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.
Communities in VTechWorks
Select a community to browse its collections.
Recent Submissions
How to review an opinion
Reid, J. Leighton; Amaral, Valter; Miles, Rachel A.; Yin, Mengyu; Murphy, Stephen (Wiley, 2026-08)
Peer-reviewed journals publish opinions (e.g., editorials, perspectives) as well as research articles. Opinion articles can be both influential and highly cited. In 2009-2024, Restoration Ecology published 268 opinions (11% of articles), more than four out of five other ecology and conservation journals assessed, and these opinions punched above their weight, garnering 14% of all citations. The most-cited opinions include calls to action, questions about basic tenets, and proposed conceptual syntheses. Such papers raise unique challenges for editors and reviewers, who must evaluate manuscript quality without the typical standard of weighing evidence against conclusions. We posit six questions for reviewers of opinions to consider: (1) Are there unreported conflicts of interest? (2) Is the literature review complete or does it cherry pick citations to support the author’s narrative? (3) Can the reviewer build a compelling counterargument that is not sincerely represented? (4) Are citations appropriate for the statements they are purported to support? (5) Does the opinion cite empirical literature, or just other opinions? (6) Is the author misrepresenting dissenting opinion in order to build themselves up? We hope these questions help reviewers, editors, and other readers weigh support for opinion articles and opinionated statements.
A meta-analysis on the relationships of agency and communion with job strain
Kalmar, Sam L. (Virginia Tech, 2026-08-31)
Strain is a common phenomenon experienced in the workplace that can induce serious negative consequences for those who let it go unchecked. Individual differences are known to play distinct roles in the severity of these outcomes, but the limited exploration of personality traits has yielded inconsistent findings. The current study helps close this knowledge gap by examining the relationship that the personality traits of agency and communion exhibit with job strain outcomes. Approximately 11,496 citations were screened, resulting in 290 unique independent samples, 563 unique effect sizes, and 67,564 participants. A random-effects, individual correction meta-analysis was conducted for both the agency-strain and communion-strain relationships. Continuous moderators were analyzed with mixed-effect meta-regressions and categorial moderators were analyzed with modified asymptotic confidence intervals. Both agency and communion had negative relationships with job strain outcomes, although agency’s relationship was stronger than communion’s. Occupational orientation and sample age did not appear to moderate these relationships. In sum, both agency and communion appear to mitigate job strain, yet agency seems to be more effective overall. Further research is needed to determine if methodological moderators such as strain and personality measure types influence these relationships.
Two-Bubble Cavitation Collapse Near a Rigid Wall: Effects of Size Asymmetry and Temporal Delay
Shashidhar, Prajwal Balaji (Virginia Tech, 2026-09-03)
This study experimentally investigates the collapse dynamics of two laser-induced cavitation bubbles positioned coaxially near a rigid wall, focusing on bubble-size asymmetry and temporal generation delay. Bubble 1 is located closest to the wall, while Bubble 2 is positioned farther from the boundary. High-speed imaging, Schlieren visualization, and synchronized pressure measurements are used to characterize collapse timing, liquid-jet development, pressure-wave propagation, and wall loading. For the bubble-size study, Bubble 2 is maintained at a maximum diameter of 6.10 mm, while Bubble 1 is reduced to 5.50, 5.03, and 4.50 mm at stand-off distances of 0.52, 1.47, and 1.97. An additional highly asymmetric case with a Bubble 1 diameter of approximately 4.10 mm is also examined. The results show that bubble-size asymmetry modifies collapse order, jet direction, vapor merging, collapse topology, and wall pressure. At a stand-off distance of 0.52, the 5.50 and 5.03 mm cases exhibit torus-torus collapse, while the 4.50 mm case exhibits tip-tip collapse. At stand-off distances of 1.47 and 1.97, Bubble 1 undergoes torus collapse and Bubble 2 undergoes tip collapse. Temporal generation delay further modifies the interaction by changing the relative growth and collapse phases of the cavities. The delayed bubble grows to a larger size and restricts the growth of the bubble generated first. When Bubble 2 is delayed, the maximum jet velocity is approximately 62.55 m/s at 10 microseconds, with jet reversal between 50 and 100 microseconds. When Bubble 1 is delayed, the maximum jet velocity reaches approximately 72.23 m/s at 38 microseconds. Overall, bubble size and generation timing strongly influence collapse dynamics, liquid-jet behavior, and wall loading in interacting cavitation bubbles near a rigid boundary.
Engineering next-generation nanovaccines for maternal immunization and piglet protection against porcine epidemic diarrhea virus
Ci, Qiaoqiao; Bian, Yuanzhi; Meng, Xiang-Jin; Zhang, Chenming (Elsevier, 2026-08-10)
Porcine epidemic diarrhea virus (PEDV) remains a major threat to the global swine industry, causing severe disease with high morbidity and mortality in neonatal piglets. Current vaccine strategies are challenged by the need for rapid, local protection at the intestinal mucosa in newborn piglets, and emerging PEDV variants can partially evade vaccine immunity. Nanoplatforms can help address these challenges. Across recent PEDV nanovaccine studies, a consistent theme emerges in that vaccine platform architecture and immunization route are not only delivery parameters but also the primary determinants of neutralizing activity, mucosal IgA induction, and lactogenic immunity transfer. Here in this critical review, we synthesize important design perspectives from the PEDV nanoparticle vaccine literature spanning self-assembling protein scaffolds such as ferritin and mi3, bacteriophage and virus-like particles including AP205 and HBcAg, polymeric carriers such as PLGA, chitosan, and alginate–chitosan microcapsules, and inorganic particles including silica and layered double hydroxide. All PEDV vaccine design considerations are organized into three interlocking layers including antigen choice and display, adjuvant–carrier integration, and maternal–mucosal vaccination strategy. Concurrently, mechanistic patterns are observed across models. For instance, multivalent display strengthens protective breadth, and mucoadhesive or M-cell-targeted approaches improve antigen retention and epithelial transport. Practical vaccine design principles are derived throughout this review to support translation of PEDV nanoparticle vaccines into maternal immunization strategies focused on protecting piglets against PEDV variants.
Computational Approaches to Support Environmental Surveillance of Antimicrobial Resistance
Manthapuri, Vineeth (Virginia Tech, 2026-10-07)
Antimicrobial resistance (AMR) is a major threat to global health. Antibiotic resistance genes (ARGs) are released from wastewater treatment plants and livestock farms, and many are carried on mobile genetic elements (MGEs) that can move between bacteria. AMR in these settings has mostly been studied with culture-based methods, which are slow and capture one organism at a time, or with quantitative PCR, which measures only a few pre-selected genes. Non-target chemical analysis and shotgun metagenomic sequencing measure many more chemicals and genes in each sample but require computational methods for interpretation. This dissertation develops and applies computational approaches to three related problems: predicting the removal of pharmaceuticals and personal care products (PPCPs) during wastewater treatment, characterizing airborne ARGs at livestock farms, and improving the reference database used to identify MGE-associated proteins.
Using a two-step machine-learning framework that combined unsupervised clustering and supervised classification, this work predicted the removal patterns of 149 PPCPs across two full-scale wastewater and water-reuse treatment trains from chemical descriptors. Classification accuracy ranged from 42.5% to 65.2%, depending on the facility and clustering approach. PPCP clusters based on measured removal patterns overlapped by 58–75% with clusters based on physicochemical properties, including Abraham descriptors and logKow. These results show that chemical descriptors can help estimate PPCP removal patterns and prioritize compounds for direct monitoring.
Shotgun metagenomics was applied to air and potential source samples collected over four seasons at a dairy farm and a swine farm with contrasting ventilation designs. Clinically relevant ARGs, including putatively plasmid-associated ARGs, were detected in farm-associated air. Total ARG abundance, Rank I ARG abundance, and human health resistome risk were significantly higher at the mechanically ventilated swine farm than at the naturally ventilated dairy farm. Source-tracking analysis identified pen manure as the dominant inferred contributor to airborne ARGs at the dairy farm (64–81%) and dust as the largest inferred contributor among the sources sampled at the swine farm (53–67%). These findings suggest that manure and dust may be important sources of airborne ARGs at livestock farms.
Because MGE annotation affects interpretation of ARG mobility, this work also addressed limitations of mobileOG-db, a widely used database of MGE-associated proteins developed at Virginia Tech. In the first version of the database, proteins inherited element-class labels from source databases, which could result in conflicting labels, and the database was composed primarily of sequences from cultured bacteria. mobileOG-db was reorganized into five non-overlapping element classes. A protein large language model classifier, mobileOG-ESM2, was then developed by fine-tuning ESM-2 on these classes. The classifier achieved Matthews correlation coefficients of 0.66 and 0.74 on test sets with maximum sequence identities of 40% and 80%, respectively. Applying the classifier to approximately 288 million proteins from public plasmid and viral databases expanded mobileOG-db 2.0 to 67.15 million protein entries.
Together, these studies show how broad chemical analysis and shotgun metagenomics, combined with machine learning and improved reference databases, can provide more information from environmental samples for AMR surveillance. The computational approaches developed in this dissertation complement direct measurement and laboratory validation.