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Sunbelt Sanctuary: Central American Immigration, Culture, and Ethnicity in 1980s Houston
No full text“Sunbelt Sanctuary: Central American Immigration, Culture, and Ethnicity in 1980s Houston” is a historical study that centers the settlement and adaptation of U.S. Central Americans in one of the largest urban areas during the latter twentieth century. Tracing this history begins with an analysis of the Sanctuary Movement as it played out locally in the city of Houston. Attuned to the activism on part of Salvadoran migrants and refugees who called Houston home during this era, “Sunbelt Sanctuary” amplifies their centrality to the development and sustainment of the Sanctuary Movement in order to reassess the Sanctuary Movement through the voices and experiences of Central Americans themselves. Additionally, this study reconceptualizes the notion of sanctuary to move beyond its connection as an act associated with the Sanctuary Movement. Central Americans who settled in Houston during the 1980s and 1990s partook in various sanctuary building practices that went beyond the realm of activism. They also established restaurants with Salvadoran foodways, introducing new cuisines to Houston. Central Americans in Houston also engaged in faith practices, and their commitment to religion, transformed religious congregations into diverse Latina/o/x religious bodies. Highlighting how Central Americans made sense of Houston through the avenues of activism, faith, and food leads “Sunbelt Sanctuary” to argue that these different methods of sanctuary-building are a form of Central American placemaking and community formation in U.S. Latina/o/x history
Formation and Evolution of Valdivia Bank, Walvis Ridge, South Atlantic Ocean from Geophysical Data and International Ocean Discovery Program Expedition 391 Drilling Results
No full textValdivia Bank is an oceanic plateau in the South Atlantic, part of the Walvis Ridge hotspot track, that was formed at the Mid-Atlantic Ridge by plume-ridge volcanism during the Late Cretaceous. Oceanic plateaus are shallow rises on the ocean floor that are emplaced by thick accumulations of lava. Their history provides insights into paleo-oceanography, the nature of plume volcanism, and regional plate tectonics. Despite this importance, Valdivia Bank has until recently lacked detailed geophysical investigation and coring, obscuring the formation history and evolution of this plateau. Geochemical and paleomagnetic studies suggest that Valdivia Bank is complex, revealing a potential microplate and ridge reorganization in the Late Cretaceous, and late-stage volcanism in the Eocene. In 2019, geophysical surveys of Valdivia Bank were carried out on expedition TN-373 and TN-374 aboard the R/V Thomas G. Thompson. In 2021, the plateau was scored by IODP Expedition 391. In my research, I produce a detailed bathymetry map of Valdivia Bank and interpret the morphology and seafloor geologic processes on the plateau. Then, I utilize IODP Expedition 391 coring results to develop an age model of Valdivia Bank sediments and apply principles of seismic stratigraphy to multichannel seismic data to understand the sedimentation history of the plateau and the nature and timing of late-stage volcanism. Finally, I perform a structural assessment of Valdivia Bank to uncover the faulting and rifting history as observed in seismic and seafloor datasets to understand deformation of an oceanic plateau. The results suggest that Valdivia Bank experienced a multi-phased evolution in which the plateau was rifted and faulted in the Late Cretaceous due to ridge jumps. Microplate kinematics reactivated faults and rotated magnetic lineation to the east of the edifice in the Paleocene. In the Eocene,thermal rejuvenation uplifted the edifice as a short-lived island and emplaced volcanoes along rift faults, promoting coral growth atop shallow pinnacles. As the plateau subsided at a new thermal age, sediment was shed off the shallow areas through debris flows, slides, gullies, and channels. Ocean bottom current intensification in the Cenozoic developed moats and contourite deposits adjacent to the platforms
Applications of Continuous Wavelet Transform in Hydraulic Fracturing and Reservoir Management
No full textThis dissertation explores the application of Continuous Wavelet Transform (CWT) in fracture diagnostics and reservoir management, offering an in-depth analysis of various methods and their effectiveness. It addresses key aspects of hydraulic fracturing diagnostics, including fracture closure identification, dynamic fracture event detection, microseismic event prediction, water hammer modeling, and inter-well connectivity for optimizing waterflooding operations. In fracture closure analysis, the study reviews established methods like the Nolte, tangent, and compliance methods, introducing an innovative approach that integrates these techniques with fluid flow equations and mathematical models. A novel CWT-based method is proposed for detecting fracture closure pressure, where pressure fall-off signals are decomposed to enable precise event identification. This approach is validated through simulation and field data, minimizing reliance on reservoir geomechanical parameters and supported by physical measurements such as strain gauges. The application of CWT extends to dynamic fracture event detection, where normalized scalograms effectively predict microseismic events associated with hydraulic fractures. Integrated with machine learning, this method enhances hydraulic fracturing modelling and improves hydraulic fracturing operations. Additionally, CWT is applied to water hammer modeling, treating water hammers as damped harmonic oscillators to analyze post-fracture treatment signals. This approach automates the induced fracture complexity evaluation by correlating damping ratios with fracture intensity log. In reservoir management, Cross Wavelet Transform Coherence (CrWTC) is used to map inter-well connectivity (IWC) between injectors and producers, optimizing waterflooding operations. CrWTC provides a detailed analysis of injection and production rate data, surpassing traditional statistical methods. The technique is validated through simulations and field datasets, improving the reliability of IWC assessments and contributing to enhanced oil recovery (EOR) strategies. Overall, the dissertation validates CWT's effectiveness in fracture diagnostics and reservoir management, proposing innovative methods that can be integrated with machine learning for real-time decision-making in hydraulic fracturing and Enhanced Oil Recovery operations
Keepers of Black Boy Joy: Exploring the Educational Leaders, Programs, and Systems That Support the Achievement of Black Males Who Stutter
No full textAbstract
Background: Although about 75% of the United States public school population comprises students of color, 15% comprises Black students, and less than nine percent comprises Black males (National Center for Education Statistics, 2020). However, Black males are overrepresented in negative education categories which include a disproportionate recommendation for placement in special education services, and under-identified for gifted and talented programs (Noguera, 2008; Reeves, et al., 2020; Schott Foundation for Public Education, 2015). Purpose: Keepers of Black Boy Joy seeks to explore the shift away from deficit-laden literature and ideologies that continue to label Black males as damaged, at-risk, or less capable of academic success than other racial groups (Downey & Pribesh, 2004; Johnson & Larwin, 2020; Toldson, 2016). This research will explore the lived experiences of Black male stutterers and engage in the conversation around how educational leaders can best support a segment of the Black male population not often featured in research studies - Black males who thrive academically while also being perceived as having a handicap because of their stutter. By exploring the challenges and opportunities of navigating academic and social settings, this research ultimately identifies strategies that may help enhance the K-12 experiences of Black males who stutter. Method: Given the gaps in research on Black male stutterers who are also high academic achievers, it is essential to understand how Black males employ their social capital and stage-setting strategies to support achievement. The study's primary aim is to identify the lived K-12 experiences of Black males who stutter and to examine how educational leaders, systems, and structures can support the academic success of this population. This study will use a qualitative case study approach to examine both research subjects - Black male stutterers and educational leaders, programs, and systems. For RQ1 and RQ2, the researcher will collect and analyze data through one-on-one, semi-structured interviews with five Black males who stutter, and five K-12 educational leaders. Interviews will be recorded and transcribed verbatim. Transcription data will be coded and thematically analyzed. Member checking will be used to ensure the interviews' accuracy and validate the data collected. Results:
This study was centered on the belief that Black males exhibit strengths that should be recognized and can be celebrated. The research explored the participants' academic and social experiences and provided a depth of understanding of the factors that impact their educational journey as students or leaders. Findings revealed two key themes: 1) Black male trauma is exacerbated by stuttering; 2) The absence of direction and vision within the educational system for Black males who stutter hinders supportive learning environments. Conclusion: Each unique interview revealed varied supports within and beyond the school system in place for Black male stutterers. Whether Black males or educational leaders, both are bound by the common thread of advocacy, and resources. To address the unique and specific needs of Black male stutterers, school systems and educational leaders must consider structural components to their support systems: 1) student-centered practices, 2) continual professional learning, 3) inclusive classroom environments, and 4) holistic approaches
Rejected and Reluctant to Retry: An Experimental Study Examining Professional Rejection and Its Impact on Affect and Willingness to Perform
No full textRejection is ubiquitous, and its effect has been extensively examined within the social psychology literature. Various forms of rejection exist, yet few studies have investigated the more nuanced form of rejection that focuses on the negation of deliverables within the context of the professional environment (e.g., workplaces, universities). My study aims to uncover the effect of professional rejection (i.e., rejection of people’s deliverables or productions) on affect and willingness to perform by using the findings from an experimental design that mitigated the involvement of the more social forms of rejection. My results revealed that the professional rejection event resulted in lower levels of positive affect and higher levels of negative affect. A mediation and moderated mediation analysis showed that the effect of professional rejection on willingness to perform was mediated via positive affect and that this mediation effect depended on the level to which a person identified with the goal of the experimental task (i.e., identity centrality). Overall, my study advances the rejection literature by examining a work-relevant form of rejection that has been generally unexamined
From the Foreland and Retroarc Thrust Belts to the Mantle Transition Zone: First Multi-Scale Retrodeformable Transect of the Active 90 mm/yr Taiwan Arc-Continent Collision
No full textThis dissertation presents integrated multi-scale retrodeformable transects of the Taiwan arc-continent collision. Chapter 1 presents reprocessed marine seismic reflection profiles of the retroarc thrust belt near Chimei Canyon offshore eastern Taiwan, which is one of the largest submarine canyons around Taiwan and results from the 100 Ma of pelagic sedimentation at abyssal depths prior to the onset of Eurasian subduction and arc volcanism at ~18-14 Ma. This onset is marked in the Huatung Basin by seismic facies that thicken arcward, including mass-transport deposits, in contrast with underlying 1-2 km thick pelagic facies. The contact between oceanic crust and the pelagic sequence provides a zone of detachment that is the locus of deep massive laccolithic intrusions at ~1 Ma imaged in our reprocessed seismic reflection profiles. The ~2-3 km thick roof stratigraphy has been flexed upward by 2-3.5 km laccolithic inflation. Chapter 3 presents progress towards a multi-scale retrodeformable transect across the entire orogen from the foreland and retroarc thrust belts to the mantle transition zone. Multiscale tomographies define two active east-dipping Eurasian and Luzon forearc subduction systems that detach from their upper crusts and form thin-skin foreland and retroarc thrust belts above fundamental detachments. A new retrodeformable cross-section that extends from the imbricated foreland to the metamorphic core defines the post 1 Ma structure of western Taiwan, which shows two detachment levels, imbricated fault-propagation folds and agrees with tomographic and resistivity images. The upper detachment is the Eurasian subduction interface, which is the roof thrust of a low velocity channel defining a mid-crustal duplex under Taiwan. The lower detachment defined by tremor seismicity and tomography is the floor thrust of the channel, which is currently active and probably results in uplift of the Taiwan mountain belt after 1 Ma
Invariant and Transformer-Based Learning for Reducing Biases in Medical AI
No full textDeep learning has revolutionized medical image analysis, demonstrating exceptional capabilities in the interpretation of complex medical images, including X-rays, MRI scans, and CT scans. These advancements have enabled earlier and more accurate diagnoses of diseases like cancer, fractures, and neurological disorders. However, challenges such as selection biases, confounding variables, and poor generalization across diverse datasets limit the reliability of these models in healthcare applications. This dissertation addresses these challenges by developing novel approaches to enhance model robustness in medical image analysis. Neural networks often struggle to effectively process unordered sets of elements, as their architectures are typically designed to work with structured data. To address this limitation, we propose a dynamic set-operator using Transformer architecture to aggregate prognostic features from nephropathology images, ensuring permutation invariance and improved generalization. Furthermore, we investigate invariant learning algorithms to mitigate biases in medical image classification, focusing on overcoming the limitations of traditional Empirical Risk Minimization (ERM). Our experiments demonstrate that invariant learning, combined with environment discovery methods, can enhance the robustness of models against spurious correlations and confounding variables. Additionally, we explore the potential of large language models (LLMs) in assisting primary care physicians with real-time diagnostic support, examining their effectiveness and biases across different demographic groups. The findings underscore the potential benefits along with the limitations for the safe deployment of AI in healthcare. In conclusion, this research contributes to the development of deep learning models that can generalize effectively across different medical domains while minimizing biases. By leveraging advanced algorithms, invariant learning techniques, and large pre-trained models, we aim to pave the way for more reliable and equitable AI applications in healthcare
Remote Sensing Analysis of Beach-Dune Evolution and Identification of Areas at Risk on Central Texas Barrier Islands
No full textTwo major problems the Texas Coast faces are shoreline retreat and the erosion of coastal sand dunes. These dunes are not only a habitat for endangered species, but they are an important barrier to protect inland infrastructure from storm surges. With advancements in drone technology, drone surveys are now becoming more common for data acquisition in geosciences. These new high-resolution drone sensors, coupled with geospatial analysis can be used to study shoreline retreat and dune volume reduction to predict future trends and enact mitigation techniques. From May 2023 to July 2024 LiDAR data was collected via drone at three sites on the Central Texas coast: San Jose, Mustang, and North Padre Island. Geospatial analysis techniques were used to quantify the impact of causes of dune volume reduction. The factors considered were NDVI estimating vegetation density, impervious surfaces as classified from the Sentinel-2 model, foredune dimensions, beach width, and storms. For this time, Hurricane Beryl caused the most volume change at the Mustang site, and Tropical Storm Harold is suspected to have caused the most volume change at North Padre site. Random forest modeling showed vegetation based on NDVI results as the most influential variables of those considered. Impervious surfaces classified using Sentinel-2 imagery at 10-meter resolution were not an important variable influencing volume change. It also indicated that more variables such as the volume brought in by dune restoration attempts at the Mustang site, should be considered in modeling sediment volume change. This study and those like it can help identify what restoration techniques best suit which high risk areas
Identifying Patterns of Special Education Teacher Turnover and Their Relationships With Measures of Principal Experience
No full textBackground: Teacher turnover takes various forms, including changes in role, location, or sector, while some teachers leave the profession altogether. Teacher attrition feeds teacher shortages, which are especially grave in the area of special education. Special education teacher attrition is not only costly for schools due to the expenses of recruitment and training but also has negative consequences for students and their families. The causes of special education teacher turnover are many, but research has identified principals as playing a key role. What remains unknown are the timing and frequency of the various types of turnover that special education teachers exhibit, and whether those patterns of turnover are associated with principal characteristics Purpose: This longitudinal quantitative study seeks to measure special education teacher turnover in West River Public Schools (WRPS, a pseudonym), a large public school district in Texas. By determining whether, when, and to where WRPS special education teachers turn over, this study identifies unique patterns of attrition. Further, it uses inferential analyses to examine the relationship between special education teacher retention and two measures of principal experience. Method: The study centered on 779 academic year-specific observations of all 210 WRPS special education teachers that were new to the profession or the district between the 2012-2013 and 2016-2017 academic years. Through data visualization, (specifically, alluvial diagramming) I demonstrate the proportional flow of teachers into and out of five categories of turnover. The categories include transfers, moves to general education, role changes, and system exits. Additionally, correlational analyses measure the direction and strength of the relationship between the number of years that teachers remain at their original placement and two measures of principal experience. Conclusion: WRSP special education teacher turnover is very high, marked by incredibly short tenures and an overwhelming number of system exits. The low variability in teacher retention may be a causal factor for the lack of any discernible linear relationship with principal experience
The Mentor Effect on Females Aspiring to the Superintendency
No full textBackground: Giving candidates equal opportunity despite gender to obtain the superintendency role in education is important. For female applicants, this opportunity can be challenging based on the potential biases posed in the selection process for the superintendent search. In the year 2019, the data from the National Center for Education Statistics shows that 76% of females in public education are teachers and only 22% hold superintendent positions. Based on the School Superintendents Association’s (AASA) 2020 Decennial Report there has only been a 3% increase in female superintendents over the past 10 years. Additionally, in the state of Texas, only 26% of the superintendents are female (Meisner, 2023). Also, out of 153 superintendent certificates issued in 2020-2021, 106 are earned by females. Even though more females are becoming superintendent certified, the numbers are still disproportional in the superintendency. Purpose: This qualitative study aimed to examine current or retired Texas female superintendents to gain insights and perspectives on how mentorship assisted them in their journey to earning a superintendent position. RQ1: What is the importance of the role of mentors to females in the superintendency? RQ2: Based on female superintendents’ experiences, what are the best strategies for a mentorship program? Method: Texas female superintendents, whether current, former, or retired, are studied to explore the barriers they faced in advancing in educational leadership. The research analyzed the effectiveness of both formal and informal mentors in promoting females to the superintendency. The study included current, former, and retired female superintendents from Texas Region IV. One-on-one virtual cognitive interviews and questionnaires were conducted to gather data. The data was audio-recorded, transcribed, and coded to identify key trends and themes. Results: The four major topics that emerged were female’s career pathways to the superintendency; challenges/barriers to the superintendency; mentoring of aspiring superintendents; and support systems. The participants reported that obtaining the superintendency was influenced by their mentorship experiences. Most of the mentoring connections that were encountered were informal. External and internal obstacles, career paths, networking, mentoring, lack of support systems, and gender biases are some of the aspects that affect females’ accomplishment to the superintendency. Conclusion: Universities, regional education service centers, and programs that prepare students for certification as superintendents should take note of this study's findings regarding the value of networking and mentorship for females. It is paramount for programs to have intentionality behind creating informal relationships through networking opportunities. When making natural, informal connections, aspiring superintendents should choose a mentor with the qualities that assist their career development. The incorporation of supports including mentoring and networking opportunities along with an emphasis on gender balance in the superintendency could result in more females ascending to and succeeding in the position