Engineering – Page 10 – UROP Spring Symposium 2021

Engineering

Implementation of a virtual reality radiation protection game in Unity for Oculus Quest

At its core, virtual reality (VR) technology seeks to create virtual experiences that reflect as closely as possible the movements and responses users would have to reality. While commonly used for entertainment, it has also found use in virtual training for jobs or tasks that require hands-on experience. This is especially relevant for radiation protection training, which requires familiarity with a variety of equipment, sources, and emergency procedures. The main question is how to implement this VR training effectively. On the most basic level, the core physics and user movement must be as realistic as possible. These objectives can be achieved by choosing a game engine that supports VR development, and a target VR device with a wide range of user mobility. For this project, Unity was chosen for its versatile VR support, including support for specific devices (Oculus Quest) and more generalized support systems that allow the game to be run on any device with the proper movement controls. Care was also taken in making in-game detector models and radiation physics scripts as realistic as possible. A well-designed VR game recreates and even exceeds the limits of hands-on training, as the player can be placed in complex and potentially dangerous situations without worries of cost or potential harm. A game which fully takes advantage of the VR platform teaches players proper handling of equipment and procedures while also providing more open-ended scenes (i.e. emergencies, high-risk scenarios) that are difficult to simulate in real life.

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Variance in the Evolution of Mimicry Behavior in Atractus Snakes

Variance in the Evolution of Mimicry Behavior in Atractus Snakes: Animals often adapt their behavior and physical characteristics to mimic another species as a method to deter predators. Previous studies have identified snake species that mimic the coloration and behavior of venomous coral snakes as a defensive mechanism. This study aims to examine the variance of mimicry in a single genus. The species Atractus elaps and Atractus flammigerus will exhibit different defensive behaviors due to a difference in the evolution of mimicry between the species. The snakes were caught in Peru, placed into an arena, and introduced to various physical and auditory stimuli, all while being video-recorded. Videos were examined by frame and any observed defensive behavior was recorded. The expected results of this study are that Atractus elaps will react with tail presentations that show the red striped underside of the tail, mimicking defensive tail curling in Coral snakes. Atractus flammigerus will have different reactions to the stimuli that do not involve a tail presentation. A difference in behavior between these two species would show that only Atractus elaps uses defense mechanisms that involve coral snake mimicry. The results of this study will further examine snake mimicry behavior and provide more data about coevolution of color and mimicry in the Atractus genus.

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Age-Dependent Anti-Predator Behavior in Leptodeira Snakes

Most animals display some form of anti-predator behavior, from expelling foul-smelling substances to making deafening noises. Snakes, despite their minimalistic form, have a wide variety of anti-predator behaviors. Previous studies surrounding the behavior of snakes have focused primarily on predatory and defensive behaviors of adult snakes. This study tests for differences in anti-predator behaviors between juvenile and adult snakes of the Leptodeira genus. Leptodeira are in the family Colubridae and are primarily found across Central and South America, living in a multitude of different environments. Snakes were captured and each was subjected to a variety of stimuli, including auditory, visual, and physical contact. The resulting responses were videotaped and analyzed to generate an ethogram for each video. The behaviors were then divided into aggressive and passive displays. The frequency and length of each behavior was compared between adults and juveniles. This study predicts that adult Leptodeira exhibit aggressive behaviors more frequently than juveniles. If this prediction is true, the difference could imply that aggressive behavior provides an advantage to adult Leptodeira due to their larger size, but not juveniles. This would mean passive attempts at hiding fail more frequently for adult snakes than for juvenile snakes. If the opposite trend is found, it could imply that juvenile Leptodeira, which have white heads that fade to grey or black at adulthood, are more visible than adults and therefore are incentivized to be more aggressive. This research will broaden understanding of how behavior can change after maturation in nonhuman animals.

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Understanding Great Lakes water level variability

Due to the slow rising of the land around the Great Lakes known as isostatic or post-glacial rebound, along with the lack of multiple water level gauges per lake, water level data prior to 1918 is often considered unreliable and is frequently unused by scientists. To solve this problem, the water level data from the National Oceanic and Atmospheric Administration (NOAA) that accounts for isostatic rebound was utilized in order to create a model for water levels from 1918 to the present that could be extrapolated to the years before 1918 and provide accurate data that is adjusted for isostatic rebound. Currently, a water level plot has been developed in R that displays all original data from 1820 to the present. This plot includes all Great Lakes and can be adjusted to show only certain periods of time in the data, such as specific seasonal and monthly averages, to emphasize trends over time in water level changes. Each lake has overall similar trends with slight differences relating to factors outside of the natural environment. However, adjusting for isostatic rebound demonstrated that the water levels prior to 1918 varied from what the original data showed. Depending on the location of each lake’s master gauge, which is the gauge on each lake that is typically the longest running gauge on each lake, some lakes saw higher or lower than recorded water levels. The original water level plot in combination with the isostatic rebound adjustments could lead to an even more accurate water level plot which can be used for future research, predictions, and analysis of trends in water levels.

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Understanding Great Lakes water level variability

Due to the slow rising of the land around the Great Lakes known as isostatic or post-glacial rebound, along with the lack of multiple water level gauges per lake, water level data prior to 1918 is often considered unreliable and is frequently unused by scientists. To try to solve this problem, the available water level data from the National Oceanic and Atmospheric Administration (NOAA) that accurately accounts for isostatic rebound was utilized in order to create a model for water levels from 1918 to the present that could be extrapolated to the years before 1918 and provide accurate data that is adjusted for isostatic rebound. Currently, a water level plot has been developed in R that displays all original data from 1820 to the present. This plot includes all Great Lakes and can be adjusted to show only certain periods of time in the data, such as specific seasonal and monthly averages, to emphasize trends over time in water level changes. It is clear from the plot that each lake has overall similar trends with slight differences relating to factors outside of the natural environment. However, adjusting for isostatic rebound demonstrated that the water levels prior to 1918 varied from what the original data showed. Most lakes had higher water levels than originally thought, including Lake Michigan, Lake Huron, Lake Superior, and Lake Erie, and others having lower water levels than originally thought, including Lake Ontario. This shows that the original water level plot in combination with the isostatic rebound adjustments could lead to an even more accurate water level plot which can be used for future research, predictions, and analysis of trends in water levels. Each Great Lake has one master gauge which is typically each lake’s longest running gauge with least amount of vertical crust movement, and the results align well with what was expected based on the placement of each lake’s master gauges. Having this new information could help researchers and scientists discover new long term trends in the water levels because they will have data that goes farther into the past and is more accurate overall.

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Predicting Pathogenicity of Clinical Mutations through Deep Learning

Recent developments in gene sequencing and personalized medicine provide a remarkable opportunity to revolutionize healthcare. Many single-nucleotide polymorphisms (nsSNPs) are associated with disease-causing mutations. Because these mutations are often eliminated from the gene pool through purifying selection, the opportunity to determine their relationship to human disease is rare. Previous studies have developed neural networks that can identify pathogenic mutations to an adequate accuracy, but success with solely human variants is still lacking. Here we will train a deep neural network with a large data set of clinically annotated human variants from the dbSNP database. Each input layer is comprised of a sequence containing a clinically annotated variant from the dbSNP database, as well as an evolutionary profile of closely homologous sequences generated from multiple sequence alignment. This input is fed through multiple layers of feature extraction to achieve a final output determination of benign or pathogenic. The final trained network will then be tested on a smaller, separate data set of disease variants to gauge the efficacy and accuracy of the training. Our aim is to develop a neural network that is able to identify pathogenic mutations in human disease patients with high accuracy. This will hopefully allow future studies to utilize this network in the diagnosis or treatment of rare disease patients.

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Computing for Data Literacy in Social Studies Classes

In many K-12 social studies textbooks, there are a plethora of data visualizations in the forms of graphs, maps, and timelines. However, students are not taught how to understand and interpret these data visualizations. Students who do not learn how to read these data visualizations are at a disadvantage because they often explain important concepts that are not present in the text. The goal of the research project is to create a database with programming tools that social studies teachers can use to teach data literacy in the classroom. The research undertaken in this project derives from feedback taken from social studies teachers in Michigan. Teachers who were interested in using data visualizations in their classroom volunteered to provide input to guide and improve the project. This project’s usability, understandability, and accessibility by social studies teachers in Michigan are in the process of being tested. The project intends to increase social studies teachers’ use of online tools to aid students’ understanding of data visualizations. With increased exposure to programmable tools, the project aims to increase student performance in social studies courses and student interest in computer science.

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Wicked Solutions Domain – Obesity

Obesity is a complex issue that has been prominent throughout the world for the past few decades. It affects all ages and is a system with multiple levels, feedback loops, and other aspects that make it difficult with which to manage. Various design interventions within local contexts globally exist, however, there is lack of access to all of these context-specific existing solutions. Technologically mediating access to existing solutions, particularly by underserved populations, can contribute to what design researcher Audrey Bennett calls a “wicked solution.” The first step to providing access is compiling information of existing design interventions derived through creative or empirical inquiry. The following review of literature discusses the general topic of design thinking and making towards addressing obesity, the many ways obesity has been addressed in the past, and, also how it is being looked at now.

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Percolation modeling

Under Professor Ziff, our research group devised various methods of modeling types of percolation. These models were initially based in C and were unoptimized for large-scale run times. We rewrote these programs in C++ and implemented various algorithms and memory structures which helped reduce the runtime of the simulation algorithms. These small improvements yielded a boost in productivity as percolation models have to be run for hours on end to yield large enough outputs to provide viable research data. These small improvements are very important, as improvements in program runtime compounded over hours can have a huge impact and allow researchers to get more done in less time.

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Percolation modeling

Under Professor Ziff, our research group devised various methods of modeling types of percolation. These models were initially based in C and were unoptimized for large-scale run times. We rewrote these programs in C++ and implemented various algorithms and memory structures which helped reduce the runtime of the simulation algorithms. These small improvements yielded a boost in productivity as percolation models have to be run for hours on end to yield large enough outputs to provide viable research data. These small improvements are very important, as improvements in program runtime compounded over hours can have a huge impact and allow researchers to get more done in less time.

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