Doctoral Dissertations

Permanent URI for this collection

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

Browse

Now showing 1 - 20 of 18312

Worth Staying For: Love, Foster Parents, and the Work Systems Cannot Do
Coleman, Michael (Virginia Tech, 2026-05-13)
Foster parents occupy a critical, but frequently overlooked, position at the intersection of the child welfare and education systems in The United States of America. Despite the central role of foster parents in the lives of children in the foster care system, foster parents are frequently underprepared for the demands of navigating schools, under-supported by the various institutions designed to support them, and systemically excluded from the decision-making processes that shape the children in their care. This study uses narrative inquiry to explore the schooling experiences of four foster parents in three foster families: Peg, Steve and Katie, and Kate. Their stories illuminate what it means to advocate for children across complex, and often unresponsive, bureaucratic systems. Grounded in bell hooks' (2018) conceptualization of love as active practice, and Motta and Bennett's (2017) pedagogy of care, this dissertation examines how foster parents experience the intersection of child welfare and education, what supports they find useful, and what their experience reveals about the demands providing care places on them. Across all three narratives, foster parents encountered schools and child welfare agencies designed to manage compliance rather than cultivate care. Formal supports, such as trainings, caseworkers, and special education processes, were consistently inadequate, performative, or absent. The most meaningful support in each case was informal: peer relationships, trusted professionals who worked outside their institutional capacities, and communities built through shared experiences rather than mandatory attendance. This study contributes the concept of love as an epistemic stance. A way of knowing children that formal institutions consistently fail to see value in. Furthermore, this study offers a critique of the compliance architecture embedded in both educational settings and child welfare agencies. The findings suggest that love, in its most rigorous and unconditional form, is not peripheral to the work of foster care. Rather, it is the central work of foster care. Implications for foster parent training, school preparation, caseworker roles, and the formation of peer community are discussed, and ultimately, a set of conclusions is drawn regarding the reimagining of the foster care system.
Factors That Influence Retention Outcomes Among Black Transfer Students at Predominantly White Institutions Using the Culturally Engaging Campus Environments (CECE) Model
Clark, Kimberly Dawn (Virginia Tech, 2026-05-13)
Factors that Influence Retention Outcomes Among Black Transfer Students at Predominantly White Institutions Using the Culturally Engaging Campus Environments (CECE) Model Kimberly D. Clark ABSTRACT Black transfer students at predominantly White institutions (PWIs) encounter compounded barriers that contribute to persistently lower retention rates. This study examined institutional factors associated with Black student presence and persistence at PWIs through the lens of the Culturally Engaging Campus Environments (CECE) model. Because race-disaggregated retention data are not available in the Integrated Postsecondary Education Data System (IPEDS), retention was operationalized as institutional Black undergraduate enrollment share, the proportion of undergraduates who were Black at each institution in fall 2022. Using a quantitative, non-experimental design, the study applied hierarchical multiple regression to a merged IPEDS dataset of 2,563 four-year, degree-granting PWIs. Predictors were entered in two blocks: (a) institutional controls, size and sector, and (b) a CECE-aligned cultural responsiveness indicator, percentage of Black faculty and staff. Institutional controls explained negligible variance in Black enrollment share. Black staff representation, however, was strongly and positively associated with Black undergraduate enrollment share, accounting for the majority of explained variance in the final model. Findings affirm the CECE framework's emphasis on humanized, culturally responsive environments and suggest that institutions where Black students are present in substantial numbers are also institutions where Black faculty and staff are present in substantial numbers. Results contribute to equity-focused higher education research by centering institutional responsibility rather than student deficits and offer evidence-based implications for workforce diversity policy, data infrastructure reform, and culturally engaging campus practice aimed at improving outcomes for Black transfer students at PWIs.
Exploring Professional Learning of Experienced Principals in Rural Virginia: Engagement and Contextual Factors
Eanes, Joshua Aaron (Virginia Tech, 2026-05-13)
Although school principals are central to shaping student achievement and driving school improvement efforts, access to sustained, high-quality professional learning (PL) remains limited, particularly in rural contexts. This study examined how experienced rural principals in Virginia select professional learning experiences and the contextual factors, such as geography, funding, and social capital networks, that facilitate or impede their participation. This study employed a basic qualitative approach and involved seven principals with at least three years of experience representing elementary, middle, and high school settings. Data were gathered using semi-structured interviews and examined through an iterative coding process. Findings indicated that geographic distance limits access to PL opportunities for rural principals, while operational leadership demands and limited staffing capacity further constrain participation. Regional professional networks and partnerships with higher education institutions emerged as essential supports for accessing PL. Participants also noted that PL opportunities are often centered on state policy mandates and compliance, with travel, time, and staffing posing greater barriers than funding. Despite these challenges, participants emphasized that ongoing PL is essential for sustaining leadership growth and improving practice. Implications suggest that regional institutions of higher education, state agencies, school divisions, and professional organizations should collaborate to expand accessible, cost-efficient PL opportunities that reduce travel barriers and strengthen regional networks. Locally delivered, context-specific leadership development, aligned with the needs of rural schools, should be prioritized alongside funding structures that support staffing and administrative coverage. Additionally, school divisions should ensure sustained leadership development for experienced principals by balancing policy-driven PL with opportunities focused on instructional leadership, school improvement, and organizational management. Collectively, these efforts may enhance both access to and the impact of professional learning for rural school leaders.
Imposing Student Use and Development of Computational Thinking Skills During a Technological/Engineering Design-Based Learning (T/E DBL) Challenge
Crosby, Natalie Elizabeth (Virginia Tech, 2026-05-13)
While both computational thinking and design learning have gained interest with teachers, administrators, policy makers, and educational researchers alike, the cross sections of these fields are still largely unexplored, especially within the context of middle school and early adolescent development. The purpose of the exploratory case study was to investigate the development and usage of key computational thinking skills while middle school students were engaged in technological/engineering design based learning (T/E DBL). Middle school technology education and agriscience students in both rural and suburban schools in Virginia were tasked with a series of increasingly complex tasks using a precision agricultural robotic system that operates in three dimensions. Each task built on prior knowledge and had embedded meaningful science, mathematics, engineering, and technology components that tie in authentically, enabling students to integrate prior knowledge and new information needed to design solutions. The following question and sub-questions were used to guide this research study: RQ: When implemented as part of middle school technology and agriscience education, what evidence demonstrates that technological/engineering design based learning (T/E DBL) promotes student use and development of key computational thinking skill types? RQ-S1: While progressing through a series of STEMbot modules requiring the completion of increasingly complex robotics tasks, to what extent do students demonstrate their: Usage of computational thinking skills? Development of computational thinking skills? RQ-S2: What relationships exist between student progression through increasingly complex STEMbot robotics tasks and their demonstrated development of key computational thinking skill types? Quantitative and qualitative sources included a pre and post knowledge acquisition questionnaire, student response documents, exit tickets, and verbal reflection feedback. These extant data from the STEMbot Design Based Biotechnical Learning project (IRB #22-856) will be analyzed employing a sequential, mixed-method research design. Results indicated statistically significant development of students' computational thinking skills as students progressed through increasingly complex robotics design tasks. These findings demonstrate that engagement in technological/engineering design based learning promotes the development of computational thinking skills, particularly when tasks increase in complexity.
Childhood Adversity and Pathways to Psychopathology
Clinchard, Claudia Jane (Virginia Tech, 2026-05-13)
Exposure to childhood adversity is a common experience, with as many as one in two children experiencing some form of adversity by the time they reach adulthood. For the purpose of the following studies, childhood adversity is defined as any negative environmental experience that requires significant, ongoing adaptation by the child and represents a deviation from an expected environment. Adversity has many notable effects, including on emotional and cognitive abilities, the brain, and on reward processing. To better understand the various mechanisms through which childhood adversity can impact psychopathology, the following studies utilized self-report measures, behavioral measures, and functional resonance imaging (fMRI) to examine different potential transdiagnostic mechanisms and risks. The present study examined 167 adolescents (47% female) approximately annually for eight years (from ages 14 – 22). At each time point, they completed behavioral tasks that assessed their cognitive flexibility and delay discounting (i.e., the value of a reward related to how long it takes to reach), an fMRI task to examine brain activation during the outcome phase of an uncertainty gambling task, and self-report measures on other reward processing and psychopathology. Additionally, adolescents reported on their experiences of childhood maltreatment (i.e., abuse and neglect), chaos within the household, and peer victimization. Parents also reported on their household socioeconomic status, depression, substance use, and negative life events. In Chapter 2, the study examined how different aspects of childhood maltreatment (i.e., type, timing, and chronicity) were associated with adolescent self-regulation abilities (i.e., cognitive flexibility and expressive suppression), and how these abilities mediated the pathway to posttraumatic stress disorder (PTSD) in young adulthood. We found differences between abuse and neglect, and further nuances based on developmental timing. Specifically, childhood abuse, abuse in late childhood in particular (i.e., ages 6 – 13), was associated with better cognitive flexibility and lower PTSD symptoms. Additionally, neglect in early childhood (i.e., ages 1 – 5) was marginally associated with worse cognitive flexibility and higher PTSD symptoms. In Chapter 3, the study utilized a person-centered approach to examine how profiles of childhood adversity were associated with peer victimization in adolescence (i.e., ages 14 – 17), and in turn how peer victimization was associated with psychopathology (i.e., internalizing and externalizing symptoms), in late adolescence and into young adulthood (i.e., ages 18 – 22). We found that the profile with more types and severity of childhood adversity was associated with greater relational peer victimization, which in turn contributed to psychopathology. Further, we utilized a random-intercept cross-lagged panel model to better understand the associations between peer victimization and psychopathology in adolescence (i.e., ages 14 – 18). The results highlighted that higher-than-expected peer relational victimization was associated with higher- than-expected psychopathology (i.e., internalizing and externalizing symptoms) one year later at the within-person level during adolescence. Furthermore, higher-than-expected internalizing and externalizing symptoms were associated with higher-than-expected peer relational victimization in mid-adolescence (i.e., age 15 – 16). In Chapter 4, the study examined how childhood adversity was associated with between- person differences in reward processing and psychopathology from ages 14 – 22. Further, we examined how within-person differences in reward processing and psychopathology were associated with each other from year-to-year. We found that childhood adversity predicted between-person differences in delay discounting, anhedonia, and BAS Reward Responsiveness. Specifically, higher levels of abuse were associated with lower levels of BAS Reward Responsiveness and higher levels of anhedonia. Additionally, individuals who experienced greater neglect and negative life events had higher levels of delay discounting. Importantly, our results demonstrate that distinct types of childhood adversity influence outcomes in different ways. Specifically, childhood abuse had a positive impact on one aspect of self-regulation (i.e., cognitive flexibility), as well as a negative impact on reward responsiveness (i.e., higher anhedonia and lower BAS Reward Responsiveness). Next, childhood neglect had a negative impact on one aspect of self-regulation (i.e., cognitive flexibility), as well as a negative impact on reward valuation (i.e., delay discounting). Further, there were also differences in adversity profiles, revealing that more severe and diverse experiences of adversity had on peer victimization and highlighting that high levels of neglect and negative life events were associated with higher delay discounting. The findings from each study emphasize the role that childhood adversity plays in the development of
Jema'ah Islamiyah: Explaining the Evolution of the Terrorist Network in Indonesia from 2002 to 2010
Hendropriyono, Diaz Faisal Malik (Virginia Tech, 2026-05-13)
This dissertation investigates the conditions and mechanisms through which terrorist networks evolve in response to targeted elimination strategies, and to what extent such strategies contribute to their eventual decline. Focusing on the Jemaah Islamiyah terror network in Indonesia between 2000 and 2010, the study examines how organizational adaptation and decline occur as consequences of leadership decapitation. It employs a theory-driven, explaining-outcome process tracing approach to evaluate three theoretical pathways involving leadership decapitation, organizational survival, and the leadership dilemma. The analysis reveals that no single theoretical framework sufficiently accounts for all dimensions of network evolution, even when it adequately establishes a minimalist cause-and-outcome relationship. By reflecting on the theoretical and methodological limitations of this research, the findings underscore the need for more refined hypotheses on organizational survival following decapitation—developed through diverse theoretical perspectives and supported by more generalizable, methodologically sophisticated approaches
A Structural Motivational Systems Perspective on Student Engagement
Ambarkutuk, Zeynep N. (Virginia Tech, 2026-05-12)
Student engagement is a critical factor in academic success and persistence, particularly in undergraduate STEM courses where students frequently encounter demanding coursework and an elevated risk of attrition. Although prior research has demonstrated that students' perceptions of the motivational climate in a course are associated with their motivation and engagement in the course, less is known about the underlying mechanisms and how additional factors, such as perceived course difficulty, operate within these motivational processes. Grounded in the MUSIC Model of Motivation, this dissertation examines engagement as the outcome of interconnected motivational processes shaped by students' perceptions of their learning environments. This dissertation consists of two empirical studies that progressively examine motivational pathways influencing engagement. The first study investigates whether course motivation serves as a mediating mechanism linking students' perceptions of the motivational climate to behavioral engagement (i.e., effort) across undergraduate STEM courses. Using a multiple-group structural modeling approach, the study establishes motivation as a key explanatory process through which instructional environments translate into student engagement and provides evidence supporting the robustness of these relationships across instructional contexts. Building on this foundation, the second study integrates perceived course difficulty into the established motivational framework to develop a more nuanced understanding of engagement processes in challenging learning environments. This study examines how perceived difficulty operates alongside students' motivational climate perceptions and motivation to influence engagement, offering insight into how students interpret academic demands and sustain effort. The findings of this dissertation advance theoretical understanding of motivational processes underlying engagement and provide practical implications for instructional design by identifying factors that instructors can manipulate to foster student motivation and engagement.
Impact of Sleep and Circadian Rhythm Disruption on Pulmonary Arterial Hypertension: Pathophysiology and Therapeutic Implications
Imani, Seun Idowu (Virginia Tech, 2026-05-12)
Background and Aim: Pulmonary arterial hypertension (PAH) is a progressive and deadly cardiopulmonary disease characterized by remodeling of pulmonary vessels and right ventricular dysfunction. Despite available treatments, the death rate remains high among patients. Emerging clinical data show a high prevalence of poor sleep quality in patients with PAH. However, it is still unclear whether or how sleep disruption contributes to PAH progression. Additionally, the role of the molecular clock in various diseases is well documented; however, how this clock affects pulmonary artery smooth muscle cell (PASMC) function and PAH remains largely underexplored. Methods: We used two models of sleep disruption (sleep fragmentation and chronic jet lag), four mouse models of PAH, and conducted hemodynamic and histomorphometric analyses to determine the effect of sleep disturbance on PAH. Bulk RNA sequencing, immunostaining, and immunoblotting assays were employed to investigate signaling mechanisms. Electroencephalography and electromyography (EEG/EMG) telemetry were used to assess sleep architecture in PAH mouse models. We then used melatonin and clodronate interventions to examine the roles of sleep modulation and inflammation reduction in PAH. The clock genes BMAL1 and CLOCK (key drivers of the molecular clock) in PASMCs were defined by synchronizing cells from healthy donors and PAH patients, followed by time-point qPCR. Finally, we explored the role of the clock gene in PAH using smooth muscle cell (SMC)-specific Bmal1 knockout mice. Results: Our data showed that sleep disruption significantly aggravated PAH, characterized by increased right ventricular systolic pressure (RVSP), enhanced RV hypertrophy, and greater pulmonary vascular remodeling. RNA-seq and immunostaining analyses of lung tissues revealed that sleep disruption caused substantial enrichment of inflammatory pathways, macrophage accumulation, and elevated levels of inflammatory cytokines. Further in vitro studies indicated that inflammatory cytokines markedly activated the IL6/STAT3/TGF-β/SMAD2/3 pathway in PASMCs, a finding also observed in vivo. EEG/EMG measurements demonstrated that PAH causes sleep disruption in mice. The combination of sleep-promoting and anti-inflammatory therapies significantly reduced PAH. PASMCs from PAH patients exhibited disrupted oscillations of BMAL1 and CLOCK, and SMC-specific deletion of Bmal1 protected mice from PAH symptoms. Conclusion: This dissertation shows that PAH and sleep disruption form a self-reinforcing pathological cycle, where PAH causes sleep disruption, and disturbed sleep further worsens PAH and amplifies disease progression. Combining sleep-promoting and anti-inflammatory strategies attenuates PAH in preclinical models. Concurrently, the circadian molecular clock component BMAL1 is dysregulated in PASMCs, leading to PASMC hyperproliferation through the cell cycle checkpoint, and SMC-specific inhibition of BMAL1 offers a promising therapy for PAH.
Integrated Buckling Analysis and Manufacturable Design of Variable Stiffness Composite Panels for High-Performance Structures
Agarwal, Mayank (Virginia Tech, 2026-05-12)
Variable stiffness composite panels, including tow-steered laminates and functionally graded materials (FGMs), offer significant advantages over traditional uniform plates by enabling localized load path redistribution and extreme environment multi-functionality. Integrating curvilinear stiffeners into these panels further enhances structural stability against buckling with minimal weight penalties. These highly tailored structural components are vital for advanced aerospace applications like wingboxes and fuselages. However, the design and analysis of these complex high-performance structures remain computationally challenging, particularly when ensuring the manufacturability of the final design. To address these challenges, this research first presents a mesh-independent buckling analysis solver for curvilinearly stiffened FGM plates utilizing the Ritz method with orthogonal Jacobi polynomials. This approach eliminates the need for computationally expensive re-meshing during shape and layout optimization studies. Building on this, the study introduces a comprehensive integrated optimization framework for curvilinearly stiffened tow-steered panels. This framework simultaneously designs tow paths and stiffener layouts while rigorously enforcing physical manufacturing constraints, including fiber curvature, and gaps, and overlaps. Finally, two distinct methodologies for tow-steered laminate optimization are evaluated and compared: (1) direct fiber angle parameterization using Simulia/Isight and Abaqus/Standard, which facilitates the explicit enforcement of ply-level strength and manufacturing limits, and (2) a bi-level lamination parameter approach with analytical gradients, using an open source parallel finite-element code Toolkit for the Analysis of Composite Structures (TACS) and an open-source high-performance computing platform for multidisciplinary optimization OpenMDAO, that convexifies the design space for highly efficient computational evaluations. Furthermore, the bi-level framework is extended to perform simultaneous structural topology and variable angle tow-path optimization, concurrently generating the optimal macroscopic material layout and the localized variable stiffness distribution. Ultimately, this work provides a scalable, robust methodology for designing lightweight, easy to manufacture, and highly tailored aerospace composite structures.
Understanding Brain Activity and Neuromotor Function in Infants at Low and High Risk for Neuromotor Impairment
Evans, Megan Elizabeth (Virginia Tech, 2026-05-12)
Neuromotor impairments (NMIs) encompass a range of conditions that disrupt movement, posture, and tone due to abnormalities in the developing brain. Brain activity that supports early motor development has yet to be elucidated in infants with NMIs, representing a major knowledge gap. This is a two-group cohort design including infants at high risk for neuromotor impairment (n=12) and those with no known risk factors (n=14). Infants were considered high-risk if they had at least one of the following risk factors: low birth weight, premature birth, multiple gestations, maternal infections or complications, and/or postnatal injury. First, we used optically pumped magnetometer magnetoencephalography (OPM-MEG) to examine differences in beta power over the sensorimotor cortex during an awake, naturalistic movement paradigm, which is also a validated assessment of movement quality. Neither beta power nor modulation differed across groups and movement/rest sessions. These findings suggest that beta oscillatory activity is more reflective of ongoing maturation and variability in sensorimotor organization; therefore, its sensitivity to detect differences in early infancy may be limited. Second, we used resting-state functional MRI to assess the relationship between motor network connectivity involving sensorimotor cortex (SMN), basal ganglia (BG), and thalamus with neuromotor function, as measured by the Hammersmith Infant Neurological Examination (HINE). There were no group differences in HINE scores, total and regional brain volumes, or in functional connectivity (FC) analyses of the sensorimotor or basal-ganglia-thalamocortical networks; however, a trend-level association was identified between the SMN and the thalamus. These findings suggest that FC in thalamocortical networks may serve as a more sensitive marker of early motor function during periods likely characterized by rapid developmental changes. Combined, the findings support the emergence of brain-behavior relationships as it relates to motor development.
From Diagnosis to Clinical Decision Support: An AI Framework for Pediatric ICU Using Electronic Health Records
Song, Haoqiu (Virginia Tech, 2026-05-12)
Iatrogenic withdrawal syndrome (IWS) is a common and clinically significant complication in pediatric intensive care units, often arising from prolonged exposure to opioids and sedatives. Current assessment methods rely on manual, intermittent scoring systems that are labor-intensive and may delay timely intervention. This dissertation presents a unified artificial intelligence framework for automated diagnosis, early prediction, and clinical decision support for IWS using electronic health records. First, a machine learning–based computable phenotype is developed to estimate real-time withdrawal risk from structured clinical and medication data. Second, an explainable deep learning model, FIR-LSTM, is proposed to forecast near-term IWS risk using longitudinal patient trajectories. Finally, these models are integrated into a safety-gated clinical intelligence system that combines predictive modeling, deterministic calculations, and retrieval-grounded large language model outputs to support clinician decision-making. Together, this work advances the development of interpretable, real-time, and clinically deployable AI systems for pediatric critical care, enabling earlier detection of withdrawal risk and supporting safer, data-driven treatment strategies.
The Relationships Among Schoolwide Positive Behavior Interventions and Supports Implementation Fidelity, Teacher Perceptions, and Teacher Self-Efficacy
Bucholz, Zachary Lemuel (Virginia Tech, 2026-05-12)
The purpose of this quantitative study was to examine the relationships among teacher self-efficacy, teachers' perceptions of Schoolwide Positive Behavioral Interventions and Supports (SWPBIS) implementation, and school-level implementation fidelity in middle schools within a school division in the Commonwealth of Virginia. Teacher self-efficacy was measured using the Teacher Sense of Efficacy Scale (TSES), teacher perceptions of SWPBIS implementation were measured using the Self-Assessment Survey (SAS), and implementation fidelity was measured using archival Tiered Fidelity Inventory (TFI) scores. Participants included 238 teachers across eight middle school campuses. Simple linear regression examined teacher-level relationships, and Spearman's rank-order correlation examined TFI and TSES scores. Results indicated significant positive relationships between teacher self-efficacy and perceptions of SWPBIS implementation at the classroom level, F(1, 236) = 19.9, p < .001, R² = .08, and schoolwide level, F(1, 236) = 10.5, p = .001, R² = .04. Teachers with higher self-efficacy reported stronger perceptions that SWPBIS practices were in place. In contrast, the relationship between school-level fidelity and teacher self-efficacy was positive but not significant, likely due to limited variability in fidelity scores. These findings support combining teacher perception data with fidelity measures when evaluating SWPBIS implementation, as stronger teacher self-efficacy was associated with more favorable perceptions of schoolwide behavior systems and may inform sustained implementation efforts.
Chemical Investigation of Lipopeptides and Oxaboroles Toward the Development of Crop and Medical Antifungals
Campbell, Rose Allison (Virginia Tech, 2026-05-12)
Antimicrobial-resistant infections and environmentally damaging crop pathogens both represent pressing issues of the current age. Natural products have served as effective drugs and structural design inspiration for over 70% of approved medications and still hold immense therapeutic potential. It is necessary to investigate new biological systems to discover novel structural scaffolds with promising commercial applications. Moon snails (family Naticidae) lay their egg masses in the open ocean with no physical parental protection. It is hypothesized that the microbiota on the eggs provide chemical protection by producing natural products with diverse biological activities. The moon snail egg masses represent a promising, underexplored symbiotic system for natural product discovery. Herein, we investigated the natural product potential of microbiota isolated from egg masses of Neverita spp. using mass spectrometry-based discovery tools. This resulted in the discovery and complete characterization of the bokeelamides (Chapter 2), a family of lipopeptide siderophores with strong selectivity for FeIII over other metals tested and a pFe (iron affinity) of 25.8 ± 0.3. The bokeelamides exhibited no antimicrobial, antibiofilm, or hemolytic activity at concentrations up to 50 µM, but were found to be weakly cytotoxic. Next, we reported the first NMR characterization and absolute stereoconfiguration assignment of the kurstakins, known antifungal lipopeptides previously shown to play a role in the efficacy of crop biocontrol agents (Chapter 3). As part of this effort, we uncovered over 50 analogs through MS/MS and GCMS lipid analysis and >3,000 NCBI strains with biosynthetic potential for kurstakin production, predominantly from the Bacillus cereus group. Finally, a medicinal chemistry approach to drug discovery investigated the antimicrobial properties of the oxaboroles, structural analogs of the approved antifungal Tavaborole (Chapter 4). The oxaboroles were generally inactive against bacteria except for Escherichia coli, while halogen-substituted rings showed the greatest potency against both fungal and bacterial pathogens. The structure-activity relationship (SAR) against fungal pathogens revealed the importance of meta-substituted halogens on the benzyl ring, with analogs having minimum inhibitory concentrations (MICs) as low as 22 µM against Penicillium chrysogenum, while bulky non-halogen substituents abolished activity altogether. Interestingly, the SAR against Escherichia coli showed a preference rather for para-substituted halogenated benzyl rings. Further studies should develop this bacterial-target SAR and explore boronic acid compounds with increased sp3 character for future microbial targets. Overall, the work described expands our knowledge of lipopeptide natural products and synthetic oxaboroles, revealing both high iron-affinity siderophores and antifungal compounds with potential for agricultural and medicinal applications.
Exploring Family Relationships at the Intersection of Family Life and Higher Education: The Experiences of First-Generation College Students
Guan, Lili (Virginia Tech, 2026-05-12)
First-generation college students (FGCSs), typically defined as students for whom neither parent has obtained a bachelor's degree, bring distinct experiences and resources to their higher education journeys. This dissertation challenges deficit perspectives that attribute FGCSs' experiences to perceived deficiencies in social and cultural capital. Within the family science literature, there remains limited understanding of how family relationships shape FGCSs' educational experiences. To address this gap, this study investigates how the multifaceted family relationships of FGCSs influence their academic journeys. Guided by symbolic interactionism, this dissertation examines how individuals construct meaning through social interaction and how these meanings shape their actions and experiences. Drawing on this framework, the study explores how interactions between FGCSs and their family members shape students' understandings of family responsibilities and expectations, parental emotional support, and emotional tensions related to upward mobility. It further considers how these meaning-making processes influence students' engagement with higher education. Rather than framing FGCSs' experiences in deficit terms, this study highlights the strengths and resources embedded in their family relationships that support their educational pathway. This study employed reflexive thematic analysis to analyze data from semi-structured, in-depth interviews with 17 lower-income FGCSs aged 18-25 at a moderately selective four-year university. Following Braun and Clarke's six-phase approach, the analysis identified three main themes: (1) family responsibility as a site of moral positioning and identity formation, through which students enacted roles such as language brokers, caregivers, and institutional navigators; (2) parental emotional support as relational recognition, where validation, reassurance, pride, and trust reinforced students' sense of competence and belonging; and (3) the negotiation of emotional tensions surrounding upward mobility, where students actively reframed family achievement guilt through boundary setting, intergenerational purpose, and the integration of academic and familial identities. This study offers two key contributions. First, it provides educators and policymakers with a deeper understanding of how family relationships operate in FGCSs' lives not simply as background factors, but as dynamic relational contexts through which family responsibilities, parental emotional support, and emotional tensions are simultaneously experienced and negotiated. Second, the findings offer practical insights for designing intervention programs that move beyond deficit-oriented assumptions by recognizing FGCSs' families as sources of both support and obligation, and by attending to the emotional labor students perform as they navigate family expectations alongside academic demands. By developing institutional practices that are more relationally responsive to students' family contexts, this study aims to contribute to more inclusive educational environments that support FGCSs' academic success and overall well-being. Ultimately, this study contributes to a more nuanced understanding of FGCSs' experiences by emphasizing the role of family relationships in shaping educational trajectories and advocating for asset-based approaches that recognize the strengths embedded within FGCSs' family contexts.
Beyond the Hidden Abode: A Critique of the Labor Theory of Value
Gignoux, Hannah Rose (Virginia Tech, 2026-05-12)
This dissertation critically examines Marx's labor theory of value (LTV) through an analysis of four foundational concepts within Marxist political economy: labor, subsistence, money, and competition. I argue that while Marx sought to develop a dynamic theory of value grounded in social relations rather than natural or fixed premises, the labor theory of value ultimately undermines these ambitions. In attempting to explain the quantitative relationship between value and price through labor-time, Marx's theory repeatedly relies on static assumptions that conflict with his broader methodological commitments to immanence and social holism. I engage closely with the value-form interpretation of Marx, particularly the work of Isaak Illich Rubin and Michael Heinrich. Value-form theorists reinterpret abstract labor and value as socially constituted categories produced through exchange and the totality of capitalist relations rather than as fixed substances embodied in commodities. I argue that these readings illuminate the most dynamic dimensions of Marx's critique by emphasizing abstraction, interdependence, and the social character of labor. At the same time, however, value-form approaches remain constrained by their continued commitment to the labor theory of value itself, especially through residual reliance on concepts such as subsistence and socially necessary labor-time.
Adaptive Epistemologies and Neo-Wilds
Cantrell, Bradley Earl (Virginia Tech, 2026-05-12)
*Adaptive Epistemologies and Neo-Wilds* advances a practice-based theoretical framework for landscape architecture under conditions of climatic non-stationarity, ecological indeterminacy, and computational saturation. The dissertation argues that the inherited Promethean epistemology, with its commitments to prediction, control, and stable representation, is not corrected by the addition of more sensing, more modeling, or more autonomous machinery. Applied within an unexamined epistemological frame, computational power accelerates and entrenches the failures of prediction paradigms rather than resolving them. A different epistemological footing is required. The dissertation proposes adaptive epistemology as that footing, knowledge production at territorial scale in which the territory itself participates, design propositions function as testable hypotheses, and divergence between accounts is treated as information rather than error. Six frameworks distill twenty years of practice into the operative components of this position. They are multiple intelligences, technogeographies of sensing, wetware, generational robotics, coupled ecologies, and reflexive stewardship. Three concepts cross all six. Adaptive epistemology unpacks the knowledge structure. The cultivant structures the ongoing relationship between designed intention and biological agency in which maintenance is the primary design act. Neo-wilds frames the territorial condition that emerges when these commitments are sustained across generational timescales. The argument is generated by refraction, a method that retells the same body of work from successive vantage points until its theoretical structure becomes legible. Practice yields theory which returns to practice, recalibrating what landscape architecture can be epistemologically responsible for in the Anthropocene.
Essays on Economic Outcomes of Training-Based Knowledge Interventions
Das, Nandini (Virginia Tech, 2026-05-12)
This dissertation studies the economic impacts of training-based knowledge interventions in low-income settings, with a focus on financial literacy and agricultural technology adoption. Across three chapters, it examines how individuals respond to information delivered through training programs and whether such interventions translate into sustained economic gains. A central theme across the chapters is that although low-cost knowledge interventions can lead to meaningful behavioral change, their effectiveness in driving more complex outcomes, such as technology adoption, depends crucially on contextual factors. The first chapter evaluates the impact of a digital financial literacy training program targeted at refugee youth in Uganda. As humanitarian assistance increasingly shifts from in-kind transfers to cash-based and digitally delivered programs, complementary financial capabilities have become critical. Exploiting the staggered geographic rollout of the program, I implement a strategy that closely emulates a natural experiment. Using reduced-form econometric analyses, robust to various specifications, I find that participation in the training program is associated with significant positive effects on financial knowledge and financial behavior among young refugees. In addition, the program enhances participants' confidence in navigating financial systems and integrating with host communities, suggesting broader social benefits beyond purely economic outcomes. The second chapter examines a bundled agricultural training program for groundnut farmers in rural Bangladesh, which combines Integrated Pest Management (IPM), Good Agricultural Practices (GAP), and fertilizer guidance. Using panel data and reduced-form estimation, I find that adoption is selective and cost-ordered. Farmers adjust fertilizer use in line with recommendations but largely avoid newly introduced IPM technologies, while responses to GAP are limited. As a result, the intervention generates no measurable gains in yields or profits, since the highest-impact components remain unadopted. To interpret these patterns, I develop a simple conceptual framework based on a signal extraction problem: when training provides information at the bundle level, farmers cannot infer component-specific returns and instead rely on observable costs when making adoption decisions. The findings highlight a key limitation of bundled interventions, where gains in scalability and administrative convenience may come at the cost of selective adoption of lower-impact practices. Building on the findings from the second chapter, the intervention was refined. The third chapter studies the adoption of multi-stage IPM technologies using evidence from a cluster randomized controlled trial that combines an improved one-day training with season-long extension support. This chapter addresses the limited evidence on the profitability of IPM technologies while also examining how farmers respond to multiple components introduced across stages. I analyze stage-wise adoption decisions using a generated regressor framework to account for the sequential nature of technology uptake. Using reduced-form econometric analyses, I also estimate the impacts of the program on farmer outcomes. The results show that the intervention increases adoption of several recommended practices and leads to substantial reductions in chemical input use, indicating movement toward more environmentally sustainable production. However, these changes do not translate into significant gains in yields or profits in the short run. I further show that early-stage adoption decisions are shaped by farmer characteristics such as landholdings and soil conditions, while later-stage adoption is largely driven by path dependence and continuation of prior choices. Overall, the chapters show that training programs can shift knowledge and behavior, but translating these into meaningful economic gains is limited by learning costs, financial barriers, and complexity. The findings highlight the importance of accounting for these constraints in program design and suggest that simpler interventions can improve effectiveness.
Lifting I-Functions from the Flag Varieties to Their Cotangent Bundles
Amini, Kamyar (Virginia Tech, 2026-05-12)
We relate two fundamental enumerative functions, namely the I-functions in the quantum K-ring of G(r,n) and of its cotangent bundle, by defining a K-theoretic operator on classes, called balancing. This operator lifts the I-function of G(r,n) to that of T^*G(r,n), providing an explicit geometric interpretation. We also define an operator acting on difference operators and show that, for certain K-theoretic classes and the corresponding difference operators that annihilate them—including the I-functions of projective spaces P^n—the balancing operation on difference operators and on classes is compatible. Moreover, for general G(r,n), we recover the Bethe-Ansatz equations for T^*G(r,n) via a procedure inspired by both balancing and the abelian/non-abelian correspondence.
VHealth Suite: A Unified, Secure, and Intelligent Patient-Centered Framework for Legacy System Integration in Virtual Hospital Ecosystems
Alsalamah, Sara Abdullah I. (Virginia Tech, 2026-05-11)
A virtual hospital (VH) is a distributed, digitally enabled healthcare ecosystem that extends clinical services beyond physical facilities, facilitating patient-centered (PC) care across geographically dispersed settings through interoperable infrastructures, telemedicine platforms, and hub-and-spoke coordination. However, legacy healthcare information systems remain fragmented, disease-centered, and operationally reactive, which limits secure data sharing, knowledge integration, and system-wide capacity awareness. These challenges are further exacerbated by rising demand, workforce constraints, and the need for predictive operational intelligence to enable efficient and scalable care delivery. To address these limitations, this dissertation proposes VHealth Suite, a unified, secure, and intelligent framework designed to modernize legacy healthcare information systems and seamlessly integrate them into VH ecosystems without requiring system replacement. The framework is implemented as a multi-component architecture that integrates secure data exchange, intelligent knowledge extraction, predictive operational intelligence, and human-in-the-loop interaction. First, the secure data exchange component is realized through VHealth-AC, a novel access control (AC) model that enables fine-grained and secure access to PC data across distributed and autonomous healthcare systems. The model employs a five-tier PC information classification scheme and operates as a neutral collaboration security domain, allowing clinicians to securely access patient data across institutional boundaries at the point of care. Second, intelligent PC knowledge extraction is achieved through VHealth-CNN and VHealth-MFusion. VHealth-CNN leverages a double-layer convolutional neural network (CNN) to extract and classify health-related features from biomedical data, achieving prediction accuracies of 91.3%, 93.5%, and 95% for obesity, hypertension, and diabetes, respectively. VHealth-MFusion introduces a hierarchical multimodal deep learning framework that integrates chest X-ray (CXR) images with structured clinical data, achieving 97.2% overall classification accuracy, improving robustness under class imbalance, and reducing misclassifications among clinically similar conditions. Third, predictive operational intelligence and clinical routing are addressed through VHealth-Routing, an AI-driven framework that combines clinical decision support with capacity-aware optimization. The framework integrates a clinical routing engine, a spatiotemporal prediction engine, and a constrained re-ranking mechanism to align clinical relevance with operational feasibility. It is evaluated using a large-scale real-world dataset from the Seha VH ecosystem in Saudi Arabia, comprising over 15 million records, with a representative subset of 1,006,111 appointments used for experimentation. Results demonstrate strong routing performance, with XGBoost achieving 73.2% Top-1 accuracy and 97.6% Top-3 accuracy, alongside effective demand forecasting and waiting time estimation, supporting improved workload distribution and reduced system inefficiencies. Finally, the human-in-the-loop component is implemented through VHealth-Bot, an AI-driven conversational platform that integrates natural language processing, diagnostic reasoning, and adaptive learning to support clinician–patient interaction. The system enhances real-time symptom assessment, personalized response generation, and collaborative decision-making, while maintaining clinician oversight to ensure safety and preserve clinical expertise. Evaluation results indicate improvements in diagnostic support, workflow efficiency, clinician–patient communication, and patient satisfaction. Overall, VHealth Suite provides a scalable, privacy-preserving, and intelligent architecture that unifies clinical intelligence with operational optimization. The proposed framework enables proactive, data-driven, and PC care delivery in large-scale VH ecosystems, improving clinical outcomes, enhancing operational efficiency, and fostering more responsive healthcare systems.
Identifying Novel Therapeutic Approaches for Individual Symptoms of Alcohol Use Disorder
Dong, Yuyang (Virginia Tech, 2026-05-11)
Alcohol use disorder (AUD) is a multi-symptomatic disorder which presents a continued challenge and burden to healthcare worldwide. While current Food and Drug Administration (FDA) approved treatments of AUD address some symptoms, they do not address others, notably alcohol dependence-associated pain; additionally, the existing treatments have limited effectiveness, leaving subpopulations of AUD patients underserved. Our work examined and summarized the current research on alcohol dependence-associated pain and provided a comprehensive overview of techniques to quantify nociception in rodent models, in the context of AUD research. We then examined different potential nociceptive signaling pathways for their involvement in dependence associated-pain using the chronic intermittent ethanol vapor (CIE) mouse model. We found that the alcohol dependence associated-pain mechanism is distinct from other mechanisms of chronic pain and that it is independent of endocannabinoid signaling pathways. As our prior work found association between plasma levels of pro-inflammatory lipid 15-Hydroxyeicosatetraenoic acid (15(S)-HETE) in AUD patients with their alcohol craving, and the 15-lipoxygenase (15-LOX) signaling pathway is involved in the development of chronic pain, we examined the relationship between this pathway and various symptoms of AUD. We found that 15-LOX signaling contributes to the escalation of alcohol intake characteristic of alcohol dependence and the development of craving-like behaviors. Overall, our findings highlight the importance and uniqueness of the different mechanisms that underlie different symptoms of AUD, with alcohol dependence associated-pain having a distinct mechanism different from other chronic pain mechanisms and powerfully implicate the 15-LOX signaling pathway in escalation of alcohol intake and craving.

Browse

Recent Submissions