Improving Research Software Engineering in Mathematics

Research Software Engineering is critical to modern mathematical research, enabling the creation, maintenance, and dissemination of computational tools that bridge theory and practice. However, the field faces systemic challenges, including insufficient funding, lack of institutional recognition, and gaps in training and infrastructure. This thesis investigates these challenges through two approaches: (1) a comparative survey study focused on mathematicians and (2) hands-on contributions to an open-source research software project. The Improving Research Software Engineering in Mathematics survey, conducted from September 2024 to January 2025, adapts the survey framework developed by Carver et al. in A survey of the state of the practice for research software in the United States to analyze research software engineering practices among mathematicians. The thesis details contributions to 1r-Base, a community-driven database of topological counterexamples. Software contributions include a dynamic citation button and an External Markdown feature, both of which were developed through collaborative workflows adhering to continuous integration and continuous deployment (CI/CD) practices. These contributions emphasize the importance of community development efforts in sustaining research software

Edge AI-Based Cognitive Engagement Detection and Multimodal Exploration

Edge AI models for real-time cognitive engagement detection will have major effects on clinical neuroscience, human-computer interface, and education. This work provides a lightweight deep learning model for frame-by- frame video classification and develops an edge device. The proposed edge device delivers low latency, energy-efficient processing, and high temporal resolution, achieving 29 frames per second (FPS) with each frame taking 30 milliseconds, all without reliance on cloud services. Our investigation also introduces a Multimodal Fusion Framework designed to integrate physiological signals and behavioral data into the engagement classification process, in contrast to conventional systems that rely solely on video-based categorization. Using synchronized EEG, ECG, and face video data from 17 student volunteers engaged in controlled cognitive activities, the study examined. While EEG alpha and beta frequency bands gave important new perspectives on cognitive workload, ECG-derived heart rate variability (HRV) acted as an indirect predictor of cognitive stress. Reaction times and task accuracy among behavioral measures provided outside confirmation of cognitive states. This work investigates the strengths and limits of each modality by means of independent and integrated data streams, therefore stressing the possibilities of improving classification accuracy and contextual knowledge of engagement levels. In contrast to conventional systems that mostly rely on video-based categorization, this study provides a Multimodal Fusion Framework that integrates behavioral and physiological information into the engagement classification process. Without requiring cloud infrastructure, the proposed edge device demonstrates low latency, energy-efficient computation, and excellent temporal resolution.https://jagworks.southalabama.edu/southalabama-shgrf-posters/1010/thumbnail.jp

Digital Marketing and Communications for Non-Profit Organizations on the Gulf Coast

Non-profit organizations play a vital role in the social and economic conditions of South Alabama and the surrounding areas. From providing essential social services to fostering cultural enrichment to supplying disaster relief efforts, these organizations equip society to care for our communities and encourage our economy. In an increasingly digital world, digital marketing and communication strategies give non-profit organizations the ability to communicate their mission, engage with stakeholders, and mobilize resources. This study aims to identify the current digital marketing strategies for Gulf Coast non-profit organizations.https://jagworks.southalabama.edu/honors_college_posters/1035/thumbnail.jp

Autonomous Control of a Hybrid Unmanned Aerial Towed System on a Moving Platform

With tethered rotor drones being more popular for aerial surveillance, moving platforms for tethered drones are being researched. However, these systems require constant power to the rotor drones for stabilization. With this difficulty in power consumption, a hybrid drone solution is presented. The hybrid drone is similar to an airplane, with quadcopter motors attached for stabilization and thrust when not moving. The controller for the hybrid drone was tested and verified in simulation. The simulation of the system was built in Fortran and consists of a driver, a tether, and a hybrid drone. The driver was modeled after a generic pick-up truck that moves in a straight line, and the tether is a viscoelastic tether made from a bead model. The controller for the hybrid drone was then created using three separate controllers. These controllers consisted of a quadcopter controller, a plane controller, and a blend controller. Testing and verifying of the hybrid controller were done using different test cases, such as not moving, moving forward, braking, varied speed, bumpy roads, and winds. The controller and simulation were found to be stable in most cases, allowing the hybrid drone solution to be possible in all but the winds model

False Narratives, Real Consequences

Social media is an increasingly significant tool in modern cyber warfare, capable of rapidly shaping public opinion. The swift dissemination of information complicates efforts to distinguish fact from fiction [1]. During public health crises, healthcare professionals use these platforms to share updates, yet their credible content must contend with false or deliberately misleading narratives [2]. This environment creates an opportunity for cyberattacks through social media influence campaigns [3]. While disinformation\u27s role in political interference has been widely studied, its potential to destabilize healthcare remains largely unexplored. Prior research primarily focuses on how vaccine misinformation affects the general public [4]. This study instead proposes an investigation into the mechanisms, impacts, and broader consequences of disinformation as a method of cyberattack targeting healthcare professionals. Utilizing a three-paper dissertation model, this research will assess disinformation at multiple levels. The first study will analyze social media narratives from the COVID-19 pandemic using natural language processing and sentiment analysis to identify coordinated disinformation campaigns. The second will examine how exposure to misleading health narratives influences nurses’ perceptions, professional judgment, and susceptibility to burnout. The third will simulate a large-scale disinformation attack on a hospital system, modeling its potential to disrupt trust and operational stability. Drawing from prior disinformation campaigns, particularly those during U.S. elections [5][6][7], this study explores whether similar tactics have been or could be used against healthcare. The findings will contribute to cybersecurity, health informatics, and public health preparedness by identifying vulnerabilities that would help safeguard healthcare infrastructure from future information warfare threats. REFERENCES [1] Hussain, M., & Soomro, T. R. (2023). Social Media: An Exploratory Study of Information, Misinformation, Disinformation, and Malinformation. Applied Computer Systems, 28(1), 13–20. [2] Di Domenico, G., Nunan, D., & Pitardi, V. (2022). Marketplaces of Misinformation: A Study of How Vaccine Misinformation Is Legitimized on Social Media. Journal of Public Policy & Marketing, 41(4), 319–335.https://jagworks.southalabama.edu/southalabama-shgrf-posters/1028/thumbnail.jp

Computational Study of the Separation of Aromatic/Aliphatic Mixtures using Ionic Liquids

Aromatic hydrocarbons are a valuable product in many industrial processes. Separating aromatic compounds from solutions of mixed hydrocarbons is notoriously expensive and inefficient, particularly in solutions with less than 20 wt% aromatics. Ionic liquids (ILs) are salts that remain liquid at room temperature and exhibit extremely promising properties such as negligible vapor pressure and high thermal stability. The tunable nature of ILs, arising from the interchangeability of ions, is a promising attribute for the use of ILs in difficult separation processes. This study involves the separation and adsorption between aromatic and aliphatic compounds with various ILs to study the selectivity and loading capacity of four ILs. The Gibbs Ensemble is implemented in the continuous fractional component method (CFC) to simulate and facilitate the absorption of heptane and/or toluene into the various ILs. Four novel perarylphosphonium cations are paired with the bistriflimide anion to form the ILs of interest. These are used to simulate the separation of heptane and toluene at varying mole fractions. Results will show a selectivity favoring toluene as well as give some insight to the distribution ratio of the compounds and the loading capacity of each IL.https://jagworks.southalabama.edu/southalabama-shgrf-posters/1001/thumbnail.jp

Reframing Rudeness: Exploring Positive Reappraisal as a Pathway from Customer Incivility to Self-Efficacy

Customer incivility is a persistent challenge for front-line employees (FLEs), often leading to adverse workplace outcomes. This research examined whether positive reappraisal can transform incivility into a source of growth. Grounded in Social Cognitive Theory, the research explored how positive reappraisal mediates the relationship between customer incivility and two key forms of self-efficacy—regulatory emotional and workplace social—ultimately influencing job satisfaction. The moderating roles of perceived organizational support and trait mindfulness were also investigated. A cross-sectional survey of 296 FLEs was analyzed using partial least squares structural equation modeling (PLS-SEM). More specifically, the results confirmed customer incivility positively predicts positive reappraisal. Additionally, customer incivility indirectly enhances self-efficacy and job satisfaction via positive reappraisal. Mediation analysis further reveals positive reappraisal serves as a competitive mediator, counteracting the direct detrimental effects of incivility. Surprisingly, FLEs\u27 perceived organizational support weakened the positive reappraisal pathway, suggesting highly supported employees may rely less on individual coping strategies. These findings challenge the prevailing view of customer incivility as a purely negative antecedent, uncovering its potential to foster resilience. Organizations could support employees by incorporating cognitive reframing techniques into training and balancing support systems to promote adaptive coping. This research offers a more nuanced perspective on workplace stressors and their potential to drive positive outcomes

Low-Power Differential Privacy Memory for Edge Devices

As the use of personal electronics have increased, new and improved services and applications have become the cornerstone of modern times. To improve these services, companies and institutions collect data to inform new features that are needed to support their services. Differential Privacy is a methodology to ensure that this collected data does not leak any individual’s personal information while still allowing data collectors to see trends in data. In this work, Differential Privacy is implemented at a hardware-level by injecting noise in memory. To design this memory, the failure rate of SRAM cells at different voltage levels was evaluated and used to determine several device parameters.https://jagworks.southalabama.edu/southalabama-shgrf-posters/1016/thumbnail.jp

Decoding Bacterial Resilience: sRNAs and Sigma Factors in Stress Adaptation and Persistence of Salmonella

Small RNAs (sRNAs) are noncoding RNA molecules in bacteria that function primarily to regulate gene expression, including those associated with stress. The Borchert Lab has identified 173 sRNAs and \u3e 500 sRNAs that are responsive to desiccation and carbon starvation (c-starvation), respectively. Prokaryotic transcription involves an RNA Polymerase (RNAP) that transcribes DNA into RNA. RNAP involves sigma factors, which recognize promoters for the initial steps of RNA synthesis. The Borchert Lab has determined that there are significant overlaps between sRNAs expressed in cells subjected to both short-term durations and long-term durations of carbon starvation. Salmonella enterica serovars can have outbreaks associated with dehydrated foods. Understanding the mechanism that allows for S. enterica survival under stress allows for building strategies in combating the spread of this pathogen and preventing recurrent Salmonella outbreaks. We hypothesize that in S. enterica serovars, the bacteria express sigma factor RpoS during short term stress while switching over to sigma factor RpoE during long term stress. This switch between the sigma factors function to regulate the stress response in S. enterica. RNAP sigma subunit selection and the expression of distinct sRNAs drive the decision between active stress resistance and formation of persisters. Our findings suggest that sigma factor expression of RpoS in the Salmonella strain SL1344 is dependent on the duration of stress