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The purpose of this paper is to design the whole structure of high-speed automatic casing system (HSACS) for lithium-ion battery (LIB), and verify its rationality and reliability by kinematic simulation and casing test.

Based on the software of SolidWorks and ADAMS, the structure of working mechanisms for HSACS was designed, and virtual prototype models of HSACS and main turntable were established to realize the kinematic analysis. The HSACS casing test was also carried out and compared with simulation.

Simulation results for the designed HSACS were presented graphically and analyzed. The graphical results indicate that the coordination motions among the working mechanisms of HSACS are reasonable and no interference occurs. Casing test results show that the casing quality and production efficiency of HSACS equipment are satisfying.

In the present work, the developed virtual prototype models of HSACS provide reliable kinematic analysis results for the structural design of HSACS, and reasonable motion relations are realized in the designed structure of HSACS. Furthermore, not only the casing quality requirements can be met, but also the production efficiency of high-speed automatic casing machine for LIB is greatly improved via this kind of new HSACS structure.

The purpose of this paper is to study distance measuring and sorting method of general grey number.

First, the concept of generalised grey number based on grey system theory is given in this paper. Second, from the perspective of kernel and degree of greyness of general grey number, the method of measuring the distance of general grey number and its properties are given. At the same time, the concepts of the kernel expectation and the kernel variance of the general grey number are proposed.

Up to now, the method of measuring the distance and sorting of general grey number is established. Thus, the difficult problem for set up sorting of general grey number has been solved to a certain degree.

The method exposed in this paper can be used to integrate information form a different source. Distance measuring and sorting method of general grey number could be extended to the case of grey algebraic equation, grey differential equation and grey matrix which includes general grey numbers, etc.

The concepts of the kernel expectation and the kernel variance of the general grey number are proposed for the first time in this paper; the novel sorting rules of general grey numbers were also constructed.

Social bots are prevalent on social media. Malicious bots can severely distort the true voices of customers. This paper aims to examine social bots in the context of big data of user-generated content. In particular, the author investigates the scope of information distortion for 24 brands across seven industries. Furthermore, the author studies the mechanisms that make social bots viral. Last, approaches to detecting and preventing malicious bots are recommended.

A Twitter data set of 29 million tweets was collected. Latent Dirichlet allocation and word cloud were used to visualize unstructured big data of textual content. Sentiment analysis was used to automatically classify 29 million tweets. A fixed-effects model was run on the final panel data.

The findings demonstrate that social bots significantly distort brand-related information across all industries and among all brands under study. Moreover, Twitter social bots are significantly more effective at spreading word of mouth. In addition, social bots use volumes and emotions as major effective mechanisms to influence and manipulate the spread of information about brands. Finally, the bot detection approaches are effective at identifying bots.

As brand companies use social networks to monitor brand reputation and engage customers, it is critical for them to distinguish true consumer opinions from fake ones which are artificially created by social bots.

This is the first big data examination of social bots in the context of brand-related user-generated content.

In recent years, a great number of top conferences and workshops on artificial intelligence (AI) were held in China, showing Chinese AI plays an important role in the world. Meanwhile, Chinese government announced an ambitious scheme, “New Generation Artificial Intelligence Development Plan,” for the country to become a world leader in AI technologies by 2030. The AI research in China has covered various aspects, ranging from chips to algorithms. This chapter attempts to give an overview of the recent advances of AI research and development in China, as well as some perspectives on the future development of AI in China.

The main purpose of this research is to examine the impact of institutional quality and sectoral employment on environmental degradation in developing countries. This paper also re-examined the validity of the Environmental Kuznets Curve (EKC) hypothesis and estimated the long run impact of explanatory variables on CO₂ emissions.

In this paper, the balanced panel data for the period 2002–2016 was used based on data availability and applied two-step SYS-GMM estimators.

The results showed that institutional quality such as government effectiveness (GE) and the rule of law (RL) reduce CO₂ emissions and promote environmental quality in developing countries. Interestingly, the authors found new evidence that employment in agriculture and industry has a positive impact on pollution, while employment in the service sector was negatively associated with CO₂ emissions, and the validity of the EKC hypothesis was confirmed. In addition, the research suggests that strong institutional frameworks and their effective implementation are the most important panacea and should be treated as a top priority to counteract environmental degradation and achieve the UN Sustainable Development Goals.

This is the first study to examine the short run and long run effects of institutional quality and sectoral employment on environmental degradation using the balanced panel data for a large sample of developing countries. This paper also used a special technique of Driscoll and Kraay standard error approach to confirm the robustness results and showed the different roles of sectoral employment on environmental quality.

Revealing research data’s production and use, the status of research data management (RDM) and researchers’ service requirements in universities of Central China; this study aims to investigate the feasibility of university libraries in providing RDM services without any supporting policies from governments or funding agencies.

Using a stratified sampling method, faculties and graduate students from 11 universities were investigated. Four pilot subjects at Wuhan University (WHU) were chosen for whom a pilot RDM platform was to be constructed.

Research data at Chinese universities are small, sporadic and discontinuous. Such data are intensively or dispersedly under researcher’s management, with some unresolved problems regarding data security, data sharing and utilisation efficiency. Researchers’ needs for data services are strong. University libraries in China can develop RDM systems and provide related services. To realise this, more work should be done on service mechanism, service promotion, software development and staff training.

The user survey covered 11 universities in central China, which may not reveal the real RDM status of researcher in different areas of China.

The practice at WHU could provide reference to other university libraries in China or other developing countries.

The practice at WHU could provide reference to other university libraries in China or other developing countries.

The user survey is designed to be as comprehensive as possible and cover 902 researchers from 11 different types of Chinese universities. The practice at WHU is one of the first RDM initiatives led by university library in China.

In the presented research, the authors have conducted the literature review and organised real interviews of fruit retailers (FRs) to construct the advanced hierarchical structural (AHS) chain of macro-micro parameters for measuring the performances of defined fruit supply bazaars (FSBs). Apart from this, the purpose of this paper is to develop the grey set-based scorecard model for solving the proposed AHS chain of macro-micro parameters.

The performance of FSBs is linked with the supply of fruits towards clients under a feasible rate, which circuitously depends upon the evaluation of the economic locality of FSBs. The authors developed an advanced hierarchical structure of macro-micro parameters via a literature survey and considered these parameters based on the sampling score of FRs corresponding to select feasible FSBs/alternatives. Furthermore, the authors developed a grey set-based scorecard model for undertaking the incomplete information of FRs against the hierarchical structure.

It is found that the work is well suited for FRs as they can measure the performances of defined FSBs in accordance with their own opinions under the proposed AHS of macro-micro parameters. Apart from this, the work is useful for benchmarking the vegetable supply bazaars (VSBs) on the replacement of AHS. The proposed hierarchical structure with a grey-based scorecard model is flexible in its nature and can undertake more than 1,000 macro-micro parameters and FRs to access potential decision.

The conducted research work has a precise value for evaluating the economic FSB locality. The overall performance scores of considered FSB localities are computed as (∂₁)=1.991, (∂₂)=2.567 and (∂₃)=2.855, where (∂₃) is found to be more significant than available FSBs. This work can be used for opting the economic locality of VSB too.

The purpose of this paper is to explore the evolvement of investors’ behavior in stock market dynamically on the basis of non-cooperative strategy applied by investors in complex networks.

Using modeling and simulation research method, this study designs and conducts a mathematical modeling and its simulation experiment of financial market behavior according to research’s basic norms of complex system theory and methods. Thus the authors acquire needed and credible experimental data.

The conclusions drawn in this paper are as follows. The dynamical evolution of investors’ trading behavior is not only affected by the stock market network structure, but also by the risk dominance degree of certain behavior. The dynamics equilibrium of trading behavior’s evolvement is directly influenced by the risk dominance degree of certain behavior, connectivity degree and the heterogeneity of the stock market networks.

This paper focuses on the dynamical evolvement of investors’ behavior on the basis of the hypothesis that common investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of anti-coordination game in complex network. While the investors’ preference and the beliefs among them are not easy to quantify, that is deterministic or stochastic as the environment changes, and is heterogeneous definitely. Thus, these limitations should be broken through in the future research.

This paper aims to address the dynamical evolvement of investors’ behavior in stock market networks on the principle of non-cooperative represented by anti-coordination game in networks for the first time, considering that investors prefer to mimic their network neighbors’ behavior through different analysis by the strategy of differential choosing in every time step. The methodology designed and used in this study is a pioneering and exploratory experiment.

The effects of the thermo-mechanical treatment on the properties and microstructure of the Al–Cu–Mg–Ag alloy were investigated.

A short-duration preprecipitation process is designed prior to predeformation aging. The novel predeformation aging (solution treatment + holding at 185 °C for 15 min+ rolling deformation + aging at 185 °C, also named T8) was performed on a heat-resistant Al–Cu–Mg–Ag alloy.

The purpose of this study indicate that a short-duration heat treatment before predeformation is beneficial to the precipitation of O during the aging process. The precursors of O during this process might pin the dislocation and cause the grains to orient along some specific direction, which might be advantageous to the precipitation of O while disadvantageous to that of θ′. This novel thermal-mechanical process could result in an increase in the quantity and decrease in the size of the precipitation of O, which leads to a remarkable strength effect. The potential increases while the current density decreases with an increase in the deformation amount, which implies a smaller intergranular corrosion rate. The fine deformed structure leads to an opposite behavior in the exfoliation corrosion test compared with that for intergranular corrosion.

The intergranular corrosion resistance of the Al–Cu–Mg–Ag alloy is enhanced, whereas the exfoliation corrosion resistance is reduced by novel predeformation aging.