diff --git a/content/applications/app_specific/running_sas.md b/content/applications/app_specific/running_sas.md
index 7163fb857f2e847b303d0e135b231b79df418a8a..21ee8c2a33d123c1997ec3056cd21d32b1863adf 100644
--- a/content/applications/app_specific/running_sas.md
+++ b/content/applications/app_specific/running_sas.md
@@ -1,70 +1,75 @@
-+++
-title = "Running SAS at HCC"
-description = "How to run SAS on HCC resources."
-+++
-
-
-- [Running SAS through the command line](#sas-on-hcc-clusters)
-- [Running SAS on JupyterHub](#sas-on-jupyterhub)
-- [Running SAS on Anvil](#sas-on-anvil)
-
-This quick start demonstrates how to implement a SAS program on
-HCC supercomputers through the command line and JupyterHub, and on HCC's Anvil platform. The sample code and submit scripts can be
-downloaded from [HCC's job-examples git repository](https://github.com/unlhcc/job-examples).
-
-## SAS on HCC Clusters
-SAS applications can be ran on HCC clusters similar to other jobs.
-[Connect to a HCC cluster]({{< relref "../../connecting/" >}}) and make a subdirectory 
-called `sas_demo` under your `$WORK` directory. 
-
-In the subdirectory `sas_demo`, save the sas code. Here we include a single demo
-programs, `t_test.sas`, to perform a t test analysis on a small data set. 
-
-[t_test.sas](https://raw.githubusercontent.com/unlhcc/job-examples/master/sas/t-test.sas)
-
-
-
----
-
-#### Creating a Submit Script
-
-Create a submit script to request one core (default) and 10-min run time
-on the supercomputer. The name of the main program enters at the last
-line.
-
-[sas.submit](https://raw.githubusercontent.com/unlhcc/job-examples/master/sas/sas.submit)
-
-#### Submit the Job
-
-The job can be submitted through the command `sbatch`. The job status
-can be monitored by entering `squeue` with the `-u` option.
-
-{{< highlight bash >}}
-$ sbatch sas.submit
-$ squeue -u <username>
-{{< /highlight >}}
-
-Replace `<username>` with your HCC username.
-
-#### Sample Output
-
-The results of the t-test are computed and printed to the `.lst` file 
-
-## SAS on JupyterHub
-Sas can also be run on Jupyter notebook environments available through [HCC Open OnDemand]({{< relref "../../open_ondemand/connecting_to_hcc_ondemand/" >}}). [Launch a jupyter notebook session]({{< relref "../../open_ondemand/virtual_desktop_and_interactive_apps/" >}}). After the Jupyter Notebook session starts, select `SAS` from the `New` dropdown box. 
-{{< figure src="/images/jupyterNew.png" >}}
-
-Here you can run code in the notebook's cells. The SAS code is then ran when you click on the "play" icon or pressing the `shift` and `enter` keys simultaneously. 
-
-{{< figure src="/images/jupyterCode.png" >}}
-
-## SAS on Anvil
-
-SAS can also be ran on a Windows 10 instance on anvil. This allows SAS scripts to be run with a full GUI environment. 
-
-Start off creating a `Windows 10 SAS` instance from the [Anvil dashboard](https://anvil.unl.edu/). [Create an instance]({{< relref "../../anvil/creating_an_instance.md" >}}) and use the image labeled `Windows 10 SAS`. Once the instance is fully launched, [connect to the instance]({{< relref "../../anvil/connecting_to_windows_instances.md" >}}) using the retrieved password. After connecting to the instance and logging , SAS can be launched from the desktop shortcut. 
-{{< figure src="/images/sasAnvilDesktop.png" height="450" >}}   
-From here sas scripts can be ran from the editor at the bottom of the SAS window. Scripts can also be opened from a script file on the Anvil instance. 
-{{< figure src="/images/sasAnvil.png" height="450" >}}   
-Executing a script is done at the top of the SAS window `Run` and click `Submit`. When the script finishes executing, the results will be displayed.
-{{< figure src="/images/sasAnvilResults.png" height="450" >}}   
\ No newline at end of file
++++
+title = "Running SAS at HCC"
+description = "How to run SAS on HCC resources."
++++
+
+
+- [Running SAS through the command line](#sas-on-hcc-clusters)
+- [Running SAS on JupyterHub](#sas-on-jupyterhub)
+- [Running SAS on Anvil](#sas-on-anvil)
+
+This quick start demonstrates how to implement a SAS program on
+HCC supercomputers through the command line and JupyterHub, and on HCC's Anvil platform. The sample code and submit scripts can be
+downloaded from [HCC's job-examples git repository](https://github.com/unlhcc/job-examples).
+
+{{% notice info%}}
+SAS is licensed software; users must have access to an existing license via an academic department or unit to use SAS on HCC resources.
+If you a current SAS user and would like to arrange for access on HCC machines, please contact hcc-support@unl.edu.
+{{% /notice %}}
+
+## SAS on HCC Clusters
+SAS applications can be ran on HCC clusters similar to other jobs.
+[Connect to a HCC cluster]({{< relref "../../connecting/" >}}) and make a subdirectory 
+called `sas_demo` under your `$WORK` directory. 
+
+In the subdirectory `sas_demo`, save the sas code. Here we include a single demo
+programs, `t_test.sas`, to perform a t test analysis on a small data set. 
+
+[t_test.sas](https://raw.githubusercontent.com/unlhcc/job-examples/master/sas/t-test.sas)
+
+
+
+---
+
+#### Creating a Submit Script
+
+Create a submit script to request one core (default) and 10-min run time
+on the supercomputer. The name of the main program enters at the last
+line.
+
+[sas.submit](https://raw.githubusercontent.com/unlhcc/job-examples/master/sas/sas.submit)
+
+#### Submit the Job
+
+The job can be submitted through the command `sbatch`. The job status
+can be monitored by entering `squeue` with the `-u` option.
+
+{{< highlight bash >}}
+$ sbatch sas.submit
+$ squeue -u <username>
+{{< /highlight >}}
+
+Replace `<username>` with your HCC username.
+
+#### Sample Output
+
+The results of the t-test are computed and printed to the `.lst` file 
+
+## SAS on JupyterHub
+Sas can also be run on Jupyter notebook environments available through [HCC Open OnDemand]({{< relref "../../open_ondemand/connecting_to_hcc_ondemand/" >}}). [Launch a jupyter notebook session]({{< relref "../../open_ondemand/virtual_desktop_and_interactive_apps/" >}}). After the Jupyter Notebook session starts, select `SAS` from the `New` dropdown box. 
+{{< figure src="/images/jupyterNew.png" >}}
+
+Here you can run code in the notebook's cells. The SAS code is then ran when you click on the "play" icon or pressing the `shift` and `enter` keys simultaneously. 
+
+{{< figure src="/images/jupyterCode.png" >}}
+
+## SAS on Anvil
+
+SAS can also be ran on a Windows 10 instance on anvil. This allows SAS scripts to be run with a full GUI environment. 
+
+Start off creating a `Windows 10 SAS` instance from the [Anvil dashboard](https://anvil.unl.edu/). [Create an instance]({{< relref "../../anvil/creating_an_instance.md" >}}) and use the image labeled `Windows 10 SAS`. Once the instance is fully launched, [connect to the instance]({{< relref "../../anvil/connecting_to_windows_instances.md" >}}) using the retrieved password. After connecting to the instance and logging , SAS can be launched from the desktop shortcut. 
+{{< figure src="/images/sasAnvilDesktop.png" height="450" >}}   
+From here sas scripts can be ran from the editor at the bottom of the SAS window. Scripts can also be opened from a script file on the Anvil instance. 
+{{< figure src="/images/sasAnvil.png" height="450" >}}   
+Executing a script is done at the top of the SAS window `Run` and click `Submit`. When the script finishes executing, the results will be displayed.
+{{< figure src="/images/sasAnvilResults.png" height="450" >}}