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A Large And Robust Legless Lizard (Squamata, Anguinae) From The Gray Fossil Site Of Eastern Tennessee, Justice D. Lamer

Electronic Theses and Dissertations

The early Pliocene Gray Fossil Site in Tennessee preserved an abundance of microfossils, including numerous anguid lizard specimens. This includes the following elements: dentaries, a pterygoid fragment, a jugal, frontals, parietal fragments, dorsal and caudal vertebrae, and many osteoderms. Because these specimens had not been placed taxonomically beyond the subfamily level, comparative anatomy of similar elements from extant anguids and some quantitative data were used to provide more refined identifications. Using these methods, it was determined that a new, robust type of Ophisaurus is represented at the Gray Fossil Site. Important novel features include relatively robust dentaries, fewer but broader …

Student Attitudes And Perceptions Of Proof In Mathematics, Emelin G. Sibrian Marquez

Electronic Theses, Projects, and Dissertations

Traditionally, mathematical proof is viewed primarily as a tool for validation or verification. However, proof holds many other important roles such as discovery, reasoning, explanation, and justification. For many students, these other roles are not always obvious. Those encountering rigorous proof for the first time often find the process abstract, intimidating or disconnected from their previous learning. This disconnect can lead to negative attitudes as students transition from computational mathematics to advanced proof-based mathematics. Utilizing a mixed-methods approach, this study examined undergraduate and graduate mathematics students at a Hispanic-Serving Institution (HSI) in Southern California. We investigated what students perceive the …

Evolution Of Propagator Wakes On The Kolbeinsey Ridge From An Integrated Geophysical Perspective, Ethan Stowell

Department of Earth and Atmospheric Sciences: Dissertations, Theses, and Student Research

Oceanic lithosphere is formed following the extension and rifting of a continent, with new material generated at mid-ocean ridges. While ridges generally spread in the direction of extension, individual spreading centers are offset by perpendicular transform faults that break the ridges into individual segments. Ridge propagation, in which one ridge segment grows at the expense of another’s shortening, has been identified in global investigations as a poorly understood component of axial reorganization. This process leaves propagator wake structures composed of faults and pseudofaults visible as lows in Earth’s gravitational field, and transferred lithosphere with a distorted magnetic signature. This study …

Theory-Informed Generative Agents For Human Behavioral Modeling In Disasters, Liming Lu

All Dissertations

This dissertation develops a theory-informed generative-agent framework for modeling human behavioral decisions in disasters. Existing flood and disaster preparedness models often emphasize physical hazards, infrastructure exposure, or statistical correlations, but they struggle to capture the heterogeneous and evolving choices households make. This limitation is especially important for climate-related hazards, where future damage depends not only on changes in rainfall, inundation, and urban development, but also on decentralized protective actions such as house elevation, flood insurance, evacuation, and early preparedness. The dissertation integrates two empirical studies: a flood-risk study in Charleston, South Carolina, and a household disaster-preparedness study across hurricane contexts. …

Leveraging Deep Learning Recurrence And Attention Mechanisms For Flood Forecasting And Assessment, Elnaz Heidari

All Dissertations

Predicting how much water will flow in rivers and streams is important for managing floods, water supply, and the environment. Traditionally, government agencies have used complex models, such as the National Water Model (NWM), which simulate how much water moves through landscapes using physical laws and real-world data. However, recent advances in Artificial Intelligence (AI) have enabled new ways to make these predictions. This research explored whether AI-based models could predict river discharge more accurately. These AI models learn patterns from past data instead of relying only on physical rules. To find out how well they work, the AI models …

Imaging Oxygen Near Implanted Medical Devices Through Tissue With X-Ray And Ultrasound Modulated Luminescence Chemical Imaging, Vigjna Abbaraju

All Dissertations

Oxygen plays a crucial role in stem cell maintenance, tissue regeneration, disease progression, and treatment efficacy. For example, understanding oxygen dynamics within implanted medical devices, such as bone scaffolds, is essential for successful tissue regeneration and can serve as an early indicator of infection. The existing oxygen sensing and imaging techniques are often limited by narrow imaging depth, low spatial resolution in vivo resulting in poor understanding of oxygen dynamics in tissue microenvironments. This dissertation describes the development of implantable sensors using X-ray scintillators and thermochromic leuco dye paired with phosphorescent oxygen dye (PtTFPP) to image oxygen using X-ray luminescent …

Nanostructured Insulated Electrodes For Directed Nanoparticle Assembly: Development And Characterization, Thomas F. Burgess

All Dissertations

Nanoparticles exhibit unique properties dependent on their size, shape, and arrangement that are critical for sensing applications, such as the localized surface plasmon resonance of silver nanoparticles. Therefore, control over their assembly facilitates control over these properties. For this purpose, nanostructured insulated electrodes were developed and characterized for directed assembly of nanoparticle clusters. Electrode characterization required a new method for relative electric field quantification from electric force microscopy (EFM) measurements, implemented via an extended Hudlet model to estimate the field between the sample and the EFM probe apex. Restricting analysis to the apex – sample interaction improves spatial resolution and …

Structure And Dynamics Of Associative Polymers Under Quiescent State And Flow, Rosita Sivaraj

All Dissertations

Associative polymers, including ionizable polymers, are widely used in membranes, coatings, fuel cells, energy storage, and other advanced soft materials. Their properties are governed by ionic aggregation and associative interactions, which influence chain mobility, phase behavior, self-assembly, interdiffusion, and flow response. This dissertation employs large-scale molecular dynamics (MD) simulations to investigate the structure, dynamics, phase behavior, interdiffusion, and extensional flow response of ion-containing and associative polymer systems under quiescent and nonequilibrium conditions.

The influence of molecular architecture is first examined by comparing ring and linear associative polymers using the Kremer–Grest bead-spring model. In linear chains, their closed-loop architecture reduces interchain …

The Exploration Of One-Dimensional And Two-Dimensional Frustrated Magnetic Transition Metal Phosphates And Arsenates Via Hydrothermal Synthesis, Emily D. Williams

All Dissertations

Geometric magnetic frustration is a term that refers to magnetic spins that are “confused” or frustrated due to geometric arrangements of magnetic ions that prohibit the spins from magnetically ordering. This phenomenon has been subject to much research due to the ability to study exotic magnetic states and expand upon knowledge that would allow for materials to be implemented into quantum computing, memory storage and advanced sensor processing. One of the most exotic magnetic states, quantum spin liquids (QSL), has never been achieved but shows much promise. In the QSL state, magnetic spins do not order down to 0 K …

Can Kinematics Specify Tool Use Affordances?, Tyler Duffrin

All Dissertations

Object properties such as length, shape, and heaviness, as well as affordance-based properties such as strike-with-ability and poke-with-ability, can be perceived via dynamic touch as functions of inertia tensor invariants. The primary question addressed here was whether people can perceive these same power and precision properties for purely virtual objects, which lack dynamic physical forces. The Kinematic Specification of Dynamics (KSD) principle asserts that missing dynamics are lawfully specified by kinematic (visual) motion patterns, such that kinematic information alone may support successful interactions with virtual objects. In three experiments, we investigated (1) whether virtual reality (VR) users could calibrate to …

Llm-Based Early Rumor Detection With Imitation Agent, Fengzhu Zeng, Qian Shao, Ling Cheng, Wei Gao, Shih-Fen Cheng, Jing Ma, Cheng Niu

Research Collection School Of Computing and Information Systems

Early Rumor Detection (EARD) aims to identify the earliest point at which a claim can be accurately classified based on a sequence of social media posts. This is especially challenging in data-scarce settings. While Large Language Models (LLMs) perform well in few-shot NLP tasks, they are not well-suited for time-series data and are computationally expensive for both training and inference. In this work, we propose a novel EARD framework that combines an autonomous agent and an LLM-based detection model, where the agent acts as a reliable decision-maker for \textit{early time point determination}, while the LLM serves as a powerful \textit{rumor …

Ai-Driven Segmentation And Volumetric Response Modeling Of Liver Regions To Radiotherapy, Aashish Chandra Gupta

Dissertations and Theses (Open Access)

In liver-directed radiotherapy (RT), liver regions receiving higher doses typically undergo atrophy while contralateral/adjacent lower-dose regions may exhibit compensatory hypertrophy through regeneration of healthy tissue. Optimizing the RT plan to promote regional hypertrophy while minimizing the risk of developing atrophy has the potential to enhance post-RT liver function and long-term survivorship. However, current clinical practice largely relies on global liver dose-volume metrics during RT-planning, which may obscure favorable dose-response correlation and limit actionable guidance for clinicians. Therefore, we hypothesized that post-RT regional liver response is governed by a combination of region-specific dose-volume and patient clinical features, and that these responses …

Technique-Level Normalization For Cybersecurity Intelligence: An Empirical Evaluation Of Att&Ck Attribution From Hids Alerts Using Fine-Tuned Transformers And Metadata Re-Ranking, Emad Sherif

International Journal of Cybersecurity Intelligence & Cybercrime

Cybercrime investigations increasingly depend on the ability to interpret large volumes of automated security events. For organizations without dedicated security operations centres, a situation common among small and medium enterprises, the manual translation of raw alerts into structured threat intelligence represents a critical bottleneck that slows investigative triage and limits cross-case comparability. This paper evaluates an automated enrichment pipeline designed to address this bottleneck by mapping security events to standardised adversary behaviour labels drawn from the MITRE ATT&CK framework, supporting both operational response and cybercrime investigation workflows. We compare three pipeline configurations, a general-purpose encoder model, a cybersecurity domain-adapted variant, …

Evaluation Of Dredged Sediments As A Partial Replacement For Fine Aggregate In Mortar And Concrete, Ashish Gautam

Graduate Theses and Dissertations (2019 - present)

The feasibility of using dredged sediment from the Mobile River as a partial replacement for fine aggregate in mortar and concrete was investigated through a series of laboratory characterization and performance evaluation. Three dredged sediment samples (A, B and C) were initially examined, and Sample A was selected for further evaluation due to its closer resemblance to natural fine aggregate. This sample exhibited lower moisture content, higher sand equivalent values, higher specific gravity, and lower absorption. Mortar mixtures with 0, 10, 20, 30, 50, 75 and 100% dredged sediment replacement showed decreasing workability as the replacement level increased. The 20% …

Alfred Russel Wallace Notes 42: How Accurate Are The Transcriptions Presented At The Alfred Russel Wallace Page Website?, Charles H. Smith

Faculty/Staff Personal Papers

A look is taken at the level of accuracy displayed by the transcriptions of Wallace writings offered at the Alfred Russel Wallace Page website, as determined by a ChatGPT analysis.

Indigenous Community Research Opportunities, Sharon Hausam, Aaron M. Canter

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

Opportunities For Leadership In Indigenous And Tribally Engaged Research At The University Of New Mexico, Sharon Hausam

Faculty Publications

This is a working paper produced as part of National Science Foundation project #2115169, “Transforming Rural-Urban Systems: Trajectories for Sustainability in the Intermountain West,” known as the “Intermountain West Transformation Network” (TN), led by the University of New Mexico with institutional partners at three additional universities in New Mexico, two in Arizona, and one each in Utah, Colorado, and Washington. The TN’s Indigenous and Tribal engagement was supported through a contract with Dr. Sharon Hausam, additional work by Aaron M. Canter, coordination with Dr. Lani Tsinnajinnie, and an Advisory Committee on Indigenous Information Needs primarily comprised of Indigenous representatives in …

Watersmart Farms - Desalination: Best Practice Study On Desalination In Agriculture Summary, V Ravisankar, W Ela, M Maharjan, J K. Ruprecht

Natural resources commissioned reports

The report reviews global and Australian best practices in agricultural desalination, with a strong emphasis on Western Australia. It evaluates desalination technologies, renewable energy integration, costs, and policy approaches to improve agricultural water security. The study concludes that desalination can play an important role in addressing freshwater scarcity, particularly where brackish groundwater resources are abundant and conventional freshwater supplies are unreliable.

This summary refers to the full report:

Ravisankar, V., Ela, W., Maharjan, M. and Ruprecht, J.K. (2025). WaterSmart Farms – Best Practice Study of Desalination in Agriculture. A report to Water Corporation and Department of Primary Industries and Regional …

Criticality In A Heterogeneous Neutron Transport Rod Model, Samuel Kaleb Crowford

All Graduate Reports and Creative Projects, Fall 2023 to Present

This work studies the stochastic behavior of neutron populations in a one-dimensional rod model using Monte Carlo simulation. The first part of this project reproduces the computational results of Dumonteil, Horton, Kyprianou, and Zoia (2025) by independently implementing the Monte Carlo algorithm described in their article, with the asymptotic behavior of the first moment analyzed in relation to the dominant eigenvalue and adjoint eigenfunction of the neutron transport operator. The model is then extended to a heterogeneous setting by introducing a central region where fission is suppressed. A global expectation over initial positions and directions is used to estimate the …

Advancements In Modern Seismic Monitoring: Integrating Novel And Traditional Methods For Earthquake Detection, Characterization, And Structural Imaging, Marc Adrian Garcia

Open Access Theses & Dissertations

Modern seismic monitoring has been transformed by machine-learning methods that detect and locate earthquakes at scales manual analysis cannot reach. This dissertation develops, validates, and applies such workflows across three settings that span the range of modern monitoring problems: a major subduction-zone aftershock sequence, the tectonic questions that sequence can answer, and an urban region without any local monitoring at all. First, I construct a high-resolution catalog for the aftershock sequence of the September 8, 2017, Mw 8.2 Tehuantepec, Mexico earthquake, by integrating deep-learning phase detection with established location and relocation methods. The resulting catalog of 11,374 relocated earthquakes is …

A Patch-Level Framework For Urban Vegetation Water Demand Estimation Using Remote Sensing And Deep Learning, Jesus Daniel Pereyra Manriquez

Open Access Theses & Dissertations

Urban water management in semi-arid regions requires an improved understanding of how vegetation and climatic conditions influence landscape water demand. Existing approaches often lack an integrated, spatially consistent framework to quantify this relationship at fine scales. This study proposes a patch-level framework to estimate relative landscape water demand by integrating vegetation coverage, vegetation condition, and atmospheric demand. Vegetation coverage is derived from high-resolution imagery obtained from the National Agriculture Imagery Program (NAIP) using a U-Net segmentation model with a MobileNetV2 backbone. A patch-based representation is used to ensure spatial consistency across the study area. Seasonal vegetation dynamics are captured using …

Domain Adaptation Of Facial Age Estimation For Law Enforcement Mugshot Repositories, Jorge Alejandro Pacheco Roque

Open Access Theses & Dissertations

Facial age estimation supports law enforcement via image-based, age-filtered queries, age-progressive re-identification, and bulk record labeling, where prediction accuracy determines if the resulting decisions can be trusted. State-of-the-art models excel on web imagery but incur higher error on mugshots due to domain shift between the professionally lit, filtered, and posed web photographs used during pre-training and the uniform backgrounds, uncooperative expressions, and decades of evolving capture technology found in mugshot collections. We address this gap by adapting SwinFace - a state-of-the-art multi-task Swin Transformer with public code and pretrained weights, trained on color face imagery for face recognition, facial expression …

Dlc Thin Films For Semiconductor Applications, Balam Arturo Sotelo

Open Access Theses & Dissertations

The growing need for resilient semiconductor supply chains has increased the interest in developing local and accessible materials fabrication strategies. Since large-scale semiconductor manufacturing is complex to establish quickly, simpler deposition techniques may provide a practical route to start developing semiconductors materials. Diamond-like carbon (DLC) is a promising candidate in this context because its properties can be tailored through substrate selection and processing parameters.

This thesis establishes an initial framework for the study and fabrication of diamond-like carbon (DLC) materials in the Department of Physics at The University of Texas at El Paso. DLC thin films were deposited by magnetron …

Stabilized Continuous Galerkin Methods For Heat Transport In Fully Coupled Nonlinear Thermo-Poroelasticity In Heterogeneous Porous Media, Payel Dey

Open Access Theses & Dissertations

This thesis focuses on the numerical approximation of a coupled Thermo-Hydro-Mechanical (THM) model with advective heat transport in heterogeneous media. The governing equations consist of three coupled equations: the momentum balance, the fluid mass balance, and the energy balance. The primary unknowns are displacement, pressure, and temperature. In this system, the fluid pressure determines the Darcy flux, and this flux transports heat through the advective term in the energy equation. Since the Darcy flux is computed numerically from the flow equation, the conservation properties of the flow approximation can affect the temperature solution. This effect is especially important when thermal …

Herd: A Policy-Driven Elastic Resource Distribution Framework For Hpc Deep Learning, Alejandro Guerrero Rodriguez

Open Access Theses & Dissertations

Modern deep learning workloads increasingly rely on distributed computation, and High Performance Computing systems can provide the necessary resources through large GPU allocations across interconnected nodes. Despite this, most distributed training frameworks operate under static resource assignments once a job is deployed. Research on NERSC Perlmutter has shown that 50% of GPU-enabled jobs use 25% or less of available GPU memory, and elastic training can reduce this underutilization by dynamically adjusting active workers. However, existing elastic systems have been developed mainly for cloud environments where fault tolerance and cost optimization are the primary concerns. Applying elastic training to HPC environments …

Where Electrons Localize And Bonds Vibrate: Computational Insights Into Lanthanides And Octanoic Acid., Sonam Choki Lhamo

Open Access Theses & Dissertations

Density Functional Theory (DFT) is a widely used approach for studying the electronic and vibrational properties of atomic and molecular systems. It provides a practical balance between accuracy and computational cost, making it suitable for a broad range of applications in quantum chemistry and materials science. The primary focus of this thesis is the electronic structure of lanthanide atoms, where strongly localized 4f electrons give rise to significant self-interaction errors in conventional density functional approximations. The performance of the Perdew-Zunger self-interaction correction (PZSIC) and the locally scaled self-interaction correction (LSIC) approach developed by Zope et al. is investigated using both …

Optimizing Urban Forestry Through Green Infrastructure: Tree Health And Water Retention In Ciudad Juarez Rain Gardens, Tomas Rogelio Lizarraga Ruiz

Open Access Theses & Dissertations

Urban green spaces (UGS) in arid regions face significant challenges due to water scarcity and extreme thermal demand. This study evaluates the efficacy of Nature Based Solutions (NBS), rain gardens and median strips, in enhancing the physiological resilience of urban trees in Ciudad Juárez, Mexico. Using a comparative framework, the research monitored a native evergreen (Dermatophyllum secundiflorum) and an introduced deciduous species (Morus sp.) across six planting treatments. Statistical analysis reveals that green infrastructure (GI) acts as a critical physiological accelerant. Trees situated within rain gardens and medians significantly outperformed those in restricted pot and sidewalk settings, maintaining higher stomatal …

A Computational Approach To Electronic Coupling In Molecular Dyads, Irving Alejandro Lopez Ruiz

Open Access Theses & Dissertations

Excitation energy transfer (EET) is a fundamental process in photosynthetic systems and molecular photonic devices, where the efficient transport of electronic excitation between donor and acceptor chromophores determines the overall performance of the system. The electronic coupling V_DA between the transition densities of the two fragments is the central quantity governing this process in the weak-coupling (Förster) regime, and its accurate numerical evaluation is the main objective of this work. Two independent computational implementations of the Coulomb interaction between transition densities were developed and applied to a set of five anthracene-BODIPY donor-acceptor dyads, studied under two geometric configurations: one preserving …

Learning To Unlearn: Unlearning And Meta-Unlearning For Continually Adapting Cybersecurity Threat Detectors, Daniel Lucio

Open Access Theses & Dissertations

Machine learning (ML) models deployed in non-stationary environments must continually adapt to evolving data distributions. This challenge is particularly critical in cybersecurity, where malware, intrusion techniques, and adversarial behaviors evolve over time. Continual learning primarily enables incorporating new knowledge while preserving prior knowledge, however, indiscriminately retaining obsolete and harmful information can hinder future adaptation and consume limited model capacity. We argue that effective adaptation should not only acquire new knowledge, but also selectively discard obsolete and less useful historical knowledge before learning from a new distribution. In this work, we propose a meta-learning framework that learns what to forget to …

Unsupervised Learning For Minimum Error Adaptive Sampling Of Atmospheric Vertical Temperature Profiles, Alejandro Medina

Open Access Theses & Dissertations

Uncrewed aerial systems (UAS) collect atmospheric data on fixed schedules, and endurance limits make blind searching costly. This thesis develops an unsupervised representation that summarizes a multi-decade radiosonde archive into a compact library of atmospheric states, giving a UAS an expectation of the column before it flies. The method standardizes both axes of a profile against the sounding's own surface conditions, which makes the representation independent of season and of station elevation. Applied to 27,270 soundings from Norman, Oklahoma, over the lowest 1.5 km of the atmosphere, 12 representative profiles reconstruct the record to within 1.0 °C of mean absolute …