Doctoral Dissertations

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Burnout in the Trenches: Unpacking the Systemic Forces Impacting Community Mental Health Clinicians
Fennell, Tiara Monet (Virginia Tech, 2025-04-22)
Across United States (US) history, individual and population-based mental health has been overlooked or outright dismissed within the health care system. In 1955, 77% of all mental health treatment episodes took place in an inpatient setting, and only 379,000 episodes of treatment were provided in outpatient settings. By 1968, the number of inpatient treatments increased to two million. By 2010, Glied and Frank (2016) estimated that the US spent an estimated $352 billion to provide care and support to people with mental illness. However, even with the large investment from the government, the number of patients needing care outnumber the number of clinicians who can provide care. Due to financial strains as well as increased demands for services, clinicians are experiencing their own problems (e.g., emotional exhaustion, lower job satisfaction, diminished self-concept, and a loss of concern for clients), which are symptoms of burnout. Given the systemic impact that a clinician's experience can produce on the provision of mental health services, it is critical to explore the experiences of community mental health (CMH) clinicians directly in order to inform changes in policy and practice in CMH. Thus, the purpose of this interpretative phenomenological study is to explore the experiences of CMH therapists and how they confront burnout. Through the additional lens of the Mental Health Systems Ecology (MHSE) model, the systemic nature of CMH will be highlighted to identify opportunities for mental health service reform and improved therapeutic interventions. Findings from this study revealed three major themes: exploitation, referring to the structural and systemic pressures that place undue burdens on CMH clinicians; ethical and moral dilemmas, highlighting the difficult decisions therapists must navigate when balancing client care with institutional constraints; and grounded in purpose as a form of resilience, illustrating how clinicians find meaning in their work to sustain themselves despite ongoing challenges. These themes underscore the need for systemic changes in CMH settings to mitigate burnout and support clinician well-being.
Ethical Leadership in the Age of Accountability: Principals' Perceptions of Ethical School Accountability
Faaborg, Ashley Hart (Virginia Tech, 2025-04-22)
This dissertation explored the intersection of ethical leadership theories and the economic neoliberal underpinnings of school accountability processes through the lens of middle school principals in Virginia. A synthesis of Shapiro and Stefkovich's ethics of the profession framework was applied to evaluate the history of accountability legislation in terms of ethical decision making. A comprehensive literature review of school accountability and state assessment was synthesized into a novel framework, the Critical Associative Factors of Ethical Accountability (CAFEA), which served as the analytical foundation for the study. Qualitative research was conducted with a diverse array of middle school principals across Virginia that examined principals' perceptions of ethical school accountability using a coding system grounded in the CAFEA framework. Data analysis was conducted using a combination of a priori coding, second cycle coding, and theming the data to identify common themes and patterns. The findings reveal the ethical values of principals, the conceptualization of their role as ethical administrators in accountability, and a pattern in their perception based on their school's socio-economic status (SES). An argument is presented in this study for the integration of four key ethical components (context, veracity, clarity, and empowerment) as essential elements of a student-centered school accountability model. By prioritizing these components, policymakers can demonstrate ethical leadership that places students' well-being at the forefront of educational policy and practice.
Understanding and Mitigating Data-Centric Vulnerabilities in Modern AI Systems
Zeng, Yi (Virginia Tech, 2025-04-18)
Modern artificial intelligence (AI) systems, trained on vast internet-scale datasets, demonstrate remarkable performance and emergent capabilities. However, this reliance on large datasets that are expensive or difficult to quality-control exposes AI systems to critical vulnerabilities, including data poisoning, backdoor attacks, and subtle human-exploitation vectors. This thesis addresses these challenges through a comprehensive data-centric perspective on AI security. First, we examine backdoor attacks in the frequency domain, revealing that many triggers exhibit characteristic high-frequency artifacts that can be leveraged for detection while informing the design of more effective defenses. However, we also show that high-frequency signatures are not a necessary property for successful backdoor attacks, which motivates a deeper investigation into their fundamental mechanisms. Building on the insight that all effective backdoor attacks, regardless of design, divert models from their correct outputs, we formulate backdoor removal as a minimax optimization problem and develop I-BAU (Implicit Backdoor Adversarial Unlearning), an efficient algorithm that outperforms existing defenses across diverse attack settings. As AI systems evolve toward large foundation models, so too must our security approaches, leading us to extend our focus to safety backdoors in large language models, where we introduce BEEAR (Backdoor Embedding Entrapment and Adversarial Removal), which mitigates such vulnerabilities by identifying and counteracting universal embedding patterns associated with backdoor behavior. Beyond technical vulnerabilities like backdoor attacks and data poisoning, we discover that even safety-aligned models exhibit an emergent susceptibility to human persuasion techniques, prompting us to explore how social influence strategies can be weaponized to manipulate AI systems, developing a taxonomy of persuasion-based vulnerabilities that bridges technical security and human-computer interaction. Collectively, these contributions advance our understanding of data-centric security risks and provide practical mitigation strategies applicable across the AI development pipeline. By addressing both technical vulnerabilities and human-centered attack vectors, this work aims to facilitate the development of more robust and trustworthy AI systems suitable for deployment in critical applications.
Transforming Architectural Practice Through Computational Design and Machine Learning: A Decision-Support Framework for Energy and Daylight Optimization
Al Radaideh, Tamer Saleh (Virginia Tech, 2025-04-16)
Architectural design requires balancing aesthetic goals, functional needs, and environmental performance, often involving complex trade-offs. This research integrates machine learning and computational design to optimize building enclosure design, focusing on energy efficiency and daylight performance in Jordan's climatic conditions. Among the tested models, Artificial Neural Networks (ANN) proved the most effective, excelling in identifying critical design features and uncovering hidden influences among variables such as material properties and glazing systems. The findings demonstrate that machine learning can support architects in exploring design possibilities and understanding trade-offs, while ensuring they retain the final decision-making authority. By highlighting interactions that conventional methods might overlook, this approach allows architects to tailor materials and structures dynamically, optimizing performance without compromising design goals. Though cost analysis was not directly included, the framework sets the stage for its integration in future studies, enabling even more comprehensive decision-making. The results emphasize that design solutions should be adaptive, allowing different walls or façades to have unique material and structural configurations. This flexibility helps architects achieve efficient, context-specific designs that align with sustainability goals. By leveraging machine learning, this research bridges the gap between creative design and performance-driven optimization, offering a practical framework for innovative architectural practices.
Effects of Human Emotions, Robot Reliability, and Team Hierarchy on Human-Robot Interaction
Dong, Jiayuan (Virginia Tech, 2025-04-09)
Social robots gradually become a vital part of human lives as they can assist humans in complex tasks. To enhance the effectiveness and user acceptance of human-robot interaction (HRI), it is critical to understand what factors could improve human trust in robots. This dissertation builds on an existing framework of human-related, robot-related, and environmental factors in human-robot trust. Emotions, a human-related factor, have been discovered to have critical impacts on HRI, but research has focused more on robots' emotional expressions than user emotions. To bridge this research gap, three human-centered studies were conducted in the present dissertation investigating the impact of users' emotions (happiness and anger) along with robot reliability (robot-related) and team hierarchy (environmental factor) on their trust toward robots in a collaborative setting, an escape room, with a social robot, Pepper. Additionally, user perceptions, perceived workload, and task performance were also measured in the dissertation. The experimental setting and procedures for the three studies were similar. To induce participants' emotions, they were asked to write down their emotional experiences regarding the assigned emotions (anger vs. happiness) for 12 minutes, then solve puzzles in an escape room with Pepper. An emotional manipulation check was completed by the participants by filling out an emotional evaluation survey three times: before the induction, after the induction, and after the completion of the escape room. In addition, user perceptions, trust, perceived workload, and task performance were also collected through validated questionnaires and observations. Study I focused only on the effect of human emotions, anger and happiness (N = 46), suggesting that happy participants rated the robot agent as significantly more likable, safer, and more comfortable, while angry participants complied significantly but fewer succeeded. Among those who failed, angry participants showed higher cognitive trust in the robot. Study II (N = 86) explored emotion and robot reliability (high vs. low) with a between-subjects design. Happy participants rated the robot as more anthropomorphized, intelligent, and likable, with higher trust. Participants in the high-reliability condition perceived better performance, complied more, and responded faster than the participants in the low-reliability condition. Study III (N = 52) investigated emotion and team hierarchy (human-follower-robot-leader vs. human-leader-robot-follower) with a mixed-subjects design. Participants in the follower role perceived the robot as less responsive but complied more. Angry participants perceived the robot as more capable of constructive responses than happy participants while happy participants showed significantly more verbal interactions with the robot. An interaction between emotion and hierarchy was shown for social presence and perceived performance. Interviews highlighted the role of emotions and hierarchy in user perception, decision-making, emotional changes, and responsibility for team success or failure. In conclusion, the results underscored the importance of user emotions, robot reliability, and team hierarchy in shaping user perceptions and trust in robots and task performance, providing valuable theoretical and practical implications for emotions in HRI.
Expanding the Geographical Footprint of CO₂ Storage through Numerical Investigations of Industrial-Scale Carbon Sequestration
Koehn, Lars W. (Virginia Tech, 2025-04-07)
Carbon capture and storage (CCS) is a technology for reducing anthropogenic greenhouse gas emissions by capturing CO₂ from point source emissions, such as fossil-fuel burning power plants, ethanol producers, and cement factories, or directly from the atmosphere and injecting the gas into deep geologic formations. This technology is rapidly being implemented by both public and private entities as a major technology for mitigating industrial and private contributions to climate change. However, to date, CCS has only been implemented in a small number of projects within a limited number of geologic systems. The goal of this work is to expand the types of geologic systems deemed feasible for carbon storage through numerical simulation demonstrations of the potential of understudied geologic systems for storing millions of tons of CO₂. This dissertation is the culmination of four projects: (1) an ensemble simulation study of the effects of spatially variable permeability for CO₂ storage in offshore settings, (2) a feasibility study on the CCS potential of Devonian-Silurian sandstones in the Pulaski Thrust system of Southwest Virginia for carbon storage, (3) a simulation study identifying major play types that could be utilized for commercial carbon storage within global fold-and-thrust belt geologies, and (4) a reactive transport simulation study on the storage security and trapping mechanisms of basalt-bounded saline aquifers such as those that exist in rift basins for carbon storage. These four studies provide a general framework for sequestering CO₂ within offshore basins, fold-and-thrust belts, and rift basins, demonstrating the feasibility of CCS within these geologies and paving the way for future site-specific CCS development.
Factors Associated with Pollinator Foraging and Floral Morphology of Lawn Weeds
Godara, Navdeep (Virginia Tech, 2025-04-07)
The decline in pollinator populations poses a significant challenge to global food security, necessitating best management practices that minimize pollinator exposure to harmful pesticides. Many common weeds in managed turfgrass systems attract honey bees (Apis mellifera L.) and other pollinators, increasing their risk of contact with insecticide residues. This dissertation project explored the potential of herbicides, optical brightener, pigmented fungicide, commercial sunscreen, turf colorant, and other deterrent strategies to reduce pollinator foraging on weedy flowers in turfgrass. Field studies were conducted from 2021 to 2023 to evaluate the effect of these treatments on floral morphology and ultraviolet (UV) reflectance of bulbous buttercup (Ranunculus bulbosus L.), dandelion (Taraxacum officinale G. H. Weber ex Wiggers), foxglove beardtongue (Penstemon digitalis Nutt. ex Sims), white clover (Trifolium repens L.), and associated pollinator foraging. Several herbicides, including halosulfuron, sulfentrazone, synthetic auxins, and topramezone reduced floral density, altered UV reflectance, and deterred pollinators to varying degrees on weedy flowers. Synthetic auxin herbicides completely eliminated pollinator visitation within two days and degraded white clover floral quality within five days, suggesting that insecticides could be applied two days post-herbicide treatment to minimize pollinator exposure risk. Pollinator visitation and floral quality were temporarily affected by herbicide application, with some herbicides eliminating food resources while others transiently impacting floral quality and density. While floral UV reflectance affects pollinator visitation, it is not the only factor; as UV-absorbing and UV-reflecting flowers showed distinct reflectance responses to herbicides, yet pollinators were equally deterred. Optical brightener, pigmented fungicide, and commercial sunscreen reduced radiometric UV reflectance and digitally assessed UV-reflecting area of foxglove beardtongue, dandelion, and bulbous buttercup petal apices by 24–79%, significantly deterring pollinator visitation to dandelion and bulbous buttercup flowers. Despite transient impacts on floral reflectance and pollinator foraging visits, optical brightener and sunscreen treatments did not affect floral density or quality, preserving long-term pollinator food resources. Deterrent practices may reduce the risk of pollinators being exposed to harmful insecticides in turf by decreasing their visits, but the effectiveness of these methods in minimizing contact exposure remains unaddressed. In 2024, an additional study assessed the effectiveness of deterrent practices in preventing contact exposure of actively trapped honey bees and passively trapped insects to white clover inflorescences treated with fluorescent powder in turfgrass. Mowing and pre-treatment with synthetic auxin herbicide reduced fluorescent powder exposure of honey bees by at least 75% and 90%, respectively, but had little effect on passively trapped insects, suggesting that trap attractiveness, rather than white clover flower manipulation, drove insect capture. Blue vane traps captured 1,117 bees from 23 species within 28 hours, with over 96% being native, while yellow sticky cards collected 384 insects from the Lepidoptera, Diptera, and Coleoptera orders. The results indicate that mowing and synthetic auxin herbicides effectively deter honey bees from visiting treated white clover inflorescences, lowering their contact exposure risk. These findings show that herbicides, optical brightener, and mowing can successfully reduce pollinator foraging on treated turfgrass, thereby decreasing the potential for insecticide exposure. This research offers valuable insights for balancing weed management with pollinator conservation, providing practical approaches to minimize insecticide risks while preserving pollinator food sources.
Beyond binoculars: Increasing relevancy of state fish and wildlife agencies by investigating facilitators of and participation in wildlife viewing
Sinkular, Emily Noelle (Virginia Tech, 2025-04-03)
In 2022, more than half of all Americans participated in wildlife viewing (intentionally observing, feeding, or photographing wildlife, traveling to parks or natural areas to observe, view or photograph wildlife, or maintaining plantings for the benefit of wildlife). Historically in the U.S., management of wildlife-related recreation has focused on hunting and fishing, with wildlife viewing rapidly emerging as a new opportunity for state fish and wildlife agencies to enhance their relevancy, especially with traditionally under-represented audiences, such as people with disabilities. However, little is known about facilitators of participation in wildlife viewing, especially when compared to hunting and fishing. This dissertation investigates wildlife viewers using a mixed-methods approach. First, we investigated the impact of the COVID-19 pandemic on participation in wildlife viewing. We applied the Hunter Retention and Recruitment framework from the hunting literature to classify wildlife viewers into four groups: recruited, retained, reactivated, and churned. We found that retained wildlife viewers generally reported higher levels of identify as a wildlife viewer and support from family in wildlife viewing during the first year of the COVID-19 pandemic. We also examined the "multidimensionality" of wildlife-related recreation, specifically the extent to which wildlife viewers hunt and or fish in addition to wildlife viewing. We found that the wildlife viewers who also participated in hunting and/or fishing were more specialized than those who wildlife view only. This has promising implications for management and relevancy. As state agencies expand to include wildlife viewing as a program focus, they are not leaving all their traditional constituents behind, rather they are supporting them in a different way. Next, we investigated how to supports birders with disabilities and found that birders with disabilities were more limited by barriers to wildlife. viewing than birders without disabilities. We also found that birders with and without disabilities expressed some similar interest in certain programs or services from their state agencies, which suggests that both groups will benefit from management decisions that benefit those with disabilities. Finally, we used focus groups with disabled and neurodivergent wildlife viewers to investigate intrapersonal, interpersonal, and structural facilitators to wildlife viewing. When investigating multiple types of interpersonal and structural facilitators we found an overwhelming interest in more detailed information about wildlife viewing locations and programs. We recommend providing detailed information to wildlife viewers as a key step for state agencies to support these audiences. Further, given that the Americans with Disabilities Act (ADA) encourages programs to be accessible, providing such detailed information supports meeting the requirements of the ADA. In this dissertation we have applied existing frameworks or theories in new ways –offering new avenues and questions for future research. These new frameworks for understanding and analyzing participation in wildlife viewing led to recommendations for increasing accessibility and inclusion in wildlife viewing. Throughout this process, we worked closely with state fish and wildlife agencies and generated recommendations that can be implemented in their management. This will help agencies expand their relevancy to new and potentially underserved audiences.
From Forest Floors to Pharmacology: Elucidating Millipede Defensive Alkaloids for Drug Discovery
Banks, Margaret P. (Virginia Tech, 2025-04-01)
Millipedes are some of the oldest animals on earth, evolving over 400 million years ago (mya). The subterclass, Colobognatha evolved 99 mya and are largely understudied compared to other classes of millipedes. Like most other millipede classes, Colobognatha possess repugnatorial glands, which store alkaloids as defensive compounds. However, they have also evolved unique characteristics that set them apart from all other millipedes, including distinct anatomy, group behavior, brood care, and the production of terpenoid alkaloids. Prior to 2020, only 11 alkaloids were known. Herein, a total of 25 new terpenoid alkaloids are reported coming from three different genera, all belonging to the same order. Key findings include the discovery of indolizine and quinolizidine alkaloids (e.g., hydrogosodesmine, homogosodesmine and homo-hydrogosodesmine) from the defensive secretions of various Brachcybye species (Chapter 2), the discovery of the ischnocybine alkaloids from the defensive secretions of Ischnocybe plicata (Chapter 3), and the discovery of the andrognathines and andrognathanols from the defensive secretions of Andrognathus corticarius (Chapter 4). The structure elucidation of each utilized modern techniques, including 2D NMR, HRMS, DFT, ECD, chemical synthesis, and Mosher's analysis. Many of these new alkaloids represent new natural product classes with carbon backbones that are unprecedented in the literature. Biological and ecological evaluation revealed the new alkaloids deter ants, a common predator to millipedes (Chapter 3), and this led to the discovery that a subset of the alkaloids potently binds to sigma-1 receptor (ischnocybine A: Ki 14 nM), while others bind to sigma-2 (homo-hydrogosodesmine hydrate: Ki 260 nM). Furthermore, ecology studies revealed that the alkaloid production is conserved over large geographical regions, accumulated as the millipedes gain segments and are actively secreted through the ozopores when physically agitated. These discoveries provide insights into a potential biosynthetic pathway shared by all Platydesmida millipedes and support the hypothesis that alkaloid biosynthesis in this order is evolving toward greater simplicity.
Towards Improving Students' Software Testing Practices using Modified Mutation Testing
Mansur, Rifat Sabbir (Virginia Tech, 2025-04-02)
Mutation testing (MT) is a powerful technique for evaluating the quality of software test suites by introducing small faults, called ``mutations,'' into code to assess if tests can detect them. While MT has been extensively applied in the software industry, its use in programming courses faces both computational and pedagogical barriers. My research investigates the successful integration of MT in a post-CS2 Data Structures and Algorithms (DSA) course with 3-4 week long programming projects. Through a comprehensive study across multiple semesters, I investigated three key aspects: the computational demands of MT in an educational auto-grading system, the effect of MT on student test suite quality and coding practices, and the development of a framework for effectively integrating MT in programming courses. Initially, the implementation of standard MT showed mixed results due to inadequate stock feedback. This prompted me to develop a tailored approach that modified MT feedback, while also incorporating additional documentation and training materials. I also observed a noticeable increase (30-50 seconds per submission) in the auto-grader's processing time and feedback turnaround time when using MT, raising concerns about potential server overload. At the same time, the collection of changes made to the environment and requirements as part of this intervention led to an overall reduction in the number of submissions per student needed to complete the projects. My findings suggest that students using modified MT, as a group, demonstrated higher quality test suites and wrote better solution code compared to students whose test suites were graded on code coverage. This version of MT with modified feedback also showed positive results in student understanding and application of MT principles compared to MT with stock feedback. Analysis of IDE activity data, code submissions, and 38 semi-structured student interviews led me to provide a framework for introducing MT as an effective intervention. Thus, my research provides a framework for effectively integrating MT in programming courses, contributing to improved student test suite development and offering practical guidelines for instructors introducing MT in undergraduate Computer Science courses.
Optimizing Bermudagrass Management Strategies Using Aerial Imagery and Wireless Capacitive Soil Sensors
Roberson, Travis Leon (Virginia Tech, 2025-03-28)
Hybrid bermudagrass (HBG) (Cynodon dactylon (L.) Pers. x transvaalensis Burtt Davy) is one of the most commonly used turfgrasses in the transition zone due to its drought and wear tolerance. Over the years, a combination of history, experience and research has provided best management practices for abiotic stress management of HBG through chemical and cultural field trials. As new tools and technologies to apply to HBG management emerge, research is necessary in order to better understand how these can be implemented in the decision making process for optimal HBG management. As technology rapidly evolves, understanding how to properly implement innovation is vital for outputs to be greater than the inputs for sustainable management. Three studies were conducted between 2021 and 2024 in Virginia to enhance understanding of how small unmanned aerial vehicles and wireless capacitive soil sensors can aide in expediting data collection for actionable decision making related to irrigation practices and winterkill stress mitigation. The first study assessed the impact of morning leaf wetness from dew and subsequent removal on remotely sensed visible imagery for creeping bentgrass and HBG. The data suggests that leaf wetness minimally influences drone-derived green to red ratio index data while maintaining a moderate correlation with soil water content (r² = 0.48. The second study evaluates the effectiveness of aerial thermal imagery in assessing the distribution uniformity of golf course irrigation systems. A modest correlation existed between irrigation applied as measured by catch can volume and thermal mean canopy temperature (Tc) values (r = 0.40). Furthermore, the coefficient of determination between Tc and catch can volume, varied between tee (r2 = 0.19-0.41) and green (r2 = 0.54-0.68) locations, influenced by turfgrass canopy density and soil physical properties. The use of drone-captured thermal imagery shows potential irrigation distribution uniformity through drone thermal imagery to make these evaluation metrics seamless, though techniques need refinement for widescale industry adoption to be applied for potential irrigation management decision making. The final study focuses on utilizing capacitive soil sensors to monitor soil temperature and moisture during winter covering events for ultradwarf bermudagrass (UDB), indicating that wireless sensors can accurately document soil moisture and temperature trends prior, during, and post-covering events. Within the study, the lowest recorded soil temperatures at 33.0◦F for Green 9 and 31.0◦F for Green 1 under the no cover treatment, and no winter injury was observed, suggesting that UDB may be able to tolerate these soil temperatures for brief periods under fully dormant conditions. Lastly, for the coldest covering event on Green 1, soil moisture fluctuated the most within the uncovered treatment compared to single and double covers, likely due to freeze and thaw cycles of the soil water, suggesting that soil moisture levels are a likely contributor to winterkill potential. Collectively, these studies highlight the potential of advanced technologies in enhancing turfgrass management and water conservation efforts in golf course maintenance of hybrid bermudagrass areas.
A Case Study of the Extent Coaching Increases the Instructional Leadership Self-Efficacy of Aspiring and Early Career Principals
Colucci, Danielle E. (Virginia Tech, 2025-03-28)
Principal self-efficacy and instructional leadership skills are among the most influential factors impacting school success (Goldring et al., 2021; Grissom et al., 2021; Tschannen-Moran and Gareis, 2007; Van Nieuwerburgh et al., 2020). The purpose of this case study was to examine the extent coaching increased the instructional leadership self-efficacy of elementary aspiring and early career principals (AECPs) who completed a specific AECP program offered within one Virginia public school division. The program provided principal coaching as a means of growing the AECPs' instructional leadership skills and self-efficacy. The AECPs in this case study received one-on-one coaching from a program leader and from a mentor principal in addition to receiving coaching from experienced principals during job-embedded learning and professional learning activities. The findings and associated implications produced from this case study provide information to support school division leaders and state departments in preparing a resilient and skilled pipeline of principals. One-on-one coaching and learning from experienced principals were both identified as key coaching experiences that the cohort attributed to their increased level of instructional leadership self-efficacy. Additionally, appreciation of being provided a non-evaluative coach and principal mentors from schools other than their assigned schools were noted within the aspiring and early career principals' explanations of increased instructional leadership self-efficacy. The findings contribute to related areas of scholarship and offer practical implications to school divisions seeking to reduce principal turnover, improve school outcomes and principal practice, and increase principal self-efficacy.
Polymer-Derived Ceramic Coatings for Stress and Corrosion Resistance in Stainless Steel: Optimization of Thermal Stability and Structural Integrity
Choi, Hyeon Joon (Virginia Tech, 2025-03-27)
This dissertation focuses on the development and characterization of polymer-derived ceramic (PDC) coatings, particularly SiON and SiOCN, aimed at enhancing corrosion resistance, thermal stability, and structural integrity of stainless steel in harsh environments. Using perhydropolysilazane (PHPS) and its derivatives, various coating compositions and pyrolysis conditions were optimized to tailor their microstructure and performance. The first part of the study evaluates the compatibility of SiOCN coatings on stainless steel, highlighting their ability to mitigate corrosion under aqueous and high-temperature conditions. The coatings demonstrate excellent adhesion and mechanical properties, making them suitable for demanding applications. Next, the corrosion resistance of PHPS-derived SiON coatings on welded stainless steel was investigated, revealing their effectiveness in reducing localized corrosion while identifying the trade-offs between pyrolysis temperature and coating brittleness. To address stress corrosion cracking (SCC) in chloride-rich environments, SiON coatings were anlayzed for their performance on U-bend stainless steel specimens. Coatings pyrolyzed at lower temperatures exhibited superior SCC resistance due to their flexible and defect-resistant structure, while higher-temperature coatings, despite their improved hardness, were prone to cracking under mechanical stress. Finally, the influence of carbon content on the thermal stability of SiOCN coatings was studied under different atmospheres (Ar, Air, and Ar+H2O). Results indicate that carbon plays a critical role in determining coating stability, with excessive carbon leading to microstructural degradation in oxygen-containing environments. This research provides a comprehensive understanding of PDC coatings' structural and chemical evolution under various stress and environmental conditions. It offers valuable insights into optimizing coating composition and processing parameters for applications in nuclear waste storage, aerospace, and other high-performance industries.
Non-proteolytic roles of the ubiquitin-proteasome system in memory formation across the lifespan
Bae, Yeeun (Virginia Tech, 2025-03-26)
Memory formation and decline are driven by complex molecular mechanisms and region-specific changes in the brain. Epigenetic modifications, such as histone monoubiquitination and ubiquitin signaling, have emerged as key players in these processes. While monoubiquitination of histone H2B is a well-established regulator of increased gene transcription in memory formation, the role of histone H2A monoubiquitination (H2Aubi), a potent transcriptional repressor, remains largely unexplored. Similarly, although the canonical role of the ubiquitin-proteasome system (UPS) has been extensively studied during memory processing, less is known about its non-proteolytic functions, such as lysine-63 (K63) polyubiquitination. Here, we investigated the role of histone H2Aubi in memory formation and K63 polyubiquitination in age-related memory decline, focusing on the hippocampus and amygdala—two regions critical for memory processing. We observed global and gene-specific decreases in H2Aubi in the amygdala following fear conditioning. Notably, H2Aubi levels decreased at the Pten coding gene, a key inhibitor of PI3K-AKT-mTOR signaling, accompanied by increased PTEN protein expression. CRISPR-dCas9 mediated upregulation of the H2Aubi ligase, Ring1b, in the amygdala enhanced contextual memory. This suggests that reductions in H2Aubi constrain fear memory potentially through PTEN-mediated regulation of mTOR signaling. Additionally, we explored the role of K63 polyubiquitination in age-related memory decline. Using unbiased proteomic analysis, we observed significant increases in K63 polyubiquitination protein targets in the hippocampus across the lifespan. CRISPR-dCas13 mediated reduction of K63 polyubiquitination in the hippocampus of aged male rats reversed contextual fear memory impairments, whereas similar manipulations in middle-aged rats with normal memory had no effect, highlighting the age-specific role of K63 polyubiquitination in memory. Conversely, the amygdala exhibited consistent reductions in K63 polyubiquitination with age, and further decreasing K63 polyubiquitination improved memory retention in aged but not middle-aged. Together, our findings reveal novel region- and age-specific roles of histone H2Aubi and K63 polyubiquitination in modulating fear memory and age-related memory decline.
Understanding and predicting the response of reservoir zooplankton communities and water quality to climate change
Wander, Heather Lynn (Virginia Tech, 2025-03-25)
Freshwater zooplankton communities are highly sensitive to environmental change and are critical indicators of water quality. Zooplankton are central organisms in freshwater food webs, composed of diverse taxa playing different functional roles in freshwater food webs as food sources for upper trophic level predators (e.g., fish and invertebrates) and as grazers of phytoplankton. Therefore, changes in zooplankton community density, biomass, composition, and migration behavior over time have direct implications for trophic level interactions and water quality. Climate change has altered freshwater ecosystem functioning through several mechanisms, including warming surface waters, declining dissolved oxygen concentrations, and changes in the timing and magnitude of phytoplankton blooms, each of which has implications for zooplankton communities. To better understand and predict zooplankton community responses to variable environmental conditions due to climate change, I used field, laboratory, modeling, and forecasting approaches. First, I assessed zooplankton community structure and migration across five 24-hour field sampling campaigns that spanned three years in a eutrophic, temperate reservoir. Specifically, I intensively sampled zooplankton dynamics across different sampling days, hours within a day, and reservoir sites and found that zooplankton community structure and migration was most variable among sampling days, suggesting that routine water quality monitoring programs aiming to characterize zooplankton should prioritize sampling efforts over several days to capture the greatest variability. Second, I used field data and multivariate analyses to assess patterns and drivers of zooplankton taxon density over six summers in the same reservoir. My findings suggested that zooplankton communities in years with warmer surface waters, lower precipitation, deeper Secchi depths, higher Schmidt stability, and lower epilimnetic nutrient concentrations favored rotifer dominance and lower cyclopoid densities. Third, I used a process-based ecosystem model to examine how warming air temperatures affect zooplankton biomass and community composition over an eight-year time series in the reservoir. I showed that warming temperatures promote greater rotifer biomass and lower crustacean biomass, which has implications for water quality. Finally, I forecasted reservoir water temperature from 1-35 days into the future using different observation frequencies to identify the lowest temporal frequency of data assimilation required to generate accurate forecasts. I found that weekly observations could be used to generate accurate water temperature forecasts up to a week in advance. This work highlighted that accurate forecasts may not necessarily require the most high-frequency observations, and that observation frequency is likely dependent on the variable and time horizon of interest. Generating accurate water temperature forecasts is particularly relevant for future development of zooplankton forecasts that need accurate water temperature forecasts as model driver data. Overall, my dissertation explores the dynamic relationship between freshwater zooplankton communities and water quality, highlighting the high variability in zooplankton structure, migration behavior, and environmental drivers over time. I demonstrate how zooplankton responses to climate change vary by taxon and emphasize their role in shaping freshwater food webs and ecosystem functioning, underscoring the important role of zooplankton communities in mediating water quality.
Managing Riyadh's Urban Growth: Assessing Resident Satisfaction in the Current Residential Neighborhoods and Examining Smart Growth Strategy Preferences for the Future Growth in the Context of Rapid Urbanization
Albarrak, Mohammed Abdulrahman (Virginia Tech, 2025-03-19)
Globally, urbanization and urban growth have reached unprecedented rates in cities. Riyadh, the capital of Saudi Arabia, is no exception to the rapid urbanization and growth that has occurred in a sprawling and low-density pattern. Riyadh has set a controversial target of doubling its current population of 7.1 million to reach 10-15 million by 2030, emphasizing the importance of making this growth sustainable. Currently, the literature on the applications of smart growth gives little attention to public participation in decision-making regarding the future growth of cities. Specifically, there is a lack of research focused on integrating the public into the decision-making process for managing population increases over a short time frame (e.g., ten years). In Riyadh, the planning process does not provide precise mechanisms for public engagement or preferences in shaping future growth. Therefore, the purpose of this study is to manage this rapid urbanization and growth smartly by shaping future growth from the perspective of residents' preferences and how to draw that into urban policies. This study aims to shed light on residents' satisfaction with the current neighborhoods. In addition, the study aims to investigate residents' preference for the smart growth strategy as a new urban pattern in the city. The study uses the survey method to measure residents' satisfaction with the existing neighborhoods of Riyadh through an online questionnaire. Furthermore, another online questionnaire that combines both a discrete choice experiment and visual preference for the principles of smart growth is used to examine preferences for smart growth. This study adopted a number of statistical models, and the questionnaire was conducted with 3,111 respondents for the first questionnaire and 1,710 respondents for the second questionnaire as completed answers. The results of the first questionnaire were analyzed using descriptive statistics and by examining the correlations between neighborhood elements, including the physical environment and demographic data. This study also employed the multinomial logit model to analyze the results of residents' preferences, and the latent class analysis to reveal the homogeneity and heterogeneity of preferences among respondents. The results of the neighborhood satisfaction questionnaire indicated a divergence in opinions across the three sections identified in the first questionnaire. The results indicated dissatisfaction, particularly with neighborhood characteristics, transportation and accessibility elements, and urban landscape components. Satisfaction levels leaned more toward neutrality to dissatisfaction, reflecting the possibility that rapid growth may have affected the quality of services and facilities in neighborhoods. The results of the second questionnaire showed strong and explicit preferences for neighborhoods characterized by walkability and bikeability lanes, transportation availability, and parks across both 30-meter and 60-meter streets. There was also a preference, though to a lesser extent, for diverse housing options and densities represented by seven-story buildings, as well as a slight preference for mixed-use buildings. The latent class analysis further revealed six distinct groups of urban preferences in the neighborhoods. These findings highlighted the need for improvements in some urban dimensions discussed in this study, which showed low satisfaction results. Moreover, the findings enabled the creation of a set of recommended urban development policies to ensure that future growth aligns with the preferences of Riyadh residents. The results reflected the need to create vibrant, integrated, and comprehensive urban communities that enhance quality of life while providing diverse transportation options, green spaces, appropriate densities, mixed-use developments, and diverse housing options.
Securitizing Air Spaces: How the Pan Am 103 Bombing Led to a New Extraterritorial Aviation Regime
Beck, Carol Nicole (Virginia Tech, 2025-03-19)
The introduction of security in airspace management presented an interesting problem as the United States inserted itself as the new arbiter of international aviation security. By its very nature, aviation security requires strict policing standards on both ends of travel, at both the departure and arrival airports. This requires unique territorial cooperation between states. But in a world of uneven power, one powerful state with network centrality has the capacity to impose its security demands on the system. How this is created, which I term conceptually as an "extraterritorial aviation regime," is what this dissertation seeks to explain. Hijackings and bombings of airplanes in the 1970s and 1980s culminated in a significant bombing in 1988: the destruction of Pan Am flight 103 over Lockerbie, Scotland. This event became a critical juncture in the management of airspace. The U.S. state used its desire to impose certain security standards to create a new extraterritorial aviation regime, directly placing U.S. security personnel in the airports of other states, and regulating international air carriers, which were controlled and often owned by other states. My research argues that the U.S. used its centrality in the aviation network to institute a new regime for the security management of international airspace. But while security was a public motivation for this new regime, aviation deregulation and economics were also drivers behind the U.S. policy change. Understanding why the new regime was formed in Pan Am's wake helps to understand why the U.S. state became the security standard-maker in international aviation and what led the U.S. to assume control of other states' airports and airplanes under the rubric of U.S. law.
Functionalized High Aspect Ratio Cellulose Nanocrystal Filled Composites for Gas and Liquid Separations
Farrell, Connor Lawrence (Virginia Tech, 2025-03-17)
Separating mixtures into their components is a ubiquitous feature of industry, and these separations are necessary for every facet of life down to the simple functions of breathing clean air and drinking potable water. These chemical separations account for a large portion of the total energy use both in the United States and globally. Polymer membrane based separations are desirable when applicable due to their lower energy requirements relative to thermal methods such as distillation. This has led to increases in membrane usage to reduce energy costs; however, membrane separations are not without limitations relating to the membrane material and application requirements. Herein I will address membrane separation technologies, their limitations, and the impact of incorporation of high aspect ratio cellulose nanocrystals (CNCs) on the performance of the resulting polymer composite membranes for desalination and gas phase separations. Lack of available drinking water is an increasing problem across the world with much of the world living in water scarce regions. Desalination using reverse osmosis (RO) membranes is one of the most effective methods of producing clean drinking water. Aromatic polyamide based thin film composite membranes (TFCs) are the most commonly used for commercial desalination and have been since the late 1970s. These TFCs suffer from drawbacks including irreversible performance reduction from fully drying the membrane before use and susceptibility to biological fouling. One technique to mitigate issues with TFCs is to utilize the desirable properties of nanoparticles through their incorporation in the TFC selective layer to create thin film nanocomposite membranes (TFNs). CNCs were selected for this work due to their high aspect ratio, potential for surface modification, attractive mechanical properties, sustainable feedstock, and low toxicity. Membranes containing as received CNCs, 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO)-oxidized cellulose nanocrystals (TOCNs), tertiary amine functionalized cellulose nanocrystals (aCNCs), or zwitterionic functionalized cellulose nanocrystals (zCNCs) were synthesized to investigate the effects of nanoparticle functionality and loading level on the brackish water desalination, drying behavior, and fouling resistance of polyamide based TFNs. Loading level was investigating using TOCN containing TFNs which exhibited an increase in water flux and sodium salt rejection up to a maximum when the m-phenylenediamine monomer to TOCN ratio was 20:1 followed by a decrease in both water flux and salt rejection with more TOCN added to the membrane. At the optimal loading level there was a 25% increase in the water flux and 0.2% increase in salt rejection relative to the unloaded control for the membranes kept hydrated and a 146% increase in water flux and 1.6% increase in salt rejection relative to the unloaded control for membranes that were dried. These increases yielded equivalent water flux and salt rejection for the membranes kept hydrated and those dried prior to use at the optimal loading level. The changes in desalination performance are attributed to the introduction of a new water transport pathway at the interface of the TOCN nanoparticle and the polymer matrix and a structural reinforcement effect preventing the collapse of pores present in the polymer during the drying process. The optimal loading level from the previous investigation was used for all work with the other CNC functionalities. The TFNs containing CNCs yielded a 10% increase in water flux and no change in salt rejection relative to the unloaded control while those containing aCNCs and zCNCs yielded no change in water flux and a 0.6% and 0.3% decrease in salt rejection respectively. These differences in behavior relative to the TOCN loaded TFNs are attributed to the transport pathway and structural reinforcement effects being subject to the interaction between the polymer and functionality of the nanoparticle as well as the size and shape of the functional group leading to the differences for each CNC functionality. There were no changes in the foulant resistance for any of the membranes when exposed to water containing bovine serum albumin and sodium alginate as probe foulants. This is attributed to the synthesis procedure in which the nanoparticles are added to the membrane in the denser aqueous phase of the interfacial polymerization. The CNCs will not diffuse well through the polymer as it begins to form, so they would be likely to be concentrated deeper in the membrane while fouling is a surface sensitive behavior, so if the nanoparticles aren't near the surface they will not affect that behavior. Gas separations are of interest for investigation into the effects of high aspect ratio nanoparticles in composite membranes as it allows for investigating more fundamental information through control of the membrane morphology and mixture composition. The range of molecule sizes in the separation is much smaller for gas separations compared to desalination with kinetic diameter differences on the order of 0.1-1 Å compared to 4.5Å. Additionally, with the lower pressure requirements for gas transport relative to reverse osmosis, simple membrane geometries can be investigated using dense films rather than TFNs. In this investigation, dense film composite membranes were made consisting 0, 0.07, 0.7, 3.6, 7.2% or 15% CNCs by volume in a thermoplastic polyurethane (TPU) matrix. The addition of TPU showed increased structural strength in the film with loading modulus increasing from 10 MPa for the unloaded TPU to 58 MPa for 3.6% CNC loaded TPU and 105 MPa for 7.2% CNC loaded TPU. The gases tested during this investigation are CO2, He, Ar, O2, and N2. As the CNC loading level increased, the gas permeability for each gas decreased. For the gases other than CO2, there 0.07, 0.7, and 3.6% CNC films all had the same permeability with all, but Ar, 47 ± 3 % less than the unloaded film permeability. The 15% CNC permeabilities were all 44 ± 1 % less than that of the 0.07, 0.7, and 3.6% CNC films. For CO2, the permeability decreased with each addition of CNC. None of these decreases are described by simple space filling by an impermeable particle. This indicates that the structural reinforcement providing strength to the membrane may be limiting some of the chain mobility inhibiting the diffusion of gases through the membrane which is seen in the diffusion coefficient of CO2 which decreases with increasing CNC loading.
An Integrative Review of Curricular Integration as a Curriculum Development Strategy in Health Professions Education
Ryan, Shane Michael (Virginia Tech, 2025-03-14)
This integrative literature review examines the concept of curricular integration as a curriculum development strategy in health professions education. The review synthesizes existing research on the definition, theoretical foundations, implementation, and efficacy of integrated curricula, which seek to connect diverse disciplines and provide a more holistic, student-centered approach to learning. Key elements of successful curricular integration include interdisciplinary faculty collaboration and the contextualization of knowledge within real-world settings. Theoretically, curricular integration supports deeper learning, enhances clinical reasoning, and improves knowledge transfer, preparing students for complex health science professions. However, challenges related to the variability in defining and evaluating curricular integration are identified, and the need for standardized metrics and more robust longitudinal studies is emphasized. The review concludes that while curricular integration shows significant promise in improving health professions education, further research is needed to refine implementation strategies, evaluate its long-term impact, and ensure its alignment with evolving expectations of professional practice.
A Systematic Investigation into Induction and Mitigation Methods of Motion Sickness in Passengers of Automated Vehicles
Dam, Abhraneil (Virginia Tech, 2025-03-13)
Automated vehicle technology can not only transform vehicle behavior on roadways, but also transform users from an active driver to a passenger, with increase in automation levels, such as going from SAE Levels 0 through 2, to Levels 3 through 5. As passengers engage in non-driving related tasks (NDRTs) inside a moving vehicle, they experience limited vehicle control and external awareness. Such conditions can lead to passengers becoming motion sick. Since two out of three passengers are prone to motion sickness, even mild symptoms of motion sickness can severely influence users’ experience in automated vehicles. This dissertation includes four studies to investigate the human factors challenge of motion sickness in passengers of automated vehicles. The first study consists of a systematic literature review following the PRISMA framework. Forty-one papers were selected to be qualitatively analyzed based on which an overarching research framework was proposed. The second study focused on verifying if driving styles simulated on a motion-based driving simulator could be used to artificially induce motion sickness in a safe controlled manner. The third study investigated two driving styles with and without an NDRT to corroborate the findings from the previous study. In the fourth and final study, the focus shifted to mitigating motion sickness. A novel auditory display was developed based on existing literature to reduce motion sickness. Findings from the second and third studies confirmed that strong lateral accelerations could indeed induce motion sickness, and engagement in a cognitively demanding task could lower motion sickness. Based on these findings, the Cognitive Distraction Effect was proposed in the third study. The fourth study, that utilized the verified motion sickness inducing condition from the second and third studies, found that the presence of repeated spatialized anticipatory auditory cues increased motion sickness due to the added sense of vection from the auditory stimuli. This was a unique observation that aligned with recent literature. Furthermore, the fourth study also found evidence in support of the Cognitive Distraction Effect. In summary, this dissertation provides a comprehensive investigation into developing our understanding of motion sickness in passengers of automated vehicles. Three unique contributions are proposed. One, it is possible to induce motion sickness in a safe replicable manner in a laboratory without the need for real-world driving. Second, cognitive engagement in a demanding task can suppress physiological symptoms of motion sickness, suggesting NDRT engagement could have benefits for mitigating motion sickness. Finally, the dissertation sheds new light on the senses that contribute towards development of motion sickness, in that even the hearing system has a role to play in maintaining balance and orientation, in addition to the visual and vestibular systems.

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