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.framer-zWep7.framer-v-16p3yoa .framer-14opanf, .framer-zWep7.framer-v-eu19ks .framer-14opanf, .framer-zWep7.framer-v-1pscdzp .framer-14opanf, .framer-zWep7.framer-v-h14fgu .framer-14opanf { order: 5; width: min-content; }\",\"@supports (background: -webkit-named-image(i)) and (not (font-palette:dark)) { .framer-zWep7.framer-v-1yvww5x.framer-1h9tjzl { gap: 0px; } .framer-zWep7.framer-v-1yvww5x.framer-1h9tjzl > * { margin: 0px; margin-bottom: calc(4px / 2); margin-top: calc(4px / 2); } .framer-zWep7.framer-v-1yvww5x.framer-1h9tjzl > :first-child { margin-top: 0px; } .framer-zWep7.framer-v-1yvww5x.framer-1h9tjzl > :last-child { margin-bottom: 0px; } }\",\"@supports (background: -webkit-named-image(i)) and (not (font-palette:dark)) { .framer-zWep7.framer-v-1f7wkam.framer-1h9tjzl { gap: 0px; } .framer-zWep7.framer-v-1f7wkam.framer-1h9tjzl > * { margin: 0px; margin-bottom: calc(4px / 2); margin-top: calc(4px / 2); } .framer-zWep7.framer-v-1f7wkam.framer-1h9tjzl > :first-child { margin-top: 0px; } .framer-zWep7.framer-v-1f7wkam.framer-1h9tjzl > :last-child { margin-bottom: 0px; } }\",\"@supports (background: -webkit-named-image(i)) and (not (font-palette:dark)) { .framer-zWep7.framer-v-16p3yoa.framer-1h9tjzl { gap: 0px; } .framer-zWep7.framer-v-16p3yoa.framer-1h9tjzl > * { margin: 0px; margin-bottom: calc(4px / 2); margin-top: calc(4px / 2); } .framer-zWep7.framer-v-16p3yoa.framer-1h9tjzl > :first-child { margin-top: 0px; } .framer-zWep7.framer-v-16p3yoa.framer-1h9tjzl > :last-child { margin-bottom: 0px; } }\",\"@supports (background: -webkit-named-image(i)) and (not (font-palette:dark)) { .framer-zWep7.framer-v-eu19ks.framer-1h9tjzl { gap: 0px; } .framer-zWep7.framer-v-eu19ks.framer-1h9tjzl > * { margin: 0px; margin-bottom: calc(4px / 2); margin-top: calc(4px / 2); } .framer-zWep7.framer-v-eu19ks.framer-1h9tjzl > :first-child { margin-top: 0px; } .framer-zWep7.framer-v-eu19ks.framer-1h9tjzl > :last-child { margin-bottom: 0px; } }\",\"@supports (background: -webkit-named-image(i)) and (not (font-palette:dark)) { .framer-zWep7.framer-v-1pscdzp.framer-1h9tjzl { gap: 0px; } .framer-zWep7.framer-v-1pscdzp.framer-1h9tjzl > * { margin: 0px; margin-bottom: calc(4px / 2); margin-top: calc(4px / 2); } .framer-zWep7.framer-v-1pscdzp.framer-1h9tjzl > :first-child { margin-top: 0px; } .framer-zWep7.framer-v-1pscdzp.framer-1h9tjzl > :last-child { margin-bottom: 0px; } }\",\"@supports (background: -webkit-named-image(i)) and (not (font-palette:dark)) { .framer-zWep7.framer-v-h14fgu.framer-1h9tjzl { gap: 0px; } .framer-zWep7.framer-v-h14fgu.framer-1h9tjzl > * { margin: 0px; margin-bottom: calc(4px / 2); margin-top: calc(4px / 2); } .framer-zWep7.framer-v-h14fgu.framer-1h9tjzl > :first-child { margin-top: 0px; } .framer-zWep7.framer-v-h14fgu.framer-1h9tjzl > :last-child { margin-bottom: 0px; } }\",...sharedStyle.css];/**\n * This is a generated Framer component.\n * @framerIntrinsicHeight 190\n * @framerIntrinsicWidth 242\n * @framerCanvasComponentVariantDetails {\"propertyName\":\"variant\",\"data\":{\"default\":{\"layout\":[\"fixed\",\"auto\"]},\"xstNYBU_c\":{\"layout\":[\"fixed\",\"auto\"]},\"W0VGwIIe0\":{\"layout\":[\"fixed\",\"auto\"]},\"Z2zrg_tIS\":{\"layout\":[\"fixed\",\"auto\"]},\"DgCdZb9y7\":{\"layout\":[\"fixed\",\"auto\"]},\"gFq5kNU4F\":{\"layout\":[\"fixed\",\"auto\"]},\"D9cDTQwfg\":{\"layout\":[\"fixed\",\"auto\"]},\"KOSRAR6dz\":{\"layout\":[\"auto\",\"auto\"]},\"R26P0Yk0R\":{\"layout\":[\"auto\",\"auto\"]},\"kXp7Fh11o\":{\"layout\":[\"auto\",\"auto\"]},\"DQeL7rT0U\":{\"layout\":[\"auto\",\"auto\"]},\"LOXAQDQmG\":{\"layout\":[\"auto\",\"auto\"]},\"apEfChu2k\":{\"layout\":[\"auto\",\"auto\"]},\"icAuX3TMW\":{\"layout\":[\"auto\",\"auto\"]},\"ls7lmTlGW\":{\"layout\":[\"auto\",\"auto\"]},\"gWvthZImY\":{\"layout\":[\"auto\",\"auto\"]},\"lZ0xJZeE7\":{\"layout\":[\"auto\",\"auto\"]},\"v0o2TuWcE\":{\"layout\":[\"auto\",\"auto\"]},\"L1RNxkB_4\":{\"layout\":[\"auto\",\"auto\"]}}}\n * @framerImmutableVariables true\n * @framerDisplayContentsDiv false\n * @framerComponentViewportWidth true\n */const FramerjggVNbE9a=withCSS(Component,css,\"framer-zWep7\");export default FramerjggVNbE9a;FramerjggVNbE9a.displayName=\"Table of Contents - Paper 1\";FramerjggVNbE9a.defaultProps={height:190,width:242};addPropertyControls(FramerjggVNbE9a,{variant:{options:[\"Xj7MMO2k6\",\"xstNYBU_c\",\"W0VGwIIe0\",\"Z2zrg_tIS\",\"DgCdZb9y7\",\"gFq5kNU4F\",\"D9cDTQwfg\",\"KOSRAR6dz\",\"R26P0Yk0R\",\"kXp7Fh11o\",\"DQeL7rT0U\",\"LOXAQDQmG\",\"apEfChu2k\",\"icAuX3TMW\",\"ls7lmTlGW\",\"gWvthZImY\",\"lZ0xJZeE7\",\"v0o2TuWcE\",\"L1RNxkB_4\"],optionTitles:[\"1 Introduction\",\"2 Data Process\",\"3 Explor\",\"4 Method\",\"5 Interpretation\",\"6 Data and Additional Files\",\"Tablet\",\"Phone - 1 Small\",\"Phone 2 Small\",\"Phone 3 Small\",\"Phone 4 Small\",\"Phone 5 Small\",\"Phone 6 Small\",\"Phone 1 Big\",\"Phone 2 Big\",\"Phone 3 Big\",\"Phone 4 Big\",\"Phone 5 Big\",\"Phone 6 Big\"],title:\"Variant\",type:ControlType.Enum}});addFonts(FramerjggVNbE9a,[{explicitInter:true,fonts:[{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F\",url:\"https://framerusercontent.com/assets/DpPBYI0sL4fYLgAkX8KXOPVt7c.woff2\",weight:\"700\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116\",url:\"https://framerusercontent.com/assets/4RAEQdEOrcnDkhHiiCbJOw92Lk.woff2\",weight:\"700\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+1F00-1FFF\",url:\"https://framerusercontent.com/assets/1K3W8DizY3v4emK8Mb08YHxTbs.woff2\",weight:\"700\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0370-03FF\",url:\"https://framerusercontent.com/assets/tUSCtfYVM1I1IchuyCwz9gDdQ.woff2\",weight:\"700\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0100-024F, U+0259, U+1E00-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF\",url:\"https://framerusercontent.com/assets/VgYFWiwsAC5OYxAycRXXvhze58.woff2\",weight:\"700\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD\",url:\"https://framerusercontent.com/assets/DXD0Q7LSl7HEvDzucnyLnGBHM.woff2\",weight:\"700\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+1EA0-1EF9, U+20AB\",url:\"https://framerusercontent.com/assets/GIryZETIX4IFypco5pYZONKhJIo.woff2\",weight:\"700\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, 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U+A720-A7FF\",url:\"https://framerusercontent.com/assets/JeYwfuaPfZHQhEG8U5gtPDZ7WQ.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD\",url:\"https://framerusercontent.com/assets/vQyevYAyHtARFwPqUzQGpnDs.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+1EA0-1EF9, U+20AB\",url:\"https://framerusercontent.com/assets/b6Y37FthZeALduNqHicBT6FutY.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F\",url:\"https://framerusercontent.com/assets/BkDpl4ghaqvMi1btKFyG2tdbec.woff2\",weight:\"300\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116\",url:\"https://framerusercontent.com/assets/zAMK70AQRFSShJgUiaR5IiIhgzk.woff2\",weight:\"300\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+1F00-1FFF\",url:\"https://framerusercontent.com/assets/IETjvc5qzUaRoaruDpPSwCUM8.woff2\",weight:\"300\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0370-03FF\",url:\"https://framerusercontent.com/assets/oLCoaT3ioA0fHdJnWR9W6k7NY.woff2\",weight:\"300\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0100-024F, U+0259, U+1E00-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF\",url:\"https://framerusercontent.com/assets/Sj0PCHQSBjFmEp6NBWg6FNaKc.woff2\",weight:\"300\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD\",url:\"https://framerusercontent.com/assets/v2q8JTTTs7McDMSEhnxAIBqd0.woff2\",weight:\"300\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+1EA0-1EF9, U+20AB\",url:\"https://framerusercontent.com/assets/H4TfENUY1rh8R9UaSD6vngjJP3M.woff2\",weight:\"300\"}]},...getFontsFromSharedStyle(sharedStyle.fonts)],{supportsExplicitInterCodegen:true});\nexport const __FramerMetadata__ = {\"exports\":{\"Props\":{\"type\":\"tsType\",\"annotations\":{\"framerContractVersion\":\"1\"}},\"default\":{\"type\":\"reactComponent\",\"name\":\"FramerjggVNbE9a\",\"slots\":[],\"annotations\":{\"framerDisplayContentsDiv\":\"false\",\"framerContractVersion\":\"1\",\"framerIntrinsicHeight\":\"190\",\"framerCanvasComponentVariantDetails\":\"{\\\"propertyName\\\":\\\"variant\\\",\\\"data\\\":{\\\"default\\\":{\\\"layout\\\":[\\\"fixed\\\",\\\"auto\\\"]},\\\"xstNYBU_c\\\":{\\\"layout\\\":[\\\"fixed\\\",\\\"auto\\\"]},\\\"W0VGwIIe0\\\":{\\\"layout\\\":[\\\"fixed\\\",\\\"auto\\\"]},\\\"Z2zrg_tIS\\\":{\\\"layout\\\":[\\\"fixed\\\",\\\"auto\\\"]},\\\"DgCdZb9y7\\\":{\\\"layout\\\":[\\\"fixed\\\",\\\"auto\\\"]},\\\"gFq5kNU4F\\\":{\\\"layout\\\":[\\\"fixed\\\",\\\"auto\\\"]},\\\"D9cDTQwfg\\\":{\\\"layout\\\":[\\\"fixed\\\",\\\"auto\\\"]},\\\"KOSRAR6dz\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"R26P0Yk0R\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"kXp7Fh11o\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"DQeL7rT0U\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"LOXAQDQmG\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"apEfChu2k\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"icAuX3TMW\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"ls7lmTlGW\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"gWvthZImY\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"lZ0xJZeE7\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"v0o2TuWcE\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]},\\\"L1RNxkB_4\\\":{\\\"layout\\\":[\\\"auto\\\",\\\"auto\\\"]}}}\",\"framerComponentViewportWidth\":\"true\",\"framerIntrinsicWidth\":\"242\",\"framerImmutableVariables\":\"true\"}},\"__FramerMetadata__\":{\"type\":\"variable\"}}}\n//# sourceMappingURL=./jggVNbE9a.map", "// Generated by Framer (f030ee3)\nimport{jsx as _jsx,jsxs as _jsxs}from\"react/jsx-runtime\";import{addFonts,ComponentViewportProvider,Container,cx,GeneratedComponentContext,getFonts,getFontsFromSharedStyle,getLoadingLazyAtYPosition,Image,Link,PropertyOverrides,RichText,SVG,useComponentViewport,useCustomCursors,useHydratedBreakpointVariants,useIsOnFramerCanvas,useLocaleInfo,useRouteElementId,withCSS,withOptimizedAppearEffect,withVariantAppearEffect}from\"framer\";import{LayoutGroup,motion}from\"framer-motion\";import*as React from\"react\";import{useRef}from\"react\";import Clipboard from\"https://framerusercontent.com/modules/Hj20QU19p80mpYsvesiZ/RfHh9MIwqlgi04HKZ3Qo/Clipboard.js\";import{Video}from\"https://framerusercontent.com/modules/lRDHiNWNVWmE0lqtoVHP/K0mI40rrezffFjPjHAZX/Video.js\";import{Icon as Phosphor}from\"https://framerusercontent.com/modules/tYScH7LTqUtz5KUaUAYP/p8dptk4UIND8hbFWz9V7/Phosphor.js\";import Cursor from\"#framer/local/canvasComponent/cMAftKS3V/cMAftKS3V.js\";import NavigationBarDesktop from\"#framer/local/canvasComponent/gi2j1hnS7/gi2j1hnS7.js\";import NavigationBarPhone from\"#framer/local/canvasComponent/iBVSIkrT5/iBVSIkrT5.js\";import CopyMailBig from\"#framer/local/canvasComponent/isptOycu4/isptOycu4.js\";import TableOfContentsPaper1 from\"#framer/local/canvasComponent/jggVNbE9a/jggVNbE9a.js\";import NavigationBarTablet from\"#framer/local/canvasComponent/MAUWF7UFK/MAUWF7UFK.js\";import Back from\"#framer/local/canvasComponent/y4Vp8L7yq/y4Vp8L7yq.js\";import*as sharedStyle1 from\"#framer/local/css/jFFn8CXki/jFFn8CXki.js\";import*as sharedStyle from\"#framer/local/css/QmPaZ0bYY/QmPaZ0bYY.js\";import*as sharedStyle2 from\"#framer/local/css/QwoQ9pCJ_/QwoQ9pCJ_.js\";import metadataProvider from\"#framer/local/webPageMetadata/uf0dOGg9M/uf0dOGg9M.js\";const TableOfContentsPaper1Fonts=getFonts(TableOfContentsPaper1);const 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In this study, we investigated the trend of insurance claims by clustering patients into different groups.\\xa0 The project is interesting because clustering information into different groups can help identify the trends of claims in each group and compare them with other information. KMeans was chosen as a tool for clustering. KMeans clustering is one of the most commonly used clustering techniques in data science and machine learning. It is a type of unsupervised learning method that involves dividing data points into k distinct clusters based on similarities in their features or characteristics. K-means clustering is particularly useful in identifying patterns and trends within large and complex datasets, making it an essential tool in many fields, including healthcare, finance, marketing, and social sciences.\"}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:/*#__PURE__*/_jsx(\"br\",{className:\"trailing-break\"})}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:\"In this project, KMeans clustering was used to group patients based on certain characteristics, such as age, gender, medical history, and types of insurance policies held. By analyzing the trends of insurance claims within each cluster, researchers can gain insights into factors that contribute to the likelihood and severity of claims. The hypothesis is that there are distinct groups of patients with low, middle, and high-risk insurance claims. 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Descriptive Statistics of the numerical aspect of the data. (A) Average Medical Claim Amount by Region and Smoking Status. (B) Relationship between BMI and Medical Claim amount for Smoking status. (C) Relationship between Diabetic status and Medical Claim amount for Smoking status. (D) Relationship between blood pressure and Medical Claim amount for Smoking status. 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To simplify the research, researchers decided to generate 3 clusters, which represent low risk insurance claims, middle risk insurance claims, and high-risk insurance claims.\"})}),className:\"framer-183dk2e\",fonts:[\"Inter\"],verticalAlignment:\"top\",withExternalLayout:true}),/*#__PURE__*/_jsx(\"div\",{className:\"framer-kcf0v7\",\"data-framer-name\":\"Excel Method\",children:/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsx(React.Fragment,{children:/*#__PURE__*/_jsx(\"h2\",{className:\"framer-styles-preset-5kn7kv\",\"data-styles-preset\":\"QwoQ9pCJ_\",children:/*#__PURE__*/_jsx(\"strong\",{children:\"Excel Method\"})})}),className:\"framer-1to6kkf\",fonts:[\"Inter\",\"Inter-Bold\"],verticalAlignment:\"top\",withExternalLayout:true})}),/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsx(React.Fragment,{children:/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:\"When conducting analysis in Excel, researchers were left with different results in comparison with the python method. The template in Excel executed KMeans clustering by implementing a formula that calculates the Euclidean distance between each datapoint in comparison to its closest neighboring cluster. The Euclidean distance formula is:\"})}),className:\"framer-1k2vu8d\",fonts:[\"Inter\"],verticalAlignment:\"top\",withExternalLayout:true}),/*#__PURE__*/_jsx(PropertyOverrides,{breakpoint:baseVariant,overrides:{OwFqr1Ahl:{background:{alt:\"\",fit:\"fill\",intrinsicHeight:49,intrinsicWidth:165,pixelHeight:49,pixelWidth:165,src:\"https://framerusercontent.com/images/xI4zWqiJVRP9GyfZi6a8fsfnc.png\"}},ZIikn2Lmj:{background:{alt:\"\",fit:\"fill\",intrinsicHeight:49,intrinsicWidth:165,loading:getLoadingLazyAtYPosition((componentViewport?.y||0)+0+6429+50+420),pixelHeight:49,pixelWidth:165,src:\"https://framerusercontent.com/images/xI4zWqiJVRP9GyfZi6a8fsfnc.png\"}}},children:/*#__PURE__*/_jsx(Image,{background:{alt:\"\",fit:\"fill\",intrinsicHeight:49,intrinsicWidth:165,loading:getLoadingLazyAtYPosition((componentViewport?.y||0)+0+6470+72+420),pixelHeight:49,pixelWidth:165,src:\"https://framerusercontent.com/images/xI4zWqiJVRP9GyfZi6a8fsfnc.png\"},className:\"framer-1q6gunr\",\"data-framer-name\":\"Picture9\"})}),/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsxs(React.Fragment,{children:[/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",style:{\"--framer-text-alignment\":\"center\"},children:\"p, q = two points in Euclidean n-space\"}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",style:{\"--framer-text-alignment\":\"center\"},children:\"qi,\\xa0 pi = Euclidean vectors, starting from the origin of the space (initial point)\"}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",style:{\"--framer-text-alignment\":\"center\"},children:\"n = n-space\"})]}),className:\"framer-p5qmz4\",fonts:[\"Inter\"],verticalAlignment:\"top\",withExternalLayout:true}),/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsxs(React.Fragment,{children:[/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:\"For the preprocessing step, the data was normalized through a min-max normalization method. As mentioned above, researchers decided to use the columns with numerical data points which included: Age, BMI, Blood Pressure, Children, and Claim. This was necessary as KMeans only supports clustering observations with numerical values. The Smoker column was also added to the model and converted to 1 and 0, which represents \u201Cyes\u201D and \u201Cno\u201D respectively since smoking status had a high correlation with the insurance claims in the dataset. Three clusters were generated in the template in order to categorize our data. In order to successfully perform KMeans clustering, 11 iterations of the algorithm were performed in order to reach a 0 convergence. As a result, cluster 1 (n = 508), cluster 2 (n = 274), and cluster 3 (n = 558) each held unique means of each column which allowed researchers to extrapolate correlates in the data. Cluster 1 held a high age group, were non-smokers generally, and held a small claim amount. Cluster 2 held a medium age group, very high claim amount, and held a large population of smokers. Cluster 3 was another general cluster as it held a lower age range, low claim amount, and were non-smokers for the most part. The overall correlation of insurance claims based on the cluster groups are illustrated in Figure 5. After visualizing the data, it seemed like smoking greatly affected the insurance claims in a person\u2019s insurance policy. Although the result from Excel was different compared to the result from Python, both methods had come to the conclusion that smoking held a very large correlation with claim amounts and concluded that it was one of the biggest risk factors in terms of insurance policy claims.\\xa0\"}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:/*#__PURE__*/_jsx(\"br\",{className:\"trailing-break\"})})]}),className:\"framer-yfgrmb\",fonts:[\"Inter\"],verticalAlignment:\"top\",withExternalLayout:true}),/*#__PURE__*/_jsxs(\"div\",{className:\"framer-3y0q0m\",\"data-framer-name\":\"Figure 5\",children:[/*#__PURE__*/_jsx(\"div\",{className:\"framer-1m5icy9\",children:/*#__PURE__*/_jsx(PropertyOverrides,{breakpoint:baseVariant,overrides:{OwFqr1Ahl:{background:{alt:\"\",fit:\"fill\",intrinsicHeight:381,intrinsicWidth:636,pixelHeight:381,pixelWidth:636,sizes:\"342px\",src:\"https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png\",srcSet:\"https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png?scale-down-to=512 512w,https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png 636w\"}},ZIikn2Lmj:{background:{alt:\"\",fit:\"fill\",intrinsicHeight:381,intrinsicWidth:636,loading:getLoadingLazyAtYPosition((componentViewport?.y||0)+0+6429+50+1319+0+0+0+0),pixelHeight:381,pixelWidth:636,sizes:\"550px\",src:\"https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png\",srcSet:\"https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png?scale-down-to=512 512w,https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png 636w\"}}},children:/*#__PURE__*/_jsx(Image,{background:{alt:\"\",fit:\"fill\",intrinsicHeight:381,intrinsicWidth:636,loading:getLoadingLazyAtYPosition((componentViewport?.y||0)+0+6470+72+1319+0+0+0),pixelHeight:381,pixelWidth:636,sizes:\"864px\",src:\"https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png\",srcSet:\"https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png?scale-down-to=512 512w,https://framerusercontent.com/images/ZBFX6PzyzCWj3isBlT9gg8OYVM.png 636w\"},className:\"framer-zc3mds\",\"data-framer-name\":\"Picture10\"})})}),/*#__PURE__*/_jsx(\"div\",{className:\"framer-1929d5q\",\"data-framer-name\":\"Text\",children:/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsx(React.Fragment,{children:/*#__PURE__*/_jsxs(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:[/*#__PURE__*/_jsx(\"em\",{children:\"Figure 5\"}),\". 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Firstly, the libraries were imported into the Jupyter Notebook as illustrated below. The more significant libraries are Pandas, which help import the .csv file into the Jupyter Notebook; SKLearn, which help perform KMeans clustering based on the given dataset; Seaborn, Matplotlib, and Plotly, which help create the visualizations.\"})}),className:\"framer-lf8d17\",fonts:[\"Inter\"],verticalAlignment:\"top\",withExternalLayout:true}),/*#__PURE__*/_jsx(\"div\",{className:\"framer-1juqmeq\",\"data-framer-name\":\"Code Block\",children:/*#__PURE__*/_jsx(PropertyOverrides,{breakpoint:baseVariant,overrides:{OwFqr1Ahl:{children:/*#__PURE__*/_jsx(React.Fragment,{children:/*#__PURE__*/_jsxs(\"p\",{style:{\"--font-selector\":\"R0Y7RmlyYSBDb2RlLTMwMA==\",\"--framer-font-family\":'\"Fira Code\", monospace',\"--framer-font-size\":\"10px\",\"--framer-font-weight\":\"300\",\"--framer-text-alignment\":\"left\",\"--framer-text-color\":\"var(--token-c79c04c9-50b5-4395-a49e-43601f9b1a7e, rgb(0, 0, 0))\"},children:[\"# Import 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Visualization\"}),/*#__PURE__*/_jsx(\"br\",{}),/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"from\"}),\" sklearn.decomposition \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"import \"}),\"PCA\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0 \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-0fa63992-dcc2-45d0-9565-4fe5c6ab7f86, rgb(29, 137, 218))\"},children:\"# Generate PCA\"}),/*#__PURE__*/_jsx(\"br\",{}),/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"import\"}),\" seaborn \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"as\"}),\" sns\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0 \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-0fa63992-dcc2-45d0-9565-4fe5c6ab7f86, rgb(29, 137, 218))\"},children:\"# Visualization\"}),/*#__PURE__*/_jsx(\"br\",{}),\"pd.options.mode.chained_assignment = None\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0 \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-0fa63992-dcc2-45d0-9565-4fe5c6ab7f86, rgb(29, 137, 218))\"},children:\"# Get rid of 'SettingWithCopyWarning'\"}),/*#__PURE__*/_jsx(\"br\",{}),/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"import\"}),\" plotly.express \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"as\"}),\" 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\",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"import\"}),\" normalize\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0 \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-0fa63992-dcc2-45d0-9565-4fe5c6ab7f86, rgb(29, 137, 218))\"},children:\"# Normalize Data\"}),/*#__PURE__*/_jsx(\"br\",{}),/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"from\"}),\" matplotlib import pyplot \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-738582c4-ffc6-4bab-b837-97132f85f328, rgb(236, 72, 151))\"},children:\"as \"}),\"plt\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0\\xa0 \",/*#__PURE__*/_jsx(\"span\",{style:{\"--framer-text-color\":\"var(--token-0fa63992-dcc2-45d0-9565-4fe5c6ab7f86, rgb(29, 137, 218))\"},children:\"# 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The visual representation of PCA that was generated by sns.scatterplot after reducing from 6 domains: age, BMI, blood pressure, number of children, smoking status, and insurance claim to 3 domains. Figure A and B are the same figures with different representation methods. Figure A represents the 2D version of KMeans clustering. Figure B represents the 3D version of KMeans clustering. 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As illustrated in Figure 6A, the tree clusters are clearly distinguished from each other where most of cluster 1 does not exceed 0 on the PCA 1. Meanwhile, cluster 2 ranges from 0 to approximately 15,000 on PCA 1. Lastly, cluster 3 is starting from approximately 15,000 on PCA 1. However, Figure 6A appears to be inadequately depicted, leaving its meaning unclear to the audience. Therefore, in order to enhance the comprehensibility of the information conveyed, an additional Figure 6B has been created. Figure 6B represents the 3D version of KMeans clustering, which was generated using PCA 1, 2, and 3. However, the size of the dot on each data point depends on the insurance claims where the smaller size represents the smaller insurance claims, and the bigger size represents the larger insurance claims. As illustrated in Figure 6B, cluster 1 has patients with smaller insurance claims compared to cluster 2 and 3. Cluster 1 has a total of 890 patients with insurance claims ranging from $1,121.87 - $11,187.66, the average insurance claim is $6,418.91 (low risk insurance claims). Cluster 2 has a total of 162 patients with insurance claims ranging from $28,468.92 - $63,770.43, the average insurance claim is $40,761.31 (high risk insurance claims). Lastly, cluster 3 has a total of 288 patients with the insurance claims range from $11,244.38 - $27,641.65, the average insurance claim is $18,897.64 (middle risk insurance claims). To investigate further, researchers calculated the correlation of PCA values with each domain.\"}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:/*#__PURE__*/_jsx(\"br\",{className:\"trailing-break\"})})]}),className:\"framer-1zrc5v\",fonts:[\"Inter\"],verticalAlignment:\"top\",withExternalLayout:true}),/*#__PURE__*/_jsxs(\"div\",{className:\"framer-c2rhol\",\"data-framer-name\":\"Figure 7\",children:[/*#__PURE__*/_jsx(PropertyOverrides,{breakpoint:baseVariant,overrides:{OwFqr1Ahl:{background:{alt:\"\",fit:\"fill\",intrinsicHeight:380,intrinsicWidth:456,pixelHeight:380,pixelWidth:456,src:\"https://framerusercontent.com/images/Ci6VTXq4FV2ANRYH5jDWVgscos.png\"}},ZIikn2Lmj:{background:{alt:\"\",fit:\"fill\",intrinsicHeight:380,intrinsicWidth:456,loading:getLoadingLazyAtYPosition((componentViewport?.y||0)+0+6429+50+4130+0+0),pixelHeight:380,pixelWidth:456,src:\"https://framerusercontent.com/images/Ci6VTXq4FV2ANRYH5jDWVgscos.png\"}}},children:/*#__PURE__*/_jsx(Image,{background:{alt:\"\",fit:\"fill\",intrinsicHeight:380,intrinsicWidth:456,loading:getLoadingLazyAtYPosition((componentViewport?.y||0)+0+6470+72+4188+0+0),pixelHeight:380,pixelWidth:456,src:\"https://framerusercontent.com/images/Ci6VTXq4FV2ANRYH5jDWVgscos.png\"},className:\"framer-140g9qu\",\"data-framer-name\":\"Picture13\"})}),/*#__PURE__*/_jsx(\"div\",{className:\"framer-14azayc\",\"data-framer-name\":\"Text\",children:/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsx(React.Fragment,{children:/*#__PURE__*/_jsxs(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:[/*#__PURE__*/_jsx(\"em\",{children:\"Figure 7\"}),\". The correlation between PCA 1, 2, and 3 with the selected domains: age, BMI, blood pressure, number of children, smoking status, and insurance claim.\"]})}),className:\"framer-1ipeio0\",fonts:[\"Inter\",\"Inter-Italic\"],verticalAlignment:\"top\",withExternalLayout:true})})]}),/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsxs(React.Fragment,{children:[/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:/*#__PURE__*/_jsx(\"br\",{className:\"trailing-break\"})}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:\"As illustrated in Figure 7, PCA 1, which is considered the most important PCA because it explains the largest amount of variation in the data, has a strong correlation with both smoking status of 0.79 and insurance claim of 1. Thus, by using SKLearn, smoking status of patients has a strong correlation with the amount of insurance claim they would receive, which was suggested by looking at the visual representation and correlation.\"})]}),className:\"framer-18a37e1\",fonts:[\"Inter\"],verticalAlignment:\"top\",withExternalLayout:true})]}),/*#__PURE__*/_jsxs(\"div\",{className:\"framer-kvtvrc\",\"data-framer-name\":\"Interpretation and Future Work\",id:elementId4,ref:ref5,children:[/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsx(React.Fragment,{children:/*#__PURE__*/_jsx(\"h2\",{className:\"framer-styles-preset-5kn7kv\",\"data-styles-preset\":\"QwoQ9pCJ_\",children:/*#__PURE__*/_jsx(\"strong\",{children:\"Interpretation and Future Work\"})})}),className:\"framer-xx8iau\",fonts:[\"Inter\",\"Inter-Bold\"],verticalAlignment:\"top\",withExternalLayout:true}),/*#__PURE__*/_jsx(RichText,{__fromCanvasComponent:true,children:/*#__PURE__*/_jsxs(React.Fragment,{children:[/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:\"Although the clustering from Excel and Python methods resulted differently, both methods illustrated that smoking status of patients had a high influence on insurance claims compared to other elements from the dataset. The smoking status also heavily influenced PCA 1 value, which means that the variable was strongly associated with the direction of greatest variance in the data. In addition, there are several potential errors that cause the result discrepancy from Excel and Python methods despite using the same dataset. First, KMeans clustering from SKLearn in Python involves randomly initializing the cluster centers, which can lead to different results each time the algorithm is run. Second, different implementations of KMeans may use different convergence criteria, such as the number of iterations or the change in the cluster centers. If the convergence criteria are different, it can lead to different results. In conclusion, the results from both methods provided evidence that each element or characteristic of patients influenced the insurance claim they could receive. However, each characteristic may weigh differently from each other. For instance, based on the correlation, insurance companies used the smoking status of patients/customers as a main criterion to define the insurance claims individuals would receive.\"}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:/*#__PURE__*/_jsx(\"br\",{className:\"trailing-break\"})}),/*#__PURE__*/_jsx(\"p\",{className:\"framer-styles-preset-12mldr1\",\"data-styles-preset\":\"jFFn8CXki\",children:\"For future study, first, researchers could choose all the characteristics on the dataset instead of choosing the specific characteristics: age, BMI, blood pressure, number of children, smoking status, and insurance claim. Although gender, diabetic status, and region were proven to have low correlation with insurance claims, those characteristics might have some impacts on clustering groups or even influence the PCA values. Second, researchers could try to use different approaches to generate the clusters such as using the K-Nearest Neighbors algorithm or using different methods of normalizing the data. Third, the dataset could be improved by collecting another domain that may influence the insurance claims: income of patients. A patient's income level can determine whether they are eligible for certain insurance plans or government-sponsored programs, such as Medicaid. Patients with lower incomes may qualify for these programs, which can provide more comprehensive coverage at a lower cost. 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.framer-1f1w5l0-container { flex: none; height: 540px; position: relative; width: 540px; will-change: var(--framer-will-change-effect-override, transform); }\",\".framer-JaGvC .framer-100avjx { align-content: center; align-items: center; background-color: var(--token-deef148b-7e63-4ec3-8c99-8690daaf1503, #e3e3fc); display: flex; flex: none; flex-direction: row; flex-wrap: nowrap; gap: 10px; height: min-content; justify-content: center; overflow: hidden; padding: 0px; position: relative; width: 100%; }\",\".framer-JaGvC .framer-140g9qu { aspect-ratio: 1.2 / 1; flex: none; height: var(--framer-aspect-ratio-supported, 515px); overflow: visible; position: relative; width: 618px; }\",\".framer-JaGvC .framer-1slnqci { align-content: center; align-items: center; display: flex; flex: none; flex-direction: column; flex-wrap: nowrap; gap: 12px; height: min-content; justify-content: center; overflow: hidden; padding: 72px 288px 72px 288px; position: relative; width: 1440px; }\",\".framer-JaGvC 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var(--framer-will-change-override, transform); }\",\".framer-JaGvC .framer-1du3uc4 { aspect-ratio: 1 / 1; background-color: #6444be; flex: none; height: var(--framer-aspect-ratio-supported, 89px); overflow: hidden; position: relative; width: 89px; }\",\".framer-JaGvC .framer-1o1yy3a-container { flex: none; height: 63px; left: calc(48.31460674157306% - 63px / 2); position: absolute; top: calc(49.43820224719103% - 63px / 2); width: 63px; }\",\".framer-JaGvC .framer-7i5qkl { aspect-ratio: 1.5537459283387622 / 1; flex: none; height: var(--framer-aspect-ratio-supported, 556px); overflow: visible; position: relative; width: 100%; }\",\".framer-JaGvC .framer-1i0cgpf { align-content: center; align-items: center; display: flex; flex: none; flex-direction: column; flex-wrap: nowrap; gap: 10px; height: min-content; justify-content: center; overflow: hidden; padding: 0px; position: relative; width: 100%; }\",\".framer-JaGvC .framer-kuimvn { --framer-paragraph-spacing: 0px; flex: none; height: auto; position: relative; white-space: pre-wrap; width: 1440px; word-break: break-word; word-wrap: break-word; }\",\".framer-JaGvC .framer-1lnxn91 { align-content: center; align-items: center; background-color: #ffffff; display: flex; flex: none; flex-direction: row; flex-wrap: nowrap; gap: 0px; height: 300px; justify-content: center; overflow: visible; padding: 0px; position: relative; width: 100%; }\",\".framer-JaGvC .framer-1xtl9tz { --border-bottom-width: 0px; --border-color: var(--token-63d76dc5-0c3e-40e3-9e8a-9e65d8071d05, #ccccf9); --border-left-width: 0px; --border-right-width: 2px; --border-style: solid; --border-top-width: 0px; align-content: center; align-items: center; background-color: var(--token-deef148b-7e63-4ec3-8c99-8690daaf1503, #e3e3fc); display: flex; flex: 1 0 0px; flex-direction: column; flex-wrap: nowrap; gap: 10px; height: 100%; justify-content: center; overflow: hidden; padding: 0px; position: relative; text-decoration: none; width: 1px; will-change: var(--framer-will-change-effect-override, transform); }\",\".framer-JaGvC .framer-18d4qqz { --border-bottom-width: 0px; --border-color: var(--token-63d76dc5-0c3e-40e3-9e8a-9e65d8071d05, #ccccf9); --border-left-width: 2px; --border-right-width: 0px; --border-style: solid; --border-top-width: 0px; align-content: center; align-items: center; background-color: var(--token-deef148b-7e63-4ec3-8c99-8690daaf1503, #e3e3fc); display: flex; flex: 1 0 0px; flex-direction: column; flex-wrap: nowrap; gap: 10px; height: 100%; justify-content: center; overflow: hidden; padding: 0px; position: relative; text-decoration: none; width: 1px; will-change: var(--framer-will-change-effect-override, transform); }\",\".framer-JaGvC .framer-1rx0it2-container { flex: none; height: auto; left: 24px; position: fixed; top: 116px; width: 61px; will-change: var(--framer-will-change-effect-override, transform); z-index: 1; }\",\".framer-JaGvC .framer-rq412g { align-content: center; align-items: center; display: flex; 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background-color: #6444be; flex: none; height: var(--framer-aspect-ratio-supported, 45px); overflow: hidden; position: relative; width: 45px; }\",\".framer-JaGvC .framer-1w940q7-container, .framer-JaGvC .framer-16moaku-container { flex: none; height: 33px; left: calc(51.11111111111113% - 33px / 2); position: absolute; top: calc(51.11111111111113% - 33px / 2); width: 33px; }\",\".framer-JaGvC .framer-1xwe8q8 { align-content: center; align-items: center; display: flex; flex: none; flex-direction: column; flex-wrap: nowrap; gap: 12px; height: min-content; justify-content: center; overflow: visible; padding: 12px 24px 12px 24px; position: relative; width: 100%; }\",\".framer-JaGvC .framer-jrfhr9 { --framer-paragraph-spacing: 0px; flex: none; height: auto; position: relative; white-space: pre-wrap; width: 100%; word-break: break-word; word-wrap: break-word; }\",\".framer-JaGvC .framer-9hsp7m { align-content: center; align-items: center; display: flex; flex: none; flex-direction: row; flex-wrap: nowrap; gap: 12px; height: min-content; justify-content: center; overflow: visible; padding: 0px; position: relative; width: 100%; will-change: var(--framer-will-change-effect-override, transform); }\",\".framer-JaGvC .framer-x4dk83 { flex: none; height: 15px; position: relative; width: 20px; }\",\".framer-JaGvC .framer-13bian9 { align-content: center; align-items: center; display: flex; flex: none; flex-direction: row; flex-wrap: wrap; height: min-content; justify-content: space-evenly; overflow: visible; padding: 0px; position: relative; width: 100%; }\",\".framer-JaGvC .framer-9tk8r3 { align-content: center; align-items: center; display: flex; flex: none; flex-direction: row; flex-wrap: nowrap; gap: 12px; height: min-content; justify-content: center; overflow: visible; padding: 0px; position: relative; text-decoration: none; width: min-content; will-change: var(--framer-will-change-effect-override, transform); }\",\".framer-JaGvC .framer-ebt95u, .framer-JaGvC .framer-1ba3n0t { aspect-ratio: 1 / 1; background-color: #6444be; flex: none; height: var(--framer-aspect-ratio-supported, 20px); overflow: hidden; position: relative; width: 20px; }\",\".framer-JaGvC .framer-sxw70n-container, .framer-JaGvC .framer-r6vadv-container { flex: none; height: 17px; left: calc(50.00000000000002% - 17px / 2); position: absolute; top: calc(50.00000000000002% - 17px / 2); width: 17px; }\",\".framer-JaGvC .framer-1atjsep { align-content: center; align-items: center; display: flex; flex: none; flex-direction: row; flex-wrap: nowrap; gap: 12px; height: min-content; justify-content: flex-start; overflow: visible; padding: 0px; position: relative; text-decoration: none; width: min-content; will-change: var(--framer-will-change-effect-override, transform); }\",\"@supports (background: -webkit-named-image(i)) and (not (scale:1)) { .framer-JaGvC.framer-vlx63s, .framer-JaGvC .framer-cdei49, .framer-JaGvC .framer-12wvkw, .framer-JaGvC .framer-w6ftis, .framer-JaGvC .framer-w6qvw2, .framer-JaGvC .framer-1vhdzfv, .framer-JaGvC .framer-1jwopj3, .framer-JaGvC .framer-17la2m2, .framer-JaGvC .framer-16cyqbs, .framer-JaGvC .framer-12ck80i, .framer-JaGvC .framer-zl844c, .framer-JaGvC .framer-104quly, .framer-JaGvC .framer-1uk006i, .framer-JaGvC .framer-dfrnyv, .framer-JaGvC .framer-1upqvdb, .framer-JaGvC .framer-1b4ts3d, .framer-JaGvC .framer-1wkl2sg, .framer-JaGvC .framer-1lv60oo, .framer-JaGvC .framer-kcf0v7, .framer-JaGvC .framer-3y0q0m, .framer-JaGvC .framer-1m5icy9, .framer-JaGvC .framer-1929d5q, .framer-JaGvC .framer-kl5k1b, .framer-JaGvC .framer-1juqmeq, .framer-JaGvC .framer-k7zy9j, .framer-JaGvC .framer-173cdyr, .framer-JaGvC .framer-1r26a91, .framer-JaGvC .framer-1k8d80d, .framer-JaGvC .framer-100avjx, .framer-JaGvC .framer-c2rhol, .framer-JaGvC .framer-14azayc, .framer-JaGvC .framer-kvtvrc, .framer-JaGvC .framer-1slnqci, .framer-JaGvC .framer-9rcyir, .framer-JaGvC .framer-1f7pagc, .framer-JaGvC .framer-1i0cgpf, .framer-JaGvC .framer-1lnxn91, .framer-JaGvC .framer-1xtl9tz, .framer-JaGvC .framer-18d4qqz, .framer-JaGvC .framer-rq412g, .framer-JaGvC .framer-gybm20, .framer-JaGvC .framer-ioz2g1, .framer-JaGvC .framer-1p1w8pd, .framer-JaGvC .framer-uevlkc, .framer-JaGvC .framer-1gkyc31, .framer-JaGvC .framer-1xwe8q8, .framer-JaGvC .framer-9hsp7m, .framer-JaGvC .framer-9tk8r3, .framer-JaGvC .framer-oj4nci, .framer-JaGvC .framer-1atjsep, .framer-JaGvC .framer-ii7aor { gap: 0px; } .framer-JaGvC.framer-vlx63s > *, .framer-JaGvC .framer-w6qvw2 > *, .framer-JaGvC .framer-1jwopj3 > *, .framer-JaGvC .framer-12ck80i > *, .framer-JaGvC .framer-1upqvdb > *, .framer-JaGvC .framer-3y0q0m > *, .framer-JaGvC .framer-k7zy9j > *, .framer-JaGvC .framer-c2rhol > * { margin: 0px; margin-bottom: calc(0px / 2); margin-top: calc(0px / 2); } .framer-JaGvC.framer-vlx63s > :first-child, .framer-JaGvC .framer-cdei49 > :first-child, .framer-JaGvC .framer-12wvkw > :first-child, .framer-JaGvC .framer-w6ftis > :first-child, .framer-JaGvC .framer-w6qvw2 > :first-child, .framer-JaGvC .framer-1jwopj3 > :first-child, .framer-JaGvC .framer-16cyqbs > :first-child, .framer-JaGvC .framer-12ck80i > :first-child, .framer-JaGvC .framer-1upqvdb > :first-child, .framer-JaGvC .framer-1lv60oo > :first-child, .framer-JaGvC .framer-3y0q0m > :first-child, .framer-JaGvC .framer-k7zy9j > :first-child, .framer-JaGvC .framer-1k8d80d > :first-child, .framer-JaGvC .framer-c2rhol > :first-child, .framer-JaGvC .framer-kvtvrc > :first-child, .framer-JaGvC .framer-1slnqci > :first-child, .framer-JaGvC .framer-1i0cgpf > :first-child, .framer-JaGvC .framer-1xtl9tz > :first-child, .framer-JaGvC .framer-18d4qqz > :first-child, .framer-JaGvC .framer-rq412g > :first-child, .framer-JaGvC .framer-1xwe8q8 > :first-child { margin-top: 0px; } .framer-JaGvC.framer-vlx63s > :last-child, .framer-JaGvC .framer-cdei49 > :last-child, .framer-JaGvC .framer-12wvkw > :last-child, .framer-JaGvC .framer-w6ftis > :last-child, .framer-JaGvC .framer-w6qvw2 > :last-child, .framer-JaGvC .framer-1jwopj3 > :last-child, .framer-JaGvC .framer-16cyqbs > :last-child, .framer-JaGvC .framer-12ck80i > :last-child, .framer-JaGvC .framer-1upqvdb > :last-child, .framer-JaGvC .framer-1lv60oo > :last-child, .framer-JaGvC .framer-3y0q0m > :last-child, .framer-JaGvC .framer-k7zy9j > :last-child, .framer-JaGvC .framer-1k8d80d > :last-child, .framer-JaGvC .framer-c2rhol > :last-child, .framer-JaGvC .framer-kvtvrc > :last-child, .framer-JaGvC .framer-1slnqci > :last-child, .framer-JaGvC .framer-1i0cgpf > :last-child, .framer-JaGvC .framer-1xtl9tz > :last-child, .framer-JaGvC .framer-18d4qqz > :last-child, .framer-JaGvC .framer-rq412g > :last-child, .framer-JaGvC .framer-1xwe8q8 > :last-child { margin-bottom: 0px; } .framer-JaGvC .framer-cdei49 > *, .framer-JaGvC .framer-1k8d80d > *, .framer-JaGvC .framer-1i0cgpf > *, .framer-JaGvC .framer-1xtl9tz > *, .framer-JaGvC .framer-18d4qqz > * { margin: 0px; margin-bottom: calc(10px / 2); margin-top: calc(10px / 2); } .framer-JaGvC .framer-12wvkw > *, .framer-JaGvC .framer-w6ftis > *, .framer-JaGvC .framer-16cyqbs > *, .framer-JaGvC .framer-1lv60oo > *, .framer-JaGvC .framer-kvtvrc > *, .framer-JaGvC .framer-1slnqci > *, .framer-JaGvC .framer-1xwe8q8 > * { margin: 0px; margin-bottom: calc(12px / 2); margin-top: calc(12px / 2); } .framer-JaGvC .framer-1vhdzfv > *, .framer-JaGvC .framer-17la2m2 > *, .framer-JaGvC .framer-dfrnyv > *, .framer-JaGvC .framer-1wkl2sg > *, .framer-JaGvC .framer-1929d5q > *, .framer-JaGvC .framer-1r26a91 > *, .framer-JaGvC .framer-14azayc > *, .framer-JaGvC .framer-1lnxn91 > * { margin: 0px; margin-left: calc(0px / 2); margin-right: calc(0px / 2); } .framer-JaGvC .framer-1vhdzfv > :first-child, .framer-JaGvC .framer-17la2m2 > :first-child, .framer-JaGvC .framer-zl844c > :first-child, .framer-JaGvC .framer-104quly > :first-child, .framer-JaGvC .framer-1uk006i > :first-child, .framer-JaGvC .framer-dfrnyv > :first-child, .framer-JaGvC .framer-1b4ts3d > :first-child, .framer-JaGvC .framer-1wkl2sg > :first-child, .framer-JaGvC .framer-kcf0v7 > :first-child, .framer-JaGvC .framer-1m5icy9 > :first-child, .framer-JaGvC .framer-1929d5q > :first-child, .framer-JaGvC .framer-kl5k1b > :first-child, .framer-JaGvC .framer-1juqmeq > :first-child, .framer-JaGvC .framer-173cdyr > :first-child, .framer-JaGvC .framer-1r26a91 > :first-child, .framer-JaGvC .framer-100avjx > :first-child, .framer-JaGvC .framer-14azayc > :first-child, .framer-JaGvC .framer-9rcyir > :first-child, .framer-JaGvC .framer-1f7pagc > :first-child, .framer-JaGvC .framer-1lnxn91 > :first-child, .framer-JaGvC .framer-gybm20 > :first-child, .framer-JaGvC .framer-ioz2g1 > :first-child, .framer-JaGvC .framer-1p1w8pd > :first-child, .framer-JaGvC .framer-uevlkc > :first-child, .framer-JaGvC .framer-1gkyc31 > :first-child, .framer-JaGvC .framer-9hsp7m > :first-child, .framer-JaGvC .framer-9tk8r3 > :first-child, .framer-JaGvC .framer-oj4nci > :first-child, .framer-JaGvC .framer-1atjsep > :first-child, .framer-JaGvC .framer-ii7aor > :first-child { margin-left: 0px; } .framer-JaGvC .framer-1vhdzfv > :last-child, .framer-JaGvC .framer-17la2m2 > :last-child, .framer-JaGvC .framer-zl844c > :last-child, .framer-JaGvC .framer-104quly > :last-child, .framer-JaGvC .framer-1uk006i > :last-child, .framer-JaGvC .framer-dfrnyv > :last-child, .framer-JaGvC .framer-1b4ts3d > :last-child, .framer-JaGvC .framer-1wkl2sg > :last-child, .framer-JaGvC .framer-kcf0v7 > :last-child, .framer-JaGvC .framer-1m5icy9 > :last-child, .framer-JaGvC .framer-1929d5q > :last-child, .framer-JaGvC .framer-kl5k1b > :last-child, .framer-JaGvC .framer-1juqmeq > :last-child, .framer-JaGvC .framer-173cdyr > :last-child, .framer-JaGvC .framer-1r26a91 > :last-child, .framer-JaGvC .framer-100avjx > :last-child, .framer-JaGvC .framer-14azayc > :last-child, .framer-JaGvC .framer-9rcyir > :last-child, .framer-JaGvC .framer-1f7pagc > :last-child, .framer-JaGvC .framer-1lnxn91 > :last-child, .framer-JaGvC .framer-gybm20 > :last-child, .framer-JaGvC .framer-ioz2g1 > :last-child, .framer-JaGvC .framer-1p1w8pd > :last-child, .framer-JaGvC .framer-uevlkc > :last-child, .framer-JaGvC .framer-1gkyc31 > :last-child, .framer-JaGvC .framer-9hsp7m > :last-child, .framer-JaGvC .framer-9tk8r3 > :last-child, .framer-JaGvC .framer-oj4nci > :last-child, .framer-JaGvC .framer-1atjsep > :last-child, .framer-JaGvC .framer-ii7aor > :last-child { margin-right: 0px; } .framer-JaGvC .framer-zl844c > *, .framer-JaGvC .framer-104quly > *, .framer-JaGvC .framer-1uk006i > *, .framer-JaGvC .framer-1b4ts3d > *, .framer-JaGvC .framer-kcf0v7 > *, .framer-JaGvC .framer-1m5icy9 > *, .framer-JaGvC .framer-kl5k1b > *, .framer-JaGvC .framer-1juqmeq > *, .framer-JaGvC .framer-173cdyr > *, .framer-JaGvC .framer-100avjx > *, .framer-JaGvC .framer-1f7pagc > *, .framer-JaGvC .framer-1p1w8pd > *, .framer-JaGvC .framer-1gkyc31 > *, .framer-JaGvC .framer-oj4nci > *, .framer-JaGvC .framer-ii7aor > * { margin: 0px; margin-left: calc(10px / 2); margin-right: calc(10px / 2); } .framer-JaGvC .framer-9rcyir > *, .framer-JaGvC .framer-ioz2g1 > *, .framer-JaGvC .framer-uevlkc > * { margin: 0px; margin-left: calc(24px / 2); margin-right: calc(24px / 2); } .framer-JaGvC .framer-rq412g > * { margin: 0px; margin-bottom: calc(24px / 2); margin-top: calc(24px / 2); } .framer-JaGvC .framer-gybm20 > * { margin: 0px; margin-left: calc(44px / 2); margin-right: calc(44px / 2); } .framer-JaGvC .framer-9hsp7m > *, .framer-JaGvC .framer-9tk8r3 > *, .framer-JaGvC .framer-1atjsep > * { margin: 0px; margin-left: calc(12px / 2); margin-right: calc(12px / 2); } }\",...sharedStyle.css,...sharedStyle1.css,...sharedStyle2.css,'.framer-JaGvC[data-border=\"true\"]::after, .framer-JaGvC [data-border=\"true\"]::after { content: \"\"; border-width: var(--border-top-width, 0) var(--border-right-width, 0) var(--border-bottom-width, 0) var(--border-left-width, 0); border-color: var(--border-color, none); border-style: var(--border-style, none); width: 100%; height: 100%; position: absolute; box-sizing: border-box; left: 0; top: 0; border-radius: inherit; pointer-events: none; }',\"@media (min-width: 810px) and (max-width: 1439px) { .framer-JaGvC.framer-vlx63s { width: 810px; } .framer-JaGvC .framer-18191xz-container { left: unset; order: 0; right: 20px; top: 321px; transform: unset; } .framer-JaGvC .framer-mamhlg-container { order: 1; } .framer-JaGvC .framer-hwf4rq-container { left: 24px; order: 4; top: 14%; transform: translateY(-50%); z-index: 4; } .framer-JaGvC .framer-cdei49 { order: 5; padding: 225px 130px 0px 130px; width: 100%; } .framer-JaGvC .framer-12wvkw { order: 6; padding: 50px 130px 0px 130px; width: 100%; } .framer-JaGvC .framer-w6ftis { order: 7; padding: 50px 130px 0px 130px; width: 100%; } .framer-JaGvC .framer-w6qvw2, .framer-JaGvC .framer-1jwopj3, .framer-JaGvC .framer-12ck80i, .framer-JaGvC .framer-1upqvdb, .framer-JaGvC .framer-3y0q0m, .framer-JaGvC .framer-1juqmeq, .framer-JaGvC .framer-k7zy9j, .framer-JaGvC .framer-c2rhol { width: 550px; } .framer-JaGvC .framer-1uaauue { height: var(--framer-aspect-ratio-supported, 335px); } .framer-JaGvC .framer-1sf4gsz { height: var(--framer-aspect-ratio-supported, 287px); } .framer-JaGvC .framer-16cyqbs { order: 8; padding: 50px 130px 0px 130px; width: 100%; } .framer-JaGvC .framer-1sapm7g { white-space: pre-wrap; width: 100%; word-break: break-word; word-wrap: break-word; } .framer-JaGvC .framer-vgft0c { height: var(--framer-aspect-ratio-supported, 240px); } .framer-JaGvC .framer-gw8y4r { height: var(--framer-aspect-ratio-supported, 185px); } .framer-JaGvC .framer-12tcimn { height: var(--framer-aspect-ratio-supported, 243px); } .framer-JaGvC .framer-71v95f { height: var(--framer-aspect-ratio-supported, 189px); } .framer-JaGvC .framer-1bshubq { height: var(--framer-aspect-ratio-supported, 182px); } .framer-JaGvC .framer-1b4ts3d, .framer-JaGvC .framer-1m5icy9 { flex-direction: column; } .framer-JaGvC .framer-1crg8fa { height: var(--framer-aspect-ratio-supported, 466px); width: 100%; } .framer-JaGvC .framer-1lv60oo { order: 9; padding: 50px 130px 0px 130px; width: 100%; } .framer-JaGvC .framer-kcf0v7, .framer-JaGvC .framer-kl5k1b, .framer-JaGvC .framer-kuimvn { width: 100%; } .framer-JaGvC .framer-1q6gunr { height: var(--framer-aspect-ratio-supported, 84px); } .framer-JaGvC .framer-zc3mds { flex: none; height: var(--framer-aspect-ratio-supported, 329px); width: 100%; } .framer-JaGvC .framer-butf67 { height: var(--framer-aspect-ratio-supported, 213px); } .framer-JaGvC .framer-139t8dk { height: var(--framer-aspect-ratio-supported, 275px); } .framer-JaGvC .framer-140g9qu { height: var(--framer-aspect-ratio-supported, 414px); width: 497px; } .framer-JaGvC .framer-kvtvrc { order: 10; padding: 50px 130px 0px 130px; width: 100%; } .framer-JaGvC .framer-1slnqci { order: 11; padding: 50px 130px 50px 130px; width: 100%; } .framer-JaGvC .framer-7i5qkl { height: var(--framer-aspect-ratio-supported, 354px); width: 550px; } .framer-JaGvC .framer-1i0cgpf { order: 12; } .framer-JaGvC .framer-1xtl9tz { --border-right-width: 1px; } .framer-JaGvC .framer-18d4qqz { --border-left-width: 1px; } .framer-JaGvC .framer-rq412g { order: 14; width: 100%; } @supports (background: -webkit-named-image(i)) and (not (scale:1)) { .framer-JaGvC .framer-1b4ts3d, .framer-JaGvC .framer-1m5icy9 { gap: 0px; } .framer-JaGvC .framer-1b4ts3d > *, .framer-JaGvC .framer-1m5icy9 > * { margin: 0px; margin-bottom: calc(10px / 2); margin-top: calc(10px / 2); } .framer-JaGvC .framer-1b4ts3d > :first-child, .framer-JaGvC .framer-1m5icy9 > :first-child { margin-top: 0px; } .framer-JaGvC .framer-1b4ts3d > :last-child, .framer-JaGvC .framer-1m5icy9 > :last-child { margin-bottom: 0px; } }}\",\"@media (max-width: 809px) { .framer-JaGvC.framer-vlx63s { width: 390px; } .framer-JaGvC .framer-18191xz-container { bottom: 22px; left: unset; order: 0; right: 22px; top: unset; transform: unset; width: auto; } .framer-JaGvC .framer-1mr6l8u-container { order: 3; } .framer-JaGvC .framer-cdei49 { order: 6; padding: 175px 24px 0px 24px; width: 100%; } .framer-JaGvC .framer-12wvkw { order: 7; padding: 24px 24px 0px 24px; width: 100%; } .framer-JaGvC .framer-w6ftis { order: 8; padding: 24px 24px 0px 24px; width: 100%; } .framer-JaGvC .framer-w6qvw2, .framer-JaGvC .framer-1jwopj3, .framer-JaGvC .framer-12ck80i, .framer-JaGvC .framer-1upqvdb, .framer-JaGvC .framer-3y0q0m, .framer-JaGvC .framer-1juqmeq, .framer-JaGvC .framer-k7zy9j, .framer-JaGvC .framer-1k8d80d, .framer-JaGvC .framer-c2rhol { width: 342px; } .framer-JaGvC .framer-1uaauue { height: var(--framer-aspect-ratio-supported, 209px); } .framer-JaGvC .framer-1sf4gsz { height: var(--framer-aspect-ratio-supported, 179px); } .framer-JaGvC .framer-16cyqbs { order: 9; padding: 24px 24px 0px 24px; width: 100%; } .framer-JaGvC .framer-1sapm7g { white-space: pre-wrap; width: 100%; word-break: break-word; word-wrap: break-word; } .framer-JaGvC .framer-zl844c, .framer-JaGvC .framer-104quly, .framer-JaGvC .framer-1uk006i, .framer-JaGvC .framer-173cdyr { padding: 20px 0px 0px 0px; } .framer-JaGvC .framer-vgft0c { height: var(--framer-aspect-ratio-supported, 147px); } .framer-JaGvC .framer-gw8y4r { height: var(--framer-aspect-ratio-supported, 114px); } .framer-JaGvC .framer-12tcimn { height: var(--framer-aspect-ratio-supported, 152px); } .framer-JaGvC .framer-71v95f { height: var(--framer-aspect-ratio-supported, 116px); } .framer-JaGvC .framer-1bshubq { height: var(--framer-aspect-ratio-supported, 112px); } .framer-JaGvC .framer-1b4ts3d, .framer-JaGvC .framer-1m5icy9 { flex-direction: column; } .framer-JaGvC .framer-1crg8fa { height: var(--framer-aspect-ratio-supported, 290px); width: 100%; } .framer-JaGvC .framer-1lv60oo { order: 10; padding: 24px 24px 0px 24px; width: 100%; } .framer-JaGvC .framer-kcf0v7, .framer-JaGvC .framer-kl5k1b, .framer-JaGvC .framer-kuimvn { width: 100%; } .framer-JaGvC .framer-1q6gunr { height: var(--framer-aspect-ratio-supported, 32px); width: 108px; } .framer-JaGvC .framer-zc3mds { flex: none; height: var(--framer-aspect-ratio-supported, 204px); width: 100%; } .framer-JaGvC .framer-butf67 { height: var(--framer-aspect-ratio-supported, 131px); } .framer-JaGvC .framer-139t8dk { height: var(--framer-aspect-ratio-supported, 169px); } .framer-JaGvC .framer-1f1w5l0-container { height: auto; width: 100%; } .framer-JaGvC .framer-140g9qu { height: var(--framer-aspect-ratio-supported, 285px); width: 342px; } .framer-JaGvC .framer-kvtvrc { order: 11; padding: 24px 24px 0px 24px; width: 100%; } .framer-JaGvC .framer-1slnqci { order: 12; padding: 24px; width: 100%; } .framer-JaGvC .framer-9rcyir { gap: 12px; } .framer-JaGvC .framer-1du3uc4 { height: var(--framer-aspect-ratio-supported, 27px); width: 27px; } .framer-JaGvC .framer-1o1yy3a-container { height: 23px; left: calc(48.14814814814817% - 23px / 2); top: calc(51.85185185185187% - 23px / 2); width: 23px; } .framer-JaGvC .framer-7i5qkl { height: var(--framer-aspect-ratio-supported, 220px); width: 342px; } .framer-JaGvC .framer-1i0cgpf { order: 13; } .framer-JaGvC .framer-1lnxn91 { flex-direction: column; height: 200px; } .framer-JaGvC .framer-1xtl9tz { --border-bottom-width: 1px; --border-right-width: 0px; height: 1px; width: 100%; } .framer-JaGvC .framer-18d4qqz { --border-left-width: 0px; --border-top-width: 1px; height: 1px; width: 100%; } .framer-JaGvC .framer-1rx0it2-container { order: 5; } .framer-JaGvC .framer-1xwe8q8 { order: 15; } @supports (background: -webkit-named-image(i)) and (not (scale:1)) { .framer-JaGvC .framer-1b4ts3d, .framer-JaGvC .framer-1m5icy9, .framer-JaGvC .framer-9rcyir, .framer-JaGvC .framer-1lnxn91 { gap: 0px; } .framer-JaGvC .framer-1b4ts3d > *, .framer-JaGvC .framer-1m5icy9 > * { margin: 0px; margin-bottom: calc(10px / 2); margin-top: calc(10px / 2); } .framer-JaGvC .framer-1b4ts3d > :first-child, .framer-JaGvC .framer-1m5icy9 > :first-child, .framer-JaGvC .framer-1lnxn91 > :first-child { margin-top: 0px; } .framer-JaGvC .framer-1b4ts3d > :last-child, .framer-JaGvC .framer-1m5icy9 > :last-child, .framer-JaGvC .framer-1lnxn91 > :last-child { margin-bottom: 0px; } .framer-JaGvC .framer-9rcyir > * { margin: 0px; margin-left: calc(12px / 2); margin-right: calc(12px / 2); } .framer-JaGvC .framer-9rcyir > :first-child { margin-left: 0px; } .framer-JaGvC .framer-9rcyir > :last-child { margin-right: 0px; } .framer-JaGvC .framer-1lnxn91 > * { margin: 0px; margin-bottom: calc(0px / 2); margin-top: calc(0px / 2); } }}\"];/**\n * This is a generated Framer component.\n * @framerIntrinsicHeight 16113\n * @framerIntrinsicWidth 1440\n * @framerCanvasComponentVariantDetails {\"propertyName\":\"variant\",\"data\":{\"default\":{\"layout\":[\"fixed\",\"auto\"]},\"ZIikn2Lmj\":{\"layout\":[\"fixed\",\"auto\"]},\"OwFqr1Ahl\":{\"layout\":[\"fixed\",\"auto\"]}}}\n * @framerImmutableVariables true\n * @framerDisplayContentsDiv false\n * @framerComponentViewportWidth true\n * @framerAcceptsLayoutTemplate true\n * @framerScrollSections {\"GJEQE69I9\":{\"pattern\":\":GJEQE69I9\",\"name\":\"introduction\"},\"rhnaTKNMS\":{\"pattern\":\":rhnaTKNMS\",\"name\":\"data-and-data-preprocessing\"},\"sIzbF_Ww7\":{\"pattern\":\":sIzbF_Ww7\",\"name\":\"exploratory-data-analysis-with-visualization\"},\"WZOSasFSm\":{\"pattern\":\":WZOSasFSm\",\"name\":\"method-and-results\"},\"LJtsnNILu\":{\"pattern\":\":LJtsnNILu\",\"name\":\"interpretation-and-future-work\"},\"jOuOg3gkn\":{\"pattern\":\":jOuOg3gkn\",\"name\":\"data\"}}\n * @framerResponsiveScreen\n */const Frameruf0dOGg9M=withCSS(Component,css,\"framer-JaGvC\");export default Frameruf0dOGg9M;Frameruf0dOGg9M.displayName=\"Facial Expression And Memory\";Frameruf0dOGg9M.defaultProps={height:16113,width:1440};addFonts(Frameruf0dOGg9M,[{explicitInter:true,fonts:[{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F\",url:\"https://framerusercontent.com/assets/5vvr9Vy74if2I6bQbJvbw7SY1pQ.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0301, U+0400-045F, U+0490-0491, U+04B0-04B1, U+2116\",url:\"https://framerusercontent.com/assets/EOr0mi4hNtlgWNn9if640EZzXCo.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+1F00-1FFF\",url:\"https://framerusercontent.com/assets/Y9k9QrlZAqio88Klkmbd8VoMQc.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0370-03FF\",url:\"https://framerusercontent.com/assets/OYrD2tBIBPvoJXiIHnLoOXnY9M.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0100-024F, U+0259, U+1E00-1EFF, U+2020, U+20A0-20AB, U+20AD-20CF, U+2113, U+2C60-2C7F, U+A720-A7FF\",url:\"https://framerusercontent.com/assets/JeYwfuaPfZHQhEG8U5gtPDZ7WQ.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0000-00FF, U+0131, U+0152-0153, U+02BB-02BC, U+02C6, U+02DA, U+02DC, U+2000-206F, U+2074, U+20AC, U+2122, U+2191, U+2193, U+2212, U+2215, U+FEFF, U+FFFD\",url:\"https://framerusercontent.com/assets/vQyevYAyHtARFwPqUzQGpnDs.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0102-0103, U+0110-0111, U+0128-0129, U+0168-0169, U+01A0-01A1, U+01AF-01B0, U+1EA0-1EF9, U+20AB\",url:\"https://framerusercontent.com/assets/b6Y37FthZeALduNqHicBT6FutY.woff2\",weight:\"400\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0460-052F, U+1C80-1C88, U+20B4, U+2DE0-2DFF, U+A640-A69F, U+FE2E-FE2F\",url:\"https://framerusercontent.com/assets/DpPBYI0sL4fYLgAkX8KXOPVt7c.woff2\",weight:\"700\"},{family:\"Inter\",source:\"framer\",style:\"normal\",unicodeRange:\"U+0301, 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}