Physical Sciences and Mathematics Commons^™

Controls On Sediment Connectivity In Fluvial Networks Impacted By Wildfire Across Utah, Alec Arditti

All Graduate Theses and Dissertations, Fall 2023 to Present

Flooding and sedimentation caused by wildfire are among the greatest threats to watersheds, fish populations and reservoirs in the western US. Burned landscapes are at risk for increased runoff and erosion and have the potential to transport sediment that may put downstream resources at risk. The ability of the channel to transport sediment downstream, known as the connectivity, is important for determining where impacts may occur. Sediment bottlenecks are locations within the watershed where local conditions produce a persistent decrease in downstream connectivity of sediment, resulting in increased sediment deposition and potentially a substantial modification of the local channel and …

Tropical Atlantic Temperature And Hydrologic Shifts During The Paleocene-Eocene Thermal Maximum, Chels Howard

All Graduate Theses and Dissertations, Fall 2023 to Present

The Paleocene-Eocene Thermal Maximum (PETM) is a geologic climate event that is studied heavily due to the similarities to anthropogenic climate change. This event occurred approximately 56 million years ago (Ma) and is characterized by a rapid release of carbon into the atmosphere, which resulted in an increase in temperature and a change in global climate events such as changes in patterns of evaporation and precipitation. We see this effect occurring in modern anthropogenic climate change due to the burning of fossil fuels releasing carbon dioxide (CO₂) into the atmosphere. In this study I use elemental data of …

Computational Study About Noncovalent Bonding Systems Involving Halogen, Chalcogen And Pnicogen Bonds, Jia Lu

All Graduate Theses and Dissertations, Fall 2023 to Present

First terms used in this thesis are introduced and defined as follows. In the periodic table, the elements in the 17^th column are named halogen including fluorine (F), chlorine (Cl), bromine (Br) and iodine (I). The elements in the 16^th column are named chalcogen including oxygen (O), sulfur (S), selenium (Se) and tellurium (Te). The elements in the 15^th column are named pnicogen including nitrogen (N), phosphorus (P), arsenic (As) and antimony (Sb).

After hydrogen bonds (B-H⋅⋅⋅B) are well studied and understood by scientists and researchers, halogen bonds (R-X⋅⋅⋅B) have drawn attention due to the similarities in …

Inundated Vegetation Response To Ongoing Restoration And Its Impacts On Fish Community Structure, Emmanuel J. May

All Graduate Theses and Dissertations, Fall 2023 to Present

Shallow lake ecosystems and their associated wetland habitats globally are subject to non-native species introductions, nutrient loading, and water level fluctuations, each of which can decrease vegetated habitat availability, exposing vulnerable native aquatic species to predation. Managers are frequently tasked with mitigating native species declines by restoring vegetation considered crucial for their survival. However, restoring vegetation can be challenging in the presence of multiple stressors, requiring managers to assess the relative importance of the different stressors limiting vegetation recovery.

Utah Lake is a large shallow lake subject to multiple stressors and has shifted from a mesotrophic lake with abundant aquatic …

Collaborative Task Completion For Simulated Hexapod Robots Using Reinforcement Learning, Tayler Don Baker

All Graduate Theses and Dissertations, Fall 2023 to Present

There is growing interest in developing autonomous systems capable of exhibiting collaborative behaviors. Using methods such as reinforcement learning is another way to train multiple robots for collaborative task completion. This study was able to successfully in simulation train multiple hexapod robots to push a target to a designated goal collaboratively. This required each robot to learn how find the target and push that target to a goal. This work suggests that using reinforcement learning for collaborative task completion for hexapod robots may simplify the complexity of the software and improve the decisions that they make.

Fire And Flow: Assessing The Long-Term Effects Of Wildfires And Impact Of High Flow Events On Phosphorus Concentrations In Mountain Streams, Rachel Watts

All Graduate Theses and Dissertations, Fall 2023 to Present

Climate change has led to significant shifts in the Earth’s weather patterns, often leading to longer, more intense droughts, irregular but extreme storms, and more severe wildfires with longer burn durations. These weather pattern changes have frequently led to shifts in ecosystem dynamics, impacting aspects such as nutrient flux, species diversity, and overall habitat health. Regarding nutrient flux specifically, changes in phosphorus (P) concentrations can negatively impact stream systems as elevated levels can lead to toxic algal blooms, which can cause habitat degradation, loss of usable recreational areas, and large fish kills. A common trigger of these P spikes is …

Statistical Analysis Of Health Habits For Incoming College Students, Wendy Isamara Lizarraga Noriega

Electronic Theses, Projects, and Dissertations

Health habits among college students are commonly overseen, especially for students transitioning from high school right into college. These students are becoming independent young adults, and learning how to adapt to a different scenery when it comes to their learning environment. As these young adults transition into college, this is the perfect time for the students to become more vulnerable and comfortable with their independence, and their weight begins to fluctuate. Many variables come into consideration when increasing weight as an incoming first-year student. Students are more likely to live alone, get a job, and rely on fast food and …

General Population Projection Model With Census Population Data, Takenori Tsuruga

Electronic Theses, Projects, and Dissertations

The US Census Bureau offers a wide range of data, and within this array, the American Community Survey 5-Year Estimate (ACS5) serves as a valuable resource for understanding the US population. This project embarks on an exploration of Machine Learning and the Software Development process with the goal of generating effective population projections from ACS5 data. The project aims to provide methods to make predictions for every city and town in the US, encompassing their total population and population divided into 5-year age groups. It's worth noting that while the generation of these projections is grounded in the generalized statistical …

Analysis And Assessment Of Land Use / Land Cover Impact On Human And Natural Ecosystems In The Salton Sea Watershed, 2013 - 2021, Diego Ramirez

Electronic Theses, Projects, and Dissertations

This study represents an interdisciplinary analysis of the changing landscape of the Salton Sea Watershed from 2013 to 2021, focusing on land use land cover (LULC) category changes, climatic variations, and socioeconomic factors. The findings of this research show a shift in land cover categories, portrayed by the changes of natural landscapes and vegetative areas into rapidly increasing urbanized expansion and increased impervious surfaces. These changes pose concerns about increased temperature in the region, a decrease in overall water availability and groundwater infiltration, and an increase in pollution. The study explores 10 sub-watersheds within the Salton Sea Watershed basin, focusing …

Post-Wildfire Effects On A Headwater Stream In The San Bernardino National Forest, Kelley Giron

Electronic Theses, Projects, and Dissertations

Southern California has experienced prolonged drought conditions that have supported frequent wildfires that adversely impact ecosystems, natural resources, and human development. A primary consequence of these events is the impact on water quality and quantity. Of equal concern is evaluating how diverse land use configurations within a watershed can alter the physio-chemical properties of headwater reaches where drought and wildfire conditions are prevalent. To better understand the extent to which wildfires impact water quality and quantity across a headwater watershed, this study investigates wildfire impacts from the 2021 South Fire to Lytle Creek, a headwater stream of the Santa Ana …

Observational Uncertainty For Global Drought-Pluvial Volatility, Yichan Li, Linyin Cheng, Chiyuan Miao, Zhiyong Liu

Geosciences Faculty Publications and Presentations

Droughts and pluvials have occurred in most regions in the past. However, what calls growing attention is the additive effects of these two opposite extreme events occurring in spatial-temporal proximity to one another, sometimes beyond either of the hazards individually. This study examines the likelihood of global drought-pluvial volatility which involves both meteorological drought-to-pluvial (DTP) and pluvial-to-meteorological drought transitions; meanwhile, identifies discrepancies and agreements among the widely used observations for such events, an aspect that remains currently overlooked. Globally, we find that the observation-based data sets including Global Precipitation Climatology Center (GPCC), Climate Research Unit (CRU) and ERA5 reach a …

Implementation Of Hierarchical And K-Means Clustering Techniques On The Trend And Seasonality Components Of Temperature Profile Data, Emmanuel Ogedegbe

Electronic Theses and Dissertations

In this study, time series decomposition techniques are used in conjunction with Kmeans clustering and Hierarchical clustering, two well-known clustering algorithms, to climate data. Their implementation and comparisons are then examined. The main objective is to identify similar climate trends and group geographical areas with similar environmental conditions. Climate data from specific places are collected and analyzed as part of the project. The time series is then split into trend, seasonality, and residual components. In order to categorize growing regions according to their climatic inclinations, the deconstructed time series are then submitted to K-means clustering and Hierarchical clustering with dynamic …

Thermal Energy Storage Using High Temperature Borehole Heat Exchangers In Unconsolidated Materials, Kayla Bicknell

All Theses

Thermal energy storage is a potential method for storing excess energy produced when supply is greater than demand. The use of the subsurface for storing thermal energy has become more recognized as a viable alternative to conventional methods of energy storage. However, high temperature borehole thermal energy storage has yet to be researched in-depth. Therefore, the goal of this project is to determine the feasibility of using the subsurface to store thermal energy at relatively high temperatures.

The focus of this work is to determine what design elements would make a borehole thermal energy storage system most effective and produce …

Dynamic Translation Of Drone View To Vehicle View For Autonomous Driving, Grayson Byrd

All Theses

As the field of computer vision continues to advance, the use of autonomous vehicles in military applications has increased and the tasks associated with these systems have grown in scope and complexity. These vehicles tend to operate in combat situations, presenting significant risk in the form of sensor damage. Since these autonomy algorithms rely on sensor information to navigate their environment, any threat to sensor functionality negatively impacts the reliability of the system. As a potential solution, I propose Dynamic Diffusion-based View Translation (DDVT), a novel computer vision algorithm capable of restoring image sensor function in ground vehicles through aerial …

Generalized Vulnerability Measures Of Graphs, Julia Vanlandingham

All Theses

Several measures of vulnerability of a graph look at how easy it is to disrupt the network by removing/disabling vertices. As graph-theoretical parameters, they treat all vertices alike: each vertex is equally important. For example, the integrity parameter considers the number of vertices removed and the maximum number of vertices in a component that remains. We consider the generalization of these measures of vulnerability to weighted vertices in order to better model real-world applications. In particular, we investigate bounds on the weighted versions of connectivity and integrity, when polynomial algorithms for computation exist, and other characteristics of the generalized measures.

Computational Quantum Chemistry Studies Of The Stabilities Of Radical Adducts Formed During The Oxidation Of Melatonin Derivatives, James Horne

Electronic Theses and Dissertations

Melatonin is a natural antioxidant that has been investigated for properties as a potential spin trap to identify short-lived free radicals. Computational quantum chemistry studies have been performed for the oxidation of melatonin to N¹-acetyl-N²-formyl-5-methoxykynuramine. This research focused on modification of melatonin into derivatives and analyzing the change in total molecular energy from melatonin to its oxidation product, as well as the corresponding derivatives. Each of the molecular geometries were optimized at the DFT/B3LYP/6-31G(d), DFT/B3LYP/cc-pVXZ (X = D, T), HF/6-31G(d), HF/cc-PVXZ (X = D, T), MP2/6-31G(d), and MP2/cc-PVXZ (X = D, T) levels of theory. …

Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye

Electronic Theses and Dissertations

Autoencoders, a type of artificial neural network, have gained recognition by researchers in various fields, especially machine learning due to their vast applications in data representations from inputs. Recently researchers have explored the possibility to extend the application of autoencoders to solve nonlinear differential equations. Algorithms and methods employed in an autoencoder framework include sparse identification of nonlinear dynamics (SINDy), dynamic mode decomposition (DMD), Koopman operator theory and singular value decomposition (SVD). These approaches use matrix multiplication to represent linear transformation. However, machine learning algorithms often use convolution to represent linear transformations. In our work, we modify these approaches to …

Early Pliocene Mice And Rats From The Gray Fossil Site Of Eastern Tennessee: Implications For The Evolution Of Cricetidae And Understanding Of The Past Ecosystem, Ziqi Xu

Electronic Theses and Dissertations

Cricetidae ranks as the second-most species-rich and abundant mammalian family, with limited studies on eastern North American records prior to the Pleistocene. While cricetids has been previously noted at the early Pliocene Gray Fossil Site (GFS), this study provides a detailed description of eight taxa: Postcopemys (two species), Symmetrodontomys, Oryzomyini, Peromyscus, Neotoma, Neotomodon, and Xenomys. Postcopemys is the most common cricetid taxon at GFS, followed by Peromyscus and Neotoma. These records expand the stratigraphic and geographic range of multiple genera. Distinctive morphological features of GFS taxa suggest presence of several new species. The …

Wallaby Pre-Pilot Survey: Ultra-Diffuse Galaxies In The Eridanus Supergroup, B.-Q. For, K. Spekkens, L. Staveley-Smith, K. Bekki, A. Karunakaran, B. Catinella, Bärbel S. Koribalski, K. Lee-Waddell, Juan P. Madrid, C. Murugeshan

Physics & Astronomy Faculty Publications

We present a pilot study of the atomic neutral hydrogen gas (H I) content of ultra-diffuse galaxy (UDG) candidates. In this paper, we use the pre-pilot Eridanus field data from the Widefield ASKAP L-band Legacy All-sky Blind Survey to search for H I in UDG candidates found in the Systematically Measuring Ultra-diffuse Galaxies survey (SMUDGes). We narrow down to 78 SMUDGes UDG candidates within the maximum radial extents of the Eridanus subgroups for this study. Most SMUDGes UDGs candidates in this study have effective radii smaller than 1.5 kpc and thus fail to meet the defining size threshold. We …

Disease Of Lung Infection Detection Using Cnn Model -Bayesian Optimization, Poojitha Gutha

Electronic Theses, Projects, and Dissertations

Auscultation plays a role, in diagnosing and identifying diseases during examinations. However, it requires training and expertise, for application. This study aims to tackle this challenge by introducing a model that categorizes respiratory sounds into eight groups: URTI, Healthy, Asthma, COPD, LRTI, Bronchiectasis, Pneumonia, and Bronchiolitis. To achieve this categorization the study utilizes a Convolutional Neural Network (CNN) model that has been optimized using techniques. The dataset used in the study consists of 920 audio samples obtained from 126 patients with durations ranging from 10 to 90 seconds. Impressively, the model demonstrates a noteworthy 83% validation accuracy and an impressive …

Hypothyroid Disease Analysis By Using Machine Learning, Sanjana Seelam

Electronic Theses, Projects, and Dissertations

Thyroid illness frequently manifests as hypothyroidism. It is evident that people with hypothyroidism are primarily female. Because the majority of people are unaware of the illness, it is quickly becoming more serious. It is crucial to catch it early on so that medical professionals can treat it more effectively and prevent it from getting worse. Machine learning illness prediction is a challenging task. Disease prediction is aided greatly by machine learning. Once more, unique feature selection strategies have made the process of disease assumption and prediction easier. To properly monitor and cure this illness, accurate detection is essential. In order …

An Exposition Of The Curvature Of Warped Product Manifolds, Angelina Bisson

Electronic Theses, Projects, and Dissertations

The field of differential geometry is brimming with compelling objects, among which are warped products. These objects hold a prominent place in differential geometry and have been widely studied, as is evident in the literature. Warped products are topologically the same as the Cartesian product of two manifolds, but with distances in one of the factors in skewed. Our goal is to introduce warped product manifolds and to compute their curvature at any point. We follow recent literature and present a previously known result that classifies all flat warped products to find that there are flat examples of warped products …

Responsibility Gaps And Black Box Healthcare Ai: Shared Responsibilization As A Solution, Benjamin H Lang, Sven Nyholm, Jennifer Blumenthal-Barby

Center for Medical Ethics and Health Policy Staff Publications

As sophisticated artificial intelligence software becomes more ubiquitously and more intimately integrated within domains of traditionally human endeavor, many are raising questions over how responsibility (be it moral, legal, or causal) can be understood for an AI’s actions or influence on an outcome. So called “responsibility gaps” occur whenever there exists an apparent chasm in the ordinary attribution of moral blame or responsibility when an AI automates physical or cognitive labor otherwise performed by human beings and commits an error. Healthcare administration is an industry ripe for responsibility gaps produced by these kinds of AI. The moral stakes of healthcare …

Dual Barriers: Examining Digital Access And Travel Burdens To Hospital Maternity Care Access In The United States, 2020, Peiyin Hung Ph.D., Marion Granger, Nansi Boghossian, Jiani Yu, Sayward Harrison, Jihong Liu Sc.D., Berry A. Campbell, Bo Cai Ph.D., Chen Liang, Xiaoming Li Ph.D.

Faculty Publications

Policy Points The White House Blueprint for Addressing the Maternal Health Crisis report released in June 2022 highlighted the need to enhance equitable access to maternity care. Nationwide hospital maternity unit closures have worsened the maternal health crisis in underserved communities, leaving many birthing people with few options and with long travel times to reach essential care. Ensuring equitable access to maternity care requires addressing travel burdens to care and inadequate digital access. Our findings reveal socioeconomically disadvantaged communities in the United States face dual barriers to maternity care access, as communities located farthest away from care facilities had the …

Automated Materials Spectroscopy And Topology Optimizations Using Genetic Algorithms, Miu Lun Lau

Boise State University Theses and Dissertations

This dissertation will focus on the implementation and development of genetic algorithm software for increasing the productivity and analysis rate for spectrum analysis, topology optimization, and others. The software artifacts generated have resulted in a basic software framework called Neo. The framework has been further developed into different software for specific spectra methods such as EXAFS, Astrophysics, Nano-Indentation, and many more.

For GA implementation that relates to EXAFS, we have demonstrated the usage of GA to correctly identify chemical species presented, for Copper metal species, Technetium compounds, and in-situ of SnS2 batteries. The software artifact was able to generate accurate …

Prospects And Constraints For A Recreational Fishery On East Canyon Creek At The 910 Ranch, S. Bishop, A. Garner, G. Mclaughlin, T. Oman, N. Omer, C. Stewart

Watershed Sciences Student Research

Summit County Lands and Natural Resources has retained students from Utah State University’s Management and Restoration of Aquatic Ecosystems program to evaluate current conditions of East Canyon Creek (ECC) in the 910 Ranch and propose prospects, constraints, and potential actions to establish a recreational trout fishery.

Perovskite Oxide Derivatives For Enhanced Electrochemical Water Splitting And Pseudocapacitor Applications., Md. Sofiul Alom

Electronic Theses and Dissertations

The global energy landscape is at a crossroads, marked by surging demand, finite fossil fuel reserves, and escalating environmental concerns stemming from carbon emissions. To address these challenges and transition towards a sustainable energy future, this dissertation embarks on a multidisciplinary exploration of perovskite oxides and their derivatives as catalysts and materials for advanced electrochemical water splitting and pseudocapacitive energy storage. In the quest for efficient water splitting catalysts, a series of quasi-2D oxides, SrLaAl_1/2M_1/2O₄ (M = Mn, Fe, Co), was synthesized and systematically studied where the B-site comprised of both transition metals and main …

Scalable Solution Processing Of Niox Nanoparticles., Peter James Armstrong

Electronic Theses and Dissertations

Perovskite solar cells (PSCs) are a promising alternative to silicon-based photovoltaics. However, PSCs face several challenges due to shortcomings in their stability, module efficiency, and scaled production. Although PSCs is still a young field of research, significant attention has been given to demonstrating power conversion efficiencies that are on par with traditional silicon. With that target reached, converting the laboratory demonstration into practical materials to increase access and abundance of solar energy are among the next large targets for the field. This comes with material challenges for perovskite and their companion charge transport layers (CTLs). Among the charge transport materials …

Effects Of A Protection Zone In A Reaction-Diffusion Model With Strong Allee Effect., Isaac Johnson

Electronic Theses and Dissertations

A protection zone model represents a patchy environment with positive growth over the protection zone and strong Allee effect growth outside the protection zone. Generally, these models are considered through the corresponding eigenvalue problem, but that has certain limitations. In this thesis, a general protection zone model is considered. This model makes no assumption on the direction of the traveling wave solution over the Strong Allee effect patch. We use phase portrait analysis of this protection zone model to draw conclusions about the existence of equilibrium solutions. We establish the existence of three types of equilibrium solutions and the necessary …

Bayesian Strategies For Propensity Score Estimation In Causal Inference., Uthpala I. Wanigasekara

Electronic Theses and Dissertations

Causal inference is a method used in various fields to draw causal conclusions based on data. It involves using assumptions, study designs, and estimation strategies to minimize the impact of confounding variables. Propensity scores are used to estimate outcome effects, through matching methods, stratification, weighting methods, and the Covariate Balancing Propensity Score method. However, they can be sensitive to estimation techniques and can lead to unstable findings. Researchers have proposed integrating weighing with regression adjustment in parametric models to improve causal inference validity. The first project focuses on Bayesian joint and two-stage methods for propensity score analysis. Propensity score modeling …