diff --git a/.obsidian/appearance.json b/.obsidian/appearance.json
index 91074e173..ab80a3f07 100755
--- a/.obsidian/appearance.json
+++ b/.obsidian/appearance.json
@@ -7,6 +7,7 @@
   "enabledCssSnippets": [
     "color_snippet"
   ],
-  "baseFontSize": 20,
-  "baseFontSizeAction": true
+  "baseFontSize": 18,
+  "baseFontSizeAction": true,
+  "nativeMenus": false
 }
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diff --git a/3-99 Research/6 Researching Techniques/Highlighting Colors and What they Mean.md b/3-99 Research/6 Researching Techniques/Highlighting Colors and What they Mean.md
index 4f159a640..c6365e8d2 100644
--- a/3-99 Research/6 Researching Techniques/Highlighting Colors and What they Mean.md	
+++ b/3-99 Research/6 Researching Techniques/Highlighting Colors and What they Mean.md	
@@ -1,4 +1,4 @@
-F9: Remove Highligh
+F9: Remove Highlight
 ## For reading papers:
 <mark style="background: #BBFABBA6;">Green</mark>: This is a quotable item 
 <mark style="background: #D2B3FFA6;">Purple</mark>: Secondary source of something that's interesting
diff --git a/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md b/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md
index 95edea504..dfb6453d3 100644
--- a/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md	
+++ b/4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md	
@@ -48,6 +48,21 @@ If this research is successful, this diffusion model will accomplish three main
 2. Perturb a nominal plant in an unstructured manner with a controllable amount of uncertainty
 3. Generate time and frequency domain responses based on training data of example systems. 
 
-The diffusion generative model has shown great promise in creating novel and realistic samples from training data. This research will train a generative model to create Bode plots of transfer functions. This model will be given a nominal plant as an input and then generate a perturbed plant. Once created, this perturbed plant can be evaluated if it belongs to the set of controllable plants for a desired controller. This process will be repeated several times to generate enough plants to approximate the set of controllable plants. 
+<mark style="background: #ABF7F7A6;">The diffusion generative model has shown <mark style="background: #FFB86CA6;">great</mark> promise in creating novel and realistic samples from training data.</mark> This research will train a generative model to create Bode plots of transfer functions. This model will be given a nominal plant as an input and then generate a perturbed plant. Once created, this perturbed plant can be evaluated if it belongs to the set of controllable plants for a desired controller. This process will be repeated several times to generate enough plants to approximate the set of controllable plants[^1]. 
 
-These generated plants can be used to verify robustness of controller implementations. A model of a controller can use robust control theory to establish the set of controllable plants, but an actual implementation of a controller can not be verified as robust in the same way. Instead, it must be verified experimentally using elements of the set. Extracting elements of the set is not a trivial task, but if this research is successful, a generative model can reduce the effort required to create perturbed plants.
+<mark style="background: #ABF7F7A6;">These generated plants can be used to verify robustness of controller implementations. A model of a controller can use robust control theory to establish the set of controllable plants, but an actual implementation of a controller can not be verified as robust in the same way[^2]. Instead, it must be verified experimentally using elements of the set.</mark> Extracting elements of the set is not a trivial task, but if this research is successful, <mark style="background: #FFB8EBA6;">a generative model can reduce the effort required to create perturbed plants[^3].
+</mark>
+[^1]: No point?
+[^2]: This is a super long topic.
+[^3]: This can be two sentences. How should it get split up?
+
+# Version 2
+## Point Topic Analysis
+**First Paragraph**
+Introduction paragraph. Most important!
+*Topic*: The goal of this research is to use a generative diffusion model to create unstructured perturbations of a nominal plant. 
+*Point*: ???
+
+**Second Paragraph - Why **
+
+**Outcomes**
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