Uncertainty evaluation at three spatial scales for the NDVI-based VWC estimation method used in the SMAP algorithm

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.     

Exact confidence intervals for the average causal effect on a binary outcome

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.     

A randomized study on the effect of modified behavioral activation treatment for depressive symptoms in rural left-behind elderly

Objective: To evaluate the effectiveness of a modified behavioral activation treatment (MBAT) intervention on reducing depressive symptoms in rural left-behind elderly.

Method: This is a randomized study registered in Chinese Clinical Trial Registry (ChiCTR-IOR-17011289). Eighty rural left-behind elderly people who had a Geriatric Depression Scale (GDS) score between 11 and 25 were randomly assigned to the intervention (n?=?40) and control group (n?=?40). The intervention group received both MBAT and regular treatment for 8 weeks while the control group received regular treatment. Both groups were assessed with the GDS, Beck Anxiety Inventory (BAI), and Oxford Happiness Questionnaire (OHQ) at baseline, immediately post-intervention, and at 3 months post-intervention.

Results: There were a total of 73 participants that completed the intervention. The scores of GDS and BAI decreased significantly, but the scores of OHQ increased significantly in the intervention group after 8 sessions of MBAT (P?<?.01). The reduction in depression symptoms after the intervention was maintained at the 3-month follow-up. Significant differences in GDS, BAI, and OHQ scores were observed between the intervention group and the control group (P?<?.01).

Conclusion: MBAT produced a significantly greater reduction in depressive symptoms than regular care in rural left-behind elderly.

Clinical or methodological significance of this article: A modified behavioral activation (BA) psychotherapy can significantly reduce the recurrence and seriousness of depression symptoms in the left-behind elderly with mild to moderate depression. This study also suggests that further study of the MBAT as an intervention will provide a direction for the management of mental health in rural left-behind elders.     

新型冠状病毒肺炎出院患者生活质量及影响因素研究

目的:了解新型冠状病毒肺炎(COVID-19)患者出院后的生活质量及其影响因素,为优化早期干预方案,预防社区生活受限,制定相应社区康复措施提供依据。方法:选择2020年3—4月在武汉华润武钢总医院治愈出院的COVID-19患者57例,于2020年4—5月通过"问卷星"平台采用简明健康状况调查量表(SF-12V2)调查患者的生活质量;采用焦虑自评量表(SAS)调查患者的焦虑状态;采用抑郁自评量表(SDS)调查患者的抑郁状态;采用呼吸困难指数量表(mMRC)调查患者的呼吸困难程度。比较不同特征COVID-19患者生活质量的差异;分析患者生活质量与焦虑、抑郁和呼吸困难程度的相关性及其相关的影响因素。结果:共发放57份调查问卷,剔除重复及无效问卷3份,获得有效问卷54份,问卷有效率达94.74%。(1)COVID-19出院后患者生活质量情况:生理总评分和心理总评分分别为(37.02±12.32)分、(38.46±14.42)分;呼吸困难等级0~3级的分别为3例(5.56%)、45例(83.33%)、5例(9.26%)、1例(1.85%);有19例(35.19%)存在焦虑情绪(SAS≥50分)和抑郁情绪(SDS≥53分)。(2)不同特征COVID-19患者生活质量比较:不同疾病分型的患者在生理总评分方面差异有统计学意义(P<0.05)。(3)生活质量与焦虑、抑郁和呼吸困难程度的相关性分析:Pearson相关分析结果显示,SF-12V2生理总评分与焦虑程度(r=-0.34,P=0.011)和呼吸困难程度(r=-0.39,P=0.003)之间存在负相关性,SF-12V2心理总评分与焦虑程度(r=-0.46,P=0.001)和抑郁程度(r=-0.40,P=0.002)之间存在负相关性。(4)COVID-19患者生活质量的影响因素分析:多元线性回归分析显示,性别(β=8.27)、抑郁程度(β=-0.34)和疾病分型(β=-11.68)是患者SF-12V2生理总评分的重要决定因素(P<0.05);焦虑程度(β=-0.62)是患者SF-12V2心理总评分的重要决定因素(P<0.05)。结论:COVID-19出院患者存在呼吸困难、焦虑抑郁情绪和生活质量下降的问题;性别、疾病分型、抑郁程度和焦虑程度是COVID-19患者生活质量下降的重要因素。COVID-19患者(特别是女性患者和重型患者)出院后要尽早进行抑郁症和焦虑症的筛查和干预,减少患者负性情绪,鼓励患者适当参与康复训练,提高呼吸功能,从而促进生活质量提高。     

Toxicity of ZnO nanoparticles (NPs) to THP-1 macrophages: interactions with saturated or unsaturated free fatty acids

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.