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Examining Short Term Drainage Impacts To Soil Health In Hydric And Non-Hydric Soils Of Waseca County, Minnesota, Ely Hartl

All Graduate Theses, Dissertations, and Other Capstone Projects

Subsurface drainage is implemented throughout the Midwest United States to remove excess moisture from soil to enhance crop growth. Hydric soils are ubiquitous throughout Minnesota and are commonly drained due to their historically saturated conditions. Changing a soil's hydrology can impact its formation and properties. The alteration of physical, biological, and chemical soil properties can occur to both hydric and non-hydric soils, impacting overall soil health. The purpose of this study is to examine the short-term effects of tile drainage on the soil health of hydric and non-hydric soils in southern Minnesota. Research methods include: 1) collect soil-sediment cores to …

Functionalized 2d Hexaazatriphenylene As Hydrogen Storage Platform: A Dft-Guided Design Approach, Islam Gomaa

Nanotechnology Research Centre

No abstract provided.

Predicting Capture And Survival Probabilities Of The Arizona Tiger Salamander: A Comparison Of Capture-Recapture Models, Brittney Nelson

Murray State Theses and Dissertations

Capture-recapture models are essential tools for estimating population dynamics in ecological studies. A fundamental component of these models is the capture history matrix, which records individual detection over time and serves as the basis for estimating survival and capture probabilities. This presentation explores three statistical approaches to these estimations: the Cormack-Jolly-Seber (CJS) model, the Hidden Markov Model (HMM) for CJS, and the Bayesian CJS model. The CJS model provides a likelihood-based framework for estimation, and the HMM CJS incorporates latent states into the model to account for uncertainty in detection. The Bayesian CJS extends this same analysis by integrating prior …

New Psychoactive Substances Detected In Wastewater Samples Collected Along The Interstate Highway Rest Areas In Kentucky, Durga Prasad Kodati

Murray State Theses and Dissertations

The rapid emergence and proliferation of new psychoactive substances (NPS) pose significant challenges to public health and law enforcement. The potential for abuse and toxicity of these substances, which are intended to mimic the effects of controlled drugs, has been raising concerns as these compounds are designed to evade being regulated. There are traditional methods of tracking NPS, such as seizures and forensic toxicology, but they are delayed and seldom effective because these substances continue to evolve rapidly. Wastewater-based epidemiology (WBE) has emerged as a promising tool for real-time surveillance of drug consumption. The primary objective of this research was …

Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu

Psychology Faculty Publications

Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …

The Sustainability Of The Outdoor Recreation Industry: Studied Through Mountaineering In Teton County, Wy, Samantha Olstein

Student Research and Publications

No abstract provided.

Optimizing Decision-Making In A Cerebral Palsy Model Using Reinforcement Learning, Richard Ampah

Pitzer Senior Theses

This study presents an original interdisciplinary investigation into how reinforcement learning (RL) can model motor and cognitive defects and potentially improve motor and cognitive functions in individuals with cerebral palsy (CP), a non-progressive neurological disorder that impairs movement and adaptability. Integrating computational neuroscience and machine learning, the research applies policy gradient methods and Markov Decision Processes (MDPs) to simulate adaptive learning in agents with and without CP-related constraints.

The central aim is to compare the cumulative rewards of optimal policies, derived from value iteration, and human-like learning policies using the REINFORCE algorithm, both with and without the Bellman baseline. The …

Predicting Human Steering From Optic Flow Using Deep Convolutional Neural Networks, Katie E. Bernard

Honors Theses

Human driving is a complex visuomotor task and the specific visual clues that guide it remain under investigation. While prior research has emphasized gaze-based strategies such as the Tangent Point and Future Path hypotheses, recent evidence highlights the potential role of optic flow, the visual motion pattern perceived during self-movement, as critical to steering ability. This thesis explores whether raw optic flow alone can support accurate predictions of human steering behavior. We trained a convolutional neural network to map optic flow vector fields to steering angles in a virtual reality driving simulation. The dataset, collected by Giguere et al., included …

Wave Reflections In A Biophysically Detailed Model Of Cardiac Tissue, Grace Moberg

Honors Theses

Regular heart rhythms are governed by the coordinated spread of action potentials through cardiac tissue. The interaction of an action potential with a tissue heterogeneity may lead to a reflection, where both a retrograde and an anterograde wave propagate off of the initial impulse. Reflections have been experimentally linked to cardiac arrhythmias, but their mechanisms of generation are not well-understood. Mathematically, reflections in phenomenological models of cardiac tissue have been linked to an unstable periodic orbit. These models typically sacrifice detail about the variety of ionic currents and processes involved in action potential propagation in favor of mathematical simplicity. Biophysically …

Identifying The Spread Of Invasive Jumping Worms Across Maine’S Forests Using Soil Edna, Rebecca Wanger

Honors Theses

Jumping worms of the Megascolecidae family are invasive earthworms from East Asia that have been spreading across the United States since the late 1800s (Chang et al., 2021). Recently, the earthworms have gained more attention for their expansion into northeastern states, as they are believed to have negative impacts on the soil biogeochemistry, flora, and fauna of these forest ecosystems that have had no native earthworms given the recent nature of the Last Glacial Maximum (~11,000 yrs ago; Bohlen et al. 2004; McCay et al. 2020). The earthworms are distinguished by their thrashing behaviors, milky-white smooth clitellum, and evenly spaced …

From Walking To Parkour: A Structured Survey Of Rl For Dynamic Skills In Legged Robots, Christopher Allred, Chandler Justice, Rosario Scalise, Yan Gu, Jonathan Clark, Mario Harper, Jason Pusey

Computer Science Student Research

This survey reviews recent advances in applying reinforcement learning (RL) to enable dynamic and ballistic motions in legged robots, including running, jumping, stair climbing, and parkour. Focusing on high-agility behaviors that challenge traditional control frameworks, we categorize foundational locomotion tasks and highlight the RL methods, such as Proximal Policy Optimization, curriculum learning, and hybrid model-based strategies that have proven effective. We discuss the key challenges in transferring learned policies to real-world robots, managing uncertainty, and integrating perception and proprioception. Drawing from over 150 recent works, we provide a structured taxonomy of objectives, algorithms, and platforms, and identify trends in simulation …

Applying Machine Learning Methods To Generate Understandings Of Differential Item Functioning In A Flu Knowledge Assessment, William L. Romine, Tanvi Banerjee, Derrick Cox

Computer Science and Engineering Faculty Publications

Current influenza trends, including the severity of the 2025 flu season and the prevalence of H5 bird flu in livestock, necessitate efforts to better understand how to educate students about its transmission. Although validated assessments of influenza knowledge exist, these have not been evaluated for affective and demographic biases. We explore differential item functioning (DIF) effects in four items focused on specific aspects of flu transmission derived from a validated influenza knowledge assessment. In doing so, we introduce and utilize a machine learning framework for exploration of DIF which offers greater flexibility than traditional statistical approaches in terms of studying …

Spatial Analysis Of American Chestnut (Castanea Dentata) Distribution And Ecology In Kentucky’S Federal Lands, Jacob Raymond Pease

Murray State Theses and Dissertations

Anthropogenic factors have been the cause of the decline of tree species across the globe. From unsustainable logging and development to disease and improper management, threats to forests have taken their toll. The American chestnut (Castanea dentata) was once an integral basal tree species in Appalachian forests, but chestnut blight drove the species to functional extinction by the mid-1900s. The recent creation of genetically modified chestnuts gives hope for future restoration of the species throughout its historical range. Despite blight resistance, effective restoration will require optimal site selection for finding and planting chestnuts, which will maximize limited resources. …

Comparative Study Of Single Imputation Techniques For The Prediction Of Missing Dairy Data, Ahmed M. Gad Prof, Ahmed Abdelhakim Ahmed Mr, Eman Manaa Prof, Basant Shafik Dr, Sakr Mostafa Prof

Business Administration

Dairy farm records are a crucial component of effective livestock business management. Record analysis allows a farm’s owner to make informed decisions. Incomplete records are less useful for data analysis, so it's important to handle missing values correctly. This study compares different imputation methods for handling missing values in a dataset of dairy records comprising 997 records collected from 234 cows between 2012 and 2022. The dataset was screened against records with missing values and then deleted, resulting in 858 observations from 200 animals. There were missing values in two variables, with a missing percentage of 13.9%: days in milk …

Identifying Intangible And Biocultural Heritage Elements Toward Environmental Understanding: Engaging Stakeholders Through Art, Martha B. Lerski

Publications and Research

Grounded in a case study in Barbuda in the Caribbean, this research examines sustainability from the perspective of what arts and heritage can contribute to community engagement and local and broader understandings about the environment. This article documents a growing body of literature recognizing the role of arts and culture, including local knowledge and traditional ecological knowledge (TEK), in climate change endeavors. Art and TEK present expansive world views. Contextual information situates research done on the island of Barbuda pre- and post-Hurricane Irma. Visual arts workshops engaged community members in mixed methods research. Results documented cultural elements, particularly intangible and …

Farm Profit Impacts Of Consecutive Drought Years Under Climate Scenarios In Southwestern Australia, Sud Kharel, Kevin J. Foster, Meredith M. Guthrie, Ross Kingwell

Climate Science Research Articles

Climate projections for southern Australia indicate an increased likelihood of years of consecutive droughts. How resilient are farm businesses and their farming systems to recover from episodic drought? This study assesses the farm economic and financial impacts of consecutive droughts in southwest Australia. Bioeconomic simulation modelling of farm businesses with different farming systems at three locations is used to examine the long-term financial consequences of consecutive droughts. Various key factors affecting those consequences are examined. Farm location, farming system and starting equity are found to be the main determinants of how quickly a farm business can financially recover from the …

The Future Of Shipping At The Biodiversity-Climate Nexus : Round Table Report, Mary S. Wisz, Fabio Berzaghi, Mikaela Gomez, Maud C. Quinzin, Renis Auma Ojwala, Emily Nuckolls

Reports

This report presents the outcomes of a cross-disciplinary Round Table hosted by the World Maritime University (WMU) from May 13-15, 2024, in Malmö, Sweden. The event brought together 51 experts from academia, industry, NGOs, and international organizations, including the IMO, to explore shipping’s role at the biodiversity-climate nexus. The Round Table had a particular focus on the impacts of shipping that are currently unregulated or under-regulated, and opportunities to address biodiversity loss and pollution as the sector decarbonizes. The report highlights the need to apply comprehensive, ecosystem-based approaches to effectively manage shipping's impacts, including cumulative impacts, on the environment, people, …

A Vision Transformer Based Assistive System For Dermatological Diagnosis In Systemic Lupus Erythematosus, Syeda Lamima Farhat

All Graduate Theses, Dissertations, and Other Capstone Projects

Systemic Lupus Erythematosus (SLE) is a complex and often underdiagnosed autoimmune disease that affects multiple organs and presents with a wide range of symptoms-ranging from fatigue and joint pain to life-threatening organ damage. One of its most visible and diagnostically significant indicators is the Butterfly Malar Rash (BMR), a distinctive facial rash that often resembles other common dermatological conditions like rosacea, acne, eczema, and fifth disease. This overlap can lead to misdiagnosis or delayed detection, especially in busy clinical environments. To assist dermatologists in distinguishing BMR from similar facial rashes, this study explores the development of an AI-powered image classification …

Identifying All Matches Of A Rigid Object In An Input Image Using Visible Triangles, Abdullah N. Arslan

Faculty Publications

It has been suggested that for objects identifiable by their corners, every triangle formed by these corner points can serve as a reference for detecting other corner points. This approach enables effective rigid object detection, including partial matches. However, when there are many corner points, the implementation becomes impractical due to excessive memory requirements. To overcome this, we propose a new algorithm that leverages Delaunay triangulation, considering only the triangles generated by the Delaunay triangulation to reduce the complexity of the original approach. Our algorithm is significantly faster and requires significantly less memory, offering a viable solution for large problem …

Program And Proceedings: Nebraska Academy Of Sciences 1880–2025, 145th Anniversary Year, One Hundred-Thirty-Fifth Annual Meeting

Nebraska Academy of Sciences: Programs and Proceedings

Program

Aeronautics and Space Science

Biological and Medical Sciences

Biology

Chemistry

Earth Sciences

Science Education

Anthropology

Applied Science and Technology

Physics and Engineering

Forensic Sciences

Ecology, Sustainability, and Environmental Science

Maiben Lecture: Mary Ann Vinton, "State of the Academy"

Friends of Science Awards: David Crouse and Daniel Sitzman

Quantifying The Vulnerability Of Smooth Dogfish And Winter Skate To Electromagnetic Fields From Offshore Wind Transmission Cables In The Mid-Atlantic Shelf, Rachel A. Sechrist

Theses, Dissertations and Culminating Projects

The development of offshore wind structures in the northeastern U.S. will contribute to renewable energy goals, but will overlap with many marine species as well as economically important fisheries. High voltage transmission cables from offshore wind farms emit electromagnetic fields (EMFs) that elasmobranchs may detect using sensory organs known as ampullae of Lorenzini. However, sensitivity to EMFs varies by species due to differences in the number and arrangement of pores, the length of subdermal canals within the ampullae of Lorenzini sensory network, and the habitats they reside and regions they forage. For species who reside or forage in benthic regions, …

Data Analysis For Maintenance Reliability., Romulo Menezes Santos

ICT

This project explores the application of predictive maintenance (PdM) in modern manufacturing, highlighting its strategic role in reducing downtime, optimising resources, and improving operational efficiency. Traditional reactive and preventive maintenance approaches are insufficient for Industry 4.0 environments, where machine failures can cause significant financial and operational losses. By leveraging sensor data, historical performance records, and machine learning techniques, PdM enables early detection of potential equipment failures, allowing maintenance teams to act proactively. The approach not only enhances operational reliability and safety but also supports strategic decision-making, cost control, and competitive advantage in globalised manufacturing contexts.

Zinc Or Swim: Investigating Zinc Pollution From Restoration Materials, Megan R. Jensik

Honors Undergraduate Theses

Zinc is an essential nutrient, but can be toxic at high concentrations, negatively affecting various biological functions. Gabions are galvanized metals coated in zinc that are used for many human purposes, including coastal restoration efforts attempting to avoid using plastic materials. However, gabions can degrade in marine environments, potentially leaching metal into the water and soil. There is a knowledge gap regarding the occurrence and impacts of zinc pollution in the areas where these gabions are deployed, including the Indian River Lagoon (IRL). To address this, sediment samples were collected from the IRL and analyzed for their physical and chemical …

Humans Vs. Llms On Open Domain Scientific Claim Verification: A Baseline Study, Benjamin Curtis, Stefania Dzhaman, Matthew Maisonave, Jian Wu

Computer Science Faculty Publications

Verifying scientific claims is challenging for the general public because most people lack domain knowledge. Manual verification by subject domain experts is accurate, but it is obviously not scalable to meet the rising number of scientific claims on the Web. Whether the emerging large language models and large reasoning models can be used for scientific claim verification, and how their performances compare to humans, are still research questions. To this end, we developed a new benchmark MSVEC2 that consists of 138 claims from credible fact verification websites and science news outlets. Two tasks were given to both human and LLM …

Characterizing Language Use In Online Accessibility Discussion Forums, Nithiya Venkatraman, Anand Ravi Aiyer, Yash Prakash, Sampath Jayarathna, Hae-Na Lee, Vikas Ashok

Computer Science Faculty Publications

Discussion forums are one of the favored platforms for knowledge sharing. Given their popularity, copious research exists on understanding the linguistic and behavioral characteristics of forum conversations, so as to inform the design of many downstream applications including discourse visualization, sentiment analysis, and question answering. However, prior investigations have mainly focused on general forums designed primarily for sighted users, and as such the applicability of their findings to dedicated accessibility discussion forums frequented by blind screen reader users remains unanswered. To bridge this knowledge gap and facilitate the development of better-informed assistive technologies for blind people, we investigated language use …

Human Perception Of Ai Capabilities At Classifying Perturbed Roadway Signs, Katherine R. Garcia, Jing Chen, Yanru Xiao, Scott Mishler, Cong Wang, Bin Hu

Computer Science Faculty Publications

Artificial Intelligence (AI) is crucial to numerous functions required for driving automation systems, including the computer vision techniques used to detect the roadway environment and make real-time decisions. However, the images used as inputs to the AI system may be maliciously perturbed, or manipulated, causing the AI system to make an incorrect classification. In this study, we examined humans’ perception of the AI’s computer vision capability of classifying various road sign images, including the original images, images with two different types of malicious attacks, and images that are scrambled randomly at the pixel level. Our results showed that participants rated …

Noaa Oceanic And Atmospheric Research Ocean Carbon Observing Science Plan Fy25 To Fy35, United States National Oceanographic And Atmospheric Administration

National Oceanographic and Atmospheric Administration: Technical Reports and Related Materials

United States National Oceanographic and Atmospheric Administration oceanic and atmospheric research ocean carbon observing science plan for fiscal years 2025 through 2035.

Impact Of An Herbicide Treatment In An Annual Grass Invaded Sagebrush Steppe, Jordan Dino Santia

Undergraduate Scholarship

Globally, rangelands are being threatened by invasive annual grasses (IAGs) that alter fire regimes, drive vegetation type conversion, and alter ecosystem function. This study evaluates vegetation responses to an Imazapic treatment applied in 2020 to control a population of Taeniatherum caput-medusae, an IAG, that flourished following a severe wildfire in 2013. The site, located on a Bureau of Land Management (BLM) grazing allotment east of Klamath Falls, Oregon, has been monitored annually using the Assessment, Inventory, and Monitoring (AIM) protocol since the Summer of 2022. Over this period, very little T. caput-medusae has been detected while bare ground has …

Igc Oral Presentation Summary: Xxv Igc Congress, S. Ray Smith, Echo Elizabeth Gotsick, J. R. Weinert-Nelson, Alayna Jacobs, Christopher D. Teutsch, Will Fleming, D. R. Woodfield, James L. Klotz, Jeff Lehmkuhler, Greg S. Halich, Brittany Davis, Brittany Hendrix, Krista Lea

IGC Proceedings (1977-2023)

This paper will give an overview of the XXV International Grassland Congress thematic, keynote, and plenary sessions. The theme of the XXV IGC Congress meeting was “Grasslands for Soil, Animal, and Human Health.” We had many people attending, presenting, and participating in all these sessions. Within a month after the conclusion of the Congress, the proceeding’s papers presented at the meeting will be available on the IGC app. By the end of 2023 all papers will be available for download through any search engine at internationalgrasslands.org.

Reasoning Through Change: Exploring Covariational Thinking In Student Exponential Graph Interpretation, Samantha Lynn Pearson

Honors Theses and Capstones

This study explores how life science students reason about exponential functions in the context of an introductory physics course. While exponential functions are essential in both physics and biology—appearing in scenarios like population growth and temperature cooling—students often encounter challenges in interpreting them. Using a resources framework, we examined the cognitive resources these students bring to exponential reasoning, focusing on what ideas and strategies they already possess. Our methodology involved conducting think-aloud interviews with nine students from PHYS 402. Interviews were coded using a framework informed by prior research on covariational reasoning and exponential understanding. Results show that students generally …