Bowmanashley9461

Overall, our findings demonstrate that droughts serve as an important underlying factor in promoting HIV transmission among vulnerable women in poor countries, and that food insecurity is a key mechanism in driving this relationship.Collectively, vast quantities of brain imaging data exist across hospitals and research institutions, providing valuable resources to study brain disorders such as Alzheimer's disease (AD). However, in practice, putting all these distributed datasets into a centralized platform is infeasible due to patient privacy concerns, data restrictions and legal regulations. In this study, we propose a novel federated feature selection framework that can analyze the data at each individual institution without data-sharing or accessing private patient information. In this framework, we first propose a federated group lasso optimization method based on block coordinate descent. We employ stability selection to determine statistically significant features, by solving the group lasso problem with a sequence of regularization parameters. To accelerate the stability selection, we further propose a federated screening rule, which can identify and exclude the irrelevant features before solving the group lasso. Here, we use this framework for patch based feature selection on hippocampal morphometry. Shape is characterized through two different kinds of local measures, the radial distance and the surface area determined via tensor-based morphometry (TBM). The method is tested on 1,127 T1-weighted brain magnetic resonance images (MRI) of AD, mild cognitive impairment (MCI) and elderly control subjects, randomly assigned to five independent hypothetical institutions for testing purpose. this website We examine the association of MRI-based anatomical measures with general cognitive assessment and amyloid burden to identify the morphometry changes related to AD deterioration and plaque accumulation. Finally, we visualize the significance of the association on the hippocampal surfaces. Our experimental results successfully demonstrate the efficiency and effectiveness of our method.This study examined the relationship between attachment style and fear of contamination during the COVID-19 pandemic, hypothesizing that anxiously attached participants would be more distressed when their safe space was threatened by someone leaving and returning. During May 2020, n = 355 participants provided demographics, personality, health anxiety scores, attachment styles, political ideology, and attitudes towards the pandemic. In both social media and MTurk subsamples (but not in a subsample from a ListServ of professional psychologists), anxious attachment was a significant predictor of distress above and beyond personality and health anxiety. In addition, political ideology emerged as a consistent predictor of perceptions of the seriousness of COVID-19, even holding the other predictors constant. Understanding an individual's attachment style may be helpful in working with them in their trauma. This research also contributes to early empirical evidence for the impact of political ideology on self-reported attitudes and behaviors during the COVID-19 pandemic.In analysis of binary outcomes, the receiver operator characteristic (ROC) curve is heavily used to show the performance of a model or algorithm. The ROC curve is informative about the performance over a series of thresholds and can be summarized by the area under the curve (AUC), a single number. When a predictor is categorical, the ROC curve has one less than number of categories as potential thresholds; when the predictor is binary there is only one threshold. As the AUC may be used in decision-making processes on determining the best model, it important to discuss how it agrees with the intuition from the ROC curve. We discuss how the interpolation of the curve between thresholds with binary predictors can largely change the AUC. Overall, we show using a linear interpolation from the ROC curve with binary predictors corresponds to the estimated AUC, which is most commonly done in software, which we believe can lead to misleading results. We compare R, Python, Stata, and SAS software implementations. We recommend using reporting the interpolation used and discuss the merit of using the step function interpolator, also referred to as the "pessimistic" approach by Fawcett (2006).We present pore-scale simulations of two-phase flows in a reconstructed fibrous porous layer. The three-dimensional microstructure of the material, a fuel cell gas diffusion layer, is acquired via X-ray computed tomography and used as input for lattice Boltzmann simulations. We perform a quantitative analysis of the multiphase pore-scale dynamics, and we identify the dominant fluid structures governing mass transport. The results show the existence of three different regimes of transport a fast inertial dynamics at short times, characterised by a compact uniform front, a viscous-capillary regime at intermediate times, where liquid is transported along a gradually increasing number of preferential flow paths of the size of one-two pores, and a third regime at longer times, where liquid, after having reached the outlet, is exclusively flowing along such flow paths and the two-phase fluid structures are stabilised. We observe that the fibrous layer presents significant variations in its microscopic morphology, which have an important effect on the pore invasion dynamics, and counteract the stabilising viscous force. Liquid transport is indeed affected by the presence of microstructure-induced capillary pressures acting adversely to the flow, leading to capillary fingering transport mechanism and unstable front displacement, even in the absence of hydrophobic treatments of the porous material. We propose a macroscopic model based on an effective contact angle that mimics the effects of the such a dynamic capillary pressure. Finally, we underline the significance of the results for the optimal design of face masks in an effort to mitigate the current COVID-19 pandemic.Adoption of any agricultural technology depends upon the way in which farmers are being informed about its benefits. Educational status, caste, gender and other social issues also play a significant role in the adoption process. To evaluate the impact of trainings on quality seed production, access to the climate resilient rice seeds, availability of information about seed sources and use of IRRI super bags, a randomized experimental research was carried out over a period of two years across five different states of India. The baseline and a follow-up survey was conducted to capture the farming practices followed by during wet seasons of 2016 and 2017, respectively. The impact of trainings, seed use, information given and agro-based goods was evaluated by comparing the adoption behaviour of treatment and control farmers. There was an increase (28.8%) in the practice of using salt solution to clean seeds primarily due to the impact of quality seed production (QSP) trainings. Female farmers responded more than the male farmers as number of women adopting the practice was higher than men.