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Everyperson's Cookbook : Busy Woman's Quick Cooking
No full textCookbook produced by the Wichita Chapter of the National Organization for Women
Minutes of a Regular Meeting, The University of Oklahoma Board of Regents, September 13, 2024
No full textPolicies, Models, & Trends in Open Access, Open Data & Persistent Identifiers: An overview and update
No full textThis presentation will explore significant recent updates pertaining to open access, open data, and persistent identifiers, and some of the ways we are responding at Oklahoma State University Libraries.
We will begin with an overview of the “Nelson Memo,” issued in 2022 by the White House Office of Science and Technology Policy to initiate planning for immediate public access to peer reviewed publications and data resulting from federal funding. We will discuss what the memo says, how agencies are responding, and what we might anticipate in 2025 given there will be a new presidential administration regardless of the election results. We will then move to an outline of the Federal Purpose License (also called the Government Use License) as a legal foundation for federal agencies’ right to deposit and reuse research outputs derived from agency funding. We will provide an update on efforts to formalize recommendations regarding persistent identifiers into a National Standard, summarizing the recommendations in the “Developing a US Persistent Identifier National Strategy” document. By the time of the conference a National Information Standards Organization (NISO) Working Group will likely have formed to author a formal text for public comment. The discussion will conclude with observations on the effect these efforts might have on research offices and academic libraries, including implications for compliance, labor & staffing, and models for supporting researchers.
We will then transition into a review of opportunities and challenges presented by these federal agency public access policies with respect to research data, including providing guidance for data management and sharing plan contents and supporting compliance with open access requirements. We will consider the importance of incorporating research data – and its impacts – in researcher evaluations like reappointment, promotion, and tenure and also outline our own efforts to quantify the impact of shared research data at an institutional level along with larger community efforts like the Make Data Count initiative.
This presentation will conclude with an analysis of the continuing shift toward transformative agreements and tension with diamond OA models. We'll examine how these developments are reshaping the scholarly communication landscape and discuss their implications for academic libraries. Additionally, we'll highlight the connection between the OSU Experts Directory and the Open Research Oklahoma repository, showcasing how this integration enhances research discoverability and participation in Green OA.N
Machine Learning Models to Predict Production Rate of Sucker Rod Pump Wells
Get PDFThe design, operation, and optimization of Sucker Rod Pumping (SRP) systems necessitate the utilization of production data. However, forecasting fluid flow rates at the surface of SRP artificially lifted wells usually poses a challenge, especially in instances where traditional separators and multiphase flowmeters are not universally available. Consequently, this study introduces nine machine learning (ML) models employing real data sourced from 598 wells with a production history exceeding three years. The dataset, comprising 8,372 data points, undergoes a random split allocating around 80% of the data (6,697 data points) for training, while around 20% (1,675 data points) are used for testing. The ML models encompass Gradient Boosting (GB), Adaptive Boosting (AdaBoost), Random Forest (RF), Support Vector Machines (SVMs), Decision Tree (DT), K-Nearest Neighbor (KNN), Linear Regression (LR), Artificial Neural Network (ANN), and Stochastic Gradient Descent (SGD). The chosen input features for the models are readily accessible during any SRP well-lifting process, and these inputs include various variables such as wellhead flowing pressure, casing pressure, predicted bottom hole fluid production rate, predicted bottom hole oil production rate, net liquid head above the pump, pump size, pump clearance, stroke length, pump speed, pump setting depth, the temperature at the pump depth, oil gravity, and water viscosity. Evaluation of the different ML models’ performance is carried out by two methodologies: K-fold cross-validation, and repeated random sampling. The findings reveal that the top-performing models are GB, AdaBoost, RF, LR, and SGD, exhibiting mean absolute percentage errors of 3.6%, 3.4%, 3.4%, 4.0%, and 4.4% respectively, and correlation coefficients (R2) of 0.937, 0.934, 0.935, 0.921, and 0.915, respectively. In practical field application, these models are deployed on a well within Egypt's Western Desert fields, demonstrating excellent agreement between actual fluid rates and model predictions. In conclusion, across diverse pumping scenarios and completion configurations, the ML models could effectively forecast production rates for different SRP wells. This capability facilitates continuous monitoring, optimization, and performance analysis of SRP wells, enabling swift responses to operational challenges since the proposed ML models offer an accessible, rapid, and cost-effective alternative to conventional separators and multiphase flowmeters.N
THE RUNNING BACK BY COMMITTEE APPROACH AND ITS EFFECT ON THE RUNNING BACK LABOR MARKET IN THE NFL
No full textRunning back salaries in the National Football League have been a major point of discussion for the last two offseason cycles. The league has seen some of the highest performing players struggle to receive satisfactory contracts regarding length and/or value. There is a significant amount of research supporting the idea that running backs should be paid less which supports the trends in the league, but up to this point, there has not been any publicly available research examining the mechanisms behind the decrease in compensation these players face. In this study, we examined if the leaguewide trend of shifting towards adopting running back by committee approaches influenced running back salaries. Ultimately, we did not have significant results leading to us concluding that we must accept our null hypothesis that running back by committee does not have a significant effect on salaries
The Influence of Cultural Worldviews on Public Support for Carbon Capture and Storage with the Risk of Induced Seismicity
Get PDFWe investigate the influence of cultural worldviews on public support for carbon capture and storage (CCS) with the risk of induced seismicity, while controlling for demographic factors, political affiliation, and religious beliefs. Using data from an online survey, we employ the cultural theory of risk framework to examine how hierarchy, egalitarian, individualism, and fatalist worldviews shape attitudes towards CCS when there is a noted risk of small earthquakes occurring due to the CCS. We find that individualism has a negative correlation with CCS support, while fatalism and egalitarianism have positive correlations. The absence of a significant correlation between the hierarchy worldview and CCS support suggests that other factors may be more influential in shaping hierarchists' attitudes toward CCS. We discuss these results in the context of each cultural worldview’s relation to nature, noting the importance of considering cultural worldviews alongside demographic variables when assessing public perceptions of CCS, given its known side effect risks. These findings contribute to a deeper understanding of the complex social and cultural dynamics surrounding social acceptance of CCS.N
Survival Prediction of Pediatric Leukemia under Model Uncertainty
Get PDFThis dissertation addresses critical challenges in survival prediction for pediatric leukemia, particularly Acute Lymphoblastic Leukemia (ALL), by introducing novel predictive models that incorporate Bayesian principles and advanced machine learning and deep learning techniques. Recognizing the complexity and heterogeneity of leukemia, our research emphasizes the need for precise and individualized predictions that factor in the recurrence and survival probability, two pivotal aspects that significantly influence treatment outcomes in children and adolescents. In the first segment, we introduce a Bayesian survival model that diverges from traditional survival analysis by integrating full Bayesian inference, providing more accurate patient-specific survival predictions that account for model uncertainty. This allows for more confident decision-making in clinical settings. The second part of our work proposes a Transformer-based deep survival model that not only predicts the time to event but also employs Shapley Additive explanations (SHAP) for model interpretability, shedding light on how clinical variables influence predictions. Further, we propose a Bayesian Transformer-based survival model that combines the feature extraction capabilities of the Transformer encoder with a Bayesian Neural Network (BNN) layer. This model outputs recurrence probabilities under model uncertainty. The outputs from the Transformer encoder are sued for K-means clustering to evaluate model performance. Our work demonstrates strong potential in survival and recurrence prediction for children with leukemia, providing robust predictive survival models for clinicians to offer efficient and effective medical care to pediatric leukemia patients
Diversification dynamics in space and time of two marine fish groups
No full textUnderstanding the evolutionary processes shaping species distributions in both marine and terrestrial environments has been a central interest among evolutionary biologists, biogeographers, and ecologists. Species richness in a given region is directly influenced by three key processes: speciation, extinction, and dispersal. Variations in the rates and timing of these processes are responsible for shaping diversity gradients such as those observed along latitudinal, longitudinal, elevation, and depth gradients. These variations arise from a complex interplay of biotic and abiotic factors, encompassing climatic stability, geographical barriers, trophic specializations, productivity, competition, and predation. Macroevolutionary studies using phylogenies can illuminate these evolutionary patterns and processes over extensive timescales and diverse taxonomic groups. Specifically, integration of comprehensive phylogenetic trees, derived from extensive taxonomic sampling of both extinct and extant species, with thorough genetic analysis, and supplemented by ecological and morphological datasets, can facilitate identifying factors influencing diversification and biogeographic trends across taxa.
The overarching goal of my dissertation is to understand how extrinsic (e.g., formation of historical barriers, temperature) and intrinsic (e.g., life history processes such as feeding mode, dispersal ability) factors may have shaped the evolution of two charismatic groups of marine reef fishes. The first two chapters aim at examining Syngnatharia, an extraordinarily diverse clade (>660 species) that includes trumpetfishes, goatfishes, dragonets, seahorses, pipefishes, and allies. The third chapter focuses on fishes in the order Acanthuriformes, which comprises surgeonfishes, the louvar, and the moorish idol (87 species). Despite progress made in unravelling the relationships of these and other clades of disparate marine fish groups based on a handful of genetic markers sequenced from a few representative lineages, the vast majority of the species lack phylogenetic placement. Additionally, very few studies have looked at genes associated with phenotypic or ecological changes in reef fishes from a macroevolutionary perspective. To fill in these gaps, my research aims to examine the evolutionary history of these groups using state-of-the-art approaches, including phylogenomics, phylogenetic comparative methods, and phylogenetically-informed genotype-to-phenotype (PhyloG2P) comparative genomic approaches based on whole genomes.
In my first chapter, I applied an integrative phylogenomic approach to elucidate the evolutionary history and biogeography of Syngnatharia. I collected genome-wide DNA sequence and geographic distribution data for 169 species to cover ~25% of the species diversity and all 10 families in the group, and complemented these datasets with paleontological and geological information. With these datasets I inferred a set of time-calibrated trees and reconstructed the ancestral ranges of the group. I then examined the sensitivity of biogeographic analyses to phylogenetic uncertainty (estimated from multiple genomic subsets), area delimitation, and biogeographic models. After accounting for these uncertainties, my results reveal that syngnatharians originated in the ancient Tethys Sea at the Late Cretaceous, 87 million years ago (Ma) and subsequently occupied the Indo-Pacific Ocean. Throughout syngnatharian history, multiple independent lineages colonized the Eastern Pacific (6–8 times) and the Atlantic (6–14 times) from their center of origin, with most events taking place following an east-to-west route prior to the closure of the Tethys Seaway between 12–18 Ma. These colonizations were facilitated by the long-distance dispersal ability of syngnatharians during their pelagic larval stages or through rafting, such as with sargassum-associated species, aided by oceanic currents.
For my second chapter, I examined factors driving syngnatharians species richness along the longitudinal diversity gradient across oceans and assessed whether patterns of morphological diversity are congruent with this gradient. I increased the taxonomic sampling of syngnatharians from my first chapter to 323 species (50% of the species diversity) to test three non-mutually exclusive evolutionary hypotheses proposed to explain the longitudinal diversity gradient: time-for-speciation, center of accumulation, and in situ diversification rates. I estimated diversification rates and body shape disparity broadly across the group, considering biogeographic regions within all three major oceanic realms (Indo-Pacific, Atlantic, and eastern Pacific), as well as within the Indo-Pacific region. The analyses showed that the extensive diversity of syngnatharian species in the Indo-Pacific region primarily stems from ancient colonizations, leading to in situ speciation during the Palaeogene, shortly after the Paleocene-Eocene Thermal Maximum (PETM), and subsequent lineage accumulation during the Miocene coinciding with the initiation of the Indo-Australian Archipelago (IAA) rearrangement. Conversely, the eastern Pacific and Atlantic regions exhibit lower regional diversities, largely due to more recent colonization events and the onset of diversification, with most lineages in these areas emerging during the Miocene. These findings strongly support the time for speciation and center of accumulation hypotheses. My study also reveals that a significant portion of syngnatharian morphological diversity originated early in their evolutionary history within the Tethys Sea, followed by a gradual decline in subclade disparity marked by the emergence of multiple adaptive peaks, particularly in head morphology. This suggests that while high species richness exists, it does not necessarily correlate with high morphological disparity across various biogeographic contexts. All in all, colonization dynamics explain the longitudinal diversity patterns of syngnatharian fishes across marine realms while morphological similarities persist among them.
In my third chapter, I examined the ecological drivers of trophic transitions among fossil and extant acanthuriforms as well as the genomic basis of these transitions. By combining genomic data for 80 extant species (~93% of total diversity) with morphological characters for 32 fossil taxa, I inferred total evidence time-calibrated phylogenies. Using these phylogenies, I reconstructed the diet of acanthuriforms and investigated the number of times the planktivory lifestyle evolved, along with the geographic location and timing of these transitions. The analyses indicate an origin of acanthuriforms approximately 64 Ma following the K-Pg mass extinction event, with at least seven documented transitions to planktivory from non-planktivorous lineages, followed by at least four reversals to non-planktivorous diets. While the earliest transitions occurred in the ancient Tethys Sea, the most recent ones happened within the Indo-Pacific region. I then evaluated the effect of the convergently evolved diets on acanthuriforms’ diversification, finding no significant effect as diversification rates remain constant across trophic guilds. However, transition rates are higher from planktivores to non-planktivores compared to the opposite direction. Diversification of planktivore species does appear to be influenced by cool past climatic temperatures, although there is also a confounding effect from phylogenetic signal. Despite ecological and morphological factors commonly driving this trophic specialization, the extent to which this adaptive convergence is caused by convergent changes at the molecular level remains understudied in reef fishes. Therefore, in this study I performed PhyloG2P analyses, using newly-generated chromosome-level (Acanthurus chirurgus) and short-read (45 species) genomes to identify genes under positive selection across planktivore lineages and along branches where a transition to planktivory occurred. We identified a total of 91 genes that underwent convergent positive selection in planktivorous lineages, along with three genes unique to planktivores. These genes are implicated in metabolic processes and adaptations in body shape, consistent with the repeated instances of convergence towards a pelagic environment, which are associated with planktivory and specialized morphological traits.
In summary, my dissertation explores the evolutionary processes shaping the distributions of marine fish species, highlighting the pivotal roles of speciation, extinction, and dispersal in driving diversity across oceans. My research also underscores the importance of integrating data from both fossil and living species to obtain a more comprehensive picture of the evolutionary history of groups. Through comprehensive analyses based on genomic, ecological, and morphological data, I emphasize the need to address various factors generating uncertainty in macroevolutionary and biogeographic inferences. Furthermore, my findings contribute to our understanding of the evolutionary dynamics as well as genetic underpinnings of trophic transitions in marine fishes, shedding light on the adaptive mechanisms driving diversification. Overall, my thesis represents an important step towards understanding the evolutionary history of marine fishes by disentangling their diversification patterns in space and time
Validation and field testing of an all-digital pressure sensor for permanent, distributed downhole measurements
No full textThe importance of downhole pressure sensing has risen significantly in oil and gas operations. Improvements in downhole sensing technology are expected to positively impact drilling, stimulation, production forecasting, and wellbore integrity. However, available downhole pressure sensors are expensive, have limited distribution capabilities, and have a short lifespan. To address these issues, a proposal has been made for an all-digital, low-cost downhole pressure sensor that can be permanently installed and distributed throughout a wellbore. This proposed sensor can measure pressure up to 10,000 psi (69 MPa) and has a temperature limit of 482°F (250°C). This study aims to design the pressure system, conduct laboratory testing to validate the sensor under downhole pressure and temperature conditions, and prepare for a field validation test of the sensor system. A literature review discusses and compares the latest technics of downhole pressure sensors. Different pressure sensor types, designs, and applications are discussed. After establishing a background study of the requirements for developing a new sensor, we do the modeling work of all the parts of the new sensor within the required ranges. Then, we have the laboratory test done in the simulated environment of up to 3,000 psi (21MPa) and 194°F (90°C). After that, we compared the result with the field test results and evaluated the sensor performance. Ultimately, we have the last laboratory test to test the multiplexing of five sensors with the 10,000 ft (3048 m) long cable, high temperature up to 536°F (280°C), and then test the sensor to fail. This integrated study helps to understand the downhole sensor, its history, the application, and the working mechanism, as well as how to make sensor selections with diverse downhole environments and operation requirements
