@1K!}w zGk&Xl_a)TIG;okc(@Jv^xA0`uB_2fzkV5oDy>}PgAIjeu!=)+;W-*t79Je^&F`C(3 zjeG%M53<#fdXCNRd_Bd(pHY=wFTVian_OZ@(5br74rEa+193MJ%4B~uwV+GUqHEIA1&XFEvzjLSZwx zt!f<)GecZTYqcrUc_6XuL*pT6J&ZaJzanb+;rUI%$d@Y0;<1#OfXV1%iFL?%&kxDEV6%x)RND5s+t(E*k%^bX1|k~ zZ!^gLesZsJUAg%`y5w0A4gY9Nkv4wI8;GFazq zF4ZFRW5`QMA$Fs^EC5=V$v!wa)@iS*>O8l6U8b(Cu8r5&X{#faDoX-pT2y>P?|2h1 z9gIqn@xgC&xY}HeW?H+I#&K*28qhXoaM|T}#aNS)e5&iI{(Go|<)u&$Du!i8F4elJ zxFw1Hjt0h)Zr(UMy2qP8w~L#Uic{CtCiws7Kfhb<*YUV z6l{T9ml(Cn$s0T}5FtTYCArGa5rG?$>%Axn8ESW6vO_`)E(23EdbnrDn_x_*lih=J zbvwAcN_SGdJR5stsKbe!-?_ep6+6(GI&-mx*ZT!k$X5*T!Y}-E`>n~xC%*I+Yz5+U z2L1WnlO`+C!@x94Vp1Xy3I$Ym8mi^}3ZljJBO~0e_Y>(?e3$HuHpiBQD2tK3Qwc#A z+lz=PGSOs_Y09)L6`B=S+g~XXL(rG8TRr!JSI4Og=>0C&K}+N(~e+;W`3@OcVGd2UIlNyaN@5n-Q_?7|xZ z;Mq_hfQCB665hUNW8@eIsM{|`b5?gJ%S>9;yB4Fbz^DtrmeVQaWHY4$*4-6=!T!c~ zZ@^YrTSoh1V`JkN*PpMb=}dc`_@SGwfTGi4B71mIxx>xw#oUi+2VwGjv&&(*z8CMt??=a0Q4?zM zvdvz2loerR+Ogb@-IV0nBySU-a-njxBS%NO{@i@Mi`_H*$IX-k`UEaYNR6R_0U;O} z_zm3(M%(=nGI3j1oH}6{_Sz%Uy&ef#gdoXh*}SK&j;jT5B@7$62M9I z0tMc_3arIl!Mel9V-b}YqC<%)DWMbp&}@fOw0wZB_g8o220cf@{{_+b9Z=?%1F?aC zmNG-$!=v@vx1+t$G&?)Ht;cC#ZiblGzE+PIP%4DXf-5SRXaJe4Zk>tLeNe4Iety0} z77yS|`c1tY`yDzkBV}=G66OI^5x`4j7ZTji)z$6W?+rG09r(p|Hdm>G^JqNMqyB!} zQHoH=tFgJ6XXd2mxqovrm;1Zt^=CkS$Zb8Rtge1CQ#@LsRiph3=(6K;LE%%ud!yD8 z{lFIb;qx#vIT@FguDo?~I2%oW_A{M*X#XMvDSU%;t}kG3YYY4!(F%0nfGj3ZED|ep zl%K=KXdbg~{8Oh#U2!pOZ8tfvfZkW;h}@k2;C`w@cK1A+n>Jf#SZhhwl!1L=frfcr zY3Kjs?~cypg+(7wnuZ*CgJOr}PcU^A5x@qmEpj<5x`1ZPBK7i#2Oix>GBq*?0mFH+ z4#>6;^0{YYoNhE7M3<3~X~l+xho_n=EqX?dCQbq$d7#Ha57LiOKg>k__h5)dmAcA}h|oY_(( znVM21bCMyn!hz>Mzhz=cA{rAGtM!9I0u^poTO4?Jc!2*U<1qw~Ru}OYe^B-#E->Ht z*7``Ebsy}lwYmHX^r{36pgTeppp)`T%EU-=;@1kR}xKNN#OP1f_s zJJkl?iLS+Ru=qxy_{=2F(HU`YaKwa}na5XGiSa7{O^dc8@F-!_(D&oyrb6FDb5Df| zgg5b8PIV6sBJiNUv@*P&=~8o%09OmJCjZW{MH6i})Mi0ev(c$82#~r_^vk1t_WPpO z471_UfGJ#2KMLi7*6v2|B&-j|lo(JQ4be%$$#%FN^SGU83oh5Ew@ zNA{@3Z-WhGWDu18=xHJ@aTqm2NOw=|0e>y!5K4$-t<53}{t<`6h9K9+ zH``AS*YRP{Ad{Ve7#!8~icw$-_dIsHf`{Q*P}wTG9sB5lLKz0dC|!P z`4}0IkuKhUg}|qwSy)(nP7xKd$C)YF-T*YRQ4vV%r0P@)+r!a$2Z{kk<_Z?MGv85ONfgb^%yUpRijkMu(I`_zY~Qv z&YmWSWv)#`1?1axG=S#jiKWXR^fRBO5eHynM$T=GTN>}Q!-@<~uq0qq3qd6jcSrDb zQp$iY3zkfyqfW|L$0<7(U z>pBlx>71|69V+YRcETGnSibv@5|`bRxm3>lki;%xl*N$(70DL01U6W*LoDXNWc&*% zu@5ML-2It~t&}vlnD0TaxRlVryJP9>Ff8>8q?2B@M&T#z&9 z2613(@z|~O_wr*tg1_piu&xMAayxQnuo;5@@$58GY49cPiVuNqU$^YfVZ?RP>Kr^w z85kHetq2N=>S$atZS*y+JWT0|tG!Vdg-VJ(UFxEYzm?kGd)5IK07ZSCZiWkToN~ID zu6bCx7E6_KIRQ78%Bx(v&<9XRC91@CB+l7&QR)uKx)tdNhjdc3@tZU${Lt` z)@6!2^AT`i+N2GjFPWi@+7j^|-Zopg?`SFLj%JaAK>(3pb_ICgbYfk$V7&u%2VlZy zC#*pa6BXrC^#s98<4naTCI)5~`eDyyh0x4Fg-A?d+CgNBI$=RWq1#=?e6F3c8=QtzY%)*jczd$A5!GBc`=oP zEJ-E5vIz~L27>k@#%i)Zo6%J1wQ;y-w1~^gqoxMzb!!HSrdZ9E821@bYIOZsKtz*C z`}d}#07H!-SCM#a#QBG_j;yb0>hOMJ71MsC^Wb}w|0>|+;m_Ul`jk#7Ch^*nGZ5+} zj3aHo>Zz=fZyV-TMT2ZeS^R%2)d@i2o1M=AKk*kxh zV>R^mdH95S7hAJC+k+r!PSs6~=`9oAF*PNcrj@1?6)uDGbk3quX@)e?kf3y~^5d)K z0!*9yewg850te1yW4Mx7H{xmy2$iSEpzMtaDE25 zs*_LG7QWUi*8q28#5^*8bJ3t&z57u+8459#5t=iM;@qg%`DY5=F5W1jn|@Cr7S$b` zVgp<*JDI}rZ27ON@=!p#X0-TH=<)IGlSTi9KhCSfP)IeE+@&=>^x;q@QN2H;Z>Xq9K4UdZp zbAhGtlo-wn7m{Vuu(d$hL~H#ZO1)YJ_aGDBg=4W>D;f=7A8As7^+pFWAILc-x?}*G z@OJ1JOsaty4;n=&2_qq4!)DfPM)jJKgTMY$gDeT(Gtywc&YvEsJ=zV1sp~=&G>P}3 z=H{MXUl#&=S$f{Ro~9i$8G-3101jUao=^xg24q8UMj&$a%Y8FbPbrfhKudu!2{v%i zu7z}{*T_g$a;0ptVFpLBgC71#R%%!w1wS`elYP9S?tn<~F0?+@ITb5Co12+9gSwLR z9}JWnxh!rrhV9>Jsks)QMbmBjK_pcK8j;uL6DtoXW;=A*VI{}*M zZaPx65_zxNpA?zT8 z&#_giGSP3Ki4g>;jkd)?(U&yi2SC!PKxtDbAgCN41xsAg-48Q}Z##`ljBu0?jYC{X z5dc>Kc-a8cf@7weV{~5tk+Az)-`En1B%_5^MB`8#}(BOG6n~!kf2!r(fe5FPU zBlozSuE5~BHwBj$b(SKQ1#7{Kh*8Av-Q^_TgX1i&8nu?a$CwVj;W890(vDUuVy-&d zwXG*W$Kbc0ZH_}XZn8(Or22^J7$&Me+Dv9Ji$hLdNVd#W^2o}?(^65bO?=P3oXQYHkh?*3y_6d0`TFLJ`2UzBf|C25QT2$}E^|(sacy{ba?^(9jn{ z0gSu1kmd_a0oY!l_!}-tN@#e*X~DFD>#=HhF8kVj~z!=6ri5=dsEVR6$EVPh1~P4BQKzr7nLF{BT(E+N^FqINf=m zTc7H;il49A`ajIQ^=egfM;Qhr9&Sz%!oaf%>-s@Ov9mk>I+jk$1AtTOcaS^>w!ee+o-)igX zBvscJp6p8F9;vLX`o7AE>8qhmBl+c)+W>Ft3hl6L`nsls8uhBG_`5zwRZ>hoh-*d< zR&81|P1utsGtk1Dj07v%D@SR0@9wW6Z@gi7y09B3{hBF})6;rvqx`8_YYa73AE(V- zZbNgji_wP$^Y5!oId;;Lu2Wz&fHhKJmV4;&HNPLjhM>>UcJJuO!6MQYm6W?|=%=Pl zHq)p#)9es4rc|~YvR1l%=4L5FytIA)>>+(6)!W4Dq%F_8Ta(_x-nR=cV{!2|ShV(* z#t)#e&w2@IiY$Z5Xla@(cJy{6pBKjszf*t@FLJZ!=cPXhKRqI3GtSrxZHCWCtRK@5#d0onj(K0@%=!U!58gzg(Ni6qD4v*SE4Ih~(A-he`nOJfSZi;e$at`bOn36_*kdh| zF(wO-@Vi65ziB4(AzFJoy+L>f1=V4rZTN`YpNubZL_^esq;U&#O%@7@aw(qIE_QB~ zOIImxJ3h>}sQ6IDN_!taS^q4z6UWO}BdOBA4wZdi8n_@NfGmsuog2zF!p3P8dq}RN zE#qH}mJ0Y5?##ZB(T|eUJbbU*;B3P)=%XZXv(5qQ&Tgrf%OT(J`m0l|q zKxJ9c?)u_3iJ$GAJ;^n@LQO0$Op$c*@|vewc7W6>KU?;Nns3%0Co)L&3h;&08B^Pp z3$&nR=5O)&PuJ@1d1$3`y!B|C9cfhdtA>2`{2L zj5)d?m<&Mr9|2oV!#RvGtT~)4lImDq_|`NKx?_5q*Z*l)lxC zeEe6cW=H(gD;j{J9i!Wy=O&KdC|W1k(OrH4n7iY%$`UktOOW#7WM+w3scpR) zti|~&ph%N@Lczgd2KTqu&uxukph1=q_Xv&?x`_zFHjdI(c$QrfprXTq%L^-tWzf_b z7xJR%8-M>TKOu@9nyb=NV+bZP@5+#UY<9yv=nsYWZvu|P&t4+g?N~TaO710m@nsUluUO(2 zntp5ox!0T#zc`t{Q`W0b33ZezFA4yC)}vgd0%WsG`w!+h zIwV3_BKqsygR?SmVC{xBd_Vew1)ukI#&Qdi%R4y^*i__Kqg5z~nbaG8zVC?$ATKlN zFdr)6Q${HORlQ%P&!Hs!uE_f<5N?(9B?}$x&s90IRC9WgTsT?N;X)zl>=YcH7M8fT zSS?u@*WhOnYFWMQA)7!-21kj_4!%fV;wur`K)@?boN?U^l~WU+Y|~(#;a@Q7J*4o` znz>L_DxRHp<_&f9d(kAF(EnIDE)8|M9KMA5@vg{r#uKm}Gm@^hl~#XJ9_6YjEVbC$ zUn6s6p`boW4gLVOtoCLCmur2T_cKNcMnTKr^NDZvqN1vJJ6*02 ztTBJEHPL&4qN2%8W)8qow708$h$LEKTgKdLghm$Kb&@}*`3O zynRD9xqUjh#j#O+5?C`eJ`*JqU$(9EQu5ix5YUl?0117yx(2Ah=U=(Og3FvR?DnMT zOpyu#xRNGPzH|g0)0JYc(aD$V*+=7xbtt^^8-sVVGRFF3Payz7MBdM<3j$MytVC(L$c2&~FkAzy5% z2Oz0m-I%x3L=-`=p(2wb3dOhcpjIvfc7X z$|~b_B1mlgL=quAYw$;WyQdi7vp1B=rAyN-vK~z+Z%Dx6VMi6mAR&VN2@gTYbqTe$ zrTooKfpWP3|L(5Q_4Aq6jI+~VrA7E7V$ZAeS7Dr*otydl3xk_M4i0MrHj6%cP|d9O z1~<388^(i4nm)ua7w6~9S~!PlZ9UnBryd)}K~F{qn+h)8=sz=_uTU7^M17-!)$6sVTz zFFO8c?o`*pZd^XoX#nZX^vdB{+yLxt#mENlVTcSud5?)>6_AL)Ow$G~{QZFki1sf< zeP7z7SRna5qF-7rm3l!l(o%0%`<*nN1!#O9wUkl!@k!K=UF5RenaB-J*wF+5u5d4BY7+;gVU^TBwPah7z45IE`0P=Hy+98<--j_2B z^A%>pI4+-ghjm*F&w`%`&o-|F8}%qKYuirw_M<%U@%^uhIw+ykkG!P{#2~Kyd@rxqEbXGP%lLr??H{Rky9Qz)APh z^kjd2VsKSL7cA9s)Dl3otDY%@Y}hQ;6D^=Td`MPycNO0$6%nLCPI^+N*C_0IcPtf& zm_38sBNkz49U}!S2H?&VqVjUIW!{`LM%q+p_zZ}MvB%^H8tLJ2kz*0~t+wp{__>@X zz^>~EX1DqArf_9zZ6lFAO-tTkkVe^(sZ82Dz6hS7)ZcQ&)}(iJeN8-5nfJO`YZ>oT z&n@8uecG*~6(=e6j$7{$FJ+SCpAnT%c=yt0lI-nR4$q@$+dmslp|(bUjiEi^#kq@h z2qy(K(4L$)%=kRj>7?S8q%c}_9mww| z7lW#GgZb9GwMR%uUTkLed)L;LtIQW4JI~Sa!K}uTk;%tHpCTW(@X=`a^~DzPSdHIy zoe|Y0nx}i7PiS`vkIVw#r=a6jqF6*NGZQUc$n|yN%Vvat(tYSB#B7UW&Ib6yYctk;puuc4%u@^#ZKE$pS^3Q?#!p~lw5=&nML?FC}Y`B z>y%Lje|o-R>}%WRd>f)*dUY$BU>c@IlOZ*ifg6=rcUU)AxU4xF5*p{d?jLFTqU(HL zK&Qp>*-1-a+FzFvEMML1|87ve9 z@_O4_##EFtk<$3GSh_b6i}qLUxw1JI3r9Q8ub^EFtG)3Giqw;~b9xP`qnaGT1vj#1 zdR{=FjD>Z$+4(uW+U97kqD%z*zD4%HTMUzoFHcy%-ofiS|0Dtk@lO;M4i?KihEk^S zklDJkEXX;8;YHHRw-*N@1@jqudyN;SUi{vhQQkZ@b7-ijsT9ZCZP<$??_t+gLbMTN zE%uP}3*iJ)b+?V7=B;R{T63+|1K;JDqDuAfcUzEL>-ViLwfM7~R?3r%rd2mui#C1r zcFPrP2jb1v^ZRRBTnxpdxVf;oC8#kusl`HgGEi2%-$Lf`%M(bq>FeccR$(EuGzvPCZ20?6hZZA zy$vPRoz0V8HmmAYxZj1Nd>x;oT4^Y$=Y8+qcw1CqGCVrb!^lOTTSNKeoMwMG2F;Q&K>r|nJ8iG@hEmzLX z`68V69EQ1ryLD*<2Pq7X_|U7CX?c&19r%bil&F5D1SL~=%^*4Ezj~1Av_Hp}RI_b= z0<~_QKbyT{&?u|588wIQN&qG}U3Q;_^z^d6DlcItet+(S_lIX8WUa}?0`ARfxJEyY z)!uDR)EgCBL`%{geN44Pe-55%a-Kv76GjpWr_- z37fCF`$5{7w<;kWo_wxH49xh8~~~IXO4A4a5Ev< zU-J(kG}&s+C?=-QDIBEc`lWfunB~DdpMH2#3noCgYC?y>Snu zJ}xUC_#g?+Md!-zyYz@?BI<;|7t?4eTxS}UzWtO#VR7ZboDWz;Z_4dY!Ma}I_p(EO zO8S|HB69QKS$_4C@0$kAW>%XwK32BiGz>ZSmR2+)dw+jF5N*BDxE%ucwn_|r52M2-|Y>Xk$iBXgKmt& z^EPd_)Q5fD{#N9zEL_8p2Y3EcJZ*l!q;r?7ihDi;l9bScO{%1N5?)V)D)J(gUajxg zM1~-{Kb|LkkkuLfaeY(%rv0H$GYPBtc*udz{!Fgiu+5%)il9;4sQ=(#$2;>lznZ;G z=vts{>y2h5Ud%IG;u6;2>aej$#D{q3Za0H1q@*E60WD)WZ%tIX-K@m5Pg8JNSXitO zl3l{ZBFT^oo9YF>Yb{74BOza1Z{qQjbb1n)YTMxdB#kafrKgZ zkdPzwdF~UuqTV>J$}8@U00N1zA(As9SJkR4$KW_M`uN#$t1|mi=iYbdO*f&|eX&fr zlFp^x&l#hnRAkgkwaR|bs9Dy$5U~8Fjw&(5jPwUxNmC*Yq1t`JH{JEp`4%puZHb{m z&e{E?V^2?1TJf;eRlp#Q3dp=NurzsxnAm8r2e#=_xyjK8^Uvqf)Xa*9wh*EE><6(` zF(z^lhAMUt7rGySvuFG(&A%XOO=k{rx!C9_6&Wj;M39KgYjtbA?QvnMT3HWEM8|Dq zjY}Ud)zswRsxk-&?rE*mvQ!0U)O}9##`#f=*U-uHy!ZWVg@RR@bS|2S_oaPvUhWi` zTEuy4o#VvDKvm6nPqbF z`1)kJ1c^)`QNp+Lad7SLL-noZ(xNSeVOHCuFWac2Cv#1N7cU_ZVgrRjbjSQ~vRO~J z=p<9(gRX=J*+kt1RSA@_3ZS%N9DgffP!aHIn?|0vLzvd9OlulWlck;yK;9hqfw%|1m zv%U;D0FX$LS%zufmD9z7zX&mp>hSX)=`6M9TO(q!XRjaz*}_n0W~Zcg4sW2O zrATbH*Q{yZq$)<|>kS*dT2)NF35aZHOeu$LI}eXd0Q1rN`dgX7<5#K`>NQPxdOnV) zN3HUNYn`{#dCt+JM)?KCjm)qx#PdDEQ1$CGcl+JVc58tPnfPia|GZS5+lu+TH$sk7 zwrMG#uU1gOHDn9|$DiK`@J2Mn9ygDDv%q&g-g*~KuR$+xJ+t1x zqT!85KfYJqXWDbG5yAM0#o<&SF@tnPt3aH|`kN)B^a!dmVaQy*HQtg7t-)o~<1q8< zL(7YKrCu;>)u}pV+FRBcoWANddLp+6a$)h_&P$DO{l|I*&_%E}i(8`8RB_)-Cxnk5vykq5qNdW?RPH`7jc z9?bcJQoCkAqf`fy^3NNj6RpWubNgUYmMq`Ep|K|@^KsgdNowKghg*3}0zO(-v5DCM zc|<9K&hj^!#(fD3No4%~FUdviA6c0uSX7rvR`=u+yhN!?_~L#uG=GB6jL)1fIY&00 zcUXUdfA$T>n$U8v)%Bn~(GmZ6?MGp6D3`tp6|m7K^Q*o4@&05FqUGv%d|H3&?l?XE zL4S;9<23PPrcivg+L9?UtvhRDvd9+}HPLy`$4q?@hdV&d#)4?NCCUpq*lo*@jGYu2 z{ca~#GJ;XJM(Fxo>1)oa(acV%frWF}CeanO<>E~kko zv_rjNT+1@YnytBMuK8~IEho1A=ArN-Ex{}?%}P@!Su(qYa{d_EOGw?rTDpu{(0Q=B zLKrc3+jAhjOSbB*cKLhtps$o)J zI{qh9j1b~7O8q-4k- zaw{9zL)1OoXRdfusy{Rcnb-Ew@yQ4qd5frB1FNxxFE`&{dVoNJi$!0eEprL~B`^39 zciXW^xQ1T;4qhK1paK>+*OfdH(A*YJs7S4Q4ukN0yyPoNjLz!+GNRoA;}6#|iETbp zS9(`B#2T}u13laW&yT-Gr!~S!iN0_*U z>VX$4SbED0bU}1|7o0A>C64y;Urq=6L$p#ptMdKtEd7;equRp(z}!TR1zSkNk8CMF zC87A^e=l_aNyqwe4|H%AZH*b5n3&j+(DMF*{G`$58oV~zAHs`b`wN>QBVDP6vtImV zbC$&Y+|cdj8r&JgLOz;=sCgP*kc@tARoGU9&4dG;NNz4j=jyyWTZYV4yXgLmMup_J z=t5SYRu+CX4BczBSc-f|7U}L|Io%hIhFivWxmS)!Cak>PEho_6IEOatX8!EXrw(;aN7xfZBI$nQDcb9aX+ zlE^NZD0L@jIrHa1Y=9t-5PPC;DLycHVWkUx8_A%5>yKBJSoGp-PzfX0RU zSt<|~Z45@MAVdr#atx*MwZG8qjgG?3rj<(<`J2ggFgApRQiYKAqD;;Q6J<#&6 z)}f0&dv%bAXVJ?;b&GPXGJkmXn|yS&NEuK0ouI?%mFb>?3BBUg79mi1#b_PyA(p`z z9){w((Mtt+>dv^fdhOKMOPkD8ZDw3Mn=cjn!(gyM73n{#dx;RyC!Ke`)KO$*INmXS z>d7{cP{49dJXK;LG}!TtFQ*oW4O-lH&NDlGX2>X!|4yhhIpWdtCDxz#)&fl#LO;Cq znxU)j8!nUk)aaix#=w<6Y-;H@t9zb!-E1`CGN~K)g+oP7ZWyGU{g8g?(me9pVd8N70vinY34viMn?BplC4gy#Yoho zKH2SzZKF%A#q{f|nPV}Nu{@dLYa;FfXf(PDj9A{ojgmo~>T zfM_*otLFWs1IcEg$?I%8JSqyy^}_8Yf@*;D9y0)o`1@?DeAs1Re7r_7#<1=CMx{vM z(XOdFZ^*oWt9F&;_STxkF7$5lsFg*hE`iCTW=*DLVm(_1pGo8TyFRUI-Kk3MbC&n~ zw&#dmE5?o#>7a(HFVQ^uX#<+IamSNxCX+Nl_l8xGqX=)7 zR&P5vMKZ`O^!Kym+mEi(fr%L@DMxsHeeKz} zD=^sgzQ)|WIcPXfCVdFf$-&C1*yx?cZ?EOj=rdpGbKqTTY;)Zr4cE_B=Q8o;yn-!7 zeXveE+Mj(X;Jn9bIKXOqFoIge%|ezA2lMc`|BN|*1@r92-@hiS9VseOEl#0T*k{z_ z7*63ZIz23RE}EEZiUbkIs&ui=#|4 zO{*&_uuY{UfJ>2c^GS%X#2oeZ((|le906E6AOk%|xhwxHzPd28Rc8>8G5%8O5lBCo z+OV+>6#*`GX2h(&`eTFf=<#{#ELg949m0}F2jM;49L@GbI^N#fz2e})7en1)@CrJ0 z#P_z}-{q70nIL?n0()pR7i?65^l|J8eU(9};?hiCzV^rD?8a=3M#mYpaFZ#G3Vj&}kN9_+Ylu z=QyBHZ$a-V;e<*=aDK4&V_`H#^`?TF?vcKj!;cPYLtGzMXGt2XX6s>-hkY-uxUAGB zqtyp!^QUm3rDVXz^pE!top;+>9&$^$|5W3m5Q()Kcdit0#W*J{RR_~v&VI+t=d_*v-qRz+C%G$TQWdw_ zwVx_XD&pQfKFp$5mt#VsLL&A_j0Nlaqql zLVP9%`(88JPA4qdQcp<0#{#tnKoOjjG`V6gQByB&Z9eyt4QEBn;QxjqnW*1qabh!i zB8A|ZS(Mn;!K39e9!U5D!3i(QF^!@tT_u}hsb$t{kuk~6p(uFJz8Hl&_pH7jtqNXu zKk)lTS3_rp$BAKgjd0bqymW&WhxLJSgPkOK>qcntMDME%mBSyn0gXwi#6mr> zz>ajvRo|3+|8mlQ@e06=y?O+!zfo9j>9rAIv(T*^jBOEGpa#o>o19n=$2ZpQjH_cR zyiKGx*%z!2yCRWMXB-bn^E#tE8p84&4zDoZtz)@1{h`k#SZ@hH=Iz>CM4c0v>fV|^-ldkM@WvGQMv`` zQ;tk7mim)bDA|sZHLh*z=fdg-f6>IhpT&~yMLeoOmU<(ZX?qW3F~_!24<`Mhrx=4`>xB%6PGVmi{l4iM8~}$Sz6j4?Ltm16W_zPL^2>@InS{YZ6RF zbouZ=>TF}`D7w4*{W?WH?Yo#lkEIc^BA25IvR^ca7pxy>Lp#@0?A7Av*wD;rzK)Ns zX680;XX7{?bibF$<4SYNsHX6m7QML#s>N+F3hQB{0(=@nyT2G~ubZK;LZeyXMRBC{ zL4DzMSRtMACDJ3ou~|b2bnn9j?P^QainN{6)3jz}*h5loYn{n0E~&ydJ@dTI*E$VO zT68z9Ol?`J9D(;(m^=8k_J3e!UZk!1*izhuov^~Kp) z?S}=rmB)RyEl*HU>)p2c0A%K}$M;RD)}?a+#C6`yz3gvLuHn9FVDbeI-@?RqJdfh0mk?RUsWFs93fcD9cL7 z;|&5pssnz>SfMt&dZ+euI zH3m09Scx{@%J{ zK+mPLm3aH-DA3Utb-mGYSE^HNVGY(Q?0^i9ms(az1tC&86IM;0r=-gh%~o19rm?iv z+rkg{y$)JBFUSO0w~sJUMzmkf!^4#-TebMzmiiq{u`(k&XH9+D}X;I8Gtix~e zuo?hm-?-g=t3_@#EJa4Gtam1=A>sEtO|8{S71%M7;~rHfluX@V(IGsAPHAz`58vHp zXJjk^TCBOX%ocdo$D?#QH22+e7*JMKtJ=Jvo?a56k|?A#jDW{vGuaD&C{;Pr)1r0N zTPr78Sa&Aq%*xfHT&|MFx!QZ<|5L4c$630SKGf*Av2Y6Hc5;FjUEA!8qQ_Z-TTSQJ z@jWm~^m1lwGaG4+^9)t8{2}%l=O-qojpB9jr1aXdFFK z_32+d;)nAqceGYaTF*T3gu%0e$!3+{ILW6iEiH0dE-Ep=@uAJ9KbWR^k+}V?zymzn ze0#Y3QeU4eJI6cXg;3#fbK?CgUK@JrvIJm0WQ;rPC9;t!HB7MR=+5pm zx}RSp7^!5-Kln~{E_0zW6C1gQW$;q*d;2Gw_cB4#DL>J*uFDPAl7R41@fkh*aP;NN zwl9M9>Gq(}4kT5YrDZXWHXyidf-im16I$TdnWQA)u%;p$2VX7Rs4%G8(y$>hvgat| zdkU#^7tFoNhE_Y73|=#Veum9V^!F-UDVR%IfRE@@Sr>sufStrGAm_^qqof@rK$GZH zoVWX6t~&HrpZkVQ-e&NyL;L=jQXy9>idpNAWABb*v1Lwv4dhz5?9S-B&V;rk6*k%@ zXRm8ZJUVszk~V)=S)XUKRjkUK&xgCeZ^N&_vvIYz&0~dvhH-p0%HU)ZxDro^JzZg1 z!}843aR!|2y%OQ=?G4O=su}Q=Rz6u?hi?Es4-K_doa}kvU<$yX>`&KQp3hP159uC{ zejoO^TV?>8DV?_W_xCe$d>ARfTZGS5%Ot1G&!qCYOTI=siQ>w{2;lRa$Wv)(oyyah zR(_oEOEl;KG5o{GPhnvb&`3^_yxYzUsN%g8#YQWi!iHgi z7KC$c@zGwZO4<+Lz$fOgg!rlzKWk}}-W?b)7;sM(dI3M3?tPQ#5MnHzHJwt4V)|r| zW-%<^bQZ=H!{_$lKm+9JeqN73PyuvzUtvh{G=PM+%BOh42HCDcR5jK#D~v&Bv8DXQ zayvA@1pSDseFISXRd@w88zYq#X8|*SVqi0$HTvxfnMI>I9{LI1`k}r@?rhX+FF*xP zW47AbNNOzzE(&mGPP~VJOQLN|O(t3VX1~dFxY-wLH@qv6mWx-tB2C$=J>qRW9PSQf zs%(XRj;Rb-SBs&CGe8rf91Q2Z36>^A)4L(2otTK#vP}2qsE@Gh2oL~Ipi!Z6Wtu;> z$??rFhdN12*q&ID*}bukaMq4+P{?h`=X&>wGVpk3Z=#q7@Gcp;0A+teXArYL_%)fz zC!kK)9iQ@9ZyQw3nkNj>$wu=#zXQJ-)uR9*hNitHGEF^COmfJYCPPboG5RzaF$vFM z`}9gSaje+%B+4|;9Oqp*B~rM`>3Mg!cDJKKOqqG8KkaD2SJvP%+NCrhpG>=UPv}$O zf#<2Qb2U*+a1r4m6rT9c;AeK|EV%^%^XB={r<>=oBH+mF* zs^BIn$lMzN&tAY2B4q<(K6@Z+?6xoOEz9`6jAKswXjEugB=H--wtYsNi3W0IlhN>E zSud8pN%E*N0!WrSu+y`cFifg+hWKeEpWG9+5V|_7tIZ(!A4y!5cT=1OEfXgup|}{~ zqwn>9GuRwG*WB!K!F;zsNvQ-K(?P1g0r6MFOvl$ocgIc_$H#}C-G#nrB|XjX2lcb^&`noU6IRVn&4t@jw~9&$gz0>o8$bUSmF0o4VI&-T1K zjxXQ3S9BIs3KsrLef@zGZPiFA&zG>GgB#5((@#s(K3~yF27Qe&8z|0t{O3^l&+uRW z@r}04hWvG^nZgWmKGrBj`J0l*hsj0q-U(Y-lM?-FpQkff2ybDx{p2X zV*?Z_Is{r|-X{X{>5idkIl_`p{z9C;WB6U-*{$QmUXq}K|K*tP*SN3fS3L5zFUBlF z5C2%u{=HVwHfJCJs2i#_ruzHde+SeAP{H3l_CFs0{?d^GT$MXIGLpY{n*YRy|GyYU zkmO0%?5qdyG-IIIq4-g~%2*7g;1&Gl9oh&R-QA9?i zWuyObY4@N0tOp#bS*-z2{?`rpJq0LshXntLHShoO6K4TTq@((89{=}u0qM$5{?8=$@PPxPHh%D5-zDnnKm5P$>z|to0)Fb}I~?{0|8-;U)uCS_RJPHF6ehslMX7JP>Jbevia1xt zl0P<6@g~$?{ncL#(6E+Jq66>Qb)DBAfWRCuYYAHPl>jI>aV1f}XIcf1a9iQ}W3G&# zuEuA;$aex*49tdfS^K|JEyol^+`4<-lr}q>dg)ZSVOMfEr|;NZ54blsJ8fAeh77|h z-1FVd$ESW^l3pg;X2;YyoLyg`$A6U9Z17a0dPv*~x1S3mlel9{UcaX}A0V;;(}?XT zcCXNo`=Q~|C%E2CF51l2Z*+9^dt8ukgQlxb(2-r?B_e@nt1y#29BScIe(ubt9}X5e zV;N$8#ISi4snQL!1O^1i7uI=g*c7`oOEqz1$b;$EGXY0^zVw$lPomuK4QJZ;EV=}_ zDkXuzktyVQRv7<6Kzv{#jymMC|4iKXz_!%Ji-(A$?rv^w?jUy$4?dgY4K9GNw@7LH z5SzPLqWsne?i+vIl3HswQ4vc-BJ40AsKFrB0=qL?+55y6ty(A7qj8K^sGeyF2~T!O z=)zSPRa)5tw4eQH4`~ZIQaY_`0>8Oj>X5 zlm0S>$&dE8Wh&6G2nd+7F1xe&8u@X9MDI_Ep*CliM@Ha?!uR0BZ88DxhO^CNv7SO* z*mR3y5_V*+iGvMc(=$k+{Ihvd}AxN z;Jzq5oYZXIQ`!ukIky?fsdV_qUo0s6@|90H;ly^8u={q211Dat={!CFZKiT>b||@q ze$w6}&hJ4F5F(}&bLIamVVnR_U!OLjhafdZxGJA`=2JCX4cnv5&6VIf*eeg1QM_9#c zbS#!I=_jErhNq?&ItHp<^E!T|H_rXevE+oHkUuFMc>muh(MR;^ud>rNp9@(hsbaen zzJ_UOtsSXu{dC=5P+6W3foI_{cS^~P5Jv&dvY@Wqnt#u zVckQ!3!od`#c35RxNmRPl~`7SPQB{GB0}fQ#g1O1sYzugkeV&xb$)xOM0T+YWwuTl z*DujGhJ-IIeP9YGw=H&ufVMlACOrW3uRog3Jpguy_N1gVIo=^PM5kkFJvMz*t8C=8N_GNc0U|R_X4@L*q^9_8>~6uS?c0T2SH-ghoh1aolb(4PQmaw7;|i!?h@`^f zI$=X3S}q7ex&%Y-l`Irq zU0-T?dD`4Jf1WO#*FfFezScdy_gU{VzjmSLzm1;Z&jIwGfh)^tz{8_nsCwS!_p;u> zl!(1Rp;TuY08R;A?5468J?TDMdq6^%e7bPHIFN+l0&7s{QZ)cXCFdSnT;})WWu`nY zJTfeM&;~&xG0!SVlf{8ORf940YHQ$1CN9_p*YE^w-lxjF6R0)^%-pPCj#SF!wOcFO zQZ51vw5e2gK0gu@6>K0Rd2zHtu9juOYtkPx{^;o$WOz~|)C%_-D}zQy|Evr)mQ_R| z^qP?5t7svP1lnqU^xW{Up!i<~JB7LJ2}XXjGR2?m<+GS51dWrVbF(;cMBADwGu^gz zy4JB4A-A7rgfusGrj}UnTPdT@Esesf;UM1UNaqA!h3W$0O)QC!t+aP)F#sL`EO*~KTgj}a*K>b%q0KkK zKTLNJ@HrS)Z%Kj)V;j#wVwlPVXZxbgW4ub(;gq?SWeYnY9at z#dwDN$%cm|PEW%Gx|}3+*y%rfDl^XRT-wk9pkrY2Mc4NVg?LT@$$xJW!&07)9dE6q zCBU=yAik7}Q1vTqzUE`j%ND3DfeZr`)}-El1@7R|SH#fgfk6+7#!EInI3?be3h)x1 zh~cy7{QwM@k;APF>|y+82goar^=xBXfHV9Y&=?Z~YcS*zj~9^}EqR_whynfm(rKLO zvzxdtM+Q)C)Hp(3nzJb5ahth_XP<0;=1*ZW0wrTu;q(CEy=uK?z8uf~;$&U{Cg8{W z@Vw6T!0)Gs>;4?1Za`Kjg<5xpv+NYZ>qE#{?sC3Nyrj0rdyc`XpuDG2fVU?2C$&8j zdA7gHRdEkO1T2$;1d^Pnh99*5n&>|<)*^||pe)X3RdO3)k;fS6S-qapl($x{`z0f8 zwg0+_K0KD1ONLP1FCob`kcaJF6~Vk>-k2nt+)p67a(d-jN_<@i78-QK+hT=41LEW3 zm8OyiCaOSLsD$TcbPER0^uKKdHCRI&t&y@o1B0(|dEAL{t8Qn>c);40`aU%u6Zbd< ziJuPUIiFww0qt)PYM1o@0fW|18SnmVtjlY|cf_~7G`Xo8wVe@{)N!l|L;H;z{l3!y zaMxas2NZq}3+-PW?vLDEKMQ_3hI{{Uam^(kq6DccLHYlNxQ}qcfOGeeBi$y-{k#8z zki|6s?CrG1i+Mj3`O*QI-TE%lnbU26LUPq^&B>$}YSSbI1w~Ipdf2yUk=wev+IeIk zIj0fc_5}r92tacqLiIjQH^0kc# zcmC30|0jyT)gQPxb+*$2-P4cwX2*zk35#3-J+Nj}ldrx%&9Kw}w55cXE%@h`f0q0( zp+Ll8BCB6w-rnqisZpvZX|b}Ek81fqAx*IST&fvnH>YS7;qNp`i4=<4w~--QLP{v? z&=D9KZ&Zy+e;=v&_5RYHn(*#b6lr5bfLPaTUXR}sxbWmXs!Y`P)~z=Utv`v^D4bw7 zyL$(K9pEsC>vlYy`fNs2GyJ8@urp6L2I>^~zkr=A(gHDmsri=Ksnpq2WUJ={4M}55 z8~_7{=8*w2krdLdm15}2#pE1GS~*xpUQqc;K99|)T5NHekO$`0X1Wx7e+=df7IpWS za%-LkOw2Tyuh?Ag*zr`v^ark7y?c71%?4qHS=I8%cRDSe)&C1P7UaZjHwn8r{iryz zoUp3&Ug0JRe>ahQwkb3FTS(+ z>60g(xG$y(3{v+R&p*zVdyHrs-89dw{TI&b3IhS$eJr)3q*W?6%-+%U0C1=SsWjn4 zC+k%Nj%vq%PelYgecC@mEmE5B>zJKjjX2+g?hoh-DCfzRzs}4YWH6O=x9vNf<~Qaj z)tjFUz1WC7@xHZ*@VY1gZ|dm%U8Tr~Y4#(JM!<*%EzvvLtw(ok z(Q*Oo#Uc@R&fBN;Hy1GHveNxndh7~+eU^L5FM%C>A&GH*yHbm6)ibwJ67ls&kazFYzAW+EiJ+-B8l1Sf`US&I?Xovkzb4;WZ=F+ zmE!G?SfIi1t(c=&7`xcwZn0;sHD_3MEQ2t3dAvaVwFq#+SxuJA0Xi4Iu}Epg5;-6> zDNo>H-s~rWUrZeTb^91<0~^XmbQO_54=k#*sOy&4BFqjj;x_oTy1?>4aqK1zR`9fd z0KvryrMp}Axw$#z{CAlnouy2R!^y2BHrW`JreTxwE!E$+fG*g0SXfxNxW+2}N;DE^ zB38?+5W257^G(jPD0T(Dhy>eWcG925+S@5&>0`FW%AGgE!tiHThhl{W2ul(reE&68neziTd_P9agm*yO26tYmrxv+TPxdbiCnyNZvN3)A^oMx!81V@tl|u zpkM)?CnV=BI6vTjz@G9F1B`V5@2oL+DmECiF%HMGA`u&XiE;=esYJ(A zoa%;N)8_9nr}OuE)^ZbuI!C(LmA2Eo2Jd|)zP>7t655w>CF%dzKgsP;fDSdwfe~dT zTFn$z(19K}|J9NoJVo==vu={d#l8=0qN;XrceZ}kcWjNw98E0$oM~sgC=1LM zg3pj6NBw*#(erp*bB7nW(p*i9KpALX98>7|(EHN~Cz9$ygTuB3Q^7ZlQI;GSR!=F~ z+r9L>q=+&|MZ6tur)nM7dtFw#ndIgYj;?M2rOomp>IYf)roe~GbNv?gOy?Cqz>Q|H zwb3U_54U<=7*&9>s4ZNg4?i8ZN$Oe6cTbCSrS zN;EGNtY^L`RQb5lmg=64Ay-G53)_k>pLq;SrLWqD)!r|l*=h|Dz!kj(*th9gy>3RT zkD3780~L)CpxU!bf3eNwX2=W8D!E~!BF=y{GfBwf`5@XT zBi%fj=JG`fP1#qwB~Qq7vd(5Slr)y(U2H= zRMf!gG^p{hX}fu3vc%WMZEcl#GR$u!Y@d$Bb73AoJ}UN3-(#`yvt4lr*QWD$Xi)1zqvglW63m3_sOzK$2F zXmP~WKtGUM05{b>e58Fl)DVsUs*?e5w=cB82{jC z^W?@zh3MWNCQ6Qt3jB6#UB-qaaip*x4sV?fpAaED!f9&zd6jwMoDJKauQaL}etPo# z#X0Q&fAj|$pEL2}tc~)RP@<|ji!OG?ujQ|>F4D=2{vUU585MQgg^w~r4c$l#Fm%Jv zDIwk6NOws}2uQayIDj+)A_xd5D$*TNiijd9f;0%y{%;?jdf#`gv(AUJ&ROexlI5D2 z-^?95u6^x&Aw!ew_RI7GLVqnrdp+7VGjY3I&0E(V*+CM3Xp=%8P3UHr3v|Uj+D+r9IB1rV(|8eeO>D)RUvCfImaWe`i{XtQ3S;3wz6}VF&=A!&BL>!>bi`EA? z7o;z*gNdDyff+l$DYSolcsd&9ZBQ3FuKCto;57Fl@mF1l+w#BaLfNyjyx(Orp`(il zEaZLvyRb_Dq*ZNwA6N9R5B~ktLBXuAd{(P1633W>^1rI44T`LS>e+vF7=Y7?FhrPaGNv*z@hqPBr@nk9*FVe) z<-2seXiR-OI;#69R-_n&or-E8WXNvi_-F0XD=_u1J*kkOSt40a$BhZh4#k)@{Moy>Fk0NV8>rwFE%8l^!D=`dG~E>56$-( zycYU@@g_u@8eDVX0SW#H}RpuZxEtiF9_0$xEbyivE6O z90B<)l7wH#rb~&>-_ssI*@m*AxVP*3J(kPJgyqF;b{}LIb5abs3c>?qG`6qO|Gqki zUtE!bQyS4*bPom@F}8laGFk@{stu?V|G4a5Tc~Odol%1~N{00ed>pyRYEHNr(hUAX zbHRH#Quy05>-`(I}+ffnLNiamL+6%yEJJgNq#<`PZb zE+u)J;A#6!2l1<#F&JAy`_COu)QPAQBV7>DKwh8GhR=m4%f9{uRHWUo`#lyu_&%RkT4P!Bc=;(}tNs{p&q{3Ia9T4-Cm!g%U=O~6*S4~?US2Q+65H?7?w9}rYp6U2r?F0_Z$Y(0wLJNAA@!a+yepN z_9QHfn(n{Nui6c8qBC1Z@k#&rdcXgAPYE`4?*0AAe{IokgTV637AB62BL2H{>g@>* z%>OSQ(;3+b!UJyO+LKWsAo%4!C@-*C3Z|0QgZZR$&8}dy<@2>HWwgi>(!G@WIM-|c zv3Lozkzh!2{moZ1E}I{mi^npU<6Gu|Ai(RZvrPa`48tXSSD!D0yI-fVGKXZu6ES>S z-&^W=3{=mp1P(~#5O02wGO0xf{$BWfPH!O7zHs;FC17iS{yJ*uAn(xItQpVi>d&t6 zn5GLl4uk7-pYNt*MjG2A|DWTsKSTHXuHBpDvu}?R$1_yiq+zj}+H~C+`C4nN64lq$Je=In?%i%WRvutfRH8xoI zvAb}qofk|A9lccnaKED&i(AwI?fd<-J3Ec-hQVX`BDj^P@`*5eP=ie-=UfKKsuSBw z#qaIkbo_fX-RNd+EzCCB-{&#YuQhE9{2V-x*mG;DVkj2xn&A>)uZv9fB#IaStZ5bi z9}QxRe;3^o0wSq}oOmq3D7&?X_pQz@4#&ry+xMrK0nqBy_=l1JkvFQP&&=*qs}C6G z*68|Xdb$aWz%LFzb3Irc@+4$!e*V7RS~mEgBIL{Fru*5zXOl}D&l9yeS@0^O#a*D1 z;W|~(n0nKoI2HWv%^6-y`Gc?Hy9mJ`Fa`7GtJ{v_Me`TU)kR?D4QDS3H$>#!rEhw3>g^(|z+KReEMq>c>gtBS+twyO4xI(BS;UD*6oe>Mh!t>lQP zYxxcpn^IwC{^jUkzrTT%>`$S7Y+N_j>a%hq7T5KjS~4YXGl}a^CaX@Nq~q}+7)W0z z6*x2bwdjuaVI6t5fxl)`^YDHCyGP%Q%4by=!m`EnxO_7PXU+X> zbq246sFv51%A49OfZHo7L{P&gd!!cZS(O>cl3Vc zxEc61s+vF~+n_DTC(PdC`uEi#vM}D-*P_`Ij9M=MSK}!qa!Rr$7U^a}%QvS}IYBTx zS*{Xb_~YhF+v#RJcLKf3HM1W9FTY6nt`1ge73=_siJG^;p7sI`gT&=?U_8I8B3Q7q z&H9eFetqQnRob4EIFwEv#7{sV@{ij?fPD^K0T<3sSVbjc5aP)$^JK zA2L0qrVZI!_7-vsLYMlex^*|M?$~gvW;Ig7+mi(2Ewmq?TGiDKkw|muCnkc?~Eg$C7*04Dq>PfavIBb{oISq z5Nfmb6P)iPOR8IbYojmxH}sprm8_bL;sXj&e7_8HlG~97eP7oD+8cE$Mv3j;ts3oO z&7$+F&6+AFW7_vc1&=(RrKP21m_0V;bu@opCy(x6I;;h+YXWf9^KfvYlS;p-3>I?s3GLMbb{tS zpA@qvM!m9-81M^o32}$|=RPaShtU;U%G-D@jG20!t+hY~LUhDkBrhr~sh(Qm4B!1} zoXmqY&f)j;Wk9AFsiXJlmj=Pvwvb;lp;Cu`K7Lu{SV@J<_&3y=FeennWyFQ4wI!vj zZAYFk6)z+}i0nGfW93@A>!h;UXniuMQnl8&PeFk}IA99D#d?{6k zA5HznyC^>A*K3<}tyBI9f&Tn_)ymMDCSrQ=8{*%wK`9K$4lu&6LmI z7HYvbc|(rgGp(oXvBoJq)iWn+A3_YBm97e$mH338FSwYz*1xgf26_`{C4eaxAw4^` zz`=BnDUa8s%IhBoB!BtwwPx8LP2(~`#ZjeK92I3EP)XKqlGyi>}O~%(FjM>4+9NpLt#UPJf7kXsyy}-`l z+YhCELClp=L2%Ds2JM%1GYt!{bGXJO?8Jx!Xfz7FbCs1Jk}mvpOO=5)cgW_5{)?3% zZq}J%w$6yB{LZ|+wEiqW<@?859h@qSX!Ap~@hPlak`GPlt@=IN*nC`QLZ5rhr$F;X z>($`kiUBFD_Kd?Zv4xA1m9!9KOuLcsX!oG--EZ9MTt+qP@>R;I#yT!`2~+u^9Y6?# zRhV`ey!frw{e7b*uPq8Q-K$?N?t$ImSX1z>Gn`!SaL@AX|Tg*rJubxw9G$-`RSv9pvQy`Lz#Wj z71Z2kJ2&|^9}ph8#Ax*rk9j00TH>NI#4nFs#RxEQ?=6rV$!Cdpgp?_n_Qy{rjOD3} zS^Ir4t-1q5Y=$_>bIj)SOp|MbGrj>ME2zT)^7lzH5S?Ead-GS{1%@4q&F51WcZKcp z(wD*+w!j4Em)mMq>Kb-`I_>6YyR{&*tz+9P8Sw3GF0X}~Pm+(t!+X5`KODn(YX$QO zN;h_Jan~&zHC*@D1x9pY&)4KAgC3q_;6ZGr2V=FrBFxDI?f_16~3ae%#v>UL31p53ih1K4N z5#gAlBAoeZ*%E$E%$=p)1=K|iyJ;`9hs7Pax9=S7zZgKlF7l zqX)H8G9AzZ^rgeb&XF}!F?iQ!N;7N-MXM;3s)2ID{ebaZ<-b@g6CeDBN{weL)kYeJU0C4%X<{N zBPBC9GI|sz<8iZk*Yo~v(EfFdCdP7n%F3vc9M?%QLmsckHM&?EkkSadl+<0nC#YWV@zTb_^{k&sDUP zI2zQ{tImFkl=3$lX)Z`V&QZ%^y98lbzgfT7xH+A@EOSrojHZia{^xpnAkt)Tlz*z+ z{gT-p_2a?J!OU(?-RW9M$`>w@)WMJ^E$G8y9pOavyepr;kzmYkiLWSRDyc4Rp|4XG zxch!IR0|=Po5o34Eur{wI7GAdMMtgKs89EUwsN~U4i$~!?D8vEl_R7B91U+uO}XA|^^JB^}B!z7KAAM2&iiH#jBu^J{$ zVvi9_MysYA@pIJz0#fKofpggD#Q?+IYR0fr4@JoLv8HIW_$ZnXuh_L?_j1U2t1_yv zF8x5kJ^v3lxcvEhVIM+g=HGgg+1e;bkrO#~E25 zmhj;$kx;??{79)T{M&R@8XNY8iCnSdHeLCtfw>1o-kWuydIRkT;-%gB`W5#@TPFD{ zWrofQ1>eh28*TiUKhvPgJL3d)SQJFn9&&#Z!(hF!5y6MGY6SUFrRxzl(42bu%P54} zZ4?y@mGy``VKsKZ8NA~n-M&%7AKro;Gn47!K4m|U>WcgNI8j$^tV4GW=ItUMPfzA< zyn`q`=LT2!B(~CH{q(8wSV(HE`J`snde~vDx<}FRw-TcM(w707T&Croirz*)1Puh_2sA+_d1<%L0!IqY|-7TU^;MR`ZxYqi}x4T^jv7)gShNt{bpiA zB2XIoz$#eITVmb3_lDpw{WRU4H)5(j+UE(0oxv%8`^gOkiE~`f<-jwF8SU30Z!-1^ zst-ai(q!Hx*?7&re0PST_cV|Uzc>L#bN0O&7$T!6FL!ro|8J8^obV#TtDD&@k$N7C zx%gg7Rw&~92EHk~*o+=42;>E99los%RGW>jzz*fK_sU*;7d;JmY#M$0``Zms{zFQ=!#z*Jyj$CM z9OJ9g3ni}WI|hU zrM#GGT%0yp@FCb8#)O1@mO29ReUlzCXloXA+==>Ra}mmuVwd?Y#tFe?PFS3yr8w%i zT3n${YgyiqNYhL2mk~N!1YPqNysUrW#(=CZ27Q?)Kr86PB>m%)Up|dZoAA#Y&vm#! zjDsB6%wsc`&@WdeIP_-~mc8M(mNUTQ%3adn_KvGh(6Fin zC3>QpuB5>W?t)f~(rNxE!Pgh9H##?qH=4d4St3@iyS+QmeQkqxT%95O{WhM5RN~{%PS>86&7nMEK z!Bytis?IY|c22n-$h;r`Jfxc3nTTG{8)=O@XztH%Za*ux{>X9p6eR+D2ZR<&fljYa%vDcu0_T>u62l8j_@B9lu3y8a~%1o`9(Tf=}vo!PR)Pe+i zVfO*jfVr;voM;6B_){5;7rtKvxlZ?bh^#|4Si_pXZz6q`743_%MTZLo9o6wImi(_# zCcGx9!Yh|>biojR(5=e)7q%oPc%?);zyNiRP=LS+Zb~e-3JG7+fD(q+!Qn}^&fk5e z_(c2J%4^h{?trG_;+k^twc#A@9!pt@p4$@hju>{kJsX0Gjl#sBw)c0J=AXD}8To`H z|MvY-5%qo##8|KxsBZ|T(I1>m>&TMKt7gB?(PoE0ipnxE_yiRc|KdJ?Bqg#Mw(ip~ zXQ_;r-F!ox*4rg9=~+SJlk_BY$804qsD>28LMju&e}|BWMN7!`T=gC8a_w{88-*V! zTUfOq*9EFNW$P;>LY42ym4WCfW1Wwh?jM{BMlpeITsv+G`6CBLB;qw-tC0RgLx%pH zCHf(}N;V%4wgT>7IDZ94k3~$~YK_Y&l;#DioFzGC*7B{YcVduYh zI#Llqd<~MyK2-E6IOuX|1-tRfK1*H{8*a&ZTD?hLhUFTo>U}=e%L5JrXktF+xb-$E!)4mrM5F`Ds7yRBbZ>>mE zB5#+4d#(4A?<=o_mp^d6@z*Q>RP$d$9RAspIJsJE@#e=apDYG6%6()t!Q`a>-hG8% z4=x?oOguDc6Q=oEULpTKPdzFA^)U}F6lYbf#J|eKiDur@$N%ro!B|#99HYbcg^~Hc zyH)=6q{xb2v!6FCH@#JW`!ohnEZ#M~7>n*;Y!FQ!9e=!~^0d7e_)DOEn8BkdV6X^4 z762lF!ee|FpCm?w` zR$y~$ zP84T%o_T)ME|T6TK}kRSRw8Few85kX;%QX z&bIF1w5eFX{~lBjX$ow{zU(Z>V2R-36IQ2n&p#(^qYb>i^W)R}yg`Mk?X&R1HLdx( z^y1zKFDQI-rVd~PMdl3BK@HIB^{0U^Zpq>d+-n&w6z5C8`Q$fOC36Y%nq0?B#J zg}ePY|I@0lXabJJ#n+cEzFmnw+x^FX7LzvaRRYXKG%`g!hpSLBU^r3e8vOeiU>X96 z*GJYJ?ZfM-CbA%CqN1X5@l*HqZt%H(wYQ{DppdxkIch6*>vJdwxWVsyQy`|}X9Z%Y zQRVGX?#!IY8qYoOb8q^Ll_v;5q>;QA@rU%;<8}1(0&uiq{1E zKTOP`BCtF^yGB8reD$*(KK@ZmXNCu#d3$&F?&*P}&;r{&0MxX`kjt<&##sC<6Up^8 zGwZqn$CQ|3<5u4Djy%#sZH3M4F&632}#<`vX9HY&;vyNRELEplASKS*hKl8VlzteO#iG(UOCdHJpJ; z_N~=`^SlV)2VMXqC!L<29)VP4I{VqJ1+VKPs!~6?KfKrZbGG2024Rs0tOJS0w`4C* zz0yn0TBVlC^1DB;l;1=^&;g|D2XuKogG*k00Lblgw|DAbT;h>Ya6BQMzw_g5-b{8K zD*!M90MFGk>f7o0Zih*&>Hb^UdI0WzlrDAH>qN7lX{pI1`%%gf03*PC*)z^H5LD))mvfKhAYa6K&WGkR=c_ReXh_K0&X zO8#_MukhQ8T;9>5>mPY+Sk^}K$}3yM`#jzc22Kc+M|`UXU{y%9hd~CLr<(lu6!N(t2)}KCaqyH+ZU7 zuB??W+&F}PSck4$UR)e@oOf*T?itOQKR7FIs#!*fa?Co)7@3t*Cces7t&SB0f=j=q zazmb=2}Sy{GKu7V?+cV-uk(r7Av7& zgy=%}A5*I`6F|ij2n{TO9au7*>VthBOtg9( zl4s;T7fWL7G7YqRDOax2UJFG&e{{AS;twheoOu6G^vhZuAbjnGo9L>nCkUYV1%MCt&&Or*C`*Uy>8xqDsPx@UCx?&{1;| zHtAkqWT&4xYQPCl?cFa>TEdl@dEJWF#)6E}*{WB;h0*$`iALx32UIEaY?b6l5(F?zYwd{XFTa@* zA8kmDpIASm!#7f**Sh&SZ>v&6u5{ZyPf4W2s% zrs}W~3Jg5rTz=zh)M@!HhKX1jN-xWurr~vo|B|Xe;L6_`*PReg8~=HOWvUZz8|&<4 zXB~!xYo2;c4O1Wm8@A3i@YeYTT0scnNAc4NX;w)*P`9owyssVTE10$Tqm4FQQ9qvq zS0Y1QKD9QIM0zd0;?somLI`1~03?nWlqIDAZ8TO2D?Y=)e597@C$#bhTUHCrZLXWm zE*V3%Yed%&RVU1y9mFsLZJ%OBB(_HaiWbGhf?Oyef5u+X_anyKRHa+6dq>K(+i%&J z*^`(#HG;t2UeCW9ZGk(NHM?SR_&f`j#lnG?@^SrO1Nus9Bdq z{oXhA=`xG`kBAu-qsfRkLO zg@1cML0(=3plw|+=b(0zR0StXEfvH_h>1!q+ID_rUm$N)yFcs-B&QqTt1aUp3cz6Z zEf>Cn$~eph9lUP9qag_8BzEGBCyCnPf76YgL)w$PulcUVNDEN~s;dv?@-S^{hZP4` zg=PjG5PKCSd5gqO3*0wF+T6^a#8cAk>%U!TrNsedRE&_%-}7R8yJ4)PDiU|s37(23 zYk~imI`Ks;b51lTpDa9$skCO$aOoLgk8~cZDRT*q5`vJaV1hx0;)(1$1 zO7~wy%g){gg&0Qh5*%-|HA5G?QY3K?n!`XU-K_PZTbC5g&ub3&U0p70Ha)~PrcO}h z*|Fps=63munoArbLCNqm8OhbxI-Z|G)#nx{>jlTgIxIIP_tghC$aMOnnNx*Dgw=7Z{|tI^f1UFz#i=> zqfyePQPl2v+jotTT~iWwALYe4#*mWhl2JDj3SGiy4p0Kiyu=7O-WO-qfYM8h~To~+fQ_| z=cKWvJ{Q-s`;tV&#>`Zy)7$^-@k}!laTW|2BBs5(6B1?>;BY`?ufg4fHrc6ak^99X zHdX(awb(T@sT4|GciP64C&Rs*`HC+v)x~@DFv+|3Xy64swF)i#A>8E1kR-tt<89Om zO=q6+!3&XiM(7igq*a_^KXq8*A|GzXsCa)*RP-{&hWEAJ-Z#bC@yHl~REpX>WI|*@ zA93_Pv7jMAArFL3T!a!{L49MA1xEyTqsN?Jh2r2LD-(5tEttnpQZk?djqPH)IsJ&ore1Zb&eW2!j&SsK-n9f$)kFgg{3Fh6zuG z))2tTbqGEa<%~1!Xhyxc;f#bjai)cL-H+t81NUzyL_~!|_t$oI(n7XI8>1t_;O075MB#3FxJRK#VQCk<8y-Lhg^lu+C^gSWW#c zGn7xjpM(HaHo+W~Ov0QJDziD8)0vn~G#&Z1etb^EfCR=3#ZNPvU1@aKPhrS!rO>#S z^6I3oQM|V^QGngaVD((sc-i%u&|~`RA)TbdI}m(pff^CptqUWT+xoRaOFmfasuwcn z_Y+RBwy+f3Ybrf2NP`*WT%N`yZQg61exlk8B7x-R808@X7{{(OY>s*4sy{xAp^;{N zK5Zt9M(exMNRsn`k~fqT+uV&)`ce~UUD0}FgwY)nK??7Jj?gliPP%_dxGNvGO=n|0 zARB8ygh!avG{x7&tSSH5eXmuQf^9&mtG8h9frtBWGErt!Db7IydM#n&z2xi`UhyD2 zp|_n)SOuof$Q?hSzlcCJE+Xg}Y-jVkg{OlicXw~4cb45t6sv3!Cl+9LW*ML&R4`kK zU200Z;=1Q6Q;f|)F;kup@C|`FA-6?Kapc!9!Y4MvC2MWl#D$fQFaNRcpYygRqtSW{ zuCRhv+9H;lfZb_$BcR;g8`*#ysdIjm$3j>v5J zqGJtC!Bb=Pd{-6*1E&!Gd;JZ_PW6;KLU%}JI+EmCNjk@qF|~{KK>wtzrs8Ul2Om|i zKELQB;E}MWao{69k_%o?eva&u4bLI=^Cp<>IgqyB>OADxEKf0HL?9R@Bk1k1m-I4b z)kt)sS=BrWsgwn`gjXD3g!{LvaC6z0t~2T`(jZZSj2GKUinR7Yl6`{=^op824T5nc z6=|b*E=_27W za~KKr5c=}cfwRx&$pS{}dv%*+c*w=>oPy3!N%AqES_ye6b z3>D3jK4PeJ#&uo2$rEx0lIF+Z&(|nYx>X?~cr>1EsRAYG{j&gPn9NO#6t?0LPOG#l zq*{d<%29=hempNdFzb~vSbkx{o?_Zb`?XHJ{x9E32658z#-LK!J7w##b|SptDU{b$ z8r|oBg%!8_wS2`E_nQ~~R^kx(XAC@R+F-Ro!KXtGEcR2i0rq@cMRlnJ zgZENcP!;==4zS)Ig%T{~JRWK%A$EpTobCOk#yS*{gG`;>jJdE@v%J0ADPK&_yGZcQ zEtMDduAy$gcvZJ(C({~9uV^mZ#ADw?gms2S7jwz#6y1%h-6K!U4KiWrP8pw6&R-Ab zsq#@Lrw>OoM6RVyPt%ZpteWOdoP4k^xD&` zQ`syB3*Os~Z9WagU%2|KQ*4NxIMBw2lV@|k-;cwN^y@22$sm4G*H+W8CWpG8y05eJ z_Sxbh`6Y6~lxgpMj0(jyiVXZ&q^Ygu2BO<6ed$n+)6|Ma&QQqJts>$ffro{{C>|op zJ5p~gXSg6=fI2tk>WqV;Z`S&3=JxB3-*-OXWFh=M@PfnnM>=`0P#gy=; z!!!-S2W!r1(MItR-CZ!`5MvBB_sh_HfdF9*o}H)o4{elB=ox!jVdpB9ny7~ja$|x| zEv)>=Baw`V+nN~uLT7mwLZeOrStLB@P9Cf&lUW%gSE&p%Jf)tstDtS_W`>I>MI+V_ z%1pGIOv8JWBi&ZLyV`V?V4CVKj@7j_QaX}pq;%g&P8aXN{eCjC_!gZWFREbD?|r5> zKb%(Vv-MoFm?e0D5z%)4gwfucS3>4|d7`{3Np6rtH)@5ef}X*K#ZAgOq7_s||;wjh|{(^*0+5}k|B%H{- zdxX_!Y}^_@Dpcw=I4pAyCP3WeFsQsW3qhY z(&(MV^qHU>g4$~&k3LF5F1LQ2l;4jgCdhzNUXMbzQTK^({E*Zh z<9kAU!yYGgH5Z$#)8BBLpd40UVdEbnZAf^jAESAw3Lr0X+8cY>8nZa|wS$aRU7y6K z@xf{RBSemYL%I`45$ODS_T{!UHj&wwL>%ELe=H(9;x{~fij>#X)>vw%^Y!T;3y$i* zX!>w5*!GoWByn<+^S(BSMw8ykj8&(mKoP;Sm^5Wk{v<2Xk^~b^ljIyo5Dhd+a1Db! zJVE_st`R-2!i(Ba8t$Qqw^e#Mfl51EDUZkv@opO(*mtErkT0>Abx!TEOcp5mD6Dy- zK_K_G`(6WKG__Cf)xbcWfap>HewQt`a9E>|NF6K&9l|R9q->ZYvWKA;wR7m#2ZnVU z)J~!v)Ak5yz8Bwm+J;T-IV*v0Oy#!6XA?568ih$_AC9AtvQ1s=_u$j&m#B!F4~_^< zOj^-IUo7@v*m`sbGX{FvKFY=nHjvth0@42*P>9ZDZmWG1t6{2-q$)E~P6>Rdkam58 zLO_#UT$5xsjEf*U%PdToJfgm{Z#0Xf^Gwwz1UQ6mc@~E?b7wXa zc*uQ%_cbmoc{{w+`LK<-N$OR7PAbv%gU()8@U`vt588S=yT1%=I7>_oa|0eXPVLpc z;j9k%F#2b4*9Z_A{1F<%u%Wfdf^Gv{Ao)-{Ua#Xma5o0F&%;mU8YL&!PqI=(P?OY;DgCc-MTK+ZQCQlqiDmC5P%s; z+VX^?D?h}QDoX%I*=0AWJ18;8XcS){#CcVL<%XLrCM-+exPqG3=92L$Q}6Lj4Nj<@ zoLt$Q0N+#RH57hwEP4NnRMQ~+SXp~k5UT7ZNt?eRvQ$-YK=JHx?GYab4i&qiFzm|H zyp-Qn1)$cQTSg&xByv<=a9ytEN=}pH@Db_aSl?8sjF3=7L~P8PGL<$w(;umZ?Q&y~1Nv2;P|d2&dgFfh+1&+7%7FJ#?m!>RPvHmzm>u}ny=twV3y3k)yOiH~yPz@3(~8Ztm8sf+RB&TYOXOjW6* zK~Q9sQHBk2Zuac)=zfK#vmvjxWZcCGj}4r!dW1=LRS6U6I-iQJJxoz!(MRq73~ZJM zju6S%X-PLloW)emFyLk>dLo~Jesl08VkBm*hK1_DR-a(E6ZzSSIlK9ee6s#$3W@Ip z1~dx21mOpn(RXoovBM9P5rY_b_EhrrG;8VcSYHZPrrA^5Pqtt*E?5HUn)rskXz4hq z7$@F_rN9nqGL=xm1rl$=Ym%2zZKGCno0fwOs1Q$&`&9Xgekc^w{|Pab!(iODCPP@P zy%*gDg{~CJa6ragfFGxXzRDLxP>Tx>-EtSeN z`0&~tH+nsur-}QC_b57eiu=_)IMKdzu|^f{D|oj)4>DY>uM*EWd=(c*40-Tri3FM1 z-JM)a6)wC-*WGtAjX1s1>}gH9NzuzRH%o){oIL74Zqr8N%QHeDqdkoQ`&2RXwRd~W zdpVs-Fo%{!B(W>gGh*E+=4a_?VbI{g`@o{MQc`Z;&%A7H#S z*-rY?nc_1>m|<9=t00eTuS3R`(j9~XhHTl^T32QI_}&e^s#oU1Ztt<`YauW^HJ-bl zV(w&IS~I`?Hil_YPA(uzvrGR9GYDw*0v)Thf2ANT;$6JBSc*dprPeT4Mgt{2ZBv8#HINr1U z>U~>JuJfmj+pLVurk@Dim1?Ay7#H`O4qC}E;j<@1Qfzj4@|xmFWCHi81Y+`#lt!@h z4Wu#CjRz@DmPBC5=-5ks4cmGdo#TYTF-LgF>2I?RPz#EX?s%z<5R&41KW8yP(BEA5xB2*;5V;di zkZg;1o3fiWH2K$J#A7D1MJsi#IDhfsG~M>GAXLY!B3hoqu#cyB{>pd0g|AEYfzNU3 znP_ZM)7ZN>&fh-zPgmV5g@N>7WJ@rkOby(AkHrmbj6%zDc+i$TpFpwKG8L30cY>1& z3v8m2wR<>4wfoSx`u7$69jmp;p;?>(9s2&{N;hVT$ku2yTX#S(rVN}b=heelmVw#^ zMr(#DWNL_6rr08?h2z}ce*1H^|NRe)5!&MR4!2a)=poFK2o^IR#cY;IE|6wlYe;iA z|CWa07l`vm^8a7|5W}RpeC(eJ3#0}7-+5^U)5bl{tcR&;t&dXG?Vl>wY5eO`BR2^m zWv@=6uM2*-BhxS04(fjeUM~~Fxb16|>r_b+m|>w;r(dy&=u-^s39ThGNy2M>^+?+2x$hiX}s0CG)}y=omqEw6(r zjshr?&OEuf$wB{R8hnHE`i`rYp{KstA};buh%=a6vm+p{vQL8IamVZLQyP=?-F2nl zN!H<~51D`V5Xr_ItOUx-ND2HZ1v7Pqj{-3KRx0-ZXbkzn<>{o53sA0K1JhrNQKmT$d2nn4NJqqIak zX7^&RSt0uXPTngC-EBK0#DI@`zcq)JdT-4N6f1rNZ-42(aj^Y-L0PM*Ltpk{uLsb# zYfS2Qh!>v|eHlng4GqtUa}M2Zd2eGY9)7Vu0I(YGfX)bri2KY1s9OYX%|bXgCde|U zkw@20p7n*GN8PGXkE4ie*e$a&CxVm~F=G+@6$67G-+7dRmP@#G)e3mEY+CtLaHiQD-6M zi*Q6q{c7joHE&MW2X%=$pfe(~8_YS^{gyla@z?vqJ5V?E#g%*;v zm;SxgA<2C?L}4+<#Hw`UR@;6*=-XLZyfGWb(}48q)@2%&9Jogdv^m>BJIox-=kRk+ zkM_1i94oe2O|?gWC<=mn!|=Y<#Rt%7kZQ(QJb^!3Bd(0zdNocMS3!Lny(Bz|g8Lb0 z5dcq*SA4;hr~>Pa!BmlsQYfhT=ivVe#Ug$TfORJ{vw7dgncOVlx5kq7=sh}-bi}>j zZ*Ly~UhdV`;=4(ph_TrW%852LnSd^w!b~;eml!ZN*W$jS$7CmyEPF7>%)}!IYDjkP zOs1}`>}d4?PE90pB8LGe%zf=Sar4NBrbJ?{QV@}zmjavPw=30zJfq>ZbGHGt91x4| zbD;Ys<~R>kMT1gU&*#tNjbzSm9xShDwIL~ArBZ63skEvqSL(-5bf^fIS z`0g*g85`ofdS!|LPh=%4$~K87>12<^nw40~?1<^WIv-I<>u8s%+4~@$v9G(MyL|Z8 zD?)60v#HgIjS3@sQ5E@IU#je%Rousk1l9C9v!=KlWmn;>bg_ldEKO}7pMo~s2$<^` z%qn*4`=FuZ{bLiIUgRTiC;Fo>@qU%MM&(K*z#jFnG6gmmCrTx%_++mHF$qAc&+?p$ zA|**$uCAuIpk#Kjk!V5+4=xDem+KP>({AD6jmUg;8s%M*0TxIp5J_YkdkWaHV|F z9#wF)K`mgH_t@1ZBx3S}7+dO!B=ZBYGw>|%{ z!3D-(DW5}7fQ^acFyO?H`|(OV5uCa#nX6o&lynY7p=<0?vyznmQ{2A-iuMk$L^p>=bvL z>5ZxJ`0#X!Uz4hYYY~d-*GTPHMj|wCAsuXL(+*+N^!B}cnA;sleqmQYG90aUI8bna zv|Yw-HL%jT-e5f5nWu$DFE&HWr8!m>%wJBVNI@6pMFmP1%;xo z3JQCu{aLwyB|}W;tX8L>^vPm0Fd;GLouWzB*wg3dJFn7keu9cf20L+Fm)qWA7wF-- zHB(D{L35yqvX!)1PPvSo$o3G$&`NZ=aag93Qi@niz!}z|;;sW-b&2uR%V_QBcc}^4 z4wp?cI1PH=;9Qj0I3TX6Dui@<*Uk8-eakcAe{Rn3Bv%9UYf;yJ$V-)0imcTM5ARJ|N zu^tkz~9>UTw;g;a_Bn6Ab%C3ueUJ6u59uphneg;q(%X?Rnn+TDPwaj^u zCy^tE<@9#MsFx$v*Ga}-3wCYI5Hx)WpRqEY%b$!?sXUWTZXB&0wAEG(NJms`Fn@~Y zjU#}W;PNnBGJh@;aG*8_Jf4Pp$!`Mrb1 zUDDT1V@|-gfx8k8O2NBW#-ec_GP#~=;Mppx9lcA;Ou9DhpuD+_UMvi;J-OXg}Xue&mohaQ{iJX}EAB$4!rIy}t z!6cWc%t^C#3hh#}{f0xA2oH|K!*N+!Y7g&DOYPDdL4ES(d5@P=6_1zjRcN2+6oP6t zztVr~j~xVJ%w{H#%W7?`2*M;sR}6*VwHu)4z;L-YQEl&jpY4|TDpwQdt2(+BTw5oEU`L4HVvdPYF}dMqzi&R&wAR_@g?5ksOf`2uAE@ zmzm?7+&!jloqNf1X!RW5lY)#AUgti{;w^bBaNG7MB{Tt-6cU$SV?7SP79@2cc ztf`%nOVL3O29u@iNy~DNVDN!MwUK0$ zxn}dPBI%NaEp~$`PCH*3p|bjmNwV~M|LOJ#YT{QIzWv8BGRuw%-?J89m1OS2AOwOm zXc;;V$_S=RZqEb~sKk{AxGSc=vl!}k05R$5^ zrO3!mXiNx`4yP<&(FTgid^+km8-OXPY{wuOb6NN_b&S=lMN}{by>oqjY!Nx`zz(Zq zP|ggxx5rGuWr&o>w9zW)gk#JhPqU*~1o5`m7PLDH8Z=n>&;Zf2;qcc|MT8NTn!wTdd)EAUc0=s8#GV7Fc{=jt+XO%Aeg5Fp*)eQdjNM;L^$Hy>9K@@-XVVze ztukt%kZwYE%vMS6qXsCU<7vqzxX(;FE{_ZL3aC0deI~A1-dwcYI;pJmK;o!imseVz zsN=f@F_V14Sb(d%^P0P+KqO8Gk418WtbvvvqC#?A3kl=s%CPZzcw6zGWm{%|YO*8c z2i_IOxL(gCsa@_4L%!~M5uIM9C@gG3hf_P;_|o|hv$meP)$g6PPo=W>N1Xyu0@BFV z3aSTpc5~Hfkv~d;*;d&fz__0i&8pH#s?sNduHc7s}%^LxB-il!*&e2=A+3U&dE=W1WA^axu88I2Nd3Miqd4ZRV}lkSjNr8$z(66k zjx)N>`-?HL<5>JDedC=JCRAsYUR}@E-h;_S?gtTTq2DF;BhHzT{;a2rHb%j1EG!F| zTB7Vro zUkP~IG`{~1*~Cgfzky@N`sQs^P^9JxC^jv@l`}CkCNMZzo?xgu5Ru&NTOve?JBvZo zOSAOFACBl(=_TChs4Et~b}~s^A$L2uSMk9Kjp=P-28_qJZVpxhd{_-sCq3mc%RGm6 zR$UOs=zUC$+O15R?*$lo$k`jvGK`(*hpyzqx%b3>k{KF(az>&CeqzojL)~TxdQM{> zUAq^*z~}`n)#T{L$}5wFmb>fO9TiE?(hF?KMKY({vA;Hr)M7EjK$SJc-D0v<6+5M{ zfpsd-ey}1dBPC4Tz7cecoS>2oZ&QetEt+Ip6YmqlIET4tp~SNb(BMpQyR(2Ip!%*C z(uaz=G=uj=OMmg~8K*S%2Yr+m%OD?N#S{=?lq8~rPh^uiQE(B5#9rE!Aojm?UqB>D ztw`Oo5u3gV5|UIRUm&OIV%r)*2?5=Y}Er$&eqp5e$!(AxBaeHk1i4Vuz1#$8CcY{zXn$EaFZ%O2gC> z*<~;4=o`vbk>(G-f2SCFn=PQ!;MoIkW$6Zf`+Z-3^{r?GCj3v z(zW=ux827~TdGX2s?nkn-)OwGs#Z3@Xz%I8=_kfg^HU?ey%4>H$cU(@)%lVt6~&^J zi6%+qO-(#&tbALekv0O!6Q^k3XQSn|vZcW_F-5oIu{__9nwfh zcZY;1f-F)%K)SoT6%Yjk0YOl@JEc?UZfR+$Z?N6x?EQY{_m5n1O;(IC=NQkppF1j` z1f6fuW8)A==l9fAD^q=CcqDW1gy~Y>NanTt{_v(5u&}!_+8$vn$Ju^x*gL@S`N^^- zKG*0axPyf{ou$&z7&UFhP4vtrXqhE2=AL1f8CG_yG1^M}vG@bZ3d&x(&lLKoW8|82 zi3!a=5ip*S(50e{1&|2X$=+){>^4fkTkq~|Cv7|JHqxz&Qod?*n|Ay^#pE3z7XAp@ zAFXfV=Q$D6h~SJ6R-NkedP=CtYLy$e`*nX4gO#di^y{!o>jPm6`X@p-+L6x;FAkP3drI1{jkcl=seN?vn-MLL>k&JpUctUJ9;r|TRpHTz) z3Lczq5BT`#?y)RGyvdVlGJtiyP^L#1oYPrJUQrrZR2;(STd3ZL+Ik;8ODz~NU=J1=$tUG{PYEFGO`hVWJ!wvko@kHYJd{oV_ zZ(AOIM9`N(eRbZl~BvOHTf0*JDGF!~eS&;J~n|9N=u`p_2B+NerPXVHqq^YDgA zD0o6De&qb?Qb}p4MNl(J0AqrB!JDd$OMpl;-QIXr4e`s(3a@MN6WH+71GL4GEh4TH z*GPETw6AjDPrDNXv<{_1KK}fhZuS>aNkfD;S?BWd&Hbm79wUZ=$8=ieMqaxQ z+&N>Z{jN%Z0mX-6vDEx;O>+s>wHWMwv4`~mwt>cxQKv6P*!t-pip$suV$~Pa2Y4A95?8_drIa9-3XXUM)F%*3m zGg9`~{K*o5`J;0q$ng zy%>+K)ecTXOGdM80ET=lNdUBf%HSQ}dmbuDAaqV*_|e!SpRz_ zo2luthQD{UKI}AQ|3k0AFP3eG9wSoE=xf-w8?h&|;%BOZLcSZpppf^0G@}dgd#_=lOW}U~>m?|~^Oi1m%h-lFU zWC|eV_X4PoB2smZzv~%&2c9-Ep;!R#*aom%&n*Bup42f1^vM8r8n7widYHy++DglW zAMESCQ`!xTUou&>^T1Tjot9aRWOs(c=)>i}AL?N&Cj}+~ShUtjz;0IYd$z$1;7$@( zqm63blO1beTk0Zz^|3Eesc9%y@#*hahVYB~QKeW8k{Mom!Zu1Rk`K-P7~-dfP~$6rG+uTXX1U4yKYfMfxz zo|zyjyx)6xgd3b z@eglX^3&bQrlZ(ZMkQ|89*P~cCU1H2ujPppDt>*et%x{@ZHa7vWyAHl8Q{GD(gNrv z9H3X>vln1(;v@K?osW~KDvMr+$YG)vg8dD^Gkn0d2C(_LkzU;N>yB>1N`ZQ;#ixad zracvrH$*epATe@M1~w52)EtZ|Z=!ny2&}@Rfw2^A%PIv%4$y*RhfQXKW0kSIKPi_l zi)vw77+=6Gc;sb6n^AEnS{?`HNCrUO5wU7P8IMQaxBsBNJD9U723CP+s$ggZS}2Ee zW`TGG4yZDZCtxFRi2eEfs9YohmpXJ==!z`u*!~@=`fL|q#o@HlNI+>n0zhq1yCz^h z6bXp4sLtA8-T*U{u22;R{S)eN-oA$Tg;{6hy#m76An$BG(s%1q zfFgZMx*{$e-=VJ?MbW2k=?|YTA_d{J?td*P`l-0TI1;fhx5?_4`1bF{_1)S5s&S+M z#n-zF%@XVzT2O5?rg+)BWbLY4xK6jIk@}0FjDam+GqkF+{%I0s&z6Y)B3b)KSGmPN zXj3)=Hqnl&FWGZ^&4%AD)4~PVygv7vtZG$e`{s&7p|>U4%FsVA_S&dfTe!QIC}H2 zjgbW*TJs~9c;Dz$M+5FR_O>=n!pF2DRP1!*zUbg0^?r*eo{JbSq6;>#WO% zE06J$VTU!6rRKJkHMK)~{m<6Oi5&eeuU9ULJIoCJFi6AOQnHB8ELdZ|J&x~Sa@fP^ZV&ilf|z?WvfV0tr+j)9{}|VB8Hze z==G`4;FD0hu_VDgl?}Bhoi2yOFQfUr!&q5vDA&gmYQVGA@3WNHOf>4CAm#KMnA{Az zHyARsVa~0>5)EC3L$_jzjg&7Mwj3j7uqTc{du&A@gw5IH8d1fhkba3XHV*%}dWpWh zlF&Drg+g8S`tZEJwhPc=Jq%r}v0qwVeoe0TYI44zRcv5;0ffC3;${1@MW2-*Id3|9 zk5KBZOt3CgA^yYG=R35U zD1%%COsbO69=uUUv1K2`-t)b{;l~>@ZP1al0;pT`z?DmI;bCZtxOCpEcwb$5SPC|u z>n4?-^`XoMon*J{5BI~Da@%4;MNMup#eF=-uvnOrT$w5Kt}BNPhgUU&`3=v3ozPky z5)NKML<;s$L;^qhnVMhzCu6XTy^-fh3JxT#u0X@bgPMr5rA94G0ODO`}+7(a+ zzdcgc_%m|%?nbWVbDVhQ#m0i(bE9g9Yq7lvb3R}oFaw=aY zI!^2}qW6tbi$?h#3^_KlOeoNz?+x~X-m~Uv$DeC5%VNDSTlcO=W?Qg|U6d>Z_awqv z>$2wMT8xlZ+32}xmP=;jr;VCqRR6sDU$taQ0D?N5_t}LcU;P`E$qRxq#O4UgL4=`q z!aq}ve&d#g&@x;i`6<9?qf{*jiDuy zW07-kGhy$jVkNHJc1BaM~NN4;Ip5qDs|R%Z9c~iy9WZrSsAEi-v=Qr#bsGl`@9GfrcURi}fm3D%PJ)<2dQ4$HB ziDtWH%x6f!v-_zOV8~fiY)0-sEgM#-#xmBXWo4j>^!e^Hw)+{6@qi3ELgUKn)&UNE znVpAP0c1h5ORjiR&YhA4V?7mM$Yv?_1eCj*t(v@Vl6Q{U6T%-SHL=YENv=q+y9pj`v0>wPV_= zU{bGftY5ekYP^jNc?CO9DvgxMs3a;VZ6F*5Gv4F>i z!((aJcZ?NmD;hVvEauML+^=_ChQa2EvsQ9XR?+-;d!Asz$l=Fo$(aXe3p!Xi9N6Kk zdH&U2m*j^jk`4TlBJy*&2u*oY)X1B&u0iK;t%`qW)bVtgJ%T+Ama=;Fb0K^ime$5p z^Z9bSW5LNt|K>OOtIC&;^Y4oql2M^w z^1Lg&;mU>OMFi5CH{0Tz6*I59z_Qgci}_3Yd}HgZ$){y4?j1RZ(WVE3o$tQ$Yv^3` zx#@ir{-+vVl=nZux=&Mrk6||ue<++H#phV_C~)o zzegk?OQi&6S(t|AU@^WGU6`Bj>f|Zxf`a6gvKM!Ozc<)uw&}WhLST@-b9?A=X<#YB zbJ{#52AcsUBmSd_RXA!uElZL;{}`;x5FeRWd^wxv=slWxsv-5{qO{c3n78dHMz z5KV(Ev&=iwi>?D$2pPO5ke>TPVlU$^ed2#k-nKZ%gw9#~;)bhawc% z@aWEm_;yL&M?1Lr&EDEMO#eZW1Ge!H`$5vA9TqzwzA7QRiaR32Y?7YHtIo5V<5(Otj*RL=y^o^83UIgiX1`{RARfr}!)Sg@%MAqqwR>1zPo4+%wa`Fhut?px zsoL@1s6PrR9-D&+QNCqXuc6!GR0$`jx^JG`=?FV=5`1h|nWt4T;>L7PV+D6K`88FC ztQ8StOcHZO+Cautj)hY-^zmZ>n}&=IicUIREEpIy`ac@e&qw)%@FA zFA=Xkxuc%|<;f|aOik+fdkoLFaMNKUP=(P4$+65cu8(_Hm(&I4yLsQ9 ziyowHIK5oOzOZ#PdqxB->=@hV7rj8tMjvHwj^#-9D%{mLxQD@$=sAZ@H-5lCIQ@!d zEEc2;`RxcEcYrW@SomRaAYMQ{&rWDF3Y@JiW5b@)JG9<)SJ^;ok|O!M4|fvl-d~l* zAA;d99o*u^L}{t`od>J70nRI)OEyy=R8M{Xkj@~!=Kw|T@iTF2tJ8-MX5K3sXp98; zpgIi9KBS~Hj*KOb%JI1A<-OsV*?!0`GCr+0vhH+j{uZ^{xNpYl39gJccl2rrpq=iH zNaKpt=%>3*o5T}}3x@Lu&JhV%Wfq0iDz`nNASUrHBiWwjef#)tJnOu~7fay*kBt5B zuL>)ziQ0VSDJ{J@uAqI)E-!Dw0pmAD2apG5VZ|}~0cU-bfk=^*T=+$z@ZM6i&Y_U+ z_ZoB#P8n)YZdkMN_~f$lWIPso!_9Lv!sP3%#g{ghjx1iFsFoK=QDD=#n;P`;LK4(U zldvWcnmi7!z2n29k!hvjvf5R(um_@RzAM`cp z6z}xj*u4f*w9%o!DVNcgyLq6R=%9n}n6)}w{K~a=5zJ9>zo@LJEV4Y5O^5tfRLwt=5*4)G1AmG3tg{Hi~L)x8yd71+l|YbEnMgiYse zCRzd{v0xNumA2!xE=b~RsgAN&F^UGu62g3GFku++mv06a5_CRtI}`NX@){W%mW}V` z-_aU=?s`Bz-as!GIovE5A;$Ca$Nkd~#>J|F_c1CZl}VeLOk)Wxdq@u@As#? z)el;q|1f|LBxyp?aP(=8R&P;nPc0MoRV?1x8V$bVk=bUdoD^mBC^K{QMH}-*JLEJr zVy9Dq1qW7_+Z={GLa_;PlXEYSwAT!_e@utYEPebHU{55sgy@8kPodA5h0L^IoE&H? zrER_y;wR;;EHTv#kc>k2UrhC zkt}r4TVvVBeEIUICxZl0fWkP(y`M4Iv*lOdd6o?c6Qm4nQ5)%5lxcJ~l?~Hx;#R2- z0>em3w4E2d*%*N`RqJi9LO66v_G$1@r3QW2UZ5j?B|YV#%|fx2!EJ2}_mpd~9_us<0YUyzFxu|D6BNrvBfFxof=i)8NU>bjUaJN!(nioCU0m zB(1#Zw@v^4wIj~Ii)N~r}p>{4JMQ% z+3RGMwN&?#^rGhT`8=BXg3@y0)(2)U2$HBnf)$WT@IDYNCzidAj!;p)ck?Spv!3X` z_&h!eq>c;TRueZJB^2V{J=D9R_3me&!1_a3N$SDLx~;>mz?J1(m0Bk=+litED@Uc zfd8=l_HoMon{kT&Y2N(l5zL}>kO$Ih4B8B-QE!bAFwBw^`2N2y1?`@dzbOvJlJ|E0Ia%-F=V5wp+fQSEI2z)|`R<|Lp-n&V3=BpL=sVC(;e6g;f4C#Dp~0wuY|wNAc&>d zP4L=tf2Aj8)Z)Kr!+$^6Cf@l*+m_!@CdPa5?}V3VExLzX=4Jc^iFvWtKP)j#?j&3$ zNG`?N|LQILp^lrN2lNRVi2LlVUPRq?X9pDB+zG{|M%)AatK3&m2=_W zMet-^JEhc4@aUvHCU|j&01wV$*oObJNc}xr!32n+#Qb~mLWr@?>N@op?JAX?5m?-H zO88m|pa0LdSw?~Eq~QyaWfzCjLXTs+@rE7p$iM`EFwM|^CZNS7sO44j^<&UB0_Dc& z3ZRHqS$~i00QOvLdSCh%woy=aKhfdkpp|5P+CwAH3GWW*ty!5p6B@>|mBymYf+}Dk z7JvWe_5A7JctQYd29`#^MoAs8m7f6$IJ z@NZONP=8kg$ZVi9gCS#Ec=u{{HO^boSUDwj1EH@@eaPFC!EnUDcj$`)Ai~mvbqqg9XhRx4u_rAiW{|-L@!f z?b7%C3Xw+rSEzz$qr43WKRhPdzHFTLrCmnYr(eic?fjMvBW zAwL?OPqKMd6i^A%A3DgNU3yNL^!IQX{u-ICqSXKTytzoS^{UGL0FZ?=QrL9%%I7js zjTod9e@pU89jk~e-90?s{@G9e^R)e|%9%vd`Shge@q4m3vBS-<%stD6g54eFjW*9o zNUS#JJ@)7P&rYA&kY;WH>)1?DhtUm21&c%mrNTLnu=a!j!>_DsHO_lGwMM?eJKy-* z-fBYe5kRk&!9V?z;XhU9-%ngXs!Wz`7@A1z*R#ExUa*g1Q3{o*mPS4u+bDdzm7yU% zZ#z9wYgpZ_pb@Wapw1-5u z=@_%U3&&SOsJ|0QhTXXDx$KW7@i&q@u<0+BV>4?Oe)Ybd9J=L6ue)jVmxW6Gr;gV2 zY_!A<0hW=CIGR-sJRM#8qdlA)m+zb`=n<>xvjzk&fK#K z>xVldt>hE0GR}^#c-NFu>P~(NsGeB!XJdcgt1~@`eDHqSb?&xL97_;1G-H1`uJwH! zil;TKW;TC?s1-vVq!L5U43?QwQD60Ijyvuvyse{BB08=4-L!dbRi#qe(=+KN_=ZS z$?w&C4RT=4i_E=x@!t&JV+!PBDEH#e#0_iUk8U6r>m2SVrJ-s+{Z7_0-qkvaUK~4@ zPCTi!dwMa`>rmh@7P_XaGhJowm6L~EcUE^Bvhn<<#HUw-1~3sp2Thm8P#5aWshDG# zYdV{U$3V~Z0P-^%|Ldzvf&X1WO&|ffeGBf6zjp)%M2NmU!m=~z+F_OLXu0~Jey!hT zr$|plHHjJ&8-$8eHxry%LT*rKkUI*dB)q@&Xd{t1Zj%3@R`*CwcjW7Exb7;8!N=i| zh1i?hozPM9SFfGty+N@!;Jv8qHJB-)VF6SMF_Xo)Dvee4to#F@sj8L-*2(iIz^ghu zo44xwcSHA2VGxS<x_95=2-~A^g{&Rt|9*!$@Wqpwy z#zqgez*?8eUn-H5f4)Dy>c!lv%Tj&4>&6g|>dS7=ncJKE>nVd=WOAY(h$hBo)w)u! zS4|WCAiwKX@{sjW)^Rv(4$vcQXa|8E_YfJ;YnlJcnWCn;Sv$OKKv&w+`Ur@^(FHTJakS%F%$ z2BpgV1Si+HFDdk~V#fVZA`0Boy4#b^KIMCyMwQdM)J@HNKB31*VaINkuJ1BL{5k{M z%ZO@)R|eb%;I9H<-8*SRc=@JRtKF2j$H2@+;qJ!#|C1oeAh*wju7^U#1P$t^%%r!? z+@s~tC2 zwrBZy=a)v5Vo3&Fq_kW2;92EMtLeq+gV%Zkol)v^5A^m7 z=&8w1H>mx559ZaI%})a9@Tl*0dGT3B+nj%Pc?KaU=YsvkaV^0Hm;96HZ5RiX)97a7 zssMbreDw_R5$uTUTxCplNP=vZ#jY1~Z2D~8(=b*(rqyq0K6BI9aWNDV^{?Wh(|A$7 z7N|~*&Q$LT`R)jb6r1(Fdqn3?CE{r__Iscz5#wIpOuo~LA$Eh0i%4R1^X@A#u1yMc zvIY1Z*v5L(`YzTb-Mf_EKjV<||Jw7~FVwlHqV_xADpq^er^mAW$bgF#;y`^@$=!&J z68%$tNkU{Lr(%ZZbw1J2s3nQYSbi@QkVAmdAom-g(o8v-d0oz_?X>F`kBS+zx#nox zK9`ZlA}j?Zv#A-a6~sxX_w75BnC-?UGmj-vMp&x&OXU{wXu`w?r+Uua{h>5gzsPWUk1wLNg|iMKp(GImm$?_Cd1_;Ywo&3@zgJ|PRH}-+ z&iroL&m_b}UWiX8GO2k^h<)!?Co!M+WF<#4PaBUG^vQj~(zfKEX<&gk;04&uRL!|e z7`F1?Z{u6LDu6TSGHIcGRDL7xqe~a^WS02!4+s9M#I5i$$f!?KEkHAMSpJ$M7kN)T zyQXr0oMLE#C`}6(CKu z(+~dH`@^Hq@I>k8_Cl$QB@y7-3`)5?3hfBRg~!qeNf-hewX|_5(Ps~8P{L3ntFP)F zkfYtNyB(eoV0YMD{IK6Nw{IB#`N{i(p>WvyaZ1tef4RXm%D~`&&3D>f@38UKPqwmeo|=?Gr4j^++;fQgR*k_yXvOl#0@LtId~93 zR_gP=NJoE{%QUNKCGYR>49o$kHT{A?BQu9IxS zcI53j8Sa^KOXH6(tPn)tkU>u)JAyx1V%**mpcjNCr}C%*6U17%g5QihCXh#t9|q-x z&r%4`+IQdTW(ql&Yz}__wBvI>dDYvyfOKFF_y&k~R8lydMOTM-6daLJ>}iRVDk@NTiUj}C-m0hU7j#d>;9+%b^BzTq+w2Pqw! zpCj{7e%FBiqZ2U6YHOrM-U9XD9Y+}OZ{(v%V0mmdmB17&9Y{Hvyf47VmiN8AxsE_O z1}20bRnta^Fty(*WCNxE(E5ce-t{mYYOyYyegU&>TVS{cI2+?GK$#O#jE0jy+);$`Zuux6 zM3tsY;7VNKUFEHbpSYVz&$dkPgFq`lGP$Edt@XYZ3qDEw_oMfBS&5DSHkevZf;9N8 z>l%DIqPYdw_f7+YUO-vrM4VlzSqPbL^fHw^1fA_}jCw?IKsb9i53GgFBgG%ziOx@7 z0D>)5p?en_I5vp8$`o=wEn5Y_QnLAgr*Lt$;OAAL0M@bpsbb?1@WOopSK77+P~T{X zHr%95$|dD`8K4N+Kl@}@FOakgSP-U~@ao9U3nWyWgNeb4vHNo}iHa$iJ0fq((Tcg=vc!|qc1012(6=16T&&&cNi zsOpx3@c7!ylmp+~f-e=Ts&3UYRSsL4Qq=r92al7Fq{^fO9=??`i-E%=B~(`~{4EGL z)5n7j_gKEQO13Aw%GBakO+)?d%_XDd>Zvf|PEJ}#Vm+_pc;N$;ejBoJ5)dFQc z#c2F~EnZ>rtCMfSJ^cKoUGy3tFf{`mF>gJfDYXH0;1fp;z=6sT^+?64wi*jfg}Isn zzM@ux`yo)u2X;iuw!D; zzJuo)@andZi6{W&kQlL0pjT}fFtcbp#?%DYz9j_BAQH+lCwy*|5T?^GOIjaDH;p<5 zw*vV!IOzO2w;7>%H@X>hjZa-&i@1(=$J6_|Xg>Rl#()6*Q9N}p(DbT(BH>_bq4avL zVG5&O?}Wk!JrA+?ZACiIT603VOi%_JgvVcUr(@B7TBu`EByP^dQSbmfGWiupAq??Bh&t?L{~C{*3P+wm;0=}y=xb3n0fdpAV8}LNH=@Ss zh~hY8#I}0w6wug4TY>K?^m;Nn^{3)6%n73&=zK}Jmt2u3HT@X`h)tlh{y8y3K!&q2 zE7kA4XwZUzJ?j&m2sn>vpYaFVVTEtFPzBMXF$VA#2+8_%IMDsG5f5PQdk5n_x7TO0 z10Yz9IP&M9$bQEm!#C#cPixQZ&(NJ{p;> z`pNaWRz@BKaqvuAx-zGyEAGC{dB%=sL7h(%VnpF5^7!WEM zZGHh%?eBs>rY{f&Xo;Yc_v48IgVgwCQybNT7yVgjP=EVJG%DH6LQXVEh&!hJr0bH9a@^nwSbv4~8YiK=3ja5eWrei{Q30 z;`51OeF?n$_G~R5a_J@aLv)*na@-7Y6n>{3b#I{c8YVcPaa{*;i*WtZsCyz&o+m#8 zP`tzJCGF|Z+F21We-LQl^|m81q7iNu0_HM#JN6EJFnZbcYyM$lAEXS;N2_pIr28fM zU48W6uC(V&bq^P93=I!>y~qh~YW490WZ4!d5?-}q%jzOxkXPcy00%uGRvtBw((&lF zI7@0AB#(yBWK!g$kt3S69Th;sfS&iS4W@$&3ig6$<)@9K>lIscZ=ib(mpEP)j47#^ zP^?(rKbVJ&mm3Ot$g^4zR9$htpd#r`!T_Nt1YCjcWKsghje+a!rG=)cvw`Ih6(e8c zrE;!*tI3Z|{9ao><;27M9&L}0NANXWuh)BUiQ7hoJ#K!qt!Pl!KY3L~udSXlh2R$F z{UbXq5^w>+g^6Fkq|jQ-vxf37^Vg9xG5IbXOH@KGn?;C(`eXM{cS$FiTbTI()k&|PltE#=#U0T7W4T-D z53+c6P=reuWWQ!9wb_MB&rr%c?liN2UtZwRA!87>XogfMAaxW636T2{%16E<^Toz%hoDQNkJ(+C3FA0Ohw`P6>qYSX+kh%s1aub$N z#oJMUHP|(##E{#~HTDnf4M0u!5b_Dz!bgpJ9Hfp5`ZZVN?DRI$XL}cQ&ttmwo1DJ4 zJDh#d5H_r}aRFG5ql@H1>i~Jx-h3|e7Dsw@mEH8be2)1_Rk}cf+~DQDuO_$Np@zgo zkyLRWK%{<7u8Z?(WL(u7eMRiVOdd?&G0Lwpy#0MtIJWn@lDt$sAKQRz_(i-3XR2XH z-o1eHaLJI!wGU(>a}zfaN~RLCjX5T37`U#x*x0l_twrsVx@q%M?Rq`V8|VEJt~)}H z@5$pv(45T3UFBX^wq`c0){`$5cRPHaqkpuGcVrjzTo($V!y|wyaF2Jj-b!=q z`(DK1fxJZv&Lu&MM=%!;>Jn~hQJLZ(U4s~7S202u?D0w30`Dt9Z^VAIb=(r#8-9Xf zB(X_z$rqE+NNK9+rLr{kto4S&2sl{SpTY|s2+L}4KfL}Pi%_{jY0989%)my+8}gpC zfd9zP^Dh1+O)z!{1#TEfjd~q8=r7gsw0)QqA)FYOADUwCdl&OKgyIccMoP#9M1oS? zZQ(Msa+XNzSerZ)1Q(}Q3znx-iZmg61;DW$cBHt73y}$EMi(V)F%f_efFf(?NYLZg zsyJrkN*toHN#JjS(}LE)D{vPNYgSt8iX>GW>nTPmiV0_jJ)xb2j46gWiv8_u7CwPi zWYAP+8>KE6bK*XNV>x7G{}FBe?D0w_Il!lXZu?ZrWlWA*7Mc_c*}vf z00FmC(JlCf>l_ueSb+1#RH@a4sj8g$#u!J7-b^kp*kofj2}3>b~9!h}hL*LUcGkkm4pMhV)uA3-4dQ z_slZ-6?FAd5dJ+<@L;MZk(2p%fzKbv6Hg5EVA`JKNEgf)%b}i7pI#m=^qfu6o67~s zKJTOpk#t9og@1}sd?4uErn<#bzew{FIzr8?n(EJvaoLHl5uki|vaK+QtcdD5+wmx{ zIgjzYEb>EGj{`%Eatrct$wHVe2A3kdC}IHeaEa^y5wQ_Of7M3K2;Y#QlZ7MKGP9qOp{-=dG|JKj zn9=s4G@whV?$n8nM$?l@c}n0@bs`3TwnHL##By=BY{*61VPBhVy!?+*+jIJsB8%~1 z9&ECS^y{5|f!${u&rclzuqW_kK{Y?GKh=G;nqEUKvwZPFuW7#g)g63@y*a<_%h{?H zO(t@+6af1{ff!e|*4OZBI?CtrY<+kPb#Tm7#b=VMJ#;=Go)uAq4q?$XSbR@c z+pbnlV_PFg>UQ0k-P_2-kt8nbzq0~y4OhG|Z@_=iy_r8g{eAoG_{+4Vbu7LO)wPWV z$Eia3%JhiNuyLwZpVeL-%X50AB*yK@JoZq%=w62r zY-N=OcMO3f?F(gH%6;9d5WV%+ta=vnV@Ga&zn*5x>V5BjC-8FMr{Ij6^;p5nFgdQ~ zF7|NDJt|gqGKL*CqNmU=^0whNrSR2TF<1Mcn%^(t6l7Jy;GL4gsM(^Yn?-9Nc%6iWZ8=XnfC_w=J5o$QDw7XjH*YOHm<@y`~u`$06EkK{toUbO_@l9%;-B$etdqs zpb(xmDs&jrYN5_9?bbg2De)tL1xe;O0zaNzhs~7JC|i|yjo4zuuhiAK(HvQSxUPf& z?vX8S3%(kvF`h9$IiHmU9wI4J?M$8eRcG#*4JFu)Pr~R!qb(9hd9x*3!vlIRoM3$o zJ&6|rD#z$;AFWo@ZmO!QUkoNj7#cpI&if+adz+*JXx9YVl=!$On-VswS)=CkZMoYY z?u@et*&nZlcwj!6cbcRhb2COk4kq4c#^S3n-I!tga;5cabzm-MMut0Ri|-?~_~yv( zn4e7*n;uWoDMXAb2&Ya)m<#Mwkzre*Fny=VmV^O)egQ-^a{j_+wKgZ%+X9u=Gt#Si zMTYucq@RwSkd3n%mHn#Xm?3{)d(hVAQIn=9m+ByuumdpD*CKRXGYJogIG-dpOE!66 z(pks{(_H-Q6N_in5EnB{9=Fx>YW;jf+T!H-b6-0(Gn!PQ5cC9MsW_h1X+0THP2-b_ zmM=tPD?$Sa1oD`%$!SinGY;$qErOC}QwMX99ggs~51`-7JmdCz09s)6ad!p&3NdO8 zSuaAe=f%8{5!$BzC5kLcfXcuPuq~EYN`d&B+>%t6+cCo z#5JOBt4FCWhA3>1SDpkq=@I4=9&&^Bs|UEqOWL1f7FtLB*C%qG_F&~E)AFcW#BIRK z;^wNBtKocB#ry5&Igjt(51UXQ5+on*OgZ76#&XXt;_3AgveHS}!y~!OFD~0}sM9FL zE}dl!`?u$x)UKZvzCK#*i3!3Q!8`MIG89TQJ$ zoiKXV^%K=t5#|PK|01gb33*?JGxj z@8Mo~OLkC*@fK}vWTI4Jc~tUVYrxQgB}q7hK0Vxu*>V)5e%omGwS7DD#-)8W>cy9c zWP(q&Jf4(6$m{Vs=*+#z=^V`5v+y%)(Z{J&NpXk}UuspOG_MsMX&fqcXdzri(}0b; z9?qpzbdS5^d^JhKegNJx7hBU>LHff#Mkl2fL5Wr|&`zJG5GU^#)pdp)F zX*ax7h`5B$z=$q32GSMo;|j1ChrtAhI*HfcJo~c8yusNK>^9q}L=Uxa=#*Sjv8 zajDe2o)o@6^M>WA_udhVd`LK!s5t$B)x2e2UNv(}=8p#B^r5C3p>2+*6uf|s%)kw8 zx;^!>$?^Wueqn|}Aj8d|+!3yxD)mVT0k+MC%4_4EEGmbgkoWH9z^5bIFhCk6@O0h( z+mj~eT;WOrRxJbU@b)av>5eom(Q5zC!+2GyA4k{NlG7#5JOW>u^(VucQwPYa501_X zXw7?X>lQZ?O0rFb{g*}7|qLCmT8lM`Q zzrieq6Hsghbhh;5f<*S6gi=TI4otKl91_In2dWepk=#6?k^vv__#r>+m>TJZjONqr zp?E}^Y*9oUbYX_l5yC&`w>t=F1EwG%<%tN04`U}Hf>Dnw5xzWxt}vX3Yz9QPXi67h zEh@l0gkGy0U_xzQS6mY#k&<;Wp4vXhpp=zpl|W98W@x}SK)NiX<0A5peeT7d=mj0b zQ<|l}iXKMKfxb4KW~xl(B3KgTp>3VB7|se0pi#I3;F8#^&Wx<$uGZKtZ^||>nV9V< z%-Zbig_KE+6`I~j+e)GX-EkD9HDg$QLh*~;Z#k`^!t%o7SQUmqB&inrABrwM7NlQ` z`@ljC_-`ptyf@+NQwS3mu($LJ4-L2u6|nokZKCYdxp=(X8Lo)v$c-lK^SggY;`;vO zpvkha(RK6q_uJ149^C|{%%x5khq9C@LTgBR_0Ku5R-#rpPNw#T6zk3T6<~_oXn2!> zYEgxczv7oD+@!YBbz*1}1)-hcVmSR;)oT!)?ZqVKkY!5ncUl`X|57&YdGuP7lBxSW z%};Jv_(s21p=;w?EFZqSrk_IlZ;l5&N+zzqay@@sXn#@o-Hut7Cssg~@|3ep*DWsj z9yZ!r3|Yj0R2rd=PbY>cwl|(ftB7>o+<3`48^s~*1+^p&(V;5U-e&UAMK$j*^_3(odW8RO7wGNMh|tjQHJ&|prz62Q4exx3)Q*8gS|Y>a%TuN97eh$u z?FYA=w0KPpokQwI{9qa>;j_k_uLE7`+!F|Xy!057HFf$O``plN&b%5mNz|Q_RRyk( z+QX=;D2c62i5{l!yf;;j${6e)z~4uf^1&KE~C@V|3ByGWmZU$we#Mz z@$|>E`@(R^R=1=B-+OlKdX@UG6@Ft6daC?rLh?Ma)o-w8^{TgX_p*)9VoaSZk&-EX z_y8@}LE)tEygZ)IVOEF1PuSUg)|8-x;Ur9c_jhHU`rFn)R)V}}`q-9?uT9`I^_XHu z!hK&xbXUaLE``%@dShL_C}njZb0QOeK<|z`0^lUynhE-040?Ig=Q$_cSY@TK1X&}m z6BoB4?9dcqF2iGVLQdKaLBl%t3wjwUB1GSFO^*0f@ijH34@%TjlVS1HtI$`~=8@^p z1d$SHS}j)N=$8}4Q-y{qzUS+O&A~&Ua{YRLaXf@W9v{GoDC8{BXS#)W2MQFB(9*5x^2t2# z<0+xkrB2>?pnHV%At(Tgh)0tFMBKHy2UEN=vhhfTC=#%c#67{MijlqdQR!pVAR_`> z*j(u1*a$0oB{!T=54Hxr?A?; z8KQ5ah$R!X9ZgapY8*VUIR8Y8pF^k%Jg1hqG8t}qTcwBIP?C#O>`7-~_tfTh88UEd z8=a44lWJ$s4HW)5?};O3B`f7G4x@{Y$7{(69=@j#M{&J3a~(z8bUKvgm+@AF{sm`q zpL^c^O{x?W&S)`^nj|h$w_f~qxueu^>Sz64L2RFVT3K%Os~IU8ty9jPWZ|5gH?fA( z8fn~OGNH%8^FpBA7v7qKwlVcel3F`w2-;=va^cBDnVOUD^vahVOH7%iHyr|IW3S(* z_UGQU!vWPc`dN))E2^inOHl-wM<%*L91fMx$D&UfS^Ru&(K`5BX$KmWoyNC3+}rt@ zyLev4T0#mt>7x+ZnHs#pJ)~@OvJK(K0VrWT=+RuRbg60ZLA%mIT1zBt&vdzh*>ip&-ylNSv$Z3X;_EQyc8vkz_JsL91cCHA8ZjC04_{!ey{CT$7O9?oJRSzjJeQ-97wR4I@= zK$}heSy&EKPCC4Ubbt9eua=9HUXEQFdAUJeIMsGLTxFP7y(CqcO8daTcUq_9^2*Lo zrAm`0oDiK>mNP=rxqj-+COIrYM*VfB)8z6mhwH#x7a#Jr2KPj`S+) z6V2kaEw-(UVN+g=mv7jOzL?}1xZ&G#eXYo|+np|bR$piR^9|0~Uc?0D+>2n3KN-WJOz4^=`g`jHi`$VkRa=?{^I6#kzA89%4Pw;Xm+WHuxDfMj7cW z1;u!Q66O{4zO$`zEYb^S3jxzIhhSfq3NnjgDjWx*tgQJa0BO|vmW*TRL(1C^B;`c5 zAiV9-(Rz{Yn+4+$6UONY`KZ^{=rdQ(WrU%4Aanb#f11%ZZ!5mj6>jxi;$R5!TdrPw zs#(VI6zHfgVb6CzG&v!Ee(L zZ`~*C4wkW>A5ZD%&y>~tIPcdGOHS~wG8tJe`m%rk5ByICGe~=GMW#>>vv}?;`bz37 z!|>$RRZZn-v#ZQ(q%IQ58N2)1_}wLF_Jp(XWZq10S;6R^71l6z1wz?3oAOe}HAMeS z_icHWrB?q~zrpk%CoazGC+V(eqf_^n@)v`rTN5uA7jNc6dZcI$Apc)`SN;!W*T$K6 z5@pL0*-F+hgzWLyl2BvKI-(FU!l1z*X-Z^`ERitwEn~@^UD+ACF-Z1(&(M26F`m!! zyr0ke7rgVsd}i)@?sLv{UFTfi?>YCG`%5Mbf_1R}Q}TJ^jGZ-_MSR@Q%z7kxiSIl; zw!}b9llgGk<7->K29mLMU^AtiO6#X;z*U3MXT$>F1+brUz zcP4>kds~G_qZPPpUC)&~8;IOEuoWU<&PMsdevzUSGCm3_i^}%Z1 zZ?x=4%X@7<9*YYpal-uwPwK26+OT~SFMT~JP~gRHBbAaVXz~0E?oL5Oo6Vjn>FP#k z0vj^s>SJByMfChqlpEJuZ?$slaYPE}M(Dj^+w11;g}170INUUc7V454J>_w!Xs9~- z=*T#b0HDDfHatp2jBObkDR*u6lE28tjId~rx-b+rhyf#gwMskkNSaGWJT~VKHQvXa zyZZLk;#kT`dGSSkmu4xseFb@qSIGg1W$BJHHx%|+Vv=OxKMN04Qt~pPz$yxdIfrbl zv+kZlwTYJ_HUk*&C692)-k#WHF&e=Q|GX;R;P+L!`2{B9XZ zmM8yt@M0@vzRyrrSU4A6R1xD#C-t}?>{9({$9tuPdZ@gwcjTXH(or@_YQ_jiB1VB5 zGS!e+6b*Z8TMO_w<4&ef&W*!_5EcbuuJWtblG@D zA-8h9a_FIV-+|C^BnVgVn|f9He@lhqullEc&)E&+p#MC@sjZkGQ|i;~F0221(${q+ zlvTWL&aK?WS+bPi^>ip%i`#_aF2dt4tY^C^bh>a-Z6SyU`@((b=P zw-fW@Eymt!p#A_M;96^4)5-J%ti*cMS$ru(1L`@m`d$%x=&2qlF+kqFm&y69rvLt2YpG-dYB28Ps z=F2S{42h#_e18Pb^j_uQkx~7fm1|L;HvH-(UW21i4Ge80okoYngT4u8jD7Dl35f@| zgiuLEtB%vI@x_%zZm~T&C~+Phwa#Q9uQH19Dl*F*aF=di5lqy9_MAV2sA8X zyP%-JoqZU&`(;#Q%$f;VzPt5EFX~Z(E(N!QgxhQ_U$jr*BvuOQ)SVRzy8Q69fy8iB zM4UnZw{$lBl)+Tod^h|f&U3_-JVdc$hLCRKJ=%L6eW0*}KA1VDJ^fB%Vy~0Qdl`b! z8oIV}=rNoefRcDM^>%Q8@oDTXfh_bI+vTIY=t{}~S(6c9Jo*Y8yTNpKweF==2Cl<= zWsI;DJ;-c9O-ZfGpdv$^uCg*rVYrgi0o~R3h07foOAC}?FuvQdlE3JNK=dmoH!Z+Q z$I%Dc!SD4BTPk*wph6bt8K^}ptAl)o%NJph%5wYStdt~Boz*;_7zMk&LPe?kz zPt1mbYD7PI^MByEo-hPCi+#EPg=Ol0o_yU|@Oy2dtrHEMq|GH`!~ zUD^|GIgaAM8e5-_oGtH;>slM)qbf!=8$t67k+1vPw;F=nb%rociu#$%KU-l3AyaRY zcCwWN*E2IS#c{|xrfq`nt~t)jQHEdWtSJ*=lkvtV^9@%$T=?O5J0>T?LZJs9LQi|NK^FFyA;8ka*#m>0sxh$Xhh73*zlSnH4QCW z#0i1;V(zJza+qtr6=CenjqFz7-cC*ei1O%n+u}5bl-Z_pDXh$3NTuU`e?2Ogu$P{~ zqsg$+H;wc6LG|S@jm>;H6f{oLoPL{YBi4g=3!aCnm>(PTh#hK$kxPe|X4h%0n&msKO#f+%|8!wi!EUXdaKEqt8ju3epq z;5X9%#mFoN_L(@Da*>*HoTsAF7h^ubX`^>aW@cu`^mnw(_!zVTk5fYU zESUraB;4@%v66xayA$a?sDA{c@zEtH`h6sO*t2TSM z9?9=zVC=)fBPpc{VoHI+7Z9E-fp`W3_mh0Rs zUgI%PHdD$!-3G4Z7W~1fg7`fqfj2aLS9A{AKEIWfD!=s)A;0!>pOVJa`29+!4FiR0 z%b3?m$hNl$`>gk1%SSYV1Y}g{SKpL>{$Tf#-#};?Z@%mxo&7pT7vUS78LP{rzX!qmHplP4B}!XK68NPU;X*wfTC=%&&Ez#%H(brwUegvm98VA)ku(HC9|0 zxPZ+?RIw*)!-VQisX)tEyc472pJ0gB;mW)}hHS z6NErZ>{@#TR6ZiAl*aai6)RHCh6mB!yr+rK)kL@;Y)ouyUU0%}a0UoSODvrT3ACc|K>bA_7nV*?;-n>DfZbbMd2muXu~5Gup#FD`4R+uooFN_u zD)T%;i(kEb>C}HUxs4YuVH)u0qKr*9qWNTNhO#uBY`IPKJWWJGvqPy9O&d# z9eo`T1qBG?0{jD!(V!r0n9Ds7$j}fZ4g!IWfv72XKs3M=Pz9t$!TVp=IuvI?RKJu{ zf^~nPuY)e#aQ5)_ z@N)Kec>1FBdC;XR`i9g$TL;oF*P_2%o*d?n8IK2*Q7;G4zgWXx2_!dxSdLM#)4-@G zgg}%m6jUq}5kDeFai}SPl6~ZsHiBZsc2|^ehozc za34g?Lc=O3t3k_Ve49?_5&MOw32%=HUny*(s~Up2jHW^Q3=W$kd+@t%{ji>sHnkFOu>@sp5ep<&?>kx_|B$tkI6 zFJ7i+=j6V7pO;_op{%^3va0%1O>IkSTYE=m*XQoRq2X^MqhsR}=y}Y-;`bj*%PY98 z?Va7def+`U&wc^p`L}KXKmXRV-}H+G=ock5H5E18&wf!*`u*%U3pI_PEG?^sG2QJ) zY(f{F9%H|f@V2y>UihL3mgA1+00XCp99k6jvunTf?9X*9_DXlQAGM0BP^({9lO-G(rKiK}}6f2mC+DNY8lk z|8gQv1JlxyJOMgRMFC7EDi#m~bVSUKIt%(M|J%lZiroL#82_8+7ZrKnuQC3&kMZDN zWBhL)i9ssN+W1(4wp*=gT(y%s`fkXLV2Oy<=sC2g`pPL<;Y%uWS;a17P>TaW zpA70lJtKp*{E4oJaOjp%y(}4Yt4`+VWXiaONp1|k&cj*k3(_EBdlL;IW|BcX5VY)3 zE*bP=wgqvZN|K)%FdA#K|Mp6ecm`6DMI_*j$RIIPM?C%-!Ub}$kIf<(A!7aHjMwf6 z{8j0%A^2++{IwANk_CT>!@o4bUrO=cfD2xOoBMcOp)7&COQZ|m&`~p+H`op$LAOtx z?-S8c-mapx?<9x$!{e6duPYHg)9Jja~#2;$#@hnMXVf%<7@5vzKBpGxho*KlA*Wc+o_~Aze1t~&_ zuJQl)Yc0cBsw^_-S=Kc&DANytr}80#I`V&8Q1~W0=rS4fkB|P<(*L)|sZi5scx_iJ z(cr?5&j_j34%~&R{xONu=1WaGo7NnCOS4-nqo~zg$WH1^kP^c-859lKx=M5ekh`5O z8Kj?!R7XPacIiA%o^}(q*2iiQ*^GfiJO>wm9i`bM48WMW0%+wDDd`)Z^fO`;;Zp zMeqJC%K8O0Z)u&tWMe4p1R2z<5qPqCZ4|uDpFeJIts%PVB9R-ym*!EBy?I{vuAp63 z{q~6|F;TzUM$Jgvb_W^6i|{}Or_a=(`JK?~Io53nF15*tPkq>UKeMiLRp@oHPjs!na@p(caV3rXFy=gm@D zAuMUI{Z|gb^s{(C9?_h_f?H%x;vrgt#B=%hDjA+7^C!E{Mm&Wsw&%+gxSx!C>L9Fg z>->u1!&9;Ew%>YQ+%b>BQ?)~@->0C#6nI9{VHJuZL(FEx9rKUaWICT6H@z3!aw9vealhF}4LM&p ztzaI!V#hjot~fh|-oi*>9>%f966`S5@Kj8G->F?sMbih{+P*i#I^{E75uhQd;N&+k zG2N#8=qtSU6S5spD4W@1L$Jc0FCT#CD!x)J#QUp z);!MIXgwil}7E01O*-#L%Z^V-ygk&I0rDcq4>OGEzIii(eKU8&b$KSqW`>rgaYkBjmHdrF+a33S~v{5*408zak+;|*c-ti`$B!4yYa#?am$>lWA^bX7Et2eTK5t&V^PVB)!8 z!Y#ffRS#D=(;vjY3kdt{sOZ(Ofn66${*-!FOH(G)bA9VO-oX4Qn+$Sh#)}Drqi1RH zbA83j0_SUn?v~e%2$!P1$?a6KwY%``vvxSjzT_UEMWoB|dM$qFr`svi4wM08o765U z{5foU9`e+?L9yMQ1NR`w{eEp&NbyR}&5zY5yFZImeJNEpzq0mrMC%T%f->dU(VI7v zQD^@+*BtSZt|;vv1?G_wCr34GNwH**AiqBeWeVss_a&+~|D@1%{u{mbhM6A^pePYS zD|nBwj0_r}w@Z11I)Pfqf;o_yeW8bf5@jX3rCs~Ls(carXWr|7SckdWBc2Q@-H#$& zB2B6B;_{-15=X_@Ji=*fSHCNVrx<$pxa=)iiavW@{enAbcC62~WMz>=8TdJizn%^a zj+rg{5hVwk$1+Ew>y*Tz95TOr`ZU4H_K4D8FER1-m7958-7A*@z7eRjb%h#we)xm? zW?KlbNjy1bYq(6Vo~r`xBpr9ub=Ov%&|T&xv3n- z5zZSH;LwUlO|T19w#)+C+`HuLm7 z+`mxdae?O1cc;^vBCHV0{M>>!doje~qXshQZeIi$#Hl8X*Ti_V#_}+qLWQq83~lbv zBL$i_+~+g(Q?g%+2E`ndfbZvH7%cpR>cg1F-R3hJ2$$ea*!}Q8+6kfxjyW3fk?mSp zyuJICl_Pg~nwr{+eg6I;j}Bbx($tLaKlkIWB;3|kq-MAe`~k-Enrq3R*1jM$3aoBa zQP}IErCROc%EeExg{>c22cz(7U9$?FW)W(Y8|=pB3CI6!DD4jrVBb+H8MN>W??jqK z?36t@q-;d|wxoXh;~%{pdE`&&K78K12a&CFPYYi?Uzf!Tt802xQjQQzU2)^BE9Cf; z5NEXzH*+(lj@97OjW3Ty(h1g4paZ&g)JKoCJd6h=-Ui*+Fy}m}frY-3dy!pN7iQpH zll1kq%Fc_cs}hSZl&eJ&LV7Ri9R)+~ZZc2dGXof#9=YIPtyf7M!*kVjby4(1(d~lT zS}z`JXP)Yj^S4a-d|A?HOzs9^m1GaKgTNCD{*YgWwR12VM-k_6SGSp{RBl$K1MsghS=4-yK_gJ#urkC$l z>0*`mhDhpXkcl(b+A&_-(L!2{R&!Z}O8t{VOQEbTnWv<&Zf1;>e&SA1IMa zn+$3ntuxlGNPGBKi~nlG{~E{tm(89Ms5WWpBMuUwa-1nNGrPq&+yAbgo zc~k|;9^Oz!sOuB2 zhz-H5Jz0v9FZthV3 zOuD&>*l$+k02#zk*NNCsLXsE(&^^C8onO?DTbJ&c(}MU%aRC0!S2RpSspi&&i~pG> zb0!Qv{ng^%#Ohz;_;Z5(HGBR+G5$Bp@ZYs&7Rey?CAAA!{Q)FWMX&Z1*FLt*Ym}Kh`ls;p z{~dSPj~$PLW2>{fhgpXP9(FWdhl<2!KAVR}Mn|I6Z%zc)1EQ{vn26#=jBx?R*`SL= zzr;V&Q~c1Q#H7vRh%xCNGDu4l(hlBY#ikvF7eRK;yoW21L5TtAcmmBhV(D2PK8JM0 zo|O#xxEoG-_H7*U>_>cC00a>7-2MNZfaf?U#W9i?@(AbQ7w{oSq5@7u>2M{J7nOCr z4t8HCkwU&cO!4dt?4E5%NVSMBa_|YsR)!=>birE@u8~I7MDV(3e#Lg*f=7jj2M8Cj z%v5W{UdXvmHVE0{bq0=MeB!}h>NMUkFOAM2JHcVl3h+}jJ{+58Y3HDuXkP6*Hef*0 zcH0V_E=G~4eLRoaGxvP=bE9I5?Z?>i)~sV{?1<)zyd5*=@F_?eYuIEP*2oJS$~QR^ z-Srk0_Z;4NlRHi^)gt-+X<>1-v3(q(TpEevLPOV~#qhIO-d5fehfj7D`W3oH2E8}HdhLbb-5dy4Ct)Q$?e;=An)+J5$OKlCj@6?2Ieeb>><`x@tzsx}Crw_~wYfZ;d5c&wY@`Y;;xJdJ>n$2i;T z@n*7pKAMSgRKvinAjiZVxe)Uuzm&#-O3++#OW}v9eIY?Ztdlu{Bz%<6$crE9sJ7OP zRI$p_zKtkwsZE^8QAv*d|8o1&^XAH)qHr&^ZJ#&H6Q~$)g<_l<5Agy15il6D zjFnK%Wi^GD!VRPDjL~*dJjQHtPj4p}CFk`f!4raB(~HG_SUn)&OR*)0@r=E9M@fwg zFo$-fs^Z-DMb&JdA3vNdvB#J*6NayxTsJxSsNX;R0D<8Of{V=~Ci+P1Sxsb6EKj|; zzK@q;r2LV;P1LMGsfV0gsr9WEk@I)oEAnrh3~?>I3?k(_BfodkQxQ&D1jVF@@Pex*ShJI`5@bY7_vv}!}Y@5XC< zfH)AhmnVZhd61GU2IaTC08*L>4tdlH#GfkO;aE%^-eyNheEj}LF7aRAza;aIcnf+C zew_?T0Gp6ORglBW5-Ssn$eICzTR_8X>e+va|4h1tx^D+ro2_z+Mnc>}aYcv|8;f_b zy+6V;1*uOGv+kXb&V_Nas?K-<6KkrJdf_DVvVU8q1hzWFdviUWYnAf}f7o1>bK|GD z3H}9EE_hMlE6PWiL5JoGChaQva?&Dk>fBb>&62l{3Fpfb$4MiHMy;=fN%Y7$SRe=d zN+UiA{kie9NY(yfWWodYr$d|JV>9RIonuZPFBzsTefZ{**m_nlv>MToa+CvS1AIvj z@OE^;-ek}zmjuI{F6o&4Xyyb7n_k%~1GQgn$tE-M>WojnVo?W|3|q__b;#h){#bX! z>YDP9L2b+-=_kU`j{@DbV-BZG+%BBCKFX4teb>TF)X`1#Rl$-@z$RvYeS5x_u>*CY zkvXu}o<6=~Mg?$T+qjuyXL}cHCMWE*hO|mJ`nk3S7CarbW4SK7Pk{nsTr$sNQ!9(0 zcz>OdHIH3G8Isz%)W)6E`N>37L*%JicvJj~6B--?quWRV7u>Z0uZZ*CtHn>_3a|1! zD9q-T@o~TKRXfGhIL+iGQ|<*?pVL#9BB5RrQ1D_CCJ&ZQUKF%V9%87(HbA zsooYX{a8nF#Za-tx8?D!payOB8x(&c)5XBu0Ed7_7-CJ;kqmnC+3Z7K2kL+p@RGHT zKo5_nSl2q=cewdybbag}d8e6wlF|P#ZX~m^^_e!wUqz}+Z!RG@?oFr&53%_uf#@@b ziaZ3jW)L3faxcqTMtViXMtf-_^wE&Eki9_Qe#J9@6A?=ktC60SYB5$YHe zk;?txar*ALhZkppM+)dZJkL5%{$>-aS6AZgVUSCK9n8nv9pnaFRxYEhZ$lR86_ z5_9gwu>0#Ifmn}XkrDE^uBZT!;*qA#rUDRg)q4VJUq znsA*z*7hOT`So;n&MIwKPT#fP9{p{>?4X>%UzZrje0h0Q*<_9nEy zz4#J+%sKPB`dsT-;T|3DTYis_bDI-6H%8#PX!nai5cq_T2dzt>(#KDY{m6|H$&J9l z`|E}a{XH}lNXZkoX!TktZ7GlG(CEZ>pq@5L;uA2c25nFHr;|BHvzXyVXgQnk6kDj9 ziB&`WGm!@>DV&?%&ntIWxGG$iah;`uJE#JlCnf{KnvdIorxn?(e|*X`S!i< zS9#v8YW1&hJ(7RLGI=1#M;pg|#zVHc<`mtMTOS2H5buN&?#L9u%Q&F>PC7$QN=sEr zMBCjvTs2I){!OSNtlKK#O=T_DNdx}+Yo7^KKlkCN)6QfNwD2MAV75vl5KI_7O)7Ol z$LjQ48%1W^7+TLA`d%N*8$3U#Uq7B5b~$X{_JQEDD|VG*f&GnYII$oi1rO|$7TjhY zctm}`+GqB-;zV+`=%*A{8 zy*gw#a<_`pqsYa4l$k&CO}}{d+syMP%*>#?!=NUM^JEZXJrhA4ezh7uvYCT#MfXJz zSTOtv}|&ML8ZHHP&(Q7|9wjh7F=w$AyiP58y+WS9=$U#y3? zCf$HCjH_FJJzTL%Xys^=yi@f;@rBsEE3q|Mx2R{UpkYLd9O4<=Xot};xF$|4OkRc& z7Pzu9(rH*z9dGn_-FU$w^|I80ucRJRB(3_XPU|KdswtiiFVS2Mzl{aA#k0f0JMG!a zNdq6lZBcP=k74)YD^zF4XGDjJK z=+p?OOMF%@`qNTnKB6zk`d!br5&AL)2R0he=IHRIVK-L)rwr45hPvnRbcPn!851as zcWPPom}dq@j@o6~WMm{a*t|TRSg4^=cICsGz95UvrH)HTzw972<+7uvsJrWm=d!=i!K%~~R|Mx7%v4-j^jAr9{1n5%U| zfdcIw3Q2B{?v!0a-xB)Cp_LO%n$ss zeEOwP%JBmB7Y|Q}=iMhRHcx9e65kPjMpHq+4)x*qGVZ#lkNc*WRHtG^EQ z2O>k_#2ZJEsCz~+YW&#EFu2d$rw8jqQAgU>?|M1f+qiu9e7l6BsJ!^1B}=p8IL#lu zs-6)UaU!1gTg#uNe}e}r2E+SkZB}L{3-9{yYgn$>Yg7?5uctA}su@dEG=6bd?4l0v z*9MuFl~)ZF%?+&$^#o7IN6CLyHm3c?eOV0TCx7n`Fg-FOi*z+D7O}xg2IYR+iG@!A zn^|tw132vA?9rLxb8xMjV@uB2QEQj~2vJe~%DZxcao&#@ahP^g3XljsL(NCKp=_uH z-C@*vJSpz#VO5RWhPTNW5Q%E*|IcvL?|n*a`C-DFp!jplk@eb`*IZ4rEO3cJqB1V_ z+gSCGPsYP7%kim1PDukt2+La#i}3N-X7==>JJ~@HR=5!vL|ucA1+Q6U2Y$_D!l@;B z%_H#!qwUu3rip0^hp;m(Ho{D$arC*$8qqWuyIE!adZ_>z9P^$UK5c$>l6P))oj%X? ziIzPd{&BXoOKoU=Py`bq-XBPJf1 z1b>K!%=a>1#lM|{GFvWLXHP#4ZjXH>b6+&HJ`&#UEFycgm}h~hXPb|CLi{WhE(6$C z#O5~t1xtML@#rnwCf8LABPUyf8mRxCu8iM|#n&WG82H0d;OoVUISI`-)SHVCPr)A% z>#Er5cKZ|km9HhxW}Bh)GKCYcN@9t&&Wv}EPngEJ-6NF;lJzv+NiBt_*NbkV*MS6p|VgA=~PNADQ!xgdi z$2N+kZ(ojc7QNB65^#zys-_UpCB9Gk^cgT=(uu`*78eYJ*BMft)iN#C$%p* zcE5fg=NERaM5HpyAndeA`Z;*E%J%jf=4#JiDmHa+p_lEXO}%lSxXvhZ+4(ONe$DP5 zm`yA7o7U*pO-C2t>4?}su@wlNir9P~c=bJ@6~YF$LAMRB->nSWm}e5`G*=k)%qnLm z+z68oeI-3&?rGuwKwy8a?-*PQSG~@LV{1LkYX`GT;GyW@MxLmSjuDu!f6eUm;KvIM zFIw6MP3U15mO{C>PP{@;z+1G;DVTq!(&f>58Se*c+U?)o`bO#LWp?{jy=J%yaEV1q z%YK}?)SZ~iHaNP73RN+}na&67x5zN);O4%uzI%TG;PPF4ayI;uP%3WcywqRpwGjO}>?_>q(78J+t-VyHV$$y^M>& zNI3_WTb;h@r&*P(i5;UTXG4#cL*EpPOjxGSHx;Ms$?Xyqy!`>OwYG)T4 zBZWiuM;713sk7+ucA6%wkIWuxlyjavz8lX0W1QcsoX_HSC4oOFgqZqs4LE+27Mx}J zas?0n#E%seR|fbsTRU|Y59r>KXN(WqE1}!d?kQeuZm5|u+LVXAC@b=$SkwrAChNi% z&@f-ej!jz+nd3)XF=oV*K^h|!y{__IT#PwKnJX>m;fMBAk^^)q>n~)k-J)6*Z>qy0 z!#s%Ew}GIb_z1>!@NN3c;Gv#ziTixb#67)t!k&^DTo0+8_(qO?cT2)AlE(s)gXq$= z2R0o5w1YvLCjfW!*R%+bH^&cv!-QB!!S|4wYU4>s`u0!l5jZE3J~Rfk#t6*)Ww~Su z%s-Iie#>jP_&e_UlFvjjl|bR;!?W3+z6NDSxz%>W3csS^mIHl$A4NSY;m#2&UHMfo zKHeNMSXNSEzhWx9v!+U8j?~HI5Z&Y}FFND}Pbz|^j7Evhr14Lr`9KuLa>sn8g+F31 zapOMX{uJU71d7Wc+`|we4*{2|!+`F`@LT_`d$F!?;y{7GI7g0qLG$Hfvvpo$JCIn< zikk*ZwDM*-_1UF6g{>D}h+cN&rW-bIfBfzA{My(2?iI8)`%QLsV?#g7{dT6*`2_Yr+yqCXi_Y_u}8CgaBD8`VOZ1aAW#3;{A|)%aIcf%^g@XV(A4Egqb~ZRV!9&Ucd8Tz!LiRGDuY?5l04fq7H`xtOG(O+NQHVqW)fnaF0L0kU{Z? z-TcD}0$pWf9S|1zd)cphx$CmW{8!ii>|edW)GFwe(gjjQrT{SNoi(M}8cbitfp|!lVk=}%0H7oH-~I4yNYjDmJz}jIz#L*gF@X$v zmo(bXu}ud3Q`wjM|6PFd*JTJYaFW9xBfv9Jm*-)kyouW4t?xBXsY-mQ7sfiE^PWC{ zD?Ucsf!8j=bhVROYi$Cu=b`1xp7pG9rxJCTQ>!920|w!rn1Y)QW7#Rtq|-;QNUZpH z^^DePYscPP*3~pMQLCa#-bv+8KK|u`nJbJh&gf@5ZRgS$e^V&E@fKDx)Qmb#q&e%P-EGEMuqrB<~X>eDP{i~@JrtpN2gTchHhs{d56_0E?BLL!J{IkY0b@jte z6~jA|)0)PgzCDnZYj86iI+MDw#q0mLNA=wo-Mb0aEn$#P3JYiNv=OG+DHbM}n^1tu z(OsCp-0Hhmx@0Xs8@?{YBzz^^ai`SKi%M(F;kkjx*{@p?mroOCFFHN#hurlD7T~U` zAKJ;_Hm7b0T*P=4It*43C(SIRI9Hy=R_2Gj+Nu%mNXt((vG zc`|d*5^go}s*bk}rZr85W#kQ(F;&wG9s7zyhB9fKdt*<7W0GPLjb6KwPT=-iQE^C| zBAS$OghFS5kD_|o4qXk{FOE-7QqVM((xsc-H49;}(>iroE4KggmGI?>vs4`$WRMd; zhgO_rT5Dvr#Ru559J)8vl~;2qO2`*?e;t)j;W9W|6J?h2GF2-LDSnf|%Pj{vzEt)#O_9?Yo|v0v;pf@0rSkx3f3__Di*S^j$=VwJ(DTpj z4*N$W^1npTOa@pMh%SQ`=$^nwU`3_B{KrjfS@ZD+^e_V;-U2>kv$#uQ%Y?A(9I+eQ zI;orAD_V3v2JUD=K$oq3l8OK^3b48wAqmCKG65{6Xs3$+si5T1zfxD6YqsyEwEXS| z!Yv$Z?U2L(O%kBBmDVNtI;4z;G=D}QW2PjOZ+cdJ0=KD?Ds!yTtBL+H1k3@?*TQ|P zi(^0Xv!k}Y-uM?r9c6Dua&1i90&`!~%4%X2AjDswW}!dq-2HCb$IPTQ|GvJp8*UW( zaNk?bSlgGc`APDC0Sk%^`vUcap^Bpk8wr&5St-`X6+H^SD__J{LciqePR$Nk62D7v4 zzv>U)2izlLUw+R=^0#~GUkgT(a}(<*hHnbMc5?c_(AQx_nm*{!$q|@BW;Zz@f!m_^KN%QQ)W~M z(CW{Yb5@fHPgObSG9h)kKlA9heaa`|%qj@q_@DXjU#se9j(PhbO#IdBB+46CpLajh zePokrUC}=YxOH{4(Jlo7skcf-7 z7_2yh6DTa6(Y)>G;TtP5RNKkJTsFCT?=-`jTT|d^A_o@HAzNgHPoC0LeK$u?+1o06 z@nS+FY4KIZ_-4x2OVq}3ubl^zKjKWXw5HQ$osN7}C8^I|t#F7;iczX4A*~`;b5w@x zj>_tfsW{}|OC>PLChpSa8$UmPKZXx)xAet8C-jjam3?DkQNVeC z^<@;&QtOK;#?xr`N#6pohch|c_Zjw#cmvzBPQc~odi~pct-ltFcBJG@+jW$w&~VR1 z=H3{4#>ZMe7ZSI7&|#c`WB*|RoFO>juh^aTe&62DY58S`Ve5@h8OMl3!v|>>1M92~ ztoW;g;Qn)NP)fY#$ZFe@`xiCekLTn}w-gn9%olHJ)SwGyg0y9-VkIZSLubG&%OxM( zd`-H{w^&)_9cnU|TjCb55-mgtf;gVn4%--CV&|G3WtcxcIi-}-!Y(&Z_`D|K6(#Jm zTy5W4!JNC&rdDGT+_6iWDwB~-b@A^7sjGU zA?ck*M4%Fe9npG>C<8d!z5`|f0$@Gh+r1FZKW29rnTf||35wx>Toy;*DfV8+?xyCs zoOt_wO4rZr;ag0q7^}|8lM7{u$JDY5Rw1|*)MosGYj{Y#jN=@V(It>=$T88)?hJKx z?BeOJ?hsJvjU0%&IH?>katcX!l1?Lrdf|ZYTNcz5{m7NU_uYg$0YD6)I)*y&*HKtZAg z7EtXCetRE|3PtcV^PB^_{17Am*eio)g;N8rw>=iJfdMC9Mj5_)eGPU`_?EDb=YFHq z(JMK~IPctDC2+`nqNZp^Wr5AgVSL0wLwcv?w|h3m{-VQ54w@o8lJ>T#xDe8N$@Rw+ zCDqzimZJ&afik!zmO7JLO+LPD!T~r*bLGk&)!oaJy+CAN1_|~revE2^PC(~Stwv#K zD9+t@)`=B+-qOTl_5sq)o6-6YS9!#bS#Dgu|D2hDeu)Von|bOZKH$+DG6Kp}{|NI~ zg~Q`LzN*z^pl#y%TZJU)+YN@JoG%i;Qzr^?wk(T0eOOeSdVAx-Qo3S0WXuMDbCQ8P z%Oi>;W}HBl)ca~Q-lKR;ofA2fUPOg|WmQtS{~;>z>}kEyqcz10xPCue(1mb*m2nPws(n8G#0rAdds#TH$FO!t z^8Wjb>x~!QeXuXTYU(D$)OuRyf=w|)aDe7`RzF=kc;aH)giISEY=#f7@AL*=*P1Ev zZT8w|B~{Tx&hny2D7TQ&C9ap|I_^Q2MW`pZld}TD=YOXXJ?#GS z<%>BG)k5ME2BPcHdlC&%^eCfIHLzQa8Sn9~D&Y+(O4?(Ss#pF?V(*V-;~oi>nDtb> zH1SWy@hLiwpln3(Q8LKEh$C>6GgGvte?x^0yRTPQ8Lu(09y-0=Q2;yB#%6CIH+U*7 zkbl7P`2BdgAD-gp3g6r?1P?QfwlPzT;ZvDu?eR&5)i|23D#c0$T_#)CVq%|ju`1}Q z$Xs15Jm4Nyk#}?}z^}HYkr@uxP%&exF{1A7S7EHNqnd@n%`DQxB z@p)_=qPSR1`Ne&yxAj@;iuA0Ki9zgoX!Uzda}QMJ%LuFZrQNvS{w(3#1 zgG8arQ6?6bTPgZjHT4KpQTXk->UAiV&{oAMz=MA}e{^BA<1nteXgR@(mW6N9wc5Ap zM%9H#x##TyZNAKcmv8tn>@jnb`k^#|0k)Z3p&yedB{ zsNQq(Snnn`{0aW@9Fv&NDBNm(l2HQ8qP-WZpql-Y!VI z^gX@EM-D{CEP#u#wLj2zQKz8V*jGGzr5~(T%QU@56`)R)LmtvnGu+?fxHKh8wXU#B zB`pTGZ5`-#_m$)$8OWfp3_LBI7aZRiyMuY#13P?jjqfGTp8V8E%kjrEo+YO`%O9HX z^6JUgswolqAj}wizKX+pU?ZKFM1-j^;mU!Otb3*&Nk-YPXVD=LHkoeD@p6^j;xm+y z401uy;W74j6^jF&NNUy2PXA@@j4id)zB5Y9P*~o zn^86P8w@$g@)TX`yy2$7c|vv0xvXtvNFC59vz>Y3Vo?*MMUR9UNxh(S#zSM(p}X<7 z9;V;!FtEHaR{Ou`ar$`-(jOgH!DK^H<2q_4_BxKd2ST!73DO+tUfJrGV%)`a|4c`m z-+W*OHololK)SIk%j}cOdQp)a!8Rb9MA|b89+{9DqsUEY`i$1G{E6E%0p4f`-Z&f4 z(ur?JOVJa#-O3EDycs78iw*Ru19{Lug1Ik^&eareKb9b!dwN+llZjlLnDoGW$`Rev{2TXh`ztX?TyQot)oO&QMAQZky)yr({>h(lzI zT*ghTKpGl2sswhmo8M)J&|?!F`F&_Zh;ZWV`G}&A5#Qs^#|)(0gVeQ)JHzvqbfW;V z7nI2m*9~RGV+z3>j& zBX6(`@vS{>$`TEpy>DvctbF_nBc&GAZo2R_+gY}7Tzx;A43g*$WW&34&Qi`cBe+WH zc?(ybNZx=UThlvUJ2{G^XTEk*jM(s~SRK3nQ8b-0OG5IhO^@?5$M8eXH)U#Xa58Pk zcnBkj3w{Onqpg>&byNzi%89x8F-@<&R(86_gDB8Hd>@xB z%nzMej_GnAaoOn=!kAcEK99jpRy5P|%_YQ)e$R@m$l}7cwj#Kt0(qDt1O&06K&Y|T zWaJppfHU9lYmG8kTA9&ZgVoPNLgK}|u$Z&RD~q9tybc5A2n1ujHg;bNi->Wrbn9bs zJ+FQA79C*TLHqLlT}p_OzjwTULM7K_U%{KK>TjEP#PN{5r}*|;0Q8cFM$fPg6xUzG z$*vVw9BFC|J7wA!^y*Aa*=YK?dr|AUg`T||r^_(b)!geJm_pDXvX81fnLRESe`)VdYx^jjXAB?AqB(0k_?XJMIT;Sve!IQcXk{<6UU`zy z&~8RVYM*wao8Sq2(XHTV`0B&8h@nXS%Rl_&w?~_p!}hFIk*$ztv#io;g01sV3fCLc z2*=mroLHj8UbcycscFddV6knKJt6Jf^v%#r5S!=OwN>E<)ve$fvCtS-Q zD1F{#%-g=&?%~dIV^gw-Qjm9a@g7r{X$(tp^j^VH=3VSC>AVNuGS+#odSJQS_PRYs z)RyIh<-AXVS#quLg#}R4LqiyID>BSpU=VeSz)T6(#Wq$txvRcSGbtUs|DI>q?*jB7 zdtTXFQ#Spa!nHu1OSbE`6tY->>ER*J4jd3+jt{H-5d{}TZ$=zaIj0wIhC6*6*_H6h zn~_6TjG^PK8vD*nC%&t=XY}HksHe7}YDfw=M}Q5F#zuDvocacLM8|Ww?58U{vvpNG zbDMSiv0Fpqpy*gXI?&^lw61Ve4#4_loI}P}6nofUkulzcIxy3lG?RqIEt*`(cOx!Z z%?xeb^j62ln)qa!k-=)x07b}eojw4kId9R5JmL1_-qU=SOs+D8?TOdY0BhSL$F&&Y zBf?o5+6C)#)mBpO zS&ls!d6O)9i^r~hI^I3!ek+f9RKI{UphjT@zdT>!xDcIMD0yJ_LOHd%C2%OshhUCv>-x*kxey^YNkPUns6 zNQ_m}BW@o%ys}r+)w7cEA9f+!FbmybId=)uZ>Ov4aP%*|@#7s2;1SmIrUFXOA`MEH z=mNDLnxhezDB+;I1PZDUdwZRvmRVb``kQ++D-+Q91>bCC%> z^M@M9tB483Iom)L@bRpU31{57S_1R<@m3PVE57U?YlSqB6ffrYGE?DueO5E1qH-h! z-7DM@sDk&ICxH3JwP{|@ymovuZEvHma!Y612HKW&+wG3dVnUwnxr3n7Q3no~%sQM! zdlIZrbF`w5!{##@$?dW~@gOuCf43*MH)na`UBl;Z_lC8L25k)_&xvH(HMHo79vqjX zO7ye~KeuoHmT;5wbwW3C0sEj3b0pno8N6qxDZ!7I{rs0TO0D+f(3ze(u(Vqa zz{^F2Kv|Ql(wa!;hbr%459vK7E(b@$uBNid2B2!h=~-hs9zLAn!4I`VPrwa6kiG!t zsS(xSGX7oxC9qW!RAq&NNyYv{1z_WqX(wmzmY~*52?ejk={fW2bt^2Q6Us_-pKp+9 zR zyDv5#IGr%L6kKo-vN3y3;JaPXspC8cI?N}W1C{#gy-J+R;Q%_faR6Kx&_Sv7dfm6u zuW4#$+PM{24tU(tr);@}jifJSnl;^N&`_(!WX$ry&*9~<2u-Y7!s9o~H{PYBmLuLR z#TKq8aeP=_Gic5$@~ql_A!(v_`?(Hxv`*VVS4i@{P2YsUoOXQh4jB|-3Y#@_r!r4K zSA2?sUh0!me<>VywpFk16x|o~j3n@Rj%5-j&L|x2j$UQvgc;q4zB#a~_iUv4hQiWf zZ0&`t?I_|)Y-*%?&g806Ujz#6fOlv&7q~c589>*@0<(AP$)QC$-s46VtruC35AGD+ zlcnVF7W{I7l6l#$Y1(a`Iiisb=4OL0cpod)ZsFUGEN+83i8qf4S14z7KNe=#6u^|e zK)Swc7Q8gJ`($_!fkC6DAYaVwTwNfzt=SFm_j3dI=jfXLKVZT?JPGqMgu11|s+J?R{PLppeaE{>@5ueYEM_x-~;iocCV)rnzW;qdW! zOW9EvCCW0NEd1^-F0f)Nr9R>lM0iI;0k-@l5HT9L^lLMK^4BH-CknUA44C69 z%n?vlxF8m#MViHhqARQKjq_y7C0@mU9X6xO@(NN;Fr5Gd{4it_xm^OBG+^}c+x^9% zN(1LjDJQ!!%?tFxKB_M*PwI};zZ#L}pgRADz4w4>s_pj$0Y#81 zU22f3R6&YL6Okq&3euZOClm#d0D&k-Zvp}eLX_S+L}{UfUP4DY2^}d3LWmOL?Dw4W ze(l`voNs3C%(^q{t_6#%hrN@Xz4!C%fB6+4#PJ~kKnXab%Wn!wAUIu(86bW>VJE7f zLS7c*_BO~YbA*B556AkByPG$gf%EO+lh7-odc1Dkm3VAiy{d^ zwZ&F9XNR@{i6=U<`o_)5f{pJt3S2r_J4YWC85k^xyGgf-?FSuB&Y5)A$<8Tbbff%+ zRBlz*Or~v^e2JJ67Hz(CW)Q<(&6a%5=sL}o{lmW$AY*EYD!5#urciQE`!BX z7vF5)N|~&O=48-%u?=J^rpog&P;#5ReHIidFNuTcpO%pYNsOnZFxOKndj?1>)-E;Q z_6z|GjE^*(+DR8;DRvB(IJ9vt(V5~ zCY`fq%y>Ojt*gdc;YO5*WYkBWKuT}SDZcw4R!#JP|+eNHZN?*`6#IX_7Ddf;EQ z$t#?M)-u*Ud-Zk$PNy0bMi)czK#hX$DN?xtwp;)|Z?Y^KNtU-D!c1Bxn+=MGaxIC0 z{P8c33GF*s-8t-)Saa6YskP|W4&R23JK$&&@c@j0Jtq(ZkSqM_t5%d7>`hi@ATRkzKId* zb};MQY^$PlemgI^Bd}9auEp!`l|<{ z%kgg;2H#1iq_XP1rGNZl{Eu3(I$JxwuayzzG_N3;&u?;KKb*MJLl%Y2=19LEUIF!e zJSATVy7H1sQsd5MtMIP9O+7G)6*=xd3 z{Z{3lbPTU(MUpxB{mFERxRtxaE5Q96HzmM4QBT`!RATGKW+62yGUcyiz}v6@sL&a0OnUj=c~2y5J5t*uLg?B%}}aIImP(R4!Fu=SE8hC*DvYv3Llv@qYsWy6DT z{wRGss2jm0SqRbp!LdIh7#!;>sZZA^RR(&@qD;G^_uxDRx%>gBWT`&K^J2w!IZB9& zo_DXL+t<6+E!VwGt>ZQ9c zH}@sODt5R`vXKBuSMtjSUA|0yp;i!6rsBlIg?Xx{;aPVQ*jev>zHyx*<@GEwYiTxP zyep7-S9e9tmrx7uA*fR{eU-#yS$F)%`8LyL5pc$%WF)Klt;ik6^pN#Sv1iO>RJF05 zG=z2{S2-D-ZUS|iOmAaqG@UB-Cs-<;xip!y`ZaB>Ci|9jqtfH0rh|5xiyMSrv)!$| zTyv;=3vah zxwthQ9mW$#%FfKM@6U_frqZukF4$@_9E(Kd`kMyOZqVkfec>-Dh{p1tK}~rU5xq_7 zCp|fJqlVn%jV>lJantKqc$u_w_wL)j{*{=}dL4QnfU3EmIiW$g>`YAIWZg`~i#hA_ z8Ai(YzeHfB(SynIdcM8Af-G;DZpAKh?ZW(UyaX@Yvo*b z2kS^OD(&>vNKbaP)IB$pak4qr6h2t=yb95mG^jxj^IDoU>H1B<1*ODQn&4<6jx1G! zpA>!{9mw4_%H-$VioJI%0IoUBxtR36>+Ahn6mpLxTAK9<9;YvXd*tcgJ`DeO{fFEm z^NQ&<3U~k!Cj)WMkzJ2n-0{tghC2_h_(MeKDEdT-+o)REPl2iAObwz}X9q8FC@!&W z`?vCszZe*RF}aV6He}^5&7sP7BW}!#&cfcVz1o zqi;(OMuc#a+mP2JH}#x`QWwEyK}hesXm6bCd)=Aay&^roK3(MhIBn#Dr6n`DBRNUJ zD=vqUx7gbTd`3&UKetPCw;txeul`H~ z>N-yL;UV%knm9#IWi02%gM}Fgb32cUT^|cLz@^qu+iMr|v0?^Vh7zGO!d+w1hNfa* zY{aJJgwHq+D;)({c59N#*YV2Tqb$&)2~zCyBH>$b$8q7H0e>B1%lt>tBNAu6IBB?o zHRA19-ngDc)J@W~@? zxNBbl7a!b@=h|rlI4I2=xMP%+SUq0$&WQA$`T*7zq=ih~Rn!1*;4E2chI?7hL~mGp zcp!1Ho6z+FkS|1{PR+hA+it`i4tYPQ8YMl!N@iLr_F8$~AJ@KV_bJ0MqZHHp6`|nH zV+?v8C->ueWnJqRCov?LO~0{mqC$~=AYO+|KAPOC^sdN!G2ZX+DDK*0ilUg9 zPt*^n{a^Yw1jg6cxgE1CSodYs+-V=JdiJbe@47Ji$2Y4XK9GYS*!0e&SmXu2M8?fu z1t}Ob3#3pFybxqGvN|PGR!$SSqA%m&dB-@~U|y%;V6eJhxNklVQYnEGNc{u8p4Nj^ zYQZFOfCITALIl4D*6##H#I2YF8T#LiQBiZWoYQ2zJ33f%o|U$_7uqAub6p5&d=biK@~o%(2G+;~@Z($OOsm)V1dz zYFH)6?sQj897!??O&VhjBt3QbYgO-`E#^x~-sLG+7^DV65N%c` zj2H*8HfmKD8MW)GDBr2q6i@f|YTz_fPEM5lNVcXnKDTqmzL>*Ia_+{SOKm9jhK%&f zpVg&Q_VH` z5ffYj;4I$)2LK3ka;Ygi9(KTpLjz(j$U|<4dY_SRQ^oKTAl&Rb4~(_~-6hAPLu%mt z{?nK*??1z4{W%W$m&BC+s7{;zv+8uXw!+AqmS`6$mK|7D{4bfB>gbE$DEJMb-%m`4 z-aUYFi&dlltMYw67Jg9!Q2>8tLuY^SQ&y~{B75+VIeL{hH;S=)bs7o=h=yZE} z-JMCi{XOCthhm7gg;JVQwh(SQ+N<6`f5%fsRPF=o@LHkmkBEc8D!9xYn&USW+&WyW zx|_$HXeOcvF&$Vy*;TnJ#J;pDXAkWOEJD1b9a8Q$SZiBkO93Hs=yEOpVpz;k1|V^4 zimz>JmB69fmM9?C+O5p0OE+g55YMF78ym(vIs5m<7Pwg@os!L-KRY9X+Q=f>C@X#< zPiXLYsY>RN9^#clU#O|H)Zm3Mfp zuqXZK5gtj5eWV7{q3o<3;9H=<+A3qS1m=9xe9pBIt^&%+8Z* zZQn?m#7W$o381&(y$s~yjmSt=q$5fhzUhZM%7nf|Uw1Wu-j)(*! z*?~|ieFgMeE=}+)cLnGE{Nk=x{IHyH9<_Q5L3G-(Obzuu4~c8 zhW$&I*yOIa_wpT~QLSfAOOUSiF|0)1ySVgFs0!2Pl@>{h$(-b1ooxdHdRv+8+3BG# zey{Be5A=o3hFi$FzSm>_%CFq*JsX7eZYv%)!4Im_#&k^Y7|0|y?vz$+pI1%;AfieK zw{jhguf2;8yOzUhsZRy3bxTZz2b#L>d#p8ObX-{p%JkDs7HsQ{7F&)Rm^e2(r~f@H zA)-}!D&%I!h(Awam$X4!Hp_^jJu_5xQnWTrGV^*YBBRW(NGXmb!==+2D%ZIZzzUjy( z=?Unzy}Z?x^m3P>jWE04l{jnE4x=O4;$3>OIdJP)1zRC}6N;H&1A~*M*b{>y>A@+& zvBcCCdt0_BWP$4K%Lu;Foo_yH$5DF_M4VuZrcMG`lJ*iBu#z+;ONX7!)>C7+wGEg;e;wYyuB0z`UZVIqL4b>Ea{ND zZRJf++sPSt5Np$z(M`LWwk_hyV16M<>J7`l%ff{D26g3bHCED_0cx1N z3bF3uDGY6vCyUfH;U-DP8IC0tqiXqmNh~WF%5*a{tin`OZ?yx5TktA`_qe6-^e%Oo zaT4|Noa9*T`J-~LZQ8ot5AqGio~sgu&rq-K-LEb-YxjPaGE=pt-kpQIE_m8NGQi3* z5ycES2RhaHTJd*g*YX-GzLpsNrl7^OjLJ++SkEqW(*Cf*u}O)Ns)T8%blNmN3xMF} zjUzAS;1{&LnTnW(6rg z*HW5{AwRA8ZUT7ZC8hy<;@=cOO|EV|F; zH20um#;9j2dYOj=hb^AN^8=5bjT8Mf@iywBBdSJ)?Im03=G6fW({g21eKm_S(>_-P zG4HOTZ&Oy9DK)nC+^O_rehb5_fT%P!`72?|(nx?PFfF+PpF3HGN2{`7nVG)1{hD2H z&j?;9(=l+RIxilcYmBmC{iFDiFnM%Ly4KSM`z1chMW+7*AgUyzh#zol%V}A-rLMs6 z$kz%6L8Z20zbx_-I;bJ5di<%Wp{o~e2_{4|-2h6C{p25+X^0n4UySUWJq8eox8>Dt zu9=)&F{(iz-sU%p8g%jGdWt>M>s@($e+ucD_$DxXJzSO3>Wi(iNquv=U$fwQj7XLJ z(no|U6ChD7aF!^COE_*L^S3nPypmLpdHnK{^#~7YRhlI%->3G8d`vOIgW6$lUjB-V za0qK}yaVSPMzYUBGu;@pUK*4Rpcql(cnwc*Y8Ub-)CbRgwx)!T{wc=2{52UL+O zR+TwKk@2S4WorkWEuquZ7td&gHH>cSDvp8wMC>tUmB3te88 zC|RaZp?p;TXW_8(?&7G$_pG0OH!?2gw3x*GGjvTgKzRo}0E$`2;ikLT-M=FBE)I?U zJ3KvVUh*0cswFxB;TlZX%J0Kps$XT_p;8}qd?y}i2e@1zF09CYTOst+5KHlhF3@?u z#PgP$_S_lR{*4nIa6@xMM{rxsS%jmm#7<$luqwqZVT~?0&JZ1Y^CcXY($PwTKNpUL z(Gw+&zJ!^Kk@N{&<7*R@E?=_2M-BDDLvtG?-SI;3`Rgf zZZ|T2_O3xEHR{8cB+7Qbh^u29Xx`8jRp+X5r2EoL|BucL^H|Ri!7bx0o(254rwpe@ zS$auH_k5g}K2>AG6b0t>rnXm!QI5j8%UVbnkhP$Q`#Gd5V}}MtT&`($a>QV4X5s~i z`?{>!ZUyJM$}Q|##?{g5$^GKDgx^we>t70!Eg@N*Cc!+sXZ`Qu{E$5h4((%=k@c(1 zX;a+>y%)ABlJZfSX+U%Pg$Lu}H-aYd6f!3D%f)Q5)~n;?ArhOCDp{WlUslQZ#(AedO+=0EiXBz?UR$$|06YV@ zx+t(c`R_LgN#)RM_eGz$B_<+=<&(|aTWTd8YpJ^$> z5ttYz&_}SDbqxUK(xI6HkD zDv1d~^AIB+h4yGxA(VX=dslk(C>GYexv8IzbE7?`Xga-PK}_mbH+>=Ln8+wkRsH-q z8^yA8&cqhh7p5=cYbY5wCQfPdN(P?$*8VsHXeO|oU@N;b% zb%-5&#g>&zT=OOO*%xoY>W}M#Ub;m+ewtwHgOJaQxh1M6F&80ePY^zRA0iWi27pbK z*u>b3?!>Zf5R0Npu)gD%6*M4LbRtC|Y3Qtw+R$~0A{!(}f#xUGg{7c2 zfz(D+NBkAjqFs(smzQVgjq4^Q?jCsc2_*gln(hZ08@X$OSHWsz70v<}w+^-3z9fRR zn8aRTT`g{Z^VV!(!&0{v#J5v6UW}b5-Gg_6`Qkx&(@pgibNWlRm0+*nX>F*%ZwkhA zU@5ts30xId0HLe^>vRGd3?l^qHkn6*I1~uzJhJ*2{h|djHee;`%{C%wN&O%LaOeY9 z*n#fcBXblIH}evCcm+v5mq@;*OH#6}Jf-sn5Ys?=B@QV6vxtiTfagR~nms8BhLT5X zY=VAMhye&Yk>L7&;Q&B?_wkYc`_upTng73e*Qxvi==8w63sfJBh&q(a;)co-)>mAH zy*eEnN)HbrZ5+x2r%B3d>8I!AVashWe9T5ER_5MfDsT}jVFzLpB!%IzX=cDlMGI&l zYTUV8ISkAj?*Z9gtiT%G{_5W${~?yJkrZ(<0{}g|SO!FCmsXd6>Lws&p8lIc$eyI- zvHzF(v>E=)4~Yr(fTVZc)Qy?~)yA6*FYes2eu-9BO!3-bSh+rYE?ANZsGG_C}hGT(d^ZTtd&dN)5tt|xXOzeTQ0qYS}aght(6wvw$y27LYG1R{`s7*6<7zPtCn z*7{cW+O4QFbrK~EetqI<;+-I(_-~3xbykuy(G95eW=p1@C}W0StH(5Y5T2|xC$BE{ zDGu14e|O2v+mb+Q!SGm#8T9#)SxCR~SLhDu?F4K&?Z5~(_W)-KM~%rA;w|xpEvSr} z^(9T(YXNLlEdyoWw)v{~AAM$UUqg~u45dD zmPMi4SlKI~vCh@154HG~z*3*JR?~FFFYaax;HF7zG-Q^23J7o860W8dSdwU6Vx90n zW52o~xNyke(TNhe0WJ%2Mt}I)dOW`ZpWMDokYjd5ckj>nE~_rl)FBgL^^AxZufj~M zbCSy^nJjRA8Qj5Aq(;}xOTdT0IKNb9XzhxT0>=O)JQMkJiIbR%QSLFKB=Tai5U)ru z@0E*Fj89KG&C)B2w;G{O7?KxkZM114KdOjb1b!sh6;GKB*iBHl`>`TERApt9W+v@t z1!#q86%v^@1wi^jKtAKCD5jF-`B_g3WPE`kJ7}U&{b*#;P--afat`9!-)gA-@mdm1 z(ug-NW&5`p`uFzk-xM6L2O&!+dt4Ocnmyhng^;*osJ?yD&pmLOA(rmV_XEN4^Vk!k z@%op42b>OSdYTW_tZ=uJ#&>_rXm0E(AFc`M{n5$a+2h>!#C2B?!79-c{-DhX!9V#+ z-w*5=?5UW#YM|EAq2QylEZ=y&Q}RsvSw0qf-u9Cl&?mU*u*#4NM0#v+d1dGK%z!da z&m+SN+dSD>PvqYzH5|tVP~8-g)5~zRO?r0zF|}{OBTJ-gHz+DZ8Lx&8L%IZO=uhlG zH45Aih>QlLuOFXrLm@NV&6`e}_ulXbb(+4Tu-6f5LZm&BYV^v*6l3eN7c40(+56FvZT;aM49n)A+T(ZwR@@V$X?2*CJ!% zWJTV@k+m$Mt9YOinOR&v)NEq?)+v)!tnXaMXI=I~fk+iVC)fph7m}et17Yq+o#c`JQ?^G8bgW3aVFu?KDJrEXK zZ^VHXCj?s4M@}62=JP%)zG5+@`ZMO+(_6HfH{LE1qfbduHGPVQpAN5igs7435lc(Nl5lLDvj(S; z+GBpfclS|TzU>Ug;H$wUv;89VF}eY&A61k2B+l7Lvc1MnhpH-YUT6 zp1A%VO=QBc0d5!7ZJ=hmKa+M4WDxKqN98c%=YR=L??Yx^5wLE#y@A;X%QUj5v9w0B?W9bE^Qce1hm>hzOd zl^!GzCfK3l=GtC(tPBd!*rH(xQ+wJEHpEy0nH%t1_*Nw!=iI|i{=@1ORh$L^y#MoUtEhTBM z>{CIco7pf6>c>6m3X^`GV!W{3bHM^EpZkOs?Srd@WJMb$%%Y@%KK90LPhyftP`rN| z8U(eNP#3k{l!Nr3vITLANuD*oz`?A-V(%Qe%(>XQMfGw+UM9V?FJJaukB#}w@cgxsc}fuzeW^DWvxUM2+WMXH?PpxN z5x*juR^S()x1&ixu+pvB^{nD=TlAiug$r&3V+&ftvh-^TgoAd;yeKDKi4gM6g~PL> z?X%>W5LtMe-K7bIEZ#eKShT7dR*mLPbe+mZ%H2taY3G>h@pT79t_8Ncyt#Ylg(5_X zIS7c(4PvU;n_avyzZj$A@QH~|GS>PDCEWwguX^)eR9;`YB}gTgOp~&$LE9<@+2}Om zvF~E$-a4NC#$xZTj$S@Tp+`7=LEXh1X$+@dk+7j?+Nv zTSEWOg<0g^x+wQ$k3uWVYty036I6|!yks@&(;uX8U&V3PCH(f%K73UYYTgFc#i};_ zx55&AS`JqK6Jh@UiZj=L*+}^)j#6Xp2_#2yAUZ4Abunso^l#qVpdV+vW9|MNrYXgM zSL*2%%}wIFaP?cSh9cO$W+|>!aEp9xBIF8jd+8zGC|04#kdrrFL;plHBI}8pKLIVH z;`}wu(oSDr>cHsjRdx!d{kqFV#^9$Ws;xgTh*`3N8;A>8_Y&sh%99XDkQG;VnFF-V zp!>=&UiATlb7xbCKjRm5d*z*ZQKDKA6o_%&#Dcu=29We!xZ}xJJk@uk%R%#A$bQl~ zkgpVE!a`d=+BsXuNdg77pQA(GS01~}pFhHTC{yzRLCc7|DLzEb&9zw=dME%gU` z<)Webx6a*J#5cvyJxUW-F+5Gf)bYqv7ZVGD?YravL5!}9;YweRZ0AC?{IZ7XIgy7o z(se97f))?FSxS8ha$!u`@aOPrvwG6SVi`j^d) zDBIhQIUW{`OeDr5ojo-k5aWwBVLV>T;|f6#lTWfQUW&Lb+@kz2 z%&n2b`$~>fu21)-#g~)MrVnom(v@7LSf;q*=G(MDBloijXx}XHss>;+63G0cs=9T9L1bTAleW+{V6Y%A1p?)ouRt2Lval{uyKyP~LX zV-75oFbEn1&b}itwrXn}B8lBdsN3g-$Q||_7S{7zscmhIaAfgn`Fdgl=y%MQuW4QM z=}Ne1KK97i_sL6W5~ebAsZKUjp$SAqG{+uQl7w!$q%-DaM7%;|%yT|_%R09Ub2kW} z`}9pTd7^EDH=~>gct!Zq@1#GQe%cRgUBx}T2QX`;evJ9Stx`W{;_~tQEpb&XmczAI zzkV152eXGb`ZniNny{FeUP&DY*2EzJwk>@tAH)UI4fj_(MMS*#ZhKQDHk6^JybgTv zWe>&27ko@%uWc9DZzwSWjBI1Uazk;ly7g%%sSBW0{iQ)spNkjz|1bLWdtHUhG+F)g zzmZX2rnbi|@GB?*&(JUN9e<^l7ygaZ3ZkPgyGIRBa!K=nha>6gkYQwHpg0;s@(Cm4 z#u~OxO6AKzLeMC6>zVqJ>yKvm(R*24h~&{?nl%?c8tPCWNxxkO?9fV2bi<_^6Xlpv zJ(m|Gd#)KkW-lceT(2OAq{!~+-@-WD&>Z)oxY!l)k>qijh;)I?vYABM5eqRF>-p^# z55xc~PGaXJxYgnWYF)6LRT^#|4o{-? za`m!JB$DyhWPg2`!NZ%vMq++mBWU3Ycj`;Y-Ee?wo?bl&XTZA7N-k-zdu@1+7q0iEK*ckP3V?8D)JwCG9_)1Cj-S*)I z4PKHy9@cH8Oky*~EVU2Wfs19;1;L1CGoN(QmWeRKFP60N*PYL8mULeWeO08Q3%Uzy zR}Q%hpcj5q)YG8sLl@})NvFhfkg>Cqb@aB*pxT8V#f)`}!65j)&H<@C!Hjy-NAd`1 za+(#w00v!vO5$}+I^{qt5TS3Dn>D%$xVdj_pF8r*p7%B&W#4}j6Ve?BJCKn93?-C1 z5-&m@;P$&=7dBz8czC$b)vd-DoB1{z${;yhC{;KK1|jLiT}8c6$a*wxMxzK80Bj)4 zZ@m8x=@m*f1PR*pZxTS?!GEvU^V0dSLEQzwL`#t5i18cloM}tAL@=x4X-VJh-0FQP zK4ITJVX(lizGzk#Ex^y4JUxspb%wRt{G)`7cGcK>%hRqs$wf=MDAwg2(CkAwSATh-5 zBhwDJUzYzla`}V`rw7>m7 z{6&3-Tg7IrDnk{;EFQ3|9tTmJ=9BdU zc62AaW5tqQk4~r~NhdwP^`TS$>kj3k76&rjtz)(*Q#z`mHa-d!^YgZA&-^wYH-1e0 z1wfi?d#?XCIzN9XfKuAQFeLXD3pf$RQ)$PfOe~{AOg98NrFQ2Q-AkKlsBW$`5T@2! zxn=nwdYOV!gz$&f+-sN{oSLLLd05KN)=3tNyg%K?<6PP(4LsM_^zlbY?fu zd(u8aga5^e!4l0kdx*cuxRK9C~LzAo$w6k!*yj z4_YM7_S?_rJ{GGfM+KytIL63M*$9oA<1XeiHtrzYJ4pHo+kGTB{{Eh;tf%auWOT@Y zi2U7=GPyp!kh>+6ob8B@$@6!g>uz^({Ji1B9I>O}jARTMopp(>+*iM5Kkrs4+BdPs zgZ*LiwJ|}ZoTDr*LimDn5Ue(;n&`DRO7%ZDbHtt4H3?OX@#T5Ge-lY$7-F9kj91Ot1?!L}T7fxJ6Av!~yuhQcJ=j zW;Nl8WsqdEF-1_S;!kA&VTP6MhH(RoKm7^sy833^RA#RB=e{B$+<3Hb^i#S)1V+)o zRcd!N!7M2KWk4QuFSh?NONjRi9IzgqcSqLKL>+;mOj?ek%An%Q-_iA2#f$A6LnlK; zJ*v2pd#|x>LWae4pTxr%hSK|)#20x$QFR(@R_I{N$!6v5ZiSZz00Z&K@5(Dbi)Yn{ zxxtbY`INTA?ixNZq7?)&e}qTGd8ZhTzOWEj-^R2HT_5pzStNxzG<{$hO+lr{@zV&5 zDFsZ`YAWLa{eaw3Z&+H$2yuUK_-SNU7O zOR9?HU08c2H#^}_VTQo+JT5Tr1xro{>a{+f@%F~j`SF=|(86uQ0KiBfD$SlbA6I9d zmTU{>0KaS$v9qRT(SMPAJ*jr`(H$R}8$w8>X6h1RSle$3wz^;=OhP;;@-sg16-leq z%C!(RZ6}!V3p?s5HojN+`TfPuS%YygqXtU&bt<5%AXoUNl?NFH(0GjE1bC;sR1H=t z*&tzhU$TE4n}5l+K8fDh6a8u_z33dS`n4+4Om3C=tta={H72d2h8R-n>BnXeUb(v( zsz{uaLF8J4k2BuG?IuB}*>|%EpOOPYf9Pl4O`ee!c8#WcD~aWdzRT9<{R!}1*9Z^c zZyw1b_LR?W^B|&^Py!M$v*6P2=@G*-ia~SswVmGUw09gOZ_I}ys&D*!Ao0BFqen0r z(BXaihw6tu*ROVSiI4W*sckAc4_h*TDs&$dyUtl18r?vGUbaA}YZD?|que zNI(npZ;hNvlOww8?*abo-ef(a2-xoNZwdqP%1@FT|9R;BAHDz-|JComWYhRJ#g&RO z=Ir=y6&k{prt4ZB7ypa)o6 zqv!vxJCr#7sh9<}`YT1Ro;m(c8OXAKE(7_0QUmKqLDpT5%*uRNwq5C$BAwv%Zz5QK zRssLK*xyt!f|KNE1OXu%B_xxm|N;3Hwfyg29 z>c0><{OMdk+5V57dOr>R!Tv%zcsRxy2uUn5sGs>Qn$y^RlPOdSc?|@_&xfIfCtBn& zUnmQnE4(gd6Yjm($;8ACXKa7Hv~%Y%q!^~_TgMp zRxT(bw%JYpz;~?kR-HE-L{ZObL?T4BpRV1DJ*cqe7JOonn7mHBg7;qWk0VPF7xz)Z z?HS53Bs8t{)@*h-p|4=1ZZeroo_qauu0d0Dg{Y0}V1)A7IEP_XX1uT&(HC!z@g~W{ z^IE4^;g-Tw4KV}7o(kaI+iv;e^|m)@>#1XAxt*@sYO{XHdi2@t_TGB+hV#dwlgdY@ zIUzKgt*oP}0f3~nVQlB3ND^ke64k!^HBG_ab#z)7!cz6^*>R<;m6zTkC{KG#0O^FHtAQq}T&swQW6_-;l}9Io;Z*UzP6(qo~Nc;&8E zp2-*STwMTHUmr^^&9CrtUs2Lp63sk+t41xn(Li2hfOnyfwb(Va?=iOpQ-#raVkuD5 z;EC*pGZBr<$5j=v%zVU$*o3|AAn*qhz47{sUiFr{BAU{5GA~In-S-|pqer)ovYdHU$?5m#l6&h%_bcM=l@RT0)T^= z9gQYB4eD2?6nRx}TVDs2X0_K=pYRfmGU-@@;u4Myl){&7gUCFg_5hP+2h$27g3V#k zqhFp>gC5MMH3mF9zP$~1Z`OQuH8vsjaJp-O*$U8bATdrV?5bn8(R$PMmX$6s;*j#E zDYqvs>3*1C;i*d~%8#P{@W|&@$+{<9Z=}&_E}0*|)J%tyOz|$=R-!FSQ4SwIr{CuS zIX52gMT;~<+?p16%4B3iXXYm4ye+w zi|3uvEGIA{!rj&Ksf+y6l5x`j;E^8Lk>OQ}RRi1Ob>eBl>dM8nCUQSOj~ZVq28buz zsQ3_>x;p&uEbrB}$VG}-@M_Qy7fPK9f7*lMx9`kog7|6^TZ*^GPZJFrn=*Hl7dcOa z>;Ocgw@4Ll-`yru*%?kXt*7?!>Ku5Zg#8dXu$6B3k##9E`zDNuXZXg8@8QYInx(cz zzFf)ph#!K{lNG|kFK&@>(&j2$66$E2E~@cgZwtLfyusAtc%-l@ey zw@%E7z5-%+c+`=!{0`(9=@R}v+&{qMtlZCn_0eU-kEILIcYl`i$o28!@*D*m2ruw^ zA6C3$$;{KO!Vu*B#4bQ=3w~!*p;V2=Y-9>AejwwOFYlgoN8HK4=?cRQZQDKhn|yl& zCQ~px9{@ahIR6nX{PAo4ZyA)CI2qJkIvo~ImZaj14GL-skoL;8{Pe+6Bz{8v=GAsH zno!#1u&L(p4$xV3MySTr244I%lraYqWct-iU#3jqdyrcUV$l|#^R|5cOxR+JPR!aD zzWmBpBt|EuEN>^w!p%i#fh)_^db^jj>ti-4Ri9CO(y4i++GTUDXDFj8n;G{mFeE;& zC&!{ZG17`_T)M07wj?Jau8ZDUY@zD?%G0O^j3syD&ctkPeqz2JwtUAGBw?vO3v&x%_UCSUdf;Bo5oq)WumUmn>vac1$@bE6}=&fYtMUr$sW zKq4Vel_r*a;u)pEbU!`x<_Mv=+ ziV$S`NY{(oZ%YgfVHrQN74INZj=U(9etyRvXYJN7+U0lg#(8-OicMy1kD?vP$)X&L z?*K^>r@OrLdZ*q{rM>msr~+VwD;7$YRJ*yz-W1->$lf1yHtDV2w;3B&xuKWJ0&KYY zZ{yli@lIDq!^#s*AagshB8FaAhRVIp+e6%Qai1kZjJ3T-?_$5Mh42!&aMtaJsYdu4 zD9vYAM4CCPt)^mHrl+@*$q?_Iy+j_W{M@IJG$geLoIfjw>vs0 zp*HdPq|?mf)a3@>gljQ-3c+kTxTC0X1$z2mr9pj#MZ-FM20KqwyaKwKf;TT|W`0F# z&|) zMom%F)fo0529r|vN9=wQ7pndnjSVl?|99b?XMBzX zRBGKdC*~+Y@SkKdR9$}~;T~HLgxy83KlIk~pE)S&8Zw3gN|wUU@|>9REgS_HrP(R_ z7p&FlGL0kxK~|-nMG4;~U(0&|T8y&!Iz@qcZ6T1c3hR5=+rlK}rq}|A)IC2HORP z&D8S5%#eG%e{O5Yl3PH3^9kEOb_9mrPne+zS}^p(pRl9Nziws@Sd4gd=QKnloo>M{ z0moB1V$ts9e|dhfpyaxnT6b{`zxqg9f#o^=ra-!}oS3~g#%4NOmKOh=-lw}gi=xs^ zp36B+OppJ`8UDK*@jtdX6Z(%u(u4HBcYLX^I>};h0P>=01-j+$%@s^dRkrs7PpN?G zvGP&!RUNFl#055P{qJ~C<{=&|#EkrELO_o2B;k_s>_>l#_w%>)m z2o!>7x;?Esr>* zSaq2fkOYnmg6PVo#|IywMiwAKzqZMf!Vt3ABlEeozCtET^MYEQy#qzg5+K3v_09VGSt0lIPK}0`HJli8YS9Cq- zf}6QNXqHVWo_F&$&52)2hwi!oSjyMibf!7EdX;~W*^Rw36>b5QBx*U~`aS(E8>jt1 z9K=M_4=tJ8Quhevy1|C(pJw>84KcJ1F`~nhdOd@~sASZ1rFjo4^xVbIIS)!Q*A`$zA5=$}iL?oc*o_o_-}~D^Ryx zmcfl+g$lHo@FU=<2Rr8Oeq5OUM$cjGI+${Ad}bbC0t=P7UJSLk%s$nz=2AjjSwc$(#4 za&B%xD%PHv*n`T@DJ(2+OS^bPFU#zH>5cC$_2*O|D(pY^ZN(=n$!hW9X+i5H1HAt| zq8j!Q&X)WYYhbHi?)gI6$GYz@^E)lWckhxbudeD-2oK#crmH$YpUuBK?|E%6M)HSs zJFITMt1=Q^YnP6{7Eg#KQ^(M|3LCGD2OO-ddMWPP z*QW0>!tg;TJ87I(t$KKg9mH9Mx9CWNVWBUez}9-{XMgbrb_L&#k*hC6R^_XfvBi(> z-De=|$G{ouK(ULIldb&34C~Bb4Ks^lLl^Os=L~P}rgTc(*P_4=@OQ9&VCpU`miF$;zs?8ZpZa_%0jY zq6@IQk7Yp0`s2p2OI@co(aVdk@#+KmO^w9pMo|4Xv`ViKVl;n3bt_FT_n|_vc7$m^ z1uAT;_|fe(mv4vW-GCXW8zB8CZ!a(d0e9fQ{$w`1ZiK3ulZT6(;xU0_=EL{(r^8#t z(L3UjZPMM^KClZ&H=r#7qOWh^#Y83);_gST*gl>8ZWc7KaCdv@PW^a}W5n475d+m} z<3ZcoMW*L@^V*o1`({I5VM=BC4Z-D#gdjcRF2M4bNKuN zy^S;Z*N4>JtUURVKv^;wknWT8C`#fPxVLA_9lCHaZsF-3p;NE5b=)Ji_HKg#*30bigu={C=cyn6{Wm)RorQ*amtEROl8r)3m&sf8MnEpwy#&w|`# zd8jXm7LDDa6Fk07g>aK+t>UcGQM@oT6?|O??P3lV|d@p&%f9* zY&eCJh4ldvFn=rYXA$w`4Jg3Jp*@(jb~jQiO>Mc*!$ME_cDOwLJ96O6*|_B&{S)u% zlt#-9)I|Z@&&QAVw#>VDirs8(wuw-vY~a*70EA;vk_Q0 ziCvuVoT!CG;QXU2>*+K1cfKj=Wp@wGYpHTQEE|dXcy&P4vze9Z6_bT|8>p^lXW`@- z$pIhP6%6#%?zBvkRDvMsc3iGdZSTU(5lgLSV-oz=1Z`~lI8jT=>D8S#ocnoz*5=GH z!IOBD7c!;}BEnaY=i()`5X9#Wn4fvzIeo&?oJG6)Q@OH&dx$ijmmb{0&-qej?-NeX zq=}DD11rvh%9(yN#y=wD%G@Fl^B`j@*2fQb<;VK+Cq&U5*23!~9tEico0 zE8_t40+M*S8y<`U->)Ll7k^i0#VeJU1t$}%7jEpz?CeVC{E(qaXW+bja9jRO!@~08 zA9nhf#BWP0=@9_cp!^I5NTt+i46#F2J*dFeBE!gNj~5FD_Y#7@7njqfFalWdA6DXv zaS597Orz};iCy+Jk-L>Euo=ltbxM4Ed`}cfzYsE`XbqNJu$saibm~~&5TaL{9~bdq zk#u^<9}}@md63ud>)!b=#$^nE_i1<{!;n<1=ZFfVJH*HelJOMj{`9n&4{$K@?zL80 ze$uU5Ky#9%JDy%B{eA7O^TSuq_iy%)*v}B2jfK!}!3EeJH6w9Tg~c$3Hx2c&{{IJi z?;X`txAu#ofT)O(E;UM*DqSTIkyna{^e&+EA_PRF1%e>G2?!_%NbiK+A@nLDy-7(x zke;AGAjP}hz4!Z_z2Cj}_nmXbIOiMpj{66?)?$^+xyYQ)e4byS{zdV2qL#7iQwy7o z#oQnjv#|OT?Z`l2xIXtgrvDsyIulGPSE9n}Env<^tGNmsYh)fMm}b8zt2(Kw?Y(=i z0_C1E00-6ua4!sK7Ic)Heq^l$BAi_UbW)TAaBG2lsIhXS7;ngc5?iyr3$fzxO+*x0pOM;tKQUOItIVNoAG84$M38sMZ@=53$@^u=0Do zdK-H4G3Qa1SEizHWDd^F0XNe^ACB5%pzcQq2$u#$1{J2vqsW*ilQ?$<}g) z+Vq>Yk~>2pNd${g;vwvFd>uf!9W^3;KOF}-$5ltIk!OIpThaVS?yfiV#}w+0Qf
OX zHb(#K@mTaN0n{q7{Dc zMH56BJkSE1m5XmiFklExU+^tqO)gELIm_)OZ+4X`ayiGE<;_ z(%OCc$K28*Y!4$oQbB&B;QYQRp@p@0WB#~vIT}c45_!3ABRHL=p^OlTqwm(J`mwK0 z@^b92B1Y^ytdCu#1)fGGPk%GDP&pH9u(yf00C(|U1)T-JG#F5{SY513*M)Mv;L(S2 zM#r?JqQb@O>5*xY6wz$*LKb(is*CSs0ua@0(p`8!>x8$} zRYfB}_nn47={JpY3oTFLS!U2Z5rnY23!|pFfy3l$cq>wD3H%~1(Xn}?;+;&no|bbr zL2toGyH4BBtsstVmrFc!WUA-YwAQnzGl_ta|=*&?|K*wy>^ntZx@R#ELYCgAr)$$Ins`J37WDsEMKOC#%x7LZtR zgRJ+4FVSjzGlj+xOXM%8OE2~*EQ#u^?P-d_qXsQwdXkiFKpw!!n?IqxzTvKInsKI_ z$eC{;@x7Xq2`%%s^X&z?PaMm7zYQ(%dD41T zz3acECHF~M9OJU7pb+BiL_KluXx-LWa)=^9{?hJ~3unSrf_?XmZX9HLf;oL)N6Oc+xd}Fe7f_-|!=T0DMiui*Ee7g$2~DU<`1D7)D=C}p9b<+ewZ*UW#J^yYEg%y>`qop?X37T z@Fkyyht=ttZj>a$pXdEc&95%d$ zi{<+0efD*GGWM)|CpYEgvS_3$dtW)PN9vO%o3DVm`lMfEWu9<(_oeX(wkf}~_l^1c z&#q@a@CU?=yW;s3wNHpQ;A_XZpSAr~>%jw52l|u${2Q_GgENq~htLgd?x40l8FA6- zw&M36NlVdBi9y8#)^2e-j-I@HzfpNHhPd)bn4C{eKK-WV@A0&2%@M zx(WJVy23$^Z?RFa68fNLd_hcx0p{4d0JMU6^N_b!*=2Oy*cJf+Z` zr%`n#^U4Z#mfbWzMxM(aFhkEC3{wuCgm=~~W;4sNvqz34;eyTe_W>txA2sl>HiE(TJI^_tb0 zcfIbyuDurNYnj@JjRSwp^*@nu$tl_sOP={NeOe13)?3L~rXY+)r z-yR(ngLW=oEW~aA(w5#DGj6TQt6(O4>ix_gx~)?c;(~1{m~mgX?gdC6v!v$1j!Az) zY>49kR5NgL=?peJHjp2FF{BswaN3)jzpXAI@o0Taj*C_2J>yNytHw??T4gsksFmkG zf!dr?YE$^9hr8~HA{5<%mu|DkOes=+z>g3au|F_^{SqvIWJGq+ zCo&l87Lo(Lw5ev)To*#PV`58C&0)Wtu<=$C{MO#vlRf7{@QKoO?9i|#eg?;i-VYBH z+%`Tv4!`~d0^?5i6wmi`o}Ws|z|fkz-dRU~Ok`+zs$`!i5S2<13qy@Bond^%xs_KXfwYghTT6gy`g=CP(5YeA-%SRgn?Ss&~n- zKKgy9oa{ZPfR`HNHfB-(A$Iq$XY|E^lTMi^k9j1m%qGnJhk0J;0uRI?3cs-;^9AUK zSWg^uRSK{wrLyoT?Y#pFJCuWdw`7}KpOMh>@Me+AwMt}BzyxX^(pcATknG25Ex_H) zh83Y`!d00Oxjsqew(>H~OIP~Z7;b%`HslJTFtYIx=`8=a>|wf%FU|OR3 ztL#E;>N%5_JD$=tGNG@QK55z}84gx9#e+$OKeHIW!UbD!4zHGAc=c8~PZ&n?>eH9n zbs3VabGw`p%jW3_Ij+K(M#a0xIIn#$ULVt&S%oV#i3aLiVGvIYmq;i1()g~I=}#AP zv;*h9XoG$)-_s{)yA|?@oRtlc_nPJl56=yC^=nmyJe(+Bt*fbveHwQD4WDjLh;t54 z5VHXV1to>MNL(A<6g#SiH6zNSu$f8F*Q+|kd2KQ0Iw@RNUE4>+-22_TVz|{HV?uKL zyaxbhOy7ClAz~MD##iQs4H_0>#wQ2J`L*>mxfZH-2q*@L(*j?Bre)Z@_mN zHpTu}GSB_Iz+q^us9AWVQg_)bzM&^21!Im9UKdCsDwgTGJz0J6sDR(HB+yc1znpbt zrVC6rN;ewb%9!JnxKLNxGd=Issw!X2AXX#Z!(qmprp$5KK!M_}K#2?LESVNiy=M&+ z#esuUn9~A5u-+|tOn4%@35La8haEZqR zbJYom2HN7erWS|JBt*B^$(Wn7Hu!vAWu^$NzmwP}{d3ZgIQ+XB-Y0_G>8m4GeP~t_ z@Y%R~Ot|*QVxOe@wG)SQ3RW$3laSl~x9aQSK5e=Pt0kdUG()yoqTUr&6B zwL*h>#GFTa0wKQxjKqw!b?T4JLSM7$tCna|8z*1gy`({TizZ=2v7L^{hu}bT4I-$& zk6=E9k*DtjG_@~LoFS4j?Ey|p%?FPUx;r5segX=4_0qfv^++x){Xeu$diu4RQ+CeW z_toy#j_}U95D4<=#@J^$aFIsCY8Rrv?|!pR82VDNQZ_t5(=O6F0oOq9TJQbP9{18T zUucsJwoswksnbQ)$0kW z>pvb;T?mr$wmF+J(WgX@@}Dj9YT*cOqh>qq&4yyvt}=to%S$HpxA zR}e8~h&ZyS530kDsopOv8QmtK+8%W}j&@+wC?51nRDHk@GR#sM!%6H{ES-hbaX}wO z3Qkt!)W&J>hMF0hOywm9s|Hn3)Kp!}E#^BjqHwu)NF)vskp)_vIM*N;`Lk{!&C^+2 zYv(MZ`<>o(*upw!Z$oKnV@V7@k@q`gB$z1BASaQFPo%RpZ&Thg)cdmOq0CeKY=?tL z_NIRoZzjs3I22V_xOFEG2|yz976D3-dp0JG#*{Zf+sliOevi)Ass|QD)1f4T_eBq4 zf=uxJy6rX1&6(PwX1xvt7FH)gA0))wnD(wwXly^|w3!t`vf`6*&u6+US+E;Xa8XyU zZ43V%Gw!JB-kXVF5yMHInnVMi!AoP27btHHbRr+3aL};Y@<*e;P06}wDyr$;s;^J; zSxxhtpjZ9G29yP^O;nnE&1q^uviaN_I#5(Peq7bioU*#(#FQ$@7wcJPHF(inK&zs> zX8-A{zVoGK%aQQg=pySzz>wQ1|GxCI*u9N7YHw&)!M%@JPt{eYnAeuil6ftNkMY{* z{fL?AgxQhuUcQ2>CasPv#xc}3gJ|UuzY&Trf5TW&7&d0PcWw#iYtbx0A8d7wlteAw zt^2!DRa4q#EewAMJ03k?-nRblKw16n2@iUJ14kXkijNxCjETKw{n8Kd-;Z!jEV3K8 z!pX_)TXE0?r2s_TqS2#-a{#9Id-6w0f?6NqCl$bn?KlE3VSdnBI6yJHtEo){!N_VA z)ln2{fOg;CAItsI7284|FKhql*#Cc*HNXG&_e(iYWgmAjb8JgH<0?GjLD>iXbY{1} z$DA&7fd2yLWfA8lD3DDb;9eznnIXxkqj$ONeE-RB$@t?xm9!{)_PdcMf=gEcQzna4 za>N5f6m*RrEkOX8Aiiro{7-2hrPYWFqu_|sKmai${ZT~F6sSiS{#EgGDhXh(_Luyk z01SW1i{Oq?S+su8nf!jeB~5Pmv;qE6xCG) zn%Vyci3ll+1@y1Npp3Fv3_gesOP;#vL-6^p(TYYKFZs(I_$NiyD4yH6UrdxLlYZke zUR-~LXBEuL6KU$lY%#h*MuSPK17u-#iG(Sm~ zY;kxu+~S7*@M2)p>?d{zXLRQYX(9)io<)9;8jIKi!o$3&O%%3)%!v51n}b*xTKGi~ zXFM7YWOzF9$ru6(|DZOD2eI>uLR`B+x$0;EU0+Y+V4JM>TqDfgh^{Yq06n4NmH-e} zfiZ|^0mjxUu_L}L z^StlA{O4N`#Xwd&o>$D4uapx<4`p;)D5fcli1aCF($TgI5~pKkHby}=n@ z>B-xa(+KO`gw!F_8*UsBsn+DIiyq8<;8fbBI z5y(22F|%8npA?tuEVc~$BD{bJv5aP&_hT-412`LBKyqz$!0v5#POo=7eqT5#Cf?B` zFRgN9QNQzO{{}bIU(kJz-tpUxi63+22E{yP^q0QUGFCegod|0@$5_%Oi%F<3+d zq@An$2)`)qr(u_)xq-q67J)&&mVh&__}{N-!WzeZoP5zHHFrJ0di*o(jq!1<==Y`z z?s^O9o=JlOC>5a!+aW#ZCG+0EbCa?jNW8HQ)-DT(yD!1*oRl)qwC8HVrpUe2Q*EJ( zgUKmdo6G`FG7Y3ud7s;KpH)i6jdnvr5p+ryh^&)tklPM+D}s|ROyN$VFFWcMOHChP zwM!n9n7P?h<}NS#29n)-`=S zdGhSbC01O2xAtYc>Jdg{LCmVplCicaiY@46aDe6fZ3>}xce@{^kTY}C|WzL7)E+|_*o^?gAa~5S^4#LV_?f<)z$D{H*Q}iurK~)gDi6E1dV{ZofZPe`Pug@Zdgf=g!2?>HRRB zgvpwpT(8wsQ1OJL^E6!y#jgjs>J&G{bG(mcaQfk>#?(+41pe@p}4tFGoEQZhO_}Yaqt*qCeoOfYp4gj$kI@-%I!UMaofKNF= zrtA6GR;k`m{N5ma@;(Lx9iF!enw337L4?r65cTW5y_^U{XyH{V;^*)mnRIcS?-E`RtlraB<{TR~h=xi6~m13%AgLeiS z8KwwA5eYf{?4gDf6z3=?Kc3A^Tv~GCO)*JcVti|_^C0Of;{>+wvy$fl!3wVr_$Z-3 zC>MZ5UD$ner?2fPqO|{9uBR(!stzf>JB6`pOuge>)Tf6*1xnAjyV97RnoZ z21G;m{=!U61GNVx(`nHxLmzza0)(5-IR9&ry4ha%x!OS9;s4T${_$Hm*%AlxFyi1I zTpG}#M4g%{2Ar{i{`tt`KA@nl0|YVu_J`)z??&|69nb?FyeGM{9&yU=QudGgj%PQb zA({nv>8|?`_XiR zc7*^#VxNk_c-;og=h&fd@@mzl^3+c#9j<t9;E5~t%mb;^BcYx;S1t5gF zNR6dkrRh6qKjR}!FtVb*uSleY)K}%d4S#gm&i3ttPlm5;vuC9w--zsUEp z8>BjvgZlndstyhq+v^rGdWg&OEc3M~8(HR#=+SnUA(=(B)n635#^rD|eDwO(G2)6$ zfa;B(ge<(~i`|Q(-D7#ZY0xUmVWxa$rW}YAPhYpFY0VqZwtc%235jqi2Om8cgNv0q zXL4rsz%b>?Wjt{lp$+s>Mb>+tkO`xAMGmBosQwo{K_7xZQdD!Ij` zTo+rFpEvl0miJ8wT$iF&jpMgH7!p3)$Zr@;afYO+Yc&d#m&+;p5YVU03`q=R!Wt~s3hsikeNtEB5=yoj z0A=BFJ2zF7M9hme_F>KX-;5o}-TpGtJn(+oi0zA^=X1Y#+y&2AFcUH4c}qt8w^E{Z zExs71EDrZw2>^HBG3+bN!F%_l9C@=dk5xtPt@*rpbXWRf@f2~z zN4jUZy8l(36@@cA5Q?3J5H?>DZG*aIRX~MS~7l^+|e9Q zPSUV^Wr@H!kTtAgP&>3mfVY;++cT@E%c!+19~*M#ORLlCH^@T3O;cZ^b`$|An`~KW z^b9d+{}N(Wd>8Kw>}5`pC;c_*ysXFw?Qaq zO{DPew$quh@26(-t%S&5mk%7Xm=QY{pg+t`n_CH(hHh8TD)9Zg0++Axtt7GO>oOdMotdH7}KX$qt4T`S*N?We> z7}erpF0vM<22+}{eczy3%=xOdGX1F5THeO$qg9>pZYn_o;6{e8(qL12P_#=6J~sO2 zGdU{9#bI_)z2D|ok7CiUvcuf&4Fqpqt$!K%>>8o42aE+o??UeE2e-51RmH3<$KA+G zEppLivtJkPmlQd{0kOsDa>mfq%Z-sQ6FS*kzotf`R?@PlTWv5%}>wl#(bum*5>ZeuQFp7JJlW zhYjgsZ%-<4W*0pT3kR$>x6Yl8i-c@g^Lplb-;|`h3cE~ zzX!^Fsc;j0;i9Fwl4~KC01f} zSjL;BcFBb;JitDxsAo~)(mK1Zmu?t!dmixA-V=KN#I>{)nNHt7)MPj8=i0w}o!}04 zCKW>NV{KN9a&z%U3)*8cZFV`+Ws{0A-f~99jH)}1pKV?m{U?2jWu zd;oT0)jL8-@w;D2sV4@^;AAv^|C79DH-Ap23s-5f{(dr$EUoXW7>Tz9Z zN;vTXmO_}UJ_QBTynhcs6o@}ZR6tPqv~lQ7?*9bXEtsy`vbWMd$$in{n~{2uz(mDh z(x{zwk3A)v;1xJa29e$!qUL!qiuD=3cF5)V@0rX}CJ~g6)df=gXVi~UU-5<}Dt@BW z*eX#8r~=-wfOp6KRh3muf1o?@1@mC8?QM*rs)GNpjCNgivv5SYefQA0y?d1VPeV@{ zZ#SV)c!AN55m0B~H9Vrsg?t0|C>&{SzEIv?UVLA8R<_hF%;h>=>%AL{9|!D24w8k{ z#U_JJa(w%Do)Xl_V@eA6!BV(1zIq>n1Zm^}OQyN)&5w(Y#mwVZL*|(?Iot>28;x!> zCQ~t7pgqm7;)9)KJpV&BU1b2T_yo<^v)m|T5( z_B@3xH5;;g`(mtoHiPr;D>WUBx<67K$jf*VLC#0}D2&_*0M~N$+a^$zN>gj3m>zjj z>ChtTliKFDOEz4OT)w_QoVWsx*5tZ6%L<0vD81;(Mdb%_4jbA;1sgP!bZLH>bO@Z# zCo;rw#DaeTu|eWJ3I2u$GFjCpuy^teS*-6CP+oDMhi9zH>wW-;!9hJ7lGF{znY0P} zY*kp%zs1&$&*GQKS9#G$(j|7(29Rgy0|w==^LQY{Q#pq``8`KaLTJ89+@yN4D(g>> zMYThPMeNBV2cKWss!-)2uV$SACPON?EHG4u7!!Aa%*hlO+X<#ae19_ai$VcGmbD5* z*f$*ae^WbhLBInIQ;&W^H#SzRjy%cwD^UEC_%PJZn}E7`29P&l&;7^GQo297Gfl=5 zi^wCe{rI8y-S3Fe(GF-$*1`YkV+{~66>?zU84`dmc#8-9<756slYjiRsn8m8!sUJdRkB0u`1w$LMe^Ef8 z6y(o{Avn#S9%O*{)9Vg6`CD86*6=pa$qAn3|JLi(d2Dv|%I#-stNDhIJt=3&%$$_7 zLwkZ764AdXtR=$Rxv{%TRW21v%kx}s>lJ|7hnz; zXB=fkE+6o2SsnHNqEO=xFgG*oo6^>}n8}`Q4vw@GB?S|Gp+HiHhIl*99^0Gua%aA; zWSG-G@9yW)Zy%+Y`C@oDxv$36on9a)kq5{Z@t|8XA1B=o-&YJ_d?keUIldWA^ z(^OP!Tz?O$Zaq7Xe?Q`dL|Ah{%L-7FBh$Y-^g%v*^5YO%7Y$0h@J*HF7lpHu_J>dB zd>0zh@=M9H^YxL1E@aU*ym48>>sJ2q;q0yXxAG}c5b1vR`uyxVhDZlp-lFFel((sa ztd;I!cR%MB_;^~93S~!WMle}nZ}3?LIKx_ZeCdu{8Bcq{#}+N>?3<+Qi{bQ&OPhim z@2Os&Im*n(()Qh%=>$iRDeGFQ;&pKSkua|X!Q^%Iocb126pjJ02s8c7QAN0v;;S2P zf)>xb`eOJ|UOkpH8YLQd(?>xU%QYJQ;wk1lCe7dcsC6O+$-SBD>(d7cksm`V`0BHEJ})~oUddH2T1XCV z1T}d)-tWtrTQ$VDtZHc+ktYFU0kV}}DUzwh%se_kji9guA zKFl6M@iNImdnXnHx`I#d%Dgkxs%z(wza_D%al`F(|n%hFlc)h$cG8Ck_ZCm@iqO)=`%Nq-JZa6RMxx8Hxcl*lU* zd~>TJ*F9%1p z)8jjFLxgVjx67dHx-p`($McybHk?s0m0w`pQBkmpv{K4^R8@_g;80^kE>LfN9(-$= zGH?V%4?n{kR*V!6u`9$|!#FL^%Y?tbegIKV(7yB%D|4}mzcpCBp0y)Z_ibXYfyP<& zpUc$bY2*3bh9F>mW`p0E1X4+eNG&^9o^#FO+@dN>_I&GtV?oq~OI3WtGAZVhNS$rA zXCPtx4T3U0s{;iR6Nl)pw3!jQG%>p_nk_i##rb#WM4->SjgEHe_ir>NE(xaG$_vPS zN+n!r7QJE|M3yF+;6<>!YPgJo@N7J5H;X0v41>SOLiC85KD%qH{w7X_!CZy8Xo=T9 znE!2JKI1pnscjfR$!7#*Ka2_qKGr7BXZ1*L4a>imn1e^cAIuNvEg6vjX(I*oxp?W= zg+M>95S1bvVwV;JK7)_DjzNW;mWPK3OpDdtpUK?oiC5Y~yFSUQ3ny*AvXJLDt`ozcPfEv)IhrHb#l__MOLk@i6< zYi!o(Ph+dcSnPSXzTssPRffmcd-#EbLR7&O0_P&-31Vk@5TPkXOPmvM zS)7Q;G?H&>4b_ycQ#o;1d{v8emil9u<}1c4uPx4Zb7su0AJq_emYun2aPgtp0Rk`6 z`&cZ6utfG4F@Ni^%~P-BM6)ePDRHBxFwy7Fmg~4Io_9NzU;MJ%OhWdB+m+4X3p@Nm zv!Y}y)b7;;@Jt_!AMSm`QIFNtW={KjRlEL!ek#}cwNxnIIXVli@Lff_T#48x_)fIT z@)>9D3ln08P37yE%Q^(3j28#JOey=0JM8*0VvP4YFB{x=GKYlL;;C1~tnM|`YE$5O z(XG?%0@!xsH@u&kjhAcA7Ol7E#!w1N)AQ))7qfRo7cx8(W{CEr3|VBf(hXe2$L9R@ zbQ_E|jp=uzB)WYM*W%eN#^rAJvEB35YCiFx#$;ZKC&?dcZzbcCaDYoqZDE%tl-Y+> z7c2hW!v@0mAw|6_#AW^h^{WKN#RtJ@UYFnow%GN46Q>qbn97CkxaFHKfw-|Kr_OebD z_mvPe8t)68{ZJEnxj)6)Wmi~;aupN_q&JXr@|e25WM2$Gy{v6u=MODNcH(0X{drD- zmWtlIvrh1$;T3AC*yUaO<_y@;4bnTf$_n@rVEhcB1FYXeD!BJGYs2;qW>q`{my`2? zUnCm4mDxG)9U_a1K7v?UNSR6?E4XttDM!2&io#sZdggj{)j*f>)#lWm;WLq7GA z^E$JX0`2)&`B!jW>_nHD!z(yVzDkbc9f+k?etsj*tv8AN#e6B&fatQlwP_?@8UXhA zb20DV?zaa{lcn&CXmA)`GtO&4^!QF#nd|No6}}&?s4NAwi!?1#@$i{1vK#DHVLw64 zc)ep)oOsr`LOb#NlD#N2RdiN^cJP_+YSy>8VxQaOnvN%S*A|Y|d7U7)o92R&&re79 z^fr2F%#m;WqOj0C*{=wkCyUI$ZF1XUQAeQAa@cNuOWYN~*2elcLnp(G%5!Tp-|n`# zn?xOfxdLaGFSM$y#9zVtYd1{xP8Szi%=cI>-3-=1+gkKIP-o*6JXhh8Riz!ugNus? zMvTStwF@o;C!|cvihY=-ZL*m`+#~b1RIcuGpJ~rnmf|E8}G*4A~$u5GF! zDL_;&zsz})=k88f-lgF4RP4l6p<#TYbm^{h-!7>fprO%~+kLYQeE(q`A}OSIWMF4o zA6;XGY14$Y$5Z>2|XFO1TeXnA-PnrZOGyM<;f zF^l#j4Dzj|AtKtDiSi97>?e002klrluXG_hTDKsGTmN%;&XBLhOFo9M#!2L(WVTo~9^-)$AdSSa*aa!kMt^CDSB4PJ@!Fa%Z5 z_o=R2pdbsB|Dkv4-1ok~X zU)tWD#6L3+d7B~Yxb1TE-BU&v0RE-@JKYA8x<6Eu9*_1}#gOUoZ0Kk!7W}wEv1r9U zLoaoni)iMvgh8PJ2jzxmTA%$^qc+R`=2JX13h2^xDM2Q3$01I+^V=_P4hgEeVN7#P z4NX--pQx^sbt}D|Vd3w8@A(Y&h*+_Z#Q`kEddO!HqZPn{GUyGEIXOK+V!{DluX#L1 zH3I{F4H9kV&^(WBov1T^VUU8hOMXAuxAPrdufz7(HqIbO0zgD^q2c$G(*>>UA(F&U9F^#noVpHPc;=fhbRG$3i^wySRz_U+oh0^Rx zahTo|^nJ34QGLu$&?{6utQ#ED@Uoq=(G;$Lamh*+tqAm4hucO7>M*y*(Z@e=*$hx4 zL-~l%Hx-)b_)e=Z1Pwr_s>FkS3+qzTsb0MKL%iS@MMaX_Y%PI*?|i zAa?zKt@#^uZ3OcS!SsF!adsU7cfP*-)7@9(yGPN74sGLCMbIEz8^LG zJ>fZCqFYIp^p?!mjq$(km!=d87_pt*%QW0gZcS8{7#Plo{X9LCxf1n*r((c7(}}m&o=G!J^dzYG z6dvh}!vJFsP3(kG!z5&?QB$>za7Cy@&>klLiK@ujMB<$)bJO=^rhOYVD#YDxU?qdu zzKWX;wwU;&ODc9rOpkJ-{6uJZ#kToIP1i!-r==^p3=ER1vz65aXB??`vd%-wTN+Nx z8+I2yd&GE-18{0iavy@W)ex8-CZ^hNI+{tNdMq^6P$>W7G}EiS`CDQlDohHk`HOS~ zUkv3F``2&x!lME9cXT!05CKzt$*Q-UMa?w0&_JdKRGng071T!?-uHQq@GC36Yhv|0 zjc&!aVY9R+Y^Li#?B7%7;ngx40IlHJo7(8$0Y0a*DQCj&-e%*jtMXnQr8IG>XCFC^ z04$N92Ew9yd@Z5Zo5YTPlVZ7eGSD~fX*E(9-O7mFMni+iR781P;j3EIF6yd}p2dTW zp82nL%D>)3IE{LGGUvCYyyt_7&AY|jH22WwIm^W2j0<2=Ue%r(MMJw#^qS8LCNLI9 z86K49Vt32;v#TyeJa#o&vg7wFWias^KB8@$l0MCYMOj@+?Jmb0;R54inBFebe}wIl z2Lvpu-XEVl?e|(tJ3$?pkxK1Id2m;pLwA+q(KNevcbl2wozHvo-xtM*+G3N|0iA|- zpSrQ#OS$S+SRQCio&o%U0_n(~v%u{aef)dd*;>Poye4)l3L0y|G)s%(N+C(d@dtKfMa*f}$$EcA)&Fv~=Fo{?Jcr{SWjymrq`O?l_@ z7}R;G*7GMGmq#a?ZS3qa={{b63KW{pO~(V)(x?^abbTqS+JAuNHlLEIUQEpXS9)kA zsXfeccUmOyC))idMu$)45dA}e(4mIXZovOFsts!7wbD+r1&o|N8&Cd<7!Cwdke#}9 z0mi?Pl4Q+y*^gXk6H1&)_!|;(+%L7p4k&l-o9Ttiy!DTIG_>(OnfZ6n;{~f&lr1ud zEPx+gL7d$tGvN5wbMrSZxUOnx)x8tHmi6gn8dYre!R$>+zRWg}1+rY=7jWH1C*Z~o zdw^4IS&4vqmUR~|%ca{CI-h2I!p*{(_(bgC*zYG99ng{%xAfVOiP`_9MTXsSY%OLcr}Z+csI+|3P0U+wZn-5r>aIsg1y z)X9K!|HzaU!I->o8rK5&9DQ*lgT~<6I1ZIbub!~I8J#!y9JeH~Y;HrD9s-ov}yEM2ce)fR~PT@YO1;}gJH;lFOxv+bOu3`E6d!$#IR>C;) zCLcFPO10!WPU&5H(2jZdLCTf$5PYFsB5-aK$8q##s@!fI;y@GZRuHC0m*19<+xlDj zPJ&Z}`dOAfd)4b}!YmNRG}s0H7La57Y?{cA<0C;*o)SONW3p90hp0a(QzV;lkygWg zEPEVTTduF2w$hX!&ak;8AL*VWrz+|z&MMOK^J3GMz6ZRlv86N=C~(~TJy}`89)BA8 zi^2!NYrGYfOU_0tfd^*nt%#1N?=VW|e6{~kSP%KOT@W!4UyN7)lQ@$PT>}gQM&(if zn1zwRtH)g4$z9F6FRkv~_XgZY4o~TFqC^@u{;W>^ulE0iv1|~aWH3Y%b)O(lqzvy3 z@0Wx_$BZA#L!S}UtD||gk(sOz`yyR(qQqJMq~WBy+H zzhv|uy#bmWpSc)}l2QOL{A;`ec^UDu+VAviJL1nrnqq_hgx>pezz_QMyUXH#j$xrJ z`~6k_@BUP1cOnjG8i5ESrSum?{*M{c$63L^2M2llqIfE1444>fe7sx@WVJD)#6%Pu zVwM#sbc{QRd=VKXivkra5nL+il^2*KkQfB<{!fqr1@Jq7-E{yuo-3KPrS}Hq`F)<87?6 zdaoE;^B(y7oxb(&`k$5sg*yZhwu%3VyI51~A8}gd|JZzH+~r_woy=q$5jYNI1$D%~ z%9O;{a8)m9qqlkaTcsEnG~Zi14N|(jus+aI^;tU3B~;|QXYN7-)sq7{6_~55)0N03--^5Mz^r15BHUUD-|JufjqYdQ8L7dChC>v3YRF1IL=7!5p0!EaY@tD!>Wlk&p(68Qd^z)WxHE%@+3|jUK zo(~en%WF%8znK+(2^e}YI`{rsus(+-dsAe?^=n+^F}8l347YM_U60Jb#OmfNd?=!* zv0=NlQT!$I`Z9AnJsg5xUO9nN z<5V=r^Ir;6ZY(X2W-dtG^XBzUIZzX%seHzLh(>@AK=)oD8dQ&?v8wS-9=2f0emLe9w~X|JGm1yEO#3>tBLDUj>z&M9e@nQj&~ zasJVz=Ds!!M(@WR(i{@Sd)1z1QK(2iaV|D5@D|aA6w<1R-j8AjSS=l}i(liZoY+N= zjH&?b^Hh~7F_@cpCPpn~3nxw-P_n7hId{_jZ0AgS2cDWBHi{m-?8Dm&t)(O27chmP zViLPN)3)s`?>b$I*i_8jyp@$^^KF0d$5f6E-KCAMDJpk}OgFME68U;Ee2~X;;w>Cu8qDAwd%zNL#R8JuVJMmmj3K8LjBS}(vS)ia`FG-;k=N}@_s=S#BE)iouUdW$53E17j zR%k-$p$afh>7e#OYc4esWSM}69$-pH;h#)Ph5(t)HML39Zag{e!D)SaN&7~+<`ZCM zV7yzQrWZccf>1jN2e6Ve70oqX3i=+Gf3o?UaIZF2#K=A}b#^e4R}%pw6pB26fa|{m z=v{eqi)Osk@PP6Xd&!v8&o$$uxbETfj5GZ{+nwB8fd9OhW+%63m}V@mQOtc0PU&G+ zUZE!)7oOTC045nGelJEm8muUlI4xZmw;NczwR}Cw=X^qEtrkP?#ATfirkUkmsJzyF zKVEE9yu8={Tt9g;*X9?+iy0cxmdhL96&R(DCweq&1)CarJ!M&|J_Tc|QJC_rd-36q zfrm*oP3JVO2ANa1-=tuk(XWRdYjJ=H1*sxC*K7Y{51_D|8+$bSi(*mc8DcLDV99XY zSNQ!AV^zN>njO~yf?Sz)<4F^$zdt(R=*<8Am30uxM5kzuhGzlJ<3+l!EE+{2AKs>Y zp)q!HVoh-6R4d{nX$v&%N==T+r**HzXBF>=6jzj4Xji`&i`VZ{k_Gr=^4-uQZeZa3 zVp}rh@F!zz(=W4L5C7SeY2%*{{ZINd{paD?S!53)f}0y}ypmxKEceX}#%k4HA3s-N zOI{84D^=I^oe$dcoKsdTk%+LOCrV(4yBP2bJwKpF&z{eBWI3qF)M)ubULN6kqK9h} z2TDHrZREdD;=>*#VU{m%WirjIu$tM|xF{x1ijAv_U+L!oA16m3KaGZ@E!E)kdzUXk z?Ey=#p&9RGiajI}qPGW~`Re%S1;D3~=FVH>3&uOJNm5P+LG_(8bBj!!?gV@;E&fzL z{Zbb)@nGWur$@1ay<%{X2C^R+vUC}b!YOU2;X8fHzWc#q#UPHW22Knq?5+ylg%x9VT-w*H=8B&1rXO?bNhHGQjk+~*IKEd5RGjd-#JqmindBQk~ z<_%gh8pIc#37u1Jp-zoqP;;_MOR=QK#&<7=X4RBgfeKQXW+29BUnH*Ru|=ermN2@C zuxUHT@#JQ#d&YUos{#G4JRO~a9Llo%dxuFLfVrhr_LF}@qE>vtg7`xnK?ty_Z?79JvfCv&#s|WwX{sl z_KB}#L8r&50Ml0H%#Xru)O<}Bn2GO89v1l;VtopWc&+7BtcBigtUZc)`W7g-`?}E6 zDEx@=w9+wNPu&><_gY;f4{$T#3gd~cPk;>G&;7Fj6)yh|d+#0BWV*Er2SHJaNUstV zP?V-rsZo(G0@4J8sDLy9X#x_6qVy&xq9C9ky+ozg&_RkwhfqV4PC^Zk#B;mfnb|YW z?3w+(XMgAH-*@&O{8GqsKka_*wbr$+b*-bP)Iit4iH}iNMHLcNJPz<8G{ukJywru2&}Yw>jl>ys63smmbu90C)~T)mUvrZ znWCi6I*>ee(8x@7T|zUr!tm8$c3WMBzH*`UsV%MdJ$}51%e`b~LUMimRXhPlN>B61 zx$fn^Zq_4JaXGFI5wAt0|!#g`h6%)g*M* z_Z#g-G`elm*LE2qx%N{n>sL|cx7qKY|9 zcAJMC>(VU_Tur?=lbUigrb3fwTS%y9Z*b5Ft(NRwU9IHCcCsTb;qJ#y+O_9d`@9<} zj=p7=X{K==^F_|Qc}v6kS_P%V0UoX)QrgBcN>8Ov*M`tgZ-USNm zy>ftDUmQI@(9)wJR4dZ0;lfGNHXB_3RFmlf44#Slj0{hP5ZNb07_e~xKuh1MBwWEW zr4|J*{@^E8r1-+KN$rKlYsov;uHqS9oV^F3d5f5Z53SaqCUr2-I>xcZr*mWbKYZv# z$T;v;WC@!pF3-N)79TOAa7iR1gifpqvrG%pv>&8i*z_(5P~so-LN$+_$I%zPet*M@ z*WsYet0B#+&dY4eniMTGxh!ANMShow#&}0`11!Ko5Wf}e;7(S=={$1Rwz-BE0acOC zg#kTM+*Mri!`9ux$JUKZtobE`gwM4J2hfE#JX(rx4y-iC>o+8`IU;28hK3eo;>RDY z-uYOGPQFq+aNC?l_D+xK!oYS{NYf2(`=O!0YYCZ@n@*uSkGHf26pm*T#jCrC$FX}T znyABzGP{Q4S1wtfa?*-O6{lZ`tnz9g29<8=+v%1GeK>fcI{EMUylMn~ygp$y47Q)B z0-geGfS!NI_b}I7cO0uD!=rO5zs?w4^E}wPdDLM}?g!Go0smyrrI_*pm?R84$}95? zlJXjcV{<0MZhUWmcTKZp!%r`ut(PMvF583W{lqdS2^G^O>f#_dbx4l;3MUs++zd5k8eBZ$JuF zFw7X4KMRXe=*fcD-pN>6V-QK_r~U@H;Z|}KW=cBv=M~rK*B4%wl=;`yZGFHyRRN5A z7oQ&Wc0sNZ&2)L*(ou35I%Lh=png67%GdmJa48}uDXLl=aoxw!LP!Fe#~50^z>ZB7 zu2R0p&ZO>>wWABFwT(9pUO472PA_7~)19p?p>gx(Xr}@JKH;d09e*OCa1Q8<=;96f zNzPJi#&K_U3?7vpBOh6sb{|m{%Iil?^&!WhE&WA*Z}S)PJRvhd?qnV}PX~*hMOM?# z0pO3Xf6rl=r@7q!J4`@#XKw!OdjM=TII*_d!|*$&u*3lO&0pTS-L7Vqt6<6L@H>YP z`{E~s5W}CULo>@aW_ZPPEL&X1&t7V#=gDN)pBimgqri053#FM-sxRBwf(rZwDL@lh z;wH8N(usUHwT37f?TNe-H$}vpQle3oADNtOFBRoJv0~b{;`?UV1VVXKrcq~zdFv$( zxy%io!&6(D_`vA&QNrZ-(r#X05$6!2&=E1twG89^lT7M~1zfot_u?f-%SvxR ze1oo#!eO?n;ZQ~*_mmh0z(t3nbLWyM6P-3l4D~qm7i*uxbLl>6u+aPK$uQ+>`e*B& zliE#G;l(I_wV9Ryh|@&eR<#`dR3!O?U!UBkULdSEYB9OSikp2aKCJ8@J7#%533Ku` zXK281k)AQt^rKDVB^ey^Wb)Dg4kYHV#tjk1+WjKJn_6LsypBpHBWa0EoT;&Q0!1Qb zSDw+_u(us2^ca_ zrd!L^duii;5%d(ZJ{f4_9;tFac=_HzfvXaa=Uh5u4IQsDDJcNV6Z$3z*fJ}`bspq@-jj#?@VBf-?G{D+OXvP=dqf2nh?Kz|h1tlg%5IWt8QE}i3K zeeA%Kq$$O#p`o&GpO=QJxN$q)J#zp3SL!e8-Kp%wcY4P{rlcpBtVX17ddQdGytc1{ zmAiw^g>%~D`oodyPgxjlY&0^qvAlWt`usJ6CD$91_f)_jEYn9o-)Oh*%j& z<@|ZHY_pSN^Nl&C2#x8tI&10qlH+d8YDK!>zDCwZD2MqJ+jYRT>&zx4cG0ojsdf`Q=;5!NfDd;9G8Anz{_5Bj7 z=eMH?U7P0`5Oixl5WeB3f9yNDo4uFhC<0*HT)5vpV$zS~pqgLvw)W~&a zd&^^$xCVO(swH3rDCE~@Vl$y@nQufEdOL#E=a<23yx)I=I3RC%gK*h)2Wq#cw7HH* z99HNk`#d^g(;sEWi*4Ow_~QfN?N+Rh-V*FGM*p${QlbxNViq+EYx=%r%N~nu&iK#( zdcB2gNwg(@1~xWHZ5=wLRv2~fUv>)6Uv{t+y}}dqK{d4MSBLS-HS$s4KCCvFs$%i0 z!}$9(QhetV#P^S`_|GS5fbvj0rQLh8YxC%({(kbJ^D}3W1`WxC!R#f~n;m73C@G)S z%oYQ?_|x_7Rb$jHe*PlKx;4C8yK&(k+)sF6liODek_)7NqO#Nd2TDSA7GQ5N!gz=D`)mnQLe9ns2*;6l+;_`nTDIFrXj#A5Dog zaMuz4oy&49{h3$uEQL}AQ9`5d`;7{3t+2Be>2X2593Dl!Sk3u8of1cWEMSxa1GLv)cjudX z`yoOfwq*u#FwEHGJztQ+`LsAkv-1t|yYFVDe@V6prab(k_poo@+wuK5>_M5EOD|uS z#NI7cW!8YX8f9ah>oBIa6|uyIZ+7$9vN~706=JB|Hgo(;!Y5269nE-pK{j0(?dIe| zg(lz(MAcRqH=iY5?IqHum=nrJQ)3h@%#}u0W7OaCxyWAH`vPGtD7#Q|q9Q`5z8dD_=S9+`03KKM|$`-I+tbOzjLJKMygNq`ZFHQLGG1Vq5_j-ku?nV2_^8dW@T zG82tJ%qE49=sRJ4c&hP>Tx)z`yhjCG_`{TyziYyF{(*td*ujAeZ{Xv1st_A_5wP_x zFvJfS*>xRCZb`6cJ%_p=<^IEBoqjE z(hzwG9=R5Tpc-E4E(Muv`(t5YdGc3FisE$}m~!zaK3r2(|9t2xCrW)CkVBKgc0v^h z$ge5n+hK3YM5MX|R6`99M;^51JNCGj@yhRi@+#fS=R%je5R!Hd<5(0JVYd%cZ|zK@ z;=o#--xzZI0;45ujqX`$jz;gVfl3s_!#HhHe$K>d5avLTkEM&qXyuliby4B_PDw{V z({JYbSfJVtdRit{oktn{erL0C(3aM26JnMS3K zn7**{l)3V&NOFRdnJR%2CsAMClru?Bja_+^v0%F7ri^qs@XC>=L=VI~`H@D~*FK3N zy)uHx#~k{I|8?F`|8;Xy=0xvV>?3I5O0YL%0Dppxc>EpVn*0{SJ;@3VVd5+&m|OzJ z_eT=T=D*yoqIr5m^i*ybU;5G4Vac>qM=D)q=oIb4P;FWvu#H4`s$8erowH#Av4`Nv;VzX^c zd5imXa_9TEm(yEXyPYzhW8VdZcob+=f)4cS$pHq-%7m0^ zaXCuw*%E%WDpK-X%82wxYxa}upcWc+9;0Ozis{|t8u+7KK*Dq|ZLVKs7#p8w%dxak zz?kR8m|;$M+fiAk%3EG;%|6Vk0fA_&+536A4+oPG3nX!em0jL!aBdN z-}1Spn=V1c*A~2adB>PCbTd?tlDb}r4cF)5+-$qu_$CC}Ku1o(Mtl-wslPI0OL@%*NyRX$kC6l4{TuE^*STROZ+kWZQgh5fs zo(J2f%dQU2upikuWqT_T^@*D2CIQ_94^ZMDJi7aMs?nH6v<#iit z4~^-IQKLLIkIHV!2nJ)h9 zIMan2tS&)UCb&p+DH+4^#Y+0?d>S}`{6`?MR?7?;?sF(HKDkzhi z%8wGp+|}(6j+TC%cQiLipWpr>)gjibBzl4;{v?dTOH3Qb8-Tgn zivnjUdd0kk1L(EX5!(mj!9;G} zw0DhItxnn@wf(VEq;%_&XvV~FQKl8EolB~ZUT>V0O-QUS_r9ADyErrLYma!|Gik zl3^&(W}TAj$5o<5q&nuas*L-+6Dh zevvMGYb$$l(uIwK^Q^117v^{=jJeyp8tbJfi~W%__nOa zCy^@`-xgI^$Dg;pGssgpxDR)h#8p~WQW)Inc}AJ(DQ(4m-Rl#sUeiyhtF(0%>0}vN z;0F;W9N>?EJwEYeqw4l}69cZt95~w|3PK*~38R{mqw4JJ?VM6(UE-yo>Pf0kHJ3O7 zA>`8QIRdfe=g+ip?PH)ivfnf%CCyl*nPU*h0kypO*OASB6!n20BsY-d@yQWrtT-sq zuQ06uI%A~7X;QXPT-&-*587#}X*nnP4XPq%J#Gu~4f1N8j79Ewz&R89U%Mfy8J#*Y zqn?F^`M$*}s!X2>I9pE_E#>a!bc{96^|9!|?;tcRR#y7!x*ZmWjA(tV>;$4evoanq zd71Q(BE|uiK;}Y&ih@AEj|%9U)gT3cRG|$i8F(|6Hg`tRW6i5uz}r4+uyDy(PzQ4SU@5($Asc&rh1I>9(1qikM++zFv z>LB}dV3MBxBXjdTtY-KO#|V+HPGO@+waAUHB7PCZU&WSLzd=s9;F`%3=v}uLXw{ra zFEi3Mlq|Ia^=?G3$RbHT$d>^B+-j~(PC(*xSHt1BD1v4^_HcyK@amDtg>MkM8Q~P? zXoif0Gi3FPSWxBf??t=~?&#w>W8lhZv!Ym&ZUH|MdDI^%b%nC>m0JVr1ZIe zl}gq3PLY2ROQk2lPqN45ckK?G=8qDJdpaFIF9jv6Kf{r4mxW>*HAeYpP`bd0c-{h@ z#J_8T{`9`Y&UI_epP@zPM0xxqAheALC&tUX1NT3_0BrQf)WLrF@n~L5ms%fmz&SY>R5IXjNj_88G)wgTO&oRGU%jKR%-PJX}r=C**D$ z1e2`v5d&Sk3-b#1d@RdUXE&vo8ddH}scZ_(zfc{e`xvfHssho4iuZcLvkJLXZlUig zC1$dBCMqP2m2sr}MW9E?g`a7T)@fb?`6TxmGz z0qpO;0)5RD6V7GZ9*dd0$YZ(SyWauOMQ1e*ZBas}Orw=~go*_)Lh84YF=r%`bwdRL zr6S}+G*nneqDzf`>&)(|{)Ta9^t}4SKZCzdD(FqMG0@mQu!!?aTNqf)u5Ngy)8piP zD|p4QeXS<)eN=+1>j4Ty3KR`t)NV?CJRdmK0Ua zhA1&e)~BdU?s}dKmjoWXWT)7~(FWangL>c#XuIA5YgRksh1OHd6i8+68&Ow12wt zK(|!n!sumdkO=K((q!F3p{KXBI)~b@^!&tij1LJVx)1Sa|XIJFQ#MM_(CFu}4;#foP%Dj|O*YaCx(nXCY=D54S(3 zu=PUE%%sytGLO!+u1Edaz7I|OS3Znf?K_6YbcT|pRVG(yiQMn|B?S@Mne*{UACP&~ zargR>)*nj!#{`!P*AYA&$4iy@q&{7*OFF#STtryJZU^}B+v07Lgp0fWI-(c*%FX}cln3-7^01U5gKC#3UvD2#X`8_^Q!RJl+`{{W zg7OJ^4X6E6!p*$53)9SKqu26JiburOrh6d+t7Q=egt#1ABt20aqZU+og}nhjEEn5Y zhzWSA#M7&P<(8#W2^$d3wvADFy83eG(3H+!>wdDh(pR3KW3s5t_C;p#ofJtmpOFhsEk!i zvVe22jKIgQ9p0LOo^d`e+H73-#|wil3rS3NhVz~yl;LS>EJVwrbh`=x9OtFe$Ym7Z zVUIzq`etg`WL^&od!DfTNW?G$InvN|<%*@7>{y!5aXiB$75s=8=)yC3lv%kPPaO#w zB}}d?wED!J!`SLt_`aQtoMh&o&eUH|c}jg%W80b8?=$)k(R`8{#pGb>F`k%t12pCx z9=7+~x^HZJKY)&%o$bYXGgZ&27Z2rAnOHBj7&enFba_xPXb@tn z0LyY<$kuo>#%&#s>F%Dl=pSwBQHW_-WR`n#TU{yxpuv-3jZq=v%m~IwN9c|B-H3B2 z0<#AGXn(YHqGHcCNJcB_jGDMbLyoj~*6ENs)BzcVfno<}0lLoDewKT_uq{U`)5${! zCD(SX`eW>{@k!>`q!{-V1dP&osTlF<|pUP6hCHIid>JCn`KX_V{&X z!yEQLcRj>clx#J%EIrp+aU%HvMEX(5F_ayxt$+KD4R&Ced+##wV$TUYI*7~ds31gyPYxD>v-$@R2#=^ z6%Xd2i@El?gO^Im_AV9`Y6bWYy%W~3)#ErP0GP-91Zr&56F;t6za-Ak`LBKa8cr*# ztNBGjZGj{SFuUmt12Ja8)9p z`U+|_ou_}47hj9}p$IA)RW{rGJ)&*+@}n~?^xNn%)o`b64}xq5NtAnNQaLKP6FKb` zha7>Ejzc}4B3qt;V6_y!YX(!zObOj{!|p?$Mt(g7yhd`s0?8EB3g7wk4FWcP`=H`I z%$X=W)99OQ;FkwNs5%ee{rxGU82TDrXiQ9Ou7~ac?!^3OQxX^I_d#0&u4HcoMs!$H zS`R~xxPF7|f=Kl&2o#p19xGiVm7u2wh(Imz-YV(*u-@JgP|kxQh><5@yDnv^Tc8>7 zGdMnjRFB@6a#UMV{suXTo?{{w)@z(E)Q z>Z9Xy-ynkzz%95KlVg}1fn1}F1fPWQAAptEsN*2a2EA%oy`B(4hj2mtlyUJRt-}ZiYUcL6VZ_vrg zwu$j3v3*2u0`eBOiJtOagL~Wp2#DaJQ2dW_mfiGlUFZGvV)pB0Yx@`;An&Y?eQjLj8&oWt?q5Q7H z7A1U7Vk4|M%#WnHZ3H2nr?Oa%H-3f?GvEAA}qp=&EO3rs4ky_YmN zMW=!+8+e%NZ%rmjjUY1S496QBxOKuz;dMrZ(I_cxfL)lGJym-iJvf3HmbCH^Zkjvt z0Fu#P#f26m^AH@cHqBz8Q2Gr)$wXsyTz?`K%0ArruDZZOf;QpkgSs&vZ?U(fHswVo zC6Zpxn`$j!a~qxB>ra`k@6omkEO3aYDs~rw*olD@k!im>UJfvFSG!?xi(; zQeNM$PcHeS9#UJY_|i4`{d40PgYN>3f*7y+!}Z%-`9Z*Zs1Iz)4-)B;gnEq*x$oR{ ze2xKS2riw~pIz6RSw3(?+i<@`Jnpf2+#_JG&L82$Cc`D{Qvv0jRSV(FR!NemV?jc-y2T< zu{QO;V*=#IrS5;{^Iug$Yr+}-iAv~e<-HrjoVWeAR)oAyosY1J)_eVxLs$LOGfZX9 z6hq@DB?emwuk>}$HYQlo=RAMX%A!t!c7&t<5mrtyl%rMj^eM(%&6xz61CwvIK{EUi zf_XA$kzT)%m$#=VtV5&(qvLHy-%#A~bSPxnNYGPI_L?kY3nfIT#pN_7A0cXC6&>pR zPWQN1FwnMdqle1VqolJO-TcmqtXLhfXA>zOo;`P3`0a2z-vd?Swjhzd&n0dx%V^ux zBVIO5up^sD7J^oT3@>Zfv92Q8jO$BLM82&OuDhP>CuX6AA@95f3)+k4Wp#5e^4U7O z3{=YzlXJXe*WBPp)RSRGI(StEwTRkm4T&V@`E6ZK&0CdKDs6Gn}mox2|_`` zQ^LRn95mcfK?aM0+P&!K0+QO#2L>3W(%u(D@PWv-qsH^cwn#N+<5KAf6=pF6)fr4B9D zgZAAc2R6wW#+_rP2z2Q_*wcesM6}pdq0E%Bd@I+uYAT#+YR2M&t8cN(a`PO|m zW4cd;k}riY`n(egNob2;7CnT?mZJcqgaVtT4Fw5+Zr=p9uyaWawhX^bZY^3<>MC(g zENN?gRWdWa{h`UlVn{{lj{NKD=!vNP1V6Jw8%HU1daSzhtUeStI9z}0;Gkj7A2Y@j zN^^OYOX37p>r9OJeuLg>9->meJ4k-Umjt@Eb+DTxY2_@QzKiv7$O%bqkFiS;Dw_7( z85(30S!YgiC`btl#+#t;tPZVA)q{eWQgBG0+|A`Y%Zdve&-A?s^}ZCsfBD>m{1e^f zKL3Y95aaxLj8kIjpxL~sO0JQ#QFN|u?LJ{W6)w6nCj@D-sUZ+ZPNDAbQGg}C0}rks zB)_|~=FqXj=@oKIbso}by}*nt{bM@O4@7s5*iXRwys!=3V(LR~R6l?${;tNn>bt(` zZ!6ISDVzO{B0nkNno0gk=#5MIMBvpO7dwO;d{F-la>?H2Px^$JKO|80=;)*V>~iF~npPWyn}9#&6|c5hOSF}lv1?bS&>C&Tbm%7Pi61NeHSY<0R6{4! zL^*XK>1=$*t?r4}H%OsvI!~HuI>aAF$rrS&d3&qu*Ogcvaer;;2+PyZ9$7g?NW=Ai zZR$oymEeuy#KKNoT78!{ErQ6-=9z^I*U~66h6l*bcQ~4Qq3b+x^X$^59f=L5d*XJT zM;q>zghyBAinN@69z5lFTq3|okwOa3P|xs)d_q}-Nk)tIRETR^ll;KH%3<@6XCjq-X{zWOByZo+W)#);^HDHP_gZfpP&&~q zf`DR=+KZf_w}Lm^%{ScG6Z+V6yYB3yLwb-c|H>8LrO?GqXcU}E(pN}rzyl7QlYZbC zY*3u&BAs?O+C0-S?d_d=M-5AFpVzNFHqbP7jGzGu5g$Zm;3WzAMqO-T!G|W*H?(|4 z&jIX_AxNYURd{L4z2Cv(Xq`mxOswl$Ty5*QWOITI-eREcihrP+5?i_}Jneg0jc86KCa(iz5wT`oiLMRW zPcetCaqrEEyt7>~={{u`{XF)5=mqYKma)K!2rc7ocSq5w8-1%cKlJ3CkkEEh2xDQq zoGLJ;dff2Bbj-c|2pcT)Nwsuk!GIV-2itjOQJ-M)#>?7h!OYIuQL}d;`EKzYjT@E{ zH748M&ZW0PjE0B3wy~)2O;F!DP-nsNSjQZ|=kvI}&DmImxvb2iygqg-cayGNv1&PS zGa#YOZr`f>A*qBXPO;7RO~0V+kaS+nCiokEROqhCizx)xsruq9eNE%%)GJz+my>r{02d^+o8kgGxr?t%Gh}h)z&U& zI%tP=@afuhPW`}}44*NmM`S_7rQS-<$ww1Dorh1Na}i3V1;xFh0D~&hI`BAG#lu(9 zAG6@q(-xq$U)<>?MECkKCnYwnad=s1Ql}n$(3UIz5tbfVKPFfd*lAJLBYG?BdLKuE zTUw``aLFaiofjr2wNh9QU3hq;RdNf!9kxOR3(}+%^1epws7zxV>bTW?y*p60|HxH#*_Mr6ZpmIOFER$5}wXUIBF#&~goqIZg3P4^bAE~~E|ql-bW zjCVY$k74YKJLUS`WXq*!n6_XM$wo9Gm`@0e!nE<|u#LohtA?C~q2yg!n?$z~SK-LC zIDWcF@e2zVvYh=+BP4qeHV(M2x?r($oXqK?KO8GCE#!0Trpf&pGw%@!q2^;u5|81c z1n#~40{H*9VE=FrIo`Vqf^?QXG$AphAO^s32h_VWaV|GBJo`- zsbgdrT?1;3hY)51Z}6falSkdufMlfIWP$@pUbp9V_axhzS=*tiNY6-umObtXElsJ{ zrGQ&;x@TNg*lp$jx^rVD;1{p{@913xfYGMZdYc(>60Lr}5hy~W;pNGfeYMD-Dt&Gm zmE*9Gv*KM?4A>1HB!9q^KG0EIi{OiGOJ@BmMY z{ToDGZFCyC#@~)!VJE-n?8+8QsU9I*_%&RIHp*FxBfBEW$T^GrC5BXoZem@#sNjwY!&GaXrHjCJ0nGXWg(%SfUj6cii+|`x5&mMCxm*T;H%mps!?5=>V3!anecD zJBQh?phhKa3cd%HsCg+nt;rMV&Bow7pr;AnAZNyMxqntr^zt6Z8)qzhu4JzvT?!RM z@htsr&HtnNmA8O)mI>buT9fk2w1+LQld!~y`(XU0sH{l737h9cAY>B_z4i@K4BM3z zTEOgR{U93CXFRfQcNaiXw{3sMrG9>8{cS?1EBm)br@;ojCfkNy5hFj1s%U{tYrF#1 zha{4m3e1LY8SWAMIePsWAS!{db<;1;ct(r}`ow~@=1Z0NAhd+c<~mv3nGG|_{G(*c zz8{k>zt0B!f!X;J3g2nJ;c;M5B!NZoB)@jdBn2Zuwg}iq7bxlcNY|b-5+sXy$k_2+ zm*Ui|RxiRHtKE6&5S~vOuNn`YmUq)ZyA6Z4}@V}DLE4RIC`LB}E148TB zYT7+fC;P?ru*kant_v*a0?F~6%`h?vMbIO?N(U6qT=@3#fByGxdR+`Nry}_o8{RTL z*v~)sjJlc6Hj4%yB(b4nk*P=stM^-U!{d9J4dVKH#kW-&ty7>v~# zyHE;0pjhzD)&%6xtTB5wF0Uu!BaMz*A#5DP0fTWNTxLaZo6JpFNeb6r){#h!lrZP` zg@nN~E61#(E-300XsQ|B z-#k;0;U1(U+jQ;)fcB+*eMk86msK<@7Tp}kP}zh z026%vE{W@V(!28s4KeK-xY})@SA-_^XLgNbJShsxjc8h?h*P-5@7xjPi z3Id2O_?jn_4!Hu{?hILn4STdK(iXKN9~B7O-v15K^SWqP3eH?NzFG?WM^ww+XW-tr zw1L{4VPYLHSj9?oJ6eC9W{(>7A!{R>lD7|o;UbEl9~g-7fHnOMvI0D!4DR@qZ;+SH zdp;Yo$eC}DwoRoxaGFmRezb!MmOn^f8ToByxL;76PS+F5%*3iR2) z7gk`3e)nDbciRW~vp?i_)zTkt-v8wD|4UE!h=*wSn~A5Y-cxI}B!|O)gb3@`f&SOb zI{UqhZ{VWBJhF(E)_I+?>Lm*t-gl&~g`2rYZQp;)A6X|Ap&_6p(}vNhkD%7Z^#}M& z3?9dA6}f;8H9Z5mfmAPS^Bgx7HP5H&oiqrZiZD7`lZ|!FJg zL|jpP?l}vxulwU`<>hLww6kiwRPAIN35sH({P3mZopHi4e~Da~KJ2_lR3w@+Z*>E8 z7!@KJ!E0vRFM{orvJ-J9NL7pqnOF2sG0Zl#C7-~YdLi!^!}ePINKPS%8Lu@-9fc6W zv#aAo1C>!xw~I@ zZ|0jfk(Xac>c{FbC{m+Nt-oWu{MJ9^;ZP^#>zJ!ZCi}$e-ynj|;chdhl?1$2wMnmU z;TxN((#Gw@kgU1o%L$FX){g0I*35&hZYlDE#iRftl?_NO-~v=_hS;B@$+wdHxjd1BOq%g1>oWXmH{o z3mwHU>!t49Zij?KxuK)HH7TWMD_w{SoR{PU)gZk0nG13EyxwIC_)@nbU{fNh%P?CV zMpMGVtQj(p_GHA?{Bc)4u8<(<=<(uB(K-wTC!vXxvp;m z&G5c!iE~xV`eQ+2Y7E&hhTA7+#+Ir*XYXCYwspa4CJtYX$z-N^C3@U!>SW%1)i9mz zH$EYw1{K0C;V~?(I`1=yij(HlP15Y_<^1UjW0;kNCb&4~2_YA2iHqVav4+(qj1SLa z>gnEPQN7-i-yaoQeVS<9w*h@(L5W|9o78`YvEPaw8%>B>S~PcE6Z?4RVPR2aM{a@B z@wAeN$7jz6tcUODgpJ=x=SMHKHrIgdhs6ocXOF4Z+*&_y_wgr!+f-1a!*-V> zOH~+{6;BpseP!w~?QHf>uSn);Uammjl;AYk_$Yb{2*c~O$yq`*r*t0OJ&Eu2Q>?D8s4Ocij={9{8$~U>xa6DURu{%q7Nf`I-z^`@?SJ<$ zHbBp`gEC}IX8Cx|g7j`iV+VsSKKz9=JB&U*{r#622anKQH^-c?XEfzIxwv;OpN@xo zJTM9fS$ZbPOk`n%Il*Hxq>|EOvd#LvPX*^GJnPbZ(|aEy*ZSxChY=qXbAhZ{O~|a8 zyhd<=dduc^QQ}Hsme7qs9oFu8{`V3Mtyun$RxM7U*W%@|)(Zz~rwvOkM{BCTeZEO$ zrJJ3Wda>0N${;1;a2>}GxarJv!^C`{q}=1(fZKfMtcjLFw2;D!&d+n^Ay%@m(>zH< zgIy|CLjXFv_AgW|{}G6Tzec~OCUz!o1A{%B{Wr?ouN(@5s?RqF-|GtUB#1l@?o~b} zUw#$$-L>c*+LZz>!Eo|H)*Y>H5LpH({a%gMh;mIr`mSu!r4- zen$;~b20)@fvYl7U_P83-`bvY1@6N)NZf+2*&q5oUd_K%IL{?I{8j=zCq1x9>R+j< z`9EV@)Nc6iIBq9{6wj~w<5NhW>*y;qRHo?s$oVZ&XY}hCuRoUrbv(KD4RWmvovc^Ui$F=6`O`uLG*QP6H$xxhWN2r&o|5e9 z|Cs>+qAe5=j%v1z-w5%IN}oUbtuZX zy42)d@R+bed8>oeIHl&qg)adZ=62G)l*)0ZWy_ps=*wN>8nIwD%*iZhXd#kmL2muI z_9Zj7lpA*CqjjSp{j;`CVz**egejkwt|juhak=J{%vISm$8nviY3rmR1l5;EK0}!j z9G9JLzwcg!Uo9?UQ!%+!c8K5aien8@>N!Q?G=1{|CU6!rwl-#_Rrf`i2NAS|>&+ow*?!b_;`L2@8MKtTx_r}xFG{6qYrsgG5ej2qBv zZ?g+rcZ|O%+2VwV$v=ApT?CZZwHO{NTu3^Pe-V;nF-Y*K-!-g`iK{l>+$+wB+j)^E*iX z5~svl)MI`!&LVQGW@JIx(2yB3Y^UYyoBpcg6-Mi8!#?cOyVf#hPeM45UEX)^+LZh6 z`gl#36&*ev`;YRmC})O#^3)^;QyoMn+zg$S`nyYjkz@_NWzjTJr=cQyFT@`EUdR#EEho6!@HiU!y81YQeez|l zO}9IWYBWEYA#~GM%_y{a?_5)f4N`Hb91-2@<{I5z>>%eIePiePopI>Pu16MloXtd= zmqVkBg)rVQc4l-lDLK_--ZQ?a!PEFdS~bvjeX(X0BboU6ZM&PiK(GePA2C{9dFiiwk!zA{KnGyI+{9GF`Rkb zZJMmD2Nws8$w4>AK$1S0%z#V%%`a`1tn8KH5=q;Nru1)Z+ib z)&2Lp=l|4E!F~@-o>USyvA;+DGIpS(yk8V0%1>?|aucEyHmQC}AH?GbJG+f4_^qdD zT#w6>#+QOzHv!GJdcN3U;cprbum19BFdp&YgiaRt_(OSQ4lN~#2CjxX|Cfil_-^6*idavv)iX_so|yZ zzGc$tmzl2?7&1I-SNTupY~zxZ$M-4wXFp=`;iN89>oG8HNB`Cp|FvtQ_TlNjZk+o_ zKoR}5PT$l?Tz;yr;_LY4VCPMa+h!bb-ulfj54UQd7`5xy_5AdjU^j$8*=Ru zLIR}O(7Pszz7%lSkKfz~y6`h5{|{a%zU%n?7&QG)KL0_W^|@~&=cuPfRhQIx;;`bS zLn5;mG*?2c1*iC^te9J7A1XQhkd8KwwK}y_g-emVJ{3qZya1uyse!mdoHCI0XNf{U zoWV4RObw_2jmDQy(^m6bg+|6i35GiK&P*n90;FS@GC#M)^K|Xe1$ZHN>=YTkUPu1r(_!TL+9F>- zP^v&isRu^ffF(lhlF1LCpMe$`_N5;y0Lny^futBNc{~zk9{WHyyb%hm`y2umMKaT9B?F}1 zV)v(wjO+o_YyAt^{ihM?e|KJ~WX>QgoVeBt!zm%jXQBY)c7|4~tZeHQSghU>=YAT% zBj~SI3TOq{fGy6=Z5gckoyt31KMk{pBp zSVn`^Q-9jNANs>e^!o+WZ*@o4)V!nfr(2=+zu0^4uqMBCTNDIAy7Uf85tSwgQcXmq ziHNAw08!~(1tdTu2-2&dARxUeO?pr0NbfDwB!F}hkPs#0cfa3#&Ru7fv-ev2oPE!; z&wcKHLDV_FZ_dp5zT+M582{~mC&5{KK2h zQI+yxSM57eb}Fs-r!y>pdafE({Y!tfm`KsuiM5oL{wFW`CMqF7+%&5HA13zqTflQw z01#fuZ}4mBsd1z4`*%k@Z?+Hj zF7}RFOxvtUG`=Z2LgP(Qu35P+*6B*CG<%a}4+Er~TMPF+h+BaX#{a@KYPJDd{!ZSX z6R7>w3;^mthdB5rO~vT)->({Z0}!crhJlh`yku$jdH^BKa!MKopl2yGc=`uo`FOMU z-gf&G3Y5VQIAC}HxkU26G`v*(f%^Y{>;AjJ)4z4=npA)tM&2d!cr9D?7Du?}ISZBT z4%AKZtC~oDTJfezntcR&_i=WLZt*=~xd+fUPy{^1urUgQ=|awi!jJi;(a$})h~H~Ej8 zmQrX*H0@c{$5Ac%xsofb)hBGp_RVQePSx@5z98_*Er-AK8-h!wISv#i~D2J;v z%+nLJxXxF;9trjh&~$xgN(KL_?z`S}T5)o7cjl+sY1V$(+V8A~|4JBY_W#8VZ19ho z4}t9X%*Yi4>l_Kvnea(z`#e^{(NTQx_4`N%iO~_dk=={FnMSUzcs} z6j@lg@bVv&<@rHrq+HJQ(rideo%ln4p9O@Vml=T6Xp~+{+Y6{{jsqaj)nf|Dh$0ui zyNTG~299$$P+H=>C480}22D(dJspOiME5hnw@^f?@3LF=?}HLmGEI zldT|n(8;!d2$Ebv_wEJ!a(aW*@A>%6&mB%1xZH69)qk_?G4gn|2Y0*i|v<-Hsx88rNpWh z&#S-svlV+xAhZe_)=o4oQA3lpsx{pq@JIKL75$9!Z(Zk^9rjNEZ6!TH{Ph(7U*El= ziGNTD1=6~tsr2e;N@4=sEJ#S7^apLf#1A3I-(QYBb4%J3nShoCvf}GfR^pkQ13AZ1 z+%r?o-2VKuZtPG4QL~%u`N}1BGVKkqz_!$SgI95B6X`iu=#%dG41iKmfdEAoV#2tq|PAd$9VotQ1eKyAfw=FCaiq1(Uz(zmzS5?Sk_lw4gyuUdQ{$|nZiOWsI*V|t5_WOsw z%>T)7G>`vrk^gp+WwZWo-edoCc;%M6l}ZTbZ_RHd5>@M)FJu$EROIfFC!}D)7VK7Tu_2-C;OlyYvt%wd{airW< zXFCl}2C0uMz5F0{$) z3r#E48x8FjnPQ|oz{ywOv$|BYrggqk6R;z>Yj;muYsTp|Ox3K-L*~yk!yLk}Tn+U; z$yc5zswedKcU}lqy$}}`B=OGm*ld7SMNJ4jAh)<4`M2o^z8>Ks%)UYe75AtB;e)35?@k{^bD7HwW`^+GV9oaE=5yEtLexbSziMiC-68>W1mbt(%g!X1)2 z>5VJ~-Rfr8J>RA?wnugIM|`I1=RkP0h@S|+#qcRz%YXvqU{hSR7r}#Jx3*Q|VIqS! zF>I|~@4Zff?gf@alxBSU(K<3<6ugoQrGsC=y1p^!v;k-&8JKxP9oa|nY~5d_h_4p3 zE+=0z$&vY9nkV=PNiS!lL=C(h140Nf4{x+9iBl%^;!uKsm9>CPiw*B2T%#zuOmt@+ zIC9V{3}w^qW0(T!)emaY^;EK8VpJueqDy|hgy>NPC@e7OM%0dkqjl#rt)`>p)9fh| ziqPoi?7sKYGaiPb2SIzPr*xzwK$2>N5pFvJ#Ij=|qAFcbCsABi>!tbuX}44!L5` z=W|7=K4pENMiQ-d*RAXF?L6wpa(SX3Y3}635@{dsq|A_hL<+&3igq`>dr8U!6csxs zu-~V zp*w924T)>X3wM|mduYDDP7+td=(%?);{Y3P@XDuUMvwq(;x<7p1UJGDipOL;VzD(E zEu74CzoAj$_wKuZ0@cFXpplCaTV07xG>4CIx;+)>l=fwj7F+sVdV(|n)13P`JtZ04 z>6`W-m55?ZHlv?)_$b(7$bB3coX5yR2bE(2o1;pl+uj12oqVKjk^Y4puMSu#aKz%`5`@ zkS$wJ%aP~iDgDb;e^74%)1CLK$Lm30If^1F zk62D}#f^j@zLmxI2o?}TV_N1-DU;SRX*Y10E3&jj} zLZDSJMG+|Hk-4N^5w-N5nJktT-iqxsaHOz8fTx$etDttWWS=O?R9ak3|9tUtmcUPx ziRH?AATzC+&`;^rIo6-?rjs(7R{E06G|QFIquHbv6B^{k-JfavAt{Rv{B6I}bFP=@ zOv1V2dsxi6L5hU%cSi$$M@+;Mk0RKCg<;hacbL-2LEY55K5U6b3FM^D4qvcc8yn&D!_L&z@1n(+z4qCts^pznEXn{drkxE~ zS>6>7$c05ik{;qKBFQQokj>vcA?j#rZBKp&JyzqGSnAlpAsr>qnspmbMW;x~-5D$9E zoJp9QKiU!J0j(Y07`R251u4s72~~I~pH{}9pm8H9!OU4K2rL4(=k2YS zTc$9?7r?41JXXK+VDI4yFY_f#HyOs2wws?_tTL4(w=qDosMcO7SRuL*=nCRnQV7AQ z4MEkSjLqV4Qg_H$*=0R3Zor3q`d!!j1-i6(9;&$}4lA&uvp1c;U>xSKpvUxEJQrA_ z>qyR7GTRJ@dW)h&c<=?Y>-n&HQnOF4>@KnFd1+;@hvnSZ`LJI-ou8TAf7}%9Mv$b8 z+T|lRF~axepUh}VVdLqX>--H1oAVY6TFJz^YY`WDrTQ-q7lVGwxDQ{iIZGwVJg^kg%CUh((&O&BGlJ=m_nKmmVh_#DfnI))P3PLRL+Z=^ z6_aCuZKAAsq^p5Uhz>6tH4`j^!r?G&_Bh66xA^okB-rub+(8G`>)qi!U&pi!lp}aH z9D~}~#l3OG#@3Qa02=_##G1oiQ)xTbPWLS#6DzwmfUhQh& zp1&8gh@wi;!lz)pi78-?7S3E)mFrpWx;Ie6I+T;?ZKjB!E{}%_Q~+GhJOeJG3?r(S zKIXfm(WT%!JBa=^4c`iLoLQr7g3j?QpnHM!Z9BU2MLTd*W}u=coNx3J z)tU&htwr%l0SH=%zDkIPXJ~K(R5@*JJ>Bh`RL9pnw`RyrJFQtZS>yDBEK-Ql3$9`7 zjpsDCaBiZs7A{(DzP=%l>vE-N^STjNA%EtQZfI)iV-NioUy_2mb*G?p@;g2RgPvvK zmMhp1Cb-lX=n`BSzZBJEk`lV>!`Gr9nI&WXCihakd(^7Zz4GsQuOcQBA+EZ)57#Qg_a!pGLt>q`9<0r zr?JNRVs@_@$bwAeh{;2){84nTsBHzF`9AgNc{yae1$dm%?<`mR`CV&u#rTGKDu-N2 zEiV|C6|j($dg;g4dsyeUFsD}Gbysi9HuiRI5ETs-^(gf%)_<12{I4fbfMm^I25CGg zd!cc=!BLmL^8Fj!t-thJ{}=f^^$4k&qHXO+X(UBpA6s*F z*eH$pv}#XfxR?3}x~4{D53mb8x_+Miah&w}KI!tEcF~retv-T)|wog7f^5wa( z8}v@zrU}&?=4a0Yf%P{k!jBNKfXW!<>UI_jMF`H@ScxwOnD`96xSNknCuJYxoMsdm ztoCxk$ z1x@yd^?9+{3%_ zdww>jon2zoUdv0!XHTR8>s_u0LSS5gv8D)b$QSXB-2%`MxV+Cw22IzdZ?UuPGUtRt*ZR};Ha5`oH<3tLPjWkf`T5V~14S_^}l6_cRdnHTEE%Y6)F z#aQG5n*EgdcAh7EH`NWkm|`pBesO^j8wA$&IrTEY_k5*-6VSb6qbGG}T+DSz(D!>&G`|&XxA!GLIAc64%EJBAugZ`Hwp3kBA0Ynr z#TxqdLaUC#L&_-^oWbmSfzsQ_HoP^{KQ-*Dg8|df4DAhAUZxL6x2^D4k}I=&`$Mgf zNEl@c8kSWr8bJZisfFm`y))VI$cCubog$Ig%Tf{jZ7+DxcuW0>y^vd?CFr7v7I3cB zti`rvMp`!d!ks&8{;I9Zp@y|$iuw_zhf&6&ZvP*Ai zmYj7>8mD|T%<~dA3kL}@Jl_w_C0tOv!5=9kOZBGSDl-L_#kdWUn}O38LL-lsS?<`s zEQZj&cp7iak?tV(MBFc!U)5B?cAZ8X%;JQqIqn{bN(0ml!)+L<$H~_TqTOa97wTpz z=(25V+(MRIJwd*EBp4)dT26MZfW-}TgXHkN zp_CbIi1&wnP$~i5F~W;{vmT zF6r~b%jtp<^qZ8t;?3VWSzaYBGYS^wb9WDoH1{gIxs1O!`o6wsVxlF}6-3onZVO-_ z>_`#PlEpJTG)k#8P|wUex@f80`+FmejM(c7c5$`q;My#58mb3;!U+fN#KO((!yot3 z0f45f4@8Hi3}!N?YQD*KNn@G*QnC5_?C^Vc+k*LAVMBTO{NN>xcbT$;h&z4j*Uu=l zXS2=vAF`O?JlkWL9yN>|jfiXr_?)JH`cdC7<$f_u%I53F0iCIEJAcJTA0u=?&k_^K zi%{6vg@-J`bw~ka2)hm9n0BQPdwCV2LqqCgbC%L@<#+C;?u$5jzUA8Gj*4>-vH*U% z7VF8fk%E+MB6 z#fg?X+<8~;|Mpo>aTUDQAAYU+tOP6dwzV}}7fVM_0t-l;W}zI?-_T?7O)X`SD6Fu{ zO%cIxuuG8{86EpsAT<3~f>lpd&#d?>)rBH@ zT00SJLn=s`EF0ckvclhDn7vLn z2APESCOz&*L1)wzl#+GA4dcvfQUX4-WD=yz!6Y(&{fh5?k@NY zl40w&Z`h2{Xbyp{x?;&9<9;vq&bXGNyR+M+Pyu~rMZE(J?k7w^`sGlfcohMZLEkek z%D?r()p9|U{Ya^)wZ85|!i-gESLKJfO5fV5t#s=*FW@41@xLj={#Qb1n*f5K7AX?T zatS?yK}BD{hmyU*lh<+gt&Q!%U1|6t3*TK?xZ|G=};%GQsTb8hB|zb`nRYyyxac7k}Ug1 z%3?}++uE_y2-Cc%K4DrrRWs)f2!$V+DWI(v#O;{$`PhGyD3-IHHmI%!N(9aUcJRJ& zHJ)c-ww>tSXyzrcl+NEDd(w**th$-;&J$2W?&_}6>V>mtu1mS{rd~=*)Hp_z{+z@?BQay zRe0;34EHiuGwAu6#v^yu0mBK&=9ZS=MVtluvj-+^Nq&o==i&xCg@WEdwc%x0@H`U+ z99sS({7LnUVR>S*d$~<#zSV$pcI}SyRoyTBU+;2=sn-;%@V%uotOf8C?m%gh!OC)| zI3X)0wr?W8wdxzRa$eu>x*hjVU~Ypm(gg&SU1xk}XOne&#IE-rROd+{ zx0=V@kLG-=rS7)2RMt$$B@74;9?CqWUJKrdZo2!>Ap1-ZC?gm7i~wK@_~knU<|Y2| znu_zJuLmqwJ0Z5&8^;14pmXSi51neTw~Xf^GRnf9>U6*2ldd%aw#!}9H13&qV$+)5 zl#Amtkh<{BH2a=B#m(4@@2vVGvU@b!`o2*P{j1*fCs2Vt=YE}C(k-@tEO#X83J*G8 zEiE3?%V~QmEJSC@zothka&E}-e@KNm^VbFEKR^E`6rB$Z&9K&C9|^9VC+%9_4t;+6Vv+wlu(~MHg?Oc8xzj5?4N8TzE7`T>_aFCr{5Cxit2-kkod`>Bl+*pXmx53-mU`z;h>EkOf2p6qqPimVWFOzG*M};2C-TZh^#e zQ|n&O1sAG4r*hxB1jIYC;n|^?u%l*SOTkN5G|*Pv>Rq_Ra$5(+TRSfeCxGab#f9u_ z32L-O_)ilSBQ7*XSs2!2D|ykH%C0p$H6hdlU-QdmO^hNyY2cT@21&oMaAVV^F5iYt&=NbZb$PBM@%^iVQ7uw zH0QI;HC|jX3JwR07EqeC3xFShQ7){cgL28W2ESD4__g+3rb$~(L!1|L)+*=+Z78%bmc z#sYqe!WnH*_2!k*p+K9Jj>nWjMvw4(Td&%DRA`Iq%Ip!JlJ86@4`s_)7E`Zc%#fcc zfAn6=V_`U}E8EVOi+bYk?}YyZoZ!EUrU5v?7s*J>``njdkE7yR=;Ad2Ety-+&VLON z#Ew1pMOsk(vZYNr;w$fOwc>E@hnTr3a3yjkpupx$(f1Rb<(;A1 zKmpP*1*!QfQ)h7Rm#;^st@BSX7cAfb!8fedlVO|Drqi+}vmf(h<&%f4(*n)xt}Ud- z%%T#{6MG^Fw?C2U^kjkcVt-ophJkooew$EI?Ri3lYi3M;>s?`7S`dunUt`D6=&<`Y zmsIi{BUs621?WSN(lDbFFMxF#n(=kpGAo1Vj(SF!sn^qN&2&D5m!;R+t2px6)c#cF zq9zPioXEpc?tddWmy@LlO(f4=D9g`tElSFQv6|MiTWFVV#=f(QS)XIL1{eqU^+R;# z)*5<_qXX&T#-z9Sx`9rLBH^@PCQixSf1u0Kqk=B(LS|3kO8FYQt*L44Ly_&3uMr1<>{}whKe9t4ljavST_=H zRu2f-U67&` zpttu}ny)ujzioFGr2$=qgYec%Apo|1HuK{bYf`!;fp&aLKz?4fDB7$kZF}d{-FoBi zxtBgXH(z_y?NxKe6j_=Z1Xe|IkU1Oi^1A>QfBnfcC$x1e#flVOwxH!ucf;0#z?+h9 zAzAxXGnj80&9rc4XK?P-s~%+N48oy|v)eMhCskAb%W3rkQtva{XR_bw(bEj}cEq>S zcf|c-ELx^C9@|o>ZA0%H-xB2ox=n6bGhtLh0)4_zrD+6MNXnu@+~7W5#8aEjM`Jw|%$AXn z7X!9AAf%dl;~Gk%`z*@HpBIhzS|d7MUCGN1Br^h6S>xa-;V_e^%W1emOicmqmk<4wK2AHm;tth8TeGVbcd5lE&K>cx>e)yEOE(A zR+ezn7uIc{VdR_kK)L!Wugn$gl37Ae0Ecl>fYxbhpt2RI0#k@0XkaHrB&tZZfipLf zP0<48(fKD_L<7k|l+#Bv&MkZIQRUkfKes`CUuDlZk@-iXn)>eU*nwD;E?%TcBVj4B z1Y((;q&Ha*`#kPOl&*JU#0Bqmoi$z2b7(;O=HxmiOS+MNif)0rPkD$eM`FV*a^hJ2py~xj+sJ(*NCAvF z`taQ({c%KP*)J$bYgV0#tv!V(WUoU5~@e+JHsIe8%nf#ue~Cr24(s}Qqh z0YNI<2`iBaMLIr28fko=qg2*;j10wymI6b7NVO|QBug+O*&aW#yF8bLPu@U>y(gli zhfl!syGzSM2gjFA(~sR38hcb&YXMh{yHG~bV_iJXh!{GyQ?|?8{o0dk;eIU#FMNt&sXA$h($!*+1dU;}Z~^k3ipECf`jUm2`*nsH0+9?s#DZOQyaVs+mI41Du!* z7!9uOLaWyvXth(V1`qu_`ya0Z{QZ6ZFaG>5P?jRpy6!m1$E?THh4*w&O>B4*3Z1FN6AvpgOSr#iQ-2M#Hw-1Mwcb0vdSXW{4@{#d!G3%P2&973tTh`TtiSruKt<}5- zUE7i8ljZ0)yMdctxfAY+m+xf>z(T_V`4&mZBUs&V?{k*4linweV@Ee-E125h2M?Zf z*KIhsJ_8TNa6_dt9}^u(QUvL?-}UX*20a3zv*P%y&RC;6lLkh#Ve^k0Q4@u6LJ~29 zmY3}{M!EPde3PL0&7e&cXamb4zHS}`3jX4T1p1Cx1lA#vz+~PuwOj7($vsdo$2DoI z-B2?nlRxQ(gUWskN>nZ6xNWSr(Ci8%foQ_(e4C>{%FxVb#)k%+s< z9hUlae!)tQxitINi=Lqxj-i;#4s8_yEiE+@yADWHhHP2cWJ_XyJ3G6M!Sx$dR6Y{Z zuVb-BtfV+KNj$N{^{d2PdRGhF=PNg`x3x``ELK5k_p=fqZyM zhP&6g4t%~uFyo#<#Ne}-kmpu+eHBABzU3#h!Rd3!9H#|8N5TU6NJf87&K1a>Jy#$s zVjaDA2*P#mZJ(99rOHDr5}6tt8zN}fjV>=}*IK}f94e-)4SGcw$Btlda0w~IsB%i~ z+Vh&sJ-%`wk@V*d%n0g7TS!HGSg3!RM`O9U^USNu_F>rd%Xaq9Z(S6Adm-VL>h3Mk zPe4nzrZK?`;JcOCb|wRt#8DQ9Yh4zbCQXse9NK2nSWs~Brm`NlV`4zp9j-y)Wb^yY zCa?OLs2`wCGXpQcI58EWEgCr_8p~$V`=ZUJ&(k)S@nN;j1)YU10zEli#rlN{vQvX} z?jQz9D2jHYO}Mfok!{m7WhIN*8L2Rh6mzay^QqvlG`F;QAo1Gb=|s$~+Zhhy*XgNh z51H&7Rrz)<(`4dfY$WROnbGtyMNvPXas6{X{7(g+CF1Yq`o=tcCScgDL(hk85|F03 zOE3y=(e){rbMhrDjbz&hgHFZOZX7@7`=J2N^Lwnbtiwf(`g>`~|IyD@rz7N8OW#vJ zph0V6zy&Br{wL+z%Ua5nWY$l(J8S%-l>fvu#xLrvzJ0nVfV13&V5rBOUFWi7&+FAh1TItD5 zTgy+`8}Q1RBYirJ-!UrIZ~zL8x~}g+3p(;++nEQTxko~k+M4dn8&x_u=2B`}kuH%M zYSKuBO6PV4#DriI?UWceu#MXl`C$w(7uuMpa`wIA>m#J6SvSG?_=dx)FRPkg_YbLh zS_7~nUGj5^y;}I)-VS$8%z9pd%aRmNec*-GnqVmN#tgPY|Lhc|jzOrp<=(|;#q0%~ z_m`+s4fbrK%a_m5-N428+m2^Lq$O%kI3PWBq~7H7wC%g~eA#Rr%i)z|&U%p0q~;rN zm@-gka>cIK)SFclX+O&c%2D;<9#Yj;+`SLqq#HFhKgH9%&v8J1?_E>g7vikOa9oDInq2^P{8l(WJ<44W)Yi%jiI|jP0kYuWH=Cn`O&tw#5t?^{Rq| z6odI#gMO4>^`|2DT0>XNA_Em*{wKso)?(}Z1Dyf~utHqt%bqm2zbn9&g7dn2@Nm8) zW-}|)+27^J_?kbHGDq^oK-+*I6h$;9;R;}Zop&dH;_{YV{4>g0UfNhetYHqsfTOe* zDoq3RGJNkla8!(^Az@2QKGL27U8UU-54m_e^i}r)(pD%}$lw}M(Tbr#n|kd0-0aq_ zM~b09m?A`1^OX@beQb448K+49>I#mF`q#)87@|{@Rd;7se)noJ3jfZq$kjjW+wZja zopc1h%kJ6VLxJ{mB9^X`ZwoM1NuAFdDuV05te$}yPAUinj&4nH`5sxnQgF4Hxm%Pd zb?ojLv9E5ryIcH=m4_OfZ3`sb_O#`9 zEzVeQ5SRn5T(Ld9bhfcFT?>CH*xPl^JF9lCXqgjfz}P$_CqtMu4k5yH2HuUgKn`5>nJeTiS<8t$g!& z!IJ=0TjuC%=H%H`{o9K94GDUUG%qeSN1r}kS#QR%&HeVA>)+N&(uHzuzfAR33bH8A zhD!(b4ndys4l$0U(69GUZ$_Q6g-xRu{~SB*&#|vK9I0--8B*uFSRbPeEM8Dj?JeWP zS1^$xU_Q`^y+B5(olT4<4e8bJ6vDYVU{|U2%R4r1sc4=p6=ZXx8`FD_-l0T`{AWy- zpFJ)=FNKf}y&Olbf0$Iy1z>&EpOOhcL{CKGEdP3s-28 zaqDiBj%XO|`l?Q@!@~l+3b#;@kyXHxntz~P{3oClGk;+@vc|)RyFw&fOw)4EiF$>JV(alBo;;8)$^ zbvJpFaY&$RK@L4e}h6Kf)USmR7<4Q)IrAPc) z!P`k?h{?h9s#R$cb02@o3zG!#Y{o=5%FGF%a@GD6ppO6=3zj1((uCKs6;3n$9P=)( zW)ZpQ#iHbcymm*+NSwpqwwH&G7I7JX)?+ z>AKA88N;SM4DGez)#d>_aDq?atjfs578~I#Ad-y z9fpoD5fzTM!7rD_YLoAp>e#%ZCh!6>rg-UgXtmM17B3tk)J&B35}__4?Kq;g*n2?M zbkF%mUEKQm`d&ce^Y>3u1^b>z4Lm{TypB1rxzae+;&r06jTFNlx6KABIHzTGW-(gN z%`PGAI*Eb-kwz8c%>(7yn*;@BGsQaAzt3wQC}%*%MCZ%&q;;g&1{ z0c@8bEE0q6chcvjzo=AXu2g-$-W#Y#uX4g^1Nn1%Ct5D})lI+?}z zoZ}J-wUFA?y5{eHs|P(^yGo5W0xUA=yF7s^IWdU98(q^1?m$Y^2%yN~Jipa4R>ptC z40uEb%9-jk9rP>3*edMFl<>7F|K#nc2({rRX<+VPzznB_PK8a4sOF~D)N)UGPfrQO z1*?Vo3oTV@147iJR8(hLdI98XXHK+J*kurQ2g?@et|?l$VBqD9d7Ufl|^GFP+#>G9*ZUem0Omz!OJZ`d9tUdyz} zl~ioqd3dj?&h}ujQ->Yq(ls3;W z#73azD07lEUesccn*(>x(Kz4Y@@d-N8CWrV-P<(^%K2&mg++HoVrOfaAn&5~4W_Ww z!98lFpLJ_Zo&}vrEd4sa%E~Y3MD+`Y4e!Z{{WDEbAsBQ7O3duQ4a+xdm>UQVZ_6%a z)+Ih?2pm%4ef@QWiEq^jt@0>mD(YiDhaD*cTY;{?*nGsC8uWm!1v!g|rRh!|xeIoT zyEtQ>37y47X~5PKA<=%48UpL)!)>Wokx%D#yaM}>+%uZjaT(&hOIKz9IzL=%JS@6+ zJEh7}@~8T%J!wye1cM+Y|Y{*{f9?dYafEB_y|NERZ~dL}${wrfn2erX%HvJz3}KYLScM z<`|B9;`B}Xs%k>sB5$okJ4M4mLL~haLvhUVyRKe?F`Rd7x!rXmaRYG!nZ(APABnn- z&#CyOsFi?9KW@x!)Kf1*@k91uRFV(rI{j-7}u06G@#3HvR$tIaLcz>oo zD!gK@G&fUg{>4N8nNK7z@e{x$JW<^UlqJ-?_rW3roPMuW1pA~5UW(F4t*t>>%Pwk8 z>s4Rp&Y-q`R3$%{z3L0)1UqVgW5N72C?2>W`!Y{uusN8O%-scgx$q@$*w26i5y&?v=~^ zJ}$A=J(YiLM_vv-iGH24K&2i5uqQCM>H9aJKsi6(oz`lM8Se*Sk^7KZh*Q?Ve@cq}@c^ z!-hA9>8bBr70%jr&`Z9h4Yi&+3X8pb!0x^HXqaq7O$!CjT_b3`emIv);*UBa* zQdhhue#oC=Rpe(+|4bcs>!!5sX+E4DH^NR`O%k}vjJI)%N}a(!?3@$0eq)&*BD zXRcV~FPTd>5@ml$2|`?j%tUhozx(6UJK3;{mIIGmb8xO%+`m}s`!@|&Ix znqOv)E2}m6rhmZ@&qnkoICh}UlRWQFg9PAeaWkFgTN??lQ#^@pULA4Jh4E__R~pkE zyd)+O>mM=g4&S2UAzwUka0!&0fD2+zfOsrz`2EVVAhbK*!sTGeT$M7`_&%rZj)x@Y zIfsw%+SFk3D!f_Gb~JDVEJ_iF0pK{`Vh!yE)2oF2yvcFgWj+-+<18U2EM=Uz08vsf zkU-ig-0jeRxz?;RSj5~oGKO-L7u;N~{?UPYcew04R6-K%QfDm-xZ0;sm&hXj1TvS* zb1mG_spq`nW!d(tY87$>&kzvMZbq`jvIVJ^l_yg80DcE#QU2cKuICT;2Qc9H(D(Bd zBF4JC?-X>*bpB_eIOgN5H78J+Hvv;#Bmc^*M zWlA-qKMb2Ti0)&z#JPTmEyVYD&{)nWe?JwA(}Z z^7L5R%%i%<{LCxEeR5B))9L#Li(8zhlgoYsDTk|&W>!RF0>w$O_}e45rhZlk&2HAA zUd@nJ0FuNDKnkCO%>l4|~I#Dl`5l&}ipb}?JpgwSMqDWMd6!01yfH5m$ZJr~6 z(`rI$<_;{GE~RUPC;BB!bIuZ9b9>$7TM9*@ER{M(2@e}~YoTfHYb z9m59aluzuM!v~_UCa&>vQiCzgW*5FDyG4a`LF*je=WYwM9>u?t_mQV2xmpU)m0=~C zt7D(Ga2C{5uq1t#ld2E)HDCXDtDV)v`eE9E(fPmuFrV@=3yi+K(h0;dQ46Kp1c`pD z2D+Pb0$5uMg%z26n)Pzy#z3R-V)w+%8uj{b*u|^SBkrGm^ckTc;mo4%kR0**J!w4E z6;|8VTrF2c9#j|UBD`nJcy@AoRu}nF7a;n?i0{^4+s@Jkz0n{XcGcPN;zz>e_6sMo zAYMB8zhylq^MXmgyLqA0@Aj()MRY3LAg$q~Q&HxhbQKS&!D+00%PlMC#NDtUm^YM&8_eLnQ zfXot~d2(6SP~5~Y?`!$+=QjDPNL4pxXVh zCb`N=-$&iAN1wyw;YM-#80-Zb_5ajSXR_#sVe7I8l!o8FF>U#vXhk&ohG}wB%fzyg zd-1GnYxHdYH%LM0`(a5P(?=7!HT%PXmRJxqWyD5?WQG-G*-Y#0GzwQhlb-X|gXG3{ z|F8DmI~>k;|Mwjv5iNS}EhJj>sFOsrh#HJO5#1;eZ7_@wy-bi0gdv3J5iNT3h=}OX z%^*561cM>_S>NCJt+vluYoEQ=-oJBQ`}|>ChIwYp{mlK`_viC|zuxCVm3D7#eeV*j zW4X?kYoI<7HnDL#wDB{DOrrx_uL%G(D^wY=6%b5vRX$v-PdQOpt*B0I?nQi4)K~@0 zN0?*A(4KHg0L4AjD^!{rb#Oai->kK(#;4tD#a~TWRJ$|uiB+K~!5X$?QoXNd$(od^ zr?aBSva@3CLjA?3g&*5^#`&lBIS1&!h!G6c4qs2VKP779ZA^YBPvdms8#&Ny&9ry8 z91xIbPbLsC%TSQD0$jpX5f9MVt#$@^URnYKv#)1gI=!*l1vyHSigRg8aAdHvR;#Er zzHD>+c4p{RJ7@j!bL#deWG$qJ+pwqo3Xu^bbz#F!5La2TNW*H!8XR5Xc#=&uN_kfL z6Kg3b^J+X(n8zYW=;C-l3fiakte6N6#I@_<_gpg^%*R{q<}%t+w;(-GmZu>WgJcb} zJO=$D&g;u1-uLzm$q)>LVO+!!CafCR`qDfxq$M!w;+&frf};jsKju~{NZFO(_E?d< z)*a8F8H;|tqP3{hPDWI&!IN+IElK#^88hGS$fZl3vCA3+-OyO#b|2c3QGPEZE17dS z89ZUhjg`845cmO(Gb{OcDt2&BgwI@#0nTin0QEoh|-{m0v zP)4MC)iZOz-HOonT|{xOZ)4eNXNpFKg`w=n{Y?hC#8wU3#1DDg%*N zb$X#t1N4rer@-gT9SZVj?y<#Wz@YfkeOlJ9GoGM#*oo&@p9d4fFiGCni$`53NtFo+MBN#oswY`|Ush?^}L8>n>@Yr$hJ6hs0>Z_41e>mvWJf3i5a#p9#;ugjX z*ePdXy^^YWLlP{+O+BuDvbj9G+^p1D$jYdB;TZ$j$8B4Kx>GG%Z7h@1+02y-+ zL5Vi`oO^?pc4XlW-miWjDAXyqA>sP^RNs%cFNB_NbB>>QbLy`0G@d$cgbCE(6eDWU zG@H{gF+zCWWL4<`o4NHs8d!k%0q1grf3jJ>$>%*H_D>Cf{S&b6iysbS zcAHn63=?&=tL1LY=oES+Lpj($3*dFJ98|!?W3ei=9^bg4TM=C6B9KFD5S2fz)e(6N3Od z)!%Gqs^e6HbuCcW`4N2H=^>eTMALT-=>hS4>swvn)E*Z_wXjrIDow6R&@o8?y+z4e+)`); zQq%tv!RcSQ|DW?zNK$pVq-#fS+`VO)nG7OJ)l~yk<$_(%)7qWTT7$?cSQ~G3)9~b- zRysLIhly_aYLukM?sM8>d;behmqgz4{i;MB_DmABX*<@#I0+1<34r;H$qS1sdhxBt z{OXuSXelQClD~C`T&~HN!V=@BuOVOe+`vq2mxz`l2TOsSMbCWd=vfil`(6?suV*eww|t&HryaJ2@)8(MEVs8>w1J9;r$@tw!ocUv+U^_d zE)UsW#=VH(A{Ns5#_xN_0Wgq-%TsW23*6R()wh?x!g+da2%bSXfxoS)$k4Jb-5aPOQb|5f_S-R$TU za^@(!hBm=)(VG>}Jlb8a9{GiiZi4ipsOJowe5sAsjf7XDupd84(L=923Q9h@;L$IX z=o}6lq9RqU(CD#a z9g(+|pfZ~f->Q?)!A?ws#4hD7{^~Zaxr8KKmL~ud{Hwe%(-}m`D(0}E1UKLk@nvVA zBj6~_P5O=Nq@6&Ford7lt6S09dKwJh@Qy6k+0wZji2As|X9vhwFegzFKZDhdR;8$f z$5^@ft+(9995zi{Nn7r2vY8g%U-)EkJAzpP>zs^noTc!(1$LANa}X3YKPqH>Yqht( znXcl?-7{uM3ir-hDU={ba^LUQn)sV z)pzbV$%`w0UwS3&(}P>Q`O47lWAC=*0F zS9hv#XpAFojrX>1Y1iT$hsvA^5Ih-BQ<>u-{FHArKV3Mk(@Qh?7B}g0=4edhVDR91 z0WR&(i*Ssa>EYN4h63Ii@=cyg6LPk#IVNe@S~V-0}dsZ~?xLwIUc|cq8hdWL>a4OL#`t z!n8VP#OihfbXwYqqEe0^@iteeAxmw&%{tHsG>r)dL(Z=v?u@mFl)`Cm;g)aMxvR@f z=8wM6YkVpGrXlO_(7rn3MMJ~mXF2&(GFKi4Zz6$7YmdfYW3)TV1Gko!eWdr<(v$RH z|1&~6k!!anEPyD7Lq!~LUmxg5C5-5Yd_q&TaX{}PG(0(H7U4N7q^@+el@%_65yJqwNa*WqKTLeOihGuGOicn8ozf_{T<@aXPr}x#}W= z2OZn1?`7m+)k-*x9N6+9djN0?zkA6T^D z4ztTG=Qf()gM)>N^!+}dZ?Z!7dPZ~AABye$23Z(B1N;-!i*dg}_HJ_am2P%Cc%k6B z$!NhSkNoP7z;fnC)p7%g>h3nZ7p{+gpVcGL6a@PWNa;j6PttQ1*;FqAmv3e79wd$H z$%os3cmclNcFogV|LRY%?9fMUQbn2ZHi|i710Y&)`{zlW;b3P^A`~OmYPEa2Zeq)M zY>TOGu+*k|^ix4e>W!J_A@7+B0c=c@d9TRfGn(vbSL z4Pf<;Xp;pBWyo-_qf~So_oP4z-Z1(g=MoLXK-1T!Sl>PmYGug$VpVR^3_)*zMmF-(?(iDEb-8& z7UlADz6p<(5nR zeR-^fQMIqTO?s5mOp%UT>!;LKtIU*RgN#i?ueli-xy$I`6&%dFwS?ilKzsy<&|(px z4xZRo2r#Yz;$1U;eYP{>koCkVK?twD;u2m{)K4-c5E;I98Fc28VKe-&x_(?_Ok$~~ z#nqf*+LZp@h-PxhLAL!1X>UD(JFAhAx3GxuIa*r_Zc){Sz#xjgLbR?*&yLUJ8j0 zY|Q%$+nl(gjxZ9!`eKljGp@J`9qqFQ!CSP|V1Dc(lz3X@hQ;Uo+O&_74?XnZ1S0`04x2N+JxcWfR*EBmh8ZDIwUH&h->1Y9T?J?`Zw=ZpHwYe%76+uSiTQ92s zUvuaisW^{173(Da0$HjbKeg+nC7)o8?s>8)DSfJ>>PB*&GsB_xhUMqTfXbZ&?2eZ3)sS!%Jg?o51_<#-`VD}85;}S~XbqH`# zwk_!w*|*0&`3>cvw%SlUnw&8IIe|UrBxjjal%5%U z9Bp$PEp>yQt|O(IBj;-)fpitk%iZaJOri4QV4cO^^m5!vt6;6|IBouC^EHz2$6YBdXxqUb-nWg}83XH!IaW z0+>_C2dO%`8=9pYpfm9Bxja#Ff~bv^qL_xqe^WE;JQ`k~OwpIQ8#XFVZ*#q`1tq(j zNh0=I-H7-p{#T}Vd0taQFR(OgY`S6}_nQ2<7D;HlfwimP&GlT^K9wH9`cxHYpMke2 zaNr(==_@fyyR4h3IW*KP!|wesAIvGc`C%VOuUbTR#W`{5D`ak;5q<0I1>!b#2o{G?l!iB#S|57?Ai`msA&xL=%xeudJg6F_6sx?sQDUjH3b*o{ zE7${LkwnJR&Uq3-5Y~{>iqN#TVSA+$i{}q<9d~p!dT*lPNS5f_=15RG?$_-2ej1)g z#ng{4Y3`zsq`=9hNRR-QHW;(YY|NaM$~M??bo4WwML+WGTt^VctPrJ4>Z=PLKZHoH zT=_1xe(yS^I`eoQ0duNBXu!;8Vuzvwd1;8?#fpH*?%;}_1@C^$tM$ykMjeLeUHFi0 z?iXYuJ0u$GVM3a&0-J1i<|P4)7zuOOSboRmt3A9+^c8cmgW8uyqKlJ*afGC32(;Gyl|1l>W+xz8M zn1V6Eb$g6C=Sl2mq5jo_E5MT_yeE+0Z`Te@^XlQMI<3){-P)O2sAzKIJblWh<_)H! z;^*(!x204%?(KM~kA1kd?-(nPvrqnowmM9mD30Gv47&o?0+U*I_$<+aHUO5HN9}3J zGxMVcWtB3ug0C_qKl%M3r}>Aew~k}Re;JW?PG2KT;UR~q1W$lshNhBgp}+v0Hy(l7 zkJ-j!wVQGCo2D$cO>euYR;)yN-D%VH(z_0Ndq#CwPtYzyxZ|{+wQ$=PN;Wv~CL&Zq z%B*YqDRZt)QK((PcZ>G;+;p|26Hk2+X6WxEZAFS|06JZ))OALN;rkCwcDzjXLcH z^73nU*1%jT@9h~SKW_J_ycgoeQ`R;*sWyX3NfV1Roeswd%PC2;z*U7hjL(gix0aR( zkQCdM;2@o4ECnJ7wa0bY))ky4xp192Ybs8?xB^RtCqlC2Ml?@flt{#%UHiYM1_`==~7zk^Ei zE`kC;entJBo^mMzayq*d!t5^?3UT++MsX$Y0ADVOo#4{~!FWQu4v$>)o5wsVD;~Dq zrIjd{?H;Bmph0CSI#MStU1|yzCCkALMg2lj!VPtCb}uh;*d;k#LSMK~LOMS!AIFsZ zYB~>cD>mg#A4ilK2y_WVmPeWcOvp^{HEx>a%0CyoL=t|}N$G;iM>QHfO%NnR&r)zN zm&tLi-OWggxHE^c*+<*Cjm}ulY1uc$IVV03Xo_a%N~V3QuL%k|id5&df`jewsJM$W z3sCrgslHaAKh=tm!gI?muUF@nm%`~czV@{~LU<8u007+P62kkIjdZZ%h_8WC=v|!q8Sc6+8-3}zK>z&qmL_0Dix-3QM|tKaImBsw zj|Um4fw&$OSc}QkDO|e%^Dr%m6{V;>;Pgr4!Ilr-x?EbCZ~E{Gh#T~FeI#C#ERqme z2;VjR{sSR9Ub{`+&HqC9=iB18g3B>rs^`^0XTcyhQ*!Zm2e*=7dU{hLfx}fmy?p3d$JAAh;TIqdiusIfHigcR` zMtwn*cdL~u-xJF|A8k6|eaSl=XjiaTuqjRJo}3#06XOFat{8`@4|9Az;V#*_DlCHOTxcyQ;%P` z2d1s~wHY^KQfqt5-9(S0@)h(Nj)99#m6Qf${&AlP{FRMTTFN&AzXFf zKQ=#s-L7QlkUdMC*uY1*p;2|@{HDI_B2TycEi1QQEPihPmgeTgDn4u$HUk5K4K;Z^ z>j1^_n+)Y0u{Yz)knQ^R{W0Ui8R+qb=&Eh!TAilZsb>}OfGMgaH$upYci=kDJ7YbuJ6?Epu4qNBt9W z+~1Kt%knD2R?oF6RL)zfkiVSjKpcOwJa0Vv8+QLKCi!dB0fn?n{IIOb7@)g{asont zkb*V`L4=H5u7f~d&8=@uDx9o1d4K76_%nL05Fkb9lSkxbSoVxbrf%lGwK6 zx?H9DvjE0;Y}-v_KMSxuJWDvKI#1PwzUHO!^QPQH;U08DFSapnOv$(P6x_o^$1m_EP-kY(h9S!SK>q%~Yf)CAklf2~d zL{nUZ;o5P*Vx`6VLxNvB3-D6vz+F_loUm#*$_z?DsBK+VxYNN-^E0jPu7K{X>6_nn zLf;*R*?$QQ^{rT&uzH&w7lib_R8S&b1@jboS2HV4a=%Ele-?Y=i_JTgC$fq0qg5GU z3h-S^TwsqONV8!5hWnmgA))fuorl`ZskZ7P6py0kAHBuyTh`YPwSH0}W8RPHL?uJn zRsENMt@5;2Cf=~C?Rq`_Ct9JQa{VMA6?HZ4V!6+~!C&-YG>0H9 zcMySjn~D%5ojrcGJ`l!O;5wKOU9U8fwYIa;Iqh0r(bIa34B3T@FlU>8*T2YQtn;56 zLedD+=m!x>%s=j)JG%Y`&4bSU`yjT!?v7^|`LX>=6RyfUsf5v3lX=?X-?7X5bNIrY zTfo9Vl*APnLea1ZDD^qd@pM>*B2lQRJBUX!8zsyZkQ!zbOxOH_Cl8W@U_L8f!7Bm* zB@6LQJw;K4363lZU!opaDiRkI*r)0b#C_Jt?;U$+v#*Tdr8}ES`VXgqTQgRDHy_W^ zXPS2Dv6RR&HSL_S?Cw>c&}zanh;qnJyC+=Y?TSFsmnaZgi6U_S25CfP0M|;QW-xl@ zBQH?eq$N@yGnapZ%77Zl2|4;4*!q1woW92Va!mPkG&}i^k;&2^atSP&8!qx`0%r@K z>E;NGS!{ary#JkTmusqW;!6!#(MRM$l#Q4LCW1@P349!|;!JIt3&)4P`GQq>)c~U4 z#5&uAYqM8HBR$FzR15*?N6mO|{^B|j>6P`Zz4>lk^aK{xvep3dOy1MU^A^WGXze9s zXnaVrUp2L-39eo32Ewl{6Bxh|RymW;9$8CKZJ1-H)vU0b8TJ+T(>1o*Z1e@J`jm;n`qI%Y+oYUZtyTQB@aA^6|9=t5spxKap!Bk z#jCekUs%X)iYSqlSAA(EUm}n9Lr+^Tp+5~pP8=RV>4|1oJ(cCGW8L>7a_{_Xm6Z-S z!znZ4t0|Z+2dX~vx*ndk8K!nts2Yk(ct9A$@G`cxm6gL`cZU59FVlmf4zBq>^c&Nq zx28tcnO>tx6e?8#;!uv?w1ZX2PVW)#6T$(!a0{~=_sfjLgXW4bTK3*YGQyd-4{8ZYK|An0JOXrS*cc#`RLb1u3Y@1{^t9j-YRha1oZP@8G}5BDh@x|=3Ut9l0WH1JbsFVzDW7-Q zDfK_^lHOrpNXTi~yG6d`$*f`aF?C3j z&kDo%x|Y1D)+v^3r54+x5ZahQ7075^tBZD;Y3-Q2O0TcPvkXr;mWcuCM=}~OQyO+2 zB#V;$ijOC56ISp;SXAV>uxl8}xH|tDn(~)QE713y={`E)YM6GeF4q-`^Kq9HYSat4 znPSW(p2~jtIov6`2OuU}q#_4H}l zM7YwN2G;wj-w^LQl1j1;m@zS86P`sa4Wk8+bng$Jt{kuYDCbY$D{XmeHnU=49lx`= z?|?Z7F9*8rScv|`G z?QJ1yFVN{xpPdq}s>|^5My@Kpl`twN0r)=yp8({~f(tY=0+4{^WM5N{L+u`?l8;kN%uSX3znF24DzAYwy{={%Yr>b8Hb$;#ajrz^=9y?jWrVmzM ztSjs?{!-RaKp2~?=&Y^!^U>1IBaXO6PA|t>Lj3%qjWa_+p&?7&N$t4ub6KLzxO_He zP^~u^LT!|I2k}Z!ZzhIuLpUFn=;b7Ek-mVt^lKj>2^5;I8D@zPIx7j2-fUAL_^4N7 zsi4eO@I#De9g=nm4mBBV$MCQ!?CCQNyF++|JMU~%-*@cYo_X$2u&XX}KCw>(B*3S) z*40IDzpNCya$LF-uEa>D2z}TH4vPs@HOOFngaz|IGp6T#$;n_UD?MulOuD5-`ADa? z7B(AMuh(HNE}VmMBR5QwZ;sV8OD|pz*A>aD8iKNk^zO2s|7fBo_~1#0x;Oy(@M+Gy z3944+gA4KO-sLYxTziOALf?LaWbP>(yHbZ(`vjk`9=6xxnTNJo@%jka5{!Hd4=wF_-1#y9lxcjzT*Vx zkly)MYdt7IYd7N7(l#p(OzNoj>u-=B#6KUtdss#oTFh}+YVWL~U$eRtNz+>ZT&aNQ zMsL5OW>1q*{ahWg1t`@sxKNYpt9Mb-954GF0KD(*(rZ7Hrzs?bzkPmD<7v`IDf76L zLgWW^7D46iSyfKm5EXo;hrXu>p@MJkNbJb$7dr6q`G~to}C(z zuSs=P#i^4MYA||GPK4?>W}+6>`6W%W@!sbcTCS9jkodc*s$QiVa6X6+l%v03hA43M zz7~koNbuxbvdeszW72=4n#Nbd!YTe3!p2|-6G|CO^p-AAuyAhs@;}Cm`x7_r-|%$> z*@ND@z6m~9@%asUGYtU4iI%@X0+oR6-VVZhB2ku?M;&S&VEg`BFDC6*x$@X}`_c+> zmiOy~ZBX6Z@;CSFC}vWgXr~=LAvBPBR|vl_m;Jd=*Xr`5$M^EPEeYXd=}IKG9pVQy zrK%D_EZ3SuZhap~pAOlO<;hjvfry-@XW=1ifG8H=wYGaqi6>!#m;4m>W0`~)S# zhEyF+?STY7!-QW@3imdlhJbM|c}_PkhtTg+{Y4SN49{hJufK|(#dMJ8cYHp*n0dg= z+;tl-`w3!or5&3P>NWSPiYlmmI)fy6z))aLvT)zv=FEjSejtA;9@_#r)j`nU)Qfo% zuvKhRZYR&Gtqjt)Y>VLD&!Q=q=`Aza?k>N-Aj~;T8CO*ssXe=%IbRRPCY!UUMZ}91@&N)lGKgMII+X8qnF~+1`I#?AATdlEIF6vL zS}>anJclXwsU{QTcHTc?u|WPV;_iP28c&j0hU^14Np0Yi%HSq$>vOe?GdwZLcYGBa zCYW3KlQzCZ#R&_PpJ66*CIj_dh>#uQ@P0;Aa#-A@ za-F9i<X7`9gD;}t#QoW?4Vm3|%u>)&(mqb-<^2ip!3PRHc%g30z)s1cN z@8RF-hvnXy=92I~mW9dyTVemX+?WFR05+p5$)$sbZnB_0ojX`Bf%8m#PKxC zXgg(~^ccmOUj9i%$~a!X;&OGq+o=%z-q9LbdyA4w8QV)(W{6d$d<6XzYtl)0)m*|>T z1=J9gqvc&PN|gaA4)EboT)F(3r(CP-ozy|TRv5u%mg?QhxO5(lALU6ac~21E*x@%T zcnJnX+OzD?azL%1QH*q1Pi6DkQJ}EUSsuB#>6c3Nq5_UFoY7sx2N2vg!IXn(o7s7teLYO?v%)h6~iSgeYhgQZLuT)1ou%59+Bqp3cle) zm}qOzlC=Zp+2nr0h3O|Zd?Rg~8}JzzbW9zZW-YilRzfhlCjwKue&O@Oml6*9LJp!T z%s!o|kNchuQdD0Zq9CAg*0#8#u7O>4H|3$&HX->=x%$fcg zs9N852*;VDaibl8a1hfv#;J=lC@yxdH>pkGj1w7^?Aa2Ny&NGU7kP!5>E$9_Px*ugU1*DZ)&CjhTGVHL4=n6IX4m+6%HZ+c`x9D%TfX_^d+L2zdgFD@JM}i zF!|QcdR1<`R2R=x++0zKLYV{e3E-`YIxDs59dfSe{=g`(GaD~+OZ<|L-peSI)|-}v z4lrvNH{v!<`%>HGI`w_#1DaIwmIpi1c4J_}v3N%Egqz;CmjCJ@W2sG1cD z^?`ZT?fu``6#i$jF#fO1lyXCQg0B|dDW^lIdnr$Dd{#>e>wOS#6?dw&DE-?@&hLOKPVQ;EhMXMg1-Tnez;||>=4vCx#u=xH4-KO1vF3Skf_ohTX52yWt)?_|d z?d4TM_z}dGXyfLEaO6n{vL#L=Icy%(($-v`wW)VL5$)YD)$b%w3w5jO6-rG+Bk$w|6@eFF005f&im+p%o zYRC^$Bk~S)Mj)2%hHF+#X9!@ZNJb-_aKRhGBjwvI%Jn`rKR7MLB`@}~dM&tx1YJ(n zIn+u@cP$iG_%+XcmZL6*xY5=QsI1WO=1r{O@-+9BOcM0QQ`_oNn=n}-|9b&x5*P@t6fLbY~IuI%FnXs%|LSv@thSk^T7B8X|vQGFF zN7Hz`@O5V8>^CSQAZ)Du zmb(xb_tjCq=5;@78s4pjqxA30xnfjhhfOK>Dc7EUeJuDTuf(Ze<7KU}e{`R>G7*+bkp#6r^rxG7|-OZO#F%Ywgu)+(sY9 z6V=1bB0&nJomt~}p=ig(YW>XkmEFdVx{d8rox`6>ci)vaXN0FnZEJbG&z|77=5 z0F?Zk2cb3kYlx%|Gh;|I;8gBPQ938C@I5rA(%~cP4KaNo`zIfI*VrzBp3shlUBKC8 zF7lGVLoh$Hg)*!HW8?<(C0Rf6ucUI`G`}Fj^|0o8L?74dNhkn)Qvx)*4hY(_OoZnt zH(|&KNei#hx%(ZV_)br8s$#cArPNlUF8z%cw+`L3rc_!OqZC_Gtl(p(O?5ikx$|!e zj4kvSK;MNB2Vyw2Ta!Bv!51tB>;Z=?U#bIQbsM55@%oZ#BmX4}&kp&Mlrnf=7oeNU zIBPDl+ORYE5_kB@#IsCh>!lX%F}J}4+3uAqn!dS!1T0(MpwIL}+Jgvs@9RnTut7)Sn#;V+ z`}NOlV#r=!`h-PDpUNSi_4wVcc5e6*)*!na74z5@xN!Iv$E0_Tcq$yuJ$ywcx$N}O zhw1JOb(5&;)laP2rU6W>lK;YwV(j2hXAOpxTl+^>a9v- z%+Sp030C*`%@KJTaAUh4G$v<%<$K-9aGjIF<29Xl{@86iw&lhk%3Mk>! zzQ7uYUGBZFVK39?h2poVmzlBvJEzcoqK$1Q17ie-h$5r#EbndF56He^qR@jObybwg zQLZ++LH$usw(p(`*@l%U*$S{>y-0|ZN^Ft9(_*BOJczPYYrz+C*_%VPbv+H{fA;Fy zztTyO7;j8=U5*h;cjAxr%B=Dxz*~;nRgGi+K`cJc1JfH-Gr~lc0uN2FHCmPU{?{nP9pGBkokC zxlv&Y23qZR=U>mcG7bx?&)zMMTg~gM+=Wrd4N1|dVdDf)Ms9(NssS~6mlQ%L$RC5E zPolHdK3vl#dHM7YrGYCMc9&%H`T2L?6YYp(Rh3zABLv|F4BCfllXP$G`G>kZNaaV$ zmn|QsPgGkMiivXCX{R~Jl!$CA7ZwqA8}DNCuD{~~ z6d`3V{yPNKKiahYi@*CHAT$kaEa3OrcW8gYBY? z7u3w51wlluHycaEu6hy6I$jq-BRK)ye&yK()#mPI$$0!lIDKCC%?r)tW*Nu4d8WyY zC}#SXarcSklPx4}c-Ahf-Y8rn!m}J+h1F_(t22KcuaKhfO3qSF=VfmNee#gO4_v3} zs}JY0d!+Qa*7lF1bpAM>@e~tSgIum$W-c7r#*Yy#;Lc6Vsy_c?$#)EZ{l1(Q5)~6 z8>}zMo3UD1y(|#5m@Z=Jkdl5soZdFm^mMnwkZgkk**C;OXt(@cRPRl=L*y>DTrl)l zqY{~!KAgX1c}v*xp)8-$gOwe!m8xpd65sD!sD5NLFV*%h{x?K+LRl!D4yFuAxKvah z5PV;egL$sgJ^Ezf0T6)hyA{=MDI#MhUXqdc3v{xubsB`_r6lSD1OVdom>x!iw6yyZ zcMk7(Id-6OLeLf-%D!M8{0x6i@Wn;>Vb>39n`eMka<#7xv@0IsnNE3S0->mP_xoqi@i z04eIa+&`3U{fqJzS>UufgdX+n$qzv^{;Gb^LNx659iIjK5r8XWPqPJBL_Rt%189$_ zkSX_N}gE5z;#N`Uw!vOj3(-bC}&hf zzgN!k8<~14*<5)|C%vv+%PV~h#aaU)Vz{cF>^Q!VA(Gp87u`lY6N`^(^#EpUL@qts z?{UPSNAZ_bC!^a@P`*l7%vrv?)U$cMk+7=(y0}JX)Js*Kwky<&mdVytk8Q+my|B*n zs>}r8>8{{y|JP0cbq*pI zp=$AT_X2@s*kh-KekmkWPj6&9m3%@%eDOn$gwWokOilgb+XjVIkyL}Qo8ByNR-*~> zSk-Iq2$DnR42DtXvNdP}Txg`FhAZ~V{LXae-tw0Lf4|tY8-`aY1nC>4F;97$<>TQomhn=wm3dwzgPP} zeUYB3nvWEA5Z&Uv)Yn;tPHewYsmkn9T8Vn%wN>>d9p)1R6G~U4c>H{BhUKA&K z;(~$bZ`R)_2%{%$&QwDO#mD399)Rv&Y;QL6lJrv|W8H0GUW_B8+=fFIqJ!79N# zEOv^Uq!&WBNbFOu3azf8E+Q`B5oo4bZ~~Zd7opmOirV&;sNM9Yag%Xd>pf;sa%{>C zT1_>h{FuzgY?Ra82tt*Wd?|kT1k6VibUKxRM;?L+A%#}(fzEk~$rg20DfMc#!HV*U zg_-*Lkr%a-d0(x&nrui#QrMJtXqq|OX3tVpA@8f$7@S7JX!i3oje*5b;guwS^jYYw6$efNnAblpiM z?z5HXn;N12EnD-y#8mz(KH~q%$NqBR^vS+$}20DrDbNtS!FxfB4naZ9s+9iO^IA_a8$x5*3?UklfHlZL z7P}n|c~M(YTQy`V8@ z5?-HW-B&aVOBIRpSAo5Va%!q?xUqFfW()BF8eG7=p~E~yR3_x(OKD@F?EYxp{sP{Z z^UD)1x?g=~)mCyUDidIEmT}c*+UENgQiGB&2RxTFl?!47qt-?`9 zJDtruY+A$Z300i8<0${A^Qrt)vw)}&olq3dHMWO&2<}f_3RDH1VOP$lPf*<`UV@-j zn<4e!TjCwY1ZxRFvyeHMwqJef9`CkjOEo(!m!{Aje&ybs)UK>mZ}po9J3`K>@+`uN z5VPn_tG#G_SZ(3Kafq+l5#ea9rMI~eE1*q>_?+;QRfR5>t@KPASAz-c^^SokD@NDR z#s&oMK1HZd)YsK#Xzv{aRip|s*FqFK*SdS@-)AyRap<=z$oOXSZcQ^Dx{m_UDky?Z z%^|%rxc0pN=)6BHV*$Ur>eK8zbP&TnH*`;mGirDh%>;HE;z9@$Vw{TLMPTwImQ$+_ zqXHw3Cb?VgPh?E$!dUVo?q83(?IU=Hq!T${6KUrr(p&LhvAzUvwSPa-Am*GwD&D(D zw{-J?o_C?!?G}~ddo}aAlqwek67Pm@nd~SkC%3M~wL5}&+`+hPHy%#HQ~RPdJ1IO< z*mWoLZB}K};WI@asD`)NVl!&6CfSwI{qo4ISBW}Ii1{+b4ruH&EAc7>N!wyyWMxAb z?KauWc$d|r#|IrM>X!_1eAenkFp;m@uJ#OGw^9hIIzOZlUNq%(4 zcLEYw>C=0$1vl62Tml16@5V{>q~~CwHA7jqvUj{?J`>J=?EA1@1h0(phLnfjK2($Z zO^pvMVm@e#9g0;QFT0*HPZIa!$BnheAMyO>LEo|{IxY>!j}8BEC;Nng){KnqK(2a3 zt?QeHL=$t(w-4XMUyuGrq#)*@SwO5eUW}Z4xqF^iUm5YYQEX!%7T$Q>0*+azWn9dYvfC*Bia@1KW=TK zm}ABvPt;QSj!k}p9-o^A{qfE02k>7(9v^D+uIQb09UK2~3$X{@D%-9puD?A1Q>a-W zt)tJmY5OerCC?wX0ZhgRX0!jcgOalAe$oOzt?Z0fFKv$baAT|XXkPdu8`*QUu)0P~ z=3z?r>z_aN0yBx(i+_jG^Dm6-f91^muY4?Na`B_A-0Z-j&piw~*Z9Sip9;Jb3YE2N zpPJr1y9jJxZN>85gadY^t?j^bz=3rv`2y(zYyZXi8`SSt84(WxBJXSJ7EY*sgO;0& z&vGh(z6ns}79ME=+6CzIZ@rIbp42YQ+E3O{*fQLzE^BFsh|$J7UeST9Y(ln~30 z^N*!l9O*(|k3;`F(l5Uo-{JxwIDZ~F@SjH-a$6Gwbiw{SbfSM5Y1@kcK^<5u{pU$i z@Ryt7Nl0WaJ?n(F`b aJLK=bhQj@S11t4kId}c9cy6-aQ~wQc{;ahC literal 0 HcmV?d00001 diff --git a/docs/assets/texturing.jpg b/docs/assets/texturing.jpg new file mode 100644 index 0000000000000000000000000000000000000000..c7e045b82073570883e983036ff98ad04746b33b GIT binary patch literal 57787 zcmdSBcUY6%wl5lbmkt6#sG`!OOECfIBA_B&h;$I?0zm>nklsPM6hTC4q>CWED7_;= zN`im_kpwgZNZ{uC_TKBPy`TM@yY@MM+~*FMc_(Df$vg6nG3F@0$@$mwbpYFKeItDU z1qA@0LjD4rqX3b5P)|1iz{CV_4FCYp1E?wZ0W{hi^!|}J?G!9RHYREKAOBvDdm5RrkpCJ`j0+E_FvP^F@PI)J$#?~2737V z2`kE82i&-2WJ3Md>SX%6FY$MmZB8(GDGks_{WFpwZ;x;*;=BjIPEV0dIYmVw3ZP`C zpkk*u9{>Q!cR@q(H~l@0{6axVMNLCXN6)~>L>|z>2B4&%qN1dxqM`Zg&rpPu-v>~$ z({PB$YtwSxbEFgX=Tdl{@tR)jRzolM{b{VYqEkQ=10xUbMLvFs%aT{FUQ<$5QN5w2 zuA{4`Z(wM2+x&rrrIodft+R`(o4beSMen zdahd;uN!(9#1!vixt#*08F|E&P!hPmSo@o^e~q!I|0B-+!Px)eYZ;&ep!}PtC@HCE zsHmuDXlckqOHcb3(KFKjO^p9e%zx8`zlil8bWUD`g1iPbH8main~jNqiS2((=PP8f zlsQKNn5ihp!bHUm00T(GvcxNZ|DQFg^Qr&q`=xv?s4(Bxurw`E*MFc zBA&z7bBgJ3mHlf=`lJ2DAne&|RGp1-xW2i26>`+wPb}EJ)+zrUzRfvVXpW*1Cw9gN zIlTc>!3{O6hsC#G;AiX|X^p%5IT@AVHKwy}D-D^U$?*ZTj3qLVbgeJcR#ngr{2T$e zUcye)m}yz=c=sEecwPELE`GrO9N+{xOHl4NL~tJDvk37%`z6NGhV3>dU z9T5$DpVpTK*yRmy7%3<^>!|DV_13(BkX~fvLRP$C@YQhMh>wQ{C- z4(Qb-D!w}#i%=ufU_t!@*GF9=PH400iWFAu^ygshmrrlkHX5=tdjcm81|wbckk;?b zQFKJEklq|f6J1=yRiaY^j%BFQ*Z-}@v+S?4!jX{2A*~1F+soI!aG6lBwc6Z@G^9}5 zNGGVFAc||YEWA$9b`})^-&X&EI^n}hBDMek+5Yw!> zWcPVh-$150>>NPk>_EX2JDE1pkWvF6IqcBu(uahkp%6LGo1`}j-A@`)z2XuLnXAhT zo21x&W@~)>U3y^yZ9wGe#`_VxH&UE?j@Z4B|*f zHFpkh117`igCOy1Or7Q^v&1vutO4Gm`<{)^%fIzd<4(x$j|6o|1t^PrvwcKP%@msTfo8d9GaFRX18xnkAfBQ&5TO9x8l0vANlzweIg@xd= zbk>ybWI<>-8)MgK{s>95oLM;C<85;`)^BZup&UYa)>9C%NY1BmUa%s?oo;&alYhO| zbPgEuP2vI5Ybx@zIalr8Gf~M3sq#DrxHis<#n_M9wx@sAk@gvJNufX*tgfHALhaVg z25Wo?mrI7z=pMpAi();zK5L0L_ z${@{|R1SA$u`|ZTR+6$%ax8UktNgiNY_TY34&HP6n11;yz1rPIZne+5T0(~#`-H0{ zdu!`J!QEn7s4@u#bugzzRQ=@lMK&)pSR^WptLD`me7JVITvi+K%CfbBEGxXElHY01 z&-h5CEmGl+fsD`^%UpxDbAV1ly;Cu(V%R9hgjO>B*G;}WT+Da`9Cj^hqkAt2HJJiz zim1fO4S?BvJH6lSSn=z(yj^OU$PefK)4i07$%?daVx*1<{JOYgh7H!7Gdq;>qy!{bW=PC1MmRD7VD?mq~9FrTVa9tZ633daqz@8}H1E)c~WUS7db_m%_)l z;Ra3|QdE*P+0h!47e+2;yB>aTV!Sij%u>Dl!Td9#d>2QD7bZ(snC*{MSsd>GYdi+M zc3}s^jO(2Fp>puB?o(@pvlDLA+uvW{)*ZAZwMNYqzw7dlwmHB(J+A-0L0-Yzs3ENe z(ai{UqANiJXF1$g%#5v%UCiaz{Af|JGPcOG>OAsOd9ZoF*CdkiEA>;pai_EXTyU#< zTC*7wF_18gbL$^)pvGOuRi4DF|FjIwW&b=->vP!a#Y_JnE3TKW06%QSmzV*t8 z(d*FH&3-3)ADKf+9>F;c-ttW4z&3y$Yg-v>q8#+caiim5a;b3dv?w5R*VS*ZYlJxe zP}FYB^qWO*WsP^`{0^_(x%Aym#eYgErL{b~_L3%_vEIm}2l#Lrl3LP&Aaa@CZzAPB z1ty#WD5N`eQ1)g+Rx@w2svtit19b5AAj6!^?;I^-9$9?Bw``2n48#DmU^9X-{x<P-+)*eWj!;L8- z-8zfhK!AhS<)F;14Ku^qJ!W=eknA?6LSW@E!|)YDtqoggi^!QAHBKX1mO?u zNnf0Aup3G+aiv7ncNk$3PdYXxG0RxXi=>K>7gUiI^6;4yPpeYT;Dl{scM&Nj+WoUG60~pDrAV zGv>;Y%rR!ESPFUiu=onqUV+p>(;1^-vFHNP|5O8}Io)YiL$IA3Dwa~W_CR+K|^`rG(H8Rr0og}1_UZx^kX zC?7fcKXJCXu&D51v}5S@OTPOQr(Svy+C&TN+fUg3Ge#rq<9!2McRWIAEkRX%5ObCl z^iIR`y?~eggH)y64AyhnNR-gNsY^omGr=%?Iv|;7_+StUAaZm`=BQ_a#^u zL8kHxHfIq7WP|b5+U)XQv3cE=Q3M>#=J8w-yCcOA;Ra~Ft-da#fp;aPv~<&-_1m5U zdLZ%CKUS|3;=F5&>+Xmfzis<8$JNj7p0MP4P-d7!6L2xMcUy^KI|qoh(75Cop^lU6 zV+qkE7}P-unS6PS{V%=Rcj5Trma%!4TTM#w>7$OXk4}I?tb{8nHP};pk@?~t_~p&27czgs|nif7wq>HGCscd=FY%prtgs|kxP(?GyuF;EkerXu{vx2Bwxg2 z1aJ=2`;MX-I8whV$XFsH8~W72~GIG*wDdp*F%M1N9;1R)gX#w33~C_F|??~uAS-5Ban?XzaDii-!+Oq;I9Vj;Nkrx)qyiv z0xvp6PRLocvrb$y;xhK9Zhh<9jKW9Oy^rxY%tRbSLbr)rRQMPI2D^_h zCP<*VDLnZ1p6S)Ubu)a5F~P_XZ4W-Z4x>%H&UGyL9psS#5ARD2{Jk~=TrSu^c@e03 zPD1+ajR#72G(#!|tKof;G;{t&mHN1x3?H8Y6+ro$gbX3poV{f&zCqF_5ChQ#x19iD zfjJQ*%5>00UMQ9J%N3V1WX6JHfAKjWZ*kbz+-38QDh`bOOm`7c*zI)=_!Tdtmj^E;AeoUde%l^&GhG)*U7NW5 zK5%@5Ja)U^MCXjNJI1Gb`HZc-!`f#fGG|S>6V1y>{UE?<)KY_<>gAdN%8bZmaGP+t zQOHUQyMSfcPng%dNouQIxjEI6X8hscD=9LX>3Eipa-jB&l%fl)dLR_s!@6|1VYau4 zHAjO}K>|e18KMTxZeV-QRwcs`Vf0M6Sv>Decj5g{VU}J2gXe&N<6Mf{?o#Nq!y|XU4|&em#_Vk1mAa z=}2$L!U4P#F$3r6yt-k=2#vl!-2!3%CJ@^_@36DhTMSutF$P}K(ifb6L@6hut>qs{ z6K=9@w!CJF>)tEhKp<1WG^6gm>xH{XmuJQgI=&V9`-CJA(>X&*W}TgV9iXT#08D~Z z7C~|L6~Zk6q1CP{L<6dX(@XL3U1-v&?F4VZTr=I5M83qbW~Ir~hf# z&e{bc=lTPjL7%;)T;e%^?Q&=8aIgG|*tbE!H~VY_VdWezjJS2G*o7F*xZDuJ?WCM8 zWqWe0FFWU>DciUNlbCUg9vE8;cJVxt*M7p~t?1^|sO$HLgSkF%YN4CRC5KnWl?=-P zp<)~0C{1NA95vzb(r=7e-%-eZ1?l5d$EZO6(@dR)={HZ#aPa7Tz=+mORn$INf_k6r zzlf070di`JR1r7_yBVJho*_`jMY7vrAw4N|6_g^Ex1Qd&xy$ln=~{?o+urP{JM0$W z9Dp_voi!(j)k2;7&P1CFj!bdPAyYdlv{$rlw7aH?P_^Ew4Gocw_%$`wtr9U&(r^wK z0LQIT5o$IB<<@gw5Lq{X>^~e)uT6 z?Fu#3kz3-GQp&%ZR1U5?MN<{K-N)aZN_2j@pe_{cEwPE|>zC<`T^0FgaIkKW5tV8> zFAgx%))F+~{;qB|T=L@McJDB$RH>V7ST$0t@xz>e`GLCy&qBZYQ;aU6;+`khz0uM7RDvB#0dK(vwzpem={h50VEKesA`A>@u`=?7=%a!5e|5 z0ff8ig|ZI9)4&WMdMM8t8ZtnZ*x_>M<6qXou~?m(Q#r=ja%{S-sWt)uRZn8X09k|2 za*E*I)j#pbq71jT&VxxaWu_3Mr;U{Tk0{704dzH-$Ifni%87Qw zNttHdi|e<2Y1n&Z&PT|&f^~PPJAG97+5sAn8zRSkz{6B$Ae|EiXcXrJPz3)`=Q9sKY z^B8_{Y|31`-FQvuwuGNTkAK!oSN*>W$U%z02E32VBg}5`jOHi*V#!7tv#nnEyPxFT z#RoG{WKcpm{AM{DNEi1?JX!yjR_}1l6onqw-T&I?CV(wxadm`3ygi`;bq-+pdBk5| z^$r?wCg5dkSR9tH35|b{dZk~ZL6hdL5kj7neQX+#o8L6qn)%e;c=Rw^RyEh`BdCwm4gwG@2|vTJ=K#DNL1W!sf5Vtygc>R$ zTGiSbbA<%hEg4+0JL+LKv#^TT?I&?0EoY#+uzr0t&i%0}y>Dx2-eoz`P#Q2Eu|BN@OoUSkY=8&N zmS@qD!)DwtX&mr*ry2svj~+JRZ!J+0KX#kAv5{#X1qPX4N)?@0ztKzO{|7>lEa_R} z_2_<&NB{{yb9KA0RtcJRDji%kRkkMX0cjzCme}A#SEK9fR-VJc{*db5cj*qkpb$%O z=+$i015z<82z!dgm)D#F9@AGgPXD>#P2^T?XlKR0%<(e9%*Qb^WmXIw{5&%F4XF;V zTvy%0FRZf9Dg(JzpuGJJ$e#=M1{OcY5L1W`kyAL3L8Y%~Qzakp%gO}zSTb5bK_1B1K+#aoAd*@zp7hGZR;KA}-P zVEBxBVv2 zhrS+{bk<)jToi<=(>o5t+oU&O_qFHhi*X=cXwB{JDWdn=inGFyif;m=&?lHB@sH3A zeb-iLzs3*ucB2QMKtF<$fQ@j>8jfjWnqY?@nqbog#$}PKWGQV;2@7%8H1c`Nz^(nY zVtq(}BG>W$?Z(BuA~KWb02l|s9|yTha6h%(fwPfwq!_!qpqmTQ%1m&^@omq`E@6co znNR9%!D|BgF7R(r){%fwnw#Bws;;L7p5SJOjB7e+BX@4};cc}V+%yL6jyA{Xdv*qAVXD!F4@G!UGV)1{GU!h0y_UEJ(4=AQ!*HAqUC?x`fMBNUD&|5S$r>kI5(9rsr)+#!1dR@@=pzZKJ$+d^nX+is;vvtoz*mc zy#usm7#Y^^VK8yffYpQ7Sif+CZ`u)8Rv`nb?>gb$Yv{IV>moU!bJGefTYTb! zsP$4$L+*cXgBGx{HCx)6 z6H=2c#8@e;fb*seI4)_{^3sFuDrRMBf$8Cn7~`Qea(c#TpX_nANXEfz-mMBU{E<rt+Glu5_P&GP(%vnENb{atZ#Y)G%IxGdhj`ae>6IrVvz#Aad1qM~J(# z!{(_7{wU>briMTNhb;CN2C_C>>8y7GAgti^LLfCrkg%wQ^R6Tt=^AT-={^Rjk_4~G zSNa5sF!XRry|ES*7%e$IeH5h)AgrA+ir|tqD)(OF;!eF#Z3CWfWMCBTYc6yH zNO``?*>TKNP!;Pi)ZuZ?94{#aF~THgBj{jC(_K723RbHSo(0ryOh$h~9Sblr2e)sz z#9n;x<`E{DYvdi%D+(=O5fE#XRAaA7b`XY4DDf_dr?+tnrpPvg!=n2MH)@hbDLO4W&md)ChqPqWaA zL{9L!!v$OFOJ_J-J+Eqh!+>VB%>-=wZ)jcx7Z~YNkZ`i<(uLVQ!sGF7uklc|AaNb2jR8{<(QUb77(SL z;}T^b_w@>_tnXVv(AG)E$r>@j84DleqQDKTz3@ozMNNBLQ_uLjuJ#Sq=Gyo6qf|(n z;SfJr*VJjTC{;b#YTBa!Zmr4t5pQvlvA^XmLgDwYh(u|px!)-ctHyR6Hj7WqwH30T zI(}pG*8=9in|OQS$dCbk)jkAL^a!6e_vfmnZO%!3Q`zII_)iL6#_tN?jkY}!4^l16 zGDc{=>Zm{8jPboXeVJ4a_J$-uF75yBPEkkn*^8k-HL@9RJZ;UJ89uITYb&39adN8r z&T)G5y$N99%(!MlpgUuz#PX6KXi77X$9C62a{l)|qdlp^V5&vXYH~(eHo)45OH?^R zfF)Yw3lOw!SjUVX!nviyS1tvV*T;vK<-7t%fkjd&jiA$uuR(9pl^(*c7`ouG3MtFmk zqc6o!W-^|h1Nuo`8zFlYr(OhJ{8OCOpo}?sGA2UuX9%whsoBx9a$WcgF8f$j#gy+btoIlu4TZV+nL3njz7;6>#tC9zpIB|RP}*ze=3HmZVu z63eW8vFFlSkK9+Yb#mqqc*zW>K74;s(-nQxrjq`+SnQMCZj!N+O5Xa?rQ7XhFB@p0 zHXl?sQBq*(_Bb6+b%}nyY_KP|#UWo#BUDLTvE;|pHC?;7oSQ~_yIM2FxpQ`tr0hM_g=8myN?SdD$P@n$TjOS0s%2 zXT}VV>`hD#V|e#APgS7;ct>n%!+JMh?XfCeeYGL5?#{`p_oLUotr&2bzH^M_W{-*S zW6b%Y<~#&?fa4`{^y9-8{uD)Q+`-W$64g-q93w}nT|zT0y3vMVv6~OIrqudW#}daz z-T(mFt&t!uEL|GWdwu^o_`PKo$|T^>uo1_bwB0oKx+NcNJQ}rf^J2N(GL6LLGdg@` z6nb-i2|&Kep=c^&BUqr8HzD>aB~&ez^S>=sdAeK&`|ay~+ReylJw0S&))m!&t`vJM zXtMmpI$1P_fr7+{X+#TOrw)!$%ENd4Lk>@4g0}@bGkyA-L__TkSlZgfQr1BeRs1BW z>^C`)rLrnVxc%Li-vOpw*vo|0$YIgsG4>Liy*+zFa(t|ix-OS}^Z6eJ4cgV;Nz?~A?N0tnc7luAHzG>x5XD%kOoA~ z<@F0iSjB$0~ppHm{cMD6=tj<ktj_u zavU;9P)4N*5_HfOWS#4DN8g0^sxB?`a7{d5&%*l zXk#S@XUI-qgg7BI;u}@+zasFhhYE;lws@#%b|KcALN1h6{v0u~3R-t4 z@IW$303DIFF-bwFxfO>tNYD(eB7~T;e?t;l$GwA6M6X)pNQK3+%I7EPU3O6@$u~si z2_Hc?&jFA2qt-Y&f$MNa?eKbnrEeTtc;T(N=J4Bw2uztUQRCBuIyn6TZPDVY~=kJab5(!R5b(mk%Hixqb%_~d@*FR|H;j+rOF_GN@~gPjwZ65hC4IBxo0 zlYj1@ae4zv)q5sFn64z+l1gAQaxWtIJdi=87bo)rO{B`9T;9tfT&oYqX2!jrIJ?_* zM0Z&|5x&|UPxn(#SR~R_jqWw~fiLE14O#n8M^VZe3BuU@mZhQ`*;I_}?IXybAS}dd?*`UR$#L>wds#i$_F5YfhoGB%yDM+&L;Jtj4C%bVVZki#EYX-Te4AW>>duXQ?;7+ zP+^216R`&|vNAq(-;9{2KC4QRp(WH-+q^^Y*a$v?FRl&cJD5iM!!oCUrw+Yr_$Q4E zxuf`P_Ym?paMYVSDRc&H%;1)JV-q4zZ2nfo_<}l|?^GG7jY4q4JP0A>h}=@B?+{J% zkKFjWT#K2#AdMvGOTTw*RtoR$0tB#EsCKHaltnWBPaDp9U(?qMjo{vW_H_1fD}O{e zOOt1SuG2X{|7@~3@6)Sf!%V$Q11G4}s9yij#Z!yWwWtD4Gz1u5AUaytC(iyw?7i<^ zktSLXo};oH#RGm>zW~-y1_TudeX1ZNj$%$8^jXg*s%NxpqyuiN7h6OMuj7SN=_Q>$ z*u(qU-0wrUq53ZG7sc*o)@<)BVx!Em0%|6yv$#f72L?8tdW+xpgoX@S7W~dtfBL?w zq~_--Xwg|k^XrTJC1J4y(JZeg*+!PvM*GXFBZK}qa{qtp!_OD~N#!~x(eR{SoigQv zLa%~XA&R1Ed|#_+x2P7==@yj_!iQeNL;QSx)w>ip1%CS0||S27+a0!(eJnsY>Oz7j;1?%A98Hv)&tU z_T5~|bh~fMH(%fLym{JVAsWEueN0cI(pUw&znDj~Z)xhnK2@=ezNYP8>mlC|y45;C zvYgkl5f(Yh)Y6++d?H0mo}&<4>s_PVg)r=OF+*EN&p23Fkk+=Io3dYz8!Ix)2Crt` zOm33WuNS{nTTgYBnsEyTK2?J8Vuun>gtA|cZ<XWVI}K+rDm8yf~0{xrXfdee$iMS@VCQ(GRUwSPx1?>084x-(~1# zo!tC1_-V7#Dmb$iYg&!_ocuRv#oAB%Qk41>-9!OoFB{9Mg@b`KraGltPwG;>eN1`D z5(+(Wts_?C*FTy~9-6pntP*0tksf-VRe6rcK(McZNn>3Ha}!#W7B$V$EVp)T7lY_G zaPwk;n5;h8F9UYQjSc4uT*%asoj(-y&2Ft>Ru@B<>jC@XWtEq%$+(_7x|6-Odx_~IqdqQD!# z@11|q8iLOk|6vTM#?B-Ow{{2BHSc@&2W=)PmT{)+^!VHjhf;^jLoVAdIauHE-Y*Rc zeXw4e_#mxkaqZ7xCFW9La|yl5__Ff1?Y*<$H9{_gdH)=cbJKq-WHR?0AR~3`JB*-t zADW_R#%^BybH37KHZnH!Qx)l=D;)aB!Rw@2-iLkLGCQ!$iE zIqK9*p#K6QSjMM7L592cL5__=p-xF|@C~N99I7e+DF*V2zYJ-=e6wQCOWO2$&te@> zp70CFnvL>JP>nTK5|If?NV`_VEoXh?P#n6R%y(T!?XWAk(>}H$=N#Z-QL(o@_Pt`p z`v@bRX1z2APJd@E?Aa>BA>|>r9-=WwFHj=QS_gcw{nFp%@g^yA3IPcVJuydp3Rm)DL{W2k;V`ak(aL;%h{P) zbuPB?na^G+Wxh!_@XR2=8?^Lh?4cZo{?4=sX8@xyXAJZko3XseeeGf}VMv71$Of!eRUIOMDGQVLrnIhUQ@|P1J134SUi_SXN3|{qy0)+YM zT)^QE(#4a}hI#e426U#@g@u1qOaBMD*ty?p!hn-Y8!%yaT|jZrf6w@;iZ?Cx7wsMu z@a|;-j#zmCiwZt*{7d@kLDl(}`~7Y!Rv^BBVcI2Sh|ikxjnIG)i;*56^oeCbWq+{i zEIQX5n`_ak<@#}kWXYy5Ya3$So=HYmb#Y|${y;{QJJwh)?>w^~2no(LY}8Y_BPg!V z$6R|uIQ36J=hk8Wv&vXspO#6g>SimS*_EF@%fdNsYN3yAistBK2?M3tCbR;!v{?1a z-orG|CW-?m@a5kNkM1Q0>Rj6^UUfmCvsth0JWGvxC(dU2=RalI|GWJf{?7**5Cve* zFOG3K*s$BvHG*LbT?YCxq{8rl$FDS;CB29pA*!nuh>G1UAhOuT5!)7nRLOX-n+SA? zPqft*vi5FzLPvj>I+j$K zs44X<_atatLi}M=ZKYRvxnrj8Ba7)s*GD=4eW^EyNY6^Qh^T_cKghbS^Dim-VRs@6 zBjNGbH>KO%%g+F`p5h51g0@pvSa`>*TPd#|+rLK~@E~;SSky4=ehH3Uk@xS^)P6pg1rjL%AJ z^t}kVEbVzBb;dX7WzLY-eg2n|>4ok%w2EV&YiLE7bW4X_uh9~Et>^6V>?|8CrP4X` zmZR3kDVttO{C*@us;*`YK)d%6+4u+-6#&Q|&A;5FCW!(zaE&<1bW!qqF!!hh%rK^SbuoK+>Z(@h zg{|D(nNPNa7_LxU0upwUkbp+SAiou?#ayP9%6xk;azA1+sF{YjCwz%AvP?@cnf5bN z+aF$3+8~&TXfefWgC)LILxb#BUVY%@X`&c0EN@e@g_e?$40b>DVX2uIt267-Sd zfI9s7P10xMeHPFtti~W(EEr%$_twlwo4A~y@C+KeGdlw>LFD5*H3nw;ZL{qi2?#Se zF?@X@78124*bGi=1urdD7q};2cuAK(w~Yz|50KxA9aM(=kJ2~oZZL=MbSqVv-t$qg zEvdbSU`#iU{^+R3^?*O-zunm23K3g7-mhCjYAXe}Wg6!C&(~2#PQwP19*LG@FEgG4L>>cv-~NYJ zhZtN#9-cAw24N*P1dsZBV;wkJaTM5Z4gEFtI|{~(%|xa5c4d!Js)LW~GP=dZuFyn+ z?OG-o1d8s#?xB{`_C5vQ7?8PcKef{HCOdWqq&axsD1`t`@J{C5G~(=EmE(_D{=xsJ z8*ll^_Xv~UCO#Ua+dAVXo)Rh9Buno~&3`Dj6o-$-E@ITMVMYW5>VrvMho{Uh3}2ga z-8VW8U9$-KM`1No4&w+ypaD)fTm$5aj?iS&X&HRhDXGi_g$p8g1pF`cxqXKu-+$Up_jF_uU~!_(iWsI zrTJf`;eUT(v7WV$MIJ|&GEjHbVnKvGK|Ezn4sV|@@VG?Dt3$lDMBaN0q;I<~^%>(s zG(y4I2_LOt67U+ko!q_?hQ014M;mI}pjQ+Z$HTZX4fi>#JL4m1kcN8teyk76KFFiV z=pVip5bO&tiaRyH{H>p1!Ffmd;EmJZskIIu!!?p*>V2 z$7J07G+sjFm?(MQ6|-h^wI)ug8ZS2wcYZks0GC^1NlO=3I?^jZ&j9;Uo4{oLbvvF>S`2j zZQeneJ{UQ*xu8s`stXF~y=L``*Ei?YnIeu~s*%8I8&IPLFsX1&mZYck?HTLOJB*|| z>E|P#*kSH=@+C;D4I$!yLP}8^V5}4DQq+Y zzxR^v$i;i5qwMAJJF2d~x8jy{ewEi7X-sQNz2tbBYG=E@jfuC&(cix!?!7|8!{zH; zk1U0l-)FrSS)t0+VJ!!iSoBQoY=6NLOR?$2M9h}Vm z#L0~vG)*2|TSLJ!j{g`Z2bEVYop#4U2KdC9a90L`kF433 zcXZ0qX?ZkKCxMK^TWL|wX@?W}((-0}iLMt?dg(GCVtI4Pf5J+1GPjleGH0znEgpxK ze0XWq3#0;jCMY#W_d9vEyp@ke&(%oT{^wgK49Ynoe zpL8(^n6cB`&-%!dc;#)-e=^kEEQ13oIR`5buN%I$3~`>imYhXkBrx@L3xJe%iYc*| zTgr`GL&$2K_N?|KHpaVJAKs)1F0IJ#NdCB-xAno%i$g;$uj7~G4HxZ10Ew!s%bQ@1 z3mLRhfZf8D43SS|`mzy~a<0lDl(Ms><&;iqAT7&eh|Z*VgUYn15vK-fL&E;~#p7;# zD5;UCgXKKa$wvY1&@;X!^-#*`?y$QvBdsJz9CWEvEu`r+wlyc11D zmd7^>#$?WP3XGD~IGE{7lxQA@E^ffuZK!)3JsacK<;NFRdH79wc?G(QW4tx*FFzdD z7?$R!CiYoc8F8Tug^$~kh+(Hz1S|ApR2R_pu>;dWT2c!`g_rfyl-mMHCX8RQ5we>_ zEs|Q(wHX5?A4Rq@0CzjyQ{YK{aCW3Cmh`&K)1tdo>G~Z715R)CiuaFfAup>Q#@#zq z-!$Krf^ZSqHjakrX3nIbAMF)bnc8|jIrW`w8z$;@s<*}>AKN<&2Ks-tVdhlA=0)v2 z)eR>&MNAW-X||fy3BQyC#A-%aer3Ni@JXOf(+tj?vcI1EaFkhlL_b)=utVU2!UIZ* zA4*o#UDt6;w;M{Rb{Xr$4IhqIV3!FtPbyPz~mY=E-&j(JgS>8m6}w8Y6jhzfJhVOutTkCeS2>54w^K%O}J(`6xHp zBefyAkPl96+Y*YfH*1w|iVcOpeLACdpnGo`IzIU0V>M}VLw6T>w$k_s zFZ(1wfQ9~xnPzemGa=hE1k4*2Xl?k(E-DUa?gWuzxn_~y`{De z^zSCGrTrm^O~{kk&}`5Wl03Z_F_9TD+D*}%7IW0LhUCvH@Y+4j&M#B768Eu=c7A-V zIufwM@IBLPKB!kNS@YIRt$WW&UyTt5ucBwztVk{ZF-i`}DIf`0}-eOl?vX}ecDb*DB{e}|lO zd{jf#OYNt<>kx2a+P)r^-GLo3s`g+RoXE3#ia*P;X#(a2XVQYNA8$NDl^5?7E8sYI znbz%H@dA{9Ub~o#ZSxLb zl8I@N)@|P`AqA1@-kkO`od%WlmF3@<;`#C~DDa8v#2J{!8km#gHSP7pMFiFS7S4EO z99_Z$m9m{t9*q|beV%0m^|6PHTK{t9kGFcN#SruehRA;Su?$iEGeQi4$AaZD3AAfrqTBrZB23XVt(m@s=W=cP6(O%)j*k;EAWu73|ih&>BzV?a>|C>#*F zVi}NB_xMO%7m3J*j%a7Qd~^#G$OL}T6^^6{BZD!PVDi{NGA<1!_`1m&ris0D5?tZ! z&KK%9%fEex*9wpSa>$kJZSz8^ueq*8fA22c@>8qtX?ty_)-W)RZW!1KO>&qe=h}yi z)mr$hU@87@Z??>TdK*_-PdipuJ2NUvr^+HSAtiu9^kTyB;kexX{RB8WQDVJFn`pBk zP(;S_%T#0y@Eq}v&(Gzwl^{jkV*?ah(1unn*2f9@N))H8hV+ivYM5iI(e752iZDm4 z%FY7Q&*lz6XB+HUcGarg$keEB#g1)DUEQv9qV}C$vDc5Z?+%bpIj(mB33R=18nD+D zkPwVqr6WU|R{)%Wh@z z;pe`-e(-h{vYS)WtCVmwXxlclhIAh)24dS1pF(20BXL%;e1vY@c2|vg^wPUcY**MfYPruG0*)#(EvP4H?K~t7JE*wl{fa^U#pXPY5k_ zgKt7%P*uoia{j^pF2ej*-=p~F3OXVU?oGvp1;)IHy*@m^{$ll4vfU}@=obx&to)G8 z<($)z7CbjB;nX$XAW~CBOo7Jx+4WOF_S>XbEUG_X_Z6(_(5F9q{_*d|P&;0ub3kZ> zdoDSQZC^MCFcH%xpBw)!|7mc5m~Vj2V&4sbUWQ*OKeie}u?OsJEDRi`JWLqT`osSkaJiRVJX+){sxzg9f?;*^^VNt zy$!p9%DSGtb-xy{m9XRbbtljBa276`Olp{Eu~&UK>)nzfw572u@Oi=7Eg^bX^!jI4 z$6i{*;`g>baI%9qK_>$H|B&{cQBB2ByC({Q3W)R$N>!>TO(_wT5)dQ31c-q2-a|)_ zDn+`05RqO(4?WU*Z$hX+I!Hnd5aQ&$^Uln@cinf*x-(z%AzA0FlmFTK+0XOa^AXeX zay}1})N>AW0uv)$Ld&Xq8)gt0E?mCL|YBpc2JO%Zv3*I09?Z>fa|`O9mIFUKqI zRu+ZQOnJ{ip1DH~s9ry}rx~ukm3S zt=4x6dL25KZ1@A5$0~PpCNbFziF^Tx;0*)fvae)!LAfka-?kz(XGAOZiQl%fmk#su zV7r=Db(?Q$J|lbsY>B)FTJ=h6^0ZfgpmB+!&aucKIV5IS@itDu%gL)~We4W)qO#Z% z1$5lkckty^b5a7znCxe2{&6xb?VekieoxW)7~^yH6-!>f3WjhX!iWZZX zx5U<9y6rKO=!FTciJyl1xjkKy0}QoH0HIYb1=ZeVGF$?-c2zLEU`BC(nDOxze1qjs z+dY~$+DoHhoB|K#e)&cj8II`*t>$%O0lfQnZTo!>AD(~Q7Uby|j zEd5r`{-tSUD&ygT*Bz^7Tb@jfjG1rUWp{tFtm}(VJ~?#&L|ks+CEt}`gSB#g?*K5d zM%%`ok4BxDAPpcdf4-RaJY@;BrB2?0mLJ8)18ZVP@MpNgRRHU@pHFWfJMgo;0nrey zpIe9vR*s+GPp#ldS4#l3H?_$zK8(L@p5qwtK~L9pq%QCuiKPvBwv|f}inY^>@X<{~$!cNvmV>uS>Q zEH1Xa;3e4$<{$Go$EHv%>>dfswpx%n%f^Lygd4yi5E^NU=&K(hkXwo z{*No5{6`WoIcturo$}%);g6jgR~FHfuA~$2eJ`uIITuU5t14LU7uR<{TLCs&7$wlq z4SDdn?Gv5P!+MKBmTgYhqpMGuYbEHy*LMd$S1TS*F4hu@CPz&%<~~gsw%`~@mSWz| z_5iGS?|}g@Q??F7Mg3luKjToj`G-zel7-t;;+~l(;GiSFC^{c=iVXkQ7|%i89DnEu z9(Df__0BEc)xHdumpE0tqu#O!SuFlX@@Vf!j6?97y8J|u*B(-p za%p>RnfV1>hYNqVPGGr7`Ct+c)eQz{zv~io2cj}J^XFogom<)BN%CgITrJoy-&Ypj z-oRE=183Lpx4YyP#;Kltz?>qwoK#o)x}Pye%d;2lJ%!+`C7&6a+3AOW#=Jp1=}*dU zsA(;ss(w)wX`g%^?z2pHouhak%B4Up|17sY59j~Bd8VRJCf$AXGJK!f$<4zCAA zkni35`Yzxn1dCAPS*h@}?5H+`3~CX~VT@Nz8}f-NuiJ|gV23|dY8c$LElLv?kxBCb zk~uY&m?KC+)D#~V5c(mt%i-u}=r-og&RGJWzP>!zu{Ei85WHcP1D0d@jsnX?elTVk zkIl~iI5$Z=I?}d-ZwEXq!gEY1QtVX)cPg(9adNFFXNdp$x`gVu+m#V$6#6HzUq1G} zaP&m572uOGMWok15-P)O`T+-Ycte6#+Lq3=7~Cdiq&p3B-QW<}r1sPNNF_<=9`w)F zcFZHvtpsMmAmoO;&$>}-FtMWhGNS(%?E81xbg9S2U+TxrJK`cgGn|~wp8O!s6qF_5 z2$9H^*$>AEKxlV!gosD&em%9r`z*bdEAD8iAzA*m#^9$$nr&?-uAv75H*T)STE<*j z#E=mAN)XEWU}=ToGn+>=kAu-lgvP>Ex9LF<4n|6}qSQtBxK8w6gACjiQ=pN!c~9NEw;jatVN&B@Z~EGzp{S}ZY)7mQd6qI;3R zXMb3{cP=u!_t4+}eP2IngXfQn{ zdNSIeRL`lPYpn}b4M@cS2C!QDW*iYBuW0!(iKj@tZox7YKX5-m{BH|>_yyCSV;%0$ zeF@UM$UgEV=G;RI~R<~ zK}~`k;$ae>X>pV#d%aYExxS2CBeL5B�Ks#Ai*GBWgu8W`lu**HO=%#HkY|}@ z;d97vqS{gW9&)%V*BKjYYIXWj6;GsckT9C@3RbJ05RP9XQ#kH($^b7~xnW>bFK81QOedBgM;Slze{rVwfFM>1{BXPw7 zBO_4t-d9}}z40dKrHP$)n9DqJ+VVWW*XRP!f?_-pKhU}oS1sK!4vtZz!3E7unu_wp z?`cj|tRs%|e4buZ_uYR#NntG_(S&eIdJ$G@GZ@(9Cb++@|r5#9;Tm*(807 zX)5udler2uB}@?J2op_LK?f_g$FR|*J)~UiVdgdHIxa{Kmw@JYkr0Bnb6=QIDP;Jtd-htJSl7A%C z@LvhEc=<>z>{gs;7HGQOmT6&O@*RK7ifiJ69)XFN!p_kZm;Zk69`j}2Y&!qJ9AbFt z@mbEi`@!_pe^jwEG?o9=#1)VOTHrB~f_w>jR)g7uo!w#^Ev+467fSbPN&M(~XTbVF z<`FmLZUge}iTT>2t)s(wYhN)Fd?$ks|LcKqCQc7sq#X^50}V0S?xz~z9AhuoW4w6F zkfX2R@&gO$oR5p~srWrS8`dCF@=7C^&d%I%c~R=mIg3qeqX9n#xim()fc#dwFZ{D~ z&QBTG4&GgG(O=Q@G=+Q&I!v8OdpK2?-G&l8G6tVYKg9izf1aD|JV`cFG+T5<9anSz zt_I6RYu|~=#iw7fkrtP=8&-_L>iJ)bWxkp!zq}>Rjy7{Pr9-)5)iw z^L1$p$yJ7Vnq{{psh-FBt=_%nB$mZ8pFMATa=v)9(bQ_~pR&|ANV77;jTZcV2G7{a zwcZfctzh573PYTu#Z#Bdn{`WN#O)5<2bcAyj;}$fQoY!s(36!~dx<`UL^@OlbS#X1 z;HXC=JH<~AM25fDo-MDCXJXWA?O&X8dCg}8@GkOjzXt@&wjt385iWS0H89G*Ot+yL zaeM<<@QOw728!ZSj=RIJc6z*iEoLRs0&`Lg@-G6bSKGfxvGEHf8GOi*%Dv2~3}w}` zuPzv4mo7L2WBe4(r^+re&;^ls(M}Mj7pVR#n{~ivN4$U0Q0@*E#6GaGJ{bE~KZ^Rt z6Am#6GZq-jp(4HQSDX!+x3w9S!5j64v`&BZ0LVxAog+vJxlWv4x7ZknoB4a8fh?o5~r=22zL&eDqeo;^S0xqcdW!8XTbvKbg{hi zV}Gd8a|Gk;^`R3J3J)4!);Ry_@wrJ?ACBzb$6I3QwtDs10H0g$oTX%9R2lyeYmlKk z%1#%3>>Vsp%Q)fAOl2go1TPw5Q)SA&HPwHEV@*rt<=%OmJA}2ajA%a?1hC_HprSdQ zd{HP4UynDrx`NY|td+z@Y-p_oDI~YoSRn;^#G1F9-}_Fc(m(jcU>uA2v)eOC&i7N` zdzCd)4#uSo!-x?%0_1biG|L2imW10WtI6f;D zO=v~=G`}Uz_pjA1UjDz$(<&i7IkFf?h$pVzh120OI8ww}fC;;3Z{TLsef+dGYG%_) zdqeBnqvxH;v81NTK_7xUh)S=IDbe99oR4$wby7Lo>N!)Ze);sbG&4Sj7-<}kzgJk* zqkrbPq1gA1F0@2naz*E`9@mD+K3H!7v2DkZRekyV)n31cjdb$mvh`i=L(lU6Pj{6JU5p%_tVq=1f2n~eXHd!GlCvKeM!i^?>2;eBFeE9rAW*;_YFe# zWjbCYfjTfr#&E&q;0r+1v{6rdbCu4I>d)M9?HcIQvN#qrU!TCdTfH;l(T|8x&IE~8 z52Y@Ka9mGKH656hcw8ykH5Y~#U47^EYseDIC26iBF8MuMS zPJLYm{y=eu7V*ZDhijABL=}L0wC_+7z^ZtEaX~fMWj*dL*iN@uJu|yZrT;~hxxnpn z#&`_`RV=9ltZ{^JElc={Aws!S`37$sPYl=DF`mwmAa3l68pzTy{N&3>EjmIXF<&e+D;afnum-6u!fnRQofzy5ccSB#o zozvMZOJC_dRF}Sb(Poen$$*poY|tls$$Oawi4MNUC0-{UQ3h3sHQPb0fDy@JKBm26&60GkighR^3hQiAs zoDs`>(6)N<69Q*j_DJ5&ro0xhxkLI42_z!-U(Q$ zTLLx=?H)8Rfm2;e53QGLSpxN?`^Ej92{7_0hbDst14-3R$zj+hBbn4&VV2YX{C(T?>1^yS(hAhDWH}?b0tjeKrM{ zrUrOkOS+fIJNJau^v>_@2LP|MWDZ1EMdi9LE5prit$aGA*3q97U2pT(gTm`h8+HGY zs2?qFic6~A>d?NK;r`8)f%N2F4DPB6RtJiaN{9f|&c!*GJ6a-fZGnX-dx=M1Rd1Tv z$@m;eRXt_8^%0@WJ`|E4mK-Yo?A0~AUB(VstN(?FCQzBc0~`Z9q_c~**_^%`Z1p#_ z{l_F>l00L9<}sTa11+m`$fx-%p&OTW$^oCQBnjg={J3f~hynVn2WVA1k_(<+20O65 zgB9;IFuR#%(5^nQe>s@^5*zwEab{vBVk#BRfV?gWwrgl@nK^;b;4GZTgQJLz3XLbu z`pVukO{1wo^z?DQ5vzQ021WMW!mWiKGx=~5?gCwdt+T`{HM|R!yvZB`c{?R}3zsO+ z0^jk;Oi5e{ws>vxqr=Yi9B40a^;*6x*!c@h&Xb;j05Rd@hU;RaT{K>Ux$D{5Ar%cX zGC>gIujr!qOVoUPPVdU~dMhJ2Supi_Sh*$m(3bS1A?9Lh72XZ!f_~{yl*K`??^ZO4 z11>f&g?|O7b^PF2pKf?TL&n2KU%v1zRT1Y1)eRZ)hv9+L|E(+H{`dbgM)RLXKj}p# zZp^&I9#*d!Q!idy@+kmV*3Bm*od-5ke|`Ou(_sg!pnZ%EoIY=^td@&{xxPuvqq@D& zUHaW!Not*&?SKKViz^e4{In#Tynfc11XzkPT2x%aN~9gWFdf;M_s)3&6OPOHT&?%J#^AgL{3+p#b?MbB2b zg>R|ZwvKqli`p+ld@2jD#lX5;ZmJyv7T$WSsO-NrA2`+n=elSMPamAZ=>nd&ebH#H zZ<>93@6g7LEnVPA(8t7DkV28j?Ou@g`~iwdPYI_@Gj0E9aiP$+2*@JeAO7 zSW=NEs-^96NmN0)_F0GjV>E}5Mw-ry@z92Idr=l1h@B2*JFOe9LzUDWQnJe~ujxpz ze`#QaW;gyL(TDb_p9Y7*ZcE7$xP~esT8~W#QSS=2 z5pg9YSxkCJU`G9VFFYp+idSSy`a9NTSJt}_%NJOw_kodBb+nj9C+AM33>pxN2UbEy zxx<5Qx3M{=G+>uZOi{3mNl;cvvz;N+u4F}+^(jVQtF$jNs2)F~&=(EC93MP>PhDoG!D;hVdxk^Ss*OL!VcuFoOy=Qdu{=5y=TnDb z8{udYaMb3pgBqYHEYw2g*V~^L4={{lf5P5HLE229c#T& z?WNJ_ghH9dhhrwrTVIv^`?{8bs42SH0vG>QM{hj>SI4}L8}@P6js0MOWEu4}S8jGb z5OdK-u9{rCkQWT6oa~%u$0F;BI%&e&1rj=$&yO{Ht&uiOwiYWK^zpZSDO?p*NZqJ> zd#Qce6>)R9wwH9fm*hW^m+MlBDY2GDt z`j`A^PW_p2zaMdX*hHwSIG0_4PAOppTj=Or2D~QAl;L)Nd#-7 z&vBtl%H}+l@K-muilp`yf+H(hHOd{#Bw9RZO^vUtqCeoDz4;W)!C4(bu5i4<<+Yk{ zuWPMB+o5=L2&m{3LRSnTVr%t-6;uB%2u2f;#cNA00`j{bDWA~rY--grY{5>m3=p!L z?KaOVqF^%9heI-qMas2iY4|#T`q0{|1Ri)RF_s(22No57J7e9LIdt%}oUf0IL_~c< zRdx@j|2IKCM==L*XD{;xq8jFCNB{HBBW2e9vFBv5T-P9}-DOssn=hJLZOOE+T7Aus zqokwjIUgp2O#H#uXYuvbc|hqeC7M(cUGiyJ5nJrUVy^dD7$n&mH}F2Z$whp#rP%?o z9LUTsbb$JaDlCNTpZ@@^iKA%NRwAV2uCgY~?-gbSUHC-hX}=(VibUkkZv;*DKbXqnp|2{wRAMR~a! zj%p%?551fm;YFv51ef(oiK1_^%ECrYyJG-c0cQO*4za2UT04vuY;2gShwzRhO(Y6% zy%~6MU`MCSYWwTCPOl%A13fySlUfk%xxiH^6{p(8#e?ad(k$4$e4EI>RMH3%^F+BZ zV1OLOB%W!46eO`v$O8JVUP8mr0*O~|@qn~IXJHo-oPQVL0akhDGj$-ePi;>8Y{~=! z3#LypHX`(EkmB}wC@7HQk6Jk(35i7TD(+iLA1NFdSr2V)O3vp?qa&d}X zZ{zn4B-ZBN)(**+hg*}#+m@tglgj15B)0*GqG-G_+JV#MZPiqz{NrNiCr{{!ZQX&< zX-~C7*GDOOKi(?}itC3JztAG^>{i;BT>nVcK)(?kW<OdG9-C5A`HWR@FL+15W!Q!=5)Cz z;+I{~`+ZNeV$nk-CKQ^l_aUGylI5e2IxPM4aKZm98bAeD%WW0Ug*rlS9-2gI)=&NI zS-0Oa7b|TxUeORzuVVI*>uK(l7QSg^Q2?re2BRYnZeiKGn|qO%Eg)ta1Bk=}J=V_a zr_FY}z<;Kk+xvoj7`q)mgs2J)Y`huo|EN3QDMCVWwh}>vyj2E}NXf;4dM*!R>p6|k zc9r#IQ80_n0<8y#`iSM(TNlwTVvIKOO^#yEA0cgA$hry_?CkuDS<3O2ZtI=`h6qme z&A$$PQG`8i8@ji@#7GZFSnmt~I0GILnO3i%25U=22~yi9ZJ=MSxU2V=>#pSiAGb;q zB4I}$>s|aV>u@N8hLMe-Ho5Aso9phAy!n454qmu|5*&PWD-6$A3Ep87j}CY*T2HnT z=;G$;RChHr9amJ{g!l?hbk=zApe|IQ`-kTT8l_pJ6_R{c=A6JYak^yl5-Zx<=7SbC zHS4v#H50dVTF&Gn@hYiQx4)_K-*mlpP3gUTpK~`8mEPNA?&UeUnp6?WZ_{7>BB3$G>0n%xaRy?@GJ%R> zTza>eP-D!N{;ZTu_@UVH?axngnXpP!Zm+@|-TLTC|KtGqE>D9@ZU48Qbx3jDe|Riz z{15Tm|L?n4NG~=qsS(M1SZuGi<9n%UHj~b5t59knwn{XN4ny5)UP6J+^;aTD2<5H*|#Btri;>*MBIeRi@xy zabrrl74J`*2dem5)TNGxZr4i7+&Gavlfw7($r{aMeYPx1O`aVZx#T@>jpW=fDPnFl zxZr+{x0-SG6c06qb%AK)G+oap7I#HSGqgUah%{`ZhRD5}H9w|FPs~vbA@m#jM2Qne zLE?AXLu#JXH`-O=5l6?iQ6o>2lqlS9-ds-}kIy^tAWj6Xrd-w?C|PFD4W>jNHdZ0N ze^kHvqKNjt@32_s645LWU8I@U{>6s8zPxO7%!aPlA_KYb{#gjg*pISd*_A6{k+KNg ziy83MTzyk&mfL=_@P%j7*2L;zrG=iV@nn&cC`!-f;=4-iy#nmrfuM&D2<~m~N%(J( z_ep6J5tLIcT={d;?GK0@dl%Zyi`qaVT+~b|Y1W!!Br#o<^GWwyNPsl`;x44knd~GzGisu_K9pykc|PQ>aOWK9iIWJtP9vsHztcZZ$N%>t5x3bIt#mQ-N9SwE z^*D&}3>lgJI`e4XZv1CkH*JTP>%Di({FaM;>wJhNcpTom(3TDU#kp=QoT=TpVQ}2U zzJ_k-4#1a(+f$~5v0xQOj_aUW<_zocp=Y@-xf`U-&JiLPFn>8Gz|1b>Q>NVRY^u|? zlvXppu$O1owqNO6SA~oDJ{y-C$hG9}mjz%t^c->M0j?fWEwq>|d`&j>jSU*1cRRY* zeHrr$wpw3<%X*7x2rGl!nOrnAQ|I%Jm#tBKz}@z6=R|5eK!*6I>}~Fe$n!;X(_Xms z*J3$}!$R^sT4vkpF(4q+~Yyd~e0Pp+>7-Y&jjf1@k-TUqMvppoY?fWKO-2 zW|{NMdMfwLc2f>*f-=8H?z>st%fM#!=(ByUQG_$4);T{{K>*Pt30{1pr|>B@ocNh* zJtAS9slfe^EIm>=5!@1>FuW8Ba@ozL}^AZQqiyT zEXU$Zgpmb6RI6zvwDvXeEhV;CccO+~pC5VXr5U=n1AkE)5AVqCK!^qrP z&*XdT+-_fA&U5htC9GI*EEhMC2oLoh@Dk?|$gbQrK-^f5p`ixeN!OAY_w58Bz>-dM zJd8l9>IMeB&_?bEZf1ZjH$@Lx_>glqQ#Hy7-Y%rH_E9h51n8KK_}T&ZYTf*m?{>mB zp1%J1MMDmQ$;_?&BFu3&mqarzF0gpFtC!A!EeLK`UXHm&fJ~*IQAtaekJnHN#BCZ` zczK9t^U6I-wSrd$4dyV;{=~**;_^(ZsR%= znyC>mw`JH!jt}Eubt?(&?27?LH5lhFMSC*sq;;6LnO?1%dJbg?^t;K1BMid{M+a)- z-Fiw?^B>l4Hm*d&>S=n$A`~Si2sF_6tIjh;(LnzCB~?Ab;H-;e9U^m6!(T(gAFP_R zI@tS|Dj6vB;O^~L;18!2;%71#g;Lz$78nbO!oMzso)JR;e)WW0FZ<&GnFtr^gN#^J z2M#S^Y2HM}n-}&s$sDUsR-%xkCx@K4(!Rb-Ky*Fq7BpvY%la!TXJ%uP+;xWy zDU?YaPi`EMt8ts-(uvG#c_WO@dmLl=u5tdQSV=*9vcf*XdP@hIuUR2%vMAD0py2cL zE6oj85^AhLhxlD6vRhFED^}p;&p8$w@T8rg)$n7SWqc3Ut`eV8o`t~3AJ{V{lUoW5R1WttCX9aWPKm$uq9O7);IVtIdW(4^3ixq)Qm+^BgT{Q4cLF z@4DBdu?Grw!>YH!yvm$(-V*<;Xb_cM5dTy~-H6|qMstH&eN=_0_Mpu75hr2g#|Y&Z z)dt&uZjvWbopyj4rrM$a{pr&Y(%yxCBw=+{^ERAOIhF((}GD;RSySw za6^_iP+QW#4cxj=Fb z^3)J*P2f8k6BrIDRwdnz#8Ir?CXkv1jrtjz*yYf-P5kxLf1*x3+2O;UKN)RhbR*+S zZMv6Z6JOY5O@POh!j72;mLDFAS3tM<{31N~@>Y`#ef2tLp091{r+1R9jYf9jS;i*w45WE3%H=Zu0)jNPc`L&@R5;) zK@IV5Qv;%lal*A<7dc3i0^9!^<3%2|{5IWaREhrfbv z;sLnl;+=5r-Lz)0=62Ccbnl21wT$MK2O!A5PW zRVi=9_C+hiwrcuE+5%c(IBP9K{l#Bx7Aqht8SU@QMoyj8u`W}at{g^8VQ${xR4a{C zYHti38vVH3YU-=1^Mr{i&q%6Lbu~HpO&2vbL=<@%9FN?C`k)e@#{96*__7G{ zx}@3R)2DCR5$~?YwusnA88**l;kukb^ka)-qi?yZ(sx+;NNj$b-E4c^ahAq*h9DBU ztqulN83|kq7W0Nf_hsC+{jNQxGO-n^T9}pSx;6(0R(Dcne#v60;#>3M`Ls0e4=Ojm z7T@^um(N{zIDl258|l(C`SG#uM>>Cpq`py=#h33v7EcYi8sUR`t|z5y4Bz+B70aX7 zC-d7U0OgW|61Fs;Vqn0*wSB?_O$4{~Y^yn-Ym8ZgW71f1T>ayK(W^WWcPd6c2@(!Q zzH?T1nj%MJH8!Fse;B!Io#^^bVnE>n|6+Dgkrwy8Su?VCC{EkZi``BwE-x;~D;9rH z-H!jb@eXQ1Q=mQRB7T53D8VgXE--2AP~jT*x^qKz8gG*H1%*`vEOS$+umrq$Gy)t_ zNe5O;qTco8hFtc|*-e*b0=@SAX=2PX$KJJMa&cP9rC3$v;Trq53Im@83co&c!3Aa3 zhaV=0pY&k)nw@6aP`_2hcJ>bn`SlMDV%FBI|5Q2l)IDdB(%wQ_rv|TOc<$uJG2w5t zJbLFgaG|2&F00UV2+0d3YZnm9#emhYE}um!ME_b+ylbhC=8bI|$+vi7`jg~)QhDol z3X*lCzV_B@YBrB}B4;si+s55XScW^Xx?s;+M!(@)Ut5(re=q^z9yd?&_swmm69H26NvhArLTK|O@>@+r9ZS(0%tC5W1 zdRZ!6a<`9VHS83A2OHd-E!T6dkN$gZHBuw;=xp_(oSfY7F<cfPhqV4fK%3gcHfoCnvXchVc$TaBwr!ItPQ7e=LNOJT}_-qzgC@*JkXg|Ze zP`o^gY`RsS+5n(HFSthtNTe%Y){e*nF{sYW!vx9TsOJ3|_BKI{={nhi`E{mb@ZMA7 zx=!7XBBPq+_TOBe4BxHh<FfKf*}+5yQ9l&6H;>D1g7e|Z8OQ9 z?1w(zeA0QqAh2l{YwKDhKkL&ir?rk;i0n|LoSCSsb0N1iXcvna@}}D}02i0}C(eZ+z=4?@44h5JoKqjTqm@7M#aOf>@yGN|UF7>I##;bY&iu0-(6{CO;B6_y@k`Zh!hP#BCnF&iM|?a|u!Ds#b#~ zWTK<*2YJOeNJIRHi4}({Io#tQCRI$7*)I2QtV3S+O~_O6y6a+xU=)hd7c392!+)D^ z8NBdux!7yNCUmvY_bw1+5v9@*H^#nDFV&g-G$v)Bpub!eT`jqaNRH{$_s2SokC#Gp z@f}xkL6hxbxKykFQNcnIy~MR%Ae>Ux*Tw$;rH;|xKk{hFgvL~rc7tL+;jU6ov#d~osEMVZDaSRFV9AG_pSPWk#MPz z;x(_BpxoV6pdZ1V=4hv99Y?!El|_*ve-F|%Bej@=oqXws>yy@p{A2q+JY&)OR>PBB z;P0O>U-pVivK^}uy-q_%w7$bjREdi;n6iVu+NB$ZzUZH#-(W9poqcbuCdLZ{E$gH$ zZA4$G;r4?j(jj-f23qCTi2f5($tzKSaXbN~J?pqk_SI}>4tK>+Ir&V;xU@DY+-N+} zOb>%vx9QVVIqZN@wlnNpzM13VbK!(6*|VL@oqw_9`ho_EB)z>8TT>?dnbtRoF~hrA zCF?fDG=cj%^Tg#YE=@tTtNkffj7X-DdhQj~D&-Q$V61L7CJcH!_)2V8{8?R`qx0Ka z-x9>_P-ZYpZD-CyjOr)PLn>UEStC}u$aaoe^m-~oAVpI?ski)K$X9KT#gQtU!v1>V z2oN4@#~u5Rgcj8ayC?s!VB6TIn{oA z`V?NiHOO&b=Hjlw5E4b}Xaf<-Epd!I?~_d5KrE$SQ#cZr9S|%)fx+2&g zy>egHDw#{Gu|4C{!o7Q)t}^##dUgp^81B#b2SmZT;&d2sCG(-5G=pN8Ns7aD$qhGm zY`~=cT|%7*g*(w&THbSceclSAo28%M!Bkv&DfoAqiBwH^2@{Rh&>+^2$yyQg&zI+g z=dR7=(p{E1zq^^C(6{lNtC~#Q%)9BeS^iK7mpd8R1tLfxsw54Aj!PWx=mFF%N)algF1R`ug}t)#R9BblqJ5Qp4)~Z1S@r8h-(C5 z)^%uw4E1D>wzG38uXbmW@%~&DLQ=N9db-BQ)5STAQ$rql2wBITftRy~w|CAis9Y~d z43Q=uOY8#SR#UvVMEi8M`1CT-)3mRZmNBazO;kMEj4ol$eskdgT`6n`>9IU$H8rik>c>!UkrDMPP5mPyt~Z@5+21xy zkmuC?>0R&}Cb-vK#<6pylMZazC+E-Jj)voFyo+Pwr4L9qq>hWakoS#o6#7^)#1zo7 z2m+D$eem~b^`E23o4&k)d<4cr)ph1Dr-K8Vs_C?2`QW~99_Ae`xMnu5Nr7-({zb1(SU=- z>~s-@|A6I=a5kPY8MiiKdzrKd%TP4$BgMUx+92G(#z0|cuBP%m=1+f_4hL&Mt@0@( zRee8`KgF-km7yHc6lHKF=?4}mN@JISw#`ym0_FW)OX0m3Is3FVlWyc|tdDHmTt8v!Ig}ZaxbCwEhs2N)=+qP?w->m|ytpHI<|Lsf;`QA>(V8kKBKb~JBICQr zc@_5yNt41Op8lI{bCBzA^1^6#Sd;_^EozTa!6i$zZ59-C@x$jWkqD-;vlefEn+!hB zx@b;gmDsrM2Nt(?+W81$NE(8O1A=WUwten-(|BcoB1ZX1#6uSkFBktUVV-DxXkmR^ zo|h{#h0wd(*YX#q_$S`(R`1eAF13gu5Md7^maJ{+&ShGZGC@^Sp~NNeqp2zj+wAw>pE zLL|P^-C&I3Pu~#4BtQnI<-5xH>dIgS?|~L)TQTcmtO|7AC1rThIXuXVs12Q6e72uU9yXa-d}=$D?n?I$a)uU(*Whh#%5FXL#5=dF}4@CZ{^qeZgi%IZvI{6M7iOg zZ?=x^ooV5WN^lOHK{T@?XGQtY*PSwEl%aPDm9JE?d^o>5AJ=K+UH_nDi5Z}c6=r(q zfv}|*W}`XC!rHB4nX?L`=F#u%+*49nx6!RNwq1scqIjz96P)qS7nnp^Oc*nYbELX8Kb&W19mZC>$kVKHy| zB)a*t`ggb+1Y);Ro2Ojhz~&OAD1e(YOV_P7Rb($Y)veF$WJt6!KwObA_1i3dX|_uO zaw@4<#P80(0PVxp*qv;lwcTcq=2|t;Dl?ve`c9ztnd6{mwr0VVS=W z_WNM|g;%#t=nHTVsC2L2}1g z#a)%OFj#0ix$7*5y%kv%!>TyBY?7S%fY0$xr^kSxtUM+#+^t#kO3680qkF85fkmh# z<)gd1-;uv?_?Oa59+)3ADG`-5D)Yjfl)EB$iCUXVkzQ>;Sgz| zE~D&+CJy2NBjl+XE2-dItJkXFxTmNLnkL-xdK@Bvmf~wyQE#DwwS`TM2RcMns}UY; zBm68LHzPAetID2`$nr)AewE1iw$=U&644v$3QceT8B_1=Z3dn_6j9;2dM60m;iAR4 zp(&%h(lGl5?$S%uzQONq$1|?ESKUr;tnvN?qF=;D-!FtH!zXI-9DNqWyqHcb5;YDGL;jyU3w9JY{p<^w@=6LD|Ah;Ua9do?yP zN?woHA47;rhhr9~8gx%=-L-%Z$WL7#@ic2dDdo@H4|`Z0qT7XfyImTif+(^x;AZp$ z(b^f`OK>9d=quX21CLq(wLF@v`^lehKrKt>c4p_Q`hiOP4x#5VJv@jPVhRQKaXrMu zhvnlmx^h@1;dMi00&OjbskqfDq+WRM_X97Y?UTDG@BBMG|~+(}Q& zlF=^Wf;60z{wC|Tn@Vr(`-Ly+^!8G^ag;qIx?^>Cip0Vr6n(~ttA*)tU%F>sEN7S( znLu^kV{dL_w?qftF8ITrZWB~?Qz22Ecu>l}r z&bRMa)wgV$Sn8KE(XS|zy%+6Yap3D1>|lTD+YW9f_mq!0TA?9Kao3st4R^spz~gu+ zht=D7qRHZRc~!4CyKZAcvdIgfBgFpVzuY(SRG009BH{RdZ zBM(Qct#J!|z$wXjx(f-nAWuUk7Sq2UX~DiSAIt5Vn5iZ|mNERGsi;TJ!`@)IW7n}_ zE$iZRE8Cbo{binnu5;#U&4Rv?`TpA1Jj|aeCnXa}E1DN?E3K+9$Na|mU&%p**AUT? zNCsPj=FjKGnuSO!y2Sx{l?hyezNW=?mD<-djn9;{WH-28Q@G@`L$QdS6|MkQ>^||$ z{j0&ao)CsP?7lqcW}{yQ8@-)1j>xQf_0>dEh?&PJ!biKSbYHvQA4G?LbzRxcj-%-| zdxo_MZot=Ai<(o6PKSt%QB&oTj@W<^nUoz_h+S=Rdw`+D^Qix+M&-}5> z5fl+{0@Z7Ow^HLhMc!$)%N20L`PC(+`6NAMuMu*4nvnylEPmSs%k3{8Bf2?V66AqD#`yPry5-M~c{o&?o*TXV%V7!Y zY(gezf%mxUB74{!E==?P58B={s>$dJ_Y5LMijm$4RZyDr4uaA|iYOo;L`Av*=|KWP z5RhI}5D*aQHPVq5Is($0)R0i5lPF+>B+mQ4bLZY!vu4)1GxyFX$_Lh)aB|K*dq2{6#C0 zE&M7%8DiIinqiwdX$2Y`pKRJpL?KGD98N0w8jnA+95@E={|R23!9UB;_ff!Dx7b-J zN+~``rG5VPV_Lr#!WY-&V&U$H%Zrs1iP)S1s&N}s;A5t7xl8EYULYTIZ; za11z*Jv@7eot2Z8Da!Hge$UYVfI6Ah&}$vV0%z-Q&5UUvhnh<%Zxt#qzSW@3xaL14 zpDa3P-qS|5#RBPDaE9}~jOP0fSM(#LazeyqryS&Ien_!ukValDbhv;doDHkg?c z>TDYG^1^L*-+#~JY=4Bgy5h4D3b6K>Rr_t^*3rDs{;Rb?3D=v#O#^*DQcd_SHXNg4 zS9xcTy-@5i&20+aEEc>M77T>~_Oe%qE?C_rc#xV*VU(5G9dUV#W~7~+;iSmhU(o_L z2fREnU1zb8$2lmb9RsyAivW&?-2m;p3|%5MJBY$%TKlgI~sODrskU^<*x`CoFi$dAt|9t6uh?)uX9l z;w<#kXmSmius9x971!LHW76^pW(*J=Qxcwv2We%%iu{kDMap>F{rZb@I@&YU5R1Gi z#nQXOzl7<#T_YZ=>W4`DMs;|dm3D7GNH(%q^a=hGpes$FF>tlo+>ZoowlfxS|4%mC z|Mq(lK-7sWC5jGEbjcr&ljyp1_-05JWhtz7-{;P(tC}-efRVuC@6OQzky7ui;Gi!& zKk1H3;^R}d65@)lf2_08P2H1Q$Ul9nQq7;wh_FmoU)7tG`*K+wV8M&3pUq?PX>^^@ z97Ag`)d3Y9-Z>?*z2v3VslWu2{jJb`zw`!!IqkAfNZt$X< zX{Q+y@UdNPfAB14qve%S!a?1Qu|MRQ(3ry?>rGx~$)DS+xTv0#-66d7s=u=`Zox8W zy?g6@x147EUnQSc&<5{gTD&9}{I46Ho1S@XdAkX~GqEdgJnC_qN zKNk*0cur%!O?2|Yi(#D1Rpmuc^&k+d-_x-zt+(BK$EcmB@!JD<7v3>&ZVhyBHZM@; zS|zudWVPdXuZ(Cu#9_ z{~?`|bF=}+S(C|IBO3Du>sP0P=S$)o@aXS0syqIv@YzoJqOxh%hm?m)<4ie$>F877FD*2Vbk7sfwbBYPdh6=cf1|d zaVC14Uqk2;9fGkV2W-}JK0onu#nroChLHa3N7`eZ1>U2*Z>&H1e!YClTddZz-zRdh zG!gBkX_35oeF8fL*oJ64Sa-7TMs8cEl=^GxEPWN$YZ7aU@p^+}GJUI=|Bk9{&lA9X zF#f-ujx6W>e;8OmjqlwQWI)%WBi~{JbT1hk7LZeD+qLxT{-%W$tt9!Jhd%LI0`b}!5<;x7U?+w+R5I!OkH$QQO_K#9HZlF{+{Z_^naN%+tEa-JDMY$H`wiXOE_TEPsDRVMW7 zz6pxanil6~Q6NeWd;NiTWzb5C>;8Ix}ue5KOwIzr;0<=w|@xSB7|IbY8|EY??Z&pU; z?dc}rb?f_&FEifDB{ep5BtJ=g^XE4cS^k@7nxpEV#br3E&q=Cv8lmeJb~)c!h{aLi z(0%e{nKnam-g-6i?y>EFbBoDb`9WB9zD3YKQ28lbR_4KzZ#z&^gbf+Id8;?-9-g+e zr2a1FRF6?&&ok!0>&==?axQe!9IJp2!1_;;3!YL)oBby^k6pn)^N}p;1OE?2FT!kj zP&;D)TGcjsqWYd~rTuTmkbt>A(>c}Wr~4X@oF&Z(QJWnHqf4;oNL>oVhZS*)_}-)J z;c}HA=fwW#%5vJX&)>S9n?<3%gQq$)e)eViB$Uo%AgWRqv>@&0>1y9D3g*hklj}aW zw@-Kfcq%zv%x@$o;bcmt{34BeXU6f@Hav#;rnaAjt?{-0Vbi@5^+tvodCO*vR0k2;+lzGU0P=N)*%;UgN%cpypEz zfH5rg%13pt@I}6MUt9@kB&GE8{R45jpXM<(&zunbWS?ERBTR15JM`{jSXQk z!GH2;@?0^FsDowLX9tW=I&cDZej@bzSDM;||Ak+{{|(oRR@0HAEI=Ai-Ck@cIQrC= z#ogcY#ZFMO^8lx`TgEQ*I!4~;`C;CZK_@O<`6H+qiIM&JD+pLhLXp z2OD%RRu$y~| zF7SxNHp&<-PS|})_m>`myi4kGTQ-~sWs7j9wvQjle>5o*P=I>0%SrG^;vJUFd+?Cy zxdLj7t=WT4=qGKJ$60cIrCop7PO!X_y}7E9l5Cyf-fmS$QqC|V?8Jb;V8 zJa`(a%eo-m9nq4yGd!jbRkebEfxWbay}}*-}3(7S`9#!Y7(m73Ukm=yz86 z@rUT(f}Pe^Uw@+;GrqkNpEBAk&189c0WqHE2PC{z04=9C#9;i-e&`k6>4WuNUhC5` zSkzyj&-^Kb)N$_MP0k61sg1n=)D|#akQd3HFDr%iUq*K?!XQ%s}7-*XaL zMynbf%$Kk2r*UsRKiO*yoq}WvrxRdbRqcZ-mjh3_s8#DmPVuf^ANsX4`a2jlcDyvd zwR2ODY=GE1S0^DYQg|)m2MP-E8Howq8YhRZDt2K0r-e+Xi7Maf{=PU&w$^;NPaR36 zHY&(Lq~s}*3rQ|`uA38yr#jSA`!y$yUI)5j_A#G=d!IJp6w{x4kFijC9NDIzcoSl9 z?{3CJY|_?$lIs~2<-07^#okUZj7*-88T)LG0aJa{KYD==se zn*UtuO)|pnG2db4J%7;HG$V_iSsKz1n?km{j`8WT8BwUnaE?$HJH8OX89z9MFu;LUS;I0Ceu@obRQXX>(Zs}Q)Lcd=B}k!d`o$tymDco-$y9MHXEllEA}Kc(Jq3? z=w`?#=0zzf+xZ4v@RH0{N7<4`(|-5uOhqxthsRVOU%lON5?@P6b{l{~I)xGJDR+#k zN#N4$`N`dDzFT2co|El4h>i#$vyWE}+SG9oI+34iVOl2GC9?UtLG7%Jw=$!}$=u{v ziW2l_;F1gJX64*sbo9pb(&D3jt)}X_XGS*eKTcm4si+-cj{gzApC{YU#^Vq@Yw!v!O8JA zfik>3TfZ>oY$41c;_Wb@SI-u%&b{@X)dY*#%HgGOhp~j8Sa5W>EHOy8eu0=VB+Eq8 z7qj}}js?{VF5ehy_{igDH7_(Q>8d878sXy*$n8ZiV)v!Ae1?+M~Tj7r36V z%SRq=TxP#)1`1HJ-711MBl~s1JBvnr`3bt9MkozQa;`?EAf-=Xx2c&+rPfI;c@_8D z?15cD(!#uE&gMAZkY$+vI#+*69P}dEJtcNAxh<6APmkQ2^nPrd@GlneDdip0j@<4K zh;fejvl6DDl9gqCZ_v5U|LqAa#nl%sG^HhuJ-FZRB-G-dEoa!6{p-;6yjIUU#)SX; zdbtu+qX8oS973606(HAy^JCyYjiw;I^Vv=X;z@J4N;sTx%xuP`;MXZqO6J^%mWv9J zOMbzd()f1lnb+Q>P+=4BPk4$wW0VIUtnc_(Y zn+D$3^e*W?#vvcmUZsx;9(3RQDfTo%RkCW~Bv)|$uExsf@s*wKi!qy<)~|)PSDy&K z@Sj&JTbncJtMsj9yBM&V%KT z5mbLOZ`g^5n zE-&Zn6Cs4raK&99c%}i^PXVp=c`QI;j&by~&b*-c0z*I*VPivYi#hp@>YG!XZF1rCxDZ7%HFg`_)u|5E-t zTU~#xDa0wv$R2bi5>FxlWEYEbYdH9JJ0Z3YybuYH5wh=E_?JEM=#-ic)chb*$XApG zvr-CCkra#8rZuNE3o8enXi$frn6s9|h=aU#Q`Jy?Q-$qpNXzu%F1@+SW3lq&qr$0B zJZNtll?yl^D4SfPn zXh@|J0gJ_Dgc;s2ngH%m%*o~Jvw4BBHy&wBy#FbXsr2y67*FUGgBNH4io9yK1&smD zL6_09Q(@-lNalEtSr?K>jOpni>ez zqcGh12NIL&MW1TGeg1(=X+oP1eAh8-2sv`LjwtbWca`(pagrd;)Z~FnL0VVhU8;3? z@87iWzaezRflxjj2Dt6|`0M?40o-}zlBtw{`JjzaEqwjm_!G$tWoK!>nx0;!3z0_p z8uKN4FJ<52%y|ESdKXWMg3nybFE%yX{Fa1oMY>!Q^Dd19N>NQ7Vkn@0AXJ>)sT(C5Tta{Z!ry4kOpfAz*l0?4R!O z#S(Sw6w=-C`q<#Dj%h31#v1f#<%`AW#Iz-ORx#G2ECC14Q_XAzou~xLr3L(g^d~$5 z=tXMz`{Q>Pt<$t1vQ6emo0WePo)3$#HMTsaPaH`#40i2IYA5HBSjtJyC&M*7|8O;* zp<(rj^AIa?V%%^z&yPxLvLCMgr4SSSRcJ0US6fsgIuOBgx~ zaL6k3l42<{oLsr}R5V^)B;LULUT)7C$I@@Nczo%;?V1_DhI|8jh{xH9rNFQYZ_{y+ zGu3`iHEsCJrK4cwVvrg8z5QRyqO!L@_h?lTE$JA6mXOel^nngN{OKaj+C;A13)@m) zbyIdPNL=V;>YKrBseyI_Jg}z^rVy_|5^=j6=vG|*5 z&W=QzZ_8b${Vxy3No+aT0kqF&0{}8Am)s6$nq;eM8sd~;E)wV9g(BNa>_|5j$c^ho ziQ8ijp4e%IITRtd@tp~T!aiLA8E+KCiEuU3t!Vk?5l_9bbZ(wX(#5AYH)@yfCem+z zj?k3}S9i}oNtQDru31EfvrcbLXz29gTxS)cVpt&>P?q^KAaaf)%QKKt3o-Dl}$#Bf>Js+jfzq z;{E#8Ut16a*nXKi1&C~?UdY%N;ZtakD}J@Gz;n)W31HeB0^&EXk-yMqwyL8{wU7Fl z_J0JtQ~0?4_aOMMUTy$97vQBmiZ%fi-!6eQEt6A1Gwq&rwM-stHmWz%3NvU9UIr!ce7pDS zW4RDn5r4F{8jWA-UsWe0zpwPnj-F3Jt387*TGEGQWs6y^r#E%S6zEo+-i5eRiWvIppwcFQf4uH_$e z;0K0Hzmn7oJM-7W6qXT-s94@#j?>ZHw4rQq94UBkR+CZGDVW4I-nR%&lKqd7nv3W} zP-ceM6Voc3?3NAv(z~@dkNA>F<#cputDWD72Ke9}ByA_#Hk!6w=MQhjtAfQL51yI3 z{$@&6ZEcsDjQC->8&|GeQ0qs;;h;ZMdpnuPS>fU&CUSlwBUxpAFuTaUy3G;uhP7wS z!n<1}o6j}X;dW}u%9ju^%lo4=&1H1kN#Xo^`CKUE(+zW>Ql5ok3!7bgj&8!}X4wfWP{K^La9(!G8{ zf6y{>*%HkNnbr}aL01b;QC|q2ei?_IAOu;)7pqi?}^2wuDcF59Sb6;OQf2}#YzxvBHw9PEs^D1o~S*w z*B`1S_v|#TX;8ne)sTy;Stj>e`4xn&*l<_+!-y`Pe;~Zs5UP|M7tW8*oq(KSopwH75$EMXU!TGB$rz##mDQ z*TinRpP2m)C3~L(-}47>PeR|zsNF@{&uMRCLcMae4g%@Ysn*iE#4aBro@UF~QWyXh zy@!ptSnEW99H*zMZ&XJ7;^B(S=OF4-UW4nG)&PDG-GIe{Y8RRd;o(Bi8F!j*r&~{8 zy#GuY&4dYyIrMszape)MiD<@+zElRcrWYVC3O!}SiHazUV|E)|7JCW>=c?8F$AqvCr_ z>#rBc)_@|g!ElOPv^{+W)V9`e&gm`)8}o*WiYmeLhDGTRzpDHwYwHz3<4ryRf%gNe zMnaKPf+wXv>^y8Z7oBn#mhA2NQhQmM#C!(|?mY-%0D&y&e*Qej@__XDBJ8`u^3;Hw->F0S4oH zs@Q>Ft*tWBG*Cem?c6udm>XAv{R8cUa*A{v`h83{8DF-~C$as+7LHc!tX?4uCXzU? zU=|CRfdXt2n=R*}Qnl{crm;O2Jl*N`n`Cy>@P#r^C<-u-xPl`oszgO+JlDO6==|3W z0TCXx3*RQjOGmu&0V^FM(=Ig~(etor3)7-_feN@X2;fz*Zu^Zm@M{Pc(ydw$a*>#4 z!M#lp$e6YWPL}a9pIIK%F2ZLlNx>Y4H@q*hn(L>Hleowq!dVe8a^*jehb|Y%VN#TE zn-_4@S5-atURa#s%9wNtNfeH3NW5^pmdEn4#zvU$n%oa`cQ^;(Fohs7kf%g|_N{pJ zY64n$i}*(6&R8=yzPn%g`7O&oplFSl{A0Ku)1T(YLTR<+@FV?sT7-_h!7RwWm+ic6Qr{4xAMW(NeU!$#63mmxjnlCysfcIfDG>h>O(Pxqb) zCWL=K&Gycl>$&wJJWKIo!Sx7m#iw?Z*zf2rG!;O6RyaOmsYFBC!!4uIh05?NWqeaj@4myrh@2f0mek z7`!u)&wP6K>c`4iLau?J|za^=fo}kyQ!}ftka) z-{>b3dLu*){n!zu*Nt`Wk~E2`1qcmvI`}O}S*jaX-UvS8t1ok^^wu7mz4vwugqpfe1h3`y zqWBR)#6g15n(}IFNFcs>5EY6`0^2p++wiFOyl7PBQCIuTko87rVE6E$nmX(gPQM8% zQR}AYMaF&#SG(CQqq$Bo&&-TqmXAeWENI#W*3sAXx;KJRbvi5v0epTp>h+miHwxS_ zQ2fa~sLtLnkd1%ZjJ@Wt2bMO-=N5ADA}CoNDgw_uWd_P{T~~l5ORej6p#KkK)+4p8Euv_j*Y;FI`CN#>O!a30hVI#&LYBEb1H)S6l z;_kn}Hosy@Hy*63D3|zQ`-(EFORr@?XvRjPqY%R3i>}3j^~I|RuL9;OQkNb{nLjM@ zQ;N9#=uOP%Xv#;bs9g+ur@%Iblfn;>LNedf$if29Y(GXzmq%Q81bPfK-ud%s7#Dnj zFDGj2eFBg14G;@~OOasS*rd{e7WiDnVYNHx_ezN}l9QZlxn0|5ai*OWNawq;cIDxw zGhmv&_Ed!Oty8o;g1UUcGyCEqvaF4_v7%=B$G$5M|GIK+5wcq+;6JsNiv8tipfJL1 z<(BMx8H9Pkd~op3G4#TgX@k5nAFOX%ay$TmxH;U`je0Q<(i7qczIn}V>Vz6U-UW8X z+^f} z7(3kh0U!-P>#z^egD>jj(TshX>mgnU5JbVwcfBx5chgwOThI^#WpGHspHx^*W~+D<({mUg-t z>iJO>G~mAeZvzF|ZWr}iziJ0A)8oQr!$$zaaXCS*_aBIBAK`!l)4=QX>R>lkw{7n& zHEw;J`n$EbX2SmJ?e`Jpwh(o7;h+eF^7=SGF(2F9hg#YjpfIMb%^g>>b^CZJA;amy zM4tW5TooG7J8VSZ#(yN7KC2@qoIrS%>u00>D3bsbFs`C!{_($fn-3(9KgHb^R!%0+~@80X7y*_ zU!*~G9-9-ng`;k0eQcjGMT#svp^PX0KvX1cd|*Z+YMVE|XGzcH6Fl|~+QH0q6>{xqpof((Tb%XH z7f-u4BrPBEkJ6p;6GMstadEa`B@V;B2UrMGV9a^dI0v%9)w$@7HrjZpkVKsalCNKU z79F7a2DDphNZJJ+otzU&<4oI=9|FiCb9|c5q#sqOY>OsxK2O&#5 zZvQ}4?gZvAD?`Fpa`jIfd=G;v67ycrgh#>M^qTO^F~|8#cB9IpooOC4AN`hZgcO;= z=afCTX_)r8q;K-5uh{~tUyjzLh??bCifG?5 zd!MX-BQ0vF=CZAC_XrFG1dRcj6yVK>gw|Vh>n??2lip?e1EJ4hx&vn}Eq@!Kmz6i# zN*Qi2ol3AuLDnFO&r|63Aw-G%xCRKXBW1!#4&QhsrY4w;I!@6w5wrWxE##2eCa*R$J2iCM0yxH~ueM zANq?=EQ04;fn-YLIoI{%I)e?SC>u9A1ht{Bh(~wjtwb6qsf-FW#R)^&9{)1_RGQ7` zV+sDMh5QE+k%-gX=L`7<`s{?3L_S5o29j)QI?iPgIVtq^BNy~|y2pinKeFgf zc})=@^5A=c_xTb@+&3_|2<}JQ+??@u$~4m^t>~&@oQS^P;Ac63GU_Rut#O(QQof5S zhkH5nW6)?g(9-KRUnJdX=EhE2}IL$S8e;T-PG z;1CaNm<}UHo&m#eCDY%-!wT$eE?+JU_-03~>voS{AcYeBD-m+U1Xu5dFguV8&n4~l zq3`}(8#hdxy{*3(xiS@%6C8kHb-%stAUN7drJi6|Smhpm0e@Otv}#d-kgtz~QFp)kn_ohM3<@-$Ceo`e37P&8rtCIML@vr8abo z0u%QLzfZ@fPLN;{12GMIL`Tx9B{u%t{sJ%dMk(`2sk<2(CL9iM?#$q*gy_E;IxuV^ z4Lj8k?0D25h8o#}CM3-syWb(XL(Yq55{Wc|?5W{5yxt-7md9 z?0&`-V@`fuxfKkY;^QTxAaY(OU-+aBUmgBWA7kj7ttoGtKV~z}B~)6I^8-HgHO(_z zGF*Fh<-r=OLd8wGE{YP+woQrp2WplBj;c2pZY>)iE>m+|#=&+!{Nca*nqWUS~G2m^j8arFL~nQ%#URZ|$x*)%sgU zK!x(7vI_(56!O5ZlWf<)90)Ulc`Q?^hi$mj3=pwLo1Gq+3@d!NZXJ9-#&y}^Ueu$X z-A8nQUk~SYV6qNfG{PB1`D3f4dV}hSx;+|!zb>|4b-U5z|_Pj8$3E5@$z|~48vh4-?y>16|Mcg zKEm<0f3r@eec3hKd|Fy7%7H;Z$TdJO8E(QrMfCtLzuGk5dISDATZZ@3i`( z*5{E|@l1%aH zZhGHq+B9jbNBlM2zU~*=qoAN;+uwh@&L4Z~T*Xt9>}JrOS?!vHtGI;|MkvD~(a!^+ z>)98Qwo`XlAN(%$BFuNI)<&%SF}3Os9c>^4Olk*7r^6P${F1*OLX#lnLKuv;G;~&( zPZSOvQ50gm1gqg=C?<$JUy0yP1y4KPx2l_L80m1npE*=t8)LHdmZr&wH6y4e(i|iK zVtXifkuV<(Jh!e1;ZLL-y5U&BkLGLrSC%2J9JT;hdWFXE_At0HJPfW6Nd|g@NLL>S z=@}t72}Kg%N?FUX#-C+c zCocTboY<6>nTy-!A?D*JOmF_E&ZXVC8R#-nlvtWfvdu&U&H-IkG;jFQ8KesgoF7+8 z@VYT_?F`D*HV>Hbl6C*`f_yL0{OZ&Yl>A-wB^WHmCsU+Jk}@ z$Qg~uL{+ED&5q0`xyXTLjo{Oa>OhtjxJ)$+7sKP6?7^U(Zj-`La3?j~_UpL>Wk#-o zGAVX9V>K=N&gdG&7D9i=lxY^7y#3EYsQ{L)=?m;nFwB7R$cIdZw8w@?Ok_Rwd2y3%A&1dQ`sFtzydD zDm}RfAmS){K>2+d&De0V?|my)y=+@yZ#`dnOq=GsuVv(p<6QeN8C?1IN!-2nBcSk> zNoWS;0=XdkDv25Ib0AkhvYIaP>a=_ z`ot=p6g(d;6F%LkFoASVVJ4{%CMN+0owLEL*t{}h!b90~3sH;4JkyfscT%PdN_Dpj zJ+o9|{=!jDXHhyD6hL*)rNe`Y55EdUm=lozVI!fJE7eP7ZgO?!taw+`-U6oFYV=_x zEoz|GvrKK|$^+`->`p&&fv&rn&LuGYHm_{7Ttd6YdWV&as^O$i*5mZGYs`U~!`-ia z9r}Vb-wUyR!kW13>#)N$aYnCQ2%)6gggAoVp2o>0CB0o;2Jpgw04Kkyb`}|(-D*x09kcUH8eix2Zb3GlYEG_RV2GP z9a;~HP`rhJJ7=xas)wt()$Qgi=fJ>VJ^rZYWyVQAYOpN~KV~VCa4tP!6ktG$&Tc9b zA{fOBwYE+_CuMyYXHJjFZSTLu`urllX1Q(;bGR15l6Y@Dg_E+F-$2(t9#z+lWTmk6 zuaTh!uQ`96&_nMAc1{=FG{gon90-hnK9xQ7S`0uXcCr)6=MI$b5DqQ=4LdJEK7w7w z%9u;TSL1tbP49x>MKl)t_})#SRPgNZT7Yi6APo?b1&pHy4Q6S^N3UvcX1+GS)ik;lh9w%6 zLZr9$A*$b(m*rNL#(^1eiG3+xbh@yOzS5u@ZJ$>rOt6TPsqs-dm%DDGsOL(RO9Ec; z{x|G0+YjEO%3lt53F8A`K49b4)4B2p;YfTI&ilxo=-+4R#ptDyJ-C>bX4<)T^I|AH zHS^Gz(H*kKC$JXYqTdIEFqmz>_lc-!&2<(VrA#|@0>7)Mf7>H+M zptc=Mz+hGTQuyJ`Sac-fmS8E)g8I%EFO>xL$;PV0?>WKW;?tj`y-$4JZQT1fE&t8Q zIL8jM9(*ta;9FWJ&vm0Il0+Vo@lQ?b6AK1I9DF8VsGeDrWhO7oYZK6Jd-Z1LcLD7Y zs!lCp6I8@!QR41AmLT4nTg$ljcgb$r1-8QbaCiXh1oi}x-%U`Yh}3=PEA6KE%3HGr zn0PG+N6}*A=iVEfafm#Z&YgIAQ{(&_)_y;BX$$2?m!rmgh!Q}>C5O-NgD#p{ zCMKW~b);qjrEGj-cnyF`*_mY=2)2_|{E;$veBo?hxmY(}7UxG;8uzl9?c(K~g)nRq*R6RaX1kUTjjx*17q>Ziz+!e|hT(o16Li}v9C6rO z>qg9F5BsH(ff*U07OBL?qudDRCFSP-q4diCbCTu%@%{g7whJ||8kSVoO5@S)`3v>H z*oF?l5$NJl4Uan4{gz`HBH9S8gD$P;ewY|kOf0&~MIZiD@m0F^(Lf&CWP9iuIk;<8 zBypq|9zXEYyv;z~{&4NICIiSg{(&Fwff6Mpdh;(VkeKkgiCP@0F##WJ z&8HFfLYa5w4wQZjW?oUzv!6W_PGRJcwT$Mg3qd&$=K)LRpY`T=KoN6m@a1e?A-=E& zr)|{7d1$YFt52ix%aRZODM7z!$DKQ*?)p%StJG#hMeqKwBsC6L-s`6Ug#U1*fTC_K zxw^{U6Urp#)~dtilI@|atubP0tGKW%+E@E7Zuvu&%hQFY-F_U1QtbSG8)57G^gh9M zKZO8P5WN%IUv{YP;3=rW#_!FnuyhmWj8mR84t*A`5uPEcn3wY8tH8)zROd$ccVzSU z0TrG{hmLsEN1>VAKklo$C-Z71&&*{%Pgm~1&xD0@o1MoZlPxog9d=tC0)s>eO6oT0 zQzigu4zPw^zkt&d9rn*R&V825E9BZo^PrgrM=X$;|Vv_SDnyA2R2fly~kaq+x20=%?f<7TiX^_Pk?PW1ubl;Z7A;4HKU5_mx3 zFq&a7Mz-nziKQbPM&oiYO$v`e=#=a{hcgypD=WmypY>pWTi7`xM^zxw7gJ~IU(z_1Q@l7N=B+X)<*+ObV-u+8=1={~jVeDzzrr*$4?yB6 z^n{}W?J}a*UHqTkoTgc&QE)GFh+6xsJ~ytlE$_gxqBni=Gxa?4%+Esy4A`AFqq@{< zF*(aCuzZ^m{KLCAS}+vaAUo6^$IY4Y{a)i~TFVPRsizTI30T8iLZLI(_IJY{2QwmAm01aAT|UE^(=<|6H50AV^Cj<2cV%Uv&y?4|enR zuRqo+#T0k9P1js?{$pijFVc5l$*7_>z8(F{s}nMTxL4AdgmY9`vYFn1Z+L~aSi$YE zzGBalxmpQA*;kJ9WL4o;SGNvZut8 zJ};=Vw0{kF+_lERK({^0PW9VuzYPZfqowdVZAikWYqQnu29BDWF7)QT<}Jo!fbFSW;M^SHOq?!Xu`~UQ&~L&Yt6b^%r95L+wAjwZGgM1Q35+e|<`OnxR&7{Z5lWDkuN3 z(EL<@C0#e9d2l}#2U#5H5oDbvaa7uGzx)#$sLoS!Sd<~I;dm^=d@MOJD9V*ek1x9T zn4uOlZ*lG%J`#+9AluQALu)d4d8z0LN4t5MqD)4OS^GIYOor(aCJ-CzH$!urxm z^QVol0^qgS5mfbvZ_m{z{r89tr%0AjV2h*i(6CO<;~X0VvfXi`~UaP)c;?(fG91(&xA%FCMev(d~zSxp40cT z_6t&Z0nzfgwzV@YRZ_D^%JUwTkoRK~kZr*{4-P|*?70_)t-hoASLr;3Y1i56&A=O+ z6|A%&UE(r$nDD6OTQ}WBK}qWVcJXsP&phENAgV=koMG9)Ziko6%kqaIf_!h0FJUAE z<|O%>Cnv0cK{V)MlY;NtX%95-`d6X_?kMh$ii&^f>rd$1^=W0bKt8WD7f;zY$yg3M z?x@YW5mpT~-D_qw=k~VU8uSal1 zT!>Ir&WE^XgA*H4=yu=sUp!m3QZBoCUpl=|lAhzKBzvTZYnrhTbE!JFjsy{n^2xM@WX+i-&5594}Pgw%4-_ePWV(4dFismv%6fpOly=nm#7hG;-HGvkBEK1(I#jC!3fQ z`{umA>kZ85({l6vl+kss+^$B5;=n9$h11^NPR$It{mM4CF#VrHdBa<$!rDmx6s29Bh86& zBfoO@TRg;M#(}PGes2onF0XeX;42z9lP+=8Q4eHXIN0}Rnmd<)ZDrvih1q`z#VbAR zTD*{yb^zJ{@TTPyYI!Li+^c|o89{lNTgVGn)v4}_mq78HipEop`Xy?AG&1?#JzlS! z?-X;!76YA^lnaXnHF{5&M|*FDNH2OwJ#+MCXOymRh@}KlD~*Oe*TEjOnd9gdXl4V`3;=Q^#l)cgy0w zR%qPMw!FhRhpeJF`+p#RNBUru?F`%CwDz|A=Vq)zD|oZx%843YYGZ<$NxC`g)KJ{ekN4HT7y!XmZ|_S&|o5 zl$MsnOv27tz+gEN#fNe@|Xww2;AFDR0R$ds8lYJ$hgQKFERm&x8n|n?N0OgeH}C)>_ZC4=O~V ztEMm}jl{IkAmOHT*GN&VTCsEmk$N?0bGtauFpy+9(u3wWDyYLx_p8I$%;&D&SQew) z@}#{fvn+|79#NOz8P{{j<0oc$;N+MPS_Flq;%vmt_*LU488!;Hy_I$XLGe~sZ37>^ z(MFGo7zBt3{omsrA@llFj299|=102OBCyZVfqpKGu&{>pJ7s+$TWBrOAYvrAAQQ|eg zIJa0mhQev<;LaTC#t7QvwMIMpmFl~MCFvgepT8b{%3^uO^X>8S33=2zJ1=Feykvc zR`Elr`Re;O?v);Q4%urFpiGN_6g^GQO&JF1bHW8sugv-lodwXRNI)x-)vKpHEwu*g zfZ>@kD+&4VOh2yP(rew{<+rpQu>bv0u|r?H6O|da!b9mXTY`ep`}%;t=~E!9DE3-$ zv~o6E%#QM;+MEjziST5+5d7KHH$^#+dL@4@<&4dg6vNiWg(4_rTZmdsBM3`9le#%w>4Kh9SFf@_#r#b21by zDP^{STEa_>2}dy7#tDBcG&fxkb70KYGWz*lWOSAy)4}~*v;O|iMLqykH%J>1O2KR@ zRQ=>yKd~ySSO~c1emE;?dxu(BYU&LM?aW(U!s>yrpG&3Sz~qQ5wT%nWBd^6BASXqb z-^Rq^^7o+AJ}_=`NWNP#Qpzt|-%`r4#0;>gH&aTV6SQu^tGdhVUhp%}&DG@Z9m z(3>9C;k0!>a*`=UJ`B6^BTm*v-R#v{IbH3l_65>NqM8r(w2KceDl~R6fCvWV%r0ox z^~ICtoUaUeUXz6)XE4%k%Ir zj_T~2&PIpIC>DZw?p)*Srz7^=Dw|qzHQodZCAu0Wnkb(gl&7)fNhap@f#Y(omk85J$a%%7BPMI)*iP z3C2YCHpZo*@U1$-`zw7Ua%=uX35k@qdyjND<8*B;;(;Q!Wfd{;Y9gVP?{KlIBk0uJ zRhHPu1tByQFr{v9$ll01v`uz;Icc&A2Tj%QnQ_FrH^W(6td+|z2IDScPECK$+v~sH zL=|B*E9~vZ#p|CBp(TrYcY7Yz5WA^HX+v^8tVE_`o`B0iI~4DwB>V@pPXx@Jj8`}N z{jnRv+msFY;;4st-QCW7Kl^UD6_=fUvIjBPH(=m}B07A|Gl=|GC)B@5F^Vhq5|_1t zUWyB1-j!JfLsNtxEckIT=-auwE8)C&%&B&?RI9N@llw&1K(DU`b|ZY>GqR*#)Sp6G z9BF}Yy+IyxRpoKCJNzNX0b78j2s(crxbsvf#E#vfpAMNu`}~3EVR{x3MUpg z#T#F4FGdZ42C*{2rM<%~g)A4MW;DeUD=U0(XgK=xxVx|NkBnL*{@h=SzCMIwzK)y* zq}LY0Nay$#iIOvG(ox3yK>o>xt_yQP>;z-&!Us5q#>{0+#p3k($uNG!kbXBWE_W|I zUVz)~$kvs`jG$pl2e)+{WL*t%dt$2Dmhi@2_*A#-R@eew$pQ8otV&K z=UHLySm2BZHQw`kSvqi@yUZflRGlBBRTdhI28kgMwo)l#Udcb4l%n{;I1(dlKOni8pNYC*Y7owb3+aO*RGPYnsm?YgCBNu&P?4kLc0pKz znuyM$Z$uWp$$qV%U(GHL$gZJ?)yQ2-;o%J6RZO^ej{=qfAWUo{E_?}i(9n?M+Q2!R z=e}Yw&SthZ!d_PlQrOcfuj?$Y;rD9cR>t0Dhp*r|M0hOHoW@Bm-bsjpd9J_F;MXOY z%R)v^b)OLlorhe;WIt0B!%ulPQQIHwb9GX!bClG0L>`hLZ+!$WRQpI2c3GdZylJg{8 zR5X$nh5$jH7h{EtL|m!@ytC~=o=JgIW{_6H_jqG)b#8;vV<@+PI9)fp+pMzX2#!a2 zM8_S4O&ZY4`mSOUd{+41L6uDnG!RPg4o6oc-tD-)aOyFBw z$ds49@x7I|?4pWc^p31(e3VH>8PZp+m-K7V8mZ~SQpFg;~P2_aZMrK$HoJF z!_?$m>!qor;rEZswVKgeu99Ou-6gS9ORQ?GUQkmg&G~EZEZ@Qa>nlY701&DnM$GDv z7w8Doz;U^{%@T%6vntlUPQh>KYpTQwv83dg3d9jYb`e7K2PopXv zGIdE+Vs>u!9zJ4wxvr@pb=%pnr4J462k(DJMf85pcuhxjwtKR_br;jWxlL}Y_X}$N zAn>jQ;Sn>qU!x#lEe^5TtkGQbPWsyBYn`0$|8$4+`d-u!s@?Xs3j$}~I~is>?`|Ba zV$65mfOvOT*U^dbFwq#Y$uJiXN96x9!iCTf9L`ye3Qw9Z*1wtp(XfLCmlx{?$w3ad zGYJO4^=I*o(!7Ob7vErPzb)?uRFP)ms%P8F4-CjWCSzvxqlUuDU5qK@E{xEch94jc z$B=qR1<`xBFaV-(MpTge5_vWPjrq8}d}4_F7!SeOnQgqa0lbYD3C5Z(C2y|m`rQ#6 z&?W62&Om;T+@i!3Y;UkC3?8K6l+A_9Ziw9k-0b)}uF1`C--Zzxhfqp{cTXU-?Lk#B z!dTrj(CT-tin?6j>Na&CoWY>`aA98_8B>q`Zz1y}JXPq+VSYvDfAZZ(MOQXw4^Xu| z5KdEkHbXo(WbQN8#AiA~j>)URFL)QYBt~nkY?V$PMH=5Ph;Cga`W~ z`v$cQiZlMl;dwInF!U#`GwtzhkNr~<9&?Gg-p&zqp!=Mw`=H5{tb(9hLf1ae5WQUf z0R*2YZK>{BcZTQP4og_(8%L2eR}v{Q5VTJuXj-|K_r7%B{Sawb(`V^e-s%zN*l%qd zE%v)7FtPceP=X;};d@W2>yU4RZvw`9b@o{Ib45s&OvI?OV|M>5VKx%-R5MzFPLu!b zOdRMQD_6YHm^AUn-N=M@QSO1g(A-sJBik?oy^P@Y{m=;ty}T0ROUFJ?)?F2lo5Tzq z=)sR$q_2L6-$(mC;A0gn_2qD#U~#VmUE$`7Z-va>6P1tnr`!U=QlD(ac18ZcWiO}S z%|6yDZny#s_<9}Th!47cJwd9BK42pC_3>8u22R}^1&bJ6$Nel*!jfVBbI3hfHjtIQ z`h3@-#^RFUz`uY57>J}`?l@5i{q?wU(%0q3J_b0=h2nEwqfh?Wf7H{!bHni5McaRE z52*hXTD;QUhss!;#ACuX_xcUHOX9TsmSyrTH_A$O$Tlj=WRyq@`SjO48)RYDSVmLg zmXiK?vvHD}PNw7)5fI@gMTqtHfn38p);!EE9j<=UIPxQ=`>hOsL{-YnS>RD<%m-?~ zp68q~=Dv%+3-NTCS5(V33LLfi#G&_@N^>{sqh1grr##I4h;g^5lak(4&|K6P310hC zpz*2YR5RwTtXE@PUCLuUs%EkKk_I5wPQ4Nm_%DD_M<}RC_AAC*zEOc1)_^q}-&t%O^Y+wZyM4L)z z2bOO&G$MDJo}ItG;QaX1C{2d!j1@=IP8aHY6=FMUk9Fd3Kho}tAJC3JIkR~R+b|9N z3+SriC`nLL5)Jq^5``uVDy)(7S<6w}Xk`f>tk8>5=V>&1l3wohOcu4oxBxN0hA77# zf7+Qm=#X|V*` zdv>C>E$qx$FS|<|s2lXK2^6up$t6R0gKc%Vqwk~{H|(AuoU5Bg-+TjSjTEkpZKWs4 zgh%3&#^lcycQjWsnE=`&7yQ&lMI3Tj3wC)Z^xdziOCxt1T&E|tx53TkCb45Y*VVsS z2$UGxD|1Syel)F@YK8TPSR1tBI_SP{alZ9a&rMeE0CMn%=$k|G*8Og(qpronLPdl? zk&|<=laJjsjy%tJ`V5Gl>(PRB(>{8hun)Iyb55-LrA91$1xfx&f!e^YbC#0MHFo!U(O>JuL0QF*eXS~(J>i1bn_V(Ab7$TB?=*&WfZP3^H9^UqLN zGkqJ@)`|_VaN4JI)|eeYvwN7|anVFd#Gcz;9%rQG=W@dIwYmOmi$IOnInPO&UW@ewg@9%xy=lgxC z&cCx&QyOVB8cj>xYF&NJMky;wBf;atgMon|$;wEmf`I|1z`(#$U;&^KZ5fp)Py+6v zDlG<9H9>d`%6OV-%bF`FfYE`@VZk85@xh?}sRBBLzzP2MTnd~P4C3E%P&*M;V37Y) zM-i0%^Wy>?|J?I`Qixpe|EUcs%LV+WHef0j;y>r$DgWHIZZT{PO5hx2bX-7>2ek&P z2p+=-0T!MZYo7WnahQFgu<1cBAbvo0qe!w6v7Y6%`N)MkWILZ$c^$IcK`e zd#~_+vj3I_f`Oy+90`#^!h(whqW+VlQ-}Z}#>swz|8I#{AS7}t%zv{Y2e80yGM7jz zu>ZN`pCl;c;y*2bvOrz{rQ%eEoAE;SAN9DQ z0q{3fjk)ibs*YfjlmBOq5W40MHJCUgD8q&RekOHVFxHB{KVI1Z3PeFwgtn=58FIBQc@EA{jeN_sMHJ9I>(2* z7#JAmT$B4_IMqeO^p_hg?@!YZNJz2I2x-C8e0x55w(s3|EM>}M~|R~I)s{imm= z)4Qhpc30}6GtZ{C8c>+%uLU(xA>j5H96ef-_s~$3)KWL zyRNof2HsjIvQAXWr|#ThU}HaQeXI`;!!`{NClL-M(;6fBI{LocIR&lGTz`)U=`7Kx z^}Z*tF0q+&SQ`F*EOr%>*3{RX_jtMf{Ic&7_9Nw6(`k+IIo%+a`LCbJu0yvAV~3NS z{_p6Rm^`-qM=Ne8c{P?jdV_llj0FBZK3ZjZ`|oYsV3qbAFG1ko73J8KD}^v#vkSkD z9)|PYnGFS)?bHt5+nT_p77rgA(wTI*s=nhO^SJzkpj}u6ZWjpo`1MM{2t6od=J2>v zc5eoh-Bt*;eHiaPoUP*s%Ab-VMKk~l{r{Z@%GQwHpVgcFBePfd5NSyGT=r8nBU5Mv zZmzBt6HY{1EKei5(nE2C6$S+d#qlJGiHRZw#l^xNALLnr0UwA4O+YRt!&X!roWq?H zF1MG8)5WT%m#3ps0s+4p$KyJUS&LS}rKUFR+MRuR^;Vyu`rI%m?7yIM27}%Vq<(z& ziy1*O*6pp2j-=wh+B>!A4x)&mRT)i|1D$2%HVlS;I%Diw%F~#g_ZO=TQyOa}-z!fS zslR5_d9PD91Zx8m6ICm}#Y)PjMTCatMvSQaij9ehjZs*NZ1ea~E3)R)*Iz%J%*iWH zuRj!B5$OvGiHIc>yy%PYxQ4r~SS8S6cFDSZwldi~d#9;cLV{;9 zW3~SA)1bqDxuo{J>`x}?2-M5#z|c^hou@W#4H36-omWq=rEZfyL?ltf!{z=Gw1Tx9 zyht}V*BW-qX1fzoig8|EjI4}ISy`D#L06vz>Zqtralw=v8(HU7xP z6~rohotsk^wKBDhk&DD!ZL~jIYC%ZtCG7(@1Iu_k=FYWw%&vezrRg844bm2ug4050 zRAAH`w2+ahX>3G>@9Ck1#e4;#=jZ1)*R{6dCzD%22DN&>&^kthhf|Mw4rB|u+)VZO zEi6!N7xqehmHP@QtoC~{cn9)ZDBkQZQlvo7me-xdY6EP>Zwyqt>270(gph>7R;ocp z?px9d3ctXE+2C9GT1Tu*@c0o3G0-to2Ek>;#PtPfX@?v2yjW_MzMDDLu&lWf3n zf)hObz!CnAPDjO9DZGFLjo(EtR8BZt0aN^CLN-d){`R0|B1l%w8Qx=?XZ*Q?Rqg?< zTV-l)YAPHx!#(BMqDYlG>4&;ep(02XM82Q~ZhXvLfB$p3U^BO*_yt#0lln@|>+Y(j zif9!##4}`v%ECq$IU@i=O|8O11tkfdff{6%v?IIx?{^OFZKj%Ze|J1NHR?VZ)MpiU ze*>Q#iLp{VIDmS+BdT#;PBfvaczvrDUSy<%`w#(|IF@PU_^Z+If5W2RsQwfg7ODK! z^o#TRNeVrV)BHxef0XF<1z6j-dhvC|+HbpvSC7kFYG{azoCY=#fl8f|&wa;V)E z5U`j8#=M+OOlD%1U5vND1Tpxvw|BzoS+tG%p^@Yu2>j^!w<%N}+bJqM;;_`o z3E)0vDo73RODwJ!jmNPsG>jS-ia8Hal4>pztmM9M)JLz>B5NpQ#m z=T4O+mgA`l!6q`=GmKSdlzEyuNeT1CBlT1+QX>w`!9@f{(_-=`ypP-q!q8CGX{=2g zV5=9CC;6$kj*()PwuoyIo9bU*g-R@tG3aWAg_ZUC{=O%;O|^(lJ1je=G-|#x55fk}&r7?{4QFqAMlehr5wr$%~3` zSpr&@J3=$_6fst`=DI9k57tzwp}F7A#+JtfbG@1`@m6>*Y$#>;UGkfzW$&SM2_tuY zMr&(JI&Tt}^2m!RfDnd4YdF}hO8i5Fuy9SMik?i97a$W_5dnZ2Z?1a6iHql5Bv>Sb zLT2(W!W`S{Ba>t)rT=G(feg?n*XnwF+COr_m?8qeXA608nC}7M8>zl=JH%vx!(Q5I z7q8TazFTWB8dhs!h01jMpm|@??aT8j{p#nrx_*wG1CW;J6s>KCyl(y2tZ)+KsMf2( zZ1{`kzEq_#>s(Zs>ytJ?c;m|KND~@Dc1t!qi}Bam+0&x$l#3o7>X%E#Nkwi#Jzgqg zoGn=XEXeUA4S@9Z|J-P{zaMZ3_6P`(QV2&pi#|iMS#%IB+{}lna@>s&KqDla>+k&X zmF4yEBI8)V>vLm0Bs}J5u83gQ{bdiXL>ef0jZSqio)P!64`kzgpUgD$WCMOdcPrM;5+OPiIWdFXm z&Aqpj@GR+h+{w1XjABH*yD{b!A68YZUl zgwuMx(+%S0hZT5z{N?60#(joW-p@$k@fvY=&G33v*F_m4s2tqTbdhib6clE|PQZ?l zP8n^Xe{fJvPC5K#9?mei#tJnX9UB7!COVuLOU56|uuyg2xw6s7A75WT)Ngh6f8kT} z%Ke6zhIazHr}^AYDY60VQku0_S1d7M$Snd|S3n-;qweY)VLp#@lvM_qI(*V3AM@KsynIB|DLW4?XE4sJwL;rc$LB=JEXsk|jXE^xN7&JS|;%2n#Q za>SqXoxQrZ=z5A^#RU-16Ii*r9}XuCXmxe4KCgFmG1|-}e_)$^8Gd;nXto=J)(ifD zMc?7`h%F-q7xAH0eHW-%t&!Q7#*{TlZh;dl2V@L!vb5M_Sk2Pcqhmn~It{aWAYi!~ zFHMS3k~nuh9_|(pj?U=YGUkCY`uq1U4wFvYfhzA@y&HYXD9h;b$lpxv^7)E_tadc5 zP>~M_u)LqEjkXMW%||7y!7NEOT1-8{ebZKS4V^HLmn}~3@CJyUvTN7v%fIzuOg%CC z;Zy7IxO?DA2@)VN@W{4HHfw6vxAG`}Bk-Cj?8R{)Z=%t59{Ml6W?3*`!yT6A>!$H( z<9R{}9ZKKF`Kp%MEMS-d&X<7!fk@aJ){C@kv0}bM+F=+Hc0IIsI}gI=JcFyvZ5JPw z&-G;Hj}NnHQU4#1;T(t#2%c4sB#l5hCt`QK{{ zYS7N7!|b#XtloH++LobxkxZ48YH$Q&C|kfA76;Yz9Ud9JLc5fWkRTfS&&g8DX=Uc( zH9+d53Wqs+yJNzsm(zBs1WsL9xHDjA3gvPWB0|vn9i`f!y(J+TF~4}MJ*DwaRj%?*8Qu{jSOP1-loR?M}1NC1gCVo8D)3Bj_@Kdl!z&ou(opeeY^*4wH6pn z`_T#pjr3#)WMyUV2{^>6G`0d>=AsGxgAg`QX4v2=s`w<`lD%L8z+oJoivFH4hOP&7RL|ho}7}A^EEY)(bOde@Oq}z=Up%>G94p1PqFW zxCo+TklCMJ!NJ(LT=e!!CwN2{D5!-BjW(%DKACT=Cd=pxKtDF*u$#bbOw~})aPgo? zXd3|65-qBxHawdrg_qwOSfofd*_YwvqEg;TyW4;51RsfMU7evul9!8IVRd=o&DTLy?zfm`(A>j80d#SZ|EQU_UkUV=> zwlnFmJQF4>J2JM8L$>=z>)U8WJc+R5aXXNn$f{I3oQa{WVAkMV&&8erL0&!%-1Aj2 zn}>^xtTyVGAZ;`j{dVUP((_jxdY~v+uyb@#s~FWHs+pddy``_@ClKOEc0?owhb4xh zCc(*B>7_#RO=ua_Zly7Y*Y9QwhZ&#CI;MXw(kJ+LXem4o^0Qa>)DL+y%_e)lI3#V= zP`*P|AZMe^56v?pncihs_nZNHK&5yTIu+TfSwele-72y!SLJs?G0fMd;;%05PNm%< zBenh4aFw#=I&*=J>1<|pW2w^4nD)t8IJDP`%~>Hbg8u?Oz-ZKNdHm;64h~M0Zh|nY zz~-;YdSrcg#$V$9@H;DQGsssB3}3}5<*G2_~Tky+hi< zOOg~Y!$@8An`cvjt5;*Q(?lwz906oR-QT=Bg*3p5@UL`<+ftSPi#C6u$fe|M+xkJj zA64Wg?ZsmnM0YRyUjX}4RKykuMoji|R@D9}(XK+#{wL(M%zv)$nLzeq^RO(g-G5BP zqN_4>=0&>wi%dceQn;2vVoi^7NfctU;ljn?VgTQG1dn=FXpHD~DagC;4sR* zChNawV_+{DFrzz&$iZSFD=PL_E{#dQ#;Au{A%oV}zW;y20wS=qZ~#>d9_(TwR#sNC zu~bfZ{w2hu#KajTPF~)04d*b#u6%Sl40pK_lB(=qMN0pXAjpF>hb*LatoZf^{#L;M z?I{9<#Q*c7!}s|n;Ny8{VL?+@cXeqA*Ko5d07a)z@fY7fG)_}Z%~Fjq#As`4tIOep zWFN@C5c`r}P%zu+=VNGSC@noC76w0GqSDvh4QBWJ4gwh6&sXOA`wKx(;4eNmRddHE z?*Dec2v$aV3l{W4LJFeZDLOAZeY|MhEq<&O=Sl*l_82z)!9Ed~NnW#FE& zg#7p>tgWqE+uD4*y^(QQzz%+L+AL%V2l&6g+#7cKUOzrY;D0}w$~!nXc=LZaU-h`z z8)unnL`epuL2LHDr?bDz5e_&QS)MNZXEKqHlM)3%uz@FIPkp^wmpomp zCc(vRwwxx9#P6|!xf)QcKV7I))6!zrtoRubA)P{}v9q&7EZ`Za=5e{9-|AXgRAlDs zE6|2Ml_p|1VwHZIscR}IaBzbN@GNlJ0I=XQXxE4&ml{){h=XrL<)hN4 zO7Q_AGBUm$PW;;DUTJpvj)Rld>G!Ib#pAS4p;N5*D+45sBDoY6SxeC;wE;DJ!)1%} zl|L%sGXTw>cc+|q;r!^4x8a9B%L;kOh3PCRvR$xLG|L#(2$WTK~_{& zs;Q}w2>C7*E0J(9W#gA@-*yX1b2)4XnDoP1LblW&UmByv6Y)QcB+=yV4L^k;W?sRS zd@C8(f z(r!#Z9^x0#_V#w~#|tC{=ve^}+5S2q)}br0}hmJOEiPD&&=3AQb9vaUQxJA=pDoS^-kj$FpUOw=EBq21^w` zKfkp@kmS3ZC4p_&;gZ@Y^^W?%Nf?w4Z^@(A$QBldK93i9x=&mhReH}K@2@@&XJ1tE zCGJn=SqZas;M0YWif)=h1r4}rimkF7>3PdIZ$cWOgyvb zSiGnAkLnhm_l6-D3kH>dFMcF5$@|<4i)=*MJ9u?uisMG4LAtNfW$!*(s5t21@H!Y zQW>rLx)enFB}h+UL?M3!yv-Q4EHe?k8eq?He~L%rA9k~i<$S=$3A_0FH2H`cK>&Ly&f+(bO>U|0_k}F z`xC6Qa2fTGO@MDvUtganF#Qxg6U`s__TXJ$lxgROZWtcs_YL* z3Xe!EfIAtjkjW(q5i!YSw^CCKCV`}_edSv6?GK%R2Du?jcnlnWC(a$Zcmn;m0(xSse+xTzF}wX$bLaGU>91T zDVV|_XiI7YA2ddhO;7{p2&~!Uc|Z(W$M#mBm3D%+R(uK-h1xkef$x%%iV@-cX`>Rt zIoa&At4$;K2R~uNzSeVYCjp)l4MqnWsw8Y12#%$U&Efh3Rap`8s&BBzb9bjkxjO{x z2FAn?Z8x?E+LysdD(n%OHV@%=rU(IcD?hXtf|xv4I+=%<-tlp@@8a&H@w zfx}hrzIhyrn09d>QK~nkqhpOSSrbJd4FGu@z%AVNnTNlx1Wyi&tO+3}VDe;9&$zox zX`f{KN(uM}^uYwwRP{;#kpib%5 z6e09dliCHMD>%Y(_OKb0NO^V24MjkRVXy6=j`vXyszR|W!%vaQgR5qA&mz@9t(h4I z2m3JIF!s(v39&_9fubaVkT8ch&3%MIzPR5kf0i3V6>~(7x)h+&{KsDsQA7pCg+mY% z0NZ&OokF0IjI^ZST`YNi+T%F|4hsUdA=-O;A^9=hbVw~~@YQ=cai#}pySI^ZN+MKc zX#3z!j{hg*3nT)B-MyJEdTksnGfM$S6OrLSEq8-^1v|V39u$8~XS+%akpZvAaE2CH zWwl%3p!5$ti76^Qr&SPcX7v^?zKO zEhV@*!0oEEyT=^2?Gh^T^H&FO3^+tZ&|)7k4Jn6~C3(UzOf{a4ErmBs{&lj4FH{Sr z%YqK$zwRrOq{s_E+MD!eLy$K%b|j#_J{Qa?q(H08(KwEt?jIMDjUrI+20c-A7hUZ- zJvlieKmUi@SOE8gn)w6OHd0Tb_F`#ip|xd+wN=T9CA^RqT5{r@tleISh_jsa*LFEQ zF?f5evx|}|0u4vz(h}GUaz;);J1n<9T|v!tU=qZD2!^NMLZE#kX$}Q2ISU^vV#os& zP9cfXHjhu>@GvZhL|m(hR_F<|$!cr|sHn}5!+xe5hO0#>-cN(>aHV9XDHU$6CXRb3_1CQ%z0X++tcl+K+gfXL zkQ2eK`5(N?&XFc*c*s?2OLFj2Jz5auc=Qg5##-dC8$au!u@r z3la8uFQ+3F(7#>q$iR*XTak|ToTtIEX+UdZJ28~U0is6e1Ygre-- z2LprF*=oJ08>f)q;a{F_X>R)Jjj*4R#IQyEk!@q(R3Lb_MPmdAUqSABof$&ousAV` zYcvrXniPUlsBq{^Dw*|DIJ~Amr5)`#C;1>QU|J;sYLkl`99AcQ}T*VHKNlj9~rj4=qw3LOJOM}(o*u-1;+6rs@=YmM{e@e+j_d01Tr zZIILAH#SEQKP)COPjnW^Xbvjk1RnVI2w8&Ih3#5H3CN4W0lYwmZ|CJr60cXPcDPUQ z_K_2C3;P3}$oAT~7a&{-SXkuCxt(6GKkj!&C=wQUooZ{fn11=)-;_3sn<|hHVeQ`^ z`z>&YS%Bk+V3etEEta|QeM__XR_9ya8A2`pD^`@^w{XC-;>r3!jW}q#bxY$!oUt`9dK;&R2Tp59kI!&(YU^)U*hIdgz>0*CQ<0D06) zt^^O5njs9vGIQXka13mH;YcnVaN6Tjrt>QJ2(p%~JM@r#8LkzkGVRX?qzisekeCXKN ztbR9kay^D;Gk`$#PCYO$LS3UY1wJ*^dqN81tLjM$TtKg7UlJL%sw z+UvP(pTU8U>DY5!%vw4jTahMt?wr(WZK`@S3JMDRxtjDQ%l)S69LaV`_EWhM;;fJW z@$JfQp(XvVbVNZE?>}ooYUIq}k3s9hP#h6inn;<^Gncj>Xa{A?XPkV66~+R74-IQn zu-&V>H4h#H!HsQW;^2_u&$C|&7p)kV97HYWMNQj3axZU@@#n(xc9i!u^*l`R%ZOG5 zkAsgvJ%f6)+~^r3QxINXN#stW4pOkgaflZ-?LM zHwzx@UBFveaA@(7e;LB}VKVT^-= z-xkbkGIEOHS<`>i%2RASI2=|;g~*Kifg4G`8J)A)(0#vp;G^N>Tssyq(HFvet`8dFkKg)2QfCnwhqEe2nQ_#9rRqE*xt2{^z!0@*o5Nm4Lw9T?U4n4CQgY^-9`L{JM;nqrrtUt6?ATxzwt0`}YI%k%qj5{!1<4rd_1 z;0JD)?)mlz69;WqcuEV_;mThhJk};sna>pdflF!2$o3bk(baHwMl){yH;yZagxrAC zb@|}%3fUa{O858rPU%bV6gsU-exs7xtgtCx!j-Puhri`HLha`(1(#RT7_06_&^s!- z#d9`Okf&qGdwZYvB&`;Q2RWNv&`{9H)!JS?iSsoH(xDMQkRhfiQxVHvs(r*jw750A_ zeIFMc96x%>;&I<{Ao-M?#aX}eeR6;a{)|OLqSIu9_VI`v>>#Be!aa@AFd-mm3p!-yVdt;#hS(W)SSvEO zU6a8({xYYqv*TiM{H0Npi<53uL9te0i3Z;4jfp53)911~6Md3gBg7#qKwA}jLk zmwZe~MKfPPuN?*o6dR)lRG!;lH`J{8JiWcl%h&F3Fk9+W`|tXAIQV_sZ45TPk;l75 zR^oE!8^WE=Fy{yp3wf(ncS3;l|9#*TqT)uQY(DfZ5Q`?+RJ)T|hvoErHLY^R{adT^ zZ6Rw&XTU2uIy#5**&ZW-W-`6u@yPD0-wRTU>xa6t^GpwhR_;>rK;eyD4v=?FU2Wh` zBjWQxW4i+L5X+N>dU?%8HF1TlpuYmHj>TyNUw9;>-r(Ad z9%I}_W{&9o`hq~hf)F1iC9T}eFjAAn1}a-$zSdU$#wsFq7QldK$EEz|Kb4gM=(>i^dh8K>4wt9l` zDS3N=QT^Q_%+%EG0~tha)*7W+#rWe)5swuQ9}L=YL*ea%#ePYxF&{%inO7$)tXw9B zyumO{agb0E-!M5cdF)XWWpc&iM1r84{&*X9`39@kUJgSo>L?Z~5!Tr(z>hDM>2IFy zzNSs)z^+q*e{^D}hM^j!`UmS_tkz-Kj%m0W@)SF#oTyna(Hfa&XY)kkJ3UY4)4TuR zAY2wp76fmXxXq*r3kv4k^qaJCBUrMCPvD>>?cMz|-FBJVLos-(RW2qb7;wGfu;myN z1LHTwMO5p_s8@J2&CWgXOUQj^SjZktr@@l70*=q)^t)~&c_9+_;~(%3|E8)#T0V9B zSq%{qG-EP0A}nEyH*E(mZ!ZsLSLJTRU} zNlPLUaDvnQD8&dD_Ib&H;{KM>_$9iCE?j%>M8JL~CVxQAQD1b$(qt2TM`rQjv)*O} z9^iD^_$yrxFdI{3W_;AK>}UxhpDn_tlzmj|(obe;wGdO%f=QKj2~ZkQ^ihB10fFC= z-eXOd!X(0OBYB2tgGlV|Hv^K}@&tMjz!Ortt@60I#zYwcLWg`Dq4ofX77UNYM~9r^ zzwROS5jN4fVn@_Yt{KN(yFbKp;$p(vES?k`tHqKcGU=!|_ZRNv*S<(%eSG9&4v5;5 z;Izv17w$di$P9KR)XLs+{i3v?*P(}i=*y!Zf`E8?F4tJVqL~vHpI|ho-tda5*LK2Y zG6@^7u_DlA5LEeYM5|3!E4jBHZJ`{_)L*83{q)o<6`Q$jBh*mVKQxfN)K)rKBfG+< z>h={Tqa8vRn-Qs9=R-)=izY0Zg-rgegLTje|6_^*k^D(~d%B!NHY(}`8X8qMuiFt< zfR9ONqQ4)rxN6e}sRQ6j;OWp4j4Zn{-cEWF08PDvF_iU8{3LEXAO0)&(n@+AT7g>0 zW1wJ-<=kD22*e*9c^fDkih%yqx&Uk6aIMWvOllEd9kJA~Lgm z8%iOz&FZ)zrDFpK7RP?shB1QtxspNN!?cadYtQw4ROW5JIa6;<^wHowFSPF#iBF$e zq-GWR5&eUOH7~PJZE?dh*(s5=P4ZcRRB#vjWU6TBwW<1$M@i&LooxAOH42u`ibn#H zPL0j8PX*HU_mRvlBu$G8)LZvcxyA=+?l!Z*-*L!lB*K!M{Z>pk^c9ZE`8v0VIDK!Y z4pzWJx-nG_DN355Kr0a*TDVgBgbJ!NI#t<>SnHS8gjbjuXmc1Vh@2@77Apv|VLVjX z>nOJN#q@?C=SCR5y~5bLekrNJwTY#-dfdnk%4WbsFm4JDk5ve#r~+~k(n7pz&z@4m zsHy~5JSnamn-417I%PAfqmL=;%NULlsi3&w>%qKBBpYgJJ!xuRX@zG>-&KnrY@wP& zUC^2k0@dN?PApA~xP3|#PWY5{3iDjZ&o0k>&D1MY+r?UbSKO!R;Dfh6(iN+kc6@9Z z3aco!_*HPP8A?LwCgQ(OkirX%FjAi|3xy}KwM+R&Eci``sfXcyI>v9g`v0aL^sSz} zi!D&|0uQ@`RHxvEyqdC^t%^=t^wC{~2iEL!*_%U{eP&KpP|f#I)7i7- z3&3SmAbsKmQ#X9W$_L5!xp?Y_EWw)`9Xn*%yj2X~6_Y5b8?4JB{_=d4Y{^UH4nmkv zMGro)KZXwTSCFqvItGhUR%^R?pM8Y!tow!F_9@9vDDOxnCwCoe0s`(8r>gks0PJK} zIU(4ilVdWd1U4ChpUhS~lwC*KMY6U=slMt|HeX2kx)K#KmY$=*#P~Klycb%eKf5%@ zldt-ECWl05GNDlL=q0;V)e|wXMu>QTfe5@TjhB3U>#|#69j4EzlQ~_dM<*2zKj-sa zhZ7exoocU7wf@e}V|kYM4-6_~HChhNsg!hizZ*oGBT1Mg9Nq8%mfyB+U+!EugwMb; z3m&}kYkd(vy#QtHyl^GlxqDA=-bzTx1pb#3xb>5R^7qwzUi zoOAODJcP@w*+Ky}YOVd@8dZNYIh);H<702$s3uP|#wY}NrIKIV3wXD)R_F-9XB=fb z;kJS#eYyesEqEVP?TT|>2Vv(**1-bM5rcD3{3ZBw1{ESr+!Kr}!?>S6?vp_5XRhi5 z8k!jZI}0slUh$Tmk`~UZRo$=xksTwGg>Ms6rN7s!L8o`IMzqx5v(qt`IF8gr3K4u{ zIA-Mvo?}Q#LJDqX0Vn&PRM)f^kT>V?B@(ik-C%}p_iGIsyF1jm z9iAUM=gD~T23_y!_1;B?%p1IuI_~caA-~-NoLz#@GaK}q&%E9b{F zpo7+2hv<#eN!OFV2N*D+49hhtSzJzNDJVqSS&?N3 zPBoizYi9hYg$Nd^zmyb(pvs7g7A@z;GGD*)xS2YL ziTP@m*sAH$xo3E}-6=U3+Ui_5`(BzWFa}xc??6-)JbjT}6L{p3cnKAgtZ-)j+{%jf z_`|~7ElY50QCL}-(wS&|!}w1a-235dxlE&+-{S&ov`9WJ9~3EiVK8!YaY^4YPYhsj&;h=FAn;p&W67q40lL|4T^W>u6Bo3*p1?4!n0ZK?+xb&Q`HBj z@`5Xru1ut}YL-5cnJ43cm!_*T>9>MDI?<^$k&HykX$ z=E5eJk(;979N`71&N_nP?I*{_`Yq1;?0|-@0BJlLMwA~^Y7nppRRZNB2aMX zHNP4fb{PuyXpWJVXq2ZWBuroL4h6hDO_!?CfWDUat&j-~1H;eHk3*~6JvZn2H-nQm zr*O_kX0+I+cn?;_>Ui6wAChwd9H5f0J>*`!$j)*$XHgQASKDH?P3ZbiY}NVxhh;{o_o!uQ=fO#81W&m)!O_MU}x~;kN0ri!@rsiS$H{ z0kW`QyZd8{=i{;K^Bfe~0tLCl5OAuL^ThP@*3#K68f}+%4h|ZP`@&-hxTPc{AfcdQ zNrXXh$pui&kQGqyuK>ilMU@Z`6f}+l-*2#*bv(%l_y}s)-rAa~(&w)|pdc|BeWYTV zn3?a3=I5I}Bn$!*zI2gx*Qi{tkrI5(dK|nD>_BO8{`j(Y;_3wxpVfB!T;n=oqE)ro zm)+#&-N0;E#i1IseZw2)?)h=DzWzGN!O5ZNH74%T=rWrqM z??GZMvb=2-mFX0^75|Ty5U2TC{n_s{k%G)A?ahQ6o3|V{NX-!9-@t z$Cu19cG0@VgE4r&_&u^YZBon2=|j<_rKRU6COPi#pb)S_$wO5#GBd>w0$09+09jN+ z(03aR&iisy60zu{KipJuBZk`Oc&1RipS<1e`mN>rM+3VTl^m2v-il?*CuUN(SpLir z7Ivvan^NwQEf$T52c9PE;(RxOoP2h#Ja2WkUar?&{WEqbvclu{@e;Q_q-PPk+3cNd zhj-cmqqtb9u@923c5pC{kPvuIYU%-f>O_fN>Dl6Cm;Jg|sDyDJ%%hl}p6}Zu$%dzB z?s+6x2e+M|a=o`?;iKorji00A(H@*QnOz`azPQWl3x6X+R8*|b+ueP^P<4%$;7tq_ zHD#m2_b#(_z#SNyot=UVZ{+a0%NC`#RQPN;_eF>IEt;RRo)dp>U^enI1t}2{OfsGk z(JMKKlXBP}h2co*=HVf2R&CG`M=S`>D=sgO5DeQNS#L2ZHi0YT>*?ys!L7T-1Y$fy z{52Z}lGW63*eoE1O-(6BGTW^-?hhvylU8Q=jj~fLI{^gWmc>^Ye_+--%xWko5S4i@ z$4Uy00fG)u>^nSti`6dku)~T-v=f8_!GD}= zO*tMEfnWD74R=?`>K`#awf(fVhBx2NHP=^w)rRb1cqyu>sy*rXz1?X< zW_ONafP>KTDb*Sn7)r#SiY(wIOiLUfU@`|00s>+fZ+9>@1Q)yovJ;;N0Sz(-BqNh# z0|NtaaBysFY@jdz0wV8Lq{-JoP3kvd&dlg?F``St7ZkRczOiJBlPqykDyrv&fh2z+ zVIO2d8za+R(DoV#dUcsJkHZr@r^k^b^0OUxjTRFfe++^A>+T2_=$WXOXDB`;JYMH4 z`KTSqaHJERyey<~Li69$xBAp?R=v&%@apSyOSS`bxywAo&jvYNeT9Hv{CPUtmDYf| zTXae}=^ryK2%4F=1Pb`Vo(V(L3XBReC>2Rb7S+8@5{8D=X7%9_aao3K#!YtViCmv< zJV+?<5`1;TB|n#Ehde7*;8zu9sqaZ~*W2GCcSk#Ai9RGs7%U(QDI87za%4$?*c9fD zW_bX66Zx^OX_L1)R4Tu}Sg;}}0q<|qzwO%6m|i_%6X|(qsDr@X5Sg-CI?4ncpg6hO3TZsj5Qz|0Z&d|Zp@k?p}rjD$-|;1l50eNoD0fehmuJJ@pB zX%>A7#Q@nzO!@VmlUhcEb`DaDE!$%Ezd&vxx*r-B?6oUHzeyzL!7-O>jc`OC`WhGyw=#4{d$SC>9ZzXz5&C4!G;H6$!2 z&(gqupMgHg>oclc8mzB~A<~7a_6H z%Sw>o$NOU4`2&pySPQ{aRFh3>y~0s-h6)TJHgF$Tn-u9@d>sn=-e$vXZO~#40SHA^ z<^ce)wipr_37FW2%;b|SVDIkkLI7`N>XT;J=3buFoLv6?0P0BJBeeqeHIR;{;?sCn#HKdH~^~_Gc;eUH9p>jMoFlJgmQG8pIq`s z{IbEsY~J=iWU`{(jMe}A7k~{UV(eGB)zrxhspSbd!!7L&Z#R&?AeTbN>2fd*a#S`t z{RlF+`zuKYu~e!-Y^!FEO9N2A#klD9{$6qhSsOg9kVpn6{3r#)&ii!D^UfjjC^{YxSGt3^mTIlRUd%1}Ub zEVunsR7@zdM|-Ax8jQnVOEp1gT)*GqBJLx6+mSzLmlGETW@5j%4~(#D@q1V@IXTDx zzm3b4KBoBITq%||6ooBK(KZCRLdIQPT}9(CW7DY*PfS#OABy95KPyoyR_yS;2ksJj zb$}RuP{-i+k*et|#=RiI2Z+`NQus!nM|;Yr-a8OuEF6+;$sg*AG}_nbpW1f?%G#EW z38;|)&vOArlfTi7ug`rVex@f88&J-fir-yb{C&{(?(+UTX zU$76g#j)xkwffSin(!h9ddV)y9-K`yFNsM&#Gq8We>kLpK=oJE<51&@ZZvzuV8w z(wF_#)PJjT*(3vT1o>j}C8O(LF^{-%^F^LcLHsThLY}}vd`8_y-_H+0STGcUbY39P zGdTqfe3kTEM7^?G*lV7SRt$*otDrDA2G!Gbv)&PnUYO)^^loPyP(Sl-;RohgUcnSQGQecnV95Y+?j=be#uzy{P`-^di^J6zHu6}yFr&3 zi98DY_TuSSd|;r_P%ZK)_xb$v0x@p|3VKSu-QlT!6li|e)4A`-m9c-uDy}2qvc+$1bel-pS}4g3 zmqA9eWgDpUzJD4I{o;N8jXOv^i11uSpw)fXU{BP;kmr1B+NG=AZ?(Y|UxA zCo>+Dl`&?19j1$22GLwp27YP!pK~r%QeX}jTfnOayR*BynoecBxh|VSWJX|(@1o`- zXq}kQZNO%BMsmA9&&1i?@9^0i!JnsJsMht{?3tC}L-zj31te}zdo?ef)UVbpE}MN4 zl^JMo8WZv+b2vd55t-6Mk(EG& z_y&q*8I4OU9+mv8Yb6 zZ0+lLzvJ7-{+GY^m4!LS9OGOQR5Uam3%_4tl`x49u@*6qwOeVoojejQduFy#dDXGf;|T#Mf{Dae5V2^IQbpV!FL37a-!i8^4Mv9m&Ew*4bBQZZ}uTT zc@$f(DgtG5L`=-`EOJ#!?W$DGze^dJ=t-HFxBH7)*M%Ip+-?NCjY@|g&1f8x&tMVU zYE9;x`oX60N!pQ28F0jEH}q%V8aiGU%IKp_*oT;h9B=(vVHiC-RVsmIv!GmAEs{r} z$LLSY9=IeG+`K8k(H5K~X;-x1c?DDnvJ3+@&%6D9m z3<*vfUiYiMyU+)#Km?-gZ|o|6(`vSz=vUdR!S*38E=HHw%?F(iR_rr*9rjZ{==rHf zKU*0p%X*<%eVW6P_K}w`Z((5x);Zm>I(IHY@R)x$T5rYYMmp>FRF9U%CYQ`cv02JH zbuI)hnAKn~0_h_L6701=_sikU1=ANk@B74uVIsss!0rpQiCrJpI9_cw8|{AKqH!-# zODT=bxO{nU!!}Ux_b$>Y$$=BJkck6*m!nE8Kk2yPsZvP5aV&?WaaPb=|H4KqJ!;b z58XxwK>a|{u4W$Qn3j+nxorr(DIIW#lH!1H4&RM8gZIT-aS<=$^wp}qz`En~rx?Hj zm(2KtG>v^EuHA4E>!=ViOnUb34FG?M(R4;MRDd7sxjC3f;nZ>^UaI9+Xtl|`6xbOrnkg9OWv(M2})tTn>|lglmIT{3!*GYa`b zMe|P%y+ke|9#rZHJbb<1E= z9pE63EL#R_y`ttmfTMV|-o)?g6TuC^m{YQ34ls<93P8Yc?@&jEV_Z8w{nIJB`PMg{ zLWdCu{Xc&+;DH0kDH_J#f>eg8{Od#o71iJh%T%fr-|t4s#D$-;w7YZp9eR6vPokE? zSPyB(O?toJNeKdia-ZQsS&Tn4+nrBm^F?O>12h-XEi2f3 z;uKZb71;wJ$dtepl^XW~?J*XW_EZ#$JYYU!%SsXoO0vsLlJktJNo%Ga zStq`QzGFg55X`nr=slL*Gl3ovS^@tH*srCrhcDSp2skfs0!u}lbc#=rBgZAY@3$6K zR#1?Tq+7Tt5)y%us1qMUSz##8k)WvVgM)+jSKCCZT>9}~2z+b_&)&WMAXRj)zmnqt zCoH@12s1KmB5>Rlu#=7X0ueUg=z5B@*L+&hAbKujzLh5XXQk)&F@vmMSh! zJD{<7=k=s@mQ^S@EH>BLrTP>hJ`bIGYp&9>KYt|SAQch6{w60gs{iwaN&3Er6y^E; zaj2;w4CRAYzwt+%LjAtVD`*&UjYWdA-#~fDbbXD8gDSa=aX6|9DySjJx1JdKlL4~A zl1Z(4hX^|S(k-9Y_sg`Fh=jS+uCRFHc13Qjk$kY7!-m?gL+O_RX?R<9d%lpr4Ai=U5SivdSNww z3wpiS9&H@jZF}UKb?0bR1%#`gK^K*j2(<**{`sGn>DWMf9pBcQ-`h4f8!Y52@lCft zLx#vw{0C}f%ViFqHmLK&q8K_PXcuw*}|_!i7&wK>R(SBe|g)kRB6hz)%|siBMa$=M9tCO zVn=|E8rkzfH62StYroCG!A7k|nW^@pdEkS9%r6<7g(i~sfSHGFVf6RVZH!^T1)ZWR zt?fM9tsioDB)nj=7eDHv>)H3k-r1Fn`fEQ~x;;1;{79kfVRGEp&7qaXoQy;ydV-CXm^QeobX}#7;(C@kIB%LnDjc#R4 zxm+I66zh|QRvIF}W&NqWLq@MlzuDzR@Qw2Jsc~;y8zks<;4-t?)N2w}O(uJVT3Z%FsLPEy0Xn{AUJa+G z{x*s1cWY@)q?6UdwaYhrC%vspt(C7DX((>T z4>#%y0U|6cy~c0~4n9#0JvpYROX*LJx0VBsV~0bjW)hO!mF1kj*?dk-(j%B(IasHD zY!YzmZ3ipwlyc zySK`iDXlk|(rkRNv9t5Eyv&I9_?N?IOV%k+ZG~75%<#d4yi+yVy!3BM%Gz!;`I&F$ zK*&TpFdWHcf8*%v_6;+HK^-12W7_ueu{BvfnLWMR>h@hnBE*|5{66ot<#o$P!ZK$v zug=c?w=c<*T5QMt^?j;4$gJ1qQZuElr}Hh+23jGYm(6b)T-JXScRox`S5r&t4bw{nf901ZtB8W$nIhf0}z-=1pZlk%wNYdvpfVxsr?-cP~YTz;rnc4o!l zMN|N<_wP(;CRpg75V4g(;Ck72HyKJ!dzc>tVcgN!vtGTe!;6wG*QVJ;T`k8 zox8Kb{9vF#rIYIQUYStX*PU{$#~m_4sPj3SYu4L77spJwXDW2e zluWv9o0Hw$BNaA!-JhKEqNBAy;wXAO1YMV=&2Sk__Wq!b?G) z&wmexl0rhY`|41Yq^Z)WcEU)pg#Fz$ucC07dW?;A4ZtW;K4&utn+ zr=~VLPKSUa9(FQD9!s&ai<1e+kg+M|6%=mQ+}fTb)o?;8Iv*7L8ja zK@);0lYidyUPGBzvqtI>?8+8iNF z?R}08iIm8sBSzN6<=kDa$cB)gxql|T4$N>NFz}^Rt2TEz+zOuT1ec&KAs_ts(E!PL zw!~yVGbau>yznte!Vx4;=dT2PgYIG~k9X;U;k}24M!ud8!7zqO*zX8R>7PFb-sbkz zve!6yeg3^B_*e;e_&8k3O zH~kz~(;x13AXsOmz+0?z*k1}-IIc-+Y<9#IgkHC@-l#_^?3l*2voMJ5-2~jM_os8V zR{;ymFeVH(4ZrHD ztfZ)dnxtris#v&RM22ZT3}H3$Oe36URADJqAR)r_sc7WA{{TyI_G3gh>b$u0PepNg zx^(I;|46lwh#`?|!Kqa_99V!}F1K=EX4yR!7i3EHBodta# z97gBj_hM5^rP|6ozKJRhE^c*p>W|+u49-YD5~eLdK}Bg(TZ9KV{`{WQYQ^lrU{WQg z;D+#oMmD#yVr3Ql%9Fx?h-KQSoA+5-`{gCz^O_nT5AAJeXc+cC6+OUay0|(&zos-Z zD-o3tC4^YFF%a3v+SorJPj3uwKD6d34sOJC*>e5-lu#Yy~x%k}o24#I~I{tP@%&mt8Q(Yr$gb%(p9 z8Yn{WMHrV^(@*&kLh7uVqxX^_(Q?J}x-%D*oUF{{v{Kb3Xi{5>~9^y*Z0c=k!{vlG4&va+1d&mhRqlN{@hw6 z*#k77cq_1T@35%hm+>6*GK&TV7(A6LH8kbrAO?vO_&f?d$?|JEqQA>@h^O4EXcP8OsZUWE6G3FXV3XD~{*miYyF8NmNBLp8b8qt+WO4ctg z`=(N#Te7pB>xY95A*gF(LlEzJ!ag{;$0S{rwns9~KM=a!=0c!bu7Q+&D#w3r>Wm4k zpI>D?57~;^nvPTc7AjS6=uaUIuWia4p^7EjGLR?u5o#wt*_P&G$_JE7ih)k)Sfwc(M=!+y_jD zo#2;Bc-%&i#@^O5!p&`vDh(qGJ1qx=nWczt%}d>+?w9q^dwqN(2&lF&;Ko*?v;m?~ zV7VfwV3zj8#pOptU{O1C|8(&K=X<8UoPKBjcw1ar+Us@zb6~%vCm$Svf`U}Xth>Ft zVN@O*A1xBfHAu=4ykA_J`=i-0*Q22}e^F6>orCs1aATL?gW?Sd^=#mUet?=nb;pep zh3fY+oba6k-RkF9pdB;hV?FWcHF~GmZcD;0jY*}<9TUp>*0&x61$r8@nH&b?GWi5j zae8|CYQ3JE-HpP+!jF&dn_5MBJ-$GnJCOPI_H>2AfmMgP5om@IAx;$)5i>-%=hGp~ zZ3C6oh4SGwp!034TmJNj4<-Rc&2|%*VRkrN?G6{;anQT6vvY{3Q#!`|{*6sWuXG<^ zENoF!2}_U?fN02eU6IJjb%MNE-~=BKVB9ANuou38FxXsT+VCz{tV7R3f`J!E@OLcz zJ?98Ghd~W0AqW?p_eY8h4K0B*T!Ju6#Y`L{0~Nn6{S(yFKUC$E&=`=B*h{ke!4$H|CP^*rqe|J{`zRkWP0{`F%?dMon zjIwkX;C^eR4=gjG2!mhHEArLVPC_hDHrv_GuqXHdyx6*Kq1pI{S!__SG2tVB*^sFa zI^#E$aK$Bg`LAGqbQI#G$Y6a^O7Z?wM+-_2uWPYn3EBod7_>#l%h0$@(&@_TVuGpbZ5JGizfIdJ~vD;|f-P@Z7 za{Kgh8=ISEQ@=3)=qft;e^Yh%c3_rd@NDyCWo2iz zq6zue`uac~v7TL(|7bReh9OP{fSDQC2e2CT2g8KG!8wEJi#p4Sm7U{QC)+;hewYx?1yw)=9S`y+$BkWlE=%^eE0=2f zsPpISk+a04P-()zX|CqOQpcD5OivoJC=k-raDZEfGNT-U^QRMKsB=D5EThw>etCVc z0+f?_6k;xpppyL&XjJ{*^Nhz5Jv}`E7>!syaN2T57bu6q z96=H0t+)ETx%#HlOerh@aEAz1i=dd%+ei`MGF7i{y~n7%8Pi6YExG(>D5A}Bk zh3XVDXc)!74v@2_<0Mj4V2%h6_qQ?t6xoDjBog?^a(m!DtNJ#?TR@Eh;;`EfL7#Aw zEUZnj0fD^Z&xxNXdUF1?>MWF87cRjHuKxybUk=y$#g&~82Rq!ZmTL6k;xWZq?fK;c zkdYw*RPM|oL?qaPg{mcl_&UmnDJh=t$A>S0`(W1?(FYPdipS;b+Yf5KoybwxN$ziF zp5PRSxNIkVK~SY~xf1G>hD=vQ1Z_~y+LNb$v|5m@`w5_3F??8oxjRT#etyTm@8w@(dzUy|k4>BbH9f7(W0!(uOa>Hc_<wzk3;j{H`P-EIs2CIcAtOB{_@pGF92LJN%!1Z)u-?DPv4od8IM zDxK>`ohC~RJvfLlFie(%Gk@#=W4u;f3aMoEZg1{j3@&Ig1)6C?IZRGYPV{(8ctz-} zkX;)3aRlN&r}Bcq{#7WmGSRG&@6~8{c?sx+>K0(%A;9#(CjBXxDbL%aX9WvhUC4UQ zL;U8W5tOARbYc2z^BnmV6PXz$ppbUN0_njL9q38`fZA#od3r9Z0~`atB5Xb2GY$^Q zM8uIm75=)e}zV>)D*6dc%nuHNCY+O_na z(+0T}K-3~maH*0$)6w|w{8k{4Ux=eeSmQn!F$B`G1L#uPq(TtR7#dVHYtnP7> z)=g6EiK{Aru_-dI1)EU?qIr7WiqJR$H0-F=v_)6ml=qe%FU2N zvqq|IGU}neN<8{0CIldHNQ0v%Nr<#}IHgT}J+W|YeEHN}U3Nb` zcAMmQFSUIKZqS!s+1yGPwDy8DSShH*024S-kvl6~$ljiLhy>d(#IVB_Kun2UTYxAc(vz_;${cEDWaagvNEBoAC1F@N@rMihu(qyn>2Ucn*yKjjMBWQ=ULg0 zKtvzdXH{|peD3kzg*)p;E^n*6Z?*^_c9Dq)Sk`^(MCx{m@6>WtQ2;p?zT1L*kr@OU z=O}X&`i&b^pxYXMJ+#?7o_05BqVH$DC4crmRoF0^;Qw_m(5{7?+VuAs8@P7~@0M1&4I>e|y6*{${uTy7ju>@*3a{4!tp&HiYR4mQL z7VGcJHBBReli%S!I(RL~jV8j?nL`ZW@t8+WXyu`WGv63pY{KzmMp8){l^mfePzq=O zn>pL@aNOY*&L_cU4S@cHvT{A{t;kCc9cCTLPpGQY34Z(dMDA+H>E^8BJa zUJs#h0;u5UGW1?R?Hxj$>AYc|~PPi|&9d^hVak1JB>sG9~XZz{imk@<(f z1flUdDR6P^hTQfgR0GGFkqxe(FCW!dop+v`Js3aI#mz9&Ig^;M#zDPDGH`=9+K(aN z6)`8-vm?HFm)hY~vUjxT?XnWH}Eztht8r4snru0OaP)?clayV|3Nl(Nki{Ty&Ayz2Q9fTBD_ z;C>iS6^&Ijoyp1mi7`U&vHcz=___1m50rUklj(h{(yzjqN(N zxsS(m0hN5;k>shUX_hsvHmYnduC@qG4vN?zcvbR9I$~0=Ctme;3YAQW?1+-sH1*R` zxr0}PoKHiWbS-?ql|C>T{SzZpI~m3qTA=RRf*s&wMnwc_wroK^0mSHm$rS+LMIvi@ zt4|Zfo*w9d2M@=*Ny-^?s_6WW$}X+tlsnJ2qk3Z5){)Vy)M>yv=yTC-G(1Mj5A-tq zrnHErf;Qan{AuF-?B-^VKhn)`cC1qW*2y7RNQEy7nhH)^el_!^sN_I-4^ZlA- zK?AS!E45~|+5OOzkhvku>1J<;n{JTAsqH;Lgefk;i5h;2Fgu3>;z)$)xL6NYCkm4R zh?An>-X{Vz#MnVATZj!l;@^ODi~yOr1p)_O&?Vn*F~k+8-3Ufs+6)Hx^yOK6UL*<)Q7Xl8=(5p9-6$j>h%xS8 zG-uZ=-XMWq6@?M<5oH;TQc0eHKGe}~8ZP?}$R)Vy_&r@HWz5uqp|MH86V3{TW*3UV zpqYG*U%;=)?Kf=flz_?b5kQeb9uZ{CRPOz?|C(er!}M$kfAvGB%a#YF_nBOox=+bl z^L`OET@pPX^P_2_stpf;#li^Fua0e9U*~w5v07TVcpztx?k<`iI6Mtrh@>%SZijPP zV-P0LBxqcZnH5Ud0w8qaztiAn7kjUoMP8mQmMfWuY3t04P9^^aJv@Om{W6{U-3KL| zA~R&DdvO!pcZOZ|h{Iy4epP+ma_P?Cvvx}n6&1{=-96v-5cR9ZY+5gi?Km@(y&{!P zK_*y=C`U;yiFIh69S`LSToh&}Pxy6K_(fwN4bNA1uQc}-$eHryp6{qB0c46b&` z-2QFlGJE%8=}qmhm*chA_GGZ%{o!@9+v;v`UkmO*#Mf*#-G9hzX>Ydi_}n}Eo7r3} zlTanwB!$;}>3x6j^X|2&GKC3&GdaC(;mF;~>)~o11j>6_r}JHS6W2niRI}bPy9l4h z_V$wZ2^ES0_syaQ1+8SO(}?F#&_jLs|MlLOn*UE z3Hbz>FTLLeAGy$y+0#Mo17L%#oK5(O7BB}KA$lX6JZZU`U#Ye1b06h-R#QxcCX1zSSTE*hq?9KAWDl6D@r#)|w9OQB1tNy{wijhm2pg*M}Kwg5%!5ac+An znd5n*S~^_P18hQ`(Ax!xSi|zuaq?tQ6678f`@sGi(Cm ze*f=SOmI8c@`vu_F6*IxvlP#brff1x3-h@f%nrASdaRw;Nbk*IplL`8jG>|AqUR&N zQw`UWIKw&oK$W5&kVzv!t5er8E!!ty5vG(i{f%fY;D;eIYrh?&e}1yf!(Oq9781qr zy~w96ee);?((Z7g%W(6EpyvYz7xQt*UpK90^V##C2w^tv?V%bq0-70PnR1C($ueuz zRx7(+H9mr+s*Pp~CCuU2=h45Or(GI!#EP)o8oQcU8|(o94K3fYP8oOx zM+ZNJUBUEY_bMDs$4(G@eSOOi)h{AK48Y#!eq0N82`P~$gNlFkVg{~8I3Zgz^&TeeqOGaY{{DQMlEHYF;P4f)pgF}!?4rfUm`B9n7Vj}e^kCqz} z>MLIwdLO}w7_<=~a)|Pg@9fW<@_v1Th9QMnst`_f>QZYJVS=3Ve#E2`(NzD_CJ93J z1057nvKIzcvSfK)ugky_>Yz8lPw;ZpVIg+&bfJjxX^YqIf|u>-O$FeT3~qMWG{D9P zj>j|pI(7S{#(2B#^?Z^wM0fg@P6S7^q$=UdzrH?!M@dFCW4g%gbfY-&${w-hw^%ef zT86(`4}ZGl+gny+yVaISPHlc`_5tPh@({D`79rraVc$16>W8B-#}O~D$r{|~EF`i% z3p=CBQJ4Me{8W~c<4*5$L+O!!fz0V$!iOL2qtHIUJ1)1=T~1Q7GYAx|fM-@=sY*NN zh1%)R#EPRcXNyf~E3m5KM?%_6#(U6M&Z#9F2p+aE3UXKVmNx zI*~Y1Mw}|BX=bG=*1`h-lE!4RxGnZ>WxBmbibsOYKWx{K!knqp&~H?cD>AfPY)sWl z2W)WPpbI3jYKDmiFbt0;zlt-l+1=o#Dx*R{7_OJS`Et{)6tBOsUvcp{*|JE+TDDs? zTT7;lG_zSea+0~lde>^*Sw_dKYA7DhulzxqK*K@Q9$r>!wY(IZ|Kh*QtMf5bdx;;e%q%v$47(XCnT5@N6 z-rQ_6_YoF0-1cg_olpL1I$J6?jJJ|>xqbQQzgLA|NOfn@n%uGkd7>UZ`2eX1t~=il z#V9qKR+nSl-^xtz{ehXUc+%jWZswa`Q8x`(407n{wFkT*bJvLY+_9>CWlX zXJv^v-deY3t1?)ZDilB4kbGfkd-d8}jpnN$oRi^QK0kf&TCNPAzCHREMW8jbrn9c3h2<`tdVd3Qa zc{wu|^!nNQLbV8?WOQ>Yl|)Oy^pV#$e96nC-5zKm zPrOk4D~d%)1}_T+17i}`a9oc>A0Irc&|aBNuYP+p;slnyJuD zN@Nner=Js^i1>+wo05S)D7%dd3$P@ZAF;NG!Rl^&FGRCeO*Xe1?=YXWW(y!{?Dk&Z- z2v&}un++>QEk$y-iuWUs?Tx1*%zBN0zY4#4*vB#Vvgsk zNgvU>?ej2Q&~aen9#6I*vqFj^qYwrdME_NBoiTp{iEdR$D1pGL>I~$z^%K-XPw3<4 zLBJCXDL!k!V*Ger)|H8<5?m9asSfmAchdiyS3x2Y9H!-HR4Z*o6)m<>2miDijjKzh zh{ELY_$Ts$dexi1;UzAY#T~c5j~Qdx{4e$J0p7!@JA>_~;c8`wE$jle>F zr)d_K#|8VNtSBD?(&;R;I*0w?y~(yqXFbrWKy^6kZ7xKXx$N@L>~f4o^tU7khLeLj-q5kOzW6_*<4IGbF_^|y%L zh4w2nD6UEsM@mwJi*WavjV-eD`^_yEIxN=cmOGw4&90i1s#ZF-&0k>}KwuF;=39_K zMR+g|;`Ls>G$zXe>wUFnD`Epdz>VMadQQQ^?@A< zg-aff(j8y09SD4zX0l%iu#L^*b~>_0AnibzYcc1Wy{4gDJz=>(+DQiIC#zX^$|hxU z>kR`-#m?C0TV_G~w%)zSVL04ZT*tLP-iOBF>qx;dG=c+l&&Oe33qfVIR7D+r(P>~` zkj@1=@kWD=c|`NBM7!dHW*R);~aBjM+F z(d=+pWJGRdXt@fC4o_fJhh<1z%%OZbym3}fXN}M=|H1u>fkG97J?NQ=X>k9*67)9T zdwRZP?J<|_$f|)a`)^redosj?#niBsbSd&dOOw5f0X{1P?qF!G&i&zaL@tM;Mvcs@ zxhfmdcls9pZNAnGNZI({sBQ|B|*4fVI-WpZxka~F#ye#^f$YEcg z%9f$U^6_0J(E|bq-}5%wp7hVFx3P)0M&CV4Q-6iV=F-w&)oAv3&G^11^=pLbRO4&RJYl9)e5TWYgBo16p%iPG? zz@P@3_2NJ}LtBb>sr+`V4Q-0A-QSYSi?M;~?=KAjazQ~}jaDpX7tpb6jG9fcFvniv z+gr6hSm1-%4~Mn57!%PK%h_Yc&3d26RpI^pws)TFz>|FhgoJb58Uqk$k_992Sw-Hs z`1N;j{NE*zvLA<#W%20MAB_Sw+7v0}9^bly6bTQRK|!bM?78@<(mA8~o|+Q$a)gCp zW(ofsutRx@!lU9h9DGvqNX04{PU@>bXbqX=`cTG7ChAo??J$x}%ghTpf}k{5%Ca%5 znZksk1Dy3~c`BKwf|kSQpv4*M@S;G&&~K0M)f@U$r~eHR{CP%k)av|)rtr1-DIt60VL0IFKJJbv5GfkahtAWQ3%#rWbbeECuMtY{NQ!oP!|3vH@d}&f{uDi?-F^yPM1=y zQ;h#t#ocpbdnZ1APRY~(IpQME$B`mn#H6pF7gB|b*+m_F`56d(FNqoH$I{7)vtBd9 z*aD(>8n$79q^~XC0h1A`59|lT0EUx^3|H3J;*sqv@xq4%voL#K!ug9FYVBEcX0g@f z&?KuecUIsxTv0%eo5LQ|6flKX{s}OdzhS#ldeFN96AW|;L4`f?7!^@M{GGpeH1Jn3 zKi%+ofZAp1AZ{P^=*fOkxA9_%K7%gRmkDtwN@JdlB96<6F|DpB=-tuwd~HfA#;T`g zGns$^F`cv3HO}aGB`aFq7(*IE(EVO4Mm1aG>PHr}Lf08ajdl;W#dHfve!e=Tv1{<> zFOMdxwY;bBIy+;}?3Cn+L#fCvAL~&#-^Yt}46ED_0bZAXpu$)++HcMq$p=4^l08eW z_e=YL=2-Yo-{^;Fs!SrPPqBVZ7DGG2PToQ(KX07`nAu}6!r4+zW`OZL;lat$B zKgNoh^AY}&C2H;dj%m${s})Loe5@Ba(~FCo=x~;_R|<3ez)I~8v;88tgFwctUu^Dk znTL^}9?>R0KIz^w&Yghm-{jq-O5QaNn{dVcz84WeN6~nF+bT}oq)h#d z9JN+n-eswRlfMW51{#hK3S{Wb_=kYytca`Aoo?2-M3CA=Ws_=3ad?lCxrEg5Pz)h1_-Z^#+>uwkjBf{7|egO%%#X6qr85Ty64#&&(YcsB^^>Q6!WpYk9mOx~O_GnVoXtL`F;ivTjGA`sl|Kqn8@VeMU19eMmYQ}j6 zZr-yU=l+(7CB&D#bG@&X5k@r0!jbfx35+%qAv_=V?SC;=YLbM%i&{@`h!`Vw3XZKc zSOM-g7t)|3#k(Ax70HI{?D zdh-G@CmgS#m0*8 zNoLaoT#nIRT|ma+JfI9--`>O8oKKH@_6#8YfqKXq6zmCht7B0{ zd_QLNVZZADe%Ml#X0^~(n%2&x9RFkTFH5zkF4w=^$IM~myC5`+u?XwFyNmLM?tS1PNtF>$O4LB`-Fv5eSK9d3UuZ@D_u)A9~m8-B;R`o*Ycw~ z0@Z2oS;W{`X#?U;Rlf&)BFlX^L(eu@zPaJh#`Um1Mh#3#r!gMhh5{MXqp_qgkHmi= z>WxsbST`GVP&vS`X>#FiLt-4xyVH02Q;#FEejwC@l`&vv6cx{T2Mol^4U=Bo{|lhi z1owESrh+wE-|sRg(Ih$(H#m1p3)`6-^W%3i(h;S*Wb@r*HmJ{##?dX=*=n|gRwdmM zB32P+@h5Z$leqKh5mrHTe6A$Xz2RMT+OT$x@h2i0xSUV>RNm(^Nw8Le&w#a3jq$t8 z7htE$(Z7xe&aj9ISZo!`9WArw$vA)3;&9~rTKC&UnD7aU8-*pqfB%(3{&P3*#S;N< zh;_X8ACWZZ<-;swzz^Vi(1+JvQxo~^TjGaf4MY!Zn=d(wsdg}P)W)R2DR3F}8N(9aldoL(6D;SK=+dg%~r2=ntWv=AClfH+!bwggb@k~uRB+xh!`*et4tmc%L*R`59}xTI9#=e z-PG)0BgoKEj*a|Ni4uN|cwJXyKk9r4tU1>)e*6ud@leP!xzy;ICc7>5#8rFk9uKdF zl0Vj!Y^4$R&GuyWYm2EwazC(lu;4`6fX9m)u>6zbvX54l)*6DT}Am&etUJ=&`Cizb3w1$6l)@l_>cFTWwLZeo=Z&e>q(8! zZ%7T_<`9!*EBx$Z`fmR4zHKMlD&#)sYuxjgpLe9lQ=6g7XQ< zUF0e{<6!smr%(T7du@^U0M8ov#r9>ofQ=<$h55deTl&|8ButUnBz_mKA9h1{4q>H7 z;qROrh{Ca}L?zn#6ib5EAvuxW{fBq7+>4%+PcHWula=RFO`<4cVCVC?z6PFdGp@Iv zyEz%Ey>0kn8?5P>)Dn@Bq$>p*b`J?0t8TtIKo!q&=mTEh2JWb|J091#N2YcX!upYw ziTeIDQGq#|PBS)&@ztob>h1OqgSbznW2QY2#p)3O*W1QN^Up+;bK-%o+rQ`8P>4h? zf1Mxs>mEF3`ut>mM?NfT;g3_Q=E_Uc{aV|vxizQDa`@hVsvC~MjjATFvlN41E`6I! z@4z5c{Xhk?b-Obz?IEL?NmdjSQ%pP0^kZV`udNyt7Ru=vzWNSPrkE&NiE9(8sqo&h zZjtoal1NHVDRD1;bVQcu{FyC?fX8E}=$y_ke65h6KaHJ|Gmmd_Bft3FP9u?9j%({= zT-!2TU)mY^&F*5iC4ObU2_O3|U^1p??BO=?sEkL=7?n=fj*wTv}UOJUnmLqzqu7UZ{Qh;gA9{9l z4*>0Wv**H$q-@rw)tBH}R$<`v%f$BEj9xqKXtz$?zq2VVsJQGMkDQg=t0E#JThG9qgA0BphgVil*+wQLU7M=*#K} z+~H2ScZv;yIgfcm!Mwzu{@MFeJ06+a=zEt0vdru5=U6tm0-N=Z@Ph)9NS*6_eYf1W zJjx_<>!R3e>322@4!1S#A5rK(IXMg~TOo!0_s84n&9oX!cyDV_Ki;-J@Y75ZfhX)u zNb;K-h9sXX;0XK9COw^dUpk5H0_rfPVbAO zLR`%xt_~}-Dl_D%Ye04xjw88It;w4@?F2I=kDZ1}qFxowtE^ox(49-6J;chMs^@tE ze$hoh9rOiD-WAOVQ3-<~_x2NZ1b3X)3^%xD|=8h@sH<~C_eE>z&*bt>&1MDP_OZXB`UTiTUeB_sEt zGZhP=`Ey}y){y^skjJENJhzn!&*wI${>>>`;FbKFpBU+rxKN{~!%q_9!h*{?^8^O| zJZox+W$r?VQO@AD*&LtcwyLmav80UWPfs4d>ux`9&Xg$rB;l=zdbW711kU%SF=(b@ z&5_;{F*xAic+FAaf``#;mYn9?iW+o99eu2c%cdy(Tcp(1Y4Q#ySXK0H6%F)+=c;|WDk{RkJ zWYQdR{gs3)9zY)*iDjqc{j*qepZ|IXZ{EeMB?*t*03 z61cqI-!d?>mcGAJ!}Xn9<)iS?*X8-?bOM;2wn&bO;4W8_NH}C^RQ`O|tYNWZM#?41iP!X+Sv#-Bz zg>z=I*ns@Wd_BtNt^zIKxezzPNx_FLjEAm0KV~(z>Z=FdZB0|=_HdE~PNY_-jY_tw z?8V8~x;fll@zEs(@F7_6W?ufjQmkgmCtS7u z9<1C;+qnWbTb9n~LAQfoOvvqrIu$|D&7suGjgW{M47PB+oC?RICKM`;`{`)Dd^z3U zWo@ei&^nlw(%Gd_9S2uxeAtkP5MhB%=obh+pogPi7raKMJr<6&4;%tyFHr#(%<<*; z_Os<{V|0T*0o~KYR&-ZqzV&GRmq~YoT9@`riJRKG5BpOL#H7Afi@QsBQ^j&ODk)Ni zXT##QDQ&9*crTFtX?U{*kw^DeScu2#$Y&G^3 zc%`jE$P|MOazDnV>}eGKois*_NZE%y*}{mjKceS85)B?BQ7f>jQaxA`7qmE*oF3E+ zXWPU$QTCK9Mo}CkMCPd)w7ClBk1BFCOOMWu=Nj4mm`ebu-l;6F&iH!oDNffz=bli& zttVMKCjI>Nxw}5a^7Y)Ld!8sVOc)Ne9hrpB`Kroo)tyAx&3&?fl1=95lkJ+DlFA3c zw5Rir+ll$J%L9C3C64`G7<3TWkTs%YTbDR?L^V4#+j0yDd3y7nbe52J_N~6uKM}`( z-HImUZnw{`SeUi${@s#hhO}9lw^M*P%=9Xvhn%q+$E3f?)d7@AftqpF;@8V7lWuci zhnL5XT*!BF&N)uQg<(%_HZd(KY@cev-^;8ce)i>iU4J3Zy@!#w)%5E1CX+ug9c3^O za+I%zmNDVPwD$az=0 zP*(EoxUaW&^_GO!_SYfumuFN`j1C$;Te5^t(veNMIy}%jYKQccKOD7W^_6z-K6%lK zwsTcj_;yrjuirDD=$6XCbYya&tqM=XPZ)GkOzjX&wU~NK(>0sl9^~Q56OMmPH`plM zhu1H#6|QbWN&7g6je4Gsjghc!SsX{LDorGZ%Fr&_?SkRyPqSb0;DCSPO8-M%x9wGI zs}?HaYR^+me%1>jDZ4BpK4+}^@qkF%6P#}|+hSM0w?8UhYuVaAzEEq4Kht-(PqNj}Z?QK<4SwZ*tR2>R#{G`#Sj=<;Zx=*qy<(!gnMY0v_auaCkfk zL@NQqC%5vK1bkT@X8>A~Bj8xp;me+NCmZPUN8wLw$?wZOJ%xrHw^_By{F{;)bhMbz}p{W(u#4Cyv$ znBl#-R!mzSU1fj&ll)bYTvBw;74hrG2m}uXPh|^1IUUM(woc`{NgMVZ?v%OsCnM=} z>B1fp+Pgx+{#UU_Z5fVb(z)`;Zcy#+AkNnFiy!Mmi#7hwXM&2Hgye>~)KEMUSHEaa zg3+@_tN79Ib6FHlfH@qEg@&QQcEBYQ70tcGv=|@R_mZra{OSADom(Gin--;h9*z;=D(m#tM6LvQRUB)l5_(d_cPKC-Hs6Hx;qm?@MfE2F7Mg zl)NBK-p&`u&e!t&k$m5KkpEOK9}w=9pqA1H#!p&2~7~5tlSay z=OD_@X4(%*=6>X4(ZvcDtX&2mysKJ+m@j@Zg4 z4C&zXy&ZO~^+jyR+DQ+_ER zv%&{UDTUl+mm@rZ%4B9a3vCy&U7eW&{U`SmVWx*=PW!N=D&(EW;o|gp#Pb_I%5y!g zt(9mQZaX&FRmV>MuxIL96u&Lc&eo`)Ca09T!BU0@e%CM`G?G|CGmgbo&N=oLlwYs) zpp#Zsuh~08pbM!lSIQmJlZnKMhIdi%W36&Jfz6d!DSxN)nfgMRmROHw{nl6Zhq=c| zWTAi=Db8>2*39RYKQN(OuBYOB1%O09+_n-^tH$xTI36qQ9PJ702% z@zoI=toEC+Lm&4i1^xJ&nN^zVmTar4`Kktud&MydlC2o!zgUXUg5|MMwb%-uizhK~ zuIR3Yze7*vic5r2NA~SDYzUQN)j^2-!qj-?c7?Hfv-AXCm6t8Yi zWEUg($S9mjPPWH4C#;olX_oFyL!i0u#3sH<1zNj`%>ipkQj}et7g|cvgS44_7Pg%P z2YY}250lDMs1gg2q0OGS&hDr+7-4r@*%EALD3R3J83Hv+}Yi(MzdKqKE3ajHAB z=tDlhAc##1>!Wlo4|RnPO6(^nxc6~iEYNbGlw3u}Y-g58OB4l@8xaLrLeNuw{{t2B ziO}9YEDhU^=u&L8P9HiKvl1IsiJt!3@G(v@FP0@3GS`4-&L8#8zAm}Yj>zFF90NHI z8QG_ZRMe#MI3@i=qR=K<1lU_P{@dFz0=SUjO zGvEv;{fs^9C}H&JjxpepZ8WcjBsaHkX)#Z8iKM~L*>AKSNrmhZ4E znL;W!R6iAB&A%~d#ktY`1Jti7&;#B64|6q zzv}@%;b)FnTLRCkI7Znv*W`%J)=$-P*|?HJ!O0@zTj-Fo+m7%o5>@DtX#cu$$wR^vEt>Nam@`%Q#A|pbq!qbKI zaSJi1lcS?yD2wHYAZl0Rg7 zMMg$uY_v5_#Dj>#0)leVzy@-HZu-CDpl9Qc8UC1u;*QJsQ;OV33wq6a)@sA|5kQNz zdQ9eiL&D);qL5_^>t+lKBs_^#UK?>R4pmj=XeEUBro%fVAB|1l+t<4{no={7yHks< z48J4^JcO1@m4d%}*hX~6Z@oPz+$FM~-P3QP6M#=4ANUO&^bRBBS_^FhjpeZ&odJ-I z+8)m=l&i;+p~|^r$yfy38~P}H5!|e?7CWW{@i&|Y=)E0Xs}ZFSdb$!8C}7&iek?mOxPdzCJ!E$dp#eMGH7@-g$p9trQ}bc&BY;HCbSoZ!DkF zb@WidDf%kGxahdO`aHh+*7lZvu}$Y@1O``l#6(U4ZwOMvLx=DBfn;-~wcpsV^i9Hd zIP%@I72>WpbH!i$q(J0|*i1+5U+5yo)GwVo+`xSux`-ibUO4Zcv+!ZntC(H?lav0G-(|$=hj_Z zw9hjLdp+H}_C*{~tFE?s?yqEx3lj@EF-SC+=`@^vbNGJk9t5;00e&4e1noV)7pQTP z@;W?Fo^INRwlrnvp#Poci3aNa4#^YDetF#T+N=dSnZIRFK+_znmR((63%cFCv{wu7 z&YEvUz6%i6)IcTS`{9s1EcMFYWTjev<8!5EcV(mti^Ro=>z^QucGF~|{!McpkvjT^ z04~FQ@KEHLYwKz+1_&fzyV8{F_Y4aQ+s>KC!2Ewt9XiM)Y;%XSR~{tf*dJQ)>d!i` zQ}DfG$LsYfEnhs!@rBJJ8aqP+|2Q3}PV&p}#50)7OAVo1prHTOId*g=RsUh7ag zh6UI$gUa|l{M|1plDFwzKHfa*w^?ADTrT1~I-x05sa`cD`>3i{0N)EWq?7Gd+~>qf zc`p#;nn7*K@|qN8v0`SS#~}CB?3yuUO?t+m&qLX*Q^i2RbP_rufj{pVX{( z&bQt@cZND&GaYb*o_U&ayU+Du4W@L(MlQ==~xN zyNrL*!~?@V*KDU%rZ^vMIcb>cMC`WYAiHsC)rifid2=$AHCX%ubTwQVrwgMDwDZ#u z2nm&n#agl&wELglMF>8*G~NPjy=SjJq~8o9BD%gTF=;oWa=fq_e&6ugazrN5o9`xG z@u$kF6kCh*&HYz`gJ;6**#6tm4vxdv*q0ExZWB8j48iHETe(6(Q_wUF6V^>N)oDB5=fB&2nQTyTe!k z>64|^Ba(*z)T}_rz+PZUb9?hvQEQHQxb!>zaVWmP8Gh7Ru9QxeBevx zWm_~3hvG@xq?z_PE1Ik>z*5o|QY|JIuC4Dy4PQ^^qnwpElG0J5rQDBa7A~f$x2+zf z+|H&O!pd?;s7{h>g9kOBL46tnU5waeKeo0cAvV%ZvnxF{qaZ#2T{`cOGH3XtTY2$t zx5cEqPj6D$3wi3 z9%dgbnwj*7#jVW_uE-~|iO7zC&vzVLI&emkaz*fZ(csWeMy&xHn^SNs3e*E*Nhk=W zp!M9ya5Y}u*LI_`HTg`=Mf<71lJVl<J3a2Px4H#d0K| zt%ashgXBjt@1*)WG-+^U1F8M8=76p`Yt7np-xswQoRwTb9#vDc+}m}Ib&WI~q1GT3 zZC=-m{$WdL<$?SQquQa*gGoE$$k*aUoqv+X*EZXP22^=#^nP?YZgeICO#sywGtNhA z$RCn)lf^ggNd`N9Ohvt;*BlV*{v($29@$E0A-Guh6ebF?lN4rfRdb=xm^f2A2DLtK z&Lr_>uV1zdEqg>M2Gyu3;PNL0-2O2(G@$L}(fCnL_ql}6@J(?iA})VPmLihZ%MFZc zaubnC0BN_`Y5$RoyTW5CN8&iJR1UoFE6XU4qt8i}B{xEX_=e(!8)nq2a9xjId@cWF z>U4Vau){6rWYz#WaN0ms;?M+|!VgnOCY=&EhzqN&YfKHZ8cx)N;`lzg_i{9zxFg`P z#6AL*fYaRB$>~F!AZNIl$c6_geO#Y)B7-E5Sa5+p(5~r8j2J!giVM=9Uspl|o=7fc z^c@Cg#GU~sd!It#p2Ie-5&ZUuan8=3`8xghAVxE>-J{yQH^XteT0ipgX1wl>qS6)Tw=QASttt94nRo^}D(%EgrYC&;t(gtoHMCnY3xaFmI}lS}Ij8kC~*Wlnd5p zF*06R(4*lAxQw4pYT5)Dd$I{Q_t+F=)m z8O6QuY7PmL$y1b^$UqZwdFZu9y07CMg7h<5CPo{F0!UxkR+?hZQSX%qBSgamm58Sb z1rf0$L-aovqpM=b>EdXU zG>-Q%YzD>IO!c)h+yM3Uv?c6lO&xtKlnW- zK;gz)l9Tf|tPN$b@9xWe=I!(bh{y(-9RcSg`|bYYgifpMXKyuv{tmo<&inS>47FC8 ztUtIO17{wm^Xf$mBK(g+CV3Ji1raqPG(n<@7#)Z~iTR60zww+`H4t6~@$AKlZ}SG< z{^X^lYOQcL{aQ**6bd^Jp~WC^(!|Z#{ofLs%lxs_Cje92VB0V3b;1?(XP!mHJ}gSt zV+LHCs9akIk4A+3;@g?Hc09$G?|5NjyY78k486qXefRtMbRq`<3Q8`GzVAZ>bW|5B zs8{NI6e+PZZx3q{R8{@(EV=Fj!ZRQi`VlS2s?;f9;)hLK-ehjGZeCxZqR5X5+b&0a7p5US!&E3eTa6S< zojB+wADENzb67+3c#6C@A6A3U{$Pn}8S^FZE^Lg+kpBo1hudwqswhM7iY&;oMYhI!D($ZaE$rx{dJwYCy zz5wd1B9A4N#c)N1$C#rFFD@}VXV;?YQ>oHfA9s6xC=DgsI@gJr-Hl$vzA^?jWW887 z7xfjlhCTz^e8z};TB(WJ_p}y_4^|p>VS)Paz8$_H>5BIiC>&Y3+PrJ}6u@T5pJvXq zWV>D0DlPZFDJ)bF0;M;(G{6ve=&=9EWeRWp8GEGH7*9T0`ad}|kaGnsk>z8@FXfl* zF#IjgKx?Q&qLC>6SE~K5)C_C~=rB@tQ)*5)|EkFS>n?Rj5G9UFFewzOKt}$b z433N&&=@GWk1AUK$ti)HJ}i(Qmq<{4GvLkdMm$>dKLaojgx+xvj9i@~X0|VJ6c1VQ zF=vnxD+vD2Ew<9c$xz`UAHTXod4UkoLm)rOF|fZ=kWl%*yLGew6DjR`it zg6@A};tdCMBT%253gdr62a}^i0mH$7no|F(kNj7v0EvO=LGjxq<^MBtkr2ReA|b38 zqW}3BHe@{cMP*mX)%cf+c!<*f`?V1=w16%Ab#!zz2dslE;{ROvmuS9o5zCalF8er( zjVXEsHI8X&Nb-MY7aQ`D5QwG!bVnmo?Vn)S|LSS%BO)>d|DA{+&p05G9kf*#_^L&a2uo?hsK{Xek6al7T-UnluGg7>NO>zhbDz07E4?i3F6X4<= zpub_!Dl+M|j0ucny|+ar<~KWI^|g!8i81eco5=Z~R+g0;@_4@)V4p}p9?9W%u_e-! z{O%Xvw^K+R5=aqJCYUN&`na1Q+~Tl)!jHhL8H=y(`AprEL#b{0+Y+C7A0Yj+8vd|j zFPk2SV}!KC5fK;f2VizP40sIsVS!@syj70*a8z>XV}pZm`a!s7w=efVGvO5t(kq}j zl|X2vYysvsdHzqw@x&jfdj34$!=VuNvoZMru)Z|l!ixqz%o5SqK-XuN_iZJzbM!6{ z7yauC9zH%DNVmmKyTjey)3a6Vh1H<5HQ>$vnl9k&&o`7z`-m);n1u*(kU&UCNSQ*+ ztE699)fjM&{rJ~%<20g$;=3Wh>4obaPbl#5Xqs~E9YBsUur-?@rEYfI?j`kq*w+2@ z-3{;_1MntgGAZGZe$T(Z3BNw<0-kF!$B0tW($Z&ZZ7`O}fQ^MDtPnl?o)g_q0JB$Q zDnSG@p`L3s{NwfM6nIA1bjoB(xdPbVnxhN8UL2Ss<^jjHhW2b0s=QubydJGrjXy{g z4y+t(S<&%*_c-6E(ry&TX~0+)DC3T-hFR9eJ(zCBaFZ}nv@1g+ZfJRHqD@zOg7Cpq z81dz~=*@TD1fb#(S$f2*5`Cczb>3e{DZnQ6>@z9{WNDNYUDj7C29{Pq(K? zxJ<3aeXx-M&%b&0>T!_*Tr`81UTWhp!z_S)-sxnFuK?(>Y5dcVN7$dE6VU~XYDCT_ z#SJ3#;_u6NCWHA>tW343-sMrrBrhF&Qc`5*ShN`IWO7y6D|3xJnwFeHtd04K(rZsr zc|GlCQ*`?BJpU`w-z~)GO7ax|l$}R+^EZ;27YuBDAE)thRf@%8_n{05puK z+rwGMd4t)oYPmA`laTdlH@=WbKYaVIFMKXGjUM-B>pVIU=Y21FdXoxmLXi zz!Vwyl>`tSCxzc$0O$=eEgi+{>nrd&_mrcWFV^U@M}w!@Tr6qWf%j4dfF=REy87lq z*y-!ni$1iKP*;bh6vZ6=G&&W?Foe-@09rXMy5V=P-w>jU`Ingrm@EwSg(@lXun(($ z)npEMeE~R^o_D_p`t$tm2q+oJKp)&=Zz-t`8v%M|a)K+{XoX%I2iWgwn0AQGVhkVp zU5eNBfr!h+Ru7ucLtv|xca2_Kusv+WhR^x;a1ui0cZ4LCcpz4cLObou+O;c`k3*v?mmiAuUhMjC@qm3z@0z(EoaANm0% zBY@*UAuYAdSHLh*Uuv{O+aVVKP3_UqOqnKs_kDEE)OP*`oato!@lXg{AHd*sW0EcA z`v1B8C>acJEbotJ;k<>0>8J6Sb^2+?WWwg?rH13g0gfM?UMjLZbD?N�kVhFg`v+ zrfOe%_~cT(DMTlLtCLG-+E&Ykaarz0w1p4`aaeEXD~Ilc&4jd>1Aw)Mx0mb5d`lH0 zeTDAI=@xrkDh$=k&q9He+%f?-(^6(G4;R~AZ?7Nf`t;!Qne}q)d}nqdCDPCl(JR!f zD+D6pAXgA4)kSnm52`{Zfu{XPIeK^vC2Src>=Z4k`F-h+gRbv2OGQ)4I<36b1y+94 zOl0>#(%7#w6{x_^7dWi9r!xJ94~GW~RZaEDZHz5D7Z2u4wnr-ChcCX?{=jrzsL}TU z-mC^(>rv5<3v;W$S4T;b2D&C{ZZi29J+o07SI!KXmD}QW3eL}pGFJ;F?|PYc7YB^t z3ek#9rt$$3Tbc6TM=So|J;guoc_EqbW>zEV;}q2^>2j(kW~cJ#dgEV}DTgpAUBi(H zj@XZWpy6EKtey=oRUc@W`ulMUto$nViir*95dDgu>wD?D7JD=;lAK0Fux`(bU@ z>rM)Z0u4FHF-0hp1OGZ|r+28Q1@q4GVwj&%FqO>I)o!L3!696X<`kJzo?2Tk5KZvI zI$U*5624$yJTgZr+W<21^bL*gOdbG#%~6Kc7kXqj;*4)7r&`grhwNK@Q*S9DlU{i5Gqsz_L2_6N|~_& zCswHmYrqY@KOqUnP9$)ffK(kk7xM;LRE~U;?b};sJzE;t6Hm(T;0u6#`b~7BrvL&lu z)LgW@V2tHKT-v{#{}U<_Kb8&M4K`vH*9TEY;0W-SFy`*Et5ZZ3xQ?-kpS>j|LzVI2 z{pt`?%Jfrh&CSxfxa|$FT7jZe-V*H}Ku4rj$h;5Mlqb>P)pj?ssh7-L1XS$k8cL2& zw=G3|Qg=|nWluyA@Kd^3WfNKhkpnti@FrPp7h#0(3?$2Eau{0-N>ZfM9ic*JRteM!o`vS^n#q&ZTlocO{g#;O#>@f9m~ zsb-oXlpL=QiaLkgR5F$^l!8i)-C}!e6eIQ)5+YunI4%?-EspgeAD^765~>|Tn5M{8 z)yj^7yxp12n0Js=_K2W5><;!JnLIv~UM(0C)mh~4C9qE`L{q663bcnJ4X0i+g8$>f%$`K&7u+O_ z@IHm}n00w4^wm+jHiCK7EPY|B|DOGbM~m8$aOH;f3^j@ll4Q4p;PjjS&g zjtrq8sXT`rJQT))v^3DvpaMRMjNPP)(=6CeAZkRkL3gp0jZmtDC{MP{%9IFdejgO7 zOrs1FNhhoP@oB7Vo035_1QunAkB%6k1G`UW+r$D&en5_p*qi8P50A>4R~=z2E;wY2 z9>)Ob$KIs0j2Ld7d=&%)DmJuGaCJ?FE8omK`^`H5Ejz8gM2n93Q~%?k2zZq)5QhCi z1a{iD{Gt^moVQ=eA`Y=MEJu^f#iriTdRN^?d)~TN9t|BWhCW?XJElCekcmli0$`d^ z!d8R9%CsCUQJ zXHlCSfSLr`jeM2i9~c9Wn_3CJ;}?|BqQ*iX*UKvrv_~QZBkMoR!e@dw>jxBUEiL4W zFfB0WP!ABxA8)Ma7>&kTrM;#&IZ`aZg-iIHj<#40zb*KO-VLZm_n?ZY@#s#hFg zvw13Cj9rA%5)>R3);)@2B)J6xz?D08qN3Ts9Z1qr8j9$b7_?|Y%AgD5VoTosxbE0X z6Iq6q_jR1$n*t7&b?~XW$>hrXX&xS8JSeANU-S$ zkrzr@->){477?ti>h8 zo6AtiXq#0$XNZeHMUMGR)2^AavL>tA@5}~prpT=81A=X6c6Ykrd*-k{z&X5{sF11H zLfYCw#s%|-aEpnn1h>yDY8C^jLDbnUpTJv0LXBgI5f>b+w6koRoKh^rQG5oSE3+bc z2In9tbLOuYQsyLB#lC*WAw9!}G*sv6(WIJq?XUGiQ5LKZk<5oH{GXt3@j3D^6ecAZ zr+O6`ILZzHQ1_Ikn^Ax7U@_#lm~IRemaRFn@id>Acuv>dEC|{rrW+auOE!i$X%8$1 zhs7M;exy9&4|W&gXm`d(hsd%A5(I5`%Q{n?QBYbB1{RGQjx_?Ab5iLs=rXdR)@!U;9j$uMjC4LKFHY^20>aaeAkt_Wo4<1CV*94VG}4@-aa!nlF&a_sxeZqDsOu!uIXXBkZNs2-bln z@anmN;owrS$8DO~DRma@OUF(w4d;AOZdiGWCFyofF7HFW);bO&?=S3zwzh@r#td`r zft;)�svt8OEbQpR#xXOFPFQ4(*ZHXSa(ixP~#t%471MkXzN21jZVj^dSySO$0_P zppxn<(i^Ij9@${>5Tn?~k(!I|m(fJ_C{fYUx&2+Ut_c};W*902su&Bn^4m^M1O#JI zap`f=GTS~#^u3cmq?{uYrG|KMIyJI5FDh0<=SG~gG*7?>qk3l2{rSt}uu z-EO&NmFY%lNzUCVb`kKtp{vH8h1vavEXoEea4EAPgLG-O0N;BfTb^nt*&meXx;YaO zhoqyDsaj+=tXwTtTzFf5M8n^VVvLRq8T%;8c8!dQhyvBJC3cs&gur7GSmt<*hg8>( z8$@7bu51UIBfxAJf(U?x(nl|E*jGNZzQjTozmuRth>Cl^GwY5^_dW?Rl6^#H@6(y} z-yJ=eDtTdGK3(VpJ};Ifx%*35jU#o*M3ACbS;)$G7CaI){+lbbug&P3fcjIUJBqhD z!!bQ^JLvc%qnS{Su}Ej6MUvai%>XGzUXC}vX{oBojDM+_FD;DmSVmvdZEui+>T7$; z-<|nsx^ETVFRE~PBuFcy3iJ(0DJraH4E?D{|G+1C5_6_~M`6fVnuDllLD0?xae+y4 z-&1J@XJc((6oDza2y%R@Q@&u4DtNdbDhG-bRvcSTAhVVurGM}>Pom;ifak83to|tzy1Sf6vYhT-PKyBck6JO2@9;xi3%I!b z`ITbwFrhIj<%ZmG%_@R2*le}sMGyb=5CEqf$`dMb>y=3hB@&=Rzn>MBn5&)NT0QLX{-gb z_Xih#LJB^^EC-Lr!w5Xe^fP(OoW^X)U7gKov5zk>de4wd0s z;ULlvN+2j#u-odx^)-KanfPU|%rXl1>x8FxL$w5?{W+b8K20C2i#7vJ2pzDq?8p{Bu{&Gz=pm z+(Qsw!9dT)7HX%DkWwWAsOaX~7p)X(kpIzuyBQ7A9>ai(5_J@>1e4-{t<=+{;Ig1u9x)N{|Lxi1b-X( zI7eh;D*n+-6C?qdnMB`L*7F~Q*b^2|nJ;3URaO5{_q&TQ0Acn2&(KUt9QE3q!v>Gm z?l$Zk9WT~9JOl|HYV1c3Ya zk-wGur>3SFEhh)aa0Oxws_R{Kk*FrhLZXu z#_a3#JKU?Ar$;532tpa|faEr2QmY|Z!1O%hy)AAn)nG2#C+fir1ShYmWs@5KPLP?P zCH&`R7HAjr49Actu$iv}v>GzJ_9Lq$;t%dGfNF(=$I=NXsrrBU`2g~L13)PQ$`_z* zdC!(A2(%R!Z8ri0vP6J(&kPXsc?r4gq!9qgXa36!nb6@x4&{fPh$S*pmJDzo}J1TV=p7xT8+OxS*HeqO?Fe-am;j$Vz;aNq!pkgE3 z?0``M1RpC8{8QDcGXhlm6|(4j=_HB_mb1++!+bEroStuk8Ire7#fKfT%2$)F?Aj=ry^Y#uRzkZ(&|L%V9(Oz zVDDPpwO~)#9zRCNQ{5%O!{>d!?s5NX*_6Zv%0AK!a!5)45wV3sz0{;{P%<&rfhCYz zx|LbBkdjkLPAdOdoc$+s;q{#VhPlpDRpd-{2Pm z$A#DV=_8@T@$A80(|Z2Q5f8sN>P;iOVA;{Ld{!(;;jBCtl2WorT`!s?FKXB;)r|zlMZO>d&C=n@~4o&CURm6V8(mLnG*TN0k3et zGiMQS3<7qyeWWJd0pX!Qt)%eXzwZcF+Fq>)gYOr25bLBz9 zsa}?V)=i*d#?bZp#7J>@P&G^qIKYj*g%uF`_^_K$vPXto8S5B&qGh~F%VJI5R(BnvC4V&pU$je`=UX@ma|1}i zv}%C)QBj9DY%X0f&s=>kVWC%$49N#~CK)K~QVy4v;!)_Q z>Ter`a~VQ2hAHpa=2R#G0L3uT1rYW5%e{Kq09|rOlH0s+#cl&I7aE8q09K-K&O36E zM#pVYWHbPxUHl`-R$cdm>OIyAH5Q17+YbHu8E{#dnW%u}NX-qF42lm%%dann#6m|W zY@}*D$Pn`L22xgufr9A;2m%S+K`@bhIH~fx_tcQCj^GC+;XkREJx;%t*ohhK-2lF` z$Lq`EHrdy5d8__NjG1b;e0&H(mEtng-vD$qpKtht-TTH$zhvGbh-vf+2jkOvyM%3_ zH<`d6D0`|;8=W`!`6$U8D!GRwY)0?mN`N|2lPyCw^3$)z$?|AvcX_#x{A z5<%sR;?M<~ED6X5&iR5rsMutQpx-b{%!u&gqh%3FiB0ra#Jw) zBiixj?sP<8c~*jV#W4^sa25r}(0ov58zF`;J1v6cwq1~S#T(1fy5+8wXs4TlD-M>) z74Wj6EG}eJPO534J{ghjhFJ!zskOs;*d5kdYkxdNQ*6;PmL0K_qiMZA@}W1eq3>_{ zU}a^svcQ1p_x=r#eHSNUW8$f)s6w+$EmL`E8q33%?urd4nlwvHFqiX1pj0|f2 zFyev&jft3B5PW|yGm{W8M#p^RQuOARRo8Mt$9I7g;bPW7O`h7nl=u62)C>9Pn*TrL|Zlr*rrUWy5*qp+h;NCAp*QJ%zGAc;Z^P!K$T6!<$1TN zruirxsh_3EoF>Cmp&?brz7NHOY^BjHWTNBKlK3ZeRV0bW4AtC7p(DV{O%RR0dSO{- z=9hvS3K>xvj|Np;-qc!Qx0lp))ISHVmZlp2A~MBxqnc?gbQG4zo~V|kD$2YybxIYK zkRGThIV~1WNS;lUH|Nqni?Pe@@-_I{37<3M#pxXk-B+Q4z@y%xUe^<^meNrzWZwAM@7!_f$QHcuA6wwU!h z6p<*+g0Ei+JIJt!G4u)GZu3+^{8eLVRz#_8G#<2@sHZlgJJoPwQIR!VrPQ-o^xN5l zYP9Nu3!;C7(J1l6<4zO@(@b`YH;a!J&z?;cK!vcPD9i~;B{k8d70ENrJaZiJKNa1o z{sf#PdK2k)c8o$`7??G1NrN9^zC&ba^}akF<}D+K9pl>vqN3VDhj20H9aC~3pmH%Y zu*W41AhWL{jwftK+f$&k`LkgLQvMkNjOLF?{d|2dEPF-rI{g25^Lx};*yX$QkU{`o zTSUl2q-ZaB6^9i$U=^?MnT5C!bn=u)F2*K|K7y8;ng{rXrH~JZy4n{cLBqhPI5$xc z5}9&CVi9|Xqr0Lm9M^LhX&T=WKf_hN+hr_RQc-qFB(3P|?933%nDKlyg%y)b%Pm9!Q3kg7z}~b!(VgvXoK_dkdjcCYj1>f&=0fQ$xP>@vFIn z`%$e*ab)iiqty}Fk+$-~LnyP8IZHQ|QkB$;1b(biZ;(2_<{ln8d>AJ`wCZ;0>Q3#; z@l;Vig6Lu~-reo{dBJ3EOU8Xms8F*oF)5k$z$oG6X;Eh9h=O3Ucc~!P<+&hO0=Hky ziw1o`vI^$t7{jG?meN9@s^jG;5ATrZhRHPXt+#hlBF99WiumP}WUQwP#vcHOjq>P6TFOh6|TwnGRH_DV7hTH!#oN1g&l{AmPo{1Y$p) zQPtU{`AYBzsnjru_F}zj(vd+G7{XH4j>wu~%19&u{yh3l>El=n`SR1di0R;$LadaL znG(5i+a#|L7%c%~=|#&TaLK!Nj>6A0eAswR0BA?M$RhcJ{(kCh5QlkjXm+`@Nv;fa zf29Iaas?e+AM^;p0Vy^-0~8EHIHo{FXp=2XH?T9s?xRjYX_808_@3TAVkM!5lm2O! zi~uVv#G-4(2aJ#%@%fIgPawcKA$3FXM=|ce&h;cuxsH$o}(;qM31=&;VYmTEPJR=H2m)E zc0*+Y1x*$x0p}K4lV?Ce2uq|xToIXcE71gv5IUWG7cQN#dCb}rBNdFiO~95>5vi2P zG7oQEkB_89rBom{qErplf8>|(|GGNMfIOCET?c}@OK^9W;1Jwhf(CbYC%C)2TW}Aq z!QI_mgFD<|?S0m{_wtYCh7BNsj5yj<7HAckSea02cp#X1*M7{PQLs8B-F(h zDlA6KV_dyqfr0ubYB^@`%fFh z%glLhfR_QntlmKkV@g6)fw<;3Poyj`By;c+om_Drk#dq%v4S3y%nM2;i%|MY9^a%) zT^>k#RP@8FL|%Tbp_x~`q(&tcw-Xo!zY!biW8UMAkPW$J7%5}4bwv-XWDB=B;jhHT zTZQ0K^jSz_M^=Y@wdE{f;rcaQE3}e6F*Q+T=psW}HHBn(jua{;-x^iUQp5ys7O)n( zDW0jd)P!j@gL^WDeU7$TJ~#(`SN+L8x@FK;lw&qLwESXPWI}yDfp`DUYiUv8@Cih)`EMXyBH40j~pZ?Un#b&iQ46F6{Mvz~oUA~8ho=XSVXtTXO6 zd_@R?7JBtR5rshK(Vj@|?x9t0mJ3D#f(YPJ*?Iy9Z-|tgB9Lypq*G$Rv_WtPsWFv= z5^!c6SQ#bLLb>6CegioMdMbXyzFV*>h)J4@Iz#f znY~}i-Wyy9Y@N~P2)f{*k)U#2j%0*mh(!c`DHgg2%ReZA6-X)o)lO;JC90^~U8wvB z#S`(}FX)I!ci-V52e#Jl*E?uihXnV%@2;KCKTfpqRvJ%bakx;4Irf*mZ#-@r#m;i37I zb4*eAZrPb1<-=a|biYDZmyPZWtNhlii`U``jlYnHo8r->_#xs12pAT zbLM^WMErzaRDYFvd?G?laZ`t27LD-6qAQcfkoGo(26@+-Rj#ZSMkNp;VQb-HmVY=d zAg@O?3ib{1BD^rzB!lKNGiBXbib2=ERY7)&uv?(@IC%&%Jy559WvK$Ko$ZJXWW2@C zav16DLjY4O*g;ELU>u+jIfla%4ERkfF-*TH4t58tWIx}Cl4bxr{2U@^MUIDZ z2+b>_oJt^Tx(Lrjj*L$1<4dY2fly3F#&2mR4VZCzHp{1kLT26k1Y`KLzoktI+ws(k zc@E}miX!R?0|~suV(~w`N}XiJR?Kw$D4!U0eR1&w4kU2Cz`B#WwuPx)gyJ%C`pjvcBqV(9r2Yf$)`_j8A z#qRU?UoIK!$5d}gjeFH9Lz;thHn2r!(%J%pi}kvALxIk|tAQdOP__#8Qx0t_M{=CF zrQr^oROE<@yb{GO*RETxmTZkN)DnA*&q&pS>303tR;-Rz$PgVe-!(l>#nbVeSzD5P z(pPC6@cd0xTj0N}XDZ2Ziex*A^CPS@4mHO_dV)!_(d{S2GRP$?dMV!OLq`76NVJCq z1^4w6_?AP+xJ=yTbPOd`_;e>@S>%B+G@RrIyw?i26V?l+Zd~1S>n*?4-0;|tt;+v` zkvXvDb}+4XAWPKx@4w3e zPVXYhyxI0O*BJ4jsKncqAYERkw`sx4{TXb^b2%l8A(z)k9$tLGMQSltAYxuPPe-{T z_e1YX_4M3y`FSNFFmgNSwe5z$Ne zxS1I!o~G@X*6M?{w!Qf!|8rC)VNOi{9oW8ye0_6g!#-Gx z`K3okd+W5?gr!ww{4VvQBjs(#Aw;R4)i~D_o5!edf_Qa@&>{7MC$3fOE{9M2MZHs zC8Fx`sh5#2ceg@P=WZ{O*K%l9 zcX^S>_P}epIHk{ZEz-r-?K#Ya#Wg98g1~EUN8+f}NOBYwetex+grQdNU2PIb|Fi0R zJwugo9Oy%Z^}O5D=DK*l+?0OpRaj3kMD-oT-T4ll$~P>1XIQ0%sJ0h*e#_uE z?5#llRYYrv6RJ<-JVCRh$q|w06`T3`wnf*+KWY4~CvlJ?1VkwM+6a{9c)E8vMT>Y< zrQdedMma}7DH#Z-=WCi2&B`}ZeJpA5dGvt9m8;7wno6nSmQ%k{4ymbS!Tt>N+J`KR zfkd_Y82I294>N^s;fr)~GlACjr@000-DdWy`Hwm6Sq&GyYx+11bsJeC| z$`xQwn~!NC9Z^*UN%37}-99nY`2basE`R5MKUB3PFs@@4wzsPmULBSGEPJCOmt3&Z zFO8B(DXNe>D^uai5{7rx!v&8RCD)>6b$u#CpbB-Q`McY=vaav5)#)Q=-K3p$OvRC> z%7-gLHC;8Tr!9{@35i`%MAAa`)128lU}#7`$C@tC-$CaGgNmUba$+QIskeiEgE4jp zD^HunU@Ny*U|&TY-e~Dy9_>!w5ryZWS&HjxNiw^nQO^p$zR9Gyb>ep3V}QC~tTy#H zJjg^iflZ@GUY+Ge4chWHy!p;==y5%9m8?9zMp8@eO8aC%^qDpa@fm`#J;;u z%*|SD+vKPCA$_v6&(F&THnDO{Rhe%4v|@OP)=FJCOM$%8XMy}3usen0m!8Vj>(p!G z1hq&%Z-r!=o-E=5hDT4zL?4?@wofcVzw4+`FN>SrHB;Fj=w^{L_BaQCW-qdA<5WL1 z2KP{#D7vPM#YreRZjFheU!HE#19LRfdK8BL@va1CRO1f4ahl zA@X`PHTtPI#r7|{zbo=D+dWjR8uG@~2*2Y%MavFv!wRkBf>$hj57E!*{$$;$vCLN) z*PW03iC96(Z)3%z(0j_IHm|?{aM;O$AfR*OmHJWffii12IC%fv=D<0j(`3&o@sym6 zwbW$)D{Z0%oo!+R;wr29uBevvWees&Sl+BW1QM!dCf&Bg5JM>0hkCQ#7$vJ=dh0DHk&H`=sIt(u%hz1O zajqR;%rP-n&W$AR`|&EYU(>XGFa&^U^H}NQ6{(UCLL>6^c{M>BUo{~TT`b#kYiK;G z<#~85HyD4oeG9F)0-J!qUL^9Rh(RRq#i@%%1QMG;xtGC7#QcSP933ICUs7G%f`YPR z$b_5xom3@n=<_1GL16ix`)O+FX{+{Z;W)pme#w5LLLDxlw>hR&jwa;+7N<)smAtC( zvE}No$x+2*v64Ce={X~4jVpC0QcimMnfDU6OI&?a+z|(Yp?EFL1#>fG>cr4FAR!@( zVm#m5Ni7v4*3QBfs(Y1lQobVKu?{xF2aCQ!!@U-CV_u-x;cqgE*A}`KL-svKV#Prr z1#J(Ve23OVqCh|%gr=5wfgJZOA}$~{-hRMUMyL{JqN-xNnYIE83Dd++{hT$R))UdT zxK`d*yux*mpbR|7rqWme!shGhZB0zy93q-aYFJy9GBwVyviJFCi9E9@jBiTs$0^hK zT#Mv1!%BSo4YQz4&cj8IJl-HxW@ItM{O?9LZs0` z8WMAnoTxxggOucW=Vn-=OgVUGq8f5N5fxTUEv_S*w5e_MRFSYEk#g3=vX?Os2M%ZE z3yc2s{IHCm5`^;e;hq$2fvbPmE3jD*fQ5B4J=Hsvn*DDZHt3&CEThR}zyI|*p9tmQ zqNa)~q-6fLZ5W9XVt~@W15N9nuYv&rUg7!jm zyf2B_AmZF?H3hw0w5sK!#IGCN9doZ^y^^1^jX!A9i@G6-B@1a_eJmUQ>BDERAo$mt zy06(d?1%mchoTDhRUNMbDUMG%?E|MhSK-}Lfw~x~|MvF~%Xe$Ozf2AR=SpIrAU`Tk zExTqQ#eSZ?o^u#GN?{?TaQ7dVS{@0D4jJow<#1^}$e4(Tv$fhQ?En9&Pap^E?x(Vn zB98WPjVMb;EBdyMUs~d7{yU7o!WQvUDUT$>WY*|V&@8;0={T(>;eW;@p8&KsTjKFa zOPlgcoS6dx{>#m*lAPDWR*A415TFf-@46Y%cx4dH%busMG5LJ>@)?n5(oZ)aZr%N) z!XS#XC~L2>^<2YkFEN_$=@1#E1G|aqU3Q>e{Z&oJZ4a~aA#kG9rG*gN=J!_6hNri- z$5{h9ACU2(PDb7tIScX`Lii3avTRzIWTc`4H14G?aw?z$Q5 z^u$|$F#d3y5*br$<>tHXMLurVrdLV#YEW;sg5fvMwI=rry>JF|A4ILTny))4IE(16 z`GcW(b3A8}YLoh&~(>JlB-UUAM~?RjI|B^ccJ~Vio z=5gNK1PmcKrWWI++rw7y*Jaau35v}6T=UMCs}Y~4nQZ#DzdeV=Y39^!+L&6l--h2d z{SkFs)|`$S%Rrk}?MJvT+8maQl6f!tP|vOtXhOtT4GN)tV&SojvCcTo$WT?Y(&3N{sYR=e{nxd)a(nO4F17?Ob1YxT0@`8<490oEzmUllNF z4U$Q0e-aLjZ&@zuZpip|k7TP&Hb44?_CLzolpz3OxR&2(mVMCuCyYM|ukv(q=-LyHo0Vp)FEX#C@ zqNGRx%E3_G1scnAkP%#1w6gJf?(%Jw)*!gtZxb*ER<3d|=T$o~5FzsI*P`0vauk_f z0WyQYA}4dCCVcl$Ay6XwLf0lY4ruw%QJZVqyecph85po`z-nAyZx;^w#PHn=-``%Z zQ+O<7mY-~SS2je+2`X4~0 z4RgA_-&Xmg?lH9e72KIb$%yXu9`1a9wb_4}@Oit=Y4TI|x}77F;koQ9E3X{}nzAoE z54au1*f80IlyvNe$lf0Y_{(Jm@LaT%CICaFTflQ!tr_P!!Rj}a1!7D9hvgu^Z8wal`Za^;oSFM$-S7g8y+yjKFL6F3qA+ zkDacj4+UM44fy7EVPIA#=6b)q-FIF9Mx#%?gvhxY1HAFr02ARQ!(qI6&3WY`Y0Fe= zzo;Hv@EsnTdAAi9?FsKYmQHdnP|pjGjTNJ0ZTWdJG&5*%UL?yu=xVs*=b9T&*V*rI zV98xTtkA@!l8n?f5`M4D*R|OmucN|bAek{5xWBQzBu#|I?ZA^&KMIKunLpc9$-HSm zh>(^x@tlop3^9;Yb7s}F<{T@6@ohA-`uJCw=ydkm4Mpa+hx^WV-iDS%{czr=!+h(e zWpf&toRtzYc~I1zmU$qFY%IL-vL7cuxyf%A1QIvrowi|C@#?(!AnS_)p({joP$w=$ zjNSvg^cpeik8{Q~Df25R3^-F`J*m&P=r1H#W~{yzfT?)C-8 z5E?$Yff(C)NDhCyA%8f{sT}_qAXMBatM9ItSAZ zworUDQ7{5H40g%h&$2qrs&NUJB+9JhAT&tuEj=(aZ8y_WG0HHbHNS3z+-}$1>8^AJ z!eazVZjRlJ&?{J4LriR%z{gAJL5<;fH{LX&x{9;CxppF0e&ti00MSwht89m|Tt}p) zhY+#aI3iT;rFJIc5+0@1bJ_5y9?l^vzFY*VS_~;CKmc1*2}Ye5Jqxo8qE+wNZoC|O zuPHblxe5kf%+zH>5wLh9b`?Rf{4|pnxk548@>2HFj%As)@N69(2Syd= zr>FUwjjDB)K5ka6LS=)LGKfNJW+wb8dZqQE!(+{90ba5*<0S$eL`H54nlblSd|EGV zk&N8BcItJMkIC+=X~UcK$>*Zu#s}Cf=AM3p4O@@aEv+%K%d`ag*Pj0RyG}LboU6`V zn3i_?9hK>tO9W;W*gsA!L7uhTJxI-HhogPBo&Dk2b&C#NH6VrG?|t4eSrg|Mq^Rg5 z>eDt@=ZSa7(=7!-!WVoZ^4)C~B(l7p%)s18S|X*gn<%4g3;n{%9IM}rzlcW0!q6i7 zD<;EQ20qFv<3=)?Sz#eZD1>}B(Ost!uaiVqItrfhIB6)kX#o=~R9m2dHBbKq1DgD{ z0eVmZ3z{!v(UTFt30e@gRf}SR2538-zr`H zpjYyU3H|5VU%M6CJNb>UQB~_Sf!qnc=kij~Paqal1)$-a>R49=)0tp5f3b~IzOh}S zGkc|M(b{dm17^ssT=@zq4l4z_-KiyKfxJS%Kk+)^QjvMpba*c0c~Pam{@sAt>g!8D!w3fPDYM)1U~3aG#|!VzWxTOaUJ6f}E!T#2FV+m!LVH-CkSK&Ts?z4Jh0$AFH>bwTM?3e6^$!%Kq z(XpTqs<(_dpFdDdP=r6p{D!2c8!*B5mLf&X**G+NnK(FX?A;WxWIDZHSG}KCHX4x$ zHy6^_7`{rFUWN5i8bmOyegns@3$j-USPV76ujaj&Uj-4W1P#J8fZ|m#ksWO=)G`;V zV7?mFN;0jdk{LbKZ2*&zjj>lCt@$}mqiBd9!pjz}RtZ}n{hG3@+{eX15zYwR5LkV# zET&i{p-2^OkN{df&4oImB*xVDJhrgyG<;`pLqK+%U9^@kay8YWp6wDuB?5C;5A-j7 zepZFUhFGGEN!3xjX)1~ewoK&r^a*Yx^C}#+#OS$j1}G5X$)9w_39 zFX!fCz8vp!%4=}8%j&`3ox8^|RrtCe_GdD6;~Z;>;j~z#&-iXVZUgw!F|`N6?DH^Z zgT-a)UK)jknV`)#y1&$ZG?nEQYy7hBNOh5xV1@DOTKP7V%bIQ7xMWO=j<@#Ir7v56 zo)Vb?oNc@2y5G^rv02Vitm%!dQ3OX48A{S$tEp2*F#uunt40scOyg_n8{kXy|LPs_ z)GN6Bs}}KzdIPO1TqqC{wMUs!MrGex3d0zTWQY;L0mLgSQ?$mqTAp!BBg&SRMSqf# z3s=y10>gfO1YX};HYg+y2uNQwhn<&Z!TUkwCnM^nna{eL6hfDkg7C{fi?iD#@OW9eK`$9vR%+duk2DSxV;RmLUc!TBgDBJP20w+LO{K?%#S%iX7~>- z>-lMO2^w~frA#Sk&@ZMQ$Z_yL&2yGNs3uUhjPXtrlw_yKdQxB|5$GhB|HADPq3j9U zCt)xoKOH|Bva|@H0u@)S+8jowj6Z)9c@^gLQ4pxAN}3xg?wx{|<&}bAIX~9N7>f4e^fC25 zCfNLCI^{{*eMr6&L|Xmr?8qrq-X`2*>stU_z#OJ@qP9!bghvcyoy_1nj+VkjNmaEz zHnv`PoMgHT9C6>xOmt#lJ7I-q^cCp6OO%3!@_`?FUKQ|UTpumln!rUVTlMJ;gYn%kbqmDX&YRoiCR}uD0ts>n0w8N5~^Lqv;C$dfO*T+b}Q{SEO559R|mv zPV5n=m^+Fb->P8FX+gnfl2u#xseGpybuvZA3eheyZ`T_9%Ron(J;#Atd_DXKJoH`z zvMgy!24YZm0a~lnT_Yi4VIN}(Y1VdNg)SD&EYAsKJWNx98eUCdG?jvtd9NRe(LrE? zFD=ES`BZHJ<>8<}sG@j%d1<6yO>M+yGFr~H{vv;LI$yfy5*UubMA>Ol?6}jLu^t&V5`3(qM^-({zv!JBk#=h_tIJO5mASp%Ju<9Kn#p`rqw~JfNhR zhe-Dw-AMSD95s)e;J|fjvriqc`8Z4mSaU4Nk7FzyxfV-uE&cTL!xb%-H|w18-jU+c ziKZyOGH^xPEO!580=qF>OCg0Qr=^vOJ+<-Dnfv}O&FdAUcmP#%Q3_Lwh0w=>%LA7I z^XtC1g-4&do!(deXl@?Av{oVD(f1xr7@1&vMEut#ZoafS^*EK0lil0n!GRE5TU&Jz z!b+)pq?d}<5PtTpVlA_sZ6VD5R`tUcl1@_2w@D=P(#LA%-yHad9y74-!W=(QgV7id zshKH29=_dTI51QGrU8XvN@5B)uk_VMEyZzBO>S>K$HY)8REdM6PYW1+L?Beb$b^Jspu5|j?;{l zm-~H|QIJ{FnxVfoBF|ObM9>)5%#DX->(UXXj{AxBy++x)cX35k>+QG)zN_#N1%BHB zTD;73Zb>GE?t*9H$f@z#q`nwW3QnpcT$QK}h8BmnnO3Y_kpC22|1{&^;zCe-HTL`@ z3ewJ|V8Gh&$b@Ao`pxJyRQ-Ed`J!}%VGUYYpE4yh0T`vPJkfZard?Vl4H#+DEb0=G zW1_u(^t8-8r(EGD&S*1a^6JbtQo~Hm-9q7^P^>rltOA&c3_>!!G9nZQy1@s+EG+4~ za$F{`G&Um}WYZ8}5yLRyP{g<+(2fJR-xUikJoFb)X3r%#D(L0Y3deNNPs*i^nuy98 z1aVVVekkLdaXs+d4oFgDqHtdg*eAX-G~v&9LmG4xBZo!b$@u@N_)_YW*_mSeS}mw` z-oeTFyCtlS1Q zJH|NcZb#~x*1yNOqgUVR=2TZ7)jB=*$IGz5Tz=R^(Tbh5j{GUcZ5|&U;q@9ww2tQ0 zZ8{m})jLZ}dflw?`K^6YJOZW($({7WdDAMnVB3U-YJqG+}A*2_Fp1WnWR z=Jn?ZypzgWt;x>!#ms9TAA|&)iiTR5)R6KQXO$Vp{@z&4ujR({VLU~8DRig5NNXl5 z2Cv0WvUvLUD`7!eSI9Q!x2cS_9tZL2<{_y{$9~R9TOO(&(ySaS(j){#(>h6Bx*1;O z9f-v6L=ln(f6Gb>rr8sXo31#suMH~P1#|mewnu-@)kN4BjpO@?-`jx?-A`QczKy6n zvTwkTn?sot(J#ZQ?l06FGO85o;gLcHt5epj|JcPYb|q3uNG1Y?gp*3#a&yD?dcWvX z1ZvJG6NoAk=}+_V#6{Cjx)Ii>rJUpXtQNiFxP5NAlD2Zu$ zscX4WXJUlHEC(e4wm~syQSjR{ET&LVU*v6eIP*|LVi`r3^0f9Hxz)O1$n~}V)p0Q9 z;D>kM%Fda~2F|sE6U%&x!QJbs1Lv5s5^4Fm*SkN{z)Ku{wyocr32yUyjfvLZDo6sn zstruu0=evU0&gDM-Vx*+#nqu;K+g!f<}PwR<@?4iPj2QAWgwaNQ)A;E#aOZo2VI(__s7L{ zcL$z3>In^_JT?gZWNxImZ9r}H@~zmm#A=ZHK?xKN6gkMg4+WW^YZwH@qHq5D63zcw z-nEZY-Y}L0ImS3PJ9;Ry@MGsDoIVmb!qBqi?U?4(K0UQKJ4hSla-!oebFY3L^bEAIM|J8UYp_GxZu2x?YQ|6o4XZfC7Hy>nH5eYmW zVs{FMj-uwezWJYC-{ZJs#E(CYI4a3CEDByjhc{VpKFkp9M9tjK$OT8R&8J+n-Sd%< zFn8R)L7Li=H;a1}Wq<8FbNpTG%E6`W`+v#28@gbY-Cyh2XItJ~dna&q7dV#UuL0%O z_&W}iC0+~IcN}kuv`wGZY}AMi{)0)Gt?jKta$VS!{|e2NP^<#F!o0Zf-|I1NFS~q! zr5O4;uN^nCG%PruiJt5~80mwtgM&alFpEd`=tba@$siZ~t22Z9+K>YB{DUaFMXBwoVQvdfFRbN4mdP%5q_>OujO0AQ% z9A@lHbT-#^^*wp^;@`a!$0`uZPu&igY}&7_iKDvGZ93xz9!y7cg7H0GQZcg}E)(56 zlY;@-elG?i=-)?*1p>D2b>Uy(!avzmx&--I$Cb(+-+MY0k^c>_mG;^V1q#v8S44j2 zO{U`0-xs;>O*8AE&!40DI_ASh9=gg?4s_i2fWJ#hB)-2}VuEZW+^Z})HLkja5{&cj)Ne#tuDowR z3}o7M$5LcBTqku#q_`bqcrDO<#pk-I%fDZ{?HQ?x6wek*^_&j%viWm11K9oWiA{Oy z-ndwX<9zm;=X!<9>q+iF7A~`)sr-|X<^%fsi&Ryu#vRw`Vt7?YsJg?w7or~X-J$`- z@Hv#@`ljniMH3Jcy@^ngM(Z(Mj(YnyR*|@E_Wqs;L_ffghyOyko7riDlQn8uQ~H=?@yJEXNjc zIIaDR%vYy)+qL1l|BDus1pYh$GVIy_;hmcnU>2C|xAU6*r(ZiC#{glGamBKZsgpP; ztOY1T#%(yw*G-nJ<@eBsD)+MKzoqF&SBa_Pn%jWDcfac3bCXZ-3NQ%M?%gud4_d!Z_`o?nGWNeuTQtn2mJ3#doS20)#hUuGSn@Z2$N}=5+89I?zEr` zop(=#3#*P-1b5!2MsFyLY6yyIxnB^4QO62>mB~Q-2TEj_d1*cOn?8hQ`_#G zOzmJ!-98q)@$HZM}r1>RzSrluKR(!BVPJ;ggicm1V`ojSy9$vKoe4K2KB? zXStgfXF9_a0%f-r!d=wY_TlB5c>!=VuWphF=wiw7$`o7`d| z12!0zAgz)xPdpF~fJd-_$n&=g;6j!F6#Mb+eq36N50w6BTsANJkkkRKBm*dCxB6k2 z0Gzl0ZrzziggVR1_HM}pD2Db?=jWr(!$SmpCjb)!1bewaQkRy!wd1lXSs%Io&@G3ZlL`(3h@x8E%rrdU)qV~Jw^ z@Vo>x#w!2~G?nZFchd*}Ft7X84KmVN{`bd;s}?Xt`eTRuNcIm#(YRvG-4BUlQ8&i^ z{Jio023!yziR;0*_TqV-KxM?aC{%GTV3z3F0=b3mu(Z`(Ff`@5x1&j151anbp{!Z-Chhzl!BYk?DwX z|LL$El#vtS@FFHSz?sW=Q4dnE$ge#8+cAni|Cg)swyR;ZcYseon#gOpZUu78VuzK_ zngV3985l08E=Y3p6lzcq@0{ObHDp-ODlsR5=30F@p@DjWS?{8VU%M`+u>I;DxX*tJ zA#$5GrG&{Lt+n6O*8!i$6uT1cqz0DBb!A(9e5WV6-hN8i4r#Ki1b?pa|&!T-$pkX zhr)81h44LB)4JWVKJfD*lsr;9v3FsjDi>g7GAD|3LJ}y(NHT5!qfA)>Z0JuYdDrHYycSEr#tL$nO5yx5`g9g zjNd3@FWd_xmFQ1iJ#G5GM+XbQjwbn|g$(7@Wk1#A?d5>Km<7#nVKbB>D+d9a3+j|l z-f0y*03;tv6Yh@OdBv&;*f_e+e!N{_YOHRjzwRbwoT5;whqM+>02VC;VvW@W)AvVK z{~oH??-Z;?x$hL7atEU?_tGjILJE`ITk(AFJd9p1(dQfgIxxRw+oe~;?!z1rVe zU`EF+OBwNKQRzHoa(LQrc)>a6zZ<0H;3XH%mI`$O+y2I(2esJZ4PEF;FYfXDRYG_V z6%yB6#YuH9f&<3x-HOduGtp5+DLSLI{y^*8(ekYWq)vbZDNg^+-JQ#62G%bD_0hIQ zb|en8W?<8Wr91>^SZ?rd6-o%#OwX$!kJFmqx#C&lh58v;3nm$-DQB$d?Sx3IlM$Zq zUZfX{S?Cc_3<-={Eh_1lj0jhZa(&CE?-wZk&W4GW7Z5nw z#_)N&GPb=QpJ@pSy!-3$rKuRbcF|BD7}D6j-NkLQTN`k>xYDAuumx%(g=Bd4MS;#= zrwK&5uZ$HaMqs;pJgAN7y#wT%m>?3G-o zJAwo8Fgi(MyRQsxk3atLx!sXKGnqKbuPHx=bJnr{5mlJ#P}8yty#0zwlW=h2Uc$zn$>5%B8B?4vN`GDwd!fyuW`T-}2_KeW zJsSBXtE8bCtJmoM=9cc$F3)u}8|ytcY=n}wCsr;f8WBZjgNN)YW4T$1kx7P~=*i~@ zcgx`n^Vv$CDQ{~zj0kT#G)ldDEQ!0 z3zR{UTq0U|Y6Jcgxg;l$!vX=>6tKqz3E?yzm-F|u&jD=!G)jpV8{T|SsEf(E`?wZ@ zZHw!NM6*5O_sAu?l0|GPh7(fqABEp(Yq4w%+#U)eQ;?0V=)vCLOuh)$3ZBB+#%b22 zIp87L75EPkZ>n}_jndZy$Kl|HNs;Nt(Z@RGqM~Q8B3OODobglSY?(_AY6NYBtTJsC zQMgR_3jUi3iX^}A*Jlvw5vFrbXzrjPW`GD!hv(!EeK&ynO*&*=Rw4S%8K~P!*6bMs zyL{raj-cm_S!e+jgh2TafMr665ud8C7Yu`xKDFTsQ zSs?-!Or31?N0PMz(9+BFE$-?fPJW4{kv=PqsjBZq3SwfVci&r7T&IZ>=zoa!!8*7E zN4EpX4x&_pmRz{*hq)QV#-3>c%}fj2iDuhH0h9$3YwtVLItcTzL>ch=UP&?b(EXd$ z$H0VXD>v4&u%MBByE6u>*y%>miDXQvCMF6@u#d&K1~Ul5{K+_kLr%s#VzgO8%h^27 z6b#4x8DzW>rzbo6@C1aIi4E7Un|fopM2X$-dzAuNejVECo1UC<+-?JEg1ZRWEzSD= z?Y4)(#O2K5;O5g+89xVA-l1tSCCx;fQ0z!*@CgcaV4EkHtv@2Q4BvtDuw&<(%o^4 z3ei7qt_~C&&coZ}LiStB;Ht+}sz)S?C-U=L)z&lGkMI#D@B<=T^#=`c&45z{s6_*P zNDg^RAsL2az9q}F`aAK$yiBkwB&8O*kCYVMn{Pkg&gbrZDE2(;{|qgu%m(L%7J zDEM!qsK-ZakJtPmo(h~hxznx+o3nu8v#C@(+X_H8}ujOM?yqaxKdEp@BaW-_hI`0 diff --git a/docs/assets/transforms_overview.jpg b/docs/assets/transforms_overview.jpg new file mode 100644 index 0000000000000000000000000000000000000000..5c2ee92252c11fb45dbc159a65c3de3ce3b007c6 GIT binary patch literal 180942 zcmeFZ2RNKv+b%qM@4b#FAMQ6kRXT>y$jLX=prJb_cDX% z%pgn{b)?)!JZ<@U!j|Kpn=5AQ!x~j2{@=HB^8A?XZ%)-jXE^u8?=*CTH8Cf~`+jrFO zX=rL`>)d~2Y+`C=ZeeNf;P}kR*~Qh%+sD@r>>m&o9uXN89TS`K=5183_xV30`zN{RaB|@j5)u%S{FVz3-|x5Jbc96LB#7zN3`y)f8F(dMkuu&* z{!rUZ#wTTjWP18?jGUQY8ZLnPE!rQF{cD1S{=bs!uY&zet_6TP0RN9bfR9f=L_k15 zL`;MW#H7T(11UM_AA$To0_7ip`gfrDYq-K?f``k4kdTlB_e)DbMnU`E4p&RKW@&yk z51=H#!!;%XI)Dn`5|bY*1o$)l+jKy1_5DvB|C`$v!PVHGI{vroc>GTt|J!vu@u!ae z?K+x^0K`tXXDSk8r^duwJc8mhAU;P zsXtB0|9dQHQ<7K=L(P^A%d||Jezfup|C0-axag^$vO+dObCb8osmVB3ld8CfqUyC4 z-Y}D*Ueys4LTmNPU@4p9T zRxB-9&CZVm`eGk5Z;fjYq78|4)^Y$fZ=ORzDsv2mt-1=(n1BGCYh6-Wp7_DyBKN~k zyl?Ea&v#<0oC2Ln=haGGjt70*UdHho^>weM$g!E4K8`e^RwE%a$$a`-mE^)*op{0H zD%4OHEZBYo!v$au^=(AQH8Iik=uyttvFg2#PmJB=pXa=%_1d=0Y;Ed+ z5+_I@SVH%dx!Sn}rW8Si){phw@qjKE64` zNOZK-rYi95J24T&?*sbjx8AO0re?H0GVNE*i3-Wm0(xLz_g?$B{gjjJ$3ow93Xxl# zALQoMA1K0Z{c_!5WqT{t+@e3t-`bcWka;_~z$@ZOSDDf+n)}|5x)tw&9W40lUVl+D zy0gg_i}`>&>=j4r{2YR?W0{-NyED^cA#&vn9VLxD6k1{0zAw8Hd}a{Z%qJ9i=)GPQ^r;%&Gj67=rfs2A}=2E|TB zJa(w%XVAL!GB=nkU$P!=@^hZVzT0EvN^!E00$y5VaI$L??Y}l>EJ>Q>so<7n) zgSI*G)?T@FXm;L5?m}v};}Qh4YlRREMO-g_iUv`x(9~b7kh*$V&O1Ll8ui^bT`^4I zFn{vqD@epLsOYJtdluWkEq!|^(zYju7ls~MlW(VV%%~R@QWQT;kkp=EmKnQSZf-Tq z{!W0VQP6zMfyh)AkZ15%Bxug5RNc?T>E(`l&Z&%dq*1=Ag&z|Sy`0c)s1}#!h*g?% z)tXC*PogxNNFRWtMdsH9e3Tq*bsx1qc?IBXCksL->|TIq#3RMB?ln&p)HOBMHtAHY zfj_)8*JaunkuKJZd*S%}_4|OCeTsaSvrcIwb<5fz%_6u2zWlB=Z*tG>;~Uc$8L|{S zJ1PX-9bnxI(KD#O5aiN;)U`7OUa;BfJBS z?xn1+S~`dWa$PZ)nRY4Umz4pAonQsDTbY|OQ3rA)p(a9v5BYOycA{9vBVoUMPK#j3 z&PQyE%`y4umyi!L!@SLIKth}CI}S+fgbgLGqa!F_WX{t8oZq*Pca5x;x?OjD+_}Ee zJrETSo@mr+^^MlP-we5T|9$tD;Owj{PoeNHp_&4B4>)27JXv?&d!77fAMJ-RN#md_ zaPdr!PSMiNS(Bw^Nkw?wQKnwz<3>+KH3x5Q`^yH4mtA%b^?5s$kThL2YwEjU#VFC@MVe)bPt4&Lih-w*FoGA+ld@%rjXB?fS zJze<(*|11kFK76`U9+V8D?8P_$3yh@`Av@AyfD&)cN|l^y_6WkXnokl0&7t=$$?x0 z$z=-~{-BrCv+GUSgvp;N?D0}xu?<>I`LD(lSnwN5W|xuyY6o5@J-m&82@dvlQ0qql zN!?FYNc8j3k9tp2x)H-S6ghmnIr>!WJ|zmbb%+lo>h4Df#xE9n@qX?~lV9u*IP1Ms z>G4~kIq=qFFhnhvm298;6jf&+fTYVhfClUPE{6N!7P8J~rbFVRo41LDK2Wz9xOmaL zy;Mwbwp-ZLF6;PPV=Q#b@_v2yDF5@Ivr!klwjdy2mEoi&3hEX_1~IHO2M6qS8@Qru zoLgh9c8+j&eUG%j{mjC`h8`x*ufI`#()Kn2?-psdV;9;4S$;Mk3GPKGx4`FE2Bnedy%{jFX#RO}?5T!1dY-e#o5(j10m}$=GV=j%J4={Pg3ry8v=(AenI{ zNt*i5uXN~L14rq))(vTojcFaAzbVrc+NrmbW+GSuou(g~L*6zG0hNN^+Bn}?*!r|1 zp;5dSZNch8iU3!xHT3c)x7WVDcpu77m`?p@-!X?cqiR}1GLPsrT{FS=5%H4Ps>KRX-@TZ-kNzf;q=Pm$#dKyFS^XV2pk1#H~6T3b*Sq zKKHzPzoh(%6lf+aAfCnJ6df;j2EsIBP5CYny!BO|pNcdASuf+)Pj>fh-(b1E zcXDqn3w~FWL$!6KWBHi5saxtN_N>&}r%Ia48?t8i$Bg6!-2B{L#8K9K+Spq4vP1x* zm+{cHYb#_B4J5Xs0$nnoLhZdPtXcc9bt-vH!fMglY5-MUg2NNu-2{ie61F8#yUIj#pUg*|hqTs0IK%E0^UIko{SG-cNMBEhbK^LKut z`$5uQ(%$WW!^*R(d+TL@*?;8DwC;$Q?a!QzS;IFk8L%d~`r1qC%y2!AjI-Sig2cQQY?&dK$M}A(nRz zhz-m#>uf?u@jDIQTx~v17sS~m#rs|!DWo>W7OeZ^=J+~770k?0=7 zSIl;w$mayY$()J=$`&cmBDAmBr$qNQJ$k%exhcqTW=xT7#{)l`WgnZS;e`aH1ZffywALu zPsUEn+Zq&VCAkv$K<{2`hLo%%4_ZPNp@j^dBq~J+WDPTVX zq}f6{hg&sT;`-!Zc#X8XzPb5f_VxPCkKp!&i)aJh4 zwn`}Z&+L~g7cw&X$UPlKRMFzXwS-J*jW>{f?bjZUdvW%gV!Z+LP4KG??MgDVTzKA z^gg5+$=^;(w*j_IMno34mo3FGRnoJqCv1L_tsoj$%Hk8MJO0+$f^7MzlF-^Q6Sq29 ze~~rfbgvEB|Fb4iOoq+9e%QR~!3(vrdu-lQkq)V1Pu~oGe&)Me_k^=&LwN(8jN;wx zI?LhyUavjhN4k#$0njC@3lYG-=5^)K5H;r=3p=*FNGS$%`uY_}im{Mv3^ zwH!hm^X8D@3NR~nb_KYnMDxTdryrSx)v*nO?opILx21iym^QBfWU%#Av>djp)erkd z%jVT%5_3ZhM!c)(|3AP31n*HvnAkg;m*7R*%5HJZ`bsai6!Kg0g_s+bZc3R+y?iI& zpkreWJnc=Fpwwsj?fKe!jh6Q!&#@L6#v(23g$**HqM}ru*oJa*q3IC7xx@WCjRo)(I#)iEz_^zE`SbaGBcW+sf4-)Bck{0$ zj5Vs?x^3F;WF)%hLMG6H1Py?qVQg0b$16anE#M093`B~Kb(R6qsg9QJvWuw9vuKhX zyoz0UX#4hyv3`RulZz~msllKugarjU{e(2@sYy)Z7H&p?$GnwTcepuFG%@vM-ur6T z83sADT3=jbq}=t*0DAP80g`R~!Re>;Xr(n^SSJTs0g<3(ISEI)c;@diJnoTkBV7vf zHyq(4 zb5;#zG7bFD8%y}0PXL;M&V#E}^bb$w9MX#Y`f`xa^<~zfx9>#F}8u#FP1u|jyLac{s6K3s7h^1>G zCLJBo5~g+t*1(R!xG?q?ioyLbx_13l9YV{~D#V2n@ACd@ol|?6tS`rePrg_=h*UJw zvc2japqYZzL6fckZWJnsSej4Mf~e6rED&7RrCj5O(4$6-&yVltrD+6OtV`yF%O|-- zsqs7|ceqhg523ig#}Fg6dO-9T*4M5!JjlaXv4W1=i~HbA1V!{~{+CumAW9B4iPzdn z-Ct6QYq~+R`dv872jY{D-h7CH#Wwsvj_Y%0*p;nliKezbzKgs?$1gm_x#nU(O)X!T zcS0gihJ@}7dtO)ukHc6L9TlOh;wMlFFh`&4zMrdg++vRht^sOAYck$sefr|1Z;IK? zfFwrfy!~kd8dZkwMF{p*fd)Knx8}q7G`?fx@`nQp2l3u0Tc6a@6I816=rVTN<5N#5 z2G2qWFWdu#k=I%L=>Mca@1C)Ff8|_lGfo(1ZO4+b-{&^05W!R zVXUlm&DmkSO6(JNC+v<_Wyj~|3daU!c)A??Nwb?IKZm@Q=iJ;SZys!s3<`}Es^AgI zj|KeCBkcCq0H>%ZEZ!%V&b8?g8fG(YXx8U}mEJ=- zXb%m_T72)P?jhm4wltJ>#f{}u&aCyap21qCf7_`s4eW4(pOq~2R{`6TX8B_BCRGu&KP6nL+m0S*S~fLw|KDr{p4+<_|X6fyU!D_o(5O z=Fb;xZrN_#r}H%XOlwLi{eH|jGE<65UR5pz{WZ%3GWA%dhUN?Rs@(Z_kC@x9H6#Zh zuV3*w7@JVMgOuzjdejZn2`;@L{X9rAd#qnGq8}41+Em|+F7iW+vh4%_`+}JAuK?j3 zx=oWFqSy(xiPb^SDPQp4Ude+P0omosfy6{wVEb8sw4;O?PGN-t-C_iIIcvSB3_N`bLQ0nJbz z^_inlSax)vc|(wbX={Bbm4nOK8+|Et&`mA=Py|;U|A%y*3NbJB*Fw2PSV@#e+^RmM ztFkzXF^M^=sP9>JGQ~#&Rk#-a`t;seqwj>(!r~~W(Naqyqc8b*Yr$<}!i{K+XFOgZ z`l@b66>GLJ^)z%~FGL{32IW4Tj`$4J$7#q-)7o_NVPo^ek5Bcfj!m_(&TF0Y-;QJE z#;qgBxyn<2((Ee~qp!8wBC~AJF_nwpK()GQ5TY5T_v}z3ltJtb*nY*+-P425&xgF) zT!N^8|Jq@EgSUt5sPe6oq^OO@m2u)cExen!|#z1 z+yy9=yVDKkJ~HSk;`gPQ*)y};g9g)8d)2&d5bvVEFFU!91ooL$tyaZDI9A)3h z5q@Ka66~XJqv6mHj~;0Fpi^b5oQLcu`X0F?9Yek_-%mh#Jrtbmr`gtY`)$f^;N@ZY zn9baXm&|*qL4p3p2@%(>_P_zNmtm=kcmn~aHBp^p+cQ{ZlwfzoXPJE`BM=u@>|obi zPybOHEHc%d_}3D1@zA0lt!S0*eXei0cpFO1R9)eyP^zes^x48^NNHa(hkdSGPmDSqYg|f^b6ld}{(BSl8V7`dZ`V?uhtKgRXs=^aejOzZNN( z#oO|LB{{@#aU)?#a=1H~p%Lwl8yq@Crxc}-2WLHWJG7%-2vN;%6bbIrc>G4LG~RWB zsU8FimNBNv4vtAew|>7gzI>R1GOf$?!C(s?=cF83H5?5v2 zUt+UV^{HoHcy5rPu6BOo6VFo?R$Cej%k?%FByI`r5y~uP1H=t=Q?C|6Q5To_Gcq4P z?g;G-Pq?^~TzA8nau7hEkHVbB7Bk<-+gCG&-JxcwmhNYXEdLO5PzrSACaU*Mz{21Tzo;X4EspMB0is^<5 zL`|ZlZDfryBjoxd#IE$Q%N?=YN@sn4f94XeqCpTvkJ;C>K>rW31aHardhKbAL%nS5 zPz3!pv|&c*SK=`cXqod_fM$lBcyC|BbandvbXD;Ha>-&qaG=IhW*fYItkM01&WcyP zrG?_{#ZL%dfnfYPYNrBcv+0%;zZ+>=zfgQx{{`pW1qS8>$yeueYN1DK+`fag;E-I} zpBzc#XfKn_SBiFiPF@1Z4OAr~yc(kGq8tlWN;`v`DHSCqce@|YjKH`cKFEuQNKAlS zFAb~B*VARrNf}WF^JY|W2_wBeQy*%O8wao?R)OD$joy6bXx`p1WX6-Injc(bX!~xN zH{AeL9flG|G^EG*RJdzBM3IC~+|PP2Ee5X(T`-)G7R()LOtk%U=bKm&e>>=`NsLBd zg>e(*)Z3xn&kaB}MK^Hh6I<ThO2QNum463--tm2eLX+ggxrACS%iV_R;q8*pb= z?#?ScHgOQqU~Y-xC{yJN)!KHWO6}!meUy-%-yq%&6BByB5b^{?QC#GMOt)!ON9Ysp zn62PCS9s)cUu#FhM%7ZJLmEY%(ZVC$8`baU)!L}IN#{dmsxcZUl8`-!)CVgJBRcv# zJzTt@&AHvAbQIBX|A0c?=G(@8+L{5ws7$yY3wfw-!rJh2t(%;gk8zSFFWXqToW5CE z{(P;eQ8P`;BRX163iyQBEfMXvb}5dqjYObqqU@ngC68abXBjjGYBfiUIV6I|u=b3x zt7Sagc_C^{$7f+D15;4PT>9-ZtVmM-G{d|b)L~M3>Hf~DXr9Z1Ti5ffJ+2=Cj@rjB zvW@YrQXsYu>X5eK`<)zM5CRnEqfd!Z=s<=Cgi9@=;|xEAu37nn=rCr6Es4ZzScRNU z=bI#Du-Sj1RES7|DL#U8aSX_w2UXWs4;8yIXTDcp{lLO38Iv!_Wh@z=h-eMK?4i|4 zz*&gF1c)36e=dSa> z*oI#+CAhZTfQT}#ug^J9ppci=7QZ(}%JoE?bGr6gqTHgBg^o(e+ldxYbKwLuj_kpI z(RT$nrRcZ3EP zGVh#_uioj270RQzn)xfbL_mS1PohkuuE8lGlcBNt1kbp_}* zo%ti3*8iVU(=AwA*>p9@dhsJWecPY2J*1{4{j50oa}@1hulJ7T*Cp%cn}`_@x0I>oO5Z&Ks1{kSa)sDC2QRKs(SGIrQ!dd9+Oio z?tlEONE<+>s{y#{zW+^%KD*8HC{gxuF-Rfc(O1t5!Xh;vB6a)M)RIzLFK(O|5YWr7 z5o&($qaP$-6D&K=3}Q4Ou%OGZcuOC3Q+u7$KB;Shnbk0?(6zGSBQ4-s5J^)5E^CSW zgltC#q6r1_M9qNJ(-GxZA-p7ZWw}!K5g5Z0&hpFc4Y zP1163h6IEJq3$IQ-rP%7uU6}3VP=!e?RBy4Oa@{H#~c$Lu`x}{H}gp=QM+Vdf$Z$r;(v5mA4LE zL9)6qJ}Dnh*la8)m1XFNX6bU7WOzXSWGyx&7T{W*AFj$|`~YnzPeZt-H5ZtzFyzk_oH*`k7N#o)2=kZkTp0;u!d?x3oq6d!<-vf|&q216GNC+TEk;lLS{_v$exX6Z6!3u_ z?%fk?s89tDTlz*_0Z0#0OTn>v`l`sB0_L(3)oJGB<*av(Qkot$sfu%+*B1Nlfvy2N z{3yFFEi@QYIP4yS`fPs*E(=}(K3X4QqXYIT{?k~jKFhpW3%Py;NHJSoxxn9EIoIO~ zAo9oURs#JJ2&Te4DVBW&C>)!~GsBzy%{+tt-F{VqTx2dLwpH%Z-wKC+H&lnV;MN1K z0G}%gpfjm3Y@Fp5+2C~?!ENpLHm2^oP zA<|rpBrJV(om;J@5~G0NV(4$B&P60q+4PsW+-Yd{GfltMxK$kLNW&SuH1#%=3h;bP zgAssRYxw(!H;Q(`s!c#=_OAfgR9$N#FDwoMf9<{U^8$(+ri^CPRDn0qFziE9@e4-W zt|;C4wsQDCk7Pb$=!XGq5uRZKp2MC##JL5oeu!^Qp*o^f4{Brh~VVQV!i^ftNhdbd1$Oseb`*V#uWgqD~409`ScY4Ndy~6`p4VOy!<40o>S*vP%Qm0 z?3`H!hQR}&3jY44rc|h4L0c(P88=}6*R>Nm9jE!Ta(`3fpPKu#&HdRS{%&0PvqSvZ zA^tDw5N@NK)!801nQ37a^Hy33MAJ~O2&YgKz!P{6Q zdnQ@N*odR-H%R@#+yBko{}@d-YM@gt-wJJhTDv-X}lH zSCDDeSAg%eRXC580-E4~R>$fx!cOr(mp3iXsar}+O6AiykA;zGc?S*Vr3w%CsrkKJxW`8Y%Rq+VISK zv3{nUp&vgrYCUk`s|vaSSNX-{4LUz+!l5m0mh6qG#cuP~KccEE2ZKs>ZViFFK$20h z&W=VYnmdbyBOQn5=>~w>0M5 zUbhv};SqmMPaEOO_?h=%Rp$50Rz;msu!=1@5Q&p)W#IA=yfZnlpr|t)o=dt-?|R;F zd~ZNrAjGO&?3zSGg5P66zlv|+AukpO1rd5*X32DUAP`R5h<6Rw@r_@Z$@I^h{w3#ExG;9Wlh~{G%h|)F(-YYAxy6; zb#GmpK;@9ZMPb4B^oOVXsoyy-5}5iJML>d zs^zGw!c&p8_G1za0c<&;O7@3Va}!jEAe<}QVl@ZKa?b4DV|q&EBksk;g~ivfvFn5U z->YXBsNxULnukE&PjCbqqu|k7&N(v3hBO!=P>*3?hS}`Vf>sbgLw%Z&&P~$7%z2}( z4ASd{d~4_<9p&w+;J#e)h7}-05S`#xzN=FP;rv)PQ6D`XXh(>gg;vP9y2mL15fb%J zPVqxj~c;sBii_J+j?%O;n+`F*Dw>&;}T1tiQL>9BL@?q~fkcvW2Fc1cdr= zjx)hpwwcLgEz~)8Ar5iYH5v(I6K`kufOafyvCYObyTieByb-*3VbUp-A02=BIpnrJ zy{uQ}#h4?Ta1bH~IIvr#-Yn+82SmD^Y-kUwx0X}VNsE^r9H|=Z!^Tp_FY{jKt&r}j?aXHdr@CAkY;+dS=75>@FJni684d3V zUVY{PW@4o-3t;ZKF}Sk2bE7*sI%g8&6wkA3;(jJkSXS(m?3o1{OMZ;L5zp~r@a5Zt zB9gCmsZ8fM=!_7Kj$`SAMso8`7NDytA^I1x#kHj~m1)C9<7>CdXde=OilJ!yK`-(x zoRX@NmD)-d*W4^I63ESn`cZ1I76O!5Pv)&#u^T7c#%09eZ_geQuFH0`Kk0ti1AOz$ zihon)r`F!^g)m0uG8H0R26lsEnr4o7{cN94`cOS|%sJS3a;s>LUYa~FJ5Ojwhd;%c zVEaC9FuHvOpv1ZIcR=TV0sX3>y(&l4Sy&j(yFDql+`>T<|MJGZ3Kb%ibq)mRg2o2t z%t}nTenLLNs&(RUhmSuGv0+?#L9vB_N{oh&2f8&F4ex7$qg=1AM>$t z*Vh_bO&f5RWr-SY>5L{8qpF$v+>`d^Tkj`g;kGr=!2Wa~b%TBs4A@D$(q4_d0sPuK#=Lz)#IJ_3E1h5Ua0~n_L(q?!P5arvF^%uFhZ9p z-ZiwlHn-5A;w^&_N>6a;%>CRx2L01Csgbh9+`8JuPysR0Ulx4$S|eVa;z_45XsZhn zh%OS^NA)yN*PW$5^PZ*TAc8{A^7PyMs`iAXo@}mSr#U$UfK6^Mhe>*f0O zX(3E#^%{r{vMF3#(Wh*if-Fv_R^)otNCxk-FIvLk3Fd7~35ipRcqw<1!m(1*%DfO6 z<^KSkZ6t@40-uA!#-x25^?ezxiZRn6F4mI0fxB}dNS{b|bVRE2G6}Q7UukU|O zqx;Y0d__iK(r!Ta@K?@_8&0?&zu+{#M2v988xicJ%x&uqq6{Tf&OyXzXkhT0_}qt{ zK$!LBMxK6O#%&%kO@+G!rkLK4vDy+by4!KL{@_*g=WoIUmgr4npei~r2!&fB9=KzV zqZmq54OFdk57|1MMguByj}AXGOoguh-?R8J~9TBKDZ#(&^NE2D+LJtmiJcklPB#jQ|OD zASc{1mCJ6o2FhV48?8JEzgpxF_qFNP26fjl+VcR%NW$7};V|Iu?T1Zahh|1&GHu|4 z$^%0SW@kq>EpoWIgD(%zbzAt?6x!m#06Po()R=uCISc-{WdspH{p?80Dsefj^>5O% zXIN0k-59iAR4Jf-s7cK-OZ4lRu1R`lwi3s#lr2k*5HWWh@dHgFIrXD7oF#-aty;*O9PKrLm%=6{T*I!I}e zq@_eXo7;#ljP7C{BJ{LPgEFeDepq3ZQ3|trQ@A#DTtt719b!;{|^?f<$+ep~Y z@h0icYD%#lLYk0vkW$$fEmMurM{D4SuRQ2f#NoV_X&ufWg$S;;E$N%KjX(O*ltZB> zHVr4d|1_MKd8a&BgQI)rb{@@ET`blq9ZTMHp-mfiSyBY#pF&e!C z6(Nj6&81vK-Y0)S!|{$c<8WK-YjHw7`Mn@lTuBoRJJN60$KAKBT+;r8A+7+wL=2&` zM9`D63W9%P`}-K79|)qj{}sZ2F&sBrlU)7n^uK>{UH1h*Wkz&S-VpNG6!{~UxfVB4&X3q#&yX5onKwEToGnke zH_ZE`whmH4cuPioEvXmCfX+Sjol$0UmP=n2z;R%jBE-Z>LOF&`m$djkJ%|I*x8}*; zWXKyFnc3853?5OI9}~y8m4MxJa|e9yL>A#D!?_hV_7AP?9dR0+v2ID!OOI_H9JAJP zj6VCS7;;qi;0ucw-pO>w1pY~Af65Oh-jQLje57lx$ z(_=?|%dA&(Ace~cEkwny()ERwmzxW9nH&E^uSoE75W7ftUAt2N zUG~s1WsS^{UtBvG%4z^BjG`IH634T3PNt|KY!4uuVTYbJmUePX6?V3^fNmb>N+;W8 z4ZpHkm5ToSv?bnDr4Pqi93oH9n zeqzO)kCEXxYS6nrJL^b4K#&And_EAa-&f(rksE>K8*5h`-__D?3%f8~R*3WbvDi~r zsqN@OIr4neBUe0|?wIN0tsvfE#7fVI?!W{_b^>EtxQMP^fMykG1yU@3h$nvWop_ne zICMBZM2(No?28RMk_Kn(@70ilnUA~A(xAvlh+5n9kIACukFtK5K^vzfF9jRPUQT3} zc`~1*2rWwO8!VV7LVI(`J8vw2y}E&fB}n76q}4;#UIaxFi_A#Y?4squj-+inviuuJ zZ)4BnNe1_v;e(Xy4SZ(61xYWELzxD=&?gEPCqb`hO#iHp{x&Te5YDg|{dTqKZK4$c zpW+Kr!BDB~pD3E%+|Xqyr;Ev|w*@o?&UIB13RZ(?lh_VR| zT6kY+dn#0eO>gis>G`K6tK9Fe`<<;aNtP8ueJ zjl^ZPG8Gzk-e7JdRtDVEy8=Sxh8yyYA7W>GSmvg0bDMBKcqAeom7Fxn;nTeeP-=_? z{2I9eIMmE-V{h!L;7lPtTNZHaGGfN4#j33#^oXJ~cvR7AE+(Qfjvoq<*7AaEZvLw1 zo57MLT+oXpLGx>R3+Z+k3V%E*wdIJ;ywz>W7QZp3Z2y+T?ZsmW6TU;-Vkvxu6G!~N z0@&lsTtO%+xS(raw(NG&DEOx^+SHSt^!putxGH%b7$EzuF&Z9}eSX@vCf8~}(gW#}; zU?HS~U#npFwOcL^Jv>ZLr)8ghjq|M|`@;P6zSP@q$~MF|U2H#s_9_Z6B9qFLmS|yR z`l%YbNsy?OA#6oysd<4j;Z`$!LP0`#caTO9R0H5I7l$Rr&83??5=i0x0KtWJYSHJF zk-4W?(Xg?TA2IuHMiWhP*PRVEzYg2~5EN9VL9Cz!OZI}+KIA7cfeH3u$i(fmbEPDV zo{x5W7Kil!E6mTgt?>|)akQyei|8E74^e(F2D5|C>8hgLDFGKOJ`{2c%FOfr1PhkS2&!O0C}n&4j8C%LYyY>x}vK*`>-+h@w)V)jWF>i^=% ze38k8hx_?gI`i_QJUN0NHB~r{&ULgDQVtHgR{@xWnW9xLaMm>f)DgW|sgT30UHpxX~j zGU&+!?kTap`Zax0nBtycY*xpY-vq6LV=sbp;aaDURaQU~7~!xBKOFyHV8x)+&d>@r z_u>i=1k*9y7 ztin5ZNEfGIBy9DaGBgDG-$yZjGztOWiAAV)R3Lc!r&V2muIJD8J86eRU8MGWx+TP zkGpwSeEACCl&grU!7xympalEHV{OE~cZykWadVK zB6+!C3jzm5BYJS&1(fg#;6i2J1EfBzp5Jn* zD5-3E0pfdE^hKZLYuA%j5&whmpXYA9wsj;JzLm!GSeV;yRzmO?PA9Ti+_{%Ar&Kwb z!){hksr_L8mE2Dr3+qW8@u)Ya+5bq+`2X4@{o7&5|AI*>7;E?4qY!D*k-A)uACx0{ z*F|*S{E!1PbS=^8@pXg*hvP?TJbr*FDk%XXwMs>e+fmktoZTL~qd6X3m_>E1C!toj zNpQYdA4k-wr|AL4S{67jhMn4}l1WE(n>?WsuieHWa)L1e zW1{>hZ|1bt-WwMWe5G`h>N+11zSQM>*vq<+>_5u2dwd?4{cPq`43!0jnznxbNd|F2 zX!CZ~z4_7-Hj3()e1K|_S1^yKRpX>p;|)>K5~}$Oo3AkW9!!x-3pVR&J*_PQXZ3Qk zVpk@_e%5g83eCv5iw+r2RI=+_0UE@(;Jn)cyz*mXFPIj%el*VbHQLf*Ww*ISr;8`O zfzho3ov)uvdwffi-YxS6Z-iS6-fBqWh^}@Z36P^CXX0T8TvDS3<4?q+a_FWYAcPCI zsJP~R}~ajWo@M2@hWS=&E_T82Z})vSWfpw-x#mx6yeO{fUz#T5IP+uQe+er5m%Kjre3@ zftQ>jMZu3yZH0!llD+k!<&(+j{fY?lr|8?gNp@(sA|zt%}I| z_Aw<-pT$^8b6ZN7`Wp1v={zO!PW`2Oq39Z*8MB%@cLlhMwnbR{6!kDafX~zq`7CtY zRR}Ty(pWctYH7+uIM&mBYq@oEpnMp&DkSr$JNR}JyMAwwdKXq$r(ib5QSBy@7Su2fqKCBT8!4OZ#07=m$t3La%=!Oo% zP98M#(V?ZDnQ8mv)8@9uDBVo9ap4Rbc`n6YW@k4;D(qhI(4ABLF-LM<0V1L6TymGe zE4TyIj2ph2slao8k?36kY;p74xrwMZBi>QXZwK)2&sbyWzXBY+tcA|z!_IA{mdvby z;hPoBCjUTX+G(&r-@w_UD-6)tfU_%rT4Hf$zmZZ-tWdT6ll<6ku*ubrwz)rEpBT=d zPM8eB-qbM`rnE_u0UVG-j*s1ZY3bWA16*%%XNq33WF|~)U+&r|2(6lspKLqs`hQ9U z*KFL$P`tmy8-}vKBr;RxZ`W#;HXR~$5{WtU%=mFC*9Fso4|GGK+BHMd6jbae$nC<^l#7o zreXahadkkfa)tiKKo`INqLifai9POl>u*ti%Q@-qsE<1k+OyxNdtKYtJ zlR^Y8{{Fra@!MKPl!}BzH&hl{Uvx<$!{PEc5*u);kA3;{lHJ0P4 z;~5m-l@23}%@j|o9LDcSX5OV4dY|O$Q;>&;$8fX1uh;c)r>^f$=h|uAzumV*LXm=q zD0axx_+8U=N`L)qOFv-mV_H>-8MTPHnlqP>Ci>H7sqh{4+x}AEzUdD-LGpbPtW_m} z!E*{KE7lFNno%ozqT9Kw(yjgAbAaQB^}4IUh>m>u;`;(orEop-Gv7>)os!q8ij?{U zZ~vf_o*xR8@4fTb@88NRDXtTc=Vw_s&v&MT>+bQr&2VsLcd&IDTu`l;7o^Bu^kY0N zJ=$szbFRB=iX?kUb+(4{Oyn3EED}~5I%S`rG^o7wAg*sES?T=cfn2Ti#Wc^V1p`J4 z*&8MVvs=y7VPa4i53yZ2Sl*8k5>t#6znk59@L6`qr!o-XP&sqC5>T7PfFg}QiM7*z z{~&IRA(@68pW(wmENbL!|Lh$?QB758Q+>PUwTsbryQ+%MDg?F4>E!C(H*ZAE*4XnE zn`CNG3_5D_`XC{#R>S+PajsDlIf8%wQf)HQ0uOFq8Mag_njIm8V^sI#mt#OUNo_5d z)V0}YC-f(|<$Da%dTaOSCVdUoU8wfA??27|lxAw0Z7l5XxMmTTUBC3La%Q(D1x(uN z>Fw`YY0;4iwj1Bq=nvyDEOX+S&!ORcQ`%J352E7QecLyrmf@5ymcjIHS4pd!gX(c( z(;wf+nD(Rp`H2pEJvafFFUAq2x!S3pO(s-Oo83J%vp){|`?%Bj%A zkZVNf+(cC%rSqXyubYRX>8yZiV5{u`3fJ^$+jvc!&yl*y$;tDE0lR{PdOj(A>ua|P zg=-BJ(DF1<4dI;wM`Dvc+a};|F(FqeXN9-stObbP;rA9AeV#jUG8f%cCUCHlw6R2B zn4;)FAuG-;3653D=y@m5VXW+jH^O;U6-n9R1BVlT%=~&KJ^Dh#{_~q1Y8q^~nNBue8k{pCw)OheTPu{`h8j`MB4ZpCFWKvrQIL zi8@4vhX}R$t!8?WJbW~6qar9cysg7y?Mj|U6kNZ*NARG>r=qm9CWoW1-R^2p*G5>Q5<~ye^jqyL9Sz{{ulQb8ox1$80U`r%$vf7F z!~4H*PuF{ZBj;mL2xP5F9e}R^GGMHrGG}*lgb3dMG8Okt0FZX8TgXpOPhis5J71J7 zDC>l4$!BLNU6x*H)mfw{hKVKPcCKq7%^lrcIVKKe!c!m#dwfNN;hWxmY`mvF`k@~( zbguobbC)d^oq>&;sqVJtzts4?P zBy`3Wl3gC}N0o*ZnfUKeDy}u!DRYra=N7sLN4WoZ)W_e@LYDVP9M?1fS*7nZG zQ7E35-?O!ppxsJZdk+m9-E?@k4?+e>f7plqfE@cmQc`3rUC$fMvd8z{y%5HPwzGpeVYXvpXjQoGk`lDkay7P`Xe zsSabS1Xxd&&#m>=`+4h?5jFDWrvG;hoQpbAIJ?V_=AWGf*;qgb@OK6Tw-0};4Dj#& zn8os6ws2d2j_A4;%lP{HUQV^016yKNV-a9sd2&rp3B(A(7oY@nMRCu}irli6d`Upe zXvHfEfEMY(M``jh}UvAWlWN( zuuhDA=%!jC=*-@nUi5xF4QD=y?}vFU6#^R(E;qLY&=e24zud#WdS!%k8M&0fcswf| z##-IC6g`=W*JZZ$wbDfd`fjL`c`!8M2YZ4du>=`;7-tf7W8vrpy|uO^9#sM727YsC z7&GBJI>SEN8zr);TqfqIv*Z;=(eb+XNsiBuv+NlvNv7Au)YxpumE?cr`S&e#71p=k zuy!NSsB1D910Wwg@;@M-Kdt~z+!VY{e4ph~YKMM0;sg?!Vm#fM$-#eIVQNuk-S1v4 zT!;@BkNkL#MfSp78_RK32Yb`3P+Mu2d`jjII;!S2@R}?tL0-I+q>U-@Rm+bvT>-_!~rig2tZ{?zv$g!18mBn0AVFr{(Rn zs89(BE`qOw=2yiCyOG=WI9l|bmenEQadmW>*O*|2j%Bl9y3S)JdA++ep>FGsnHg>{ z23Q45!%46<1z7W7B#?3!!dHl)(L)KD(gd{N{$4r7qPTK_DFs9 zPp}pfd!B^OEL3(UB6d*>!-OvF^eqY$wYZD%?NqC>AYR%HpbqQoN-~#srO$uXOO)XQ zYc#iPROcN1QFx}N)1~F;O<%w?(hRqDne8;2l%v1|uN>}+q9L6WTgW|~$=9iUAG9(& zlNYDfpQyHZJqxvpAH2uMnB{u};sC0K>#>ogbt@)fli9w-&tCm8la?0Whq zPorlKBy@B)HtE_c`$wYSHINvQrJ0&DH*|Jb8*P6{L(oS3gp4J!#a}`JUYv3%Y1>?X zH?lB+UyI^E-_uBy&Hg38Y+#KI@0Mxmk2H zmjg?6q&WDLysw+ad0R#2ryJ4KM~^R3uD;o2)JqMddwJeg@DdZ4(wC%h^|+hPHaA_X zMH?kz?7pu@uD%$+Yrme~a0S#G)^oX~v~pYyH|!H5omCSjUfUAgX3seu-oPU}WRr=) z&S4rZA6htApfp{G9GI_TtUST-r*tCeb!q&y=@v%G)5AU_W9+ueA$D7M>jhR!k3&_9|`{21{hcHQUt>KpT-fIaZnA%pr7kMcP**G$)y z3&sx(21JQeSU!hUc)0H%{XwK(qoTXB=0e|_@87=(OJ#ljcK?8{zH%rY!;$(H>j@}P z&)g?#g(9Q~3XosrTUC8TyqXKjrrc?nr+yF`Za#Mk4F)}Gzjsc6P~9zj|MAm@2OnSW z1p!vooBvkPJv6y8Sv0;8tVMP-WXcJX70l&n#4M92bO5x%nDa4e$^b?7GG$# z(;y!s<|I3n!qAX=cyO*zQdmi-{|OD#bkIZ7c26+_tZS`=DQuNV?dK@ zk;Zw+9)9kYCHnzjBFze*v{8cORoi1FgB6q^q4@D2ohjR@2jQCUpL=OX#u{sV&%?kln&&VFe2hN=)eJf;Za-J zn;l9|i%CbXp1np%VffTBvc>jZ^tKhEo-YJtv?z%w(euHSDq#+|;f?!i^_y=F2Crvt zb*^Z2y5M8YQ2GU^!xiStt8(PN=@Y?n*!GL#8|3-@mwn8VG~}$=$ziU+?e~6#M<8s# zf#$qbD8;Zkq{{<2hHgqZa1!6{oL@BU@)5Sq2${*@AI8o$=yfmVls!xBr#Fu~o3E#i zK7{f&$R0dPv&t1Jqp%Vm0lx(#@wRkTLG8LKtz^PFh_y&e!jtr)hLp2$iM(Ym9$a!O zfxbxGYbXNp`l%2OW`rvhRjY?I(9&*mMvSTD7b)A^<&B2ss`0EH+BAWyCXe~$fuH>=pBA&`Y+D=tu_I> z!XFpZaW|(g@9oT%XH~(Mt@zJeO*$Jcm41T;5(TUbbIFxA_gSJlK>;&Ei8ZYddAg7~hSI2nmfb_GCkNe56I{)L&Nud%jZj>_#`$?(iF;p40}`jUNHk4X0EK)d2EO-cYGrK2?>=>3<;-Lf;S)>hN#eu=km)|iKwwqt zCk-Gi{|$;cknvm5y8h&%e6P)aWaglv{9cxhn;A0bdAvKbVJJf+N42WRBE3I&aH%4$^Wus&{n*_?H-O!w>6<9kHqw&^`xi^B9jLGbrEWkAHH;6PG z>bFYMWr7FNH zw&$Vf&PPo+kYW%k$&TCCZ&la53Pf0ET50&R zX`{F@?a$BY)3x?BG~B&CimUsRn+Z3F@|?Y5-VkU!|8iU(kI+{ur8tV$!E9d|0i{U_ zKh|YMD3XRgCx34mtPX&~b zLg90&Et8`!n={l~KBPcL8+Ze7%D1lJwg@LOJhn7c#eRdxl2vLaEhiL>?7;aTWazKjhDu|m54 zB0zWq>15Hq$QGD09klIGsssQfbG8_FE5MaVLM>-7=Waa2Yy!*{Epg(0lyvU&wg z$J53}yuGN;pB}hu_<->B=debzM;( zr^yO`-jKAi$dGQy3)`k0dVNXA|LpCsqs6lL{xx)-{8eEall{Qz5;Zih9YR)izzC+A z>vTHHT^}xWb+~0Z|I77PRY`0Eiv+K{?#OO-IK&z;v)d8evzv>Nqt#szmhs(@Ie*A8 zrgE_NxmvB`ZnM%og&IQI%hEXF&g?IQdznZ91^Fov(i;Lmd}-bIVA- zp|^K&R*c$9L3ZZcRbU_OWBWNn^pmG?vlC|Ix|&Vv0I5L$JO>zS+yunVuYxK0$F`38 z!k9QdwMIT*e6_@K&oVHU2AIH3aYcX?#au%LBWVIp!C`VB)S4GF&E#5^Nz2W`tTUe3 z9geUU8waX}r9Dvv?hQ;$lBgk4+|8v+FveTIe%fQ?+KslV*0_sB-I7=Aogz<}W%Ks$ zQR#z1U&tS3FjMOTL1SsWqb+u`6WWU2AAy$U8KD7ku0z2{a{HL;lxkx7!}c+)kY$3` z3(_Ab$1%R{-tqO!Y26>4YUrx9B}T+r$}aqDAAmL<=zAitFh$(aZ;;d|W*vw`X)yT> zYH+#YiK+o0tko5v^VDC{Tt8ED%l;XnvPdKYbiveE|4R>;BU&zf#exzhJSxaCnl-04 zUcSiSWMGp|gyuggj?-q~>3ggqNq{ihDleXX^R+oq!ovN?S7_#)CgvR=jU>SoplMcI zg6f#mACJEFkX3lpob2r6aha($HZ{&{x?9aND;E1c*H-?RP&ZDF9di?yKI0M!u}6f# z@17in_?~y}%kf=lsZFkY8S}iCGOESUO)+o2WIA&8N#R$#P%5RG@<3}K#f41SzLn~D z-4*NQ<4Giq82x+lInyUyZ`mL6DC;QQxs@bQQEW@DHss(KK>g4|fAg5;lFfeUMyn$_ z9GQcuEH`wh-o9wdLD7|a8lD02Psa}A`K#xQlZu&cau7SuYAVZ2|4be?c{n|f18Qku zmhkaKNS2e`84Porj~j+i1TaF`Ix_YVVIJ@(U30Z6OuTvYN3E<~XGV6YK$rL! z`!^r7dH+ib@7bA`@59>@LVMBpz~Y(}M}~z~+QW(K;)5W!WE|~^9E_RPj9o(O;I|iF z8QX53GUTxv==c|pIC}Dj7LcYc5IXVNSf_4&?2t4T_F7c6KjW*m-CZG}I}@!m)C)7wq_MzQrnh+G>tJ zQ_3rLnD#oGZsI#LDhN%Itd?XpA)8@N#x87uZ^_VHitP9*hap}s1xtkx%az4Ctvc~N z&rtcWNzU6Uzc}^0BgOJaqXxqAIs^9(Yl18n@5!Q?f`QA@@xxkdTrJ;Nx-+(E3_4Nl zxqh#ol3>f-K**j5VK_Fw?Ted^xri=NV2ZjfIKzdt96s%2gy{U_<5IL%A=_If`E0-z zq|#Sms>sEep>$H1*-IZNS7!08Qv%Nh_*F0tUR9)_fWMq}f<=)Nms;%<@57a3s zN3@W1{R(CT5pjOy>#?XG*(WWBiJ>fF0p9{~Co_55RIAiQ_?e8c*>GN|h54+OJKzLr zjw7xOBBZ`dQhrc8a66$Oe5(smRoO`dj3a42dga?YD<@*CVOPeJwPe%k9)A0E@61u` z@kgI9?eVB1Vhao>yq!sGx3hs>JQAh{$R91Y$F?7SFjJHEo+z_TF*0W;VR_5o_^VL- z?j8v(D0WHIX780i_Nm)dzHj#Z?n@ZV4-<=8S}qF4F&8H1VU;l1em*wdpXWP2NV__C zo>?bJeDDoRmHtQtb7G<3Zwb))@EqL`XmHm075!@rX0j4}^F*bxps`BzwV<89o|S`Q zO|f>TvpK<3I}_h2xeJC<{9C^qqk{#h)pV-@1qQCyH0kkG+Zjo77PfCm{wRj!?k}TI zYuXs${*>F|V*5-FaW_j)kf*51xK>WUj~HDn$086hQ6cE!WZOhy=_Z)CnpiG(+y{YL zlO|}2WxcX_T)K4e<5fO&?|?6SpY+lQ8oy!?7C-<9eOn=)0R7>uW2LFPLi{=sEZ*Zz zn+Y8(u|Ww#)!b*l)QS=V`BG~D+gC6w0AMQY5Mi^UE#olAXH0gtcmUHR*1*-8z2-~Q zjFYwMA_$gqkjg)l*zj7YPRR{XV1DZ=UXBh!u@V~Ioyn#oUJkq3sG+4e*BFcyDqz7>y{sNF6*oUIQ(IS;J zOFL2x9sY8&+$Y2fR!`#Po3gg5Yh&?q27}0Mzm0y#!=kpFqJ80SX6W@x^g$^afHF4n;PsnLj}rlV+U-K{I`AP;_}HPsY)-U0w&=^@Kuk|+dt!EjESx7~$orF>vkfOzVGweE+!p*rb$>s8*li{JYb6+)A7~T{* zu+~Nvc*aQT%|BkY2^`UV#MDi-3a>fu@n<*-!N?;IW8}bJ8pnVoc2}UY)5+u65N$(a z%KRa>+FDxVau$gn$KOq_`=@js(|^>pJR|)6kGW!v|71Ee^9Z2GszB-o+=BOscP*VU z1J>dnR-Y&BmW!~#Fb&|a**&+L1J}4T7J^-6N3;$9&i1;?=|xgQ*g(~FHSk& zk@ZC`8;DxkHj=p9&fq$z^?t9d_{x@QcxdI2cy3o4ea-JRuJ;9wJP6*qyj=lE zd*oaO=&|`U36wv_Wa*>03-A4J+~%+vFBV+d{(f4f5qT*-=wb>O1Ln%py&OZPXMBH_BRZ@Tr_?avxL7wrhdAz0jS&Pc% zffDJ&8^@vD3ejUQ(l zI5NDynG$2|Lc7Oz!~Ovz5`yGtP94r*@UE*j`+Vc>VBfK2_+XDxl(5?yv6wsgMFGJ| zrS*);2QAeEV!DyCbb?q5 ze;={v+tc3SB*d~f#8tMlGqK9!P72!ezV@FX1UII=R}nG4L9}v|+lz9jrHF$QC%-OZ zp)f*Vc+I5=U0M0Couk9Ordr3+uxnsPwz5v&DhBzOlnXaVXd6iD+C1!m6Ejci1CN@r zdfkWLV+3s+)}-@oVd;#`2{XDu`7f-x@@n&FVdeJ<9mf2$zc%AMSg%23Vx++9#VC0uLSf&r#Dj^kT|v0>7^3wFib z?FTAmEFART8S-`s$_^m*ke@WoSvz5M|p;%BPB)YduuVhM1b2K;uVGvNg5=_U}o{koH6Xk zUs)%P+gYei;PLVER;a+a&;6@U7Y+r6d5hgv`nPTh#CE+CY(Rx0M`OxPYy6%`LT@0AxXI-W+hCOmH0G&JE&`0OdS;*xjKR`Fu7))eQ{01c&0Pt@mAN-2C zPACE^iX5S}Pc^4UdnG%RZ`16MuYA8CI&dm{rU2xHm$HE#N!&ZSmP5L>$TvcZy^He7 zMUl3jjkQ|T_J+Wyyo;P<1SSp{-Q)Ae{0kojYSJl5(eH9jV0|v-uxwYQFcOs8#imBx z53EoAR%)tO#i*%5ex#_qFuO&%O#i(wv3o&!-#2eepBw_4?gP>yGZ%PxchG(M)kYJ? zT^o)Yu3sopzD7cB3>Lc2Z+$&THdpJZ?jGPm7aChbGd9}=pZF=GqiLpQndBB9ey*Wm zUrd%i3wl~jZnJPcciDUIkD6`oxCryEa|o@ogk0*rBJD7znug)~c)bYkc6Y3HXsD{I zRnSRaZHO$-%=|9-lS4~nUq|mT2Hp{?+qrnB8k3G1>3V6V)!hIlmC=^*oqD@cFfAhc zgyH7LejgXQWUKeA_f5Zt8dhw{TU%bSK)uhLuCiL$2#Oq$*boitNAhjQIKcolMP^2xV6G^Yl&Y`bp zu_8d4v<0#^RMd>tj708SwJK}gJZbtd-94rF5w3TFW8&|I_onG81BQTQz8UpLy>>G@ z638cZ*PV_DvTbV|E4Oa+QM!MmGJ4=eOUtjyR5}X+fe1i3_&@>jXA$y$+EX{3(&Fr8 zHUG}Mz}&#h$7S{x?aBpk2$|>h{2^HQuP&-~EI)99SRqL-@wNfAwr2980U@dery3su z*&{6iIu5Dlh)C)-YVYLavRz}l@RMJn8s@I}tx&plTU)EpC)z1?Rvn*%RF`j03f+Zf z^mZmFZn7-t z#J3D$?PFMD3r`EwQoPklxjuSRunb*_2w7x9Bf84jRybQ^>V5g$iG%Y^HIG^Y9tY!5 zvG)|r6F{d!@#tP^%4L6wdRCa{=gGLS-l(lemHQ|E_&4>*f9GdHLewfw@e*-)+cEpX zqp4y;m7Lwd=0!wc%F8z(CRMrQ4czTXk$sx>i@1`{^Bm;`ZRHgrNs=9JuS(p1B|$-M zT6h^MCkyJm2MqzNZ}(s_MD`vt1T)U)z9f{F<}TqX7ld`4&OS*b={#-f>qHw%Rj^Wq z2BcH6E45fnD?qxuY9}G<*ni_UC_cxE5Y$~jnqw*jOlFH(+aP=osdW;;zh*`SQP3^nY4zSAN7QuRa0Qok?&GNr(Gazb`B`|!eUrN}OMTJ7dc#P*k5y~~wB1gL{4Q&l^8%(?B zCIiVvZV%gg6a#!)M__2kEWB5a8)et-x8VKl*`n!=__?o5i~+r)vCj|1VsiyN4Z7AO ziAX-qzLB9wCfdNanXcojB7k9PPlSY~8+Ql&oL+s%vS_6I)j7Rcr@VWKTH@nW5|Z5k zx!zWzb8U8n zUw$*zYQC$Dks9CEK|*vuXxB>8{9O5qJ)AzZTTb{ZFc`Cyt?bpTSbFhDzS-`mf20V; zr95tCbw*&!OsZqK=SUfkJAvv3GGYzK95AtX3pi-6#5;ZEQsFL^D^x8`G^6Up=fm6dfMqw*Ny`m_qGp`nmc*)Gq?bKPOkuVSY!eA}poP4RDVNWAg z8z-ig%Yrz5T{H2pGj)-?k@(pQ9_ZIo6cZrsuyhBjul%jhh1VqU$qz|_tB9mW%pIV39&4fNh%OwHst{!vu}=#OTG#gp4BQgGkX;% z8f7B-b+CSz>jt*R^Z6{!@>%HT^O!a~prkNcAtiT2%w<~xHjbdf4smmfnbr|5++DM$ zucWdUSnJ7^hA3+~*GwO#*u^QZmfF1Oq}nqU>K&5qqOZsmOhx(|TM#*T)10L;b6Z(w z7^@fh1a0j*=6a1Pp=API&Ak`QzizNmq1Jf@L)%sSB&bRQbjc4nLQH9Ae<_A~sq4%eeA_d!&Y@t8Yn-W$Qp2V& z$_6p<&%w&@ac?=ntOo^BoJQ?3RVTdQ6QFT8P zcT#>@XFsMKB_U{IZ#_5~aIp5c-CF-ej@(Et?Apq{Zcj7Y&P795WvkG=_n+kbMU&ez z1U_%e=op%sc8z{{jn^us;2J}LgpeZa4r#G+KU_{o#7$A7cej<*#w(^f`k7Ym@ziT* zDz*}Psd3I|Q{yML1>B+ZMqFdL{<4E!+4h=yRMh9pZ0^;eiH%nL%cu4@v9GAvMU1)$Y9o1-$F_ddQ}&V32a~x{ zj}-k7V!!ml$P5W<`@zwk$}gep`y@l#;CkiGeOreLffIiX5r;ib=_@`RE88DCRof3l zjw4vrQyQaTDkC==qgYsjsnd{FZWvpyX};8^ zAyYWpjdZplFC%`K{5(uxQ165E8{cezc{T{RgE}Z#W_qaqW4u$?!8k0rXt0f0aS9oB z#uWvreMRg>ZF#+Iw4P{I5hQKL@A=+=bNmYEg_dth+WQ@LR7TRkDP`o^xLt0&%Ay;u z7^B-W(Yq8@^>LAMG1BMeN>K^Fq~Lc663$DIS^5UAZA)DBLy#0~hMXcu90DGu_?gi> zN0>Zx^zppm_Wj3OAlIzwq4Mo`x(pE`F|z#3+^^@Iz7Q(DlcO}*Z4|ISOIir96_JW+N+#?NMVq%hw?=|Y2K?Q|!xMmgJ3DRDOS zwNbm~N!VTrMHfbL{_7i@N#adf3%%qL2@hf(3aKFK#DlCcVQoYWV~6Wsa5Hj@PWGZj zKf@|+Dmbk(#MhH?5KwS89CaZC5At18;ML~2PB~D{_EuN!NjciB4CfC>zs9mbZ6otp z-tx&klz&cid_B7(ahKWSN7k_>9uk@hy9|} zz#z`HF>XnlhKMb+&^A&0(Lp*dV~mxmAJc2K4e61Y=`P=;=(bx>-L3$(7QcP9ihL1Y_Z}-RMo)wtW6Akl2dB?i~+n0nt0hezxO?8?H#;r|($L9^hYp64Z zIa*aZHs@0mPsCrslD1_24oRm$j$m-`iw$^M#aQc8IGR+M1eGlZMF82Q7H8Kiu6SR4 z`^UK-CODx#csZJ@K%gj5%lPs~VbL##hFk?5!cP;lRBA~>2@itKS>td1T~0kW zUN_7gUHKT*+i4;c9RMc7#CIH-8x}0AfBj~-JbvJ;KkGNi!l+U|*V<3B{)=jOF9uA2 ziN3TZC5HAKep>|p*yCt+(mB_tLQHz{@YnuQdgtQASs)TmQa%`U515ehTu)h8jlEy- zvDQx<7iuGZ6-=_TNRB3HY#BRkQQfORIw#4y)5Sf3=)L6oRt~XQx@8ZXDt2L5h7|$F z&I`m_{H3#iuea;RcihDC=MHB9;QrXel%WaYBZh%YfwpS{?eW4t{ zmSz1uEUVjVAf@r~Laf1!E`@kO?Rvu-|F9W)BAo^8=Y1=%n`SR9tJ?}tBOMEn&NiO# zo(8Gmf^tXgtx@}GQwtgVqAb>x-Px{!@|YBYQ5FTS7PV_0b9jOWs>I)naI?)97{4yxuu>$G zUmBq6GD)h(fy$mnSo$N3a%6dJ}XxXr%{A0gv3FLx^($w zt7_Q}m{gR3Z%7V8Y${uM=2=&cvE+Asnlb>>^9Hla4)_>#plBGV!T4AUOXTHOx&R?e zwO=|(!;Fg!y~2nCQ;Ab?-lc@HP}&_%hcRUsX&SRV-j6mqXwfrt!`s?Q%AM>PC4YIQ z^R0}xlOEe-(!8oJUY3F1D{{mys%n#3SGig$WiV!_X+^+JMvG<1HJvx_J}VvAu5ca< z@b8|=b>*1ss$hxZPK8xJm}9h$lF+;U_0C_jh=E-S(6#?(gByL!d<%TcJl7G9YgW-) z!1nYFr~Mar97x}6qan}XNS);Lg!=G?)0@QVe{qo?ZlzPEZVXF7J_ zSVlePZVFg2GqSEMN_xW!G{<XAv^ZTy8ZEr7e_PJGxBX~`-)NMuuGyYb{k zk|qeRgfpk6wPr%V>g$(GL8lFdB$c015~uofH~gZG4SI)U`(-O5lq~w z+|kQRY)W_bzI{NyKr46LIluf2nM~>J!>zysK<-p0v}aL3z1eS;OL5pDVSTIeZKiQ!F>l@t-Ln_zm$Qx7;37$CE{h=isRo=VMb4!}2|JoXyTDLoC)&Y&-aDmi`KeZOy(}7e0;T0-6Lzf8Ix7v;^iDCdl z{=9lxam5~H=C^!m5l(ae=PMy{S`+OkeU@7&TF7v<$4FY4e4ovT=1x>N(|4VpD4{T4 zi=IoZ+e9$!;u*obv&g}0ry%uo6~Q-85=~iOvmFHH;YFQ*tFc-@+-*wyZ&08C7@KUi zPMN2{;h4-D+wyZ6H-whP1<^xr*XH3z8Zh-sXP6;o7gf|g%V>Nj&&h_M$yLOF=EAcz zQT=A5UJ?s?k_zQO%DrNeBSuDBgkmY5$qx?*`Sv^eHn#EoQw_Q0YaCxER7C^{+1w;} zeNL%5GhP%~kV-u-T;-a+xQx$VoY)euQu^NANEFCHvK{~-kbYPIrLa-f;?4!rmHH)#4Hw%h&mZ@`h;2B?{Ga3oW~ z3urt}MiIiA)ipK4yDevsS_My2ilr38Ce}ns|S}3SKkA{`(-1(T) zqHLo02AIZa;=OVuwR3bPk(;#W!lN&{B=uU~sORvPogA#MDtjS$-upoB@YTDv{9536 zeSrVRc?(=VsWZPa(=`A4j#hJTKrc8h6v?DVX&|(61?g_iigSWdmCbD#r>5nbE*LRj zI&L3Wuxk)<#V}!g>9MD5OAm1@(2W7)Qn)3WI@gI~Lid%iW*Rvw-c3>e$4gqVIA^iE zc>?E4`CieVSD)wl94jSdl5eEWiv@ml^L34L+EV^nVg}_V#Aa1oB{?wZZoV~19_I;R3G(#zxor~ zbp>h=8NrI1|67RWE5#&ndDi>Z&LND!nCbQNPI$-?Dt#MH0;5{hy18hMvFdCSLqDms z@z0xgn9|-pHZe0Zbg4=A>b38IVjDlEO|0M@v&b*@qK;OTF{dY`HgW_JKFhg{;Rc~vLkql2nn1p_WBQzf$T_gFiNWv z$V#G_kP$`hPE}Wrb=5aW#fFu5jQ3Nj(iyoZ<}%a=^OZbuPp*7~I&VJ=!AW5NXfSFV zd7{4T&)1=np;)&ODVSX}XO^jnoG*wSyvyz$sGe&d9GcLKt+pu`jjeP&md>`^TD%vp zKfXC3=)^Uqv$(S{Q4Y}ROSb8`jMoi>jX971HIS9TYSd?GE~f&mD|R>JqY|I zOf+&&YO_npNw(H6R$oGtNuf(eqiAuYNb&aA5aU^xw#)sKW#U#Soh}E@GD&cwjGiBP!5g`hU9a69qNy6(A3cp=h zJA(fc8vL{o9hOWOCV0{?ak3>)k$AT(zdlO+w7$vSI!j{ZeRHnGhXPA;4DWByGgNPM zMJof6L~R^N)f+9sH-*}9IG!2s%b)8C)^~K`Ras4UvdOlNea%ARx<07KFw9V5nF`;< zb`J-vDaTrw(J_DOmRwZ)(7w5w0&+kyrTpT zK2dM*T{&tjKPtTI(how56{YX(lt;EZeA1m};c&>);;5gyF zz|re=+Lut~v<9&uhQaFGIAP$M??}G zVt~!9(MV@wN%w7qQyTuA8bw;$LB1j*7AX7SPAAY*vi`Jv$PLWkEAv?C#Y-m9}*Rh;_#7tR2lbaW2Vhep)xF&JDj5;*^wkq5x+i{K6xyOF3GwnOfP!f*7i>I z3$9RudD*b03{j5hIR>Z$!i;5OHw&XQe@*%`larpiG+2{v0itx@_b3)YC#QS#dsq9Mxubm zH-C`?fN{e+o7bdTXR~U`ptifpla?7~N_>e$3qZD`>&_R=!4bL`SXI|2jql&Gn_&#g zBcxEmN5P$PH1(H)*{@A|()piDQ_sB{p1i?(C+h9<7a#&XOWIOTUg6g}j$nO&#IZmL zZJSWVm%;~xFf=C>^Ql)GU`T(O)&KXx1FFPwO!y?~gB9QU}&Svb{MA zEZXn3Ge+y18d@9T4#xDdZoZdNiJ@aMw5GCbzv02!;*-4Z|1^`XxTJRP;)L^46mQHQ zHPfBzhaKm>yVan zq{;t1@Bfeg81nk}_|AWpD2$9{>oF#o4y#*FFB5uv6aVYrnHx5a(J5nQHCfJvZgv%z z#z;;?0FQ_HAYH=D$r0$@SRskG=DRY@7!)~S)RRE)f5 zu4CK1#t9dXpRJOjf`P2nN5vfcYY)~x^pWo!;?YDi$kSGWU$Z@NTG#=?%A~D7 zqfOE?Rxz){M}U}jj>2gmm#+p+J4{M>?dJ?`+~U^Z$$}>C$F7##J69(sF+lc6gewyj zK94vu5jJGdb{ic`Y+( zR6A5@Y^xhBnp|(KcidI6PMJ_Y+oEHSb{9|Cnxkp}-$%vo)uH*6!mKK`aCDR9N#i|d ztEx>Cl@(5c@45{#^!Dx#xr*j#R70xg71?9THt+UPrrN~d9gtp!o-1L(3$#kNQZh2% zdrgx#u^U&U`xKboq|(ELUC>%v^X@2oPL_#TyU$b(CEPn*7K#9qVkOJA7bTnZf{vew z)9a@-7c4f4d=RSX1kWht`BREh1PiO)yPXyz5v!_4@D=y}8>r{sH1mIvXZ^QcpPPHI z1+(H_esMln^yV$P8y7r1Kgs*6Rg0{+|FdiJf&U#ai?etM-^2ew-Frqg)wWxsK|w@B ziu4v0kPaf!OGHJQ7!m0uN{2}A5C}@|0s;y`l#Vp%RU%!QNSEF_frJtQgm~8T_GiC) z@3F`EzOlzSzZ`~St(7~;y02@_dCgh04^*(3(Z^AW1ms#4$)c&OBU2ii`bwk(2)@{? zIZ-M(oR+@T>vl@N<8}<1es3;+JM_ znmt|BC70fHD_0!8FtO6kJN5O*wc5?SQy7gKZ%3XZN)G9o;PCbEPZRyu!uado2&U+7 zaBB3bua%CFFMZHOs653lGkh6=;Hf12YA35uesH)nhMw zbuNyT8&k-MNKTuXc2W^}%&guE(%jMc!092ieg{Rb?Mzl2Mq~D9TcFf!2s7_e?9R5S zq}1Wzx$|5CSH@AoKEo}oa9)U^auiSo2sbTU`V-baFs||stiM+B4XTlSp);#Q*k%%OUvg7Z!=cI{Xc(9uu1DL4)_fcpC0qV9j`-&#D2VrI$6v{Y?fnn_Ji7 ztY*`Hu4w3!GtlxVZK*oH9K2T)1o{TzBs(^cQ3Y?&IIqCskHhgaVt;vg?x|-!@!*V> zp!4^$l{!R0{&o_Uzdx%u&Txe-HaI{?b6ICr`bs#tfi_&WE&_5-7GjKdo1QR0ROlxx zugaNZ)o1NQGi@fXcy1=={UO^G`#+QIsxtKw&?e&^G@P5|*6M}J=$_2lr6F7mfP`id~eGC*&{ZE-;9 zEPpkej3*;Za0>R|OUMO*G0y;43yZ(whx@srp<{VRNeeu~pG@9~i>{;@nLhZ$xbu?9 zrCw?egMLL4HzjHkR6hZuIq?M>%_5E1wV0jKvf{;|*bxa0?<{#kp6Y}eB%fFKd&f3) zo%deCFTC;}Zeosz5pRnF!wp{B<55(BmkA>o2IiSCX5zgxf$NT%nu3g~&NJ>Z$LeU$ZES6Ebk|Eoiz!7^j1%)If-{7;oGpm*n>Nt+o=@cHVRu zSH{l;hFv%6g)TM31ZRC5-2uiK08`iN?sJw0Zoqih{k#92N~bu$gk*&LhR%JduUzsQ zB!ZrY4Sjv|*AnzY-Q0rY+dq38|68EQ$qDMJV%S(LJJa*>l{K z*(3W7HW@Sz1cz@7cR@LGcKP5Q8zi-LUsU9;VuLF`7bc!Yg~|k4Usz2yOx6Spj5R+j|tyw=Du`6Re7W@aaV)`d~c3Y~_)+b*~i=_*5HH zja$H+Tis*Jjyh45n8@xN_N^76O=WKnHS6W>agWIiN^_hreOvaa_Ot2agng=a>iE5$ z$%|HrCa?7#2z=I3*E*MNx5jH32k#>>z?~PBgiZmKa7e_Ki}@q&N#?{^4M)+MMX7h+ zA|tI^5|YDouge$ObP$A*IGC{+T#t|y*v)GIwyvo#OuPdXvC$wiO}%VLq40e^VO(k_ znGP|Q@YJ*cQ1=i~vO`{&!ko z;0wX>U(X$F3L>sUBJkoNb9Mj&h>>zUTVZn- z0JbWENym@{^YlbH25SeQfnUHh$y)Gl&>TNe;FN2Qh((?*1L&-n=QN_YMAhhD9s*l7 z0{cGgZx8~7&Cc+?qOYG-d=|G$@`0S~AzS0iXMjx<_z5*b2|7O-!-a))^aKBSKDB>6 z&zf0Va&kct*y^7LEVwA-^`(U?_RjDxZ3%!CxA^O(mcvVy=psO7_qoL1A^(C3!JSyB z{Euzx2kx!@KFm*^nW0P_QlGN^8Rb+3Tp{WcAe#QivlyEj)sDw!!w==>zLQo>vOWhi z43qoU67r+@0IXX=jNh?t5Xzq_fvn}P18=F;7&!p_39JU#EStEstMWfT z#^>3|@^5bf6_N547lGzTziR6qlKN4PM?N^x&{!a=>Te;ZxuB$=+u9&LCd=*AfRBG& zdGUW)DIwof*S(5rCfjXqa*Ai{z5V6;GAH-NWo|X8h4E(L@q>6aq5y#!$Bf%m z)SDmRm{iK$Mk5V>E)RJ=sA>k>$Mm|A++!B?W&G;OSW zSAIw~n)v^+E}2iK zB)Oi(1g{#fT3=(j_R9Rlsf4M+$x(Y5XaHxOQ;(xaZQ~MKdmuA$JIU4aHtfgwgL(gE`!L~^Y!JA6AQJV zJcG;^84NOb^iuAA`UPTpy#~t6XOk_2|4`;83Sw>BF75)-bmk~bsgyzNu2|XbPBlkS zSOn9(eY0NS1r=FP&}|pt!L5vAu1jb48j1p+#{eF9E2br$01SlNWjQS(7OmI0FQGoo z+X5oL0F6J2(&3fX{{>R2{+yee|2WJv0D)#e_M%bi0sOQ9=+sT7`Am7jK&f4`BJi8F z#qPIwn@f#jif@eUwtIVxF^_rGGH5U=tk%6~Ff!(!VlP~9>rj*0^#pt{$h=RLRF(=n zX;~2u(-*wkX=EP5DjjOZWAl4OBfULCLpH~1%Ztx9Rz;gj>OsU(-R&bc4|<` z-0&>zgK?z#u5H+hzDaB|oYu9szVTn9f82}{55MzObNJ!Np^29E{U@?DHEBLeY3{@Ho$ZppLElu$ zx}^XyjW|(biS`mvhwy4)j?$-Rt@Ei_Yg*WAlXeQ8X8oa@pAoou_(nT=!OI<-{yb`NNBCL$lndB8qdqU$R_n z*_JqAnm1|8xZlFfjsE(k-_A2bjxtG zJO{9jf)QvBONl@^3W0QgFhZX;HN(=Rg-3;Zwnl|FCB-ZEl@0#SG~iiLD@53mGnLPI zHRWr#(h}#ajV#rOX*1b4rQM98r0MxZw36lt&)n4x(giHET~yEm4E8}j#)-YFC~h6s ztqR*C6FSG#?k-$9&l>dWJNd~th4-l(X<+Ai#C++z6`5IJJ=_^b+oFTILP*@wC?8#{t&i3nn!PS;TyEsfn3xk)B!U#f z%22#4)NcXPAzM|KOya`;K?7xsR5beHCWKB=A)A0SO`PY_T+(Q2Dz8EBmA(#3Ij=Cy zd-aw`_jeoZ7(c;>P+JS$LHt0ZG86GOE-oo=om&)}l2p8rCdp$sIcwOW$ebrN+5E^U zRF`@$=%Z_w=C46TmigZxnt*o%|NG^`G#QP?cO6TzBRZURSF6-@R1Eu2ayl(eu9@(* zCMEtT5-Z}xPZIkkw?H$_Hk@ddyJ?V;ueX&HMptAV*G}8-$ZgV@g*=t zTIdPsI;V&&^raM^YDOK;!3YN)X6F~38XEXND09J?)1JgkGs?W)9Dp|NYe-xLtOFgV z!Us}6#Qrj2r|f`&2~(YuU*lgl0Sc-G@RcpvtT_jnh7T#@iBJ%-f4jP?FaD!I*#I~U#*R@26VA7B^Wpp*j6?ivgAQYzR>t-;9sn6RBiCXr znM?LGTvl4Ugl`E^K^xkmGx-QpINAktdq1=b7$zkuIcD3RKwg!Wl^o27>nA;t>=(M0>?YXsJb+@ym$RF4LBL zXQT*&!vHtRSvoG2hIhlOCT_3gT97KfoI zNR1B~+iAY;gIowid0ZJ$pM!c=7B!J{t#(@jzV$0t#CJAMQmiceBwuRBzx{8cd&Vq?CC%Su`=n@_x}^ zFA@`NBTl&{q)iMX?FLv0adU0W%-Hb|QC`BU;#oL8RbNIvsVmPgo@P2)YbvZs%ZM*g zI#E63nn@V)meWM_7e&RN?%7*@!azS6g{p=`1afRin_o(5^V7kZ8VhZuWmNwt7tt?& zu-D6|Kjxkr6Yr|nPoD1GaY+DF&Jk2rq9{??wir)iuY9xSwTWG|zq&Ys;J8(JNjvO&C|~gAGkVX(?X33{X7wef(eT=Yg3b1K++sdg%XQAFT^-7HBZpUqD@IO`RNk zGQ=`4v7OMM;nJ3ge0|Fs?O2q;mJd%E-8KXAEJY7^Xkx2q3LK8=PetE8pyKT^u<(iF z8yMhmk#}nsEc{3?U*y;&Xeep}M!QRePkJuC9+KW-s>pnX^d0!|8`SZtT7NfOQ5^n} zsx;^Q?xEJS)adrFeVZ3QU0Wa4EAW^K#k*;2Y!uAt-^64Ay;1QS04F*B@n5=RQ&>1; z>G(Hj>pjV$Q4=QtAoEI`GOdW?KhS~yGKPwQT5K>scY1DP z?nIl*kHQxi9dSP93k2wbFJc*hufpK?M*~4%R*jMDU$ZLH!&@5yswAeS2D~|S1fJ7aL4H#s3?5Fx`a%!c=X!u!daE3O z^+F8L1Qr{ej_ecO=d;a9HolSB2+qok<(>q_4 ztFIjL%H!8BPq%iG59#gts7pxN-r2nz#+*_IRYsSOaeNoEzpxexWYwEU{~HWm=xy!n z7s_v%*;RMKUaKnGo$qn8tbVmNrOejlr^XL?u+Fbh;|-!_kWy2|uUo`&l2o6;&xK9* z7L816!%1zRwKZW&=)KX#mT+=ubw|vq?qzu^o+}hKY9*&04sAl_S{Zb$z1z^t&Sl9W zLW{e<=)^GTSHA#mGXt6P|B;^2i}rsnIwj=xwaZd(y+m;IEnh#2jjE<=+Dc-B{P!HA zYzF@OPxYmfulKh51uUGwZP0hWSp-z`Dd)E?eVOek3IYZ}f4MO`idr?*8S>26>aHuK z?P5e6x8Lvz4|pj-mrRes-mvi}HH3mQk*y7rINV`+D*t^n4TaP5tf*r({3^P67-9vB zNU~GBF>QdN&JN2`RIPh#kCe;Fb98#2RPg> zvutsq$!rZBzFQsbcoQCB{!JlX`evhH)LYk^t-mHik`Ag-n4(k5bx37b80n5r*JEr* zCD8zIdAi!_+QBvAGNI)*e#5`yQR+28y8M*L>kHA+(oD~3C;FjALwD3I>c*Tueu=Vw zdU1A9FVfuT3WJo`U6HO(oo*#zO*AS#9$B^94!&wHAKn6)q-||x#Ti63a}Xb5JMyO- zDfTuh)e5F&zgON+QxvPEzgY8T+w%E#3B6#__7S>v03)+V8yCno9LVlNz7=>0Ya0z& z;P^U>snUMDhu5;pwQ~~Z8@YaAY@)@i`|5m9;PY?H*T7Xw>4jVJ4BXO7QuiTZ@OCGfA)ZzM&+>K#Y~2|U`&yHPWFf3w0t z(jjI1JSJM9Z*bt;%ezt69yMTW_vuz#$j*cZVNoc0^!!Iym3}x9C%)Jfb_Yo#-Ubd; z7J*WmZ?NPoc=j#=4!7Oc91|+(-%=>+d??zs@P$Rduuq&P(f1%sq-z9AZESJ#d4k!} z^-o$9qhA*tyrnBlH5i3JZ$DZTTrSmo)9(1_+(pWr5+<6aUUz4%)^p5y`k=$M%OfLX zv4!?@v)2>(sBSIOckWt}q*~uRO9mok3&%4z*LgjU1kIb36*7r%MO)P--~|I zxb)r%_LV^rl=tMqBj35W(f$79*{}1vagKQi&gk|M`$gKTy)uy=z_{K!JDi&Ig6HQ6 zhr|cbtZuI#sAlRV#F4|3;u#6ZA~l>Y-jd*rHEC&PAG5-Vu;-EX~3cI9q|^3u{#OEiq5tSvg8Wn*Jex?W4X!ngj$&Li?#G0GHv zi@Ws9v&cpmC85lWkiLkf^YKHn*f;Y7W15-DRbNx@4HIPzREG~59aXZm1`#y_qD$T9 zsi;-tPWP@}RJAGdIYSZ6SXwbxdgp-*WB#&^#pnQwJvpbW!5t?NXVR!YZ&6`7AshZY zuC$Ct<3(_zF7elX4_E%#wIqcju;((ILi@Raz=B*GU5;= zQ@=qIWhQ04(6Bk0kAoNDfdMzq-T2P3Jf9o~EqnXiHsxqf`Ar)<%>#!g8<-jvKC5@# zUKM%fl0PqKhfNXsvJ*?e2-;TsBq7Hu|dCa9* z2obv_*vhCP{V@ZX82uS)%ffZarAIZdN}YIK`H0;;G01Kq*B=zQ75lk*bFtifK()T( zVZ8Jjr=k*aGZ+V1&;owhnBSn!fwn~9nye`2` zJ%Bu83bMBjDG%*FK#4rHq{3qWEGN+e%k_*nKrnDr1;Yx!`jPF(R^ZrwdHz7daOw7O z#x3+LXVifoJWD;4mn^yN+R^8*7Ydt?zLc-~Ix_j|RGl(SwJPuGov>${H(8}M$QoCE z0d|CYmzK7^lqxsFA|Wet0|&}U;mvcsK%^<$-#@6xmA!{CjO?v6s|Sx#hqkG0JCt(+ ze3?j9M!Yw^lxC*TR--%jIAxPtKaN~XkMRvP=X0x9n|Hg*-f5K|I8M2jW?mGtuoL4k zvUK`9e;ZYx_$=zvT|L(GL6i>1u%~B01GcbBArnK?!v4TdDwNz;D<8gIJ#uh5T!?&W zDnkFxD#|Qs-N;)c^hpYb6^}@RJPbows#OGUzBJyk10;+$IQXI zMK)F#pQjtfX|9Cz&vljfw~%PZ5wz7MorT3W&(;oecoIClD1@Ac?D zjS{oBif&>PJkKw!sEZWS_|H7Z8jC6Dmhxcw2U=9@_iG5bQbwda8P8Ar4QgszJC+;( zO5&N7J>pL>K<6H!CP^sHx22Ex+QcnUV zqE&0_hHZvywW3{Lrc7GtugG+!rx;qXf-YZPTQ?R~A5GN1=c<-K0MFwS=6C7Me8!)S zRYRExnVY|ixS&R9f;XdvUEIm(O;nwoFG&XdxDl%L<>^XIselh^zR9mEW~a$>0mZzf zd}YMbP83tEk}H)C8135`wycV-R1c)!!mSzZuhieKj%;PZHwgM`m@o9iry<-=CD)r} z#)xWx2(!}l2HWWT%BIn(BFZWgt;R;iFo8Uqlu3=B?@AWco+azFimfQF71a>LnG=@M z=U9DU9ce#8EsN&z3JdMVO6yk4@i5W(V8Og1RxNpfj_(QR#qPhmDWX|_OQc{kGH}QgUdKRh{<+7so z!x*)F>|3^;Qp3#)SQcoTJRPbQ);4%FVrwP>ec^7E*u@qnu+1=gw_BJ>aXm-Gr zmi9v6Kp;2PlayST;jcgDR22Z%9e{8D(MkoALp zN{&NAH^KY#j=h0A4d7#Fi3_W}kmi{?e(>&z{j%NomjBI<#=pL%v+3j~SEN4lqzZi^ zk#=Gn6*y_u@jV`e;5t=US7yLbltt#@xXVj6nbSIE8+e=jVVQVR*ES19JM$n-97-9|8VQI;2<*}yJ@nVsA1ujSq>}268UJ!|M|7n&arS-?gZjJJ zg8NQpqX&G9{`TfaSDyLYti^o-A|JA}Uh*Yv&u_ zX3ul!|C(8^el6ft*o~ftoY0k?Ydmu%sU#u4ArG#bQus}He>;0DV$jaCID3wp560%u zU!3>xj<3FDc0hJt>-{yL+oujv>*Y~@HWjJtT#30vW~Az`%``pw!(-qB(O?N2TLWRZ zlfj{lT^3%L$QQjkTF0#+t1#T}n3? zsg?Q#fVee**8zvgN`O-e2H1t~BgmJ;dw@>EW*is+gq;lllVQg&H{Vpt?@}1aMV4ss zJ9^ADBrbOACDZCj)9Cth)m8ZI@=goY*#{H)7WWboOMae6hko41Og)Rr50bDM z&XMSCB>;l>*roS*papt-fsjsW8%Lj9_LRa4C2SuiXCc4e1`}9FA#nYQD&X(Hu-G}^ zn-Oc%Ou31EI@gXa?F6W0BW9*nKo<3WUOXg_8Pz$*;Ms_zUH2N`d}?NzNT*m#&$2?E z*nR*y0mjDk2&cfn8N)b24+mZHZiP;ye&fCZq0b$*c4mY7fttgiarm*p7-?+3J7j0+ zA-5NHg7-G)wtf&q1%W($j9?@Cb!B&I)THB6fHK>N6)7&l27*-@YIlYbnxW$bU(V z-0c>^g>YOJH~>Cp(Ag|CvK63wIZVmnyjSbyMX{Br+XDeKU)$bNSNeBS z3s8z?bZrZP05BP}g3$gA5}U(9HUNs+96&5noeAKBQvI*nEZBtAMP+FK_4QXMXM&IXD7Hsfm(`KRq?(8gZmD_TH-CLDzMH#7-Q1l_4Z69~>n(0!(_ zhVn2XLgqC8IBK@6_B(QByhvF=fuwNo2gqFEOQ{DWMgt&e5Yl+FC>hZI06oJuNQtN3 z{1P&1K#LZ8tyHb6nH-znzDwya3&M58<5Pl5zm1Kj%)WecTrQ)xf88p<&r_drwqX-H z7Y{I7P4+m2mN)j?7YM_(}Gf6%ktm_+aOFc zbNuU{_UQ=LJHa2LX_YO3FtlOHi5O*9q{5lb6grS}TG{V%QnuZN6*eVE+MX(Jk{HAG zzZtvTFy7efS9qsbWAiX>AxGxYrqP#0?O(jMFl(#44pGe7tJd$I_q1JXJPn^wUG3!?IY$Mm#zm8;Fj+Oh*rkQkZA>=c zwuenFixE{+U5qX&ihh5{78>GI&X}kx+`HE+6k0SY)XW=u2vtG{aVAj;I4!(L20(Q=}#YK z;Ar*D+|8mfM;rKlRV(`kQ;G9;U39o(?hYw>TE&*S9<5?K>j!$x8#bk-@)q0Akz?u)9a zodC4PK*-OZR0`o18W!~=dx`n_QHDO;E;^{OMnbspyzGw)uI5R1DO}j+h#^3C6$F@; z-e^3TmqH&?0c{)^uwSWqugq~A$d$vWlK;3jxBzM?!1H(yF#VtF$@>Q|rmsh$@?#$) zEN!|~0XevKfniLoh}+l;so2_YX^@~hCXuDZRdz8tS}xCeddyHFI(qIY+Z5g&x@Z-X z0sw0c`-9VB`X_`^s^3tABpgMbjgs^Z5OTQQpID%pdaax@qN5sMzt{4w5K8^YpCsvF z!i1M&@$GR#e{yF=|H)?$_XXXq7T_HEfdqgc*JY9OuoJ3MQXS1z(mfa8R);>gYIf%Q zjtKwRON|W$gs7D2|AL2;bpTW8kR(!l{3`rh!(R;h_K@Qe#D4d~16kNYc3%nZ52?KS zwNm9q0N+?4B$3RBzd`pmWc@Kj^pjHWj-POEbJkH&gq)+bZ=tsH4V4Qyrbe255*6<3 zjlM5sUkbba8dp_CG$<#aQp{xuDmco8{BRo_cSg3IIg_?~M>7>WEcBrFwD7>klRDsq zmT5Q7RQt8l`-%=*&Q72Q7@XPR<0l3oicr^2V!>Gx8@06tbgIsL z+bpShn*LszODt{oTdE8qRLGepS7Kyv#?vjn3_o70aCH>FHne`? z9v-K9xmb?;oUn1N=UiXQ6By5a)D#|yJDV*m-AoG%1?*0H3pV^zhCdGGWUh!D#-4vl z8m!J-^Q=ZsHvjz5dj}=_S*Vm3BIR!o)67M*B&=a~O|Z}oZQ(Y*^I=~ahJgW`CBrbS zQ|h<%7dAPf{jE>$gh@S&UbBe#mYIB*!6a7c7ptRne@*-~g!XWb%E34kUyEI838c7f z(sikO;kCJcDoyI`+FvEo?Jk%2f4Gl~4_4{u2%1d~NmP8%?@am)5=G8K#>%%WHGo+_ zG#0#No}xwCr$sFfK!7U5JGFQJVaH#`=K~)8A;Irikk8b{^^!E4fR4jy?nIZ#x|3uY zMffp9yJC#`QxK1;>(eOvJZGKBz6sJOc)#~B`}7%dKzyvcpcJxgDzirt8Q!W^NQX>j zlY9fKkPh+3D<@-8j7W?Ir zX-fQKHm2g_lH4sW)FSv<$8V6n{J@{joAk#);{Q0>9|wvE&}BI@-1_S^+5PpDrO-bP zq5Q|OlE@}V*AE}T4lRrSlgnWl^43wS>^%*9arnsg-=6ZT)bcInv}8jc-khQrlD7J~ z;m{VP|JBbq#Shri|FU?0zwpkiDpE%qQhc$G)Tmou34~CrrEaO=3jn<=ti)1B4KK!V zjARCz6;A(c@jrWeTWr~|I87f780V_O?+br=tmzV0)SsaEY`NY=+EJ%6b$T{rgeuT&&(H(QkO*bpA^ zVg^$`EvjPb*A%8ced@d;zD2r&bkIKQI74;<#S~^5g8a5a>L{DS$=DT(V>Hlp=rY3K zS)t4k3os_g4ykoHo0|szsy+?8iD3%;=i}8kNsA=(k{W&o+;|#%%8YhypUL`y{>Q^P zbJMVKq8(|b?Fi|Dv>3+_(yR1Y@PB>SzV~x;pic{T7vq?3cmR@2F`a%2C%yg|Yue$W zeE<6UOt=uPS&mr$lAUB*Zr~omik=mOo#k_W9hFm5EFm; zUmFuq&`&a(nrP@(*0--IP%8Npw;Ns+&$*7Gm7+`(HEGwct@SdxzoMCPL0n1Z;7XSD z^Zd`tabe9$!rKAqUenv_Wun-DPAHjA<03R#`Kq0Fzf1&?F(tmB^~q;}Ca8pB?fR(- z8SY2}v~NcHs>yrdHz*?Q4(S@UJyH7w%^@Zz`RB((Gvx)0jotoHQh)60+WRq4PBcy- zd6|9Nc3Dlp7+|P%2|^2})}~&<8@JVpm)AR}EWaRUpa;)YeIiGp+~a+9+@;e!q;s9l50pP*@af6$-86v0 zefk%RCA}F1(miJM;V9(b`m@hFfYRYQHSA;)bwXDnh)|D0Q!ANA?ZwBExN%2O%`98S zlx;N7Q*iq@%;uDD`~#k3-WxFsn|;WZ>Y=&yZB2F^zQ0Ri+rs02gR+u;gObzHBq^Bx z!w{>|&Oh-~f)Qe)y z-UD;xJYB}Hh@`fLVo9^+GEX;0w%2C7kIREF^v5;J^mXUzIoS#K0X_o*yjh^*Ch0jL z2{Q;JHh;kuxYtD}3&03^c$UPuU;X>AZy0B$s-Uyg`koM_Z!>lH3)MaXnxggFYGc;S zC09?L7MENlsl541J-`E0R3>dOCPm?SLe)TY;LYInlZqvVHp&!>Clckk$B*WA-wl3s zAN$G=Xw=?VL9pUy7speU?7H~_3^u*t^`C*~y}o zfvIyo@1f}ukL*U;I(&t8ihq8t4IG6cS2QR>s9=fgGixCSqBf_Ri53ebVyfvf@6y?P z`|Nzb&+A_Z|JgtrN2FgYdM`qhSmaVLtP54_iu&<^mV z$-LP693L6Ov#e?}+b-k0Q18Xi>WZIL{tC}xpHvi&rzUko=zU6HkWJCxm21Dd{Sb7v zm4!Zk2S^8V$LABa7NMcatUyL3ITn%0L$LKN-E^O_uknr)%gvvjYZKnK<~B`?w$i`U zVksvSH2!uITr-Z*EkKA6>~ZIf2{8@kp*O?brN5l;<9XnDdo=nxJ;L2pTZ@U%^J)x& zbRn@HBy4m?&L1^)BDn);h>EzdNbD)VY7AGQ7zlCd*~14Ld0>Z({G^^}dND(h#B&jS zARF>?>Nma`+r6lZ{8$%j9oxxfc;Ts1%OV=ZVWzP7@aw4?Kv#yPFFn9H?uL=Lj0m&6 zm|1YeZ3lg?Ex5a5UNL{PhLyK2{++9k^t~miLaYM5m2l?11PhU`-tB0FMhqd0!%aw2 z*mh>=gx-akip!2G7r?VOLE@3mE<6b2{q90`dh)s86CH&fE64@JxJhz*LD)Zq8<9G1 zkwz!uJL`9D;;s}l@a4U0(2hELN8P1XXWvvTS^IXK@!_oy#Kboa6hok7;1r4$2tBY< zB1gEvR|$M#kp)04`=!_-NryC=$hfC=S#&W*qb`s4vH{zZ$9Ey0J_|vxc#QB94t@SslJUDq#vdMVxT;$14Wyb9QaP4oDBX2A$%b|LLM1}P~s)sMmJSxRf^oIvcIHQ z@sK=brziR?zxyrDMZjt^9cjJGh7fFo(gUs)NmKnd*|qthh)KCFV$+?V$cvnaf{RL= z<5nLNzy7f6uZ4r3Z=!Hm^bSzbOIKAx2?W@Y+P>8OTxWcQxe&IgnFR}JYxK8of-OZ) zh!k6Wy*!rUGIj5W#lZarlRddkelM%F*mm|c8?=01GVZFm?VR;q4L9xgBO&3nA{fCK zNqyrh&bA%R!5@QAaCSoUnuycNJKWe1QdJl3PF1s%E5joDoa*Gd0g^Zxp^<3gTgz-j%K3J7Ov-hVK%g^w-`A9`lc zdmmqer5f2G$~Lp(Uf`Ij1U=Fqc#1WA2>z+lxgCM1rSH?BS_*=+Aw0g+W6h~H7Dds)oiII+^M~b1^};T`2)p%TPXjO)e>JlID#;ugaH{PC z(HQc`P&3A^MOJNUpsrm{KoO-LJnqyStqzI zD4*HGIo8iMR*`9m2HrC1d7yj^`&Ne9HG4C~ZOXjOD`nM(Cy}^o5grbxCLKX6KN`-~8t;iS;f%&3ZP~ zn~{aqnOCRnhGsu?(2s=p%v&+HUDQ}NdCoo=DKmE9sCBVh8{WeXgX=|bUj-B6fIO1~ zXU@(&yC)^tPFMKs&eM5C^uEa-Y^EcsG!e4r{his(?6q=4r^h8!8BC+A5=8Ut6qn!Y zFfAp#sd{;V?NXiWi@RVEA{zja_!7AY*O!2Svbi>Spx|+KYN9>+oMy#Rt3PCtV_YGx z#qoKH=S{QaZAZ`JNYO@qMc~HVBBjh`gpe9mX0SujH@W5#%sZTUGJnu${=6T+MND61 z(Furou&unQ{OyUyTG|2YZ_rDdVFXt;p{&#VV%-p`V^S%za^ciR-16(Ghj*&9zJ;6- zkN&G6vwIWi%g7nI7pb~j9u49c{zWvs+4_loJa%)_@!`(Yv!<_VjkmgJnv>kg8I;OX zW~>_|BS%ZRlDYRTp;Nm-3<%k?*k%TzFd-Qzu_I^cP`Y79ZRRXcD&t8lSI!!n7QWlZ zahJ{EkAG;0u7<3IFs%gA0c+rdpvF4KAH=g5Zjx>^{%n%_TvMClW4@)sux=cf)yJw$ zgH8bp_2hc1`yo2QnKtBUG2)9zX8V(iSXA)KYDZi1Op=5(bIsLl_zUu@4Q5p}g}f|~ z=8I#ybk;8!G;g_v+n&OGEcHiU#zim0KHR!Tw=qySgK>9#aWmVg_WEUdH6eA;>;#(L z<4rmV0p3gMpd_ucP-XfJa3y#Bslb%O$&!y2tnt+92n9V+=B?^oX)fVHgPCHCa&iK@}@O<;utem9qOX z7-}iJle$ryY%|TEZA(~P(Y>&PqS&ATy_@#KQGSoerudHS`3KR8lqWWKsh+fdD9j}d z>5n-V+nvOvdwUn&%=UH6DXwVcc$$DvbN}@2hJ-4sYIVXjvA$w`Hl2)&;BwHBcqr`3 z9Y_fHilQ90txb2@biii6(o;X3{%=^7vNn`Q9K7nixK8N^+yrZ*UK^?3q^lq zU!HJ22a0un6iLcl0~e3)#ySNrOwrt55UaE=btpp8)m5iZjhg@L0?3v3$+zymY@w9f zeyHjnMO(fmm%StO&*4u*AvPZ<>P&DP-NT-dfLq;|)wexyQ{O9HRR)~b56D_26hZLK z!tZc>RKS{TbZH@Fzb1npyVkm=WJSH+!rYkDwW6DT=`5nIu1z@hrca7F?2;|( z8yKWoFH2XH0E`gJX8Pd;83!IyV6;e z2HKHV3ANA>1luP9`!2K!)xjP!R_2bh7d_Cptj{9zUj0*jHQ&2$MM*b7{J|Y2!H@ew zb)-D}Mwx#2gzdIZI)~ddU=L$!%8T10E2!4s9KM`yxYBgE+8%zi{z5;%y1Z{RM?*B= zk5}d*m~=^+P|GQ*<{EB_o~yypH@>Ko{_E30N57qgPwu?hjC3G_odWN z3jnqL$GB$M#nIm&d(^A6D<%G)97w`pv!{+#`D!U!Wki*ZWVdwdyi8t-hLBKyTYGY-{2vIwWz|t;1@Os-~pZxn^2wEGqd3jMbrm8=ieozKYNU zyl%HW!C;~e?i|5Ql-VeUPQ@d!Nms)97+<)jj!)LuH4n!2;=f}70ZY?$oNy-^j6mkV zHfF)N+_~_or5yY5LCxYI)?&o_>kI=fa=h)OAI~8=brP15l*svvSxJKTsaY@1)?ob3 zR9R>PcS#AnnR75J#jCywJ;osWgJ4V%$tRYe32`d?mIq`sW+;69TZ)#XO_I-9)Y(}2KU_Sx`-U3&XK z(Zt2x4whOxGvA%9VV-IG1XZb@KE#am8*z5im7t3+U;CB?69KU_`81(+iT1U9o{!gD zYbGTjrdiG4Q0^AN_SafD)K*i3ViEh;E9fP;6Y9N3)PH(}(Yn}n{# zjJQHenKtJuK2XD?2g4zW>EEm2CG5f+h077`H_qvB#+hpNqr`>ZsDn=Z7o35n>{J+G ziOWRIgU=Jb=8Z`it|ShM6_*w-y=$v$;7#g`FcnIf%2aEvL@A~eys;X z!0@87wpW0NedpS#-=4`!kk>z~nbUuYqy5J6)3i;f5lB11uouE2j7NN|G z9YN6qQf{UCttNQpc6p?YW%C|E;OaY1Rrj)WuN}A6w`SBQg@L$pmv#xlYTKxVfy)jJ z`L7R6%9!EO0wotd)OdTr?3Mi<^zf(6S1_jWIBdWM{rhXYDQSA<@t5$XWx(~r@;L2ytpiyFZW%bg zb!5(hGl;YpKGYJ;^q{%Ct=p%X;Hy6ISm)LJQQ4=~n;S*kX5PD!69xat)&-L!ik*EG z;ZMF3AIzFgxWe=flMRw zqc5#DM4MiXfOl%-^tndn;}$EoR%HLqKGpq&eFBK7m4Tc;sRRBl;T%(XX%E>OC!Ifo z|2;x|72pJS_KpMXe*G;8s-UlVpzqj}U$?ti4%sa_2DFfXHdxc5IBJ{#pi8{9CIDaV zd?pxGAsiR3>+tm);E5AVSFn=Q6NApzOe_Ra5kG^C*E&XA@&$SFsWct~3;jMMg*Q_p zCo75&Ht_!t_ukQPwSV6z(YuHeb)to+AxeS}(IX;yH_;72L>qOYcY+`xh+cX5Df&Yz*4iZRw zFJomkUB-q2rNCd9=hN@xN2hHU!~g~3FU&Li4a1(@GQsJ?YVgh2Qggax2fZH~t#v7S z3(2m$d{?~}6AWnM%fmv5Mh+x6uXHT#B|vZM@dA*-C;!7x;(vapQFC070Vqkz;?a2~ zBxv#tLD+Mi`K0aM3-U{9Q01hWcD|g@S&ZkzWq$SlqY~~EfLpud%>RE-!u`)+>VNds z|6e=p7iMQ=4WaEBqM<<#e?Etx=DVbP5Z_9K`U`ehYk|k)!`r9b9-DuypWT6aCK*Gq z`Ow5?jU&xUR&Hew#AvNFBSMD5nYvzOz-7jyUuA9 zT^^WI3zwrQT-=#+Y|R*3)}7?bUUxbl^A%UMPh+N&6MR70RrrIb2K>bo5fLC=wWE>i z+^AKQU(_?wIJeNwHX>;DtyzfsjsERLgZFD2cW#CdS!0%0t2&3H)1)o|W;zw5^=@r# z%3y@B>XcwX!gHIqWCr!g4|%-UI0TFLq;ailnY&ZC){~QvUsJH?w^%WZze2Q^*)pjL z`c_w?RzyA(wqs3aRN`9T*Z|1cBjb(r({Qq*wn!qQY1%ATpc6)7#Nb%lu^^E70@OkE z+gK3C?81_wT(bGjoW&Wuq&HAbd|+sGEy9Gn+HEoM<17B&9eoa3R91zboMEHzhkL6F zSz@|#yo|DWjx@9Hzzdsvjza?haYngZg*hEd%#GhCjzm0T9~Do**J|5<+0mg15%n;E zc?MW02*0_g{bZdd*n9*wF`Cx~ICPU)h-n;AVvO7^)ZQwrvu&QFv%ZaLv27enQ8DNV zFEw`}iad+>$o1hm5Ay62G1Ay(py!49&z|ejTB0#IyK=xoEVU6j{bP|@}k(sX?Sjy`}%c-DXs|vALHOLwb14deH%B!C?k7BQ%l&>L_lNAu{LjM+YLqU0_0tlJ5d@N4xLGEL(nXSlHwuh= z8223P*yuvHRK4w$7jiY&Swk&bkThW+GOP)bRL%&QL+m)$Q|EFsM7F=5!uODoi*$x3 ziMf8|J@Fg-hr7-OQE@KQHqsFvQg+%l15zP{Q1BYKr|qUAn59mm05RIEkPCM7vvx9K z@f0T72U4U;%H}o6l6Bq`i9X=_rEl&coPl;@fXa5a(YNvhXrj8)ii-wG!h|LI!ITTT zLBf*~SMdVfwcACZhKMVP2k?H42M-<(e5-k&YUB2SeL0Wg4u%!w(4Fxj@e3yZ$D9bf z7#hSA`U257zLFuU{*uUe)#&L>JUkb3O8j01(U>6e01k8`#2wSy&LUEu!RAaAvIIFh zi8a>8`RY(j^o0 z$&J0Rf@K5QORs+O=F{GHWnb{*KkU|^^l*x;!0Ph#^avNqt`!&w#LNF0Raj@H!BPM| zZIb1Hg$p(mK%s+S+p0BSf>Us5J|_KiX0qbIa9U%cqHxsf`>V#9i7`!xa3zDKY*-R& zfEMfeLtCl_^*fbs#WF^#qHto+O!HAWCA47gr9rJvD<>wf2twsLfW@}xGZYmA$o9rbXC=B41e&vou; z6*ZP}vhF~y*N>y2La}U?x9%*{zj)akX1%b>Xy~zUKisOuIZCT5s@SRHwz4f@n%)t( zW-H!HfevHThjxn*KD`dwbZ*+_HW3OM%aFCubhF_pef8Wd`(dcM{(D}LHj%{`{7H-( zkYEc0@Pwa-VX0QHNX8Ews%taGwdzzuhBh^LGnV+2e<|@K{~Ts{Uziome79k*Z8qo3 z;imDzQh+e(v%8~X&upejwQ^me|Fd}o&l@7=zN9ZXJ}LS%-*cprH169XF(;M)dO8MIMC%#QrWB;CzIfsvnTX`^ZOu~uJbDl=Ew+P6@iAnKeS z85B_6DYsgc0(Oy!9rWP$wvTD8;15*|v91)KlRc81w9HodI)rtaRs1V450skZ`PEhH zc!#o_IVW_di9z)>JppLO5xv0$CW71D0iUiccIK9f*8*9um^!6!0x8-kShSm5bd`v( zeVy3ij^zU(;S>k8VrjfHiYD^vXEFP6;5KBxqSg^&rJBov~+$jX)yOwXPQN~Fcc8EL`VIfasMt1{d5 z8TKe}wmw{0kVDj5$gX|>^g)|)$_w0Il`d0M-m2Est359PdqZJZ&Lv=Ci%14stb)%J zFi9XXn0;Vz01SN&Fb5R+XPX89QoxDpJfhyCJHVj`H?$;)`fN#!&WVy^ErrJIOtDO* zlt4^HzR%g`zfL#px(tVRi7Wa#Q=%K?d83O7?Zxr=e*|UgJd?~I(|L|LYHuSu`n}8) zz&-sNM5Mi{1$vU${lJOQCnL<~T*`-~M%BjG{=vYB#+&xV7`aSM2K!TV)f~lYac@pk zI*3kA)_t|btt&PNjfmi_nSM21%j$nSFM3WkQ_+Jy#o|-i6FE#_e5?qIgl^~Wq8Rsz z@$WKZNdBwaZak|3ZBy%ohB+hbagK^zZ*+4)u#rQz5c)HDv~><~U`51z%G)a>I^ z#?4eskZ+u}5o2IordyHCYUO61+_1tPl1tgEv&wqrW||OAfdb+IJ(<;Df=6ucAbRC4 zx3``hp3AeNK_Lo`RJvEdYR2RVqFIK%UF%`V4tDX+-8nyVcdlB!<`PW(G`0QACBHdC zW12k0&PuDC-=mjz70|6LGf61WIknN&YU6`@MG}!MvR!lD>E+JuPE4lZncGJN79Hm) z=0idA%maIyeH)bqbcXB-TH9p?%hs0cKJt8+rqvu!fENl8iPepAExPIx9wh8|W(h*a zXiDWc__80R(np9&uBkmq=-ixB4$CS85}|i~|ILI4L*BQYdF>7-0WKy9*Ed5~+bEzO z?U(wdeBre-66LpB_odKL(~tXl4Ij^}XKx}(@>)XsWU43uzpP;_!R54pc~t~#V+)6W z?Oawx!iqKYGlm5dLEWNo)N^}FLQ@Wn#%^-LYy2)l2pgW{c5(2|YEU=KL5|4s(S#a{ z7-dBfzg_g`8khFlyauhr)K&r9P%KiL9MZ@ab|hLQ-|G*NoUDfO#cVpCOJR>jDo&bus0#$5T(5jF1RyXRp&3`ee_cWP^5AO-dH@kOLO zj%n6aZ>%(U@s&1g;zaq-u}E;28yTi(Ss5ka$6pWlAeSO3W+gpjA`-RI7Ue#!M~8H8 zl4XiFet%9-9iie2M;y?gWerAv_}ms*%`q2GelH8Ar(*||-5ra8<>oAI=^lanuacBp zr`P42nSEyPZ28_(_pT=H7Xr3VfGjoi}qL>s)ld3Q6EVNi*_#YP8b=rT)7t0_d9!76=pK%5q&li z70?u1CgQAQ?Y}9z+L<>(qF90JZ>4KNlSEc}?zQMnYgebg{61lC;cuvAc~Gu; zh7ZqK81mm>fYiTZBDiyNI}LP0{`L+_eNOqd>FY}+$W;B5ri&HK*TF`zCBxTy$HRfJ z&+RRjc2dCh@X}>f~h%$3*Xa;qvoP} zVw&-rvj&XDGp@2I6PtV0f#@ydVf14}ge0pQ^|JHaLJ&vO*YDq))2bup&DzYEG}^s= z#2f;2%LRrA0+RM0;hi}v%+9aIN5nG*+i}3DQVYAJrPLb_%UHFc+-bL`x^a_@V`B7U zDjPp^p1XVv$$heOYh|lbfAY65)X}{@cQy0cNPoNt!fTIco?1^cyCB}W6P@kg0#DVe z{bCV~$U=d;4qW$Eapg!56Qt+F5QQr)ff(s**PlE`(Aas72#q{>o?O-#?)`MIW|Q?J zRc|gv8qLru7$6BeHHkdqBA(G+{(@%FcfN-sJBM#P>k++w18s*&jJr>d@7xX}$Fid? z&(2Od+?VFm{LHVDPFef*@0@@J++7?bhTU8#lHDmG(*y~Eqk#H_{J4$Hu@M$6dk9(c14&bz7S~*GGKmasEvgb56hP zG5E$JF;<>FsB4)zfMI<%Tgnad>{P$=b*i_C>e9&i#mAjbWF(dCU|R{=dE-oH$0`22 zL~Aa*va)F%uY=o%KaZWU8{wVi#$-FB?Df(4|x9!{vZH?JGdezYbtZ`$G zDw?JfcGJQH44#9?bPuE_78_fDn>9sJ{mC0b#vT=t+9nx2yu--+crP7wbiiJ;C(StJ z7hhm1H^*K$IUGkdfJszLUYuLBvY)@|$@cONk9vvX*2JpQd z9LjxtCxkd!xl$*fWCLOlf$!KMn|0*}Fi@OZxlqGllI%X6G8V1XCB|Lj6#kh--@?-* zg*FO}i>=;~;i-0IKirjQ=7qOK16x#Rf_fND*{qqx$Myx{7$V&Iss+MTp>XqYATKRpvYg*i;O$$#w zNKLCj@_eto3QX+|`__@6n&mpg*_d$e=|#0ni2e=zHLgma92wd}zJR0luEhH_6R+-S zUO&)*ETMkxadogDM|G)6Dre^qM4y3ZGD+B~TeO@ul9kmm9ooKSFvm~hS$QKU_+Q7-Zie6zW8EEPj7(N?xmQ`Q!5^Cu(24b9 z_vq}nSDOI)i}U&UFU}|7bYEMY_CZy7P`_#1_?`l}WDBfgMD4YiWqk&Jh4M5{Ftvro z5^3)m*u*jC_*Nv22$)hbE{t&G!YDVSS}$xiT@T}rDptoWpox0&tz^ss^C({T5;hgM ziEpas-)4`sJu4julH4|AT9p|l3Yw9pO6gd$#9Ud+lY%YGhuIUdkpA;f5jU5E)dZu4 zFuJCEVlCh!r}VmGlnVirko)r$n8X*Th!nJJCn960YJ)=4xK7X~&Hgh19Y1xD52aM` z(xcmK)BOOusd#@7sT~ih?cKjdYUy=IE%BmA!mKBzySNTDjSzAD}#_fk(hnq z&4KEoDf0NMFAu3x&YX3wi(w8Hpe{P7o<1ghbm>@%yr1 z!XO|j0tgvy$7@fr|l+Z zc8&x);Mv}@vwFdlMV>Yl(m|(OR<}D;u{;FOT|7TTi zzZ(Xy#A$%pf!U$f^X)A5pVp=@!BP!2PRBFlyGtD5T*t3jc1gSv7*jk7#MNUe-@R`j zt`2ayx{VuaqibeBFZakWb@Yoyrh{&RJHJ9K$*U(kk7Fbn@*s!V`i{bSVLk)`1GcdA zha&iw7?|_$tcwe7Y8fyzz+p>x`I8vHRE(H+(E@iT@GFJ8#wqnGz(oqexVv79YHur?JN z_C5+A2bgKu#J0LDG2S_>VpJD9|c$;;djm8dM}T$JB+)~PG6l0&Ex#=+sXvNM__Ht-y*LZ0JD=S1u#3$ z&soE%ZL6^W*<|<<515{UrxmboTkSCxS46u^$whE9Sm%nW)rU%^FLXc^N;mvV^!t-p zP#0BDu8zgC{KHo}mA#;qsz@9q#;YKnsonHBi$N7pnC8h(HT;728;dP7DJtF!z0<$k zMX^m6xX5wT`TRvtA^VFVEj6vCab!bU-=TFfZ}yEmW6e?>9=lMHjUl5uaS4h$U=WrY z16XwS`eoNozojyT;hFZ?3caQ@-0DJ5NxZKtzqRl>UfB3aAFYX$?-Ep~pY8dw&_b7@8zqPSdwCsocoE*rQ5@{ku}x#=Vs7vD8_?E?vs^No+d(U-o{SlEgvzWYUO`D*et|J~h zLuOa5&tJK3aHk;dVEb0xVsq%cd?O={P7MJFG%BMtr2^`t$RcQl@xvh@_6QxsCe-ta zDd|%%=OO;keUhnIz^)jPL$QX@Kzb-dc^ZzTs5d&#W>t!;&_-Dlej;!CxMJJ*zP*8v z&0toZ9V!5XocnhR7j$2ju4q*Wl;Z(PaezHLJl6t}JTfRi<$7gh| zJK2ip^j@Qk-gY-uz%;%p$_qrZ%W>;lYcnJw+sc=xwmwZIk|n;HSn5q-w&V~o!^G!l zB{bg)+%WpQbD4H#c~|P3>2l@k_lU=;2d_5}xZ##`=h^6>fnGmBS25RL3D7DNG+$&b zj0x(mhpLKl!A%$LF^-!oDz)UF+{vPRdv{%+zd?gpmvmpTN&%e{+3bweW`(Mn$!f_f z&_MllSw2kbS`LV^xAu9tZ19%UiLH6=`eX+GP!N5dl+2blYzmL(!Tlg% z(=qt`BT$9kb+`X-!KKT5+IAzamPaOk75n2#U@g~F?wg?Yr1^9hhkP;7nl=jtyt*9W z7GSj|tSB+ar)?lUu$r0vDypoELbi#vB!=PvEgny>W#Gzk0*iE<*AxR zbYMT}>71zv33F~vlqfZxcjOT&yuF5ZE7%ftrE4+g7`hr67obdn0UW;#WE0VKVJ=k=<1#H|qx$S%`K8l6h$FN?MkiZ$)8oLaqN1 zMx6^cH$gh7RTszfGBe`A;RSDB2LsWI4st7}MM8wFkdnXX-l4)X{;IxsQ!tZB)`OMS zl%V*PCRmi|X5#wpT=zzt`274#H$VnV-n|L${t?wDlu7#sui|)&>y7VDVn^aF(>*YC zD-*Q5>&Cp|WPn>~t&|KS!XNtD^Y_TzY%R$udt*K_o~ZRA0-m?4#%#2>%EszIyWeWN zR16oH=+2Hdn%`H;bXa-R-DsI*3{9tIklQH@!}5-yACC|5raJF8708lVqL|627{c2L zQtt`sTi;J`p^dtRXSp@5m||`{L6bybWefVR%jJ%4ux3WB_|Qnat_)d?j{3&F7GxwG z{BnCcYmmXY9$tOQz;K}nV+!M~ACspy-%htAYN=~?ju(})TB{R4KdJC7A1zXz zXR;^Wk7QlF0Wo@z3YqiZ?Kh2$oTpe+&8%+#1pFYQscD*u?ZtXro6>LjS|No*6t3== zWPb;B)U7~+)k1C`iAa>Q6TFPn&X`vom&_crdwmECy8E5RmtLE0p(_3Ook50pC)?KE z70nt}0q(gmTF-S4X3Ey^A+uAX?%I3=;G*m$CjKWE<$tHi{9YFDeE0uIl=&6`LZd~m z2C=&=8EZIs-amN0ZCOfS67X7j>A7bR=_L`pQ7Yi{4===uBgR}{HI=7-@Mxh4>$5vD zD({rMd}VTzeu|5$vFY3q6{>8%>G%0PHAFg3xXEc)Kd;%pefg%GbIIb;JXReg+#4bc z7j7LxoH$7tc?;!+)VlEKk|aE#-k0#dPYp^4q?_)RXKo!MiF#el$b>mPrYH1<4 z9gi;JUO%nO>BBv(?%aEKT}RE6(C5KK;ZtP+YDKYv%mJCvxLKN1%3=&p;JiUgG;y65 z_$CzgbX>Kj(#gBgJKGzH+_a4VWu{)Qy>C9-$}qHPl;W=p0_=!e8OGpKNBUE*D^{RX zV||ic?zspe{a?%<32uwz`#k@4^0R0j)7IhR_t})U5@92iFZUFBki2>K6Y|w<_3DTP z{SeYuVxbvA9oyR_c`-`lOMmrO7u%K;ei~A_L15^^5>vk1=OYZwBzyY5 z3=Nx}A+e8uJu^@pnGc^Z%o#N#;y6!c+`=wS{(@GG^8ieg{14uao*_vW_=0bV4|r{H zgp2Z9M#Hda{B8R;+Aj4cgV9VljdMWIw9n)Zs0}&t(mQTp60QGB)X@px%kjS^B30_W z`O5<7&(wcpg#MrNSNQW}*DM0-I-l)6{_uD42)+t^PqL&} z{72$|1HxnX=^O7rMxI9(q`+D=t^XHwNVmMv2OA~~+be@@Kdmi9a|vLDPW^yOk6>*6 zyUm8}fK4Rj|JX$4vP@PwbWX=uJ4-*b<4s@SsJkEQx#1={Q7Ws!F6n+586x3-#0<%n zQ_C1P8n;TD%qAg4cz+8C8h%@FlZz*EFfpHd%bCcR;fh?4KT!@{iG*(h5v9p zc*J2|VwWGU0;qI6l+lK%@{veZm6orK_;Yiop}0 z_?V5HGv@wuu%v8fVl!t!cAK)PQ$$UtL4Ek88pC6H{9l*{?Q?wZunHuR5)3InqYKhB z9Nzao?(RCY%kW)y`?Qg!>frrY<1sPbZb{y|N8nqqegu~0(n!!uW&^osu^+d=#pd*egH= z3C$@z_jN;YZp+7pAyl+K$UyKD)Znp7))7KF63vI|D0W_|v- z<5=n3u_Qby=V0YthVe7}UV~_As5yxdFG!wKANge?MEsjhkl*VvZ*3wsS!bv;1Fr+^Ai8g*Ui+BEkzaU-6hV^-&&$Cr$i5vTxy$qT`NgBW0df$ z4}ynTwUJ^bOJry{oH!7n9L+Z-QY#kFYHemI*)+iIs*|}tHh6pC`@`j=k#~+?!MT&8 zCVoq$9Fh4;d*bbqVppRW=>%UgG~Ng(!>^m2upy448%v}>0opqepvNNBco z*u6)Y9fP8PCDu>N2v^1Ap}gz(fK`08I#O3{{5h|yh)r$8N{^c|@*dB71`eGRw}GDz z8IDe02)jN@_GdBu+d`>=T@)wJ3M5E%yBW=`D;(}k=5PY~WA@8Cz_T(d7h3jj7D_!( z?^T;d=!FoVx|(ctZHAYSFFZ4q19vg_O7aW7p%#a=BI05@S0oj5FIyX@@uoxLdc84S9lHT zMv>Rmvr3-&;Tu=(61BmTZK43)LI{{njvcU*4e~!Q>R!4#aVqN~5a{rtA<*i!<>KRS z<_rB^gj#kiW|b$x;nS(iPxcFKc@Uqrj^Xd3;&BWb;1wk=~6EU8TlefyaCi23)mlrx2* z>vR#H&;1{Lbwy&_H7-Okg13%C!JHUB81vksW9eEI9cJq4M@qb^CUY%Z5FBwSdp(8I zYB~BuvHMoJd`ph*d8=lcZBnM~lO0DK6*^B*G$eqp1e32k0f}%G;>E z^-j80V}!}XyoBA{n5x)=dmp;KVfV|P$WPT{Tu{fumg(Jw*|*0zryP>*`cKq^yP6uW z`rCT&Tg<01bKIF7>aiUfQ_({mb%4XOZz8_ep{f9q4hL&_iJQHqCIysHv)p@`a^NPO zxbi|i$II(6L7?YN@0?TX7F!#Ct0$Y+!oS^AzRk;v=q$$yQnFyN^KE9X)6L~$ZJqP5 zfPcIH{ZxF7Tl;y>bKB2zqJ8A=*Ng?R%wx(8(3Gug{`b_PM6uFV{v3twrSN8ut+?4t zFYiV(T|-uuj_NF-P6N669gqrC$p|G?Q{1u@T=`nWMYJCL^YwG+`{gfL4sWuy4C#oi z(n)+C!ChodoWoKi@NqSqi_%>IYQ~(~(lT_<$ ziwL?sCHEk2&&XqY4is5yH*yHyR9S}Qw%-^)%Y;y67rehNto~@_95U0+Fa`}7MjD2e zS^&Zp)8e?wW+oSrLZ|dOl{)NY_`z=$`y}?zXJ=v>9%sI02Sd+jc(;h`ULP3ZU2OtZ zuTCKH9Jc<_CyjVDxDn~@-lQ`nQ0A7~PL0E0&I@O!xy`w=Il=x%y8gbSwh8Jp;xhMt zefzo+LaoSl6P%etR1qX;g4t?s6pcB3?9h3ZVUQ5Ykd}3wUfN$gSXdP8ig>x8K^GXo z9DbC|UKumYnkTTzOmGdkk`oexGQF%Dn-2A~*{*g?nkTDOO{x)75YZ+{#|WJ)&O)n<`~~|3 z1NFL?5K{etkjHVu6gvjG$bfVu>PBhWusT&tHE&O;#tW&Ys*fC5dfzx=atp z-5Equd^*5tA{X^KPqv4?W`}z^BJ%44zHVHblHJbK4v0>-5a0dEihE@>r8Lv}KaxRO90G+-7(| zLsLf2(%JFd80V7xupM&EJJvkOoNNiqxHlGkb-XU>?mi=@z8c1hkuS-rBAeOKy}dF= zouZ*kOc|KwHuc^7a`SeldPKY38aeu*kwdz)%a|Pyl2Q4tlfx zcnyizheEh7^Bv6+q8{m!u!57Jv8i=&dUUHHf!JrdCrLd1+Udi!M$NQ$R?R> z^4R1C?S~1M=;PTKM$hLfw3Wp?p7OHeZQok&VINIPTwSX&*JW8Fe;wkNEN0$w0fP1J z8c3eGv(BgT26oC{BIRx1}#D8Z|46*dTU!@DG zPX7TwG55>!|KPc$z|aOOK@YE^HYRbLosbo-45qNLG498MU2qT1?;=-S?r95MBE!uF zfz)pWE0c2r-A*3u%G8fsiLN4g0J7dP!xz2P#|A9tu3O)7&W#`m4RJXisrSRvms(`b zuV4Pb^S@+4i-zaaBzB61-w+(+>bz1iRvgOpjlN6LmUf>}{tw<8f&?7$Q#TKZXy@$%DjscF*DKKdAT_S;sesX)AJ2n}&_XXi3Ljtu$? zd3@B#fj{C|T1Q$CvU*TE@0ek1$7&lL^JT#Gq3u7tf9jv`vAYsdHH?yYJGsw2i6l6MD%U+0FI zEoj}0(8!<5f1P-X-U0N0Q$T}+VR2OL!QAREM0E!=W!0w>e0$HEg9q&v?g@7`9774a z9=*=}o{dNLiaS|F=!@7-Jd`iniQzEt{^S52mmMu`)R4hd4^Zm$hpB2-kf`@{j)Q>B z9P1{5EB?BXl?vPN_qUb30}40W?3W4mTG>%W zXm!ea%o;p*m9N&`KawLq?WYNAqws7aH4ji2Z{{p8gW4b64HTEX%{XMO&RY<6x7S*q z?JM6MHne59inOklDN;W#Yv1=U7?rZ>5N?wUqQoevkL9Ng>>LZj<7lIWW@A6HaZv#j zVe8^M$=bS3RS~TeSWc8nT4@nRyWLbO2?EcJxfC=b<N6-E0w$ zF+ci#!DJJGQtK3rRG<<*gv)b4f#8=3>58g1ja~(YdG_W9;=WEz_3H;i?kRCb1v4-Z z5IXdqUCQM&DfCUZ;bS@MByVK0B{)MKiV40l3=jhhaP|O0PG|(X$|;rXuaoDr+`U)Z z$p&*hDtsI6*)r3tfLHAx3XBUpb;A-T0&9-Z$lOtfc7#0Nq{FnF(rTcB&V-2fMa{5l zBKQ8w*oLUSjuL_yLp3bFTgV^0-#j}C7%~vXXhBsUUgpqQC%Zii^tdB7F`|F){%+{PQtQ) z4jDc-u$4Li#e%;bg*4l&>W|7%pco`FGWm_ubfnTD)WAixYYB_$U0{uSD_D z6iMCrYy(uy*#-&+U*7@KSHP+d6POOB%EnBqPoWpd3Z2kP@~fd=XX83Gp)bFtI@C9) zBtN3vu()kY8%SD}-O3o$pF`1l`$Brp;ku!sH}q_NgIXsNns=3SGP3d&cNz#Xo_^!D zpfaY5Xtw{SeO_z8KNWbsUh;Q+I&B31s#k6Qs#i&k@GWqF$op>(_m}F%-nkdq{GB{bTtC*jnzPj(n~X^w4xR* z&%P_Q1o}SG%EOyA^oe)CK`0}{%tFH%KiexwnoCV+^ryjRkBFaDvr#TCaO8bO zay8~51AU^cDuM(^AEDU6@tXcj6B8b#=$GFdleL2UqS#}c&}lX+z-uaCq(3S+m_ zm1KkKOtgO$_^Nde(_tm*CnYCGYk>_l<^~W6^>DnoiL`e74<4CNpIzxZ^Qly$3746s z)Vt>3IB`|04&NAcf-?hse)4?4{pvtRvYC45h^0oo>GpdvyR8lR{FH9VsHuHzYPjvQ zipt!P2t#JVx1U-ukt`|s!txRa2;|4 z`>h1XS^*rKR!Ich zTZ(ZI=ok$RY%;m`Wn0I>iD`6as?Vc5%xqSfpJQ7!+mtMm`Mp3uzW1AlY({;0If6~{ z9R+NuNyE!f=ci~;uxsrIru=OiY4m?)7=kBC?@)O^Gf{ytK{Hfdt55Gk4CmE>ydROfrGyp`nx~+=RZ##4v zO=-9lX_lyz4ih!IcOjT=np3olS&{V*SMM%-9?O^{Yu_He_19p83--!vrmj$t zF7n08DZ2g?6+Wt5(c;#K9?l6uD+#EM-GhlN$mEFIn{Pf`pFi-EOv}yRHZ6`Uq|K66 zi;>lOG_`A1UR)nDCYITgs(8z75v$!G)!;JlB(xhwDt`-lq_5@C%Rvr^tV(+6=HWy6 zMe`OzU-KUbS!?9mlQMq{AHwHZOEGH%hX#nQ?y=6(P(q|KBz$&b`D+jfL^kwfE;sGs z_~p&T3Y@p2%I@RQf1Vb2^5r5^j&DVu1=M*2Xw|6zf25U9tT;L?Zq2mIHTAmM2#HVd zS5)qPrs^jBt~}qOZ->8*TLCfFV!F|Wz3nnf@Rc127n#oX)?4XaV{;28=H{6VbXR(Y z2#uhr2zu!Lk0s@BlW+JS;Xr>>emjm2MH5mBhzJr*YNp1OYwH2U)L4fm!MbTzwP?mS z3kx?71n-A0fAH)Z=}~GSYqd>Z6Q7JvP2nbH7P^G3Zw@*RajW~RV|F`s&-%EeOzT?fJ8rKf9!Q_Pk9w8nP1cejsowFvy_$vd?){f% z$#bT|LQJDREWd zB9x-Tv}9b=GuY3?b}~~RVmRl!X&3h?ufHw%c~aC!xL7(2;nMtIwdt|imF2ibZOE19 z!C6>{WTw}s(xWAMDLXM$+ea7mBKrrod%vSTo2sVrfT`iNZ8T2K&dxT3N5vN-Y7qN< ztKi%aGegHb6W*J5QVqp7-fe_}>kY@BvNHv~U_JAyM|{IP&NZ3sdT%ygx9{G|60WS= z4CIt1;NiW(|G{u1^Di)}d21CBdMHP<0+;PT`1F@*J8agblaV1bI3SjWf;W?OW7F^4 z*mqx;&W9`?)7Al|2Bko733=F&?p}kIX;zNSBp_J2;znx!Hz#FmlpL^WKR>01l6zv8MN0DYUVRE4dDKX}XFYbS+OUhRu>h4bk@ zc%}^k{FkZn?WfUMZde}Rf0f_DT>=5LI>6E;02^-jgV)-2IoYS9Hc@&;Q}KKc_HU;q z{_}q1fj<>!?O+0&DgO7FS-zDP7WWeFb1F@EccOzv;4F4BO z_W#UqupKy{7v)kN7r)2Jg#R)4Top;It(Z(w$^id2h1cJRlF46)5@7w1Lk3-2m5z}d zPW0PMBwR*)nm1qAyL_!@rtB%^%&O(Q{`|1|C%aL9i$L$dce_vWDo&?Iu|Qg5kWc{8 zWZp>ae7W{bFa)q6qLqag9%PrZStEzf!#^lV=n+x+yrWi>)u{5$YhYLN&w7?omnb=M zN=4C*yE7U@1@%x*reI}fsN_thgS$b9Dw51PDcht@AwFVJNs-3|?Yu0_&Ods4FC&3z z895x4Lv{MoOUuqxNZ8(NkP|L(&Bfkxn+saU{f4LE6;Fmr)Ga}-WbW|WfnXJ0S*jlw zCq4Chkk!QSsZtyHk6-uv#3?jOTSwhp8JRfrYuwTYlH~UkK3+xfc{tqN>T1KsOq=^V zXUPJt04}O6t5@CQ9J1Fk~)2*LvSVzx0t9Px36CN<^S#qJ;B7oF`EY|Ku zm259v443 zpzy`R!~c>0nN1{s6&^I05r$(h`ik;OLK7DTuGy6K$0|w=R+dRJeKjc*zUuZh9Zl7c zHz7B^+nHF5V_n$Bu{0*G-i=;89kUsc$P{eI9(!o>P2(`*3Cbl5TVqEVe~fKMIDF0l z=Y1}d{+_QToERTq2GD~S59856oJeM`Q6yYM(?xzTwh+<8TC9Isb(98x+qW=1QQ!#pA~kIa)s7 zsvMKvc^L$U72fxkjcrnQ$e5iBjR;>ibo^;YNuKnRq@=Q_NVh>JK3@25Y|M}vDBpmh zeFtZaC_fMfo&PPnq6Pdj_OqXC*sD?(Q&KCk$9tt&az>SCju=Fu@!tpKHLwV>OmIs= zn8*`k*_F?5^o?ku^q5Tp7o!(-jo%QTkBDXcr$aPGXd0DTYI%~$ScysdhNjPYGXLN` z?p=pY;1QAeXB(3z7jcPO5{r*5sge^Y~x z`E_=|sbv4C+L@>9*UO2-r?{DM*w%M!B1Y$5XIDMWOWfb~vHIsV^RH~Q06FN|vBIjQ zzY1t}U5uP6@Ve|n;o1t89Q{65ocW-dZwa{xiP$7P`%0&5 zF!A26{Dv%xccyg2Z(;FiwbA^TUmYDhAxlf7*zb9NsoSHz5E;A#9!etj2_X85dLL|> zG_q^DW}X`|Lm!9I*i|e3TIm-fSeeD&ZhH4tW=az<0oC&G-?F6zKB9T3C}h*$ewpBd{PI-GYeUvKVd;mCQyY(EVpbv=O7U@DK^RhC0}eh| z)WrGGT&=^x-@qJ(f9_sRyf}^lU^Rr7=*70eQ4-)g?Yav-8G$WxWBGBzIqw6V_^^T@AqB)NHW8mc{20xlripck9)KOZGeBc z7H9%gN>P)!5GBE8ZT>L3Rym*H*jW=8JwCWY7KFB)pnzS79lK!2R6T2pw!;c!+N_hZ zimbj$JX#%m%Y~r#LZn(C@9-Nt_e+nM7 z!P0CwnqR;4;e_iip8y{#tQ|LPQ^J0~KIma}CyE$(tca%D=Y=0G!tQ{YoPeSSJuB*e z`DT`JamX~w+vHJ!Z7iV�tmWYaK3h=2@vHk->zH&b{nwM0eVJv~Cbf(C$$coV|R} zfz*>ji}7aAK8xh0$G+9tj-c&!S>s5yUgSu&&LYHe@tMh=YdDzc*0%{BUagursfMlG z)d_pxcr#XK8HkHG()wxvz>79`8t0dlgGZy&i${4i(FtBT^2=BA5V6 z1bI?}b;g6WgXt?(P(w*5ATbIPpyLdeJrI_=csoQmqW)@N=IIzpLn8K2x#S8#0u0*2 zTAv7oLp6i}HA@=?X3&#I z{2P7Hc>&fI`VG>XIGKhBcGCm@Ezg(emw$RF~T1FH+QA|rcFV;GQv zlrCf~UX*~Hx^yp`lnwdXPn3m1nY8ItRLrMZ+dC`5L$E&kNTn~QCeZzra3BS$gr%8< z%taDu8HnSV79E(fQbZEHz8r}sWNq*|q2N9j(_MZ_HlnyL;o-U$CmD5wP#Ap;ManYh z{9qCamy>3UEmyBRwK5XbKMHB|C2zMZjo&B1uMy-Ow7@<+iQDwL>hc=V4d9QP8@uu1 zP2xi1Hv2u5USmn@`y&>8Vku^a`@n*oISN@^pF024eeXsbN7=F^27)|jmL^av#<-_p zRJ1UWNc%I^F>aWQdxklN@WwUcG3!H1QUac=>DxFT6t>r{y zyb>j&Gj`cgsv63@#C@fh{Ay|#d%*LN(`UsF-_Qj}IFY~TYRq2+oyUyK3NpIX8)3lq zA6JhcA^BGZIehL{RTgAFkHD8|4`)HpK+R7}8FBezbk zrf9#`EJ7{$?%8r|TaYrfw5DXQij{BQ4I|_#1j^WXA3jKaF)FV~CK) zE;M&B<;Z%v`!nh=!H~-X>m^o9cKI8;4PBR7U}*Vi{*(Y(~qzny$8#a_^B@X4o$NGAKHtur1bHJEM~8j7@y z3P_a!zee=stvgmv1g+@IRk{1Qn#GJyDcQC$C^FqxQ>_>)yvm#EDF~Er66&X_O#|@H zYFG{IZ7%(HW~W~9TL5SkRB*ikz_Zzsf)`+I0JU;N7~AqZvIX-D2TsIQCNA=pz@M>T z<(3L&&h0GybA+rO3Dkk$(}0Z+$(2@=m%&a1Rqc7!oaO<$93{fHFIHn0$wz)o@`tu`yrTzzJH_dRG zsRSA8XYul4F=H;HBAb}SdL+NOhY>_C|&iN_E1+k$&<20vXHhB z`8mSLpmkT(X~$je^_XUT76@=Gk5WJj%vLJJ58XP{7gLharQ@XaRj$=g%QjFtMh0SR z)I(TGnw^=Yd!rkfX`{6<7Gcvi*Mk+%wtK|-8+9X;&z1KbR=9(W^wVs!XCGbq}n0!BU|OWl)xHOi>?7(ah!4!OYPaYl5J9t7x^)_O4Q-mv|ML1$OV9x2Lsi zNLx2AI4N-k4g0xXwr%%HDa?oeuP+q+BGs-bV2sjjP38ErJ3A&rO| z>1yTaE?&;ybPU^j9-TS9MsJ=DH?3bE>1~rTHnXQ#kCYQwowKs%uoc9rG?B-sKzbS8@^6eqwb81%`s)_9*rR>sok*Beav&=G^^2@gS2Q?a-EN0Cz{&uPvj=dMW!$?+&Io}(07)QU4rdg!fc+Dh3hU@3Og8Lvb)+shHQacbO0G=W?zN9!K>lp$5RD?E7^nqSb_Hhs!{yjx@4rt247{+GIC&|l*cJP(KXgmeyT0j`di5*D<2FG>&42vhma0fZJb6wC z1rZmP1uiuS8DPk?QE6qN8OHY~6s3ngdUs6GkFsBvv2>Txr1K`AK#ZMMJEw|)nIyv# zRmeZ*^$=p*Ggb}qgXcO)*|ekOtD~EbLOLr<1NE;ohef=KXBMtFmEn+ZLE!?aYuZu+ z=`$lt5MkS!-OL)*B*8$|!F-N7Lp_!Etf;nqmx}O7lV|&%Xdb?Kh;5L?8`|A?{Sr%+ z1}KKNR6$KyJE#H^d;e8^rYSsafrCQ%n|Oh90Yf zF*WmG@qC8J>D(=@3jgAAd8eRXPAJ4)L_7-hV(h%@L+yFJnm)PgiHaf0XhFF-Af>XN zND6|izof#PV^ha9U}u8z5Z9U{wi;d$>3;6siD0MG8ISsst7pf^lucK}lmFouG~P6K zavcgkv(nb&1`ZTeIhGh_(DNH_-BR)Al_UQw51s8U)CS`7px$dk`#Oqz8tN1cH~GTa z)AaA3%1wRfO?H}mP)jEbdagHk)0L*F=a36VS-&o1`V}udh-aUE5i2x1Lxkb@Vgzo8 zq4M*AKIM#O*QG8rXx+9Yu8q2S&(P*&xbO=in-$(0lEq3nm;d6)SPuKXM&p1&)J64k zZA*uYbmhl2b&wblV52@JnES&(A^Efa(vtw(YIuv_$qOKiekZEVC!Z&g;$~7|}Md{?=pkz@xgLhK1GI78@m8BBji5lg3-<4Y4rjd zJ+X5+Q|fM4{1qK~PrdyhE5=}E_RNU0QJog6bdt)@=*H=fHO<6mP6Ju@0=14uLf-v5 zI)kFz0<5lYf+;qN^5Bzv6!OgiaI4G15{M7kO}^HVvDk_V=Hg`igzJ2 zD9j&g95o@zNULnE@jW5nbww{aeo9$=yvtaG##y@aVH+X}7kRdi+1nT?snAA}$_0Ryp@kc?pPrQIDt$Lq@ z95$cml89??u0LX3gSGtAtgb-FS#_jz5JDUqUVjF#|7p|!|J-V=m$wH;0sG90vOjt0 zxOKu2QhTaW^_zW8_O z2a@ry3Wn!HV=dh7KmL*?+F2zPy{?zI)2Mzt+qci#bBN$PK|zNz^X=EI04DCxNvYt% z-@hW|m>%54GNFmn`s~%>3gA)fK=6l@r?KJw7g$GlQQ_~eZrquh2r!rohjreo9dZ#{&np?H6K873M)yz=9M%@5c zOC}^oC(%1`n-nd6@){1?rCo)t>#&Wjb*v5XcC5kqk0ES~5Fq7^cTnP6@Bgv*{P~q6 zUh|5M1xr%{)=ih+X+66`$4_SMzW7a#u<$<8m7~DJ2V4BHiDl_<&z|(pJ7+VGxvLFL zZw6|fm5`#pa~QGg{WopjJ14;y(_1z$|JLu_WA(vdjEBf-XVm#cQS`<1%Jg;pek7}b zDfR(bQyx?k&~DYCB}n778}k42{n!#N&?o6k9h z(GiQY3sG$j>Ma&V7^LiS%S+R3JHG)Ddgx(-5kcNFNaOtxgVU$t4 zR}Lx0r3X5nGA39c4Q8p#6>gp1kyAX0k$NCyBp6hqHwX39TwH3dQV-;~FOpaUA9tLf z6WK3+eV7HaCt7U$qKF4A+d@JxQ$boINw(MD_|KR@!g>6|YdFmPS`q{f_vsbB3}{ zdwER=*XG0UbB*RoJ4STRy|2Fv9j4UOp`GGNP@aYR#f18KxWciwhD954W-viYeIgSt z%91Bt#}&teCP|ck@W0 zT6a1I1zP%J{YRc%DN1!PwY#7F*uH`*J^M338udSdCUX7)O;mn^CPXrUUGmwSY!%se zh~nAa4;~7M9%?L)C4edIAyB1RN()y-HV^gssTA~_3Cus_XogrK8=&jI*#3v(zT#+| zHxwR?R6lgyIU!3$Y?W`H$ktT1fC&KojyXg1OPHQdRUDN$m+uL{9oO6g{2^6z^Ro9Z zdk8*4~7w^*XT3lvql%b;%SACj+J&D*_K3z7KV0g2Nhk?>O2%0u<{Q?o%;nSUwnV)WgMr+YKpQ%P)8$k;EXHN=lk+%=W}QzYGi{PwPjp{mLAU82jV8GvlC`@LwThW+>bfSir+~pJ}qq^ zWAINTBxVdwJ@YAdLvlYFMc5jejR`dxaM~iVI?{>We_1;$;$AK3x)GFW(<{kJ##Rz| ziJ9Z^8`iW=)}32>Muv!k7kgXh+GhEoO)*Xfeo28`Yy%u60qZG&c+~7l=MQZPU!1}_ zGf7(UDIKGS7Zy{Z(RfECsi)5% z!rhj%84#ul~ienkLh2PJRC9$XWVS z8GB}*xK|oOxWLxZJw&2irV__D-41{-SZz}S@ciQ2<9}6DKtrFNnFu*E7K>BiQkg>GKXAf!R}I%V)=;%U*mK1o8yhJnn=` zMEHDkf!!Sd7mKRo37ktQgCd-4(D&8Pxr7L=lj0AySN&D(s}luob;hAPEd^j>(AlmS(CZZa zmFTKR7@Hfj19p!A$4GJl3jIJ*WXL}#oZ33`^ze}-mk<6eJiXpQ&HeCAuqAVwKR~J} zZfoqhxN<}l*&VzPH_cEk7DY3BGkz~2g{s(d*Ie&OBVcq^ zYSMiSR5lnnu)7>ZtE+4l-zccs-_^sGsB6J~AX+ZZ$#Gz+p`r~K2w7bJ-?dr$|7x>- zmkuZ{bvK-t;@Iz0t%ed;`?H5IMCv^ER@A(7EB}0B+~Ac{_9E#Pzv2J752`7`(lXzYOU=hW58tkPaZ45SI(t=Yr#+ zOPzHZ|70YtrJ&;WoX`JBjb1kgObDK5K-wRZ83V;nga$`OvlWX+fOshoGc`8cuTzky z0|IM$nNR-}2z>UIv^;}euV$Ze3)zQ&QcuF)-YD|02vgV`ofm_DOiK>YX6#bUS>_tA z^NtFD9q~=D;d{^hi{nf?@Z2=y!0=Feh_nss-icd- z@pRNT2+A3N89mi>0gS$zthc8}(4YP`GZAJ^u(`+o8X4^}eW?F#kdfF?n^9%ipp>+e z_}E5rv8O1zl4ZGdd$_!;QRHYRMdn;Lum+R3h+wZ_me6*`&CcU`!5+d$*d?)0Pv$(w zJRoQ(1m(4|y*;hQ>A@P*33}*p(WPxU*5e9B8+RRunfXtX^^*lUFdW|-ZP=e`!V^y{ z_L{}RFOGW}rx%93b`tABg_ybI643?{M&$ z7u_hzlgoIsMRh`yHJm{lm?@;#UhYf1e4ZJR}D4}0^oe9#X}^z#meUC zD?y7Xjkjaz*tbpJ7SFlT0U5ZajS2Xeyt$r0`kq#4i}|%_D)i~7=WhjyoznBe(ppH= z&H2vROG$!y^UbY8XCCRXb5recRHL8>nt;7StPWD0(5foG*onYU#nmZeqWdYkK!PD# z`?CJKjL+U)n|ettdLv#$SUR-yetZ@t;?p=smUF5+BXxukP{=`wTvmwD>dPzNyB;}x z?wU@KxuWvZOG|Bm9=vE_as)P4DdQA(SVb9|nUVjTBWXP$#(;oAcGCD^8F^@d`Hy-(t3D9f0D!$A0pNw1o?TGH>$;iFz4LRRE2A7av#RbY(M?S) zVbl8E#4G&lPlD#d?v#Mc(oBtJ!=f&eX$)82TP4+glou5t;0Iit)6iJPq%-K zwY4-gK}tS*b|F4f-v%J{Gf(7!94pE_l1}@EQASEJzalr1f4p``>rN)TLsxg&LlGSh zq~X!pN^$05yhd6QC<{spE74+QF}2Mx>0z*|<7sQeIT?PEK0G{a7NZX@OUX9KOIz5CcPIQ@6le=_6*&FuiUbYeBd+HK_^(-@ z8p^}&qiHgaJ@Qa&4Z~s}?m-U?&L(O1h8X_>6*hPHTK&YOu5@*wjoCA}-P}7J46b7p zyG+nkK(BLww>m~aO!xfvJj1^h$m;(Ln>N|Oepp)kZxJH*?|GwVK`f1vFl}jRbf}_#Ru($w^Peyw{K?lI1t|Cf2NeEUx`{54^z$> zYoO{HUj5WbDO{YZwl<_QE`DC!C@;jXs4%bFfVZngA03N;ycDz?s4+#l^D`rdh4`|b zadd|jOwt9+k~|BCmJEByq+no8Bhx%Xo2Th@W1;*T&BywUhK+uTo|(jqmpSn+xu3FH zc(ka{4V1!kZZXgc6p0!xY2RWk(=~6|2p)P>&viPCbW-Dv9+4lh&uAR|VE>*Z6ZCG$ zu;XWsV@Zr@h2LGO8Om%X1`>R_(~K9%@~DZUm-7|n&~2}=%K1=cmcDVMd+>P~(!um$ z$5IMYeoAKnZ#tvv;<R73zXxR-o9N13$A9>0b7JQr z{^@{g4l2+3*M3C!9vHvOUoqzDEt#RP(mKge9ok5$DUF44ejsc-$L5(&K-%#M@q(@5 zOtq>YPI}^G4(sbqM|0fvIYG?{OBVC5;{B-q^?3ilj|LSs8v~>h5wb@BsjB=cpNyGM zsRm`ih>5bI`iiLMAxP^a+hTt_!h39|J{H(ETfTt4W_sV(B(GLn||sZOMB-RWo`b9y{P>bUQM{LQp*^z=T}PTM*Fs1n~~A%Th|l1ExhWJ4I-!>+e?^GtS9O_~wBrA9El+hq-r zIQ2oS_s9ak)nw#>!5!4fOoe*G{S+B*FrpkVG-bT16L6;)|5?;!6B#<`OoEi;4~zjk ze1!#OPtLNvm06Yt{pKG1kJyk=>>e@!&_S40Hhyd1EUF>eFKP-Z&P z|7s)Z>fp|~(f48IRvk(-FuzU54cB_=zqaK4gCxM z^#95Z06?k-M*u|o-9Y}14*Z~vS$h}Anq&cgPO!7bZ3#v%1_$ol*{<5VbM&Tj9orMx z=p+?87mW>{vd2x;@22y#=fOfC+bT}=$Ik&k{(a7sie)FUoL(RXwJh|LZSr@#jvvqe z4>;Is2q66qM2%+g2l2237>N7j=X-!>pBJfGGJd1O&r{b01*_1Eg2MsV<4^bq9cv9x-Vhl%RpA)SBYxq?8A#{=J z5}|$Nm7=QM_RHQ9+brG~j0x)a?huZ>C-VU&rPZKu%-DE(qOvMszJ2)l74zH754>&* zWlGALmnS@k*sTpoG)cc@>o{SR$7;>~E>)>8E8OzB66W5SrRRKYS&x+GV+0(Ji9c`H zY>KVuS;{=cRQ1lIk9?BT|QxOjxW#RO@p1bss#Ve=LN-%+-x^UfS!;M79Ug0C+-$G z4nQ<6{;=jRQ+d_i5y!-Sdx=on4S*Bn}d933skt?|x~d2ME!M zmbd1ew>`hu;Bi@GZHWg2vGFU7|u?5I3G$$W;}MynUZ?31cNtx{`B zmD&6($o8PZH)nc9sF(vz`M5IKv1e%q}Y3ya!)jcD*8bcbA0}T*jj~VgMd`w8&kqE z++nhZ8T>nJwvW`iuBGg@2F|rE>^>#e$YV&$+N}|4r3+Ct(AgfZ2@hXz<8)dcFb;Jz zTc&4@MZ^PrHXTe8ma!t%J8q~Lx9)eEytNV(_))i%QqMq{mu<;L``!Ek=krD&iOv!m zBwoMIh$h3uZ?5&_eDR`&wHLd8#WVSq>%TI+`9YdYAvq9Q)tWZxt3$_*!ei<_#bj)b zCcBNc_fPA0JfR+MJ-DrG;Hf~IQ)z2}NalI?T4>@6{iQ=!nThI0Nt17oH2{~^4-lYU zQ@xF`&VFEh(;`maYt+u%Z$g{z)AhDX7nvnKvEQ8(I@EFqpId>GE>km8qj2$vTK?zb z)^8Q3(V_y3CA`pu=VjYTN<edS_4qpl{ncus5@A672t1eMm)8CkY09Wc;>O}>88W$9>-6>!G5~_ zEn@lH%Bka^V02HY;|u}DWv$<^GyC(^sZ!tCycGE*b!VsR4UBgNlo_ErV)v^vbxtR| z&#&u18sLqdVr*js@)J*jAMwS8)VOsNZNh_a3?(mFXxb8f-Dax-aEe1Vn=51YHA^`eAe|54j zk$--MwS7F1V{&JQigt;Os1n zo{0Si)#WJlSC0IWpN>2n$cTYV@=4amjosP$Gb;l^vHWG$m#)@;?7PnLC552qBPC{Z z<+6CKLJLIH14eGX4iecSf_hO5ITF`ucDPTt=BExUlslDfpKhn`-*hHPcVf9tC?Uaa z3R(ch!0!ZbcwDKpxLO}h$U~~XBkNpWxA+stfM_ zLjhPXCmi;TCSKY0M=Vxr{!~>Wsbbd-i#bcz2)_|7*v@vH;z^V8PGVce$^(~`@%ZXk zM2ahY=}V+gEam=N7@OfavXB4v|&v` zTHEEKpD}X?HkY1O18|6K4I~%i_7zXAG+}&Ll5imHC8%F9R-ki@H}`Hwl6cl>4(*4+ zo0}ezA8ia+D{hAR3zp8^{Pb};FZL0Um4Xka#Pi5+Jpm z^)TNj^99kMM_Ry4t_L8#g2E~y9ZygPZAJn)TZ`>{lkHoTCyec*1PPT(uQ#Yga)={C zo2uFZ(~3e3>#L%M_#R%nzhV&I68Ayh&h)}PdH+T`SG?0NRPZM}Nc%-|SbTAeC`d4t z|7q&9i>X>sk*UkR9=ST-MgM6f(vqF{k8u6dw%#D)iqZ@$2`VZkCiRKY%(bChC&P2j z%H$K&aCgz&1)+;gd=Uk*4yRtw3U$)ki928A*1x}iC7cVTa+#S^3{0NLYCzatnEt|h z8C=|&C{$Sdo=+`aw_!tWPJ`om*HR@sUn2m;V->V6< zT@MX=o-TH_@)>WjjRWXJ2;Z^Htaxg45*=z*U3XMi+v(5)h@GeGlE!vt+kAjsuI)OLtbfyEazj>)YSzw6N~{WYFHs{3 z7(=4{EkD~*{^y%*Dxr5n`mUDlSojK<;he*}%h3DD7r`wcT;F4#5cL zLSsf=2Dka|(TPIWR1F^#h-|n^(dA# zV{Q~waYRI&AQnb$y=|>G;+9|OWozz|8qQTps=2yJ_59^RkaHx@=Gk@p_RlTu#t~of z_yK9h;aZZElT9%I?re&IRdp^LrkIh$xs7Cv#NL;+tnp+0a^G_K1~|=4)l(4*YI`J};N_&4Iw$7aCi#QU#4x_%ZG@;F409r6Jg zlcR+7yIIiXo5(D*a5e*-!3@@iqXCsb?ZGX#4Qg%I)% zKoj6wZWqhaz2T6QbILV+2av;ICl3X&2w#2q1JJ}d9kq96)c`p0AVcZTi_(uVgct0y z4yum(1&0^;Ea6&vqFYZ+IM#0LDxrnPvotkU#|B-#XVBye{vZx%l;#Ggm>`*%84w_k zf2Mz4j{RqbcV-&u6^?DR?oW(5fW7v&yt{Xk-}?IN&>xm{mJ`hM(eR4p~Wg|03zX$JZ(3GNX*b7e>B#<^m zi+zMb4DMXUWeWK)RgJ$Vf%lg5v0GhMw)Hqi;?o?P1EI08@g!ICNbh8>O=Y;SDp&^- zhg^bq8;LhQT;vDcGOZXSvaDt@eYJNVv_rO6K^Kz0;zc)9qnbH^NoniLX0W_8YR%Jt zC^k7Te;*nJ4O{C_?3apbpN_vp5+Z>NeiR`4t_@$_ZUg2GQYV3`hTq_O9 z^}^uWH*76G0V>_hc_wg|*MJ^CR@TbhJWD4hYm%Lb>jh5N+E)#()1DzzYM@&)Ql->* z0+1OgzmfFtJM}RP4F<3P0S|K%#0h8uQllBMDr6uV9iC#_QL~z?K=f#y8b`j&+xJ)Z z*2m~VjIV7G%s=9UccNX(CFqbD^t?Z5N3c&`h2;7JrGjR0VMct2%@}%xMx>g}-7!;f zb0i8hofz!KqDH7Ou&&uSdAp`^A$AZ5(;CBxXdnp&kKMGbw?C$ulce1@BlqUE%GWaO zhUXc4S(vr+dFv^&Y?J18CM$y<3l_YTF$Jn?t>9)0rxEH%(|5T%Qt#Ky-PW}O)m-qB z1LoAq-^b0q#rEv>r;^^k1u5JhI@0^{l!{J50cs9wJ|gkX)_ljjwaX3oLfeXiKY^fs zjWn^qPgUCzD8$U-HQ6i)OeZu=*Lp;eP4L9iV1*Vesb~tHtbPe?DzoHwn+vT<1b*6` z)s?W;x2=T=V%cx-)#1jq#;!M*NhKU|m{rl8IAy!?uXuJdM_N>WPJ-5v%c61v?!o8` z>%ZZZ{of|urmWukux=6Hdes4x60;My=diRXy7&|sUE`-rf5(^6jJ_rIZls!tWLwhg z@CKDjOY!$UVO2=zKlk-}W{&zH@z; z8_H4ZIv6c7HTDBdu_Rxm=}83p2+>D;#ktQoo#By)5Lk_+F_U}7f2d6+^6zVt{iRYy zJ~2}L)s~bK!c~gX_6Z+i@M?gaU1Z>-VH1O^pP?qziwctLD-McLZC$6|ouAsE#GgOP zXbK9Y_7EvWanyTqgo<3dTCI|NXSfeZUids6kG$x`U3RJm>m;AfNWq#|UT9#58pAL) zbImbvt>@C6+*Pt{*|^!FAXB^-^L%z5#w9?P1G$)bB!KB@3!P}DU&4{3f5oE*BMbqf zp|>d?Hrr~j>&8W#@C+aXPG6X28v&zCuPP(d{Q&9P$dQSSghd>he!fk5J>5BI<5_L< zGz5=3T=|>@!84LGoTqBf2cALzL;LcNSUPY_@ZVjQ1F#ob8y?hUByI9PHM_B@g#|ZO z1@ao`q!GD=2 z;H|5&m;>5H34mCgM@+sMW3G2#;(9rF=kr&*tq8?2JJ=Fn*3EE){5tci5B`I3&|E!$ z9lqYw#QgCfch1yNV!LONH}{yo2fGbBp6}Z?Ogsb><_|u@StugzWeGqhdiS0jmfAdB zC_PbAS=WQ?bO9L}fB*2zI(X>l z+xm}(n*{13qi+cQxQ3Vib^NOt^0p!#0_z992<+iKU_&6sJa3Yp*ae<4CR!Rf)U#ubC%Ik%o{f_T+{>x% zTD0ZM7c?6?wKTZTqGj|YF}>+wqF^_h=OWH$Jim?d$;XhZXHyE0srio;1ho3BUf=N! zNdmAA){1ZDkPh*b*!T&|?b=+*g=Bc24xL1Gl1RcEgg}Ypgu`9v5@+@vwrW_VjotEb zp!N}Y;2ym!{#v(llTbJ&@{6^Jo?IsvTw{9}wM5}9im3Pns$o8rN z^GN;v0xpT(emx}BBamFH*cp19vYqn#^RY6F%k%&01JGopG)6lh<4gUA_EL9F55>ut z#5mtYw+>w9R7a^3QmU|79`{Rnr>1sX>ROzXi<=pk(C6?ruIZEb=~;$y+xcgM0Za)yXzmnz~X& zfg3=q)LMw2m{xiH221o;JmXAQqcA5HOLh#1E5MCQo|epL1t8|1QR)Hv!`Z>aok`dX z_{0s2ppU@0hyHev&R&OS%R1-iB3FJQjywyz1dN?J*wHSmQIr#Vz;e(7v>KYPwaMJ* z85#!?#6Cv#Gz=hyM!w9!A!%jerk~4M*76yK9!*vtv@p!9y=3gGpA|1pYK zHceO$zzpyJ>M^WEuf02t2ktxM(LcLv`Dg)z_|^eD?(VL3X%`!--{TS%tE_57UMyO7 zlF8Gas6pMv`=|TF3_sp;OITWk(pO;8Hdj0S=*lxEcyAY#-=~OkP|w=5nWEGS2#QvH0Ae!rzY~Y2jRJHgXcRtIRdXVHd7EfY# zk^76HQ3fh2w}gppWtF!LhIo!K#l0NQz~Pr;`T&MYc@xX-g&{DCw7#`+y?fK0ifXPN zRqY}474O!D7O;*36)gcfZ~_r}L}ZhQIWsdS|Ng-~&p&S{=vw8vwq6K;yKkV{P6$fX zu>|($6daAcA9$H58#c=T3#K-CHkt`%`nhREtiTKjtXC4qN%#arR_XZ~mkKqEC4aul zP>fL>El{rec@_XH+2Ta>eS01y*Es*wI?JDaK{0Vci@eL$pPC2%)E5>s(t&~KnLo7- z`|&3vcM1IJpPzgGSO5Gmmwt_(U-Rpa)$P~%^Z)evT>LWtr^ksFM5+O~9H&=7%>5!8 ziW|;eO6u2#BE6KuzNo32iw^6_6IKQrzm%ucU1a@_K)Hoc4;i9YURMEqO0j6Iag|ht zhr_53Fc&-V**SubIGyD`jT~r5@=*LeH|Bq}dkyMG{_pOmi2$FyK@GMT3!Ak3iuZVJ z&!(OUJeyP}){g~rInEO8+tv=%kAB4~bv{X_p!Vn~GPP6wA{KY_6p{x1d2@zVRh@K$ z6Bix&VYP|v|H`zec>E>je|0Zks`+OTpJe-sGRUm}$V8P>+8}k9^{LU)W)8t=;$RG2 z`!X#4XNiXN#72{UmwELU!L|Qh^AQO5X#wR^zcX2X9di-vIOEQfeZ{*@bJ7CaAFfx* z`I|pv!%;~)*D}zZ^8k1G_j(e4jTJnt|4EIbC|~?fQhS^Q!%Kx8Krr;DsuY06#ordM zz#sm`jfVZ8!12#~*Kg+t=3s#!u3o9D$8r;^#%wi)4Ei2?1-T)#KCE@miMM^eP{zdK zXe=9hj%XhOPNW$S>*QTC%oA6uGk2f3pHHWNA4b*AJVs@BOdt!G*0$v*hw7+2Q=PO& zS5No6101>M9(+LliXRzJkP&wUu)q_E!OJE-xI+NK^oQqw3q%Bu&P>2&fJ@K+^agI% zvL3dbh!yDZP29cK0Jwhu{MoDlSoFmR%M+4ou$k*HG}WHv{uy7u;h3;L-cCd){`98Y zx$tW){F)2D=E5I_^RM;b*Lv`4J@~aA z{8|sbg9-mXSraj($4@X5jnhC}_7yLVJYHT9_xU7kah*iWHPK=s{*%)c8ajdRqNiMYH(92?-6TBMD95+(-^A|Z% z>f9&`x4(UrGX4t;cPW?#=LVpnUgiKQ3rw+BDe?eovlkUEueIrT8;2raEZqmzJJSwkKMyv{5J7lU7xJ!e_pZ$1+7w>M?N4 z=rxwegypKIG{Gz&YxQ)YGk6e8L{oS6gOaul>N|@B_7(BTwmk!M+if4=nP2f{Ghl^! zZDasjgrbHG%`(dY6b5wShyaDLsde0oJA0AuV z%oLZezeJGvgPBE{oRNAVUfin(+g3MCJ^-}AvU0}~9a2`%1H%Cag#L##2JQLCqt01% zEF}v7TvP8sXfP}-)1*Un%$VbbD$mx8ryo~e1f-Xhy-~s$R^7h+;(B;U;GF`e$?8B1 z=Z5kzg@=9_YUvXTJ?_i!aLi1A7s15nEs@x)OYC*W6cZgqDR=r>4Z8zkbS!08$8;z0 zB)~*Kp0WM7GZNO;6TnjXx(!aEj}g=z_PF7mYE4g7+NGt;H*h~M?(t?(Rr1+EZ}TTD z6OuZ3A4%qXJo+Kd#v81#1z6KlFkWrh$2R5w;;|VqL(QYXR$u>HC|KK{!b{PWe zM=pRm%c%N(1}b`e=9pj&Obz0hGPZ#W25mjw;P1n(RZnE`+s0o}hz8byUskQ496bPE)2w{nYSngq+CRbK(LE7uFgJ zBql2X%JjHkTRn6AYzi2^bnBvv-~$ZQVmOTbrfwGdM`PL6{oA#-tq{7(RE=lGU1h}? z^;Y0mN=syP3mjNdi#E&WSbT!{^YhDf%MQeQTiK%;J1njkzB+wP>uuo{+X7jI$qP1s z14n{oKB=m^<~7DbRBr_fVIk#{5>Lmd^)v8R0;yK*fwXmlt;!F@9aL)P-^UkboljG| zH+1BFd~e#TPmG1swCd!8h^IINZ2)Ol8ePq!pO~~hX5UFUS!+)FP)0&WvA`#1>5YHL zeSC2hCyoh16MVv5Mzw7K;(9qt;k#!(4Nt}03NtCP z6e)liOQ<)16`r&AuRDtxX_&c)Nw@bqIC$=SpzFYE$gV4X$*|{{WE*ArG+*00fwMOx z1LqPyVDXQy;06+@zv2NBulOEj=;%f!f?2zW*%R53dxL3x=6<4s?8R|vvJ(wY#mwG^ z@>S>QDX(L|Pc1=Gm z0Kz)s{oEVhPU134PWcS#-VEs~>`V;}8iLSk3cciUs|uagGWE_)EgCNz*|FKo9mAW# z^1kCqLkc&8pZfcaS%&)J9xNs2Cl4BYU*vfg+T;VdhbNKN>i#xiH#;ADoTf_bRr%y4JeZT5vYaUKDV4HqMBToGu196Zh~@!6eaK%H|bNVrcTQI>(J|#S11<9{JI& z^{XQf-$H!Pl~(ls!{Sck1I~DF|0)M;4}zz#0vq-wToV}7epN)xdu4Tv-5;Z2)R(Og zt;;e5wK8Hi+6x;-ZQACc<`UEU(q%WpP@L-6OE7R>c$S;*Pd@$ypL)l)WjR-5y03*l z_IRL(-?P8Ua^{Cs6$|3S7Km~i`Qn+~CrZrC=z04oFfq8QZR4&pp>ObUlXkMFnB!~y z;S1lk_+M4efEO2kbN1}TvylQ){fn7WVXO#Ex3igM_5%J`L$O;cBJi~RqQqim^Cs&K z1V!+ULHdowQ4wEEP67~0KK@x?9Qrw5Vo}81{U7N;!L3yFYK>~o0{fxxP*|at_aDpC z?158xEcAt=w^(5yzLzkY`nyH|?m(SBq@P|goZ8PfjL_|a`fl&{$CA?4v?YGA?aJS} z?0K=X8bVy|-xH-PH3Ppt`7$44%(8@!8;H8r@o`JC;N8KKYrfvndaFGrLoZo|ss;6Z z88>U@LI(`9LR^_=$4d2njwAXYyB*yRK!8PiXw{Y;s3Qq-sr%R9PtT)yy~TN(As{I2 zUXTkonjs9MSpxpF%K-BB1igak=nRYLIV2b%;OYnYQD$E*R-vA@I2^WSB%aFN?Bw-f z!%$~;6iR*KyIR5c8onhMlj>xE>-=pkC)GTo=P!i>m83@m2R+#k=6@l7MlthC*L{a| znfNZvlrXRaUH9W=Me!mtDu}`;4Jw98-lwLn*G;Kk)yWWxEi@3WOxTdWz+K5Fqe`q1 zXN4v6jLZwqPe>)d z!mK)p^}b=KAig4xGtRm)Z)nj8UF30~=5CzK)kyEaI-ORR43{=%E43?3s@n7L%*6-1 zrf?ed7+3^oI*0>S7(A2oaQ&Fy2Iw6zCnQU6nT`KPOX!0P*Zv^o${*CFKJm+I{kwgi zE8*SNk+bpbV$9V%Jr~DKx1r?Pv`m_aJHdo{5quftT!G=GR;qK~%%Mu?`iP~+5YKE& z*4N@cA>5_U4X@Gsj7&g{Kn;?DcS8eL!qpxc*(>It)GNOzq%o{7S{RcfGw~$y)H(A65}IZGIT5 zWp(&%%HEDKNptQec<$ICvEI>jumn$x#EGR|9o?5JH5Z&Wrk_8_zIBUoc0S;NYyB&$ zml8FXXCGtL=!!?Bp*1ovFfopKmAL#0`M>U4cu&@#e|RSC*|c;-Wtv9@vx%r`?Y{ER z{IJdnE#6F+q{Qv0(1s|F8&eg^L{$>^>AX%x(Pinf>c~za{2Q;hJZXGJD); z?8x))rN&hZQ_HOh=iylm~DC=T8|U>A!f)kOFaO)KU5HvZ|A6leP`5FMU4+mFtcm!r$?s z{BrKEY)$1`F>t@^W7czU^LLX_|6u6up>|5kdBjs1YZ1s z^wo?F|A$2i!2#T1{Coy&M`$HR7Zxb} z06#yALA}g#X;5RFYswkp^MAZ%P*b&k@Y>bdSHe#D_WRfD(-s^ZLVZYd3;}4I?*wte zL6KC$9?df6E&a0(L!sWD-sOuqq7ya|q4H+3WT^O~+ap6B6 z!bza`C4m;8fM_G|Ll!il@vyEHgPB%i+7UmVc`{so;PWVRiKNWlIE>XlzH`p4Unj$`%M{vKRa6zqr8?c&+Hpyh~1t1eKO!fQ>OksjZA;XiF+4v1m#@Y-|=vb z5n>>e0Th=GViH7wKKA zOw2qljJh|0^sT7km?e(k!STy{OxtQ1KW3@Nd=gc4#b)~MHOim4jO%EFWg&RoycFA3 z&WQ#XIMB~h+eo=R$RwPA?pVCO8&4fo3?EDRk`Wm7apTvb%aY>k1nFL5q3QFir|&r) zy?>BT6A!5JDx5hA5cQ0U4B>AZ zNPy#Oi;4}7H8Ulsaz`I@YT}m#s*FHoOB__bUWw4HHW~eUarisa?W#IqTSj)d$>)yp z9B)QRT9llrY;naKdB4PYk0s=4(k}Zv)5M=;fP7G*a4y+`;-i{-jkpZWoktyw7dE+@ zgf7{D2{V`PuU?TXm`K!m&bCoyc<_$O7l+{Ubu$E-mdj^> z_|66@1~Ioqr?%pnw?f4=?Bc9nV1Hsr;dq-Q5E|6A%&FW!skhd203a0`hh#iq?St2Y zSyCf9XJ&UvVtf7VLzNM*caCfEle?GiS{y*;%DXO!##cjImvSlRATRyZF&)jV?QQkV ztyp}UrRcC#a%x6T*NujYOAbUct;>ddNhpwRAUo`!pJ;>shvnEZ@DEGx;j??K>&3s&FUhPhxsNg8mEBB`3+aQ8nJio5? z5_4?XN3jnh#J*r&6%DZo#NXvr?ftK90*8LeZ)2^KCZ{&BCWU?D%T`q07nKBG$--Qu zg4Q1^om|n$o;UY`<kUxdK(ZCu4e$IisO86FJ6SFX2 zE4ShJ%{CH}!AzR|ifMVqa+pQ)#Mija`5?LBY@cCx=b63VTT#kOsuhM8H6OPd>V(aP zlh)SmnZ~XMOW$BK%vOwbgKCn(cjTx|_(B~(yBG*2-ugI7_MXbOohWOY$o$b!nmvN@ zNb}X`@m2JfbkT`@=`SkaFmQu=F9~J(z2LOE{Y%SOxfIWyflMi zKdNlaz)brG`0v;dsy(8m-c}XE+}}2>U2EwIC}CSPa;8}T@i(dLDEu-TU3c0DLPn48 zV5%VIO&zsO){wC}^h-M*qqKBXAgcje0!(X_@ixB>~%+3|=>X6k18A;NG`Wa6{H z^pGee%@Ek$j*uPYpwwMR!Hl~}z-i%%e6zjJ+M{|oPj+6LN^m!b-=-8XhG!xfeC`yJ z0;XHL@WLjcFj;01U2N4@ID9Ad-9UQ1T|~9OyX!7-uYR9$dVYEm`Is+3@=F6rlVt;Z ztlcz}ynI63a~hqEon-I86pSD|(OZbwV-ikJ#La~tzI**7s7d#?em63)P#PGdknzjH zMv6+VDm`JJLQlDzu`FJEH9qutq{w1H_=))Q&Xq#US|J++l(Y{aIFrVDcy9C$el@Z# zg*naJwETJ$XySj-59A9`cNi#ypg(Pnro}-^sXG#~7X2Uv7#j zS{_aFFAUxPr835KNxJwGF-<$>izy3i0gQ&kA%uMp+Ow4*U;)_MY7>=FVqAm%BgRHe zb*3PqJ5xkpo;SlejzyY2bdu@aA_7NDwFgl-?SVVwF*ZLiAKkHRou*$vnKw zM)k6C8q~nkdhp!qOzlHU7g5gi0xy7v>X`SVI+4*pekpq%vY#IiqA0-8%1i;A_dS~Z zyJWI{>9E0L)()%0%wHtLpYZ1T|J+AqPJ#fCuf#lkaeiANty zF4FA*Uuq=LJ{kdn$#3=AnW&=f(jIjMm3PiUJnNd@IA1*s7ZCrRn4uE>ESTYJbCD)WLe8wx`cPBK+)=8+8h$ zj$i2t*&rk z>?3OVb_12GkJ+|hm3|ybT9@R#MhSaRnL%R93uhW;)ZRNksI^w)-Z`~UG!*lMI~DWh z%vy){K>$S~z8E$^gVY|OlmP1>*}R#WPm9YA3!{dXYJp0XmcBtx`s8mLWF#HC|D?Q@ zvm7y=XCALY>8(kiM^epg0e7N|KuOk}d~00#4Sj!&sTYbJ1n*DN@r{(kl)YNf2L$|`ZS-y(6Jl0Z+Y??b$R+w9N1MM zA8_LBwxm5?C*Q&M^b0LOZrP%Q^}b%Noq#oTb^Cm6G{fSq|M#ZFCxd8dX(}bIhIR?= zLIro$5VWj8oncF-rVwhT9y$;X!r~lh$?8nbSqf3AfFR$Z(5X}8$(Gr zd|>i&!|V&)^c2)d>{(cP&*%!xH`MhSo^h@v-nO0@j4n3X5@*oNz z`lRlGB>gI7kFI)$>f{aE*W6CuDf4eDakgnVDk-RVSDRkD*9*_33fd5o58^3>A1Ens z14t~hX*bezuiSE~u5th9+F$lX&(+k^w;a7WX)WMkpJRIO_&aZr1D=^2tQ19!pc#jL zIcO~5 z8K!)z>F{sJS1Z4vv}jmWwPNOySt`A=Qk5@R#B{X}ctYM|td7?l0p^U!6JUkOc{aMRvNK zt3CP*_oT{``iCh?6+~;ko0!&L3WmGeyL+p7U^V?WZGt{u)^3-Fu`2Sj7+gQ9q02;4 zYM7at{5m##n|X07nAu@==(oa|Y+)p2k=W%}|t(+4y)C-Dp&fb^Gh_0+GIc5Mv_CV_6 zdt|P4U(!$b9mp{cE2DMGno#4Kmn2#{l0>HWqY%4f_iInm9;Ff8eby2^L!^aYeNwc? z!Ou==VkKb;{meS#Aq#3q~- zQ)n?=^0GEq>J^uq=gN+e$CF6=E)*;CqCr3~p@Tvomdq!Fmjr}vW-=fgk1Uq?NQore z^iW^5ljb>?o$gX{wtJK6D2o{r*fKJu#^XT^MzZ`<-V?gugugE(vGxAndIsI!6EJ-h zezYf7G2fEr`k(aLIQ=L(!aUZn>+hSvvQB>otUme;7MqeaFMV}FPb?&#*=2v5y90KQ z%v2D{1})7;YY)>oj`HZ?E9nFf$*qOdoC9Wc?2iguX^^hVtcB%m(QNEaB&`yE28g)3 z4wR(q4E=Ibr=%Zvg1FSte6em?NAKQKs~GW-+!uh>**gvC)~)rH_|pBa3ohzC;R4EB z-KV2|%AJ{a;Aj0CPeuv3!VJ6f(i0ztFsW6+g*o{*`#To|t%h^MPka*3Am6IWQR_Sx z-9vQ~psXLHPtmVX`D_74s%>ZZG7tQUcQH8OwAgH8cw^Hgm%EihH#F20L(F3ruO}?B zE}WE}h0-jTa%d4|lNT+kG0r%#n6D|h==6Exr`oW;ocuj)McZao;rgpG3a?fa>Ko0p zOoS+!ogh&N-96q31K3o+xVj5fC~h4@b>^>rcV_3ezms9xp1fy!8#7I`IitwL%2Y_P zdi9H|{LKq2$Q=cmDS#r)cBbz@PQrC(s<5(KdFye#s3eW*$2;Uaky*93Dx%7PnB>UR zHuC#uMK;{My`x<8o*{lh}Y?Ey73#pAqG_g)GXSmCt+zb|CB82d?k%jUYTpS5Jt-}0BokB@Q%Y}ljEOu*_$53#iX6z1D5QZd`#~Z0vYz1#2pX2vu@X+WVtd;5Rd}png*|h{KsR=L0`eVzK+;~EQ-7RMq;Kh9EzB>OgDg5NY=$@G;jbJdC)y1;7A2i1Zn}Tnm#abW8=Ej|F-;oo4^&Wb#9J>& zxI{PZ=JEX7lf`Z64m8tbCqH$CMx*@5i0_4`#W)4~PzB*25$t)oCB+P*k-h?Y=`@?} z-hg(VuNa0_NJ*KRsTqBA+VqTAXFcgNevv(5_!RRz+}ku0u^a&8JzWHdS+N@9ZF&*% z4gD{Z2aWCW`YDgtq&SR&O6G$qS?RY5HwEoK)))bQR=`Pxa=_|QaU~#R3w)sLx=Jqb zs9M#|%1=Cg{5wdkjO2Rjq{eCOl8o0}%5yLMPBI z&$4gI=?}<{()vcI&V8D`uF5WukhS)(n}ppsN^KV-YsTRkP%p94%(mCeU&xu#?cy*h zRv=6rP$)FB{E(^g;8BKy$ReiS>^5`_iu^Wwd)kPP%Gpx~3%^BK?;U7I*1(#&3G=2< z^^rGI9<7r(Bv`Vxvy0ihVw~9@k)OAUxm z4dSF4V@%}b>~N@Ov`3D9u0YnvLl^1H3&ScqO(eZ03WDkCbjrTRo7tHQYA7^PI`-y6 zN+J&mRhr|!#5tGfmH7yiq*(OSii7mnt*ClqeYu75l)(O)ge8e4%5FMwj|KKwQ_y)+ ze`e3$Jp!Ji(O5qisFsrFHx?I-b~U+op{VG>1lEU61$IUAV-*%4{^WfMpiqYftKw2{@h z@C>6_jEuW&L*bVb{%Yj7h2|F;<(3+yX&2`RXJ%Q$Qs*A1&LNZ#OnYG=9b5{S%Lq&< z@61JLQTkKS#x{;TfuUvd9rPe`KdQLw?wSIBlTd}_n*Z|JnRLWV-`@WzQ38F@OwsJ! zi>qUNS-LpU&KFAB!o@TATPeE@CEr}X^@aw9M*5b^w;GR7ugEJlreun|T9F~2mSmxc z_5ZE@1f`VsJX<)cocj@9wB&Mb&sH71_4o@1Fz7n4IF*s{DhQ$hKXz1$^ZvsO0yfC% zUlxb!8Qofv8vjypa1<~ez*u@rqS+AGhNP|5c9*0I=Eih?o2ROUrVBG+TJ$_rH2(fH zI`ZS)@$V`1E;a!}@>(1}f66rGEH+_-MkAPneypAeA0R{_ce`DntY%|zMX*5gx+!;` z_irHV7HP^2i_nq;iEwzftM zR9Am+g&nUP5UA;OW$mJ;z(+eZHrZo&d*w$Ba4=uDx)3P^!87CCG1YzxE71DY-2r9W zFr5>jz83EjES-`rF^}ndV6PO>KjNg{rJ26O4_Hz3y9&=xysAinr+~nlQ&n_JVk)0= z<7Bn--JBKUlqMnd1%ZWm`J6?;1%K{q7av@3TIOZ2&>u|D`HBHEBr7w~*PZ?VO?^6V z`q61&{@RDpv(16$0xvj@ehfT2^*-$3YdcOI*57-02tk?LYob4km0~Umu7`M}piisI zvmY^c+8SEp$d;LAFBeLCOD4>?pUOGjMrED;9@EbxJkjYpVkBfTNdrO zqT>GM#wkt-S{#~2M#9thP1|o+BnQXMH>CuOiTq^z-)?5lO{#%dnx$W!SQ-*K|iR*yQozDghG~YV7x?z);93KNA^>$YJ*w z-=>@4ELO?Eq`buEz>6zlVu-&iV$Z8NL#{DRIY>%0_$_Y_cW``8Q?9lF#mFh6m-~2{929q{n6;a&Y++?Y~_H)MKyScJD+%J8K#%*EE7UIo7wC z9FZWbf~>N`RS7iVXHA5s6=!vHa;;hmrQWKycL+{%?)fj0JYVr$xY4xu@RgK&M+~XF z{}Ww+Y^_c7eomJ|l9?srW|+-q8NDHBq(zm^_pBkB_2TqoNsz+8DKn0>FgunYm%#0L z;&PGz{Tk3qRUp~F1a-yqUuw(^FP|HZghpx3ZSS{5YI#K3huSZSjg)^FunT3K*Cd(6 zFh>bcJG{%XSP)Jrnr$BPq??~!S!9R)oj5B4QN!l9Rhir7t0PHc zwKC)Af-yc4>Lpkh?8hAa$m&6uP^Ol-L+-3}K)YLYF~3JKGo`vSZL1P{0ir{WkJ3(D zKanVqQ84IbXvWI2tA=}Q2&jjEB!MwvKnF1}Zb_vD(^yAUT9^q?pam!FD0kE+c{O9A z!#ueZV$k(_T(6+cy*P|X$3tp-&+>5-8Tk2WdN2vZ<^0XfRkv!owBYl+TmM=>#P0W0 zk$x`e2z9xI%lGd>2jR}8hzW=!R?K&~!8-{nf$YApjxF#e@d@dbdh2B!NS!Roaoqn_ z^lEWXX$YTCoGISUoS-v=w}8#)`V_IGeLjK|StShv1u0yoy0}TX>XAoN+kZXu)v;%L zR2TAXw|M>j;=5`yAGSe+CSsy>7xMvbMValkiNAzPMem)Q_mgz1t8#XAbaZlBHV;^W z>yg$xa@MRKGnmYc9s3pa7Y<-H`u(B}N&D^b(j}Suzpch%tHK5G&&D_Uq^#7>4<97E zWsclTUNz|JYO6Lozk}u@2(2(;s8%ce@g`zp#`X#9E|~uzud_WF9Q- zp+3Q6Wa7LHTKK;4)$G%ShfHdHN0l5Hs|_UEr?2cK=#Fs!#zs5NE=lV)O;-XkPL}0; zAvpFNo;?LBh<-m*%MgSP+jQEd2W{vF<7dM33tYuyI7hH1a4}$xD%J-Q{TB|(b{lxXnOG$|+x0B|fNtl+ksPR=kT}{K zT4jIW@JU&OJf)SS(R`J=CJbc2l(Yk z)n?f*2ZZ@M6M^df?wHIapFItAa^@05-NRB~FlEoqMMQ`7a16hfSSSpTFzLJ9a(y6E@J zQP2HhB@-2$|bu_#`|86Q1+$x5WqUPu+#vM%BMyM;}c zRtrl4&hvV9xzUaQ<{@1BsI=XN>TX* zu{2ZEVlIw!Bj-M+?ys6ozSz8X5KL1l{o<^EE8GOQ@DZ{MdnW!X+26MBc5iqPD=7Tv zq~w$5QPZt5KiO+I;krON6V+fN;>77DfYm3uq}|kR0NoROuvqe!x5kGu^g*E()12Yi zlH+A5ifrf}jML0CV=)G;aPH_*HTy(O3}zYXfaE$JAx6R0ku26`mD(q*8&ST+Hu6%w zr06xvB?nPGN2TjN-#&RhZPuNDX&*GUQ27$*5`2jasVz4_W~KPnD4hqIJL%Z!c8k(6 zBCz0mO?A{SKrXdV^St1~G1f0e%lKt3go>XVH_%Jdf~9whwFYF6^O+G!OHKerqp}b` zFuR@?>C)M7^l_-nwO-{l%Y5dyhYlcC25&Es8NC3upz3dr^Cs57f?m4V@_+2|}OFy3kQB|0#{(h%nDfXf*z z#zA3{KT2jOBfp%`ug=19?zFV>SDvUgnO|A%fiXA{lWx3G3Jhf?#D=jETln!Ls)&#I z^jI68M*B0o2HFQ%U2Y86S3C%IwNGS-!M5&X9Xx>=YmdktoBGf^gNr&rQ?&Z9=$NzG z|2Faa^&aOjgTAj8Eb~V-SPlARK%Ek8BM!g#wPYsLermtMn7EUp8q$u7UU(}?au|+S z^3Kd>^AET8|5%Cd#A?xPs5>>iV{?1Gt>t)Yzj;^avM^pOj@VM$+WvOlTA*hQ7T`3l z@TW<;y?FR`&tFg}&JV{1YaoHTjBTz^bQ7j^+x)MYP3>%_)O8)yY**bP{8)((+>ItU{sO z&nEE)ooQM=8#v6=rxn%ZB!(6cR0RZf3*kKo$A1n&jSo6ZKAedoEX~^_*&00^87aGP z{$>S-|8waeq%ig*{1#P;F>PJ!v+M&BgkLD#AaMRQZH;Q&oVRI&3glvpOX}bIN8i`@yux3D z-j`tET3IIOyR-rE#c(YqA--h`1b+rTt0smR1XNeV{ouy}j(GhWiwkprfpri8jKtFYl z)Q_*>2k^wzF+7qBezCn}#*3LhpFO?%;ghAe?(6f;N-2|{yZ8&fM|gPtI{*38)a)2m zouavO;XRxm=%?ub5TZw+TzXF~Lb+uEL;U=0e$L9h+Qla1^LTq9lJI(HJb_*t+nAHV zzx$rAqWvN5mS3ZrMk@u}y%+CP)1z*GePa7}s_)}!e{~_7CLHe!m7_JoXzQ(@zGoum zX})|Fk)L}^oZXk_8p%8r>CKnI5CM?Y3s))@VefpMu3A1i%zOFN*P_m*MZ@WYJNLHq zs66_LbbT5tkq$SC45pa_6Pockg}QMBJpLI+a`htYn6VbItR?AeNzT%r-{B6KyC=$Q z6bS(t3h)Nc=MWfR`vC~-cN**D319Jwi7W$Dh-wU_ufL(LHa1x`>@To%h2xrE6fHD=KqaMk`!6SkJ=LLW~scWC^a#!6J9YpdcUseR{>G|5}<`3I1 z#5~PH>+xv!W-z`oqxx{MCKAl63@2UU7gDet%KJ7*28Xx4<}_Jd z*O=2ES|17{*6YJihJz*%Qgj0xl{bdjSMWlh_0FYBZ;v0cK162=p4A9&|2bMi;4HxT zWQ{;H5i|V)Re<+F5=A+eI!^?@#EK7+=9z$XT2sZwC4yg$UCtfTDyMUnJR?tWgyXeC z;-@X%SZ1$sxV0{tcY#G2GQ%_z7|o1gyqvsi#7R_TwrYRxr%u1t4?EPKX?nY%UbE5afWK9V+dW&YUF#o6Nv?=dR?W^I zJl^LXi-_)VrG z@P}F`kIsOs_^P?P_L~pQaL;3!yA;RgY8N?wj4J<(GQZIUm$xat8W|C^cJ<4L zl)yCovllP!s!}Hzrv|A=e4)}&wvLQDQ7pAe*TKHeE-cqxQnpljlg)Sbr?_XNef|vFLBm1iQE>=v&YdVS)>{BE&46s!&+@^68`wK0Hnoe*EY?*b~YOQZ%EA z?4!hV3M6GL7MApP)%SYz#sXPfSdRzYEK+O zb}e-_hHi7b?u@;cXPSs$^r;E~fy~A6d!JvtxD1+J6cHBeH4+$Q3rsWRuG%c|kd6B6 z#G;C#def6y$BrUgkUtu$qnV&7GoP`d@*kGj?0!bFAIpz_<=_10*MCl#{C7jL8a@C@ zGl0th=46xvQ+mRi@;3}erscNJcta}^V|#vDD{gliczC31-B>^I*`V({i!9NU<=^#9 z|9TIvsXz=aNuqjM4-?wu$S5&DR#Vt@@T1=|M9k+ZO!nw^;8*oAEAATZ`d3_NJ_(gV z%r1k4A{J{R4!dSeQHfSFD=6BqU?Mv^%=s0tJ<#GyO@>T|Rz3QMAMpU)hC>KQ zqM+FSbWK+2(3NE#`gKZL-3ml}PNTR8I#WNl$g4+Gzs2lVPRsl4*!Q= zC)nfyWrT@H_kAEHhN>RPgr1-`gqJR03bu{n7P&WmDFjW04KM>pSbp)nWL8Wn6mPr` z%)2`^JoI3`*$h1SBt7y6(AOR*8lXBHM#H`M?0GR*o*j9Ef>*6>1Q zwPxr+L>oz1MQ1oxB_!XD8L*S-?6mYHqf$OR4(5IDOAkAc>YMW4q>-C|5t?>F{{Ajv2b&IeM_nUh|I^r_!jo8x^87L+@T5kRYyJ0wg4lg z8tF>&D0FtrDDq`feq_(0C3riaH)_6$F$`jDH?O9HsTvq!I@%Ay^{6o(pLx_sHNnfg zHGA%F**#j@_ijY`UGTeiN1V(hpg@1yl%_LCEdvpb@tr(M@2g#sxxO&(y3i$@TWO`U zcg#XwqbGA&L;QQK;ya3@H(lu3f$9X@o-?`1M5fqf{)UQ$G7eifIcnRieMN0MO`Fbr z3fTaG{l`-o%uxG>CBxp4Y4om|ek3~m)gDY5`y&#H`unq)DLnPREc5RVGU&hOfc^ib zjQ_s&|G&MjMyxZ;stg(JHOPHWOo+%BGkj%Wx*R#1y~jvte9s&GAMv`!{`3ET-->?x zk9*bs{3*VF{v(-(c`9twL$b||J>!=*b6ac1y8ti-d_+ct5UgaxC-WK_mlDgRPM~8>{ zPb@D$^WUgf`;U9&eCtbj@#slu49`eAOOynKi*ZVYrq38hn4}X?(bd1z!9Dtxia9xd zOW!w%JrdTs7@P6kwfj5-Dx!4dw6uLbEQ@h!jHUqd`iJHIM4$%d(;hk>@2z-#qoko; zTQM#6`~7dRPr}c;XJBkD(x(AyB7|^k{h%A*qb~O{A(!|{!V;G;_}(Z17lM74Zs7km!oH~+Zf z^6t*u7!Q1-IrP1U_oB&b*1!Jm|EoQ%2U3_xO)*<6bihmR2EC_aPLI%t2>GR2F3qWIfz!Qb1o(<>@_vt zPY@r92>7Vzno=EBf17g?oPt|wdji8Besn&{Ta|zPDw9QG{A=yG z8wP}+W}abGI&!5L#2mTlgS=qkSXdBU7O?!hQOJ!HGd)PI5%l|-SXC8c^Zi@_btEBU zrG4a4Mq~X7x6G0Vb4G(k5$lD-;~Lk~b(ykEl|IR^WU{p&i8OCZ)nQq{y*2I_>e%VI zQLBspDI>gRuHfAED(n_bYV!1S{xBF`j>LyP=l*ot;1;>+_P#T9Q%A2L(=1|vjm+DDe*jEes z!BOcp6P;ORq1yt!l&tF$MvkGBrOEDRh~$XRFfp4rYiHY*#%PNatxcipOV<%T+;^`E zxO->03-zxr#nR3&CMEx2*)AY!#s|@jXVrCaY(U?&7Y3_k2sJ=Sa$Jo4LJ%q*>hpwyw<0XOI8#=9|<6YgG8C`_FXGO)H_kI4YXn z*U)bN)EC8T06vNAvcWN(awXu`Yk|m8Kf-GWp$Yl0emX!+Rz{2Tz4m^plKYwlX^0gz zZANT<4(&HGph8LZJMom5elV-fKP)f)_ID2t8i|Gb`hVWMZRuZrgcdJy)f0_m3OmjW ze%b!~X-Jw4l857FoCH3g(@)U3fld6$bBn3Yzhd~7^*L%mZ-|F*+g)zDO^%vOF@W((FWtmy? z?$*$CKllm_lXh$%alIO+lh&;~({Ey~1xx4D-SgAN#Yl9aU~4WEY%a z%qiHu95*dAZn9dVY=VAmrOm1>e^J(5vZU}KI?d}|v)Npug-7DStIh|vIju+_0-l%~ zYs5u_fPi=#Dtl^8imu9p+T)V(K#orb-yPp{ADBQ0`a*2ycFYzm`mT(+QPOv;D8;>b z_Q{&7{i3>Pb(`1HS-! zBW3ANCqoO&Z`T6x2sy5j`mNk&w`-?J4K2-+>i5v$JgkmNi9+XC4TCe>GAf`b5yok_ zCGdh~1s9>X6??$-DSx-{e_3YLlqPpWJM5qz;58!IooT`B%_(YLrZ!rZ67~wp&rR}} z0_fXJwkMm61nh5bF!9Pbqbs`kn|fi)8UEdnGF(GqwnyI7!WqHi8g0385?>aMnR(Xi z1XB9%QyrOlzx^=*=)r}}YZkdKlOcxl9fGQRI#(Y-zmd;ewP1<_zS~a6I{`JFAW8<1 zbr20)Bm2hpqy`Sx&W4P-J5u%1jZ-mc<(~+>tG(=>=eu)$)L$ijcc8zz?&lRI9SPdT zQO)*NYVb%-#3IFOU(R-<+LK}ECylKgf|u=E|pWQh|7H) znk0V`4BsQURQ?z%#29ZM|9u2@%6_My^vdT^%eOuWGU`Eh+`^rDurqp$*XI>rGTCkE zb1OsUWtjXDJnP^gfAVmaQC36TC`-gzIqfq2?1b)eyooe+=DsFERk0ohKmMr6Qkd(B zL#_DbfgfUF`r7Q$d4HM?-Y^A_#>LJ)zhJ>`*hzo72vq^!3QkyWw49bTaHrkx{rK|= zH1_A>@r?J6Glh;*AxePuK`=1+iGGo~bC`fm{@8w>qQ&LUMqJ43J)QZ-Nc$tUN@TjV zK6)!kkU-#YsW>t4<*66}&CGlRgO8i=!(!|xt3P2iy+~p7vJ?x0ggF1VXGQLN`JxKBCpl{%~o|?F7yp zziTM`Ab!{2uE3jF6{-|*HVN)Zy9K@L8W|%fQ8C-{ z*MIRRo;(%iuOk24WWN5W8Y{L164=9v0Kqo1n9*R18II&nNbe0XF*`!Y$d=@2M3Ceg z;){2$WWGtOUSQ?ee9m+o;gITm1$(MIT{5W=YO}3FJ+)zPj$gm`%P7N7SElezu;wnF zyC0YO+y20h5{4<#@56ugZIYDf!;yCaHVF|`1hMAE9I4Q_HTg}W0l-k&^VSK@7|01Y zh*@NVPr(%M;D)BY4mJ`zkCBRm`s?MF%iQ>d7xU-Y9OM1K{WZO=s%$4$kTV4K?YwGB z1j~^ra7eug7Y2+;%SmjvnwiR+gM#32k&ce`S*g_|<&a<3PmM~;J=Yp~Qdj1hz^41t zrVmMQBfB2GkpqfL@gzRhVfQN7%}pVQ?;*h|s&MNrTK~~v+4YDOpSR*(v(FRR734yI{K##zjq&~LX!+DV%_qCWD%AX!$K^Z6GM(9USod@BV1hGoy%!|5 z1n^lm%%Ii7W(GEcoT07OOPPmxPeM}`=egcY!mljeTjxG0;S%i9ACG&Cj4@H6x@8eZ z&u@}#s61O6t+zTfvO`5H*BbC|70I`*LAT=w_Vg$;V1>?|rV5n-hN5ICGAd2VTL{W}BR9r~|wyxup1blQX8I zJ&vUf*8LVRI-p(GA6e3>V?Vy|k;eJ$dg7X#prG(J;g%^2q6%p1U6Q1T#p!}2fc`tl zmg71;vTM7W!3m_K3ryL2)(@8BS9g()B z>YOk2ph~gUf?Cj{s(Spi;jvSnKBF4Np3@zvVk@#OA7CmruHNmbNDUnkk={a0A{J@_8X^Rq^ZA~gv*)+7GrN1vAIvaACNSjlF86(3*XxRb)jQ}M zN(AGD_3>0mBl6dX?^nh`)NdUgBD6(jkAC+mFTTsV6dH%5#R@=Wa_{h@Y=$HPtRb@g z9eLn1Y{}{iu7+!7J;XC7b(lw8KMD$233BY0W3-WWKNVNa@=xoljJ{_>x32x-`NwH} z0*=U8Wl?Jq&4lF2c)z#sv!}Y_G6jY*ED7^_2{ql=s^`gh7~>k}&ua$#)RF~fttDbd zx4Ev!;1BT5Eu$IH_VdB^Sp0+YtrV@y!b+Dtl=Im8AwP&WXj>NSkeAj&f{|R*_$)`Ksj*?ZNai1 zjqn@X^fLX>6Co=n&p8%at4Glnq61l|FivlavC%pz7ssgG8Jy$zDqA%Rxx8_N< zG)ci4%&hjm764=f-|utI19hIohudB({A;35zx!<-PZahN@zXkJP(mYtMG*wqXc+x1?7+(vU zdWaVYwD;z-$&rG2GO|Bhx>?GfUn+Tjo4Ygl1%)d7bKf2R^fNj(dCW-=k>C6&z+0_@eTr_o;ceov%*<=6Kh?6UQv$``vfGb-P}y009Q6qb@_Hj+YH@eSw_GR( zJF`x|b2hTg>VsmcSIM})K4LXS-CGatv0geVtT2&e;5t7NQy90lw;$ZFWc^5o1O~jQ zc68y$F~1q^J4DNGRQr~*;5dJI_0Mm;O|AW$o;zqeXpWmP zAcoeFtN>s|3!v|SmEOTqch#-SzXA#nKjp}1i{&aW+DUglp5_pRMA(njJMX$UUSxFu z;|^&{+>b+ZOvJvd(8YiZItN7xk4Fh>urO)gV*+gR?XUtVJMz+pPBM?^GJ{s(e$C7ks~? zS)vxonERB_S&aLr(zh)c7Gv{H6II?627P>&bM4P1L?3xCyFZ`^3%gcsXtSB>`TF)R6ru25KifpGO5Dw@j;7&peQ0_%CDV50%*KU(A($4?q~{C0)z!CfT#C`KjXT=1Y+)Z0OZ)Eio-`uL+r)eb z#SOxwqJ@0U{gQ*6HMbpqq2TI?DPhovMyJi@i{J&QgO2)-X-m^X7qVNOF~)yGN0E$h zmFB1~sHU#r7J69cl@2?=J{mc%e#f2i;#h1+{!4hlKV522#?No3yVlT@h~x?%jXUdk zF0B{d@Oyw@s{@p<&4##;4YZ!?qp07SX>cHVdZjs-MO+wmIrb{>vKbSOO=qHw&b7c6VEFLzS67iw8?PG}{o3nAt(xKFM;(Jn%s|k< zWpy6L=#U>LF`~`bj<-$v9qDrFT#CJTV%k6dq61?0+wrZ4yHdT(UM^LRb)p{XBAo98 z$pV+2)fR>G5#Ke#*=GB|EwEI=j}f&{5bo_n1ZB~0A>je;29FoPw@i4#o4Hhkyhk+VcZ zB$H2iP*NOhr9|y8%p6?-S5Z^@6-mXsx4#7_&-)(;#c92KYV~fXP~Fd{**? zN@Y1}*+qg_2Sl|OaBtJ07ehB7s$A#OTUqWs1$EEffBqtO)Y!x;#`finB~79DlBfTx zCb%pbSQKTWUBZZ?40ML*c;OUY82yda+aW9Up!s>3b?H3g{bdhknSj4CE_=69ud_)= znKeea@We#rkl2a+P<-An3oKKM#%@-^4*CV}gK}Oj;xl>ArqFp|b)!hcgnU7?Mr9Yo z{b!pGZb58vyHF!(E;qxKJp5|JJ20ERW1S#JI}1^LuV-Fzw29yG*!*;4xa50Ji?^?{ zjEGct;fH|j$x-q@u&6nZekY>sW0u2wGotHso|8@N`QF_x?^UVn^Q3rO*`^+QOYYEq4{Ck~3KoaA zCdEt#H=oC-61Hy7AF7C@WID(rM%#EMk1TU5&r^wRBif4i9|ynC(aAd3Y|&@QaJ{DK zhW)})rjHBCYrcqS!)>RJ1xK4+{T3Sz9f*ZCr?5kzMa%t5s=4$+ zzHF4wBHnet+2p2vwbSLRF~5)$k?c=`9@(mVcY5ufrC?&@;Ewph(H1uNbD$r7aEYsM zwxHc~@;=kPxg6XM=KM`qR`^=bIqNVI(8Dfss#Flh8YkvOXBP18LJNK$|Gl*d(EAzS ztxf>rEr>~l-<$tQXDrlh5pig^>D$=sKy~Z+n>yI;gTJBTw(+r}BC7ZcAnqr1+}$+GP*G1~P&>0%7$ z0!o*blqs*vihy@0?v9SHa{-}BGOBY*A+~Sl>cO^{X=SJC4~Z%mQwJ8rdbJpJoA?ABDL?2Uifa_& z0QexOnq~pbzw+$#+{E)aG8oepzp%{vq*&6XgtbpZaR5WwWB>*_ zliJfbaAQeR%ZsU{98ySb@U^A<>vw_87v$zk|6nKI4ub9|zho^Cy97z~j_&jS_0^+W z{kpKa^Jfg65f~<%q61wA9mLE}>@ZWfOw>=(Znj~a2Rd@+QTmry&h)l~{fwG-oWHq8 zECh$}YJ=yXOen(n$;g~fgQ#p`htG=+TFq`gO>=V3RY%|5Z@Z>l;bcU}I04j=^lIP^ z9I!-lPdpA}&O&y=rwVZ6MNQDle4j4*4)PnM;q^zx6D|<_iD(W@XB;;+Y1o+pqRva{L5>wEq@4Qpbo8r{k;z{g4Z?pJ-5I+W;qaQ8E zH6!|kuh`1EoDJyvxRBlpSY!Av4$iDEuGVU-A90F4z||%K)N|Pq#X~GwG4C!mS|BN4 zA|i?x6Hut@%@PX_A5Tj1vwox9_u1izCK+WpwI zykOf=FuZT}vBMzDwL8w5sZFYfrJg@zhg%F&3s< zsSp-$XSmZD>$=n3>u>q4i?ZF866bkNd-u0ROi}dkF&Ernj`Y~A2L7lUFQ4>#e@<{B z{z$UG7I#03+xsppZ5H7z z*4x+LSEg;<(bOk3ZzjEiwzeS4i@7cYVm`Fp(L+Oy+4i>h@xECq`J4U83-X%xYUQc| z145c{vK>7SzPn=7{$}Sp!FOLOeU4gG2c;@o@WVxk+ZC{ovoVy#NWZORq~pVd8yDud z&LtU_Sr^CktRm0Om)9RqeQxIzV7n)r23*i2GD&W@){gDiC?R}EKGd%nTo69~eoLTK z>yaSePIrILe52p2$98|2I21f=qz7pliP3~MqHPOI0x;ee34#p#68%-aBCGa_ zf|ebsUb~oC@T(xox!A_j-K30P2thI|*1L9K$c}}U1Cn`-Nuy(N2FC_5^l{cj(6#dF zHv=XSg?|?ht#=>cPvA><5J@yjZ0UuLkA@%9Pa*Xs4E}gz{mFY5V%DQxwVpl{JaqZA z^4WVsqwPSJ)U}FC8!P9VCjh#&Opy3w)V2(mDtXGmM!}DkQKLrkx0-q!K{Oie$&Ev#abbqsNKpQkFA2)Q8}KC zk-Jt6-*QA;P4hJc;%L-xSV9vKgjX6vMaL`mI{O*-tw25c=RANCvq^p3t}{V@QZ~K) zeaiiJOnRtwT35PLkTTqkcmq#^f&MszqCrgHJO>LbRA)rGazR)9ZMLtzH$ zZn_Nm%0}QNnbyeQc4rn)a3-(#ma-vMjuGqD18S&x?-h$`JMA)o+$qlKc~Qf*HyD}P zsy9algQ0XGeN-2Aa25PnCSoQj=U3?s9HFjdNb74R>L@L=YN&qfMXCGv9MI)^o%KU% z$kA&$-Io4B!CPCK7<$34?@>VvI3PhhpcwuJbHyuaL|Drf;l$CpL_m~WL4h>EYeRE) zs3k}9|91;OM7WLfGfZ^+iienij*#btsh%F5Yrp&cm;LWc1LS1R`{-P2Bc7mVpLoZO zcvQ0RqJwJDEWab5;tOL%+wrKafP3AuHHq{oWHumK6wK=h@8-vt@^4HL!bQ=5nk!aF zp7;38?VWYv7r66 zCDfj(0qZDZ26=bZ`ElLMl;qo!oJ)<-HV}(ZnvYSwx=jklNer9oo8qoIgen?gNzV4} zt#iK}um909g_TbfOU7;5HJW7e8A)~D{R+YQQIK9P_8H*RfVO{r9kCsR%P-9X98(ee zy=m;KHI=Aa0|i`bGV+O{{F{s8gH(!2=|Yfs?VEe3njsLX$0Gge25!6s!%PdS84l^8 z+y04yqZ-excQX#o#BVnpT7S2bv+;kB+Ne27XLMgX3IG*iX9NJT5Tbu6D-Nz#vkjXX zU+_`4c^g@6L0uK-jsJDS!_2wb@X7AI9RaATzjX}Rh3JHE$IS4*WE61yr2!7@vKCnU zSdp^L3O8R!N~M!eU>fB0spjPe>F1I|&IhZz`L==nqWJB@1Y87gn+t~0TRT6$+Wvov zVsoG#)Fk=Y~1mcq}`x001zlWoh27mq#(S@yGjeFSHn8dMq2tWbnRx3 zW5hjx81kjuSo9@Df&^Ift_qNzt27rSxEIYaAV`ADUx{x?q-*Lm?S)LCbq@Kbg+U8{ z>gb9@oMs>e{3B1GKBTi*T^OmOf zh|Z7Eva$t?hyD_;uHP7PPgBfkhX~!|U(@jv&bpGodv>51L#=UYnaa$}4&b7Koazmq z`Cqv|{il7G)%@3G+RJm??O6%0W$f5XOK8T0c{iPig*!Tj)LZO$HX=lSQKeuJYM2wO z+T>o8Sgh65*S@OT_NaE=Rk%<}FqAx(jHY!JZUQh`l)yL(jF!qxq8Jr!UE9=B^Yj+pgGPN@Lo$aW4o$HF9I ziTQ4=l9fdez3{@O#42DY8ijt94wRP`>_Bya*B$WH;)U_w_hG z*@_y{hqpZx#1#(@(BOUm?zaxH<==pWfG6*Myh&%FW&e_kyP}lC`u!&9?3nglU0tS= zn$*ASLuEoi774;a(cVpb7sFfPc*e`^Seq4R0N?0a0SZaAEjnS-ec21+*E!pny=^MWV3xhw{&JQClJ|XlMWd z+*k6Yu0Z!QBUxm8<<;yJ6|mBxg`-`!_exn;;5TZVOzKd3>JZf4xp738SmKX^Q0Wxv zC3#lgfEimNhfEcc$px0eS8SH!f$5`+&!#HZ%-YtJp zQ6106KpJ!v7VYf-Y-oCzfu9E~{rJOd2Pag7>yjoT}-~861vX;w#+uB#N zwyky4-9T<$bBO7Eqahp<1Kh7c*edwwSzH ztA`Jg$k>cH$d}*`FA0BD7fUk6L@Sb`z~-BBKU)8G(4H$+byK_x2^(aPmv zokzaA#>XYseHfgT4$Kjoqqz474q3@?ZZ0IoUU_MugOT-6VzES~*+cbA0c4mv#3ZUH zQ>$o7rv44yipfga(y)j{3dtVA73$12k(}@FRQ<1Qa*K;ERTlu0>8+x9+1?taY*Wkf z8*9dtMFeEB!=H(9XyA@oMjt2oGVns$96y@ptU|~ObCcnktlVRbthQ^uX(Ae1GG}9C zZ6iZ=?`Dj$AJTU_)&bu0Py0m6Kq30_(GQbl6}up_HN>mkPWQAq_Zwku0l3Rl<}VULyJUQ24R4(#W~{dDVsu?UkeR=j_|8BS@*LOy}6A z40@a=Rb4S~&+S&4i7eV_^weq7-dP!od+P#f9@ODX-@894>p*LIocEQXiPc(T$g2BO z%WYyWo*qQBzcBmB?ZUbojpkgrMGUBM*lTn4=Dre7wVOYBLRTy+51nr8{PtaWyv z0YEW_n-N6LN@6rxCp9ZQ=#cL_fq(t)vk1qe#UCFddWW%plYzGSkgQ5h@i;chwkfv{Cf9C=D4Bn7kGZb036~@e?L?4NuL4bew@+7st(xMXz1$3BAgK$ zO}pkjr8SThtX)^(Y`5jKLD{olr4%N>Ev*`w{B@00KZe&lT=-zE3YO(WOu$311r6x^ zZ8|WBMIM2eKTx@A-b5-mHz->xB4E}AydBW12__2SqgJ04C9etk5!yOtqXEy~&WkG+ zJk_6)%p4Dx-wS1}`v;fRN8jyU!atf`W=kq?R`;AmXe!_Sb! zO2yJ1tTa}|t(z_Q1$!e(WPWk^iOq*e&aLZxe=Cq4HxWT~S7jU4K5DB&|1TNj0?E67 zCA6X<%RN@gGOz4N-!Ea>yIA44Z*EGkfA-J1Ax3y}LoBuu)vGUnca|7trr%!{W<`1z zH-SvLyV_U!^dPcnGZdA!A2OIebHU8WZt2}@W9#ORbtz9J`|ZblH4DU~lZ1DWjIi&H z`x!0^tsA1}r7TG0+^u6$>u#9U zDm){Jns71B>S7R4tJTzIz%fU^)6P?%X~>%&W<{+_9U}+B5;}-}JJCXrZASMwl1U5X ziZ5~g`#B@~gWkna)w7(pY&H?W9@f?ZM+-%5Ul}H z`v-*Mw4HK}-4{xk<<^gxMw=(s=^9)~8+@n55c$k)+5ujo)biB`2p5{z7m8_Nhiu&z z;{L$b*;jF zp*N4_zmH>NtpuMM=P+tDhVW)AXeM*1SUuVacTWe3h^rN022DTgy#b*NrBMKXNtNHb z<+2V@7d(txMK$_K%>--a{AHQAIez7+9HYQ*q-pzIC)wr4;J;+l+G5jy+HE|jk zyisltBP!`SN|{Qp z8oawP@uHmefOhCc=ip7Bj5 z477(KooSXbs&2G97@>{ZPL`1K1%xHvH$tHnR0{#1SG)s;l5J;H3- z%&4#R!_q5O-YPCzCBwSg#*0YT&x#3&(x=B)tVlMWPT>y0uB0GlK_5Kq41HKPCl5EO zaW39;fof~)ht1!a6BRw~PBwTkHz9pnE+-7;MpzkZp@XGaE$MjfXJ{Dp^r+LM9DYZ_ znl`V-{4P@>+52{%{(by6J=tu>SE?qLicACOh&%6CTnAs>#YHE{{<(~B#vPUUcb%zI z=Y`ffg1HqP+s6nEwJa0twKqO7*wcI&Bm+uAa@hMTEa4e30BgZ!5!SFZxpOIO+4n}K ztEGqfC|QdDkJefPq2UAZ82z>*5;PKyO!VxyS}KJ!Ov{}t z7<2VRk_zfNuP`bJ)hA0Xb|XiIY}a%`R$I%X)_|n|*K71%4wz^LpUbEC=1v&nsR$XN z;CFj!in*;uei2fX;#RaNZ=@#Y?27)Lp+j;o!kkf4S6Y|ZUo)D#h18vu#+F+GBdRvn z!4J<9F6X)w_LzCP@_o5>ogesqaoY+wDXIfj3ok4lTR1o^L2#Rm;)Uhu;Y)ta{XR7C z3#w~Elu#+}CySLH_{bnViX@k*RmW*UULT+;vdOf2mjS9ebNrP6(F=2&7QR&@Ta!d$ ztati}YS-#34N_a~qW8hmwsxoFEP%-pZ5ZyV^kTNNwiz@z>sP_*%N5d-wcdpTH;p>F z3J$qVKd^>%F@9_4ocGk@p)<=%pdOII`wd2O6SD}z12`%|yzI&ll5=AX0OdXXXB@Cl zsW+E-iN9Hvxd`DddIkxZEEzR4rgU!+1t^qAL}*N(JU(>n1QrFE;Ug*HfT$g9nhWiamdst+{85X-%mcSz+gF^6>Mlrh7K^#(c}7V~ za!^Fc?Unc6Ft45?jedJX-GcFl zqDl8$uZk*{aK~9YFWhdwo^6rD~a!? zMS2q&ce%OGY~PD2_B2SoR^LtD<++39AdkgI5PE0(AQB_88fbN5>GFs({x}iJ?(8ge zK4G-jxNZ61W1{qr2PV(+6&22IImLeT9C(cf9h&3zhqu%Qa2yU^z>qGY!om+)zv10; z>!`x3+B_&t%p_QowXK0?)9%&AQ$Xhcd>*4^?7@C1r3^#~+=L;~8FR@G!cC-+1jXB- zagPa)9Pp{D|N#EZy!q8X+znPhNr@7I;)T$IfA)@sA5 zex;KW(PA{Sfx$4M?pDSD)*vSArBmgsaq)GL?CWHgrhql+e;bYXzjaIX{Yz$qzpQS> zOOFB@bOi!-q^VT%%i&caRji4vbp+yp^&VYhPKrb`Iy15V+JO0zC$SLNWr5|AP6Ahu zRF^fq-ouI?;4Uk<)vdp0(Pl;}IvZ4*us>du`6l3O__Y3m=IIz&MC8mEGNB+!EeTz< zo%Z_;++JH1EFVET@O-LYH>Q)+7WY{pw>+DcatTtFAxtaN=d2SW5BGcTNGw=ZD{xjd zH{6uN8eI_q-#jvrs=H}YPq6m(FBYixC^^_EM8T<_UUq< z3D(p?ONYD`&VAzY|ESyk}&J40AX;6J$ zo2;#VN8XW%{zT6{h4ks(xYMXNMDwn>c*sQ?XEd6@0n0;QA>Ah++-<%GGpx z$LUvfTO6IUVLW0K>)wEW`G0it{U15cS1w8ai}gd1LCo06P{MeP9J7<|E>{<=Ti|U9 zBdVOHe4m;NsLl2<%@x{MqMhewFgi!0;Myay1lsF7Y(&XCT+ z!aOGn|D38n|EU9frEfNaKSo%zMgjqNCm_4s3mW%CEm31+@(Y#WEy0fm`R{f?N^NI!u+L6zQzCIuUbGR5E zpu{^THoXT!Z@M^(4YAF=Q!kEtX8>QaF=z__hr_O?A88#X1r z+WQ_@Z@f>5!zmi=>k1psfiy^PVhyH@ri>9lK{`YIBJj);XNoAWbZ8#fgQ_j8t0-f> zj$sxxZuF^=R}6*~ju2gh`q=`_GLe2_2F7|oT`*VB%)ZySiOVxZH#am>q;;ado3?^N zgkc_fE5up-GJ%pd)}1I>bz0rEd#&&QpL}eF~*;o<0rI=Qiau_o|wJNu4ai!n|uOVgl%xH6*7 zRnr1~xxVMZ(6ubS(D#Hr<=Vxk4da5E#@EWaa- zM)N-73?NjWqE)@GNRL131f4MbY<5J&Xve-Ec!~=>%)?2KgSbg1IG35x0tHCVEfQbw z`{LKphZ-p&Y@a(n_vKL>rHn_N7abK73W(HYta)fr*s&>~5$-XWF8^?$D^Dm_B1Ha6 zwl_+`ewIaQLT5P0kCbf_iR*+nL@FG1Y?jD8A*3;nh>Y?~iJH*Feo3B*XDQ}o`5O~g z`pkJGC&wA+Fr*1_5`}Ryqrx1TZvNT7&N(aFUxjgrcfYlK(}b0sc&ikXtkKFr{_D5x zkhaEUE1a{5NHHkP62$?Vd1S75F?J;csPE<9Qs%7LgA#MU)2G~`x_N_}fy7CcZRBts zh>o6!jz{t(Rsf9U24D)F;%MyQh(HtuW&e$r{PK!=m8c=i???l_t4zNC)HVq$jOZHF zipH?RrRLzFRW7hb6PcUi8Zlo_^{+a`qCcM0;0+s{{a;cuhFfH4LeQWj7w$z(FcxYm zE2=-AZ4w-+aPw}?8xh$U3z@;7V_iW5PT=fk0?u4yY&2KL{x&^H^*@`3tOKxltUEYK ze|k;>E&xKF#cZRp2r!&P+DuH}GdzXye8(aTTY!p)(M&2lk{vk} zplYLKYso`KojK?s)9m=Nq)A zwAV|Oil&yd<$j*)j4~s9q7-MLeJlg)k&zWIF{iHG27F1V(8#g_mnR7nK<1*JG;poj zgt`n8pnYaXpj(-r6%2(-(~w9*m|VX-K4Li$a!5 z1?NSBlQ&#|#2Mp%$wHK8SyuemkXAxR%jqZnzSbQR&I7rV>ZuQNUe; zIDZ8JrG`UTsgYEDb9wFv**8lXLs&ITugxJMBDhsh{TWC=cyt%df zbxW9OV@oEt*!n^fd>hM(@d|wN=7$WV@BhofBRg;IdxF&&(vrsfDb0zbZU{z4a}gcT zEy}VH7V7{R4!z4Us2({g;eJ=S52*Q0KrRu%JYC{cj@i9#y%r-15w3X`f-X^ zXHRF2N22#X9?pW-ZLHK;AQMp{R}24=wI2_+u*tsyI*O-eb1EfuqNo|Q;~OU0*crr~ z1jkx1UEF_G0p2MzqmKeDpNxVwr(w;=>%q%i{vdjrl0PKI$;l z78z?}vbcaEvKn0I&T-Ne6D;c3e8IOlxWvuACsN;TS$@ss;>kcE`Hzy_zMZWB7KE`GZ(+g9Ah1r_>K-Dz~D!-n`O+7tbM45}N$4S2SFp^sDV(o(Xjx&ZK zkex{ft;~seV<&L4dFp)G#pTB)-&@1Hx*p_Or-}@?$Fe7;$!{%Q7gUe2@&-KcqCrf4rgrIDVpQTm_I zq~t#kb5)L9_mqNr)tUE>l6_kpD&tIye+~dE95{hTw^@-sWi&qr6o^WgCguq~cc9(s zv?U5PvjX3^5c^f_p!S+-G+xST*Az`FGvcMi47~rq9pK8^h3+N+;gqAx4p%u~vFr^e z$Il9sISf4yn-WuEMxG6782i5BBl}$>J$fY!{887mrD3_p!@>Z}qZ)EP_S(~{v*RBn zgz372aeJ(kw7-kuXXYm^H!gglW-Z}@vwi$%XQc^M7s_Qgv>9bLRp%t5Wd5u&<~S@u zKq)c(V6~Mx$b(S?dsl?wut)m4PP~g&?_zM`T(kDAUoKj6vLv-<^&{aTj*+GwA4_-5 z4@Y!G5nLx?&qPn=9=Sc=sy3G9zd&3^3xBS#=miP~- z9XSX}D3tdAa?uZ(A1cqy4u$>oug*)iqW9C>s|4=P;quLnKK6-Gf~{h{34EqVBG}{kTL-f9@&8^YN&c6b>A!u? zEQMnpp0Xe(0!GBN!#^~=c@wBczRFfbN=MJQ&-6F=vQ1nckhcX)xe0jo+x(YaNlQNb z$%PI{HwlxKd?f`JAZEjPBe0Thc{Gbd*JW75|Y8=2@n98VJ^ zfUFNRF|8VIOPs(~<5!Y3wIHG3iV5msro3mag&2k4nyL6h>ALAE?zL3^ z&;Q~7w@Up#{8{%!*lxJRvIG|!yL9G^fbfRP0L^cSis1hg!?gC#z;h7D4q=;otGvx z{5sjYf^ zsE4qTowG4DTuoZyJ9OlIdL$>zY`ie7X3cQLa2Og0>Kur-u!oL_Iwij?DNwx^aN}X^ zbU61R1@LeVaNvz%U;GBqIoiXe+uN5CcJs3m%0>(7nk@*%heyZCQDJGH$S6P`eJWP>E&A5$<$)*?ZqFCJV{Meh7%qMCG0(n24Zc%+(H&VH&|Gd@% zz#+d+G#|D}hrTiudmU%2YntfFaTNwLLnCA1f*47eD-D>2BQdK|C#g@z3r)YNKN1>_ zSZ;L~$9!LF!X}0;G{5Q<%lUpXB|hjb&NU=4!c6}Y2oW3E;w1*$O3L^_OnT?zc``N9 z{y<_DiI$l6Jrl1G{E%q(n6(O4@chYC&YEt<8?vZ!{{9#Z8zwoGH-(iq)aPyt8fpyHL6o_&!G+I!eGd|B`(yT59Gjev$KL@(uMK5KyAcD5z|ayexD*cVU7C^SwJbpspz` z!{~zV*k#eOeX9Knmlevm`5sIDGm+gc7Up>eNdUF>g9K2yZZ-pf94@xP=dumu&Cz3J zCsO-5e|7`@C3}wop2`2b?7w{J{5$)qhwCVjs24o1JF8In{lSH8X}0DGUkZ7h}e}nzrkI7zl*3$A4`VWa_flo%I>&KHb$C z;uT7a0g!i2;at5J{=}J4!kk`2S<)4Mghqer7m=R+Mf<)k(Hrh`l`)0~48J+?G|8lU z4Z>>^56T{W?3pJC?)asnE{_^+JU6Xnx59`H*CJZP_jQO!Td7np>)M`~VRrMomeksqdD-}!5-xjC*gjA4g zi1All@=Mm1#U%|huZ!!XMDx{T8REtpb}k|%M$Qj^O4r!?ux>e-NBW%pQ^~&ZU{1X~ z|CCKJHpRK)4BAoE^iP!eKes8}3)cA(c(oo;-&5XCgG79E*xI{QBysU+kJn;Rh>@?=rJf832wo%0DL;6LzVip=Z2CyX}n-;rG& zh{Jo0`n^I552(W#x-LsQq;=SR1{jvSmQ(~SjIWtRO6x+kG1sBZ;(DDr9j3VVx{okV zbITc4eoh(jOBz}}b&WCNeUkH+bis<%<;b{<>dAOLFhFD=4Z@Y3N7tCm3)6*0j8*=D0bRvU8V>T);}Ln31R<2zQtJToL(`-N^#|I- zKg`8!%}*NV&QCLVTN$isPbVs5-6p6Bhwk1z(OG53=)|Z*uN@C=(<3roF8>%CV4V|5 zvYRi^BlKQ>ACmguW7@IdgP3$xrA2?emM+(JL2iyeJ9^A>bxu zK8)6$vdk;iQhnl~O5XD)`_VxLf7fKjR02Hb4$x<>0`|5jmY~W7QJhERi%k-J8O)(~ z{#wL-U38oO$V`+Zq+y!82tK{qd?vTzMywD$i@72ustPIOVode9h(}wop+eM=|J%=aOLVq)Ilg$PbQ^(iq@omSaawI@|re1(QH&=EQ$wbm{slbSEfsq@YqPq zqvy>hPoWg0C~)TOrwONWQ_2EXo(Tf>I&9t2$WLv51+)?da|a6P)p4gkY$JB ztFDS#dFila*lV_7AY(x2D;R_pt5#-}t!Tk7&3q<8dMmIE$p zWG2CdZdoSim_^TvvjmyAC7x!raMUDQe8_6<`vlI+W6$}`zy8Nv&n>m62-pJlGHFzp z2}U!jErkzBLo1>ElEYO1^W4JkcZ?H>hsu{8t_9eqJuhdNRwupk+*#Uq#o#{M?r@w4oZA%-hGOF?T4!(}C9Xa2a#dO_;_|83G7- zvbaVp1R>@$?XiMh28H^FUjMdjqsw?Olc z<=GH(arL`;9*pTR;W7S7zpFc{8l0N2_Y=_^^`D;l(S^rs1{~@NzeWmZOTxT%jK(Yk ziCsG@qgqO~c$cnvFmfHq*r6ehaN1khvhHt-_WTqp=ayei`xFCHi+i-eqW$Z#u2DtS zk>Ek>sQQW1S~~pk>d&WV3Dhn|x#J#m72Wp+1*ap@P!3wdE}D`H<8+k?dciccjEfXD zk`$->7|@y!7@?Y>c_Z=A zo80O>h;cp)(;Pg_OA&o}u&vP2gY^3)`~EUJO4KYOtG%kD!sMg-3+~R{HjQ-KmALs? zr{X!f$nxe9@j0Yl_0dN{3*Ti$6t_v7};JWo&a<#U#lDEzCa)0l} zH|lg*`V=70SzHS)@b7}8m&Z}3m@yb_s6N&TnIqb@_)=*T_HC02nHqoACvwzBie4M9`UNF@bNXK@_TC;zJrM~Z zr4i|*DxBAZIL->6K=LQLk84}!%sb=xi3gVyVur=lrRGw`!c{naL!~?ekZ%Sqrb=WA zBZ2i>Sv8xJo?7>Na8IMBCmnE=)O;WI>%k{oNv*FBGw_mFZUuff*kHGeXTePI^bM5Svof^MbX%OKGiMr6D}90B!DvAtr+c3bR;U(*B*@D#{2v$x3?tS z>C3V4lyoC;8HjHRzD}EZ-#Y-*%d`gv8Sk+p^k7e^5r z`JEu%dBXZ|7u!~Y+zF3#u0IEO^9zdh!2SHaQZxJ)V+=EU_>^>*4OoB|40symy!*{Bfm?3=a)iC4 z-%*Gx&(?M#2{2_xWl*lsN$$O-qy+fj7dOAl5P(a%%C>lnze+5}{mjt179QwMSmyUeCWNe62-|9Mv5U^QWl2@Ux%-VDm~a$1X5tUZSuF5 zd0aDX7X8XaD`vg3T;5QvB@Cr&cNClC5eD5!fp8)Q=NZt(9H>{G86NUi- z>1ZRO{jC!!RFz_VJm|(C7U;9vmDo@rv~2R{C#WJV_dq5NB*q7 z*~f+WH;D7KP?g{l9CIxY8;Hp1SuU~Iy{V35S0fFlaHlMJBBBl@z|vX(OLA0o#OO$= z6jFNBRe$~23cc%)6S97nVA05uD<&UFEfSEFgO$h^+b8=F8UY3Gp~IW%uC;TQ(^dI z1-aB%YAY84<5cZ%m^|j9$8d}jT5mlZ;T~Z`NP&c_c+I+a#1;p{)_Cc(Fs@c)yU+gO zD=bFZxjV0jt$-jDD9oj^SRR-uJmP+z6iH>IT?T@3qwq#HLFiUs$aC$6a*y`&ff^%j z6K5IpyaOqx@&a=g2FlUv1bW&c?%tG1l2jTF5~##MtT;-!?A8P5PxD(AycNDBBCKiQ zi}!7FGQPTYSuF)*hd`1bY@Gx0^~)Y5DNHL&M%pZ(s;Y+|b`V|>-Cq!<1I_*h>Ak}_ z>K7dxlY^SY($07fS^%jNYaFbpx=o99VD6036ZiJ+6acm&h$fzXoy9t@Iyn}Wa#xL` zusQ&R%|Bh}zuc-^U6HV{(U5MZ9!j5*B~PislV_KsnZ$Sjmjf8;-Mn~)6%U(VQD|AU zSdrr-s@W~D6->H$z^Ye6=utud9mjiQKOm>BI$1Au_o>I0aqNr(O4SSSPqCby+6cF- zSL_9OfRhciX63KkPk`%J%lS-24oPc_;Q9Fz7Sn_K|3JhOcT{&p%8Xl3548MFY7C2S zgTHWo*qXCmZ_E>u4Bm2iBgvc?qXM%kCg0=_f%P8>ul>;NC`N0f87JLkJr2ZH18GoO zaZEFbu(i!u660UkqaDPTw9_VCQ=O*Mxi{k+Ue)kTmFR1jAi#&%8h|y)jcN>LABS;fFFX?Mn+gn~OBPSdLwNA` zj16j<&IIiql3WL&zC=e)m}lrl<=Z7tK@mN z8pU@S$G5Ydp8hU!4@<}RH}jTcSJ=mbIbS*8?4(8kF~b1qNe2Z>ZT;YmG>mdh_yEV{Duc%LFQrA3+vx#DwWC*ayVQ+FPCZxeo^cIwa8U|W)~ zWG0m5&F}uRk1AsT%p_bmp3vX#`VR!1#7eu2I&L-n1N8xRvn)U`Mjebp2z!@vcOihD zPo;+e?A1S+7!SOnl1>by`u5uKX1Z`!OUeB1R{ZwB5cMCw^8dG|{7-mS<^S_c89mbm zlx#)$#!=IhTYMm0S~Ec=mrj{3+ZA&WW!wLRv{U_?|6d2e{!gyX|NovnyCfqVsvvs7 z)*QObuK(;E6` z`!9d1^-ECf^iMWHh5!j#P7$rIZSLok5{Ro>F9yUpw zkRJR3^A0V8mQZxfHcy;ie3F&w-vT5J1oY_H5?Z zPdC5~NgLR**9j(ku62lx3<+>epyTd;h6ueCvEVtbA- zi+;cgP)^!@K}TQ&%F*Lm-K#urSgkZFZ71KdvC%)Q&cWx9NLsSoV#MC_3=6z2Om5LL zY@TjA{{zoz3E_vHB)9841n3em7N0Hx1GuN%9Vx`h zPU*Lk%$DhkxrxIZ50N=Q4C@Ju(EF{zRk(AZM?+`AFZKakOX#zyPt?H7`mnN&9v~k` z!Du-ND-v5`R)_z%8!!SRM4zos;B&b@A7{ax)e7Syji zU8C%6ZPDVT;zgy(rxKEXnyZDKBJ1X)F5DZ7sB}vDc+s}E&j3PTajoN;6^2$eI4rte zugGf^yrU;~%X?iHxt}fmz{ZKT57B_R!>Km}jG4YsF*%?&r^ecY-4gkucSZGvZJe2( zPzAE*s+z{X;Me_FCQl4H#J%C-)H1ft?Q8uE$YydZR?oHDn{5fhNs+}u^fqdP5sUNu|_GjdGTVrS@t&bmam`C z)0K87bn;Thf;eI|pL_NR0|MNj(2B#qGg((FA6^BLGtx})bzWwf#~Z|+;aKKaE!eEU z|M)$ZT}_I|FVS2R)*Zt4K_tS6nPH%AjpL;z$fl(8_>2K*7;# zqm7w2Y;SMhXYtIqk)#boN-fbiXy0l;9eUB$NX8LIMkP9ttDwsX(Xy5c-RuS9$0J6k z`~oIZZR%R9%)7au8@N!5W!sw{hMwf8$;WM5vNF#d9`6eGY73`N%ou}QY}U67 ztKiz;x6^4~7sqHVRj0ou88C$>>9FHwexD=Upr7E3Q^sKtf~28yo?$10pwT_IFI3z- zgM*yyZ^>ZIpH|f>y>i{soy4lEHilhYanCY>O09M@uiTyKs9t;E-q9D9dHuEMt{AR9 z3~ca{mE-ZZWH=X@*O5x9E*2W*VPlE1K@mnEs?{n1%}(1wtsee`?|}}_k6?-gYROP3 zRhCQ32n->*Hw0xl>>!5XZxcDGy`-W;M`=acIzJJ2E#1`hqx*LHn@q{G^E-9V9!Pk> z9mw{;L9iQ+{q?Q&{Bp!%CN(89T08RQ2}Reb{{>A#49CY)LA>UYJ|;9fs(*Ji1xkWQ zjSu5@B>H8+A=^FgK%r>Zl`-~Hd-2LpV(<3JD(!T;xPKf$E@!90QJ%F~_My_KDv9I|gzSR{eQ)nd zv67H(#Ku`Th6H)AtJQ>3Nxic6Dd}DfY)wust1Vp(WTc`q89H5eCQdvM6d4w11pUoU zxTqBvXK_eH)IRRxM&~_AwNBWa_M%-kXj^eR*q1D)FR=7aF<}~FpOQ?e$UTw)oMlYa z`&t%dX1t~hdX|W7J$%JnVyq`0;Yzh}G^GQXVp4H-KTy@39M5=`5Q{ zS6pS_pNT(aO{b3uwSp5$fgB9y;c~mS{))KPa+2oyA*Q32x#V9&*_c+>d(RtV%>*=H7910ey&WltcjzTp{{gUv*Re2%L5HV zt02T_FvduAwDZ{zmc7ZgqIJos*ZU8%jx}zN6t9*1pV!K*SHQl|@RV+wXqt|jj+<$; z4xb=scpDk~i7j9hWL46$3lM0*mV+GZtC-jRCq$MjV5L9c=S%my+pTG(c!$W+TitY) z7{or~s68h1ZkfNTWgSs~2De4P{JvPt0)4GxUl`Qgfdm`Zv+*+GUmXhQ+DnYcqrvBM6u&oc^8ssH%6#ElJw8@cg z8}MnV0LTS!Q`;KpkL#iuo+bO$Rg0}~@vL0`zG1hvzG;xo8qXDggFzEbpWaIy~Kpy!?;q>z>_QM!G?=|p=8;z~?WS_2+@|*peLJn8@>M{_f~S#ISP1NHZ$^^U;XMZ{|PP zLus6TO?nh;tPpOvD>pcKDt@X=o^Lr^VcxP((@KY;DAf<(yBo4umuQ!e8spHVV;|pV z%S-^>swbe2$ND+2(g2a~6IK%CK3wfb?4{v=#Af*se5+unWxM{{_L<<*x!dYj!TFlf zN`dS_u5h)#^|~m5*nmG`h`Clh`=|QKhWz{B3f&~yfHf}lx3Y?|6di^j*|(&rHIa4y+l_#p@Z*s!kJM!j{s;Y=N699Dc|37RQJrZTlJAXX!FQ0eicB+FI%W=(ss@I?1LiC?e|ABApa%H zeCShjViD#svah<@(d(^jS8{Li@^XIf#?TXA-bnrcbCa*rBzEjQtN9pVbnC7-+o1|+ zz>MM3#m_CM*>{N50M@v(Cz7@fQ-0nL6X4(U&-F+y3dMW=JQsA)e5 z5IxPM6KQ>S+s1|^zX^uxRYnO->CqHWirn+r%z*)EocVbNr)rEdI^AKlhy4$iEH1d+-t-@IXR0822X-NC)I{4{^N)8Fojo|S7 z0|k&Lb*J(~%z*rit#Z%eq4EfC%_SxMD!3;@-5`VQJ@eye?_p^<8otr) znns=C^raXJVC2CQNqp#m`&9T-11k1itG?UM;Vw78Ev0HL(j9OudLVWmw4DQd-M3K_ z$ItS{`Y79a5)C_6YwmXy?5$~&Z9Hjuyb%73w5-V$Cqj_$RGTdUbW~ZxfHI6>bZ{hX zt9O&B(769SFAlq8L^1kKv3-~AC)4OlM-D8PS3hYO3Ho@)E!K}>5UFyg|&y7Vs|ZHZ5a}39d#z zq-VLDU!s`bPy8O>hc2%b_Pj}n34bh`FoEoVuNRITE1 zUH_5!TYUzC1DqH4J7cuXh;DVJxpd_S>EyMjzxkZ!RMKTgFx}Kve8NaZ2w!t){eCllFZ%?yUD|1J_(D4*fg*WM~tn zI;d%l^&!e&ohM`}?qqrWw(5l|{>7XT;T`>qw}TX*(dTOILQ!@*l?{hR_}*9=t2Vnc zoliATd`c;34KYR$MtzRUvs|jJ(HxqX|8v1>yTU7}WBH1iIJ}u=?lq){B3L+6`7u)H zsLf^(lB&-VR>qaEvbU+RH_QEqgf6eG``#E`X71Kf>ti{s#yr#I)1AiVcKd}{r9?WN zUdeAGf*gDQIR{BO=^$>q+EGAOaPOxs^GVHw6JH+hAaZ~ftgGSU{7pTH!!}~ZGt{%;L89fH_{o(b$+=5M zYZia>z#~O_64R)0!Y{|l!pQzu{?>LBWutr96clUUWpAgA2eir?Ns74R-(SrA=fnAh zl|;tI?q!RH*flOX(52`y92^Kfm=?FHJd=D8g@Uk@_DYK%_0hc7UxK^73Mb`ffecNha~(uP-o-*MA=@iq z$-7h}kc87?LnOA{<;#ZECp%5=H+1Lf!Oogmd@wd6B5lp*YyY3$Fqz)}z0BPphc9ne z+nb&lSUz%eWfxu+9y=cW=61qVaG*yJqyvNng zOhg(>tLF!tE|peOEo(ft&Z%1ef$D&PZBfGYxo7uRf!KUC8%Z$$PCG4B{!gg!e|}*9 z7XJsJhWDod9d#>XgI(Hc2ds;cf0+sT`dt7N%=0i)ivGzG_}iz(n*6q>DJThfIOj`d zV>6ZQ!hawdWiAZxl*o6UxjCa&rKzLAa zmDt&UqC@PE1-aRBHYQd-rleP?fBH9k`0TNDLh(`3&gsM1`bxi%vfzeC@Y$dWqr=P& zUXjP&)Y$qxup8I(ip8Rhyj&dP0Y9(u^KqqDGq3;V{I0*1_U7P%(F1o1Mk26U=fJWf zN2kR-h~(SNG{k*Y@x#3{hsA);o{aEkT?8jdj4XD@JWtUV@eV{0IZpAPxxT3PKQNI< zkw^exE&AQ{U@`wd1bxa-0c0Q$1VMzciLykof9kS~>yi87z;5vkaq42lae#Y>J91jT zXXr%&U$@KR4Z4ZGq*@C!LH3_WR71V{82S_zPfuY8s$}K#WcKq9kD*;oT3N`p)M*x!mZY~ z?Krm&AfEvmSdY`K5n2PG{Kbj>WIQUsHkqH3(!p-is(18#+~DO=#q=U8g!jY9NzP-n z$A*`qyRhgjiax%>mk{?I#^{z=T2I-!CJpaO8_hT522oxup7+z_cmOQ^Z)E$}4N962zoP*2Gyo?gU!EsHWWC2gsdxI9*11N*!1ySOd(3H=uosLG zjFm=54RJ7`Bb2KTHoP1p`j%^D^mI!;=Dui1SYa+oqb--!)_U1NQ;DO4{o>Q_=C`(P zfbxQz4N7f!PMJBVI>w9-DG?9Sh%D0q|GyX&{MyDc}89|R2O@el_Q zJEBhJmM1xX!M!8DD<4*!D=-8Y&q;8-1(w3wsTfL}c^!WD{>m@`Mjs%27Qa$JJ8!8U zWsndgJ)>*=LN5)4SSw#XJP#P}*4uk@~3b?HgJ_UZFbN$X7|9{_=sKp|{+y8Ne>6DR0N{uDw3nzc50D2or+5 zy{<XzDUuU?1+6g_KitO(E2`Xh)_-i~PQ_S6I|+id?nN_Pk;; zf%B!DduNeI=aABoIB4S7f1(|Do&gYCv`0^N`s4bf?{fXO7&g$sKXv-iAq*9+oJr5K zkF}SSG)B|Ks2`aC=1c`X?(TKCOYLBySX_0 zb^a(<{f8z_2osMduSE2Fr9OvkM!?9&vJ>!EfDQXGLDV^8u|mkUoN9>M+Wi!E$%Ajq zJ_svDAN5DpPX)4j_~&F(2!%BU3-FPK!}+8t87pP!%8*!0~(iaEz@nYTc@32`Vr0RHt<@VBsGKnYqg;RNJ&}_q0kP zwMD$mFKj*?k~pv_fWCD>rpWsr&#)rIV?}GSCpcwSz6sxHJ$S|)_I%#fPslR8g<5T} zerbJ{9O7-X>i-W!w{;|&qwp;)Q`0q6gr;}7C6J3GoB0D{@(a@9p)^)J`GGIaNNf~k z=c^rv|GLLjV#oc~+$$%wH=;cvXKaQKS>e*2>{+_pdJ-Vo*EoNQkv!W5nXUl6PJ6_V z^th0+Wkx`+u{Tl>BLEidJ&O|&tI2;7NF{RW`{cDxhg*O{4Q|2MEJ2Ndeo13U|dye)ZTX7!%aJ8m+#u4@*_xwfM_s{N=flpWFP=^)}8>Vw{*$ zdi?E{yUQ={%hcgMX5`Oz(v_E-Bu5rqVtHg!_iffxvysBHJbJ>!yQD=uN#DlV8hOw4 z`I~{z8b}IQ_U8zTetCshvVVJ__rFmHfIdNb5d zh@IOcMc+etZBCgX&)z9>uBDQ~e;sCc-gGr~e+nro7U-A^hC(=x}^#Hu63Shq=U8|zC(6U8ww6YS$mVeqZk+Hy)Ek{d&H{~mf{iQ`a!MsSW z(PlXP8VAWa+`pE04O@bFQ>AdQEcM`&Y#hF|v5Y>gm0t5H@g~!~(y4dp$%e1`Ws+ys z*4XYnp?rI__j6zW0aSO#Fs8rB@|{fe33Ctsy^)tykUDu^f4yEk{rBshZ&wpp$7+sz zd1b$zwC3x;r$O~UgdM3485Cv!v-jUE>)xTZ<|)MW;ylr`I|qtjth&A+&Yo4z_;;qX z?mVW+I^bvv9M(4+Ohy7%S$Wngg!VW8oW}6)uMbQULkp~woy61nLk^B-K+r$80+`cm8=JZNs@~cT6jJnY zLdEA(V*zJ6KLh00hf^ShOLj%rYEvB~Hbq8C(2Np0Q zXW|kKZZ(Swyus=rx}_hVB;S}1Rk|=aU5I&~ty9ISP_@*PZ$gCikYhRSh?6JNzW(2R zic-G5d9C|l61ONBGh}f0H860-3COIh2VD7M-rB_EBQFMRky-w47jA?=SF5e}qy4ybT`m_q z-dKo7TgG>RM@)Ar%EU;g1^-acAq(uu)y5+gb0YvO8jl9sb^`D2Q>vZ?{n{-g&^?cJDMnF8M{bUf>pSS{j~?neRb4N^Uq$ zJlc`8M}AwJ6_Tgf1%w~eC!pHno+ED`_a&Acty;u9StzC8`5?+^qysm1H#ZhEjrO`T zKnV;1AMNHt(qvO`o%tlWHq;>Y{oTu^_lBYn{UR_MxfzS)kYRK# zXJiE${28L6(}c{QdnKDmkwoGmn8}KndRbtbJuvCY3k*F0#0D_YkVkN?Z>}1kb;~@0 zANs|#pM(;|Q?z!SVpkieTjtk6cyzaAF;7z-(Zj=56bd5_P=P~dxW^oLb3Ndl{(Bq0 zbc+k=p5C9YQJ(V6*wB|f{CUCmpwTJWS!`U<8pL}?wQU&bNTkg8BeWSY9&u?%ZXYD> z>%Q1>8)7{z+0;F@FqW`yoz4{b^68hygt9$>K!WqlC`Qq%L_a*NUlX!-Cp}NqBvtp!5SmY=%xbL48EFkZsJfb|hgGXCiqy?8JN#Jo@uf@YGNItpkp; z{PC4?6xBd|>cq!^dr&2m41e>*?!!f zAj(3&UB_5BWhX}_m_945cM<&aRadOWvy2Z<0< zUjCi8k*WhSLx7ALHdr5La|cYQg0{i;Mr^(nRJGmY#uWMmD0!7ORR$U7k?IObg$DsN zp##IgGeRqj2NZ=L&EzdS(J!`gOymJH0l{~plmX$>)@Z1v)(AJ zh+8=*c{keh)<$$I@^W$ydCnK#@gI%6tBGOLjy|_4WBtF+#7|(zh8~T*Kb_~8S+OnOyPlJ8QYo(% z`f3(0Zz=8%tv_9;Eoo|Misy3&Tr zjsHN;Sr=~41OIG!gIt)_+duu3*;m2)2in_%c~ad1Z4MB4ajWnb-U#kd`FzygRagJn z^Ez9hyk(Mae?c{oZ@OWOJN}eewxx{6T=T~oF>WM)npqBQN+5Gm{Kr->^tEf=e}iZE zIy)OW0INW0(Kel_k?HO<1B-?s zGNOhy0OV6^bM@TT>aXMP{;<^QsP67`pl1!8h~3mAYki zwflK?>KS?7rCQ1E?>dz2BG{J{5aDjjgVHz`mM1_7$e)E$!46XW0~MErO4a@YO#pNj zY%k!&H%9^ecx!nGV-MqpP>sTfu$&N%aiax{_Vc!>8oOgXuX)7=_nG4M*Xp}?H&M#V z*E}UU$!rPCOw?-3_#A+ZH|7mGaNCa>-y+*djhH+x&w_1oIdhS)&9)__;V(V1(mTaCH?L8{R`v#vjd*gV<1*fr_(^md1g(lRW3Y7TA^*nRBQ&L6dmk zq)5n4D_BXT=;&`>as7ACwiS4J4Y%!jNAZ)6PKNE8`<`@!X<9Yvz5+lV`inWD{q~b} zzSDdZ{|YSX{FgB#_hxvpegvnaL}_Z<|KpP!e0h)~w`6U)-Gtdp3Z3Pl%CI3llsQTl zc{4m4!?Kcf4UyKHF#isi5Ecdx~`Ie(7{$D${<>l0zDn4l8O!)1)9dl^P(As~;!-Dr7l$z%uYz%B=# zmKA<}pMv3dpwC4r%{i58|2nnd5bxY@7|V{P-}S=}o8J^iAG?=$_0ve-`Hif!Hv!3% zqTljdy?g!RYV~JlDEik%49Uh@6f@RD9vy};!zSFX%>Woot_pU(nDvP@KnC^}yH}iz;FF7>f@#Lx}I5etPKmUQ;QzNcfVljfVaSrq-&fyKQ#~fC5CH-?J z<*|+{3$_m|PQRUc`ZCRmbm!_WFLmj>L%h@sYw-wXh)3k#pB=`sE}mTGiyOu}wY9Xw zbG1kEGMS|a4wVS9fr@Y(f=U5$9bXZ8#V?*kAlzS=ir(N%_*a_e3Tl&?Z}tQBbfse^P+s7qEd&>2RE~?ssZM+2?{!;gdO|I!hevX#^y0^;=)Ytmu;;~ok zDu99|CQPtNeCW<`=Vz*^t!??b)2k5rlZzwSn^H_UvzVG9+wVX#a*9y;vO@seX1@h2 zK?-q2Yy4-FF9y2aVZ|Ee7ap~sPkA~b{J*#+fbQ$HTXf=upHTBgKJ-2nPK_-9bt5-F zZyy&@cxD_bjAYJ)RJ4BLUpTP+NZ#Btce2K#$1V1IAlun$@4{S(45<3+huJy&s4()# zwvUK>+5N;BzX}^oZ?-zEg#{6>?sYcTrdQ)nL6|h;&EQrvmgX)7C~KZ0XJdS%|AAQH zUJfKnj5aCw*m=*>D?J^4s@DTw=UZM&25Ght3`LWII8txbAnrq)#8_^OI{I!WnP?Ek zfDwRIdcO9SWhs0QH7wC5e`qt#P{kwC-@ z`(i(WV==k2buny`>U)uFN|Ws$Bk=j+q`zgVS8`HO9Wh}iyWzI@AiMWiBUEP@gIDYT zsbXd@TjpP^-9+kf$m;&2+q8cu+bC}b@LmJqh5!qp{>LxbV1{b%${!v#gbRNaJr~?t zJ4o4v6^i-gWt-Z@1_z0l?)TZ;wX5u<9m1~V(Hj3ihHtYjPh$~Oq-eJbizTSyXSipM z&DCV@5?@>N{gCdAV)ACmaQo{@);#{&<1mgnC4IMCSiJO~UHB5{hSGX8=5M1{uf(4a24iX@=EQQkiM$A9PaMbftbz(#E2fbtqcjd?E*habif(@-4_lLggiw=?-SdUi5R|AXAxpn71m ztuWA`WuI{Tg64k~cdv(5GlH$)4R`2KL~C>B%ZFORttiJR4BzeyC5#-h`=k-Ykm_$- z*0cmJ>26CK8=UJg73QIT&h+A?Di3hHR0Hd(vR%t)wb~~?Q|#fuh{{RcHjh=GcW#Z4 z7NuafA(Km45)6q|ze?H1~*~Nh;u5Dl%wbd*hO{o+06A0775I%4%=X zeaYea#ZsA01&3MAtC0p!sg%fzrijV<8q7VU_V)O&y@@?Q+6afLAnc#+Ftla-1nNH# zcL;OVv_9bYOec~ssyiq|DM{c3AT+Sy)P!8SV1bc-a?d`&h6v0AVyV`-OJ{FPjtf9c zU6Sf30kuM`vVsREf&cnhL?2#T+X8^iM|9;R$Y?H~{DywG)D3tN86*O(d*|4BUT_>OWS||6D$iH&ECgs3o(6~I7G#&4p&%HmA+2Sd-I@;WS`phK;FSnAlDHG zDuI53Yz8QcfY2>jZfND6N*=EQxYQz^_rur?jnJvjtInoZ0Q2qqY)2rf-z^#M+5$*G3 zb_==zO!=*YU?|7<(Dilp-%ligp2S^EX;b$Hg<8VAiI<;z_)(okOuqK_Mib47bQvy? z>O?03r!nqfaA1P(+NQn9mO*<0s=)3~lA9S-=Xqe->n$KTK?L)k(yHyhl~x6H+>GtU z>hX`~+D#hbOO03zMRiF!fC0cm3Q(9iBm}VefC4u&Tyb=ZUF7nyguXJ zt@#zi}F3+n62MHe&{ZoebOhJ&0mGQe^2UG2)4$$ta6#CS>LN|~Cs+-fYFTSslHa;$VtW<8Z7(VT%Qfo;Ndtw@!~8po&EQ^S8lyANgkDm-V{ zO9g#u@{MiaKcYFzL>jfoJ)^nlXwH*BVan)`?K7ZlAjS@J;`cp-xDU&+z>-g7#PNTT z)oSCyJX&so%S!JNbv}3XfXg#0m8|0;)T2QZobWo8m@R5iz(2LI2x$Cmz^hRwy!!4V z1w5Gw`(qV%xf$yel3WoxaHWplxI6<4Yx!N=_0V?= z!JK7P=|eH_@}-n2=O>o40oG))VHkyy8XyOwiUp4e zJ9W1Wvc7+gfBpp3B}OJjQs1LYf?gfu5WV|^5#B8%_n<(Wk#2fO*bSDJy2!RAQvH2r z26|{tU{uK(Lwsz5eefT&4ZTSrv_1;>;9^v2G>g@akbGfPQMOw@|)4EELC9i-3b(JzW5;C}KUBYgq?N{|c0J z*vRuR;cT&g3d#t2i_>RGiua$9upuz3r@|6I*;bSvV7QR|30H=+5GpNHBszsc+jR9z zR3LRs7Jg}ymJwo`_)(0}=i68C2p_JrPq8V1epnH94R-EX$fWYyeEA>fGV8c+35y4% zUFq@T9I162P@q3c*zr#f&}}&m630(}t}XCs!ZG+c*yq%aoF?HC?5;VF(JtNe;NWhE zGFy~kDgfLLDl;GgF>0;58FB>nOlv7?c0cjcEVq>eDx z^<4=Y54W{%`2w+)`PZlFAML1Q>eO_@6$wMYH-*DH-PV8pllHN8oJjQ-YI2FcjfXw0#k+sU9%MxB&+ z=RGPn%Fy!x>I*a6(IpQ7FYDgu zCa@4hdH(vjYUC{?9Ix(ZT6nurmQ-jpJQ2ndJ-2?XgK1p$E{eD03@!!p+ z=AQob)x7I zw)*s6%223Dn=6L;*xESs-OSGS5teDriwxF2Q$r* z0c1vcjP&o7P;0YEp80So- zdKi6)F=}p-s_t>@8wI-#HSzWH^}g5!mMAhQ5LyZq5K2hhh=_&0nb7j!GSM#X(-trA z{K}|VsKtJPjg21Azzwd{c%~GSoE`xAY88y!bz@`|0;_%9#LG46=k*OPP2Uc$8Hd!A zr`$2SLiOr)C1+C{O97CWtu|KfY^@B>x#y6&x zr>gThw#l6q%XcABzlEr)vhGiK)NfAi+Y|Q|?!V89E7fFGYo%I|y7XjZ&XHYabKgR-26?-XsWJ)#|T&j?HG+ZDDRgzM{57u;0wb*T6spHn%K{tIf2>ojPj zvsWZ1;yNDStFz*kIL#Z{2|~E@_Ts42{0YT~Z?PAMw{*w#otUl%Alf^@86i|v+`zsX zMPVbI5$j14u4kJ6fPO-NFlbpP53bz3 z8HDVW&xba)Fek`c_ZB^f?bCU}zwEXV!NomP=h2@+zJ_0kRF@)262-@YuUXl^%M6u+ z#SCN)p4u)95t(=_c^)9j%7d*jmh6Widfca}RRGFC5*zhXi~uwMgpAsh1au0|iyt+n z?-}bIi-st=4(X_UmF2p^CV$D(4aKZ3Nb<3{^P81%`|ax%zuu*#vV}QqL7PPfW;;WM zr?e`6c}vMMCA9PGbi#4IdSjg z_X!yDXW)7gqTUPhhg8kkc(K5J2G7ii$za%@RRRMt8wMBG&nFp{p~puudf=37+$yT5{VMFmZ^cg5vZ(JQpT03{rR8OWFC$Dl6$YViyseyTEx7YJ&xQJTD5tD~yR3453rJ#_6-YO4O# zcZp$r9W?)NVi+MzWUVo2gh9c>uK5Y$#>AZqyV+H>X3zM2UUfRZ0S;=#drD9*%u0*~ zh|FKy5q2pjyK>v&LO+_{PIwx-Ym|gz^5A!>J}|0Hr2AB^T&bKWN-V@%M5*x-Xs{q0 zO@$kUfmHTcr_fR|T1^$J662R}lSN&^Md0b7^ZulQhmOr~lUFusme>z)ve}j&n>MxQ?ctdWKfPeRb!zIbE->7JN{;A-bu)7v$ zw>B;BI?cv9eg3x1oCn#?4Ux~^r0sBMUz-^qFN1BR3pt-*l;1TqUZ)|H?t|M{@pZ&fd{xx`?+OK7VC)&OViwmGF^+~z zG+eARf|jqD4D+)|$ElCqGQWQT$B23jU+c=HLD1p7dY2{6(|&8PSi%okFYVwyLq6-d zDKU8TetRw^LnZ(CVyFbOzsunI#z=4xehZkM=ddPQA;eeDMRlNiDUVb3%x~GmNastN zFNM2($us$JUziqhCG!Vf1sFfBF#83zBQZ1Y6d}wz{(~m4Y*k28L&nc&$A~o@kMNL( zVNIfdgC-b883oboDY24_0fdbdRwJs#_N`itoeuKLg3)DEMM0xU#Zva-_@Z2nmA_(2 zS?TK!4Be}-=Z-(s3^Aje;_EqAraY9MPE;1wHY=y}-wxfUiFx+1@9}_>7@aN}{7Ncx zJQz68jUiwvK$bOdpo@wv_D}tzueb|8U{2opfxPqNw*SC#=SHoM(VLDd_^1d3NcanH zgkqqPkP>X*k6;&+@xCnBQ(wW>u$txYyXNAS*s3!@Q%H!*_;>4|RoK;npQS?@vxQHnb_DnGOv>-x0;Yp& ztT-ktk`D0#FB^t2Yiz+g7AEw^dRqB^svv8X;~d3Uqc)A>t&WqpjYgS}PH#R>r< z63wYR&e@$ehx4QSzX*>agdkG}+<1p>jk#j%#eYx$JsLD*yBnZbvZ;HEOu_a|jdZ6x ztHQJo>c8eXeZ^kvt*@&^U3;u~$SPK!EhMI7AB@ z)Uz-eiE2+szdq9gRNz8y_Zh&IP7xxPa)%n>41A1XzN*xAYN!Uf?lbTOczS;(W>V3z zO;EhvdN|@dYr$Qa_E0C0HjR$Lpb}}tRV%+9DXtH?M^eFn`>NVT3NQ!%SD&KAZn(tl_bZ=@+M`1y#b_65JQA7Vp($}Nx_4W#~|MX9Da;eEeFi3+$ zmv4peL=jf{ydvM&3)M~k7NRqY>d|luGp|m8oWUEL>eJ?5Cq5I(7lz){H%-=}ioa}# zMd1t!cWU6SMkL$JwS^sZxiQ7MDy^asMOgGm*+t&>;=ACq!R-zi^tx}Vu0(r37W7U{ z3+oUM)NyJCt}jRP+@{qnFsgG3}`K>3yS|?Beal(SX2!S2b#TA0C8}oD!BYV!yr{x-2!^ z0G-}btdxft@3ZG^E7t8B}*<>T3YrUQ3h z=%EOXdsLDczLF-b?c+WbjQyd1y=3|*L)0&Ee;VrPaT#ybr}sl293)5%7Ni;c z7EsEgo7Ma<6&C&KV!|ARM<&(_cH4*Uub`vlvr1WZ5b5d0iJ>d^`8M4a(mXnEF;8)o z>hzrl8Qq*pPHlM$vPhbTVa|^uUIPsW*T*vm{rSI+-{hemjms9Jn!Z(E^UQ0Fay-w# zykHzskT4MRzYLuKbO21OVZTAVP!o3nG${wWIchY%SAQ0xWVQd&DtRAVlWHXjd!x(A zf8ncB+J^5D7m7t)!|hdZbe7iS%tJzdtX~ovJPW9lt?0-ff7mY_6|faLA1LrC%3d)Bx6`GMIM zA%M<1TVg{gE2csV+CA4&_A*9y^Wz6LKGhTc1BxJ74?o%qVU~<-lb$HQ5K!S7x=+{8 z($LcAdxdz+rccu^?a5gCVV~imz=;BO=AD`cLBSdi?#qT?mMgb3qs%7`fFixJD7##y z;;3_Msmt3XfSE<)1l0DfGQ>H!aE$R3w5k_Tf4~Hnu>1`eNbE^hcT{Fn>MVDxqlnqN zLpK;*bJlRYRsq~kQ;)K|?)zFj4d?P~QV!qTaBccQjQx|KO3@;s{tRgRX19mf*Ayea ztItrHB`Kj&V*`{M!k&J3y~$=BE{hJtFXR6f&QJaK4kWJKVcUO~2eSkMZoQ(bZN2d9E>c3k?)V&ThWY;4g2)!yqSfdSKv(l8q zPB+ucyi#=QW8pZln|uYy5H&`tr=eXcxL>b2-~B%B1SPGoY5=778iXOqMP@SdQ96fp zbz2h*nxDf~I9BFjLml-aerQ%%i;8Cc7r-3^>|Ou&kE)LpFl8F(J>KvyM|Rt+g7|Hr zcdvyTmCZq=ls_#8cScA;Cqxl({Hur)ZoM94L+CFDCN(F5vR5QUa-6qY&f0+J5j+MJ z`Mor9^#X%GBv<+`)KI7BObBab$vDwnP2B9O_m=T_41}&EffAEl*n4i_Hv-|Pk z#tTcQ7n%nlubPKm^NZ1JwDjYI@WuKhNhpEr?h%AB(p_GLi9-3)HV+Mp*wG#rsrF&% z?@xj)E~;xg!Puzx>n&2?8f%h~Y7T2lNK8mW`%f|iGh`@u7AJFGF=4%alC9oX^ZTK6 zNut0F#@u9`n}MAEK(o9zi3wpe)n-#fGV+wYiholye{X76muDLG>w`VKV#QlN;8N(r zHzA;#3|*Z7-|t^!i~z}g*4PhZUXrgrf!0oO2RncKu=ea$)^};Yd-s<+mCuvj@#h8z zK7O+nzfSdbiMxLuUUazIe>W*CS99`eV|8s~o00Vct>>?f+M=fkw|zD(Lup?2wrJMKA7a%BB|gK?d=S_XJ0PyvN^EugBJYcWuC5HX)&P-mJI6>G=(kH1m0vy& zotHGtSfr(E%?V&Hh01wSEEDiz@7b^N52iTiJfYU%`u7L-7Lr$845~p#;e+R66I+?n zmDPDC_QC6sA{UcS=q+`_@%$rPoSl-HRKFie4XLxkbFoozh+C&kylcLfwBZ@+3RWC3*x=qmr`WxrTg8 zb$S?k(u9TJR4^!@zsKI+-Gu>jlFDrDBv{IjqD@WA-$=FPk6r0Mgh`bzc@oRNZe%f5V;y6DqzbRSiIHq@wCc?>_J5FrWxC zVN9f)!C`RQx8HbSn~dMb$@~?V%TM?bzcQ~f(7^k=hpGIz%)ya=pnzHQGLVBYlIvYC zR5IV?L$q+`*_1<*QZtbspF<-#|=Enpc8idPa#D`!Dnwt;bL(<4^@t2zjzS`9! z8yL;JTjq~l_0n=ZF_?NTcZ%3gCe5C2Etya9?p)xGxtM5qJHaZKk!*~;C*Z-kdK`zi zE3ITF^)NeU2mPHgtUS%B2lKe8!xc~5g~!|TWotReI`gydtLuquv@8+>R+Mu3pL-Gf zJ7>(_sJvR%A1&FHcVo9Xk(EW(fAKeX?pD)`Xo%T(A?g-`__5b@k2MZqA+UZ4UTcbdv+CnpC;ivb>@BWHQ6c3O_qhNORP1 zuH&-p!snK*LtfUiA}0w3%?jJtoo-@+r0*0(h^&o2272?CbGhKQwsGvf-q5VF0GYpr zVAo=w@MtnHiPY|2ab{!XHtj~S^~bg8RJb(?gC;%p>J2mY)+e`=9Y<`keBP}km~8C( z9y#;Av)Is3e#LqZPwAUqKGThz=oF|5tEjJ#uv4Ftt;Df3G_;v?bFAzUEt=$bUwuh7 zDoi#0*s?!Ai@IEoGc^B+KmrkHvXO8wWT+zc}tW_XwRo`P*(Gl6l&fKU{+ zY9k}RYmS=6Wa4t>DyF3jZwp_~42U1^(+A5(ScWxIM?0kF{#6xxX?Gq-EsB;^^C&=L zgQ(z@LXWYqKlQJhLqUvyA}TIMCX!dfgZd49AL|I$RTkToD0N=RZdjZ~43OaFQb2%% zv}V@ouUfVDxcI%uHEeA3=_wP`u4SWVXdS{N&Nn>1_ubEB_H3|LqtTgP-PVwSH5syVr`QQGKTTAk@Tf~A?d`BQ{Z`15&dJL?_VsRCA+HjC?n)Be12sd9s;{`Wrg z+(-85XR7mE1SZ3r-LAJ#{B#1g!s1D7!k2ou$4k%OC871V4xP+VmlwFTSkJmYKQCLL zT=|=7K!;TEH`Vhj)^ml~iH{;_xzh!GJ{_p(sM?wT?3X`$`=4rnGzdZeNTDiJy>Re) zUi;D3{eR!;SpS~>*Kv^s&$)&|CqOWII2xcnN<2?iSA#nl5N@UIk&@7FdzZ>pU?Lx6 zCh60!jhiJuSp1T9uXw|Xfg8|^@&XxO2QkY)sCsBH)Lsn#CY272)3YK(jJ&I~b7OCa z=cSgpw5w)w`B&!F4+j-yL%u~<7s5IOw^mLYrK+K6gz z;8l3oTM!@`>6awilXml~!5xYAv^AnLiNO#5F8G4cY8lPy?f#*nORr+jnoi2DKfjgb zEj9@HA@*03M2LnGS?Ww3!A=qadXoK#6c)1EB*F#DqK!#JsWlc`hrSlCK#bz}JaEJT zegiI%*0dWa!7#s*FybQ;WQ~<6cyN9T2Ux!UWIObB@Qt_WwkW47CfrLcVIT6GxcmKw zZGPP%d$;q2r|*q|o5@P&At)EG@G(**h?bJ8!Px=n8Molc-c9Bih*Y&t|Fuu?SDb)R z)sZM(TlYM#&CnIlOz>hVi22|+RFln_4S*x?DAe%?PPRRPy_n`z=zSf5=PD>9<9hN^ zovSoSTjdD5^CA>1H@<^rG7nI4l0{A}{_q$NEGJ=!b>j>rc90Y%X3k=Igt# z7K>9?q5#vpI$j(dR*?|Zb3m&XQ2DjoD-h=G?WFkY8`UF^g7}A;)Y`YDxt_5BDx6+W z(rIpg)&Wqv*Bpndi@>{gCVE!Oth2*;CfcX|8b>RRNqNxyaO8iC z1^ESWpNYbez(oCTDl!)u%e!|}1V>pABqMDeoINczZ-#E<1bFOK@jx}_6Xf}=<*q(? z$e}v3oiMs*bEdHL3&q-|>b*KPkL(^OZpN?Qr<|yxm40mdN^N*je`@<#mV5i#_q9;1 z{XL{>QrNs#Uxgkqx)zvpq!Z}O8f^@-Avg=8P0boTdWX6UqZZ1(m~FWx;ji^%O?BW~ z8Jb7pTvO=*(ZU5EkPOSg@0*TIc7j1kW^smX)6aFHKZgtwPP(Z;ubsSUA3TeH>U5N) z37l)BQO|SdO^ryN6j^+F%x}Re7VVPlyM5(eDMns6=XVkDgnrMV_VCiX_0PXOv5J&C z8zO8G?Mc_p4Cl7rAo&q$eqDL|!*LZ$!(|Iu**Q>CFR_57jUsK@E0?9#a{O5WOsg7g!*hR!`sx+mrYAZF(CfLs{k4;)avwoLL52XzCBcEviX%MB4LY zgfD@~oCI*xqNe8)+bd%dcJK8Lc1breniveX42p2x5<7|g5=OzZOO9%S;z0sPx1`wM zd*?v(f(t-OOzHQ}q>We`RcGbcEqyg4UFup=n7Eq}MvJWLM9gXDW=FdYP|ZxDxXDr& zhuLD{6H;Ae@DPZrL4(`{c`w2Bj9PL|$N4=y1+dGTm^cG53wzgjuD@0jNLQ(}F4R*vg8Ptl zQC)zKI=vfEwuEaxB*c5`lxqd4&4=3eQ+W&Mr-Ma29OUradbWQ6W6|~C{u~z4?q{+C z2~2==8U;9gffw)L;mIBreQ%8pVUB)aRrIrz!tZWlbuz65Dc7`GnfYdRH1c(tk1$e~x@pc{3$GA?LM zFrs;~fOA;o)Ax~`5^;a_y!yoZS7~xJKT`!%;SK=rLDpK;StN3Ma5`yWQ&eRyj=;f& zV^3Zl_Wy#G^{VL8_5F@>&?lXB+H;a}F{%eN@J;j?hO>6(av~&4;DY@;8uQk|B_&PD6zBIRp?7%9PB6~iQ95e3wi7>66HF0u z_4XQZJv{c;j10}&CnF1p<|2p7J7z7J53I%?yi|10ht-DAUP8oR z9O#38YSe?nlz=T&U~DTLtF+u&(vgCtB}DXov}l}D(QT%fQ2`i_hTAkk>=;r6+0@T(c9GHLxPZg%Ozx!U`{l;c|&~P$zxG2Qworlwtn!X$>^Q0lh zR(^WttK3&Z+-TOp3urV&65kZ@I%yt^F)sy0kpnUOn4cy)`aeD_ZZC^8$32EiXzCJ} zk92%__QK%_?zk z5(h#CuMw}tK!!JP zv<%o2ki^vUybka$B=123(-IgndHOgj|CjP<>T>o)wq;AbH>cq-u8K0!b%Xmgt;yU@ z-SP3`FeGceLo~A9BYkge?VgQ!dS}ihyisJaOQCXE09Q-+{U5m|RGbi|O-&*aG0mB9<@6YtyS~yQ=5Rx=$ANSm>A2|?#zI+i;m~@Z( zC<)W6+Ka3McUAF`kZ611$$DsoMOU>M;<%Q1o zEK~?VEK(5OzgqRKLxU`f*N6kBpgY)S)MSdG*1bzZ%ZtBwI>ZCvf9NA7e~fhZih~(G zWaJ(3is7m(34q%8a`2C3RgyN=D{Q{90swU9_A1*8PwiDH!G?8ZJo||JkB&yU7stcy zb&TF~iI*MY1APopN8yV*55g&oc$S0ia~iaH87BM5$nkW#YSpFR=?=REt;v{zWURq$ z=EFKUD&|#Y@0H6a7i1`s31JAu9x(j^ZkhAW@;1;3ck66o>3O!-^?8Do%-)eqZ7sQY zknth800(4^-X^i*$GgZv1W95N;nHRWHi?^L+Cx!l9+P=7S;a9j@OpQlI*l;jE3b1s z70oMO#=-cxQ>RLSaL|RKcVDUL4@bFWd)ZDQ%+{9PZgsUZY*wgO!SRO5g=Mn=V@z_l z>MgGwS&2s9SF4SM`wa&-kQ6$DIZ1(qOTRkUs?RQ^{`s?Cs2J>=yx%%085ozLAazG@ zS3fZY<2wgHn6$eA02ulrRj#^oNqQ z!4XB%iU;)?p$EVoqp$w5lnDETTW_#9u?_eXX<=*795A9nrAfE0*JtoM%(a}1Ac^L~ zD`6-mQuj2!npY`2&95obxV#tY?*c1oK*#KTY;I(H7NeZV6rtLYLqg&;Fq_S1?qnB& zaz0PN@hONbVx3wi+fdpUy5rLJ&4(a9*e`7}^`=Xt{`%*Faj$-@E;g9E?ZxfzUS>sq@g)(ltq z1r+@nUjBub=d|Lyx+UqcuS`jMBL7cWa z+)vcGiM|Qg?Eo}RAyx3*r0`7hs52qT2$4cFt(3&!UvEchGMSXEKVSy7;*Mx{e|DP( zp8Md+eJ>{wrq>UA1Uy<7QxoQfgF=Ft$x2=fB-PG-JwVMT86q*^sc49-hfrc<-@lVy zKxTA6Zs^KM-S%2zcCYGn2nFIw6wn1pLbDK=>36D&+cUt>^RC~YziK7ZuSM>R=oe{j zAGSo!qxtD*s6Zbxm73xz)q%3IJAbC?Ptb)?ebRQ}FJ&Tr*L2B#`_yi@p?!2VfASqi zOW#D}^vK5duE8+-jpE=RE37C?DZ&7M=MRXj30>NDt(cT_Mh_2r%Cj=>&pTso@@PD$ z7{~H4Tp2Apyk28+A9p%~cBpmj)S!QO2&mJ&+>^d;w`|AZj;nZyjUUS!k6VR(nAcSf z{#qZ=gf>+Vzx^FdgD2#6U&#UwJ6#;N)#FWV9pp>1@aR(cYqf@o ziuy#O41R`fbEw@yS49b^R|J(V!jK$(pi6cR!=>#Bf0k39BTJ;sD@uh9wUq{K^gPA+ z9h;4hlwmsub72^bUVzEKMz&De4?%$N$L7`bFgqRy+b9+!X&!5(b{6gY?Fqi%r##)G z_jc4okfts90!b?f4?yZHf-ohXZ88;hODjuO5V6|G){bw1r9}opKR$eSee*#;*_6LO zy@`ee2&)&x9CR&Y0}|7&fs&!XGBG(@TlcpW#4-gPPs?6`hP|Vg50+<{65BRI)Ogn< zvO&GM^MTz+>NX%D*peiUkV9hmUrO(9R#WCXV)q5jLZKDQckHFy76%>8spA06l`U(6 zh8vQ0o5D}>KQkgTPbk?z%m5rt+nsz8K;+7O+Llr8p?i!o5dZLLcyq{eo8xigQC(kQ zlgAxelv(f%1TV>tklfcj(Vq!hgcLmTR6JX-iP`hoD|+6LGrvEzmLr0WWL&*Pb?d5y zQX%CB5U=(-DRTKL$q0s7qFf=ke)5Y*+uyNi*V&{}OINA7(emLtm8bkV)rI%BKVMz} ztX==qANXzjR+wmOY#%gpBVzwcK&ioI%gsiKj?94j7+N;vF(1u~$-(^Rp8&g@+Bn&e zP}Og4?5<}%27vA7=G9uJi`DLf_7>bmvoAKuu%L702x7nX<-d7-P^P3%aa|IkwcC z4GXl_9NlUZjuR8)YLnDA-DJ1cxOKZA|?6Br^Nl>@DklI!p6PddmAyx8gzi zq?FHyEBM4HLNGyzl^=SFFh9*6)PHeQ9PP0@&c@Vw{nA3K^UMfRSm}lablB#}d1?oU zwcgEm(I!a<7B}3H3*(BpGmcv+$c*TlVy4w;bFL$An0I{t$5soWh5J6jr$^$3i&FC! z`e87J4;yl5jtHF3N%x;tzYh zL+m6s^@}^Vxu|K=E>Kp~MU6W_%)h)1$6{9!0Mw2 z^Ha~~%6!RLOU_%>O~3r5<2mTFNV{QwZf$z!XiTt39lq~Uc|spN6m7o$HQ+}i-^ksARx=sp7qJw^O^aa8@*hoWRvXS9)2(6+?; zjSb(WrHq=sSAcxBLvCfohBASyTZ-r9(DU%~#wOhr_u+tm4IHy3uP9G^AALM^g2U!U zDG#4XBc7e-;SgF?^JFc2QY^yMKYxdPS7k^jqt;WM8t;+(+OW(FaJ_q;x zw~7VvPsOtPZxxHg%s&;&_kSuDM9fIg2psPYQR)NT9 zW&3LlgbVK04f_R3{N*xVTAErvcozCuO&uqE|Ek>lgbLeXIw?6WI!(EPcta8b&KfeZ zNBu488Q}OoRUD&oGvx<<*PQ&=CY-;e`_*SSE9@s*|ajsaFA2*_BA({Fe92?!mG^OYE{uevp?J zPgSX&N3p$P_v+#{Ui^FFh|~3@j!XAxpFZdR7!vG5)@f`ZMM?It@LVUml#_#mZ*@$x zDFx-*x(^l3Z*TkZHO8v8-l5I*@?xoTB#67D+IIX+wM=C(*X9eH7Pv`A#7F|Da~H{C zPa5h%vb5dH*DHo{kUEZaoFwwZlZ|w(j%0@SVoeA1lJAS$gfGrj-5XP*!6tB`Dc5Uf z+Q0;VeG;m|{cQs|4x^ft1!7Up4^&IyYD`AUL(5+JM9i-pM@ieteXkk|J5&DUz}d#R zY6F}pj12+^qFO(39^i&y0pixfw!kos^NLHu;qO(u5BEKy)(50Z3h>mklwtcTK>f`c znsWs|+NW9C*2 zO6+DU9u+V1Jf-h6Jq9r76bk$>Pk&?H0<*oHGhmqYtcX6vZS|XJE0MQLoe{r07o!{wF#orxNXayzU@UAQ zOL0nxevjwW$J+3_2M6X^ZzYbArhF^<%M=^uT_gPH z=UD<70nmEsw@Wi2JwQc!TTAw+eSw1X+{Y(wWFZai0yY_Z)R<}0f+VS4U{`@02 z_j~H>bvO1`?{n#47<;C1`{0AiKD0Equ7WO-=}4-CMlc)VI;j+ME)vMUuRiLBO=7bp z4X#;1*r830mE(1@E%e%ol_^>qt9l9fq8Hyv?j_+ZfJmQ%7=wy z<6i4>0n>ZQH=8vDVKkwywASI%HTlTy1X2dUV)YmuG;%Wf(HF8g2dEJ>}n%z`w9QJ8o| z3pD*}%6Z=0TAK8upCN;t`&a#Y-!_G!Tp{81)MIJ}K>Cbc+Ec&t%{GrDeo(~3%wEAeh5W_3YUe^E9b@xVGr!X_*f)>8dPK2q7N$a_AT1(J( zm0JxTjiXI?IeBHjP+e>m`y-YE`%b1llOc1GjH|lVAWXlS(giA0ykt7E#VLhBUmJ71 zL@=0Y!?{hHSA)uwUpH>PNofL9_NRp71d5n82E|PRcQ^Sz0uqhJkI*xoEh*62#%$v4 zE#+G)&od_%>kS!Om_vS)g?6{tx$2OP&g6hO#}t7MEpP*`5wU=tJ}81F!;VNFXJNvD z+P)>4GmHX?Jcs3pQLn&ko_d4o?@6rq$bPI!Hw2_ZDC3fvJ&}_e876YquEjXo4F$#ESBPdn$11DGyh9xSIJd+GQdCf5X){{xuJXoQZlu-O z5M~$`b2XaH`>>cMq7z#MM*`6Cdzc{8p82%6qGfGR+%r^TNA2Chvu%ofsbp5*x>fxq zy+DBa3%3uJS8!4(?^)y3ulyQA1P}lRbhrkmpCJ)n^bTK)eoMA~#5=>IZP9^R^13(m zBW+wydf;V^NVrVBTH&WFu}25d`F40zn7SN-9)BF$07ZZ?5CPKV1-*8aaYzZYX4j(8 z$IenO;93B`M+^(!`(~Z@Ql2#2r&55R6zKGBCA?;3h9jT;ENXDLw9pUDTeftto83|7 zA@p2h*9r2vX}c#^!d!8UHN=vKYN`TE^dW)s;TJR_@A^lMgDw{p(pKZo^Hzb(I}dN6 zNq^JDj7LX?TMy!grQgN3&ps8O&adbkCK^5ts+Ykv;kjO*0PKP)E4 zCW$bdY#=B1zL&(um^s(iFZeD&9-b|K!7V$F;*YIKJw? zxO4R_<4#G@r%cA{dGEV{Q8E2StWb7mN$wtZ~^=UAVxG0z(){qS?+6pffG)#a%Pu8Wy8}DVUa+5?J+tSTJ@c7)uI8`S08IDvjr0K| zBmjUn@dt3V4v5x+czXZHwf-<^_HZ4)Ov& z6I7Iy2dLdKG9mwGb|U?&FZ!=8(=>nDLMEV|d^eir^*;6v^r{=cOiji{0U;x~4j^SF zA!8=F>IVRctDqqH7yaut;s*&S8946zKN`328 zkdcv5P*M3N`-d3+ovw(JkPzn}Cnu*O{xZ?g&@ugQ)73Ij zEp4ul0D3YKqB4;&13-XFd|8SF;QzM&V=^GS`uTrl{C`-#$gU>-OBs`?+D>myJWoAv z@v3Oe=%w-WS~r_)O*YQe6CoYqA`=$>8o7%DL1&%m5#DqMp7&A8&6Vy!Wd`(<@5|W~ zxP{-m2{rg-B6}yd&y#DZbzJS@d9*$Ql#MX1a0Teox&rjvKFv&Ift7o|tscYV@)S`m z9CmlqZB8G=8{no>3@>LqXz3KX`LZLd`&Std;Nn;yTbIc06@WhSmfz=|4?a1@6ko?i znMBJw4G*=0TSNN`NvpL5TC zMAKX!h#nu*a9J!`I|J@C2@UY}>zd_qnicPSlyyI2sysSreUHz0pUU_7&GkN_BxMj|z?u0TmHMjV~w3SnG^{#-( zr1a?}>5+`C$@F#GgF~Um=n>wu&r;W@uXnM|fYwS8w4Iu0%>ie|PLoO}@4OY(2&`CF zX!_W|SX!59E;(KHpcT~8y)BR0d@WO()V7AR30Xg*Sn{^75_D6D_fhCoYsUa=J`|hnT z4Fq=or{C@=zzBV61ZXWAfqe5ROOgdF4x{ioVT9YOt7P(?v#IUq0gZd z9i0Ty_E0=HL!w+K&oe|&g6yO6dG+RB>&GiDV-?Jr5Px@QkR_lxTMx}fyG^uAq z!DhW(HRz0$81HqCCy0GTB_^JXz&U+*o@O$P<{gP}B;Vvy@>TSgwcJv$yuo-UtWQ+< zL^cI~hLyPjP_SUV(cpm#&*($E=Et4z!3GU`#J%O>0K*7vU|@r&9JeyTfXib+uw5ie>T? zvUU;Zvdv$fe@@x^@akCNvyei#HiZvei?np{=hKj63BfXC;0y z5aDwLc(K~h&%B7OKQz&GXf;FaS_!$eOF&qR+HzeoZ!N`!A$cidY%W|<@Fi1-wa-rE zd1oUtom3y~?fl6`V-LBv7MISS*3sj@c;A!E_0|4Nx=1sWKmi)qdu()>{ORsd{~7aZ zek*aW)o_H#mo&wnF)#1EG28~0Bud6wMD_Y+xH1Tl>eLHO(PkbFZouJm0z=- zOzTNedCS9+#QJ7z<3m;f2rw)j#HVFI6Gq)>3_T77cUzSevSs~l%EhZT`WWVtLfr~V`C%Y@0takQA$i+ zr_K%~m#3%wAeHMf54?#D#oW4VASmwcZZakdXcgbdJ`El6{kZCQYdG%PGMMRTo$AB= z1g9NFwi@%yAk0My{w^%07-eRiNj#y#Uy{OMf)YN;ilEYop7}31 zqMa=Wj|kolaVXi+V$1NvR_wh`><+cd-SGKt9d5q3`zAILWhvxr5A^{5H1_dTNJDSC z$479PkKI`A`*O(eOM8<5zM$d1XODzE==(8%AV&(QDE`S6;8hU>Oz7nS5^{!aPqq=Q z;eVDNS+O$*sNs8RUXKAZwu*^_2lz&vF6uhhQcqI$eunMo*&mI4^KhC z=Y=;p`%Tk}shf(~@WwNg@Q+B}hJ^u%Sl*~w(dx#Oj>m@6>lLoqia!*iCFs0^4lX3h zVkn53{J+zHSCjvx#{z)&k7FfP;-gS=o2$`X>Rv|m_7w>xeQ7H@$I>Y_m}TC<@&yy< z!dwpm^{_bc3V?b;_@RpY)fw?uOEe7pQH*NziOAxpc8vQ9Y^h>6b^3ghKx>WGkYmNl zt+(_MJqq=90qLyZlH{|Bq(R|Eu0s*;cQJp;kzcJbEm$hw_k{lT(D>)y@{AD)%@|dm zZ|Xs$=c<{-`nDpuUk%~o;|tpS5t!J^3IeYk_GMJr(E4EkrADpsEnv_hDI>Vih^J^? z`H~Wwqceqnw7zW7$I~8`r}6a*CJ263)~d^!Ibicswe&m`RlIq&09t$3j%gD8p$w+A zbA$x*g4FT?>ul>Y5F(+>o0ok%0mc}S`r@^r{ZKU7W_Itj@(-1l2Opmtb%wjivA4H; zz!?-2yE^Ay41U}+CE4wg#gb^>58SK0tP!OOXrCM#Xno{t;7y`k$$}`ShSFZk2EPe&HSxMpv&vrSMX7TItt*^!3|0zMIqVJMEOD z|ENUm=<0EsPJcaw{b@{Lw?ANRdmGQ%x4D|2&Fs@9j+H~}A84t~opnVu&ZTb+@b4RM zjgybg+swaktW4rIuh{wkf)S=*O^khv2|(J@p?Wk$#>WkY2S0rMG=?YF#dCib(tgPh z7Wv}c5$4e?=tmU*NPVKYblyOqaot=twZlei{7pQYeB*~#4kKa^yq^p{&={9o0o;se zo`$!b!ZRY}P(gawZCp5Zsz+Niw|tVd-|pZ5sei9?!rswv#q7!OUl)=m-yAmISud=j zjEfW6#}l;$AjKQ9pXqd{QvGF0>lu0=N>>0SrSi+XY^#TRwU{1lNt_aF*nl7eo7e4M zy|A2S{0y?$@1n*FOu_1TAE2zVe8u9VgKUi0UrCB~)&$*)}*WBIK_PWj|-*v);y=*Qdyxs);8P=SehBbf= z9-_AN;Z{xm|sO#x`^iyTTnv8Ise=Z2aN*PyDY- z1fF@Fk&-Y$G*~oVn0B=pKR-r@SpGHepQ zjc2oe*f4Pg@L5f4Z!Q(lH&KbqZG^?FT<+;X_zXLn~h)>35PhYw=V#!eVhWdc0 zghdFifg|70FD{dJ_ibEx-z*q6TmhPGy26%=e9ceajJEHg?J)MdC_R}daGT^e|<2GjyNYAF3Apn`g|Y|W{+C!e?W(-+$U zekRg>6eR>cBnMbth0Zy*G&(a!YChdvU#7fRG(YBJKiY3Bj9qHIB@o8^;757be#OrL z)>FAn#-6_mKX3zPkjoz(mh{Lr$?tIDH(d5A7ASw6`c>36S;R?Wp7sml3nJ$YvO@WCA z#E3TN<4%4vGI;Pw*RQ{zf+GA)+MbC(>?qCeY>PsK)!+pnH$>7btX}m1 zxB&x1TEX@YwD-SPIxfq*yfh&%IM{wl|N0&4v1{~ttC^Qn8_vBtk_oH1!Oz~Q`57y2 zQ2fA6LWo1Y5)OW=hy_s=;Hc;#6Cmh7ES$7Ee=w4YQA*cRwU&lxcf zE=xde;FvD57`%Pys*jWES8ss}bR*VZtFAL?qa`%|SDGOC8tJH!e>5Y*WtFxxUI2|4 zfHM+}N%8ZM>T4H_H|!f#zIzB@Rvx3qc>4EMTl9swZ!nr0;ifQR*an<3q+=bLy9Ne& zuLw-yol8oagNR|pAh^`(a(ZIyCg5*leDIR<4SO!Zx!H@vbcEY2vi^3t__QL99EVxB zP(yuleRFf$>!o|^!VFu&=e8~YPo(0iQfgP#w5!^7ik-xJxBuxc{+HLZ9vu%gvTSc} zYI@q*Z(2-VWT;S#z|ZO~Ey65R1Y5mHj z5R@<%XQstSip%OwJygrUc`Z+eqgTKiHM&st-lk^LGk4lY)VP5;KEAoX$|4SDv{+Nj z*aXPOl-&_x-0R%1{A(<)_%mJ8j7L+J3_YbHFmH01ML_AsczoKSUsb}I^>Qvc{~#V` z(}PpO!c3Yb8h1{?Y`z;7o@~G38x?e;k4+jAp0q_Q*f@^L4LZZ3AV0rgh-ks%B`eKDTHA3=-5aq1*&1_`2-E{Gl64Tl5vjT%M;>__ zkz+lrCGS_+^tG_XRJ6L={bxP%+oyod_jk9IEP714;F@8I6;n*Uhi1akR&!W2V+yP;^T4$dqHBR|*vL#0 zcAhzbxFd>?Qn>HphUJt-^fxs=9p0vyFV&}HD)uI3`d;} zP;Uk{=Z90@qL#l!E$0hNa;EMQf+B%UutYxs3k1|Z*k_FTBQbs2^5)=BKs_}~GB~i{ zeOB$4Pj%4_r0z0ji9+bmb<+c09INjIXU0C>>+IPd3wGlUqu&aRXolasA3V+-9RqLs z^+fx>u%0SL86mL8*y1aIqZ0U6m{S!Io-la?BEhR{MfUYKuL)pPLc<7_?bj~majFK` zk@amXdlmjUnwO42){lkX>6hi9!uiWD=`2@(u$ICUP;#y2+*WAf6sC-5-eMv7k7oU} zZbu5OMcr@~buBwzhtrH=djlE4cK z7sK!9Ibs;#^%pCC1xPz#2p<{9gkwW3vub0Fx&{KD485TkXiV$j`|Qqbr1ss4oC#zM z^M&({e;^DN38BwkfMtmu+<`H}^`luYH!lyvn!^Jdh8-PlgTBW{H2hLqa2{w6tVy-M zKq^XggKA(gDtvakFcJfBr-ym&Me`zW!!q zWiqaXST=2s%V})3-@gLTK*wQC#rwyooDD4}HuT-Mhi%WF&o^pDNLIA#@Qybh-HqKL zPjSpZsHo8n-J-@6W5uQ)8sHS>JH6N|X5<#WaY--E1V%jo0B=hXk=OK9P9sI;8i2; zo7>!GW75yM_+5Pb*YGF60}>X>8(da@W1(V%RbbPb);R*7vkjKD_l`%hEUAcmcHtv; z$aY)qt7oIpVu#um-6$9x)^x~;ny6iI5YN71mPj3D~>_ z;x==8?zAk){s*R`e7t&Kf(Adt3Zpdpp`Zz7k(uf|sR$v#rPP3+8~rtXrOXL(aXpK1 zvt2LXYSoUJmS*ALXUZ0#Xq9@H3%TLUV+v9?I}j8u5*0d za8%p`CU4E+Z!vT-drQa_9Z_X1r)6@zrg547RPIe%71pix4f}o@<9^wUa8Euw1;yI! zw;v{a@r0ZVF(Sacl~ewzR4-#Pmy_-J_x7#;^Fx^7nXX$t;hBBKNpGLp!BQJrd47pD z>u2!3b_ve7J<*|%;pRae{j58i^q|ME4afqW77)UY2jN0iA-?Mm8bSq{8@%gw&7w-E zujlz`u>3L)d}0==$d^%3)HDMr#?V}Tc`7Z6jqyfP1S2?ZGxX^)Ty89PWCSpb7K9q@ zww9bIgEFoFziz02Fiew(lNkmm(k!L}n2)GsJh0waO%4su>={qV_ltnm%yi$ukt>IbvwZ7{NZCpup=^FG#QHoOHNW&Avw zGOTQh=#0&bf04dCis=AFzMCtIWQqs_t-TNL!#Xom6}t9o2V_#HTo!GHQ9zI$gNzSy z4?ye)KVUkHi6G|`dF?XyIb`Ks-t+yju(%u`1bYF>|`V z5UC(Kkhk+Z^h_7soVEEzPHE)(DD#-F(u!#j8zLvjSLI>ujFEHawW*&m&W(1egX7n} zqgeVj$CE)D&XptOdY>HztHRQY==O*PRb6)-&UIV5wc&_}hv7 zDi(j5QSbA~8Y)y-bTp-_nDw~aAGx3F;D)I9p=sEp{P8OQdDA4r8%>TOW5vx*XC!mx zC7mB&X1usD^)Ipka|J;Ae+(+y1EJEe2F6hd%B^{erY(#)e0nY;OFt~#8ptv&%|AQ6 zd4gku&aKi!>XiQ}W`GLuE_!q%NEO#R8I$SKwI_>4L=-O#C*2${atY{VbvA?bC>I-n z7mAjjUn0C5?XXU++{g9tp{|JBU#ABL&M>o=@2X2ts|Rg33n%Ef6LakZp2sC;(CNAy z2CN)8(A4}uV6E!TVvkW=!n0W-5H(P zmduBCz7Ok@f-e0X!G{Z9E_SRE1kIGo)Isxco5cfg2E6AC%!4s4bdINDmT0*$W)3S9 z$NhrcRJD8+v&YH$zkJUQh+m8zL^$mo^R8L%>!MAG+BS5lxS81x<3U2Q|BN4)YRVOz zDSp58CGV5%*2BV5T+z%$&>b-yJvIvwBF+c+uNt0su*Ozj0luZL$>FG%uK+u_aKshB zGxJ;!NPh*`x0!&Qq};%g5olYk0M}Kc5&OcSSAa6BF2`wvD<}hj8V^BmJk|2L=qkF9 zdH-1;m90f|;8ktKdu94XMK+Vd=*RIwVcimwNPclVTgyNf6?$#}Op6WbhF^nk@XI3Y z9q$-x-5V2`tXeoo6$>>?3`5cgc4=%`{|Oy{rG2fE}q{GJq5D;dHFpI&Dv)XR;wE%sDifprcyc9 zd7I(K7hBuc&3&~slijm$JbS_wzzhfOi;~Z?XBDWD2lh_>UVacY6Oeh9SuH2O=lTvc zLkvshFlCJe8>;cjbEuZY8ve0Y0S@UmmuF}w9#ivpTQa8~vCw>5?jien`G&ZK;0$dB z>^5+J6KB}5;^;UkUE118gDJ3oZ-R=G)@2>gzHOzMVQc8u#_rnl))UXxVT^(%R$?u8 zCcI|zR3>amE(4NQ{EE+HOv2&ZV<~ZY+C~mO% zQNLzDsj5Q4f73hdbQLQpHwa8d(0W zo~U$)-oIx}@L%rEpMi{5fGu6r>Sf&1E5OM;Gn4(yVfg$urV2YnHQ0Pv1l3$J`QWgm zJn-eF(~ZmeAD9^)UEbl=W8q+ZK=WpYw-wSPssm?DgsTnqXVxIf0X}c5l7f?Y_*Dj$ z%Ib99h~)rPb2+S^aY@@+GH3T4Hw;V|P~q9lmtA;urW znz-GZx(>rist%ekK*ek!Z?_Ga5T=a_3zv0DQ%d($#q+^D@w7VU_XmvWSq#;+V0gAn zT&TlkRj2a$o?k~s&J*_RdzN?ITHD|G`&|KK=}-f$y~o|~idi}A4Xd9?NTqw_0Fw7> zj1Ll`?|o|{+TB?YOQieef$5s~ki0uuGsfVrgEy2nDBAofO>r0YPHS|B}8xHxmeMM1W z9$!|TtRkx(V2{x$E5q`37~kFM8o|+QQ+LsN5;iq5(O2*21B#k{15pp9q)beS+4SHl z=YFx~_Q{jh%JgWhkU-+W#5A<05SL7h)4o?fERGR8u^*MzN;*!9TKi8ll$=|^GUZx>%RyY zjFWm5|^C20D3%}ThKB_)x5`jiF$tO3*j*6URNJt>zMThvZO$`KbS zhW%a&?;nw4b=bkQ>|zQuLCs=sJ(3f)jt(}>N)17huRlJCHKGzHx)Uy$$e|6>w9crH zcyjD-`Yw@L`^*MMBbL5^-wTBe$RAnJmASg|kz_};F8y(q|9Km0p#Z`tu(7KEXSus7 z09CMG(5G`6i&Adt=gv0TuV}t~JrUqmpA(azI2+Tj171|bbeS&9J*Y<^UR0M(ce+>i zAN4n|xYWmKT7@wM{+egzaU*?{tj24C!J%^I}1rwQXER#`l#J}Kss$onDV`oJ>f;VVh7J6o-ohF>VH;Z7*u zsWR^KZMf?>;WBwV&Geuhw*KUN6_pe7g~9lMi{<^vcdFQn`d9J`Ffp}}m>lV-T~&E|M>Y{TXCBL_5c_GIek9(?g)@+z z)L@i`{djyo(GO?vM_Ubj?JMq9fqK(P<6@L3x>@>3>njC!oI&7@Dm!M}2Nyb6^iPzX zA9)8=^KlKqMnrc_EB2U_zmDoOp2+Y9lf3e$`WcsX`@r?@>H>Vz9X>?dz_-@@BF*+v z3p~cYd(TBGRG;ywnTH{}Ki3!u*^nAhe*N90e3__CgWX;;=;hb#b!Ku+VR&$6+uCKb z{>I~Of}vnC)O}N=e@NgI^GH#Jh=!8VN|Z(a#|FBZ`mdA6H4y_{T$7!?>wd017aI+` z$mI%*HHjg^F9)G?Og1$`!rI!}u_FT;$Bz1fP#s`#TinV#>afTFeN^i0TSHEV86a zF9(dXCg?u~C5O~?k1zq?94K)-5mH;{Obl*S26OHq6H{akmed;Dj15JG^zuD+xubHY zZv9Y$PiaWhp1;vGo;(?2G-;kV@iim{>g6_%W65ncQk1wX@0yW*-~&)Z&aHtL#Mg(S zwUzfk0!mQ^Rt3&;VqHaEvSKk`W}0Z|v-j`DhyYmQM-$0v!sn)+n{m>f2W>L$=b$z> z!TnKm8;L1RGImpsP z^01#JXqmclR8{&sR8r+QmfhLX|3iJL!xtAzEy#nPK@<5KT6Ze{Trkc6fm=@O^ZlxJ zGpuRG83@gHhx^k<8NsLRB*+)e|8nA4O)(KI`FGnJJLhEl8>8a4QVxM9Z7inpMmN9v zuL0NlBPf5WjgL8(5^E4tJbf-6C48+|*$MyR;VYw0BU5#IG=AgFJ&nUV+<_HovDEuP z&Tj>zh?;GS7oCw4ZAaxNpE}a2+dqqalyW37bY_;tyEzq9cPfT3lPF>J9CRioz4mXR z^4A1fyX5Ng_WHGjlWiY&cHQ8Z*En#cHzfTm|4n+}HR)|Z*5YWyT1EI>C&9}Pku)Xa z!g?H)<=&Xlz4YM*A5}xcac%(Gx$V(;Fzzwohcg%926SSD5`7kK z{EoXz7=|&xyy=Y9wJf&1+h^ZZ$}~yciVffvIX9=WVll|Jk?b)yvf_Si^xyUCU93fM~^w%5P(*+wTT9-w z;-DDE`Uk|>1zw(JaLKT?&L%SYy*= zbMhL3-VtkX?^?Yg(tfP!&bkfrwzH$WG}ZI;{AX+B){R857{EM{7ZE)eYfQa4Vf^+eoQ6a^YR_c+gpol14iYb0V#U; z-qEqsf-X2+F)8!M@@BO>>=B*(!YueL~US z;3G2PdY9F($HiQK>af20FlMZUS&q#0MdQ#a$4_nsQs?4PjXkD<^*KNPnlV7J6A!v8 zppr|_h1KTbftENOtSt(^t9XB}Ak|SjY?bVTcTEtvS2%||dB|hmzke4&I%v5xkUN~q zt4mhtaH%kWt(x;`RlDs9Vx## zigbm`^^@+GeCw}KDGJC|$dKBgOvYJ7s$us^pp!rrypY((FDoP9kNb@=TTN;DUFHkJ zkLiV;C*SUop6?MY2!`oCH?MOTR83Uot#<9Z@TiUgV~h(HZN&5Va(-zgap#DT9pz-) zhF`n<7z|3gu}<~t#AeFPD#Gv8aZN!EAK^wWlhnDlY*ySl?WuLNGhO)g`hBzW^Ff)FGhlY(t? zmCcFR;Ht4&L2iJ=HoU>x_Q{8K0`$hY$WPs@t?vMA#WSBIZTuZGw;M3cXoJ*9b{u5S zNg5@h9~EI-Y*aL8PYc1Azn7o8gmzgVs@(|22XCrZ zh2m?zNY@<7nzdNP0|N)=4|_1DT!PH1{|TT^0lOX}Fx;0}r$t0!>8Gqz@Vp>JovS$aaj|HtQh;d=) zYgc`T*m;X_hPRim%W@M(BZYAR&|zfa0nNG}s9%8gXl_t|k42iNc(NM>WK0Ugo z!auEUF}r&+%vcO% z=wTKi15KIGQ}|yx$^Xe|Cgw!fKHt6q^wO<~4Uw65Y!l|Iqb_l`BtS$Dr%&(672xJz z8a3$j7kdOd+qDZD{533YZIuPu4{ZFMkG5Z5qR>+OVj{X+AuL6c{*Ci(#AbAfibZCw zE%k_y@Zl=5VBJ0cAPc7rfeo$FE`ybg*))n?!Q;Kx->57hSst*MKMa2tmUSRPYIsTh zk36B=k;I@PHX1v(W|~-rH735i!Kv}Ci|?T~dAhKja}QgjwBo=`CLAUE1G9Jl)3Wcb zbF6an(AA` zNc8U(c>CXqW_+2T7wTwE2`q;TxHL-{+@ClpJ^pkaP@Y8;FvIibBQ-=G8<9@Ck$B6~KgP zuAO*p60;Vbax8fL$>*7=P_p_QvzbU`vPI{`zPz`_OoKLC$yCx$LIQijgpR0&eNRbK ztbhtwIO>={oBkOR)Pq5C_B&I4uiisGy~7$tG2g-|270CR4c%rWuN_E7x*%j-2@#Kn z3PKh);0F_H#r)X6ceR1jO@0>l^E5#>414WfJS1aO{rz|Xu!v=t2B-lMq1sfaM~5}a zxN*ka<3G`{vRjSGH6;9uudPE2{C)p9RSkX<5o>XbJ6d(1P}m4tiuyD07jLls;qA)C zB$LU&SQboyUNCT+F8^^{-nD={64PkBGI8UIe7jgtOWK^+hIN{zC|_gKhNdmn%Ocw} zT`%0-o283#KutIzd%`tc}x*gS_b{>7Vy$mxmJhLKh?&s9;72`y3YDkCL}q2EjG%N2DLMu*R`7|;#5j?r7e%16Wn)3f57 z@i)l`F&CzULRnwTr{Td7lVI)O>uGk&C2XM{>^1W3O4rnr!L_83^(iTaAQrnaSR>yxGuuNFVkzB7P|?w^)m&|4Jbk}<@;-WQFZoSnpCD5bd(q&_5s} z5pF51j*`?P3k0bWjaWYH2&^%5nU-ICVeIY1PsD=VseWJ`<~RKt6|oD}`{`_7_>fC@ z;?o!#9eER-pN{Z^Q$P}XG4-pu>w3niI7q^_jcD^D#r;2b^`6atCrJgqV$lMxt>W3h zhA6pSxoeSXrlgKOP9hV2LQ{TLvzGS06H4xU^&f+-o4&zt?LT zv2(+aRXfdzaux*&GPSkl+uy{WUH@u~nMc=DRzl}^B7r<7pO=HyYqFag=64_7|EU{H zW}m5I_zn4GWBs-IH&N>mX-;zJs*fFI{Ff2(i>?B{DA5MW*>@|6?a^PUdv+;xO!^HF!dxrfk+v6kori%cSD<&VSieC0;#)ekY z!1sR|DaZHwfrI%X8G2Q@+{vSD=>Uf0X(?NHW0WFBW9q~^IFkip-TT(#O>Kiiy}g}2 z=d@v^!a>{#e5826x(`WNjSJPTLdi%DHzw3k(EByT?A^-=ygn~vh^%PVD7{o&JrCSZ3Kt@@4rjpZ`JCbad7q0qWn_kFPVl# zUEvz)91S>V)Mys_gOfQgk+Dp8^n!l zUkZsO_0_)YxM-#{{e;(^hRXObgo*brGa5~lyQdi6odW;<`VzeSTMzVx{05Jf+-Q7m zvf6GoMW%60kR941X8pkQ?!;+C@%6v`)~22=1^k^0liaf0fhF<%0h;bfe6H$()<0Hx zA|Ii_hS=|@5j_-teC15;@gM&Q2cL!ogD?@RK>w6=;ilKr8x(HoT~XtM(}SDw=+FI5 zs*_EOu@{)S_1sSMbw~ypR{#8SU0|m0Za%u7mM2h z1J21v@qXuP5Z;ZUgy+jQf!wK0Q?iW(=U^+|R5g=6d&jU@ROA>-gVcMS8~U14VpupD zG-$Wd;f?a_MTS&WKz#n#)1@2OOp7#R9AQ?I*BT5Tzsq8cOqY(gfVczV#fUGs>8BiD z0peGgWVFR0Vnc%*vw^$y4oWD8h0#ZqP3?`uqCg>+idb`-c~WguPxlWgO+##|%-jHi zDN<_YsnrjA2JNXwQ&lXSIKPU~pFb8u($mTJ>JlF4mTsz*Sl!~eAPn7aia5CUThrL9 zuFLkFerjv<&C%Q3A|!vU_K2r>Dv)zuWC|+g)dJ;cL<_{My>5J6(}nC=YoC_$Fk)y+ zE0^RzH{PuK5i0LM@9~v!2*HXss=^MBuV?m|T;qogsH!BIwfTi3}zyEiOPl|zVn1WEPi}}*A{w98Ovpps3Jz$+19>plN&p$ z`VyTHo%QY~hj!|huVDMhNY!#@NTOrAv5cxotZ~7cEj7c^WMj>`69B6NC$a3BfpZW_ zf%4Dtdi!cc@$JEAm;X%c;PCvIXm@Y(6`-(8kB`)iZ!V9ppei5~hY3SFgtMoA-3sci zTYhtBw>04Yqx22COa7S4vq~DB*awFyFQvoB`-)S#c(LW+(BSnElLttthpY+H&ljt2 zd1O2rR2NiLD9PoL{1ud;n3i_&C~{`=ZyHn^Yl=et9YQc`$vt^G+n!PA(|qBGMg!kKG!pf(Ai2V3 zqajhhwT*9+%%{ zk-D9}RlmF2(!A9(N_OrH0Ec!`S(gcjr%TDZi|9SZ8-2o3_MQ!@HVa$S6^%T4QeGgM zKU{byRNV<5d&o1QZO$~L#tCBhyOUj9kO$7Je?pF(zfI|Sd%8a*b8uR5 zR7;_Q=m>I#3V-b8cI{Rkf;jhs8u>21z9>>a`6qgouhz0u=haD{H3MRUZhZIVvv|C2 zm^?_c`RsR$z@}a#8jfAXys)o!B8E*s#>UlsKLOi*?+<^*1WG>+kO)ULT49b2INwsb z9J_u0w)DB^X7FDm2f>*Ne-rK5hhR`ma>M3m41hglhV8y{;3R9h!gvE2Wy<;!-$}TX zF8aI-(Jmy4stY@ZF774BO?B}>in}>D3BqXQ&N&{Xw@#miOu_ZJxO+|}L14D5Fo{0{ zfh{0hh{9T$I~~)kt%%;Y~-}4%6&AxZmmC7u^UZx^}9Cq<1EnhX?<*U{6l(kusSZ< zqXt5^0Zy0g5?qNC#}=0^>_P=o@AC{)|Huy(ok^c5F5FV1^eW8~O}SJ0>La=Q<7WZ4 zZO+2COVFY5vQ2G~%D&aMCZBt0vd3gyeP5A%^oj%XGd^^Bg42hT+oP&_Z#lu}mkMrq zK6*Q1SYHUmEBb1)W5Fz00PpbcaV;Blqy|*H2EP4(wl%Z zLzNDJAXU16fPfN^E+zC{q<2C`dX-)hYJ?DHpF1;m&7FJBz2{81Yi6zc2dtI7$qL!o z+57!I@AG`#ckN`i1@aG=O#KeJ19TeRyJU*L^PpZVn_F-We>*;wHBO2IgxN4yIYgnt z7@eg&C9hRb1y(SfWo{&5;C(Qz8J>7${G5#WZ*|H3g#aKRYZr4j+kZ)eG&!U$RJ&9>CoGMbN!dbiSrcO{u z5TlyIZxFB$UtphCatS+H^z~=6`PCBS++VL&Cs3|hcws5LsY`c|>Cg+vJMD~9Zg&C<+nc8>`)C<- zF126#1-~T`nY9Vld$cNfV8~RF{*B1&&(_GpC%xQa1J%wRGiFXQihUuX6E8(BEJV5- zg-_rd^=Vs2(cDQd^4-+#g!bcK!3_9Td*3dBf*rjIWjWp%LV*jv~V7S_K z%{_d96;lZ!ubSLQixw8Kg~dj5wkU-*N8C|b=3yE$$Q)5?g!yN?L}i6NQ{#zAX?HlU zPpG>Y%V+X)(6wM60F7WcXeU4$d;?q3H)`wH_#aB#Xliy(pHV=#&K58md6-yjnz&2mm?YtB}%#NF|) zrMiI*&Kq(Wo6#{6pL~dYc%`L?cAFR#2-J*XjV2wY#>(*zsf-c}**N3XV%F#^0_TX_-?@FM%UPBTZO-4q(%=NggqoE)vdI)>aQXW>8@?iOVRXiu z!%Nu}NNsQWx@_ED1THokb)e+f)_U<(ukG#Hnr#Qr1ynPrZm*s$*SmVwn6STMsb~E8 zu^1uC!(3`mH`DadnctjSSJjvZqte)sA%SU&k=9iggl>U-bXIKi>%icZug4s_^B6T(0G4s zyH1`GdD5pu1PSsj^m`~5coMn7-PG8gJgWuCIG3AO)#9kPD6p%`R>2m#h__HFn$L|F z-et0D5-&+rd5&fd&CX$K%yH-x_p`M`o^-oKy!HFqvzJ-ef?`r|4WyHmf-a;Rr90uQ zS?6id$Q=Hny;`PuP6iXjxS;5w);eOLMDi9J2fMXjh!P)lZ5iNSZ+Ykcee& z>dMC_{qo2u2-h4?tpj9f9xLtjF6#;Bta!U%mo81`(<#^FppranvZKwF*Ma zh;PTWeFr=h!?+FvQLesAW4Vz^{lh>_u%Rt%rPmy}ePui?abuy^b-Jyc6_{nq+T(NR zqsf&-y-i-^J~((QTFh5h-?Vu7NzWqc?aA{WT#X1-W%DycxSB`A6;! zjdgqoUR8;)(*e_iM^e8?q_+9oW$#o74*Ui=1vV+N!XuR&%>?~LbVDk#h4uK=UuUUL zhlKuA-t>sk<+USxR|zw{&J4v_8>d$!MLC4mxshP|7LE|nwu>9O)Y{}NrPr}XPqB>I zfU<1i_w80s|Jn_%} zOfK!4{L*Adtiq?{KgAOxo99@l!YR{f$ap8hO)lz7_(LDlM5xggxZrA5PA*Ru9rMd?A zIv__kIu$24jv;Yj8yzG&zd;0-GtkS#afnJ8L^f6r*&CM$*svnKT?8$dAm)RCZ0WwN zBbE0RERq<$UcCZs&9%KyHvi>oaa*cLVdiD(vVA;S7s*VD9d9TY2|`rEISN2(EHbbL4=Pv(W;{ z9g;`pLT`B7@nrBk@N)P{dbNR<+64N_DWyo*ZS?gHHhr%)ZS~a0H2pSO%If-U6Z|V+ zXMmt?H1?X;k*ksNcDZ|JZ+1G_I4b8v%F5G68negn(-?cSFmKgU7!5Rp^zl9$&H;{k z$CFStvFYzGalS4-^=Ptp{<1Pay`aF*=u;;fzZ2D&^+yF?A0^;4B4 zZwBJyWU)RB`23u3XVdTOyD4CsgqSNT`OO(r&(j2?zu7`bBs-cY|C+kZoTQOelg{_!bnC(3d9VRWE;a0s$ZKAyv zvW_k=nWq^DiLfD9qj*lyE?ZzcA?^IUCE*#t!yw%@ylut6zv#PsB*-XiTdNjeCA~b) zgkio!MJXLVorRwNEHav)c`gV`2O2M4?DH+_JCXV5K-BED6^UPW_roO>uZD%$JX_jx zP6x3SQ~bt+2V9vC%il+;y5g%GoGi?KS!;U?L`DMY(7vt!=;5}>lP88YLo>#L4Xdo# zc)QD8~z5ERf@XOQOkaPWM9Fn z=JJc%?OcM~;(lKzxlXXJKXGJMZL;kbv5zj)uBlrzZlf24`oCTvdvGDE77ZVRJ~xI5(-MP+~Z7ex$s^ z!BCvqy`;jscj7?837V`pit{-leuVF>r`idEM~og@91aUvQXz+a2p(;0__;*1zM(I1 zDp<(z6~Yf-?{cF6Lcr?|VGuzGgZb`)6wHp_t(Ci>L32^@m+2Yoo*!P{Ds?-Lna*ZG zm@bkq{CJ~f>Kx7caI|#w5892U*6%p?8z8^j-OffXV|?j;@``D8w+Xr1lw z>T^>Ze?>*}3xaa#P?D1NwD^hWY$K;byMfo6j5H^)EEW=%v!(Q(cw-MA%?kw%KhTpu z`Z-|Jb5GsOogm|fpXxe*(P3Bfq<9CBD?$g$Aw&^oB#uYnh4&3e-p}~nBLZcEw||48 ztw;cgYU(lv`39ZWb?sW_ijk|(^}Q_BEIeCS2~y-|(%JWA2y1*2ylX>fdPCf*v0()y zCc)Vv$dex3D5js;@$g-#t9qf#_`DTU3zJm|k=+BD%7L;(+=ta2#asmMxCVno09c73 z93{8b-`!mlOF{M|6McgpEBTp>#%DtM!!VKVQq>JAPB1QVfSb8NiK3Mq*>V|=_LT1a z!a3D#h~=8{Zedkl)O{zM)2uDCmc6`{Aok5tY6# zTp1uCrZGzlLYVh(?rBcrLA5ihLE}p#(c8eJ*?NrH8V4MsjD#j&m$%r7MZR`8oHqCa zsy8LK71Vvc#y@{0ZYGGAXaMVA%nE{u`{cJGJjdyzkDgnM8u_QsgOmzBP! zUB|DUnenzBBi0Z-2wcm3Ln}ggH;1oiut9Ss(kV0hqc`o;c9SP}-vwt&s7thAQRNdS{nfCxKk8iW|*$rR^Obkz4*LA=d}B@_R+WaL10y^ z#rP{y+O@Nfd@doF-q^3E^Re!`+Lnlkvf999wtY~N|F?d!+u}c9TEiWE zHzv3$?}SY6sX_m2=Z6TQgn}7Rw992arg27wFxROI{`*4X{>ZWq&BJt;Bm$b`Q?;Rj zDFsHVeYt|>~0W_=lV$umS+y? z7%$jm8r40x@BqWLKG1&uv*Lm-*KCYq6VMm0> zye=kqrxlYv$f|dew;PbZ0Ty5<< z8#<@Y{-_YFZNAIBr07?#`D8ok6(3;7I*8F#R(GJc>Z zl;K137H&=wAmAOm9B)-Z)ojdlk*vNC_|td%jUv&sq)D0G@}*Cr~E4q;H>eo8Rzu;kKa6i0*is=S5oFTKuv< z`!jRQ<4~*UOu`;Pa6x^n%EU?S$7)SwL$g7bd~y~sVlKLyCx^1j)3yXJk#vYyYRK~& zAILJ50`p(kWBFBS-=G_x!=o?D#U$BsNN{(i?mI;pj4{$E!ew&`qI3zR*spZD z+~ovTNNownf?=fE5h{H1NuT)fWH$iW&{4e^MUaQQSr>23?0$-xt>LLJ5u%cKsBLTK zpseYO+Hn`M>g=(xi088$QGgvV3>3p{DGX3iIXAJ?zH|F`+Vfq$(b}O z)?wkXi$zPoXA}@XiOh8CWv5WdUs^%r?=!h9Jx<6dUP!%Bi@#`xG<^^gSfVpjzw_|X zgM$ym*B>zoNa?kc@Va=p9yS`JYwFiG0ea15OFtI+UHDDz^>r@XFH|;2q-e+D=V~c~W-+dq*%|B|j8Nib+5|@2ZT$wUOA1zG zZ0%^B5Y|6ju$bA-@ONQty`oEUiL`&&>=Au0foAhQ)1@dOgla}!5k?BcgzujGL_0VH z7WGV+d{X<_isY%qf0u!2NZ_CIXAY~^yem_Iz4~qiMwjPfp56E$4%^snv~KuP0W+XW z_5xITbh!^vbF^5wXt~aGRKz~WovJ@ z^!-$reyyR`Eoyek&uCpK@kj!Gw>G)$OLjp%)Y052T997cbfiIyAleuvY_IVHu>RoV zcn-ZDph*jg1=WbSj`D4eyi=}| zA_Z(68~e?X$-cN*qTK0cY+~)wV%>=Qk70>>881NIWR0oAKJdEIoeq2q2dY1+olmKk zf(ktYQH7T5t`*uTBJgDc`Qv93;*I^96i168o-bRc6 z2JHTX!xdzH0 zau8k)&Hg`AIsclj_aD6t`g`_o>xlo?v8n$P^1i|p&>pB-P%f}UzR4W7dp}fo%A`9z z9(Rha#8vkFMBJBBmgQoU-FN&4NVR{1YTM*S?#I<-N!2m~$4D2b6fJ}2bOWIh;G4y) zXd<31&otK}&}UI)P(|UtPgnT&=nMa+_y3;zf9E6nk3L2IgI@3d!)XB}&>(Q3iTNAp z3a*Cw`23_qJC$Up0R98+ic5Kijk%sd2xDNr(}EL)`(%0V(DhlS1N%`OXn*JTb5B~lEA79h_IQqYE_Gf3kXT)>8FNObn`2NbJ^4rS1$-ZH=$(wsTqpf)qEHR7> zc-bmzXNJYx^BJ7ODGW z!sz?8dSm@PGPQ{B(rl)`^8F`8MdNNK650f}6XT8OfPh}D_b15AnbHK-qFV`d!nkK; z2%-HAO18^`F7{(TYFVmN2`&!r{DOUO|H1%u-AIY4-f2j0uUB{$!w)yV4f$XB@B~j2 zbpU@InqR43iOSM1@p-mr2s^R2YN3hKY>F1HUy51%!sL><7NZ_g`3FDF?(-7-eE4*b zkB+)9#fx;!=W}~*kIcfxNA7(j#Nx-G<*-D~nZ~#8G5At2z6^=e{Yi@|SMpYCeSTHe`?(a67JU4m?u$#< z-GS8AG3pA?=z}h(cDGApuFP%J^~ZaY#HKddX=j{&{h1@?CYMR;$;Fz1WBJhUfq^{9 z20Jd$Ug&(G$l*7)-gaB2$S{r}UPXS|7aPdaWs396d!#L=-;95EUt}0NAM+ZebV| zlz(mmQghu<8+k5U~R$HVbW-ffp=6Mbw%7h&lprsia0Rf@gHiwlWH8T-m zt=iv6f0&>Xx(~?$KOfy|Zhf!)?v%hzctXWhu(Mro?=k$45EZ3^{<)?d+Z0R!QJ#rt zh&y+(^IxBYpTM?eT;k&T#E!K-I^2ne^)n@Q!tdWHFB5CkEWb8NPi9!9aU_49p=!Of%3r@m$q%2oTFZDc`+4Jf%IRvfuf zx-NQeF}6+AtTub-m~M}op5Hc!V#YWI>(XJP8*^|&fSp`rXeWl~H;eDi&YFg2eLkdK zcJvtZb>eh*cUh{++c}ewXHNZ2`7f9%X@i*#F#BS6r&9Gvga~69M)C6cbsX$ruV+yG z&htjr_mT7Z?uRzkM^+Q|VPBoHna0mg$Q>(VU6h{IM@}wq3?wkz(_o6b7I1{(sHd;X`&_aA+n z&yADvou+OC-J;rvB9D^F0CTE6dibz5B=r{qmCV-b*LY)(*Uk&ma$KN}dsv&^%TEpU z?k#hCtnQB%%JP$jS~g$p2ZkkC;h>v;VH8SO>CINZ?(^|VG&9?NF=BMIW7K$&l$^iz zSxi64e5Sq$MWXZ35^eiJ6UH#~ti{;7lX1(#;zO6G;8LG~^QDp&KOBVA?KR6K%Z6?I z;`Gmynbm&pS!YLbcEM;TJif;AHmL1__4V^zRY8yn;r*~BBW6P%>B@cnuOCAH>F(1v zS9dGg9pKzt0T+wB8>z+p`Ua$lfLCsztg^G^(R(P0P5c=|6qZTQiH)7qChNIJ{15p< z1!I`X(N#e5a%8&x{_1;Zt#21RiWv2#`J2T`vD-P=S&LW0HX-8zp5(o{aI#4lxAOpS z-F4Vk594R9tF~MRZQQe+W-oU@8?8l!*G4O@mOSw`o8`y^=WSE{8e1z0@mz(s1zOa7 zsjI#dDi-2{M_a_xz;vqUGA-Qkrh^?wT!kn0=4my&B}$-Qtij^l10`WE6%NR!*63p| ztg>%5$POoVZf&^MJC;ZKWiECDji$1B==oII=&a+~t^OF>X!;e>FDsbTub2w^3cfU& zO=9*ZBqmtdq^)}_+&f75ApZ~%FRz14TYNGn;)OUWT`UZ9IC*W|)WF%G5aco2LP3FH zMaNuA*4L~<+02c5MKCHq+x5ZK$&5TZGGkJ6Dky?ArPz~2Y!h@hA8v(|D#C|{37I+& zmu_e4-bw}_E5}~I<$y3x#xH5Y{4(k^g+|C zNJXsQ?ZhZ&PpLk!N0d~H7S?k@(E2o-$dxO8bJLg4eVM(oPmawK;j(VFdPHJY+IZ@+ z;(MBCLjZt0mSO#pExy(cP|C<-o>U5ZM))&^*wR7s+fYC6iR^jg!RBhWTeQ2{ZR|I0 z>1x!a$$PCwai|~H9*Bmgm%*(um@1UpcLm(@!D6(@s^+w`#JgM>y&f;Y@vXBTuoKeE z8MGVfte>6G%?8=gNCac6d)GP6~2lgLtu^4e3)bA=IQ z7`90!qF~!S2ljQjPbfJ3+Tl)cb_U^OGt+nLzgm9&jTF6AN-)h_h0+>~ofV_Cw#rsE zjv+u7l(d)RzBynFbRjfqmd)%u(z6hS`uV!Te2vbR^Y$EH zGEmLI-}y21mAWcOBNsGIINZSk5Tl^;rI&HDwkVBWin|5djY(xz3v>7GyAQV5|y``<`GXi-X0PzOXLU31HlnP$J*SxRt~V2KLt%*u=!^pQ#5_G7xJ&N%Ch4vRu{m35L>e|K@<8jkPAl)dG zn;`MrV{lBSHxSml8rne;Ebph&N{Iq@&tf?zMnYdF*zBU7=Dg#6*fS`k8>+r#C&TT< zZB#s=%+7(Ky$uKMe)lR&kHJgZw=d4rliS~95{4UTSWb45P`3eRtvkFFdFn(rqI^c=k#7C{zKo3W>s#}0 zX{JGuUzod#7B#>u$y$%fG>e%`j9U|)yi4=p`E$)Qe49D92i5V;ojIWEkS??%I7^#|ZWio5pU zbgQhUD!QY=C7=a(cV5+btyQip)bg(^jf%GY=%+NApZa*ii`^Xd?pU;4yG$w7E}T~_ zd4pW6pBFj0AJ-YT`8I=F-8%cmJr7`F?#%w{K<`!^!r$Xz=DRL}mJCOWL{V;)4IAb0oupai@?Kd2jBo zcY2JvBf7!w-R0ZLN}g34CdW+d|75eFc??<%Fd2EZBSOL$iP z&99I_LhEP!1OV1&mKST))(KdUWJQVe!g5Bu zV5??=7i-v*vWlPl`6;QteBZ2?rVCw_Sr??Z)Rsf_&)b^-snf5tdxdyHL|$Vf3w?g{ zc-mgePX09#gvawK8#hEt0UwC^3!%GBVmFQ6WAI!`!Sq;Wra%ib)$%QiUd~zu`zOyv zq8T8Kq*7I^pqsg#b{gbPoY&7udHtf^l6j#L>6C}ZajgylPtRq}<=Hk`yn*b^k=}9bf6sC?xEs}BJvXP6ZQ2(BRP89sg0*D; zQd+o2{mCQ>S8Y8nRb|Kdy+NOU=XM+4li5t;6tXk&+B0IGr}<=Jo*hkG7uc9z{cBM@ z#TRn?5U#Sp*ix_F+A_Z+Ld`K~w8rwqi-bH_UTN|dH6AYuO_>(4vRfmAstJj`3!SGg z$l98Je!BS#QqZOXu@2(a3T~goVTJv@`CB=Pa2{009yJI~c||GyVOG=c^Gd_({snC< zmyiAY+A6iY$~TM&N^Lgr(V)|Mxn!ycZgSyU^>x?qU;@K2&(j3)2C&wY%VACevtQcX zyyqoMq@4V_-w2ct>n5nKBrUS!4{FUn$Hbe}_xqPlb!VG36KHIjQxy%iMZndQYoz+! zFPTf=oP80CA+nMz1%<{Upg}I$Q^MXy-fOWLk_f^-=hEV~5Y9woB;tJHVhpbVklJZm zG$G01!p?gUH#^7sZ$FUBU`5N_10t#|o=j-Aq(yw2$S+ubEaM5JdRX~b-QBpT1 zjX^45QR(b~cQAQw=Ws)`nbQU|TEG5_Z^;)qwW*klC+w?Fxq0e~7+A^wlAf3&+pr?u zLmtpm_Og91ct+S93SMp}-YYFibtG7oHS=wsy>B$s7q46Pa;{@L*t*le_O=ZmHUVz` z^V*;n)=o}^^WE0A3^6OqPdF3aX*{jhDnoCr5ySj1Dzf!2D{MLy>xR)O-I>1comW;) zd2EJWii40E_peKiDQL%CuL^5CV$!|8ElC7s^C0JXuZzAT=y=olog_%+C{yi)D&;073128(KVE2mcO%b!HVWlXW+VCyBI8;U{dGC5bTSRayiG(qvEx7y z^|`-6!Fj(yo2e&IhcK)^e2f1-pYoqa>_1PK|Hr;Bf+?uOdx>~{@83^T7Fk@fpY;~w zX>_e{SE78vz#FW>ueHH#H+OOb6NTr=mASq3R|~vow^s3>TWPznOJG@F@Nlkd{I69A z|04EZc5C)@>S9^sL~SO=EK3lbP4v~R88uK~qC3qr{`K?gspcge-ZDg_FyNS3rAE7M zoc6C@_1tPJkHeR0)1sM=L8xI3`8P)i($4ycru(hhH^QsK<$kukYgT@G-}Eo0Q=j>5R)N>Mr#1wrDzx zkChqTAn)3CBjFc==r`?8Xs1SRZ+21py&Fld-&oRR9ym0~c)KrVoCYen57b3#K^|&q z5Rn zHrpGD1JQ0r!{F#HE9y6<3{2a)u+gi z{s*%E{Wh}vY>+v2m+Q>JfZW9ABr$UDD#F*xNRdw(ZdePRb{dkZk6CajC`U8teV>ew zekL&ZtGzuC#srbLO@o*r7kf)L%-Exis8v0^X~*)M>v=hXe%46Mn;i+y1-^ZGA$e&* zqc>9X20i%gQ?C)bDsE#t2S z%325SM!jDCFP7Y@9v*H^Zag#7v84A(<&)*`|4?HT>Oq27k^}T}GX>u#2l|?DCaH3j zke21YzNc}Aa(w*G$Nx6U^}oJ7gW%=YZqG7BxNeN&o?5TSBZR)>UOLFV75{82{~Z4t z5Pwr-yRB)(A)AdZ#5}DG$!e4Oqo&ncJ}6BOQvV9t^nh3#aUwf_$4={Kvq^q0yY7a1 z6G3e1x6|3&9}ZWZFIkj-+ApIe{%JMwSjLe3DaLYAai;K%sBLl2?3GltgudE+0n|Vg zSP*YOK;@2)6bURiWv`{90P>2V;VV?067E6(_cgjRsrJ*TS>XxOq7r$UPU` zS*~`tG2ZKo;eH=N1*e3z^ztNsmdVAApIfN$lw59?RO~eyMtEY_9cGPLTto~aS-Tx5n$v~JBkd? zrmb%Fiqij}Er0(@T-D~CgbX42?3&M(|M^sDHJf zJi7N3S}TIbzQI1!?Dra9++5*?1UztJ^Bbh^jzid>v_9EzBr^SO^znyg9a&l z_El|VJTLb(-qcnTFcPHJH>bL)RCwn#)yx>9qz7yYOWSn<4D;3-D~tzmet_?ypCMuG z;+FXy&%vH!X-ry&khzTl_Qg5XTf{96cqN#6FQHk8{#cA0*>SaKl!|UpyAh49*vM$0 z0kRdw({tli6d}5If8aB)w*dsOax3AdT^E_;_G4)6ECWhaI8RkP(8z{Z;%(?*K{|&| zC3hN^TnMY+?xKZ;F7SR51wU0hhAlTYfY#3WayObwhW4a9p3&J2@qaA~`3E~BcsuYo z*r@_U>Nlto0JKlc&YTNFE>J004S3}0CDlLG#u5MLdgo0_?9hSO4W%1`73gkSMfJaY zoI|d?=7vdLrpB&7&kId2GEd#!b)0H@>D~Yp{A31r*72`3gz)}G#1pst;;1mo&ZBsB zsM2(y?{t{!vw(U?jkrPxD8|>}Z?Aqah2BKcDeePUX zu;-fRD$08Re>5_Wq*MNNQnM_<-GNSkq5Z+1Wo|>GpFQ;PTqm5dB86W%K;eddssi@Y z#1rkWl!~mX@MEWNr%u$rVwydk zyr%T9duaa0GMf~6(XP6hF}&v_>M^uS?f~EzyU`pl&2=YIa{0TsR})sB5i-1b!5gwu z)55=RZZu!t0ob-3g?SeQS3wZ_l$Z5Ms$FgkgVYbUUe#DUuzEru2tkB9t``l;YX}B< zs%t5!Hzj3L$d{PPPZU7avu?g*T=CGN*cUonbxCe-EU0_GebE%}GY$mJ7M)`Nn@Z#d z^v`ufdS3@2{0sfbsLkZ3xz+cDRv1VSc;q+8pi~oW8;W;K+cWhjm$sJdIW6G| zilz)&sJW38S7Z&b=~#IARz>@T=NprDIw+ai)#917BryI=ks26*$SS=a+`%_5;vFc_ zRNrKe%OyC3Digh(b%8zLyMyZFQtY&fVXw1_tzBh+IL)}7YyYStQ=DZs3k;0)r!)Ry z$m7GmuX$gta_s_Mrep_QaH#|Os*s21D9!?L z)P8u2DW0Aj8^$CK%0PRYB|Xd3_2Zm)q?z9C9v%(dS|Tcz;a9i7UA5`v)xXt){%_MD zb>E;n)A$wo*(l z8vVJCws(~y5iUdrvvsJkuL zHB!U(tjv}zv*y=LuPF7toqr)cNu=-dHwN@x=Rbkb;%31WqPe#;6Xtx~O00XURIOzB zXoOBzMef~)>g14;^q*;uum_=p#hoV>%Yp96$vW(<>*8JqlMw+TsAL_*y?vl7`Ry_8 z-&mCYtL^PR$cFG*-B{mD0F!fHxp}!Zpdz<$Zy~5t)WONEa7iIgdVcW7ls308m*&1P z?zcufpxxIy)wQC4RBS1;LgUJjS*g#tT4Hsiup4H4b*))!o}C^n(xCoFWJk>EVn07A zjn;y7b`LK&!A(2aJXI;{w| z#Sr>PPHxw52K&H?4X+lp0>Axo$H)-NT{pRI)OgC(+S*c8^*Y(#N|3lXo&3ACZK4l} zyDeZS?$^w1MbX0IL~3Ijy@YvnoL3x;>`$q|IGm1KdU)K$?ncSnWJ#fS%L?gVv;oX&LsY~0ZeU{fOHJ#(B) z@gu8jg`=?}ErCs02ty4U1lXAdr1FemCne#dBnkM|nP}*mUS8oF#(LV6Ov8A>D_(Kv zl+WXh>yETfexAe=!+W2WV_i&WeZq%n9TxCxAf&VHoM7y|su{>@=fZ|2trgkaOcN2t z)=OemQ_1JKes`$c30c8;$es>*>$aLnjFDX)!q%D5VfyHJhk7YOk8*ajyz7sVA0qNs z28_gJTr|P7j@dHEv`_66bBE4GPbb4C7A!mcxoeh6|1{;iJi--%wz$Er;AaU0@*~ZAZk-syZidk30$v5`U)pQYgDYO%VtW=Fx79xVpf@g#8x)ES>Vtea7!lxj5+13jn692m- zV&7TZERtWJj#y20=z+(A1t5>cgN4wKce);<9K$LzSJnw$*EcFZd75+a-RACbeq7vk zMTDi6xdF#WS+F_Us^@77WoBEc?rg4O=c?5MbVGMLKU!;(BoQCoF3vg)(jpy%32YN^ z3r$eZJiDtf9a{7OY_r%~eVZ}+;NegA4*l7? zCdG%xuAhRQ@k(*MyD!KzMI2&)yx7x^c{;FGBG^(hC9kw0lOKB{s{d;(II5Yg$4F-z zQJ_g>esbuWKGG_>#yrZc?#8Y z`i7uV`+BZc4Lsh~Z?h-Q+HhSSu9*&Kjyz1M!Qw6@oy%TdmfHqF9V4|rF{n3=#73!P zXV?wgf+M|>7Kw}Uh+dw{7M)ZOtXf8Y=QvRF&R6O+pUfZKe8Ki;6Ud*&0IfpoJao4J zZjB`Q4eI3qcmOWYbFfjk-wHqvh@B&p1&Z=>)46YGJ_F5G(bo~p{;+HD((herw>D6v z5lmJ%a8{7~=(vIY25D;)XDI0Wado%tASKHzUR`_E;d0nQ)4I+u1NEhtgvATNS~}~l z^h)pX-pP!H>CSdX+P+;~9rKoFh*DqGG0*7-MClTVX45Ym0)4cXRX^;_IsjKoGo&1J z%FBsUBAs74y5NI#zdJIYQm=IIC`TtubDk>#}@W?)RLQ z1T7Oga0eT7Ex$Qi9kI`d=ANwWJ+f2QGk* zXc(yy|2?cXIB0hg9bZIu+1$-{2mUFmT0@5C>EL`#%(a6E0%>`797eqC;5~qk9pz1?zkvvwG=W&G-RkwN%=qdk&1Y+S zy_n9(BcoGVdzmTS7exOYkGg`Qjokoi$hI7mAN*mjgHB%7n*lp+B9y-)OQ6Q;5t_$` z{dKZh9w3~0n@|91n%dERAKkb6LkwZg;w66$A3b1aahiL>B>Qn^rG=HRZy_>8bipfj zt|9n_VhFmT{{earOjM%bsm3sDd(td8+|G>Asz$X^nJm#n8PqXn^T=zl>x$#-Fs?_* z$Xw9wOQ>s==Ehfn^F!h#~Z{ULPV0=bCo(g5faW=7+6XLEhJzu4NDp+7W% z0geZ6uIc{OM4Eq?ar56fIa`<@VDO{pd!ROF2G%5BO`C`Q)us?x(SNyW0S~ql{00pQ zPbeJ$AdIJWaFf5fprZI&5t9l+Am*4zj(LepT@8n5(OG|XjWNI*X~C zxHA`|27c1Ir}MJ#aJD2#@3R9vqhMjM`K}@<5?i!EfBU7wk;JX~;PMR@65ByEFEs8I zL(RdEBqmPP?lA%t#4kHi1yCg#hbg|idFzWc6=-EyhpyWCEYHDA(&Gl(<%tk^vYmn; zApN>lpN>lGT76AgA8`34!)tLxCC0LaApz3xee5xd*w!ngRSlxgMWdJZY+a*gcNCT& zugJuh46(oD?;}YVS$oy~km26Jhi6KE7W7C8tbg%Sdq#r(xH5c$I)s@yUwbR6`Xq7xDU~UGW zhW07_nCo1TI=euCYJ-_)t%R&euwioSFD-5OW(bsiaBsJp0<}>eMIx+*4Nf24>fs=a zO<|{8SgCSckld6?SM?#RT*}K;29H5x!$xfO?euG#r_zAP)ZBH8hTbT6-AY7CI`K@n z-SO6OTB7ZdVbtMuLB4bn`&y=C5|kH!Sb_gCex}m`>M`OmfF^+~iACBWUM9#1W{?R*s` zqei;x2)e;A3x_an#=`C%n5w-07{OA89AUsU;Zf~=aEI1<0R979>L}_`P}8g;^e9h# zcPY}4;r?x5Z`wD-!$7k_tBgACy z%g#;f=)Bg7FO#W@7j275cQ&$_zi-W7;<2j3gazWe0@}DQQ%}5(PueFG^8pK>;N=vu z|FLe|dB?rQBF*C$f5cyif|P#IHFi*Ar(o>uROTv9DBUhoS*NBrvtZ_~aWSaXd_a9(fb){= zUdrAp&BGjYGB^iUlarVkS-hQ8b0kraGJD!$1rkm%`bd!QoAATWJ*dm%N=v~PJ2>!| z+Yj)n46}+g=w}rbJi1>g_M3kt+AQUzTKA_ZuK8ATQCVB9;T1K3)rait{M4V>Jr}_f zEdsGFm^*juUKU;@6;Sim=Cpo(@6@pGJ1YsLgk~i}-@AGa!{dvTU39UEBW%9{>1`nL zxfdHJr8okk&t^5gT{TxSrZxGdt_~iugv`Z9SVG#hx)MdCRWUcp@YUyGpXr70)8wNP z<%hn{;wz5DfiCN%66&vepiIz;zz6JuW$4YF>6Yf)>22C+|K#_M1z8*ks;c3?sU8vQ zFlI?lF2^Ew>`fO~FmDGh*|VnoGzTTEUFew^Ufn4n2aYa<9cW`VC9M|{kPjisQr|<4 z2qu>VkTo-C0wn3ycVjR%Ci&QSR;P&2`og-~K~!S>6MbQE@A)YFz4ST67YkX+CiB+m zsam*W=Q*vBD;bBhzpX^?38LW%xDy9L{V45yh{#jpqr|B^OXBWSyxsH8WT6&Ru{1gghn7+pQkGaV@t?%S7~QI~F}CbThpwc@HrYOe3L&5$f(R-e#! zF9t#%32xzu$C~uNPxbgN(~gumz9u^JlF~a;XDXbUtCLz;Te0W;;gChkRIfX-_^mV= zL56WwKFm)^7yIDA=ct{DuFsrTqigJ8tGD&?eqn0hQ(Gnz9Tidy^J)z{43(p#bXa)ushYMRxlEWm8SHZ#b=9 z;|~J2!64g&Sa!IKOQqZG(0F1AcbFzRHA2P=&xo=AHf27=%&0M;tJ9id^p)~0smooV z_+n}4j~^@oNY}z2=*L>$Kl^yj>$}5S&;OvRF2;_J{U~40rHfmvc-MuzcZS)NFypZ- zQI7h~!?LB(wYq5jGV1w2g?;wDc^jT z`|NpnpTGrBjrAiZtI9$Yiuczte@SbrwcRIpbkF-tE4qaO$}nyBL*PuVZm1?(X5`4` z$9zmhCwOk<4*5W0ve}(hYaA?Ok345HC!%BMUk7B4w4$CnEaW_s(t3_fCr1{3JzeSEUi-6==-@%eF6>sVt{`RmtY7 zC94B>%eVSg3JV?_?6IbG8+1)Tbn3X!oMi%0?}(|wDg*(tGux`4P=|l=N;HR|o%Ezk z?mZhZ2k%7vk%9@Q*CF42&j{9kkh#z78LC`Hd>M$6Pd&hTkOS3eS1Xh&y{y#KQi25^J~fa+^x8l2Tm*p ze{;J`?UXg~5R{)c@zh@=|7mF`?|;KP3b&^?qs4t^1U_OI3LL#{9&?KKC7wWJA}*jVD)!={oo`#7T?dKkIO34 zTA0-H`%-;HTxBNAivk%W}~XxDU9` z{GF3+bCf>)q#pDr_(?cp?9T{{;=&^T=R3=~#r+*jXolEr`#neq?OkuiHnA*lWoN%@ zQyGgUBmZjrht7wX@MLc2Gz5DSus0F@Rn89~UyjYQAC$2=3|oqg1v(l_j}GUOPs$X8 zFJAIy5y@z=OsQzP%$|r6qg!&PiCWPI=zK8a+svF`_)p;Pj41Z!umOHu{iiZ;#~IY; z=m5Yszw{ML&`@7`+R7i#%@GoPC32PEya$g+;#B z?(jKqNm?pF|%bm(WO!4I`KR` zh>IU|&Enn0-GiE&Q9TA4&#LrVS39*slPYAc6XeVs&j#=Lv9!AX0ZCJST0MPJ<~Xwb zPET9euV?u`KSlt}p)3s8hvIjZYH`7__?Q~RSNng^Oac8%BU1T)e5LNeT;ZQUDFLHj zG2lUZQtgra*AY9QX_hpVVhjDgTe&82CRLlt!e$-(&}-heeJ| zE^8rc#aN^c_c>}49`Ty1fLU4J(=zRH1tmnc-Sp4TX{^|7&!?#&iOt3?HKd^p-+aUCs%ABGTFADyZ*wUoaKxbX7) z13DT}3@VeyZL$O^gz9LGw34)NdV4K*2Rp({m!=*kU=x3K(DQA)5bwaRND^W`+;Fj< z9C+*!W&O$0>C60_75@S@a&O&b5lvbf+F{ReuI2^EQDFpV-!q;`801kF2S&k_GuM&w zSgwt2uQ50%1Icy$x#!=EG>^?tNb(tiWiI5**Cj-_L8bkKLFt;>Mi9$4=i0(Ym}9Zy zc&-8bZzjVXWfM`yoahZ+rm8C1xm4h0X-98>>frz*^*l0#=-2g){FRvemg4)% z%AW@5{cUfGoak(4BX)8R+&lY^QbVH3jU*+i8#aML;C5Gb2V^Gk=cPd`9md_Bv-Z1L z7o)gf6NRbZ-hByME8N(H*7?qHad+*!EZXrL`v}1}-An#)uBkXbs3#QuKwFRobW_{2 z?5TfV5L6S(j7t`QMzj)_Vx99a5%vO@R)U_J{u0K{Xfc_(% z71QXvSPTtYV5qujUn;f6G3wFx;>Nw3I?;^O*T_~S7ul{C*Go^5)2w1{ekcv;dzoqC zwAV9jpK92b(@=eOm3Gk@E^)^I^03H|VtVbFOU1}etKNmPv+iE@)Xd^R`vI{xL>ZkL zvWuT9+@5fmWxOg;le+jt!s=RcpO{B6z#DlF`rNP!UQQbYC?N4PX5JP);%44XTe;d9 z@y_mP){ygsPlP`ZWgZ$9-72+L%DbQ4&-L8;{XmF8*R-8tjTP5qDf4>S*l`IkGn2n@ zXvd4#Zt5Jo<2Ovczlr~hi8)}Qm8&@U?$=a7%a7VO?SaN+_tVBegzPIe{sG>JT{I2N zfxnFv>Yh=jWmpz_w8zvl6C*e=-&Vjx(;9@aGUiM)ty6CgO;r0@tTxAB)b5QjhAa?xp+?Uq`*VdS%$<%0=^9M)yN*VDDy~Rnh#t zQjR>t*~?~Hgug|rWAd5=3~^7Vh7&f2$~S|tEYF6vL@{csPR5;&iFRshsaN@4Rp=ut>2)_)Y7+6u+- zaGmf1y7Lk6*gq0o{kv;W$TpNr#?(H~%xrUc@L0D7t&RztCg${hnGRSdYY8N+f%`n$ zh<-k1TH$O7$SD)He`&**k&%d*fZqNb41f-?PYfZie2Xmlq%V|Q?i)+SVw$oTF{(RA ztk5BU@lvU82McTSsK^1CLg}|c27_eb0f$O?8=*O25wV^1es*QYcrrGf{_cVbZN`p_bMfU1$_%E+kg>j8ip>Dx=8V(ma zptRokm+QRIYzB<)8ujN|#+`o8zI|{6!r=y)EYCL5&!)Mrj7{3l-k!_(lpn@+k&|O& z@>ca%#g~VOtY4)e4Jkut>s@)UW-v%j=f!a7Gii``sNxrV2%{F(Ki3EwW<6S zgXHi#bIuXjj{YEZam#}X#l@1Xsz9{|6@>IBmk&Km>mIUu8x$N?nghy$;DpP;%lS#2 zIy6V^$9F|^BJsth#wIg9h9n^piM`2;R_tt{gkF6H0MT^$bv2q%866wxAd<piE_;90GX${;wklmUd+`W8Qa| zGq^rYlOU~OGOzZVj4e7R{qewF^SFPW;e2Mf&h*^%DIrtvzXDRu#4f99^5) zpr~D!(x|8v>UV2>>^%t$<(M{Su@?+=9Mq_59@a87w1>^jsnr41TpJe1oRZ<$LmWgtTFgK2WwIjI4He2|KHanRdR+G;{7I zzZY#!?4-Jx?SC*@8-Hqwg&&UK=Hzy9FyOJQWXK1ckoZFh`@Wfhi@zX}&A(TQT4F_d zX@A2p_vF-EZ*iYuDNm*G!wfHR0}QV(dvk&5Gg1B4H+@#;@3V1bXwO?cnyJLfh+raSYY`44~T8+74FNaxC^anu%C@Jj(1lev_O(d)(ktw=dvQe`9&$O#NHNF(76&(bJg7ppNtf_*K?PkOVgB-;5up#Jt6uaD}+c$IOf*w~U3PII}Qk>^;%qpzv-``-hOAk!=J zO~;0q_(H|tUoQzpZ;%fcZ@?*F(Ba*rkWBZ}l2QSHj@iPa20C;OIk2f}c(LW<5<1b} zrOMbbvS-M&L0lI<#Bj3o)8~nt6eSkkzmnn=0l$+r;r)3fzqBBgBGR&WHW!Rb&pb5k z_yeNFi+GPnYY1ybVcdr5o0}+-q93>NJc{})M8g|GFR^h=fo-aV#UE+#dY##NMXXFT z^~Kbv!}EBP4G8~LP=z7gYKY!OJwbMhNHeec&G#rby>ccc;T`MpP8U9Ftv+}uj>xQs#&{Bw#soco}No_@AP{(g@=uj zBn+;%%Jak&7WnrgF2nzSYDeP;L_ zxMaON)>P)fT>+2#xJ|AOBT20_?+ck5LzT~yLe*H4-v>%ONIF!}HviPbHReiHE&>)6 z8_T(x+Qm)`(7iyMrt9Wvn;2ADH2Z;-7NNiIb+o|4V7g1h;Lp5;&epoKW)Gs#yLZ$9 zy2-*aDWN)AF5Gts_x5Ie#Tcu%%~McdnP8UtuWfSc0e^k}URq(SEH3wyoWP>~)|&H4 z0SeUj7H0Yp75jLjmywqeLur2sVSH->looB20x zNY$1@lIe^=^?CYxaNa`oVD#6w3zgIMEQ|?^#f&67>K$2x#&?zdCa!ABl&;(Cq;El9 zHrrn5F4|}GPF?N4sihjc-X_+X^VSE#TQIJuJtJP=CB0ARhMQ>0OMpef?;f_g~D&+^J2_HV(-9z z3_Oc^mBC;zYH#Yu==%mP_?k+v&g{&{p)09qLaoa+W$R$4x)!1Ul-01mFDY{V9_2ug zg?5=+(y;S$C{w{Jy~W-M9inwbOVthA6%Y=(|n$B+;C#V6^Jwk;1COX#}@Vx z(~*4wAn~SYahAmt{Q;TB0$Qd#mQPKSYU0>LOR^Zb_H$I9IKk=#+ zGvvMX)z0#o9Yg=!l2OTPLeb572>~^?@jUn;cui_V>l?skM-7)L$MIV$7i;|kEth6f zi1ekbFrCqh@T(QN_)0^3V_s)4wpu~%<&v5n2%r5Ro$;g2^1N~iH4azpc zi9Ez0K;S1_7T7I5)NRYUg-eD}qJ`A}lW7|@f@mqv7WHQ3;WGZT*TFKX0mVc}i3@$h zl%2~5|1i71=|k0euR0Q^t6g&l4MxZ)TjkEmejA_lqM6t}r$CDs^vQ&;S7{tca@_Og zp-YxHoj!ED3uT0fFl2{5!and?mL@(W+1ZoZ?^+(F;LmmE80~z=Ul1~!n_$2g|LV?X zt%cr+q>-`k%AyH5*0bTqc6O?yM36n#Qmqr)F zbmral&H_`Kc}JLYzh*I2c71*6TBY{;#&OD2a&Q=t&5c)VG^KjhV`1DZ$zNd#&2{KI zEL3R!5Ws|78k3ja2OBnPd-r3px9E||b)&YM@d3Xi72Awr)RAze<;fFbtScm}tO`Xm zg>+}X%1rLlL0Aq?QZsvv}|`lGyYpEsWyiz9fk`aD~zA(+Sc^6>GeQ^yH8RnP#YcW zf+@W;`s7vFNm&IEd}J-qLJRXd&Ud|AI~fil{29v%mKgVLb*(^;*|OGsUpv5G&o4{n zL>PL{efULZ`B;hCfnXSkmg`1l-Km@?t=iKv!4IKtea%xQ{8TwtwdLnQ-aDudYaWXG z@aabEo0r!U^*p2(KC+0QxdLfcex9d`wuBXbo>N?3-|tzHuQ7ZVdyt5F#7a-odmQZccEC#nF`r!#H~6%(%LUB=_zto?Fe9v)zHq_=9kah-^2%mIOO z;_z*Rn=+@wqXo3(7)>1;=)rfl zmxNid{p?(K?0$2LPg$^Lf+Vfs9W-}v+1^#8M2D47+r!S{n4{(x#Lreb(bpJA0ZbJW zojXv_F|8l6l*Jhetr_qRFSiWkdQ{5W@SSZXgSE;Szt$aR3XE6JKf>HA!19e@1^6?IFealeJZsOYpS!S;mAyU zC&*|Yo|&{aYZOfQX50J53N!TdB7)z9Wedo@x$FM7Z1vg&>6HOSw21`mxuN}m$qvt@ z1ZSk04s`onCqG9QhRg~kzU8MCsQm8sDPjr{wLo+NjR(%r6TD}fGhH_yd$%y%wvn^`+v}En=CQSOPy#>#Nqm1m*jHJLR;|3-2j`gE{|2ojMKEeAB zZzO;?EBU}m_<@BRd;UV0Fzqn&g#F1UBa4P9zA7=2q{zCX<-Xz!p)mH4MS&NpsQGEH zUB5$`Ub>ZrVXm=P^4C(<@tc(y){pM$Y5FDIK9D1XJ*vSdFOq28IWRsYR;z1C6RuGY z2mLZTt_Be`3*Fkiu8OcMU3ypIK4@rrZAmKxPKqU`(#Gf_JsI4UM~oJAB{wAPKGD-1 zkAF%(*vv_L@So8E{_=f76qFva`W^#7fUMa5fO1QVH%%^fR=BXSP}0_2cKC@$wI9hp zKDYk0RPf)qy8X>^JD#=!uzqg>rWyFmZT`9<&y@Oe;ew-q3kSSl>v{E#=znqgZ}>mV z3H}ys5G0~o0|8(-36i$uE?Ty(uDnH~pt1{@98Z4Okfne<65?G!1Y3xr34cPE$OE8M z`v9%K&sKgM{IORWR(|(AFNC@799LvF*JY0slTT~?^e4v%E4)?)pdlZI$>3+?8J!^Ljw9>O z@3lTqU9m4JBj}Km!7N=FW1=wj$dp*;T(;0Frbjv>H&J)ZpUcl9>FM|7o}dW#!GX{U zL?E8}qv*gZ&eml;q+h-sZlDo9N`z8`v`jgzIH@9p%pj?2V;7b7dY_?46U3G8Wo^;+ zqIb~a6jsrSq6SU=?Horn$bR*A_(a%B7*M%+4UWbW9Y(?L-3ofwAkN>Pi{m5;_?7U6 zaIif4fcj^b5l8{@1yW(S7k${`NUMdhT^^7dZIg=fR&`>%cqG8S=oCMj5@WFc>SYN$ z>Ml*IhUyK=BT|1S|MBc{XJjcs-7@hl8a8~Tas(1z*+G_-OhGy%>x@z z>hI1Ku9HiV=dn#NB{X3ho_Yc+yENyk6EXS%t%01e8x~x*qa?|APZmMESjiJ(WM~WR zZNdwpZN@H@2PVqBWLm&aVm0kJy~M)rU3~nJp!u`R4YUOv4%=NoC!khh+e-zy9wd9H zc29Xoq{i|e-4|cErdrB;s=BIRuS_qWlA9Jmw^u z`K=%r3}VyN(0p2B`?3un9(HTMWzv-#$4fqsc%$$#yz9pY5n#v=9(wu24hj(MyDxs? zBY+&`Qt9&l&@p*qFyRH>VTKs^vLjc!_^na%=8*%-A8D^1R~fp=?~sHOJ~U7)a9Q;z z>xuy3fxT@BP>C)6$Uc$TS-==&rl%C;2sbITb@B;Yug^KKGh@(KHRP3Jh)iaTFL}tKwHsnE;HA0PM@ zb-EwTuz{Sc`vh0B)HoZygZ@?G@o%r(jid0?Iwv*>l*DPLREx;rV59w)1=uqTaygqI zO`wW#K+}0o@>O-p_QOY|@ic>+cScx~2tzJ}IijDT+ma!s6f*9=Ff8`qVo2ECbw$)U#o&G7PvgPEu%nmx&uR5 zv@1*Ma;6}?W!<}8GvywN=Z5Pfjmb`)Ha`kDTfXL`Tf${ncn%LDTbOo6FxFj{4h;rh z$)(xp)o3fbR(Ljjg%YGaetp;8=0TSFpI}u17NK(_!#%*XbM)>dW#XOO)vP%b8u{=d z?odcd?D5YS-XpdZ)NawrK~SYunYWJ(8XSzgTPv9F#Fw-hQXehk^2M?@*J?$Yn8f^X zr%3a%Y?$yf>8yLc#lY;c&7jd??${*B`hW+-{74lpWS>O{XG|=CX?$zAOBrzj5DLKDhZi4oEOW;ZVtk*+3 z!_uMp=l4B1djS+@278&EUVW9dwY=Q>vEK0vc0@j&1m6##Xc3TM_!_lo!R)X3)h+lU z@(<`aYj2v*L0qQ41KK#*y}c?^T6a>ENFm60`zbX}f!D ze;D*sYNDll7E`RPupx0RWkeVi&*+|*eHukZ7eENQ2Q-~;w-CV~7=;49+K^r9gEUuB z?4s=KRF?t_R_G$94ETe)X_ZaHM@M~=-UaRmGaGUg<3Mp6l-NKZO$rHl_4Ec&caFdVI$W)_=RIe4U07$ivsmLi{Da@jtZgsi& zZF!Q3rwy0KyZ?K?^Y*u}VNL$#awCess(Vrc!%ppi*VwY6nNFqAH4zkO zX6j+jMQA%RCdUg~9@|x-b!CC|8GZ~?IQ+G@!skqNB!HNI>H;Zve;P0KV)QGW1Z%#b z^22@hHR!R0*SgR*d0Y9>31)V0V<^zrXj4 z#T~2UhF)OzKrkdQOPy;wvYrv`TcrqXS3I=*ta`&ul2CG^K=Ttp;AG2nnDE4hcOyFO zPG9%b6;MS)^0IIgHDxhj15=@z18R6r9I&byuz79(K+76C+PMzvIy|K>?hOF|3|Ms}~*RKIu z$vO683y>N8aNNL$zuo!k0%-NGvjc$4fbkEAz4i&9e8|Rer!>F*hvN;9|01lIU@dk! zc2NPaxEnM$5)F626hl{4rweIVU&v+S< zRwU{)%;lnX+N|xZij^qCJ_j$4>O|V**VvWnnls2zOaQ@JW_IO#QQg*t!En#knSG}V zb_;DTtI9| zA%ZiO+_Gp~zi31|VX73ucEW`0V&Uwv{BHBR|J}BBdR4Bp=H;9{`?Ou&sOA>X{I=-1 zDE!NW@HHKrmysEw#0i2Pg$@p8c`nR|=M}=yOVDBSpK~`NxAXjyu^TfrGao+>C*iA) zVG2!h@UPg`ljsp|!apD=j4lzBS?>hjR0idX%q5rNHrP4Cl4c;k2KjTukKGtf5%?sDOQ{es+aK5 zlzVMQ#C03)juiwb2`nWAfu5JKUShWM?TAun$A0dq=gYOg8}44+dhcb z09DTn-wr={4oJExOW;S2;KQBl-&*+aY`lR-EMDUad2Xxi!ZhvD!k*xwnj9-u$hTmG zwJD`7dR6X8);pe<1y0i_)jCOpE8-zW{7`8Lz6*rsw+_MWd=zh_?#=diJK~33J<`^0 zm*H*t6MB9r)6IQ|x%s~N-xcUlAJ)!bMq&uhjQQSt=ww7YNfnM*Oi^6 zWfYj|72!VgukL(p6J4UfN}-<*W2TuI+uYxXWj%;gN*LsJ+FMIbZ{JIYS3OQU>(vel zV3F7J!(Awx=~KIuESH2Qi_D><0bGN@&T?v~jLHqhsy%7-3BH0gYTS z*qlXANvU%6OT&2VvIGwM6oyJXq??u0F|GoEc}FyCuI^_7Vh%MXqBOO%gm2@BAL-p2 zVyWJv($?lSpDpa_ZBwSwi~83c?%!T{S5Yyo6!vdwYGnp*PA_l!V!P|!>@4EPwEZ(nt`+^-%k&AaY9C1=NU z0`~c|QFcqK2=Qsaos0AEWTLkGssQAoAte~<8kMlBy{=w!*{b~g^a#AzI#tjHp+h)T zgQ>Oxc^^{8mpP&mrThDi_G}iD23P7HZxY>~q(l?oiI>Vu#HU+mF%i<6KRQdRA+x=L z(O)^jjhV9C>tEa<)AYtE4FS`%NE79n$b8N|Uz=%Jqtn;UI^Bt;)H`b!YQ<~;i-HX% z>rQIn=hnqlH1X!CaKpx{2Ji=l?A^>O<;`u2owih=4}j z*oLa4_mq2hZdO-SGDW!t>!R3>5nCckM2>A#;$^qqKFdp|wqtTE>n1Kh#^-y9p}*|J-aEQX0y@4AP4xyVt1zl?Z&ZKTio{Mv z?8NtntBUS`@#9TgObd}Wd#9`Gx1MFj-`V}f)siwpWQ2XIUsRt33K6ie_;5w}ss2k2 zsQ)iHAk{Wc0>=+vR^#Kpy(RuTU;ka*5c+ot-2VdzA?WpI$8wJ}`PzyOBqQH6U}7B@ zqCopMtVu*HzxQWY+q+$prdJ#Af9IWQh6w^1E;`<(%lx0OHJE+cpbQP%BE(jOD(1Q! z|6+5?q9f?^ubCu8lPoQSv~YQQI+J>r{q7^c4y)6X$TsEf_mM2_S)JUEP5z*xu=Vw$ z>-+7f4GrPrb9pq@FrK4nt5YsDTfA`Iqdh0CNJjlUv(e5XMr=* zThA+twk4zm#w*PL{dbdswh2S((U^a9PVc>+PB`_3F`t=`~i)gs>Phtyk5AO z!=kSW@z-3<5=KefI8RUFE3qe8mNl{V@p)+>VSLFL?z-Oh;Y0j6h~V}$f|RC?OKynp_w_c`|-xlt@oEg$^5)e z%VwF0=Xb1AsZEHD_id(OZbR%JWnv2Em?(|kr|uEts6_gSiPhJ|g*?$pOAG%ABFjs^ zaPNQ<@jD){I8wL1>xc{ca>-IXjb%Ih27FXahSnwKtl`>x z2L<-PwlK(#NtQXR^0Iey^Xc{n=K8B4?4V`I9gs;>00hpe8emgU_HNt9o7e z&3n>>1fn*2gfO}r8O_*P<5cmKEd$#Y29_gZjBS|3En!w&Eux^ZMR}|48sfCx5rDN! zmh55JvR4G25)&bC+q+_4z4W?|OreEA&&RBYl>lObHLJF6hh)UaXT}|kXCu5j^iPJK z3zamJJNL5??Rq0n5GKq^R0o4^w}@3XUAG3Zke=@TMw~B;@_QgFT!~iEs;M|^sdO1t zlPRNDmuZ#N7g-;%qig4Z7nZyn{zh1uZU)gPVm{ZCA*GKxVA?-gi#vT1n zi}HUb0{{y3|7h(R;1ha|*r2m9on^qs6kq(x^hB{<3W7^v3lzB6>`nM%KX$__AhAYd zUs>T8gW}_rl?j{z#ZF(qpQW_K;j^9t@B0>&wq7-#y5{gMzo@y%HZL%lWXG9hOWDov zu;=yb`yfIcJF$dD9*U&ATx!q0YARhNmrzx9V=7^89tFm@WUKgD3I*nmo&IwEqww11 z{ra<30vKtQI-ksb%!&!n*NzEsRA`HaY<)#$FOfuL*TY{R3%Y zn>tcMWdC&KxMRR?WWsP%Ts!)%r11bC#v(hjh}Y}Ek>Z|pc6Qh9rKSy1pd2gU=o;C?HE=ct)yE%yqDLME*3+jI#$kN^3dUubgD<@ z_DSqb*tG=i2V+f8H|?P?Q+v<08*bvg(pOxI<0r`}sRec@nHsSkf;rWZ-rg@FG2H;8 zo+}F{t$&FwdNp(w^G(Cl>j?6!+dDbp@|z3|v9ClIkNA~l?}9)|i?y~QYtCv2=uUzb zOWqNj!Gp@M!vF2>zr@}D6Q`JKe?Md1@*V@s5V1`nov(<&IA%wv;{QXDBbBPXd-R%oy>1zCe z$1>3e=wfodm8^wbX}RuJ_V>NoaW?vuHMLY( zU9M2(Ni@?daun*0RMQ*xiDtK-QQU+#EQ2!w3U~ z6DL8pF%5u~)OOaxI`q>Vh5D8{pVcmxJJA_;&X_^F5(p@N?%-^;QeP)3;n&&Kgi+a2 zjq>d;jf;0+9jn=66LZCD_6cMAFrpWw9?Bt`QNkqm4{fhqo^Ej#OPaMslv<`+d5%yXr4W zzHQp|d4Y8gvheH{_kdO(jQP!1kD=8iD;D*;R;tyFeU z89SrR^&^n$dFWm3ti1TD54#$E(I(p2BD#{_ktrI$Q*Dw4WTpSN|N7T%=|8c5I`&W7 zszHbiDXe2l9aN3UKfg7X0srpQX6E}mB5#Bo>peN>dTZzcA9f5LQShy!{oe`lgCC9) zVtYFb;3546)QG8P^6U8@U2ycU3H6D(_2tXNCS736A?=G{C%iT+3@cCsBN-D#+}jbq zbUxGNuB@s4^hi84A?`=F%o9r1pkv#>0AaFVa5XO)jK2*=r{eDdy&8j75)q&CE&sb0 z`!(4q8j3a-A9i7%ereAN1NzIAJ04PWw==e}(;Vx6Kz;7#TDhsWSA;eB+WibPc@obO z6SnB~Tldz-{Jl2)y=P|3%zIX+JC4<=KfmR+uD220tQU@j1+z(Oh z8N76VsPT-ZR@0{RT*qLj5jZHeY|%vj#2xi-yYV%&;oj#f4NU8q;iwGxN~7%UNy9^@ zZ>7rl-hn>PTi;ZKItZx~DOF*^1r}~N{f0y!{HI#0IZ(T!huP22UO^`_@O$2=oeY`z zsX4zJ1!LCLqZ-Bcf4$abi2J6s@anYf6f$kSxR%;|@Ig)pqv3gPVA6rvk@-^DkBp-_ zF01YJ6TX<@`1w}A7QtG>xoe^Nyjv@1o*oloB_d_G+x@lg?6eNNQ~j}wv^mXbX`Hpz z`E%yk(dE%K+^sjxC2BcaN8X_lFUL*h**sHLKN&23IeubO{}3$gJ}8(z_D?WY{O{yH z|0~2n43f`q{VdM$&Q-_6zY10;T^>9Jph1EEu zDP5e&r|9veaa?DU)9AN_>AYW*U<_#EQALTCGGrt?kBD10fbd}-lzivO74^+eEoA#* z=?(?Yo7&@VqM0W{Wc1%&`WIPVy^3z2#PWybvXSYB-7qZJoPYE?;v0^4G?@rBAC9^` zC?z~B$Kf4BL-EE%9QDqtCul@OhTznB%|f5Vk%0MoO>R+3d9l{}e&eTX&(BD@!7&<= zrql}|d0!csjM6hk>UUU}CLPNh{(#C42FIQ2{($BnOXfGkb+?XjF$aNiJ7iJP6!u8# z%w@}77iF(>=ZMmMzL9Q2T~@9+4~ciEulO+5%xC5=bc=_xnjK+8OcUwP%Y;aMGTh7* zXr~?4Xls7bJj&gWm+TXeAQ*e)$NOy5G<=K#XCL^^m$|%n_Q1n?9Lb)M#w*q_UT6*Pa936=t5OhMXwu z_~&ph@hlJRi3%sgxI#~v=Z5jk;5X{hOdv`2tbp5J-L|e@T#mKRKNemKyc4!F1!wUq zre{Ts6EbQdQb1w-CD_e#d5TEnjQwuCXs?^}qfC)*z<%)gBOT}XP%0-7Um7>IW4KeKRrbURuQkkU6P~jj|XV=b1)6PmBO!>bOqF z$)RrROZ7VknsR@u+PvOKfVpG7Ssgkrc{Z->3?M|4IQUqdFC4uDdTv`6-TcKDqZle% ze9?J0AF>=9388Q};Z?EU^XjC%GEwQ_6GiSP7!&OZnWHR;5x`{CVh)@hzQm25OKo># z@SAoHY4!7|!dAS!C!qBELNJ5;sTbiluZ2U6gCKv8iDGoENzhu5f95wQaMw@2d>d3w zJVX4>{XJ;B?Kq2lI`XE*Ronu=9fju{pF)Nq#D__BBmu5W8j-PAPakkmVNbq+RlFqO z9v9$3xod|8(T5vt@5Mh<-I%hF$_y;W8IqP7}Za2KWB3933PB9mONP_@2|f|ZhauS zBft!k95+-#uSa_1%vDlr$r8nw7uX3t6H4HRhttKr$Ken%m};xMZ7`{fX2W=}RC04m zriaUeOzN?oI~uHyXUXV|u9w`>3s7OL%{9^X-?|s*n;n-9@4HSgNnP4d&S&NTG6+bF zxHOU_XHc!N_+-;9`Ms3m$%uZ97I&*P!eVQLm~Zu=%Ga`da)ve+n0$GG$o9d{3%=q; zWDfKpo_0QUF3^n|4=yTOA1*}Y>G|j7IxoWcx{V)mrVn*&>`Mi2OTU-m2Gv+ zDO+Q!AsugBXD~4k3jgHeyoPTxwn7ZO>FX+2yILz|#}QA5Kg%xv0WJGw=BTDWA#v&# ztb0|@@;RIf9PMLKv|OsB6IYeM1b)9_@|+>6&rDzQqp%0RI#YR%to^fje;?7FZtj7% zZ5%$;GzG8du2KXSq`BK>>EKd0CR~EajL8U0KX==eWA2N+%F%0WcH04C0&H~rU?+-c z(e?{sps`@iHTwnc3GEpl9|z!m`wEn7>ia@d;zs4-y=|AbU(u|#hn1VnzGsdY=4Hv2 zVZS9tbsshM>iC3?1mF0#!`HnJvd1Pvc3R8%qe?ltKVYGSb~<;BUp75y3U~9?=U%NN z$T$9k^TqWjdp&hC6%Nlkhj7Dm51r3KFwTx=7mrxcd=cDs93z?e-U0X%{_^i$j5mfGs#hNZ+bd6|7qM#jn8Rq?(`S#czUhJ9GH znA!GO!_jJlGMQ9pbPThR*A4i`HqhjD2wWCUUi$yB_uf%W_1o5P5EKy*QF;*-5R@jp z6BVV32neA^1*A!rCLvLfB2_>{x(G-o(xpb}9jSqU^j;H62&C}s=ZyD$j&C&R z{Tr4y>9ogJ(@GNo>P?aKzc^Bj{m(?IQfRxi#1M>rj+l9IBM4eH>B6{l)u-p1@jkV{ zn~zuQqZT99Mc7-d`G#PSEU2HGW!M%QSCk$@SA0$pgS*CA{(S!T{wxd5>q6CGUF?Xe zwxmybRZ#|-<63Q#dxog)CgqWrGjCpnEVUiXV4i(k)=2E0x*)G8>XE48WjezKXYfm! zbBkQTl8RmT*WRSG1Kq(M2fB7{>Qnbr6poo&&SCqU?~h)++mDiXwb3@4|B$DjU9*4L z{|wVDk5IJ_PM%xd0noDJQD7n$pNUo7uS0~2b8|3Hwh1UEey6&?F~as-C^o5f4Qhd2 zhHiQjRdu~QTyW0qx8^YuHI6?0c~UxgkstfdjDXjVmzrGVqG!G){-hbm^@uWzGWlr@ z!6E12>DYj|nEC~>x^q)H726=tJ+<-{>Y{;vx99g!64!S+&>;cxEkThmpb&hU(EgF{ z>`TW(M+#S4AAWeZk<_zW092l-So7Kb}g2rj87JUKwK8-Pt9u+1s?lGK_#=KV3 z12D`mN*ik5_~iic5Kz}?FPcM6>f<{JNwa$DttpTOKL8O(&Rxk+0rNr`c|V_xix z*%!0WJoo%B_hVkZpG`8%?zzcQbd(kV6Cl_S;UxHFZi4!3GI_(cP&Q-YBP!@KyDcFBO?BZk#Iwdrn z>;B7>z)uD=?mLiZm2crx6MHmKa&ug#K}e!7$@n`VY}OH`9GFF@dC-V8$E+pEH%XQe z&tw(!Up>9uP`<6@LldtLgNy)XYC_G`(`T^oceC{(lO-CHcPoOrMIzT|(1snZK{Adx z=dz|=%gde7mmPWZ?+I@Io!5U43GUyackWPD3;X615QqHN*nB=x(yJY(n1Zk48|HS? zu?4L{6-}X9*Q56Rat%xKE`N^GQ&tWJpMUYZ_gNK9Mxw68pd0M!ysA-iUHG*Ho!XBR z?`T|^%g!xa;Vu1cr?7ZIll7t=RR5tbM8&_uNUQPQfH7?PMzkPQQYEMOz-;lWOrq6v zR{5{x_@c^BU!{$GoZ25$hN+~l7j^0R7WR)0C~~)*-33&vWlBelQ)-|0&A&-i8Bs2v z_ZZ6(voz)$J~hie z0o5m+&)Co#Iur~Fak}$k_45u7l-|yZJQm1pFf;wRsqe!-vcj{#i40Y7F1;I$ z``A@-XLzg9k(`s|eI^nGd zD%of*8(d_&T+r|BS&^KUo0LOa)T_ndL+a}$D!bjiGse3-|f#+Ot_<%?VVf<Xd$`@GoX+R7EDqUOz zan-v^l>N69Sv&DuaH}&kf6_;PjQNl!Lk!z{PsGXnq6QqoNUAVHPlK_!QDQe5FMXqV z`_614eDl^Vy2C4w_Gk0@J6!KA!3Ft#`ck7t`Gk@pRBL@bM@Y80sbgC=`=ecD?Wp)O zr)C+RNDi3qM#hHLF-~cS4!JvhK!jyCqY`|;{i_qYP3>V_PQqrhfjomDlF6o;p60aH1g zfEZLxfAOQgOTC#QTYi_1L#pdAC-F7q22Vw%m(?ijoNNGrL&m61DlLd3=+R>QE)H0I1J^c0DbN|kM3H^UwP99?|``zATBt>9C;<=!8^BnezCr{ zJM}Lh1}ly(4O`x#(LaAYyDfSeE;?hjKFv8M0Vs%y_>_-SPMFh&n+6&DnvDv&!`pJ| z4#$=EUe={d%y}XT8$)BOtM^7Yix|b<>=+)+qOtuc5nR?ygY%b+26tVkxi#Is)mcdz$=UKQf# z#D87S0s9Y z#d#@lL)~Rgy;_dztjfEJCc^jOMPvKd7YZed69zLgxa2pT7sv*gluNN(789*!TVK6k zl2%al5|}nMROslOz$0z2HJdJ2=xw`9v+8=>{qDL>KBMoV5fGlUPnb2j^%cAk58|LE z2Ik$xx%HA!hT~aZ9nG!Z*_=QB0en~VhMS}<1}W{}O3_I;dO=T+3M|(p4y9Jrcw(96GoO8EZD($+IR(Ym z?=u}8f)5W6&0oF~Hs&TR{KdakyNL^mj>l>L;GBiD0}FN;dpq@2qJAs47Mh186ry;{ zi^_0*hlBnAz(1HUT80Q^_G?xR+_~nj*2kj99BusCj8D{)WBZ)s$R$i=?!&ajFQpHb z=Sw%eF{p4ipeZB*9Jqe(sAl)0u>yHYJ$zx7YFC&(Bac%h-ieF?L6mLZJU%!5u2E!q zN!#qQ@lGxBlJOGEyutK%N!T41*7>H->kMb6(D=Jlp&2+Jkq{&t(89V2HX99caPDBl0SL) zY@j*j*17h@Yt?lnZ-XqHzmJ)Y``_PgGu`TYc@GgrKG5<-x4Q38)Hr9!Hba1`BcaOu^m;(g51)4pV5ph%dZ^aq^``gF}up<-3tu6C3$-`zY zkY1;}sitoDOM`vwo^P1{*QosQb;xfHgN@vHdrjVTyUX5+pj>V{|aZ{!n@gjH#e#(MBRR(vg(J7HBf6JQK`E0`Ouh zan$}tr*$=c3VK?OkT~0@`x6*7%rnQVKfASi_xc`tPn;dMuOiO}>bRkXOLGIU-h81= zGQ%(c;A->s{>sV8pX&Q@+SY~ncV+MoPd`=X_I83Q{^`4KtgymL zTJv*jF$b*gNSgL@ne^jLSw&9qM?QG$Yx>$1Y6WAEZM+uflr{)52If<{>6eWU8I_sb zVO284tVzoF;6J9my}8TNbz|Bz>4mV60@ZEm0>znAFb5P>gPzws`I1ic=z;bVIh=N2 zL*z@ZB+2mZxik>{Wsmm?Lf~`{zF?j^pBA3>J(SGlmFVL>LhXVpR5*?`-D7Fp`}rqE z(;s+S^d!VvzAL#3(1U9d%2md3E7&C({MOiuFVyC_ z9Kc0Xp$(b%$i&E{b0fcWmGWc(!FuZm?-AbTRBC3DxLGnRZoZVkLZSot}2gfod_;}Y(W$M>(Dt>E`C;y2VqblPeJYYc4VI+a1~#;`2u9Uy;)rkP}L7&pZ9<2 zS9M}bdo@PaWJEINY`BanvA>z0OYN9fI3R1AS{zeFZAl!vl<&-u5-r~d@ei@9>JJ!J znRkx&W?Z;*yD#HI;piRfuVx}=`WR0;9lE^%pFTiEQEuufO{tbfKUbfb4(V=9kJFy* zB(wM|g*_dtXZg~uR*LF2{*=nVLL))B+jgwz`3xaDW+>< zH_C+*KJ#h|?DhgA(sq5-_dixQrAXc8D z?fUKnFaOs zT0gb6rKAr)=ppY}zRKzluVR>ZZGDy1PPXNJ*kgOa3o@RUv$u0XVgjgVSO-Jmjjv54 z+WATE>CUr79b#VkhWOrOPFQ7nMYbeJ%r!Crr5}BRY~JdH4xWqS7M98#d>`#UIwWS8 z@cJsQWO%&6pj2LnJ;9v`6U^p0ih!&^VX#x^{#tB{PW303x=HXNMBRA(RvzOnb_!HEGRVEXaR=}4jyX;K z%D1DKfP^2bYLf)we67k2Ec#LWke6FPft1;;;_@^^Mx^=r07FCWe>tO=jLOp9crdoY7?Z^23GFU0qqni@@)1XQ~jJEJkpL9MtF05zZ#*GmPDP!!?2>rfwU6IFq@rWkv#zsbYTAeUYA5B z9M{EMCcHu)FO9F1T2`NJf6P<@!{II&$)&uA2wQ&o#=0b6X`)$c;Z#G-z2PUg!!{&? zpN>%-ePmm_H(whIsPD>FR3UT5M9D_?U^%bwhSz@Z?8=)h%4L%Lpo+r#BY9od1Z&&H zs;O?SXAjS~FTPp*e13Fo#K3Zm`YG_lT=_>y56CVkph2%gi9G>55kZh|)*;6VNr``m z@GK&M$#VQD0ErqZDkSbOq86W{ng>$m2M*=eV;d3nWOXfE=1;G?$D_5akK z8&#e2W9j>Pn><{06FOcePa*&vv6&p8!XO0W>2dm#Bt|4b2hy8zf8FwmP#i19hI(A( z0bszY_&|p>3FXcs{d0>eib!j5I#tA5s9zopCoYTaMM*|~T zY$u?@HE?s~Dv}A)Q@gq=-jPPSJGlQA3;)t(bLu_+qQ>VFP%+dAI}=v-JdGkboVfMu z$%8Z&L-1%#Rp4nHJLTSQ%{6vPv{QA11$ttGFDq?JT6#22*^Ni z+Yfd;!{m_^92$tI%q5$@`gEbu?3gWNB*HmB)r3afQ9h#hN%+mz(G2VcKfZl61U+7k{tdk|0*fxe7 zJrm;W^Pih4y)=989|4|*s2yNCTEP=53!2Sk-rnIu|@_^MfX3pOXab9C)4=JD>E8S zOOBx^5?YIE%pbscEA2$Dj|%K+UwKp0b$jp33csiD0`dVR9L7RUP@%>aJQ$Y&oiFSIE_^n^KN0u@*|;yDxM&}gqgUkuQBO1d;TX)Ys= zpSWmNGm#x3Z#Lo zc=Ov=q^ec=MNk(@s4$hFE%?^NZNB=KCK_*S^4DImrGIrgj@)3!fBeTgrB7ApF=nt?6Z4mXAm`=q$&8*MQR! zGCEtwAVfQ7aWmmn&C=8mi@m^<@zB&bkZI)i0*pk^&8n^R(rkOR%)pBSF5cYtMP21Z zvZITOnI7Hw$@)A3M9QigtkMt3P-wuaHRztT@NQVrDQT-uSn94lpk|;_HkDdjklm*R z5~7Q3vjeOE$fGs+veC|vzU4ieydkWhKR{du1%A1bUbThdglk<>i_k(oy_* zSvqBIN>V`T$)%-E(4uE?p+BeyCNT%S2z9JW90+cJzBq;#Jz3`boJtiJ<|@U(-2F|^ z^unDh!B&ajfXj9`ekHfK-NxkO^7H;IkbVRM{AzC0BR^-$_f^$*&8IHKae#f~g$SDW zRl{gOwt<}JI7{u6@8bk%d=ZYJCgawSig=VtwA%R8H(uDpcq!B1Bb#;S6$_sdz+zXa z13%N2$ubicofQ2-a?ObbL{XNuES7rKlt*{o-0`ybHAt$GaPFznoa_>>9x*fRfs&Up z&ys%?j|!(wf4fIHxRNz&r^zb7W>|?x|oR(=I2O?ZHwUn^VQe(61 zsk$-Mau;W)f*GoCSS3N`wVqZcNOT7|4}zbafaug}ksC8C5{cF#57zLhAL0ewks<}F zXYUqGyggdFGvKyVtlYzevd1$z$-MGe$1CdF%dg%}%mJr{Zn>OxL31vj1MW2A69 zz?r>IEf0av0=z$_x_x_sr)Zzieq)st^f$HO9|msH_)~wYjP&x0S$%z)0#01ctiqMZggK>08QNbJ>|Bf(QMh3t6s5pftb@%B3W z)JUrHv}Qn_QU)zXbgGjH&HSCuoa~6~M8#Yo36hITNLIic^7H!g(eD)DoU7vCov+$p zC9)UIErz@+yJxdwFBYk&DY_Wak;YCyDeR1DTB9xCGND6Bhc6L?OKUMg^YWy3DX~Km zWUjVW5=-I0unWEHA zYk$b*b<=smbZ9+)-G~r$7Fh@sjZDm4g@m0J__@m7JiSWCZVAPdUA-)ijcP%D^7>w& zZ%Z6O9bb;E3Hd_J^)PGB`I)9q#B`S#>LMN3oV@Y2pperrhjKG6jj|!pmAz-V>sl(? z=fciGaU%^(=m>v7od)at_tC#E|F33@+JBf^ME{9o=bwhDKi1#B_v>HDL-5*u^-iZ^XIc>F zVE3`?t(oW6U2j$%^Pp8CAOiSlh}@ zlJi>NJdN5})$ZmP-9^yEcsqA6V_JZ%$JFLDcdv~ZUnL@_0RsG$A#&M1A{I(7#z6w( zY=^oi#ja<`TnlUa&^sDg411Nm&p=SJv>@;=47dzn76oHDPC$C$he2NaPXs!EBh_H4;@ z7)5q9h1gk7tgD6PlSER6VVpK!*Y#hX{a)kO9lrFa&Gh{p+B};{S<*p!DJ%%vHN@Tu6PXCbmSz&(a>kO+05Y%8WqV51Bj63daeIgO(t;BZ zH~}%!4)8+2RkGkCVk(6qPeA{IPMAYUN5IvAqe;S)o?-CH5FZhbn$slRA+=C~5&OtJ zzGJjH1xC>v$i$>%lE{63IR^*I@Ca&U8%iY1EI{uf?AB0wYkxU~Y@#%9mYG_p9n1+R zgbzns2CU%R1n?gFF_gL$Lo!y0=@UD1N!es#5PgRHAp% z|C-`sGU1Tt&HKkI&J5qc?uh4WGkY8CWGrxIcpm_IRx3ly&{J3^USlhyo5!MGaS(Ns zmBD)?h9aCeR}PPm#@aF8hcUIAIH8s;1DGuC+~{YB;FCH&nM?Tsr{Z6#Nb0_zzdnCa_SiC~glwm#rxb7_qYjb{giM*liR zN8_q#DWyQO_3~;`{uOkqni@GyMRyMEVlg|GkN)P$IaEalva{B{HI;E*?a{?M>kq+dJ{@dpP5 zFC3+diHJs_N%BUV{KD85`33Yr@siDBA1Fp`KhNN>^lBB;tMGL{UW9qG)|gm&*GS{K zbU^_645n0>Qe}1Eu8fu$l8;oSS-1b{L_4awF~Da|joNs;h`wE_6!w5~wXcwwWc*O? zG0;+LnAd~78iS?aR2lsb9)6b|${E!^EJWdB8~suEo)q^{TUAC6o%H??X^U12aczxR zlfSoLM2yqAw&?IKjY)M2cAoohQ&jvubOSDm+V?fHx{Q*NE8dbnA)coqLOyCQ@NwSf?T9QLUbNYzu`N&>Alq~uZH+TY zc6D`;*%-K`>AS=`boZ-Nv4AZD|0WbP%M)t=s9o8&y3qlG9Bj2Xp$_?=4s|TK;~1fKoVDnkd*3F6PoVg&ooEu|z2T0YX_PAdhc62=(JYkv+It`$}a2qS;DjVYI}4HPVZYi zS!+wfm#SK}Wif*-t>Qa629z=`185wnZXoVvY9nNkJtv?^3-d55LSC*_3-`T(FF!uLu)nsvxDs0e|A1(& z8v(CuOLU={QPQXveQYlD^Px$ODv=^;vD8amQQVPlV&I9yo!5kE!Gc!i7)N@;#U!mA z7r7DAVJnv+%ySt#Fb#NXGi@zocLeZ-G}yT@8*!#IKUY0`W~w>&PGn;y$XZRGg>)TT zU2!w{x--XIa>e1-8gg$K?&bCG2u$pc_>Gy}&^^boB>ye~LK14}e3@CPDP1n(P|Y;St(RQ^^Rvz# z^L+#SmhJtF#ei=BKGh*jxz(nf-0&tXL+Xr%BJ1z4+=v3b;=Aajn$9E3hjblE%{GoA z!+FB;$ld-O#I=rQFfHQADj-l-5V>{#4(K4}a$!?j6OKgdbg(Xrd=S)NMibTF=@_9#p6X*+n0;yGv>ZGQ9;IIF+ zCnU?Vh}T>KlI6A;a-}q-Ziv@rJ#^>;jwT170;8~d*bDTfwMU=4O|z-NwhziJZ3=eZT|G{JdzqC3y*!#3 z{)T!Pxf+*frK51#^ht2%6*NHgQzi1wIC##$GzjXhXf7BabGnM{NUE9g9B?W+{L;02 ziz+H`Dvxeh^Wt1qTEPuIVa?J4%FXX7Lz(kPMm<9Z!ZW|3xD8jOD(_MZ=>A_wR^04sw80}$E7pgk#1jKr4LmUy2wQymK=ivDm zJ8{(NAcS(@?=kw9->rLIK8Pv{Ejs^7cY~TZYH;8IRBQ_YBED@x7@h;!0a1fu2ma~= z6Tay}mx7P8TuZHajaubsmBMPL&v8v|y!AuHl!FMt0u%G@C2nU`p9~u8$9f!no80A# z*v0DsJu4V+J=b|_P1Qt*07X6RTsM~Xb%PmBqV<-a{ZG6^fUiXF;wk=6mDje3M`t7B z;sf5F(FRfaVYCD~AQ=mK#q*9K6T^l7T!fz-<5(L=JiA^-J)lyyRClvPL!RzoM?QhO znak~U1And`SbKR=_sz5Ox6f#-@805Z^%ab*EiH`@u}S-{?(aYQy~rmVA_&Hbqt!s1 z_dC2jOw!HiT;n%e_bIcssL1Lri?DkssDEXFzv|`wBUN0bcp^N@8~lC;MSr? z$N3iU{Tm&9yc#mhBH;xpn2=)N}X0<_rsh!y8d5o6!-XMcx2l=E_8 zOG#FhW*j>`usrRM_Y;cBj{E_xp+}l-9Z^orGyU!l6*{uBUmZZ33x8<>9Y6WECmtD( za*<#`Jb|&)4lM*$I3N1pZFqfd0NBDa)jaaftK%`01j-F@Np>ZoL2|ayBWkdGr!yReT?JTLZ;5?P7NpG$Ka^LpTdSbn>;=I!!{oQzoOe&>VpA7wLDK!SaGy5zYYu3itNQIYZHV(6&61d1~V+dP` z*GetgHwiDs^==3S=KgNI^YHAE%^rgdFML^Hf4*VTkQ@wWpK70(sKeLT-)R3mY|+QD zl2-6qa)Df?DSAgcGjh(-o5m>A`QRCmLbo{}-ITeo#{+IoaMa~zDk^EFJ^{fZex_3B zaPyBA?<`md>6;8E>n~n+ThWd4z43t5$+>07fJYAb0!tsvuf>CYeoHo~OwN<~$Q9h5 z1tkcfqR;jaDjpam42`L``)wE z2(P8_rdd@qhs1ff^a*HV$2vBf(h8-P=`ztBmt{1A6k1uc8vW!Ur$1BO`?>dHhD!JS7< zqI$D4gD+BIozSi`&|kH?d~M@0mVa z)K`^;-f5}5&O{v(V!H4Q<6=J6xL>`Jl(Ni<<8Zt)htao~Ss5p56C~zi2@fbN1dG-e z6x$k;3&njKD*W9^0F2EK$%D)RHWtCCOKPIyP}Cc5j;E12FSWmXT-VY`eq(pl*!0Pk zTPqiyiC{B>;im+B%p}|b4h%7Briqb%7UBvoREbUc%^Ut_-l{9EQEOu2ka2| zN?t-1^GK3ATg)e*JG%NL4ge8qH2_Mn0OCEwFT>#z(3y*XIWX%_O2HBUA>E4o4HQYd z;7LE^@tGu`WCM|%zn}!cbFm1A*yD5Nh}mW+pjv#B4Bz29K|0Vzxkyn%Q{Tj4JbkR~)+!R0d@vGl7-vF~I9 zt;dwb#HTHiKS8^-Vpzq;xfK<7&M!A4%(4HR2?w)_AKZX32^eVSp6%V!lU5H_+xjdO zDv%zXnHy-&xTx@eSBa4SY(cQ6r_Y5SUVm6N|9m3RX*W;fvH2K&$1RT72#rUvA{LKC zQJczhJ7ji8V>hsEX6$ib+TmecTbdkxu(G_~>0-#eJGGxk=^##|I5{20J&)ic+59T4 zY{6%4D);C;+;vRDxjB1qx_t`LWqw^WGfr*hzN{Jgvx7MzFCuCv_+j^0W6Ic0nSZH` zd3~{{c9*tMB_ zf+MQ(>W`x+ElDM^N<)+K2i5~YO&Lkcd)S9TT8oCo#ZsJFKWThvAUAj) zS*%1ls6qRy6;n{5kv`ygfb7K)Ue#yt{wlz!|3;wacEQ4kXMxXGnlm}7kf+u) zy8|`G9L&IL>urZNSbaGZq-a-Yo{416H_0lyMD9z&`3baCTwsIz2)vFWM-L8q)y`=pOR#y2D{Y?i1qd5fOE`{6Axp^~HaCq~IwkBEbCYKSR(-b|k0G{{` zPgJY2T_m%Ur0jctk@5D5`)^(L5W_0U_zptw3Fxd_vvM@skX{l+IAK$ms^zR?-CR?M z2Pc5D)S|}2fTD-Qk6?zcuU_P+HQe>jGZL7BYdWov19bv<*Ad=q?gKrcwd0WzfU;U-0a zXLK30sVK{Hjj-P2|LP?)X{zfdqHaqd51x?D3NS|tyM5qN}qB)mS7K!%G@K< zQqE`t5fzPro|hdUXsgg>Ip42oY|F8JdXRXg3yeFE#f*K2GM3kkWSd+}&q=U83=H6W zMtanjKbp?j&K~JVY&5Fz+FPJ-q5dtBjAf>}@hw1~9=qXeK zCm?2f8Hy=l7L3&&_?wdfvL=QNTml6F@CSc%fe9&O+Apz$kO{Xv{S(kBATIOa*u3BQ!n(4KAl}Ri{M1lXcGj+!6RL*_15xnyTQ*jw&7HjOrx;kyBj9&3kg*8-qk%q?1%rc@VLYN*-6-cPqC&t zS|R$ul!?{}*)Y9tky57e;}TjtM^YDmmEj>%C;ouz`6ZALuY@!-8Z|e`yi@od>P(mVt9AN?I&Ma23F=D{#A%YQXEKna=Y0@T z78_@|Y|w}6^@5}v6V`>9Y9Zj==L86R1-~^?SAMMokyYKJm$Z*G`7iC4YT~(Yns`)m z0P1}AQPOQx9Bbg!+Ed2hs8IdxY<9|U%YLDEt~@(HubmsZ8Mf`E*pah5X z3cO`--^MS}yc%Gx9)OvF0sM}pBxl)?^d_xG_3)s=3!Y9QJ~y-lec%R!4T|{TR!qt@ z%5guh3H`N3&A2>}E9m&sB0$qjCq2OBB3n>Y&Kc5mKe?MC%;t8Q+ zU{L+VMV+!0kPfqFe~z-~7%AWj2`CywWSoGcXF9RgEsPwE(?}qmm;gy(lkGwCKeF!2 z117=O6e(_8$imR6=n#u3jlZ8RdZqL6(qsF zM1m5^t4jg8+1dYhkN^95{EP38uc%F2j#e&TD_5il!v&!Gh*yF90+3tTIVJ`SVCr6- z!Bd{R5<1+A*|qW56L385@n*ElN{r=C^=)WR{_Y{+|0vA=AHsh+dWEm8Ph8at|L*&s zor2!oy$3ZmTcWqFQoN6RBOj;j9zTlN&Vf*L`42K_oeKS<9eeB^>TiG02ZF3!v@cQp z2RoNcbh1oQjq&BU2Q-mK)yK!ro6eFG4;)`2xz{P2b-mB=GiGYc7*y(ODyh_ME%qRfEpaqFJj?{(Os@0xdJ#!U>Ww!AM->|I`~-13Pwf!i=Q|5 zQh7~47&URY`WMr8W=hqe3;Zb{FqGOp!`7hTlIm$rpJ?fM%5iMd;&Ml~4FSEJanpuJ zYAG!AKp^Qiayjle>Fp;$mA-i)>~JIko|#}@1@8p!$ss1gC{qxOG0trh$dsk+$=?xM zZGpMgNue{lf>{9346){^f&wz4#ei@i@cggP>k0cGRcnSUo`ALj=d9G{knMUR^RZ!? z6Ya%=)BJCmp%djhYvj4I#x5uF6J!S1i7zY@Tc&nleQd1EKP4sxTgxRhzHd`~lq$TCuIF4HUc<;-7$_ z`9cEWR*7{+y;5OgDuYK(DA~iyY$9BFJmQKkeGsZAAftmZ04nGjs6Ka;fNubTI6s)$ z`%`vc!iJQ3UV9*HY~~8-nI`N0Z@4pMrb+m>$DID@dq5{%XyiK7s`Wk{5N~afUuQSj z$E0uGT1}^HA=Enu$}acN8CshV_f;kE9M~ZT6um5%)$$Fuvv0q82JOTa`?Glc>|~Lp zOeTKH5TZ)gN%}^rCj0ZHH+;gw#kcqkmFe6gX0{Y%4}@9+Z2&sdW?ZhH)0tgatB1|J zsx0n3vh&HVFoLh^7mT zi7Gzslp8f?;SgfUq4df$UxpuyNvqTm0UcYJera$Yt`+!i=JEeNIs5<8>%V&j@6XT* z!4I)D zRB?v{0dRss*das=^LrnKrwJc?<>=L4`&R1afLJ!jR4a1McTp?5xC2kqAshgo5jbEJc(_3N!-he+=x7D7URD zQ*|17%l^d?^%M17e}b0se1PZ1K-j=1s?$BA#4muD2QK5z* zCe;{+;nz&tQq#}qS4_QEl&hgREky2erzI|;6EvHs9!mGvVTm4%G-_S_f!Y_ zwn3x&69A$%e2Yg;N=>=d_=ye|!n+Zwmk_FO2NIDz4DZYwyoT#oLLDr^!(dXl+qk@z zf%AU()km@-9D*N?A3XYh+I#P)rrs`p6a+<)A|0fuRH;gr78_lNf^-1|sWJ3U06_ui z(v=pe5fCB}dLZ;7Akrn&1Oe%Zv;ZOBd*0vu&Aqec&a8ER@4Pc>X07=n>m+C8B?^I^@_0W`yjpT+TOab9&m8k)b%u+t zvH$)$NzgSDuTdqyp;iK9n38`a@qJ{Q5$vHX19JBZZbDk2Qx(tqj2AwD9=H1v{JjiP zu+D{@B+fz+9n#&1(Hq8F;n(d_1Zy?RSjpN%kKSZ9Mq(husBKcjW7o!pwfuGdp9}Aq zgHOJnM@aY*E&3}R1T28AQ`TWOL)T)veM~a0GCS>@aju!1J`V(9Z9J&gMhq7dlMFvg zwXaR2#vzfG2HqOfiQoc8JA^F*p*1EFeY2Qk@JR4C)(~a3;T1W{e!*v_Pbzc(Ipp#4 zwDSl^w<&TPi)`e(>HsB?CcWImr*W`(%eL)x|3bHP7;?g^P8YZQK(cfn!HXdRYxu~j zIkVQJ-|f@|53tr*7*H3-yj}3ozn2*Kk3K&9-!=&Se?zE$Z87`XzJGN=Q)*MOaSK-N zv)*<9Yg<t;J?WVIzLg&K3temSdn>F777MzWV z7Nl9XyS=%{rl~?o(`orp7pm&|YWH#9jYRdbYbRGe(hA(G62vWbGrtpHKDEtTN*v3n zsWD*fScA_K8yQ$tmna;66ji1#gVmBWuVlY17!(<-2$e!2jSw>?OV3On#aa4p-1{!S z8gD!*)8IeuA67nU2L}-Vw!=mCcn?4+&i4TXO%a6)w0#~>w)uoF0ShFNanuyQzwnG6)kd}opj;8GKRQ4z!_ zI*zB-n;*lONp4ENMOsqA8k6KtG(r@D1p!#Ic77_!+@TA1TKYa%Pr7A5jH2G#c8=&A z3$t5BvWcv{bAVKuDO%7~Oo)`JbyonW;LWnC#Ig*x(HcC3bEvhc{NHNh->wBKfHI)Rkv`(U? z{hI~g{{q(OwX5MruQSKF+bUUU%66JAnRz4D66x=D4gVV#FAYtPCf_*O4%Z6qJgM11O+r`d(L``2h@j@kL&KJGY9B26Xw&4%7njiWbq)d$Cpr>{t&yPbAd zP#$sFoPZ>x&i|5#5ktUKp!o5Y)vd;(`;dJmnx32As%(@UpSZ4wl!qe+1aEhz2RSf2 zHTxQTjKCbM${(^38L-OTAeKPUquc!YKMbmyj}MI<+%^3Bfhf7fuAGBZumrk_{S8MY zMJ=~Hy60SJ*QXv4s5|}CChH<-CU(US0Q=0hLqRNGt5o{!r9E8P7t2SH{VK*afkDQY z&c!)^(3b})i*@w~65`1WMC!ytaQVA^(i!E)&-dYrpMa5YRs*PcU;BVB#D6Ae8Tv?1 zQ#FTCS|^jac21WB6p3?c!<=DYPwE#t^XX$Lrz4*qwdLH61A>ucJv$+o93gj+gK{&_ zx_wq}e4EyDNdA51)G4C5iz!l%Aqrd(cdB{0qchs{>Oq)*v+_DWhCN%I=^9ev!?Y3a zj8Ot7{wk)Ala30fNL1^gd z>ZQ<*)vZCNWv|37Pk_0;9q-R+S5jsR8Du!u@?MI8D6*5!+%E4c1Bjiiqc+gUdmgRiz$}8{|uvHK9`%-e|i!(GUmsv zm?$w~Ru809Aq+l<(;D#?Cs%(UXRj*?m+*fiJzQEA<8hCyn19yg2vJ<=g2vIh@|{Q| zq#e^&+k%N*&nWFA8|1SJXzHq94Wdk$R@-ae7>s-NG4u8d!hz(VODSc=r&h8<-AFWF zK<&F;=uY1^5YSm|L7LPRf^X>=v@V(4Wb5B^=Y1~tOt(8!vgE7+_Vg&bDs3r5R7N@m zi!fc28%U4!+Tij6V1N4ca7RNKe)-O3z-K9YG49SP3zvI5M~#QmiPHmkNf5XzC#X%D z?3dM@_1S8QXYsM;+;$u*=RC7JQ@f5QV;Gka2d7?4`#s7YhtgunLHOG+b5MANs)uIx zDhJmN;k{n)tQKi-&0!l8BftSZPZHB3?EDa^f6G(7;HnwK6hiKf*pAx<8dL;#;tI6W zUB=B4j15Lz!ZqxPCP*{CadUT)gGsz7itu4W@;CXm|(uE0ohIdx!ij=4Lau-|0K&T&=|jQ=hDVkhwbZa zZ$hXk+hKipTA_r&&kimX8*S^ddwPO&U97&h{ci110Ir6L6mr-?1e1j^d8?(Ifn@j;~~jR1Aj*ZYL2x zuO3@epU2PVd&>r~K(-L^1))aXf^gRe+|$r;zo|E3dF{VCL^+?3U|&Mhr{OR)Ao#+) zpp3L#BfMH0ZX3Pkmk5^XhhrK5B{QZr(vBx=;Ogp& zX|keF=v3T};$KvO+`mADe+!hDX&orF8IM07>5ow6$M-=h%R?<2O>H-_XTEJx7LG8F zktraEjZgm%6o^U4C%{W&Fyibdm;Kt$kIXA}Hq&dEzL^zbR&P9r9$OEKaDCqRTR5*F z4KV&vf%Ny(^?I6vo|SdsKTntsFaCLS0K3&u{t+cHf-5Z%`(sANs$p2%K!hrcQ>B>J zyW;@L^>?yGubM?&^#n%W$Bf?q7PJ`;0KgMqXd-HK+AmvY{Srf_P)lHPb~Tqd@ZkcA zm(Y$xHABLMH$$ox(VgskpY!coMn<(KHFFF@w+mf4vo9n%6k0IWA71IB4Qp|D{0Z)p z01qarIA5&hL2pRA;tI?9rlvghPDgi$W{S8P7n9(pJ%*E6BoAMVY*ThR04IG7)BKN0 zpJ0}!?l3i=WkL?F6_c=4I3I!w3h2MPQYm&_Sm4yoA%tp@VBVP=i(JCQU|7it!V;8g z~C*U z#__k+1qclOMa8anxF!tiWPmo<6+G$(Eh-*F!NB}Zi&jI<-_Cx9RIFf@eSQb}oZs@S zZu>JyJ|v$5u*)QkrGGZ}{`oxouk@VeuYaF*_MgUbuJRzGzQoZBVf!g{VM96Yp#~2h z#|zRMJGdbI&Wo|l_2H*F%qu&D{i`J{;HgnJ;!Yl`U2E@@6-efBs ztS5;$CU1E!UK}8B_05n~eih3Z1|at4<*bB&oKpP5$@Fi>Fgwz8ccNGVS%awbBkYjE ztG0fhaDK8PNM1(Gv2bKGV%HAgzt`hO8*odBwDNePtH6wh?oSn%fq3glH}2Zm&yj2p zE^{%1;_Mt3Xxa3_D}$?5#e0zaB$(oV%*x8n>G1lF@bqfK8^1xQHGZd>$oBYbr8Mhs z+oEizEF(gv?dY!L4kj*pjVuIbBHydH@RNvD_k!z*o&h%4^{B8HmWz36o!L=n9oCIK zt;;NbQKRik9=tj}Tzy+dgD-bFJv`^9!L#lDo}ByVsh4)bXtet~KJLlFdd_ zYmNq>L(BwS>?HnNZ7pvbkC4lHJLpvy~-AP_zV>SSi8-?*_7j+L}t!L?47$+l+<*j zDp_$Uu`(u0<5FYW`p@1rfjrYecI#qFu;niR}Xl1WUdJAd~eYeXzzpfVrU45C671*OlYkA zb3>o`fp@He1b5}dv;Mhqfq}y>VtNq<5_v#NJHT2;KRgPfh?DjnBv-M zCm>KcXYP0^7HA-5My&hh+mq1*dh<<(qC$NVm%Gfg=Pq{AMvT`x(XzEmoF4j;#affZ zaq@jU6&fCAG)k7D=wQWTuS$7+etMUR<~7yt^Qv)@Cw!Dwul_Y}&)>VR<6 za<_)tGc(vCJ*ly;y31NTQbU1M=Ka`)?H+=&;l$N%Q~V~zu@+^G4Gjqo@2bqH&p3F4 zmW1N^&RWzBLQ7!sWBZrySP4%d+jC|0t~cC2Wv>5|2zVr`jt;{~(uCbdq@`7CESmD0X}FIztDl;%HlM8!So|IRoNc3Hsl%hTuL=h}=W+N5DY zB$4IT3)8)ta$kvIIc5EAFtZW9-)zBO;;aXC65H<>t7yigSS*p8HO!v z5if;ntU4dl>h98arR+fZ&<}`dhZUqd%ON&Gy#dv34cMOMLB^au_8(0jP%do!Pp?n* zDwR>eAK$AaJY$JP>T?JgUmCU%ou6-5AK#Jd_F|OqN#}FiX;FrP2fT2<`yv4C~zB!nSkCIiJ zzQUPnWd^ZsO>X#&9Nwjaxsxggo69osgw4JM@oHjKN>wZR{_1Gq`-js;_S%+D9!J(N z=h+E)2=QE~CIr%n-SnaP% z36IME-0Yo0&rQ2p9frzOPW_JQR!G0oWV1U6l?_Lq-6?FNZ5qS88c-OP*P2k*L6Cwk zTky@h1(;aVC{!v$J#8*d&PaArDo^keUag=2dOw~paoJw$kvA9?#hh@Kz8VjS9o8h; z_n*=gybG)LeMcDNm{gy?8PQ}b+bTCLv10pWSjV{#Up2K?H|&t7lYcAkj!urDxgGk9 z2AQpSjWT6-F-!m=cDJRuaZ2`v@FRr@y|D{|ojZSS>>SWrB*k24OHZLqK|x15==g(> z0G5qySelLuW9+~&Dt8bcSslw}ui{t1a+V2B{5fAaF8t`DHVxhzwxe^jc;qDc(>|wV zMpk=%F$2Tuvjq)i4=rIwEl|o_!a5``JnkysDftYDrk=ugl2?q)`)lX^Gr_gL=et0E z{R1Sa|2u4;S@poa=@gs|qmSvXA81~Ckmhscj?&&0rOL*g7?>T)w!Q1Q$9=W+H;HcQhr%(vDJLZOIQOc&yj`?XPkTU!n=>|6cu$YAT0|vqzmEG6F9BnVi*zK+e|i=s6-Y+pZ}`817l2yp6_QV7o7q=K)hm}D3nXDt+`D(bMz7?DC37Es^$24TG0Kw z#@=^VAZtke5dx4dKOvA8FZuEt7>$4Ojoa9K?7i*f-J|=MBai(PExFh^V4jMBvZ*Tk z&LQOiAgI#5Cx9=C!!B@Va@*@JgPY4giJwr9wW1r6uSX-UdKNfxiKeFMkL`Tfg{C>@ z#p9aH($dS_GdFgPuOa^9r^iQ6C6wT)0xLvW< z)A!xybRMkVGqt}&l`@V+4~cP}irqU^J5~9nwj0*s;%`21XHsi~sHaiiFhrg|tLI4W z#>52D{<#qgcG8&dRJV@?H z7SBNC7{V>-uq10s%b94-_c~M#sX~vNG)dCO5$Zkk=N)5Fl=qOHTEFx}MDDq}!(sI! z5U6i~Orc(e?lskDs-&3gEVrHci2RScaqG#vC2vlUHK%-VPB?z04mmeKI3Nnl!nb{( z$dcW!^0dZ%xeP?R1VL0^U*hHE(2D<;v{ND9g}Z{Io4*&~=Rw_?Jmb!oP-7wXbq_Y(hhLvd*8lKoy2uB} zc-j^U(E`G_6U%%KoLh@qHpF+Dd>Q$1U;TEssW;lH=ZX1fY5p*Xq!cc+ikYcsw~Bd7 zR{ZSNyq%kAm4wh7k#W3vqwB)`6|j&Gr{*%1?k*~q8NMMb9{OA5ZaEU$l-~6+f|4%EZ|I?rRPuudVrDX`0dbW-1x^Gri z)-vlNDUs#L-l1Ts0Cjqd-HouR=K0C0*aDYZ{l>hMyH*!kOGt2?x@nXp`c$%Kk$0);uJDz69kf^O3Dm6#oFiE-<;l07_~-Z( zVHY$eQQpr66>bU*3divztpcr~R;UQ7X6A|ef&zg)4@P0K1SoVrPe~TEE&qK(tC^K2 z%(bDOyY^RvUHk#*^*9Z?s*2!tq zQxPlQ)!dh#mS18$pn2K*0e=8z$h)BUjKI+-T}AObWj3Et4f8f2QxEwq3CSh3kywxb z`7(YPXXCV@sA2HK7HzfWU+g?eeh&LdzCNSn(bwhamkp{mf)w=v`B z*t74~gUdC`VL#60eqIxPe=B%xQgINBz52%*B42447}kp&o3veZypg7gPIj-(tGsG3TJKfYK`C8(|+EqWILLs&_H*dQHwbIrw zYF+d@)Wk4AH>Efw^2RxfwAWM{ddT!PI+y`5ziipiyj?)9HTfw-WhHRO#Pztq?>@&5 zs^1+A=d=Tl+7Ct&n-fm#Ix#FZ*0*&aUQ9aAj5gWA5+G9@L}@p-7C!(VA(Q}pvIX>6XRgb7?v{1_#&h4wjPQUwX&hzV-j3Rdv^iEGiE^I-ouW?_`ljVvxuR2Qme(Xu z!qOVRwtS|OG7^a`w#1lsWR0b5pYB8XpRNJ1!dXg$Xe~?HZible++C>BU6Z7Pqn3L# zx}q)<{jJ;)DWvh@q&tuMBx1~#BITHIc7oP#s_VYiblTredQxLBXW*3IykKqZvn}pb zbs<`Ydr0ZLwmI~4dttpoTAJVH5OhoCCBbnz8GYMpiCNAA9G0n7_wQP~Kx_VbTevCh zd};l%$l$2(3833my=^O0o*|^DwQl4&72uJLt)Di49t(29%;+dr4LZmHOcYn`8_xzG9d(tWhy7?ky z>mE{vq!U7bm=g~QNo<`B^$ljD2I4JEA7|{<^#A0)ir+hTSNLGv&R$hG&RC0~vV->J z)t9&Kx#!!UA*?6j^q}h&FB*BC^r}A;6EN2dQT6gRI;zQ;l)<`^a`263(;ZTZx_WvK zQa6gzt?H_lP#$gdp}s#zU58$@FhgR#_AL=QfIngM1hH00T_eqW9wgc>9ByjgUvy5I zTl(OiEa{}52w%Xq?~K5vf4?)OeSZsVm1J=Z?vZzO;Oj~Nm1n57n;StW^ISfo8Odoa zfEVFEpX*UR-Q)|q`(#MM!A3BNp3}J2OwUFitDz=HLm7#81@sU3XZxEx3Y*Hcjj5M| z4CMPRqo4u?-rmK0MqJxcGD(%Ih`0T z8S-Vqo)yV8yu?V+(h4tb0nkiXE{7PCJ$IATTTFU=9Q%D+%S*%HPTLEqp-!CjEt3dk z0h0u|hwKs;`0uGmzxlzE4_UP0wle)#WO9Sy!ZpCccQv)qTZTEGvsHC+^AzmN#Vzyn z3p~_j9;HTlllUUOz&Md!U<9kD@A0vvZdS`N6bMa`jhYw#Ga~-~%HQ#iP=5VWfcih% ze^o6<^AFOL{1gBCKU+Zc{V%Sy|A$*g=7+m5V`aMpYbnVdp_Mm9c-vOt9+pLE+liSXNY(h|JPtZZ>s(y?wJ@)~9pYoXP`6!~tVN(p z+Lw*Bs z0*cWufSqt`jJnAE@rF%bFuB-|mR0V8R`6m3`Z6v&n!?*aNPhE$(otfCMzU)<4168h z7NQ!HSCZ?aQD>lTM|Qz4lLBl=9)tkxvm)4aUOm3rjRnE!C6hk`u7Or6#U4QUY;_No zkm;zLRZ^~4HB_v~ry)zCdEcE9v$4P*7?47wJ4|r>?pder*|n!owYL4T$iy#5J3G#G z#;|hqG#p?pnz?}N>il|`I-x(^HM?1@YweTXt)$VsZ$P(3am_M)T#Ul=+$Il;vXiCP{Q6z_B$(4X5~(6jP_p=*y!QjPRI_$Yu^hZ!wPh|*LD z3>hM7MoHr>3+fqZfB3ce6^&Oh(waVbcpQ8;Iuz6<>Rw(p!@Ejz^see6AYJ zzbwcING-bjZGrLqp72f7vaDP)^<`q2;ay2Fjpot)#gswvE3kCYyiS~ge#sxndEln4!Z}V zo_fwDYSs|A)@bedLJF2Q`YVAN4V#;GH|?(Nu{RZ=Epnb**qF7EN%XY|f&5vx7I;0n zU(V{oFW=jK(8tvm=H$ZacPaJ%lmG!a|M5t z-&E~JUVGueKK8P^%9@&*7N{H>o?H~}(o*pm1OUP_f4H3jm$Ly&KT~GTP?MHWjIp?QLhIwmBuEAAA&Qo)A^M-KTni#x9FQgGNotM zLlk{S4~IF91y5Dy)&-c(ihT2gy16*>m8Q^7M2oy$;1k6xQ-2S$-QRL(tKH*yN_C0n zp~U>%7;5&&X%T{*!g$hwvPGiTxS*BMNQ2}WNQcrAnWBG*w?w9+sjfP$V z;FRx~tQJ{}Pn)0tD=iK1hvXbJ5dQoy@w`+jcjmIHQ8`@LbZiwPW%IBhS$0>%5E16m zi=~uL=fQMHv0Pp8{1PWN%qG*AI>n2xXoGDqSOK!k3H z)nVS+(Nm-X>p`Tub)hn+W)m`%btY#y0Tp_}gDb6AOx8Pxq>H5IG|t>IdR;aF=62EX z#V*aQ3q?3aA$(n4X_TK-)yh_PfS7&1r#_UWP1P~BU9_>B_$t@x>9JiU)*oyNt*blT z*F?yksQ*a1!I~+H1*(DWZTHH>=jlT-VY`dyJGs)ucHLOlFx;qJl7JE^+JQ2dtxEEJB6HWuj{`Lw0{O8%Hmav>@G@NE z0kk2@Yr))~ndbch(4)@nDl+;Y`K_%CsR57SvbBbJ))JYsTs;ntZ#2KXgg0R~>xf_} zhKuY4Ey9>=Ts|Xe0tP7t`_`wFCcFKaliwBZ`<6BMyj=T|P}S`z z%pHZ1sBHh(W!Xs22NiD9Z}5H5?$$PJw*A9is}`3cBQIWml1s~@@)J>|M{E_C?Z|fC za{at%D>z9{YFjq1i#Kja+HUAM2fiMWK#lR|7Ho}Z;SW^I6pP!edRg`vD;F|9FFs&x z0F}lJ+C30D0Xcg6BGjL4>`fMNxWTGd^7JQ4hIgA}gX2+YR+d(KN8zxJe!9|7SI8d^ zym{9kb8I+@ZkvV)Q|88EMS|R~o2Z0tS6PW0&RM;JvZr3dp=)!Q50inO$O-6x&w=q> zm`e&HSJ7=kwP~H^;6sB-3)frmn7U`P*7J%JRk1?7H^3RO!m@X0r)|aJL({S|q;m{x zwq?x6Hrui^LqtzBq*NahKB~bsizHzb=5{jBNuj&KE2rxabbytZ3CgW4&`?5j{Iu0=2<-!>$uKWw` zztIw;!Y7x1@OzT9P6QcGm^?hIjI+_lI8VZqgu1@|WZXN)l`p5FQU$^5bdl8QmStn$ z%vQt$LB_x$ebp7hblpePrrNfB;EYI6RS{L0mhKEY9Q||TyH7m+vLk^S>8&`*kB3M2=@GF~uoshOaOz_-jofl~1L z6T_2eGZyLUxGC#)s?OT)o_eO#)}*_ZVInZqvs{J6Sill7-L)W;x!aD7TBvXg4HYfj z_HdVeXjJ{cFN6Nwc<72f(~bo`ZqD2!quF;1l1UzG=mxN&DxkN#Z3}zcMzU`fK=5U9UJmn9Zs^Us=48quJlmAE`u#RpdfhhBE?p31RuInI zyPJ5W$45dqoY}$A)SudV+yB{XX1cVIrZ1q2WEG$vQ+IeoxYLxPK>^XZE5HDGR`^Fp z`H~M}*OB(hQ`wxiYm(KvY7wG9E1{H1iDy};$`I^ymc$r#;}w~`(|qvv@|5IElkwV< zU*4-;1>38~xzp0izNotG8YprinTC9y5YU|{w`NH&DsC>x%bTb-?k~G>zA@(fIIBcj zV%PgyJ{?uxF;x4?KhPWm>0XUXPb+JN6By z@rVfv)`VT`SX!i`OnH%%mjqfx>z3jd8FMO4g<2t-7CT+_(~Frle^G7heZQBIm5{-+ zGG{JPl`C=2W=0LP+WMukva+fZOuTG-v|OL**|;(48K9>O z*l7z1&8eWgwgZOXpS5fwi<_hrR|m#hMq1|>+)w4q6o0_=9H-B4-u?19ulA}3IJ;hH zd33K{3hEvo5GhbVu3vA{W-xmB?8r_yWlA22nsiRR0|4Bvd+OFX6SorK3cr*rdF|$*9r#gGO>;o5`Rj-9Fii^HX^+G za%I4y94?iogcC2Tulr@@yvxr)G9jurbOYTuH3>Tfq37Ew01@sT6l&@~!%tyi{EPH_ zQR@7wm6S)Z3FluL8>wvgKzf7Cs_~du4685iumgC^gDe)nnE58)3n>~ZXQ7 zAqMRPl@f|$){Ou6J3MEywqg8e;>0S&#X?9Gk^*0#x2 z;`yCe2e0yHR&@yt#?}w_T8sEljMt5Oh4LTgA;y|jZ|X1_LOG7O%+-2_7yODBbK%x9 zXQ_4~Klg@da9o{8`h||NKu8BxGb70D2Q_r?#SIT#KjpWD0_znHijiayTLI>F^f2kVj#dnYZ1wR>E%0kEo(Z_Xt_wDYkAiflH&(brvP3_icJgXGJ=P^A?_`Yx8La z&F8MQ`l)6`!<4_c1^d@ktea(Fqm#ZLnzMEArCFg~)7@%0H=0THvW%yFM1QU@*K>cY zCa$4?qc*`tuRKFiZ$LE78(O^YswdqqX$wRXhmKR4H^`3~NO0T;yR~ap86wt2qPzu?@2n-BSE3_rStX{PovV)UkcW-jHcK-0tg_ zqg(1~V$rDHF;rP5{`-%aPUv>&qwQ4j`fVNFB%ZrMViVIZv|JxhYv(?_PMd0WEE6N+ z+S8P;geI!wJ}kMZH@q>nnz=3VG6(apg%3%-)^_PTDjX*`zK6eip^OsGbrMMRnF}Pl z`;{kVBp)#`JpczxI1a~XgXM}{?m)qAe@(%<2~TY+iP2sG;mp%t}Ws{{V7MP*sYfI!cp-9NQcsU~TaYB&@qx~0j z*1@!ox*ea>;Y9vmw)=YhWM1B43*nfLeetp;&ofeb;J4+@;782_FR@wd zHyWQ+rsUQ1d9*|Hcb!TX+d#VZ=BV$LA>p`r)zxL&#Oo6;Q^&YM`j@G0JiBe|Xi7yT zcbXR_=sDv8r%{xyp}r%i*0sYm&-3S(AV*@n_pX?G%)kQd_f1omCb&MkM1 ze()X89OOLZj(dCa)vOQe7PaRGZtnGGyX2dgw;_rbMDCgAW0PQNOAG#kJ6u;=6Ehb76-B`!+LD+NlULOW-n?i0o>01`|3hT`@BTrE|YC zu}N?~QSJArE4pSXA8J`W(Wyq-t8`mfNd{ZX`{*Dyoe@L+Gt-Zogd^V7k2cPBbe5&l zlE(U8Zd0`h6NOtSE0=n8$dYnLtNaqUtHq9Lz4>i3B1@`)?b)|NkeutgIkQ_9H(pa+ zZahiVtDMnff(d7y?3!eCSV?6C{JG>V0#%*Qx8!Ju@xPfm8@-k9Gh($LC#fHJ^)}+F zzGSAVNNbY1GyAF{(XV<^au7QS(3CLraLeYPW80wPk7b!QKC%WT*&^#AdCU=%*h z*ix$CMKD3>clHvyrmOaf!LK*{tEEJ-*RcPEW@{7eV)oDMJI4hca`{&q@~QCZWL6c6 z(h16_;G40MIx(f=Mv`_y(RX@f17KU9cePwLhC0hPPaFL++P9v;8OlD&j+Mn=|ys5N=516il`-2wz))8^*(vch16 zKAxE-V!h(S(>^tyUQdnAxa6|2!<34_azojCq+wk(=43c2P_>cHwAoLDM^8;@jx9k} zHg43|-@G9+ZZ5NAN$}jJ@-#Ld2~35PJ(K!V{)uty1K|eF_UJ#3{>HZI<#`FZ{d9cv z9|9#i3fFX6uX4O@BD0#KX zW1LfBjLNmC%FQvFwXs7O^@-qfZxKl>YpSMGNLZBQSQAu(pLuRwN49is) zTq_Aj?S_sOu9dh}1uSHbH&L6-nK>&&UTImRa~nW{Q%BPBeX=)y7vR?Gf8ndhvC$s! z2}1gc#YOyC@->P^%tcIA4i75i&+tT*6CY! zsgBKQusQf$s&(v9m$VNqKlFnCoE;6b_APk zUIQ|Ur)Itc_7~@kZkbuT_&WqP$amYj*>B*Tx5bExqR7hak__Mmp*1SBH{K2Z+Dd8t zOv)cs_o8TeOyTM(S!Kj)I*pTHphxelr)!U_!V zuQCdt7Me|2aYyfd8vB=vo29ze__*7eM~|96a^!Z5tND)}RBNqqLR_sCiIr zunOR@EMTW#V8UQu#6?s+!B2Bx3{?jfhq$sgY#WYq(Y;}4qhXip1buw&Hwg?is+Q{w zrRqB^Y8CShUv5`6Rr=$hpb|Hezs@#x`gLcn=rU%brhOA0)lHjN|E2Qra6bN#=W-|~ zN{L?oTa2OrZ5q}Rzz%^A9w#hIZfG|GbXx(P2TBV6>ni|6mgDcEe}4iM48oQY#)!v` z(A4;^djqKnpYi@vQ=nwQ0NQkD(E!;Z*1szMr$V?0f9QXj`k(48odE1RmQImwQ2*T` z@O%D$x35hIF3+t^Xsj3XpDwZg?UKd+V_o7z61gG2JbHa1>G<%Mkr_SE&|i@r$@hCc zZr$?dGadehp}=3CX!@M=pP#V`192AT_GI4Tue>_LSBqVe=+mbh#&4mJ-X*K8`WP5*zVd~1`py#8nyfS^R_}{AL zzqy_3etSMC7r6J_uOAxsue!$<;%$R!I;n8 zA2VHY7TZ4a#xqXmVzeKS_(4P=!ft8{1_(HeS{k11C3+kr%{hHXh&#GSC zrMdI`ufKFpaa|+`jRSzBgzMc77E_!;EJ7c*7>Rx1C?34IXQ$_X&YR2u*|ZkIV8AflB)NU6-}pJ(l@?4+GA- z*$!PiZ{uu8!-wOUVz@JrXc&mlWS>9-z(C75IX1R8Ta%6Q))70I#X--)a`lLz@VN7G zarAntQaHhB-~ASjLSm1Jj!}Tr{eC@W5b$AF zbsHvIr7xw{it_RTzqdn*P=#D|U^iew8ZwoMd-J>Q=1 zx?f*!3MFC;tvXhw=k(lH26D_d+T4VuG9lYx(t<*ui5$0svNAKTthASp?(|*m7Nqxv z^Kx_Jq>H4c@}&7Pz}{bPrVhr^5(})TPIU2us7b$NXWO){%`j2i1cKkR2?e~r!Vr7I zdg)-u%xSShAdydR!ouVdvYC&6_&t(QZtu!6D*3&?w_m{C{+`(@PF6GzmwfCUo@7uk zH8Z1{wM~_!GEeHdxnIjPSfJgi?R@@oUL?8UvgJ1@{_^&)bz>Zz5t^xqrO>bf8k@!L z54(LEL#=sKL_ZUIstlLtvoe| z**!1C68H=CWl-NXJf;LLom}9i`0wUR_J;D^2l42VxK1uGTl8JoQojTUb zGaj~l99D}G>}8l;4iTn=K9-xTq~9mBTs?KrJl}sEVXi&CTn#1Ub0@A@rvyg&4DwwV zMws^h2HC(8G|#8zCDwy)!^~kTFDi3owe+9;JO*PcYdc#?Di;qt2mz}UJGgws8;y4HRBkP_swCGq!!oqG~@UE}dNtdD0)zM=0W@mwC$6QJPRyaZ)1<1Yy^uJ9#q}eGy|XH9Fk8(g zD+^pL@2z>iI&Fj@_H{HeBD31e<+<5`A)%Zuk;N(H+Ao() zV*p1rC94o1@xSbye>ta!JvB|3DH) z=LZH;H-9N0a&IC8h9I%Sp8Q0+#a8QTwHepzlK;~5nzaHQcelnQUf_Psp-W`_z_}ew z<*f5zbGUPz5eK5<>E`gNBW~T#qgaKd&8z%#Fi_o4BJLxQ*KmEU zkjqOJuPiYzCtozXh-w)T8bZ*wCUnE%LSv1L2`==038{HQ$P7pzW;=|T60)#V4-Ki0 zk}W#9rJee?$*)7o5S-(rXm1m%?Yf4)MzkDa>V8EpQn#QwQ<>u5OXc0R234 z;EhLpO8c-`=}KPQ@jOb8wZuZh31pa~ibaO1kB;t#PO})376zNWd`wmZV!^TvlSg>I zRJVGHKK)?ZVrFB>B=UX)+0w8Pb0AeZ03xUxn}L)`h?7@Be_pP2%PFGh94R{=rjPwf zTHR}m%yHalNKb?2a{K6ZSPTVRTf&Ry21Da+1^^)K=g+U27QA@9A(%qG+vjv@93Rp5 z-3cqp_mbSH?bnk-A3uowO1Hx2(CxRp6H#Q__13aR8cBz4v~ar8=#adwF+fV(eiF~; zX&4Jk%*=JWU%^?3f+q3VM_cBZ8uz*A8si$V$oylF=0mdlb}w~R!p(xgd(;Pb95)75YE z#sx-#U%Z~eTEDZyuTPgc5>+lg^COy+BW<2NrzTJ#);1zf5)U;(njX-PP8vgi1$Ygkqo?SFbH!$@8v?nHbnZak-eq@OgEw)9U?SIv>qvS z_H`61Ic$#MNukH3s`$LWZnt#pP&@WE7IDvF+~$NTUB6JNZyNvrs>U}2 z=C}w8*|5t}^w*4XFZRNyKOOKC1nB0N?E2Z&%JP@ zKB-tzrd|5kfcp`e$0#Md?{(>l8DMMM56;)LWd$|_3!VE}{BSBdsWf5}mANYo)Ni_C31D2NZoiSTylci6FZv1CiI0w}!z$i2~ zJ(eWFKI^*}9N)wvD&*QWHU2DZUJp*5&!jZu=dQh$HBa500DkBQV)qPh-8cXps)ZYD zh80Z$e3BvjzFP9>)qY$f9!vG=EG?5^M=_a)s$%odS=Z(3jS<0cUa!am5$+H_z1b9I z!$SU4c5V0M#gcXNZ0(7|&!8=)J!ZUQ!uUJ^AG%|6{*86z5D#Ntz7)qm>czy46MELG zPF++!_bGv20lTvqEC5vgOWsJ`^!jX{D1}hj*BnnVa?~P1qgPSJU|TOxn5N4S&p13R zr_4&RNhmx#NIR7yf;_I#iYfTJAjDJusak_C+IVY(=x;(?}0UQyu5bW!4 z+Kxvlv=xcEqUy1CO^M+>JV&_^<01J3M(j)&g9)`&<(^LiIGNHdboCTtAUm3How$Sh z3Gqwu?}nxd>RwK_%v+*ML&SZeD3K794Jm>Fk5{0=W|4jONlm@7;drFe+WrV`zA;`{op*=X(8xM( zPo!Uq0X^M&HSMs3ZsRQFEr}NU2ZvpBYV}vHYZaP^jF|~lxnL!)gD2kIu($r3VNDb$1Ej~U7@qk z@A_(J*{0I7iauq1KsvlW(U_p0)R8a(=ibbB+{!Rpm_hm2FhGU2^!6&0B{u2hrNQ32-U$QtH_en82KZt4WnlLcResaD4 z`7@TWH$q^+wi^KUyVRJ#)F@OH&r5>cbdwI9EJE9R@o@?!x(YKUwn>rzGpV1Vgn~8C z9^Xqxt-w!)8&?OZsy#gt7n(jtWj&yN z5*Rv~8~#Tt-Q0B1P=2Du__3lum}W3bmi{zOleZjaoFh(_{1e0A4uQSv+}%=g3|C-f zZM*$)ozd(2l+c52u~!As&swsAhVqOI2h*AUZB*k`48?xk*|N0|us&2ew#^N%frQ4K zg-VT&qoM@QBs4x+c!CscES=FwfWb!+`9!oPvn|;g1=3iGXRc_lnF0w#mvWM|3j|ht zw;HN<)ep~=f$>Nv?$|sjB0u)MAI4;Nvg$07o%|)%e8G~G?j2bs4>FPz8glh(^9LCn zL_3&X6*Kb0Gd^Vs9OYukVYw{!{JWSBg9dtjcrN^2d$!?0gPc(K^Qd@<=CoI7{(@gk zQ&!iJ)ny8um7D41KZSIAKSY*gug#wlrTz3nN2b=W1l-&T<@;fOl8Ps^A{KjCwa72a z^K~xa|7rbN^K4-oIt9A>;z3Tj=aG{HJJvN=RUY)95c_Tip=|n~DD>RMh9R{S@x_m+ zL9jJ8RJ|Hj?aID4<74{DhOvKFOLk~S>WZ(cE^W)YQ}IRJ6L|eybXO83SrYyjS3)mN zUf=F_ZA#_0;|38$l)&f^M<<}zzN@T5=g8M?+f>mBO`I>7+sYufchUWzACA8cg(tuf znp<@(MndGLu-^#Ocm+;!4|J}n=>0RoGjHZ7ws%J%a>!PM(5oG_@f$Wwx+?yU?=S2j znX(+zpqRj?F}tMa{tI`YBpPy<(m3S=Lp-ilRJCUUmqU~L`qsyLf0I>y!1HkrIAq4* z$Yl1MfX7xG17MDFe`*b$*PC1YharEEHDp+uv%%Gd#}@5N(&yB{xj|M`Rgcjdn0stQ za7xY$RwG-b`e+Hy$rD)KYaRQpOxogtg1|csU5-sHG^Ghn34g`Gg^7q?{6<`4Y6whA5}xdCRCq^MeMt86iOlr;bWEY4v_Hpe%;nr!xj`8 zKb!u*^sRYU4?dh_whwSPlncMRVd_9#fNrGyrFm|oFc(^fZjg8t9K#s>#KS_c(= zJ?T7LUuG)*+ntC+EZX};-TxkO$+3;y>UZB|E5a-2-7}gp#iJta;LeTyF-Dag&$bok zv#q?Owa+`-OAvS(H#N#W*+xKk@HHRfZK~MAK`LK;BeMyD{k^%;dVK8B1hS@~Ju>hy zVPo6%SWp0fO5J#yIE(6RI101VV;a@ECfVQ^rA5*w%vmUg+)Fr>EM=;sl&B>M0n>JU zJ%*;uI-eA1%A9ag)2%<^Y>3EAd0Jv5t4TnncnGIn8|X@?c7i5F93?;3sZz=;Tx1;- zL{>#1H`+MG6LC81W8e99e^T=c`Xxb@u`M#SiNV6q3EqqxZ6>tnif{RGp*!CZ0y_4a zbTLi>|Fh*=Gu^cO<^`HnIfvA5ib;Wsj={0@(n@|xnT(;v831r*U;XN<(fAY$_IoYY z)@!FdkwZvanO#4Hq-0+2)OV*SB1IjO-Lgxs$od{GZtK9@7A4j93ZJZ+Yg#=iJKU)g92q}9Ea2DV{2wZ~gxygBt zr+$H4>rvk$nG&#A#*2#QzeNq?Jtd&&eB_ClOl%LfMiw;u~0y6ZR*IC z1~7RH4q+;h7DfIdQHKO=-zUgY%JR&v0Pq~*y$D8-Mr;;1s%reEN(+b0!k}&bL`WZ^ zUadXwV>gn!?*Q8+8um}}$7=+bhYZgk>3S2S5iwq3I&*CSyJ{G-(H^lFo)xF^X-iA= zrigExJdk^UIP7`?oln6C%X)%yC!q5RIv5pV+Mw(2H6CM1_x^HXw1nT2Js5d$gc665 z)Rx-mYH&n5+4(~B(Z{rf$j#j9uzUyPrlGlm$_T{LIT(d4@gx|<6{GwlPPIloss`)r z0t*AlT$ASgTeWubE00qVl~rU?_r51~tpZp3$+g{2)X0ZUW#)BA6)_-_zFI+)+_eMe zFf_k0+q|7*Bdb=oZ`^Y0p)Uj;vOSSZ)3}(^98)fuVUPB?-w`2=|LRA6dImHT+K6Rj zr@$Y?6dY?k;gA(I%G$=|2ouAg55YsMMa4oJE?Hyg@XNhJ9S4cY-Vo_b)UXVQM6nJg zJ9C!O5Fc8R-2lNCIqvrg9iuUa1e6d~Y`HqTU9@#FT9)YG=Z@Dum36k#twSfD89o{E zD@PMk#38eTgTLB{2y8tsbr*O`SNx2U?yi$JFHkC}{^o;E5fs97O-bl7uT=iD9223T zh|auj0D_%Ui}EG%mS9YBa-DKhxXxV6_?_uGUncLSH;SBtdSPqd^{mrg?@idmkN?!~YB$%>CFySDJ@KO-Gc zG0AXt4uU$9Jv&;<#tz+EUYKhkMpoPCvh2@G?`O2XHe|S4U@)&)1Bz05_uv(* zO_n9+WXvUl4w%~=QtisG@fs4#b{?UYSYW4(m!YjR-y+4JLeI)0{xl+~!TuVS#UJ2| z6bA|DLrU7jfd#Yk%G&Ih!Y&se=tfH! z4<$#b$YQ%B;q+1(lPyEX4UNSop`ejiq{j_5y#!vVW?ZnE#57bJc@g=41vByq&6UJT z`5OgJ{=p~A{3i-DKJStjj6OW?r)190O3v&nwt77ZfqfcpoTA3tb$sNq56gcU5<*2) z_<1{vks!2*N()NExcF#);TDPV(EeiM%C;*KxMWP2X>#(sJH|AWtY2nz09!EAGleBe z4Or?Jsx#&>r#y&@z{1m&Xe@kj9pu$!}OXD zUWE3Kl~KZ@tY~xm2qcD4B#7jiMkiMhZ-B*!wt@@6>K|sP7i%u2bT>zqSL%T}3bZJy zt5qDzUO&jVckP)oM{^gg1uYhPMK_%Zf&ez{T}g-Iqq#;6CRGhjoBecHjnc$el-sa{ zU`tgzJi*uB6ei#}NNd(yI)zvAj4BxM)MBl3tk%H#xq>CERz!$s$912Nx6{)(R*v7w z91wPp;GEm0MdJOl9-Drx=odfS`{oq|cL1htxR{*1)9tCQ`jx8MBXQFc|Kf^*;^V=9 zJfuCIljEF`B27Q$(YQ@)+i~q!QEc1&ep`MX3QQr=t=~GeBwBh~_=l)EBLJ_u)`IU> z=3uClJZ&K;5}^0i6rQwas9G=%k!-55!vU{WwrYP+Xw{{dRzRJmOLcdqaN}wr09P;6 zV{s~6wPY)0b}#qb-icV4-OZ4-J5ZJ7ULDPyJ)4JZ(g8Ta?cF_P)oCcTONe_^6_E#~ z7qxDAS%5P7F8;5HsUwW71R9{p?O7_+&RZ-Enn91}^m}pLOU{bjYLIZ-WrB#RzJ z+MWgpvSZItw)O-r+NmvQinQmp_R%ln0-pM#rtBidN~twAobj~U&20GupANH+CUe)E z-Hwy~RZ+ob^65cUI$Qdw&utyt}vF9tO;@4JN6*x&_&P4Cuy)Y}!vym&M zU^b;I9zS#K9^bEJnd&7812`Uqz%pfN# zW^JO51!l6yF!Vt_vti*g&#Gm5_M&ZC(~fiYXVI**T-`ZhpYdh#Vz{trFcYaHYSRdM zgMbY;P@beV?Tq7lsCxE5pajB^_L;yek`2k^_c!6*s^+b-9ZZ=ZQJ?n9pA?3ZGTvAJyfpWsrHx$p?J zne1@g8=j6PeC93I2v8v!AhJu}WMN|v@=$X1>e}V?iPrOW<~k@_djDymCQNYr6;vC<2C0Igs!M-wu85k6A#nH<^&awN5m-jt~y~bS#JXM|plN6)DVXKiOCe+y=08%`9Z^ z*DETj_UW2GKx9%?&O69O{OY$yi+DeCFz|inFT#$7}v(#dD(H}$Y=ML z=K=lcbzz(E;9yi}^Ooi%(OvcBF5TSIeaT~p?={s?2bcx9gS-sFF%j~?q3cz$ z${xd|?TW#SwMp%B`};d*l;M^ayy^)w+!l!alC&!5{rPl}$riPv7e@pISB|6A#%VcS zFo1w#tS}?3ghXy=zX@VXODl?A$72!iaoIS5k!aT@^nHf%#sCEc+HE5fvD8+IfbRD{ zl^$C@wW0+gJ2_f;{UO!FjRE{Oh%wiRgH)Ofts7o6D_+pcFj&1|Cvn_8|-9c>XyE3Vk7`-e1Y%w9^*xf3NL+W%XUsW9r&Zf;Nj2dcA~9;_;W^=Z^$4 z@HxN&{xqfTv`%`~Z#SO+rRBACR8&r!>tVRE2VQShEG8P*0c>$NSRuj{b6#714|o#< z%!Xi*GiJon05{taoB7Fb$5%OA!dP4gZEg!mv53Fiv2ZpSA!36qV+rrn@W8AowGbqN zyU*@G)?62omUKTVGKGe-47|(d5|)$hhx2y1rNvNy`ogSz*!lhrg1JXpbeaS`oh}KO_o$ zs!udN)SxXJG>%cDid(bKRNgwrO^vo>4KkMD5bM1WYdIK(wYPU0E8)BO{VAV)r`xFC zg9sF=Zaq&$CSK7uApS$%%ejgpnS01mQuvzF*@A|NUrt_P&`K{6C_}&}nx`lY-Nu>f z`JhxJ_>zg=Y(4nPuiSejRSdM}*u7x)Mz|JMxDiH0*e;yv=QQ6`?{j z`~FGtmFeTfK$4d#l?C3GIq)&)sc(8wCB6Q;Z^-dPVpG0e@j~eLT_xP_&RNerkhXM> z2k8daU6u+4LhIZR#Y5U*tP8Kb3gL(7sIc`*<>-~D3G=zQsbC@KGMqH$8Ah(Y%%Te( zKSe`;JdONTY$%PszuW%}RRPy40+}FuAB>GOHhP=f z7EtR?ge235Ix~?k6!3Vt1FO3Hi@=5aK3==a7SE>*A1Vv->FH@G-;$Lfc?2l-GYgd~Xw@cO>L_j+R}f1W3HMgCL9L4}LoB zd8V2gGas!g<9>!y&qUm!+)hP4QIdT9Ocfth_7)O>_yqD|YW!zM9Em|Xc1GiT^&&~e ztoUU*5{4k9gy(`;MUkWFc1127A5(9KW+m=0QgYg^yPWMepyzPfOzb`WwmUOa#U=-N z4%_}0Xk>GAEAa|2Odd>R6OmX}<3kYJ-xd=HC{l1??MH7kpV-xabQ4zl&WJZ#1=139 zaJiHw9bK)zUv7BRAz`BOd-BUR;oXmi7%@)6HiopcHO9FPNi$GdyU~Ou&duj)p`P}R z#i>B>OJ}I*`5mO92t69cGQ?Hh#aN?)7kQa}4^z2lPaxuEd5Yc&iASHzBq;3z1)e?k z6w~IEgs!RI9q&(9tfK%BMpet6H|E=7bH2$}s~gj(zn1iUjBdfCctBh-erW9MWzE%0 z1W6%+R8!p#_Dp=0*keV0r|Di8mqFAjeHN=&O$0V0h(*NTXu}YDcmm$+Ox7VVDAZK7 z_PY22?p41e8(hk9;aP#dTM``&v0}jC5v(V3$<`9LJgsuuSOLB+~<)+l4j;hm+ z#wp1wTXtNth^P6;S`uMkuaeLvVITLH>@S`{*c*G(&7bxfsTnPB zAyeZA>eN(AZ;B)~(O)!|6)vok8qg2}!kBLHcc*h^WHjLEu3X0|O}$*Xmn>kzHVS zGXahKDE%ixj=Py5LYLw15%?=`q$|b^TntvK_s_Eo%DZAv1DP^`xA9ut?~37)NlEN< znHA-|=jF14ty(N5lQDiHohoIS+ zb?(NTj$bnN?FWV%*Aq(yTl`)PGf=MjkrtFyD^<-Y<@&LOdUtN)Ry{u6LRz*+)lAPWAF z{|9&%p#A@X|4Bmp-yWWxc+u@Ru1#DH>y)hv2j?)AG6jLR+c|oA`fT0c$#S$v7|@*U zihL=X`6p*njTS_c?|WSs!O>2WlIZo-H?_W{ z1*BkjcwO6izuyi)X=$Db8t=;y2z%EL5wEPQKtVyZpEis&n2kwirlsAFvrX}X+V6gUK1pN! z;~CfEPF?^v^ z2oh*Fp#Y}q!~2XVZ}e-Ka1qgvC4jF8&=B7pDapus6ZfT?w4Pd4(5s`==~)<9@s8%N(0yl=|q{8z*rBntl}NKfQ@(fNSPv;QsQd>o_;x!N7b z_q$&afg$QI34(-)C*(n27=M4cn4;a$YBV1(ohkckI6%7ZLs8}QA~efNSXgy5^mTIB zfo%h3O+6JAJw3=H(!3DM{4Ekh=qfmM3vD`E3J#71`$iXT!YC`NW6sSKjOrFjK19>X zMMyiWQuW1ii5Tp=vo#Hliqg{3!a`9eSS*(waG3E-wle=@jVeu}#uZTRr;PEeWz8O> zeFY6|BROGTIFi_@(!WP2%aI)+whc8-cuhk4*Hp`(2~Qfi_nopKIPqPo_lkQpbA1G6k;Wkx4QPS$@h)3Y_Y90db|J7SyWDKn&u z$yrf8-&_6~0v@{>lT?fjxfUtr3&PT9S``|9GeyK@F7Q8NMuepzM;hQcoXC#2vrK2y zQoe-9vG3Q9LhvBO-(3Od0>fy2~fs^NyQIkhsqo z7zzhk13e&7L=8TRaet)!Mw_13K`L$zFCp^m{^22h7LN0GQ>(iuZm2IM0trj$3UP&~T zEp)S#eIz}Mq^yh7kCZ6R3PT2j=1P4^+P?Sndk-8ts41_gxdTY&=OoSka4CC#d&YL7 zl~a`eBJ0xP+O3V*q^|jMXm5uGrImXp6vL8uYSt`W@BVg95o3^MsJeC2`(}d6MALhm zW$4@KoT3m%Tb=WPOqC2sA?ji5ef#_BdW`9!{h}+>=v(9$`;M!@tGywDC^wKhkNxX$ zVhztj3#Z#}3LCxe{>Uq)eH3~NZgbLA;u-yQMs z4)zM!3Alz-#gsc6>2Tu>bqZCLVyC$&AkV{2p&F=EXVPt|tExhrL_-YEJAEw_X#+H_1j-|Eg$xq3F;DdXFY-U^< zyuNN2#ZTbcMhQEMPZ8|&zW=>Q#Yf**M@mB>@Y%>_lFa>i!%7FKXKP8vp>u#$W1ha^ zK-0MZr!OgGC=yq5c+=;?Z`mk^V`M6;RIdi6_*t|lE_L!ie2cvs#wzCT z*}J14hXnv}B~ek1q!ks97of;II9t){frnbz{?Ka$l9rReZfxI=x7LM)b3mm4Uw55N zdd;tuOm{Lpqt2*L`NuHdCDh{9a1_QTrO|?sVkD%w025zf#>HTHQQgEvd$Y3Qj`5y2 z8Th~EI*LrwlB|3u8dI;SaraVDo@-!Zi$KAvJE;r8%_%I6!Y=x-<${P1{h za3CZegDiF+`yEIJVfPtn;p`hM>5gN2r)+xlm6w313@Uu8+Ase10vIw8($F-s^vztp zgOWa;SvIz>ZtMuQ1WOK@Ev7TGR559v4KnqXt7X&ekAGM(aP>0wZKFji){QUVz^0}w zK~qFQX({wl?1uqvX$xtCt$XMJN5ZY>*Gnnsr4~56Nh*f2qc-)@w6^knpR}U6R2dDl zl=V*Tp~N7cAJ#lh?Y(|!eX?)zF43~54@*f)izgPqpS&8tF_=Fh1no^Y-RkZp>swYX zsRg+-5DfgzA;sl9}qSD&Kp4fMn7-*C@g(H%J+13n%Cmcy>(ZBSE9+$YzjB1rr_ z`_ZIMU+<5xZR5eNp<9PqZC5H%D`V*CDw1=4Xv#?EV`IY#dpj%3BuyA8O3Spk(bCDt zPc><0Ghzwb>UXs4r}J#tFMmCBe&NNr8=aUy>tfd&pv$oo*D(i>l2(1Ic791qTih=+ zaiXMN!#J?kkcO}g5o?J0I($@p=VcA)uc6fHZy6SgPDz{igW=}|topAG4#tZtw*#t^ zQFy+Chm(z>fLi+vA6NN0>zKPwk84jb9HXFp8d1v4BL}_@8y=7EKw0l(*=aluh%3^9 zfSap=`PI4YS=@>s6A^t6=8c|87Tcoo^54^9D0XM^7vIkI;xOoE6vDh31!o7)gudro@F^T>QCMMO%_FKfk};;cGW*BwBeaGXG<(kFy+? zq)5J2|7aezKMu4%%Smh@8iRaLxL8S77es#7l4F7r3>ucFUPrlQcL&w?rADlY`S~WT zI?1+h2soc>oP6pC2Mp&jPcO@sm5EvmlRo20H-)~r8z+DB;GWj9Rq^;{_vrT?-EiGp zsS*0Q<+kedv`V+4PtkH-zfU!18}AzPDr~^oiIS?62YvMGy(R|Qd|B~wy>&A!5Zt8) zx44Y~_p(>UyX;O336Eqn4VkzE&7ay#iEK)QI6g^&ug; z+gl0RZ&X-HV~1rj-qjku5kT+*@%prks(S~FH#P*R1*nnHP#fnZm#Fs=)T(vc<-TL zeutjxZh(a1`vFi2j-N0iLNnscNV;0w5v6`Hoo3-m|yri41@$r|> zT;=%-gOUlxA)c+~N?Ax4^x9lOvDhb-TjOU=CmSPlT3Xt-=X*q`w{jv)Rs1GRr7&2V z*{{pNQ}JJibyT9>$pzRV?i$>ZBCB2PO}y@+&BkP8qQ~gyV%i=gU_~T`@eK)*EFw?c zzI!u>z|-q)ekJV<0{>Cg;=WM<#gR%?Q-M_ThgH$e%vjX%0Zq)ul^)%;C}{m|E!=&@l2ijm7)*}2 zOZAsNufCngEt303QG16T4B=t)aC`2Y<72I-$=LOjrmFq;48REWtX(%nDHZmq(Jq8+?+x1zwRsH3cx=@#&*OYVK%+|d;+(**8K|$2<$;yb= z)l8>1CT9XdP&McF(m*PcZxbsQ+i{Bv?=7DIC1f_3Z)~2+B#$;n*TPU~GgTlu=?*T3 z^HNxhhPNT^WxVwAIh@HsCMsGQ(c_11qp{Ui@3Fg-GsP>o+W6`$lBR1C^ve_=W+DkS z#a8SSharq8UzOA&x?Ag!WR;CJ0Bw_83^39wCJD%@FsSfWRcK+(K-}3OfnW~@N^`GL&2rmLut{-E~ zZei0*{%A-cHh96?hUDc3ygw1uf7o?TeNu<#!-~b_ynKKfTYnsF2o-pb?8BFnYiX#O z-;LLlRWG$LH9PW<85_5+Yrpi*7aHbWQ{{U`@!>YUiU@Jv$?;7-3(vTtLSW_&iZtYF zb;QlbV-zADE20bn0Efysz%5Q%=9@4r8opV;V$9SnoExIxx>5qU#bkH@Fwuu>SMipr zx4}u_Jtmq^$yw;4mFS32x%c0u_GDz-Ie~@vr&aOue=Ptu#Do~P?&db10ajTFrJ&zk zWUOjC>d3Qb{zu3A1k++w?X5-G3X@>lQC|DLAdAWIYMg!!=|_E)wP*ggzl0U6#B6TM ziNY~gxfCz^LFR)7X1bTRyG-ZnJ-hMwY(?MwC*7t}_p7W`%51l-9WRXd z6T1RAx7K{N%b5Ts4r5;1?H^@%g%>ZUjf$Xcj(iNTcAa~+Ih^jd=O<$o8nt>6Rlp+@ zuew!fL>gg|D(r-*Ztnr~+NE5Q-)X5DU%MNd8K=Sq(?j;i z6~DmGNm#j5bQu?mpD}SeH6iCjd1y}gR^R09xiyXu{~Mgh>rdxFznI`5LzS+<4*jsR zFI(+v9MdA=NwUbMhLE0o)|$a9LhjYCh&xUFUGM#BD$P-+PMlVMVKryEqwRjUb)O@-72 zjAY;aOn0XnQO+i5x00vuBeBg*Qc;d2;s`eC+$4VRjo9mTESAiooaA0jhknQS*nC;; zY*%d$9t{(gsNT|5l0x2cThc3%jLTv+0)hycjA-wNb35Cz*+e6&IX|iT+3Io^1^3dd z3`oZy5O`LCKyzAHOmp~D&9GJAZo)Dyy@Qat&`fp0MYq|r&Y0FVY^94yC8D%-cNGLJ zY;Q`Qh^++`3~zKr#wN@_ieqU`N(d~0&KpNljka4ZmI>Q6mC58RJ#8ZwcTKU5^ai4} zlM*s$_cBmw);sC-91W;*Qa1|z<7+V>CW@4gbLe%^Cv=o1z70hdgS8#6JjupvydY0; zz&Q<6qFL>e2DBY)pAsPQ`t!D_#sv#$a( zY23^8*v#bfIM3m6i5#Gy%#&>Pn3({x&ZevWoKY@4@TQStKl~6Z#cceMUvB&>&k!WHJp{n!1U~zU}j> ze?JR=xo!Jf_sE2Q#_KaT4s?l9lF@4vbwtR#*?waa!Phl zb_sTB^q`;1fJ!61Sdzo0?@g4g(@B}tC8-dcejw9B1u-GX9eyj9-(7fk81Vkv0h(Oqj_&Sl+nO5 zLPMiXMT;1hs`;(tp;d>tDcv7nif5$C0orWCzAt5k$*9#no0n4sCq-oaTq{{XL_W}vu7L;&un~O;uV70NwYatakE`7e# zkv;GBlm=;#d`3dfPl^P{dOGsbvp3o;9;n9DBNDCa>QWV#@v-R;Gaw}kqN=3tB1EU- z4To{y(o;258THyqSBZLRAdh}8Y#K^N%V!v9l6R4|NoOIirUlN}nKnp)F7R zywNaA&Jf>wg@dT?7{V(z@~K?X7$Q2Q$<)W1m5Ly2o~p2v7cH`!gYK?8+0PNF0?j;5 zR&yF@pYscF#5-fr2NYu)?zI_Ps@VI}SXi%?qPt0h9uHwD17b)a;@*P0*ddi80tPMs53kX5=@Hf_X z`<@`QYA{6)=6?Y(LC(Hg76G+>L9bG2S(JBn>8VbYS9W|EHn6qg&1#FhJ`63pi0a);eu=-!%&B!CMs-{tl35#Jo;~YMj$;c zwNqg@Jw3J7s=M)Fo**>jx?kW;Ye!8hKmdW0%G0=5`;-Ozej$; zN-!zxFeLo2mzYDuM@v+H_{Jm^-HuqJE5#egYglQU0Wpb=>G2sAU{X!ZTo4b%v<4Fs6mlO2x1{d)a6ZwZsN zUpN5^IRX)z4SP#zjS;rsKolavY#j^+OUrAa0L;#kl0>|$o^>asCR;L+ZEhh)2u5t! zOjshe1Y0OUE%!oB7$cyIR$_Yh(aC;*YQZZC5?wiy{I_9`6Z1R_X2QX)1B3tB0T>06qW zBC#;dgS{ z@uTjBfh0LnEmlV;g0J*Q#O1Xm1-)M3njJ|8dKhrPRlnWgK<(m4PR2-9h+1se&zhR3 z>et^I0gXT_MnDseR(x}G(>gW+%&Pf$Ifc1dUf+7C17=TdUjW4hA`T(T5dK3$;lv2L zyH!-Xn5wM^FvRRH+>*jXyzKlI4l`|Mr`i!$2vg7?mqIM!LdD5}ibc2}W%icxgL<>~ zCicL6sCSjPO$j!IWD{gFEW&3QTmuP=_+mF0AM{A>TWf=7RM%8_JZ=#Qak3|~AqyrR z3E_y3jbp?b77mm~q5!eeEw0AwNp=T{okRpRAmd14M;E>v2tsg0hUIz3epqzxH3Dq_ z0ZlmCz)jLk?3f5Jda zO&4WI$W;U>iK-Q@~Kmn&_&kbk$VjW0cB;!MN2O>`>GK@ALLDFbL*@!ADQMS8fZH*%}&F8^vV`EjtdRC@D9jGE~Vb55< zzpPd$PB1i)A`EGt%IX`jW}c6v9|2)=E?J16Bq0w*rr~w#v0_E#l9rj7n^)j)row0% zZ?3+o5zq+iECe*+*jdOof4#Fd&S%--{`o_jzi3_J&O;z4CwpN3UJi$S>55|H21pSg z5ojMU$Vl?r0|7rO6`{fq1VgSnkzZmpifl8pejpOrSm{bm65hH}Q|zp1aR-9lpv9LE zcHmkgNlfU>=t9k6WkCvOENPKZLe)YkN}Xbm4?$n#A?gs73NsD4SqtqG`@g_D_=Lg% z%rk<7k!xW43B9Q*FL$|W-0m8W%S8exj;O{Gfqzt$lw+5{{%wdZ94!7#X6-ix*mJ-?(5(o|6G=OyYgD8?7QZhL2!zWvtk2BK!gUxM>SAtM*GTYjj@H>LxhO$I~Cy_81Li!W2 zR#nkQ;qkpwSDQUavYBW*^&gFZMqsBS&{_z`A=iDAlb$rPe^$4G6!l?$7PB9Y?Lq41 z1+VRv)%*H>f8U-$T6x~@%NKsW;ddJO$@*UpDcH4@w^lcAn-J*Uy(lfsSy55`>)Zui zpDP@4petd{#wrx~1w|nXPz54lXrN@QH-vl7kl%0h`h)3ChciWZ`9wkx!s!NT6f`iX zUxe;L_`;D248a7%IR~^LD(aABOFf7PN!B3=hm>saB@{T&2jNl_v4@nGB*G`Kcy+s7 zH8s^9cP+-FqRqmJM3g~7c#YK(wpo0riQpi1TNs9tnU={)7MBONWkI*cBibSSh6t0> zWCtpgLOkQ2>01j_o*2(%6aS_R>l^wb{= zc^j+zpZv7mfQ8|sYn~(@`SQEa*)2aM-Px1||5dx@t>SMSR{NEGjxx$`XMwvGzNLCJ zdBN+NaI~|V%bc2f{KOQAT25gMwdMA4fF z-cu9vvQi5=7w$fG9G=d}TUx@ub>$UR6%|!g)wRB07>$cqBrAA_Jtf(mB*+IgqgH!D zf;SOwBe)dvxaa@wNJ>e~%&=?SN;~^8=L|O-z{4a8YeBkyp)oKG|x&q}QP_3EIKwFO^F_ zTK|jc$WN6^-Y@y_=+1kzgMR5Q7zm&@a5__uIp(Nf;GI>gi_6N(e0DriIFeJ-Asny) z#VSO4!8iCt2wGrd7a{pyvJN2^@%a+mE-xa26g#qlMEFOF%?`^@OIgu~$h9Sc3W$6{ z5TWcj1k(`fTcq8GC^a0G3J$)cghZ@`33`2gj7xCq<#t#5yk6iohV`aQl6=RkhTb!XCKJ)PjP-p~Hm8gks&U+S1bXYm1B7IA(3}`VH%9 zgljNBaA5UecP8Um74n52Rg1$GEGb!4Xer9c*N)PSr$7fZ0y`OjRzWy=6gnTCF!bst z{^0e8!{ZBMc)#b6oa6WFQeGWcBWQNH9VliSVxRUP4mI-Smg z4nAn{qQwgrE?T%~5rz+}%V3^odKN^$I27NIR6)hnT~ujEEBFa}&{~6dAx%hd3r7|< zdm`>Su#=F?LHHXL>I!OwBUte40W}cpLkKe9AFzD*0v4=dWlIEap>PyLFFv0KssT9= zN5B{Gd!a6*6ao#%iIACyvhXDW3Mq(}MZg{pUu@)NtU1A$g9Wgu zY3W_McA;#K*H^Z&Y}vBq>o$~aEU&1j2w|7%#5aeH{cIDQNs;XG^2{u~*}d^h=zvCG z=OfT62nR3>?wK*^wEp+LwumsVDR@+5d)OZql%KSJ(HVd1W^BB&q0*B5z5AlIK-A} zzz3=ys}95?NQvy)D3|>TjC7KjIcs(Z; znMY=N8V`Sc>4y;6K-EPDzoAT?BMnEI5vk_=5gaaH7*exF! z#w(w$=H2PQ-SYqU>jnlZww{0g+mZ>#^gd|!d`6u7EC-+6`ezxqd3+&qnOVr%4PLgK z<@4K;Dw3@%nrrE8Bo~9*kVZAM6Q<_br}re3!9u zrf9Pr(+zJ30TyZW?%lg*&z_@3?f&zxf6QC7hJD%u4-jGqAwH1m6!AnzDTXY9kT~SG zx>6TG9;SGC2{Q}}p2yuHr8M7=-%`RMHgksSC;0op=t9jy`22{pb=$B1XBTUTKSLOlQQ zR~wg9fcL8_7C-gcTQ$9tx^ydW78Rs)uUi_Em)Z7~@4vX)9F&(`{x}cK-nbmaRq1QNc6Mst_?@%Xzy_)}dx_Nj+q5#knLOA}t5s zGMgkEf+Ps>g^J&ll5;6(5LrZaA+Hc}4Ne865E2QIOO{MP@(h(yl}HlBIb?k_P|zY_ z5(0k_hNxt;3ZV(9Mb+qMC^EVs2VCcB+lz!{Vy$e>=PMfjp!STENv9xOH8;i?p0>vA>*FH6GM8C|5$M){g z$=L`z6w)atna`+!*(CedEVrd%Q}R4Z&OWXKoy9%Ne3tcY|N2V*&xkPjS&=s6jClC(inkgc9Biyl;1L!tciAsmWusR zqy|N7oFeMRl2p+RaUu#v)}k1QJa6=i4O%dvoxgDDhDvu*N_Hq*84kGpVSkd%-o00k zoLp_g(I|ZSqDElHBG9@B2YqMCzvH|?6CeA1!OEJ4-dud+83SIMy!*fYxAxUfSF@z< zx5ZT#KJe?IdlZ~=SdW~HsPBQs5nE8RI@g}QXU>2R*3BWM%@O|h(WmhG!|#wR(={xc zd0v=eO7ak`PtD-+L@@w$k?^K;f*#0dnRrt&MH&BNqS%v$r(+}$Q z%FQFk4#^=OBiYA4u0LbSoL4?wg#kySC0PRD;LOoCt~>07cSqk?D76fwzRK?_glQ^j zY5aVQ8Ip6vn8LIa+p=OegvRNxW~T`f2B#rGx06aCLq zCnH6=XkK-RGG(G@rs!4DsvJUzBK0;RHUBtC5IevMqmc#)SJ)j&y0@^ zDb}N0z`Ekj^9J32@en+aa?17*FMqQ7%qep|`o0ud#ipE_hgg=sU*0Z>aucXyI*nEr zXBL020t|wm{J8Gydw+TR%e4%8hm9_L>89OB4iJhMvr)+AMYhs2E#YXTH>M?#eA$ zT(ofU&vWJ$uPZOFsui2%;=z>FF+qHihB7nL_Z_#NGu0_%9s1A+Xargf0r z4F-#A8fY{SjgL#K;t67OBLSBone2@fD4YhPWyVkV%!KLY60z$!cT&@`q;FQmTWVrS8(J z-uP)km3S@9H_ZpUSWEd@lk#tMH!MX5UaQae+2W0e$+J) zBkDmIAv4NCM2sris8|L>`Oy!5MEhh`wm%WF6%H#B4O%Qt=!Ot)SR%F6)nywuRF;?H z;Dh~e*%Oy9tX17^FCM{g`r-Bls$4#oi&HkbukpFdgWl>Pg9nWqIdb6OA)0N-yQ{x6 z0<8;yR!um7YQnL-S)al}lF834c=WQN&g5u=(XiZd*1#hcS3W*tnIZ>x-5CGKTpW0u zcX*G2>;_i1vf09+`MbSU@(snlzy7BIiF=-~U)NI)EW%jCd{1yx%ITU7UJ+UPf~EFn z^VMkBo@dG2w}JSb7o}}Db{_USt!8#_XK@nKGbWf3AukY9x!@df9&e~wGD-BprbHrE z&;oggzx+!m3YOx)K zXs{Ru&m8PO2a|$!`26fz7j*gj_#^hPGri9f@_B3t;mrKpUcGx4b?cs$waHJ9s8b&r z0gXWGK%kY{a2Vj=LvZq01MrivywpAAl|?b;8oTz(diL587arLoIVswaFMio@_Puld z@!<-WCukI+0^iRsFa0sPv4Xp3*>l(L1~rLc8>GaNlp(OBj13?nmcr95wuT0;+@mcC zo6(e*x_11jmT>HN%y)W?IXT(vU?vx+2ulc7CrP1$N!}ocggnF*c~uYu@sE!@7gy`p zMqOA&iJZ~I>TmQ^WEK%Zx*^Kpiz^}|KO!vR#770?d0m{yrw${VYMS_#dH4Yh7v^OgdE`<1jvH6h zt(#Gy4rl~40<8*x)-K@ytke|S-4_g=_}JVZ|EfTZg0Y1eK{PD5KSw9>^!qEm`fVeZ zf+5RW|6BX<59`i2xZBZtbs_dSY+**7`BE=Z6*E`9D+4q#Ll|hf-DEF z!{8i61*w*dv6k|W%{5w*x?0jlZ5GoCPP7e2E4T?ex(OK>>0Ju*kpZkLtHFmSuE^0% z2$2Dkwh$ad4>9jYd4LEg#vrc=;vfPlN)iEaBF@Dj<5fa=BJC{dE};RDdDXW%ku`}7 zN^hg`t13h?QLHRZgwT&j-=&CVXsb{H;o@BQ2n&akovGol)$0pIyl#jHqK!Z>jFbb; z;qv-xYTYb|WxIQyyV4SL_vq1W*Ac^aA2rJ1NY+-O3SRxK5onzVv;o2aaI8$Z`$ zo|^aW>=L9MNA1-)22G)1IdcFDT%VY+jBVbyTH_8r_1^NCUl;f6pfg4yiII}SYrir5v3r+a#dW6 z{uMbTlORTZ6jhPA#o84Skcm}{NF%i>h6x7|(ZWb zz{{3y>=;{Jo)8J;=VtaFzU#n&1G2NTGc&W2l9Dvr5O+i$8i7`fK-(Z30Jux9jH^%X zd;jZ;pLlm!=e*?I<>J*CV9~HVbM1&3vx-?vE1ha2mX`bYkZjD5>}yZzmzicSUpYn* zj(4|AIM{x+x_rr?gbyv%y=f^*CTjaEpDKI2RW+A{*Vx!JWYH~Xyx z+3yTTTCDCcrteKpghW8i`hpF}IbVDUd(h|^q`;sBBCal#2+D9YLj0*q808s6se^O1 zctxHXEJU5DRN`A+5XL8}9Knsme_{7Z+u05!5VlrSyA!Nlu{uQvHazUof~3P{vliy0 z^(xA7rX+VN$m`s>Gh5j?l9Sm;R@R}vGy)odR*gWbdsA-&t%F7uoOVzVlGwXnUbu3d z++?a=YNcU$;fCEZoVIGWFypW#iec>g`4x};dkKqOkM1-|&CRpR7HsszZnGlFi-Zs8 zG3T*kK2EpQv5oXSEZuIfBuK}m`NxSgt?$6sh|wtRY1DwC-3PKVGjp=D95(Jg^EZby z%s>gj2eF()Ywj=a|e7^`B%sie!uj`^LiY#SqXu1OX>52(-ub~ zt;v>xQ!N=|#A*JC7T52Vl)js#Z#5^I+i-~YR(*5?1RRbeEIGP&>$G6uO15l8*(dy0 zU>re!{zn;r83{4dM=z+5{1!2SLDXf4hM_MqF@K^loGTI`Q$};hNOK8t@vYz*DzT_v zFcQf<#EGyl5kd_SCW$zNF32i(rA-KVtJ2d_lan1;nK}9Sx%v5dnOWkWGj-D*jWUn^ z(gyYk8jP3OD ze^&kH$93<0Q(E1lv!%yhWWkJMGs02xlV#m&maz1|VX^$Rp1cFScB1McUS6qrU;1G%HS|SuEb$mnQ;HNFNz|F`! z;ndUf^YWF~FWhMm&q3*eMd?E$pb==x2(-Q5u*05+kMsPjr1>jq9{$&oErE~oP%izs zBD!Nc4!*8BsqZt_?mBuhGfE*z*#)P5OH6m~h0pM)@0Uu!2?=sU;k(?1t>P=J4u|5oMRog;ufAyYK@JDS&gZ zP*!}K2t^&4i1G`0iFVda`}~cPfVvoY9;GNUv+R|+s#u7Ty^e51>ktKrk02HDTmDf+ z$wH!EDurkQ3*b}J@(KzZjt0E;nX~AyMnEIbMiFR}gafR5cS*hZi~)#RU;NLiujUH( z8!-p&H2QT-Wq|u@rPwXSe2nOuHF4N}DyBAXcE89|mOxzzm}~TyY)R=|)cB4n=HgmM z80ELo5T+UbJyGlG(g#2Ngokv2_W>iW$aMFnzJ3fd#M1WHfBo+Kb zNHWAn$~FWQk#s~zM+8|At4@d!PQr-bTdWq5S419DV#!++%@EPlB1)GDRCbYT(;FNlLuvA_UuqZ?x1 z67?NsPgp*Ja~R}<)4G^wB)KJjfE~ajLL!GjDa?5V5rIia_hTXu&8A3jl)~_bOM-03 z6lhF#88&?2z(IutLiDH)jetg=T_Vti2?zJ%_;FniA5-WLhHrg-!TJi}Z^L}Vm~ogd z4bSZL;LJ6X-&*+X#4mpTY1a||Coe2+awju<{D9P|YPigN_Q!62VVNCbq`L41^) zBP#8P;F?#8JtQ%xBN0LX0{;*nc!wYwQW_!T9^#TrCd3|u)fw^fREk816sIz!$SZ{# zl6e?6L&T~0q~xT&{rc}a?tor>`X$=hm>Ij#A05yLXau&3K-(r9bno)N_t~{yW<^cl zmgoNT_@se-U8h+YOAz4)LtkB7-QN`}Ccg0-Ctb_EBQN{B%TufGKYPT!!*hLs@avzi zIs4vUmX`=)(&!d$b(vc8-$cu%Tgi&wo!-FZfBcqPZrSOr zYTpgO+h$SME`tXT%FW5ZfE2G;;v>vR1!<7t2=y(MEs_WbVjw>1OMD}~un3-^_yDv) zPz;#_sRmD$l!A!MGFtwT+7v}dM5L0Zm{SO@BBUA7go0>@L%1nRvM1%|7Y-Y-Yer@! z?Qh>VNcT=7(7_SdG)uKnAXqnd>)8VlNI(&$yt>fLE%3%snC))CVtEC2B4 zOA{r%x9eiY=l4yu{nMIHc!Cm+kkn&d^;<5;fg{~2+&6<+x z?A5FHkfFm^lcG}SZ;gOPpuHl{<_QNkCXLtI=yWf!N_O87nehmqhAr;`weggFTb0RqH_fJ5T=Fak*&2oN%GxJ6Xv4;*lAyKU2l|K~?ux8_~1-oUckfZr)q>JzC_bE!G&pHn&<?_5Sz2|KP!cuYdjPckI}aPNxAMbC!k+pkbJ-Xl-qM?sM-PT-p~3AU`RT zE9~B0tX9$IFe)8o!3XYvhKDG5h@J@&{T6)NsU%0;6uQLIV6|*_OaTwZKL13 zXKcE}x8EPXdIM~dMs0K1GpBSomMvTMo$q|-{`>ET&++!Rzr9c>fHO93+}P34@q!n; zU@nt!0kjRw(bCfL@>jg<8Mi;}nhk4eC3Yk!u)#Y=1%IhjEhB2dVh4w;o7FQO?*J=E zk{qJ&VKhHP8$%9(BeJ*!k2&KZP8XzTl3)~ohq5sQUl=DqLs%W)48b2hC*%)-Hg3D^ z_NPDnwpc9g<+E2y0ZV~}Oo4@?qP1mJ`n%kHu}*NM%p)98)P{HiZ` ziF50%&g)d2f4h<@%TA|L41I*w{IfZEpK6Gl%21fBUzO9zA+elJK?q z+0TBK^T^1^>q=a>r0+s>`ngR<4aPTud>-t4#U3}@^ zj=cNxkA3XFZ(Y_GU)7($KG>1*LNZf6)y6CG`z~Hw{D*)1@$Y@;#{ch66QwNsSl;!Y z|Hpa91J2UVJJ()2(*X(vXRb<`FSDi5yYIex_wL;@l$q^&?Q35PB6;jFu^<0ufA(kZ zeCIoFx#bpAN8xiIUYVWOhAs&On8o2I#bPm77h_{%mFn(nE?+1VWxEom>Z=807ki`l zg9R7Q%DBP>b5f3kG)-ZIs9h_A!mubL(tr##)FI%*E#>AXC|Jgv+%%dLjYL~o5*?jg z=xr=pu`-cJfIuXlb(R8`fC8}E&|9b9^TAUpvGK4n^pGQ#O4zGGu?)>2;BO)x4~AGE z6$}Lf*zI)zvI6l-(5S1r$^`{D_$6O^$8wgI{Akz2|NP9OAOD@LZHdtO!PW=%CXuS# zw7L6KKlMZVQXl&JJx9Vf_r3aWKJcG^vGl$lNzR8KcAoSk=bi7A!|Z>J!pEQdiL-O( zsp`3c@w0b}owZu$Qnc!hJMP%Neb&x0`}gnv`OkmOy?T0jSf6PolDEF~t#5nV+dlTO zkA3*VAAZ9d-mpU5rD%_>^Q07j&$Mdw>ZJn%-@E(nM;?9j;DH0EkeYosf=GT7^x%cS7Y1#YnWdY^2}>m$!36uj`i&dcuirQ@ zxJ+(kou$A9$rORx+s6eLa|gTWwO~+DkXq}6l8_9dKsx=wZg_j(HQ3Q0UR+* z=LJH+NI2Zu+QNp2Sk#ZkVsf$Tv@hxpw9o(tqvjvHZ0+b@79T&%?rx8L@V{Pz-Y9_M z(Szxe0**qd`q$q)_>Vstrl+p#kH7UL&ssY00_PK-aNhb>C!3}73c~o8e{nwld578b z8{cr!Y3H7MF6vKkaVopaIvfCq=5{BO$)`N!Da7!(@Q?rakG;LUU;EnEKK zm&?T++9U-T>Qg=iJ|jl)K!yMg6GM`SOlDyX66H^zj9?kRKM)AAkNi`g`qXQ$yCKoi zVvTJmY3=D^QUGynxl}F`3uvY@932}O9Ud7TA05vZ^7&l8Tq)7N>69Gs^}@i5fS=wB z1Ob7=zZ1@%^wUs#M`vGOZ(D0y|Kh&h-mdo6mN2;$dB735m@U34>sn}lgC8*(4!rwy z8~@u!9(ZVf>My?X#M8FPcCYO8cH-~5YhUt1UwY!`M1hX?#4&_}WCjKY`}>z{*}4sl zjn>vSMs1QLn{}1~7l{H4LCLA){{4IJzxTe0sR{TQNDqU-aJ(fEjmDNN9cXWB0r$dV zL#PKoBN_>dXt7=^mrLnP27pq86;doEv)Re^@kA@8ZwCgJtXRHu!@4EXJW4#@+%w+eW42%Cu@wbD#kXx z``zyn^Nx4CNDGSziA%o%uw|$BZR7Ro^iY!c$7%vy-VDN|XGlbC=)R7(ijNV0ydU|`8FJHkK z843y|Zk6`3P$&Sa3>HB)SAvg#xB@9!C>)ByQVTQI`tgH4FX^);r=}l!L9g=Z-s^JMVO! zcw#1L&mQbcIKT5dGcj|(ccnNSANj~fK7j(RKQ~o6LJfTvqOiraL<#HyI7al=bG=%6AfDg2| z;_>J}UkCGZC>)ka{^B{LASh=H9XxRFy}uY9Ife!($YI&qja}{SbU#!vKpH`$CjJ0w zqM(hcFB}Mkk()?&r5Wx;G@ogf4_S&6=9?{_PsI`~@kET3-IYaMgT?-IHkZogld0_J z*s-7dWa`n!y1KhMH?CQ^ZtaST{!kZ>Jaf0E1q(PJIZ7M9@vAF7^^F5l8DUN!Raw3` z{+a(Pj17XTL}TLw#>R=i6k7BruK#@ZyPa3P%ITa#i)Mv+?KvzodEQHV{l+)G@s_u| zg?n6o{q=wIH-B?+$COLk^sBpeeksOfUY~H$+jZr!}ItgCgG`>2Xp0(EX8VoYg&@75+ z+d{EiuGH`|r^jQFMA*l)4=sYB5Rmku5Cy1_M-Oy*`q04xqvPW!+66y=7o=*YH^Kz~SLkCjGNtJUBj;zUjtoi@Lj7TH;m-+9URvuL~S- zK!E@L!c|Wk$?Q3teMI#}g|YF{wFq3!OdE0lHIS-2_qoo#eeQu7iE>%W{^egfZ+ern zX3bgEbLlh9ylQG8;Zom_RVR1ec_*ve`H=nk*T3H1-+!s^XzRa36kraJ#ecyd$b$i$ z<$?^o*eMV;M=mFl?P4*T%YsCFfgtj4J|Gd&!?b3ckEuP92hDIj$?0Et$sI{w> ztzWZj<;rC~|H7Y1U5Z@TW#N;F?)BnZm%Q)q_CToHcJzQYPOhlS12`@xhl4rj*MI%j4?_nBF!tQX)itQZyhZ8-e#$gzv!2UI0RsGQy@zCKT|9a0)eUX-UG|o~|m=1|}I35l}LjFiNP%7q^ zEML~q(Src)JRX)|XMAk@q5FR^nJTn*^)K)2ibo^h02X#1ryl}ZFq{ri(Fpk3S|TmM zGRz6KCXS;!8Vg3?%=m?|0fQEM|C!`?A)jV@plhz#42%YC7*@)xMv~nhXrX*G+!l|t zCE^E;j6S+&|LDXd^(CVpX zSS$f1ZY()5RBhmlkgH*4N#F;z~AON~d%C4-K=EKx(n@EjM=MNkn9qjKF*p7kRR}0`c{<#-iSl&F(u{hrIUXm+t zo>%pfRBbD@6tEPSw-i8^qN}Ux*YAAJkACvALx)EW9v-XJ;<62KIarDWs^vf>;y<)^ z57s=_Toa4N&rXrfaVDqJSmmFb7*FL2gUi>e2nEHX0Gb$0q!PcYanTejk@b4ESc|nU zN@UC7>GaY4525FV9tXu~Fd~u->$djw^|!Tm($d*QPZILrNT{o=j)DlB^d zqqAJ~6^kg07W}~`zKhh$|E!NUu`!|!*a0)6C5FOkJzwk`n@+PaWigjo36m!lZ#2Mq zj-!AD9LEu4z6LKRhhx6d$hO;3z*6ASQveKs#%OnU=M6izef``2ChMGl1NCZ%b=CEN zuU;uvODIDO?cY7PdLtUjr)d#rV|a9;R453Z5Q`p>YQ3t4FMtB9L6Lv7IZt%Nl`6F) z>tjmQe2Ilult%;;h{qB=i2DFZT2%Xe{WQ~n2x z7FmE33D&s_2GH`^4EE7krF+H}UY!{%;8-BPyX9~!kRQ@MhNZxQpa6DRy1To!ZQb~b z2OdqOb5*CFF9lHK2s*NSG*>8&j}EuAw|DpUw{`ZQhI!&c!wvXf+2frBZGQSM!;4yru0z%#Ac2W#M_w-v-OV zqs6>_qRY8TWnL4?Hr`UeQsDAX01?Iw*X>xmsGD`D%=@q$3Z*(q6<8XtR(#k%KYDQg z$k2hQ@zImEC!5WWj!&hsMPwJqQ`lG@2@5$zJ|jS3Rv|)-1FiW?p@O1l18qOS0)sLUAha%XUI+@-lq* z0K3=DYMc#t6gUa4^pfm#K2hK@TN<5Dq_J(a6tEPy5)^*hoH~tyFa52*+WI*QsP? zd@`*o@O?GMR|5hdn4v6^5EX_{iv)oX#-nH2<)Q@9$~c)5;fg4On16O)iH7|l@P-Rs zBwmV9n|C9*%dDUad`vWFu!igy=W|#LQ^@DohKN0hPIm9BJ#Ge3UhR~a=g)u1EsfrN zxAXFsJA;GsoKCj+mI9Unmz4r6SK(mqwp1nuXi&@{8lWg}*4eeh@z-j;)a$*wQk77$AAOM9!PgoEOqKN^E12hmg=?WEjIxJ)$Js}H!E`0ESh`|*C zM&N1qeXMMavJp_zrmqd0Vsc7#)N;H-cp}?Y$qx7R8fb;v;j1G}DVHWkM-bVdoqBws zt3GTw91EliTtW^9HopG&kDcc{#~B-wSKc~H0ZRc(fwQInlR4Y0EM2+?Y$0f)>R?_A zzgmHU?cvAR7C;2!%_Q9rjt&VjKWGgIm zRTQEy#DEd+%=8}#`y)YFN2`nrGiq@bfZ`r(L&yS?V5qA#9F29F7xdGB0B;l@7<~sPnRy zIsf{vE>Wz3(RtZBY@;m&t|SF|y1P~_U;fZTPxyi%6gVn%kcY@q>at=5%z-|IAC*$H zIZ=q1nw%OrHn!)9;X;||Jy7&jQn^xlA_P(ZVw5GDFN7CM>0$_@!G>^I83s>8f`P8q zNH$kSO{7rq0SN>*7$?FUf0T`mgZ{R7Fcy}Y4X*HVNQB96YWIq|SAjZ;GFa|g17TEZ zz6iVHqL@-G6tbmid18gr6z%{3KmbWZK~!|4qpPR8ufL_Wy-}z2KmiLl7DzX^Bpi+( z{?K{JOPt~185+&JwKH+nXDMJQU@34K3beK+mh|_=<1w*{0l26-<+>lPhG=G>Pyu#O zDG69aaYTJ|GLtO=H_(jmS8KI&u9OJFDDk0bQ7Y9!Sj~VZ67U6)wIG>MriJh>6ml3) zfP5p&!jrfYtp(%d8tZ9A1fw}wt`ZE2(gs|Oug2ZLJWY_U?R)}vuefwHg`>*zAk zBU^#dz|=3xQ{`|=Xoy9sP9*4$g#xiiur(HHjfdLea&C!-6A>62fk+5lPs74EzTuu+ zMOvYUxk!U?Y=NuN6lny17*K_2QY_{QxeNxGOwDY)v~lIyEtto}SL8QYe#F zSgr$;m>gHDa|Ksd>*Ft+=f3zHj?PZ!=RbFDy>%9iuHsi^79Fn2!1CqGzx?GdKk&c< z=IKBB(T}pD_f<&=`_Sh`0Td}h;n1?Bi&=aMJiviA$`wH#qLv{#9Oz_-3MQHv`CC{Z>rUoEIIOIo51B77? z{0LJ-sZ>QNO-~|V!UY&J(52zi>J?~+swlh-fg8f<09z1^?Nko15O<9w*s4BKDpn>( zk4=tGB&ViQ$z(R2%7aLXMfTBEn)=&(_FfVljy-#vfB*McRIxf7 zv&eCE1)lrd=eD-Ce&s7)*|u%lFMs*V0|yR#>QkS(x=3K3_IxP-lVj)h&G$X{7~75xC(}qT z*pS5+uLs$%wH~PWF|C0(#w-eH&pd*Zm zR#^B-yD^p?3}#bP;E7@}kLV^Ei#mSnqN?IZpQ}7VGRp^ z(P%6f3I*6u=0tH$bF&tT-vW*W@=IQP4hMvJ&wE6n+_)`UoDY1!`RZ2}2)*oMoI3?# zvDgb=_(A~3d*1V&uYK)nOO`CT?Y7&_y&7BMYNPyiab2j;9XVRqL5-HMt_f)pkX<<4G;!|I-1Gi8eyrx*(jIFr2s}t zLyt2P$tF%1HmEQlHma5?g+Qs4%jIfg)GYSG z*k3o%(h_fJjYJ|~5p-b}Y8SD9V}bm#vvoLTRDEM`WnHvwY}>YN+ji2iZ95&iV>{{C zwr$(ClaAi`?yI_0x6a@F<7})o=NfZBKld@9tJ^2%=P|%M>Sv#jr}u%@S<3@mbq~GP zbNE!?mAjbc=MM4bZXvBFx&DEMBFyi}r3h&8ru5n7<%U05rZnB^ajNfIq?rI^UTPZ? zdbx5KMkcM@cK&oVQaX&83xRB6#oAF*c`{p$yXOT9rkH+Ss7Go1bkb6(t^)nz7dwRT ziBGAct1`MB)eX`fagrY@rKkv{2aU>nRWM6(HL*3Wr)fLwkHjC9eNaZcXiXaOmwZ`; z_+!=#oo>3=YKZy@{j8Z#B~4(^f}AM(3c4BeqaaAv-%OBB3W*%!GYrOkAv*O~VMn1= z`%+lyi!C!Vj$AZ*Rz}=_jd|>rJ8N*io}A%mKXV;7i-Q}00)(oWPcp#4@BxMy1|6>F zojcDp+npW(05D1i3(+j^pg}pmva+$7Jy*s8##YAw8iICegy#psln|BTQAD{7OK!O^ zaDIy}<0s?w%gYlKTulI3Z0v>n%-1ku5bLc_D?(1C01w!d63VtXa|ANoGs5!sHm|3V zJ&q@~@YXD-qy@kK9I_IflJc z$j&g%bpvcwvE47VdUx6{YhbHpF$|c{+AeE4f$+vOFs4w~A=|Uj+V%mi((njq&h6Vi z;YyZ&f0K|?oH%Ekx2rI)v=)U~ZI~EJfZDYs5(OL6t5zI646D`5&Ewd_hV@|xrP!7q zRYDCQxq~cnn~?Cf!N4)q4K72N-PmV#!_Opi9J>?jArT6J^5P2Np=ld&zu`U62ExB7 z_exQe?b#*Eg6{$2A*lpOY$@m(z-u(zSxpdCkhlvCv@7A&D-~#|xSU2xY3Y&Sf%u9I z0B6Dw^fN>ZAPW6S!kh^o#7R9mLVMS6Sc~z7L^Pses-4AfoVv_&D8278j|F118w?Q0 z4S~#=4e&3`H*=Vp8~B$EuuM(3txIdHj|24KrwYJ4vxVZ_z3!*AOW((rJ}-!%EW!Oy z10g~}sm>ACb5dH^IB>>7A%~+ZK_FXdEB(QsG>6AB5<|58U=SQsRI)mz%+NA9p@ojT zU;+6@1y_*fw!*jvd{e|J&=W}Yk%4gK9Rp#`!JJ~c>Ts!p5kU1|Nbbo1s7ZF%7^6ml zS(84k7zs;skoL+1Az8)s-)0LawNm zS%WIY=3Xo~*2K61q6}Xy`L+Ps0~^+SAMQW2#0G zvY4IUj_iMfr#IJv^#j4wfnZG^F+Oz~4Y7job>L+P3X^I455S!)QJ6xv4N4L=um{ng zvf;3Bp_C@7?C6aZn#9bV`FG40WNPgrx&X!ys#_sCJ%R#g#l;|2dz*FV<2%;cBNi3kblm$N~VhAPM}>A)Fc zKzyfn-)%eu>Mdpm5e5JAZ4c(UP^ff-cCE-Q&+_`!CxNs55fJnC@t6wBpm2oAQ9}b7?b`)teBPh0a|Pz0aOwGKxu6#3Q!RcCn!F`6Bp7~ zT?ov&RTP6uc?xn7m80-o(0D`U1_&{&r#KGdrRT7aR${dSY*jV&Ku?0FTaaO0b9Jl< zxk;6yWFT4+;>`v-o2%>D+1Q&F16t&e5;uI~VD=)4yAChKMyL1oz~j3yH{Rp>s*QDL zkCgq}ryExsft$c%Muv`&gJJY2;N+-nF!!C+`<|7G0vH!3f*8g<<8oB#H~s^};XO=# zxLf_HeDos^2qh#j5pN|8rRVn(Qi#uH1}lPOuh*BTOM?gT~PW6upC4t5RW8cLb17(cSQ$N#EKhgH1s2Jsf zE`H1Fs4?$_QMWkG_tCGgycJzEc>n#%J6z}!jZT}b+4G>*+IaupF&=Pd3cx2idJeaR zZkH>B*ptVyRwqswlSa5>Rn=P{?XeKYG^p)*&x(9Jw^?w1D6rX;(OA|BhL6~Zggz%g z66H=1=YaD>*N_VxqQ;p#$;p5jw>+yAlGVgFO;);1=NYa;&V$I|TT2$~mjzQk4p5;; z>mm=EW}uwk>|=%x1OmW_)T+^F%nY!`HejF+y`H33yjBQi-j{aPezeyWl(0g01uMT z^^eg;EXF`6WE>1ciI`PdMZx*6>F>Z3Vi~?aH1{ep-^DaF-l;U~Iy9rw#dXY0RPbm_ zg%N=zG$5R8;neVdnBB7elyMKLWn{}B;B%)kXn+b&rJL8A!VH2-D_J-ow#+K3y7!Q2 z_c0szm$NoKk~ne+ya|^nIXX1jW;|YK=Iy6)tOF1;0A@y_40J5F1_oilWY*~^iUlgS zdm~-Tk|mq$!_Fl{>BX5xVU3ZbTnG;cv>rwZ7GEOe){8f_GG$V?qHqbQ9!f4j3GoMW z$$vpcay&p~01MDlYbm@&Rfw%q7|ID67FKxinJe7s z!BE^+v&pJ0gBY~#5eT$vE$9o?!NJFO6L=rTHtzYlPVHtEg}=;_529olG{E}Tf7KRE z*zxoIVI(PdF0J?vKy2~8w`pac;fMJPQO1Im?w_JcqzMc;z@9M3??ucxBAev;fI|@i zJ(Z14p3Z}22NlPJB|I@!?W9wnK`euh1Dw$WY@ePA6+DLlbz`|?2{JKD6z#*A*z~6T zCxmyqmEWyw@jut{w|aiaIQe4P6dawBAR(v{)R;gxI67P`)1b93gF+B$Maj_iRbsnn zh2p?Ii+?tBNCXk?hmwob1nJ7*0`-04Cf}d4Id~A>%SOig?6urp9Jn@sS{CpR!02Il zUz3HfH+P7T6^jq}J`EUYS-G2J$dV^RNjuYT*=QF6-UmA?W>|oqpE*iU zuL@%|Yy(3na_QPM9Ir*zQGpbhrmD|8Da{lCL1!yWBy$wri#)-M$(P@&f(9d}3;)D* zC6+$PW3{oB$KkXalJ+bX}emc9GFB%;wWm(MN)8H8z zpiUK^@G_|W6EW)Ge?fomIaM^|gg(`n503YE1<5*{a$`_w=8TnK)Q=8vYpu}p*|mqD zA6TLKOXnJgmm`>hqZ7ecHk^FV!gK823BYAaAAf`l=pz}+$bZ&`VN*6#JUPP*^B<#{ zcvqjy-AQ)--a+&`6W#r{(u#A;9QSk|AMj}hpnVy9EgJw55ssE?{hu52zOFdC&*fv` zRvPc9fDDAIB388xX>co7zA9{}RbYegZqRN7TEa{#I0I?|MH7LPK|s*R&&20K$0x*9 z$mJC}21}$_q{K*Y_d>EEa;avRUeQ;=E{kcZ!$-=g5h9TUX`Sz>UFYlS6trR|H}q8h zjEZ><=>W#rSrf&q=X|(hrVXLv=WrBr4cw`Xb#0uQ6J_gs9){9CVX?R?)w_XF(H^Jo ze$9a<`rrOlaI=^)9|-V@iWXW&)g!((ts1M1&qTBXz9s(-=#+ z5q`o2j!YXFi2r@$?7qc%NuzC^O^O70+_Wpb5*JZ#+0_7!SBm98$0Aw!$ zV1V!Qyzlc6!cQWM5&hSW)vq&2!QfdZZGxGdqbOw|j0%<_O&bLvHj?z2(DC`=4<^=4 zSzKJ==eD+fyDnkS%wf~RD#&%QAk~VMBz<|}a^W1^6le}fYd`sGt0T%Jwxwwsnm??G zdY(`kYpE0H0R%-x2ST{EtgvlTW~}F~HG1V3QOhFbe;A`enbE{)v3{sdH#bl~LqKUY zYodk^VMDrs6Y2IGJEuQ8^7YyHINk?;JOeq=Dm!UDj;1(7%-S5ky^r&I7f@cBTgf@> zw(IQ|UkuNdCU{U$XAHiNrw#{q>Owx?xT_p6zzJsY-VgQzIF;iq;tv9b_o^G6vo-eu z{uZ76mtq4*YdKBI`#b^!?Rb7Yui_d_DEdDnZ30-WT{JDBC#c|WZ=>Jfus7D}^DGp6 z-NQ7af?-oPVQ%{ckeni?KCI`R*y)dEJFDZnvdd7RP;bBS_g5&+OLeG;6=bpUFq8Qx zgo#2=j0Dk*BK`^^a8cSDwP?)imL-+n&oSE%y0=}K8SGP=Rny@PraprIrb)5w8A>z3 z;Wdf5T36%dJg&uTb?{nv=G4pGK5PPKzJ^vR8Y**}Uu))D?mtdQrTo^i=xeRvU<_4G5EFq5 z@qocmI)+csG=u#3!aAV5sS{^rN=%iAi|}X=HVL8-PqvjusX#ez%j|MfimWU$Y__uY zXy}P+w%!P>COefJHmw8l&Mmp%J@|kUt(@#!iK^gnH!M%4vUR^ySdQTd@%8-{tqL;M z&=}iV7Im89%M@Qli%%=Xj}#jYhx4E=I7o_QFhaIkCIA^YRH;er)tysFgudDvA@b+5RqPCABA= zFncVep3&nhcRT|pS{pOwyhY(?l*!cp924PJgdS=w86FNg?@&)JU^+^qOxq?FBm<~p zoX*3>k=GWm>*qS$tpF#T(pb)$wfgSrZcyT)ex?%!*h5?3(XLPY`h>x-5gW}~JRaYt z`|j|@_TZ-@>+*}*B0BgxARLFydKbs_D6xa46Jvn~WXcq0={n2AM}wcsF0ydDC$j>e zPdI#6i|s2#kAQb_S%)4W3dwf89>DqetO>AjT39UGgKENqV=a37_#iRF$d{Vgc$C_# z`(3}Cra|5AzVT%n8J`!FCPj^2*62^kNlUv0g<8g8HSI6+sU~1K$#eec{A;sR-i4`M z1L7e59VGonm^2~lcOiXBN8a?gSe#02{Si7gOlE=YV(>%&MbeQdGv3oPqi)yVG8ZR< z-Mu}a3J+Lx3*9~=@7YgYQ2))%%@&7kwiJdH%0KF2xt0{*AP_ zp1b9GEa$#YMXZrOhXGvoZ*p`0=)lcY_ik(aSS5d24OmsOIjAM`zA}2GM!^f=E4)W} zckchI67k<>@k)C{YYPj`AJ?r}x@(WiqCw)_zt;6`=0`IQ_8rGsYFOOz;M}R?;VhNF zh|>G^ATjYgkuyh!u_<~*fNzhC5Xu#ULMvzYQ}+%);0`m|(>R1=r4cf%)VP>VfK4!ymzcmGu{nzdM^ zg2)7oV9AZm+7iLSFf0{d$e`c)zjn%tPo^;nI_~v_YFJOsa>CI4T9}ofn7^yB?V)Pn zO7Hvv&P&Jjc;+(aPv}SUUh(Wlg~2iHdF3PX(Gu>mhmdwt1`NwlLdW(rN`T=}NHdxv zbR`ba;jHM%qK+h|!!317+G{SPnX>6uSOyQ#YR60KY>!eOd7HJkmbTYB+8i90CysM| z{fhpF0U4qhTDV|ES*$Hs3qQpTGZ$H=stq{xDCKwZBR`A=_p}5qCRHAbd;|TH*4pDL zK|_*;c}NcX=-zdyGAe;!uR48D*&7x7zCZ3R=-$*T7UIG)ra#;3E8JGZGoRF0-)=7L z>^{6d`L}+JfkhN3q;O$F1finWOIB{+%7@NR<(r_!f0th6oPrnY8B3u7&Op(d6(aRo zbCk-Q8eBsrPK)%6+JA5*qf1Sut9vkSS=`;+-I*nC)VZ;-nLsdd0Nr9ec)uO7Xbk&f z3Ou^?89R-;*A4Z%OH(*@B`9^+8}3Sy;{$p{_8Pf=NjL!Mrf3&>!Zy@Z4;ufXAJ}rjdd<32EsLW5mhXch%Enjm$Y5kwJaXZM zn4PdlSJW}me|TgQ1=0sDlbJYdQUv4s&0u-3JXC{uLC8`NdG}Ym9Ua~x`$)_&gGNN^ zR6{py*|h`-1!yjc7>;bJhcIuzNK6}Nx4~p$e$sbrjv%<7bnt`H0g?iLYq5#Bl@L?d z>r&2-&`K|Yd%USI<_J~1yL%vrF93acbZ{Z+y%gERA3CC@;!L{G!pB3xkDBfC+T^d{ zhT9*n6fM%}Q*_%T&?l1o&7*D*vHI5RL9_(mWf#grS0Aggj_fzj6JEB-Y0*{l65$#ClQO7%;8I{s#EjV@&|DsM=TGqhS4EygXoFmYw@^~K zYK!l&D=H-yN3c~aw2^^{QFZ4IJG2B%Y7gD-9-t}C`FbxV*nYzgcLiS!x=KvHpAm{9 ziS^SQ!Nh7Xys`|+qvgmGQoV4W7Y9Q{G2aPVI=DrE>CSqet7lFHPP_KuU5dq9uw7z7 zVt8d!83?qtzTUnE(}4#ew3_3bL4(nCU}i-}NE!)-Y}ysRQ4IekZ)6EEew$9;X9)t=n1PZboRgi>ZPtWn6-`xCa^tRLV zh~FgeQ3lXYoXmJYVxkfg>jz0u%i&s{XcHa5zKL&BKP1M)ci_*58M-Ko^F>Yc42ie5 z&KNSv5=b&l`5*!!40f z*c?QS;@+4}*&tXm#3B2w&0yRFm>Sg6v7mm}gAU4)i@=4V19=sZfmel> zDL;Z`?D?EOo|KT3_2`A=5raPiv#Fy_>5?Y?qlmy#+sTn|s+Ja(4)ut{R1`!i7Dsnh z(QQ@njBw7^l{(YXj=ole47BkTarT&pL6!e15Jm=mkceGy6cl zik*oEVX@3h+H9WmI>bfZpGMQ^@*HvSO9g49?&E56Jzv;#=zQ=06)*5T1Uy2w{!eZ% zEG7|#{nOli)!B7aB3=#Pf#sT6nI%R(F-1fr5Ube>sKhN|vTg&{jxI7Brt5#?5vQr! z$-+5AKPQe7l-J=FiVG_1-7a6?FF6@*8o%@`H?9CnrgX&Yp;35t>`aX1mkm8gtCxq*mwdh8$8GIYU!flC>tF@4DBTr*ElT`9+VE%}dJyM8is`G=!nfOD5!LkS- zSw(t>Gf7^bZ;kE*zUsK*_Rpc_Z{}!Z zMACVEs&FUQUK?vA&C<$AP;cgop=AiYAkhCX=VgZQBmFV8wa#a`N-lMfIU0|{kq_K; zW+%#?9O!U<6tOS98ZwxLYf0OE)B^Jm-4>Dcdw)4d{sM_=4sE4Cl>}=}uBi~7v)4Qo zIbIM^YftlTKQ7$7Dj8T630ghf)4uAhcpgjyMH0*CX>YHAlK;58yBjVGDx@k)96%Q^ zPdsD+JIgv#$HUF|&HHy->o@G^t|m{Nm<;2J>*Bin+>mS(B{}mjd;IvB#F%dBZBjOR z=-q^MW}1A>=Ok~LfM5LYMPa3A2i2 z3!n0eWq%eA>mvfN8P6V$D_3ip2hhH(PX3Kw({4<$Myu(+@|+fgXDj+yuc&GxjM6!; z^+{9pp~MeIf0QPTgNDcD?^5ts=OZG2TzF&zB4QISpYO3B+JW7Vl_f)>-=$-zj;Sss zAY7x*2Pys`7g3HVmL_LGvI*X5cCz@ie`XsS)zr4JnS4N}_3`#8bdQHBS#_d><%%O6 zBS$1rNza_Y8kf zJ&wQ{8qn=zIe?SRYOYF4x!QuryRz;w<>bo3B`E6u5=ux2Lrk0eYsvc66gNbhqy4Yr z^a(!6LljmT`T7$KmtY!D<}^QJ)o4;QOSpT>XQs`1Af~b?0GU*UZ)^3Wba~oMra=8s z8r~X|YQhqu6k*}<^_YcpDahb)EL(B&CZwvWMbX}!nzq}Xi>me`Z#-9vjTQ6enYd_k z-}@Zmokvz#Zm-)jn7v#{qKvzeVj{arFEC5nN*UnJOuv?{7E=+8q=0Fp9QAL7|^Y`i{RH$?uBWL z#!Qp0%^arX?S)>8?=WlbBVIH|+y{1MhA&2+{A%fj z+IIargTW#+3;4oQ3m)>lXkt~Ye)umVYAn%YD!ZVM9c|s|o3fl?X{VLAvCyqd+Q)VY zn8TAaC0Y9sE2UiGgacsHkDlVi5Zxi!Y$4K|=r)Cs39E@A&VT=`%sYg2uJUNvEy#|LwVf3I7pz0otYE+3!Qams`QRxxx5lP;`NiGf!gzAw&<` zlwde*dC)BE5!1h{Az2=&*>AB!Vk+vgYLMbAo!M~Hb9{0to!HXH2%of|IwMjBV}#bX zS8ZP{7EGnhEiF0wB?+Ad-7^TU79X37uP|2~sx^jNBq>wGdH~Slw?sYAg!w)+0s`b0 z+NW{}rwyE6Mq03s)NFFEP`QqU3;TQ3D%GnTvvMd)gm6L2Cc|J;62eTcTCu{vj~Gdm z*dmAFV3YAoX3}+K?RkZxxa3H9-BYBk{2iyzpSiI)+(&N>luq2} zzF?~qn;MdO3{?2*tq_Os=&J=`GvO!0SbI@#a>x{P5n-xjrdyM2>L=5qLSwttX7m*n z%iKwSO&#e0jhg$OTH0KG>XUbwogx3N|2g=fs5{-5v+MIB7si;9&6raI?D5m9m@#e( zsOtpadoEP~V}NSFA$SAkeXGY0vOamtk&LUT|H#p8hI|6I?}>&I7*pTO)68_mNP#Kz z-}}lUAH!Y(*Vn5IGlEUE#F{(~DXGRpVs77pA^(pXr$Bjg^K)0)gO{D|n^9PY`152brTzq^Co`O69Eo(^XyZx-2yQ^4{GLJzQX_$%#kxN@m?XcG^L6X6!XS4d8pJZV{O6;%jK^>U19Qt=;@d+ zwOn3BLzL>C;VY%onI-3@DqxOK!NKE+_yilff^8RYymK=P>4k+0 zAyw=ZqI(Ud^PVAFjL2fcEzhbWMmj_#*K6d&)C2x#ES4&*PnY4ep;N$5seBfvz6<=P zPSR@btQ4S(&q$F#iqCz8kB(3*B%z|d>vMwnG4L^skwoY2>}b(V$i-+e zW5Fy4YxjwJK)A43OSZaNdh#{;K&2oCO?tDbWbp^ud6^7J=cUas;Q!jeTRazrM=3IT zt?pxVh|i8-CV*~N*hxFdrU*~7hEbBbHHDFdmR>~_|2kHAA1md+#vLY4!rfGW8Ld{N?m<$0YVM_Xb8k`P( z^JJN6T}ktExuV}i^Xhisc|NOu;COY_Bb6a=xMZZNK|c(siE0Mj?peDr!!Iet_w0vM z`Yg>Vy=GU#y2{Ed{DrkIhtlvoC3HU=xA>#nA|RArtczD~e^rI^C6weOAlRA*n!ic8 zx4~fYsZvQ|)JY}pRe{Bcb7O{eP{OKXl|n2tHDL)99B=e$aqstX&NNvv4-=uJ^Cz45 zr{Q`@sH*npDm78x67711(`x`B_C6?n+Aaj6Ao%y&GH!0eF`t{|_sQHVGF~P}uk+nX z-Oq34VlCI6f9jC2%7>{8Zn=-yNdlz!pWp#+jdDBH*Tr78#U(nF@XxH6Kf~NIu(f|F1c8W!h_OjQn*B>&|2sGzY<-$b(ncXGbS== zn!1}SD#rmsC->o+T)mh`xr{TrIz%1(a$=Z;XJ-=2TT94?RU`?9fn7ydo5pp z&-aG4Psae7r=!C|7w~9C*7sxHY(6~P(vIt5c@#i^+H85KHdKFKRsf_c3&Km1$V7X? zdQtuu% zpwA*fB{4#=9vu;@C4MEVU}^2@;a&cQK!;~D8m0XXR-7`i<) zO_g82%QX3b_56=KK4-rJLiK!h<^p*ZoAh^=sAWYwf5hPbQ?KogRWOb2Yz`l9B+L+TcF{q3}1yvd|;pz(_aR zlI&;XdCvNXEA=X2;t(cB`*jS#fj9!yh05+37C}=T&zGr;2J5Y!^~dx2Qkso{hcQcw z&($d`{H$_>t_M9U8ffe@T2GE85Eh9oI_6!$Hoi3VDTen3XdX3Hu*cp!>Pgl9s&bab5FfPNUP@pS8Q0)E;k0 zclA}#!i-F3HMzNR>9)>HF!2HvnYsUl*M`Yv1>eI4g;k3lJLy7F~@1NFfti z;KBxfSmbe9EcpfS zyu)tqu3>cPK7bAa*Do%X9dqj%>8(;%g{oY@>BIj_@g z%X{Oxzp=8*1_PEBwLZp!=>D@v366K}8iucuAFJC7yKLx`s;jF#zp}qE}D5Mjv}L^0xsZh>sT9C6jCAE>dEAKODaA!R`mnT6w@OBIu)!w}VrTY?CY z1_)loue2~6vxCz240!bDP!!T&ryjnA66lv6lio!b2mzun^H2+#tUM|6g>^s}1s7Uu z=fxI-OOGR|E1`EENVKl`iMKc~2;-W##&YHT9uQ$eZxxyv6_Hz8T)Kor+BkEP6t=eO z&GB)Ce`H1w2kSYGMIB_K7J*sL%+r$R?Lo=30mM@9eB=Fnq#8{~zdBpFCzf_T3GO^* zd3x(B-Se+Z9P{q91Q5h4e#O4|EjRP$Q`e35+nx-J+FzGXud`r^clcQ2s>t#H7ljAQiRkyQd!XyGlgU&Ew^I*`DTDHODpm&hF zNnrBur>-_x@3w&YGn!E@CK)q2IPMx3yD8cuL`L$<)!7-Z$%!NIaP4g9Y^}Htv>&2| zHOW_gDj{=y3kY&QZA`Bkw4E~(mNVoNg|WSu%Az#DNYXPSdC~X}TX;5E{CMr(;4Wvz zsL9@F=_T1CIyB=3rxlvN5-d{GF=3^D#vPBe?Cdho`ygB_z4=p2*YD6;rqn?$41x6V zn2NQe?#AaftYiJ4mrr9l-wtB(zLU*BZXS(-PQq{%eyT8gfy;XHgW4 zwW9{I?GO$?t;g}o;nIb_gOGC(l7PSwX|b528km1q5~qv*Arpx@3uR5Q+8)|V^n|BT zVbY&woHs?{N9ODmL82~n+ea?C!lAYZ#fjpLF`!FHb8eSo;a;9!mhIF|1-W!K^)x+N zvn>CcHRc%7LAoM7Ooekn``&LhsnjEaNA6K?Z?Ci$NxCjlj*~(U#u&EQyNivJSq{~N z%)h;1<*XAskL|3TSJJmE{9pU@$vbGPTi^B56aHf8&~#LrM%p9B_D7sBl3v}p{jI#( zl~vLNCP!YJi}yRuZDM*CNWr6SD*nq|v zAoI(HVUhboUF?iLUR`oer5V!E>@O#qia=mARxSWN79g zLPLpJ1pIt$Y<@A>qJjW7%bWotER^%|5)L6mw9LLSS+t02+?1gL(Vh;q)z;f#pk^#Y zy#vJr0TfhDekgs4Wm6WyxdI2A4yqNRa5_iM>7bc|I^Px^HCYV3uI*0vh=Y}$R0S^O zbiL94bM0(t$kdr9WAaEQ^bbdZSRDkdDw7;c2x&a1IK4IxRQMs=?*?hj-yn!L-BLVR zy`LpXlkM?9gqPG7J1EC@TK**Jg;FHmiCT1;zk^>&|Dz(Eiv0K5qIAw;Ul=b$T0p$V z(zNOhM5zH3J_1|<3FUn?btX4OIl0EjZbw4CnqavdoxZ6#mK>Y(Boa_*OuhVYvI^G3 zDB>}Sd5T8qrSy!h(ugc^2a5(P>Q+2Vel!;@f(N8-B*q<3-X_%y0vKL4^brYXXKQ0) zzDfT&a=KnoP$h()1KOh20vjWB@vh$&5Eq41MmbS39N#j^d!J2IXMV8|vaJM!9t3_( z$cMJ;2X#0vay3qu^py%$C5LiuYp(yj9xsXi?&Ae=v&l%_N48C$R{m6`out%MWNPYa z+uin!3iVyu#t27%k0nakWjz0|Nf_cSw38^Qm3R5_w}ZL25em{1f-rdQ?l6>!giPiq z1h;2Nmow9pJhcmRvt>-`ikeZR8hj5?6_BJ&s&~n7<}YWORS||_DV$k#st7r1%`r@2 zyki<#1G7rKHJo9T;AC3_rqtu8;L(4vt3!v(m3>YN1kPrpgoG1y=O^5)Mj95i(fhFy zKa%W-vIZ9WTFExfcE9ZCIdZ|fZ82nnz=eajU$@_*4L*&nt)rTkbhG3jzTQR!C3FiL z8y`CW6I&J2cnQ+g+qRRr{r$Y}gZ=wJMil$l@Ifqlfu;aPShLMFGWQorK2{e2gKQad znG%{wt9_IRE%1DxN>PzQY2ha2E+Xh{_*jXgK{9U{?21?74SfCIqqNA~@W%#IWL5;M z#BILNj3M)z31n!(OHRtk`xUO~TH_iXVnc;MV0;7WmBFDwn7>s(BLn%fZ@m3N^8)fk7lt}3tC(e!7a5U~GwwLhFBE!(#M&t9PS`hY!BNn??@w18^ zBu|I60*4pvGj%b4&|4Pcon`>zr4BmbS=r9181AbGomRC!dFK6mp5{GQS!}y5%0nU& zuwDNHuoyfar#VsIZ-2gTHS0>M#?H=f^cH&m*0zH3kDIon(=Jc2r&=wIO2*d{9dfP1 ztdYPTP#KfRaYL{KU0yNL!2%P22>uQrq8c(qCJtLv8g?WNUC!smU8l0lcBFcmgDY*Y zUY`2VsaCrtI3eL&#-g{lneb}@1|hYq#B;WRhG`MPR3j&63n`8ofz>V6pgCeDiLz22 zlGBS8U*iw$s^fIFg8M{o=no_`f`RoiMUHcGi3EY~5ivOs{8(xCREK@L>Gmkyn@E}I z>yx`%>PZ|Qs4piupRWs;UP#KS;&-#kGX76`Z9vU*3N-q$`}3Vbt7(jQ6YJnhDkhG* zC-2~mnoG%lE)DR4>2+x_twGNocgV9lX`ETz*jU(I^_lKK7YMMUNy(T%YapMB4^y&` zA}@QZkqj+R##VJ^$uJtw%mr5Ev=pWAF+M7^(6laa>6}MGug$o5rZXJom4i7AYZJRz z5G4Y6=L=8c^M;aQg3Ne!&s23zj}pHZL45wJsUQ|ipOAxubPXrWtU~-2#v7HWUQ7cp zaTLW2pks?VCSCcNuD2KBVPy6c`!KB9hFw zrdbLV=_<5%cZE-G^fJ>0GVug3d9`5l@X^v;NYGEpW_?dsTX+3G{VO?lw=_e2Z#i< zJY7w>l4KZe3^o>aj7~HuF6*VI_&)Z{pgcsiaio+IEYAYrSw#gt#rq1t4Jom-q3fqj zm?ZifDJ0-MIf6-YkaHu|%6ukeVBSXBXqKfyZ?1^w1N{z$kw}F56N){Bk;F+=WMHBP zRn5UIiHzp6pl3_;=}&Cd<+ceiW`#y4l}4pWy8UPACTaTim@1 z$wqk@e?t?ew<%n8)Q%c$bmY z#z?TvuH!a%30c*`XC1(2L#G8ZCEf>IFZkAv=ntSi@wuKMeP3_3{`3=m_MiI$=Sw_5 z&X6gEz%OL#-6WRw4L=2QyVpFq4VS&f$z2l|*WjOBT3Osqr%HV&Ijj4;DcLw~Y04fq z&^OCi@B=mW8&q=x8|2?q8ds~Cd$r+2vFMTQ2M0k=Ak7(K5$J94J%Gi+^`U0Gz~?hr ziZ)tp2jh!LsvG?t`YSm*!WdWp9eoysT`hK4l3xf9=W3|{OhD2#pFbqUb|TdfDpwz~ z7R^pmg3~#d=3+}di2=T9@OqR30A)Z%wV6wbrB~X~n20_W^S;^kJ-RP{z3%wjYWDt9 z=khHhRU*HZ+rED4*>m+$klJji!0!`gTj64Wa-550?lN+`hxXuRHfB-h;URv72lu;# zs0JC0L~CFMcpavKxS%;2{`(%mbzloLIi1O|s5=ORGdsBSbvBqWC@(7M8K52}9V0@B zC!-xq=@BbzZmn!ayO}}rGcqVt$so9zeS%f}#?hfW^2=2p5I`^h1of3473-1o76vZC+}lpuK_E%64{! z2tbhXrO7;81niJWMOD$@j`dbD-5Tx{DO!9j-p?2KtG`wkH+{kkrmM&F%>g{+Gt90% zaE~pg(J*-2osXT@U~YwQ4#N|9e@)W}*KZdvJYCIJzekJFw%3r4Ka3s_7VHO2z_pN4 z6z9qSA(EdY7}2fs^QfF&|77gxmTk-A#r zz;gOO&N7Bc{vmwdyzl(CxA(iuUCr5tP3z)AEB2Ca7nj6pI(jfRZDVK? zs=^@P4ci~W8+TQowmG}mCY`gHqIV|KoTI3u52T<^4-5|=L+QQ8?FA0vrc9Df7_|ZT z4gy%yNPY{dD*S6FPd#JjzAXcBK6-2QPpxk8$f{%N2}}lNIA#>C{GD+7BWUqu+__i! zF_CFdkwLzbn!Jqb8vouI3Ai0SKkFq4F12H@Z#|jN9=P#Col7s&jO+|=+959XTo9b1 zY*)=`$`};&4|ZnRmb3ZchzdsX83_<2*oH54umD`HB)%QB{eCEU=DDF_=a+OmXTl;p zYo&;{l#BwZA#g$(BP;9T^YvzDR5JNzfS+p2-g(e}GKc;7Y;4fk*fxlr@q#`vb3=M8Z_%8; z?1Vs;gFqIQ>+_IQ|8NUFbFop!+%cW`$wM2wE(chS;UF%^j$QB54g$_cV};_;b4LIh zw_U(jjpYj+`{5x5mc!J&EoAACw*eW{PJ|>((Ao1m*p%~sdN|g zzxC^kgTs#4kuOLmPo;qF;PAgoLM@$6Tv`;bbDNL%OQOW9&+$g3h z-V8Dm0bV2v3E679+wS+V^6~;(N5Zc9rG9;RejYh&{8#q%ky;pjTrB-obnp;6`NXW=1jJ`pbQcmxmOi<_zo9@kiuIc-K=r$qH% zF9h&si=72{`X;;%5`Hsj6x{*w`U7m*0EDBTw`hP1p00iS@l-Nm6Ib`FM@O!g*Brz( zFwgJ7{g;;)b{h>7ugAH$c~bzqd@A$aG)q{D4F+db1O&ttAuT4XMyFQ(5%LVwBK)QP z21q7RB2d>0DvO*o%AFy@iXdte`Hp>bgh2h4tICG~hCX<*RWVYC2&bYa?}DjKwv5D? zBDN65MS02(YemzDNr>E4qn)b1F-*U4%Og24s5C$H0B1%aEjmpk+?Pu;3(RYy> zxT}a;be&b{yVSIb8w{bX*Hw|DG`v{MrucL8mh^p=_HBXSrB|B@)1mo|u;$)Br1fqk zytvi+Y-9G^g#zf%kkFHWkicIfec0m&S8ZK!0Aq_QCi7GVY#!IMySe?MVG)X7LM02g zwJV^)ZTLYr?s0sHFcG5fcugv&&h6P}aDkRXxDp{mAtPH3hG5DEPCs%q!27?bc942k z3JHMmCZ-ZVhBSwO!if-2o~Lm)d=>HztI7u(U2J#( z0kJ`YI(u9;nd>qCf0@BL_E8F@JL9aBA3-Ek-P6CZYdPCMh+0wDmS9UM*cezFHgp+f;<%KZ_7oX1T` z@PSHCQ28B%0xu3fAQsG2TvdqFh7Y3(#c@I??q%;Ij7!%7{ia!?-{|)-Q*+~@Rgh2L zQl_c`6iw0ltlR5$-Mm`ZB<9iobK}wb@t?SRp+r_uWrWbJBVhQvOMZHG>sl<0yNC4w zj;~Kxd-VJ^(zP{ookBqOuK=^2K&yB~l#t>=#i9f|8dufGnbo-|Dm^#`1^5ZZo)#0E zxxKmWi;c$(m#3rUY!9)!y4z=9tP*$*q*D}2LiyQW`YHrB%9wqIkvXxsz;W{Y{vpSd zXA*f~d6u>yJ~F5lB`INOOm(U|Am2VGV)4Du1Aurw0g`)K1Pc)y*!L|nMeBxg(#F>< zfDUiB#ZOXJw$dtz-vA9}j+MY};{v~=g!PjCowTrN>Hdl0>&(S+vW5Nn$Nd%yJP_m* zf@@}8u-)Qh(4756;QoekA7E}nHiN=b0;?d~tS1^gf2e;D$@>4Y`$wunflfQ_NL;x=7 zR7;Mk{kRZzP+>s!KwNBPp8eP$f>aS-O4dhop21k?rEQj@;CR8Da+6CF;b22llISMo z^_I3yyT((gg9C}4mnW>?b)43jKXd+bf%OP3<+&DVWz5#-Tny-ucHMw>FYA9Ehw#+_zJI>_N&5O?~Lx+>yJ&^&Po`zUZ+DfO@YAVb(;_!FD? z?0#gF>NDZ4iYemuKCDdbeDHkH`p`WDP!=iYU!dHcJcVP5F~yQ9#VF_>V50pkFYXw{ z05`jZLil*k$2Xojs+D<^%$elH_KBYTtqbxp4mX#6#rME%k>g-1OIm2gj57=0ae+LUJJF7AZVmECY?-! zX5k4P%*3`6g2u{+NDVZTV0^$Xg6dM@9*YWBz%djfB)&!x%*mEy>yLbKecib~Lix+* z3*P;`l6Vq?t7zmtr z`wK2>79aMSJyTs>_0&^UySrEIx-!|h7@CHEvdyy!fr5#U2$88gGyG#dR!;|UHJg$D z{3WtaHG_&`Q>;Pu)mUyuEZI)77jhH4oOfoj$XSBQ2mOA+Z( z1v26JR8X0ED;HzfUt$2ReZqLLbt1zTyqB(g^+S*Omi%_T5gJig3SpR?*I_Y6R+oZ?2Gk|KSCvNTcz_skPSlfMz zMIp$JX+ZB==6i+HDfQjP7Yxh?!m;?**JYocyRMnv9Ji)&wHpxk3@bTtb4h7gY^*{E zh`uNZW>m)qZ?rAa&=YmIXJJFocV}hQ!(Rt2jj^RipsNO`QFIk;jL__cuHg-W+0S7o`h znI?pCABm%ynmU*y1zu11(V%>K<9T~yS(_|Ftxl6Y?G)gKsNTA3<_$WO_$u58PGN$RM%L`BLfy`d+tvYBy}?i6c^FC;yIC6e21&Mqzw_l){$o15#iv&+lF z0hmn!URs)%?gu))-ledf-;mx7_$Kb%fQJo`mZmFgU!U&k z^Hu4RWD0bdlI02ui;Ub&*;3E?AKjUZoJvKR!W?zU0Ze3x;1n?qn)-mnNN&)OCDwMI~_#g({@cp^qD&h4`63+ ze&B`0glCD*`3ue{c7$OZQ=!RF^S!ySv3@QgVNNxLg#fN3EW??bpKqt3Oz((D-GQqjMVE#^YQ=`*5A7}bOOZ8~B$LG*@Oyt6vfn>PW++2w z(MiDHudt8cbObD-9%lhpJC{0Pnx;Kiy4GK9TgD4Yn z1V{y+lO~G-)4PZFxku?wSO&``89MiSm2(3JSl21t{HC|j=$$8DvbDrpSn6C}AGR>x(#V@lDB=zn zvYtG**T_oj+Z%SeIe}eZS6eZ4`#+mL7Z$}i!d@2)}rHEf@;VyWzY$97Y}9Nb%A^2IVl zj()VirXKd;Kt7XtitYv;s?o)n@rXg7Wi;wmbH!K>5a*E^5a;h<7(WF_6J3*aQdiBx zPc75AT4|;znq!^IxVH35OI1UG9+&;z*QJP?w!CED>Vup$WEGyzHoz`k1Ij*z0Z>wg z)#y3BESly?yJVm&_-<}z(_Hu0rk2;ss>%#Pc3^gLgkW*wl?Raj@;Regx- zoL`9eAJ&|Ps#qEm`k^egrFModIh;3riOT1ZMhwU73sxr5v`8ee4|qzG1QUG7c)--2 zS5eO)UD)&*<3#0Pkz<&zdQJkrY}a=(d!ni`-<g)z%k*yW$s;KV-2&BM1aZ1}^K{N17KYU;Pct#FTbgAc7qAE-WyBkD?9mK(uIR}AL zJZswqPT4lJmA&Ru2Wq|c^I1`gA%%zB&h4zNZX`NRYAS1`5mc!#);iI4m`dwon|pgF zV!_}M3BZ|35D8XOr0>-#qEgFk1MJZ=M(Uz6Dre*nJt0P1FnzIpj|n1j4;T>&vg$>@ zYDN--QPKs|{21;OC3I|Jgow%HU)7!ZcpJ+t1VD_qKSHPoS{J;*d>ZI9qsz4o-FBSt z-)EVR{ZdrKQWmgAcKHRVw;x*rM}}dg^|OnndU#*y$I{-8OieV=N&Ngi0`d&k45i@c zvOy|?B47bW?@rl`_;hc}>b(Jea^!Et203RQ9t96xwC*`UFzduN=c39O@avpTxxV1O zsJk5msY?QG{rR$7wWwiQ?=wO%;M?$u{s@v}a=DY|WhJ;d(a1-h<6w8G#wOy1(uZ2M z2H$ve7Y(zrSuIs1l%%KVthIFl1+rdk6jCJ$okN)PuGKo~J@!nO6thxR4M6WweS!mK zMJiI7fQvV%$rEhR8XeLW{lU@Q=p>RAZGz9x*~7W8U}+E;$Ce-@msUr-i=;$*mPav1 z?UeR#g0>#UB;rn%>{B-IRvIB>7+Y5koyqTOEm(VT_OEt^CE5(d;SX)IS{_rTK- zLlVM&Ki!Tdn)aR6YU3v#L1jp%$?$HSeCQsD>Nll+{PWA|gu|h|89B=_|A&yZ55aZX zAvh_*-B0vM`_h0pXM$lx_ooQwcMKb}kstUJKuV6qQDq1nL7kwo@AL4KU{1I8D>Yu) z!1F5K7egXCY<+TTYj4QAsc-yYxxqyzh)n_#mIdVLl{*(IFGUO*3j!aBc17p%yFfjr zZ2hXUo3-Lg9WQeMT(#`v;&+cApO*)HG71xBxT1%}j({(-(Xq2A_0NLZPN?5$3kqQe7uFfSKz}#=X(h_=BC7niL(PSY6#IMaHdD(y2RbQ( zC}2u707y#tTQ)?c(0P4aRZCowkp+uBGrokfPgn`g6z=|cYN6ihqpFN&_4qPam^t2| z!N2pJj}cny%eH&ntX{%F6#1v?5UBWgKtoU|uFq08sEfFza3OAB`N>pZDy}v7paE*E zl|a%K`=GN%enxkuL>P*M^*o&da#lQ@_IcQ#$&&F>MTTMjSVAuyhtq1UiL~L_m1x5O zd~_+1ck?uynJ>9!QRVXX;qoGSCLyS$6kH+5n<4j3_sQ~|~ z<@QrMR6dq4DzT_2oTYS(8Xhb_kH8QDz&}Y8EMI)WtnN00g@dm=riMyYlS{fT&YZ{% zzXL>#1-0CY8${1sX(tqwlj6ZI1O@}Ln~kpn+}sndO2At4!68Jz^lR+&C?u*$Yl zY$_Ot@+MRUnUy5eaaU=(-7|k~=AvwknvVlj6!CDp^e*8BSFfJabc`BA@y-EQsMge3 zRa`$)A%p@rxQ(q3@{|Cv7jdzmRwoYyclV}3mnfiReYnV8a%8oMa)F^@(Nu^K|Mb>eBB7gOkApV9#ru1nCnvZWa)g??Ke_c zNB#m7V{b8tVTpJD9&27v$UDPOc3WTdpzF{s`L2ygk1PODAgcF6mhBUhU$=inp0!%R zL;i_F-dSTuk2nuu>G!VA<%koH)aYdlM;Kz_=rDl$@&J~Wx9bXFMSH1WmK|1!@%ITY zpY{=Y?zk42HbMc;8p#$y_8_$~zsk=+sG_u(CU1SH(^3OtB5{D-v-q^n(A4?oB!9^i zonr2}K8Tw_2x3_BANg9oaJ9EB8l_9my{h9IpOY7!*q`i*L#)GPaIiCvQi^oVEwn+- z;Hb{hxw7{iOjnfuQaYtIiO{3xTpVSM@X*$YsZNoG7?$zBOb<%+_(t7Rh(4|7R`%B2 zSo~apNYOY^(Wo3@JkTQp2HQdBvORkj`k^*>*Bm&@kiXe>#%GRhFL@O|mS;G!mcav0 z_n~);6dYYj;oYw+H_j_eQ{@F$Mq-QIUDEi2h?^^m1NeG zkl;(yUt=cqTUx;B={6>iYN}0jJtW+>lEO==GH5W}f!r?k1=@6yLY zH3K{NcfsG+dTiKa=laopu$9(vPd~G`VQU(dTP%3sHD@@syG;Mh7bmc@2ssQ#Yx=7b`1%e*we_+R!I*TnaS?_|iiV?w9tz2yKR6@;48 ziv~eH5r2PObXuwFjNs7PzM3?=QPNSqQOf>$UKRHJ0;dW|OuFf(8TodJyTMI8w3Ebg zh~h<+P!jPils)=LiAq0nZtFsX=t}DvSHfS?R|yq@B(|c%vflR>#QKv71&ii}wFTKW z(3b^1kK&lU1!)^LkP~vLVp*`0Gl(y_V1Y!%r9;of7Sxc$X~GBML;W2I6Gd&U?$ih^ zH2RW@dP`TKXMfLrX;vz8|0E1SG4;+Da3Z+mxXty*y!O{yKchxUB6EJwacCJkyDSZ- zV-8Gu!oU9moc$wqjD1*tQy}LXFN6!SG^vxoE)4lfR|b>8!Ew$?$Yl!N8W9p;oCdgY z0)Q+^cn-;p2T}Ej6WHsl5F>cG#u?A0ixL|qVxq|xdBtRu?hEa7WvfFI4W`%bsBcqP#hn{nlr*viJszlng zgxc7Y)ZkXtx^1)gXXt)O$pmMLHEV+(ScJ|vQ9*|2$=m>Z&TiZ_iD+>x5PJABjN?nc z@b>2Z=$?jmensQ<)Joz)gCf{BKQ7U-;GR<2U9BO2-{(BpY=T~uBRfmbR;+=2C~|kJ zK$yD}*5jvKXYmyd647MfhW}Z#GLbR8j}Sh4_%Ii4(2kTCg#gD<$B-t^o4V5j1*C6W zKrq=B+c_svz>hx0`K8~Y(cvFN$=;{UrM?ICVwEU{eYC4WOW?>qu-=ljlTxeM#QR+Q zOOgT%!l*L;lnx)w@$;OC^TyuVne+CCW;?+*+zJ{=7%H zPQNXI6+R;-a>!;_6}&>wMkIb*H1WKO7|wc2S4BhqC@Aoh76BOp@K}Bzlba?_dK{_8 zj&6*~pnBSSkRBBa!yihMdOE49Vo5s{lP((N`N=@>B0<|{Ck7E~CS)ibc6#(gh%^Fh zdxr|{v%rP69E<}G80GDI0I)ONp%?6TxfQ=HKh1brKaDbEsOoGxE#tUDe-0~Y9mwNo z7egcHxD0u8M#b>Qm-H;uZ_HwnT_#8MPYL8-`?*ecmDB#o z8!U`}-MMvXIgDpKj7QgcdhUOEr2I^H(%o}~FF7y(jK+SY;xMQ=*mlX%Gg4$)(|abC zsO-~^cV%G$`bQAgrFNDqHCgefjbJ^okop{*UsdYNZ6BEdJivi}_IkZ#%AdeC=Hr(4 zLGxKJ!4u)o!&r?Q1uE=2Q|zG-TYzpT-6?Trp4u>_Ph~o#HOu2<0W}T^tt(v58P_3Y z_g~?6fQp2tdT;~v|K1TOW)ePDOsX4)Q{HoLu} zPU-9#&1%dOgA71!65f;WYRk)Tp4Mxd)hYPe2OrIMx=E&s8!kMIdfgd-(`P4z{1O@M zKgXezydvQYrWFAd|KpwVrn{|%(H;oXg>{23BBd`y!wF9LBT}r`d>#Qo3KVr_8iXIV z4sf5p*g~fQpeOWxK}z`}41x6$l1%GW=3DD4gND7>9E-jC4wGJMVlu6V_e!!LKXYTs z{&V{j8(>NNPTvo8hw4AnZ^2;rjcX*Wq1Bf0OYDAv0C&k?Kp2gW{)jVhbF{?yPpJ(g zEDbouj(iy<`>b-O)cvXjHwA{(F@-bV(wK3xj+la#dX9tO-+2{Q0>mz~kub}DzqKm@ zNafH&a4IoZiZG!D!Un(o3%ME@onwnOlVrDO(Xi0RpdHHCv(LqS&{K@eK4Am&i{oeuEdjrWUmq3Qe zX1LS6S>e>g?s40@Tev>*(~Mo=*JQ)U{1YnC!y>^T{lo`p|H^O|87%$X@FN=xnKssD z_MVp{z&{1hVozUdJ?|rUr2jVOjvZc%N{s7V{omL8jzsnfqHGo;(3p+2aq&Vk0NBNKtHh{bscgq`AZCXd+Y)ojBTIAJ|I$J8CC?`TNsd-Zii1rL z`8^m@)<=D({OG2yl5||#(U8~JAPSXjV|7=#yy0Fv9XR&UY}q4q=Tp}mFCKrVkcadj z0AD&hFVu=-!hdnFLQyz8sS>|NfBfo6{QLr9U&VVMI->!qkW3=cuI?{oO&pkqMR|J{ zt@m~2I3&t7Wi8|9#PPcsI$0)t!}O$!E9X%LYV66_1?Owbz2`S%;OMyj@ck>yRf%lV zVIpjcVip_RG#F0g0($_zphACL;luOI4o%&;DAA_zwN|d*HLzMh#yZcZ?ld>>H=J+& zz0+>eC~w#nssH`V9}>h^>*QNmx7QVofi1-5InXQ4?kAi*9dv+sWt!9&S)`iXz`)nO;;_`yJ2v^c?P(tcBff`ude(k?~Y5 z@785MUXPtXo4!f}*NtOQ1SUn$y3@q^>yUU@h}yIJQ2ti@$|rwB^vy%QLOoIfUoS%T-!UlP;Il#vb3E0bkeA zb8<|aYuwYQ3t-|J)S6Sz>l{OTaZ&-7k=(XgZ^$d6Wv`-9j;%1yCtu561S zp{H|+%q!#TX0uAzwTfG6nj%mjEU|ptd#6cFPvfvb%sS0%k1`(J0 zV_})2XQ}*CKzr-AO*@0)ewFeAC>KKtk2o-Riub%1Uhoy5#I(VXfx^zpx%R46YLF(6 zNWoD1~xe-F=3{IppSM(vjhYOVcN4@$pU;NMUmZrn9ERQWbuDpsk9BU1~G zf_KIGb+n#kaO(l*B1}`L_8JJTM6CLCSTT%vUpAfgWrZY}z7s|1_X^tM_r~P$S+);R zh1%TcHKnX3@Qr1~AeNU9k+`7mH3P>*^5cCIK&wnQa5C~UexAb^<0KDo{)IcJ?A*+ zO4G7E>q=RgC%&w1h2Wgr)@T{%m=a0gN^@$407BKkO@)%z9F&D_oM4wZ9Sod+bCi;h zz(NG1awB%-PElCzOjwUHal6p8bJbMWn%L1N@nMhC`G@;28C1LSJzr!Q{V`q^w+@5r}kPg<&2UQ(y3RZ$**W@HEz@^$89N?3*b9TI&3l-=%b9Gdea&ngg zqZ$&QgKi{Aa!8TdKFqv#g<$Bx^`3B%7q%&fn_rNg@!obt8dNVb`~tm}XC2R~{Y-V= z45WKOeP@ASe-(!&)FQ-3CmlzOLH^*gBHH2XY~vT#FgYxm46U1XhL91?tm0VZ16=2Y z8nvsZk_<=%oFtyOrK=Ud36D8srg_zBiv=SAIth{yaJ}HexsFdq6vTjeAQ}S^24;AV zL(r$q?b+P%Q&MjYXyu&sy!9k`V)zg-Uf2=$->?cV>n}?O&+8)Ts!OODb0$==MCdQ; z)=Gde0Y~-cf3cVPy-tN8Ef`|6I>apGT%`cY+$Jx|Dq0n5x6=RjITZHBKuwIR=EY>8 z)wUtHHCmKCAXtKYr;^>IyILqYdGIuk%;po=D@52z#F?Sk9!f6uc8a#_bUr8?68 zKKOs#0SL@F_YJ6X{3Bv~GN6OKOt0vS|2~Mu2V8Ini5>sncaVVgC=F#da)*|G`8+qd zGI$Mk`IT+okce2Ed~70%U4*~PcN_X0&7AeHXxp@hEP3R7m@q)yE_?P5C5ROw0|Fl! zPTfI?d)L05;Pi{YGX7*P-T0w&*HbRWD!1MI%7J-j5wv$01$Ob~>1vIx+fVMnY+qxq zfrWo{h#vPoNrKiPMICo{2Ewb=Q7I>_x4!(0qa9CJed_^P&?|V}iS&@;F2Cwy1cu|4 z{pBtz)s!Tamg??Q^7EHjEuT`z7#Xx*iuE zVp!w9O);fA{n{(!R8i&Gv2EL6iqa4xDBrXq>d@Tfj=U0L@`S!f`Ox@x*LE_b zX{}8EXD?d#|0ok2U?*Xyb70sv7rK_87cE;aTF<~+BI7+zkSr$ss!Oj?7Oggr>ul25 zZnCo)k!Y=bwl{=CqbS|PwytdXtQ5!Vu_N!*s;~x}WuF#_9TLV->N(j3?`+;W$7`7o z%r}0EMAI(mNzOrOwnry%GbB<8kcQ0EYInQX-Y|;eMNa5|P z%hl2>*8kZ$P*0h)*ei!ArNI0U)@X_y%xi<|n?gUs)XKYCD7Ye_5SX;3^_FxJG`*4H zcoKzohJ7wS#bK{n-e4d36$%)uNNTiVmVcuWb9%DF4Mt;ps**g9fZsy-sgvlNyU_=8)8ctkyAId)(Z}H0Z_5Ei&D)%(<(k+ikrS7z$!DtiLMvoAvlTU-{v}vC607 zF4!wFDUb%T3|_#+ywz?oxpn<}z26&$%?z3HdRDy0jftbnAj)K9M|$J}Ov2}OLQoRZ zpWa-GEu4K9J#VX!$ElKB1jPSZ-B0hW0l)79o$c&JxFV2I&)X*8iXY~|))>-=x|S`l zzQWufbl#e2D`HUBA1mMpFj_9tRea1-%F!w&1hN!M9RXnonUK$_Bqc?rQa1S}1Dh-Q z&%y2piDa6xKY5wgzlQ!1yQ#+~>`jOA=_{gSFT3G>1G>ZSeQ=O3P^+0n(S%f;FIuDGn?37m_TAE49f8#8?**@F;96kXX69=Eo#bkCc5hSUnCkUIN92Qtnchb9B zZ2=)ZRCjH28e5w)R>?@$9IR3bB!){LPuE*9nW#!4Y~2!=#RQoDgU2Iga6&J%C!NrJ z*f6jI2!$LTj@+-V4Z~abJai1KI%7pZP?8PcT*tGfz6Z~xc#%%%0Ivm!(X2l zS;C1c!2B6^Pm?t?hirr-l2#R~zzI%rx=>qoK?zA)DlB6PJWme_qQ(^E2f7F`i~K*9 z4>Z%?A(4~@`#*>WekqUzmaLj*K9u&KbNs(=!HPawuA%x*iLpXKKkmRC2jLXweNx*m=HK+zvMhL{t5bT0-xl&J%Me<#kJuNq6%b##kbow=flIrDhPS& zv)^=eI(2nw#h%aDY~Fm&XJi{5HW&3h#Bbc|<3{#M=pIb1oK*0w4w zettS#LE^Od_;F=#SVSw8L%y%+WxH=+7Ds<-!(H^|xuKEcy!Euc!>d91NB;++MT57} z3T?_xKgCQsTjizw8EnRxEAcntx2X&To25^2F&})D-4`IH*pt7*E z%p2(q7QqOZx!H-xn;sh@A35BEgFh10%RGu4$iu>kxUHMCD$|G{H8rz5KVK2YvCQ_) z>q)tuktiq&UsuyqjuXe|IXbNTq-&4+XK}G--LdU}@J;km;7i;nj$W z+~|HCNZlGj!0Ncj(<)9P zpE>)M$kR%;a`oLrjY#MZh;8f5*Aly>WsxchEDC~pm`RHr55~g1n$1&7HKG&Kdv(0j zDyy36`nI?~-OlErXy{w+9pbyK8L3~pi{*=kB3PPdngt~pG>%~gRPtoztrmCsw6Rzv zIILI>CeRL!rG}JuI+x%gkH}>+NxVLErFRT;lk%NedbP2bgdD+0w7Sq9rB-Ygo2d~u)_4I_I95*v}PrZXgAclSO`>tyEHcDa^>YvYmrQG%KV zG0WJ6%lO}G;(vqc9@$hjWn%V=m^Y!{7WlQEmfn?#`<3u@6oG-O12B3`ryiVZkDH)* z@J3Wz$Sm(KODKjn-EL+nEPKI{%|sqz_$(q6hJ60s<!7Hf|v(C7SyL(&(3!SPI3#g z78b(QfBz0z-#IB8hd4qRqr?(%%KPB$MDHP&}6v5DngwJ`z za08C;YmAFHviFKunjAUH4I9JJnvbpWTQ83)iv2FfKoqR6R8)-~q^`7OE{GvB zDbEQn;GQXZ2|7VtKs6N!?Y0_K(+CbnvkVgvAI5H&a}HAYQ65+X=wM5vt=Y5!P>3Y% z*$)Jkb|A!5aJG&k_g4x+PsGLt?M35B0xj5K$i6ctCn%x+r!q3BmnaHWVq0*t1Q zJ+QP8Z%y2M0<#}DgS7?1x8bUIK!+gTp9MznVU7Gu+6bv<91#YBUD(d9|MX4*jnx7Y_r-j_p^W%+&Xl=*ftY2V=f9QhroG*^kl^n@eML0`quE5!!7 zaZnikd;}ML*;1Dl1y3=rMj)3*o$R{HY#pq-hG%?zA7&8g>Y8sTLEGYy(X;M+r!8sBQ8+Nkaw9c@5 zu;|3pm4C+_=@Y44i3IaYXz|8E+K8SANzs$mzK^N+dA3(%+r7r}hdm959!8yPFE~!5 zkO4*6XhsPJLRmr|m&$h!YXw!k@YBYs-6c9cmCSnSu@Evvke;J|X*Hhe(wg)gv@dBX zo7G4wAiu3<#D6(}6f(rnw{0n8IReW6QOfQb)T4Suf(XQg|I&o_6h#1_j7JzK#Q&Ev q_6Gp@xTexi#Q)1G|9`yY#ji~Uwdg0FzbhE

Ask questions about the documentation and project

Stay up to date

Find out what's new with this project

-
\ No newline at end of file + \ No newline at end of file diff --git a/en/help/index.html b/en/help/index.html index ea03f80b..a58adf36 100644 --- a/en/help/index.html +++ b/en/help/index.html @@ -12,4 +12,4 @@

Ask questions about the documentation and project

Stay up to date

Find out what's new with this project

-
\ No newline at end of file + \ No newline at end of file diff --git a/en/index.html b/en/index.html index 93ec3fbe..9a4a7cc1 100644 --- a/en/index.html +++ b/en/index.html @@ -12,10 +12,7 @@

Supports optimized implementations of several common functions for 3D data

Differentiable Rendering

Modular differentiable rendering API with parallel implementations in PyTorch, C++ and CUDA

-

Get Started

  1. Install PyTorch3D:
    conda install pytorch torchvision -c pytorch  # OSX only
-conda install pytorch3d -c pytorch3d  # all systems
-
    -
  2. Try a few 3D operators e.g. compute the chamfer loss between two meshes:
    from pytorch3d.utils import ico_sphere
+

Get Started

  1. Install PyTorch3D (following the instructions here)
  2. Try a few 3D operators e.g. compute the chamfer loss between two meshes:
    from pytorch3d.utils import ico_sphere
 from pytorch3d.io import load_obj
 from pytorch3d.structures import Meshes
 from pytorch3d.ops import sample_points_from_meshes
@@ -31,4 +28,4 @@ sample_sphere = sample_points_from_meshes(sphere_mesh, 5000)
 loss_chamfer, _ = chamfer_distance(sample_sphere, sample_test)
    -
\ No newline at end of file + \ No newline at end of file diff --git a/en/users.html b/en/users.html index 34569cb0..611eefdb 100644 --- a/en/users.html +++ b/en/users.html @@ -6,4 +6,4 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -

Who is Using This?

This project is used by many folks

User1

Are you using this project?

Add your company
\ No newline at end of file +

Who is Using This?

This project is used by many folks

User1

Are you using this project?

Add your company
\ No newline at end of file diff --git a/en/users/index.html b/en/users/index.html index 34569cb0..611eefdb 100644 --- a/en/users/index.html +++ b/en/users/index.html @@ -6,4 +6,4 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -

Who is Using This?

This project is used by many folks

User1

Are you using this project?

Add your company
\ No newline at end of file +

Who is Using This?

This project is used by many folks

User1

Are you using this project?

Add your company
\ No newline at end of file diff --git a/files/bundle_adjustment.ipynb b/files/bundle_adjustment.ipynb index 4125006b..67862446 100644 --- a/files/bundle_adjustment.ipynb +++ b/files/bundle_adjustment.ipynb @@ -2,11 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "bD6DUkgzmFoR" }, "outputs": [], @@ -69,26 +68,30 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 717 }, "colab_type": "code", - "collapsed": true, "id": "uo7a3gdImMZx", "outputId": "bf07fd03-dec0-4294-b2ba-9cf5b7333672" }, "outputs": [], "source": [ "!pip install torch torchvision\n", - "!pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" + "import sys\n", + "import torch\n", + "if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):\n", + " !pip install pytorch3d\n", + "else:\n", + " !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -98,20 +101,7 @@ "id": "UgLa7XQimFoY", "outputId": "16404f4f-4c7c-4f3f-b96a-e9a876def4c1" }, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": { - "tags": [] - }, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# imports\n", "import torch\n", @@ -129,7 +119,12 @@ "sys.path.append(os.path.abspath(''))\n", "\n", "# set for reproducibility\n", - "torch.manual_seed(42)" + "torch.manual_seed(42)\n", + "if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + "else:\n", + " device = torch.device(\"cpu\")\n", + " print(\"WARNING: CPU only, this will be slow!\")" ] }, { @@ -144,14 +139,13 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 391 }, "colab_type": "code", - "collapsed": true, "id": "kOvMPYJdmd15", "outputId": "9f2a601b-891b-4cb6-d8f6-a444f7829132" }, @@ -176,11 +170,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "ucGlQj5EmmJ5" }, "outputs": [], @@ -200,11 +193,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "D_Wm0zikmFod" }, "outputs": [], @@ -218,16 +210,16 @@ "\n", "# create the relative cameras\n", "cameras_relative = SfMPerspectiveCameras(\n", - " R = R_relative.cuda(),\n", - " T = T_relative.cuda(),\n", - " device = \"cuda\",\n", + " R = R_relative.to(device),\n", + " T = T_relative.to(device),\n", + " device = device,\n", ")\n", "\n", "# create the absolute ground truth cameras\n", "cameras_absolute_gt = SfMPerspectiveCameras(\n", - " R = R_absolute_gt.cuda(),\n", - " T = T_absolute_gt.cuda(),\n", - " device = \"cuda\",\n", + " R = R_absolute_gt.to(device),\n", + " T = T_absolute_gt.to(device),\n", + " device = device,\n", ")\n", "\n", "# the number of absolute camera positions\n", @@ -253,11 +245,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "xzzk88RHmFoh" }, "outputs": [], @@ -289,7 +280,7 @@ " SfMPerspectiveCameras(\n", " R = cams.R[edges[:, i]],\n", " T = cams.T[edges[:, i]],\n", - " device = \"cuda\",\n", + " device = device,\n", " ).get_world_to_view_transform()\n", " for i in (0, 1)\n", " ]\n", @@ -302,7 +293,7 @@ " cams_relative = SfMPerspectiveCameras(\n", " R = matrix_rel[:, :3, :3],\n", " T = matrix_rel[:, 3, :3],\n", - " device = \"cuda\",\n", + " device = device,\n", " )\n", " return cams_relative" ] @@ -326,7 +317,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -336,151 +327,11 @@ "id": "iOK_DUzVmFom", "outputId": "4195bc36-7b84-4070-dcc1-d3abb1e12031" }, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAsGF/D+/UnkKYJ5tLwAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkP8Hizgo/Ow/yNEAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n+X/Sb11tQjaMFQAAAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n7/oMn2jsAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nLQBH13AvND0AAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noYrO4bkAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAABJRU5ErkJggg==\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAV0AAAENCAYAAACsBrZAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niqIoO/p/KHpiidaXSt4AAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Optimization finished.\n" - ] - } - ], + "outputs": [], "source": [ "# initialize the absolute log-rotations/translations with random entries\n", - "log_R_absolute_init = torch.randn(N, 3).float().cuda()\n", - "T_absolute_init = torch.randn(N, 3).float().cuda()\n", + "log_R_absolute_init = torch.randn(N, 3, dtype=torch.float32, device=device)\n", + "T_absolute_init = torch.randn(N, 3, dtype=torch.float32, device=device)\n", "\n", "# furthermore, we know that the first camera is a trivial one \n", "# (see the description above)\n", @@ -496,7 +347,7 @@ "# the mask the specifies which cameras are going to be optimized\n", "# (since we know the first camera is already correct, \n", "# we only optimize over the 2nd-to-last cameras)\n", - "camera_mask = torch.ones(N, 1).float().cuda()\n", + "camera_mask = torch.ones(N, 1, dtype=torch.float32, device=device)\n", "camera_mask[0] = 0.\n", "\n", "# init the optimizer\n", @@ -517,7 +368,7 @@ " cameras_absolute = SfMPerspectiveCameras(\n", " R = R_absolute,\n", " T = T_absolute * camera_mask,\n", - " device = \"cuda\",\n", + " device = device,\n", " )\n", "\n", " # compute the relative cameras as a compositon of the absolute cameras\n", diff --git a/files/bundle_adjustment.py b/files/bundle_adjustment.py index 7276352b..59915179 100644 --- a/files/bundle_adjustment.py +++ b/files/bundle_adjustment.py @@ -1,4 +1,4 @@ - +#!/usr/bin/env python # coding: utf-8 # In[ ]: @@ -37,14 +37,19 @@ # If `torch`, `torchvision` and `pytorch3d` are not installed, run the following cell: -# In[1]: +# In[ ]: get_ipython().system('pip install torch torchvision') -get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") +import sys +import torch +if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'): + get_ipython().system('pip install pytorch3d') +else: + get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") -# In[3]: +# In[ ]: # imports @@ -64,11 +69,16 @@ sys.path.append(os.path.abspath('')) # set for reproducibility torch.manual_seed(42) +if torch.cuda.is_available(): + device = torch.device("cuda:0") +else: + device = torch.device("cpu") + print("WARNING: CPU only, this will be slow!") # If using **Google Colab**, fetch the utils file for plotting the camera scene, and the ground truth camera positions: -# In[2]: +# In[ ]: get_ipython().system('wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/camera_visualization.py') @@ -97,16 +107,16 @@ camera_graph_file = './data/camera_graph.pth' # create the relative cameras cameras_relative = SfMPerspectiveCameras( - R = R_relative.cuda(), - T = T_relative.cuda(), - device = "cuda", + R = R_relative.to(device), + T = T_relative.to(device), + device = device, ) # create the absolute ground truth cameras cameras_absolute_gt = SfMPerspectiveCameras( - R = R_absolute_gt.cuda(), - T = T_absolute_gt.cuda(), - device = "cuda", + R = R_absolute_gt.to(device), + T = T_absolute_gt.to(device), + device = device, ) # the number of absolute camera positions @@ -152,7 +162,7 @@ def get_relative_camera(cams, edges): SfMPerspectiveCameras( R = cams.R[edges[:, i]], T = cams.T[edges[:, i]], - device = "cuda", + device = device, ).get_world_to_view_transform() for i in (0, 1) ] @@ -165,7 +175,7 @@ def get_relative_camera(cams, edges): cams_relative = SfMPerspectiveCameras( R = matrix_rel[:, :3, :3], T = matrix_rel[:, 3, :3], - device = "cuda", + device = device, ) return cams_relative @@ -180,12 +190,12 @@ def get_relative_camera(cams, edges): # `R_absolute = so3_exponential_map(log_R_absolute)` # -# In[8]: +# In[ ]: # initialize the absolute log-rotations/translations with random entries -log_R_absolute_init = torch.randn(N, 3).float().cuda() -T_absolute_init = torch.randn(N, 3).float().cuda() +log_R_absolute_init = torch.randn(N, 3, dtype=torch.float32, device=device) +T_absolute_init = torch.randn(N, 3, dtype=torch.float32, device=device) # furthermore, we know that the first camera is a trivial one # (see the description above) @@ -201,7 +211,7 @@ T_absolute.requires_grad = True # the mask the specifies which cameras are going to be optimized # (since we know the first camera is already correct, # we only optimize over the 2nd-to-last cameras) -camera_mask = torch.ones(N, 1).float().cuda() +camera_mask = torch.ones(N, 1, dtype=torch.float32, device=device) camera_mask[0] = 0. # init the optimizer @@ -222,7 +232,7 @@ for it in range(n_iter): cameras_absolute = SfMPerspectiveCameras( R = R_absolute, T = T_absolute * camera_mask, - device = "cuda", + device = device, ) # compute the relative cameras as a compositon of the absolute cameras diff --git a/files/camera_position_optimization_with_differentiable_rendering.ipynb b/files/camera_position_optimization_with_differentiable_rendering.ipynb index 56e89b55..ee879db3 100644 --- a/files/camera_position_optimization_with_differentiable_rendering.ipynb +++ b/files/camera_position_optimization_with_differentiable_rendering.ipynb @@ -2,11 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "-P3OUvJirQdR" }, "outputs": [], @@ -56,26 +55,30 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 717 }, "colab_type": "code", - "collapsed": true, "id": "sEVdNGFwripM", "outputId": "27047061-a29b-4562-c164-c1288e24c266" }, "outputs": [], "source": [ "!pip install torch torchvision\n", - "!pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" + "import sys\n", + "import torch\n", + "if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):\n", + " !pip install pytorch3d\n", + "else:\n", + " !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", @@ -86,7 +89,7 @@ "import os\n", "import torch\n", "import numpy as np\n", - "from tqdm import tqdm_notebook\n", + "from tqdm.notebook import tqdm\n", "import imageio\n", "import torch.nn as nn\n", "import torch.nn.functional as F\n", @@ -97,16 +100,16 @@ "from pytorch3d.io import load_obj\n", "\n", "# datastructures\n", - "from pytorch3d.structures import Meshes, Textures\n", + "from pytorch3d.structures import Meshes\n", "\n", "# 3D transformations functions\n", "from pytorch3d.transforms import Rotate, Translate\n", "\n", "# rendering components\n", "from pytorch3d.renderer import (\n", - " OpenGLPerspectiveCameras, look_at_view_transform, look_at_rotation, \n", + " FoVPerspectiveCameras, look_at_view_transform, look_at_rotation, \n", " RasterizationSettings, MeshRenderer, MeshRasterizer, BlendParams,\n", - " SoftSilhouetteShader, HardPhongShader, PointLights\n", + " SoftSilhouetteShader, HardPhongShader, PointLights, TexturesVertex,\n", ")" ] }, @@ -134,14 +137,13 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 204 }, "colab_type": "code", - "collapsed": true, "id": "sD5KcLuJr0PL", "outputId": "e65061fa-dbd5-4c06-b559-3592632983ee" }, @@ -153,18 +155,20 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "VWiPKnEIrQdd" }, "outputs": [], "source": [ "# Set the cuda device \n", - "device = torch.device(\"cuda:0\")\n", - "torch.cuda.set_device(device)\n", + "if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + " torch.cuda.set_device(device)\n", + "else:\n", + " device = torch.device(\"cpu\")\n", "\n", "# Load the obj and ignore the textures and materials.\n", "verts, faces_idx, _ = load_obj(\"./data/teapot.obj\")\n", @@ -172,7 +176,7 @@ "\n", "# Initialize each vertex to be white in color.\n", "verts_rgb = torch.ones_like(verts)[None] # (1, V, 3)\n", - "textures = Textures(verts_rgb=verts_rgb.to(device))\n", + "textures = TexturesVertex(verts_features=verts_rgb.to(device))\n", "\n", "# Create a Meshes object for the teapot. Here we have only one mesh in the batch.\n", "teapot_mesh = Meshes(\n", @@ -210,17 +214,16 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "KPlby75GrQdj" }, "outputs": [], "source": [ - "# Initialize an OpenGL perspective camera.\n", - "cameras = OpenGLPerspectiveCameras(device=device)\n", + "# Initialize a perspective camera.\n", + "cameras = FoVPerspectiveCameras(device=device)\n", "\n", "# To blend the 100 faces we set a few parameters which control the opacity and the sharpness of \n", "# edges. Refer to blending.py for more details. \n", @@ -235,8 +238,6 @@ " image_size=256, \n", " blur_radius=np.log(1. / 1e-4 - 1.) * blend_params.sigma, \n", " faces_per_pixel=100, \n", - " bin_size = None, # this setting controls whether naive or coarse-to-fine rasterization is used\n", - " max_faces_per_bin = None # this setting is for coarse rasterization\n", ")\n", "\n", "# Create a silhouette mesh renderer by composing a rasterizer and a shader. \n", @@ -254,7 +255,6 @@ " image_size=256, \n", " blur_radius=0.0, \n", " faces_per_pixel=1, \n", - " bin_size=0\n", ")\n", "# We can add a point light in front of the object. \n", "lights = PointLights(device=device, location=((2.0, 2.0, -2.0),))\n", @@ -263,7 +263,7 @@ " cameras=cameras, \n", " raster_settings=raster_settings\n", " ),\n", - " shader=HardPhongShader(device=device, lights=lights)\n", + " shader=HardPhongShader(device=device, cameras=cameras, lights=lights)\n", ")" ] }, @@ -285,7 +285,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -295,21 +295,7 @@ "id": "EjJrW7qerQdo", "outputId": "93545b65-269e-4719-f4a2-52cbc6c9c974" }, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140092634331216", - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Select the viewpoint using spherical angles \n", "distance = 3 # distance from camera to the object\n", @@ -349,11 +335,10 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "YBbP1-EDrQdu" }, "outputs": [], @@ -402,11 +387,10 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "srZPBU7_rQdz" }, "outputs": [], @@ -434,7 +418,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -444,32 +428,7 @@ "id": "qyRXpP3mrQd3", "outputId": "47ecb12a-e68c-47f5-92fc-821a7a9bd661" }, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Reference silhouette')" - ] - }, - "execution_count": 19, - "metadata": { - "bento_obj_id": "140046464048336" - }, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAlYAAAEtCAYAAADKqC6AAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkiSV5P8D4F92xJykcVkAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140047413426192" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.figure(figsize=(10, 10))\n", "\n", @@ -482,7 +441,7 @@ "plt.subplot(1, 2, 2)\n", "plt.imshow(model.image_ref.cpu().numpy().squeeze())\n", "plt.grid(False)\n", - "plt.title(\"Reference silhouette\")\n" + "plt.title(\"Reference silhouette\");\n" ] }, { @@ -499,7 +458,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -519,271 +478,9 @@ "id": "HvnK5VI5rQd6", "outputId": "4019c697-3fc6-4c7b-cdfe-225633cc0d60" }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "78b2d6baaf28479c8aebf3b35cd9cf74", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, max=200), HTML(value='')))" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSnGKBKU4RYJSnCJBKU6RoP4PtK1qrRux1HYAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046487997712" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046488867728" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046463357264" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0\ndHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAU1klEQVR4nO3dfZBddX3H8ff33nMf9u5uspsAIjEP\nLaTyMKkwQDREHWEEpxlxQBhUnFRBEau2TrWl06maTcVqH6HFPozaDrUMhFZGS4WOOjZiiJUQpTwm\nklgDkSSbkN087OPdvffXP/id27Mn9+5DHvb8Ej6vmTO7e3/nnnvO3fu5v9/5/X7nXnPOISLhyWW9\nAyLSnMIpEiiFUyRQCqdIoBROkUApnCKBOunDaWYjZnZt1vtxvJiZM7Prs94Pyd5JH07nXNk5901e\neWEvMbMbT+Tjmdk5ZvagmfWZWb+Z/cDM3pQon2NmXzezl8zsZTP7lpm99kTu0/FmZl/1b3rJpWpm\nv0isc42Z/dTMDpvZc2b24URZ3sw+b2YvmNmgmT1vZr+XKP9uk+2Pmdn6FvvTbmZ/aWY7zGzIzDaY\n2bJE+Rlmdo+Z7TWzQ2a2ycxWndhnaRY4506ZBfg08O0TuP0c8L/A3wGdQAX4a2A/0ObXuQ/4L+As\noBtYB2ycwWM44Pqsn8sm+/UA8AX/+wXAKHADUAKuAAaBK335WuB54Dz/nF0ODAPvmeR53QTc0qL8\nH4Ct/nHbgNuAXwIVX/4I8E3gNKAI/D4wAizK+nk7puc86x04Di8aB1wPfAao+WUEWAAY8AfAz4Ah\n/3N14r53A/cADwKH/G2fAX7S4rE6gQ8DcxK3/brfh9f7F8c4cFmifKEvv3Amx+N/LwJ/6t8QhoEn\ngXcl1r0UeBQ4CPQDDwELfdnpwL8BLwMDwOPA5Yn7jgDXTnOf3gnsSIThTuC7qXX+EfiW//03gEtT\n5T8Fvthi+78N/BiwFuV7gY+mbnvOvznkgJuABYmyOf55fEfWr89jem1nvQPHfAATX8x3J2tO4OPA\nTmAZkAdW+Xf8SxLr7wduBHJH8dhnAl8HHvPbv9LvT7nJi6tprTDF8fypf0M51wf1E0AVOMeXPw98\nHoj8C/JfgPt92VeA7/jbI3/fl4BohscYAduA9yZu2wh8KbXex4CXmty/BLzPv4Esb1Le5d9Y3jTJ\nPuwDPpa67Yh98Ld3++ftF0Bn1q/PY1lO+nPOKdwK3OWce9o5V3POPQx8G/hgYp0+59y9zrn6TDZs\nZqPAbuB1wDXOuZqvrUaccyOp1ft8rTpTtwB/7pzb6pyrOue+7Jtz7/blXcCgc27cOXcI+IBz7j2J\nsiow5Mu/DLzOOTc+w31YDYwB/5q47XQfqEmP0cy+6mv8O4DfdM5tarL93wUec879eJJ9+Hfgk2Z2\nnpkVzewD/g13furxfub34ypglXPu8AyPNSinejh/Dbg92fEAXA0sSqzzi0nu35JzrgS8FtgC/MjM\n5k6yuvkacdrMrNvXAs+lirYDv+p/vw34jJltNbO7gLck1vsScCHwku8seZ+v3WfqNuCvpvHmdcQx\nOudu8eeIHwfuNrN3T7iDWRn4JPAXU2z7U8AP/bn8L4E3+MCOpR7v9cA8f368wcx+ZaYHG5JTPZzD\nwK2+Rzdeis65dyXWqR7txp1ze/z50lzgWqAXKJtZe2rV03zZTJRb3G6Jx7/b19y3+9rsO2b2JV/2\nUx/iDwIHgL8BfmBm0w6omb3Bv8E9mCrqbdISaHqMzrlR59wDvvn/O6nid/hA/2Cy/XDOHXLO3eKc\ne61z7gzn3Kf8cf+yybr9zrnbfRP+A9M91hCd6uHc5muPBjNbNJMXaOq+l5nZzia1ZMm/iz/hO4Qu\nSdznHP9u/t8zfLhe4LBvvsXbyvnzz23+79Occwecc/c4597rz/t+y5d18cqL9T+dc58A3gis9B1Y\n03UN8Lhzbm/q9k3JY/TeCPzIP/aPzOwjqfJSuqbz2//OVE1tM3uzmb058XcX8Cbgh2a22MxeNLML\npvF4J5VTLZzDwEIz6zKzIvC3wM1mdqWZRWa2AviJb9oejf/x4bvLzLrNrAJ8wd+23jnX54dSbjez\ns8xsPvBnvmdzK6+8sL5oZn8/1QP5ZuQ/A5/2Y6slP0QwD7jfzF4H7DKz6/y4Ypt/I9rmN/Fjvx/t\nPtRv9J1hL87geC8Fnmpy+1eAy8zsRjMrmdlV/jz4y778UeCPzOwiv29v8Z1C35rO9s1suW+qd/mb\n3gbc48exO/zQymbn3KP+eHYDd/jnvGhmHwfO9r3XJ6+se6SOdUn1br7Z94weBi72TcA/9P/AYd/z\n+dHEfe9Oj4tONpTiy5cC/+GHJw74MbYVifIO4J982SHfkTI/9ZgPTvN42vyY6ot+ez+Me5p9+fXA\n036Mcb9/Mb7ely0D1vt9OOSHUlYl7jvlUIp/I/uTFmWrgGd84LcBNybKin6sc5d/3p/3byyW2sZ+\n4CNNtv02/zycltjeV3xnzyE/RHRGYv0z/ZDYAf+/fxx4Z9avzWNdzOmTEGaVmS0C/tg598FprC6v\nYqdas/Zk8O6pOkBEiJsZIhIe1ZwigVI4RQIVTVZoZmrzipxgzjlrdrtqTpFAKZwigVI4RQKlcIoE\nSuEUCZTCKRIohVMkUAqnSKAUTpFAKZwigVI4RQKlcIoESuEUCZTCKRIohVMkUAqnSKAUTpFAKZwi\ngVI4RQKlcIoESuEUCZTCKRIohVMkUAqnSKAUTpFAKZwigVI4RQKlcIoESuEUCZTCKRIohVMkUAqn\nSKAUTpFAKZwigVI4RQKlcIoESuEUCZTCKRIohVMkUAqnSKAUTpFAKZwigVI4RQKlcIoESuEUCZTC\nKRIohVMkUAqnSKAUTpFAKZwigVI4RQKlcIoESuEUCZTCKRIohVMkUAqnSKAUTpFAKZwigVI4RQKl\ncIoESuEUCZTCKRIohVMkUAqnSKAUTpFAKZwigVI4RQKlcIoESuEUCZTCKRIohVMkUAqnSKAUTpFA\nKZwB6OnpyXoXJEDmnGtdaNa6UI6Lnp4eisUibW1tzJkzhw996ENZ75LMMuecNbtdNWeG4hoziiKi\nKKJer3PfffdlvVsSCIUzY2aGc45arcbY2BiDg4Pce++9We+WBEDhzFi9XqdWq1Gr1ajX6zjnqFar\nWe+WBEDhzJiZUa1WGyEdHx+nVqvxwAMPZL1rkjF1CGXs/vvv57nnniOKItrb2ykWixSLRTo6OqhU\nKlxzzTVZ76KcYOoQCtTAwAAXX3wx4+PjVKtVxsfHG4uat69uCmfGDh06xNjYGGbGyMjIhHCOjo7y\njW98I+tdlIyoWRuAO++8k4ULF1KpVHjssceIooju7m6KxSKFQoFisdho4q5Zs4ZiscjixYupVCoM\nDAwwMjKCcw6zV1pHZoaZsXPnTrq6uujo6ADf+XTrrbdmfLSS1qpZq3AGoKenh8WLFzN//nzK5TIb\nN26ku7ubUqnUCGepVGL79u0sW7aMPXv2MD4+Tr1ep16vc/jwYfChzOfz5HI5CoUC7e3tmBm5XA4z\n44UXXmDRokXcfPPNWR+yJCicgbvjjjtYsGABlUqFzZs3U6lUKJVKlEol9uzZQ6lUYt68eVSrVYaG\nhhgeHsbMKJfLFAoF8vl8o8bM5XKNxTlHLpcjiqIJ5bVajZtuuinrw5ZJwhnN/q5IMwcPHqS9vZ1C\nocDy5cvZtGkTuVyOvr4+zj33XA4ePEhvby/1ep1CoUBbW1ujloyiaEI4kyFs9tM5x759+1i3bh1j\nY2OsXr0668OXJtQhFIienh56e3sZHBxkbGwMfE/uihUr2LdvH7t37wZonIdGUUShUJhQayZrzOSS\nDmwURZx11lls3bqVcrnMunXrMj56aUbhDMhnP/tZ+vv7GR0dxTnHFVdcwZYtW+jr68PMGsGMw5kO\nXjPNyqMoolQqsXTpUp555hmKxeIsHqVMl845A7NmzRoA2traGueV+XyeQqFAqVSatNk6VbM2XvL5\nfGOJooiRkRE6Ojqo1+tcffXVWT8FrzqahHAS6OnpwcxYvHhxI5hxz2uhUDgifLzyj20sSVPVqPF9\n6vU6HR0d7N27l0KhwEMPPTQrxypTUzgDkbzgemhoqPF7fDlZOmTNAjlZQFvdP75PqVSiVqsRRREP\nP/zwcT02OToKZwCSwVy1ahUDAwON5mcymJMFrLe3l3379nHw4MEJ4U4GMx3SOJjj4+OUy2Uef/zx\nRkeTApo9DaUEJIoiNmzYwMjICGbW6PQhcd1n/DN5W19fH52dnRM6i6Jo4r92stoToL29nfPPP58D\nBw7Q3d3dsjkss0c1Z8biWtM5x6WXXsro6CjAhFozXdslzxf7+voolUoTOn3i388888yWnUXxEl9D\nms/naWtr46mnnmo89ve///3MnhdROIPgnKOzs5Onn366cSVK3AGUXi9earUaBw4caMwAyuVyE3ph\nc7kc1WqVc845p1EDx0tavV5nbGyMOXPmcOGFFzIwMNCYNijZUTgzFA+bACxbtqxRawITQpQOaTyn\nliadPumhlDioyeZx+hw02ZFUKBTYvXt34z7r168/gc+ATEbhzFAydB0dHY2ZQa3WIVV7lsvlxjrN\nlkqlwosvvjhhplCr7eJDXywW2blzZ6NGzufzx/moZbrUIRSIQqFwxG3NAtTqtvSQiZk1Ji1Mdt8k\n5xylUqnxt8KZLdWcGenp6ZnQ65o2WZDSYUzXuPFUv/7+/ikD2WqiQrJpvGHDhhkcmRwvqjkzEPfQ\nJmf5PProo43f02FJ/52cltfR0dH4SJO4l7VcLpPP5xkZGWlss9UEhWZ/p6f6aVglG6o5M5IMi5lx\n0UUXNV2vWWDSV52Uy2WKxSL5fB7nXOMjTuKOo3i4ZCrpzqHkY2/cuPE4HLXMhGrOjCQnFQBs2bKl\ncTstalBSgYnXia/njC+urtVqk4axWU0cn19Wq1XOOOOMppMfZHYpnBlKvvBffvll8vk84+PjMEXz\ntlltmlSv1xsTDJrdr9l+xE3Y0dFRlixZcsRQjsI5+9SszUi6M6hWq0248qRZUzR9XtjsYurk7KF4\nG+ml2TbjWjeejCDZUzgz0qwmWr58eSM8yYkG6fs1m2ww2bzZ9M/ktpJN2rGxMZ544gmiKDoiyKo5\nZ5/CGQgz45FHHuGSSy4Bf6VI/NUM6fWafQLCZPNvW9WYyc8fAli/fj1vf/vbj+gYkmwonAExMzZv\n3tz4OsD4+1OmU4PGptsrm2wSR1HE0NAQK1eubAS1VTNYZo/CGRjzn4QQD4lMFtCjlf7wr3w+z/79\n+6lUKtAkmAppNhTOAG3fvr3RKZT88GimUTNOZ0ZQMpyFQoF6vc6CBQsmdCjRpHkss0vhDECzwK1c\nuRIzm3DuOd3JBK0ka8v4fBNgeHh4QidQs4Cmz33lxFM4M5D8WBJazMzZuHEjlUqlMXc2GdCZhtQS\nX9OQ7J11zrFx40aKxeIRnUfp5a1vfetxfQ5kagpnIJo1R+PPAjr77LPJ5XIMDAwwOjraCGvc5G0V\n1PS5ZfIqk61bt1Kv17nsssvI5/ON4CffAOIlnhghs0szhDIy2RUpaT//+c8bEwOGhoYolUoUi8VG\nszSXy1Gv1xsTCZhkFlEc5qVLlzZq7HhGUatx0XgCvcwu1ZwZWbt2LaTONydrqh48eJCuri66uroo\nFAqMj48zPDzc+MLd9CT39FKv13n22Wep1+uN2rPV+snba7UaV1111Sw8I5KmmjNjyfm1rWrRuHz3\n7t2Uy2Xa29tpb28nl8sxODjYaIrGnx+UnGW0Y8cOFi5cSLFY5Lzzzpsw5zauadO1bpK+XTs7+jqG\njLW66Do98T29Tvx9J6VSiY6OjiM+uKvZ3Nv490KhMOE8NPkVgcn1AS6//PJZeR5ezfQVgIGa6tKw\nVn/HvbfVarVxoXX60/eSn7oXN2Xj81MSNWdy6CSuRZnmbCM5cVRzBmDNmjVHfd1k/JEkyVDGv8df\nD5j+FL645kwPrcS1Zvy1DDrXnB36IqOArV279pguaG41NtnqcrFmHUBx508+n6dcLk/4SgfJhsIZ\niKmuBGlV1mz+63SDmuyVjZvJw8PDjI+P09nZeYKOVKZL4QxEetZQ2mS16mTDMc3GLpsNoYyOjjbO\nXwcHB6lWq3zve987xqOSY6FwBiRu3jYznc6ZqWrOVuOa/f39DA8PMzQ01Pg5MDCgYZSMqUMoUFPV\npElxr2y68yfd8WOJL+PdsWMHxWJxwtCJS3zvCr7ndvHixVx33XUn8EilVYeQwhmw+LtU0p/Il+48\nSoeyWQ9tcgxz165dje3Fn0ubHEpJWrBgAUuWLOHKK6+cxSN/dVE4T2LpkKYlrzpJD6c0m1iwd+/e\nSR8v+Zro7u5m/vz5rF69+rgek/w/hfMUkGzqpmcMpccrk+OW6amB/f39E7ZBi9oZ/x0uc+fOZd68\nebz//e+fpSN9dVE4TyGtzkfTNWi6pr3tttsm3UazKYP5fJ7TTz+d9vZ2Ojs7ufbaa4/rsYjCecpq\nFbJ8Ps/nPve5Gd+XVEjNjCVLljA0NMSePXu44IILuOGGG47T3gsKp0wlHdRkQFesWAHArl276O3t\nZXh4uHHJmxw7hVOOypo1a6hUKqxcuZLBwUG2bdvGvn37FM7jSHNr5aisXbuW4eFhdu3aRRRFLF26\nlCiK+NrXvpb1rp3yFE6ZUk9PD88++yyHDh2iXq9z/vnnN3p85cRROGVa1q5dy5NPPsnAwAD5fJ65\nc+dmvUunPJ1zyozdddddvOY1r1Gv7XGiDiGRQKlDSOQko3CKBErhFAmUwikSKIVTJFAKp0igFE6R\nQCmcIoFSOEUCpXCKBErhFAmUwikSKIVTJFAKp0igFE6RQCmcIoFSOEUCpXCKBErhFAmUwikSKIVT\nJFAKp0igFE6RQCmcIoFSOEUCpXCKBErhFAmUwikSKIVTJFAKp0igFE6RQCmcIoFSOEUCpXCKBErh\nFAmUwikSKIVTJFAKp0igFE6RQCmcIoFSOEUCpXCKBErhFAmUwikSKIVTJFAKp0igFE6RQCmcIoFS\nOEUCpXCKBErhFAmUwikSKIVTJFAKp0igFE6RQCmcIoFSOEUCpXCKBErhFAmUwikSKIVTJFAKp0ig\nFE6RQCmcIoFSOEUCpXCKBErhFAmUwikSKIVTJFAKp0igFE6RQCmcIoFSOEUCpXCKBErhFAmUwikS\nKIVTJFAKp0igFE6RQCmcIoFSOEUCpXCKBMqcc1nvg4g0oZpTJFAKp0igFE6RQCmcIoFSOEUCpXCK\nBOr/AHYKWRdVX+yiAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046463617296" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046462817104" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nA9Dty2EIq8KlAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046462421328" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nOAnxFIqTEE+hOAnxFIqTEE/5f2/1FXcXOyHzAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046449306128" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046462420496" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140047413338448" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046448682192" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nhHgKxUmIp1CchHgKxUmIp/w/0QygjXE7caUAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046448559248" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046448290512" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nFCchnvL/tMIznaGp+z4AAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046447898384" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046434818256" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIZ5CcRLiKRQnIZ5CcRLiKf8PphZo5rDxwscAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046434053200" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046434176144" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIZ5CcRLiKRQnIZ5CcRLiKf8PHKmZncHcDcYAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046434051856" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nnikmekEAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046433628112" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCsVJiKf8P8ZamgYBgyMkAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046433023312" - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAOcAAAD4CAYAAAAXdPFuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0\ndHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAepElEQVR4nO2de5BkVX3Hv7+eR09v94yzs8sui8uy\nIBhcBdbIQ9CQaJUPoKQgYIxWWRgrMQlFxWiVMVqkdleMQWPYZFeSCgsxIW4ehkoUAgbXyIqWWhg0\nCrUuuxEWhNp139Mz3dPT3dMnf3jO9fSZc2/f7umZOdPz/VTdmp77OOfc2+d7f49z7m1RSoEQEh6Z\nxW4AIcQPxUlIoFCchAQKxUlIoFCchAQKxUlIoCx5cYpIRURuXOx2LBQiokTk5sVuB5l/lrw4lVJD\nSqn/wM877kYRec981yki60Xkv7VQVjvbzhCR+0TkJRGZFJGHReRsa/uIiNyvtx8XkS+JyLr5bnO3\nEZEPisgBESmJyHMicqeIDFjbbxCR74vIhIjsE5HfjilnWER+KiJ7E+rKi8hfiMghESmLyDdF5CJr\n+14Rqesbtb3k5+HUF4wlL06HmwDMqzhF5GoATwB4KWaXfwTwSwCuArAOwE8AfElERG//WwDrAVwG\n4AIAFQAPzGebu42I/BaA2wG8F8AwgBsAvB/Ah/X2VwP4VwB3AlgN4DYAfyUib/EU92e6jCT+AsB1\nelkF4CEAXxGRFdY+n9Q3anspdffMFxil1JJeACgAN+vOMqOXCoCXAxAAHwXwDICy/vte69i/B/AF\nAA8CKOp1twN4MqG+mwFsBvBruu7V1rY8gAaAt1vrBgCMA7hcd9Q6gKus7Wfrcja3c7768yCATwN4\nFsAUgB8CuN7a9zIA39L1nwLwMICz9bYzAPwbgOMAJgF8D8CbrGMrAG6MacMb7X31un8H8M/6818C\n+Kqz/T4AX3LWvV7f5O4CsDfhnI8C+D1n3T4Av6E/7wWwdbH7YreXnrGcSqlPaqv1FX3XfAnArfqu\nfbO+O38IwL0icql16DUA/gXAqClHKfW6hHoeUEr9b8xmYx0z1v413fl/GcBrAfQB+L61/acAjmkh\ntcsd2mpdC+BlAHYBeEBEztfbdwN4TFubcwCcBPBZve1PAYwAOE+f+z8A+IKI9MMJFzzX4FtKqcfw\ncyvZLyJvA3C1tpbQ5/J957An7XPULvAu/Z0UW5yneLy8U/qaGt5kudH/KyK/muL6BU3PiDOG3wWw\nUyn1lFJqRin1CID/BPA+a5+TSql/Uko15lqZUmoSwNcB3C4iZ4tITkT+GMBKLZAzAFSUUhXn0JPa\nqrbL7wD4c6XUfqVUVSn1OQAvAvh1vX0UQEkpVVdKFQHcopR6l7WtCqCst38OwHqlVD1t5SJyO4Bp\nAF8E8HGl1Jf0pjO0eJLO8Y8APK+U+mKKqr4M4IMi8ioRGRSRWwBcpK8ptBU9oN3es/R3/F8icm7a\ncwmRXhfnKwF80k4SAHgHgA3WPs91uc73alftBwAO6mv8XQC1hGNEu6upEZGVWvT7nE3/p60htABu\nF5H9IrITwK9Y+92p3fOXROQLIvJubdVTo72VIW29t4rIB5OabM5RRC4A8Ifas0nDhwE8rm98LwK4\nRAu2pttxq1Lqd5RSh5VSEwD+BMDh+c4/zDe9Ls4pAL/rJAkGlVLXW/tUu1mh7iDvVEqtVkqtV0p9\nCsC5ulP9DMCQJ4u4Wm9rh6GY9ca1hlLq73Xy6ZPamj0qInfqbd/XIn4fgNMAdgDYKyLtCrSmXdw/\n1y4q9Lm4noB9jn+rEzgvpKyjqMW3Tim1Rin1YX1eL8bsr/RNd8llwW16XZwHtXWIEJEN7XbAdhCR\na0TkEuv/C3W8901tTesALrW2nw9gDMB32qzqZwAmtHtnysoAuFCfN0RktVLqtFLqC0qp39SW6vf1\nNhNjf0UpdRuAKwC8AcDFKc7xiyJyh7M6a3kHT9jnqLkCwLdF5BwAbwLwJ3oo6bi28G/Q/5/tHAcR\neaOIvNH6f1Qnkx4XkZeJyN0istHa3qe9pv9r43qGx2JnpOa6ONnLv9EZy1GdybxFd+C3AOgHcKVO\nvtygfpGt/c8O652VrdXr79WZzzO0tdgL4B+t7fdroZ6lY6Z/B/Cotf3PAPxNyvPdqWOt87U4Pgqg\npK3Keu0V3KTd1Zy2jv+jj92vM715fZN+t87Qrkpx7rfqDPCv6bIvAfC8jn+hh5KmtVuZBfBWnS1/\ng95/vbPcpW9O6/X2y3X7RtUvMuiHAGwEUNAJvG9a7fkegEcArNHbP6O9gdWtziXkZdEbMOcTaO6s\nb9Rp9wkAr9Mu3scAvKBd3GfslLxPnCmGUr6qO3FV113Ry+16+8v0uOW4ToLsApC3ji8A+DvdeYo6\nmbLKadODKc83B+Cv9fmd1nHZpda+NwN4Sgv2hB5K+SW97SKdyS3q5XsArrWOTRpKEQB/oF3HihbO\nnQCGrH2uBfC0FulBAO9JOKet9lCKe+PTN9p79PUs6iGgNdb+6/V1PKpvAt8AcPFi9825LqL4JoSg\nEJENAD6hlHpfit1JD9PrMedS5Ne1K0yWObSchAQKLSchgUJxEhIo/UkbRYQ+LyHzjFJKfOtpOQkJ\nFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqT\nkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkECh\nOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJ\nFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJFIqTkEChOAkJlP7FbgDpnAceeAC1\nWg2Tk5OoVquoVCqYmZlBNptFLpfDqlWrcNNNNy12M0mHiFIqfqNI/EayYNx///0ol8s4cuRItE4p\nBRGZta+93v2Mn3+nGBsbw7nnnot3vOMdC3YOJB6l1OwvkuIMlx07dqBYLKJerwMJogOAjRs3IpPJ\nNC0ign379s0q11dGNpvFxz72sQU6M+JCcS4Bdu3ahVOnTqFcLieK0bB27VpkMhn09/fPEmcmk0Ff\nXx8ymQyefvrp6Jg4a2o+r127FrfeeusCnTEBxRkmu3btwsmTJ1Eul2eJb+PGjdE68/fZZ59FJpNB\nPp9vEqERp4h415tto6OjGB0dxdGjR6P1k5OTqNVqOHDgAHx94bzzzsMtt9yyQFdkeUJxBsR9992H\nqakplMtllMtlwLJiGzduRKPRiAQFS5zPPfccBgcHMTAw0CS6NOI0/69atQqnTp2K9jXWdWBgAMVi\nEU8//XSTRTWsXr0at9122yJcrd6H4gyAHTt2IJfLoVQqYWJiAjMzMwCADRs2QCmFmZkZiEgkHFec\nhw4dQn9//yzRGYG5AvXtNzw8jEql0lSuEWdfXx/6+vpQKpVQqVTwzDPPNLVfKYUrr7wSb3/72xf4\nyvU2FOcic++990IphfHxcVQqFdRqNQDA2WefjXq9PkuUttUyn59//nkopZDNZptEaIvTFqgrzoGB\nAeTzeVSr1aZyTX1GnKbMSqWCH/zgB7PO5ayzzsIHPvCBBbpyvQ/FuYhs374duVwOExMTqFarqNVq\nWL9+PZRSqNfrswTpfjZ/Dx06FP0/MDDQJELXpbXdXbMMDQ2hv/8XQ9tufbYl7evrQ39/P2q1GqrV\nKp566qkocSQiuOqqq/DWt751wa9lL0JxLhL33XcfBgYGcOzYMVQqFaxduxaNRgPT09ORtfK5sD6B\nvvDCC03ZViNKX8zpitOOLbPZbFMbXXHa5Q8ODja5uj/+8Y+jfTZs2ID3v//9C3YtexWKc4G5++67\nsWrVKpw8eRKVSgUrVqxAuVxuEosRE5zkS5xbKyJ44YUXZu1vMMK13VTzFwD6+vqwYcOG2Db7bhCm\nrWbJ5/M4fvw4fvjDH0Z1btq0Ce9617u6ct2WI3Hi5NzaeWD79u1Ys2YNisUiKpUKCoUCJiYmZlko\nWFlapdSsz77FHJ90U200GpiZmUG1WkW1Wo2ywpOTk9HNwIevvkajgXq9Hi2Tk5PI5/N49atfHbVn\n3759+PKXv9zVa0hoObvOZz7zGbziFa/A+Pg4SqUSBgcHUa/XUalUZllNn6Wy8VlP8/mll14CPBMU\n4iYsXHLJJU2CS/re7XpcS2wWpRSmpqbwox/9KKrv8ssvx7XXXtvBVVve0HIuEBdccAGmpqZQrVaR\nzWZRr9dx4sQJwHITDbalhMdyNRqNaJmZmYmWer2ONWvWpBIYAFxxxRVNNwSf9W61uG1YsWIFhoaG\n8JrXvCYq54knnujadSQUZ1fZunUrarVaZCWr1SqOHTuGbDbblPSBIwj3/ziRzszMROXbbrLr9tpc\nffXVTdbaJUngSQItl8vI5/MYGhrCpk2bon2+/vWvd/WaLmf4yFgX6evrQ7lcRqPRiISZy+VmWSt3\nBk6cQFwBNxoN1Gq1aHjDPdaORc10vYmJCfT19aHRaDSV6daTFjNxIpPJoFQqoVAooNFo4FWvehX2\n79+PqampNq4YSYIxZ5fYsmULLr74Yhw+fDiybGYYIpPJYHBwMDHO9AnGXYwwa7XaLCvoHi8iWLdu\nHXK5HPr7+6OMrbtvK2HGDfHYUwiHhoYwPT2NSqWCAwcO4LWvfS1nEbUBY855ZMuWLRgZGUGhUIgy\nmjZJ2dl2l0aj4S3Pl7wx46nG0tZqNczMzDTFsp22wV7q9Xo0/W96ehqlUglf+9rXFuz69yp0a7vE\nmWeeiXK5HLmbviELExMqz2Nb7n5xosxkMtEcXHiEb8RpZveICKrVamQ93bjUF4fGYbvNxk0GgFqt\nhmw2G5V/4sQJ5PP51OXONw899BDGx8dx5MiRphunfb2Gh4cxNjaGQqGAm2++eVHba6A4u0Amk8Ga\nNWvw7LPPRk+Z+NxOW5hp4k435oSOa5WeJB+HnfyZmZlBJpOJxORaWLcdNr722uvNYjLIfX19eOUr\nX4kDBw5gzZo1bV7F7rJ79+7Iqj/55JPefcw5NxoNlMtl1Go1FItF3HPPPVi5ciXe+c53LnCrm6Fb\nO0e2bt3a1EkREz/6/sKToPEJ0sZYRRPz2aIy82FNdhaWkHyubJJbG9dun0VXeo4wrBuDUgoPP/xw\nV65xu9xzzz0oFosolUpNsbbBvb7ZbBZDQ0PI5XJRZt08ubOY0HJ2kenpaW9HRoeW093PTcoYK2rv\n486ltdtix6u25fRNfki6OdjnZv/faDRiE08Lxc6dO3Hs2LEoAVetVrFp0yYcPHgQ0Fay0Wigv78f\nSilkMhkUCgW8/OUvb/JKzFNDi8myEefu3bujMbqkmTft8JOf/CT6bO62buc1gmino9r7ZjKZqCzz\n2cUdqjEW1dcOV5zuZ981cW8qtjW24zZYz4Yal/Khhx6a9xeJ3XXXXSiVSpiZmYkmfBhxmRjY/W5t\n8Z04cQInT54EtCcUCj0rzp07dzbNijGD9kg5Xa4TWg1v+BJCSfv7yvYJ3TfrB46Va6cen1V36zVv\na7D/N3+NVXIzy/PBpz71KRSLxeh/u+1pbohKKWzbtm1e29gpPSXOO++8M3Lr6vV605sFENOJ2xVo\nkrvnE6drYeISLEmkaWOSVWznPOzyWrnavljZuLZ2Amq+2L59O8bHx73ta3UjNIQqTPSSOM3UORNv\n2UMPSOiwaTp+XCbV/jw+Pj6rfNt62O8FcjtMWpc3rpP5PIKkDpkU/yZlZ+O2w7Gcg4OD8245P/vZ\nz84aT/bd8JLqD8mF9dEz4oQeNjBWyoiyXXH6iHML7WMPHToUbbPX2+KMc0076cC+c/B5CK1cbTg3\nkzTJKt9620MYGxtrsl7djjs//elPo1QqNV3TuJuJ77xDtpY2S16cW7ZsafrffhzKJ6L5olgsYmxs\nzPvOWTPWCH2zSHqmMqmtce6s728rSwfnJuFzA91kj/nfTQTZEyPMuZr3IpkYtFts3boVU1NTsTcM\n99zM+qUiSJslP84pCYPprdy7brYBOuvnawOsB6Bt625wh1zc9sedR9r42Fd20nY3ieS2z13sp2aM\nIO0x1Uaj0ZWHsT/xiU9EbWjn3EN3X+NY8pbTvdOjA0uZNnkAj3jcNsS1zZ7uBo8FTYrrWgmzU+HG\nxZbuZ1/73OthW1B7nW1p58Idd9wRTfJo5/tdihbTsOTFmSbwh9WJ5vplmbtwXGd729vehkcffXRW\nm1TMlDszaJ+UxbVF3g1PoFVsmUaY7g0pk8ng5MmTGB4ebkrG2Vb0wQcfxPXXX992ez//+c/j+eef\nn7W+VQiwVC2mYcmL08XuNDfccAM2b94873XaneQb3/gGrrnmGjzyyCOztkEnreyObyes4pIYnVhT\nl1YZWruMuG1xYjbnMDIygnq93hSPKmfqYLts37696dfVWtGtm3AILPmY08bu3BdeeCFOnTo1b3XF\nCaFSqWDv3r247rrrYo91X/mRFNPBExO6n33rfPFjUjlpYkr3fzf5Zj+SZmdv3X3TsmPHjqYHy9Oy\nEHmGhWDJP2y9ZcuWpi9jxYoVWLt2LYaHh5HP5zE6OoorrriiK3W16yblcjm8+c1vTpwA7vsZBUl4\nZeZc16XZHoexhHbWNp/Po1KpNFlG37tyzWT9/v5+3Hjjjd7yd+/ejXq9jlKpFP0Y8NTUVGqxqYBn\n+yQR97B1T7m1SikMDAzMehnWE088gcsvv7xrdaTtLOVyGY899hiuu+66WIG6s4fi4kvX3U0am/QN\nMyS5yIixxG6dtpUcHBxENpuNXstiz8ZqZX0Ne/bswdTUVPTzFPV6vek1LObF262Ya7IpVJa85YRj\nPXO5HEZHRzEyMoJ8Po/h4eHoZwguu+yyjuuwE0FpM6Hmcz6fj57zTEKs30rxvS1vLtbU93+a9vhc\nbhGJLKZxYw3277bYltM8zmasZyaTidxgW5jVajX6WcK0T4Ys9Thz2bymZHp6Ono1h/nSq9VqZEE7\nxbU8cTc1nyUrl8sYGxuLLdPgxqK+xTeG6ItR08SK7utG3MX1QMwzm4VCAaVSKbrGbuxs1+er25Tt\nWkqz2HWl+V5EZMkKM4meEOe2bduijmnemzM1NYXp6enoizZCneu7VVtZTtdqmXaZCQpr166Nzbja\nx5iJ++0s7kQHV2TuujTiNOJRSmHlypUYGhpq+kEms5/PlU1ybW1B2p/N9+VLXiV9J71Iz8Scdkcv\nlUrRO3MKhcIsoXSrniTceM5Y0yNHjiCbzeK8887D/v37E49zXy3ixqPizB5K49omnYdPUKLf4jc1\nNYXTp083CdcuK404bYHano17I2pYr/FMQy9aTfRKzGlj5tqKCIaGhrBu3TqsWLEC2WwWAwMD0a9s\nmXjo9a9/fapyzetI2onbfEkYd1uhUMDIyAgOHz48axs8SRmftXVj0TQJJfdvw3mv7TnnnIPp6Wmc\nPn26yW21y7Nj5LjfCjWvBXVjUJMIMsK0PRw7hvVdN/tm2wvCXBbZWhulFCqVCiYnJ2fFiGbmSl9f\nH77zne8gk8kkDre4k+tb1Zs02G8LRymFUqmEUqkEpRRyuRyGh4exefNm7Nmzp6lMtw4bE59JyrnE\nvizt5s2bcfz48ShLevjw4cj9TLopuZlmxFhg13r6LGa9Xp81USHOwqc916VMT8ScNtu2bWv64iYm\nJjA5ORn9vqSJcdzl29/+dmyZrVzEpH191ssVrKFSqeDYsWPYs2cPVq5ciYsuuijaL841d4XmS764\n4rA5//zzsW7dOuzfvx9HjhzB8ePHUSwWoxgw7rxdIcZ9biVOe0l6o6B9DXtdlIaec2ttzPDH4OAg\nCoUCCoUCcrkcCoVCFJPaP7NuFtfVdefTJnWOOJfUt1/aTlYoFDA4OBi56aOjo96XNrsW2xX0pZde\niqNHj0Y3KONaJvWBpHbarq3vB3vNNuPW2q7t6dOnowSQz21O04alPnfWsGx/PNd8gX19fRgeHsaK\nFSswNjYWjbfZMZLvF6KvvPLKxDFOn2B9AukEV2C+eHNgYCAax7XfHtfQv9di3EUzSaDF953qBmTT\nKuYUEa84T5w4EWXTW8259V3PXhEmlmPMaTBf6MzMDE6fPh39dIB5R6ltPZV+g4LpVCKCxx9/PPrl\nLF+HjZuRA0+cGde2pG2++Mquz3Y/3W1xbUoi6WYQ104kuLS+TG6j0cCZZ56JgwcPproZuG3vJWEm\n0fOW08bMJFJKYWRkBENDQ8hms02LbQmMKL773e8mltuphZyrZe0U1/WO8wjSts2+XrZba9bZP3pk\nW1DfY2Ct6EVhLlu31ocZFoF+zMmIdHh4uMm1NZ0u7nX+6KILO5/EJaB8CSrfMWmwQwPbzbXDBTcW\nffHFF5vqa3Ude1GYWE7T99KwdevWSHzFYhFHjx7F+Pg4isUiJicnUS6XMT09Pctl9OG6sK3w7ePL\norY6plUddpmuW+zLePpi5lbC9GWK49b5XNt2zqdXhZlEz8eccZgv2/ydmJiA0k9buI84tYoN0UGK\n33dcXD2tEjXucfb+cVbTPaaT84hrS6t4U6yJE742u21arixLt9aHfWfOZDLI5XLRjKKjR492lNRJ\nIk5sPtEk/d9JvT6x+/pBXNvisshxbq2dwbWFad5wEDf+u1wSQIw526RbHaLdsVHfvj4hzTUBlRTj\ndVK+yXT7hOiuM8uxY8di29XrgrShOOdAmo6SdvJB2nKS3NdWgu9UXO265T5xu5bTZHDdDLiI4Pjx\n4163uxfmy7bDsh3nXGh8HbbdYQnEiDTtWGUa4lzItMS1xY01ffGvW79huYmyFRRnl4jrkO0miuzy\n0KEVTJs0Stq/U+KSQfC478vJde0EirOLxGVM50o3xlBbZZuT9mkXn0B92WKSzLIc52yXVnf4uI7W\nTYHON3HuZ7vYZSQtH/rQh7rW9l6F4myDpNgpaZuvjLS446CdtjPNMe6EilZuaVw5vvcb2Y+wpX0/\n0HKH2do28D2dkqbDdjpU4UuapBmaSVNO0r5JSaJW52uPeca9SfAjH/lI6rYvB5it7QKmw8YlU+Jm\n3bjMZZgjLnZLElQn7vVckliw3Fqk8CaIH4qzDZKGDex1Lr6kSxrrae+bJNCkYQ1gdsY4qe60bWpV\nTpw4O/m9lOUK3do2sV9g7Zu542JbtLlmXdO6p61m/6QpI6l+Qxoh224tAHz84x9vu95eh25tF/FZ\nsVazdeZDmL7ZNRLzqkzDXNqQZnaSr83dyAIvR2g5O8B+/WbSOOFcZgq5JFllpLhJdKPOdhJKvuPa\neYvhcoKWs8skuY1J8VwrASUldeBY4k7E0w6dJoXSJsZIMhzn7ADfHFA3aWOvt+lEmL7j7b/tjoPO\nByrmOU4Dp+q1D8U5R+IyooA/UeTOoPHt7x6TVK87UWCx8LnvIdw0ljIUZ4eYV50YfDNqECM433ip\nSztDGq3KagdXSO2MUdoTDWz4tElnUJxzwJeJTYoX4zpvpyRNiGjV7qQy7f2SstCtyiJzg9naLmC/\nzS8ug+sKudWQRJrEEZwETFLmOOn4pLrTttcH48x08O1784hPKL6JCq61mYtbC8cityNMeKxu3PGt\nElxx0KLOHYqzC9gxla9jx00Q8CWHWk3/i+v0aVxmNy5uFRvbx8S57XHtZZw5d+jWdpFWv+HZjjVJ\n4266+7Yad00SdrskTbCgO9sefMHXAmHPHrJJO8XPd2zc/nHHx5XRasw1zRTBJKHLMntrXregOBeY\npE7qExM6mLvqK7cT5joxAnRl5wTFuQikfaVmnFvqs1RptseJPqmsTqEo5w6ztYtAOy5e0pxZd7+4\nqYI2boKom5MU7IXCnD9oOReIVm6uoZPYMe5YXxmtkkZxdbnWl7Fl9+BTKQHjGwM1+ITjxqbutMBW\ndbVaF3ez6Jb1Jemg5Vxg0lqcVpnVbpMU79rQYnYfJoQCpV13dz4sWdxQDGPKhYHiDBz73UQ+fMLs\nlkh9VpoWcuGgOJcQCykMJnkWH4pzCRInlrQTA+ZaD1kYKM4eoVMhme+ZMWR4UJyEBApnCBGyxKA4\nCQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkU\nipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQ\nQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4\nCQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkU\nipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQ\nQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4CQkUipOQQKE4\nCQkUipOQQKE4CQkUipOQQKE4CQkUipOQQBGl1GK3gRDigZaTkEChOAkJFIqTkEChOAkJFIqTkECh\nOAkJlP8HtUg08UdcRyYAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140046419917008" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ - "loop = tqdm_notebook(range(200))\n", + "loop = tqdm(range(200))\n", "for i in loop:\n", " optimizer.zero_grad()\n", " loss, _ = model()\n", @@ -828,6 +525,9 @@ ], "metadata": { "accelerator": "GPU", + "anp_metadata": { + "path": "fbsource/fbcode/vision/fair/pytorch3d/docs/tutorials/camera_position_optimization_with_differentiable_rendering.ipynb" + }, "bento_stylesheets": { "bento/extensions/flow/main.css": true, "bento/extensions/kernel_selector/main.css": true, @@ -841,6 +541,9 @@ "provenance": [], "toc_visible": true }, + "disseminate_notebook_info": { + "backup_notebook_id": "1062179640844868" + }, "kernelspec": { "display_name": "pytorch3d (local)", "language": "python", @@ -857,255 +560,6 @@ "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.5+" - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "02acadb61c3949fcaeab177fd184c388": { - "model_module": "@jupyter-widgets/base", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "2d05db82cc99482bb3d62b6d4e5b1a98": { - "model_module": "@jupyter-widgets/base", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "3df8063f307040ebb8ff8e2f26ccf729": { - "model_module": "@jupyter-widgets/base", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "79d7fc84b5564206ab64b2759474da04": { - "model_module": "@jupyter-widgets/controls", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_efd9860908c64bfe9d47118be4734648", - "IPY_MODEL_f8df7c6efb7d47f5be760a39b4bdbcf8" - ], - "layout": "IPY_MODEL_02acadb61c3949fcaeab177fd184c388" - } - }, - "c621d425e2c8426c8cd4f9136d392af1": { - "model_module": "@jupyter-widgets/controls", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "d8a109658c364a00ab4d298112dac6db": { - "model_module": "@jupyter-widgets/controls", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "initial" - } - }, - "efd9860908c64bfe9d47118be4734648": { - "model_module": "@jupyter-widgets/controls", - "model_name": "IntProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "IntProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "Optimizing (loss 327.5365)", - "description_tooltip": null, - "layout": "IPY_MODEL_2d05db82cc99482bb3d62b6d4e5b1a98", - "max": 200, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_d8a109658c364a00ab4d298112dac6db", - "value": 200 - } - }, - "f8df7c6efb7d47f5be760a39b4bdbcf8": { - "model_module": "@jupyter-widgets/controls", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_3df8063f307040ebb8ff8e2f26ccf729", - "placeholder": "​", - "style": "IPY_MODEL_c621d425e2c8426c8cd4f9136d392af1", - "value": "100% 200/200 [00:06<00:00, 29.48it/s]" - } - } - } } }, "nbformat": 4, diff --git a/files/camera_position_optimization_with_differentiable_rendering.py b/files/camera_position_optimization_with_differentiable_rendering.py index d0f6518f..b763b44f 100644 --- a/files/camera_position_optimization_with_differentiable_rendering.py +++ b/files/camera_position_optimization_with_differentiable_rendering.py @@ -1,4 +1,4 @@ - +#!/usr/bin/env python # coding: utf-8 # In[ ]: @@ -24,20 +24,25 @@ # If `torch`, `torchvision` and `pytorch3d` are not installed, run the following cell: -# In[1]: +# In[ ]: get_ipython().system('pip install torch torchvision') -get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") +import sys +import torch +if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'): + get_ipython().system('pip install pytorch3d') +else: + get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") -# In[2]: +# In[ ]: import os import torch import numpy as np -from tqdm import tqdm_notebook +from tqdm.notebook import tqdm import imageio import torch.nn as nn import torch.nn.functional as F @@ -48,16 +53,16 @@ from skimage import img_as_ubyte from pytorch3d.io import load_obj # datastructures -from pytorch3d.structures import Meshes, Textures +from pytorch3d.structures import Meshes # 3D transformations functions from pytorch3d.transforms import Rotate, Translate # rendering components from pytorch3d.renderer import ( - OpenGLPerspectiveCameras, look_at_view_transform, look_at_rotation, + FoVPerspectiveCameras, look_at_view_transform, look_at_rotation, RasterizationSettings, MeshRenderer, MeshRasterizer, BlendParams, - SoftSilhouetteShader, HardPhongShader, PointLights + SoftSilhouetteShader, HardPhongShader, PointLights, TexturesVertex, ) @@ -67,19 +72,22 @@ from pytorch3d.renderer import ( # If you are running this notebook locally after cloning the PyTorch3D repository, the mesh will already be available. **If using Google Colab, fetch the mesh and save it at the path `data/`**: -# In[2]: +# In[ ]: get_ipython().system('mkdir -p data') get_ipython().system('wget -P data https://dl.fbaipublicfiles.com/pytorch3d/data/teapot/teapot.obj') -# In[3]: +# In[ ]: # Set the cuda device -device = torch.device("cuda:0") -torch.cuda.set_device(device) +if torch.cuda.is_available(): + device = torch.device("cuda:0") + torch.cuda.set_device(device) +else: + device = torch.device("cpu") # Load the obj and ignore the textures and materials. verts, faces_idx, _ = load_obj("./data/teapot.obj") @@ -87,7 +95,7 @@ faces = faces_idx.verts_idx # Initialize each vertex to be white in color. verts_rgb = torch.ones_like(verts)[None] # (1, V, 3) -textures = Textures(verts_rgb=verts_rgb.to(device)) +textures = TexturesVertex(verts_features=verts_rgb.to(device)) # Create a Meshes object for the teapot. Here we have only one mesh in the batch. teapot_mesh = Meshes( @@ -107,11 +115,11 @@ teapot_mesh = Meshes( # # For optimizing the camera position we will use a renderer which produces a **silhouette** of the object only and does not apply any **lighting** or **shading**. We will also initialize another renderer which applies full **phong shading** and use this for visualizing the outputs. -# In[4]: +# In[ ]: -# Initialize an OpenGL perspective camera. -cameras = OpenGLPerspectiveCameras(device=device) +# Initialize a perspective camera. +cameras = FoVPerspectiveCameras(device=device) # To blend the 100 faces we set a few parameters which control the opacity and the sharpness of # edges. Refer to blending.py for more details. @@ -126,8 +134,6 @@ raster_settings = RasterizationSettings( image_size=256, blur_radius=np.log(1. / 1e-4 - 1.) * blend_params.sigma, faces_per_pixel=100, - bin_size = None, # this setting controls whether naive or coarse-to-fine rasterization is used - max_faces_per_bin = None # this setting is for coarse rasterization ) # Create a silhouette mesh renderer by composing a rasterizer and a shader. @@ -145,7 +151,6 @@ raster_settings = RasterizationSettings( image_size=256, blur_radius=0.0, faces_per_pixel=1, - bin_size=0 ) # We can add a point light in front of the object. lights = PointLights(device=device, location=((2.0, 2.0, -2.0),)) @@ -154,7 +159,7 @@ phong_renderer = MeshRenderer( cameras=cameras, raster_settings=raster_settings ), - shader=HardPhongShader(device=device, lights=lights) + shader=HardPhongShader(device=device, cameras=cameras, lights=lights) ) @@ -166,7 +171,7 @@ phong_renderer = MeshRenderer( # # We defined a camera which is positioned on the positive z axis hence sees the spout to the right. -# In[5]: +# In[ ]: # Select the viewpoint using spherical angles @@ -197,7 +202,7 @@ plt.grid(False) # # Here we create a simple model class and initialize a parameter for the camera position. -# In[17]: +# In[ ]: class Model(nn.Module): @@ -234,7 +239,7 @@ class Model(nn.Module): # # Now we can create an instance of the **model** above and set up an **optimizer** for the camera position parameter. -# In[18]: +# In[ ]: # We will save images periodically and compose them into a GIF. @@ -250,7 +255,7 @@ optimizer = torch.optim.Adam(model.parameters(), lr=0.05) # ### Visualize the starting position and the reference position -# In[19]: +# In[ ]: plt.figure(figsize=(10, 10)) @@ -264,17 +269,17 @@ plt.title("Starting position") plt.subplot(1, 2, 2) plt.imshow(model.image_ref.cpu().numpy().squeeze()) plt.grid(False) -plt.title("Reference silhouette") +plt.title("Reference silhouette"); # ## 4. Run the optimization # # We run several iterations of the forward and backward pass and save outputs every 10 iterations. When this has finished take a look at `./teapot_optimization_demo.gif` for a cool gif of the optimization process! -# In[20]: +# In[ ]: -loop = tqdm_notebook(range(200)) +loop = tqdm(range(200)) for i in loop: optimizer.zero_grad() loss, _ = model() diff --git a/files/dataloaders_ShapeNetCore_R2N2.ipynb b/files/dataloaders_ShapeNetCore_R2N2.ipynb new file mode 100644 index 00000000..15c3f9e0 --- /dev/null +++ b/files/dataloaders_ShapeNetCore_R2N2.ipynb @@ -0,0 +1,541 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dataloaders for ShapeNetCore and R2N2\n", + "This tutorial shows how to:\n", + "- Load models from ShapeNetCore and R2N2 using PyTorch3D's data loaders.\n", + "- Pass the loaded datasets to `torch.utils.data.DataLoader`.\n", + "- Render ShapeNetCore models with PyTorch3D's renderer.\n", + "- Render R2N2 models with the same orientations as the original renderings in the dataset.\n", + "- Visualize R2N2 model voxels." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 0. Install and import modules" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If `torch`, `torchvision` and `pytorch3d` are not installed, run the following cell:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install torch torchvision\n", + "import sys\n", + "import torch\n", + "if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):\n", + " !pip install pytorch3d\n", + "else:\n", + " !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import torch\n", + "\n", + "from pytorch3d.datasets import (\n", + " R2N2,\n", + " ShapeNetCore,\n", + " collate_batched_meshes,\n", + " render_cubified_voxels,\n", + ")\n", + "from pytorch3d.renderer import (\n", + " OpenGLPerspectiveCameras,\n", + " PointLights,\n", + " RasterizationSettings,\n", + " TexturesVertex,\n", + " look_at_view_transform,\n", + ")\n", + "\n", + "from pytorch3d.structures import Meshes\n", + "from torch.utils.data import DataLoader\n", + "\n", + "# add path for demo utils functions \n", + "import sys\n", + "import os\n", + "sys.path.append(os.path.abspath(''))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If using **Google Colab**, fetch the utils file for plotting image grids:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py\n", + "from plot_image_grid import image_grid" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "OR if running locally uncomment and run the following cell:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# from utils import image_grid" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Load the datasets" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If you haven't already downloaded the ShapeNetCore dataset, first do that following the instructions here: https://www.shapenet.org/. ShapeNetCore is a subset of the ShapeNet dataset. In PyTorch3D we support both version 1 (57 categories) and version 2 (55 categories).\n", + "\n", + "Then modify `SHAPENET_PATH` below to you local path to the ShapeNetCore dataset folder. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Setup\n", + "if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + " torch.cuda.set_device(device)\n", + "else:\n", + " device = torch.device(\"cpu\")\n", + " \n", + "SHAPENET_PATH = \"\"\n", + "shapenet_dataset = ShapeNetCore(SHAPENET_PATH)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The R2N2 dataset can be downloaded using the instructions here: http://3d-r2n2.stanford.edu/. Look at the links for `ShapeNetRendering` and `ShapeNetVox32`. The R2N2 dataset contains 13 categories that are a subset of the ShapeNetCore v.1\n", + "dataset. The R2N2 dataset also contains its own 24 renderings of each object and voxelized models.\n", + "\n", + "Then modify `R2N2_PATH` and `SPLITS_PATH` below to your local R2N2 dataset folder path and splits file path respectively. Here we will load the `train` split of R2N2 and ask the voxels of each model to be returned." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "R2N2_PATH = \"\"\n", + "SPLITS_PATH = \"None\"\n", + "r2n2_dataset = R2N2(\"train\", SHAPENET_PATH, R2N2_PATH, SPLITS_PATH, return_voxels=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can retrieve a model by indexing into the loaded dataset. For both ShapeNetCore and R2N2, we can examine the category this model belongs to (in the form of a synset id, equivalend to wnid described in ImageNet's API: http://image-net.org/download-API), its model id, and its vertices and faces." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "shapenet_model = shapenet_dataset[6]\n", + "print(\"This model belongs to the category \" + shapenet_model[\"synset_id\"] + \".\")\n", + "print(\"This model has model id \" + shapenet_model[\"model_id\"] + \".\")\n", + "model_verts, model_faces = shapenet_model[\"verts\"], shapenet_model[\"faces\"]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can use its vertices and faces to form a `Meshes` object which is a PyTorch3D datastructure for working with batched meshes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "model_textures = TexturesVertex(verts_features=torch.ones_like(model_verts, device=device)[None])\n", + "shapenet_model_mesh = Meshes(\n", + " verts=[model_verts.to(device)], \n", + " faces=[model_faces.to(device)],\n", + " textures=model_textures\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "With R2N2, we can further examine R2N2's original renderings. For instance, if we would like to see the second and third views of the eleventh objects in the R2N2 dataset, we can do the following:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "r2n2_renderings = r2n2_dataset[10,[1,2]]\n", + "image_grid(r2n2_renderings.numpy(), rows=1, cols=2, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Use the datasets with `torch.utils.data.DataLoader`" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Training deep learning models, usually requires passing in batches of inputs. The `torch.utils.data.DataLoader` from Pytorch helps us do this. PyTorch3D provides a function `collate_batched_meshes` to group the input meshes into a single `Meshes` object which represents the batch. The `Meshes` datastructure can then be used directly by other PyTorch3D ops which might be part of the deep learning model (e.g. `graph_conv`).\n", + "\n", + "For R2N2, if all the models in the batch have the same number of views, the views, rotation matrices, translation matrices, intrinsic matrices and voxels will also be stacked into batched tensors.\n", + "\n", + "**NOTE**: All models in the `val` split of R2N2 have 24 views, but there are 8 models that split their 24 views between `train` and `test` splits, in which case `collate_batched_meshes` will only be able to join the matrices, views and voxels as lists. However, this can be avoided by laoding only one view of each model by setting `return_all_views = False`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "batch_size = 12\n", + "r2n2_single_view = R2N2(\"train\", SHAPENET_PATH, R2N2_PATH, SPLITS_PATH, return_all_views=False, return_voxels=True)\n", + "r2n2_loader = DataLoader(r2n2_single_view, batch_size=batch_size, collate_fn=collate_batched_meshes)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Let's visualize all the views (one for each model) in the batch:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "it = iter(r2n2_loader)\n", + "r2n2_batch = next(it)\n", + "batch_renderings = r2n2_batch[\"images\"] # (N, V, H, W, 3), and in this case V is 1.\n", + "image_grid(batch_renderings.squeeze().numpy(), rows=3, cols=4, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3. Render ShapeNetCore models with PyTorch3D's differntiable renderer" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Both `ShapeNetCore` and `R2N2` dataloaders have customized `render` functions that support rendering models by specifying their model ids, categories or indices using PyTorch3D's differentiable renderer implementation." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Rendering settings.\n", + "R, T = look_at_view_transform(1.0, 1.0, 90)\n", + "cameras = OpenGLPerspectiveCameras(R=R, T=T, device=device)\n", + "raster_settings = RasterizationSettings(image_size=512)\n", + "lights = PointLights(location=torch.tensor([0.0, 1.0, -2.0], device=device)[None],device=device)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "First we will try to render three models by their model ids:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "images_by_model_ids = shapenet_dataset.render(\n", + " model_ids=[\n", + " \"13394ca47c89f91525a3aaf903a41c90\",\n", + " \"14755c2ee8e693aba508f621166382b0\",\n", + " \"156c4207af6d2c8f1fdc97905708b8ea\",\n", + " ],\n", + " device=device,\n", + " cameras=cameras,\n", + " raster_settings=raster_settings,\n", + " lights=lights,\n", + ")\n", + "image_grid(images_by_model_ids.cpu().numpy(), rows=1, cols=3, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Suppose we would like to render the first three models in the dataset, we can render models by their indices:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "images_by_idxs = shapenet_dataset.render(\n", + " idxs=list(range(3)),\n", + " device=device,\n", + " cameras=cameras,\n", + " raster_settings=raster_settings,\n", + " lights=lights,\n", + ")\n", + "image_grid(images_by_idxs.cpu().numpy(), rows=1, cols=3, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Alternatively, if we are not interested in any particular models but would like see random models from some specific categories, we can do that by specifying `categories` and `sample_nums`. For example, if we would like to render 2 models from the category \"faucet\" and 3 models from the category \"chair\", we can do the following:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "images_by_categories = shapenet_dataset.render(\n", + " categories=[\"faucet\", \"chair\"],\n", + " sample_nums=[2, 3],\n", + " device=device,\n", + " cameras=cameras,\n", + " raster_settings=raster_settings,\n", + " lights=lights,\n", + ")\n", + "image_grid(images_by_categories.cpu().numpy(), rows=1, cols=5, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "If we are not interested in any particular categories and just would like to render some random models from the whole dataset, we can set the number of models to be rendered in `sample_nums` and not specify any `categories`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "random_model_images = shapenet_dataset.render(\n", + " sample_nums=[3],\n", + " device=device,\n", + " cameras=cameras,\n", + " raster_settings=raster_settings,\n", + " lights=lights,\n", + ")\n", + "image_grid(random_model_images.cpu().numpy(), rows=1, cols=5, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4. Render R2N2 models with the same orientations as the original renderings in the dataset" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We can render R2N2 models the same way as we rendered ShapeNetCore models above. In addition, we can also render R2N2 models with the same orientations as the original renderings in the dataset. For this we will use R2N2's customized `render` function and a different type of PyTorch3D camera called `BlenderCamera`." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this example, we will render the seventh model with the same orientations as its second and third views. First we will retrieve R2N2's original renderings to compare with the result." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "original_rendering = r2n2_dataset[6,[1,2]][\"images\"]\n", + "image_grid(original_rendering.numpy(), rows=1, cols=2, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we will visualize PyTorch3d's renderings:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "r2n2_oriented_images = r2n2_dataset.render(\n", + " idxs=[6],\n", + " view_idxs=[1,2],\n", + " device=device,\n", + " raster_settings=raster_settings,\n", + " lights=lights,\n", + ")\n", + "image_grid(r2n2_oriented_images.cpu().numpy(), rows=1, cols=2, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 5. Visualize R2N2 models' voxels" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "R2N2 dataloader also returns models' voxels. We can visualize them by utilizing R2N2's `render_vox_to_mesh` function. This will cubify the voxels to a Meshes object, which will then be rendered." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "In this example we will visualize the tenth model in the dataset with the same orientation of its second and third views. First we will retrieve R2N2's original renderings to compare with the result." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "r2n2_model = r2n2_dataset[9,[1,2]]\n", + "original_rendering = r2n2_model[\"images\"]\n", + "image_grid(original_rendering.numpy(), rows=1, cols=2, rgb=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Next, we will pass the voxels to `render_vox_to_mesh`:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "vox_render = render_cubified_voxels(r2n2_model[\"voxels\"], device=device)\n", + "image_grid(vox_render.cpu().numpy(), rows=1, cols=2, rgb=True)" + ] + } + ], + "metadata": { + "anp_metadata": { + "path": "fbsource/fbcode/vision/fair/pytorch3d/docs/tutorials/Dataloaders_ShapeNetCore_R2N2.ipynb" + }, + "bento_stylesheets": { + "bento/extensions/flow/main.css": true, + "bento/extensions/kernel_selector/main.css": true, + "bento/extensions/kernel_ui/main.css": true, + "bento/extensions/new_kernel/main.css": true, + "bento/extensions/system_usage/main.css": true, + "bento/extensions/theme/main.css": true + }, + "disseminate_notebook_info": { + "backup_notebook_id": "669429066983805" + }, + "kernelspec": { + "display_name": "intro_to_cv", + "language": "python", + "name": "bento_kernel_intro_to_cv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.5+" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/files/dataloaders_ShapeNetCore_R2N2.py b/files/dataloaders_ShapeNetCore_R2N2.py new file mode 100644 index 00000000..86e2fa4b --- /dev/null +++ b/files/dataloaders_ShapeNetCore_R2N2.py @@ -0,0 +1,301 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[ ]: + + +# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved. + + +# # Dataloaders for ShapeNetCore and R2N2 +# This tutorial shows how to: +# - Load models from ShapeNetCore and R2N2 using PyTorch3D's data loaders. +# - Pass the loaded datasets to `torch.utils.data.DataLoader`. +# - Render ShapeNetCore models with PyTorch3D's renderer. +# - Render R2N2 models with the same orientations as the original renderings in the dataset. +# - Visualize R2N2 model voxels. + +# ## 0. Install and import modules + +# If `torch`, `torchvision` and `pytorch3d` are not installed, run the following cell: + +# In[ ]: + + +get_ipython().system('pip install torch torchvision') +import sys +import torch +if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'): + get_ipython().system('pip install pytorch3d') +else: + get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") + + +# In[ ]: + + +import numpy as np +import torch + +from pytorch3d.datasets import ( + R2N2, + ShapeNetCore, + collate_batched_meshes, + render_cubified_voxels, +) +from pytorch3d.renderer import ( + OpenGLPerspectiveCameras, + PointLights, + RasterizationSettings, + TexturesVertex, + look_at_view_transform, +) + +from pytorch3d.structures import Meshes +from torch.utils.data import DataLoader + +# add path for demo utils functions +import sys +import os +sys.path.append(os.path.abspath('')) + + +# If using **Google Colab**, fetch the utils file for plotting image grids: + +# In[ ]: + + +get_ipython().system('wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py') +from plot_image_grid import image_grid + + +# OR if running locally uncomment and run the following cell: + +# In[ ]: + + +# from utils import image_grid + + +# ## 1. Load the datasets + +# If you haven't already downloaded the ShapeNetCore dataset, first do that following the instructions here: https://www.shapenet.org/. ShapeNetCore is a subset of the ShapeNet dataset. In PyTorch3D we support both version 1 (57 categories) and version 2 (55 categories). +# +# Then modify `SHAPENET_PATH` below to you local path to the ShapeNetCore dataset folder. + +# In[ ]: + + +# Setup +if torch.cuda.is_available(): + device = torch.device("cuda:0") + torch.cuda.set_device(device) +else: + device = torch.device("cpu") + +SHAPENET_PATH = "" +shapenet_dataset = ShapeNetCore(SHAPENET_PATH) + + +# The R2N2 dataset can be downloaded using the instructions here: http://3d-r2n2.stanford.edu/. Look at the links for `ShapeNetRendering` and `ShapeNetVox32`. The R2N2 dataset contains 13 categories that are a subset of the ShapeNetCore v.1 +# dataset. The R2N2 dataset also contains its own 24 renderings of each object and voxelized models. +# +# Then modify `R2N2_PATH` and `SPLITS_PATH` below to your local R2N2 dataset folder path and splits file path respectively. Here we will load the `train` split of R2N2 and ask the voxels of each model to be returned. + +# In[ ]: + + +R2N2_PATH = "" +SPLITS_PATH = "None" +r2n2_dataset = R2N2("train", SHAPENET_PATH, R2N2_PATH, SPLITS_PATH, return_voxels=True) + + +# We can retrieve a model by indexing into the loaded dataset. For both ShapeNetCore and R2N2, we can examine the category this model belongs to (in the form of a synset id, equivalend to wnid described in ImageNet's API: http://image-net.org/download-API), its model id, and its vertices and faces. + +# In[ ]: + + +shapenet_model = shapenet_dataset[6] +print("This model belongs to the category " + shapenet_model["synset_id"] + ".") +print("This model has model id " + shapenet_model["model_id"] + ".") +model_verts, model_faces = shapenet_model["verts"], shapenet_model["faces"] + + +# We can use its vertices and faces to form a `Meshes` object which is a PyTorch3D datastructure for working with batched meshes. + +# In[ ]: + + +model_textures = TexturesVertex(verts_features=torch.ones_like(model_verts, device=device)[None]) +shapenet_model_mesh = Meshes( + verts=[model_verts.to(device)], + faces=[model_faces.to(device)], + textures=model_textures +) + + +# With R2N2, we can further examine R2N2's original renderings. For instance, if we would like to see the second and third views of the eleventh objects in the R2N2 dataset, we can do the following: + +# In[ ]: + + +r2n2_renderings = r2n2_dataset[10,[1,2]] +image_grid(r2n2_renderings.numpy(), rows=1, cols=2, rgb=True) + + +# ## 2. Use the datasets with `torch.utils.data.DataLoader` + +# Training deep learning models, usually requires passing in batches of inputs. The `torch.utils.data.DataLoader` from Pytorch helps us do this. PyTorch3D provides a function `collate_batched_meshes` to group the input meshes into a single `Meshes` object which represents the batch. The `Meshes` datastructure can then be used directly by other PyTorch3D ops which might be part of the deep learning model (e.g. `graph_conv`). +# +# For R2N2, if all the models in the batch have the same number of views, the views, rotation matrices, translation matrices, intrinsic matrices and voxels will also be stacked into batched tensors. +# +# **NOTE**: All models in the `val` split of R2N2 have 24 views, but there are 8 models that split their 24 views between `train` and `test` splits, in which case `collate_batched_meshes` will only be able to join the matrices, views and voxels as lists. However, this can be avoided by laoding only one view of each model by setting `return_all_views = False`. + +# In[ ]: + + +batch_size = 12 +r2n2_single_view = R2N2("train", SHAPENET_PATH, R2N2_PATH, SPLITS_PATH, return_all_views=False, return_voxels=True) +r2n2_loader = DataLoader(r2n2_single_view, batch_size=batch_size, collate_fn=collate_batched_meshes) + + +# Let's visualize all the views (one for each model) in the batch: + +# In[ ]: + + +it = iter(r2n2_loader) +r2n2_batch = next(it) +batch_renderings = r2n2_batch["images"] # (N, V, H, W, 3), and in this case V is 1. +image_grid(batch_renderings.squeeze().numpy(), rows=3, cols=4, rgb=True) + + +# ## 3. Render ShapeNetCore models with PyTorch3D's differntiable renderer + +# Both `ShapeNetCore` and `R2N2` dataloaders have customized `render` functions that support rendering models by specifying their model ids, categories or indices using PyTorch3D's differentiable renderer implementation. + +# In[ ]: + + +# Rendering settings. +R, T = look_at_view_transform(1.0, 1.0, 90) +cameras = OpenGLPerspectiveCameras(R=R, T=T, device=device) +raster_settings = RasterizationSettings(image_size=512) +lights = PointLights(location=torch.tensor([0.0, 1.0, -2.0], device=device)[None],device=device) + + +# First we will try to render three models by their model ids: + +# In[ ]: + + +images_by_model_ids = shapenet_dataset.render( + model_ids=[ + "13394ca47c89f91525a3aaf903a41c90", + "14755c2ee8e693aba508f621166382b0", + "156c4207af6d2c8f1fdc97905708b8ea", + ], + device=device, + cameras=cameras, + raster_settings=raster_settings, + lights=lights, +) +image_grid(images_by_model_ids.cpu().numpy(), rows=1, cols=3, rgb=True) + + +# Suppose we would like to render the first three models in the dataset, we can render models by their indices: + +# In[ ]: + + +images_by_idxs = shapenet_dataset.render( + idxs=list(range(3)), + device=device, + cameras=cameras, + raster_settings=raster_settings, + lights=lights, +) +image_grid(images_by_idxs.cpu().numpy(), rows=1, cols=3, rgb=True) + + +# Alternatively, if we are not interested in any particular models but would like see random models from some specific categories, we can do that by specifying `categories` and `sample_nums`. For example, if we would like to render 2 models from the category "faucet" and 3 models from the category "chair", we can do the following: + +# In[ ]: + + +images_by_categories = shapenet_dataset.render( + categories=["faucet", "chair"], + sample_nums=[2, 3], + device=device, + cameras=cameras, + raster_settings=raster_settings, + lights=lights, +) +image_grid(images_by_categories.cpu().numpy(), rows=1, cols=5, rgb=True) + + +# If we are not interested in any particular categories and just would like to render some random models from the whole dataset, we can set the number of models to be rendered in `sample_nums` and not specify any `categories`: + +# In[ ]: + + +random_model_images = shapenet_dataset.render( + sample_nums=[3], + device=device, + cameras=cameras, + raster_settings=raster_settings, + lights=lights, +) +image_grid(random_model_images.cpu().numpy(), rows=1, cols=5, rgb=True) + + +# ## 4. Render R2N2 models with the same orientations as the original renderings in the dataset + +# We can render R2N2 models the same way as we rendered ShapeNetCore models above. In addition, we can also render R2N2 models with the same orientations as the original renderings in the dataset. For this we will use R2N2's customized `render` function and a different type of PyTorch3D camera called `BlenderCamera`. + +# In this example, we will render the seventh model with the same orientations as its second and third views. First we will retrieve R2N2's original renderings to compare with the result. + +# In[ ]: + + +original_rendering = r2n2_dataset[6,[1,2]]["images"] +image_grid(original_rendering.numpy(), rows=1, cols=2, rgb=True) + + +# Next, we will visualize PyTorch3d's renderings: + +# In[ ]: + + +r2n2_oriented_images = r2n2_dataset.render( + idxs=[6], + view_idxs=[1,2], + device=device, + raster_settings=raster_settings, + lights=lights, +) +image_grid(r2n2_oriented_images.cpu().numpy(), rows=1, cols=2, rgb=True) + + +# ## 5. Visualize R2N2 models' voxels + +# R2N2 dataloader also returns models' voxels. We can visualize them by utilizing R2N2's `render_vox_to_mesh` function. This will cubify the voxels to a Meshes object, which will then be rendered. + +# In this example we will visualize the tenth model in the dataset with the same orientation of its second and third views. First we will retrieve R2N2's original renderings to compare with the result. + +# In[ ]: + + +r2n2_model = r2n2_dataset[9,[1,2]] +original_rendering = r2n2_model["images"] +image_grid(original_rendering.numpy(), rows=1, cols=2, rgb=True) + + +# Next, we will pass the voxels to `render_vox_to_mesh`: + +# In[ ]: + + +vox_render = render_cubified_voxels(r2n2_model["voxels"], device=device) +image_grid(vox_render.cpu().numpy(), rows=1, cols=2, rgb=True) + diff --git a/files/deform_source_mesh_to_target_mesh.ipynb b/files/deform_source_mesh_to_target_mesh.ipynb index 4235ba68..f6a83206 100644 --- a/files/deform_source_mesh_to_target_mesh.ipynb +++ b/files/deform_source_mesh_to_target_mesh.ipynb @@ -2,11 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "nF07sDgJWHQy" }, "outputs": [], @@ -28,7 +27,6 @@ "cell_type": "markdown", "metadata": { "colab_type": "text", - "collapsed": true, "id": "HfwwW9HqtuvQ" }, "source": [ @@ -75,26 +73,29 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "_qkuyhyTeRyM" }, "outputs": [], "source": [ "!pip install torch torchvision\n", - "!pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" + "import sys\n", + "import torch\n", + "if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):\n", + " !pip install pytorch3d\n", + "else:\n", + " !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" ] }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "ylbZGXYBtuvB" }, "outputs": [], @@ -112,7 +113,7 @@ " mesh_normal_consistency,\n", ")\n", "import numpy as np\n", - "from tqdm import tqdm_notebook\n", + "from tqdm.notebook import tqdm\n", "%matplotlib notebook \n", "from mpl_toolkits.mplot3d import Axes3D\n", "import matplotlib.pyplot as plt\n", @@ -121,7 +122,11 @@ "mpl.rcParams['figure.dpi'] = 80\n", "\n", "# Set the device\n", - "device = torch.device(\"cuda:0\")" + "if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + "else:\n", + " device = torch.device(\"cpu\")\n", + " print(\"WARNING: CPU only, this will be slow!\")" ] }, { @@ -143,14 +148,13 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 204 }, "colab_type": "code", - "collapsed": true, "id": "oFNkB6nQWZSw", "outputId": "c1bbe6e2-a4ea-4113-d53d-1cb1ece130f1" }, @@ -161,11 +165,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "dz0imH-ltuvS" }, "outputs": [], @@ -176,11 +179,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "rbyRhI8ituvW" }, "outputs": [], @@ -208,11 +210,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "6BxDTpB2WHRH" }, "outputs": [], @@ -233,11 +234,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "482YycLHWHRL" }, "outputs": [], @@ -259,7 +259,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -269,32 +269,7 @@ "id": "UoGcflJ_WHRO", "outputId": "b9a2d699-2c68-4696-9dff-d30eea7a0fb0" }, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nCHYAMAzBDgCGIdgBwDD/AU8iaGS1VVyZAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n7ADFCDtAMT8BTQ7lWnNuNtwAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# %matplotlib notebook\n", "plot_pointcloud(trg_mesh, \"Target mesh\")\n", @@ -313,11 +288,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "Sc-3M17Ltuvh" }, "outputs": [], @@ -329,11 +303,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "0BtSUfMYtuvl" }, "outputs": [], @@ -344,7 +317,7 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -362,130 +335,9 @@ }, "colab_type": "code", "id": "9DAjqI9Atuvp", - "outputId": "d59e959b-8616-40fe-aec4-5b09b27e325f", - "scrolled": false + "outputId": "d59e959b-8616-40fe-aec4-5b09b27e325f" }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "12fdcbc799cc4da899d889d0399616c2", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(IntProgress(value=0, max=2000), HTML(value='')))" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngMAo4/8HJ+YS78xGjdYAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAFDmDz7fp3UtihBAAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0\ndHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nOy9eXwkV3nv/a3q6lXdrW5Jo2WkGc3G\nGMYer2MbYy4xGBsw4ARizGZss9w4LyQv+OUmOIRAQl7nOrmEJDeE68u1sQdsYxNMMGGxsQ02EC/j\niWdsz4xnl0bSjHapJfVeXVX3j1aV1Vp7VVe3zvfz0YxUXX3qVHf1r57+nec8RzIMA4FAIBDUD3K1\nOyAQCASC8iKEXSAQCOoMIewCgUBQZwhhFwgEgjpDCLtAIBDUGULYBQKBoM5QVnhc5EIKBAKBPZGW\nekBE7AKBQFBnCGEXCASCOkMIu0AgENQZQtgFAoGgzhDCLhAIBHWGEHaBQCCoM4SwCwQCQZ0hhF0g\nEAjqDCHsAoFAUGcIYRcIBII6Qwi7QCAQ1BlC2AUCgaDOEMIusA1nn302Tz31VLW7IRDUPELYBbbh\n4MGDXHHFFQD85V/+JTfccENFj/eHf/iH+P1+68ftdhMIBKzHr7jiCjwej/X4WWedlfP8Bx54gO7u\nbhoaGvi93/s9JiYmKtpfgSBfhLAL6pJMJrPiPnfeeSfRaNT6+fCHP8wHPvCBnH2+8Y1vWI8fOXLE\n2n7w4EFuueUWvvvd7zI8PIzP5+PTn/502c9DICgGIewC27Bp0yaeeOIJHn30Uf7mb/6Ghx56CL/f\nz3nnnQfA1NQUn/zkJ+no6KCzs5MvfelLaJoGwL333svll1/OrbfeSnNzM3/5l39Z0LFjsRgPP/ww\nN910U17733///bz3ve/lLW95C36/n7/+67/mhz/8ITMzMwUdVyCoBELYBbbjne98J1/84hf54Ac/\nSDQa5aWXXgLg5ptvRlEUjh8/zr59+/jFL37BXXfdZT3v+eefZ8uWLQwPD/Pnf/7n9PX1EQqF6Ovr\nW/GYDz/8MOvWreMtb3lLzvY/+7M/o6WlhcsvvzzH/z948KB1wwHYunUrLpeLo0ePlnj2AkHprLSC\nkkBgC4aHh/nZz35GJBLB6/XS0NDArbfeyre+9S1uueUWANavX88f//EfA6AoChs3biQSieTV/u7d\nu7nxxhuRpNcWpfnbv/1bduzYgcvl4sEHH+S9730v+/fvZ+vWrUSjURobG3PaaGxsFBG7wBaIiF1Q\nE5w6dQpVVeno6CAUChEKhbjlllsYGRmx9tmwYUNRbff19fHUU09x44035my/9NJLCQQCuN1ubrrp\nJi6//HJ+9rOfAeD3+5mens7Zf3p6OmfwVSCoFiJiF9iSuZEzZEXb7XYzNjaGoix+2c5/Tr5897vf\n5fLLL2fLli0r9skwsssAn3322ZZFBHDy5ElSqRTbt28vqg8CQTkREbvAlrS1tdHb24uu6wB0dHRw\n9dVX8/nPf57p6Wl0XefEiRM8/fTTJR/rO9/5DjfffHPOtkgkwmOPPUYymSSTyXD//ffz61//mne+\n850AfPSjH+Xf//3f+c1vfkMsFuPLX/4y73//+0XELrAFQtgFtsRMO2xububCCy8EsgKcTqfZsWMH\n4XCY6667jsHBwSXb6Ovrw+/3Lzt4+uyzzzIwMLAgzVFVVb70pS+xbt06Wlpa+Od//md+9KMfWRH5\n2WefzZ133slHP/pRWltbmZmZ4Zvf/Gappy0QlAXJ/Gq5BMs+KBAIBIKqsaT3KCJ2gUAgqDOEsAsE\nAkGdIYRdIBAI6gwh7AKBQFBnCGEXCASCOkMIu0AgENQZQtgFAoGgzhDCLhAIBHWGEHaBQCCoM4Sw\nCwQCQZ0hhF0gEAjqDCHsAoFAUGcIYRcIBII6Qwi7QCAQ1BlC2AUCgaDOEMIuEAgEdYYQdoFAIKgz\nhLALBAJBnSGEXSAQCOoMIewCgUBQZwhhFwgEgjpDCLtAIBDUGULYBQKBoM4Qwi4QCAR1hhB2gUAg\nqDOEsAsEAkGdIYRdIBAI6gwh7AKBQFBnCGEXCASCOkMIu0AgENQZQtgFAoGgzhDCLhAIBHWGEHaB\nQCCoM5Rqd0AgWIsYhpHzu/njcDiQJKmKPRPUA0LYBYIimS/O8/9f6vf5zwXIZDKk02kcDgeyLKMo\nCoqiIMuyEHtBwQhhF6xpShXnvr4+1q9fj6IoSJK0QLBN5guzJEmLbpNlGcMwSKfTpNNp6zFT4BVF\nscRfloWTKlgcIeyCmqcQcY7FYjidThRFWfDclVhMiEdHR1m/fr0lsqVG1osJvtlHVVVJp9Pous7p\n06fp7u62hN78Wez5grWHEHaBLVhOnAF0Xbe2rWRrLEdfXx8tLS00NzcDiwup3TD753A4gKxtMzk5\nyaZNmywLx9xHkqRFI3u7n6OgvAhhF5SNfMXZ3L6YSM/n2LFjtLW1EQwGrW352BpLMVcAaxXztTLP\ne64lYxgGmqaRyWRynjNX7E3Br+XXQLA8QtgFOZQqzqdOnaK7u3vF4+QrzpqmAQg/eR5LifJSVo6u\n66RSKQzDyPkGYAq+GKStL4Sw1yH5inM6ncYwDJxOZ1G2xmLiPDg4yObNm4vu+1qlkNe9UJYTe03T\n2Lt3Lzt37rSi//mRvbip1h5C2G1KJWyN+Zw5cwbDMNi4caO1zY6ecyVFz06s5nnOfZ8zmYzl3wM5\n2TjmvmKQtrYQwl5ByinO8XicM2fOsG3btgXHKdZzlmUZXdfFB9Qm5Ps+zLVTKnHsuSJvXodikLa2\nEMK+AouJ89zfFxPnVCpFLBYjFArlfZx8xDmRSJT9a/FaiYYFxTFXyPMdpDUMA6/XK8S+iqwZYV8s\nEl5OnEvxnFOpFAMDA4TD4bJd1MtNfhFUl7UoXMv59nv37uXCCy8Ug7RVpG6FXdd1yytcThBPnTqF\ny+Wio6MDKC2VzqRck1UqjbhZlE41Xr9KWDHlwPysmJ485A7Szp9JKwZpK0fdCvtclhNnc7vdLY61\nKsJ2FDBB/iw3k1YM0laOuhX2Qi6ItSrCtdJPQX0xfyYtLD9Ia+7rdruFb58ndSvs+VKJC6RSbQoR\nFtQryw3SDg8Pk0gkctJyTc/e9O2F2OcihL1CglmJbwFrFXFDy8WuHnslmFs2wYzw586kTSaTiw7S\nrvWyCXUr7IXUDqkVEV6rlpFgbTP/RrbSTFoxSFvHwp4vkiTlpDuWq81auVkIBHYnn8/SUmJv1raf\niynusizjcrmsyL6ePmNC2GvEiqlEmyJiLw8rCYJhGKiqmvOTTqdz/k4mkzgcDkKhEMFgEJ/Pt2S7\na/E9K0Z0l8vISSaTHDx4kPPOO8/ad34FzFoWeyHsFYqua6FNQWEYhkEmk8kR51QqRX9/P5qmLRBt\nM2KUJAmn07noj8/nw+l0Wp5xPB6np6eHeDyOoigEg0GCwSCBQACPx1MXZYcLpZxjCnNfP1PMzWMs\nNZPW6XTWXNmENS/slaAW3vhaoRI3tMUEerloWtM06z1VFCVHmHVdR5ZlS6DNH/Mrfr4kk0k8Hg8t\nLS3WtnQ6zczMDNPT0wwODlr7eL1eUqkU6XQal8tV1tdmLZGvb59MJnO2OxwOdu/ezR/90R+tSj+L\nYc0Le61YMSKFcnEWi5SXE+hkMsnw8DBut3uBEDudThoaGgiFQtbfZrS2FJFIhM7OTmumZTlxuVw0\nNzdbqz2ZdYjGxsYYHx/n4MGDqKqKz+cjEAhYkX0l+lJNKpEFlE+by4n9PffcI4TdztSSbVLrIrwc\nuq4vKsZTU1Mkk0kGBwetbXO/LsuyvKhAe71egsHgAoE+evQozc3NOZFxrSBJEh6Ph6amJiYnJ9m5\ncyeGYRCPx5menmZ0dJSTJ0+i6zoNDQ2WjeP3+2s6E6Rawr4YteK717Ww5yOwtSLstdKmGVWuNFho\n/szty1xhnivGwWCQ5uZma5uiKDXx4aokc73ihoYGGhoarHpHuq4TjUaZmZnh9OnTRKNRJEmyovqV\nBmftiF2EvVaoa2HPh3qwIyrBYpkcS9kdmUzGeg1jsRgvv/zyAoF2u934/f4Fg4crfbgSiQSNjY00\nNjauxmnXBbIsWwLe2dkJZKfqR6NRpqenFwzOqqpKIpHIGZwtlkp9U62EsNcza17YK4Gdouv5A4Vz\nxTkSiRCPx0kkEtb2ucdYLIvD5XLlDBS6XC5rWjfAM888w65du8qexSB4jWKuA0VRCIVCOWsEmIOz\nQ0NDHD161BqcnRvZ1/PgbCnXlt1vDGte2O0kwithGIYlwisNFs6ddDU/k8OMpn0+HwCbN28uKpNj\nMcxzF4JcWcrx+pqDs263m/POO8+y0aanp4lEIvT39xc8OGsnP7xSbdpd1EEIe1VmiS6XyTF/m6Zp\nANYg2auvvrpoJsd8f3q5TA6T0dFRDMMgEAiU5bzLgaYb9I7HAfA5ZZ7rj7NVi/GmcBOyLG4WlcQc\nnPV4PLS2tgKvXXfVHJy1m72j63pen69qIoS9BGE3Mznmi3E6nSaRSHDgwIGyZHKYfXzuuee48MIL\ny3XqthtfSKQ1vvBvBzk8NEM0qTIeN1+zceAoADKgOCS6Qm7O3xDinPWNXLOzjbCvepbBanw76Z9M\nsKd3kiPDMRLpNB1Kgq3bM6QyBh5FZiSaZiaZoTPkodHrLNtxlxqcjcViTE9PLxic9fv96Lpe9ijb\nTh67pmlC2O2OWSsmnU6vGD3nm8nh8XhQFIUNGzaUNZPDTiJcbgzD4LYfHeRXR0ZxyBIJdfH6PTqQ\n1gxOjic5OT7ED/cP8d8fPcod79vBe87tWN1OV4Ch6RS/OTbOvoEI00mN0Wiavskk0ZSWs58E3P/q\nc7yhzc/wTBrDgAa3gqbrvG17C+/Z2cbGJm9F+ijLMoFAgEAgsGBwNhKJkEqleOGFF5adOVsIlbL2\nim1T0zTbzxWwd+9KZGJigkQisWSqnTmwmMlkiMViCwTa5XJZNkchmRwAvb29Zc3kqJUJSsW2+ZNX\nhvj1sfFs0aZMYc9XdYO/+PEhEqrO0ZEoLX4X11/UuSpRfCmvn2EYDEzE+fK/H+a5nkkKKUVnANNJ\nnX0D06gayFJW7A3g5FgfPzk4zI62BhSHgzdtCfHGzU20BtxF93UlzMFZv9/PxMQEF154Yc7M2aGh\nISvzptDBWbt57JlMRkTs1WRmZgZN03JqcszP5JicnGRwcJAdO3ZUu7trmicPj+JRZFRNB71wsYyr\nBl97/Bh+t4KqGdz3XD8bmrx0hTxcc047l2wO43PZ43KPxNM89EIfP9w/RO9EcuUnLEN6NpDXZl8y\nCcCA/skU/ZMpAH56cBRFhrNa/fzJ2zdzwcYQ8irYR0vNnJ0/OGtakKs5c7YUYRdWTJXp7u6uygSl\nWsIO5z44lSSW1nA7ZTRdZkrTVn7SIkQSGWaSGQyy94aRaJr/7JvikZeHkYEP7lrPBk+KtzY0sprz\nTlOqxnM9k5yOJHjghX6Oj8Sp1KtuAIu9ehkdDg5Fufm+V/idbWG+9vtn41HKP+C5nGAWOzir67rt\nrBgh7DZnLQu7Heydx18d4e8eO0pC1RmPpnGUqjUSLFZeXwe+t/cMMvDtfVM8fEsI3YDHDg2TUDXe\ndXYbm1saSjx4FsMweProGM/2TBBJqPzy8CjxtEamvGX/i+bp45O87R+f4YrtLdx29baq9iWfwdnx\n8XFGR0cZHx+3ovqGhoaq5aELj70GWMvCXm2iqQx/99hRphIZ4qoGEiwxZkqjx0E0pVmWw1JoK4in\nJMF4LMP1d+0hoxlMJbKZN//yVA9X71jHOR1BZlIaLQEnLlni2ZOThHxOLtvcxMWbwwxOJnn88Ahh\nn5NtrQF6Ixqn95/h4f3DSMDNl23kp68M8vNDo4W/IKvITErnV0fGSaQ1PtJdvnbL4YfPH5w9ceIE\ngUAAl8vF9PQ0vb29K5Y1rmQ/RcReZapVK6ZWqPa5T8ZVkqpOLK2hG8ay1vpUsjh7Zj7mjWF4Or3g\nsZ8dGOFnB0YWfd4DL5zGp0A8t1w3AQVi2hFcDgnDgD9+6OWK2SzlRtU0nj42QWNGYuf5Gh5necSq\nEgOdi82cVVWV6enpogZnhbALBBWi1e/CADJFDJZWg/miDjAzuy1ZYCaPHchmUBr8uMfg4L37+Nr7\n38D6kBdnCX7YagYKTqdzycHZqampZQdnRR57nVPtqLXeKOT1dDsdrA95GI0ujJ4Fq0dGh8MjcT70\n7X20+F38/ft3sL3NX3R71UpNzHdw1syUkySJ6enpgmfOZjIZ4bHbnbUs7HY497FYZURdBisv3Mzv\nFixk7msTTetEJ5J86J59PPbpi1kX9BTcnt3WIVhqcHZgYIDJyclFyxqvNDgrSgrUAHYQt7WMd5mU\nO1kqKqUdyIq6KVri3V2axV4bVTP48L37+MUfXVpwDRi7zRJdDFmW8Xq9aJrG5s2bgay9Yk6mmj84\nawq+OTgrrJgaYC0Lux1mnl53YSd3PHZs0ceCboXpZKagGZlzKdeZKcAi9npdMzyj8j+f6uVzb9tS\n7a6sSj12h8Ox7ODs8PAwiUSCTCbD/fffz/j4OCMjI5blYzdqd72sMrGWhd0O3HDpBvzuxaMfQ6L0\nvPY8cKygGWtN1E3ueXaAH7x4ptrdACo352I5zMHZzZs3c+6553LJJZewY8cOtm7dyvDwMB/+8If5\n1re+VfZ+lYM1L+xrGTvUTJ9JZkgtMnPH5ZCQWDkvvRyI+/ri6MBf/fw4B85M5f2cWlntqJh+SpJE\nOBzmrW99K7t27eLJJ5/kD/7gDwpqY2JigquuuorXve51XHXVVUxOTi657/T0NF1dXUUtmr3mhX2t\nR+zVPvdfHh5d9CJUZNB1Y7b4SWWxyYTQsqJI5XvpPnLPSwxMJsrUWuHYrQhYKR77HXfcwZVXXsmx\nY8e48sorueOOO5bc9y/+4i94y1veUtRxhLCvYWG3Q0kBVdPxOB0LLkSn4uAN64Pl7dwaQi6jjWUA\ntzzwcn771sjqWaUKe7Hpjo888gg33XQTADfddBM/+tGPFt3vP//zPxkeHubqq68u6jhC2NewsEP1\nI/bLtzUT8jkJehWccvaCbA+4uemNG/nfHzmfJq+9sw/siIOsGOt6NmqXZretJGPLPd4XSTEVT5Wp\nh4Vht5uFpmlFrxg1PDxspV22t7czPDy8YB9d1/n85z/P1772taL7KLJi1riwV5uNTT7+5wfP5X//\nppeZZIa3ndXCh3Z1IcsSe3omGI+/VkpAAmRZQquRmarVwgBe3+4nmlIZmk6TUI1FKz6a6aCmRK1k\nSV131z4e++NLly35azfbpBJtrhSxv/3tb2doaGjB9ttvvz3nb0mSFu3DN7/5Ta655hq6urqK6h8I\nYV/T2CHdEeD17QH+4QM7c7a9cnp6Qd0Vg+yaqG5FIlWDU/hXCx04PhonperLirXBbCQvQT4v59BM\nmud7I1y2OVyejlaRSnrsTzzxxJKPtbW1MTg4SEdHB4ODg4umSz777LP85je/4Zvf/CbRaJR0Oo3f\n71/Wj59PXQt7vtOQRcReXSJxlZ7xGF6nA8MwcCkOHn7xNPH04oW/NM0oafLSWmCppQXnY8CKFTPn\n8r09/csKu92i60q0WUpJgWuvvZbdu3dz2223sXv3bn73d393wT7333+/9fu9997L3r17CxJ1qHNh\nz4e1LuzVPvdXB2f4kx8eIKlqDE4lMYzsYtVBj3PJASDNELNJy0WhGUF7+6dt53kXSzWyYm677Tau\nv/567r77brq7u/n+978PwN69e7nzzju56667imp3PkLYKyjsdv8ArFbfzLVlzQXDzTVo0+k0t/10\ngMlYhsmkbkWOesZgLJpecuKQEPXimFs/p1hmUjr/+uIZrr+oc9HH7RZdV6LNUmrFNDc38+STTy7Y\nvmvXrkVF/eabb+bmm28u+DhC2CskbuYNw87CXiy6rueI9FyhjkajHDhwAF3XyWRem7M5d71Z88ft\n8TCW0JlK6QvtAAkcDomM8NJLRiab+tjmkxmIlp61f/8LSws7VK+642q1KVZQEtgaSZLQdd0S5bkC\nvZhom99sJEnKEWiXy4XT6aSxsZGJiQm2bNli1b1e6cMT9PYyHsudtG8AkiE89HKgSNnBUd0Af4OH\nLkXjzFRq3mtrUMh0ppGZpdMeq23t5Usp/cxkMqII2FqlWt69GU0vJ9DpdJpMJoOu6ySTSfbt25cj\n0C6XC6/XS2NjY862fHJ3BwYG8Hq9OJ3OvPr7zh1t3PmbngXT+p0OCalGRMKOKHK2znpWriUUh8Sx\nkXj2wQUva2GRazSt89sTE7x5a9Oij9spuq5Em6K64xqmHMJuetOmIKuqysDAwKKiPT+anm97NDY2\n5mxTFIVEIsGRI0e44IILynHK1vELOe/3XdDBPc+eysniUGS4aEMje05FytavtYYp6hkD/G6ZRFrH\nIUuomrHiGEU+9eu/9vhx3rz1kgXb7VLXJR+EsAsKZrGLZr7tsVRkPdebVhTFEmpN09A0zVrXca5w\nFzMTzg4ZQRubfKwLuOmfyNYikciK0nO9kSXFZTHhkWc31mPdl2JxSNnXI5rUyF6OUl4Dz/ns0z+Z\n5OVDh2lrDtPY2IjHk12Uo1bGlaqV7rha2Lt3NsYwDDRNW3YQcf/+/ZblAUtH0/NFeilvempqio0b\nN9bEB6cQXA4Zr0smnTGs9U9N19cUGVnKVmF0SCDNzj41fWKZ8vnxXkUmMVtt0iEVluNtN5oanKQ1\ng6lEBt0AvYw38aBHwekPE4/HGRwcJJ1O09DQgNPpRFXVsgq83awYsYJSDZHvIKKqqtZzHA7HggFE\nt9tNIBBgYmKC7du309DQULaLoNwXtx0idoD2oJuJaJJEeul4W5LAMyu6kmbkROblitIVOVsS0eWY\nvYnIEloNZ+W4FQdOh06kAoUZ3S4H7S1NhH1tQFYoY7EYZ86cYWZmhhdeeMGyABsbGwkGg0VHuXYr\nBSyyYqqMGTkvN4io6zrRaJTnn3/eiqTnRtRmND33sXwust7eXjweT9nv7Hb/qlvIzWJkJsVf/eRV\nXjg1uWiJALOOScAt0RzwMDydwqjQ5CQJ2NjkxemQiSZVEqpONJUpS+53tRiLJlG1yqz5Gomr/HDf\nGT55eTeQfd/9fj8tLS3Issy2bdtIpVJMTU0xNjbGyZMnAQgGgzQ2NhIKhXC73WXuVWGU4rGb1pNd\nqWthn5ycZGho6LW86dloeq5wOxwOnnnmGS677LKyH98O0fByVPMGYRgGX/zRIQ4PzaAu43fogI7E\n6UgKl0OqiNAG3A5U3UCZrXMryxKyJPHRSzfw22PjHB+N1eSkqO3r/Lw6EiWzeGWGopGAlKrzr/uH\nLGE3mRt4uN1uWltbrXoomUyG6elppqamcuwbU+iXWkDablaM8NirTHt7Oy0tLVU5tl0KbK1EtW4+\n08kMPeMxXIq0oj8+k9JxyjBToTXqVM0g4FFIqhqylP27PegmnsoQiadrUtQBJhJqXqtDFXqzNMhm\n20xE0wX1R1EUmpqaaGrKpkma9k0kEuHUqVPEYrEc+6axsbFiXrZIdxQUhZ3Ss1arPZN8bhYjMykG\np1J5l+DNs6ZVUWi6ToPLgQHEUhrbWxvY1Ozl0UOjTMXVFZ9vV/ojKWslpYrYV4tcPoUIpmnf+P1+\nq0RtKpUiEonk2DfJZJLR0VHC4XDV7RsQg6drmkoNTNo9Ys/3Q/3J7+wra5ZGvsyPTmXApTjon0wg\nSxIhr4KqGRwdiTOTVGt+9utiY7/zK2MWe89s8uU3Ca0Q3G43bW1ttLVlB2UzmQwvvPAC8XicoaGh\nvO2blRBWjKBoqiWadmc6oTIaTa3qItIS2fRFU+jMV9Lnksno2Vo1mmEwEVeJnZnGpcioWn0WHMtJ\nEy2hnQs2LFy6sNx+uKIoKIrC5s2brWApGo0yNTW1wL4JhUIEg8G8omlhxQiKopo2R75UK90xldGq\nEgnPHaNVHKBq2enxc5EkCVXXiSdqNRdmZUxrppS3wOOQuOGS4lf4KRTz8yRJEoFAgEAgYNk3yWSS\nqakpRkdHOXHiBECOT7+YfSPy2AVFUwuDp+Umnz6emUrhlCvrm+f0iYUipi6RKZKpde8lD1r8Tkaj\natHCLklwyaYQOzoWX2x8tb9ZejwePB5Pjn1jZt+cPn0aVVVpaGggFArR2NhIQ0NDyXnsQtjXKPUi\nwpUg5HXidMio+uoou73fhdUnmsyUNKt2S7OHK7Yvnm1mh2t+fvaNruvEYjGmpqbo7e0lHo+jqiqy\nLKNpWt72jYnw2NcwtZLuWA0eOzgsxLaKJEqcTRvyubj6DdVJIy4GWZYX2DevvPIKHo+HkZGRvO0b\nE2HF1BB2n9EJ9TF4eiaS5PsvnqEr5KFnPE6mfq1sW1NsCqRDgs9esYlG7+IZMbXwOYKs2Le0tNDQ\n0AC8Zt9EIhHLvvH7/ZbQz82+EVZMjVCJ1Y5qId2xGt8qphIq0uwkoPUhL0NTCZZYs3pVqVSut10p\n5lwl4A/fvJELNoSWbrdGhH3+NbqUfROJROjt7SUWi+HxeBgaGmJ8fDynAqsdEcJeISolmrXOWDRF\n38RrValW+4zMFD9FlnIGSteSqBeD2wE//sOLWR/yVrsrZWO5z9Nc+2bDhg0YhkEymWRoaIjjx49z\n66238td//dc88sgjVZvdvhyFF/GuQ2pJhO0esa/E5x8+kPP3aguq6fysheyXcvLV95yVl6jXUsRe\nSD8lScLr9fKOd7yDnTt3cvfdd/Pzn//civDzZWJigquuuorXve51XHXVVUxOTi7YZ//+/Vx22WWc\nffbZnHvuuTz00EMFHQPqXNgLmdpsd9sEamPwdLk+ziQzTCXK+xXWo0g45WxxMOe8q1kug77YX6Iq\niwz8xTu3cs05bdXuSlkpxwSlYDBY8AI3d9xxB1deeSXHjh3jyiuv5I477liwj8/n4zvf+Q4HDx7k\n0Ucf5XOf+xyRSGGriQkrBpHBslr82/7TZW9zQ9hDyOsm7HPy4sAUiiwRTWXQdAOXDFOp0kZn15r3\nPpe3vS7Mn79rO62B/Ouz1ErEDsV/qy4l3fGRRx7hqaeeAuCmm27iiiuu4G//9m9z9tm+fbv1+/r1\n62ltbWV0dJRQaOmxjfnUdQwJE9IAACAASURBVMSeL7VixZS7n6t580lndO55pr+sEbAEOGQHm1u8\nJDM6AbfCdCJD2Ovkv765m2QZBmXXatLOOr+T//etWwoS9VqilOu+lHTH4eFhOjo6gGz12eHh4WX3\n37NnD+l0mq1btxZ0HBGxVxARsb/GdFJFlsDtlEmrelkE0wAOD0c5PBzF65QIepyc3dGAIsGeE2P4\nFEjZO3nBlrgdEn9w+Ua2tPgKfm6tROyVrBXz9re/naGhoQXbb7/99py/JUlatg+Dg4N87GMfY/fu\n3QVbPkLYqR0rphIRe7lZqo9hn4ug10lC1Uhn9LL7GwnVIKGmGZ5JI5H9KupwlF7oaq2xodHN1687\nm9e3+6vdlYpSSWF/4oknlnysra2NwcFBOjo6GBwctBYhmc/09DTvfve7uf3223njG99YcB+FFUNt\nWTG1yuhMClXTrYWVK4kBaGQXyXYpEh6ldl+31UIGusMert6xriRRr6WIvVhK8divvfZadu/eDcDu\n3bv53d/93QX7pNNp3ve+93HjjTdy3XXXFXUcEbFTO1kxlWqzVDRNs9aQTSQSjIyMMD4+bm1LpVLc\n+3KMyIxOk8tgJLk6/UpmdDQdFBmCbpnpEgdS6xkdmIirOB1rJ9arRnXH2267jeuvv567776b7u5u\nvv/97wOwd+9e7rzzTu666y6+//3v8+tf/5rx8XHuvfdeAO69917OP//8vI8jhJ3asE3MNlcDwzDI\nZDKkUqkccZ67IHgqlUKfLeIly7K1pmw6nbYKK4XDYWv77hOHcE5NMzidWpVzAKxyBbrOkqIuzf4I\nyc/m9l+6Of/Mi8WopYi9GvXYm5ubefLJJxds37VrF3fddRcAN9xwAzfccENR7ZsIYae2RLjYfuq6\njqqqC8Q6mUzy8ssvW9tMFEWxRNn8v7GxMWdh8MUu7kOHDtHe3k44HM7ps27onClQ1Mslukslxygy\nuB0y8dWqH2xzXJJOarSP044Y4XAYr9dbEyJdDKWuoCRqxdQItWCbzL8QNU1bMqo2fzdrWkiShNPp\ntITaFGdzdRqXy4XT6Sx49D0fdj/bx1NHxwt+nkPOTjryOWWiaZ10nisaKbMlac0JSkuVpw37snXJ\nBdmJXhubGzh3+2YikQjHjx8nmUzS0NBAOBy2hH4lailiLxZN00TZ3lrALjnnhmGgquoCy8P8f2xs\njEgkYomvLMsLhNr8IJrbFUVZ9vx6e3sJBAIlnetKfPuZvqKWwdNmA+lIUs++nhi4HCxbNMwpSzQ3\nKIxG1RXrjQtRz+KSodXv5vqL1i+ojxKNRpmcnOTo0aOkUin8fr8l9B6Pp9pdLwmxNF6dU0mPXdf1\nZX3q+RaI0+m0hHquBeJ2u9E0jQ0bNhRcn2I1Wey1VDUNuYiFHQyy/rgBmHeGtLb0bFAJWBdw4XZI\naIYQ7XxpcMn83vntvGdnbtmAucvQbdy4EV3XLaE/fPgw6XSaQCBgCb3b7a6ZiB2qM3i6Wghhp3Bh\nz2Qyy9of6XSaWCyGLMv09PQsEGq3200gEMiJtvO5yBRFqYhVUkmeOzmBqhlFrdbjkiG9iP29VFMG\nkFQ1BqfErKR88Trg61c3s2vnxhX3lWWZYDBIMBiku7sbXdeZmZlhcnKSQ4cOWasSzR04LxU7ZoGJ\nFZSqTCF35HQ6TTQaXdazNi8yh8ORI9Qul4uGhgaampqs7X19ffh8Pmv6cLnOx44X+lK8NDDFf71v\nH+kiVN2tULB9IzMnwhfkRUqD//3iNOefbaAUWDVNlmVrIYpNmzah6zpHjhwhnU5z4MABNE2jsbGR\nUChEOBzG6Vx8cY5aQ1gxVUbXdaamppb0rFU1+3U9kUgQjUbx+Xw5Ym1GHeZPIW+mLMs1JcLlxDzv\nL/zwQFGirsjZyUUzBeade1wyHqcDRypT9Hqeaw1JghfPpHjkpSF+/4LSghBZlvF6vfh8PlpbW9E0\njenpaSYnJxkYGEDTNEKhkPWTj9Db0doRwl5lVFWlr68vJ2UvGAxavzudTiRJ4uDBg3R2dhZUPa0a\n1ELEbn4I+ybi9E8mVth7CQxILObBrEBS1Wn2SSJiLwDNyC53t7dvqmRhh1whdjgclv8OWUGcmppi\ncnKSvr4+DMPIEXq72xsmQtirjNvtZufOnSvuVysTlGqJ05FE0Z5IMWstu+RsvvtINI0sUfGyBfWE\nLGdTPyuNw+HIWX4uk8lYQt/b24skSTlC73A4bBmxC4+9RqgVYa+lm8U/PHm8KIEuFkWRZv11A59L\nQXFITCVUK2VSsDSNbpkbLuksS1uFCLGiKDQ3N9Pc3AxkBTMSiTAxMUFPTw+SJBEMBslkMraLku2e\nxCCEndqZeWq3yGUxJEniP3oivDQws6rHjacNwl4FVTNQHKBpuhD1PPnSW5pZ31j9nHRFUWhpabHW\nEFVVlfHxcYaHh3nxxRdxOBzWQGxjY2PVxLUWgish7IgiYOXmV8cKW8arXMRVDUWWmYqLwdNCeLIn\nzhUXlqetclonTqeT5uZmBgcHueCCC0in00QiEUZGRjh+/DiKolhCX8wydfWMEPZZasE2qQUrRtN1\nHj28cIHe1SCVMUgtWRlGsBQ/Phzj9wemOb8rWO2uLIvL5aK1tdWqYZ5KpZicnGRoaIijR4/icrks\noQ8EAmta6IWwY5+SAvXAXzw5XNZKiWt5zdHVQge+/sQJvnPzBSW3Ve7BzuXac7vdtLe3097eDkAy\nmWRycpIzZ84wMzOD2+0mHA4TCoUIBAJl61ctWKJC2KkdK8buNwtN0zkwWvysT4lsXrWZ0dLid2Jo\nGuMJYZZXmv2nZ4imMvjd9pKEQm4UHo+Hjo4Oa1JgIpGwcuhnZmbwer2W0JfyObLzZ9DEXu9ilVir\ntkm52dMzseI+EuBzySRVfYEPbpA723QypoolvlYJc/3YXRvrpx671+vF6/Wyfv16DMMgkUgQiUTo\n6+sjHo/zyiuvWELf0NBgm36XAyHs1FZWjJ1vFv/thwdX3GdD2IMsy/RPxJfcR5ayAq8ZwoZZTV4Z\nmClZ2MtNuW4UkiTh8/nw+XysX7+ePXv2sGXLFiKRCL29vcRiMasyaigUwufzLXncWrgBCGHHfoti\nLIWdL6iXT08xFlu+oqIMTCcztAbctAfdDM+kycz6LnO9dKdDIj2bBC9MmNXjoRfP8PE3bSipjdX0\n2EtBkiQaGhpoaGigs7MTwzCIxWJEIhFOnjxJPB63ShSHQqGcRUfsHFyZ1LWwF3JB1IoVY9eL6n8+\neXzFfXwuGbdDon8ywfldQS7c2MiTR8bIaAZOWSauahiAmjEskReDp6tHLLV2M4okScLv9+P3++nq\n6rJq0c9ddMTv9/PKK6/YftYpICxMqB2P3a4R++nJBP9xYvkURwlQNZ2xmEpC1dnTG2FP7xROWUY3\nDJAMZAlcDiknSlfsecp1Schb+szOWonYV8KsRb9hwwbOPfdcLr74Yrq6uujp6WFgYIDzzz+fr371\nq6ver3wRwo79veu52LGftz96ZEXLJOhxkNayGS8SgATDMymmkxkMI7uQclfIQ8jrpNn3WkSkGtmL\ndH5FWYdtBN9+70exnJpM8cujY9XuRg52+dZrlje47bbb6OjoYO/evXz84x/P67mPPvooZ511Ftu2\nbeOOO+5Y8HgqleKDH/wg27Zt49JLL6W3t7fg/s1HCDsiYi+F/ok4Tx5eWQymklmbxfwxp/tLErgU\nmVTGYCCSZDKuMhHP4JpzZeqAV5FxOcCjZJe/s0+RL/u9J8ViAP/9sRNoJby4lYiwy91eqX00DANF\nUdiwYeXxCE3T+MxnPsPPf/5zDh06xPe+9z0OHTqUs8/dd99NOBzm+PHj3HrrrXzhC18oum8mQtip\nHWEH+0Xsn3nwpRX3WW79BsOAzGzeo2GALEuzEb2Uc3HGVJ2MDpouoepGHcXJ9mJkOvstyi7YKX2y\nGPbs2cO2bdvYsmULLpeLD33oQzzyyCM5+zzyyCPcdNNNAFx33XU8+eSTJX/OhbDPYjfBXAy7XeC/\nODTMkeHYivutFACqszsoDgmP04EOCxbokGbbUe0TqledSlwNOvCDF88U/fxaEOLV7OPp06dzIvuu\nri5Onz695D6KotDY2Mj4+HhJx617Yc/nDaylnHO73IAyms6t//pKSW14HLkOtWQYTCVeS5k0ffu6\nv0iLQKZy7v7Tx1eeaLZaVEKES23T7jcuEJ8ZoHasGDsN8j7+6giZEpPMk7PZdRLZwVBzJTwZcMqz\nJQbI+vD2OGv7sJy0lCo7Da7is2NqISumlM+QrusF9aezs5P+/n7r74GBATo7O5fcx1x8xKxRXyxC\n2LGXYNoNwzBIpVLMzMwwOjrK6dOnOXnyJN/61ZEyHyf7v0MCpyKBJCFJ2XTHZt/qLLBgn0ybpTH7\nuFzGealXcmvQzelIssRW7E2xN4tCV0+6+OKLOXbsGD09PaTTaR588EGuvfbanH2uvfZadu/eDcAP\nfvAD3va2t5V8M7N/pv0qUCvRdTnb1DSNVCpFJpNheHiYVCq14MfE6XTidrutn8PjGofGlp9lWghm\npgxkywhoc5ZecsgwmVidiTO1UMN9Nfr4y8Nj/Pb4BP98/Tmcsz5Q0HNrJWIvts1CV3JSFIVvfOMb\nvOMd70DTND7xiU9w9tln8+Uvf5ldu3Zx7bXX8slPfpKPfexjbNu2jaamJh588MGi+pZz3JJbqANq\nyWNfDsMwUFWVVCpFOp1eVKwzmWzGgyzLuN1uVFW1Spw2NjZa4u1yuRatZ63rBu/5zpOrdk7qrD2j\nyJJVfkBQOZwyYGjEUxpf/feD3PXhHWUteVsMtSzsANdccw3XXHNNzra5k5s8Hg//+q//WlR/lkII\nO/bPOdd1nXQ6TTKZRFVV+vv7Fwi22X+n04nL5cqJsIPBoPW7oig5fXvmmWfYtm1b3n356YEh1CrM\nPNcNQyxSvQpkdJhOZ3/vjaj09fcTi0ZpaGigqamJ5uZm3G73ks+vRMRebkrpYyaTsdXaq0shhH2W\n1c5gMQwDTdNIJpNLRteqmrU7JEnC5XJZF1UgECAQCNDS0mIJdimrxeR7oRuGwdd+cazo4yzHcjVh\nJLIevND0yjP3NU5kDO45LPG1919CLBZjYmKCQ4cOkclkCIVCNDU1EQqFKip0dhs81TStJmrF2L+H\nq0A5I3ZzsDEejxOPxxkYGFgg2Lqe9RccDkdOZO12u/H7/dbvTqcz56IeGBhA0zQ2btxYlr4Wyov9\nUwzNpCvS9lKvvlOG7S1uTk5ma8ysJpUoQOZRZNxOmZlEBo9TRjMgVWp6UQX55dGxnAJZGzduRNM0\nIpEIExMTnDx5EqfTSVNTE01NTQVnjaxEpezMYvuo67qI2GuFfIQ9k8ksGVmbnraJy+VCkiRSqRSa\npllfY03vutg7fiUHZPO50H9zrPx1RGSWL83rkGE8lkHVVl/8SnmlPYpEWjOs2jhmWw4ZvE4Hb97a\nzPBMkr2nppZtRwIU+bWxhtUmo8MLpyJc3P1anXaHw0Fzc7OVkpdMJpmYmKC3t5fJyUmOHz9Oa2sr\nTU1NOJ3OkvtQ6x57NVjTwm4ONiYSCWKxGKdPn150sFGSJGuwce5POBzOGWyce7FMTU3R399Pd3d3\nFc+wvPzHicImrnidMg4ZoqmlVWklvUpmYChTW+VkXbLExiYfwzMpPIoDpOy1Fk1meH17gDdvbeK+\nPf2Mx1aeui9JlDxfoFT+4Zc9PPDxpddD9Xg8rF+/nvXr1/PSSy/R3t5ONBplYGAAwzCsaD4YDBZs\nGdotK0Z47DZhbGyMWCy2ILqeO9ho+t2qquL1egmFQpZgOxyOoi4Cu6c7FsrfP36Ml09P57WvI5uG\njiRBbBlRLxWfUyatGVXLlvnj39nED17oZSieG91fsb2Jj1++mScPj7D7uX4ymoEsS6xv9PDW7S38\nwy9P5l1oyw6DxWem8s9pN6sgrlu3js2bN6OqKpOTkwwNDXH06FE8Hg/Nzc00NTXh9Xor2OvKIDx2\nm5BKpZAkadlUvrGxMcbHx9m0aVPZjlsrk57y6eezJye467en8m5TliDU4GIiplZ0wDNbT6Y8RyjU\nT2/2KXzqv2ymUxvkK8+lUTXDGuD9xeFxnjgynrN+K4bBwGSCv3/iRMl9NcsJrNbVFfblb6fMv5ac\nTietra20trZiGAbxeJyJiQmOHj1KKpXKGYRdTDDtFrELK8YmdHV1WYOVS1FLIlwNvrenv6Al6lwO\nCXStpPKv+ZDRjaKnz7sViVRm4bJ8K+GQoDXgxiFLnIkk6ZnW8TgdSJJOco4Rbp662T/NKN9gbLm+\nA7kc0oJia4vRP5Hg+y+e4foL1+fV7nJrhZrL0W3YsAFd161B2J6eHhwOh5VS6ff7K1pvSQj7GqBW\nbJNqtGkYBntORQpqM6YaxPJIdncCiiKRyBR/TsU8UwIMHdwOCc0wVvSwHYAxu8B2yOdEms2nf3jf\naX54RGUmvbRlklPkTHqtdMJiIj/38dUgH1FXZAlJlvj7J3v4/fM7cCxXg5nCslhkWbb8d8h+u56Y\nmKCvr49oNIrf71+QGVYOhLCvEWpFhGH1qzvqBqTLPHpnipohQ4NbIaWpOGWJ1CrN6TeAtG7gdkg4\nVpjR6nJA2OtkOJqdUzAeU5El+OBFnfz0wAguB7QHPXn50F6nA13XSWSM7BgE2YW7M5pBwO0g6HVy\nOpK0yga4ZEhXeeBUn/WX9Nm0TF8eBcKKFU23201HRwcdHR3WmqN9fX1MTU0RiUQIh8OWbVPKvI1S\n+ig89hpCWDFL8z8eO0IsXf6slGxFRwl59pzyiR7LTUozViz8ldZgLJZbF8cw4FdHRnEqMpok4XM5\naA+6GZpOLXi+U4amBhepjI7ikHHIChe0NPDBi9azoyNIk9/Fpx94id7xGGlNp6PRQzyt4XHKyBKM\nRlUrz70aC3vrBiQzBooM//LrXm592xaUZaL2cn2OzDVH161bR0NDA11dXUQiEcbGxjh+/Dhut9uK\n9n0+36otXC8i9hqilmrFrOY3i///Z4f57vMDZTmO6WnPzctOaQYj0cpMeMqXfO4n8/cxgFhao6vB\nzVA8iWfW69/c7CWdMTgzlUSS4PVtfu696UIafS7+sy/CkaEo6wIu3nbWuhxL466PXcDzx4dBkjhn\nfZCHXhzku88PYACXbwmxf2CayXgm19ZhdUU+oxvct+c0p8YTfOOD56zacU3bRFEUWlpaaGlpASCR\nSFgTpBKJBMFgkKamJsLh8Iq58yLdcQ1h51oxlWxzOR7YUx5Rl3ht+Tuo3mSbcrKx2cc/fWAnn7vv\nOSK6zpZ1DXzl3a+nu9lHLKUCEg3u1z5eF20McdHG0KJtuRSZCzcEcTgcyLLMJy7bwI2XdpHRsgOz\nY9EUX/npUfYPzOBxyihkiKVhOqWvqrjrRnYRjn9/ZZj37mxbdJ/Vqu7o9Xrp7Oyks7MTXdeZnp5m\nYmLCqms+N3d+/vNL9diFFVMj1Ep0XYk2lzr34elESSViZQm6m7wMTqUwMGZT5iRGplPLipEiZSNk\nOxtjiizxz9fvpDPs4/O7PLzpTW/KebzBXfpsS0WWUORsZNjid/MvH9xpPXbk6FE0d5CvPH6a4yMx\nShh7Lop7nxtYUtirgSzLhEIhQqHsjVNVVSYmJjhz5gyHDx+2Zn43NTXh8XhKXmhDROw1Qq0Mnq5W\nxG4YBh+9e2/Rz/cqsGVdA7ohsT7kRs3oDE2nyeSxCPX8KfjVYKkqkhLQHnRz940X0hn2rXq/TGRJ\nojXo5hvXn8OtDx/ilTMzq3r85S5DO9RjdzqdtLW10dbWhmEYVgGzw4cPo6oqbrcbSZKK8svt6LFL\nkvRVYMIwjH+c/ft2IezUjrDD6lhGkbhKf2ThQGBe7ZHN9T46HEPVs4OHhVgv5q7VEncZcMgShvba\nTUgCNjZ5+PK738DF3SHczvJ9sM2icbFYDL/fn1e2h3kNtAXdPPDxCzgyHOW//+I4+/uzM4P12W88\nlXgNZQk+8cauMre6NOVYn3R+AbP+/n5GR0d58cUXURTFmgnb0NCw4rFs6rF/G/gh8I+SJMnAh4Sw\nz1IL0fVq3Sx6x+PFtwVE5ySRFOunV0vUJQk8igPdYdAWdPOH/6Wb957bUVSNk0wmQzKZJJVKWf/P\n/d183c0IMhaL4fP5aGlpobm5GZfLtWT7c6+vs9r83Pux83m+d5J/e2kIpyzT3ujmW7/tK3tefNir\ncM05S9swlZgpWk4cDgd+vx9d19myZUtOAbNYLEYgELBsm8Vefzt67IZh9EqSNC5J0gVAG7DPXj2s\nEpW6EGshhXIxhqcTK+6z2tPay4EZwS4VyUpSdgLSdRd2cm5nkLedtQ55kdQ+c1lBs2Z+b29vjoCb\nheMURcHtduPxeHC73ZbXa/4992YRi8WQZZlkMsnY2BgHDhzAMAyam5tpaWnJK5q8dFOYSzeFgWzO\n+f0vnGEmuXKhsUII+Za+2VSCSt8o5hYwMwyDmZkZxsfHOXDgALquW7nzjY2NyLJsSytmlruAm4F2\n4NtC2KkdK2Y12jw8NMN/e/jQis/TyQrkSmV37YQ5s1Oa/X2+j+5zOfird7+OS7oaSKVSDAz050TZ\nZvE4WZYtcdZ1HafTSSAQsES8mMJxpoCZU+67u7tRVZXx8XF6e3uJx+M0NjbS0tKS1zXgVmTu+shO\n/uCBV4irGmqZ5gn8zuua8joPO7NUH80CZsFgkM2bN5PJZJicnGR4eJhjx44xPT3Nz372s2VXkKoi\n/wZ8leyE7o8IYae2BzrLzX+9bx9qnjVeajFidzuy9pADaHBBNJ2d4XlZh8xHdzjxJc7Q3++xCsaZ\nxeM8Hs+C0swAkUiEzs7OivTX6XTS3t5Oe3s7uq4zNTXF2NgYIyMjxGIx2tvbl12qbkdHgB/+wUX8\n4tUx/uXXvURTpU00c0hw3QUdJbVRKOaNtNxt5vP5VBSFdevWsW7dOgzD4PTp0/zkJz/h8ccf5/zz\nz+cf//EfueKKK8rat2IxDCMtSdKvgIhhGFrdC3s+b2AtDXRWss2kqjFSoRWSJMDnzNaFqUYpWgkI\nuCR8isFYAhSHjM/t4D07W/jiu87C5bT3R0GWZcLhMOFwGF3XCYVCpFIpDh48iK7rlmVjFs8yaQ24\nueGSTt64OcSnHzzA0Arppkvhc8p866PnsiG8cqndamfFVKJNSZLo6uriyiuvZNOmTXzhC1+wlq5c\njkcffZTPfvazaJrGpz71KW677bacx7/+9a9z1113WTeRb3/720Wt4TA7aPpG4AMg0h2B2rJNKskz\nJ8cr1rYEKA4HTkOvylJwAY8Dr0tBzWS4+qwg/+1dO/C5FBq9peecVwOPx0NbWxsbN260LBuzeJZp\n2YTDYcsP3raugZ9++mK+9dtT/J//6C94jkKj18l5ncEKnMnqU44iYC6Xa9nBbXPfz3zmMzz++ON0\ndXVx8cUXc+2117Jjxw5rnwsuuIC9e/fi8/n4X//rf/Gnf/qnPPTQQwX1SZKkHcBPgH8zDOMYCGEH\nakfYobLfAv75lyfL2raJLGXTHmNpja6wh4HJBLIkZWuYV+SIC/mzd57F753XwZFjx2gOh2htrL1F\nHpZiMctmfHycnp4e3G63Fc273W4+8zubueGSLu7bc5qH9w8yGl056gTY1Fyd18tunn0h6Y579uxh\n27ZtbNmyBYAPfehDPPLIIznC/ta3vtX6/Y1vfCP33XdfwX0yDOMQsGXuNiHsNUSlL/Bjo9GKtKsb\n2WJaimwwMpXA6wA1j8lK5cLrlHn/Bdla4ssVsKoVlhO7uZYNQDweZ2xsjEOHDqFpGk1NTbS0tPDp\nt3Tz4sA049HIioPffreD2997VpnPIj/sWI8933TH06dPs2HDBuvvrq4unn/++SX3v/vuu3nXu95V\nVL/mI4SdtR2xmxw8M00eJdSLxgCQ4JyuED6XgqYbvDwQYSpZ2fVMnQ6J//G+syt6DDvj8/nYuHGj\nZdmY9VSi0Sg7Q04OOiWSGcOyZhwSBL1ONoY9vHlrExvC2eX88inXWyns4LGbVCrd8b777mPv3r08\n/fTTZWlPCDu1Vba3Ev2Mx+M8vPdMUc8tZHajqsFkPI3PpRBNqsQrUA7YxCHBRy7u4rqLOnl9e6Bi\nx6kl5k+13x6JMBl9lV/1ZzCQ+J3NAT739m20NPqr3VWLSg2eFkshtWI6OzutomQAAwMDi2ZQPfHE\nE9x+++08/fTTZUulFMJObQ50roSu66TT6QUzH83/VVXFMAySySSaphGPZQpbIk4GTS883XFkJs1k\nTGUiruJ2yKgrLFtYDE1ehX/5yHlcuDFc9rbtQDmuVUmSCIfD3HDhOj53dQsej4exsTH6Tx6jd45l\nEwgEqnotV8pjX42yvRdffDHHjh2jp6eHzs5OHnzwQR544IGcffbt28ctt9zCo48+Smtra1F9Wgwh\n7NRexJ5Op5ecpj5/qvrcmY/hcNj621xybP/+/XRv3sLRva/mLdLNDU4mYvkNus1FkbLlezXdQJZA\nK/fNFNjY5OW7H7+ItqCnrG3bjXKLndfrZcOGDWzYsIFMJsPExAQDAwPMzMwQDAatLBu7TacvhlJy\n4zVNw+PJ79pSFIVvfOMbvOMd70DTND7xiU9w9tln8+Uvf5ldu3Zx7bXX8id/8idEo1E+8IEPALBx\n40Z+/OMfF9W3nGOX3IKgbJhT1ZeKstPpNOl0mkQiYYm1OVXdnKgyf6r6SkiSxGOvjnNkeOWBU0WG\njA4TMbWogU+nQyKd0XE7ZWvlpFIwl5aTyNZL2dnVyOfetpVgjaYwVoPFImJFUWhtbaW1tRXDMJie\nnmZsbIze3l6cTqdVy8brrXymjF3y2E0K9divueYarrnmmpxtX/3qV63fn3jiiaL6sRJC2Kl8xG5W\n8JsfXc8VbMhmNMyPsoPBoPV3IpGgp6eHc889t6z9+8nB0bzO33RNin2lzKXodMPAMEArcaaSAXic\nMu/d2cGX3/P6vJ5TTzWYqgAAIABJREFUbYusHKzmt0tJkmhsbKSxsZGtW7eSSCQYHx/nyJEjqKpq\nWTaLLWhRj9i0uuMChLBT/IfdrOC3VJQdi8V45plnAHC5XJZYezweGhsbaWtrw+12LzpVvZz9XKlN\nWQKP07Hi2qamG+5yQEYrvEaMPrsociadXfnH5cguJF2svncEXXz8Td185JINK+8sWJJCriuv10tX\nVxddXV1WLRVzQYtAIICqqmQymbJZNnaL2HVdrwk7yv49rBK6ri9pieRTwc/tdrNv374Fq+uUSrmj\nNd0w8DplEgXkOqa17PT8mXTxfZEAVTOWXbRhOTyKzD03XcTmloai+1DLlEvsSrme5tdSmZmZYWJi\ngv3791t1zltaWkqybOwm7Dau7pjDmhN2c/BxvlgnEgn27t1r2SKSJOX42B6PB7/fb21TFGXFi6MW\nvpo+dSrJ0ZEUjV6FyLwFk5djMVGXAK8ikZ4V7JVqsRuQd71wx+ySeRLgdTn4u/edvWZF3Y6YlRHd\nbje7du0imUwyPj7O0aNHSafThMNhWlpaaGxsrPrnQgh7HWAO+iSTSSs6cblcOVF2Y2MjLpeLnTt3\n5m2LVINKjAUcHEmT1gy8ToWk0yCtaWhFZiA6HRJbWzwMTaeIJBdvRCI7k3Emj0qDEuBzyWwKKXz1\n985jIq7idMjs6AjUbI2XclALqbkej8dabFrTNCYmJhgcHOTIkSMEAgGam5tpbm5e0dYQEXtx1L2w\nB4NBzjrrLNxu97JvyPHjx+1aZ9mi3Bd4OqNzbCLDRExDllUksl67RDYXfCSqklymYJcZRUNWhP+/\nt2/FqyfZvXcEj0emfyKZs79ThqDXhVuR8hJ2Wcr68Ls6fZzT2Vj8idYhdrBi8sXhcCywbMbGxujv\n78fhcFhZNj5f9daRzRc7rqC0GPbvYYmsJOi1Rjk/iL8+NkZM1dB5LeNFT2v82Ttexw/2D6IkMpBZ\nfHapBDkVAj2KxLldjYyNaWi6weBMkvkE3QqJdIbxWH5fCbxOB2/fHuJ9bxCWS70wdzGLLVu2kEql\nGBsb4/jx46RSKcLhMM3NzdaKRSJiL466F/Z6otwXeP9knGg6V7g1A/7u8eMEvU48TgeJtIbTIZHR\nITMnfcVcYg7A65RwOR188UeH+Pq7NxLyyPRNLTzeeCL/ZdoUWeJH/8+luDNRpqYWaUxQFqpdPdHt\ndudYNuaKRUePHsXv95NOp9G08paeKOWcRbqjoCKUK2KPpzUe2T+0aMpiWjOYjKc5q9VPLKWSVBev\nxGhui6sGSTVDNKnx+Z/08qYNHg6MpAqu+T2XD1y4ng1NPkZHY8U3UqfUwizpYjBtGXP5v2g0yuHD\nhzl+/DinTp2yHivVsik13VEIu6CslHPw9M5fn+ToyNKzTTUdXh2KgpTfhCSdrIceSWhE03pJor7O\n7+LGyzZaf9erkJVCOT12OyYLSJJEIBAgEAiwfv163G434+PjHD9+nGQymZNlU+6l85ZDeOwCW/Nc\nz+SK4mtY/+RHKmOQ0TK8eDpedL8UGb74ru1sEamMAl678bjdbtavX8/69evRNI1IJMLIyAjHjh3D\n5/NZA7BO58rZUsJjF9iKckbsSoWiHM2A/uniPNGwz8l9N1/Etjb7lI0V2A+Hw2GlSxqGQSwWY2xs\njJdffhlJkqyJUT6fb1EBFx67wFaU6yuzphscPDNdlrbKgVOW+NOrt3H1jjbaG+u7KmM5KKc1ZVcr\nxmSl/kmShN/vx+/3s2nTJtLpNOPj45w8eZJEIkEoFKKlpYVQKGRZNqu1glI1sX8PBTmU40P95UcO\nLZufvtq874IObrys8JXZi6Uanr1ZomKxH7M+fiAQoLW1laamphWjQjuLcTkpVIRdLhcdHR10dHSg\n6zqTk5NWOqXP56O5ubmkLBthxQjKTjk+zOmMzk8PDi/5uCyBJIFLlmgLuumbTFpFumSJogt2zUcC\nFIfEjo4Af3LV65bd1+6DpyuJtilOHo/H+vF6vYTDYWv2cywWI5FIMDY2Rk9PDz6fj3Xr1uU1O1Ow\nOLIsL2rZTExMEI1GaW1tpaWlhYaGhrw/WyIrRlARShW5I0NRUstE67qRnVGayBicmkgiAzLZrJdy\niLrLIfHp39nEO89uRzegu8mL4lja7692ZLqSaEejUZ5//vllRTufrA1z4k4oFLJEaHR0lL6+Plwu\nlzVzM5/BwUKodSsmX+ZaNolEgra2NlKpFL29vcTjcUKhEM3NzYTD4WXfL+Gx2wQ7X7SFUuq5qJrO\nZ763b0WBNu8dBoCcnZVayLJ5S+FRZL72++fw9jess8X7ouu6VQhusZ+5kbbb7cbr9eLxeHJWonru\nuee47LLLytqvuSK0efNm4vE4o6OjvPzyy8iybC24shoLXRSC3b9ZmRiGgcvloqmpybJsIpEIY2Nj\nnDhxAq/Xa2XZuFyunOcKj10AlD8iKuXD83zPBMPRlZe0M4VfAqsgWKkfWZdDIuRzctWO8q3ruBxL\nifbY2BhnzpzhxIkTVhrd3Gi7sbHR+n0186OXw+fz0d3dTXd3N8lkkpdeeoljx44hSZIVyRcr8msl\nYl8OWZZpamqiqakJwzCIx+OMjY1x4MABDMOwsmwaGhqEx16LlPsiMtMTy9Vmqe30jBWWX+4scSGM\nuYS8Tl7fFii9IfKPtBcTbYBQKERHR0dZ+rLamFbP9u3bkWWZsbExjh49iqqqNDc309raumSaX6Wx\nW12XYtqUJImGhgYaGhro7u5GVVXGx8fp7e3lnnvuoaenh9/+9rd0d3fnvfZpNRDCPku5RbgSlJLH\nHktm+IcnTxT0HIcs4XJIRNN6SVaMW5HZ2Ozjr9678vJ180V7fHyc6elp9u3bl1N6ea5gz420Vyr6\nNjExYZtIvFjmlp82J+1kMhnGxsY4efIkyWSSpqYm1q1bRyAQsPU1XQ0K+Zw7nU7a29tpb2/nb/7m\nb/jwhz/Ms88+y7e//W2efvpp29oy9uxVFajUsnPl9h2Lbe+6/7NnxaXvFh4LYqqOPKvqElhme77J\nkgGPg/s/vovXtfqRJBZE14lEwhJyfbbEpOlnu91unE4nPp+P7du3112lzlJYbAFqU4DM+uf9/f3E\nYjHC4TDr1q1bdJGLcgYz9RCxL4f5DfArX/kKGzbktxzjo48+ymc/+1k0TeNTn/oUt91226L7Pfzw\nw1x33XW88MIL7Nq1q+C+zUcI+yyVEOFyt1nsBT6dUDm5gg1jZr7MJZnJRuqmFeOe1dQ8SqlbdDXA\nZO9Bnjv5mmjPjbQDgYD1+2KiPT4+ztjYWE3U6rYLc+ufm7ncQ0NDHDlyhMbGRtatW7di9oedsNM3\njkI8dk3T+MxnPsPjjz9OV1cXF198Mddeey07duzI2W9mZoZ/+qd/4tJLLy1bP4Wwz6EWRvWL6WPP\n+MreupSH11KIoJv4fA1cfPFFJUXatfC+2JX5udyRSITR0VFOnDiB3+8nlUpZ35RKpVLRdblZrZIC\n/7e9N4+Pqrz3+D9nliSTmayTzCSZSSALEWURlYjaWmQRWmjR+sKNXgWpFayt2lor/VWterVq6c/e\nC2i9FhVtC7hwC/RnixUr1aqXRUBBtpB9lswkmSwzmfWceX5/hOd4ZjKTzJqN5/16BbKczDwzmfmc\n53yXz/fAgQOoqalBVVUVAOCWW27Brl27Bgn7I488goceegjr169PaE2RGB+n7BFgPOzYE+VfZzqH\nPSaaIVgyq5dxwI2zjSx8kmISFSaO41BQUIDa2lrU1dXBaDQiEAjg2LFjOHbsGGw2G3g+ds/8kWAs\nhWKAgRxQrHF1s9kcErIxGo0wm80hxxw+fBhtbW1YunRpQuuJBtuxn2M8CHu8L0ZCCExdTmzd35qy\nNcTD2m9MxndnlY3KfTOGhjZEqdVqXHDBBeB5Hh0dHWhra4NSqURxcTGKiooG1XEPxfmwY09luWMw\nGMRPf/pTbNmyJSW3J4UJ+znGyu46Vggh8Pv9UUv+qB/Ge60Cur2pnUATC8a8DNw3v2bE75cRH4QQ\nyGSyiA1Rx44dg0wmE+P1ozUTeCydLOIJxRgMBrS1tYlfm0wmGAwG8Wun04njx4/jmmuuAQC0t7dj\n2bJl2L17d9IJVCbs5xhLO/ahRLu/vx+ffPIJgIFyN2kiUqvVip8rFAq0Odx47+ND8a8byTckvX7H\nZUneAiMa6d6AhDdEdXZ24sSJEwgGg0M2RI21sMlQjMSOva6uDvX19WhqaoLBYMD27duxdetW8ed5\neXno7PwqTHrNNdfgt7/9LauKGetEEvZYd9rRRNvlcuGqq66K6f6PW50ABuaH8jF2GSlkHJQyDp4E\n3R8z5Rz+c54WhoLUDcoYT1dSiRLvYxypEsWsrCwYjUYYjUb4/f5BDVHFxcVxmWiNBUbKtlehUGDT\npk1YvHgxBEHA6tWrMW3aNDz66KOYPXs2li1bltAaYrrvtN3yGCHWP2AqduyEEAQCgZAa7cbGRvA8\nD4/HA57nwXEclEqlWKetUqkG7bRT8Xh4IYiDzQ509/vFxOhQO/Gy3Ex8rUaLD+s7IZfJkM0L6PME\nEIhD3/U5GfjLHdNgt9tj/6VhGE+CMdGJ1BDV1NQEj8cDrVYrdvamkrF2FRBvjH3JkiVYsmRJyPee\neOKJiMfu27cvoTVFYsILe6wMJ+zhoh3+QasJlEqlKNIcxyEvLw+5ublQqVQj1qVGCMEz757BjsMW\n8JKHFO3RKWTApZPycdsVFdh3phMcIchQyJCfnYEOlz/m+33jzjpwQU9yi2eMCyI1RFmtVvT29uLM\nmTMoLi5Gfn5+0qI81rrBg8HguKj/Z8KOgRcPIQROpxMulysm0aYuf9KddvgL0OVyoaCgYMSbaxz9\nAbxzzAYvH9sVCB8Emjr70d3vhycgoN8nxB1jv3xyPkrzVeju9sa/4PMcuqGIVcDG2gQl2hCVm5uL\nU6dOQavVwmaz4cyZM2OyISrZxzyWTjTRmPDCPlxMm4q21zsgSLQTcjjRHst4AgIc7uFdHKW0ONxY\n/frhYQdcR+N3N84QPz8fYuKpJF5hj/fYkYIK5lANUcXFxTFNiJIylkIx44UJL+x+vx+ff/75sDvt\nL774AlVVVdBoUjdIeTRKKINBguf3xWf2BQAuX+LdhzdeWooizeiUwjHGDuGCSRuiCgoKxCvijo4O\nNDU1QaVSibXyo2GkxYR9nJOZmYm6urqYjh0r5Y7JcKStF3/7Mr7kZW4mhz5fYut8/NsX4ObZxoR+\nl5EYYy0UEwu0ISo3NxdVVVXihKijR48m3BDFiM6EF/ZYGUt17IkSDAbxy11fwhtDKYtCNuDeSDAw\nBCORynW9JgM3XWYctEtLJRN9ZzWRiPUkEW1C1FhpiJoIMGE/x3jrPI3EW59Z0BZD8lIuee8FCdDl\njj8Mo1bK8Oi3p0ImG/xGHitWxROZsWy1Gy/Shiifz4eOjg6xIcrv98PtdjN3zzhhwn6OibBj33HU\nApls4I86VH+RQACOfLVHj3eF2UoZfrZoChZeODJj7hjjg1ScJDIzM0Maog4dOoT6+vpx3RA1GjBh\nP8dEEHZfIIgsuQx9fHRvGDk3IOzJrEqTpYgq6uwNl37OlyuYjIwMKJVKXHzxxYMaogoLC6HT6diE\nqCgwYZ8gWHq86PEE4B5mSlKy80uVcmDN1ZXQ5USPf54vwjOajMVQTDrDOpEaokwmE5xOpzghKhUN\nURMFJuznGO879g/rO5GpkEGhkIEfInlKVxNvujRLwSEnSwl1phxLpuuTWep5jSAI8Hg8ouWE1+uF\n2+2Gz+cTk4asMmRoIk2IGssNUaMBE/ZzjFdhd3p5/H/HrNjwQSO6+2NrSuIAFKqV6HYHYtrBywAE\nBIKLynLw0KJaFKqZ8ESC2k5IhZt+Tme6yuVyZGVlQaVSiUO4dTodfD4fnE4njh07BrlcDr1ej6Ki\nIiiVyrSvezzs2KMRPiGqt7cXdrsdDQ0NUKvV0Ol0cTdETQQmvLCPpAnYSLPjsBn//UEjbH2+mI5X\nnNvA8EGgK8JJQMEB4S4EHAB9bgb4IPDc8hnQZKbGpGy0SGZ9wWAwxOCN/n/o0CH4/QOeOtTgjYp3\nTk6O+HW0HST1H8nPz0d5eTk8Hg9sNhs+//xzZGRkiCJPxWm8vU5HCo7jkJ+fj/z8/CEbos4HJryw\nx8p427Gfanfi1U9a0TuMdYAMAyEXcm49whBbdJ5EDtF09gfwjZqiYUWdkuqpUSMlZNSFM3y37fF4\nEAwGwXGc6MiZlZUFtVqNjIwMzJgxAxkZGSk7qalUKkyePBmTJ09Gf38/bDYbWlpakJ2dDb1ePyZK\nFCMxltY1VEOU2+2GxWKZ0A1RTNjPMd6EvdXhgRAkQ96+nAMUchkKVXJYnQEEYjCCCT+CAyDjODx7\nw7TkFjzKEELg8/ng9XoRCATgdrtF8fb5Bq545HJ5yG67sLBQ/Dpa23tjY2NaG2nUajWqqqpQWVkJ\nl8sFm80Gt9uNkydPQq/Xn/ex5FgIb4jav38/eJ7HsWPHwHGcGK/Pysoa7aWmDCbs4xQ+GIS51wth\nmBMHLwTRmUADEoUAKC9QIScrtpfKaO3YBEEICZNId9uBQAAcxyEjIwOBQADZ2dnIzc1Ffn5+iMXy\nWIbjOOTk5CAnJwcOhwNlZWXo6OjA2bNnkZeXB71eP+pVIWNpxz4UMpkMFRUVqKioEBuiTp48iWAw\niKKiIhQXF4/7higm7OcYbzv2nUetyFTI4BzCvCtDzg1Y9yau6+A44IdzK+P6nXR0nlKHznDR9nq9\noqBId9tU7KgPPhUc6jKo14+typ54nR2lseSenh7Y7XacOXMGBQUF0Ov1yM3NHRciO9qEN0R1dnai\nvr4efr9fFHnaEDVevNgBJuwi40XY7e4gfvb2cfy7oQtC8FyoBJG128MTZMg5aDLlcLj5uO9LpZQh\nP1uJ+RcUJ7vsIQkGg/D5fIME2+PxwO12i5Um0moSeumsUqnGzZstHUgdFGnpn9lsxunTp1FYWAi9\nXg+NRjMiIj9eduzRCJ8Q1dXVhebmZrjdbhQWFsLhcIyb19p5IeyxCOx4qIpxeXm8fMwHq6cDwjkl\np4nRaMhAoEzwxZiXrcSGm2ZClZFcqRjP81F323TGKw2JqFQqqNVqaLVaqFQqeDwemM1mTJs2vmP8\nI4G09I828bS0tMDtdqOoqAh6vR5qdepm0U5kFAoF9Ho99Ho9BEFAZ2cnHn74YdTX1+O+++7Dbbfd\nlpKh0+nivBD2WBjrO/ZgkOAP/25CYy8BT4buLpXiEwB7HOPtQn43EMTUkpwhj6FhEirUPT096O3t\nxeHDh8XhJeG12wUFBSgrK4tpxisNtUxEgsHgoP9j2RHG8nxIm3ioMDU0NIiNUDRMlUrG+449GrSv\nYPPmzVi+fDmWLl0Kq9U62ssaEibsaSSVwr7toAk7P28fVGc+HMncu9MTQGOHCxV5ioi7bb/fLyYl\nqXDTzy+88EJkZmaOm0vXdEAFm45eDBdy6WuD4zgIggBBECCTycBxXMqeOypMer0ePM+jo6MDp0+f\nhiAI8Pv98Pl8541FbjLvR0EQkJGRgUWLFsX8O3v27MF9990HQRBw5513Yt26dYOOefPNN/HYY4+B\n4zhcfPHF2Lp1a8JrpDBhP8dY3rGfanfipX83w+sXosbT04FAgNMnjsFTmC3utnNycqDT6ZCVlQWl\nUhlxzqvT6Uz5bnAsEgwGQQiBIAji5/T7wOCRd/R/Ktz0c+nt0duin6da5BUKBUpLS1FaWgq/34+D\nBw/ixIkTIIRAp9NBp9MlXNs9UXfsFEEQ4upgFQQB99xzD9577z0YjUbU1dVh2bJluOiii8Rj6uvr\n8fTTT+Pjjz9GQUEB7Pb4huREgwn7OcZqjP20zYX/Z+cJdLv9A3XriN/nJVFUShmWzb9qQr9ZoxEu\nzlS4pR/AgDAfOXJE7A6VyWQhb/54BFkmk4nHU2GnOQipyKeKjIwMZGRk4JJLLoHP54PdbhctDXQ6\nHYqLi0fE0iAa6Xg/JnPyiVfYDxw4gJqaGlRVVQEAbrnlFuzatStE2P/whz/gnnvuQUFBAQBAp0uN\nFTYT9nOM1R3734+3w9TjAQkCQjBU0BWyoX3Xk0WXE3835Vg9QYYTLUwSLtyRpkNJ39yXX345XC4X\nrFYrWlpakJeXh9LS0qRryqnIK5VKCIIgJqB9Pp+4q09lmCszMxPl5eWipYHdbhctDXQ6XUyzScfD\njn0khd1sNqO8vFz82mg0Yv/+/SHHnDlzBgDwta99DYIg4LHHHsM3v/nNhNYnhQn7OcaasBNC0Nnn\nxpEWB/p9PLIUMsiDBF5+QNw1SsAVm+dXwswy5qf3DtLIUPFtq9Uq5gLCwyTAV8Idq3BqNBpMmTIF\nNTU16O7uhtVqxalTp1BUVITS0tKYBqSHJ6Gl/0t9aLKyslBWVhaym5fL5SkVeZVKJU406u/vh91u\nx5EjR6BSqaDT6aDVakfEVGusnSgEQUj54G2e51FfX499+/bBZDLhG9/4Bo4dO4b8/OTee0zYz0Eb\nEEYKaigV6Y0cCATQ7Q3i5eN+tPUFwQcBlz+ITAUHOUfAk/SLOgB82uRAt9uPguyx56cRa2IyXLiN\nRiM6OjpQX18PQghKS0uh1+tT8oblOA6FhYUoLCwUK1HOnj0Ln88ntv9H+rsHAgN/zIyMDKhUKvGj\nsLAQWVlZEX1oaGiI53lxR89xXMpFXq1Wo7KyEpMnT4bL5YLdbkdzczM0Go3onEjvb6wJcSSSWSPP\n83Gd0AwGA9ra2sSvTSYTDAZDyDFGoxFz5syBUqlEZWUlamtrUV9fj7q6uoTWSGHCLiGVO/ZAIBDi\nTSJ9M1NDKWntdk5ODoqLi6FSqaBUKvH/7j2LLn87eI4HBwEEgO9cSYyMS35gRiy4fAI+beyOy389\nVW9sqVDzPC/uWhNNTEoxGAwwGAzwer2wWq04dOgQ1Go1SktLQ4Qq3vVGarKiYZPW1lY0NTVBLpcj\nPz8fRUVFYq1+pCT0cNA1yuVyMdkqjcunOukqtTSoqqqC0+mEzWZDQ0ODaD2cjo7jVJ8oRjIUU1dX\nh/r6ejQ1NcFgMGD79u2DKl6uv/56bNu2DXfccQc6Oztx5swZMSafDEzYzxHPH5saSkXabVNDKYVC\nAZ7nkZmZCY1GA61WK4p4LC8Oa48XDveAmMnOjbMDADmGFnU6qDqY5Pi7gdsIQp6ALgz3Bo81Mclx\nnBhjPnjwIPR6PUpLS8WqjWRFKysrS9yN9vX1wWq1or6+HlqtFqWlpcjJ+aqGP5plr9frFXfLUudH\n6Ylaamng8XjQ3t6O1tZWZGdno7S0FFqtNiXxeLpOaWUN3WWmWuSpc6LU0qCrqwsZGRnQarUpsTQY\ni8nTeK7sFAoFNm3ahMWLF0MQBKxevRrTpk3Do48+itmzZ2PZsmVYvHgx/vGPf+Ciiy6CXC7H+vXr\nodVqE1pfyH0nfQsTBGk8PNKUG+mbGEDIm1ilUqGgoAAqlQqZmZniC6elpQVyuRxGozHmdTj6/XB6\neQRB4BfIoAqY4VqT6AlAkylHdoYcnU4/ZLKBEI4v9r4mAEBOphJfq4r/RUZDI8kmJmnycNasWfD7\n/Whvb8cXX3whtn7TKpRkobtRhUIBrVaLzs5OfPHFFwgEApDL5eJH+BWWtOwzVlQqlXgycTqdsFqt\nOHv2LAoKClBaWpq0IMZaWZNKkaeWBna7HR0dHbBYLCmzNEhHaCfR20wkYb1kyRIsWbIk5HtPPPFE\nyFqee+45PPfccwmtKRrnnbBHm3LT09MDn88Hq9UKmUw2aMpNSUlJ3G/ieJOnuz+3YPPHrQgGCdp6\nPEmVNfoCAvJVSnCygR1/plIBv8DHdXvXXFAETQRXx6EqSnieR19fH5qbm6HT6UJ2q8BXws1xXFxv\nsIyMDNGRjwpiQ0MDCgsLUVZWFrK7jgR1f4x0wqZvWCrcGo1GrALp6+uD3W4Xm3yKi4tTkjiU7nqp\nx0tbWxtcLheKi4tRWlqatMOgtLImXOR5nk95IhAYiMlPnjwZwWAQXV1daG1tRX9/f0KWBukKxSRK\nup6zdDA+VpkkDQ0N6OrqEpNUkabcZGdnIxAIoKamJqX3HesLqaHDhfXvNcDtH7is9waC4AAoZRwC\nCQTUA0HA3ueFEAQEEAQEPiSkI0XODbg4hpdO/vWLdvxkfiU057xihotvU4fF2bNno729HZ9//jk0\nGg0MBkNKLWVprJeKR2NjI7xeLwoLC6HRaEIGZtCchvRkLb3CysrKGlKoCwoKxOoQq9WKpqYm5Obm\noqysLGWPKdzjxW634/Tp0+B5Hnq9HiUlJUkPhJDJZBAEQQwhUj96nufFK5NUJl1lMtkgSwP6dyou\nLoZOpxsVa9yRjLGPJueFsJeWlsJgMAw55SYQCIhhllQRz479w/oudPf7IZdx4LiB3yEAkMQOw39O\nqJWyAaGPNmeDACjLyUBbb6injFIuQ3uPB9XFA7usWBKTQGi4oaenR7w0pzHyRAYaRJtuJLXt7erq\nEksZi4uLUVlZiezs7JS8GdVqNWpqalBdXY3u7m5YLBacOnVK3F2nylxLLpeHdIbSEyTtGB3qioE+\nR+FXJfQ5UigUg6yNKysrRdFPtnwymmhGsjSor68Hz/OiyEd6TYzF5CnbsY8h1Gr1sKWM6apjj6WE\nkhCC9091IBAkCJJz8+nOEUjBkgLDLCFIMEjUgYEQTrlWA4UiMWGUxl95nofNZsOxY8egUChgMBjE\nGDkN4URLRlNRimTbG2mWqNPphMViwfHjx2MO1cTzmKQljXR3LQgCSkpKUFJSkrJuTWn4qb+/HxaL\nBQ0NDWJCnuO4EOGmE6CkzxHN+wwn1JEqa2gsPpU7+XBLAzrkIpKlwVgT9njLHUeT80LYY2E0G5SO\nW/pw2uYCh4FdtQwD2s4BkMuGF+Z0MbemENlJWvYCXyVTNRoNKioq0NPTg8bGRhw/flyMAVORDh8C\nnYiRWE5ODi4C/bLAAAAgAElEQVS44AIEg0HR1dDv94vCm6o5l9LdNc3PHD58GFlZWSgtLY07uSvN\nA4Sf5ILBIORyOXJyciCTyeByueDxeFBYWIipU6emJelK/4+1siZe0czIyBBLTyNZGuTl5SX8eNIB\n/RuMB5iwn2O0WuGDQYLn9zUhIAShzpTB7R/wDciQDfihazLkaHR4R3xdAHCwsQMNDQ0wGAxDhk/C\nJxxJ/6fln9K8Rm5uLnQ6HTIzM8XdNc/zYpI6VZe7MplM3AX6/X5YrVYcOXJE7N7UarUp241mZmZi\n8rkB1PQxNTQ0hFS7EEIGhZOkwh2eB6ANStGGidAcQ0tLCzweD3Q6HUpKSpI2YBvpyhogsqXBl19+\nKYajYrE0iAUWYz/PGKkde3hFyf4mBw639SBICAR+IPzBE8AXBOyuAOwYgRbTKBD5QCckHfqr1WqR\nmZkZUsNPG4ek1r1ZWVnIz88XbXyHeiNlZ2dDr9eHNAvl5OSkNDlJ10fb5Knwnj17FlqtFmVlZTG1\n/Q8HrXX3+/1Qq9WQyWTo7e3FkSNHIAgClEolcnJyoNFoBvnSJyIY0gRlIBCA3W4XnRpLSkqg1+uT\nDgtFq6yhAikV+VSFTqilgU6nw6lTp+DxeFJmacBi7OcZqRJ2qXDTengaJ6bfp/dnc/qwYV8TeIFA\npZTD5ePFypSRcnAcCoH3o7W1FcBA2KG9vR1+v180uiooKEioazIS0mahnp4ecbybXq9HWVlZSv3C\nw0M1Z8+ehd/vR2lp6ZAxcml3afjOm8akpTvu/Px8lJaWQqVSIRgMwm63w2q1oq+vD2q1Gvn5+SkT\nCqVSGdJR297enlRYKBLhxmQ0XAMg5PNUolAoxNdFf38/bDZbVEuDWGAx9vOQWIQ93Hc7WsckAOTm\n5qKzsxOfffYZysrKxDADfSE2dPUhSDhUFWWjxeEBd07O5TKIo+9Gk8riXMyZc0nIG4EKlMlkEr0v\ndDpdWhpeeJ4Xm5LCE66pQBqqoTHyQ4cOiTtruVwuCjntLpXmAWhIiXaXDoVcLheF1+PxiPel0WhE\nK4NUXZ1kZWWFhIXa29vF1v9UOE9Ke0Fo2aTb7YbT6YTRaExZ+aRUhDmOg0ajgUajCbE0aGxsFP8O\nBQUFafWqYaGYcQjdsaeqYxIY2EXNnDkTPp8PFosFhw4dQmFhIYxGI9RqNbIUA5evxZoMaDIVONvh\ngqM/ABmG7zBNNzIA35hSNOiNIpPJxCSk2+2G2WxGU1NTyONKFQqFQpwg73K5YDab0dDQAK1WC4PB\nEPd9RbKCoJ/THgc6rq+vrw9erxcFBQWoqalJ2m1PikqlQlVVFSorK9Hb2wuLxYIzZ87E5QYZK7Tm\nnzpPSss0S0pKIt6XVLjDcwE09EY7r+kJTq/Xi4luuptP1pgs2kYr3NKgt7cXNpsN9fX1KCgoEBOv\nkUSehWImIEN1TNJElMViEb07InVMAvF7lGRmZoqXk3QsGSEEhjIDaoqzUd/hBgDocrJQkpuJ4xbX\nkLc3EmEamQy4bNLQYpadnY0pU6agurpaNDASBAFlZWXQ6/Up3d1oNBoxfNLR0YEzZ86A53nxvhQK\nRYj1bbh4U+GWWkGo1WoUFRUN8nOh0PtqamoCz/MpL2fkOA75+fnIz88Xm3jq6+sRCARSXsETXqZp\ns9lw6tQp+Hw+qNVqZGRkiAlw4Ktkt3RObSw5E2DghBxeWZNo0nW4+5I+h8FgED09PbBarThz5gwK\nCwuh0+mQk5Mj3k4yws6qYsYQHo8HDzzwAG677TZceOGFAAa3s3Mch7y8PMyYMQMmkwktLS0oLS1F\nWVlZSifIcBwnXvr39/fDZDJhsbYH0/NzwGWoUFmYBbngx4N/70eXm0Scb6qIIUyTzPg8GYDMDBky\n5TJ0uHyx/Y4kpOHxeGCxWHDgwAEUFBTAYDCkrIac1rvTuLHT6YTJZMLp06chk8nEBpzs7Gzx/8LC\nwqQcFGljjbScUaVSiVU1qbr0lzbx0EqQo0ePIiMjQ2xMikcQpfbAkSpwaM17Tk4O/H4/ent7oVAo\nUF5enhIb46GMyWIV+XhFWCaTiSevYDAIh8OBtrY20dKATic6H2Ls3DBx5dHO3yVNMBjEnj17sHHj\nRvh8PqxZswbf+ta3hnzhBgIBWK1WWCwW5OXloby8PKnLYzr9JppPCb1sVSqVKNQW4amPe+HwCOhy\n+eEOBBEkwJzJeagu1uDNw5YBgYui3DJuoFk10T+cDECmUgalXIY375yNisLESucIIejs7ITZbIbf\n7w/JMQz1O5F8fKRlk9LqG/qRmZkJt9sNi8UCl8uFkpISlJaWpmVAMyFEdILs7u5GUVERysrKUhqC\nkkKnM3V2dorJWFrfLU3kSj8iJXKlu+9o4kRj/3a7HWq1GiUlJSktCQUGl08CiCryLpcLra2tIaPk\nEkEQBHR1dcFms6G/vx8KhQIXXXRR3JYGO3fuRGtrK375y18mtZ4UEvUMNeGFnUIIwenTp7Fx40b8\n+9//xq233orbbrtNnDUY7Xe6urrQ1taGYDCI8vJyFBcXDzrjh/uth7dy092RtByQ/i99Mff29qKt\nrQ0NdifeauTQ5wfUmQqsWzwFFxvz8Pcv7fivfzYgO0OOent/2jzZZQB+dm01Vl1ZkZLbozmG9vZ2\n5OTkiJUMUmEKr3eXPk+xhgCAgb+FzWaD1WqFUqlMqQtkODRUQ+vw6dCOVFzlhce53W43enp64HQ6\nRTMqtVoNjUYzSLiTvX9CiGi05nA4UuY8GQ61FZaGRKXFBfSKjF5pp4LOzk6YTCZwHIdAICBeacZi\nc7Fjxw7YbDY89NBDKVtPkjBhl9LT04NXXnkFr732GubMmYM1a9Zg6tSpUZMtPM+ju7sbZrMZTqdT\nTLDRRJK03V0qSIl0TQKA3++H2WxGs7kd+sI8VFRUQKPRwNTtwZqtX8DHC2jv9SUcbokFpYzD+hsu\nwqKL4huuKz3JhZ/o6KV1IBAAIUS0dc3JyQmxO04VNOHqcDjSvrOmoZr29nao1WqUlZUNW+kivZIL\nD5cA0U9yMpkMHR0dsFqt4hQonU6XlsHTNKTR3t6eUufJ8Pug5cHSkkl6FZZKYXc4HHA4HKipqRFr\n/+12e0RLg3DeeOMN9PT04Gc/+1nK1pMkTNgjIQgC/vrXv+J3v/sdvF4vrr76agDAokWLoFarQ3aR\n9I2lVCrhdrvhcDiQm5uLioqKlMWQw5FeMQiCAKPRCKs/C//593o0dPRDLgO8PBH/uqn+Y6kz5Djw\n0NUh4jScGVesJznaCWq1WtPiACklfGctTbimGhqqsVgs6OnpQX5+fkjXaaQ4d6TQUqwbAtrYZbPZ\nkJ2dLZ5Q0nGFQg28rFar6I2j1+tTkuClFUtutxtutxv9/f1wuVzIzMxETU1Nytwnu7q60NPTg+rq\n6pDvU0sDu90u5laKi4tDTpZbt26F2+3GT37yk6TXkSKYsEdj8eLFIISINec8z2PZsmW45ZZbhkyO\nEULE5AzP82KYJh1vKGAg/mkymdDZ2QmFphCP7nNAIICPD6Kr3w85l3pPGTmADXMVUKsyxZ1UKsRI\nCp3AYzabxfh4WVlZyqpBwvF6vbBYLLDb7cjJyYHBYIhaGjcc0vLJSHFuYCBR5/f7wXFcSDljqpNw\n4bH/SFOgUonP54PNZkN7ezuUSuWwzpNAqPuk9INuoKQllPQ1Rq/k6OsvWWOyaMIuhVoadHR0QKlU\nQq/Xo6ioCNu3b0cgEMC9996b0H2nASbssdLV1YXNmzfjz3/+M77+9a9j7dq1qK6uHvKN7/F40NbW\nhq6uLpSUlIgWwemAOgp+9GULtp70wynIMb0sFz+7tgY3bz6IHk/qKuA1GTLs+F4Venp6RNFN52ML\nBAJob2+HxWKBSqWCwWBIaeOOFEKIWNcdLeEabz33UHFu6c461lBNotCOWqvVCq/XK5ZOpiOZDED0\nqu/o6EB2djby8vKgUCjg9XrhdrsHXaHQD1q9FEv+RFpZQ8uVExn519nZib6+vpjnirrdbthsNuzd\nuxdvvPEGZs6ciQ0bNiTtx5MimLDHC8/z2LlzJzZt2gSVSoUf/vCHmDdv3pAvIkEQYLVaYTaboVar\nUVFRgdzc3LStsa+vDyaTCX19fSgrK8O971jR2OWOWjETLwoZh09//nWoMxRiF6jFYkFWVhaMRmPa\nOv3o7tNsNqO3t1fcxadDmHieD6k84ThO9EWhnyeTzI302GhTUm9vL4qLi1FWVpa2oRP0ZNne3g65\nXI6ysrKEp0BJ7ZWlXafSPgG5XC4O76CdroWFhSkNe8VTWRNOR0cHXC4XKisr477PZ599FkePHoXF\nYsGWLVswa9ashNafQpiwJwohBEePHsWGDRvw+eef4/bbb8eKFSuGLH+ku8G2tjb4/X4YjUbo9fqU\nhGmk9cn0//7+fjidThy2+vDnehlc/MAfjsPAP8lY4Lx37xUw5H+1O6GiazKZ4HQ6RdvadO3i6QmF\nVrlQW4FYRTXWem4q2sBAcr2vry/tCVdBEMTYfzAYFKtq0tXdKN1ZR5sCFQwGI4ZLaA5FeqKTfoT3\nCdCrhvb2dtF5MtEhK0MRLvJ0Jx/txGW32+F2uzF58uS47+ull15Cfn4+Vq9eDULIsO/nPXv24L77\n7oMgCLjzzjuxbt26kJ+3trZi5cqV6OnpgSAIeOaZZwbNRx0GJuypwG6346WXXsL27duxYMECrFmz\nBpMmTRo2TENj4zqdDkajccidZzxGU+FJSrlcjv2nzdh9pBX/Z/GDJ3IYClQ4ZXNBCAJ8nPWRHICf\nLqjC9782KeLPpaETtVoNo9GYcLw6FpxOJ8xmM7q7u6HT6URnxFTXcwNfJVzNZjOCwWBaummlSEM1\nGo0GZWVlabkionkBu90Om80Gt9uNjIyMEHfGSMIdaaBJrNDqk/b2dgBASUlJyqt4witr6GMJT7om\nI+y///3vodfrsXLlymGPFQQBtbW1eO+992A0GlFXV4dt27aF1OTfdddduOSSS3D33XfjxIkTWLJk\nCZqbm+NZUtQXx4TvPE0lOp0ODz/8MH7+859jx44dWLNmDQoKCnD33Xfj6quvjvjCV6lUmDJlCqqq\nqsRuwszMTNF6VCre1FtDGrfNycmJ2WgKAK6YasQVU43wer0wmUyw2ux4yiWHw0Mgl3Fw+viY698J\nAIc7um2wUqlEeXk5jEYjent7xS5QuotPRz13ZmYmcnNzYbfb0dLSAgBiXDc7O1t8vpKt55Z2ndKE\n64EDB5CXl4eysrKUn8Ck7pY0VHP69GlxpxtPqIa6iko/3G53SJOXSqVCcXExMjMz4fV64XA4EAwG\nU26bAIyc8yQwEAqSinz4yL+R8mM/cOAAampqxFj+Lbfcgl27doUIO8dx6OvrAzDQw1JWVpbQuiLB\nduxJQAjBwYMHsXHjRpw8eRJ33HEHli9fjs7OTvGSM9xoipYEUitfaV1wuuqQv2w046n3mmB2BjG5\nKBtX1+rw0kctcA9TRpMh5/DCLTNxVXVhzPcnLWPMycmB0WgctrEl0XrujIwM0Yisq6sLRUVFMBgM\naYtX0xCb2WxGf39/2it4aKLcYhnoNi4rK4NOpwtxnaSiTROVdGCHNEGZlZWF7OzsYXsFaC2+zWZL\nqehGgzpPdnZ2pu2ESW0MAoEA3G437Ha7OHIw3sf13//936iursatt9467LFvv/029uzZg82bNwMA\n/vjHP2L//v3YtGmTeIzVasWiRYvQ3d2N/v5+7N27F5dddlk8S2I79nTAcRwuv/xy6PV6tLW14ckn\nn8Tjjz+O0tJSPPDAA5g9e/aQRlN0V33ixAkUFxfDaDSmPAYpk8kwo6Yc22vK4XK50NbWhmabFUo5\nwAWGPnNnKeVxiTrw1UCLiooKdHd3i9N9iouLodFoBpl0RYpzxzOrU61Wo7a2VrQTPnnyJACEiGCq\nkBpp0TAUvQJL9UQmmqSUy+XQarVwOp1obGzEyZMnIZPJoFarkZOTA7VaLU6eUqlUST3eWKZApVJ0\nw50nzWYzTp48mdCA8EilpzS5S19j1HJZq9UmZEyWatvebdu2YdWqVXjggQfw6aef4rbbbhPHRSYL\nE/YUsGrVKjz00EMoKiqC3+/HG2+8gRdffBGlpaVYu3Ytrrzyyoh/rKysLPFyjQ56piPC0tGso9Fo\ncOGFF2LKFB652has32fC2Z4g5ByHQIT4TKz3Plw9NyFEHNKhVqvF4RmJTg6KRLidMA2dFBYWwmAw\npNQKF/gqDFVeXi7G/s+ePRtzwpXmUqSVJeEnO1oOSId21NbWQqlUiqGanp4eZGRkiCfCVCIdRuJw\nONDS0gK32w29Xp/yJGi48yR1ufT7/dDr9WKpJk3sSp8zaYgpPISp1+ujnuwSMSYLBoMxJ7YNBgPa\n2trEr+nsAikvv/wy9uzZAwC48sor4fV6xVxcsrBQTJoghOCTTz7Bhg0b0NzcjNWrV+PGG28c9g1B\n/WLcbjcMBgNKSkrSlrAjhKDZ2ol9x1vwfmM/Dtu/Cs3IZcDS6Xo8c/1FKavnpk1dJpMJfr8fBoMh\nrQlJWplhNpvB8/yI3B8NnQSDQeh0ukFXKbQ0MFpSN9p800hIQzUAxKqadD0+mgS1Wq3gOE60MkhV\nFU/468zpdIphCkIIMjIyxGEb0lBTsnYUw438ozzzzDO4/PLLcd111w17mzzPo7a2Fu+//z4MBgPq\n6uqwdetWTJs2TTzmW9/6Fm6++WasWrUKJ0+exIIFC2A2m+N5LKwqZjQxmUx44YUXsHv3bnz729/G\nD37wA5SWlg75Oz6fD2azGTabDUVFRTAajWltiujv78fv3j2BHSddCBLgstIMrLk4G4RPjTlXODQh\nabPZUFBQAKPRmPJddbT7y8/Ph8FgSLrHYKjSQLob5HleDC8VFhZCrVZH9H5PFurMaLPZopYypuP+\n7HZ7XFOgIl2p0BxBeDml9IqFhr6o8yS9v1TH/8NH/gEQK2ueeuopfP3rX8e3v/3tmG7rb3/7G+6/\n/34IgoDVq1fjl7/8JR599FHMnj0by5Ytw4kTJ/CDH/wALpcLHMfhN7/5DRYtWhTPcpmwjwU8Hg+2\nbt2Kl156CZMnT8bdd9+Nurq6Id8M0lF09PI/kTK4WOu5MzMzwfN8iD+3TqdLm0BQe1+TyQRBEMRR\ne+m8Sunq6oLZbIbP5xvSTjh8cIdUjOile/ium+4gqeBIE65ut1vscE1XwpVaNFgsFvT19Ymhk3Rt\nCsIbrqjvuUwmGyTeka5UqHjHWk4Zbp2QTudJafmkIAj4xS9+gW9+85tYvnx5yu4nSZiwjyWCwSA+\n/PBDbNy4EVarFXfeeSduuOGGYd/sfX19aGtrg8vlgsFgQGlpqSiAw8W5E6nnpsNAHA5H2u0EgIET\nn9lsRkdHR8Lj7+KBXhVZrVZxohIhZJD/u7SyhD5viYQf6K7TarWKCdd4mq3ihed5MXQCpC6hHP5a\nk8499fv9YtluXl4eioqKkJOTI1Z9pVp8HQ4HrFYr+vv7odPpUFJSknBVlMfjQXNzM5qamtDY2Cj+\nb7PZxOE8Dz/8MG644YaUPYYkYcI+Vmlubsbzzz+Pv//977jhhhtwxx13QK/XDzpOGn+kg3z7+vqg\nUCjES8VIce5ERUgKtUqgHi7l5eVpbUSisXGTyQRCCIxGY8IGa1SoI53wpNUSHMeJu8qSkhKUl5en\n9SQmbbZKt60AMCBa1PwsllBNeC08Fe/wRKX0ZCdNVNIpUO3t7QlPgYqHWJ0nu7u7Q4S7qakJDQ0N\noh13ZWUlqqurUVNTg5qaGlRXV6OkpCStQ7KTYOIL+3Dtu5QdO3Zg+fLlOHjwIGbPnj3Cq4yO2+3G\nSy+9hD/84Q8oLi7GtGnTwHEcVqxYMWQ9N20Tl8vlqKioSJuxFPDVZbfJZEJ/f7+Y3E3ngF9ap97Z\n2Rk11xApsevxeMTEbrQkZaSdq7QOX61Ww2AwpM0TBxhsK5DuDlep+ZnT6UR+fj6ys7NFIXe73WKY\nKZJhVyKJymhToNJlgNbW1oampibs3LkT+/fvh0qlAs/z4Hke+fn5qK6uRnV1tTivt7q6WpxKNc6Y\n2MIeS/suMLBLWrp0Kfx+PzZt2jSmhP2DDz7AI488IrY6d3R0IBgMYtWqVViyZMmwBlhOpxNtbW3o\n6+sTwzTpFFw6DKS9vT3tyc9gMAi32y0m62iFBE1w0Vmn4UKUzKU/PYnR4SrpbkYCQnfVeXl5YoI3\nmeHL9GpFGu+WeufTsIpcLk+r2RrwVVWU1WqFy+USu2rjjf/7/X60traGhEuamppgNpsBDFQH0V23\nUqnEF198gYMHD+Kjjz5K61XRKDCxhf3TTz/FY489hnfffRcA8PTTTwMAfvGLX4Qcd//99+Paa6/F\n+vXr8dvf/nZMCXs4hBA0NDRg06ZNeP/993HjjTdi1apVKCoqGvL3AoGAGDcuKChAeXl5WuPUNPnZ\n1taWcNgkUjklFSIarw2fIESNunQ6HQwGQ8obu6SEx8aNRmPar4wcDgcsFsuwCVee5wclKSOVVEpD\nJpESldITZ7q6QMPXTeP/dApUdna2OKrS5XKJgt3Q0IDm5mY0Njaiq6tLbIKjoRL6v8FgiHqlk4yV\nwBhmYgt7LO27hw8fxlNPPYUdO3bgmmuuGfPCLqWvrw+vvfYaXnnlFcyaNQtr167F9OnTh3yhEkLQ\n0dEBk8kEACgvL09rog4YEAeTyYSurq5BgisIgtj2PpRtQHjMdiibBUEQYLPZYDabE3J+TARqJ9zT\n0xPSaJUu/H4/TCYT2tvbIZPJkJ2dLe6yIzUy0c8TvVoJ96lPR0MSvZ+Ojg40NTWhubkZHR0deOGF\nF8DzvBiTp4ItFe+hht+ch5zflgLBYBA//elPsWXLltFeSkLk5ubixz/+Me655x68++67ePzxx+Hx\neLBmzRosWbIkYsiF4zhxhiO1EmhoaEBpaSnKyspS7ktDbUyLi4uRnZ2Nzs5O/N///R+AgVCJUqkM\nEaB4bAOiQf3Fy8rK4HK5YDKZcPbs2bSGFHJzc5GbmwtBENDe3o5jx45BoVCIJ5VEHos0USk98UkT\nlVTQ+vv74Xa7RQuKVIcWpF2gPM/DZrOJbe60ISnW+L8gCDCZTGhsbAxJVtKpY8XFxaJg19bWYteu\nXejt7cXbb7+Nb3zjG2OprHDcMSF27MOFYnp7e1FdXS3GgNvb21FYWIjdu3ePm127FEIITp8+jU2b\nNuHDDz/Erbfeittvv128jI1GIBAQq1vy8vJQXl4eV1w83tFmtLHEarXC6XSKIpzO2D8VXLPZPCJh\nEyB0aHZxcTEMBkNI3JiGmqRlgeH18JGacqIlKmnClcaU0+GLEw61aejo6EBeXh7cbjcuvfRS+Hw+\nMUwiFW+bzQaZTIaKiopBu+6Kioq0GN6dh0zsUEws7btSxlsoZih6enrw6quv4rXXXkNdXR3Wrl2L\nqVOnDhumoUOyg8GgOK8VwKDSwKFGmw0nQFICgQAsFgusVivy8vJgNBrTNo+TIp0wle7kJ03wUvEL\nBoNigpfjONEqN1y8kz3JSROu+fn5KCsrS3mzTnd3d4hwO51O7Nu3D01NTdBoNLj00ksxY8aMEPEe\nwyWCE4mJLezA8O27UqIJ+3Alk8899xw2b94MhUKB4uJivPLKK5g0KfIQipFGEAS888472LhxIziO\nw5o1a7Bo0aJBuzhpktLtdsPpdKKnpweBQABKpRIajQZqtXqQ7WuqdoP0pGIymUL8W9JV3wwMnPjp\nlUp2djaMRmNC7fbhz10k7xcq2hzHobe3Fz09PaKdcLqT2A6HA2azGR6PB6WlpSgpKYnpRBYMBmG1\nWgftultaWuD3+1FQUDBo102HQb/11ltQq9UxWdkyUs7EF/ZkiaVk8oMPPsCcOXOQnZ2N3//+99i3\nbx/eeOONUVz1YHiex7vvvovnn38eX3zxBaZNmwafz4cf//jHKCgogFKpHNRFSYWIhjByc3NRXl6e\n9h21tNM0Uggj1YSP9SsrKwsZCBKpmYkKOC0PjJbgjXaSCJ/ElG7LBOCrkBvtqG1ubsa1114Ls9kc\nItxNTU0hBmLh4l1ZWZm20kdGSmDCPhyxlkxSjhw5gh/96Ef4+OOPR2yNsWCz2fDjH/8YVVVV0Ov1\nqK+vx6FDh3DZZZdh7dq1qKmpGTZM43A40NraCkEQxDBNOnfUwWAQNpstxA8nXXFxmqjs6+uD3W5H\nT08PZDKZ2L0bqR4+VVcs0hNZOmr/qWe7VLi7u7vR3NyMs2fPoqysDPPmzcMll1wSU4kgY8xzflfF\nxILZbEZ5ebn4tdFoxP79+6Me//LLL+Nb3/rWSCwtLvR6Pd58882Q7/E8j127duH+++9HVlYW7r77\nbsyfPz+iWHMcB61WC61WK5YvNjY2ptUrhlZclJaWio1W9fX1CVXwSI27wksraaKS7rh1Oh0qKirE\n6g+32w2tVpu25i6VSiX673d1deHs2bMIBAKiEdlwAksIgd1uH9QS39TUBI/HA41GI+66q6ursXDh\nQrFE0Ov1YufOnaiqqsKcOXNS/tgYYwu2Yz9HLLXwlD/96U/YtGkT/vWvf42rS1VCCD7//HNs2LAB\nR48exe23344VK1YMu2ukXjFmsxkajQbl5eVJW94Oh7SCJycnJ+Q+w+1yqYDTmvhEE5V+vx8WiwXt\n7e3Izc0Vx/qlE6mdsMPhgFqtxuTJkwcJd1tbGwRBQHFx8aCQSVVVVVrj94wxC9uxD0csE08AYO/e\nvXjqqafGnagDA7vxWbNm4ZVXXkFHRwdeeuklLFiwAPPnz8ddd92FyZMnRwx/yOVyGI1GGAwG0UTJ\n7/eLlr7pCtPk5eVBqVTC4XDg888/FxO80WriqZlXomRkZGDy5MmYNGmSGMLwer0pH3ji8XhEwZYK\nOM/zMJvNsNvtuPTSS3Hdddfhm9/8JmpqalBRUZHWMlHGxILt2M8RS8nkkSNHsHz5cuzZswdTpkwZ\nxdWmjnu2FLIAABGCSURBVEAggB07duCFF15AXl4efvjDH+Lqq68eVqw9Hg9MJpM4ystoNMZ1opMm\nKsNDJtESlXK5HDabDXa7fUSGjwAD1r50F19QUACDwRBTUtnhcER0EXS5XFCpVKKLoNSMSq/Xg+M4\n2O12/O///i/WrFnDSgYZQ8GSp7EwXMnkwoULcezYMXH6UUVFBXbv3j3Kq04NhBAcOnQIGzZswKlT\np7Bq1SrcfPPNw3Y2ShuCVCoVKioqRKc8QRAi+piEuy6GV5kMd1KhlSYmkwkymQxGozHtVgLSMk2P\nx4OjR49i4cKFaG9vH7ZEkAp3VVXVeHURZIxNmLCPJMPVw/t8Ptx+++347LPPoNVq8cYbb4iujmOB\n9vZ2vPjii3j77bexePFi3HXXXSGJZYo0Udnf34+enh44HA4xZJKZmRnRxyTRcXqRoFYC3d3dYrI1\nVQlev9+PlpaWEOFubGxEb28veJ7HqVOnUFlZieuvvx51dXWorq7G5MmTx12IjjFuYcI+UsRSD//C\nCy/giy++wIsvvojt27fjL3/5y5irhwcGTkB//vOfsXHjRqhUKsyaNQtOpxNr1qwRd910wpBUvGUy\nmdiBST1N0mmUBQyE0uiVg1qtFpOtw51AIpUINjQ0wOFwiDH38MELBoMBMpkMPM/jb3/7G6ZPn46q\nqqq0Pj5GfAy3ufrJT36CDz74AMCAXQItfQUGckozZswAMOavypmwjxSx1MMvXrwYjz32GK688krw\nPI+SkhJ0dHSMuXjqv//9bzzwwAPiLtRms8Hr9WLFihVYvnz5sPFtaX16ZmYmysvL0zpgGfhq5qfJ\nZILb7caRI0ewaNEi2O32kM7K5ubmkBLBcAvYdPvLMNJHrPMZKBs3bsSRI0fwyiuvAAA0Gg1cLtdI\nLjlRWFXMSBFLPbz0GIVCgby8PHR1dQ3rtT7SfP3rX4+49hdeeAFz587F0qVLcdddd4k5h3Ck9em9\nvb1obW1FfX19yqtMeJ4X6+2lCcvOzk4IgoAnnngCkyZNwrJlyzBnzhysWLECVVVVE23oAuMcBw4c\nEPsFAOCWW27Brl27ogr7tm3b8Pjjj4/kEtMOE3ZGXBgMBjz11FN45JFHsHXrVqxYsQKTJk3CD3/4\nQ9TV1UXd5ebl5WHGjBnw+XwwmUw4cOBAXJUt0hJB6eAFu90OuVyO8vJycbe9ZMkS0UVQoVCA53m8\n8847uOCCCzB16tRUPyWMFDBc6GTLli148MEHxRLkH/3oR7jzzjsBAK+99hqefPJJAMDDDz8shuIo\nQzUbtrS0oKmpCfPnzxe/5/V6MXv2bCgUCqxbtw7XX399Sh/rSMCEPcXEUg9PjzEajeB5Hr29vdBq\ntSO91KTIysrC6tWrsWrVKnz00UfYuHEjLBYL7rzzTnz3u9+NmkDMzMwUfUjsdjuOHz8Or9eL3t5e\nXHHFFWhpaUFDQ0NIstLlciErKyukq/Lqq68OKREcCoVCgeuuuy4dTwMjBQiCgHvuuSckdLJs2bJB\nO+ybb755UMOgw+HA448/jkOHDoHjOFx22WV49NFHY77v7du3Y/ny5SFXjy0tLTAYDGhsbMT8+fNF\n58rxBBP2FFNXV4f6+no0NTXBYDBg+/bt2Lp1a8gxy5Ytw2uvvYYrr7wSb7/9NubPnz9u47kymQxz\n587F3Llz0dLSgueffx5XX301vvvd72L16tXQ6/XiseEugjRk0tvbC7vdjubmZsyYMQOLFy/GjBkz\ncP3116O6ujrt3Z+M0SXe0ImUd999F9deey0KCwsBANdeey1aWlpiajYEBoT9+eefD/kePbaqqgrX\nXHMNjhw5woT9fEehUGDTpk1YvHixWA8/bdq0kHr473//+7jttttQU1ODwsJCbN++fbSXnRImTZqE\n3/zmN3jsscfwxz/+ETfeeCMCgQAMBgOsViuAgTcN3XXPmzcPd955p5ic7ejowKuvvoof/ehHLP49\nhknG3jpSxUmsPk07duzAhx9+iNraWvzud79DeXl5xN/NyMgYdnMFAKdOnUJ3dzeuvPJK8Xvd3d3I\nzs5GZmYmOjs78fHHH+PnP/95ck/YaEAIGeqDMQbo6uoiCxcuJDU1NWThwoXE4XAMOubIkSPkiiuu\nIBdddBGZMWMG2b59+yisNBRBEMj27dtJa2srEQRhtJfDSAE8z5OqqirS0NBAfD4fmTlzJvnyyy9D\njvnnP/9J+vv7CSGEvPDCC+Smm24Sf6ZWqwfd5ltvvUW+//3vi1+//vrr5J577gk5prOzk3i9XkII\nIS+++CKZN28eIYSQ9evXk//8z/8Uj3viiSfI+vXryTvvvEOmTJlCqqqqyJNPPkkIIeSRRx4hu3bt\nEo/91a9+RR566KGQ+/n444/J9OnTycyZM8n06dPJ5s2bY39yRp6o2s2EfRzw4IMPkqeffpoQQsjT\nTz9Nfv7znw865vTp0+TMmTOEEELMZjMpKSkh3d3dI7pOxsTnk08+IYsWLRK//vWvf01+/etfRz3+\n8OHD5KqrrhK/jiTs8d4mz/MkNzeXEELI1q1byV133SX+7K677iJbt26N7cGMf6Jqd/pMthkpY9eu\nXVi5ciUAYOXKldi5c+egY2pra0X/GjoDs6OjY0TXyRh77NmzBxdccAFqamrwzDPPDPq5z+fDzTff\njJqaGsyZMwfNzc3iz55++mnU1NTgggsuEPsyIoU+6OzVSITbW9OKkyuuuEJ8HUvzUn6/H9u3bx80\n9YyG8gBg9+7duPDCCwEM9IT84x//QHd3N7q7u/GPf/wDixcvjuMZmpiwGPs4wGazibXiJSUlsNls\nQx5/4MAB+P3+cZfwYaSWWKpNXn75ZRQUFODs2bPYvn07HnroIbzxxhs4ceIEtm/fji+//BIWiwUL\nFy7EmTNn4rr/P/3pTzh06BD+9a9/id+LVnEyXF5qw4YN2L17NxQKBQoLC7FlyxYAQGFhIR555BHU\n1dUBAB599FExkXpeM9R2flQuLs5TFixYQKZNmzboY+fOnSQvLy/k2Pz8/Ki3Y7FYSG1tLfn000/T\nvWTGGCeWEMeiRYvIJ598QgghJBAIEK1WS4LB4KBj6XGxhk3ee+89MnXqVGKz2aKub+XKleStt95K\n+PExWChmzLN3714cP3580Md1110HvV4vXoparVbodLqIt9HX14elS5fiqaeewhVXXDGSy2ekCIfD\ngWuvvRZTpkzBtddei+7u7kHHHD16FFdeeSWmTZuGmTNnhvgMrVq1CpWVlZg1axZuvfXWkOqiSGGT\naF3Q0UIusYRNjhw5gjVr1mD37t0hr9Xu7m74fD4AECtOYilpZMQPE/Y4OXjwIGbOnAmv14v+/n5M\nmzYNx48fT+t90rp3YKDLLlKzjd/vx3e/+13cfvvtWL58eVrXw0gfzzzzDBYsWID6+nosWLAgYlw8\nOzsbr7/+Or788kvs2bMH999/v2hgBQDr16/H0aNH8dvf/jbljW/Sct4LL7wQN910kxg2oWZZDz74\nIFwuF2688UbMmjVLFP6TJ09i9uzZuPjiizFv3jysW7eOCXuaYDH2OKFxyocffhgejwf/8R//genT\np6f1PtetW4ebbroJL7/8MiZNmiTOND106BBefPFFbN68GW+++SY+/PBDdHV1ifHHLVu2YNasWWld\nGyO17Nq1C/v27QMwkCi/5ppr8Oyzz4YcU1tbK34uTZTn5+eHHJdMF/RQv7tkyRIsWbIk5HaeeOIJ\n8fO9e/dGfGxXXXUVjh07NtxTwEgFQ8VpRiVqNA6g9buXX3454Xl+tJfDGCVi6S8ghBCZTEYuvvhi\ncvHFF5PvfOc74vcbGxvJ5ZdfTqqrq8lNN91EfD5fSD4lGAwOyq+Es3//fjJ16lSxT2DlypWktraW\nzJgxg9x7771k8uTJpLGxUXzNHj9+POT3N23aRNasWUMIIWTbtm3kxhtvJIQQcvz4cTJz5kzi9XpJ\nY2MjqaysZK/1sQerY08lFouFVFVVkQsvvJC4XK7RXk5cxCpGhBDS29tLDAbDoGYRxgCx9BcQMrh2\nmybKc3NzidFoJNOmTSMFBQVkzZo1SSfKLRYLCQaDxOv1kttvv51873vfG7JRx+PxkOXLl5Pq6mpS\nV1dHGhoaxNt68sknSVVVFamtrSV/+9vf4nhmGCMEE/ZU8p3vfIf8+c9/Jk8++eS4E71YxYgQQu69\n915y6623jrvHOFLU1tYSi8VCCPlKZCMRqSknGAwSrVZLAoEAIeSrCpZYb7O3t5dccsklQ1aVfPDB\nB2Tp0qVxPSbGuIJVxaSK119/HUqlEitWrMC6detw8OBB/POf/xztZcVMLM1OAPDZZ5/BZrNh0aJF\nI7m8tBBLpckHH3yAWbNmiR9ZWVnicyOtNJk1axaOHj0KIPb+gkhNOV1dXcjPz4dCMZDmolUnySbK\nafUUIQQ7d+5Me/6HMUYZSvVH4xTESC+xxHAFQSBz584lbW1t5NVXXx33O/Z4rlIIGQhXFRQUkP7+\nfrJgwQKSn59PysvLE+4vMJlMhBBCGhoayKRJk8jZs2dJR0cHqa6uFo9pbW0l06ZNI52dnWT+/Pmk\npqaGLFiwgHR1dRFCCDl48KDop/LHP/6RKBQKMW5/8cUXkyNHjhBCCJk3bx6ZPn06mTZtGvne975H\nnE5nAs8YY5zAQjHnE8k2O23cuJE8++yzhBAyIYQ91vAG5X/+53/IihUrxK+jNdLEe7vS24oWimEw\n4oAJO2OAWMRoxYoVpLy8nEyaNIlotVqSk5MzyAUv1bz55pvkoosuIhzHkYMHD0Y97u9//zupra0l\n1dXV4i6ckMgVJpR4K03mzZtH/vrXv4pfSytN7r//ftFl8Gc/+1nIlcCDDz446LYcDod4fEdHB6mp\nqRHdEJcvX062bdtGCCFkzZo15Pnnnx9yXQxGGEzYGQPEIkZSRmrHfuLECXLq1Ckyd+7cqMI+lGWs\nTqcLqTApLS1N2JKhqKiI+P3+kO9JK00ef/xxQgiJKWwylA1sQ0MDqaurI9XV1WT58uXiCYDBiBEm\n7IwBYhEjKSMdihlK2KP5lAwX1ognZPJf//Vf5Ac/+EHUn7NKE8YYglXFMAbQarV4//33UV9fj717\n94pOeLNnz8bmzZsHHb9q1apBcyZHi2j+JdEqTCixVJpQtm3bhltvvTXke6zShDHeYMLOGDEWLlyI\n6dOnD/rYtWtXWu933bp1eO+99zBlyhTs3btXHOV26NAhcdI9ADQ3N6OtrQ1z584N+f3vfe97mDFj\nBmbMmIHOzk48/PDDaV3vSPPiiy+KpZyVlZWYN2/eaC+JkSTMK4YxYkTzEImVaP4lWq0WPT094Hke\nCoVikCcKvUoJJ/wqZfLkyRGHRoynPoVEWLt2LdauXYtAIID58+fjpz/96WgviZEkbMfOGDdEs4zl\nOA7z5s3D22+/DWD4cAsjMvfddx/mz5+P73znO6O9FEaSMGFnjAn+8pe/wGg04tNPP8XSpUvF8WYW\ni0V0EoxmGQsAzz77LJ577jnU1NSgq6sL3//+90ftsYxHtmzZgpaWFvzqV78a7aUwUgBHCBnq50P+\nkMFgjH8+++wzrFy5Eh999BEKCgpGezmM2OGi/YDt2BmM85xNmzbB4XBg3rx5mDVrVkhCmTE+YTt2\nBoPBGJ+wHTuDwWCcLzBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GY\nYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YG\ng8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkG\nE3YGg8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAmGYpifcyOyCgaDwWCk\nDLZjZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GYYDBhZzAYjAkGE3YGg8GYYPz/sl1hXi6GaqQA\nAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngzHFYMLOYDAYU4z/H2PLFEJYxWFYAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nGP5/fOKAZXnlYdgAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nD88Egxd2Hh4engkGL+w8PDw8E4z/D51kV+6KZj62AAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXYAAAF2CAYAAAB6XrNlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], + "outputs": [], "source": [ "# Number of optimization steps\n", "Niter = 2000\n", @@ -499,7 +351,7 @@ "w_laplacian = 0.1 \n", "# Plot period for the losses\n", "plot_period = 250\n", - "loop = tqdm_notebook(range(Niter))\n", + "loop = tqdm(range(Niter))\n", "\n", "chamfer_losses = []\n", "laplacian_losses = []\n", @@ -564,7 +416,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -574,32 +426,7 @@ "id": "baXvAo1yWHRd", "outputId": "11ebe2ad-4352-4492-bd67-e6a3c95adc85" }, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0.5, 1.0, 'Loss vs iterations')" - ] - }, - "execution_count": 79, - "metadata": { - "tags": [] - }, - "output_type": "execute_result" - }, - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAw0AAAFUCAYAAABm/9D2AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nFvT/AyfB6EfRGCKLAAAAAElFTkSuQmCC\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "tags": [] - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig = plt.figure(figsize=(13, 5))\n", "ax = fig.gca()\n", @@ -610,7 +437,7 @@ "ax.legend(fontsize=\"16\")\n", "ax.set_xlabel(\"Iteration\", fontsize=\"16\")\n", "ax.set_ylabel(\"Loss\", fontsize=\"16\")\n", - "ax.set_title(\"Loss vs iterations\", fontsize=\"16\")" + "ax.set_title(\"Loss vs iterations\", fontsize=\"16\");" ] }, { @@ -625,11 +452,10 @@ }, { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "krikJzrLtuvw" }, "outputs": [], @@ -669,7 +495,7 @@ "bento/extensions/theme/main.css": true }, "colab": { - "name": "FitMesh.ipynb", + "name": "deform_source_mesh_to_target_mesh.ipynb", "provenance": [] }, "kernelspec": { @@ -688,255 +514,6 @@ "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "0bd231c2134e4127a3756807317d6aae": { - "model_module": "@jupyter-widgets/base", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "12fdcbc799cc4da899d889d0399616c2": { - "model_module": "@jupyter-widgets/controls", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_23804ad243d44cecbff89ab0b7f40c7e", - "IPY_MODEL_be25dd06faf04bf29733cc16deefb189" - ], - "layout": "IPY_MODEL_0bd231c2134e4127a3756807317d6aae" - } - }, - "23804ad243d44cecbff89ab0b7f40c7e": { - "model_module": "@jupyter-widgets/controls", - "model_name": "IntProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "IntProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "total_loss = 0.002734", - "description_tooltip": null, - "layout": "IPY_MODEL_6e2ff75105a74afbb4ed3fafd414e16f", - "max": 2000, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_283601ac2fe54ecc8716aed8842a5dd2", - "value": 2000 - } - }, - "283601ac2fe54ecc8716aed8842a5dd2": { - "model_module": "@jupyter-widgets/controls", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "initial" - } - }, - "5462de8f68be408d98a6a495e630f448": { - "model_module": "@jupyter-widgets/controls", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "6e1e9eb164434a06b7b1bc73e4eb4fcd": { - "model_module": "@jupyter-widgets/base", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "6e2ff75105a74afbb4ed3fafd414e16f": { - "model_module": "@jupyter-widgets/base", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "be25dd06faf04bf29733cc16deefb189": { - "model_module": "@jupyter-widgets/controls", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_6e1e9eb164434a06b7b1bc73e4eb4fcd", - "placeholder": "​", - "style": "IPY_MODEL_5462de8f68be408d98a6a495e630f448", - "value": "100% 2000/2000 [01:35<00:00, 21.01it/s]" - } - } - } } }, "nbformat": 4, diff --git a/files/deform_source_mesh_to_target_mesh.py b/files/deform_source_mesh_to_target_mesh.py index 030305cd..7ed0bd6d 100644 --- a/files/deform_source_mesh_to_target_mesh.py +++ b/files/deform_source_mesh_to_target_mesh.py @@ -1,4 +1,4 @@ - +#!/usr/bin/env python # coding: utf-8 # In[ ]: @@ -40,7 +40,12 @@ get_ipython().system('pip install torch torchvision') -get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") +import sys +import torch +if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'): + get_ipython().system('pip install pytorch3d') +else: + get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") # In[ ]: @@ -59,7 +64,7 @@ from pytorch3d.loss import ( mesh_normal_consistency, ) import numpy as np -from tqdm import tqdm_notebook +from tqdm.notebook import tqdm get_ipython().run_line_magic('matplotlib', 'notebook') from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt @@ -68,14 +73,18 @@ mpl.rcParams['savefig.dpi'] = 80 mpl.rcParams['figure.dpi'] = 80 # Set the device -device = torch.device("cuda:0") +if torch.cuda.is_available(): + device = torch.device("cuda:0") +else: + device = torch.device("cpu") + print("WARNING: CPU only, this will be slow!") # ## 1. Load an obj file and create a Meshes object # Download the target 3D model of a dolphin. It will be saved locally as a file called `dolphin.obj`. -# In[1]: +# In[ ]: get_ipython().system('wget https://dl.fbaipublicfiles.com/pytorch3d/data/dolphin/dolphin.obj') @@ -139,7 +148,7 @@ def plot_pointcloud(mesh, title=""): plt.show() -# In[75]: +# In[ ]: # %matplotlib notebook @@ -164,7 +173,7 @@ deform_verts = torch.full(src_mesh.verts_packed().shape, 0.0, device=device, req optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9) -# In[78]: +# In[ ]: # Number of optimization steps @@ -179,7 +188,7 @@ w_normal = 0.01 w_laplacian = 0.1 # Plot period for the losses plot_period = 250 -loop = tqdm_notebook(range(Niter)) +loop = tqdm(range(Niter)) chamfer_losses = [] laplacian_losses = [] @@ -234,7 +243,7 @@ for i in loop: # ## 4. Visualize the loss -# In[79]: +# In[ ]: fig = plt.figure(figsize=(13, 5)) @@ -246,7 +255,7 @@ ax.plot(laplacian_losses, label="laplacian loss") ax.legend(fontsize="16") ax.set_xlabel("Iteration", fontsize="16") ax.set_ylabel("Loss", fontsize="16") -ax.set_title("Loss vs iterations", fontsize="16") +ax.set_title("Loss vs iterations", fontsize="16"); # ## 5. Save the predicted mesh diff --git a/files/fit_textured_mesh.ipynb b/files/fit_textured_mesh.ipynb new file mode 100644 index 00000000..b751dc3a --- /dev/null +++ b/files/fit_textured_mesh.ipynb @@ -0,0 +1,940 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "_Ip8kp4TfBLZ" + }, + "outputs": [], + "source": [ + "# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "kuXHJv44fBLe" + }, + "source": [ + "# Fit a mesh via rendering\n", + "\n", + "This tutorial shows how to:\n", + "- Load a mesh and textures from an `.obj` file. \n", + "- Create a synthetic dataset by rendering a textured mesh from multiple viewpoints\n", + "- Fit a mesh to the observed synthetic images using differential silhouette rendering\n", + "- Fit a mesh and its textures using differential textured rendering" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "Bnj3THhzfBLf" + }, + "source": [ + "## 0. Install and Import modules" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "okLalbR_g7NS" + }, + "source": [ + "If `torch`, `torchvision` and `pytorch3d` are not installed, run the following cell:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "musUWTglgxSB" + }, + "outputs": [], + "source": [ + "!pip install torch torchvision\n", + "import sys\n", + "import torch\n", + "if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):\n", + " !pip install pytorch3d\n", + "else:\n", + " !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "nX99zdoffBLg" + }, + "outputs": [], + "source": [ + "import os\n", + "import torch\n", + "import matplotlib.pyplot as plt\n", + "from skimage.io import imread\n", + "\n", + "from pytorch3d.utils import ico_sphere\n", + "import numpy as np\n", + "from tqdm.notebook import tqdm\n", + "\n", + "# Util function for loading meshes\n", + "from pytorch3d.io import load_objs_as_meshes, save_obj\n", + "\n", + "from pytorch3d.loss import (\n", + " chamfer_distance, \n", + " mesh_edge_loss, \n", + " mesh_laplacian_smoothing, \n", + " mesh_normal_consistency,\n", + ")\n", + "\n", + "# Data structures and functions for rendering\n", + "from pytorch3d.structures import Meshes\n", + "from pytorch3d.renderer import (\n", + " look_at_view_transform,\n", + " OpenGLPerspectiveCameras, \n", + " PointLights, \n", + " DirectionalLights, \n", + " Materials, \n", + " RasterizationSettings, \n", + " MeshRenderer, \n", + " MeshRasterizer, \n", + " SoftPhongShader,\n", + " SoftSilhouetteShader,\n", + " SoftPhongShader,\n", + " TexturesVertex\n", + ")\n", + "\n", + "# add path for demo utils functions \n", + "import sys\n", + "import os\n", + "sys.path.append(os.path.abspath(''))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "Lxmehq6Zhrzv" + }, + "source": [ + "If using **Google Colab**, fetch the utils file for plotting image grids:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "HZozr3Pmho-5" + }, + "outputs": [], + "source": [ + "!wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py\n", + "from plot_image_grid import image_grid" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "g4B62MzYiJUM" + }, + "source": [ + "OR if running **locally** uncomment and run the following cell:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "paJ4Im8ahl7O" + }, + "outputs": [], + "source": [ + "# from utils.plot_image_grid import image_grid" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "collapsed": true, + "id": "5jGq772XfBLk" + }, + "source": [ + "### 1. Load a mesh and texture file\n", + "\n", + "Load an `.obj` file and it's associated `.mtl` file and create a **Textures** and **Meshes** object. \n", + "\n", + "**Meshes** is a unique datastructure provided in PyTorch3D for working with batches of meshes of different sizes. \n", + "\n", + "**TexturesVertex** is an auxillary datastructure for storing vertex rgb texture information about meshes. \n", + "\n", + "**Meshes** has several class methods which are used throughout the rendering pipeline." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "a8eU4zo5jd_H" + }, + "source": [ + "If running this notebook using **Google Colab**, run the following cell to fetch the mesh obj and texture files and save it at the path `data/cow_mesh`:\n", + "If running locally, the data is already available at the correct path. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "tTm0cVuOjb1W" + }, + "outputs": [], + "source": [ + "!mkdir -p data/cow_mesh\n", + "!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.obj\n", + "!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.mtl\n", + "!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "gi5Kd0GafBLl" + }, + "outputs": [], + "source": [ + "# Setup\n", + "if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + " torch.cuda.set_device(device)\n", + "else:\n", + " device = torch.device(\"cpu\")\n", + "\n", + "# Set paths\n", + "DATA_DIR = \"./data\"\n", + "obj_filename = os.path.join(DATA_DIR, \"cow_mesh/cow.obj\")\n", + "\n", + "# Load obj file\n", + "mesh = load_objs_as_meshes([obj_filename], device=device)\n", + "\n", + "# We scale normalize and center the target mesh to fit in a sphere of radius 1 \n", + "# centered at (0,0,0). (scale, center) will be used to bring the predicted mesh \n", + "# to its original center and scale. Note that normalizing the target mesh, \n", + "# speeds up the optimization but is not necessary!\n", + "verts = mesh.verts_packed()\n", + "N = verts.shape[0]\n", + "center = verts.mean(0)\n", + "scale = max((verts - center).abs().max(0)[0])\n", + "mesh.offset_verts_(-center.expand(N, 3))\n", + "mesh.scale_verts_((1.0 / float(scale)));" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "17c4xmtyfBMH" + }, + "source": [ + "## 2. Dataset Creation\n", + "\n", + "We sample different camera positions that encode multiple viewpoints of the cow. We create a renderer with a shader that performs texture map interpolation. We render a synthetic dataset of images of the textured cow mesh from multiple viewpoints.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "CDQKebNNfBMI" + }, + "outputs": [], + "source": [ + "# the number of different viewpoints from which we want to render the mesh.\n", + "num_views = 20\n", + "\n", + "# Get a batch of viewing angles. \n", + "elev = torch.linspace(0, 360, num_views)\n", + "azim = torch.linspace(-180, 180, num_views)\n", + "\n", + "# Place a point light in front of the object. As mentioned above, the front of \n", + "# the cow is facing the -z direction. \n", + "lights = PointLights(device=device, location=[[0.0, 0.0, -3.0]])\n", + "\n", + "# Initialize an OpenGL perspective camera that represents a batch of different \n", + "# viewing angles. All the cameras helper methods support mixed type inputs and \n", + "# broadcasting. So we can view the camera from the a distance of dist=2.7, and \n", + "# then specify elevation and azimuth angles for each viewpoint as tensors. \n", + "R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim)\n", + "cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)\n", + "\n", + "# We arbitrarily choose one particular view that will be used to visualize \n", + "# results\n", + "camera = OpenGLPerspectiveCameras(device=device, R=R[None, 1, ...], \n", + " T=T[None, 1, ...]) \n", + "\n", + "# Define the settings for rasterization and shading. Here we set the output \n", + "# image to be of size 128X128. As we are rendering images for visualization \n", + "# purposes only we will set faces_per_pixel=1 and blur_radius=0.0. Refer to \n", + "# rasterize_meshes.py for explanations of these parameters. We also leave \n", + "# bin_size and max_faces_per_bin to their default values of None, which sets \n", + "# their values using huristics and ensures that the faster coarse-to-fine \n", + "# rasterization method is used. Refer to docs/notes/renderer.md for an \n", + "# explanation of the difference between naive and coarse-to-fine rasterization. \n", + "raster_settings = RasterizationSettings(\n", + " image_size=128, \n", + " blur_radius=0.0, \n", + " faces_per_pixel=1, \n", + ")\n", + "\n", + "# Create a phong renderer by composing a rasterizer and a shader. The textured \n", + "# phong shader will interpolate the texture uv coordinates for each vertex, \n", + "# sample from a texture image and apply the Phong lighting model\n", + "renderer = MeshRenderer(\n", + " rasterizer=MeshRasterizer(\n", + " cameras=camera, \n", + " raster_settings=raster_settings\n", + " ),\n", + " shader=SoftPhongShader(\n", + " device=device, \n", + " cameras=camera,\n", + " lights=lights\n", + " )\n", + ")\n", + "\n", + "# Create a batch of meshes by repeating the cow mesh and associated textures. \n", + "# Meshes has a useful `extend` method which allows us do this very easily. \n", + "# This also extends the textures. \n", + "meshes = mesh.extend(num_views)\n", + "\n", + "# Render the cow mesh from each viewing angle\n", + "target_images = renderer(meshes, cameras=cameras, lights=lights)\n", + "\n", + "# Our multi-view cow dataset will be represented by these 2 lists of tensors,\n", + "# each of length num_views.\n", + "target_rgb = [target_images[i, ..., :3] for i in range(num_views)]\n", + "target_cameras = [OpenGLPerspectiveCameras(device=device, R=R[None, i, ...], \n", + " T=T[None, i, ...]) for i in range(num_views)]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "TppB4PVmR1Rc" + }, + "source": [ + "Visualize the dataset:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "HHE0CnbVR1Rd" + }, + "outputs": [], + "source": [ + "# RGB images\n", + "image_grid(target_images.cpu().numpy(), rows=4, cols=5, rgb=True)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "gOb4rYx65E8z" + }, + "source": [ + "Later in this tutorial, we will fit a mesh to the rendered RGB images, as well as to just images of just the cow silhouette. For the latter case, we will render a dataset of silhouette images. Most shaders in PyTorch3D will output an alpha channel along with the RGB image as a 4th channel in an RGBA image. The alpha channel encodes the probability that each pixel belongs to the foreground of the object. We contruct a soft silhouette shader to render this alpha channel." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "iP_g-nwX4exM" + }, + "outputs": [], + "source": [ + "# Rasterization settings for silhouette rendering \n", + "sigma = 1e-4\n", + "raster_settings_silhouette = RasterizationSettings(\n", + " image_size=128, \n", + " blur_radius=np.log(1. / 1e-4 - 1.)*sigma, \n", + " faces_per_pixel=50, \n", + ")\n", + "\n", + "# Silhouette renderer \n", + "renderer_silhouette = MeshRenderer(\n", + " rasterizer=MeshRasterizer(\n", + " cameras=camera, \n", + " raster_settings=raster_settings_silhouette\n", + " ),\n", + " shader=SoftSilhouetteShader()\n", + ")\n", + "\n", + "# Render silhouette images. The 3rd channel of the rendering output is \n", + "# the alpha/silhouette channel\n", + "silhouette_images = renderer_silhouette(meshes, cameras=cameras, lights=lights)\n", + "target_silhouette = [silhouette_images[i, ..., 3] for i in range(num_views)]\n", + "\n", + "# Visualize silhouette images\n", + "image_grid(silhouette_images.cpu().numpy(), rows=4, cols=5, rgb=False)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "t3qphI1ElUb5" + }, + "source": [ + "## 3. Mesh prediction via silhouette rendering\n", + "In the previous section, we created a dataset of images of multiple viewpoints of a cow. In this section, we predict a mesh by observing those target images without any knowledge of the ground truth cow mesh. We assume we know the position of the cameras and lighting.\n", + "\n", + "We first define some helper functions to visualize the results of our mesh prediction:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "eeWYHROrR1Rh" + }, + "outputs": [], + "source": [ + "# Show a visualization comparing the rendered predicted mesh to the ground truth \n", + "# mesh\n", + "def visualize_prediction(predicted_mesh, renderer=renderer_silhouette, \n", + " target_image=target_rgb[1], title='', \n", + " silhouette=False):\n", + " inds = 3 if silhouette else range(3)\n", + " predicted_images = renderer(predicted_mesh)\n", + " plt.figure(figsize=(20, 10))\n", + " plt.subplot(1, 2, 1)\n", + " plt.imshow(predicted_images[0, ..., inds].cpu().detach().numpy())\n", + "\n", + " plt.subplot(1, 2, 2)\n", + " plt.imshow(target_image.cpu().detach().numpy())\n", + " plt.title(title)\n", + " plt.grid(\"off\")\n", + " plt.axis(\"off\")\n", + "\n", + "# Plot losses as a function of optimization iteration\n", + "def plot_losses(losses):\n", + " fig = plt.figure(figsize=(13, 5))\n", + " ax = fig.gca()\n", + " for k, l in losses.items():\n", + " ax.plot(l['values'], label=k + \" loss\")\n", + " ax.legend(fontsize=\"16\")\n", + " ax.set_xlabel(\"Iteration\", fontsize=\"16\")\n", + " ax.set_ylabel(\"Loss\", fontsize=\"16\")\n", + " ax.set_title(\"Loss vs iterations\", fontsize=\"16\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "PpsvBpuMR1Ri" + }, + "source": [ + "Starting from a sphere mesh, we will learn offsets of each vertex such that the predicted mesh silhouette is more similar to the target silhouette image at each optimization step. We begin by loading our initial sphere mesh:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "i989ARH1R1Rj" + }, + "outputs": [], + "source": [ + "# We initialize the source shape to be a sphere of radius 1. \n", + "src_mesh = ico_sphere(4, device)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "f5xVtgLNDvC5" + }, + "source": [ + "We create a new differentiable renderer for rendering the silhouette of our predicted mesh:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "sXfjzgG4DsDJ" + }, + "outputs": [], + "source": [ + "# Rasterization settings for differentiable rendering, where the blur_radius\n", + "# initialization is based on Liu et al, 'Soft Rasterizer: A Differentiable \n", + "# Renderer for Image-based 3D Reasoning', ICCV 2019\n", + "sigma = 1e-4\n", + "raster_settings_soft = RasterizationSettings(\n", + " image_size=128, \n", + " blur_radius=np.log(1. / 1e-4 - 1.)*sigma, \n", + " faces_per_pixel=50, \n", + ")\n", + "\n", + "# Silhouette renderer \n", + "renderer_silhouette = MeshRenderer(\n", + " rasterizer=MeshRasterizer(\n", + " cameras=camera, \n", + " raster_settings=raster_settings_soft\n", + " ),\n", + " shader=SoftSilhouetteShader()\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "SGJKbCB6R1Rk" + }, + "source": [ + "We initialize settings, losses, and the optimizer that will be used to iteratively fit our mesh to the target silhouettes:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "0sLrKv_MEULh" + }, + "outputs": [], + "source": [ + "# Number of views to optimize over in each SGD iteration\n", + "num_views_per_iteration = 2\n", + "# Number of optimization steps\n", + "Niter = 2000\n", + "# Plot period for the losses\n", + "plot_period = 250\n", + "\n", + "%matplotlib inline\n", + "\n", + "# Optimize using rendered silhouette image loss, mesh edge loss, mesh normal \n", + "# consistency, and mesh laplacian smoothing\n", + "losses = {\"silhouette\": {\"weight\": 1.0, \"values\": []},\n", + " \"edge\": {\"weight\": 1.0, \"values\": []},\n", + " \"normal\": {\"weight\": 0.01, \"values\": []},\n", + " \"laplacian\": {\"weight\": 1.0, \"values\": []},\n", + " }\n", + "\n", + "# Losses to smooth / regularize the mesh shape\n", + "def update_mesh_shape_prior_losses(mesh, loss):\n", + " # and (b) the edge length of the predicted mesh\n", + " loss[\"edge\"] = mesh_edge_loss(mesh)\n", + " \n", + " # mesh normal consistency\n", + " loss[\"normal\"] = mesh_normal_consistency(mesh)\n", + " \n", + " # mesh laplacian smoothing\n", + " loss[\"laplacian\"] = mesh_laplacian_smoothing(mesh, method=\"uniform\")\n", + "\n", + "# We will learn to deform the source mesh by offsetting its vertices\n", + "# The shape of the deform parameters is equal to the total number of vertices in\n", + "# src_mesh\n", + "verts_shape = src_mesh.verts_packed().shape\n", + "deform_verts = torch.full(verts_shape, 0.0, device=device, requires_grad=True)\n", + "\n", + "# The optimizer\n", + "optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "QLc9zK8lEqFS" + }, + "source": [ + "We write an optimization loop to iteratively refine our predicted mesh from the sphere mesh into a mesh that matches the sillhouettes of the target images:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "gCfepfOoR1Rl" + }, + "outputs": [], + "source": [ + "loop = tqdm(range(Niter))\n", + "\n", + "for i in loop:\n", + " # Initialize optimizer\n", + " optimizer.zero_grad()\n", + " \n", + " # Deform the mesh\n", + " new_src_mesh = src_mesh.offset_verts(deform_verts)\n", + " \n", + " # Losses to smooth /regularize the mesh shape\n", + " loss = {k: torch.tensor(0.0, device=device) for k in losses}\n", + " update_mesh_shape_prior_losses(new_src_mesh, loss)\n", + " \n", + " # Compute the average silhouette loss over two random views, as the average \n", + " # squared L2 distance between the predicted silhouette and the target \n", + " # silhouette from our dataset\n", + " for j in np.random.permutation(num_views).tolist()[:num_views_per_iteration]:\n", + " images_predicted = renderer_silhouette(new_src_mesh, cameras=target_cameras[j], lights=lights)\n", + " predicted_silhouette = images_predicted[..., 3]\n", + " loss_silhouette = ((predicted_silhouette - target_silhouette[j]) ** 2).mean()\n", + " loss[\"silhouette\"] += loss_silhouette / num_views_per_iteration\n", + " \n", + " # Weighted sum of the losses\n", + " sum_loss = torch.tensor(0.0, device=device)\n", + " for k, l in loss.items():\n", + " sum_loss += l * losses[k][\"weight\"]\n", + " losses[k][\"values\"].append(l)\n", + " \n", + " # Print the losses\n", + " loop.set_description(\"total_loss = %.6f\" % sum_loss)\n", + " \n", + " # Plot mesh\n", + " if i % plot_period == 0:\n", + " visualize_prediction(new_src_mesh, title=\"iter: %d\" % i, silhouette=True,\n", + " target_image=target_silhouette[1])\n", + " \n", + " # Optimization step\n", + " sum_loss.backward()\n", + " optimizer.step()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "CX4huayKR1Rm", + "scrolled": true + }, + "outputs": [], + "source": [ + "visualize_prediction(new_src_mesh, silhouette=True, \n", + " target_image=target_silhouette[1])\n", + "plot_losses(losses)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "XJDsJQmrR1Ro" + }, + "source": [ + "## 3. Mesh and texture prediction via textured rendering\n", + "We can predict both the mesh and its texture if we add an additional loss based on the comparing a predicted rendered RGB image to the target image. As before, we start with a sphere mesh. We learn both translational offsets and RGB texture colors for each vertex in the sphere mesh. Since our loss is based on rendered RGB pixel values instead of just the silhouette, we use a **SoftPhongShader** instead of a **SoftSilhouetteShader**." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "aZObyIt9R1Ro" + }, + "outputs": [], + "source": [ + "# Rasterization settings for differentiable rendering, where the blur_radius\n", + "# initialization is based on Liu et al, 'Soft Rasterizer: A Differentiable \n", + "# Renderer for Image-based 3D Reasoning', ICCV 2019\n", + "sigma = 1e-4\n", + "raster_settings_soft = RasterizationSettings(\n", + " image_size=128, \n", + " blur_radius=np.log(1. / 1e-4 - 1.)*sigma, \n", + " faces_per_pixel=50, \n", + ")\n", + "\n", + "# Differentiable soft renderer using per vertex RGB colors for texture\n", + "renderer_textured = MeshRenderer(\n", + " rasterizer=MeshRasterizer(\n", + " cameras=camera, \n", + " raster_settings=raster_settings_soft\n", + " ),\n", + " shader=SoftPhongShader(device=device, \n", + " cameras=camera,\n", + " lights=lights)\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "NM7gJux8GMQX" + }, + "source": [ + "We initialize settings, losses, and the optimizer that will be used to iteratively fit our mesh to the target RGB images:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "BS6LAQquF3wq" + }, + "outputs": [], + "source": [ + "# Number of views to optimize over in each SGD iteration\n", + "num_views_per_iteration = 2\n", + "# Number of optimization steps\n", + "Niter = 2000\n", + "# Plot period for the losses\n", + "plot_period = 250\n", + "\n", + "%matplotlib inline\n", + "\n", + "# Optimize using rendered RGB image loss, rendered silhouette image loss, mesh \n", + "# edge loss, mesh normal consistency, and mesh laplacian smoothing\n", + "losses = {\"rgb\": {\"weight\": 1.0, \"values\": []},\n", + " \"silhouette\": {\"weight\": 1.0, \"values\": []},\n", + " \"edge\": {\"weight\": 1.0, \"values\": []},\n", + " \"normal\": {\"weight\": 0.01, \"values\": []},\n", + " \"laplacian\": {\"weight\": 1.0, \"values\": []},\n", + " }\n", + "\n", + "# We will learn to deform the source mesh by offsetting its vertices\n", + "# The shape of the deform parameters is equal to the total number of vertices in \n", + "# src_mesh\n", + "verts_shape = src_mesh.verts_packed().shape\n", + "deform_verts = torch.full(verts_shape, 0.0, device=device, requires_grad=True)\n", + "\n", + "# We will also learn per vertex colors for our sphere mesh that define texture \n", + "# of the mesh\n", + "sphere_verts_rgb = torch.full([1, verts_shape[0], 3], 0.5, device=device, requires_grad=True)\n", + "\n", + "# The optimizer\n", + "optimizer = torch.optim.SGD([deform_verts, sphere_verts_rgb], lr=1.0, momentum=0.9)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "tzIAycuUR1Rq" + }, + "source": [ + "We write an optimization loop to iteratively refine our predicted mesh and its vertex colors from the sphere mesh into a mesh that matches the target images:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "EKEH2p8-R1Rr" + }, + "outputs": [], + "source": [ + "loop = tqdm(range(Niter))\n", + "\n", + "for i in loop:\n", + " # Initialize optimizer\n", + " optimizer.zero_grad()\n", + " \n", + " # Deform the mesh\n", + " new_src_mesh = src_mesh.offset_verts(deform_verts)\n", + " \n", + " # Add per vertex colors to texture the mesh\n", + " new_src_mesh.textures = TexturesVertex(verts_features=sphere_verts_rgb) \n", + " \n", + " # Losses to smooth /regularize the mesh shape\n", + " loss = {k: torch.tensor(0.0, device=device) for k in losses}\n", + " update_mesh_shape_prior_losses(new_src_mesh, loss)\n", + " \n", + " # Randomly select two views to optimize over in this iteration. Compared\n", + " # to using just one view, this helps resolve ambiguities between updating\n", + " # mesh shape vs. updating mesh texture\n", + " for j in np.random.permutation(num_views).tolist()[:num_views_per_iteration]:\n", + " images_predicted = renderer_textured(new_src_mesh, cameras=target_cameras[j], lights=lights)\n", + "\n", + " # Squared L2 distance between the predicted silhouette and the target \n", + " # silhouette from our dataset\n", + " predicted_silhouette = images_predicted[..., 3]\n", + " loss_silhouette = ((predicted_silhouette - target_silhouette[j]) ** 2).mean()\n", + " loss[\"silhouette\"] += loss_silhouette / num_views_per_iteration\n", + " \n", + " # Squared L2 distance between the predicted RGB image and the target \n", + " # image from our dataset\n", + " predicted_rgb = images_predicted[..., :3]\n", + " loss_rgb = ((predicted_rgb - target_rgb[j]) ** 2).mean()\n", + " loss[\"rgb\"] += loss_rgb / num_views_per_iteration\n", + " \n", + " # Weighted sum of the losses\n", + " sum_loss = torch.tensor(0.0, device=device)\n", + " for k, l in loss.items():\n", + " sum_loss += l * losses[k][\"weight\"]\n", + " losses[k][\"values\"].append(l)\n", + " \n", + " # Print the losses\n", + " loop.set_description(\"total_loss = %.6f\" % sum_loss)\n", + " \n", + " # Plot mesh\n", + " if i % plot_period == 0:\n", + " visualize_prediction(new_src_mesh, renderer=renderer_textured, title=\"iter: %d\" % i, silhouette=False)\n", + " \n", + " # Optimization step\n", + " sum_loss.backward()\n", + " optimizer.step()\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "2qTcHO4rR1Rs", + "scrolled": true + }, + "outputs": [], + "source": [ + "visualize_prediction(new_src_mesh, renderer=renderer_textured, silhouette=False)\n", + "plot_losses(losses)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "akBOm_xcNUms" + }, + "source": [ + "Save the final predicted mesh:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "dXoIsGyhxRyK" + }, + "source": [ + "## 4. Save the final predicted mesh" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "OQGhV-psKna8" + }, + "outputs": [], + "source": [ + "# Fetch the verts and faces of the final predicted mesh\n", + "final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0)\n", + "\n", + "# Scale normalize back to the original target size\n", + "final_verts = final_verts * scale + center\n", + "\n", + "# Store the predicted mesh using save_obj\n", + "final_obj = os.path.join('./', 'final_model.obj')\n", + "save_obj(final_obj, final_verts, final_faces)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "MtKYp0B6R1Ru" + }, + "source": [ + "## 5. Conclusion\n", + "In this tutorial, we learned how to load a textured mesh from an obj file, create a synthetic dataset by rendering the mesh from multiple viewpoints. We showed how to set up an optimization loop to fit a mesh to the observed dataset images based on a rendered silhouette loss. We then augmented this optimization loop with an additional loss based on rendered RGB images, which allowed us to predict both a mesh and its texture." + ] + } + ], + "metadata": { + "accelerator": "GPU", + "anp_metadata": { + "path": "fbsource/fbcode/vision/fair/pytorch3d/docs/tutorials/fit_textured_mesh.ipynb" + }, + "bento_stylesheets": { + "bento/extensions/flow/main.css": true, + "bento/extensions/kernel_selector/main.css": true, + "bento/extensions/kernel_ui/main.css": true, + "bento/extensions/new_kernel/main.css": true, + "bento/extensions/system_usage/main.css": true, + "bento/extensions/theme/main.css": true + }, + "colab": { + "name": "fit_textured_mesh.ipynb", + "provenance": [], + "toc_visible": true + }, + "disseminate_notebook_info": { + "backup_notebook_id": "781874812352022" + }, + "kernelspec": { + "display_name": "intro_to_cv", + "language": "python", + "name": "bento_kernel_intro_to_cv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.5+" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/files/fit_textured_mesh.py b/files/fit_textured_mesh.py new file mode 100644 index 00000000..9b00136f --- /dev/null +++ b/files/fit_textured_mesh.py @@ -0,0 +1,580 @@ +#!/usr/bin/env python +# coding: utf-8 + +# In[ ]: + + +# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved. + + +# # Fit a mesh via rendering +# +# This tutorial shows how to: +# - Load a mesh and textures from an `.obj` file. +# - Create a synthetic dataset by rendering a textured mesh from multiple viewpoints +# - Fit a mesh to the observed synthetic images using differential silhouette rendering +# - Fit a mesh and its textures using differential textured rendering + +# ## 0. Install and Import modules + +# If `torch`, `torchvision` and `pytorch3d` are not installed, run the following cell: + +# In[ ]: + + +get_ipython().system('pip install torch torchvision') +import sys +import torch +if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'): + get_ipython().system('pip install pytorch3d') +else: + get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") + + +# In[ ]: + + +import os +import torch +import matplotlib.pyplot as plt +from skimage.io import imread + +from pytorch3d.utils import ico_sphere +import numpy as np +from tqdm.notebook import tqdm + +# Util function for loading meshes +from pytorch3d.io import load_objs_as_meshes, save_obj + +from pytorch3d.loss import ( + chamfer_distance, + mesh_edge_loss, + mesh_laplacian_smoothing, + mesh_normal_consistency, +) + +# Data structures and functions for rendering +from pytorch3d.structures import Meshes +from pytorch3d.renderer import ( + look_at_view_transform, + OpenGLPerspectiveCameras, + PointLights, + DirectionalLights, + Materials, + RasterizationSettings, + MeshRenderer, + MeshRasterizer, + SoftPhongShader, + SoftSilhouetteShader, + SoftPhongShader, + TexturesVertex +) + +# add path for demo utils functions +import sys +import os +sys.path.append(os.path.abspath('')) + + +# If using **Google Colab**, fetch the utils file for plotting image grids: + +# In[ ]: + + +get_ipython().system('wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py') +from plot_image_grid import image_grid + + +# OR if running **locally** uncomment and run the following cell: + +# In[ ]: + + +# from utils.plot_image_grid import image_grid + + +# ### 1. Load a mesh and texture file +# +# Load an `.obj` file and it's associated `.mtl` file and create a **Textures** and **Meshes** object. +# +# **Meshes** is a unique datastructure provided in PyTorch3D for working with batches of meshes of different sizes. +# +# **TexturesVertex** is an auxillary datastructure for storing vertex rgb texture information about meshes. +# +# **Meshes** has several class methods which are used throughout the rendering pipeline. + +# If running this notebook using **Google Colab**, run the following cell to fetch the mesh obj and texture files and save it at the path `data/cow_mesh`: +# If running locally, the data is already available at the correct path. + +# In[ ]: + + +get_ipython().system('mkdir -p data/cow_mesh') +get_ipython().system('wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.obj') +get_ipython().system('wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.mtl') +get_ipython().system('wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png') + + +# In[ ]: + + +# Setup +if torch.cuda.is_available(): + device = torch.device("cuda:0") + torch.cuda.set_device(device) +else: + device = torch.device("cpu") + +# Set paths +DATA_DIR = "./data" +obj_filename = os.path.join(DATA_DIR, "cow_mesh/cow.obj") + +# Load obj file +mesh = load_objs_as_meshes([obj_filename], device=device) + +# We scale normalize and center the target mesh to fit in a sphere of radius 1 +# centered at (0,0,0). (scale, center) will be used to bring the predicted mesh +# to its original center and scale. Note that normalizing the target mesh, +# speeds up the optimization but is not necessary! +verts = mesh.verts_packed() +N = verts.shape[0] +center = verts.mean(0) +scale = max((verts - center).abs().max(0)[0]) +mesh.offset_verts_(-center.expand(N, 3)) +mesh.scale_verts_((1.0 / float(scale))); + + +# ## 2. Dataset Creation +# +# We sample different camera positions that encode multiple viewpoints of the cow. We create a renderer with a shader that performs texture map interpolation. We render a synthetic dataset of images of the textured cow mesh from multiple viewpoints. +# + +# In[ ]: + + +# the number of different viewpoints from which we want to render the mesh. +num_views = 20 + +# Get a batch of viewing angles. +elev = torch.linspace(0, 360, num_views) +azim = torch.linspace(-180, 180, num_views) + +# Place a point light in front of the object. As mentioned above, the front of +# the cow is facing the -z direction. +lights = PointLights(device=device, location=[[0.0, 0.0, -3.0]]) + +# Initialize an OpenGL perspective camera that represents a batch of different +# viewing angles. All the cameras helper methods support mixed type inputs and +# broadcasting. So we can view the camera from the a distance of dist=2.7, and +# then specify elevation and azimuth angles for each viewpoint as tensors. +R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim) +cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T) + +# We arbitrarily choose one particular view that will be used to visualize +# results +camera = OpenGLPerspectiveCameras(device=device, R=R[None, 1, ...], + T=T[None, 1, ...]) + +# Define the settings for rasterization and shading. Here we set the output +# image to be of size 128X128. As we are rendering images for visualization +# purposes only we will set faces_per_pixel=1 and blur_radius=0.0. Refer to +# rasterize_meshes.py for explanations of these parameters. We also leave +# bin_size and max_faces_per_bin to their default values of None, which sets +# their values using huristics and ensures that the faster coarse-to-fine +# rasterization method is used. Refer to docs/notes/renderer.md for an +# explanation of the difference between naive and coarse-to-fine rasterization. +raster_settings = RasterizationSettings( + image_size=128, + blur_radius=0.0, + faces_per_pixel=1, +) + +# Create a phong renderer by composing a rasterizer and a shader. The textured +# phong shader will interpolate the texture uv coordinates for each vertex, +# sample from a texture image and apply the Phong lighting model +renderer = MeshRenderer( + rasterizer=MeshRasterizer( + cameras=camera, + raster_settings=raster_settings + ), + shader=SoftPhongShader( + device=device, + cameras=camera, + lights=lights + ) +) + +# Create a batch of meshes by repeating the cow mesh and associated textures. +# Meshes has a useful `extend` method which allows us do this very easily. +# This also extends the textures. +meshes = mesh.extend(num_views) + +# Render the cow mesh from each viewing angle +target_images = renderer(meshes, cameras=cameras, lights=lights) + +# Our multi-view cow dataset will be represented by these 2 lists of tensors, +# each of length num_views. +target_rgb = [target_images[i, ..., :3] for i in range(num_views)] +target_cameras = [OpenGLPerspectiveCameras(device=device, R=R[None, i, ...], + T=T[None, i, ...]) for i in range(num_views)] + + +# Visualize the dataset: + +# In[ ]: + + +# RGB images +image_grid(target_images.cpu().numpy(), rows=4, cols=5, rgb=True) +plt.show() + + +# Later in this tutorial, we will fit a mesh to the rendered RGB images, as well as to just images of just the cow silhouette. For the latter case, we will render a dataset of silhouette images. Most shaders in PyTorch3D will output an alpha channel along with the RGB image as a 4th channel in an RGBA image. The alpha channel encodes the probability that each pixel belongs to the foreground of the object. We contruct a soft silhouette shader to render this alpha channel. + +# In[ ]: + + +# Rasterization settings for silhouette rendering +sigma = 1e-4 +raster_settings_silhouette = RasterizationSettings( + image_size=128, + blur_radius=np.log(1. / 1e-4 - 1.)*sigma, + faces_per_pixel=50, +) + +# Silhouette renderer +renderer_silhouette = MeshRenderer( + rasterizer=MeshRasterizer( + cameras=camera, + raster_settings=raster_settings_silhouette + ), + shader=SoftSilhouetteShader() +) + +# Render silhouette images. The 3rd channel of the rendering output is +# the alpha/silhouette channel +silhouette_images = renderer_silhouette(meshes, cameras=cameras, lights=lights) +target_silhouette = [silhouette_images[i, ..., 3] for i in range(num_views)] + +# Visualize silhouette images +image_grid(silhouette_images.cpu().numpy(), rows=4, cols=5, rgb=False) +plt.show() + + +# ## 3. Mesh prediction via silhouette rendering +# In the previous section, we created a dataset of images of multiple viewpoints of a cow. In this section, we predict a mesh by observing those target images without any knowledge of the ground truth cow mesh. We assume we know the position of the cameras and lighting. +# +# We first define some helper functions to visualize the results of our mesh prediction: + +# In[ ]: + + +# Show a visualization comparing the rendered predicted mesh to the ground truth +# mesh +def visualize_prediction(predicted_mesh, renderer=renderer_silhouette, + target_image=target_rgb[1], title='', + silhouette=False): + inds = 3 if silhouette else range(3) + predicted_images = renderer(predicted_mesh) + plt.figure(figsize=(20, 10)) + plt.subplot(1, 2, 1) + plt.imshow(predicted_images[0, ..., inds].cpu().detach().numpy()) + + plt.subplot(1, 2, 2) + plt.imshow(target_image.cpu().detach().numpy()) + plt.title(title) + plt.grid("off") + plt.axis("off") + +# Plot losses as a function of optimization iteration +def plot_losses(losses): + fig = plt.figure(figsize=(13, 5)) + ax = fig.gca() + for k, l in losses.items(): + ax.plot(l['values'], label=k + " loss") + ax.legend(fontsize="16") + ax.set_xlabel("Iteration", fontsize="16") + ax.set_ylabel("Loss", fontsize="16") + ax.set_title("Loss vs iterations", fontsize="16") + + +# Starting from a sphere mesh, we will learn offsets of each vertex such that the predicted mesh silhouette is more similar to the target silhouette image at each optimization step. We begin by loading our initial sphere mesh: + +# In[ ]: + + +# We initialize the source shape to be a sphere of radius 1. +src_mesh = ico_sphere(4, device) + + +# We create a new differentiable renderer for rendering the silhouette of our predicted mesh: + +# In[ ]: + + +# Rasterization settings for differentiable rendering, where the blur_radius +# initialization is based on Liu et al, 'Soft Rasterizer: A Differentiable +# Renderer for Image-based 3D Reasoning', ICCV 2019 +sigma = 1e-4 +raster_settings_soft = RasterizationSettings( + image_size=128, + blur_radius=np.log(1. / 1e-4 - 1.)*sigma, + faces_per_pixel=50, +) + +# Silhouette renderer +renderer_silhouette = MeshRenderer( + rasterizer=MeshRasterizer( + cameras=camera, + raster_settings=raster_settings_soft + ), + shader=SoftSilhouetteShader() +) + + +# We initialize settings, losses, and the optimizer that will be used to iteratively fit our mesh to the target silhouettes: + +# In[ ]: + + +# Number of views to optimize over in each SGD iteration +num_views_per_iteration = 2 +# Number of optimization steps +Niter = 2000 +# Plot period for the losses +plot_period = 250 + +get_ipython().run_line_magic('matplotlib', 'inline') + +# Optimize using rendered silhouette image loss, mesh edge loss, mesh normal +# consistency, and mesh laplacian smoothing +losses = {"silhouette": {"weight": 1.0, "values": []}, + "edge": {"weight": 1.0, "values": []}, + "normal": {"weight": 0.01, "values": []}, + "laplacian": {"weight": 1.0, "values": []}, + } + +# Losses to smooth / regularize the mesh shape +def update_mesh_shape_prior_losses(mesh, loss): + # and (b) the edge length of the predicted mesh + loss["edge"] = mesh_edge_loss(mesh) + + # mesh normal consistency + loss["normal"] = mesh_normal_consistency(mesh) + + # mesh laplacian smoothing + loss["laplacian"] = mesh_laplacian_smoothing(mesh, method="uniform") + +# We will learn to deform the source mesh by offsetting its vertices +# The shape of the deform parameters is equal to the total number of vertices in +# src_mesh +verts_shape = src_mesh.verts_packed().shape +deform_verts = torch.full(verts_shape, 0.0, device=device, requires_grad=True) + +# The optimizer +optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9) + + +# We write an optimization loop to iteratively refine our predicted mesh from the sphere mesh into a mesh that matches the sillhouettes of the target images: + +# In[ ]: + + +loop = tqdm(range(Niter)) + +for i in loop: + # Initialize optimizer + optimizer.zero_grad() + + # Deform the mesh + new_src_mesh = src_mesh.offset_verts(deform_verts) + + # Losses to smooth /regularize the mesh shape + loss = {k: torch.tensor(0.0, device=device) for k in losses} + update_mesh_shape_prior_losses(new_src_mesh, loss) + + # Compute the average silhouette loss over two random views, as the average + # squared L2 distance between the predicted silhouette and the target + # silhouette from our dataset + for j in np.random.permutation(num_views).tolist()[:num_views_per_iteration]: + images_predicted = renderer_silhouette(new_src_mesh, cameras=target_cameras[j], lights=lights) + predicted_silhouette = images_predicted[..., 3] + loss_silhouette = ((predicted_silhouette - target_silhouette[j]) ** 2).mean() + loss["silhouette"] += loss_silhouette / num_views_per_iteration + + # Weighted sum of the losses + sum_loss = torch.tensor(0.0, device=device) + for k, l in loss.items(): + sum_loss += l * losses[k]["weight"] + losses[k]["values"].append(l) + + # Print the losses + loop.set_description("total_loss = %.6f" % sum_loss) + + # Plot mesh + if i % plot_period == 0: + visualize_prediction(new_src_mesh, title="iter: %d" % i, silhouette=True, + target_image=target_silhouette[1]) + + # Optimization step + sum_loss.backward() + optimizer.step() + + +# In[ ]: + + +visualize_prediction(new_src_mesh, silhouette=True, + target_image=target_silhouette[1]) +plot_losses(losses) + + +# ## 3. Mesh and texture prediction via textured rendering +# We can predict both the mesh and its texture if we add an additional loss based on the comparing a predicted rendered RGB image to the target image. As before, we start with a sphere mesh. We learn both translational offsets and RGB texture colors for each vertex in the sphere mesh. Since our loss is based on rendered RGB pixel values instead of just the silhouette, we use a **SoftPhongShader** instead of a **SoftSilhouetteShader**. + +# In[ ]: + + +# Rasterization settings for differentiable rendering, where the blur_radius +# initialization is based on Liu et al, 'Soft Rasterizer: A Differentiable +# Renderer for Image-based 3D Reasoning', ICCV 2019 +sigma = 1e-4 +raster_settings_soft = RasterizationSettings( + image_size=128, + blur_radius=np.log(1. / 1e-4 - 1.)*sigma, + faces_per_pixel=50, +) + +# Differentiable soft renderer using per vertex RGB colors for texture +renderer_textured = MeshRenderer( + rasterizer=MeshRasterizer( + cameras=camera, + raster_settings=raster_settings_soft + ), + shader=SoftPhongShader(device=device, + cameras=camera, + lights=lights) +) + + +# We initialize settings, losses, and the optimizer that will be used to iteratively fit our mesh to the target RGB images: + +# In[ ]: + + +# Number of views to optimize over in each SGD iteration +num_views_per_iteration = 2 +# Number of optimization steps +Niter = 2000 +# Plot period for the losses +plot_period = 250 + +get_ipython().run_line_magic('matplotlib', 'inline') + +# Optimize using rendered RGB image loss, rendered silhouette image loss, mesh +# edge loss, mesh normal consistency, and mesh laplacian smoothing +losses = {"rgb": {"weight": 1.0, "values": []}, + "silhouette": {"weight": 1.0, "values": []}, + "edge": {"weight": 1.0, "values": []}, + "normal": {"weight": 0.01, "values": []}, + "laplacian": {"weight": 1.0, "values": []}, + } + +# We will learn to deform the source mesh by offsetting its vertices +# The shape of the deform parameters is equal to the total number of vertices in +# src_mesh +verts_shape = src_mesh.verts_packed().shape +deform_verts = torch.full(verts_shape, 0.0, device=device, requires_grad=True) + +# We will also learn per vertex colors for our sphere mesh that define texture +# of the mesh +sphere_verts_rgb = torch.full([1, verts_shape[0], 3], 0.5, device=device, requires_grad=True) + +# The optimizer +optimizer = torch.optim.SGD([deform_verts, sphere_verts_rgb], lr=1.0, momentum=0.9) + + +# We write an optimization loop to iteratively refine our predicted mesh and its vertex colors from the sphere mesh into a mesh that matches the target images: + +# In[ ]: + + +loop = tqdm(range(Niter)) + +for i in loop: + # Initialize optimizer + optimizer.zero_grad() + + # Deform the mesh + new_src_mesh = src_mesh.offset_verts(deform_verts) + + # Add per vertex colors to texture the mesh + new_src_mesh.textures = TexturesVertex(verts_features=sphere_verts_rgb) + + # Losses to smooth /regularize the mesh shape + loss = {k: torch.tensor(0.0, device=device) for k in losses} + update_mesh_shape_prior_losses(new_src_mesh, loss) + + # Randomly select two views to optimize over in this iteration. Compared + # to using just one view, this helps resolve ambiguities between updating + # mesh shape vs. updating mesh texture + for j in np.random.permutation(num_views).tolist()[:num_views_per_iteration]: + images_predicted = renderer_textured(new_src_mesh, cameras=target_cameras[j], lights=lights) + + # Squared L2 distance between the predicted silhouette and the target + # silhouette from our dataset + predicted_silhouette = images_predicted[..., 3] + loss_silhouette = ((predicted_silhouette - target_silhouette[j]) ** 2).mean() + loss["silhouette"] += loss_silhouette / num_views_per_iteration + + # Squared L2 distance between the predicted RGB image and the target + # image from our dataset + predicted_rgb = images_predicted[..., :3] + loss_rgb = ((predicted_rgb - target_rgb[j]) ** 2).mean() + loss["rgb"] += loss_rgb / num_views_per_iteration + + # Weighted sum of the losses + sum_loss = torch.tensor(0.0, device=device) + for k, l in loss.items(): + sum_loss += l * losses[k]["weight"] + losses[k]["values"].append(l) + + # Print the losses + loop.set_description("total_loss = %.6f" % sum_loss) + + # Plot mesh + if i % plot_period == 0: + visualize_prediction(new_src_mesh, renderer=renderer_textured, title="iter: %d" % i, silhouette=False) + + # Optimization step + sum_loss.backward() + optimizer.step() + + +# In[ ]: + + +visualize_prediction(new_src_mesh, renderer=renderer_textured, silhouette=False) +plot_losses(losses) + + +# Save the final predicted mesh: + +# ## 4. Save the final predicted mesh + +# In[ ]: + + +# Fetch the verts and faces of the final predicted mesh +final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0) + +# Scale normalize back to the original target size +final_verts = final_verts * scale + center + +# Store the predicted mesh using save_obj +final_obj = os.path.join('./', 'final_model.obj') +save_obj(final_obj, final_verts, final_faces) + + +# ## 5. Conclusion +# In this tutorial, we learned how to load a textured mesh from an obj file, create a synthetic dataset by rendering the mesh from multiple viewpoints. We showed how to set up an optimization loop to fit a mesh to the observed dataset images based on a rendered silhouette loss. We then augmented this optimization loop with an additional loss based on rendered RGB images, which allowed us to predict both a mesh and its texture. diff --git a/files/render_textured_meshes.ipynb b/files/render_textured_meshes.ipynb index 7edb7f3e..1e3033cc 100644 --- a/files/render_textured_meshes.ipynb +++ b/files/render_textured_meshes.ipynb @@ -2,11 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 0, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "_Ip8kp4TfBLZ" }, "outputs": [], @@ -53,30 +52,33 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 717 }, "colab_type": "code", - "collapsed": true, "id": "musUWTglgxSB", "outputId": "16d1a1b2-3f7f-43ed-ca28-a4d236cc0572" }, "outputs": [], "source": [ "!pip install torch torchvision\n", - "!pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" + "import sys\n", + "import torch\n", + "if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):\n", + " !pip install pytorch3d\n", + "else:\n", + " !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'" ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "nX99zdoffBLg" }, "outputs": [], @@ -87,20 +89,21 @@ "from skimage.io import imread\n", "\n", "# Util function for loading meshes\n", - "from pytorch3d.io import load_objs_as_meshes\n", + "from pytorch3d.io import load_objs_as_meshes, load_obj\n", "\n", "# Data structures and functions for rendering\n", - "from pytorch3d.structures import Meshes, Textures\n", + "from pytorch3d.structures import Meshes\n", "from pytorch3d.renderer import (\n", " look_at_view_transform,\n", - " OpenGLPerspectiveCameras, \n", + " FoVPerspectiveCameras, \n", " PointLights, \n", " DirectionalLights, \n", " Materials, \n", " RasterizationSettings, \n", " MeshRenderer, \n", " MeshRasterizer, \n", - " TexturedSoftPhongShader\n", + " SoftPhongShader,\n", + " TexturesUV\n", ")\n", "\n", "# add path for demo utils functions \n", @@ -121,14 +124,13 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 204 }, "colab_type": "code", - "collapsed": true, "id": "HZozr3Pmho-5", "outputId": "be5eb60d-5f65-4db1-cca0-44ee68c8f5fd" }, @@ -150,11 +152,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "paJ4Im8ahl7O" }, "outputs": [], @@ -166,7 +167,6 @@ "cell_type": "markdown", "metadata": { "colab_type": "text", - "collapsed": true, "id": "5jGq772XfBLk" }, "source": [ @@ -176,7 +176,7 @@ "\n", "**Meshes** is a unique datastructure provided in PyTorch3D for working with batches of meshes of different sizes. \n", "\n", - "**Textures** is an auxillary datastructure for storing texture information about meshes. \n", + "**TexturesUV** is an auxillary datastructure for storing vertex uv and texture maps for meshes. \n", "\n", "**Meshes** has several class methods which are used throughout the rendering pipeline." ] @@ -194,14 +194,13 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 578 }, "colab_type": "code", - "collapsed": true, "id": "tTm0cVuOjb1W", "outputId": "6cd7e2ec-65e1-4dcc-99e8-c347bc504f0a" }, @@ -215,18 +214,20 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "gi5Kd0GafBLl" }, "outputs": [], "source": [ "# Setup\n", - "device = torch.device(\"cuda:0\")\n", - "torch.cuda.set_device(device)\n", + "if torch.cuda.is_available():\n", + " device = torch.device(\"cuda:0\")\n", + " torch.cuda.set_device(device)\n", + "else:\n", + " device = torch.device(\"cpu\")\n", "\n", "# Set paths\n", "DATA_DIR = \"./data\"\n", @@ -249,7 +250,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -259,21 +260,7 @@ "id": "YipUhrIHfBLq", "outputId": "48987b1d-5cc1-4c2a-cb3c-713d64f6a38d" }, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140631044165712", - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.figure(figsize=(7,7))\n", "plt.imshow(texture_image.squeeze().cpu().numpy())\n", @@ -297,20 +284,19 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "dX466mWnfBLv" }, "outputs": [], "source": [ - "# Initialize an OpenGL perspective camera.\n", + "# Initialize a camera.\n", "# With world coordinates +Y up, +X left and +Z in, the front of the cow is facing the -Z direction. \n", "# So we move the camera by 180 in the azimuth direction so it is facing the front of the cow. \n", "R, T = look_at_view_transform(2.7, 0, 180) \n", - "cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)\n", + "cameras = FoVPerspectiveCameras(device=device, R=R, T=T)\n", "\n", "# Define the settings for rasterization and shading. Here we set the output image to be of size\n", "# 512x512. As we are rendering images for visualization purposes only we will set faces_per_pixel=1\n", @@ -322,8 +308,6 @@ " image_size=512, \n", " blur_radius=0.0, \n", " faces_per_pixel=1, \n", - " bin_size = None, # this setting controls whether naive or coarse-to-fine rasterization is used\n", - " max_faces_per_bin = None # this setting is for coarse rasterization\n", ")\n", "\n", "# Place a point light in front of the object. As mentioned above, the front of the cow is facing the \n", @@ -338,7 +322,7 @@ " cameras=cameras, \n", " raster_settings=raster_settings\n", " ),\n", - " shader=TexturedSoftPhongShader(\n", + " shader=SoftPhongShader(\n", " device=device, \n", " cameras=cameras,\n", " lights=lights\n", @@ -368,7 +352,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -378,21 +362,7 @@ "id": "gBLZH8iUfBL1", "outputId": "cc3cd3f0-189e-4497-ce47-e64b4da542e8" }, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140630998081360", - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "images = renderer(mesh)\n", "plt.figure(figsize=(10, 10))\n", @@ -419,11 +389,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "BdWkkeibfBL6" }, "outputs": [], @@ -435,7 +404,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -445,21 +414,7 @@ "id": "UmV3j1YffBL9", "outputId": "2e8edca0-5bd8-4a2f-a160-83c4b0520123" }, - "outputs": [ - { - "data": { - "image/png": "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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "140630596295504", - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.figure(figsize=(10, 10))\n", "plt.imshow(images[0, ..., :3].cpu().numpy())\n", @@ -485,18 +440,17 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "4mYXYziefBMB" }, "outputs": [], "source": [ "# Rotate the object by increasing the elevation and azimuth angles\n", "R, T = look_at_view_transform(dist=2.7, elev=10, azim=-150)\n", - "cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)\n", + "cameras = FoVPerspectiveCameras(device=device, R=R, T=T)\n", "\n", "# Move the light location so the light is shining on the cow's face. \n", "lights.location = torch.tensor([[2.0, 2.0, -2.0]], device=device)\n", @@ -514,7 +468,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/", @@ -524,20 +478,7 @@ "id": "rHIxIfh5fBME", "outputId": "1ca2d337-2983-478f-b3c9-d64b84ba1a31" }, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAi0AAAIuCAYAAABzfTjcAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "139721054514064" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "plt.figure(figsize=(10, 10))\n", "plt.imshow(images[0, ..., :3].cpu().numpy())\n", @@ -560,11 +501,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "CDQKebNNfBMI" }, "outputs": [], @@ -585,7 +525,7 @@ "# view the camera from the same distance and specify dist=2.7 as a float,\n", "# and then specify elevation and azimuth angles for each viewpoint as tensors. \n", "R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim)\n", - "cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)\n", + "cameras = FoVPerspectiveCameras(device=device, R=R, T=T)\n", "\n", "# Move the light back in front of the cow which is facing the -z direction.\n", "lights.location = torch.tensor([[0.0, 0.0, -3.0]], device=device)" @@ -593,11 +533,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": { "colab": {}, "colab_type": "code", - "collapsed": true, "id": "gyYJCwEDfBML" }, "outputs": [], @@ -609,22 +548,9 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAABBAAAAKWCAYAAADwXGoPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\npaZ7s1oAAAAASUVORK5CYII=\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "bento_obj_id": "139721051438480" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "image_grid(images.cpu().numpy(), rows=4, cols=5, rgb=True)" ] @@ -643,6 +569,9 @@ ], "metadata": { "accelerator": "GPU", + "anp_metadata": { + "path": "fbsource/fbcode/vision/fair/pytorch3d/docs/tutorials/render_textured_meshes.ipynb" + }, "bento_stylesheets": { "bento/extensions/flow/main.css": true, "bento/extensions/kernel_selector/main.css": true, @@ -655,10 +584,13 @@ "name": "render_textured_meshes.ipynb", "provenance": [] }, + "disseminate_notebook_info": { + "backup_notebook_id": "569222367081034" + }, "kernelspec": { - "display_name": "pytorch3d (local)", + "display_name": "intro_to_cv", "language": "python", - "name": "pytorch3d_local" + "name": "bento_kernel_intro_to_cv" }, "language_info": { "codemirror_mode": { diff --git a/files/render_textured_meshes.py b/files/render_textured_meshes.py index d218f06f..3c6c7444 100644 --- a/files/render_textured_meshes.py +++ b/files/render_textured_meshes.py @@ -1,4 +1,4 @@ - +#!/usr/bin/env python # coding: utf-8 # In[ ]: @@ -20,14 +20,19 @@ # If `torch`, `torchvision` and `pytorch3d` are not installed, run the following cell: -# In[1]: +# In[ ]: get_ipython().system('pip install torch torchvision') -get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") +import sys +import torch +if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'): + get_ipython().system('pip install pytorch3d') +else: + get_ipython().system("pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'") -# In[1]: +# In[ ]: import os @@ -36,20 +41,21 @@ import matplotlib.pyplot as plt from skimage.io import imread # Util function for loading meshes -from pytorch3d.io import load_objs_as_meshes +from pytorch3d.io import load_objs_as_meshes, load_obj # Data structures and functions for rendering -from pytorch3d.structures import Meshes, Textures +from pytorch3d.structures import Meshes from pytorch3d.renderer import ( look_at_view_transform, - OpenGLPerspectiveCameras, + FoVPerspectiveCameras, PointLights, DirectionalLights, Materials, RasterizationSettings, MeshRenderer, MeshRasterizer, - TexturedSoftPhongShader + SoftPhongShader, + TexturesUV ) # add path for demo utils functions @@ -60,7 +66,7 @@ sys.path.append(os.path.abspath('')) # If using **Google Colab**, fetch the utils file for plotting image grids: -# In[2]: +# In[ ]: get_ipython().system('wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py') @@ -69,7 +75,7 @@ from plot_image_grid import image_grid # OR if running **locally** uncomment and run the following cell: -# In[13]: +# In[ ]: # from utils import image_grid @@ -81,14 +87,14 @@ from plot_image_grid import image_grid # # **Meshes** is a unique datastructure provided in PyTorch3D for working with batches of meshes of different sizes. # -# **Textures** is an auxillary datastructure for storing texture information about meshes. +# **TexturesUV** is an auxillary datastructure for storing vertex uv and texture maps for meshes. # # **Meshes** has several class methods which are used throughout the rendering pipeline. # If running this notebook using **Google Colab**, run the following cell to fetch the mesh obj and texture files and save it at the path `data/cow_mesh`: # If running locally, the data is already available at the correct path. -# In[3]: +# In[ ]: get_ipython().system('mkdir -p data/cow_mesh') @@ -97,12 +103,15 @@ get_ipython().system('wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytor get_ipython().system('wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png') -# In[2]: +# In[ ]: # Setup -device = torch.device("cuda:0") -torch.cuda.set_device(device) +if torch.cuda.is_available(): + device = torch.device("cuda:0") + torch.cuda.set_device(device) +else: + device = torch.device("cpu") # Set paths DATA_DIR = "./data" @@ -115,7 +124,7 @@ texture_image=mesh.textures.maps_padded() # #### Let's visualize the texture map -# In[3]: +# In[ ]: plt.figure(figsize=(7,7)) @@ -130,14 +139,14 @@ plt.axis('off'); # # In this example we will first create a **renderer** which uses a **perspective camera**, a **point light** and applies **phong shading**. Then we learn how to vary different components using the modular API. -# In[4]: +# In[ ]: -# Initialize an OpenGL perspective camera. +# Initialize a camera. # With world coordinates +Y up, +X left and +Z in, the front of the cow is facing the -Z direction. # So we move the camera by 180 in the azimuth direction so it is facing the front of the cow. R, T = look_at_view_transform(2.7, 0, 180) -cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T) +cameras = FoVPerspectiveCameras(device=device, R=R, T=T) # Define the settings for rasterization and shading. Here we set the output image to be of size # 512x512. As we are rendering images for visualization purposes only we will set faces_per_pixel=1 @@ -149,8 +158,6 @@ raster_settings = RasterizationSettings( image_size=512, blur_radius=0.0, faces_per_pixel=1, - bin_size = None, # this setting controls whether naive or coarse-to-fine rasterization is used - max_faces_per_bin = None # this setting is for coarse rasterization ) # Place a point light in front of the object. As mentioned above, the front of the cow is facing the @@ -165,7 +172,7 @@ renderer = MeshRenderer( cameras=cameras, raster_settings=raster_settings ), - shader=TexturedSoftPhongShader( + shader=SoftPhongShader( device=device, cameras=cameras, lights=lights @@ -177,7 +184,7 @@ renderer = MeshRenderer( # The light is in front of the object so it is bright and the image has specular highlights. -# In[5]: +# In[ ]: images = renderer(mesh) @@ -195,7 +202,7 @@ plt.axis("off"); # # The image is now dark as there is only ambient lighting, and there are no specular highlights. -# In[6]: +# In[ ]: # Now move the light so it is on the +Z axis which will be behind the cow. @@ -203,7 +210,7 @@ lights.location = torch.tensor([0.0, 0.0, +1.0], device=device)[None] images = renderer(mesh, lights=lights) -# In[7]: +# In[ ]: plt.figure(figsize=(10, 10)) @@ -220,12 +227,12 @@ plt.axis("off"); # - change the **position** of the point light # - change the **material reflectance** properties of the mesh -# In[8]: +# In[ ]: # Rotate the object by increasing the elevation and azimuth angles R, T = look_at_view_transform(dist=2.7, elev=10, azim=-150) -cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T) +cameras = FoVPerspectiveCameras(device=device, R=R, T=T) # Move the light location so the light is shining on the cow's face. lights.location = torch.tensor([[2.0, 2.0, -2.0]], device=device) @@ -241,7 +248,7 @@ materials = Materials( images = renderer(mesh, lights=lights, materials=materials, cameras=cameras) -# In[9]: +# In[ ]: plt.figure(figsize=(10, 10)) @@ -256,7 +263,7 @@ plt.axis("off"); # The renderer and associated components can take batched inputs and **render a batch of output images in one forward pass**. We will now use this feature to render the mesh from many different viewpoints. # -# In[10]: +# In[ ]: # Set batch size - this is the number of different viewpoints from which we want to render the mesh. @@ -275,13 +282,13 @@ azim = torch.linspace(-180, 180, batch_size) # view the camera from the same distance and specify dist=2.7 as a float, # and then specify elevation and azimuth angles for each viewpoint as tensors. R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim) -cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T) +cameras = FoVPerspectiveCameras(device=device, R=R, T=T) # Move the light back in front of the cow which is facing the -z direction. lights.location = torch.tensor([[0.0, 0.0, -3.0]], device=device) -# In[11]: +# In[ ]: # We can pass arbirary keyword arguments to the rasterizer/shader via the renderer @@ -289,7 +296,7 @@ lights.location = torch.tensor([[0.0, 0.0, -3.0]], device=device) images = renderer(meshes, cameras=cameras, lights=lights) -# In[14]: +# In[ ]: image_grid(images.cpu().numpy(), rows=4, cols=5, rgb=True) diff --git a/help.html b/help.html index 2f3d008f..e293fce6 100644 --- a/help.html +++ b/help.html @@ -12,4 +12,4 @@

Ask questions about the documentation and project

Stay up to date

Find out what's new with this project

-
\ No newline at end of file + \ No newline at end of file diff --git a/help/index.html b/help/index.html index 2f3d008f..e293fce6 100644 --- a/help/index.html +++ b/help/index.html @@ -12,4 +12,4 @@

Ask questions about the documentation and project

Stay up to date

Find out what's new with this project

-
\ No newline at end of file + \ No newline at end of file diff --git a/index.html b/index.html index d522c74e..559c4bfd 100644 --- a/index.html +++ b/index.html @@ -12,10 +12,7 @@

Supports optimized implementations of several common functions for 3D data

Differentiable Rendering

Modular differentiable rendering API with parallel implementations in PyTorch, C++ and CUDA

-

Get Started

  1. Install PyTorch3D:
    conda install pytorch torchvision -c pytorch  # OSX only
-conda install pytorch3d -c pytorch3d  # all systems
-
    -
  2. Try a few 3D operators e.g. compute the chamfer loss between two meshes:
    from pytorch3d.utils import ico_sphere
+

Get Started

  1. Install PyTorch3D (following the instructions here)
  2. Try a few 3D operators e.g. compute the chamfer loss between two meshes:
    from pytorch3d.utils import ico_sphere
 from pytorch3d.io import load_obj
 from pytorch3d.structures import Meshes
 from pytorch3d.ops import sample_points_from_meshes
@@ -31,4 +28,4 @@ sample_sphere = sample_points_from_meshes(sphere_mesh, 5000)
 loss_chamfer, _ = chamfer_distance(sample_sphere, sample_test)
    -
\ No newline at end of file + \ No newline at end of file diff --git a/js/codetabs.js b/js/codetabs.js index 60072d24..4fcdc461 100644 --- a/js/codetabs.js +++ b/js/codetabs.js @@ -1,5 +1,5 @@ /** - * Copyright (c) 2017-present, Facebook, Inc. + * Copyright (c) Facebook, Inc. and its affiliates. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. @@ -7,19 +7,19 @@ // Turn off ESLint for this file because it's sent down to users as-is. /* eslint-disable */ -window.addEventListener('load', function() { +window.addEventListener('load', function () { // add event listener for all tab - document.querySelectorAll('.nav-link').forEach(function(el) { - el.addEventListener('click', function(e) { + document.querySelectorAll('.nav-link').forEach(function (el) { + el.addEventListener('click', function (e) { var groupId = e.target.getAttribute('data-group'); document .querySelectorAll('.nav-link[data-group='.concat(groupId, ']')) - .forEach(function(el) { + .forEach(function (el) { el.classList.remove('active'); }); document .querySelectorAll('.tab-pane[data-group='.concat(groupId, ']')) - .forEach(function(el) { + .forEach(function (el) { el.classList.remove('active'); }); e.target.classList.add('active'); diff --git a/js/scrollSpy.js b/js/scrollSpy.js index ec05853a..1f278b26 100644 --- a/js/scrollSpy.js +++ b/js/scrollSpy.js @@ -1,5 +1,5 @@ /** - * Copyright (c) 2017-present, Facebook, Inc. + * Copyright (c) Facebook, Inc. and its affiliates. * * This source code is licensed under the MIT license found in the * LICENSE file in the root directory of this source tree. @@ -21,7 +21,7 @@ return; } - timer = setTimeout(function() { + timer = setTimeout(function () { timer = null; var activeNavFound = false; var headings = findHeadings(); // toc nav anchors @@ -75,7 +75,7 @@ document.addEventListener('scroll', onScroll); document.addEventListener('resize', onScroll); - document.addEventListener('DOMContentLoaded', function() { + document.addEventListener('DOMContentLoaded', function () { // Cache the headings once the page has fully loaded. headingsCache = findHeadings(); onScroll(); diff --git a/sitemap.xml b/sitemap.xml index ed747358..58a8425f 100644 --- a/sitemap.xml +++ b/sitemap.xml @@ -1 +1 @@ -https://pytorch3d.org/helpweekly0.5https://pytorch3d.org/indexweekly0.5https://pytorch3d.org/usersweekly0.5https://pytorch3d.org/docs/batchinghourly1.0https://pytorch3d.org/docs/meshes_iohourly1.0https://pytorch3d.org/docs/renderer_getting_startedhourly1.0https://pytorch3d.org/docs/rendererhourly1.0https://pytorch3d.org/docs/why_pytorch3dhourly1.0 \ No newline at end of file +https://pytorch3d.org/helpweekly0.5https://pytorch3d.org/indexweekly0.5https://pytorch3d.org/usersweekly0.5https://pytorch3d.org/docs/batchinghourly1.0https://pytorch3d.org/docs/camerashourly1.0https://pytorch3d.org/docs/cubifyhourly1.0https://pytorch3d.org/docs/datasetshourly1.0https://pytorch3d.org/docs/meshes_iohourly1.0https://pytorch3d.org/docs/renderer_getting_startedhourly1.0https://pytorch3d.org/docs/rendererhourly1.0https://pytorch3d.org/docs/why_pytorch3dhourly1.0 \ No newline at end of file diff --git a/tutorials/bundle_adjustment.html b/tutorials/bundle_adjustment.html index 2b1e68d3..6735bfdc 100644 --- a/tutorials/bundle_adjustment.html +++ b/tutorials/bundle_adjustment.html @@ -6,7 +6,7 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -
\ No newline at end of file diff --git a/tutorials/camera_position_optimization_with_differentiable_rendering/index.html b/tutorials/camera_position_optimization_with_differentiable_rendering/index.html index ea74c9cf..b9f29dab 100644 --- a/tutorials/camera_position_optimization_with_differentiable_rendering/index.html +++ b/tutorials/camera_position_optimization_with_differentiable_rendering/index.html @@ -6,7 +6,7 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -
-
-
+

5. Conclusion

In this tutorial we learnt how to load a mesh from an obj file, initialize a PyTorch3D datastructure called Meshes, set up an Renderer consisting of a Rasterizer and a Shader, set up an optimization loop including a Model and a loss function, and run the optimization.

-
\ No newline at end of file + \ No newline at end of file diff --git a/tutorials/dataloaders_ShapeNetCore_R2N2.html b/tutorials/dataloaders_ShapeNetCore_R2N2.html new file mode 100644 index 00000000..fdf14336 --- /dev/null +++ b/tutorials/dataloaders_ShapeNetCore_R2N2.html @@ -0,0 +1,614 @@ +PyTorch3D · A library for deep learning with 3D data
Run in Google Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
+ + +
+
+
+
In [ ]:
+
+
+
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
+
+
+
+
+
+
+
+
+

Dataloaders for ShapeNetCore and R2N2

This tutorial shows how to:

+
    +
  • Load models from ShapeNetCore and R2N2 using PyTorch3D's data loaders.
    • +
  • Pass the loaded datasets to torch.utils.data.DataLoader.
    • +
  • Render ShapeNetCore models with PyTorch3D's renderer.
    • +
  • Render R2N2 models with the same orientations as the original renderings in the dataset.
    • +
  • Visualize R2N2 model voxels.
    • +
+
+
+
+
+
+
+

0. Install and import modules

+
+
+
+
+
+
+

If torch, torchvision and pytorch3d are not installed, run the following cell:

+
+
+
+
+
+
In [ ]:
+
+
+
!pip install torch torchvision
+import sys
+import torch
+if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):
+    !pip install pytorch3d
+else:
+    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
import numpy as np
+import torch
+
+from pytorch3d.datasets import (
+    R2N2,
+    ShapeNetCore,
+    collate_batched_meshes,
+    render_cubified_voxels,
+)
+from pytorch3d.renderer import (
+    OpenGLPerspectiveCameras,
+    PointLights,
+    RasterizationSettings,
+    TexturesVertex,
+    look_at_view_transform,
+)
+
+from pytorch3d.structures import Meshes
+from torch.utils.data import DataLoader
+
+# add path for demo utils functions 
+import sys
+import os
+sys.path.append(os.path.abspath(''))
+
+
+
+
+
+
+
+
+

If using Google Colab, fetch the utils file for plotting image grids:

+
+
+
+
+
+
In [ ]:
+
+
+
!wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py
+from plot_image_grid import image_grid
+
+
+
+
+
+
+
+
+

OR if running locally uncomment and run the following cell:

+
+
+
+
+
+
In [ ]:
+
+
+
# from utils import image_grid
+
+
+
+
+
+
+
+
+

1. Load the datasets

+
+
+
+
+
+
+

If you haven't already downloaded the ShapeNetCore dataset, first do that following the instructions here: https://www.shapenet.org/. ShapeNetCore is a subset of the ShapeNet dataset. In PyTorch3D we support both version 1 (57 categories) and version 2 (55 categories).

+

Then modify SHAPENET_PATH below to you local path to the ShapeNetCore dataset folder.

+
+
+
+
+
+
In [ ]:
+
+
+
# Setup
+if torch.cuda.is_available():
+    device = torch.device("cuda:0")
+    torch.cuda.set_device(device)
+else:
+    device = torch.device("cpu")
+    
+SHAPENET_PATH = ""
+shapenet_dataset = ShapeNetCore(SHAPENET_PATH)
+
+
+
+
+
+
+
+
+

The R2N2 dataset can be downloaded using the instructions here: http://3d-r2n2.stanford.edu/. Look at the links for ShapeNetRendering and ShapeNetVox32. The R2N2 dataset contains 13 categories that are a subset of the ShapeNetCore v.1 +dataset. The R2N2 dataset also contains its own 24 renderings of each object and voxelized models.

+

Then modify R2N2_PATH and SPLITS_PATH below to your local R2N2 dataset folder path and splits file path respectively. Here we will load the train split of R2N2 and ask the voxels of each model to be returned.

+
+
+
+
+
+
In [ ]:
+
+
+
R2N2_PATH = ""
+SPLITS_PATH = "None"
+r2n2_dataset = R2N2("train", SHAPENET_PATH, R2N2_PATH, SPLITS_PATH, return_voxels=True)
+
+
+
+
+
+
+
+
+

We can retrieve a model by indexing into the loaded dataset. For both ShapeNetCore and R2N2, we can examine the category this model belongs to (in the form of a synset id, equivalend to wnid described in ImageNet's API: http://image-net.org/download-API), its model id, and its vertices and faces.

+
+
+
+
+
+
In [ ]:
+
+
+
shapenet_model = shapenet_dataset[6]
+print("This model belongs to the category " + shapenet_model["synset_id"] + ".")
+print("This model has model id " + shapenet_model["model_id"] + ".")
+model_verts, model_faces = shapenet_model["verts"], shapenet_model["faces"]
+
+
+
+
+
+
+
+
+

We can use its vertices and faces to form a Meshes object which is a PyTorch3D datastructure for working with batched meshes.

+
+
+
+
+
+
In [ ]:
+
+
+
model_textures = TexturesVertex(verts_features=torch.ones_like(model_verts, device=device)[None])
+shapenet_model_mesh = Meshes(
+    verts=[model_verts.to(device)],   
+    faces=[model_faces.to(device)],
+    textures=model_textures
+)
+
+
+
+
+
+
+
+
+

With R2N2, we can further examine R2N2's original renderings. For instance, if we would like to see the second and third views of the eleventh objects in the R2N2 dataset, we can do the following:

+
+
+
+
+
+
In [ ]:
+
+
+
r2n2_renderings = r2n2_dataset[10,[1,2]]
+image_grid(r2n2_renderings.numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
+
+
+

2. Use the datasets with torch.utils.data.DataLoader

+
+
+
+
+
+
+

Training deep learning models, usually requires passing in batches of inputs. The torch.utils.data.DataLoader from Pytorch helps us do this. PyTorch3D provides a function collate_batched_meshes to group the input meshes into a single Meshes object which represents the batch. The Meshes datastructure can then be used directly by other PyTorch3D ops which might be part of the deep learning model (e.g. graph_conv).

+

For R2N2, if all the models in the batch have the same number of views, the views, rotation matrices, translation matrices, intrinsic matrices and voxels will also be stacked into batched tensors.

+

NOTE: All models in the val split of R2N2 have 24 views, but there are 8 models that split their 24 views between train and test splits, in which case collate_batched_meshes will only be able to join the matrices, views and voxels as lists. However, this can be avoided by laoding only one view of each model by setting return_all_views = False.

+
+
+
+
+
+
In [ ]:
+
+
+
batch_size = 12
+r2n2_single_view = R2N2("train", SHAPENET_PATH, R2N2_PATH, SPLITS_PATH, return_all_views=False, return_voxels=True)
+r2n2_loader = DataLoader(r2n2_single_view, batch_size=batch_size, collate_fn=collate_batched_meshes)
+
+
+
+
+
+
+
+
+

Let's visualize all the views (one for each model) in the batch:

+
+
+
+
+
+
In [ ]:
+
+
+
it = iter(r2n2_loader)
+r2n2_batch = next(it)
+batch_renderings = r2n2_batch["images"] # (N, V, H, W, 3), and in this case V is 1.
+image_grid(batch_renderings.squeeze().numpy(), rows=3, cols=4, rgb=True)
+
+
+
+
+
+
+
+
+

3. Render ShapeNetCore models with PyTorch3D's differntiable renderer

+
+
+
+
+
+
+

Both ShapeNetCore and R2N2 dataloaders have customized render functions that support rendering models by specifying their model ids, categories or indices using PyTorch3D's differentiable renderer implementation.

+
+
+
+
+
+
In [ ]:
+
+
+
# Rendering settings.
+R, T = look_at_view_transform(1.0, 1.0, 90)
+cameras = OpenGLPerspectiveCameras(R=R, T=T, device=device)
+raster_settings = RasterizationSettings(image_size=512)
+lights = PointLights(location=torch.tensor([0.0, 1.0, -2.0], device=device)[None],device=device)
+
+
+
+
+
+
+
+
+

First we will try to render three models by their model ids:

+
+
+
+
+
+
In [ ]:
+
+
+
images_by_model_ids = shapenet_dataset.render(
+    model_ids=[
+        "13394ca47c89f91525a3aaf903a41c90",
+        "14755c2ee8e693aba508f621166382b0",
+        "156c4207af6d2c8f1fdc97905708b8ea",
+    ],
+    device=device,
+    cameras=cameras,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(images_by_model_ids.cpu().numpy(), rows=1, cols=3, rgb=True)
+
+
+
+
+
+
+
+
+

Suppose we would like to render the first three models in the dataset, we can render models by their indices:

+
+
+
+
+
+
In [ ]:
+
+
+
images_by_idxs = shapenet_dataset.render(
+    idxs=list(range(3)),
+    device=device,
+    cameras=cameras,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(images_by_idxs.cpu().numpy(), rows=1, cols=3, rgb=True)
+
+
+
+
+
+
+
+
+

Alternatively, if we are not interested in any particular models but would like see random models from some specific categories, we can do that by specifying categories and sample_nums. For example, if we would like to render 2 models from the category "faucet" and 3 models from the category "chair", we can do the following:

+
+
+
+
+
+
In [ ]:
+
+
+
images_by_categories = shapenet_dataset.render(
+    categories=["faucet", "chair"],
+    sample_nums=[2, 3],
+    device=device,
+    cameras=cameras,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(images_by_categories.cpu().numpy(), rows=1, cols=5, rgb=True)
+
+
+
+
+
+
+
+
+

If we are not interested in any particular categories and just would like to render some random models from the whole dataset, we can set the number of models to be rendered in sample_nums and not specify any categories:

+
+
+
+
+
+
In [ ]:
+
+
+
random_model_images = shapenet_dataset.render(
+    sample_nums=[3],
+    device=device,
+    cameras=cameras,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(random_model_images.cpu().numpy(), rows=1, cols=5, rgb=True)
+
+
+
+
+
+
+
+
+

4. Render R2N2 models with the same orientations as the original renderings in the dataset

+
+
+
+
+
+
+

We can render R2N2 models the same way as we rendered ShapeNetCore models above. In addition, we can also render R2N2 models with the same orientations as the original renderings in the dataset. For this we will use R2N2's customized render function and a different type of PyTorch3D camera called BlenderCamera.

+
+
+
+
+
+
+

In this example, we will render the seventh model with the same orientations as its second and third views. First we will retrieve R2N2's original renderings to compare with the result.

+
+
+
+
+
+
In [ ]:
+
+
+
original_rendering = r2n2_dataset[6,[1,2]]["images"]
+image_grid(original_rendering.numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
+
+
+

Next, we will visualize PyTorch3d's renderings:

+
+
+
+
+
+
In [ ]:
+
+
+
r2n2_oriented_images = r2n2_dataset.render(
+    idxs=[6],
+    view_idxs=[1,2],
+    device=device,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(r2n2_oriented_images.cpu().numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
+
+
+

5. Visualize R2N2 models' voxels

+
+
+
+
+
+
+

R2N2 dataloader also returns models' voxels. We can visualize them by utilizing R2N2's render_vox_to_mesh function. This will cubify the voxels to a Meshes object, which will then be rendered.

+
+
+
+
+
+
+

In this example we will visualize the tenth model in the dataset with the same orientation of its second and third views. First we will retrieve R2N2's original renderings to compare with the result.

+
+
+
+
+
+
In [ ]:
+
+
+
r2n2_model = r2n2_dataset[9,[1,2]]
+original_rendering = r2n2_model["images"]
+image_grid(original_rendering.numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
+
+
+

Next, we will pass the voxels to render_vox_to_mesh:

+
+
+
+
+
+
In [ ]:
+
+
+
vox_render = render_cubified_voxels(r2n2_model["voxels"], device=device)
+image_grid(vox_render.cpu().numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
\ No newline at end of file diff --git a/tutorials/dataloaders_ShapeNetCore_R2N2/index.html b/tutorials/dataloaders_ShapeNetCore_R2N2/index.html new file mode 100644 index 00000000..fdf14336 --- /dev/null +++ b/tutorials/dataloaders_ShapeNetCore_R2N2/index.html @@ -0,0 +1,614 @@ +PyTorch3D · A library for deep learning with 3D data
Run in Google Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
+ + +
+
+
+
In [ ]:
+
+
+
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
+
+
+
+
+
+
+
+
+

Dataloaders for ShapeNetCore and R2N2

This tutorial shows how to:

+
    +
  • Load models from ShapeNetCore and R2N2 using PyTorch3D's data loaders.
    • +
  • Pass the loaded datasets to torch.utils.data.DataLoader.
    • +
  • Render ShapeNetCore models with PyTorch3D's renderer.
    • +
  • Render R2N2 models with the same orientations as the original renderings in the dataset.
    • +
  • Visualize R2N2 model voxels.
    • +
+
+
+
+
+
+
+

0. Install and import modules

+
+
+
+
+
+
+

If torch, torchvision and pytorch3d are not installed, run the following cell:

+
+
+
+
+
+
In [ ]:
+
+
+
!pip install torch torchvision
+import sys
+import torch
+if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):
+    !pip install pytorch3d
+else:
+    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
import numpy as np
+import torch
+
+from pytorch3d.datasets import (
+    R2N2,
+    ShapeNetCore,
+    collate_batched_meshes,
+    render_cubified_voxels,
+)
+from pytorch3d.renderer import (
+    OpenGLPerspectiveCameras,
+    PointLights,
+    RasterizationSettings,
+    TexturesVertex,
+    look_at_view_transform,
+)
+
+from pytorch3d.structures import Meshes
+from torch.utils.data import DataLoader
+
+# add path for demo utils functions 
+import sys
+import os
+sys.path.append(os.path.abspath(''))
+
+
+
+
+
+
+
+
+

If using Google Colab, fetch the utils file for plotting image grids:

+
+
+
+
+
+
In [ ]:
+
+
+
!wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py
+from plot_image_grid import image_grid
+
+
+
+
+
+
+
+
+

OR if running locally uncomment and run the following cell:

+
+
+
+
+
+
In [ ]:
+
+
+
# from utils import image_grid
+
+
+
+
+
+
+
+
+

1. Load the datasets

+
+
+
+
+
+
+

If you haven't already downloaded the ShapeNetCore dataset, first do that following the instructions here: https://www.shapenet.org/. ShapeNetCore is a subset of the ShapeNet dataset. In PyTorch3D we support both version 1 (57 categories) and version 2 (55 categories).

+

Then modify SHAPENET_PATH below to you local path to the ShapeNetCore dataset folder.

+
+
+
+
+
+
In [ ]:
+
+
+
# Setup
+if torch.cuda.is_available():
+    device = torch.device("cuda:0")
+    torch.cuda.set_device(device)
+else:
+    device = torch.device("cpu")
+    
+SHAPENET_PATH = ""
+shapenet_dataset = ShapeNetCore(SHAPENET_PATH)
+
+
+
+
+
+
+
+
+

The R2N2 dataset can be downloaded using the instructions here: http://3d-r2n2.stanford.edu/. Look at the links for ShapeNetRendering and ShapeNetVox32. The R2N2 dataset contains 13 categories that are a subset of the ShapeNetCore v.1 +dataset. The R2N2 dataset also contains its own 24 renderings of each object and voxelized models.

+

Then modify R2N2_PATH and SPLITS_PATH below to your local R2N2 dataset folder path and splits file path respectively. Here we will load the train split of R2N2 and ask the voxels of each model to be returned.

+
+
+
+
+
+
In [ ]:
+
+
+
R2N2_PATH = ""
+SPLITS_PATH = "None"
+r2n2_dataset = R2N2("train", SHAPENET_PATH, R2N2_PATH, SPLITS_PATH, return_voxels=True)
+
+
+
+
+
+
+
+
+

We can retrieve a model by indexing into the loaded dataset. For both ShapeNetCore and R2N2, we can examine the category this model belongs to (in the form of a synset id, equivalend to wnid described in ImageNet's API: http://image-net.org/download-API), its model id, and its vertices and faces.

+
+
+
+
+
+
In [ ]:
+
+
+
shapenet_model = shapenet_dataset[6]
+print("This model belongs to the category " + shapenet_model["synset_id"] + ".")
+print("This model has model id " + shapenet_model["model_id"] + ".")
+model_verts, model_faces = shapenet_model["verts"], shapenet_model["faces"]
+
+
+
+
+
+
+
+
+

We can use its vertices and faces to form a Meshes object which is a PyTorch3D datastructure for working with batched meshes.

+
+
+
+
+
+
In [ ]:
+
+
+
model_textures = TexturesVertex(verts_features=torch.ones_like(model_verts, device=device)[None])
+shapenet_model_mesh = Meshes(
+    verts=[model_verts.to(device)],   
+    faces=[model_faces.to(device)],
+    textures=model_textures
+)
+
+
+
+
+
+
+
+
+

With R2N2, we can further examine R2N2's original renderings. For instance, if we would like to see the second and third views of the eleventh objects in the R2N2 dataset, we can do the following:

+
+
+
+
+
+
In [ ]:
+
+
+
r2n2_renderings = r2n2_dataset[10,[1,2]]
+image_grid(r2n2_renderings.numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
+
+
+

2. Use the datasets with torch.utils.data.DataLoader

+
+
+
+
+
+
+

Training deep learning models, usually requires passing in batches of inputs. The torch.utils.data.DataLoader from Pytorch helps us do this. PyTorch3D provides a function collate_batched_meshes to group the input meshes into a single Meshes object which represents the batch. The Meshes datastructure can then be used directly by other PyTorch3D ops which might be part of the deep learning model (e.g. graph_conv).

+

For R2N2, if all the models in the batch have the same number of views, the views, rotation matrices, translation matrices, intrinsic matrices and voxels will also be stacked into batched tensors.

+

NOTE: All models in the val split of R2N2 have 24 views, but there are 8 models that split their 24 views between train and test splits, in which case collate_batched_meshes will only be able to join the matrices, views and voxels as lists. However, this can be avoided by laoding only one view of each model by setting return_all_views = False.

+
+
+
+
+
+
In [ ]:
+
+
+
batch_size = 12
+r2n2_single_view = R2N2("train", SHAPENET_PATH, R2N2_PATH, SPLITS_PATH, return_all_views=False, return_voxels=True)
+r2n2_loader = DataLoader(r2n2_single_view, batch_size=batch_size, collate_fn=collate_batched_meshes)
+
+
+
+
+
+
+
+
+

Let's visualize all the views (one for each model) in the batch:

+
+
+
+
+
+
In [ ]:
+
+
+
it = iter(r2n2_loader)
+r2n2_batch = next(it)
+batch_renderings = r2n2_batch["images"] # (N, V, H, W, 3), and in this case V is 1.
+image_grid(batch_renderings.squeeze().numpy(), rows=3, cols=4, rgb=True)
+
+
+
+
+
+
+
+
+

3. Render ShapeNetCore models with PyTorch3D's differntiable renderer

+
+
+
+
+
+
+

Both ShapeNetCore and R2N2 dataloaders have customized render functions that support rendering models by specifying their model ids, categories or indices using PyTorch3D's differentiable renderer implementation.

+
+
+
+
+
+
In [ ]:
+
+
+
# Rendering settings.
+R, T = look_at_view_transform(1.0, 1.0, 90)
+cameras = OpenGLPerspectiveCameras(R=R, T=T, device=device)
+raster_settings = RasterizationSettings(image_size=512)
+lights = PointLights(location=torch.tensor([0.0, 1.0, -2.0], device=device)[None],device=device)
+
+
+
+
+
+
+
+
+

First we will try to render three models by their model ids:

+
+
+
+
+
+
In [ ]:
+
+
+
images_by_model_ids = shapenet_dataset.render(
+    model_ids=[
+        "13394ca47c89f91525a3aaf903a41c90",
+        "14755c2ee8e693aba508f621166382b0",
+        "156c4207af6d2c8f1fdc97905708b8ea",
+    ],
+    device=device,
+    cameras=cameras,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(images_by_model_ids.cpu().numpy(), rows=1, cols=3, rgb=True)
+
+
+
+
+
+
+
+
+

Suppose we would like to render the first three models in the dataset, we can render models by their indices:

+
+
+
+
+
+
In [ ]:
+
+
+
images_by_idxs = shapenet_dataset.render(
+    idxs=list(range(3)),
+    device=device,
+    cameras=cameras,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(images_by_idxs.cpu().numpy(), rows=1, cols=3, rgb=True)
+
+
+
+
+
+
+
+
+

Alternatively, if we are not interested in any particular models but would like see random models from some specific categories, we can do that by specifying categories and sample_nums. For example, if we would like to render 2 models from the category "faucet" and 3 models from the category "chair", we can do the following:

+
+
+
+
+
+
In [ ]:
+
+
+
images_by_categories = shapenet_dataset.render(
+    categories=["faucet", "chair"],
+    sample_nums=[2, 3],
+    device=device,
+    cameras=cameras,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(images_by_categories.cpu().numpy(), rows=1, cols=5, rgb=True)
+
+
+
+
+
+
+
+
+

If we are not interested in any particular categories and just would like to render some random models from the whole dataset, we can set the number of models to be rendered in sample_nums and not specify any categories:

+
+
+
+
+
+
In [ ]:
+
+
+
random_model_images = shapenet_dataset.render(
+    sample_nums=[3],
+    device=device,
+    cameras=cameras,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(random_model_images.cpu().numpy(), rows=1, cols=5, rgb=True)
+
+
+
+
+
+
+
+
+

4. Render R2N2 models with the same orientations as the original renderings in the dataset

+
+
+
+
+
+
+

We can render R2N2 models the same way as we rendered ShapeNetCore models above. In addition, we can also render R2N2 models with the same orientations as the original renderings in the dataset. For this we will use R2N2's customized render function and a different type of PyTorch3D camera called BlenderCamera.

+
+
+
+
+
+
+

In this example, we will render the seventh model with the same orientations as its second and third views. First we will retrieve R2N2's original renderings to compare with the result.

+
+
+
+
+
+
In [ ]:
+
+
+
original_rendering = r2n2_dataset[6,[1,2]]["images"]
+image_grid(original_rendering.numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
+
+
+

Next, we will visualize PyTorch3d's renderings:

+
+
+
+
+
+
In [ ]:
+
+
+
r2n2_oriented_images = r2n2_dataset.render(
+    idxs=[6],
+    view_idxs=[1,2],
+    device=device,
+    raster_settings=raster_settings,
+    lights=lights,
+)
+image_grid(r2n2_oriented_images.cpu().numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
+
+
+

5. Visualize R2N2 models' voxels

+
+
+
+
+
+
+

R2N2 dataloader also returns models' voxels. We can visualize them by utilizing R2N2's render_vox_to_mesh function. This will cubify the voxels to a Meshes object, which will then be rendered.

+
+
+
+
+
+
+

In this example we will visualize the tenth model in the dataset with the same orientation of its second and third views. First we will retrieve R2N2's original renderings to compare with the result.

+
+
+
+
+
+
In [ ]:
+
+
+
r2n2_model = r2n2_dataset[9,[1,2]]
+original_rendering = r2n2_model["images"]
+image_grid(original_rendering.numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
+
+
+

Next, we will pass the voxels to render_vox_to_mesh:

+
+
+
+
+
+
In [ ]:
+
+
+
vox_render = render_cubified_voxels(r2n2_model["voxels"], device=device)
+image_grid(vox_render.cpu().numpy(), rows=1, cols=2, rgb=True)
+
+
+
+
+
+
\ No newline at end of file diff --git a/tutorials/deform_source_mesh_to_target_mesh.html b/tutorials/deform_source_mesh_to_target_mesh.html index f1a536e7..789f4fa7 100644 --- a/tutorials/deform_source_mesh_to_target_mesh.html +++ b/tutorials/deform_source_mesh_to_target_mesh.html @@ -6,7 +6,7 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -
-
-
+

4. Visualize the loss

@@ -8594,10 +417,10 @@ AAAAAElFTkSuQmCC
-
In [79]:
+
In [ ]:
-
fig = plt.figure(figsize=(13, 5))
+
fig = plt.figure(figsize=(13, 5))
 ax = fig.gca()
 ax.plot(chamfer_losses, label="chamfer loss")
 ax.plot(edge_losses, label="edge loss")
@@ -8606,517 +429,14 @@ AAAAAElFTkSuQmCC
 ax.legend(fontsize="16")
 ax.set_xlabel("Iteration", fontsize="16")
 ax.set_ylabel("Loss", fontsize="16")
-ax.set_title("Loss vs iterations", fontsize="16")
+ax.set_title("Loss vs iterations", fontsize="16");
-
-
-
-
Out[79]:
-
-
Text(0.5, 1.0, 'Loss vs iterations')
-
-
-
-
-
- -
-
-
-
-
-
+

5. Save the predicted mesh

@@ -9124,10 +444,10 @@ FvT/AyfB6EfRGCKLAAAAAElFTkSuQmCC
-
In [0]:
+
In [ ]:
-
# Fetch the verts and faces of the final predicted mesh
+
# Fetch the verts and faces of the final predicted mesh
 final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0)
 
 # Scale normalize back to the original target size
@@ -9142,11 +462,10 @@ FvT/AyfB6EfRGCKLAAAAAElFTkSuQmCC
-
-
+

6. Conclusion

In this tutorial we learnt how to load a mesh from an obj file, initialize a PyTorch3D datastructure called Meshes, set up an optimization loop and use four different PyTorch3D mesh loss functions.

-
\ No newline at end of file +
\ No newline at end of file diff --git a/tutorials/deform_source_mesh_to_target_mesh/index.html b/tutorials/deform_source_mesh_to_target_mesh/index.html index f1a536e7..789f4fa7 100644 --- a/tutorials/deform_source_mesh_to_target_mesh/index.html +++ b/tutorials/deform_source_mesh_to_target_mesh/index.html @@ -6,7 +6,7 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -
-
-
+

4. Visualize the loss

@@ -8594,10 +417,10 @@ AAAAAElFTkSuQmCC
-
In [79]:
+
In [ ]:
-
fig = plt.figure(figsize=(13, 5))
+
fig = plt.figure(figsize=(13, 5))
 ax = fig.gca()
 ax.plot(chamfer_losses, label="chamfer loss")
 ax.plot(edge_losses, label="edge loss")
@@ -8606,517 +429,14 @@ AAAAAElFTkSuQmCC
 ax.legend(fontsize="16")
 ax.set_xlabel("Iteration", fontsize="16")
 ax.set_ylabel("Loss", fontsize="16")
-ax.set_title("Loss vs iterations", fontsize="16")
+ax.set_title("Loss vs iterations", fontsize="16");
-
-
-
-
Out[79]:
-
-
Text(0.5, 1.0, 'Loss vs iterations')
-
-
-
-
-
- -
-
-
-
-
-
+

5. Save the predicted mesh

@@ -9124,10 +444,10 @@ FvT/AyfB6EfRGCKLAAAAAElFTkSuQmCC
-
In [0]:
+
In [ ]:
-
# Fetch the verts and faces of the final predicted mesh
+
# Fetch the verts and faces of the final predicted mesh
 final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0)
 
 # Scale normalize back to the original target size
@@ -9142,11 +462,10 @@ FvT/AyfB6EfRGCKLAAAAAElFTkSuQmCC
-
-
+

6. Conclusion

In this tutorial we learnt how to load a mesh from an obj file, initialize a PyTorch3D datastructure called Meshes, set up an optimization loop and use four different PyTorch3D mesh loss functions.

-
\ No newline at end of file +
\ No newline at end of file diff --git a/tutorials/fit_textured_mesh.html b/tutorials/fit_textured_mesh.html new file mode 100644 index 00000000..16c1a569 --- /dev/null +++ b/tutorials/fit_textured_mesh.html @@ -0,0 +1,849 @@ +PyTorch3D · A library for deep learning with 3D data
Run in Google Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
+ + +
+
+
+
In [ ]:
+
+
+
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
+
+
+
+
+
+
+
+
+

Fit a mesh via rendering

This tutorial shows how to:

+
    +
  • Load a mesh and textures from an .obj file.
    • +
  • Create a synthetic dataset by rendering a textured mesh from multiple viewpoints
    • +
  • Fit a mesh to the observed synthetic images using differential silhouette rendering
    • +
  • Fit a mesh and its textures using differential textured rendering
    • +
+
+
+
+
+
+
+

0. Install and Import modules

+
+
+
+
+
+
+

If torch, torchvision and pytorch3d are not installed, run the following cell:

+
+
+
+
+
+
In [ ]:
+
+
+
!pip install torch torchvision
+import sys
+import torch
+if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):
+    !pip install pytorch3d
+else:
+    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
import os
+import torch
+import matplotlib.pyplot as plt
+from skimage.io import imread
+
+from pytorch3d.utils import ico_sphere
+import numpy as np
+from tqdm.notebook import tqdm
+
+# Util function for loading meshes
+from pytorch3d.io import load_objs_as_meshes, save_obj
+
+from pytorch3d.loss import (
+    chamfer_distance, 
+    mesh_edge_loss, 
+    mesh_laplacian_smoothing, 
+    mesh_normal_consistency,
+)
+
+# Data structures and functions for rendering
+from pytorch3d.structures import Meshes
+from pytorch3d.renderer import (
+    look_at_view_transform,
+    OpenGLPerspectiveCameras, 
+    PointLights, 
+    DirectionalLights, 
+    Materials, 
+    RasterizationSettings, 
+    MeshRenderer, 
+    MeshRasterizer,  
+    SoftPhongShader,
+    SoftSilhouetteShader,
+    SoftPhongShader,
+    TexturesVertex
+)
+
+# add path for demo utils functions 
+import sys
+import os
+sys.path.append(os.path.abspath(''))
+
+
+
+
+
+
+
+
+

If using Google Colab, fetch the utils file for plotting image grids:

+
+
+
+
+
+
In [ ]:
+
+
+
!wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py
+from plot_image_grid import image_grid
+
+
+
+
+
+
+
+
+

OR if running locally uncomment and run the following cell:

+
+
+
+
+
+
In [ ]:
+
+
+
#  from utils.plot_image_grid import image_grid
+
+
+
+
+
+
+
+
+

1. Load a mesh and texture file

Load an .obj file and it's associated .mtl file and create a Textures and Meshes object.

+

Meshes is a unique datastructure provided in PyTorch3D for working with batches of meshes of different sizes.

+

TexturesVertex is an auxillary datastructure for storing vertex rgb texture information about meshes.

+

Meshes has several class methods which are used throughout the rendering pipeline.

+
+
+
+
+
+
+

If running this notebook using Google Colab, run the following cell to fetch the mesh obj and texture files and save it at the path data/cow_mesh: +If running locally, the data is already available at the correct path.

+
+
+
+
+
+
In [ ]:
+
+
+
!mkdir -p data/cow_mesh
+!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.obj
+!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.mtl
+!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
# Setup
+if torch.cuda.is_available():
+    device = torch.device("cuda:0")
+    torch.cuda.set_device(device)
+else:
+    device = torch.device("cpu")
+
+# Set paths
+DATA_DIR = "./data"
+obj_filename = os.path.join(DATA_DIR, "cow_mesh/cow.obj")
+
+# Load obj file
+mesh = load_objs_as_meshes([obj_filename], device=device)
+
+# We scale normalize and center the target mesh to fit in a sphere of radius 1 
+# centered at (0,0,0). (scale, center) will be used to bring the predicted mesh 
+# to its original center and scale.  Note that normalizing the target mesh, 
+# speeds up the optimization but is not necessary!
+verts = mesh.verts_packed()
+N = verts.shape[0]
+center = verts.mean(0)
+scale = max((verts - center).abs().max(0)[0])
+mesh.offset_verts_(-center.expand(N, 3))
+mesh.scale_verts_((1.0 / float(scale)));
+
+
+
+
+
+
+
+
+

2. Dataset Creation

We sample different camera positions that encode multiple viewpoints of the cow. We create a renderer with a shader that performs texture map interpolation. We render a synthetic dataset of images of the textured cow mesh from multiple viewpoints.

+
+
+
+
+
+
In [ ]:
+
+
+
# the number of different viewpoints from which we want to render the mesh.
+num_views = 20
+
+# Get a batch of viewing angles. 
+elev = torch.linspace(0, 360, num_views)
+azim = torch.linspace(-180, 180, num_views)
+
+# Place a point light in front of the object. As mentioned above, the front of 
+# the cow is facing the -z direction. 
+lights = PointLights(device=device, location=[[0.0, 0.0, -3.0]])
+
+# Initialize an OpenGL perspective camera that represents a batch of different 
+# viewing angles. All the cameras helper methods support mixed type inputs and 
+# broadcasting. So we can view the camera from the a distance of dist=2.7, and 
+# then specify elevation and azimuth angles for each viewpoint as tensors. 
+R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim)
+cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)
+
+# We arbitrarily choose one particular view that will be used to visualize 
+# results
+camera = OpenGLPerspectiveCameras(device=device, R=R[None, 1, ...], 
+                                  T=T[None, 1, ...]) 
+
+# Define the settings for rasterization and shading. Here we set the output 
+# image to be of size 128X128. As we are rendering images for visualization 
+# purposes only we will set faces_per_pixel=1 and blur_radius=0.0. Refer to 
+# rasterize_meshes.py for explanations of these parameters.  We also leave 
+# bin_size and max_faces_per_bin to their default values of None, which sets 
+# their values using huristics and ensures that the faster coarse-to-fine 
+# rasterization method is used.  Refer to docs/notes/renderer.md for an 
+# explanation of the difference between naive and coarse-to-fine rasterization. 
+raster_settings = RasterizationSettings(
+    image_size=128, 
+    blur_radius=0.0, 
+    faces_per_pixel=1, 
+)
+
+# Create a phong renderer by composing a rasterizer and a shader. The textured 
+# phong shader will interpolate the texture uv coordinates for each vertex, 
+# sample from a texture image and apply the Phong lighting model
+renderer = MeshRenderer(
+    rasterizer=MeshRasterizer(
+        cameras=camera, 
+        raster_settings=raster_settings
+    ),
+    shader=SoftPhongShader(
+        device=device, 
+        cameras=camera,
+        lights=lights
+    )
+)
+
+# Create a batch of meshes by repeating the cow mesh and associated textures. 
+# Meshes has a useful `extend` method which allows us do this very easily. 
+# This also extends the textures. 
+meshes = mesh.extend(num_views)
+
+# Render the cow mesh from each viewing angle
+target_images = renderer(meshes, cameras=cameras, lights=lights)
+
+# Our multi-view cow dataset will be represented by these 2 lists of tensors,
+# each of length num_views.
+target_rgb = [target_images[i, ..., :3] for i in range(num_views)]
+target_cameras = [OpenGLPerspectiveCameras(device=device, R=R[None, i, ...], 
+                                           T=T[None, i, ...]) for i in range(num_views)]
+
+
+
+
+
+
+
+
+

Visualize the dataset:

+
+
+
+
+
+
In [ ]:
+
+
+
# RGB images
+image_grid(target_images.cpu().numpy(), rows=4, cols=5, rgb=True)
+plt.show()
+
+
+
+
+
+
+
+
+

Later in this tutorial, we will fit a mesh to the rendered RGB images, as well as to just images of just the cow silhouette. For the latter case, we will render a dataset of silhouette images. Most shaders in PyTorch3D will output an alpha channel along with the RGB image as a 4th channel in an RGBA image. The alpha channel encodes the probability that each pixel belongs to the foreground of the object. We contruct a soft silhouette shader to render this alpha channel.

+
+
+
+
+
+
In [ ]:
+
+
+
# Rasterization settings for silhouette rendering  
+sigma = 1e-4
+raster_settings_silhouette = RasterizationSettings(
+    image_size=128, 
+    blur_radius=np.log(1. / 1e-4 - 1.)*sigma, 
+    faces_per_pixel=50, 
+)
+
+# Silhouette renderer 
+renderer_silhouette = MeshRenderer(
+    rasterizer=MeshRasterizer(
+        cameras=camera, 
+        raster_settings=raster_settings_silhouette
+    ),
+    shader=SoftSilhouetteShader()
+)
+
+# Render silhouette images.  The 3rd channel of the rendering output is 
+# the alpha/silhouette channel
+silhouette_images = renderer_silhouette(meshes, cameras=cameras, lights=lights)
+target_silhouette = [silhouette_images[i, ..., 3] for i in range(num_views)]
+
+# Visualize silhouette images
+image_grid(silhouette_images.cpu().numpy(), rows=4, cols=5, rgb=False)
+plt.show()
+
+
+
+
+
+
+
+
+

3. Mesh prediction via silhouette rendering

In the previous section, we created a dataset of images of multiple viewpoints of a cow. In this section, we predict a mesh by observing those target images without any knowledge of the ground truth cow mesh. We assume we know the position of the cameras and lighting.

+

We first define some helper functions to visualize the results of our mesh prediction:

+
+
+
+
+
+
In [ ]:
+
+
+
# Show a visualization comparing the rendered predicted mesh to the ground truth 
+# mesh
+def visualize_prediction(predicted_mesh, renderer=renderer_silhouette, 
+                         target_image=target_rgb[1], title='', 
+                         silhouette=False):
+    inds = 3 if silhouette else range(3)
+    predicted_images = renderer(predicted_mesh)
+    plt.figure(figsize=(20, 10))
+    plt.subplot(1, 2, 1)
+    plt.imshow(predicted_images[0, ..., inds].cpu().detach().numpy())
+
+    plt.subplot(1, 2, 2)
+    plt.imshow(target_image.cpu().detach().numpy())
+    plt.title(title)
+    plt.grid("off")
+    plt.axis("off")
+
+# Plot losses as a function of optimization iteration
+def plot_losses(losses):
+    fig = plt.figure(figsize=(13, 5))
+    ax = fig.gca()
+    for k, l in losses.items():
+        ax.plot(l['values'], label=k + " loss")
+    ax.legend(fontsize="16")
+    ax.set_xlabel("Iteration", fontsize="16")
+    ax.set_ylabel("Loss", fontsize="16")
+    ax.set_title("Loss vs iterations", fontsize="16")
+
+
+
+
+
+
+
+
+

Starting from a sphere mesh, we will learn offsets of each vertex such that the predicted mesh silhouette is more similar to the target silhouette image at each optimization step. We begin by loading our initial sphere mesh:

+
+
+
+
+
+
In [ ]:
+
+
+
# We initialize the source shape to be a sphere of radius 1.  
+src_mesh = ico_sphere(4, device)
+
+
+
+
+
+
+
+
+

We create a new differentiable renderer for rendering the silhouette of our predicted mesh:

+
+
+
+
+
+
In [ ]:
+
+
+
# Rasterization settings for differentiable rendering, where the blur_radius
+# initialization is based on Liu et al, 'Soft Rasterizer: A Differentiable 
+# Renderer for Image-based 3D Reasoning', ICCV 2019
+sigma = 1e-4
+raster_settings_soft = RasterizationSettings(
+    image_size=128, 
+    blur_radius=np.log(1. / 1e-4 - 1.)*sigma, 
+    faces_per_pixel=50, 
+)
+
+# Silhouette renderer 
+renderer_silhouette = MeshRenderer(
+    rasterizer=MeshRasterizer(
+        cameras=camera, 
+        raster_settings=raster_settings_soft
+    ),
+    shader=SoftSilhouetteShader()
+)
+
+
+
+
+
+
+
+
+

We initialize settings, losses, and the optimizer that will be used to iteratively fit our mesh to the target silhouettes:

+
+
+
+
+
+
In [ ]:
+
+
+
# Number of views to optimize over in each SGD iteration
+num_views_per_iteration = 2
+# Number of optimization steps
+Niter = 2000
+# Plot period for the losses
+plot_period = 250
+
+%matplotlib inline
+
+# Optimize using rendered silhouette image loss, mesh edge loss, mesh normal 
+# consistency, and mesh laplacian smoothing
+losses = {"silhouette": {"weight": 1.0, "values": []},
+          "edge": {"weight": 1.0, "values": []},
+          "normal": {"weight": 0.01, "values": []},
+          "laplacian": {"weight": 1.0, "values": []},
+         }
+
+# Losses to smooth / regularize the mesh shape
+def update_mesh_shape_prior_losses(mesh, loss):
+    # and (b) the edge length of the predicted mesh
+    loss["edge"] = mesh_edge_loss(mesh)
+    
+    # mesh normal consistency
+    loss["normal"] = mesh_normal_consistency(mesh)
+    
+    # mesh laplacian smoothing
+    loss["laplacian"] = mesh_laplacian_smoothing(mesh, method="uniform")
+
+# We will learn to deform the source mesh by offsetting its vertices
+# The shape of the deform parameters is equal to the total number of vertices in
+# src_mesh
+verts_shape = src_mesh.verts_packed().shape
+deform_verts = torch.full(verts_shape, 0.0, device=device, requires_grad=True)
+
+# The optimizer
+optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9)
+
+
+
+
+
+
+
+
+

We write an optimization loop to iteratively refine our predicted mesh from the sphere mesh into a mesh that matches the sillhouettes of the target images:

+
+
+
+
+
+
In [ ]:
+
+
+
loop = tqdm(range(Niter))
+
+for i in loop:
+    # Initialize optimizer
+    optimizer.zero_grad()
+    
+    # Deform the mesh
+    new_src_mesh = src_mesh.offset_verts(deform_verts)
+    
+    # Losses to smooth /regularize the mesh shape
+    loss = {k: torch.tensor(0.0, device=device) for k in losses}
+    update_mesh_shape_prior_losses(new_src_mesh, loss)
+    
+    # Compute the average silhouette loss over two random views, as the average 
+    # squared L2 distance between the predicted silhouette and the target 
+    # silhouette from our dataset
+    for j in np.random.permutation(num_views).tolist()[:num_views_per_iteration]:
+        images_predicted = renderer_silhouette(new_src_mesh, cameras=target_cameras[j], lights=lights)
+        predicted_silhouette = images_predicted[..., 3]
+        loss_silhouette = ((predicted_silhouette - target_silhouette[j]) ** 2).mean()
+        loss["silhouette"] += loss_silhouette / num_views_per_iteration
+    
+    # Weighted sum of the losses
+    sum_loss = torch.tensor(0.0, device=device)
+    for k, l in loss.items():
+        sum_loss += l * losses[k]["weight"]
+        losses[k]["values"].append(l)
+    
+    # Print the losses
+    loop.set_description("total_loss = %.6f" % sum_loss)
+    
+    # Plot mesh
+    if i % plot_period == 0:
+        visualize_prediction(new_src_mesh, title="iter: %d" % i, silhouette=True,
+                             target_image=target_silhouette[1])
+        
+    # Optimization step
+    sum_loss.backward()
+    optimizer.step()
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
visualize_prediction(new_src_mesh, silhouette=True, 
+                     target_image=target_silhouette[1])
+plot_losses(losses)
+
+
+
+
+
+
+
+
+

3. Mesh and texture prediction via textured rendering

We can predict both the mesh and its texture if we add an additional loss based on the comparing a predicted rendered RGB image to the target image. As before, we start with a sphere mesh. We learn both translational offsets and RGB texture colors for each vertex in the sphere mesh. Since our loss is based on rendered RGB pixel values instead of just the silhouette, we use a SoftPhongShader instead of a SoftSilhouetteShader.

+
+
+
+
+
+
In [ ]:
+
+
+
# Rasterization settings for differentiable rendering, where the blur_radius
+# initialization is based on Liu et al, 'Soft Rasterizer: A Differentiable 
+# Renderer for Image-based 3D Reasoning', ICCV 2019
+sigma = 1e-4
+raster_settings_soft = RasterizationSettings(
+    image_size=128, 
+    blur_radius=np.log(1. / 1e-4 - 1.)*sigma, 
+    faces_per_pixel=50, 
+)
+
+# Differentiable soft renderer using per vertex RGB colors for texture
+renderer_textured = MeshRenderer(
+    rasterizer=MeshRasterizer(
+        cameras=camera, 
+        raster_settings=raster_settings_soft
+    ),
+    shader=SoftPhongShader(device=device, 
+        cameras=camera,
+        lights=lights)
+)
+
+
+
+
+
+
+
+
+

We initialize settings, losses, and the optimizer that will be used to iteratively fit our mesh to the target RGB images:

+
+
+
+
+
+
In [ ]:
+
+
+
# Number of views to optimize over in each SGD iteration
+num_views_per_iteration = 2
+# Number of optimization steps
+Niter = 2000
+# Plot period for the losses
+plot_period = 250
+
+%matplotlib inline
+
+# Optimize using rendered RGB image loss, rendered silhouette image loss, mesh 
+# edge loss, mesh normal consistency, and mesh laplacian smoothing
+losses = {"rgb": {"weight": 1.0, "values": []},
+          "silhouette": {"weight": 1.0, "values": []},
+          "edge": {"weight": 1.0, "values": []},
+          "normal": {"weight": 0.01, "values": []},
+          "laplacian": {"weight": 1.0, "values": []},
+         }
+
+# We will learn to deform the source mesh by offsetting its vertices
+# The shape of the deform parameters is equal to the total number of vertices in 
+# src_mesh
+verts_shape = src_mesh.verts_packed().shape
+deform_verts = torch.full(verts_shape, 0.0, device=device, requires_grad=True)
+
+# We will also learn per vertex colors for our sphere mesh that define texture 
+# of the mesh
+sphere_verts_rgb = torch.full([1, verts_shape[0], 3], 0.5, device=device, requires_grad=True)
+
+# The optimizer
+optimizer = torch.optim.SGD([deform_verts, sphere_verts_rgb], lr=1.0, momentum=0.9)
+
+
+
+
+
+
+
+
+

We write an optimization loop to iteratively refine our predicted mesh and its vertex colors from the sphere mesh into a mesh that matches the target images:

+
+
+
+
+
+
In [ ]:
+
+
+
loop = tqdm(range(Niter))
+
+for i in loop:
+    # Initialize optimizer
+    optimizer.zero_grad()
+    
+    # Deform the mesh
+    new_src_mesh = src_mesh.offset_verts(deform_verts)
+    
+    # Add per vertex colors to texture the mesh
+    new_src_mesh.textures = TexturesVertex(verts_features=sphere_verts_rgb) 
+    
+    # Losses to smooth /regularize the mesh shape
+    loss = {k: torch.tensor(0.0, device=device) for k in losses}
+    update_mesh_shape_prior_losses(new_src_mesh, loss)
+    
+    # Randomly select two views to optimize over in this iteration.  Compared
+    # to using just one view, this helps resolve ambiguities between updating
+    # mesh shape vs. updating mesh texture
+    for j in np.random.permutation(num_views).tolist()[:num_views_per_iteration]:
+        images_predicted = renderer_textured(new_src_mesh, cameras=target_cameras[j], lights=lights)
+
+        # Squared L2 distance between the predicted silhouette and the target 
+        # silhouette from our dataset
+        predicted_silhouette = images_predicted[..., 3]
+        loss_silhouette = ((predicted_silhouette - target_silhouette[j]) ** 2).mean()
+        loss["silhouette"] += loss_silhouette / num_views_per_iteration
+        
+        # Squared L2 distance between the predicted RGB image and the target 
+        # image from our dataset
+        predicted_rgb = images_predicted[..., :3]
+        loss_rgb = ((predicted_rgb - target_rgb[j]) ** 2).mean()
+        loss["rgb"] += loss_rgb / num_views_per_iteration
+    
+    # Weighted sum of the losses
+    sum_loss = torch.tensor(0.0, device=device)
+    for k, l in loss.items():
+        sum_loss += l * losses[k]["weight"]
+        losses[k]["values"].append(l)
+    
+    # Print the losses
+    loop.set_description("total_loss = %.6f" % sum_loss)
+    
+    # Plot mesh
+    if i % plot_period == 0:
+        visualize_prediction(new_src_mesh, renderer=renderer_textured, title="iter: %d" % i, silhouette=False)
+        
+    # Optimization step
+    sum_loss.backward()
+    optimizer.step()
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
visualize_prediction(new_src_mesh, renderer=renderer_textured, silhouette=False)
+plot_losses(losses)
+
+
+
+
+
+
+
+
+

Save the final predicted mesh:

+
+
+
+
+
+
+

4. Save the final predicted mesh

+
+
+
+
+
+
In [ ]:
+
+
+
# Fetch the verts and faces of the final predicted mesh
+final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0)
+
+# Scale normalize back to the original target size
+final_verts = final_verts * scale + center
+
+# Store the predicted mesh using save_obj
+final_obj = os.path.join('./', 'final_model.obj')
+save_obj(final_obj, final_verts, final_faces)
+
+
+
+
+
+
+
+
+

5. Conclusion

In this tutorial, we learned how to load a textured mesh from an obj file, create a synthetic dataset by rendering the mesh from multiple viewpoints. We showed how to set up an optimization loop to fit a mesh to the observed dataset images based on a rendered silhouette loss. We then augmented this optimization loop with an additional loss based on rendered RGB images, which allowed us to predict both a mesh and its texture.

+
+
+
+
\ No newline at end of file diff --git a/tutorials/fit_textured_mesh/index.html b/tutorials/fit_textured_mesh/index.html new file mode 100644 index 00000000..16c1a569 --- /dev/null +++ b/tutorials/fit_textured_mesh/index.html @@ -0,0 +1,849 @@ +PyTorch3D · A library for deep learning with 3D data
Run in Google Colab
Download Tutorial Jupyter Notebook
Download Tutorial Source Code
+ + +
+
+
+
In [ ]:
+
+
+
# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
+
+
+
+
+
+
+
+
+

Fit a mesh via rendering

This tutorial shows how to:

+
    +
  • Load a mesh and textures from an .obj file.
    • +
  • Create a synthetic dataset by rendering a textured mesh from multiple viewpoints
    • +
  • Fit a mesh to the observed synthetic images using differential silhouette rendering
    • +
  • Fit a mesh and its textures using differential textured rendering
    • +
+
+
+
+
+
+
+

0. Install and Import modules

+
+
+
+
+
+
+

If torch, torchvision and pytorch3d are not installed, run the following cell:

+
+
+
+
+
+
In [ ]:
+
+
+
!pip install torch torchvision
+import sys
+import torch
+if torch.__version__=='1.6.0+cu101' and sys.platform.startswith('linux'):
+    !pip install pytorch3d
+else:
+    !pip install 'git+https://github.com/facebookresearch/pytorch3d.git@stable'
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
import os
+import torch
+import matplotlib.pyplot as plt
+from skimage.io import imread
+
+from pytorch3d.utils import ico_sphere
+import numpy as np
+from tqdm.notebook import tqdm
+
+# Util function for loading meshes
+from pytorch3d.io import load_objs_as_meshes, save_obj
+
+from pytorch3d.loss import (
+    chamfer_distance, 
+    mesh_edge_loss, 
+    mesh_laplacian_smoothing, 
+    mesh_normal_consistency,
+)
+
+# Data structures and functions for rendering
+from pytorch3d.structures import Meshes
+from pytorch3d.renderer import (
+    look_at_view_transform,
+    OpenGLPerspectiveCameras, 
+    PointLights, 
+    DirectionalLights, 
+    Materials, 
+    RasterizationSettings, 
+    MeshRenderer, 
+    MeshRasterizer,  
+    SoftPhongShader,
+    SoftSilhouetteShader,
+    SoftPhongShader,
+    TexturesVertex
+)
+
+# add path for demo utils functions 
+import sys
+import os
+sys.path.append(os.path.abspath(''))
+
+
+
+
+
+
+
+
+

If using Google Colab, fetch the utils file for plotting image grids:

+
+
+
+
+
+
In [ ]:
+
+
+
!wget https://raw.githubusercontent.com/facebookresearch/pytorch3d/master/docs/tutorials/utils/plot_image_grid.py
+from plot_image_grid import image_grid
+
+
+
+
+
+
+
+
+

OR if running locally uncomment and run the following cell:

+
+
+
+
+
+
In [ ]:
+
+
+
#  from utils.plot_image_grid import image_grid
+
+
+
+
+
+
+
+
+

1. Load a mesh and texture file

Load an .obj file and it's associated .mtl file and create a Textures and Meshes object.

+

Meshes is a unique datastructure provided in PyTorch3D for working with batches of meshes of different sizes.

+

TexturesVertex is an auxillary datastructure for storing vertex rgb texture information about meshes.

+

Meshes has several class methods which are used throughout the rendering pipeline.

+
+
+
+
+
+
+

If running this notebook using Google Colab, run the following cell to fetch the mesh obj and texture files and save it at the path data/cow_mesh: +If running locally, the data is already available at the correct path.

+
+
+
+
+
+
In [ ]:
+
+
+
!mkdir -p data/cow_mesh
+!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.obj
+!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow.mtl
+!wget -P data/cow_mesh https://dl.fbaipublicfiles.com/pytorch3d/data/cow_mesh/cow_texture.png
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
# Setup
+if torch.cuda.is_available():
+    device = torch.device("cuda:0")
+    torch.cuda.set_device(device)
+else:
+    device = torch.device("cpu")
+
+# Set paths
+DATA_DIR = "./data"
+obj_filename = os.path.join(DATA_DIR, "cow_mesh/cow.obj")
+
+# Load obj file
+mesh = load_objs_as_meshes([obj_filename], device=device)
+
+# We scale normalize and center the target mesh to fit in a sphere of radius 1 
+# centered at (0,0,0). (scale, center) will be used to bring the predicted mesh 
+# to its original center and scale.  Note that normalizing the target mesh, 
+# speeds up the optimization but is not necessary!
+verts = mesh.verts_packed()
+N = verts.shape[0]
+center = verts.mean(0)
+scale = max((verts - center).abs().max(0)[0])
+mesh.offset_verts_(-center.expand(N, 3))
+mesh.scale_verts_((1.0 / float(scale)));
+
+
+
+
+
+
+
+
+

2. Dataset Creation

We sample different camera positions that encode multiple viewpoints of the cow. We create a renderer with a shader that performs texture map interpolation. We render a synthetic dataset of images of the textured cow mesh from multiple viewpoints.

+
+
+
+
+
+
In [ ]:
+
+
+
# the number of different viewpoints from which we want to render the mesh.
+num_views = 20
+
+# Get a batch of viewing angles. 
+elev = torch.linspace(0, 360, num_views)
+azim = torch.linspace(-180, 180, num_views)
+
+# Place a point light in front of the object. As mentioned above, the front of 
+# the cow is facing the -z direction. 
+lights = PointLights(device=device, location=[[0.0, 0.0, -3.0]])
+
+# Initialize an OpenGL perspective camera that represents a batch of different 
+# viewing angles. All the cameras helper methods support mixed type inputs and 
+# broadcasting. So we can view the camera from the a distance of dist=2.7, and 
+# then specify elevation and azimuth angles for each viewpoint as tensors. 
+R, T = look_at_view_transform(dist=2.7, elev=elev, azim=azim)
+cameras = OpenGLPerspectiveCameras(device=device, R=R, T=T)
+
+# We arbitrarily choose one particular view that will be used to visualize 
+# results
+camera = OpenGLPerspectiveCameras(device=device, R=R[None, 1, ...], 
+                                  T=T[None, 1, ...]) 
+
+# Define the settings for rasterization and shading. Here we set the output 
+# image to be of size 128X128. As we are rendering images for visualization 
+# purposes only we will set faces_per_pixel=1 and blur_radius=0.0. Refer to 
+# rasterize_meshes.py for explanations of these parameters.  We also leave 
+# bin_size and max_faces_per_bin to their default values of None, which sets 
+# their values using huristics and ensures that the faster coarse-to-fine 
+# rasterization method is used.  Refer to docs/notes/renderer.md for an 
+# explanation of the difference between naive and coarse-to-fine rasterization. 
+raster_settings = RasterizationSettings(
+    image_size=128, 
+    blur_radius=0.0, 
+    faces_per_pixel=1, 
+)
+
+# Create a phong renderer by composing a rasterizer and a shader. The textured 
+# phong shader will interpolate the texture uv coordinates for each vertex, 
+# sample from a texture image and apply the Phong lighting model
+renderer = MeshRenderer(
+    rasterizer=MeshRasterizer(
+        cameras=camera, 
+        raster_settings=raster_settings
+    ),
+    shader=SoftPhongShader(
+        device=device, 
+        cameras=camera,
+        lights=lights
+    )
+)
+
+# Create a batch of meshes by repeating the cow mesh and associated textures. 
+# Meshes has a useful `extend` method which allows us do this very easily. 
+# This also extends the textures. 
+meshes = mesh.extend(num_views)
+
+# Render the cow mesh from each viewing angle
+target_images = renderer(meshes, cameras=cameras, lights=lights)
+
+# Our multi-view cow dataset will be represented by these 2 lists of tensors,
+# each of length num_views.
+target_rgb = [target_images[i, ..., :3] for i in range(num_views)]
+target_cameras = [OpenGLPerspectiveCameras(device=device, R=R[None, i, ...], 
+                                           T=T[None, i, ...]) for i in range(num_views)]
+
+
+
+
+
+
+
+
+

Visualize the dataset:

+
+
+
+
+
+
In [ ]:
+
+
+
# RGB images
+image_grid(target_images.cpu().numpy(), rows=4, cols=5, rgb=True)
+plt.show()
+
+
+
+
+
+
+
+
+

Later in this tutorial, we will fit a mesh to the rendered RGB images, as well as to just images of just the cow silhouette. For the latter case, we will render a dataset of silhouette images. Most shaders in PyTorch3D will output an alpha channel along with the RGB image as a 4th channel in an RGBA image. The alpha channel encodes the probability that each pixel belongs to the foreground of the object. We contruct a soft silhouette shader to render this alpha channel.

+
+
+
+
+
+
In [ ]:
+
+
+
# Rasterization settings for silhouette rendering  
+sigma = 1e-4
+raster_settings_silhouette = RasterizationSettings(
+    image_size=128, 
+    blur_radius=np.log(1. / 1e-4 - 1.)*sigma, 
+    faces_per_pixel=50, 
+)
+
+# Silhouette renderer 
+renderer_silhouette = MeshRenderer(
+    rasterizer=MeshRasterizer(
+        cameras=camera, 
+        raster_settings=raster_settings_silhouette
+    ),
+    shader=SoftSilhouetteShader()
+)
+
+# Render silhouette images.  The 3rd channel of the rendering output is 
+# the alpha/silhouette channel
+silhouette_images = renderer_silhouette(meshes, cameras=cameras, lights=lights)
+target_silhouette = [silhouette_images[i, ..., 3] for i in range(num_views)]
+
+# Visualize silhouette images
+image_grid(silhouette_images.cpu().numpy(), rows=4, cols=5, rgb=False)
+plt.show()
+
+
+
+
+
+
+
+
+

3. Mesh prediction via silhouette rendering

In the previous section, we created a dataset of images of multiple viewpoints of a cow. In this section, we predict a mesh by observing those target images without any knowledge of the ground truth cow mesh. We assume we know the position of the cameras and lighting.

+

We first define some helper functions to visualize the results of our mesh prediction:

+
+
+
+
+
+
In [ ]:
+
+
+
# Show a visualization comparing the rendered predicted mesh to the ground truth 
+# mesh
+def visualize_prediction(predicted_mesh, renderer=renderer_silhouette, 
+                         target_image=target_rgb[1], title='', 
+                         silhouette=False):
+    inds = 3 if silhouette else range(3)
+    predicted_images = renderer(predicted_mesh)
+    plt.figure(figsize=(20, 10))
+    plt.subplot(1, 2, 1)
+    plt.imshow(predicted_images[0, ..., inds].cpu().detach().numpy())
+
+    plt.subplot(1, 2, 2)
+    plt.imshow(target_image.cpu().detach().numpy())
+    plt.title(title)
+    plt.grid("off")
+    plt.axis("off")
+
+# Plot losses as a function of optimization iteration
+def plot_losses(losses):
+    fig = plt.figure(figsize=(13, 5))
+    ax = fig.gca()
+    for k, l in losses.items():
+        ax.plot(l['values'], label=k + " loss")
+    ax.legend(fontsize="16")
+    ax.set_xlabel("Iteration", fontsize="16")
+    ax.set_ylabel("Loss", fontsize="16")
+    ax.set_title("Loss vs iterations", fontsize="16")
+
+
+
+
+
+
+
+
+

Starting from a sphere mesh, we will learn offsets of each vertex such that the predicted mesh silhouette is more similar to the target silhouette image at each optimization step. We begin by loading our initial sphere mesh:

+
+
+
+
+
+
In [ ]:
+
+
+
# We initialize the source shape to be a sphere of radius 1.  
+src_mesh = ico_sphere(4, device)
+
+
+
+
+
+
+
+
+

We create a new differentiable renderer for rendering the silhouette of our predicted mesh:

+
+
+
+
+
+
In [ ]:
+
+
+
# Rasterization settings for differentiable rendering, where the blur_radius
+# initialization is based on Liu et al, 'Soft Rasterizer: A Differentiable 
+# Renderer for Image-based 3D Reasoning', ICCV 2019
+sigma = 1e-4
+raster_settings_soft = RasterizationSettings(
+    image_size=128, 
+    blur_radius=np.log(1. / 1e-4 - 1.)*sigma, 
+    faces_per_pixel=50, 
+)
+
+# Silhouette renderer 
+renderer_silhouette = MeshRenderer(
+    rasterizer=MeshRasterizer(
+        cameras=camera, 
+        raster_settings=raster_settings_soft
+    ),
+    shader=SoftSilhouetteShader()
+)
+
+
+
+
+
+
+
+
+

We initialize settings, losses, and the optimizer that will be used to iteratively fit our mesh to the target silhouettes:

+
+
+
+
+
+
In [ ]:
+
+
+
# Number of views to optimize over in each SGD iteration
+num_views_per_iteration = 2
+# Number of optimization steps
+Niter = 2000
+# Plot period for the losses
+plot_period = 250
+
+%matplotlib inline
+
+# Optimize using rendered silhouette image loss, mesh edge loss, mesh normal 
+# consistency, and mesh laplacian smoothing
+losses = {"silhouette": {"weight": 1.0, "values": []},
+          "edge": {"weight": 1.0, "values": []},
+          "normal": {"weight": 0.01, "values": []},
+          "laplacian": {"weight": 1.0, "values": []},
+         }
+
+# Losses to smooth / regularize the mesh shape
+def update_mesh_shape_prior_losses(mesh, loss):
+    # and (b) the edge length of the predicted mesh
+    loss["edge"] = mesh_edge_loss(mesh)
+    
+    # mesh normal consistency
+    loss["normal"] = mesh_normal_consistency(mesh)
+    
+    # mesh laplacian smoothing
+    loss["laplacian"] = mesh_laplacian_smoothing(mesh, method="uniform")
+
+# We will learn to deform the source mesh by offsetting its vertices
+# The shape of the deform parameters is equal to the total number of vertices in
+# src_mesh
+verts_shape = src_mesh.verts_packed().shape
+deform_verts = torch.full(verts_shape, 0.0, device=device, requires_grad=True)
+
+# The optimizer
+optimizer = torch.optim.SGD([deform_verts], lr=1.0, momentum=0.9)
+
+
+
+
+
+
+
+
+

We write an optimization loop to iteratively refine our predicted mesh from the sphere mesh into a mesh that matches the sillhouettes of the target images:

+
+
+
+
+
+
In [ ]:
+
+
+
loop = tqdm(range(Niter))
+
+for i in loop:
+    # Initialize optimizer
+    optimizer.zero_grad()
+    
+    # Deform the mesh
+    new_src_mesh = src_mesh.offset_verts(deform_verts)
+    
+    # Losses to smooth /regularize the mesh shape
+    loss = {k: torch.tensor(0.0, device=device) for k in losses}
+    update_mesh_shape_prior_losses(new_src_mesh, loss)
+    
+    # Compute the average silhouette loss over two random views, as the average 
+    # squared L2 distance between the predicted silhouette and the target 
+    # silhouette from our dataset
+    for j in np.random.permutation(num_views).tolist()[:num_views_per_iteration]:
+        images_predicted = renderer_silhouette(new_src_mesh, cameras=target_cameras[j], lights=lights)
+        predicted_silhouette = images_predicted[..., 3]
+        loss_silhouette = ((predicted_silhouette - target_silhouette[j]) ** 2).mean()
+        loss["silhouette"] += loss_silhouette / num_views_per_iteration
+    
+    # Weighted sum of the losses
+    sum_loss = torch.tensor(0.0, device=device)
+    for k, l in loss.items():
+        sum_loss += l * losses[k]["weight"]
+        losses[k]["values"].append(l)
+    
+    # Print the losses
+    loop.set_description("total_loss = %.6f" % sum_loss)
+    
+    # Plot mesh
+    if i % plot_period == 0:
+        visualize_prediction(new_src_mesh, title="iter: %d" % i, silhouette=True,
+                             target_image=target_silhouette[1])
+        
+    # Optimization step
+    sum_loss.backward()
+    optimizer.step()
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
visualize_prediction(new_src_mesh, silhouette=True, 
+                     target_image=target_silhouette[1])
+plot_losses(losses)
+
+
+
+
+
+
+
+
+

3. Mesh and texture prediction via textured rendering

We can predict both the mesh and its texture if we add an additional loss based on the comparing a predicted rendered RGB image to the target image. As before, we start with a sphere mesh. We learn both translational offsets and RGB texture colors for each vertex in the sphere mesh. Since our loss is based on rendered RGB pixel values instead of just the silhouette, we use a SoftPhongShader instead of a SoftSilhouetteShader.

+
+
+
+
+
+
In [ ]:
+
+
+
# Rasterization settings for differentiable rendering, where the blur_radius
+# initialization is based on Liu et al, 'Soft Rasterizer: A Differentiable 
+# Renderer for Image-based 3D Reasoning', ICCV 2019
+sigma = 1e-4
+raster_settings_soft = RasterizationSettings(
+    image_size=128, 
+    blur_radius=np.log(1. / 1e-4 - 1.)*sigma, 
+    faces_per_pixel=50, 
+)
+
+# Differentiable soft renderer using per vertex RGB colors for texture
+renderer_textured = MeshRenderer(
+    rasterizer=MeshRasterizer(
+        cameras=camera, 
+        raster_settings=raster_settings_soft
+    ),
+    shader=SoftPhongShader(device=device, 
+        cameras=camera,
+        lights=lights)
+)
+
+
+
+
+
+
+
+
+

We initialize settings, losses, and the optimizer that will be used to iteratively fit our mesh to the target RGB images:

+
+
+
+
+
+
In [ ]:
+
+
+
# Number of views to optimize over in each SGD iteration
+num_views_per_iteration = 2
+# Number of optimization steps
+Niter = 2000
+# Plot period for the losses
+plot_period = 250
+
+%matplotlib inline
+
+# Optimize using rendered RGB image loss, rendered silhouette image loss, mesh 
+# edge loss, mesh normal consistency, and mesh laplacian smoothing
+losses = {"rgb": {"weight": 1.0, "values": []},
+          "silhouette": {"weight": 1.0, "values": []},
+          "edge": {"weight": 1.0, "values": []},
+          "normal": {"weight": 0.01, "values": []},
+          "laplacian": {"weight": 1.0, "values": []},
+         }
+
+# We will learn to deform the source mesh by offsetting its vertices
+# The shape of the deform parameters is equal to the total number of vertices in 
+# src_mesh
+verts_shape = src_mesh.verts_packed().shape
+deform_verts = torch.full(verts_shape, 0.0, device=device, requires_grad=True)
+
+# We will also learn per vertex colors for our sphere mesh that define texture 
+# of the mesh
+sphere_verts_rgb = torch.full([1, verts_shape[0], 3], 0.5, device=device, requires_grad=True)
+
+# The optimizer
+optimizer = torch.optim.SGD([deform_verts, sphere_verts_rgb], lr=1.0, momentum=0.9)
+
+
+
+
+
+
+
+
+

We write an optimization loop to iteratively refine our predicted mesh and its vertex colors from the sphere mesh into a mesh that matches the target images:

+
+
+
+
+
+
In [ ]:
+
+
+
loop = tqdm(range(Niter))
+
+for i in loop:
+    # Initialize optimizer
+    optimizer.zero_grad()
+    
+    # Deform the mesh
+    new_src_mesh = src_mesh.offset_verts(deform_verts)
+    
+    # Add per vertex colors to texture the mesh
+    new_src_mesh.textures = TexturesVertex(verts_features=sphere_verts_rgb) 
+    
+    # Losses to smooth /regularize the mesh shape
+    loss = {k: torch.tensor(0.0, device=device) for k in losses}
+    update_mesh_shape_prior_losses(new_src_mesh, loss)
+    
+    # Randomly select two views to optimize over in this iteration.  Compared
+    # to using just one view, this helps resolve ambiguities between updating
+    # mesh shape vs. updating mesh texture
+    for j in np.random.permutation(num_views).tolist()[:num_views_per_iteration]:
+        images_predicted = renderer_textured(new_src_mesh, cameras=target_cameras[j], lights=lights)
+
+        # Squared L2 distance between the predicted silhouette and the target 
+        # silhouette from our dataset
+        predicted_silhouette = images_predicted[..., 3]
+        loss_silhouette = ((predicted_silhouette - target_silhouette[j]) ** 2).mean()
+        loss["silhouette"] += loss_silhouette / num_views_per_iteration
+        
+        # Squared L2 distance between the predicted RGB image and the target 
+        # image from our dataset
+        predicted_rgb = images_predicted[..., :3]
+        loss_rgb = ((predicted_rgb - target_rgb[j]) ** 2).mean()
+        loss["rgb"] += loss_rgb / num_views_per_iteration
+    
+    # Weighted sum of the losses
+    sum_loss = torch.tensor(0.0, device=device)
+    for k, l in loss.items():
+        sum_loss += l * losses[k]["weight"]
+        losses[k]["values"].append(l)
+    
+    # Print the losses
+    loop.set_description("total_loss = %.6f" % sum_loss)
+    
+    # Plot mesh
+    if i % plot_period == 0:
+        visualize_prediction(new_src_mesh, renderer=renderer_textured, title="iter: %d" % i, silhouette=False)
+        
+    # Optimization step
+    sum_loss.backward()
+    optimizer.step()
+
+
+
+
+
+
+
+
In [ ]:
+
+
+
visualize_prediction(new_src_mesh, renderer=renderer_textured, silhouette=False)
+plot_losses(losses)
+
+
+
+
+
+
+
+
+

Save the final predicted mesh:

+
+
+
+
+
+
+

4. Save the final predicted mesh

+
+
+
+
+
+
In [ ]:
+
+
+
# Fetch the verts and faces of the final predicted mesh
+final_verts, final_faces = new_src_mesh.get_mesh_verts_faces(0)
+
+# Scale normalize back to the original target size
+final_verts = final_verts * scale + center
+
+# Store the predicted mesh using save_obj
+final_obj = os.path.join('./', 'final_model.obj')
+save_obj(final_obj, final_verts, final_faces)
+
+
+
+
+
+
+
+
+

5. Conclusion

In this tutorial, we learned how to load a textured mesh from an obj file, create a synthetic dataset by rendering the mesh from multiple viewpoints. We showed how to set up an optimization loop to fit a mesh to the observed dataset images based on a rendered silhouette loss. We then augmented this optimization loop with an additional loss based on rendered RGB images, which allowed us to predict both a mesh and its texture.

+
+
+
+
\ No newline at end of file diff --git a/tutorials/index.html b/tutorials/index.html index db22d201..6f15fe09 100644 --- a/tutorials/index.html +++ b/tutorials/index.html @@ -6,7 +6,7 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -
This installs the latest stable version of PyTorch3D from github.

Run locally

There is also a button to download the notebook and source code to run it locally.

\ No newline at end of file diff --git a/tutorials/render_textured_meshes.html b/tutorials/render_textured_meshes.html index 29484fe3..011e9f88 100644 --- a/tutorials/render_textured_meshes.html +++ b/tutorials/render_textured_meshes.html @@ -6,7 +6,7 @@ ga('create', 'UA-157376881-1', 'auto'); ga('send', 'pageview'); -