Digital Commons Network^™

Characterization Of L-Band Resonators And Relaxation Times Of Soₓ- Radicals At X-Band, Georgina Naa Odey Amassah

Electronic Theses and Dissertations

Electron Paramagnetic Resonance (EPR) analysis requires resonators optimized for specific experimental challenges. Volume resonators enclose samples, while surface coil resonators allow imaging of larger subjects. For in vivo studies, L-band frequencies are commonly used because they offer a good balance between signal-to-noise ratio (S/N) and the ability to penetrate tissue. Rapid Scan (RS) EPR at L-band frequencies was chosen for my studies of resonators because of this balance but presents a challenge for sensitivity.

The spatial position dependence of signal intensity was evaluated for selected paramagnetic samples using 10 mm and 30 mm surface coils. The 10 mm coil, with …

Self Spin-Orbit Torques, Ryan Greening

Electronic Theses and Dissertations

Spin–Orbit torques (SOTs) provide an energy-efficient pathway to control magnetization in nanoscale heterostructures. Recently, spin-orbit coupling within ferromagnets has been shown to generate self spin-orbit torques (SSOTs) on the magnetization itself. Previous work on self spin-orbit torques relies on thick ferromagnets with complicated film structures with chemical disorder or compositional gradients to generate inversion symmetry breaking. This dissertation advances experimental methodology and presents data on the quantification of self spin-orbit torques in magnetic thin films due to the spin-orbit coupling of standard 3d ferromagnets.

First, I develop an oblique-incidence magneto-optical Kerr effect (MOKE) technique that exploits a mirror-assisted double reflection …

Developing Deep Learning Methods For Cognitive Impairment Detection Based On Non-Invasive Data, Muath Alsuhaibani

Electronic Theses and Dissertations

Cognitive impairment detection is on the rise to help reduce the burden of healthcare costs on institutions and individuals. Mild Cognitive Impairment (MCI) is an early stage of cognitive decline progressing to Alzheimer’s disease (AD) or AD-related Dementia (ADRD). Detecting the early stages of AD/ADRD is crucial for early interventions among older adults to mitigate cognitive decline over time. However, the current diagnostic methods are often costly and/or invasive, such as MRI and PET scans. Thus, the search for non-invasive and cost-effective screening tools for the early detection of cognitive impairment using speech, language, visual, and motor data is growing. …

Enhancing Cataract Surgery Outcomes: Optimal Use Of Pre- And Post-Operative Eye Drops, Keith Skolnick M.D., Anu Valiaveedu

Mako: NSU Undergraduate Student Journal

Many preoperative and postoperative cataract patients struggle with comprehending the use of prescription medication as directed. Language barriers and low health literacy levels are major factors contributing to improper use of prescriptions. To increase patients comprehension, the Fort Lauderdale Eye Institute employed an educational intervention consisting of a live presentation and an instructional video. Results found that 44% of patients were hesitant to ask questions to clinical staff, 32% felt overwhelmed, and nearly 70% lacked confidence in using their prescribed eye drops. Following the intervention, 91% of patients reported increased confidence in their medications, and most indicated that the video …

Engineering Protein Linkers For Optimized Telsam-Darpin Fusion And Crystallization With Electric Field-Based Polymer Orientation, Maria Jose Pedroza Romo

Theses and Dissertations

Fusing a variant of the sterile alpha motif domain of the human translocation ETS leukemia protein (TELSAM) to a protein of interest significantly enhances crystallization and diffraction quality. TELSAM is a pH-dependent, polymer-forming crystallization chaperone that, when covalently fused to a protein, forms a well-ordered crystal lattice. However, the success of this method depends on two factors: 1) the design of the linker connecting TELSAM to the target protein, which influences both crystal packing and target orientation, and 2) the prevention of TELSAM polymer flipping, a phenomenon that disrupts lattice periodicity and impairs structure determination. To address the first challenge, …

Decreasing Foraminiferal Flux In Response To Ongoing Climate Change In The Santa Barbara Basin, California, Emily Harvard, Katherine Cherry, Claudia R. Benitez-Nelson, Eric Tappa, Catherine V. Davis

Faculty Publications

The rapid response of foraminiferal assemblages to changing climate makes their shells an invaluable geological record of the past. However, the time frame over which foraminifera respond to climatic signals and the specific drivers influencing assemblage composition and abundance remain obscure. We focus on the impact of ongoing, anthropogenic climate change on planktic foraminifera in the California Current ecosystem, which would appear as a nearly instantaneous event in the sediment record. The Santa Barbara Basin sediment trap, located off the coast of California, USA since 1993, provides a record of more than 30 years of particulate and foraminiferal flux in …

Satellite-Based Identification Of Mesoscale And Submesoscale Eddies And Fronts In The Gulf Of Mexico, Ethan Cruz

Theses and Dissertations

Mesoscale and submesoscale processes in the Gulf of Mexico (GoM) are fundamental in shaping the region’s physical and biogeochemical ocean dynamics. Advances in high-resolution satellite observations now allow detailed detection of submesoscale (< 25 km radius) and mesoscale eddies and ocean fronts, which drive heat, nutrient, and carbon fluxes. This dissertation integrates two complementary investigations: (1) a comparison of eddy-tracking algorithms: Contour Tracing (CT) and Temperature Thresholding (TT), applied to Optimum Interpolation Sea Surface Temperature (OISST, 1/4°) and Operational Sea Surface Temperature and Ice Analysis (OSTIA, 1/20°) products; and (2) a comparative evaluation of three ocean front detection algorithms: Canny Edge Detection (Canny), the Cayula–Cornillon Algorithm (CCA), and the Belkin–O’Reilly Algorithm (BOA), across multiple satellite-derived parameters, including sea surface temperature (SST), sea surface salinity (SSS), chlorophyll-a (Chl-a), and altimetry-derived absolute dynamic topography (ADT). The eddy-tracking analysis shows that the higher-resolution OSTIA consistently detected more eddies than OISST, with TT performing best during winter when SST gradients were strongest. The front detection analysis, incorporating datasets from the Surface Water and Ocean Topography (SWOT) and Plankton, Aerosol, Cloud, Ocean Ecosystem (PACE) missions, was evaluated under diverse conditions, including flood and drought periods, Loop Current phase changes, and extreme weather events. A machine learning–based Gaussian Mixture Modeling (GMM) approach was also developed, providing a novel framework for dynamic front detection. By benchmarking traditional and machine learning methods, this integrated study identifies optimal algorithm–dataset combinations for resolving submesoscale and mesoscale features in the GoM, with applicability to other regions.

Milkfish (Chanos Chanos) Bones As A Biosorbent For Mercury (Ii) Contamination In Water, Seth Uriel K. Neri, Ethan Kyle Mangao, Christian Kevin F. Redoblado, Anthony Cesar Y. Ponce, Roby Boy P. Riego, Jupiter O. Yap

Sinaya: A Philippine Journal for Senior High School Teachers and Students

Heavy metals, such as mercury contamination in water sources are a major environmental and public health issue in many countries. Traditional methods for removing heavy metals from water are effective but often costly and unsustainable and may produce secondary waste. Recent trends favor more sustainable alternatives, such as biosorbents in treating water with heavy metals. Milkfish (Chanos chanos), a common fish in the Philippines, contains hydroxyapatite in the bones that can bind with heavy metals through physical and chemical adsorption mechanisms. This study aims to evaluate the mercury (II) reduction capacity of biosorbent derived from milkfish bones in water, specifically …

Dissolution Mechanism Of Nonionic Polyether Surfactants In Supercritical Co2, Ning Xu, Yanling Wang, Baojun Bai, Shizhang Cui, Zan Gao, Yu Zhang, Di Li, Wenjing Shi, Wenhui Ding, Peixu Ma

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Polyoxyethylene ether is an efficient CO₂-philic compound with significant potential applications in CO₂ flooding, which requires CO₂-philic surfactants with high solubility in supercritical CO₂ (scCO₂). This study elucidates the molecular and atomic-level dissolution mechanism of the fatty alcohol polyoxyethylene ether (AEO) in scCO₂ by combining phase-behavior experiments and molecular dynamics simulations. The solubility of AEO in scCO₂ is measured using a semiconductor laser. AEO containing three polyoxyethylene (EO) groups exhibited the highest solubility in scCO₂.The solubility of AEO in scCO₂ decreased with an increase in the number …

Full-Stack Quantum Computing, Benjamin C A Morrison

Physics & Astronomy ETDs

Quantum computing is a promising tool for solving computational problems in several areas, including the simulation of physical and chemical systems. The design of practical quantum computing systems for these applications is a daunting task, requiring collaborative work by interdisciplinary teams considering different abstractions of the same systems. This dissertation presents work on the development of those abstractions, and on components that bridge multiple layers of abstraction. I first provide an introduction to quantum circuit model computation, error correction with stabilizer codes, and physics simulation algorithms. In joint work with the QSCOUT software team, I then describe the development of …

Is Criticality A Unified Setpoint Of Brain Function?, Keith B. Hengen, Aaron Shew

Physics Faculty Publications and Presentations

Brains face selective pressure to optimize computation, broadly defined. This is achieved by mechanisms including development, plasticity, and homeostasis. Is there a universal optimum around which the healthy brain tunes itself, across time and individuals? The criticality hypothesis posits such a setpoint. Criticality is a state imbued with internally generated, multiscale, marginally stable dynamics that maximize the features of information processing. Experimental support emerged two decades ago and has accumulated at an accelerating pace despite disagreement. Here, we lay out the logic of criticality as a general computational endpoint and review experimental evidence. We perform a meta-analysis of 140 datasets …

Acoustic Characterization And Modeling Of Heated Supersonic Tactical Jet Aircraft And Launched Rockets, Logan Troy Mathews

Theses and Dissertations

Understanding and accurately modeling the acoustic sources and propagation of high-intensity tactical jet aircraft and rocket noise is essential for vehicle design, environmental impact assessment, and mitigation strategies. Despite progress in the understanding of these sources, significant challenges persist in both predictive modeling and noise mitigation. This dissertation advances both the characterization of full-scale supersonic tactical jet aircraft noise sources and the development of modern empirical prediction models for rocket launch noise. Across multiple measurement campaigns and modeling efforts, the work integrates advanced array signal processing, high-fidelity field measurements, and improved empirical methods to expand the physical understanding of source …

Magnetic Ordering And Dynamics In Assemblies Of Magnetite Nanoparticles Throughout The Superparamagnetic Transition, Johnathon Michael Rackham

Theses and Dissertations

Magnetic nanoparticles are used in nanotechnologies and biomedical applications, such as drug targeting, hyperthermia treatment, MRI contrasting agents, and bio-separation of compound solutions. Magnetite (Fe3O4) nanoparticles stand to be effective in these roles due to the non-toxic nature of magnetite and its strong magnetization. To this end, a greater understanding of the magnetic behavior of the individual magnetite nanoparticles is needed when a collection of them is used. This research seeks to discover the local magnetic ordering and dynamics of fluctuations of ensembles of magnetite nanoparticles at various stages of the magnetization process, throughout the superparamagnetic blocking transitions, and for …

Modeling The Importance Of Life Exposure Factors On Memory Performance In Diverse Older Adults: A Machine Learning Approach, Evan Fletcher, Marianne Chanti-Ketterl, Emily Hokett, Yi Lor, Umesh Venkatesan, Ruijia Chen, Omonigho M. Bubu, Rachel Whitmer, Paola Gilsanz, Zvinka Z. Zlatar

Moss-Magee Rehabilitation Papers

INTRODUCTION: Many health life exposure factors (LEFs) influence cognitive decline and dementia incidence, but their relative importance to episodic memory (an early indicator of cognitive decline) among diverse older adults is unclear. We used machine learning to rank LEFs for memory performance in a large and diverse US cohort.

METHODS: Kaiser Healthy Aging and Diverse Life Experiences (KHANDLE) and Study of Healthy Aging in African Americans (STAR), participants underwent neuropsychological testing and answered questionnaires about multiple LEFs. XGBoost and Shapley Additive exPlanation values ranked the importance of factors influencing cross-sectional episodic memory in the full sample and by sex and …

U.S News & World Report 2025 Graduate Program Rankings, Unlv & Unr, Dre Boyd-Weatherly, Caitlin J. Saladino, William E. Brown Jr.

Higher Education

This fact sheet presents 2025 graduate program rankings for the University of Nevada, Las Vegas (UNLV) and for the University of Nevada, Reno (UNR) based on the data published in spring 2025 by U.S. News & World Report. The graduate program categories reported include business, education, engineering, fine arts, law, medicine and health care, sciences and mathematics, and social sciences and humanities.

Machine Learning Research On Time Series Data, Zeyi Fan

Lingnan Theses (MPhil & PhD)

Time series generated by complex systems, such as industrial IoT and user behavior systems, confront two core challenges: structured missingness (e.g., continuous or periodic gaps) that disrupt temporal dependencies, and the difficulty in effectively modeling dynamic long- and short-term temporal dependencies inherent in evolving patterns (e.g., user interests). Traditional approaches struggle to balance the preservation of local dependency continuity and the rational association of global long-range dependencies in structured missing scenarios, often incurring high computational costs. In temporal pattern modeling, the lack of adaptive mechanisms to fuse evolving long- and recent behavior trends (e.g., stable interest inertia vs. short-term preference …

Efficient Decontamination Of Organophosphate-Based Pesticides And Nerve Agent Simulants Mediated By N-Containing Nucleophiles, Emmanuel Kingsley Darkwah, Puspa Aryal, Saidulu Todeti, Jared Kenik, Samuel Insall, V. Prakash Reddy, Chariklia Sotiriou-Leventis

Chemistry Faculty Research & Creative Works

There is a growing interest in developing safer and more effective decontaminating agents for organophosphate-based pesticides and nerve agents. In this study, we present an effective method for the nonaqueous decontamination of these compounds using small-molecule-based decontaminating agents under ambient conditions. Our approach utilizes aryl and heteroaryl carboxaldehyde hydrazones and hydrazides to effectively hydrolyze nerve agent simulants into their nontoxic degradation products. The effectiveness of this method was evaluated using a range of nerve agent simulants, including dimethyl 4-nitrophenyl phosphate (DMNP), dimethyl methyl phosphonate (DMMP), and triphenyl phosphate (TPhP). In the presence of the heteroaryl hydrazone, the rate of hydrolysis …

Theoretical Study On Electronic And Optoelectronic Properties Of Some C^N^N- And C^C^C-Chelated Iridium(Iii) Complexes For Oleds, Ayhan Üngördü

Turkish Journal of Chemistry

The electronic and optoelectronic properties of 8 C∧N∧N- and C∧C∧C-chelated Ir(III) complexes were investigated using density functional theory at the Becke-style 3-parameter Lee-Yang-Par and triple zeta plus polarization level. Based on reorganization energy calculations, complex 7 was identified as a promising ambipolar material, while complexes 1 and 2 had efficient hole transport properties. Complex 8 had low ionization potential and is therefore a strong candidate for hole transport applications. Complex 4 had high electron affinity and therefore has potential as an effective electron acceptor material. Photophysical analysis showed that all complexes had phosphorescent properties, with complexes 5 and 6 showing …

Combining Code Analysis And Pedagogical Guidance: Automated Tools For Teaching Debugging In Introductory Programming, Yana Malysheva

McKelvey School of Engineering Graduate Student Theses & Dissertations

The ability to debug code is critical to being a programmer and represents a distinct skill from writing code. Yet debugging is rarely explicitly taught in introductory programming and Computer Science courses. Instead, novices typically develop their own debugging habits and strategies when they encounter bugs in their code, which are often less effective than those of expert programmers. When students do seek help with debugging, they traditionally turn to office hours conducted by Teaching Assistants (TAs) or, increasingly, to Large Language Models such as ChatGPT. However, both sources of assistance have limitations. TAs are often students themselves with limited …

Code Stories For Software Evolution, John Joseph Allen

McKelvey School of Engineering Graduate Student Theses & Dissertations

Programmers spend more than half of their time comprehending code, and in particular struggle to answer questions about the rationale, intent, and history behind software artifacts. Through this dissertation, I explore how history-aware tools can help programmers understand unfamiliar software artifacts. First, I investigated how providing additional context -- historical code changes grouped by the original developer's stated subgoals and the web foraging activity of the original developer impacted the process of code reuse. I found that programmers utilized these resources to 1) make better analogies between their reuse scenario and what code was already written, and 2) anchor into …

Towards Graph Foundation Models: Few-Shot And Zero-Shot Learning On Graphs, Hao Liu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Graphs naturally model complex relationships and interactions across various domains, including social networks, biological systems, and recommender platforms. Graph Neural Networks (GNNs) have emerged as powerful tools for learning effective graph representations through iterative message passing, significantly improving performance in tasks such as node classification, link prediction, and graph classification. However, the success of GNNs largely depends on abundant labeled data, posing challenges in practical scenarios where labeled data is scarce or unavailable. This dissertation addresses these challenges by exploring few-shot and zero-shot learning within the graph domain. We first propose COLA, a self-supervised few-shot node classification method that exploits …

Spatial Patterns In Electronic Health Record Data-Based Predictive Modeling: A Case Study Of Prenatal Care And Preeclampsia, Abigail Lewis

McKelvey School of Engineering Graduate Student Theses & Dissertations

The electronic health record (EHR) documents interactions between patients and healthcare systems and is widely used for secondary research on health outcomes due to broad adoption. While EHR data support efficient clinical informatics research, they are subject to biases stemming from healthcare seeking behavior, health system attributes, and individual or environmental characteristics. Place-based characteristics, in particular, strongly influence when and how patients access care and shape health outcomes. These biases in EHR data can affect predictive modeling pipelines which leverage them, contributing to variation in model performance across groups. In healthcare, where predictive models are increasingly used to guide care, …

Computational Imaging Under Incomplete Information, Weijie Gan

McKelvey School of Engineering Graduate Student Theses & Dissertations

Computational imaging is a pivotal field that synergizes physical measurement principles with advanced algorithms to generate visual information. An important task in this field is solving imaging inverse problems that aim to reconstruct high-quality images from observed measurements. Model-based deep learning (MBDL) has emerged as a particularly powerful tool for tackling these inverse problems by integrating machine learning (ML)-driven priors with knowledge of the imaging physics. This dissertation focuses on the pervasive challenge of informational incompleteness in computational imaging, arising from various practical and physical limitations, that hinder the widespread adoption of ML-driven computational imaging algorithms in practice. This includes: …

Multimodal Representation Learning For Geospatial Soundscape Mapping, Subash Khanal

McKelvey School of Engineering Graduate Student Theses & Dissertations

Sound is one of the fundamental senses that helps us reason about our environment. There exists an intricate relationship between the visual appearance of a location and the distribution of sounds present there. We propose leveraging this relationship to formulate the task of soundscape mapping—predicting the most probable distribution of sounds that could be perceived at a given geographic location, as observed in its overhead imagery. To support research on this task, we curated a comprehensive dataset, GeoSound, which consists of geotagged audio recordings from various sources, paired with both low- and high-resolution overhead imagery. We approach the soundscape mapping …

Faster, Higher, Stronger: Modern Methodologies For The Calibration, Exploration, And Utilization Of Agent-Based Models, David O'Gara

McKelvey School of Engineering Graduate Student Theses & Dissertations

Increases in computing power and availability have led to the widespread use and adoption of agent-based models (ABMs) in the physical, biological, and social sciences. At their core, ABMs represent a novel paradigm for scientific inquiry: their micro-level specification allows for the simulation of the individual components of a system which yields a deeper understanding of dynamic processes such as contagion and adaptive decision-making when used appropriately. However, several hurdles exist when attempting to use ABMs to their full potential. In this thesis, we will explore and address several challenges in designing and utilizing ABMs, with a focus on applying …

Spectral Mixture Analyses Of Hematite-Rich And Clay-Bearing Terrains In Meridiani And Oxia Planum, Mars, Thomas Jake Condus

Arts & Sciences Graduate Student Theses and Dissertations

Minerals have characteristic absorption features in the visible and near-infrared wavelength range, which can be detected in remotely sensed observations using methods such as spectral parameter maps or modeled via spectral mixtures. My dissertation uses both methods on orbital and ground-based single-scattering albedo data to assess the surface compositions of Meridiani Planum and Oxia Planum, regions of Mars that are rich in secondary minerals. A probabilistic approach to spectral unmixing was adopted to account for the nonuniqueness of model solutions, with endmember abundance and grain size maps being produced for Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) orbital images. For …

The Implications Of Insecure Use Of Fonts Against Pdf Documents And Web Pages, Junjie Xiong, Mingkui Wei, Xiao Han, Zhuo Lu, Yao Liu

Computer Science Faculty Research & Creative Works

This paper identifies the importance of the safe use of fonts in web and document security. We find multiple attack surfaces that can be exploited by an adversary using malicious fonts. We conduct a comprehensive evaluation of Portable Document Format (PDF) documents collected from the real world to investigate how an attacker can bypass PDF signatures. We further evaluate the potential security threats that an attacker can bring to web-based emails. Our study shows that various security issues may be caused by the inappropriate use of fonts, which are nevertheless overlooked in the past years. As such, guidelines promoting the …

Geol 12 Natural Disasters Syllabus, Anestoria Shalkowski

Open Educational Resources

Hazards are events which have the capabilities to damage property and or life. Understanding natural hazards and how these can become disasters are important in reducing the impacts of such events. This syllabus provides a description of the material to be examined and the expected student outcomes upon completion of the course.

The Future Intensification Of Hydrological Extremes And Whiplashes In The Contiguous United States Increase Community Vulnerability, Surendra Maharjan, Wenzhao Li, John D. Bolten, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Hydroclimatic whiplash rapid shifts between drought and flood poses growing risks to U.S. communities. Here, we assess historical extremes and future projections using a normalized streamflow metric: the annual mean flow’s deviation from the 1981–2020 average, expressed as a fraction of that average. This metric is applied to United States Geological Survey records and Localized Constructed Analogs downscaled projections under Representative Concentration Pathways 4.5 and 8.5. Results reveal sharp regional disparities, with drought deficits exceeding 300% of normal flow during multi-year droughts. By linking hydrologic outcomes with the Federal Emergency Management Agency’s National Risk Index, we find that counties facing …

Receiver Function Imaging Of The Mantle Transition Zone Beneath The East Sayan Mountains And Adjacent Area In Central Asia: Implications For Lithospheric Drip And Intraplate Cenozoic Volcanism, Yangyang Liao, Kelly H. Liu, Stephen S. Gao

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

To provide constraints on the formation mechanisms of intracontinental volcanisms and intriguing lithospheric thickness variations in the East Sayan Mountains and surrounding areas, we stack P-to-s receiver functions to image the 410-km and 660-km discontinuities. Mantle transition zone (MTZ) thickening observed in a continuous area is attributable to ancient slab remnants, and Cenozoic volcanisms in the peripheral area can be explained by slab dehydration. The thinning of the MTZ in the Tuva-Mongolian Massif can be explained by mantle upwelling branches induced by slab subduction. Our results reveal an approximately circular area in the MTZ that is significantly thicker than usual, …