Digital Commons Network^™

Transgenerational Impacts Of Covid-19: Exploring The Epigenetic Impacts Of Sars-Cov-2 Infection On Parental Reproductive Health And Offspring Development, Isaac Mckay Stirland

Theses and Dissertations

The mechanisms and consequences of SARS-CoV-2 infection, including clinical manifestations, immune response, pathogenicity, long-term sequelae, etc., have been studied in detail following the 2019 pandemic however, very little has been done to explore the interplay between SARS-CoV-2 and host DNA methylation. Given the role of DNA methylation in genetic regulation, genomic imprinting, and induction of transgenerational effects, an understanding of viral interaction(s) with the host methylome is imperative in promoting reproductive and developmental health. Numerous reports describe infections with similar pathogenicity to SARS-CoV-2 and their correlation to altered host tissues at the epigenetic, physiologic, and macroscopic level. These reported epigenetic …

A Century Of Depicting Characters With Disabilities In Newbery Award And Honor Books, Merna Kay Raines

Theses and Dissertations

A Century of Depicting Characters With Disabilities in Newbery Award and Honor Books Merna Kay Raines Department of Counseling Psychology and Special Education, BYU Educational Specialist Between 1922 and 2021, 426 books received the Newbery Award, with 64 books featuring characters with disabilities. However, it was not until 1931 that the Newbery Honor Award was given to recognize the author of a book featuring a character with disabilities. Newbery Award-winning books are considered quality literature and are found in most libraries and classrooms. Understanding the portrayal of characters with disabilities is important because students easily access these books. This content …

Enhanced Vapour Detection Through Electrospun Metal-Oxide Nanofibers, Sri Varshini K Ms

Theses and Dissertations

The objective of this work is to fabricate metal oxide-based nanofibers, which helps in monitoring indoor air quality, which is deteriorating due to VOCs like Formaldehyde, Toluene, and Ammonia, commonly found in paints, plywood, and adhesives. Prolonged exposure to these VOCs can affect the respiratory and nervous system. They are classified as carcinogens by the IARC.

Based on the analysis, this work was framed to deposit Fe2O3, NiO, and ZnO/Fe2O3 as well ZnO/NiO and Fe2O3/NiO nanofibers on the glass substrate through horizontal electrospinning method. The obtained nanofibers are vacuum annealed at 50 ℃ for 30 mins to remove the water …

Climate Change Policies And Good Governance In Egypt, Mahmoud Elshourbagy

Theses and Dissertations

Egypt recognizes the impacts of climate change and is particularly vulnerable because of its high-density population, economic burden and geographical location. In response, Egypt established National Climate Change Council in 2016. In 2022, the council issued “National Climate Change Strategy 2050” to integrate and align the efforts of government bodies to adapt and mitigate climate change risks. One of the strategic goals of “National Climate Change Strategy 2050” is to enhance climate governance in Egypt as a critical tool. This study attempts to evaluate climate change policies in the context of good governance by using a tool developed by World …

Design And Realization Of Concurrent Cryptosystem For Medical Image Privacy On Reconfigurable Hardware, Vinoth Raj R

Theses and Dissertations

The protection of medical image privacy plays a crucial role in maintaining confidentiality for the secure storage and transmission of patient’s sensitive healthcare data. Medical images are the widely used data type in the e-healthcare sector. Traditional cryptographic algorithms have limitations when applied to large-scale medical image datasets due to their high computational requirements. The primary goal of this research work is to design and implement indigenous algorithms to provide confidentiality for grayscale and color DICOM (Digital Imaging and Communications in Medicine) images through an encryption process. The research leverages the benefits of reconfigurable hardware, namely the Field-Programmable Gate Arrays …

Efficiency Of Enzyme Induced Carbonate Precipitation (Eicp) By Crude Extract Urease For Geotechnical And Geoenvironmental Applications, Kaniz Roksana

Theses and Dissertations

Geotechnical engineering is currently facing challenges, including accommodating rapid urbanization, adapting to climate change impacts, and prioritizing sustainability, all while ensuring the safety and stability of critical infrastructure. Biocementation is a recently developed new branch in geotechnical engineering that offers innovative and eco-friendly solutions by leveraging natural processes to enhance soil properties. This dissertation examines the potential of soybean extract urease as a cost-effective substitute for analytical-grade enzymes in Enzyme Induced Carbonate Precipitation (EICP) applications for biocementation. This research examines its effectiveness in various aspects, such as coastal erosion control, desiccation crack remediation, and the removal of heavy metals. Essential …

Lgbtq+ Identity Development And Individual Vs Group Psychotherapy Experience: A Consensual Qualitative Analysis, Aileen Marie Rands

Theses and Dissertations

Multicultural topics, such as LGBTQ+ experience, have accrued predominance within the field of psychology. It has become clear that better understanding minority experience is of utmost importance. Pervasive stigma, discrimination, and mistreatment culminate into minority stress; thus LGBTQ+ individuals face greater risk for poor mental health and seek out psychotherapy at higher rates. Despite this reality, limited psychotherapy research exists in this area generally and essentially no research has looking into the experience of LGBTQ+ individuals in group therapy. The current study investigated experiences of LGBTQ+ clients who have participated in both individual and group psychotherapy. Eleven participants were interviewed …

Mind Matters: Investigating The Impact Of Mental Health First Aid Training On High School Staff, Sarah Jo O'Neill

Theses and Dissertations

This dissertation, titled Mind Matters: Investigating the Impact of Mental Health First Aid Training on High School Staff, examines whether Mental Health First Aid (MHFA) training equips high school personnel with the necessary tools to identify and support students in crisis. Conducted over six weeks during a series of Kitchen Table Conversations, the study involved eight high school staff members who participated in a structured MHFA training program. Qualitative data collected from participant discussions revealed that while the current MHFA training format is a good start, it lacks school-specific contextualization. More importantly, the opportunity to discuss and process the material …

Sustainable Well-Being For Young Adults: An Online Course To Build Ecological And Psychological Flourishing In A Changing Climate, Jeremy Stanley Bekker

Theses and Dissertations

Sustainable well-being is "happiness that contributes to individual, community and/or global well-being without exploiting other people, the environment or future generations" (O'Brien, 2010, p. 2). Sustainable well-being education may encourage environmentally sustainable behavior while also teaching people how to live meaningful lives. However, there is currently a lack of research-based disseminable courses for teaching sustainable well-being. We hypothesized that taking the course would result in lower eco-anxiety and higher well-being, as well as increased pro-environmental self-efficacy and pro-environmental values. We used a randomized crossover repeated measures research design to assess pre and post effects. Quantitative results indicated that participating in …

Evaluating Learning Outcomes In A Serious Game: A Practical And Model Checking Approach, Matthew D. Douglas

Theses and Dissertations

This research introduces a novel computational framework to evaluate and predict the educational impact of serious games during development. By using finite state machines (FSM) and model-checking techniques, this study evaluates two serious games. Traditional evaluation approaches, often reliant on resource-intensive human trials, lack scalability and fail to provide early insight into the alignment of game mechanics with learning objectives. This study addresses these challenges of traditional evaluation methods.

Class Imbalance: A Landscape Of Classification Models, Joshua L. Edmonds

Theses and Dissertations

Class imbalance poses significant challenges in machine learning classification. This study evaluates the performance of seven models (ANN, k-Means, kNN, LDA, LR, SVM, XGBoost) across multiple imbalance levels (10\%, 5\%, 1 \%, 0.5\%) and investigates the effectiveness of sampling techniques (Undersampling, SMOTE, SMOTE-ENN). ANOVA results confirm that model choice is the most critical factor, with XGBoost and SVM demonstrating superior robustness. SMOTE improves recall but reduces precision, while undersampling generally degrades overall performance. While significant, imbalance levels do not play a critical role in model effectiveness.

Analyzing U.S. Army Recruiter Productivity Through Cohort Differentiation And Behavioral Tendency Composition, Mary M. Bates

Theses and Dissertations

This research analyzes differences among aggregate achievements of U.S. Army recruiting cohorts, determines which behavioral tendencies are indicative of performance level, and investigates aggregate behavioral composition with cohort achievement. Analyses require implementation of OLS regression, ANOVA, Tukey’s Test, Mann-Whitney U test, Holm-Bonferroni adjustment, XGBoost decision tree, logistic regression, and the Kolmogorov-Smirnov test. The results show insignificant achievement differences among cohorts and weak yet prevalent abilities of select measures of behavioral tendencies to indicate recruiter performance.

Improving Smartphone Gnss Jammer Localization With Cloud-Based Environmental Occlusion Modeling, Glenn H. Jones

Theses and Dissertations

The advancement of Global Navigation Satellite System (GNSS) technology in modern smartphones has made these devices pervasive in both civilian and military applications. Although smartphone GNSS chipsets are more susceptible to jamming and spoofing than military grade hardware, smartphone networks offer an underutilized opportunity to detect and mitigate threats to position, navigation, and timing (PNT) services essential to the Department of Defense (DoD) and civilian first responders. Traditional methods for geolocating ground-based jamming sources using smartphone GNSS often fail in environments with dense vegetation or significant occlusions, resulting in substantial localization errors.

Lethality And Survivability Of Autonomous Self-Sensing Uavs, Jeffrey T. Wilson

Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) have seen increased usage over the past two decades during the Global War on Terrorism (GWOT), operating in low-risk environments against dispersed enemies with minimal counter-drone capabilities. However, as the U.S. military shifts focus to Multi-Domain Operations (MDO) and Large Scale Combat Operations (LSCO), UAVs face significantly higher risks, including frequent and successful attacks, as well as the exploitation of their technology. Battle damage assessment (BDA) is not new; however, autonomous self-assessment by UAVs represents a novel advancement. Currently, UAV BDA relies on manual inspection, requiring approximately eight hours per drone. By adopting self-sensing technology, UAVs …

Evaluating Dry Air Personnel Decontamination Of Methyl Salicylate As A Chemical Agent Surrogate In Extreme Cold Environments To Reduce Airborne Risks Using A Manikin, Lance E. Campbell

Theses and Dissertations

This research investigated a mobile air shower as an alternative to water washing for personnel chemical decontamination in Arctic environments, where traditional methods like disrobing and rinsing are impractical. Interest in Arctic operations has grown with recent U.S. military focus on strategic advancements by Russia and China, yet research on air shower effectiveness for chemical decontamination remains limited. This study examined whether a commercial off-the-shelf air shower could effectively decontaminate methyl salicylate (MES), a surrogate for chemical warfare blister agents, from a manikin outfitted in military cold-weather gear. Researchers used a ppbRAE 3000 photo-ionization detector to measure MES concentrations following …

Simulating The Impact Of Self-Sensing Materials On Aircraft Sortie Generation, Harmoni J. Blackstock

Theses and Dissertations

In conjunction with the Air Force Research Laboratory Materials Lab(AFRL-RX), this study evaluates the potential military value of the prototype material sensing composites on Unmanned Aerial Vehicle (UAV) operations in intelligence, surveillance, reconnaissance (ISR), and close air support (CAS) missions within a contested Indo-Pacific theater. Using a Simio based simulation,UAV performance was assessed under varying combat conditions, focusing on Remote Sensing, deployment strategies, initial lay-downs, and varying loss rates. Re-sults show that UAVs equipped with Remote Sensing technology significantly improved sortie generation and logistical efficiency. Scenario 17 achieved the highest sortie rate(965.5 sorties), outperforming the next-best scenario by 25 sorties. …

Atmospheric Water Generation: Bacterial And Inorganic Chemical Quality, Garrett E. Stanley

Theses and Dissertations

This study investigated the quality of untreated water collected from a vapor compression-based atmospheric water generator (AWG) operated outdoors in Dayton, Ohio. The concentrations of bacterial and chemical constituents were determined. The concentration of culturable bacteria was between 200 and 2300 CFU/mL, significantly higher than the reference levels described in recreational and drinking water quality guidance. Three discrete bacteria phenotypes were visually identified; two were yellow in color, rod-shaped and gram-negative while the third was milky white, circular, and gram-positive. Chemical analysis on 15 randomly selected samples revealed the presence of Barium (average = 0.16 mg/L), Magnesium (0.08 = mg/L), …

Proof Of Concept: Using Uas Technology To Accomplish Aerial Roof Inspections, Madison R. Fanning

Theses and Dissertations

With the growing use of simulation across industries, the digital twin remains an underexplored research area, particularly in emergency management and response. Its real-time updating capability is often overlooked due to the misconception that "digital twin" is merely a complex term for simulation. This paper highlights its distinctiveness through an evasion exercise involving two independent entities in a collocated environment. Using a highly integrated virtual environment (HIVE) and internet of things (IoT) devices, we link the physical system with an analytical simulation, demonstrating the impact of lag times in high-pressure scenarios. The computational model leverages agent-based modeling (ABM) and discrete-event …

Proximal Policy Optimization Applied To The Beyond Visual Range Air Combat Maneuvering Problem, Daniel B. Joseph

Theses and Dissertations

Artificial intelligence (AI) grows ever-more important in warfighting. Emerging technologies allow for the use of AI to control aircraft and weapons systems. This research investigates the application of reinforcement learning (RL) through the Proximal Policy Optimization (PPO) algorithm to a two-versus-two (2v2) beyond-visual-range (BVR) air combat maneuvering problem (ACMP). Implemented in the Advanced Framework for Simulation, Integration, and Modeling (AFSIM), the methodology frames the engagement as a Markov decision process, wherein an autonomous RL agent learns continuous control decisions—throttle, pitch, roll, and yaw—under a cooperative communication scheme. A multi-phase curriculum-learning approach facilitates the progressive acquisition of flight stability, weapon deployment, …

Machine Learning Techniques To Predict Solar Particle Events And Radiation Of Aircrew, Haley Traub

Theses and Dissertations

Solar Particle Events (SPEs) are high-energy phenomena from the Sun that pose risks to technology, human health, and Air Force operations. Accurate prediction of SPEs exceeding 100 MeV is crucial for mitigating these risks. This thesis explores using Bayesian statistical models to predict such events, integrating prior knowledge from solar physics with the ability to update predictions based on new data. The research uses a dataset spanning three solar cycles (21–23) and incorporates attributes like flare fluence, peak flux, latitude, longitude, and class. Four Bayesian models (PyMC, Bnlearn, and two Dredge models) were compared to machine learning models. The Bayesian …

Evaluating Educational Benefits Of A Custom Cyber Game: ‘Hvac Attack!’, Jillian S. Valente

Theses and Dissertations

Cyber competition and conflict remain an enduring concern for the Department of Defense (DoD). Positive control of cyberspace is crucial across the vast diversity of military operations and supporting activities. Military members play an important role in cyber prevention, detection, and remediation, but most receive relatively little training outside of the annual Cyber Awareness Challenge. Particular career fields within the DoD may benefit from specialized training in cybersecurity, in particular the civil engineering (CE) community supporting critical infrastructure protection. Prior research has suggested that game-based learning (GBL) can be beneficial for teaching cyber concepts.

Machine Learning Techniques To Detect Anomalies In T-38 Flight Sensor Data, Sydney M. Wekamp

Theses and Dissertations

Accurate sensors are critical for ensuring the safety of aircrew. However, detecting faulty sensors remains a significant challenge for the Test Pilot School at Edwards Air Force Base in California. Current methods rely on either student pilots identifying anomalies or waiting for sensors to fail completely before repairs are made—an approach that lacks reliability and consistency. This research aims to address these shortcomings by implementing machine learning techniques to detect sensor faults proactively. To date, applying machine learning to a dataset of this size, encompassing numerous sensors on the same aircraft, is unprecedented. The project focuses on establishing strong baseline …

Forecasting Army Recruiting Mission Distribution, Maxwell A. Deihl

Theses and Dissertations

The Army’s recruiting landscape has changed markedly in recent years, raising questions about whether forecasting methods of Army contracts remain robust. This thesis recreates the presented models in Joshua McDonald’s 2015 thesis. It replicates and evaluates the models with updated data (2018–2023) to assess their current validity and compare them to novel alternative approaches, such as simpler regression models or neural networks. While the 2015 model remains a valuable baseline, results suggest that either refining its variables or adopting alternative methods can improve predictive accuracy and interpretability. Ultimately, the United States Army Recruiting Command has many options regarding how it …

Atmospheric Water Generation: Experimental Observations And Assembly Of An Artificial Neural Network, Houston Hoss Anderson

Theses and Dissertations

This research investigated the performance of a Tsunami T50 Vapor Compression Cycle styled Atmospheric Water Generation (AWG) machine operated under ambient conditions in Dayton, Ohio. Water yield from the device was measured volumetrically and these values are paired with respective weather data, collected from a local monitoring station, to build an Artificial Neural Network in MATLAB and JMP software. Water yield varied over the course of this study but averaged 1.2L and maxed at 5L for 4-hour operating periods. This work is part of a 3-year project; future data is needed to enhance both training and validation of the model …

Tracking News Narratives: Topic Modeling, Sentiment, And Media Coverage Patterns, Alexandria G. Lai

Theses and Dissertations

This study introduces a novel content-driven influence measurement framework, built around a custom influence formula that integrates Non-negative Matrix Factorization (NMF) topic modeling, sentiment analysis, and influence metrics to analyze media narratives over time. Applied to news coverage of the 2020 U.S. presidential election and the COVID-19 pandemic, the framework identifies key topics, sentiment patterns, and influential sources. Results demonstrate its ability to distinguish between transient political controversies and sustained public health discourse while capturing shifts in media influence. While effective, refinements in topic separation, sentiment analysis, and temporal weighting could enhance adaptability. This study highlights the novel influence formula …

Molecular Scale Investigations Of Interactions Between Pfas And Concrete, Eric E. Keeler

Theses and Dissertations

Per- and polyfluoroalkyl substances (PFAS), widely referred to as “forever chemicals,” exhibit high environmental persistence and potential health risks due to their robust carbon-fluorine bonds. These substances are prevalent in aqueous film-forming foams (AFFF), used in industrial and military applications, and are known to contaminate environmental surfaces, including concrete. This study aims to characterize the molecular-level interaction energies of six PFAS species—PFOA, PFOS, PFHxS, PFHxA, 6:2 FTS, and PFBS—with calcium silicate, a key component of concrete, using density functional theory (DFT) calculations. Change in Gibbs free energy (ΔG) was determined for each of the interactions, revealing negative ΔG values for …

Autonomous Vehicle Path Planning Under Uncertainty, Madison C. Gillan

Theses and Dissertations

Autonomous vehicles are increasingly being deployed for use in high-stakes and uncertain environments where safe and efficient navigation is critical. In these scenarios, traditional path planning approaches, which rely primarily on deterministic models and fixed assumptions, fall short due to the inherent uncertainty of dynamic threats, sensor inaccuracies, and incomplete information. This research addresses these challenges by developing a novel path-planning methodology that combines the Chance-Constrained Rapidly Exploring Random Tree* (CC-RRT*) algorithm with a probabilistic risk assessment heuristic. This method models uncertainty in sensor detection zones, obstacles in the environment, and the Autonomous Vehicle itself, which allows for uncertainty during …

Data Lakehouse And Machine Learning Pipeline For Aircraft Fuel Efficiency Experimentation, Skyler G. Kepley

Theses and Dissertations

Fuel efficiency is crucial for the U.S. Air Force, impacting mission success, aircraft performance, and cost savings. This study presents an information system that integrates flight and maintenance data using a data lakehouse. It automates ingestion, enrichment, and predictive modeling, leveraging AutoML for optimization and SHAP for transparency. A case study on C-130J aircraft shows that optimizing D Check cycles can save 11.52 pounds of fuel per flight hour. These findings highlight the effectiveness of data-driven decision-making in aviation, offering a scalable, automated solution for improving fuel efficiency and reducing costs.

Island Nation Duress: Simulating Passive Peer-To-Peer Bluetooth Communication During Disaster Relief, Jason K. Medeiros

Theses and Dissertations

Pacific Islands under U.S. jurisdiction are highly vulnerable to natural disasters, yet many lack the infrastructure to effectively respond and recover. Clear communication during and after such events is critical for evacuation, hazard awareness, and first responders’ coordination. This research explores a simulation-based approach using Bluetooth communication to relay messages across Guam, assessing its efficiency through statistical analysis. By examining regional differences and geographic impacts on Bluetooth messaging, the study aims to identify key factors that enhance peer-to-peer communication for timely and effective disaster response.

Job Demands And Resources: A Look At The Vha Workforce To Support Dod Goals, Anthony J. Rivera

Theses and Dissertations

This study investigates the relationships between job demands, job resources, burnout, turnover intention, and workplace attitudes among employees of the Veterans Health Administration (VHA) through the lens of the Job Demands-Resources (JD-R) model. The findings reveal both expected and novel insights. Consistent with prior research, the study confirms that excessive job demands, without enough resources to balance then, lead to burnout. This, in turn, increases turnover intention and negatively affects how employees view leadership and the work environment. A significant discovery, however, challenges conventional assumptions: favorable job demands were positively correlated with turnover intention, suggesting that employees in favorable roles …