Digital Commons Network^™

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 …

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 …

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, …

Preservation Of Sedimentary Rubidium Isotopic Signatures In Subduction Zones: Insights From The Schistes Lustrés Hp-Uhp Metasediments, Western Alps, Mary Clarich

UNLV Theses, Dissertations, Professional Papers, and Capstones

When oceanic plates bend and sink into the mantle at subduction zones, they carry sediments from the surface down into the mantle. The recycled sediments contain elements, that are depleted in the mantle, thereby influencing the composition of the mantle wedge and the formation of arc magmas, which are the building blocks of juvenile continental crust. However, it remains poorly constrained how much these elements, particularly fluid-mobile elements such as rubidium (Rb), are lost into fluids during metamorphic dehydration, and how much is transported to sub-arc depths where arc magmas are generated. Rubidium in subducting sediments is mainly hosted in …

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 …

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 …

Integrating Augmented Reality Visualizations Into Data Science Notebooks Using Microsoft Hololens 2, Derek Willis

Theses and Dissertations

Data-science notebooks support iterative analysis but are limited to two-dimensional (2D) displays. This work presents an approach to extend such environments with rapid augmented reality (AR) visualization while preserving conventional 2D workflows. An opensource R package was developed to convert notebook objects into three-dimensional (3D) models, export them in the Graphics Language Transmission Format (glTF), and transfer directly to a Microsoft HoloLens 2 via a USB connection for viewing in the native 3D Viewer application. The proposed workflow eliminates manual conversion and transfer steps required by earlier methods. A user study employing a post-session questionnaire indicated that participants found the …

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 …

Evaluation And Mitigation Of Bias And Toxicity In Open-Source Large Language Models Using Crows-Pairs And Bold, Sai Harika Gade

Theses and Dissertations

This thesis evaluates bias and harmful language generation in five open-source language models and tests practical mitigation methods that do not require retraining. Two masked models are assessed with a sentence-pair benchmark for stereotype preference, and three generative models are assessed with a prompt-based benchmark for harmful continuations across demographic domains. The study uses a unified experimental workflow to compare model behavior, summarize differences across bias categories, and measure changes after intervention. Results show that the masked models favor stereotypical content above a random baseline, while the generative models usually produce low average toxicity but still show uneven risk across …

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 …

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 …

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 …

Agentic Synthetic Data Generation For Automated Model Development, Frederick Eugene Diehl

Theses and Dissertations

Large Language Model research has made large strides in capabilities from sentiment analysis to writing code. These advancements have been realized thanks to research into specific capabilities such as prompting techniques. Language models today have demonstrated the ability to create content, transform, and classify. These capabilities are not limited to academic exploration but also found in commercial products that are positioning themselves from application augmentation to personal assistants. These commercial products tend to steer towards single actions such as “summarize this article” or “write a function that performs action...” In parallel research has continued to advance towards more advanced constructs …

Automatically Constructed Preference Pairs For Chain-Of-Thought: Consistency Gains With Accuracy Tradeoffs, Cameron Scolari, Lanyu Shang

Honors Thesis

We investigate preference optimization over chain-of-thought (CoT) reasoning using automatically constructed preference signals derived from the accuracy and internal consistency of a model. Our results show that framing reasoning as a preference learning problem improves both the accuracy of the final answer and the structure of the model outputs. We observe a non-monotonic relationship between performance and the Direct Preference Optimization (DPO) scaling parameter β, where moderate values maximize accuracy while lower values improve stability, highlighting a tradeoff between optimization strength and reliable generation. We further identify a tradeoff between reasoning consistency and accuracy. Increasing the consistency weight improves agreement …

Ai Shell, Jacqueline Roebuck Sakho

Books

An AI Configuration Shell to train and deploy an Argumentation Coach. Presented and distributed to the UNC Commons Collective in May 2026.

Pwnagotchi: Deauthentication Attacks, Wpa Handshakes, And Wireless Network Security, Emily Musgrove

Computer Science Honors Papers

Wireless networks are the foundation of modern device communication infrastructure. This project examines the security implications of automated WPA/WPA2 handshake collection using the Pwnagotchi, a portable Wi-Fi network auditing and penetration testing device. The paper provides a technical analysis of WPA and WPA2 authentication mechanisms, including the structure of the 4-way handshake, the creation of cryptographic keys, and the role of deauthentication attacks in forcing reconnections for handshake capture. Additionally, the project explores the vulnerabilities associated with using legacy wireless security protocols such as WEP and TKIP to allow for older technologies that continue to require such encryption methods. This …

Dynamical Systems Modeling To Determine The Role Of Crosstalk In Shaping Stat Signaling Profiles, Laura F. Strube, Anamarie Martinez, Neha Cheemalavagu, Karsen Shoger, James Faeder, Rachel Gottschalk

Biology and Medicine Through Mathematics Conference

No abstract provided.

Synthergy: Social Deduction And Deception In Llm-Powered Agents, Lauren Campbell, Andrew Forney

Honors Thesis

Synthergy is an online social deduction game designed to enable comparative analysis of how large language model-powered agents engage in social deduction and deception under conditions of asymmetric information. Inspired by social deduction games such as Town of Salem, Throne of Lies, and Mafia, the game consists of two factions, Harmony and Discord, to which agents are secretly assigned. Agents must infer others’ affiliations through dialogue, in-game abilities, and voting behavior. To evaluate agent behavior, we conducted 100 simulated games across six agent types: a random baseline agent (RandomSynth), an LLM-based agent (Synth), a chain-of-thought agent (CoT Synth), a Bayesian …

Adaptive Two-Derivative Runge–Kutta–Nyström Method With Trigonometric Fitting Approach, Nur Nabila Huda, Khai Chien Lee, Nurul Huda Abdul Aziz

Turkish Journal of Mathematics

A fifth-order trigonometrically-fitted explicit two-derivative Runge–Kutta–Nyström method with an adaptive step size strategy, denoted as ATFRKN5, is proposed for efficiently solving second-order ordinary differential equations of the form u^″(x) = f(x, u(x)) that exhibit oscillatory behavior. The order conditions of the method are derived using Taylor series expansion, enabling the construction of two-derivative Runge–Kutta–Nyström schemes up to orders four and five. Trigonometric fitting is applied by incorporating the basis functions e^iλx and e^−iλx, λ ∈ ℝ, allowing the method to adapt naturally to problems with dominant frequencies. …

Optimal Control Of An Inverse Two-Point Boundary Value Problem For A Pseudoparabolic Equation With Samarskii–Ionkin-Type Boundary Conditions, Khanlar R. Mamedov, Tursun K. Yuldashev, Zholdoshbek Zh. Shermamatov

Turkish Journal of Mathematics

This paper investigates an inverse optimal control problem for a pseudoparabolic equation governed by nonlinear control function in a two-point boundary condition. The differential equation is considered under Samarskii Ionkin-type boundary value conditions with respect to the spatial variable x. Necessary optimality conditions are derived, and the associated nonlinear functional equations are analyzed. Using the contraction mapping principle, the existence and uniqueness of the control function are established. Subsequently, the redefinition function and the state function are determined. The convergence of their respective Fourier series representations is rigorously proven.

Comparisons Of Some Weighted Mixed Biased Estimators For The Linear Regression Model, Dünya Karapinar, Murat Polat, Ni̇met Özbay, Selahatti̇n Kaçiranlar

Turkish Journal of Mathematics

This paper presents comparative results on the two-parameter weighted mixed estimator, which is a distinct class of estimator defined to address the problem of multicollinearity. The two-parameter weighted mixed estimator is a general estimator that includes the weighted mixed estimator, the weighted mixed Liu estimator, and the weighted mixed ridge estimator. Detailed comparisons among the mentioned estimators are carried out based on the matrix mean square error. Theoretical findings are supported by two numerical examples in addition to a Monte Carlo simulation study.

2026 Revised Draft Final Bpsou Backfill And Cover Material Quality Assurance Project Plan (Qapp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Urban Conflagrations: Structural Ash And Soil Metal(Loid) Contamination After California’S Eaton And Palisades Fires, S. Anselme Dossou, Leon Kelly, P. Louis Lu, Robin Jones, Oliver O'Donnell, Justin St. P. Walsh, Daniel D. Richter

Art Faculty Articles and Research

In the weeks after California’s Eaton-Palisades wildfires, structural ash of burned homes and soils from yards and curbsides were sampled for analysis of Pb, As, and eight metals from 32 burned residences. About six months after fires and after US Army Corps of Engineers’ Phase 2 cleanups removed 15 cm from structural ash footprints, 17 properties were resampled within about a meter of original sampling sites. Concentrations of metal(oid)s in structural ash and residential soils varied between and within properties with significant spatial and temporal patterns. Lead concentrations were highest in structural ash and soil of yards of select pre-1970s …

Modeling Velocity Distributions Of Interstellar Neutral Hydrogen In The Heliosphere, Lucas Robert Dyke

Dartmouth College Ph.D Dissertations

As interstellar neutral hydrogen (ISN H) is the most abundant neutral element in the helio- sphere, the region within which the solar wind interacts with the portion of the interstellar medium through which our solar system moves through, it is integral that we aim to under- stand its many properties and interactions within this region. This work details the synthesis and use of a model of ISN H, using trajectory methods to backtrace from a target point at a radial distance of 1 au where explorer probes like Interstellar Boundary Explorer (IBEX) and Interstellar Mapping and Acceleration Probe (IMAP) reside. …

A Governance-Aware Multi-Agent Framework For Enhancing Fairness & Temporal Accuracy In Disaster Response Systems, Md. Ashfaqur Rahman

Theses and Dissertations

Large Language Models (LLMs) have demonstrated significant potential in disaster-response decision support, however, their deployment in high-stakes humanitarian settings raises critical concerns regarding factual reliability, fairness, temporal validity, and governance compliance. Hallucinated outputs, demographic bias, and outdated recommendations can directly impact vulnerable populations and undermine public trust. This dissertation proposes a governance-aware multi-agent framework designed to enhance fairness and temporal accuracy in disaster-response systems through structured Retrieval-Augmented Generation (RAG), verification-driven orchestration, and adaptive correction mechanisms.The proposed architecture decomposes response generation into specialized agents responsible for real-time retrieval, fact-checking, bias auditing, temporal validation, threshold-based correction, and monitoring. By embedding governance constraints …