Physical Sciences and Mathematics Commons^™

An Ordinal Categorical Data Analysis Using The Stereotype Model Within A Bayesian Framework With A Logistic-Normal Prior, Nathaniel A. Sakyi

Open Access Theses & Dissertations

Ordinal categorical data are pervasive in applied research, yet their analysis is often compromised by modeling strategies that implicitly assume equidistant category spacing or impose restrictive structural constraints. Metric regression models and latent-variable threshold approaches routinely misrepresent ordinal information, leading to biased inference, distorted uncertainty quantification, and loss of structural insight. This paper develops a Bayesian framework for ordinal regression that explicitly accommodates \textbf{unequal spacing among ordered response categories} while preserving ordinal structure and interpretability.

The proposed approach builds on the stereotype regression model, which embeds ordinal categories into a latent one-dimensional continuum through estimable score parameters. While the stereotype …

Hvsr-Based Resonance Analysis And Fault Zone Characterization In The El Paso Region, Alexandro Dominguez

Open Access Theses & Dissertations

Horizontal to Vertical Spectral Ratio (HVSR) analysis offers an efficient method for characterizing near-surface structure, resolving sediment thickness, and identifying fault-controlled basin geometry in regions with strong impedance contrasts. This study applies HVSR techniques to continuous ambient-noise recordings collected across the El Paso region, a tectonically active segment of the southern Rio Grande Rift where accurate subsurface mapping is essential for seismic hazard assessment. Ambient-noise windows were processed, spectrally smoothed, and stacked to obtain stable HVSR curves, from which fundamental resonance frequencies and corresponding sediment-thickness estimates were derived. Spatial patterns in these resonance frequencies reveal pronounced basin asymmetry, abrupt lateral …

First-Principles Study Of Uranium Mononitride, Roy Noe Herrera Navarro

Open Access Theses & Dissertations

This thesis presents a first-principles investigation of uranium mononitride (UN), withemphasis on the connection between uranium 5f electron correlation and defect stability. Electronic-structure calculations were performed within density functional theory using the Vienna Ab initio Simulation Package. Exchange-correlation effects were treated within the generalized gradient approximation, and a Hubbard correction was applied to the uranium 5f manifold. The adopted Hubbard parameter was motivated by first-principles linear-response analysis and considered in the broader context of DFT+DMFT descriptions of correlated uranium systems, including recent interpretations of UN as a Hund-metal system. Bulk UN was studied in unit-cell and 2 x 2 x …

Singularity-Enriched Neural Networks For Elliptic Problems In Polygonal Domains, Harshini Reddy Kodiganti

Open Access Theses & Dissertations

This thesis develops and analyzes neural-network-based solvers for the Poisson equation on polygonal domains, where re-entrant corners induce reduced solution regularity and challenge standard numerical methods.

Three neural formulations are investigated: Physics-Informed Neural Networks (PINNs), Physics-Informed Extreme Learning Machines (PIELMs), and Rank-Inspired Neural Networks (RINNs). PINNs rely on gradient-based optimization with automatic differentiation, while PIELMs employ randomly initialized hidden features with least-squares training, achieving significantly lower computational cost. RINNs extend this framework through covariance-driven orthogonalization to improve numerical conditioning and stability.

On convex polygonal domains, all three methods are benchmarked against analytical solutions. Both PIELM and RINN consistently achieve higher …

Metabolomics In The Dryland Critical Zone: The Role Of Soil Metabolites In Phosphorus Acquisition, Kalpana Kukreja

Open Access Theses & Dissertations

Earth's Critical Zone (CZ) plays a key role in sustaining life through carbon, water, and nutrient cycling from the top of the canopy to the groundwater. A key feature of critical zone research is the integration of multiple interdisciplinary techniques. An emerging set of techniques that can add to this approach is the field of metabolomics, the quantification and study of comprehensive metabolite profiles. In this dissertation, I apply metabolomics to address knowledge gaps in dryland critical zone ecosystems, specifically how soil metabolite dynamics influence biogeochemical processes, and with a particular emphasis on phosphorus (P) cycling in the Chihuahuan Desert. …

Plant Communities Of Arid Ephemeral Stream Streams, Biogeographic Filters, Climatic Sensitivity, Urban Impacts Across Spatial And Temporal Scales, Luis Miranda

Open Access Theses & Dissertations

Ephemeral stream networks, locally known as arroyos, are among the most ecologically significant yet least protected habitats in arid landscapes. Despite supporting a disproportionately high plant biodiversity compared to surrounding uplands, these riparian systems lack regulatory protection in most arid U.S. states and face increasing pressure from urban expansion and intensifying climate change. There is an urgent need to understand how these factors influence riparian plant communities and hinder their ability to recover, enabling effective conservation and management strategies. In this dissertation, I explored the interplay of biogeographic gradients, precipitation variability, and urbanization in shaping arroyo riparian plant communities across …

Understanding Machine Learning Model Behavior Under Fairness And Privacy Constraints, David Anthony Sanchez

Open Access Theses & Dissertations

Machine learning systems deployed in high-stakes domains are increasingly expected to satisfy demands beyond predictive accuracy-including fairness across demographic groups, protection of sensitive information, and explanations that human stakeholders can inspect and trust. This thesis investigates how those demands can be met through learning frameworks that explicitly govern the relationship between data and models, arguing that trustworthiness is a design problem rather than a post hoc correction. The thesis is organized around three studies, each targeting a distinct point of data-facing control. The first develops CondFairGen, a fairness-aware conditional generator for tabular data that improves subgroup equity by dynamically reweighting …

Eocene To Oligocene Continental Arc Migration In Ecuador And The Origin Of Spatiotemporal Trends In Zircon Lu-Hf Radiogenic Isotopes, Muriel M. Sandoval Vazquez

Open Access Theses & Dissertations

The modern continental arc system in Ecuador is well understood but less is known about arc systems in the past, hindering our understanding of the tectonic evolution of the northern Andes. The Macuchi arc, located in the Western Cordillera of Ecuador, was thought to be the main continental arc system during the Eocene, but new zircon U-Pb LA-ICPMS dates from intrusive arc rocks in central Ecuador indicate a more complex history. During the mid-Eocene, the footprint of arc magmatism broadened and expanded into the Inter-Andean Valley and Eastern Cordillera. During the late Eocene to Oligocene, the arc migrated back toward …

Overcoming Glioblastoma Resistance To Temozolomide With New Derivatives: Design, Synthesis, And Mechanistic Studies, Hualin Zhang

Open Access Theses & Dissertations

Glioblastoma multiforme (GBM) is an aggressive brain tumor with rapid progression and poor prognosis. Although temozolomide (TMZ) remains a central component of standard therapy, its clinical benefit is limited and resistance frequently emerges through DNA repair pathways, particularly O6-methylguanine-DNA methyltransferase (MGMT). Because DNA cross-links are generally more difficult to repair than monoalkylated lesions, we hypothesized that TMZ derivatives bearing protein-reactive functionality might generate damage that is less susceptible to MGMT-mediated resistance. Guided by this rationale, we designed a new class of N3-modified TMZ derivatives containing covalent warheads, developed a synthetic route compatible with the chemical instability of the TMZ scaffold, …

Environmental Movements In El Paso And Ciudad Juarez: Possibilities And Limitations Of Cross-Border Organization At The U.S.-Mexico Border, Vanessa Maria Almada

Open Access Theses & Dissertations

At the U.S.-Mexico border, the anthropogenic and nationalistic construction of the landscape has accelerated urbanization and unequal development without establishing effective binational institutions for governance over a shared commons. Borderlanders, then, contest unsustainable development with the added complexity of navigating a barrier which creates diverse socioeconomic and political realities that challenge cross-border cooperation. This qualitative research analyzes environmental organizations in El Paso and Ciudad Juarez. Through ethnographic study of mobilization in response to environmental legislation and administrative action in each city, the immediate barriers to cross-border cooperation and limitations of nationalistic institutions in the borderlands can be better understood.

Exhumation Of The Pelona-Orocopia-Rand Schist And Fault Kinematic Constraints On Evolution Of The Eastern California Shear Zone, James Boyette Barker

Open Access Theses & Dissertations

Southeastern California has experienced a complex recent geologic history as it continues to evolve from a convergent boundary to a period of NE-directed extension and evolution of the Eastern California Shear Zone (ECSZ). This transition is recorded in exhumed bodies of Pelona-Orocopia-Rand (POR) schist and in changing styles of fault deformation. This thesis has two interrelated goals. First, I aim to refine the timing of transition from NE extension to NS contraction in the ECSZ of southeastern California by integrating (U-Th)/He thermochronology with field-based structural analysis. The second prong of this study is to constrain broader patterns of POR schist …

Exploring Connectivity And Element Distribution In The Critical Zone Using Deep Cores Below Agricultural And Natural Drylands In The American Southwest, Angie Lynette Cano

Open Access Theses & Dissertations

Water movement controls how solutes are transported and stored in arid Critical Zone (CZ) systems. In natural drylands, low precipitation and high evapotranspiration lead to long term salt accumulation in the CZ, whereas irrigation increases water input and increases downward solute transport. This study investigates how agricultural practices alter subsurface hydrology and geochemistry by comparing two deep CZ cores from the southwestern United States: a 50 m deep core beneath a flood irrigated pecan farm named 5R farm, in the Rio Grande Valley in Tornillo, Texas, and a 97.5 m deep core from the Red Lake Playa in the Jornada …

Timing And Synchronization: Software And Hardware Approaches For Precision Maximizing, Christina Alicia Alejandra Carreon Jimenez

Open Access Theses & Dissertations

This thesis explores the design of synchronization mechanisms that allow multiple FPGA boards to operate as if they were a single coherent timing domain. The solutions span three layers: a software PLL for E1 telecommunication links, a PCIe-based timestamp exchange protocol, and a hardware-level multi-FPGA mesh architecture. Across these layers, the work demonstrates that practical, low-cost synchronization can achieve sub-microsecond accuracy without the burden of specialized hardware such as GPSDOs or White Rabbit infrastructure. Experiments show stable alignment within the nanosecond-microsecond range, validating the feasibility of the proposed methods for SDR and telecom applications.

Spike-Sorting Algorithm For Neuropixel Probes, Luis David Davila

Open Access Theses & Dissertations

Modern extracellular neural probes like Neuropixels, allow for high-density extracellular neural probes to record terabytes of electrophysiological brain data. Spike sorting is the process of isolating individual neurons on this data through various clustering and filtering techniques. Modern spike sorting algorithms are held back by their need for human intervention to separate high-quality from low quality clusters, due to the volume of data that can be collected a completely automated approach is required. To address this requirement, we have developed a framework to preprocess, cluster, grade, and separate high/low quality clustering results using custom models trained on the grades. To …

Molecular Mechanisms Of Pfas Induced Protein Dysfunction: Implications For Neurodegenerative Risk, Daisy Lee Wilson

Open Access Theses & Dissertations

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with widespread human exposure and well-established links to adverse health outcomes. However, despite increasing epidemiological and experimental evidence, the molecular mechanisms underlying PFAS-induced neurotoxicity remain incompletely defined. This dissertation investigates PFAS toxicity across biological scales, integrating protein biophysics with neuronal cell models to elucidate pathways relevant to neurodegeneration. At the molecular level, we demonstrate that PFAS disrupts the structure and function of globular proteins, including the impairment of α-lactalbumin's calcium-binding capacity and of β-lactoglobulin's retinol binding, through concentration-dependent conformational destabilization. By applying these findings to a neuronal model, we show that …

Riemannian Manifold-Coupled Joint Sparse Graphical Models For Spatially Structured Precision Matrix Estimation, Abdul Rahman Adam

Open Access Theses & Dissertations

This thesis introduces a novel geometry-aware framework for joint precision matrix estimation in spatially structured data. Unlike existing joint Gaussian graphical model estimators that rely on Euclidean coupling mechanisms such as fused or group graphical lasso, our approach incorporates intrinsic Riemannian geometry through geodesic distance penalties on the symmetric positive definite manifold.

The method measures similarity between precision matrices of adjacent spatial regions using the affine-invariant Riemannian distance, capturing deformations of concentration ellipsoids rather than entrywise differences. This is particularly suited for spatial transcriptomics, where regions may share dependence structures despite differences in scale or composition.

An efficient Alternating Direction …

Comparative Case Studies Of How General Chemistry Ii Students Explain Entropically-Driven Phenomena, Raymundo Aragonez

Open Access Theses & Dissertations

Understanding how students conceptualize entropy remains a central challenge in chemistry education. Often referred to as a "driving force" of chemical reactions, the dispersal of energy as a process proceeds is indicative of a process's spontaneity or thermodynamic favorability. Students frequently default to discussing phenomena in deterministic terms, potentially reflecting the language choice and heuristics selected by the instructor such as "disorder". In this study, assessment prompts about entropy from a convenience sample of general chemistry textbooks were characterized as to their potential to elicit three-dimensional learning, and students' responses to assessment prompts from a curriculum aligned with three-dimensional learning …

Automated Arctic Coastal Boundary Extraction From Multispectral Satellite Imagery, Harshavardhini Bagavathyraj

Open Access Theses & Dissertations

Arctic coastlines are changing rapidly as permafrost thaw and coastal erosion accelerate under a warming climate, creating a need for accurate and scalable methods to monitor landscape change. Two geomorphically important indicators of this change are the shoreline, which represents the land--water boundary, and the bluff edge, which marks the transition from vegetated tundra to the coastal slope or cliff. However, delineating these features from high-resolution imagery remains challenging because Arctic scenes are spatially extensive and visually complex. In this study, we address these challenges by developing deep learning methods for automated shoreline and bluff-edge extraction from high-resolution satellite imagery …

Bayesian Deep Learning For Photovoltaic Power Forecasting: A Probabilistic Framework For Uncertainty Quantification And Grid Reliability Optimization, Pablo Abraham Bustamante

Open Access Theses & Dissertations

The global energy landscape is undergoing a profound transformation, driven by the urgent need to decarbonize power systems, enhance energy security, and meet growing electricity demands. Solar photovoltaic (PV) power has emerged as a critical component of future energy infrastructure due to its abundance, scalability, and cost-effectiveness. However, PV generation is inherently variable and weather-dependent, introducing significant uncertainty into grid operations and complicating the task of balancing supply and demand. Accurate forecasting of PV power generation-particularly on day-ahead and hour-ahead horizons-has become a strategic necessity for grid stability, economic efficiency, and environmental sustainability. PV output is influenced by numerous factors, …

From Infiltration Pathways To Aquifer Recharge: An Electrical Resistivity And Vadose-Zone Isotope Study In Pecan Agroforestry Systems, Jose Josue Cabral

Open Access Theses & Dissertations

Groundwater in arid or semi-arid regions is critical for agricultural production, yet the contribution of irrigation return flow to regional aquifer recharge remains poorly constrained. As is the case beneath flood-irrigated pecan orchards in the Rio Grande floodplain of Far West Texas. This study integrates time-lapse electrical resistivity tomography (ERT) with stable water isotopes (δ¹⁸O, δ²H) in vadose-zone soil-pore water to evaluate how irrigation water infiltrates. This study tracks how irrigation return is stored and may contribute to recharge of the Hueco Bolson aquifer. The objectives are to (1) relate observed resistivity variations to stratigraphic heterogeneity influencing infiltration, (2) characterize …

Computational Studies Of Dna-Wrapped Carbon Nanotubes: From Enantioselective Dna Binding To Molecular Recognition Of Small-Molecule Analytes, Sayantani Chakraborty

Open Access Theses & Dissertations

Single-walled carbon nanotubes (SWCNTs) exhibit chirality-dependent optoelectronic properties and near-infrared fluorescence that make them promising platforms for biosensing. When functionalized with single-stranded DNA (ssDNA), SWCNTs form conjugates capable of selective molecular recognition. However, the molecular mechanisms governing chirality recognition and analyte-induced optical modulation remain incompletely understood. This dissertation investigates these mechanisms through an integrated computational approach combining molecular dynamics simulations, enhanced sampling techniques, and machine learning. First, atomistic molecular dynamics (MD) and replica exchange MD simulations were used to investigate how short ssDNA sequences interact with enantiomers of (7,5) SWCNTs. Analyses of base stacking, nucleotide orientation, sugar-phosphate positioning, and contact …

From Covid-19 To Influenza: Transforming Public Health Surveillance Through Freeze-Drying Innovations, Rui Dong

Open Access Theses & Dissertations

Public health surveillance increasingly relies on wastewater-based epidemiology (WBE) as a non-invasive, community-level early warning system for infectious diseases like COVID-19 and influenza. However, detecting minute viral concentrations in complex wastewater matrices remains a significant analytical challenge. Traditional concentrating methods, such as ultrafiltration, are limited by high performance variability and significant viral signal loss due to necessary pretreatment steps, such as pre-clarification, which inadvertently discard solid-associated viral fractions. To address these limitations, this dissertation introduces and evaluates freeze-drying as a novel, pretreatment-free concentrating method for wastewater viral surveillance. By sublimating water, freeze-drying uniquely retains both liquid and solid-phase viruses within …

A Diagnostic Test For Confounding Under Collapsibility In Generalized Linear Models (Glms), Samuel Dela Gadah

Open Access Theses & Dissertations

This thesis develops and validates a diagnostic framework for assessing potential confounding in generalized linear models (GLMs) with collapsible link functions. Under collapsibility and effect homogeneity, the absence of confounding implies equality between marginal and covariate-adjusted treatment effects on the link scale, which motivates the change-in-estimate parameter δ = γ − γ(c) as the target of a formal hypothesis test. Two complementary inferential routes are developed: a nonparametric bootstrap and an independent estimating equation (IEE) procedure based on a stacked-data construction that yields a closed-form sandwich variance and is implementable in standard generalized estimating equation software. A backward elimination procedure …

Prediabetes Prediction Before Disease Onset Using Multimodal Health Data: A Machine Learning Approach, Luisa Veronica Gracia Mazuca

Open Access Theses & Dissertations

Prediabetes is a critical health condition that increases the risk of developing type 2 diabetes. The hemoglobin A1c (HbA1c) test diagnoses patients with prediabetes, but the disease has already caused metabolic alterations. Early detection is essential for timely interventions, and machine learning models offer a promising approach to identify prediabetic individuals through the analysis of biomarkers such as cytokines. We compared four classifiers-logistic regression, decision tree, random forest, and k-nearest neighbors - using cytokines (TNF-α, MCP-1, IL-1β, IL-6, IFN-γ), age, BMI, and waist-to-hip ratio (WHR). Models were evaluated using stratified 5-fold cross-validation and ROC-AUC. K-Nearest Neighbors (k-NN) achieved the highest …

Development Of A High-Throughput Framework For Studying Choice-Movement Dynamics In Freely Moving Rats Across Motivational And Pharmacological States, Atanu Giri

Open Access Theses & Dissertations

This thesis develops and applies high-throughput behavioral assays and analysis pipelines to study how external contingencies and internal state shape rodent decision-making. First, it introduces RECORD (Reward-Cost in Rodent Decision-making), a modular platform that combines 3D-printed arenas, microcontroller-based control, and closed-loop trial structure to deliver graded rewards and costs in a foraging-like environment. RECORD supports scalable data collection across multiple arenas and a software stack for parsing, databasing, and extracting spatiotemporal behavioral features and psychometric choice functions. Using this framework, the thesis quantifies how animals integrate sucrose reward magnitude with aversive light cost, revealing structured individual differences and sex-dependent movement …

Exploratory Proxy Occupational Health Risk Assessment On Pm2.5 Exposure Among Outdoor Personnel At International Ports Of Entry, Josdell Maria Guerra Ruiz

Open Access Theses & Dissertations

Despite growing public health concerns on PM2.5 exposure and its respiratory health effects, no documented evidence has been found on the application of proxy methods to perform occupational health risk assessments for PM2.5 exposure among outdoor personnel. The purpose of this research study was to conduct a descriptive and predictive occupational health risk assessment for cancer and non-cancer respiratory health outcomes related to PM2.5 exposure among outdoor personnel at targeted international ports of entry (IPOE). A total of 61 samples were collected, for 24 hours, at two targeted IPOEs (every sixth day) over 12-month period. Samples included measurements on PM2.5 …

The Effect Of Temperature And Hydroperiod On Rotifer Hatching Diversity And Phenology In Ephemeral Playas, Brent Samuel Hogue

Open Access Theses & Dissertations

As climate continues to change, weather events such as heat waves and precipitation are expected to become more extreme, and organisms living in these ephemeral habitats will experience unprecedented conditions that may test their limits. However, some organisms that live in these habitats are adapted for resiliency in the face of fluctuating conditions. The focal taxa of this study are rotifers, which have the ability to produce diapausing eggs, that are stored in sediment egg banks. Diapausing eggs will hatch once suitable conditions occur in the habitat, while the rest remain stored in the sediment. This strategy assists in the …

Robust Logistic Regression With Elastic Net For Contaminated High-Dimensional Data, Chitra Bahadur Karki

Open Access Theses & Dissertations

High-dimensional logistic regression is particularly vulnerable to outliers, which can distort estimation, weaken variable selection, and harm prediction accuracy. This dissertation introduces RobENetLog, a robust elastic net logistic regression method that jointly selects informative variables and reliable observations by extending ideas from least trimmed squares regression to the classification setting. The proposed approach combines adaptive outlier detection with trimmed penalized estimation so that it can address contamination in both predictors and responses across a wide range of dimensional settings. Simulation studies show that RobENetLog consistently improves predictive performance and robustness in the presence of outliers, while remaining competitive with standard …

Characterization Of The Synhalokinetic Megaflap Lithofacies And Stratigraphy At Sinbad Valley, Paradox Basin, Western Colorado, Michael David Laase

Open Access Theses & Dissertations

This study documents the halokinetic evolution of the Sinbad Valley salt wall and flanking megaflap through the characterization of its lithofacies, stratigraphy, and major structures. Sinbad Valley salt wall is in the northern Paradox Basin, in western Colorado, and is the most proximal salt diapir to the Uncompahgre Uplift, the clastic sediment source for the basin. Megaflaps are recently defined structures involving early minibasin strata that are folded up to form steeply dipping "stratal panels" along the sides of steep diapirs. The Sinbad Valley megaflap crops out as a ~7.5km long and 400m wide panel of folded and deformed Pennsylvanian- …

Three Essays On Workplace Ethics And Ai: Conceptualizing, Scale Development, And Validation Of Self-Value Actualization, And Ai-Enabled High-Performance Work Systems, Mansura Nusrat

Open Access Theses & Dissertations

This dissertation advances understanding of workplace ethics and responsible AI integration across three interconnected essays unified by social cognitive theory. My first essay introduces self-value actualization (SVA), a novel construct defined as the dynamic, integrated psychological process through which individuals continually strive to align and fulfill their core moral values through observable professional behavior. Drawing on social cognitive theory and emotional intelligence theory, I conceptualize SVA as a higher-order self-regulatory orientation comprising three mutually reinforcing processes: value congruence, moral reflection, and adaptive morality. I developed and validated a 9-item SVA scale across four studies using expert panels, exploratory factor analysis, …