Physical Sciences and Mathematics Commons^™

Large Language Models As Information Providers For Appropriate Antimicrobial Use: Computational Text Analysis And Expert-Rated Comparison Of Chatgpt, Claude And Gemini, Marcello Di Pumpo, Maria Rosaria Gualano, Danilo Buonsenso, Francesca Raffaelli, Daniele Donà, Vittorio Maio, Patrizia Laurenti, Walter Ricciardi, Leonardo Villani

College of Population Health Faculty Papers

OBJECTIVES: Antimicrobial resistance is a critical public health threat. Large language models (LLMs) show great capability for providing health information. This study evaluates the effectiveness of LLMs in providing information on antibiotic use and infection management.

METHODS: Using a mixed-method approach, responses to healthcare expert-designed scenarios from ChatGPT 3.5, ChatGPT 4.0, Claude 2.0 and Gemini 1.0, in both Italian and English, were analysed. Computational text analysis assessed readability, lexical diversity and sentiment, while content quality was assessed by three experts via DISCERN tool.

RESULTS: 16 scenarios were developed. A total of 101 outputs and 5454 Likert-scale (1-5) scores were obtained …

Turning Waste Into Fertilizer: Aloe Vera Leaf Shavings Improve Plant Growth And Support Soil Fertility In Organic Systems, Isaiah Edward Jaramillo, Carine Cocco, James Jihoon Kang, Chu-Lin Cheng, Engil Pereira

School of Earth, Environmental, & Marine Sciences Faculty Publications

The Aloe vera industry discards large amounts of outer leaf tissue (“shavings”), creating an opportunity to repurpose this byproduct as a sustainable fertilizer. This study evaluated whether aloe shavings can serve as a plant-based alternative to compost in organic Aloe vera production. A field trial in the Lower Rio Grande Valley of Texas tested three treatments: aloe shavings (applied to supply 39 kg N ha−1), organic compost (39 kg N ha−1), and a non-fertilized control. Laboratory incubations further assessed nitrogen mineralization and microbial respiration. Aloe shavings significantly enhanced vegetative growth: leaf number increased from 5.7 to 12.3 leaves per plant …

Clark Tailings Consolidated Waste Management Area (Ctcwma) Site Investigation Draft Data Summary Report 2024 Surface Water, Groundwater, And Soil Characterization, Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Microclimatic Conditions In Shulgan-Tash Cave (Southern Ural, Russia): Implications For The Preservation Of Eastern Europe’S Largest Paleolithic Art Collection, Olga Chervyatsova, Rayan Akhmedyanovb, Nailya Saifullina, Ludmila Kuzmina, Mihael Kotov, Yuri Dublyansky

International Journal of Speleology

This study presents the results of a long-term investigation of the microclimatic conditions in Shulgan-Tash Cave (Southern Urals, Russia), which hosts the largest assemblage of Upper Paleolithic paintings (ca. 16.3–19.6 ka) in Eastern Europe. The cave exhibits two distinct seasonal ventilation regimes – winter and summer – differentially influence its two levels of galleries. In the Lower Level, which contains 83% of the images, near-atmospheric CO₂ concentrations persist year-round, and temperature variations associated with seasonal infiltration events are minimal (1.0–1.3°C). By contrast, the Upper Level, including the decorated Hall of Paintings, is affected by downdrafts of CO₂-rich …

Confinement-Induced Resonances For The Creation Of Quasi-One-Dimensional Ultracold Gases Of Alkali–Alkaline-Earth Dimers, Lorenzo Oghittu, Premjith Thekkeppatt, Nirav P. Mehta, Seth T. Rittenhouse, Klaasjan Van Druten, Florian Schreck, Arghavan Safavi-Naini

Physics and Astronomy Faculty Research

We theoretically investigate the role of confinement-induced resonances (CIRs) in low-dimensional ultracold atomic mixtures in the formation of weakly bound dimers. To this end, we examine the scattering properties of a binary atomic mixture confined by a quasi-one-dimensional (quasi-1D) potential. In this regime, the interspecies two-body interaction is modeled as an effective 1D zero-range pseudopotential, with a coupling strength g1D derived as a function of the three-dimensional scattering length a. This framework enables the study of CIRs in harmonically confined systems, with particular attention paid to the case of mismatched transverse trapping frequencies of the two atomic species. Finally, we …

Cv: Teresa Bixby (Chemistry), Teresa Bixby

Chemistry Department Faculty Curricula Vitae

No abstract provided.

Electron Yields Of Lunar Regolith Simulant Layers, Christopher Vega, Matthew Robertson, Thomas Keaton, Heather Allen, Jr Dennison

Journal Articles

The charging of bulk lunar regolith has been recognized since the Apollo era as an immediate and critical issue facing our return to the moon. Accurate electron yield (EY) measurements of bulk highly insulating granular materials—which largely determine how such particles charge through interactions with space environments—are lacking due to many experimental complexities that have led to a critical knowledge gap. Such knowledge is essential for addressing fundamental science and myriad important lunar applications and simulations related to lunar dust and regolith electrostatic charging. The few prior EY studies of lunar dust were limited due to severe charging effects and …

Re: Comments On The Draft Final Butte Mine Waste Repository Geotechnical Investigation Work Plan (Dated September 23, 2025), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Cloud Seeding: Enhancing Winter Snowpack To Bolster Utah's Water Supply, Lily Lambert, Kendall Becker, Binod Pokharel, Scott Hotaling

All Current Publications

As Utah’s climate warms, the state is working to combat the decline in winter snowpack caused by rising temperatures. Cloud seeding is a safe technology that, under the right conditions, can boost snowfall. In this fact sheet, we describe what cloud seeding is, where it is currently used in Utah, and the safety measures and management practices that ensure its responsible use.

Re: Butte Priority Soil Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp): Bres No. 91 – Robert Emmett Dump, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Butte Priority Soil Operable Unit (Bpsou) Final Bres No.94 – Rialto Dump Reclamation Improvement (Ri) Field Sampling Plan (Fsp), Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Eutrophication, Hope Northagen, Sarah Erwin, Ethan Gilliam

All Current Publications

Eutrophication refers to the ecological state of a water body after excessive nutrient pollution. The external introduction of nutrients (primarily nitrogen and phosphorus) accelerates the growth and reproduction of plants, algae, and microbes. This fact sheet explains where eutrophication comes from, its impacts, how it is treated, and what you can do to help restore and protect our lakes, rivers, and oceans.

Barriers To Machine Learning Adoption In Regulated Electric Utilities, Donald R. Shiflet Jr.

USF Tampa Graduate Theses and Dissertations

Machine learning (ML) technologies have the potential to revolutionize regulated electric utilities by improving operational efficiency, enabling predictive maintenance, and optimizing energy management. Despite these advantages, the adoption of ML in this sector lags other industries due to technical, organizational, and regulatory barriers. This research, grounded in the Technology-Organization-Environment (TOE) framework, explores these barriers to uncover actionable solutions for integration. The study identifies key challenges, including explainability, cybersecurity, workforce resistance, and regulatory ambiguity to ML adoption in electric utilities. Utilizing an exploratory qualitative methodology, this approach integrates insights from the literature and industry interviews to rank barriers by frequency, severity, …

Needs Analysis Of Interactive Learning Media For Teachingheat Transfer In Physics: Students’ And Teachers’Perspectives, Rizki Eka Shintya, Ika Mustika Sari, Ida Kaniawati

Jurnal Pendidikan Sains

Heat transfer material in physics is known to be abstract. This study specifically analyzes the conceptual difficulties, and visualization needs specific to this material, which is different from the analysis of physics needs in general. This analysis does not only look for the need for traditional media but explicitly looks for the need for interactive media (simulation, animation, virtual laboratory). Therefore, this study aims to identify the need for interactive learning media in physics education, specifically in the teaching of heat transfer, from the perspective of students and teachers in West Java, Indonesia. Using a quantitative descriptive survey, data were …

Efficacy Of Teaching At The Right Level Approach Combined With The Problem-Based Learning Model On Science Learning Outcomes At Middle School, Heri Syahputra Azhar Panjaitan, Ryan Dwi Puspita

Jurnal Pendidikan Sains

This research seeks to evaluate the efficacy of the Teaching at the Right Level (TaRL) strategy in conjunction with the Problem-Based Learning (PBL) model on the scientific learning outcomes of eighth-grade students at middle school Islam Terpadu Khairul Imam. This research addresses the inadequate scientific problem-solving abilities and science learning outcomes of Indonesian students, necessitating a more interactive and individualized instructional technique. The methodology used is a quasi-experimental design with a nonequivalent control group. The sample included two purposively chosen eighth-grade classes: one experimental class (n=25) underwent the TaRL–PBL intervention, whereas the control class (n=25) simply used the lecture approach. …

Tableau Part Ii - October 2025, Rubab Shahzad

Day Family Research Lab Workshop Series

Part Two of Introduction to Tableau. Learn to make cool visualizations using Tableau. A hands-on opportunity where we will go over calculated fields, hierarchies, unions, dashboards, and stories.

Prior experience with Tableau is recommended

Skin Cancer Image Classification Using Deep Learning With Data Segmentation Technique, Akhilesh Kumar Shrivas, Hema Vastrakar

Karbala International Journal of Modern Science

The human skin is an impressive organ and structural element often impacted by a diverse range of recognized and unknown diseases. Diagnosing disorders that affect the outermost layer of the body is the most uncertain and difficult component in the scientific field. Dermatological diseases are one of the most significant health concerns in the 21st century since their identification is challenging and costly, plagued with challenges and the subjectivity that comes with human interpretation. The main objective of this piece of research work is to develop a robust model for the classification of skin cancer diseases using deep convolution neural …

Second Moment Of Degree Three L-Functions, Sampurna Pal

Doctoral Theses

Let $F$ be a Hecke-Maa\ss\  cusp form for $SL(3,\mathbb{Z})$. In this dissertation, we obtain a non-trivial upper bound of the second moment of $L(F,s)$ in the $t$-aspect: $$ \int_{T}^{2T}|L(F,1/2+it)|^2 dt\ll_{F,\epsilon} T^{3/2-3/32+\epsilon}.$$ Immediate corollaries include improvements over the existing results on the Subconvexity bound for self-dual $GL(3)$ $L$-functions in the $t$-aspect and for self-dual $GL(3)\times GL(2)$ $L$-functions in the $GL(2)$ spectral aspect, the error term in the Rankin-Selberg problem, and the zero density estimate for $GL(3)$ $L$-functions.

Prompt Engineering For Genai In Cybersecurity Incident Response: A Multi-Platform Evaluation Based On Nice Pr-Ir-001, Yuanyuan Liu

Journal of Cybersecurity Education, Research and Practice

This study explores the application of prompt engineering in cybersecurity education, mainly by evaluating the performance of different generative artificial intelligence (GenAI) platforms when performing tasks consistent with the NICE framework role pr-ir-001 - Network Defense Incident Responder. The study employed structured prompts designed for a medical technology environment compliant with HIPAA and NIST SP 800-53, while the tasks of the three GenAI models (GPT-4, Gemini, and DeepSeek) were to generate event response scenarios. Their outputs will be evaluated from four aspects: accuracy, relevance, clarity and completeness.

The results show that the three models differ in depth and consistency, but …

Arizona’S Experiential Learning Opportunities: Regional Security Operations Centers And Cybersecurity Clinics, Joshua Kipers, Paul Wagner, Robert J. Honomichl

Journal of Cybersecurity Education, Research and Practice

The increasing frequency, sophistication, and economic impact of cybersecurity incidents have intensified the global demand for a skilled cybersecurity workforce. Traditional academic programs often fail to provide the applied experience necessary to prepare graduates for the rapidly evolving threat landscape. This paper examines Arizona’s innovative approaches to experiential cybersecurity education through the establishment of Regional Security Operations Centers (RSOCs) and the Arizona Cybersecurity Clinic. These initiatives integrate Kolb’s Experiential Learning Theory and the NICE Cybersecurity Workforce Framework to align academic preparation with real-world practice. The RSOCs, supported by the Arizona Department of Homeland Security, provide paid student internships focused on …

An Integrated Pcb-Based Heating And Auto-Ranging Platform For Volatile Organic Compound (Voc) Detection Using Carbon Nanotube Based Sensors, Thomas Kalach

USF Tampa Graduate Theses and Dissertations

This thesis presents the development, characterization, and integration of a novel low-cost, high-dynamic-range sensor platform for the detection of volatile organic compounds (VOCs), leveraging the unique electrical properties of carbon nanotube (CNT) thin films. The platform introduces a fully integrated auto-ranging analog front-end circuit capable of real-time resistance measurement spanning over eight orders of magnitude ranging from tens of ohms to hundreds of megaohms, without compromising signal resolution or precision. This was achieved through a digitally controlled, multi-path feedback architecture and controllable current source.

To further enhance sensor performance, the system incorporates a copper trace heater beneath the sensor array, …

Development Of Natural Product Analogs As Therapeutic Agents, Jacob Mara

Theses and Dissertations

Cancer stem cells (CSC) are cancer cells in a tumor mass that may self-renew and develop into various cell types, resulting in a heterogeneous tumor. CSCs have been shown to have a role in many facets of cancer formation, including tumor genesis, proliferation, and metastatic activity. They are also implicated in chemotherapeutic treatment resistance and the recurrence of some malignancies. Based on these capacities, CSCs have been identified as the next target for cancer therapy and control. Salinomycin's potential for therapeutic use based on ongoing research, as well as the synthesis of its derivatives and their biological activity, will also …

10.13.2025 Ored Connect, Liz Williamson

ORED Newsletter

• ORED Small Grants Program RFP
• Mississippi Impact Grants RFP
• Contest to Promote Lab Practices
• Field Fest
• AAAS Membership for Faculty, Staff, and Students 

Draft Final 2024 Residential Metals Abatement Program (Rmap) Baptist Student Union (Former Mckinley School) Soil Remedial Action Construction Completion Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Empirical Methods For Support System Design In Deep Serpentinite Excavations: A Critical Evaluation, Anas Driouch, Redouane Oubah, Abdelaziz Lahmili, Latifa Ouadif

Journal of Sustainable Mining

Underground mining excavations in fragile serpentinite rock masses represent a significant challenge today. The complicated features of these rock formations, especially at great depths, make it difficult to classify them using commonly employed methods. This paper focuses on the application of empirical methods for the classification of serpentinite rock masses and the design of support systems in underground mining excavations. Specifically, it concerns an access tunnel excavated entirely in serpentinite at a depth of 460 m. Geomechanical classification systems indicate that the Tunnelling Quality Index (Q-system) and Rock Mass Rating (RMR) evaluate serpentinites as rock masses of exceptionally poor to …

Bifusenet: A Multimodal Network For Estimating Blood Alcohol Concentration Via Bidirectional Hierarchical Fusion, Abdullah Tariq, Arooba Maqsood, Martin Masek, Syed Zulqarnain Gilani

Research outputs 2022 to 2026

Drunk driving remains a significant public safety challenge, demanding innovative alternatives to conventional methods such as field sobriety tests and breathalysers. Estimating a driver's level of intoxication through facial cues is particularly challenging due to the subtle and person-specific nature of alcohol-induced behaviours. In this paper, we present BiFuseNet, a 3D spatio-temporal multi-modal network designed to classify alcohol impairment levels into three categories: sober, moderate, and severe. Unlike prior approaches that rely on either uni-modal RGB video or hand-crafted facial features, our method exploits complementary physiological cues from RGB and infrared (IR) facial videos. We introduce a Bi-directional Hierarchical Fusion …

Building Resilient And Sustainable Supply Chains: A Distributed Ledger-Based Learning Feedback Loop, Tan Gürpinar, Mehmet A. Gulum

Computer Science Faculty publications

Global supply chains face increasing disruptions from cyber threats, geopolitical instability, extreme weather events, and a range of economic, social, and environmental sustainability challenges. As these disruptions intensify, enhancing Supply Chain Resilience (SCR) has become a strategic priority. This study investigates how Distributed Ledger Technology (DLT) can contribute to SCR by mitigating vulnerabilities and strengthening key capabilities within global supply chains. A qualitative research approach is employed, utilizing expert evaluations to examine DLT’s impact on supply chain vulnerabilities and capabilities. Five workshops were conducted with 25 industry professionals from logistics, IT, procurement, and risk management. Experts examined how DLT could …

Cortenmm: Efficient Memory Management With Strong Correctness Guarantees, Junyang Zhang, Xiangcan Xu, Yonghao Zou, Zhe Tang, Xinyi Wan, Kang Hu, Siyuan Wang, Wenbo Xu, Di Wang, Hao Chen, Lin Huang, Shoumeng Yan, Yuval Tamir, Yingwei Luo, Xiaolin Wang, Huashan Yu, Zhenlin Wang, Hongliang Tian, Diyu Zhou

Michigan Tech Publications

Modern memory management systems suffer from poor performance and subtle concurrency bugs, slowing down applications while introducing security vulnerabilities. We observe that both issues stem from the conventional design of memory management systems with two levels of abstraction: a software-level abstraction (e.g., VMA trees in Linux) and a hardware-level abstraction (typically, page tables). This design increases portability but requires correctly and efficiently synchronizing two drastically different and complex data structures, which is generally challenging.We present CortenMM, a memory management system with a clean-slate design to achieve both high performance and synchronization correctness. Our key insight is that most OSes no …

Improved Streamflow Forecasting Through Swe-Augmented Spatio-Temporal Graph Neural Networks, Akhila Akkala, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Pouya Hosseinzadeh, Ayman Nassar

Computer Science Student Research

Streamflow forecasting in snowmelt-dominated basins is essential for water resource planning, flood mitigation, and ecological sustainability. This study presents a comparative evaluation of statistical, machine learning (Random Forest), and deep learning models (Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Spatio-Temporal Graph Neural Network (STGNN)) using 30 years of data from 20 monitoring stations across the Upper Colorado River Basin (UCRB). We assess the impact of integrating meteorological variables—particularly, the Snow Water Equivalent (SWE)—and spatial dependencies on predictive performance. Among all models, the Spatio-Temporal Graph Neural Network (STGNN) achieved the highest accuracy, with a Nash–Sutcliffe Efficiency (NSE) of 0.84 …

The Effect Of Renewable Energy Consumption, Economic Growth, And Energy Use On Co₂ Emissions In Indonesia: An Ardl Analysis, Raihan Ahmad Mustofa, Mariam Kamila, Rininta Nurrachmi, Syifa Shafnastiara

Jurnal Kebijakan Ekonomi

Abstract This study examines the dynamic relationship between renewable energy consumption, total energy use, economic growth, and CO₂ emissions in Indonesia over the period 1990–2021 using an ARDL approach. The results show a stable long-run relationship with quick adjustment after shocks. In the long run, energy consumption is associated with higher CO₂ emissions, reflecting the continued dominance of fossil fuels. Renewable energy helps reduce emissions in the short term, but its long-term impact remains statistically insignificant. GDP does not show a significant effect, suggesting that meaningful decarbonization will require a more intensive shift in the energy mix.

Keywords: ARDL, renewable …