Physical Sciences and Mathematics Commons^™

Characterizing Microplastics In Flood Sediments After Hurricane Helene In Asheville, North Carolina, Abigail Sgan

All Theses

Microplastics are contaminants of emerging concern whose ubiquity across natural environments results in their involvement in many kinds of natural processes, including transportation and deposition in natural systems. The purpose of this thesis is to characterize microplastics and determine the mechanisms that affect their distribution, transport, and sequestration within known Hurricane Helene flood deposits in fluvial and Southern Appalachian wetland environments after Hurricane Helene in Asheville, North Carolina. Four fluvial and four Southern Appalachian wetland environments were sampled after Hurricane Helene. Samples collected in fluvial environments were taken as grab samples from surficial sandy flood deposits left behind by flooding …

The Aggregation Of Microplastics By Enhancing Extracellular Polymeric Substance Production In Pseudoalteromonas Sp. Ncimb 2021 To Improve Removal Efficiencies In Environmental Matrices, Janelle L. Mercer

All Theses

Microplastics (MP) are ubiquitous in the natural environment and are a growing threat due to their small size and durability. Plastics are released into the environment through improper waste management, wastewater treatment outfalls, industrial spills, agricultural runoff, and landfills. These particles breakdown into secondary MP through degradation pathways. MP, less than 5 mm, require intricate removal techniques from water systems. Filtration techniques, though viable and effective, have implementation constraints due to high cost, maintenance demands, and filter fouling. By integrating coagulation and flocculation processes prior to filtration, MP removal efficiencies can increase, while minimizing operational challenges during filtration. Extracellular polymeric …

Habitat Associations Of Small Mammals And Their Role As Sentinels For Biodiversity In The Southern Blue Ridge, Katelyn Steen

All Theses

Small mammals play important roles in healthy forests, but we still know very little about many of the rare and state-listed species living in the Blue Ridge Mountains of South Carolina. Traditional surveys are expensive and time-consuming, so we tested a newer, camera-based method called AHDriFT. From 2024 to 2026, we set up 60 camera systems across high-elevation forests to track six state-listed species: the Carolina red-backed vole, woodland jumping mouse, eastern woodrat, masked shrew, pygmy shrew, and eastern spotted skunk. We detected all six target species and conducted occupancy modeling for four. We found spotted skunk occupancy increased near …

The Impact Of State Insulin Copayment Caps On Diabetics In The United States, Ryan C. Meyer

All Theses

Insulin is a life-saving medication for people with diabetes that helps regulate blood glucose levels throughout the body. A Type 1 diabetic cannot survive without insulin, and a Type 2 diabetic’s quality of life greatly diminishes without access and use of this drug. Currently, many diabetics skip, ration, or abstain from insulin due to financial barriers. As of June 2026, 29 states have enacted insulin copayment caps for state-regulated commercial health insurance plans to reduce the financial burden of insulin costs. This study examines the impact of these caps on all commercially insured diabetics in the United States, particularly on …

Theory-Informed Generative Agents For Human Behavioral Modeling In Disasters, Liming Lu

All Dissertations

This dissertation develops a theory-informed generative-agent framework for modeling human behavioral decisions in disasters. Existing flood and disaster preparedness models often emphasize physical hazards, infrastructure exposure, or statistical correlations, but they struggle to capture the heterogeneous and evolving choices households make. This limitation is especially important for climate-related hazards, where future damage depends not only on changes in rainfall, inundation, and urban development, but also on decentralized protective actions such as house elevation, flood insurance, evacuation, and early preparedness. The dissertation integrates two empirical studies: a flood-risk study in Charleston, South Carolina, and a household disaster-preparedness study across hurricane contexts. …

Leveraging Deep Learning Recurrence And Attention Mechanisms For Flood Forecasting And Assessment, Elnaz Heidari

All Dissertations

Predicting how much water will flow in rivers and streams is important for managing floods, water supply, and the environment. Traditionally, government agencies have used complex models, such as the National Water Model (NWM), which simulate how much water moves through landscapes using physical laws and real-world data. However, recent advances in Artificial Intelligence (AI) have enabled new ways to make these predictions. This research explored whether AI-based models could predict river discharge more accurately. These AI models learn patterns from past data instead of relying only on physical rules. To find out how well they work, the AI models …

Imaging Oxygen Near Implanted Medical Devices Through Tissue With X-Ray And Ultrasound Modulated Luminescence Chemical Imaging, Vigjna Abbaraju

All Dissertations

Oxygen plays a crucial role in stem cell maintenance, tissue regeneration, disease progression, and treatment efficacy. For example, understanding oxygen dynamics within implanted medical devices, such as bone scaffolds, is essential for successful tissue regeneration and can serve as an early indicator of infection. The existing oxygen sensing and imaging techniques are often limited by narrow imaging depth, low spatial resolution in vivo resulting in poor understanding of oxygen dynamics in tissue microenvironments. This dissertation describes the development of implantable sensors using X-ray scintillators and thermochromic leuco dye paired with phosphorescent oxygen dye (PtTFPP) to image oxygen using X-ray luminescent …

Nanostructured Insulated Electrodes For Directed Nanoparticle Assembly: Development And Characterization, Thomas F. Burgess

All Dissertations

Nanoparticles exhibit unique properties dependent on their size, shape, and arrangement that are critical for sensing applications, such as the localized surface plasmon resonance of silver nanoparticles. Therefore, control over their assembly facilitates control over these properties. For this purpose, nanostructured insulated electrodes were developed and characterized for directed assembly of nanoparticle clusters. Electrode characterization required a new method for relative electric field quantification from electric force microscopy (EFM) measurements, implemented via an extended Hudlet model to estimate the field between the sample and the EFM probe apex. Restricting analysis to the apex – sample interaction improves spatial resolution and …

Structure And Dynamics Of Associative Polymers Under Quiescent State And Flow, Rosita Sivaraj

All Dissertations

Associative polymers, including ionizable polymers, are widely used in membranes, coatings, fuel cells, energy storage, and other advanced soft materials. Their properties are governed by ionic aggregation and associative interactions, which influence chain mobility, phase behavior, self-assembly, interdiffusion, and flow response. This dissertation employs large-scale molecular dynamics (MD) simulations to investigate the structure, dynamics, phase behavior, interdiffusion, and extensional flow response of ion-containing and associative polymer systems under quiescent and nonequilibrium conditions.

The influence of molecular architecture is first examined by comparing ring and linear associative polymers using the Kremer–Grest bead-spring model. In linear chains, their closed-loop architecture reduces interchain …

The Exploration Of One-Dimensional And Two-Dimensional Frustrated Magnetic Transition Metal Phosphates And Arsenates Via Hydrothermal Synthesis, Emily D. Williams

All Dissertations

Geometric magnetic frustration is a term that refers to magnetic spins that are “confused” or frustrated due to geometric arrangements of magnetic ions that prohibit the spins from magnetically ordering. This phenomenon has been subject to much research due to the ability to study exotic magnetic states and expand upon knowledge that would allow for materials to be implemented into quantum computing, memory storage and advanced sensor processing. One of the most exotic magnetic states, quantum spin liquids (QSL), has never been achieved but shows much promise. In the QSL state, magnetic spins do not order down to 0 K …

Can Kinematics Specify Tool Use Affordances?, Tyler Duffrin

All Dissertations

Object properties such as length, shape, and heaviness, as well as affordance-based properties such as strike-with-ability and poke-with-ability, can be perceived via dynamic touch as functions of inertia tensor invariants. The primary question addressed here was whether people can perceive these same power and precision properties for purely virtual objects, which lack dynamic physical forces. The Kinematic Specification of Dynamics (KSD) principle asserts that missing dynamics are lawfully specified by kinematic (visual) motion patterns, such that kinematic information alone may support successful interactions with virtual objects. In three experiments, we investigated (1) whether virtual reality (VR) users could calibrate to …

Ai-Driven Segmentation And Volumetric Response Modeling Of Liver Regions To Radiotherapy, Aashish Chandra Gupta

Dissertations and Theses (Open Access)

In liver-directed radiotherapy (RT), liver regions receiving higher doses typically undergo atrophy while contralateral/adjacent lower-dose regions may exhibit compensatory hypertrophy through regeneration of healthy tissue. Optimizing the RT plan to promote regional hypertrophy while minimizing the risk of developing atrophy has the potential to enhance post-RT liver function and long-term survivorship. However, current clinical practice largely relies on global liver dose-volume metrics during RT-planning, which may obscure favorable dose-response correlation and limit actionable guidance for clinicians. Therefore, we hypothesized that post-RT regional liver response is governed by a combination of region-specific dose-volume and patient clinical features, and that these responses …

On The Operation Of A Proteomics Core Facility: Selected Mass Spectrometric Studies And Methods, Rachel E. Muriph

Graduate Doctoral Dissertations

Mass spectrometry has become an indispensable analytical platform for investigating complex biological systems owing to its sensitivity, selectivity, and molecular specificity. This Dissertation demonstrates the versatility of liquid chromatography-tandem mass spectrometry (LC-MS/MS) through three studies focused on nanoparticle characterization, protein structural analysis, and plasma proteomics. In Chapter 2, LC-MS methods were developed to characterize novel lipidoid incorporated into lipid nanoparticles (LNPs) and to evaluate their in vivo biodistribution following systematic administration. Comparative proteomic analysis of the resulting protein coronas revealed distinct differences between liver and lung targeting LNP formulations, providing insight into the potential role of adsorbed blood proteins in …

Evaluation Of Dredged Sediments As A Partial Replacement For Fine Aggregate In Mortar And Concrete, Ashish Gautam

Graduate Theses and Dissertations (2019 - present)

The feasibility of using dredged sediment from the Mobile River as a partial replacement for fine aggregate in mortar and concrete was investigated through a series of laboratory characterization and performance evaluation. Three dredged sediment samples (A, B and C) were initially examined, and Sample A was selected for further evaluation due to its closer resemblance to natural fine aggregate. This sample exhibited lower moisture content, higher sand equivalent values, higher specific gravity, and lower absorption. Mortar mixtures with 0, 10, 20, 30, 50, 75 and 100% dredged sediment replacement showed decreasing workability as the replacement level increased. The 20% …

Criticality In A Heterogeneous Neutron Transport Rod Model, Samuel Kaleb Crowford

All Graduate Reports and Creative Projects, Fall 2023 to Present

This work studies the stochastic behavior of neutron populations in a one-dimensional rod model using Monte Carlo simulation. The first part of this project reproduces the computational results of Dumonteil, Horton, Kyprianou, and Zoia (2025) by independently implementing the Monte Carlo algorithm described in their article, with the asymptotic behavior of the first moment analyzed in relation to the dominant eigenvalue and adjoint eigenfunction of the neutron transport operator. The model is then extended to a heterogeneous setting by introducing a central region where fission is suppressed. A global expectation over initial positions and directions is used to estimate the …

Advancements In Modern Seismic Monitoring: Integrating Novel And Traditional Methods For Earthquake Detection, Characterization, And Structural Imaging, Marc Adrian Garcia

Open Access Theses & Dissertations

Modern seismic monitoring has been transformed by machine-learning methods that detect and locate earthquakes at scales manual analysis cannot reach. This dissertation develops, validates, and applies such workflows across three settings that span the range of modern monitoring problems: a major subduction-zone aftershock sequence, the tectonic questions that sequence can answer, and an urban region without any local monitoring at all. First, I construct a high-resolution catalog for the aftershock sequence of the September 8, 2017, Mw 8.2 Tehuantepec, Mexico earthquake, by integrating deep-learning phase detection with established location and relocation methods. The resulting catalog of 11,374 relocated earthquakes is …

A Patch-Level Framework For Urban Vegetation Water Demand Estimation Using Remote Sensing And Deep Learning, Jesus Daniel Pereyra Manriquez

Open Access Theses & Dissertations

Urban water management in semi-arid regions requires an improved understanding of how vegetation and climatic conditions influence landscape water demand. Existing approaches often lack an integrated, spatially consistent framework to quantify this relationship at fine scales. This study proposes a patch-level framework to estimate relative landscape water demand by integrating vegetation coverage, vegetation condition, and atmospheric demand. Vegetation coverage is derived from high-resolution imagery obtained from the National Agriculture Imagery Program (NAIP) using a U-Net segmentation model with a MobileNetV2 backbone. A patch-based representation is used to ensure spatial consistency across the study area. Seasonal vegetation dynamics are captured using …

Domain Adaptation Of Facial Age Estimation For Law Enforcement Mugshot Repositories, Jorge Alejandro Pacheco Roque

Open Access Theses & Dissertations

Facial age estimation supports law enforcement via image-based, age-filtered queries, age-progressive re-identification, and bulk record labeling, where prediction accuracy determines if the resulting decisions can be trusted. State-of-the-art models excel on web imagery but incur higher error on mugshots due to domain shift between the professionally lit, filtered, and posed web photographs used during pre-training and the uniform backgrounds, uncooperative expressions, and decades of evolving capture technology found in mugshot collections. We address this gap by adapting SwinFace - a state-of-the-art multi-task Swin Transformer with public code and pretrained weights, trained on color face imagery for face recognition, facial expression …

Dlc Thin Films For Semiconductor Applications, Balam Arturo Sotelo

Open Access Theses & Dissertations

The growing need for resilient semiconductor supply chains has increased the interest in developing local and accessible materials fabrication strategies. Since large-scale semiconductor manufacturing is complex to establish quickly, simpler deposition techniques may provide a practical route to start developing semiconductors materials. Diamond-like carbon (DLC) is a promising candidate in this context because its properties can be tailored through substrate selection and processing parameters.

This thesis establishes an initial framework for the study and fabrication of diamond-like carbon (DLC) materials in the Department of Physics at The University of Texas at El Paso. DLC thin films were deposited by magnetron …

Stabilized Continuous Galerkin Methods For Heat Transport In Fully Coupled Nonlinear Thermo-Poroelasticity In Heterogeneous Porous Media, Payel Dey

Open Access Theses & Dissertations

This thesis focuses on the numerical approximation of a coupled Thermo-Hydro-Mechanical (THM) model with advective heat transport in heterogeneous media. The governing equations consist of three coupled equations: the momentum balance, the fluid mass balance, and the energy balance. The primary unknowns are displacement, pressure, and temperature. In this system, the fluid pressure determines the Darcy flux, and this flux transports heat through the advective term in the energy equation. Since the Darcy flux is computed numerically from the flow equation, the conservation properties of the flow approximation can affect the temperature solution. This effect is especially important when thermal …

Where Electrons Localize And Bonds Vibrate: Computational Insights Into Lanthanides And Octanoic Acid., Sonam Choki Lhamo

Open Access Theses & Dissertations

Density Functional Theory (DFT) is a widely used approach for studying the electronic and vibrational properties of atomic and molecular systems. It provides a practical balance between accuracy and computational cost, making it suitable for a broad range of applications in quantum chemistry and materials science. The primary focus of this thesis is the electronic structure of lanthanide atoms, where strongly localized 4f electrons give rise to significant self-interaction errors in conventional density functional approximations. The performance of the Perdew-Zunger self-interaction correction (PZSIC) and the locally scaled self-interaction correction (LSIC) approach developed by Zope et al. is investigated using both …

Optimizing Urban Forestry Through Green Infrastructure: Tree Health And Water Retention In Ciudad Juarez Rain Gardens, Tomas Rogelio Lizarraga Ruiz

Open Access Theses & Dissertations

Urban green spaces (UGS) in arid regions face significant challenges due to water scarcity and extreme thermal demand. This study evaluates the efficacy of Nature Based Solutions (NBS), rain gardens and median strips, in enhancing the physiological resilience of urban trees in Ciudad Juárez, Mexico. Using a comparative framework, the research monitored a native evergreen (Dermatophyllum secundiflorum) and an introduced deciduous species (Morus sp.) across six planting treatments. Statistical analysis reveals that green infrastructure (GI) acts as a critical physiological accelerant. Trees situated within rain gardens and medians significantly outperformed those in restricted pot and sidewalk settings, maintaining higher stomatal …

A Computational Approach To Electronic Coupling In Molecular Dyads, Irving Alejandro Lopez Ruiz

Open Access Theses & Dissertations

Excitation energy transfer (EET) is a fundamental process in photosynthetic systems and molecular photonic devices, where the efficient transport of electronic excitation between donor and acceptor chromophores determines the overall performance of the system. The electronic coupling V_DA between the transition densities of the two fragments is the central quantity governing this process in the weak-coupling (Förster) regime, and its accurate numerical evaluation is the main objective of this work. Two independent computational implementations of the Coulomb interaction between transition densities were developed and applied to a set of five anthracene-BODIPY donor-acceptor dyads, studied under two geometric configurations: one preserving …

Hfir Antineutrino Flux Mapping With Scale Mesh Tallies, Jacob Adam Mireles

Open Access Theses & Dissertations

This thesis develops and demonstrates a workflow for mapping the spatial distribution of reactor electron antineutrino flux around the High Flux Isotope Reactor (HFIR) using three-dimensional mesh tallies from the SCALE 6.3.1 Monte Carlo transport suite. A detailed HFIR model is executed with KENO, and the mesh-tally output is post-processed to construct a voxelized antineutrino source term. The source field is normalized to reactor power and propagated to sampled spatial points surrounding the reactor to generate three-dimensional source-side flux maps. The main analysis focuses on how the mesh-based HFIR antineutrino flux differs from an ideal point-source approximation. In the point-source …

Physics Model Calibration Via Functional Kernel Regression, Kwesi Appau Ohene-Obeng

Open Access Theses & Dissertations

Physics based computational simulators encode the governing equations of complex physical phenomena through parameters that must be inferred from empirical observations, and the observational record in modern experimental campaigns is increasingly a high dimensional functional response rather than a scalar summary. The canonical treatment of this calibration problem through the additive discrepancy decomposition of Kennedy and O'Hagan incurs O(N^3obs) Gaussian process inversion costs at functional resolution, sensitivity to discrepancy prior specification, and the confounding identifiability between the calibration parameter and the discrepancy function; scalar reduction strategies bypass the cost but discard the morphological information that the functional response carries about …

Towards A Multi-Framework Approach To Explainable Artificial Intelligence, Henry Salgado

Open Access Theses & Dissertations

Artificial Intelligence (AI) and machine learning (ML) models are increasingly being deployed to support decision-making in high-stakes domains such as healthcare, criminal justice, and education, where trust, accountability, and transparency are critical. However, increasing model complexity has made many modern systems insufficiently transparent. Existing approaches to explainable AI (XAI) typically emphasize either intrinsic model simplicity or post-hoc attribution methods that estimate feature importance for predictions. While these approaches provide valuable insights into model behavior, they do not necessarily establish whether the identified importance is grounded in the underlying data patterns or in the structural relationships that generate model behavior. Many …

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, …

Pseudo-Riesz Bases, Deborpita Biswas

All Dissertations

In this dissertation, we will introduce the concept of pseudo-Riesz bases, extending the influential notion of near-Riesz bases first proposed by J. Holub in the 1990s. Our goal is to develop an analogous theory for pseudo-Riesz bases, obtaining results parallel to those known for near-Riesz bases, with suitable modifications.

We will develop the foundational theory of pseudo-Riesz bases. Unlike classical Riesz bases, these sequences need not be complete or independent; however, they still retain meaningful expansion properties. We will investigate the conditions under which a Bessel sequence can be transformed into a Riesz basis through finite modifications. In particular, we …

Causal Discovery Methods For Single Cell Rna-Seq Data, Melanie Lambert

All Dissertations

The advancement of single cell RNA sequencing (scRNA-seq) has enabled the study of causal relationships between genes at single cell resolution. Although many causal discovery methods have been applied to scRNA-seq perturbation data, they are not well-suited to capture the characteristics of scRNA-seq data. The overall goal of this dissertation is to enhance researchers' ability to gain insight into genetic relationships.

The scRNA-seq data is high-dimensional, typically containing thousands of genes, and is sparse and zero-inflated due to dropout events, as well as noisy and subject to biological variability. Traditional causal discovery methods, such as constraint or score-based approaches, do …

A Longitudinal Analysis Of Hospital Consumer Evaluation In Virginia, Tulay Akmandor Inac

Health Services Research Dissertations

Suboptimal patient experience signals a need to improve clinical efficacy, patient safety, and healthcare quality. The COVID-19 pandemic intensified hospital resource and staffing demands, reducing hospitals’ capacity to invest in patient experience improvement. Prior studies remain limited because many lack longitudinal structure and organized theoretical models, making temporal inference difficult and weakening analyses of patient experience disparities. To address these limitations, this dissertation incorporates three studies examining patient experience and pandemic-related effects.

In state-level markets comparable to Virginia, limited research has examined longitudinal patient experience trends across regional hospital systems using HCAHPS scores. The first study uses descriptive trend analysis …