Physical Sciences and Mathematics Commons^™

Constraining Neutron Star Kicks Through Gravitational Wave Detection, James Phillips

Graduate Theses and Dissertations

Neutron stars have, on average, much higher proper motions than those of hot and bright O and B type main sequence stars. Thus, it is widely suspected that asymmetries in core-collapse supernovae provide a substantial kick to these compact objects at birth. Gen- eral Relativity predicts that such supernova asymmetries will generate bursts of gravitational radiation, though no such burst has been yet detected. Here we argue that the polarization amplitudes of those gravitational waves can be used to calculate the kicks imparted on that nascent neutron star. We begin by reviewing the evidence for natal kicks, then we describe …

Synthesis And X-Ray Characterization Of Nickel Phosphide Nanostructures For Water Oxidation, David Thompson

Graduate Theses and Dissertations

The pursuit of earth-abundant 3d transition metal catalysts for alkaline water electrolysis remains an active area of research. While NiFe layered double hydroxides (LDH) are currently the most active catalysts for the oxygen evolution reaction (OER), doping Ni-based catalysts with phosphorus to form Ni metal phosphides has emerged as a promising alternative. However, the complex crystalline and amorphous phases of NiP_x have hindered their characterization, and the OER mechanism and origin of activity remain unclear. This dissertation aims to elucidate the synthesis, OER performance, and in situ reconstruction of amorphous NiP_x-based nanomaterials, with a focus on in …

Insights From Automated Mineralogic Analysis Of Modern Sand, Quinten Jones

Graduate Theses and Dissertations

Methods for determining and categorizing the modal compositions of sand and sandstone have long been a subject of debate in the field of sedimentary geology. Point counting is the most commonly used technique for determining modal compositions from petrographic slides, which are then categorized based on relative proportions of quartz, feldspar, and rock (or lithic) fragments. However, this approach fails to adequately preserve relevant textural data, such as grain size and sorting, which play an important role in diagenesis and in influencing reservoir quality. Additionally, the categorical nature of point counting results in a lack of specificity and loss of …

Leveraging Machine Learning Models For Enhanced Landslide Prediction In Western North Carolina, Andrew Edmonds

Graduate Theses and Dissertations

Landslides pose significant hazards to human safety, infrastructure, and the environment, particularly in regions of high elevation that experience extended periods of heavy rainfall. This research focuses on preparing and evaluating landslide susceptibility maps (LSMs) for the Blue Ridge Mountains, a portion of the Appalachian Mountains in western North Carolina, utilizing three machine learning algorithms: Logistic Regression, Random Forest, and Gradient Boosting Regression. Sixteen landslide conditioning factors, reflecting topographic, geological, environmental, and anthropogenic influences, were identified for model input. The landslide inventory database, comprising 7,350 locations, was randomly divided into training (80%) and testing (20%) sets. The performance of each …

Towards Multimodal Scene Graph Generation Approaches To Video Understanding, Trong-Thuan Nguyen

Graduate Theses and Dissertations

This thesis advances video understanding by enhancing Video Scene Graph Generation (VidSGG) through improved temporal modeling, the integration of long-range temporal dependencies via continuous updates to interaction histories, and the utilization of Large Language Models (LLMs) for scene graph reasoning. To this end, three novel datasets and corresponding approaches are introduced. First, the ASPIRe dataset incorporates interactivity annotations and leverages the Hierarchical Interlacement Graph (HIG) for hierarchical temporal modeling, providing deep insights into scene changes and effectively capturing intricate interactions. Next, the AeroEye dataset, focusing on drone videos, is paired with the Cyclic Graph Transformer (CYCLO), which establishes circular connectivity …

Quantifying The Effects Of Urbanization On Stream Nutrient Loads And Decomposition, Caroline Anscombe

Graduate Theses and Dissertations

Urban stream syndrome (USS) refers to the common symptoms of degradation in urban streams globally. Two symptoms of USS are increased nutrient and salt concentrations in streams, affecting ecosystem structure and function. Excess nutrients negatively impact freshwater ecosystems, placing downstream habitats at risk of eutrophication and harmful algal blooms. Excess salt runoff, derived from road salt application, is toxic to freshwater organisms and affects leaf litter decomposition, the base of aquatic food webs. Here, I aimed to quantify the effects of nutrient pollution and salinization on urban water quality and ecosystem function. Despite the widespread consequences of nutrient pollution, most …

Geochemical Analysis For Potential Critical Mineral Resources In Carbon Fly Ash, Korei D. Patterson Teer

Graduate Theses and Dissertations

The growing demand for critical minerals, coupled with the increasing supply chain vulnerabilities, has intensified the need for alternative domestic resources of critical minerals beyond traditional mining. Many of these critical minerals are essential for advanced technologies, energy storage, and national security, yet the United States remains heavily dependent on foreign imports, particularly from China. This study evaluates the economic potential of critical mineral recovery from Carbon Fly Ash (CFA), a byproduct of coal combustion, to determine its viability as a secondary source of critical minerals. A geochemical and mineralogical assessment was conducted on CFA samples from various storage sites …

Achieving Flexible Fairness And Privacy In Federated Learning, Alycia N. Carey

Graduate Theses and Dissertations

Having access to large, high-quality datasets is crucial for training machine learning models that achieve satisfactory performance. Unfortunately, it is common that a single entity (e.g., mobile device or organization) does not have access to such datasets due to monetary or resource constraints. Traditional machine learning requires that all training data reside in a centralized location during the entire duration of model training, however, in many circumstances it is difficult or even impossible (e.g., due to governmental regulations) for multiple parties to combine their data to meet this constraint. Federated learning is a machine learning paradigm that facilitates the joint …

Controls On Nutrient And Sediment Export In A Non-Perennial Agricultural Stream, Kathleen Cutting

Graduate Theses and Dissertations

Climate change is expected to increase flow variability and intermittency in streams, changing the magnitude and timing nutrient and sediment delivery. This may exacerbate water quality issues in agricultural landscapes, where nutrient and sediment inputs are often elevated. Elevated nutrients can drive eutrophication in downstream waterways, and excess sediment loss can decrease primary productivity. Non-perennial headwater streams are particularly vulnerable to the impacts of climate change and agriculture as they serve as key sites for nutrient cycling at the terrestrial-aquatic interface. Despite their importance, the interactive effects of agriculture and stream intermittency, as well as unpaved roads in rural watersheds …

Quantum Oscillation Studies Of The Nodal Line Semimetal Ni3in2s2-Xsex, M. M. Sharma, Santosh Karki Chhetri, Gokul Acharya, David Graf, Dinesh Upreti, Sagar Dahal, Md Rafique Un Nabi, Sumaya Rahman, Joshua Sakon, Hugh O.H. Churchhill, Jin Hu

Physics Faculty Publications and Presentations

Ternary shandite compounds with the general formula T3M2X2 (T = Ni, Co, Rh or Pd; M = Sn, In, or Pb; and X = S or Se) have emerged as a large pool of topological semimetals. This family of compounds hosts different topological phases for various combinations of T, M and X. This paper reports the observation of quantum oscillations under the high magnetic fields in Ni3In2S2-xSex single crystals. Angular dependence of oscillation frequency suggests an evolution of the Fermi surface from three-dimensional to two-dimensional on Se substitution for S in Ni3In2S2. The effective mass obtained for each composition by …

Icylib: A Scalable Solution For Reproducible Image Classification Workflows, Leo Williams

Data Science Undergraduate Honors Theses

With the rapid expansion of e-commerce over time, ensuring the diversity and quality of product images has become a critical challenge infeasible for human completion. In conjunction with Walmart Global Tech for the Team 1 Data Science Practicum Project, image classification models were trained to assess product image sets, but training and deploying such models often involves repetitive code and inefficient processes. This thesis presents a reusable modeling library, named IcyLib, designed to streamline the training, validation, and testing of image classification models as well as dataset importation using PyTorch. IcyLib provides a structured yet flexible approach for model implementation, …

Extending Simulation-Enhanced Bayesian Optimization Of System Designs: A Computational Study, Luke Kim

Data Science Undergraduate Honors Theses

This honors thesis builds off work initially accepted for publication in the Proceedings of the 2025 IISE Annual Conference & Expo, which introduced “Simulation-Enhanced Bayesian Optimization” (SEBO)—a hybrid testing optimization approach that combined the usage of unbiased but costly physical experiments with the usage of cheaper but potentially biased computer experiments to optimize engineered systems. The original study established the SEBO methodology and demonstrated its effectiveness on a multimodal, two-dimensional benchmark function. Expanding on the work performed, we conduct a broader evaluation of the SEBO framework through parameter testing and experimentation under a variety of additional benchmark functions. This investigation …

Enhancing Product Image Classification: Utilizing Machine Learning Models For Retail Applications, Avery A. Thompson

Data Science Undergraduate Honors Theses

The expansion of e-commerce has continued at a blinding pace since the COVID-19 pandemic, and retailers are constantly looking for new ways to retain customers. Ensuring that diverse and well-classified images are on product pages has been a paramount method for retailers to ensure retention as they increase product engagement and sales and enhance user experience. Managing and labeling these vast catalogs of images by hand is becoming increasingly infeasible, so some online retailers have started to turn to automated classification models to assist them. Accuracy in these classification models is integral, as a good image classification model can improve …

Nonparametric Methods For Bayesian Community Detection In Complex Networks, Kedran Young

Graduate Theses and Dissertations

Network analysis is becoming an increasingly popular interdisciplinary area of study, with emerging interest in fields like sociology, biology, economics, and ecology. Within the niche of network analysis, capturing the community structure of a network is one important achievement that many statisticians have been working toward over recent decades. The most popular modeling technique for latent community detection is the Stochastic Block Model (SBM), which falls into the category of latent variable models and will serve as the baseline model throughout this thesis. SBM is widely regarded as the most effective community detection method as it detects latent community membership …

Comparison Of Rt-Qpcr And Rt-Ddpcr On Assessing Model Virus In Wastewater, Wafa Youssfi

Graduate Theses and Dissertations

There is an increasing demand for quantifying viral loads in diverse wastewater systems using polymerase chain reaction (PCR). This study evaluates the performance of two commonly used workflows: reverse transcription quantitative PCR (RT-qPCR) and reverse transcription droplet digital PCR (RT-ddPCR) in wastewater. We compared the two methods by measuring the viral ribonucleic acid (RNA) of a model virus Phi6 in samples collected from various treatment stages at the Westside Wastewater Treatment Facility in Fayetteville, AR. RNA was extracted from real and synthetic wastewater samples and analyzed in parallel using both RT-qPCR and RT-ddPCR. Findings reveal that both methods demonstrated similar …

Securing Distributed Energy Resources: A Secure Gateway For Modbus To Solid Communication Using A Raspberry Pi, Donna R. Thakadipuram

Electrical Engineering and Computer Science Undergraduate Honors Theses

As distributed energy resources (DERs) such as solar panels, wind turbines, and battery storage systems become more common, securing their communications has become increasingly important. Many of these systems still rely on legacy communication protocols such as Modbus, which were not designed with cybersecurity in mind. This project addresses this challenge by developing a secure communication gateway that allows Modbus RTU devices to interface with decentralized Solid pods, which are personal data storage units that give users control over their information. This system is built on a Raspberry Pi 4, and it translates telemetry data from Modbus into a Solid-compatible …

Analyzing Unmanned Aircraft System (Uas) Incidents From Nasa Asrs Data Using Unsupervised Machine Learning, Kacey Haws

Electrical Engineering and Computer Science Undergraduate Honors Theses

The NASA Aviation Safety Reporting System (ASRS) assembles voluntarily submitted aviation safety incident reports in their database to act on the information provided. This database allows the government, companies, and citizens to submit incident or situational reports to its database to discern recurring issues in the National Aviation System (NAS) so that the proper officials can act [1]. The narratives provided in these reports are text-based, resulting in large amounts of data to process. Previous work in the University of Arkansas Aerospace Systems Engineering and Transportation Laboratory (ASYST) lab involved parsing unmanned aircraft system (UAS) incident reports manually. While these …

Defend: A 1m Dataset Foundation Model For Tobacco Analysis, Matthew J. Shepard

Electrical Engineering and Computer Science Undergraduate Honors Theses

The study of tobacco imagery and marketing is a complex challenge that involves extremely large datasets. It also demands a detailed analysis of the so- cial context and specific types of tobacco being marketed. Despite major recent advances in computer vision and foundation model technology, this still poses a substantial challenge. Through the DEFEND model, we aspire to address these obstacles by integrating features such as multimodal learning, hierarchical under- standing, and feature extraction to develop a foundation model designed to handle the unique challenges of tobacco image analysis. One of the core elements of DE- FEND is the Tobacco …

Managing Graphical Fidelity With Stylized Shaders For Independent Game Development, Benjamin A. Edens

Electrical Engineering and Computer Science Undergraduate Honors Theses

This paper outlines work performed by the author within the Unity3D game engine to gain preliminary experience with technical art implementation and suggests design choices that could be useful to other students or independent game developers to manage complexity within their games while maintaining visual appeal. The final product of the discussed project is a small game consisting of an outdoor urban city environment as well as an interior aquarium environment. This paper begins with the author’s motivations and goals for the project before describing the implementation of specific aspects of technical art, including 3D modeling, rigging, animation, level design, …

Automated Solar Pv Analysis With Machine Learning And Computer Vision: Dataset And Methodology, Malachi Massey

Electrical Engineering and Computer Science Undergraduate Honors Theses

Solar power is a vital resource in a world being threatened with the ever-evolving impacts of climate change. A combination of new and developing technologies have allowed solar photovoltaic installation to increase at an exponential rate. With this rapid and unprecedented growth comes the task of maintaining tens of thousands of square miles of solar photovoltaic panels. Manually observing and testing solar PV panels for defects or obstructions is costly and time-consuming, distracting valuable resources from the continued installation of new units. This research aims to (i) firstly, introduce a novel dataset on solar PV obstruction, named De-Solar dataset; (ii) …

Multimodal Learning For Visual Perception And Robotic Action, Taisei Hanyu

Electrical Engineering and Computer Science Undergraduate Honors Theses

Multimodal learning aims to weave information from images, language, depth, and other sensors into one coherent representation, much as people naturally combine sight, speech, and sound. Progress toward that goal is slowed by three gaps: vision encoders that cannot balance crisp object boundaries with global context, 3-D semantic maps that are computationally prohibitive for real-time, open-vocabulary queries, and vision-language-action pipelines that depend on large token pools with weak relational grounding.

We first introduce AerialFormer, a lightweight hybrid of convolutional and Transformer layers that captures long-range structure without sacrificing fine detail. On the large-scale iSAID benchmark it reaches 69.3% mean IoU, …

Environmental And Societal Impacts Of Agricultural Land Abandonment In Indonesia: A Bibliometric Review, Jane A. Landrum

Geosciences Undergraduate Honors Theses

In the past decades, Southeast Asia has faced one of the highest urbanization rates globally, with land conversion, agricultural land abandonment, and deforestation occurring simultaneously. High population growth rates and migration away from rural areas have also led to increased food insecurity, which has increased the need for agricultural production. In Indonesia, high rates of urbanization on the island of Java have historically prompted governmental policy solutions aimed at population redistribution and agricultural extensification (rather than intensification). The cost of this conversion of lands to agriculture often falls on the environment, with peatlands and forested lands being converted to large-scale …

Protein Structural Changes Of Envelope Glycoprotein In Human Immunodeficiency Virus Type 1, Abigail S. Bridges

Chemistry & Biochemistry Undergraduate Honors Theses

The envelope glycoprotein (Env), present on the viral surface of human immunodeficiency virus type 1 (HIV-1) facilitates host cell infection, making it a critical target for immune responses and vaccine development. Env is able to transition through three prevalent prefusion conformational states, state-1 (pre-triggered), state-2 (closed), and state-3 (open). By transitioning through these conformation states, Env can successfully evade immune responses and initiate viral entry into the host cell. This study uses molecular dynamics (MD) simulations to analyze the conformational dynamics of the mature, cleaved Env glycoprotein in the state-2 conformation (PDB ID: 4ZMJ). Simulations were conducted with five replicates, …

Using Gaussian Process Regression To Learn Thermodynamic Equations Of State With Uncertainty Quantification, Austen T. Lee

Chemical Engineering Undergraduate Honors Theses

This study investigates the use of derivative-informed Gaussian Process (GP) models to estimate thermodynamic behavior across temperature and density by building a Helmholtz-based equation of state. Argon, a stable monatomic gas, was chosen as a case study within the vapor region. The GP model was trained using values of experimentally measurable properties found by taking first and second derivatives of the original potential function. Results show that while the GP model offered uncertainty quantification and informed thermodynamic behavior, it predicted values that deviated from the ground truth depending on the property. The model exhibited high confidence in regions with substantial …

A New Method Using Lidar And Well Logs To Identify And Correlate The Pennsylvanian Atoka Formation Subdivisions In The Surface Outcrops Of The Boston Mountains, Arkansas, Robert Brent Boyd

Graduate Theses and Dissertations

The surface outcrops of the Boston Mountains in northwest Arkansas primarily consist of the Pennsylvanian Atoka formation. Where fully preserved in the Arkoma Basin to the south, the Atoka formation exceeds 18,000 ft of sand and shale. However, it remains undifferentiated on the surface geological map of Arkansas. This study investigates the possibility of identifying and correlating the subsurface subdivisions of the Atoka Formation to the surface outcrops of the Boston Mountains using a new method. Recognizing the Atoka subdivisions in surface outcrops using standard lithology and biostratigraphy correlation techniques has been challenging. The subdivision of the Atoka has instead …

Simulations Of Richtmyer-Meshkov Instability Using High Order Weno Methods, Ryan Holley

Graduate Theses and Dissertations

Turbulent mixing due to hydrodynamic instabilities occurs in a broad spectrum of engineering, astrophysical and geophysical applications. Theory, experiment, and numerical simulation help us to understand the dynamics of interface instabilities between two fluids. This thesis presents an increasingly accurate and robust front tracking method for the numerical simulations of shock-induced turbulent mixing known as Richtmyer-Meshkov Instability (RMI). Front tracking is an adaptive computational method, where the interface instability is explicitly represented as lower dimensional manifolds moving through a rectangular grid. All the cell-center states (density, velocity and pressure) are updated using higher order weighted essentially non-oscillatory (WENO) scheme. Performance …

Automation Of Vulnerability And Patch Management: Information Extraction, Association, And Optimization, Kylie Mcclanahan

Graduate Theses and Dissertations

Vulnerability and patch management is an integral part of a robust cybersecurity program, yet it grows increasingly complex due to the sheer amount of data that must be analyzed. Particularly in Operational Technology (OT) environments, analysis must be done manually because of the lack of automated solutions. Additionally, there are many steps in this process, from the initial discovery of the vulnerability to the implementation of its remediation, and each step in the process requires different data in order to be performed effectively. In this work, we provide approaches and strategies to assist operators in industrial or OT environments throughout …

Application Of Ordinal Regression Models To Acquired Stress Resistance In Wild Strains Of Saccharomyces Cerevisiae, Carson Stacy

Graduate Theses and Dissertations

This thesis explores the application of ordinal regression to the analysis of semi-quantitative growth assays often used when comparing fitness for different strains of the model yeast Saccharomyces cerevisiae. For stress survival assays, yeast stress resistance is measured using an ordered survival score that ranges from 0 (no growth) to 4 (confluent growth). Traditional approaches to analyze this type of data either treats data as a nominal categorical variable or as a continuous numerical variable. These approaches risk loss of information or violation of testing assumptions. In contrast, cumulative logit ordinal regression uses the information contained in the order …

Functional Consequences Of Lysine Acetylation Of Phosphofructokinase Isozymes, Xinyu Lin, Nour Fatema, Qinglei Gan, Chenguang Fan

Chemistry & Biochemistry Faculty Publications and Presentations

Phosphofructokinase (Pfk) catalyzes the phosphorylation of fructose 6-phosphate and is a key regulatory point in the glycolysis pathway. Multiple lysine residues in both Pfk isozymes, PfkA and PfkB, have been identified to be acetylated in Escherichia coli by proteomic studies, but no studies have been implemented to further characterize these acetylation events. To investigate the role of Pfk acetylation, the genetic code expansion strategy was used to generate homogeneously acetylated Pfk variants at target lysine sites that have been reported to be acetylated in nature. We found that acetylation of K309 of PfkA and K27 of PfkB decreased PfK enzyme …

Elucidating The Mechanisms Of Collagenase H From Hathewaya (Clostridium) Histolytica In Collagen Degradation And Developing A Cross-Linked Platform For Efficient Capture And Release Of Adeno-Associated Virus Serotype 2 (Aav2), Adjoa Otubea Bonsu

Graduate Theses and Dissertations

In biological systems, Hathewaya (Clostridium) histolytica secretes collagenases that degrade structural collagen in host tissues and cause tissue necrosis. Despite their detrimental effects, these enzymes have significant therapeutic potential by effectively digesting various collagen subtypes to treat connective tissue disorders. The bacterium produces two homologous collagenases, ColG and ColH, with a catalytic module crucial for hydrolyzing collagen and binding domains, including collagen-binding domains (CBDs) and polycystic kidney disease-like domains (PKDs), for substrate interaction.

Although the crystal structure of the catalytic module of collagenase G (ColG) has been determined, shedding light on its chew-and-digest mechanism, the structure of collagenase H (ColH) …