As a key step to endow the neural network with nonlinear factors, the activation function is crucial to the performance of the network. This paper proposes an Efficient Asymmetric Nonlinear Activation Function (EANAF) for deep neural networks. Compared with existing activation functions, the proposed EANAF requires less computational effort, and it is self-regularized, asymmetric and non-monotonic. These desired characteristics facilitate the outstanding performance of the proposed EANAF. To demonstrate the effectiveness of this function in the field of object detection, the proposed activation function is compared with several state-of-the-art activation functions on the typical backbone networks such as ResNet and DSPDarkNet. The experimental results demonstrate the superior performance of the proposed EANAF.

Our paper takes the sample of listed companies from Shanghai and Shenzhen A-share SMEs and then theoretically analyzes and empirically tests the impact of digital inclusive finance on the financial performance of SMEs. The results show that financial performance of SMEs located in areas with a higher level of digital inclusive finance is significantly higher. Digital inclusive finance can play a role in expanding the scale of innovative investment, reducing the cost of debt financing and improving the ability of risk-taking, thereby strengthening the financial performance of SMEs. Our findings enrich the academic research on the topic of digital inclusive finance from the perspective of SMEs and provide suggestions to the government, banks and SMEs to continually implement the digital inclusive finance policy.

Digital Inclusive Finance (DIF) is a novel approach that employs digital technology to foster the development of inclusive finance, which can effectively alleviate the financing constraints of enterprises. This paper empirically tests the relationship between DIF and the financial performance of construction enterprises, with a focus of supply chain finance (SCF). The findings indicate that DIF can enhance the financial performance of construction enterprises, and SCF is one of the mechanisms through which DIF affects the financial performance of construction enterprises. Moreover, the cross-sectional analysis reveals that the impact of DIF on financial performance is more pronounced in firms with characteristics of private capital-holding and high operating pressure. This study not only enriches the research perspectives of DIF, but also provides valuable insights for policymakers to formulate effective policies.

Against the backdrop of systemic financial risk prevention and the pursuit of a virtuous cycle in the real economy, whether Local Government Financing Vehicles (LGFVs) shareholding alleviates maturity mismatch of corporate investment and financing activities is a question of critical importance, not only for the development of individual firms but also for high-quality macroeconomic growth. Using a sample of A-share listed firms in China’s Shanghai and Shenzhen stock exchanges from 2009 to 2021, this paper theoretically analyzes and empirically tests the impact of LGFVs shareholding on corporate maturity mismatch. The empirical results indicate that LGFVs shareholding can significantly alleviate corporate maturity mismatch and the finding is still robust across a series of empirical checks. Mechanism analyses show that LGFVs shareholding improves firms’ long-term financing capacity through a resource-provision channel and restrains overinvestment through a governance optimization channel, thereby collectively mitigating corporate maturity mismatch. Further analysis indicates that the mitigating effect of LGFVs shareholding is more pronounced in firms with concentrated LGFVs shareholding, firms controlled by non-state-owned capital and firms under higher economic policy uncertainty. Our findings provide valuable theoretical insights for policy design aimed at optimizing corporate financial behavior and curbing corporate financial risks.