Digital Commons Network^™

Beyond "Thanks For Your Service": Navigating The Challenges Of Memorializing The Global War On Terrorism, James Craig

Dissertations

As objects of public commemoration, the American public expects our national war and veteran memorials to draw coherent narratives from diverse, often contradictory, experiences. In return, our society bestows these places with extraordinary authority, allowing them to define the essence of events from years ago. This dissertation explores that phenomenon in the context of the national Global War on Terrorism (GWOT) Memorial, which has been approved for placement in the National Mall and is in its design phase. As its framework, this dissertation uses the four truth framework developed by the South African Truth and Reconciliation Commission. With a focus …

Investigating The Consequences Of Conjugated And Secreted Isg15 On Coronavirus Pathogenesis, Mudassir Syed Ali

Dissertations

Coronaviruses have evolved a breadth of mechanisms to antagonize host innate immune responses. One widely studied mechanism is the ability to deconjugate ISG15 from target proteins in a process called deISGylation, which is catalyzed by the papain-like protease (PLP) domain of viral non-structural protein (nsp) 3. Since PLP activity is required for viral replication, it has been challenging to generate an infectious virus with a PLP that maintains protease activity but has lost deISGylase activity. In this study, we generated a chimeric MHV-A59 with its PLP2 domain replaced with that of the human coronavirus HKU1, which has been documented to …

Pyruvate Dehydrogenase Kinase 4 Mediates Sex Specific Outcomes In Sepsis Induced Cardiomyopathy, John Yap

Dissertations

During sepsis, males often experience worse cardiac outcomes than females. Here, we identified pyruvate dehydrogenase kinase 4 (PDK4) as a key contributor to this disparity. PDK4 is a mitochondrial protein that regulates glucose utilization by inhibiting pyruvate dehydrogenase (PDH). Using a mouse model of endotoxemia, we induced acute inflammation with a sublethal dose of lipopolysaccharide (LPS), which caused cardiac dysfunction and significantly increased myocardial PDK4 expression in males but not females. Cardiac-specific PDK4 overexpression promoted LPS-induced cardiac dysfunction in both sexes, whereas cardiac-specific PDK4 knockout provided protection. In wild-type males, LPS disrupted cardiac metabolism by decreasing PDH activity and fatty …

Interrogating The Dispersal Process And Relevant Genes In Vibrio Fischeri, Jeremy Esin

Dissertations

Biofilms are aggregates of bacteria encased in a matrix that shields bacteria from environmental hazards. These structures are formed in response to cues from the environment and drive colonization of new niches. Biofilms can be both beneficial and detrimental. Largely, research focuses on biofilms that have negative outcomes in clinical, environmental, and economical settings. However, the value of beneficial biofilms is recognized and studied. The marine bacterium Vibrio fischeri is part of a model system for studying symbiotic biofilms in a eukaryotic host. V. fischeri produces a transient biofilm at the surface of a specialized light organ and then disperses …

The Day You Begin: A Case Study Of Culturally Responsive Pedagogy In Early Childhood Classrooms, Kim Shelton

Dissertations

Culturally responsive pedagogy (CRP) has garnered growing attention in early childhood education due to its potential to cultivate inclusive and equitable learning environments for increasingly diverse student populations. This qualitative case study examines how early childhood educators perceive and implement CRP in classrooms with high concentrations of immigrant and culturally diverse students. Additionally, it explores the perceived impact of these practices on instructional effectiveness, classroom climate, and teacher-student interactions.

Data was collected through semi-structured interviews, classroom observations, and document analysis. Thematic analysis yielded four central findings: (1) teachers’ understandings of CRP varied considerably, with some demonstrating strong intentionality and others …

Developing Machine Learning Models And Graphene-Based Flexible Humidity And Temperature Sensors For Machine-Learning-Assisted Sensing, Seth Hajian

Dissertations

Flexible sensor technology has recently gained tremendous momentum in both academic research and industrial applications, transitioning from conceptual frameworks to practical implementations across diverse fields. This remarkable advancement can be attributed to several converging factors, including the maturation of nanomaterial science, the advancements of machine learning algorithms, and the critical demand for intelligent sensing solutions in healthcare, environmental monitoring, and industrial automation. The growing emphasis on personalized medicine and real-time health monitoring, accelerated by global health challenges, has further highlighted the necessity for accurate, cost-effective, and adaptable sensing platforms. This dissertation presents the fulfillment of three interconnected research projects focused …

A Parallel Fuzzy Logic Framework For Surgical Skill Evaluation Via Instance Segmentation And Deepsort Tracking, Mohsen M. Mohaidat

Dissertations

Manual evaluation of suturing skills during laparoscopic training is often subjective and labor-intensive, resulting in the lack of scalable and consistent feedback for trainees. This study proposes an automated framework that not only significantly reduces the need for in-person assessment by experts but also ensures scalability, thereby addressing the objectivity and cost-effectiveness limitations. While low-cost laparoscopic box trainers have become increasingly popular for residency training, performance assessment still depends on expert supervision. The proposed system aims to alleviate these limitations.

This study introduces a novel automated framework incorporating an optimized DeepSORT algorithm for classifying, localizing, and tracking surgical tools using …

Identifying Success Characteristics Of First-Generation College Students: A Framework For Early Intervention In K-12 Education., Christopher Harmon

Dissertations

This dissertation examines how K–12 educators can better support first-generation college students by identifying the characteristics that promote success and developing early interventions using Wagner et al.’s (2006) 4 C’s model: Competencies, Conditions, Culture, and Context. Guided by Michael Quinn Patton’s Utilization-Focused Evaluation (UFE), it closely investigates how factors such as family background, academic preparation, finances, and social support shape first-generation students’ capacity to persist and excel in college. The research draws on interviews with first-generation doctoral students, offering a detailed, first-hand account of their educational journeys from early schooling through advanced degrees. Notably, the findings highlight the importance of …

Design And Development Of Hip Implants For Longevity Through Integrating Advanced Groove Structures And Additive Manufacturing, Asarudheen Abdudeen

Dissertations

This doctoral research concerns the design and optimization of hip implants (HIs) to enhance performance, durability, and improve patient outcomes by addressing the key issues of wear, deformation, and stress distribution. Innovative surface groove designs have been introduced to both a solid and a hollow femoral head with the aim of reducing friction and wear. The addition of grooves, with both a hemispherical and rectangular cross-section, onto the femoral head reduced friction, as debris produced by the inner liner was trapped within the grooves, significantly reducing adhesive wear. A numerical simulation study compared the effects of surface modifications both grooves …

Experimental And Computational Study Of Slow Crack Growth Of High Density Polyethylene, Abdulla Fawzi Almomani

Dissertations

This dissertation investigates the slow crack growth (SCG) behavior of High-Density Polyethylene (HDPE) under various mechanical and environmental conditions. The study combines experimental analysis and computational modeling to enhance the understanding of SCG mechanisms in HDPE, particularly in pressurized pipes and under the exposure to hydrocarbons. A novel Crack Layer (CL) theory-based SCG model is developed and validated through experimental data, offering a predictive framework for HDPE failure assessment. The main objective of this dissertation is to quantify and model the viscoelastic-viscoplastic behavior of HDPE under monotonic and cyclic loading conditions while addressing SCG kinetics in structural applications. The study …

Comparative Genotoxicological Analysis Of Occupational Pesticide Exposures: An Experimental Approach And Systematic Review, Moustafa Samy Sherif

Dissertations

This dissertation investigates the genotoxic and cytotoxic effects of pesticide exposure through three complementary research components: a systematic review of occupational pesticide exposure in Arab countries (AraSys), a systematic review on encapsulated versus conventional pesticide formulations (Encap-Sys), and experimental toxicological assessments of various pesticide formulations in human cell lines (Pyr-Ex). This experimental component includes cytotoxicity assays using propidium iodide and DNA damage assessments via alkaline comet assays in HL60 and HepG2 cell lines exposed to pyrethroid insecticides and glyphosate-based formulations.

The AraSys systematic review revealed a critical positive association between occupational pesticide exposure and DNA damage in agricultural workers in …

Social Media And The Effect On Student Engagement, Lara Mcelveen

Dissertations

The purpose of my study was to determine the impact of social media on student engagement and behaviors in high school classrooms. The overarching research question that guided my study was: What is the impact of social media on student engagement? I used a mixed methods approach of quantitative and qualitative data to research my topic. I collected the data using surveys of two stakeholder groups in the study: young adults and educators. The survey results showed that both educators and young adults perceived a decline in class engagement and the rise of behavior in the classroom from social media …

Colloidal Quantum Dots: A Path Toward Making Mid-Wave Infrared Sensing A Ubiquitous Technology, Mohammad Mostafa Al Mahfuz

Dissertations

Reducing the size, weight, power consumption, and cost (SWaP-C) of infrared detectors could make infrared sensing more widely accessible. In the critical mid-wavelength infrared (MWIR) spectral range of 3-5 gm, commercially available detectors are limited by the high costs associated with epitaxial growth and hybridization, as well as the need for cryogenic cooling. These factors restrict their use to defense and space applications.

Colloidal quantum dots present a promising material for overcoming these challenges, with wafer-scale monolithic integration and Auger suppression being the key material capabilities to minimize the sensor's SWaP-C. Infrared sensors based on colloidal quantum dots have been …

Childhood Neuroanatomical Markers Of Familial And Nonfamilial Attention-Deficit/Hyperactivity Disorder, Rahman Baboli

Dissertations

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder, characterized by developmentally inappropriate levels of inattention, hyperactivity, and impulsivity. Children with family history of ADHD are at an elevated risk of having ADHD as well as a higher risk of persistent ADHD into adulthood, reflecting a source of etiological heterogeneity in ADHD. This heterogeneity in terms of both biological and environmental risk factors may explain differences in neural correlates, outcomes, cognitive, behavioral as well as developmental trajectories. It is therefore critical to understand the influence of having, or not having positive family risk factors on the neuroanatomical structures of the …

On The Design Of A Framework For Large-Scale Exploratory Graph Analytics, Oliver Andres Alvarado Rodriguez

Dissertations

Large-scale exploratory graph analytics merges data science with high-performance computing to extract critical insights from network-representable data. Data scientists routinely analyze data from the natural, social, and computing sciences by representing it as networks, or graphs, where objects become vertices and their relationships become edges. This representation allows data scientists to add graph analytics to their toolbox. However, designing tools for large-scale exploratory graph analytics is challenging due to the complexities of graph algorithms, such as high communication in distributed systems and large memory demands. These challenges can lead to overly complex software, which limits usability and development to a …

Machine Learning And Optimization For Intelligent Decision-Making, Elson Cibaku

Dissertations

This dissertation presents a series of innovative machine learning and optimization model designs that address complex operational challenges across logistics and power systems. By integrating advanced neural architectures with robust optimization techniques, the work delivers scalable solutions designed to improve efficiency, reliability, and decision-making in dynamic and real-world environments. The first study introduces a two-stage approach to effective vaccine distribution. This framework tackles the capacitated vehicle routing problem by combining adaptive clustering techniques with reinforcement learning and a simulated annealing pickup policy. Through extensive computational experiments, the approach demonstrates substantial improvements in routing efficiency, reducing both computational time and logistical …

Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan

Dissertations

This dissertation presents a comprehensive automated framework for power converter design, leveraging reinforcement learning (RL) and graph-transformer networks (GTN) to address critical inefficiencies in traditional manual topology optimization. Motivated by the combinatorial increase of circuit design spaces and the computational cost of iterative simulations, this work develops a robust framework for generating energy-efficient topologies requiring rapid and reliable circuit design.

The framework integrates three key components: (1) an upper-confidence-bound-tree-based (UCT-based) RL model for circuit topology space exploration, (2) parallelized UCT algorithms to accelerate exploration processes, (3) a Graph-Transformer-based Network enabling fast circuit performance evaluation. Experimental validation demonstrates the whole framework …

The Interplay Of Accommodation And Oculomotor Vergence Within Young Adults With Binocularly Normal Vision And Typically-Occurring Convergence Insufficiency, Sebastian Fine

Dissertations

Concerted binocular coordination evoking oculomotor and refractive responses to visual stimuli are essential to daily function. Oculomotor dysfunctions can inhibit binocular responses to visually-near stimuli and have high comorbidities to accommodative dysfunctions. Three visual cues for inward (convergent) and outward (divergent) oculomotor movements, when presented concertedly create natural-viewing conditions: disparity- the binocular difference in light cast onto the fovea due to differing ocular perspectives, blur- the acuity of a visual target which stimulates accommodation, and proximal- the perceived distance of a visual stimuli based on size.

This study aims to quantitatively investigate oculomotor vergence and accommodation performances between individuals with …

Modulation Of Cerebellar Cells By Transcranial Ac Stimulation In Anesthetized Rats, Qi Kang

Dissertations

Noninvasive brain stimulation (NIBS) is increasingly utilized in clinical trials for the treatment of neurological disorders. Each NIBS technique offers distinct advantages. Transcranial electrical stimulation (tES) is easy to apply and requires only simple equipment, while transcranial magnetic stimulation (TMS) can penetrate deeper than tES into the brain and it is more focal. Transcranial focused ultrasound stimulation (FUS) is superior to both in terms of penetration and focal stimulation. This study focuses on the modulation of the cerebellum, traditionally believed to be associated with motor coordination but increasingly recognized for its role in cognition and emotion as well. While tES …

Adversarial Robustness In Advanced Machine Learning Models Integrating Graph Neural Networks And Large Language Models, Mahmoud Nazzal

Dissertations

Artificial intelligence (AI) has achieved remarkable performances across various domains. In most real-world applications, data often takes relational forms, such as graphs and networks, or sequential forms, such as text and time series. As AI evolves, specialized models have emerged to handle these structures; Graph Neural Networks (GNNs) for relational mining and Large Language Models (LLMs) for sequential understanding. Despite their success, these models face challenges in security, robustness, and interpretability. GNNs excel in relational reasoning but are vulnerable to adversarial manipulation and lack interpretability, while LLMs are strong in linguistic reasoning and generalization yet struggle with relational data and …

An Inquiry Into The Physics Of Mixing And Floc Filtration, Andrew P. Pennock

Dissertations

Flocculation and clarification are two essential processes to deliver safe water at a reasonable cost to consumers. There are two major thrusts to the research presented in this dissertation. The first is to better characterize the physics and mixing parameters used for the design of hydraulic flocculators in the context of drinking water treatment plants. The second major thrust is to investigate floc filtration as a mechanism for the removal of primary particles during floc blanket clarification.

The intensity of mixing in environmental and chemical engineering applications is often characterized by the Camp and Stein velocity gradient. This parameter has …

Fact-Checking As A Multi-Step Process: From Ambiguity Resolution To Claim Validation, Wenbo Wang

Dissertations

The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. Fact-checking—the process of verifying claims against credible evidence—has emerged as a critical safeguard against misinformation. Yet, the task is fraught with challenges: claims are often ambiguous, context-dependent, or composed of multiple intertwined assertions, while automated systems struggle to replicate the nuanced reasoning of human experts. This dissertation addresses these challenges by reimagining fact-checking as a multi-step, knowledge-guided process that systematically resolves ambiguity, decomposes complexity, and validates claims through structured reasoning. Additionally, the proposed …

Next-Generation Extended Reality Systems With Real-Time Edge Artificial Intelligence And Mobile Computing, Pedro H. Regalado

Dissertations

Mixed reality (MR) and augmented reality (AR) systems are reshaping digital experiences by seamlessly integrating physical and virtual environments. This dissertation presents a comprehensive framework for next-generation immersive systems, combining advances in real-time data processing, multi-user synchronization, and secure communication. The core contributions are structured around three interconnected systems: MediVerse, TeleAvatar, and MultiAvatarLink, each addressing critical challenges in mobile MR.

MediVerse is a secure and scalable framework for real-time health and performance monitoring, integrating intelligent IoT sensors, wearable technologies, and MR interfaces. It supports multi-camera fusion, adaptive compression, and real-time three-dimensional (3D) point cloud generation, enhancing data accuracy and responsiveness …

From Neural Networks To Large Language Models: Innovations In Financial Ai, Mathematical Reasoning, And Structured Data Representation, Junyi Ye

Dissertations

This dissertation explores the evolution and application of artificial intelligence techniques across three critical domains: financial modeling, mathematical reasoning, and structured data analysis. The dissertation presents seven research projects that chart a progression from specialized neural architectures to sophisticated large language models (LLMs), contributing novel methodologies and frameworks at each stage.

In the financial domain, the research first introduces TS-Mixer, a MLP-based architecture for time-series forecasting that captures both feature relationships and temporal dependencies through a simple yet effective design, outperforming more complex models in S&P500 index prediction. The dissertation then presents DySTAGE, a dynamic graph representation learning framework that …

Towards Explainable Ai On Graph Neural Networks: Xaig, Jiaxing Zhang

Dissertations

In the evolving landscape of artificial intelligence (AI), Graph Neural Networks (GNNs) have garnered growing prominence for their adeptness in processing graph-structured data. Despite this, the interpretability of their predictions often remains elusive. The demand for transparency and explainability in complex prediction models has reached unprecedented levels. To address this, post-hoc instance-level explanation techniques have emerged, aiming to unveil the rationale behind GNN predictions. These techniques endeavor to unearth substructures that elucidate the predictive behavior of trained GNNs.

This dissertation embarks on an exploration of Explainable AI (XAI) technologies within the realm of GNNs. Amid the challenges posed by the …

Leading Change For Transgender And Gender Diverse Healthcare: Assessing Organizational Readiness, Braxten Lovett

Dissertations

Background: Transgender and gender-diverse (TGD) individuals face persistent stigma and systemic discrimination across multiple societal domains, with healthcare settings—intended as safe spaces—often being among the most harmful. Despite increased visibility of TGD populations and growing research on their health inequities, inclusive healthcare remains insufficiently addressed by many healthcare leaders, adding to the urgency to advance equitable, inclusive care. Additionally, structural cisnormativity and binary gender frameworks continue to perpetuate misinformation, erasure, and health disparities. Addressing these entrenched barriers requires systemic reform rooted in cultural humility, inclusive practices, and a commitment to dismantling cisnormative bias within healthcare delivery and policy. This study …

Does The Value Last? Exploring The Longitudinal Value Of A Research Experience For Preservice Science Teachers, Elizabeth A. Leong

Dissertations

Little attention has been given to the preparation of secondary preservice science teachers (PST) to meet the vision for science teaching and learning outlined in A Framework for K-12 Science Education. Existing literature suggests PSTs would benefit from authentic engagement in scientific research. But research experiences for preservice science teachers or preRETs are rare (Krim et al., 2019). This longitudinal qualitative case study explores the value retained one year after participation in a preRET, which engages PSTs in scientific research and education-focused professional learning. This study utilizes the preRET Value Creation Model (preRET VCM) (Authors, 2024), which overlays the Value-Creation …

Understanding And Engaging In Equity Work: A Phenomenological Action Research Study Of Community College Esol Instructors, Emily E. Packer

Dissertations

Community colleges (CCs) are regarded as accessible and affordable pathways to higher education and financial mobility, offering significant potential to promote educational equity (Fink et al., 2023). These institutions enroll the largest number of English for Speakers of Other Languages (ESOL) students in adult education; however, CC ESOL students face lower rates of degree completion and transfer compared to their non-ESOL peers (David & Kanno, 2021; Fink et al., 2023; Raufman et al., 2019). While research has examined factors contributing to low CC ESOL student persistence and interventions to improve overall CC student outcomes, research on specific efforts to support …

What Is Your Why? An Exploration Of Why Teachers Remain In The Professsion At An Urban Elementary School In The South., Malikah Bennett

Dissertations

This qualitative research investigates the factors affecting teacher retention at a Title I elementary school in the Southern region of the United States, utilizing Herzberg’s Two-Factor Theory of motivation and hygiene as a framework. This study seeks to identify intrinsic motivators, such as recognition, professional growth, and a sense of purpose, as well as extrinsic hygiene factors like administrative support, work conditions, and compensation, to analyze their influence on teachers' decisions to remain in the profession. Data were gathered via semi-structured interviews with a purposive sample of 10 teachers, all possessing five or more years of teaching experience at Cardinal …

Student Engagement In Ela Choice-Based Core Curriculum: A Case Study Of The Dramatic Writing For Film, Television, And Theater Course, Brian Thomas Clements

Dissertations

This paper describes a case study examining student feelings towards engagement in choice-based core ELA courses and teacher feelings towards student engagement specifically within the Dramatic Writing for Film, Television, and Theater course offered in the state of Georgia. The context of this study focuses on the impact that student agency, choice, and voice have on student engagement from their own perspective and how Invitational Education Theory connects to this impact and the course itself. The case study examines the course, its students, and teachers in two schools in a large, suburban metro Atlanta school district. Through interviews and observations, …