UTSA Runner Research Press (Univ. of Texas at San Antonio)
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The Desire of the Moth
No full text<i>The Desire of the Moth</i> constitutes the opening quarter of a novel that will follow a young man's first experiences with love and death. These events will unfold during his freshman year of college, placing the work in the genre of the campus novel. The story as a whole will concern how its protagonist Cole Autry mistakes his fascination with his classmate Sylvia for passion, fails to comprehend the romantic love he develops for his best friend Adam, and only recognizes these grave errors when Adam, Sylvia, and two other friends die in a mysterious hiking accident. Campus novels that influenced my thesis include Donna Tartt's <i>The Secret History</i>, Tana French's <i>The Likeness</i>, Joyce Carol Oates's <i>Beasts</i>, Sally Rooney's <i>Normal People</i>, and John Williams's <i>Stoner</i>. This first quarter of a larger work relays Cole's arrival at college; his initial experiences with classmates, courses, and his Romantic Literature professor; and the forging of a friendship group he will come to call the Geneva Crew (referencing Mary Shelley's genesis for <i>Frankenstein</i> at Lake Geneva).Englis
Experiences in Delivering Online CS Teacher Professional Development
No full textThis work was originally presented as a conference paper at the 55th ACM Technical Symposium on Computer Science Education in Portland, Oregon, in March 2024. The conference paper is available at https://hdl.handle.net/20.500.12588/6426.This paper describes our team’s experience in designing and delivering the online teacher professional development (PD) program, Computer Science for San Antonio (CS4SA), aimed at empowering educators with computer science (CS) knowledge to increase Latinx participation in CS and STEM education within a large, urban predominantly Latinx school district in South Texas. This paper highlights the successes, challenges, and lessons learned while facilitating two cohorts of the CS PD through online platforms during the COVID-19 pandemic. As a result of this program, participants recognized the importance of integrating CS into their classroom and becoming advocates for the discipline at the high school level. Additionally, teachers, investigators, and other personnel learned important lessons for enhancing the program’s impact through collaboration with district administrators and refinement of the online learning experience.This material is based upon work supported by the National Science Foundation under Grant No. 1923269.Computer Scienc
Do You Really See Me: Understanding and Enhancing Educators' Recognition and Response to Middle School Students' Social and Emotional Needs
No full textThis qualitative multi-case study engaged the testimonios of three educators who openly shared their social and emotional experiences from their middle school years. The central inquiry, "What valuable insights can you offer from your middle school experiences to help other educators recognize and respond to the social and emotional needs of their students" directed their reflection on their journeys. The primary focus was to investigate how these experiences can offer help into recognizing and addressing the social and emotional concerns of other educator's students, explicitly utilizing the Ethics of Care theoretical framework as the basis for their evolution. This framework centers on building nurturing connections with teachers and staff and is a blueprint for fostering encouraging connections with students. Demonstrating care through modeling can foster mutual respect among teachers, staff, and students, as Noddings (2005) suggested.
Through data collection, open coding, theme coding, overall analysis, and interpretation, the results created a conceptual framework termed "The Chain of Social and Emotional Trauma." This framework offered another lens to visualize the pathway of emotional understanding, enabling educators to identify and address potential struggles faced by students.
The insights from testimonios shared in two off campus sessions sparked candid reflections on the educators' experiences. Common themes, including vulnerability, trauma, silent suffering, coping mechanisms, resiliency, and social and emotional resources, emerged with profound sincerity. These themes served as inspiration for constructing the conceptual framework, offering a transition into the potential struggles and challenges middle school students may be facing today. This study was meant to increase awareness among educational leaders, empowering them to strategically plan future initiatives to meet students' needs through advocacy and implementing school-based mentorship programs.Educational Leadership and Policy Studie
Thermodynamic Properties of Analog Martian Lava as a Function of Composition, Temperature and Crystal Fraction
No full textLong lava flows on Mars involve dynamic processes, including rheological changes and variations in thermal properties during cooling and crystallization. This study uses an initial composition identified by the Spirit rover at Gusev Crater as an analog for Martian lava. Measures of thermal diffusivity (D), heat capacity (CP), and viscosity (η) were obtained as functions of temperature (T) and crystal fraction (ø) for picritic basalt samples from superliquid to cooling temperatures between 1350˚C and 1000˚C. The heat capacity indicates a glass transition temperature (Tg) at 686±11˚C, with CP=1.1±0.1J/g∙K in the solid state and CP≈2.0±0.5 J/g∙K at the liquidus (~1370˚C). The configurational heat capacity relates to ø, revealing samples with 0% to 99% crystals, consisting of olivine, spinel, clinopyroxene, orthopyroxene, and plagioclase. The glass phase increases in SiO2 and Al2O3 during crystallization. Thermal diffusivity (D) varies with ø, being lowest in glass samples at D=0.37mm²/s for supercooled liquid. Thermal conductivity (k) was calculated as 1.3W/m∙K for glassy sample, increasing to 1.8W/m∙K for sample with ø=99%. Viscosity changes by two orders of magnitude, transitioning from Newtonian to shear-thinning behavior below due to crystallization. The Grätz equation states that the effusion rate depends on the cooling properties of a specific lava composition, which affect how long a flow can travel. This equation is used to evaluate uncertainties applying laboratory experiments that work to detailing thermo-rheological models and reducing these uncertainties. However, other uncertainties related to morphological measurements can be minimized by advancing technology as remote sensing, rovers, and access to in-situ samples returned to Earth.Earth and Planetary Science
Fabrication and Characterization of Quad-Component Bioinspired Hydrogels to Model Elevated Fibrin Levels in Central Nervous Tissue Scaffolds
No full textMulticomponent interpenetrating polymer network (mIPN) hydrogels are promising tissue-engineering scaffolds that could closely resemble key characteristics of native tissues. The mechanical and biochemical properties of mIPNs can be finely controlled to mimic key features of target cellular microenvironments, regulating cell-matrix interactions. In this work, we fabricated hydrogels made of collagen type I (Col I), fibrin, hyaluronic acid (HA), and poly (ethylene glycol) diacrylate (PEGDA) using a network-by-network fabrication approach. With these mIPNs, we aimed to develop a biomaterial platform that supports the in vitro culture of human astrocytes and potentially serves to assess the effects of the abnormal deposition of fibrin in cortex tissue and simulate key aspects in the progression of neuroinflammation typically found in human pathologies such as Alzheimer's disease (AD), Parkinson's disease (PD), and tissue trauma. Our resulting hydrogels closely resembled the complex modulus of AD human brain cortex tissue (~7.35 kPa), promoting cell spreading while allowing for the modulation of fibrin and hyaluronic acid levels. The individual networks and their microarchitecture were evaluated using confocal laser scanning microscopy (CLSM) and scanning electron microscopy (SEM). Human astrocytes were encapsulated in mIPNs, and negligible cytotoxicity was observed 24 h after the cell encapsulation.Neuroscience, Developmental and Regenerative Biolog
Computational Learning Models to Classify Skin Burn Injuries Using Multi-Modal Imaging
Get PDFPrompt medical intervention is crucial for minimizing risks of hypertrophic scarring and infection, thus improving patient outcomes in burn care. Burn depth is a key determinant for the best course of treatment. However, physician assessment?the current standard of care, is found to be only 60% accurate compared to more objective measures of burn assessment. Aiming to improve this accuracy, short-wave infrared (SWIR) imaging is presented as the basis of a non-invasive assessment tool for depth determination. Deep learning techniques allow analysis of complex data generated in SWIR imaging and can be developed to delineate between operable and inoperable areas in the injury site. In this study, burn areas with heterogenous depths were imaged from 27 patients using a SWIR camera and a phone camera. A blinded panel of 5 burn surgeons classified small regions on the conventional photographs as either a superficial partial, deep partial, or full thickness burn, or as normal skin. Preliminary classification techniques include a MobileNet convolutional neural network (CNN) classifier fine-tuned on a subset of surgeon-classified images of the regions of interest (ROIs), and an unsupervised k-means classifier which takes as features the texture properties derived from gray level co-occurrence matrices of these ROIs. To improve these techniques and to serve as the foundation for a patch-wise classifier, a multi-modal CNN was trained on texture, color, and SWIR features derived from both image types, which achieved an accuracy of 85.90%. Finally, contributions of each feature toward a given classification were determined through SHAP analysis.Biomedical Engineerin
Multimodal Learning for Infrastructure Mapping in Remote Sensing
Get PDFMapping the world is currently undergoing a transformation fueled by the widespread availability of high-resolution, remotely sensed imagery. However, conventional mapping methods primarily rely on simple classifiers that analyze each pixel without considering the broader spatial context. This approach results in incomplete and inaccurate maps, particularly in rural regions and developing countries. These areas often rely on community-based mapping platforms, like OpenStreetMap, which, while valuable, suffer from data inconsistencies due to their reliance on volunteers to contribute. Furthermore, while we exist in a three-dimensional world, most mapping efforts are limited to 2D representations of roads and buildings, overlooking the wealth of information available in geometry and height datasets.
This lack of contextual awareness and 3D representation presents a significant opportunity to leverage modern computer vision techniques for creating more accurate, complete, and informative maps. For example, existing road extraction methods often fail to accurately map through obscuring objects like tree cover. We explore using models to incorporate global spatial context to enhance mapping accuracy.
This research also examines the potential of integrating additional modalities and geometric information into mapping to generate more realistic and useful maps. This includes developing methods for mapping 3D geometry of rooftops and estimating building height from a single overhead image. We further provide a case study for utilizing thermal infrared imagery for mapping solar farm infrastructure, demonstrating its potential for providing insights into turning mapping predictions into a renewable energy efficiency analysis.
Finally, this research considers the challenge of utilizing the modality of text data in mapping. We explore the issue of mapping uncommon objects which lack labeled data and experiment with the viability of adapting vision-language foundation models for the remote sensing imagery domain. By exploring these techniques, this research aims to usher in a new era of global mapping, characterized by greater accuracy, detail, and a more complete representation of the Earth's surface, particularly in areas with limited or unreliable data.Electrical and Computer Engineerin
Biogeochemical Controls on Arsenic Mobility within Hyporheic Zone Sediments
Get PDFArsenic contaminated drinking water is a global concern, specifically in the Bengal basin where millions rely on arsenic contaminated groundwater for drinking purposes. Currently, the primary process believed to be responsible for the high dissolved arsenic is the microbially-mediated reductive dissolution of arsenic-bearing iron-oxides. Recent studies suggest that the interactions between oxygen-rich surface water and iron-rich groundwater in the hyporheic zone precipitates abundant iron-oxide minerals which sequester arsenic. The objective of this dissertation is to investigate the comprehensive role of hyporheic zone processes on the cycling of arsenic in sediment along the Meghna River, Bangladesh, and the Hooghly and Beas Rivers in India. The inorganic and organic chemical properties of the riverbank sediments were evaluated and the resulting biogeochemical processes influencing arsenic mobility within the hyporheic zone were determined. The findings show three distinct hyporheic zone scenarios which impact the fate of arsenic through differing biogeochemical processes. Along the Meghna River, a shallow silt layer, rich in labile organic matter, promotes arsenic mobility in the riverbank by fueling the microbially-mediated reductive dissolution of arsenic-bearing iron-oxides. Along the Hooghly River, surficial sands and minimal organic matter permits the precipitation of arsenic attenuating iron-oxides, maintaining low arsenic concentrations in the riverbank. Along the high-energy Beas River, a low residence time and oxic conditions prevents the microbial reduction of oxides, allowing for efficient transportation of As-bearing minerals to the underlying deltas. Together, this research provides a comprehensive analysis on the solid-phase properties of hyporheic zone sediments influencing the fate and transport of arsenic.Civil and Environmental Engineerin
Creating Healing Space Through Plática: Processing the Overturning of Affirmative Action
No full textAffirmative Action in Higher Education:
Within higher education, affirmation action, which stemmed from the Civil Rights Movement in the 1960s, is "the practice of considering student background characteristics such as race as a factor in deciding whether to admit an applicant" (Wood, 2023)
In June 2023, the Supreme Court banned affirmative action in higher education spaces and prohibited all colleges in the country from using race as a consideration in admissions (Jones & Zinshteyn, 2023)
"By disregarding the significance of race, these approaches risk creating a wider divide between equal opportunity and communities of color" (Maye, 2023)
[...]Educational Leadership and Policy Studie
Using Close-Range Photogrammetry to Estimate Aggregate Embedment in Chip Seals
Get PDFThe full text of this item is not available at this time because the author has placed this item under an embargo until May 16, 2025.Chip seal is a cost-effective pavement surface treatment technique commonly used for enhancing pavement longevity and structural resilience. An essential parameter for the assessment and management of construction quality in chip seal applications is the level of aggregate embedment. Current methods for assessing aggregate embedment in chip seal often rely on subjective visual analysis and imprecise binder application rates. This underscores the imperative for a more dependable, data-driven, and engineered methodology for evaluating this critical parameter. This study aims to develop a quantitative methodology for measuring aggregate embedment through the introduction of an innovative application of Close-Range Photogrammetry (CRP) to address the determination of aggregate embedment.
The study initiated the creation of 3D models of chip seal using CRP, based on two- dimensional (2D) images captured with a smartphone camera. These models facilitate the generation of aggregate distribution curves, enabling the quantification of embedment within chip seal samples and field trials. Results show that CRP is effective in detecting various levels of embedment depth. In laboratory specimens, clear variations in aggregate distribution curves validate the reliability of CRP. Finally, field demonstration revealed that CRP was able to detect between bleeding and non-bleeding areas in chip seal sites.Civil and Environmental Engineerin