Physical Sciences and Mathematics Commons^™

Stability Analysis In The Twist-Bend Nematic Liquid Crystal Model, Zhenqiang Li

Mathematics & Statistics Theses & Dissertations

The recently discovered twist-bend nematic liquid crystal (LC) phase is characterized by a nanoscale helical modulation of the nematic director n, forming a conical helix along the z-axis at an oblique angle θ. While many models assume a constant cone angle and equal elastic constants K11 = K22 = K33, this dissertation removes both assumptions by considering a fully anisotropic elastic energy with K11 ≠ K22 ≠ K33, and allowing θ to vary spatially. We analyze the stability of this system under frustrated and free boundary conditions using variational methods. …

The Impact Of Drought And Socio-Economic Factors On Attitudes Toward Immigrants In South Africa, Pamela Antwi-Nimarko

Graduate Program in International Studies Theses & Dissertations

Estimates of the global migrant population have steadily increased, with current data from the International Organization for Migration (IOM) reporting approximately 281 million migrants worldwide. Alongside this growth, anti-immigrant sentiments have risen in many host countries. This study seeks to contribute to the research on attitudes toward immigrants by exploring climate-related factors, particularly drought, as a key influence.

Leveraging a unique dataset combining the World Values Survey (WVS) and Afrobarometer, the study examines how drought, along with individual and contextual factors, affects attitudes toward immigrants. This dataset allows for an in-depth analysis of the direct impact of drought on public …

From Image Enhancement To Model Protection Integrating Generative Ai And Secure Learning In Computer Vision, Mohammad Shahab Uddin

Electrical & Computer Engineering Theses & Dissertations

This dissertation aims to address critical challenges in the field of computer vision and machine learning, focusing on three key areas: image translation, denoising, and model security. The research encompasses novel methodologies and models that significantly advance existing techniques. This dissertation will not only provide valuable contributions to the academic community but also hold significant potential for practical applications in domains ranging from surveillance to autonomous systems.

Consequently, this dissertation proposes three goals. First, we present new approaches for converting optical videos to infrared videos using deep learning. To apply powerful deep learning based algorithms for object detection and classification …

Nanosecond Pulsed Electric Field And Plasma Jets For Cancer Therapy, Edwin Ayobami Oshin

Biomedical Engineering Theses & Dissertations

Nanosecond pulsed electric field (nsPEF) employs nanosecond-duration, high voltage pulses to induce oxidative stress, leading to temporary or permanent damage to cells or tissue (also known as reversible and irreversible electroporation), and has been considered a promising approach for cancer therapy. In parallel to this, nanosecond pulsed atmospheric pressure plasma jets (ns-APPJs) have also shown to be effective in inactivating cancer cells or increasing sensitivity of cells to electric fields. ns-APPJs are known to generate reactive chemical agents, including reactive oxygen and nitrogen species (RONS) which induces oxidative stress resulting in cell proliferation, apoptosis, and necrosis. In this dissertation, a …

Mechanochemical Reaction Kinetics—A Theoretical Modeling And Experimental Study, Maria Dolores Masso Ramirez

Mechanical & Aerospace Engineering Theses & Dissertations

Mechanochemical reactions represent a class of chemical processes triggered by mechanical energy, widely recognized for their efficiency, solvent-free nature, and environmental benefits. They are increasingly applied in synthetic chemistry, a branch of science focused on creating new chemical compounds through controlled laboratory reactions. However, the mechanisms underlying mechanical activation remain poorly understood, primarily due to the difficulty in quantifying energy transfer during milling, where solid reactants are ground together using a ball mill. This thesis aims to bridge the gap in understanding the relationship between mechanical parameters and reaction kinetics by developing and validating a theoretical framework based on dimensional …

Streamer Discharge Simulation For Plasma-Assisted Combustion, Stuart Jairo Reyes

Electrical & Computer Engineering Theses & Dissertations

A common and successful method to achieve atmospheric pressure fuel-air plasma-assisted combustion is through repetitive ns pulsed discharges and dielectric-barrier discharge. The transient phase in these discharges is dominated by transport influenced by strong space charges produced by ionization fronts, this can be best represented by the streamer model. The function of non-thermal plasma in these discharges is to excite the species in the fuel-air mixture to produce radicals which accelerate the chemical conversion reactions which directly lead to temperature rise, ultimately culminating in ignition. Therefore, the characterization of the streamer and its energy partitioning is essential to developing a …

Testing Autonomy: Hybrid Scenario Synthesis, Benjamin E. Hargis

Electrical & Computer Engineering Theses & Dissertations

Hybrid Scenario Synthesis merges static and adaptive techniques to generate interactions that rigorously assess autonomous performance under multi-factor testing. Multifactor scenarios employ multiple individual stimuli to rigorously test system responses in complex settings. Static Scenario Testing involves scripted test cases that simulate specific conditions or events. These scenarios represent typical situations an autonomous system might encounter. The benefits of static testing include early defect detection, focused review by trained experts, and efficiency. In multi-factor scenarios, however, statically defined scenario factors are not able to guarantee meaningful interactions as the presence of other factors may invalidate underlying assumptions regarding the system …

The Role Of Artificial Intelligence In Workforce Learning And Development: A Systematic Review, Mildred V. Jones

Educational Leadership & Workforce Development Theses & Dissertations

The purpose of this study is to investigate how artificial intelligence (AI) is currently employed in workforce learning and development. The study examined the types of AI employed and the affordances realized for organizations and employees. A PRISMA systematic review methodology was utilized to address the overarching problem statement and answer the three questions guiding the study. The PRISMA extension Preferred Reporting Items for Systematic Reviews and Meta Analysis for Protocols was used to direct each phase of the research. In addition, the Preferred Reporting Items for Systematic Reviews and Meta Analysis was used to conduct the article selection process. …

Expanding The Lexa Bacterial Two-Hybrid System For Human Protein-Protein Interaction Screening: Application To Tumor Suppressor Par-4, Rebecca M. Richardson

Chemistry & Biochemistry Theses & Dissertations

Protein-protein interactions (PPI) are fundamental to cellular function, influencing processes such as signaling, structural organization, and disease progression. Disruptions in PPIs are implicated in cancer and neurodegenerative diseases, highlighting their importance as therapeutic targets. However, traditional methods for studying human PPIs, such as yeast two-hybrid and co-immunoprecipitation mass spectrometry, are costly and technically demanding. This dissertation explores the LexA-based bacterial two-hybrid (LexA-B2H) system as a cost effective and accessible alternative for investigating human PPIs.

This study focuses on the interaction between glucose-regulated protein 78 (GRP78) and cleaved prostate apoptosis response-4 (cl-Par-4), a tumor suppressor protein involved in apoptosis and neurodegenerative …

Weapons Of Mass Disruption: How Small States Use Cyber To Resist Larger Powers, Russell Alexander Korb

Graduate Program in International Studies Theses & Dissertations

This paper examines the ways in which small states can engage larger actors using cyber- attacks. Since the end of both World Wars, small states have increased in both numbers and relevance, with strong international institutions and norms against military aggression allowing small states to gain legitimacy by the very act of participating in the international system. However, although small states can now do more than simply choose a larger, stronger benefactor to ward off their enemies, they still cannot defy larger powers outright due to the still- dramatic difference in capabilities between them. Those small states interested in confronting …

Planetary Atmospheres, Ryan M. Johnson

Physics Theses & Dissertations

Planetary atmospheres are frequently studied using a number of spectroscopic methods. One of these is observing spectra to analyze what molecules are present or chemical reactions may be taking place. To this end, we have produced a line list of the electronic a¹Δ−X³Σ⁻ and b¹Σ⁺−X³Σ− transitions of SO. Additionally, a line list pure rovibrational transitions of the a¹Δ and X³Σ⁻ states were produced, but lacked the necessary experimental data for the b¹Σ⁺ state. These line lists can be used in further …

Effects Of High Temperature Compaction On 3d Printed Carbon Fiber Reinforced Polymer Composites, John D. Barber

Mechanical & Aerospace Engineering Theses & Dissertations

The aim of this dissertation was to study the effects of hot temperature compaction (HTC) upon the polymorphism and the mechanical behavior of an additively manufactured (AM), carbon fiber reinforced polyamide (PA6). Different pressure and temperature levels during HTC were tested to determine the overall effect upon the mechanical behavior and the material crystalline composition. Treated, carbon fiber reinforced PA6 samples were analyzed using differential scanning calorimetry, x-ray diffraction, thermogravimetric analysis, scanning electron microscopy, double cantilever beam testing and three-point bending testing. When considered with respect to as-printed samples, an HTC temperature of 190°C combined with 80 psi pressure resulted …

Biogenic Modification Of Tidally Modified Substrates From The Micro- To Macroscopic Scale, Rogers Clark Caldwell Buntin Ii

OES Theses and Dissertations

Digital outcrop models generated by high-resolution photogrammetric imagery permit investigations into organism-substrate interactions at the centimeter to sub-millimeter scale. This dissertation uses this three-dimensional technology to study two sedimentary successions— the Archaean Dresser Formation and Cretaceous Dakota Sandstone— by capturing images via unmanned aircraft systems and single lens reflex cameras. The ~3.48 Ga Dresser Formation provides evidence for some of the earliest life on Earth in the form of stromatolites and microbially induced sedimentary structures. Aerial imagery of the 3.5 km2 Buick Geoheritage reserve capture the site’s geologic structures and close-range imagery documents stromatolites and several microbially induced sedimentary structures …

Low Dissolved Oxygen Operation Enhances Biological Phosphorus Removal In Wastewater Treatment, Haley Morgan

Civil & Environmental Engineering Theses & Dissertations

Biological phosphorus (bio-P) removal occurs when bacteria are exposed to anaerobic/aerobic conditions that stimulate polyphosphate-accumulating organisms (PAOs) to uptake phosphorus. In most treatment plants, dissolved oxygen (DO) concentrations in the aeration tanks are commonly at or above 2.0 mg O₂/L, which is often referred to as the most optimal aeration condition for bio-P. If bio-P can happen efficiently at lower DO (< 0.3 mg O₂/L), then the energy demand of aeration can be decreased appreciably. This research was conducted in a biological nutrient removal (BNR) pilot plant to assess the performance of bio-P at progressively lower DO operation. This …

Enhancing Iot Security Using Lightweight Machine Learning Algorithms: A Comprehensive Approach Using Ensemble Learning, Feature Selection, And Federated Transfer Learning, Khawlah Harahsheh

Electrical & Computer Engineering Theses & Dissertations

The rapid expansion of the Internet of Things (IoT) has introduced significant security vulnerabilities due to the resource-constrained nature of IoT devices and their exposure to cyber threats. Traditional security solutions are often infeasible due to the high computational and storage demands they impose. This dissertation presents a lightweight, AI-driven security framework that enhances IoT network resilience by integrating feature selection, ensemble learning, and federated transfer learning while maintaining data privacy and minimizing computational overhead.

The proposed framework consists of three primary components: Feature Selection for Intrusion Detection, which optimizes performance by reducing redundant data and improving detection accuracy with …

Synchrotron Radiation Interferometry At Cebaf, Sankalp Rajendra Shinde

Physics Theses & Dissertations

Synchrotron radiation interferometry is a method to measure transverse beam size in electron accelerators. By using synchrotron radiation interferometry at a dispersive location in CEBAF at Jefferson Lab, we measure the electron beam size and energy spread. This interferometry technique allows us to monitor the energy spread non-invasively, to measure precise electron beam rms energy spread for hypernuclear experiments, and verify that they meet experiment requirements in real time. This dissertation discusses the design, simulations, construction, and commissioning of this Synchrotron Radiation Interferometer (SRI) in the Hall C line at Jefferson Lab in 2024–2025.

The Structure Function Of The Free Neutron At High X-Bjorken, Madhusudhan Pokhrel

Physics Theses & Dissertations

Understanding the internal structure of nucleons is one of the primary goals of nuclear physicists. As protons and neutrons are only the bound state solution of the QCD lagrangian (at least inside atomic nuclei), studying protons and neutrons helps uncover nuclear structure. Due to its easy availability, many studies on protons have been done on a wide range of kinematics. However, free neutron targets are not readily achievable. So, any information on neutrons has to be extracted from neutron-rich nuclei, and some nuclear models have to be used to subtract the contributions from other nucleons to extract the information …

Leveraging Artificial Intelligence To Strengthen Human Resilience Against Phishing Attacks, Muhammad Mavins

Cybersecurity Undergraduate Research Showcase

Phishing attacks are a major cybersecurity threat, tricking people with fake emails, scam websites, and social engineering tactics. As these attacks become more advanced, traditional security measures are no longer enough to stop them. This paper looks at how Artificial Intelligence (AI) can help detect and prevent phishing while also making people more aware of these threats. Using machine learning (ML), natural language processing (NLP), and behavioral analysis, AI can examine email content, sender behavior, and metadata to spot phishing attempts. AI-powered cybersecurity training can also teach people to recognize and respond to phishing by using personalized phishing tests and …

Soft Law, Activism, And Climate Displacement: Rethinking International Protections For The Environmentally Displaced, Guljannat Huseynli, Andrea G. Brown

Graduate Research Conference (GSIS)

Climate change is displacing millions of people globally, yet those forced to migrate due to environmental factors remain unprotected under existing international refugee law. This paper argues that legal recognition for climate refugees can emerge not through immediate treaty reform but through the evolution of soft law and norm creation. Drawing on constructivist theory, it examines how activism, international organizations, and legal precedents contribute to shifting global norms. Through case studies such as Ioane Teitiota v. New Zealand and the Fridays for Future movement, the paper shows how strategic litigation and advocacy can build momentum for future legal protections. It …

An Analytical Prior Selection Procedure For Empirical Bayesian Analysis Using Resampling Techniques: A Simulation-Based Approach Using The Pancreatic Adenocarcinoma Data From The Seer Database, Aditya Chakraborty, Mohan D. Pant

Epidemiology, Biostatistics, & Environmental Health Faculty Publications

Introduction: In the field of medical research, empirical Bayesian analysis has emerged as an increasingly applicable approach. This statistical framework offers greater flexibility, enabling researchers to incorporate prior information and rigorously estimate parameters of interest. However, the selection of suitable prior distributions can be a challenging endeavor, with profound implications for the resulting inferences. To address this challenge, this study proposes a new analytical procedure that leverages resampling techniques to guide the choice of priors in Bayesian analysis. Subject and Methods: The study group consisted of patients who had been diagnosed and had died of pancreatic adenocarcinoma (cause-specific death) who …

Rapid Prediction Of Coastal Flooding With Deep Neural Networks, Ali Shahabi, Navid Tahvildari

Graduate Student Government Association Research Conference

With the increasing impact of climate change and relative sea level rise, low-lying coastal communities face growing risks from extreme storm tides and recurrent nuisance flooding. Thus, timely and reliable predictions of coastal water levels are critical to resilience in vulnerable coastal areas. Over the past decade, enormous efforts have been made to utilize machine learning (ML) based data-driven models for the emulation and prediction of storm tides. However, flood advisory systems still rely on running computationally demanding real-time hydrodynamic models. because developing highly reliable ML-based models suitable for real-time forecasting and capable of capturing any surge levels is challenging. …

Zombie-Auras: Genai And Hybrid Text Production, Joshua Nieubuurt

English Faculty Publications

This paper explores the iterative evolutions of textual production and their impact on the “aura” of texts, as conceptualized by Walter Benjamin. The study identifies three key phases of textual production: the natural, the mechanized, and the digitized, each progressively displacing the “cult value” of texts. This cult value is lost through increased ease of creation, reproduction, dissemination, and dislocation of creators and audiences in time and space. The advent of Generative AI (GenAI) marks the latest evolution, transforming the “aura” into a memetic “zombie” form—familiar yet opaque, evoking both the sublime and fear. By examining Benjamin’s notion of “aura” …

The Elizabeth River Marine Debris Stakeholder Roundtable, Wie Yusuf, Joseph Barnes, Robin Dunbar, Jennifer L. Whytlaw, Tom Allen

School of Public Service Faculty Publications

Convened by Virginia Sea Grant, Old Dominion University, Clean Virginia Waterways (CVW), Virginia Coastal Zone Management Program (CZM), and the Virgina Marine Resources Commission. Supported by Sea Grant Marine Debris Community Action Coalition funding (for project titled From Learning to Willing to Doing: A Collaborative Approach to implementing the Virginia Marine Debris Reduction Plan.

Bridging The Gap: Understanding And Mitigating Csrf Threats In Service Worker Environments, Sivakanesan Dhanushkanda, Mustafa A. Ibrahim

Graduate Student Government Association Research Conference

Progressive Web Applications (PWAs) are gaining popularity due to their rich features. Service Workers (SWs), one of its integral components, make this possible by providing users with offline functionality, improved performance, and effective caching techniques. SWs act as proxies positioned between the client browser and the web server, capable of intercepting requests and responses. Recent research has revealed that, despite being designed with security in mind, there are ways to circumvent these security precautions and launch various attacks.

Sensitive functions in JavaScript are functions that can introduce security vulnerabilities if not properly coded or validated. These functions can manipulate the …

Successfully Navigating The Disruption Ai Will Bring To Survey Research, David M. Rothschild, Trent D. Buskirk, Stephanie Eckman, D. Sunshine Hillygus, Frauke Kreuter, David Lazer

Information Technology & Decision Sciences Faculty Publications

Surveys are a core methodological tool in government, industry, and academia, providing essential data for theory development and evidence-based decision-making. As artificial intelligence continues its rapid advancement, it stands to fundamentally transform the entire survey lifecycle - from design and administration to analytics and reporting. Previous transitions to new technologies, such as telephone, internet, and non-probability surveys, led to divisions within the survey research community with real consequences for both the trajectory of research and trust in the industry. We believe the survey community should take proactive steps now to avoid similar challenges with AI integration. Specifically, our paper examines …

Enhancing The Accuracy Of Image Classification For Degenerative Brain Diseases With Cnn Ensemble Models Using Mel-Spectrograms, Sang-Ha Sung, Michael Pokojovy, Do-Young Kang, Woo-Yong Bae, Yeon-Jae Hong, Sangjin Kim

Mathematics & Statistics Faculty Publications

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are prevalent neurodegenerative disorders among the elderly, leading to cognitive decline and motor impairments. As the population ages, the prevalence of these neurodegenerative disorders is increasing, providing motivation for active research in this area. However, most studies are conducted using brain imaging, with relatively few studies utilizing voice data. Using voice data offers advantages in accessibility compared to brain imaging analysis. This study introduces a novel ensemble-based classification model that utilizes Mel spectrograms and Convolutional Neural Networks (CNNs) to distinguish between healthy individuals (NM), AD, and PD patients. A total of 700 voice …

A Time-Domain Boundary Integral Equation For Moving Acoustic Sources In Uniform Flow And Its Solution By An Advanced Time Propagation Approach, Fang Q. Hu, Douglas M. Nark

Mathematics & Statistics Faculty Publications

This paper presents a time-domain boundary integral equation (TDBIE) formulation for predicting acoustic scattering from moving sources in a uniform mean flow. This work is motivated by the increasing need for accurate aeroacoustic modeling of modern aircraft configurations, including VTOL and eVTOL systems with rotating components. A key challenge in time-domain scattering simulations with moving sources is the determination of retarded time for a given observer time, which involves solving an implicit equation at each time step. This can be computationally costly, particularly for numerical solution of the TDBIE where every surface element on the scattering body acts as an …

Covariate Selection For Rna-Seq Differential Expression Analysis With Hidden Factor Adjustment, Farzana Noorzahan, Hyeongseon Jeon, Yet Nguyen

Mathematics & Statistics Faculty Publications

In RNA-seq data analysis, a primary objective is the identification of differentially expressed genes, which are genes that exhibit varying expression levels across different conditions of interest. It is widely known that hidden factors, such as batch effects, can substantially influence the differential expression analysis. Furthermore, apart from the primary factor of interest and unforeseen artifacts, an RNA-seq experiment typically contains multiple measured covariates, some of which may significantly affect gene expression levels, while others may not. Existing methods either address the covariate selection or the unknown artifacts separately. In this study, we investigate two integrated strategies, FSR_sva and SVAall_FSR, …

The Integration Of Big Data In Fintech: Review Of Enhancing Financial Services Through Advanced Technologies, Soudeh Pazouki, Mohammad B. Jamshidi, Mirarmia Jalali, Arya Tafreshi

Management Faculty Publications

Big data analytics is revolutionizing the FinTech industry, offering new opportunities for real-time decision-making, personalized financial services, and improved risk management. By leveraging advanced technologies like machine learning and artificial intelligence, financial institutions can efficiently detect fraud, predict market trends, and create innovative solutions tailored to customer needs. Big data also plays a critical role in promoting financial inclusion through alternative credit scoring models, providing access to credit for underserved populations and fostering broader participation in the financial system.

However, the integration of big data into FinTech is not without its challenges. Issues such as data privacy concerns, regulatory complexities, …

Analysis Of Errors In The Management Of Cutaneous Disorders, Robert J. Pariser, Sarah Alnaif

Department Dermatology Faculty Publications

In this study, we prospectively and retrospectively evaluated the occurrence of errors in the management of cutaneous disorders from patient visits and medical records in a single dermatology practice in southeast Virginia over a 3-year period (June 2020-July 2023). Providers should be able to improve diagnostic accuracy by utilizing established rapid bedside diagnostic techniques.