Physical Sciences and Mathematics Commons^™

Quantifying Co2 And Ch4 Fluxes In A Semi-Arid Floodplain: Assessing Spatial And Temporal Drivers, Miles E. Kelsey

Earth and Planetary Sciences ETDs

Rivers transport sediment and carbon across Earth’s surface, and their floodplains can store carbon over decades to millennia, making them important to terrestrial carbon management. While soil carbon can persist long term, it may be released as greenhouse gases through processes like methanogenesis and heterotrophic respiration. Environmental controls on these fluxes remain poorly constrained across floodplains in different climate and geomorphic setting, but especially in semi-arid systems where measurements are limited. To address this gap, we quantified CO₂ and CH₄ fluxes along the Middle Rio Grande (New Mexico, USA) using 227 chamber measurements collected May to November 2025 at three …

Heavy Metal And Metalloid Accumulation In The Gallinas River Following The Hermit's Peak / Calf Canyon Wildfire, Olivia A. Kelly

Geography ETDs

This study evaluates the persistence and bioavailability of heavy metals and metalloids in the Gallinas River three years after the Hermit’s Peak/Calf Canyon Wildfire of 2022 using a multicompartment sampling framework that includes water, sediment, and benthic macroinvertebrate tissue analysis via inductively coupled plasma optical emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS). Results indicate that the Hermit’s Peak/Calf Canyon Fire continues to influence the hydrogeochemical condition of the Gallinas River. Sediments contain elevated concentrations of several metals and metalloids, and these same elements are detectable in macroinvertebrate tissues, linking sediment contamination to biological uptake. Zinc (Zn), silicon …

Nanoscale Structure And Spontaneous Self-Assembly Of Hydrothermal Organic Products, Glorianne P. Dorce

Chemistry and Chemical Biology ETDs

Carbon nanomaterials derived from citric acid and urea exhibit behaviors that challenge conventional structure–property models based on static bulk descriptions. This study examines how precursor pairing and reaction duration, post‑synthetic thermal history, and time‑dependent aging govern nanoscale organization and optical response. Through controlled synthesis and processing, distinct nanostructures with tunable structural and spectroscopic profiles are generated.

A multiscale framework integrating nano‑FTIR, atomic force microscopy, and thermal analysis reveals chemical heterogeneity and continuous structural reorganization across length scales. By correlating local chemical environments with optical behavior, we show that fluorescence efficiency and photostability depend on specific nanoscale architectures rather than average …

Continuous Polygenic Trait Evolution Under Brownian Motion With Gaussian Mixture Models, Mary S. Hopkins

Mathematics & Statistics ETDs

Gaussian mixed-models (GMMs) show promise as a tool for modeling polygenic trait evolution for multiple taxa with established phylogenetic comparative methods (PCMs). When phenotypic traits are influenced by more than one gene, neither a gene tree nor a species tree may be completely adequate to model specific cross-taxa dependencies. In such cases common solutions include using trees inferred from concatenated DNA sequences [35, 95] and consensus gene trees [35]. The GMM-based model, first proposed by Jiang in 2017 [55] allows traits to evolve on more than one tree with distinct topologies. This approach provides a framework for trait evolutionary modeling …

Bayesian Designs For Two-Arm Clinical Trials With Time-To-Event Endpoints: Incorporating Historical Data Through Power Priors, Sara Hajraf H. Almutiri

Mathematics & Statistics ETDs

Bayesian methods provide a flexible framework for time-to-event analysis by incorporating prior information. The power prior offers a systematic way to borrow information from historical data. This approach is especially valuable in clinical research, where historical data can enhance inference in early-phase trials with limited sample sizes. This dissertation develops Bayesian approaches for two-arm survival studies using both closed-form and simulation-based methods. The closed-form inference is derived under exponential and Weibull survival models. Under the proportional hazards framework, the posterior is derived through a normal approximation to the log hazard ratio, allowing inference on the treatment effect when the variance …

Quantum Control Protocols For Robust Quantum Computing, Leeseok Kim

Electrical and Computer Engineering ETDs

The fundamental goal of quantum computing is to precisely control quantum systems to perform meaningful tasks, including implementing high-fidelity quantum gates for reliable quantum computation and accurately simulating complex quantum many- body dynamics. In this dissertation, we develop improved quantum control protocols for three distinct objectives, quantum error suppression, quantum optimal control, and analog quantum algorithms, achieving performance beyond standard approaches. First, we introduce new dynamical decoupling protocols, including both determin- istic and randomized constructions, that can substantially outperform conventional deterministic sequences. We then extend the randomized approach to dynamically corrected gates. Second, we propose a randomized quantum optimal control …

What Is The Skeleton Of Cognition? A Structural Account Of World Reconstruction Through Processing Axes, Griselda Poe

Publications and Research

This paper describes how the placement of a single processing axis reorganizes human cognition and generates a reconstructed world.

Most existing psychological and social theories begin from emotion, desire, morality, or social behavior. In doing so, they have discussed what forms on top of the cognitive skeleton without first fixing the skeleton itself. When the skeleton is not fixed, entirely different explanations of the same phenomenon can coexist, and it becomes difficult to identify which constitutes a foundational account.

This paper fixes the skeleton first. That skeleton is the processing axis.

The question is: when a single processing axis organizes …

Classification Of Hif Detection In Nev Profile Using Wavelet Transform And Convolution Neural Network, Abdul Hafiz Kassim, Mohd Abdul Talib Mat Yusoh, Aster Smith Valentinie Wilson Nottelmarc, Ahmad Farid Abidin, Sim Sy Yi, Daw Saleh Sasi Mohammed

Turkish Journal of Electrical Engineering and Computer Sciences

High impedance faults (HIFs) present a critical challenge in power systems due to their subtle signal characteristics, which often remain undetected by conventional protection methods. These faults typically do not produce significant phase disturbances, making reliable detection difficult. However, analysis of the neutral-to-earth voltage (NEV) profile under fault conditions provides a promising alternative for fault identification. Existing approaches for detecting and classifying HIFs using NEV signals remain limited and may result in inaccurate maintenance decisions. This paper proposes a fault classification framework for multiple fault types, including HIF, three-phase fault, three-phase fault to ground, double line, double line to ground, …

Complex-Valued Convolutional Neural Network With Time-Frequency Representation For Electrocardiogram-Based Arrhythmia Detection, Kajeeth Kumar Gurusamy, Muthurajkumar Sannasy

Turkish Journal of Electrical Engineering and Computer Sciences

This research proposes an end-to-end procedure for arrhythmia detection based on electrocardiogram (ECG) signals using complex-valued convolutional neural network (CVCNN) incorporated with time-frequency representation. The proposed model leverages complex numbers to capture amplitude and phase information that enhances the ability of the model for detecting time-frequency variation in cardiac signals. First, signal preprocessing techniques---including normalization, wavelet denoising, and R-peak detection---are applied. Subsequently, the model extracts complex features from raw ECG data by employing the Hilbert transform to derive the analytic signal and the short-time Fourier transform (STFT) to generate a time–frequency representation. The proposed CVCNN framework effectively learns spatial-temporal features …

Accurate Diagnosis Of Diseases By A Novel Ai Pipeline Based On Feature Extraction, Feature Ranking, And Feature Selection From Medical Images, Tuğba Nur Bozkurt, Mehmet Emi̇n Yüksel

Turkish Journal of Electrical Engineering and Computer Sciences

The rapid growth of the global population has led to a substantial increase in the number of patients, while the availability of healthcare professionals has not expanded at a comparable rate. This imbalance highlights the urgent need for efficient and reliable computer-aided decision support systems that can reduce clinical workload while maintaining high diagnostic accuracy. In this study, a novel and systematically integrated artificial intelligence-based pipeline is proposed for medical image classification, combining statistical significance-driven feature ranking with evolutionary feature selection in a unified framework. The proposed pipeline consists of four sequential stages: feature extraction, ranking, selection, and classification. Features …

Adapting Independent Large-Scale Pretrained Models For Human Action Recognition, Selen Pehli̇van

Turkish Journal of Electrical Engineering and Computer Sciences

Transferring knowledge from large-scale, independently pretrained image and text models to video understanding requires addressing several challenges, including maintaining generalization capabilities of models, integrating them into multimodal architectures, and fine-tuning with temporal dynamics. This study evaluates the effectiveness of parameter-efficient fine-tuning (PEFT) techniques in transferring pretrained knowledge from two independent models for video action recognition within a simple, streamlined multimodal fusion pipeline. Specifically, we adapt CLIP as the text branch and DINOv2 as the image branch, keeping both backbones frozen to preserve their pretrained robustness, while introducing lightweight, task-specific modules to adapt and fuse the branches with temporal dynamics. A …

Adaptive Backstepping Nonsingular Fast Terminal Sliding Mode Control For Robotic Manipulators Based On Disturbance Observer, Xin Zhang, Xu Wang

Turkish Journal of Electrical Engineering and Computer Sciences

This paper presents an adaptive backstepping nonsingular fast terminal sliding mode controller integrated with a nonlinear disturbance observer to achieve precise trajectory tracking of robotic manipulators subject to model uncertainties and unknown time-varying disturbances. A dead-zone–based adaptive gain mechanism is introduced to dynamically adjust the control gain according to the deviation of the sliding surface, thereby enhancing robustness and reducing chattering. The proposed reaching law ensures fast, nonsingular, and adaptive convergence, suppressing high-frequency oscillations without compromising stability and the nonlinear disturbance observer enables real-time estimation and compensation of modeling errors, friction, and external disturbances for superior rejection. The semiglobal uniform …

Chaotic Artificial Bee Colony-Optimized Stacking Ensemble For Robust Multifault Diagnosis Of Wind Turbines, Veilraj Revathi, Solaimalai Jeyadevi, Madasamy Sudalaimani

Turkish Journal of Electrical Engineering and Computer Sciences

The complex electromechanical structure of wind turbines, along with harsh operating conditions, poses significant challenges for precise and robust fault diagnosis. To address this challenge, an ensemble multifault diagnostic framework based on an adaptive chaotic artificial bee colony (C-ABC)-optimized support vector machine (SVM) and gradient boosting machine (GBM) is proposed. In the proposed framework, data redundancy and overfitting are reduced through a two-stage hybrid filter-transformer-based feature reduction approach using ReliefF, followed by Principal Component Analysis. The chaos function of the proposed C-ABC maintains an adaptive balance between the exploration and exploitation phases, thereby preventing premature convergence, which is a common …

Welcome Tilly Norwood: Forecasting Hollywood’S Ai Policy Futures, Samuel P. Rooker

Senior Honors Projects, 2020-current

In late 2025, weekly trade publication Variety Magazine reported on the announcement of a new acting talent in Hollywood: Tilly Norwood. Norwood is an industry outsider and the pet project of Eline Van der Velden, who unveiled the actress’ existence to the world at the Zurich Film Festival. The announcement quickly gained media coverage while Van der Velden has since faced cyclical backlash from Hollywood trade unions, which does not seem entirely without reason. Tilly Norwood is a digital persona, a generative artificial intelligence (GenAI) program, designed by Van der Velden’s novel AI talent studio, Xicoia, to become the next …

Surface Directed Microwave Assisted Fabrication Of Znmn2o4 And Its Composite As Anode Materials For Lithium Ion Battery, Anirudh Singh

Electronic Theses & Dissertations

The Lithium-ion batteries (LIBs) are widely utilized in portable electronics and electric/hybrid electric vehicles. However, the limited theoretical capacity of graphite (372 mA h g⁻¹) restricts further advancements. In our recent work, a series of ZnMn₂O₄ materials with various additives were synthesized using the microwave reaction method and evaluated as anodes for LIBs. Additives such as 2-methylimidazole (2MIM), polyvinyl alcohol (PVA), and cetyltrimethylammonium bromide (CTAB) were employed to prepare ZnMn₂O₄ with distinct morphologies. Our findings revealed that ZnMn₂O₄  with pure phases was achieved when 2MIM and CTAB were used as additives. …

Subject: Quarterly Operations And Maintenance Report Grove Gulch Sedimentation Bay For Fourth Quarter 2025 And First Quarter 2026 Silver Bow Creek/Butte Area Npl Site – Butte Priority Soils Operable Unit Consent Decree-Civil Action No. Cv 89-039-Bu-She, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Degrees Of Access: The Role Of Family Education In Applying To Graduate School, Emma Tweed

Math and Computer Science Honors Theses

Access to graduate education in the United States remains heavily stratified by structural, financial, and informational barriers. While undergraduate first-generation student outcomes are widely studied, fewer structural analyses examine how graduate-level “educational inheritance” shapes prospective applicants' navigational capital, particularly within competitive STEM fields like mathematics. Drawing upon theories of social capital and the “hidden curriculum,” this study investigates the relationship between an individual's knowledge of the graduate school application process and the highest level of education attained by an immediate family member.

Using the Knowledge-GAP survey instrument funded by the National Science Foundation, data were collected from a diverse sample …

The Extraction And Chemical Characterization Of The Avian Pigments Turacin And Turacoverdin, Sarah R. Bekkali

Honors Scholar Theses

Bird coloration is a trait that extends beyond mere aesthetics as it has an extensive range of biological significance. Plumage patterns and hues can influence camouflage, mate choice, social dominance, and physiological performance. Bird fitness, their ability to survive and reproduce, is greatly dependent on color. Melanins, carotenoids, and pterins are well-studied pigment systems that are commonly found across many avian species’. Alternatively, porphyrin-based pigments are rare and less-studied as they only found in turacos a sub-Saharan African bird belonging to the family Musophagidae. This thesis focuses on two pigments of interest: turacin, the deep crimson-red pigment found in …

Saving The Great Basin: Creating Places For The Birds, Bees And Beyond, Carlos Gomez

Hospitality Design Graduate Student Capstones

This project looks at how vacant and underused parcels along the Truckee River in Reno, Nevada, can be rethought as part of a larger ecological system. Rather than treating these parcels as empty leftover spaces, the project sees them as opportunities to create small habitat patches that can support native species, improve stormwater function, and strengthen the river corridor over time. The work focuses on three sites along the Truckee River: California Avenue, Island Avenue, and Commercial Row. Each site responds to a different condition along the urban transect, from a sloped residential river edge to a tighter urban parcel …

The Biowell System: An Integrative Framework That Connects Ecological Sustainability And Mental Wellbeing Through The Regenerative Processes Of Bioswales, Nathan A. Bussa

Hospitality Design Graduate Student Capstones

The Biowell System is an evaluative framework that connects ecological sustainability and mental well-being through the regenerative processes of bioswales.

The Yorp Effect In Reboundx, Kaelyn Clement

UNLV Theses, Dissertations, Professional Papers, and Capstones

The Yarkovsky-O’Keefe-Radzievskii-Paddack (YORP) effect is a radiation-induced torque that can affect the spin and rotational obliquity of small bodies. It has been observed to alter the rotation rate of asteroids in the Solar System (Lowry et al. 2007; Taylor et al. 2007). Under extreme circumstances, YORP can cause a body to fragment, inducing a cascade of fissions. This effect may be important in driving the pollution of white dwarf atmospheres in conjunction with other radiative forces. I developed a YORP calculator for REBOUNDX (Tamayo et al. 2020), an extensional library to the N-body integrator REBOUND (Rein & Liu 2012). I …

Micromagnetic Simulations Of Field-Driven Antiferromagnetically Coupled Skyrmions, Aidan D. Kirk

Physics and Astronomy Honors Papers

Competing magnetic interactions can stabilize smooth magnetization textures and can be characterized by a topological winding number. A specific spin configuration/texture, spatially localized within a two-dimensional plane, is commonly known as a skyrmion. On the classical level, the significance of skyrmions for condensed matter physics and their potential for applications, ranging from spintronic devices to qubits, has been intensely investigated in recent years. This thesis focuses on antiferromagnetically (AF) coupled Neel-type magnetic skyrmions, which are comprised of two skyrmions with opposite topological charges, yielding a net topological charge of 0. This configuration results in the cancellation of their respective Magnus …

Adaptive Channel Switching For Contention Resolution, Shafqat Hasan

Theses and Dissertations

Contention resolution is a fundamental problem in distributed computing, where multiple devices compete to transmit over a shared channel without centralized coordination. Classical models typically assume a single always-available channel and focus on minimizing makespan. However, modern wireless systems increasingly operate under spectrum-sharing frameworks in which access to high-capacity spectrum is opportunistic and may be interrupted by higher-priority users. These settings introduce new challenges, including asymmetric channel speeds, adversarially scheduled evictions, and non-trivial switching costs. In this thesis, we study contention resolution in a dual-channel model consisting of a slow, always-available channel and a faster channel subject to adversarially scheduled …

Accelerating Defensive Cyber Operations Via Unsupervised Log Clustering And Automated Regex Template Synthesis, Charles Matthew Jones

Theses and Dissertations

Modern Security Operations Centers (SOCs) ingest millions of log entries per day, but manual parsing does not scale to the volume, heterogeneity, and rapid evolution of log formats. This dissertation investigates whether unsupervised clustering can automate the generation of candidate field-extraction templates while remaining deployable in production and feasible under realistic runtime and memory constraints. The central research question asks whether a machine-learning-assisted pipeline that proposes extraction templates for security engineer review—relative to reproducible human-authored baselines such as hand-written regular expressions—can measurably improve rule-set deployability and corpus-scale extraction quality. Improvement is quantified using four applicability metrics: Coverage Rate (CR), Exclusive …

Parhsom: A Novel Parallel Hierarchical Self-Organizing Map Implementation, Rebekah E. Lane

Theses and Dissertations

The digital age has completely transformed the way that information is processed and stored, which makes cybersecurity a crucial field of research. Cybersecurity contains many different domains, but this work focuses on Intrusion Detection Systems (IDSs). Within the literature, Hierarchical Self-Organizing Maps (HSOMs) have been used to create trustworthy, explainable, and AI-based IDSs. However, HSOMs are trained sequentially, which means that training HSOMs on large datasets is slow. This work presents a novel parallel HSOM architecture, called parHSOM. The purpose of this research is to investigate the effect that parallel computation has on the HSOM training time. parHSOM is tested …

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 …