dlnd_face_generation.html

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<title>dlnd_face_generation</title>

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.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.7.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.7.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.7.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff2?v=4.7.0') format('woff2'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.7.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.7.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.7.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.fa-pull-left {
  float: left;
}
.fa-pull-right {
  float: right;
}
.fa.fa-pull-left {
  margin-right: .3em;
}
.fa.fa-pull-right {
  margin-left: .3em;
}
/* Deprecated as of 4.4.0 */
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
.fa-pulse {
  -webkit-animation: fa-spin 1s infinite steps(8);
  animation: fa-spin 1s infinite steps(8);
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=1)";
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2)";
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=3)";
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1)";
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  -ms-filter: "progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1)";
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook-f:before,
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-feed:before,
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before,
.fa-gratipay:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper-pp:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-resistance:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-y-combinator-square:before,
.fa-yc-square:before,
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
.fa-buysellads:before {
  content: "\f20d";
}
.fa-connectdevelop:before {
  content: "\f20e";
}
.fa-dashcube:before {
  content: "\f210";
}
.fa-forumbee:before {
  content: "\f211";
}
.fa-leanpub:before {
  content: "\f212";
}
.fa-sellsy:before {
  content: "\f213";
}
.fa-shirtsinbulk:before {
  content: "\f214";
}
.fa-simplybuilt:before {
  content: "\f215";
}
.fa-skyatlas:before {
  content: "\f216";
}
.fa-cart-plus:before {
  content: "\f217";
}
.fa-cart-arrow-down:before {
  content: "\f218";
}
.fa-diamond:before {
  content: "\f219";
}
.fa-ship:before {
  content: "\f21a";
}
.fa-user-secret:before {
  content: "\f21b";
}
.fa-motorcycle:before {
  content: "\f21c";
}
.fa-street-view:before {
  content: "\f21d";
}
.fa-heartbeat:before {
  content: "\f21e";
}
.fa-venus:before {
  content: "\f221";
}
.fa-mars:before {
  content: "\f222";
}
.fa-mercury:before {
  content: "\f223";
}
.fa-intersex:before,
.fa-transgender:before {
  content: "\f224";
}
.fa-transgender-alt:before {
  content: "\f225";
}
.fa-venus-double:before {
  content: "\f226";
}
.fa-mars-double:before {
  content: "\f227";
}
.fa-venus-mars:before {
  content: "\f228";
}
.fa-mars-stroke:before {
  content: "\f229";
}
.fa-mars-stroke-v:before {
  content: "\f22a";
}
.fa-mars-stroke-h:before {
  content: "\f22b";
}
.fa-neuter:before {
  content: "\f22c";
}
.fa-genderless:before {
  content: "\f22d";
}
.fa-facebook-official:before {
  content: "\f230";
}
.fa-pinterest-p:before {
  content: "\f231";
}
.fa-whatsapp:before {
  content: "\f232";
}
.fa-server:before {
  content: "\f233";
}
.fa-user-plus:before {
  content: "\f234";
}
.fa-user-times:before {
  content: "\f235";
}
.fa-hotel:before,
.fa-bed:before {
  content: "\f236";
}
.fa-viacoin:before {
  content: "\f237";
}
.fa-train:before {
  content: "\f238";
}
.fa-subway:before {
  content: "\f239";
}
.fa-medium:before {
  content: "\f23a";
}
.fa-yc:before,
.fa-y-combinator:before {
  content: "\f23b";
}
.fa-optin-monster:before {
  content: "\f23c";
}
.fa-opencart:before {
  content: "\f23d";
}
.fa-expeditedssl:before {
  content: "\f23e";
}
.fa-battery-4:before,
.fa-battery:before,
.fa-battery-full:before {
  content: "\f240";
}
.fa-battery-3:before,
.fa-battery-three-quarters:before {
  content: "\f241";
}
.fa-battery-2:before,
.fa-battery-half:before {
  content: "\f242";
}
.fa-battery-1:before,
.fa-battery-quarter:before {
  content: "\f243";
}
.fa-battery-0:before,
.fa-battery-empty:before {
  content: "\f244";
}
.fa-mouse-pointer:before {
  content: "\f245";
}
.fa-i-cursor:before {
  content: "\f246";
}
.fa-object-group:before {
  content: "\f247";
}
.fa-object-ungroup:before {
  content: "\f248";
}
.fa-sticky-note:before {
  content: "\f249";
}
.fa-sticky-note-o:before {
  content: "\f24a";
}
.fa-cc-jcb:before {
  content: "\f24b";
}
.fa-cc-diners-club:before {
  content: "\f24c";
}
.fa-clone:before {
  content: "\f24d";
}
.fa-balance-scale:before {
  content: "\f24e";
}
.fa-hourglass-o:before {
  content: "\f250";
}
.fa-hourglass-1:before,
.fa-hourglass-start:before {
  content: "\f251";
}
.fa-hourglass-2:before,
.fa-hourglass-half:before {
  content: "\f252";
}
.fa-hourglass-3:before,
.fa-hourglass-end:before {
  content: "\f253";
}
.fa-hourglass:before {
  content: "\f254";
}
.fa-hand-grab-o:before,
.fa-hand-rock-o:before {
  content: "\f255";
}
.fa-hand-stop-o:before,
.fa-hand-paper-o:before {
  content: "\f256";
}
.fa-hand-scissors-o:before {
  content: "\f257";
}
.fa-hand-lizard-o:before {
  content: "\f258";
}
.fa-hand-spock-o:before {
  content: "\f259";
}
.fa-hand-pointer-o:before {
  content: "\f25a";
}
.fa-hand-peace-o:before {
  content: "\f25b";
}
.fa-trademark:before {
  content: "\f25c";
}
.fa-registered:before {
  content: "\f25d";
}
.fa-creative-commons:before {
  content: "\f25e";
}
.fa-gg:before {
  content: "\f260";
}
.fa-gg-circle:before {
  content: "\f261";
}
.fa-tripadvisor:before {
  content: "\f262";
}
.fa-odnoklassniki:before {
  content: "\f263";
}
.fa-odnoklassniki-square:before {
  content: "\f264";
}
.fa-get-pocket:before {
  content: "\f265";
}
.fa-wikipedia-w:before {
  content: "\f266";
}
.fa-safari:before {
  content: "\f267";
}
.fa-chrome:before {
  content: "\f268";
}
.fa-firefox:before {
  content: "\f269";
}
.fa-opera:before {
  content: "\f26a";
}
.fa-internet-explorer:before {
  content: "\f26b";
}
.fa-tv:before,
.fa-television:before {
  content: "\f26c";
}
.fa-contao:before {
  content: "\f26d";
}
.fa-500px:before {
  content: "\f26e";
}
.fa-amazon:before {
  content: "\f270";
}
.fa-calendar-plus-o:before {
  content: "\f271";
}
.fa-calendar-minus-o:before {
  content: "\f272";
}
.fa-calendar-times-o:before {
  content: "\f273";
}
.fa-calendar-check-o:before {
  content: "\f274";
}
.fa-industry:before {
  content: "\f275";
}
.fa-map-pin:before {
  content: "\f276";
}
.fa-map-signs:before {
  content: "\f277";
}
.fa-map-o:before {
  content: "\f278";
}
.fa-map:before {
  content: "\f279";
}
.fa-commenting:before {
  content: "\f27a";
}
.fa-commenting-o:before {
  content: "\f27b";
}
.fa-houzz:before {
  content: "\f27c";
}
.fa-vimeo:before {
  content: "\f27d";
}
.fa-black-tie:before {
  content: "\f27e";
}
.fa-fonticons:before {
  content: "\f280";
}
.fa-reddit-alien:before {
  content: "\f281";
}
.fa-edge:before {
  content: "\f282";
}
.fa-credit-card-alt:before {
  content: "\f283";
}
.fa-codiepie:before {
  content: "\f284";
}
.fa-modx:before {
  content: "\f285";
}
.fa-fort-awesome:before {
  content: "\f286";
}
.fa-usb:before {
  content: "\f287";
}
.fa-product-hunt:before {
  content: "\f288";
}
.fa-mixcloud:before {
  content: "\f289";
}
.fa-scribd:before {
  content: "\f28a";
}
.fa-pause-circle:before {
  content: "\f28b";
}
.fa-pause-circle-o:before {
  content: "\f28c";
}
.fa-stop-circle:before {
  content: "\f28d";
}
.fa-stop-circle-o:before {
  content: "\f28e";
}
.fa-shopping-bag:before {
  content: "\f290";
}
.fa-shopping-basket:before {
  content: "\f291";
}
.fa-hashtag:before {
  content: "\f292";
}
.fa-bluetooth:before {
  content: "\f293";
}
.fa-bluetooth-b:before {
  content: "\f294";
}
.fa-percent:before {
  content: "\f295";
}
.fa-gitlab:before {
  content: "\f296";
}
.fa-wpbeginner:before {
  content: "\f297";
}
.fa-wpforms:before {
  content: "\f298";
}
.fa-envira:before {
  content: "\f299";
}
.fa-universal-access:before {
  content: "\f29a";
}
.fa-wheelchair-alt:before {
  content: "\f29b";
}
.fa-question-circle-o:before {
  content: "\f29c";
}
.fa-blind:before {
  content: "\f29d";
}
.fa-audio-description:before {
  content: "\f29e";
}
.fa-volume-control-phone:before {
  content: "\f2a0";
}
.fa-braille:before {
  content: "\f2a1";
}
.fa-assistive-listening-systems:before {
  content: "\f2a2";
}
.fa-asl-interpreting:before,
.fa-american-sign-language-interpreting:before {
  content: "\f2a3";
}
.fa-deafness:before,
.fa-hard-of-hearing:before,
.fa-deaf:before {
  content: "\f2a4";
}
.fa-glide:before {
  content: "\f2a5";
}
.fa-glide-g:before {
  content: "\f2a6";
}
.fa-signing:before,
.fa-sign-language:before {
  content: "\f2a7";
}
.fa-low-vision:before {
  content: "\f2a8";
}
.fa-viadeo:before {
  content: "\f2a9";
}
.fa-viadeo-square:before {
  content: "\f2aa";
}
.fa-snapchat:before {
  content: "\f2ab";
}
.fa-snapchat-ghost:before {
  content: "\f2ac";
}
.fa-snapchat-square:before {
  content: "\f2ad";
}
.fa-pied-piper:before {
  content: "\f2ae";
}
.fa-first-order:before {
  content: "\f2b0";
}
.fa-yoast:before {
  content: "\f2b1";
}
.fa-themeisle:before {
  content: "\f2b2";
}
.fa-google-plus-circle:before,
.fa-google-plus-official:before {
  content: "\f2b3";
}
.fa-fa:before,
.fa-font-awesome:before {
  content: "\f2b4";
}
.fa-handshake-o:before {
  content: "\f2b5";
}
.fa-envelope-open:before {
  content: "\f2b6";
}
.fa-envelope-open-o:before {
  content: "\f2b7";
}
.fa-linode:before {
  content: "\f2b8";
}
.fa-address-book:before {
  content: "\f2b9";
}
.fa-address-book-o:before {
  content: "\f2ba";
}
.fa-vcard:before,
.fa-address-card:before {
  content: "\f2bb";
}
.fa-vcard-o:before,
.fa-address-card-o:before {
  content: "\f2bc";
}
.fa-user-circle:before {
  content: "\f2bd";
}
.fa-user-circle-o:before {
  content: "\f2be";
}
.fa-user-o:before {
  content: "\f2c0";
}
.fa-id-badge:before {
  content: "\f2c1";
}
.fa-drivers-license:before,
.fa-id-card:before {
  content: "\f2c2";
}
.fa-drivers-license-o:before,
.fa-id-card-o:before {
  content: "\f2c3";
}
.fa-quora:before {
  content: "\f2c4";
}
.fa-free-code-camp:before {
  content: "\f2c5";
}
.fa-telegram:before {
  content: "\f2c6";
}
.fa-thermometer-4:before,
.fa-thermometer:before,
.fa-thermometer-full:before {
  content: "\f2c7";
}
.fa-thermometer-3:before,
.fa-thermometer-three-quarters:before {
  content: "\f2c8";
}
.fa-thermometer-2:before,
.fa-thermometer-half:before {
  content: "\f2c9";
}
.fa-thermometer-1:before,
.fa-thermometer-quarter:before {
  content: "\f2ca";
}
.fa-thermometer-0:before,
.fa-thermometer-empty:before {
  content: "\f2cb";
}
.fa-shower:before {
  content: "\f2cc";
}
.fa-bathtub:before,
.fa-s15:before,
.fa-bath:before {
  content: "\f2cd";
}
.fa-podcast:before {
  content: "\f2ce";
}
.fa-window-maximize:before {
  content: "\f2d0";
}
.fa-window-minimize:before {
  content: "\f2d1";
}
.fa-window-restore:before {
  content: "\f2d2";
}
.fa-times-rectangle:before,
.fa-window-close:before {
  content: "\f2d3";
}
.fa-times-rectangle-o:before,
.fa-window-close-o:before {
  content: "\f2d4";
}
.fa-bandcamp:before {
  content: "\f2d5";
}
.fa-grav:before {
  content: "\f2d6";
}
.fa-etsy:before {
  content: "\f2d7";
}
.fa-imdb:before {
  content: "\f2d8";
}
.fa-ravelry:before {
  content: "\f2d9";
}
.fa-eercast:before {
  content: "\f2da";
}
.fa-microchip:before {
  content: "\f2db";
}
.fa-snowflake-o:before {
  content: "\f2dc";
}
.fa-superpowers:before {
  content: "\f2dd";
}
.fa-wpexplorer:before {
  content: "\f2de";
}
.fa-meetup:before {
  content: "\f2e0";
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  padding: 0;
  margin: -1px;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
div.traceback-wrapper pre.traceback {
  max-height: 600px;
  overflow: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  display: flex;
  flex-direction: row;
  justify-content: space-between;
  padding: 5px;
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
[dir="rtl"] #ipython_notebook {
  margin-right: 10px;
  margin-left: 0;
}
[dir="rtl"] #ipython_notebook.pull-left {
  float: right !important;
  float: right;
}
.flex-spacer {
  flex: 1;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#kernel_logo_widget {
  margin: 0 10px;
}
span#login_widget {
  float: right;
}
[dir="rtl"] span#login_widget {
  float: left;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
.modal-header {
  cursor: move;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
[dir="rtl"] .center-nav form.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] .center-nav .navbar-text {
  float: right;
}
[dir="rtl"] .navbar-inner {
  text-align: right;
}
[dir="rtl"] div.text-left {
  text-align: right;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  position: absolute;
  display: block;
  width: 100%;
  height: 100%;
  overflow: hidden;
  cursor: pointer;
  opacity: 0;
  z-index: 2;
}
.alternate_upload .btn-xs > input.fileinput {
  margin: -1px -5px;
}
.alternate_upload .btn-upload {
  position: relative;
  height: 22px;
}
::-webkit-file-upload-button {
  cursor: pointer;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
ul#tabs {
  margin-bottom: 4px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
[dir="rtl"] ul#tabs.nav-tabs > li {
  float: right;
}
[dir="rtl"] ul#tabs.nav.nav-tabs {
  padding-right: 0;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons .pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .list_toolbar .col-sm-4,
[dir="rtl"] .list_toolbar .col-sm-8 {
  float: right;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: text-bottom;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
[dir="rtl"] .list_item > div input {
  margin-right: 0;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_modified {
  margin-right: 7px;
  margin-left: 7px;
}
[dir="rtl"] .item_modified.pull-right {
  float: left !important;
  float: left;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
[dir="rtl"] .item_buttons.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .item_buttons .kernel-name {
  margin-left: 7px;
  float: right;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
.sort_button {
  display: inline-block;
  padding-left: 7px;
}
[dir="rtl"] .sort_button.pull-right {
  float: left !important;
  float: left;
}
#tree-selector {
  padding-right: 0px;
}
#button-select-all {
  min-width: 50px;
}
[dir="rtl"] #button-select-all.btn {
  float: right ;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
  margin-top: 2px;
  height: 16px;
}
[dir="rtl"] #select-all.pull-left {
  float: right !important;
  float: right;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.fa-pull-left {
  margin-right: .3em;
}
.folder_icon:before.fa-pull-right {
  margin-left: .3em;
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.fa-pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.fa-pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.fa-pull-left {
  margin-right: .3em;
}
.file_icon:before.fa-pull-right {
  margin-left: .3em;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
#new-menu .dropdown-header {
  font-size: 10px;
  border-bottom: 1px solid #e5e5e5;
  padding: 0 0 3px;
  margin: -3px 20px 0;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.move-button {
  display: none;
}
.download-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.fa-pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.fa-pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
.CodeMirror-dialog {
  background-color: #fff;
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI escape sequences */
/* The color values are a mix of
   http://www.xcolors.net/dl/baskerville-ivorylight and
   http://www.xcolors.net/dl/euphrasia */
.ansi-black-fg {
  color: #3E424D;
}
.ansi-black-bg {
  background-color: #3E424D;
}
.ansi-black-intense-fg {
  color: #282C36;
}
.ansi-black-intense-bg {
  background-color: #282C36;
}
.ansi-red-fg {
  color: #E75C58;
}
.ansi-red-bg {
  background-color: #E75C58;
}
.ansi-red-intense-fg {
  color: #B22B31;
}
.ansi-red-intense-bg {
  background-color: #B22B31;
}
.ansi-green-fg {
  color: #00A250;
}
.ansi-green-bg {
  background-color: #00A250;
}
.ansi-green-intense-fg {
  color: #007427;
}
.ansi-green-intense-bg {
  background-color: #007427;
}
.ansi-yellow-fg {
  color: #DDB62B;
}
.ansi-yellow-bg {
  background-color: #DDB62B;
}
.ansi-yellow-intense-fg {
  color: #B27D12;
}
.ansi-yellow-intense-bg {
  background-color: #B27D12;
}
.ansi-blue-fg {
  color: #208FFB;
}
.ansi-blue-bg {
  background-color: #208FFB;
}
.ansi-blue-intense-fg {
  color: #0065CA;
}
.ansi-blue-intense-bg {
  background-color: #0065CA;
}
.ansi-magenta-fg {
  color: #D160C4;
}
.ansi-magenta-bg {
  background-color: #D160C4;
}
.ansi-magenta-intense-fg {
  color: #A03196;
}
.ansi-magenta-intense-bg {
  background-color: #A03196;
}
.ansi-cyan-fg {
  color: #60C6C8;
}
.ansi-cyan-bg {
  background-color: #60C6C8;
}
.ansi-cyan-intense-fg {
  color: #258F8F;
}
.ansi-cyan-intense-bg {
  background-color: #258F8F;
}
.ansi-white-fg {
  color: #C5C1B4;
}
.ansi-white-bg {
  background-color: #C5C1B4;
}
.ansi-white-intense-fg {
  color: #A1A6B2;
}
.ansi-white-intense-bg {
  background-color: #A1A6B2;
}
.ansi-default-inverse-fg {
  color: #FFFFFF;
}
.ansi-default-inverse-bg {
  background-color: #000000;
}
.ansi-bold {
  font-weight: bold;
}
.ansi-underline {
  text-decoration: underline;
}
/* The following styles are deprecated an will be removed in a future version */
.ansibold {
  font-weight: bold;
}
.ansi-inverse {
  outline: 0.5px dotted;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  position: relative;
  overflow: visible;
}
div.cell:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: transparent;
}
div.cell.jupyter-soft-selected {
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected,
div.cell.selected.jupyter-soft-selected {
  border-color: #ababab;
}
div.cell.selected:before,
div.cell.selected.jupyter-soft-selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #42A5F5;
}
@media print {
  div.cell.selected,
  div.cell.selected.jupyter-soft-selected {
    border-color: transparent;
  }
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
}
.edit_mode div.cell.selected:before {
  position: absolute;
  display: block;
  top: -1px;
  left: -1px;
  width: 5px;
  height: calc(100% +  2px);
  content: '';
  background: #66BB6A;
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  /* Note that this should set vertical padding only, since CodeMirror assumes
       that horizontal padding will be set on CodeMirror pre */
  padding: 0.4em 0;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. This sets horizontal padding only,
    use .CodeMirror-lines for vertical */
  padding: 0 0.4em;
  border: 0;
  border-radius: 0;
}
.CodeMirror-cursor {
  border-left: 1.4px solid black;
}
@media screen and (min-width: 2138px) and (max-width: 4319px) {
  .CodeMirror-cursor {
    border-left: 2px solid black;
  }
}
@media screen and (min-width: 4320px) {
  .CodeMirror-cursor {
    border-left: 4px solid black;
  }
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
div.output_area .mglyph > img {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 1px 0 1px 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul:not(.list-inline),
.rendered_html ol:not(.list-inline) {
  padding-left: 2em;
}
.rendered_html ul {
  list-style: disc;
}
.rendered_html ul ul {
  list-style: square;
  margin-top: 0;
}
.rendered_html ul ul ul {
  list-style: circle;
}
.rendered_html ol {
  list-style: decimal;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin-top: 0;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
  padding: 0px;
  background-color: #fff;
}
.rendered_html code {
  background-color: #eff0f1;
}
.rendered_html p code {
  padding: 1px 5px;
}
.rendered_html pre code {
  background-color: #fff;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  color: #000;
  font-size: 100%;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: none;
  border-collapse: collapse;
  border-spacing: 0;
  color: black;
  font-size: 12px;
  table-layout: fixed;
}
.rendered_html thead {
  border-bottom: 1px solid black;
  vertical-align: bottom;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  text-align: right;
  vertical-align: middle;
  padding: 0.5em 0.5em;
  line-height: normal;
  white-space: normal;
  max-width: none;
  border: none;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html tbody tr:nth-child(odd) {
  background: #f5f5f5;
}
.rendered_html tbody tr:hover {
  background: rgba(66, 165, 245, 0.2);
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
.rendered_html .alert {
  margin-bottom: initial;
}
.rendered_html * + .alert {
  margin-top: 1em;
}
[dir="rtl"] .rendered_html p {
  text-align: right;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.rendered .rendered_html tr,
.text_cell.rendered .rendered_html th,
.text_cell.rendered .rendered_html td {
  max-width: none;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.text_cell .dropzone .input_area {
  border: 2px dashed #bababa;
  margin: -1px;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
.jupyter-keybindings {
  padding: 1px;
  line-height: 24px;
  border-bottom: 1px solid gray;
}
.jupyter-keybindings input {
  margin: 0;
  padding: 0;
  border: none;
}
.jupyter-keybindings i {
  padding: 6px;
}
.well code {
  background-color: #ffffff;
  border-color: #ababab;
  border-width: 1px;
  border-style: solid;
  padding: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.tags_button_container {
  width: 100%;
  display: flex;
}
.tag-container {
  display: flex;
  flex-direction: row;
  flex-grow: 1;
  overflow: hidden;
  position: relative;
}
.tag-container > * {
  margin: 0 4px;
}
.remove-tag-btn {
  margin-left: 4px;
}
.tags-input {
  display: flex;
}
.cell-tag:last-child:after {
  content: "";
  position: absolute;
  right: 0;
  width: 40px;
  height: 100%;
  /* Fade to background color of cell toolbar */
  background: linear-gradient(to right, rgba(0, 0, 0, 0), #EEE);
}
.tags-input > * {
  margin-left: 4px;
}
.cell-tag,
.tags-input input,
.tags-input button {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  box-shadow: none;
  width: inherit;
  font-size: inherit;
  height: 22px;
  line-height: 22px;
  padding: 0px 4px;
  display: inline-block;
}
.cell-tag:focus,
.tags-input input:focus,
.tags-input button:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.cell-tag::-moz-placeholder,
.tags-input input::-moz-placeholder,
.tags-input button::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.cell-tag:-ms-input-placeholder,
.tags-input input:-ms-input-placeholder,
.tags-input button:-ms-input-placeholder {
  color: #999;
}
.cell-tag::-webkit-input-placeholder,
.tags-input input::-webkit-input-placeholder,
.tags-input button::-webkit-input-placeholder {
  color: #999;
}
.cell-tag::-ms-expand,
.tags-input input::-ms-expand,
.tags-input button::-ms-expand {
  border: 0;
  background-color: transparent;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
.cell-tag[readonly],
.tags-input input[readonly],
.tags-input button[readonly],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  background-color: #eeeeee;
  opacity: 1;
}
.cell-tag[disabled],
.tags-input input[disabled],
.tags-input button[disabled],
fieldset[disabled] .cell-tag,
fieldset[disabled] .tags-input input,
fieldset[disabled] .tags-input button {
  cursor: not-allowed;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button {
  height: auto;
}
select.cell-tag,
select.tags-input input,
select.tags-input button {
  height: 30px;
  line-height: 30px;
}
textarea.cell-tag,
textarea.tags-input input,
textarea.tags-input button,
select[multiple].cell-tag,
select[multiple].tags-input input,
select[multiple].tags-input button {
  height: auto;
}
.cell-tag,
.tags-input button {
  padding: 0px 4px;
}
.cell-tag {
  background-color: #fff;
  white-space: nowrap;
}
.tags-input input[type=text]:focus {
  outline: none;
  box-shadow: none;
  border-color: #ccc;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
[dir="rtl"] #kernel_logo_widget {
  float: left !important;
  float: left;
}
.modal .modal-body .move-path {
  display: flex;
  flex-direction: row;
  justify-content: space;
  align-items: center;
}
.modal .modal-body .move-path .server-root {
  padding-right: 20px;
}
.modal .modal-body .move-path .path-input {
  flex: 1;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
[dir="rtl"] #menubar .navbar-toggle {
  float: right;
}
[dir="rtl"] #menubar .navbar-collapse {
  clear: right;
}
[dir="rtl"] #menubar .navbar-nav {
  float: right;
}
[dir="rtl"] #menubar .nav {
  padding-right: 0px;
}
[dir="rtl"] #menubar .navbar-nav > li {
  float: right;
}
[dir="rtl"] #menubar .navbar-right {
  float: left !important;
}
[dir="rtl"] ul.dropdown-menu {
  text-align: right;
  left: auto;
}
[dir="rtl"] ul#new-menu.dropdown-menu {
  right: auto;
  left: 0;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
[dir="rtl"] i.menu-icon.pull-right {
  float: left !important;
  float: left;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
[dir="rtl"] ul#help_menu li a {
  padding-left: 2.2em;
}
[dir="rtl"] ul#help_menu li a i {
  margin-right: 0;
  margin-left: -1.2em;
}
[dir="rtl"] ul#help_menu li a i.pull-right {
  float: left !important;
  float: left;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
[dir="rtl"] .dropdown-submenu > .dropdown-menu {
  right: 100%;
  margin-right: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.fa-pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.fa-pull-right {
  margin-left: .3em;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
[dir="rtl"] .dropdown-submenu > a:after {
  float: left;
  content: "\f0d9";
  margin-right: 0;
  margin-left: -10px;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
[dir="rtl"] #notification_area {
  float: left !important;
  float: left;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] .indicator_area {
  float: left !important;
  float: left;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
[dir="rtl"] #kernel_indicator {
  float: left !important;
  float: left;
  border-left: 0;
  border-right: 1px solid;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
[dir="rtl"] #modal_indicator {
  float: left !important;
  float: left;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.fa-pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.fa-pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.fa-pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.fa-pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  height: 30px;
  margin-top: 4px;
  display: flex;
  justify-content: flex-start;
  align-items: baseline;
  width: 50%;
  flex: 1;
}
span.save_widget span.filename {
  height: 100%;
  line-height: 1em;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  text-overflow: ellipsis;
  overflow: hidden;
  white-space: nowrap;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
[dir="rtl"] span.save_widget.pull-left {
  float: right !important;
  float: right;
}
[dir="rtl"] span.save_widget span.filename {
  margin-left: 0;
  margin-right: 16px;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
  white-space: nowrap;
  padding: 0 5px;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
    padding: 0 0 0 5px;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
.toolbar-btn-label {
  margin-left: 6px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
[dir="rtl"] .btn-group > .btn,
.btn-group-vertical > .btn {
  float: right;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
[dir="rtl"] ul.typeahead-list i {
  margin-left: 0;
  margin-right: -10px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
ul.typeahead-list  > li > a.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .typeahead-list {
  text-align: right;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  min-width: 20px;
  color: transparent;
}
[dir="rtl"] .no-shortcut.pull-right {
  float: left !important;
  float: left;
}
[dir="rtl"] .command-shortcut.pull-right {
  float: left !important;
  float: left;
}
.command-shortcut:before {
  content: "(command mode)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
[dir="rtl"] .edit-shortcut.pull-right {
  float: left !important;
  float: left;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
[dir="ltr"] #find-and-replace .input-group-btn + .form-control {
  border-left: none;
}
[dir="rtl"] #find-and-replace .input-group-btn + .form-control {
  border-right: none;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
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<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
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.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
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.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
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<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

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<h1 id="Face-Generation">Face Generation<a class="anchor-link" href="#Face-Generation">&#182;</a></h1><p>In this project, you'll define and train a DCGAN on a dataset of faces. Your goal is to get a generator network to generate <em>new</em> images of faces that look as realistic as possible!</p>
<p>The project will be broken down into a series of tasks from <strong>loading in data to defining and training adversarial networks</strong>. At the end of the notebook, you'll be able to visualize the results of your trained Generator to see how it performs; your generated samples should look like fairly realistic faces with small amounts of noise.</p>
<h3 id="Get-the-Data">Get the Data<a class="anchor-link" href="#Get-the-Data">&#182;</a></h3><p>You'll be using the <a href="http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html">CelebFaces Attributes Dataset (CelebA)</a> to train your adversarial networks.</p>
<p>This dataset is more complex than the number datasets (like MNIST or SVHN) you've been working with, and so, you should prepare to define deeper networks and train them for a longer time to get good results. It is suggested that you utilize a GPU for training.</p>
<h3 id="Pre-processed-Data">Pre-processed Data<a class="anchor-link" href="#Pre-processed-Data">&#182;</a></h3><p>Since the project's main focus is on building the GANs, we've done <em>some</em> of the pre-processing for you. Each of the CelebA images has been cropped to remove parts of the image that don't include a face, then resized down to 64x64x3 NumPy images. Some sample data is show below.</p>
<p><img src='assets/processed_face_data.png' width=60% /></p>
<blockquote><p>If you are working locally, you can download this data <a href="https://s3.amazonaws.com/video.udacity-data.com/topher/2018/November/5be7eb6f_processed-celeba-small/processed-celeba-small.zip">by clicking here</a></p>
</blockquote>
<p>This is a zip file that you'll need to extract in the home directory of this notebook for further loading and processing. After extracting the data, you should be left with a directory of data <code>processed_celeba_small/</code></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># can comment out after executing</span>
<span class="c1">#!unzip processed_celeba_small.zip</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">data_dir</span> <span class="o">=</span> <span class="s1">&#39;processed_celeba_small/&#39;</span>

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<span class="kn">import</span> <span class="nn">pickle</span> <span class="k">as</span> <span class="nn">pkl</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">problem_unittests</span> <span class="k">as</span> <span class="nn">tests</span>
<span class="c1">#import helper</span>

<span class="o">%</span><span class="k">matplotlib</span> inline
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<h2 id="Visualize-the-CelebA-Data">Visualize the CelebA Data<a class="anchor-link" href="#Visualize-the-CelebA-Data">&#182;</a></h2><p>The <a href="http://mmlab.ie.cuhk.edu.hk/projects/CelebA.html">CelebA</a> dataset contains over 200,000 celebrity images with annotations. Since you're going to be generating faces, you won't need the annotations, you'll only need the images. Note that these are color images with <a href="https://en.wikipedia.org/wiki/Channel_(digital_image">3 color channels (RGB)</a>#RGB_Images) each.</p>
<h3 id="Pre-process-and-Load-the-Data">Pre-process and Load the Data<a class="anchor-link" href="#Pre-process-and-Load-the-Data">&#182;</a></h3><p>Since the project's main focus is on building the GANs, we've done <em>some</em> of the pre-processing for you. Each of the CelebA images has been cropped to remove parts of the image that don't include a face, then resized down to 64x64x3 NumPy images. This <em>pre-processed</em> dataset is a smaller subset of the very large CelebA data.</p>
<blockquote><p>There are a few other steps that you'll need to <strong>transform</strong> this data and create a <strong>DataLoader</strong>.</p>
</blockquote>
<h4 id="Exercise:-Complete-the-following-get_dataloader-function,-such-that-it-satisfies-these-requirements:">Exercise: Complete the following <code>get_dataloader</code> function, such that it satisfies these requirements:<a class="anchor-link" href="#Exercise:-Complete-the-following-get_dataloader-function,-such-that-it-satisfies-these-requirements:">&#182;</a></h4><ul>
<li>Your images should be square, Tensor images of size <code>image_size x image_size</code> in the x and y dimension.</li>
<li>Your function should return a DataLoader that shuffles and batches these Tensor images.</li>
</ul>
<h4 id="ImageFolder">ImageFolder<a class="anchor-link" href="#ImageFolder">&#182;</a></h4><p>To create a dataset given a directory of images, it's recommended that you use PyTorch's <a href="https://pytorch.org/docs/stable/torchvision/datasets.html#imagefolder">ImageFolder</a> wrapper, with a root directory <code>processed_celeba_small/</code> and data transformation passed in.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># necessary imports</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">datasets</span>
<span class="kn">from</span> <span class="nn">torchvision</span> <span class="k">import</span> <span class="n">transforms</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">image_size</span><span class="p">,</span> <span class="n">data_dir</span><span class="o">=</span><span class="s1">&#39;processed_celeba_small/&#39;</span><span class="p">):</span>
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<span class="sd">    Batch the neural network data using DataLoader</span>
<span class="sd">    :param batch_size: The size of each batch; the number of images in a batch</span>
<span class="sd">    :param img_size: The square size of the image data (x, y)</span>
<span class="sd">    :param data_dir: Directory where image data is located</span>
<span class="sd">    :return: DataLoader with batched data</span>
<span class="sd">    &quot;&quot;&quot;</span>
    
    <span class="c1"># TODO: Implement function and return a dataloader  </span>
    <span class="n">transform</span> <span class="o">=</span> <span class="n">transforms</span><span class="o">.</span><span class="n">Compose</span><span class="p">([</span><span class="n">transforms</span><span class="o">.</span><span class="n">Resize</span><span class="p">(</span><span class="n">image_size</span><span class="p">),</span><span class="n">transforms</span><span class="o">.</span><span class="n">ToTensor</span><span class="p">()])</span> 
    <span class="n">image_dataset</span> <span class="o">=</span> <span class="n">datasets</span><span class="o">.</span><span class="n">ImageFolder</span><span class="p">(</span><span class="n">data_dir</span><span class="p">,</span> <span class="n">transform</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">DataLoader</span><span class="p">(</span><span class="n">image_dataset</span><span class="p">,</span> <span class="n">batch_size</span> <span class="o">=</span> <span class="n">batch_size</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<h2 id="Create-a-DataLoader">Create a DataLoader<a class="anchor-link" href="#Create-a-DataLoader">&#182;</a></h2><h4 id="Exercise:-Create-a-DataLoader-celeba_train_loader-with-appropriate-hyperparameters.">Exercise: Create a DataLoader <code>celeba_train_loader</code> with appropriate hyperparameters.<a class="anchor-link" href="#Exercise:-Create-a-DataLoader-celeba_train_loader-with-appropriate-hyperparameters.">&#182;</a></h4><p>Call the above function and create a dataloader to view images.</p>
<ul>
<li>You can decide on any reasonable <code>batch_size</code> parameter</li>
<li>Your <code>image_size</code> <strong>must be</strong> <code>32</code>. Resizing the data to a smaller size will make for faster training, while still creating convincing images of faces!</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define function hyperparameters</span>
<span class="n">batch_size</span> <span class="o">=</span> <span class="mi">128</span>
<span class="n">img_size</span> <span class="o">=</span> <span class="mi">32</span>

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<span class="c1"># Call your function and get a dataloader</span>
<span class="n">celeba_train_loader</span> <span class="o">=</span> <span class="n">get_dataloader</span><span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">img_size</span><span class="p">)</span>
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<p>Next, you can view some images! You should seen square images of somewhat-centered faces.</p>
<p>Note: You'll need to convert the Tensor images into a NumPy type and transpose the dimensions to correctly display an image, suggested <code>imshow</code> code is below, but it may not be perfect.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper display function</span>
<span class="k">def</span> <span class="nf">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">):</span>
    <span class="n">npimg</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">npimg</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">)))</span>

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<span class="c1"># obtain one batch of training images</span>
<span class="n">dataiter</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">celeba_train_loader</span><span class="p">)</span>
<span class="n">images</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">dataiter</span><span class="o">.</span><span class="n">next</span><span class="p">()</span> <span class="c1"># _ for no labels</span>

<span class="c1"># plot the images in the batch, along with the corresponding labels</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">20</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="n">plot_size</span><span class="o">=</span><span class="mi">20</span>
<span class="k">for</span> <span class="n">idx</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">plot_size</span><span class="p">):</span>
    <span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="n">plot_size</span><span class="o">/</span><span class="mi">2</span><span class="p">,</span> <span class="n">idx</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">xticks</span><span class="o">=</span><span class="p">[],</span> <span class="n">yticks</span><span class="o">=</span><span class="p">[])</span>
    <span class="n">imshow</span><span class="p">(</span><span class="n">images</span><span class="p">[</span><span class="n">idx</span><span class="p">])</span>
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8RC45GoqleuKCnRh6BYR6HoVA8fKAHht3clvzo+g/xlTlcEtZlSBKQSdA/3Rf3dvCt66saq5AI3Oki42hMtfprp/oYDulOBCg15Q4xEs0z+vZDdfn4PbskoT8hksHRuqYMOTAz66p/hQOUEEqZiAro13hGuI9nY+9dFj7xz+0ZVbuGYNFG7zenEY0hvRkgedYSkYo/3Dqvy8yP12zm4iWlCCR1orqAzo3tcDR1EGRnVHMwq7y0kblt67znnnEumE/fw/lfOOec++as/q34/hySqA2p/F2NsOlB7Mcl3DdT+O9c0/25eVtKuCPTzNdBW7977VnWjsw6onfOErsGC44QO2NhQcj4m9hyPMdZwfQdqYxsJuCdIYhgFSJYM+RfHFytZA+2yBYrs9JyRYjnwnOeCObUTg2nKeQk6+RRSibNDxadVSFa6MeQWoMb3MKDHB0qqtwapQH1NbUi68TmkUMNy3u22RV8eravfJki2O4T8cQDqcR/yrBB051ZX5xz3RQ8P6JAHmnMB6umCUyGTYSI5blwsUQoHpHnu9svYSPcQTv0YayHbs0upFJJiMglqC2O7tyq58jZlFkgoPcTY7qCfCugYp+UwYULaKecWKN4xglsLSXHjjsYXxy/pwcNcdUkCUJeRoPfpI8XsVSQUfOeqpLbfPNKYffR0NjY4H14VWZK4k73ZNf78/1IC48NDyaqZ1D5bcFK72DFvwb2LsgnGJ7jMMUllQGkbxnY2gVNLOS9aoKSvI8n5cU/x+THlrqhLDTKgFqSklAXWkCjcwxih5DGEXPcc6+snfe2pbrQ0jm9c4Oa2LMxrni84PMFJBJK0GAl7w6liTuwg+YQbzPUrSqy6u6697grWlg5kVi90aEGCznmC6g7dOSkFh5yDiUOvt9WetzeUOP7RoebTfSTUfbCnZMCrXbVHnxKBMSTVkGjmoeIIpenzhMdLFeQUhXPz+JBDJg1pGKW0nGc5EhUzkb3DHBphLaLZAcW5lE00u0jIDglVZ03SnvNhue5RtoflJoCU1YeTLhW+XCOo5+/DTef4qeJgbw1SKez1hmeaczHmdKPJOfd69qW/i/l9LAx+lbDPW+8o/v3xD96ryj9970ZV3ghgYNFU4/WQZL/dVls0sHaGbT2nxpg7dBnrl3EySRF/sedPMBfTCVNlIAkxUhHUTyWPqkGWnO1I6sNxF0eao3efSgKPfPWLcqqFFAFF+d/loSgKl5TzrmAKAlQ6gEszTbEWXLrSi9Md0KiB8rQR2p/pBVZaasNLkNB9eFMJv+/c3HXOObezpflxNoD0DbKmzY7GSuwgZZpC1pbr/u7CuOcIz8P+5YvndG9b+7VLO9onn0PyOjrBPibXOv1dYUwcg8FgMBgMBoPBYDAYDIY3APYSx2AwGAwGg8FgMBgMBoPhDcBLcVqLInNZOpOotGF7sbEuuUUjEn2PkoW954+r8sGByoGvY9ZxzpuQ3HRBuT87E725BhpzCwytDzdFs9qYU5hAGz8+E/XpZCQK1eGZ5Dff3pMbRhz/sirnoC3eqH1clXs7agMHSUYCmvvZsei6pJG9SHJTVLKT5VEfi6Jw09LtKQTtvQ7aJel9QzigFKD7ugV3HN0jD2nXRVN8By5U33vnVlW+tC1aIVQTLs9FSa7uHs4oU9DtziDVW4FjQ3z/UVV+8Fw0xVO4ntDlgFnIpwuUV7zrRCVT0MnpWkU6I10AlklgHY+G7ovPfuGcc+7eF7/WNXJKTOB2AjeMw1NR+VLIGm7fUB/9+I4kjDtwxJgONIY7yLw+PRFVlY4rGej341L+4FN7htba3BBtPwbFde9Q42s0hVSRbgvMIA+6JqVd8QLlVdedThYGXlVsNuDGls2Op8zgVeF5zkXR7LxRrPHegPNfHdT8Rk3t1oYLVLMQrXO1qzpfXheVcw3zIh1DGoa2Is10ium93lL/D0tZYtEjhRYSC2T470NOdQI66/09jb8TOBV4kOrkiKETzDlKThJIWOkOB0b7gkPWFBKFZSIvnBuWEpKINH8ck6Zq8wTtn47o9qa+rkVq8zM6lWRwsEFc8ihRQwQnRTkIdf65U02L9GfIFeJIv0eUfqCPuquK3Ue47/uQ0DC+5JA20iksn2qNOTyULHqwrnnQ7qg+u/lMurL39fLm4ng0dF98Oounn33y8+r3AhK8AK42BWnscJZLkovdJfyc4wKSKEiMmliDHWTYcR1OWKDw37oyo43/9OMPqt9WeorD211JfP7vn39SlQ9Gmis1Sqtw/RDuMIEPmbGnNqBsD+HUTQod8wB9+wBy+S3KDpeMSmKwoCuACw4kVPVC9atnKt+Ey+qH72ot3FrXGtmBhCpG0Amx0gfk1qM+OXRRXrkJCXgAXJMKymzQ/xHna6brr0BadaOrOfR1W/P188dKRdDwNGbPEb8nY+xXW1o/Mu8iyehSRRyuKONGsSChgkybbjeUuC/IToQU+7kEMlRKdUP0VYj1pwuX3a1Lkm1Q9tzvz2QQPt3+zrTOTc7Vlj72JB6kNxFcGNtwnCs8jcvRiGsH0jO0EGexzk1xTK1OR+HX6UgFzKciXWDxz2vYQ/4UEqp//JMfVOV1OMXVMS/qkDnWsVcLELvoChjVsL5i7gY8puwbbwzZdsjnG6R8CNUXga+Yl2N/W2DceRh3KWR/ybZkNmurKq/39Az6q2/lIOfR0cnpuq/XZWxx3fLpQgWZNh7LFp9rWTXs1biHadd1zg6eHdvoz+1VjeHb1yRn/fCWZI43r+4455xrLDhMqQ9/8ME7VfnKlZ2qPIXkawiZ5RPsV89ONI/v3lUM9SCRv7KjtSOAKx6d7SiRj/GMPR6/vETcmDgGg8FgMBgMBoPBYDAYDG8A7CWOwWAwGAwGg8FgMBgMBsMbgJeSU/m+c43GjBe1u7Nb/d6oibaUgU58BNnUaCxKUgc031ZTGd4zcLG2V0UJ9UA9CyGpmZyJZvfurmhRt2++VZV3yyzgAWRew6nOcTZRfb+6L8raL37zRVV+/PheVV5dV91z0G9vRD+tys1V0bzabdW92VF9gxhOOZm4ZiGoeL5Pt5DloCiKisoXg0ZIadAQbkA+5Av1EO4iOD4GVS4GPfTymmioP3hXFLYPb4r61mqoLwpQeTO4A8ydAthO04QyGZ3DI2UZ55hLyJxzLknk3pCC1tyoQaoBiu4EkoC5k4RzzvmgC+Zw5Mj/DST+H49G7qvPZhT5k0NJxUhhzCGDyCCzogvOSle0vnfhSHV9R9S/Lmj2Q8gsOnAT6vU0X4MAY8NXfYb92dhI4HxD15YWMs/3cO4Mspn+EP0CGucIFOUItGg6kWWQAEbRxTTqzHE8aLxP09kxdJ95VfiB71rdmfwhAGW+C6plF7TfLWTj32yqrTpweFhDnTc7osC30YcRqcQvuB+E3AUZydyZhA4lzlOcorRqith6PlB5d10x/zNQUh/CVSWBbM0D9bsGmV0yxXylmwuo25MFecvroRsXzrm8dP/KAjQcxmcMGUoEiVcb7X8Z7nzbLYw9HB9BqhJBTry1rjFTw20+P5FEOGqo32/NnUC2RAnvgH7cAJ05AuV5CnlWBgngIRwqjn/zWVXuJ5B/1BEjIG08xzKH6e0eHkmWFSHuhKUribfET1DnZ6fuX/zzf+acc+4YDn+UVWSQjHl05KALB8ZbiHukfKG+4EiGdWmKtsrUEKuY69//4P2q/NMfzuTcN3cl5Q5wnc0mqPZwuPmLX3+jekHC58GNqACFvcjhjoUYSvkjJSI+XHmGoNffh6Tkna72BsvHrL6UMoeQDNU8tUUDcqrrG1rz/u4Pf68qb8GFqBZpjlCKsyDjoaRyYYeNvZ37XSk2ZexB/WJXqwJzMabjGaTFMSQ0bezZerewfmzqXj97IrfYB0faS5wlknGmqfouiTWPs0pqt7zYWhRFJaMqIMcuEAeTKV1fcQwd5BiKuSdD/3AP3Mc5mV5gY1P9T5n3/r7aKpvO9szJBI6oR3IGy0b6PcSeKMOYmKLuNex/2g04g8FljmtbjdIV7p0RXzLshf5NqXDmt0QJVRtt/tPvf68q/0f/SM9QO3X16eS5nh0DrAMx5FEe5oKPNAK+T+mfajE6h0wPcql5GKNEiNLZnOfDPteHK2itCecrxN0animaifprG05xHbTUCtyPx2PFqRAORl7BRfA1cDIKrW8B2jj0KWvHHpvpIzAO6WrYaah/bmxC+glZ2aV17V3X4Da2taa5cBnHX7+q9xHrW7Nzcg1bjdUnV2JJjnOOIex5uC3u78kl7Or2n1Tlf/rf//Oq/Ghfe9d2B6kl9rSH4esWv6ZywNgdcBX4bjAmjsFgMBgMBoPBYDAYDAbDGwB7iWMwGAwGg8FgMBgMBoPB8AbgpeRUcRy7q5evOeecW1kRHdOBpjfoi3qU56Jgdrug8yPD93Sgcg4qfquu47OxaGinz0VLvLIuB6srH0hCtY66zZ01ctxqmi9wX6vidTo7tEVl+9/+1S+q8qMv71blOBNVbghK+Nsf/mFVDgLRb8NI5yzg1DFNVZ+ALgrBvIpL1Od4XkW9TUETHIP2lyBLdwO2E14BOh3cAWjA0AXl7sNr6p/3rsrVYR1yjhrNG8A9TkC/S0o504RsUFCZ+SayAFU9XxdVj/c3d0lyzrkT/B5GkA2wDIcxOpHEkF/llDFN6dbzeriqyXTiHt+7NytDWuZB7lWDqwmzp9dA82+vaMxfWRfFfQOuKXQEIkWyAwnV2rbkjOOR5v0KqJBBaV02hGyA7eazXnBTGsORynmS+jXRF8FIdNMMrhEZaMMpKf+QL3mQC5CyHYDaOpc1BcHy3nt7XuDq9Vk712JVtAMXiVXMlY2Gft+BJHWzBdchOIltYPw3MS/q6E8P0raCUgnEBp9zrZTwkG5a4Bx0I8vRD+m6/mB9TfE8RRzZP5aMJcE168jwPxqJSsw1Ygh5Z4Iy7efoCLFMeEXhotKFgmqqGFKGJijkO2sa229vqb8+gNtCC25yxRhOZD1JZ2JIIW9d1e8+nBU++xpSiQM5O3783kzS+s73JXNd25FsIAcNPz8Dhb+vefbrb3Rud6Y+3Y41Tk8Hmi/bW3JR8hA7H+cqN7tqwDH2FU+fiK58PpjFj8l4eXLj0XDoPv3kV84551KM2wKSNToiBpBEUJLoL0gzdUyMeZxB+jc81X15WJcuY35/75rkx//49yXzuVH2VwwaOGXIV7flkvHH3/+wKp/sS57wAG5H0wz7EzgQ0WFpCoeVGmjxyQBSccrLsGd4iBj9ZPLyLhzfDZ4ryrjtO43hyGlONJ3af+7S5pxzP/nhj6ryDiTxAfaOAea0D+mqF1NyCmk1pNgOkmZ/QVpVngNy8gX3Uspv8LsXQcIBuYCL1c4TuEk2PN03pQs+JO0+5Cp397WXH+aQBUDSmRVwVFsWisK59HfdqaZwN0tQ5nwquN/CGkIZYIz1bzpU+2TYlzTpFAW3yBGcAkenklNN+7Pfs4naaXyq9SyAS1GOtRUmdM5B2hFHun4Le6GihjQMC8sZ9p/Yw+SQXKWQ8wQL7levaV30PBeWLnQBnmEoifnjP/hhVb5z41pVPn8iyecAfRfiuczRCRmSlBTPICxT1FVkF+/Li/lc9y6WvNGh1/O4L4YLFSR3EZyVPcTaAK7IIZ5HVxHLa4g7f/ADyWiPHijVx2AKV84lSv11Tuf8UrfsQ7/MdBo5XXrRVoxnbcSVW7talz6+qRQO78Md9/qO9q7rkJWtINVAC2tqvavnmLDcD2fI8xHXIXGDrNuDtKrAnM8D9WcTzwr/8O/r2f6zL7+uyn/y53KwfnagGMCMKBPsK5iDZOE5ksd8RxgTx2AwGAwGg8FgMBgMBoPhDYC9xDEYDAaDwWAwGAwGg8FgeAPwUnKqIAjcam8mVcpBcTsCTdtPRXPstUVhSpFF++xI9OwanE/oIMXfD/dEedzsiXK1clWyqTgEbY2ZxecSCvCaIgc5QaHySkPlD29BagQa4p///OdV+WT/eVUejUWVo/PAzfdEv2qDChjFom4loPZFBWmR85twS4RXubeMQLWc0sUFr/Z8vuYDZdAHVS6Cw9MlSAU+elcSt60V/V4DzbUG2VLhgUrGJN3e7/4W0uEoYpZ4ZKaHM9hkS2OlD4qx29d5xpDnJKDc9knns2D1AAAgAElEQVRVRSUiUFJraKg0F1U8T/i3y0Oapu7o6Ki8nuodgU4co041ZOznvFxpa96sw52mCycbDkBKsRpwP9mGQ8qjJ5ov9Z7aPSsHVnoimvY0IcUX878pym3c0DE10Edj9HUC2nqf1GlEOMoh6IpFO5VsCmoortUonVuW6k7lea4ezu6hg/be6knWtt7WGNvoqH121kQJ3cacWwWttLuifm6D1htxzhUXU6+LhLIyyEXKsu9xXIOmDNuLIqLMClIt0FPfvnm5Kv/2rqSqg2NJAtqg0B7BOchHrGyh/c7GlOsJSbI8+c0CPOeyMqaBbe1W4bb2zq6kSu/uSqrx3mWVf/DOzaq8hnl5NtZ6GXYkg/DggtHCOCmGuv+nkD8dTrU2f/T3fuycc273h+9Vv/lwxyogyfLPzlBW7Ewb6seTf/VpVX5rVfU6hNuUB63Zux/LlWRjV+P93j1Jl0+PtK9wkDyu9GbnPwjULq+KLMvdWel2WVA+in1DDplQ8QLrmxhScbpneYjL41PRrb1zSZvevSSa+T+AzOD3P5IU6vKGxlG9lF9QGlpAnhi3VIGb1yVV+OH7t6vys7/SfuYI7R0Wuk6rqxieQ0LuUTZFGaUTckikj+AKRKeqZWMueQ6wR2lR8g2J3O9/7/tV+dqVG1WZEsYA60xRZ1lz1IfbqE95wUTzz2XcTEEuWa6vPscXGtHzsaeB44pHJxPQ/wPcH2V/xVTzJYLs7vKK1pIp+vHwHPIl9HtRKDakbj7el7dJ9YrC+fkscEwR+yYDpVKgDCoZq26cC1juXQTpmw8d0uhMc3EKB6AtOFIlkP7t78lxanwmOVVyXp4Hzq5ZX3UMF/yZqEWGRAUSmwVnw6b2Ze1QsWkCBzsfMm8ffeuwv/IghfQQJ16XnKoonMvKOOljb3/zlp7hPv5Y6w+dbQdnmDcF5YyYZxGlVS+SU0EqyL0b4hIls5W8H/siH88F3oJ0CNKqQOPL+dzTwgk01roc17EXRfoKHxuItR5cybqQxiNNydf35ADte8t8wpjDqyTCTOuRoc4LEipEf0qo3oIL1R3Iqd6CC+7lNe1dNyEVX13V75RQRSHcpNiHZZkOqimeF70M+ymkMnHc+4d0+dW9blzVXuUnP7pTlX/+ieR/pxi751gjBogvnVX93sRz1GRMfeV3gzFxDAaDwWAwGAwGg8FgMBjeANhLHIPBYDAYDAaDwWAwGAyGNwAvJafynFfR6R8+flT9PgZtcBeZx5OpqEFHJ6Jkd9t0J4JUApTUCPKPnU1R7tt1SQco6UohBfAWZBMzml1B+hyyimfgPDNrfFzTfbxzE1nTx5JQ3X36oConp6J6PlXSateDy0FnR+dZWRUtK4xFhc8hBViyjmp2/qJw47Ktcrj1BJDeNOB2Q2cYH/RND9S9FlyQblzbrcqXLsFJBTRkj5nfQQP14CTjgbpX1Q39TSkFXQgKlFO4alAqdHVbVNkpZDj7A43XIWRDEc4DdZTzQH2swbViCjelDG2WLpHtmBeFG5Y0YrJnc9DAffRvsw7nEUgBupDZxKRqg0KewiEiB8+7gNvG+ormy+EhxgxCTK87k4L0T0RnzFI6S4AGjvYsQC1OIYmp13WdBjLL+3Czy1DHFFTYlJKrmuqYgXI8gctYGs7OWeTLm5NFnrnpaBYXc7hoTQYaV511xb6rO5LSXIHzzEI8Rab7WhMSKtBQ6cJG2nAB6rVDOzOeSp7KwUyquM5NB7uI10ET7oIy/OFNyS8P+p9X5Skc8uqgxZ9DKsSxsLGhtjk51do06r8eR5zQD91Ga0YL3oaTwodwm/rhbVHIf/j+21V5c13rWR191EC71HsaHK11nTNsiGZMF7z8VO2y8kjr1S76YOu9maQm7ur6Kca218TWAE4KXk39ezmTa9L2o6dV+eGeZAabkcbU3Ue/rso/T+XKtLUl6vRaFzIWOGRtbWhdaa7M2unJl5JlvioK59w8POQYoKSQL/wOOnlA1w6OeU9tmIMmXYc8+48+EiX73/mJnKfeva7x0m2rn2PE8WDubBdRHg7JYKDx3lPocO9DTvXp/XtV+f43D6vyGHukeh3jDGvHFPdEV6yEZaxNE+wBjqYv78LxneB5lY4thHyCcue1lu7n8s4V/CnGfAgnMsTUBHaadFgrQO2nsxtp/h5lpwt6qfI37D/pssSyjzL3YA7SqgDxPQRVP/d13x4kSE3sxy6va55trkvq9+yh5jdUzy4sY8YyfXGKInfT0slseKY69E8UM1JIE1I8ZxR074JjUQf7nD7OeQJ57jrWDcqFH9yVVGICGVcxgsy0lH1lA8iARpBGwG2K23oPzkRFoOOnOM+4rb4KajwP1mvEHSjoXAZHJLpvFXCiYzstF0W1X/JjSDtvad1oQSJ+fKC1ajCC9AhSWqbKCBf2Gpq7Pp2n4HCYe0zBcLEctpqLnLcB5VyQojOlA58RIL/xPPVpCClY3MBaS4c01KWzomfEwtM8DkfaEz58Cgms/xrmoiuq2L6YSoBrpNqBz4Jv7Wg+ff+6XKiu4R1BE7EqwficYC86xv6T6SI89H+AeDqXDYYp+s1XP+SQgxaFrukVekZ0CcZcrrpw63znHa0dty7r/j65p3V0hH1CDc8fkz5SynTUHhxf3xXGxDEYDAaDwWAwGAwGg8FgeANgL3EMBoPBYDAYDAaDwWAwGN4AvJScKpkm7tmTGa3yyQNlxb4Gh40+KIYnyPwe+KJZtTug8oEeVw9FZyrAfG8jw/cCRRksQFLeclB153RFOmMsqFpAX/NS0LNAxWqDtn7n9jtVOXWiYj1/Llrb6ExSs/6eKOT1pih3XWS/rkeg2Wa6blyb1ZQyo1eFVxTOS2ftk2dwNABNuAmXriYyjNONIgB9cA1uR7euiSq51hNVn5KVnC5XkFOFOCf7wi+dHHwP2fgp4UC9psgwHoUaB4066ots56dj8cz7E1FrScUOIdFKQCenW0m9rvujpCVdkOe4paHIC5eWtO0JOeug/o2myOoOx5Ux2r9GGRKcHTJQRSkzLJDNfXwqJ4aVLUnUmnDNOTwQdfntqzP64QFcvR4/FU2bcqe1NWWtnwx1nekQLhkNutnBnSdRDEpQXw8OdsOJ7m+1DfcPUNQpHTsppTh0WVoG5i4RPhyyLl/SmLxz62pVvg4JVbOlfovRbw3IAGPIkBYMMUCf9hGXF6JMcfF9euW88CCn8vEtgHILb+GMmNtw/MGwdNev6L5XH+gfjlGVNpy7JqcaC9OJaKurq4o7aysaR2dnorA+OBQ1/1Xhe57rlDF8BXTirZ7Wsw9uqh8/ek+ysfqK1rYc/eg2RbEt4DjmQo3zoNB4LhgPsV5evnmjKje6cPYoxw8ltT4o6Y7rJW2W4I7ShFzv+hVJZ3/7mfTEdciYm5C0jPqa0+Gu+shvqn/TnO6POn70YNbv6XS5bmNzZxI2Q073NsQSP0N7Yw0jDZxzhPKrn7yjNfIf/d4HVfnKtvZR9QadLOGCiLJfyqigyHCxr7gQ1CBbhpRg55IkMx++I2nVJ/e0b3kC6UoDToEOssXBUPPJX3CuhDwBMve0pvHyPHo9Eg6vcC4orx9CV+I71ePStqjvrbrmaIa6LoZODYgQ7ntBrt89DEXuk+j8k/uMjdwPFar8vC4L0gWVgwUVFo5nmW46qK8HWWRGd7VE+9gO9mBXNjVOPnvwRMcXmou+3/4bNXx1ZFnmhuezNXzc1zNEimeLZEIpH+YZ2rCDVACDE52HEqoVyHlCzNd7X2vfnqF9fLq4QvJUlBLuHL8tuI3h3C8SEvqINdOR2rg2gvsWXHsL9HOGa0X4fZKqnRJI0OoJpHXx65JTOTd/2gqxbqy2EU8glZmgbRPEkwDyTLoMpZAt0X2V7rdUHHIvHnIicfSW7Yip7RKkRHALDoW6PtMCsIcjpCiIMR7HOE8YwtEMz7E+1t0mbmQQa8wGSEEy35stdTI654qyLwr0YY5n0gDP8DvYe719WXuCbUioFp4FEQfHqdptCBlgAylGGpATh3iGdkwNUrrJpZAm+Sncq7FXyulaBZmVt2DL/LtOgs4511vXfnVnV/f91SPFyhSxo9FAyo0x3OcgUW92NEa+K4yJYzAYDAaDwWAwGAwGg8HwBsBe4hgMBoPBYDAYDAaDwWAwvAF4KTnVaDxwn/3658455zbXRCVKxnJmmk5EsR2eq3zpsujkMSj/LhPNqQXqZ8Ls5AGcUuigAnpXhHJKdlxJeSO10cFVyAf1kPS1ANTXBrKKb3ZFeb59WbT48Uj3ej6UhGR4dk/3dC7KVQ0UvRVk+x+BihyXdOglqqmcc84FZVvQeaMOSngTlNoW+soDxzAEbXUTTlvbOztVOapBpoI2jyHhCdgXeKWYJ3CZmvMD2YdolBwSuyhjxnpQTCEzopNND/KMzploqweQClFa5UFmQvo1aeaUU1Hm4eCi8KooiqKSUQ1BLXagddKZp4Z606WnHqgvanAkIW0wjnUMM8If7ssdpgmXm91tZM+/J9nl8cksTmxsKnZ8df+rqvzs4FlVbnVFc499jaMx7nVwrj5qdCThIrUyhYOKDypmAmotKcoBXSTQdZNSC8c586oIfN91W7N637wq57r3bt6sypc3VqvySkP1pGNaCNpojEkUgTIfpJAWUCKJebRAzyYnl+N/rjPAb8UCfxc05QXeOKQEqCPllJ0uXIpAv33yWJI7jotgR7H4+ERj8exctHuHmH71qtYg98tP3LKQF7kbTmZU9SwFrRuajAb6iBKdxdF0sVwngyMD/yCl9I+SC8gm1m9KOrJySWNp3u0eXU0o8aDDI+JuBlc3D44jG5uY/xvqu98+lszYSyCBgOz1FLK4EOvN7pbmQQvx9Yvffuuccy5dpt2fc64oGyWHPoluITlkG3QdShBvKA+ge9+1LbX9j27J1WIlpFQGmhxKRPB7nmtflM+dV7D3ocw4x/U5bhpwHnwPzptv70oSu/clJOFnmlu1WLF7CHkGXUY8yMPpYDXEGnSav0hU8moovMKlpVSCkqga5som1orWQn+hf0H597yLv3UuOEwtzGneG47BPS/EwOo3nltlDzey4GbEui+orxDrcZ0Q8d2FlDHQqUd13IBcuYEKnQ+03/e7c4nvcl0bJ4OZ/Gk6VCzPppAvQXrB5wm2Q/9ELnnJGBJyyDCSvsbn3qN7VZnOXz24Pw5HcBIaqj6VKyidxDgv6cLquP7id8iAXuSQVyD+Uu5NV03KVRzaKZ0qztLdK8K+YtmYS3EDSLhD7MNGE9zDFGMbdp1U/uVIN5FnXFPpMoy9Ea4b0dmLkitMvKKao3B7YzoByiNRTl8Qz0LMsxrkVG58saMa9wDcoyb4fTy9eO/6WlC4ampz3FKGXcMzXAsOhI0Yz2U4JuB+8gXar4uF+Ivz3i049aH/yzju0aVsQXmN+6AbFM7BfXHIGiB1RQPzbB1S9RZ+P57oGWUC2VRUaCye4Vkzapo7lcFgMBgMBoPBYDAYDAbDv5WwlzgGg8FgMBgMBoPBYDAYDG8AXkpO5fLcZdMZ9Sf2RZnOJqLp5VPRfVug7a506LYgilsciGZcDJBJHc5JSQHHB2TvzgLaU4FORfZ5STn0clDmSE+EKww5XD5oVkGh+6gXouJu9yQbOdiUk0b+XBTQyTno5CMdswo3nevrapsnueiaSTpeuIelAO5UpBu34XrRQb81QTsMIYOqgQ62ASehRltyh5TSMLiUhJDnRGjnCLRY0kOTYNYOWaJ/n4IqnqEPQ0q+QDeOQOWPAh3fBGW4WVeZDhukU5IKSHp9CplfDNpms6l2PYHL0qsiLwo3SmZtNJqorSLU7wRuPJ2QThqUCqqudUqJcM90Fmi35Gpwfiya/ehcMWD35ttV+a235H7y7ZefO+ecuwmJxw4cWb78WtKqp/clw7q0o3lWgFt7fq65QomeN9XYGMKVoraGuANqawoqblDTXHQT0t/LNvYupn/+bRAGgVsv5XzbK4qDm6Bm9uB2FMNhhmOSEgpSslM4MGSe2iSAg01IVy/qNkHzziEDnNNZffeCuoBiHOB8fgFKKmnIOKYTq74NULxHkOjubEv+ceVtOQUeH2ks3n10vyoP+lqPjo5Er18miqJw0zJe0QGj4DjEWB2PRGUP4Y4SQTbooBr20hf0CyjKdIvIIW1oX5G8NQAFOivlwhRBFFhDfdSF8q8EcdyDbLQGycE6HCoaTcWLCPedDDUvz041HjOs+x24C9Z25Mw2Lsp1cYkSDud5zitjJJ2+SN8uwMnmmoMquwBylBrq//YGHNPg/kg294KGhnuUnJIDzcV59y+cYkFCBYdB3Aen+eam+ud7Hyhuf3pXEsajM8nD4572Px7rhTUFIWhBKjDCetxPlussVtXJOReWUogAkpga5A49rIV0BPIgeaHciBZ6nkeZ1cVSfM7RAvvOheMX5B+/e/2QEo9CfepBCotTuMBdXK8CMnIPa2eEQTClNBb9soL7XmspTh1BulrrzMajt0w5VZG5bDqLl9OR4gSl4jW4KiZ45uBaMYWrDeVU+33F4hTzotvRM80WnGeG55KPjSnVxb7LL/u5RvccOLAFC3IqSqUQtynxYW4BOujib0P0Id26atzrYdzncMqZQBYWtl/eEec7o1zrI0prsFc7w7Pj2ZHizBlcSJuQ7fYQmyn/zx3mKPa0lG55eK7hE9WC42hZXw9BfdEdmP2CXxf6DnswzL8p5taUrn3ooymclUdIKTJZcHGCpI5zvSovMf+Gx3gC+VJ2sZwRSu6/4fCHMYz9HxWedDwO0J4Lz+LYcwRM14HxlZUxfcGxE+PDxx6m4H4ZkmDKH33E8ICyRciG13oaZx04IZ9jOR4xtQOegTOMC2/48n1nTByDwWAwGAwGg8FgMBgMhjcA9hLHYDAYDAaDwWAwGAwGg+ENwEvJqTzfd41SHhKRMgvKGF1T2k3RE5tNOBKB+hSHkt/04aZTIIM8s/OTlhdDquJBWlXA+WJOZ8tzck8hs0GZTh0LtHX96rwCFPIG6Jerkog8e/6wKifIvj4BFXNzU/Sr4pLkSEkiyc2TozmlcJn2VJ6bv7sLQccnBbMG+UwDlLU26LUFaJCkEp4ORGclwbYNdxE633RAw6/XdExU+12HhWwMR5AJ3cZU9EC980PV3aPzUgb5H11Y6ORAZwHKDECpZ/tloPoWaLNmG9ZjS1RzFEXhJtPZNSnhoIRlADrm6UDjaq1OaaPaPIa0LIBsMUQG/LV1Hd8/Ef2VczfCXPzg/Y+q8risw4MHD6rfmnU4ErUkKTo6AGUb0r0A1M0UNMQhpGroFjcZqa+LscorXc1dsmmjmJIyxKO5Q88SFRxhGLitlZmc4eqmYsBGB85cGNsLrF5Q4DNQ/AuE9KKgbFXnjGLde0S6MeMf5IdFqHbLyjYkNdvH30WkwbIjGERzzifQw1NSxeEgksAFBJZh25DYvHVDMivKDL755m5VrsWvkTZexjTe5hSxZXgOajQcUVod6qYgD4Z7Iee3H1zsskjZSo44NsW665M1XtaNUt0Cc95BuucVkJ9AfkfKcQSZZaersVyDtLQdaax1r8JlDGv6aIy1GVzr09F+Vd65MrvWvc8VI14VhZOr5cJeAe1DNxhKq2hGFIAav9KG5BiOfH4NcbahdgjRViEo33TQZF/MlUAp5DYhXY84/Wjbg/WsDgr5h7dvVOU71zRv/uxryRMrFx7nnA/3jzylLAlrNyQ8BZw9Jj7G/RLhFXLlo5yK1H7uRXM6P2H8U5ZaYC9QIIYUAeUcQg75Y77g4qdzMk7OY0fqU5IGmj+kHXSq8+Esufg1lnIqXh/SGjp3XmxO5RqQ8l6+vF2Vv96Ti6Q3XweWKPnP09Sdnczme//kEPWEMxDuPcO1xwPtsU+O9Ld09Qpjzb/1Nbg/wql0jP3SyaH2OV7G/SVdVmdtFWEPu+DCS2kjpCg54sXCPo77yYyupkhRENG1U2t0TDkV6pBjTZlgvxRPFLuXjbmbax11Ska69rNHelYaHCjdhId7juFanCK2eHRmQiqALIDLsaNEkdIjzhg6HpVjaSHlBiWR/u8c6tyiXNX5F18ngbNYwk0n5voEsrg+0otMsXhD5b/gTEgZ17LgOa96FqAzGh17O5DH9ZpwtMNLgoWtK5+tudTSwZNlLGQe1isHaanDHqKYr0top2xh24T0GJQtssz4X1CGjnvCer2CONKEbI/pKk6nmH8e5jqGAiV03xXGxDEYDAaDwWAwGAwGg8FgeANgL3EMBoPBYDAYDAaDwWAwGN4AvJScyg981yhp0yGdoUB3i0Cba8OpiI4kOchVGShap4+ViT4fiko28EQxiluiJK3sgLbUA42xLrlAUcq7ogS06IwODqCp4RjSSl2Oui/QWeHaA2mV70kicnyizPara6r77rbqsLmi80wKufWcjme0Q99fnquR53nOL/sopPTII+1SxzdA/V7p6R4Pn4tSywzwQQMyMciZjgeiex6civJah/To6mU5qWyti5Ifl65RzNxeoE8S0FCPTtVWxwcaT8OJJBnMfH8GB6cBpDcLzgKkBYJFH0JOkIF+mcJBJILj1TJRFIXLSnpegDFJGnYCPuFRX/fZQL8koBaOQTmsg86fg2YeYTxcviYJy8NHT6ry+ZlkSCur6sePP/jQOefcXcggD+Eq9N4H36vK9x4+qsqPn+jclH/UQK2c5sgaj/FI54EhKNIdOvWgHKHfwcZ3WUlzXaZTXD2O3O1rszF/dUt0zF5L7ROA7k8KbgJOLe9rUoCO6asdanVQ9Q80PuuQFvS6ilvtFqRYlH+UTe6P0A6gfpOlTPcgSotOUtXx4XNpDPcxFgLMpzri1GSscXwCqv3+UPHo4Llo2ZRRdCHdXDbmDkKTKSR+E8X4MZxMJpBWZT2VC0iR8xzraw6JH9z3/BzOgbjPjFI79McCC7uUYvmIZ96C+g0SLjj48KuPB9myT+leXeu+B5utWgfr9ZruY6On8TWGi8zeISSgu1ob4mB2zC9qcrBbBirFJBsCMdFbOBZ7BSyYHlp5Gw43zbbcqTJQrD1IO/wFNze2v9qN9Pw5tZ9OKkUKuRNiGaXFpPXnkCR0V1THjz96vyr/4qHm03io/gxwHynG/aJDlhowQ93S1/T5sPAKl82l+Lw29p8F5SaUWIBOn9JNCO01OdV+bgpXpAxU+QDiqgYk6CEp+mj3uXTLg2ONwx61QMybwOGtj33MeKDfA+yNWqD8N5pw58FYo0OSV1B+JWyvS7paZ7+Xdabj66siL3I3LWW7QzhJdep0UoTEBrLqBDE3xvhf7UgqFcda5zLoLJ49liPbdKg2r6Pf6mjPgC435VyknJEb6QVJBt2IIMOZog0TOIBNEWvWICNrrWvP4DhGIRuvBYovjGuTscZLDccvE55zLii1zVQPjc6wF8feK8H+u4M9d4i/Pcc+lnvrEHJeD/eZQMJZgxQrwvmDBUnS7L9FdvGzRkpJlKq1sP9MMIcGcCQ6x3zFdsgl6F/KJSeQrqaII1PoxVPO3WptWGb6DefmkYAuiS3UZwfjcHNFz4hMxbHgzkZ3QMpKaVUFSWiCOZqgX3w6Al/g5sb9O5/nsbS6fKiDGDeD+sWurTnqHiBdzMb2blWmbD/y1f8p1osp5VSqjhtNKJ38bjAmjsFgMBgMBoPBYDAYDAbDGwB7iWMwGAwGg8FgMBgMBoPB8Abg5dypPL9yb6EMqtUWrchDhv00RXZt0G1rXdHg6Grz5dffVOWj56ITki7JrPobG5JqvPfeu1X5rRu3qrJfUusKcKjGdFBKdL6jQ9Xl3iPR8495fCBeVr0JB59Yv8eh6FRHp6L8d45FD7+CbPLNpujnu1ui/O+dzCigUbQ8Fw7nlB180Y0JQwF9SzlVnl0sK9u9fLUq99YkByOCOrLwgwaXg4Z4BgldoybKZaukxZIGPp2Kanh0JPeAA7QxjE6chzbuNEWnLRoqn+CcPsYlae5QdjgPFEFm34fJjsuT1+PC4VxRuQKFyMYfUM+CuTjKLm7n/WPd52++lQtJuyHa7uqqqNRbK3BzQFb69R3RCRNwRRfiRGvW1tevvVX9trGlv0tBca3vXK7Kw09/VZXvf/N1VT6GdK7e13hZ34b8B64FA9CGJ3BICOgyBkkLOcDevLxEd6p6HLn3bsxc7TZ7cKnBeGNW/QGo4n1Ictron0vbkp3UG4pD04mOP4MkYO+J3CGeQp3SaNHBQzKLXmf2ewtStuEQclfMiQASzWeI519/K3ey0VjzY3Nrsyp376g9vtgXzZ1SlKMTSbFO9iTRPD1WPCDNP0lfz1wsiqKSdJLuS3kGacMF1jMHujdlG5RI+qRhj+Dwk2pd8uhUU1c8qCFg0bluHncpLQ4jyiQwVyBpGByo/PyBJI/9A/XF6FTxZTJRmz871xgIR6rLSiRnx5WO9hLP9tWnj5/eq8q/99H12TmCZdLGvcoFKgW9nW2WweHGw8T0KLEEh5sy34fYT0Bh5mJQ+WkfxrHa4rioQWZVyumi/OJ2GI01LwdwkjpC7Ng/1Nw6xl5lmKr/ux3tSR5CZtLqapxNckru4L6D+uSo52jBYmV5KDzn0jLsjLCecxwumNFAmkBpTYLjWdPxULFzcC659vG+JGcpZCFrcDxa39TeqLWi34NyHU2nWsOKoebZ+dFeVX70REH6CLLlyNc42oL0qVXXHpkSzQn2wxw+3Ad6kBc08agQQy5QyWSXuC76nu+a830nXCQjykRQN7qHNuD21oG0P0T9D5+pPQ8ONOZ5+i5cdjhHwwXpJOJp2QA5pTc4lvLLMaR33IuN8Iw0wfHegZz59g80/q7dvl2Vm5AKjxG7wxrX46q4IP8fIb4vE4XzXFq6+fhozzHmWR/rfwFXNybrCDG4zo+0JuxBlrXRV0xb39IeqAFpfQPPevWIsju4xpVr55j1KrgGQDr02TIAACAASURBVJ5PaSOch8/PsL96plQAIxzvYUxNsAegXJbS7BSRlGk/6C473/t7y1ZTVZXTdbt4hlpB2pQmJFQ1SEYbOL6F44OIjpyYI5A5hR72KAGdhfE8GqM/S6eqETRUXqJGqWfa57Bv3bn6x/F5OKbbG8YKYkq3S7km5M+Ii9MJ94Z09Ma1opd6JeOcMyaOwWAwGAwGg8FgMBgMBsMbAXuJYzAYDAaDwWAwGAwGg8HwBuDl3Kl8zzVLN5MctNowEt2+1hA9KhuKbsqs97VQdKo0Fw3u8paon7twJ6Kk4ORItNXjPdG5734mqrY3Unl7d0a9bsN5ZTwS3f7oUHTKL7+WVOPBU1EYOytymdjcElV1tQOK4ER0OmKEFOaP90WzuzMVhbzT1Lu0dqx2unVt2znnXC2W5OHVUVRuGqS71SiDAAes09A9JpBk5JDMHByovYfMtg83imZTtMa1NWQzZ4Z9SjSQ1d0rJQoZ6NEnkIScn6ntQzijhHWNxTNk4ycNktnmKWujs0FMdwLQIMnEq73ACYT3sUx4nlfR8AJQwhcovuRJw8nGg5vcPsYk6f9TyK8mqWSOzEp/fVNz9M4tSRjXAmRnhxRkpT37PUbm91NIFR8/1dz+4oHG/LNnmq9BXbTFdkfzMkOfnp5pnNbh/tLvKx5NhpJT1UABnUACU8DRxM1lFUukqoaB7zbKNqmBLusX6qvJggubypd2RBle3xBN30P/jEfq26KvOdLOROVst7UEjOA21D/X355ANhBtzuZrY1P9cHaif2+A3kupwt1v1Z8JbNB2VnUfq3CYOAvUP6twPBjDEWR0rLEVoQ/f//DDqnzv/r2qPBgtz+WPKJycKhgTKCvpddQuzTbcpmiElKnf9x9oXToHbfzxkdr6CeYFqdddyN+uYo5eQjv2dmb96K+q3bJE/fXoG0krP//NV1X566/Uj4fPJUto1lT3BmIwjPrcMeTKnVDrwYMHmvdFIblIsuBoqb7L07lT3PI0HJ4nOvqiDAKyk4TCGsRcSIkCrN8TrIVfPpBs6at7klb9+tt7Vfnta5IT3rykOb2zoXWv29E+pt6YzYUB4gXXyCPM29/e1V7pm/saWykckVZXNEZXIVX/4O0bVfnhzyRtzSC5ynLFlBTuVB5dDp2QFq/n+6FfOFcr9ws5nD4KrGfci+bQmPjYA8VwsgngggPjQFcDzT+aql8GlJZhAiRYcwrIhFQZONxATjU5hTwUUpkOJCq9ntbCVUi4GpAuRNiXRHQow/5miBhZYO+SQ152RjejfPmujUWeu2kp0R1BJj1BH9ZixY95igfnnPNQPse6dIJ9zvmpzslaB5AyHJ+pHUZOe5R2TQOg3dZ65UoHzxxzPoVUdYixeAipPuVUKWRDBaTwESTeQ0ghmbri1juSVk0wRup4tohjnSfGvJyMdH/LhOcVLiwloiuQZzfwjOjjnhldh4hLMKV1q2sa23043n765d2qXIebHt3ErmLPtLuh+dKA/Ljbm83jCVwSByO1+Rj1untfsvAHD7UuTjHnKdXvtBUj6D54Tmc5zFFKeROmA4HTJe1A588s3hL1VIUrXFbOO8qGm0i3UIfciFGdrq9nmMenA64bOn4MWX6Ee2dqh03sO7c2tc9ZgZxwpXzWZ6qODPujsa95sHeg2PpsX8+xp33N/xD3t72tNXprZ7sqDweI3ZBCU2Y8oVsdJPXcxWT5y+9pjIljMBgMBoPBYDAYDAaDwfAGwF7iGAwGg8FgMBgMBoPBYDC8AXhpOdWcCpenkB2AEx5BouOFoKrifVEBp4TD5xdnXk8KVW0MWhbpim1k+M+nomIdnOg8m1dLuUJd9LnCSVpwcCrK5TQQxWn3puROjSZkG1O4GSSiea11RT/uHIuWVeC+D45Fszs91bXWWzhnrmN2Vkt3KtBdl4E5hbEB6UUEWh4zjHchMTqj2wNkMg8hfRmBVjiASwPHxcaW2vP2Wzeq8rvXr1TlOqjCcyphAnnWGTLq90FTPk81Dh6d6PeHcI8YnIk+GqB/KKfi202wVhf6grTFBu5vfUOUuwHa6fNHqsOrwnNS+PigpjNj+wTZ2RckYXXRgJt10bprcHage4EHV6RzuKo9PtQ8q9WVhX8IuiclD+3mjM6aQybR76svhsc6XzDUORoF6NJNlXvrolPy/oZwJ/KR+f18rPGQIl7kkBeNYWmWov2mJRVyqRIO59zcPCIAVTVHvKMbwvqqpIeryPY/OJI8Yu9E93460HlGkEf5mCOrpKH2NBY2GxrPlJQ0y3IIacnuusZ7/1xt/OCZHItO4ajwHP3zEM5yAdx56l315wi0/hGsfUK4X7W7GtO3b79TlSeIGfcfSiK0TBTOubycjAUI+h3Ipja3NFa9EOMfMfLBY7XFZ3DwOkEc2wf9/nSgtjg6gaQ0Uly60dWcfv+q6OTf/8kPnHPO7azLKW4Mt7ff/NknVfmTz76tygd9XZOufaurWv8irCthpHM2IG9dW9X4hQGii/E/czc75xZlSqE/+93zlrguFpDZwGGqQAzwcb1swYIQcio4fDmUEzgIDsYak08fSpL2+QP1+e1trZE/uiPnzfffvl6Vd7ZnYyqBzOQZJKnfPLxXlb99rhhxcIZ1q6U538e+LDnWviiE0CFErOSey0GKy3gaYCx63APmy5PfEPUwdHdKeen4ABR67Anp9OLRvQ20+aRQHx3uSf727BlcS4+0dz07UD8ODrX/29kU5f72uuZf1MHede54kmluh5AcT7AePDmgg5jatnWuNq8dQN6K9XINsX63p3IzgLwFknYHKST3+EM4bvZcKbX4W8gAXoQ8y12/dN7KMa58rJETxM0cmowM83U00Pj0Pd1jo6VYdQI59+EJXJogD+xgDwE1jSsgG2/M10vEAsp9jk4Vn48gLRlgXQyx7+501T8bq5DBYu9GecYU8rszyp8h/6vj/HFbcTZbEDItD7Hvu2uls90H2POvUDqO9soRE3LE4MxnvNJ61uhq33EIZ+MvsXY6tNHhnubrEWQxly+pXKuVTruQXD6Dg+e3cGR8+ESxYDDSZNmEbOvm20oz0IG08QSOY3yWmWCA8ZlsBKdnyn1D7Hu7pVzrGSTXr4yiqGRRMUJDjFhJN1XuXenwNUX6jQSx4hzHDPt0j9XcDfEAtvpM43Z7Q/uDy5vaG791bdaH7abG+9mh9laH+yp/C9fIvVPFggGedWP0w+m2/nZ6rvoW2IsyBkwhqUwwvinvLRba7+XXRWPiGAwGg8FgMBgMBoPBYDC8AXgpJk7gB67dnL0JHiDJbcIvUR6/vCAxIRgmI7xF//QzJRP+5NMvqvLpBIkSO/qKWceX2Nvr+sqwgeRzwxGSUpVfvdaRtCyr6Q1eHuuLSFTTW8RzMAG+QuLFu/fEOFhDksEf/76+kHWQ/CzydJ6zid6y7R3qzfyNS3q7HiAp4Dz5mL/EbKqeQ/5gvO0eTpBItKN2JSunj48tGb6Q7OENd4iv+SG+Pk7wNT3AW+6jPX2tP0ASsvauvmDNv5YVeEs9Rraz/SN9ZTtDctZjJLAbnKjs+/oqc4IvdOd4s8pkZxEYAhOHN+Uxvgogod5CkmgmMV0y/JLRMuXXDCYsxFfGMd7YRx195ck8teNf/+bzqnyWqLN9sE9W8DW9e+NyVeaXJiY925iojebDuHBgM+EtexCDRYQvYWeJYs03T+6pXvc1p9caihE9JJluIC40Ys3XZKy37sVUY6NA4urJmF/4orLuS8xs7JxzZVsUC8nokKQWjJgOmI2jI33t/faZvgL/Gl/z98CaGKnobt1QrDrDmB8iUemVHSVWrWFsz79QZXj9H4Jx0H+iej3f05j42Vf3qvL+udr+7/3kj6ry+bm+cnz+RMl09871pSoIdK1LXX3d67X1JSaq65gGvj7nxXIZjXN4nnNRUI4VsOJijD2fbBOsRefnGmP3HymOMnfhMFG/Z0hKHmCeTfYUx7K+5ssEMZjJ+gZzxpSn9kkjMC3xJWp3W18W167rRu5+q6+fZCisgxXVRfL/VqJyvak2WF1TuQtDg3ZdczoFe+W4ZFJm2fK+/jvPc948RoLhQCYcv86ie5yP9YF7nnuPtFdgYvkCbIeF8empr755LMZFlH5ZldeQIHRzY7bW1sCk4NfsBGvhsA9GGubl/lR1RL5HF+FLIdtggISMNSTOL3IkMC4UbJgM08fxU2+JfQc04tB9XH5ZP4kU139+ri/o/HTpw1hj2tc/3LunRKm//Oyzqpw2tb+5S0MHMLpbiKOPn2lO1y+Jabzxzp2qHJRrjs8k0BhTTw4V33/2jVhxG9ffq8pfPdH8Hya65lu72t/W+tprvYV59s71G1U5wrwMwGrxkKCVbNSVcNbXwRL7My9yNynX5AHYMX2ww2gwsYYktWTexhFMDc415h891n7+82/VnlzTrl0WE58f2WvYO9LcIygNEZjIO8NcGWGdHYNlcDrVXHn2UP3Twzx/B2z1zg31ZxNsmgnm3Glf62h6HwlawSRs4dGvtiazlmWi22q4f/ijD5xzzv3wXTE+s0j1OO2rDWPsm6OmjvGxnzvaV1wcTME6PtGeIoaZxdVL6kfupWpI8jwCE8YvmSSez2TSGjv1QO12aVPnHk6ZxFd1eYqxNoG5TgGGcA/PkRMwU9KJ5lQKZiAZy2SMtctnNd9bLjdjHsN9JNiG8MDVsIdvoN0SzI9DxMf9QyQcn5B9g3vEWriFZNbNFGNnoONbocZ5f302v2hCNMGG6ui+zBNGWJNOsM+6vw+FAJK6f7av60S/FbO7g/Hk9fWs23Lao6W5xhkNdXI8U7rs5VlxxsQxGAwGg8FgMBgMBoPBYHgDYC9xDAaDwWAwGAwGg8FgMBjeALyUnMrzPFcraYwT0P8DUMwoN5iCThhP4Q2PBKN90KzqyJy0BjnN5u41nQcUz+26aFybSGI0GkJGUFLIE9CJ6yGSuiFR2GmAhGAt0aN6O6JEtUCFPAM9fTRRvVZ6OqdD0iImIDxCAtIkk3ShWdN1z8tkldnfgmL1InjOVWKW6Rh9Ajqs54lqWywkXFUbXtpR/5BanoHmGoEGOR6rb9uQaG2D1ttF4i/SDafzJJKg8fq4jgeKa7sFiUGh60yRiDuOkbQVEq1kSoqj6nJ8qvP3mRAXbROCRshkydnS5TclisJlJSWvgIRjTuudXbvA4arrBhIC37l9syrHXbXdE0jUmM1vHe3ywftKIHt+LJprAep1giR2SZUgF5LBhuq7sSNa9Aj0/BoSQuZNzd3jU9ETY9AvxxPVvdfTObc3VX66p7mbICld1MLYAB00nycgXLIKwJvPO84/xIw4pFRCfzcAxfP5PiRMz0XJ/tUTldcRQ//dH/ydqhyOFfMefv7LqrwdieK7hqS1WSmFzZBg10eszCH5akBKs7MOSixkkzXM86ghGWp/RfKoTx5LttPpgRLd0FhoIXaEGH8hJIXuNUk4At9zvcbsXuuQe0WQPhWg6k4gqx0isWWrK6nGBNKdcyQ23l7XPW9d1rrxh3c0R3zMiw7G0vZlxexuScXPobPrgML/Rz/+flVOz9TXBeLL6N2rVbkPOe7hALI4SOSiseY05Ze9lvo6gKFBI6b8TXVol/0eh0v+BlWejrnLSXsuCsqsdEwTY36tpvozsWq9h3VuTeXLlyRJ3Ubi8ke//Y3OA4n1EfYchT8bazXQ9NeQQHT1DBJXjKGPtiXruYuEjxmuMzhU7CiGkBxhjg4gBVmQKmK7UkCy7WGdKigJWCLyNHHnJ7NEpMM9yZCadcWfRghZLdaiBPvVArHinfc+1AW21F/NJ6LlT491Le9UcqYUidtXsXYFkBH4pVQig5QiP1ebNzAnNjBXblyTRGWQQbqOmHoDyT+9Q9H/QyQn7ieqSzdXDAiRQLUJKcUWZJxR+beUzb0q8iyr9r7PHj2tfp8OJI/b2dzEX1DqBZMHJhLFnF5d1f5nd1sxFMoKd3VX8bQYae60kXDaY4LsshxAKtSGTKaL9dKD3HejrWMaiL+Up22saU5HTaRqoGwYCX8D6L8eP5TMNappfdlq6ZzxuvYYy0S9Xnd33pslZS+mMJVAZ6RIcst4voKE/DXIkvf3NJ/W0RarNyURZ7vs4DklgEFDiETB2UTrpZfO5kWG9AMx+vTaNcXOFPNygqTw9x5onvGZ6QSJ0FewX9lBEvtjGBQc70nSMx7o90YXCbXx3PvhrRvOOee+eAgZ7yvC9zxXL40KOg2Nkxb2FU2al6APTxFj9g51788hfau3NRe5VuTYw8Xo5wDPbhHufQq5mV8+U6xe1xxeuazyCVJFDHPJKYMaZOAwDqFEk9K+T77RvvSwr330VkvniX0kZkcqGIfn0QxS6yQxOZXBYDAYDAaDwWAwGAwGw7+VsJc4BoPBYDAYDAaDwWAwGAxvAF5KTuUKMdLHQ9Hjeg3R9EirnSBjd6MmulMDFNYfffB+Vf7x26C71XXOuCMq7BSSl5pHuqfeR534otx5JbV0PJDEogE5z+6a6FzrXVGlhqDWZpGob7//keo7HYneiaT+bpwgg3UsCq0DnWo4gFsXqJYbkH8Mjkua6xKpqp7nVbTFHPcYgboehcwwDqcJ8KRvXReV/saNG1V5mlOyAKcyyO9IG+0gw34ECmkB2VJRalg8UBxDSPgiuOP0OqKqr2+p7Xd36A6g8s6qxlkK2VoBquwBaJBHyDxfQG4zgczOdUSno3RkqfA8F5QSLh+uAzFdqMBwT9D+q6Dfv31NGfZ3tzUXjkDr7LZ0/GpXx7RBD8+v7KoMtywf8sfRcDZffLRzva651e7CmaYluvQEdMOPPpSEqw+K6RiORz6uz7F8Bgljjjl6hPMkHvrRo+PKvM7LlOQUbq49oAw1dOxPjZ8YbdUNNW+uQ8/Y7IFu/zYkT3X11fhQdNuw0DE7cORorKif/Vjt4JWONzmcAVJIbCK4l129JgrrVcSL0anafgKKfB6obVuIxb98JAfDMaWKcGGI4PgUQ95Si3Wewn890sZOveF++v7MbWZ8hrgFB78MczSrqU4rK4oVtVXF2tUj9e9H1+Wy0ILDRghJyhhypuwSaOZbopPHbV1rWrZdjv4PY/3dyi4cS9rqozM48hSh6htCUnf1zm0d80jH/8+ffKpz5rqPQV/98hhOkGsfqr6M90fHs3m8TJmx82QsRukpFFQuoSYD68M66Pt/8LbkqRSD9adq5xrm4kZLbb7Z0+93/vhHVXl6pjak82Ecztqw3tRY6WHtuY11mTH00bH6s7au/YaHWN0C/Xx3TTHlL3/5q6r857+9V5W1ojqHZdF5aEDfo+zl9Ugbc5e7UTa7v5vbimfbHd1Ds6Z29kHhb0Iq9vZbkioVDjLPRP24uqrzDCFnGjr1RxMuf5c3NReLieJnXsrs/aHWoWAkicfuiuL+h5BQNrGG1SBdjTCPV7uaN2H7RlX2IXXIkcYgwB4PYd01Edf/wd+RHLdTduN/84lkT6+Mwjk3d55LVZ8Isvk65lAEFyofcou4Bgl/S+vZEGvOyor2fwmlvZj3XNPQVFW/Oecqp1cv1PUblMzAJbCHe8own3s9SDggJ9mGdKy3oTFE6XK3p/s7a2uf8+yeJH/jgfq8BqfOENLpZSKKYrd7ZSY/aow1nj/5Sm57e5ANXt3UHG0hprYg33NIBRB5cLOF/LrWpiMqOjLT/Sd9rtOQd5UyKzz2uAAxAmoa18NeOMfY3NpWXfqncNA6kkQ1xF6nVtccPcUzUAYp1vhcz6+tGPtnOB3+8N3Zuvsnf/EztyzUw9C9tzmLOUGkdqij/lFDbUxXsY1Ac+tDPHPfGHPeqA8L7NsL7LMD7Nvo/NyARVbkq8PqpUQxxryp+Tr2B9g7byA9xOkTxLBC86y5oueSHPP40qr+9sETuR/iNtzBI+1n+BzveZQU6vfp32KLakwcg8FgMBgMBoPBYDAYDIY3APYSx2AwGAwGg8FgMBgMBoPhDcDLyak857yShp0kpJiJ4uSjnCDdewY6MTODv3VFNPs6qLf82xRUqBS/R3TFIl0ZVLm8pFyPQF/tQP4VxaK+NRqiTW3A+WQCOldWkN4J6ulUHKrHB6IwkupZ5MpgPYW7DN20cHrXKqmhvre8d22e57layQkkXS8gfRQSlBTtGuOgTdBQt+HGFQSiFYbgHgaQ+WSgomfIGM9rOVBV53S6BfcIUOk90FN92IZc2ZQkIAKdLwEletQXzfP4ROXHe6LB1UDbW3BiAyV8PBRF93Bf8qvtS6KlLxO+77lWIyzrJEpiFxInh3o/OdLY42gKIPmgs8r2FTjZdEQbbSFrewjnpDH67rwv6ueEzibDmeTJp0bBp4xP1++sa0yR7kqNQram+56OmiiDkoqx0QcV82gHErkvfluVh7nuIw31t9WtLluRU5lTgT6K2+XYzjHmgzrkK+irq1sa8z7iVg5a8QROgZSMRZBl1ODC4aYa215a/q1Chysgca0jRnjglTYRC9ZBQ502dP0UcSGe6P5W4U7x4FR1KTCSA9CZqYGJa4i/CwKX5aFRi9z3b85o48/hnlGD02AKKm2Tzhs9ldfrWn/8TPLE8TnkZ5zHaPdGV+tYvAPKOaQYKSSf9VL2PIVTQ4G+cKSwxzqms656RSPVN8Z4qSFG3sp1zN/9Pckwnk9FLXegQu/vK3Y8eqY28zE2vvl2FptHE/oivjr8UtrAeZZDHpyhHKE/d0Hf/95ltc8WXHB80MNzOOnVISGttxXDGqCl7z/DOtOncGk2znMEpQgxeXdDdPIG5EQ3T3SOArKBVo0uj5BQZppzo32ti7/68p7qlTFoMUhCToU9QF4sUQoHpM5z+8Vs7P70/Q90bcgWC1zbQ/3yGLIcR0k51oGhxtwKts+thiT/riuJWm9T638Ya5zktELKZ+MuyyEVhXsJZcZ36pBwoAk96Hwo1QghIfEx7iJIZDnv/VQxIo1UruH4j1YkNauVDmXcI70qfM9zzVKWFPu6br0NN6aG2jKiJBuyoukYDqfYn1FuuwJpfw5JnMe9McZLgX0pHQTT0tnN9+DuhXUrrmPfNMaeCOdron/8iLJ4laeQfDUbutcm5FGUC3Ya+j1CW+bYJ/v+61kXszx35/1Zu2+twRlrS3HpyZncgUbYl9OpqtfC/eC5I4fjI9u63sEeGGHpHHEvTSktg9taOe4KOO9F0BXmkCG6XOU26pjCYaiOuLPWxB4FqUBGme77Sa51cUJNF9a/Ltbm23Sc3N0t72d5bmOtes394Z3ZfD8Zam0+H8G9FrHBQd7Vw55gG86b7BNu7dknU8y/BM5fcaB2xhbURXhHEIezNg9risk5npHqW5oTPTx789k+g7S1vaK/XVmHRAt7gBqeGx480h4wHWN/xdctVPkVdEV0Lw1j4hgMBoPBYDAYDAaDwWAwvAGwlzgGg8FgMBgMBoPBYDAYDG8AXtqdak4p9iETarRElSpAzetDStEEfygbi9bWDCFtwjkDUP/GoI3WQHklFXZ0JilMHorGNSkz+DdA8xojA38O6dAY1MYWZCk1ZEqfkp4K6inlXEFBmq2oniFpxqBm9/t0TtJ5RJddnpOD5zkXlrKVGJRNSh8K0IeTie6xAZpeC3+bDeUMFMIpqpiqzVPcu4e+8CihIJUMUpC0pDZOE7Q3qJchaG35SHVJ+nD1cOqHOmlzqdo+RH/6dB4A9ZSysILSPtxfDonSCE4Iy0QcBu7K9mzuNNui1a7CgeYU1O+nh6BCnuuez471+86G5mKnDcoh3KzqkBk6OO4Mxmr3yUT3nGG+BHOaN9qW0oU0hSsTYkrcUt9lKbP3a57XPZVHpP9PJUWJMS+3VuTy0YgfVOVTSMESHw4ixd8sLAnzoeUVF/z4NySGoBgHkAlFNcqKSMmHgxQy4GOKugDZ9j04e/iQWRVwtimyuYQD8i9IKRqUG2akJKsuPuroQxZWFPq9cHDzgMxu0hfNdQBHsklXMrLpBJn/J7rvZPp6JByNes29f+eWc865OH5Y/b7SVEOHOR2+IMuhY09d5WkIV7I13Vt85brOAwmeh7HhI75ORxr//lhjOy7nboG+y0dwlcO4GOSKi70NyH9eIA8JBjo+yyVbLDL1l4MU+SFcIeJYUpRHzxSnvvjiq6p8fDSjKw+Hy5VTzWNRwTkOp6WC6wCOWcX+oIt5vIJPZKurarfaivrTayleO+xFpiONcwfZWA394so9EqWSOdbNEM43mytq1/VtxcoAEp46ZCZFrrYf7UsevgupQht7gEMaaHKfQ4sjyjaK1/P9MC8CN0pmbZpiTahBiu3DZcXPVI8E+xsfQdKvY77mjHU63luFmxukox7KdKQKPcbp0n0Te944UjsHkBb4MeIZBmcD4yvEGCkCSHD/X/be5FeSLM3uuzb67G9+8WLMyLmYVdlV1d1kkwJakECQgqiVAAFaSYD+FEmQQIECtNCeG60IQQJFtSAuGlST6rGKVZU1ZeWcGfPwZp/dbdLCze38rOu9rogODxCv9Z1N3vA0Nze797vf/czeOffg/D76I4EwwfcgF4LjX4bx8iY6fnK8nIuseV4VRZG7ZL5c9+iA2YZkJkC/hlgLO3CyDQPIZ+BIyrwZYr5QQhdg7uTY/mGOsaj9CXwV5xjXZlv5kbXiGNcS4Xc4VXieFLJZxpDX5Xyic6vGvwF3VG6fMME62p2+nhp1MZ+7e1/dc845d7snV9E33rhTte9DHjyES+gY8rcb28pdBecW5msMR7a65h1rJEI0xVq3AanPSq6TIS5ibBEygSS500NOQU3bgrwowDMt3cQWqOsmeMZKYe03nWGbDSxJ25uK8RYk8Gl5+nVWqFEcuhvXl7mlP1EsPXoMl2jU1THqnD62sHizlJs759zOvsYzwxqSYp6NJpoj5+fqn5NnqmfOUGcEOWv15dzxsLYFqG29vvps7x05afa3IHnEtUSQhbHu7h7clLXb8AAAIABJREFUrNoTbEXx/OhPqjbKHOcXlBPzc+Sj2vPFi9WrxsQxGAwGg8FgMBgMBoPBYLgCsJc4BoPBYDAYDAaDwWAwGAxXAC8np3JiynY25HbQ3RC9azQUPW4Kmc0QMohpLNpcGIHChF3y4zYoTNj5nrTOHBKBxUz0pwS7gyclx2w2xK7ukB/EoN6Ncb2TU13Lxq52AG+CHpcu9PvDGXYVB4UdG0/XqLsFdlYfDHT8ZCZZ2EpFUKzVycFzRUkVbIEmRjkYHYUmkCxs7WjMI1B5/QTUOtJcSZ8GxZpOUT6ohzPQCseQ3KXljvAN0M23eoqb0ZniaQEanJeoXz3EH4M+SOD2gXHLJmoHiJEANFcPVEAf52/E63NquAytZuw+fH8prSggYVlgt/XjM8iKMD8OTySrOD5V3+1DNhXTQQUxH0PmQUeqOcZuDipkjHFvlA5CdJhL4NJWgO+66IDCDspoADkXY3aRaEf4JMO1YI5Ox5Am4RpqspBEfZPSlaJsFwV1A6+IwrmVmoVSDTq3FBGdVEjfBTUfjjQenEmKGmUTvwvKpg+XBC+j3QnklbjltNw+Py1Awcf3IjrSUTYF2ngIFxzOLbegC4jaB9uSCzYeSq5El60F5AGTicb56Plz/dZrcsRpNJvuvfeWdPEBqL/sz/OR+qt/rphvdXVM3IOcAzEZYM5RLpNQFgw6dwhnDX8GJ8ARpFNlnHgR5gQo6T7cHAqw7ZNz9XnQ1fUukAsDSOeOR6oH/vTPf1q1v4IrIB1aNvq69tPBF/pduGil5T1l2TqJ45D50dWNdHzMA8rgGpCd0DLIw31llCujf8IYzoqYu8PnkHUOIX2AU6BfunlEkD8zZ2V0WIEDSxvyVEp4fMTTYkZ5tWK6i3ulvNqnVRLcROh8kyIhFWt03CS8wnNRUq4zMHfpwtElRu4KLpGw5JBK+civjuMFKXaNBY/jc9YIoQ5aLOhIuvw8wHVxLYwhj3SoeTPILegyGcK1KIdbIMpPV8ARLofTrFfrA9Q6kEz0WpIAnsyPy4PdGuFVdVYPcqoAslr2txcyb8JpKL1YBs91KXAXy5noQpXgxxL0P3+3UbpAeYgbxgFtZ07ONbc7kGFs9DAvKefCmAR4/kkxbhnlrJCdUSKdIDekvL8FfX7Wh2SRuIffLKWYs2/drT7f3pWUvY167uxY0tvBiM9EkLbgGcALKSFTv0TIUSFdKz31e46nAB/OYUEZ2/yeF2gNm8/xvIA8121rTvBa+CyYZnxeVZ9P8bw1g1xuQkflvub0rZtydA4ghfz66dI5kA5mr4o8z92orLNbcKbdgNshc1JNnk03VUjJ+nu6lyakcuw3uspOhuqfn//oF/ocWyVEiP/Vuss5zNqZtW3cRNxsb+EQzBXECh0M4y0d/x7y7Fcff1m1G7/4tGr7XJshrXJYg2tbrjg6UV4OY+IYDAaDwWAwGAwGg8FgMFwB2Escg8FgMBgMBoPBYDAYDIYrgJeWU612TO5tikrUgCzn7BCSFNCdEtAAE+zOXhSiymUx6KGgHvmgN9dcnc4koXj0hShMdFxZsezvP5cDzRiU8AgU1yyRdIh0flKRu3D/cZTugLtboJ2j3YL9Ugh613Co+xhORKnc2CipW94aaeOelCQB6J5gcrsMND4HSmobO91TntEEZbgFKiMdvsImJVT6XTAS3Qy75JOKt5InbW6JhheApj3HjvFPnj2u2h5ia6Ot79IZwptjR3TQMwPSw9Hm7vEhaM4p3RnQN2H415hiL4Ao8N3+5jJWnp4ofiag3lMWl0BucgT52RDSJ7qyhC66sJ1BqjiB89Z4pPYcVHzOl8Zq53/sJD8Za84FoKp2OxqX5gb7nGMEFw70PyVlUzi/jYbKR4MhrhdDPYZsY4YYXMmo8vWqqdyiPC9dTyiZyRyvAVIN0D0dKcOkk4P6SQcpj24nufq5AJ2f7jELfD4rHeKyXH0ctyDLpLSkgGME6OwR3Hxy8uJBf/UD/eY25FTbO3AzRD4tkJB8UFvfeUvU4+1N/e6//Nd/5taFPM/dZL6M403KPOGYOEF8jiE/nSM+/YjyFI1d1oQuJKK0E2sU5BkO7nMF2hFp86VEmbIt58N5zodrIPJffiTZsI957vd1Hh/SoTmcws4HykcDOEvQNIyuKQvk2lZXcz0uHXpqzONXhOd51ZpCt6eCLmz4nH/9WkAmxHGmDIJLeIg4jzLIwBd0j1FOH8Mxr425k46XNP8cbnNeSndLOulAPuBzLcbcRU1SYC1mbo2gOYkhhXZzJkbcbOFd9KnzkQ/WibzI3LSs4xaIGdeFwyFo6pRT5XBbdKG+W3eYoSQMjigzxW0KKXixge0CIJ3J4IQU5SunOM2/vKc8l0E2TMXrAnVsjPU3bMupKsD4BnCwSxCQBSTlBXRRlGJ5Hly2fMguN8vcHK5vPH3Pc41Scr/IuSbA3QexnSKyaoJZxKqHuUuXLq8WtpjHqCmHqFFoqtaHg2ajlOQsUB8tIHdq0O22q/bwTA6qAa6+A8fRqKX4o9tUgD6n+2sL7kVRT/UXHb02tyVp6nYgjVkjsiRz58+XOWo0Vow1phe78bK2HuEZZISx4PNFgLr0Mtc4SpXOzjVHTzFfop6uoVfWUhnCmTXhBDKoY2xLsLWzV7U3+upzyknnqMGnc25FoLWbdbqHeG9Agr61qdgYnh1X7Z/9aindYey+KgaTqftXP/y5c865d9+QM2aEeivCJKLD8xRjfvxE17mzq75qQJYVQMIdwB11gee4ELVIiL1KQqzIUbm9RI6+zwJKpFk4wE3VQUKOZ5SaCR0cV4tE3+3i+fbNOwdVu9dBvOJEGbcawLyPGwg8lY9/JYyJYzAYDAaDwWAwGAwGg8FwBWAvcQwGg8FgMBgMBoPBYDAYrgBeUutROFdS+pvcNR48ofGZ6NYz0IATUALnE1HZMk/tFPRjurX4DdCMsVP5yaGcRx49klzq6aF2E39+vKTQzRNRzDZBRwtBH22Dqv7hBx/oWkB3axzsVm06NLmUDhVwvmnomOsHoF+FuifPg6PQsWjUcbzs47VKOIrCpaWEg5RmDzS+BSiOMZyPIu6iDTpYeIlTRw+77VNONU10v3NQhSmbayFeipJClyak0EJu57G/RYnzQBmOIMNpg2KcTnUtbbhmtRoXO0wtcL0FfjdPIK2bgEIevZ73pFmWueHZcn4lkETNQVUdDMXHo2xlDCpnQgsj3A+NX+YpnQwgAxxLnjSaaX5lmMcxKMd+c5Uz9L0cc8hDoJNmTFp0fxOxRuc3UkgxXzPE8hTyryHcD+a42QwSpPMhpAkldZMOK6+KwjmXlHOxAE00ggQhRwznl7kAIN+EEajucDTw8b6+GCsu/KlydLG42GFscKpj/PIaqDzw6QaxISqxN9FBM5yviS/XVBXUdGJNCZqiEsdwMKTkpwClN8Ccu7Yvankcvthu/y+LIA7cxs0lLXgAt7dkKho+nU8yuEfkkEElkF8FHqVVkDlBwpJjjZyfwYkPsqXxqc45BV09WeVaX2vlzk30M6Qfo2c6h3euednfRZ/DnS7AuIRO9/fd772ne3qmtftXn3yja5xpjnrI02Pkl7iUT+RrnIvOOedd4E7lcY2sySv1vXM4GR4i597YUq1QJAj0Bb4Mej7XlgEcOc6nOqZLPU25pnmgtqeQOaaoeQJ+DbEVYE3NQSFPIctNIfPKEEOUtlPaRrK65y7OX5RZrRO5K9zUlZLPvtbwcAtyqjFcw7jQwb7Jxxh56Ec30XxJju5V7bMn31TtOc6z+53v6jyhclEA98ewlFYtAsxz1odwmMshl3t6+LRqN8+Va3YgBdtADMZwLfLpuqZfZelay8EeEliG2mjr3beWl4u661XheV4lm85QV0fIB14EaT9dq2rxRok7nidwx5TBsz4YwD2vCafcrV256bQ7ksp5pXRjNoMbEd2FtnSOt99RHnzyzedV+xmcF3PotjboGuhxrYcLGsaqt6Mxv3ZHEhgfMqPNHUg+NnRP60SWZW54vuyP0zP05w7kRjie95NALk7HphD1ZxhAaofnl5RuT5gXCXLtgwePqvY3j55U7eOVzB657dOPP67a3Crj2x3dxwTy4DCgixociZD/5rVnILjSOYFOXAVrY8jCBqgZvvr64a+d71UxXaTu54+Wa/UjjGEfDs/fffdu1d7NIElKIGs7Qz35DPLgvp4P4g08f2CdefpA4/PksbbLWGDtarZ1ntbKwTFGPqUbIrZ5GT+XI1qK7Ra62CIgx9LNetyDLDnMdH97O6q7W3DW5ZoXItF2UWv1O+qzz/Qq5a+EMXEMBoPBYDAYDAaDwWAwGK4A7CWOwWAwGAwGg8FgMBgMBsMVwEvJqYqicOl8SVvr7mD36Ikoa8NT0a0LUMbo+DDDbu9JIIpWAQpVBElEEIvmmMDKYqMvOuPb779TteO26Fe3bt5wzjn38Lno2zPQqXZBPdzsipK1c02fB4Wud3wk2lQr1u8vUkgysIN1C7tNb1/T+bcacA0oQJuDtGo2WfZNvkY9VVEUFW2bVL+cDiR0OsF7vgA0QQ/SKjKSeakpmcr4H2NSCUGJC+h8AYmGV5S7jeOEY9Bd+XmvBTck0MZz7DDvNdXflHl53PkelGGYOjgP156Baj+HvCuj28NgjVo4IElT9+RwOdeSifrwFO3zMWiVdHVDn09yOj5QKgUJBeQFHJcOdpPPxqJ5H51oJ/oG3ZJKiuJwIDroGPKvJvrcByV8NoAsZSoabAo6I6nQ8wXkZZCujDEvEzquwH2ks43+iOBUVZ7f99cryfFKandaGwf9/7imXoBsoqD8CrIWUMWDiBR3OKn5Y3cRaBQFYw03x7X1W8ucB3UiDexq8zyGrGAyhWNRU2PSCCFdCeFUAZntKaQ6I0gLwHh1Hl28INGjjKnZfk1OcVHo9m8sKennR4r90xNRdcOCUmF19DShFEb33ypEOW7Q4Qf9NYecMR2But/UunSa63d/+SvR9cUa15zobWPtjrAOnUiq/He/82bVzhKN0eIJnHJAbR4e6xpPcx0zRYC1fMg8mpClot2MkRtKx6vpmt2pVnR+Sk0oG84hE+P8ewqnk4enut83ttXutODUCHVO7sP5DbKB0yPlyCzTOrbAnPJWDmPIlVlysTyIbj7FQJJtv+agBXliSscU3espJAnTBWQ+yE0e6gRK7Ws1Rv6a5FRF4SbltWQp1p5Qcqo8oAspXEhwzx7WQsrSRs+0/px+9UnVPnoumv/mu9+q2gGkOE8fax6lkETsl06vi7nW3HOsoRnqsQPWpU3d071HD6v2JGMtd6dq97fkBBOifqMT7ALxXmDNiCEjCGPUT73l9XjrdOH0nPOqPKffSgr9RquvfmhD1lIgDjOMp8N6n+LZYoytHSg/j+CgWiD/Ui47gLxkJemaQBKZoC5N8TklhoNznWMGSdA55Ix0GGtuSvrE3FRAohw2lP9bm9f0u1gwoz31n9eF5GONWOS5e1DWTV8fam3Zuyt3ogjbTcRwYIprtTtkwHQNxryczemgiprCVw7YuXGrar+LnPn5l19V7R//YunEVCDnbcDh64033q/a18pnS+ecC9H/EzybODjY8Xk4Q36hdCjGmDYgL6Ob3eGZagP+1mlZJ2dZzaPtlbFyWRxzWwUoFaczyqDwjBbiINTnnUfKoZRez3e1Xp7j+F98rDx7PtDnMVyxI9QHq20xAkhPiyalafh8ov779C/+omr3MOY72EKlh7kY0wUbUn0fY8v1OnEX14AF9Fqt+OVlqcbEMRgMBoPBYDAYDAaDwWC4ArCXOAaDwWAwGAwGg8FgMBgMVwAvxYH0nHNhaXPQgfRohp2nzwbavb8AfdoDs2oxFCVq5STgnHNhBKcG0N28BnaZbqrdaOmYm2+KNrp/Qzuv5yXl9/t4X5WB5lVAK1OAeh5CFuDNRF8bDUT5moIiOYPjzjwVFXJOyvFY7bcORG3d7su1YDrFd7Nl39Bl6VVRFLlLSielyVTj0Kf0gk5boFv7PiimOWnS6FtQsqdzSE9ynTMBPTjnzuzQcwSkh5a0QhjQuAK7oxddUBmncD6CfGY+F8Ww1dbvJPhN7umeXUJV9UAD98BaJCUygStC8XrUVC5Nc3dYUvdTyqmwq/8EnEcSLBPE9gBSlSdH2g49o0MSju/3NO8bTcXM3r5ou1OM6eMnctA4LanI/F4TFN/utuZBZ0NtD9TDOZwHhthNfjaCVIOUf/THPOO81/1FyCMeXJR2cT3+1rZzzrlfPBQV/1VRFJIVeIixDDGZ11yokEtyOuWgTUnAucaTu+oXGPMZHKloMdPe0r3nkM0VZd+mhfpycAJ6L5zPmtyNHxTfBHnQhyNgAJeds7HO+eCJpAqktkegG9MosGaCA6lqsyX5wTqR5c6dj0rXrki/gdTvWrhWL4AkCq52izklmYrhGLJBUrLnoP+3trerdg6Hg7av+do7EUX47OFynT4Z6HyPP5fcYzgX/f32DcxXxEXsq2/PThRrc8Tj+UTnGU8lL9vaEoW/6yN3ZFqTGh2tGRtdSQTiMk7/+PRLt06spI1ce3zUB5RH0O3vDA549yCne3NXY9LtagyjCMVQCkcWzPVz1FGffqFxefRYUvGVEqu/o5gbTFQ/bMAp7lvvwhkM5cToTL+TgX5O17gZAvkENPcR13HQ/SnDSeGg5iG/eK/p74dF4dxKQXv4XPd2d0dj4aOfQ8ipPDh7LeB2ODx6VrWffPkrtZGXegeSatx4//tVO+juV+14Tjq9+uL4dClvS860Vjo40/iQZPkbms+7dyVtfHyo+ffga8lDHPLx7KaucQvrK5RVbuHpvj18HkTIQZAUnJd1T7q+EtVleeaGpUzk+Lmkf51N9eX1dzWeva7cYOa434zTDDFMCcoAsqUI8ow23HcnQ635zx9rjCaIkaiUcHg1+aDG+Ok9yd0KFIXtNvOCOpwuo9ORfn+G+iem/hk5K8eat7mrZyHXUh6PIUHz8Ky1TiyK3N1Lln39g88/rT7/4APF7WZH4ziEG2iBfmQ93UI9FwSQf2LRT1HbxX1I7XDOnZbybg8SxUlZG9G1tg8HpQa28GihdvXpiHWmNSBJNY4L1F0Z8iId1Tzo1H3UCSGuPYVT49Ez5aZp6ZK4zu03nNN6Qaki5fas+fJC6/psrrWiwLYGjx7r+CGOaTzVvRyeKneP0Lc+HczQb3O645bOswnythtrbhV0G0QdPYZU8vBj5dDTfcXozWuaT90+ZOANSGHPdE8T3HcBieZ8rpg+Qnt6pO++KIyJYzAYDAaDwWAwGAwGg8FwBWAvcQwGg8FgMBgMBoPBYDAYrgBeSk7l+37lskAq++FYFN+jE7W7oPB3A1GPvFQ0sSloUIGjpEc0pxg03AhUuXQumqFXiP7ohzpPWFIUQwfqPWjglAXMQX3LsKt4Furccx87dEOONM91LSloXsMJaNdPJRG4uS0K41t3ROfb3xW1/HS0pINFoZy1XhWFcy4r6YkJpBetDVFSZ6BJT2YXyy1IJ6djGN2mQshq6JoTge6ZgW42By2dtNSwsxzPALRPH5xwD7qmPOOO9eL8zeCOk3RAvYQMasF7IvWbTlW8Bkq+QCcf09mi0D2tE1nh3LB06knn2BEeVPEUrlIeZAF37r5RtRs90UOP4bKyWIgqTopnCopnF9mD57l9966+C/mLX/Zpqyv6P+V3pPCHdKMB9TSFVGoBOeMZZAFn5+c4BmOBmApApw1APx0+Fi19a1P3dPNg6UQQg+a+DqRlzEW0UcK4kTGd0z0mp7sBZA2gimaQszLPzWagvyIXN1q6X1KPm1uiE6/UB8WCtG7I1FLMP0h/UuidwhmcB3NRkknX/eKhpDf3Hqgd9+CqgZye16SNmMdo+6CzrhNPnx25f/I//VPnnHN39kT57yKHtDYRz5hDAdazmgsH+m4ykmxwAte4FqSNPuj/cxj/xJv6/Lt/98OqvfNwKXP60Q8kD5nAHenGpvr573xfUuU2wh/DVZv/Iw+SOsim3n//dtXOQ33+5L4kE8fnGsiDa3Ji2dkSLX5rc/ndH/2Z3LbWAUn1WG8oyeUB1hl8bwGd72O4zXz1HLmkc/H4TzPIVPA3tYNrcnCZTDUuz5+Jqv/FF18755x7L36r+uz2m8rtm5Bztfpa3304r6Sgwg/OUc9AWjWc6v6enWuspljrC7pJ+pRgI68hYLh2rhNF4dyqZPmzH39UfZ5BEv+tG4qlvZhyes25w2eSsH32U53n+EjOKvvX1e/vfvt3q3ajpb4u4Ba229N4LNAXx6UEPOpoDm1CNhXCscTD+bqQxLz1LcnlPv7ZT6v2L7/5vGpfnyiPvP++XHZ6Pc3FJNOaEUF+k0D+dQ8x+MnTpexgOFmfa2NRSOZOx8wmZl0bNUQD8q4JtmpgO0EdMBpJNjGbwTUHUhkP49NsqB92d5STeM6VtGoKOT+l9E3kkbih/i5qewRgfYf8eAo33ynyfxt1ekh5DpwQIziYBegzP1Kf5cHrcW30PK+673v39Fz4q0+Ut7fhAlTAyadmXod6iFsuLHjPyDM9SH6LGLGNOimkFAr93mwsr9drq/9DPCYzb9UUhB1IaxKtueNDxRolmnTx9C6p0zPUVX1sQRBj64t7D1WnL8pnKdZRrwrPOReu7pTGh2gPILEtfG0TUhSsUSEVxnPhOaSNBdzJ/Kb6k/Ob6+4cdewJaqRPPlrm673nkjAGTY3h7k09Y3duql5r7+raDz+7V7VHeM4fnWk8b15XPu/0lP9mia59irnY39b5T84kM59M8A5i9vJjZ0wcg8FgMBgMBoPBYDAYDIYrAHuJYzAYDAaDwWAwGAwGg8FwBfCScqrAdcrdxItclKjDZ99U7TFoQjd2RCvd7YmG6Pv63ItFYUzpagBW0TwV3cjHruEFnC+SmajLCaQzRcn7qrmzgLZeQLbV6MIxY1eUvKCFXeMdKHlt0BYzUb5iuDvRuWky1W+dnor+RUnP7rZo1H68pO4FwWduXSiKwmXlPfuQlTXauvcJduxP6WsEql+zDXpffHEYUXIVUBID2v4Ebl+TOfoW9EGvsRzPViDqOXdHH2P38smEjlSi28WgTW+BbumKiyViGaVjoMJm3CUecVnbER6xlq15p3j9XuEmJc09CBR7Hjy24gYoweBCbm2IVuuBBn/txo2qvZhInpTABWA0E/0xgftXG/TcBvqrDUeglYNDglfHOdx5+Ep5nkxxDHZvX0AiBCryHPc9y3XOEBKayNc1hqQxI34C5LUbu6L6XttefjcM1/feOy9yNy0dC/wGxhBOIB40Zp7PNijGcANKU7pz6JgZpKJz0MCjoIvPIXco1CdFQBnScmzprsB5GSFdTJGrRwWklSGcITqa52M4cnz8jZwFnh/p8wPI4BYzystAxcY1zBA78etRcLizs6H753/wR8455/7935Os4ntvSdqS9nWtGWjGTbgtkvJbYAFMPd1/0NV90r3JnYtyHyGnJRFyUUPHH2wt+/3vffdtneIr0Y/bgb7Xhiz1+JGkFFyve3ABSUHPPwXlOcLc6UHm1Yn13e1TUJQhY+1vwMWuv1oX1zegnue5oJRK+sj9MfJjCnehCI5tjVjHTzDPnsI973isueAaqGGGkCUib/ZbWo+//+1vVW3/uzqmW7qm7GyJpt3tQaqKVEX3vhQyqBnW4gS1ENtDyGxP4IiWgrZPdxifslXITxP8Ft311onceW5eSiseQvo1+6na3eZvVe3NA8WbQ446G6m2vPdY8o/Ogeqzt37v36varR3R8pNc/RVA3k2XyzBU3+0dlN/NVSOnWFszXFcKNy061W1v6j7e/7Zkkz/44V9U7YePdB937tys2t0u845yk1dozi3wqPDLe5KU/fjeUuo/ma1PNu4HgWt0lzmhswmLKci66fBHncd0ojw4hwzCw7q+gOQ4rLnTIv5ZQ+DeG5DTRx5ri2W7HVJWiG0DcI0+7mMM+dUEkjQfNWSMGqbA+j4bq04Pu3AnhBQrLHCNqCugGF2r/IYIPc9tl9Kx5yPVk//sj/5N1d7HNg4fvqP1cqePegjXF1H6RRdBSIzorDqG/OUEjn90KPPxnLBSZflYWxLIWVmnRZBktfE55YmNTT1rzFDfeI7jq3sKIAujlH6I+XWE6zkcYzuKcqqsczg9J7lZiOcM7IjhTgbqS5SQro+45ZYISe2RCHOaMkO6JWOeNaGz43qZesqFD0unzHNPc+vdD/+WrustufRFkFDefO/dqv3FLyVDHQ4kxc0hbdwtVLfs95W7H5+oE07Gyl8NuN81UFdMCtQG2MblRWFMHIPBYDAYDAaDwWAwGAyGKwB7iWMwGAwGg8FgMBgMBoPBcAXwcnKqIHStkrY3HIua9vTBVzohOLxtX1SlXltt10C7IxpSAIrkOejHv/pS9M2v7n+hY7D7PJ1bbmHH6RvlTtQxqOd5BnrwM93H1z+QC4qPXaXffkdOHXfuamfrgwPJT7IcO1KDunz9Fuh06dOq7TnubK9rmC1E0ep0lr8brHn3+JXEawEZV40azVd7EXiXkNU02qK4dTuicDtQObmTfI7fOoRrB+nc/W1RQvt76vOwdEkglTWGk04EKqN7rN8cgPq/mIu2R6csn9vggwoYUEIFamsKVyxKShagOXs4vsb6XSPyvHCT0uUHzDwXgqq7DapgF44k+VT0xydPdA/fu6N43rum/m+BBnj+XHPk0WNJXjxQPFugQm5iR/Z+SftPESPjmSiPC1Cec/RzA7TVGDvV97qi4rbg/lJ4isc4kmzjGNTlczhbkebaglvQfh+SwWJJo/Tc+mQAWZa70bh0JqG08RKnlxAyJKYEn+4GiDevxplWezTRvS/AbfUyOGjgq50GXC28ZT9nkLt5oPrO4GY3QR5MID3dvqGYCCDxORoqtk4S0Va3dyh/hLRurvHMGTtYC3h/YfRr/5k/AAAgAElEQVR6/maRO+cmZR6590Rz4p1b16t2gXGk8x6ZxRz3EBRrjukIsfoE829xpjNNziGdgeMOc3lQSuRi9EkTjmOnkNB89pXOdw45zRs3lSPe/Zbm5Wmg33xwpLXt3qHkWpugKCcJJAoNuPJEFzs3Lcpctl4ZgOfClfQHuSdAn9EZM8a1dZu4zpHufQwXjjGkGn1PY3t8pDVqeCQJz3VIpA4Q/3Tpyst5P0ZKSiGrm2E8Z3A6GcMRssBa1cFc9OBGRLny+RhzDvPMh5wqwec5aPe4bZdlr0dO5ZxSXYqJcw4J2dNz3cM7e6o/Y+TLrW3F9sG+1kXfU5139oXm3/2P5GbShQx374ZqGtaUDutlXuZMfwHJJWQzOST8C8znp8fKl2cjzacutgWg+08W0SFNl7KALMtHH6SQqM4hexjAjXTlvrJO0bjn+S5qlXKqLbj1UG6N/mljTXBYBzwHiZenGO514eSHuDg7k+QuQ70aFKwdIYmjy+3qeLhpZchPE8jGE/TWEPKvHHN0e1t5MG5SbsP1mtI65ejxmXKKG6tmuLmnPOLjGl6bnMoP3F57eR/HcNV6iDXhZKjr3tlRznvrQG2PsinUQAXjGW5Gx3An/eqTL6v2o6dycrrztqRbt24cVO1G+axB9+XBhOufxuvzn/6iaoeoM77zO5Jr7t/Q8+IceTSHW14Bd1nm3Tmc6H765adV+/BPfli1xyNdz3ixnCDZmodzJfEKULcwgZzCGeoY21nsQ2JNB9OcMiuM5wi19ZPHcjPbwPuCnq8xD7COYWl2O+U2Lm/vyQ1zJ1Etf/aJ6hA8wrlnX0tu6iHH3dxQDt/a1by8+bbWhVZHzyIf/0RxcYx3FCnq7tCDgza2LsgprXpBGBPHYDAYDAaDwWAwGAwGg+EKwF7iGAwGg8FgMBgMBoPBYDBcAbyUTsfzfOdHS2rT4Fj00cHp86od+6JHJQkkTI47o+vdkQ86dwSJTBeHH9zSeR4eg6IPZ4cdUOLe+r52579V7sK/DaoeLVSePpO059FQu6bf/4Ucod7x7uh3dkWham+InkhXJG8sPtudN3RdWSb663YPEgjQ3xK4qax2XC+KNWpyCu16PgQN7hFkAC5Vv05BtYXZDcRgzgWkx6V0YKBLl45PQFUl5ZS7saegn4ee/2vHeuDPRfh9MC9dDtcediHdcXL8D9IQPcToYk5nAzif6XDnsw9IVU1eE23cc84vtVpz0OZDUKDboIR2GnAYmmvH/gfHmrv3rytWv/em3CviWHfaa4uKfIr+nY3gaEZa+LEkArP2UpYDtYI7xffmHpziNvQ7fVDei65yRL8DSR1kZE3IGyKMdTbR2I0g4zoB/biH73qgKPul1MVbI/U4z3M3Lne7b+A6KavJckgFfcphLnaq8qHfi+h0gPwbx2pP5uqTOSj+zVD97zdE/Wz2+uU5RDEtQGefYzwPvxDVt4XfpNzOwc3n+bliMY+Ud27d0fg/hfx1OIU7WSIJbStTXHiQVAQeFpU1wg8D195bUofP56LPnk3UniSUrmp8p6Dt+sg5Dm56IVwbxieipf/yE8mYv36ofmlsqL92rmmcbt66gWOWfdSAg12M+Rfiuk4/EiW9CRnDW8gRfkvx+OU9yYZPp5AxbIpynGJunZ2JWn7ztujKOaQDXz0UBXqju5wrXCtfFb7vuVYp26zNLc4n5NBOS/MjxPyb4+9iU6wbg4HmxZ1bcsfY2NT9nj9VLfL8AaTdI93n7EhzKiw1jx7c4/pwmaR514LyVDhvbkE26+BMlCB2z8cawzPI+ejgWJduQloFyjtzJ50g1wnPFS4of58OMClkCk/Rh9M7cHuDRnWzpz66c+tNnR+SqK0dza2H54rPZ2P10fYNyTZyyOsC9Ong+TLvBW31W9SmbA59Bf7/s2eq2TJIL/YhOW7DiTNGHmlhHU/oCoqaIfPVHyczHXOCOZ2X41649dWoQRy7nevLOdIYKq/NEUusS7sp3N7o1JgpV3lwm2J9kEDmEdRqR7WnY80FP6ecio6Iyy/A1M/NIXeisyulOkGKdR+Od21IvtodjRul+h7vFfXMs0fKvzPU0XRi24LMzvPXKYYTPN93cemy10COilBzpHA+fPpcteI5npty1EYOtYiL1S4gPx6dKGZ8xEmbW0bg2SeHHLyocoDGOaI7FpysDrAGtDc15+aQ6vOZqcUtRXw4ziEvzNAfAzhPPTyS1O8+5Gh+rR5d9tM6c+vStXHZJ3lNhouaD884Xz7RGN7eU4w1sHZGTuMW4X1BgOseYS5MIUPrb6sPm8hhdB4tyrgYnWreRnCMjvB8MlsoPgJs2/D7/+jvV+0OtggoINHs7mpePjrStf/JR3p3MEVu7W3TQY75UrFIJ8IXhTFxDAaDwWAwGAwGg8FgMBiuAOwljsFgMBgMBoPBYDAYDAbDFcBLyanywrkVE+nefdFHR9ixuwXq23BB+qPO0wQ7LgNVyYVwmwEl9O234M6wt1e1H90XbXA+wm71p/qxLFlSz04fgnIZglYHKuZ7O6Lw7X9HdK733v+ganc3dS0Z6Oe50009g/vSRz/RTuJv3had6vqeaNQNyAvmoLGn3vI+sjXS4wrnVfKsKWiEp6B7U3pzDmrwaAaHi7mucw7OYAsUXA/05GZDFNaD63JtoVPVKZ06QOdu90sJB3ajT+AqcH4qquEJHBsWGaRgoFbTNWSa6j4WoAQvSLnDDvoZ+sBBLuZR0oXf8kmFdi+/8/hlCIPAbW4t5UmTKejQoNj2m3pHu9ET9S8Bbf481/z75AvRAN/YEG2xpuaDvIAyp4R9MQCNEUzdsHR6oVPPdld0fq8Fd6R+G58rF7R6mjcL3OsUVM88VZ8nC13L6VBx8vRYu9+PZ5Ko7G3pvkfn+jwMltTQdTo5FEXuktK1YjLRb8WQCrZrEg61YzpY4V08Ly8FtzuAhGcHUoFurD48X0ASN4A7yhROQuW8j3sakxy09Xwkqm8LVPV2rPHMQPEeQgr48UO5EE4xzegUMjhTPzV85c0Mek26xgVwURjCuWet8J1zpfvWGdwizueQocCZ4ByyPspQMrigxJAt7bV0n9tb6scbcId6dKQxGo9EaYa6xhVT0Zt39pfy4jYkTgWovI2JKL7fuyvZVLSv45u7upZ7M+XIL0H9/vyexnT/TV3MO2+/U7UPQBtPIFf4+HPlo0eHWie22svY4/r1qvCc5/xSiko3FP6dK6assC3HtgTjPMN6MoHc6/Gh5sXuc8lg2pjH+5C+uYniYmdb6+UbN9Te6C+voYBrSBMyvDny2qzQ+LiO7oNysTnmzWCmvPkMtcEZ1t3Ep1xefcb1ooC0KqBq4zXJqZyTxIDyLQrvHp3qfp4PFOe9DUgoUMduYp1zgWqQzk05z/ztNyW5OnymHBBPIbOg0yDmcaeUmvqQNmZYtzLklAhumt9+61tVewv1VTbW/J9PNBebqF2p3Jwjfj1sb7DAQD4+VfwOIC9yK1nAGtdFz/OcV9bETaz3EertGdb7AaQxnLsz5Ac6KAa4ryDU8Rtt5TbKabINyPIhi/XxW155TrraLLD++S2NT4ik3IGT0hRSXMpP6AJHcX6G+uf8mZ6FPvrJz6t2e0P9twf30c6u5MdxDxKlNWLhcnc/X97TGM9cdHgtUCs/gPT+/jM9C7wHl8fNbfQ/chHUam4DD5gHd7UVxgLzeIKY988gUS1PWUSKlwg1Sgv5otmGbHFDa2uxiVqHkjrcaxRw2xGN4zFqlKMh3FQhv0wL6v5w/tLZqHDrfF50Li/P10IdHkJ7OJ9BTvVY6/Sb1zWfejfV5s4OGbZqaGArjjf2FZ9HkI8l6P+tW6pLbrwtJ6qtN5bxsot3BY2mYjxB/ipQT/ZuKz6yNp4tHnytC56ov0eJ8sgf/lu5h/34c7lczSCtC1BTzVEb1BypatbQL7YVhzFxDAaDwWAwGAwGg8FgMBiuAOwljsFgMBgMBoPBYDAYDAbDFcDLyanyzA1Keub9B9gBfQ43FUhGokK01TF2T2/GkHZABrUIRRmLQINPIf9owQnizQPRWZMJZEjYqT8sabHjiWhqBaiqPmjru9j5feNAVPUm6MfOJ11Z17sAtW8KGnMTdPYb13XODbh5eKBN0WloMl72cZq+/I7Vl6Oo5AYZaJp0F8jBtR1CBnAC6tlsS3S3KSRGQQwudc0RCu406JQd7NjdhuuBA0W8VVLXeY5xrjGM6cLUgQwHFE4PtPVz0G8nC117hpjjruKzEeKyIG0cdHL0WQF3qpr12BrhB77rlZKnThdU1QkdgXQd25BTZdgdfgFK8NlQ1N5Pn0oGcQM70fdAqexgHDd2QQ9tqn8T7tRf/lSM+d/pSpYQgAYbgHOZIpAixMAEu9bPRpILzOF+MJvo86NjUT2fHOr+QvwW3R+miP2wlPJl2frGMwwCt1W604xBnR2NEPtwdWpTTgU3hti7+F18Aep9gbils1sMOvnedeye36Y8Ce5XzeXx/kCxQmeMEG5TESwGk57aQ4gbnoHKPIObYa8r6vfRsY5JZjqmAZlRECgufcxjulNl6YvRU18WeZG7SbrMRx3EMKU1Y+TIk4H6qMh0DCVhEWQu2zvKad1d0eM/iN+r2gct5eMnX2ptHo+1Bo9++quq/fknXyzPvS9K8k5Xcgsf1xImmGeZxiLD+D48xO9kWCMRO19+LQl2DEp9BmnuE8iOvnoqSn0Waqw/ePtt55xzUaQYfGUUrmIv+/jbVoh8E4FCHiP3jUGTnmI9GaNWOEFOenYo2cAN5mXIfM8gMRuAbr+SFjvn3F4piQibiv1FClcpSJJTT2PYiGjDqOtaJMp3x3AFenwiSc45rjFxrIvUNzljB58HlFG8HkOc1RUs/4P6I+c6h3Xjm6eaKzc7mkM+HHu6cBArNNQuxA/EPc3RHp37Zrrn2VT9O30uJ74Ca9cKkaf6oxVCQoI+3N1WPVlAOn4+Udx5cKSK4aYzn6IGDijd0T2hjK7HEnKWX64ra/RPdXleuGlZN9B1MoZk/ewUUmesG+gqt+DWBNgWoI3zcDXP8S/WAQG0OmnGdRGSiFLy68FdKIFr40pK7pxzQa5504BEcz7XNeb5xb9Dp1oqEj/5lXL7L37206r9/re1FcTJoWJuCBnXdocysvUhz/JK6pbRpRXXnaOfh3C+u3f/cdU+uis3v51duQwzHqZTSKIacALDWoQp4mLmdWzd0VzVt5BwOzxfpA04S6acQ1i7UXMUdFSD5Njh8zHy0SEk/KeoCadwh6vlTjr2rlFGVZ3Tc84rn8XynNuH8NlRfXyOfVM+/fp+1b6zKbnpRh/P9hj/HM9rIXLSxpbyb/ZI61Lngdal2xuUGS+vrcA2ALzeBNu/RNt6/iiaXMNQo0HuNEde/vhrnf9f/D8/qNrHqGc8DNYccskFZHBBwflNKfeLwZg4BoPBYDAYDAaDwWAwGAxXAPYSx2AwGAwGg8FgMBgMBoPhCsB7GbcVz/MOnXP3Xt/lGC7BG0VR7P3mw34zbAz/ncLG8erDxvBvBmwcrz5sDP9mwMbx6sPG8G8GbByvPmwM/2bghcbxpV7iGAwGg8FgMBgMBoPBYDAY/t3A5FQGg8FgMBgMBoPBYDAYDFcA9hLHYDAYDAaDwWAwGAwGg+EKwF7iGAwGg8FgMBgMBoPBYDBcAdhLHIPBYDAYDAaDwWAwGAyGKwB7iWMwGAwGg8FgMBgMBoPBcAVgL3EMBoPBYDAYDAaDwWAwGK4A7CWOwWAwGAwGg8FgMBgMBsMVgL3EMRgMBoPBYDAYDAaDwWC4ArCXOAaDwWAwGAwGg8FgMBgMVwD2EsdgMBgMBoPBYDAYDAaD4QrAXuIYDAaDwWAwGAwGg8FgMFwB2Escg8FgMBgMBoPBYDAYDIYrAHuJYzAYDAaDwWAwGAwGg8FwBWAvcQwGg8FgMBgMBoPBYDAYrgDsJY7BYDAYDAaDwWAwGAwGwxWAvcQxGAwGg8FgMBgMBoPBYLgCsJc4BoPBYDAYDAaDwWAwGAxXAPYSx2AwGAwGg8FgMBgMBoPhCsBe4hgMBoPBYDAYDAaDwWAwXAHYSxyDwWAwGAwGg8FgMBgMhisAe4ljMBgMBoPBYDAYDAaDwXAFYC9xDAaDwWAwGAwGg8FgMBiuAMKXObjf7xf7e3vOOeeCQO9/Al/tPEsv/nJRVE3P937jb+VZdvFpPH3X42kKNC9oB1GkD/HFIs/xsT5PkqRqL+bzC3+Iv+/5wYXt+kVefL0e/lHwkPIfx8fHbjQa/eZOewHs7O4Wt+/cLX/3EhQXNi9FUagP8wz3gr4tOP6XnJTH8Jerz4sLPnPOFTjWR2wFkcI7CDX+nn/xu0v+/GUhyiu8rP+KS/7x0Uc/OiqKYu+Sr70U4ma7aHY2nHPO+Z7ux2PnehePRTqf6ZBaPOM86ACfcw7XUDuGOaA27jp+lTNqv4MT8tjLpo1Xe++sL+T4cobcwfvmD+S1WOIZcTzuKQxj55xz49HQzWfTtczFIAiLsMxLPKEf6F/dTrtqb29tVe0oYurmvado416YqxzHFn2C7yaLRdWeTec4Znl8FDerz8JQ15Ki72tzEW3Px3wNmSvVzJH+ZzNdS5Lqf4TI6TPk6MVCuTvHiZjfx6PJ2uZiqxEVG53G8jfwuV+bH/rcKy5OgPw4r80FrFeM4Zw5EMfgnHntp379GP5myjmENtf6djOu2uELrOPEi6wlL3bQEqfnIzeezNazLm5vFrdv3VheQqGY4XxKE8XhdDxWezqp2nPEKseEeQvpzwVsY96HQYBjLq55vAuTJNfCi/P5xd/7S2s0c/Ql53e19QL1ldO1+4E+D8IYx+uYjz/9fG1z0fO8wr/g/tjn/N9cO4NL6gJOEh7PUK2tOfXr+Y3XXFySD34TskvWM3fp+bzf1HT1vrs47oILaoN5kro0y9cyF/vb28X+zZvOuXrfZHPMrcW0ak/Pz/TlTLm/4JjU6u3aJKqaWC1dgu+mqGl5TF6rG34djKZLa/zaNy4ZlEuqTu+S8QmRVPxI8yxqNKp2HGn9bvV6Vfvrz79Y21zc3t4ubt26+WvXXW8j56A9m2p8Hz95os/5LHZJnNfnN3Iqao1mQ/ffabV0TJmXUj7HXrZe1x6U8OzIOipRe5EqNlPUMfW5e2Hz1/51MZbXkGaZy/L1zMXA84rVfK/1K9cTXsEl1395TXJZLXRxzNfqnMvGv/wv8xTHKmPdVE/WF/yic/kl4+xfkhMvXS8vwWXpepEXLzQXX+olzv7envsn/8M/ds451+/p4WKjrQkxGyqherWJoKANYiz4WDj5wDUdjvQ5i/vw4knpEn0XedwlZSz3rh3oJwPd9mympMCHkcNnShz3vv5CJ8y0kMSxjo9b3aodtfs6PlLirEc1Xh6hjaZLyoew/+6//8duXbh95677V3/8b8vf1eceA5ttPmTXzqR/sXCdD9T504mK2xwPVj5PVHvgxsMXH0bTZTtDQkxT/WbmdI64pTHZvrZbtTf3NReChmI3x1LLZNrEpGQ6LPhgmhYXfp5wYcKD9NZGeM+tCc3Ohvu9f/RfLduBFqEo0u/5EV5EjgdV+/i+4jnI9EInaiqGmw3NrRYWPC60zVaMtuJ8gnHP0Ecb3eW8iLFoenhwYSEcIi/4CMIYDwIcrxkWyDMUdbOxrsUhZhYoCBdIU4mnzx2Knu3du8455/7wD/6ZWxfCKHK3br3pnHMOz2yu29M9/r3f++2q/Z//Z/9p1b59XbHtCt37+eCkap8Ode98+IjwY41ANz8dHlftR98oVL/4+OuqPTpf9s+NO+9Wn23t7Fft47PTqt1BfPS6mpdRS+PW31fMFcjt03O1P/lUv//0WHG8vX9Dx3zxVdV++Phx1R4Oz6s28/Wf/78/Xttc3Og03H/597/rnHMuCHRv3Y7WuU6MxR95zkNymWOuzPASK4rUj3xBNZ6qneA8KZb1aYIchQfqRTnX0lxxcTpXLAzwR4x+T/P/u++/UbX3ungxzgfKS146XVaYuUsKs9/0cPs//9M/+Cv//8vg9q0b7g//r//FOedcshhWnw/Pj6r280f3q/bPfvwXVfvnH/24an/1xYOqnaZ4aArVh7GG03U76v+tvvpzb0vzot/RefC3CNcoX+QWtYdMBU6rqzzbwMu3CA92fNScIxHWHvjwNMrz+1FH1xVfwzk3q1ZvS3VXb0fzNW7rhfSHv/8frW0u+p7n2s1lXxdO99NsMv8p3tqozzY6ephlZc0HujZrBzyInYwVMxnWyNjXXOQfIGsPNeW84wsCPiTlqJ1zPKAP55qjfLhlnRRwngWKgQx5CmnXtXEM62s/1O/2mdfLmvmXD565dWH/5k33P/6L/8M559wc6/Tg62+qdvH1J1X75//3/6Yvnz+tmrMzjUmeoW7jS0bEOSoF9/BYNcTxUNcwQW084wvwakT1Ow3EUIg/JuS1WlHgi1PW3Rn/6IGXpXGtLtI9bW5qXnavbVTtG2+9pfbN96v2d37/P6ja/8V//J+sbS7eunXT/cH/+c+dc84VTtddYE4EiPogVz9/8vHPq/Z//d/8t1X7M6zzWc44FyL0b7Oh393eVl98+13VL3/nww91THuZA05PVUelieYWX7qn/MMo1tHnp4qdh8+fV+1HzzRHnp+gRp3xj044f+2PcJf+5RvHLK/hCX7/VRH4njtoL8eL60a7pX6N+LyT4g/6iM9Fof6Zos7P+Nc6nIcvuQpP8ZJ7uoZFevEfa8Myz241kO98xcrpGLU/1k6+F2B7nmr8i0yfdyPdX7+NP1Z4GDfeH18q4RD+sZVV0dfDxQvNxZd6ieM551bX3W2qKMnxF6qAawYivuCF8i03vkv2Cyci/1o7LzQYc7ytzRd8+6mBaXSWD44ZfoeLHAd/NtUxTST3Ju716JkeUkIsbF2kkailJBrzL+b8yxVHEddQ++tqeZ0v8MecF4bnnKvWb0y4BC+zEryUSRmEGFz+xX020YuAbIHrJ5sq44uqi4OcL/1C/vWrLGIivEBL8aYuwecLXMvDIyXQ88fbVfvglh5EwkiFboZ4jfoqoj280KixOZh05oxL9AeuZ52Im013593lQhyhQCkSPbSOB3oReXZ2WLWbKOBaLRWlAWLeY9ji+A6K2AgvPfkXjwCfhxFexpRPAx7GK5szoes3ZzUKj84Rx3jRg9+MMLd2NvWAMIp1T0mmGI/wu/4QSXqOYhzxGJWLwBqnovM9zzWby+Tvo4/ffedu1f4H/+A/rNpv3MZDUIiXqCh0A+SkrS29TG6AOdPGOKcz3e/R00dVezxWn2xt6yXNRnd5/us39NB249btqv1WobmVLnQODy+aPLw46vU0z1p9xdawrZf4CxRRPl7EzJED3n1HBepkonUhQYHkeyz11ofA81y3HMcchWjDV4xtddX/TbxEy3BvC7zEmWI9yz2dZ45+9JE7kwxFElhUZB1meBj0y/mV+XhBhIeFHEyJdKRrfP5E61//7sXxWGerXsx0LYp1zqRXR16kbrpY3ttkoHt8+KVeeP/iJz+t2v/2hz+p2vfua94kqeJzNFIc+r7Wgd0dvSwI8YZktlCfnByL6ePnGotuV3N3Ol6eM09R++BFdWOo3+z1VZOQORshP06w7mc4po0/0tUTIOY32s2WHodnM51nkeg++tuvT8m/qi8aeIDzHYt81Gpg87H2SlAvhqjhCh/xjHRC9gM7aYF5XGPO8HrLF7MhXrJmlzzo5JjPKepYDxfD6+IDArNfSOY46xj+sZUv/pF3a0zm6ph1zmfPrV4uNvAibnDv06r91R/9YdWen+vFft8pn7Xxx9T5QnMhBAslbmteDPHAzT/4xOi4BeZFiHbVJXhYDRBP/Ks960ZmTbJi+XxQYw7VWO+4XIzz5FT9MZ2qfXaoP9JM7mrd3+jhj85rhefqUVd+ihjjw02C/vr5x3pJd3yoF+lN1KVNxHALxIAuWTZgMu/uqC68u7dTtd+6cb1qb3WW8fDmdR2b4SGeYxTg9+eo/4/O1Of3t5Xr7/X0rPHwue7pCC90hhP91hjPZDM+vzqhqPXv+tdU39MfC1jLk23P6+EV4P2Im6AmmWb8LmMbbJlaiGCeMc9eQgZYPZdHEeeTDuWzCv+4GaIdB7UJW2GGScdrTFMwcQL+LtuXsRwvY/G8GGxPHIPBYDAYDAaDwWAwGAyGKwB7iWMwGAwGg8FgMBgMBoPBcAXwUnKqMAjcbr+kh4Eqn8xFn41AJcqw+RjlTDUp0SW7WVJvHDZFQ2tD2pKBwrYA5W0GrXBRSju8MemglHtAy4ZrSXCNfWz8NZ+K5jwZi/J/jr0gFpAp3XhDdM0G9g2pbdybk0b26xvkvcjmeC+MonBeSfGdDHQv3Dskgh6QG0xPZxjPSzaM5dj6+cW0MoRIjVpJqqIPkt5Kh+9DhkGdeIq+hJLOjSGrOLv3jT5/ImlRry+ZVWdPEpFGWzHnNxA7pLNysyxQ2mfHkjQNn4nCul54LivpnPlMcXj2+JuqPR9JHx6mGt8ANMNOJ8bnik9uPhZx7yn2NefrghKK2iYKup5SWpaBnr7AXOXmn9wEk3u0zWbYwwc/M0P/+9CCpZBokgofQN/bBOU2Rn+MJurXk6PlOKb4nVeF53uuUcpwrh+I3vsPIaH68IP3dG3YS8O/ZCPLFnJlBFpxF7Rx7kk1mGuO7G1JNrXV1L4WXgqaf7rs9C72ROuCjh0gt3rIEVwjJqB4e9CS7/bVBxvIuXlNhgDJyQAU+ZauIc8/qNqLGfb8mXKD+vXB9z3XK/fc8EGxbsf67a225so29jyKIa1KofFfIO9OpmhP1KdzyG/GU313OGbu1G/NIL+YJys5le6jB2nP6QS/iYNm2NB3NFbsbG0q1pi7azvKAjVpFanFL7AnTvX5GpfFxXzm7n35S+ecc5/9UhKqn/yFZFP3v9DeTAlqj2Yk6qi+sFAAACAASURBVP0A+4FNkB8LSoXH8ws/9yGnc9h3xMsV53kGiVA510htd045HPvX18YkrcUBNmVm7UHZjsOJCsrFuPeZzrm9hb3otiQVuDbWMbsz7gayPnieV0nYoSz9S1R57uWEtQX7TTFuKf+OsJ8VZVncHJUyCNL4uRfZAuPulRIBSi65IXttM1duioRzz6lQZ07B+hcUpPBfvNE26zGPizdyU8FNArFf1/pQVNcxP9I+Io9++OdVe/KN9kbZwx4wfZ9yb937BHX+HP1wdq5abYHagpu2xyhYG6xd+ehSDrTPvTn8i2uiBSQh3IuSmTKqSdawjmJMoKJ3PpJhwPS7wL4tmdbdJ59+XLV/iP2c1o2inCOMJa8uIqtaA6wnH/3sF1U7SzQuNyFPeuea8u7NfdUubdQ9lLF1OpJu3642XHbu1rZqh52tZd1ToF7m/lRRePHYpYk6/Tr23mH71o5qqoeHega590B7+D2B5O0YMsEzPMtMkL+5591KmrTW7Tc8r9obK69JibA9BuKZEj9KwqfonwVitSYrvWSD55oRBzRafE6lKUBczhfuU5NisoxRHyWUVvG9AH6zjee/zKOGirXKJe80amqxi/cENDmVwWAwGAwGg8FgMBgMBsP/D2AvcQwGg8FgMBgMBoPBYDAYrgBezp3Kcy4u/QgTOKLkoLvVpBRw0phPSKGnvxZs+CDbaIDymo7gGDMFFQsSqsVING/uPp+ly2ubji62EgshIaGtJneBD0htBOGJUiw6MY0HomjOYO3c3+Au8Bfv9E25xsotYZ1yqiIvXFLugD46V7826MYF6cUZrfYw5j4kYx5p43AP41WTHkrXMh+8udru/JQqrWQwwcX0+oiUNVAcGzg+9RSLw2PRF0dHojXehatYXqPC6vwwnHE56dq13fFFrZ4Hr4Nu7FxRZC6dL2Pr9IHo/4OnX1btKNec6MGpo9mFNWwTEqoEUrgCNpygmScTxXbk63M4KNcsSwO6jJURMcfY0nqeDhvcdb+B/kxBhc5wT3QWywtaa4Fy6dPmEhTGpgY1iihBUt+cngzLe1gffN9z7c7y937vb/9O9fnvfu+3qnYbriDcMD9DnMfIYe0mnPEwtpFPGarmcSdU37Z25NLggzJfpJyvpZuWdwkllrkdndWC3aNfqH0+V4zmoOj2epJW3bwBq0jIRToDyd0SxMXWtr47mej8n376uXsd8LzCxfEyjlvg2+9uKJau76ifN7uI7doKDBkr1p8FpIqLhe5/BjehKfQUUzgC5YViPoE95ryc6wv0+RTz/2igPD7x1P8J5kcQUGYDmjnyeFFbBS5p1z4GvRlj+jLW438dnJ+eun/5v/7vzjnnfvoL2YQ/fCSZdAtysy3YfjcC5hvSxtWH3SbtxtWfHbgDdiCF7MEdsQV7cIe6KC5tXhuwz6mtrZh/nP+UjSRnyufnsFM/gszkdKS4GE910gmksI2mxmqjpznXjHXOO4ear2+9pfY64XlyJ2Ft0aBdNsJngVzo0EfsPLqZNmONEeVajHk6qDQ62AoAst1pInlEUTq3vH1TduxT5K2zoeq0uKW4OIH85Axy+JS1JWJninxReKy7afkMWQ7rHsipYMDnJuUczWtygldEnrlsuJx3n/2ZJFTPP/2sam9j/d7E3GrQGQy19Bjyx/PxDMeghsG8bEIqkdAIHPmpiWtYORUFHrcHqFn1Vs0Ma2FtDiFGWa9R4nYC59MJnZJQL7HiZP5NIOFL55p/h/e/dK8Lq98Panmd7kS0DVIc9nqSIe1t6rnpwzckm/r935JN+rtvvlm128ijlOh7lDpDWtXfkMwpLsfG9yBbrLkqXuKyHEC2f4lciJbkHp+ToHttoD86fB5GsjnGs26AZDZ/Dc+LeVG4+UoWxecsHIOywc2RK2f4H6zPam5WzDG1Np4XKf3ERfCZMvT43Lc8poOHkjby9gRum2NI1fMALozBxZbhLWznkheXSIJrru+Q5V5SttTG669R2xgTx2AwGAwGg8FgMBgMBoPhCsBe4hgMBoPBYDAYDAaDwWAwXAG8lJyqyHM3ny1pmykoYKOBHAh80IxnU1H2JtgBPSTdCC5UASQ9UQtUMlCoSC1dwC1pBqeoDPTmqHROWYAeSQlVDOpdqy2K3XRGRwhQ30DbmtMpBxTaNiisi6lorty6OwKlktIIUsXD8pxrlVMVzqUlzS1B37f7kDjAlecU0jB/IR5tCBlMmNLRAH0FfpwPa52oQYcNvkcE3ZD05PL+M8ptQGskk5eUvBByqtDTdQUFY1d0+cOn96v2dva2zgn5BymydAeoOTyABuk1X4+cKlvM3PnDpYxq/FyuKcFC8r1mA44ccGOaY7zoslKAwp1Dwtjz1F9v9DW33t6VdGenCzkeYrsgRbKks4KF6mZwuRvB1WMBmWUAvRwMTtwJcsohpDUncNZZBKKwex05kYWQDHqIjYKOenBQaZVdScnfq6LZaLh3337LOefc7/7Ob1efb/Xp9kQ6JqVpGs+aJBS5j5Ioj7JVyKMCkK9rStickhz+7qoNuSO6JK858oBuCmcwurQEuF7GRRAoL/f7ur9rkO24WE4OGZ3N0B/f+96HVXtGu561InOZW8Zf3IQcD3Oi0dT9x9BQ+R4p1uhn9GMYo+8Qq7EPmUeo9kablF8kxxodepmDwX52C7hJ3NnHGtZQPDb371btQaL7uP/guc4NnWlttlyqrPrN6xuPWK0Z3l/Ly+FiLKZz99Uvl443oxNIHBpyQ8mgpT2DDCdLlDcXyB895N+dnvLNwSbdS0Tl3+7rt3o91SLtvr7bgmtiVOZ0ytDz2rqIGMLCmMDtyIv1O4mveB2nOv4JJNVPjlXPjBP0P6Rm4ZnycstXfzw61Px7cqh1at1Y1QYB8gxjhfL1vOYSAhc21HYNyObpSMXiuYX6r9VRDtiM1ae3bsr98vFzSbojbzmm370rx5wnT/T/jzDndw8kJ6Es6N5juTgtWENCanQMh5vRSO0YcqomarMAMbOAu2xC57LymHXOxWQ2c88++dQ559yv/vRP9flUcRV0IVODxDOHzP90phg7x3hyDd/f0lwcDhGTyMuUUxTQinvu16XOdAArIFWNKG3GtgrPjrWG9Vu6jz3IKT0IUB481X0MIKWpSXjwrJMiplkzBMjMXgp93GsDrrVWQ0GeBlepN29rLhzD1elbtyQ5fOv6XtXe24A8qqv+jWOds8DcDTAvA/zuqnb3IWHL2Lc151XkVzihNVHTTOEO125rTe134KgGSe2iC4c0rIus32O4u54gBwzL+jlY31R0ReHcSp1dfw6F2xqeJ+YpJVQXx2eBOcLHP+abBh3BMP9ifN4K2OcF2sv/bkIRt9PTPyaQsw8guRzBeTDFNgxhTQqIbQzwvqKWIxA7tfILcr66o+SrwZg4BoPBYDAYDAaDwWAwGAxXAPYSx2AwGAwGg8FgMBgMBoPhCuCl5FTOk/vBZEbZAXZMz0TVTUAtdtgFPgFtOwLNyofDTwi6USMUbSkDVX50JhlXjt35D4eSALVLp5IE0gKol2oSqhZ2LCfPaziCkwI4/8MzSXH4NqzbEy06gowoQZ9FcNwhjZeUNX+NMiqd3zm/pPM3e6Lxzea6tuNDOTbNR6KY+rj+GDx8uo1F2EU9AE3XBxXdC+CCBJpgzbCEMpySHxiinxJILzK6WtU2+gb1DRS3BiRfs1yx++Drj6v25v07VfvO+9/WOeFwRHCkFpDf5by/NSJL5u788ZL+38wU+wF2ZGfsgfHoJgvd8+lDObG0x5pPH+6LYvqdu6Jwv39T9OMbG5C8tBDPgeaoF0FaVboP+KA/U0KXwwGDhNusIPUX93Gmefn8kejkXxzJEeXTE93TZ0fKC4PmVtXubKrtw4lnRplgmP2lq311tNtt99vf/65zzrk37tyqPg+Dy2KGTgv8FM4r1PiBzp2D1uuhndOxhDKLmkTxAskj5FE+qbKUU2E8eY4w1PjHNUcm9T3StYtAH96A1GyG+xiAVuxjjl4/uFG133tHbhZrhedcUMZHFCDPQEnZgMsY3REpW6tJj2oSNjol4LvgTdNNjzJZxoBXo7GXtHFo4SJwf33EYDvS+bb6upabPfXtZKjYOT7ROpG7i+WHLyRKvGz5W785lfP90LVLuWX2TLLaHBTrMQqHMziEkGK9AancLqRP+5BH3IA84GBbEs9OTUKlOO9AftGC29HKVSgATTvF2pOg5nJ0Rgk0Vn0PtRXac8ipJmmAtmqe0ZHWncEEOQW5g7T4c8hVDk9ej1Occ5Db1VxleATdYygzUy6cTdVHPUjuI+TaNiRUG5Ah9VBVv3MgCdXt23L/izNJg1Zr59s7WlsjSIG6kS7+zh04WM01L/vIBUPIptobqkWHiIeHWC9rWw2gZmjUJP8a1AHr/fKr/hpL1elw6H72r/+Nc865Z9/IOSmcaf3e7kAeAfe+4QAxSdcfuMr0kH+bWGobTX3egpPftFZfQp7EoCqfCzy4kdK9aP9gV59DNlUMJKe61lecXd9VLPC5IYDD2RndprBGnEEGPuXzBHI6JWXBa/xT/iouanIa1DEFri+ZaezOnj6q2te66q/bW8qRG5AktdGn3KrCw1gHcBzyI7ZRg1RSXUivcKyj2yzr0jm2zcACRQlV4TR2jB3K7rpYM8ZwIruGOdd9ruez4IlkzCtn4/W6Uzk3KyVS3PqCTqJzSJLqbmOIPZyT8cZnxCZqyh7qqA1IdbfRn/sbGv9tSNdXUsEM9WEDTrp3dxUrCdzknk10H3O8u0gwj3PUSx4dJ5E3M2wRUXPSZLzU1qaLXZlfFMbEMRgMBoPBYDAYDAaDwWC4ArCXOAaDwWAwGAwGg8FgMBgMVwAv505VFG5RUhRTOBVxN24Pnwd0mAHld7oQ9SwEVbW29zV35gYNsBWK2tYBhWkIShLlXecnS2lFBAr/FFTZrKNjkwlkKfidOWQGi5osQfc6AoU1JM12U9TpPKXL1cWuM5R6ZStpQrE+/rjn+y4sKWldX/S+J9+IQp7CbayAA1A2g3sRdszPyaUlnRQUT4/OU7yeArFDpwi2y93MA54Du5GD2ecyfO7gJAB2uGtQqgGZVXImmuJnP/pB1d4/0E757U3tiE/tFiVlKWjLpAuuE0VeuHy6jLmwATo0dtovQo3FAO5Nz4+e6vpA2/7WgWj73z9QbNzdhjsQaIsdSKiCpmjbBR2hAtBcS1pqI9b/j+CsQvplBj1PVmj+OdAcY6d+jjKds4tr2e3onFuHOs9HT59U7VEK+UdbdHWHnOF5y+8Wa3ThaDUb7oNvvbO85rZ+i24zdUch5Am6TYEaTQqpQ57L4SYXgB7qpZRcXUwb9yAJvFAeU/uI0lDkONJQkR8bMWIoIH2fUhC4DWI+tbF2gFnuhmPddxMyplvXMbZrhO+cW6kYPUjIMtDg/T5iPqBjBvo/03pCmUdeRGjDJQbrTwoZXQ4tGt0RGD9p6Rw2hy515VronHMZ8nLotEYWEzgPbUAusC36/8kZZNQE8yUp35d8XqcZ8zwXn/5V4Eeh6+8tpS/efa2FrCWSVH0ynEJCjD+FHUC+st1RexPU/w5cLVpod+CY1+mrPzsbqiFCUPtXdVHgQzaLdShEPGWYIIGP8cQ497rq751NzaEJ6p8ppBoD0P3TjPUMJASsZ0CXH8wxv9eM1W/WJLkorDJMCrrNTCG/Yc3ZQH0bwlklxnd7kNEdQBbz7h1JqLYxR0aDnaq9s7GU8+5uav3NckmYt3NJ7m5AdruAnKoJScijx1rb9uBm5VAbXe8qHz0+VW1wCJfXEIG911UMdifqp5UrZLBGCcdsPHKf/WjpSjU4kuyrBRn+CHH4YC5JyQJShm5bc6WxUF91IPFu0dkNt9CEdGTegkQY10mJsl/GVwo5cbehPv7gLY3bo+e63j042L25L1n3jWuSX53CHS4dS07UwFyfwxFwksPBF3HfRj3o14ThkN+uGVXdj77NKadCh47OJdU8fyZ3tj2M43YLcj88o0W4N4dnzYLunqgvKbPyaJFUtlk7u5byeNCAqynrsSG21kD9zxo5Rt0TsL5CPmrGuvYnTxX7oynOCcfbXlfxcDpYPp+tcxuOwhVuXtaLlF7nkGzXtjuo3SMdphzaOr4Dh6kdSCRvbmru3NrWPd7epZujxqIZsj+X5z851XPsyanmXAwnZqgs3Y2R1svnA62Xj4a6xuOam6fazYjbo1zW/3TlgjQNOcPkVAaDwWAwGAwGg8FgMBgMf0NhL3EMBoPBYDAYDAaDwWAwGK4AXk5OleduUXKI2nBX6nC3dVDIB6AhkYZLGnwPFOIQu4o3QUML3cV0+h4oytO5KFebkFwMS8pjCJoSqV2kvC+gy+Eu/dw9fAanqgZoe8OMtHRxro4O5ZTT3ZIUp7sNmiuodRl3wi6pkOs04yi8wuXh8oxz0IdHJ9olPx+KjulmcOZaSE5VgJpbYPfwHPKknFz+GmUeVEbSCi+TU1X9ALcb/j5deODSEoA+SdesmJR0fN7GTuXHX39dtR9++VXVfve3RXN1Bd6B4hoKSBTiS52GXg2eUx8lkMSkPuMQ1PehxnEAeu77e5pDb2ypvdnFzv+QvES+6P9RoDnnY+d952Huwk0ubi3bUVP5IgU9PUdcBJ76LaILA2iwrgEnvA6kK6Dqb07FefzOLs4J2ucfP1R/nKSIjbbo7b6/PD8dl14VYRS6g5I2XVOV4dooA0iRG3y67eGaUrj0Bci5AajXNSovaJ0Bcrpj3OKYlcORh/f/lHZR1+QVcGmDPCoHnTbGjdO1IEdMe5BhBHCeaoAWPw91/h4kdIOhctbWBmJ0nSiKimocUtYLt5sUba9LxxA4XyBfFrjnBRwfZ4nGd4F1LscxpOdmpECDcr8apgkkdFnCv+lATjCE/BnyBr8jeUgXrikhFtgU5+caUNRiEIdcppUqLv3HWhAGkdvaWc7FuA3XRlCsE2hyQ/RPjDWH9UkIF75mrDzYhOS12YIMtC+qeH9LEpoGHDQDzMvVPKZ7WUQKO+bfAo6EmQ83FjgTJZHutdumFAwU9q7m08GG4iKDs0xS6BrnheZlCtnGLHt9Eo7VHeU15zfEOdqLFO58CCs64jnMJ0rifci1O6hd9yCL2t7Q2DHX8fxbO0tpVRcSumlOZxW412xBcgVFWoF1lDLLg33VKx2FYG0rAhdr/ZufKq5P4P7aaunLe1uSgjXicruCe8oLr4osTdz58wdVe4Uc7mmnJ6pRJ74k4RtdrGFzDWgPMpheT/0co0ZcTBXbcVPzMkasLljnM6eXCdVPNc8++FvvVe1b1+VS9vjxN1V7DzLbt+/I7Y/xsVjonlpwvqX7XAEprDeBE2RBSQtrbSFJXp+0UX6ekDW5i593Dp9KQuWnWs+ubeue26jdQ49uW2p7Ptv+hZ/7tbocjmNlfZlDClc0UOe2FDseHaZQZ7pAcRQEiBGsi72evtuAbHGzpziNIQUfQOY4ONe8PMccnZXP5vkat98onORSNdlPcfFzFtdyyqYaaG82NYZ3tpSHbu9pnO/Ane0A0qpt1BlNSJEDFI8rGXYHUsV+V+M9myuH7+K5aN6Fw6aWX9c8Vp01faJjxpBoJlwXsO74dOhi/YNj+Jwc/jVs/oyJYzAYDAaDwWAwGAwGg8FwBWAvcQwGg8FgMBgMBoPBYDAYrgBeSk7l+Z6LSypUoyZ3AJUPcpr2RKcvQHfqYkftCJT4DiiMrZprFZ2qQGEFpWsD17AAbS4u3ZXmkFhEpNhBErMAPcrzRI+qyXXoMEUHA9D8ZqCzZok+f/jgQdXevy7Ho4KyAMgRFuUO4MUa6XGucG6lGhqfi4a6oDNXAjegGk0f7ikYhxx07iyjMxMpbtgxPtf95ik+dxfT8vySru5DWkLSWUEZAtq8FlIBC1C8Q8iyWrjeM9AXH3z+WdV+4/3vVO0I1NaU1OYZ6HHYTX+9KFxYxmiKe+a8TMaQNg5EP+Yc7Tculie20eYcBSuyNi/SgFRLOLdgpFb0Vzo4sJ3niDX8js/fAW0/m8MRDlT9CFvONyH5WLjzqt0f6we2QJ09Qj/NMlGjg5Kmvc6p6Huea5ZOAyECnnKnOWj1BRxgIigVc7iFFHCSCXJSPDGhIOHxIPnwIfPwkM/I8FzRaNkPOQcL4+lAlc6YOyDz8CEVcLWcgjmEmOZPhQGkepHOCdMKl0BOVATqp7Vj1S+g01MxMkm0njVxDB02MuTaJNEx04VyUTLDHJkxv0G6hpyWg8JLaV6+crPKQD2vOaHRPUHfGwzkwhHA8SHsv1m1W1zPsJbQtYiJpIDjFtdjj1JLd/E9rQtB4LvN0rFne0M548Fz3S9p6s2aY6bOEyGG6TTSBTW+CXeRCLVQsyepTBPyjybkrB7iZeW2EmS/TiV3zrmATnF0Z9LluiSGDBW0/iDWfbRBf+/Guq5+Ay5FARysINNeIB8s6IS3PlVqDUUhiQbCx4Wo+RKsJwmkz5TY0mGUtUOC3ivg2tfG+G5DhtuCwyHK0ppbZ6uULvtwKEyeaE5QttWAbCuBW1O3rVy4ASl0p6e1bbevYxaQ47ZPFONtSJ0/G8KBNlat+P33JdG6VizvteYy+YooiqIaF4/rHPMQXOO2IUn0Frqv1qbqswgusQXWvONzScnoNsY5GqImn0Gemy70+UqqdPO6tkl4/wPJqQbcrgC2Nm9ck3vZtS316xG2bfCaXbTpyAkpoKf516BTDtbLALmJUjDfhwTNnbl1YrWOkC3A9E03sef371Xttq/73G1r7IJQMZzjmYJJrV7r4PkC45vzGRCx65f5NaWrLGT+DrnWXeIqVHBto0acjo+5cmrQ4GO42i3M4w2uDQ71EGIpKdb/vFgUnstKd1Af21lEzGXcwgJj28Y/9lu63zf3dS+3djV39yEVpWyKblx0IYswtnR7WglquT1AgP+/wMNa2tI56Dzdp1Mrcu7JWLnyqyPUt5Ba81IolYop80PAzjlJ3cvnUWPiGAwGg8FgMBgMBoPBYDBcAdhLHIPBYDAYDAaDwWAwGAyGK4CXklM5z3de6TZD+VAESpebiw7UofNCUzQ4Hw4zEXbJb0NOFVxClQpBcwvQLkjnjCkXWJ5/jJ3nk6kofDDzcTOn+5hQUkTXAlzLDNT2Ftwnppe4Zxwfi7r59MmTqr2xJwpmhr5ctddKj8sLNx8vqajDU8lLctAaucO+BxmE58iBhsMUPvVA0y3ojAIXjKwmocB3L3GqWkkVUu4GD5paCpptAurrHHKqBSQcGeh/PqiMESh/Icb2CG4CgyON2zZc2aZT9dl4Kop6J365KfbiKCqadwAaPB2pZnBeowMBY7gJen4DcpoQkpuCDkkpHEYQMyFcg4LwYleilRHIYsGxgxQuv0QKgDHN4MhTwAUuyHlPoKXTZSSE7CiQLCuG80YTO9efjzU/ilLqkmdr1AF4nvNW3OKa0dnFDmMx+jjkmCBn+HQmwhypOTYgV3rIxQFyGKWidF5bSatyTk9w3imzdJRTIs/mycXSDqZNyj+Y/gpwsUlVrbn2QP9F6W62Ti3cX8LqFwu6cyHNpQvF2/Bc1PqiJco0r7smi0GcOzp+YZ4V+Lz2pxk6BUHyOS2lLSHmTQHaeOqRToxcEKk/p5AuNCCF9CPOf8glayoozHvGD+7bh7SKjkLFX/rvOhD4get3l7T9XThHhsGjqp1MNM8CzJs29FQxnBrpiOgjD1ESFUQXt4uanhjfrbWXHVpTFSD+uOYWNU0kXRtVf8UR28qhMWq0GDkiCilnVDvD2pniGhY1ExwG6TqdqopKdhNGF0u1KStkmUHHGraLmlRCx1Mu3u6oj/o90fhjjjtyYxv91Vq1Ee+jc8l6d/ZkldKsaR41byi7bTX/v/beq0mSLL/yuy5Di9SlRVeL6QZmMLOYxRp2aTQajS/8gqTxA/AzLF+4RmKN5JpBLIAZADMtq7t0pc6QrvkQnnF+Pp0JdHVH2VrC/udl7kRHRbhf7ZHnd48+ZzBWO3aBFI1h/x+3lQq0i9eJM379UulTRLeGw9X8VW44Ma6q5yUmumRsN9RrgiqJR7rHJfr8l2+1b8sSYINAK4YYu9t9oMXE8vFcEBNnq7H5X/5CuP0WruWr3/1uXfYxth88vK/vwTjOsWBeIHFygT01qH23xBrtMI7JH1+m0jrnXAW0px0xtfGV26T8eoAxzYi4/WKmfn6C5MMu0MJeH9fHFCIg/KVDGwFL5vNFRVSX0yH2Q0U9RquQ8y/vCOssEXGMP/ZZh3WC6ZBVyOReoOM4rqOD9KWDXc0BD+8qxWyKRXXxdlV/YaBE5J8qz1XOq9lXz7tm3sT7h0ye2hUe9cGO9jl3x5oft4doZ9wv0/7aWH/CsPHAuC5yjl6nEqLPRRxcPtdl4LEB6h57mP2hPudOX5jjy1M8T1yDeJc8agbzP7fJMY8RYaLzD5Q5cUwmk8lkMplMJpPJZDKZboDsRxyTyWQymUwmk8lkMplMphugd0un8jzn15hFRm8sko3CXBazHhEquISIUxGJCmn5p534GstrDAuTzFrOLZAO1a1Pc6ebeIEUKpAoLoYli+kgcOE10gl8WDFLWE9p4y2Bn3iwdM1nwrv6QyBUCdNHkssPd5tSVZYuqdNskrmuoUqIqahMy2DDMcYKpcU7YAIJToPHvVc+LfwNGEvv52nz9dt9/OaYMyWMqVU8jR/f3zi9nGX0Jw92vjAC/nAqm+fRi6/X5dEt2RoLWCI7Y/XGEPbCTevSwhzjHuYYi0mqPkwMiElIUQNVRL9FsxRoI49JVbD/E53xkKaRw35artEgnthPiyEsj8QwMKcQV6lg1XcZU21wjXqHC2LgYkCoel2k3CEtjbbc48kKrarKzVn/PYe+jXYoaI1GOaQHE3US4j0VE6EabYgvBsIWYs4L8Hp+zWdeYm5hA/1BW9G1CjtrSDSGtmZefubwmgAAIABJREFUb8K6xWn/sLmGwB+9a+y0AdaRDsZfVmwS25A855xf1wFxNqZqRbRMEx8BBhWGso2X8IFXxBN9pnNgDmTiFy28aHi4ktf1VYDFKYFQFmhfv6OUl7B3sC4HXb3uw6rfCa6wNjvnCiJUJW3GwPVw38TfiM59H6z66fJ937VbK1RsZ0s4VQxkyINln6hUB+kZLIfYXJScH4n+cZ+D+yUKSZSMVn2/7l+05hPVKDEuPXa5a2qwqjim8R/wnQFRzAY1QG6BSVBEHvg3w/eFU3mYS6/GE70GS8F7+z6q9of/lmMrwr3tjbTmtxprIeoF+8J2X6iBX3/vHPvWHHP9ABhUgDEaY53t8OgCpGYOhvq3DscVDAa69i1g4Us8EvTw+uGF9hWfv1Qq3ehi9Z6kycr9JFWVlj2fyUCNvo/nBqBpATCM58+VBrvEXqjbV50coG47jc/X1/rA70Efuk5b1/Dppz9zzjn3+PGn69dePPtuXX79RgjtwS3NL52uPuN8ovdcnAvbOD1SYlSOZNc5cHludIh6FlgXJnO8H/uoNubxzau+sEaaJZD1o8N1+RQ4VZ+JR0j584k+cTuEbww4vollcy7i3oT7iMsy5sLmIwrwG5aZSMQ5sgBO5WO9RqKvh89hilIXe52toTDm3S21V/vV63U5qit509mN/rrxrp4TW0Dc9vsaiw+3Nd/c3xJCtYv3dDFeY8y/fKZhsmBjz3fNnL5uQq6buHZsT1zOJDPMKQH2a/1I/2C/hzkcc3TW+H7sqUqi4viNQN/q2qi/4Bos65+TOXFMJpPJZDKZTCaTyWQymW6A7Ecck8lkMplMJpPJZDKZTKYboHeLzikr5+oklOX56fplojidFq3CsMHR7ncN5sJflGi5I15AW3UjKQeJCEUiW2qntp8mmd4LR6TbG8nWSuvvEjhVCkSlB4SkP5QtLAEB8fxMKVRz2KMG2zu6dpx4nyBxJwFOldX3VP6IE6uvk+d5rnVpYeOp+0ikqgomUsGyhlSNECfaB0iyaKBKSGbygbL4DSQC18Y0HSIBtRWOFjee6E4rI+2WYVsWvoCu9UaaFWybQAvCGNbTc9lZz49kJQ7xoYOx7I7BAKfpv6efSatKdsKCaBl4Mib2EF/wgTW0YL1l4hexxYipVajTuKt7jlt6vYHUQZfWwoD9KLg6+aTk+FjyVHwgAjnSdJawogNpSYnr4GNC3N8gBk6FZI+yUDsm9ec0sLwNaJ0AAn4tz65OlYrQVll6sS5zfsphGyfW1mbyH7BBWsU9xzF3NdpR1egDMZ0Kn9FIsiIGCoTVIXGLqQ4psQom63AdiXjtjRgmvU5ra0i0quPehzyvcq3W6vvbWP963attw+0W0xZUDiImVWmMpFPdz3IpBDYO9PkO62VFbAnlpFJdr7FgOs9z9H30NVrSiU35MedLXW+7S4RU/bFhqcc7fCYaXmPZLq9AgDaZh+N5vmu3V/Mck1FGA7XJ8ZkQhwh9jDbwRqofJv8GIUlbP8YC7f4+rNplg0KCLZwJcpfvdVdbzJk2xgTHFHu3yUTr3Gyue81SprAQ/4MNHHNNyEQm7LuqDWLh18nzPBfW60uAe2adc96IuV9gIg3XS9R5hHsYdTWf7G8Jy4mjq8dF0NH7R9gLhvW6xz31cChkYjge6VqwdkaRPi+K9f7OWMhjB2hVifrw26qP8Vh7YDfUvbLvp690bUcz9dnzxWrtSfPNInGXKD6x3oC4n4c9D9r2/FhIEvfqjw6EMPV3lPQz6uoeq4X6ecyUx0Tra4RzIT788PG6/PGHHzrnnDt+LTzom99/pe/EHvnBHWH4xNznU43Fw1d8vkKSVEd9q7u7tS4zoSs9VKpmwiU45bjXvBwFGuublbfGkzjymbj59qWQt1MkiHX6HKNXJ+j5pdrXrzAuAjyPNFKJgMuAvwq4NylW38sUOu6peR8lHp99PA8xTbVksiShL+zrONcwcY70/AB7ift3bq3LhxP1zbO6TaNQdfpTVTnnivpaA9x9BCZpG0jg3TEStfp6fdDGMSgx10u0CdezRgopsWq9pbHPa3DBq9fLBliGvS2fkTDlE/nn9xOPHfbV/1qY51M+muJbmYSYohzzexu/jbh3ljlxTCaTyWQymUwmk8lkMplugOxHHJPJZDKZTCaTyWQymUymG6B3wqnKPHOLw9UJ4slbnSR+dwSUBHb3ijY0eIKLSshQDot3xLQbWFhzpCxktOLDapkuYXnENWf1if8tWLL6sFCynMFCubezq89r67PJ7jBNZYnrOp/LcvX2UPhNG9+V4GT5Oa49QUJBWts4y00m4ngKZMqBTRFfadieYRUPYN/1A6IJspWxfYhhhEwsAu7G8IYWrMKNcLK1txEWZyRyFEgJSwvZRImm5bDcpri9JfsQj7tHCgwTU2gtp2/Og7XOixqeP/e+dPkttIo3E3t0b7R4D4BtdImYEBEA8tFFkkaMFIwWUg1asT6H+EvQSEuprxd29hYwnwhW2RLzQgHvYQbnbwr7cwYrZopEhhT2/xTW1g5wlS2k/1xEqoMEGFmvv3rd97+PMPwUXaY9eehjRIxCIGZEFY9PZbc+RULB9EJWato0BwO14WgLdvKRLNnDIfs/ECYmtdRFpvQxycWhjpczzWuLs8m6fLHQ3HfG+X9L1xhhYmj0JyaMMbWCiXecd4hORFdjfj9Vvu+5bmf1PbvbWguHfeKnmkfZzz30w/lc88Y3L2TL/+3nat/jY7VvxUkS9dXqAunC8B619PnDunP0PNVnVam9UtThMlRfK86A7sWaXxOntlsARc5yIpq6Fq+BTXHOcnj9alzun3vpx8rzKhfVKVldIHG3doSyTIE7ZDPNPW3Y/blUnwK/Oj05Unkg5KNINF5aXcytSCNp+VfX4aWH3GswcdWV5QrI7RxzxOsXStB5+UI2/Itz4ZpcFkkeVLgu4lQF5twGCo7P4dq0US7O6S+TzTDN789hzv3B3MX0OuxdmTZCgrMP5MnH3jVurGmav9vAqcZYU9v1vmeOinjw+NG63NkG8g//fxjre/JM/3aA70mxH8uRMBXi77ejPa0HJZCbLWDhFVjkGdiBwF99flFtcjBq2+SHjU6j60RbLRa6rwro0xBtMr1Qf55OtRZNgIS3sf8E/eG2emrDx/fvrsucG948+8Y559zTbzWe5lj/7twSAlNi7/zqRHPrF9+80DWCQu0NdI137gvD6wx0XUcTzTVHmKeOE7X/Eshbinn5dCpEd6PyNHdwjsqwX59d6P4TtEuGvt3u6P47be1dieUEjf035iKMb6LVjVAiooA12lsFeB7ykbyGtbsCCuS1dL0+kyJxVIZj4jEQ4gLfn2P8MdmYK+Gorzr4xWefrMudGun8j3/7pducPFd4lziVrm2EZLZHe2qfR/uaE7eH2ltEQPgroIX5NWlTjdRaHilA/BztGTDNsV7rmomWaJOQiKa+Mip45gZwdiRUhkiyjVsac/mMGJzekxdX41Ql5vGCON2PeF40J47JZDKZTCaTyWQymUwm0w2Q/YhjMplMJpPJZDKZTCaTyXQD9E44VZYs3asvfuecc26H9nCc2JyDNslgN4t8JtLIBrVMZTk8v5DdbLZUeZ7CEgqLWQH0aA47Ycm0nvp/Bz1ZvhJYuA7PZOfLYfkrYaFlgsgCCMcSJ7zzhPEWbH4F8BvaKxdIlIkXQIBSWdTTdTrV5qyqVVW5vG4kYkglrr+E1c8HnFYivSnFfS1QDxnSU5iYcuoDv3Cwosf6rvFQtuGtsTCPsLbfFcDqcnS0Cayyh4eyrc9nsjIymShB+s8caEcCm3CS0uYHnAf1RFu2T3QQCUrVOwbA/VBVVbVOZOvQSgr7sUdsCXbGbdikiRO2kLZRdfT+BW2LwOuYYFUyqYSec1gR/XpMxUxwQd+eI1kpQ99Z5rDievq8DOMyqdTvUqay8GR7dIIWLJq7Hd3TEcZihbmm2qRdvJbnPBdeIjFEHzAPhQ0ECNcPDO7g9u11eYAxdHGitJnpQvPKZCE85/BYSXr3795bl7e2ZbEPY+A/tQ2UaWceLaNTzcMvn8pafnaqa1kwwQrYyBaSVNrsi3A7L3EfPaazYD0iRunTfuu/n7EY+J4b1IlMY6DFMb26sMkSOZ0gXeKrb1VHv3+qdenlmSogKdRvz+Z6/e1U8+E57r+Fa9ht6xo+PljZ8p/s6jOCSG23RPLbiyOVnx7pus4zpa+0BrJI9weq8wcPH63LWztqX4+Tp7u63MCEiI7VrxMd3YS8et6OA/XPAyB+oBzd25daZ0Jcx/mFkIAK1vi7d5SO0xkIw3h9JLQqxfh+gvIBUzjUvdYJZhXm2zxlSqfmssmpxvmz7zQuJ2fqc4MOsFlfbfj0tVJjLoBeFFgXQ3LRdMXTKt5o5/eTVOU5/GWybFyI3oO5nIkoPjFMppNgbe9hnpmcad/xD/8khOGDW0JuImAWbay7ox0mTq3Gzm5X8+9gqHW5BHqWAcM/PdKRBrMLjd2C+2XgrSW2q2wuD4lHxKj7wAp9cIJzMnX+Jbqw4fa8xHDQPt41/WqGveASe6/ZQnUyn2lc7ra1hyDyH28hMYzpcEB+zy80XubAfzo1Zn734w/Xr/GZ5/CV8Ngvv9MRC6fnQhtbGH8PHu+ty10wsTlSWQs0aKul6+1hLk6O9PkLIGgZ2itDf3lfavYOJljquzn+lsBMv32u/coS+/XdA7V7hD4cFUSxsX/CmlMU3G8hte3yCvFcWmEDEuA5JgiBBeGIiORc/aIAulosNF9wj0ecK0/4rIsk5vJq1JOpl3f2Vv03Cje4z/Gc8+s+N2hpvn9yW2l8n9zTXnGvxyQxPOcjbfT4WGMoR3syqYo4fRfPIjtjfe8QKZJt4EmXpYKpl3y+Da7Gl3IgVItMrx9xT3uiMtPeqmuSrbhv4bMjqqOx1vyYHGpz4phMJpPJZDKZTCaTyWQy3QDZjzgmk8lkMplMJpPJZDKZTDdA7+S7yrPMnR2urG33Hzxcv+7BBpcAg2CUAq2Qy5ksuccXshO/PZTl8AQ2w+NzWZjOYGEtYUsPcQ0dpJYMerXN8basqjNYTJ8fyxZ9hESGIJAtrI20ASYBMRFlGygA0Z0StrkUtsUC1bSYyQK9hBW+zFbf1UiL+omqqsplteWa98LULaJVOXxfS0QDLaay1Xu5bJ09WNy6PJEc6FuZwraPez+bq/59tG2vV1uPYSVdIpFgBkt4BrsraYZWS5bULuy0Iey3hzP1xekEdQObH+1uRGx8/JcmevOe0qk8z4V1mgKt7ETOiD61kLQ0AnITxcDlmCCA/nAOhOViiVP7geIMkKyyuyMUrnNF+lQbFsZkobngzaHs4YensqSWsPb3kSbRw7WHwIsYCBAA5yqRvsO+H8HOOMSp+72l2vSiRg83SnB4lfPqTlpUtGaiXxGlIJqACaTCvYRA1bwWUgNDJsYAE8P9XOJ5zjm3ADbR6QM/qBM/KiBRBebThAgjrtfHXNBBCkgEnM8HilvQb4qBnMK2HCyJnTGdiqmIwCg2Gyy2lu97rteu+zbQs0ZKAezQs7nqdnKucuDr/bf3ZVEej5EshBSaVyeYU4kQ4j0VEhdAKLsXx6vPjIC2hm3gzLCkP32jMfzyBGlffd3TowP1tb2x5hcimg7t0kgFwrUzCdA1UqtoOX4fc2rlynJVFxGu7WBb2EuO+WBxorWKbZtmGkN3bgur2bmj/QfxCA/jPkP56K32JUzkcLCIXyKVxMoSYujAPU5ONFfnqOOwq7byYEmPO9rP3GKC2jffrMvLJTEMXUMjZRT9i1AF59FNg1WX27ISc4hHFBW4O1/3sc/qYb7aHWiOur8j5GbYVbvMFuobz15qH8tkvw4ww/Gtg3U57K0+v3PN3DFF27368tt1+XUDM1G/6/Z0vQe3lYo02BOKQPz06Fx7OQS3uP2R+kaI/U0KDD+rE07LDe5RnXPrLBmuIR6RSs4lRIPI3hZXYxND1M+nn/xsXX70+IN1mc8QPtJ0Bz0mVqp+xlsr/KnX5T4Eexsc53CxK1QqQ/RbDGykA8Q7TfU5i6XmiDdHwhw97AG2gGtGkfoOm6hoNNePgTh+iCrnr8cXcBfO6429C9OjdP9nc80hU6DgX75Qmtd4pHt+ACz8wX09pw6x7w3Cq/cXfrC6nhLHXRDPvkCS8Nm5yhPEiREV7reICGEfUyA5Fwg/93gRcMYg4FoocRkN6r6/ydUx8Co3iFbXdAtpaI/2VJd7fY2JGGtIhmMrTrEWcSM2GGif08O4XCTaR77FkSfPXgtFRAhZI0lvvz4KYNTGPtPD/hedP8N08Xai73z2WuPmDN+/CJk+qjXyBJiVx2kHrcGjYErMv0znbCRV/UCZE8dkMplMJpPJZDKZTCaT6QbIfsQxmUwmk8lkMplMJpPJZLoBeiecKgh8N+yvbEstWJUK2hlhGVqCazie4URqWNImC9msZrDzz3FK99GprMsvXspOVyIhKYKHadDRtX3ywSPnnHMxcJKjuaxSv/3ii3X5zYkQLt/TZwxhm9zaliW1A1s0fW0eviuOVa5KpDkA10pmstMtcU/Ve8CpnKuEGMC5RasqyxUxgInaMF3IYjbswp4dy3IXRLApwh4ZxrK+tUKcvA9r5XQme1pYvyfC6ehTpA1MZ+ofISyIDaqpYZ/UjaMZXB8n3E8WuG+gXXOgELSC+kxBanjF3xNOVen+aGXmV/O097CrMlPAfJ+pZGgvJEK10aZ+yGQpYDkYr5MjoQAeMMPO1srmSCvvbKo+VQDLG8DC7oWyynZ7QDU8jZVZpn+bI1kgI1riITUOyQ5MKGkBywkwp4S1vX3TrVldDkJiUyBKGPRVwNZ7ciTL/tvnL9fll7CbfvlC7dDua8w9vCfM49au8ICtkepqwZQu9O3BeNUWBfoKE96mSMc5QZLK777+Wu9ZAuHBABwO1c6PPn68Lm8f7K7LsdN86iNBzgNyR7yESVCxT8xjc/I93/XrOT9kqmHExAQkzCBNJcS8VALFmZyrfJoikarU/f/mpdro6SuVQ1/jdRzBZt9XXTzYW13DrT3Zg6Ou+sXvXwJzXmq9PM312dFc93R4rDn43r7S0jrALNnHiUexk/v4u1KFMpdAvWdzo7EsSrdYo4BAb4AGtYGndoCwohu6MfCkGOjFSyRynH3zdF2OYOW/Awy1BSyyc6T6D/D61m6d9of6S7FuziZaIy+QgvbdK80Rz96onGA9G2DevgWb+9a2UJDyTPulaIm1EPuHuLFeMFkHPvZNA1V1Z6mA9odISomQpFhgv9qCxb0PLCbG+ncORCZBss52T/U14p4PtzY9Vx/ojTXXtYerdbEKmLCHZLEpU1t1vefA+16fYs27QOLLsdpot6e2uLejtLQxrqXX0bXfA/LV6SCBFnOTew+IauWcu6xZJrdk3J+wy+D1AN3q9pbWjU/vPVqXB0gQXCLt8ukLjYX7+xqLnz25sy6PB0AhiavXaF0DOyvVJr2h7mOBPeHnXwuJevON2u0Ca2qF9eLJQM8f2yNdS4h+3A10T6O2xm6E4y0yIGLe+6OptC8mQsVnRCT2ZkgVLjH3T8C8MB3sNfYoodN6tf+12vFXP9N8+MefKDlsj2hhC8+ydV2kZ/p3h6+eq4x91xGSCF9h/IVIGbv34MG6zDG0g7WBRwRkwGFz1gf6eyPjj6mmaxRnc/Np4Jwb1d3mACnUu0BJ2+hXXONDzP3jIZ4hGsiVyq8P1bYTHJeRF8B2+cwa69/Osc97e7ZaLz08nw9R9xnWnrdIxP78jeb2wzONvxZwZvxE4ZJrksQapDifC9EsRKtSoLPlj5hPzYljMplMJpPJZDKZTCaTyXQD9E5OnDgM3b36L7dxW78kFvhLEHPuJ/ilcjrXL1sp/qI8wy+xRzi0+AUO9nv7Vn+JShb6VbqNg8C8DlwuOJz0Vn244N2H+svuEn+1xR88nOfpr4YVnCOnOHy3DPQL7XbAv7rq/UO4S7qh6ukMLpsMfyXKcOhvikNCLy0LzYNyf5qqonJl7fyh86JCGwY86At/berAWRPCVTTHIcdffv3lunyOQ047kdrq3q7+yrG3p78Cbe/qkCsPrglX17MfqS55OGOGX38nE/Wh717qrxxz9JsIfylrRTg0F+XeUL8ip+jTKZxjCQ4EjFr4izN+gfbe0585yiJ3k8u/7PX115Z2F2MCf8EY4y8ye0P91XB/oDaNcMjz0Rsc5lXi4Gg41O7c0l9lx20c4A3HVoWxPqwP98tSDbqTQ41t/tkyw1g5gevqbKHx0W3pOweRXoe5yBXoyzx0cIq/RJU8cDPFX0P514/6L0kbPdfYec6v//qKM03Xrp9VWa8vcKjva8yPf/1f/25d/uo7/dXoFH+pGow15gIcoLlA385w8PqjuzoQs8KhcINy1b88HBq6wF+nDzEmfvu5XI6/g+MxwKGhIQ4Znz/7al0+STSOfx78ybp8q6XrKnBwJf9qRSdOWXH8bfoI1ZV8z3PdywOf+W0+DzXUuOnCrZMkcJDO8Zdyp/aKJ2rHUUd/QZzk6s/ZQn8hDB0O/M41Bz+6q78Q/vs/Xc0HjzDnFgvNEZOp6vOLgcZKEeg9Fdx6rtR3zvBXqRB/rQ7x5/OA7kFsQ7gOsTIDHLR+OTw2ORbLsnKLyWp8TeF2OJ2r7i/wV9ICB022O2qHCAeiHsEV8+w1nMhYO5dwJaeZPnN3qPbvYk0L8Pmd2l2HPw66iykP59e/uzjVtXz3UtfyD891mDydQ95rzP87WqPv35a7YYwDLc8QRNHjX0jxV+4sUZ+iD0fH2P50ea5a960Sa2+EPaHv4zBV/NsuHMIp/ssLHGDqw9HjFZr39nZwR3CCj+GimC00v87OtKb1d1f3H+DQzEaV4C/Br+eq598cyYH5+Qu1ew7HYV6id8D1+ulYTpz/6c//bF1+svtkXd460Hu2d7RneMXD2Lur19OFPvunqqoqV6SrCgixVjUcCDjVlG14B/PTJ7fkCFwUGruvcSB8Umn/Meqr/sOhPmf/QnXYxtrFBIVL10GFi0nR9ks4go9natzTUp/3OVwmhxPVcQaX8ctD9ZvP7un+hnA6eHi26GK+6GIMtEP19WzKNRIPRBtQVU/inL9zzAMTzJEL7D+Wb7WevXyrvj1DPT7+0z/V58Ct9gzPU9FbBLC0dCj7p572EXfglqlql0iBPU/LQx/MVJ/PDjUWPz9D0ArGnP9U157M1Nce7mod/5OHOnx5f6A+2N+GSxbzToCFMUQ52LRN3DkXeL4b189u+3Bk9ujOx3zjY8PaaPMUrsFDtcnzN+rPh3AQpngWeHxfjsDdrr4rLtV3RtjbX4a4xAjN4Lo8xzx4iFCcoxO481vaK43gPv3yCznKX2BNXTJABXbAsgIZgkPMG4AG5ozWj3heNCeOyWQymUwmk8lkMplMJtMNkP2IYzKZTCaTyWQymUwmk8l0A/SOBxsHblQfPhnC4snDjAKYHmmNXgCrODuVhWkBu3Kay07XwkFE+/s6fDMCRkP72HAoe+AOkJL7o5X9d6+j/z7dkpXt3i1ZRtsXsjDyQOIUNr8KeEZewB6MQylbQx6ipyr24JGdTPVdPAiXOfFeuXmcqkiX7uTp56vPXcoOxtOYSrShj9e7XdVJAttlleDQ3LEsgO2B6rzbVnlvWxb+4RDo2ZYs5AUOvErK1eeXmfpEFeAgwW21d38su3fYkQ386EQWvhyoTgqLPI1sIxz+m6OPzk5kifyb//x/r8u//O//x3V5cFs218ZJwxtUlufu8HB1yHcU6uC93kBt1Dg0Fod89dvqnz0cfNrCb7r7B7Kb+rHaNO6rTjttYIkXOkxuNlddzy7Uxy4OV9bSdA67aaZa7wP5OS81PoY9XO9Abd2DPbjEd15MZHNtA/uMvasxwYu5rLAe8JsS47usLbKbHIvOab7McUg0D1r2g6vH4nCs/r+Lg3/PcZhwD1jLYKg57/aB7Kl94EwhvjeOeQgwsaXV2Gkc0oa65CF07Zb6x8Ge5lnW4P5t9bNXb3Ro/bdfCa26c1vXu7ej+3A9XXsGLMnHobMVT958T2eMO1e5yrvigGpHFEDzXwwsdLyj9wSx+mGVAls8keX4W1iRk7bmpeEBDmUHojzEWvRvPtOc9tHD1XywhfGRnOvaf/mB5rAzHrK80Ht6fc0pH3yoOSgay358AXTMr1g3LONg44Btd7XWONUG59Ysz92rkxWi+OJQFvjvXgtbnHPNxrpxb0vzY4Bxc3IiVCkAWnFwW3U1naoP37mtMTLCYbMBDsjuYP7dv3t/9T0vn61fWwI9TRaae/NCbXj7Nton03wxxGHGKQ5C7gNb5TqyAJbUQqBAxHCBme67LMkIvR+0sXLOFfV8xYOxe23dW57gnrFXHPU0Rmdz1V2GQ/D3d+6vyzH63zaQs1/86ufrcgttkDVwYeBX9bgoiSgQ4YBVn+EYj+8Jw8h9oQMLHFCdISwgB5Jx56764PBA+7HRtu5jjL3oHvrGONb4cDWCfuJt8O/BVeXc5doLfJsHpW7jwPQ+4Lxf3MKh/dvaT/zu5bd6/Y7ek+NQ1iHwi4M9PXMkOZ5dphpfWGbWa06M+auBDwL95WHft4GzzrEX2ka/zIFTZbjX4V08uwD/yXHI7gBHBNzHMQYf3Vc//uorzR9/ebo5LG6l1T2V2N/w0O4EYzEG8rKN/ubjKIZjYEv7wIa7fRy439frHz0SKrUVqI6WCCjxcKC4N6gPqM61Lga59hzeQn1hH2Pxzr/V9/ztN8Ic3+JQej7T/v3z36/LSak58s//RHPHzjZDPIAfN0InVK+9ug/6G1wXA99zo7ovDvD8F+FwYoYRtPC8G3Dtx2HCU7zn1q7mm+GWynM8o33y+N663PeAds/0+VvoL636Wb8TI4gAa+gUSGobr28BSeT+uoujIrYHKr89w5EC2BDnDaZ5HQDQAAAgAElEQVQehxZjzcNQd63GzzDvvi6aE8dkMplMJpPJZDKZTCaT6QbIfsQxmUwmk8lkMplMJpPJZLoBeiecyjlZp3zYEHliP0JC3GAsG1p/JKsUHGAuhT1tCgvrCU6Nnk5kYaxSfUEEXGsH9uPdnuzN4+7KkhbCYjYayDb54J7s/MEr2Z97SCoIYcn3kbbANIdeV1XZRYLIOU7lXnpEhJr5DJfKYWENaitWtUHrcZklLn37dHWdsSxjc9jjmPzkV0wD0v12YlkzB7AJ7sLW6QLVVRTBFot26+JUcd9XOYE9rSjqf1vpe0qHlABidbDkBUAFdnaFnKSwc2YoL4FNhcDpFgUsshPZP99+Lkvk4tPPdA2wxZcesZTNqSwLN5mt0kcOD4EYhuo/uzu65yHQkw5GfS9W5Y1xzztolxA27wD9JALqM0P7ztFdq1z9fFmn1V2moznnXImT7SviPx0kbpX6nhi2+C7GYtGmpVPfnwGJCoEzhrAZV8h3qSrY/4GA9vwVJuR7m8UALu+MDlgiVB6TCGD9/OjJB+vyAfDEz5DqcHgk22gLOOMQqOAQiQM84b9PVA2W/KJOfigxlwW43r1d2dBDjP+tkeaLKVILF7AG7w80dp/cl+X9LjDLLp3CS7WP12IiC9oIaQlF9Z6S4qrSzWssxUuAlQBxCIgfI8mQ5RS2/WWhtuuoy7utRJ9zdgwsFOlstx+qLj75TPX4MRCp7V5tG+dYbcmqfndfc8Ef3dc88sW36l+3dvWeP/lIlucTX/0rQeIDq99rRGngb0kNLKORR/P94gbxuEWSuL//ZpU88cVT7QOevRQ64gNluL+rRgmwF9rtATv5QO1/ghSWCn0huiO0aWekesM064Zjjamf/dGv1uWDuysL//IEaUGV0um6bfWJ8ba+sw0MYGf743WZm8EAc+4A6IqHBMNXh0InfVjkE+DnJezk3AOUsMtvckYtq8rNaryzDQwpLHR9I+wzPr0nrOg2EpiiUHXU7gCtaCDKaq+9uxpb9+8J/xwAEVmcCq3IptpHuDq1JECaHUgEt7+nPeqf/erX6/LJhdLHPn4CdAd13moBxQPGubOtPWoc6/1tbFeCDMcbYPB2MGclNSbobXBujaPQPThY9flWX20yQyrWAHuVBxg3v/6TX67LB9gLPnikeXCOxL7uQP92a6R1dAwUeIy0sQqplsuF5su8xpgjom/AqXot9blHdzWe7yMl6ucffrQuz86QDgc8vARa1MbAmSHZ6uhC/+GsgyQuIEKPcezB7V9r7/q//532tD9ZHvY1SCasMIdwPzVCyuqvfyGsaHtL7fL8hebm6RHSiTAWbwEX/xi4dpwBV05Up85HstflPIEjBPoYz/uhriXNn67Lc/TND5Dat1Nh8e5oUJdj9dOPnzxal//4E6XDDTEYU6Z4IeVuiYdpv05d9ja4MPqec516kxCj3figX2FO9ErOPUhDw/MHEaZT4HQLpOlWvuqtjRRAl6sNt5EmNwJmfJkKyhQvhj6FeOYY9TX+WjiqoUDC2WKiPc+dvj7oLR6k5lMeR6L7K4AQlziWAFODa2M+DX8ECmdOHJPJZDKZTCaTyWQymUymGyD7EcdkMplMJpPJZDKZTCaT6Qbo3XCqqnKuTpDycDR7DDShO5TFaQhbZw6r1BLJByUs9yNYEXuVfl9aIlmq24HlHyhApwXrLP7tpaXWg2WOaQtP7uqU9g5sYTEs0jxuOsB9t5DUMNzWtRSlqrV3oXs9Ay6S4rT6soFWwXZYNf93E/Jc6cJ8Zc0rQyYZqd2YwBPBh9ajJa4F+xpSxZKlrG/8nBbQpjbaKsBJ/ZMZrKpT2fBb8aqeeep6Cexsju8cjNEmI1nyFgu1WwiGoIyRYAHbeJnr9fM5EL5C/7aLxJEAKR9NbsC9F3me56Lahjdf6LuPjnEaPjCo6ECIF09q78E+PYKFuAO7ZFjo86slbJRLYGZogyJRf24jreWS9MqICIEbKGjfxrV3iZ8g/cjDtYToDyMkLi2Zcob2yoD0pRjrRG7auM6HNfbwn6KnbqOq+zTHeDNdAHgly7DR7sNOvg/0aPFYn5Kj3zK9qZEmgM8sUszRQNLSZVF/htrVw/w1QMLHsAuL8476X5qoHZgwxLm1B4ShKGBtZZocvtdH+pPDekQ7ax7qczapsizdtE6ECvB3kS6Q3KpAAlqoOcpD4lgIhMPBtp/ATsxElL0xUhNgjx/vq20ePoZtfkvzYVisri0HWuADyQqB03346SNdL9a8NlDMYRdINfpGeKb7YGqDB2yqYqKl3vIHmI13ZXFTmi2W7r/8/QolODxWWxUFUMEt4MSwupdARiNc3PZIdX9vTzb8CClIEcZLhDnPwx7m8WMhT48/+HRdTi/7GhCLAJ+BZnCtYYT3IGUE/c/HOM8Qn4GX3XQuhMdhDvUwj8wz/YMW92jYb1xcCGcgLv9TVVaVW9brSMA0NKCxD+8ID/zlJ0qVeXwf2MS+yuMdIW9xpP7fIjrTZhswrVV18ZbzGHCqy7mfaAn31yGSUu6OhNHuY43Oge373L9hviiR5sM00rwQquFN1b5zYK8pkxqxHOf1HLxJJG7Q7br/4U9X2OAc3MG3371Ylz95qMXtk3tCpfYOhCrtdNQmDw60LgZIfmoBw4nRPwPU4WKpOjm5UFpdXqki8hq5X/pYK7F3ZlIPkx/7QEKIG1ZbOFpgqvfMZuo3czxb5PjMCPfdzvDsBBS3hQSzHvDqTcpzmucLpjZi3giRDMUk3xHw74/uCFV8grZOid80kqr0b8c40uMMmNnCAef0gQPV28sgV3t5bc1h+3fUj3oe5rMzpbPeQmpfiHmhj+SyqKXPHGCdiIl/I0ErR6Jr6amelsR+6msvNzgYfc+5frS6Jh8pWsSNcuDBWYFjDbA/Y2pbH2tniGfxFH2SaW4+9nBtHOnRw+8CIfbw2XrexzM2Nh/cX/Ozu0BfQ1//dsx5Exj410AVffSt0vF5Qs8rBeYDPCI1kqrCH7G3MSeOyWQymUwmk8lkMplMJtMNkP2IYzKZTCaTyWQymUwmk8l0A/SjcaoSmELkIUkG6IMHe6CDnb/EKflVKl9RuSQiINtaCRuSH8F+DgtVhTQFH3Ymr7YxxgHSdmB5fLgle16EBIMQJ2vHsCeGsKEyYKOEbfZsJptViPqogILksKcSpfBgAatqRGST6VSe57moTnKZA4NySN7wYWsLeKx3wdPDgerAjtkbyc7q0xp2TXmBRKg56i2Fjfay+kPUDW3CeYqEKaTdjJHAwDQih/SyPJVNMV3Knjq7gFUOfdchecMLYGdeyubKRKHqPfFUnue58NIvD+v9DMlPr16+XpffDnTPbk8WclrOfdgfS9gMC9S7g1XUr2DLh104QCJXD7bRS0vxMtI1xl19RhcIjQ9LfolyhbFdohMwhSOC3ZQnwhdMvkGzZGxeoBExEhVGraC+B7c5ec5dVn/lNSaBtXz+H4YuEeGgHRN10kHClwuvrhOiUnmC+YnpAxj3fo2/Rvj93+P4ADLa6WnMDWB9pZpJCrCf4/4SeE+Xc42zCRI84kzrRTxWuUCiwnKTPmOoKCs3rVPrEA7nuhH7GxK+ctVLXqm90iVxUrVFBrS0XWps3d6HjRl15zNZB2PUYRzlxQoRyJgklBKt0fe0YTO+j6SqMpXde3ahBIccjGaA9s2x0FVcO4kPVtcMMLynWv/v5gZjmhfu2dsVVkIatod73xtrPHW5AHF8oO7Z/xvWbyDhIRLhPKZWBWq3/Tvao8TAr7J6vPo9oGlIGmphjY5bwDaQlMP2KTE+EqLfSOHxsEY64OdMtOTrRJF2kbJUYa35f/7zX7iNql4PaeG/M1b9/+qJEqkeHwhVerAnRHxvV/hnvKV7cMAjYqSc5I0/hwJLA/5SIZGrB4ykVff5EG3hh0RCgVmhywfog8QyeSmoAhdGxPWAF0yBauT6nAWSY8+R4jnHAJnW6FqxQea/HUfu4zo17Lf/qLSkA+DxHz5QGt4+cBSEFLoQC2ObCVwYoz4Q4irT/RKrJjriXTNe1kcfYB0n8h9gjWTCbjoHuolnBZ9JQMDzQrAXXoT3MAS1DTwICNVgqP5NJOe//tMGE6n+UHXfbiy92Id52DfmQF7ypdalNo/HwN69AP4fd/R6G2OU6ajnh2rfNtM1uR+q+0Po6fuZWBrgWSdsCfPqzvV6zmUJyCVxsQbSwz4DjD2vNHcwcZPpfwvMzfP62Yf97qfK97z1cQYe1jkm/Pq4Rz6fJ0DSAiB0nJNaWDfaOFrFES0tr96Th/h9Ib9i+mE98MAS37t67a7wHMnlnb8z8GiHMFD7lEy1dUSr8FXXlHntpffuvhpz4phMJpPJZDKZTCaTyWQy3QDZjzgmk8lkMplMJpPJZDKZTDdA74ZTOSE+RGUyWqtgm2oj7SfCCeABbFMVcSPYHAvY+QtYHlOckL2EVbUFa2sMO6GrbakhUhv8XN+5A/xniQSDSSKreCfW57WRGlDCHnsO62kGRIwJTUXJ07d1ieSpvPdD36zlB4HrDFa4wWKJBDBgOGHGk9D1euLpdR+oQADLeQHLrg/fXCMlBnazhHY2WFgjcAlRbYsN8e+6sNKdAaVL57C+jvX9vg+cBAgDURFaLwvUQZ7A8gprbdEDKnAN9rLR2AaoLEuhYyXGDfrSfKo+/F1P9vzsU9lA/QCpGqhTDwkqMWyrXaSNhLFs+fMXOp0/bsv23O3LZurlqzrNMmBQGP/9AT4b9uMMyRtLvE5UxsHGWWGM0v4cop8EaJdsiRP+0X9iIJX9/qr+/GCDv3tXOoW/gPXzOmd6VVyNNsK97wLYTT0cdd+wgWOS4TTEyaeEhbQkOnWJu+Af+rA7N68Rln1UW9BIqkC7AaVpjEsgj0FJVEH9ewG78RjJFmXEcb85m/H3tbrBDHjaZK4EnsJDah9ww2VC3FblImdb0GasisxypcrMUEfdWBjp/Ezzd0BLdrmyZEc+UsAwzhzmwtDTHLGNxK0EfSoFmstUG1doLiAqVTYSqdAfaLW/LpGq+v5LP1VV5bm8TtYI0LmZ2OYhPa8Ty77vYcxVSLWgJzvqa64kEuUx1QiYebutzw/aTCPRWrSs911EkxzWOS/g3ArcMGY6GuZTLFYBIzOI8CCF0AeiXAHPGAzU/z757I/X5YMDrTsVxvEmcSrP811c7/U6qLf7u+qHj7bUh3eB4fZxo21UaQBWinuHyOc6g/kbY2dxoWSjYooUKMxFa1weaUdexcQcYK5AcXzM720k6HDuxkc6jywwEi0D8sRo9xz45QX2Ehnm+LS+nmqDOFWWZe7w1UvnnHPz87P168Nt7dVb2HMCGnYdoo38GzUeCSIPqHal+dFxnkX78PiFAO8vMszp9bOLD9yVnHaIBbCL7/HIGTGdh5gX6rtFRARDlMMVgT+uwPECIcaoG2g8/MPzV+69qHJuPb1cc5wC5/sEN0GUj/uz/lD/OG7pHlodlYmizecacznQtXabyXV6T+lf9meMTxyDUeH502F/GIVC1cIC4w/j2MdzZFDo/hyen90ceyasxyUSPdMF9j0zzS/C5De3z/E8b40tVVgXE6z3FZ6bGa8UMY3LvxqhC9H+Ptd+1H+A+SwIr94v8tn68qgSD3uxxl4C/46YFxFKD3NHgeerFMfIzFK1VYrxmuMIkoKoHD6zIsKnK+OW+QfLnDgmk8lkMplMJpPJZDKZTDdA9iOOyWQymUwmk8lkMplMJtMN0DviVJ7z6hO26fpJ5jjVHZa4EuUIFsKggCUOr9NincNCusCp0W+OhW1cnMhq+emTj9dlOIRdWduZSgfLF366iminBUKSprKbphey28VI0KElOF2qzISgNGPKCjElWHGJEQAvuLSAbdCp6jw/dHFnZf0LcI/JTEkvZS7bYYgEJh/dhfVWBGhnJGUE9LDCBkrkIEOqU1CqzX2cDh/VSFejDzFNi2wHbH5eI2WLVmVY3NAmy4kwgNlU5SUsmQ3kCyfVB13Y6zms3hPBUVWVKy7rscQJ/xVteirPgITlrC/YE1tISukBg2p31Y4h4h9m6PMTJOsMtpRg09+RtT6Zr6yfXq7xMUXyTq+taxwN9P2doayycaRrzPE5ZSpbaYKUu6xSf2DKRwEGKWESFvrJrVu69of3VmkYLaac/URVrlqfoF8x6aLxHqlooJkoN2yler8P630DYcLJ+7RzF6iHDPbdBKlVl1hiXlxt6y7x3lZLnxeHV1vVaRUvMV4zYIssEx1pAfMLgMvSrx0iEWKZLNz7kOeErpXAWebsV3PObUzhw9iFDZt4EtergqldSBDygXl4SK8okCaU9zSm3pyv2uME6NMo0HUReZ2nmPdjYTke0l+CLlNbgCBd46OvGn8/urpMHKLc5CJ4pap1MonPpC8mPEVAnIChMpmyKNhvYbHGN7WBWbWRVNUCBhgS7cj1mZNjJQ6enq7W7BLpQsTjSGq0gbi225hDfaQwVsSysLfBnO8DVY0wpjtIvPrZx5+sy//+3/35uhwAbRxvqS/+b//r/+I2qcvbKIEYDoFWbXWQPEqElOkrGH8B1pBWiYQnjMUAGN38QvvS0xoLcs65DPNPDPwpra+H/aLAvOjBkp9k+ozFucbu1i7mPCShcW4mIudhvWYSZJYxrQ74IPrj4wOt719/98w559y00cN/mpIkcV9989Q551wbKW0dzPE5xplzGKNIuyF+z4oogY1XwENLJIL5GDwB8f+E+yt9V9xbja8WjnKYLng8A45+6GseGSDBjswx0yET7LPyBnaNxm3gHHr/dKq+yOePAmjdZMGU2s1qjcXg3rgvrTD+Uoy/OequgWhDPp+VSu4jsKfH+rfA8wXxQyaK+ZdzNtrf5zNQ46gJoj1YfwP1KY9pzS0g6kv0zQmSbTFnFSgn+N4FUMgMc5C3nqc3BxpXTulJZWM91nsy9NUQc0YGDCrHv2386IC9KJF7r4HccW+h14kcMrHrcj8fMDGXx2nwWoC4FfidoSK2jvefLnSvx0gQXTKRGOOvuZcnZqfXc2KUqLMfKnPimEwmk8lkMplMJpPJZDLdANmPOCaTyWQymUwmk8lkMplMN0DvhlN5spDlsHIHsObR4ZcnsBnDYk2cKilkDStg5aT17/D0ZF3+/dMvdTmwJM3OZC2NgDzt3D5wzjk3RjpPCNvkdCkL1QWwqeNDYVs57Pw7e7KT8yewOeypKTAGWqUypFkVsHr5sFD5QGO8H2Gt+pdUlZXL61O1S9q9YfcsUtWl5xFlAFaDnhPCphijXzjYtukfy3iaOeptcvhmXU546nqywlqKoWy8Z0gtODnRvyvdtu4pV1v5ThbaAt+fL5DwArTgAqkSjRPukT7gt2D1HQq9YdrK+8Kp6i/6nrymD3FdzEtiGLD80x4Oe2oL1j8PKQsXMyXuvDlR+exMdTR+uLcut0fAqarV97ZjWftLoHXLha5rNFYHY/JQC1bxNlJ+0onGsQdqpqqABSBlIMNEldLeC0/nCLjc7nDVl8Jgg2Oy0hzmo76DBu8EizW8pAnqjakTJSZFDx2kwDy0hB03Sa+2HnMuJu7Zjld9PgQ+Qbvp+VTj5mKCMQy7a7+FBDvMocRweK9MzeE/YFKaQyJO1APaGCP96X0NRs+5yybA0uaqAm0HnCoCelFgDk5p+ScuivatUC8R5+BYc1ELy/p0qTnty8/1b/+P/2+F5RydKOnil481Xw639HlnGJdlKZzn3geq861Qdb4sr8Y5ro0ouabceBVdoNqcW7whr041YepFziRD2OQLtEleId2usY6iDXH9TORg2mVMC/dcn/PVb/9+Xb640Jwb1HMRP3u+AB4HrJV28ghjl372CpZ9h7HIVLcmoqU+8uEHT9bl2x98ti7f++DxutwDFjsYqC43qaqs3LJGQVP0E5+YEHD3qqe68Ft6T9jBeoJ50WOCI6Kflhhnxy++0xcjQW8UEUtGWlndB3ysT0xn5RoZA2G8SLQHOnuj693e3l+XAyaIIZ3RYS9aYX+bYD/ko913sO7e+VC43Px8dX/HC80LP12eq+q+3Qem3gcCs+Q1O+LTusduBsQMexi/gzZs6b4q4IHZTG0+vdBYzDGmA6QyXqKFPpJ3M6YBAs87majdmDDWQ5pvK7z6OWBREbnDng71McExCQuk7C6muqenx9ozt97Dc8Za64mbGFhx5Vsz3M/b46N1eYYjF0a4zxaS8rxGmjGes4DIxMDxen09J/jA8cr6ecTDkRJlTvYFcwQRcQ/jDGS3j/dU+Ld5qj4QZHjeytnX0I6ogyXwRx/zSBHX3+VtzptRFKU7qXGvXkfjr419MFOlmMxXYs7l824jmTLi0Q4Yl0iBLYnuAwnlsRwLPNOtUxnxu4SHz8aW0LUzNdYS9V0SoUTzvz7V/Hie8BgGvaeJfl+dttnA0XAfxBx/qMyJYzKZTCaTyWQymUwmk8l0A2Q/4phMJpPJZDKZTCaTyWQy3QC9YzqV0B8PFira/31YhlKehp7CkosEkwroUQEL8Sls+d+9ebUuL2H53doRtvHs5HBdvpjK8uS++P3qvUieimHnX8DiluBazk6U1tSJaZuT/avblZ14wVO5cVA/EQGe4k3bfQA/NFxkzl9bujaXzFFVlUuTS4shTtGGpQuHa7sc1sfMR2LXXDcQMBGqYafDqesB06GQzhGpDn1YlZep7IzPv63RNu/p+rV5AvQCFtrReGddJjbFZIh8gfQwpFDNZ3rP7EKWzHP82yhEwoOToo5sv0XDXvj+UlUa9uhaAb8OONUSNsRpwjQKIiywJ3o4hR++dKZJLZFKV5aqrxdvvl2XiUsu5qt/6wO5i5gkRAsjLO+lz2tRv2j3YIOFFddVxDj1XXkJjI73DVt0yVQ0JvTUtviy3CySc4mZ0pLKubWR2+Oh71Wcb4BWwTZaIHmGNvAF5scIYy5AssYCmJXDWFvUSRldIEEe+iGrp2TCBxO0MEGmvEEwM7RcF8Q5aLkFztjqI31noLHYwMv8q23cP1met07eIcJWYs0DNdpIFfHY31AXbbSLX8GS3VGbekiMiSvZqiPU9fFEbf3yjea6yxSaEBjUN2815naQwhDEuqf7HzxYlwfA2TLYwBdA3hLico6o3zXjiIEytIVzqqveDxa3ToPEd82RgPcKewzPCbUc9bSegeRzSUpUHHMY1sgc87KPhZfJe+en+l7idO3Wqs/HWENDJLa1u2ofHxuLikka2Igw+SzLkQ6D1yPgJ8Nd3eytj4RuPQBuM9zSejwcAWHw33nr+YNUOefy+paSQve5wHqSzVVOkIJT9MDhJhor5UL164ARZJhbTt++0Hdh7xpiDeZaW2BPsThbHReQL5lahz6CveXOrhDGPlCp6Rug6NjftIAEl0SBgRr5xGiRZpQuhKukSCv88pvP9TH13FBt9M/BpSvLeq+AS94e6V54ZEGG/UQeck8ChM51UAZahX1Lgf1fjqMVErRVGWJuQ52cnq3wn1aovjKdMdUW6xb2+wXadpmpvuM2kriwv654r7i/GdGVuepmAMy26ODfztXmfvC+1kXnCu8yYZfJk8CBsEby+e/r18/X5S9PdLQFMcwY7ZhjvZwBhZqdayx2uxo77a1bup5Qn5POV/0/bhF9wT5qojYqmCDo6fWoA1yI7YXnJ+KMRL7KVJ+TLVnGv8VcTkxojZp7747kXKesLN2r+qiC7X3VXw/rTIi1nGXXSFAFNl7i+vms3Egb0+tc84hV8y65pl7umgs8B+Sl6jhC2zKZ1iEdNMdceY4jV749V3mGfa9XXf1cyP2nA/bJLD8m0/6YvY05cUwmk8lkMplMJpPJZDKZboDsRxyTyWQymUwmk8lkMplMphugd/a0Xrp9KlifKtieaQZKYPGb47T3HN7yHJbE6UwWVp5Ofo50oLv3Zefe2ZWFd7SjZI2TM1lCX75e2Uy/eCG7a8pT44ERtWEV3kaqDu1rR1PZ2rpMi4E9LvVlNWM6VQrrZAlLZQlrMQIPnF97VKtqg0iO51xxeT+wbkXwrzVTXHCdeJnpNUsgY3TyMXmm1Zb1Ogxk8cxy2dYGg9v4Av3j2WxlN54ulMzRAR7XaQul6KMNU6A/ObAFYn6TufrcBH10gkQChnbEsdq2heSEoKPXS9RldgXytAl5nu/idn2v6D8+Kp3loKVrTWEbXAD3WqA/BMCWFkinOTuTxXMJS3N3rM9vIZXs/AJYYp1wMb4lDHIB6/cMtsUcyUY94IzlBEkwC9W5H8O2nsPyChslm4LjMocV08Pru33dx2Uf22xiXOXWMybnUGAAtFoGsHiG6Ic55qQUGFQE26qDDXy0JayBA5ZzYQCr8AI25/MaSZvPMSfhGolwdGC5jXC9TJtiUl0LKQTLTO3GZEMPdRAwbQLYQAArega7fMtHbMQGVVWey/Iap2KSAkP4FkwKIxIDtLSrcdyK0dbEkGCPr5g45Gnei8A2bKG+foZYhp3x6vW3sAcfIuGtA9v6nbtaWx89OFiXS6zdb2dYC0ukpTliPNA1tmj+PzqLNxi48c/o+zgVE2beArFeAMN9dFfI0B7mQeIWKRCerKeOkcAmnxHtxrxIbCcC8tgerr4rAEpQZVfvMWbZHO9RZTIFaQb8YwkrP5OAugONs/29O+vycE9r984tlQdIbYxjJEF57ykRxxM6xoS7U2AQC2BCrhiti1UjSVT174DTJOCVMyAp6bkSVD1gLio1U88YeVKerfrVcKw66bdVz0zeC7qaw/oV124hJydvhKKMlpwXNXdEuT6HfZD9Op+o/NnjD9bl359ob+5dXsMGt6hV5VyZlPo/tfZ3VA9v8HywRB9eIN11QLID2KIjPoYWYgotk7nitsZLrw2ccKx9p1fPcx7mu/tDPaswYcyhnzGph6mh+YRJcUjSxDVmBfE79dcQc9aTe/fW5a/fKkHs2yP11+o94anOaTbnI+uqlXcAABspSURBVAyfg5K5xmIFnP/VoZ7h/uGLr9blPSDUBerCtYCRO+xXj4QZRh3Nb/0DPTtyD1TURwTkTPbEERrtHtZcJIjNjoS8cj8W9TT+8gj7K7RRhWfHOVDMGZ6Hc/SNCOs4sZy4rgNvgzhVXjp3WqPVEyDWB0PN5SH2lh7SDlMeEcD1HpgT05gd973E4DkWEYvs4fmm7atfzOo9ZQqceQ5slmhVjGMJYqbTYYy+mek9b4HlFo0kTSCa6OzXZXByTxc1jqZx7yxz4phMJpPJZDKZTCaTyWQy3QDZjzgmk8lkMplMJpPJZDKZTDdA74hTec7zvp9OlTNtpKL1D7ZSWKjmsMonsAFOFrK7zeFF37qzvy5392Tt9pEO1QNe4yJYumpb1Ax2xhTX24aFq9eTPXJrS9bNLqx6Gex/c2AGOe67gL05BaqxBDpQwqIX4XT0Ep8T1lb4TeJUle+7qk4VCWDji+Hjyng0OExgfkWrO+4X90JLZIFy0sDKYBVHPI0PDKDXE/JxaXOjHbuqrrbwJUuc5F/RgoikpkR2Wgdr4u0PHq/LZSS76fkLpaO1OrJHbh3INh4BIaJ3tP1j/HE/QP3h2P36v/ufnXPOeUipCGHxjPDdA+Bk3S5sqLATp5nG32yO5IMZkroukKCA9ui3hNGMgLak+K5LFCZCmkqJtiPWNFvS/q7rCmCz9JGa1eqpDjyeAo90gDIATuMzLggYGT6/11HfOKmTQ4pyg75x5zS8GqlOuGbwlV6ge4xh62bCDMdl5aGdgR7lGK/eEmXgcTHu8xKDc865qr1qryKCrRhWddZPinkkgfWb9tiyUjssYI8ugCSEMeuAaVrqf0T4CmKESMXzo/czFqvKuSRZfTZtw+x7KRAqtlcJ9IgBC0TOYozpMGQf1jjyHBAyfFDl6fUYY71TrcZUF4kZW23UbQAMcSmMdbFEClhba2QGvC7LgVAxccJdp3+5XTy+Z4N28avUCPgDspaCx5wk3M+gn7PNuS8CHpXMNLf5aNsKiBH3FkugWFUJdHJZfxd2cSH2Hr2u2ioKNXckxMWAomTX7MtyrGe9gT5z/65QDeJUvZH2aC3MO3HEOfp9Ycaei+t1psD6cI59AeeioGpMvOsiE4E8IKoZ1xbg1y0PcxQnAeCMEVDICPvV9tYK6WoDvYg8zGcOKCrwcz9EUs9Y+6XTqbA/H3hGD/u9CnuDEqlYVaI6WE5UByP0q4+Ay33zYrVP8jaJU5XOLZarDzwGVu1jkdwD1pdjPkgxhnKkoBJbKjhGcbRD0TgvQEWvUNu2cVRCHGnPc4kZ+khtzIDtJTgSIsPaliAFLgr5TIX9CdptifIC+HmGZ60O1sJ7HwiDK4EZ/92XT/X51fubTy8Tdlm1SSM1VnUU4jIK7At/8/nX6/KjHfXzNvpcDMww6gCzwesvj16uy8f/r/rV/lh4/1Z/1Y59zGFRH58NxD4Hqh32mRSn8ZfjaI+oDRQce5Gc7Qu0sdEf0TeYAF0kxIFqpHuDzVlWzk3quL83OErhIZIJA+wbfMyDxI1yTBDMkSrQ9/jYyTRFD3NVhb0du22I/Wi/fv4nphZgDZtgbfU5/QNZm2KP9upYr+M0h0bKI6uc7cN5McI9tbEudNAXIv/dG8+cOCaTyWQymUwmk8lkMplMN0D2I47JZDKZTCaTyWQymUwm0w3Qu+FUlU78D+FlSpHCkNOeC5wmZxmpCQVQogKJHNsHQqj6PSUIFEA7lkjECIF3VTj9vFfjCA9wwr+Ha08SnBQPDIuuJh/X2Ia1Lp3DfpvBwq5/2kioWMK66ZByUMFfRnt9WX/vJsOpisq5s2z1gQugMUygYUJPQDs8rKoBU3o8nJEOu1sGO+ACCQ9T2EzhYHMhTyfH+y/THuBCbdhKmQDh0Fb+EthcF/0DduoeEqbuHChtY7uvFJYCdZCgn/X31UcdrNI8Hd5roGmbU9zquIcf/6K+Pv4WCzQIVvFuppPu/UK20jgmyodT8jOMb9gDM4ydYooUgET4WXECm3kX9uPailqWshZHmBc6tBAXsgpPkTYVIwWshfSji5lsq62IySeMe0O7oP/S3lkCO3gz0/uPamv5PN8sTnXZVa5L32G6TwB8zQNO1Tz5H9gOJzGiam9UV+cvjtfl6bEsxg5oVWuoMbLzZIVQhMCaTl8oGaWAVbrqABUZql7dFpIN2rCqw1baBvrmIzVggcStFjCvAKkFDOXi626jyWJSWVZuXuOHcQxLPCZ2L1IjhRFt/lj/qmvKQHroSy+ApdJafzEFIsAQsYLjePW/vRC2aCRcMXHCX2IcfKf+EiFAJwHalXtqr+vSGa6naTh3ele9vNkFcf1dzoX1eGEiFdPhaP1GuJBbYu3PUeElsI0MOHeCdvNmGCNIhJucaw59/q3m6ynW7N4lFg27uY8620IK3ZMPhVX0R8JACmDuBasbnxMjESZqIbFvoH0ZEap2R32KCS4B18VNxhlBnhN5QJzmFPNZwoQ74JbEWFNsNmK0Xb7Ang/7i+WF1tfpqeZX7kuJloVDtUFW43JnoRKXijn2VBP1Lx/rmYc0O+5vvLnW5QQYZysgUgtcFdPLDM3yxZnW6b96LqR84uvaXtTrbloyJ+enKS0K9+x0hXCeZNoHns5U3u0I66tK7BuwGGao+3kjGgb4I/ZLM7ThAkiMA4rHJJmop7GwrNOOYqyLM6TZLSdM9UT7YByMbykxqb+t+8sb6BvWV/TjDOPMRxLsEnuAl0eaux328lsjpes5d+g2pqrSXI3jDxKmkGKfH2PNGW/pmt6eaG/56kxo72ePhHP6WHcnxxp/XdTLR7d1XEKFeayHZ8N4sKq7eKTFzQMGU6DtXMo1Hallu9rrTM7Rp5CEG6RXPy9G2NOG2NfP8UxWYV0pgOyukzE3OLWWlXPLGqd6far54O2F6mfQ0bzSjXTNMddv7IXKxt6G673e7l3z3FkAaS5RJ9wTrPfUeDBs8dgGIOlrJNk5lwDtP8PrL8/wDN84TuH73+lc0xnTxt61x7RWvMnnDwA/IinOnDgmk8lkMplMJpPJZDKZTDdA9iOOyWQymUwmk8lkMplMJtMN0DvhVGVZuvl8ZfONYPGuGKvR+AdENWA9Q9oTXE5uG7bdBWyDT799vi4fH8pa58Gil8FWxjSnooYlSsd0JCRLLOS58uErHcHOuIXy/r4sj52RXi+nsj8XJdKxcF0LJFR4sHS6mDwEirVHa5PpVHnp3HFtj3/1SvbKNiz4A5APEe34pBHw+jWutkYKwNGpbJqvgXMcH8pyGsE+uLWluo1bq3YpE/33o2PZKk/PVfZCXcxwLNvc/oGs3+OR7KbHh7qu7FDt04YldQ8nzydt2slliS5h+aMVvQg2ZzP+Q13a8FjnxDNK2P9zDPXMafyViASo4PHLwaQsYTM/Qj/3gVDc/+zJujzGuAiBSFb19WbA7xKMiYtUluMpTt2fIZ2ljdSQLVinI9xHgVSmAPbnEGOO+BKTEI6Bkf32SO1+3l7hAkm5QSTH89Y+TL/BU1VXlJzzgXoFwKkK4KNw/rocaTDJmdrtBAjp4KOP9G/vAIV9hYSFmeaG169X9udiKWtwhrmD5A/ttBHaanKuMXf/w4frcg+oXAgvbI55wUe/DGFPLa+rM1jOq01GqEBFUbnzi1UdRBETKJh0pjEXw2LrcozRBn6McYl0miXSY07PZEV/fYjxglSeGJZ/JkdcHK/G1Aks0jnGTQeJEx7T9naB4iTCP9r7SqzhPBIAV/gh6VRMfOA/4By3yfUQXwzrP/pSdfUehtjGrJFwo9cbyXhY7olo5Vg8sVVwv/vym3X5xXPV84MHj9blnVsr/Jdr9Pmpxu3v/1GfcXakNfeX/+aP1uW4iyTNkii8PtPHe0IgnUzIa6Ech0QCgHpxjL6nseh5SvkhhnIIJOYc830AJDME7uTFmGuxX50B6fnu2bfr8ssXQt7u3XuwLm8hNYpratJIIlv1gXZfYyvs6zujNvoRkqRevxHi9PbVs3V5DLzh3j1h4S2kRpaw8HP9OMw1N//ja5X/5oX6T94BJupW11NtkOHIy9Kd1pjNBdaBv0Ki0s/vPVqXB0POuSgj1bDEOtCKVD8lUMjXGGcFeMlOR+3CVDGHtKGL+hiJqsBahbSxGLhhdiFsefLq9bq8fK3v/6MDJSZ1sI5PcJxE3Nc+KwXa/s1L9cX8tT7/N//4u3V5ASw8Dq+fmX+q1nQI03uRQlkinassgPi1gcuhvb56qz757wJ95if3tP68PFP9fvO3X67L27t6z91Hwks7RLHrOaOswOIgibBc6HpzHJWxyPD8F2AdHQI1Qj8qMx4CofoPMHfO+V18psWaUTLRs0bZN5pm7CpX1HPF6ULf+/uXeg4f9HRfdzAW2zhKwm8cK4EEK57KgffkmJMKoGfc/5Up38+jGFbvz3FsxhJ9a56qrVJ8tocE4zdzvf4GvxE0ju5o4FRoQ+zluR8PGsgV64afaelUJpPJZDKZTCaTyWQymUz/KmU/4phMJpPJZDKZTCaTyWQy3QC9E05VlIWbTlfIQwsWtBAfE0cqExHwgT4FODG825E918HidzGVbTWFPWwKX/KbI9kPPVxPdyDLY1Lb9c6B3IAmcKfnQjhGwLk+QyLLINTndYCQBLDzp7B2LfAFGWxzCU42D/H7GdNHAiAf5Xs4bdwPY9fdXtmwy47swG20QzGRZTHEid0Z0oPySPVAa3QJS3ZQyhLsZ7iJueokBeaRwvI62lXyUzBY2VKDHpIHTtWeRyfCwro4pX7U0anzbdR3jJSas6lwgskZEo5gD+/s4CR7pJNdvBXmN7otC3V/DOts8P5+J71MLqqATTWseRh/JfrYEn21dEReMC6R2uUhQmxvWzhhBKt4+7Gsqj5xKlzQpe3fa+GkeCAH0ZFssK23SId4Lqt4OpWNM9rWNQ5H6o/TifoD01qqUuNyAaQyBd4wqdTW80p26KW/6g/5Jn/3rpxzl23n0ZrJ9xBBaETm4XV4UmFbbmNeZvJNdq4+f3iq8XfrsZC44Z/9QteD+XTZqT8T4zlCAoqPtJvZkeaR53/9t+tyF22+yxSqSNfIdCamxjRsxaizFLZsz+caBOTqPbnGy6pyi2Vt4S31ffkCNmyijZHup4P7D7GGccrPc6AXWhbdq7caly8PkT4GnKryhb0x3W92vnr/4TkwrELvbWOMjrAWduEJ3h0qQWQH5dIDclUiuRIpP0VBvojbEKJMSBRk6lqNRm8S4XDOuaq+Jq9haaYN/GrsawErN5OqEsyzGfgk3jrvPMM9niO1ZQYUfAor/auz1Rw5QNpGiJREYiAJUuMWC312FcCaj2vJUff720I79m8pwbEHnCMCIkgsmhZytlb5ntKpXFWtU0uYTHcEDOmrU93/f0CaUAtYgOuqHuM+EtzQeAuUT4BcfPTkw3V5/49/vi6HaA9iaZdtFgV6jThH4YCczJHs+OzFutx+prU4Qt3G2KO2htiXYL5MU33mN6+1B/ryUOUl+kOI+TiscdBN0nF+4K9R9RS98tsTXc9kIUzmyT2h8ntj7cMC9MkQ+zAP2Fwf9bO/d39dPgRmGu+q/7eR+DZEglGnxv8L7IvnU+1n5ud6VpkBkyk6ev/WWJ9HtC5NtEZ7SHAK8SwyR/3/w9Pv1uUKa+rRDMgPkpWi7H0h/572qNhDpujDOXAgzvHtWNfdBwb41WslYf72O2Fjd548Wpd37msvevyFcLLZa61vZyGeB5dI9qqfg0K0o2Py8FJzB699Xun11q4mvdGe7oNpYnmChEpGSHrcGzOVDkeHIN2rjc9Mpqt74j53E7o8kmSJy/zuRM/N3Wd4Xnyg57Y9pOe1GmnMWHMQidjAldEn5zhOIZlqXqyAonNO8ur7J3ZWeHgmx95/QeTZ1z73BZL5ZqhOrtdMWAyRcshUMd5rgednJpQ20oyDd/pJxjlnThyTyWQymUwmk8lkMplMphsh+xHHZDKZTCaTyWQymUwmk+kG6J28O1VVuWWysjYVSArqwM7rN6JB8EWwGIUR0w5UXuIk+sFQVt1fH8jm2ALaNL2QpYuW5gS+8aRYvb6YANuBrfwMaEEPFtqDXX1/C6dW58AFiEoVPH0deMYSNuY817/1cLI6cQGWvUuP6ga9qmEUu927K8tpDKwtOH+zLn/7l3+h99MCj7O5M1jZArTtEla/3lD24PGO7PZFLgvroCvkKcLJ7G1Y+L06ncrh9PIPHz1el/cGslumC1kmfR8n+cNazZPPU1gil2iTAhb2LlCINmyhi+ey9L6F/XLw81+vy2FfVt9NqnKeyy9TNtBnmADCwZjBqjiDVREuc5enasd2R/fcQcpDH7bkQ9h2nyK1andf9uNWxMSh1b9t4fM4JiYTtd0FUlYCp/ccbKu/9GB/J1pT5EDnMAktceL8DPb3nEkdofpsjrnJuUu7LKGDnybP81xQ2yd5eL/XSMRhn+QJ+EQ7gGayL2D+vUx4c865Bzuqw2d/9/m6/PVvVfZhOR891vzbe3zXOedchKSjGZJvpi9kXz55Ibt/Wmoe/Pg//HJdLrtAblHdFVLCUlhSK+APxHNy2MPbkfpFALTK8zaYLPYH8msMdjLR/MeUQtqhXefqey6xbkV4T+gBaaVVF6zK9rbmn/0QKEisuqgqvT6brK73AAjjGdYqzsW7+0Cex6rn8YHQgoNbmoOzAms62nGxVN9copyltFdjHJdX40vrMbjRFA4gbw2e0fuDd7nvvWeOJL3TifYk+13tVSZAiDsD4C4Iu4lgjb97S6lCCyTPFAvtVy7RCiadENvqAGXdw7yZA89II9V9CIS219W6tXMgPGGIdbwFBDvAukCk9zowLX8fCWNu1UJFPS94uKY59iv/+EpI7tu5+vztA2CYwNK8FhJmsNd48ljJfseHWrv+4j/+p3X53lMlSO3cvqvXHyiVr9Nb1bsHFH16oWucINkzO9d43R2qjT54/EjvqYCoYD/mYS2ugGudTfWev/xciP1zYHdRV3XApL3pZNWO1SbXxcB3rdFqYLSBhnBfsYukodcnWmemGeZHTq5Eb7G36wHzOACSPXuuepi/FjZPJC7HM0r37gozj1oa0Bev1PZzpKAuT4RWdXv6zjsPhSqSwidmWTHBB3VzcaF5oUCCz3AghM4P1acq7HkazOMGVTnn8npO5RyVzJBsif1fY97F2t4DWnZ0rn3h3/yV9t+Pbqs/fLKPPeIQ6XNtfc74idKpuh9of+PqMRICwy6OhF4Vh3pOSjEX97f0nduPgWW2gLEiWazA/XGPUhC7Bcbl4ZmywLPu7r7W4G+/feqcax5p8VNVOeeKGqUkjj7DV/z+pY4vIBL16X0dvbDb09rWwTN0jHkDoZYuQp/sMmET+HmBY0v4OWF9DTmwqawg1g08GXPB63Pg6adIR8Uq1uHaxkHKdComol7zbO8jIZHHzlQ/Yho1J47JZDKZTCaTyWQymUwm0w2Q/YhjMplMJpPJZDKZTCaTyXQD9E44VVmWSjlgAghSpYgFRDj53af1CE7aAja7fC6bbw927h3YRtvAqW4NZO0lUjLF6efz5eozlz1ZRnmqdbGjfzfJ9P3LEBgU3ORJcjVOReyBr89wT1XDQkxrNorXlDclz/OcH60saRFQn24EhKNxirosZpGPE76BrASRLG5LpGr4mdoqwCn88VgVOpkiEQXYTAxrv6uRpxx13AHitETa1Bw2xQGSpIgeXOA7icHlwI8SnAwP958LgSJVS1mb337zT+tyFxbWnc+EjmxWpfPq5Be/QVARocIJ+Pi9dgG77elM9Xx3BCswLPcZ6qKAVXuAMRe9QFLcRP3f31Ifqy5P/m/Jtp+cC8VxM9l9hyHspj2c/N7CifSYI6Yz9bsSfcAHRjRf6rqWsPHmuI+qQp9hcle2mj+8DSMc1VWRSY2kqqrx/qvKHhAbj23ORECcet/f17z58N/+0bp8+qVs4xf/JDv54u9/ty6HtT2fY+L4N7I1JyeyHreApD7+9afrcm9PFmDQfC7AmGZ6UY71xY8xN7Gd/atrh81VufdjG48i3+3ur+716681tyRAjkEyuBjXGiK9qUJt5GjHeam2W+Qq93rqq9tDWHKRgkBsaQmrduCvLmiERJQd0GYhrMhhBGx4S3Pb8J7SzEb3ZJ2uuI7OdI2zma59CuxsisQJBDi6EhZpYlaXKMCm06k0R14TqdRAGKUM9uxDJOh8sKekjhnmnvlC9x4jBcxHUtRtJBxG9/RdZ4dI3ruoxxr6SgBkcBupLqOO2iFfqn3ygO0s/OTutr6/i/1XB4lUIfZ3xKlcybbCvsJd+ZYNq3KXrVPSQg/88zukLn31XAk3H91VH26Vus+E80lXddTdEjbxxx8Jz8j/y1+vy6//z/9rXT7GHPxsAMyxXqNabSCsA62Rt0Zqi15Hr2/fFgbSHwrnWAJXKYCIJ5hfKoynZ6/Vp/4OiDQx4y20XgwSJ6sfITY5s3q+5/y6nrsF0CAmhrW0h3wNTOXwRHv/B6i3NsKGCsyJiy72AQN91/YjrZFn3wjXamE/303U/6PZaky3kAA1nGkt9BLtFVPgseMDzRFxj5g5JsKUeAz2qInmkSPgWh5JqcbcwPMtsKaG7+9v+Zeod5ljDWEiFd/MlB70N59oDdLB/uY74Wof/UZ7lJ1fKR2uBGZ8/p1Q17tI5Qyeq52yOokz72CtXAJnngFnxfNQB3udcoBETOJimdoibFC6+j8JkpgKPHslc137eITkZCSHXiZBVhtFVZUwxmdsYn0XSCr9HKhqBVTp03tai/b7SGPGpUYRkqrc1WWPzBUWlDlSw1y9V2fyVY61IME/XKD87EyfcYLHz7Sli+wiVQoho429lc9jD7BGepnaluJxJHnx7m1nThyTyWQymUwmk8lkMplMphsg+xHHZDKZTCaTyWQymUwmk+kGyHsX65XneYfOuW//xTeaNq2HVVXt/ctv+5dlbfjfVNaON1/Whv86ZO1482Vt+K9D1o43X9aG/zpk7XjzZW34r0M/qB3f6Ucck8lkMplMJpPJZDKZTCbTfxsZTmUymUwmk8lkMplMJpPJdANkP+KYTCaTyWQymUwmk8lkMt0A2Y84JpPJZDKZTCaTyWQymUw3QPYjjslkMplMJpPJZDKZTCbTDZD9iGMymUwmk8lkMplMJpPJdANkP+KYTCaTyWQymUwmk8lkMt0A2Y84JpPJZDKZTCaTyWQymUw3QPYjjslkMplMJpPJZDKZTCbTDZD9iGMymUwmk8lkMplMJpPJdAP0/wNnh6Poia7JvwAAAABJRU5ErkJggg==
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<h4 id="Exercise:-Pre-process-your-image-data-and-scale-it-to-a-pixel-range-of--1-to-1">Exercise: Pre-process your image data and scale it to a pixel range of -1 to 1<a class="anchor-link" href="#Exercise:-Pre-process-your-image-data-and-scale-it-to-a-pixel-range-of--1-to-1">&#182;</a></h4><p>You need to do a bit of pre-processing; you know that the output of a <code>tanh</code> activated generator will contain pixel values in a range from -1 to 1, and so, we need to rescale our training images to a range of -1 to 1. (Right now, they are in a range from 0-1.)</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># TODO: Complete the scale function</span>
<span class="k">def</span> <span class="nf">scale</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">feature_range</span><span class="o">=</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)):</span>
    <span class="sd">&#39;&#39;&#39; Scale takes in an image x and returns that image, scaled</span>
<span class="sd">       with a feature_range of pixel values from -1 to 1. </span>
<span class="sd">       This function assumes that the input x is already scaled from 0-1.&#39;&#39;&#39;</span>
    <span class="c1"># assume x is scaled to (0, 1)</span>
    <span class="c1"># scale to feature_range and return scaled x</span>
    
    <span class="nb">min</span><span class="p">,</span> <span class="nb">max</span> <span class="o">=</span> <span class="n">feature_range</span>
    <span class="k">return</span> <span class="n">x</span> <span class="o">*</span> <span class="p">(</span><span class="nb">max</span> <span class="o">-</span> <span class="nb">min</span><span class="p">)</span> <span class="o">+</span> <span class="nb">min</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># check scaled range</span>
<span class="c1"># should be close to -1 to 1</span>
<span class="n">img</span> <span class="o">=</span> <span class="n">images</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="n">scaled_img</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">img</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Min: &#39;</span><span class="p">,</span> <span class="n">scaled_img</span><span class="o">.</span><span class="n">min</span><span class="p">())</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Max: &#39;</span><span class="p">,</span> <span class="n">scaled_img</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
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<pre>Min:  tensor(-0.9843)
Max:  tensor(0.9686)
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<h1 id="Define-the-Model">Define the Model<a class="anchor-link" href="#Define-the-Model">&#182;</a></h1><p>A GAN is comprised of two adversarial networks, a discriminator and a generator.</p>
<h2 id="Discriminator">Discriminator<a class="anchor-link" href="#Discriminator">&#182;</a></h2><p>Your first task will be to define the discriminator. This is a convolutional classifier like you've built before, only without any maxpooling layers. To deal with this complex data, it's suggested you use a deep network with <strong>normalization</strong>. You are also allowed to create any helper functions that may be useful.</p>
<h4 id="Exercise:-Complete-the-Discriminator-class">Exercise: Complete the Discriminator class<a class="anchor-link" href="#Exercise:-Complete-the-Discriminator-class">&#182;</a></h4><ul>
<li>The inputs to the discriminator are 32x32x3 tensor images</li>
<li>The output should be a single value that will indicate whether a given image is real or fake</li>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.nn</span> <span class="k">as</span> <span class="nn">nn</span>
<span class="kn">import</span> <span class="nn">torch.nn.functional</span> <span class="k">as</span> <span class="nn">F</span>

<span class="k">def</span> <span class="nf">conv</span><span class="p">(</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span> <span class="kc">True</span><span class="p">):</span>
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">conv_layer</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Conv2d</span><span class="p">(</span><span class="n">in_channels</span><span class="o">=</span><span class="n">in_channels</span><span class="p">,</span> <span class="n">out_channels</span><span class="o">=</span><span class="n">out_channels</span><span class="p">,</span> <span class="n">kernel_size</span> <span class="o">=</span> <span class="n">kernel_size</span><span class="p">,</span> <span class="n">stride</span> <span class="o">=</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span> <span class="o">=</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span> <span class="o">=</span> <span class="kc">False</span><span class="p">)</span>
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">conv_layer</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">batch_norm</span><span class="p">:</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_channels</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">class</span> <span class="nc">Discriminator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Discriminator Module</span>
<span class="sd">        :param conv_dim: The depth of the first convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Discriminator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>

        <span class="c1"># complete init function</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv1</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv2</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span> 
        <span class="bp">self</span><span class="o">.</span><span class="n">conv3</span> <span class="o">=</span> <span class="n">conv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span> 
        <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">16</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>


    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: Discriminator logits; the output of the neural network</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># define feedforward behavior</span>
        <span class="n">x</span><span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv1</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv2</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">leaky_relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">conv3</span><span class="p">(</span><span class="n">x</span><span class="p">),</span> <span class="mf">0.2</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">16</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">classifier</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">x</span>


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<span class="sd">&quot;&quot;&quot;</span>
<span class="n">tests</span><span class="o">.</span><span class="n">test_discriminator</span><span class="p">(</span><span class="n">Discriminator</span><span class="p">)</span>
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<h2 id="Generator">Generator<a class="anchor-link" href="#Generator">&#182;</a></h2><p>The generator should upsample an input and generate a <em>new</em> image of the same size as our training data <code>32x32x3</code>. This should be mostly transpose convolutional layers with normalization applied to the outputs.</p>
<h4 id="Exercise:-Complete-the-Generator-class">Exercise: Complete the Generator class<a class="anchor-link" href="#Exercise:-Complete-the-Generator-class">&#182;</a></h4><ul>
<li>The inputs to the generator are vectors of some length <code>z_size</code></li>
<li>The output should be a image of shape <code>32x32x3</code></li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">deconv</span><span class="p">(</span><span class="n">in_ch</span><span class="p">,</span> <span class="n">out_ch</span><span class="p">,</span> <span class="n">kernel_s</span><span class="p">,</span> <span class="n">stride</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">padding</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="n">layers</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">ConvTranspose2d</span><span class="p">(</span><span class="n">in_ch</span><span class="p">,</span> <span class="n">out_ch</span><span class="p">,</span> <span class="n">kernel_s</span><span class="p">,</span> <span class="n">stride</span><span class="p">,</span> <span class="n">padding</span><span class="p">,</span> <span class="n">bias</span><span class="o">=</span><span class="kc">False</span><span class="p">))</span>
    <span class="k">if</span> <span class="n">batch_norm</span><span class="p">:</span>
        <span class="n">layers</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">BatchNorm2d</span><span class="p">(</span><span class="n">out_ch</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">nn</span><span class="o">.</span><span class="n">Sequential</span><span class="p">(</span><span class="o">*</span><span class="n">layers</span><span class="p">)</span>

<span class="k">class</span> <span class="nc">Generator</span><span class="p">(</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
    
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Initialize the Generator Module</span>
<span class="sd">        :param z_size: The length of the input latent vector, z</span>
<span class="sd">        :param conv_dim: The depth of the inputs to the *last* transpose convolutional layer</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Generator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>

        <span class="c1"># complete init function</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span> <span class="o">=</span> <span class="n">conv_dim</span>

        <span class="bp">self</span><span class="o">.</span><span class="n">fc</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">Linear</span><span class="p">(</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">16</span><span class="o">*</span><span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv2</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">2</span><span class="p">,</span> <span class="n">conv_dim</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">t_conv3</span> <span class="o">=</span> <span class="n">deconv</span><span class="p">(</span><span class="n">conv_dim</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="n">batch_norm</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
        

    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Forward propagation of the neural network</span>
<span class="sd">        :param x: The input to the neural network     </span>
<span class="sd">        :return: A 32x32x3 Tensor image as output</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="c1"># define feedforward behavior</span>
        <span class="n">x</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fc</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">x</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">conv_dim</span><span class="o">*</span><span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span> <span class="c1"># (batch_size, depth, 4, 4)</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv1</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">F</span><span class="o">.</span><span class="n">relu</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv2</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        <span class="n">x</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tanh</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">t_conv3</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
        
        <span class="k">return</span> <span class="n">x</span>

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<h2 id="Initialize-the-weights-of-your-networks">Initialize the weights of your networks<a class="anchor-link" href="#Initialize-the-weights-of-your-networks">&#182;</a></h2><p>To help your models converge, you should initialize the weights of the convolutional and linear layers in your model. From reading the <a href="https://arxiv.org/pdf/1511.06434.pdf">original DCGAN paper</a>, they say:</p>
<blockquote><p>All weights were initialized from a zero-centered Normal distribution with standard deviation 0.02.</p>
</blockquote>
<p>So, your next task will be to define a weight initialization function that does just this!</p>
<p>You can refer back to the lesson on weight initialization or even consult existing model code, such as that from <a href="https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/models/networks.py">the <code>networks.py</code> file in CycleGAN Github repository</a> to help you complete this function.</p>
<h4 id="Exercise:-Complete-the-weight-initialization-function">Exercise: Complete the weight initialization function<a class="anchor-link" href="#Exercise:-Complete-the-weight-initialization-function">&#182;</a></h4><ul>
<li>This should initialize only <strong>convolutional</strong> and <strong>linear</strong> layers</li>
<li>Initialize the weights to a normal distribution, centered around 0, with a standard deviation of 0.02.</li>
<li>The bias terms, if they exist, may be left alone or set to 0.</li>
</ul>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">weights_init_normal</span><span class="p">(</span><span class="n">m</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Applies initial weights to certain layers in a model .</span>
<span class="sd">    The weights are taken from a normal distribution </span>
<span class="sd">    with mean = 0, std dev = 0.02.</span>
<span class="sd">    :param m: A module or layer in a network    </span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1"># classname will be something like:</span>
    <span class="c1"># `Conv`, `BatchNorm2d`, `Linear`, etc.</span>
    <span class="n">classname</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span>
    
    <span class="c1"># TODO: Apply initial weights to convolutional and linear layers</span>
    <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="p">,</span> <span class="s1">&#39;weight&#39;</span><span class="p">)</span> <span class="ow">and</span> <span class="p">(</span><span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Conv&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span> <span class="ow">or</span> <span class="n">classname</span><span class="o">.</span><span class="n">find</span><span class="p">(</span><span class="s1">&#39;Linear&#39;</span><span class="p">)</span> <span class="o">!=</span> <span class="o">-</span><span class="mi">1</span><span class="p">):</span>
        <span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">normal_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">weight</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span> <span class="mf">0.02</span><span class="p">)</span>
        <span class="k">if</span> <span class="nb">hasattr</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="p">,</span> <span class="s1">&#39;data&#39;</span><span class="p">):</span>
            <span class="n">nn</span><span class="o">.</span><span class="n">init</span><span class="o">.</span><span class="n">constant_</span><span class="p">(</span><span class="n">m</span><span class="o">.</span><span class="n">bias</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
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<h2 id="Build-complete-network">Build complete network<a class="anchor-link" href="#Build-complete-network">&#182;</a></h2><p>Define your models' hyperparameters and instantiate the discriminator and generator from the classes defined above. Make sure you've passed in the correct input arguments.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
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<span class="k">def</span> <span class="nf">build_network</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">,</span> <span class="n">g_conv_dim</span><span class="p">,</span> <span class="n">z_size</span><span class="p">):</span>
    <span class="c1"># define discriminator and generator</span>
    <span class="n">D</span> <span class="o">=</span> <span class="n">Discriminator</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">)</span>
    <span class="n">G</span> <span class="o">=</span> <span class="n">Generator</span><span class="p">(</span><span class="n">z_size</span><span class="o">=</span><span class="n">z_size</span><span class="p">,</span> <span class="n">conv_dim</span><span class="o">=</span><span class="n">g_conv_dim</span><span class="p">)</span>

    <span class="c1"># initialize model weights</span>
    <span class="n">D</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init_normal</span><span class="p">)</span>
    <span class="n">G</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">weights_init_normal</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="n">D</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">()</span>
    <span class="nb">print</span><span class="p">(</span><span class="n">G</span><span class="p">)</span>
    
    <span class="k">return</span> <span class="n">D</span><span class="p">,</span> <span class="n">G</span>
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<h4 id="Exercise:-Define-model-hyperparameters">Exercise: Define model hyperparameters<a class="anchor-link" href="#Exercise:-Define-model-hyperparameters">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Define model hyperparams</span>
<span class="n">d_conv_dim</span> <span class="o">=</span> <span class="mi">64</span>
<span class="n">g_conv_dim</span> <span class="o">=</span> <span class="mi">64</span>
<span class="n">z_size</span> <span class="o">=</span> <span class="mi">100</span>

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<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="n">D</span><span class="p">,</span> <span class="n">G</span> <span class="o">=</span> <span class="n">build_network</span><span class="p">(</span><span class="n">d_conv_dim</span><span class="p">,</span> <span class="n">g_conv_dim</span><span class="p">,</span> <span class="n">z_size</span><span class="p">)</span>
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<pre>Discriminator(
  (conv1): Sequential(
    (0): Conv2d(3, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
  (conv2): Sequential(
    (0): Conv2d(64, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (conv3): Sequential(
    (0): Conv2d(128, 256, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (classifier): Linear(in_features=4096, out_features=1, bias=True)
)

Generator(
  (fc): Linear(in_features=100, out_features=4096, bias=True)
  (t_conv1): Sequential(
    (0): ConvTranspose2d(256, 128, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv2): Sequential(
    (0): ConvTranspose2d(128, 64, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
  )
  (t_conv3): Sequential(
    (0): ConvTranspose2d(64, 3, kernel_size=(4, 4), stride=(2, 2), padding=(1, 1), bias=False)
  )
)
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<h3 id="Training-on-GPU">Training on GPU<a class="anchor-link" href="#Training-on-GPU">&#182;</a></h3><p>Check if you can train on GPU. Here, we'll set this as a boolean variable <code>train_on_gpu</code>. Later, you'll be responsible for making sure that</p>
<blockquote><ul>
<li>Models,</li>
<li>Model inputs, and</li>
<li>Loss function arguments</li>
</ul>
</blockquote>
<p>Are moved to GPU, where appropriate.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">torch</span>

<span class="c1"># Check for a GPU</span>
<span class="n">train_on_gpu</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cuda</span><span class="o">.</span><span class="n">is_available</span><span class="p">()</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">train_on_gpu</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;No GPU found. Please use a GPU to train your neural network.&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
    <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Training on GPU!&#39;</span><span class="p">)</span>
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<pre>Training on GPU!
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<h2 id="Discriminator-and-Generator-Losses">Discriminator and Generator Losses<a class="anchor-link" href="#Discriminator-and-Generator-Losses">&#182;</a></h2><p>Now we need to calculate the losses for both types of adversarial networks.</p>
<h3 id="Discriminator-Losses">Discriminator Losses<a class="anchor-link" href="#Discriminator-Losses">&#182;</a></h3><blockquote><ul>
<li>For the discriminator, the total loss is the sum of the losses for real and fake images, <code>d_loss = d_real_loss + d_fake_loss</code>. </li>
<li>Remember that we want the discriminator to output 1 for real images and 0 for fake images, so we need to set up the losses to reflect that.</li>
</ul>
</blockquote>
<h3 id="Generator-Loss">Generator Loss<a class="anchor-link" href="#Generator-Loss">&#182;</a></h3><p>The generator loss will look similar only with flipped labels. The generator's goal is to get the discriminator to <em>think</em> its generated images are <em>real</em>.</p>
<h4 id="Exercise:-Complete-real-and-fake-loss-functions">Exercise: Complete real and fake loss functions<a class="anchor-link" href="#Exercise:-Complete-real-and-fake-loss-functions">&#182;</a></h4><p><strong>You may choose to use either cross entropy or a least squares error loss to complete the following <code>real_loss</code> and <code>fake_loss</code> functions.</strong></p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">real_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being real.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: real loss&#39;&#39;&#39;</span>
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span><span class="o">*</span><span class="mf">0.9</span>
    <span class="c1"># move labels to GPU if available     </span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>

<span class="k">def</span> <span class="nf">fake_loss</span><span class="p">(</span><span class="n">D_out</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Calculates how close discriminator outputs are to being fake.</span>
<span class="sd">       param, D_out: discriminator logits</span>
<span class="sd">       return: fake loss&#39;&#39;&#39;</span>
    <span class="n">batch_size</span> <span class="o">=</span> <span class="n">D_out</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
    <span class="n">labels</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">batch_size</span><span class="p">)</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">labels</span> <span class="o">=</span> <span class="n">labels</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
    <span class="n">criterion</span> <span class="o">=</span> <span class="n">nn</span><span class="o">.</span><span class="n">BCEWithLogitsLoss</span><span class="p">()</span>
    <span class="n">loss</span> <span class="o">=</span> <span class="n">criterion</span><span class="p">(</span><span class="n">D_out</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(),</span> <span class="n">labels</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">loss</span>
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<h2 id="Optimizers">Optimizers<a class="anchor-link" href="#Optimizers">&#182;</a></h2><h4 id="Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">Exercise: Define optimizers for your Discriminator (D) and Generator (G)<a class="anchor-link" href="#Exercise:-Define-optimizers-for-your-Discriminator-(D)-and-Generator-(G)">&#182;</a></h4><p>Define optimizers for your models with appropriate hyperparameters.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">torch.optim</span> <span class="k">as</span> <span class="nn">optim</span>

<span class="c1"># Create optimizers for the discriminator D and generator G</span>
<span class="n">d_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">D</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.0002</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="p">(</span><span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.999</span><span class="p">))</span> 
<span class="n">g_optimizer</span> <span class="o">=</span> <span class="n">optim</span><span class="o">.</span><span class="n">Adam</span><span class="p">(</span><span class="n">G</span><span class="o">.</span><span class="n">parameters</span><span class="p">(),</span> <span class="n">lr</span><span class="o">=</span><span class="mf">0.0002</span><span class="p">,</span> <span class="n">betas</span><span class="o">=</span><span class="p">(</span><span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.999</span><span class="p">))</span>
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<h2 id="Training">Training<a class="anchor-link" href="#Training">&#182;</a></h2><p>Training will involve alternating between training the discriminator and the generator. You'll use your functions <code>real_loss</code> and <code>fake_loss</code> to help you calculate the discriminator losses.</p>
<ul>
<li>You should train the discriminator by alternating on real and fake images</li>
<li>Then the generator, which tries to trick the discriminator and should have an opposing loss function</li>
</ul>
<h4 id="Saving-Samples">Saving Samples<a class="anchor-link" href="#Saving-Samples">&#182;</a></h4><p>You've been given some code to print out some loss statistics and save some generated "fake" samples.</p>

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<h4 id="Exercise:-Complete-the-training-function">Exercise: Complete the training function<a class="anchor-link" href="#Exercise:-Complete-the-training-function">&#182;</a></h4><p>Keep in mind that, if you've moved your models to GPU, you'll also have to move any model inputs to GPU.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">n_epochs</span><span class="p">,</span> <span class="n">print_every</span><span class="o">=</span><span class="mi">50</span><span class="p">):</span>
    <span class="sd">&#39;&#39;&#39;Trains adversarial networks for some number of epochs</span>
<span class="sd">       param, D: the discriminator network</span>
<span class="sd">       param, G: the generator network</span>
<span class="sd">       param, n_epochs: number of epochs to train for</span>
<span class="sd">       param, print_every: when to print and record the models&#39; losses</span>
<span class="sd">       return: D and G losses&#39;&#39;&#39;</span>
    
    <span class="c1"># move models to GPU</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">D</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
        <span class="n">G</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>

    <span class="c1"># keep track of loss and generated, &quot;fake&quot; samples</span>
    <span class="n">samples</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="n">losses</span> <span class="o">=</span> <span class="p">[]</span>

    <span class="c1"># Get some fixed data for sampling. These are images that are held</span>
    <span class="c1"># constant throughout training, and allow us to inspect the model&#39;s performance</span>
    <span class="n">sample_size</span><span class="o">=</span><span class="mi">16</span>
    <span class="n">fixed_z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">(</span><span class="n">sample_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
    <span class="n">fixed_z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">fixed_z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
    <span class="c1"># move z to GPU if available</span>
    <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
        <span class="n">fixed_z</span> <span class="o">=</span> <span class="n">fixed_z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>

    <span class="c1"># epoch training loop</span>
    <span class="k">for</span> <span class="n">epoch</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n_epochs</span><span class="p">):</span>

        <span class="c1"># batch training loop</span>
        <span class="k">for</span> <span class="n">batch_i</span><span class="p">,</span> <span class="p">(</span><span class="n">real_images</span><span class="p">,</span> <span class="n">_</span><span class="p">)</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">celeba_train_loader</span><span class="p">):</span>

            <span class="n">batch_size</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">size</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
            <span class="n">real_images</span> <span class="o">=</span> <span class="n">scale</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>

            <span class="c1"># ===============================================</span>
            <span class="c1">#         YOUR CODE HERE: TRAIN THE NETWORKS</span>
            <span class="c1"># ===============================================</span>
            
            <span class="c1"># 1. Train the discriminator on real and fake images</span>
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">real_images</span> <span class="o">=</span> <span class="n">real_images</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>    
            <span class="n">D_real</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">real_images</span><span class="p">)</span>
            <span class="n">d_real_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_real</span><span class="p">)</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span> <span class="o">=</span> <span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="c1"># move to GPU, if available</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">d_fake_loss</span> <span class="o">=</span> <span class="n">fake_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span>
            <span class="n">d_loss</span> <span class="o">=</span> <span class="n">d_real_loss</span> <span class="o">+</span> <span class="n">d_fake_loss</span>
            <span class="n">d_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">d_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>

            <span class="c1"># 2. Train the generator with an adversarial loss</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">zero_grad</span><span class="p">()</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">size</span> <span class="o">=</span> <span class="p">(</span><span class="n">batch_size</span><span class="p">,</span> <span class="n">z_size</span><span class="p">))</span>
            <span class="n">z</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">z</span><span class="p">)</span><span class="o">.</span><span class="n">float</span><span class="p">()</span>
            <span class="c1"># move to GPU, if available</span>
            <span class="k">if</span> <span class="n">train_on_gpu</span><span class="p">:</span>
                <span class="n">z</span> <span class="o">=</span> <span class="n">z</span><span class="o">.</span><span class="n">cuda</span><span class="p">()</span>
            <span class="n">fake_images</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">z</span><span class="p">)</span>
            <span class="n">D_fake</span> <span class="o">=</span> <span class="n">D</span><span class="p">(</span><span class="n">fake_images</span><span class="p">)</span>
            <span class="n">g_loss</span> <span class="o">=</span> <span class="n">real_loss</span><span class="p">(</span><span class="n">D_fake</span><span class="p">)</span>
            <span class="n">g_loss</span><span class="o">.</span><span class="n">backward</span><span class="p">()</span>
            <span class="n">g_optimizer</span><span class="o">.</span><span class="n">step</span><span class="p">()</span>
            
            <span class="c1"># ===============================================</span>
            <span class="c1">#              END OF YOUR CODE</span>
            <span class="c1"># ===============================================</span>

            <span class="c1"># Print some loss stats</span>
            <span class="k">if</span> <span class="n">batch_i</span> <span class="o">%</span> <span class="n">print_every</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="c1"># append discriminator loss and generator loss</span>
                <span class="n">losses</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">d_loss</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">g_loss</span><span class="o">.</span><span class="n">item</span><span class="p">()))</span>
                <span class="c1"># print discriminator and generator loss</span>
                <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Epoch [</span><span class="si">{:5d}</span><span class="s1">/</span><span class="si">{:5d}</span><span class="s1">] | d_loss: </span><span class="si">{:6.4f}</span><span class="s1"> | g_loss: </span><span class="si">{:6.4f}</span><span class="s1">&#39;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span>
                        <span class="n">epoch</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">n_epochs</span><span class="p">,</span> <span class="n">d_loss</span><span class="o">.</span><span class="n">item</span><span class="p">(),</span> <span class="n">g_loss</span><span class="o">.</span><span class="n">item</span><span class="p">()))</span>


        <span class="c1">## AFTER EACH EPOCH##    </span>
        <span class="c1"># this code assumes your generator is named G, feel free to change the name</span>
        <span class="c1"># generate and save sample, fake images</span>
        <span class="n">G</span><span class="o">.</span><span class="n">eval</span><span class="p">()</span> <span class="c1"># for generating samples</span>
        <span class="n">samples_z</span> <span class="o">=</span> <span class="n">G</span><span class="p">(</span><span class="n">fixed_z</span><span class="p">)</span>
        <span class="n">samples</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">samples_z</span><span class="p">)</span>
        <span class="n">G</span><span class="o">.</span><span class="n">train</span><span class="p">()</span> <span class="c1"># back to training mode</span>

    <span class="c1"># Save training generator samples</span>
    <span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;train_samples.pkl&#39;</span><span class="p">,</span> <span class="s1">&#39;wb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
        <span class="n">pkl</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">samples</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
    
    <span class="c1"># finally return losses</span>
    <span class="k">return</span> <span class="n">losses</span>
</pre></div>

    </div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Set your number of training epochs and train your GAN!</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[19]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># set number of epochs </span>
<span class="n">n_epochs</span> <span class="o">=</span> <span class="mi">30</span>


<span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DON&#39;T MODIFY ANYTHING IN THIS CELL</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="c1"># call training function</span>
<span class="n">losses</span> <span class="o">=</span> <span class="n">train</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">G</span><span class="p">,</span> <span class="n">n_epochs</span><span class="o">=</span><span class="n">n_epochs</span><span class="p">)</span>
</pre></div>

    </div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

    <div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Epoch [    1/   30] | d_loss: 1.4163 | g_loss: 0.9732
Epoch [    1/   30] | d_loss: 0.6484 | g_loss: 3.6041
Epoch [    1/   30] | d_loss: 0.7146 | g_loss: 3.2044
Epoch [    1/   30] | d_loss: 0.8229 | g_loss: 1.3199
Epoch [    1/   30] | d_loss: 1.3677 | g_loss: 2.2726
Epoch [    1/   30] | d_loss: 0.9292 | g_loss: 1.1299
Epoch [    1/   30] | d_loss: 0.8529 | g_loss: 1.3935
Epoch [    1/   30] | d_loss: 1.1183 | g_loss: 0.7649
Epoch [    1/   30] | d_loss: 1.7915 | g_loss: 0.5325
Epoch [    1/   30] | d_loss: 1.1524 | g_loss: 0.8016
Epoch [    1/   30] | d_loss: 1.1248 | g_loss: 1.2953
Epoch [    1/   30] | d_loss: 1.2533 | g_loss: 1.8455
Epoch [    1/   30] | d_loss: 1.2688 | g_loss: 1.8830
Epoch [    1/   30] | d_loss: 1.1398 | g_loss: 1.0276
Epoch [    1/   30] | d_loss: 1.1619 | g_loss: 1.1189
Epoch [    2/   30] | d_loss: 1.1125 | g_loss: 1.1256
Epoch [    2/   30] | d_loss: 1.1362 | g_loss: 1.0490
Epoch [    2/   30] | d_loss: 1.0465 | g_loss: 1.1190
Epoch [    2/   30] | d_loss: 1.1252 | g_loss: 0.9342
Epoch [    2/   30] | d_loss: 1.1728 | g_loss: 1.3026
Epoch [    2/   30] | d_loss: 1.2694 | g_loss: 1.5369
Epoch [    2/   30] | d_loss: 1.0844 | g_loss: 1.2984
Epoch [    2/   30] | d_loss: 1.1399 | g_loss: 1.2693
Epoch [    2/   30] | d_loss: 1.2867 | g_loss: 0.7182
Epoch [    2/   30] | d_loss: 1.1678 | g_loss: 1.0375
Epoch [    2/   30] | d_loss: 1.2220 | g_loss: 0.7005
Epoch [    2/   30] | d_loss: 1.2170 | g_loss: 0.8755
Epoch [    2/   30] | d_loss: 1.1192 | g_loss: 1.0262
Epoch [    2/   30] | d_loss: 1.1716 | g_loss: 0.7538
Epoch [    2/   30] | d_loss: 1.1359 | g_loss: 0.9903
Epoch [    3/   30] | d_loss: 1.1014 | g_loss: 1.0974
Epoch [    3/   30] | d_loss: 1.2340 | g_loss: 0.8186
Epoch [    3/   30] | d_loss: 1.2061 | g_loss: 1.1866
Epoch [    3/   30] | d_loss: 1.0886 | g_loss: 0.9804
Epoch [    3/   30] | d_loss: 1.1047 | g_loss: 1.2196
Epoch [    3/   30] | d_loss: 1.1499 | g_loss: 0.9854
Epoch [    3/   30] | d_loss: 1.2827 | g_loss: 0.9722
Epoch [    3/   30] | d_loss: 1.1465 | g_loss: 0.8123
Epoch [    3/   30] | d_loss: 1.2496 | g_loss: 0.9111
Epoch [    3/   30] | d_loss: 1.1840 | g_loss: 1.1455
Epoch [    3/   30] | d_loss: 1.1764 | g_loss: 1.3340
Epoch [    3/   30] | d_loss: 1.2773 | g_loss: 0.5926
Epoch [    3/   30] | d_loss: 1.0939 | g_loss: 1.1996
Epoch [    3/   30] | d_loss: 1.0644 | g_loss: 1.2512
Epoch [    3/   30] | d_loss: 1.1087 | g_loss: 0.9215
Epoch [    4/   30] | d_loss: 1.0792 | g_loss: 0.8114
Epoch [    4/   30] | d_loss: 1.1390 | g_loss: 0.9836
Epoch [    4/   30] | d_loss: 1.1142 | g_loss: 0.8760
Epoch [    4/   30] | d_loss: 1.1601 | g_loss: 1.1379
Epoch [    4/   30] | d_loss: 1.0356 | g_loss: 1.5288
Epoch [    4/   30] | d_loss: 1.0953 | g_loss: 0.8255
Epoch [    4/   30] | d_loss: 1.1266 | g_loss: 0.9302
Epoch [    4/   30] | d_loss: 1.0932 | g_loss: 0.9250
Epoch [    4/   30] | d_loss: 1.0571 | g_loss: 0.8970
Epoch [    4/   30] | d_loss: 1.2487 | g_loss: 0.8363
Epoch [    4/   30] | d_loss: 1.1223 | g_loss: 0.9185
Epoch [    4/   30] | d_loss: 1.0020 | g_loss: 1.1302
Epoch [    4/   30] | d_loss: 1.0124 | g_loss: 0.9924
Epoch [    4/   30] | d_loss: 1.1282 | g_loss: 0.9111
Epoch [    4/   30] | d_loss: 1.1275 | g_loss: 1.1711
Epoch [    5/   30] | d_loss: 1.1193 | g_loss: 0.9006
Epoch [    5/   30] | d_loss: 1.1228 | g_loss: 1.1246
Epoch [    5/   30] | d_loss: 1.1923 | g_loss: 1.7984
Epoch [    5/   30] | d_loss: 1.0036 | g_loss: 1.2323
Epoch [    5/   30] | d_loss: 1.1081 | g_loss: 0.8448
Epoch [    6/   30] | d_loss: 1.1406 | g_loss: 1.1230
Epoch [    6/   30] | d_loss: 1.1465 | g_loss: 0.9538
Epoch [    6/   30] | d_loss: 1.1923 | g_loss: 0.8765
Epoch [    6/   30] | d_loss: 1.1121 | g_loss: 1.3103
Epoch [    6/   30] | d_loss: 1.2776 | g_loss: 1.2722
Epoch [    6/   30] | d_loss: 1.2886 | g_loss: 1.3540
Epoch [    6/   30] | d_loss: 1.0968 | g_loss: 0.8339
Epoch [    6/   30] | d_loss: 1.0670 | g_loss: 1.3746
Epoch [    6/   30] | d_loss: 1.1489 | g_loss: 1.2891
Epoch [    6/   30] | d_loss: 1.0497 | g_loss: 0.9960
Epoch [    6/   30] | d_loss: 1.1883 | g_loss: 0.9221
Epoch [    6/   30] | d_loss: 1.0840 | g_loss: 1.0466
Epoch [    7/   30] | d_loss: 1.1113 | g_loss: 1.2898
Epoch [    7/   30] | d_loss: 1.0115 | g_loss: 1.0643
Epoch [    7/   30] | d_loss: 1.0560 | g_loss: 1.1609
Epoch [    7/   30] | d_loss: 1.0844 | g_loss: 0.9665
Epoch [    7/   30] | d_loss: 0.9949 | g_loss: 1.0481
Epoch [    7/   30] | d_loss: 1.0553 | g_loss: 1.2102
Epoch [    7/   30] | d_loss: 1.0632 | g_loss: 1.1997
Epoch [    7/   30] | d_loss: 1.0458 | g_loss: 1.2593
Epoch [    7/   30] | d_loss: 1.4761 | g_loss: 1.6195
Epoch [    7/   30] | d_loss: 1.1631 | g_loss: 1.2043
Epoch [    7/   30] | d_loss: 1.0406 | g_loss: 0.8412
Epoch [    7/   30] | d_loss: 1.1385 | g_loss: 1.1748
Epoch [    7/   30] | d_loss: 1.1729 | g_loss: 0.8487
Epoch [    7/   30] | d_loss: 1.2401 | g_loss: 0.6519
Epoch [    7/   30] | d_loss: 0.9892 | g_loss: 1.0945
Epoch [    8/   30] | d_loss: 1.0371 | g_loss: 1.2000
Epoch [    8/   30] | d_loss: 1.2157 | g_loss: 1.4648
Epoch [    8/   30] | d_loss: 1.1497 | g_loss: 0.7926
Epoch [    8/   30] | d_loss: 1.1108 | g_loss: 0.9357
Epoch [    8/   30] | d_loss: 1.2267 | g_loss: 0.6026
Epoch [    8/   30] | d_loss: 1.1009 | g_loss: 1.0944
Epoch [    8/   30] | d_loss: 1.1383 | g_loss: 1.1767
Epoch [    8/   30] | d_loss: 1.2184 | g_loss: 0.9321
Epoch [    8/   30] | d_loss: 1.0610 | g_loss: 1.1464
Epoch [    8/   30] | d_loss: 1.3097 | g_loss: 0.6740
Epoch [    8/   30] | d_loss: 1.2178 | g_loss: 1.6595
Epoch [    8/   30] | d_loss: 1.1317 | g_loss: 0.9554
Epoch [    8/   30] | d_loss: 1.4765 | g_loss: 1.9320
Epoch [    8/   30] | d_loss: 1.1177 | g_loss: 0.7593
Epoch [    8/   30] | d_loss: 1.0753 | g_loss: 1.2052
Epoch [    9/   30] | d_loss: 1.0877 | g_loss: 1.2228
Epoch [    9/   30] | d_loss: 1.0556 | g_loss: 1.0463
Epoch [    9/   30] | d_loss: 1.0897 | g_loss: 1.1512
Epoch [    9/   30] | d_loss: 1.5037 | g_loss: 2.2627
Epoch [    9/   30] | d_loss: 1.0453 | g_loss: 1.0561
Epoch [    9/   30] | d_loss: 1.1182 | g_loss: 0.8169
Epoch [    9/   30] | d_loss: 1.0895 | g_loss: 0.9533
Epoch [    9/   30] | d_loss: 1.1548 | g_loss: 1.3240
Epoch [    9/   30] | d_loss: 1.1044 | g_loss: 1.2076
Epoch [    9/   30] | d_loss: 1.1514 | g_loss: 1.5784
Epoch [    9/   30] | d_loss: 1.0534 | g_loss: 1.1244
Epoch [    9/   30] | d_loss: 1.3173 | g_loss: 1.5742
Epoch [    9/   30] | d_loss: 1.0663 | g_loss: 1.0949
Epoch [    9/   30] | d_loss: 1.0321 | g_loss: 1.5189
Epoch [    9/   30] | d_loss: 1.1899 | g_loss: 0.6562
Epoch [   10/   30] | d_loss: 1.5206 | g_loss: 2.3812
Epoch [   10/   30] | d_loss: 1.8025 | g_loss: 0.6602
Epoch [   10/   30] | d_loss: 1.0558 | g_loss: 1.6582
Epoch [   10/   30] | d_loss: 1.3137 | g_loss: 1.8393
Epoch [   10/   30] | d_loss: 1.0190 | g_loss: 1.1186
Epoch [   10/   30] | d_loss: 1.0672 | g_loss: 1.0237
Epoch [   10/   30] | d_loss: 1.1986 | g_loss: 0.8544
Epoch [   10/   30] | d_loss: 1.0095 | g_loss: 1.2982
Epoch [   10/   30] | d_loss: 1.0083 | g_loss: 1.1047
Epoch [   10/   30] | d_loss: 1.1870 | g_loss: 1.1345
Epoch [   10/   30] | d_loss: 0.9569 | g_loss: 1.3614
Epoch [   10/   30] | d_loss: 1.0733 | g_loss: 1.5730
Epoch [   10/   30] | d_loss: 1.1122 | g_loss: 1.0643
Epoch [   10/   30] | d_loss: 1.1695 | g_loss: 1.6987
Epoch [   10/   30] | d_loss: 0.9483 | g_loss: 0.9393
Epoch [   11/   30] | d_loss: 1.1093 | g_loss: 1.8418
Epoch [   11/   30] | d_loss: 0.9710 | g_loss: 1.4419
Epoch [   11/   30] | d_loss: 1.0127 | g_loss: 1.3291
Epoch [   11/   30] | d_loss: 1.0599 | g_loss: 1.2890
Epoch [   11/   30] | d_loss: 1.0188 | g_loss: 1.5732
Epoch [   11/   30] | d_loss: 1.2794 | g_loss: 1.9547
Epoch [   11/   30] | d_loss: 1.1997 | g_loss: 1.2084
Epoch [   11/   30] | d_loss: 0.9819 | g_loss: 1.2507
Epoch [   11/   30] | d_loss: 1.0274 | g_loss: 1.0079
Epoch [   11/   30] | d_loss: 1.0504 | g_loss: 1.4699
Epoch [   11/   30] | d_loss: 1.3261 | g_loss: 0.7689
Epoch [   11/   30] | d_loss: 1.3751 | g_loss: 2.4914
Epoch [   11/   30] | d_loss: 0.9413 | g_loss: 1.2844
Epoch [   11/   30] | d_loss: 1.0540 | g_loss: 1.3472
Epoch [   11/   30] | d_loss: 0.9242 | g_loss: 1.2153
Epoch [   12/   30] | d_loss: 0.9774 | g_loss: 1.0907
Epoch [   12/   30] | d_loss: 1.0453 | g_loss: 1.1170
Epoch [   12/   30] | d_loss: 1.7017 | g_loss: 2.5800
Epoch [   12/   30] | d_loss: 1.2577 | g_loss: 0.7803
Epoch [   12/   30] | d_loss: 0.9488 | g_loss: 1.4522
Epoch [   12/   30] | d_loss: 0.9845 | g_loss: 1.0841
Epoch [   12/   30] | d_loss: 0.9772 | g_loss: 1.1810
Epoch [   12/   30] | d_loss: 0.9856 | g_loss: 1.2134
Epoch [   12/   30] | d_loss: 1.0383 | g_loss: 1.1478
Epoch [   12/   30] | d_loss: 1.0002 | g_loss: 0.9283
Epoch [   12/   30] | d_loss: 0.9496 | g_loss: 1.3066
Epoch [   12/   30] | d_loss: 1.1767 | g_loss: 1.7504
Epoch [   12/   30] | d_loss: 0.8946 | g_loss: 1.2265
Epoch [   12/   30] | d_loss: 1.4223 | g_loss: 2.0788
Epoch [   12/   30] | d_loss: 0.8700 | g_loss: 0.8008
Epoch [   13/   30] | d_loss: 1.3152 | g_loss: 2.7188
Epoch [   13/   30] | d_loss: 0.8911 | g_loss: 1.3004
Epoch [   13/   30] | d_loss: 1.0605 | g_loss: 1.8945
Epoch [   13/   30] | d_loss: 1.1545 | g_loss: 1.6592
Epoch [   13/   30] | d_loss: 0.9443 | g_loss: 0.9389
Epoch [   13/   30] | d_loss: 1.0050 | g_loss: 1.5454
Epoch [   13/   30] | d_loss: 0.9190 | g_loss: 1.5693
Epoch [   13/   30] | d_loss: 1.0274 | g_loss: 2.0174
Epoch [   13/   30] | d_loss: 1.1585 | g_loss: 0.6603
Epoch [   13/   30] | d_loss: 1.0609 | g_loss: 1.8280
Epoch [   13/   30] | d_loss: 1.0070 | g_loss: 1.6330
Epoch [   13/   30] | d_loss: 0.8646 | g_loss: 1.6078
Epoch [   13/   30] | d_loss: 0.8490 | g_loss: 1.5487
Epoch [   13/   30] | d_loss: 0.8848 | g_loss: 1.2145
Epoch [   13/   30] | d_loss: 0.8983 | g_loss: 1.0534
Epoch [   14/   30] | d_loss: 1.0160 | g_loss: 1.0099
Epoch [   14/   30] | d_loss: 0.9832 | g_loss: 0.8644
Epoch [   14/   30] | d_loss: 1.0004 | g_loss: 1.8258
Epoch [   14/   30] | d_loss: 0.9274 | g_loss: 1.1376
Epoch [   14/   30] | d_loss: 0.9958 | g_loss: 1.6482
Epoch [   14/   30] | d_loss: 0.8642 | g_loss: 1.1932
Epoch [   14/   30] | d_loss: 1.0758 | g_loss: 0.9580
Epoch [   14/   30] | d_loss: 0.9565 | g_loss: 1.1676
Epoch [   14/   30] | d_loss: 1.1047 | g_loss: 1.8078
Epoch [   14/   30] | d_loss: 1.1696 | g_loss: 2.3004
Epoch [   14/   30] | d_loss: 0.8834 | g_loss: 1.5361
Epoch [   14/   30] | d_loss: 0.7827 | g_loss: 1.4719
Epoch [   14/   30] | d_loss: 0.9283 | g_loss: 1.4238
Epoch [   14/   30] | d_loss: 0.9225 | g_loss: 1.4049
Epoch [   14/   30] | d_loss: 0.8044 | g_loss: 1.2605
Epoch [   15/   30] | d_loss: 0.8853 | g_loss: 2.0712
Epoch [   15/   30] | d_loss: 0.8283 | g_loss: 1.5698
Epoch [   15/   30] | d_loss: 0.8910 | g_loss: 1.4360
Epoch [   15/   30] | d_loss: 0.9978 | g_loss: 1.0923
Epoch [   15/   30] | d_loss: 0.7566 | g_loss: 1.2488
Epoch [   15/   30] | d_loss: 0.8601 | g_loss: 1.2757
Epoch [   15/   30] | d_loss: 0.9375 | g_loss: 1.2737
Epoch [   15/   30] | d_loss: 1.3662 | g_loss: 2.1720
Epoch [   15/   30] | d_loss: 0.8651 | g_loss: 1.7633
Epoch [   15/   30] | d_loss: 0.9090 | g_loss: 1.0765
Epoch [   15/   30] | d_loss: 0.8585 | g_loss: 1.6671
Epoch [   15/   30] | d_loss: 0.7759 | g_loss: 1.5457
Epoch [   15/   30] | d_loss: 0.9399 | g_loss: 1.4294
Epoch [   15/   30] | d_loss: 0.8531 | g_loss: 1.1056
Epoch [   15/   30] | d_loss: 0.7299 | g_loss: 2.0598
Epoch [   16/   30] | d_loss: 0.8547 | g_loss: 1.2371
Epoch [   16/   30] | d_loss: 0.8743 | g_loss: 1.6882
Epoch [   16/   30] | d_loss: 0.8473 | g_loss: 1.1834
Epoch [   16/   30] | d_loss: 0.8631 | g_loss: 1.2036
Epoch [   16/   30] | d_loss: 0.8624 | g_loss: 1.2638
Epoch [   16/   30] | d_loss: 0.8860 | g_loss: 1.0043
Epoch [   16/   30] | d_loss: 1.0716 | g_loss: 1.0531
Epoch [   16/   30] | d_loss: 0.7352 | g_loss: 1.8368
Epoch [   16/   30] | d_loss: 0.8940 | g_loss: 1.0585
Epoch [   16/   30] | d_loss: 0.7522 | g_loss: 1.6751
Epoch [   16/   30] | d_loss: 2.0134 | g_loss: 0.6462
Epoch [   16/   30] | d_loss: 0.9823 | g_loss: 1.3514
Epoch [   16/   30] | d_loss: 1.0514 | g_loss: 0.8442
Epoch [   16/   30] | d_loss: 0.8151 | g_loss: 1.5000
Epoch [   16/   30] | d_loss: 0.9236 | g_loss: 2.3659
Epoch [   17/   30] | d_loss: 0.8792 | g_loss: 1.2284
Epoch [   17/   30] | d_loss: 0.7866 | g_loss: 1.7435
Epoch [   17/   30] | d_loss: 0.8107 | g_loss: 1.3060
Epoch [   17/   30] | d_loss: 0.7911 | g_loss: 2.0041
Epoch [   17/   30] | d_loss: 0.8919 | g_loss: 1.8393
Epoch [   17/   30] | d_loss: 1.4075 | g_loss: 0.7503
Epoch [   17/   30] | d_loss: 0.9896 | g_loss: 2.2000
Epoch [   17/   30] | d_loss: 0.8586 | g_loss: 1.6801
Epoch [   17/   30] | d_loss: 1.2079 | g_loss: 0.8745
Epoch [   17/   30] | d_loss: 0.9888 | g_loss: 0.7970
Epoch [   17/   30] | d_loss: 0.8831 | g_loss: 0.9526
Epoch [   17/   30] | d_loss: 0.8694 | g_loss: 2.0752
Epoch [   17/   30] | d_loss: 0.8590 | g_loss: 2.6306
Epoch [   17/   30] | d_loss: 0.7589 | g_loss: 1.5733
Epoch [   17/   30] | d_loss: 0.7423 | g_loss: 1.4682
Epoch [   18/   30] | d_loss: 0.7078 | g_loss: 1.5783
Epoch [   18/   30] | d_loss: 1.1613 | g_loss: 2.5673
Epoch [   18/   30] | d_loss: 0.8083 | g_loss: 1.2569
Epoch [   18/   30] | d_loss: 1.0047 | g_loss: 1.1279
Epoch [   18/   30] | d_loss: 0.7887 | g_loss: 1.1680
Epoch [   18/   30] | d_loss: 0.7093 | g_loss: 1.3033
Epoch [   18/   30] | d_loss: 0.6902 | g_loss: 2.0943
Epoch [   18/   30] | d_loss: 1.2363 | g_loss: 0.7548
Epoch [   18/   30] | d_loss: 0.9304 | g_loss: 1.0020
Epoch [   18/   30] | d_loss: 1.0083 | g_loss: 1.0655
Epoch [   18/   30] | d_loss: 0.9626 | g_loss: 1.3367
Epoch [   18/   30] | d_loss: 0.9956 | g_loss: 2.0750
Epoch [   18/   30] | d_loss: 1.0578 | g_loss: 0.8512
Epoch [   18/   30] | d_loss: 1.2345 | g_loss: 0.6968
Epoch [   19/   30] | d_loss: 0.8108 | g_loss: 1.4820
Epoch [   19/   30] | d_loss: 0.7942 | g_loss: 1.9899
Epoch [   19/   30] | d_loss: 1.5514 | g_loss: 0.9290
Epoch [   19/   30] | d_loss: 0.7958 | g_loss: 1.7276
Epoch [   20/   30] | d_loss: 0.7300 | g_loss: 1.9711
Epoch [   20/   30] | d_loss: 0.6955 | g_loss: 1.4185
Epoch [   20/   30] | d_loss: 0.8420 | g_loss: 2.1487
Epoch [   20/   30] | d_loss: 0.7328 | g_loss: 2.0209
Epoch [   20/   30] | d_loss: 0.9038 | g_loss: 1.3228
Epoch [   20/   30] | d_loss: 0.6992 | g_loss: 1.6803
Epoch [   20/   30] | d_loss: 0.8520 | g_loss: 1.4169
Epoch [   20/   30] | d_loss: 0.8049 | g_loss: 1.8920
Epoch [   20/   30] | d_loss: 0.7393 | g_loss: 2.3488
Epoch [   20/   30] | d_loss: 0.8858 | g_loss: 1.0757
Epoch [   20/   30] | d_loss: 1.0653 | g_loss: 0.7106
Epoch [   20/   30] | d_loss: 0.8076 | g_loss: 1.7839
Epoch [   20/   30] | d_loss: 0.7977 | g_loss: 1.1864
Epoch [   20/   30] | d_loss: 0.7328 | g_loss: 1.7801
Epoch [   20/   30] | d_loss: 0.8293 | g_loss: 1.2676
Epoch [   21/   30] | d_loss: 0.7015 | g_loss: 2.2792
Epoch [   21/   30] | d_loss: 0.6314 | g_loss: 1.5548
Epoch [   21/   30] | d_loss: 1.1821 | g_loss: 0.7774
Epoch [   21/   30] | d_loss: 0.9858 | g_loss: 0.8063
Epoch [   21/   30] | d_loss: 1.1330 | g_loss: 2.4111
Epoch [   21/   30] | d_loss: 0.5936 | g_loss: 1.8239
Epoch [   21/   30] | d_loss: 0.6908 | g_loss: 1.3396
Epoch [   21/   30] | d_loss: 1.1116 | g_loss: 2.0180
Epoch [   21/   30] | d_loss: 1.1290 | g_loss: 2.6318
Epoch [   21/   30] | d_loss: 0.7174 | g_loss: 1.8046
Epoch [   21/   30] | d_loss: 0.6493 | g_loss: 1.9356
Epoch [   21/   30] | d_loss: 0.7103 | g_loss: 2.2721
Epoch [   21/   30] | d_loss: 1.3207 | g_loss: 0.9494
Epoch [   21/   30] | d_loss: 0.5610 | g_loss: 1.6068
Epoch [   21/   30] | d_loss: 0.9956 | g_loss: 2.0134
Epoch [   22/   30] | d_loss: 1.0781 | g_loss: 0.7754
Epoch [   22/   30] | d_loss: 0.6334 | g_loss: 1.7974
Epoch [   22/   30] | d_loss: 1.3889 | g_loss: 1.0207
Epoch [   22/   30] | d_loss: 0.7432 | g_loss: 2.3824
Epoch [   22/   30] | d_loss: 0.7900 | g_loss: 1.3477
Epoch [   22/   30] | d_loss: 1.1534 | g_loss: 3.1911
Epoch [   22/   30] | d_loss: 0.7274 | g_loss: 1.1840
Epoch [   22/   30] | d_loss: 1.1343 | g_loss: 2.0271
Epoch [   22/   30] | d_loss: 0.8408 | g_loss: 1.3085
Epoch [   22/   30] | d_loss: 0.8131 | g_loss: 1.6099
Epoch [   22/   30] | d_loss: 0.6639 | g_loss: 1.9895
Epoch [   22/   30] | d_loss: 0.6976 | g_loss: 1.7421
Epoch [   22/   30] | d_loss: 1.0648 | g_loss: 1.0624
Epoch [   22/   30] | d_loss: 0.7098 | g_loss: 2.4176
Epoch [   22/   30] | d_loss: 0.6392 | g_loss: 1.6749
Epoch [   23/   30] | d_loss: 0.6399 | g_loss: 2.4643
Epoch [   23/   30] | d_loss: 0.7666 | g_loss: 2.3626
Epoch [   23/   30] | d_loss: 1.1332 | g_loss: 1.8697
Epoch [   23/   30] | d_loss: 0.6773 | g_loss: 1.6100
Epoch [   23/   30] | d_loss: 0.5452 | g_loss: 1.6722
Epoch [   23/   30] | d_loss: 1.5500 | g_loss: 0.8063
Epoch [   23/   30] | d_loss: 1.4498 | g_loss: 0.8978
Epoch [   23/   30] | d_loss: 1.6129 | g_loss: 1.4089
Epoch [   23/   30] | d_loss: 1.1908 | g_loss: 1.8145
Epoch [   23/   30] | d_loss: 0.6786 | g_loss: 1.9299
Epoch [   23/   30] | d_loss: 0.7843 | g_loss: 1.6259
Epoch [   23/   30] | d_loss: 0.7212 | g_loss: 2.0608
Epoch [   23/   30] | d_loss: 0.6834 | g_loss: 1.7714
Epoch [   23/   30] | d_loss: 0.6863 | g_loss: 1.7365
Epoch [   23/   30] | d_loss: 0.9065 | g_loss: 2.6481
Epoch [   24/   30] | d_loss: 0.7898 | g_loss: 1.3991
Epoch [   24/   30] | d_loss: 0.6767 | g_loss: 2.4474
Epoch [   24/   30] | d_loss: 0.6663 | g_loss: 1.4137
Epoch [   24/   30] | d_loss: 1.1645 | g_loss: 0.5703
Epoch [   24/   30] | d_loss: 0.6979 | g_loss: 1.6709
Epoch [   24/   30] | d_loss: 0.6123 | g_loss: 2.5622
Epoch [   24/   30] | d_loss: 0.8905 | g_loss: 3.1970
Epoch [   24/   30] | d_loss: 0.5491 | g_loss: 2.0105
Epoch [   24/   30] | d_loss: 0.6835 | g_loss: 2.2028
Epoch [   24/   30] | d_loss: 1.5222 | g_loss: 2.7852
Epoch [   24/   30] | d_loss: 1.0478 | g_loss: 1.0288
Epoch [   24/   30] | d_loss: 0.7701 | g_loss: 2.5719
Epoch [   24/   30] | d_loss: 0.9096 | g_loss: 2.8232
Epoch [   24/   30] | d_loss: 0.7748 | g_loss: 2.8616
Epoch [   24/   30] | d_loss: 0.8875 | g_loss: 2.5466
Epoch [   25/   30] | d_loss: 0.6706 | g_loss: 1.8292
Epoch [   25/   30] | d_loss: 0.5951 | g_loss: 1.6363
Epoch [   25/   30] | d_loss: 0.5982 | g_loss: 1.7398
Epoch [   25/   30] | d_loss: 1.0417 | g_loss: 0.9539
Epoch [   25/   30] | d_loss: 0.6409 | g_loss: 2.0635
Epoch [   25/   30] | d_loss: 1.3614 | g_loss: 1.0145
Epoch [   25/   30] | d_loss: 0.6724 | g_loss: 1.7418
Epoch [   25/   30] | d_loss: 0.7410 | g_loss: 2.9064
Epoch [   25/   30] | d_loss: 0.8402 | g_loss: 1.1347
Epoch [   25/   30] | d_loss: 0.6421 | g_loss: 1.7071
Epoch [   25/   30] | d_loss: 0.6867 | g_loss: 2.4764
Epoch [   25/   30] | d_loss: 0.8246 | g_loss: 2.7270
Epoch [   25/   30] | d_loss: 0.5715 | g_loss: 2.6195
Epoch [   25/   30] | d_loss: 0.6195 | g_loss: 2.1261
Epoch [   25/   30] | d_loss: 0.7253 | g_loss: 2.3209
Epoch [   26/   30] | d_loss: 0.6431 | g_loss: 1.8679
Epoch [   26/   30] | d_loss: 0.5486 | g_loss: 2.2509
Epoch [   26/   30] | d_loss: 0.5868 | g_loss: 2.1403
Epoch [   26/   30] | d_loss: 1.4917 | g_loss: 1.5397
Epoch [   26/   30] | d_loss: 0.7494 | g_loss: 1.2139
Epoch [   26/   30] | d_loss: 0.6004 | g_loss: 1.5971
Epoch [   26/   30] | d_loss: 0.6605 | g_loss: 1.3502
Epoch [   26/   30] | d_loss: 1.4176 | g_loss: 1.1397
Epoch [   26/   30] | d_loss: 0.6317 | g_loss: 2.5736
Epoch [   26/   30] | d_loss: 0.6641 | g_loss: 1.6743
Epoch [   26/   30] | d_loss: 1.0032 | g_loss: 1.0669
Epoch [   26/   30] | d_loss: 0.5560 | g_loss: 2.2545
Epoch [   26/   30] | d_loss: 0.6109 | g_loss: 1.4363
Epoch [   26/   30] | d_loss: 0.6953 | g_loss: 1.5843
Epoch [   26/   30] | d_loss: 0.5374 | g_loss: 2.1452
Epoch [   27/   30] | d_loss: 0.4978 | g_loss: 1.9177
Epoch [   27/   30] | d_loss: 0.5113 | g_loss: 2.0669
Epoch [   27/   30] | d_loss: 0.7057 | g_loss: 2.7888
Epoch [   27/   30] | d_loss: 0.5923 | g_loss: 1.8538
Epoch [   27/   30] | d_loss: 0.7858 | g_loss: 1.8739
Epoch [   27/   30] | d_loss: 0.6745 | g_loss: 2.6973
Epoch [   27/   30] | d_loss: 0.5814 | g_loss: 2.2917
Epoch [   27/   30] | d_loss: 0.5697 | g_loss: 2.1319
Epoch [   27/   30] | d_loss: 0.5487 | g_loss: 1.7540
Epoch [   27/   30] | d_loss: 0.7763 | g_loss: 2.8566
Epoch [   27/   30] | d_loss: 0.5074 | g_loss: 2.3100
Epoch [   27/   30] | d_loss: 0.5819 | g_loss: 2.0430
Epoch [   27/   30] | d_loss: 0.6446 | g_loss: 1.5642
Epoch [   27/   30] | d_loss: 0.5396 | g_loss: 2.0639
Epoch [   27/   30] | d_loss: 1.5163 | g_loss: 1.9802
Epoch [   28/   30] | d_loss: 0.7176 | g_loss: 2.2461
Epoch [   28/   30] | d_loss: 0.5087 | g_loss: 2.2338
Epoch [   28/   30] | d_loss: 0.8431 | g_loss: 2.7540
Epoch [   28/   30] | d_loss: 0.6919 | g_loss: 1.2845
Epoch [   28/   30] | d_loss: 1.2073 | g_loss: 1.0724
Epoch [   28/   30] | d_loss: 2.5942 | g_loss: 3.8589
Epoch [   28/   30] | d_loss: 0.6351 | g_loss: 1.7188
Epoch [   28/   30] | d_loss: 0.6510 | g_loss: 2.9044
Epoch [   28/   30] | d_loss: 0.5427 | g_loss: 2.3343
Epoch [   28/   30] | d_loss: 0.5879 | g_loss: 1.8236
Epoch [   28/   30] | d_loss: 0.6423 | g_loss: 1.5682
Epoch [   28/   30] | d_loss: 0.7359 | g_loss: 1.6043
Epoch [   28/   30] | d_loss: 0.5618 | g_loss: 2.6877
Epoch [   28/   30] | d_loss: 0.5231 | g_loss: 2.2745
Epoch [   28/   30] | d_loss: 0.6513 | g_loss: 2.2698
Epoch [   29/   30] | d_loss: 0.6270 | g_loss: 1.8825
Epoch [   29/   30] | d_loss: 0.6032 | g_loss: 1.9919
Epoch [   29/   30] | d_loss: 0.5595 | g_loss: 2.0732
Epoch [   29/   30] | d_loss: 0.8972 | g_loss: 0.8369
Epoch [   29/   30] | d_loss: 0.5627 | g_loss: 1.7591
Epoch [   29/   30] | d_loss: 0.5324 | g_loss: 2.4182
Epoch [   29/   30] | d_loss: 0.7483 | g_loss: 2.7673
Epoch [   29/   30] | d_loss: 0.6600 | g_loss: 2.4129
Epoch [   29/   30] | d_loss: 0.5693 | g_loss: 1.9657
Epoch [   29/   30] | d_loss: 0.6966 | g_loss: 1.5330
Epoch [   29/   30] | d_loss: 0.4565 | g_loss: 2.6803
Epoch [   29/   30] | d_loss: 0.6972 | g_loss: 3.1186
Epoch [   29/   30] | d_loss: 0.9398 | g_loss: 1.1033
Epoch [   29/   30] | d_loss: 0.5365 | g_loss: 3.0471
Epoch [   29/   30] | d_loss: 0.5582 | g_loss: 2.7457
Epoch [   30/   30] | d_loss: 0.4875 | g_loss: 2.3242
Epoch [   30/   30] | d_loss: 0.5762 | g_loss: 2.2304
Epoch [   30/   30] | d_loss: 0.6063 | g_loss: 2.1497
Epoch [   30/   30] | d_loss: 0.5183 | g_loss: 2.1894
Epoch [   30/   30] | d_loss: 0.5378 | g_loss: 2.1857
Epoch [   30/   30] | d_loss: 0.7649 | g_loss: 1.1636
Epoch [   30/   30] | d_loss: 0.5818 | g_loss: 2.5111
Epoch [   30/   30] | d_loss: 0.5900 | g_loss: 1.5964
Epoch [   30/   30] | d_loss: 0.6129 | g_loss: 1.4287
Epoch [   30/   30] | d_loss: 1.4531 | g_loss: 1.0767
Epoch [   30/   30] | d_loss: 0.5418 | g_loss: 2.3317
Epoch [   30/   30] | d_loss: 0.5472 | g_loss: 2.3874
Epoch [   30/   30] | d_loss: 0.4948 | g_loss: 2.3442
Epoch [   30/   30] | d_loss: 0.5167 | g_loss: 2.2185
Epoch [   30/   30] | d_loss: 0.7261 | g_loss: 1.4600
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<h2 id="Training-loss">Training loss<a class="anchor-link" href="#Training-loss">&#182;</a></h2><p>Plot the training losses for the generator and discriminator, recorded after each epoch.</p>

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<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[20]:</div>
<div class="inner_cell">
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
<span class="n">losses</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">losses</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Discriminator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">losses</span><span class="o">.</span><span class="n">T</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Generator&#39;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Training Losses&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">()</span>
</pre></div>

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    <div class="prompt output_prompt">Out[20]:</div>


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<pre>&lt;matplotlib.legend.Legend at 0x7f25be8d6860&gt;</pre>
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edi7dq12rbk1Lo33ngjbrrpJrzvfe/DmocewC3/9NVM/ZUzVY5Fqt56IZPmTkQ5InoewDEAv2PmdZpi/5OIthDRfUSkHQKJ6JNEtIGINnR0dIyi2y6cyTeJYWBgUB3e9KY3oVgs4s477/S3eel73/72t+POO+9EuVwGIGSQwcHB2LrOPPNMdHR0+OReLpe1i2cA4i1g8eLFAIAf/se9/nY5VS8gFsm+916x/8c//jGuuOKKWk5z3JGJ3JnZZuZVAJYAuISIzlOK/AbAMmZeCeBhAD+MqecuZl7NzKvnz58/mn4LOHZ6GQMDg0kNIsL999+Pxx57DMuXL8cll1yC66+/Hl/96lfxiU98Aueccw4uvPBCnHfeefjUpz6V6JnS1NSE++67DzfffDPOP/98rFq1Ktbz5ZZbbsE111yD17/+9ZjnLanHQmP/1a9+5U+o3n777fj+97+PlStX4p577sFtt902Fpeh7qg65S8R/QOAQWa+NWZ/DkA3M89KqmdUKX8f/Yr4+7obgeYZtdVhYGAAwKT8BQAMdgJ2GZh2ApBvmuje+BjTlL9ENJ+IZrufWwG8BcArSpmF0tf3AdiK8YCRZQwMDAy0yOItsxDAD12L3ALwM2Z+kIi+DGADM/8awGeJ6H0AKgC6AXx0rDocgpFlDAwMDLTI4i2zBcAFmu1fkj5/EcAX69u1DGBD7gYG9UDSItOvLkwOR0AgfVHtNDR2hKqRZQymMrb8HDi4acybaWlpQVdX16jJxKB+YGZ0dXWhpaWl5joac4FsKyckGUPuBlMZXTvFv8X66M16YcmSJWhvb0dd3JMbFaUBwSlNnYA1OWixpaXFD9KqBZPjLKoFWQAMuRsY1AOFQgHLly+f6G5MLDb+EOg7BKz6I2DOsonuTV3QmLKM5Yb7Os7E9sPAwMBgkqIxyZ08cjeWu4GBQR3gTSZPoXmHxiR3y5C7gYFBHeGTuiH3iYVnuRtXSAMDAwMtGpPcjeVuYGBQTxhZZpLAJ3djuRsYGBjo0JjkbiZUDQwMxgLGcp9gkNttY7kbvFow0AEc3DjRvTBoIDQmuXswlrvBqwXr/w3Y/t/j09bwcWDXI/W1Yg9vFqm6y8P1q3NMYCx3AwODqYoXfwnsXydynNcL7e7aDcXe+tVZV5gJ1UmCqeeTamAwacBjEfntPasm8+R4oUHJ3cUUGmUNDKY0vGd10qcVnjqc0pjkbkjd4NWKhr/3Jzm5V3t9mYEjLwD25Jv/a0xy99HoN7qBwSRGPa3shrHcq0T3bmDrg8CeNRPdkwgalNw59MfAYMohzoJsWMt9kvfbH3Sq7Gd5yP07+byAGpPcp2CSHwODbGjQe957Zif74FRt/7xYG5p8VDr5elQNJvuNYmBQK6aa5e574Ez2/lerubvnNTIg/k0ipJI7EbUQ0bNEtJmIXiKif9SUaSainxLRTiJaR0TLxqKzASb7DWJgMFZo1Hu/QSz3auGRe/du4OlvTWxfFGSx3EcAvImZzwewCsA7iOgypczHARxn5tMAfBPAV+vbzThMsRvFwMDHBFruY9FGo0iptcoykxCp5M4C3vtGwf2nXoH3A/ih+/k+AG8mGsNp8UbR7wwMasWUu7e9Z3ayL41ZrSzTwOQOAESUI6LnARwD8DtmXqcUWQzgAAAwcwVAL4ATNPV8kog2ENGG+qy0PtUeAAODNDToPT9VDbJGttwBgJltZl4FYAmAS4joPKWIzkqP/IrMfBczr2bm1fPnz6++t2rVU+1GMTDwMcUmVCd9ypAac8tM4jeRqrxlmLkHwBoA71B2tQNYCgBElAcwC0B3HfoX15Exq9rAYHKjQe/9hrHcX0WyDBHNJ6LZ7udWAG8B8IpS7NcArnc/Xw3gEeZxmfkZ+yYMDCYCk8EVsq5tNYrmXiUm8fnkM5RZCOCHRJSDGAx+xswPEtGXAWxg5l8D+B6Ae4hoJ4TF/qEx67GMSW8FGBjUirh7ezzv+Tq2VY23jOOItRryTfVrPyuq9pZpYHJn5i0ALtBs/5L0uQjgmvp2LQsMuRu8ytCwBk0VssxLvwQ6dwBv/OLYdkmHbQ8BhWnA/DOylVdlGeZJkz+nMSNUG0a/MzCoEZPh3q5nH6qJUO3cUb92s0Im5KGu7Mep3jKTaHW4xiR3A4NXLRpVlvH+SnX2HQI6d9avjTSM9APlYnq5aiZJVc3dLlfXpzFEg5L7ZHerMjAYLabqhKpU58YfAi/8vI5tpODpO4Bn70ovV80kqToQOIbcRwcjyxhMdcTe2w16z6sTqiP9E9OP0mB6mWoCkyKWu5Fl6oQGvdENDOLQcwA48mL8/nE1aMbQcu89WMe664xqZBnVW8ZY7qOFsdwNpiie+3dg628wKVwh6zqhKvm5OzZQyaB9jwalIWComjhKaUK1GvdGdSAwmruBgUEiJkMQ01gMJIeeAx77GjDUKTUzBu2s/1dg3XerOEDqQzWae8RbxpD76NAo6UMNDOqBqfSGenyv+DsgJQ4cC2u3NJStnF0BBjvD29JkmVd+Czz6Fbfs5NXcs0SoTl5MpZvewCAE2ZKcoPt8LNuV/cGdCgBNNOp4BARtf0jMcbSdKPUnhdwPbw4+G2+ZesOQ+pQHc5Wa6VTGRBH9eJF7AiEeWA90bBu7fnhvErLFnXVClTlquZsgplHCuEJOfRzaJDTT3vaJ7snEgOM04PG458fh+ZJJME7KYAZ2Pgy8+Mux64d3beU3hKyukE5Fo7lPniyRjUnuBlMffYfE3+HjE9uPCUOMtT5VDJpMlnsdznXHw8CahFU/vespk7u3bag7uA91cCoay92Q+yhhJlRfNZgqZDYajLvlPg5tRTR3XfN1aL99fbL3i7cvNIC6BL3uuyKKNg46cp9E+d0blNxdmAffYKoidG9PkOU+mrYqI8nH22WArOCztn2JOCul2vuSBB3xVyPLqOdoNPdRwrhCGjQCmOvjGldvy92uZHQVrLGtoW7giW8In/bYPpSAQqv4HEeI9kjwuTRQW188VBM3kNX6dmxErpEh9zrBWO4GkxnbHgIe/3qNB4+htd7+LLDxB/WtU4bn5dTlZnzUEigDTdPE5zjLXbbWR/pG16dY6Ucny2QMYrLLGsvdyDKjhCH1qY/JseDBqOD5Q9dCznFkUw+iLw1mS6BVc1vecd6i0zFkWZgu/sZa7hK5Zw1KikOq9COdazWyTGSbIffRwcgyjY/SYEbymAK/8agJOUZ/r7k6p7oQ+9EijvA8yz3OW0aWZUY7UZkSXHS4dwhrd3eh4lRxbZwKIr+HmVCtE4ws05gYPg48dTtw4NmJ7sk4gYH+I9Ew96zo2C5VVYd7XqcV61BrW6p7Yazl7skyMZa7LMvEDRD71wG716T3KWXuo717GAAwUnE0vusx/XdsE8RUfxjLvaEx3CP+du+KLzNJ1qGsC9gBNnwfePZfqzhGurd3PizvqE9/mMfPOIoj93yz+BtruUvkHmcR73oE2Lc2vQ9yG9rzlqWvjISt9ZZpIMudiJYS0aNEtJWIXiKiv9CUuYqIeonoefffl3R1GRhUjanwdjYWqXNHVYcT/htfsNYG9O2psPLCHTKLt0w1aXi1dcnkHq2LdH7uuu9yOaeMyewtkyVxWAXAXzHzJiJqA7CRiH7HzC8r5Z5g5vfUv4samPQDDQ5lwm2qoyZ9ewzzuYfIPZdQrk7PV+z5E2BZ8fsrGSz3rJAtd8cGLPW8nfD+0K6Kfp82iEmZ/C4PB3ML44xUy52ZDzPzJvdzP4CtABaPdceywZD71MVUIv5Jdp96RDlmlruLNM2dSFjucftDlvsoyT0lMZhnuZNuf1w0rWMnBzHtexp46jag2Ftbn0eJqjR3IloG4AIA6zS7X0tEm4noISI6N+b4TxLRBiLa0NHRoSuSEcZybygMdon81917ajh4CvzGWe9TR7H6RlNXlv6M1fMTqTeuHY/cY/aPleWuHUwS/Nzl3yVC9Amae9cO8XdklAFYNSIzuRPRDAC/APCXzKxGFGwCcAoznw/gWwDu19XBzHcx82pmXj1//vxa+2xcIRsNvfvF32NbJ7YfE4WssgwnTOoFO0bdncyau450h7rFOq+Z4FnuMX1OtdxLooyVq4PlrsgyalfkPkTWRY2z3CvRnyOkuXtvnxPDU5nInYgKEMT+Y2aO5N9k5j5mHnA//xZAgYjm1bWnBg2MmJt8KnnEJCLjwx2yTsfQcndGIcus+65Y5zXLcf2Hgf6jyZp7ErmzDVDOLTNay72KfO2eN5GufChVcVmjuUtlKWVwG2Nk8ZYhAN8DsJWZvxFT5iS3HIjoErfernp2NAwjyxg0EDIHxcheGRNouWeRbbJY0sU+YMPd6ZZ7XF2OLVnudfSW0dRFESkmhtAjk6uT1xUyi7fM5QCuA/ACET3vbvtbACcDADN/B8DVAP6MiCoAhgF8iHk8mNeQe0NAtdCz3BoTbPXUFVnPIUuagdEEFh3fA8xZXoUrpIIdkr/9SD/QOjtbH2u23B2x38qPr+YOxFvrEVkmyRVyYt9MU8mdmZ9ESi+Z+Q4Ad9SrU6nwJfcp8OC/mvCq/b1qkGXqnR7g8GaRyOzs90jtpPVLSV7Wvj74PtIXT+6RauK8ZZBM7o4t9lOdNXfdQJHk0hiaUJWOtTVpiLX9nKSyzOTGq5UsxhFHX67Ry2W0mEJ6fGZvmQyae63wsioO90iWu6aNIy8Eq18l9buYlKWxWm+ZJM3dErLMaC33lAnVxEjTOL1emzhM2ia/fTqOcIts35C9z6NEg5K7IfVxw8sPAJvvHWUlo/EamKS/9Ug/8PKv47MNysgsy2RIO1vr24+3MAY4WZbZ+qDcWHy7I/3Z2070c6cMlnuCLq9tT3ONUmQZSpJlYiNUFXInih+EhjpFZssdv4vpdP3RoOTu4lX7mj9V0MDW+a5HgKMvAR3b0stmdoWMIZFwofjjj7wAHNwYs1MKKHJq0dyVdssJKYOTJA61T0l+7iHLvYq+6upLk2W8Xd4HbzIXUCz3GJ93QOOyKRk18lqsWQyCOqAxyd2QusFEQ7ewcnzhbHVm8ZZJuvePvCgIXgfPcpfT/Vbj554U2BM5TiX3hD5nmVClnFi2L6v1rl06LyaFQGwdHFwzHbnnClGStvKBBKOi/3DwudbsoFWiMcnduEI2FmrxfJlKPvC1eMvEF0rYpQmH9yD/Bkmae1xbEQ+YBILM6i1DJIg7TZaxckDPfmD9v6X0N6E9XeIwqZ+RK+G9NQD6CdVcIZrNMudmufTSJsjXXF4cJctCKXVAg5K7B0PuBjFwbOCxr8VbsnVDhkGoJlmmBstdl1/cg2+5MzLnlolbpNtrK/a4amWZJMvdHQCAYPm+NGgtd82EqnZiVSqTaLk3RXPEt8wSf+NyyRRaxN/RrgebEY1J7t5NVx7K/oMbTCBGYYXXOn6XBsUDmmUhh5pQTcfq6OeeZrmr+/c8AfQeREj/9dqpFKsgzFFY7nFISz/g+7knZK7UtamrT85T47kwhgbT0J+w5T4kySiyLKNq7q1zxF9vvQL1mjfNEF+N5Z4B5aIIhzaoHbseBY7vHafGxvNNy2trEsg79YxQTbXclf37ngY6t+k19y0/S3l+arTcs+ZzT7PcZW8Zv66Y8y8NBh48uoGnLK3B6kk0Sb8LO/DP48iLwSDoHWNpZBnP77/YE97uLYySK4gFSsqjXA82IxqP3I3OXl/sfwZ4/icT03airj7KpEtVTXiOcf21TATWEsQUF0DDLF1Ozl53yBrOStiafbWm/PWsZ3n/mn8OW+Eenv4W8PQd8e2Vh4PPHinveULfLhAMlM2ute0Rsjdw6GSZfDNQaA0s91DKYwZAwno3sozBlEEt6QdGC/8BnyDLPWlln9hjZFKqUZZRCdn7J1vuqjdHJgmoGs1dHQiSgpgy+LmrXikjSQFUSB+8PFlG4zbKvj7jEnLTdLcvLpF756KTZUDCeo+z3IlEfUaWiYGx3BsX4/nbeQ/4mHndaGQfZinjYoLVG1vlKHPLqImsWCIqnSxTTf+q0tzrbLmrJJpGjmnn4w0W3gRo6Fj3rzc5bRWC70BYc1dBBLTMjmru3kBBlliVqWRkmRgYcm98ZPgNR5s4zLcsx9Fyf+mXwkMHCJNfZlkmQ4RqquWukXbSyD02vXBCmfHwlnFIITYiAAAgAElEQVRcbxlV206TNVItd7c+pwzMXCQO8Q6V62AEJK562OSaNBW7lvvwcWD/OukNw5PCqD5J0DKiAcndoG4YN0ta0c/HRZZxH6Aky91xgMNbRpdOVq6/Y7tUd0z4ehKyaO6JlruapVCWGLzBMkNeFfV4XZnEc1LrS/C9z+Itow4kaakP1PpUK9sbLOyy0Mm1dbhvQT65e7JMguUOCMsdEBHMXrCSlx8+7XzrjMYjdyPL1A8Tdi3HwI1QRRbL/cgW4JX/DGc7zIq0axcKUx8jzd2xlQRXTnh/KBKVE/qSRZZRI1THwXIHYjT3Ki13Tzf3YJfE72eXYyxwaGQZhdytGFlGlylTnlAdR3LPks/dYMpigsjdJ8YsAUC1estksNwrbiThWHgvxCWeSjymSsv9yW8Ky/N1N8L3gtFp/fJ2XSbDTPr+BHjLAK7lrsoyCZb7rkejg3XTdMmDxR0svAFDIfdgBU93clpnuZMrr0Q7C7TOjW6WJ1SN5Z4EY7nXDeN0kwXtRZTNLAfV1paTgdzlqM16wnEUizqrxsraj7Gwy4EV67eRZrlryD3LW0JSStzIYVV4y6hJwdSyOiItF+Pb3v9MtG+FacHnfJO4bt6AESfLeHVEJlTdpf905E4EtMwELv4EMHe5dE7ShKohd4NxwUTJMpnalT0NamkjgyukPMlYK3TnEjexmVpXlmNirp3qqieXrYvlru6rRpapQnOPkLsFnP9HQE4i02p/L9k6zzULWcZzh4zTzr3rFGu566Jm3XttxvwgZYJ3jDfvkeT6WWc0Hrkbzb1+GDfLvYpX+sihY2m5j3IAEQdrNikeKaoleWwr8OhXAlnIPy5BBtGWkbbp8sWELHevL9VY7gntVmW5J8kupO+zv98Cps8DTn6dVKZKbxOZ3PNN4hr4skyc5e5eJ89ClwdPNWpWh9B9Z2SZjDDkXj+M07WMyDEp7W76kaSbjlJzly339o3AQEfwfTTkLuvZKtSJTpWM9j0l/hZ7RT2bfgR07qjdci8Px8gysndSwoRqprbGwVvGroh8N6EyLkVZo7HcJevcs9y9dAJ5RXNX5SsrJ/55i7OUh91tMbKM7rN8/ZPy19cZU2NC1RsVDarDuL0FZdVgXfQezF42DjrLfcd/i4frqpvdfRpZpn0jsPN3wJU3Z7unssgyKqHKE8p2WZzvyw8Ay65IrhfQ82RpMJAtdL7y9ZBlsljuw8eBZ74TJNBS+xGBsljH5p8Ave1KEY/cJZmj2vVUZXLPN4t5ipd+5e4T5B6xP/zr5Pbx8OagP03TkmUZ9bM8oYpJJMsQ0VIiepSIthLRS0T0F5oyRES3E9FOItpCRBeOTXcR/1pqUD3GS5YJWZBAYMXUcaGLyGGK5a6ztD1dVN6282Fky7+S8BYSiRTNaOXWGsRUHpR89WM095pcIav0lvFWG/LWYE0qC0Qtd5XYgYDcQ8nDRqO5K66POllGXlGJrLCV3jQtus3va5zl7kVLW8FgNg6clUWWqQD4K2Y+G8BlAD5NROcoZd4J4HT33ycB3FnXXqaiQcm9/4hw3WoIf/M6tlPN+cplh7qBrl3ZjvPILkl68ffZmm16AukZKqFip8gnEZfEmAlGIuVzBj933bUrDeonVEOukO42neVul6OEDAC7HxPeJ2q9RPoMlHE6dGJumRSyq7ssU4jfB/cyEQXXKeKt4/aZUtIQq4ORP6Fah0n8jEgld2Y+zMyb3M/9ALYCWKwUez+AH7HAMwBmE9HCuvdW9Ej8yZIGdLJj4w/FwzOpvVbGop0aXSHXfVekqc10WIzlrutXHEErKNsOvv/UXvz3y0fDbyNdu4B9a4OCquUeiYCVZBnZq6cWDxtATMxykuaeYrm//ICQU3T7/ORaUr0e2UX6GPMmlma5J5bRyDLVEqMccKRa3DpXSMpJgVMKuTsV1xVSR50xsow6oQpMDnKXQUTLAFwAYJ2yazGAA9L3dkQHABDRJ4loAxFt6OjoUHdXB91rT8Mh4wTjmDU/QdetVsu9GqiaexKBZ5T6bEds29slJ65iMeDsXiM9uKorZIwsI1vrEa+RmPPe+TDQdzi8LTZhWUbNvf9IfJvMwPrvAR2vBNvUfCv++cRZ7q774GV/Blz0UfmA4Jg4Hd37/WgUmrs8MKjk7ssyHPxv5RTLXR5Y7PggppAso8pIjPG23DNPqBLRDAC/APCXzKzm3NQN2ZE7hZnvAnAXAKxevbq2p1Z+jY1vqrHwapNlxiOIKWK56x6m6ix3fTuyhk+iSlWWCXnOSBJESNsnhM41qf19TwV+2l5Z1pC7TnNPPpnoJrskPEUGjgXbPEs4q0uiUwG8pFr5lmB7VZb7KGQZmWgjlrsm/QDl9BPygLSASMqEqmp8TlbLnYgKEMT+Y2b+paZIO4Cl0vclAA6Nvns6SK+0/qYGJ/cJTwNQZ3heE8U+fTtVcfsoLXe/niTLvTpyF13yiFPTZtKEquwWBw63k1WW6dkPHN8XLpvoCulku466MjorOc5y1/rQu+37E6OKdJGZ3GVLWDeQJUAmd1ljv+DDUZJmKJa7FV45yV+0O8UujsjGHPaPnwzkTkQE4HsAtjLzN2KK/RrAR1yvmcsA9DLz4Ziy9cGUkGVcjOfgdOTFeNKtFw49Jwj+6EvuhhhvmUwYpeWehcBD16Fa33edlJHkChljuWedUNXtk8k99GagST+QCB25awjbkynkQas0CPTsi5YFXEL0nlfFuk2LNfAHhVFo7nGWe67Zbz84c5eEZVdIeRUnIPB9j7QT5wrpDa4ZzreOyCLLXA7gOgAvENHz7ra/BXAyADDzdwD8FsC7AOwEMATgY/XvqgtflpHHpQa33MdrcLLLwNbfANPmApd+CqnXrVbyl12/oGmmKs29ti74k5iJ5O79zRbY48R5oqhRh5G3hiTLXZ5c1dSvQ8T7xtGfgzyoZrLcM96Har4VANj4g8BoiNQrkXvEcte4o8rQ6fiOblBOgtRmSH/PhffBvWIyuRNF24mNUI3R3L03tHGWZVLJnZmfROw0uF+GAXy6Xp3KBiPLVN+M287IGFvukQFYtdiraLf/sLCcCq1V9kENx9dZ2AnErymvvVzMQreVk1nJMgQQ9paJTJrKlntWclctdzUilsNvAlkt96yE40kbcvk4YgcCKQNA1HLPKMto5yMSzmnVtcDz/xG040H2nCErqqkDgvRtSZbR9alqP/fxn1Bt3PQDcbJMZQTY/l/jtpRVXTDukaIZXw3rZrmrZKSbFI9Bbzuw6Z7q+6Aui1YHbxn91eBoIIyjyDIcI8vUqrmnWe7qeWXW3LNa7l6+laypjCVyr1VzD9XnJL+NLL0YmHOKvg6ZlDWWuyifC8syuj5pI1TlMjERqmOViVSDBiR3F3GyzJ4ngIObgGMvj3uXasc4W+6Z2x0tuXs3+Gi8ZQAMdSmHZyEqldy1Zne4bGhXlGxY64nCUY8LdaFq1aoOySUxfu5J1ygyWDpRXV8+h3pb7moyrTRkstzj+qfR6oHkc1InSUM6eyFcTjEw2J9Qdf3cyQLO/QBwwmvCx6VNqEaUBdVyN+QehaxRRrYB6HSXOmuaMW5dGjXGLZhItfiq0NztcvCqqkNpKFgQQbXc1frG43xVv++s3jKE6DZvk64ddqIh7YnpB2Is97TsiElQyV2duK635R5Jg5t2HzmIVXazWu6zTwZOeZ2wygF9hKx6jIeZUshNiubuHy9r7gvOBl7zZmk/RQcQb7uuD74r5CTzlpl80EyohrS/3nC5hsB4yzLe17QbTCr/+K3AuoSsEs98G3jG3a9q7qOKUNXg0HNRSWCoW1p1HhrLvVpZRpb6SsCjXwEdel7anzB/wE6C3KLo6rF+7tVMOnN0AJHbzWq5Z11L1hvMvChONZNjpN46yDJEwKlXAs0zpfIx5+QR+Mo/FI4DshullWK5e9vVZRpV4k5LHBbxc3fEbkPuGZCm1zaSe+R49TVVLlHLK/uT1q6UrfrYdupkuW//ryBtrod13w0GFyCjt0ySVS/10V2GL9f+jLsrjqC9bQmyDGRZJkYrj+tTHOIs96Tzi6snCzzL3QukKg3GlwXckH0NucvRn+pSenKZ0HfJDTN2QHDLnPAa4RkmI0ZzD92SauKwSP1WuO/avqpBlmZCNR0xssyx/iIGRyqachOEYh+w5efRBRl0GDdZJmZiMwEVx8Gm/cfRPxLz8GnbUSf04iz3DBOqcfDf0OL6kEFz9/aFyDfrZLM0aKhl4xaq9vqRRZap5u0m4gqpIfcs99i232Zrz1LIXfUDj/TPjjHGKMjtEvecqOQq+4lnlWVkyOSu85ZhKLo8BWX9OnLp7URkGbeuSebnPjmhpB/48TP70VLI4c/8TRNsue99AujaKVbdWbQqpfBEae7pssxIxcFIxcFwyUZbc8ySZHHtxLms1WMwk8PvdajGW0ab4zxFc5fPTWu5S9tiLXeZ6EehuauLg2z7rZCpPLkk5Fvv4qLrRaDZy78OtvVlDCr3ZBlfc0/xmglNqEogCtIRZCV339K3gVwMuSZ5ssj7NAMOg8PSja6snBLBlo2eyeUK2YDkHq+5F8t2cEYTTe7QSB/FXvHQyYvnAuNoucv6LpBFlqmpayqhxlruozjvSgq5R/qgux/c9jOSe9gglr6oWrU62adKL7GWe62auyLLdGyP7lfrmzYv21ulDt7CIN4Am+YSyU68jOpb7jG6fcRyl8ixFss9bpCRIU+Qa718NJkq1XrU9ANmQrVG6F7/J5zcNXj2X4HN9050LwKkEgj7mRAzc00o/D1Ga4+rzHHE2qJZkGa5ZyH3LPvkTbr9hzdrXDXVlL86Txb3c8gVkmt7bY/IMrr9Sn1xATxZQDlxvE/uKS6Rjg29V4pkucelLoiQuxzRWgW5z1oi/qauoIQYWUZD3BGPmaT0A+4AZyz3BGgDYMQ2ghPZNmHwH1KpH3aMbj1hrpBpujL7IfeZeygTSWz9MSSfRNjVlAWQzVsmYbDReLgwNMaDTm9OC2LSJQ7zNHfKAVwZneWuLaPUl2WR5zgQCQL07ufUtm2AdAtRk5A2yAKOvaLZj9osdx2Br/wgUBlOd2EEqrDcFfpMTPnr1mEs9yrhXiiq9bV2ojFu3jK6gTHxgIDcs15Pp5IgywRkWnGcaJ1J10GVEDJb7hqPkYg3iWYlJm1d8raE66EST6aUv1DkC6X+FdektJeBYGV463nWAmZBgD65K5b7az8dXfM0Tg6JTCSrZRI096xBTIAINGuZFWu5+3coQ4lb0Eyoetu0C3Z4RTQR9CZCtXqwR+6IcSub9JjElruG19QyISlFR+6KpT44UsH6vceVRS+QTFBlJZ1Eml5cTfBSaGLTRfeeyKRsWJZJIfc4bxm1JpXc/YyLSv3zTktoj9Ot58jCGlTFIK9BrhAvy7TMDOdtT/KWSUPdNXed5S7+dE07FR0rPpFBlvHIXRU+jOU+Omh+UMfVhalWb4MxQcKkZQ0uifVB9e0GlntcAU1O7xTLfdB1qzzWOxw9Ng6q/BEncan98khAd2/I29TBo329WN9WKmcVezFnaK84i6T7S55QJUtjucufJasOHJBPUQrISoPnlZUE7cA5SnLv3iWcBNKetSTLPQ0RP3ePHBMs96zeMkGlAIByrhVOU5tC7gmyjDpQxPm5yz7zhtwzQGIbx714ViS16iRFvSM2s6DYK4J/qmqXYcuyjLq4MBC9SWW9OcZy916CWW0/KUJSJfesfuheu1rXRKn9p24XScrkh3KoM1QXg3Fm53+nty9blRFSU6z20ISqZLkPdcfXXwt0ln2tlvsJpwmrtVISmRfTJlTZgX4gydB+xCNltJZ7zMQuAAYlyDI6yz1hQjUky0irOhlyT4LGcvdJYxJZ7v6EqmZfRB4ZB3J/5T+jfsyZZBlpQlWXLElL7jEBRBGyV+pKIgk7o9veo18RpKNa6roJTrXvgzHr+nrkHtZl4vsgyzKqLhuSbHQTqkr5lX8InPnO+Layol6W+2V/BjRNE0vvASI6NYu3TM2Wu5oETNbc446pltaCfjCQ3XJPSh5GGst9nBfraEBy18Aj90klyyQgSYOtBv1HgocstU25DY0nj/4gRVHRSUwaWUYNIFL82pVHKb4uGboJ1HKMb3R5CFHfco3lrp5/bBh9uJyICUqz3D3SVpdxUydUvbolbxkZM05MDoJLzU7oQvdWVIvl7h3j5W+fPl9ZacmD6p2TYLmfkDCfEKu5a+ZJPKSl44204fWN3DfUpug+uR++LBMTPevW5cNY7hmh+UFtWyfLTDS5J2nuVU5sxmHD94Fn76rtWNFwym5Jlokto1ruFSlyUf+GQopMExybRO4a6/DQc3Gdqs1yj+TOCVtZoe5mlWUiRMPQWu5eA6qln0bAWYlMN3DW5Aqp9Kd1Dh7cfAC7uorA6W8TbxrawxIs9xVXA61z9MdFZJkqcstkhmq5p8gyvrdM1glVaQA35J4EnSzjectwYrkJgc66KA0oCxyPoq9pkZoeklz8YqG4Qqb5gwPioVNTwSoTqqx895H0eq8mlso3Ad27Y7rNihSg9F1NKuahFJMYLcnjJra8p7mnWe4pskwaMlvuo5BlQlare8yFH/G/l0tlHOorA0suCuc9T21LIs64QSrOcn/518DWB7IdkwY3Opi9/siyTMHz+kmIUE3yqAHCi22bIKbqwA4DINCkstxd6Pqx8fvCEs2anXGsoCPrp24DCtPEq/LC88OukBFLtx/Y8bvwNsfWWO5hzZ1ZJXko5TVQZZmZi4G+gwhFdcr1MLvLpTnxlrt63UsDMYNgBo+nSPseaSdMqIYsdy9CNSnqUQNVH467hlrLPSO5h5YRdI+ZtRhonQPbsWFxBY5uEEtrKy7oJ1QmTnOvAINd0fJA9gEvaMT/xIxwbpnmNreIhrj9vrmeTqEqpfPxUiuQtN34uWuguSjsMtCk0tz9iRPNQ6VKDLX80FUfo7MqdG8VQ8BgJ7BfpLcNuUKqbXbtAjp3hLfpZBnZ9Q/w4xIi5J4ky/S2h7+3nSTeWoaPR8t6HjvyWp/y/eANFFk1d11/M0xGA5AsP2W791m13FNklrLtoHdYeosJEVnaJK+KjOQuLyMokRwT4WjvMAgOOM1aTvNzjzs+SaaK+w2yrLerJWuXpD1Z5uTLYspLE6qxaX6lz/LAOJmyQhLR3QDeA+AYM5+n2X8VgAcA7HE3/ZKZv1zPTqbBIyArFMSkISIrB8xZVp9G7YqoL836SSKsOHkiC7IuceahFlmG5fQDHB2odJOcTiUYvCITql61MeebdE49B8LfZ5wk/g52RnN2e772HvGpbnPe+roRWWZQH8CiBDGxKvOokGWZ5pkADss7w59DfeCUSTpg6+E+DJZsXHbqXJCs4QLJfRqNK2ReTh0QHNMxUMZzR7tgkQWHqlh2Ttd+rOUek1smCWnk/to/VzI/KhGqlgVc9YX4431yt6A3mqA/n0k4ofoDAO9IKfMEM69y/40xsWs0d63lrpTb8jPg+Z/UpwvFPuDxrwOHNsWXSYqQjCtbDaol91raPbAunDhM1d11UaKyB0vEFVL89dwrtXp9ErxXZCAgHLsUPQ9Pn/ce8tJQuK3yYLhf/nG23gOnFs3d08+9lYN0x8mWu/c5RZYZLNnarqdiNGQik7tEWhW3SottMLItGN07XMbujgHXaBiFLJOEtDIts1CkZhzsGQ71LdLf2MHP3d4yR0Tjqtvj6pxsE6rM/DiAOkdU1AHS3e2nHxgvWWbYvRxxyY7k9tMISy5bDaomd93NxjjcO4wBb5ET1V3u8GY4KomE5A0NuVeGNWVVzV1v0aeG0IcWOpZyiqtM50Wv+tb9sXC/4yz3CPSWOzTfwrvcNwWiYEDyCFKVdvz7xMkky2RoXY/RWO4xskwhnwPBAbENSuu3S2q/33oUR/tH0FcsZ7Pc1Xp1udZrwG82H8LP1h9A2Xbg/c6suGTEwuv34guBSz4V3Q7EWO6NGaH6WiLaTEQPEdG5cYWI6JNEtIGINnR0xASMpCFBc7fGK7eMH32Y8HB47SdEXTrM7s1VA0YlywR+7nu7hvDCQXdVI81AFEk/IF9XnadOkuWuesuoP2UquUsPeojclWvokfu0uSL3+EBH0JiVC1INZL1HlLkDdrLKMgQ0qwu1x8kynuWu3FMx91jmRG7+AXZyRGUS8hrXQABk5UDswGIblFdlGbV/6qS3si2jLDPChLW7u9A9WGMuehfH+sXxjjIhn+myyksGxiYPi3sbaCxy3wTgFGY+H8C3ANwfV5CZ72Lm1cy8ev78+TU2FyVWP0J1vCz3WE8IuUyML7WE3R2D2LDvuC8rVQXHxtrdXdhxTAliKhej+rTXJWas3d3lJ+xitW+aASOkuQOK5a4hd9Vy7z0Y+KMrskyk/bS3nBC556U+q5a72y8rL4JsBo4G/W6aIbk8pjzJkckv9z5Dyu/lyzIUyAq6FNC6gKZqvWWyQhclmtVlMG5CVaj+gtzTPFTc40KB2zV4y/QM22Cy0N6TsrRfRgh1KIhCzTRo1pITx60/UybMOmHU5M7Mfcw84H7+LYACEc0bdc/SGw4+qpq7N+utKVtXJJJ7uizTOSCsh0ot5O5ap50DCsG+8HPguX/XBP2QH5B08Lh4MOzICkIaco8Y3ynkrlrum34k7QyT+rSRY2Fvm1pkGbscb7kTAW2LgP7Dwbk1zwjLMlkeVEWWobQHkx3XcCcxgT9jAbD8Dd5OuWDUck+SN974RYzkxJtA9Zq7nZx/PAkxlrsDErIMnMyyjOXncdHvjztOhkO5GnQpPVh9g8iC2L7qPHAsjFRs7O4cgO3fQAkuq3XEqMmdiE4iEmdCRJe4dcY4oNYBmrvan1D1LCorp5CQ5DpWD6KXfZPTyqQRFoII26oQJ8v0HQy3L3fJMxLdG89RsxUmWu5eOVmW0U2oStkVY/zYWZZ6XrhPaixFapKtOMq5q9RrZBlvQpVywOyl4vfvcz1WmqaHZRmZlOIISpGm0i13hi/LFFqAiz8e6P8hyx1h6UoXxKQQcJB0Ta4kAxxbk/htdJq7Z4FaXEElbUJVJ8vEBf3IUGQPYbZVG4EaD4aQZZir0Nxjr5tG+sw3Y3fnII72jeBIn/u8nPkuYMHZNfc5K7K4Qv4EwFUA5hFRO4B/AFAAAGb+DoCrAfwZEVUADAP4EFctCGZHx8AI+jsGsHjxbHi3XGRC1Soo5C6RkFPRZzesBqE3hJQyGUboil3D5YojwjgvHQosd6/Xjjxb6kV1qs2oAUdpE6rFXqlOVXZR6or0XbS/p2sQxZKNsxcqniahletJIvcYWYYsYNZS8bl7t/iebw0vHG3lg7ecphnh/sfkoKG021v2lpH7Gy2okLtOlolpIhL9m3aAMwrLXe8K6cACgTGnxUJHmp0YsdyVfleR58Yj4ZGKjaN9I1g6t1UIRC0zgXP/R6Y6vOZUh4GqNPcsZfIt0iufu+2kiEf5mCCV3Jn5j1L23wHgjrr1KAUDxTKO9o9gge345E7D3QDmBrllrHy85W6X6kjuSbKM9/Blsdyrd2vkTGlW9V3yENb6o5Y7Myd7y+gmVL1AoHyTpg+e5h4z4LntH+mNSQgWsqxJDOLaCVUp3Lt5BrDgLOHZ5BGcHGQlE15eWQpOmTfxn1GN5d5fLOPFQ304b/FMtE2XvGXk/kp1ic+KLAPOMOkpelFZsALNLc1iPsHDqVcBu9dE+gYgJjNjRkJVB1W5BmbkyEFFJfeYCNV478KMIgLB7/aujkH0DpcxZ3oBbc0F4NQ3AjMXZavHhSP3kyg66FTTV92bSC7+2o01Gi5C1Y+tlH6U5kPrMXt4v4iUYxbkLf9osjactjxbFvjJ9xN+LK9MBllGq7nblcQFKSqVFKlJQ+6OUi4kB2lkGVsqn1lz95BvCZUt2U7E2ox0O23uQSY+slyru4yINOFPqLrlT1oZrkMmd9lSVgd9NbulJ8torm2PGzXaM1QOyzJ+f3WRiarlnt1bxp6xCDjzHcHxF10PzDlFWzaoK1nyOdpXxNrdXZH7RBvYBc9yd5ADw2ZlUDrzXVqt3rfcI8401VNREC8R7VtWsFPDcWn+70BN51NvTHwPqoQ82949VEL78SEwGK3lHhDb4ne28uG7R9aGsybaSoKcCCgO0kNbLNvoHUogap075Pp/BR6/NaELEhFrg2yiy6oFudk9zV2WZZwIuYd2+x8kgk4i91xgufcOl7Fx33F0DRTdQ/2RIrnPKlQLMhdnuUuyDCBy5fj9KoiBkxm242BH57AfqBWRLSKWe7XeMvL94ekA6qpMsp87p+ZF8VRhR30TICVaUnuwuj/8vd2daI+458ZIRQwCMSNPDmxW5LYFZwGX3iDVYYVajJojYs/gSAWlFPdgjj3P7CRN3jPA7Ortbp9GI8vEuBvr9489Go7c/Tx/zNh2pB8Hjg8Lo5NysNgRj13ShGo9LHefhLJo7jZ+vG4/7n5qT2zRkExRKQFr/hkYTl5mzZHPSSfRaC33hHYR1dydkOWuaO6OHX0rUSUOt2yH6xVULg4BvQeD3DKRDlYxoYoEzV0dfOVwdK+Pjo2Dxwex/3gJh7zl/tQAmUheeoFzj/46uZ9yEJPfXXl5OLmcdz29PmdzhdSSeyp5qG8FymRl3OExE82OP73JsJGLSnihOQeljRgS3XKwF5sPxN/7id4ttVj/zKHBItMMRjWae6hOQ+6JCPnJumAGmHJuAqMcIq5GtcoypSFg873RBTHkNRHjIFlkfcPJ632GLPeBI2GyilmQIp3cI09aVJaRyZ05srSbbNlHvGV0k6lyKHYuIPdBNwI2n7OATT+Kvvb7DVZpucdq7gmWuxX4xzuOA4dywaVSSUyZFPfKNdnKeqsRJMgyoXPk6NxMmkuhokQELjxVWO5N08Lf0xB7nwtXyBwJ33NbZXfdm4sfDRo/oVqJjBIBVDIOV7Bes/AAACAASURBVF2F5a6dUKVROtOleP+Ms1TTcORueT9Kfrq/jcFwyAKxm52OLIToXyaitIWVZRzeDHTvEYsly8gky2TX3H2SLReBQ8+Hd8YslGyXZXLXtKEQXtdQOfK6HbLcu3cDOx8WHwdL2H60P3Tj9xcr6BmWlq/TuUFOOyH4LL09Dfv5UMKae3SyNnweuzsHwgOB7BZHFJ4claGSu6z9+uReBrG4byL7/P5k93jyH2VGsiyjrvPr3Y9xlrs6gekbN27d3gRiviUDeRBwyZ8CF/+p/33jvm68cqQvVGrk/I8oh+nrZSIQO8hBGFeJ5O57y4ivCfydiGTyrUFz5/AwU78J1ZjEYeOIhiN37/oUF12GPXMuB+Ba7nDJHa4FEyvLVBG27JFEaGUWSA9iNlnG3xRz4/gTm3seB46+hLLtBGWHe8QJKjKNI5NaiiwzUrHxzO6uwAtF5+fuLQYNYNvRfnQNlvyHNec+kVsP94uBZMfDYok/FTMXB5+lKDzvrL0H2vEtYcWdTxmkjvaNoGtQetNSyTdXSAli0tzekuXOcMCUDyhBtZodvbeMDnbTzKCMVpaJsdw9n3xvoI2sPKT3lvFlmTPeAaz+E+EVlEYeRMD0eSHLvWQzjivzQZHzVLNu+uUsWGzDIvHZ1rwtqudB3r2XVDYBIl1AzM5aJlRr6EOmCVVtXYbcE2H5N7eFjulnAgh+IAs2HFgiSEdH7rkCnnz2WdzzzL7ENn6/9Sh2HusH7DKKZRvtfQp5xi0jJ0Nj9cVZHb4sQxY6B0awYd9xdLi5L1DsFdknn7kzCMQBwNKApXWLlEhkpOKAmTBcVjR12XzKKW6ACN4ocvI9Odwt3mRe1qyCY+WBfBNsh/HK0UHYCln7wUtuvQ67A15CwFffcmlxaF2GQMeOXljv2ugkDo/ch7qRLw2EF5mILDihkHvcD7j6TzAyU/JUYQcRWcaDGuTl55bPEDshwSf3XB5oO9E7gZSjkidU/bpZ2v76m4CWWbF9sLgCyyI4ZMFW4zU0by6e5R7l9mznrdXca/CW8UrKMg9TRlkmbgEW3WAeqtCQeyIsaeT37kHHYTc7nYPuYRu/29qBvqFw4NLz7b14fGAxrK4d6O6NWU4N4gHe0t6L32w+DNglbDnYi8d29YYf7Lhl2sIVuWWDQBjVWvF+f1+WKbTgsGtdj5QlbdvLFTMUBP7K3jIht0i//aBv5UpApjIcuf+aB6Nshy33VJAFXPZpvHjytdhxbAgHugZD122kReQTImnegxlRacJFxWpGce5ZwQbVcrcKwvJN09xleG59Lz8ABlDKTQueOXUwsEvA9v+KzEVE0HYiQg+unFvGg/c5tCAIR9NEpAQxBRGqNbz2Z3WzlO8T1fdfAnvkTiRkmRjfdvHZCm3SDZRZJBE/kpQBx/29RjNh6TDA0u9etwnV8AGibiPLJCPsCiYuls0MYgaxg+3HhlBhEilFPTgVDJaB9mKr0Aid+EnVYjkgimd3HYHtMJoqg3Ae+QrQd8ivD4BPKhv3Hce63UrGhYjlHg0I8u5v2w4sV08K8QcCu6x9CFkiCbtcwUjFxrEeiThkco+JgHVszduNBE+jz8lad9KcBRFQaIHVOgdMhMpgd7DANlnom38BAMAqB4OrI/vXp3nLRNK/5lPSD0j9XrJa5Hnx6qiMYOCElTgw62Kp/8rjUCkBBzcBXTvFOST1zdfCOUaWcdstCn2bXVfMyAR/RuJwshLZeX8Q7aT/VV9HVjlckHsgy0TiNRLSC2gt5AwNywZSxWpxD5OyNFYJx2Gw5cmuGROHVemK6a1SxWzIPRHy2473ozoOi5sMtnshCZVK8Ipv22KNR+8V3IKDA91DvixxrK+I23+/A50DIxgaCoin07XwTxzcKm5c9yFXyX3nsX5sO6r3qHFcy4zg+Ddmz1AJO48N+PdyQO4VlNhCxWoJPAZChCfZKANHYbs3Zdku4b6N7bh33W7f+hkolrD5QA+YGaWKE/XN7jsczuCoLkCNGMs9iYDdH8eygObKAMoVJxjQmFG2hEtirhwMQg4jltwjmT505K4NYtJMTp7+VmDVH4Ws/4G554ZXEMqYS12HECf4X6Tr5nnsuHMbm/b34MHNh/zrvu1oPzbtP14FuWew3ImAua+J3x9Xd0YS8p6/nEVwdBOqob54z6rbRoTJs+V1YbcsADju/R8s8Ve9twwzlGCrLAdn8XMPwO59WEMGqVGh4RbI1s22215EILPrdUsoSVJFcWREuLxJuZTv29iOM05sw7tXLsSezkHYDuOF59fjwr5HMMN5IwaaT0TOffAK9jBspynQHhVyL1UcDI4oP527z0stQNKs/NYj4YHglSN9mNc9hCWOjbJjCf3Sa8MuIzAL3Sdj/zOg4S70N52I2cUDsMsVHOtjNDlldPaLwK59fBh7bBv9xQrW7+3GGRL7NJX7gY0/QFOf5GapSYHgWWKhezbJldS9vmWbMXPkMEpNOX8AJQAla5p7GkFfHIeB/WuB1rliQGyZhdi8c5EJ1Tz89VIT+hOuI/Bld/KtYJKugTcYLDxfHOulKvagss+iC3yZJwiWtHCsr4h5s21Ycvu5vJA4RsQi3CM2o2Lb/ptQ92C8lPTKkT7Mbm3CSbNa/IFDa7nHLRBRJdJ9g7xyno5OeldIwJ1YD+YfIusDSOWyGM0OM2xLRKDbrqODGGS4tnPlwHJ3WSQdCa6h0c+BR1Z88NXYoOEsd6/DDiB5fQjL2GIbDllgslAuB2Q1XBwBU86/uJZ7+x7uDSxXyymjcuRFVBwHM0piIRGLJV3b0cgH7t04UnFQLNshf/WKbeNQzzDKrsuibLmrIHbw/IEebDvUAxui/57lPjwygsGS217FXVJu16NgZvQ3i0yDtjuQWVzBro4BFCsOjrvRoOv3drvtS4TqTmSG+qMhbc9yl2/JZ3cexc5jAyjbDkrRqBX33B3sm30ZShVH0mEZpVyr+0nuCwv3z12PiOs6ZxleOPED/jHh6hXL2vOl17llAnpLShognFyL8LLy97n1F1q163BGXOYWrQJOe7P47u48OlDGrmN92Ns5EG2/yV24I98Cppy4vyI6dfBIbtzXjXW7u/DQC0fwk2f3h3oRcydpNqV5cET3Zs1AzVnIXelH4DlVq+bO2D7vrTg852IMN4s5HN+dtaoJVWnuzpIs90yqTHUk7Vnuo/Ohrx6NR+4aVyqbGRY78FZhZ1ihEObiSMm13MVFJtcLor9Ywd7OQQyVbZx/5OeY2bcTpYrn6QDkOLD+bUea/FL09BF3wnKobIsno7cdezv7sa97CJ19Q26b0QnVAIyjfUVsP9Ij+ongQXn05YN45JVjbidG/IGl1DIPXdOWAwAqR7diWqkTTfYQ8q5rC7m679Ke9Wiu9IfyoTDgJyH04Hjkfvpb/W1lO2ofHuzuQ4fr0fPs/n73/G3XRU3cTiXbweGZK9HTsih0zmVqjlhooRQHpQFsOzYImYRCl0y13D0CLusXbugtcZRwJOnFsQqiP94Gb/BgWys/hfRYRoiIvWmNsiP6XiyVECFTzwWxaToY5L8ZhpNLeW8/Dko24+ld+reYTLLMvNMBIuztHsZz+49n90jJ6pbo9sGyAAdxsoxbl687x1juGQOImIGRfBuOzF0Ndt/CfM29BvZ0GLDd+yrHlTr6uUv3sCdJGcs9GUTezRFcKMcRk6kit4yFac159A4W8aK7fNzg8AgcyvsjvJyy9VfPHcTujkE0VwbgMFCU3AVnNgHNeXGMbLm3d/Wha3AEcGw4DrsDAjA0YgP7nwY23YMRV7uXNfdyxQmscPmcIAYaLwjLyuUCN0R2t4OBPU8AndvFOc0739eLh9pfwMojv0STPegPfgTGjNJRLO57Dqd2PwHVJHGUwcaplHG8aKNYCQaBkbKNfI5CBGxJpGeTcHvctL8HezoHQ7IMAJS4EHrgK0xAYVqoJ6FB2rbx0pEhSRAV1713uCzO38qhY2AkWPPVJ/doxGjZdnDP2v14YoeynKOUBMt7O4pEqDoOcMrrgJV/CLTOidTtdi30kHsasuPmGmc7HMS0af9xHBh0z6tpOkAIJvZzygLUq671o3rbWvTKqd5Ilsjj5EuBs98PADjYO+L+ruqkpp7ISg7Qee7HgEs/pd3vH0+y5R6NgAZE6om1u7v8a+3LV1rLPR0hOdbX3AMJpHow2BLX39LMO+mRYULV65P7llZr70aDBiT38OsdIAhCyDIi/YADofP97uWj6OgfQc/gkG8RA8Bbzp6H968KUoPK6QEGJO38pOkWViwWOrvtMNgu48WDvXj54HFsPzoAsBN6QxgsVfwUrJ41P1gUUZ3EDrYdHcCWdilfOIBzFs7E6QtEtK3FYuK3uamAki2WxLOcCnJOOSDJl0Vek4rV7E8QH3XdJ5vsQf8hIjh+mPysYjtmF9v9gUpcszCxHuzqx0tHBvHLTQf9bTYDecsKlQu9zVgFf7DqlxY89lwvmXIoVxQJpmla6MGWfe1th93fKcCGvd14+XCfyLZo5bDz2ECw5mteeEuE3QsFhko2bKspmj5YlmVUzyQ5/0uhFTjhNaHBIGpsSvlDvIFCrkOy3h7b1oHnD7hzLbOWAiDkXNmP5SA5ImDOKRh0o3rnTFMm+9xOpFruzbP8NwLvvq9E0k+okpD48/iOTtyzuQ/H7GnhWAgJpYoDL56IADBy0OX72t8t7sFiOXyto4peNk+VkEFSL8vdvf55LmX0c48hd3l76xzgjLcB5/1BYLkbb5lk+EFM8gjuMJpyguAdsnDmSbPQbA/g1K7HcP9jz2KorxvTW5v9i7xkVnPkoSm4csbASAWLZhbw+tPnYWFb3vcUqdgOugeG8LuXj/p54/d1DeDZPULTnjXcjhlPfx2bdh7Ciwd7ReAQCH3FCiy2MX9wu/Z8mvMWFrdWcAbv8XPjtBTy/oNncQUWl/23Aw9lqyVwsQLQkrfQXBnwjyN20FwJ+/O3NkmSBHPoRu7uH4CjmV/P59xVarzwcXkewmr2LcyWQs4nO28i1qFAHiO4ZNI0Awx5Yjw8FyAPwoB4owHEgia2ugKPznJ3H7ChsgOH8pg9TUkGJpF7vOUuTY6r0ckuWJFlfIvUD16oQLXw8o47NzB3uSvLlMBgVEgaQNw6vTfIfC5chyci2VqiiHE9dD//98vHcKhnGBv3HcevNx+KTQHgOQf8+Jn9eFx98wGwp3MQ3350JzoHKyILRKLm7skynpzqnqemZGSbJnhKDmoeal6AocIc2HlvfiQ7uZN0/9nuG7DlVGoMYorB4ouA5jZ4K0dxhlQk9UTjkbv3o7jft817G2wWl2/lohlYMncGTj5hBs5ZOBMLBrfhvKMPoKXShxPapvmvR00W+6+7M5rF3+lNwUO/cEYOq0+ZgxzbsIiQswg9w2Ws3S5C7j2tdPvhXmzcdxwAsKh/C4ZKNoa729HvEp732ji3lbC0d4P2fJryFk7sfwnvLmzC/ILw6mkpBCRmcQV5p4zN7b0hP+JKrjkUXTmtOY8mexC2VRDWFDtoqYRzhiw7YTqWzBEPQsUWsoxXR3fvIBzKoWvaqRgqBOHmeYvccuL65KUYgb7mRb5E0jtc9mWwku1N+lm+r3w+R+LhL0wDc+BeaTP8J812GEx5/7s8CUwEDKuKlqq5X3Q9sET4rQ9URJbE5rzGfdKF7ZO7Z7lLmrsHOZd5SHJnPbnD05aji2PsnfNaYNkVbpoGQs61FGVyd/zjRYVxMQr6ICYl906kLGFXxwAe396BXccGtDKKKB8cu+NoNODPW2C9a7DsN+WQFVufXGeguUdM9zA3v+5GsTyhArmN4daTsGXhNb5mXpPl7gQulTkuZfSWqc3PPXXt3Tqj4chdjeo9Pm0ZSpxHwWIsmNGElUsFMc1syeOE6YHVNXt6q7CWCAA7yOcs/PkbX4PrLjsZV7T/K2a2Bg/YwhlWyHrLW4T+YsXXz2e7EqnsO+6QhcGSsNJPXzADFy+bg7LrHXJSW/zKT5Z0o6w8sQlnLZztDziAkEEsVwoZGKn4ZFpGM+S1JKcVcmiyBzGSm4EFbc1YsagtQu6thRxOnCmkjD2dgxipOCi5Cy5bXAFTDpVcK7YsvDo495x4aMuWuH4tlUBWOjrjbD8vicPwB7qQLOORu+VadiP9YGaf3B2X8AFZlok+JLbDGLYp9B2exebJMmT5lvagHUxMhkBKHZBc/7zFLhZfFJRPkmXkydlgVlaUdewICRQLs4HlrxcSBBEspwKHGSXpjcmzyL36Iv332qvCM4Z9KZMwVJLiP+JM99DAoCkjvaWQ+4+RiyF3aRBH8Nzqmg5tap6hjY7V87dHY7XIMoHlnsuquauW+9JL3e3J5O6kBenVGY1H7u5f+UcuO0CeWFhcVg4oD4KIsGxekDly1vRWMOWwcHarT9zN+RxauIhVS2dj0awWzGot4OS509CW55Br4HSXbC0Wr6EL2zyvG0aTq2Mz5XyJojlvIW9ZfgTd7ELwgLYW4i95s1PEyfPafMnIC+/2dO49nYN44WAv+otllKwmWFLkaGtTDjmnhEquFfmchfOXzMSbT5+Ji5eFJwSbchYsEgNFz1AZFW8yiSs4a/EcXHDybADAK/PfDgAoWJ4sQyjlZ6BgCyt546IPo5SfESEIZkbFcdCUF/76npzkW+7LrkBP22kYniHWNnWYhV+5lfPJXQebGUPSs9FfLAtNOZeXZBmCYzVhx7F+9LiFteljl78BuOCPg+hZ72ZqbgPe+EVg1pKgbK4JfcVyMKnrnycUy93T3D1vJRtJrocMQp5FcrYyggHEVvzBR6QJfpHn3BuQ9LIMg8WAEMonHnzOyal1pbeCV470+dHZofzmPhlzJL0Ac5DpMc0V0lHOK2K5Z9Tcvd8gPOemdLYKiDcnz3IvZ4tQVcn9NW8U900MuVdyLbV2b1RoOHK3pFd4Dw5yKBDDXyfSDfEuSHpla0szrnvdqUKWkF+7R/pRyFkgIpyzcCYWz24VLodS9sj5M8SPv2hmAR++5GQ0kzg+ZzFOWyAs39bmZv8mK7iEX3bJfU4hsAimNyfEjblrek5vziNvEWyrGZZTwZnzRD3ew7e9s4j1+8Ov1a1NORA7sEkcC2YUiJG3oj/x6Se2+Z8LLcJqXtiWw8I5M9DqSkI9rcKK9Sx3BmEkHxwnk7D8prFh33Ec6iliWlPOt9wJQoY52DOMY7kTsf+kt/kpDY4vvkqQrUsOYcs9PNk6JE3O9nkaTWFayHIfqFjoHAgGZq3lu+xyYPZSf7Lw0MK3ABdeFy0HALkmvHSoDy8f7gsxylDJVgjU++sO9to1S2UIzd1hoETBG2ZAguK7PGHvu8Qixka1cjjSW8SGfcfRNyKNhJIfuDzYyXWrmSH9/rjFt7T3+PNLHsE6JPnGU5zl7tUTPq/oOJA1iCm6bWSmcAlGy+z0CiL1MSotczFUmIN9sy/LaPtXNzF6+MSrcGDWRRiZvji9cB2RSu5EdDcRHSOiF2P2ExHdTkQ7iWgLEV1Y/24G8CZUZSmSiZCzXMudcsCIIHeatVQ6MI/WpoIIXmjf4A8AkYU4ABE1KOVQmTu9GecumolVi6Zj/vQ88pZovCVHuPDkOTh74UzMkibumnLuxKI7Ys/OBw/azBZRbnpzDucukha38OA+iBeePAdLF8wBgTGriXF0xtnobREW5YAdlXlaCzmRFZMKYhKOg8jN8xbNDLU1d1oTzl8yCzNb8jjpJHHDzSyIgeUMl/jnuOdDAE5f0IbmvIViLiB3b/5i46IPg/yshIwndwSpgxkWhssOCjnyB+Ufr9uPisMoWCKMZCQnXCP394hgLX+xFQW2w5D5p8MN0kJzm5TilwL91X3+4jRrILDqe2aeGbbWZbj1DRXmotQSzEW8fLhPa7l7DTt2JdGv3BvAbCuPPg4CpmwnbOGq/Y8ssxfaafmRroMjwXFWLoiQlAe7OMlHnuvwiHztvKv94DJ/UhOWMqGqrUycl1dfjOU+VK4EXlAJ0A0gA/POBy7/LDD9BM0R6fXZlMeWhdegr2VRfSdUXdi5VhycddG4+7lnST/wAwB3APhRzP53Ajjd/XcpgDvdv2MCIkEK5dAqQZaQZRxXlmmaLlZRWvlBnJebjcKxzeIH8azY3nbgxfuEK53OG8IuRaIeZ7YUAK4Adsm3bk+d14L5bc14x3kn4ZXDNkoQ+rxHZF4ulbZ8wEoL2prB7l9L9/B7ARUW4ZQT52JRcxFNOQtDhbmoWM2YVWxHMd+Gq86cj/ltzZhZmYne4TIsEkmcbMqjkLMEsbvyU1tLdDCYtvwSnLv6NDi5lv+/vS8Njuu60vvOW3pHdwPdDWIHCICkSHETSXGTRNGSZS2jJS5ZtmQltmo0UTzxMuMklbIrValK/uVPPDU1U048sTOeKpfHM0kq4yiOl7HkZazRalESaZEU950ACZBYiG5097v5ce99777XrxfsBPC+KlR3v37LfRevv3vuued8B6M330NLPARoBprjIXz1ofU4d/0WLh4FwqaGVNTEXckW/OhKwulzGdNuxMG0FICLrvPfuFVEXOyzJhlx+XrHpoqImoQSASWLcH1yGmdG8jDLeVhZx3KnCssdCGsEUyNclCGO6R6MD51BImSASMO07eJwopyqoSIU0g9igLweW4tE2wBw9W+c75TZS9nilpLt31bkHHyn+uJfX4pkcUNZKfa6ZbxRUnbb64RCkqIH5LjvGiN3leHk27yZrtjGRJ4nEVyJd/6nJNex3j4/NTzRkNXsRMuoM3fiv/kZQA2pdrelEbfMbEl6cf0ydYcgxtivANTSPH0KwF8xjtcBpImofb4a6NMgAHD5/xhpMG3LXQO2foYnoBghNGXaETGE7rfqz701AoyeBa59VHmNUsFfQ8UqAVYRhqZhX38GrQlnYAhDlJJTflRFYbmHLCfWmojQloz4EzvgWqQjI2zPAhCKoyz840U9jv5cAl3NMSQjJrqbuWuFmAVLM3gkELNQs+C0pgOZAWhmGJl4mP9MlUiSnkwMO3rSnPTBSd4y41gr1jHc0RqV93Jgfc6OFso1hV3/r+mShaawAU0jlBhw5WbeTv5xCXkpGBov4KOrkwjphETEsOPXb0S6cPjiGI5cGsP1yWlMFN06HkUfwrk5xUNLpeVesx6zkFmeDGUrVf1cC4/yVVjkZcctozbhtZPXxKDC9/vFRcLVcedZK0n3RbU22XHi/s+Pn9uD7CSa+uR+y2y2Z5z8cpX9575Xsp8d30FS9FFJIfV3O57FBx2f9pzTuZ/JUNb33qq1J18s452zIw0qOlaer0497krMslzebKtPzRbzIRzWCeC88vmC2HbZuyMRvQTgJQDo6emZ9QWJAEX0EYw0HgVjWZy0wk38D3CiHaySW/WvlnRtedr/+3IJuHLYOa8S2pQOWxg1NPTnHOt2x0An9KMhUMm/DqovXEWmnR/Z43evQ2n0Ak6/rqGoRZD0yVzklrvJ/eyK5e4L+YCqoX4eVUQ1jNDQNHxm33qwI4dhMYaRtiSOCyVMxyHBF5j/8P4BaBrh18c2IlYcRdgYdi3eAUA8rEEjwtErkwhZN9Ap46CrRMsAwMR0GSGDh4qO50soWwzjxGOhxwsl/OrtizCsAraI1kRMvcJyZ4zhO/9wGl3NUXvAqZaoAwDlvgMYPTKMm5FOWDTpaplD0Q4ZO5ERjp67atG+cWoEm9qTdmRG3kiBTVuIh3VMFsqwmBwQajNBuYpdJt0oinI1yPa5u2cC06XKa7zf/ozrcy1CYqTZ45um17bc1SiggpEEDHf7ZRsvJbfhQnInPl7lPC65CvFergXkEhH0ZGI+R1XC/r8x9/9nIdwyErWes4XAfCyo+v0Sfe+CMfYtxtguxtiuXC43y8sxEJH7HwKCSbJAQpW4ZqvU+D9l6kalIiDArbjTv+LvjYiL3JtD3E+eUkIqN3S3YrC1yV7wu7z++frXVtuv1CRNNqXQYpawpSuFg1t67WmlirXZGPYOrhGBx+XalrtN7mp90eohm1KrnUDoSEVx3/qsvVl9aLuao9DE7IWRAeq/H0CllZgwNRRKFixoGBorIJ3gA5lFemW8q9MIhHTibidwi2287AxyDGQv9DIiNEWMiuvKzOELo1O21HJleThl/2grjuUeBiOjwnJXn0Gnp4WlajkWoZeop8uWnQxW1kJgIGTifFYm+baeFVrta7ldJXfp62UgOwcBqOGWqXEdxpjSNtUN5FOsA45FLr+RfeEd7CVKWgSWV0PIc/1qqDcg+h5jOTIchtaY7PBMF1QlFtlwnxdyvwBAWblEF4BL83Bef4STGEkMogA1q0+HKX9efprfgCD3OnrdPXuAA/+GCzyNnvE/j4QRdpG7b21WU/gBi1PY1duMJ3b01ffXqe1PtDrvQwkgux4hXUNz71bfQ9uSEXS1JDhx17XcxXVc5F5nIqfMJKS7qDkWsskjbOrY0eOEXn75gUE8vo0vVKpRGkROJBMjDZ+4cw22douBjLSqljsDIWTo9rG3pst2BE1XOuoi92mdR/54FyRlxiuRsyhfy+IsKCzJxODSK6xD9dy2/IDS9rzofm84Zn5aIXcyAJCdVCct95OZA7geG4AX8uxVLXdxKZU8LZCd89GQz109n4eSyhZzuWVsy13Ta8+A5MxGOU/Z7TuCew9/ONo0lW2bDVQZDl1vtMzezMjdO7AtFuaD3H8I4HMiamYvgJuMsQqXzLwh1YkzrR9HXnMWUBgIuiR3r3Vuk3u5fjGGSIq7KfwWZ7yC/kYEKOaBca4lg9J0ZSFheczoGZi6BjMUcWRfq0Fto6lMMY0QkOrk8bTx6j5Jfr8EnHu90rWk6UBULIzJftJ0p4/0GpY74CL3iKnjwY2t+OSOTrS1cNfII5s70d3itNnQNWjiflRdm1SUu7RSURMtiTDu7EhB03Q0x0wh/iYXVDlCdkgrzxaW4Z35YhkTotywqQAAHoBJREFUhRJ0jRCP8MzWgpHEicxBZHc/g7ZUBKUyw3i+aBPZhJ2L4IizyR/djz64jNdOOtE+gGPpA3yxk4jsdRXVxVFmotXKD39KPJLewSOvFpLRTHxyR5d9mLTcr8buwKlWP+dEjWgZOJat6nEpMxJJY+Rxy1go6AmMRPt8z8XP5/5cshzLnZEjl6xp/qqQ9mBkL6j6zxzGc7twPTaAq4mNFfu52mPHubOKts2Ec+0BijmDjLpeVhOeC52+Nom/O3SxepvtCKHG2zcfaCQU8vsA/hHABiK6QEQvEtEXiOgLYpcfATgF4ASAvwDwLxestQIaefxkpMOAT/UdgKd6h5t4bHM9t4wkOZn56Cq24MmWk0T39neAy+/zmUFijXufiuIS4arFhm2obonZVAbSNLjkatXrNa8FcqImqV9f1Iw4oAqN861daSQjJjp2PIa9D/4TpLo2+hzGr3NHWxN2r+WDX1dzDGAMm9qT+OQOMenLDOCOtiRaMy0VP55Nj38JpfW/B0b8h+Ky3KfLCOmEqOlo0lyLr8eudZ22dMK3/+E0/uyVE3wwEJa7qROmpp1iK5bFcOzKON445Y4dKChELN/K7Nrv/OY0bgrROcYIIUNzLTTfYnxw91q0U0rk0NaeHKIhw5GyBkQiGHMNiBLX4oN8vypEIUlfrYVugUdwMbjdmdNlC+92fhbHc5/wP5kPyoq7iYnBDuARObWUKuVEQu0LNYKKGRF8lH3QDhqo53ayWOUAQDNwl8hjVcud99HMGfji6BRODU9WnQGqs43FRN0FVcbYc3W+ZwC+OG8tagAaEYqWe7psSEErb9KOGQH2f6nBExvOMQC3lotiMTQUB6ZGnX1VS/7E3/PXZCcw9GHl+ezPGhBJArXCedXSdyBg+2eB2S7IAjz7MxQDjv0YAHP88Cq5W0pCUDUQVRXRghkB9d1b5Th+nbChY/9ABumYyWPpf8vEacUA1ncf0LYF1tFJYOyG6xTRbC927unEjd9dxhqRGAYGTAnL3dQ1RE0dn9nWg++94yT6yGQy+aO6PjmN8QIn46lprkFPxF01/+/wFd/mq5b76FQRzXBnef7u0hj2DWRggZOx+vu9JfIRvG6ZKcG8/dk4WvtbgclrNi0VyrAVISOm7iJAADjZcj/OpPdjsziCJy2N4LHN7Xb0EQAUlUtawn3iXaep5veuhZLFHI0j5Xy65kj+5otl/OCt83hkc5vSBvGqXPK7r53B5/b1IpOolBmwmKuMimu7fPVyaa21Ey9cmbeicYZW2y1TKJUxXbbQ5NleVNZu/Ai1WvjnQmPZldkD+EOqPpiMNBi2W2b2dTDtYyXJhZscco+keHy8hLTkzYizTyIH7PsiMPQ7vijr58MO+yQuqch7mF/qncz0HiQ03dkmCzcDs7DcMbv4XjX2mgh3doiZhLcdREC0GX0Z4NyQ7APnfxwLGXhiayfwSw2MMZAFHL8yjks3p7BbZMi2Jt0zC9Mz0P/48BVID48kXFPnEgnHlRq4pTJXZzd1zaXvPzJZQlfJctWUvT7J11rKlpCiKPHvdI0wZskSfB63TLGMsNiHdF7ARFruP/1wGOwoNyJUy/3A+ix+dfya0P9xskH/7weXMTZVxNhgEcmIiaKlQUfZtR5gMX5+zeN2aMTnDrgtZNVXrtKvpjmzgrF8ESOT07h0wzFUjl+dxE8vH0fI0BAyHFmKv/rHs3h8a2XkdD2iZKyyX2tWgvKeR5ExkMfpdRZUD52/AYsB+zzbZaZvdcuduV4XC8tOfgDgbhlHkIr4QyZ1xudQ5NiGdLmEFZeG150iRYakmwPgGs6RJNCzF9jwiJtopcJdZtD/mknxgHtdOzOF9/5Jd7Yxy1kE9iP3Wpb7bLPrqg0INrm7v9/encaL9/Xbn5/fq4TMSt0W4mGOF29MIRE27Dh/7z2FPTo+Y1PFijR7vyShk8Nc0vbXHw3jNyecSkiM+I9fJckrN/OYLlkolhmiplOEPRkxcPxaCWevV07X5YBBBLHO4SxMqmJwavs70u6By5nq8zdliyFfKtuhmI6cMRNrBajo6+kGyV3dr1R28gMYiD8WxPWKvIlXkwVn/WRE9Pt0yapwN738/uUKUq3GgzZRWj6W+wzI3ckH4NEyGlHFzKbaMV5ILvLVMYLic2+4dfODZUrujpWQSXCddqsoU9DnQO6S+KRv2XQWEF3kvudfONZ6WrGsvVa5ajnKyJd0N3DvVyuvHcsCe78A9OyfXdvta/q4gmzLnSnk7vMgh+q4ZeYV/jMIIkIibKIvE8O2rhRamyLql/ZbKY8wkEtA3/gYJ0nS0Z+L2xIK1aoYSURDust1IPGjDy6DMeDtM6PIF8voz8kZjbDKlXZMFEq23z1s6pjW44iaOgZyCUTjCbz8/uUK98eUTe7C1aVY7uo9RpQ8Axn+KWExhnyxbLuN/vehSzhz7Zbt85fl/nhUCbewZcFu3WdBuBbySsRQSbXcSeN+7kgSuvKblOedKKgDqXNfXnI3NKog5mLZ8o2+qeVzn5HlLt1XJQvXJgqQ3TubRCh5v+Uqbi7vQLxYWJZuGY2cUfKewQymJpLIkZhWz8lyl4TjEyaoknusBZieqNxejQDbtrg/q4OGhGYoJd1mQKTJdmBMCU7yWuSkRMPUtdwbSOG+65823rZaqKVtTRraU5UFqlU8fGcbfnrkKrZ0pfjA2bEdAPDUdkecyU92AeC+7HyxjKaIgY3tSfRl4vgvvzzp2idkaEjHTDy6uR03p4o4NTxpW8WqW4Yxp9B62NDw0F0DiJy/BEPTcEdXK86dKWMs754tSLLUAP6Maabvo6Pq+uueHRhj+OYvnDaPTRXxkyNXsEPKQlgM1ycKGM+X7IVP6UQJGRqmpss1dXdU3FRmO2WLucNaASDcBK2skLsdmVSGjB9jyvMW8pC7aVQmQP23X5/G2mwcj2xug0bkqK/KaCFWWZN4Jm4Pue+RS44sdqP2S9lirmegWCdfwl68XVw59+VJ7kROSFfE1NHblgKGRGj9bLLHjBAPZZTHSukBNTTQu5jY3AuMX+Ghhds+U30eefBrjbVBHZQ2PQmcfxNoakDFYdtzwPhl4ND3K88jP8sZRD1y12s9DuJhTnfX2GcGqOX7b+BXlo6F8Om7a7clHvIf6AdycRy5NGZrBEV8ZJi3daVx7zoeciqlnKWLQdcIb3Q7hSReP3UdGXDSioQNu7/jiSSAUV4iUIGMliEivq8Z9ZWjiCnt935fzUhlpMHUCUWL+7MBYJ3IJJVZoCFdwxTKDfncdY3w3gVngbtkMTv5yyxP8X9VOAl9iuyFVllacbLgVDZSm+sl91CV7NbT1ybxzV+cRHPMxAv3rOX3raaWeJpfzS3SKKiOMuV7bZ9CpDSGHZYFXfmdycSwutEyc2rdzLFs3TISsZBHRXA25D74ENB3L5DdwD9n1/PXNZvd540kgZz4bu1BHoUTigMt/bzeph/4r6p+G1RSjjYD6x+ujPzxgxF2DwIVbhlDcVUxf3Lf9izXpK6F+XbL1HIPSdRLqqoDPx/qVx9abxcskZax336xsCK9IBOuZPy9puGOjjQe3MhdbdK3HNI11yCfSPCchhtTbp2iKdXnDgBmzNUNHWnePlMhQU1z++CrWakW6YiFDFyfdMJhiVn8NyOeJ3meRsi9pyWGM9ecGrVly/G5y1oASPdA18gm2+kyv7+JQknxNyuWu+4edE1Dqxnpoq6TuAqqe0zhGfnc/WLy6zziU6EWjMb6KtxssjhNtcElWFCdAeSMiEiUx1OJsV4ijh+MCK+QI8k0kePJQmqGKGk8Embz06IRmqNfMx+Yy1qBq8Cy7ibFRhZUW9byReBFhXzQfX5RRMDgg8DOF+btai/s78Nzu3tcV/aLI5dQyy7q6gMHbuE9srndifwBNzhso2Pj40B2HZqi/P8iLfdP7exCRzpizzodco+CQBjIxfG5fb3oTPO1DzXaR9cIT2ztsK8l4/W9YCD0Z93utZapsyAAk3G+PiT9940sqMbDhou0imXHLTMa7cWZ3qeB9m3QNMLVsTzePTdqrwNMlyxFBsH5P3stdzDWMDGre3nJ1EueN6eK+EslF2FoPG+7yKrOfBqwr73XlYNktQxdNcJnMbFMyZ0/KPEQVxZ0EVUtfZRqmKllvRCYi5Wqtl/Tgfv+lfsz1SH3xi4y+/b5YeMT3MVTLWO3ezcfZOeIJ7a146FNa9AcD6EtxS1iWd1IFUbb1s2JWnal6hIxFclcdSddIzy5vQOf39+HR7coC7NtW4Atn0LY0BE2NZtcklHT1vMH4AQSiuis1qYIMokw9va34P4NOZcGv0aE7pYY/vjj63BnRxKXb/rnPjBRg1ddTD6f2glmRnErxqUgdJFlW/QIh+WNygS7qOl+7l2yAUTIR9sBIntN4BfHhl0LtY4MTfUF1ULJapzcVTVYzyFei/raRAGjt4q4Osb76nuvn8O3f32aH+tD4uRzTj94xeimfSx3xhhePTqE6xMFJ+wyWFCtD/mcJOQDrBJjtUQbP0SSvGhHzRBAedF5Hgc7tgOXDjmf5+iCcJ1HHYhIUyx3xl1Nw8eBpsookQXDtmcrZznNffxvgTHYWjm7yjZxd4IsFg4AH9vQioPrW/Gnr3AJaLVilu5xy6gD3YBUARUVrbwzx0w8hEs3OLnoGiEdU2dZ4tXjfjN0zaXRI48FuAspk6j+jHP3RxlhnQHCm3ExtQOjmx+Dfv6GOD9B1wklJQrmje4XfTV9oqFKIlbJWzbdK+nsvUf13IZGeHpHF1oSIbx24hpODFcv1u1FrTGgQqBNtGPcs6DNxc8qjydqjNxPXZvEkUtjOLA+B0tZYFbdRGNTJRw6fwNnr0/WqD61sFjWlrtd3k0l9JqLgh6sexjY/hzXbKmH+Sb3dZ/gf5L05mtmYCcFKdox8j1jQG4DdzlFZ1iSbC4+95a1tfVwFhkDuQRevG+tq8YuiSQfaYGqlru9LWxgS2fKfxLTdTfQf9BdXBtc117C0AjNcU7+73Q8j+m7/7DhNqvrTFmfjE5AZImK/3Uq7H6eNMW6Vt9LqBWwehR9oIjHcvdG/siU/6lpx000PFGoWABWyZ2I0JOJIRE2kAgbXFu/TuTO0FgeI5PTNcnXa/0XbHJ3u7CqnYOU8jAnhibwjZ8dr7hfADh6ZRy/PTeKUtly5wAo17fVLxXVSWnBv37qOs5en8RCY1mSe4Xl7iL3GVjuoXjj1uN8k7umA107+WIs4NaDmdN5ZZk56ULQ4bDRXEyH+Y5zX1okq4RJPr2zC9u6Uy7XQTxs4MntHXhuT5+rXqwLugH07qsYpNWQTo3ILn5eNOLQ6ukMKVCTS1uTDrlvUlw3Lx3ox8c28hnZnr40tnc7A7iuOY+EoZErlE9Ffy6Op3d2YXNnChvbmyrcMpIonZkE367KJAyNFZCK8n5iHleW5y3X42FumQc/fO+Nc/jua2dqWvgqueeLZQyPF+w2q66UqudQ2nVIzHJGJiqL9kxN8yig8XzJtSjt1e0BRJ6BJzb/jVMjuDA6hYXGsiR3GSdsa6cbDWqSA8DdfwB0383fm7VjqV1YKJ97Cw/xQnGe/tmynar4mJ3+uMiBtssQHekoHrhjTUUEzUAugYgpiX1mA90eIZhmaA65A40FQ0mQy2ftPIv3rXNmRBFTR2jwIBBOINzcifuVWYNGDqFrGiEZrf07eWjTGjyyuR1RTzjpNUGY0qcv2+XVwPHmGKiWu2rVy8XVqaL7+GqoRe7jhRJeOXoVpbKF7795DodFTdaJQsktz1zj/NIvLl06fvtOFnhbj1waw88/dLSMXORuH8/shVbGGIplbslXLCovAJalz31E6Hnk5PTUpUleh4QTOS5SleycmWtivi13idwdPOyxddP8nM+OulEsd9stMwdyn/cM1WWIWT4D+wez2DeQAREhpBF2r23Bm6dHXCSNrZ/2L9ZeBc/u7sYHF24iaup4ZleX42pIdQH7vwzAbbnpirUe0jVkEyFc9LEeveSpWu7ZRAjXhCXbFDFx41bRnlFIMtvY3oQPL48jGtJdBOYmd+f8MnJHdevUAmNwadOoODnEEwt7WmKu3ILxfNG1v98AMdiaQL5YtslcqoHKV78F37fOuBVESz6Wu8VUeWFne61IrfnCsiR3OQrbC0uqHG8jJGSEgVYfedpamEuoYs3zEtC5Y/7O53XLyILhwBzDHQNytzGLgU61vO8ZzGJvf8btGqmSJ7FnbQs+uFgpI9qeitoun67m6gEBMhtXU8T2miKGfe1oSHdJEHt5z8kFAFqTEZvc01ET5+H43J/Z1YXT1yaxvTuN9lQUA60Jfq6zYlBRZRWUAUO+92bLbutO4b3zlfc9li8iHtJrSid4Z12ThbJrZuC9x7XZOJ7Y1oH/8c4FTJfKYIzZ588XLZfscy1YfpY7c8e5y+2B5V4HMRmLPJvY9plioSz3+UK6B7hxzpnrqwuruskXUWeK3v3A2dd4yOLAA/PX1rmgcweQ7FjaNhg+8hEzRDWftxf7B7PYPzj7xejmmInLNzk5TQrrOBk17eu3xEK4OO1Y8H7kfmB9Dv3ZOE4OT9jbncpR/ICu5pg9yGwTvv5HN7dh6FITylMMbynzCNXVk/JxD335gUGcG7nlS+6jk0WsSYZhhwL5QK2eJTEy6fjO3zk76vpO9sXweAH5YhlHLo3ZJHz62gR+eWwYv+ejXOmFOx/AKQSj+txtctcDcvfFP9vX67I2ZrSIOlssdJz7XLHlGUfvBoBtac+l3f3387/bCesfXrprmxGeXFVN2fM2RHs6iss38yiWLdtX3BQx0JaM4NEtbQjpGi4emrILdLf4hFnu7OVhmR1FPlPobonZhlUtX7mmEdqSEYyW3ZEhMQ+5a+RowWcTIRi6ho50FG2pCHpbYnjjtOP+kAqOXuSawvYCat7H0lbJXRbUlu4dWfwlFTWRL5Zx9Mq4TdSXbuRhMVZRocsPfj53yxP7HljudVARCmb4h4bNK253n7MRAgylzN/t3t7liu7dS92CGeHewSwy8RDWZuO21HBTxAQR4Y62JE4LaYFcUxiPbm5Be6r6rKQjHcVXHlwHjbgsMuAkhFWFEP0iheRipjv7Nx0zMTI5ja1dKTy4kUteR0wdz+3uwanhCb9T2vjsnh6ULYZffzRsb8tPV7ZJ6u6rCNu+e37Cp7Z34L//5jQujN6y95FkfN0nasYLWYLw8MUxO4TSndjkSDMsBrnf5r6GBrEYbpnlBqmLsxizmgC3LXSNsLkz5fJDq4Jqaom57pYYjDruAl3jCpNxEUffSJRLLMSrcEl4I3DSQr7Z79qq1LF04aj3siYZQUc6iomC0458qVxh3auWu0RY+PtlH8TDBtYkI2CMRza1iKLifkTsrRWgEcGyGE4OT+LvP7xa4VIKGRosxuyQz7C+8J6AZWm5V8Bb33Q+cdfzwMjphTv/QmHgAaD3nsWZ1QRYFnhmVxeujuVd5DjbjHhpfcs6tNVBIBC2d6fx6lkeNugly7v7WpBNhLl8s/do0dRMIoRYyMDNqSLChoaXDvS7whTHptTomJJdQvGTd3Xix4evVChz8pZxqO4UuZbQmgzzfprkyZJ5rewK98wlwq5Y9YipoWQxV0Uvif5cXOjvWw65+yiRzjdWiOW+gNZpuuf28zs3AiJ/3fgAqxZdzTHs7G1xbZOLid5M1HqQ1ndd2YDuPfy1hsRHRzqKewazvollmXgYuka4X6T6A0BvJoa4yG71oi0VsYn+Yxta0ZuJ29LNXqiLnhJy4Olqjtl9Eg3prqxdAOhsdufIMACHL97EsSsOuaeiJp7e0YUnt3XwaCXL8bl7i68sBBq6AhE9QkTHiOgEEVUIlBPRC0Q0TESHxN8fzH9Ta2Am2SABAgSw0ZeJ4b51WRzcMDORNkmCdX3HXTt5pJYxOwMsGtLxlQfXoTcTR05oAvVlK4vKHNyQw6aOJGIhXamMxdt2Z0eqwhUEOC4lldxluGhrUxhrmpxZ78fuaMVdPWnbHZVNhPH7QmMegDvAQyBi6ujJxECiStW18QLePjMCU6+eITyfqOuWIV6e/s8BPATgAoC3iOiHjLHfeXb9AWPsSwvQxsaxmGJYAQKsABARdvW11N/RB5+8q9P2lzeCL9w/MCdN83vXZbGlK+Vr4d8lhNZePTpkx8yrSWK/f89afHh5DK8cHcLG9iTG80WsW9OEV48OuYp+7BvIIBYy0J9LIBUr4LWT1zE2VUTE1HFwQyuyiTB+9ruriJq6y7Wybk0CH111L/42K32zrTuNs9dvoVhm9gCx0GjE5N0N4ARj7BRjbBrAXwN4amGbNQvs//L8lYALECBAXfRl426VyzqIhnSX2uZMYepaVdE0id6M4z5Rs0BDhmYXaelIR/DMrm57JiBDIQEeSXTvuix0jZBLhLGlM4WH73SMxs2dKbywvw9dzVGXa+XxrU7uhZSP3qcsIg/kEraEczS0OEudjVylE8B55fMFAHt89nuaiA4AOA7gq4yx894diOglAC8BQE9Pj/fruSFcRRc8QIAAqwbdwjeejJo2mUtkEyFs605hsJVzRUcqgv0DGWzu9BdwIyJ8fNOaiu3NIopG93hWTJ1QLDPs7GnBwfWtvNaEen0xmGxWxN4WEo2Qu59zyDu3+j8Avs8YKxDRFwB8F0BFSiNj7FsAvgUAu3btWmR14wABAqx0mLqGf36gH1FTr/BrG7qGB+5wyJqIsKc/4z3FrPHU9k789twomiJGBbEDwNbOFBJhA4O5xTFEGyH3CwDUSsRdAC6pOzDGrisf/wLAf5p70wIECBBg5qgqy7zA6G6J2TMHPxi6hvVr5rE0Zx000gtvAVhHRGsBXATwLIDPqjsQUTtj7LL4+CSAD+e1lQECBAhwG+LhO9tcJQ1vJ9RtFWOsRERfAvATADqA7zDGjhDRfwTwNmPshwC+QkRPAigBGAHwwgK2OUCAAAFuC2xaJP/5bECLXbRVYteuXeztt99ekmsHCBAgwHIFEb3DGNtVb78g+ydAgAABViACcg8QIECAFYiA3AMECBBgBSIg9wABAgRYgQjIPUCAAAFWIAJyDxAgQIAViIDcAwQIEGAFYsni3IloGMDZWR6eBVC/Yu3qQdAfbgT94UbQH24s9/7oZYzVFeBfMnKfC4jo7UaC+FcLgv5wI+gPN4L+cGO19EfglgkQIECAFYiA3AMECBBgBWK5kvu3lroBtxmC/nAj6A83gv5wY1X0x7L0uQcIECBAgNpYrpZ7gAABAgSogYDcAwQIEGAFYtmROxE9QkTHiOgEEX1tqduzGCCi7xDREBEdVra1ENHPiOgj8dosthMR/anon/eJaMfStXz+QUTdRPQqEX1IREeI6I/E9tXaHxEiepOI3hP98R/E9rVE9Ibojx8QUUhsD4vPJ8T3fUvZ/oUCEelE9C4RvSw+r7r+WFbkTkQ6gD8H8CiATQCeI6JNS9uqRcFfAnjEs+1rAH7OGFsH4OfiM8D7Zp34ewnANxepjYuFEoB/zRjbCGAvgC+KZ2C19kcBwAOMsW0AtgN4hIj2gtcx/oboj1EAL4r9XwQwyhgbBPANrNx6x38Ed7nP1dcfjLFl8wdgH4CfKJ+/DuDrS92uRbr3PgCHlc/HALSL9+0Ajon3/xXAc377rcQ/AH8H4KGgPxgAxAD8FsAe8AxMQ2y3fzfg5TL3ifeG2I+Wuu3z3A9d4AP8AwBeBkCrsT+WleUOoBPAeeXzBbFtNWINE0XJxWur2L5q+khMoe8C8AZWcX8IF8QhAEMAfgbgJIAbjLGS2EW9Z7s/xPc3AWQWt8ULjj8B8G8BWOJzBquwP5YbuZPPtiCW041V0UdElADwPwH8MWNsrNauPttWVH8wxsqMse3gFutuABv9dhOvK7o/iOhxAEOMsXfUzT67rvj+WG7kfgFAt/K5C8ClJWrLUuMqEbUDgHgdEttXfB8RkQlO7N9jjP0vsXnV9ocEY+wGgF+Ar0WkicgQX6n3bPeH+D4FYGRxW7qguAfAk0R0BsBfg7tm/gSrsD+WG7m/BWCdWPkOAXgWwA+XuE1LhR8C+Lx4/3lw37Pc/jkRJbIXwE3prlgJICIC8G0AHzLG/rPy1WrtjxwRpcX7KICPgy8kvgrgU2I3b3/IfvoUgFeYcDivBDDGvs4Y62KM9YHzwyuMseexGvtjqZ3+s1gseQzAcXC/4r9b6vYs0j1/H8BlAEVwS+NFcL/gzwF8JF5bxL4EHlF0EsAHAHYtdfvnuS/uBZ82vw/gkPh7bBX3x1YA74r+OAzg34vt/QDeBHACwN8CCIvtEfH5hPi+f6nvYQH75iCAl1drfwTyAwECBAiwArHc3DIBAgQIEKABBOQeIECAACsQAbkHCBAgwApEQO4BAgQIsAIRkHuAAAECrEAE5B4gQIAAKxABuQcIECDACsT/Bzwacc2yl8qmAAAAAElFTkSuQmCC
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<h2 id="Generator-samples-from-training">Generator samples from training<a class="anchor-link" href="#Generator-samples-from-training">&#182;</a></h2><p>View samples of images from the generator, and answer a question about the strengths and weaknesses of your trained models.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># helper function for viewing a list of passed in sample images</span>
<span class="k">def</span> <span class="nf">view_samples</span><span class="p">(</span><span class="n">epoch</span><span class="p">,</span> <span class="n">samples</span><span class="p">):</span>
    <span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">16</span><span class="p">,</span><span class="mi">4</span><span class="p">),</span> <span class="n">nrows</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">8</span><span class="p">,</span> <span class="n">sharey</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">sharex</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
    <span class="k">for</span> <span class="n">ax</span><span class="p">,</span> <span class="n">img</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">axes</span><span class="o">.</span><span class="n">flatten</span><span class="p">(),</span> <span class="n">samples</span><span class="p">[</span><span class="n">epoch</span><span class="p">]):</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">img</span><span class="o">.</span><span class="n">detach</span><span class="p">()</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span><span class="o">.</span><span class="n">numpy</span><span class="p">()</span>
        <span class="n">img</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="n">img</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
        <span class="n">img</span> <span class="o">=</span> <span class="p">((</span><span class="n">img</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span><span class="o">*</span><span class="mi">255</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span><span class="p">))</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">uint8</span><span class="p">)</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_visible</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
        <span class="n">ax</span><span class="o">.</span><span class="n">yaxis</span><span class="o">.</span><span class="n">set_visible</span><span class="p">(</span><span class="kc">False</span><span class="p">)</span>
        <span class="n">im</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">32</span><span class="p">,</span><span class="mi">32</span><span class="p">,</span><span class="mi">3</span><span class="p">)))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Load samples from generator, taken while training</span>
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s1">&#39;train_samples.pkl&#39;</span><span class="p">,</span> <span class="s1">&#39;rb&#39;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">samples</span> <span class="o">=</span> <span class="n">pkl</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">f</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">_</span> <span class="o">=</span> <span class="n">view_samples</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">samples</span><span class="p">)</span>
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<h3 id="Question:-What-do-you-notice-about-your-generated-samples-and-how-might-you-improve-this-model?">Question: What do you notice about your generated samples and how might you improve this model?<a class="anchor-link" href="#Question:-What-do-you-notice-about-your-generated-samples-and-how-might-you-improve-this-model?">&#182;</a></h3><p>When you answer this question, consider the following factors:</p>
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<li>The dataset is biased; it is made of "celebrity" faces that are mostly white</li>
<li>Model size; larger models have the opportunity to learn more features in a data feature space</li>
<li>Optimization strategy; optimizers and number of epochs affect your final result</li>
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<p><strong>Answer:</strong></p>
<p>As notice it is hard to tell the model's efficiency while having this low image quality.
For next time I think I will enrich the data with more faces (different races and ages) iterated  over more epochs and differnt optimizers.</p>

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<h3 id="Submitting-This-Project">Submitting This Project<a class="anchor-link" href="#Submitting-This-Project">&#182;</a></h3><p>When submitting this project, make sure to run all the cells before saving the notebook. Save the notebook file as "dlnd_face_generation.ipynb" and save it as a HTML file under "File" -&gt; "Download as". Include the "problem_unittests.py" files in your submission.</p>

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