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BACKGROUND Post-stroke depression (PSD) was one of the most prevalent and serious neuropsychiatric effects after stroke. Nevertheless, the association between liver function test indices and PSD remains elusive. OBJECTIVE The aim of this study was to explore the relationship between the liver function test indices and PSD, and construct a prediction model for PSD. METHODS Patients were selected from 7 affiliated medical institutions of Chongqing Medical University from January 1, 2015 to January 1, 2021. Variables including demographic characteristics and liver function test indices were collected from the hospital electronic medical record system. Predictors were selected using univariate analysis, least absolute shrinkage and selection operator. Subsequently, multivariate logistic regression was adopted to build the prediction model. Furthermore, receiver operating characteristic curve (ROC), sensitivity, specificity, accuracy, calibration curve analysis and decision curve analysis were used to assess the performance of the prediction model. RESULTS A total of 464 PSD and 1621 stroke patients met the inclusion criteria. Six liver function test items, namely AST, ALT, TBA, TBil, TP, ALB/GLB, were closely associated with PSD, and included for the construction of the prediction model. The ROC curve was 0.751 in the training set and 0.708 in the validation set, respectively. Furthermore, the calibration curve analysis plot and decision curve analysis plot showed that the prediction model featured a moderate clinical practicability. CONCLUSIONS The prediction model constructed using these six predictors displayed a medium prediction ability, which could be used for the participating hospital units or individuals by mobile phone or computer.

Given the global ecological environment deteriorating, the ESG (Environmental, Social and Governance) concept advocates that economic growth and environmental protection must go hand in hand. Green taxes, in particular, are critical to economic development as they serve as a key lever for the government in regulating the national economy and improving environmental quality. This paper aims to examine the pollution reduction effect of green taxation in China. We constructed fixed effect models using provincial panel data from 2012 to 2017 to empirically examine the effect of green taxation - including environment protection tax, consumption tax, resource tax and vehicle purchase tax - on pollution emissions. The findings show that environmental protection tax has a significant inhibitory effect on exhaust gas emissions but a poor inhibitory effect on wastewater and industrial solid waste emissions. Other green taxes - consumption tax, resource tax, and vehicle purchase tax - do not have an ideal inhibitory effect on pollution emissions. The paper concludes with policy recommendations organized around improving the environmental protection tax, actively promoting the ESG concept, and optimizing the top-level design of the green tax system.

The contradiction among population, resource and environment has become increasingly evident that requires the manufacturing industry to improve the compatibility of its activities and the environment. Green supply chain management is a valid way to resolve the conflict between manufacturing industry and the environment based on a systems point of view and the concept of integration. In the content of this paper, the concept of green supply chain would be combined with the method of DEA and it is established from the perspective of input and output in order to offer academic reference and practical guidance to automobile manufacturing industry for moving toward green development that is a set of complete carbon performance evaluation system of automobile manufacturing industry in green supply chain.

China launched its carbon emissions trading market and established a national carbon emissions trading system in 2017, both of which call for accurate carbon audits to reflect carbon emissions of enterprises. Drawing on the carbon audit theory and the driving force-state-response (DSR) model, this paper aims to construct a carbon audit evaluation index system and to analyse the application of the system in the iron and steel enterprises in China. Data was collected from the Statistical Yearbook and the Sustainable Development Report and Financial Report of the iron and steel enterprises in China from 2011 to 2015. Research results show that establishing a carbon audit evaluation index system plays an essential role in implementing carbon audits; the system also improves the corporate carbon auditing system and evaluation mechanism, optimises the enterprise’s energy saving and emission reduction process, and makes a positive contribution to a low-carbon economy. The research also identifies several issues in relation to carbon audits in the iron and steel enterprises, including insufficient infrastructure and the shortage of talents for carbon audits, and the lack of innovation in clean production technology and capital investment.