Physical Sciences and Mathematics Commons^™

Using Seafloor Geomorphology, Classification Schema, And Spatial Analysis To Predict Geologic Structures, With Applications For Mars, Emma Morgan

Theses and Dissertations

This study evaluated whether seafloor geomorphology can be used to predict subsurface fault locations along the Cascadia continental margin and explored whether such relationships can be transferred to Mars. Geomorphological classification schemas such as geomorphons, bathymetric position index (BPI), slope, rugosity, aspect, and curvature were derived from seafloor bathymetry data and used as predictor variables in maximum entropy (MaxEnt) models developed separately for Pre-Pleistocene, Pleistocene, Quaternary, and active fault datasets. Model performance ranged from AUC = 0.62 to 0.67, showing moderate predictive skill, with younger fault systems exhibiting stronger geomorphic associations. A secondary analysis showed a weaker but detectable relationship …

Evaluating The Spatial Relationship Between Geomorphology And Subsurface Structures On The Us Atlantic Margin With Applications To Other Terrestrial Planets, Andrea Caitlyn Stiles

Theses and Dissertations

High-resolution digital elevation models (DEMs) are widely available for terrestrial planetary bodies, but subsurface structural data remain limited. This research evaluated whether surface geomorphology could predict subsurface features, specifically faults and methane seeps, along the US Atlantic continental margin as an analog site. Faults were mapped with seismic interpretation and compared with quantitative geomorphic classifications derived from 100-m bathymetry including slope, aspect, rugosity, bathymetric position index, and geomorphon classes. Maximum-entropy modelling was used to predict fault occurrences from surface data. Results indicated that specific geomorphic landforms and slopes had the strongest control on fault presence, reflected in topographic expression of …

Accuracy Of Parameter Estimation For A Simple Gene Regulatory Network Model Is Sensitive To Network Motif, Number Of Parameters Estimated, And Magnitude And Direction Of Regulatory Relationships, Nikki C. Chun, Kam Dahlquist

Honors Thesis

A gene regulatory network (GRN) is a set of transcription factors that regulate the expression of genes encoding other transcription factors. The dynamics of a GRN explain how gene expression changes over time. GRNmap is a MATLAB software package that uses ordinary differential equations to model dynamics of small-scale GRNs. We used the program to estimate production rates, expression thresholds, and regulatory weights for each transcription factor in three related literature-derived GRNs based on yeast cold shock microarray data previously collected in the Dahlquist Lab. We noticed large differences in estimated weight values when 1-2% of the expression values were …

Phase Field Modeling And A Fully Discrete Numerical Scheme For Two-Phase Incompressible Mhd Flows With Different Densities, Electric Conductivities And Viscosities, Xiaoyong Chen, Rui Li, Jian Li, Xiaoming He, Yanping Lin

Mathematics and Statistics Faculty Research & Creative Works

This article establishes a phase field model for governing the two-phase incompressible MHD flows with different densities, electric conductivities, and viscosities. In addition to the coupling between the Cahn–Hilliard phase field equations and the single-phase MHD equations together with the varying parameters, it is physically faithful and mathematically rigorous for the modeling to incorporate a relative flux term, which is related to the diffusion of the components, into the coupled system, inspired by Abels et al. and Shen and Yang. We present a linear fully discrete numerical scheme for this complex multi-physics system, which leverages the artificial compressibility method, an …

At The Crossroads Of Traditional And Nuclear Forensics: Decontaminating Radiologically Contaminated Dna Evidence Using Magnetic Beads, Rin Nyx Ruby

UNLV Theses, Dissertations, Professional Papers, and Capstones

Known for its impressive discriminatory power, deoxyribonucleic acid (DNA) fingerprinting stands as the “gold standard” of forensic investigation. However, complications arise when such evidence is contaminated with radioactive material. Though biological samples exposed to ionizing radiation can still yield comprehensive DNA profiles, most forensic laboratories lack the facilities which meet the safety and security requirements necessary for handling radioactive material. While nuclear facilities can decontaminate samples prior to forensic analysis, conventional methods for radiological decontamination – such as mechanical cleaning and chemical washes – may degrade the quality of the forensic evidence. The purpose of this study is to evaluate …

Cold Plasma Treatment Of Hydroponically Grown Basil: Effects On Essential Oil Composition For Sustainable Applications (Ocimum Basilicum), Judith Serwaa Marfo

Seton Hall University Dissertations and Theses (ETDs)

Abstract Essential oils are known to have medicinal benefits and pharmaceutical applications. This study investigates the impact of cold plasma treatment on hydroponically cultivated basil (Ocimum basilicum), focusing on physical growth traits, and essential oil composition. Preliminary trials validated our solvent extraction protocol using IPA, hexanes, and methanol without heat on store-bought basil. Rotary evaporation and GC-FID analysis successfully identified key compounds; eugenol, estragole, eucalyptol, and linalool. Plasma-treated hydroponic plants exhibited enhanced physical characteristics, including larger leaves and intensified green pigmentation, compared to untreated controls under identical conditions. The plasma treatment didn't just increase how much oil was extracted, but …

Semi-Rational Strategies For Antifungal Peptide Design, Akilah I. Mateen

Seton Hall University Dissertations and Theses (ETDs)

A recently emerged opportunistic fungi, Candida auris, has been subject to increased scrutiny due to its virulence and rapid geographical spread. Due to the indiscriminate use of antimicrobials as treatments for infectious diseases and as pesticides, the ubiquitous threat of multidrug resistance (MDR) looms large. The lack of progress in antifungal development is of high concern in the treatment of infectious diseases and a rise in fungal resistance highlight the need for updated treatment strategies. This work describes three strategies used to address these concerns:

•  The synthesis of a photosensitizer-membrane-active peptide (PS-MAP) conjugate, Ir-HKII15, that combines the ability of …

Phase Identification Of (La, Sr)Coo3 Solid Oxide Cell Electrode Films Using Dft Based Exafs, Musab A. Siddiqui

Seton Hall University Dissertations and Theses (ETDs)

Perovskite structured mixed ionic electronic conductor (MIEC) materials formed as films by metal-organic precursor deposition have excellent electrochemical performance in solid oxide cell (SOC) air electrode applications due to the large surface area provided by the manufacturing approach. MIEC films created by metal organic precursor deposition are often multi-phased due to low heat treatment temperatures and locally generated low oxygen partial pressures caused by the release of carbonaceous gases during the drying step of the fabrication process. In this work, we use extended x-ray absorption fine structure spectroscopy (EXAFS) to examine the phase contents of La0.8Sr0.2CoO3 (LSC82) and La0.6Sr0.4CoO3 (LSC64) …

Shelters In Motion, Erin Nicole Vallido Trasmano

Hospitality Design Graduate Student Capstones

Shelters in Motion is a modular temporary shelter system for festival and outdoor events that replaces disposable tents with reusable, durable design. Overall reducing environmental impact while significantly improving comfort and user experience.

A Descriptive Analysis Of Plant Leaf Disease Detection Using Machine Learning And Deep Learning Models: A Systematic Review, Arzoo Chamoli, Anuj Kumar

Turkish Journal of Electrical Engineering and Computer Sciences

Plant leaf disease detection (PLDD) is a growing active research area with burgeoning practical applications across various sectors such as agricultural monitoring, food security, and environmental conservation. Accurate segmentation and classification of plant leaf diseases remains a key challenge in the field of plant leaf disease prediction. The challenge demands automated methods for the plant disease identification because it needs to develop better crop management systems, which will boost agricultural production. In this article, we provide a systematic review of various machine learning (ML) and deep learning (DL) methods extensively used for PLDD. The review strategy follows a formal protocol, …

Multiobjective Optimization Framework For Renewable Energy Iot Networks Balancing Security, Energy Efficiency, And Communication Reliability, Muhammad Hjouj Btoush, Ashraf S. Mashaleh, Amjad Gawanmeh

Turkish Journal of Electrical Engineering and Computer Sciences

The deployment of Internet of things (IoT) networks powered by renewable energy sources presents unique challenges in balancing security requirements, energy efficiency, and communication reliability. This paper presents a comprehensive multiobjective optimization framework for secure renewable energy IoT nodes that addresses fundamental trade-offs between these competing objectives. We develop a mathematical model incorporating energy harvesting dynamics, security protocols, and communication performance metrics across various environmental scenarios. The proposed framework employs a modified NSGA-II algorithm to identify Pareto-optimal configurations for different deployment contexts. Through extensive simulation analysis, we demonstrate that hybrid energy sources (solar-wind combinations) with lightweight security protocols achieve optimal …

Predictive Current Control Approach For Grid-Integrated Multifunctional Converter Under Source And Load Disturbances, Ravi Kumar Majji, Tirumalasetty Chiranjeevi, Chilukoti Varaha Narasimha Raja, Nagulapati Kiran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper discusses and presents a model predictive control (MPC)-based predictive current control technique for a solar photovoltaic (PV)-integrated grid system during dynamic operation. This control technique employs extension pq (EPQ) theory to estimate reference currents and utilizes an MPC framework for tracking reference currents. Various MATLAB/Simulink simulations were conducted for solar PV generation (source disturbances) and dynamic loading. The results of the OPAL-RT OP4510 real-time simulation are also presented. A multifunctional grid-integrated converter (MFGC) integrates solar active power into the utility grid while achieving unity power factor, reactive power compensation, current balancing, and harmonic suppression. EPQ optimizes mathematical calculations, …

The Origins Of Chondrite Families, Isabelle M. Perron

UNLV Theses, Dissertations, Professional Papers, and Capstones

Chondrites, a type of primitive asteroid, are thought to have formed from dust and gas early in the life of our Solar System. These chondrites have remained unchanged since their formation, avoiding being melted or differentiated like other rocky bodies have. Due to this unique characteristic, chondrites can give us useful insight into how asteroids, planetesimals, and even the terrestrial planets formed. In order to study chondrites and their formation, I used code developed by Li et al. (2020), which utilizes thermodynamic code GRAINS (Petaev 2009), to see what conditions the chondrites may have originated from. GRAINS uses a variety …

Constructing A Laser Stabilization System For Frequency Metrology, Stephanie Letourneau

UNLV Theses, Dissertations, Professional Papers, and Capstones

Frequency metrology and quantum control, which uses light as a tool for measurement and manipulation, relies on spectrally narrow, stable lasers. Often thought of as being perfectly monochromatic and coherent, in reality, the free-running instantaneous linewidth of lasers can be on the order of hundreds of kHz in the millisecond time-frame and drift on the order of tens of MHz over hours. To correct for these instabilities in real-time, a variety of laser stabilization methods have been implemented, including the Pound-Drever-Hall (PDH) method, saturation absorption spectroscopy (SAS), and dichroic atomic vapor laser locking (DAVLL). All of these methods rely on …

Transboundary Groundwater Flow Between Niger And Nigeria In The Iullemeden Aquifer System, Gare Ambrose-Igho

UNLV Theses, Dissertations, Professional Papers, and Capstones

Groundwater is important in regions where water resources are not abundantly distributed such as arid and semi-arid regions. In many countries in Africa, groundwater serves as the most reliable source of water supply and supports over 50% of the African population. Groundwater is stored in underground water-bearing permeable rocks, rock fractures, or unconsolidated materials known as aquifers. Groundwater can be transboundary, meaning it crosses international political boundaries between two or more sovereign states. Transboundary aquifers are prone to overexploitation that depletes the groundwater resource and can cause a lowering of the water table and possible ground subsidence. Overexploitation in transboundary …

Digital Literacy And Language Proficiency As Factors Of Accessible Digital Training In The Hospitality Industry: Employee Perspectives Of Training And Working In A Diverse Industry, Gillian Bowden

UNLV Theses, Dissertations, Professional Papers, and Capstones

This explanatory sequential mixed methods study explored how digital literacy and language proficiency impact employees’ access to and engagement with digital training, as well as how these experiences influence their perceptions of training and the organization. In the quantitative phase, survey data were collected from hourly employees at a large foodservice corporation (n=67). Four constructs were assessed: digital literacy, language proficiency, accessibility, and engagement. Results indicated strong, statistically significant relationships with higher levels of digital literacy and language proficiency associated with greater accessibility and increased engagement with digital training materials. The large effect sizes suggest these competencies play a meaningful …

Exploring Ai-Driven Scaffolding For Critical Questioning In Argument Evaluation, Ebenezer A. Belete

UNLV Theses, Dissertations, Professional Papers, and Capstones

The fast-paced changes caused by generative AI (GenAI) innovations call for exploring the potential benefits of GenAI in empowering 21st-century pedagogical strategies. Previous studies in the field of argumentation have shown how students can benefit from using critical questions. However, scaffolding argument evaluation through custom GenAI using critical questions has not been systematically investigated. This study involved two components: (1) designing and determining the usability of a GPT-powered conversational assistant (CQMAA Conversational Assistant) and (2) testing its impact on participants' efficacy for argument evaluation and their acceptance of GenAI as a learning tool through a pretest–posttest experiment. A convergent mixed-methods …

Relativistic Transients From Compact Objects: Radiation Processes And Geometric Effects, Connery Chen

UNLV Theses, Dissertations, Professional Papers, and Capstones

Relativistic transients from compact objects probe the most extreme regimes of physics, where strong gravity, ultra-relativistic outflows, and high-energy radiation operate simultaneously; understanding the underlying radiation mechanisms and extrinsic geometric and relativistic effects is essential for interpreting observations and constraining source properties. I develop theoretical and computational frameworks to quantify how geometry and relativistic motion shape observed emission from fast radio bursts, gamma-ray bursts, and neutron star mergers. I analyze fast radio bursts from the Galactic magnetar SGR J1935+2154 and show that emission geometry strongly governs burst energetics and detection probability, and influences the link between radio and X-ray emission. …

Interpretable Deep Learning Models For Trustworthy Prediction Of Enzyme Functions, Louis Dumontet

UNLV Theses, Dissertations, Professional Papers, and Capstones

Trustworthy prediction of enzyme function from protein sequences remains a central challenge in computational biology, particularly when annotated data are limited, imbalanced, or incomplete. This dissertation develops interpretable deep learning methods for enzyme discovery and enzyme function prediction from amino acid sequences. First, it introduces PEPIC, an interpretable convolutional neural network for substrate-level prediction of hydrolytic plastic-degrading enzymes. Using curated and expanded sequence datasets, PEPIC improved predictive performance over benchmark methods, identified sequence regions aligned with catalytic and substrate-binding residues, and supported the discovery and experimental validation of a previously uncharacterized PET-degrading enzyme. Second, this dissertation investigates the integration of …

Harnessing Backcasting To Identify Drivers Of Critical Warming At Hoover Dam Using Hydrodynamic And Machine Learning Models, Eunice Ledres

UNLV Theses, Dissertations, Professional Papers, and Capstones

Elevated water temperatures can pose a significant threat to dam infrastructure, potentially damaging turbines, overheating internal components, and forcing generator shutdowns. This study uses a backcasting framework to evaluate how future scenarios may result in elevated water temperatures. Backcasting defines undesirable outcomes and works backward to identify the conditions that lead to them. The developed backcasting framework integrates 3D physics-based simulations with a Long-Short Term Memory (LSTM)surrogate model and SHapely Additive exPlanations (SHAP) interpretation. The combination captures temporal water temperature dynamics and quantifies the contributions of different drivers to elevated water temperature releases. As proof of concept, these methods are …

From Flight To Hatching: Adult Sexual Dimorphism, Life History, And Egg-Stage Ecology Of Pseudocotalpa Giulianii, Mandylene Mountain

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Nevada endemic dune beetle Pseudocotalpa giulianii is currently known only from two dune systems in Amargosa Valley, Nevada, yet much of its life cycle occurs below the sand surface and remains poorly documented. This thesis addresses key gaps in adult-stage biology and egg-stage development that are relevant to understanding reproduction, vulnerability, and habitat requirements in this dunerestricted species.

To characterize adult sexual dimorphism and life history, I quantified morphological differences between males and females and measured sex-specific adult survival under laboratory conditions relative to the aboveground flight season. Males and females overlapped broadly in external body size, but tarsal …

Exact Solution Of Steady Seepage In An Asymmetrical Domain Underneath A Cofferdam, Tan Nguyen

UNLV Theses, Dissertations, Professional Papers, and Capstones

For decades, the evaluation of steady state seepage beneath asymmetrical cofferdams has relied on numerical methods, such as Finite Element Methods (FEM), Finite Difference Method (FDM), Finite Volume Method (FVM), Mesh Reduction Method (MRM), Meshless Method (MM), Boundary Element Method (BEM), or geometric idealizations, most notably Griffiths' vertical Method of Fragments assumption. While exact closed form solutions via Schwarz-Christoffel (SC) conformal mapping have been well established for symmetrical geometries (Banerjee and Muleshkov), the generalized asymmetrical case has historically remained an intractable mathematical frontier. The primary barrier to an exact analytical solution has been the "crowding problem," a numerical phenomenon where …

2d And 3d Insights Into The Formation And Emplacement Of Martian Meteorites, Sierra Rhaye Ramsey

UNLV Theses, Dissertations, Professional Papers, and Capstones

Martian meteorites are the only samples currently available from Mars, making their study critical for understanding martian igneous processes. Despite extensive study over the last five decades, the formation (e.g., mantle sources, crystallization pressures), emplacement (e.g., intrusive versus extrusive), and shock histories of these rocks remain uncertain due to their innate lack of geologic context and limited petrologic tools calibrated for martian conditions. This dissertation analyzes a large suite of 22 igneous martian meteorites using complementary 2D and 3D analytical methods to better constrain the magmatic, emplacement, and shock processes responsible for their formation and ejection from Mars.

Chapters 2 …

Visual Interpretability Of Multimodal Tissue Perfusion Classification Using Grad-Cam And Saliency Maps, Metehan Zorluoglu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Accurate identification of the tissue perfusion phase from hand images can aid doctors in decision-making with non-invasive techniques. The present study proposes a multimodal deep learning model for classifying the tissue perfusion phase using infrared, thermal, and visible spectrum images of the human hand. The proposed model consists of various preprocessing techniques such as manipulation, homography alignments, and masking. The significant contribution of this thesis is the interpretability analysis of deep learning models, achieved through the analysis of saliency maps and the Gradient-weighted Class Activation Mapping (Grad-CAM) methods. The purpose of this method is to find out how the convolutional …

Assessing The Relationship Between Subsurface Geology And Surficial Geomorphology: Remotely Predicting Geologic Features And Geohazards Using An Elevation-Trained Machine Learning Algorithm In The Northern Gulf Of Mexico, Allison L. Wing

Theses and Dissertations

This thesis evaluates the capacity to predict subsurface geologic features and submarine landslide susceptibility using surficial geomorphology derived from bathymetric elevation data in the Northern Gulf of Mexico. Quantitative geomorphic variables including slope, curvature, aspect, rugosity, geomorphons, and Bathymetric Position Index were generated from 30-meter digital elevation models and used as explanatory variables in presence-only Maximum Entropy models. Known locations of faults, pockmarks, mud volcanoes, hydrocarbon seeps, and landslides (particularly intact scarps) were used to train and validate predictive models through k-fold cross validation. Model performance was assessed using omission rates and AUC values. Results demonstrate that specific geomorphic signatures, …

Beyond English: Auditing And Mitigating Cross-Lingual Data Contamination In Multimodal Large Language Models, Pavan Dharma Adapa

Theses and Dissertations

This thesis extends data contamination auditing for multimodal large language models to multilingual settings. Using LLaVA 1.5 and a high-fidelity French parallel dataset derived from ScienceQA, the study evaluates how performance changes when identical image-question pairs are translated from English to French. The resultsshow a substantial cross-lingual performance decline and frequent flips from correct English predictions to incorrect French predictions, indicating that benchmark performance can depend heavily on memorized English-specific patterns rather than stable multimodal reasoning. To address this weakness, the thesis introduces an inference-time mitigation strategy based on perturbation ensembling and cross-lingual consistency aggregation. The proposed method reduces instance-level …

Regional Variability In Tornado Tracks: A Gis-Based Study Of Surface Roughness And Land Cover Differences Between The Lower Midwest And Southeast United States, Joshua Morgan Dison

Theses and Dissertations

Throughout the years, much research has been dedicated to the physical processes leading to tornadogenesis and tornado decay. Much of this research is centered around the inner workings of the supercell itself. Recent studies are now showing that tornadogenesis and decay processes may be generated by interactions with the Earth’s surface. This study examines longtrack tornadoes from 2001-2016 in the southeast and lower Midwest regions of the United States. Utilizing the National Land Cover Database (NLCD) and American Meteorological Society / Environmental Protection Agency / Regulatory Model (AERsurface) surface roughness values, efforts are made to see if statistical significance is …

A Pedagogically Effective Conceptual Framework For The Resilience Of Unit Test Suites To Refactoring, Daniel Paul Knight

Theses and Dissertations

Unit test suites are intended to support safe and efficient source code refactoring, yet in practice they can hinder rather than help when tests are tightly coupled to implementation details. Such non-resilient tests require frequent co-evolution, consume valuable engineering time, and may disincentivize beneficial code improvements. While concepts such as passive and active resilience, test smells, and technical debt have been studied individually, they have not been integrated into a single actionable framework, nor has their pedagogical value been systematically evaluated. This dissertation introduces a novel conceptual framework for the resilience of unit test suites to refactoring, grounded in resilience …

Low-Dimensional Metal Halides For Light-Emitting Diodes (Leds): Photophysical Aspects And Device Engineering, Udara Madushanka Kuruppu Kuruppu Achchige Don

Theses and Dissertations

In recent years, low-dimensional metal halides have garnered significant interest due to their exceptional optical properties. This dissertation focuses on the structural, optical, and photophysical properties of both lead-based and lead-free low-dimensional metal halides and investigates their applications in light-emitting diodes. In Chapter II, the nature of Mn2+ doping in two-dimensional (2D) lead halide perovskites is discussed. 2D perovskites show strong excitonic and dielectric confinement due to their quantum well structures. Introducing optically active Mn²⁺ dopant ions into these 2D perovskites further enhances their optical properties and promotes energy transfer from the host to the Mn²⁺ dopants, resulting in dual …

Assessment Of Local Ecological Knowledge, Oyster Predation, And Habitat Function To Improve Management Of Nearshore Habitats, Cynthia Evelyn Marie Lupton

Theses and Dissertations

Coastal ecosystems along the northern Gulf of Mexico are ecologically and economically vital yet increasingly threatened by environmental change, habitat degradation, and knowledge gaps that complicate restoration and management efforts. This dissertation integrates social and ecological approaches to improve understanding of predator dynamics, stakeholder perceptions, and habitat function related to nearshore habitats. Thereby, providing information that can inform adaptive management and restoration in the region through addressing three overarching objectives: 1) evaluate stakeholder perceptions of oyster (Crassostrea virginica) predation and management practices; 2) quantify environmental and habitat factors influencing oyster drill (Stramonita haemastoma complex) abundance; and, 3) assess the influence …