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Andean Laboratories: Agrarian Reform, Agricultural Innovation, and Armed Conflict in Peru, 1950-2005
No full textThis study examines the unique, local green revolution that took place in Peru as scientists in the second half of the twentieth century sought to adapt transnational agricultural technology to the high-altitude environments of the Andes. Initially, U.S. institutions such as the Rockefeller Foundation sponsored agricultural experimentation on the Peruvian coast, but they failed to address how new technology would reach growing Indigenous and mestizo communities in the Andes. By the 1960s, community protest over a lack of land and farming technology, as well as mass migration to coastal cities, helped prompt the Peruvian military under General Juan Velasco Alvarado (1968-1975) to intervene in national politics and pursue both agrarian reform and agricultural innovation. Although the Velasco administration fell short of its goals, its reforms ushered in a new era in which innovators from government offices, universities, and NGOs began to work more directly with Andean communities than ever before. As these innovators worked to apply technology such as hybrid seeds, pest control, pedigree livestock, and megadams to Andean landscapes, they often realized that community knowledge and perspectives were crucial to the success of any project. In the late 1980s, the nation’s internal armed conflict interrupted rural development projects, yet many communities and scientists persisted. In scholarship, the history of violence overshadows the history of science, yet a look beyond the edges of the armed conflict reveals a robust history of innovation efforts that, despite shortcomings, helped raise agricultural production in some communities
INVESTIGATION OF THE HABITAT AND CLIMATE DRIVERS OF COLLARED PIKA DISTRIBUTION AND VULNERABILITY
No full textAs environmental conditions continue to change at a rapid rate, understanding habitat requirements and climate vulnerabilities is critical for species conservation. The collared pika (Ochotona collaris), an alpine specialist found in Alaska and northern Canada, faces potential threats from climate change, yet its habitat requirements and responses to environmental change remain poorly understood. In this study, we use existing spatial data, combined with observations from new survey efforts, to 1) identify regional variation in collared pika habitat preferences and climate response, and 2) assess the climate change vulnerability of collared pikas and predict changes in distribution linked to future climate scenarios. To identify habitat preferences, we used a model selection approach, comparing climate and habitat characteristics at known collared pika occurrences to those at surrounding areas. Our analysis indicated that collared pika occurrence is primarily driven by the presence of talus, proximity to the talus edge (with pikas preferring areas closer to vegetation), and talus patch size (with pikas preferring small patches). The rangewide model indicated that collared pika occurrence was positively correlated with maximum winter temperature and negatively correlated with maximum summer temperature, annual precipitation, and solar radiation. While preferences for talus characteristics remained consistent rangewide, the effect of climate variables including precipitation and maximum summer temperature varied regionally. To assess climate vulnerability, we combined trait-based and correlative modeling approaches, with the results suggesting the species has high vulnerability to climate change. Our trait-based assessment indicated that collared pikas are moderately susceptible to climate change due to high exposure to changing conditions, high sensitivity to climatic variables, and low adaptive capacity. To predict future changes in distribution, we employed a presence-background species distribution modeling technique to identify the current climatic niche and projected this model into future climate scenarios. Our models suggest a loss of ~55-70% of climatically suitable areas by 2080. Together, these results inform conservation status and strategies for this species and highlight the importance of conducting regional and species-specific analyses
OBSERVATIONS AND SIMULATIONS OF THE INTERACTIONS BETWEEN COASTAL BREEZES AND THE ATMOSPHERIC BOUNDARY LAYER IN THE COASTAL HOUSTON ENVIRONMENT
No full textThe atmospheric boundary layer (ABL) in the coastal environment is constantly evolving due to gradients in temperature, moisture, and surface roughness. The ABL influences regional air quality and weather forecasts through low-level stability and thermodynamic fluxes. Even though the ABL is intrinsic to daily life, it is historically under-sampled and poorly simulated in numerical models, because it evolves on a high spatiotemporal scale. The sea breeze (SB) is a contributor to the rapid coastal ABL evolution and develops because of the land-sea thermal gradient and advects the marine airmass onshore during the day. As a result, the SB can contribute to convection initiation and alter air quality in coastal areas. The TRacking Aerosol Convection interactions ExpeRiment (TRACER) field campaign gathered observations in the coastal-urban environment of Houston, Texas. With the goal of understanding the convective cloud lifecycle, a dense network of ABL measurements was gathered to understand how coastal breezes influence cloud evolution. Ground-based remote sensors and small uncrewed aerial systems (UAS) were deployed throughout the campaign and gathered a high temporal and vertically resolved dataset throughout numerous SB events, some of which triggered convection initiation. Vertical profiles of temperature, humidity, and winds were collected by the OU CopterSonde UAS from June to September in the coastal region of Houston, Texas. These profiles offer 5 m vertical resolution, on average, every 30 min through diurnal transitions, SB events, and nearby deep convection. During the campaign, CopterSonde observations were gathered through 17 SB events, 6 of which led to convection initiation. The UAS data can resolve the thermodynamic evolution and interactions between the SB and the pre-existing convective boundary layer. Using the UAS observations, SB impacts and interactions with the ABL are investigated. The range of SB thermodynamic impacts is found to be broad and depends on the time of SB passage and influence from additional water bodies, like Galveston Bay. The SB is also found to convectively destabilize the ABL by advecting an airmass with enhanced equivalent potential temperature. The rate at which equivalent potential temperature increases in response to the SB provides insight into how conducive the environment is to convection initiation. The resolution of UAS observations also provides a unique opportunity to evaluate numerical weather prediction on temporal scales consistent with the PBL evolution during coastal breeze passages, and beyond the surface layer. A case study is evaluated using observations during a bay breeze to sea breeze transition to understand how model parameterizations influence the forecast. The Warn-on-Forecast System (WoFS) is a convection-allowing ensemble designed to predict high-impact weather by combining rapidly updating data assimilation cycles with varying PBL and radiation parameterizations. While the model is not geared toward PBL studies, it provides a benchmark to evaluate commonly used parameterizations for NWP to offer insight into best-performing combinations and potential improvements. The biases of state variables calculated from the UAS observations show distinct differences from biases calculated using surface meteorological station observations, suggesting that traditional ABL evaluation practices may underestimate errors in the mixed layer. Additionally, the SB is variably represented in terms of the depth, arrival time, and intensity with different parameterization configurations. Only a subset of members simulate the preceding Galveston Bay breeze, and none do so accurately. The bay breeze is very sensitive to initial conditions, especially for members with local mixing schemes. As a result, initial cloud cover induced by the radiation scheme affects the ability to simulate a bay breeze, as well as the SB onset time. The mixing scheme for ABL parameterization lends differences in SB depth, intensity, and evolution. This variability across simulated SBs motivated analyzing how these differences impact simulated convection. Two events are analyzed to understand how simulated convection initiation differs with the ABL parameterization. Forecast performance is evaluated using storm object identification and matching with gridded reflectivity observations. One case's performance is consistent across all members, but the other is greatly dependent on the ABL parameterization. Local mixing scheme members tend to have more moisture across the region and disperse rising motion ahead of the SB front, which leads to an overestimation of storm objects inland. Nonlocal mixing members have more isolated lifting and unstable air close to the SB front that causes an underestimation of convective storms. These differences are less impactful when the environment is very unstable upon initialization. Then, all EMs result in an overestimation of convective storm objects ahead of the SB. These results suggest that the simulation of the convective boundary layer is more critical to accurately depicting convection initiation than the sea breeze characteristics
Upper Troposphere Lower Stratosphere Composition Change in Tropical Cyclones: Assessments from 17 Years of Satellite Observations
No full textTropical cyclones (TCs) are known for a variety of impacts, including threats to life and property, although their effect on the chemical composition of the upper troposphere and lower stratosphere (UTLS) remains understudied. The transport of air between the troposphere and stratosphere, known as stratosphere-troposphere exchange (STE), involves greenhouse gases such as ozone and water vapor whose impact on Earth’s radiation budget and climate is most sensitive to changes in UTLS composition. Therefore, we examine observations of STE in TCs and relate these changes to TC and environmental characteristics. We utilize 17 years of trace gas profiles from the Microwave Limb Sounder (MLS) aboard the Aura satellite in conjunction with TC track information and environmental data to relate UTLS ozone and water vapor changes to TC intensity, distance from TC center, and environmental wind shear. We find that accounting for varying tropopause heights and basin-specific background composition is important to accurate assessment of UTLS composition changes within a TC. We also find that TCs are associated with increased water vapor throughout most of the UTLS and dehydration at tropopause level, while ozone is reduced greatly in the upper troposphere. All diagnosed UTLS composition changes demonstrate significant sensitivity to distance from TC center and TC intensity. Additionally, we find that TC-induced UTLS HO changes are highly dependent on shear magnitude, where weaker shear is associated with more pronounced tropospheric hydration and tropopause dehydration
INTERESTED, BUT NOT IN SEX: ANALYSIS AND THEORY ON THE IMPORTANCE OF ROMANTIC ATTRACTION IN UNDERSTANDING THE EXPERIENCES OF ASEXUAL POPULATIONS
No full textThe research of asexuality, which refers to a feeling of no sexual attraction towards others, has rapidly expanded in recent years to reconsider the foundational elements of attraction. Within the last few years, differentiations between sexual attractions and romantic attractions have become recognized and have increasingly become a standard consideration in such research. This dissertation contributes to this understanding by constructing Chapter 2 and Chapter 3 as qualitative research articles. Each of these will draw from a qualitative dataset of 21 in-depth interviews with participants who identify on the asexual-spectrum of identities. While the sexual attraction of participants ranged from low-to-no attraction, romantic attraction was more varied. This provided for a good comparison of the lived experience of the participants based on romantic attraction. Results from this research further found several points where this differentiation between sexual and romantic attractions was highly relevant for understanding the lived experiences of asexual-spectrum individuals. Feelings of camaraderie with non-asexual peers on topics of dating and feelings of positive affect towards one’s own sexual identity each appeared to vary by romantic identity. Further, the findings of these studies provide possible answers to questions posed by previous research by giving evidence to how asexual individuals may perceive romantic relationships differently from non-asexual populations. It further examines how asexual individuals may perceive dating or marriage on both a level of personal importance, such as comparing the importance of romantic relationships against friendship relationships, and on a level of its social importance, the purpose of romantic relationships as a means to be “normal” by common social standards. Chapter 4 constructs a theoretical model, the Attraction Orientation and Contingent Intensity Model, which builds on the current understandings of the differentiations between sexual attraction and romantic attraction to further account for inconsistencies in the current usage of sexual and romantic identities. In particular, this model will examine sexual identities as potentially bifurcated descriptors, some of which refer to directionality of attractions (e.g., heterosexual, lesbian, bisexual) and some of which indicate intensities of feeling (e.g., many asexual-spectrum identities such as gray-sexual, which notes low-or-infrequent attraction but does not note directionality of attraction). This model gives an answer to a common tendency that has largely existed in asexual research, where individuals note multiple sexual identities and multiple romantic identities, and further works toward a goal of applying considerations of differentiated attraction to non-asexual populations. Overall, these chapters contribute to the growing body of academic literature on asexuality and on understanding romantic attraction as an important concept in understanding the sexual and romantic feelings of a population
TOWARDS ENHANCING RESILIENCE AND ACCURACY OF AI MODELS AND WIRELESS NETWORKS UNDER REAL-WORLD CHALLENGES
No full textThe rapid evolution of wireless networks toward ultra-dense, user-centric, and AI- and machine learning-based architectures introduces unprecedented challenges in ensuring reliable, efficient, and resilient network operation. Key obstacles towards these networks include (1) frequent occurrences of the outages and inadequacy of traditional methods to handle extensive volume especially in dense deployments and high shadowing scenarios, (2) performance degradation and subsequent adverse affect on optimization methods due to positioning errors in users and remote radio heads, and (3) the lack of resilience of the traditional machine learning based solutions against the scarcity and distribution shift of high-quality data required for effective machine learning modeling. These issues undermine the effectiveness of traditional management and modeling approaches, which are often incapable of handling the complexity, heterogeneity, and real-world uncertainties of next-generation networks. This dissertation systematically addresses these challenges through data-driven frameworks that leverage advanced artificial intelligence and domain-informed machine learning. First, we propose a robust, automated two-tier outage management solution for dense cellular networks. An enhanced XGBoost-based detection model achieves superior accuracy in scenarios with high shadowing and sparse data. At the same time, an actor-critic reinforcement learning compensation strategy ensures fair and efficient service restoration for both outage-affected and already-served users. Next, we tackle the adverse impact of positioning errors in user-centric ultra-dense networks, which can severely degrade area spectral efficiency and energy efficiency by misguiding service zone formation and user association. To mitigate this, we introduce a data-driven optimization and error compensation framework that combines residual learning, automated machine learning, and multi-objective optimization. Our results show that the data-driven optimization and error compensation approach recovers up to of performance lost due to localization errors, outperforming baseline methods. Complementary time-series forecasting techniques, including seasonal auto-regressive integrated moving average (SARIMA) and multilayer perceptron regression, further enable dynamic compensation for the degradation of key performance indicators, with SARIMA achieving the highest prediction accuracy. Addressing the pervasive challenge of data scarcity in wireless propagation modeling, we develop a domain-informed generative adversarial network framework. By integrating analytical propagation equations into the training of generative adversarial networks, the proposed method generates high-fidelity synthetic data even under extreme data limitations. Experimental evaluations demonstrate up to 50% improvement in data quality metrics and a 48% reduction in root mean square error for downstream machine learning tasks compared to conventional augmentation techniques, establishing a new benchmark for data-driven modeling in data-scarce scenarios. Finally, to enhance model robustness against distribution shifts and support resilient digital twin applications, we introduce a multistage framework combining conditional tabular generative adversarial network-based data augmentation with attention-through-segmentation training. This approach accelerates the convergence of generative adversarial networks by up to 35%, while attention-through-segmentation reduces the root mean square error by up to 67% and improves generalization across diverse and dynamic wireless environments. Collectively, the methodologies developed in this dissertation advance the state of the art in artificial intelligence-powered wireless network management and modeling. By addressing outage resilience, positioning error compensation, and robust propagation modeling under data scarcity and distribution shifts, this work lays a solid foundation for the next generation of intelligent, self-sustaining wireless networks that can meet the demands and uncertainties of future networks
Targeted Photodynamic Therapy for Endometrial Cancer Using Folic Acid Conjugated Graphene Quantum Dots-Hexagonal Boron Nitride Nanoassemblies
No full textEndometrial cancer is the most common gynecological cancer in the United States, with current treatment options frequently being limited by a lack of specificity, increased toxicity, and moderate therapeutic efficacy. Photodynamic therapy (PDT) is a minimally invasive alternative to standard of care. PDT in the management of endometrial cancer has challenges such as oxygen dependency, poor light penetration, and biodistribution of photosensitizing agents. In this study, we developed a novel folic acid conjugated graphene quantum dot-hexagonal boron nitride (FA-GQBN) nanoassembly intended for targeted endometrial cancer PDT. GQDs were synthesized using a green, bottom-up approach using rice powder and incorporated onto hBN nanosheets to further provide stability. The nanocomposites were PEGylated to limit the aggregation and functionalized with folic acid (FA) to allow for receptor-mediated targeting of folate-receptor-positive endometrial cancer cells. Confirmation of successful synthesis, conjugation, and cellular uptake was performed using FTIR, DLS, TEM, and CLSM techniques. In vitro cytotoxicity studies using XTT and LDH assays confirmed the biocompatibility of FA-PEG-GQBN nanocomposites and showed inconclusive results for testing ROS. In vivo studies established a subcutaneous HEC1A model of an endometrial tumor. There was no detectable fluorescence of our nanoassemblies, and FA did not enhance tumor localization. Despite this, FA-GQBN nanocomposites remain a promising platform for targeted photodynamic therapy in endometrial cancer
DEVELOPING CODE READING SKILLS IN ENTRY-LEVEL COMPUTER SCIENCE COURSES
No full textCode review and debugging are fundamental practices in software development, essential for ensuring code quality, consistency, and knowledge sharing. With the growing use of AI-based tools for code generation, these skills have become even more critical. While large language models (LLMs) can accelerate code writing, they also introduce new challenges related to code correctness, maintainability, and integration with existing systems. As a result, effective code review and debugging are increasingly important in both industry and education. In computer science (CS) education, these skills are equally vital for student success. In large-scale programming courses, where autograders are commonly used, students must be able to identify, locate, and fix errors independently. However, despite their importance, code review and debugging are often neglected in early programming instruction. This is largely due to the complexity and resource demands of integrating these practices into the curriculum, both for instructors and students. Without explicit instruction, students often rely on trial-and-error methods, which can lead to frustration, reduced confidence, and poor learning outcomes. This dissertation addresses this instructional gap by examining the challenges students face in learning debugging and code review at different stages of a CS program. Using qualitative methods, the study explores how students develop debugging skills in a CS program at the University of Oklahoma and how the absence of structured guidance affects their learning. The findings from this study indicate that even students with intermediate to advanced programming experience struggle with debugging when not explicitly taught in instruction, and that unguided practice can have a negative impact on their learning experience. To address these challenges, this research introduces \textit{Code Insight}, a novel instructional intervention to be implemented as an in-class activity, grounded in the principles of active learning. Designed for integration into classroom lectures, Code Insight simplifies the teaching and learning of code review and debugging practices in introductory programming courses. This intervention emphasizes code analysis over code creation and is structured to minimize grading in instructional burden. Importantly, it is intentionally designed to minimize excessive cognitive workload on novice programmers in a CS program, ensuring that the activity supports learning without introducing unnecessary complexity and additional workload on students as well as instructors. The effectiveness of \textbf{Code Insight} intervention was evaluated through anonymous student feedback collected across two semesters. The results indicate that the students felt more confident in their ability to review and debug code after participating in the activity. By identifying and addressing common difficulties in learning to debug a program, this dissertation presents a practical and scalable solution for enhancing programming instruction starting from introductory courses in a CS program. It highlights a critical gap in integrating code review and debugging practices in CS education and offers a pedagogical approach that supports the development of essential programming skills and enhances students' motivation and self-efficacy when working with complex programming tasks
Museums and Digital Archives: A Qualitative Study of Vertebrate Collections
No full textThe museums we know of today had their start from both an interest in collecting cultural items for entertainment, as well as to use as educational tools. Since then, it has morphed into a varied stewardship of researching prehistoric specimens, protecting humanity’s commonwealth, and preserving such items for future generations. In the modern age, this includes digital aspects of museology that have become increasingly necessary among institutions to properly maintain their public trust and relevancy through collaborative research, educating their audiences, and interactions with benefactors. Digitizing paleontological collections is a growing element within an institution’s stewardship of responsibility towards both their local patrons and the global community. However, there are challenges that must be addressed and resolved while integrating this aspect of preservation into a museum’s archival practices. Digitization is a relatively new integration, and thus there is no shared baseline of ethics, laws, or best practices surrounding actions or procedures that are shared across other areas in the field of museology. This qualitative study explores the current best practices of museums regarding digitization- how they utilize technology, tools and resources to enhance their digital archives, as well as evaluate the long-term strategies they currently implement. The impact of this thesis is to add evidence of how the digitization of specimens has been integrated into the field for the past few decades and to highlight its growing vitalization in the modern world of global interconnection. The survey responses are aligned through themes to better highlight what common advantages and disadvantages that museums must navigate when incorporating digitization into their daily responsibilities
FACILITATING LEARNING THROUGH TECHNOLOGY: A COMMUNICATION PERSPECTIVE ON EDUCATIONAL TECHNOLOGY INTEGRATION IN ELEMENTARY CLASSROOMS
No full textEducational technology is prevalent in today’s classrooms. The study explores currentchallenges in educational technology (ed tech) integration by looking into elementary teachers’ background and experiences with technology in the classroom. This thesis recruited six elementary teachers, grades second through fifth, from a local elementary school in the suburbs of Oklahoma City. The researcher interviewed the participants to gain their experience with ed tech, their take on support and training, and their suggestions for the future. Diffusion of Innovation framework worked with the study by determining how quickly (or slowly) the teachers adopted educational technology. The findings showed lack of support from admin, good and bad devices, training from peers and learning companies, along with suggestions and improvements for the future. This research is a communication perspective on educational technology in secondary schools. Keywords: educational technology, communication, teachers, diffusion of innovation, support, training, improvemen