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The purpose of this paper is to design a unified operational design domain (ODD) monitoring framework for mitigating Safety of the Intended Functionality (SOTIF) risks triggered by vehicles exceeding ODD boundaries in complex traffic scenarios.

A unified model of ODD monitoring is constructed, which consists of three modules: weather condition monitoring for unusual weather conditions, such as rain, snow and fog; vehicle behavior monitoring for abnormal vehicle behavior, such as traffic rule violations; and road condition monitoring for abnormal road conditions, such as road defects, unexpected obstacles and slippery roads. Additionally, the applications of the proposed unified ODD monitoring framework are demonstrated. The practicability and effectiveness of the proposed unified ODD monitoring framework for mitigating SOTIF risk are verified in the applications.

First, the application of weather condition monitoring demonstrates that the autonomous vehicle can make a safe decision based on the performance degradation of Lidar on rainy days using the proposed monitoring framework. Second, the application of vehicle behavior monitoring demonstrates that the autonomous vehicle can properly adhere to traffic rules using the proposed monitoring framework. Third, the application of road condition monitoring demonstrates that the proposed unified ODD monitoring framework enables the ego vehicle to successfully monitor and avoid road defects.

The value of this paper is that the proposed unified ODD monitoring framework establishes a new foundation for monitoring and mitigating SOTIF risks in complex traffic environments.

There is no proposed solution to address the unresolved issues of constructing the Chinese university intellectual property information service system (IPISS) to promote the whole process service efficiency of IP creation, utilization, protection and management. The purpose of this paper is to propose a complete system, including theoretical framework and system development which addresses the existing difficulties to IP create, protect and transfer for researchers in universities. The paper shares the practice of utilizing the system developed by Wuhan University IP research team known as Wuhan University Intellectual Property Information Service System (WHU-IPISS).

First, the IPISS of 23 universities in China was investigated on the internet. Aiming at the deficiencies of the system, such as single service type, lack of patent display window, low management efficiency. This paper constructs the theoretical framework, proposes the IP ecological chain model, divides it into four sub-chains and carries on the functional design. Further, under the theoretical framework, the IPISS was developed, including the resource supply management system, user demand matching system, resource assessment system and expert support system. Finally, the system was applied to Wuhan University to provide IP services in the whole process for university researchers.

WHU-IPISS realizes the functions of IP resource supply, demand matching, value evaluation and expert support. It solves the IP needs of university researchers and provides a guarantee for their technology research, patent portfolio, patent transfer and patent rights protection. It also improves the efficiency of IP service and can construct the IP ecosphere in universities.

The WHU-IPISS solution resolves issues of “How to develop the university IP whole process service model, fulfilling the IP service needs for universities' researchers”. The software will be released as open-source for other universities' use. The publishing model is also useful for those universities that intend to implement the IPISS.

The purpose of this paper is to alleviate the problem of poor robustness and over-fitting caused by large-scale data in collaborative filtering recommendation algorithms.

Interpreting user behavior from the probabilistic perspective of hidden variables is helpful to improve robustness and over-fitting problems. Constructing a recommendation network by variational inference can effectively solve the complex distribution calculation in the probabilistic recommendation model. Based on the aforementioned analysis, this paper uses variational auto-encoder to construct a generating network, which can restore user-rating data to solve the problem of poor robustness and over-fitting caused by large-scale data. Meanwhile, for the existing KL-vanishing problem in the variational inference deep learning model, this paper optimizes the model by the KL annealing and Free Bits methods.

The effect of the basic model is considerably improved after using the KL annealing or Free Bits method to solve KL vanishing. The proposed models evidently perform worse than competitors on small data sets, such as MovieLens 1 M. By contrast, they have better effects on large data sets such as MovieLens 10 M and MovieLens 20 M.

This paper presents the usage of the variational inference model for collaborative filtering recommendation and introduces the KL annealing and Free Bits methods to improve the basic model effect. Because the variational inference training denotes the probability distribution of the hidden vector, the problem of poor robustness and overfitting is alleviated. When the amount of data is relatively large in the actual application scenario, the probability distribution of the fitted actual data can better represent the user and the item. Therefore, using variational inference for collaborative filtering recommendation is of practical value.

The purpose of this paper is to show that the droplet impact phenomenon is important for the advancement of industrial technologies in many fields such as spray cooling and ink jet printing. Droplet bouncing on the nonwetting surfaces is a special phenomenon in the impact process which has attracted lots of attention.

In this work, the authors fabricated two kinds of representative nonwetting surfaces including superhydrophobic surfaces (SHS) and a slippery liquid-infused porous surface (SLIPS) with advanced UV laser processing.

The droplet bouncing behavior on the two kinds of nonwetting surfaces were compared in the experiments. The results indicate that the increasing Weber number enlarges the maximum droplet spreading diameter and raises the droplet bounce height but has no effect on contact time.

In addition, the authors find that the topological SHS and SLIPS with the laser-processed microwedge groove array produce asymmetric droplet bouncing with opposite offset direction. Microdroplets can be continuously transported without any additional driving force on such a topological SLIPS. The promising method for manipulating droplets has potential applications for the droplet-based microfluidic platforms.

Steer-by-wire (SBW) system mainly relies on sensors, controllers and motors to replace the traditionally mechanical transmission mechanism to realize steering functions. However, the sensors in the SBW system are particularly vulnerable to external influences, which can cause systemic faults, leading to poor steering performance and even system instability. Therefore, this paper aims to adopt a fault-tolerant control method to solve the safety problem of the SBW system caused by sensors failure.

This paper proposes an active fault-tolerant control framework to deal with sensors failure in the SBW system by hierarchically introducing fault observer, fault estimator, fault reconstructor. Firstly, the fault observer is used to obtain the observation output of the SBW system and then obtain the residual between the observation output and the SBW system output. And then judge whether the SBW system fails according to the residual. Secondly, dependent on the residual obtained by the fault observer, a fault estimator is designed using bounded real lemma and regional pole configuration to estimate the amplitude and time-varying characteristics of the faulty sensor. Eventually, a fault reconstructor is designed based on the estimation value of sensors fault obtained by the fault estimator and SBW system output to tolerate the faulty sensor.

The numerical analysis shows that the fault observer can be rapidly activated to detect the fault while the sensors fault occurs. Moreover, the estimation accuracy of the fault estimator can reach to 98%, and the fault reconstructor can make the faulty SBW system to retain the steering characteristics, comparing to those of the fault-free SBW system. In addition, it was verified for the feasibility and effectiveness of the proposed control framework.

As the SBW fault diagnosis and fault-tolerant control in this paper only carry out numerical simulation research on sensors faults in matrix and laboratory/Simulink, the subsequent hardware in the loop test is needed for further verification.

Aiming at the SBW system with parameter perturbation and sensors failure, this paper proposes an active fault-tolerant control framework, which integrates fault observer, fault estimator and fault reconstructor so that the steering performance of SBW system with sensors faults is basically consistent with that of the fault-free SBW system.

Detection of hidden defects of aluminum alloy plate with damping coating is a challenging problem. At present, only a few non-destructive testing methods exist to address this engineering problem. Without the restriction of skin effect, remote field eddy current (RFEC) overcomes the interference caused by the damping coating. The RFEC, which has potential advantages for detecting the hidden defects of aluminum plate with damping coating, can penetrate the metal plate to detect buried depth defects. This study aims to test how thick the RFEC sensor can penetrate the metal plate to detect the buried defects.

The magnetic field distribution characteristics are analyzed, the magnetic field intensity distribution is calculated, and the structure and parameters of the coil, magnetic circuit and shielding damping are determined through the two- and three-dimensional finite element simulation methods. Optimal excitation frequency is obtained, and the distance between the excitation coil and detection coil is determined by analyzing the relationship between excitation frequency and remote field points.

Simulation and experimental results verify the feasibility of applying the RFEC detection technology in detecting the hidden defects of aluminum alloy plate with damping coating.

In this paper, the RFEC testing model of hidden defects in aluminum plate sample with damping coating is established by using the finite element method.

The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.

This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.

The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.

This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

The purpose of this study is to investigate the impact of government policies adopted by the Tunisian government to cope with the COVID-19 sanitary crisis on stock market return.

The author uses daily data from March 2, 2020, to July 23, 2021.

The author finds that policies interventions have a negative impact on Tunisia's stock market, particularly stock market returns due to stringency, confinement and health measures. Also, Government announcements regarding economic has a negative impact on Tunisia's stock market but this impact is insignificant. By conducting an additional analysis, the author shows that the government interventions policies amplify the negative effect of COVID-19 on stock returns.

These results will be useful for policy authorities seeking to consider the advantages and drawbacks of government measures. Finally, a legislative proposal about the audit of public debt should be included in the Constitution to spur Tunisia's economic and social recovery.

This study contributes to the related literature in two ways: First, it is the first study to examine the impact of government actions on stock market performance. Second, it bridges a gap in the literature by investigating the case of Tunisia, because most studies focus on developed and emerging economies.

The transition to green growth goals requires the concerted efforts of the whole society. Enterprises, as important players in the market, play a key role in promoting green and sustainable development. The rise of the concept of sustainable development has enabled more enterprises to disclose environmental, social and governance (ESG) information, and ESG behaviour is regarded as a positive strategic behaviour to implement the new development concept. This paper aims to explore the influence of ESG performance on enterprise green innovation.

This study applies a fixed effect model and the regulation effect of empirical analysis to explore the influence of ESG performance on enterprise green innovation. The object of investigation is 2014–2021 Shanghai and Shenzhen A-share listed companies.

The results of an empirical analysis outline the following conclusions: (1) ESG performance has a significant effect on enterprise green innovation, mainly by easing the pressure of the financing enterprise, fitting stakeholders’ environmental protection concept and obtaining employee organizational identity that influences enterprise green innovation. (2) Government regulation positively regulates the role of ESG performance in promoting the green innovation of enterprises. (3) Heterogeneity analysis found that the strengthening role of ESG performance on the green innovation of enterprises is stronger in green invention patents, state-owned enterprises and nonheavily polluting industries.

Despite the valuable findings, this study has a few limitations. Thus, it is necessary to extend the object of investigation by adding other Asian countries, which allows for comparison analysis and allocating best practices for promoting green innovation. Besides, innovation and ESG performance depend on the quality of institutions. In this case, the future study should incorporate the indicators that reveal the quality of institutions (corruption, transparency, digitalisation, voice, accountability, etc.).

According to the above conclusions, this paper proposes suggestions at the level of enterprises, government and investors. At the enterprise level, ESG responsibility should be strengthened, ESG information should be consciously disclosed and the quality of ESG disclosure should be improved. Government departments should play the role of supervisors, improve the construction of ESG information disclosure systems and promote the formation of ESG systems. At the social level, investors should improve the ESG information status and pay more attention to the ESG performance of enterprises.

This study fills the scientific gaps in the analysis impact of ESG performance on the green innovation of enterprises. This paper contributes to the theoretical landscape of ESG efficiency by developing approaches based on two empirical models: testing the impact of enterprise ESG performance on green innovation and testing whether government regulation plays a regulatory role in the relationship between ESG performance and green innovation. Besides, this study analysed the ESG performance and green innovation within the following categories: heavy and nonheavy polluter industries; state and nonstate-owned enterprise groups.