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In recent years, the incidence of cardiovascular disease has continued to rise, and early screening and prevention are especially critical. Phonocardiography (PCG) and electrocardiography (ECG), as simple, cost-effective and non-invasive tests, are important tools for clinical analysis. However, it is difficult to fully reflect the complexity of the cardiovascular system using PCG or ECG tests alone. Combining the multimodal signals of PCG and ECG can provide complementary information to improve the detection accuracy. Therefore, the purpose of this paper is to propose a multimodal signal classification method based on continuous wavelet transform and improved ResNet18.

The classification method is based on the ResNet18 backbone, and the ResNet18 network is improved by embedding the global grouped coordinate attention mechanism module and the improved bidirectional feature pyramid network. Firstly, a data acquisition system was built using a MEMS-integrated PCG-ECG sensor to construct a private data set. Second is the time-frequency transformation of PCG and ECG synchronized signals on public and private data sets using continuous wavelet transform. Finally, the time-frequency images are categorized.

The global grouped coordinate attention mechanism and bidirectional feature pyramid network modules proposed in this paper significantly enhance the model’s performance. On public data sets, the method achieves precision, sensitivity, specificity, accuracy and F1 score of 97.96%, 98.51%, 97.58%, 98.08% and 98.23%, respectively, which represent improvements of 3.54%, 3.92%, 4.18%, 4.03% and 3.72% compared to ResNet18. Additionally, it demonstrates a clear advantage over existing mainstream algorithms. On private data sets, the method’s five metrics are 98.15%, 98.76%, 98.08%, 98.42% and 98.45%, further validating the model’s generalization ability.

The method proposed in this paper not only improves the accuracy and efficiency of the test but also provides an effective solution for early screening and prevention of cardiovascular diseases.

Steel structures are easily corroded under coastal atmospheric environment due to high humidity and high saltwater spray. To extend service life of steel structure infrastructure, it is necessary to remove rust and apply paint on the steel structure once a year. However, existing wall-climbing sandblasting robots are difficult to work on narrow steel beams and cause serious environmental pollution. The purpose of this study is to design a robot that can effectively remove rust from narrow steel beams and reduce environmental impact to extend the service life of steel structure infrastructure.

The heavy-duty wall-climbing robot designed in this study can effectively solve the above problems. The robot achieves adjustable magnetic adsorption force of the permanent magnet adsorption through a novel switch design and can work flexibly and stably on narrow steel beams through a worm-like internal and external alternating motion structure. In addition, it is equipped with a sandblasting recovery device to reduce environmental pollution.

The on-site test results on steel beams show that trust removal level can reach Sa2.0. The recovery rate of sandblasting and rust removal is close to 95%. The robot can carry a 40 kg sandblasting equipment and move at a speed greater than 40 cm/min, indicating that it can efficiently complete the rust removal work of narrow steel structures.

The originality lies in the design of the robot with features such as adjustable magnetic adsorption, special motion structure for narrow beams and a sandblasting recovery device. The value is that it can solve the problems of existing robots in working on narrow steel beams and environmental pollution and effectively extend the service life of steel structure infrastructure by efficiently removing rust.

This paper aims to reveal the green governance role played by stock connect in transition economies from the perspective of corporates’ environmental violations and provides implications for the coordination and optimization of subsequent stock market liberalization and green transformation policies in pursuit of carbon peaking and carbon neutrality goals.

With the data of Chinese listed enterprises, this paper takes the Shanghai-Hong Kong Stock Connect or Shenzhen-Hong Kong Stock Connect in China as a quasi-natural experiment and applies the multi-period difference-in-difference (DID) model to identify the impact of stock market liberalization on the corporates’ environmental violations.

The findings reveal that the stock market liberalization significantly restrains the corporates’ environmental violations. These findings are robust to a series of sensitivity tests, including excluding two-way effects, adjusting the year of policy implementation, replacing the core variables, introducing the regional fixed effects and excluding the interference effect of other relevant policies during the sample period. Furthermore, the stock market liberalization is beneficial for upgrading information disclosure quality, improving internal governance capability, strengthening environmental protection incentives, and thus restrains corporates’ environmental violations. Meanwhile, heterogeneity tests show that the inhibitory effects are more significant in those grouped samples which is large scale, state-owned nature, located in eastern region, with poor evaluation performances and heavy tax burden.

We make two marginal contributions to the current literature. First, this paper enriches the literature on the factors influencing corporate environmental violations by focusing on how the macro-level financial policy influences the micro-level corporate environmental violations. One the one hand, prior studies mainly focused on the consequences of corporate environmental violations; however, there is still a puzzle that the effect of stock market liberalization cannot be fully justified to influence corporate environmental violations. The findings help explain this puzzle by examining that stock market liberalization can restrain corporate environmental violations. Moreover, prior studies mainly focused on corporate share price (Yunsen Chen et al., 2022), market liquidity (Han Kim and Singal, 2000), information disclosure (Liang, Lin, and Chin 2012), corporate governance (Bae and Goyal, 2010) and corporate violations (Lingyun Xiong et al., 2021), but not on corporate environmental violations. We assume that the suppression effect of stock market liberalization on corporate environmental violations can help reduce corporate environmental violations, improve corporates’ awareness of environmental compliance. Second, this paper contributes to a better understanding of the literature on stock market liberalization by investigating the restraining effect of Stock Connect on corporate environmental violations from the perspective of information channel, corporate governance channel and motivation channel, which is of practical significance. Moreover, we investigate the differences in the inhibitory effects of stock market liberalization on different enterprises' environmental violations, from firm size, property rights, enterprise assessment results, tax burden to geographical location, which is conducive to the construction of a green financial system and the promotion of sustainable economic development. Our results show that firms which are large scale, state-owned nature, located in eastern region, with poor evaluation performances and heavy tax burden tend to compliance with environmental laws. These findings emphasize the importance and benefits of Stock Connect.