UTSA Runner Research Press (Univ. of Texas at San Antonio)
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Modeling and Experimental Evaluation of 1-3 Stacked Piezoelectric Transducers for Energy Harvesting
No full textPiezoelectric energy harvesting in roadways can power distributed sensors and electronics by capturing underutilized mechanical energy from traffic. In this research, 1-3 stacked piezocomposites were developed and evaluated to determine optimal designs for multiple applications. The design of these transducers aimed at operating in a multitude of scenarios, under compressive loads (1–10 kN) at low-frequency (10 Hz) applications, intended to simulate vehicular forces. Power comparison was utilized between numerous transducers to determine the most efficient configuration for electromechanical energy conversion. Design guidelines were based on mechanical integrity, output power, active piezoelectric volume percentage, aspect ratio, and geometric factors. The forces applied in this study were reliant on the average vehicle weight. An intermediate PZT volume fraction and moderate pillar aspect ratios were found to yield the highest power output, with the stacked 1-3 composite significantly outperforming a monolithic PZT of a similar size.Electrical and Computer Engineerin
Activism and Change
No full textGrade Band/Level: Middle School/Grades 6-8The Tejano experience includes working to create a more just society through struggles for educational rights, worker's rights, and political inclusion. While there have been gains, the quest for equal protection of the law and the ability to participate equally as Americans is ongoing. This series of activities can be broken into several classes or used individually as desired
Exploring Group Dynamics Within Anime Communities
No full textResearch on anime communities has accumulated in recent years, with many studies emphasizing processes related to social cohesion and identification. To this point, other group dynamics have received little attention in the literature. Building on previous work, this thesis uses in-depth interview data collected from in-person and online anime communities to explore a broader range of group dynamics, including those related to power, status, and solidarity. I conducted and analyzed twenty-seven in-depth interviews with members of a university anime club and a Twitter/X anime community. Anime communities were found to promote inclusion by fostering socially integrative rituals that contribute to feelings of emotional energy and solidarity, but also promote exclusion through the cultivation of competitiveness, the formation of cliques, the promotion of elitism, and the exercise of social control over perspectives and behaviors defined as deviant within the context of the groups. Group dynamics were also found to vary by modality, as power and status dynamics not found within in-person communities were found within online anime communities. The implications of these findings and promising directions for future research are discussed.Sociolog
Holding Out for a Hero: Examining the Impact of Psychological Capital Development on the Mental Health, Burnout, and Work Engagement of Doctoral Students
No full textDoctoral students are at high risk for mental health problems, including depression, anxiety, and burnout, among others. Extant research has focused primarily on the prevalence and treatment of mental illness in doctoral students, but few studies have employed a positive approach to doctoral student mental health that focuses on prevention and promoting optimal human functioning, rather than on deficits and disorder. Counselor educators are uniquely positioned to address this problem, as a positive, strengths-based approach to mental health is a cornerstone of counselor identity. Interventions to develop psychological capital—comprising hope, self-efficacy, resilience, and optimism—represent a promising avenue for not only equipping doctoral students to whether challenges, but also reducing the impact of program-related challenges in the first place. The purpose of the present study was to examine the impact of a psychological capital development intervention on doctoral students’ mental health, burnout, and work engagement. Using a quasi-experimental design, I compared levels of mental health, burnout, and work engagement between doctoral students who participated in a brief psychological capital development workshop either in-person or virtually and those who did not receive the intervention. Results provide insight into how positive psychological approaches and interventions can be applied to doctoral student well-being, as well as how counseling professionals may integrate insights from counseling, positive psychology, and positive organizational behavior to promote wellness both within and outside of counselor education doctoral programs.Counselin
Casa Viva Derramadero
No full textDerramadero faces a growing demand for housing that accommodates families, students, and workers, yet traditional construction methods struggle to provide affordable, high-quality living spaces. The lack of adaptable and sustainable housing solutions exacerbates economic and social challenges, making it essential to explore innovative approaches. This project proposes modular housing and robotic technology as a scalable solution to address these pressing issues while balancing affordability, efficiency, and sustainability. By integrating flexible design principles, the project allows for diverse unit configurations that adapt to different user needs, ensuring that the housing remains practical and inclusive. Climate-responsive materials enhance energy efficiency, reducing long-term costs while improving residents' comfort. Additionally, incorporating culturally relevant aesthetics helps maintain the identity of the community, fostering a stronger sense of belonging. Through collaboration with Alianza México, this initiative aims to create a replicable housing model that can be implemented in other regions facing similar challenges. Robotic construction methods streamline building processes, reducing costs and labor demands while improving precision and quality. This technological integration ensures that sustainable, affordable housing can be produced at scale without compromising design integrity. Ultimately, this project goes beyond solving Derramadero’s housing shortage—it establishes a new paradigm for accessible, resilient, and socially conscious urban development. By leveraging modern technology and thoughtful design, it offers a pathway to long-term economic and social stability for the community.Architectur
Who Defines "Capable"? Understanding the Lived Experience of Neurodiversity in Engineering
No full textThrough a eight-week ethnographic study within the RESPETO (Rhetorical Engineering Education to Support Proactive Equity Teaching and Outcomes) Project at the University of Texas at San Antonio (UTSA), a participant-observer approach and the Pláticas method (Guajardo and Guajardo, 2013) was used to explore how the intersections of identity and disability, particularly hidden disabilities and learning differences, influence the educational and professional trajectories of 14 undergraduate engineering students. Drawing from critical race theory and raciolinguistics, this project addresses the historical marginalization of underrepresented students in engineering, highlighting the need to move beyond surface-level representation to understand their complex lived experiences. This ethnographic study examines how students, specifically female students and those with disabilities, perceive exclusion, and differential treatment, navigate challenges, and employ strategies to overcome barriers within engineering education in Hispanic-Serving Institutions (HSIs). To do that, the research questions are: How do the intersections of race, ethnicity, gender, class, and disability influence the educational and professional trajectories of students in engineering? and What strategies do students with disabilities use to navigate the challenges and barriers they face?Culture, Literacy, and Languag
SlantNet: A Lightweight Neural Network for Thermal Fault Classification in Solar PV Systems
No full textThe rapid growth of solar photovoltaic (PV) installations worldwide has increased the need for the effective monitoring and maintenance of these vital renewable energy assets. PV systems are crucial in reducing greenhouse gas emissions and diversifying electricity generation. However, they often experience faults and damage during manufacturing or operation, significantly impacting their performance, while thermal infrared imaging provides a promising non-invasive method for detecting common defects such as hotspots, cracks, and bypass diode failures, current deep learning approaches for fault classification generally rely on computationally intensive architectures or closed-source solutions, constraining their practical use in real-time situations involving low-resolution thermal data. To tackle these challenges, we introduce SlantNet, a lightweight neural network crafted to classify thermal PV defects efficiently and accurately. At its core, SlantNet incorporates an innovative Slant Convolution (SC) layer that utilizes slant transformation to enhance directional feature extraction and capture subtle thermal gradient variations essential for fault detection. We complement this architectural advancement with a thermal-specific image enhancement augmentation strategy that employs adaptive contrast adjustments to bolster model robustness under the noisy and class-imbalanced conditions typically encountered in field applications. Extensive experimental validation on a comprehensive solar panel defect detection benchmark dataset showcases SlantNet’s exceptional performance. Our method achieves a 95.1% classification accuracy while reducing computational overhead by approximately 60% compared to leading models.Electrical and Computer Engineerin
The Impact of the Urban Heat Island and Future Climate on Urban Building Energy Use in a Midwestern U.S. Neighborhood
No full textTypical Meteorological Year (TMY) datasets, widely used in building energy modeling, overlook Urban Heat Island (UHI) effects and future climate trends by relying on long-term data from rural stations such as airports. This study addresses this limitation by integrating Urban Weather Generator (UWG) simulations with CCWorldWeatherGen projections to produce microclimate-adjusted and future weather scenarios. These datasets were then incorporated into an Urban Building Energy Modeling (UBEM) framework using Urban Modeling Interface (UMI) to evaluate energy performance across a low-income residential neighborhood in Des Moines, Iowa. Results show that UHI intensity will rise from an annual average of 0.55 °C under current conditions to 0.60 °C by 2050 and 0.63 °C by 2080, with peak intensities in summer. The UHI elevates cooling Energy Use Intensity (EUI) by 7% today, with projections indicating a sharp increase—91% by 2050 and 154% by 2080. The UHI will further amplify cooling demand by 2.3% and 6.2% in 2050 and 2080, respectively. Conversely, heating EUI will decline by 20.0% by 2050 and 40.1% by 2080, with the UHI slightly reducing heating demand. Insulation mitigates cooling loads but becomes less effective for heating demand over time. These findings highlight the need for climate-adaptive policies, building retrofits, and UHI mitigation to manage future cooling demand.Architecture and Plannin
Archaeological Report, No. 513
No full textThe University of Texas at San Antonio (UTSA) Center for Archaeological Research (CAR) was contacted by the City of San Antonio (COSA), Public Works Department for archaeological monitoring for the HemisFair Internal Streets Phase II project. This project involved upgrades to various streets and utilities within the HemisFair Park between East Nueva Street and the Tower of the Americas. Two areas were deemed to be archaeologically sensitive by the COSA Office of Historic Preservation (OHP) and required monitoring of all subsurface activities. As public land owned by the City of San Antonio, a political
subdivision of the State of Texas, the project fell under COSA’s Unified Development Code (UDC) (Article VI Sec. 35-630 to 35-634) as well as the Texas Antiquities Code, and the archaeological work was performed under Texas Antiquities Permit No. 30741. David Yelacic served as the Principal Investigator until his departure from the CAR in August 2023 when he was replaced by Cynthia Munoz. Peggy Wall served as the Project Archaeologist.
Monitoring began August 30, 2022 in the two areas deemed to be archaeologically sensitive, an area of 0.08 hectares (0.2 acres), and was completed on January 10, 2023. CAR archaeologists monitored approximately 160 m of excavations for duct bank, gas, storm drain, internet line, and irrigation. This area was part of a mixed residential and business area before the acquisition of the land by the city for the site of the World’s Fair in 1968. Five features were documented, one site (41BX1300) was revisited and updated, and one new site (41BX2623) was recorded. Two of the features (Features 1 and 6) are associated with site 41BX1300, the former residence and outbuildings on 316 South Street. The three other features (Features 2, 4, and 5) are associated with 41BX2623, former residences at 403 and 409 Matagorda Street. Due to the impact of modern construction at HemisFair, CAR recommends that the portions of sites 41BX1300 and 41BX2623 (Features 1, 2, 4, 5, and 6) encountered within the monitoring areas do not warrant eligibility for listing in the National Register of Historic Places (NRHP) or as a State Antiquities Landmark (SAL). CAR further recommends that due to limited exposure of the sites during monitoring, the area should be assessed for impacts to the sites before any future excavation activities. Avoidance is recommended, if possible.
Collected artifacts and associated project documentation are curated at the CAR in accordance with Texas Historical Commission (THC) guidelines under accession number 2906.City of San AntonioCenter for Archaeological Researc
Optimization and Crowdsourcing of Ratings Based Reinforcement Learning
Get PDFRatings-based Reinforcement Learning (RbRL) is a recent advancement in artificial intelligence that enables a reward function to learn directly from human generated ratings. This is different from other reinforcement learning from human feedback (RLHF) algorithms like preference-based and ranking-based learning. Despite its simple form, RbRL involves numerous hyperparameters and is sensitive to a variety of design and training factors. This thesis conducts a comprehensive investigation into the influence of different hyperparameters and architectures on RbRLs performance using synthetically generated labels. Beyond optimization, this work also explores the feasibility of crowdsourcing within the RbRL framework by incorporating real human ratings, aggregated through majority voting and mean-based methods.Computer Scienc