Digital Commons Network^™

Kinetic Control And Trapping In The Supramolecular Polymerization Of M-Terphenyl Bis-Urea Macrocycles, Sophya V. Garashchuk, Gamage Isuri P. Wijesekera, Isabella G. Rushton, Vaibhavi A. Samant, Fahidat A. Gbadamosi, Dr. Md Faizul Islam, Sophya V. Garashchuk, Prof. Dr. Linda S. Shimizu

Faculty Publications

Herein, we examine pathway complexity in the supramolecular polymerization of a novel m-terphenyl bis-urea macrocycle. Designed to induce kinetically metastable states, the macrocycle‘s concentration-dependent aggregation was studied via 1H NMR and IR spectroscopy in THF and CHCl₃. Temperature-dependent UV-Vis spectroscopy in water/THF revealed a cooperative nucleation-growth mechanism, indicated by a shift in λmax to longer wavelengths upon cooling. Morphological studies using DLS, AFM, and SEM demonstrated fibrous aggregate formation. Thermal hysteresis observed in assembly-disassembly cycles indicated kinetically trapped species, with cooling governed by kinetic control and heating by thermodynamic processes. Deviations in ΔH values during cooling, compared to van′t …

Ultrasonic Spray Coating Of Carbon Fibers For Composite Cathodes In Structural Batteries, Thomas Burns, Liliana Delatte, Gabriela Roman-Martinez, Kyra Glassey, Paul Ziehl, Monirosadat Sadati, Ralph E. White, Paul T. Coman

Faculty Publications

Structural batteries, also known as “massless batteries”, integrate energy storage directly into load-bearing materials, offering a transformative alternative to traditional Li-ion batteries. Unlike conventional systems that serve only as energy storage devices, structural batteries replace passive structural components, reducing overall weight while providing mechanical reinforcement. However, achieving uniform and efficient coatings of active materials on carbon fibers remains a major challenge, limiting their scalability and electrochemical performance. This study investigates ultrasonic spray coating as a precise and scalable technique for fabricating composite cathodes in structural batteries. Using a computer-controlled ultrasonic nozzle, this method ensures uniform deposition with minimal material waste …

Machine Learning For Reactor Power Monitoring With Limited Labeled Data, C. L. Stewart, B. L. Goldblum, R. G. Abbott, L. Appleby, Brett J. Borghetti, V. Hollingshead, J. H. Whetzel

Faculty Publications

Real-time reactor power monitoring is critical for a variety of nuclear applications, spanning safety, security, operations, and maintenance. While machine learning methods have shown promise in monitoring reactor power levels, there is limited research on their efficacy in label-starved environments. The goal of this work is to assess the feasibility of classifying nuclear reactor power level using multisource data in scenarios with limited labels. Data were collected using low-resolution multisensors at four nuclear reactor facilities: two large research reactors and two TRIGA reactors. Within each pair, one reactor dataset served as the source and the other as the target in …

Analyzing Stability Of Estimates At Completion For Long Duration Development Efforts, Bradley Vuu, Jonathan D. Ritschel, Brandon M. Lucas, Edward D. White

Faculty Publications

Defense program managers utilize Earned Value Management (EVM) methodologies to measure, report, and predict the cost and schedule performance of their programs. Previous research conducted by Christensen (1996) and Kim et al. (2019) has shown varied results in the stability of EVM Estimates at Completion (EACs). Stability is defined as a 10% or less deviation from the final EAC at a specified percent completion point of the program. The Christensen (1996) and Kim et al. (2019) studies also noted that program-specific factors, such as phase, can impact the accuracy of EVM metrics. This study builds upon those works by assessing …

Distribution Comparisons Of Eac Cost Growth For Aircraft Work Breakdown Structure Elements, Kyle P. Marquis, Edward D. White, Brandon M. Lucas, Robert D. Fass, Jonathan D. Ritschel, Shawn M. Valentine

Faculty Publications

This article analyzes and investigates the distribution of cost growth of the Estimate at Completion (EAC) for the Work Breakdown Structure (WBS) elements of approximately 60 historical United States Acquisition Category I Research, Development, Test and Evaluation aircraft programs. Using the method of maximum likelihood in conjunction with the Akaike Information Criterion, the authors suggest that both the lognormal and Weibull distributions provide relatively good fit to EAC cost growth, with the lognormal slightly edging out the Weibull. As a summarized finding, the authors present their empirical results for the mean, coefficient of variation (CV), the 15th and 85th percentiles …

The Effects Of Snow Cover On The Dynamic Pressure Of Nuclear Detonation Blast Waves, Adam Card, Andrew W. Decker

Faculty Publications

Blast pressure is the primary military targeting metric for nuclear weapons. Any local conditions that affect blast pressure have the potential for altering nuclear plans, both from defensive and offensive standpoints. Understanding the impact of snow to the blast wave, therefore, provides a benefit both to military planners and to warfighters on the ground, for any operation occurring in arctic environments. No existing data provides a quantitative description of how snow on the ground affects a nuclear detonation blast wave passing over it. Similar blast waves passing over dust have experimentally proven to enhance blast pressure in a localized region.1 …

The Impact Of Solar Angle And Cloud Shadows On 3d Reconstruction Of Rolling Stock Cargo, Carlina M. Ostrand, Adam D. Reiman, Frank W. Ciarallo, Scott L. Nykl, Clark N. Taylor, Joshua F. Krutz

Faculty Publications

Meeting the relentless demand for more efficient air cargo transportation is of paramount importance for commercial needs and military missions. This study describes an experiment to test an innovative approach that harnesses cutting-edge stereoscopic vision technology to create 3D point clouds of rolling stock cargo across varying solar angles and cloud shadow conditions. Virtual cargo point clouds are generated by calibrating and systematically organizing the depth and location points from an RGB-D camera and then reprojecting them in a virtual environment. Measurement accuracy was rigorously tested across six camera positions in various combinations of weather conditions against physical ground truth …

Adapting To Ai: The Evolving Role Of Faculty In Higher Education, Ronald R. Danault

Faculty Publications

Artificial intelligence (AI) is changing the face of higher education, and there are important issues regarding the future of the faculty (Stoerger, 2024). Although there are concerns about the impact of AI on the conventional faculty roles in teaching, assessment, and administration, these tools are now being adopted in learning processes. Rather than dismissing AI as a threat, it acts as a catalyst for reshaping the way faculty members teach with the help of AI and, hence, become facilitators of the learning process (Haoyang & Towne, 2025).

This paper aims to discuss the integration of AI in the higher education …

On Large Language Models In National Security Applications, William N. Caballero, Phillip R. Jenkins

Faculty Publications

The overwhelming success of GPT-4 in early 2023 highlighted the transformative potential of large language models (LLMs) across various sectors, including national security. This article explores the implications of LLM integration within national security contexts, analyzing their potential to revolutionize information processing, decision-making, and operational efficiency. Whereas LLMs offer substantial benefits, such as automating tasks and enhancing data analysis, they also pose significant risks, including hallucinations, data privacy concerns, and vulnerability to adversarial attacks. Through their coupling with decision-theoretic principles and Bayesian reasoning, LLMs can significantly improve decision-making processes within national security organizations. Namely, LLMs can facilitate the transition from …

Racial And Ethnic Inequalities In Actual Vs Nearest Delivery Hospitals, Nansi S. Boghossian, Lucy T. Greenberg, Jeffrey S. Buzas, Joshua Radack, Molly Passarella, Jeannette Rogowski, George R. Saade, Ciaran S. Phibbs, Scott A. Lorch

Faculty Publications

IMPORTANCE Minoritized racial and ethnic groups, such as American Indian and Black individuals, often receive lower quality health care compared with White individuals. There is limited understanding of how these disparities extend to obstetric care, particularly when comparing the quality of care at the actual delivery hospital vs the nearest obstetric hospital based on the birthing individual’s residence. OBJECTIVE To examine inequality in care based on the actual delivery hospital and the closest delivery hospital to the birthing individual’s residential zip code centroid. DESIGN, SETTING, AND PARTICIPANTS This population-based retrospective cohort study used data from 5 states (2008 to 2020 …

Exploring Emotion Classification Of Indonesian Tweets Using Large Scale Transfer Learning Via Indobert, Connor Shaw, Phillip M. Lacasse, Lance E. Champagne

Faculty Publications

Business, political, and other social structures create strong motivation to understand the attitudes, motivations, feelings, and emotions of a population of interest. Social media is a rich source of self-disclosed information by individuals from all walks of life about virtually every domain of the human experience, but the vast quantity of data is impossible to effectively analyze without advanced natural language processing algorithms. This research creates a transfer learning based emotion classification model for Indonesian language Twitter data. Transfer learning consists of two steps: pre-training and fine tuning. Three variations of Indonesian Bidirectional Encoder Representations from Transformers (IndoBERT) are tested …

New Method Of Impact Localization On Plate-Like Structures Using Deep Learning And Wavelet Transform, Asaad Migot, Ahmed Saaudi, Victor Giurgiutiu

Faculty Publications

This paper presents a new methodology for localizing impact events on plate-like structures using a proposed two-dimensional convolutional neural network (CNN) and received impact signals. A network of four piezoelectric wafer active sensors (PWAS) was installed on the tested plate to acquire impact signals. These signals consisted of reflection waves that provided valuable information about impact events. In this methodology, each of the received signals was divided into several equal segments. Then, a wavelet transform (WT)-based time-frequency analysis was used for processing each segment signal. The generated WT diagrams of these segments’ signals were cropped and resized using MATLAB code …

Special Delivery Of Proteinaceous Matter To Deep-Sea Microbes, Yuan Shen, Ronald Benner, Taylor A.B. Broek, Brett D. Walker, Matthew D. Mccarthy

Faculty Publications

Earth’s deep ocean holds a vast reservoir of dissolved organic carbon, traditionally considered old and resistant to microbial degradation. Radiocarbon analyses indicate the hidden occurrence of younger dissolved organic carbon components, assumed to be accessible to deep-sea microorganisms but not yet demonstrated. Using compound-class radiocarbon analysis, molecular characterization, and bioassay experiments, we provide direct evidence for rapid microbial utilization of young, labile, high–molecular weight proteinaceous material in bathypelagic waters. The abundance of labile proteinaceous material diminishes from epipelagic to mesopelagic waters but notably increases in bathypelagic waters, where it exhibits a short turnover time (days) and resembles surface plankton in …

Origin Of Large Effective Phonon Magnetic Moments In Monolayer Mos2, Hussam Mustafa, Cynthia Nnokwe, Gaihua Ye, Mengqi Fang, Swati Chaudhary, Jia An Yan, Kai Wu, Connor J. Cunningham, Colin M. Hemesath, Andrew James Stollenwerk, Paul M. Shand, Eui Hyeok Yang

Faculty Publications

Recent helicity-resolved magneto-Raman spectroscopy measurement demonstrates large effective phonon magnetic moments of ∼2.5 μB in monolayer MoS2, highlighting resonant excitation of bright excitons as a feasible route to activate Γ-point circularly polarized phonons in transition metal dichalcogenides. However, a microscopic picture of this intriguing phenomenon remains lacking. In this work, we show that an orbital transition between the split conduction bands (Δ0 = 4 meV) of MoS2 couples to the doubly degenerate E″ phonon mode (Ω0 = 33 meV), forming two hybridized states. Our phononic and electronic Raman scattering measurements capture these two states: (i) one with predominantly phonon contribution …

Synthesis Of A Series Of Rare-Earth-Based Multi-Anion Chalcogenide Iodides Re3Si2SeXS8-XI (Re = La, Ce, Pr, And Nd) Using The Flux-Assisted Boron-Chalcogen Mixture Method, Gopabandhu Panigrahi, Habiba Binte Kashem, Gregory Morrison, Hans Conrad Zur Loye

Faculty Publications

Single crystals and polycrystalline powders of rare earth mixed chalcogenide iodides La3Si2Se1.21S6.79I, Ce3Si2Se1.39S6.61I, Pr3Si2Se1.22S6.78I, and Nd3Si2Se1.18S6.82I were prepared using the reactive flux-assisted boron-chalcogen mixture (BCM) method at 850 °C. All compounds crystallized in the monoclinic crystal system, space group C2/c (space group number 15). The series adopts the La3Si2O8Cl structure type, containing isolated SiQ4 tetrahedra connected by REQ8 (RE = La, Ce, Pr and Nd) polyhedra; this arrangement creates tunnels that are filled by I atoms. The partial substitution of S by Se was carried out to modulate the optical properties. Phase pure samples and uniform solid solutions were obtained …

The Southern Miss Bower Academic Center: A Recent Academic Library-Athletics Partnership, Blake Denton

Faculty Publications

In 2019, A. Blake Denton published a literature review that identified and described 35 partnerships between academic libraries and athletics programs at higher education institutions in the United States, 20 of which were established for library marketing and development purposes. Recognizing that the literature documenting marketing and development partnerships was dated, he published a study in 2021 that provided updated, more comprehensive accounts for eight participating institutions and an analysis of the evolving nature of their relationships over time. This third article analyzes the partnership at the University of Southern Mississippi that resulted in the relocation of the athletics program’s …

Time-Dependent Shear Flows And Their Applications In Parabolic–Parabolic Patlak–Keller–Segel Systems*, Siming He

Faculty Publications

In this study, we investigate the behavior of three-dimensional parabolic–parabolic Patlak–Keller–Segel systems in the presence of ambient shear flows. Our findings demonstrate that when the total mass of the cell density is below a specific threshold, the solution remains globally regular as long as the flow is sufficiently strong. The primary difficulty in our analysis stems from the fast creation of chemical gradients due to strong shear advection.

Trans-Arg: Predicting Antibiotic Resistance Genes With A Transformer-Based Model And Pretrained Protein Language Model, Mohd Manzar Abbas, Amit Ranjan, Aixin Hou, Supratik Mukhopadhyay

Faculty Publications

Antibiotic resistance presents an emerging challenge to global health by reducing the efficacy of antibiotics administered to treat bacterial infections. Traditional approaches for detecting antibiotic resistance genes (ARGs) involve alignment-based sequence similarity techniques, which are time-consuming and resource-intensive. This signifies the necessity for developing advanced computational methods to detect ARGs early. To address this challenge, we introduce Trans-ARG, a novel multi-head attention transformer-based model designed to predict potential ARGs. Our approach leverages the pretrained ESMFold model to extract embeddings from protein sequences, capturing intricate structural and functional information. Protein sequences labelled as ARG or non-ARG were used as the dataset. …

Kg-Dta: A Knowledge Graph-Based Meta-Path Learning Framework To Predict Drug-Target Binding Affinity, Amit Ranjan, Adam Bess, Md Saiful Islam Sajol, Magesh Rajasekaran, Chris Alvin, Supratik Mukhopadhyay

Faculty Publications

Drug target affinity (DTA) prediction is essential at different phases of drug discovery and virtual drug screening. However, traditional wet lab experiments are time and resource-intensive owing to the complex interactions within the vast biological and chemical spaces. Computational methods have proven their potential to predict DTA, but none have considered the association of drugs and proteins to capture the complex interactions in the biological network between drugs and proteins. To address this, we propose a novel framework leveraging knowledge graph-based meta-path learning (KG-DTA) to enhance DTA prediction. First, we construct a weighted heterogeneous network of drugs and proteins that …

Pre-Exposure Prophylaxis Uptake Among Black/African American Men Who Have Sex With Other Men In Midwestern, United States: A Systematic Review, Oluwafemi Adeagbo, Oluwaseun Abdulganiyu Badru, Prince Addo, Amber Hawkins, Monique J. Brown Ph.D., Mph, Xiaoming Li, Rima Afifi

Faculty Publications

Introduction: Black/African American men who have sex with other men (BMSM) are disproportionately affected by HIV, experience significant disparities in HIV incidence, and face significant barriers to accessing HIV treatment and care services, including pre-exposure prophylaxis (PrEP). Despite evidence of individual and structural barriers to PrEP use in the Midwest, no review has synthesized this finding to have a holistic view of PrEP uptake and barriers. This review examines patterns of, barriers to, and facilitators of PrEP uptake among BMSM in the Midwest, United States (US).

Methods: Five databases (CINAHL Plus, PUBMED, PsycINFO, SCOPUS, and Web of Science) were searched …

Byu Nano-Carbon Physics Lab, Robert Davis Dr., Richard Vanfleet Dr., Felipe Rivera Dr., David Hayes, Nick Allen, Bridget Kemper, Dan Broadbent

Faculty Publications

BYU Nano-Carbon Physics Lab

Started in 2003 by Physics Professors Robert Davis and Richard Vanfleet, who received the BYU Technology Transfer Award in 2024.

Over 81 undergraduate and 21 graduate student projects in the lab have advanced carbon nanotube (CNT) research.

Applications of research from the lab have resulted in over 30 patents, many of which have been licensed to companies for use in the world.

This display showcases highlights of work done in the lab.

Uncertainty Propagation And Sensitivity Analysis For Constrained Optimization Of Nuclear Waste Vitrification, Lagrande Gunnell, Xiaonan Lu, John D. Vienna, Dong-Sang Kim, Brian J. Riley, John Hedengren

Faculty Publications

The vitrification of high-level waste (HLW) by heating a mixture of glass-forming chemicals (GFCs) with the waste can be improved using a constrained optimization problem. This study explores how different uncertainty propagation (UP) methods implemented with the optimization process can affect the glass formulation of nuclear waste glasses. UP is the effort of propagating uncertain inputs through a system to understand and quantify output distributions. Uncertainty intervals are crafted from output distributions to inform the optimization algorithm. UP is often implemented with Monte Carlo (MC) sampling for large nonlinear systems, which can be difficult to implement within a constrained optimization …

Nanostructure Retention To 1100 °C In Soft-Templated Niobium Tungstates Using Dual-Carbon Strategy, Sean C. Wechsler, Alexander Gregg, Coby S. Collins, Santosh Kiran Balijepalli, Morgan Stefik

Faculty Publications

Mesoporous metal oxides (MMOs) have diverse applications including energy storage, catalysis, and separation membranes. Block polymer structure directing agents enable the control of morphology and pore size, however preservation of the nanostructure is often limited to a narrow range of heat treatment temperatures which constrains the tailoring of defect chemistries. High temperature treatments typically lead to collapse of the porous structure as surface area is reduced during crystal growth. Here, using a mesoporous niobium tungstate it is shown that neither in situ carbon generation nor ex situ carbon infiltration alone enable preservation of the ordered mesostructure at temperatures high enough …

Multiwavelength Analysis Of At 2023sva: A Luminous Orphan Afterglow With Evidence For A Structured Jet, Gokul P. Srinivasaragavan, Daniel A. Perley, Anna Y.Q. Ho, Brendan O’Connor, Antonio De Ugarte Postigo, Nikhil Sarin, S. Bradley Cenko, Jesper Sollerman, Lauren Rhodes, David A. Green, Dmitry S. Svinkin, Varun Bhalerao, Gaurav Waratkar, A. J. Nayana, Poonam Chandra, M. Coleman Miller, Daniele B. Malesani, Geoffrey Ryan, Suryansh Srijan, Eric C. Bellm, Eric Burns, David J. Titterington, Maria B. Stone, Josiah Purdum, Tomás Ahumada, G. C. Anupama, Sudhanshu Barway, Michael W. Coughlin, Andrew Drake, Rob Fender, José F. Agüí Fernández, Dmitry D. Frederiks, Stefan Geier

Faculty Publications

We present multiwavelength analysis of ZTF23abelseb (AT 2023sva), an optically discovered fast-fading (∆mr = 2.2 mag in ∆t = 0.74 d), luminous (Mr ∼ −30.0 mag), and red (g − r = 0.50 mag) transient at z = 2.28 with accompanying luminous radio emission. AT 2023sva does not possess a γ -ray burst (GRB) counterpart to an isotropic equivalent energy limit of Eγ,iso < 1.6 × 10⁵² erg, determined through searching γ -ray satellite archives between the last non-detection and first detection, making it the sixth example of an optically discovered afterglow with a redshift measurement and no detected GRB counterpart. We analyse …

A 3d Superposition Approximation For Gamma Knife Dose Calculation, Payton H. Stone, Lam M. Lay, Raymi Ramirez, Daniel Neck, Connel Chu, Joyoni Dey, David Solis

Faculty Publications

Effective dose calculation is essential for optimizing Gamma Knife (GK) stereotactic radiosurgery (SRS) treatment plans. Modern GK systems allow independent sector activation, enabling complex dose distributions per shot. This study presents a dose approximation method designed to account for shot flexibility and generate 3D doses external to GammaPlan. A treatment plan was created with the TMR10 calculation for individual sector activations using a Radiosurgery Head Phantom. The resulting dose arrays established a basis set of sector-specific distributions, which were then referenced by shot parameters from the plan, allowing dose accumulation through superposition. This superposition approximation (SA) was compared to the …

Basil And Swiss Chard: Edible Crops For Use In Floating Treatment Wetlands Improving Agricultural Runoff, Clare Escamilla, David R. Tyrpak, William H.J. Stronsnider, Sarah A. White

Faculty Publications

The plant species established within floating treatment wetlands (FTWs) influence nutrient removal efficiency. To enhance adoption of FTWs by agricultural producers, both economic and ecological benefits from FTWs are needed to increase their use within irrigation retention reservoirs. Thus, we ascertained the feasibility of growing food crops in FTWs by evaluating two edible plant species to determine survivability and nutrient accumulation when grown in FTWs. We quantified plant growth (at saleable/harvestable size), nutrient uptake in root and shoot tissues, and overall nutrient removal efficiency of sweet basil (Ocimum basilicum) and Swiss chard (Beta vulgaris) over a …

Modifiable And Non-Modifiable Risk Factors For Dementia Among Non-Hispanic White And Black Populations Aged 50-64 In The United States, 2006-2016, Jingkai Wei, Matthew C. Lohman Ph.D., Monique J. Brown, James W. Hardin, Chih-Hsiang Yang, Anwar T. Nerchant, Daniela B. Friedman

Faculty Publications

Background and Objectives

Research Design and Methods

Adverse Childhood Experiences, Resilience, And Syringe Services Program Attendance Among Persons Who Inject Drugs In Northeast Georgia, Usa: A Mediation Analysis, Mohammad Rifat Haider, Samantha Clinton, Monique J. Brown, Nathan B. Hansen

Faculty Publications

Background: Syringe services programs (SSP) are evidence-based venues offering harm reduction services to persons who inject drugs (PWID), such as sterile syringes, STI/HIV testing, and linkage to care to decrease drug use-related morbidities and mortalities. Adverse childhood experiences (ACEs) have been linked with reduced resilience, while increased resilience can help PWID attend SSPs. This study examined the potential mediating role of resilience between ACEs and SSP attendance among PWID.

Methods: Data were collected from adult HIV-negative PWID in northeast Georgia, between February-December 2023 (N = 173). Data were collected on SSP attendance (Yes vs. No), resilience, and ACEs. Covariates included …

Geographic Disparities In Unpaid Caregiving, Emma Kathryn Boswell, Monique J. Brown Ph.D., Mph, Lorie Donelle Phd, Rn, Fcan, Nicholas Yell, Taryn Farrell, Peiyin Hung Ph.D., Elizabeth Crouch Ph.D.

Faculty Publications

Purpose: An updated, nationally representative examination of rural–urban differences in the experiences, health, and well-being of caregivers is needed; previous research on this topic uses older data or has limited generalizability. This study examines rural–urban differences in the characteristics, experiences, and health of caregivers. Methods: The 2021–2022 Behavioral Risk Factor Surveillance System (n = 44,274 unpaid caregivers) was used, with rurality defined according to the 2013 National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme. Chi-square tests compared rural–urban differences in these caregivers’ characteristics, including demographic factors, caregiving intensity (e.g., weekly hours spent caregiving, reason for caregiving, past-month ADL/IADL assistance), …

A Standardized Methodology For Evaluating A Digital Badging System [ Data Package ], Benjamin T. Pederson, Mark G. Reith, Ralucca Gera, David S. Long, Edward D. White, Jonathan Zemmer

Faculty Publications

Digital badges, a form of micro-credentials, have grown in popularity over the past decade. However, few standard processes exist to assess the potential of digital badging systems within an organization. This study proposes a generalizable methodology for comparing a badging system with other methods of recording skills and competencies. The experimental design is tested using the military's cyber operations community as the target organization. Finally, mixed-method data from thirty-six participants is analyzed in accordance with the methodology. Based on the results, digital badging systems are perceived to be more valuable and usable than a current method of military talent management. …