Digital Commons Network^™

Instance-Adaptive Gated Fusion Of Multi-Transform Image Representations, Prince Appiah

Open Access Theses & Dissertations

This dissertation proposes the Instance-Adaptive Gated Fusion (IAGF) framework, a novel deep learning architecture for adaptive and interpretable fusion of multiple time–series image transformations. While existing methods rely on static concatenation or dataset-level optimization, IAGF introduces a learnable gating mechanism that dynamically assigns per-instance weights to Recurrence Plots (RP), Gramian Angular Summation Fields (GASF), and Gramian Angular Difference Fields (GADF). The gating layer performs a convex fusion of transformation-specific embeddings under a softmax constraint, ensuring mathematical stability and interpretability. An entropy-regularized objective prevents dominance collapse and promotes balanced exploration of transformations during training. Comprehensive experiments across eighteen benchmark datasets, spanning …

Evaluation And Identification Of Risk Factors For Stress Among Maquiladora Workers Based On The Mexican Official Standard 035 Survey Tool, Andrea Baca Melendez

Open Access Theses & Dissertations

Background and significance: Occupational psychosocial risk factors are workplace conditions that can trigger physiological, emotional, cognitive, and behavioral changes. They are strongly associated with mental health issues such as anxiety and depression, as well as non-mental health conditions like myocardial infarction, stroke, and occupational injuries. Analyzing these risks from a sociodemographic perspective provides valuable insights for improving work environments and workers’ well-being. Purpose: This study aimed to identify and determine the levels of occupational psychosocial risk factors among workers in a manufacturing company in Cd. Juárez, Chihuahua, and to examine their relationship with sociodemographic variables to inform future interventions in …

Simulation, Modeling, And Economical Optimization Of Small Modular Reactors For Flexible Power System Operations, Javier Bejarano

Open Access Theses & Dissertations

The transition toward a low-carbon and increasingly renewable electric grid has heightened the need for generation technologies that can deliver both stability and operational flexibility. Small Modular Reactors (SMRs), with their modularity, reduced geographical footprint, and capacity for flexible operation, have emerged as promising resources for supporting modern power systems. However, a comprehensive evaluation of their technical performance across steady-state conditions, fault-induced disturbances, and economically optimized dispatch is necessary to understand their role in future grid architectures. This thesis provides an assessment of SMR capabilities using benchmark test systems, data-driven forecasting, dynamic simulation, and unit commitment modeling to evaluate how …

Enduring Efffects Of Juvenile Fluoxetine Exposure On Serotonin Transporter Expression Within The Hippocampus And Prefrontal Cortex Of Male C57bl/6 Mice, Daniel Eduardo Calvo

Open Access Theses & Dissertations

Prescription rates of fluoxetine, the most dispensed selective serotonin reuptake inhibitor, have been rising among the juvenile population. Since adolescence is a critical developmental period in which the brain undergoes pruning, chronic increases in serotonin levels may lead to long-term neurobiological changes in brain regions responsible for emotional regulation. Thus, using mice as a model system, this thesis evaluated how adolescent fluoxetine exposure (AFE) influences the expression of serotonin transporters (SERT) in the adult hippocampus and prefrontal cortex. To do this, postnatal day (PD)-35 male C57BL/6 mice were administered with fluoxetine (250 mg/l in their drinking water) for 15 consecutive …

Ai-Facilitated Abuse & Misogyny: A Feminist Response To Non-Consensual Intimate Image Deepfakes, Lizbeth Carmona

Open Access Theses & Dissertations

The creation of non-consensual intimate images utilizing AI deepfake technology has been demonstrated to overwhelmingly target women. The harms of non-consensual intimate image deepfakes are similar to other forms of misogynistic abuse, including intimate image abuse and online objectification. This project seeks to contextualize this phenomenon within feminist accounts of misogyny and its role in regulating women's behavior. In particular, this project highlights that the accessibility of this technology has lowered the threshold of abuse, despite the individual woman's preventive measures. Furthermore, this project argues that the dissemination of non-consensual intimate image deepfakes is a morally problematic situation because it …

Hydrological Responses To Rainfall Pulses In Desert Vadose Zones: A Multi-Scale Approach Integrating Geophysical, Isotopic, And Eddy-Covariance Measurements, Alfredo Dagda-Torres

Open Access Theses & Dissertations

Drylands are shaped by natural episodic precipitation, where short, intense rainfall pulses interrupt prolonged drought and drive most hydrological and ecological activity. Yet the mechanisms that determine how pulse water infiltrates, is redistributed, stored, evaporated, and ultimately used by desert vegetation remain under quantified in landscapes underlain by shallow petrocalcic horizons. This dissertation integrates three complementary approaches 1) three-dimensional electrical resistivity tomography, 2) eddy-covariance evapotranspiration partitioning, and 3) stable-isotope tracing to improve a mechanistic understanding of pulse-driven water movement and plant water use in a caliche-rich piedmont at the Jornada Experimental Range. The first component characterizes how infiltration pulses interact …

Intelligent Predictive Frameworks Under Data Scarcity And Uncertainty, Solayman Hossain Emon

Open Access Theses & Dissertations

Modern predictive systems frequently operate under conditions of limited annotated data, high uncertainty, and the need for reliable decision-making. When the predictive models expand across heterogeneous data types (e.g., spatial, temporal streams), the challenge lies not only in accurate prediction but also in adapting in data distributions shifts or label scarcity. To address these issues, this thesis explores an Intelligent Predictive Framework that operates robustly under data scarcity and uncertainty across two distinct domains: medical imaging (spatial) and time-series forecasting (temporal). In the first part of this work, a semi-supervised mean teacher (MT) paradigm is tailored for medical image segmentation …

Development Of Oxide And Oxynitride Thin Films For Advanced Optical Applications, Nathan Christopher Episcopo

Open Access Theses & Dissertations

To develop Ga2O3 and TiOₓNᵧ thin films for optical applications, the process–structure–properties relationship was investigated using a comprehensive set of characterization techniques to establish the atomic structure and composition of the films in relation to the deposition conditions. The results provide critical insights into how deposition parameters influence the atomic structure and composition during magnetron sputtering. Furthermore, the correlation between atomic structure and composition with the optical and electrical properties of the films was examined to determine how variations in these factors affect functional performance. Collectively, these findings offer the necessary information to target desirable optical properties for Ga2O3 and …

Borderlines Of Becoming: Transfronterizx College Students Navigating Surveillance, Hybridity And Belonging Along The Us-México Border, Aylin Garcia

Open Access Theses & Dissertations

This narrative literature review examines the educational experiences of transfronterizx college students along the U.S.– México border, a population largely absent from higher education scholarship. Drawing on Borderlands Theory, Anzaldúa’s frameworks, and critical perspectives on neoliberalism and militarization, this thesis highlights the border as a site of both constraint and possibility. Structural violence, surveillance, and militarization intersect with linguistic, racial, and class hierarchies to shape students’ mobility, identities, and sense of belonging. At the same time, students mobilize hybrid identities, cultural wealth, and transborder networks to assert agency, cultivate belonging, and resist deficit narratives. It also identifies persistent gaps, particularly …

From Morphology To Machine Learning And Genomics: Understanding Phenotypic Variation In Wild Ducks, Sara Gonzalez

Open Access Theses & Dissertations

Understanding the genetic underpinning and distribution of phenotypic variation within and between divergent groups is core towards shedding light into how populations diverge and adapt, as well as how hybridization breaks or builds on these scenarios; and thus, central to evolutionary biology. In wild organisms, however, quantifying and linking phenotypic traits to underlying genetic processes, like mutation, gene expression, epigenetics and allele interactions, remains challenging. This difficulty arises from the complex interplay between morphology, environment, and gene regulation, as well as the logistical barriers of collecting and standardizing large-scale data across individuals and populations. As a result, researchers are increasingly …

Our Trajectories As We Leave The Teaching Profession: Pláticas With Former Bilingual Teachers On The U.S.-Mexico Border In Texas- An Explanatory Sequential Mixed-Methods Study, Carla Medina Jaquez

Open Access Theses & Dissertations

Teacher attrition has had a negative impact on the educational system for many years. New and experienced teachers have been leaving the classroom. Although the reasons appear repetitive, we know relatively little about what teachers must go through when deciding to leave the profession and what happens to them afterward. A teacher shortage is occurring along the U.S.-Mexico border, as in many other cities across the United States. Despite undergoing a lengthy certification process, teachers continue to leave the classroom. This research employed an explanatory sequential mixed-methods design to explore how new and experienced teachers navigate their transition out of …

Facilitating Deep Learning Performance Analysis Through Automated Roofline Model Generation, Irvin Lopez-Audetat

Open Access Theses & Dissertations

This thesis presents a tool to profile deep learning (DL) and machine learning (ML) models by collecting FLOPs, memory movement, and timing data through cyPAPI to generate roofline performance models. The tool is containerized for portability and reproducibility, integrates directly with PyTorch workflows, and provides fine grained insights into computational bottlenecks across model components. Unlike prior system-level or benchmarking-centric tools, this project empowers developers and researchers with an accessible, modular framework for performance analysis and optimization.

Exploring Intersectional Risks Of Substance Use Disorder, Mental Health, Hiv/Aids, And Hepatitis C Among Hispanic Adults On The Tx-Mx Border: A Mixed-Methods Study, Md Mohsin

Open Access Theses & Dissertations

Purpose: The purpose of this study was to explore intersectional risks of substance use disorders, mental health, HIV/AIDS, and HCV among Mexican-origin Hispanic adults on the Texas-Mexico border. Methods: The study employed an exploratory sequential mixed-methods approach, which involved collecting and analyzing qualitative data first, followed by quantitative data collection. Selected purposively, 15 in-depth interviews were conducted among the target population. Using convenient sampling, 106 cross-sectional surveys were conducted. Qualitative interview data were analyzed manually using thematic analysis. Quantitative data analyses included univariate descriptive analysis, bivariate, and multivariable penalized logistic regression, negative binomial, and zero-inflated negative binomial regression. Results: The …

A Half Century Of Biophysical Change In Polygonized Tundra On The Coastal Plain Of Northern Alaska, Mariana Mora

Open Access Theses & Dissertations

Climate change is amplified in the Arctic. As a result, Arctic tundra landscapes are undergoing physical changes through accelerated thaw and ice-wedge degradation. Understanding the magnitude and direction of these changes in the Arctic is a necessary step toward understanding the response of the Arctic to climate change and feedbacks to the Climate System. Through repeat measurements collected from 1973 through 2018, we were able to assess decadal time scale changes in polygon geomorphology, thaw depth, land surface compression and expansion, and vertical elevation within a highly polygonized tundra system, and their implications when scaled to a regional level. This …

Evaluating Large Language Models For Requirements Engineering And Verification: A Comparative Analysis Of Gpt-5 And Gemini 3 Pro, Guadalupe Nevarez

Open Access Theses & Dissertations

Large Language Models (LLMs) are increasingly viewed as viable tools for Systems Engineering, yet empirical data regarding their effectiveness in generating engineering-quality requirements remains limited. This thesis compares the performance of GPT-5 and Gemini 3 Pro in generating system functional requirements for the Miner Guardian Drone, a prototype UAV designed for minefield remediation. Both models were provided with identical prompts and tasked with producing 15 functional requirements. Two independent raters evaluated the outputs using a nine-dimensional quality rubric aligned with IEEE 29148 and INCOSE guidelines to ensure rigorous assessment. The difference between the models was analyzed using descriptive statistics and …

Decoupling Piezoelectric And Pyroelectric Effects In Anisotropic Polymer-Ceramic Lattices Produced Via Fused Filament Fabrication, Sofia Alexandra Perez

Open Access Theses & Dissertations

This thesis investigates how multi-material fused filament fabrication (FFF) can be used to engineer lattice structures that decouple piezoelectric and pyroelectric responses within a single polymer–ceramic composite. A hybrid ABS–BaTiO3/PLA lattice—referred to as the Hybrid PIZCAL—was designed to direct mechanical strain along the Z-axis while suppressing deformation in the transverse directions. After thermal poling, the lattice exhibited a 293% increase in Z-axis voltage sensitivity compared to a monolithic ABS–BaTiO3 cube and significantly reduced off-axis electromechanical output. Finite element simulations and directional compression testing confirmed that geometric anisotropy and material zoning produce strong, axis-selective piezoelectric behavior. The second part of this …

Expression And Purification Of Prohibitin Proteins And Investigation Of Their Interaction With Mycobacterium Tuberculosis’S Virulence Factors, Zeina Rhaim

Open Access Theses & Dissertations

Prohibitin (PHB) is a highly conserved mitochondrial protein involved in cell cycle regulation, apoptosis, mitochondrial integrity, macrophage activation, cytokine production and many other critical cell functions. The prohibitin complex, formed by Prohibitin-1 (PHB1) and Prohibitin-2 (PHB2), functions as a mitochondrial membrane-associated receptor. Cancer, neurodegenerative disorders, and renal conditions were found to be linked to an irregular PHB expression. Emerging evidence has also highlighted a significant role for PHB in tuberculosis (TB), particularly through its interactions with Mycobacterium tuberculosis (Mtb) virulence determinants. The molecular mechanisms by which PHB influences TB pathogenesis remain poorly understood. Our preliminary studies showed that PHB1 was …

One Step Fabrication: Software-Automated Printed Circuits Via Multi-Material Additive Manufacturing, Gabriel Sanchez

Open Access Theses & Dissertations

As of now, the creation of 3D printed components faces many issues regarding stability, repeatability, and manual labor. Existing methods lack an integrated software framework that automates circuit generation while ensuring predictable behavior in printed geometries. In this work, circuits are modeled by leveraging distributed equations that reduce to lumped approximations when the printed geometry remains uniform. The system is implemented through a parametric, domain-specific programming workflow and evaluated across 100 Hz to 100 kHz to assess the accuracy of the predicted electrical values. Printed results were validated by empirical studies involving an RLC meter and by comparing both theoretical …

Development And Optimization Of A Deep Level Transient Spectroscopy System, Samuel Ruiz

Open Access Theses & Dissertations

Deep-level transient spectroscopy (DLTS) remains one of the most widely used techniques for identifying electrically active defects that affect leakage current, carrier lifetime, and overall reliability in semiconductor devices. Legacy boxcar or capacitance meter implementations, however, often struggle with limited signal-to-noise ratio, labor-intensive data collection, and poor adaptability across diverse material systems. This thesis presents the design and optimization of a semi-automated, lock-in-amplifier-based DLTS platform. By pairing a Zurich HF2LI with PID-controlled cryogenic sweeps, precision signal generation, and MATLAB driven acquisition and processing scripts, the system will (i) enhance SNR through phase-sensitive detection, programmable low pass filtering, and parasitics calibration; …

What Limits Dryland Ecosystems? Patterns Of Soil Fertility And Resource Limitation In The Chihuahuan Desert, Dylan Stover

Open Access Theses & Dissertations

Human activities are substantially altering global resource cycles with widespread implications for biogeochemistry and ecosystem functioning globally. Drylands, regions where precipitation is outweighed by water losses, are especially sensitive to these large shifts in resource cycles due to their inherently low and variable resource availability. In these regions, resource availability and biological activity are often concentrated around plants – or fertile islands – and predominantly driven by pulses of water. However, our knowledge of the processes influencing biological productivity in drylands – patterns of soil fertility and resource limitation – remains lacking, and their unique biogeochemical and biological processes create …

A Unified Framework For Embedding-Based Synthetic Data Generation With High Cardinality Categorical Features, Cesar Iram Vazquez

Open Access Theses & Dissertations

High-cardinality categorical variables remain difficult to model in tabular data, where classical encoders encounter sparsity, susceptibility to leakage, and the loss of meaningful relational structure. This dissertation develops a unified framework for learning, evaluating, and synthesizing representations of such variables using both traditional encoders and modern embedding methods, including Word2Vec, FastText, Node2Vec, TF–IDF/SVD, and supervised entity embeddings. The framework is applied across three benchmark datasets (Adult, PetFinder, Breast Cancer) and a hierarchical educational case study (IPEDS/CIP). Embedding quality is examined through both downstream predictive performance and structure-focused diagnostics that quantify neighborhood behavior and geometric coherence. To assess whether synthetic data …

Hubert-Based Models And Evaluation Strategies For Pragmatically-Faithful Speech To Speech Translation, Javier Vazquez

Open Access Theses & Dissertations

Pragmatic fidelity in speech-to-speech translation (S2ST) has largely been understudied, leading to communication tools inadequate to support non-superficial dialog. We aim to improve pragmatic faithfulness in English-Spanish translation through the development of machine learning models that are able to predict a corresponding pragmatic representation in the other language. To evaluate performance, we developed a pipeline that utilizes a recently-developed pragmatic similarity evaluation metric to compare models. Further, we developed models that exploit HuBERT features as these have been found suitable for various prosody and pragmatics related tasks. Our models outperformed human and state-of-the-art predictions, albeit the methodology being limited to …

Ode To The Infomercial, Edward Wade

Open Access Theses & Dissertations

'Ode to the Infomercial' is a poetry collection in five sections which explores themes of contemporary American life, parenthood, and the media landscape. While primarily written in a narrative voice, the poetic approach is as diverse as the content. Interwoven throughout the collection is religious imagery and political posturing accompanied by healthy doses of self-criticism and humor.

Metal Zonation And Evolution Of The Bronson Slope Porphyry Cu-Au-Mo Deposit In The Iskut Region Of British Columbia, Canada, Luis Jacobo Yagual

Open Access Theses & Dissertations

Bronson Slope is a Cu-Au-Mo porphyry deposit located within the Stikine Terrane in the Golden Triangle District of northwestern British Columbia, Canada. This deposit represents a complex, multistage magmatic-hydrothermal system emplaced into sedimentary and volcanoclastic rocks of the Triassic Stuhini Group. Bronson has an inferred resource of 517.3 Mt at 0.33 g/t Au, and 0.09% Cu. This study integrates detailed and quick logging from 20 drill holes, totaling 20,296m, SWIR spectral analysis, ICP-MS geochemistry, XRF analysis, magnetic susceptibility measurements, geochronology, and 3D models developed in Leapfrog Geo which define the stratigraphy, intrusive geometry, extension, alteration footprint assemblage, metal zonation, and …

Voices At The Intersection: A Listening Guide Analysis Of Campus-Based Advocates Navigating Institutional Policies On Sexual Violence, Arely Zaragoza-Hernandez

Open Access Theses & Dissertations

Campus-based advocates occupy a critical yet complex position within higher education institutions (Nightingale, 2023; Wood et al., 2021), serving as frontline support for students while simultaneously navigating the mandates, policies, and bureaucratic structures that define their roles. This research study explores the lived experiences of advocates working in university settings, focusing on how institutional mandates from compliance requirements to administrative expectations shape, constrain, and sometimes empower their daily practices. Using a qualitative, phenomenological approach, the study centers the voices of campus-based advocates in Texas to illuminate the tensions between their professional commitments to student-centered care and the institutional imperatives of …

Physics-Guided Strategies For Enhancing Neural Networks Trained With Limited Data, Jose Guadalupe Perez Zamora

Open Access Theses & Dissertations

Deep neural networks excel at a wide range of processing tasks across various disciplines. However, the quantity and quality of data significantly impact network performance. In specialized domains, high-quality datasets are often difficult to gather, interpret, and curate for effective learning. Few-shot learning techniques, including transfer learning, data augmentation, and meta-learning, have emerged to address these constraints.

We propose three physics-guided strategies for enhancing neural networks trained with limited data: (1) combining existing models like LSTMs with Physics-Informed Neural Networks through two-branch architectures that merge their outputs, (2) deriving custom physics-informed data augmentation algorithms to expand limited datasets, and (3) …

Does Reducing Videofluoroscopy Frame Rate Affect Dige/St Grades In Modified Barium Swallow Studies?, Shitong Mao, Carla L Warneke, Sheila N Buoy, Ariana J Sahli, Brinda Rao Korivi, Carly E A Barbon, Kristy K Brock, Katherine A Hutcheson

Faculty, Staff and Student Publications

Understanding the effects of reduced frame rates on the reliability of Modified Barium Swallow (MBS) ratings for swallowing safety and efficiency is essential for clinical practice. While previous research has examined frame rate (simulated pulse rates) implications concerning penetration, aspiration, and residue ratings, the impact on summary grading systems like the Dynamic Imaging Grade of Swallowing Toxicity (DIGEST) remains unclear. This study analyzed a total of 315 full MBS videos collected from 278 patients, and 76.25% of patients were diagnosed with head and neck cancer (mean age 62.51 years, SD 8.53; 12.23% female). We performed pairwise comparisons of DIGEST grades …

Smags-Lasso: A Novel Feature Selection Method For Sensitivity Maximization In Early Cancer Detection, Hamid Khoshfekr Rudsari, Sara Khorami-Sarvestani, Johannes F Fahrmann, James P Long, Samir Hanash, Kim-Anh Do, Ehsan Irajizad

Faculty, Staff and Student Publications

Background: Sensitivity and specificity are foundational metrics for cancer detection tools. However, most machine learning algorithms prioritize overall accuracy during optimization, which fails to align with clinical priorities of early detection. We aim to develop a feature selection machine learning algorithm while maximizing sensitivity at a given specificity.

Methods: We developed SMAGS-LASSO, a machine learning algorithm that combines our developed Sensitivity Maximization at a Given Specificity (SMAGS) framework with L1 regularization for feature selection. This approach simultaneously optimizes sensitivity at user-defined specificity thresholds while performing feature selection. SMAGS-LASSO utilizes a custom loss function with L1 regularization and multiple parallel optimization …

Differential Microrna Profiling Of Blood L1cam And Bulk Extracellular Vesicles In Bipolar Disorder, Gabriel R Fries, Salahudeen Mirza, Jun Wang, Camila N C Lima, Wei Zhang, Marcela Carbajal Tamez, Giselli Scaini, Jair C Soares, Joao Quevedo

Faculty, Staff and Student Publications

Objective: This preliminary study aimed to identify microRNA (miRNA) signatures associated with bipolar disorder (BD) by profiling blood-derived extracellular vesicles (EVs) of both putative neuronal origin and from all sources.

Method: In two parallel studies of individuals with BD and controls (CON), we characterized miRNA expression profiles of blood EVs selected for L1CAM, a putative marker of neuronal origin (n = 20 BD/20 CON), as well as bulk EVs (n = 21 BD/20 CON). For each study, analyses identified miRNAs differentially expressed between groups, followed by functional interrogation and testing for associations with clinical features.

Results: Results of …

Periostin Promotes Sarcoma Growth By Promoting Tumor-Associated Macrophage Migration And Differentiation, Jin-Fen Xiao, Kristin Ishaya, Emily Y Ko, Annaliese Fowler, Marina T Broz, Jlenia Guarnerio

Faculty, Staff and Student Publications

Soft-tissue sarcomas (STS) are characterized by abundant extracellular matrix (ECM) deposition, yet the functional contribution of specific ECM components remains poorly understood. In this study, we identify periostin (POSTN), a matricellular protein, as a regulator of sarcoma progression and the tumor immune microenvironment. Analysis of human sarcoma datasets revealed that high POSTN expression correlates with poor prognosis and elevated expression of ECM-related and myeloid cell–associated genes. In murine genetic models of sarcoma, tumors expressing high levels of Postn displayed enhanced expression of ECM genes and monocyte-recruiting cytokines. Functional silencing of Postnin vivo reduced tumor growth without altering tumor cell …