Open Research Oklahoma (Oklahoma State Univ.)
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Temperature influence on benzene behavior in crude oil during tank fires: Liquid-phase diffusion and implication for firefighter exposure
No full textHazardous material responders maintain conventional wisdom that elevated liquid temperature from a crude oil fire reduces volatility and therefore lowers the risk of exposure to volatiles in post-fire crude oil. After a crude oil tank fire is extinguished, responders often work near the post-fire crude oil when conducting damage assessments or removing oil from the tank’s structure. If the conventional wisdom is not true and the volatiles are not removed by heat, responders lacking adequate protection may be exposed to unhealthy airborne concentrations of toxic aromatic hydrocarbons such as benzene. Post-fire crude oil was examined quantitatively seeking answers regarding the survival of benzene and the risk posed to unprotected responders who are tasked with near-field engagement. The first study quantified hydrocarbon volatility of liquids in the heat-affected layer (hot zone) of crude oil following thirty-minute tank fire evolutions. Most notably, benzene persisted disproportionately to aromatic counterparts in post-fire crude oil. The second study utilized a novel-design tank fire apparatus that enabled temperature and aromatic liquid concentration analysis with emphasis on foam extinguishment as the variable. A relationship between benzene persistence and foam extinguishment was observed. The phenomena of benzene persistence in post-fire crude oil, with influence from foam extinguishment, initiated a hypothesis postulating the role of liquid-phase diffusion as a potential contributor. Hence, the third study which utilized a novel-design diffusion column to investigate the influence of an adjacent high temperature zone on benzene’s diffusivity. Benzene did not diffuse disproportionately to toluene, ethylbenzene or m-xylene, despite its higher diffusivity in solvents. Although the contributing variable to benzene persistence was not identified in this work, two significant findings contributed to the body of knowledge. First, post-fire crude oil should not be regarded as benign based on the observance of benzene and its persistence in crude oil following a tank fire. Secondly, liquid-phase diffusion can be disregarded for now as a contributor and further research should focus on alternate explanations. Ultimately, there is rebuttal to the belief that post-tank fire crude oil is benign, giving priority to benzene exposure in hazard communication for responders
Economic feasibility of wine grape cultivation in Oklahoma
No full textThis study evaluates the economic feasibility of cultivating American hybrid and European wine grape varieties in Oklahoma to inform sustainable viticulture strategies. It aims to determine which varieties offer optimal profitability under regional climatic and crushed grape market conditions through comparative analysis of financial indicators. Using a 100-year Monte Carlo simulation with primary and secondary data, the study analyzes Net Present Value (NPV), Internal Rate of Return (IRR), and Benefit-Cost Ratio (BCR) across four varieties. Results indicate that American hybrids, particularly Vignoles, dominate in financial viability, achieving consistent profitability and resilience, while Norton follows closely with stable returns and minimal risk. Cabernet sauvignon shows marginal feasibility, meeting thresholds despite challenges, whereas Pinot grigio fails to achieve financial viability. The superior performance of hybrids is driven by their extended productive lifespans, disease resistance, and cost efficiency, reducing replanting frequency and non-revenue phases. Cabernet sauvignon’s limited viability stems from higher costs offset only partially by market returns, whereas Pinot grigio’s shorter lifespan and price constraints lead to a high probability of losses. These findings highlight the economic risks of prioritizing European varieties in Oklahoma’s climate. The study concludes that prioritizing American hybrids maximizes economic sustainability, with Cabernet sauvignon as a supplementary option under favorable conditions. Pinot grigio is economically unviable
Employment and earnings growth and an input-output analysis for sub-state planning district seven, North Central Oklahoma
No full textExploring the gender wage gap in North American forestry
No full textThis dissertation investigates gender-based wage disparities in the public forestry workforce across Washington, Idaho, and Montana, drawing on state government payroll data. While existing literature has extensively examined gender wage gaps in corporate and service industries, less is known about compensation equity in male-dominated, public-sector fields such as forestry. This study aims to address this gap by analyzing how gender, state, and occupational hierarchy interact to influence salary outcomes among forestry employees. A 2 × 3 × 4 factorial ANOVA was conducted to examine the main and interaction effects of gender (male, female), state (WA, ID, MT), and job level (Entry, Mid, Senior, Manager) on annual salaries. Job titles were standardized and categorized into four hierarchical job levels based on industry norms. The analysis revealed statistically significant main effects for state and job level, as well as interaction effects between gender and job level, and a significant three-way interaction among state, gender, and job level. Gender-based wage disparities were most pronounced in entry- and mid-level roles, where men earned significantly more than women, particularly in Washington and Montana. At the senior and managerial levels, these differences diminished and were not always statistically significant, suggesting that wage gaps are more severe at lower occupational tiers. The findings are interpreted using the Human Capital Model, which attributes wage differences to education and experience; the Labor Market Discrimination theory, which addresses structural inequities; and Occupational Segregation theory, which explains gender clustering in job types. Even after accounting for job level, substantial unexplained wage differences remain, underscoring the presence of systemic inequality and the need for additional factors such as age, education, experience and tenure in gender wage gap studies
Assessing the impact of multiple rain gauges as an input to machine learning streamflow prediction model
No full textStreamflow forecasting is important for managing water resources, providing essential insights for flood control, irrigation planning, and ecosystem sustainability. Long Short-Term Memory (LSTM) networks, one of the most recent developments in machine learning, have shown promise in enhancing prediction accuracy. However, the use of multiple rainfall gauge data in streamflow modeling remains underexplored, particularly when incorporating multiple ground-based rain gauges. This study investigates the impact of integrating rainfall data from several ground-based rain gauges on streamflow prediction accuracy. The Washita River Basin in Oklahoma is the study area of the research. Data from 10 Oklahoma Mesonet rain gauges are used as input to make streamflow predictions. Four LSTM models were developed using the NeuralHydrology library: one with a single rain gauge that was found to have the highest importance, one with simply averaged (lumped) rainfall data, one with spatially weighted aggregated rainfall data (i.e., Voronoi polygons), and one with spatially disaggregated rainfall inputs. Before model training, feature selection was done using permutation feature importance. Station-level ablation tests were also performed. This showed that the most important station was the one closest to the watershed outlet. The models were trained on nine years of daily data and evaluated using the Nash-Sutcliffe Efficiency (NSE) metric. Results show that the disaggregated model achieved the highest test NSE (0.41), while the lumped model has the worst (-1.10). The spatially weighted aggregated model and the single gauge performed closer to the disaggregated model (test NSE of 0.30 and 0.35). These findings suggest that preserving the spatial variability of rainfall data can enhance LSTM-based streamflow predictions when that data is available
Freshmen students' sense of belonging after participating in a college of agriculture living learning program: A convergent mixed methods study
No full textThis mixed-methods research study investigates freshmen students’ sense of belonging after participating in a college of agriculture living learning program (LLP) utilizing the University Student Belonging Scale (USBS) across three constructs: (a) feelings that impact belonging, (b) school spirit, and (c) social connections at the university. This study aims to fill a gap in existing research utilizing the Need to Belong Theory (Baumeister & Leary, 1995). This study aims to compare Freshmen in Transition (FIT) LLP participants with non-FIT LLP participants utilizing the USBS. Quantitative objectives include describing how FIT and non-FIT participants perceive their sense of belonging during their freshman year and comparing these participants’ sense of belonging. Additionally, qualitative data was collected from the FIT participants so I could gain an insight to the students’ lives during their current experiences within the program. Qualitative research questions involve how students describe their sense of belonging on campus through their experiences within the FIT LLP, how participating in FIT influence the students’ sense of belonging, and how the FIT LLP could be adapted to provide students with a higher sense of belonging during their freshman year. Limitations of this study revolve around focusing solely on the FIT LLP, my experiences with the FIT LLP, Ferguson College of Agriculture, and Oklahoma State University, and not utilizing all constructs of the USBS. Despite these limitations, the findings within this research will provide insights on how to increase students’ sense of belonging and how LLPs affect students’ sense of belonging
Embedding security awareness in IoT systems: A framework for providing change impact insights
No full textThe Internet of Things (IoT) is rapidly advancing toward increased autonomy; however, the inherent dynamism, environmental uncertainty, device heterogeneity, and diverse data modalities pose serious challenges to its reliability and security. This paper proposes a novel framework for embedding security awareness into IoT systems—where security awareness refers to the system’s ability to detect uncertain changes and understand their impact on its security posture. While machine learning and deep learning (ML/DL) models integrated with explainable AI (XAI) methods offer capabilities for threat detection, they often lack contextual interpretation linked to system security. To bridge this gap, our framework maps XAI-generated explanations to a system’s structured security profile, enabling the identification of components affected by detected anomalies or threats. Additionally, we introduce a procedural method to compute an Importance Factor (IF) for each component, reflecting its operational criticality. This framework generates actionable insights by highlighting contextual changes, impacted components, and their respective IFs. We validate the framework using a smart irrigation IoT testbed, demonstrating its capability to enhance security awareness by tracking evolving conditions and providing real-time insights into potential Distributed Denial of Service (DDoS) attacks.Computer Scienc
Participant perception of the value created by participating in a virtual community of practice: A case study
No full textProviding dispersed teams with meaningful professional development is a challenge employers face. To increase engagement and ensure value is created, it is imperative to understand employees’ perception of the professional learning opportunity. This study focuses on employees’ perceptions of participating in professional learning that was designed using a virtual community of practice (vCoP) framework (Wenger et al., 2002). The vCoP framework is built upon the three elements needed for social learning: the domain of knowledge, community of people, and shared practice. The first embedded case is a design case of a successful vCoP, the NASA STEM Pathway Activities-Consortium for Education (NSPACE vCoP). The second and third embedded cases explore employees’ perception of participating in professional learning in a vCoP and the value created as a result of the experience. Data are analyzed using Wenger et al.’s (2002) vCoP framework and Wenger et al.’s (2011) Value Creation Framework (VCF). The study participants were all Oklahoma State University (OSU) employees working on the NSPACE cooperative agreement and stationed at OSU or a National Aeronautics and Space Administration (NASA) center around the nation. This study successfully used the vCoP framework and VCF and recommends replicating the study with larger populations and additional vCoP environments
Suggested extension planning guide with promotional material for conducting LP-farm workshop
No full textExploring curriculum congruence within Oklahoma school-based agricultural education teachers
No full textThis quantitative methods study examined curriculum congruence within Oklahoma School-Based Agricultural Education (SBAE) programs. Curriculum congruence is defined as the presence of and the interest in teaching in the 11 Agriculture, Food and Natural Resources pathways. Given that SBAE is an elective program with flexible curricular frameworks, teachers often have the autonomy to select and shape the content they deliver. This flexibility highlights the importance of personal interest in shaping curriculum decisions and instructional practices. The purpose of this study was to explore the degree of curriculum congruence across various agricultural subject areas and assess how teacher interest influences that alignment. Findings revealed that higher levels of teacher interest were positively associated with greater curriculum congruence. These results emphasize the need for targeted curriculum adaptation and professional development, especially in less-preferred content areas. The study suggests that empowering teachers through increased autonomy, curriculum flexibility, and meaningful professional development opportunities can enhance curriculum congruence. By aligning content with teacher interest and strengthening support structures, SBAE programs can foster more engaging and impactful learning environments. Implications for practice include involving teachers in curriculum design, offering interest-aligned training, and promoting instructional strategies that bridge the gap between teacher passion and required content. These efforts can ultimately improve the quality and consistency of agricultural education, better preparing students for careers in agriculture and related fields