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On High-Speed Breakup Of Water Droplets Behind High Mach Number Shocks, Sydney M. Briggs

Graduate Thesis and Dissertation post-2024

Water droplet breakup in high-speed flow is a relatively popular experimental study to analyze breakup mechanisms. There is a plethora of experiments performed at low Mach number and low Weber number, but studies with higher speed flows and higher Weber numbers are less common. In this study, water droplet breakup is assessed using high-speed shock waves (Mach 2.3-above Mach 5) in a shock tube. Multiple methods are used to introduce droplets, and multiple different water purity levels are considered. An assessment was made into whether cavitation played a role in the breakup process physically, as this has been a budding …

Synthesis And Evaluation Of Chalcones As Treatment For Negative Sense Single Stranded Rna Viruses And Applications As Broad-Spectrum Antivirals, Lorael Kirton

Graduate Thesis and Dissertation post-2024

Chalcones are a class of compounds naturally found in plants and are predicated upon a 1,3-diphenylprop-2-en-1-one scaffold. Chalcones possess many biological activities ranging from anticancer to antiviral activities. This thesis investigates the broad-spectrum antiviral properties of chalcones. Some chalcones have been reported to affect host cell mechanisms such as mammalian target of rapamycin (mTOR) signaling cascade or the cell cycle to reduce viral replication. Previously, a series of chalcones 8 were synthesized and investigated in human cytomegalovirus virus (HCMV) and human immunodeficiency virus (HIV). In this study, ten new chalcones predicated upon the design of 8 were synthesized and a …

Mechanistic Insights Into The Antimicrobial Action Of Fungus-Derived Xanthoquinodins Against Clostridioides Difficile, Erika A. Serravalle

Graduate Thesis and Dissertation post-2024

The bacterial pathogen Clostridioides difficile is the leading cause of antibiotic- and healthcare-associated diarrhea, imposing significant clinical and economic impacts. The emergence of hypervirulent strains, such as PCR ribotype 027 (RT027), has exacerbated disease severity, recurrence rates, antibiotic resistance, and epidemiological spread. Expanding resistance profiles among C. difficile strains continue to limit the effectiveness of current IDSA-SHEA recommended therapies, which are already compromised by high recurrence rates due to antibiotic-induced disruption of the gut microbiota. These challenges highlight the urgent clinical need to identify and characterize antimicrobial compounds targeting alternative pathways in C. difficile physiology. We report the discovery and …

Deep Reinforcement Learning-Based Optimal Takeoff Trajectory Design Of An Evtol Drone, Nathan M. Roberts, Bingling Huang, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The continuing development of electric vertical take-off and landing (eVTOL) aircraft presents promising opportunities to alleviate transportation congestion. However, designing and executing takeoff trajectories that optimally balance energy usage, passenger comfort, and aircraft constraints remains challenging. Conventional design optimization provides a solution for pre-defined flight conditions and environments but is not ideal in real-world applications. In contrast, deep reinforcement learning (DRL) implements optimal policy making real-time decisions with no assumption of mathematical models. Seeing the lack of literature on DRL-based takeoff trajectory design of eVTOL aircraft, we implement and conduct DRL-based optimal takeoff trajectory designs for the Airbus³ Vahana …

Genomic Consequences Of Habitat Fragmentation In The Florida Scrub-Jay: Diversity, Adaptation, And Disease Susceptibility, Maryam Ghoojaei

Graduate Thesis and Dissertation post-2024

Habitat fragmentation is a severe threat to biodiversity by reducing population size, gene flow, and adaptive potential, especially in habitat specialists like the Florida Scrub-Jay (Aphelocoma coerulescens). This dissertation integrates whole-genome sequencing and immunogenetics to assess the genomic consequences of habitat fragmentation across three primary Florida Scrub-Jay strongholds: Archbold Biological Station, Ocala National Forest, and Florida’s East Coast. In Chapter 2, I focused on adaptive genetic diversity at the Major Histocompatibility Complex (MHC) class II genes. I characterized MHC allelic richness, evaluated signatures of selection, and examined associations with pathogen infections. Despite population declines, I found moderate MHC diversity, suggesting …

A New Dawn Of Joy: How Joy Is Cultivated Among Black Transgender And Nonbinary Young Adults In Florida, Courtney Marciá Gardner

Graduate Thesis and Dissertation post-2024

The state of Florida had a record-breaking number of implemented and proposed policies between 2023-2024 that impacted transgender and nonbinary individuals. Black transgender and nonbinary people are particularly impacted by these policies due to the compounded effects of their race and gender identity. Nonetheless, despite the growing literature on Black transgender and nonbinary individuals, a lack of research exists examining positive aspects of intersectional experiences among Black transgender and nonbinary individuals. This qualitative study shifts away from deficit centered frameworks by investigating how Black transgender and nonbinary young adults in Florida cultivate joy in their lives. This study uses a …

Large Language Models And Networks: Edge Proposal, Synthetic Corpora, And Adaptive Node Generation, Nathan Gonzalez

Graduate Thesis and Dissertation post-2024

Natural Language Processing (NLP) and Artificial Intelligence (AI) have evolved from brittle rule-based engines through data-driven statistical models to today’s transformer architectures whose multi-head attention enables rich contextual reasoning. Against this backdrop, this dissertation unifies three complementary investigations that deepen our understanding of how large language models (LLMs) can reason over, generate, and strategically adapt language within networked settings. First, instruction-tuned LLMs are recast as latent-relationship detectors: by prompting models to hypothesize links between text-described entities, we recover edge sets that reconstruct social, thematic, and citation graphs with high precision, revealing how attention distributions encode topological cues. Recognizing the difficulty …

The Effects Of Resistance Training Volume On Muscle Quality Among Older Adults, Kevan Knowles

Graduate Thesis and Dissertation post-2024

BACKGROUND: Age-related declines in muscle strength are more closely linked to deteriorations in muscle quality than muscle mass. Echo intensity (EI) measured by B-mode ultrasonography is a common non-invasive marker of intramuscular adiposity and fibrous tissue. Although high-intensity resistance training is effective, the added value of higher training volumes on muscle quality and strength in older adults remains unclear. PURPOSE: This study aimed to compare the effects of different resistance training volumes on various measures of muscle quality, size, and strength among older adults. METHODS: Twenty-five older adults were randomized to either moderate volume (2 sets per exercise) or high …

Understanding The Mechanism In Shaping Guest Acceptance Of Service Robots In Caribbean Hotels: The Moderating Role Of Cultural Familiarity In The Cac Model, Jamilia A. Lawrence

Graduate Thesis and Dissertation post-2024

Service robots continue to become increasingly popular in the hospitality and tourism industry. Understanding the cognitive and emotional processes is important in explaining the sequential processes of guests accepting new technologies. Especially in regions like the Caribbean, where human-to-human interaction and personalized services are highly valued.

This study investigates how cognitive evaluations of service robots, including utility, coolness, autonomy, courtesy, and interactivity, influence guests' emotional responses and their acceptance of the technology in Caribbean hotels. Additionally, the study explores the moderating role of cultural familiarity in the relationship between emotion and acceptance.

Using the cognitive-affective-conative (CAC) model, 415 responses were …

Change Point Monitoring In High-Dimensional Factor Models, Mahdi Mirhosseini

Graduate Thesis and Dissertation post-2024

This dissertation presents the Factor-Augmented Detection (FAD) algorithm, a robust methodological framework for online change point detection in high-dimensional data streams, grounded in classical factor model analysis. To tackle the challenges of monitoring large-scale datasets, the FAD algorithm decomposes data into a parsimonious set of common factors and sparsely changing idiosyncratic residuals, facilitating independent, targeted analysis of low-dimensional factor dynamics and sparse high- dimensional residual evolution.

Following decomposition, structural changes in the factor components are identified using established multivariate sequential monitoring techniques, specifically the Multivariate Cumulative Sum (mCUSUM) and Multivariate Exponentially Weighted Moving Average (mEWMA) procedures. Simultaneously, sparse alterations in …

Analysis Of An Aero-Engine Using Ammonia As A Fuel Carrier, Kangana Patel

Graduate Thesis and Dissertation post-2024

Numerous studies in the literature have explored the decarbonization of aviation. Some opt for sustainable aviation fuels (SAF), while others propose Hydrogen(H₂). Recent studies have also investigated Ammonia (NH₃) as a potential hydrogen fuel carrier. This study of NH₃ as a viable alternative fuel could help reduce overall emissions and overcome the challenges of H_2, which is highly flammable and difficult to store. This study aims to develop a core-engine model in a system simulation software called Simcenter Amesim. Results show a reasonable similarity between jet-A fuel and NH₃ cracked H₂ within …

Critical State-Based Study On Deformations Due To Construction Activities And Blast Densification, Jorge Enrique Orozco-Herrera

Graduate Thesis and Dissertation post-2024

The behavior of geo-structures and foundation systems in densely populated urban areas relies on the successful performance of the supporting soils when subjected to static (e.g., the weight of the structure or service loads) or dynamic (e.g., earthquake-induced ground motions, construction-induced vibrations, wind loads, or traffic) loading scenarios. Construction-related activities and ground improvement operations can also be responsible to alter the stress-strain-strength behavior of supporting soils by causing vibration-induced ground deformations, excessive vibrations, or mobilizing soil shear strength in relation to in situ or as-built conditions. Construction-related activities and ground improvement operations such as blast densification trigger complex dynamic input …

Computational Methods For Population Genetic Inference Using Identity By Descent And Local Ancestry, Yuan Wei

Graduate Thesis and Dissertation post-2024

Identity by descent (IBD) and local ancestry are essential for population genetic inference, such as understanding genealogical relationships and demographic history through genomic data. With the availability of large and high-resolution datasets, new opportunities and computational challenges are brought for efficient and accurate methods to infer IBD segments and local ancestry. This dissertation presents three computational methods designed to assist in population genetic inference. First, RaPID-Query is introduced to efficiently query IBD segments for individual haplotypes over a large genotype dataset. This method is based on the positional Burrows-Wheeler transform (PBWT) algorithm and utilizes a random projection approach. RaPID-Query is …

Integration Of System Dynamics And Agent-Based Simulation To Emulate Cyberattacks In An Iot-Based Smart Grid, Francisco Valdez

Graduate Thesis and Dissertation post-2024

The electric power grid is a cyber-physical system (CPS) that plays a fundamental role in modern society. With the integration of renewable energy sources and advanced communication technologies, Smart Grids (SGs) can enhance both the profitability and reliability of the electric power system. The communication network that interconnects numerous remotely distributed generators, devices, and controllers plays a vital role in grid control, and current trends favor the widespread adoption of Internet of Things (IoT) devices. However, this network is inherently vulnerable to cyberattacks. This dissertation presents a hybrid methodology to model and analyze the dynamic behavior of an electrical Smart …

Holographic Optical Elements For Complex Beam Transformations, Shaghayegh Yaraghi

Graduate Thesis and Dissertation post-2024

In this thesis, we explore the design, fabrication, and application of volume holographic phase elements in photo-thermo-refractive (PTR) glass for two key purposes: expanding the eye-box in augmented reality (AR) displays and controlling optical angular momentum (OAM) modes in laser cavities.

Encoding complex phase structures in PTR glass enables efficient beam shaping, multiplexing, and wavefront engineering, offering strong potential in AR displays, optical communications, and structured light. Holographic optical elements (HOEs) recorded in PTR glass exhibit high diffraction efficiency (over 99%), thermal stability, and chemical durability. Combined with low absorption and scattering in the visible and near-IR, these features make …

Shock Tube Droplet Breakup Experiments Facilitated By Acoustic Levitation, Anthony J. Aguilera

Graduate Thesis and Dissertation post-2024

Droplet introduction methodology in a shock tube differs based on the experimental conditions. For experiments in which the objective is to image droplet breakup, acoustic levitation allows for a consistent droplet shape and for diagnostic equipment to be aligned to a droplet prior to an experiment. A levitator was designed and used in the University of Central Florida’s shock tube facility. Polystyrene doped droplets were levitated to increase the likelihood of cavitation occurring. Multiple droplets were impacted by a shock wave, and the breakup regime was captured using a high-speed camera.

Examining Information Flows Within Transformer Models Using Transfer Entropy, Clayton Barham

Graduate Thesis and Dissertation post-2024

The rapid growth of artificial intelligence, in terms of both power and prevalence, motivates the need for new ways to study explainability in deep neural networks. This is especially true for transformer architectures and large language models, which are the driving force behind the current surge in artificial intelligence. The complexity of transformer architecture foils many pre-existing methods for studying explainability in deep neural networks. To address this gap in knowledge, this dissertation proposes a new method of studying explainability in transformer architectures that leverages insights from neuroscience, employing transfer entropy to map information flows between components of the transformer …

Skeletal Embodiment Of Structural Violence: Testing Application Of The Weathering Hypothesis In Analyses Of Identified Sex, Jasper K. Shaw

Graduate Thesis and Dissertation post-2024

Structural violence refers to the experiences of inequality faced by marginalized sex, gender, race, and socioeconomic groups. Unequal access to healthcare, housing, and education can cause poor health that may affect how a decedent is analyzed by forensic anthropologists. This research hypothesizes that, due to gender- and sex-based marginalization, females will display greater rates of stress and correlated accelerated aging (i.e., weathering), than males. Computed tomography scans from 100 males and 99 females aged 20-69 years old and white and middle class, were sampled from the New Mexico Decedent Image Database (NMDID). Stress was assessed via cranial porosities, antemortem tooth …

High-Efficiency Dual Active Bridge Converter With Stacked Secondary Phase For Next-Generation Ai Data Center Power Delivery, Anirudh Ashok Pise

Graduate Thesis and Dissertation post-2024

The rapid electrification of hyperscale AI data centers is accelerating a shift from legacy 48 V distribution ladders to ±400 V high-voltage DC backbones, concentrating residual loss and dynamic stress on a single isolated bidirectional interface. This work presents a high-density Dual Active Bridge with Stacked Secondary Phasing (DAB-SSP) architecture as a scalable GaN-based solution for 48 V–800 V rack-level power conversion. By stacking 400 V secondaries, the topology leverages 650 V GaN devices while satisfying 800 V system requirements, reducing clearance and creepage distances, minimizing magnetic path lengths, and embedding leakage inductance necessary for wide-range zero-voltage switching.

A rigorous …

Black Teachers, Labor Consciousness, And The Making Of The Modern Civil Rights Movement In Florida, Marissa M. Bellenger

Graduate Thesis and Dissertation post-2024

Histories of Black teachers have often portrayed them as passive actors in the labor and civil rights movements of the twentieth century. While recent scholarship has highlighted the agency of Black educators, few studies have examined how their professional networks facilitated both labor activism and civil rights strategies. This thesis examines how Black educators in Florida leveraged the Florida State Teachers Association (FSTA) to challenge the racialized economic, political, and social structures of the South by organizing equal pay campaigns with the support of the National Association for the Advancement of Colored People (NAACP). From the late 1930s to the …

The Effect Of Four Vocabulary Tasks On The Initial Learning And Retention Of Formulaic Language: The Case Of Phrasal Verbs, Eman Barri

Graduate Thesis and Dissertation post-2024

The quasi-experimental study investigated the effect of four vocabulary tasks on the learning and retention of English phrasal verbs (PVs). University Intensive English Program students (91) completed one of the following tasks: One Fill-in-the-Blank, Three Fill-in-the-Blank, Sentence Writing, and Composition Writing. Their knowledge of eight target PVs was measured using a modified vocabulary knowledge scale at three points: pretest, immediate posttest, and delayed posttest (two weeks later). A mixed factorial ANOVA revealed a significant interaction between task and time. Follow-up repeated-measures and one-way ANOVAs showed that the Three Fill-in-the-Blank produced the highest scores on both posttests. Consistent with findings on …

Robust Evaluation Framework On Adversarial Purification, Yuan Du

Graduate Thesis and Dissertation post-2024

This dissertation proposes novel Energy-Based Model (EBM) learning strategies and adversarial robustness evaluation framework that addresses critical gaps in iterative purification defenses. First, we introduce strategies to learn EBMs by controlling MCMC sampling trajectory lengths for distinct applications: (i) short-run sampling for state-of-the-art unconditional image generation on CIFAR-10 and ImageNet; (ii) mid-run sampling for classifier-agnostic adversarial purification; and (iii) long-run sampling for principled density modeling. Using three novel MCMC initialization techniques within standard Maximum Likelihood objectives, we enable significant performance gains without architectural modifications. Second, we address evaluation deficiencies in existing iterative stochastic defenses by developing the \textit{Memory Efficient Full-gradient …

Evaluating Health And Immune Proxies Within And Across Sea Turtle Life Stages, Tiffany M. Dawson

Graduate Thesis and Dissertation post-2024

Understanding variations in health and immune function across life stages or physiological states is important for population monitoring and for understanding species’ responses to anthropogenic disturbances. Sea turtles are a model species for evaluating these changes within and across life stages due to their long lifespans with ontogenetic habitat and diet shifts. In this dissertation, I tested whether health and immune hematological proxies (Packed Cell Volume [PCV], white blood cell counts, total protein [TP], biochemistry) differed: (1) across the reproductive season, (2) between species and (3) foraging groups, and (4) with reproductive output for adult female turtles (Chapter 2). In …

An Integrated Approach To Waste Management And Development Of Data Driven Decision Support Tools, Mert Gokgoz

Graduate Thesis and Dissertation post-2024

Municipal solid waste management requires balancing environmental performance, operational efficiency, and community participation. Proper recycling contamination in single-family units is a persistent barrier to material recovery, reducing the effectiveness of local programs by increasing recycling contamination. This dissertation develops an integrated, data-driven framework that combines behavioral modeling of communities via statistical analysis and machine learning (ML), and life cycle assessment (LCA) to support decision-making in residential waste management. The first component examines household recycling behavior using data from Orange County, Florida’s Recycling Quality Improvement Program (RQIP). Cart-tagging results were integrated with socio-demographic data from the U.S. Census to predict contamination …

Qualities Of Instructors Adult Second Language Learners Identify As Being Most Effective In Supporting Their Language Skills In Intensive English Programs, Nick Myrca Gauthier

Graduate Thesis and Dissertation post-2024

This qualitative research discusses the importance of the pedagogical and social qualities of instructors in the academic achievement of adult second language (L2) learners enrolled in intensive English programs (IEP). Its primary goal is to comprehend the role of social traits such as empathy, patience, approachability, supportiveness, and respectfulness and of pedagogical traits such as building trust, motivation, and minimizing language learning anxiety when instructing adult L2 learners. Within the framework of this study, a semistructured interview format was used to gather the lived experiences of seven participants who were either enrolled or had been enrolled in a university’s intensive …

Generative Adversarial Networks For Dimensionality Reduction In Evtol Aircraft Takeoff Trajectory Optimization, Samuel Sisk, Farzaam Khorasani-Gerdehkouhi, Abdulaziz Abutunis, K. Chandrashekhara, Xiaosong Du

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Electric vertical takeoff and landing (eVTOL) aircraft play a key role in urban air mobility (UAM), which aims to alleviate traffic congestion in urban areas. Despite their value, eVTOL aircraft suffer from battery energy consumption, which affects their range and endurance in real world flight tasks. Especially, the takeoff process has been identified for excessive power demands. Multidisciplinary analysis and optimization manage to discover optimal takeoff trajectories with minimum energy consumption while balancing multidisciplinary trade-offs, such as short distance takeoff and passengers' comfort. However, conventional parametrization methods (such as B-spline curves) leverage an empirically high-dimensional design space to include real …

Methods And Applications Of Coherent Analog Photonic Processing, Andrew B. Klein

Graduate Thesis and Dissertation post-2024

Photonic processing is a compelling approach to address the increasing computational requirements of neural networks, promising increased processing speed and better energy efficiency for operations such as matrix-vector multiplication. However, in practice the limitations of photonic hardware necessitate that these systems adopt fixed-point encoding rather than the floating-point standard used by digital electronics. The reduction in accuracy incurred by this requirement must be managed and addressed for real world applications. In this work, we present a reconfigurable, scalable, and parallelizable photonic multiplier cell using coherent balanced photodetection of analog signals to produce signed multiplications. This style of system outperforms other …

Ai-Powered Image-Based Assessment Of Pressure Injuries Using You Only Look Once (Yolo) Version 8 Models, Mehedi Hasan Tusar, Fateme Fayyazbakhsh, Niloofar Zendehdel, Eduard Mochalin, Igor Melnychuk, Lisa Gould, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Objective: The primary objective of this study is to enhance the detection and staging of pressure injuries using machine learning capabilities for precise image analysis. This study explores the application of the You Only Look Once version 8 (YOLOv8) deep learning model for pressure injury staging. Approach: We prepared a high-quality, publicly available dataset to evaluate different variants of YOLOv8 (YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x) and five optimizers (Adam, AdamW, NAdam, RAdam, and stochastic gradient descent) to determine the most effective configuration. We followed a simulation-based research approach, which is an extension of the Consolidated Standards of Reporting Trials …

Advancements In Slow-Wave Thin Film Lithium Niobate For Opto-Electronic Communications, Joseph W. Haefner

Graduate Thesis and Dissertation post-2024

The views expressed in this dissertation are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the U.S. Government.

The explosive growth of human connectedness over the previous decades has, and will continue to strain the communication infrastructure under-girding modern economies, and society. The continuous expansion of data-centers, advanced artificial intelligence models, and remote data storage will require novel high bandwidth solutions for both long haul and local inter-connects. Current solutions seek to expand link bandwidth through the use of complex high baud rate constellations, in …

Towards Achieving General Video Understanding, Rohit Gupta

Graduate Thesis and Dissertation post-2024

This dissertation investigates the problem of general video understanding, aiming to develop models capable of robust, adaptable, and semantically rich interpretation of video data across diverse domains and tasks. Despite significant progress in video analysis, existing methods remain limited by restricted vocabularies, inadequate fine-grained discrimination, and vulnerability to noise and adversarial perturbations. To address these challenges, the research advances four complementary directions encompassing multimodal fusion, open-vocabulary recognition, robustness enhancement, and unified video–language modeling. First, a multi-modal prototype contrastive framework is proposed for fine-grained video classification, integrating visual and auditory cues through a transformer-based architecture and supervised contrastive learning with class …