diff --git a/docs/demos/24-07-11-scipy-2024/scipy-2024.ipynb b/docs/demos/24-07-11-scipy-2024/scipy-2024.ipynb
index e6b7090b..6aa560c2 100644
--- a/docs/demos/24-07-11-scipy-2024/scipy-2024.ipynb
+++ b/docs/demos/24-07-11-scipy-2024/scipy-2024.ipynb
@@ -320,7 +320,7 @@
     "<h2>Xarray Climate Data Analysis Tools</h2>\n",
     "</div>\n",
     "\n",
-    "- Collaboration between:\n",
+    "- Team of climate scientists and software engineers from:\n",
     "\n",
     "<div style=\"text-align: center; margin-top:10px\">\n",
     "    <img src=\"../../_static/e3sm-logo.jpg\" alt=\"E3SM logo\" align=\\\"center\\\" style=\"display: inline-block;     margin-right:50px; width:200px;\">\n",
@@ -328,31 +328,15 @@
     "    <img src=\"../../_static/seats-logo.png\" alt=\"SEATS logo\" style=\"display: inline-block; width:200px\">\n",
     "</div>\n",
     "\n",
-    "- xCDAT is an extension of Xarray for climate data analysis on structured grids\n",
-    "- A modern successor to the Community Data Analysis Tools (CDAT) library\n",
-    "- Team composed of software engineers and climate scientists who are also users of the software\n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "slideshow": {
-     "slide_type": "subslide"
-    }
-   },
-   "source": [
-    "#### Scope of xCDAT\n",
-    "\n",
-    "- Focused on routine climate research analysis operations such as loading, wrangling, averaging, and regridding data\n",
-    "- Provide features and utilities for simple and robust analysis of climate data\n",
+    "- Focused on routine climate research analysis operations\n",
     "- Leverages other powerful Xarray-based packages such as xESMF, xgcm, and cf-xarray\n",
     "\n",
     "<div style=\"text-align: center; margin-top:10px\">\n",
-    "    <img src=\"../../_static/xarray-logo.png\" alt=\"Xarray logo\" style=\"display: inline-block; width:200px; margin-right:50px\">\n",
     "    <img src=\"../../_static/esmf-logo.png\" alt=\"ESMF logo\" style=\"display: inline-block; margin-right:50px; width:200px;\">\n",
     "    <img src=\"../../_static/xgcm-logo.png\" alt=\"xgcm logo\" align=\\\"center\\\" style=\"display: inline-block; margin-right:50px; width:200px;\">\n",
     "        <img src=\"../../_static/CF-xarray.png\" alt=\"CF xarray logo\" align=\\\"center\\\" style=\"display: inline-block; margin-right:50px; width:200px;\">\n",
-    "</div>\n"
+    "</div>\n",
+    "\n"
    ]
   },
   {
@@ -1547,7 +1531,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
     }
    },
    "source": [
@@ -2088,7 +2072,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
     }
    },
    "source": [
@@ -2865,7 +2849,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
     }
    },
    "source": [
@@ -2877,7 +2861,7 @@
    "execution_count": 12,
    "metadata": {
     "slideshow": {
-     "slide_type": "fragment"
+     "slide_type": "-"
     }
    },
    "outputs": [
@@ -3761,7 +3745,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
     }
    },
    "source": [
@@ -3808,7 +3792,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
     }
    },
    "source": [
@@ -4767,7 +4751,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
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    },
    "source": [
@@ -4821,12 +4805,17 @@
     }
    },
    "source": [
-    "#### Calculate the near-surface air temperature (`tas`) in the Niño 3.4 region.\n",
-    "\n",
+    "#### Calculate the near-surface air temperature (`tas`) in the Niño 3.4 region."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "Users can also specify their own bounds for a region. In this case, we specified `keep_weights=True`.\n",
     "\n",
-    "- The weights provide full spatial weighting for grid cells entirely within the Niño 3.4 region.\n",
-    "- Partial weights for grid cells partially in the region."
+    "- Full weight for grid cells entirely in the region\n",
+    "- Partial weights for grid cells partially in the region"
    ]
   },
   {
@@ -4848,7 +4837,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
     }
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    "source": [
@@ -4976,7 +4965,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
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    "source": [
@@ -5034,10 +5023,9 @@
     "\n",
     "It can also be useful to show the departures (\"anomalies\") from the climatological average.\n",
     "\n",
-    "In climatology, anomalies refer to the difference between the value during a given time\n",
-    "interval and the long-term average value for that time interval.\n",
+    "In climatology, **anomalies** refer to the **difference between the value during a given time interval** and the **long-term average value for that time interval**.\n",
     "\n",
-    "- _For example, the difference between the January average surface air temperature and the average surface temperature over the last 30 Januaries._\n"
+    "- _For example, the difference between a January average surface air temperature and the average surface temperature over the last 30 Januaries._\n"
    ]
   },
   {
@@ -5095,7 +5083,7 @@
    "cell_type": "markdown",
    "metadata": {
     "slideshow": {
-     "slide_type": "subslide"
+     "slide_type": "-"
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    "source": [