Physical Sciences and Mathematics Commons^™

Photoelectic Driven Decomposition Of Uracil Via Hard X-Ray Irradiation, Trimaan Malik

UNLV Theses, Dissertations, Professional Papers, and Capstones

Radiation damage into biological samples creates substantial challenges across a wide range of fields, from biochemistry to materials science. This comprehensive study investigates the effects of x-ray irradiation on uracil, the only nucleobase exclusive to Ribonucleic acid (RNA), to understand how doping with 10% (by mass) of specific powdered elements impacts the sustained radiation damage. The experiments were conducted at the Brockhouse Undulator Beamline of the Canadian Light Source synchrotron. Virgin and doped uracil samples were irradiated with hard x-rays, above their respective absorption edges, and studied with x-ray diffraction to compare their decomposition behaviors. The Uracil reflections on the …

Lake Mead: A Living Museum, Marley Salveter

UNLV Theses, Dissertations, Professional Papers, and Capstones

Lake Mead, the largest man-made water project in the nation and a prolific source of electricity, irrigation, and recreation for much of the western population, is currently experiencing a drastic transformation. Amid the ongoing water crisis parching the west, the once overflowing reservoir is consistently shrinking, descending into depths historically uncharted.

While serving as a bleak demonstration of climate change’s effects, the body of water is simultaneously assuming an alternative role that may be less apparent to the public. As water levels decline, Lake Mead is actively metamorphosing into a “Living Museum”, by gradually unveiling previously submerged artifacts. As a …

Evaluation Of The Extent Of Floods In 2022 In Different Land Cover And Land Use Classes In Sindh Province, Pakistan Using Sentinel-1 And Sentinel-2 Imageries, Alina Shrestha

UNLV Theses, Dissertations, Professional Papers, and Capstones

Floods are one of the most frequent and most devastating natural disasters, which cause widespread destruction and pose significant risks to human life, infrastructure, and the environment. Advancement in remote sensing technologies and methodologies have demonstrated their efficacy in disaster-related applications, such as the detection, monitoring, and analysis of floods. This study explores the utilization of Synthetic Aperture Radar (SAR) and optical imagery for flood extent mapping and studying the extent of flood over various land cover and land use classes in Pakistan's Sindh province, utilizing the cloud computing power of Google Earth Engine. The change detection method identified extensive …

Online Learning For Acid-Fast Bacilli Detection In Histopathological Images, Shizhao Wang

UNLV Theses, Dissertations, Professional Papers, and Capstones

The acid-fast stain is frequently used for laboratory diagnosis of tuberculosis. It is a labor intensive task requiring thorough examination of extremely high-resolution images to pinpoint the presence of the mycobacteria. This paper presents a machine learning assisted slide image analysis tool with the aim of aiding histopathology professionals in the accurate diagnosis of tuberculosis in patients through the analysis of microscopic imagery. The proposed tool combines a digital whole slide image viewer with an online learning framework. We also conducted a survey of different state-of-the-art online learning methods, and found that MIR with pre-training has the best performance on …

Simulation And Design Of Ion Traps Using The Method Of Fundamental Solutions, Trevor Taylor

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this thesis I apply the numeric method, the Method of Fundamental Solutions (MFS), to solve for the fields create by ion traps in various configurations, such as quadrupole ion traps, linear ion traps, toroidal ion traps, and toroidal surface ion traps. The traps are then designed to maximize desired qualities such as minimization of their anharmonicity, and their ability to shuttle ions. A particular focus will be on the toroidal surface ion trap, as well as its ability to shuttle ions. This trap is planned for future experiments involving measurement of the electron Electric Dipole Moment.

Understanding Disk Substructures With 3d Self-Consistent Thermodynamics, Shangjia Zhang

UNLV Theses, Dissertations, Professional Papers, and Capstones

Protoplanetary disks are birthplaces of planets. The past decade witnessed a great advance- ment in disk observations by Atacama Large Millimeter Array (ALMA) and extreme adaptive optics (ExAOs). Hundreds of disks have been observed at high angular resolutions and revealed rich substructures (e.g., gaps/rings) at midplane and atmosphere, at least part of which are per- turbed by planets. Deep understanding of disk physics has a great potential to unveil more young planets from substructures and distinguish those that are not caused by planets. I worked on con- straining young planet populations using planet-disk interaction simulations and substructures and self-consistent treatment …

N-Methylation Of Amphetamine By Phenylethanolamine N- Methyltransferase: Implications For Chronic Therapeutic Use, Mackenzie Pavlik

Master's Theses

In current forensic analysis, the presence of methamphetamine in a sample is routinely presumed to reflect methamphetamine abuse. This is due to the expectation that individuals either abusing, or receiving amphetamine for therapeutic purposes (e.g. as treatment for ADHD) will not generate any significant levels of methamphetamine as a product of metabolism. We have hypothesized however, that because amphetamine can serve as a substrate for methylation by phenylethanolamine n-methyltransferase (PNMT), (which will be in equilibrium with the reverse demethylation reaction) some individuals chronically taking amphetamine for therapeutic purposes may generate low levels of methamphetamine that would show up on a …

The Forget Time For Random Walks On Trees Of A Fixed Diameter, Lola R. Vescovo

Mathematics, Statistics, and Computer Science Honors Projects

A mixing measure is the expected length of a random walk on a graph given a set of starting and stopping conditions. We study a mixing measure called the forget time. Given a graph G, the pessimal access time for a target distribution is the expected length of an optimal stopping rule to that target distribution, starting from the worst initial vertex. The forget time of G is the smallest pessimal access time among all possible target distributions. We prove that the balanced double broom maximizes the forget time on the set of trees on n vertices with diameter …

Unraveling The Physics Of Quasar Jets Using Hst Polarimetry, Devon Clautice

Theses and Dissertations

We present a multiwavelength study of three high-power FR II (quasar) jets -- 3C 273, PKS 0637-752, and 1150+497 -- with an emphasis on new high-quality Hubble Space Telescope (HST) optical polarimetry and Chandra X-ray Observatory imaging. Relativistic jets from active galactic nuclei transport energy and mass from the supermassive black hole’s accretion region out to Megaparsec-scale lobes, with effects that feedback into galaxy formation and cluster energetics. We build on recent work which has called into question our fundamental understanding of FR II jet physics, and suggest that highly-efficient particle acceleration must be taking place in situ …

Selected Topics On Sequential Designs For Decision Making, Caroline Kerfonta

All Dissertations

This dissertation is comprised of three parts. The first proposes a sequential approach to determine the experimental setting with the minimum variance (Kerfonta et al., 2024). Two acquisition functions are developed to assist developing the approach. Theoretical results along with a case study using data from crystallization experiments is conducted to show the ability of the proposed method to correctly select the experiment with the minimum variance. The second and third parts propose adaptations to the Bayesian optimization algorithm using transformed additive Gaussian processes (TAG) as the surrogate model. The goal of using the TAG framework is to decompose the …

Factors Predictive Of The Development Of Surgical Site Infection In Thyroidectomy, A Replication Study Of Myssiorek (2018), Kaitlyn M. Kenig

Capstone Experience: Master of Public Health

The original study aimed to show that thyroidectomy does not result in surgical site infection (SSI) in most cases, and thus routine prescription of antibiotics is not necessary. The study looked to see what risk factors could predict the incidence of SSI. This would highlight those individuals who were at most risk of developing SSI, and then antibiotics would only be prescribed to these individuals instead of all or most individuals who undergo thyroidectomy.

This study used NSQIP data to look at incidence of SSI and look for risk factors that may be predictive of SSI. Only surgeries that were …

Final 2022 Insufficiently Reclaimed Sites Sampling Bres No. 08 – Belle Of Butte Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Artificial Intelligence-Powered Assessment Of Pathologic Response To Neoadjuvant Atezolizumab In Patients With Nsclc: Results From The Lcmc3 Study, Sanja Dacic, William D Travis, Jennifer M Giltnane, Filip Kos, John Abel, Stephanie Hilz, Junya Fujimoto, Lynette Sholl, Jon Ritter, Farah Khalil, Yi Liu, Amaro Taylor-Weiner, Murray Resnick, Hui Yu, Fred R Hirsch, Paul A Bunn, David P Carbone, Valerie Rusch, David J Kwiatkowski, Bruce E Johnson, Jay M Lee, Stephanie R Hennek, Ilan Wapinski, Alan Nicholas, Ann Johnson, Katja Schulze, Mark G Kris, Ignacio I Wistuba

Faculty, Staff and Student Publications

Introduction: Pathologic response (PathR) by histopathologic assessment of resected specimens may be an early clinical end point associated with long-term outcomes with neoadjuvant therapy. Digital pathology may improve the efficiency and precision of PathR assessment. LCMC3 (NCT02927301) evaluated neoadjuvant atezolizumab in patients with resectable NSCLC and reported a 20% major PathR rate.

Methods: We determined PathR in primary tumor resection specimens using guidelines-based visual techniques and developed a convolutional neural network model using the same criteria to digitally measure the percent viable tumor on whole-slide images. Concordance was evaluated between visual determination of percent viable tumor (n = …

High-Dimensional Mediation Analysis Of Multi-Omics Data, Sunyi Chi

Dissertations and Theses (Open Access)

Environmental exposures such as cigarette smoking influence health outcomes through intermediate molecular phenotypes, such as the methylome, transcriptome, and metabolome. Mediation analysis is a useful tool for investigating the role of potentially high-dimensional intermediate phenotypes in the relationship between environmental exposures and health outcomes. Rapid development of high-throughput technologies have made mediation analysis of multi-omics data critical to gain groundbreaking insights into the biological mechanisms underlying the disease etiology. This dissertation aims to develop mediation analysis methods that utilize the enormous amount of multi-omics data in assessing mechanisms of disease etiology. It contains three projects where I propose advanced mediation …

Evaluation Of An End-To-End Radiotherapy Treatment Planning Pipeline For Prostate Cancer, Mohammad Daniel El Basha, Court Laurence, Carlos Eduardo Cardenas, Julianne Pollard-Larkin, Steven Frank, David T. Fuentes, Falk Poenisch, Zhiqian H. Yu

Dissertations and Theses (Open Access)

Radiation treatment planning is a crucial and time-intensive process in radiation therapy. This planning involves carefully designing a treatment regimen tailored to a patient’s specific condition, including the type, location, and size of the tumor with reference to surrounding healthy tissues. For prostate cancer, this tumor may be either local, locally advanced with extracapsular involvement, or extend into the pelvic lymph node chain. Automating essential parts of this process would allow for the rapid development of effective treatment plans and better plan optimization to enhance tumor control for better outcomes.

The first objective of this work, to automate the treatment …

Quantum Computing Based Image Segmentation For Treatment Planning Applications, Rachel Glenn

Dissertations and Theses (Open Access)

The exponential advancement of quantum computing has led to its increasing integration into medical radiology. Quantum-inspired algorithms have helped accelerate magnetic resonance fingerprinting for possible applications in clinic settings. Numerous global initiatives are currently integrating quantum computing into medical radiology and health care applications. Given the potential of quantum computing to enhance clinical care and medical research, we have developed this primer to introduce medical physicists to the realm of quantum computing. In this primer, we explore the application of currently available quantum computing-based auto-contouring methods to image segmentation. These implementations serve as prototypes of existing quantum algorithms tailored for …

Weighted Ehrhart Theory: Extending Stanley's Nonnegativity Theorem, Esme Bajo, Robert Davis, Jesús A. De Loera, Alexey Garber, Sofía Garzón Mora, Katharina Jochemko, Josephine Yu

School of Mathematical & Statistical Sciences Faculty Publications

We generalize R. P. Stanley's celebrated theorem that the h∗-polynomial of the Ehrhart series of a rational polytope has nonnegative coefficients and is monotone under containment of polytopes. We show that these results continue to hold for weighted Ehrhart series where lattice points are counted with polynomial weights, as long as the weights are homogeneous polynomials decomposable as sums of products of linear forms that are nonnegative on the polytope. We also show nonnegativity of the h∗-polynomial as a real-valued function for a larger family of weights.

We generalize R. P. Stanley's celebrated theorem that the h ⁎ -polynomial of …

Using Pre-Trained Models For Vision-Language Understanding Tasks, Rui Cao

Dissertations and Theses Collection (Open Access)

In recent years, remarkable progress has been made in Artificial Intelligence (AI), with an increasing focus on integrating AI systems into people’s daily lives. In the context of our diverse world, research attention has shifted towards applying AI to multimodal understanding tasks. This thesis specifically addresses two key modalities, namely, vision and language, and explores Vision-Language Understanding (VLU).

In the past, addressing VLU tasks involved training distinct models from scratch using task-specific data. However, limited by the amount of training data, models may easily overfit the training data and fail to generalize. A recent breakthrough is the development of Pre-trained …

Investigating Controls On Temporal And Spatial Variation Of Dissolved Uranium At Springs In Horn Creek Drainage, Grand Canyon National Park, Arizona, Usa, Collin Davidson

UNLV Theses, Dissertations, Professional Papers, and Capstones

Groundwater is a critical resource in the Grand Canyon, providing water to local communities, millions of annual visitors, and ecosystems. One major concern for this critical resource is the potential for uranium contamination in conjunction with uranium mining efforts. Upper Horn Bedrock Spring (UHB) in the Horn Creek drainage of the Grand Canyon sits below the oldest uranium mine in the region, Orphan Lode mine. UHB spring contains the highest concentration of dissolved uranium in the region, eclipsing the Maximum Contaminant Level (MCL) set by the USEPA by an order of magnitude on average. This research and recent collaboration with …

Performance Effects Of Dissociated Hydrogen In Nuclear Thermal Propulsion Engines, Richard Adam Gorrell

UNLV Theses, Dissertations, Professional Papers, and Capstones

Nuclear thermal propulsion (NTP) research considers hydrogen dissociation as negligible to design and analysis of propulsion engines. This study reintroduces chemically reacting flow to NTP engine analysis for investigation of the dissociation effect on engine performance. A first-principles approach observes the basic chemical mechanism and reaction within the high-speed, high-temperature NTP flow to baseline expected atomic hydrogen levels and validate equilibrium. A surface reaction study looks into hydrogen absorption through dissociation and its effect on the boundary layer, and bulk flow. For total performance, the resulting dissociated flow is analyzed through nozzle expansion and performance metrics calculated.

All historic reactor …

Standard And Non-Standard Log-Linear Models For 2 × 2 Contingency Tables, G M Toufiqul Hoque

UNLV Theses, Dissertations, Professional Papers, and Capstones

Log-linear models can be used to model the joint relationship of two or more categorical variables in a multiway contingency table. In a log-linear model, the logarithm of the expected joint counts (or the logarithm of the joint probabilities) in a contingency table can be written as a linear model.

Most log-linear models used in practice are standard. Standard log-linear models include the traditional parameter terms we see in ANOVA models: an overall effect, main effects, and various kinds of interaction terms.

Standard log-linear models are divided into hierarchical and non-hierarchical. Hierarchical models satisfy the hierarchy principle: if a higher-order …

Computational Study For Tissue-Specific Dosimetric Quantities Of Secondary Radiation For Mars Exploration, Sungmin Pak

UNLV Theses, Dissertations, Professional Papers, and Capstones

The two main sources of primary space radiation, Galactic Cosmic Rays (GCRs) and Solar Particle Events (SPEs), encompass a spectrum of ions, ranging from protons (Z=1) to nickel ions (Z=28), with energies spanning from less than 1 keV to exceeding a few TeV. While SPEs represent sporadic events primarily comprised of a high flux of low- to intermediate-energy protons, GCRs are characterized by continuous low flux of diverse ions with higher energies, peaking in intensity near the solar minimum. During a Mars mission, astronauts will encounter primary particles of high energy from GCR and SPE spectra, capable of penetrating spacecraft …

Identifying Disease-Related Gene-Environment Interactions Based On Method Of Moments, Linchuan Shen

UNLV Theses, Dissertations, Professional Papers, and Capstones

Human diseases are often caused by a complex interplay of multiple factors, including genetics and environmental factors. These factors can play critical roles in the development and progression of diseases. Although genome-wide association studies (GWAS) have successfully identified many genetic variants associated with human diseases, the estimated effects of these variants are small and can explain only a relatively small portion of the heritability of the underlying diseases.

Detecting gene-environment interactions (G × E) can shed light on the biological mechanisms of diseases. However, most existing methods that investigate G × E only look at how one environmental …

Algorithm-Based Linearly Graded Compositions Of Gesn On Gaas (001) Via Molecular Beam Epitaxy, Calbi Gunder, Mohammad Zamani-Alavijeh, Emmanuel Wangila, Fernando Maia De Oliveira, Aida Sheibani, Serhii Kryvyi, Paul C. Attwood, Yuriy I. Mazur, Shui-Qing Yu, Gregory J. Salamo

Physics Faculty Publications and Presentations

The growth of high-composition GeSn films in the future will likely be guided by algorithms. In this study, we show how a logarithmic-based algorithm can be used to obtain high-quality GeSn compositions up to 16% on GaAs (001) substrates via molecular beam epitaxy. Herein, we use composition targeting and logarithmic Sn cell temperature control to achieve linearly graded pseudomorph Ge_1−xSn_x compositions up to 10% before partial relaxation of the structure and a continued gradient up to 16% GeSn. In this report, we use X-ray diffraction, simulation, secondary ion mass spectrometry, and atomic force microscopy to analyze and …

Convergence Estimate Of Minimal Residual Methods And Random Sketching Of Krylov Subspace Methods, Peter Westerbaan

All Dissertations

This study concerns two main issues in numerical linear algebra: convergence estimate of minimal residual methods based on explicit construction of approximate min-max polynomials for in- definite matrices, and development and analysis of Krylov subspace methods using non-orthonormal basis vectors based on random sketching. For a matrix A with spectrum Λ(A), it is well known that the min-max polynomial problem min max |pk (z)| pk ∈Pk, pk (0)=1, z∈Λ(A) is used to bound the relative error of Krylov subspace minimum residual methods or similar methods. For a symmetric positive definite matrix A, the min-max polynomial for the Conjugate Gradient (CG) …

Models Of Functional Redundancy In Ecological Communities, Sandra Annie Tsiorintsoa

All Dissertations

Functional redundancy is the number of taxa that perform a given function within a given community. In most systems, high levels of functional redundancy are important, because they contribute to ecosystem stability. However, we currently have very little understanding of why functional redundancy varies among communities. One possible factor that could affect functional redundancy is environmental complexity. Many studies show that simplified ecosystems harbor communities with lower taxon diversity. What is less clear is if this simplicity and lower taxon diversity also affects functional redundancy. To answer this question, we use metacommunity models to explore the connection between environmental complexity …

Developing Machine Learning Agency Among Youth: Characterizing Youth Critical Use, Examination, And Production Of Machine Learning Applications, Ibrahim Oluwajoba Adisa

All Dissertations

This study explores how middle school-aged youths at an afterschool center utilized, examined, and produced AI applications for social good with the support of adults and peers. The study employs a qualitative single case study design. It uses thematic analysis and quantitative ethnography methods to analyze data from multiple sources, including field notes, interviews, focus groups, story completions, video recordings, and artifacts. Findings indicated that engaging youths in critical exploration of AI tools enhanced their ability to design interest-based AI applications that provide solutions for healthcare problems, security, and accessibility. Moreover, the computational thinking practices that youth engaged in increased …

Design, Fabrication, And Characterization Of Advanced High-Power Single-Mode 9xxnm Semiconductor Lasers, Xiaolei Zhao

All Dissertations

This thesis presents the comprehensive design, fabrication, and demonstration of advanced high-power, high-efficiency single-mode semiconductor lasers operating at a wavelength of 9xxnm. We begin with the design of the laser epitaxial structure, serving as the cornerstone for achieving high-power high-efficiency lasers. Our methodology integrates a semi-analytical calculation model, which accounts for Longitudinal Spatial Hole Burning (LSHB) and Two-Photon Absorption (TPA) effects, facilitating a thorough exploration of how design parameters influence output power and conversion efficiency. This approach offers an effective and time-efficient epitaxial structure optimization strategy compared to conventional full 3D simulation models.

Subsequently, we demonstrate high-power, high-efficiency ridge waveguide …

Engineering Multifunctional Silicon Nanostructures From Biorenewable Cellulose Nanocrystals, Nancy Chen

All Dissertations

The imperative search for alternative materials to address the pressing demand for advance energy storage is underscored by the escalating environmental predicaments. Lithium-ion batteries (LIBs) with graphite anodes have become the benchmark in energy storage; however, they are approaching a saturation point in terms of energy density. Silicon emerges as a promising contender to supplant graphite, owing to its profuse availability, cost-effectiveness, and impressive specific capacity of 4200 mAh g^-1. By integrating silicon anodes, LIBs stand to undergo a radical transformation, markedly diminishing in weight and size, thus heralding a novel wave of compact, lightweight energy storage systems. …

A Manufacturing-To-Response Pathway For Manufacturing Optimization Of Carbon Fiber Reinforced Polymer Composite Structures, Madhura Limaye

All Dissertations

Over the past decade, there has been an increased adoption of thermoplastic and thermoset based continuous carbon fiber reinforced polymer (CFRP) composites for structural applications in several industries. Among the different manufacturing methods, thermoforming process for thermoplastic based continuous CFRP’s offer a major advantage in reducing cycle times for large scale productions. Similarly, out-of-autoclave curing process for thermoset based continuous CFRP’s using heated tooling enables production of large composite structures. However, these manufacturing processes can have a significant impact on the structural performance of parts by inducing undesirable effects. These effects include inhomogeneous fiber orientations, thickness variations, and residual stresses …