UTSA Runner Research Press (Univ. of Texas at San Antonio)
Not a member yet
6846 research outputs found
Sort by
Interrupting Racial Bias: Action Research on Racial Literacy Professional Development with Secondary Literacy Teachers
No full textThis qualitative action research study explored how the implementation of racial literacy training influenced teachers’ discussions about race in their classrooms. The study examined how racial literacy training prepared teachers to address race-related topics and investigated their perceptions before and after undergoing such training. Through the use of positionality professional development and dyad conversations, this research aimed to understand shifts in teachers’ preparedness to engage in meaningful discussions on race.
Through dyad discourse, this study’s findings revealed that while teachers were aware of surface-level racial issues in education, they often lacked the strategies to address deeper systemic inequities. Many educators initially reported discomfort in facilitating race-related conversations, often due to fear of saying the wrong thing, lack of resources, or insufficient professional training. However, after participating in racial literacy training, teachers demonstrated increased confidence, a deeper understanding of structural racism, and a greater willingness to integrate race-conscious discussions into their curriculum.
The study reinforced the necessity of structured, ongoing professional development rather than one-time bias training. To move beyond passive awareness, teachers needed to engage in continuous self-reflection, practical training, and active efforts to address racial biases in educational spaces. Schools would benefit from institutionalizing long-term commitments to racial literacy education, providing teachers with concrete strategies for facilitating critical conversations. By fostering an environment that prioritized racial literacy, educators could create more inclusive and equitable classrooms, ultimately preparing teachers to engage thoughtfully with race-related issues in society.Bicultural-Bilingual Studie
Educational Assortative Mating and Health Outcomes among Chinese Couples
No full textEducational assortative mating and the differences in educational attainment between couples are likely determinants of their health outcomes. This analysis uses the China Household Finance Survey data from 2019 and an ordered logistic model to explore how educational assortative mating is related to health outcomes among Chinese couples, and how these associations may vary by rural versus urban residence and by birth cohort. Our results show that individuals with spouses of higher educational attainment generally report better health, with the effect being stronger in urban areas and particularly for men. Gender differences are significant, as men benefit more from larger educational gaps across both urban and rural settings, while women gain more in urban areas when their husbands have much higher education levels. Additionally, the health advantages of educational disparities are more pronounced for those born before 1980, especially in rural areas, while younger cohorts see diminished benefits.Applied Demograph
PHOTOPHYSICAL STUDIES OF GOLD(I) NHC ACETYLIDE COMPLEXES, POLYMERS, FLUORESCENT CHEMOSENSORS, AND RADICAL IONS
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, 2027.This dissertation explores the design, synthesis, and photophysical characterization of luminescent molecules, complexes, and polymers with the potential application in optoelectronic devices, chemical sensing, and photocatalysts. Three independent studies were conducted to investigate different classes of chromophores, including phosphorescent gold(I) N-heterocyclic carbene (NHC) acetylide complexes and polymers for organic light-emitting diodes (OLEDs), aggregation-induced emission (AIE)-based chemosensor for pyrophosphate (PPi) detection, and thiophene-based radical ions for excited state dynamics exploration. The first study delved into the synthesis and characterization of gold(I) NHC-acetylide complexes (ImAuPA and BimAuPA) and their polystyrene-based polymer derivatives (AuPS-10, AuPS-15, and AuPS-25). All the complexes and polymers showed deep blue phosphorescent emissions with moderate solid-state quantum yields and extended decay lifetimes, highlighting their potential in next-generation OLEDs. The second study involved the development of fluorescent chemosensor TPE-NH3, a derivative of tetraphenylethylene (TPE), for the selective detection of PPi anion. With inherent AIE characteristics, TPE-NH3 displayed significant fluorescence enhancement due to aggregation upon interacting with PPi. Principal component analysis (PCA) complemented this study with the analytical determination of unknown concentrations of PPi, providing good accuracy and precision with respectable error margins (0.06%−8.96%). The third study investigated the excited-state dynamics of thiophene-based radical cations and anions using ultrafast transient absorption spectroscopy and theoretical calculations. The findings revealed distinct radical ion absorption features and the influence of molecular structure on excited-state lifetimes, providing valuable insights into their potential application in photocatalysis. Overall, this dissertation contributes to the broader field of photophysical research, paving the way for new material innovations in energy and sensing technologies.Chemistr
Trading the Tractor for a Spade: A Psychometric Approach to Cancer-Related Cognitive Decline Assessment
No full textThis study evaluated the ability of response time modeling methods to capture environmentally-driven changes in cognition. The cognitive domains of attention, executive control, and working memory were assessed across the final three weeks of the semester using the Attention Network Test, the Open-Source Anticipated Response Inhibition task, and the Dual N-Back task. The attention data was fit with a shrinking spotlight model, the executive control data was fit with an ex-Gaussian Stop-Signal model, and the working memory data was assessed with Systems Factorial Technology. Academic stress was measured across the three timepoints with salivary cortisol and self-report measures. This approach to measurement was analyzed in terms of model fitting accuracy, longitudinal changes, and stress mediation.
The shrinking spotlight model accurately represented data, capturing 14 of the 15 observations in a 66% highest density interval. Alternatively, the ex-Gaussian Stop-Signal model did not meet the 66% highest density interval requirement, likely due to a shortage of error trials. The Systems Factorial Technology is nonparametric, so the working memory data did not require model fit assessments.
In Bayesian hierarchical regression models, each domain was assessed for changes over time. The domains of attention and executive control both decreased over time, while the domain of working memory increased over time. In all scenarios, this indicates that cognition improved. Further Bayesian hierarchical model analysis illustrated that stress mediated the changes in attention and working memory, but not in executive control. This study elucidated the sensitivity and accuracy of a modeling approach to cognitive assessment.Psycholog
Quantum Edge Detection and Convolution Using Paired Transform-Based Image Representation
No full textClassical edge detection algorithms often struggle to process large, high-resolution image datasets efficiently. Quantum image processing offers a promising alternative, but current implementations face significant challenges, such as time-consuming data acquisition, complex device requirements, and limited real-time processing capabilities. This work presents a novel paired transform-based quantum representation for efficient image processing. This representation enables the parallelization of convolution operations, simplifies gradient calculations, and facilitates the processing of one-dimensional and two-dimensional signals. We demonstrate that our approach achieves improved processing speed compared to classical methods while maintaining comparable accuracy. The successful implementation of real-world images highlights the potential of this research for large-scale quantum image processing, architecture-specific optimizations, and applications beyond edge detection.Electrical and Computer Engineerin
Los Tejanos: A Plaza in Texas in the 1930's, An Exploration of Culture through Art (4th-6th Grades)
No full textBased on Texas Essential Knowledge & Skills, Grades Four through SixCarmen Lomas Garza’s “A Plaza in Texas in the 1930's” offers a glimpse into the past and the details of a unique culture. This resource guide provides students with a visual way to connect with a previous era. Students will use critical thinking skills to analyze and make personal connections to “A Plaza in Texas in the 1930’s”. The contents of this guide are based on Art and English Language Arts TEKS for grades 4 through 6, but some activities may be modified for lower grades
Source and Destination Memory for Emotional Event Discussions in Children with Autism Spectrum Disorder
No full textThis study examined source memory (remembering a memory’s origins) and destination memory (remembering who you disclosed information to) in 27 children (4- to -7-years-old; M = 5.48, SD = 1.09), with and without ASD. All participants individually engaged in a novel conversational event with two puppets, “Katie†and “John†which involved each puppet eliciting five emotion stories from each child for 10 stories total (e.g., “Tell me one time you felt [emotion]†) to use as “to-be-remembered stimuli†for destination memory. Each puppet also shared five anecdotes about themselves for the same emotions to use for source memory. Additional participants will be included, as data collection is ongoing. Preliminary findings reveal that overall, children with ASD provided significantly fewer accurate responses compared to neurotypical peers regarding source and destination memory accuracy about emotional events. Findings emphasize these memory differences may center around children with ASD endorsing hearing events they never heard and endorsing disclosing events they never discussed.Psycholog
Radioactive Gamma Signature Pattern Recognition with Hopfield Neural Network and Quantum Computer Algorithms
No full textQuantum computer algorithms represent an emerging technology that applies quantum mechanics theory to the foundations of computer science. Over the past decade, Quantum computer algorithms have evolved to a point where complex classical problems can be addressed by applying quantum technologies.
Grover’s algorithm stands out as one of the most practical applications in quantum computing, enabling the expansion of Quantum computer to merge with AI algorithms to solve complex classical problems. The detection and identification of gamma-ray radiation from synthetic radioactive isotopes pose a significant concern for social health and national security. Handheld NaI(Tl) detectors are frequently employed for the in-situ identification of such materials, primarily due to their portability and cost-effectiveness, albeit with low-to-medium resolution. The search and identification of radioactive materials in intricate environments present a substantial challenge, largely attributed to the continuous interaction of gamma-ray photons with background radiation. Several factors, such as the low resolution of the detector and the distance from the isotope, contribute to the distortion of the spectrum. To increase precision in detector readings, the data is analyzed by an expert spectroscopist, a process that is often time-consuming and susceptible to human error. The consumption of data is another factor to consider when automated systems are analyzed in real-time. The evolution of AI systems has been facilitated by the collection of large datasets from modern technologies, enhancing their accuracy and information access capabilities. However, the increased data volume, and the complex architecture of AI networks necessitate al-
ternative storage paradigms to complement existing data center infrastructures. Advancement of Quantum Algorithms in the last decade has offered a solution to these issues, by providing an automated and accurate system, that provide an expansion on memory space infrastructures.
In this study, we present a novel approach that precedes and enhance our previous research on Hop-field Artificial Neural Networks for gamma ray radiation detection. Our novel method combinesa popular Quantum algorithm call Grover’s algorithm in conjunction with Hopfield neural net-work to compress the size of the circuits and obtain a more efficient method to process gamma spectra that correspond to high radioactive materials. The QHNN is trained with sample of 137Cs, 241AM,239PU,235U,192IR and 60Co these samples correspond to gamma spectra with well-resolved spectral lines of each isotope of interest. During the test, 20 real-time distorted test samples are entered into the test memory. During the training cycle, the memory can be compressed from two 1x1024 (equivalent to 2048 neurons at the classical level) to 4 qubits per training cycle and during the testing cycle we use ten one dimensional vectors to compare the presence of 137Cs and 60Co and this constitute a total of 10240 individual data set that are compress in only ten qubits. The rest of the isotopes are testing batches two isotopes per cycle where 241AM and 192Ir are test on the same cycle,238PU and 235U and another cycle. five one dimensional classic vectors per cycle with a total of 5120 individual datasets are utilized to test for presence of the corresponding isotopes to this translate of only to 5 qubits in the quantum memory per cycleElectrical and Computer Engineerin
MATERIALS CHARACTERIZATION FOR ZONE-CONTROLLED DEGRADATION OF BONE TISSUE SCAFFOLDS AND PRODUCTION FACTORS APPERTAINING THERETO
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, 2028.Despite decades of medical advancement in orthopedic reconstructive medicine, unbridgeable “critical sized defects” remain an obstacle in the treatment of traumatic bone injuries. A novel approach to treating these injuries with osteogenic scaffolds composed of multiple layers with alternating mechanical properties has been proposed stimulate bone growth over larger gaps.
This study developed suitable materials for this device. 3-D printed scaffolds with varying ratios of hydroxyapatite and β-tricalcium phosphate, and varying ratios of mineral phase to binder, in sintered and unsintered states, were tested for weight, density/porosity, elastic modulus, and fluid permeability, over 28 days of aging in phosphate buffered saline at pH 7.4 and 6.0, at 37°C. Weight and elastic modulus were tested weekly; permeability and porosity were tested at the end.
Results indicated statistically significant differences in stiffness between sintered hydroxyapatite and β-tricalcium phosphate scaffolds, but failed to conclusively prove differences between the binder fractions, and showed no appreciable degradation in either weight or stiffness over time. Permeability was within acceptable margins for bioactive scaffolds. Unexpectedly, the expected ratio of stiffnesses between materials was reversed; which was attributed to differences in the sintering characteristics of the initial powders.
Unsintered scaffolds showed immediate degradation via hydration of the binder component, and were not structurally stable. The materials developed indicate that production of a multilayer scaffold with varying stiffnesses is possible.Electrical and Computer Engineerin
Anger-Related Mass Shootings During a Pandemic Year 2020
No full textThe purpose of this study was to expand the literature on mass shootings by analyzing anger prevalence, anger elicitors, and anger expressions related to mass shootings occurring in the year 2020. Mass shooting reports and data were gathered from relevant online resources, e.g., public databases and news articles. Cases (N = 114) meeting the operational definition of mass shooting were first coded for presence or absence of anger. Cases (N = 38) involving anger were then coded by two raters for type of anger elicitor and type of anger expression. Anger was clearly present in a majority of cases (69%), a large majority of the shooters being male (97%). The most common category of anger elicitor (44%) was physical assault (group 7), followed by Group 1 (Insult, Affront, and Rudeness) and Group 4 (Abandonment and Rejection). For anger
expression, results were generally consistent with previous research; most cases involved anger reflection (73%), externalized anger (84%), acting in retaliation (94%), both verbal and physical expression of anger (63%), uncontrolled anger (65%), and punitive anger (100%). Finally, veteran status accounted for only 0.8% of all mass shootings in 2020. Overall, the present findings confirm the prevalence of anger in mass shootings but also suggest that in the pandemic year of 2020, the main anger elicitors and anger expressions were slightly different from what had been previously reported. Findings raise implications for the treatment of anger in those who perpetrate or are at risk of perpetrating mass shootings.Psycholog