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Vegetation water content (VWC) is the key input parameter for a soil moisture retrieval algorithm based on microwave remote sensing, and VWC uncertainty can limit the estimated accuracy of soil moisture. There has been little research on VWC algorithm development and validation in China, and the uncertainty of the VWC estimation method has not been well evaluated. Therefore, the aim of this study is to evaluate the uncertainty of the VWC estimation method used in the SMAP (Soil Moisture Active Passive) algorithm on three spatial scales (the point-scale, 30 m scale, and 1 km scale) for maize in northeast China. Results from three ground experimental datasets showed that the SMAP VWC estimation method was strongly biased with an average overestimation of 1.16 kg m?2,1.04 kg m?2, and 1.13 kg m?2 for the point-scale, 30 m scale, and 1 km scale respectively, and maximum bias occurred in the mid-stage of maize. Also, a new power relationship between NDVI (Normalized Difference Vegetation Index) and VWC was proposed for the 30 m scale based on Sentinel 2 NDVI and field VWC values from 2017 experiment, with respective R2 (coefficient of determination) and Root Mean Squared Error (RMSE) values of 0.80 and 0.67 kg m?2. The results confirmed that this power relationship was still suitable for VWC estimation at the 1 km scale, and it has smaller bias than the original SMAP VWC method. Future work will be carried out to evaluate the applicability of this VWC estimation method over a lager region. It is expected that it can improve the accuracy of soil moisture by providing high precision VWC input parameters.  相似文献   
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Based on the physical randomization of completely randomized experiments, in a recent article in Statistics in Medicine, Rigdon and Hudgens propose two approaches to obtaining exact confidence intervals for the average causal effect on a binary outcome. They construct the first confidence interval by combining, with the Bonferroni adjustment, the prediction sets for treatment effects among treatment and control groups, and the second one by inverting a series of randomization tests. With sample size n, their second approach requires performing O(n4)randomization tests. We demonstrate that the physical randomization also justifies other ways to constructing exact confidence intervals that are more computationally efficient. By exploiting recent advances in hypergeometric confidence intervals and the stochastic order information of randomization tests, we propose approaches that either do not need to invoke Monte Carlo or require performing at most O(n2)randomization tests. We provide technical details and R code in the Supporting Information . Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
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In a biological microenvironment, free fatty acids (FFA) as ubiquitous biological molecules might interact with nanoparticles (NPs) and consequently change the toxicological responses. However, whether the chemical structures of FFA could influence their interactions with NPs remain unknown. This study investigated the interactions between ZnO NPs and saturated or unsaturated FFA (complexed to BSA), namely stearic acid (SA, C18:0), oleic acid (OA, C18:1), and α-linolenic acid (ALA, C18:3). It was shown that BSA, SA, OA, and ALA increased the atomic force microscope (AFM) heights as well the polydispersity index (PDI) of ZnO NPs. BSA modestly protected THP-1 macrophages from ZnO NP exposure, whereas OA and ALA led to relatively less cyto-protective effects of BSA. Moreover, only co-exposure to ZnO NPs and SA significantly promoted the release of interleukin-8. BSA, SA, OA, and ALA equally changed intracellular ROS and Zn ions associated with ZnO exposure, but co-exposure to ZnO NPs and OA/ALA particularly activated the expression of endoplasmic reticulum stress-apoptosis genes. In combination, these results showed that FFA could influence the colloidal aspects and toxicological signaling pathway of ZnO NPs, which is dependent on the number of unsaturated bonds of FFA.  相似文献   
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