Doctoral Dissertations

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

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When Being Normal Isn't the Goal: How Therapists Co-Transform Beyond Normal with their Autistic Clients
Tillett, James Ian Skipper (Virginia Tech, 2025-01-23)
For over a century, attempts to fix, capture, and control a way of being now known as "autism" have haunted and harmed countless autistic people, all under the guises of medical care and treatment. These unjust events precipitated from rigid Western scientific and cultural paradigms about what is real and what is normal, leading to the deep misunderstanding and social oppression of autism and other non-normative ways of being. Presently, autistic people still endure oppressive and traumatic behavioral interventions and minority stressors (such as internalized prejudice and discrimination) in consequence of living in an "autistiphobic" world – a world that is preoccupied with being normal. Yet, non-normative ways of being such as autism generate new possibilities, which can liberate and facilitate connections between people. Systemic and cybernetic therapy frameworks – in combination with insights from the neurodiversity paradigm of autism – may offer insights into co-transformative psychotherapy practices with autistic clients and people close to them, enabling more authentic autistic being in the world. This study used interpretative phenomenological analysis to explore how neurodiversity paradigm-embracing therapists retroactively make sense of their co-transformations with autistic clients; specifically, their reinterpretations of social normativities and connectedness. Results showed that participants came to both 1) recognize and oppose normative oppression in their therapeutic practices and 2) align with neurodivergent authenticity, autonomy, and connection as therapists and people. Implications of this research for therapeutic practice and broader sociopolitical issues are discussed at the end of the project. The goal of this research is to offer curious therapists possible paths for ethical, liberatory, and generative work with autistic clients.
China's Forest Product Imports and the Impacts on Tropical Forests
Sun, Xiufang (Virginia Tech, 2025-01-23)
China's forest product imports have surged over the past two decades, fueled by robust economic growth and an inadequate domestic timber supply. In 2017, China implemented a complete logging ban in its natural forests, further widening the domestic timber supply gap. Many observers highlight the large and expanding trade volume as a significant driver of deforestation and forest degradation, especially in tropical regions. This research investigates the relationship between China's imports of wood-based forest products and tropical forest loss (deforestation), as well as the impacts of China's complete logging ban in natural forests in shaping this relationship. I found that the logging ban has contributed China's timber imports from both provincial-level and supplying countries' analyses. However, economic development, wood products exports, and forest endowment have also played important roles. I found a positive relationship between China's imports of wood-based forest products and the forest loss across all tropical countries, except in Latin America. Additionally, land conversion to agricultural production and pasture for livestock, and rural population are important drivers of the tropical forest loss. The analysis results provide insight into the complex policy, environmental, and economic factors influencing China's imports and tropical forest loss. This research offers valuable guidance for the Chinese government in crafting balanced policies that protect domestic forests while addressing tropical deforestation.
Oxidation of Tetrahydropyridines by MAO B Biomimetics: Mechanistic Studies
Price, Nathan James (Virginia Tech, 2025-01-23)
The Parkinsonian Syndrome-inducing effects of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) on the body have been well-documented since its discovery. However, its mechanism of oxidation by monoamine oxidase B (MAO B) has been debated for just as long. Proponents of the single electron transfer (SET) pathway of oxidation faced severe critiques in that the hypothesized radical intermediates arising from the SET pathway were never directly observed. Work performed herein provides that exact evidence using biomimetics of MAO B. The first section of the dissertation will highlight the ability of one such biomimetic, 3-methyllumiflavin (3MLF), to provide a chemical model for the oxidation of -unsaturated tetrahydropyridines. Using a nontoxic analog of MPTP, 1-methyl-4-(1-methyl-1-H-pyrrol-2-yl)-1,2,3,6-tetra-hydropyridine (MMTP), reactions with 3MLF were performed under both aerobic and anaerobic conditions. The anaerobic studies of these reactions proved to be the key to the direct observations (by 1H NMR and EPR) of flavin-derived radical behavior. Armed with the knowledge of how to prepare reactions for the direct observation of flavin radical intermediates, studies of N-cyclopropyl substrate derivatives were subsequently conducted to gather evidence for the formation of radical substrate intermediates. If the hypothesized SET is the first step of the reaction mechanism, then the resulting aminyl radical cation could undergo a cyclopropyl ring opening. Several products derived from the substrate were observed; among them were ring-opened variations suggesting that the reaction does begin with a SET. Thermodynamically, this process is unfavorable, leading to the hypothesis that this reaction step may be better described as a proton-coupled electron transfer (PCET). The kinetics of this process were studied at length. Finally, to provide a more compelling argument for the fundamental reactivities, two other flavin biomimetics are investigated. Their reactions with tetrahydropyridines were put under the same scrutiny as 3MLF, leading to the conclusion that the chemistry discussed herein is not unique to 3MLF, but is much more broadly applicable to other flavin biomimetics and MAO B.
Three-Dimensional Fluid Simulations of Mid-Latitude Ionospheric Processes with Hybrid Chebyshev/Fourier Pseudo-Spectral Methods
Almarhabi, Lujain (Virginia Tech, 2025-01-23)
Ionospheric irregularities are small-scale plasma density structures driven by instabilities arising from combinations of plasma drifts, density gradients, and electric fields. These irregularities can cause mid-latitude GPS scintillations, characterized by amplitude and phase fluctuations that degrade communication link performance. However, the processes behind these scintillations remain poorly understood due to limited models and observations. This thesis explores the Gradient Drift Instability (GDI) and Kelvin-Helmholtz Instability (KHI) to understand their potential roles in driving mid-latitude ionospheric turbulence and irregularities.par Initial investigations involved a two-dimensional (2D) numerical model to study density irregularities in the Subauroral Polarization Streams (SAPS). This model analyzed the turbulence spectra of the GDI. Previous work identified GDI as a key mechanism for generating ionospheric irregularities in SAPS, emphasizing the role of background electric fields and velocity shear in shaping turbulence. Using a fixed background density profile and varying latitudinal velocity profiles, the model explored how velocity shear location and neutral wind direction affect turbulence spectra of the GDI and their associated power laws. Turbulence spectra for cases with no velocity profile and with different neutral wind directions are analyzed. The impact of velocity shear is studied by translating the velocity shear location relative to the density gradient. Numerical spectral analysis results are presented and compared to recent experimental observations.par A newly developed three-dimensional (3D) electrostatic fluid model extends these investigations to capture the behavior and evolution of ionospheric plasma clouds. Historically, these artificial plasma clouds have served as a case study for understanding irregularity evolution in the textit{F} region. The GDI, driven by the (mathbf{E}timesmathbf{B}) drift, was identified as the primary mechanism causing rapid structuring of these clouds, cascading energy to smaller scales transverse to the magnetic field. Nonlinear 2D and 3D simulations were conducted across three regimes: highly collisional ((approx 200 , si{km})), collisional ((approx 300 , si{km})), and inertial ((approx 450 , si{km})). The results show that structuring evolves more slowly in 3D simulations due to additional dynamics, particularly the ambipolar potential in the current closure equation, which introduces an azimuthal "twist" around the magnetic field axis. In the collisional regime, this twist disrupts flute-like perturbations ((k_{parallel} neq 0)), while in the inertial regime, the cloud rapidly diffuses, retaining flute-like perturbations ((k_{parallel} = 0)).par Building on this 3D model, altitude-dependent neutral and plasma density profiles were incorporated to better represent ionospheric parallel dynamics. This enhanced model captures ionospheric irregularities, their generation mechanisms, and their altitudinal variations. It was used to examine the dominance and interplay of GDI and KHI within SAPS across varying altitudes, advancing our understanding of mid- to high-latitude ionospheric turbulence processes.par This work was supported by NASA under Grant Number $NASAMAG16_2-0050$, the Kevin T. Crofton Department of Aerospace and Ocean Engineering, and the Bradley Department of Electrical Engineering at Virginia Tech.
Exploring the Impact of Personality Awareness and Personality-based Influencing Preferences on the Perceived Influence Capacity of New Leaders in Higher Education Community-engaged Practice
Thompson, Crissy Loraine (Virginia Tech, 2025-01-23)
This dissertation explores the leadership development needs of new administrators engaged in community-engaged scholarship (CES) within higher education institutions. As these individuals transition from entrepreneurial, autonomous roles to formal administrative positions, they often lack essential competencies in areas such as project coordination, conflict resolution, interdisciplinary collaboration, and managing university-community partnerships. Addressing this competency gap is critical to enhancing their effectiveness as leaders who can bridge institutional and community interests. The study investigates the potential for the Myers-Briggs Type Indicator (MBTI) to enhance perceived influence and leadership effectiveness among emerging CES leaders. A professional development program was implemented, incorporating MBTI assessments, specialized workshops, and individualized coaching aimed at strengthening influence-building strategies. Results indicate that increased self-awareness of personality traits, particularly among extroverted participants, was linked to enhanced perceived influence competencies. However, introverted participants did not consistently report lower influence capacity. The integration of personality assessments, developmental workshops, and coaching significantly improved participants' self-efficacy, critical thinking, and application of influence strategies in practice. Notably, coaching was perceived as a key factor in translating theoretical insights into actionable leadership behaviors, resulting in improved job satisfaction and performance. These findings highlight the importance of personality-based professional development in strengthening leadership capacities for CES roles. By fostering selfawareness and adaptive influence strategies, higher education institutions can better equip new leaders to serve as effective agents of community change and institutional collaborators, thereby enhancing university-community partnerships and advancing social equity initiatives.
High-Resolution Additive Manufacturing Error Prediction and Compensation Through 3D CNN Leveraging Semantic Segmentation
Standfield, Benjamin N. (Virginia Tech, 2025-01-23)
Additive manufacturing (AM) is a relatively new domain of manufacturing processes that began with its first patent in 1986. Since then, AM processes quickly grew in popularity due to their flexibility, superior efficiency in high mix low volume manufacturing settings, and lower material costs compared to more subtractive processes. Despite its increasing popularity, AM processes remain behind subtractive processes in terms of quality and the speed at which new technologies are integrated. Introducing Industry 4.0 technologies is an excellent opportunity to address the need for quality assurance tools for AM processes. First, the question of how the quality of additively manufactured parts can be increased to match parts created through subtractive processes must be asked. In this dissertation, two machine learning (ML) models are developed and utilized in a federated environment to mimic what one would see in a production setting. The proposed models increase AM part quality by (1) predicting the resulting geometry of an AM process and (2) compensating for geometric errors by altering the initial stereolithography (STL) file before slicing. In addition to performing geometric error prediction and compensation, the models were enhanced to be resilient to changes in geometry by training on segments of a 3D object rather than the whole object. Next, process parameters from fused-filament fabrication (FFF) processes were added to the ML models to add resilience process parameter variance. Lastly, the ML models were deployed in a federated environment created from three FFF 3D printers that collaboratively created a dataset for the ML models. Collectively, these works expand the research area created by AM, federated learning, and error compensation. This proposal addresses research gaps in the current literature by first setting the prediction and compensation resolution of voxel-based ML methods to a static 100 µm, thereby reducing the error associated with each voxel. Secondly, process parameters are introduced to the model, further increasing prediction and compensation accuracy compared to predicting on the geometry alone. Lastly, the models are deployed in a federated AM environment with multiple 3D printers acting as clients to reduce each client's time spent generating data while maintaining model performance.
High-Rate Histotripsy Methods for the Rapid Removal of Soft and Fibrous Tissue
Simon, Alexander David (Virginia Tech, 2025-01-22)
Histotripsy is a non-invasive, focused ultrasound ablation modality that uses the precise control of acoustic cavitation to disintegrate tissue. Acoustic cavitation is the transient expansion of pre-existing nuclei to dimensions orders of magnitude beyond their original size due to large increases in the tensile (peak-negative) pressure of the medium. The peak-negative pressure required to generate a cavitation bubble is defined as the cavitation threshold. Once the cavitation threshold has been reached by an applied acoustic pressure, the remaining internal pressure of the bubble results in violent expansion. Histotripsy utilizes focused ultrasound to tightly control the region in which the acoustic pressure exceeds the cavitation threshold forming cavitation bubbles within a precise focal volume. The rapid expansion and collapse of the cavitation bubbles cause large deformations to the surrounding medium at high strain rates capable of mechanically disrupting cellular structures. During histotripsy therapy, numerous cavitation events are generated from a single pulse within the tightly bound focus of the transducer, defined as the bubble cloud. The disintegration of the targeted tissue volume occurs from the rapid expansion and collapse of bubble clouds over the course of many pulses. By maneuvering the transducer array through the use of robotics or by electronically steering the focus of the array, volumetric ablation of tissue can be performed non-invasively. Histotripsy was recently granted de novo clearance from the FDA for the ablation of liver cancer establishing its clinical relevancy in the field of medicine. This work is inspired by the amazing impact of this therapy and fulfilled with the desire to expand the knowledge of the underlying mechanics of histotripsy to allow for the treatment of malignancies that have not been previously investigated. This dissertation proposal outlines the development of high-rate, non-invasive ablation of soft and fibrous tissue using single-cycle histotripsy. My Ph.D. thesis is motivated to develop histotripsy for the ablation of larger volumes than previously considered feasible and tissues that are more resistant to histotripsy-induced damage by utilizing high pulse repetition frequencies (PRF). In this work, (1) I propose histotripsy for the ablation of uterine fibroids, which are large, fibrous tumors that would require unsuitably long treatment times using traditional histotripsy methods. To deliver higher doses and treat larger volumes within a clinically relevant treatment time, (2) I investigate the effects of PRF on reiterative bubble cloud dynamics in single-cycle histotripsy, and (3) demonstrate how bubble clouds form under high PRF conditions. In the last chapters of this work, (4-5) I developed a high PRF pulsing strategy that can efficiently ablate large volumes of soft tissue and uterine fibroids. The findings and implications found in this document aim to increase the robustness of histotripsy as a non-invasive ablation therapy for many new applications by developing faster ablations and furthering the understanding of the underlying mechanics of histotripsy at clinically relevant pulsing rates.
Plasma Assisted Ignition in a Three-dimensional Scramjet Combustor with a Photon-preserving Radiation Model
Shetty, Rajath Krishna (Virginia Tech, 2025-01-22)
This thesis studies how plasmas created by nanosecond repetitive pulsed discharges (NRPD) can affect and improve the combustion characteristics in a high-speed fluid flow that simulates scramjet conditions. This is done by creating a computational code that incorporates the effects of plasmas, high-speed fluid dynamics, combustion chemistry, and photoionization. Many physical effects across multiple temporal and spatial scales appear, and creating a code that efficiently and accurately models these effects was the biggest contribution of this research. A new chemical mechanism has been created that incorporates high energy states for nitrogen and oxygen. This code was applied to examine how NRPD is affected by high-speed fluid flows and different electrode geometries. In quiescent simulations, the multiple pulses couple with each other increasing the overall temperature, which can lead to ignition due to the plasma added. When there is a freestream flow the convection of the previous pulses plasma can prevent coupling between the pulses. Without modification to pulse characteristics (increase in frequency, intensity, or length), combustion may not be achieved. Next, a more applied study of a three-dimensional scramjet is conducted to examine how the plasma affects the flow by the scramjet geometry and conditions. These larger simulations add effects from turbulence by implementing an LES-EDC model. These simulations show how plasmas generated by NRPD can affect the fluid flow inside a scramjet combustor cavity.
Evaluation of Balanced Asphalt Surface Mixtures with Conventional and High RAP Contents Using Laboratory and Accelerated Pavement Testing
Tong, Bilin (Virginia Tech, 2025-01-22)
Balanced Mix Design (BMD) represents an asphalt mixture design methodology that replaces certain traditional volumetric parameters with performance-based testing to address predominant distresses such as rutting and cracking. This approach offers an avenue to properly design and produce engineered asphalt mixtures, including those with high reclaimed asphalt pavement (HRAP) contents, recycling agents (RAs), fibers, and polymer-modified binders. Laboratory performance tests are essential to the BMD process, as they ensure the production of durable, high-performance materials. Beyond laboratory performance evaluation, accelerated pavement testing (APT) plays a crucial role in bridging the gap between laboratory material characterization and field pavement performance. This dissertation aimed to assess the BMD concept for designing durable, long-lasting surface mixtures in Virginia, with particular emphasis on higher RAP content mixtures (HRAP mixtures, i.e., exceeding 30% RAP). The study involved laboratory and APT testing of six surface mixtures featuring a range of RAP contents (both conventional and high), two binder grades (PG 64-22 and PG58-28), one RA, and one warm mix additive. Findings indicated that dense-graded, unmodified surface mixtures with higher RAP contents can be successfully designed using the current Virginia Department of Transportation (VDOT) BMD special provision. These mixtures can be produced in the plant with no significant deviations in aggregate gradation and asphalt binder content from the design specifications. The combined effect of variations in different volumetric properties during production may influence the primary performance of the mixtures, potentially resulting in an imbalance. As a consequence, the produced BMD mixture may fail to meet one or more performance thresholds. Additionally, the results underscored the effectiveness of BMD concept with incorporating RAs and/or a softer binder when designing HRAP surface mixtures. Importantly, the current selected BMD tests characterized the laboratory performance of mixtures, aligning with the performance observed under APT. This research provided a steppingstone towards the examination and validation of the VDOT BMD thresholds, which ensures satisfactory field performance. The study also indicated that while current BMD thresholds provided sufficient margins for satisfactory field cracking performance, rutting resistance may become a concern for overly designed BMD HRAP mixtures. For instance, mixtures with excessively high asphalt binder content may exhibit compromised rutting resistance. Furthermore, to address the challenges uncovered during BMD test analysis—issues like the constraints of traditional pair-wise comparisons, risks of repetitive design processes, and the difficulty in pinpointing critical factors in mixture production—this dissertation proposed innovative solutions to enhance BMD application and streamline the evaluation process. First, a novel Composite Performance Index (CPI), visualized through a 3D plot, captured the "balance" status of various mixtures. Second, a machine learning-enhanced BMD framework was introduced, offering intelligent optimization throughout the design and production phases. The integration of these two tools offers significant potential for simultaneously improving multiple performance indices of asphalt mixtures. Finally, this research demonstrated that the performance of higher RAP content mixtures can exceed that of lower RAP content mixtures through the application of BMD approaches. This dissertation not only advanced the implementation of BMD for surface mixtures but also contributed to the sustainable and performance-driven evolution of asphalt mix design. The insights gained from this study provided practical guidance and strategic recommendations for enhancing asphalt mixture design, production, and performance monitoring.
Towards Cyber-Physical Security for Additively Manufactured Parts via In Situ Monitoring and Electromechanical Impedance
Raeker-Jordan, Nathan Alexander (Virginia Tech, 2025-01-22)
The layer-by-layer nature of additive manufacturing (AM) allows for toolless fabrication of highly complex geometries that cannot be made via traditional processes. AM is unique in its ability to precisely define both the material properties and geometric shape throughout the volume of a part, giving designers unmatched freedom in the creation of new components. However, this freedom of design also creates numerous challenges in the qualification of these parts. As AM processes primitive material in real time to produce each voxel of part volume, manufacturing defects may be dispersed anywhere throughout the part. Many part designs may have complex geometries or material parameters that are challenging for traditional qualification and inspection techniques to inspect for such embedded errors. Even more troubling, this freedom of design also extends to malicious actors, who would then be able to embed intentional targeted defects within the volume of the part. As the AM process is driven almost entirely by computer controlled machines and cyber-domain data, the AM process is uniquely at risk of nearly undetectable cyber-physical attacks, or cyber attacks that can cause physical damage. Additionally, as much of the valuable intellectual property associated with the design and material parameters of parts are stored in digital form, theft of these design files could result in mass replication of lower quality counterfeit parts, putting the supply chain of these AM parts at risk. In order to mitigate these vulnerabilities in the AM process, prior works have focused on in situ monitoring of the manufacturing process in order to ensure the part is constructed as expected. Typically for in situ monitoring, the constructed geometry is compared to the design files associated with the part in question using a monitoring system connected to either the AM machine or the larger network. However, such methods trust the validity of both the design files and monitoring systems used for verification, when either or both may have also been attacked. Therefore, a valid in situ monitoring method needs secure access to a provable set of validation data, while also isolating or air-gapping itself from the network to prevent cyber attacks on the monitoring system itself. Similarly, other works have focused on mitigating the risk of counterfeiting by novel means of part identification tailored for the AM process. Many of these identification methods leverage stochastic or prescribed features, such as surface patterns measured via visible or ultraviolet scanning, or internal porosity features measured via x-ray computed tomography (CT) scanning. However, these surface features are not impacted by alterations or damage to the part in areas away from the specific features being measured, possibly preventing the detection of attacks or damage to other areas of the part in transit. CT scanning can be used to detect damage or alterations to more areas of the part and incorporate this measurement into the identification mechanism, but may be prohibitively expensive while also possibly failing to properly penetrate and measure a sufficiently complex AM part. In this work, efforts to expand the cyber-physical security of the AM process are explored, including (1) a novel method of in situ process validation by means of covertly transmit- ting process quality information to an otherwise air-gapped monitoring system, (2) a novel method of metal AM part identification via a low-cost piezoelectric sensor-actuator able to record a part frequency response that is dependent on the geometry and material properties of the part as a whole, (3) an exploration of part-to-part variation across AM processes, again measured via a piezoelectric sensor-actuator, and (4) a novel means of using the same piezoelectric sensor-actuator for detecting the presence of remaining powder in metal AM parts.
School Leaders Perceptions of Family Engagement Practices with Immigrant Preschool Families in Virginia
Harris, Lesley R. (Virginia Tech, 2025-01-21)
School leaders across the country seek ways to increase family engagement. Children learn and grow when parents, teachers and community collaborate in ways that encourage student development (Epstein and Sheldon, 2014). Current family engagement models do not support families of diverse socio-historical backgrounds and are not differentiated (Coady, 2019). "Every family needs a voice in certain school decisions" (Constantino, 2016). The purpose of this qualitative study, informed by phenomenological case study, was to describe school leaders' perceptions of family engagement practices with immigrant preschool families in central Virginia school divisions. The researcher conducted one-on one interviews with school leaders that support site based preschool programs in public school. The intended outcome of this study was to provide Virginia preschool school leaders with qualitative data to support the engagement of preschool immigrant families in Virginia. Data collected included four preschool leaders. An analysis of the data indicated that all school leaders perceive relationship building, open two way communication, and community partnerships as key components to family engagement with immigrant preschool families in Virginia. It is anticipated that this study's results could help school leaders implement practices that will impact the engagement of immigrant preschool families in Virginia as well as support student academic achievement. The findings will indicate school leaders lived experiences with preschool immigrant families.
Researching on Multisensory Design Communication for Design Development and Collaboration among Designers and Stakeholders
Ge, Mengting (Virginia Tech, 2025-01-21)
Focusing on VR/AR-enhanced design representations, this research explores Multisensory Design Communication (MDC) in the context of design development and collaboration among design professionals and stakeholders. To address the differences between various groups of design participants, three secondary studies were conducted: Study A examined MDC among inexperienced LA designers, Study B focused on MDC among experienced LA designers and other design consultants, and Study C explored MDC between designers and stakeholders. These studies aim to understand how design representation methods, project phases, and participant roles influence design perception, cognition, and the overall communication process in MDC. Based on the research findings, the benefits of VR/AR-enhanced representations in design practice are discussed, and guidelines for selecting appropriate design representation methods for different design participants and project phases are developed accordingly. The findings from the three secondary studies indicate that VR/AR-enhanced representations significantly improve entry-level designers' perception of design information, especially the design details, though their impact on overall design cognition is less notable. These technologies enhance interaction, immersion, engagement, and enjoyment during MDC, particularly benefiting less experienced LA designers. Experienced and multidisciplinary designers tend to favor traditional methods in the early stages but appreciate the use of VR/AR technologies during design development. The use of VR/AR-enhanced representations also improve their perception of design details rather than design cognition. Meanwhile, similar to inexperienced designers, these innovative representations can evoke a more immersive, interactive, and engaging MDC experience for experienced professionals. Stakeholders also benefit from the immersive and interactive features of VR/AR technologies, which stimulate creative thinking and enhance MDC during project presentations, though they are generally satisfied with traditional approaches for presentations and reviews. When comparing the impact of VR/AR-enhanced representations across the three different groups of design participants, inexperienced LA designers may be the group most influenced by new technologies such as VR/AR, and they potentially gain the most benefit from them. Additionally, VR/AR-enhanced representation methods tend to have a greater impact on stakeholders compared to experienced designers. Based on these research findings, guidelines for selecting appropriate representation methods for various design participants are proposed, recommending the use of VR/AR throughout the project for less experienced teams and selectively for experienced and multidisciplinary professionals. By exploring MDC and related representation methods in design practice within an ecologically valid research environment, this study contributes to the LA design process, practice, technologies, and theory. In terms of the design process, it explores how key factors influence MDC in the LA design workflow, offering theoretical and practical suggestions to enhance the LA design process from the perspective of design communication. In practice, it provides insights into improving collaboration, decision-making, and engagement in real-world LA projects. Regarding design technologies, the research examines the role of VR/AR-enhanced representations and offers guidelines for integrating these innovative technologies with traditional approaches. Lastly, this research advances LA theory by expanding knowledge on design communication and representation through the lens of design practice.
A Critical Systems Case Study in Agricultural Technology Development at the Land-Grant University
Smilnak, David Michael (Virginia Tech, 2025-01-21)
Agricultural technology development has historically exacerbated social inequities. As agriculture progresses into the latest technological revolution – Ag 4.0 – it is unclear how institutions such as land-grant universities are considering the social implications of their agricultural technology research. The purpose of this study is to explore how land-grant university initiatives focusing on agricultural technology consider the implications of agricultural technology research. To do so, this research focuses on Virginia Tech's Center for Agricultural Innovation in Agriculture (CAIA). Guided by critical systems heuristics, this case study utilizes five data collection methods to inform a critical case study including: key informant interviews, a document review, a survey, stakeholder interviews, and a focus group. While striving to be a cross-campus interdisciplinary and innovative research incubator the findings revealed in the five years since its establishment, CAIA has been shaped by structural norms at Virginia Tech's College of Agriculture and Life Sciences (CALS), reducing its interdisciplinary and innovation potential. Rather, CAIA supports the existing research of CALS faculty. CAIA has adopted measures of success that ideologically aligned with techno-solutionism and, while present, consideration for the social impact of agricultural technology research is a secondary priority. While this is consistent with ongoing trends in a neoliberalized higher education system, CAIA can take deliberate steps to uplift social impact in agricultural technology research such as being deliberate with who is engaged in the center towards interdisciplinary research, and working with CALS to ensure public-private partnerships serve the direct needs of small and medium-sized growers in Virginia. Empirically, this study contributes to the ongoing discourse around the neoliberalized land-grant university and the use of critical systems heuristics to guide research involving agricultural innovation systems.
On Data-Driven Modeling, Robust Control, and Analysis for Complex Dynamical Systems
Sinha, Sourav Kumar (Virginia Tech, 2025-01-21)
This dissertation advances tools for robust control and analysis of complex nonlinear dynamical systems. Specifically, it leverages standard synthesis and robustness analysis techniques developed for linear systems and provides additional results to design robust controllers for nonlinear systems over the considered operating envelopes. To facilitate the application of these linear techniques, nonlinear systems are represented as uncertain linear models. A significant contribution of this dissertation is the development of data-driven approaches to generate these uncertain linear models, which capture the behavior of nonlinear systems reasonably well over the considered operating envelopes without being overly conservative. We propose two approaches where a nominal linear time-invariant (LTI) approximation of a nonlinear system is first obtained using traditional linearization techniques, and data-driven methods are then applied to model the discrepancies arising from this simplification. In the first approach, the discrepancies are modeled using polynomials, resulting in an improved linear parameter-varying (LPV) approximation that can be expressed as a linear fractional transformation (LFT) on uncertainties. The second approach utilizes coprime factorization and a data-driven lifting technique to approximate the nonlinear discrepancy model with an LTI state-space system in a higher-dimensional state space. Additionally, a purely data-driven modeling approach is proposed for nonlinear systems with uncertain initial conditions. In this approach, a deep learning framework is developed to approximate nonlinear dynamical systems with LPV state-space models in higher-dimensional spaces while simultaneously characterizing the uncertain initial states within the lifted state space. Another contribution is the development of a systematic method for identifying critical attack points in cyber-physical systems using integral quadratic constraints (IQCs). IQC analysis is also used in developing a framework focused on the design and analysis of robust path-following controllers for an autonomous underwater vehicle (AUV). In this framework, the AUV is modeled as an LFT on uncertainties and is affected by exogenous inputs such as measurement noise and ocean currents. A tuning routine is developed for robust control design, using the robust performance level derived from IQC analysis to guide the tuning process. This framework is applied to design $ H_\infty $, $ H_2 $, and LPV controllers for the AUV, with the results validated through extensive nonlinear simulations and underwater experiments. Finally, this dissertation presents novel controller synthesis and IQC analysis techniques for LPV systems with uncertain initial conditions. These methods, combined with the lifting-based LPV modeling approach, enable the design of static, nonstationary LPV controllers for nonlinear systems in a higher-dimensional space. When interpreted in the original state space, these controllers become nonlinear with explicit dependence on both the scheduling parameters and time. Through examples, it is demonstrated that these controllers outperform those designed using nominal linearized models.
Rheological Considerations for Dual-Extrusion Melt Processing of Dissimilar Polymers in Composite Structures
Mansfield, Craig Daniel (Virginia Tech, 2025-01-21)
Gel spinning is the current industrial method of choice for combining ultra-high molecular weight (UHMW) polymer resins with a substrate support polymer resin to produce composite filaments with a porous structure and high surface area per unit volume (specific area). Gel spinning is typically used to overcome a wide gap between the maximum processing temperature of the UHMW resin and the minimum processing temperature of the substrate resin and to avoid the high melt viscosity of the UHMW resin, but requires the costly recovery of toxic solvents. The UHMW resin is used because it forms a stable gel phase in the presence of water; a lower molecular weight resin (LMW) simply dissolves. A dual-extrusion process, which minimizes residence time with mismatched temperatures, was used to render a melt-based scheme practical. Dual-extrusion involves the separate plastication of materials prior to combination in a low residence time mixing head to form a desired composite. In this work, the UHMW and LMW resins were both poly(ethylene oxide) (PEO), and the substrate was polyarylsulfone (PAS). The initial focus of this dissertation is to investigate the rheology of PEO when subjected to temperatures beyond which it is known to degrade. Literature indicated PEO undergoes non-oxidative thermal degradation above 200°C and PAS is processed up to 350°C. Dynamic oscillatory shear rheometry was used to study 0, 25, 40, 50, 60, and 75wt% UHMW PEO in LMW PEO to take advantage of the sensitivity of viscosity to changes in molecular weight and material configuration, indicating degradation. Samples were exposed to 220, 230, 240, 250, 275, and 300°C temperatures for 5 minutes to explore conditions that could result in sample degradation. The viscosity decreased less with increasing UHMW PEO content for samples exposed to the same temperature and the viscosity decreased more with increasing exposure temperature for samples with the same UHMW PEO content. Parameters were regressed from observed data to predict the change in molecular weight via empiricisms relating the viscosity to molecular weight, shear rate, temperature, and time. This regression yielded a single master curve describing the behavior of PEO across all conditions, stable and degrading. The purpose of the second part of this work is to investigate the utility of the correlation developed with PEO in the first part with respect to characterizing an additional polymer resin, PAS, predicting the processing conditions for combining PEO and PAS in the dual-extrusion process, predicting the degradation of PEO in the dual-extrusion process, and characterizing the structure of the resulting composites with comparison to expectations from literature. The overall goal of eliminating the need for a toxic solvent in phase inversion gel spinning by changing to a melt process with dual-extrusion leaves theory and enters practice in this part. The correlation developed for PEO in the first part was used to regress parameters for PAS, extending the use case to an additional class of polymer resin. The regressions for both PEO and PAS were used to select processing conditions for operating the dual-extrusion process to yield composite filaments. Samples were produced with a range of compositions and prepared for microscopy as is, after etching with water, or after rinsing with water to remove extractables. Extractable content was characterized by the change in dry mass before and after rinsing samples using optical and scanning electron microscopy techniques. The observed excess extractables content of rinsed samples agreed with prediction from the regression for PEO and microscopy indicated qualitatively similar structure to similar gel spun materials in literature.
Impact of growth stage, supplemental red LED, and salinity stress on the quality and aroma attributes of hydroponic fennel (Foeniculum vulgare Mill.)
Liu, Jingsi (Virginia Tech, 2025-01-21)
Fennel (Foeniculum vulgare Mill.) is a widely used culinary herb valued for its distinct flavor, rich essential oil content, and health-promoting secondary metabolites. Due to its diverse culinary, medicinal, and industrial applications, optimizing fennel aroma, the key quality characteristic of fennel and its products, is of significant interest. The production of aroma compounds, which arise from secondary metabolism, is influenced by factors such as growth stage and environmental conditions. Understanding how secondary metabolite biosynthesis are affected by these factors is crucial for optimizing the quality and flavor of fennel. In particular, supplemental red light and salinity are known to modulate the production of aroma compounds in herbs, but the molecular mechanisms underlying these effects remain largely unexplored. Controlled environment agriculture (CEA) provides an ideal platform for studying plant responses to environmental stimuli. Accordingly, this dissertation aims to investigate the influences of growth stage, supplemental red LED light, and salinity stress on the quality and aroma compounds of fennel cultivated by CEA. Fennel was cultivated with nutrient film technique (NFT) hydroponic systems under controlled conditions. Solid phase microextraction (SPME) - gas chromatography - mass spectrometry olfactometry (GC-MS-O) was utilized for aroma characterization. RNA sequencing was used to generate transcriptome profiles of fennel under different environmental treatments. A total of 32 aroma-active compounds were identified in fennel microgreens, compared to 28 in mature fennel. Compared to mature plants, fennel microgreens contained a significantly higher level of monoterpenes, showing an 81.4-98.1% increase when compared to mature fennel. Supplemental red LED significantly increased both fennel yield and aroma compounds accumulation, particularly phenylpropanoids such as (E)-anethole ("sweet", "anise"), estragole ("anise", "herbal"), and p-anisaldehyde ("floral", "sweet"). Transcriptome analysis showed upregulation of key genes involved in phenylpropanoid biosynthesis, including eugenol synthase and isoeugenol synthase, which likely contributed to the increased phenylpropanoid concentrations under red LED light. Salinity stress, while significantly reducing plant growth, did not notably affect the overall content of aroma-active compounds. However, salinity triggered defense mechanisms in fennel, particularly through the activation of plant hormone signal transduction and mitogen-activated protein kinase (MAPK) signaling pathways. The findings of this study enhanced understanding of aroma formation of fennel in response to environmental factors at molecular and transcriptomic levels. These results also offer opportunities for growers to optimize fennel flavor through precise control of environmental conditions.
``The Veteran Problem''? The American WWII Veteran
McDonald, Todd Allen (Virginia Tech, 2025-01-21)
The purpose of this paper is to analyze a specific dimension of the veteran policy discourse in academic and news articles published during the Second World War. I conduct a textual analysis and apply frame theory to structure my study of 45 academic articles taken from JSTOR and 314 news articles taken from ProQuest. My findings reveal three distinct frames that represent veterans themselves as a social problem and/or threat. One frame suggests that a mass influx of WWII veterans into the US economy would cause an economic catastrophe similar to the Great Depression in the 1930s. Another frame indicates that veterans have been indoctrinated into military life and that they had values and beliefs that were incompatible with American society and democracy. The third frame claims that policies which provide public benefits to veterans exclusively could create a privileged political class that could undermine democracy and meritocracy. My research adds value to current studies of American veterans by emphasizing the extreme fear that has character- ized elite political discourse on WWII veteran reintegration and how that discourse related to veteran policy proposals during that time.
Degradable Polymers for the Controlled Delivery of Bioactive Small Molecules
Swilley, Sarah Nicole (Virginia Tech, 2025-01-17)
Gasotransmitters are endogenous small molecule gases that are freely permeable to membranes and possess biological signaling functions. The three recognized gasotransmitters are carbon monoxide (CO), nitric oxide (NO), and hydrogen sulfide (H2S). H2S is featured in this work, as well as persulfides (RSSH), which also have similar functions to H2S (e.g., angiogenesis) and are the presumed signaling products of H2S but are less studied. Other compounds that are considered potential gasotransmitters include methane, sulfur dioxide, hydrogen cyanide, and nitroxyl (HNO). This dissertation covers compounds that release HNO, which possesses similar functions to NO (cardioprotection and vasodilation) but has been studied much less. While HNO, H2S, and RSSH have vital biological functions, they also have short half-lives in vivo (seconds to minutes), thus necessitating the development of prodrugs, also called donor compounds, that can release these reactive species over a biologically relevant time scale. While donor compounds extend the release rate of such small molecule gases, they do not have the ability to release drugs as slowly and continuously as endogenous gasotransmitter-generating enzymes do. As such, polymeric delivery systems have been developed to extend the release of drugs, and in the case of gasotransmitters this more closely mimics in vivo production of HNO/H2S/RSSH. Polymeric systems have been employed to modulate gasotransmitter delivery to control drug release rate, location, and longevity precisely. H2S has been employed in numerous polymeric systems, as discussed in Chapter 2, but there is a significant gap in the literature focusing on polymeric donors for HNO/RSSH. Researchers need to develop novel materials that demonstrate an extended release of these small molecules to better understand the effects of long-term exogenous delivery of HNO/RSSH/H2S which exist fleetingly in vivo. Therefore, materials that release a continuous, well characterized amount of gasotransmitters are vital for biologists to understand long-term effects of such short-lived gasses. The aim of this dissertation, in part, is to hopefully inspire the development of novel HNO/RSSH/H2S releasing systems. In Chapter 3 we discuss an HNO-donating polymer. Here we demonstrate a simple system derived from polyethylene glycol (PEG) and sulfonated polystyrene (PSS). We synthesized a polymeric version of Piloty's acid — a well-known HNO donor — by converting the PSS into a Piloty's acid motif in a two-step process. We found that by simply changing the block ratio of PEG and PSS, we were able to vary the release rate of HNO over an order of magnitude. In Chapter 4 we focus on the development of depolymerizable H2S donors encapsulated within polymer micelles. We report the synthesis of two classes of monomers, one derived from norbornene and one from acrylates. We anticipate that the results from this study will further direct and impact the study of exogenous H2S-releasing materials. In Chapter 5 we discuss electrospun polymer films made of poly(ethylene oxide terephthalate)/poly(butylene terephthalate) (PEOT/PBT) with embedded RSSH donors. We found that the RSSH donors can rescue cells from H2O2 exposure and do not interfere with angiogenesis in HMVECs. We report the fabrication, characterization, and drug release studies of the polymer fiber mats. Lastly, the appendix included at the end of this dissertation briefly discusses the synthesis of a novel depolymerizable poly(thiourethane) derived from a pyrrole monomer.
Exploring Pre-Licensure Nurisng Students' Perceptions of Faculty Feedback on Clinical Skills Assessments in Community College Programs
Lucas, Carolyn Kay (Virginia Tech, 2025-01-17)
In academia, research on feedback has been helpful and has enhanced awareness of students' and professors' perceptions, thereby promoting effective strategies for giving feedback to students. According to Boud (2015) and others, feedback is a significant component of the teaching and learning process. Quality teaching and evaluative processes give learners an advantage in becoming exceptional nurses. The current study aimed to research the perceptions of pre-licensure first- and second-year nursing students and their professors regarding clinical skills performance assessment feedback. A quantitative, cross-sectional, non-experimental design was utilized in this study. Convenience sampling was conducted with 163 nursing students either enrolled in the program's first year or second year of nursing education and those who completed the online survey entitled Students' Perceptions of Professor Feedback survey. In addition, nine professors who taught and assessed clinical skills in the first and second year of the nursing curriculum completed the Professors' Perceptions of Feedback survey. Data was analyzed using descriptive statistics and multiple linear regression. Based on the findings, it was reasonable to conclude that students generally felt that professor feedback was an effective teaching and evaluative strategy in nursing education. Specific content areas, such as the quality of the information given during feedback and the emotional impact of feedback, had a meaningful, significant effect on students' confidence levels.
Enhancing the User Experience and Decision-Making of Green Building Certification Resources through Usability Testing Methods
Jefferson, Dwayne Ernest (Virginia Tech, 2025-01-16)

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