Physical Sciences and Mathematics Commons^™

Implementing General Moment Equations For Parallel Closures In Nimrod, Hankyu Lee

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding how magnetic fields impact plasma transport is essential for improving the efficiency of thermonuclear fusion power plants. To address the transport problem, both plasma fluid equations and Maxwell’s equations must be solved. To solve these equations, it is necessary to derive closure relations that allow the system to be closed. Previous closure models are useful for describing the behavior of high-collisionality plasma but are not effective at low collisionality. To obtain closure relations valid for low collisionality, the first-order drift kinetic equation must be solved.

This study presents methods for numerically obtaining parallel closures for NIMROD code by deriving …

An Examination Of The Effects Of Prey Density, Mortality, Nutrients, And Foraging Tradeoffs On A System With Inducible Defenses: An Empirical And Theoretical Approach, Benjamin C. Ralston Daniel

All Graduate Theses and Dissertations, Fall 2023 to Present

To grasp the functioning and stability of ecosystems, it is important to understand species interactions. With many ecosystems becoming more imperiled from urbanization and anthropogenic influences it is important to understand ways in which species can adapt to rapid changes in their environment. Phenotypic plasticity is one such tool at nature’s disposal to initiate rapid change, where species with the same genetic makeup can have different expressed traits depending on their environment. Inducible defenses are one such form of phenotypic plasticity in which prey can express different levels and forms of defense depending on the threat of predation present in …

Dynamics Of Climate And Tectonics On Surface Processes And Their Sedimentary Archives In The Colorado Plateau And Basin And Range, Usa And The Calabrian Forearc, Sicily, Natalie M. Tanski

All Graduate Theses and Dissertations, Fall 2023 to Present

Landscapes change over time in response to movements of the Earth’s crust and the effects of climate. This dissertation examines how these factors shape different landscapes, focusing on erosion of river canyons in elevated plateaus, how the transport history in quartz sand may be encoded in its properties, and how a paleo-delta has formed in response to sea-level change and fault displacement. I use dating techniques, field methods, and topographic analyses to offer insight into erosional patterns and rates in different landscapes.

Rivers can take a long time to adjust to changes in boundary conditions, even after those changes have …

Informed Intervention Design, Deployment, And Analysis For The Computer Science Classroom, Jaxton J. Winder

All Graduate Theses and Dissertations, Fall 2023 to Present

Improving the teaching of computer science is a challenging task. Educators and computing education researchers devote large amounts of time, energy, and resources towards doing so effectively. One of the ways this is done is through research-informed design, deployment, and analysis of targeted interventions to the classroom. This thesis will detail research conducted at Utah State University targeting classroom interventions: centered around their design, deployment, and analysis.

One of these interventions aims to tackle student procrastination through the offering of “grace points”–forgiving a small amount of mistakes on a student’s assignment–for analyzing a homework assignment early. Through studying this intervention, …

Sparse Neural Network To Enhance Performance Under Limited Parameter Constraints., Nailah Rawnaq

Graduate Theses and Dissertations

Over the past decade, the widespread adoption of deep neural networks has been a breakthrough driven by significant computational advancements. Additionally, the number of parameters of those models is exponentially increasing for performing complex tasks and achieving better performance. However, in most practical cases, often there are constraints in the number of parameters due to limited resources in storage size and computational cost. Network pruning can lead to an optimal solution to this problem. In this thesis, I present supporting evidence to the hypothesis that higher sparsity leads to better performance for a convolution-based neural network. I perform performance studies …

Gan With Skip Patch Discriminator For Biological Electron Microscopy Image Generation, Nishith Ranjon Roy

Graduate Theses and Dissertations

GAN models have been successfully used for image generation in various sections such as real-life objects like human faces, cars, animal faces, landscapes, etc. This work focuses on biological electron microscopy (EM) image generation. Unlike other real-life objects, biological EM images are obtained through electron microscopy techniques to study biological specimens. Electron microscopy offers high resolution and magnification capabilities, making it a powerful tool for visualizing biological structures at the nanoscale. However, using GAN models for biological EM image generation poses challenges due to the complex and unique arrangements of biological structures and the sparse and asymmetrical patterns in EM …

Tuning Electronic Transport And Magnetic Properties Of Layered Magnetic Materials, Md Rafique Un Nabi

Graduate Theses and Dissertations

Two-dimensional magnetic materials (2DMMs) have gained significant interest due to their potential for novel physical phenomena and device applications. Mn2-xZnxSb, with its tunable magnetic properties and stable tetragonal layered structure, offers a rich platform for exploring these phenomena. The introduction of Zn into the Mn2Sb lattice efficiently tunes magnetic and electronic properties, making it a compelling candidate for high-performance spintronic devices. With this motivation, we synthesized Mn2-xZnxSb (0 ≤ x ≤ 1) single crystals using a flux method. Mn2Sb exhibits ferrimagnetic order below 550 K with antiparallel spins aligned along the c-axis for two Mn magnetic sublattice Mn(I) and Mn(II), …

Investigations Of Sulfurized Polymers For Their Use In Lithium-Sulfur Cells, Alan M. Rowland

All Theses

With the invention of the Lithium-Ion cell in the latter half of the 20th century, there has been a continued endeavor for innovation in compact energy-storage. Combined with the ever-growing need to move away from fossil fuels, electrochemical energy storage has seen a myriad of research projects in the pursuit of finding the ‘beyond-lithium’ cell. One of these projects that I personally assisted with was lithium-sulfur cells, which allow for a significantly greater energy storage capacity when compared to lithium-ion cells. In investigating a popular cathode in lithium-sulfur cells, sulfurized polyacrylonitrile (SPAN), it was hinted that there may be more …

Training Uav Teams With Multi-Agent Reinforcement Learning Towards Fully 3d Autonomous Wildfire Response, Bryce Hopkins

All Theses

As climate-exacerbated wildfires increasingly threaten landscapes and communities, there is an urgent and pressing need for sophisticated fire management technologies. Coordinated teams of Unmanned Aerial Vehicles (UAVs) present a promising solution for detection, assessment, and even incipient-stage suppression – especially when integrated into a multi-layered approach with other recent wildfire management technologies such as geostationary/polar-orbiting satellites and CCTV detection networks. However, there remains significant challenges in developing the necessary sensing, navigation, coordination, and communication subsystems that enable intelligent UAV teams. Further, federal regulations governing UAV deployment and autonomy pose constraints on real-world aerial testing, creating a disconnect between theoretical research …

A Comprehensive And Interactive Visualization Tool To Support Equitable Adoption Of Electrified Transportation, Aashay Maheshwarkar

All Graduate Theses and Dissertations, Fall 2023 to Present

As urban areas continue to grow, the deployment of electric vehicle (EV) charging infrastructure becomes crucial for sustainable development. This study is focused on the development of a data visualization tool that integrates diverse datasets, including traffic patterns, Points of Interest (POI), pollution levels, and socioeconomic indicators, to analyze the current state and potential expansion of EV charging stations. Our visualization tool highlights the significant impact of EV infrastructure on reducing urban pollution and improving socioeconomic outcomes. Areas with a higher density of charging stations show significantly lower levels of unemployment and pollution, emphasizing the dual benefits of EV adoption. …

Optimization Of Learning Algorithms In Neuromorphic Computing Systems., Oyinpere S. Ameli

Masters Theses

Spiking Neural Networks (SNNs) are a type of artificial neural network that aim to more closely mimic the data processing processes observed in biological neural systems. However, one major challenge in training these networks has been their non-differentiable nature, which makes it difficult to apply traditional gradient-based learning techniques. Different approaches have been proposed to address this challenge, ranging from supervised learning - largely inspired by error backpropagation in Deep Neural Networks - to unsupervised learning, which closely emulates biological learning approaches such as spike-timing dependent plasticity (STDP). Neuromorphic hardware platforms such as Intel's Loihi offer programmable plasticity that allows …

Spontaneous Plant Colonization Of Newly Established Green Roofs: An Experimental Approach, Braden Matthew Coats

Masters Theses

Urban Heat Island Effect (UHI) increases heat risks in densely developed environments. Ecosystem services provided by green spaces are known to mitigate UHI. Green roofs, designed as novel ecosystems, transform less-utilized spaces like rooftops into functional areas, executing ecosystem functions in densely populated urban environments where traditional green spaces are less common. Research has examined ways to reduce the obstacles of implementing green roofs to maximize accessibility and efficiency of the performed ecosystem services. Research involving plant community dynamics found that maximizing biodiversity on green roofs enhances the ecosystem services provided. Utilizing spontaneous colonizing species, or species that are not …

Assessment Of Enzyme Stability In Subsurface Sediments By Computational Methods, Kambiz Kalhor

Masters Theses

The microorganisms found in marine subseafloor sediment play a vital role in global carbon and nitrogen cycles, with an estimated 2.9×10²⁹ cells, accounting for about 0.6% of Earth’s total living biomass. These microbes grow at a very slow rate, with carbon turnover occurring over the course of years to thousands of years, about six orders of magnitude slower than sulfate reducing bacteria in pure culture. These slow metabolic rates suggest that the enzymes they produce must also have extended lifespans in order to be effective over such long periods of time. As a result, these enzymes are likely to …

2d Temperature Map Acquisition Using Hyperspectral Imaging System (Hsis), Anthony Kim

Masters Theses

Imaging techniques are close to our lives and are used for various applications. In the engineering field, one of the dominant techniques is hyperspectral imaging. It is a necessary tool that combines spectroscopy and digital photography and provides additional information on what is imaged by the imaging system. Hyperspectral imaging has been applied to various fields including remote sensing, cultural relic conservation, food microbiology, forensic science, biomedicine, etc.

In particular, work was done to apply hyperspectral imaging to measure the temperature and emissivity of an object. Due to its ability to measure temperature and emissivity without being in contact with …

Transfer Learning For Predictive Maintenance: A Case Study, Colter A. Swanson

Masters Theses

In light of recent strides in high-performance computing, the concept of transfer learning has emerged as a prominent paradigm within the realm of Artificial Intelligence and Machine Learning methodologies. Analogous to the human brain's capacity to assimilate information across related domains for pattern recognition, transfer learning has swiftly asserted its dominance, particularly in deep learning applications such as image classification and natural language processing. Despite its ascendancy in these domains, there exists a lack of comprehensive investigations in alternative domains, notably those encompassing tabular data formats. This thesis seeks to redress this gap by conducting an empirical examination of transfer …

The Geometry Of Ancient Solutions To Curvature Flows, Sathyanarayanan Rengaswami

Doctoral Dissertations

Following the tremendous success of the mean curvature flow, other variants such as the Gauss curvature flow, inverse mean curvature flow have been investigated in great detail, leading to interesting applications to other fields including partial differential equations, convex geometry etc. This calls for an investigation of curvature flow as a general phenomenon. While basic existence and uniqueness results, roundness estimates etc have been obtained, there isn't a substantial body of work that addresses the geometry of solutions of curvature flows and their relation to the choice of speed function used. It is therefore interesting to investigate curvature flows as …

Mathematical Modeling And Numerical Approximations Of Combustion Instability Frequencies And Growth Rates, Harvey B. Ring Iii

Doctoral Dissertations

This dissertation presents a mathematical model and numerical simulations to determine the resonant frequencies and their associated growth rates for longitudinal modes in a combustion system similar to that found in a rocket engine. The mathematical model, which is applicable to a two-duct system with a thin flame between the two ducts, each of which having constant area and properties, considers the case of axial mean velocity and uses a vibrating wall at the inlet to select the frequency so that all modes may be found. The model is applied to the acoustics equations describing pressure and velocity fluctuations, derived …

Creating A Virtual Hierarchy From A Relational Database, Yucong Mo

All Graduate Theses and Dissertations, Fall 2023 to Present

In data management and modeling, the value of the hierarchical model is that it does not require expensive JOIN operations at runtime; once the hierarchy is built, the relationships among data are embedded in the tree-like hierarchical structure, and thus querying data could be much faster than using a relational database. Today most data is stored in relational databases, but if the data were stored in hierarchies, what would these hierarchies look like? And more importantly, would this transition lead to a more efficient database? This thesis explores these questions by introducing a set of algorithms to convert a relational …

Shedding Light On Past Ice-Free Intervals In Northwest Greenland: Luminescence Dating Of The Base Of The Camp Century Ice Core, Hawke Woznick

All Graduate Theses and Dissertations, Fall 2023 to Present

The goal of this thesis is to provide greater resolution on the age and character of the subglacial sediment recovered from the base of the Camp Century ice core, northwestern Greenland. Geochemical analysis indicated that the upper sub-ice sediments were geochemically different and experienced greater weathering than the basal unit underlying a one-meter silty ice lens. Analysis of feldspars within the very fine sand fraction indicates they are dominated by potassium feldspar. Sediment was dated using luminescence, which provides an age for the last time sediment was exposed to light. Luminescence analysis returned ages around 420 thousand years old, which …

Evaluation Of Electrochemical Corrosion, Electrodeposition, And Other Electroanalytical Methods As Investigative Forensic Techniques For Advancing Metal Substrate Analysis, Crystal C. Kitanovski

UNLV Theses, Dissertations, Professional Papers, and Capstones

Friction ridge skin, bearing unique patterns of epidermal ridges commonly known as fingerprints, has served as a crucial tool for identification since ancient times, with its utilization dating back to Chinese culture around 221 B.C. Today, friction ridge skin impressions remain vital evidence in forensic investigations, aiding in the identification of suspects. While fingerprints, palm prints, and footprints can all serve as identifying markers, this dissertation focuses specifically on fingerprints, broadly classified as visible or latent. Latent fingerprints, though invisible to the naked eye, constitute the majority of prints collected from crime scenes, necessitating physical, chemical, or physicochemical processing for …

An Analysis Of The Propagation Of Gravitational Radiation Under A Graviton Of Nonzero Mass And Its Implications For Cosmological Measurements, Margaret Johnston

UNLV Theses, Dissertations, Professional Papers, and Capstones

Under the assumptions of General Relativity (GR), gravitational waves propagate at the speed of light and their mediation can be represented as a particle through a massless graviton. We investigate the impact and observability of the presence of a massive graviton, how such a modification to GR would also modify the observed gravitational waves from astrophysical sources, and how this effect can be used as an independent measurement of cosmmological parameters, including the Hubble parameter H0. We simulate the impact of a massive graviton on compact binary coalescence observation in a near-future LIGO-Virgo-KAGRA interferometer network through a modification to the …

New Insights Into The Diverse Intraplate Volcanism Present Within The Howland And Baker Island United States Exclusive Economic Zone, Nicholas Foresta

UNLV Theses, Dissertations, Professional Papers, and Capstones

The origin of oceanic volcanism has been attributed to various mechanisms, such as upwelling mantle plumes, lithospheric extension driven decompression melting, and small-scale convective cells in the asthenosphere. Discovering the range of magmatic drivers present in the ocean basins aids in understanding mantle geodynamics and tectonic processes. A recent seafloor exploration campaign within the Howland and Baker Island (HBI) U.S. Exclusive Economic Zone (EEZ; approximately near the equator and the International Date Line) resulted in the collection of multiple lava flow samples, which offer valuable insights into the complex origins and dynamics of intraplate seamounts. According to current absolute plate …

Application Of Machine Learning Algorithms In Healthcare, Dwaipayan Mukhopadhyay

UNLV Theses, Dissertations, Professional Papers, and Capstones

Machine Learning (ML) is a subset of artificial intelligence that has made substantial strides in predicting and identifying health emergencies, disease populations, and disease state and immune response, amongst a few fields of healthcare. Here we provide a brief overview of machine learning-based approaches and learning algorithms. Second, we discuss a general procedure of ML and review some studies presented in ML application for several healthcare fields. We also briefly discuss the risks and challenges of ML application to healthcare.This dissertation also consists of four different cases in healthcare where we have applied ML techniques on real life data sets. …

Effects Of Climate Change On (Semi)-Arid Ecosystems In The Southwestern United States, Charlotte Van Der Nagel

UNLV Theses, Dissertations, Professional Papers, and Capstones

Climate change is considered amongst the most severe threats to terrestrial and aquatic ecosystems globally. Ecosystems in the southwestern United States have specifically been impacted by intense drought conditions since 2000. Higher temperatures combined with altered precipitation stresses many ecosystems; however, ecosystem specific responses to such stressors may vary. Here, the effects of climate change on semi-arid ecosystems are analyzed for some of the most vulnerable ecosystems in the southwestern United States: lacustrine, riparian, and dryland ecosystems.

Lakes and reservoirs in arid environments often serve as drinking water sources and recreational areas where high water quality is essential. Climate change …

Characterizing Gsk3Β Interaction And Kinetics Via Isothermal Titration Calorimetry, W A Bhagya De Silva

UNLV Theses, Dissertations, Professional Papers, and Capstones

Glycogen synthase kinase 3β (GSK3β) is a multifunctional serine/threonine kinase involved in several key signaling pathways, including glycogen metabolism, WNT/β-catenin, and Hedgehog signaling. Hyperactivity of GSK3β has been linked to Alzheimer’s disease, bipolar disorder, type II diabetes, and some cancers. Therefore, GSK3β is of interest as a target for therapeutics. Lithium ion (Li+) is a classical inhibitor of GSK3β. Structurally similar beryllium ion (Be2+) is ~1000-fold more potent. Lithium and beryllium have demonstrated pathway-specific and cell type-specific inhibition of GSK3β, prompting an investigation into the inhibitory mechanisms and thermodynamic characteristics of the metal-enzyme interaction.Isothermal titration calorimetry (ITC) is a label-free …

Scoring Single-Sample Pathway Expression Level Using Graph Autoencoder, Eunyoung Jang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Single-sample pathway analysis (ssPA) is a bioinformatics technique used to assess the activity of biological pathways in individual samples, rather than relying on aggregated data from multiple samples. This approach allows for the detection of pathway activation or suppression in single samples, making it a valuable approach in research and clinical applications where individual variability is critical. In this paper, we propose a deep-learning method that scores individual pathway expression levels using a graph autoencoder. The proposed method provides insights into the biological processes and leverages the high dimensionality of gene expression data by setting the nodes in the neural …

Image Processing Techniques For Water Droplet Penetration Time And Contact Angle Estimation, Sai Balaji Jai Kumar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Water droplet behavior on soil surfaces plays a critical role in numerous environmental processes, including soil erosion, hydrological dynamics, and ecosystem health. Accurate characterization of soil water repellency, quantified by parameters such as water droplet penetration time (WDPT) and contact angles (WDCA), is essential for informed decision-making in agricultural management, forestry practices, and land-use planning. Despite the significance of these parameters, challenges exist in reliably estimating them due to the complex and dynamic nature of soil-water interactions. This thesis address challenges in estimating WDPT and WDCA, by leveraging state-of-the-art image processing techniques and machine learning algorithms. The research focuses on …

A Heuristic Approach To Operations And Control Of Btm-Ders For Bill Management And Grid Services, Md Arshad Rashid Shaon

UNLV Theses, Dissertations, Professional Papers, and Capstones

Behind-The-Meter (BTM) distributed energy resources (DERs) have emerged as a critical and transformative force within the energy sector. These decentralized energy assets, which include solar photovoltaic (PV) systems, battery energy storage systems (BESS), and thermostatically controlled loads (TCLs), are increasingly essential for empowering customers by granting them greater control over their energy production and consumption, thereby reducing reliance on centralized power sources. Additionally, they have the potential to play a pivotal role in enhancing grid resilience by providing grid services. This study investigates the management of customer electricity bills and grid services through the integration of various BTM-DERs, particularly solar …

Mining Gambling Data For Modeling Gambling Behavior Patterns, Piyush Aniruddha Puranik

UNLV Theses, Dissertations, Professional Papers, and Capstones

Understanding player behavior for responsible gambling research is a difficult task due to the lack of data on players’ activities. Past studies in this area are largely limited to publicly available behavioral data or aggregated players data. Problem gambling in gamblers is typically identified only after they have already been addicted or have already been engaging in problematic gambling behavior. Furthermore, “risky” gambling behavior has historically been difficult to define due to the varying patterns of gambling activity that could potentially be attributed to it.In this dissertation we illustrate the methodology and algorithms used to engineer financial data for further …

Implementing Radformation At Personalized Radiation Oncology: Enhancing Efficiency And Precision, Devin J. Peart

UNLV Theses, Dissertations, Professional Papers, and Capstones

RadMachine is a data quality management application implemented at Personalized Radiation Oncology (PRO) to streamline quality assurance (QA) tests. It offers various functions assisting medical physicists in a radiation oncology clinic, including inputting, analyzing, managing, exporting, and monitoring QA data. Physicists create test lists following the recommendations provided by the American Association of Medical Physics (AAPM). These lists track results for units such as the Varian Edge, Varian BRAVOS, and Siemens SOMATOM go.Open Pro CT scanner. Ancillary equipment used for testing also has assigned test lists to store calibration factors and receive calibration expiration reminders. The primary goal of utilizing …