UTSA Runner Research Press (Univ. of Texas at San Antonio)
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Trends and Disparities in "Deaths of Despair" in Texas, 2000 to 2020
No full textThis dissertation examines the rise of “deaths of despair” (DoD)—mortality from drug overdose, suicide, and alcohol-related causes—in Texas from 2000 to 2020. Through a three paper structure, it explores demographic patterns, premature mortality, and structural drivers across diverse counties. The first paper documents a 153% rise in DoD mortality, with drug overdoses driving much of the increase. The burden is highest among non-Hispanic White and
Black males, particularly those aged 25–34 and 55–64. The crisis has expanded beyond rural areas, widening disparities across the state. The second paper analyzes Years of Potential Life Lost (YPLL) in 2020, revealing nearly 372,000 years lost to DoD. Young adults and men bear the greatest burden. These findings highlight DoD’s impact on both life expectancy and economic productivity. The third paper examines how county-level conditions measured in 2000 predict long-term mortality. Income inequality, unemployment, and rurality are significantly associated with higher DoD rates. A nonlinear relationship with educational attainment suggests more complex structural influences. Rather than healthcare access alone, broader patterns of economic insecurity and geographic isolation emerge as key contributors. Together, the papers underscore the urgent need for equity-focused, place-based policies to address the structural roots of rising mortality across Texas communities.Health, Community and Polic
How Sex Education and Sexual Health Awareness Influence Rape Myth Acceptance: The Mediating Role of Sexist Beliefs and Moderating Role of Gender
No full textSex education (“sex ed”) shapes understanding of relationships and gender norms, but its long-term effects on attitudes toward sexual violence remain understudied. While comprehensive sex ed (CSE) teaches consent, abstinence-only programs (AOSE) often reinforce traditional gender roles (Santelli et al., 2017). This study examined how sex ed and broader sexual health awareness relate to rape myth acceptance (RMA) through hostile sexism (HS), benevolent sexism (BS), and social dominance orientation (SDO).
In Study 1, CSE showed no overall association with RMA, but was associated with higher RMA among women, (β = .21, p = .032). Men exhibited greater RMA, (β = -.73, p < .001), and HS mediated the relationship for women, (β = .08, 95% CI [.01, .17]). Study 2 found greater sexual health awareness associated with lower HS, (β = -.26, p = .005), BS, (β = -.19, p = .009), and SDO, (β = -.32, p = .004), mediating its negative association with RMA. Gender was again associated with RMA, (β = -.43, p < .001), but did not moderate effects.
These findings imply that formal sex ed may not sufficiently reduce RMA unless it confronts systemic inequities. Sexual health awareness, extending beyond classrooms, appears more effective in reducing sexist beliefs and RMA. Practical steps include revising CSE to explicitly critique gender hierarchies and power dynamics (Haberland, 2015). Limitations, such as a regional sample, highlight the need for longitudinal research. Ultimately, dismantling rape culture requires education targeting both health behaviors and the ideologies underlying sexual violence.Psycholog
Bayesian Analysis and Parameter Estimation for the Generalized Exponential Distribution
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 May 15, 2030.The two-parameter Generalized Exponential (GE) distribution is widely applied across various domains, including reliability and survival analysis, environmental studies, and industrial quality control. It is also commonly used as an alternative to the gamma and Weibull distributions. While existing Bayesian analyses of the GE distribution often rely on informative or weakly informative priors, there is a notable gap in the literature regarding the use of objective priors, which are more appropriate when prior knowledge is limited.
In the first project, we address this gap by exploring objective priors, including the independence Jeffreys prior and probability matching priors. We conduct a theoretical examination of the propriety of the posterior distributions under a range of vague priors and validate the conditions necessary for ensuring that the posterior distribution remains proper. To achieve computational efficiency, we propose a generalized ratio-of-uniforms method for generating independent posterior samples. This approach eliminates the need for burn-in periods or starting values, offering a more efficient alternative to traditional Markov chain Monte Carlo (MCMC) methods.
The second project tackles the challenge of parameter estimation for the GE distribution in the presence of interval-censored data. The Expectation-Maximization (EM) algorithm, while conceptually appealing, faces difficulties due to the lack of closed-form expressions for the E-step. To overcome this, we apply the Quantile EM (QEM) algorithm, which avoids direct analytical integration, thereby simplifying the implementation process. Our findings demonstrate that the QEM algorithm exhibits superior convergence properties compared to the Monte Carlo EM (MCEM) method. Simulation results further illustrate that the QEM algorithm yields more accurate and reliable parameter estimates, particularly when faced with complex censoring schemes.
In the third project, we study Bayesian inference of the GE distribution based on the reference priors with partial information (RPPI) and investigate the propriety of the resulting posterior distributions. Based on censored samples, we implement sampling algorithms to generate posterior samples of the unknown parameters under RPPI priors to make inferences. Simulation studies and a real-data application are provided for illustrative purposes.
Overall, our research significantly advances the field of Bayesian analysis and parameter estimation for the GE distribution by introducing non-informative priors, developing efficient computational algorithms, and addressing parameter estimation challenges under various censoring conditions. This work not only fills a critical gap in the literature, but also provides robust methodologies that can be applied to a broad range of real-world problems.Management Science and Statistic
Saving 'Happy' Foundation Histories: The Preservation of Gay History in San Antonio and Contemporary Dilemmas in Queer Archives
No full textIn the United States, the gay liberation movement of the 1970s into the 1980s served as a watershed for the emergence of gay community archives. In 1988, Gene Elder, a local artist and activist, founded the Happy Foundation Archives and dedicated it to San Antonio’s queer history. While LGBTQ history is often overlooked in Southern and Southwestern states like Texas, the Happy Foundation provides vital insights into San Antonio’s history of resistance and empowerment. However, the collection highlights significant gaps, notably the underrepresentation of lesbian and transgender people of color. This absence raises critical questions about the racial and gender-based discrimination within queer history and archives.
This study uses materials from the collection to illustrate the importance and vibrancy of San Antonio’s queer history but also uses theoretical frameworks from archival studies and queer theory to approach the Happy Foundation as the subject of research. This analysis is framed within the “archival turn” in humanities situating the Happy Foundation in the broader context of the queer community archives in the U.S. examining how absences are produced, the shift towards institutionalization, and practical dilemmas in archives. The current socio-political climate, including recent threats to LGBTQ+ history, add to the critical nature of the preservation of queer history and the representation of people of color. The Happy Foundation is an example of how the visibility of queer people of color is obscured from history but also stands as testament that the preservation of local histories is powerful against widespread erasure.Histor
Breastfeeding and Intersectionality in the Deep South: Race, Class, Gender and Community Context in Coastal Mississippi
No full textIntersectionality, especially with a race&ndash;class&ndash;gender focus, has been used to study many facets of women&rsquo;s experiences. However, this framework has been underutilized in the study of breastfeeding prevalence. Our study is the first of its kind to use intersectionality to illuminate breastfeeding network prevalence disparities with empirical data. We use insights from this theory to examine breastfeeding patterns reported by women living on the Mississippi Gulf Coast. Mississippi makes an excellent site for such an examination, given its history of racial discrimination, entrenched poverty, and strikingly low rates of breastfeeding, particularly for African American women. We identify a series of factors that influence racial disparities in lactation network prevalence, that is, breastfeeding among friends and family of the women we surveyed. Our investigation relies on survey data drawn from a random sample of adult women who are representative of the Mississippi Gulf Coast population supplemented by a non-random oversample of African American women in this predominantly rural tri-county area. Results from the first wave of the CDC-funded 2019 Mississippi REACH Social Climate Survey reveal that Black-White differentials in breastfeeding network prevalence are significantly reduced for African American women who report (1) higher income levels and (2) more robust community support for breastfeeding. We conclude that breastfeeding is subject to two key structural factors: economic standing and community context. An appreciation of these intersecting influences on breastfeeding and long-term efforts to alter them could bring about greater breastfeeding parity among African American and White women in Mississippi and perhaps elsewhere. We end by identifying the practical implications of our findings and promising directions for future research.Sociology and Demograph
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