Engineering – Page 13 – UROP Spring Symposium 2021

Engineering

Rendering Realistic Models of Radiation Sources, Shields, and Detectors for Implementation in Games

Astounding visuals can be experienced throughout a plethora of video games. While it may only take a couple of seconds to view the breathtaking visuals presented in a game, each model may have taken days, months or even years to complete! The objects presented in a given game evolve through a long process, starting from initial modeling to eventual rendering for gameplay. Since this research focuses on teaching players about radiation detection, some of the objects required for the game, such as radiation sources and detectors, must be modeled from scratch as these are not available as standard objects in asset libraries. Such items require careful research concerning their overall appearance and dimensions in the real world, and their suitability for inclusion in a game in which technical realism may be desired. In order to allow the game to run as efficiently as possible, the models must hold a low polygon and vertex count, or be “low-poly”, so that the game may operate smoothly as a player moves throughout the virtual space. Objects optimized for gameplay should additionally possess fewer textures as these may also consume memory and slow gameplay. Even if the objects are low-poly models, they can look very detailed through the use of lighting, shading, and texturing to create the stunning visuals often visible in professional games. By attending to gameplay related requirements and using those techniques without compromising portrayal of actual items, an optimal game with realistic radiation sources, shields, and detectors can be created. This creates a more effortless and enjoyable learning experience for the players.

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Developing a forecasting model for the Great Lakes

The Laurentian Great Lakes constitute the world’s largest freshwater lake system, and support hundreds of different animal and plant species, as well economic activity for many Americans and Canadians living in the Great Lakes basin. However, fluctuations in observed water levels over the past decade indicate a possible shift in regime, leading to uncertainty regarding the future of water levels and water resources in the region. This research sought to develop and expand upon a rudimentary simulation model for forecasting Great Lakes water levels across different time horizons to explore climate scenarios. In R, I used the copula package to generate stochastic series of precipitation, evaporation, and runoff based upon historical observed water supplies records. I also fit a log-linear regression model of water levels on each lake to outflow on each lake. Using the copula produced net basin supply and the log-linear outflow model, I generated a number of possible 12 month forecasts for water levels on Lake Superior, Lake Michigan-Huron, and Lake Erie given their respective beginning of month January water levels. Then the 95% confidence interval was found to create a range of likely water level values for a given future month. This model can be used to explore different long-term and short-term plausible scenarios for future water levels on the Great Lakes, due to perturbations like climate change or the implementation of a diversion of freshwater to other states.

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Wicked Solutions Domain – Poverty

Across the world there are certain “wicked” problems that face us including poverty. The goal this term was to compile existing design interventions that address this wicked problem among others towards providing access to them by professional designers and lay communities. After we find the solutions that already exist for these problems the plan is to create a central location that will serve as a resource for communities wishing to tackle these issues themselves. This term, we conducted secondary research by scouring scholarly articles and books for design interventions that could populate our database, as well as other articles that can serve as background information for the problem as a whole. After we compile the list of solutions to the wicked problems we will visualize them in a format similar to that of the Johns Hopkins University’s Coronavirus pandemic map. The format will be based on Professor Bennett’s “wicked solutions” diagram and will be called Wicked Solutions Domain (WISDOM). The aim with the WISDOM platform is to make a long lasting and meaningful impact on the aforementioned wicked problem that is impacting communities globally, and aid designers around the globe in combating it.

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Characterization of a thermoluminescent dosimetry system for seven different dosimetric materials

A series of experiments was conducted to fully characterize a prototype planchet-based thermoluminescent dosimeter (TLD) reader, the Rexon UL-320-FDR. Seven sets of dosimeters of different TLD materials were used in calibration, dosage, and heating rate experiments. This was accomplished through irradiating a set of 100 3mmx3mmx1mm dosimeters, or chips, for each material. Calibrations were conducted through three trials, with statistical analysis to obtain calibration factors for every chip in each set. Corrections were made for nonuniformities due to position in the field of the Cesium-137 source. Groups of ten chips within a set received a unique dose of between 2.4 and 29 mGy to check linearity and study noise. Heating rate experiments chips irradiate to 15 mGy were processed in groups of 10 with different heating rates for each group of 10, ranging from 1 to 20 ยฐCยทs -1 . Preliminary analysis revealed a relative standard deviation in calibration factors of <10% for LiF:Mg,Ti, from both experimental errors and individual chip variations. Linearity in sensitivity as a function of dose was generally observed over the range of doses. Some unusual behavior was observed in the glow curves, or signals recorded as a function of time during heating, for heating rates exceeding 10 ยฐCยทs -1 . This work substantially helps improve the accuracy, understand the uncertainties involved, and optimize the heating rates of future experiments conducted with these sets of TLDs and the Rexon UL-320-FDR. Additionally these data sets are of great use in designing and testing glow curve analysis software.

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Metabolism and Histone Deacetylases: A Systems Biology Perspective

Histones are proteins that provide structural support to chromosomes and help condense nuclear DNA into chromatin. Histone acetylation is a process that diminishes the affinity between histones and DNA so that gene transcription is more permissive. This process is regulated by the opposing actions of histone acetyltransferases (HATs) and histone deacetylases (HDACs), both of which are critical to many cellular processes such as DNA damage repair and proper transcription. HDACs are sensitive to the metabolic state of the cell, and the dynamic between metabolism and histone acetylation impacts several biological processes, including development and immune function. HDAC inhibitor drugs are currently being explored for treating various conditions, including cancers, viral infections, inflammation, neurodegenerative diseases, and metabolic disorders. However, it is currently a significant clinical challenge to identify subsets of patients sensitive to HDAC inhibitors. Thus, this review compiles recent applications of systems biology methods such as high throughput drug screens, cancer cell-line profiling, single cell sequencing, proteomics, and metabolomics that can help to determine the interplay between metabolism, HDACs, and HDAC inhibitors. Compiling these systems approaches can ultimately help identify epigenomic and metabolic biomarkers for patient stratification, enable the design of synergistic combination therapies, and illuminate the gaps in our knowledge regarding this interplay. For future studies, metabolic modeling and machine learning methods can be used to analyze gaps in our current understanding and identify additional potential biomarkers for patients sensitive to HDAC inhibitors.

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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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Determining the thickness of glaciers in regions without measurements

Glacial erosion is a major contributor to the global rise in sea level so it is important to be able to predict the long-term fate of a glacier. One important factor is ice-thickness, which can in turn tell us the total volume of a glacier and how it fluctuates over time. However, although the surface elevation of glaciers can be directly measured, it is much more difficult to determine the elevation of the bed of the glacier. Direct measurements of the ice-thickness through boreholes are expensive and time-consuming, so a previous study examining the Columbia Glacier in Alaska estimated ice-thickness using the mass continuity equation between adjacent flowlines. They used available data for velocity fields covering different portions of the glacier, the surface mass balance (the difference of ice accumulation and ablation), and several digital elevation models (DEMs) over a span of about fifty years. Comparisons with existing direct measurements of ice-thickness demonstrated the accuracy of this method, but this amount of data is not available for many other glaciers around the world. We are working with the same DEMs and plotting the surface elevations in different years. We will then try to determine the ice-thickness by calculating the surface slope and driving stress of the glacier, and we will compare our results to direct measurements as well as previous studies. If this approach is successful, we can then apply it to accurately estimate the ice-thickness of glaciers for which more data is lacking.

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APIS Ice Cover Modeling

We updated statistical models that model the onset and extent of ice cover along and around the Apostle Islands National Lakeshore(or APIS) – a US National Park that is famous for its picturesque rock formations in winter and accessed by foot. Over the past 50 years, climate has changed dramatically, leading to extreme variability in when and if Great Lakes freeze to a safe amount. We modeled when ice cover reached a specified extent, and if ice cover would reach that specified extent in a certain year. This project models ice cover extent using survival and beta regression models using teleconnections and historical daily ice cover data dating back to 1973. Analysis of results shows a significant increase in ice cover variability after the 1990s. The model accommodates for this change, and can be split into two different models.

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MetabolonR: An Intuitive R Shiny Application for Metabolomics Analysis

Zyad Shehadeh Pronouns: He/Him Research Mentor(s): Fadhl Alakwaa, Research investigator Research Mentor School/College/Department: Neurology Department, Michigan Medicine Presentation Date: Thursday, April 22, 2021 Session: Session 2 (11am – 11:50am) Breakout Room: Room 11 Presenter: 1 Event Link Abstract For privacy concerns this abstract cannot be published at this time. Authors: Zyad Shehadeh, Fadhl Alakwaa Research

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Utilizing bioinformatics to decipher transcriptomic networks in bone and joint development

To gain a comprehensive understanding of the functions of the myriad of cell clusters within the human body, many cell biology research studies utilize a process called single cell RNA sequencing to analyze the expression of different genes across cell clusters. In order to properly analyze the information gathered from the single cell RNA sequencing process, researchers must hire an outside body to run an analytical program to develop plots and graphs to visualize the data. Problems may arise regarding the accuracy of the developed plots and graphs because of their lack of understanding of the research project itself. This may lead to incorrect assumptions regarding the gene expression and, in turn, the function of different cell clusters. For the Hankenson Lab’s work on gene expression during bone and joint development, I personally ran the analysis and developed the plots for single cell RNA sequencing. The first half of the project entailed using the Single Cell Portal to track the different expression of genes within the WNT pathway to gain a biological understanding of the study. The second part focused on utilizing the Seurat library within R Studio to run multiple analyses on different data sets involved in the study. This involves normalizing the data set, identifying variable features within the data set, running a principal component analysis, and a non-linear dimensionality reduction. All these different programs allow for the development of heat maps, violin plots, and UMAPs. These plots will then be used by Hankenson Lab to further their study in identifying different cell clusters involved in bone and joint development as well as each cell cluster’s function.

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