All Faculty Deposits

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The "All Faculty Deposits" collection contains works deposited by faculty and appointed delegates from the Elements (EFARs) system. For help with Elements, see Frequently Asked Questions on the Provost's website. In general, items can only be deposited if the item is a scholarly article that is covered by Virginia Tech's open access policy, or the item is openly licensed or in the public domain, or the item is permitted to be posted online under the journal/publisher policy, or the depositor owns the copyright. See Right to Deposit on the VTechWorks Help page. If you have questions email us at vtechworks@vt.edu.

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Fighting fibrin with fibrin: Vancomycin delivery into coagulase-mediated Staphylococcus aureus biofilms via fibrin-based nanoparticle binding
Scull, Grant; Aligwekwe, Adrian; Rey, Ysabel; Koch, Drew; Nellenbach, Kimberly; Sheridan, Ana; Pandit, Sanika; Sollinger, Jennifer; Pierce, Joshua G.; Flick, Matthew J.; Gilbertie, Jessica; Schnabel, Lauren; Brown, Ashley C. (Wiley, 2024-12-01)
Staphylococcus aureus skin and soft tissue infection is a common ailment placing a large burden upon global healthcare infrastructure. These bacteria are growing increasingly recalcitrant to frontline antimicrobial therapeutics like vancomycin due to the prevalence of variant populations such as methicillin-resistant and vancomycin-resistant strains, and there is currently a dearth of novel antibiotics in production. Additionally, S. aureus has the capacity to hijack the host clotting machinery to generate fibrin-based biofilms that confer protection from host antimicrobial mechanisms and antibiotic-based therapies, enabling immune system evasion and significantly reducing antimicrobial efficacy. Emphasis is being placed on improving the effectiveness of therapeutics that are already commercially available through various means. Fibrin-based nanoparticles (FBNs) were developed and found to interact with S. aureus through the clumping factor A (ClfA) fibrinogen receptor and directly integrate into the biofilm matrix. FBNs loaded with antimicrobials such as vancomycin enabled a targeted and sustained release of antibiotic that increased drug contact time and reduced the therapeutic dose required for eradicating the bacteria, both in vitro and in vivo. Collectively, these findings suggest that FBN-antibiotic delivery may be a novel and potent therapeutic tool for the treatment of S. aureus biofilm infections.
Exploring stress and coping skills of medical students: a repeated cross-sectional cohort study
Musick, David W.; Criss, Tracey W.; Rudd, Mariah J.; Mutcheson, R. Brock; Harrington, Daniel P.; Knight, Aubrey L. (2026-02-19)
Objectives: To examine stressors and coping skills as re-flected in the student population at a southeastern United States medical school, including identifying key stressors over time and coping mechanisms used. Methods: Repeated cross-sectional cohort, mixed-methods study conducted between 2016 and 2022 at a four-year med-ical school program. Participants were students from seven classes, with two classes providing data during each of their four years of medical school. A census sampling approach was used, with survey data collected annually from each class across four years. Two surveys were used: the Perceived Stress Scale (PSS) and a modified Coping Orientation to Problems Experienced (COPE) Inventory. Open-text ques-tions captured qualitative responses. Statistical analysis in-cluded Welch’s t-tests, Pearson correlations, and Cronbach’s alpha reliability testing. Qualitative data were examined through inductive thematic analysis. Results: Students reported moderate levels of perceived stress across all four years with fluctuations identified by year of study. There were no statistically significant differences in perceived stress based on student gender; however, qualita-tive findings identified gender differences related to coping strategies. Thematic analysis of qualitative data revealed three recurring categories of stressors: academic workload, residency application and match pressures, and personal life challenges. Stressors shifted from academic in the pre-clini-cal years to career concerns during the clinical years. Conclusions: This study highlights the presence of stress throughout medical school and underscores the importance of adaptive coping strategies and the need for phase-specific interventions to support student well-being. Future research should evaluate the effectiveness of interventions in reducing stress across training stages.
Testing and Microcracking Assessment of Cement-Treated Full-Depth Reclamation
Tong, Bilin; Amarh, Eugene; Diefenderfer, Brian K.; Brand, Alexander S.; Hasibul Hasan, Rahat; Katicha, Samer; Benavides Ruiz, Carolina; Flintsch, Gerardo W. (SAGE Publications, 2026-04-21)
Full-depth reclamation (FDR) has gained increasing recognition as an efficient and cost-effective pavement rehabilitation method by recycling up to 100% of existing materials on-site, with Portland cement-stabilized FDR (FDR–PC) providing enhanced structural integrity. A comprehensive understanding of the mechanical properties of FDR–PC is essential to optimize its design and improve implementation efficiency. This study investigated the mechanical characteristics of FDR–PC, the interrelationships among various tests, and assessed the use of microcracking on constructed accelerated pavement test sections. Tests conducted included compressive strength (CS), flexural strength, elastic modulus, and shrinkage behavior in the laboratory, and deflection testing using a falling weight deflectometer. Four constructed FDR–PC pavement sections, including 3.25% and 5.5% cement content (by weight), both with and without induced microcracking, were built to study the shrinkage concerns observed during practice associated with FDR–PC. In addition, the influence of the microcracking technique was evaluated. The findings include: (1) a correlation factor of 1.46 to account for specimen-size effects in FDR–PC CS testing; (2) a slower loading rate than that specified in ASTM C469 may be more appropriate for characterizing FDR–PC; (3) the American Concrete Institute-based modulus predictions tend to overestimate FDR–PC stiffness; (4) the American Association of State Highway and Transportation Officials model provided the most accurate 7-day modulus of rupture (MoR) estimates; (5) length change test results were influenced by density and cement content; (6) strong correlations were observed among all evaluated mechanical properties; and (7) microcracked mixtures gained stiffness over time, with greater initial reduction in the lower-stiffness FDR–PC and significant stiffness recovery in the high-stiffness FDR–PC.
Historical availability of arable land affects contemporaneous female labor and health outcomes
Jha, Chandan Kumar; Sarangi, Sudipta (PLOS, 2025-08-04)
We contribute to the understanding of mechanisms underlying deep-rooted gender norms by exploring the link between the historical availability of arable land and contemporary gender outcomes. We argue that an abundance of arable land in historical times, i.e., pre-industrial period, required more workers in the fields resulting in norms where women worked and contributed from outside the home as well. Consequently, these societies emphasized women’s health due to its positive effect on their productivity in the fields. Moreover, this economic contribution provided women greater bargaining power in the allocation of intrahousehold resources. The historical availability of arable land for a nation is measured as the weighted mean of the shares of its constituent ethnic groups’ ancestral lands suited to cereal agriculture. Consistent with these arguments, we show that countries with more ancestral arable land have higher female labor force participation rates and better health outcomes, measured by maternal mortality ratio and female-male life expectancy gap. We then illustrate the ‘persistence of norm’ mechanism, by showing that ancestral arable land measured at the district level is positively associated with individual-level attitudes regarding women’s participation in the labor market.
A Comparative Analysis of Transfected and Integrated Auxin Reporter Systems Reveals Sensitivity Advantages in Protoplast Transient Expression Assays
Taylor, Joseph S.; Villaseñor, Eric A.; Rashkovsky, James; Simson, Jaime; Wright, R. Clay; Bargmann, Bastiaan O. R. (2025-02-28)
Reporter-gene activation studies using transient transformation of protoplasts are a powerful tool for the investigation of transcriptional regulation in plants. Here, we perform a comparative analysis of reporter-gene activation sensitivity using an integrated versus a co-transfected reporter-gene construct in Arabidopsis seedling mesophyll protoplasts. The DR5 synthetic auxin-responsive promoter was used to assay the response to auxin treatment and over-expression of activator Auxin Response Factors. We show that sensitivity, as measured by the fold-change in fluorescent-protein reporter-gene expression, is significantly increased by using a co-transfected reporter-gene construct.
An Interpretable Ensemble Heuristic for Principal-Agent Games with Machine Learning
Baswapuram, Avinashh Kumar; Chen, Chen; Cai, Wenbo; Büyüktahtakın, İ. Esra (2026-04)
This paper addresses the challenge of enhancing public policy decision-making by efficiently solving principal-agent models (PAMs) for public-private partnerships, a critical yet computationally demanding problem. We develop a fast, interpretable, and generalizable approach to support policy decisions under these settings. We propose an interpretable ensemble heuristic (EH) that integrates Machine Learning (ML), Operations Research (OR), and Game Theory. First, we reformulate a PAM as a mixed-integer program to improve efficiency. Next, we solve thousands of PAM instances under varying config- urations to generate training data for ensemble tree-based ML models that identify key solution patterns. These patterns form a hierarchical heuristic that provides feasible and interpretable solutions. We demonstrate the EH’s efficacy in managing the Emerald Ash Borer (EAB) infestation, an urgent public-policy threat to U.S. ash trees. Empirical results show that the EH produces high-quality solutions with 1-2% optimality gaps while significantly reducing computational time compared to exact optimization. Furthermore, the heuristic explains predictions using an average of 4.5 of 9 input features, enhancing transparency. Our findings demonstrate that the EH promotes rapid, informed, and accountable policy decisions by balancing interpretability with computational efficiency. Practically, it supports real-time simulations for stakeholders without specialized ML or OR expertise. Methodologically, it demonstrates a robust integration of optimization and machine learning to solve complex policy models. Beyond the EAB application, this approach provides a scalable framework for real-time decision support where transparency and justification are paramount.
Strengthening S-STEM Pathways: Lessons Learned From Cross-Sector Partnerships
Moyer, Stephen; Richardson, Amy Jo; Newcomer, James (2026-04-22)
Synthesizing data products, mathematical models, and observational measurements for lake temperature forecasting
Holthuijzen, Maike; Gramacy, Robert; Carey, Cayelan; Higdon, Dave; Thomas, R. Quinn (2025-06-01)
We present a novel forecasting framework for lake water temperature, which is crucial for managing lake ecosystems and drinking water resources. The General Lake Model (GLM) has been previously used for this purpose, but, similar to many process-based simulation models, it: requires a large number of inputs, many of which are stochastic; presents challenges for uncertainty quantification (UQ); and can exhibit model bias. To address these issues, we propose a Gaussian process (GP) surrogate-based forecasting approach that efficiently handles large, high-dimensional data and accounts for input-dependent variability and systematic GLM bias. We validate the proposed approach and compare it with other forecasting methods, including a climatological model and raw GLM simulations. Our results demonstrate that our bias-corrected GP surrogate (GPBC) can outperform competing approaches in terms of forecast accuracy and UQ up to two weeks into the future.
Deep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers
Büyüktahtakın, İ. Esra (2026-04)
Artificial intelligence (AI) is moving increasingly beyond prediction to support decisions in complex, uncertain, and dynamic environments. This shift creates a natural intersection with operations research and management sciences (OR/MS), which have long offered conceptual and methodological foundations for sequential decision-making under uncertainty. At the same time, recent advances in deep learning, including feedforward neural networks, LSTMs, transformers, and deep reinforcement learning, have expanded the scope of data-driven modeling and opened new possibilities for large-scale decision systems. This tutorial presents an OR/MS-centered perspective on deep learning for sequential decision-making under uncertainty. Its central premise is that deep learning is valuable not as a replacement for optimization, but as a complement to it. Deep learning brings adaptability and scalable approximation, whereas OR/MS provides the structural rigor needed to represent constraints, recourse, and uncertainty. The tutorial reviews key decision-making foundations, connects them to the major neural architectures in modern AI, and discusses leading approaches to integrating learning and optimization. It also highlights emerging impact in domains such as supply chains, healthcare and epidemic response, agriculture, energy, and autonomous operations. More broadly, it frames these developments as part of a wider transition from predictive AI toward decision-capable AI and highlights the role of OR/MS in shaping the next generation of integrated learning–optimization systems.
Automated Flow-Cytometric Readout of Reporter-Gene Activation in Transiently Transformed Protoplasts
Chisholm, Samuel; Taylor, Joseph S.; Wright, R. Clay; Bargmann, Bastiaan O. R. (Springer Nature, 2026-04-01)
Reporter-gene activation studies are essential for dissecting gene regulatory mechanisms, yet traditional whole-plant assays are often low-throughput and difficult to quantify. This chapter presents a streamlined method for analyzing reporter-gene activity using transiently transformed Arabidopsis thaliana mesophyll protoplasts. We describe the use of the pBeaconRFP vector for positive-fluorescent selection, enabling the isolation of successfully transformed cells via flow cytometry and fluorescence-activated cell sorting. Additionally, we introduce the pEvTV Gateway-compatible vector for flexible reporter-gene construct delivery and an automated pipeline for reproducible flow-cytometric data analysis. These methods facilitate rapid, robust, and scalable quantification of transcriptional responses, exemplified by the activation of the DR5 auxin-responsive reporter by gain-of-function Auxin Response Factor expression. The protocols are adaptable to other tissues and species, offering a versatile platform for high-throughput functional genomics.
Mobilizing People to Tackle Tough Challenges: The Structural Dynamics of Adaptive Leadership
Kaufman, Eric K. (2026-04-07)
Guest lecture for Virginia Tech's ALCE 6014 class on "Theories in Non-Formal Learning."
Generative AI as a Cognitive Bridging Partner: Applying Adaption–Innovation Theory to Human–AI Collaboration
Kaufman, Eric K. (2026-04-14)
As organizations increasingly integrate generative artificial intelligence (AI) into leadership, education, coaching, and knowledge work, an important question emerges: How might AI interact with or facilitate cognitive style diversity? Kirton’s (2003) Adaption–Innovation (A–I) theory provides a rigorous framework for understanding differences in problem-solving style, structure preference, cognitive gap, and coping behavior (Fridel, 2023). While AI tools are rapidly entering the workplace, they are rarely examined through the lens of cognitive style (Jablokow, 2026). This roundtable proposes that generative AI can be explored not merely as a productivity tool, but as a structured thought partner that may: support Problem A (task resolution), Influence Problem B (managing cognitive diversity), serve as a potential cognitive bridger, and/or affect coping load across wide KAI gaps. The session aligns directly with the 2026 Symposium theme, KAI at 50: Shaping the Future of Work and Wellbeing, by examining how A–I theory can guide responsible and style-aware AI integration in leadership and teamwork contexts. Rather than positioning AI as a replacement for human cognition, this roundtable situates A–I theory as an interpretive framework for understanding and shaping human–AI collaboration.
Sales promotions and firm valuation in the airline industry
Sharma, Abhinav; Shin, Hoyoung; Santa-María, María Jesús; Nicolau, Juan Luis (Elsevier, 2026-10-01)
While prior research has shown that sales promotions can erode firm value in industries such as hotels or enhance it in restaurants, their impact in the airline industry remains underexplored despite the strategic use of promotions in this sector. Using an event study methodology, we analyze 369 promotional announcements issued by major publicly traded U.S. passenger airlines from 2000 to 2024. The results show that, on average, promotional activities generate positive and significant abnormal returns, suggesting that investors perceive them as strategic components of revenue management rather than as distress signals. Further analysis reveals that volume discounts, in particular, produce significantly higher abnormal returns than other promotion formats, highlighting their superior signaling and behavioral reinforcement mechanisms. These findings contribute to the marketing-finance interface by demonstrating that not all promotions are equally effective in signaling strategic competence to investors, emphasizing the need to account for promotion type in valuation studies.
Mirtazapine Induced Tardive Dyskinesia in an Older Adult
Syed, Amin; Soni, Karishma; Bankole, Azziza; Ratnakaran, Badr (Elsevier, 2025-10)
Mirtazapine, first sold in the United States as Remeron in 1996, is a noradrenergic and specific serotonergic antidepressant FDA-approved for major depressive disorder. Its mechanism of action is referred to as NaSSA due to its alpha-2, 5-HT2, and 5-HT3 antagonism. It has also been used off-label as a third-line treatment option for akathisia, appetite stimulation, and SSRIinduced sexual dysfunction. Incidents of hyperkinetic movement disorders caused by mirtazapine have been reported, but even more infrequent for cases involving tardive dyskinesia (TD). The aim of this presentation is to highlight a case of TD with the use of mirtazapine in an older adult and search for more literature involving mirtazapineinduced tardive dyskinesia.
Land subsidence on Java Island and its contributions to relative sea level change
Ohenhen, Leonard O.; Shirzaei, Manoochehr; Kumar, Praveen; Aditiya, Arif; Tiwari, Ashutosh; Davis, James L.; Kolawole, Folarin; Chaussard, Estelle; Sadhasivam, Nitheshnirmal; Dasho, Oluwaseyi; Zhong, Wen; James, Roselyn H.; Daramola, Samuel; Nicholls, Robert J.; Minderhoud, Philip S. J. (AAAS, 2026-04)
Rising sea levels and land subsidence combine to determine relative sea level (RSL) rise, which is intensifying coastal hazards. However, many densely populated regions lack the observational infrastructure to identify and quantify land subsidence contribution to RSL, hindering effective planning of responses. Here, we used satellite radar observations to generate a high-resolution assessment of land subsidence across Java Island, Indonesia, and evaluate its contribution to 21st-century RSL change. We identify widespread and temporally evolving subsidence with rates ranging from 1 to 15 cm/year in multiple coastal cities. Using machine learning spatiotemporal clustering and ancillary datasets, we attribute the dominant subsidence mechanisms to resource extraction across various geographic and geological settings. We further construct virtual tide gauges at 5-km intervals along the northern coastline, revealing that contemporary subsidence will dominate RSL budgets over the next 25 years along >75% of the coast. These findings underscore the urgent need to integrate subsidence into sea level risk and adaptation assessments in vulnerable coastal regions.
The Credibility Gap: Epistemic Injustice and Neurodivergence in U.S. Legal Contexts
Van Vorce, Hailey; Parti, Katalin; Armour, Chelsea; Edgin, Jamie O. (Sage, 2026-04-10)
Neurodivergent people, including individuals with intellectual and developmental disabilities, continue to face systemic barriers to meaningful and fair participation in the U.S. justice system. Legal standards governing competence, credibility, and culpability remain anchored in expectations of neurotypical communication and reasoning. These expectations do more than shape procedures; they define who is heard, believed, and ultimately brought to justice. This commentary examines forensic ableism, the privileging of neurotypical cognition and communication in legal contexts, through Fricker's framework of epistemic injustice, with a focus on testimonial injustice. In practice, credibility judgments are rooted in neurotypical norms that often devalue neurodivergent testimony. Across competency evaluations, credibility assessments, and capital sentencing decisions, disability-linked patterns of expression and interaction are frequently misinterpreted as signs of unreliability or diminished competence. Addressing forensic ableism requires the redesign of legal processes and broadened disability education to aid in the recognition of diverse cognitive and communication profiles as legitimate ways of knowing and participating. We call for reforms grounded in accessibility, epistemic humility, and collaboration with the neurodivergent community.
Was Sutherland right? An analysis of cryptocurrency offenders
Dearden, Thomas E.; Parti, Katalin; Hawdon, James E. (Emerald, 2026-04-09)
Purpose: The purpose of this study is to examine the applicability of conventional criminological theories to white-collar offenders involved in cryptocurrency-related market manipulation, specifically pump-and-dump schemes. Using Sutherland’s differential association (DA) framework as a theoretical foundation, this research tests whether demographic and theoretical factors – such as self-control, DA, anomie and strain – predict illegal financial behavior in emerging digital markets. Design/methodology/approach: Survey data from a national sample of US adults on the promotion of cryptocurrencies for financial gain were analyzed using t-tests and regression models. Findings: The findings of this study suggest that traditional theories of crime, including DA, anomie and strain, lose predictive significance when demographic variables are considered. High-income, male and younger individuals were most likely to engage in cryptocrime in general. Overall, the results of this study highlight the complexity of white-collar criminality in digital spaces and suggest that financial and demographic factors outweigh conventional criminological theories when predicting involvement in cryptocrime. Originality/value: This paper considers early notions of white-collar crime against modern online financial crimes. The authors addressed the intersection of criminological theory and modern cryptocurrency crime.
“Alexa, I’m home!” intimate surveillance, care, and control in AI-enabled homes and bodies
Brantly, Nataliya D. (Springer, 2026-04)
As artificial intelligence (AI) increasingly mediates everyday life, its expansion into intimate spaces produces new configurations of surveillance that blur the boundaries between care, necessity, and control. While smart home and digital health technologies are widely promoted as tools of safety and well-being, they embed pervasive forms of surveillance that remain underexamined. This paper analyzes how AI-enabled infrastructures govern intimate life through data extraction, algorithmic inference, and corporate control. Drawing on the combined theoretical lenses of surveillance capitalism and biopolitics, it conceptualizes smart homes and digital health systems as sites of marketized biopower, where corporate actors increasingly manage domestic routines and bodily processes. Using a structured critical-comparative analysis of two analytically complementary cases, the Ring Doorbell and the Dexcom continuous glucose monitor (CGM), the study traces how similar data logics operate across distinct domains of intimacy: domestic and bodily. The analysis demonstrates that, despite differences in function, regulation, and perceived necessity, both technologies centralize control under corporate infrastructures. In both cases, care operates as a governance strategy that legitimizes surveillance, normalizes dependency, and reframes autonomy as responsible participation in proprietary systems. The paper concludes by identifying ethical vulnerabilities and calling for AI governance frameworks attentive to intimacy, dependency, and predictive control, rather than privacy protections alone.
Corrosion Behavior of SS316H in Non-isothermal Fluoride Fuel Salt
Lee, Woohyuk; Leong, Amanda; Zhang, Jinsuo (TMS 2026, 2026-03-17)
This study investigates the impact of thermally driven mass transfer on the corrosion behavior of SS316H in molten NaF-BeF₂-UF₄-ZrF₄ salt using a static, non-isothermal system. A vertical temperature gradient from 717 °C (bottom) to 634 °C (top) was established over 6.5 inches without a forced salt circulation. SS316H samples were placed at heights of 0, 3, and 6.5 inches and exposed for 5, 10, and 15 days. Despite the absence of forced convection, significant mass transfer effects were observed. The hottest sample exhibited the greatest chromium depletion, while cooler regions showed less. Metallic deposition occurred on colder samples and in the surrounding salt, indicating directional transport driven by the thermal gradient. These results demonstrate that thermal gradients alone can induce notable corrosion-related mass transfer, challenging the conventional reliance on thermal convection loops. This highlights the need to consider temperature-driven mass transport in evaluating materials for molten salt reactor environments.
Metal redox control in molten NaF-BeF2-UF4-ZrF4 salt for corrosion mitigation
Lee, Woohyuk; Leong, Amanda; Park, Jaewoo; Zhang, Jinsuo (2024-10-11)

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