Open Research Oklahoma (Oklahoma State Univ.)
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Fracture flow in granite rock cores using non-Newtonian fluids: A potential solution to flow channeling in enhanced geothermal systems
No full textGlobal scientific attention is turned toward improving the economics and technical challenges of deploying Enhanced Geothermal Systems (EGS), a promising form of geothermal energy exploitation, at a commercial scale for power generation. One such challenge is the development of an early thermal draw-down path across flow paths within EGS reservoirs, known as flow channeling. This phenomenon describes the preferential flow of working fluid in a single path. The goal of EGS operators is to maximize heat extraction from the system throughout the project lifecycle, but the development of a thermal drawdown path may significantly impact project economics. Since fractures constitute the major conduit for fluid flow between wells in EGS, numerous methods have been proposed to manage flow within these fracture networks to mitigate flow channeling.
In this study, to manage fracture conductivity, the flow of Ionic Liquids (ILs) has been experimentally studied to understand its applicability to fracture conductivity tuning. By using ILs, thermo-viscous tuning is possible within EGS to manage fracture conductivity. However, what level of response can be observed for rock fractures due to the flow of ILs? Here, we presented results in terms of reversibility – A fraction of the post-conductivity relative to the pre-flow conductivity of the fracture to water in terms of measured frictional pressure drop. It is important to quantify IL performance in terms of reversibility to measure the degree of change to fracture conductivity due to their flow. The studied ILs include 1-hexylpyridinium tetrafluoroborate [HPy][BF₄], 1-hexylpyridinium bromide [HPy][Br], and 1-Butyl-3-methylimidazolium bromide BMiMBr and Choline Magnesium Chloride Hexahydrate [ChClMg Cl₂.6(H₂O)] - DES. By flowing these fluids between a pre- and post-flow of De-Ionized (DI) water through a single vertical fracture, we reached the following results: (1) IL would generally lead to a significant drop in the flowrate when injected into a fractured granite sample, and (2) the tested fluid has shown a higher average rate-recovery as well as reversibility at higher temperatures. We concluded that factors such as viscous force are a major contributor to pressure losses, leading to a reduction in flow. The reduction in flow may enhance heat recovery to the already channeled fracture path within EGS systems over time. This work provides insights into the possible behavior of ILs as both working fluid and intermediate remedial fluid in EGS systems in the event of flow channeling and or at the inception of a thermal drawdown
Approximation of conformal mapping via the Szegő kernel method
No full textWe study the uniform approximation of the canonical conformal mapping, for a Jordan domain onto the unit disk, by polynomials generated from the partial sums of the Szegő kernel expansion. These polynomials converge to the conformal mapping uniformly on the closure of any Smirnov domain. We prove estimates for the rate of such convergence on domains with piecewise analytic boundaries, expressed through the smallest exterior angle at the boundary. Furthermore, we show that the rate of approximation on compact subsets inside the domain is essentially the square of that on the closure. Two standard applications to the rate of decay for the contour orthogonal polynomials inside the domain, and to the rate of locally uniform convergence of Fourier series are also given.Mathematic
Phenotypic and proteomic analysis of a Chlamydomonas mutant, shf1, defective in flagellar assembly
No full textIntroduction/Objectives: Cilia and flagella are essential for human health. Defects in the assembly and function of these organelles are associated with a collection of disorders called ciliopathies. Studies have suggested that regulation of ciliary size is associated with external environmental factors. Although TOR signaling pathway has recently been implicated as playing a pivotal role in linking the cellular environment with determination of cell and organelle size, additional biological pathways involved in this process remain largely unknown. To learn more about these pathways, we undertook a phenotypic and proteomic analysis of a mutant defective in assembling full-length flagella, shf1. These mutants assemble flagella that are half the length of wildtype. Interestingly, the flagella of these mutants are unstable in the presence of acetate.Methods: Wildtype and shf1 cells were grown to equal density on a 12-hour light/dark cycle. Flagella and cell body sizes as well as acetate-induced changes were determined by microscopic analysis. Quantitative proteomic analysis was performed using label-free methods and analyzed using MaxQuant software. Statistical analysis was performed using two-tailed student’s t-test to identify proteins whose levels varied between wildtype and shf1 cell bodies and isolated flagella.Results: As previously shown, shf1 cells assembled flagella that were half the length of wildtype cells. Surprisingly, the cell body volume of shf1 was increased up to twice that of wildtype. The inclusion of acetate in the media resulted in aflagellate shf1 cells and cells were seen to lose flagella within 30 minutes of addition of acetate. Proteomic analysis on isolated cell bodies and flagella identified 4,943 and 3,169 proteins, respectively. Preliminary analysis of the proteomic data demonstrated that 4% of the cell body proteins were present at levels that differed in a statistically significant manner. Similarly, a statistically significant difference in protein levels was seen for 9.8% of flagellar proteins.Conclusions: Although shf1 assembles short flagella, their cell bodies are approximately twice the size of wild-type cells. This suggests that regulation of flagellar length and cell body size are coupled together. As originally reported, inclusion of acetate in growth media results in the absence of shf1 flagella. These results suggest that acetate induces instability of the shf1 flagella leading to flagellar disassembly. Our preliminary data suggest that shf1 and wildtype cells have significant differences in protein composition and levels. Currently, we are examining the proteins that are statistically different between these two strains to learn more about the pathways regulating flagellar assembly and function
How to find a measure from its potential
No full textWe consider the problem of finding a measure from the given values of its logarithmic potential on the support. It is well known that a solution to this problem is given by the generalized Laplacian. The case of our main interest is when the support is contained in a rectifiable curve, and the measure is absolutely continuous with respect to the arclength on this curve. Then the generalized Laplacian is expressed by a sum of normal derivatives of the potential. Such representation was available for smooth curves, and we show it holds for any rectifiable curve in the plane. We also relax the assumptions imposed on the potential.Finding a measure from its potential often leads to another closely related problem of solving a singular integral equation with Cauchy kernel. The theory of such equations is well developed for smooth curves. We generalize this theory to the class of Ahlfors regular curves and arcs, and characterize the bounded solutions on arcs.Mathematic
Kernel methods for system identification and fault detection in nonlinear systems
No full textIn recent years, data-driven methods for the analysis of nonlinear systems have flourished. Derived from machine learning techniques, these methods allow one to analyze, predict, and control the behavior of a nonlinear system without prior model knowledge. The only requirement are data taken from the nonlinear system of interest; moreover, data-driven models are particularly useful for complex nonlinear systems and have seen success in many branches of engineering, from modal decomposition of fluid flows to designing stabilizing controllers for nonlinear systems. In particular, this thesis will focus on the extension of two of these data-driven methods: dynamic mode decomposition (DMD) and kernelized principal component analysis (KPCA).
DMD, which relies on representing a nonlinear system as an infinite-dimensional linear operator, has seen success in predicting the behavior of both continuous-time and discrete-time nonlinear systems without prior model knowledge; however, the extension of DMD methods to discrete-time, controlled nonlinear systems is nontrivial. In this thesis, we develop a novel operator representation of discrete-time, control-affine nonlinear dynamical systems. The representation is learned using recorded snapshots of the system state resulting from arbitrary, potentially open-loop control inputs. We thereby extend the predictive capabilities of dynamic mode decomposition to discrete-time nonlinear systems that are affine in control.
KPCA is typically a data-driven dimensionality reduction technique that allows one to study a nonlinear system via a reduced-order model in a higher-dimensional space; however, KPCA can be used for fault detection in nonlinear systems without prior model knowledge. Reliable operation of automatic systems is heavily dependent on the ability to detect faults in the underlying dynamics. While traditional model-based methods have been widely used for fault detection, data-driven approaches have garnered increasing attention due to their ease of deployment and minimal need for expert knowledge. In the latter portion of this thesis, we develop a novel fault detection method using KPCA with the occupation kernel as the feature map. Occupation kernels result in feature maps that are tailored to the measured data, have inherent noise-robustness due to the use of integration, and can utilize irregularly sampled system trajectories of variable lengths for PCA
Racial ambiguity: Preferences, perceptions, and prejudice towards those who are beyond racial group boundaries
No full textThe United States of America has a long history of discrimination against people of color. With past legislation such as the “one drop rule,†mixed-race individuals have also faced similar levels of prejudice and discrimination to their monoracial minority counterparts. Currently, biracial and multiracial populations have been growing at an exponential rate since the U.S. Census began allowing respondents to select multiple races. This research attempts to add to the current literature by investigating how the majority group (Caucasian) and monoracial minorities perceive and judge racially ambiguous individuals from a multitude of different racial makeups to provide more generalizable evidence of the treatment of multiracial individuals in America by asking 1) Do perceivers judge racially ambiguous/multiracial individuals based on racial stereotypes/ on a rule of hypodescent? 2) Does the majority group have better perceptions/ judgments of other majority group members than racially ambiguous/ multiracial individuals? To answer these questions, participants completed an online survey consisting of various cognitive tasks and questionnaires to determine their perceptions of racially ambiguous individuals to show how the results compare to their judgments of Caucasians. It was found that there were no significant differences in the perceptions of racial minorities and Caucasians, but white participants did report significantly higher positive emotionality towards other Caucasians.Psycholog
Farmers’ food security preparedness based on risk perception
No full textAgriculture is intrinsically exposed to risks that could threaten food security across the globe. In the farming community, it is critical to understand what farmers perceive as the greatest risks to their operation, what activities they use to mitigate for those risks, and where the information about those risks and mitigation activities is obtained. To answer this, a qualitative, deductive, pragmatic study of Arkansas poultry and cattle farmers was conducted utilizing semi-structured interviews and critically examining the transcripts. Protection Motivation Theory is the theoretical lens utilized in this research to investigate farmers’ threat appraisals, coping appraisals, and information seeking attitudes towards risks that may influence their mitigation activities. Farmers state that weather events such as drought, floods, and extreme temperatures; diseases such as Avian Flu; and predators such as coyotes, wild hogs, and even humans are some major concerns for their operation. To mitigate these risks, farmers engage in some mitigation activities such as providing shelters, vaccinating animals, implementing biosecurity practices, getting guard animals, and putting up protective enclosures. While farmers recognize that there is a plethora of risks such as weather, disease, injury, and predators that are potentially destructive to their operation, it is ultimately monetary pressures that are perceived to be the biggest risks to their operations. It is also monetary pressures that influence farmers to engage in mitigation activities for those risks. When the farmers were asked if the government could be of assistance to mitigate the risks, most farmers did not want any government help on their operation, even if they were receiving government grants and subsidies. While this research primarily sought to understand farmers’ risk perceptions and mitigation activities, it also found that the preferred method of informational seeking about risks was dependent on age. Younger generation farmers were more likely to look to social media and the internet for information about risks and mitigation activities, while older generation farmers relied on indigenous knowledge, friends, and family
Climatic challenges and adaptive behaviors: Analyzing the influence of temperature on movement and site selection in cattle and goats under pyric herbivory
No full textThe rangelands of the Southern Great Plains hold significant importance in the region's economy, agriculture, and conservation efforts. However, these rangelands are increasingly impacted by changing climatic conditions, which affect both the ecosystem and the animals that depend on it. Understanding the adaptive behaviors of livestock in response to these climatic changes is crucial for developing sustainable rangeland management practices. Our study aimed to (i) analyze the influence of weather parameters (air temperature and relative humidity) and species type on movement patterns of cattle and goats and (ii) assess how variations in air temperature alter the site selection behavior of these animals. We utilized GPS-telemetry data collected from thirteen cattle and nine goats during the growing season (April to September) from 2020 to 2022. Generalized additive mixed models (GAMMs) were employed, and Akaike Information Criterion (AICc) was used to select the best-fit model. The interaction between air temperature, relative humidity, and species type was the most significant predictor of movement distance (adjusted R² = 0.086). Notably, air temperature emerged as the primary factor influencing the distance moved, surpassing all other measured parameters. Results from resource selection function analysis revealed that time since fire significantly influenced site selection for both species compared to the other environmental variables we examined, with significant negative coefficients (-0.148 for cattle, p < 0.05; -0.089 for goats, p < 0.05). Both cattle and goats preferred woody vegetation and water sources as temperatures increased, with cattle showing a preference for shaded areas at approximately 28°C and goats at around 40°C. These findings emphasize the necessity for adaptive rangeland management strategies that account for species-specific thermoregulatory behaviors and incorporate fire regimes to bolster ecosystem resilience. The insights obtained from this study are instrumental in formulating sustainable rangeland management practices to address the challenges posed by changing climatic conditions, thereby ensuring the conservation and productivity of these vital ecosystems
Failed cotton herbicide rotation restrictions to corn in Oklahoma
No full textThe Oklahoma Cooperative Extension Service periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311
Trends in the prevalence of down syndrome through the COVID-19 era: An examination of the National Survey of Children’s Health, 2016-2022
No full textIntroduction: Down Syndrome (DS) is the clinical manifestation of Trisomy 21 and is the most prevalent chromosomal abnormality in live births, contributing to cardiovascular abnormalities and intellectual disability. Although lifetime prevalence of DS is increased compared to 1950, precise calculations remain stringent due to limited birth registries and limited data availability. The prevalence of DS increases with increasing maternal age and medical advancements leading to longer survival of individuals with DS and decreases with early termination of pregnancy following prenatal diagnosis and decreasing overall birth rates. Since the 1990s, these opposing factors have resulted in a stabilization of DS prevalence. However, the DS prevalence has not been explored throughout the COVID-19 pandemic era. Thus, this study aims to assess changes in the prevalence of DS among children under 18 years of age from 2016 to 2022 and potential disparities by ethnoracial groups.Methods: In this cross-sectional analysis, we analyzed the prevalence of DS using the National Survey of Children’s Health (NSCH) from 2016 through 2022. We used a design-based X² test to determine if the prevalence of DS differed among the years and regression to determine the presence of a trend. We also estimated the prevalence of DS by ethnoracial groupings and tested for differences using a X² test. Survey design and sampling weights provided by the NSCH were employed and adjusted for analyses requiring multiple years of data, according to the NSCH methods manual.Results: From 2016 to 2022, the prevalence of DS exhibited notable fluctuations among the 278,538 individuals sampled, with 603 individuals reported their child having DS. Specifically, the weighted percent of DS prevalence increased overall from 0.14% in 2016 to 0.26% in 2022, revealing a statistically significant 0.022% annual increase via regression analysis (95% CI: 0.0072%-0.037, t=2.92, P=.004; Table 1).By ethnoracial group, the prevalence of DS was highest among American Indian/Alaska Native (0.45%), Native Hawaiian/Other Pacific Islander (0.30%), and Hispanic children (0.22%), though the distribution of DS among ethnoracial groupings was not statistically significant for the combined years (X² (4.83, 1.3e+06)= 0.84, P = .52; Table 2).Conclusion: To our knowledge, this is the first study to assess the prevalence of DS among children through the COVID-19 pandemic, which found a significant increase in its prevalence from 2016 through 2022. While we do not suggest nor are we aware of any correlation between DS prevalence and the COVID-19 pandemic, a variety of social, demographic, genetic, or other factors could be at play to explain this observed increase, such as average maternal age or rates of conception and childbirth.In conclusion, our study contributes to the evolving landscape of DS prevalence and highlights the importance of considering external factors in shaping health outcomes. The observed variations in DS prevalence among diverse populations underscore the complexity of such genetic disorders and emphasize the necessity for multifaceted, inclusive research to guide public health interventions