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Evaluating the accuracy of allocation to classes in monothetic hierarchical soil classification systems, including the World Reference Base for Soil Classification, US Soil Taxonomy, and Chinese Soil Taxonomy, is poorly-served by binomial methods (correct/incorrect allocation per evaluation observation), since some errors are more serious than others in terms of soil properties, map use, pedogenesis, and ease of mapping. Instead, evaluations should account for the taxonomic distance between classes, expressed as class similarities, giving partial credit to some incorrect allocations. These can then be used in weighted accuracy measures, either direct measures of agreement or measures that account for chance agreement, such as the tau index. Similarities can be determined in one of four ways: (1) by the expert opinion of a soil classification specialist; (2) by the distance between classes in a numerical taxonomy assessment; (3) by distance within a taxonomic hierarchy; or (4) by an error loss function. Expert opinion can be from the point of view of the map user, to assess map utility, or map producer, to assess mapping skill. Examples are given of determining similarity between a subset of Chinese Soil Taxonomy classes by expert opinion and by numerical taxonomy from soil spectra, and then using these for weighted accuracy assessment. A method for assessing the accuracy of probabilistic predictions of several classes at a location is also proposed. [ABSTRACT FROM AUTHOR]

Irisin is a hormone-like molecule mainly released by skeletal muscles in response to exercise, which is proposed to induce the 'browning' of white adipose tissue. Since its identification, irisin was reported to be closely associated with many metabolic diseases, including type 2 diabetes mellitus (T2DM), obesity, cardiovascular disease (CVD), and metabolic bone diseases. In recent years, irisin has attracted increasing research interest, and numerous studies have been published in this field. Thus, it is essential to identify the current research status of irisin and measure research hotspots and possible future trends. In this study, by utilizing two visualization software named CiteSpace and VOSviewer, we analyzed 1510 Web of Science publications on irisin published from 2012 to 2021. Our results show that the number of irisin-related articles published annually has increased significantly. China participates in the most studies, followed by the United States and Turkey. Firat University, Harvard University, and Shandong University are three major institutions with larger numbers of publications. The analysis of keywords co-occurrence indicates that insulin resistance, inflammation, and circulating irisin levels in serum are the research hotspots. Apoptosis, BDNF, and osteoporosis will likely become the focus of future research related to irisin. Overall, this study may provide helpful insights for researchers to understand the current research situation and identify the potential frontiers of irisin.

Objective To assess the psychological status of staff at the centers for disease control and prevention(CDC) in Sichuan during the outbreak of coronavirus disease 2019(COVID-19) and explore the influencing factors. Methods The staff at Sichuan provincial,municipal,and county(district)-level CDC were selected by convenience sampling.Their basic information,work status,training status,work difficulties,and support from the work group were collected from the self-filled questionnaires online.The Generalized Anxiety Disorder Scale and the 9-question Patient Health Questionnaire were respectively employed to measure the anxiety and depression of the staff.The stepwise Logistic regression was carried out to analyze the influencing factors of anxiety and depression in CDC staff. Results Among the 653 staff,58.35% and 50.06% presented anxiety and depression,respectively.The regression results showed that age( OR =0.95,95% CI =0.92-0.97) and mental support from the work group( OR =0.61,95% CI =0.45-0.82) were the protective factors while physical fatigue( OR =1.82,95% CI =1.20-2.74),work pressure( OR =1.61,95% CI =1.21-2.12),and insufficient protective equipment( OR =1.92,95% CI =1.06-3.49) were the risk factors for depression of CDC staff.Age( OR =0.97,95% CI =0.94-0.99),length of sleep per day( OR =0.74,95% CI =0.56-0.96),and participation in technical training( OR =0.33,95% CI =0.12-0.95) were the protective factors while mental fatigue( OR =1.68,95% CI =1.18-2.41),work pressure( OR =2.94,95% CI =2.08-4.17),and unclear incentive system for overtime( OR =1.99,95% CI =1.23-3.23) were the risk factors for the anxiety of CDC staff. Conclusion The anxiety and depression status of CDC staff during the COVID-19 outbreak were worrying,which were mainly affected by age,sleep,supply of protective equipment,incentive system,fatigue,and work pressure.