Ethan Holleman

NBI Background The National Bridge Inventory (NBI) is a program of the Federal Highway Administration which is an agency within the U.S Department of Transportation. The NBI makes available records and statistics about all the bridges in the United States which includes information about bridge location, integrity, inspection history and usage. Potential encoding discrepancy As a side project I have been working on creating a more exhaustive Python package for parsing NBI data. This is mainly focused on decoding the numerical representations present in data files to their semantic meanings specified in the NBI documentation. I ran into errors when trying to decode the state code fields, which based on the available documentation uses the coding table below.

This recipe (aside from the electronics) is derived from Joshua Weissman’s video, How to Make Real Tonkotsu Ramen. Ingredients Below are all materials you will need to prepare the soup. Broth / soup Ingredient Quantity Units Pig trotters 3 lbs Green onion 1 bunch Yellow onion 1 Shallot 2 Knob ginger 2 inches Ramen noodles 1 package Chashu (Braised pork belly) Ingredient Quantity Units Pork belly 2 lbs Soy sauce 1/2 cup Mirin 3/4 cup Sake 1 cup Ginger knob 2 inches Green onion 1 bunch Glove garlic 5 cloves Tare Ingredient Quantity Units Bonito flakes 1/2 cup Kombu 3 pieces Soy sauce 3/4 cup Dried shiitake mushrooms 1/4 cup Chashu braising liquid 1/4 cup Electronics (Optional) Ingredient Quantity Raspberry Pi 1 DS18B20 Temperature Sensor Module Kit 1 Protocol Prepare electronics So I was planning on monitoring the soup using the DS18B20 temperature sensor but it did not arrive in time so unfortunately I don’t have data from that.

The past couple days I have been running some ligand docking simulations as part of my current rotation with the Cortopasssi lab using Rosetta. One of these docking simulations involved fitting a small portion of the insulin receptor (IR) the lab is interested in, into a known binding region of the Shc1 protein. Any Rosetta docking simulation will require hundreds of repetitions, which generate a significant number of pdb files which show the final conformation of the protein and ligand at the end of a given simulation. While reading about the best way to aggregate and do analyise on these results I spent a bit of time looking for ways to visualize everything Rosetta spits out.

I spent most of the day today learning about Javascript and CSS by building a (very ameutur) website that you can use to test your Poker pot odds calculation skills. Determining pot odds is useful as when compared to the probability of winning a hand the call’s expected value can be approximated. You can visit the website at potoddsquiz.com view the the code at the GitHub page or use the website embedded directly below. This is the first Javascript project I have built from scratch and hosted somewhere and was a great way to start learning more about the very basics of web development and the Javascript language.

Are you using the UC Davis FARM for molecular modeling and need to figure out how to setup GROMACS? Well hello extremely small subset of the population! This is the guide for you. Note, this is only for a basic installation. For maximum performance refer to the GROMACS guide linked above. Getting started We will be working off the installation instructions on the GROMACS website but will modify a few steps to deal with the quirks of the FARM at the time of writing and the fact you will not have sudo privileges. If you want to cut to the chase, you can run this script, which will run all the code in this guide in one go.

Day trip to Yosemite National Park. Hike up to mirror lake Campground near Curry Village Good advice. Ethan with log on the trail. Erica with boulder. Moss 1. Moss 2. Moss 3 (lots of interesting mosses). At mirror lake Mirror Lake visitor info placard. Mirror lake facing Northwest towards Mt. Watkins. Half Dome. Ethan and Erica in front of Half Dome. Interesting log, ground in the log’s shadow remained frozen. Panoramic view facing Northeast with (from left to right) Mt. Watkins, Ahwiyah Point and Half Dome in view.

Skribbl.io is a great free quarantine / social distanced game where one person attempts to draw a word while everyone else guesses what they are drawing. When setting up the game you can supply your own list of comma separated words doing the game. The problem with doing this manually is that one person playing will know all the words. For an upcoming Zoom party I created a python command line application that takes in subreddit names and a few other parameters and using the Praw library retrieves the most commonly used words from the top comments of posts to a subreddit.

After finding the COG-UK data I was looking around for other interesting COVID-19 datasets to play around with and build my R plotting skills with. User moritz.kraemer posted this article on early case descriptions which included a lot of geo-spacial data that I was interested in takeing a look at. There was a significant number of fields devoted to hospitalization related measurements and so I focused on that subject for the plot below. The dataset includes patients with and without hospitalization records and so first I filtered down to just those with records and those who also had location data. This subset of patients formed subplot A.

The Covid-19 Genomics UK Consortium has been collecting and sequencing thousands of COVID-19 genomes from patients in the UK and around the world. All of their data is publicly available. Here I played around with the phylogenetic tree they have created from global alignments of all the genomes they have sequenced. You can download the tree in Newick format from their data page which also hosts sequences and the alignment files. Visualizing the COVID-19 phylogenetic tree by country of origin Genome count by country Note this plot is log scale in the y-axis. 16 most prevalent UK COVID-19 lineages Density plots showing the number of genomes of the 16 most prevalent lineages detected by COG-UK.

Apartment Tour Taken right after move in. Skys during the wildfires Those are not clouds. Davis campus cows Around Davis Hiking in Winters, CA Fishing at Putah Creek Thanksgiving Bubbles Lots cat pictures have been taken California changes a man