Doctoral Dissertations

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

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Bayesian Variable Selection and Inference for Nonparametric Kernel Machine and Functional Models
Jin, Phil Geun (Virginia Tech, 2025-05-20)
In this dissertation, we have focused on developing three methods to address the challenges in highly correlated high-dimensional and functional data. In the first study, the Bayesian variable selection method is developed under a generalized fused multi-kernel machine regression. This method can apply to continuous/binary/ordered categorical response variables. We demonstrate the advantage of our method using bio-photonics Raman spectroscopy to identify which molecular fingerprinting wavenumber is associated with drug dosages of brain tumors. In the second study, we propose a Bayesian inference based on the Bayes factor. Our approach employs a generalized fused multi-kernel machine regression to adjust for multiple tests and identify significant pathways. The advantage of this method is illustrated by using genetic pathway data to test significantly correlated multiple pathways associated with Type II diabetes, estimating nonlinear relationships. Finally, we introduce a testing procedure for the departure of nonlinearity using a functional single index model. This procedure employs a randomly projected empirical process to reduce dimensionality while preserving essential statistical properties. The method is applied to autism brain imaging data to test whether fMRI signals are related to the autism diagnostic observation schedule. Therefore, the proposed three methods advance the field of variable selection and inference by offering innovative solutions to problems associated with correlated high-dimensional and functional data with practical applications across various domains.
Designing Electrolytes for Durable and Fast-Charging Alkali-Ion Batteries
Xia, Dawei (Virginia Tech, 2025-05-19)
Teaching English to Nonnative English-Speaking Chinese International Students: A Culturally Responsive Approach
Ruccolo, Vanessa L. (Virginia Tech, 2025-05-20)
With the increase in international students in U.S. higher education institutions in the past forty years (Durrani, 2023), the academic changes brought about by the COVID-19 pandemic, and ongoing political tensions with China, I sought to understand adaptations made by instructors to address the needs of Chinese international students. The purpose of this study was to explore the practices of instructors who teach English writing to nonnative speakers, specifically international Chinese students at higher education institutions across the United States. Participants were those instructors of gateway English/writing courses at both two-year and four-year higher education institutions who have at least 1 Chinese international student in their course within the last twelve months. This research project used comparative case study to conduct eight semi-structured interviews with participants from universities across the U.S. I used Gay's (2013) culturally responsive teaching theory as a lens for analyzing my findings to determine what mechanisms instructors use to address Chinese international student engagement and development in the course. This study examined how instructors of gateway first-year writing courses, both in-person and virtually, engage in classroom practices that give attention to Chinese international students for whom English is not their first language. I inquired about whether instructors use external resources and any possible changes or additional practices used in response to COVID-19. I wanted to look more closely at current instructor practices over the past decade with a focus on Chinese international students, given how universities actively court but do not properly support them. I sought to better understand how instructors cultivated and/or constructed better learning practices for nonnative English-speaking students over the course of their teaching careers, as well as the impacts of synchronous and asynchronous teaching in response to COVID-19. This study illuminated several key concerns instructors have, and these have been organized into two main categories: perceived issues and instructor approaches. I discuss these findings and then apply Gay's (2013) culturally responsive teaching as my lens for analyzing the instructor approaches to teaching NNES Chinese international students, using her four applied attributes to unpack the instructors' classroom experience as well as their perceptions of student experiences.
Exploring Novel Adjuvants and Herbicide Synergies: Pyridate and Ethoxylated Lecithin for Improved Control of Turfgrass Weeds
Corbett, Bret (Virginia Tech, 2025-05-20)
Transformation in US Agriculture: Insights from Energy Price Shocks, Ecosystem Service Enhancements, and Renewable Energy Developments
Hu, Chenyang (Virginia Tech, 2025-05-20)
Agriculture in the US is undergoing significant transformation in response to shifting energy markets, environmental challenges, and renewable energy policies. Using economic simulation and econometric models, this dissertation explores how changes in energy prices, renewable energy policies, and conservation programs influence agricultural production, land use, and environmental outcomes across the country. In the first chapter, the focus is on the impacts of energy price shocks and ethanol policy changes. Since agriculture relies heavily on energy, from fuel to fertilizers, changes in energy prices can significantly affect farming operations. The findings show that higher energy prices tend to increase the costs of production, leading to reduced output. A 40 percent increase in energy prices leads to crop output reductions of up to 13.7 percent for rice, 12.1 percent for corn, and 12.0 percent for oats, while prices increase by 9.6 percent, 6.8 percent, and 7.4 percent, respectively. Livestock output falls modestly, but higher prices offset these losses as pork and beef values increase by 13.1 percent and 3.1 percent, respectively. Conversely, a 40 percent drop in energy prices boosts crop output (e.g., corn +6.4 percent) and lowers prices (corn −3.9 percent), leading to only a 1.3 percent gain in value. Livestock value increases slightly (about 0.27 percent) due to higher output but falling prices. The study also evaluates the effects of increased ethanol demand. In the highest-demand scenario (increasing the blend wall, the allowable proportion of ethanol that can be added to gasoline, to 20 percent and quadrupling exports), corn production jumps by 44.8 percent, and processing for ethanol grows by 151.1 percent. This expansion reduces livestock feed costs by increasing the feed supply, thereby boosting pork, poultry, and beef output. However, the resulting increase in meat supply pushes prices downward, especially for pork (−6.2 percent), leading to a 3.4 percent decline in the total livestock sector value. The second chapter compares two agricultural conservation programs for reducing water pollution from nitrogen (N) runoff: (i) a Yield Reserve Program, which pays farmers to reduce fertilizer use; and (ii) an expanded Conservation Reserve Program (CRP), which pays farmers to take land out of production. The research finds that the Yield Reserve Program is generally more cost-effective at excess N reduction, reducing N loads by up to 771 million pounds under a 2 percent corn yield reserve scenario. However, it also causes a "rebound effect", increasing corn acreage by 9.2 million acres because lower per-acre fertilizer use combined with subsidies encourages more planting. The CRP shows a much stronger "slippage effect" as up to 76–79 percent of retired land is offset by marginal land brought into production, diluting the environmental benefits. Despite this, both programs show promise in excess N reduction, especially when targeted to high-output regions like the Corn Belt and Northern Plains. The third chapter shifts to a rapidly evolving issue in the energy transition: the siting of large-scale solar photovoltaic (LSSPV) facilities. Although solar energy is key to decarbonizing the power sector, new solar developments increasingly face community opposition. This study combines a nationwide property sales dataset with solar site locations to measure the impact of LSSPV proximity and visibility on nearby property values. Difference-in-differences estimates show that LSSPV significantly increases agricultural or vacant land value by about 19.4 percent within a 2-mile radius, while simultaneously reducing residential property values within 3 miles by about 4.8 percent. The estimated average negative impact on home values is primarily driven by site proximity and diminishes with both distance and time. Effect estimates are more robust to alternative specifications when proximity pairs with visibility rather than invisibility, but no evidence suggests visibility significantly amplifies the proximity effect. Heterogeneous effect estimates indicate that high solar lease potential, being in heavily Democratic-leaning counties, and brownfield redevelopment largely mitigate the negative residential value impact. The analysis reveals no significant heterogeneity of price impact across a few factors, including varying site visibility, directional orientation of properties relative to the LSSPV site, and different tracking systems. Evidence indicates that the negative impact on residential values might mostly stem from negative perceptions, but channels through physical conditions cannot be entirely dismissed. Our assessment provides benchmark information for local externality mitigation plans, potentially reducing community opposition and expediting the renewable energy transition. Together, these three studies offer a forward-looking view of the potential for US agriculture and rural economies to adapt to shifting energy landscapes, conservation needs, and renewable energy development. The findings provide valuable guidance for farmers, planners, and policymakers working to ensure sustainable and inclusive rural futures in a changing world.
Nonlinear Observers for Aircraft Maneuvering in Wind
Hopwood, Jeremy Winston (Virginia Tech, 2025-05-20)
Knowledge of wind velocity is fundamental across fields from atmospheric science to aeronautics, yet direct wind sensing is often constrained by operational limits. This motivates indirect wind estimation methods that infer wind from aircraft motion. However, typical model-based estimators lack rigorous stability guarantees across the full flight envelope --- a major limitation for safety-critical aerospace applications. This dissertation addresses these gaps by advancing nonlinear observer design and flight dynamic modeling to estimate wind from aircraft motion with assured performance. First, a symmetry-preserving, reduced-order state observer is introduced for the unmeasured part of a system's state, leveraging the fact that the system dynamics are invariant under the action of a Lie group. By using a moving frame to construct invariant observer mappings, both the design process and stability analysis are simplified. In cases where the system's nonlinearities comprise the Lie group's action, the nonlinear observer may even yield linear state estimation error dynamics to enable a multitude of design and optimization techniques that improve performance. Next, a quasi-steady nonlinear flight dynamic model for multirotor aircraft is derived from blade-element and momentum theory, ensuring validity over a large operating range while remaining identifiable from flight data. The utility of this model is assessed through a high-fidelity simulation study based on wind tunnel data. Recognizing the challenges of parameter estimation in large-domain models for unstable aircraft, a two-phase data collection methodology is proposed. In the first phase, a set of linear time-invariant models is identified at multiple operating conditions to define an uncertain linear parameter-varying (LPV) model. In the second phase, a robust LPV control law with an H-infinity norm bound guarantee is synthesized, enabling automated flights with sufficiently large excitation signals for nonlinear system identification. Finally, the nonlinear observer theory is combined with the large-domain flight dynamic models to achieve provably effective wind estimation for maneuvering aircraft. The framework is extended to uncertain aerodynamics and random turbulence by formulating the system as a stochastic differential equation. A nonlinear passivity-based wind observer is also introduced, serving as a full-order alternative to reduced-order methods. Together, these observers offer stability guarantees applicable to general maneuvering flight, demonstrated on both fixed-wing and multirotor UAVs. Overall, this dissertation contributes to safer, more autonomous aerospace systems.
Exploring the Genomic, Plant Growth Promoting, and Biocontrol Potential of a novum species 'Candidatus Pseudomonas auctus' JDE115 with its description
Ali, Md Sahadat (Virginia Tech, 2025-05-20)
'Candidatus Pseudomonas auctus' sp. nov. JDE115 is a Gram-negative, facultative anaerobic, motile, rod-shaped, and fluorescent bacterium isolated from soybean (Glycine max) root nodules in Virginia. Growth occurred at 0–5.0% NaCl (optimum 1%), pH 6.0–10.0 (optimum 7.0), and 10–40°C (optimum 28°C). Phylogenetic analysis based on the 16S rRNA gene and whole-genome sequencing placed JDE115 within the genus Pseudomonas, with the highest similarity to Pseudomonas glycinae MS586, but below species delineation thresholds for ANI (94.59%) and GGDC (57.10%). Chemotaxonomic analysis identified ubiquinone-9 (Q-9) as the dominant quinone and C16:0, C17:0 cyclo, and summed features 3 and 8 as major fatty acids. The DNA G+C content was 60.68 mol%. These features support the designation of JDE115 as a novel species. Genome sequencing revealed a 6.18 Mb genome with 5,648 genes, including 5,509 protein-coding genes. Functional annotation identified traits linked to phosphate, potassium, and zinc solubilization, siderophore production, systemic resistance induction, and antimicrobial compound biosynthesis, positioning JDE115 as a strong candidate for sustainable agriculture as both a biofertilizer and biocontrol agent. Functional assays demonstrated that JDE115 promotes plant growth under nutrient-deficient conditions. Inoculation of soybean plants with JDE115 enhanced shoot biomass, root development, nodule numbers, and total nitrogen uptake. Auxin production, phosphate solubilization, and biofilm formation traits contribute to its beneficial plant interactions, highlighting its potential as a multifunctional bioinoculant for sustainable agriculture and food security. JDE115 also exhibited potent biocontrol activity against the soil-borne fungal pathogen Agroathelia rolfsii, the causal agent of southern blight. Dual-culture and broth assays showed complete fungal inhibition, and scanning electron microscopy confirmed structural damage to fungal sclerotia. JDE115 produces a range of antifungal compounds, including chitinase, glucanase, protease, cellulase, siderophores, hydrogen cyanide, and volatile organic compounds (VOCs) such as dimethyl disulfide (DMDS) and 1-undecene. Greenhouse experiments confirmed that JDE115-treated soybean plants remained disease-free, while untreated controls succumbed to infection. Further evaluations demonstrated that JDE115 effectively suppresses soybean cyst nematode (Heterodera glycines) and root-knot nematodes (Meloidogyne spp.). Greenhouse assays revealed over 90% local and 85% systemic suppression of SCN reproduction. VOC profiling confirmed the production of DMDS and 1-undecene, with bioassays showing that 1-undecene induces nematode avoidance and mortality without direct contact. High hydrogen cyanide production and enzymatic inhibition of egg hatching and juvenile survival contribute to its nematicidal activity. Overall, 'Candidatus Pseudomonas auctus' JDE115 demonstrates broad-spectrum plant growth-promotion and biocontrol capabilities. Its multimodal mechanisms—including nutrient mobilization, systemic resistance induction, and pathogen and pest antagonism—position it as a promising microbial tool for integrated pest management and sustainable crop production.
Novel Electromagnetic Properties of Elementary Particles
Mathur, Varun (Virginia Tech, 2025-05-19)
Quantum electrodynamics is our most precisely and stringently tested theory. What happens when some non electrically charged elementary particles couple to the photon? We discuss neutrino electromagnetic properties, a dark photon portal to dark matter and magnetic monopoles produced by cosmic rays in the milky way. We don't just discuss these models, but show how to place(in some cases) leading constraints on these models using future particle physics experiments or astrophysics. The Deep Underground Neutrino Experiment will have the highest muon neutrino flux yet, and will be able to constrain neutrino electromagnetic properties better than current terrestrial experiments. Dark matter is known to be cold, but a subcomponent could be hot or boosted, if this is a dark photon which necessarily couples to the photon, we could see this in future gaseous detectors which are better suited because they have less in-medium effects than liquid Xenon for example. Monopoles of TeV scale masses can be produced by Cosmic Ray - Interstellar Medium collisions. These monopoles would impact the well measured 10−6 Gauss galactic magnetic field or it's production mechanism allowing us to place constraints on monopole cross section.
Paradoxum Ex Machina: Exploring the Impact of Generative Artificial Intelligence Technologies on the Strategies and Actions of Entrepreneurial Ventures
Rady, Judy Maged Mohammad Abdelhalim (Virginia Tech, 2025-05-19)
The rapid advancements of artificial intelligence (AI)—and more recently, generative AI (GenAI)—are fundamentally reshaping the entrepreneurial landscape, altering how entrepreneurs acquire critical resources, tackle uncertain environments, develop opportunity, and address entrepreneurial action processes. Despite these dramatic transformations that we have already witnessed, the era of AI technologies is often described as 'just the beginning.' As these transformative technologies become the new norm in the field of entrepreneurship, the use of these technologies raises important questions regarding the transformative benefits as well as the perils these technologies introduce in the entrepreneurial landscape. Accordingly, this dissertation explores the dual nature of AI and GenAI as both enablers and disruptors in entrepreneurship, offering a theoretical and empirical investigation into their transformative effects across three core entrepreneurial domains: legitimacy and resource mobilization, opportunity identification, and venture ideation. Through three interrelated essays, this dissertation explores three critical paradoxes that are introduced or magnified by GenAI technologies to provide a profound understanding of how entrepreneurs are able to create and capture value by using with these technologies. The first essay focuses on the paradox of legitimate distinctiveness, analyzing how AI startups use rhetorical strategies (i.e., particularly firm hype) to attract and secure investor support. This empirical study demonstrates that while moderate hype enhances firm valuation, excessive hype backfires unless bolstered by credibility and comprehensibility factors. This study also offers novels empirical contributions to the field of entrepreneurship by developing a computational linguistic approach to measure hyperbole, offering methodological tools for future research. The second essay investigates the automation-augmentation paradox, theorizing the emergence of hybrid intelligence through entrepreneur–AI ensembles and its implications for the rise of cyborg entrepreneurship. By integrating entrepreneurial and artificial intelligence, these ensembles, or as "cyborg entrepreneurs," demonstrate enhanced task performance through the emergence of a shared cognitive system shaped by complementary human and AI capabilities. The essay defines and conceptualizes hybrid intelligence as comprising three core dimensions: transactive memory, generative learning, and meta-heuristic reasoning. Together, these dimensions provide a theoretical framework for understanding how hybrid intelligence influences opportunity identification, entrepreneurial action, and entrepreneurial overall task performance. The third essay addresses the paradox of future knowledge by examining the epistemic risks GenAI introduces during the ideation stage and their potential impacts on opportunity actualization processes. While GenAI can produce highly creative venture ideas, these outputs may be erroneous, misleading, implausible, or difficult to interpret. Drawing on the entrepreneurial work and entrepreneurial judgment literatures, this essay explores the unique types of challenges these tools pose and mechanisms for entrepreneurs to navigate them. Specifically, it introduces a novel entrepreneurial judgment framework, comprised of possibility and plausibility judgments, to guide entrepreneurs in assessing the attainability and potential value of pursuing and acting on GenAI-generated ideas. This framework provides a structured lens for mitigating epistemic uncertainty and enhancing decision quality during early-stage opportunity development. Collectively, these essays provide a cohesive theoretical foundation for understanding how the growing adoption of AI and GenAI influences entrepreneurial action, cognition, and communication, offering multifaceted contributions to sociology of expectations, entrepreneurial cognition, entrepreneurial judgment, and entrepreneurial action theories. They highlight both the promise and perils of these technologies, laying the groundwork for future research and offering practical insights for navigating a rapidly evolving entrepreneurial environment.
Responsibly Emboldening Predictions via Boldness-Recalibration
Guthrie, Adeline Pearl (Virginia Tech, 2025-05-19)
Probability predictions are essential to inform decision making across many fields. Ideally, probability predictions are (i) well calibrated, (ii) accurate, and (iii) bold, i.e., spread out enough to be informative for decision making. However, there is a fundamental tension between calibration and boldness, since calibration metrics can be high when predictions are overly cautious, i.e., non-bold. The purpose of this work is to develop a Bayesian model selection-based approach to assess calibration, and a strategy for boldness-recalibration that enables practitioners to responsibly embolden predictions subject to their required level of calibration. Specifically, we allow the user to pre-specify their desired posterior probability of calibration, then maximally embolden predictions subject to this constraint. We demonstrate the method with a case study on hockey home team win probabilities and then verify the performance of our procedures via simulation. Additionally, we introduce BRcal, an R package implementing Boldness-Recalibration and supporting methodology. We reformulate boldness-recalibration as a nonlinear optimization of boldness with a nonlinear constraint on calibration, and describe how this is implemented in BRcal. The BRcal package is demonstrated using a case study on foreclosure prediction. Lastly, we extend the methods to account for underlying spatial association in the data and demonstrate via a case study on moose presence.
Soil-derived dissolved organic matter cycling at terrestrial-aquatic interfaces: Implications for wetland-dominated landscapes, stormwater control measures, and drinking water supply
Wardinski, Katherine Mary (Virginia Tech, 2025-05-19)
Terrestrial-aquatic interfaces (TAIs) are transitional zones between the terrestrial landscape and aquatic ecosystems (e.g., soil-water, floodplain-river, upland-wetland). Water movement across TAIs, known as hydrologic connectivity, mediates the transport and transformation of biogeochemically significant substrates, such as carbon and nutrients. Dissolved organic matter (DOM) is a soluble and reactive form of carbon comprised of organic molecules derived from allochthonous (e.g., soils, plants) and autochthonous (e.g., algae, microbes) sources. Soils are source of DOM found at TAIs. However, hydrologic connectivity of soils located at TAIs can be spatiotemporally variable. This dissertation seeks to quantify how variable hydrologic connectivity influences the transport and transformation of soil-derived DOM across TAIs. Using a combination of laboratory and field based methods, soil-derived DOM was characterized in three different soil ecosystems (1) urban stormwater control measures, (2) wetland-dominated landscapes, and (3) forested drinking supply watersheds. First, anthropogenic stressors in urban landscapes are known to alter DOM cycling but few studies have explored DOM cycling from stormwater control measures (SCM) soils. I leached water-soluble organic matter (WSOM), a proxy for soil-derived DOM, from the soils of SCMs to explore how SCMs design influences DOM cycling in urban settings. There were low quantities of WSOM, regardless of SCM type. The composition of WSOM was similar to other WSOM studies in natural soil ecosystems. The composition of WSOM was more microbial-like than SCM surface water, highlighting how the route of water movement through an SCM (e.g., runoff retained in an SCM as surface water versus runoff filtering through engineered soils) influences the composition of DOM exported to downstream aquatic ecosystems when SCMs are hydrologically connected during storm events. Second, wetlands in low-relief landscapes have dynamic TAIs, but few studies have quantified DOM release as a result of seasonal groundwater saturation and rapid water level changes during precipitation events. I simulated vertical groundwater saturation on intact wetland soil cores over a 40-day laboratory experiment and analyzed the concentration and composition of DOM in soil porewater. Porewater DOM concentrations were sustained over the 40-days, supporting the hypothesis that wetland soils can act as quasi-infinite sources of DOM. As experimental saturation progressed, DOM composition shifted towards more aromatic, plant-like organic matter signatures. I then performed in-situ sampling of porewater and wetland surface water at two wetlands during an early winter rain event. As wetland water levels rose and the soil-water interface expanded outwards, surface water DOM tended to be more dynamic while porewater DOM concentrations were stable. A simple water and DOM mass balance suggests that groundwater inputs sustained wetland surface water DOM during the rain event. Finally, high levels of DOM can lead to the formation of disinfection byproducts (DBP) during drinking water treatment which pose a threat to human health. Further work is needed to quantify and predict the DBP formation potential of soil-derived DOM to inform watershed management and protect drinking water quality. I leached Water-Extractable Organic Matter (WEOM), similar to WSOM, from soils collected in drinking supply watersheds. Chlorinating WEOM samples demonstrated that soil-derived DOM has the potential to exceed DBP regulatory limits. WEOM composition and watershed characteristics were explanatory variables of WEOM DBP formation potential. Together, these findings further our understanding of how variable hydrologic connectivity influences soil-derived DOM cycling at TAIs in both natural and engineered soil systems with implications for carbon cycling and water quality.
Integrating Groundwater Conservation and Risk Mitigation under Uncertainty: Strategies for Sustainable Aquifers and Agriculture
Yu, Qiuyun (Virginia Tech, 2025-05-19)
Groundwater is a crucial resource for agricultural production globally, especially in water-scarce regions. However, increased irrigation demands, weak governance, and climate change-induced variability threaten the sustainability of aquifers, jeopardizing long-term agricultural productivity. This dissertation investigates how integrating groundwater conservation policies with financial risk management strategies can simultaneously achieve aquifer sustainability and maintain economic stability for farmers. The research specifically focuses on the Sheridan-6 Local Enhanced Management Area (LEMA) in Kansas, U.S.A, an innovative groundwater conservation initiative that implements multi-year pumping restrictions. Employing a multi-method approach—including stochastic optimization, mixed-integer programming, and agent-based modeling—this study comprehensively evaluates how farmers respond to regulatory constraints, uncertain weather patterns, and economic conditions. Findings highlight that multi-year groundwater allocation systems, such as LEMA, provide farmers with valuable operational flexibility to strategically manage limited water resources amidst varying precipitation and fluctuating market prices. Crop insurance (revenue protection with 75% coverage level) emerges as a critical financial instrument for stabilizing farm incomes and mitigating risk; however, it can unintentionally incentivize higher groundwater use, thus potentially undermining conservation objectives. Agent-based simulations further demonstrate nuanced farmer behavioral responses, revealing complex adjustments in cropping decisions, irrigation practices, and compliance behaviors under different regulatory and economic scenarios. Results underscore the inherent trade-offs farmers face between short-term farm profitability and long-term aquifer sustainability. Ultimately, the dissertation emphasizes the necessity of aligning groundwater policies with economic incentives to balance resource conservation with agricultural resilience. The insights and methodologies developed here offer valuable guidance for scalable and adaptive groundwater management strategies, providing robust policy recommendations for other regions facing similar groundwater sustainability challenges.
When the Map Fails the Territory: Hidden State Models, Complex Traits and the Evolution of Bird Migration
Bone, Nicholas Jordan (Virginia Tech, 2025-05-19)
Phylogenetic comparative methods often rely on simplifying complex biological traits into discrete categories, potentially obscuring evolutionary patterns and generally limiting inferences. This dissertation confronts this ``map versus territory" problem by developing and evaluating methodological approaches that integrate known and unknown trait complexity into macroevolutionary analyses. To establish the statistical power of discrete methods in detecting trait complexity, I first demonstrate the utility of structured hidden Markov models (SHMMs) for identifying underlying continuous architectures, like threshold traits, within simulated and empirical discrete datasets (Chapter ref{ch:1}). Taking bird migration as an example of a hard-to-measure complex trait, I then develop new continuous metrics of bird movement from large-scale community science (eBird) data, using entropy-based measures and phylogenetically aligned component analysis (PACA) to reveal a multi-dimensional structure of evolutionarily relevant combinations of traits, representing underlying movement behavior in North American birds (Chapter ref{ch:2}). Next, I fit SHMMs informed by this structure to global and North American bird phylogenies, testing hypotheses about how migration may have evolved, while accounting for classification ambiguity (Chapter ref{ch:3}). I show that models incorporating hidden states that imitate the structure from Chapter ref{ch:2} were often preferred over generalized hidden Markov models and standard Markov models, suggesting that migration both contains hidden complexity and evolves along specific pathways. Overall, this dissertation provides a methodological framework for integrating continuous data and theoretical knowledge into discrete trait analyses, demonstrating a more holistic treatment of how to treat complex discretized traits like avian migration in phylogenetic comparative methods.
Optimizing Search and Rescue Canine Welfare and Performance
Dickinson, Sally Anne (Virginia Tech, 2025-05-19)
Despite technological advancements, Search and Rescue (SAR) dogs remain essential in disaster response and locating missing persons. However, their unique physiological and psychological needs are often underappreciated, insufficiently understood, or deprioritized in favor of mission objectives. In this dissertation, I apply the tactical athlete framework, commonly used for military personnel and first responders, to SAR dogs, emphasizing the role of physical conditioning in promoting stress resilience and optimizing performance. Initially, we surveyed 192 SAR handlers to assess their perceptions of frustration, arousal, and stress, their sources, and the role of physical conditioning in mitigating their effects. While over 50% of handlers engaged in regular physical conditioning outside of SAR training, many handlers lacked an accurate measure of their SAR dog's physical fitness, a challenge similar to that faced by humans, who increasingly rely on wearable technology, such as smartwatches, to optimize conditioning and monitor physiological responses. To explore practical physiological monitoring methods, we conducted a validation study comparing a medical-grade electrocardiogram (ECG) with two commercially available heart rate monitors (Polar H10 and PetPace) to evaluate their suitability for SAR operational settings. These findings provide valuable insight into the feasibility and accuracy of wearable biometric monitoring for SAR dogs. Many handlers also acknowledged in the survey that frustration occurs in SAR dogs; however, they did not directly associate frustration with stress. Research defines frustration as an emotional response to a blocked goal and considers it a negative welfare state. Survey findings indicated that handlers frequently use frustration in training to elicit desired behaviors and prepare SAR dogs for real-world scenarios. We investigated whether frustration, a psychological stressor, results in measurable changes in performance and well-being, distinct from physiological stress caused by exercise. We found that elevated frustration could be identified through biometric monitoring and was behaviorally associated with decreased performance. Finally, we explored whether SAR dogs could benefit from the K9 tactical athlete concept beyond the expected improvements in endurance and strength. While many handlers in our survey reported engaging in weekly physical conditioning, responses indicated that many did not explicitly recognize its psychological benefits. We applied the K9 tactical athlete framework in a 7-week conditioning program to examine this further. Dogs that demonstrated improved physical fitness also enhanced performance in stress-inducing search tasks. Collectively, this research underscores the need for accessible handler education and technology to support the monitoring and interpretation of SAR dogs' physiological and psychological states. Furthermore, these findings contribute to the scientific understanding of stress responses in SAR dogs and propose methods to mitigate the stress response, thereby optimizing welfare and operational effectiveness in these critical working dogs.
Non-smooth dynamics and sensitivity analysis of multibody systems with clearances and friction in differential variational inequality framework
Chaturvedi, Ekansh (Virginia Tech, 2025-05-19)
Mathematical representations of multibody systems can be classified into two categories based on the type of constraints they carry. Ideal constraints in the multibody systems are the ones which enforce absolute alignment of bodies with respect to each other in the desired direction of motion. However, clearances in mechanical joints are integral to all real-world multibody systems. The clearances between the bodies allow the bodies to undergo a certain misalignment and the dynamics is governed by the contacts thus formed. The conventional formulations of joints as smooth algebraic constraints ignore the effect of clearances. To deal with contacts, and hence clearances, while the popular continuous dynamics approaches assume the Hertzian nature of the contact modeled by nonlinear unilateral spring-damper elements, the non-smooth dynamics approach results in a differential variational inequality (DVI) problem with complementarity constraints. This work provides a comprehensive re view of key contributions in the field of non-smooth dynamics and describes a framework to implement the non-smooth dynamics approach to fundamental mechanical joints with clearances with dry friction. Since clearances are small compared to the dimensions of me chanical components, contact is assumed to be inelastic. Based on this assumption and the general non-smooth dynamics framework, parametric formulations are derived for cylindri cal, prismatic, and revolute joints with clearances. The equations of motion of systems with clearances and friction, and their time-discretized counterparts are derived as second or der cone-programming (SOCP) problem. Although the SOCP framework can also simulate systems with ideal joints, eliminating friction carrying elements results in a condensed con vex quadratic programming (QP) form. Both formulations are compared for systems with frictionless joints with clearances. Additionally, special focus is given on rotation preserv ing Lie-group integration schemes for smooth as well as non-smooth systems, to circumvent the normalization constraint on quaternions. The problem formulations are assessed through multiple case-studies, demonstrating the versatility of the non-smooth formulation, and a de tailed analysis of the results is presented. With a unified framework available for simulating frictional contacts as well as ideal-joints with friction, sensitivity analysis equations are de rived forming a generalized sensitivity analysis framework for smooth as well as non-smooth systems. In addition, as another step towards making a robust framework, higher-order time integration is explored in differential algebraic equations on Lie-groups, using a time-finite element approach.
Does better sleep set the stage for a physically active and progressive workday? Considerations across the daily cycle of rest, commuting, and work
Dosumu, Fiyinfunjah Adenike (Virginia Tech, 2025-05-19)
This dissertation explored employee daily experiences through the lens of the resource allocation process whereby employees strive to meet their daily work and non-work demands and incorporate valuable experiences and activities into their workday. Previous research has largely focused on segmented aspects of employee daily lives. However, there is limited research on how employees' daily activities in their work and non-work lives may interrelate in a more dynamic sense. I assess how employees' recovery through nightly sleep quality may set the stage for subsequent engagement in moderate-to-vigorous physical activity, and the implications of this intensity of physical activity for job performance, specifically for employees who primarily commute to a physical work location. Using the effort-recovery model, I hypothesized that nightly sleep quality will positively covary with moderate-to-vigorous physical activity. I additionally considered a potential moderating influence of commute variability on the relationship between nightly sleep quality and moderate-to-vigorous physical activity. I then assessed moderate-to-vigorous physical activity as an antecedent of work goals progress, using the resource-based model of physical activity and job performance as my theoretical basis. My final sample consisted of 81 employees who commute to and from work at least 15 minutes each way. Using multilevel structural equation modeling, which enabled modeling at the within- and between-person level of analysis, I found that daily engagement in moderate-to-vigorous physical activity positively related to daily work goals progress. Furthermore, higher levels of engagement in moderate-to-vigorous physical activity on average influenced higher levels of work goals progress on average. This dissertation contributes to the scientific understanding of the implications of physical activity for work criteria.
Exploring host-parasitic plant interactions by examining mechanisms of resistance and susceptibility
Kaur, Sukhmanpreet (Virginia Tech, 2025-05-19)
Parasitic plants extract water and nutrients from host plants by using specialized structures called haustoria. These interactions can cause 100% crop losses, yet growers lack control options that are effective and affordable. Host crops with resistance to parasitism would be an ideal solution to the problem, but well-characterized examples of host resistance to parasitic plants are limited. This dissertation examines plant responses to parasitic plant infection. It includes studies on resistance mechanisms in carrot (Daucus spp.) against two major parasites, the root parasite Phelipanche aegyptiaca (Egyptian broomrape) and the shoot parasite Cuscuta gronovii (swamp dodder), as well as investigations into Arabidopsis and tomato molecular responses to parasitism. These comparative studies reveal parasite-induced changes in hosts across diverse plant systems. The chapter II of the dissertation examines interactions between P. aegyptiaca and wild carrot accessions (D. glaber, D. littoralis). Phenotypic and biochemical analyses revealed pre-attachment resistance due to reduced exudation of parasite germination stimulants called strigolactones from roots of the wild carrots. Additional post-attachment resistance was also documented. The chapter III evaluates responses of wild and cultivated carrot (D. glaber, D. carota cv. 0493B) to C. gronovii. While D. glaber was susceptible, carrot cultivar 0493B displayed complete resistance. Histochemical analysis showed that haustoria failed to establish vascular connections in resistant plants and triggered localized pigmentation. Metabolomic profiling indicated parasite-induced shifts in host metabolism. A resistance-associated QTL was mapped to Chromosome 1 (30–50 Mb), and transcriptomic analysis identified four candidate genes, including one potentially involved in lignin biosynthesis. Chapter IV broadens the investigation by characterizing host responses to P. aegyptiaca in a well-studied model species, Arabidopsis thaliana, and an economically important P. aegyptiaca host, Solanum lycopersicum. Rather than focusing on resistance, this chapter investigates how susceptible hosts respond to parasitic infection, with a focus on transcriptomic changes in the host during infection. Analyses revealed that both hosts shifted their gene expression related to defense and cell wall metabolism, while species-specific differences were found as well, with tomato inducing hormone signaling, particularly ethylene, more than Arabidopsis in early stages of parasitism. Chapter V again focuses on wild carrots and the biosynthesis of phenylpropenes, a group of secondary metabolites, which serve as natural defense compounds and have pharmaceutical and industrial applications. Tissue specific analyses of phenylpropenes and a corresponding differential gene expression analysis were conducted to determine key genes in phenylpropene formation. Gene candidates for cytochromes P450 and O-methyltransferases catalyzing the proposed enzymatic steps in phenylpropene metabolism were identified. These analyses provide a foundation for future investigations of phenylpropene formation in carrots and other plant species. Together, these studies enhance our understanding of resistance in host–parasite interactions and offer genetic and biochemical insights into protecting carrots and other crops to improve crop resilience, agricultural productivity and food security.
The Landscape of Impact: Creating a New Design Framework for Targeted Project Outcomes Through a Practice Based Approach to Research
Bradley, Sharon Eileen (Virginia Tech, 2025-05-16)
The purpose of this research was to explore the potential for design to achieve wide-ranging, positive impacts in targeted and measurable ways. An increasing number of studies indicates that the built environment plays a substantial role in public health and well-being, yet even fundamental human needs such as access to healthy food and safe outdoor spaces are absent in many communities. This research was conducted as a Practice Based Research investigation. It examined a body of work - that of my 30-year practice, Bradley Site Design - and mined it as an empirical resource. Combined with a comprehensive literature review, the investigation formed the basis for a new design methodology and business model that prioritizes the health and wellbeing of people and planet. The examination of project and practice artifacts in the context of established discourse on topics such as impact assessment resulted in a synthesis of applied and theoretical knowledge, revealing new perspectives in design practice. The resulting research product is Design For Impact, a methodology and set of instruments that provide a framework to address localized community needs and generate outcomes that measurably affect human wellbeing, economic stability, and environmental health.
Systems to Transform Interdisciplinary Graduate Education: An Ecological Systems Analysis of STEM Graduate Students' Longitudinal Interdisciplinary Identity-Based Motivation
Webb, Margaret (Virginia Tech, 2025-05-16)
Despite growing recognition that solving complex global challenges requires interdisciplinary approaches, traditional academic structures continue to create significant barriers for STEM graduate students attempting to pursue interdisciplinary work. To address these barriers, this dissertation examines how academic systems influence interdisciplinary identity development and motivation among STEM graduate students through the lenses of Ecological Systems Theory (EST) and Future Possible Selves (FPS). Drawing on longitudinal interviews with graduate students in an Interdisciplinary Disaster Resilience program, this case study reveals complex developmental trajectories, salient microsystems, and system interaction patterns that shape interdisciplinary scholar formation. The research unfolds across three interconnected manuscripts that : 1) identify three patterns of interdisciplinary identity development that challenge linear models; 2) map 12 critical microsystems, spanning past, present, and future, that influence development; and 3) analyze how the core functions of these microsystems act and interact to create supports, barriers, and negotiations in students' development. By integrating EST with FPS, this work demonstrates that interdisciplinary development emerges through interactions among individual aspirations and the entrenched functions of academic microsystems rather than simple acquisition of specific skills or competencies. The findings help explain why sustainable change in interdisciplinary graduate education remains challenging: stable patterns within academic microsystems operate to sustain underlying core functions that actively resist isolated modifications and privilege disciplinary over interdisciplinary development.
Pancreatic Cancer: Oncomicrobes, Electric Fields, and Fluid Flow
Ahmad, Raffae Nazir (Virginia Tech, 2025-05-16)
The pancreatic tumor microenvironment exhibits remarkable complexity, prompting critical investigations into how the microbiota influences tumor progression and how stromal elements impact interstitial fluid dynamics. This dissertation examines dual aspects of this complexity: first, by elucidating the specific contributions of Fusobacterium nucleatum (F. nucleatum) to pancreatic cancer pathogenesis and developing a novel therapeutic approach for eliminating these intracellular bacteria; and second, by analyzing how a stromal-targeted therapy directed at hyaluronic acid modulates interstitial fluid flow within pancreatic tumors using clinical patient data. We demonstrated that F. nucleatum invade both pancreatic cancer cells and normal pancreatic epithelial cells (nPECs). This invasion process was partially mediated by the bacterial adhesin Fap2. nucleatum infection induced a distinct cytokine secretion profile, characterized by elevated IL-8, CXCL1, MIP-3α, and GM-CSF. F. nucleatum invasion promoted migration and proliferation in Panc1 and BxPC3 cancer cell lines. Conditioned media from infected BxPC3 cells stimulated migration in both uninfected BxPC3 and Panc1 cells, suggesting paracrine effects. While F. nucleatum-infected nPECs exhibited a similar cytokine profile, they did not display increased proliferation or self-migration. However, conditioned media from infected nPECs enhanced BxPC3 cancer cell migration, indicating potential cross-talk. Building on these findings, we engineered an electro-antibacterial therapy (EAT) that enhances antibiotic delivery into the intracellular compartment. This approach employs pulsed electric fields to achieve controlled permeabilization of host cell membranes through precise modulation of electric field strength. By combining pulsed electric fields with a standard-of-care antibiotic, we achieved greater than 99% clearance of intracellular F. nucleatum from pancreatic cancer cells. We next examined the broader biophysical features of the tumor microenvironment. We characterized interstitial fluid flow in pancreatic cancer patients, recognizing that desmoplasia creates significant barriers to treatment and influences interstitial fluid pressure. Our analysis of patients treated with PEGPH20, a hyaluronidase enzyme, revealed a transient reduction in velocity magnitudes one day post-treatment, though values generally returned to baseline by the conclusion of the dosing cycle. We observed substantial heterogeneity of velocity magnitudes both within individual tumors and across multiple tumors within the same patient. In one patient with five distinct tumors, we identified variable treatment responses that correlated with tumor size, though velocity magnitude itself did not emerge as a reliable predictor of treatment response.

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