UTSA Runner Research Press (Univ. of Texas at San Antonio)
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Epilepsy in a Dish: Multi-Electrode Array Analysis of ARX-Mutant vs. Healthy Brain Organoids
No full textMutations in the ARX gene are associated with epilepsy and neurodevelopmental disorders, disrupting neuronal function and connectivity. Brain organoids, three-dimensional models derived from human stem cells, provide a valuable system for studying disease mechanisms in vitro. This study examines the electrophysiological activity of ARX-mutant brain organoids compared to healthy controls using 3D multi-electrode arrays (3D MEA) and Mesh-MEA technology, which enable high-resolution, in-depth recordings of neuronal activity.
Brain organoids were derived from both healthy donors and ARX-mutant patients. Electrophysiological recordings were performed using 3D MEAs with shank electrodes, which penetrate into the organoids, and Mesh-MEA systems, which allow brain organoids to develop around the electrodes. This long-term integration enables continuous recording of the same brain organoid over extended periods, facilitating the monitoring of neuronal network evolution. By allowing stable, chronic recordings, Mesh-MEAs provide a unique opportunity to track how neuronal activity patterns change over time, offering deeper insights into network maturation and disease progression. These platforms allowed for the assessment of spontaneous activity, spike dynamics, burst patterns, and functional connectivity within the organoids.
ARX-mutant organoids exhibited hyperexcitability, abnormal burst synchronization, and disrupted network connectivity, characteristic of epilepsy-like activity. Long-term recordings with Mesh-MEA further revealed progressive changes in network activity, highlighting differences in how neuronal circuits evolve over time in mutant versus healthy organoids.
This study provides novel electrophysiological insights into ARX-related epilepsy, demonstrating the utility of 3D MEA and Mesh-MEA technologies for capturing complex neuronal dynamics. The ability to monitor organoid activity over extended periods using Mesh-MEA offers a unique perspective on the development and progression of neuronal network dysfunction. These findings support the use of brain organoids as a reproducible model for studying epilepsy and may contribute to future therapeutic strategies targeting ARX-associated disorders.Neuroscienc
The Role of Wildlife Charisma and Where it Comes From
No full textProfessionals in the wildlife conservation sphere often ask why public care and resources are not equitable to all species. Understanding how wildlife is charismatic to people is key to my work in asking the question of while this inequality exists. Included in this research is a definition of wildlife charisma, theory of how it comes to be, and an explanation of how it is possible to measure a species’ charisma. I pay special attention to species perceived as "weird" because they are species that are often on the fringes of public attention and care, and generally as a consequence less resources are devoted to their conservation. This research focuses on the northern right whale dolphin (Lissodelphis borealis) as a “weird” species that can be encountered in my fieldsite, Monterey Bay National Marine Sanctuary. This species is of my highest interest not just because of their strange looks, but for the fact that they often shoal together with Pacific white-sided dolphins (Aethalodelphis/Lagenorhynchus obliquidens), which allows for a “charismological” comparison between them while in the field. Despite shoaling together, these species are vastly different in looks, behavior, and their interactions with whale watching vessels, meaning that their charisma differs between them. Additionally, both of these highly pelagic species are less familiar than the common bottlenose (Tursiops truncatus) as a result of the influence of art, media, and other popular culture factors, hence their “weirdness.” Ultimately, my research is exploring what “dolphin” means to the public and its implications in cetacean conservation.Anthropolog
Examining the Relationship Between TELPAS and STAAR/EOC ELAR assessments for Emergent Bilingual Students with Disabilities in Texas
No full textThis study examines the relationship between TELPAS (language proficiency) and STAAR/EOC ELAR (academic content) assessments for emergent bilingual students with learning disabilities in Texas. This research investigates differences and similarities in assessment to inform educational practices and policies for linguistically diverse students with disabilities.Culture, Literacy, and Languag
A Salute to Military Flight: Educator Resource
No full textThe Institute of Texan Cultures hosts a three-part exhibit honoring the centennial of military flight in San Antonio. The exhibit offers a look at the birth of military aviation, the local military community through the years, and artistic expressions for the love of flight. The educator resource can be used in conjunction with a tour of the exhibit or as a stand-alone unit
AI-Informed Multi-Threat Decision-Support Methodology for Long-Term Bridge Asset Management
No full textThis dissertation develops a methodology and tools for a risk-based multi-threat decision-support tool for long-term bridge asset management (BAM), with a particular focus on chronic aging-induced condition deterioration and more abrupt and extreme seismic hazard impact. In Volume 1, a stochastic bridge condition deterioration and seismic damage simulation module is developed. Seismic fragility modeling and risk assessment is carried out, considering site-specific seismic hazard and the effect of seismic retrofitting actions. A life cycle cost analysis module is introduced to holistically quantify and aggregate the direct and indirect costs incurred from bridge condition deterioration, seismic damage, and intervention actions over a prolonged planning horizon. A benefit-cost analysis for various seismic retrofitting actions is also performed. Then, by integrating the above bridge deterioration and seismic damage simulation module and the life-cycle cost analysis module with the advanced AI technique, deep reinforcement learning (DRL), a methodology for generating AI-based policies for sequential maintenance decision support for a portfolio of bridges is proposed. Departing from traditional reactive condition-based decision policies, these AI-based policies can offer much more proactive and adaptive decisions to minimize the expected long-term life-cycle costs. Practical action constraints are also introduced to align with real-world engineering practices. The proposed AI-based policies are evaluated based on individual bridges as well as on a portfolio of bridges and demonstrate superior performance in reducing the life-cycle costs compared with other condition-based policies. In addition, the AI-based policies also exhibit robustness to potential human override. Moreover, an investigation into the effect of seismic retrofitting, coupled with AI-based agents, is conducted for more comprehensive life-cycle benefit-cost evaluation of seismic retrofit actions.
In Volume 2, the bridge-level AI-based maintenance decision policy previously developed in Volume 1 is further integrated into a network-level decision support framework by considering network-level budget and resource constraints. A Pareto Frontier-based ranking approach is proposed to rank the maintenance projects suggested by the bridge-level maintenance policies by holistically considering multiple decision factors. The top-ranked projects are then allocated with the funding and resources for actual implementation. A thorough comparative study is carried out by comparing the efficacy of AI or other condition-based policies at the bridge level under the proposed network-level decision framework and different budget scenarios. It is observed that the AI-based policy outperforms other traditional condition-based policies in almost all considered cases.
In conclusion, the research tools developed from this dissertation can not only offer proactive and adaptive bridge maintenance decisions at the individual bridge level, but can also optimize the budget and resource allocation at the network level by better utilizing the limited resources, preserving the overall asset conditions, and reducing the socioeconomic impact due to deteriorating bridge assets.Civil and Environmental Engineerin
Flags of Texas Settlers
No full textGrade Band/Level: High School/Grades 9-12Twenty-four flags of nations representing Texas' earliest settlement groups are outlined here. We attempt to answer some of the many questions your students may have about the flags of Texas, the flags of the world's nations, and the flags flown in front of the Institute of Texan Cultures. Where did the colors and symbols of flags originate? Which flags have been changed since the early settlers left their countries of origin and which have stayed the same? How do the flags of the world's nations differ? How are they similar? What are the reasons for these similarities
Computer Science Professional Development for Middle and High School Teachers: Insights from Three Cohorts
No full textComputer Science for San Antonio (CS4SA) was a computer science (CS) professional development program designed for in-service middle and high school teachers—educators actively teaching. CS4SA aimed to prepare teachers with essential CS knowledge and skills while expanding CS opportunities for Latinx and other underrepresented minority populations within a large, urban school district in South Texas. An Institutional Review Board approved this research.
The program engaged teacher participants through culturally responsive pedagogy, integrated professional learning communities, and project-based learning strategies. Teachers appreciated the collaborative nature of these approaches, which deepened their understanding and strengthened their professional networks. Over a pilot program and three cohorts (2020–2024), participants attended a Summer Institute, monthly workshops, and completed online modules aligned with state CS teacher certification standards.
This paper examines the program’s instructional design and shares insights from participants, including those who returned as peer mentors. It also outlines adaptations to address challenges such as COVID-19 disruptions and limited district support. Findings indicate that teacher participants valued their professional development experience and quickly applied their new skills in the classroom. Many teacher participants integrated CS into their math and science lessons. They introduced CS concepts in after-school clubs, supported by program resources that enabled projects ranging from Unity game development to robotics and Scratch programming. One teacher secured funding for additional robotics resources, while another invited a software developer to discuss app development, demonstrating the real-world applications of CS in various industries.
Despite challenges such as school closures due to declining enrollment, staffing reductions, and limited district support, educators found creative ways to engage students through robotics and coding projects. CS4SA helped build a community among participants, allowing them to exchange ideas and resources. While the program's impact on expanding computer science education within schools was more limited than anticipated, it played an essential role in supporting teachers as they integrated CS into their classrooms. These findings highlight the role of professional development in supporting teachers as they integrate CS into their schools and classrooms.Computer Scienc
A cognitive bias influences reports about conscious experience: Listening effort and the peak-end rule
No full textListening under challenging conditions is often effortful and aversive. Decision making research shows that affect at the peak and end of an experience have a disproportionate influence on memory relative to the entire experience. We tested if retrospective listening effort reports are biased by the peak-end rule. Participants (n=372) reported fatigue and mood before and after listening for intermittent tone “signals†in continuous white noise, as well as their mental workload related to the task. Decreasing the signal/noise ratio increases task difficulty. Four groups were tested, each with the same total signal/noise ratio over ~12 min. In three groups the signal/noise ratio decreased for two minutes, either at the beginning, middle, or end of the task, and a fourth group had a constant signal/noise ratio (static). We hypothesized that retrospective workload judgments would be greater for the peak vs. static group, and when the signal/noise ratio decreased at the end vs. the middle and beginning. Results supported both hypotheses: (peak>static group, p<.001, d=.81; end>middle/beginning, p<.001, d=.91). Findings suggest that reported listening effort includes a decision-making stage that is susceptible to the peak-end rule.Psycholog
The Quest to Map the Nanyang: An Analysis of Jesuit Influence on High Qing Maritime Cartography
No full textJesuit missionaries from Europe arrived in China during the Ming Dynasty (1368-1644 CE) and established a presence in the capital, which they maintained during the Qing Dynasty (1644-1911 CE). This thesis project aims to answer the research question: How did the Western cartographic methods introduced by Jesuit missionaries influence Confucian scholarship and Qing cartography of the South China Sea and Southeast Asia during the High Qing era (1683-1799)? Through archival research and critical analysis, this study examines China's scientific development, the impact of Western technology and methodologies, and the relationships between the Jesuit missionaries and Qing China's literati scholars. This project narrows its research parameters to the Nanyang region, which includes Southeast Asia and the South China Sea. The purpose is to build upon established scholarship regarding imperial China’s cartographical endeavors in the High Qing Era, a period marked by cultural interactions and territorial growth. To explore the cartographical methods of this period, this project analyses primary sources such as maps, charts, and correspondence.
Previous research on Jesuit cartography in Qing China has primarily focused on land mapping and has argued that, instead of demonstrating Western intellectual superiority and undermining Chinese thought, the interactions between Jesuit and Chinese scholars resulted in a unique evolution of ideas and creative works that reflected the transforming landscape of the 17th and 18th centuries. This project investigates how this conclusion about Sino-Jesuit collaboration applies to the Qing's projects in the Nanyang region and contrasts the types of work done in land versus sea settings, considering that the maritime world presented a very different landscape with challenges and possibilities. It concludes that collaboration regarding maritime mapmaking was minimal due primarily to China’s limited regional presence.Histor
A Novel Entropy-Based Approach for Thermal Image Segmentation Using Multilevel Thresholding
No full textImage segmentation is a fundamental challenge in computer vision, transforming complex image representations into meaningful, analyzable components. While entropy-based multilevel thresholding techniques, including Otsu, Shannon, fuzzy, Tsallis, Renyi, and Kapur approaches, have shown potential in image segmentation, they encounter significant limitations when processing thermal images, such as poor spatial resolution, low contrast, lack of color and texture information, and susceptibility to noise and background clutter. This paper introduces a novel adaptive unsupervised entropy algorithm (A-Entropy) to enhance multilevel thresholding for thermal image segmentation. Our key contributions include (i) an image-dependent thermal enhancement technique specifically designed for thermal images to improve visibility and contrast in regions of interest, (ii) a so-called A-Entropy concept for unsupervised thermal image thresholding, and (iii) a comprehensive evaluation using the Benchmarking IR Dataset for Surveillance with Aerial Intelligence (BIRDSAI). Experimental results demonstrate the superiority of our proposal compared to other state-of-the-art methods on the BIRDSAI dataset, which comprises both real and synthetic thermal images with substantial variations in scale, contrast, background clutter, and noise. Comparative analysis indicates improved segmentation accuracy and robustness compared to traditional entropy-based methods. The framework&rsquo;s versatility suggests promising applications in brain tumor detection, optical character recognition, thermal energy leakage detection, and face recognition.Electrical and Computer Engineerin