Physical Sciences and Mathematics Commons^™

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, …

Zero-Knowledge Proofs For Verifiable Machine Unlearning, Bidur Niroula

Open Access Theses & Dissertations

Machine unlearning aims to remove the influence of deleted data from a trained machine learning model. This is important because privacy regulations such as GDPR, CCPA, and PIPEDA give individuals the right to request the deletion of their personal data. Since unlearning can be expensive, a dishonest server may skip it or return an incorrect model and this motivates verifiable machine unlearning. Existing cryptographic approaches prove that the server executed a specific training or unlearning algorithm on the committed dataset, so the proof is tied to the algorithm's trajectory. Empirical verifiers avoid this cost but are known to be circumventable …

Deep Neural Network-Gaussian Process For Housing Price Analysis, Bismark Nyarko

Open Access Theses & Dissertations

Neural networks have demonstrated remarkable predictive performance in complex, high-dimensional settings. However, their highly parameterized structure and nonlinear architecture often make them difficult to interpret, limiting formal statistical inference and principled uncertainty quantification. In contrast, Gaussian processes (GPs) provide a fully probabilistic framework with a relatively small number of hyperparameters, enabling coherent uncertainty quantification and seamless integration into hierarchical and structured statistical models. Despite their theoretical flexibility as nonparametric function approximators, standard GP formulations frequently exhibit weaker predictive performance than modern neural networks in large-scale applications.

In this work, we employ a Gaussian process covariance function designed to approximate the …

Efficient Solvers For Phase Field Models, Raymond Obeng

Open Access Theses & Dissertations

Phase field models provide a versatile framework for describing phase transitions and pattern formation in materials, enabling the study of complex phenomena such as crystallization, grain growth, and defect dynamics. Among these models, the Phase Field Crystal (PFC) equation has gained significant attention due to its ability to capture atomic-scale structures while evolving on diffusive time scales. However, the numerical solution of the PFC equation presents substantial challenges arising from its high-order nature and the large-scale, coupled linear systems generated by discretization.

In particular, standard formulations of the discretized PFC system lead to non-symmetric and often ill-conditioned linear systems, which …

Contamination-Aware Boosting For Cancer Prediction, Francis Opoku

Open Access Theses & Dissertations

Modern cancer research increasingly relies on machine learning methods to model complex relationships between high-dimensional genomic predictors and clinically relevant outcomes. Gradient boosting methods, particularly XGBoost, have become widely used due to their strong predictive performance and ability to capture nonlinear effects and interactions. However, these methods are sensitive to contamination in the data, especially in the response variable, where even a small fraction of aberrant observations can disproportionately influence model fitting and degrade generalization.

In this thesis, we propose a contamination-aware extension of XGBoost, termed CA-XGBoost, which improves robustness by explicitly modeling residuals through a latent mixture framework. This …

Computational Studies Of Alpha-Lactalbumin Binding To Perfluorodecanoic Acid, Randhal Smith Ramirez Orozco

Open Access Theses & Dissertations

This thesis investigates the structural and thermodynamic interactions between Perfluorodecanoic acid (PFDA) and bovine alpha-lactalbumin (ALAC), a critical milk protein essential for infant nutrition. The primary objectives were to computationally determine the most probable binding sites of PFDA to ALAC and to quantify the strength of these interactions alongside the structural changes they induce. This study addresses a critical gap in understanding how persistent environmental contaminants like PFDA are recruited and transported by nutritional proteins within the milk matrix. The methodology integrated high-throughput molecular docking with long-range, molecular dynamics (MD) simulations to provide a dynamic characterization of the ALAC-PFDA complex. …

Penalty Approach To Constrained Optimization Problems In Water Reservoir And Energy Generation Management, Edwin Horacio Trejo

Open Access Theses & Dissertations

The growing demand for resilient and sustainable energy generation has driven interest in Hybrid Floating Photovoltaic-Hydropower (HFPVH) systems. Operating these systems effectively requires making water release decisions that satisfy physical and regulatory constraints while maximizing energy production. Prior work by Vega (2024) developed a Dynamic Outlier Filter Long Short-Term Memory (DOF-LSTM) architecture for forecasting reservoir release patterns. That predictive work is valid and addresses an important component of the HFPVH decision pipeline. However, the constraint system in that work operates externally to the learning process, and the behavior of penalty-based constraint enforcement had not been studied independently in this context. …

Soil Microbial Responses To Artifical Light At Night, Randall L. Walker

Open Access Theses & Dissertations

Global change, driven by both natural processes and human activities, has significantly transformed ecosystems. Urbanization and artificial light at night (ALAN) are key contributors, disrupting natural light cycles and influencing biological rhythms, biodiversity, and ecosystem functions. Thus far, there remains a gap in knowledge of how soil ecosystems are impacted by ALAN. This study uses a laboratory incubation to investigate the effects of ALAN on soil microbial communities and functions across urban and natural ecosystems. Briefly, soil was collected from eight sites around El Paso, Texas and neighboring New Mexico representing urban and rural light exposure. Soil was then subjected …

Stochastic Universal Differential Equations For Epidemiological Modeling: Uncertainty Quantification In Disease Transmission Dynamics, Alice Menaya Armah-Bonney

Electronic Theses and Dissertations

Epidemic forecasting requires not only predictions of expected case counts, but also quantification of uncertainty, although existing surrogate modeling frameworks for agent-based models remain fundamentally deterministic. In this thesis a Stochastic Universal Differential Equation framework is presented that extends the deterministic Universal Differential Equation approach by incorporating a learnable stochastic diffusion term, enabling calibrated probabilistic forecasts while preserving the mechanistic interpretability and computational efficiency of the deterministic baseline. In doing so, a two-phase training algorithm is introduced to ensure stable convergence and the framework is validated against the ensemble output from ExaEpi, an exascale agent-based model of a COVID-19 outbreak …

Mechanism Of Formation Of Guanine-Guanine Crosslinks As Products Of One-Electron Oxidation Of 1-Methylguanosine In Acidic Medium, Ibrahim Braimah Mr

Electronic Theses and Dissertations

Reactive oxygen species (ROS) from normal metabolism and environmental exposure may cause oxidative DNA damage. Guanine (G) is the most oxidizable nucleobase. One-electron oxidation (OEO) of G in produces guanine radical cation (G•⁺), which deprotonates to form guanyl radical G(-H)•.This radical exists in two tautomeric forms: G(N1-H)• and G(N2-H)•. Dimerization of guanyl radical yields G-G cross-links (D1/D2); a tautomeric form for dimer formation remains elusive. This study presents the first characterization of G• dimerization products from the OEO of 1-MeGuo in acidic medium. Photolysis at 470 nm in the presence of S₂O₈²⁻ and Ru(II)(bpy)₃²⁺ generates two major stereoisomers (D1AW* and …

Durable, Distributed Llm Inference On Cots Devices, Brycen E. Dunn

Electronic Theses and Dissertations

The advancement of Large Language Models (LLMs) has fundamentally changed the nature of natural language processing. The substantial memory requirements of frontier models creates a significant barrier to entry, centralizing inference. This thesis presents the design and implementation of a distributed inference framework designed to democratize LLMs by leveraging commodity devices. The framework combines the resources of heterogeneous COTS devices into a unified compute pool, enabling the inference of models exceeding a single device's memory capacity. A novel Task Partitioning Engine (TPE) analyzes model architectures, profiles node capabilities, and supports pipeline and expert parallelism strategies. The primary contribution is a …

On The Algebraicity Of The Tic-Tac-Toe Matroid And Homogeneous Mixed Bowtie Systems, Benjamin R. Allen

Electronic Theses and Dissertations

This thesis is presented in two parts. First, we explore whether the class of algebraic matroids is closed under duality, a decades-old open question. We consider the Tic-Tac-Toe matroid as a potential candidate to answer the open question. The Tic-Tac-Toe matroid is known to satisfy many of the necessary conditions for a matroid to be algebraic and has a non-algebraic dual.  Second, we focus on decompositions of the complete mixed graph into mixed bowties. A complete mixed graph has between every pair of vertices an undirected edge and antiparallel arcs. A mixed bowtie is a graph consisting of two 3-cycles …

Stability Of Paraffin-Insulated Nitrogen-Doped Carbon Fiber Ultramicroelectrodes, Maxwell H. Kwakwah

Electronic Theses and Dissertations

Nitrogen-doped carbon materials can facilitate the reduction oxygen-oxygen bonds, a key step in electroreduction of both O₂ (an important reaction in energy applications) and H₂O₂ (an important reaction in sensing and biosensing). Our lab previously demonstrated that thermal decomposition of urea in the presence of carbon fiber (CF) results in an N-doped carbon material that exhibits good electrocatalytic properties for H₂O₂ reduction. However, previous methods of insulating single N-doped CF via laser heating of borosilicate capillaries and epoxy to prepare ultramicroelectrodes (UMEs) seemed to adversely affect surface nitrogen contents and electrocatalytic properties. More recent work that utilized paraffin to …

Post-Vote Tampering In Nigerian Elections And The Role Of Blockchain-Enabled Electoral Systems, Ransome Chukwubuikem Enechukwu

Electronic Theses and Dissertations

Post-vote tampering during the collation and transmission of election results remains a persistent challenge in Nigerian elections, enabling manipulation of already-cast votes and weakening public trust in electoral outcomes. Existing technological interventions, including biometric voter accreditation and digital result transmission systems, improve voter authentication but do not adequately secure the post-vote result collation process. This thesis proposes a blockchain-enabled framework designed to protect the integrity of election results during the collation and transmission stages. Using a Design Science Research methodology, the study develops a permissioned blockchain framework based on Hyperledger Fabric that records polling-unit results as immutable ledger entries and …

Estimating Body Size And Biogeography In The Genus Alligator, Madelyn M. Turala

Electronic Theses and Dissertations

Several studies have examined correlations between total body length (TL) and skeletal measurements in the American alligator (Alligator mississippiensis), with some measurements serving as stronger predictors of TL than others. Femur length (FL) has been found to be tightly correlated with TL in A. mississippiensis, and this relationship has been used to estimate body size of extinct crocodilians. This thesis demonstrates that the humerus, radius, ulna, and tibia are also strongly correlated with TL and useful for body size estimation in A. mississippiensis, and thus, can be applied to related extinct crocodilians. Additionally, species distribution modeling …

Extreme Precipitation Events And Population Exposure: Site Recommendations For The Future Tennessee Mesonet, Victoria G. Redlund

Electronic Theses and Dissertations

This study examines frequency of and population exposure to extreme rainfall events in Tennessee to guide the placement of future mesonet weather stations. Using 1991-2021 daily nClimGrid precipitation records, extreme events were defined as events of rainfall ≥50 mm. These events were collated on an annual scale and normalized alongside square-root-scaled population densities derived from Landscan to develop extreme rainfall vulnerability maps. Results highlight where extreme rainfall is most frequent relative to population densities in each county. The findings were compared with models of mesonet suitability and feasibility to determine how meteorological needs correlate with siting needs such as land …

Adsorption Of Pfas On Bridged Functionalized Organosilica Materials, Elisha Lawerh Kabutey

Electronic Theses and Dissertations

PFAS are hazardous contaminants that have a devastating impact on human health and the environment. Their hazardous nature has led to the development of various adsorption methods for removing these contaminants from water sources. In this study, functionalized organosilica materials were synthesized from bis[3-(trimethoxysilyl)propyl] amine using the sol-gel method. The surface amino groups of the organosilica were converted into amine hydrochloride groups. Their adsorption properties were evaluated using salts of perfluorooctanoic acid, perfluorooctanesulfonic acid, and perfluorobutanesulfonic acid. Results showed excellent adsorption capacity of the materials. Adsorption of PFAS leads to particle agglomeration and flotation of the spent material. A column …

Ontogeny And The Effects Of Perinatal Stress In The First Immature Skeleton Of Teleoceras Aepysoma (Perissodactyla, Rhinocerotidae), Joe Gajewski

Electronic Theses and Dissertations

Recovery of an immature fossil rhinoceros (Teleoceras aepysoma) skeleton (ETMNH 32999) from the Gray Fossil Site in Tennessee offers the first insights into the ontogeny of the species. ETMNH 32999 is interpreted to be a subadult male in an age class equivalent to ~17-20% of potential lifespan. Comparative analyses support the hypothesis that subadults of related taxa are typically ~91% of average adult size in most dimensions. However, certain cranial dimensions are substantially lower than expected in ETMNH 32999, averaging only ~74% of the average conspecific adult. Such departure from typical growth rates is suggested to be attributable …

Utilizing Physics Informed Neural Networks For Disrupted Signal Dynamics, Nicholas J. Joyner

Electronic Theses and Dissertations

Physics-informed neural networks (PINNs) have been used in many applications including engineering and physical sciences. PINNs allow the incorporation of a priori understanding of a process’ structure into the modeling. We attempt to leverage the PINN structure toward the evaluation of disruptions to classical dynamical models by combining elements of ordinary differential equations into our loss function with sigmoidal gating to balance the penalties for deviations from the data with those for structural deviations. This enables the identification of the signal structure and the limits of disruption influence. As a use case, we consider stock value from 2019-2021, which expresses …

Discrete-Event Simulation: A Leslie System Model For Transportation Demography, Md Zobaer Ahammad

Electronic Theses and Dissertations

Transportation systems are influenced by demographic change, household formation,and patterns of vehicle ownership. These factors affect long-run transportation demand and congestion levels within urban infrastructure. Understanding how demographic dynamics interact with transportation behavior is therefore important for analyzing the long-term evolution of transportation systems. This thesis develops a modeling framework that integrates discrete-event simulation with a Leslie-type matrix model to study transportation–demography interactions.Simulation outputs are aggregated to construct a transition matrix describing changes in transportation states. This matrix acts as a linear (or affine) transformation on the transportation state vector, allowing the system to be analyzed as a discrete linear …

Machine-Learning Landslide Susceptibility And Runout Modeling In The Nolichucky River Gorge After Hurricane Helene, Grace Braver

Electronic Theses and Dissertations

Extreme rainfall from Hurricane Helene (September 2024) triggered widespread landslides across the southern Appalachian region, highlighting the need for rapid landslide susceptibility assessments that capture both landslide initiation and downstream runout. Traditional susceptibility models often focus solely on initiation zones, limiting their ability to identify which slopes will generate destructive landslides or where material will travel. This study addresses that gap by (1) integrating Geographic Information System (GIS)-based machine learning susceptibility modeling using ArcGIS Pro: Maximum Entropy (MaxEnt) and Random Forest-Based and Boosted Classification and Regression (FBBC) and (2) the U.S. Geological Survey (USGS) Grfin (Growth, Flow, and Inundation) runout …

Ai Institute Summer Camp Webinar Summary, Dora Nguyen

Paul English Applied Artificial Intelligence (AI) Institute Publications

This report summarizes the AI Institute Summer Camp informational webinar hosted by the Paul English Applied Artificial Intelligence Institute (PEAAII) at the University of Massachusetts Boston. The webinar introduced the structure, curriculum, learning objectives, and student outcomes associated with the 2026 AI Institute Summer Camp. In addition to summarizing the webinar content, this report analyzes participant questions, engagement trends, and areas of audience interest. Findings indicate strong interest in coding accessibility, mentorship opportunities, student outcomes, research experiences, and program flexibility. The report also identifies opportunities for improving future webinar delivery, including expanded eligibility guidance, pre-camp learning resources, enhanced presentation of …