Physical Sciences and Mathematics Commons^™

Soil Health In Nebraska: Exploring Practitioners' Needs And Insights From A Long-Term Organic Farm, Ingrids Isabel Mata Vigil

Department of Agronomy and Horticulture: Dissertations, Theses, and Student Research

Soil health is foundational to sustainable agriculture, environmental resilience, and long-term food security. Yet, the adoption of soil health assessments remains limited, often perceived as too technical, costly, or difficult to implement in real-world contexts. To better understand these challenges, the first chapter presents findings from a statewide survey of 41 soil health practitioners in Nebraska, including farmers, extension educators, NRCS staff, and conservation professionals. Respondents highlighted the need for simpler, more accessible, and context-specific tools for soil health assessment that help practitioners make informed decisions aligned with their management goals. Complementing these insights, the second chapter includes an independent, …

Future-Proofing Careers: Unlocking The Potential Of Ai-Driven Digital Badges, Harika Rao

Faculty and Staff Publications & Presentations

This poster explores the transformative role of AI-driven digital badges and microcredentials in addressing the urgent need for adaptable, workforce-ready graduates in an era of rapid technological change. By offering personalized, stackable, and industry-aligned credentials, higher education institutions can empower learners with just-in-time skills that traditional degree programs often fail to provide. This poster highlights how AI can support granular competency assessment, flexible online delivery, and lifelong learning pathways, enabling students to showcase evidence of skill mastery in ways that are both affordable and scalable.

Exploring Communication In Multi-Agent Cooperative Reinforcement Learning, Matthew Kalarickal

Math and Computer Science Honors Theses

This work focuses on communication strategies within a cooperative multi-agent reinforcement learning system. The goal is to explore how communication can be used among agents to potentially improve performance. The research operates within the scope of “learning tasks with communication,” where the primary aim is to solve domain-specific tasks through information exchange using explicit communication protocols. Three distinct communication strategies were implemented and explored: Combinatorial Ghost, Feature Sharing Ghost, and Move Sharing Ghost. Fully Centralized Training and Execution and Centralized Training with Decentralized Execution training approaches were based on the different communication strategy used. Performance metrics were recorded for these …

Exploring Subfield Interest Development In Undergraduate Physics Students Through Social Cognitive Career Theory, Dina Zohrabi Alaee, Benjamin M. Zwickl

Physics and Engineering Science

This study investigates how undergraduate physics majors develop an interest in specific subfields. We examine interest formation through the lens of social cognitive career theory (SCCT) using four SCCT constructs: learning experiences, self-efficacy, outcome expectations, and proximal environmental influences. We conducted 27 interviews with physics majors across multiple years of study between 2020 and 2022. Our first research question used SCCT constructs to provide detailed insights into factors affecting interest formation in various subfields of physics. We identified many factors that positively impacted students’ interests, such as positive learning experiences (e.g., coursework, experimental projects, extracurricular clubs, and self-directed learning), high …

Direct Coupling Of Continuum And Shell Elements In Large Deformation Problems, Astrid Pechstein, Michael Neunteufel

Mathematics and Statistics Faculty Publications and Presentations

In many applications, thin shell-like structures are integrated within or attached to volumetric bodies. This includes reinforcements placed in soft matrix material in lightweight structure design, or hollow structures that are partially or completely filled. Finite element simulations of such setups are highly challenging. A brute force discretization of structural as well as volumetric parts using well-shaped three-dimensional elements may be accurate, but leads to problems of enormous computational complexity even for simple models. One desired alternative is the use of shell elements for thin-walled parts, as such a discretization greatly alleviates size restrictions on the underlying finite element mesh. …

Urbanization And Earthquake Resilience In The Kathmandu Valley, Alex Nation

Nepal: Geoscience in the Himalaya

The Kathmandu Valley is the fastest growing city in South Asia and is developing in a haphazard manner, subsequently creating an unnecessary earthquake risk. Few papers have been published regarding the development of Kathmandu and its surroundings as a whole and relating it to earthquakes. This study conducted visits to some cities in the valley and analyzed the infrastructure, architecture and engineering, as well as city layout. It was discovered that zoning is completely absent in the region and planning attempts are unable to keep up with the rate of expansion. Further awareness, enforcement of codes, and zoning is needed …

Strategies For Thoughtful Dissemination Of Climate Change Knowledge: A Blueprint For Scientists In The Heart Of The Empire, Christopher Cronk

Nepal: Geoscience in the Himalaya

This interdisciplinary research investigates how climate change education, Indigenous knowledge systems, journalism, and anthropology intersect in shaping environmental awareness and action, focusing primarily on Nepal and drawing parallels with Indigenous Peoples of Turtle Island (North America). Stationed in Kathmandu, I conducted interviews with climate educators, journalists, anthropologists, and activists to explore how scientific and local knowledge are communicated and acted upon. Findings highlight the strong awareness of climate change in Nepal, the systemic barriers to effective mitigation and adaptation, and the potential of community-led initiatives like the Community Forest Program. Anthropological insights proved crucial in linking human experience to environmental …

A Preliminary Classification And Quantification Of The Microplastics Within Remote Glacial Runoff In The Upper Manang Region Of Nepal, Caden Lipsky

Nepal: Geoscience in the Himalaya

Microplastics, defined as particles of plastic waste less than 5mm (US EPA), are becoming steadily more common throughout remote ecosystems and are damaging to human and environmental health. The level of microplastics found in water sources within remote regions has become increasingly concerning following growing influxes of tourists and residents each year. These particulates found in freshwater have historically only been found downstream of populated areas; however, more recent cases have demonstrated their appearance at higher elevations and lower population water sources. This study aims to develop a preliminary understanding of the amount and type of contamination that has occurred …

Geological And Cultural Investigation Of Clay Used In Newari Pottery, Inés Fabián-Hicks

Nepal: Geoscience in the Himalaya

This research project investigated the geological and cultural aspects of clay used in traditional Newari pottery in Nepal. The study aims to compare the particle-size distribution of raw clay directly sourced from traditional deposits with that of processed clay prepared for pottery production. Methodologically, the project will employ a combination of mechanical sieving and hydrometer analysis to generate detailed grain-size distribution charts for both clay types. In addition to laboratory analysis, the project incorporates a cultural dimension through a field visit to Pottery Square, an interview with a Newari potter, and a field visit to the source of the clay …

Examining Equitable Participation With K-12 Teacher Leaders, Eva Thanheiser, Kathryn Elizabeth Roman, Ruth Heaton

Mathematics and Statistics Faculty Publications and Presentations

Many organizations and researchers in mathematics education call for antibias practices, but addressing hidden biases remains challenging. Equity QUantified In Participation (EQUIP), a quantitative tool designed to analyze classroom participation patterns by social markers, helps teachers identify these subtle inequities. This paper describes a professional development (PD) intervention introducing EQUIP to five teacher leaders (TLs) and three coaches in a predominantly Latine district, focusing on setting up EQUIP to identify and address participation inequities in their classrooms. The TLs implemented EQUIP in their classroom and gathered participation data twice. Findings revealed that TLs took up EQUIP in different ways and …

Response Of Wheat To Phosphorus-Enriched Ironstone Gravel, David Weaver, David Rogers, Ron Master, Peta Richards, Robert Summers, Simon D V Clarendon

Grain and Other Field Crops Research Articles

Context

Gravel fractions ( > 2 mm) in soil are almost always excluded from laboratory analysis and glasshouse experiments as they are considered to be inert; however, the > 2 mm fraction is always present in field experiments. Aims

To determine whether the > 2 mm fraction of ironstone gravel (IG) soil enriched with phosphorus (P) can supply P to wheat (Triticum aestivum L.). Methods

An IG soil was separated into different size fractions ( < 2, 2–4, 4–6, 6–8 and 8–10 mm), and adsorption and desorption experiments, volumetric moisture measurements and glasshouse experiments were conducted. Each of the > 2 mm fractions were enriched with P to different levels and added to a sand culture, or to the enriched < 2 mm fraction in different amounts (25%, 50% and 75% IG). Wheat was grown in pots and growth correlated to P added from enriched soil fractions, weighted Colwell P, soil solution P concentrations and volumetric water content. Key results

The < 2 mm fraction of the IG soil adsorbed more P than the > 2 mm fraction of the IG …

Chat With The ’For You’ Algorithm: An Llm-Enhanced Chatbot For Controlling Video Recommendation Flow, Shuo Niu, Dikshith Vishnuvardhan, Venkata Sai Reddy Punnam

Computer Science

The rise of short-form video platforms like TikTok, driven by algorithmic recommendations, fosters immersive flow experiences. While users value personalization and engagement, they also seek greater agency over their For You recommendations. This paper designs, prototypes, and evaluates TKGPT, an LLM-enhanced conversational interface that helps users articulate their interests and understand recommendations. Through qualitative interviews and a user study, we examine how the TKGPT influences algorithmic folk theories and the sense of agency. Findings show that users primarily use TKGPT to seek relevant videos, explain preferences, and exert control over the algorithm. The resulting For You videos better reflect user …

Retraction: A Database Of Teleseismic Shear-Wave Splitting Measurements For The Ordos Block And Adjacent Areas(Seismological Research Letters (2022), 93, 5, (2731–2739), 10.1785/0220210310), Lin Liu, Stephen S. Gao, Kelly H. Liu, Tu Xue, Yan Jia, Sanzhong Li

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

An earlier version of this article (Liu et al., 2022) included private data from the Himalayan-III program which should not have been made public. The authors acknowledge and regret their negligence during the selection of the measurements. The impacted data represent only 2.7% of the total data published in this article, and after review, the authors and the editors agree that this unintentional error has no bearing on the work's scientific conclusions. Therefore, we are retracting the impacted data and have made corrections to remove any Himalayan-III program data from the article's text, figures, and supplemental tables.

Investing Hysteresis In Floodplain Dynamics Of Lakes In The Middle St. Johns River Using Sentinel-1 Sar Imagery, Keenan Hubbard

Doctoral Dissertations and Master's Theses

Floodplain dynamics are often complex, with hysteresis potentially affecting the temporal relationship between flood stage and flood extent during subsequent inundation phases. This study leverages Sentinel-1 synthetic aperture radar (SAR) imagery to map flood extent in the Middle St. Johns River Lake floodplains and examine the presence of hysteresis during flood events. SAR scenes corresponding to river gauge readings were analyzed from the rising and falling limbs of a flood hydrograph. By comparing these flood maps, we assess differences in inundated areas at equivalent water levels during each stage of the flood event. The findings aim to enhance flood monitoring …

Experimental Analysis Of Satellite Operator Training Using Game-Based Virtual Reality Simulation, Lana Laskey

Doctoral Dissertations and Master's Theses

Satellite data plays a vital role in modern global infrastructure by enabling communications, navigation, and weather forecasting. As demand for satellite technology grows, so does the need for highly trained satellite ground operators. Traditional training regimens for satellite operators employ simulation using two-dimensional computer console displays paired with the varied ability of trainees to generate abstract mental imagery of the scenario. However, this development of mental imagery imposes a considerable learning curve and cognitive workload on the trainee, which may negatively impact the user experience and knowledge gained during the training scenario.

This experimental study investigated the effects of game-based …

Aircraft Bird Strike Risk Prediction Using Machine Learning And Analytic Hierarchy Process, Jason Anthony Powell

Doctoral Dissertations and Master's Theses

To address the limitations of Next Generation Radar-based bird strike forecasting, this study modeled 12 spatiotemporal weather features from the National Oceanic and Atmospheric Administration alongside bird strike risk using Long Short-Term Memory Recurrent Neural Network (LSTM-RNN), XGBoost regression tree, and Bayesian network algorithms. Five years of bird strike data from four geographically diverse airfields served as the target risk variable, categorized as low, moderate, or severe based on Department of the Air Force risk models. The ensemble model, which combines the LSTM-RNN and XGBoost regression algorithms, yielded the most accurate forecasts, achieving 80% to 93% accuracy across all airfields, …

Graduate School Blog - July 2025 Volume 1, Cynthia Haynes

UofM Grad School Blog

The July 2025 UofM Graduate School Blog – Volume 1 continues the Cost of Graduate School Guide with a deep dive into hidden and variable expenses such as residency-based tuition differences, program-specific fees, and differential tuition. The blog provides practical tips for prospective students on how to ask the right financial questions when comparing programs. It also features a student spotlight on Billy Brooks, a dual MHA/MBA candidate motivated to transform healthcare access and equity. Upcoming events include a Virtual Fall 2025 Open House with Financial Aid and USBS, a Dissertation Writers Retreat, and both in-person and virtual Graduate Student …

The Discontinuous Petrov–Galerkin Method, Leszek Demkowicz, Jay Gopalakrishnan

Mathematics and Statistics Faculty Publications and Presentations

The discontinuous Petrov–Galerkin (DPG) method is a Petrov–Galerkin finite element method with test functions designed for obtaining stability. These test functions are computable locally, element by element, and are motivated by optimal test functions which attain the supremum in an inf-sup condition. A profound consequence of the use of nearly optimal test functions is that the DPG method can inherit the stability of the (undiscretized) variational formulation, be it coercive or not. This paper combines a presentation of the fundamentals of the DPG ideas with a review of the ongoing research on theory and applications of the DPG methodology. The …

Thematic Hotspots And Strategy Analysis Of International Ai Regulatory Texts Based On Lda Models, Taitian Mao, Yihe Peng

Journal of Scientific Information Research

[Purpose/significance]This article conducts an in-depth exploration of international artificial intelligence (AI) regulatory policies and gains insights into the regulatory focuses and trends of various countries, with the aim of providing valuable references for global AI governance strategies.

[Method/process] This paper applies the LDA topic clustering analysis method to conduct an in-depth study of twenty-seven international policy documents. The aim is to accurately identify the topics, analyze the key theme words, and further reveal the regulatory hotspots in the field of artificial intelligence.

[Results/conclusion] The study reveals six core regulatory themes: systemic risk assessment, ethical and legal regulation, social impact governance, …

Customizing Ai Strategies Across Multiple Generations, Matthew Harrer

Theses

This project investigates how artificial intelligence can help brands and marketers connect more effectively with Generation X, Millennials, and Generation Z. The literature review lays the groundwork that focuses on consumer behaviors and the integration of AI into digital marketing practices for each generation. The second part of the project involves a secondary data analysis of 21 recent marketing surveys and reports that explores topics related to trust, personalization, and social media. By integrating the findings into an insightful guidebook, marketers will be able to maximize these insights into clear actionable strategies.

Serving Others Using Generative Ai, Kenneth C. Arnold

University Faculty Publications and Creative Works

Ken Arnold, computer science professor at Calvin University, explores the idea of use Generative AI as a tool to help us serve others.

Artificial Insights Or Historical Fidelity? Crafting An Ethical Framework For The Use Of Genai In The Restoration, Reconstruction And Recreation Of Movable Cultural Heritage, David Ocón, Chunzhi Yin, Jose Luna

Research Collection School of Social Sciences

This article explores the ethical considerations surrounding using Generative Artificial Intelligence (GenAI) in preserving movable cultural heritage, focusing specifically on its application in restoration, reconstruction, and recreation. While GenAI offers innovative methods for preserving and recreating cultural heritage, it also presents significant ethical challenges. The article reviews current studies on the role of GenAI in heritage preservation alongside relevant ethical guidelines and proposes a tailored ethical framework for its application in movable heritage. The framework addresses several critical ethical concerns, including cultural integrity and sensitivity, accuracy and authenticity, intellectual property rights, sustainability and social impact, and governance and ethical accountability. …

The Ethics Of Consent: Reflecting On The Case Of R/Changemyview, Casey Fiesler, Jessica Vitak, Michael Zimmer

Computer Science Faculty Research and Publications

The SIGCHI Research Ethics Committee was established in 2016 in recognition of how the shifting technological landscape has complicated research ethics in HCI. Our research community has also taken up the call to help understand and guide this complex space, examining topics such as research taking place on online platforms without explicit consent, the use of bots as confederates in field experiments, debriefing for large-scale experiments, HCI research that involves or implicates marginalized populations, and ethical considerations for studying social media platforms such as Reddit.

Analysis Of Vision Transformers And Domain Adaptation In Long-Range Facial Recognition, Zachary Michael Swanson

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Atmospheric turbulence presents a significant barrier to long-range facial recognition, introducing severe geometric distortions and blur that degrade image quality. This thesis investigates deep learning approaches for mitigating these effects, with a focus on transformer based architectures and domain adaptation strategies.

An in-depth benchmarking study was performed using convolutional neural networks (CNNs) and vision transformers (ViTs) on the Husker BRIAR Research Collection from up to 500m (HBRC-500) face dataset. The results demonstrated that vision transformers, particularly hierarchical vision transformers like the shifted-window (Swin) transformer, outperform CNN-based models at long distances due to their ability to model global spatial relationships and …

Biocomputing Approach To Modeling And Modulating Calcium Signaling, Sehee Sun

School of Computing: Dissertations, Theses, and Student Research

Biocomputing is an emerging field that seeks to perform computational tasks using biological substrates and processes. Unlike conventional computing systems based on silicon hardware, biocomputing leverages the parallelism, energy efficiency, and complex dynamics of living systems. Among various cellular mechanisms, calcium (Ca2+) signaling stands out as a central regulator of diverse biological functions, offering a promising basis for programmable logic and control in living cells.

This thesis introduces a novel framework for modeling and modulating Ca2+ dynamics using biologically inspired Boolean logic circuits. Specifically, we propose the Ca2+ Boolean Logic (CaBL) model, in which Ca2+ fluxes and interactions are abstracted …

Bridging Knowledge Gaps In Digital Forensics Using Unsupervised Explainable Ai, Zainab Khalid, Farkhund Iqbal, Mohd Saqib

All Works

Artificial Intelligence (AI) has found multi-faceted applications in critical sectors including Digital Forensics (DF) which also require eXplainability (XAI) as a non-negotiable for its applicability, such as admissibility of expert evidence in the court of law. The state-of-the-art XAI workflows focus more on utilizing XAI tools for supervised learning. This is in contrast to the fact that unsupervised learning may be practically more relevant in DF and other sectors that largely produce complex and unlabeled data continuously, in considerable volumes. This research study explores the challenges and utility of unsupervised learning-based XAI for DF's complex datasets. A memory forensics-based case …

Toward A Simplified Framework For Sequential Character Recognition, Nicholas Howe

Computer Science: Faculty Publications

This paper proposes a novel approach to handwritten charac- ter recognition using convolutional non-recurrent deep neural networks. Such a network can run in parallel at every point of a document, offer- ing potential advantages in speed over recurrent approaches. The net- work’s output feeds into a beam search optimization for final decoding. Preliminary quantitative results show that the framework can achieve bootstrap training from labeled word images. It provides an alternative to sequential models that rely on connectionist temporal classification for alignment.

Quantum Simulation Of Molecular Dynamics Processes─A Benchmark Study Using A Classical Simulator And Present-Day Quantum Hardware, Tamila Kuanysheva, Brian K. Kendrick, Lukasz Cincio, Dmitri Babikov

Chemistry Faculty Research and Publications

We explore how the fundamental problems in quantum molecular dynamics can be modeled using classical simulators (emulators) of quantum computers and the actual quantum hardware available to us today. The list of problems we tackle includes propagation of a free wave packet, vibration of a harmonic oscillator, and tunneling through a barrier. Each of these problems starts with the initial wave packet setup. Although Qiskit provides a general method for initializing wave functions, in most cases it generates deep quantum circuits. While these circuits perform well on noiseless simulators, they suffer from excessive noise on quantum hardware. To overcome this …

Mixed Quantum/Classical Theory Approach To Rotationally Inelastic Molecular Collisions Implemented On A Quantum Computer, Jonathan Andrade-Plascencia, Tamila Kuanysheva, Dulat Bostan, Brian K. Kendrick, Dmitri Babikov

Chemistry Faculty Research and Publications

All elements of a quantum algorithm for calculations of rotationally inelastic molecule + atom scattering within the framework of a mixed quantum/classical theory are outlined. In this approach, the rotational motion of the molecule is described quantum mechanically using the time-dependent Schrödinger equation, while the scattering process of two collision partners is treated classically. The matrix of potential coupling is precomputed on a classical processor, whereas the quantum hardware is used to propagate the system of coupled equations for the rotational state-to-state transitions. All quantum circuits needed for practical implementation of the algorithm are presented. First, the quantum codes written …

Aiding Depth Perception In Initial Drone Training: Evidence From Camera-Assisted Distance Estimation, John Murray, Steven Richardson, Keith Joiner, Graham Wild

Research outputs 2022 to 2026

Remotely Piloted Aircraft (RPA) pilots frequently experience difficulties with depth perception, particularly when estimating distances between the drone and environmental obstacles. This study evaluates whether the use of onboard camera imagery can improve exocentric distance estimation accuracy among ab initio drone pilots operating under visual line-of-sight (VLOS) conditions. Two groups of undergraduate students performed distance estimation tasks at 20 and 50 m. One group used direct observation only to estimate the exocentric distance between the drone and an obstacle. The second group, as well as direct observation, had access to a live video feed from the drone’s onboard camera via …