Physical Sciences and Mathematics Commons^™

Impacts Of Climate Change In The United States, Nathan T. Thompson

Journal of Nonprofit Innovation

Climate change, a shift in long-term climate patterns primarily driven by anthropogenic factors, poses a super wicked problem impacting every sector and region globally, including the United States. This paper explores the scientific basis of climate change, its contributing factors, and the myriad consequences on terrestrial and aquatic systems, as well as mental health. Notably, the emission of greenhouse gases from fossil fuels and agricultural activities is the primary cause, exacerbated by ideological division and psychological distance. The U.S. has seen some progress with a 7% decrease in emissions over the past 30 years and a growing shift toward renewable …

Computational And Experimental Advances In Nuclear Magnetic Resonance For High Resolution Structures, Ryan Toomey

Theses and Dissertations

Since its inception, nuclear magnetic resonance (NMR) has been a valuable tool for determining chemical structure. In recent years, the field of NMR has been advanced forward by the ability to calculate theoretical parameters with increasing accuracy and efficiency. These calculations are compared to experimental data to produce high resolution structures. The progression of these applications has been made possible by improved instrumentation, data processing methods, probe and experiment design, better quality functionals and basis sets, as well as increased computational power. This research is especially relevant with the emergence of artificial intelligence, which has great potential to expedite steps …

Locating Diversity In Reservoir Computing Using Bayesian Hyperparameter Optimization, Whitney Lunceford

Theses and Dissertations

Reservoir computers rely on an internal network to predict the future state(s) of dynamical processes. To understand how a reservoir's accuracy depends on this network, we study how varying the networ's topology and scaling affects the reservoir's ability to predict the chaotic dynamics on the Lorenz attractor. We define a metric for diversity, the property describing the variety of the responses of the nodes that make up reservoir's internal network. We use Bayesian hyperparameter optimization to find optimal hyperparameters and explore the relationships between diversity, accuracy of model predictions, and model hyperparameters. The content regarding the VPT metric, the effects …

Geology Of Sinai Tholus, Thaumasia Plateau, Mars, Haley Mosher

Theses and Dissertations

A new geologic map of the Sinai Tholus region on the Thaumasia plateau, Mars reveals the structural, magmatic, and stratigraphic complexity that can be found in the Tharsis region on Mars, and may help answer key questions about the origin of the subvolcanic basement, evolution of the regional stress field, development of Valles Marineris, and magmatic history of the region. Sinai Tholus is a topographic high in a relatively flat, lava flow covered part of Thaumasia Plateau, just south of the central part of Valles Marineris. Here, five stratigraphic units and one generalized impact unit have been mapped at a …

One-Dimensional Cores Of Peano Continua, Shogo Starr

Theses and Dissertations

In this paper, we define a berbering of a Peano continuum, which is the space one gets by attaching a null sequence of circles to a countable dense subset of a Peano continuum. The topology of a berbering is one that recognizes which circles are small, in the sense that any neighborhood of the original Peano continuum will entirely contain all but finitely many of the attached circles. We then show that given a berbering of any simply connected, locally simply connected Peano continuum $Y$, there exists a one-dimensional Peano continuum $X$ and a map from $X$ to the berbering …

Feature Engineering For Grain Boundaries And Other Variable-Sized Atom Clusters, C. Braxton Owens

Theses and Dissertations

Obtaining microscopic structure-property relationships for grain boundaries are challenging because of the complex atomic structures that underlie their behavior. This has led to recent efforts to obtain these relationships with machine learning, but representing a grain boundary structure in a manner suitable for machine learning is not a trivial task. There are three key steps common to property prediction in grain boundaries and other variable-sized atom clustered structures. These are: (1) describe the atomic structure as a feature matrix, (2) transform the variable-sized feature matrices of different structures to a fixed length common to all structures, and (3) apply machine …

Wind-Carved Wonders: An Aerial Study Of Yardangs In The Puna, Argentina Using Drone And Satellite Imagery, Derek Gordon Ashliman

Theses and Dissertations

Yardangs, elongated landforms sculpted by wind erosion, are prominent features in the Campo de Piedra Pomez (CPP) region of the Puna-Altiplano Plateau, Argentina. This study explores their formation and evolution through the examination of a 6 km by 0.5 km area captured in 2019 and a 5 km by 0.5 km area in 2024. High-resolution drone imagery and satellite data were employed to classify and quantify yardangs, gravel, and underlying bedrock across a vast study area. The research reveals a variation in yardang distribution and morphology from northwest (windward) to southeast (leeward), noting a significant decrease in yardang and bedrock …

Dynamics Of Dissolved And Particulate Trace Metals In A Snowmelt-Dominated Stream, Provo River, Utah, Usa, Kendra Louise Caskey

Theses and Dissertations

Trace element concentrations vary substantially during snowmelt runoff, with changes in the dissolved versus particulate fractions potentially impacting their movement at the catchment scale. To investigate trace element behavior in a snowmelt dominated stream, we measured concentrations in different size fractions in the Provo River (northern Utah, USA). We sampled the river at three locations during water years 2016-2018 and 2021-2023 for trace metal and major ion concentrations. During the final year, we collected three fractions (unfiltered, <0.45 µm filtered, and <0.22 µm filtered) for trace metal chemistry and calculated the particulate concentration as the difference between the unfiltered and 0.45 µm fraction. Stream measurements included pH, discharge, turbidity, and fluorescent dissolved organic matter (fDOM). We also sampled water sources (soil water, ephemeral streams, and snowpack) to compare trace metal concentrations across the watershed with the stream. Trace metal (Al, Be, Fe, Pb) and rare earth element (REE +Y) concentrations had the highest particulate and dissolved concentrations during snowmelt runoff. In contrast, major cations were primarily found in the dissolved fraction with lowest concentrations during snowmelt runoff. Major cation and particulate metal concentrations increased from upstream to downstream. The increased trace metal and REE + Y concentrations during snowmelt relative to baseflow may be explained by increased discharge and associated increased turbidity and fDOM. A comparison with water sources suggests that dissolved and particulate trace metals in the stream are sourced from flushed soil water, as trace metal transport through the watershed is facilitated by suspended sediment and dissolved organic matter. For most of the trace metals and REE +Y, concentrations were similar in the <0.45 µm and <0.22 µm fractions. Yet Al tended to have higher concentrations in the <0.45 µm fraction, suggesting a colloidal form of Al between 0.22 µm and 0.45 µm may exist. Differences from upstream to downstream may be related to changes in pH, from ~7 at the upper site to ~8 at the lower sites, which would change sorption capacity, saturation indices, or speciation. Our study demonstrates that trace metal concentrations are variable during snowmelt as the metals interact with suspended particles or dissolved organic matter and are influenced by changing water chemistry, with implications for understanding water quality impairments in snowmelt-dominated streams.

Deep Learning For Source Localization In A Laboratory Tank, Corey Emerson Dobbs

Theses and Dissertations

Deep learning has been applied to underwater acoustics problems in many forms. One difficulty in applying deep learning techniques to ocean acoustics is the spatially and temporally varying environmental properties. Another challenge is the lack of labeled data for training large networks. The overall goal of this work is to develop deep learning approaches for source localization that can be adaptable to different conditions. In this work, a convolutional neural network was trained on acoustic data measured in a water tank, while the water was at room temperature, to predict source-receiver range. Tests were done to ascertain ideal quantities of …

Linking Geospatial Trends And Geochemical Fingerprints To Anthropogenic Phosphorus Dust Deposition In Subalpine Soils, Austen Michael Lambert

Theses and Dissertations

This study shows that fugitive emissions associated with the surface mining of phosphate rock are a significant phosphorus (P) source to surface soils in northeastern Utah. Phosphorus is a nonrenewable resource essential for all life. Anthropogenic alterations to the P-cycle have led to widespread P pollution, and the unsustainable management of P has led to the threat of global depletion of P resources. Thus, accounting for both natural and anthropogenic flow paths of P is essential for the conservation and pollution reduction of P. One such source of human alteration to the P-cycle is the mining of phosphate rock. Mining, …

The Cofactor Matrix For Optimized Normal Transformations & Real-Time Caustics And Refractions Using Signed Distance Fields, Dane William Christensen

Theses and Dissertations

This thesis contains two distinct manuscripts both focused on real-time rendering research; an abstract for each is provided: 1. We survey methods for mapping normal vectors to a transformed surface with emphasis on the cofactor matrix form. We demonstrate that the cofactor matrix uniquely and correctly supports matrix transformations that are rank deficient or have negative determinants, while also generalizing to operations such as rotation, scaling, translation, and shearing. We derive and demonstrate the completeness of this new convention in contrast to other approaches, while also establishing its computational efficiency benefits. 2. We present SDF volumes as an efficient datastructure …

A Sensitivity Equation Framework For Parameter Estimation In Dynamical Systems, Joshua Newey

Theses and Dissertations

We present a new framework for understanding parameter estimation in dynamical systems. The approach is developed within the modeling approach of continuous data assimilation. We outline the basic assumptions that lead to our derivation. Under these assumptions we show that the parameter estimation turns into a finite dimensional nonlinear optimization problem. We show that our derivation reproduces and extends the algorithm originally developed in [9]. We then implement these methods in three example systems: the Lorenz '63 model, the two-layer Lorenz '96 model, and the Kuramoto Sivashinsky equation. So as to remain sufficiently general, our derivations are largely formal; we …

Pretty Good State Transfer And Fractional Revival In Double Extended Star Graphs, Kellon G. Sandall

Theses and Dissertations

Much research has been done in the realm of quantum walks over networks of qubits. We primarily study a type of graph consisting of a path with two stars connected to the leaves which we call a Double Extended Star. We find that Pretty Good State Transfer can occur in many ways in a Double Extended Star and that Fractional Revival cannot occur in Double Extended Stars except when the length of the path within is one.

Extreme Ultraviolet And Xray Applications Of Carbon Nanotube Devices, Scott Olsen

Theses and Dissertations

The vacuum ultraviolet (VUV), extreme ultraviolet (EUV) and xray ranges of the electromagnetic spectrum have many unique properties and applications, such as medical treatment, photolithography, and astronomical observation. However, these applications require unique optical element designs, setups, and materials. carbon nanotubes (CNTs) are a fascinating material with thermal, mechanical, and chemical properties that may be beneficial for VUV, EUV, and xray applications. They are conductive, can be patterned into high aspect ratio structures, and are stable in high temperature vacuum. In this work, we report several carbon nanotube devices developed for the VUV, EUV, and xray range. These devices include …

Geological And Geophysical Model Of The Sand Wash Extensional Decollement, Utah, Brigham Louis Cardon

Theses and Dissertations

The Sand Wash Fault Zone (SWFZ) in the southern Uinta Basin is a significant extensional fault zone exhibiting complex deformation patterns. Our study integrates detailed structural analyses with a broader tectonic model to elucidate the tectonic evolution of the region. The SWFZ, extending over 34 km with a NW-SE strike, is underlain by an extensional decollement. Substantial deformation is observed in the upper layers, notably within the S2 sandstone of the Eocene Green River Formation. The deformation diminishes with depth, terminating at the oil-rich Mahogany oil shale zone, below which minimal deformation is observed. Our tectonic model, developed primarily through …

Using Neural Networks To Reconstruct Temperature From Fluorescent Data For Use In Bio-Microfluidics, Jacob G. Kullberg

Theses and Dissertations

It has been theorized that Quantum Dots (QD) can solve the temperature sensor issue with microfluidic devices. Quantum Dots are nano-sized semiconducting crystals with a radius of an excited electron-hole pair. When a QD is excited by a short wavelength light, the QD produces fluorescent light. As the temperature of the dot changes, the dot expands and shifts the fluorescent spectrum. Quantum Dots are small enough to be placed inside the microfluidic devices, and a spectrometer can measure the change in fluorescent data. This fluorescent data can be used to create fluorescent images corresponding to the QD temperature. These fluorescent …

Cellular Sorting Of The Dictyostelium Discoideum Slug, Erin Flowerday

Theses and Dissertations

Dictyostelium discoideum (Dd) cells are amoeba cells that feed on soil or plant leaf matter bacteria. They divide freely in the presence of food. When starved, cell division is ended, and cells transition from unicellular to multicellular organisms initiated by a chemoattractant, cyclic adenosine monophosphate (cAMP). This study intricately examines cellular sorting within the Dd slug, focusing on individual cell dynamics. Represented as oriented ellipsoids, these cells maintain constant volume through a viscoelastic structure. Applying force to specific semi-axes reveals predictable deformations, highlighting the relationship between force and deformation rate. Manipulating damping coefficients and spring constants uncovers insights into cell …

Investigating Cloth Sculpting For Simulation Control In Virtual Reality, Matthew S. Bishop

Theses and Dissertations

Artists require control and predictability over physically based simulations to create their required animation. This control can lead to reduced iteration time to get the desired simulation results. Controlling cloth simulations can require manual effort to create goal keyframes for control algorithms to match. Current techniques and research utilize a keyboard and mouse to create these goal keyframes. Other research has looked at using a virtual reality (VR) head-mounted display with controllers to improve the experience of completing similar animation tasks. However, we are not aware of any research that attempts to use VR as a tool to assist artists …

Optimization Of Mass Spectrometry-Based Methods For Low-Input And Spatial Proteomics, Andikan Jones Nwosu

Theses and Dissertations

Eukaryotic cells are highly heterogeneous. These cells are arranged into different compartments, carrying out separate functions and facilitating biological processes. Proteins are the effector biomolecules targeted to subcellular locations that help fulfill specific tasks in living organisms. Spatial proteomics can help unravel molecularly how protein abundance and localization are altered in cells, which is not feasible in traditional bulk-scale proteomics. To achieve this, our lab has developed a miniaturized sample processing platform called nanoPOTS, reduced separation columns' inner diameter to increase ionization efficiency and concentrate analytes for mass spectrometers and optimized data acquisition modes for increasing proteome coverage in spatial …

Striking At The Root: A Categorization Of Dns Clients, Tyler Dean

Theses and Dissertations

The Domain Name System (DNS) root servers have provided a useful look into the DNS and internet ecosystems for decades. We present a categorization of clients querying DNS root servers. Using two clustering algorithms on DNS traffic sampled in 2020, we can predict the structure and volume of queries originating from different types of clients. Previous research has used unsupervised techniques to better understand DNS traffic patterns, but none have, to our knowledge, considered clients beyond those driven by queries from end users. By performing clustering on IP addresses rather than on individual queries, we are able to examine the …

Strong Gelfand Pairs Of Some Finite Groups, Joseph E. Marrow

Theses and Dissertations

Strong Gelfand pairs describe a relation between a group and a subgroup, using a relation between inner products of their characters. We find all strong Gelfand pairs of the dihedral and dicyclic groups, and several of the sporadic groups. We provide some results for the strong Gelfand pairs of the affine linear groups, in addition to the exceptional classical groups $\mathrm{Sp}_4(q)$ for $q$ a power of $2$.

Information Geometric Approaches To Optimal Experimental Design And Reduced-Order Modeling In Ocean Acoustics, Jay C. Spendlove

Theses and Dissertations

This thesis demonstrates the application of information geometry to problems in underwater acoustics. Information geometry combines the fields of information theory and differential geometry by interpreting a multiparameter model as a Riemannian manifold in an ambient data space. Information geometry tools are especially powerful in context of problems of experimental design and model selection in ocean acoustics. The application area specifically considered in this research is geoacoustic inversion, where seabed parameter values are inferred from acoustical data. Chapter 2 contains a paper submitted to the Journal of Theoretical and Computational Acoustics, which introduces information geometry tools such as the model …

Documentation Of Norm Negotiation In A Secondary Mathematics Classroom, Michelle R. Bagley

Theses and Dissertations

While previous mathematics education research has shown that norms can change in mathematics classrooms, little research has closely documented the struggles, concessions, and compromises involved in the negotiation process. Negotiating norms is a complex process entailing deliberate teacher moves intended to promote norms, often met with misunderstandings or resistance from students. This thesis documented the negotiation process that occurred when a teacher attempted to require conceptual explanations from students who had not previously been accustomed to doing so. I recorded six days of instruction in a 9th grade algebra unit, transcribed the class discussions, and inferred norms "at play" for …

An Information Geometric Analysis Of A Shallow-Water Waveguide Using Vgs Parametrization, Michelle Wang

Undergraduate Honors Theses

In geoacoustic inversion, selecting an appropriate seabed parametrization, especially with an unknown number of sediment layers, is a challenge that is compounded by potential bias when establishing bounds in the parameter search space. One approach to addressing these issues is rooted in the techniques of Information geometry. Information geometry informs model selection and parameterization by quantifying which model parameters are informed by observational data. This paper provides an information geometric analysis of a shallow-water waveguide, where the acoustic properties of the lower half-space are derived from the viscous grain-shearing (VGS) model.

Specifically, we consider single-frequency transmission loss (TL) across a …

Rigorous Verification Of Stability Of Ideal Gas Layers, Damian Anderson

Theses and Dissertations

In this thesis we develop tools for carrying out computer assisted proof of the stability of traveling wave solutions of the spatially one-dimensional compressible Navier-Stokes equations with an ideal gas equation of state. In particular, we obtain rigorous, tight error bounds on a high-accuracy numerical approximation of the traveling wave profile for parameters corresponding to air, and we obtain rigorous representations in a neighborhood of positive and negative infinity of the solution to the first order ODE associated with linearizing the PDE equations about the traveling wave solution. We also develop supporting tools for rigorous verification of wave stability.

Addressing Social Inequalities Using Ai, Big Data, And Machine Learning, Erica L. Jensen, Lakell Archer, Sumaya Ali

Journal of Nonprofit Innovation

No abstract provided.

Application And Development Of Ceragenins In Medical Device Coatings For Clinical Settings, Elliot E. Sherren

Theses and Dissertations

Hospital-acquired infections (HAIs) pose a significant and increasing threat to global health. One primary cause of this threat is increasing antibiotic resistance. As traditional antibiotics continue to grow less effective, there is an urgent need for novel antimicrobial strategies. This work explores the potential of ceragenins, also known as cationic steroid antimicrobials (CSAs), as a promising alternative to combat HAIs. Specifically, we investigated potential roles that CSAs can play in the context of multiple medical device coatings in healthcare settings. Ceragenins are synthetic mimic of antimicrobial peptides (AMPs) which exhibit broad-spectrum antimicrobial activity against many common pathogens that have been …

Exploring Seizure Signal Processing And Methods To Characterize Seizure-Like Activity In Mouse Brains, Benjamin Kearsley

Undergraduate Honors Theses

Status Epilepticus (SE) is a dangerous type of seizure that is difficult to treat and can have permanent or fatal consequences. Developing methods to properly process and classify SE in Local Field Potential (LFP) signals are important steps towards being able to predict SE in clinic and save lives. This thesis explores methods for the seizure data processing LFP data with the goal of gaining a deeper understanding of the effect of brain region and tissue preparation paradigm on power output in specific frequency ranges. The brain regions compared are the neocortex and hippocampus, and the preparation paradigms are 4AP …

Elucidating The Role Of Aging In Protein Misfolding And Amyloid Cascade In Transthyretin Amyloidosis, Chad Hyer

Undergraduate Honors Theses

This study attempts to provide the first comprehensive proteomic analysis of protein folding stability (PFS) in transthyretin amyloidosis (ATTR) across different age groups to shed light on the mechanisms of age-mediated protein misfolding and the amyloid cascade. Utilizing the Iodine Protein Stability Assay (IPSA), we characterize the PFS of proteins across the serum proteome in a cohort of 100 individuals (18-85 years old) to investigate the impact of aging on changes in protein folding across the proteome. Presented are preliminary data from 20 participants.

Our study overcomes limitations in previous studies of ATTR by providing a structural perspective on TTR …

Synthesis Of Streptococcus Pneumoniae Serotypes 6a And 6b Di- And Trisaccharides As Propargyl Glycosyl Antigens For Glycoconjugate Vaccines, Tianyao Meng

Theses and Dissertations

Streptococcus pneumoniae (Spn) is a globally prevalent Gram-positive pathogen responsible for invasive pneumococcal diseases (IPD). Among its over 90 serotypes, Spn serotypes 6A (Sp6A) and 6B (Sp6B) are two of the most common causes of IPD around the world and are more frequently isolated from infections than most of the other serotypes. Our group has previously developed a method for making immune responses to bacterial glycans T cell-dependent, involving attachment of short synthetic glycans to a virus-like nanoparticle (VLP), and in combination with a natural killer T cell (NKT cell) adjuvant. This strategy enhanced immune responses by facilitating T cell …