Physical Sciences and Mathematics Commons^™

R Code And Supporting Data For "Fast And Slow Water Handling Strategies Explain Pinyon Pine Decline And Juniper Expansion", Andrew Kulmatiski, Muhammad Faraz Rehman

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This repository contains the datasets, R scripts, HYDRUS-1D model files, weather data, and supporting materials used for the M.S. thesis, "Fast and Slow Water Handling Strategies Explain Pinyon Pine Decline and Juniper Expansion." The study investigated root water uptake and water-use strategies of pinyon pine (Pinus edulis) and Utah juniper (Juniperus osteosperma) using stable isotope tracer experiments, soil water flow modeling, leaf water potential measurements, stomatal conductance measurements, and environmental data collected across an aridity gradient in southern Utah, USA.

Managing Prairie Dogs On Agricultural Lands, Cory Farnsworth, S. Nicole Frey

All Current Publications

While prairie dogs are an important species in the region because their burrows provide shelter for many wildlife species, they are also preyed upon by many mammals and birds. However, because of the damage they can cause to cropping and range systems, their populations may occasionally need to be controlled. After you have identified which prairie dog species you are in conflict with and the scope of the damage, you will want to decide how to manage them. This fact sheet provides information on control options and the general ecology of the three prairie dog species in Utah.

Geothermal Energy In Utah: Massive Potential To Meet Growing Electricity Needs, Emily Labonty, Kendall Becker, Logan Mitchell, Jennifer Bodine, Scott Hotaling

All Current Publications

Including more geothermal energy in Utah's energy mix would help address issues of concern for many Utahns: poor air quality, climate change, and the need to support renewable energy research. Geothermal energy, heat from within the Earth, is a renewable energy source that can provide flexible, baseload electricity––like coal or natural gas––but without the climate-warming and polluting effects. This fact sheet provides information about geothermal energy, generating electricity from geothermal energy, and current geothermal projects in Utah.

Geothermal Energy In Utah: A Safe Technology With Limited Environmental Impacts, Joseph Harding, Kendall Becker, Logan Mitchell, Jennifer Bodine, Scott Hotaling

All Current Publications

Geothermal energy has the potential to transform Utah’s electricity landscape, driving a future with improved air quality, lower carbon emissions, and fewer environmental impacts. In this fact sheet, we provide an overview of geothermal energy and its potential environmental implications in Utah. We highlight that recent geothermal projects in Utah do not use fresh water and that new well designs are expected to reduce the consumption of salty, brackish water. If these efforts are successful, geothermal energy would have lower water consumption, reduced seismic risk, and a similarly low land-use footprint compared to fossil fuel sources of electricity.

Creating Sustainable School And Home Gardens: Managing Rainwater, Lawrence Krissek, Kathy Cabe Trundle

All Current Publications

Rainscaping can help solve drainage problems, reduce erosion, improve water quality, and conserve soil by effectively managing rainwater movement across the landscape. It can also provide environments with increased biodiversity while reducing the need for supplemental watering.  The details of rainscaping your garden are very site-specific, affected by the amount of space and money available, your garden’s physical and weather/climate characteristics, and your garden goals. This resource sheet addresses the use of natural methods to ensure efficient rainwater management.

Utah Growing Water Smart: The Water-Land Use Integration Guidebook For Central Utah, Kelly Kopp, Joanna Endter-Wada

Utah Growing Water Smart

The Utah Growing Water Smart workshop brings together key staff and water and land use planning decision makers to help communities build a more resilient and sustainable water future. The workshop uses a range of public engagement, planning, communication, and policy implementation tools to help community teams realize their water efficiency, smart growth, watershed health, and water resiliency goals.

Sql Query Optimization - Human Vs. Chatgpt, Hailey Dennis

All Graduate Reports and Creative Projects, Fall 2023 to Present

Large Language Models (LLMs) such as ChatGPT have become ubiquitous tools for working professionals in the software industry. Many engineers are finding new ways to increase productivity by offloading tasks onto LLMs, while others are finding it difficult to trust code produced artificially, even after review. Taking a look at both perspectives, this study aims to compare a human’s ability to optimize SQL queries to that of an LLM and assess the experience using both methods.

Manual query optimization is a tedious task that relies heavily on statistics, heuristics, and good intuition. The SQL developer must search for the optimal …

Open Space Management Planning: A Framework And Case Study From Eagle Mountain City, Utah, Nathan K. Shumway

All Graduate Reports and Creative Projects, Fall 2023 to Present

Open Space Management Plans (OSMPs) are increasingly used by municipalities to guide the long-term stewardship of natural lands; however, little formal guidance exists regarding how these plans are structured, developed, or organized in practice. While numerous OSMPs are publicly available, their compositional logic, procedural workflows, and thematic priorities remain largely undocumented within academic literature. This study addresses that gap through a qualitative document analysis of fifteen publicly accessible OSMPs from the western United States, published between 2015 and 2024.

Using manual matrix-based coding in Microsoft Excel, each plan was analyzed through three lenses: structural composition, procedural development, and thematic content. …

From The Hopf Fibration To Instantons: Geometry In Gauge Theory, Emily D. Wessman

Undergraduate Honors Capstone Projects

This paper explores the relationship between topology, differential geometry, and gauge theory through the study of Yang-Mills theory and its solutions, known as instantons. Beginning with the Hopf fibration, we show how principal fiber bundles encode topological information and appear in physical contexts such as electromagnetism. In particular, we consider how the fibration of S³ over CP¹ ≅ S² represents the Dirac magnetic monopole, and how the Chern number associated with the bundle is exactly the winding number for the monopole.

We then develop the framework of gauge theory, focusing on connections on principal SU(2) bundles …

Utilizing Pine Needles To Compare Spatial Profiles Of Polycyclic Aromatic Hydrocarbons (Pahs) In Two Urban Areas, Autumn Jensen

Undergraduate Honors Capstone Projects

Polycyclic aromatic hydrocarbons (PAHs) are an important class of semivolatile air pollutants known for their adverse health impacts. This research used conifer needles as passive air samplers to create spatial maps of two Utah cities (Rose Park and Spanish Fork) to compare overall PAH exposure and identify any differences in their congener profiles or PAH “fingerprints”. Conifer needles were chosen due to their prevalence as a passive air sampler in previous research and their ubiquity in urban and suburban environments. Second year needles were collected and the concentrations are considered to be an annually averaged view of the PAH concentrations …

Discovering Strategic Behaviors In The Floor Using Reinforcement Learning, Kevin Parks

All Graduate Reports and Creative Projects, Fall 2023 to Present

This project investigates how a reinforcement learning (RL) agent can develop territorial strategies in a highly stochastic, grid-based approximation of the television game show The Floor. I design a custom Gymnasium-compatible environment that models the show’s core mechanics on a 10×10 board, including probabilistic duels governed by player skill, adjacency-constrained attacks, chain-attack rules, and a Randomizer mechanism for selecting new initiating players. A Maskable Proximal Policy Optimization (Maskable PPO) agent is trained under several reward configurations and evaluated against stochastic non learning opponents as well as random and “always pass” baselines.

Across experiments, the best-performing configuration achieves a win …

Beyond Morphology: Testing Molecular Assessment Of Macroinvertebrate Communities In Alpine Streams Of The Teton Range, Usa, Joshua Vollmer

All Graduate Theses and Dissertations, Fall 2023 to Present

Alpine streams and the macroinvertebrate communities that reside within them are threatened by the rapidly changing climate. Long-term monitoring of these communities is required to understand how they are changing and to predict their future trajectories. Historically, stream monitoring and assessment has been performed by collecting and identifying individuals using their morphological traits. However, in alpine aquatic ecosystems, distinct macroinvertebrate species often lack the morphological differences that allow them to be distinguished. DNA metabarcoding, an alternative method for identification which uses genetics instead of morphological differences, is not impacted by this issue, and therefore, may be better suited for alpine …

Design And Verification Of The Multi-Slit Solar Explorer Camera Field Programmable Gate Arrays, Jordan M. Johnson

All Graduate Reports and Creative Projects, Fall 2023 to Present

The Multi-Slit Solar Explorer, or MUSE, is a NASA mission that will take images of the Sun to study solar flares and the solar corona. The mission will provide insight into the mechanisms behind space weather. The mission consists of two cameras: the Spectrograph (SG), and the Context Imager (CI). The Utah State University Space Dynamics Laboratory is providing both cameras for the mission.

This report describes a part of the design and verification process for a central component on these cameras known as the Field Programmable Gate Arrays (FPGAs). These FPGAs are programmed to acquire, handle, and send images …

Visualizing Probabilistic Model Checking: An Interactive Framework For Exploring Ctmc Models, Ishara Mawelle Kankanamge

All Graduate Theses and Dissertations, Fall 2023 to Present

Probabilistic model checking is a critical method for analyzing systems characterized by uncertainty, such as communication protocols, randomized algorithms, and biochemical networks. While formal verification tools provide precise numerical data about these systems, interpreting these results is often limited by large state space, high-dimensional state space and time dependent evolution. Current tools typically output raw numerical data, offering limited support for intuitively understanding the time-dependent behavior of a model. This research presents an interactive visualization framework designed to bridge the gap between complex numerical analysis and human intuition. The framework integrates coordinated visual interfaces, including lower-dimensional state-space projections and synchronized …

Assessing Geomorphic Change From Large Wood Additions In An Intensively Monitored Watershed, Alexander Walt

All Graduate Theses and Dissertations, Fall 2023 to Present

Rivers across the American West are under stress. Over time, human activities have decreased riparian vegetation and removed naturally occurring large wood from fallen trees and beaver dams. Overgrazing, wetland drainage, and artificial barriers like levees and berms have further changed these ecosystems, leaving behind simple channels that lack varied habitat for aquatic species.

Efforts to restore rivers have made some progress, but many projects are small in scale and focus more on reshaping the river rather than restoring the natural processes that keep it healthy. This study evaluates a different approach—Low-Tech Process-Based Restoration (LTPBR)—which works with nature to rebuild …

An Alternative Representation For Temporal Json, Bishal Sarkar

All Graduate Theses and Dissertations, Fall 2023 to Present

JavaScript Object Notation (JSON) is a common format for representing and exchanging data on the web. Most systems only keep the current version of a JSON document, even though, in many situations, it is also important to know how that document changed over time. For example, an application might need to answer questions such as “What did this record look like last week?” or “How has this list grown over the past year?” A simple way to keep this history is to store a full copy of the document every time it changes, but this quickly becomes wasteful, most of …

Leveraging The Iron Oxide Archive Of Mineralization, Deformation, And Exhumation Across Geologic Time, Jordan L. Jensen

All Graduate Theses and Dissertations, Fall 2023 to Present

The iron oxide mineral hematite commonly forms from groundwater near Earth’s surface and can preserve a history of fluid flow, fault slip, and landscape evolution. This record can be decoded using (U-Th)/He thermochronology, a dating method based on the temperature-sensitive ingrowth of helium from uranium and thorium decay. Because later heating and natural variation in hematite crystals can produce ambiguous (U-Th)/He results, I integrate dating with tools that reveal differences in hematite chemistry and textures. I apply these techniques to two distinct settings: ancient granitic rocks in Colorado and an active fault zone in the southern San Andreas fault (SSAF) …

Effects Of Beaver Dams On Components Of Riverscape Health And Biodiversity In The Great Basin, Cashe C. Rasmussen

All Graduate Theses and Dissertations, Fall 2023 to Present

Networks of rivers and their floodplains (i.e., low-lying areas adjacent to rivers and streams that could plausibly flood) have been degraded, reducing the availability of freshwater and habitat for people and wildlife. Therefore, land managers are pursuing cost-effective restoration strategies, including partnering with beavers (Castor canadensis), to promote the health of these ecosystems and associated benefits. However, our understanding of beaver-mediated restoration benefits remains incomplete. Here, we compared locations along streams with and without beaver dams to measure the benefits of beavers in the Great Basin of the Western United States. We measured the effects of beaver dams …

Advancing Context-Aware Detection Of Socially Harmful Discourse Using Transformer-Based Models, Santosh Chapagain

All Graduate Theses and Dissertations, Fall 2023 to Present

Social media platforms are a central part of modern communication, shaping how people share ideas, build communities, and discuss social issues. While these spaces can support connection and self expression, they also enable the spread of harmful language such as hate speech. At the same time, social media is an important place where members of marginalized communities, including sexual and gender minorities, express stress, discrimination, and emotional challenges in ways that are often indirect and context dependent.

This research examines whether modern artificial intelligence systems can better identify harmful language and expressions of minority stress in online posts. The study …

Influence Of Coterie On Utah Prairie Dog Translocation Success, Bonnie Stokes

All Graduate Theses and Dissertations, Fall 2023 to Present

The Utah prairie dog (Cynomys parvidens) is a threatened species found in southwestern Utah. Utah prairie dogs are small, burrowing squirrels that live in family groups called coteries. Translocation, the intentional capture, movement, and release of animals from one location to another, has been widely used to aid in their recovery; however, post-translocation survival remains low. The primary objective of this study was to evaluate the effect of translocating Utah prairie dogs as intact coteries on post-translocation survival.

This study was conducted within the West Desert Recovery Unit in Iron and Beaver Counties, Utah, during July–October 2023 and …

Student Programming Behavior With And Without Phone Notification Suppression, Gavin T. Eddington

All Graduate Theses and Dissertations, Fall 2023 to Present

Many students work on programming assignments while receiving notifications from their phones, such as text messages or social media alerts. These notifications can interrupt focus and make it harder to stay engaged with a task. This study examines whether silencing phone notifications helps students stay more focused while programming. 

We collected data from students in an introductory computer science course while they worked on programming assignments. Students completed some assignments with notifications silenced and others without. We measured their activity using software that records typing behavior and identifies when students take long pauses, which can indicate interruptions or loss of …

Gradient Based Optimization Methods For Robust Learning And Biomedical Signal Modeling, Jarrod Mau

All Graduate Theses and Dissertations, Fall 2023 to Present

This dissertation explores how modern artificial intelligence techniques can be used to better understand complex biological data. Specifically, it develops new machine learning based methods and applies them to two important biomedical problems: analyzing brain signals and studying protein behavior.

The first part of the work introduces a new machine learning approach designed to improve how computers classify structured data. Traditional neural networks are powerful but can sometimes generalize poorly. This research proposes a method that combines the flexibility of neural networks with the reliability of ensemble techniques, leading to more robust and accurate predictions across different types of datasets. …

Constraint-Aware Metaheuristic Optimization For Experimental Design, Benjamin N. Fuller

All Graduate Theses and Dissertations, Fall 2023 to Present

Designing experiments becomes much more challenging when many variables and strict constraints are involved, as is common in modern science and engineering. This thesis introduces a new computational and mathematical framework that efficiently searches for optimal experiments in complex, high-dimensional spaces where traditional methods fail. By combining geometric techniques with flexible optimization algorithms like particle swarm optimization, our methods handle difficult constraints while scaling to real-world problems. Built in the high-performance Julia programming language and released as open-source software, this work bridges advanced theory with practical tools, offering researchers a powerful and accessible way to design better experiments under realistic …

Adversarial Heterogeneous Agent Learning For Robotic Systems: A Framework For Coordinated Competitive Behaviors, Christopher T. Allred

All Graduate Theses and Dissertations, Fall 2023 to Present

Autonomous robot teams must move reliably, explain their actions, and work together—even in changing or adversarial settings. We present a structured, three-stage pathway that builds coordinated team behavior from strong single-robot skills. First, we develop robust legged-robot locomotion and interpretability using only internal actuator signals. From these proprioceptive cues, robots learn to classify terrain and predict short-term power use, enabling energy-aware movement without external sensors. We further analyze learned behaviors with motif discovery to reveal recurring sensor–action patterns, which clarify how agility emerges and guide reward design. Second, we compose these skills into heterogeneous teamwork using centralized training with decentralized …

Sequential Products Of Anaerobic Denitrification In Calcareous And Noncalcareous Soils By Use Of The Gas Chromatograph, Grant S. Cooper

All Graduate Theses and Dissertations, Fall 2023 to Present

The sequential products of anaerobic denitrification were determined on seven Western soils (four alkaline, two acid, and one neutral) by soil and gas analysis. The soils with 1% alfalfa and added KNO3 were incubated at moistures slightly greater than field capacity and with an atmosphere of He. The soils and gases were periodically analyzed and balance sheets prepared. The sequence of NO3-->NO2-->N2O-->N2 operated in all soils. The rates of nitrogen interchanges and maximal amounts of nitrate, N2O2 and N2 were determined. From this data it was postulated that the rate-limiting process for denitrification in acid soils is …

Drought-Tolerant Plants Of Great Salt Lake: Determining Dormancy Break, Germination, And Seeding Timing Requirements To Improve Restoration Under Hydrologically Extreme Conditions, Montana Horchler

All Graduate Theses and Dissertations, Fall 2023 to Present

Wetlands are declining worldwide, and those in arid regions are especially vulnerable to climate change, drought, water diversions, and other human pressures. As a result, land managers increasingly rely on active revegetation to re-establish native plant communities and their associated ecosystem functions. Restoration that utilizes seeds as the propagule source is often the most cost-effective way to revegetate large areas, but in highly variable environments such as exist at Great Salt Lake, Utah, drought and flooding regularly limit plant establishment. Restoration practitioners require science-informed strategies to reach their goal of establishing diverse native plant communities with high native species cover. …

Continuous Symmetry Discovery And Enforcement Using Vector Fields With Application To Time Series And Image Data, Benjamin D. Shaw

All Graduate Theses and Dissertations, Fall 2023 to Present

Machine learning powers many technologies we use every day, from image classification in computer vision to analyzing time series data such as sensor readings or financial trends. One way to make these systems smarter and more reliable is by using symmetry, meaning patterns that remain unchanged under certain transformations, such as rotations for images or uniform changes in signal amplitude for time series. Discovering these patterns can improve understanding of data and help build models that perform well in new situations. 

Current methods for finding symmetry often rely on large neural networks and are limited to simple transformations like stretching …

Social And Institutional Factors Influencing Restoration Decisions In Sagebrush Plant Communities In The Great Basin, Carmen Calzado-Martínez

All Graduate Theses and Dissertations, Fall 2023 to Present

Sagebrush landscapes of the Great Basin in the western United States have changed dramatically over the past century. Invasive grasses, repeated wildfires, and past land-use practices have made it increasingly difficult for native plant communities to recover once they are damaged. Most restoration efforts occur after disturbances such as wildfire, when ecosystems may already be severely degraded. An alternative approach is proactive restoration, which aims to strengthen ecosystems before major damage occurs. 

This dissertation examines whether proactive restoration strategies could realistically be used in sagebrush rangelands and what factors influence their adoption. The research combines three complementary approaches. First, interviews …

Counterfactual Explanations For Time Series Through Local Pattern Mining And Generative Models, Omar Bahri

All Graduate Theses and Dissertations, Fall 2023 to Present

Machine learning systems increasingly make decisions that affect people’s lives, from medical diagnoses to loan approvals. When these systems analyze time series data—sequences of measurements collected over time, such as heart rhythms or sensor readings—users need to understand why a particular prediction was made. Counterfactual explanations address this need by answering “what-if” questions: what would need to change in the input for the system to make a different prediction? 

This dissertation develops methods for generating counterfactual explanations specifically designed for time series data. Time series often contain distinctive local patterns—short subsequences that distinguish one class from another. For example, a …

Post-Wildfire Erosion And Biogeochemistry: Integrating Aerial Imagery And Soil Testing To Assess Landscape Recovery, Justin A. Allred

All Graduate Theses and Dissertations, Fall 2023 to Present

After a wildfire, land managers are required to monitor large tracts of land with limited time and budgets. Traditionally, tracking landscape recovery is a time intensive process. This research explored the effectiveness of using drones (UAVs), strategic soil sampling, and computer modeling as additional tools for land managers in order to monitor the recovery more efficiently.

By using drones to collect aerial imagery and using machine learning, plant regrowth was monitored in back-to-back years. The machine learning model performed well at telling broad groups apart (trees vs grass) but it struggled to identify differences between plant species. Because many plants …