Physical Sciences and Mathematics Commons^™

Assessing The Health Impacts Of Pm2.5 And Ozone Exposure: A Study Of Hospitalizations In El Paso, Alexia Breanna Reyes

Open Access Theses & Dissertations

Air pollution has been widely associated with adverse cardiovascular health outcomes; however, most research in arid regions has focused on high-intensity dust events rather than routine, non-dust conditions. This study aimed to evaluate the association between non-dust air pollution and cardiovascular hospitalizations in El Paso County, Texas. A time series analysis was conducted using hospitalization data from 2010 to 2014. Daily counts on non-dust event days of cardiovascular hospitalizations, including hypertensive diseases, ischemic heart disease, cerebrovascular disease, and diseases of pulmonary circulation, were examined in relation to ambient concentrations of fine particulate matter (PM2.5) and ozone. Quasi-Poisson regression models with …

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 …

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 …

Hfir Antineutrino Flux Mapping With Scale Mesh Tallies, Jacob Adam Mireles

Open Access Theses & Dissertations

This thesis develops and demonstrates a workflow for mapping the spatial distribution of reactor electron antineutrino flux around the High Flux Isotope Reactor (HFIR) using three-dimensional mesh tallies from the SCALE 6.3.1 Monte Carlo transport suite. A detailed HFIR model is executed with KENO, and the mesh-tally output is post-processed to construct a voxelized antineutrino source term. The source field is normalized to reactor power and propagated to sampled spatial points surrounding the reactor to generate three-dimensional source-side flux maps. The main analysis focuses on how the mesh-based HFIR antineutrino flux differs from an ideal point-source approximation. In the point-source …

Physics Model Calibration Via Functional Kernel Regression, Kwesi Appau Ohene-Obeng

Open Access Theses & Dissertations

Physics based computational simulators encode the governing equations of complex physical phenomena through parameters that must be inferred from empirical observations, and the observational record in modern experimental campaigns is increasingly a high dimensional functional response rather than a scalar summary. The canonical treatment of this calibration problem through the additive discrepancy decomposition of Kennedy and O'Hagan incurs O(N^3obs) Gaussian process inversion costs at functional resolution, sensitivity to discrepancy prior specification, and the confounding identifiability between the calibration parameter and the discrepancy function; scalar reduction strategies bypass the cost but discard the morphological information that the functional response carries about …

Towards A Multi-Framework Approach To Explainable Artificial Intelligence, Henry Salgado

Open Access Theses & Dissertations

Artificial Intelligence (AI) and machine learning (ML) models are increasingly being deployed to support decision-making in high-stakes domains such as healthcare, criminal justice, and education, where trust, accountability, and transparency are critical. However, increasing model complexity has made many modern systems insufficiently transparent. Existing approaches to explainable AI (XAI) typically emphasize either intrinsic model simplicity or post-hoc attribution methods that estimate feature importance for predictions. While these approaches provide valuable insights into model behavior, they do not necessarily establish whether the identified importance is grounded in the underlying data patterns or in the structural relationships that generate model behavior. Many …

An Analysis Of Mating Strategies In Rotifers Inhabiting Temporary Habitats, Ariel Bollinger

Open Access Theses & Dissertations

Reproduction is critical for organisms inhabiting ephemeral aquatic habitats where desiccation risk favors rapid and successful mating. Monogonont rotifers rely on sexual reproduction to produce diapausing eggs that withstand harsh conditions. I investigated how mating behaviors vary among populations of five rotifer species based on the hydroperiod of their habitat: Epiphanes brachionus and E. chihuahuaensis were sampled from habitats with short (SH) and long (LH) hydroperiods; Euchlanis dilatata was collected from a short (SH) and a permanent habitat; and Plationus patulus and Sinantherina socialis were collected from a long (LH) and a permanent (Perm) habitat. I hypothesized that SH populations …

Expression Levels Of Heat Shock Protein 72 And Their Correlation With Biomarkers Of Renal Function Among Hispanic Construction Workers Exposed To Ambient Heat In El Paso, Texas, Maria Fuentes

Open Access Theses & Dissertations

Heat shock proteins (HSP) are intracellular molecular proteins that are upregulated in response to cellular stress, including heat exposure. Through their protective functions, HSP help maintain protein structure, prevent protein denaturation, and preserve cellular homeostasis during states of physiological stress. Because of their cytoprotective properties, HSP have emerged as potential biomarkers for detecting early signs of tissue injury and predicting clinical outcomes associated with heat related illnesses (HRI), including acute kidney injuries (AKI). AKI is a leading cause of hospitalizations due to heat stress exposure and heat stroke. In the absence of early detection and effective therapeutic interventions, AKI may …

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 …

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 …

Transnational Indigenous Environmental Justice: A Distant Comparative Study Of Nepali And U.S. Environmental Policies And Counter-Archives In Technical Communication, Shankar Paudel

Open Access Theses & Dissertations

This dissertation investigates how institutional communication, state bureaucracy, and Indigenous sovereignty intersect within Rhetoric and Writing Studies (RWS) and Technical and Professional Communication (TPC). Current TPC research increasingly focuses on social justice; however, the field still lacks ethical frameworks to deal with the complicated dynamics of transnational Indigenous Environmental Justice Communication (IEJC). This study addresses this gap by examining how two distinct Indigenous communities - the Tharus of Chitwan, Nepal, and the Ysleta del Sur Pueblo Tigua Indians of El Paso, Texas - communicatively navigate, contest, and resist state environmental policies.

Grounded in decolonial Distant Comparativism, Mestiza Consciousness, Rhetoric of …

From Screening To Risk: Assessment Of Potentially Toxic Elements In Children's Toys Along The El Paso, Tx, U.S.A.-Ciudad Juarez, Chih, Mex Border Region, Jesus Rodriguez-Loya

Open Access Theses & Dissertations

Children are uniquely vulnerable to potentially toxic elements (PTEs), absorbing them more readily than adults and encountering them through the hand-to-mouth behaviors of early childhood. Exposure carries element-specific consequences: lead (Pb) impairs cognitive development with no established safe threshold; cadmium (Cd) damages the kidneys and reduces bone mineralization; arsenic (As) is a recognized carcinogen and developmental neurotoxicant; hexavalent chromium (Cr) is carcinogenic and induces allergic dermatitis; nickel (Ni) is the leading cause of allergic contact dermatitis in children; and excess zinc (Zn) disrupts copper absorption and causes gastrointestinal distress. Toys are a distinctive source of such exposure, yet none had …

A Study On The Complex Doping Of Na2x2teo6 (X = Ni, Cu, Fe, Co, Zn), Omar Salas

Open Access Theses & Dissertations

Na2Ni2TeO6 is a layered honeycomb antiferromagnet in which Ni2+ ions form magnetic honeycomb planesseparated by sodium layers. In this work, four compositionally complex oxides derived from Na2Ni2TeO6 were synthesized to test whether the NNTO-type structure remains stable when 50% of the Ni sublattice is replaced by mixtures of Cu, Zn, Fe, and Co. Powder X-ray diffraction and neutron powder diffraction show that all four samples retain the hexagonal P 63/mcm average structure of the parent NNTO phase, demonstrating that the layered honeycomb framework is stable against substantial multiple-cation substitution. A small CoFe2O4 secondary phase is present in all four samples …

Integrated Framework For Tsn-Enabled Ot Networks And Scalable Edge Computing To Enable Real-Time Feedback Loop, Taposh Kumer Sarker

Open Access Theses & Dissertations

The advent of Industry 5.0 envisions smart manufacturing characterized by human centricity, sustainability, and systemic resilience. Realizing this vision requires the seamless convergence of Information Technology (IT) and Operational Technology (OT) networks. However, integrating massive, stochastic IT edge computing workloads with deterministic physical control loops introduces severe architectural friction, inherently threatening the safety guarantees required by industrial machinery. To resolve this fundamental incompatibility, this dissertation proposes the Edge-Augmented Real-Time Industrial Control System (EA-RICS).

EA-RICS is a comprehensive, multi-layered architecture designed to dismantle systemic bottlenecks across the physical data plane, the centralized control plane, and the edge operating system. First, the …

Active And Passive Seismic Studies Across Glacial And Geothermal Environments, Lucia Fernanda Gonzalez

Open Access Theses & Dissertations

The collection of passive and active-source seismic data remains central to the detailed investigation and understanding of complex Earth processes across diverse and often inaccessible environments. Of equal importance is the selection of methodologies that must be tailored to the geological setting and dataset resolution to accurately depict the subsurface. In this dissertation, we apply a range of classic and/or "newly" developed algorithms, unique to each chapter, on seismic datasets from distinct glaciological and geothermal settings to evaluate their performance and enhance subsurface interpretation. In Chapter 1, we analyze active-source seismic data from Lemon Creek Glacier in Juneau, Alaska, using …

Hinterland To Foreland Regional Transition From Basement-Involved To Thin-Skinned Deformation In The Southern U.S. Cordillera: Sierra Rica, New Mexico, Sarafina Middaugh

Open Access Theses & Dissertations

Late Cretaceous to Paleogene age contractional deformation in the southern Basin and Range province is obscured by widespread, Cenozoic extensional faulting and volcanism. As a result, debate continues about the structural style and tectonic evolution of the region. There are two end-member structural models that have been proposed for deformation: 1) high-angle reverse faulting and basement uplift and 2) thin-skinned faulting and development of a thrust belt. We undertook new geologic mapping, cross-section construction, and structural analysis in Sierra Rica, in the bootheel region of southern New Mexico, to help evaluate these hypotheses. A major thrust system, the Sierra Rica …

Best Linear Unbiased Prediction Based On Optimally Selected Order Statistics Using Compound Design, Foster Nkansah

Open Access Theses & Dissertations

Any life-testing experiments with censoring generate ordered failure data, which are used to estimate model parameters of the underlying lifetime distribution. However, predicting unobserved failure times is an important goal post inference. Balakrishnan and Bhattacharya [2021] showed that joint best linear unbiased predictors (BLUPs) are more efficient than their marginal counterparts. In this thesis, we introduce a compound optimal design to compute joint BLUPs based on a suitably chosen subset of the observed data. It is shown that the linear predictors of the parameters from any location-scale distribution, based on a few optimally chosen ranks, obtained from the compound optimal …

A Penalty-Free Runge-Kutta Discontinuous Galerkin Method For \\[12pt] Time-Dependent Fourth-Order Partial Differential Equations, Jose Armando Perez Becerra

Open Access Theses & Dissertations

Time-dependent fourth-order partial differential equations arise in a wide range of applications in applied mathematics, physics, and engineering, including thin structure models, phase separation, and pattern formation. Their numerical approximation is challenging because the presence of fourth-order spatial derivatives typically requires high-regularity discretizations. A useful alternative is to reformulate the original problem as a coupled second-order system and approximate it by mixed discontinuous Galerkin (DG) methods.

This thesis builds upon the penalty-free mixed DG framework developed by Liu and Yin for time-dependent fourth-order problems. That framework avoids the use of interior penalty parameters, preserves the symmetry of the associated bilinear …

A Numerical Method For The Phase Field Crystal Model, Patrick Ameyaw Tabiri

Open Access Theses & Dissertations

The Phase Field Crystal (PFC) model is a continuum-based framework used to study theevolution of crystalline materials while preserving microscopic structural features over diffusive time scales. It captures complex phenomena such as phase transitions, defect dynamics, and microstructure formation via a nonlinear sixth-order partial differential equation derived from a free-energy functional. In this context, the phrase "sixth-order" indicates that the highest spatial derivative appearing in the equation is of order six. In this work, we study the mathematical formulation and numerical approximation of solutions to the PFC model. Due to the high-order spatial derivatives and nonlinearity in the governing partial …

Uncertainty In Neural Networks: An Interval Approach, Yahriel Isaac Guel

Open Access Theses & Dissertations

Neural networks produce predictions but not reliable measures of how much to trust them. A clinician handed an output such as "97% chance malignant" has no way to tell whether that 97% reflects the model's actual reliability on inputs like this one, or whether the same number would have appeared on an image the model has no business classifying. The standard approaches to uncertainty quantification - Bayesian neural networks, deep ensembles, and Monte Carlo dropout - are useful. However, sometimes the uncertainty we need to handle only comes as lower and upper bounds. This raises a natural question: what if …

Provenance Analysis Of Advanced Persistent Threats In Operational Technology Environments, Laura Aminta Guevara

Open Access Theses & Dissertations

Live vulnerability testing and penetration assessments of critical infrastructure are costly, complex operationally and, in many cases, unsafe to conduct directly against live systems, whether these are commissioned in-house and through third-party providers. For Operational Technology environments specifically, these constraints are further aggravated by the limited vendor support and inconsistent security patching available that characterize many industrial communication protocols. This significantly restricts the scope and feasibility of conventional penetration testing. At the same time, the increasing overlapping of OT systems with enterprise networks and the internet has expanded the attack surface of ICS infrastructure, making more pressing the need for …

Numerical Methods For Modeling Darcy-Forchheimer Flow In Heterogeneous Porous Media, Nate Mcnair

Open Access Theses & Dissertations

Classic approaches to modeling fluid flow in porous media rely on Darcy's Law, which assumes a linear relationship between volumetric flow rate and the pressure gradient. However, in recent years, applications such as enhanced geothermal systems have highlighted the need to model nonlinear flow behavior, since experimental and observational data show that, once flow velocity exceeds a certain threshold, the relationship between velocity and macroscopic pressure gradient becomes nonlinear. This requires alternative models that more accurately capture the physical behavior of these systems.The Darcy-Forchheimer model provides one such alternative by introducing a nonlinear velocity-pressure relationship. However, this nonlinearity creates additional …

Log Anomaly Detection With Parameter-Efficient Tiny Language Models: From Centralized Fine-Tuning To Privacy-Preserving Federated Learning, Isaiah Thompson Thompson Ocansey

Open Access Theses & Dissertations

System logs are a primary source of information for identifying faults, misconfigurations, and security incidents in computing infrastructure. As these logs grow in volume and complexity, manual inspection becomes impractical, and automated detection methods are needed. This thesis investigates how compact language models can be applied to the task of log anomaly detection under two operational conditions: when log data is centralized and when it is located at different data sites.

In the first part, we propose LogTinyLLM, which applies parameter-efficient fine-tuning through Low-Rank Adaptation and adapter-based techniques to adapt tiny language models for identifying contextual anomalies in log sequences. …