Medicine and Health Sciences Commons^™

Optimisation Of Photosensitive Recording Materials For Broadband Holographic Optical Elements, Michael Murray

Doctoral

The introduction of broadband (white) LED outdoor lighting has led to significant energy savings. However, this has come at the cost of increased light pollution which has negative impacts both on ecological systems and human health. This light pollution is largely the result of the lack of control measures for the directionality of the light emitted by outdoor LED lighting. The lack of directionality also results in higher energy consumption in order to compensate for the light scattered to the atmosphere and sufficiently illuminate the target area. In this thesis holographic optical elements (HOEs) are proposed as a complementary technology …

Volume 17, Christian O’Neill, Kyara Greene, Savva Sidorov, Laura Bisaillon, Luke Clemmer, Hannah Gordon, Kitt Benson, Taylor Blount, Rachel Danzitz, Nicholas Duellman, Chase Gionis, Hima Fernando, Seth Franzyshen, Onyx Gonzalez, Bryan Lin, Samantha Start, Ysabel Wells, Maggie Duncan

Incite: The Journal of Undergraduate Scholarship

Introduction Dr. Amorette Barber, Director, Office of Student Research

From the Editor Dr. Hannah Dudley-Shotwell

Cover Artist’s Statement Maggie Duncan

On Mentoring Dr. Yulia Uryadova

Ukrainian Resistance in the Face of Russification: Nestor Makhno and Anarchism

by Christian O’Neill

Life Vest by Kyara Greene

Isolation and 16S rRNA Identification of Bacteria from Fire Department Connection Pipe by Savva Sidorov

The Effectiveness of Planned Exercise in Reducing ADHD Symptoms in Children by Laura Bisaillon & Luke Clemmer

Linguistic Analysis on Confidence and Communication Strategies with Disparities Between Sign Fluency and Hearing Impairment by Hannah Gordon

Freedmen in Indian Territory by Kitt …

Understanding Delays In Emergency Department Care: A National Analysis Of Wait Times, Gregory Forsberg

Mathematics, Statistics, and Computer Science Honors Projects

Emergency department (ED) wait times remain a persistent bottleneck in the United States healthcare system, impacting patient outcomes, hospital efficiency, and equitable access to care. This study analyzes nationally representative data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a complex, multi-stage probability sample. Using survey-weighted analyses and predictive modeling, we examine the effects of patient characteristics, triage acuity, and visit timing. Results indicate that operational and system-level factors, including hospital capacity, geographic region, and temporal variation, are among the most influential predictors of ED wait times

Pattern Dynamics And Stochasticity Of Brain Rhythms And Spike Trains In A Tauopathy Mouse Model Of Alzheimer’S Disease, Clarissa M. Hoffman

Dissertations and Theses (Open Access)

Systems neuroscience posits that every aspect of perceived physical reality, every aspect of animal and human behavior, and every cognitive phenomenon emerges from patterns of neuronal activity. While most researchers embrace this idea, there are major difficulties in describing and analyzing these complex neuronal dynamics—spike flows produced by cells ensembles, synchronized extracellular field oscillations, and other patterns—which limits our understanding of how the activity of individual neurons and the whole-animal cognition and behavior might be connected. In particular, we lack the approaches and even the semantics for connecting the individual cell outputs and the integrated results of their activity. Current …

Smart Medical Support System And Swin Transformer Framework For Breast Cancer Detection And Segmentation In Mammograms, Ahed Abugabah, Prashant Kumar Shukla, Piyush Kumar Shukla, Abhishek Dwivedi

All Works

Accurate and reliable breast cancer detection from mammographic images remains a critical challenge due to subtle lesion appearance, high intra-class variability, and class imbalance inherent in clinical datasets. To address these issues, this study proposes Swin-BreastNet, an explainable and optimization-driven deep learning framework for binary classification of benign and malignant breast lesions from full-field digital mammograms. The proposed approach leverages the hierarchical Swin Transformer model to effectively capture fine-grained local texture patterns and long-range contextual dependencies through Shifted Window Multi-head Self-Attention (SW-MSA). A key novelty of this work lies in the integration of Harris Hawks Optimization (HHO) for automated hyperparameter …

Artificial Intelligence In Medicine: Barriers, Solutions, And Strategies, Anil Harrison, Melissa Stradley Moreno, Caroline E. Williams, Munevver Mine Subasi, Ersoy Subasi

HCA Healthcare Journal of Medicine

The integration of artificial intelligence (AI) and machine learning (ML) into health care holds the potential to revolutionize patient care by enhancing clinical decision-making, improving diagnostic accuracy, and reducing costs. Despite this promise, adoption remains limited due to a range of technical, regulatory, educational, and cultural barriers. This paper examines these challenges and proposes strategies to support safe and effective implementation of AI in clinical practice.

Key barriers include the lack of model interpretability, often referred to as the "black box" problem, which undermines clinician trust and accountability in clinical settings, evolving regulatory frameworks and unresolved questions surrounding liability, and …

Dementia Detection In Low-Resource Languages: Evaluating Translation-Assisted Transfer Learning For Multilingual Clinical Assessment, Kylar A. Deloach

Honors Theses

Alzheimer's disease (AD) is a growing global health concern, with millions of people affected worldwide and cases expected to rise significantly in the coming decades. Early detection is critical for patient treatment and care, and recent advances in natural language processing (NLP) have shown promise in identifying linguistic markers associated with AD. However, most existing work has focused on English, leaving speakers of other languages with limited access to such tools. This study investigates how effective AD detection models trained on English data are at transferring to Greek, a low-resource language with limited dementia-related speech data available. We propose a …

Investigating The Synthesis And Antibacterial Activity Of A Main-Chain Cationic Polymer, Emily Smith

Honors Theses

Antibiotic resistance is a growing threat to public health. Due to the overuse of antibiotics in agriculture, the overprescription of antibiotics, and the misuse of antibiotics by patients, antibiotic resistance is spreading at an alarming rate. As antibiotic resistance spreads, the antibiotics we depend on to treat common infections become ineffective. Therefore, it is imperative to develop novel treatments for infections that do not increase the prevalence of antibiotic resistance. One treatment being explored is the use of synthetic polymers with antibacterial properties. Synthetic polymers are advantageous because they can be synthesized from widely available precursors and their structure is …

Volume 12 Full Text, Bjur Staff

Butler Journal of Undergraduate Research

No abstract provided.

Exploring Gender As An Analytical Framework In The 2018-2019 Revolution And Ongoing Civil War: The Role Of Gendered Violence And Sudanese Women's Resistance, Ami John

Butler Journal of Undergraduate Research

This paper will interrogate the intersection of gender, war, and political upheaval within Sudan while focusing on the role of women in both the 2019 resistance and the ongoing conflict and revolution. By the end of 2018, mass protests had called for the ousting of Omar al-Bashir, the long-standing Sudanese president. This event set off a chain reaction which led to events that fueled the long-standing rivalry between the two militant groups that were active in Sudan, the Rapid Support Forces (RSF) and the Sudanese Armed Forces (SAF). The tension caused by this rivalry created unforeseen circumstances for the local …

Front Matter And Table Of Contents, Bjur Staff

Butler Journal of Undergraduate Research

No abstract provided.

Drug Risk Knowledge Discovery For Western Medicines Based On Knowledge Graph Link Prediction, Jianxiang Wei, Ma Hengyuan Ma, Yuehong Sun, Wenwen Du, Letian Hu

Journal of Scientific Information Research

[Purpose/significance] The risk information contained in drug instructions is usually incomplete, and some new adverse reactions can only be discovered in actual clinical use. This paper proposes an information organization and knowledge discovery method for pharmacovigilance, in order to timely and accurately identify missing risk knowledge in drug instructions. [Method/process] Drug instructions of 8 152 Western medicines are collected as the research data; On the basis of ontology construction, data annotation, and model training, the UIE model is used to jointly extract entity and relationship triplets from the research data; A new knowledge graph link prediction method CompGCN-RotatE, is proposed, …

Research On Temporal Knowledge Graph Completion Method For Emergent Events Based On Bigru And Graph Contrastive Learning, Peng Wu, Zhenyu Lu, Xuechen Zhang

Journal of Scientific Information Research

[Purpose/significance] During emergencies, social media short texts contain critical information but are heavily interfered with by noise. Traditional static knowledge graph completion techniques struggle to effectively address their dynamic evolution and data sparsity issues, making it imperative to introduce temporal modeling methods. [Method/process] This study proposes a dynamic completion framework that combines the temporal feature capture capability of Bidirectional Gated Recurrent Units (BiGRU) with the noise-resistant representation learning advantages of Graph Contrastive Learning (GCL). At the completion level, the ConBiTE method is introduced, which captures temporal dependencies through self-attention mechanisms and BiGRU, while leveraging GCL to enhance the completion of …

2026 - The Thirtieth Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the 30th Annual Symposium of Student Scholars, held on April 22-24, 2026. Includes abstracts from the presentations and posters.

Program And Proceedings, The Nebraska Academy Of Sciences 1880–2026: 146th Anniversary Year, One Hundred-Thirty-Sixth Annual Meeting

Nebraska Academy of Sciences: Programs and Proceedings

Program and abstracts of the proceedings for the Nebraska Academy of Sciences 136th annual meeting, 2025

Sessions

Aeronautics and Space Science

Anthropology

Biological and Medical Sciences

Earth Sciences

Ecology, Sustainability, and Environmental Science

Physics and Engineering

General Poster Session

2026 Maiben Lecture: Shifting Extremes: Understanding Nebraska’s Changing Climate and Preparing for What Lies Ahead, Deborah Bathke

2026 Friends of Science Awards: Julie Shaffer and Irina Filina

2026 C. Bertrand and Marian Othmer Schultz Colleaguate Schoalrship Award: Piper Ryschon and Bryce Reeson

In Memoriam: Paul Royster

Optimization Of Pediatric Multidetector Ct Imaging Parameters Using A Machine Learning–Based Monte Carlo Simulation Model, Ali O. Masoud, Adithya Rajnaryanan, Khamis O. Amour, Ahmed M. Jusabani, Justin E Ngaile, Manoj Kumar, Mwingereza John Kumwenda Dr

Tanzania Journal of Science

This study utilized Monte Carlo (MC) simulations to optimize radiation doses in pediatric multidetector computed tomography (MDCT) head scans by analyzing key parameters like tube current (mA), tube voltage (kV), pitch, and slice thickness. The findings indicate that reducing tube current significantly lowers the Computed Tomography Dose Index (CTDIvol) and Dose Length Product (DLP), effectively minimizing patient radiation exposure. Higher pitch values (0.7–0.9) further reduced radiation by decreasing beam overlap, while using a thinner slice thickness (0.6 mm) improved dose efficiency. A comparison highlighted the effectiveness of optimization: simulated parameters kVp 100, mAs 81, pitch 0.98 yielded a CTDIvol of …

Theory And Simulations Of Delayed Stochastic And Deterministic Models Of Prion Diseases, Gangadhara Boregowda, Omar Sharif, Daniel Gutierrez Iii, Allegra Simmons, Laurent Pujo-Menjouet, Tamer Oraby, Michael R. Lindstrom

School of Mathematical & Statistical Sciences Faculty Publications

Neurodegenerative diseases (NDs), such as Alzheimer’s, Parkinson’s, and prion diseases, are characterized by the dynamical spread of toxic proteins through the brain. In prion diseases, cellular prion protein (PrPC), produced by neurons, misfolds into a toxic form, known as scrapie prion protein (PrPSc). PrPSc induces neuronal stress which ultimately leads to cell death. In this paper, we develop mathematical models for the progression of prion diseases, incorporating a cellular defense mechanism that introduces a delay term affecting protein translation and a volatility term accounting for unaccounted biological factors influencing the system. We also extend the model to capture the spatial …

Synthesizing Fluorescent 3,4-Dihydropyrimidin-2(1h)-Ones Using A One-Pot Synthesis Reaction, John R. Griggs

Create@State

In medical and pharmaceutical practices, Biginelli (3,4-dihydropyrimidin-2(1H)-ones) products have a number of potential uses due to their anticancer and anti-inflammatory properties.  In addition, they are a possible treatment for acquired immunodeficiency syndrome (AIDS). These compounds can be further modified to exhibit fluorescent properties. However, before using them in medicinal studies, it is useful to establish a procedure that can easily be modified and is synthetically accessible to allow for further optimization. The experiment was performed using the Biginelli compounds as a substrate, along with a variety of aromatic aldehydes and acids. After obtaining the products and purifying them with vacuum …

Spatial Computing With The Apple Vision Pro In Minimally Invasive Procedure Simulation: A Randomized Crossover Feasibility Study, Sydney Cooper, Aaron Kyle Jones, Rahul Anil Sheth, Koustav Pal, Bruno Odisio, Mark Blaylock, Shelita Kimble, Justin Bird, David Rice, Daniel Shoenthal, Emil Patel, Vipin Kamath, Sanjay Gupta, Jeffrey Siewerdsen, Joshua Kuban

Advances in Cancer Education and Quality Improvement

Purpose: This study aimed to evaluate the feasibility of wearing the Apple Vision Pro (AVP), a mixed-reality headset that integrates augmented and virtual reality, while performing minimally invasive procedures. While studies have demonstrated that spatial computing technology can improve surgical precision and reduce the risks of surgical complications, to our knowledge, no studies have specifically addressed the impact of the AVP on task performance during simulated image-guided procedures.

Materials and Methods: Thirteen diagnostic and interventional radiology residents performed image-guided central venous catheter placement, thoracentesis, and paracentesis on simulation models. Each participant completed a non-timed practice followed by the procedures once …

Swosu Research And Scholarly Activity Fair 2026, Swosu Office Of Sponsored Programs

SWOSU Research and Scholarly Activity Fair Programs

On behalf of the University Research and Scholarly Activity Committee (URSAC) and the Office of Sponsored Programs (OSP) at Southwestern Oklahoma State University, we are pleased to welcome you to the Thirty-Fourth SWOSU Research and Scholarly Activity Fair.

The Impact Of State And Federal Policies On Academic Researchers: Findings From A National Survey, Dylan Ruediger, Chelsea Mccracken, Jonathan Barefield

Copyright, Fair Use, Scholarly Communication, etc.

Key findings

● State and federal policies targeting divisive concepts or DEI are shaping research agendas at scale and across disciplines. Twenty percent of all respondents, and 29 percent of researchers working in states with divisive concepts or similar laws, reported having avoided certain research topics because of state laws and policies.

● Eight percent of respondents representing a wide range of disciplines reported having had a federal grant cancelled in 2025.

● Eleven percent of respondents reported that federal and state policies restricting research activities are compelling them to seek employment out of state, to leave the academy, or …

Organic Synthesis Of A Hydrazine Functionalized Ammonium Compound For Improved Capture Of Aldehyde Metabolites From Exhaled Breath, Po'iu N. Burgo

Undergraduate Theses

Breath analysis has emerged as a non-invasive and inexpensive way to screen for respiratory diseases. This technique involves measuring concentrations of specific metabolites found in exhaled breath that serve as a biomarkers for disease. A subclass of volatile organic compounds called α,β-Unsaturated aldehydes, products of the lipid peroxidation mechanism, are underrepresented as biomarkers of lung cancer. These have been found to have relatively increased concentrations in the exhaled breath of lung cancer patients compared to a healthy patient. One of the reasons that these metabolites have been underreported is that the techniques used to measure and characterized exhaled metabolites do …

Techno-Enviro-Economic Analysis Of Precipitated Calcium Carbonate Production From Carbon Dioxide In Cement Industry Flue Gas And Calcium Hydroxide, Natalia Debora Panggabean, Widodo Wahyu Purwanto

Journal of Materials Exploration and Findings

CCUS is a technological solution to reduce emissions from the cement industry, which is the second largest CO2-intensive industry. This study aims to analyze technical, economic, and environmental performance of Precipitated Calcium Carbonate (PCC) synthesis in cement industry flue gas. The process simulation includes the CO2 capture system from cement plant, CO2 captured used as feedstock for PCC synthesis process through its reaction with calcium hydroxide. The simulation was carried out using ASPEN Plus software. Technical analysis was performed to determine the CO2 capture efficiency and PCC synthesis efficiency. Economic analysis was conducted to calculate CO2 capture cost and production …

Feasibility Analysis Of Thermal Oxidizer To Determine Remaining Life Using Fitness- For-Service Level 3 Method, Yudhi Yudistirawan, Donanta Dhaneswara, Wahyuaji Narottama Putra, Gama Widyaputra, Dewi Kurnia Suci, Agung Putra Mahardhika

Journal of Materials Exploration and Findings

An aged thermal oxidizer (TOX) in the oil and gas industry necessitates a comprehensive evaluation to ensure its continued safe operation. This study presents a Remaining Life Assessment (RLA) and a Fitness for Service (FFS) evaluation for the four main components of the TOX, in accordance with API 510, API 579/ASME FFS-1, and ASME BPVC Section VIII Div-1 standards. The investigation includes the determination of maximum stress and maximum temperature required to assess the operational viability of the reactor. The four components are radiant, convection, transition, and stack sections—were modeled using the finite element method (FEM). Following the geometric modeling, …

A Backend Database Architecture For Persistent Epilepsy Classification Records, Attiksh A. Panda, Deep Desai, Artem Zabarov, Katrina D. Prantzalos, Satya S. Sahoo, Shuai Xu

Student Scholarship

Epilepsy affects over five million people globally each year, yet consistent clinical diagnosis remains a persistent challenge due to the lack of standardized classification workflows across medical institutions. The Four-Dimensional Epilepsy Classification (4D-EC) framework, developed by Lüders et al., provides a comprehensive structure for characterizing paroxysmal events across four dimensions: seizure semiology, epileptogenic zone, etiology, and comorbidities. Despite its clinical and educational value, no dedicated informatics platform existed to support its routine use until recently, limiting widespread adoption among clinicians and trainees. This project addresses that gap by implementing a full-stack web application that operationalizes the 4D-EC framework for clinical …

Ai’S Role In Searching For Evidence: Friend And Foe, Barbara (Basia) Delawska-Elliott, Brandon Wilkinson

Publications 2026-present

No abstract provided.

Statistical Inference Is Not Moral Reasoning: The Case Against Ai On Hospital Ethics Boards, Elan J. Haronian

Seaver College Research And Scholarly Achievement Symposium

As generative AI becomes more integrated in healthcare, it seems inevitable that AI will eventually be used on hospital ethics committees. However, before implementation, their roles need careful consideration. Although AI promises to reduce costs, increase efficiency, and reduce human workloads, there are important ways in which it is limited, especially when human emotion and connection are crucial, as in clinical ethics boards.

In this paper, I highlight several problems preventing AI from being useful on hospital ethics boards. These include issues of opaque reasoning (the “black box” problem), liability, transparency, privacy, and consent. While there are proposed frameworks for …

Bio-Cybersecurity: Securing The Healthcare Industry, Amanda D. Coleman

Cybersecurity Undergraduate Research Showcase

Bio-cybersecurity refers to the aspect of cybersecurity that applies to the biological sciences and the protection of digital biomedical information. Today’s healthcare industry has evolved with the enhancement of internet and biomedical technology. While hospitals and private medical providers remain compliant with the Health Information Portability and Accountability Act (HIPAA) through traditional means of securing documented patient information, the emergence of beneficial internet-based healthcare services like virtual appointments and digital patient records requires new policies and healthcare cybersecurity frameworks to protect sensitive information from unauthorized access. This paper examines the role of cybersecurity in healthcare, the vulnerabilities that exist and …

Dermal: A Multi-Input Deep Learning Model For Improving Access To Dermatological Screening, Aubreye Freeman

ATU Scholars Symposium

According to the World Health Organization's press release on December 12, 2024, global healthcare spending is dropping significantly, leaving a large percentage of the world without proper healthcare. In an attempt to alleviate this problem, with respect to the field of dermatology, we created a deep learning model, Dermatology Enhanced by Recognition and Machine Aided Learning (DERMAL), to assist in diagnosing skin conditions. DERMAL was trained on a portion of the Google and Stanford Medicine's SCIN dataset, which has more than 10,000 images of various skin conditions. The 9 most common skin conditions of the dataset were selected as the …

Investigating The Effect Of Kcl Stress In Raphanus Sativus, Mason P. Oelke

ATU Scholars Symposium

Presented by Stephanie Nelms at the Arkansas INBRE Conference on November 7-8, 2025.

Presented by Mason Oelke at Arkansas Tech Scholar's Symposium on April 9th, 2026.

Potassium is an essential macronutrient for plant growth and development, yet excessive potassium fertilization can induce salt stress with detrimental consequences for crop productivity and nutritional quality. Despite its agricultural relevance, potassium chloride induced stress remains significantly understudied compared to classical sodium-based salinity. This thesis investigates the physiological, biochemical, and molecular responses of Raphanus sativus to KCl stress using an integrated approach that combines germination assays, mineral profiling, and gene expression analysis.

Radish seeds …