Physical Sciences and Mathematics Commons^™

Physics Oriented Deep Learning For Material Prediction And Generation, Nihang Fu

Theses and Dissertations

The discovery of new materials is critical to advancing various industries, but traditional experimental methods for materials discovery remain slow and resource-intensive. Recent advances in machine learning (ML), particularly deep learning (DL), have greatly improved and accelerated two main aspects of modern computational material discovery: material design (e.g., material generation) and material screening (e.g., property prediction). However, a key challenge remains: standard ML models often struggle to perform domain-specific tasks effectively. Incorporating domain-specific knowledge, specifically the underlying physics of materials, into ML/DL models is key to improving the accuracy and reliability of material generation and prediction models.

This dissertation discusses …

In Vivo Analysis Of Fe-S Cluster Assembly And Iron Homeostasis In Escherichia Coli, Dexter Mclaurin Reasons

Theses and Dissertations

Iron-sulfur (Fe-S) clusters are an essential cofactor for a wide range of cellular processes, and their assembly and storage require tight regulation.

In Escherichia coli (E. coli), there are two pathways of Fe-S cluster assembly, the Isc and the Suf pathways. The Isc pathway is used under good growth conditions, and the Suf pathway is used under iron starvation and oxidative stress conditions. Once the cluster has been assembled on the scaffold protein of either pathway, it is transferred to Fe-S cluster trafficking proteins. In E. coli, the monothiol glutaredoxin GrxD and the BolA-type proteins BolA and IbaG …

Explainable Process Recommendation Through Multi-Contextual Grounding Of Dynamic Multimodal Process Knowledge Graphs, Revathy Venkataramanan

Theses and Dissertations

Can I eat this food or not? Is this food suitable for diabetes and why? Which AI pipeline is best suited for a given task and dataset? How should an end-to-end pipeline be constructed? These questions differ from factual question-answering tasks. Recipes and AI pipelines are processes consisting of several entities interacting with each other. A recipe consists of ingredients, cooking methods, and their interactions, while an AI pipeline includes datasets, preprocessing techniques, models, hyperparameters, tasks, and results. Each entity must be analyzed individually, and collective inferencing is performed to derive the final decision. This decision-making process, known as compositional …

Sequential Data Modeling Of Influenza A Via Traditional, Dwt-Gpr Hybrid, And Deep Learning Architectures, Edmund Fosu Agyemang

Theses and Dissertations

Influenza A is responsible for 290,000 to 650,000 respiratory deaths a year, though this estimate is an improvement from years past due to improved sanitation, healthcare practices, and vaccination programs. In this study, we perform a comparative analysis of traditional, deep-learning and discrete wavelet (DWT)-Gaussian Process (GP) hybrid models to predict Influenza A outbreaks. Using historical data from January 2009 to December 2023, we compared the performance of traditional ARIMA and ETS models, four variants of DWT-GPR models and six distinct deep learning architectures: Simple RNN, LSTM, GRU, BiLSTM, BiGRU and Transformer. The results reveal a clear superiority of all …

Directivity And Sound Radiation Of Percussion Instruments And Harmonic Analysis Of The Alto Saxophone, Hanna Michelle Pavill

Theses and Dissertations

This thesis investigates how musical instruments radiate sound, with a focus on directional behavior under realistic performance conditions. High-resolution measurements using a rotating microphone array were used to study percussion and woodwind instruments, providing new insight into how design, excitation, and frequency content shape acoustic output. The first set of experiments analyzed the directivity of the bass drum, triangle, and open snare. Each instrument exhibited unique radiation patterns reflecting its structure and playing method. The bass drum showed dipole-like behavior at low frequencies, transitioning to omnidirectional spreading at mid frequencies, and increasingly irregular patterns at higher frequencies. The triangle, due …

Martingale Methods For Structural Change Detection And Feature Attribution In Dynamic Networks, Izhar Ali

Theses and Dissertations

Dynamic networks undergo structural changes when their generative process shifts at a change-point. We need to detect this change-point with minimal delay while identifying its underlying causes. This is an optimization problem of minimizing the expected detection delay while controlling the false alarm probability below a threshold---leading to three critical challenges: non-parametric detection without distributional assumptions, exact feature attribution, and early detection with rigorous false alarm control. We construct additive martingale statistics from multiple graph features using conformal prediction, providing false alarm guarantees via Ville's inequality. Our key theoretical contribution proves the Martingale-Shapley equivalence: each feature's martingale value equals its …

Low Surface Brightness Features Of Edge-On Galaxies In Deep Sky Surveys, Kyle R. Adams

Theses and Dissertations

In this thesis, we present a comprehensive visual analysis of low surface brightness (LSB) structures in edge-on galaxies using two statistically complete samples: 838 galaxies from the SDSS Stripe 82 region (ES82) and 5,745 galaxies from the Edge-on Galaxies in SDSS (EGIS) catalog, both containing galaxies with spectroscopic redshifts out to 𝑧 ∼ 0.2. Using deep imaging data from the SDSS, SDSS Stripe 82, DESI Legacy Imaging Surveys, and the HSC-SSP, we construct RGB and coadded images for comparison and to improve feature detection. Average limiting photometric depth for each survey in the 𝑟 band for the surveys analyzed in …

Applying Ceragenins In Translational Medicine: Activating Mesenchymal Stem Cells And Preventing Healthcare-Associated Infections, Aaron L. Zaugg

Theses and Dissertations

Healthcare-associated infections are a major global concern. Increased infections among vulnerable populations lead to millions of deaths, annually, complicated by the emergence of multi-drug resistant pathogens. These infections are often facilitated by medical devices serving as abiotic surfaces that facilitate the formation of biofilms. Notably, colonization of prostheses and other bone-associated medical devices can lead to corrective procedures, revisions and death. To address these issues, inspiration can be drawn from natural sources of bone health and defenses against infection. Cathelicidins are endogenous peptides involved in both bone maintenance and infection control. Ceragenins are small molecule mimics of cathelicidins with broad …

Linking Static And Dynamic Structures And Properties Of Materials With Computational And Mathematical Models, (Enoch) Sin Hang Ho

Theses and Dissertations

Terahertz (THz) spectroscopy is an effective technique to study and manipulate the structural dynamics of materials, due to its frequency range being very similar to the vibrational frequencies of collective atom motions in a host of materials. High-field and broadband THz radiation can be generated via optical rectification (OR) in nonlinear optical (NLO) crystals. The efficiency of OR response in an NLO crystal is determined by many factors, including molecular hyperpolarizability (β), 2nd order electric susceptibility (χ(2)), crystal structure, primary growth orientation, refractive index, absorption and phase matching condition. In this dissertation, I will focus on using computation methods and …

The Cellular Mechanisms Of Alzheimer's Disease Protection By The Pilra G78r Variant, Wenhan Cheng

Theses and Dissertations

Microglial dysfunction is increasingly linked to Alzheimer’s Disease (AD). Immune receptors like TREM2 and CD33 play opposing roles in microglial activity. TREM2 activation triggers immunoreceptor tyrosine-based activation motif (ITAM) signaling to promote microglial activities, including amyloid-β clearance, but variants in TREM2 such as R47H that impair its function increase AD risk. In contrast, CD33 is an inhibitory receptor that contains an immunoreceptor tyrosine-based inhibitory motif (ITIM) which transmits signals that suppress microglial function. An AD-protective variant in CD33 alters CD33 activity, potentially enhancing TREM2 function. PILRA is another inhibitory immune receptor expressed by microglia that contains an ITIM. A naturally …

Quantum-Chemical Modeling Of Mechanisms And Selectivity In Open-Shell Organometallic Reactions, Michael T. Davenport

Theses and Dissertations

Quantum mechanical calculations have emerged as a powerful approach for directly evaluating reaction mechanisms and selectivity in transition metal-ligand complexes involving organometallic intermediates. Density functional theory (DFT) quantum mechanical methods enable the generation of potential energy surfaces and structures that define reaction mechanisms and allow for the evaluation of selectivity through statistical transition state theory. However, in certain cases, it is necessary to go beyond statistical treatments and incorporate atomic motion through molecular dynamics simulations. Additionally, many transition metal-mediated reactions involve unpaired electrons and spin state crossings. This dissertation focuses on the application of DFT-derived potential energy surfaces and molecular …

Hierarchy Viz: A Visual Analytics Framework For Visualizing Hierarchical Data Using Machine Learning, Vinay Kumar Uppalapati

Theses and Dissertations

Automated visualization systems aim to generate visualizations directly from raw data with minimal user inputs. However, while existing systems focus on data visualizations mainly using line charts and scatter plots to explore the data patterns, they struggle with hierarchical data representation where data relationship is essential. Hierarchical visualization, crucial for understanding multi-level relationships, typically requires users to manually define hierarchies and have expertise in visualization tools to create meaningful representations. This makes the process complex, time-consuming, and reliant on domain knowledge. To address this, we propose HierarchyViz, an automated system that detects multiple hierarchies in raw datasets and generates intuitive …

Deep Neural Networks For Particle Identification In Simulated Proton-Proton Collisions At Lhc And Rhic, Omar Mazhar Khalaf

Theses and Dissertations

Particle identification is an essential part of experimental high-energy physics, which allows the study of the most fundamental constituents of matter. This thesis explores the use of deep neural networks for identifying particles in simulated proton-proton collisions at the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC). The deep neural networks were trained on LHC datasets which have various momentum ranges including regions of high transverse momentum above 3 GeV/c. The key findings of thesis include achieving an accuracy of 99.99%, 98.3%, and 90.14% for 3-5 pt, 5-7 pt and above 7 pt regions respectively for the …

Structural Analysis Of The Aileu Metamorphic Complex And The Laclo Fault Of Timor Leste, Banda Arc-Continent Collision, Emma C. Morrison

Theses and Dissertations

This study presents a structural analysis of the brittle and ductile features within the Aileu Metamorphic Complex of Timor Leste, located in the active Banda Arc–Australian continental collision zone. The deformation history of the complex is interpreted from the Permian–Jurassic deposition of sediments and basalts into intra-arc basins of Gondwana, through to the present- day collision of the Australian continental margin. This collision led to the development of the Wetar Suture and subsequent back-thrusting of the Aileu metamorphic rocks northward over the Banda forearc. Field evidence confirms that the Laclo Fault is currently active, with the most recent movement exhibiting …

How Transitioning Autistic Adults Consciously Perform Neurotypical Communication, Makenna J. Allred

Theses and Dissertations

Using semi-structured interviews this research explored the experiences of transitioning autistic adults with online communication. Participants shared information about navigating online communication, highlighting specific challenges such as interpreting tone and sarcasm, managing unspoken social norms, like emoji use, and responding to ambiguous or unexpected interactions. Participants shared that misunderstandings do occur in their online communication and how they recognize those miscommunications and strategize around preventing and mitigating them. These findings reveal that while computer-mediated communication offers opportunities for connection, it also presents unique obstacles that can exacerbate feelings of frustration due to miscommunications or misunderstandings. To prevent these social frictions …

Semitic Root Encoding: Tokenization Based On The Templatic Morphology Of Semitic Languages In Nmt, Brendan T. Hatch

Theses and Dissertations

The morphological structure of Semitic languages like Arabic and Hebrew is based on non-concatenative roots and templates. This complex word structure used by humans is obscured to neural models that use traditional tokenization algorithms. In this work, I present and evaluate Semitic Root Encoding (SRE), a tokenization method that represents Semitic words with distinct root and template stem tokens, and apply it to neural machine translation (NMT). I evaluate whether tokenization with the SRE method leads to increases in translation quality, whether it allows NMT models to hypothesize unseen word forms needed at inference, and how impervious resulting NMT models …

Building And Demonstrating A Framework And Guide For Human-Centered Threat Modeling, Warda Usman

Theses and Dissertations

As researchers increasingly seek to understand threats faced by people rather than systems, there remains little consensus on how to study these threats in ways that are grounded in human experience. Traditional approaches to threat modeling are often designed for system vulnerabilities and offer limited guidance for eliciting or analyzing threats as understood by individuals in their social and cultural contexts. This dissertation addresses this gap by advancing human-centered threat modeling (HCTM) in security and privacy research as both a conceptual framework and through a set of empirical studies. The dissertation employs a mixed set of qualitative methods across four …

Incorporating Propensity Score Weighting And Nonresposne Adjustments Into Complex Survey Data With Survival Outcomes, Xinrui Shi

Theses and Dissertations

Propensity score weighting (PSW) plays a key role in minimizing confounding in observational research, especially when estimating treatment effects for time-to-event outcomes. However, its integration into survey data with complex design – particularly data with multiple stage sampling and censoring – remains underexplored. One significant challenge in such settings is the presence of nonresponse, which can introduce additional bias and complicate the use of standard weight adjustments. Moreover, there has been limited study on how PS weights can be effectively combined with nonresponse weighting adjustments in complex survey data that include survival outcomes. This dissertation aims to extend current methodologies …

Efficient Signal Synthesis For Data Augmentation Using Generative Ai, Yagna Veera Narayan Kaasaragadda

Theses and Dissertations

Modern signal processing AI applications face increasing demands for diverse training data while operating under computational constraints. State-of-the-art generative models, though effective, often require prohibitive resources, limiting their deployment in real-time or embedded systems. This thesis proposes a computationally efficient framework for synthetic signal generation using a two-stage architecture that combines a Vector Quantized Variational Autoencoder (VQ-VAE) with either a decoder-only transformer or a discrete diffusion model. The VQ-VAE encodes high-dimensional signals into discrete latent tokens, significantly reducing model complexity while enabling symbolic sequence modeling. These discrete representations are then modeled using transformer-based autoregressive models or Score Entropy Discrete Diffusion …

Advances In And Applications Of Capillary Scale Liquid Chromatography, Samuel William Foster

Theses and Dissertations

Analytical-scale high performance liquid chromatography (HPLC) is one of the most widely used analytical techniques in the world. Efforts have been made to reduce the mobile phase consumption of HPLC by reducing the inner diameter (I.D.) of the column. By using capillary-scale columns (< 0.5 mm I.D.), separations can be performed with orders of magnitude less solvent consumption. This work describes advances made to capillary scale instrumentation as well as applications enabled by these advances. A compact capillary-scale LC was used for the analysis of numerous pharmaceutical and illicit drug compounds for point of need analysis. A miniaturized mass spectrometer was coupled to this instrument for on-line reaction monitoring within a standard chemical fume hood. Kinetic profiles of commercially available capillary columns were developed in order to provide guidance to others during column selection. The implementation of a column oven improved the analysis of large biopharmaceuticals. Several critical quality attributes of monoclonal antibodies including fragmentation, charge variants, and glycosylation profiles were able to be determined on the capillary scale. These results will help to make capillary-scale liquid chromatography a more viable solution for chromatographic analysis.

From Lists To Infinite Scroll: A Comparative Analysis Of Youtube’S Two Recommendation Algorithms, Selimhan Dagtas

Theses and Dissertations

As social media platforms increasingly dominate information consumption, the role of recommendation algorithms in determining user experience has grown both in complexity and impact. This thesis investigates the behavioral patterns and algorithmic preferences embedded within YouTube’s recommendation systems, comparing long- form videos with the rapidly growing category of short-form content, YouTube Shorts. Through a combination of automated data collection, engagement metric analysis, emotional sentiment detection, and toxicity assessment, this study analyzes the evolution of content over successive recommendation depths. Using a controlled digital environment, the research explores how content recommendations change in response to user behavior, including varying watch times …

Equiangularity From Compatible Orthobiangularity, Tyler J. Myers

Theses and Dissertations

An equiangular tight frame (ETF) is an equal norm sequence of vectors in a Hilbert space whose coherence achieves equality in the Welch bound. Such sequences necessarily have minimal coherence and thus are, in some sense, as "spread out" in space as possible. ETFs have a variety of applications, such as compressed sensing and waveform design. The main problem in the study of ETFs is determining the pairs (D, N) for which an ETF with N vectors in a D-dimensional space exists. Real ETFs are moreover equivalent to a special subset of a well-studied class of graphs known as strongly …

Constraining Nuclear Data Uncertainty Requirements For The 19F(A, N)22Na Reaction For Non-Proliferation Applications, Tyler R. M. Smith

Theses and Dissertations

This thesis explores the requirements on nuclear data uncertainties needed for the use of the ¹⁹F(α, n)²²Na reaction for nuclear non-proliferation applications. An overview of how neutrons are produced from alpha decays in a UF₆ medium is discussed. Calculation demonstrate the role nuclear data uncertainties effect the neutron yield and energy spectra as a function of enrichment.

Rotating Scatter Mask System Optimization Study For Determining Optimal Image Recreation, Seth L. Grover

Theses and Dissertations

The Rotating Scatter Mask (RSM) system is a radiation imaging technology currently limited by the mask design and governing identification algorithm parameters. To optimize the RSM design, Dakota—an optimization software—was integrated with a ray tracing code that simulates particle interactions with the RSM detector, and with the Locally Competitive Algorithm (LCA), which reconstructs the source image based on the ray tracing code’s Detector Response Matrix (DRM). Since the original ray tracing code was developed in MATLAB, it was translated into Python to improve compatibility with both Dakota and LCA. The Python version of the ray tracing code was then integrated …

Contract Quality Feature Extraction Using Llm, Aaron C. Washington

Theses and Dissertations

This study explored the potential insights generated from linguistic complexity measurements and large language model (LLM) based assessments on the quality of contract documents. By combining structured True/False prompts with log-probability analysis and ambiguity scoring, the study introduced novel contract-quality assessment methods. Results support a feature-driven approach to contract evaluation, one that offers automated, scalable insights for triaging risk and improving drafting practices. These assessment methods contribute to the growing field of legal natural language processing by offering modular tools for effective contract analysis.

Fused-Silica Microelectromechanical Systems For Relative Gravimetry, Ethan Doerstling

Theses and Dissertations

Gravimeters are devices that measure gravitational acceleration which can be used by the United States Air Force (USAF) in the areas of navigation and remote sensing. Fused-silica microelectromechanical systems (MEMS) devices offer capabilities to make inexpensive relative gravimeters with higher thermal stability than common silicon devices while maintaining good gravitational sensitivity. The fused-silica devices in this research were designed, simulated, fabricated, and tested to observe their performance as gravimeters. The devices exhibit properties of highly sensitive accelerometers but the current designs do not qualify as gravimeters. This study provides information to improve the sensitivity and stability of these fused-silica MEMS …

Calculating Moment Magnitude Using The Coda Calibration Technique To Update The Earthquake Catalog Of Iraq (1900-2021), Muntadher Al-Kaabi

Theses and Dissertations

The first comprehensive earthquake catalog for Iraq based on moment magnitude (Mw) ‎was compiled by Onur et al. (2017). It spanned the period from 1900 until the end of ‎‎2009, covered the region between 26°–40° N latitudes and 36°–51° E longitudes, and ‎included more than 18,000 earthquakes, of which roughly 4,000 are of Mw 4.0 or larger. ‎With the ongoing efforts of updating the probabilistic seismic hazard assessment ‎‎(PSHA) and the Iraqi building code, the need for an updated earthquake catalog for Iraq ‎in terms of moment magnitude (Mw) has been raised. Robust estimation of moment ‎magnitude (Mw) can be …

Blockchain-Enabled Master Data Management, Shakhawat Hossain

Theses and Dissertations

Master Data Management (MDM) is essential for maintaining data quality, accuracy, consistency, and governance within organizations. However, traditional centralized MDM systems continue to face challenges related to data integrity, security, and scalability. This research presents a blockchain-enabled MDM framework designed to overcome these limitations by leveraging blockchain’s decentralized, immutable, and secure architecture. The study aims to identify and address the shortcomings of conventional MDM practices, examine the applicability of blockchain technology in enhancing these systems, and develop a functional prototype to validate the proposed model. The framework incorporates decentralized review mechanisms that improve auditability and ensure trusted data verification by …

An Investigation Into The Inclusivity, Methodology, And Education Of Severe Weather In K-12 Schools, Stephen Holden Wooten

Theses and Dissertations

Schools are a focal point in the lives of everyone in the community, especially teachers, parents, and students. Investigating the connection between these individuals and tornadoes by identifying shortcomings in education, training, and emergency procedures can induce more effective and informed decision-making for future encounters. This study evaluated the inclusivity of tornado protocols for students with disabilities, uncovered where parents prefer their child to shelter in early dismissal situations and clarified how extensively natural hazard education and tornado drills are covered in schools. Two surveys and semi-structured interviews were used to obtain responses from earth science teachers, K-12 guardians, and …

Global Attractivity Of Positive Solutions Of Higher Order Nonlinear Difference Equations And Its Applications, Abdulaziz Almaslokh

Theses and Dissertations

Difference equations play an effective role in many mathematical models that represent some phenomena in different fields such as physics, economics, engineering and biology. From this perspective, studying and analyzing such equations are interesting issues for the advancement of scientific research. In particular, studying the asymptotic behavior of positive solutions of some population models that are a system of difference equations has become a necessity. In this dissertation, we examine the global attractivity of positive solutions of certain higher order nonlinear difference equations and apply these results to some population models.