Fine Tuning the content

src/Components/About.js

@@ -5,50 +5,45 @@ import ButtonSwipe from "./ButtonSwipe";
 const About = () => {
   return (
     <div id="about" className="about">
-      <h1>About Polyphy</h1>
+      <h1>About PolyPhy</h1>
       <br />
       <p>
-        Polyphy, an interactive visualization and model fitting tool that
-        provides a novel approach for investigating cosmological datasets.
+        PolyPhy is an interactive visualization and model-fitting tool that
+        provides a novel approach to investigating cosmological datasets.
         Through a fast computational simulation method inspired by the behavior
-        of Physarum polycephalum, an unicellular slime mold organism that
-        efficiently forages for nutrients, astrophysicists are able to
-        extrapolate from sparse datasets, such as galaxy maps archived in the
-        Sloan Digital Sky Survey, and then use these extrapolations to inform
-        analyses of a wide range of other data, such as spectroscopic
-        observations captured by the Hubble Space Telescope. Researchers can
-        interactively update the simulation by adjusting model parameters, and
-        then investigate the resulting visual output to form hypotheses about
-        the data. We describe details of Polyphy's simulation model and its
-        interaction and visualization modalities, and we evaluate Polyphy
-        through three scientific use cases that demonstrate the effectiveness of
-        our approach.
-      </p>
-      <br />
-      <p>
-        Polyphy has two tightly coupled main components: simulation and
+        of Physarum polycephalum, a unicellular slime mold organism that
+        efficiently forages for nutrients, astrophysicists can extrapolate from
+        sparse datasets, such as galaxy maps archived in the Sloan Digital Sky
+        Survey, and then use these extrapolations to inform analyses of a wide
+        range of other data, such as spectroscopic observations captured by the
+        Hubble Space Telescope. Researchers can interactively update the
+        simulation by adjusting model parameters, and then investigate the
+        resulting visual output to form hypotheses about the data. We describe
+        details of PolyPhy's simulation model and its interaction and
+        visualization modalities, and we evaluate PolyPhy through three
+        scientific use cases that demonstrate the effectiveness of our approach.
+        <br />
+        <br />
+        PolyPhy has two tightly coupled main components: simulation and
         visualization.
-      </p>
-      <br />
-      <p>
+        <br />
+        <br />
         The simulation component implements the MCPM algorithm to reconstruct an
         optimal transport network given a set of point data in 3D space. Such
         data can represent the distribution of galaxies or dark matter halos,
         typically on the scales of 100s of megaparsecs. MCPM uses a swarm of
         millions of particle-like agents to explore the simulation domain.
-      </p>
-      <br />
-      <p>
-        {" "}
+        <br />
+        <br />
         The visualization component facilitates analysis tasks of the estimated
-        network. Thanks to the interactive nature of Polyphy we can observe
-        changes of the estimate in response to changing MCPM parameters. The
+        network. Thanks to the interactive nature of PolyPhy, we can observe
+        changes in the estimate in response to changing MCPM parameters. The
         main concern is whether the reconstruction fits the input data (i.e. all
         the input points are contained in it) as well as the plausibility of the
         obtained filamentary structures.
       </p>
-      <Link href={process.env.PUBLIC_URL+"/story"} underline="none">
-        <ButtonSwipe>Know More!</ButtonSwipe>
+      <Link href={process.env.PUBLIC_URL + "/story"} underline="none">
+        <ButtonSwipe>Know More {">"}</ButtonSwipe>
       </Link>
     </div>
   );

src/Components/Footer.js

@@ -12,7 +12,7 @@ const Footer = () => {
       >
         <Grid item xs={12} sm={12} md={3}>
           <a href="/">
-            <h1>Polyphy</h1>
+            <h1>PolyPhy</h1>
           </a>
         </Grid>
         <Grid item xs={12} sm={12} md={3}>
@@ -24,7 +24,9 @@ const Footer = () => {
             <a href="/story">
               <p>Story</p>
             </a>
-            <p>Documenation</p>
+            <a href="https://polyphy.readthedocs.io/">
+              <p>Documentation</p>
+            </a>
           </div>
         </Grid>
         <Grid item xs={12} sm={12} md={3}>
@@ -47,7 +49,9 @@ const Footer = () => {
             <a href="https://github.com/PolyPhyHub">
               <p>GitHub</p>
             </a>
-            <p>Slack</p>
+            <a href="/opportunities">
+              <p>Opportunities</p>
+            </a>
             <a href="/team">
               <p>Team</p>
             </a>

src/Components/Hero.js

@@ -9,19 +9,19 @@ const Hero = () => {
         <Grid container spacing={2}>
           <Grid item xs={12} sm={12} md={6}>
             <div className="content">
-              <h1>POLYPHY</h1>
+              <h1>PolyPhy</h1>
               <div className="heading-underline"></div>
               <p>
                 Structural Analysis of Cosmological Datasets via Interactive
                 Physarum Polycephalum Visualisation.
+                <br />
+                <br />
+                PolyPhy is an interactive tool to analyze intergalactic gas and
+                dark matter filaments (together known as 'Cosmic web') using the
+                Monte Carlo Physarum Machine (MCPM) algorithm inspired by the
+                foraging behavior of Physarum polycephalum 'slime mold'
               </p>
-              <p>
-                Polyphy is an interactive tool to analyze intergalactic gas
-                and dark matter filaments (together known as 'Cosmic web') using
-                the Monte Carlo Physarum Machine (MCPM) algorithm inspired by
-                the foraging behavior of Physarum polycephalum 'slime mold'.
-              </p>
-              <a href={process.env.PUBLIC_URL+"#about"}>Get Started !</a>
+              <a href={process.env.PUBLIC_URL + "#about"}>Get Started {">"}</a>
             </div>
           </Grid>
           <Grid item xs={12} sm={12} md={6}>
@@ -46,7 +46,7 @@ const Hero = () => {
       </div>
 
       <div className="cta-arrow-wrapper">
-        <Link href={process.env.PUBLIC_URL+"#about"} underline="none">
+        <Link href={process.env.PUBLIC_URL + "#about"} underline="none">
           <div className="cta-arrow"></div>
         </Link>
       </div>

src/Components/Navbar.js

@@ -127,10 +127,10 @@ const Navlinks = ({ dir, sp }) => {
         </ul>
       </li>
       <Dialog open={open} onClose={handleClose}>
-        <DialogTitle>Want to join Polyphy's Slack Channel?</DialogTitle>
+        <DialogTitle>Want to join PolyPhy's Slack Channel?</DialogTitle>
         <DialogContent>
           <DialogContentText id="alert-dialog-description">
-            If you want to interact with the developers of Polyphy and know more
+            If you want to interact with the developers of PolyPhy and know more
             about the software, feel free to request{" "}
             <a style={{ color: "#f7981b" }} href="mailto:oelek@ucsc.edu ">
               Dr. Oskar Elek

src/Components/News.js

@@ -5,7 +5,7 @@ const News = () => {
   return (
     <>
       <div className="news-wrapper">
-      <h2>POLYPHY UPDATES</h2>
+      <h2>PolyPhy Updates</h2>
       <br />
         <a
           className="twitter-timeline"

src/Constants/publications.js

@@ -2,7 +2,7 @@ export const publications = [
 
 
   {
-    name: "Polyphy: Structural Analysis of Cosmological Datasets via Interactive Physarum Polycephalum Visualization",
+    name: "PolyPhy: Structural Analysis of Cosmological Datasets via Interactive Physarum Polycephalum Visualization",
     journal:
       "IEEE Transactions on Visualization and Computer Graphics (presented at VIS 2020)",
     image: "https://elek.pub/img/polyphorm_sm.jpg",

src/Constants/usecases.js

@@ -21,7 +21,7 @@ export const usecases = [
       "https://elek.pub/projects/Rhizome-Cosmology/images/8-corners-sm.png",
       id: "sec-3d7e",
     brief:
-      "In this experiment we fit and visualize the MassiveNuS dataset at redshift z=0 (i.e., present day). This is a large dataset of 12M dark matter halos resulting from a cosmological simulation of a 256​³ Mpc region of space .After fitting the data with Polyphy we render it with volumetric path tracing. To distinguish between the input dark matter halos and the reconstructed filaments, we use two different emission profiles: white-red for the halos and yellow-blue for the filaments. ​The inner four views correspond to the upper corners of the density cube, while the outer four to the bottom corners. Thus, we obtain a view of the dataset from all directions. In Burchett et al.  we analyze another large-scale simulation: IllustrisTNG . Thanks to Polyphy, we were able to visualize not only the structure of the Cosmic web, but also the directionality of its filaments and relationship between galactic star formation rates and their relative positions in the structure.",
+      "In this experiment we fit and visualize the MassiveNuS dataset at redshift z=0 (i.e., present day). This is a large dataset of 12M dark matter halos resulting from a cosmological simulation of a 256​³ Mpc region of space .After fitting the data with PolyPhy we render it with volumetric path tracing. To distinguish between the input dark matter halos and the reconstructed filaments, we use two different emission profiles: white-red for the halos and yellow-blue for the filaments. ​The inner four views correspond to the upper corners of the density cube, while the outer four to the bottom corners. Thus, we obtain a view of the dataset from all directions. In Burchett et al.  we analyze another large-scale simulation: IllustrisTNG . Thanks to PolyPhy, we were able to visualize not only the structure of the Cosmic web, but also the directionality of its filaments and relationship between galactic star formation rates and their relative positions in the structure.",
   },
   {
     name: "First application to observations: SDSS data for nearby galaxies",
@@ -49,6 +49,6 @@ export const usecases = [
     image: "https://elek.pub/projects/Rhizome-Cosmology/images/frb_PT32.png",
     id: "sec-07db",
     brief:
-      "Fast radio bursts, or FRBs, are strong and extremely short (around 1 ms) flashes of electromagnetic radiation spreading through space on intergalactic scales. Discovered only about a decade ago, they are one of the active topics of inquiry in both theoretical and observational astronomy.      The adjacent visualization recreates the hypothetical situation of what an FRB would look like, were it emitted in visible light rather than the much longer radio waves. We see that due to occlusions by the Cosmic web structures the FRB radiation spreads through space very unevenly. Thanks to Polyphy, we were able to both reconstruct the Cosmic web structure surrounding this virtual FRB and visualize the situation in a physically plausible way.",
+      "Fast radio bursts, or FRBs, are strong and extremely short (around 1 ms) flashes of electromagnetic radiation spreading through space on intergalactic scales. Discovered only about a decade ago, they are one of the active topics of inquiry in both theoretical and observational astronomy.      The adjacent visualization recreates the hypothetical situation of what an FRB would look like, were it emitted in visible light rather than the much longer radio waves. We see that due to occlusions by the Cosmic web structures the FRB radiation spreads through space very unevenly. Thanks to PolyPhy, we were able to both reconstruct the Cosmic web structure surrounding this virtual FRB and visualize the situation in a physically plausible way.",
   },
 ];

src/Pages/PublicationRoute.js

@@ -18,7 +18,6 @@ const PublicationRoute = () => {
         download: true,
         header: true,
         complete: (results) => {
-          console.log(results.data);
           setData(results.data);
         },
       }