Engineering – Page 2 – UROP Spring Symposium 2021

Research Discipline(s): Engineering

Analysis of Wheelchair Dimensions

The goal of this project was to characterize wheelchair dimensions to provide guidance to vehicle manufacturers who are designing integrated wheelchair seating stations in automated vehicles. UMTRI has a database of wheelchair crashes that include front and side view photos of hundreds of wheelchairs. My task on the project was to digitize specific wheelchair points using Image J software, calibrating each photo using a known scale dimension on each photo. These data can be used to define key dimensions for each wheelchair, such as maximum length, width, and height. Forty wheelchairs, including both manual and power styles, were analyzed. Results will be used to create generic 3-dimensional wheelchair models that represent the range of wheelchair sizes available.

Understanding Dynamic Loading of Wheelchairs Secured in Vehicles During Crashes

To develop integrated wheelchair seating stations for automated vehicles (AVs), manufacturers need to understand the loading involved when securing a wheelchair to the vehicle, because wheelchairs can weigh much more than vehicle seats. The University of Michigan Transportation Research Institute (UMTRI) has conducted hundreds of dynamic sled tests of wheelchairs since the 1980s that include data on securement forces. These tests have involved manual, power, and stroller wheelchairs and a range of crash dummy sizes from small children to large adult males. This project first involved updating the wheelchair sled test database with the most recent test results, and then investigated factors that affect load levels. The main finding is that the weight of the wheelchair has the greatest correlation with the amount of floor loading. Results from this analysis will allow vehicle manufacturers to design wheelchair seating stations for AVs that will allow passengers who travel while seated in a wheelchair to ride safely and independently.

Design of cancer-treating proteins

One of the most elusive diseases known to man in terms of treatments, cures, and diversity is cancer. Despite how far the medical field has come, there are still no cures for any type of cancer and treatment options vary drastically in terms of success depending on the type and stage the disease is caught at. When looking to find better treatments or even possible cures for cancer, the most important factor to consider is how proteins produced by cancer cells differ from normally produced proteins and how these proteins interact with one another. In addition knowing things like a cancer protein’s binding sites and what could interfere with and inhibit the function of cancer proteins is critical when coming up with possible treatments and cures. By analyzing these protein-protein interactions and performing a de novo protein design, it is possible and feasible to find proteins that can target cancer-related proteins and slow or stop the spread of the disease in the body.

Design of Novel Protein to Inhibit PD-1/PD-L1 Protein-Protein Interaction for Cancer Immunotherapy

Cancer is the second leading cause of death in the United States and around the world. All cancer is a result of gene mutations, which can cause the formation of abnormally functioning proteins that change a cell’s behavior from normal to cancerous. Contrary to prior cancer treatments focusing on treatments not native to the human body, this research study aims to harness the natural immune response. This project involves the design of a novel protein sequence using a computational protein design program called UniDesign. This novel protein will be designed to inhibit the PD-1/PD-L1 protein-protein interaction, which is responsible for preventing T-cells from destroying other cells. In cancer patients, the new protein could be used to inhibit the PD-1/PD-L1 pathway, which would allow T-cells to destroy cancer cells. Thus, this treatment utilizes the native immune response as a source of cancer therapy. In order to determine the effectiveness of the novel protein at inhibition, the binding affinity of the new protein sequence will be compared to that of the original PD-1/PD-L1 PPI. As such, the protein developed in this project will have the potential to target the PD-1/PD-L1 PPI to ultimately treat cancer in patients.

Antarctic Atmospheric Rivers

Atmospheric Rivers (ARs) are long and narrow areas of concentrated moisture found within the first few kilometers of the atmosphere. When they make landfall, this moisture is released in the form of rain or snow, at times transporting moisture from the tropics or subtropics. Due to their impacts at landfall, there has been an explosion of interest in characterizing ARs. However, the AR definition is largely qualitative and relies on regionally specific case studies from the North Pacific, therefore, a number of AR detection algorithms exist. I will be focusing on the region of Antarctica because there is little studied from that region, and there are large differences between algorithms when applied to that region. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) aims to identify and quantify the uncertainty in AR science due to algorithm choice. The focus of this project is on a set of AR catalogues from ten algorithms run on MERRA-2 reanalysis (1 hour time intervals and 0.5 degree latitude and longitude intervals). This project seeks to understand and quantify the differences between regional and global algorithms when applied to the region of Antarctica by examining how the number of AR events changes with algorithm and comparing algorithms along transects in Antarctica. We can cross analyze the output of each of the detection algorithms to identify areas of inconsistency in atmospheric river detection and understand the nature and source of those inconsistencies, which is the goal of this UROP project.

Testing a New Search Engine for Class Videos

The current research project investigates the relationship between a new search engine for instructional videos and the academic performance of university-level students and instructors. During the new-age of virtual learning, the hindrance of social interaction combined with the sudden increase in digital screen time has negatively impacted the mental health and in turn, the academic performance of many students because they are not being able to focus or concentrate on their work. A study proposed to determine if a new academic tool provides help for students academically utilized participants, who were recruited through email communication to various universities across America, to use the engine and record their grades on academic assignments and poll their opinions on the product. Currently, the research is still in progress and has no definite conclusion.

Testing a New Search Engine for Class Videos

The current research project investigates the relationship between a new search engine for instructional videos and the academic performance of university-level students and instructors. During the new-age of virtual learning, the hindrance of social interaction combined with the sudden increase in digital screen time has negatively impacted the mental health and in turn, the academic performance of many students because they are not being able to focus or concentrate on their work. A study proposed to determine if a new academic tool provides help for students academically utilized participants, who were recruited through email communication to various universities across America, to use the engine and record their grades on academic assignments and poll their opinions on the product. Currently, the research is still in progress and has no definite conclusion.

Silicon Oxynitride Derived from Rice Hull Ash (RHA) as An Anode Material for Lithium-ion Batteries

Climate change has increased the urgency to replace current energy production and storage techniques with more eco-friendly ones. Of all efforts that have been dedicated to improving the performance of the lithium-ion batteries (LIB) present in the market, Ulvestad et al. demonstrated that LIB anodes containing SiNx exhibit significantly higher capacities than commercial graphite anodes. Herein, we explore and optimize the performance of silicon oxynitride as an anode material for LIB. Carbothermal reduction of rice hull ash, an agricultural waste that is composed of carbon and SiO2 that intimately mixed in nano-scale, was used as the production methods in attempts to access high-performance anode materials in environmental- and economical-friendly processes. Factors such as temperatures, atmosphere, heating duration were adjusted to investigate their effects on Si2N2O yields in the products . Heretofore, it was found that: 1) higher reaction temperatures (1350-1600 °C) and longer treating durations (2-8 hours) lead to higher conversion of SiO2 in the starting materials; 2) the gaseous atmosphere (N2, NH3, N2+H2) is an essential factor determining the Si2N2O:Si3N4 ratio in the products. Future plans will focus on the influence of different densities of starting materials (pellet vs. mound powders). Testing and analyzing the electrochemical performance of the optimized products would be the goal for the longer-term.

Taking a Stand: The Effect of Social Issue Stance-Taking on Human Capital Attraction

Companies can attract human capital, or potential employees, through wage incentives and non-wage incentives, such as commitments to causes like workplace diversity and environmental sustainability. This project examines the question of as these commitments to social issues become more prevalent in recruitment efforts, does this make companies more likely to support them. A data set of every job posting in the United States over the past decade is being analyzed by a code written in the program R that automatically sorts job postings based on keywords relating to specific non-wage incentives. In order to test the functionality of this code, smaller samples of the data set are being analyzed by manually searching for these keywords. The expected results of my role in this project is that by analyzing the smaller samples of the dataset, the main code will be validated in classifying job postings. We hope to find that this is a reliable way to find a company’s commitment to social issues and if so, that we can apply this technique to other demographics regarding the job market.

Residue Depth Computation

Proteins, a class of macromolecules essential to biological processes, are characterized by their structure which directly correlates to functionality. Residues are considered the building blocks of proteins and studying their positions has been crucial in understanding the role a protein plays in a biological system. This research project investigates different measures of residue depth through calculations of RSA, DPX, Residue Depth, HalfSpace Depth, and L1 depth. The L1 depth function surpasses other residue structure predictors in that it can obtain positions of residues buried under the protein surface, or nested in pockets. In addition, the function uses O(N) time complexity, making it much more efficient than the HalfSpace predictor. Values of depth have strong correlations with properties such as physiochemical propensities, flexibility and polarity. Data was obtained from CULLPDB, Phospho3D, and PLB datasets. After reading in necessary information into an IDE, residue depth of each protein in the datasets and the correlation coefficients between the means of depth values of amino acids and hydrophobicity index of amino acids were calculated through an algorithm written in C++. These results showed that the means of depth values were strongly relative with hydrophobicity of amino acids. In addition, the secondary structures of the residues are also associated with L1 depth values, as residues in sheets are deeper under the surface in comparison to residues in coils and helices.

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