Open Research Oklahoma (Oklahoma State Univ.)
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Air traffic management: Class B airspace capacity for urban air mobility
No full textUrban Air Mobility (UAM) integration into the National Airspace System (NAS) is a critical focus for the Federal Aviation Administration (FAA). This dissertation examined the integration of UAM operations within Class B airspace. Class B airspace is highly congested and reserved for the largest airports in the US. The research assessed the impact of Unmanned Aircraft Systems (UAS) and forecasts their potential strain on existing air traffic control (ATC) capacity. Utilizing a quantitative methodology, this research analyzed current and projected air traffic data. The research highlighted how future UAS operations will saturate NAS capacity in densely populated airspace sectors. The findings revealed that UAS activity is likely to exceed current capacity thresholds in high-demand regions, underscoring the need for policy interventions, infrastructure upgrades and technological innovations to maintain safe and efficient airspace operations. The research also contributes to the FAA’s strategic goals as outlined by Congress in the FAA Reauthorization Act of 2024, by producing three key findings that can improve AAM integration
Establishing and sustaining telesurgery skills training in medical institutions: An exploratory case study
No full textThis qualitative research study explores the integration and diffusion of telesurgery skills training within medical institutions, using Rogers' Diffusion of Innovation (DOI) Theory (Rogers, 2003) as a guiding framework. As robotic surgery becomes increasingly integral in healthcare, telesurgery skills training is viewed as crucial for enhancing surgical proficiency, accessibility, and patient outcomes (Kumar et al., 2008; Rudiman et al., 2023). Data were collected through interviews with program directors representing seven institutions implementing telesurgery skills training and analyzed using Braun and Clarke’s (2006) thematic analysis, following a six-phase process to identify key themes. Findings revealed critical themes related to stakeholder engagement, financial sustainability, standardized training, educational challenges, technological infrastructure, access expansion, and legal and ethical considerations. While the participants expressed optimism about telesurgery’s potential, they also identified barriers of high costs, limited faculty expertise, and a lack of established standards. DOI Theory provided a lens to examine adoption factors ‒‒ Relative Advantage, Compatibility, Complexity, Trialability, and Observability. This study contributes to understanding how medical institutions can effectively navigate the complexities of telesurgery skills training, aligning with global trends in technology-enhanced healthcare education
Interactional dynamics in U.S. Supreme Court oral arguments: A conversation analysis of hypotheticals and analogies in Second Amendment cases
No full textThis study proposes a Conversation Analysis (CA) approach to explore the interactional features of US Supreme Court oral arguments. Specifically, the analysis examines how pragmatic devices such as hypotheticals and analogies are produced and contested in oral arguments related to the Second Amendment. Using transcribed recordings of Supreme Court oral arguments, the research focuses on interactional sequences where justices and counsel deliberate two pivotal issues: the right to bear a firearm and the type of firearms allowed for ownership. The analysis reveals how Supreme Court justices construct hypotheticals and analogies to elicit specific responses and reinforce particular ideologies while the petitioners’ and respondents’ counsel strategically work to maintain alignment with their own arguments. The findings contribute to our understanding of discourse strategies in legal argumentation and shed light on how pragmatic devices like analogies and hypotheticals influence the interpretation of constitutional rights
Influence of exercise intensity and cadence on hemodynamic characteristics after severe-intensity exercise
No full textPurpose: To test the hypothesis that the change in pulse wave velocity (PWV) from baseline to immediately after exercise would not be altered by changes in intensity or cadence.
Methods: Twelve participants performed a ramp incremental test until task failure and a 3-minute all-out test to determine critical power for each subject. Using a blind-study method, subjects performed cycling tests for all conditions. The first condition was exercise at the lower range of the severe intensity (S1) domain at a cadence of 60 RPM. We had two conditions in the upper range of the severe intensity domain (S2), one at a cadence of 60 RPM and the other at 100 RPM. Baseline and post-exercise pulse wave was measured and used to calculate pulse wave velocity.
Results: Severe intensity exercise led to a decrease in PWV from baseline to immediately after exercise at the start of the recovery phase. No significant difference was found between the severe intensities 1 and 2 at the same pedal frequency (p=0.13). No significant difference was found between the different cadences of 60 RPM vs 100 RMP (p=0.06).
Conclusion: In all conditions, the subjects achieved failure. Findings suggest that when exercises are performed to failure, the PWV immediately post-exercise is not significantly influenced by the cadence or intensity within the severe exercise domain. Further analysis needs to be done to see if over a longer period of recovery differences occur for different cadences or intensity domains
Public health responses to sexual violence
No full textThis thesis addressed public health responses to sexual violence, a pervasive public health problem with serious, far-reaching impacts on individuals and communities. Therefore, this discussion is centered around prevention strategies for sexual violence survivors, survivor-centered care, and policy development to be implemented on such evidence-based intervention programs that encourage education, awareness, and systemic change as the basis. Key topics include the role of sexual health educators, integration within healthcare systems to bring about trauma-informed care, and a determination to address disparities in support for underserved populations. The study examined effective frameworks to reduce sexual violence and improve survivor outcomes from a review of recent related literature and some case studies. This thesis places special emphasis on transformational leadership in public health. It thereby highlights innovative and collaborative efforts that must be leveled against sexual violence to create safer, more equitable communities. My research questions are “How do public health initiatives influence the accessibility and effectiveness of support services for survivors of sexual violence?” and “What are the key challenges and opportunities in implementing community-based prevention strategies for sexual violence?
Pyocin pathway mysteries: Exploring the role of two novel proteins for pyocin production in Pseudomonas aeruginosa
No full textPseudomonas aeruginosa is an opportunistic pathogen notable for antibiotic resistance and its production of bacterial antagonist molecules. Among these molecules are pyocins: intraspecies killing particles that resemble bacteriophage tails and are normally produced by P. aeruginosa in response to DNA damage. The expression of pyocins in wild-type cells is controlled by the transcriptional activator PrtN, which is normally repressed by PrtR. DNA damage, detected by RecA, triggers pyocin production through RecA-stimulated auto-cleavage of PrtR. Pyocin-producing cells then display elevated levels of pyocin gene expression, culminating in explosive cell lysis to release the phage-sized particles. We recently discovered that in cells lacking the tyrosine recombinase-encoding xerC gene, elevated pyocin production occurs. However, blocking PrtR cleavage by mutating it to an uncleavable PrtRₛ₁₆₂ₐ version completely inhibits pyocin production in ∆xerC cells but does not fully block pyocin gene expression. The traditional model suggests that expressing PrtN from an inducible promoter in a ∆xerC prtRₛ₁₆₂ₐ background would restore pyocin production. However, PrtN alone is insufficient to restore pyocin production, thus, the impediments to pyocin production in these cells remain mysterious. Transcriptomic data leads me to hypothesize that putative proteins 07970 and 07980, which directly precede the pyocin gene cluster and are highly downregulated in ∆xerC prtRₛ₁₆₂ₐ cells compared to ∆xerC cells, are important pyocin regulators. Here, I show that pyocin production is reliant on the production of both the known pyocin activator PrtN and the putative anti-terminator protein 07980, redefining what we know about the pyocin production pathway
Embedding security awareness into IOT-based smart agriculture system
No full textSmart agriculture harnesses Internet of Things (IoT) technologies to enhance food security, optimize resource utilization, and promote environmental sustainability. Operating as autonomous, data-driven ecosystems, agricultural IoT deployments face unique security challenges due to their heterogeneous, resource-constrained components, diverse communication protocols, and wide geographic distribution. External dependencies on third-party services—such as weather forecasting, pest detection, and remote diagnostics—further amplify the attack surface, while dynamic environmental factors, energy constraints, and limited technical expertise complicate effective security management. Traditional rule-based approaches lack the adaptability to address evolving threats in these complex systems.
To address these limitations, I propose a context-aware security-aware framework designed for uncertain and dynamic smart agriculture environments. My framework integrates a deep learning (DL) classifier for real-time threat prediction with explainable AI (XAI) techniques to elucidate the model’s decision process. The XAI module identifies critical environmental and operational factors contributing to detected threats. I adopt the Security Assurance Case (SAC) methodology to formally represent security requirements, their interdependencies, enforcement mechanisms, and evidence of compliance. A novel mapping mechanism links XAI-derived explanations to SAC elements, enabling automated identification of affected requirements and their functional implications.
Additionally, I introduce an Importance Factor (IF) metric to quantify the criticality of each system component. Derived from graph-based centrality measures applied to system call graphs, the IF metric highlights components with high impact on overall security posture. These IF values are incorporated into the SAC model, enriching runtime interpretation reports to prioritize mitigation efforts. While detailed mitigation strategies lie beyond the scope of this study, my framework lays the groundwork for informed decision-making.
I validate my approach using a smart irrigation testbed under realistic operational conditions. A deep neural network trained on network traffic data effectively detects distributed denial-of-service (DDoS) attacks, and the XAI-SAC integration produces actionable, context-aware reports. Experimental results demonstrate that my framework successfully embeds security awareness into smart agriculture systems, providing interpretable insights and enhancing resilience against sophisticated threats.
By delivering interpretable threat analyses and formalized assurance representations, the framework empowers stakeholders to make timely, evidence-based security decisions. Future work will explore automated mitigation orchestration, scalability enhancements, and broader deployment scenarios
Worldviews and enactivism in hinge epistemology
No full textThis master’s thesis focuses on engaging deeply with contemporary hinge epistemology. There is a serious gap in the philosophical literature concerning the concept of a worldview, even though many theorists in this field rely on something like it to make their theories whole. In chapter one, I attempt to fill this gap by offering a full analysis of the concept. This analysis culminates in an exhaustive list of the essential features and functions of a worldview. Included in this list is the relationship that holds between hinges and the rest of the features described in a worldview. Chapter one concludes by showing what effect this would have on hinge epistemologists’ theories if they were to take my arguments seriously. In chapter two, I offer a separate theory for hinge epistemology that relies heavily on Enactivism. By introducing this understanding to hinge epistemology, I show how it solves certain problems in accepted hinge theories but also maintains the functions those in the field want hinges to play
Resampling-empowered incremental learning for cost-effective data-driven diabetic retinopathy prediction
No full textDiabetic retinopathy (DR) is a serious complication of diabetes that can lead to vision impairment or even blindness if not detected and treated in the early stage. Recently, leveraging the electronic health records (EHR) data, machine learning-based DR prediction has become a promising research direction to achieve timely detection of DR. In practice, the EHR database usually increases periodically, leading to an urgent need for an approach to update the DR prediction model by incorporating the new data. However, it is costly to keep retraining the model using combined data. Therefore, this study proposes establishing an effective incremental learning (IL) framework that allows the machine learning-based DR prediction model to continuously learn from new data while retaining knowledge from previous observations. Specifically, the proposed IL approach integrates a weighted sampling strategy, so that the model is able to learn new information without forgetting previously learned patterns. The proposed sampling-empowered IL approach was tested on different classification models. The results demonstrated that the proposed IL-BBWS enables higher efficiency and even more accurate prediction of DR, while mitigating the challenges associated with periodically updated EHR database. The selected random forest model achieved an F_1 score of 0.34, indicating the effectiveness of the approach compared to benchmark methods. By leveraging IL with BBWS, healthcare providers can achieve significant cost savings and maintain DR prediction accuracy
Carbonaceous aerosol from the thermal degradation of plastics through atmospheric oxidation: Airborne particle method development
No full textNanoplastics, known but not well studied pollutants, can be aerosolized and have the potential to spread widely in the atmosphere with residence times on the order of weeks. The bleaching of nanoplastics is of interest due to the main climate contributions of aerosol particles’ relation to light absorption and scattering. An experiment was designed to study the bleaching of Red PETG 3-D printing filament by oxidation (ozone exposure). To that end, an experimental apparatus comprised of mixing volumes, desiccants, filters, a tube furnace, ozone generator, smog chamber, ozone analyzer, Photoacoustic Extinctiometer (PAX), and Scanning Mobility Particle Sizer (SMPS), among other tubing and connection hardware was developed. Aerosolized plastics nanoparticles of the dyed PETG filament after thermal degradation were injected to the smog chamber for study during their residence time in the smog chamber gas volume. Results are inconclusive for oxidation experiments, due to difficulty with the magnitude of bleaching due to ozone when compared to noise introduced by size distribution evolution. Next steps for the developed experimental apparatus, injection methods, and data collection procedures include trying alternative (more robust) aging mechanisms. Aging by introduction of hydroxyl radical injection from photolysis of hydrogen peroxide is one specifically promising alternative