Physical Sciences and Mathematics Commons^™

Extending Geometric Acoustic Ray Tracing To Multi-Room Environments: A Case Study On Gunshot Sound Transmission Between Adjacent Rooms, Tyler Ton

Theses and Dissertations

Accurate localization of gunshots in multi-room building environments remains a challenging problem in acoustic forensics and public safety applications. Existing approaches model sound propagation within a single room, neglecting the transmission of acoustic energy through walls and other building materials. This thesis presents a study on modeling multi-room gunshot acoustic transmission, combining geometric ray tracing with structural acoustic transmission-loss modeling to generate impulse responses for two horizontally adjacent rooms separated by a shared wall, providing a foundation for future inter-room gunshot localization work. The proposed system uses GSound-SIR, a geometric acoustics engine, to simulate sound propagation in both of the …

A Fundamental Study Of Fatty Acid Ionic Liquids And Their Effects On Biomolecules, Achismita Dutta

Theses and Dissertations

Fatty acid ionic liquids (FAILs) are a class of ionic liquids (ILs) with relatively low toxicity and potential applications in biological systems. This study examined the interactions of tetramethylguanidinium decanoate, tetramethylguanidinium octanoate, choline decanoate, and choline octanoate with lipid membranes, proteins, and nucleic acids. Membrane leakage experiments using model lipid vesicles showed that decanoate-based FAILs produced greater membrane permeabilization than octanoate-based analogues, consistent with their higher membrane permeability. These effects were stronger for the ILs than for decanoate alone and occurred below the critical micelle concentration (CMC), suggesting that micelle formation may not be essential for membrane disruption. The ability …

A Hybrid Rule-Based And Large Language Model Framework For Extracting Acronym–Definition Pairs From Scientific Literature, Petro Skrypnyk

Theses and Dissertations

Authors of scientific papers rely heavily on acronyms and often use them without defining them, making the literature harder to read and index. This thesis develops and evaluates a hybrid rule-based and large language model (LLM) framework that extracts acronym–definition pairs from scientific PDF documents. It extends an earlier Rowan University system that combined a regular-expression parser with a single LLM on 200 papers. That system showed that neither the parser nor the LLM alone is sufficient for accurate extraction of the pairs. The framework is a fully automated pipeline from PDF input to scored results. It compares four LLM …

Synthetic Strategies For Bioactive Peptides: From Aggregation Inhibitors To The Total Synthesis Of Tunicyclin C, Stephanie Graciela Garcia Morin

Theses and Dissertations

In Alzheimer's disease (AD), a brain protein called "tau" abnormally clumps and forms neurofibrillary tangles (NFTs), causing damage to brain cells. Ac-PHF6-NH2 is a hexapeptide segment of tau protein that plays a dominant role in tau aggregation and is used as a model to design tau protein aggregation inhibitors. In this research we synthesized four dehydroamino acid (□AA) containing PHF6 analogues with △Abu (derived from L-threonine) and △Val (derived from □-OH-Valine) at position 2 or 3 via dehydrations or azlactone ring-openings as key reactions. We evaluated their proteolytic resistance, ability to inhibit aggregation of PHF6, and impact on the morphology …

Measuring Proteostasis Changes In Apolipoprotein E Mouse Models Using Quantitative And Kinetic Proteomic Methods, Ariel E.A. Denos

Theses and Dissertations

Alzheimer's Disease (AD) is a neurological disorder associated with brain mass loss and cognitive decline. It affects millions of elderly people and is currently uncurable. Since 1906, when the disease was first described, researchers have uncovered many components of AD pathology. However, it is now evident that curing Alzheimer's Disease will require intervention before the pathological onset of amyloid beta plaque deposition, tau neurofibrillary tangles, and associated neuronal loss. Studying AD from the perspective of early intervention requires special attention to small changes that may disrupt the normal processing of cells. Cells undergo a natural cycle of creation and destruction …

Multi-Band Extinction Modeling In Early-Type Galaxies With Circumnuclear Disks, Nonnie Bash

Theses and Dissertations

In this thesis, we present a spatially resolved, multi-band dust-attenuation method for correcting the stellar luminosity models used in dynamical supermassive black hole (BH) mass measurements. If uncorrected, dust extinction effects may dominate over other systematic uncertainties when determining the BH mass ($M_\mathrm{BH}$). We expand on a simple dust-attenuation method that treats the circumnuclear disk as a thin dust layer embedded in the galaxy midplane. Using a Multi-Gaussian Expansion, we create a three-dimensional stellar luminosity model to calculate the fractions of stellar light originating in front of and behind the disk along each line of sight. We infer the pixel-by-pixel …

Developing An Object Level Understanding Of Sine And Cosine As Ratios And A Coherent Trigonometry, Jeffrey Peter Nair

Theses and Dissertations

Solving right-triangle problems as well as integrating right-triangle and circular trigonometry into a coherent understanding are documented challenges for students. Prior research has deeply investigated students constructing ratio meanings for sine and cosine using a circle-first approach, which then can be extended to right triangles. Also, past work has separately documented distinct meanings that are useful for sine and cosine, in addition to the ratio meaning, including as lengths in a unit circle and coordinate points. This study took these existing ideas and put them together into one possible developmental progression, based on APOS theory, where students can learn length, …

Modifying Lta Zeolites For Reversible Hydrogen Sulfide Capture And Elucidating The Structure Of The Incorporated Metal And Sulfur Ions, Adeyemi D. Ojaide

Theses and Dissertations

Hydrogen sulfide (H2S) is a highly toxic and corrosive gas that poses significant environmental and industrial challenges, particularly within the wastewater treatment and oil and gas sectors. H2S leakage is among the deadliest industrial hazards, highlighting the urgent need for the development of highly efficient, non-corrosive adsorbents. This dissertation provides an in-depth examination of the use of metal-zeolites for H2S capture. We carefully investigate the impact of multiple divalent and one monovalent transition metals on LTA zeolites to optimize H2S removal. While Linde Type A (LTA) zeolites offer a robust structural framework for gas separation, a comprehensive understanding of how …

A Graphical Approach To Isospectral Unfoldings, Dallin Seyfried

Theses and Dissertations

Isospectral reductions are mathematical techniques used to shrink a matrix, or a graph, into a smaller, dimensionally reduced form while preserving its spectrum. Simple graphs that share isospectral reductions also share quantum walk properties. As such we further develop the inverse process, isospectral unfoldings, to find graphs that share isospectral reductions. We first prove many conditions relating to isospectral reductions and unfoldings. Afterwards, we define two new unfolding processes: general unfolding which unfolds the graph one vertex at a time, and equitable partition unfolding which excels at larger graph unfolding. In particular, through equitable partition unfolding, we discover many graphs …

Learning, Abstraction, And Creative Search For Interactive Agents, Jonathan Demke

Theses and Dissertations

Artificial intelligence systems are increasingly deployed as autonomous agents that interact directly with complex environments. Ensuring these agents remain reliable, adaptable, and useful presents an ongoing practical challenge. This dissertation studies agent-environment interactions through a progressive lens, examining behavior from foundational training stability and abstraction discovery to adaptation in unpredictable settings and open-ended creative search. The investigation begins by analyzing how hyperparameter settings affect early-stage Deep Q-Network performance, yielding practical guidelines for debugging reinforcement learning implementations. To address the challenge of long-horizon planning, the discovery of temporally extended options is formalized as the Minimum Shortcut Problem, demonstrating how agents can …

A Coupled Reaction-Diffusion Model Of Promoting And Suppressing Interactions Among Cancer Hallmarks In Endometrial Cancer, Jeddy Bennett

Theses and Dissertations

Spatial transcriptomics enables the scoring of Cancer Hallmarks at a high resolution across a tissue biopsy, yet current analyses of these data remain largely descriptive, treating each spot as a static, independent observation. This thesis develops a coupled system of advection-diffusion-reaction partial differential equations to model the hallmark landscape as the steady-state solution of an underlying spatial process, and casts the recovery of its physical parameters as a PDE-constrained inverse problem. The framework is implemented in FEniCSx on tissue-specific finite element meshes derived from two endometrial cancer biopsies provided by the Huntsman Cancer Institute, with subdomains, boundary interfaces, and an …

Sand Distribution On Titan And Implications For Sand Transport And Interconnectedness Of Sand Seas, Delaney Rose

Theses and Dissertations

The vast equatorial sand seas of Saturn's moon Titan are of particular interest for understanding surface processes and the budget of organic materials on Titan's surface. Previous studies have described sand dune morphology, transport, collection, and distribution patterns utilizing Cassini Imaging Science Subsystem (ISS), Visual and Infrared Mapping Spectrometer (VIMS), and Synthetic Aperture Radar (SAR) imagery. Studies have also shown evidence both for and against a global interconnected system of sand transport between Titan's major sand seas. This study worked both to create a higher resolution dataset of sand distribution using trimodal thresholding techniques applied to SAR images, as well …

Properties Of Enjoyable Mathematical Contexts From The Student Perspective, Emilie Nadine Hendrickson

Theses and Dissertations

Researchers continue to grapple with how to meaningfully engage students in mathematical content. Many students report disengagement due to perceptions that mathematics is difficult, irrelevant, boring, or anxiety-inducing. This study sought to understand how students interpret and respond to different mathematical problem contexts, with particular attention to the reasons students describe certain problems as enjoyable or unenjoyable. Using semi-structured interviews, this research examined student responses to a variety of mathematical problem types primarily across affective engagement. Students reflected on specific problem contexts and explained which features supported or hindered their enjoyment and engagement. Students described that contexts were enjoyable have …

Quantifying Dust Structure In An Elliptical Galaxy Via Optical–Near-Infrared Color Mapping: A Detailed Study Of Ngc 6251, Luke Reed

Theses and Dissertations

The giant elliptical galaxy NGC 6251 is a well-studied active radio galaxy that hosts one of the largest known relativistic jet systems, with a projected size of approximately 3 Mpc. In addition to its large-scale radio structure, the galaxy hosts a prominent circumnuclear dust feature surrounding the active nucleus, previously interpreted as a warped dust disk. This thesis focuses on the inner morphology and dust structure of NGC 6251 using archival Hubble Space Telescope observations obtained with the WFPC2 and NICMOS instruments.

The central structure of the galaxy was investigated across multiple wavelengths through image calibration, PSF modeling and subtraction, …

Understanding The Correlation Between Prediction Performance And Trust In Ai Through Scenario-Based Tasks, Likhitha Kammara

Theses and Dissertations

Trust in artificial intelligence is commonly assessed through self-reported scales or behavioral reliance, yet behavioral reliance is retrospective and can only be observed after a decision has already been made. This thesis examines whether prediction accuracy — a user's ability to predict what an AI system will recommend before its output is revealed — can serve as a prospective correlate of trust in the same empirical sense as behavioral reliance. The study was conducted in two phases using scenario-based AI decision tasks across disaster response, healthcare, and infrastructure restoration contexts, employing a between-group design in which participants either predicted AI …

Developing An Understanding Of Concavity Built On Covariation, Jade E. Gregg

Theses and Dissertations

This study investigated how six students developed a quantitative understanding of concavity founded in covariational reasoning through a series of task-based teaching interviews. A key finding was the importance of multivariational reasoning--the coordination of more than two variables--in helping students reason deeply about concavity in context. Common difficulties, including confusion about negative rates and overreliance on visual representations, served as productive opportunities for learning when addressed through carefully designed tasks and discussions. The findings extend existing frameworks of covariational reasoning and highlight instructional approaches that can support students in developing a robust, quantity-based understanding of concavity.

Analytic Solutions To Oceanographic Kinematic Property Equations, James Turbett

Theses and Dissertations

With the recent advent of large submesoscale drifter deployments, interpreting the timeseries of kinematic properties (KP) - divergence, vorticity, shear, and normal strain rates observed therein is a pressing issue. The evolution equations for the four KP are derived from the two-dimensional momentum conservation equations. The resulting equations, a nonlinear coupled system of ordinary differential equations, capture the submesoscale motion of drifters along fixed ocean surfaces, with time and space scales on the order of days and kilometers. This thesis builds theory around KP timeseries behavior by solving for the analytic solutions in the particular cases that one KP is …

On The True Interstellar Anisotropy Of Tev Cosmic Rays And Its Implications For The Local Interstellar Medium, Noufel D. Maalal

Theses and Dissertations

Several ground-based cosmic ray (CR) air shower experiments have produced sky maps of intensity anisotropy in the energy range from 1 TeV to a few hundred TeVs with very high statistics and angular resolution. These measurements provide opportunities to study CR sources and propagation in the interstellar medium (ISM). Such studies present two major difficulties. Firstly, CRs are deflected by the heliospheric magnetic field on the last stretch of their journey to Earth. Secondly, measurements at different latitudes are difficult to compare, leading to uncertainties in latitudinal variations on the order of the observed anisotropy. Experiments usually assume latitudinal variations …

An Analysis Of Heat Spread Through Smoldering Pine Needles, Timothy Keith

Theses and Dissertations

The goal of this thesis is to calculate the average speed of flame spread through smoldering pine needles. We present two different models for doing this: the first is a very large system of ODEs meant to represent the spread of flame through individual needles, the second is a macroscopic model based on the porous medium PDE. Simulations are run for each of these models and compared to each other as well as to existing models and experimental results.

A Mathematical Model Of The Interactions Between A Collagen Lattice, Fibroblasts, And Fixed Surfaces With Varying Topographies, Mary Jenkins

Theses and Dissertations

Collagen is an important structural protein in the body, which plays a role in wound healing, particularly the contraction process. Collagen lattices have been studied for nearly 50 years to provide insight into wound contraction. In some cases, collagen interacts with surfaces that have fixed shapes, such as medical implants. Our model focuses on the interactions of a collagen lattice with such a fixed surface. We mathematically model a collagen lattice as a network of nodes connected by springs. We also model fixed surfaces that have various topographies. Our model includes fibroblast cells that connect to both surfaces and remodel …

Learning Trajectories Of Online Batch Selection Methods, Luke Green

Theses and Dissertations

Modern deep neural networks achieve strong performance on large-scale datasets, but often require substantial training time. Online batch selection methods seek to reduce this cost by updating models on informative subsets of each batch rather than on all available examples. Recently introduced methods leverage teacher models and report substantial speedups, particularly in noisy-label settings. However, comparisons are often based on the number of epochs required to reach a target test accuracy, a coarse metric that is sensitive to implementation details and may obscure important differences in learning dynamics. In this thesis, we implement several online batch selection methods in a …

Advancing Data Usability, Activity Modeling, And Stability Optimization In Computational Enzyme Design, Spencer Gardiner

Theses and Dissertations

A grand challenge of computational biology is to computationally design, in a single pass, a protein sequence that catalyzes an arbitrary chemical reaction at a high rate under specified conditions [1]. This work details advances in three essential areas on the path to that goal: data quality, activity prediction and modeling, and stability optimization. The structure and implementation of the Allotrope Simple Model (a FAIR data format for many scientific instruments) was examined in [2], setting the stage for training deep learning models on high-quality experimental datasets from diverse sources. In [3], the limits of physics-based and deep learning tools …

Beyond Single Images: A Comprehensive Benchmark For Album-Level Vision-Language Understanding, Shawn Huang

Theses and Dissertations

Automatic album organization has been studied extensively over the past decades due to significant progress in digital photography. Recent Vision-Language Models (VLMs) have shown strong performance on multi-image understanding, making them natural candidates for automating album organization workflows. While VLMs’ abilities in multi-image understanding have been widely studied, their performance on album organization remains underexplored. To bridge this gap, we introduce AlbumBench, the first comprehensive benchmark for automatic album organization. Specifically, we (1) define album organization tasks as photo selection for album-specific user objectives, photo rating according to how well user intents are fulfilled, and album-specific photo grouping given a …

Tuning Ion Mobility And Molecular Confinement In High-Performance Polymer Electrolytes For Energy Storage, Ezzeldien Yousef Muhammed Yousef

Theses and Dissertations

This research addresses the critical energy density limitations of aqueous supercapacitors, which are traditionally constrained by the narrow electrochemical stability window (ESW) of water 1.23 V. By employing two distinct molecular engineering strategies, this study developed high-performance electrolyte systems that significantly extend voltage stability and thermal resilience.

The first system, CsBr@PAM/HA, utilizes a polyacrylamide and hyaluronic acid hydrogel matrix. This system exploits the chaotropic nature of Cs⁺ ions to disrupt the aqueous hydrogen-bonding network, enhancing ionic conductivity to 104 mS cm^-1. Through systematic salt screening, CsBr was identified as the optimal electrolyte, enabling a stable 2.0 V …

Engineering Nanoelectrocatalytic Systems For Co2 And Nitrate Conversion Into Value-Added Chemicals, Abdelrahman Mohamed Abdelmohsen

Theses and Dissertations

The thesis addresses two major related environmental crises: nitrate pollution of water systems and the ever-increasing levels of atmospheric carbon dioxide. Both challenges are closely linked to anthropogenic disturbance of nitrogen and carbon cycles and require sustainable, energy efficient mitigation techniques. In this study, we investigate electrochemical conversion routes as a unified approach to convert these pollutants into value-added compounds: ammonia (NH3) via nitrate reduction (NO3-RR) and ethylene (C2H4) via carbon dioxide reduction (CO2RR). The first half of this work deals with the design and engineering of Cu-Zn alloy electrocatalysts for efficient NO3-RR. Tuning the alloy composition and surface nanostructure …

Design Principle For Staple-Mediated Stabilization Of Peptides And Proteins, Samantha C. Hatfield

Theses and Dissertations

Macrocyclization, or stapling, has emerged as a powerful strategy to enhance the stability and function of peptides and proteins by constraining their conformational ensembles. Stapling can improve thermodynamic stability, increase resistance to proteolytic degradation, and enhance biomolecular recognition, making it particularly valuable for the development of peptide-based therapeutics. Despite these advantages, staple design remains largely empirical, relying on iterative screening of linker chemistries, lengths, and attachment sites. This trial-and-error approach limits scalability and hinders the rational design of stabilized peptide systems. In this work, we address this challenge by integrating large-scale experimental datasets with molecular dynamic simulations to develop predictive …

Beyond Emergency: Charting Pathways To Sustainable Development In Fragile And Conflict-Affected Settings: A Case Study Of Yemen, Sharif Abdurabu Salem Farid Alsahbool

Theses and Dissertations

For nearly a decade, Yemen's eastern governorates of Hadramawt, Shabwah, and Al‑Mahrah have been relatively stable, yet the international aid system has kept delivering short‑term humanitarian relief like food baskets and water trucking instead of shifting to sustainable development that could rebuild people's lives, create jobs, fix infrastructure, and strengthen local government. This thesis investigates why this transition has taken so long. Based on 21 interviews with government officials, international NGO staff, and local NGO managers in these three governorates, the study develops a new way of understanding the problem. It introduces three ideas: the 'emergency mentality', which is a …

Context-Sensitive Control-Flow Analysis For Non-Standard Language Semantics, Tim Whiting

Theses and Dissertations

Control-Flow Analysis (CFA) is a static technique for understanding the execution of higher-order programs without running the code. CFA aids in identifying bugs, assisting program comprehension, and exposing optimization opportunities. Constructing a CFA typically begins with an idealized evaluator--such as an abstract machine or interpreter--and proceeds by approximating components of evaluation to ensure that: (a) the analysis is sound (representing all possible behaviors), and (b) the analysis is guaranteed to terminate (finitely representable). These constraints necessitate a loss of precision, providing an approximation of the values that flow to program locations rather than exact execution traces. This imprecision causes the …

Data Science In The Utah Draft K-12 Standards Of Mathematics, Kate Webster Green

Theses and Dissertations

In today's data-driven world, the field of data science is becoming increasingly important. Research has shown that more job listings in Utah require applicants to have data science skills than ever before. Due to this growing demand, there is a push to begin data science instruction in grades K-12; however, what data science instruction is in grades K-12 is not yet clearly defined. Previous research has identified the skills and processes that make up data science in grades K-12, and several states and research groups have begun developing and implementing data science standards and learning progressions. This study analyzes the …

Scientific Crosstalk: Natural Language Processing, Praveshika Bhandari

Theses and Dissertations

While sentiment analysis has made significant strides in domains such as social media and personal correspondence, its application to formal scientific writings remains under-explored. The crosstalk between emotional expressions in personal and professional communications has also received limited attention despite its potential to reveal insights into the emotional drivers of scientific creativity. Our research introduces a computational framework designed to detect and quantify emotional expressions across various documents over time. Leveraging state-of-the-art transformer models fine-tuned on domain-specific corpora, the framework models emotional tone distribution. Integrating emotion analysis with knowledge graph modeling enables the exploration of emotional trends alongside key scientific …