Digital Commons Network^™

Butte Priority Soils Operable Unit Butte Reduction Works Smelter Area Intermediate 60% Remedial Design Submittal, Pioneer Technical Services, Inc., Atlantic Richfield Company

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Multi-Level Variable Selection Using A Bart-Enhanced Mixed-Effects Framework, Keming Zhang, Yaoyao Li, Jungang Zou, Sijian Wang, Bernadette A. Fausto, Liangyuan Hu

College of Health Professions Faculty Papers

Selecting important individual- and cluster-level predictors has become increasingly critical in healthcare research, where data often exhibit hierarchical structures due to collection from multiple clusters. Mixed-effects models, which account for within-cluster correlation and between-cluster heterogeneity, are a natural approach for multilevel variable selection. However, currently available variable selection methods for multilevel data are predominantly based on mixed-effects models that impose restrictive parametric assumptions, potentially limiting their utility when the underlying relationships are nonlinear or involve interactions. While nonparametric methods have shown promise for variable selection in non-clustered data, they have been much less studied in the multilevel setting. Moreover, nonparametric …

Robert, Powers; Unl Chemistry; Nmr-Assisted Drug Discovery, Mark Griep, Robert Powers

Department of Chemistry: Faculty Interviews

Dr. Robert Powers became a chemistry professor at the University of Nebraska-Lincoln in 2003 and is about to retire after 23 years. Prior to UNL, Bob was a drug discovery researcher for 11 years at American Cyanamid, which eventually became Wyeth and is now part of Pfizer. Bob was born in Jersey City, New Jersey. Something in his youth must have sparked an interest in chemistry because he earned a bachelor's in that subject from Rutgers University in New Brunswick. Then he traveled 1200 miles west to Purdue University in Indiana where he earned his doctorate. Next, he did postdoctoral …

Draft Final 2024 Unreclaimed Sites Sampling: Ur-21 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Bayesian Spatiotemporal Model For Counterfactual Estimation In Socioeconomic Studies, Duwani W. Gonzalez

Statistical Science Theses and Dissertations

Impact evaluations of regional development programs often require estimating counterfactual outcomes for a small number of treated regions using survey-based areal data. In practice, evaluators typically rely on two-group quasi-experimental methods such as propensity score matching (PSM) and Difference-in-Differences (DiD). These approaches perform poorly when only a few regions receive treatment, and when the set of observed covariates is limited or only partially relevant. Moreover, they typically do not explicitly exploit the spatial and temporal dependence present in survey-based areal data such as in ACS (American Community Survey). This dissertation develops a family of Bayesian spatial predictive models for directly …

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 …

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 …

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.

Validation And Implementation Of Automated Planning Optimization In Utah Valley Hospital, Oluwatobi Adeniji

UNLV Theses, Dissertations, Professional Papers, and Capstones

The increasing complexity of modern radiotherapy demands planning workflows that are efficient, standardized, and dosimetrically robust across diverse disease sites. Knowledge-based planning (KBP) systems such as RapidPlan offer a data-driven approach to automate and improve treatment planning by learning geometric–dosimetric relationships from high-quality clinical plans. In this work, I am evaluating the performance, generalizability, and clinical applicability of vendor-provided RapidPlan models across seven anatomical sites: intracranial SRS, prostate SBRT, right and left lung SBRT, liver SBRT, head and neck, and glioblastoma. Subsequently, a complementary institution-specific SRS model tailored to single-isocenter multitarget workflows was created. Seventy retrospectively selected patients were replanned …

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 …

Unknowing Sacrifices: Public Health And Radiation Illness In New Mexico And Nevada, 1940s-1960s, Beatriz Avila-Marquez

UNLV Theses, Dissertations, Professional Papers, and Capstones

The detonation of the first atomic bomb in the early morning of July 16, 1945, in New Mexico welcomed the atomic age that forever changed the world. After that day, thousands of lives were lost due to nuclear weapons, and hundreds of thousands more continued to suffer from the effects of atomic testing. The Atomic Energy Commission, fueled by the arms race of the Cold War, chose Nevada to continue the United States’ nuclear weapons testing. Knowledge of the dangers of radiation exposure, the effects of radiation, and techniques to prevent exposure are now available in part due to the …

“A Land No One Would Want”: Environmental Activism And The Rejection Of ‘Wasteland’ Narratives In Southern Nevada, Steven Butler

UNLV Theses, Dissertations, Professional Papers, and Capstones

This paper traces events within the history of environmental activism in Southern Nevada. The first chapter discusses the proposed high level nuclear waste repository at Yucca Mountain. The second chapter examines the closure of the Reid Gardner Generating Station in Moapa, Nevada. The third chapter details the Southern Nevada Water Authority’s Groundwater Development Project. Each of the three chapters is linked by common themes within the history of Southern Nevada environmental activism, including dedicated coalition-building and the refusal of “wastelanding” of the region.

Establishing A Comprehensive Framework For Sfrt Lattice Treatments: Optimization, Planning, And Clinical Evaluation, Gregory M. Gill

UNLV Theses, Dissertations, Professional Papers, and Capstones

Spatially fractionated radiation therapy (SFRT) using lattice radiotherapy (LRT) has emerged as a promising treatment technique for bulky, nonresectable tumors by delivering spatially heterogeneous dose distributions consisting of high-dose vertices embedded within lower-dose regions. Although early clinical experiences have demonstrated potential therapeutic benefit, widespread clinical implementation of LRT remains limited due to the absence of standardized treatment planning workflows, consistent optimization strategies, and clearly defined evaluation metrics for heterogeneous dose distributions. The objective of this study is to develop and evaluate a structured framework to support efficient, reproducible, and safe clinical implementation of LRT.

To address these challenges, a comprehensive …

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 …

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.

An Evaluation Of Artificial Intelligence Chatbots As Alternatives To Specialized Software In Teaching Bayesian Pharmacokinetic Analysis, Reza Mehvar

Pharmacy Faculty Articles and Research

Objective

Methods

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, …

Thermal Physiological Ecology Of The Relict Leopard Frog At Hot And Cold Springs, Robert P. Pelletier Iii

UNLV Theses, Dissertations, Professional Papers, and Capstones

The relict leopard frog (Rana onca) once ranged across drainages in southern Nevada, northwestern Arizona, and southwestern Utah. Following a decline, the species only persisted in a few geothermally influenced hot springs, which led to the perspective that hot springs were high-quality habitat. Rana onca has been under intensive, multiagency management and the species has been translocated to establish additional populations, including at cold-water sites. Three research studies are presented into the thermal physiological ecology of R. onca with the aim of informing conservation strategy. The research was focused at a thermally influenced hot spring and a cold-water spring to …

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 …

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 …

Iterative Silver-Label Refinement For Temporal Information Extraction In Biomedical Literature, Chan Lee

UNLV Theses, Dissertations, Professional Papers, and Capstones

Temporal information extraction plays a critical role in the biomedical domain, where the ability to identify events and their temporal relationships is central to interpreting research findings. However, annotated corpora for this task remain scarce and costly to produce and the existing models developed for clinical text do not transfer well. This work bridges that gap through iterative silver-label refinement. A temporal model originally trained on news-domain data is adapted to biomedical text through cycles of automatic labeling, targeted correction, and retraining without the need for comprehensive manual annotation.

Key contributions include a practical iterative refinement methodology demonstrating that the …

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 …

Effect Of The Sava Syndemic On Hiv Viral Suppression Among People Living With Hiv In The United States: A Scoping Review And Meta-Analysis, Jacquelyn Rodriguez

UNLV Theses, Dissertations, Professional Papers, and Capstones

The SAVA syndemic highlights the interconnected and mutually reinforcing nature of substance use, violence victimization, and HIV/AIDS. The synergistic interaction of these conditions creates structural and behavioral barriers that disrupt the HIV care continuum and contribute to significant health inequities. Achieving a suppressed viral load is a critical clinical outcome for people living with HIV, while viral non-suppression can be an indicator of poor health, elevated transmission risk, and disease progression. Still, the association between SAVA factors and viral suppression/non-suppression outcomes within U.S. populations remains inconsistently characterized due to heterogeneous methodologies and variable inclusion of high-risk groups. This mixed-methods study …

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 …

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 …

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, …