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From Covid-19 To Influenza: Transforming Public Health Surveillance Through Freeze-Drying Innovations, Rui Dong

Open Access Theses & Dissertations

Public health surveillance increasingly relies on wastewater-based epidemiology (WBE) as a non-invasive, community-level early warning system for infectious diseases like COVID-19 and influenza. However, detecting minute viral concentrations in complex wastewater matrices remains a significant analytical challenge. Traditional concentrating methods, such as ultrafiltration, are limited by high performance variability and significant viral signal loss due to necessary pretreatment steps, such as pre-clarification, which inadvertently discard solid-associated viral fractions. To address these limitations, this dissertation introduces and evaluates freeze-drying as a novel, pretreatment-free concentrating method for wastewater viral surveillance. By sublimating water, freeze-drying uniquely retains both liquid and solid-phase viruses within …

A Diagnostic Test For Confounding Under Collapsibility In Generalized Linear Models (Glms), Samuel Dela Gadah

Open Access Theses & Dissertations

This thesis develops and validates a diagnostic framework for assessing potential confounding in generalized linear models (GLMs) with collapsible link functions. Under collapsibility and effect homogeneity, the absence of confounding implies equality between marginal and covariate-adjusted treatment effects on the link scale, which motivates the change-in-estimate parameter δ = γ − γ(c) as the target of a formal hypothesis test. Two complementary inferential routes are developed: a nonparametric bootstrap and an independent estimating equation (IEE) procedure based on a stacked-data construction that yields a closed-form sandwich variance and is implementable in standard generalized estimating equation software. A backward elimination procedure …

Development Of A Simulation-Driven Evaluation System For Foreign Objects In Aircraft Structures, Daniela Garcia

Open Access Theses & Dissertations

This thesis investigates the use of simulation-driven methods to evaluate the behavior and potential impact of foreign objects within aircraft structures. Foreign Object Damage (FOD) remains a major concern in aerospace safety, as small components unintentionally left inside aircraft compartments can create uncertainty regarding their effect during flight. Although current inspection methods can detect the presence of foreign objects (FOs), they often cannot determine whether these objects pose a significant structural risk, leading to conservative maintenance decisions. To address this limitation, this work develops a simulation-based framework that integrates Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) to evaluate …

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 …

Exploring Cognitive Load Theory In The Post-Secondary Engineering Classroom, Gabriel Q. Van Dyke

All Graduate Theses and Dissertations, Fall 2023 to Present

Engineering programs often emphasize subject-matter expertise over pedagogical training, which can leave students struggling with course demands and contribute to retention challenges. This study applied Cognitive Load Theory (CLT) to examine how undergraduate engineering students experience the cognitive demands of their coursework compared to non-engineering classes. Using a sequential explanatory mixed methods design, cognitive load surveys were followed by interviews to address two research questions: (1) What are the differences in intrinsic and extraneous cognitive load levels between engineering courses and non-engineering courses taken concurrently by undergraduate engineering students? (2) How do engineering students perceive the unique challenges or benefits …

Ionospheric Plasma Electron Density Measurement And Theory Using Impedance Probe Techniques, Justin Wellington

All Graduate Theses and Dissertations, Fall 2023 to Present

The ionosphere plays a critical role in how radio frequency (RF) signals, like those used in Global Position System (GPS) satellite communications, travel through space. Disturbances in the ionosphere, such as equatorial plasma bubbles (EPB), scatter these signals and cause communication dropouts or navigational errors. To study these conditions, spacecraft use instruments that measure the surrounding plasma directly. One of these instruments is an impedance probe, which applies a small electrical signal to a sensor and determines electron density from the measured impedance.

This thesis improves the modeling and interpretation of impedance probe measurements. A numerical method is developed that …

Aerodynamic Parameter Estimation For A Scaled F-16: A Simulation-Based Sensitivity Analysis, Kathle C. Tischner

All Graduate Theses and Dissertations, Fall 2023 to Present

The physical motion of an aircraft is determined by the resulting forces and moments acting on the aircraft. These forces and moments can be defined as a mathematical equation where the control deflections, rotation rates, and orientation of the aircraft are multiplied by individual constants and summed together to define the entire force or moment. This method results in a highly accurate model that defines the motion of the aircraft at low angles of attack and sideslip. Initial calculations of the aerodynamic model are created based on analytical estimations based on the physical properties of the aircraft. Additional refinement of …

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 …

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 …

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 …

Reconfigurable Antennas Using Varactors On A Planar Parasitic Layer And Pin Diodes On A Dome Parasitic Layer, Andrew J. Hendricks

All Graduate Theses and Dissertations, Fall 2023 to Present

This research explores two types of reconfigurable, steerable antennas. These antennas change their beam direction based on electric input signals. The antennas have a layer that overlays the main antenna circuit board. The layer has small copper rectangles (pixels) that may be connected using either varactor diodes (which behave as voltage-controlled capacitors) or PIN diodes (electronic switches). The first antenna can steer in the xz-plane in any direction within about 23° from boresight (straight up from the antenna) and in the yz-plane to about 29° from boresight. The antenna uses varactor diodes on a planar layer. The second …

Assessing Young Children's Computational Thinking: Validation Of Items And Item Design Features, And Diagnostic Approaches, Chungsoo Na

All Graduate Theses and Dissertations, Fall 2023 to Present

The goals of this multiple-paper dissertation are to evaluate the psychometric evidence of the Computational and Spatial Thinking Assessment (CaST), designed and developed by the Coding in Kindergarten (CiK) research team (supported by NSF #1842116). In Chapter 2 (Paper 1), I evaluate the psychometric quality of the CaST assessment at the item level. The CaST has moderate item difficulty and high item discrimination, on average, with high reliability and no gender- or age-related item bias. In Chapter 3 (Paper 2), I identify seven item design features from the CaST assessment and examine their impact on item difficulty. All item design …

Unpacking Science Achievement: Institutional Alignment And Mediating Conditions In A High-Performing Charter School, Brenda L. Bennett

All Graduate Theses and Dissertations, Fall 2023 to Present

This study examined how science instruction was sustained over time within a high-performing public elementary charter school. Rather than focusing on individual programs or teaching strategies, the research explored how schoolwide systems, relationships, and supports worked together to shape classroom practice.

The study focused on one public K–6 charter school in a western state with consistently strong science performance on state-reported measures and examined how institutional, organizational, and classroom conditions mediated the relationship between science instruction expectations articulated in state and charter policy and teachers’ enacted practice.

Results suggested that strong science instruction was not produced through strict mandates or …

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 …

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 …

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 …

Comparing Strategies For Wetland Revegetation In An Uncertain Water Future, Hailey M. Machnikowski

All Graduate Theses and Dissertations, Fall 2023 to Present

Wetlands worldwide are expected to experience more frequent and intense droughts and floods due to climate change. These shifting water conditions introduce challenges to restoring wetland plants, especially using direct seeding. Seeding is cost and labor-efficient compared to planting, but seeds and seedlings are highly vulnerable to water stress, so restoration efforts often fail when conditions are too wet or dry. Understanding how to improve seed-based revegetation under these conditions is increasingly important. Therefore, we sought to understand the response, measured by percent canopy cover or dry biomass weights, of native plants to different durations of drought in greenhouse experiments, …

The Role Of Response Time In Math Anxiety, Christine K. Hartmann

All Graduate Theses and Dissertations, Fall 2023 to Present

Math anxiety is characterized by feelings of discomfort or distress that are triggered when an individual is tasked with using numbers. Math anxiety impacts people at all ages, from early elementary school into adulthood (for review see Ramirez et al., 2018). In these studies, we investigated the cognitive impact that math anxiety has on both children and adults by measuring their math anxiety and reaction time on two tasks. The first task was the arithmetic affective priming task (AAPT), which purportedly shows that those with math anxiety tend to complete math tasks more efficiently (faster) when they are primed to …

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 …

Analyzing The Influence Of Stem Project-Based Learning On Students' Perceptions And Career Interest In Stem, Melissa S. Barker

All Graduate Theses and Dissertations, Fall 2023 to Present

Although science, technology, engineering, and mathematics (STEM) enrichment programs aim to increase participation in STEM, the design features that meaningfully influence adolescents’ task values and career-related beliefs remain insufficiently specified. The purpose of this study was to investigate whether STEM PBL activities designed with an interest-focused theoretical lens of Subjective Task Value (STV) and Social Cognitive Career Theory (SCCT) influence students’ perceptions of STEM courses, majors, and careers. Additionally, I sought to understand what elements of the STEM PBL experience were most impactful. I designed and taught STEM PBL activities for students from the Native American lands in southeastern Utah …

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 …

Factors Affecting Mathematics Teachers’ Instructional Decision-Making: An Ecological Systems Theory Multiple-Case Study, Camille M. Lund

All Graduate Theses and Dissertations, Fall 2023 to Present

Though research on effective mathematics instructional strategies is robust, there remains a gap between research and the instruction that takes place in mathematics classrooms. One such effective instructional practice—mathematical student discourse (MSD)—has been extensively researched, but little research has looked holistically at the ecological factors that interact to influence teacher decision-making for this practice. In this qualitative multiple-case dissertation study using Urie Bronfenbrenner’s ecological systems theory as a theoretical lens, I conducted semi-structured interviews with three elementary teachers who teach mathematics in districts across northern Utah. These interviews utilized the researcher-created Ecological Factors Map to explore how teachers described the …

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 …

Housing Markets In The American West: A Dynamic Time Warping Analysis Of Inter-City Relationships, Daniel Johnson

All Graduate Theses and Dissertations, Fall 2023 to Present

Housing markets revolve around perhaps the most consequential good to the average person, yet the relationships between local housing markets remain understudied. While major American cities appear to follow similar patterns, the nature of these connections is not fully understood. This project looks at housing markets across the western United States, using Dynamic Time Warping (DTW) to identify which cities tend to lead or lag others in price movements, and look at the overall similarity of their market movements. We also explore whether geographic distance, population growth, and income growth help explain why some markets are more similar than others. …

A Mixed Methods Analysis On The Effect Of Active Learning On Extraneous Cognitive Load Within Undergraduate Statistics Courses, Michelle Brady Rich

All Graduate Theses and Dissertations, Fall 2023 to Present

Students enrolled in college-level statistics courses often lack the foundational skills of statistical concepts which can potentially lead to increased mental load. Additionally, the curricula within undergraduate classes often focus on traditional theory with little student exploration or participation. This combination of increased mental load and passive lectures can be explored through the Cognitive Load Theory (CLT). CLT examines how new information enters the limited capacity of an individual’s working memory and how exceeding this capacity affects the ability to transfer the information to long-term memory. This research focused on the extraneous cognitive load, or the load imposed by the …

Examining Motivations And Perceptions In Secondary Technology And Engineering Education: A Gendered Analysis Using The Fit-Choice Scale, Abigail Villanueva

All Graduate Theses and Dissertations, Fall 2023 to Present

This study examined why individuals choose to become secondary technology and engineering education (TEE) teachers and whether motivations differ between men and women. TEE programs help prepare students for careers in science, technology, engineering, and math (STEM), yet schools face teacher shortages and low female representation in the field. Understanding what draws people to this profession can support better recruitment and retention efforts. Sixty-six current TEE teachers completed a survey about the factors that influenced their decision to teach. Overall, the strongest motivations were a personal interest in teaching, enjoyment of working with young people, and the desire to make …

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 …

Rainbow Dominating Sets Of Graphs, Samuel L. Powell

All Graduate Theses and Dissertations, Fall 2023 to Present

The content of this thesis may be compared to a stack of plates with a common design that are broken, one at a time. If the plates are broken into large enough pieces you would be able to choose one fragment from each broken plate to discover the entire design that the plates share. For example, if you were still missing the center of the design after taking a piece from some plates, you could look for the piece of the next broken plate with the region in question.

We study the question of how many broken plates might guarantee …

How Novices Write Code: Discovering Best Practices, Matt Rau

All Graduate Theses and Dissertations, Fall 2023 to Present

Learning to program is a difficult endeavor, leading to chronically high failure rates in introductory programming courses. One thing that makes teaching programming difficult is that we don’t fully understand what problem solving habits and writing strategies separate successful programmers from struggling ones. Knowing how to teach these habits to a new programmer is an equally difficult challenge,

Studying the way people write code has proved difficult. Until recently, there was very little relevant publicly available data, and no good ways to analyze student programming behavior at a large scale. In this thesis, I address both issues. I publish a …