Improving Early Detection And Response To Clinical Deterioration Among Nurses Through Competency-Based Interventions, Courtney E. Miller

Doctor of Nursing Practice (DNP) Scholarly Projects

Problem: Clinical deterioration among hospitalized patients remained a significant contributor to preventable morbidity and mortality, often due to delayed recognition and response in general care settings (Choi et al., 2025; Chung & Jung, 2024).

PICOTS: For registered nurses working on a general level of care inpatient hospital unit (P), how did a competency-based training program bundle incorporating didactic educational intervention of learning how to use technology, machine learning (ML) based early warning system (EWS) of trends and patterns to identify at risk patients, and low-fidelity simulation-based education (SBE) (clinical readiness to improve confidence with education and coaching) (I), …

Implementing A Standardized Resilience Bundle For Neonatal Intensive Care Nurses, Jennifer Bouzid

Doctor of Nursing Practice (DNP) Scholarly Projects

Background: Nurse resilience is associated with improved psychological well-being, professional satisfaction, and retention. Neonatal intensive care unit nurses are frequently exposed to emotionally traumatic clinical events that may contribute to burnout, compassion fatigue, and turnover. A women’s hospital in central Texas identified increased nurse turnover and lower employee engagement scores related to well-being and intent to stay within the neonatal intensive care unit.

Purpose: The purpose of this quality improvement project was to implement and evaluate a standardized resilience support bundle for nurses following traumatic clinical events.

Methods: Guided by the Plan-Do-Study-Act framework, the project implemented a resilience bundle that …

A Quality Improvement Project: Nurse-Led Nutritional Support To Reduce Missed Chemotherapy Appointments, Eva Balboa

Doctor of Nursing Practice (DNP) Scholarly Projects

Introduction/Background

Malnutrition affects approximately 43% of cancer patients nationally and is associated with missed chemotherapy appointments, treatment interruption, and poor clinical outcomes. At a 30-chair outpatient cancer center in South Texas, a retrospective chart review revealed that 45% of patients experienced malnutrition-related symptoms contributing to appointment disruptions. Despite evidence-based recommendations for routine nutritional screening and support, no standardized protocol existed at this site.

Objectives

 The purpose of this quality improvement project was to implement a nurse-led nutritional support protocol and evaluate its effectiveness in (1) reducing the missed chemotherapy appointment rate from 10% to 5%, (2) achieving 100% compliance with …

A Guideline For Underserved Adult Residents In Need Of Affordable Transportation Access To Healthcare, Tammie E. Walker

Doctor of Nursing Practice (DNP) Scholarly Projects

Background

During the development of the 2022 Tarrant County Public Health Community Health Assessment, two gaps were identified that contribute to disparities: transportation and access to healthcare in areas of high need (Y. M. Wingate, Ed.D., Community Health Assessment Division Manager, Tarrant County Public Health, personal communication, June 20, 2025). As of 2017, 5.8 million individuals reported delaying medical care due to a lack of accessible transportation in the U.S. (Wolfe et al., 2020). The National Health Interview Survey (NHIS) of 2022 reported that 5.9% of residents living in the West South-Central region, which includes Texas, found that, within the …

Presidential Slaves: The Story Of Black People In The Lives Of Antebellum U.S. Presidents, Nika Davis

History Dissertations

The historical narrative about American slavery included many topics such as the African slave trade, the Middle Passage, slave culture, rebellions, religion, and abolition.  This study revealed more information to be examined in the record of American slavery relating to the presidents of the United States and their enslaved laborers.  This oversight proved prevalent during the years leading to the American Civil War from 1820-1860.  Therefore, this dissertation focused upon the enslaved and free Black people who intersected with the presidents and their friends, political acquaintances, and family.  By studying their lives, this dissertation revealed that the slaves associated with …

Comprehensive Analytical Investigation Of Tetrahydro-4h-Chromene And Dihydropyridine Derivatives, Ryan J. Burk

Chemistry & Biochemistry Dissertations

Novel calcium channel blockers (CCBs) with dihydropyridine (DHP) or tetrahydro-4H-chromene moieties are often chiral, so effective enantiomer separation methods are needed for continued drug development. The purpose of this dissertation is to outline a comprehensive method development model for the chiral separations of DHPs and tetrahydro-4H-chromene derivatives. The scope of this dissertation is to address analytical challenges during initial synthesis, chiral separations, and data analysis during post-processing for this class of chiral compounds. The first section focuses on the method development strategies for separations of DHPs in the sub/supercritical fluid (SFC) and normal phase modes with the 2-hydroxypropyl-β-cyclodextrin stationary phase. …

Novel Methods For Environmental Fluoride Measurement, Cable Warren

Chemistry & Biochemistry Dissertations

Fluoride analysis has been an important focus of analytical analysis for many years and will continue to be so going forward. Today, fluorinated compounds, specifically per/polyfluoroalkyl substances (PFAS), better known as “forever chemicals” have captured the moment and are the subject of vast research and regulation. Under this context, I have researched new methods of fluoride separation and concentration in complex media as well as a novel method of PFAS destruction and total organic fluorine analysis for screening of PFAS in aqueous samples. Through research and work on micro-scale detection methods, an understanding of the state of the art and …

Characterization Of The Human Thnatomicrobiome By Decomposition Stage Through Bioinformatic And Meta Data Analysis, Ashton C. Laughlin

Biology Theses

Estimating the postmortem interval (PMI) is one of the most crucial factors in forensic death investigations. Recent advances in forensic microbiology have led to increased interest in using the study of the human postmortem microbiome, or “thanatomicrobiome,” to improve PMI estimates. In addition to current PMI estimation techniques, microbial community succession could serve as a valuable tool in estimating PMI. Further research is needed to develop a comprehensive understanding of the human postmortem microbiome. The purpose of this study is to contribute to the expansion of this tool by reviewing the current literature and analyzing previously published data using the …

Adversarial Robustness In Biomedical Time-Series Models, Rohan Tiwari

Bioengineering Theses

This study investigates adversarial vulnerabilities in deep learning models for biomedical time-series classification across two clinically important modalities: electrocardiography (ECG) and electroencephalography (EEG). Using the MIT-BIH Arrhythmia and CHB-MIT seizure datasets, I evaluate time-domain attacks (FGSM, PGD), Fourier-domain constrained attacks, and learned spectral perturbations designed to reveal modality-specific sensitivity patterns. Across both tasks, a consistent trend emerges low-frequency components (0–5 Hz) constitute a dominant axis of adversarial vulnerability, with perturbations in this range producing the steepest degradation in classification performance. In ECG models, protecting the physiologically relevant QRS band (5–20 Hz) significantly improves robustness, whereas EEG models remain highly sensitive …

Risk Factors Of Child Sex Trafficking: A Gender-Based Scoping Review In The U.S. And Cross-Border Contexts, Peyton Forbes

Social Work Theses

Child sex trafficking is a major public health issue affecting the youth population of the United States and internationally. This scoping review examines risk factors on multiple levels including individual, family, community, and macro and digital contexts. A systematic search of databases identified 32 studies meeting inclusion criteria. Findings suggest that individual-level risk includes cumulative exposure to violence and trauma, substance use, mental health and behavioral problems, child welfare and justice involvement, runaway behavior, educational disruption, limited social support, and intersection demographic vulnerabilities (e.g., gender, sexuality, race/ethnicity, disability). Family‑level risk reflects unstable or unsafe home environments characterized by substance use, …

Women’S Exposure To Incel Content, Perceived Safety, And Gender-Based Violence Risk In The United States, Deja Bledsoe

Criminology & Criminal Justice Theses

The rapid proliferation of incel-related content across digital platforms has raised concerns about online misogyny and its potential impact on women’s perceived safety. However, less is known about how exposure to such content shapes women’s perceptions of risk and emotional responses in everyday digital environments. This study examines the relationship between exposure to incel-related content and women’s perceived risk of gender-based violence and safety-related anxiety. Guided by strain theory, social control theory, hegemonic masculinity, and intersectionality, the study employs an anonymous cross-sectional online survey of women aged 18 and older. Quantitative analyses were conducted to assess whether exposure to incel-related …

Evaluating The Robustness Of Gnn-Based Vulnerability Detectors Under Semantics-Preserving Code Obfuscation, Jesse Ks Chumo

Computer Science and Engineering Theses

Graph neural network–based vulnerability detectors are typically evaluated on clean benchmark datasets, yet real-world code frequently undergoes semantics-preserving transformations such as identifier renaming, dead-code insertion, and control-flow restructuring. The extent to which such transformations affect detector reliability remains insufficiently understood. We evaluate ten vulnerability detectors from four architectural families across the Devign, Big-Vul, and DiverseVul datasets. To quantify robustness, we evaluate each model at three transformation budgets: one transform, two transforms combined, and all three together, finding that token-based models degrade under identifier renaming and compound transformations, while models that read only code structure are largely unaffected. We further evaluate …

A Productivity Rate-Based Comparative Carbon Footprint Cost Analysis Of Small To Large-Sized Open-Cut Pipeline Installation Activities For Sanitary Sewerage Construction: A System Boundary Concept, Amir Reza Zakeri

Civil Engineering Theses

Underground sanitary sewer pipelines are essential components of urban infrastructure; however, open-cut pipeline installation requires excavation, bedding preparation, pipe placement, backfilling, embedment, and compaction activities that rely heavily on construction equipment and fuel consumption. As a result, open-cut installation can generate measurable greenhouse gas emissions during the construction phase. With increasing attention to sustainable infrastructure delivery, there is a need for a consistent approach to quantify construction-phase carbon footprint and convert those emissions into a comparable economic indicator. Accordingly, this thesis aims to create and apply a productivity rate-based calculation framework for estimating and comparing construction-phase CO₂e emissions and carbon …

Towards Application-Driven Optimal Memory And Storage Management, Venkata Naga Prajwal Challa

Computer Science and Engineering Dissertations

Modern computing systems increasingly run on diverse hardware platforms and support applications with widely different access patterns, performance goals, and data lifecycles. In this setting, traditional one-size-fits-all approaches to memory and storage management are often inefficient because they apply fixed policies regardless of application behavior, workload context, or hardware asymmetry. Such generic designs can lead to unnecessary data movement, wasted bandwidth, excessive rewriting, poor resource utilization, and degraded user-perceived performance. This dissertation is motivated by the view that optimal memory and storage management should be application-driven: instead of treating all data uniformly, systems should adapt their decisions to how applications …

Development Of Multimodal Measurements And Analysis For Early Detection Of Alzheimer’S Disease, Fiza Saeed

Bioengineering Dissertations

Alzheimer's disease (AD) is the leading cause of dementia, and existing diagnostic methods such as PET scans, cerebrospinal fluid sampling and biomarker quantification, and gene sequencing are all either invasive, costly, or not sensitive enough for early detection. This dissertation introduces three different studies that develop a novel multimodal, non-invasive approach to diagnosing AD at its early stages by combining broad band near infrared spectroscopy (bbNIRS) and electroencephalography (EEG) technologies.

The first study showed cerebrovascular-cerebrospinal fluid coupling (CBV-CSF), which is measured by using 2-channel bbNIRS as an indicator of brain aging and early AD. Linear correlations between total blood (Δ[HbT]) …

Autonomous Uav Mission Planning Under Threat Using Model Predictive Control With Proportional-Navigation Pursuers, Mehmet B. Ozcelik

Mechanical and Aerospace Engineering Theses

Autonomous unmanned aerial vehicles (UAVs) operating in contested environments must

complete mission objectives while avoiding restricted regions, radar exposure, and pos-

sible interception. This thesis develops a MATLAB-based simulation framework for

two-dimensional UAV mission planning under threat using model predictive control and

proportional-navigation chasers. The mission requires the UAV to travel from a start

location to a goal while visiting required checkpoints and avoiding no-fly zones and radar

regions. A chaser attempts to intercept the UAV using either a basic pure-pursuit-style

law or a proportional-navigation guidance law.

The framework integrates environment generation, augmented visibility-graph rout-

ing, waypoint management, UAV kinematic …

Llm-Driven Closed-Loop Uav Control With Obstacle-Aware Model Predictive Control, Halimcan Yasar

Mechanical and Aerospace Engineering Theses

This thesis presents a closed-loop control architecture for uncrewed aerial vehicles (UAVs) in which a large language model (LLM) serves as a high-level decision module operating over a persistent, metric 3D world model.

Rather than generating low-level commands or open-loop plans, the LLM selects one parameterized maneuver per decision step from a small, verified library of flight primitives conditioned on a structured representation of the drone state, tracked object positions, and mission specification.

Translational motion is executed by a planar model predictive controller (MPC) with soft obstacle avoidance, using obstacle hypotheses provided by the LLM, so that safety-critical constraint handling …

Guideline For A Burnout Bundle For Nurses In Psychiatric Mental Health Units, Festus Irabor

Doctor of Nursing Practice (DNP) Scholarly Projects - Archive

Abstract

Problem: Burnout among nurses, especially in psychiatric mental health units, significantly impacts both their well-being and the quality of patient care. Despite its severity, with approximately 30% of nurses worldwide affected and contributing to a 31.5% nurse turnover rate (Ge et al., 2023), there are limited formal guidelines specifically targeting nurse burnout prevention in the mental health setting. The issue is particularly acute in the United States, where 91.1% of psychiatric nurses report experiencing burnout, compared to 79.9% of other healthcare professionals (Anger et al., 2024). In the local unit 38.05% have experienced burnout.

Purpose: The PICOTS for this …

Iron Deficiency And Iron Deficiency Anemia: Inconsistent Screening Practices And Delayed Result Processing In Children 12-18 Months, Madonna J. Mahoney Marshall

Doctor of Nursing Practice (DNP) Scholarly Projects - Archive

Introduction:

Iron deficiency and iron deficiency anemia in children aged 12 to 18 months are prevalent conditions that, if not identified and treated early, are associated with adverse neurodevelopmental outcomes.

Purpose:

This quality improvement project evaluated the impact of a standardized screening and follow-up protocol on laboratory result retrieval, provider review, and caregiver follow-through in a military pediatric clinic.

Method:

A pre-post intervention design guided by the Plan-Do-Study-Act framework was implemented over 11 weeks and included staff education, standardized workflows, and caregiver outreach.

Results:

The intervention improved laboratory completion and caregiver follow-up rates; however, sustainability was limited by staffing constraints …

A Study Of Adaptive Reuse Of A Decommissioned Golf Course Through A Nature-Based Approach: Woodhaven Golf Course, Fort Wort Texas., Justin B. Watson Mr.

Landscape Architecture Masters & Design Theses

Across the nation, golf courses are shutting down due to a lack of demand. Golf course developments began in the United States in the early 1950s During that era, demand for golf courses and housing was high. As golf’s popularity grew, developers saw golf courses in developments as high value-add amenities (Grooms, 2010). During the late 1990s and early 2000s, developers across the country raced to construct as many golf course communities as they could even as the number of golfers leveled out (Downey,2011).

Decommissioned golf courses across Texas are being underutilized as potential amenities for both the local community …

Buckling Analysis Of Auxetic Composite Laminates And Optimal Design Using Lamination Parameters And Machine Learning, Hans Bendon Maria Tamil Selvan

Mechanical and Aerospace Engineering Theses

Composite materials are widely used as structural panels in aerospace, automotive, and civil engineering applications, where buckling is often a critical failure mode. This thesis focuses on the analysis and design of composite laminates that maximize buckling performance under prescribed stiffness and thickness constraints.

The first part of the study investigates the buckling behavior of auxetic laminates, which exhibit a negative Poisson's ratio. While previous studies suggest that auxetic laminates can achieve higher critical buckling loads than non-auxetic laminates under simply supported boundary conditions with lateral restraint, the influence of other boundary conditions and plate aspect ratios has not been …

Investigating Sex Differences In The Regulation Of Conditioned Morphine Reward By Orexin, Farzana Akter Koly

Psychology Theses

Strong activation of the brain’s reward circuitry by morphine and morphine-associated cues drives the progression toward morphine abuse. Additionally, orexin neurons in the lateral hypothalamus (LH) are activated in response to cues paired with morphine reward. The orexin system, particularly the orexin-1 receptor (OX1R) regulates reward-seeking behavior through its activation. Despite the well-established role of orexins in reward-related behaviors, the specific contribution of OX1R in morphine-associated reward remains unclear. Furthermore, while sex differences in drug reward and reward-related behaviors are well documented, they remain unexplored in the regulation of morphine-associated reward by orexins. To address this gap, the present study …

Characterizing Gut Microbial Communities And Symbiont-Mediated Detoxification In Herbivorous Insects, Rachel C. Vargas

Biology Dissertations

Insect gut bacteria are vital contributors to host physiology, yet the broader prevalence and fitness implications of symbiont-mediated detoxification remain poorly understood. This thesis investigates these dynamics across three research chapters. Chapter 1 uses 16S rRNA sequencing to characterize how grasshopper gut microbial communities vary across species, dietary breadths, and gastrointestinal segments. Chapter 2 evaluates the detoxification capacity of over 150 bacterial isolates from diverse herbivores against the plant allelochemicals phenethyl isothiocyanate, rutin, and chlorogenic acid to determine if host dietary specialization predicts microbial metabolic ability. Finally, Chapter 3 employs fitness bioassays to test whether inoculating generalist herbivores with detoxifying …

Sewer Pipe Condition Assessment Using An Ensemble Machine Learning Framework For Infrastructure Decision Support, Mahnaz Rouhi

Civil Engineering Dissertations

Aging wastewater infrastructure presents significant challenges for municipalities across the United States, with many sewer networks approaching or exceeding their design life. Conventional inspection methods, such as closed-circuit television (CCTV), are limited by subjectivity, cost, and inefficiency. To address these challenges, this study develops an ensemble machine learning framework for assessing the structural condition of sewer pipelines using inspection records enriched with geospatial attributes.

The primary objective of this research is to enhance predictive accuracy, interpretability, and decision-support for risk-based asset management. The scope of the study encompasses 4,802 CCTV inspection records from Dallas, TX, and Tampa, FL, integrating physical, …

Videoscoop: A Non-Traditional, Domain-Independent Framework For Video Analysis, Umme Hafsa Billah

Computer Science and Engineering Dissertations

Due to the proliferation of cameras in handheld devices and the widespread use of CCTV, images and videos have become a preferred alternative for capturing and disseminating information. Automated analysis for understanding image or video contents (e.g., objects, activities, backgrounds, situations of interest, etc.) is critical for many applications such as Civic Monitoring, Surveillance (in general), monitoring activities in Assisted Living environments, and many more. Image and Video Analysis (IVA) research has been ongoing for several decades, resulting in numerous techniques for algorithmically analyzing and understanding image and video contents.

Image Analysis (IA) has advanced in several areas, including object …

Deep Learning For Wireless Communications, Swarada Ajit Kulkarni

Electrical Engineering Dissertations

The rapid evolution of wireless communication imposes stringent requirements for ultra-reliable, low-latency transmission in dynamic, interference-prone environments. Traditional model-driven signal processing struggles to adapt to nonlinear hardware effects, time-varying channels, and complex interference patterns. Deep learning (DL) offers a transformative, data-driven alternative, enabling end-to-end optimization and robust adaptation under uncertain propagation conditions.

This dissertation investigates deep learning architectures for intelligent and resilient wireless communication through three complementary contributions. The first introduces a Vision Transformer (ViT)-based modulation classification framework that leverages self-attention to capture local and global dependencies in spectrogram representations of Quadrature Amplitude Modulation (QAM) signals. The ViT achieves superior …

Adolescent Girls’ Experiences Of Digital Dating Abuse Through Social Media: A Scoping Review, Kiara E. Rodriguez

Social Work Theses

Teen dating violence (TDV) is a prevalent adverse childhood experience with lasting psychological and behavioral consequences. As adolescents increasingly engage with social media, with 95% of teens aged 13-17 reporting using it, digital spaces have become a significant context in which dating abuse can occur. Digital dating abuse (DDA) refers to patterns of abusive behaviors that are directed toward a dating partner through digital technologies, including social media and mobile phones. Despite the growing role of social media in adolescent relationships, research on how adolescent girls experience DDA in these contexts remains limited. The central question for this scoping review …

Using L1-Magic For Feature Enhancement And Reduced Redundancy In Hyperspectral Data, Ashley Alfred

Mathematics Dissertations

Hyperspectral imaging offers detailed spectral information, but achieving high spatial resolution typically requires large and expensive equipment. This study explores an alternative approach: enhancing low-quality hyperspectral bands using an L1-norm minimization technique known as L1-magic. The goal is to improve the utility of low-cost hardware by preserving discriminative features, promoting sparsity, and reducing spectral redundancy. We apply L1-magic to enhance low-quality bands and hypothesize that this method selectively amplifies key features while suppressing redundant information. Experimental results indicate that the enhanced bands approach the quality of high-resolution data, enabling robust feature extraction without reliance on high-end hyperspectral cameras.

Understanding Motor Competence In Autism And Developmental Coordination Disorder: From Everyday Performance To Underlying Postural Control Mechanisms, Crystal E. Alvarez

Kinesiology Dissertations

Motor competence plays a foundational role in children’s participation, physical activity, adaptive behavior, and overall quality of life. Although motor difficulties are highly prevalent in autism spectrum disorder (autism) and developmental coordination disorder (DCD), these challenges are frequently under-identified and insufficiently characterized, particularly in autistic populations. Existing research demonstrates substantial overlap in motor challenges across autism and DCD; however, relatively little work has integrated caregiver perceptions, standardized motor assessment, and mechanistic postural control measures within the same investigation. Therefore, the purpose of this dissertation was to examine motor competence and postural control in autistic children, children with DCD, and neurotypical …

Ultra-Low Noise Ion Detection For Neutrinoless Double Beta Decay Searches, Karen E. Navarro

Physics Dissertations

Neutrinos are the most abundant particles in the universe that carry mass. Yet, we know very little about them since they are electrically neutral and interact weakly. A small instance after the Big Bang, an imbalance occurred that caused matter to be produced in greater quantities than antimatter. A leading candidate for this unexplained process is leptogenesis. Leptogenesis predicts that neutrinos are Majorana particles: a particle that is its own antiparticle. Today, particle detectors are being constructed to search for this property through the yet unobserved neutrinoless double beta decay (0νββ) . If observed, this would demonstrate that neutrinos are …