Doctoral Dissertations

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https://hdl.handle.net/10919/11041

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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.
Airborne Dissemination of Antibiotic Resistance Genes Near Farms and Effectiveness of Ionization Against Airborne Bacteria in a Classroom
Kormos, David Aaron (Virginia Tech, 2025-03-13)
The Covid-19 pandemic heightened attention to airborne microorganisms and their widespread impacts. This dissertation examines two facets about airborne microorganisms: (1) dissemination of antimicrobial resistance in the environment and (2) ionization for disinfection of indoor air. Antimicrobial resistance (AMR) poses a significant threat to public health, exacerbated by the dissemination of antibiotic resistance genes (ARGs) in the atmosphere to an extent that is not yet well understood. Chapters 2 and 3 of this dissertation characterize ARGs in the atmosphere through a literature review and experimental observations at two agricultural sites, respectively. A critical review of 52 studies revealed that ARGs are present in aerosols in urban, rural, hospital, industrial, wastewater treatment plants, composting and landfill sites, and indoor environments. Commonly studied genes include sul1, intI1, beta-lactam ARGs, and tetracycline ARGs, with abundances varying by season and setting. Temporal trends varied based on the type of environment and human activity. Characterization methods included qPCR, ddPCR, and metagenomic analysis; standardized methodologies are needed to unify findings about the dissemination of ARGs in the atmosphere. To address knowledge gaps identified in the literature review, we designed an experimental study at a dairy farm and swine farm, where beta-lactam was the dominant antibiotic used. We quantified ARG concentrations, size distributions, and emission rates in the air and related these to ARGs found in nearby water and soil samples over four seasons. Concentrations of most ARGs were higher during warmer months but varied more by sampling location or exhaust fan usage than time of year. At both farms, blaCTX-M1 concentrations peaked at 104 gene copies per cubic meter (gc m-3), while the exhaust from a building at the swine farm contained genes like intI1, ermF, and qnrA at concentrations up to 105 gc m-3. ARGs were found in aerosol particles of all sizes, and the fraction in coarse particles (>5 m) was enhanced near emission sources. The presence of ARGs in fine (<1 m) and accumulation mode (1-5 m) particles indicates potential for long-range transport. Emission rates reached ~105 gc s-1 for some ARGs, including blaCTX-M1, and 106 gc s-1 for intI1. Inhalation exposure to blaCTX-M1 was comparable to ingestion exposure from soil at the dairy farm. In chapter 4, the effectiveness of an in-duct, bipolar ionization system for reducing airborne pathogens was evaluated in a real-world setting: an in-use lecture hall at a university. There were no significant differences in positive, in-room ion concentrations between periods with the ionizer turned on and turned off; however, negative, in-room ion concentrations were significantly lower when the ionizer was on with constant fan speed. To account for day-to-day variability in total bacteria concentrations, related to occupancy and other factors, we examined the ratio of bacterial colony forming units to 16S rRNA gene copies (CFU gc–1). There were no significant differences in this ratio whether the ionizer was on or off, suggesting limited real-world effectiveness of the treatment technology. Factors such as occupancy and the heating, ventilation, and air conditioning (HVAC) system emerged as the primary drivers of bacterial load in the air. This study highlights the need for further research to validate the potential of ionization to reduce levels of airborne pathogens.
Experiments augmented computational analysis of structural materials: A focus on metallic and biological systems
Bollineni, Ravi Kiran (Virginia Tech, 2025-03-13)
Over the past few decades, the demand for energy-efficient treatment processes to reduce carbon emissions and the need for high performance materials in advanced engineering applications have posed significant challenges for materials scientists. This research first investigates the influence of high magnetic fields during heat treatment an energy efficient alternative to conventional processes on the microstructural evolution and mechanical properties of hypoeutectoid steels. The study demonstrates how magnetic fields affect phase transformations, microstructural features, and mechanical behavior. To establish a robust structure-property relationship and enable microstructural tailoring for targeted mechanical properties, an end-to-end computational framework integrating experimental characterization, physics based finite element simulations, and deep learning techniques is developed. Additionally, a mesoscale finite element model is constructed for fully pearlitic steels to simulate plastic deformation and damage, calibrated and validated using experimental data. A deep learning-based approach is then applied to analyze the structure-property relationships and design pearlite lamellae for optimized mechanical performance. Furthermore, the study extends to bio-inspired materials, investigating Nacre like structures for topology optimization aimed at enhancing mechanical properties and wave filtering capabilities. The dynamic behavior of these metamaterials is examined, revealing how hierarchical design influences their multifunctional properties. The findings of this research contribute to advancing the understanding of magnetic field assisted heat treatment for ferrous alloys, providing a computational framework for mesoscale plastic deformation and damage modeling in metallic systems, and developing methodologies for forward and inverse structural design targeting specific engineering applications. These insights pave the way for optimizing materials to achieve superior performance while promoting sustainable and efficient manufacturing processes.
Mechanistic Studies of Flavin-Dependent Monooxygenases Involved in Bacterial Defense and Plant Metabolism
Lyons, Noah Scott (Virginia Tech, 2025-03-12)
Flavin-dependent monooxygenases (FMOs) are a large family of enzymes found in microbes, plants, animals, and humans involved in defense pathways, xenobiotic metabolism, and natural product biosynthesis. One class of FMOs, Class B, carries out the oxidation of heteroatomic substrates, via hydroxylation, S-oxygenation, Baeyer-Villiger oxidation, and decarboxylation, using NAD(P)H as a coenzyme. In this dissertation, the characterization of several FMOs from bacteria and plants is described. The putrescine N-monooxygenase (NMO) FbsI from Acinetobacter baumannii is involved in the fimsbactin siderophore biosynthetic pathway, a virulence factor that allows acquisition of free iron from a human host by a pathogen. We show that putrescine is hydroxylated to form N-hydroxyputrescine and is favored over the aliphatic diamine cadaverine and amino acid L-ornithine. The three-dimensional structure of FbsI was solved and shown to have similarities to other NMOs, and characterization of active site mutants revealed residues essential for catalysis and cofactor specificity. The flavin-dependent S-monooxygenase TvMAS1 from the society garlic Tulbaghia violacea has been implicated in the production of marasmin, a natural product with human health benefits. We find that TvMAS1 has a broad substate scope among thiol and sulfide-containing compounds, particularly L-cysteine derivatives. Additionally, we show that S-allyl-L-cysteine is the preferred substrate and propose TvMAS1 to primarily have a physiological role in allicin, not marasmin biosynthesis. Lastly, we characterized the auxin-producing FMO YUC10 from Arabidopsis thaliana and showed the enzyme to only have steady-state activity with aromatic α-keto acids indole-3-pyruvic acid (IPA) and phenylpyruvic acid (PPA). We also propose that a C4a-peroxyflavin intermediate acts as a nucleophile to perform the oxidative decarboxylation on IPA and PPA. The work in this dissertation fills several knowledge gaps among bacterial and plant FMOs and with the established mechanisms aims to guide future drug discovery, green chemistry, and agricultural bioengineering efforts.
Guidelines for Integrating Care Pedagogy into Faculty Development for Future Emergency Remote Teaching (ERT) in Higher Education: The CARE Framework
Al Amri, Kamla Sulaiman (Virginia Tech, 2025-03-11)
The COVID-19 pandemic drew considerable attention to online teaching at higher education institutions around the globe. This left some institutions unprepared for the sudden shift and dealing with many challenges, including, but not limited to, faculty development. This study employs a design and development research (DDR) methodology to identify and create guidelines and considerations for integrating care pedagogy into faculty development programs at higher education institutions during emergency remote teaching (ERT). These care-focused faculty development guidelines are designed and developed using Type 2 model research and operationalizing the ADDIE Model. The guidelines were structured into a framework called CARE: Care adoption in remote environments. A panel of eight expert reviewers was recruited to validate and lead the evaluation process after the formation of these guidelines. The hope is that these care-informed faculty development guidelines may offer clarity and guidance to faculty at tertiary education institutions. This will allow them to implement effective, care-full pedagogy within emergency remote teaching settings and help students to optimize their online learning experiences.
Operation Hot Sandwich: Incorporating pyrones in [4 + 2] cycloaddition reactions to prepare thermorubin
Kohanov, Zachary Aaron (Virginia Tech, 2025-03-10)
The current increase in antibiotic resistance is of growing concern to the global community. Once easily-treated infections now require last-resort antibiotics with further application only encouraging the eventual buildup of resistance. New drugs are required to fight these infections, specifically with novel mechanisms of action that bacteria have no resistance for. Generally, these drugs will have different scaffolds, contributing to their different mechanisms of action. The literature contains a vast number of antimicrobial metabolites that are understudied but could serve as potential leads for future drugs. One such metabolite is thermorubin, a molecule with a unique scaffold and bacteriostatic mechanism of action. It shows promising sub micromolar activity against both Gram-positive and negative bacteria but suffers from poor oral bioavailability. Difficulties in obtaining this material have led to our development of a total synthetic strategy including a new method for incorporating pyrone moieties into aromatic systems. Based off the Hauser annulation, these conditions were successfully used to insert 15 different pyrones esters and amides into an aromatic system as a dieneophile or a 2-electron component. Modification of the electron-donor, the 4 -electron sulfoxide diene, was also attempted and proved to be somewhat effective. After attempts to use single sulfoxide cycloaddition products failed to propagate, a new donor substrate needed to be created: a symmetrical intermediate already containing both phenyl sulfoxide functionalities. This material was tested and proved successful with further optimization needed to complete the total synthesis of thermorubin.
Adversarial Risks and Stereotype Mitigation at Scale in Generative Models
Jha, Akshita (Virginia Tech, 2025-03-07)
Generative models have rapidly evolved to produce coherent text, realistic images, and functional code. Yet these remarkable capabilities also expose critical vulnerabilities -- ranging from subtle adversarial attacks to harmful stereotypes -- that pose both technical and societal challenges. This research investigates these challenges across three modalities (code, text, and vision) before focusing on strategies to mitigate biases specifically in generative language models. First, we reveal how programming language (PL) models rely on a `natural channel' of code, such as human-readable tokens and structure, that adversaries can exploit with minimal perturbations. These attacks expose the fragility of state-of-the-art PL models, highlighting how superficial patterns and hidden assumptions in training data can lead to unanticipated vulnerabilities. Extending this analysis to textual and visual domains, we show how over-reliance on patterns seen in training data manifests as ingrained biases and harmful stereotypes. To enable more inclusive and globally representative model evaluations, we introduce SeeGULL, a large-scale benchmark of thousands of stereotypes spanning diverse cultures and identity groups worldwide. We also develop ViSAGe, a benchmark for identifying visual stereotypes at scale in text-to-image (T2I) models, illustrating the persistence of stereotypes in generated images even when prompted otherwise. Building on these findings, we propose two complementary approaches to mitigate stereotypical outputs in language models. The first is an explicit method that uses fairness constraints for model pruning, ensuring essential bias-mitigating features remain intact. The second is an implicit bias mitigation framework that makes a crucial distinction between comprehension failures and inherently learned stereotypes. This approach uses instruction tuning on general-purpose datasets and mitigates stereotypes implicitly without relying on targeted debiasing techniques. Extensive evaluations on state-of-the-art models demonstrate that our methods substantially reduce harmful stereotypes across multiple identity dimensions, while preserving downstream performance.
An Information-Theoretic Examination of Next Generation Location Systems: The Role of LEOs, RISs and the Near Field
Emenonye, Don-Roberts Ugochukwu (Virginia Tech, 2025-03-06)
Navigation is integral to modern infrastructure, with GPS serving as the foundation for applications in transportation, banking, and communications. Despite its widespread success, GPS is vulnerable to failures due to its low received signal power, susceptibility to jamming, and reduced accuracy in dense urban environments and deep fades. A failure of GPS could have severe consequences, making it crucial to explore alternative or supplementary navigation technologies. This work investigates the potential of three approaches—low Earth orbit (LEO) satellites, reconfigurable intelligent surfaces (RISs), and near-field propagation—to enhance localization accuracy and resilience. LEO satellites, originally designed for communication, have recently seen widespread deployment through constellations such as Starlink, OneWeb, and Kuiper. Their growing presence presents an opportunity to explore their feasibility for 9D localization, which includes 3D position, velocity, and orientation estimation. However, using LEO satellites for localization introduces significant challenges, including ionospheric delays, high Doppler shifts, limited synchronization due to the absence of atomic clocks, and uncertainty in satellite ephemeris data. To address these challenges, we leverage estimation theory and the Fisher Information Matrix (FIM) to establish theoretical bounds on localization performance. Our analysis shows that localization is possible using signals from multiple LEO satellites observed across several time slots, even in the presence of time and frequency offsets. We derive closed-form expressions for the FIM and identify conditions under which localization is feasible, highlighting the required number of satellites, base stations, and transmission slots. RISs provide another avenue for enhancing localization by dynamically shaping wireless propagation channels through software-controlled meta-material surfaces. We analyze the localization potential of RISs under both near-field and far-field conditions, focusing on angle of incidence, reflection, and orientation estimation. Our FIM-based study reveals that in far-field scenarios, angle estimation is only feasible with multiple RIS phase profiles, whereas in near-field, a single phase profile suffices. This distinction has implications for RIS-aided positioning, indicating that a single RIS reflection may not provide sufficient information for localizing a user in the far-field unless additional mechanisms, such as multiple reflections or phase variations, are employed. We further investigate near-field propagation, assessing the available localization information when a source transmits to a destination node. Our Fisher information analysis reveals that in the near-field regime, 3D orientation and position can be jointly estimated, whereas in the far-field, only 2D orientation and position can be determined. Additionally, we explore the impact of propagation model mismatches on direction-of-arrival (DOA) estimation using the MUSIC algorithm. Our simulations quantify the performance degradation when incorrect assumptions are made about the propagation environment, showing that estimation accuracy suffers significantly when near-field effects are ignored. Notably, in near-field scenarios, using a far-field-based beamforming model leads to an underestimation of DOA estimation errors, while in the far-field, MUSIC remains effective with appropriate beamforming design. Overall, our findings indicate that LEO satellites, RISs, and near-field propagation hold significant potential for overcoming the limitations of GPS and enabling precise localization for next-generation applications. By leveraging these technologies, it may be possible to achieve robust navigation in environments where GPS performance is compromised, paving the way for resilient and high-accuracy positioning solutions.
Insights into the Mechanisms of Metal Oxide and Cationic Antimicrobials
Benmamoun, Zachary Wang (Virginia Tech, 2025-03-06)
Bacterial infections are a leading cause of death worldwide with over 7 million bacterial infection-related deaths reported in 2019 alone. Metal oxide- and polyelectrolyte-based antimicrobials are widely studied and used, but their mechanisms of action and interactions with bacterial cells and other substances found in nature are incomplete. The overall goal of this work is to gain insight on the mechanisms of metal oxide and polycationic disinfectants. The first part of this work presents the development and study of antimicrobial facemasks that kill 99.9% of pathogenic bacteria responsible for hospital acquired infections, Staphylococcus aureus, Pseudomonas aeruginosa, and Streptococcus pneumoniae within 30 minutes. These facemasks were made by adhering cuprous oxide (Cu2O) microparticles to polypropylene textiles. Furthermore, we investigated whether surface contact was necessary to kill bacteria in drying droplets on the facemask surface and found that surface contact produced better killing than exposure to Cu+ ions that dissolve into the droplet. The second part of this work describes the mechanism of action of polycationic antimicrobials. The goals of this section were twofold. Our first aim was to develop a method of studying both polycation adsorption on bacterial cells and antimicrobial activity with single-cell and time-resolved measurements. Our second aim was to determine whether the surface density of antimicrobial required for kill is a better metric of effectiveness than solution concentration required for kill. We adsorbed bacteria to the surface of glass coverslips inside a flow cell. We then flowed through the cell a mixture of fluorescently tagged polycation, polydiallyldimethyl ammonium chloride (PDADMAC) tagged with Cy3, and a fluorescent dye, Sytox Blue, that indicated membrane permeability. This allowed us to image the density of PDADMAC on the cell surface, as well as the time taken for individual cells to permeabilize using fluorescence microscopy. We found a time lag of 5–10 minutes between adsorption and death and found that the time-to-die of an individual cell was well correlated with the rate of adsorption. We also found that the time-to-die and equilibrium adsorption differed among species but followed a trend of more adsorption onto bacterial species with a more negative zeta potential. Most importantly, we found that there was a wide range of cell responses, highlighting the usefulness of single-cell measurements in addition to ensemble-average measurements. Polycationic disinfectants need to be deployed in a wide range of environments, ranging from almost pure water to hypertonic salt. Owing to their cationic charge, one would expect the salt content of the medium to affect the antimicrobial action. So, we investigated the effect of ionic strength on polycation antimicrobial activity. We used our previous method to measure the time-course of adsorption and kill of our labelled cationic polymer in NaCl solution. We found that addition of NaCl decreased the density of polymer adsorption and diminished efficacy of PDADMAC. At salt concentrations at or above 0.15 M, which is similar to normal saline, PDADMAC was no longer bactericidal but instead bacteriostatic (stops growth). Fluorescence depolarization measurements showed that PDADMAC rigidified model bacterial membranes, but salt reduced this rigidity. We also found that the bacteriostatic effect is reversible, and cell growth resumed once PDADMAC was removed. The third section of this work focused on the effect of capillary geometry on the height of capillary rise. Angled capillaries are common in natural and engineered systems such as porous media. However, this system has not been studied by experiment or modelling. The goal of this section is to examine the equilibrium height of a meniscus in a trapezoidal capillary as an example of an angled capillary. To do this, we constructed glass capillaries from hydrophilic borosilicate glass microscope slides and used pure water or ethanol-water solutions as the liquid. This system was modelled by numerical solution to the Laplace equation to obtain the shape of the vapor-liquid interface. Both experiment and theory showed that there is less capillary rise for greater wall angles of the trapezoid, and the rise is more sensitive to the wall angle (α) than the contact angle (θ) at angles close to vertical.
Investigating Droplet Impact Dynamics on Engineered Surfaces: Effects of Roughness, Wettability, and Prospects for Anti-Icing Applications
El Ghossein, Joe (Virginia Tech, 2025-03-06)
Understanding how water droplets interact with engineered surfaces can help address critical challenges such as ice accumulation on airplanes, wind turbines, and power lines, which can pose safety risks and result in costly damage. This research examines how surface properties, including roughness and water-repellent coatings, influence the behavior of droplets as they spread, rebound, or freeze. By utilizing high-speed imaging techniques, the study captured droplet behavior on various materials, identifying key surface design features that improve water repellency. To ensure these surfaces can endure real-world conditions, the study introduced innovative imaging and durability testing protocols. Using 3D profiling, the research tracked microscopic changes in surface structures over time and under stress, such as scratching, peeling, and chemical exposure. These tests identified critical points where surfaces start to lose their water-repellent and anti-icing properties, providing valuable insights into how to enhance material durability. The work also developed a custom-built Supercooled Box Device to simulate extreme freezing conditions, such as freezing rain, and test surface performance in controlled environments. This tool serves as a base for future investigations into how superhydrophobic surfaces (SHS) can be optimized for anti-icing applications, offering a modular platform to explore freezing droplet dynamics and assess surface effectiveness in realistic, controlled conditions. By combining droplet impact analysis, durability testing, and experimental facilities, this research provides a comprehensive framework for creating surfaces that are both highly effective at repelling water and robust enough to endure harsh environments. The findings have significant implications for advancing safer and more sustainable technologies in aviation, energy, and infrastructure industries.
Teacher Perceptions of Reasons for Transfer in the k-12 Public Schools in Saudi Arabia
Alhomoud, Nouf (Virginia Tech, 2025-03-06)
A significant body of research globally has examined teacher turnover and mobility, highlighting their critical impact on educational systems, teacher retention, and student outcomes. However, this study was the first of its kind in Saudi Arabia to investigate the factors influencing teacher transfers, providing a foundational understanding of this critical issue within the Saudi educational context. This quantitative, non-experimental study examined the reasons prompting teacher transfers between school districts and within schools in the same district. This study focused on all public-school teachers in Al-Jouf district who transferred within the past 5 years in Saudi Arabia. A total of 245 responses were collected across various educational levels in the Al-Jouf district. Data were collected using a validated survey instrument, the Reasons for Teacher Transfer in Public Schools Questionnaire, which measured five key factors: social conditions, working conditions, insufficient organizational support, leadership style, and student characteristics. Responses were gathered via an online distribution process and analyzed using SPSS (V29) to conduct descriptive and inferential statistical analyses. Descriptive and inferential statistical analyses were conducted to examine the factors influencing teacher transfers between different school districts in the Kingdom, transfers within the same district which is Al-Jouf district, and gender-based differences in transfer motivations. Descriptive analyses revealed that social conditions, particularly the desire to be closer to family and home region, was the most influential factor in both district and intra-district transfers. Working conditions, such as overcrowded classrooms and excessive teaching hours, ranked second, while student characteristics had the least impact on both transfers. To explore gender-based differences, independent samples t-tests were utilized. Results indicated statistically significant differences for external transfers between different districts, with male teachers rating excessive weekly teaching hours as more significant reasons compared to female teachers. Additionally, for internal transfers, the desire to be closer to family and home region showed a significant gender difference, with male teachers rating it higher than female teachers. These findings align with international research emphasizing the significant role of social and working conditions in influencing teachers' decisions to transfer, while highlighting the minimal impact of student characteristics.

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