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 40 freely available and openly licensed textbooks are among our most downloaded items.
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Recent Submissions
Developing culinary tourism to support local tourism development and preserving food heritage in Indonesia
Hajarrahmah, Dini; Daniels-Llanos, Melani (Springer Singapore, 2017-10-13)
Meals are always part of the traveling experience. Indonesia’s tourism is blooming and developing the culinary tourism market. As the visitor encounters food every day, can a visitor experience the local culture and place through savoring the local dishes? This paper will study the opportunities in Indonesia in developing the culinary tourism as managed by local people. The discussion in this paper will put a focus on the potency of culinary tourism to support local economies and industries and ways to preserve them.
Validation of a Commercial ELISA Kit for Non-Invasive Measurement of Biologically Relevant Changes in Equine Cortisol Concentrations
Share, Elizabeth R.; Mastellar, Sara L.; Suagee-Bedore, Jessica K.; Eastridge, Maurice L. (MDPI, 2024-10-01)
The measurement of fecal cortisol/corticosterone metabolites (FCMs) is often used to quantify the stress response. The sampling method is relatively non-invasive, reduces concern for elevation of cortisol from the sampling method, and has been shown to measure cortisol more consistently without the daily diurnal rhythm observed in blood. Commercial ELISA (enzyme-linked immunoassay) kits offer benefits over previously validated immunoassay methods but lack validation. The objective of this study was to evaluate a commercial ELISA kit (Arbor AssaysTM DetectX® Cortisol ELISA kit, K003-H1, Ann Arbor, MI, USA) and provide analytical and biologic validation of equine fecal and plasma samples. Horses (4 male, 4 female, mean ± SD: 4 ± 5 yr) were transported for 15 min with limited physical and visual contact via a livestock trailer. Blood and fecal samples were collected pre- and post-transportation. Parallelism, accuracy, and precision tests were used to analytically validate this kit. Data were analyzed using PROC MIXED in SAS 9.4. Plasma cortisol concentrations increased in response to trailering (254.5 ± 26.4 nmol/L, 0 min post-transportation) compared to pre-transportation (142.8 ± 26.4 nmol/L). FCM concentrations increased 24 h post-trailering (10.8 ± 1.7 ng/g) when compared to pre-transportation (7.4 ± 1.7 ng/g). These data support that changes in FCMs can be observed 24 h post-stressor. In conclusion, the Arbor AssaysTM DetectX® Cortisol ELISA kit is a reliable, economic option for the measurement of biologically relevant changes in cortisol in equine plasma and FCMs.
In-Motion, Non-Contact Detection of Ties and Ballasts on Railroad Tracks
Mirzaei, S. Morteza; Radmehr, Ahmad; Holton, Carvel; Ahmadian, Mehdi (MDPI, 2024-09-30)
This study aims to develop a robust and efficient system to identify ties and ballasts in motion using a variety of non-contact sensors mounted on a robotic rail cart. The sensors include distance LiDAR sensors and inductive proximity sensors for ferrous materials to collect data while traversing railroad tracks. Many existing tie/ballast health monitoring devices cannot be mounted on Hyrail vehicles for in-motion inspection due to their inability to filter out unwanted targets (i.e., ties or ballasts). The system studied here addresses that limitation by exploring several approaches based on distance LiDAR sensors. The first approach is based on calculating the running standard deviation of the measured distance from LiDAR sensors to tie or ballast surfaces. The second approach uses machine learning (ML) methods that combine two primary algorithms (Logistic Regression and Decision Tree) and three preprocessing methods (six models in total). The results indicate that the optimal configuration for non-contact, in-motion differentiation of ties and ballasts is integrating two distance LiDAR sensors with a Decision Tree model. This configuration provides rapid, accurate, and robust tie/ballast differentiation. The study also facilitates further sensor and inspection research and development in railroad track maintenance.
Breaks in the Air: The Birth of Rap Radio in New York City [Book review]
Harrison, Anthony Kwame (University of California Press, 2024-03)
A book review of: John Klaess. Breaks in the Air: The Birth of Rap Radio in New York City. Durham, NC: Duke University Press, 2022. 232 pages.
Exploring the Electronic Structure of Strongly Correlated Molecular Systems using Tensor Product Selected Configuration Interaction
Braunscheidel, Nicole Mary (Virginia Tech, 2024-10-14)
The field of theoretical chemistry has provided undeniably useful insights about molecular systems that otherwise, through experiment, would not be obtainable. We are constantly developing new and improved methods to fill in the gaps about how various factors including the electronic structure can affect the chemistry seen experimentally. The goal of most quantum chemistry methods is to develop a method that is widely applicable, has low computational costs, but with as much accuracy as possible. Some of the most challenging systems in our field include those that are considered strongly correlated. Strong correlation is usually referring to the need for a large number of configurations to properly model the chemistry. These systems can not be solved exactly, thus various approximations must be made. A set of methods that take advantage of truncating only the unimportant configurations to solve these challenging systems are selected configuration interaction methods. Even though these selected CI methods can often provide accurate results, their general application is limited by memory bottlenecks. In 2020, our group developed the Tensor Product Selected Configuration Interaction (TPSCI) method to overcome these memory bottlenecks. We take advantage of the local character of these strongly correlated systems by doing a change of basis into tensor products, then do a selected CI algorithm in that basis.
In this dissertation, we discuss how we have extended TPSCI to compute excited states. We first test on a set of polycyclic aromatic hydrocarbons that were previously studied with TPSCI. We find very high accuracy and dimension reduction as compared to state of the art selected CI approaches. We then validate TPSCI's ability to study the electronic structure involved in the singlet fission process in tetracene tetramer with extending analysis using a Bloch effective Hamiltonian. This effective Hamiltonian allows for intuitive analysis of the singlet fission process. We also show how accurate and interpretable TPSCI can be on an open-shell biradical transition bimetallic complex, in addition to, hexabenzocoronene that is not straightforward clustering due to the conjugated benzene rings.
To alleviate the previous system size limitations, we recently implemented a Restricted Active Space Configuration Interaction as a local solver for clusters. We present novel results of using this new solver on a tetracene dimer. We comment on specific coupling strengths and show the electronic dynamics of our TPSCI effective Hamiltonian which support a CT-mediated mechanism for the tetracene dimer singlet fission.