SHAREOK Repository
Not a member yet
49261 research outputs found
Sort by
The Developmental Trajectory of Friendship Jealousy in Adolescence: The Role of Attachment Security and Emotion Regulation
Get PDFThe current study investigated the developmental trajectory of friendship jealousy across a one-year interval during adolescence. It also explored the association of attachment security with friendship jealousy while testing the potential mediating role of emotion regulation. A total of 1,158 middle school students participated in this study at three time points. A set of self-report questionnaires were adopted to assess attachment security to mother, father, and close friends, emotion regulation in general, emotion regulation for anger and sadness, and friendship jealousy. Friendship jealousy tended to be stable for girls from 7th to 8th grade. There were negative associations between parental attachment security and friendship jealousy at all three time points, but parental attachment security did not predict friendship jealousy one year later. Attachment security to close friends negatively predicted friendship jealousy concurrently and one year later. The mediating role of emotion regulation was not supported in the longitudinal analyses
Integrated Hydrologic Validation of Satellite Precipitation over the United States
Get PDFIncreasing precipitation extremes across the globe will naturally lead to not only increased flooding but an increase in the occurrences of flash floods, with assessment and prediction of these events becoming more critical every year. Floods are a natural facet of the water cycle and serve as an unmistakable indicator of changes in that cycle globally. As such, the characterization and monitoring of floods also needs to be undertaken at a global scale especially in the face of an ever-changing climate. A key tool in that process is understanding the inherent capabilities of satellite-based precipitation products in their ability to model flood characteristics. Hence, this work focuses on assessing the innate differences in the high-resolution Multi-Radar Multi-Sensor (MRMS) system and the Integrated Multi-satellitE Retrievals for GPM (IMERG) suite of satellite products when used as precipitation forcings to simulate hydrologic outputs through the operational Ensemble Framework for Flash Flood Forecasting (EF5) hydrologic framework. The biases of precipitation presented by satellite products has been well studied, but less has been done to assess how significant these errors persist into physical hydrologic processes especially when compared to ground-based radar estimates. By using each precipitation product as an individual forcing for EF5, the simulated hydrographs can be post-processed where discrete simulated flood events are determined and matched, assessing the ability of each precipitation product to accurately generate reliable simulated representations of flood characteristics. Relationships between these flood characteristics, such as peak flow and flood duration, and physical basin characteristics are investigated. Steps are also undertaken in reimagining the calculation for a timing characteristic of floods in order to increase the accuracy of the estimates, allowing for future integration into the methodologies presented herein. Increasing knowledge regarding the capabilities or deficiencies of satellite precipitation products with respect to flash flood modeling will have implications on the ability to characterize flood events over areas with little or no coverage by ground-based precipitation monitoring networks and subsequently improve flood forecasting operations globally
Effects of Hydraulic Design and Retention Time on Removal of Constituents of Emerging Concern from Secondarily Treated Wastewater Effluent in Treatment Wetland Mesocosms
No full textTreatment wetlands (TWs) are an ecologically engineered, natural infrastructure approach designed specifically for water quality improvement via natural biogeochemical, physiochemical, and microbiological processes. The natural processes in TWs attenuate nutrients, total suspended solids, metals, and other chemical constituents. Along with more traditional water quality parameters, TWs have been shown to remove many types of constituents of emerging concern (CECs), a wide range of pharmaceutical, industrial, and agricultural compounds that are poorly removed in traditional wastewater treatment. The City of Norman, Oklahoma is considering the implementation of Indirect Potable Reuse (IPR) to augment water supply, and TWs are a possible treatment step for the removal of CECs from treated wastewater before discharge to a water supply. Hydraulic scheme (free-water surface (FWS), subsurface flow (SSF), and an open water control (OWC)), vegetation presence (planted and unplanted), and hydraulic retention time (HRT) (10-days, 5-days, and 3-days) were designed and manipulated in a 25-mesocosm TW compound to determine the impact of these design factors on the removal of the anti-seizure medication, carbamazepine, from secondarily treated wastewater. Traditional wastewater constituents like biochemical oxygen demand (BOD) and total suspended solids (TSS) and common physiochemical parameters were also monitored throughout the experiment. Carbamazepine concentrations were analyzed in the influent and effluent from the batch-reactor TW systems using enzyme-linked immunosorbent assay (ELISA) test kits. Longer HRTs were associated with increases in carbamazepine removal efficiency. TW mesocosm hydraulic design (FWS or SSF) was most significant to effluent carbamazepine concentration during the shortest HRT, 3-days (p = 0.005). The presence of vegetation did not significantly affect removal efficiency during this experiment (p = 0.975). Greater carbamazepine removal efficiencies were seen in this experiment than in previous studies, which could be due to the longer HRTs in the mesocosm-scale system or the availability of sorption sites on the fresh substrate. The results of this experiment provided promise for the effectiveness of TWs for the removal of carbamazepine and established a long-term experimental site for future TWs experiments
Efforts towards the synthesis of furan containing bioactive compounds
Get PDFFuran is a valuable subunit in pharmaceutical chemistry. However, there are still
challenges in synthesizing furan-containing compounds. Two approaches have been
attempted to address this issue. 1. Using enynal molecules as a carbene precursor for
synthesizing functionalized furyl-pyrrolidines. A cascade approach was developed for
synthesizing functionalized (2-furyl)-2-pyrrolidines, showcasing both convergence and
remarkable stereoselectivity. This domino process proceeds through an N–H insertion
into enynal-derived metal-carbenoid, followed by an intramolecular aldol reaction to
provide pyrrolidines with high diastereoselectivity (>98:2). This chemistry utilizes Earthabundant zinc chloride as a catalyst with loading as low as 1 mol%. This method operates
under mild conditions and demonstrates high chemoselectivity by accommodating
substrates bearing functionalities such as free alcohols, alkenes, and alkynes. 2 Towards
the total synthesis of collybolide. Collybolide is a natural product that was first isolated
from the fungus Collybia maculata. It has attracted attention due to its potential
therapeutic applications, particularly in the treatment of pain and inflammation. Its
complex structure, however, makes it a challenging target for total synthesis. Our route
starts from simple glutamic acid. This route aimed to minimize the use of chiral reagents
and catalysts to install all 6 stereocenters in Collybolide. So far, after 11 reactions, we
have achieved the intermediate having 15 out of 22 carbon atoms and 4 out of 6
stereocenters in Collybolide without using any chiral reagents and catalysts other than
glutamic acid. One of the significances of this route is that different from the traditional
synthetic route, we installed furan moiety at a very early stage. Furan is known for its
instability, however, in our route, it is stable throughout the synthetic pathway
Developing Novel Computer Aided Diagnosis Schemes for Improved Classification of Mammography Detected Masses
Get PDFMammography imaging is a population-based breast cancer screening tool that has greatly aided in the decrease in breast cancer mortality over time. Although mammography is the most frequently employed breast imaging modality, its performance is often unsatisfactory with low sensitivity and high false positive rates. This is due to the fact that reading and interpreting mammography images remains difficult due to the heterogeneity of breast tumors and dense overlapping fibroglandular tissue. To help overcome these clinical challenges, researchers have made great efforts to develop computer-aided detection and/or diagnosis (CAD) schemes to provide radiologists with decision-making support tools. In this dissertation, I investigate several novel methods for improving the performance of a CAD system in distinguishing between malignant and benign masses.
The first study, we test the hypothesis that handcrafted radiomics features and deep learning features contain complementary information, therefore the fusion of these two types of features will increase the feature representation of each mass and improve the performance of CAD system in distinguishing malignant and benign masses. Regions of interest (ROI) surrounding suspicious masses are extracted and two types of features are computed. The first set consists of 40 radiomic features and the second set includes deep learning (DL) features computed from a pretrained VGG16 network. DL features are extracted from two pseudo color image sets, producing a total of three feature vectors after feature extraction, namely: handcrafted, DL-stacked, DL-pseudo. Linear support vector machines (SVM) are trained using each feature set alone and in combinations. Results show that the fusion CAD system significantly outperforms the systems using either feature type alone (AUC=0.756±0.042 p<0.05). This study demonstrates that both handcrafted and DL futures contain useful complementary information and that fusion of these two types of features increases the CAD classification performance.
In the second study, we expand upon our first study and develop a novel CAD framework that fuses information extracted from ipsilateral views of bilateral mammograms using both DL and radiomics feature extraction methods. Each case in this study is represented by four images which includes the craniocaudal (CC) and mediolateral oblique (MLO) view of left and right breast. First, we extract matching ROIs from each of the four views using an ipsilateral matching and bilateral registration scheme to ensure masses are appropriately matched. Next, the handcrafted radiomics features and VGG16 model-generated features are extracted from each ROI resulting in eight feature vectors. Then, after reducing feature dimensionality and quantifying the bilateral asymmetry, we test four fusion methods. Results show that multi-view CAD systems significantly outperform single-view systems (AUC = 0.876±0.031 vs AUC = 0.817±0.026 for CC view and 0.792±0.026 for MLO view, p<0.001). The study demonstrates that the shift from single-view CAD to four-view CAD and the inclusion of both deep transfer learning and radiomics features increases the feature representation of the mass thus improves CAD performance in distinguishing between malignant and benign breast lesions.
In the third study, we build upon the first and second studies and investigate the effects of pseudo color image generation in classifying suspicious mammography detected breast lesions as malignant or benign using deep transfer learning in a multi-view CAD scheme. Seven pseudo color image sets are created through a combination of the original grayscale image, a histogram equalized image, a bilaterally filtered image, and a segmented mass image. Using the multi-view CAD framework developed in the previous study, we observe that the two pseudo-color sets created using a segmented mass in one of the three image channels performed significantly better than all other pseudo-color sets (AUC=0.882, p<0.05 for all comparisons and AUC=0.889, p<0.05 for all comparisons). The results of this study support our hypothesis that pseudo color images generated with a segmented mass optimize the mammogram image feature representation by providing increased complementary information to the CADx scheme which results in an increase in the performance in classifying suspicious mammography detected breast lesions as malignant or benign.
In summary, each of the studies presented in this dissertation aim to increase the accuracy of a CAD system in classifying suspicious mammography detected masses. Each of these studies takes a novel approach to increase the feature representation of the mass that needs to be classified. The results of each study demonstrate the potential utility of these CAD schemes as an aid to radiologists in the clinical workflow
A framework of subseasonal-to-seasonal (S2S) ensemble hydrological forecasting at a watershed scale using dynamical precipitation forecast: forecast verification, adaptation, and streamflow prediction
No full textAccurate and reliable streamflow forecasts, especially at Subseasonal-to-Seasonal (S2S) timescale (spanning 10 to 30 days into the future) could greatly benefit various human socio-economic activities. The Ensemble Streamflow Prediction (ESP) framework is commonly applied and currently in operation for streamflow predictions at S2S timescale. However, ESP’s reliance on the randomly resampled historical precipitation has limited its performance and compromised its reliability. As an alternative, the S2S precipitation forecasts derived from coupled general circulation models (GCMs) present an opportunity to overcome the limitations of randomly resampled precipitation in the ESP. Despite this potential, the application of available S2S precipitation forecasts in hydrology has not undergone a comprehensive assessment. Therefore, in this dissertation, multiple S2S precipitation forecast products from the North America Multi-Model Ensemble Phase II (NMME-2) have been collected and analyzed to validate their forecast performance over the contiguous United States (CONUS) as well as to test their hydrologic applicability at a watershed scale. The introductory chapter provides the context and outlines the research questions that motivate this dissertation (Chapter 1). A comprehensive evaluation of the performance of the raw S2S precipitation forecasts from NMME-2 over CONUS is conducted (Chapter 2). This dissertation further validates the applicability and superiority of S2S precipitation through a standard forecast adaptation technique under the ESP framework at four selected experimental watersheds (Chapter 3). In addressing the limitations of extreme precipitation event prediction, a novel Machine Learning (ML)-based post-processing technique is developed to improve the predictive skill of available S2S precipitation forecasts over CONUS (Chapter 4). This developed ML-based technique is subsequently applied to the four aforementioned watersheds, effectively adapting raw S2S precipitation for streamflow prediction within the ESP framework (Chapter 5). In conclusion, this dissertation underscores its major findings and offers insights for future research directions (Chapter 6). Through its structured exploration of available S2S precipitation forecasts from NMME-2 and their hydrological application, this dissertation contributes to advancing the field of streamflow prediction and offers recommendations for enhancing streamflow forecast accuracy and reliability
Coaching in the use of a trauma-informed intervention
Get PDFWhile the literature supports the claim that instructional coaching is beneficial to classroom teachers in the improvement of their use of evidence-based strategies, there is not a plethora of research studies that have specifically applied coaching to trauma-informed strategies at the individual teacher level. The purpose of this single-case, Multiple Baseline Design study is to determine what effect coaching might have on teachers’ use of a trauma-informed response strategy. Statistical and visual analysis indicates that it was effective and a functional relation was found between teachers’ use of a trauma-informed response strategy and instructional coaching. Maintenance and Social Validity data were collected and analyzed as well. When coaching was provided to teachers on how to use a specific trauma-informed strategy, results indicated a functional relation and effect sizes, ranging from small to large, for the three classroom teachers. The implications of this study highlight the need for education administrators to consider incorporating coaching into their professional development models to assist teachers in implementing trauma-informed strategies. Limitations of this study were noted and the implications for future research were addressed.
Keywords: *coaching, *teachers, *trauma-informed intervention
Experiences of Aging in Society Project, July 2023 Report
No full textThe Experiences of Aging in Society (EOA) project is investigating how societal beliefs about aging and older adults may affect health. Ageism is believed to increase risk for many health problems commonly thought to be a natural consequence of getting older. Ageism refers to stereotypes, prejudice, and discrimination related to old age, aging, and older adults. On the other hand, many older adults also identify benefits associated with aging that may protect their health. Since 2021, our team has been collecting information from a diverse group of adults ages 50+ about their feelings, expectations, and experiences with growing older. Thanks to your help, we have been able to research how positive and negative experiences of aging may affect people’s health, both immediately and in the future. We are also studying similarities and differences across several US racial and ethnic groups. Project results will inform programs, policies, and research that promote the health and wellbeing of older adults.Study conducted by the Stress & Health Disparities Lab at the University of Oklahoma & supported by the Vice President for Research and Partnerships of the University of Oklahoma (2021 & 2023JFF), the Michigan Integrative Well-Being and Inequality Program (R25-AT010664), the Michigan Center for Urban African American Aging Research (5P30 AG015281), & ResearchMatch.N
Impact of Microphysics Parameterization Schemes on the Assimilation of GOES-16 All-Sky Infrared Radiances for a Bow Echo Analysis and Prediction
Get PDFAssimilating infrared brightness temperature (BT) from the water vapor sensitive channels of the GOES-16 Advanced Baseline Imager (ABI) has been shown by past studies to improve the analysis and prediction of severe weather events. These studies are limited to using a single microphysics scheme. Microphysics schemes are expected to affect bow echo dynamics and BT. Therefore, this study aims to investigate how assimilating GOES-16 ABI infrared BT with different microphysics schemes affects the analysis and prediction of the 3 May 2020 bow echo case. The Gridpoint Statistical Interpolation based Ensemble Kalman Filter (GSI-EnKF) system and Weather Research and Forecasting (WRF) model are utilized to conduct data assimilation (DA) experiments using Thompson, WDM6, NSSL, and Morrison microphysics schemes.
Correlation structures between BT and model state variables indicate that assimilating infrared BT can adjust bowing MCS dynamics via latent cooling and the rear inflow jet. Such corrections during DA cycling enhance the rear inflow jet and bow echo size, primarily for microphysics schemes featuring faster hydrometeor fall velocity and stronger latent cooling. The improved analyses lead to better forecasts of the bow echo’s shape, size, timing of the bowing process, and wind speeds. Substituting a larger microphysics-dependent effective radius for a constant default value increases prior BT, the magnitude of BT innovations, and accumulated impact on the rear inflow jet, especially for the WDM6 and Morrison schemes. In the subsequent forecasts, incorporating microphysics-dependent effective radius further improves the experiment using the Morrison scheme but degrades it when using the WDM6 scheme