Digital Commons Network^™

Men’S Hockey Looks To Snap Losing Streak Against Merrimack, Aiden Szymanski

Digital Edition

No abstract provided.

Using Artificial Intelligence To Mitigate Bottlenecks In Last-Mile Logistics: A Developing Country Perspective, Marvel S. Ogah, Comfort Ademola, Gregory Asiegbu

International Journal of Applied Management and Technology

The digital revolution of the logistic value chain has improved critical aspects of the global supply chain, especially in the aspect of last-mile logistics (LML). Bottlenecks, however, such as delays in deliveries, increased lead times, pollution, poor cost management, and tracking issues, among several others, plague the logistics operations in developing countries. Artificial intelligence (AI) can help mitigate these bottlenecks toward delivering incremental value to the end customers. This paper investigates the extent to which AI has been adopted in the logistics value chain in developing countries using a descriptive approach. Quantitative data were collected from 290 logistics and e-commerce …

Electrocatalytic Degradation Of Methylene Blue Using Rgo, Sb2o3, And Rgo-Sb2o3 Composite Ink-Based Electrodes, Maria Irene Myers Armas, Andrea M. Fletes, Thomas Eubanks, Arnulfo Mar, Jason Parsons, Helia Magali Morales

School of Integrative Biological & Chemical Sciences Faculty Publications

Water pollution from industrial dyes is a critical challenge due to the resistance of these types of compounds to degradation and potentially harmful effects on living organisms and human health. In this study, the electrochemical degradation of methylene blue (MB) was investigated using ink-based copper foam electrodes with reduced graphene oxide (rGO), antimony trioxide (Sb2O3), and rGO/Sb2O3 composites. The materials used to synthesize the electrodes were characterized by X-ray diffraction (XRD), which showed the successful synthesis of GO, rGO, and the Sb2O3-rGO composite. Additionally, the synthesized electrodes were examined using SEM. The MB degradation was studied using kinetic behavior and …

Translating Low-Level Features Into Student Friendly Explanations Using Xai, Ben Johnson, Keith Nolan

Research Outputs: 2025-Present

An alarming decline in Gaeilge proficiency has renewed education efforts, fueled by the rise of AI in recent years. This research presents the development of a deep learning framework designed to evaluate spoken Gaeilge (henceforth Irish) proficiency of learners by quantifying student voice sample similarity to everyday Irish speaker truth samples, combined with explainable AI (XAI) techniques used to generate proof-of-concept student-friendly feedback. While automatic speech recognition (ASR) systems for high-resource languages like English have access to large, detailed datasets, the Irish language relies on a limited availability of speech resources, that challenges traditional model development. We address these gaps …

Data Preprocessing Methods For Automating Mlops Pipelines: A Comparative Study, Surya Teja Gowd Ayinavilli, Keith Quille, Tarry Singh

Research Outputs: 2025-Present

Preprocessing tools for data are increasingly being utilized in MLOps pipelines to develop models automatically. However, the fairness and reliability of automated processes are inadequately researched, risking causing performance degradation or bias. This discrepancy is addressed in this thesis with an evaluation of automated data preprocessing methods compared to a baseline approach, designed for integration into a TensorFlow Extended (TFX) pipeline. The performance of each method was compared in terms of classification measures and subgroup fairness to determine potential bias. Significance tests were employed to compare the performance of each automated method against the baseline. The results indicate that around …

An Explainable Ml Approach To Modeling Trust In Hri, Csenge Hubay, Musfira Jilani

Research Outputs: 2025-Present

Recent years have seen a growing interest in industrial and social robots; however, their widespread adoption remains constrained due to a limited understanding of trust in human-robot interactions (HRI). Existing approaches to assessing trust in human-robot interactions primarily rely on post-hoc measurements, often collected through self-reports, which are not very effective and do not allow for real-time decision making, which is one of the main aspects of human-robot interactions. This research proposes a data-driven approach to measuring trust in HRI.

Towards A Framework For Bias Evaluation Of Ai Agents In Agentic Workflows, Gary Condon, Musfira Jilani

Research Outputs: 2025-Present

Multi-agent AI systems, with minimal human oversight, are increasingly deployed in high-stakes domains like hiring, healthcare, and criminal justice. However, existing bias evaluation methodologies focus on isolated Large Language Model responses, failing to address sequential agent interactions where biases can propagate through decision chains undetected. Current approaches suffer from three limitations: absence of multi-stage bias tracking, inability to distinguish systematic discrimination from model non-determinism, and risk of contamination when agents infer bias evaluation intent. This study presents a novel evaluation framework incorporating demographic swapping methodology, contamination prevention architecture, and statistical analysis for multi-agent workflows. The framework employs dual presentation systems …

Educators' Evaluation Of Explanation Types In Xai For Higher Education Dropout, Henry Maathuis, Jan Glazenborg, Meike Grol, Keith Quille

Research Outputs: 2025-Present

First-year student dropout rates represent a global challenge, particularly in Computer Science programs. In response, the Predict Student Success (PreSS) tool was developed over two decades using Naïve Bayes, a black box machine learning model, to identify students at risk of early withdrawal or academic failure. Given growing concerns about the use of black box models in high-stakes domains such as education, this study builds on former research by comparing the Naïve Bayes model to three glass box AI models: Decision Tree, Explainable Boosting Machine, and Automatic Piecewise Linear Regression. These models were used to generate four types of explainable …

Contamination Prevention In Agentic Workflow Assessments, Gary Condon, Musfira Jilani

Research Outputs: 2025-Present

Large Language Models (LLMs) may infer that they are being evaluated and strategically modify their responses to appear more aligned than they actually are; a phenomenon described as alignment faking or evaluation awareness. This presents a fundamental challenge for bias evaluation in AI systems, particularly in multi-agent workflows, where sequential decision-making steps occur with minimal human supervision. When LLMs infer that they are being evaluated, they may suppress or diminish discriminatory behaviours that could otherwise manifest in production AI Agent workflow environments, making traditional bias assessment techniques less effective.This work presents a contamination prevention architecture developed in response to observed …

Leveraging Graph Neural Networks For Explainable And Adaptive Seismic Risk Modelling (Work In Progress)), Shivam Tyagi, Musfira Jilani

Research Outputs: 2025-Present

Seismic risk modeling predicts the likelihood of earthquake occurrences in different regions over time. This presents a distinctive challenge as both the spatial structure of underlying geological features and the temporal evolution of seismic events must be accounted for accurately. In addition, for planners and decision-makers, it is essential that such models are not only accurate but also explainable. However, most existing models lack explainability, which limits their usefulness. This research proposes a novel graph neural network based seismic risk modeling methodology that is both explainable as well as adaptable, as it allows decision-makers the flexibility to choose the risk …

An Explainable Multimodal Framework For Real-Time Bitcoin Forecasting, Dipesh Badal, Abdelsalam Busalim, Donghyeok Lee

Research Outputs: 2025-Present

High-frequency crypto forecasting requires systems that are accurate, explainable, and designed for human decision-making. Bitcoin presents a unique challenge for Human-Centred AI (HCAI) due to its volatility and sensitivity to heterogeneous technical, fundamental, and sentiment signals. This paper presents an explainable multimodal framework for Bitcoin forecasting at 15-minute resolution. We align five modalities - market data, on-chain metrics, the Fear & Greed Index (FGI), news, and Reddit - onto a unified, leakage-safe 15-minute grid. We evaluate tree-based, sequential, and Multimodal Fusion Block (MFB) models for next-interval log-return prediction using chronological splits. Results show that while short-horizon prediction remains challenging, multimodal …

Examining How The Strive+ Intervention Affects Caregivers' Comfort Levels And Behaviors: A Quantitative Study, Nastacia Taylor

Creating Healthy Work Environments (CHWE)

Support To Reunite, Involve, and Value Each Other (STRIVE) is a five-session manualized psycho-educational family intervention that incorporates cognitive behavioral therapy strategies to facilitate communication skill development, problem solving, and creating a positive family atmosphere. This strengths-based dyadic intervention has been shown to reduce delinquency, drug use, and high-risk sexual behaviors among disadvantaged adolescents aged 13 to 17 years with lived experience of homelessness.

The updated STRIVE+ was tested to investigate the possibility for lowering youth risk factors for commercial sexual exploitation. Adolescent behavioral family treatments are an effective strategy to intervene to prevent adverse developmental consequences. The STRIVE+ intervention …

Metformin Exposure After Glioblastoma Diagnosis And Mortality: A Large Population-Based Study, Vittorio Maio, Roshani Shah, Manisha Lin, Patrick J. Moeller, Iyad Alnahhas, Richard Hass, Wenyin Shi, Scott W Keith

College of Population Health Faculty Papers

BACKGROUND: Glioblastoma (GBM) is an aggressive primary brain malignancy with limited therapeutic options and poor survival outcomes. Recent real-world studies and early-phase clinical trials evaluating metformin have yielded mixed findings. This study assessed the association between post-diagnosis metformin exposure and all-cause mortality in a large population-based cohort of older adults with GBM.

METHODS: A retrospective cohort study was conducted utilizing the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database. Adults aged ≥66 years diagnosed with GBM between 2007 and 2018 were included, excluding those with other malignancies or diagnoses made by autopsy or death certificate. Metformin exposure was modeled as …

Modeling Spasticity: A Systematic Review, Gaby Gonzalez Chan, Jonathan Marsden, Alexander Besinis, Pablo Borja, Hilary Gunn

School of Health Professions

Spasticity, a type of hypertonia characterized by a velocity-dependent increase in muscle tone, is associated with damage to the brain and/or spinal cord in different neurological conditions. However, secondary non-neurological factors, such as soft tissue changes, can complicate the assessment and differentiation of the underlying causes. Accurate assessment is crucial for effective treatment planning, with clinicians relying on passive movement to grade the ‘feel’ of the spastic limb. This review aims to identify and evaluate the feasibility of spasticity models or simulations for clinical teaching. Models based on human spastic limbs were examined, with no restrictions on specific conditions or …

Synthetic Blood Data Generation For Fair Machine Learning, Sahithi Makam Ramakrishna, Fernando Perez-Tellez

Research Outputs: 2025-Present

Synthetic data generation is a promising solution to privacy concerns in healthcare analytics, particularly when working with sensitive patient information. This study evaluates the performance and fairness of generative models in creating realistic synthetic datasets derived from blood test and demographic data. Three distinct medical datasets are used, including anonymised clinical data from a public hospital in Ireland, a public UCI medical dataset, and a Korean National Health Insurance dataset from 2002. Seven generative models - CTGAN, TVAE, Gaussian Copula, CopulaGAN, MedGAN, DiscGAN, and FASTML - are applied to generate synthetic records. The quality of these records is assessed using …

The Effect Of Cementation Load, Unload Time And Storage Time On Film Thickness And Μtbs Durability Of Dual-Cure Resin Cements. An In-Vitro Study, Sara Adel Botros, Abdullah Hassanien, Nader Maher Tadros, Farid Sabry El-Askary, Salvatore Sauro

Dentistry

No abstract provided.

Kathy Tidwell Is The Calm During The Storm And Through The Decades, Marisa C. Atkinson

University of Mississippi News

OXFORD, Miss. – Iconic. Just as the columns of the Lyceum are iconic to the campus of the University of Mississippi, so is Kathy Tidwell.

Grant Brings 29 New Trees To Ole Miss, Clara Turnage

University of Mississippi News

OXFORD, Miss. – A recent grant from the Mississippi Forestry Commission will help replace trees lost at the University of Mississippi due to recent storms, including those damaged during the January ice storm.

Implementation Of Adverse Childhood Experiences Screening In Pediatric Primary Care, Megan Nicole Waite

Creating Healthy Work Environments (CHWE)

Introduction: Adverse childhood experiences (ACEs) are potentially traumatic events that occur in childhood including abuse, neglect, and household dysfunction. They are highly prevalent among children, especially those that are racially, ethnically, or socioeconomically disadvantaged. ACEs are negatively associated with unfavorable health outcomes in children including behavioral problems, cognitive delays, and poor physical health. Various governing bodies recommend routine screening for ACEs in pediatric primary care, but some studies report screening rates as low as 4%.

Aims: The aim of this quality improvement doctor of nursing practice (DNP) project was to implement an evidence-based ACE screening protocol and referral to behavioral …

Fostering Civility Between Nursing Faculty, Students, And Clinical Partners To Promote Positive Patient Outcomes, Breanne N. Wilburn, Kathryn A. Osteen, Christine J. Oliver, Courtney K. Brandt

Creating Healthy Work Environments (CHWE)

Nurse educators contribute to healthy practice environments and positive patient outcomes in part by educating students on civil practice in didactic and clinical environments (Foreman, 2023; Naseri et al., 2022). Incivility among students, nursing faculty, and clinical partners is a growing concern in the nursing profession (Foreman, 2023; Hajira et al., 2022). Nursing educators serve as examples for students through participating in culturally inclusive civil discourse (Meires, 2018). Further, student incivility in the academic setting could lead to future workplace incivility and is tied to unhealthy practice environments and negative patient outcomes (Park & Kang, 2020; Wei et al., 2018). …

“It Takes A Special Person” --Exploring Undergraduate Nursing Students’ Emotional Needs While Providing End-Of-Life Care, Kalei H. Kowalchik

Creating Healthy Work Environments (CHWE)

Background: Navigating end-of-life (EOL) care as a nursing student can results in intense emotions such as grief and despair and there is limited research on undergraduate nursing students’ thoughts and experiences on the need for emotional support resources when caring for patients and families at the EOL.

Purpose: To explore undergraduate nursing students’ experiences and their perceived need for integrating emotional and psychological support services while caring for dying populations.

Theoretical Framework: The Nerstrom Transformative Learning Model was used to guide this research which identifies how adult learners interact in their environment with a limited worldview that is …

Quality Improvement Project: The Influence Of Education On Provider Self-Efficacy And Utilization Of The Columbia Suicide Severity Rating Scale (C-Ssrs), Doreen Nwaogwugwu

Doctor of Nursing Practice Projects

Suicide remains one of the leading causes of death worldwide, underscoring the critical need for consistent, evidence-based suicide risk screening in mental health facilities. Despite being a validated, evidence-based tool, the use of the Columbia Suicide Severity Rating Scale (C-SSRS) is often hindered by inadequate provider training. The purpose of this Doctor of Nursing Practice quality improvement project was to evaluate the impact of provider education on self-efficacy and utilization of the C-SSRS in an outpatient mental health clinic. This quality improvement project used a quasi-experimental, one-group pretest-posttest design guided by the Health Belief Model, Lewin’s Change Theory, and the …

Transformative Technology And Shortening The Statute Of Limitations Applicable To Taxpayers, Jay A. Soled, Leslie Book

Faculty Publications

When it comes to submitting tax returns and paying taxes, most taxpayers understand the nature of their civic duties and do so dutifully, if not willingly. However, many taxpayers fail to grasp why the IRS has such an elongated time period—namely, three years— to audit their tax returns and propose an assessment. Indeed, when the IRS exercises its oversight authority, records may no longer be available, and memories may be dulled.

Since the original institution of the three-year tax assessment limitations period nearly a century ago, tremendous technological strides have been made. Indeed, over ninety percent of income tax returns …

Elena Dorozhkina, Piano

Bailey School of Music Concert Programs

Elena Dorozhkina, Piano

Relationship Between Navigation Success, Diagnostic Accuracy, And Ventilation Strategy: Retrospective Chart Review Of 224 Consecutive Navigational Bronchoscopic Procedures Performed Under General Anesthesia, Basavana Goudra, Prarthna Chandar, Divakara Gouda, Harrison Yang, Ganan Muhunthan, Suvan Sundaresh, Michael Stuart Green

Department of Medicine Faculty Papers

Background: Navigational bronchoscopy (NB) enables precise sampling of peripheral and central pulmonary nodules using shape-sensing or electromagnetic guidance. A major challenge is anesthesia-induced atelectasis, which alters lung anatomy, reduces registration accuracy, and is known to lower diagnostic accuracy. To counteract this, ventilatory protocols such as the Ventilatory Strategy to Prevent Atelectasis (VESPA) and the Lung Navigation Ventilation Protocol (LNVP) have been recommended. Their adoption and clinical impact, however, remain uncertain. Methods: We conducted a retrospective review of 224 consecutive NB procedures performed under general anesthesia at a single academic medical center (January 2020–August 2024). Demographic, anesthetic, and ventilatory data were …

Myelodysplastic Syndrome Secondary To Chimeric Antigen Receptor T-Cell (Car-T) Therapy For The Treatment Of Relapsed/Refractory Multiple Myeloma, Waqqas Tai, Daniel Kim, Joe Dib, Jessica Thomas, Swathi Gopishetty, Precious Idogun, Afoma Anyadibe, Anuoluwa Ayetoran, Syed Zaidi, Savitha Balaraman, Ishmael Jaiyesimi

Student Publications

We present the case of a 65-year-old man with relapsed/refractory multiple myeloma (RRMM) who developed therapy-related myelodysplastic syndrome (MDS) following chimeric antigen receptor T-cell (CAR-T) therapy with idecabtagene vicleucel (ide-cel). The patient, initially diagnosed in 2019, underwent multiple lines of therapy, including high-dose melphalan with autologous stem cell transplantation, before receiving ide-cel for progressive disease. Despite initial remission, a day 100 bone marrow biopsy revealed MDS with a 7q deletion, a cytogenetic abnormality not present on prior marrow evaluations. While CAR-T therapy has revolutionized RRMM treatment, long-term complications such as therapy-related hematologic malignancy remain under-recognized.

The temporal relationship between CAR-T …

Understanding Rhetoric Using Meth, Hugo Castellano

English Student Showcase

Professor: Khimen Cooper-DeHoyos Faculty Readers: Tawnya Hillin-Smith and Jason Carney    Class: English 1301/Spring 2026

Visual Healing In Visual Communication Design: Exploring Calm Aesthetics For The Psychological Well-Being Of Urban Society, Siti Indah Lestari, Ivo Ramadhani

Bahasa dan Seni: Jurnal Bahasa, Sastra, Seni, dan Pengajarannya

This study investigates the concept of visual healing from a Visual Communication Design (VCD) perspective, focusing on its potential contribution to emotional comfort and psychological well-being among urban office workers. Contemporary workplace environments are increasingly characterized by prolonged screen exposure, dense visual information, and sustained cognitive demands, conditions that intensify visual fatigue and psychological strain. In this context, the study positions visual design not merely as an aesthetic practice, but as a psychologically responsive medium capable of shaping users' emotional experiences in everyday work settings. Employing a qualitative Research through Design (RtD) methodology, the study treats the design process as …

Adapting To Cultural Diversity At Work: A Thematic Analysis Of Resources Mobilized By Local And Posted Agricultural Workers In France, Alexandrine Ceschiutti, René Mokounkolo

The Qualitative Report

When workers have to adapt to a new culture, they develop intercultural skills as cultural intelligence (CQ), which is the ability to show an interest and act effectively in an environment characterized by cultural diversity. There has been little research on this subject in France, and studies have focused on expatriates, while acculturation also affects people from the local community. This is the case for local agricultural workers (LW), whose perceptions we compare with those of foreign posted agricultural workers (PW) in France. Our study had two aims: (a) to explore the personal resources that these workers perceive as necessary …

Qualitative Methods For Health Research, 5th Edition: A Review, Rikki Mangrum

The Qualitative Report

Qualitative Methods for Health Research (5^th ed.; Green et al., 2025) is an introductory textbook that provides an overview of qualitative methodology as it is used in health-related fields, including public health, healthcare delivery, and medical science. It provides instruction on theoretical principles, core methods and their implementation, and related topics such as developing research proposals and publishing study results. This new addition includes updated content and new content pertinent to recent developments that have affected health research practices, such as the COVID-19 pandemic and broader awareness of the impact of colonialism and racial discrimination.