Digital Commons Network^™

Modeling Sickle Cell Disease Using A Sleep-Pain-Inflammation Cycle, Milan Marsh

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

A Compartmental Model For Annual Bat Migration, Elena D. Wheatley, Rhianna Yates, Leah Glasser, Christopher Hay-Jahans

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Modeling The Impact Of Treatment During An Ongoing Tuberculosis Outbreak, Bach Le, Jude Shive, Erin N. Bodine

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Parameter Estimation And Simulation In Pollution-Induced Asthma Disease Model Using Physics-Informed Neural Networks, Aadi Gannavaram

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Detecting Burned Vegetation Areas By Merging Spectral And Texture Features In A Resnet Deep Learning Architecture, Jiahui Fan, Yunjun Yao, Yajie Li, Xueyi Zhang, Jiquan Chen, Joshua B. Fisher, Xiaotong Zhang, Bo Jiang, Lu Liu, Zijing Xie, Luna Zhang, Fei Qiu

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Timely and accurate detection of burned areas is crucial for assessing fire damage and contributing to ecosystem recovery efforts. In this study, we propose a framework for detecting fire-affected vegetation anomalies on the basis of a ResNet deep learning (DL) algorithm by merging spectral and textural features (ResNet-IST) and the vegetation abnormal spectral texture index (VASTI). To train the ResNet-IST, a vegetation anomaly dataset was constructed on high-resolution 30 m fire-affected remote sensing images selected from the Global Fire Atlas (GFA) to extract the spectral and textural features. We tested the model to detect fire-affected vegetation in ten study areas …

Statistical Challenges And Simulation Results For Pilot Clinical Trials, Weiliang Cen

USF Tampa Graduate Theses and Dissertations

Background: The effect size estimated from a pilot trial is often an inaccurate reflection of the true effect size observed in a large trial, leading to either underestimation or overestimation. Published data suggest that effect sizes from large trials are typically smaller than those reported in their corresponding pilot trials. To address this discrepancy, conservative or discount adjustment methods are widely recommended to modify pilot trial effect sizes when calculating sample sizes, thereby maintaining adequate statistical power. This study aims to assess effect sizes from both pilot and large trials and to evaluate the performance of existing adjustment methods.

Methods: …

Analysis Of An Effective Training Curriculum: Solutions Toincrease Participants' Interest In Training Teachingmaterials, Maulidya Husnul Khatimah, Yoto Yoto

Jurnal Pendidikan Sains

This research is important because it analyzes the curriculum as a primary tool for generating and maintaining participant interest. Curricula that are irrelevant, monotonous, or misaligned with participant needs are often the main causes of low motivation and participation. Furthermore, this research encourages the exploration and implementation of more innovative teaching methods and materials in training curricula. External pressure in the form of demands or instructions, rather than internal motivation, drives most training activities. This can reduce engagement and learning effectiveness. To overcome this, training institutions need to design programs that are relevant, flexible, and able to encourage participants' intrinsic …

Interpretable Machine Learning For Cardiovascular Risk Prediction: Insights From Nhanes Dietary And Health Data, Md Ahiduzzaman, Md Nahid Hasan

Faculty Publications

Background: Cardiovascular diseases (CVD) are one of the leading global causes of death, which requires an accurate early prediction. This study aimed to develop transparent machine learning (ML) models using National Health and Nutrition Examination Survey (NHANES) data from 2017–2023 to predict CVD risk based on dietary and health factors.

Methods: We analyzed data from 12,382 adults (aged 18 and older) from NHANES 2017–2023, including 41 dietary, anthropometric, clinical, and demographic variables. Recursive Feature Elimination (RFE) was used to select an optimal subset of 30 predictors. To address substantial class imbalance in the outcome, we applied the Random Over-Sampling Examples …

Survival Analysis Of Breast Cancer Patients In Texas Using Classical And Machine Learning Methods, Sidketa Fofana, Tamer Oraby, Salique H. Shaham, Everardo Cobos, Manish K. Tripathi

School of Medicine Publications

Background

Breast cancer is considered one of the most common cancers in women worldwide. In this study, we used an 11-year cohort of malignant breast cancer survival data in Texas to investigate the factors that might explain why some breast cancer patients live longer than others.

Methods

We performed standard survival analyses, including generating Kaplan‒Meier survival curves, using the log-rank test, and applying Cox proportional hazards regression to identify the unique features of breast cancer patients and determine the main factors influencing long-term survival. We also conducted a Random Survival Forest analysis for classification and prediction. Finally, we used Mahalanobis …

The State Of Our Streams: A Land Trust's Approach To Monitoring The Health Of Three Headwater Streams, Lauren Mcgrath

Sustainability Research & Practice Seminar Presentations

Lauren McGrath, Director of Watershed Protection Program, Willistown Conservation Trust, presents "The State of Our Streams: a land trust's approach to monitoring the health of three headwater streams."

Computational Data Analysis, Kathryn S. Biles

LSU Master's Theses

Data science has emerged as a cornerstone of innovation, shaping an ever-expanding range

of professional careers. As technology advances and the volume of data expands expo-

nentially, the ability to extract meaningful insights from data has become indispensable

across industries. Far from representing a single career path, data science enables profes-

sionals in nearly every domain to make informed decisions, optimize systems, and drive

innovation. Yet, many high school students and incoming college freshmen have limited

exposure to data science fundamentals or the career opportunities they unlock. This is

the gap that Computational Data Analysis, a high school-level curriculum I …

Circulating Levels Of Insulin-Like Growth Factor I (Igf-I) And Risk Ofmultiple Myeloma: An Observational And Mendelian Randomisation Study, Yolanda Benavente, Sara Hermosa, Nikos Papadimitriou, Alyssa I. Clay-Gilmour Ph.D., Elizabeth E. Brown, Jonathan N. Hofmann, Nathaniel Rothman, Qing Lan, Sonja I. Berndt, Demetrius Albanes, Mark Purdue, Mitchell J. Machiela, Stephen J. Chanock, Parveen Bhatti, Wendy Cozen, Aaron Norman, Susan L. Slager, James R. Cerhan, Vincent Rajkumar, Shaji J. Kumar, Et. Al.

Faculty Publications

Evidence for an association between insulin-like growth factors (IGF) and multiple myeloma (MM) is inconsistent. We examined total IGF-I concentrations and risk of MM by combining baseline serological data among UK Biobank participants (n = 444 187; 732 incident MM) with a two-sample Mendelian randomisation (MR) analysis using identified genetic variants associated with circulating total IGF-I and IGF-binding protein 3 (IGFBP-3) in the InterLymph consortium (2434 MM and their 2567 controls). Finally, additional lymphoid neoplasm (LN) subtypes were included for comparison with the main hypothesis. Circulating IGF-I level was positively associated with MM risk Hazard ratio-HR-per one standard deviation-SD-increase …

Shaping The Soil: A Comparison Of Equine, Bovine, And Ungrazed Hay Fields, Brody Ellis Higgs, Taylor Madison Wynn, Scottie Craig Berry

Scholars Week

Shaping the Soil: A Comparison of Equine, Bovine, and Ungrazed Hay Fields

Brody Higgs, Taylor Wynn, and Scottie Berry

Mentor: Dr. Iin. P. Handayani, PhD.

Hutson School of Agriculture, Murray State University, Murray, Kentucky, USA

ABSTRACT

Kentucky raises grazing species for multiple reasons, including food, recreation, and show. The most common of them are equine and bovine. These animals graze many acres across the state of Kentucky and impact soil properties in their pastures. This study was conducted on three pasturelands across Caldwell and Calloway counties in Kentucky. The pastures consisted of a cow pasture, a horse pasture, and a …

A Remote Sensing Assessment Of Illegal Gold Mining And Its Impact On Forests In Amansie West District, Ghana, Mina Poku Agyemang

Scholars Week

Forest degradation, driven primarily by human activities such as agriculture, urbanization, and mining, leads to biodiversity loss, soil erosion, and increased greenhouse gas emissions. In Ghana, illegal mining, known as ‘galamsey,’ poses significant threats to land and forest resources, damaging ecosystems and affecting public health (Aboka et al., 2018). Despite mining's contribution to Ghana's GDP, the negative impacts of illegal mining may outweigh its economic benefits. Between 2018 and 2023, Ghana lost approximately 5.9% of its forest cover while mining areas expanded by 1,917.6% (Abugre et al., 2025). This alarming situation necessitates an investigation into the changes in land use …

Witnessing A Wounded World: A Theology Of Ecological Trauma, Timothy A. Middleton

Theology

A crucial intervention at the intersection of ecotheology and trauma theology

We are in the midst of a global ecological crisis. At times, the scale of the suffering involved can be hard to fully comprehend. The whole planetary ecosystem feels out of kilter. Meanwhile, trauma theorists, and society at large, have become increasingly aware of the incidence of trauma in a growing variety of contexts. In Witnessing a Wounded World, Timothy Middleton asks what might be gained by viewing ecological suffering through the lens of trauma.

By bringing concepts and methodologies from trauma theology to bear on questions that …

Exploiting Chloride Conservative Tendencies As Contaminant Surrogates In Groundwater Transport Modeling In A Typical Hydrogeological Environment Of Northern New Jersey, Toritseju Oyen, Duke Ophori

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

This study investigates the transport of chloride, a conservative tracer and surrogate for contaminants, in the fractured Brunswick aquifer of northern New Jersey using a dual-porosity MODFLOW-MT3DMS model. Focusing on the First Watchung Mountain region—a microcosm of northern New Jersey’s hydrogeological environment encompassing Montclair State University and adjoining communities, the numerical model simulates groundwater flow and solute transport in a hydrogeologically complex, urbanized setting. Results indicate that chloride migrates through the fractured aquifer via both local flow systems (e.g., Third River) and regional flow systems (Passaic River) within decades. Chloride concentrations exceeded the EPA’s 250 mg/L threshold much faster in …

The Science And Economics Of 3d-Printed Filament Recycling, Michael Domingo, Dane Freund, John Mcswiggin, Adam Meadows

Sustainability Conference

In recent years, 3D printing has grown rapidly, both in homes and commercially. This has led to increased demand for plastic filaments, many of which contribute to plastic waste. This project explores the potential of recycling household plastics into 3D printing filament, promoting sustainability and creating a circular economy. Materials like PLA, PETG, ABS, and polypropylene can be recycled or even composted. Existing research has shown that recycled filaments can maintain comparable tensile strength to their virgin counterparts, depending on the recycling process. Furthermore, implementing circular economy practices for plastics could save billions annually by mitigating pollution and reducing landfill …

Elucidating The Relationship Between Water Quality And Antibiotic Resistance Of Rainwater Microbes Across Western Humboldt County, Theo P. Murphy, Eve Wendley, Justice Laskowski, Tyler Paredes

Humboldt Journal of Microbiology

Limited studies have been conducted regarding the fecal contamination and microbial dispersal through rainwater, with no known studies investigating the potential connection between antibiotic resistant microbes and water quality in rainwater. This study seeks to identify the presence of a correlation between water quality and incidence of antibiotic resistance in rainwater microbes. We hypothesize that there will be a correlation between these two variables. We additionally anticipate a high incidence of fecal contamination across rural and urban collection sites alike, with fecal contamination being more prevalent in rural areas than urban locals. To determine water quality, we measured the concentration …

Building Resilience Against Coastal Climate Risks, San Diego Regional Climate Collaborative, Brenda Castruita, Marius Van Dongen, Brandi Upshaw

San Diego Regional Climate Collaborative

The South Carlsbad Climate Adaptation Project (Project) is an initiative led by the City of Carlsbad (City) designed to address the growing risks of coastal erosion and sea level rise within the city. The Project focuses on a one mile segment of South Carlsbad Boulevard that runs directly along the coast and has experienced decades of coastal erosion, shoreline retreat, and recurring flooding–all of which are expected to intensify due to climate change. In an effort to protect critical infrastructure, natural resources, and public safety, the City has been evaluating the long-term viability of the current roadway and exploring various …

Experts’ Validation Of The Fundamental Cybersecurity Competency Index (Fcci) Using A Commercial Cyber Range Through Human-Generative Artificial Intelligence (Genai) Teaming, Dariusz Witko, Yair Levy, Catherine Neubauer, Greg Simco, Laurie P. Dringus, Melissa Carlton

Journal of Cybersecurity Education, Research and Practice

The increasing volume of cyber threats, combined with a critical shortage of skilled professionals and rising burnout among practitioners, highlights the urgent need for innovative solutions in cybersecurity operations. Generative Artificial Intelligence (GenAI) offers promising potential to augment human analysts in cybersecurity, but its integration requires rigorous validation of the fundamental competencies that enable effective collaboration of human-GenAI teams. This research study employed a mixed-methods research project designed to evaluate human-GenAI teams, emphasizing the role of expert consensus in shaping the experimental assessment of the Fundamental Cybersecurity Competency Index (FCCI) in a commercial cyber range. We engaged 20 Subject Matter …

Security And Privacy Of Wearable And Implantable Medical Devices: A Course-Based Approach To Medical Device Cybersecurity Education, Michelle M. Ramim

Journal of Cybersecurity Education, Research and Practice

As wearable and implantable medical devices become integral to remote patient monitoring and precision medicine, the associated cybersecurity and privacy risks demand urgent attention. These devices are increasingly targeted by cyberattacks, potentially endangering patient safety and data integrity. To address this, we developed an experiential learning course titled Security and Privacy of Wearable and Implantable Medical Devices, designed for advanced undergraduate and graduate students in health and medical fields. The course immerses students in real-world challenges through lectures, labs, and project-based learning, leveraging wearable devices such as FitBit^TM to analyze and interpret real-time personal health data. The curriculum …

Electrochemical Breath Sensors In Medical Diagnostics: Emerging Trends And Future Directions, Natalie E. Strom, Courtney J. Weber, Olja Simoska

Faculty Publications

With the rising prevalence of metabolic diseases, infections, and mental health disorders, there is a growing demand for noninvasive diagnostic tools that enable early detection and continuous health monitoring. In this context, exhaled breath biomarkers provide insight into physiological and pathological processes. Electrochemical breath sensors (EBSs) have emerged as a promising platform for rapid, real-time, and cost-effective disease tracking via the detection of volatile breath biomarkers, such as NH₃, NO, and CO₂. Recent advancements in electrode materials, biological recognition elements, and sensor architectures—spanning nanomaterials, enzymes, aptamers, and molecularly imprinted polymers—have enhanced the analytical performance of EBSs. …

Electrochemical Breath Sensors In Medical Diagnostics: Emerging Trends And Future Directions, Natalie E. Strom, Courtney J. Weber, Olja Simoska

Faculty Publications

With the rising prevalence of metabolic diseases, infections, and mental health disorders, there is a growing demand for noninvasive diagnostic tools that enable early detection and continuous health monitoring. In this context, exhaled breath biomarkers provide insight into physiological and pathological processes. Electrochemical breath sensors (EBSs) have emerged as a promising platform for rapid, real-time, and cost-effective disease tracking via the detection of volatile breath biomarkers, such as NH₃, NO, and CO₂. Recent advancements in electrode materials, biological recognition elements, and sensor architectures—spanning nanomaterials, enzymes, aptamers, and molecularly imprinted polymers—have enhanced the analytical performance of EBSs. …

Practical Real-Time Permanent Magnet Energy Spectrometer Using A Diode Array For Therapeutic Electron Beam Tuning And Quality Assurance, Mason W. Heath

LSU Doctoral Dissertations

Purpose: Develop a practical, real-time permanent magnet electron energy spectrometer and evaluate it for beam tuning and quality assurance (QA) of therapeutic electron beams.

Methods: Aim 1: A 0.55 T permanent magnet was coupled to Sun Nuclear SRS MapCHECK® PC boards, providing two interlaced diode arrays. Detector response, R_meas(z_diode) versus diode position z_diode, was extracted from raw diode array readings, correcting for diode sensitivity and other factors. Using Monte Carlo (MC) computed, monoenergetic detector response functions, a curve-fitting algorithm extracted the energy spectrum, from R_meas(z_diode). The energy spectra for 7-20 …

Validation Of A Risk Score For Cancer-Associated Thrombosis Using Nationwide Ehr Data, Ang Li, Omid Jafari, Barbara D Lam, Jun Y Jiang, Rock Bum Kim, Shengling Ma, Emily Zhou, Joyce W Tiong, Elizabeth C Chiang, Justine Ryu, Christopher I Amos, Jennifer La, Nathanael R Fillmore

Faculty, Staff and Student Publications

Importance: Venous thromboembolism (VTE) is associated with increased mortality and morbidity in patients with cancer. Existing risk prediction models are typically validated within individual sites, a fragmented approach that limits clinical adoption.

Objective: To validate the electronic health record cancer-associated thrombosis (EHR-CAT) score compared with the benchmark Khorana score in a contemporary cohort of patients with cancer across the nation, before and after treatment, excluding those at high risk of bleeding.

Design, setting, and participants: This prognostic study included patients in a nationwide longitudinal EHR database from January 2018 to December 2023 with follow-up continuing to April 2025. Patients with …

Losing Focus In The Age Of Tik Tok: Clinical Evidence For Policy Action On Social Media Use, Megan Conefrey, Robert Griffin

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Tracking Livestock Heart Rate & Location Using Long-Range Radio Networks. An Immediate Solution For Farms Without Reliable Wi-Fi, Dermott Harkin, Martin Bradley

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Voices Matter: Tackling Accentism In Ireland. A Study Addressing Accent-Based Discrimination Awareness In Education, Sadhbh Reddington, Victoria Graham, Holly Jordan, Mairead Moriarty

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Supporting Single Parents: How Loneliness And Self-Stigma Can Impact Single Parents And Their Quality Of Life, Alana Powell, David Mothersill

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Income Inequality And Attitudes Towards Immigrants – How Increased Inequality Drives Division, Niamh Anderson, Vincent O'Sullivan

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.