Digital Commons Network^™

From Recognition To Action: Advancing Nutrition Care In Irish Healthcare, Aoife Gillane, Sarah Donovan, Lisa Ryan

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

The Future Of Metabolic Health: A Needle-Free Alternative For Blood Sugar Monitoring, Conor Cleary, Martin Bradley, Christopher Crosson, John Wade

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Transforming Plastic For A Sustainable Planet: Next-Generation Materials That Biodegrade Naturally, Kristof Racz, Clement Higginbotham

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

The Dock Beetle: Reducing Costs And Pesticides In Irish Agriculture, Bianca Araujo, Daniel P. Fitzpatrick

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Ireland’S Energy Transition: Unlocking The Potential Of Offshore Renewables, Caoimhe O'Hare, Madjid Karimirad, Gautam Baruah

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Implementation Of The Nature Restoration Law In The Eu - Pros, Cons And Impossibilities, Emma Mcdonagh, Liam Sunner

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

From Conflict To Connection: Educators Leading The Shift Towards Restorative Practices (Rp) In Deis Primary Schools, Ellen Slattery, Clara Hoyne

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Bridging The Gap From Preschool To Primary: From Policy To Practice, Aimee O'Connor, Cóilín O’ Braonáin

SURE Journal: Science Undergraduate Research Experience Journal

No abstract provided.

Problems In Extremal Graph Theory And Spectral Graph Theory, Fareeha Jamal

Dissertations

Spectral graph theory is a subfield of algebraic graph theory that studies the matrices associated with graphs. It lives at the nexus of Linear Algebra and Combinatorics. Many intriguing results in the domains of Matrix Theory and Combinatorics have come from studying the eigenvalues of graph matrices; in fact, several open problems in both areas have been resolved. Beyond its theoretical appeal, spectral graph theory has found meaningful applications in theoretical chemistry, particularly in the mathematical classification of chemical graphs. These classifications underpin quantitative structure–property relationships (QSPRs), facilitating the prediction of physicochemical properties such as enthalpy of vaporization, molar refractivity, …

Mathematical Analysis Of Toxicants And Diseases Impact On A Prey-Predator System With Control Interventions, Nuru Yazidi Juma, Thadei Damas Sagamiko, James Philbert Mpele

Tanzania Journal of Science

This study developed a generic prey-predator mathematical model incorporating logistic growth for prey and a Holling Type I functional response for predator consumption. Prey-predator interactions form the foundation of ecological balance, but in recent decades these systems have been increasingly threatened by toxicants and infectious diseases. The combined effect of these challenges can lead to severe population declines, biodiversity loss, and ecosystem instability, making their study important for conservation and environmental management. The model includes the effects of diseases and toxicants on prey and toxicants only on predators, and explores optimal control strategies to mitigate these threats. Without considering time …

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 …

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 …

Use Of Modified Z-Domain Peptides To Specifically Label The Constant Region Of Immunoglobulin G And Vegf, Madeline Allen

Department of Chemistry: Dissertations, Theses, and Student Research

Antibodies are increasingly being used in medicinal therapies due to their ability to specifically bind to a target antigen. This fundamental behavior of antibodies has been used as a key component in drug development to address common problems with traditional drug molecules such as off-targeting, fast drug clearance, and low efficacy. This thesis provides some background into how antibodies can be used as potential treatments for a few diseases. Chapter 1 begins with an overview of the human immune system, and the role antibodies play within it. Then, the variety of ways in which antibodies can be used as medicinal …

(Si15-121) Analyzing Seitr Tuberculosis Transmission Model Using Caputo–Fabrizio Fractional Derivative With Diverse Contact Rates, S. S. Sumaiya Banu, T. Gunasekar, S. Manikandan, Kamalendra Kumar, M. Suba

Applications and Applied Mathematics: An International Journal (AAM)

In the modern age, tuberculosis remains a pressing global health concern. Our study introduces and evaluates the SEITR pandemic TB transmission model, dividing the population into five compartments to explore distinct characteristics relevant to our investigation. Additionally, we delve into the application of fractional calculus. Through the Laplace transform method, we derive series solutions for all compartments, ensuring their existence and uniqueness. We also investigate the reproduction number of the tuberculosis epidemic model, examining how varying contact rates impact disease spread. We apply the predictor-corrector method for the Caputo-Fabrizio fractional derivative to verify the accuracy of our approach. This accurately …

Chemistry And Biochemistry Affiliated Publications: Snapshot Of The Research Publications 2019-2024., Jeremy J. Smith, Lutishoor Salisbury

University Libraries Faculty Publications and Presentations

This report highlights the chemistry and biochemistry faculty publications for the period 2019-2024. It includes tables identifying the types of publications, the characteristics of the authors, inter-departmental and external cooperation, summary of the citations of the publications, and the JCR ranking of the journals in which they published.

Art Forms: Born Out Of Necessity, Urmi Duttagupta

Publications and Research

This collection of artworks expresses the artist’s profound passion for mathematics and life’s complex balance. As a female mathematician, she uses artistic expression and intricate patterns to evoke mathematical beauty and feminine strength, celebrating the presence and resilience of women in mathematics.

Data-Driven Optimization And Parameter Estimation For A Metric Graph Epidemic Model With Applications To Covid-19 Spread In Poland: A Real-World Example Of Optimization For A Challenging Rosenbrock-Type Objective Function, Hannah Kravitz, Christina Duron, Brittani Nieves, Moysey Brio

Mathematics and Statistics Faculty Publications and Presentations

In this paper, we apply data-driven optimization to estimate key parameters in a metric graph-based epidemiological model, with the aim of analyzing the effect of road networks on the geographic spread of epidemics. As a case study, we fit our model to data from the COVID-19 pandemic in Poland during 2021. Our dataset integrates county-level daily case reports, national census information, and traffic flow studies. This framework allows us to examine the relative contribution of specific travel routes over time and infer unobserved transmission patterns in the presence of incomplete or unreliable case reporting. The optimization problem that arises from …

Dynamics And Optimal Intervention Strategies In A Shigellosis Transmission Model, Mehmet Gümüs, Shewafera Wondimagegnhu Teklu, Kemal Türk

Mathematical Modelling and Numerical Simulation with Applications

This research explores how water treatment contributes to limiting the transmission of Shigellosis, an infection caused by bacteria from the Shigella genus. A mathematical framework is formulated to evaluate the influence of protective strategies and water purification on the spread of the disease. To confirm the model's biological relevance, its well-posedness is investigated. The basic reproduction number $(\mathfrak{R}_0)$, a critical indicator of disease behavior, is derived using the matrix operator method. Findings indicate that if $\mathfrak{R}_01$, the infection persists, with the endemic equilibrium exhibiting local asymptotic stability. A comprehensive cost-effectiveness analysis reveals that combining environmental protection with water treatment represents …

Edge Percolation Centrality: A New Measure To Quantify The Influence Of Edges During Percolation In Networks, Christina Durón, Hannah Kravitz, Moysey Brio

Mathematics and Statistics Faculty Publications and Presentations

Numerous centrality measures exist to quantify the influence of edges within a network, with edge betweenness being one of the more well-known measures. However, such measures are inadequate in network percolation scenarios (e.g., the transmission of a disease over a transportation network of highways) as they fail to consider the changing percolation states of edges over time. This paper addresses this limitation by extending percolation centrality, a measure originally developed to evaluate the influence of vertices during a percolation process (i.e., a dynamic spread of a contagion) in the network, to the edge level. The proposed measure, edge percolation centrality, …

Investigating Potential Alzheimer's Disease Therapies Through An Agent-Based Model Of Impaired Microglia Metabolismmodeling Impaired Microglia Metabolism, Cheyenne Ty, Abigail Penland, John Gerving, Martin Mendoza-Ceja, Megan Pratt, Kamila Larripa

Spora: A Journal of Biomathematics

Alzheimer’s disease is the leading cause of dementia globally and is marked by amyloid-β plaque accumulation, decreased brain pH, disrupted metabolism, and increased permeability of the blood-brain barrier. Microglia, the resident immune cells of the central nervous system, are essential for maintaining brain homeostasis and are critically involved in the progression of AD. While microglia can initiate protective immune responses to injury and disease, dysregulated microglial metabolism may contribute to the exacerbation of Alzheimer's pathology. To investigate potential therapeutic strategies, we developed an agent-based model simulating the effects of exercise and metabolic enhancement on dysfunctional microglia. Our findings suggest that …

Health On The Rocks: Geohealth In Kentucky, Rachel L. Washburn

Special Publication--KGS

Geohealth bridges the earth and life sciences, revealing how Kentucky’s unique geology directly shapes public health risks, clinical outcomes, and opportunities for innovation. This factsheet highlights the critical intersections between geologic processes and human health across the Commonwealth—from landslides, floods, and tornadoes to radon, mine drainage, and microbial contamination. It outlines how natural and anthropogenic forces influence respiratory illness, cancer, trauma, and infectious disease, and how bedrock and weather extremes define local exposure pathways. Beyond risk, it also showcases Kentucky’s leadership in developing geoscience-informed health solutions: bioremediation, microbial drug discovery, and geologic-health monitoring networks that strengthen preparedness and resilience. Understanding …

Advancing U.S. Competitiveness In Agentic Gen Ai: A Strategic Framework For Interoperability And Governance, Satyadhar Joshi

Harrisburg University Other Works

Abstract : The rapid evolution of artificial intelligence has given rise to agentic AI systems—autonomous entities capable of perceiving their environment, making decisions, and executing actions with minimal human intervention. This work provides a systematic analysis of agentic AI frameworks, governance models, and implementation strategies. Drawing on a comprehensive review of the literature, we examine the current state of agentic AI technologies, highlight key challenges in governance, security, and ethical oversight, and compare architectural frameworks for responsible deployment. Our results, illustrated through detailed framework comparisons and governance analyses, demonstrate that while agentic AI holds transformative potential across multiple sectors, notable …

Design And Development Of A Standalone Digital Holographic Microscope Employing Phase-Driven Reconstruction And Classification For Biomedical Imaging And Optical Diagnostics, Charlotte Kyeremah

Graduate Doctoral Dissertations

Access to advanced biomedical imaging technologies remains a significant challenge in resource-limited settings, especially for early disease detection and monitoring of diseases such as malaria, HIV, and other blood-borne diseases. Although point-of-care (POC) devices have gained popularity in global health, many rely on antibody-based tests, lateral flow strips, or optical readouts that often lack quantitative capabilities, sensitivity to early infections, or versatility in different diagnostic targets. In addition, these systems are typically dependent on disposable reagents or manual interpretation, which limits their effectiveness in remote areas. Digital Holographic Microscopy (DHM) presents a promising alternative as a label-free imaging method capable …

Hurricane Katrina Archive: Faculty Publications Bibliography 2005-2009, Lsu Health Sciences Center - New Orleans Libraries, Sharon Duffy, Matthew Folse

LSUHSC Hurricane Katrina Archive: Bibliographies

This bibliography includes 91 articles about Hurricane Katrina written by authors affiliated with LSU Health – New Orleans between January 2005 and December 2009.

Spatial Patterns In Electronic Health Record Data-Based Predictive Modeling: A Case Study Of Prenatal Care And Preeclampsia, Abigail Lewis

McKelvey School of Engineering Graduate Student Theses & Dissertations

The electronic health record (EHR) documents interactions between patients and healthcare systems and is widely used for secondary research on health outcomes due to broad adoption. While EHR data support efficient clinical informatics research, they are subject to biases stemming from healthcare seeking behavior, health system attributes, and individual or environmental characteristics. Place-based characteristics, in particular, strongly influence when and how patients access care and shape health outcomes. These biases in EHR data can affect predictive modeling pipelines which leverage them, contributing to variation in model performance across groups. In healthcare, where predictive models are increasingly used to guide care, …

Faster, Higher, Stronger: Modern Methodologies For The Calibration, Exploration, And Utilization Of Agent-Based Models, David O'Gara

McKelvey School of Engineering Graduate Student Theses & Dissertations

Increases in computing power and availability have led to the widespread use and adoption of agent-based models (ABMs) in the physical, biological, and social sciences. At their core, ABMs represent a novel paradigm for scientific inquiry: their micro-level specification allows for the simulation of the individual components of a system which yields a deeper understanding of dynamic processes such as contagion and adaptive decision-making when used appropriately. However, several hurdles exist when attempting to use ABMs to their full potential. In this thesis, we will explore and address several challenges in designing and utilizing ABMs, with a focus on applying …

Bridging Scales In Epidemic Modeling From Individuals To Networks And Ecosystems, Saiprasasd Vr

Theses and Dissertations

Epidemics have shaped the trajectory of human history, repeatedly exposing vulnerabilities in healthcare systems and influencing socio-economic dynamics on a global scale. The COVID-19 pandemic, in particular, underscored the pressing need for flexible and responsive modeling framework capable of adapting to dynamic and evolving epidemic scenarios. Motivated by these challenges, this thesis explores the development of innovative epidemic models that integrate classical mathematical modeling techniques, network-based frameworks, and modern data-driven approaches. Each chapter addresses a distinct dimension of epidemic spread, from vaccination dynamics and community coupling to ecological complexity and adaptive human behavior, culminating in a model-free paradigm suitable for …

Hot Spring Associated Infectious Diseases In The Great Basin And Southwest, Matthew Bentz

UNLV Theses, Dissertations, Professional Papers, and Capstones

Like all bodies of freshwater, natural hot springs can harbor pathogenic microorganisms that carry the threat of infectious disease. The unique chemistry, increased temperature, and popularity for bathing may alter the risk profile of hot springs compared to other natural bodies of water. Despite this risk, the role of hot springs as a reservoir for infectious diseases remains understudied, particularly within the context of regional public health. Nevada and the Great Basin/Southwest have increasingly promoted hot springs for the purposes of tourism, and they share a strong link to the cultural heritage of the region. The unknown risk profile and …

An Evidence-Based Intervention To Increase Trypanosoma Cruzi, A Neglected Parasitic Infection, Diagnosis In Rural And Moderate-Size-City Us Clinics, M K. Lynn, Hunter M. Boehme, Jeffrey Hall, Patrick Kent, Alain H. Litwin, Quang H. Pham, Melissa Nolan Ph.D., Mph, Prisma Chagas Team

Faculty Publications

Background

Chagas disease is a chronic, insidious parasitic infection (Trypanosoma cruzi) that slowly develops to irreversible organomegaly over several decades. The disease is traditionally acquired in endemic Latin American countries during childhood; < 1% of foreign-born adult residents in the United States have been diagnosed or treated with this potentially fatal disease. Low physician knowledge is a primary factor leading to misdiagnosis.

Methods

Starting in April 2022, a 4-part T cruzi clinical education intervention began, which included (i) 2 grand rounds presentations to >100 internal medicine providers; (ii) implementation of a “clinical Chagas champions program” incorporating 14 key clinical staff at varying departments and administrative levels educated on their specific role related to T cruzi screening, diagnosis confirmation, clinical management, and medical billing; ( …

Changes In Mental Health Care Utilisation Before And During The Covid-19 Pandemic Among People Living With Hiv In The Usa: A Retrospective Cohort Study Using The All Of Us Dataset, Atena Pasha, Shan Qiao, Jiajia Zhang Ph.D., Ruilie Cai, Buwei He, Xueying Yang, Chen Liang Ph.D., Sharon Weissman, Xiaoming Li Ph.D.

Faculty Publications

Introduction Despite the profound impact of the COVID-19 pandemic on people living with HIV (PLWH) mental health, large-scale, real-world data on mental healthcare utilisation and associated factors among PLWH remain limited. This study explores mental healthcare utilisation and associated factors among PLWH during the COVID-19 pandemic.

Methods Using a retrospective cohort design, we identified and included 4575 PLWH through computational phenotyping based on relevant Observational Medical Outcomes Partnership Common Data Model concept sets from the All of Us programme between March 2018 and March 2022. Mental healthcare utilisation was measured using the yearly count of mental healthcare visits and compared …