Open Research Oklahoma (Oklahoma State Univ.)
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Assessing production variability and short-term aging effects for asphalt mixes in Oklahoma
No full textSeveral state agencies use Superpave mix design as the standard for asphalt mixture design, relying primarily on volumetric properties. However, the Superpave mix design limitations in addressing cracking and rutting resistance have become evident, especially with the increased use of recycled materials, binder modifiers, and additives. As a result, there has been a recent shift by many agencies including the Oklahoma Department of Transportation (ODOT) towards the Balanced Mix Design (BMD) approach to enhance asphalt pavement durability by incorporating performance-based criteria for cracking and rutting resistance. To support this transition, the ODOT has introduced a provisional specification based on using the Indirect Tensile Asphalt Cracking Test (IDEAL-CT) for cracking assessment and the Hamburg Wheel Tracking Test (HWTT) for rutting evaluation. To evaluate the effectiveness of this approach, the ODOT has launched several pilot projects utilizing the BMD provisional specification. This study evaluates the lot-to-lot variability in IDEAL-CT results of plant mixes and determines an appropriate laboratory short-term aging (STA) protocol that takes into account plant production variability. To this end, six plant-produced mixes were sampled from three different pilot project locations, representing a BMD mix and a Superpave mix from each location. The plant-produced mixes were sampled from different production lots, and tested using IDEAL-CT. Laboratory-produced mixes were prepared and tested under different STA conditions (2-hour and 4-hour aging). A performance-based approach was utilized to compare plant- and laboratory-produced specimens, using the percent within limits (PWL) concept. Results indicate statistically significant variability between lots for both the Superpave and BMD mixes. Using 90% PWL, it was shown that a 4-hour STA lab protocol better simulates plant-produced mixes when production variability is considered. DSR testing further confirms that the binder from the 4-hour STA mix shows high temperature performance more closely aligned with that of the plant mixes
Thinking like a C-suite strategist: The impact of salesperson executive officer mentality on B2B buying team complexity and salesperson performance
No full textBusiness-to-business (B2B) purchasing decisions are increasingly marked by larger, more diverse buying teams with multiple functions and C-suite involvement whose competing priorities complicate the sales process and negatively impact win rates. In an exploratory qualitative study with 26 B2B buyers and sellers (Study 1), I identify buying team complexity as a central barrier to success and uncover a novel salesperson characteristic, Executive Officer Mentality (EOM), that helps sales professionals effectively navigate their customers’ complex purchasing journeys. EOM reflects the extent to which salespeople adopt the perspective of their customers’ most senior executive team, focusing on long-term strategic outcomes, aligning solutions to C-suite-level objectives, and tailoring value propositions to the language and priorities of senior stakeholders. In a scale development study (Study 2), I develop and validate a new six-item measure of EOM, confirming its reliability and construct validity. Finally, in a field study investigating 1,632 sales opportunities nested within 59 sales professionals (Study 3), results confirm that greater buying team complexity significantly hinders win rates, but salespeople who exhibit higher EOM mitigate this negative effect and substantially improve their likelihood of winning. Collectively, these findings introduce EOM as a critical salesperson capability for addressing the growing complexity of B2B sales. By thinking like a “C-suite strategist,” salespeople can more successfully align a diverse and growing number of stakeholders and improve sales performance in complex buying environments
Unraveling soil carbon complexity in the Nebraska Sandhills
No full textThe Sandhills ecoregion of Nebraska, one of the world’s most intact grassland ecosystems, represents a significant potential contributor to climate change mitigation through carbon sequestration. This thesis investigates the drivers of soil organic carbon (SOC) storage across this heterogeneous landscape using data collected from two ranches in Cherry County, Nebraska. Analysis of 620 soil samples from paired sites demonstrated wet meadows contained substantially higher SOC concentrations (mean = 2.95%) than adjacent upland dunes (mean = 0.45%), with soil texture being the dominant driver of SOC differences. A strong negative relationship between sand content and SOC in wet meadows (R2 = 0.584, p 95% sand) showed consistently low SOC (0.04% to 2.48%). Additionally, I analyzed covariation in soil elements and SOC. Analysis of 106 soil samples for 18 elements revealed substantial heterogeneity in elemental composition, with wet meadow soils containing notably higher concentrations of most elements, particularly calcium (11× higher), sulfur (7× higher), and magnesium (3.6× higher). In predictive models using both upland and wet meadow soil samples, boron, sulfur, and zinc displayed significant associations with SOC (p < 0.05), highlighting the complex biogeochemical relationships potentially influencing carbon storage. This research demonstrates that in sand-dominated rangelands, soil texture fundamentally constrains carbon storage potential. Carbon sequestration policies should thus recognize the inherent limitations of sandy soils and prioritize conservation of areas with fine-textured soil. Future research should investigate how hydrological restoration might increase carbon accumulation in wet meadows, leveraging their value as carbon reservoirs within this ecologically diverse landscape
Assessing the impact of hydraulic fracturing on groundwater availability for food production in the Southern Great Plains, USA
No full textThe Southern Great Plains, encompassing Texas, Oklahoma, and Kansas, is a critical region for food production, livestock feed, and energy generation from both fossil fuels and renewable sources. Hydraulic fracturing operations in this region compete with agriculture for limited groundwater resources, particularly from the Ogallala Aquifer. This study evaluates the water demand of hydraulic fracturing (fracking) and its impact on agricultural water availability using hydraulic fracturing disclosure data, NASA's Gravity Recovery and Climate Experiment satellite observations, and crop water productivity models for 2000-2023.
Our analysis identified 16,040 active hydraulically fractured wells, with Texas containing about 65% of these wells. Major operational hotspots included the Permian Basin and Eagle Ford Shale in Texas, along with Oklahoma's Anadarko Basin. The average water consumption per well reached approximately 4.2 million gallons, primarily sourced from groundwater, with some counties totaling 250 million gallons in water usage. Time-series analysis revealed a significant negative correlation (r = -0.76, p = 0.01) between groundwater storage and fracking intensity, particularly in regions with concurrent agricultural demands.
These findings highlight growing water resource competition between the energy and food production sectors. The study advocates for integrated water management strategies incorporating policy measures, technological innovations, and alternative water sources to ensure both food and energy security. The results provide valuable insights for addressing the food-energy-water nexus in water-stressed regions worldwide
Rainfall erosivity variability based on updated rainfall records
No full textRainfall erosivity (R-factor) is an essential input dataset used in soil erosion models such as USLE, RUSLE, and RUSLE2, as it quantifies the combined effects of rainfall and runoff in causing soil erosion. Accurate estimation of rainfall erosivity is critical for predicting soil loss, evaluate the risk of water pollution from construction sites, and supporting land management decisions under changing climate conditions. However, the determination of erosivity depends on rainfall data, and due to changing precipitation patterns, erosivity datasets must be updated periodically. The main objectives of this dissertation are to:(1) evaluate the applicability of published regression equations for estimating annual rainfall erosivity based on annual precipitation in EPA Region 6; (2) estimate monthly rainfall erosivity using high-temporal-resolution (5-minute interval) data from a dense gauge network in Oklahoma; (3) assess the performance of gridded precipitation datasets when applied in the erosivity density approach to estimate rainfall erosivity; (4) quantify discrepancies between the estimates generated in this dissertation and those from published global datasets (GloREDa 1.2 and GloRESatE); and (5) identify changes in rainfall erosivity and erosivity density with variations in rainfall through trend analysis from 1995 to 2023. The results demonstrate that commonly used regression equations introduce substantial bias, highlighting the need for region-specific models. High-resolution gauge observations revealed significant spatial and seasonal variability in erosivity across Oklahoma, with increasing trends particularly evident in the eastern regions. Comparisons with global datasets uncovered considerable discrepancies, underscoring the need to update these products. Additionally, significant upward trends in both erosivity and erosivity density were observed, indicating intensifying rainfall events. This dissertation emphasizes the need to revise existing rainfall erosivity databases in response to changing climate conditions. There is a critical need for robust estimation approaches that integrate gridded precipitation data and leverage machine learning techniques. Gauge-derived erosivity estimates are essential for training and evaluating these emerging methods
Role of writing in uncovering colonial beliefs and shaping an international teacher identity
No full textYou are invited to witness autoethnography as a method by exploring the essence of how writing through intersections of teacher identity, cultural background, and writing pedagogies unfolds. By challenging the traditional academic structure, terminology used, an iterative process of data collection, analysis and interpretation, the author uncovers an on-going understanding of self as an international graduate teaching assistant navigating diverse roles and identities along with the complexities of colonial thinking, linguistic identity, and pedagogical development. The author draws on Chang’s (2008) autoethnographic framework with balancing acts, incorporating self-reflections, photographs, and artifacts to analyze and interpret the revelations and tensions that emerged in the teacher development journey. Key findings reveal (a) the awareness of colonial thinking beliefs in my own practice, (b) my understanding that being a teacher of writers requires recognizing my own identity to build relationships with others, and (c) the recognition that identity development as a teacher educator involves unlearning prior teaching beliefs to embrace transformative change. Findings contribute to the implications of the role of autoethnography as a humanizing approach to teacher development in writing pedagogies
Design and evaluation of an ejector nozzle with variable-area diffuser for a micro turbojet engine.
No full textThis thesis investigates the effects of geometric parameters on the performance of an ejector-augmented nozzle with variable-area diffuser for micro turbojet engines. Micro turbojet engines are air breathing jet engines that have a thrust range between 10-500 lbf and typically use a centrifugal compressor. The engine used in this study was a Jet Cat P100 which has a stock thrust of 22.5 lbf. The primary objective of this work is to evaluate how variations in mixer duct length, and location; and nozzle-diffuser exit angle affect thrust output. Analysis was first conducted based on previous work to determine the areas for the primary nozzle, secondary outlet, and the mixing duct for experimental testing. Experiments were conducted with two variable-area nozzles, a two-dimensional, square, and axisymmetric, round nozzle, directly coupled downstream of the turbine to evaluate the effect on thrust. Follow-on experiments were conducted with a simple ejector nozzle analog test article to determine optimal geometry and placement. Experimental data was collected for a range of throttle settings and geometric configurations. Engine thrust increased by 12.7% with the best ejector geometric configuration. A final production representative design for the ejector nozzle with variable-area diffuser included a push rod actuated axisymmetric configuration. The push rod nozzle consisted of eight individual flaps with the ejector integrated to the exit of the primary nozzle, allowing for ambient, secondary air to mix with the primary exhaust gases. The nozzle was made of 316 stainless steel for good oxidation resistance with a max operating temperature of 1600 F. All flaps were attached to a ring that was connected to three servos motors, controlled mechanically with a servo tester. Results provide insight into how geometric configurations of ejector components influence micro turbojet engine performance and can improve future small-scale propulsion system designs
Design of a robust IEEE compliant floating-point divide and square root using iterative approximation
No full textIn this work, an IEEE 754 compliant normalized floating-point divide and square root unit is presented that utilizes iterative approximation. This research provides a robust architecture that allows multiple formats and all IEEE 754 rounding modes while still exhibiting high-performance. Moreover, this thesis presents a design that adheres to the IEEE 754 2019 standard as well as demonstrating methods for rounding results to all five rounding modes using iterative approximation. Performance, Power, and Area estimates are determined from physical synthesis using ARM-based standard cells in a TSMC 28nm process. This thesis also presents comparisons with other implementations and demonstrates the efficiency of the approach presented here
Transcriptional and signaling mechanisms in viral pathogenesis and pulmonary fibrosis
No full textThe first part of this work focuses on Bovine alphaherpesvirus 1 (BoHV-1) latency and reactivation. We identified that the viral transactivator bICP0 is regulated by host-derived transcription factors during stress-induced escape from latency. Using promoter assays, we demonstrated that the glucocorticoid receptor (GR), Krüppel-like factor 4 (KLF4), and Specificity Protein 3 (Sp3) differentially activate the bICP0 early promoter. Notably, GR and Sp3 cooperatively enhanced promoter activity, whereas KLF4 exhibited independent and potent transactivation. These findings underscore the importance of ligand-independent GR signaling and transcription factor crosstalk in BoHV-1 reactivation.
In the second project, we evaluated the role of mineralocorticoid receptor (MR) in HSV-1 replication using a neuroblastoma cell model. HSV-1 infection upregulated MR expression, and pharmacologic blockade with Esaxerenone, an MR antagonist, reduced both MR and glycoprotein B (gB) expression. These results suggest that HSV-1 co-opts MR signaling to enhance replication, and that MR antagonism may serve as a therapeutic strategy to control neurotropic herpesvirus infections.
The third and fourth projects focused on oxidative stress and fibrosis in pulmonary disease. We conditionally deleted Glutathione Peroxidase 4 (GPX4) in macrophages and observed exacerbated lung injury, increased fibrosis, and elevated inflammatory cell infiltration in both bleomycin and asbestos-induced lung injury models. GPX4-deficient macrophages showed skewing toward an M2 profibrotic phenotype and increased senescence markers, indicating that GPX4 is a key regulator of redox balance, macrophage function, and fibrogenesis.
Lastly, we identified Homeodomain-Interacting Protein Kinase 2 (HIPK2) as a central modulator of TGF-β1/SMAD and WNT/β-catenin signaling in human pulmonary fibroblasts. HIPK2 knockdown significantly attenuated fibrotic gene expression and fibroblast proliferation in vitro and reduced inflammation, collagen deposition, and impaired lung function in a bleomycin-induced fibrosis model in vivo. These findings establish HIPK2 as a molecular integrator of pro-fibrotic signaling and a promising therapeutic target for idiopathic pulmonary fibrosis (IPF).
Together, this dissertation advances our understanding of host transcriptional regulation in herpesvirus latency/reactivation and identifies novel redox and signaling regulators of lung fibrosis. These mechanistic insights open new avenues for therapeutic interventions targeting transcriptional control and oxidative stress in both infectious and chronic fibrotic diseases
Embedding security awareness into a blockchain-based dynamic access control framework for the zero trust model in the distributed system
No full textThe Zero Trust (ZT) model strengthens distributed system security by enforcing strict identity verification, fine-grained access control (AC), and continuous monitoring. Unlike traditional models that assume implicit trust, ZT treats every entity as a potential threat, requiring dynamic access control mechanisms to regulate privileges and mitigate risks.
Dynamic Access Control Schemes (DACSs) are vital for ZT implementation, adjusting policies based on real-time context to reduce insider threats and suspicious behaviors. DACSs autonomously coordinate Access Control Lists (ACLs) with security events and evolving policies. Embedding security awareness enables real-time risk assessment and permission adjustments. However, as systems grow in complexity, centralized policy management struggles to scale and adapt, making decentralized solutions necessary. Blockchain-based management addresses these challenges by providing tamper-proof policy storage and immutable access logs.
This research introduces a blockchain-based DACS framework to implement ZT principles in distributed systems. The framework dynamically manages ACLs and enforces policies through smart contracts. I developed an extended blockchain node architecture that maintains ACLs for each node’s objects, incorporating a minimum trust metric (TM) threshold to evaluate access requests. The TM, reflecting trustworthiness, adjusts dynamically based on observed behavior.
A security awareness component analyzes access request patterns in real-time, enabling proactive risk assessment through a newly introduced Risk Factor (RF) metric. This metric continuously evaluates operational risk and informs dynamic privilege adjustments. I also extended smart contracts to enable continuous monitoring and real-time updating of trust metrics. Nodes exhibiting suspicious behavior are automatically penalized through a dynamic enforcement mechanism embedded in the smart contracts, ensuring adaptive policy adjustments even against credentialed but untrustworthy entities.
I validated the blockchain-based DACS framework by deploying extended smart contracts and node processes on an Ethereum test network. Through simulations of broken access control attacks and normal access scenarios, the framework demonstrated enhanced security, scalability, and adaptability. These results confirm the model’s effectiveness as a next-generation security framework for dynamic, decentralized environments