Physical Sciences and Mathematics Commons^™

Artificial Intelligence And Translation: Exploring Current Applications, Limitations And Future Potential Of Language Models Through Japanese-English Translation, Loklin Elias Nord

Undergraduate Theses, Capstones, and Recitals

This thesis highlights the recent improvements and capabilities of Large Language Models (LLMs), specifically their ability to produce translations between different languages. The continued up-scaling of model sizes has led to breakthroughs in the level of their observed intelligence, allowing them to produce translations that are similar in quality to highly skilled human translators. However, to facilitate the reasoning processes that LLMs now possess, their demand for computational power and the supporting hardware and resources has increased proportionally. Considering the impacts of this technology on the environment, energy resources, and its accessibility, my research explores the possibilities of smaller, highly …

An Assessment Of Carbon Dioxide Removal Potential From Stormwater Ponds Using Concrete-Based Materials, Yu-Hsuan Tai

Theses and Dissertations (Comprehensive)

Stormwater ponds (SWPs) are engineered stormwater infrastructure known to be major greenhouse gas (GHG) emitters, including carbon dioxide (CO₂). Concrete-based materials have great potential to capture CO₂ as carbonate minerals (CaCO₃), through aqueous carbonation, driven by their alkaline nature and high portlandite (Ca(OH)₂) content. However, the mechanistic understanding of how specific parameters including mass, surface area, and degradation of calcium silicate hydrate (C-S-H) phases collectively control carbonation kinetics and CO₂ uptake under dynamically evolving conditions remains underexplored. Laboratory-scale experiments were conducted to evaluate the effects of cement dosage, particle surface area, and …

Time Series Mediation Analysis With Non-Linear And Machine Learning Methods, Timothy Marsh

Theses and Dissertations (Comprehensive)

Non-linearity in mediation analysis has been primarily studied in the context of binary variables which encode a treatment and control, estimating a `direct` and `indirect` effect of a covariate (a.k.a. treatment) X on a response Y, with a third variable M (the `mediator`) that is affected by X and in turn affects Y. The focus of mediation analysis in general is to quantify the overall effect of X on Y, including the effect through M. This presentation will focus on one or more continuous treatments and apply non-linear methods, including splines and machine learning models, to mediation analysis in a …

Likelihood-Based Inference For The Poisson–Tweedie Family, Si Chen

Theses and Dissertations (Comprehensive)

This thesis develops likelihood-based methodology for flexible modeling and inference for heterogeneous count data within and adjacent to the Poisson–Tweedie family. A mean–dispersion regression framework is introduced to jointly relate the mean and dispersion to covariates, enabling separation of covariate-driven heterogeneity from distributional parameters. Likelihood inference is implemented using recursive probability mass function evaluation, and performance is assessed through simulation and applications including RNA-sequence counts. The framework is extended to accommodate excess zeros via zero-inflated Poisson–Tweedie models, with full likelihood-based estimation and improved risk estimation illustrated using insurance claim data. Finally, boundary behaviour is investigated through the discrete stable distribution …

Robust Statistical Methods For Microbiome Abundance Data, Yiming Shi

WUSM Theses and Dissertations – All Programs

Differential abundance analysis in microbiome studies aims to identify taxa whose abundance differs across biological or clinical conditions. The observed data are typically taxon-specific sequencing read counts, representing reads assigned to different taxa within each sample. These counts are indirect measurements of the underlying microbial abundance profile and are constrained by sample-specific library sizes. Microbiome count data are also typically sparse, overdispersed, and heteroscedastic. Together, these characteristics create substantial challenges for differential abundance analysis and make the results highly sensitive to normalization procedures, model specification, and the statistical methods used for inference.

Normalization defines the scale on which samples are …

Enhancing Agricultural Sustainability Under Climate Change: A Multi-Scale Framework Integrating Climate Extremes, Resource Efficiency, And Data-Driven Modeling, Shahryar Fazli

Computational and Data Sciences (PhD) Dissertations

Agricultural systems are increasingly challenged by climate variability, where shifting temperature regimes, hydrological variability, and the rising frequency of compound and cascading extremes threaten global food security and resource sustainability. Addressing these challenges requires integrated frameworks that bridge biophysical monitoring, predictive modeling, and adaptive decision-making. This dissertation develops a data-driven, multi-scale framework to quantify and enhance agricultural resilience by integrating remote sensing, climate analytics, and machine learning across the United States, with a focus on California and the Western U.S.

First, hyperspectral and thermal remote sensing data from EMIT and OpenET are integrated to characterize crop nitrogen–water interactions and assess …

Wildfire And Fuel Treatments In Utah: A Practical Guide And Outcomes From An Oak-Maple Ecosystem, Annie E. Prescott

All Graduate Theses and Dissertations, Fall 2023 to Present

Wildfire is a natural part of Utah’s landscapes, but as wildfires become more extreme and communities continue to expand into wildland areas, it is increasingly important to understand how wildfires behave and how their negative effects can be mitigated. One way to reduce wildfire risks and protect life, property, and ecosystem services is through fuel treatments — actions that reduce the amount and arrangement of flammable vegetation through mechanical removal, wildland fire, or other methods.

Information on wildfire behavior and fuel treatments is abundant but often scattered, ecosystem-specific and difficult to access. In addition, most research in the Western U.S. …

Toward Optimizing Fruit Production In Utah Soils: Apple Salt Tolerance Screening And Tart Cherry Fertility Management, Kaitlin Dabbs

All Graduate Theses and Dissertations, Fall 2023 to Present

Fruit production in Utah can be challenging due to local climate and soil conditions. Tart cherries and apples are major fruit crops in Utah, and improvements to these cropping systems would be beneficial for farmers and local consumers. Two experiments were conducted to evaluate desired improvements for these crops. The first study looked for salt tolerance in ten new apple rootstocks. Salty soils can be found throughout the state limiting the land suitable for apple production. When grown in salty soils apple trees often have reduced growth and production potential. A specialized drip irrigation system was constructed in a greenhouse …

Quasi-Poisson Analogs Of Regular Poisson Varieties, Casen Thompson

All Graduate Theses and Dissertations, Fall 2023 to Present

Let G be a complex semisimple linear algebraic group with 𝐶 a conjugacy class of parabolic subgroups of G. In previous work, Dr. Crooks defines 𝑢_𝐶→ B_𝐶 , a universal flat family of a fine Hamiltonian Lagrangian G-bundles over 𝐶, and shows that 𝑢_𝐶 is a family of regular Poisson varieties. This manuscript introduces a natural candidate for a quasi-Poisson analog of Dr. Crooks’s construction, 𝑢_𝐶, using the framework of quasi-Poisson geometry established by Alekseev, Kosmann-Scwarzbach, and Meinrenken. It will be shown that this proposed quasi-Poisson analog indeed has a valid quasi-Poisson structure and …

Machine Learning-Based Regression For Magnetic Field Prediction From Odmr Spectral Data, Jesse B. Hernandez

Electronic Theses, Projects, and Dissertations

Optically Detected Magnetic Resonance (ODMR) using nitrogen-vacancy (NV) centers in diamond enables sensitive, room-temperature magnetic field sensing, but real ODMR spectra are often noisy and difficult to analyze with traditional peak-fitting methods. This thesis investigates whether machine learning can reliably predict magnetic field strength directly from ODMR spectra, and compares four model families under a single regression task: a random forest, an artificial neural network (ANN), a one-dimensional convolutional neural network (1D-CNN), and a Transformer.

Training data were generated from an NV-ensemble simulation calibrated to real measurements provided by the Ulsan National Institute of Science and Technology (UNIST), spanning 0 …

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

Theses and Dissertations

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

Computational Studies Of Triplet State Formation In Zinc Dipyrrin Complexes, Reuben Kwabla Adigbli

Electronic Theses and Dissertations

Zinc dipyrromethene complexes are promising earth-abundant photosensitizers due to their strong visible-light absorption and tunable excited states. To rationally design them for photocatalysis and photodynamic therapy, a molecular-level understanding of triplet-state formation is needed, but details of intersystem crossing remain unclear. To study the effect of π-extension, we synthesized an indole-substituted zinc dipyrrin complex: the dipyrromethane ligand was prepared from indole and mesitaldehyde, oxidized to the dipyrromethene, then coordinated with zinc. DFT and TD-DFT calculations determined ground and excited-state geometries and energies in different solvents, modeled absorption spectra, and visualized charge distributions. The results show how solvent polarity shifts energies …

Stimuli-Responsive Proton Transfer: Photoacid Design, Co2 Sorbent Regeneration, And Polymer Applications, Melyse Ava Laud

Theses and Dissertations

Control over proton transfer enables the regulation of many pH-dependent chemical and material processes. Stimuli-responsive functional materials provide a means of achieving this control. Functional materials such as Metastable-state photoacids (mPAHs) reversibly release large amounts of protons when stimulated by light from a weakly acidic site within their structure. However, the dark acidities of previously reported mPAHs limit their use under basic conditions. To address this limitation, a benzimidazole-type mPAH was developed with an improved ground-state pKa of 11.9 and a metastable-state pKa of 9.8, enabling reversible proton transfer under mildly basic conditions. Additional mPAHs were examined to determine how …

Study Of Fast Switching Metastable-State Photoacids And Controlled Drug Release From Polycaprolactone (Pcl) Vascular Scaffold, Rana Salman Abbood Abbood

Theses and Dissertations

Metastable-state photoacid (mPAH) has become a common tool for controlling and driving chemical processes with light. mPAHs with fast reverse reactions are desirable for precise temporal control or generating quick pulses of proton concentration. In this work, different approaches towards fast reversing mPAHs are studied. Experimental and computational results showed that stabilizing the charge–transfer intermediate is an effective way to increase the rate. A novel mPAH with a reverse reaction ≈500 times faster than the most widely used mPAH in methanol has been developed. Another water-soluble mPAH exhibited a reverse reaction with a rate constant of 7.8 s−1, the fastest …

Noise Characterization And Mitigation In Intermediate-Scale Quantum Systems, Muhammad Qasim Khan

Dartmouth College Ph.D Dissertations

Current quantum processors, at the intermediate scale of tens to hundreds of qubits, remain error-limited. This thesis studies two related sources of error. The first is environmental noise, which may have temporal and spatial correlations and nonclassical components. The second is state-preparation and measurement (SPAM) error, which arises in the operations used to characterize this noise, a prerequisite for boosting operational fidelities. Neither can be characterized alone. Noise spectroscopy techniques use imperfect preparation and readout, while SPAM characterization is affected by qubit decoherence. Our methods vary measurement depth, drive duration, or sequence repetition so each source changes the measured signal …

Powers' Conjecture On The Third Largest Eigenvalue Of A Graph, Kevin Schmidt

Master's Theses

In 1989, David Powers conjectured that for any connected graph G on n vertices, the k-th largest eigenvalue of the adjacency matrix satisfies λk(G) ≤ ⌊n/k⌋ for every 1 ≤ k ≤ n/2. The conjecture has since been resolved case by case, in the sharper form λk(G) ≤ n/k − 1: the case k = 1 is classical, k = 2 was settled independently by Hong and by Powers in 1988, and k ≥ 4 was shown to fail by Nikiforov and Linz. This thesis surveys the resolution of the remaining case, k = 3, achieved in March 2026 by …

Factors Influencing Non-Perennial Stream Initiation In The Mt. Hood National Forest, Allison Bast

Dissertations and Theses

Historically, non-perennial headwater streams have been overlooked due to their small size and infrequent flow regimes, often leading to them not being recognized as legitimate streams, despite scientific evidence that has shown these streams significantly affect the quality of downstream waters. To combat this issue, environmental managers need to be able to accurately identify and delineate the origins of these streams; however, despite decades of research, an accurate, universal method for predicting how and where these streams commence has yet to be developed. Early studies conducted in steep, humid environments, identified a strong inverse linear relationship between the size of …

Knowledge-Enhanced Feature Store For Operational Ml And Llm Workflows, Saurabh Suman

Master's Theses

Modern machine learning (ML) organizations rely on feature stores to manage training and production data, yet as catalogs grow to thousands of features, semantic management becomes the bottleneck: discovery, governance, and metric selection remain largely manual. This thesis proposes and evaluates a knowledge-enhanced feature store that augments a dual-plane store with a hybrid knowledge layer—relational provenance, a lineage graph, semantic vector retrieval, and an online cache—and an LLM-driven multi-agent layer for profiling, matching, grounded metric recommendation, and pipeline generation. A working prototype was evaluated across three task families—semantic profiling, feature-matching retrieval, and discovery—using classification, ranking, and operational metrics computed by …

A Study On Some Distance Based Domination Parameters In Graphs And Their Applications, Shanmugavelan S Mr

Theses and Dissertations

Distance-based domination has emerged as a significant development in graph theory, attributed to its applications in communication systems, interconnection networks, parallel architectures, and chemical graph models. This thesis focuses on two such graph invariants: hop domination number and 2-hop domination number of graphs. The hop domination number of some generalized graph structures like generalized thorn paths, generalized theta graphs, and snake graph families is studied along with a newly introduced family, namely generalized ciliates.

Moreover, a variant of hop domination number, namely, the 2-hop domination number, is studied for some grid families like ladder, hexagonal grid, and its variants. Furthermore, …

Portrait: Holistic Data Visualization Using Neural Networks, Chayan Maitra

Doctoral Theses

With the exponential growth of complex data across domains, effective visualization has become increasingly crucial for understanding relationships hidden within high-dimensional spaces. However, existing visualization techniques often struggle to effectively capture and represent such high-dimensional data. Motivated by this challenge, we have developed NeuroDAVIS, a neural network model designed to visualize high-dimensional data by extracting meaningful latent representations through deep feature extraction. While NeuroDAVIS has successfully addressed the visualization aspect, we have soon recognized the necessity of identifying the most relevant features that contribute to the visualization and downstream analysis. To address this issue, we have extended our framework and …

Relationship Between Aleks Use, Implementation Models, And Grade 9 Students’ Achievement On Algebra 1 Summative Assessments, Deneen Alfordburke

Walden Dissertations and Doctoral Studies

The problem that was addressed through this study was Grade 9 students’ achievement on the Algebra 1 New Jersey Student Learning Assessment (NJSLA) continued to be below the proficiency level that is defined by the state, despite implementation of Assessment and Learning in Knowledge Spaces (ALEKS) Algebra 1 software. The study was grounded in Doignon and Falmagne’s knowledge space theory (KST) which evaluates students’ current knowledge levels and guides them along individualized learning paths based on what they are ready to learn next. The purpose of this nonexperimental quantitative study was to determine whether the predictor variables Grade 9 students’ …

Representing Post-Fire Reality: An Empirically Informed Temperature Index Approach To Post-Fire Hydrologic Modeling In Oregon's Western Cascades, Logan Hastings

Dissertations and Theses

The invaluable water resources stored in snowpack face mounting threats from rising temperatures, drought, shifts in precipitation regimes, and increased fire frequency, which pose challenges to operational hydrologic modeling in Oregon's sensitive maritime snowpacks. The gridded temperature index (GTI) approach in operational models like the Hydrological Engineering Center's Hydrologic Modeling System (HEC-HMS) from the U.S. Army Corps of Engineers remains in common use for its minimal data requirements, but how GTI parameterizations should adapt to post-fire conditions is largely unknown.

This research assessed the impact of the 2020 Lionshead Fire on HEC-HMS performance in the North Santiam River basin across …

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

Theses and Dissertations

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

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

Theses and Dissertations

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

Quantitative Analysis Of Blue 1 Dye In Commercial Sports Drinks By Uv -Vis Spectroscopy And Hplc-Dad, Mikayla Bush

Forensic Science Master's Projects

Food dyes are natural or synthetic substances added to foods, beverages, and cosmetics to enhance color and visual appeal. Although they provide no nutritional value, they are widely used to attract consumers, particularly children. Concerns have been raised about the potential health effects of synthetic dyes, including links to hyperactivity in children, tumor formation at high doses, and possible impacts on gut and brain function. In response, regulatory efforts are ongoing. In April 2025, the U.S. Department of Health and Human Services (HHS) and the Food and Drug Administration (FDA) announced an initiative to phase out petroleum-based food dyes, including …

Methodological Optimization Of Microplastic Visualization For The Comparison Of Eastern Oysters Cultivated In Traditional Plastic Or Novel Non-Plastic Aquaculture Farm Gear, Mikayla Straube

All Theses And Dissertations

Microplastics (< 5 mm) are a pervasive physical pollutant. This study was predominately focused on the development and utilization of fluorescence microscopy to locate and identify microplastics and other particles in the presence of a background autofluorescing biogenic precipitate. Oyster digest samples are visualized with fluorescent microscopy using Nile Red (NR). Photobleaching, or concentrated light exposure, of the filters was tested to determine if it can quench the autofluorescence signal. It was found that photobleaching significantly decreased autofluorescence intensity of the biogenic precipitate in emission wavelengths 518, 580, and 670 nm even with the application of NR, while minimally impacting the fluorescence behavior when bound to plastic particles. In application, fluorescence microscopy still yields some gaps in microplastic identification  when compared to Raman spectral results. This methodology was broadly developed to be able to quantify ambient microplastic quantities in farmed oyster samples. The specific level of aquaculture’s contribution to plastic pollution in global waterways is difficult to estimate. The methodology was applied to a local case study that compared microplastic loading in cultured eastern oysters raised in traditional plastic farm gear and novel plastic-free farm gear. Marginal trends in the gear type treatment and microparticles identified across the harvest season were identified, however effect sizes were too weak, and evidence was too inconsistent to currently suggest that gear type and harvest date affect microplastics and other particle quantities g^-1 oyster tissue (d.w.).

Catalytic Synthesis Of Protoberberine Alkaloids And Their Evaluation As Selective Dopamine Receptor Ligands, Ashok Reddy Gudipally

Dissertations, Theses, and Capstone Projects

Dopamine regulates motor control, cognition, reward, motivation, and neuroendocrine signaling. Disruption of dopaminergic neurotransmission is closely linked to central nervous system disorders, including Parkinson’s disease, schizophrenia, addiction, and related neuropsychiatric conditions. Because these functions are mediated by multiple dopamine receptor subtypes with distinct roles in physiology and disease, the discovery of subtype-selective ligands remains an important goal in neuropharmacology. Within this context, protoberberine alkaloids, particularly tetrahydroprotoberberines (THPBs), are attractive molecular frameworks because they combine structural complexity with broad biological relevance, including measurable activity in CNS-related diseases. Prior work from our laboratory and others established (–)-stepholidine (1.60) as an important lead …

Bridging Data Gaps In Retinal Imaging: From Structural Domain Adaptation To Topology-Aware Synthesis, Gözde Merve Demirci

Dissertations, Theses, and Capstone Projects

Comprehensive visualization of the retina is essential for diagnosing and monitoring blinding diseases such as Diabetic Retinopathy and Retinopathy of Prematurity (ROP), where pathological changes often extend beyond a single field of view. Despite significant advances in automated retinal image analysis, clinical deployment remains limited by two fundamental data gaps: a structural learning gap, arising from scarce expert annotations and poor generalization across imaging domains, and a spatial coverage gap, caused by the difficulty of acquiring multi-view retinal images in fragile populations. Although these challenges are often addressed independently, this dissertation argues that they are tightly coupled: accurate, …

Potential Energy Landscape Formalism For Quantum Liquids, Yang Zhou

Dissertations, Theses, and Capstone Projects

Atomic delocalization due to nuclear quantum effects (NQE) remains poorly understood in low-temperature liquids near the glass state and during vitrification. Many liquids can be described accurately by treating their nuclei as classical particles, but this approximation fails for light elements such as He and H₂, small hydrogen-containing molecules such as water, and systems in which zero-point motion or isotope-substitution effects are important. Developing a general thermodynamic and statistical-mechanical description of such liquids has been challenging. This dissertation extends the potential energy landscape (PEL) formalism, originally developed for classical liquids and glasses, to liquids that obey quantum mechanics and exhibit …

Mapping The Water Quality Of Jamaica Bay, New York (1996-2024): Principal Component Analysis And K-Means Clustering, Sneha Srivastava

Dissertations, Theses, and Capstone Projects

Jamaica Bay, located along the southeastern coast of New York City, acts as a biodiverse estuary of wetlands, meadows, and salt marsh islands. The purpose of this study is to analyze the water quality conditions of the region over time, comparing locations around the bay to identify hyperlocal features that influence larger trends in the hydrological system. Ten variables were used as water quality indicators, including total Kjeldahl nitrogen, salinity, pH, Secchi disk depth, and total phosphorus, among others, across five stations in the bay, between 1994 and 2024. After data cleaning and standardization methods were applied, principal component analysis …