UTSA Runner Research Press (Univ. of Texas at San Antonio)
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Evaluation of Machine Learning Fairness in Regression Domain
No full textAs the application of Machine Learning (ML) models continues to expand across various domains, it becomes increasingly important to ensure the fairness of these models' function. While measuring fairness metrics is straightforward in the classification domain, it remains complex and computationally intractable in regression. To address the computational intractability challenge, prior research proposed various methods to approximate fairness metrics in regression, but their consistency remain an open question. To fill this gap, this dissertation investigates the consistency of fairness measurement methods in regression tasks through the following studies. The first study examines the consistency of the outcome of various fairness measurement methods. The experimental results reveal varying levels of consistency, with some methods, particularly, the probabilistic classification-based density ratio estimation approach, exhibit relatively poor consistency in certain cases. Then, the second study focuses on the probabilistic classification-based density ratio estimation approach to fairness measurement and explores the sensitivity of its outcome to the choice of underlying classifiers. Results demonstrate that the use of different classifiers could impact fairness values, leading to inconsistent measurements in certain circumstances. The third study analyzes alternative density ratio measurement approaches beyond the probabilistic classification-based one. The experimental results indicate concerning inconsistencies among various density ratio estimation-based approaches, raising fundamental questions about their reliability for fairness measurement in regression. To gain deeper insight, the fourth study investigates whether data distributions could contribute to such inconsistencies by generating synthetic datasets with varying distributions. The findings suggest that inconsistencies may indeed arise from the data distribution in certain cases.Computer Scienc
Green Synthesis of Silica Nanoparticles from Sugarcane Bagasse Ash for Stable Pickering Oil-in-Water Emulsions
Get PDFThe present study explores novel alternatives for the exploitation of sugarcane bagasse ash by obtaining and modifying SiO<sub>2</sub> nanoparticles through a green synthesis method. The hydrophilic nature of the nanoparticles was modified using oleic acid. The nanoparticles were characterized using FTIR, FESEM, and DLS, and their performance in the stabilization of Pickering emulsions was also studied. FESEM micrographs of the nanoparticles revealed an irregular and agglomerated structure. EDS confirmed that their main components are oxygen and silicon, and ATR-FTIR spectra demonstrated that oleic acid effectively modified the nanoparticles. Subsequently, O/W Pickering emulsions were fabricated by combining rotor&ndash;stator homogenization and probe ultra-sonication, using dodecane and liquid paraffin as model oil phases and SiO<sub>2</sub> NPs as stabilizers. Static light scattering measurements showed that the emulsions exhibited polydispersity, while photographic monitoring confirmed that their physical stability was affected by the concentrations of oleic acid and nanoparticles: concentrations of up to 20.0 wt% and 1.0 wt%, respectively, produced emulsions that remained stable for 7 to 15 days. This study identifies the behavior and challenges associated with novel pathways for the valorization of sugarcane bagasse ash. The stabilization of Pickering emulsions using the obtained SiO<sub>2</sub> NPs highlights their potential in pharmaceutical, cosmetic, and food applications
Tissue Mechanics, Microbiome, and Inflammation Modulate Post-injury Rehabilitation in the Upper Airway
No full textThe full text of this item is not available at this time because the author has placed this item under an embargo until August 26, 2030.Upper airway injury from nerve denervation, inhalation injury, or traumatic/prolonged intubation can lead to long-term complications in laryngeal function, affecting voice, swallowing, and breathing outcomes. This dissertation investigates how changes in airway biomechanics, inflammatory response, and the local microbiome contribute to airway injury and healing. Emphasis is placed on characterizing how these biological systems interact across different forms of upper airway injury.
Using swine models that replicate recurrent laryngeal nerve injury, inhalation burn injury, traumatic intubation injury, we characterized injury-specific changes across multiple areas. Biomechanical properties were quantitatively assessed in the denervation model to evaluate vocal fold atrophy and recovery. Inflammatory, microbial, and biomechanical outcomes were assessed in intubation and inhalational burn models using immunoassays, immunohistochemistry, 16S rRNA sequencing, and indentation-based mechanical testing. We also evaluated the therapeutic potential of drug eluting endotracheal tubes designed to modulate local inflammation, reduce fibrotic remodeling, and preserve mucosal integrity.
Across models, airway injury was associated with mechanical stiffening, epithelial disruption, immune dysregulation, and microbial imbalance. Localized drug delivery via endotracheal tubes impacted these outcomes to varying degrees, with composite coatings demonstrating the greatest potential to reduce fibrosis and promote reparative immune phenotypes. This work offers an integrative framework for understanding the multifactorial nature of airway injury and recovery. The findings provide a foundation for future strategies that target mechanical, immunological, and microbial pathways for improving patient outcomes.Biomedical Engineerin
Optimizing Cold Food Supply Chains for Enhanced Food Availability Under Climate Variability
Get PDFProduce supply chains play a critical role in ensuring fruits and vegetables reach consumers efficiently, affordably, and at optimal freshness. In recent decades, hub-and-spoke network models have emerged as valuable tools for optimizing sustainable cold food supply chains. Traditional optimization efforts typically focus on removing inefficiencies, minimizing lead times, refining inventory management, strengthening supplier relationships, and leveraging technological advancements for better visibility and control. However, the majority of models rely on deterministic approaches that overlook the inherent uncertainties of crop yields, which are further intensified by climate variability. Rising atmospheric CO<sub>2</sub> concentrations, along with shifting temperature patterns and extreme weather events, have a substantial effect on crop productivity and availability. Such uncertainties can prompt distributors to seek alternative sources, increasing costs due to supply chain reconfiguration. This research introduces a stochastic hub-and-spoke network optimization model specifically designed to minimize transportation expenses by determining optimal distribution routes that explicitly account for climate variability effects on crop yields. A use case involving a cold food supply chain (CFSC) was carried out using several weather scenarios based on climate models and real soil data for California. Strawberries were selected as a representative crop, given California&rsquo;s leading role in strawberry production. Simulation results show that scenarios characterized by increased rainfall during growing seasons result in increased yields, allowing distributors to reduce transportation costs by sourcing from nearby farms. Conversely, scenarios with reduced rainfall and lower yields require sourcing from more distant locations, thereby increasing transportation costs. Nonetheless, supply chain configurations may vary depending on the choice of climate models or weather prediction sources, highlighting the importance of regularly updating scenario inputs to ensure robust planning. This tool aids decision-making by planning climate-resilient supply chains, enhancing preparedness and responsiveness to future climate-related disruptions.Mechanical Engineerin
Identification and Safety Evaluation of High-Risk Pedestrian Midblock Crossings in Three Major Texas Cities
Get PDFPedestrian safety at midblock crossings presents ongoing challenges in rapidly growing Texas cities such as Dallas, Houston, and San Antonio. This study focuses on midblock pedestrian crashes, using filtered CRIS data from 2003 to 2023 to identify high-risk locations through spatial analysis. These hotspots were further assessed through field surveys that documented pedestrian and driver behavior at selected sites.
Existing crosswalk locations were extracted using Python-based methods and matched to crash locations to evaluate the presence and timing of safety treatments. The analysis focused specifically on active midblock countermeasures, including devices such as Rectangular Rapid Flashing Beacons (RRFBs) and Pedestrian Hybrid Beacons (PHBs), to assess their relationship to crash frequency over time. Additionally, the National Walkability Index (NWI) and Social Vulnerability Index (SVI) were used to examine how walkability and vulnerability intersect with midblock crash risk.
Findings reveal gaps in treatment coverage and spatial disparities in pedestrian crash risk. The results support data-driven recommendations to guide agencies in prioritizing active safety improvements at high-risk midblock locations.Civil and Environmental Engineerin
UTSA Postdoc Appreciation Week Research Symposium Booklet
Get PDFBooklet contains schedule of events and abstracts for the poster presentations
A Systematic Review of the Recent Empirical Literature on Math and Science Teacher Recruitment and Retention
Get PDFThe shortage of math and science teachers is a pressing issue in the United States (US) and globally. This review closely follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and synthesizes findings from 43 peer-reviewed empirical studies published between 2005 and 2024 on the recruitment and retention of math and science teachers, offering a new perspective for understanding and mitigating math and science teacher shortages. This review revealed (a) the qualifications and characteristics of math and science teachers who enter and remain in the teaching profession; (b) that financial incentives, experiential learning, mentorship, and professional development are commonly used strategies and mechanisms to recruit and retain math and science teachers; and (c) that psychological, sociocultural, and working conditions are factors that influence math and science teachers&rsquo; decisions to enter and remain in the teaching field. While this review primarily focuses on the US context, it offers valuable insights for researchers, practitioners, policymakers, and other key stakeholders worldwide by identifying strategies, mechanisms, and factors that shape teacher recruitment and retention in math and science. This review also discusses gaps in the literature, directions for future research, and implications for research, policy, and practice that emerge from the empirical evidence.Educational Leadership and Policy Studie
Entrepreneurial Orientation in Social Entrepreneurship: A Systematic Literature Review and Research Agenda
No full textThis study aims to conduct a systematic literature review on entrepreneurial orientation (EO) in social entrepreneurship to clarify theoretical boundaries, integrate diverse findings, and identify research gaps. The &ldquo;Theory&ndash;Context&ndash;Characteristics&ndash;Methodology&rdquo; (TCCM) framework is adopted to analyze 81 articles on EO in social entrepreneurship. The review reveals that the field remains fragmented due to diverse theoretical and empirical contributions. The study highlights the need for future research to adapt theoretical perspectives to understand EO&rsquo;s unique and hybrid aspects in social entrepreneurship, expand empirical research into under-represented geographical areas, conduct more longitudinal and qualitative studies to track changes in EO over time, and explore new variables that can further our understanding of EO in social entrepreneurship. The novelty of this study lies in the application of the TCCM framework to systematically analyze the literature on EO in social entrepreneurship. This framework facilitates the organization and evaluation of theoretical underpinnings, methodologies, contexts, and variables to identify relevant research gaps and future directions on the topic.Mechanical Engineerin
Mexican Labor Ouroboros: A Survey of Latino Racialization in the Early Twentieth Century
Get PDFMy research project researches unfilled gaps left behind by historians such as Gail Bederman, Julian Lim, William D. Carrigan and Clive Webb to create a new narrative to explain the development of Latino racialization in the Southwest United States during the late nineteenth century and early twentieth century before the Great Depression. I suggest that Gail Bederman?s arguments about the development of masculinity continued beyond the conclusion of her book, finding new roots in differentiating Latinos from Anglo populations to manufacture consent for Latino domination in Latin America and the United States. This ideal continued to adapt from state enforced domination into a new means of federal control in the twentieth century as the traits which were associated with Latinos under this belief began to become associated with quarantines and disease along the border, which turned Latinos from a passive race fit for domination to a threat to border security. This fear combined with developing ideas surrounding eugenics and inherent racial differences to enshrine these ideals of masculinity into scientific theory, which found advisors in the United States Congress who used these theories to debate political decisions. I also argue that both Texas and California developed their racializing narratives differently during this period, and that their differences suggest that the southwest was not a singular region with a single viewpoint, but one which varied depending on the social conditions and demands of each state.Histor
Paper Botany: A Closer Examination of Botanical Illustrations from the Trujillo del Peru
No full textThis thesis examines the botanical illustrations from facsimiles of volumes three, four, and five of the <i>Trujillo del Peru</i>, compiled by Spanish bishop Baltasar Jaime Martínez Compañón from 1782 to 1785. They are examined from an art historical and ethnobotanical perspective to expand on the significance of the volumes' contents, particularly on matters of cultural erasure and huacas (an object, place, or other subject which represents manifestation of life force). To accomplish this, this research contextualizes these illustrations in the extensive history and cultural context of the Spanish Royal Botanical Expeditions and post-conquest Peru. This includes inconsistent enforcement of the Extirpation visitas and the iconoclasm of Andean cultural artefacts. Documentary artworks similar to the <i>Trujillo del Peru</i>, such as Guamán Poma's El primer nueva corónica and Lequanda and Thiebaut's Quadro de Historia Natural, Civil y Geográfica del Reyno del Perú form a small genre which the <i>Trujillo del Peru</i> can be inserted. The <i>Trujillo del Peru</i>'s watercolors are also compared with the concurrent botanical surveys of Ruiz-Pavón (1778-1788) and Mutis (1783-1808). I argue that the botanical volumes are historically and culturally significant as they demonstrate a profound Indigenous Andean knowledge of the natural world and, as such, an epistemological and philosophical departure from the base principles of scientific collections.Art and Art Histor