Doctoral Dissertations

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  • Reduced-order Adaptive Output Predictor for a Class of Uncertain Dynamical Systems: Application to EEG-Based Control of Working Memory
    Ansari, Roghaiyeh (Virginia Tech, 2024-04-18)
    This dissertation aims to develop a formal foundation to design an adaptive output feedback predictor for a class of unknown systems where parameters and order are unknown or high-dimensional. We present a reduced-order adaptive output-predictor scheme based on modal reduction and Lyapunov's method. Moreover, the credibility of the proposed reduced-order adaptive output-predictor scheme is validated by mathematical proof, and numerical and experimental studies, such as single pendulum, double pendulum, six-link pendulum, rope as a high-dimensional rope, and EEG data. Then the dissertation goal is to experimentally validate the proposed reduced-order model parameterization technique for tracking uncertain linear time-invariant (LTI) single-input, single-output (SISO) systems. The proposed theory focuses on parameterizing a high-dimensional, uncertain model and introduces a reduced-order adaptive output predictor capable of forecasting the system's output. This predictor utilizes auto-regressive filtered vectors, incorporating the input and output history. The adaptive output predictor is a simplified and known model, making it suitable for controlling high-dimensional, uncertain SISO systems without access to full-state measurements. Specifically, this work establishes the foundation for parameterizing uncertain models, creating a virtual structure that emulates the actual system, and offering a more manageable model for control when the objective is solely to regulate the system's output. The primary focus of this research is to assess the effectiveness and output-tracking capabilities of the proposed approach. These capabilities are extensively examined across diverse platforms and hardware configurations, relying solely on input and output data from the models without incorporating any additional information on the system dynamics. In the first experiment, the predictor's ability to track the angle of a single pendulum, including additional dynamics, is evaluated using only input-output data. The second experiment targets tracking the endpoint of a rope connected to a single pendulum, where the rope emulates a high-dimensional model. A vision system is designed and employed to acquire the rope endpoint position data. Before the rope experiment, a set of experiments is conducted on single pendulum hardware to ensure the accuracy of the vision system's data collection. Comparative analysis between data from object tracking via vision and data acquired through an encoder demonstrates negligible error. Finally, the input and the endpoint output data from the rope experiment are fed into the predictor to assess its capability to track the rope endpoint position without utilizing specific knowledge of the experimental hardware. Achieving negligible error in tracking implies that the predictor provides a simple and accurate representation of the rope dynamics. Consequently, designing a controller for this known model is equivalent to designing a controller for the actual rope system dynamics. The predictor, by closely emulating the behavior of the rope, becomes a reliable surrogate model for control design, simplifying the task of controller design for the complex and uncertain high-dimensional system. Finally, this study introduces a novel approach to enhance controller design for complex brain dynamics by employing a reduced-order adaptive output predictor proposed in [1], fine-tuned with chirp binaural beats. The proposed technique is promising for developing closed-loop controllers in non-invasive brain stimulation therapies, such as binaural beats stimulation, to improve working memory. The study focuses on parameterizing uncertain models and creates a predictor that utilizes auto-regressive filtered vectors to forecast mean phase lock values generated by binaural beats stimulation. The simplified and known model of the predictor proves effective in tracking brain responses, as demonstrated in experiments evaluating its ability to track mean phase locking values. The results indicate negligible tracking error, suggesting the predictor's reliability in representing brain dynamics and simplifying the task of controller design for the complex and uncertain high-dimensional system.
  • An Investigation into the Psychological Capital of Second-Career Teachers and Factors Influencing Their Scores
    Flanagan, Amanda Grace (Virginia Tech, 2024-04-12)
    The purpose of this qualitative study was to examine the Psychological Capital (PsyCap) of second-career teachers (SCTs) and their perceptions of what affects their PsyCap in the workplace by surveying and interviewing second-career teachers in public school districts in central eastern and northern Virginia. The research questions were: What is the PsyCap of a second-career teacher? What are the factors that second-career teachers perceive to contribute to their PsyCap? Participants were located in rural and suburban school districts in central eastern and northern Virginia. Data collection consisted of demographic surveys, the Psychological Capital Questionnaire survey (PCQ-24), and semi-structured interviews. Eighteen second-career teachers were purposefully selected from 34 who completed the demographic survey data and PsyCap-24 to participate in semi-structured interviews using the interview questions protocol. Common themes from the interviews were determined using deductive and inductive coding. Major findings were that second-career teachers exhibited a high average workplace positive PsyCapof 4.8; mentorship and strong peer support significantly influence second-career teachers' positive PsyCap; and a teacher's relationships with colleagues and their team's impact second-career teachers' positive PsyCap. Additional findings also showed that positive relationships with administration and prior-life experiences in other fields contributed to an increase in positive PsyCap. Whereas extra duties assigned to second-career teachers negatively impact their overall PsyCap. These results underscored the significance of nurturing positive PsyCap among second-career teachers, adding to the broader research on educators' PsyCap and its impact on teacher retention and job satisfaction in education.
  • Studies on Molten Salt Fuels: Properties, Purification, and Materials Degradation
    Park, Jaewoo (Virginia Tech, 2024-04-12)
    The molten salt reactor (MSR) is one of the advanced nuclear reactors expected to be alternatives to the conventional water-cooled nuclear reactor systems. Despite many advantages of MSRs, properties of molten salts have not been sufficiently measured in previous studies. In addition, the corrosion of structural alloys by molten salt is the biggest challenge for the operation of MSRs. This study focuses on measurements of thermophysical and thermodynamic properties of fluoride salt fuels, salt purification, and the degradation of structural materials in static and flowing molten-salt fuels. For the measurements of properties, phase transition, specific heat capacity, vapor pressure, contact angle on nuclear-grade graphite, and density were measured. The methodologies for the property measurements used in this study were validated by measuring the properties of metals or salts that have been well studied. For the flow-induced corrosion tests, the salt flow with different velocities was simulated by rotating the stainless steel 316H (SS316H) specimens in molten NaF-KF-UF4 (FUNaK) contained in glassy carbon crucibles at 1073 K. Salt samples were intermittently collected to monitor concentration changes of corrosion products in the salt, and surfaces and cross-sections of post-test SS316H specimens were analyzed to study their corrosion behaviors. Different batches of FUNaK were synthesized using different methods of purification, such as thermal purification, U-metal purification, and hydrofluorination with electrochemical purification (chemical purification) to study impacts of salt purification on the corrosion of SS316H. The corrosion test of SS316H by thermally purified FUNaK showed that the Fe concentration increased at the beginning and then decreased while the Cr concentration continued increasing while the rate decreased. In addition, (Cr, Fe)7C3 layers, Cr-metal particles, and dendritic structures concentrated with Cr and Fe were observed on the glassy carbon crucible after the 2 m/s test. The U-metal purification and hydrofluorination with electrochemical purification reduced concentrations of oxygen and hydrogen in FUNaK and mitigated the corrosion of SS316H significantly. The infiltration of the fluoride fuel salts into graphite and the fluorination of graphite by the salts at different pressures and temperatures were also studied. The salt infiltration into graphite at pressures above its threshold pressure was observed, and the formation of carbon fluorides on the surface of post-test graphite specimens was identified.
  • Why Special Educators Stay: A Phenomenological Examination of Factors Impacting Special Educator Retention in Northern Virginia's Urban Public Schools
    Gavin, Matthew (Virginia Tech, 2024-04-12)
    Cultural stigma and a looming teacher deficit, exacerbated by the COVID-19 pandemic, have created an increased need for special educators. Considering these issues, this research used traditional phenomenological qualitative methodologies to understand why public-school special education teachers of students with low incidence disabilities (SETs-LIDs) remained in the profession. The purpose was to better understand the lived experiences of SETs-LIDs, and it was designed as a phenomenological qualitative study. The primary research question was "What factors impact SETs-LIDs who continue to teach in special education during difficult times?" Secondary questions were (a) "What are the lived experiences of SETs-LIDs that influence their retention?" and (b) "How do SETs-LIDs cope with the challenges of their work?" Data were obtained through a demographic survey and independent interviews, which were designed to better understand why public-school SET-LIDs remain in the profession. Participants were selected based on responses to the demographic survey, and inclusion criteria included SETs-LIDs with diverse employment backgrounds. Ninety-six special educators responded to the demographic survey and 15 SET-LIDs were interviewed. Textual descriptions generated from the research were work satisfaction from relationships, intrinsic or altruistic motivation, positive administrative experiences, and external factors. Structural descriptions of the research were frustration, a desire for understanding, inequity and exclusion, and uncertainty. The "what" and "how" of individuals impacted by the difficulties of SET-LID attrition were interpreted. Participants described meaningful relationships with students and administrators as being fundamental to their retention. This research also found that SET-LIDs desired resources, understanding, appropriate professional development, and expert guidance. Implications for professional practices and future research were suggested.
  • An Examination of the Challenges Experienced by Novice Principals Leading Rural Schools in Virginia
    Wheeler III, Frank Thomas (Virginia Tech, 2024-04-11)
    Novice principals leading rural schools experience unique challenges that define their leadership practices. The purpose of this qualitative study was to examine how novice principals interpret and understand the challenges they experience as developing leaders within a rural school setting in Virginia. The research question for the study was, what challenges do novice principals situated in a rural setting in Virginia experience as leaders of their schools? This study adds to the existing body of research on the challenges novice principals face as leaders of schools situated within a rural community. For this study, six novice principals working in Rural-Remote (Code 43) schools (as defined by the National Center for Education Statistics) in Virginia participated in a 45-minute, one-on-one interview. The findings revealed that the novice rural principals experienced unique challenges with hiring staff, managing limited budgets, wearing multiple hats, distributed leadership, meeting their community's expectations for accessibility and visibility, readily available collaboration opportunities with professionals in similar roles, and intense feelings of ultimate responsibility. Participants hired with previous administrative experience within the district reported smooth transitions to the principalship. Although the participants reported limited activities from their districts to assist with understanding the rural setting, they expressed satisfaction with the overall support provided by their school district. The implications could help school districts, policymakers, and principal preparation programs effectively manage rural principal successions by establishing mentorship programs; providing field experience to aspiring principals; creating robust principal induction programs; and finding creative solutions to attract, hire, and retain rural school staff.
  • Investigating Relationships Among School Climate, Academic Growth, and Benchmark Achievement Within Elementary Schools in Three Divisions in Virginia: A Quantitative Study
    Thompson, Summerlyn Lotz (Virginia Tech, 2024-04-11)
    Educators have a responsibility to foster a positive school climate while also ensuring that all students meet established educational benchmarks and make adequate growth. The relationship between school climate and student achievement is well-documented, but there is a gap in the literature examining the relationships among school climate, academic growth, and benchmark achievement. Accordingly, the purpose of this study was to investigate relationships among school climate, academic growth, and benchmark achievement at the elementary school level in Virginia. A nonexperimental, correlational design was used to address this research question: What are the relationships, if any, among school climate, academic growth, and benchmark achievement among fourth grade students in three school divisions in Virginia for the 2022-2023 school year? Existing data sets from 73 schools within 3 school divisions in Virginia were used: (a) the 2023 Virginia Survey of School Climate and Working Conditions, (b) fourth graders' Fall 2022 to Spring 2023 growth in reading and mathematics on the Northwest Evaluation Association Measures of Academic Progress assessment, and (c) fourth graders' mean performance on the 2023 Virginia Standards of Learning assessments in reading and mathematics. A correlational analysis was conducted to examine the relationships among these variables. Results were analyzed, and there were 12 findings. The most significant finding was a stronger positive relationship between school climate and benchmark achievement in reading and mathematics than between school climate and academic growth in either subject. This study contributes to the body of research on school climate and benchmark achievement by addressing relationships among school climate, academic growth, and benchmark achievement.
  • Teacher Participation in Decision Making and its Relationship to Job Satisfaction in Middle Schools in Riyadh, Saudi Arabia
    Alwadi, Abdulmohsen (Virginia Tech, 2024-04-09)
    Background: Teacher job satisfaction is considered an important topic in the education field. Many variables impact teacher job satisfaction. This study examined teacher participation in decision-making and its relation to teacher job satisfaction in ten public middle schools in the north of Riyadh, Saudi Arabia. It also sought to determine the impacts of gender and teaching experience on job satisfaction and participation in decision-making. Methods: A quantitative method with descriptive and inferential statistics was used, as well as a correlational analysis of the data. Pearson's correlation analysis was used to determine the relationship between teachers' participation in decision making and their job satisfaction. Ten public middle schools (located in north of Riyadh) were randomly chosen for this study. Of these, five were chosen for the male sample, totaling 62 teachers. Another five middle schools were chosen for the female sample, totaling 72 teachers. Accordingly, a total of 134 teachers of both genders participated in the study. Instrument: Two valid and reliable surveys were developed by (Aldeeka and Khasawneh, 2021). The participants were given two surveys to complete. The first survey for job satisfaction included four domains. The second survey for participation in decision-making also included four domains. The surveys had a total of 54 questions. Statistical Package for Social Sciences (SPSS) was used to analyze the data. Job satisfaction was shown as a dependent variable, whereas decision-making participation was the independent variable. Gender and teaching experiences were as controlling variables. Findings: The major finding of the study were as follows: 1) There was a positive correlation between job satisfaction and participation in decision-making (r (134) = .468, p <.001); 2) There was no difference in job satisfaction between males and females; 3) There was no difference in participation in decision-making between males and females; 4) There was a difference for teaching experience in relation to job satisfaction; 5) There was no difference between participation in decision-making in relation to teaching experiences; and 6) The level of job satisfaction and participation in decision making for the total sample considered within average level. The findings aim to support educational policymakers in the education field. Additionally, various recommendations were put forward to boost teachers' job satisfaction.
  • Graph-based Time-series Forecasting in Deep Learning
    Chen, Hongjie (Virginia Tech, 2024-04-02)
    Time-series forecasting has long been studied and remains an important research task. In scenarios where multiple time series need to be forecast, approaches that exploit the mutual impact between time series results in more accurate forecasts. This has been demonstrated in various applications, including demand forecasting and traffic forecasting, among others. Hence, this dissertation focuses on graph-based models, which leverage the internode relations to forecast more efficiently and effectively by associating time series with nodes. This dissertation begins by introducing the notion of graph time-series models in a comprehensive survey of related models. The main contributions of this survey are: (1) A novel categorization is proposed to thoroughly analyze over 20 representative graph time-series models from various perspectives, including temporal components, propagation procedures, and graph construction methods, among others. (2) Similarities and differences among models are discussed to provide a fundamental understanding of decisive factors in graph time-series models. Model challenges and future directions are also discussed. Following the survey, this dissertation develops graph time-series models that utilize complex time-series interactions to yield context-aware, real-time, and probabilistic forecasting. The first method, Context Integrated Graph Neural Network (CIGNN), targets resource forecasting with contextual data. Previous solutions either neglect contextual data or only leverage static features, which fail to exploit contextual information. Its main contributions include: (1) Integrating multiple contextual graphs; and (2) Introducing and incorporating temporal, spatial, relational, and contextual dependencies; The second method, Evolving Super Graph Neural Network (ESGNN), targets large-scale time-series datasets through training on super graphs. Most graph time-series models let each node associate with a time series, potentially resulting in a high time cost. Its main contributions include: (1) Generating multiple super graphs to reflect node dynamics at different periods; and (2) Proposing an efficient super graph construction method based on K-Means and LSH; The third method, Probabilistic Hypergraph Recurrent Neural Network (PHRNN), targets datasets under the assumption that nodes interact in a simultaneous broadcasting manner. Previous hypergraph approaches leverage a static weight hypergraph, which fails to capture the interaction dynamics among nodes. Its main contributions include: (1) Learning a probabilistic hypergraph structure from the time series; and (2) Proposing the use of a KNN hypergraph for hypergraph initialization and regularization. The last method, Graph Deep Factors (GraphDF), aims at efficient and effective probabilistic forecasting. Previous probabilistic approaches neglect the interrelations between time series. Its main contributions include: (1) Proposing a framework that consists of a relational global component and a relational local component; (2) Conducting analysis in terms of accuracy, efficiency, scalability, and simulation with opportunistic scheduling. (3) Designing an algorithm for incremental online learning.
  • Rational Design of Poly(phenylene sulfide) Aerogels Through Precision Processing
    Godshall, Garrett Francis (Virginia Tech, 2024-04-02)
    Poly(phenylene sulfide) (PPS), an engineering thermoplastic with excellent mechanical, thermal, and chemical properties, was gelled for the first time using 1,3-diphenylacetone (DPA) as the gelation solvent in a thermally induced phase separation (TIPS) process. PPS was dissolved in DPA at high temperatures to form a homogeneous solution. The solution was cooled, initiating phase separation and eventually forming a solidified PPS network around DPA-rich domains. Evacuation of DPA from the gel network creates monolithic PPS aerogels, one of few physically crosslinked polymer aerogel systems comprised of a high-performance thermoplastic. In this work, specific properties of PPS aerogels were controlled through the manipulation of various processing parameters, such as polymer concentration, post-process annealing conditions, mode of manufacturing (casting versus additive manufacturing), dissolution temperature, and drying method. The ultimate goal was to elucidate key process-morphology-property relationships in PPS aerogels, to ultimately improve aerogel performance and applicability. The phase diagram of PPS/DPA was first elucidated to determine the phase separation mechanism of the system, which guides all future processing decisions. The phase diagram indicated that the system undergoes solid-liquid phase separation, typical for solutions with relatively favorable polymer-solvent interactions. This assignment was validated by the calculation of the Flory-Huggins interaction parameter through two independent methods - Hansen solubility parameters and fitting melting point depression data. The influence of polymer composition on PPS aerogel properties was then characterized. As polymer concentration increased, aerogel density and mechanical properties increases, and porosity decreased. The particular morphology of PPS aerogels from DPA was that of a fibrillar network, where these axialitic (pre-spherulitic) fibrils are comprised of stacks of PPS crystalline lamellae, as suggested by x-ray scattering and electron microscopy. These interconnected microstructures responded more favorably to compressive load than similar globular PEEK aerogels, highlighting the importance of aerogel microstructure on its mechanical response. Upon solvent extraction, PPS aerogels were annealed in air environments to improve their mechanical behavior. Annealing did not dramatically shrink the aerogels, nor did it appear to affect the micron-scale morphology of PPS aerogels as observed by electron microscopy. The resistance to densification of PPS aerogels was mainly a product of their interconnected fibrillar morphologies, aided by subtle microstructural changes that occurred upon annealing. Exposure to a high temperature oxidative environment (160 – 240 oC) increased the degree of crystallinity of the aerogels, and also promoted chemical crosslinking within the amorphous PPS regions, both of which may have helped to prevent severe densification. With enhanced physical and chemical crosslinking, annealed PPS aerogels displayed improved compressive properties over unannealed analogues. Additionally, the thermal conductivity of both annealed and unannealed aerogel specimens was below that of air (~ 0.026 W/mK) and did not display a dependence on polymer composition nor on annealing condition. Generally, these experiments demonstrate that annealing PPS aerogels improved their mechanical performance without negatively affecting their inherent fibrillar morphology, low density, or low thermal conductivity. To fabricate aerogels with geometric flexibility and hierarchical porosity, PPS/DPA solutions were printed through material extrusion (MEX) and TIPS using a custom-built heated extruder. In this process, solid solvated gels were first re-dissolved in a heated extruder and solutions were deposited in a layer-wise fashion onto a room-temperature substrate. The large temperature gradient between nozzle and substrate rapidly initiated phase separation, solidified the deposited layers and formed a printed part. Subsequent solvent exchange and drying created printed PPS aerogels. The morphology of printed aerogels was compositionally-dependent, where the high extrusion temperature required to dissolve highly-concentrated inks (50 wt % PPS) also destroyed self-nuclei in solution, yielding printed aerogels with spherulitic microstructures. In contrast, aerogels printed from 30 wt % solutions were deposited at lower temperatures and demonstrated fibrillar microstructures, similar to those observed in 30 wt % cast aerogel analogues. Despite these microstructural differences, all printed aerogels demonstrated densities, porosities, and crystallinities similar to their cast aerogel counterparts. However, printed aerogel mechanical properties were microstructurally-dependent, and the spherulitic 50 wt % aerogels were much more brittle compared to the fibrillar cast 50 wt % analogues. This work introduces a widely-applicable framework for printing polymer aerogels using MEX and TIPS. Intrigued by the compositional morphological dependence of the printed PPS aerogels, the dissolution temperature (Tdis), and thus the self-nuclei content, of cast PPS/DPA solutions was systematically varied to understand its influence on aerogel morphology and properties. As Tdis increased, the length and diameter of axialites increased while aerogel density and porosity were relatively unaffected. Thus, the isolated influence of axialite dimensions (analogous to pore size and pore concentration) on aerogel properties could be studied independent of density. At low relative densities (below 0.3, aerogels of 10 – 30 wt %), compressive modulus and offset yield strength tended to decrease with Tdis, due to an increase in axialite length (akin to pore size) and number of axialites (akin to number of pores). At higher relative densities (above 0.3, 40 and 50 wt %), axialitic aerogels were so dense that changes in pore dimensions did not result in systematic changes in mechanical response. All spherulitic aerogels fabricated at the highest Tdis¬ demonstrated reduced mechanical properties due to poor interspherulitic connectivity. The thermal conductivity of all aerogels increased with polymer composition but demonstrated no clear trend with Tdis. A model for thermal conductivity was used to deconvolute calculated conductivity into solid, gaseous, and radiative components to help rationalize the measured conductivity data. This work demonstrates the importance of nucleation density control in TIPS aerogel fabrication, especially at low polymer concentrations. The specific method used to dry an aerogel generally has a great influence on its microstructure and density. Vacuum or ambient drying is the most industrially-attractive technique due to low cost and low energy usage; however, it is typically the most destructive process due to high capillary forces acting on the delicate aerogel microstructure. Three drying methods, vacuum drying, freeze drying, and supercritical CO2 drying, were used to evacuate PPS gels fabricated at three PPS concentrations (10, 15, and 20 wt %). Almost all aerogel specimens displayed excellent resilience against shrinkage as a function of the drying method, besides the 10 wt % vacuum dried sample which shrunk almost 40%. While the micron-scale aerogel morphology captured by electron microscopy appeared to be unaffected by the drying method, other properties such as aerogel surface area, mesoporous volume, and mechanical properties were effectively functions of the degree of aerogel shrinkage. Aerogel thermal conductivity was low for all samples, and in particular, vacuum dried aerogels demonstrated slightly lower conductivities than other ambiently-dried aerogel systems such as silica and carbon. In general, vacuum drying appears to be industrially viable for PPS aerogels at concentrations above 10 wt %.
  • Enhancing Safety in Critical Monitoring Systems: Investigating the Roles of Human Error, Fatigue, and Organizational Learning in Socio-Technical Environments
    Liu, Ning-Yuan (Virginia Tech, 2024-04-09)
    Modern complex safety-critical socio-technical systems (STSs) operate in an environment that requires high levels of human-machine interaction. Given the potential for catastrophic events , understanding human errors is a critical research area spanning disciplines such as management science, cognitive engineering, resilience engineering, and systems theory. However, a research gap remains when researching how errors impact system performance from a systemic perspective. This dissertation employs a systematic methodology and develops models that explore the relationship between errors and system performance, considering both macro-organizational and micro-worker perspectives. In Essay 1, the focus is on how firms respond to serious errors (catastrophic events), by exploring the oscillation behavior associated with the organizational learning and forgetting theory. The proposed simulation model contributes to the organizational science literature with a comprehensive approach that assesses the firm's response time to "serious" errors when the firm has a focus on safety with established safety thresholds. All of these considerations have subsequent impact on future performance. Essay 2 explores the relationship between safety-critical system's workers' workload, human error, and automation reliance for the Belgian railway traffic control center. Key findings include a positive relationship between traffic controller performance and workload, and an inverted U-shaped relationship with automation usage. This research offers new insights into the effects of cognitive workload and automation reliance in safety-critical STSs. Essay 3 introduces a calibrated System Dynamics model, informed by empirical data and existing theories on workload suboptimality. This essay contributes to the managerial understanding of workload management, particularly the feedback mechanism between operators' workload and human errors, which is driven by overload and underload thresholds. The model serves as a practical tool for managerial practitioners to estimate the likelihood of human errors based on workload distributions. Overall, this dissertation presents an interdisciplinary and pragmatic approach, blending theoretical and empirical methodologies. Its broad impacts extend across management science, cognitive engineering, and resilience engineering, contributing significantly to the understanding and management of safety-critical socio-technical systems.
  • The Peasant and the Farmer: (Re)Constituting Settler Colonialism and Capitalist Relations in the US Imaginary
    Jones, June Ann (Virginia Tech, 2024-03-27)
    In the face of catastrophic climate change, scholars and activists have sought to fundamentally transform the existing food system in the United States. One solution being offered, repeasantization, seeks to reinvigorate the idea of the small farm accompanied by principles of ecological production. While invoking the term "peasant" promises something potentially new in the US context, where the farmer is hegemonic, this movement could end up reenacting the failures of the homesteading and back-to-the-land movements which reconstituted settler colonial and capitalist relations in the US imaginary. Using literature from peasant studies, development studies, and Marxist theory, I develop a theoretical orientation towards this potential problem which focuses on how the ideas of the peasant and the farmer are part of a dialectic which has regularly reinforced the existing dominant paradigm. Imagining a new way of thinking, I introduce the concept of the "peasant+ imaginary" in order to outline the ways that the general way of thinking about farming and farmers in the US serves the ideological function of 'othering' alternative practices and subjectivities. Through a historiography which focuses on the structural logic and compulsions of settler colonialism and capitalism, I reconstruct the history of the peasant-farmer dyad in the US context. Through a critical discourse analysis of Farmers' Bulletins, I also show how the United States Department of Agriculture reinforced a settler-capitalist farmer subject-formation in the interest of a "national agriculture" which served to marginalize Black, Indigenous, and non-capitalist ways of being. This dissertation is my contribution to literature which seeks to reimagine the US food system, with the goal of creating a truly sustainable agriculture which nourishes the land and the people who work and live on it.
  • Harnessing Systems Bioengineering Approaches to Study Microbe-Microbe and Host-Microbe Interactions in Health and Disease
    Datla, Udaya Sree (Virginia Tech, 2024-03-22)
    The core of the dissertation lies in developing two novel systems bioengineering approaches, a synthetic Escherichia coli killer-prey microecology, and a combined infection-inflammation NET-array system, to investigate the role of the mechanochemical complexity of the microenvironment in driving the microbe-microbe and host-microbe interactions, respectively. Herein, the first part of the dissertation includes designing and engineering a synthetic E. coli killer-prey microecological system where we quantified the quorum-sensing mediated interactions between the engineered killer and prey E. coli bacterial strains plated on nutrient-rich media. In this work, we developed the plate assay followed by plasmid sequencing and computational modeling that emphasizes the concept of the constant evolution of species or acquired resistance in the prey E. coli, in the vicinity of the killer strain. We designed the microecological system such that the killer cells (dotted at the center of the plate) constitutively produce and secrete AHL quorum-sensing molecules into the microenvironment. AHL then diffuses into the prey cells (spread throughout the plate) and upregulates the expression of a protein that lyses the prey. Through time-lapse imaging on petri plates automated using a scanner, we recorded the "kill wave" that originates outside the killer colony and travels outward as the prey dies. We found that the prey population density surrounding the killer decreased in comparison to other locations on the plate far from the killer. However, some of the prey colonies evolve to be resistant to the effects of AHL secreted by the killer. These prey colonies resistant to the killer were then selected and confirmed by plasmid sequencing. Using this empirical data, we developed the first ecological model emphasizing the concept of the constant evolution of species, where the survival of the prey species is dependent on the location (distance from the killer) or the evolution of resistance. The importance of this work lies in the context of the evolution of antibiotic-resistant bacterial strains and in understanding the communication between the microbial consortia, such as in the gut microbiome. Further, the second part of the dissertation includes quantifying the interactions between immune cells (primary healthy human neutrophils) and motile Pseudomonas aeruginosa bacteria in an inflammation-rich microenvironment. Neutrophils, being the first responding immune cells to infection, defend by deploying various defense mechanisms either by phagocytosing and killing the pathogen intracellularly or through a suicidal mechanism of releasing their DNA to the extracellular space in the form of Neutrophil Extracellular Traps (NETs) to trap the invading pathogens. Although the release of NETs is originally considered a protective mechanism, it is shown to increase the inflammation levels in the host if unchecked, ultimately resulting in end-organ damage (especially lung and kidney damage), as with the severe cases of sepsis and COVID-19. In our work, we developed a combined infection-inflammation NET-array system integrated with a live imaging assay to quantify the spatiotemporal dynamics of NET release in response to P. aeruginosa infection in an inflammatory milieu at a single-cell resolution. Importantly, we found increased NET release to P. aeruginosa PAO1 when challenged with inflammatory mediators tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6), but not leukotriene B4 (LTB4), compared to the infection alone. Our device platform is unique in that the nanoliter well-assisted individual neutrophil trapping enables us to quantify NET release with single-cell precision. Besides, incorporating confined side loops in the device helped us study the role of mechanical confinement on NET release, showing reduced NET release from neutrophils confined in the side loops compared to the relatively wider chambers of our microsystem. In summary, our work emphasizes the importance of studying the heterogeneity of NET release in host defense and inflammation. In the future, our system can be used for screening novel neutrophil-based immunotherapies and serve as a valuable research tool in precision medicine.
  • Multi-functional Holographic Acoustic Lenses for Modulating Low- to High-Intensity Focused Ultrasound
    Sallam, Ahmed (Virginia Tech, 2024-03-27)
    Focused ultrasound (FUS) is an emerging technology, and it plays an essential role in clinical and contactless acoustic energy transfer applications. These applications have critical criteria for the acoustic pressure level, the creation of complex pressure patterns, spatial management of the complicated acoustic field, and the degree of nonlinear waveform distortion at the focal areas, which have not been met to date. This dissertation focuses on introducing experimentally validated novel numerical approaches, optimization algorithms, and experimental techniques to fill existing knowledge gaps and enhance the functionality of holographic acoustic lenses (HALs) with an emphasis on applications related to biomedical-focused ultrasound and ultrasonic energy transfer. This dissertation also aims to investigate the dynamics of nonlinear acoustic beam shaping in engineered HALs. First, We will introduce 3D-printed metallic acoustic holographic mirrors for precise spatial manipulation of reflected ultrasonic waves. Optimization algorithms and experimental validations are presented for applications like contactless acoustic energy transfer. Furthermore, a portion of the present work focuses on designing holographic lenses in strongly heterogeneous media for ultrasound focusing and skull aberration compensation in transcranial-focused ultrasound. To this end, we collaborated with the Biomedical Engineering and Mechanics Department as well as Fralin Biomedical Research Institute to implement acoustic lenses in transcranial neuromodulation, targeting to improve the quality of life for patients with brain disease by minimizing the treatment time and optimizing the ultrasonic energy into the region of interest. We will also delve into the nonlinear regime for High-Intensity Focused Ultrasound (HIFU) applications, this study is structured under three objectives: (1) establishing nonlinear acoustic-elastodynamics models to represent the dynamics of holographic lenses under low- to high-intensity acoustic fields; (2) validating and leveraging the resulting models for high-fidelity lens designs used in generating specified nonlinear ultrasonic fields of complex spatial distribution; (3) exploiting new physical phenomena in acoustic holography. The performed research in this dissertation yields experimentally proven mathematical frameworks for extending the functionality of holographic lenses, especially in transcranial-focused ultrasound and nonlinear wavefront shaping, advancing knowledge in the burgeoning field of the inverse issue of nonlinear acoustics, which has remained underdeveloped for many years.
  • Analyzing Networks with Hypergraphs: Detection, Classification, and Prediction
    Alkulaib, Lulwah Ahmad KH M. (Virginia Tech, 2024-04-02)
    Recent advances in large graph-based models have shown great performance in a variety of tasks, including node classification, link prediction, and influence modeling. However, these graph-based models struggle to capture high-order relations and interactions among entities effectively, leading them to underperform in many real-world scenarios. This thesis focuses on analyzing networks using hypergraphs for detection, classification, and prediction methods in social media-related problems. In particular, we study four specific applications with four proposed novel methods: detecting topic-specific influential users and tweets via hypergraphs; detecting spatiotemporal, topic-specific, influential users and tweets using hypergraphs; augmenting data in hypergraphs to mitigate class imbalance issues; and introducing a novel hypergraph convolutional network model designed for the multiclass classification of mental health advice in Arabic tweets. For the first method, existing solutions for influential user detection did not consider topics that could produce incorrect results and inadequate performance in that task. The proposed contributions of our work include: 1) Developing a hypergraph framework that detects influential users and tweets. 2) Proposing an effective topic modeling method for short texts. 3) Performing extensive experiments to demonstrate the efficacy of our proposed framework. For the second method, we extend the first method by incorporating spatiotemporal information into our solution. Existing influencer detection methods do not consider spatiotemporal influencers in social media, although influence can be greatly affected by geolocation and time. The contributions of our work for this task include: 1) Proposing a hypergraph framework that spatiotemporally detects influential users and tweets. 2) Developing an effective topic modeling method for short texts that geographically provides the topic distribution. 3) Designing a spatiotemporal topic-specific influencer user ranking algorithm. 4) Performing extensive experiments to demonstrate the efficacy of our proposed framework. For the third method, we address the challenge of bot detection on social media platform X, where there's an inherent imbalance between genuine users and bots, a key factor leading to biased classifiers. Our approach leverages the rich structure of hypergraphs to represent X users and their interactions, providing a novel foundation for effective bot detection. The contributions of our work include: 1) Introducing a hypergraph representation of the X platform, where user accounts are nodes and their interactions form hyperedges, capturing the intricate relationships between users. 2) Developing HyperSMOTE to generate synthetic bot accounts within the hypergraph, ensuring a balanced training dataset while preserving the hypergraph's structure and semantics. 3) Designing a hypergraph neural network specifically for bot detection, utilizing node and hyperedge information for accurate classification. 4) Conducting comprehensive experiments to validate the effectiveness of our methods, particularly in scenarios with pronounced class imbalances. For the fourth method, we introduce a Hypergraph Convolutional Network model for classifying mental health advice in Arabic tweets. Our model distinguishes between valid and misleading advice, leveraging high-order word relations in short texts through hypergraph structures. Our extensive experiments demonstrate its effectiveness over existing methods. The key contributions of our work include: 1) Developing a hypergraph-based model for short text multiclass classification, capturing complex word relationships through hypergraph convolution. 2) Defining four types of hyperedges to encapsulate local and global contexts and semantic similarities in our dataset. 3) Conducting comprehensive experiments in which the proposed model outperforms several baseline models in classifying Arabic tweets, demonstrating its superiority. For the fifth method, we extended our previous Hypergraph Convolutional Network (HCN) model to be tailored for sarcasm detection across multiple low-resource languages. Our model excels in interpreting the subtle and context-dependent nature of sarcasm in short texts by exploiting the power of hypergraph structures to capture complex, high-order relationships among words. Through the construction of three hyperedge types, our model navigates the intricate semantic and sentiment differences that characterize sarcastic expressions. The key contributions of our research are as follows: 1) A hypergraph-based model was adapted for the task of sarcasm detection in five short low-resource language texts, allowing the model to capture semantic relationships and contextual cues through advanced hypergraph convolution techniques. 2) Introducing a comprehensive framework for constructing hyperedges, incorporating short text, semantic similarity, and sentiment discrepancy hyperedges, which together enrich the model's ability to understand and detect sarcasm across diverse linguistic contexts. 3) The extensive evaluations reveal that the proposed hypergraph model significantly outperforms a range of established baseline methods in the domain of multilingual sarcasm detection, establishing new benchmarks for accuracy and generalizability in detecting sarcasm within low-resource languages.
  • How Professional Development Supported Principals as Instructional Leaders Within Two School Divisions in Virginia: A Qualitative Investigation
    Hall, Rebecca Bienvenue (Virginia Tech, 2024-04-11)
    Principals have an impact on the teaching and learning that takes place in their schools. This research focuses on principal involvement in professional development (PD) to meet policy requirements while developing principals' skills to meet their changing roles to serve as instructional leaders accountable for student academic performance. The purpose of this qualitative study was to identify the types of PD principals and principal supervisors find most beneficial in developing principals' instructional leadership skills along with the perceived benefits and challenges of participating in PD designed for the principalship role. The secondary purpose was to identify the impact principal PD may have on instructional leadership practices and student achievement. The two research questions were: What types of PD do principals and principal supervisors find most impactful to developing principals' instructional leadership skills? What are the perceived benefits and challenges of participating in virtual, hybrid, and in-person PD specifically designed for the principalship role? A demographic survey and one-on-one, semi-structured interviews were completed with five elementary school principals, four secondary school principals, and three principal supervisors from a rural and suburban school division in Virginia. Deductive coding was used to analyze the data from interviews to determine common themes, patterns, similarities, and differences. Nine findings were discovered, including principals engage in PD focused on instructional leadership skills and perceive that PD has improved instructional practices and student outcomes, principals find value in networking and choice in PD, time is a barrier to participating in PD, and principal supervisors select and support principal PD opportunities. The findings provide principals, principal supervisors, and providers of principal PD with guidance on how to design PD focused on developing instructional leadership skills. Practitioners can utilize the study to guide the design of effective PD sessions that leverage the benefits noted by study participants while overcoming the challenges. Division leaders may consider the findings when developing PD plans for principals based on the literature and perceptions of study participants. These practices will help ensure principals receive the timely, targeted PD they need to become instructional leaders with a positive impact on student achievement.
  • Crystallization Behavior, Tailored Microstructure, and Structure-Property Relationships of Poly(Ether Ketone Ketone) and Polyolefins
    Pomatto, Michelle Elizabeth (Virginia Tech, 2024-04-08)
    This work investigates the influence of microstructure and cooling and heating rates on the physical and chemical properties of fast crystallizing polymers. The primary objectives were to 1) utilize advanced methodologies to accurately determine the fundamental thermodynamic value of equilibrium melting temperature (Tmo) for the semi-crystalline polymer poly(ether ketone ketone) (PEKK), 2) increase understanding of the influence of microstructure (random versus blocky) of functionalized semi-crystalline polymers on physical and chemical properties, and 3) understand the influence of additive manufacturing process parameters on semi-crystalline polymer crystallization and final properties. All objectives utilized the advanced characterization technique of fast scanning calorimetry (FSC) using the Mettler Toledo Flash DSC 1. The first half of this work focuses on the high-performance semi-crystalline aromatic polymer poly(ether ketone ketone) (PEKK) with a copolymerization ratio of terephthalate to isophthalate moieties (i.e., T/I ratio) of 80/20. Due to the fast heating and cooling rates of the Flash DSC, PEKK underwent melt-reorganization upon heating at slow heating rates. This discovery resulted in utilizing a Hoffman-Weeks linear extrapolation of the zero-entropy production temperature to establish a new equilibrium melting temperature of 382 oC. Additionally, a new NMR solvent, dichloroacetic acid, was discovered for PEKK, allowing for comprehensive NMR analysis of PEKK for the first time. Diphenyl acetone (DPA) was discovered as a novel, benign gelation solvent for PEKK, enabling heterogeneous gel-state bromination and sulfonation to afford blocky microstructures. The gel state functionalization process resulted in a blocky microstructure with runs of pristine crystallizable PEKK retained within the crystalline domains, and amorphous domains containing the functionalized PEKK monomers. The preservation of the pristine crystalline domains resulted in enhanced physical and chemical properties compared to the randomly functionalized analogs. Additionally, heterogeneous gel state functionalization of PEKK gels prepared from different solvents and gelation temperatures resulted in differences in crystallization behavior between blocky microstructures of the same degree of functionalization. This result demonstrates that the blocky microstructure can be tuned through controlling the starting gel morphology. The second half of this work focuses on understanding the influence of cooling and heating rates on the melting, crystal morphology, and crystallization kinetics on isotactic polypropylene (iPP), iPP-polyethylene copolymers (iPP-PE), and iPP/iPP-PE blends and using this information to gain understanding of how these polymers crystallize during the additive manufacturing processes of powder bed fusion (PBF) and material extrusion (MatEx). The crystallization kinetics of iPP, iPP-PE copolymers, and iPP/iPP-PE blends exhibited bimodal parabolic-like behavior attributed to crystallization of the mesomorphic crystal polymorph at low temperatures and the α-form crystal at high temperatures. Incorporation of non-crystallizable polyethylene fractions both covalently and blended as a secondary component, resulted in decreasing crystallization rates, inhibition of crystallization, and decreased crystallizability. Additionally, the non-isothermal crystallization behavior of these systems shows that the non-crystallizable fractions influence the crystal nucleation density and temperature at which polymorphic crystallization occurs. Utilizing in-situ IR thermography in the PBF system, the heating and cooling rates observed for a single-layer PBF print were used to mimic the PBF process by FSC. Partial melting in the printing process leads to self-seeding and increased crystallization onset temperatures upon cooling, which influences the final part melting morphology. Nucleation from surrounding powder and partially melted crystals greatly influences the crystallization kinetics and crystal morphology of the final part. Utilizing rheological experiments and process-relevant cooling rates observed in the MatEx process, the miscibility of iPP/iPP-PE blends influenced the nucleation behavior and crystallization rates, subsequently leading to differences in printed part properties.
  • Are You Judging Me? Exploring Legitimacy Through the Lens of Black Travelers
    Tucker, Charis Nicole (Virginia Tech, 2024-04-09)
    In recent years, the focus on the Black travel market has increased exponentially. While some may consider this to be a new market segment, Black travelers have been in the travel industry for years, however their legitimacy as a viable market segment has been questionable. This dissertation uses a three article approach to further the scholarship on Black travelers. The first paper uses a qualitative approach to explore the evolution of the Black travel market as represented in Black print media from 1920-2020. It further uncovers the tensions that exist between the socio-cultural and political norms of the times. The second article develops a valid and reliable measure of legitimacy using cognitive, pragmatic, and relational dimensions. The third article uses an experiment to investigate Black travelers' perceptions of racial justice advocacy statements made by destination marketing organizations (DMOs). Results from this dissertation indicate the longstanding engagement in the travel industry primarily through entrepreneurial endeavors. It also showcases Black travelers' ability to disrupt institutions and systems due to their willingness to share personal accounts of discrimination and through activism travel. As it relates to the evaluations of the tourism industry, Black travelers like to be recognized and represented in tourism-related products and services. Thus, their evaluations of DMOs' response to racial justice warranted a more detailed approach than what was often displayed.
  • Factors Affecting Fuel Transport of Firefighting Foam
    Islam, Rezawana (Virginia Tech, 2024-03-21)
    Aqueous film-forming foam (AFFF) used for fuel firefighting contains polyfluoroalkyl substances (PFAS) that have been identified as environmentally persistent and bioaccumulative resulting in phase out of AFFF. Currently, there are no environmentally friendly foams available that can perform at the same level as AFFF. Fuel transport has been recognized as a potential mechanism behind poor fire extinguishment, but the key features are yet unidentified. To fill these knowledge gaps, identifying the properties and features of surfactants used in firefighting foam that will prevent the transport of liquid fuel through the surfactant solution was imperative. To achieve that, this research was performed exclusively on single surfactants that have applications in firefighting foam. Impact of single surfactants on fuel transport was evaluated. Thermodynamics of the interaction between single surfactants and fuel; and kinetics of fuel transport through single surfactant solutions was observed. It was hypothesized that the liquid fuel transport would influence microstructure in the bulk of the surfactant solution. Experiments were conducted for different single surfactant structures. Various methods were applied to identify the microstructure and interfacial properties of surfactants with and without exposure to liquid fuel. The factor affecting microstructure, identified through this study was further used to evaluate the firefighting performance of single surfactants through ignition test. The thermodynamics of the interaction between fuel and single surfactants helped us to understand the fuel transport mechanism and role of micelle on fuel transport. Surfactant and fuel interaction has been studied below, at, and above the critical micelle concentration of surfactants. The effect of surfactant concentration, convection, and surfactant types were observed on the fuel transport. Moreover, an ignition test was conducted to evaluate the firefighting performance of single surfactants for various fuel types. Overall, the findings from this study will help design a new type of superefficient, environmentally acceptable surfactant for firefighting foam application.
  • The interplay between pathogenic bacteria and bacteriophage Chi: New directions in motility and phage-host interactions in Enterobacterales
    Esteves, Nathaniel Carlos (Virginia Tech, 2024-04-15)
    The bacterial flagellum is a rotary motor that propels motile bacteria through their surroundings via swimming motility, or on surfaces via swarming motility. The flagellum is a key virulence factor for motile pathogenic bacteria. Viruses that infect bacteria via this appendage are known as flagellotropic or flagellum-dependent bacteriophages. Much like other phages, flagellotropic phages are of interest for clinical applications as antibacterial agents, particularly against multidrug resistant (MDR) bacteria. Bacteriophage χ is a flagellotropic phage that infects multiple species of motile pathogens. In the projects described below, we characterized several aspects of the complex interactions between χ and two of its hosts: Salmonella enterica and Serratia marcescens. In Chapter I, we describe in detail the existing knowledge on flagellum-dependent bacteriophages, pathogenic bacteria, and the flagellar motility system. We also expand significantly on flagellotropic phage χ. In Chapter II, we describe our discovery of S. enterica cellular components other than motility that are crucial for bacteriophage χ infection, making the key discovery that the AcrABZ-TolC multi-drug efflux system is required for infection to proceed. We additionally found that the host molecular chaperone trigger factor is important for the χ phage lifecycle. In Chapter III, we outline our characterization of the initial binding interaction between χ and the flagellum, determining that of flagellin's seven domains, C-terminal domain D2 is the most important for χ adsorption. In Chapter IV, we expand on this by discussing our work that determined that the χ tail fiber protein is encoded by the gene CHI_31, purification of this recombinantly-expressed protein, and demonstration of its direct interaction with the flagellar filament. Lastly, in Chapter V, our findings indicate that S. marcescens is able to detect χ infection and lysis in the surroundings and alter gene expression, resulting in an increase in the production of the red pigment prodigiosin. Overall, our hypothetical model for χ infection is as follows: χ binds to the flagellum of its host using its single tail fiber, composed of monomers of the CHI_31 gene product gp31. This tail fiber interacts with CTD2 of flagellin, and the rotation of the flagellum brings the phage to the cell surface, where it interacts with AcrABZ-TolC to inject its genetic material into the host cytoplasm. At some point during the process of production of phage particles and subsequent cell lysis, the host molecular chaperone trigger factor likely assists with proper folding of χ proteins. After cell lysis, cells in the surroundings are capable of detecting lysis and responding accordingly, at least in the case of S. marcescens. This research is clinically relevant for a number of reasons. Phage therapy, the use of bacteriophages as antibacterial agents, requires knowledge of phage infection pathways for optimal implementation. The fact that the flagellum and a complex mediating MDR are both essential for χ infection leads to particular interest in χ for this application. Knowledge of the host-determining factors between χ and Salmonella may lead to the ability to alter the χ phage genome to target specific pathogenic Salmonella or Escherichia coli strains while avoiding disruption of beneficial bacterial communities.
  • Feedback in Digital Game-Based Learning (DGBL): Influencing Students' Self-Efficacy and Motivation
    Engelhardt, Mason Robert (Virginia Tech, 2024-03-28)
    As a teaching approach, digital game-based learning (DGBL) has grown in popularity and can positively influence students' motivational perceptions in difficult subjects, such as mathematics. DGBL has the capability to provide immediate feedback to students that can impact their results and experiences during gameplay; specifically, research studies have supported the conclusion that immediate feedback featured in DGBL can positively influence elementary students' self-efficacy and motivation related to DGBL gameplay. However, few studies have investigated the specific types of immediate feedback featured in DGBL within elementary mathematics. The purpose of this qualitative study was to investigate how different types of immediate feedback (i.e., destination, corrective, and explanatory) featured during DGBL use in mathematics influence elementary students' self-efficacy and motivation for gameplay. This study involved fifth grade students interacting with a digital game and being interviewed individually to elaborate on their perceptions regarding how feedback featured in DGBL influenced their self-efficacy and motivation. Findings from this study suggest the importance of DGBL immediate feedback as results indicated a positive change in both self-efficacy and motivation among students.