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Environmental information disclosure (EID) is an important embodiment of corporate social responsibility. With the awakening of public awareness of environmental protection and the increasing pressure of environmental preservation, enterprises tend to strategically manipulate environmental information for the pursuit of profit, which will consequently lead to environmental information disclosure falsification (EIDF) and disruption of both the market regulatory order and the development of green economy. In this article, support vector machine (SVM) technique is applied to construct the detection model of corporate EIDF. Based on the theory of "public pressure," the detection indicators will be improved from three aspects: public pressure, corporate governance, and financial indicators. The training set and test set are constructed by combining the manually collected cases of environmental administrative penalties from 2015 to 2019 with the indicator information of nonfinancial listed enterprises in China's A-share market, and the SVM detection performance is compared with the logistic regression of the benchmark model. To solve the problem of category imbalance, we have introduced the Borderline-SMOTE oversampling technique. Based on the detection results of SVM and Borderline-SMOTE, we find that the Borderline-SMOTE-SVM model has the best detection performance, surpassing the SVM and logistic regression models. These conclusions have constructive policy implications for regulatory agencies, investors, the third-party service sector, enterprises, and government policy-making to achieve high-quality corporate EID. [ABSTRACT FROM AUTHOR]

The number of older adults is rising rapidly in China. Various concerns such as chronic diseases, financial inadequacy, and a feeling of loneliness have adversely affected the mental health of older adults, and this has become an important public health and social issue. To realize healthy aging, the Nineteenth National People's Congress of China put forth the Healthy China strategy, speeding up the promotion activities of mental health and pension measures, carrying out public welfare pension insurance for the entire population, and contributing to the mental health of older adults. This study used data from China Family Panel Studies. This study mainly uses the random effect estimation method (random effect, RE) and the feasible generalized least squares estimation method (FGLS) to control for heterogeneity to explore the impact of social and commercial pension insurance on the mental health of older adults, the moderating effect of social capital on pension insurance, and the mental health of older adults. The results showed that social pension insurance is proportional to the mental health of older adults, whereas commercial pension insurance is inversely proportional to mental health. Social capital had a significant moderating effect on pension insurance. When a country develops an aging economy, the emphasis on social capital helps make targeted industrial development suggestions. The government's expansion of insurance coverage is crucial for improving the mental health of older adults., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Chai, Li, Jin, Lu, Cui and He.)

Interconnection is the priority direction of the Belt and Road initiative, which can provide substantial assistance to win-win cooperation. This study establishes a new indicator system from the five dimensions of policy, infrastructure, trade, finance, and people-to-people, evaluates the connect index of 63 Belt and Road countries from 2013 to 2020 based on the DEMATEL-ANP method which removes the potential subjective interference and interaction between indicators, and predicts the trend of the connect index by using the grey model. The findings indicate that the five dimensions of the Belt and Road connectivity have unevenly developed, among which the policy coordination has achieved the least. Singapore, Russia, and Malaysia have the highest connect index, and we can find that the 10 countries with the highest connect index are basically from East Asia & Pacific and Europe & Central Asia, which possess large economic and geographical differences. Moreover, there are 17 "omission areas" characterized by low national income, poor infrastructure, low population density, and small land areas along the Belt and Road. Finally, the Silk Road Economic Belt is facing structural imbalances in connectivity, and the relation features "proximity but not affinity" between China and its neighboring countries. These conclusions are friendly cautions and have constructive policy implications for the Belt and Road countries to achieve high-quality interconnection.