Digital Commons Network^™

Adverse Childhood Experiences, Positive Childhood Experiences, And Digital Media Use Among Children And Adolescents In The United States, Elizabeth L. Crouch, Emma Boswell, Monique J. Brown Ph.D., Kevin J. Bennett

Publications

No abstract provided.

Myfoodrx: A Personalized Food-As-Medicine Mhealth Application For Food-Insecure Adults With Chronic Conditions, Jay Hiteshkumar Jariwala

USF Tampa Graduate Theses and Dissertations

Food insecurity (FI) remains a persistent public health challenge in the United States, disproportionately affecting underserved populations and contributing to higher rates of chronic conditions such as diabetes, hypertension, and obesity. Traditional Food-as-Medicine programs have emerged as promising interventions, but often follow a generalized, non-personalized approach that limits long-term effectiveness, especially among diverse, high-risk communities. This thesis presents MyFoodRx, a personalized mobile health (mHealth) application designed to address the intersection of food insecurity and chronic disease through tailored nutritional guidance, real-time pantry integration, and adaptive educational content.

Developed through a User-Centered Design (UCD) process, MyFoodRx leverages a modular client–server architecture, …

Towards Mitigation Of Hallucination For Llm-Empowered Agents: Progressive Generalization Bound Exploration And Watchdog Monitor, Siyuan Liu, Wenjing Liu, Zhiwei Xu, Xin Wang, Bo Chen, Tao Li

Michigan Tech Publications

Empowered by large language models (LLMs), intelligent agents have become a popular paradigm for interacting with open environments to facilitate AI deployment. However, hallucinations generated by LLMs - where outputs are inconsistent with facts - pose a significant challenge, undermining the credibility of intelligent agents. Only if hallucinations can be mitigated, the intelligent agents can be used in real-world without any catastrophic risk. Therefore, effective detection and mitigation of hallucinations are crucial to ensure the dependability of agents. Unfortunately, the related approaches either depend on white-box access to LLMs or fail to accurately identify hallucinations. To address the challenge posed …

Inferred Global Dense Residue Transition Graphs From Primary Structure Sequences Enable Protein Interaction Prediction Via Directed Graph Convolutional Neural Networks, Islam A. Ebeid, Haoteng Tang, Pengfei Gu

Computer Science Faculty Publications

Introduction: Accurate prediction of protein-protein interactions (PPIs) is crucial for understanding cellular functions and advancing the development of drugs. While existing in-silico methods leverage direct sequence embeddings from Protein Language Models (PLMs) or apply Graph Neural Networks (GNNs) to 3D protein structures, the main focus of this study is to investigate less computationally intensive alternatives. This work introduces a novel framework for the downstream task of PPI prediction via link prediction.

Methods: We introduce a two-stage graph representation learning framework, ProtGram-DirectGCN. First, we developed ProtGram, a novel approach that models a protein's primary structure as a hierarchy of …

Where Have You Been? Backtracking Microplastic To Its Source Using The Biomolecular Composition Of The Ecocorona, Amanda L. Dawson, Utpal Bose, Sophia Escobar-Correas, Kuok Yap, David J. Craik, Cassandra L. Pegg

Research outputs 2022 to 2026

Microplastics are a diffuse contaminant with various global sources, pathways, and sinks. This study aimed to backtrack microplastics across environments using metaproteomic and eDNA metabarcoding information stored within the ecocorona. Pristine polyamide (PA) fibers, polyethylene terephthalate (PET) fibers and fragments, and PET and PA preincubated in bovine serum albumin (BSA) were deployed into a tank housing Penaeus monodon to develop an ecocorona. Upon collection, BSA was detected within the ecocorona, along with P. monodon proteins, using mass spectrometry. BSA preincubation influenced the diversity and abundance of ecocorona proteins with pristine microplastics having more significantly enriched proteins. Most ecocorona proteins reflected …

An Empirical Investigation Into The Effect Of Brain Drain “Japa Syndrome” On Agile Practitioners Developing Healthcare Information Systems Software In Nigeria, Yazidu Buba Salihu, Julian M. Bass, Gloria E. Iyawa

Communications of the IIMA

Within the software engineering context, agile approaches encourage customer collaboration, iterative development, and flexibility. However, the mass exodus of highly skilled professionals, known as the “brain drain” or "Japa Syndrome," has emerged as a significant challenge, especially in Nigeria. This phenomenon has particularly impacted agile software development practitioners by undermining project continuity, knowledge transfer, and team dynamics. This study empirically examines the effect of brain drain, “Japa Syndrome,” on agile practitioners developing healthcare information systems software in Nigeria. It employed a qualitative, multi-method approach to gather empirical data from 13 agile practitioners in Nigeria’s healthcare information systems sector. The study …

Interdisciplinary Beef - Forage Management Demonstrations, G D. Lacefield, W R. Burris, E D. Miksch, M Rasnake

IGC Proceedings (1977-2023)

An interdisciplinary project, designated as Comprehensive Cow-Calf Management Demonstrations, was initiated by a term of extension specialists to demonstrate recommended management practices for cow-calf producers. The team consisted of extension specialists in beef cattle, agronomy and veterinary science. Cooperators for comprehensive on-farm demonstrations were nominated by county extension agents for agriculture and local veterinary practitioners. Selected cooperators were using a minimum of recommended practices but exhibited a willingness to make suggested changes. Farms were inventoried initially for cattle number and condition, soil capability and fertility, and existing facilities. Farm plans were then developed that would permit utilization of available resources …

Impact Of Information Security Awareness Training On Knowledge, Attitude, And Behavior: A K-12 Case Study, Michael S. Robbins, Christopher Robbins

Journal of Cybersecurity Education, Research and Practice

Abstract— Information security breaches remain a serious threat across all sectors, often exploiting human factors rather than technical flaws. This study examines how a structured Information Security Awareness (ISA) training program influences employees’ knowledge of security policies, attitudes towards those policies, and self-reported security behaviors within a K-12 educational environment. A quantitative pre-test/post-test design was employed with 201 staff members (administrators, teachers, and support personnel) in a public school district. Participants completed the Human Aspects of Information Security Questionnaire (HAIS-Q) before and after undergoing an interactive cybersecurity training program. Statistical analysis revealed a significant improvement in information security knowledge, attitudes, …

Multisource Information Fusion Method For Human Gait Perception, Guiliang Chen, Guowei Liu, Yongchao Li, Chao Cai, Zihao Li, Dong Yang

Journal of System Simulation

Abstract: In response to the insufficient gait perception capability during lower limb exoskeleton assistance, a human lower limb gait phase optimization classification model was proposed. A wireless transmission gait information collection system was designed for collecting the required gait phase feature information. Human joint angles were accurately calculated by fusing acceleration and angular velocity information using extended Kalman filtering. Additionally, kernel principal component analysis was applied to reduce dimensionality in conjunction with plantar pressure data. The LSSVM algorithm was employed to classify gait data, and the PSO algorithm was utilized to find the optimal classification parameters. Experimental results demonstrate that …

10.20.2025 Ored Connect, Liz Williamson

ORED Newsletter

• OTC Director Candidate Forum
• ORED Small Grants Program RFP

Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang

Journal of System Simulation

Abstract: Existing infection risk assessment methods mostly evaluate infection probability through mathematical models or simulation, but they lack analysis of the relationship between air circulation and individual infection probability. This study proposed a risk prediction model for infectious disease transmission based on indoor air circulation. At the microscopic scale, the space was discretized into grid points. By integrating CFD numerical simulation, the entire process of virus droplet release, transmission, and action was fully simulated. The simulation results show that in an obstacle-free room, the error between the total indoor viral load predicted by the model under windless and low wind …

How Fair Workweek Laws Affect Labor Markets: A New York City Case Study, Joseph Pickens, Aaron Sojourner

Upjohn Institute Policy and Research Briefs

No abstract provided.

Heuristic Approaches For Coordinating Collaborative Heterogeneous Robotic Systems In Harvesting Automation With Size Constraints, Hyeseon Lee, Jung Yun Bae, Abhishek Patil, Myoungkuk Park, Vinh Nguyen

Michigan Tech Publications

Multi-agent coordination with task allocation, routing, and scheduling presents critical challenges when deploying heterogeneous robotic systems in constrained agricultural environments. These systems involve real-time sensing during their operations with various sensors, and having quick updates on coordination based on sensed data is critical. This paper addresses the specific requirements of harvesting automation through three heuristic approaches: (1) primal-dual workload balancing inspired by combinatorial optimization techniques, (2) greedy task assignment with iterative local optimization, and (3) LLM-based constraint processing through prompt engineering. Our agricultural application scenario incorporates robot size constraints for navigating narrow crop rows while optimizing task completion time. The …

Quantifying Single, Compound And Cascading Climate Extremes: Implications For Agricultural Resilience In California, Shahryar Fazli, Wenzhao Li, Rejoice Thomas, Surendra Maharjan, Mohammad Sina Jahangiri, Andre Daccache, Hesham Morgan, Mohamed Allali, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

As climate change intensifies, extreme weather increasingly threatens California’s Central Valley (CV), a vital agricultural region exposed to rising risks from heatwaves (HW), droughts (DR), and compound extremes. These events disrupt crop productivity and broader processes like water demand, pest dynamics, and soil stability, posing systemic risks. This study examines the spatiotemporal dynamics of HW, coldwaves (CW), DR, excessive rainfall (ER), and their compound (e.g., HWDR) and cascading forms from 1951 to 2025, using NOAA nClimGrid-Daily data. We assessed trends in frequency, intensity, and duration over long-term (1951–2025) and mid-term (1981–2025) periods. Results show increasing HW and DR in the …

Revised Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 37 – Josephine Shaft Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Revised Draft Final 2022 Insufficiently Reclaimed Sites Sampling: Bres No. 37 – Josephine Shaft Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Park Reclamation: Tackling Invasive Species At The Oconee River Greenway In Milledgeville, Ga, Christine Mutiti

Academic Affairs

This project focused on the ecological restoration of a kudzu-invaded section of the Oconee River Greenway while integrating high-impact learning into the Environmental Methods and Measurements (ENSC 2000) course at GCSU. Kudzu (Pueraria montana), a Category I invasive species, has significantly disrupted native plant communities at the site, making it an ideal setting for applied learning and ecological intervention. The project engaged students in authentic environmental research by involving them in every stage of the process including problem assessment, methodology design, field implementation, data collection, and reflection.

Students initiated the first phase of invasive plant removal using mechanical …

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 …

Topology Across Scales On Heterogeneous Cell Data, M. Torras-Pérez, Iris Yoon , '13, P. Weeratunga, L.-P. Ho, H. M. Byrne, U. Tillmann, H. A. Harrington

Mathematics & Statistics Faculty Works

Multiplexed imaging allows multiple cell types to be simultaneously visualised in a single tissue sample, generating unprecedented amounts of spatially-resolved, biological data. In topological data analysis, persistent homology provides multiscale descriptors of “shape" suitable for the analysis of such spatial data. Here we propose a novel visualisation of persistent homology (PH) and fine-tune vectorisations thereof (exploring the effect of different weightings for persistence images, a prominent vectorisation of PH). These approaches offer new biological interpretations and promising avenues for improving the analysis of complex spatial biological data especially in multiple cell type data. To illustrate our methods, we apply them …

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.

Graphrag-Enabled Local Large Language Model For Gestational Diabetes Mellitus: Development Of A Proof-Of-Concept, Edmund Evangelista, Fathima Ruba, Salman Bukhari, Amril Nazir, Ravishankar Sharma

All Works

Background: Gestational diabetes mellitus (GDM) is a prevalent chronic condition that affects maternal and fetal health outcomes worldwide, increasingly in underserved populations. While generative artificial intelligence (AI) and large language models (LLMs) have shown promise in health care, their application in GDM management remains underexplored. Objective: This study aimed to investigate whether retrieval-augmented generation techniques, when combined with knowledge graphs (KGs), could improve the contextual relevance and accuracy of AI-driven clinical decision support. For this, we developed and validated a graph-based retrieval-augmented generation (GraphRAG)–enabled local LLM as a clinical support tool for GDM management, assessing its performance against open-source LLM …

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 …

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 …

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: 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.

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: 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.

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, …