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The effect of impurity element Fe on corrosion behavior of AZ61 magnesium alloys in various states has been investigated by immersion test and hydrogen evolution measurements in 3.5% sodium chloride solution. The corrosion rate is found to relay on the impurity Fe concentration in the alloys and decreases with decreasing Fe content. When Fe content drops from 150 ppm to 10 ppm, the corresponding corrosion rates under as-cast and solution treatment conditions are reduced from 8.54 mm/a and 8.61 mm/a to 2.54 mm/a and 0.21 mm/a, respectively. The corrosion pattern of the AZ61 alloys is the localized corrosion, and the galvanic couples are formed among the impurity particles, second-phase particles and the matrix. The Fe impurity particles tend to act as main cathodic to form micro-galvanic cell with the α-Mg matrix, which is harmful for corrosion resistance of AZ61 alloy.

The g-C3N4/MoS2 nanosheet heterojunction was prepared via a facile ball milling method. The microstructure and morphology of the composite were characterized by X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), UV-vis diffuse reflectance spectroscopy (DRS) and photoluminescence (PL) spectroscopy. The photocatalytic activities were evaluated by the degradation of organic Rhodamine B (RhB) under visible light irradiation. The results indicate that MoS2 nanosheets are successfully coupled into g-C3N4 to form a C3N4/MoS2 heterojunction. The kinetic constant of RhB degradation with g-C3N4/MoS2 nanosheets-2 wt% heterojunction (0.0368 min−1) is about 4.3 times as high as that of the bulk g-C3N4 (0.00840 min−1). The enhanced photocatalytic activities can be mainly ascribed to the efficient separation and transportation of photo-induced electron-hole pairs. The possible photocatalytic mechanism of composites was proposed according to the light trapping experiment.

In order to evaluate the land quality geochemical survey achievement in the service of the accurate management of urban land resources, the initial area of the Xiong'an New District as urbanization pathfinder in China is chosen as the research subject. The sample points were set by differential classification, and the spatial interpolation accuracy of the soil elements at a plot scale and a quantitative assessment of the consistency of the land plot (pattern spot) prediction evaluation were studied under the conditions of different sampling densities. The regional geochemical variation values randomly distributed on the plane can be reflected quantitatively by differential classification sampling, which can meet the basic demand of the quality attribute of a single plot (map spot) by the accurate management of urban land resources. The spatial variability of soil elements is mostly middle to moderate, and Cd, Cu, Pb, Hg, Se, N, P, and other elements of high spatial variability are affected by human industrial and agricultural production activities. Under the same sampling density, the larger the element variation coefficient, the worse the spatial interpolation accuracy. Although the interpolation accuracy of the same element index is affected by the sampling density, the increase in the sampling density could not identify the continuous component on the structure of the soil element content. The soil environment is clean, and the heavy metal content is lower than the GB15618-2018 standard. The interpolation results are basically consistent with the grading results of the measured values, while the contents of N, P, and K of the nutrient indices vary greatly, and the predicted and measured geochemical grades of the plots (map spot) differ substantially under the influence of factors such as human disturbance and spatial variability. The quantitative evaluation of the six different sampling densities indicates that the 16 points·km

Machine learning methods offer great promise for fast and accurate detection and prognostication of COVID-19 from standard-of-care chest radiographs (CXR) and computed tomography (CT) images. Many articles have been published in 2020 describing new machine learning-based models for both of these tasks, but it is unclear which are of potential clinical utility. In this systematic review, we search EMBASE via OVID, MEDLINE via PubMed, bioRxiv, medRxiv and arXiv for published papers and preprints uploaded from January 1, 2020 to October 3, 2020 which describe new machine learning models for the diagnosis or prognosis of COVID-19 from CXR or CT images. Our search identified 2,212 studies, of which 415 were included after initial screening and, after quality screening, 61 studies were included in this systematic review. Our review finds that none of the models identified are of potential clinical use due to methodological flaws and/or underlying biases. This is a major weakness, given the urgency with which validated COVID-19 models are needed. To address this, we give many recommendations which, if followed, will solve these issues and lead to higher quality model development and well documented manuscripts., 35 pages, 3 figures, 2 tables, updated to the period 1 January 2020 - 3 October 2020

Supplemental material, sj-pdf-3-tar-10.1177_1753466620986391 for CARE: an observational study of adherence to home nebulizer therapy among children with asthma by Deyu Zhao, Dehui Chen, Ling Li, YingXue Zou, Yunxiao Shang, Chonglin Zhang, Li Zhang, Jiahua Pan, Qiang Chen, Tao Ai and Qian Ni in Therapeutic Advances in Respiratory Disease

Supplemental material, sj-pdf-1-tar-10.1177_1753466620986391 for CARE: an observational study of adherence to home nebulizer therapy among children with asthma by Deyu Zhao, Dehui Chen, Ling Li, YingXue Zou, Yunxiao Shang, Chonglin Zhang, Li Zhang, Jiahua Pan, Qiang Chen, Tao Ai and Qian Ni in Therapeutic Advances in Respiratory Disease

Supplemental material, sj-pdf-2-tar-10.1177_1753466620986391 for CARE: an observational study of adherence to home nebulizer therapy among children with asthma by Deyu Zhao, Dehui Chen, Ling Li, YingXue Zou, Yunxiao Shang, Chonglin Zhang, Li Zhang, Jiahua Pan, Qiang Chen, Tao Ai and Qian Ni in Therapeutic Advances in Respiratory Disease

Supplemental material, sj-pdf-4-tar-10.1177_1753466620986391 for CARE: an observational study of adherence to home nebulizer therapy among children with asthma by Deyu Zhao, Dehui Chen, Ling Li, YingXue Zou, Yunxiao Shang, Chonglin Zhang, Li Zhang, Jiahua Pan, Qiang Chen, Tao Ai and Qian Ni in Therapeutic Advances in Respiratory Disease

Imaging-guided percutaneous microwave ablation (MWA) with high thermal efficiency comprises rapid, successful management of small renal cell carcinomas (RCCs) in selected patients. Ultrasound Committee of Chinese Medical Association, Interventional Oncology Committee of Chinese Research Hospital Association developed evidence-based guidelines for MWA of RCCs after systematically reviewing the 1969–2019 literature. Systematic reviews, meta-analyses, randomized controlled trials, cohort, and case–control studies reporting MWA of RCCs were included and levels of evidence assessed. Altogether, 146 articles were identified, of which 35 reported percutaneous MWA for T1a RCCs and 5 articles for T1b RCCs. Guidelines were established based on indications, techniques, safety, and effectiveness of MWA for RCCs, with the goal of standardizing imaging-guided percutaneous MWA treatment of RCCs.Key pointsMicrowave ablation is recommended for managing small renal cell carcinoma in selected patients.Imaging protocols are tailored based on the procedural plan, guidance, and evaluation.Patient’s selection evaluation, updated technique information, clinical efficacy, and complications are recommended to standardize management.A joint task force (multidisciplinary team) summarized the key elements of the standardized report. Microwave ablation is recommended for managing small renal cell carcinoma in selected patients. Imaging protocols are tailored based on the procedural plan, guidance, and evaluation. Patient’s selection evaluation, updated technique information, clinical efficacy, and complications are recommended to standardize management. A joint task force (multidisciplinary team) summarized the key elements of the standardized report.