VTechWorks
VTechWorks provides global access to Virginia Tech scholarship, including journal articles, books, theses, dissertations, conference papers, slide presentations, technical reports, working papers, administrative documents, videos, images, and more by faculty, students, and staff. Faculty can deposit items to VTechWorks from Elements, including journal articles covered by the University open access policy. Email vtechworks@vt.edu for help.
Open Access Policy
Virginia Tech's open access policy enables researchers to deposit the accepted version of scholarly articles with no embargo.
Theses and Dissertations
Virginia Tech was first in the world to require ETDs in 1997, and continues to add scans of older theses and dissertations.
Open Textbooks
More than 50 freely available and openly licensed textbooks are among our most downloaded items.
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Recent Submissions
The Development and Study of Protein Photocatalysts for Photoinduced Electron/Energy Transfer Reversible Addition-Fragmentation Chain Transfer Polymerizations
Anderson, Ian Carey (Virginia Tech, 2026-03-16)
This dissertation reviews literature relevant to the broader project of Biocatalyst Development for photoinduced electron/energy transfer-reversible addition-fragmentation chain transfer (PET-RAFT) Polymerizations. Chapter 1 traces the history of reversible deactivation radical polymerization (RDRP) and discusses the utility of photo electron/energy Transfer (PET) catalysis in RAFT polymerizations. We report, for the first time, an inherently photoactive protein that catalyzes PET-RAFT polymerizations. Zinc myoglobin (ZnMb) was identified as an inherently photoactive protein that was uniquely suited to photoinduced electron/energy transfer chemistry, and this protein was synthesized and used for PET-RAFT polymerizations. ZnMb proved to perform well, demonstrating all of the required features for a well-controlled polymerization, such as linear pseudo-first-order kinetics, linear growth in molecular weight with conversion, and maintained living chain ends, as evidenced by successful chain extension experiments.
Inspired by the method developed for using ZnMb as a protein photocatalyst, we aimed to explore some of the consequences of using a protein in polymerization. For instance, we examined how polymer molecular weight affects chain-extension kinetics due to steric interactions with a restricted protein active site. Additionally, we investigated other reaction parameters to tune when using a protein, such as buffer composition and resulting protein stability. We demonstrate that by changing buffer composition and adjusting the salinity of the mixture, we can alter the kinetic performance of the polymerization while still maintaining a well-controlled process, as evidenced by linear pseudo-first-order kinetics, linear growth in molecular weights, and low dispersities.
Essays on Multi-Faceted Optimization and Data-Driven Modeling and Analysis of Logistics, Lot-Sizing, and Scheduling Problems
Sangha, Sandeep Singh (Virginia Tech, 2026-03-16)
This dissertation develops advanced optimization models and solution methodologies to address three complex and practically relevant problems in operations research: biomass feedstock logistics, integrated lot-sizing and scheduling, and data-driven large-scale production scheduling. Across these domains, the work contributes novel mathematical formulations, decomposition-based algorithms, and hybrid machine learning--optimization frameworks that improve the scalability, accuracy, and practical relevance of decision-making tools used in modern industrial and supply chain environments. The first part of the research proposes a comprehensive biomass logistics framework for cost-effective ethanol production from switchgrass. A mixed-integer programming model is developed that incorporates equipment routing, facility location, and transportation decisions, giving rise to a challenging three-stage structure. A nested Benders decomposition algorithm with multi-cut optimality conditions is introduced, enabling the solution of real-world problem instances that are otherwise intractable for state-of-the-art commercial solvers. Results demonstrate significant reductions in computational time and improved solution quality, thereby supporting the economic and environmental viability of biofuel supply chains. The second part investigates an uncapacitated integrated lot-sizing and scheduling problem with sequence-dependent setup costs. A network-flow-based formulation is proposed along with facet-defining inequalities that enhance model tightness. Deterministic, stochastic, capacitated, and backordering/lost-sales variants are developed, and a tailored Benders decomposition approach is introduced to solve large-scale instances efficiently. Computational studies show the proposed algorithm to outperform standard mixed-integer programming approaches and provide insights into the value of stochastic modeling for production planning under uncertainty. The third part addresses a real-life, large-scale integrated production scheduling problem in the manufacturing sector. A hybrid machine learning-mixed integer programming framework is developed to identify feasible machine-product assignments and generate optimal schedules that balance machine utilization, minimize changeovers, and satisfy operational constraints. Extensive tests using real production data demonstrate the approach's effectiveness and practical relevance. Together, these studies illustrate how rigorous mathematical modeling, advanced decomposition strategies, and data-driven insights can be integrated to solve high-dimensional optimization problems in logistics and manufacturing. The methodologies developed in this dissertation form a foundation for future research in stochastic optimization, machine learning-enabled decision systems, and large-scale industrial scheduling under uncertainty.
Not All Noises Are Equal: Investigating Auditory Distraction in Emergency Care Using the Tesseract Simulation Platform
Du, David; Lau, Nathan; Ojeifo, Olumide A.; Upthegrove, Tanner; Baber, Adam; Jones, Nathan A.; Parker, Sarah H. (SAGE Publications, 2025-09)
Auditory distractions in clinical environments can impair performance, yet their impact in emergency department (ED) waiting rooms remains understudied. This study investigates how distinct noise types (baby crying, conversations, and equipment alarms) and temporal patterns (continuous vs. intermittent) influence nursing triage performance. Thirty-two ED nurses completed standardized triage tasks within the Tesseract, an immersive audio-visual simulation platform replicating ED waiting room conditions. Preliminary results from 16 participants suggest that the effects of noise depend on both acoustic features and temporal structures. Subjective perceptions of distraction did not consistently align with measured outcomes. This work provides early evidence that auditory distractions influence clinical task execution in complex, task- and context-specific ways, underscoring the need for targeted mitigation strategies and soundscape-aware simulation training.
Comparative Efficacy RCT of 3 Intensive Infant/Toddler Therapies for Unilateral Cerebral Palsy
DeLuca, Stephanie C.; Ramey, Sharon L.; Darragh, Amy R.; Conaway, Mark; Heathcock, Jill C.; Lo, Warren; Gordon, Andrew M.; Trucks, Mary Rebekah; Wallace, Dory; Cabral, Thais Invencao (American Academy of Pediatrics, 2026-02-01)
Objectives: Unilateral cerebral palsy (UCP) can result in lifelong upper extremity (UE) neuromotor impairment. While both constraint-induced movement therapy (CIMT) and bimanual training have demonstrated efficacy for children with UCP, there was limited evidence to inform treatment decision-making in children aged between 6 and 24 months. Thus, we performed a comparative efficacy trial testing 3 high-dose therapist-delivered interventions, 2 CIMT interventions varied by constraint type to bimanual/no-constraint intervention for use in treating this age group of children with UCP.
Patients and Methods: Fifty-eight infants/toddlers with UCP diagnosis, aged 6 to 24 months, were enrolled and randomized. Exclusion criteria were uncontrolled seizures, fragile health, prior CIMT/bimanual therapy, and recent botulinum toxin. Participants were randomly assigned (1:1:1) to 1 of 3 treatments all delivered 3 hours/d and 5 days/wk for 4 weeks: CIMT/full-time cast, CIMT/part-time splint, or bimanual/no constraint. Anonymized assessments at baseline, end of treatment (EoT), and 6 months posttreatment included the Mini–Assisting Hand Assessment (AHA) for bimanual abilities and the Bayley Scales of Infant and Toddler Development, Third Edition (Bayley-III) Fine-Motor (FM) subscale on each UE for FM abilities.
Results: Fifty-three infant/toddlers completed treatment and EoT assessment (mean age, 17.2 months), and 41 completed 6-month assessment. All groups had gains from intervention: Mini-AHA scores (P < .003) and Bayley-III FM/paretic side (P < .002). Bayley-III FM/nonparetic side also improved across groups (P < .001). The CIMT/full-time cast showed larger gains on Bayley-III FM/nonparetic side when compared with bimanual/no constraint (difference, 5.9; 95% CI, 1.2-10.5; P = .015).
Conclusion: The trial confirms comparable benefits from therapist-delivered CIMT and bimanual/no-constraint interventions for infants/toddlers with UCP aged between 6 and 24 months.
Intellectual Property Committee: 2005-2006
(Virginia Tech, 2005-2006)