Digital Commons Network^™

2026 Urs Abstract Booket, Undergraduate Research Center, Minnesota State University, Mankato

Undergraduate Research Symposium

Complete Schedule of Events for the 28th Annual Undergraduate Research Symposium at Minnesota State University, Mankato.

Adaptive Semantic Audio Filtering Via Neural Source Separation And Intent-Based Vector Scoring, Tamar Yakar, Ilia Labzovsky

Defensive Publications Series

Acoustic environments containing multiple simultaneous speakers present challenges for conventional noise cancellation and transparency technologies, which often fail to isolate specific audio based on semantic relevance. Traditional methods, such as directional beamforming or spectral profiling, cannot distinguish between sources based on the topical content of speech.

An adaptive semantic audio filtering method is disclosed to address these limitations. Ambient audio is captured and decomposed into discrete streams using neural blind source separation. Each stream is transcribed via automated speech recognition and converted into a context vector. These vectors are compared against a user-defined target semantic profile using cosine similarity scoring. …

A Sticky Situation: Mannose Glycosides, Morgan Romanski, Scott Hasty

2026 Student Academic Showcase

Mannose chemistry is notoriously difficult due to the electronic structure of the molecule. The dipole moments on the molecule provide stability, meaning adding and removing substituents come with many obstacles. This results in numerous byproducts, prevents reactions from going quickly, or prevents the reaction from occurring at all. In this project, the issue of producing a mannose molecule with the desired leaving group for glycosylations is investigated using two different methods of synthesis of attaching 2-mercaptopyridimine to a benzylated mannose on carbon 1. These two methods investigate and aim to solve the issue of epoxide formation and the mannose molecule …

Complete Synthesis Of A Beta-Linked Disaccharide, Abby Dunn

2026 Student Academic Showcase

The continual need to develop strategies and methods for oligosaccharide synthesis drives carbohydrate chemists to discover new glycosides. This push has led to the discovery of an attractive 6-methylpyrid-2-yl leaving group for chemical glycosylation. Presented are three syntheses of the molecules 2-mercapto-6-methylpyridine, glycosyl donor 6-methylpyrid-2-yl-2,3,4,6-O-acetyl-1-thio-β-D-glucopyranoside, and glycosyl acceptor methyl-2,3,4-O-benzyl-α-D-glucopyranoside. The 2-mercapto-6-methylpyridine molecule was affixed to the requisite sugar to produce the glycosyl donor, 6-methylpyrid-2-yl-2,3,4,6-O-acetyl-1-thio-β-D-glucopyranoside. This sugar was then coupled with methyl-2,3,4-O-benzyl-α-D-glucopyranoside using silver triflate (AgOTf) to obtain the targeted disaccharide.

Effects Of Gibberellic Acid (Ga3) On Growth In Setaria Viridis Mutant Families, Rebecca Laird, Charmaine Dao, Kayneisha Hepburn, Madison Brown, Hailey Veninga

2026 Student Academic Showcase

The grass Setaria viridis has frequently been employed in research due to its short life cycle, small genome, and close relationship to food crops like maize (corn). Setaria is utilized to study the genetic processes governing reproductive development. In this experiment, the effects of gibberellic acid (GA) therapy on several Setaria viridis mutant families have been investigated. This experiment also aims to detect variations in plant height phenotype by comparing GA-treated plants with untreated control plants. The researchers collected and planted eight dwarf millet seeds and one wild type mutant seed and planted in a ‘control’ tray and a ‘treatment’ …

An Exploratory Analysis Of A Regional Nonprofit & Family Services Organization, Alison Schrumpf, Eleri Tye, Hailey Veninga

2026 Student Academic Showcase

Nonprofit organizations are essential in supporting youth's mental health in their communities, and the data they collect allows us to evaluate program effectiveness and how services can be improved to better support their communities. This project aims to evaluate program and provider outcomes, client demographics, and assessment scores for a regional nonprofit and family services organization to better understand client success, program effectiveness, and the impact of COVID-19. The dataset includes client demographic information, programs, zip codes, first and last session assessment dates and scores, discharge types, and provider IDs. To investigate score changes, we are analyzing the correlation between …

Optimizing K-Nearest Neighbor Based On Dragonfly Algorithm For Diabetes Retinopathy Classification, Ahmed Subhi Abdalkafor, Alaa Abdalqahar Jihad, Esam Taha Yassen

Baghdad Science Journal

The K-Nearest Neighbors (KNN) has been proven to be an effective method for addressing classification problems. The performance of the KNN algorithm is heavily dependent on the value of parameter K, which represents the number of nearest neighbors. Choosing an inappropriate value for K can affect the classification accuracy because a smaller chosen K can lead to overfitting and vice versa. So, the appropriate selection of the K value has a significant impact on the performance of KNN. Manually, adjusting the value of K is a very difficult process because the appropriate choices for this value depend on the status …

Detecting Eigenvectors Of An Operator That Are Near A Specified Subspace, David Darrow, Jeffrey S. Ovall

Mathematics and Statistics Faculty Publications and Presentations

In modeling quantum systems or wave phenomena, one is often interested in identifying eigenstates that approximately carry a specified property; scattering states approximately align with incoming and outgoing traveling waves, for instance, and electron states in molecules often approximately align with superpositions of simple atomic orbitals. These examples—and many others—can be formulated as the following eigenproblem: given a selfadjoint operator L on a Hilbert space H and a closed subspace W ⊂ H, can we identify all eigenvectors of L that lie approximately in W? We develop an approach to answer this question efficiently, with a userdefined tolerance and range …

An Examination Of The Value Of Study Abroad When Learning A Foreign Language: A Study Of Differing Student Outcomes. To What Extent Does Studying Abroad Enhance A Language Learning Experience?, Julie Syler

Honors Theses

The purpose of this study is to articulate the importance of learning a foreign language and examine the value of studying abroad when learning a foreign language, by conducting qualitative research on different study abroad experiences. There is an ongoing discussion of the importance of foreign language learning and whether or not it is a beneficial endeavor. This literature review explores the benefits of foreign language learning to demonstrate their impact and how they occur when studying abroad. Furthermore, this investigation examines how and why study abroad experiences promote language acquisition. The improvements in communication and understanding in a foreign …

Reforming Academic Publishing To Support The Sustainable Development Goals: A Call For Leadership, Seán Lacey

Publications

Paywalls and high article processing charges in academic publishing restrict access to scientific knowledge, limiting who can produce, use, and benefit from research. These barriers disproportionately affect researchers and institutions in low- and middle-income countries, reinforcing global inequalities in research capacity and evidence-informed policymaking. Addressing these challenges requires determined system leadership to reform funding models, expand equitable open access pathways, and ensure publicly funded research is freely available. Without coordinated action, the promise of inclusive, globally shared scientific progress central to the Sustainable Development Goals will remain unrealised.

Mcgehee Blow Up And Collision Manifold Of Planar (2+2)-Body Problem, Nathaniel Scott Sill

Theses and Dissertations

This thesis analyzes the dynamics of the Planar (2+2)-Body Problem which consists of two asteroids moving under the gravitational force of each other and of two larger primaries. We use the McGehee blow up technique to remove the singularities in the dynamics associated with a triple collision with one of the primaries by introducing a new set of variables. Additional variables are introduced to reduce the dimension of the problem. We then derive the dynamics for these new variables. We then use the energy relation that comes from the original Hamiltonian to describe the collision manifold which is pasted in …

Re: Approval Letter For The Butte Priority Soils Operably Unit (Bpsou) Revised Draft Final Quarterly Operations And Maintenance Report: Butte Treatment Lagoon System (Btl) Second Quarter 2025 (Dated April 10, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Factors That Affect African American Representation In Cybersecurity Academic Programs In The United States, Damon Walker

Dissertations

The U.S. cybersecurity workforce continues to experience a critical talent shortage alongside persistent inequities in racial representation, particularly at the faculty level within higher education. This mixed-methods dissertation examines African American representation among faculty in cybersecurity academic programs designated by the National Centers of Academic Excellence in Cybersecurity (NCAE-C) and investigates the factors that influence recruitment, retention, and advancement. Grounded in a transformative research framework, the study integrates quantitative analysis of national institutional data with qualitative interviews to illuminate structural patterns and lived experiences shaping representation.

Quantitative findings revealed pronounced underrepresentation: African American faculty comprise 2.57% (130 of 5,051) of …

Optimizing Quality Of Service In Cloud Computing: A Performance-Aware Task Classifier For Heterogeneous Big Data Workloads, Pawan Bhaker, Sophiya Sheikh, Rintu Nath, Ajay Nain

Baghdad Science Journal

The Big data originates from various heterogeneous sources worldwide. Due to the diverse origins of data generation, big data involves a variety of tasks. Some require storage resources, while others need computational resources. Additionally, cloud computing provides centralized storage and computational resources for executing these tasks. However, resource optimization and efficient task scheduling remain challenging. Moreover, accurately categorizing tasks and effectively allocating resources based on their nature pose challenges for cloud computing, especially when assigning tasks to heterogeneous resources to minimize task completion time. To address these issues, this paper proposes a Performance-Aware Task Classifier (PATC) algorithm that classifies tasks …

A New Reinforcement Learning Agent Framework For Digital Image Forgery Detection Using Prioritized Experience Replay, Muthana S. Mahdi, Saad N. Alsaad, Hasanen S. Abdullah

Baghdad Science Journal

Digital image forgery detection has become an urgent and complex problem in an age when powerful editing tools can easily alter photographs. The familiar maxim ``a picture is worth a thousand words'' can no longer be taken at face value, since even subtle manipulations may conceal or fabricate critical details. Conventional detection methods frequently suffer from highly imbalanced datasets and narrow feature representations that fail to capture the diverse artifacts introduced by modern editing techniques. In response, this work presents a novel framework that casts the forgery detection task as a reinforcement learning problem, enabling an agent to learn a …

An Informative Analysis Of Applying Feature Reduction Methods To Supervised Machine Learning Algorithms, Mustafa S. Abd

Baghdad Science Journal

Feature reduction techniques are fundamental to enhancing machine learning (ML) algorithms by reducing the number of features in a dataset. The study here explores the impact of Principle Component Analysis (PCA) on ML algorithms within an unbalanced classification framework, in partnership with feature selection techniques like Cluster Variation Attribute Evaluator (CVAE) and Correlation Attribute Evaluator (CAE). In addition, the research introspects a comparison analysis evaluating the effectiveness of several ML methods, including Multilayer Perceptron (MLP), Decision Tree J48, k-Nearest Neighbor (k-NN) and Sequential Minimal Optimization (SMO). The informative analysis of results signifies that the MLP technique with PCA minimized the …

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 …

Llm For Clinical Named Entity Recognition: A Study On Rag With Pubmed And Umls, Apoorv Tripathi

Electronic Theses and Dissertations 2020 - Present

The first step of biomedical NLP is recognizing clinical named entities, which consist of identifying and categorizing a variety of clinical entities such as diseases, symptoms, genetics, diagnostic tests, procedures, etc. from a body of unstructured clinical text. This study presents a PubMed and UMLS based Retrieval Augmented Generation framework which improves the performance of the Large Language Models to identify clinical entities by providing context. In particular, the framework consists of a two-stage pipeline, where candidate tokens are identified from initial LLM-based classification and refined with retrieved context from either PubMed or UMLS. The proposed framework is assessed across …

Differentiable Objectives For 3d Scene Relighting Via Gradient Descent On Olat Basis Coefficients, Anson Savage

Theses and Dissertations

Designing effective lighting is an iterative and often time-consuming process. This work contributes to automatic lighting design research by presenting a render-engine agnostic optimization routine: gradient descent on RGB multipliers of one-light-at-a-time (OLAT) basis images. We compare several objective functions to accomplish lighting tasks and show that our method is capable of quickly and effectively exploring different lighting styles using either text prompts or reference images. We also present several datasets specific to lighting tasks and show that fine-tuning on these datasets can improve performance.

April 23, 2026, The Daily Mississippian

Daily Mississippian (all digitized issues)

No abstract provided.

April 23, 2026, James Madison University

The Breeze, 2020-

The Breeze is the student newspaper of James Madison University in Harrisonburg, Virginia.

Mechanism Of Improved Miscibility Of Co2–Oil Systems By Multiester-Headgroup Surfactants, Ning Xu, Yanling Wang, Baojun Bai, Yu Zhang, Wenjing Shi, Zhaonian Zhang, Wenhui Ding, Peixu Ma, Zan Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

In the pursuit of carbon neutrality, the CO₂-enhanced oil recovery provides dual benefits by enabling both carbon sequestration and incremental oil production. However, its application is limited by high minimum miscibility pressure. CO₂-philic and oil-affinitive surfactants have emerged as an effective, low-dosage, and cost-efficient strategy to reduce the minimum miscibility pressure. In this study, macroscopic phase behavior experiments combined with molecular dynamics simulations were employed to systematically elucidate the influence of multiester-head surfactants on CO₂–oil miscibility. Using a modified pressure–volume–temperature apparatus equipped with optical power monitoring, we determined that multiester-head surfactants reduced the first-contact …

Exam Analysis: A Quantitative Approach To Software Pedagogy, Christopher Shepard

Theses

Software engineering exams serve as a tool for evaluating a broad range of skills in the classroom, including theoretical understanding, practical application, and process reasoning. Despite their importance, post-assessment analysis is often overlooked, and the absence of structured reflection by instructors can limit their effectiveness and mask patterns in student performance. By treating exams as data, educators can uncover trends that drive more effective teaching strategies, refine evaluation methods, and work to strengthen student support systems. We conducted a systematic analysis of existing exam data and administered a student survey to determine if student perceptions align with actual outcomes, asking …

Synthesis, Structural Elucidation, In Vitro Antibacterial Activity Of Mononuclear Ag(I) Complex Derived From (E)-N-(4-Fluorophenyl)-1-(Pyridin-2-Yl) Methanimine And Triphenylphosphine Ancillary Ligand., Olufemi Stephen Odulaja, Saliu Alao Amolegbe, Muritala Adeniyi Olusola

Tanzania Journal of Science

Chemo-therapeutic application of metal complexes to remediation and subjugation of emerging infectious diseases with a view to improving potency and efficacy of a variety of drugs is gaining more momentum, especially in the 21st century. This research work designed a new biologically active complex [AgL(PPh3)2]NO3,C, obtained from the reaction of Ag(I) nitrate with bidentate pyridinyl Schiff base ligand (E)-N-(4-fluorophenyl)-1-(pyridin-2-yl) methanimine L, with triphenylphosphine (PPh3) as co-ligand. Characterisation was done by FT-IR, UV-Vis, NMR, (TGA/DTA), X-ray crystallography, and elemental analysis. The combined effects of pyridinyl Schiff base ligand and PPh3 on the antibacterial activities against Staphylococcus aureus, Escherichia coli, Klebsiella pneumonia, …

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 …

Grp-02-199 Topological Constraints For Protein Folding, Charles Fanning

C-Day Computing Showcase

We study whether topological loss-based constraints improve multidomain whole-chain protein structure prediction beyond the ColabFold baseline by better preserving the topologies of folded proteins. We benchmark against Wasserstein metrics with our own virtual persistence and RKHS semi-metric constraints as well as higher-order virtual persistence diagrams.

Uc-177-226 Scrapper Kinetics Llc, Mikhail Rudenko, Andrew Torimoto, Jimmy Lock, Marco Cheng

C-Day Computing Showcase

Scrapper Kinetics LLC is a multiplayer and multimodal physics puzzle game. Where players get to choose between playing in VR or Desktop mode, and then, with up to 7 friends (8 players total), try to make a profit in the harsh dead space hulks they have been hired to scrap. We made the game as a test to see how easy it is to have completely different devices interact in the same play space.

Ur-166-204 Multi-User Stem Learning Experience Powered By Llm Conversational Agents, Devon Haynes, Chance Boecker, Oliver Haggard

C-Day Computing Showcase

While Extended Reality (XR) provides experiential and interactive foundations for STEM education, current storytelling and narrative-driven applications often lack responsive nonplayer characters (NPCs), limiting interactive potential through pre-scripted stories. Additionally, despite the growth of Large Language Model (LLM) integration in XR, limited research explores the combined use of multi-user XR systems and conversational Artificial Intelligence (AI) to facilitate real-time, adaptive instruction. This project seeks to address these gaps by 1) Developing a narrative-driven STEM learning XR prototype that incorporates synchronous multi-user interaction and an embedded LLM-driven conversational agent and 2) Exploring the effectiveness of combining these technologies to improve learning …

Ex-04-142 Modeling Distress And Evaluating Chatbot Safety For Suicide-Related Social Media Texts, Rehma Razzak

C-Day Computing Showcase

This project addresses the urgent need for transparent chatbot safety evaluations amid rising concerns about AI-facilitated self-harm. Using public social media datasets, we simulate two tasks: (1) detecting suicidal ideation via emotion-based risk scoring, and (2) stress-testing a support-style chatbot against 888 high-risk prompts, including euphemisms and “for a story” framing. A multi-label classifier trained on GoEmotions feeds emotion profiles into a logistic regression model to generate suicidality risk scores. These scores guide a local chatbot built with Ollama’s llama3, which analyzes user messages and steers responses toward safe, empathetic behavior. Evaluation shows ~90% of replies were safe or supportive. …

Gc-113-125 Carter’S Lake Visitor Center Boating Safety Game, Hunter Blake, Chancelor Brown, Lauren Robbins, Will Bryant, Kendrick Bryant

C-Day Computing Showcase

The Boating Safety Game is an educational, kiosk-based touchscreen game created for the U.S. Army Corps of Engineers and the Carters Lake Visitor Center. It is designed to improve the knowledge and engagement of boating safety concepts for visitors, particularly for students and youth. The project was developed using multiple game scenarios meant to reinforce safe boating practices through tutorial scenes, top down navigation, life jacket and required item selection tasks, and player motivation through quizzes, feedback, scores, and a star ranking system. The game’s design emphasizes accessibility and retention through simple touchscreen interaction, guided instruction, and repeated feedback on …