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The chapter articulates the transition to and evolution of the commercialisation of Chinese professional football. It is periodised based on major turning points. The research yielded two major findings. First, there exists a distinct ‘Chinese way’ of commercialising football. However, it does not indicate that Chinese football doggedly avoided the Western governance model. For the club governance, Chinese football authorities set about recommending privately operated enterprises, large and medium-sized state-owned enterprises. Second, the commercialisation transitions of professional football in China were triggered by exogenous policy shifts, rather than endogenous changes in market structures, resulting in higher horizontal financial fragility than is associated with the commercialisation model adopted in more developed Western markets. The applicability to voluntary football clubs is assessed as well.

This chapter explores how the development of football fandom for the Chinese national team and local football clubs is strongly associated with societal changes. Although the performances of Chinese football teams, especially the national team, have failed to impress the world, football remains the most popular because of millions of supporters with loyalty and passion. Most studies related to fans mainly focus on the economic and political implications of spectatorship along with the rise of China. Nevertheless, few articles are available to answer the fundamental questions, such as ‘When did these supporters come out?’ and ‘What were the factors of the development of fandom?’. By going through archival records and published documents over the last decades, this chapter offers a comprehensive and historical analysis of the development of football fandom in the People's Republic of China (PRC) and deals with these unanswered questions. As such, this chapter does not intend to be the most authoritative one but is one of the rare sources to lay down the foundation for research on Chinese football fandom. Furthermore, this chapter also proves that studies on football fandom can be a useful window for observing Chinese society.

Unmanned aerial vehicles (UAVs), known for their exceptional flexibility and maneuverability, have become an integral part of mobile edge computing systems in edge networks. This paper aims to minimize system costs within a communication cycle. To this end, this paper has developed a model for task offloading in UAV-assisted edge networks under dynamic channel conditions. This study seeks to efficiently execute task offloading while satisfying UAV energy constraints, and validates the effectiveness of the proposed method through performance comparisons with other similar algorithms.

To address this issue, this paper proposes a task offloading and trajectory optimization algorithm using deep deterministic policy gradient, which jointly optimizes Internet of Things (IoT) device scheduling, power distribution, task offloading and UAV flight trajectory to minimize system costs.

The analysis of simulation results indicates that this algorithm achieves lower redundancy compared to others, along with reductions in task size by 22.8%, flight time by 34.5%, number of IoT devices by 11.8%, UAV computing power by 25.35% and the required cycle for per-bit tasks by 33.6%.

A multi-objective optimization problem is established under dynamic channel conditions, and the effectiveness of this approach is validated.

Along with the national government's expectation transformation, administrative system reform, economic transition, social demand structure's upgrading and population change, these negative effects are turning increasingly obvious and thus become huge powers that push the reform of traditional elite sports development mode forward. Against this background, in order to make this reform better adapted to China's reality and future development, the chapter suggests that Chinese traditional elite sports development mode should shift its driving forces of development from single to multiple, change its administrative system from government-oriented to society-oriented, develop its training concepts from instrumentalism to humanism, improve its construction of development from unbalanced to balanced and alter its effectiveness of development from extensive to intensive so as to achieve sustainable development.

This paper aims to propose a hybrid force/position controller based on the adaptive variable impedance.

First, the working space is divided into a force control subspace and a position subspace, the force control subspace adopts the position impedance control strategy. At the same time, the contact force model between the robot and the surface is analyzed in this space. Second, based on the traditional position impedance, the model reference adaptive control is introduced to provide an accurate reference position for the impedance controller. Then, the BP neural network is used to adjust the impedance parameters online.

The experimental results show that compared with the traditional PI control method, the proposed method has a higher flexibility, the dynamic response accommodation time is reduced by 7.688 s and the steady-state error is reduced by 30.531%. The overshoot of the contact force between the end of robot and the workpiece is reduced by 34.325% comparing with the fixed impedance control method.

The proposed control method compares with a hybrid force/position based on PI control method and a position fixed impedance control method by simulation and experiment.

The adaptive variable impedance control method improves accuracy of force tracking and solves the problem of the large surfaces with robot grinding often over-polished at the protrusion and under-polished at the concave.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.

The mounting health misinformation on social media triggers heated discussions about how to address it. Anchored by the influence of presumed influence (IPI) model, this study investigates the underlying process of intentions to combat health misinformation. Specifically, we analyzed how presumed exposure of others and presumed influence on others affect intentions to practice pre-emptive and reactive misinformation countering strategies.

Covariance-based structural equation modeling based on survey data from 690 Chinese participants was performed using the “lavaan” package in R to examine the proposed mechanism.

Personal attention to health information on social media is positively associated with presumed others’ attention to the same information, which, in turn, is related to an increased perception of health misinformation’s influence on others. The presumed influence is further positively tied to two pre-emptive countermeasures (i.e. support for media literacy interventions and institutional verification intention) and one reactive countermeasure (i.e. misinformation correction intention). However, the relationship between presumed influence and support for governmental restrictions, as another reactive countering method, is not significant.

This study supplements the misinformation countering literature by examining IPI’s tenability in explaining why individuals engage in combating misinformation. Both pre-emptive and reactive strategies were considered, enabling a panoramic view of the motivators of misinformation countering compared to previous studies. Our findings also inform the necessity of adopting a context-specific perspective and crafting other-oriented messages to motivate users’ initiative in implementing corrective actions.

The purpose of this paper is to investigate the fault estimation issue of nonlinear dynamical systems via distributed sensor networks. Furthermore, based on the communication topology of sensor networks, the nonfragile design strategy considering the gain fluctuation is also adopted for distributed fault estimators.

By means of intensive dynamical model transformation, sufficient conditions with disturbance attenuation performance are established to design desired fault estimator gains with the help of convex optimization.

A novel distributed fault estimation framework for a class of nonlinear dynamical systems is established over a set of distributed sensor networks, where sampled data of sensor nodes via local information exchanges can be used for more efficiency.

The proposed distributed fault estimator gain fluctuations are taken into account for the nonfragile strategy, such that the distributed fault estimators are more applicable for practical sensor networks implementations. In addition, an illustrative example with simulation results are provided to validate the effectiveness and applicableness of the developed distributed fault estimation technique.

Revenue management (RM) is a significant technique to improve revenue with limited resources. With the macro environment of dramatically increasing transit capacity and rapid railway transport development in China, it is necessary to involve the theory of RM into the operation and decision of railway passenger transport.

This paper proposes the theory and framework of generalized RM of railway passenger transport (RMRPT), and the thoughts and methods of the main techniques in RMRPT, involving demand forecasting, line planning, inventory control, pricing strategies and information systems, are all studied and elaborated. The involved methods and techniques provide a sequential process to help with the decision-making for each stage of RMRPT. The corresponding techniques are integrated into the information system to support practical businesses in railway passenger transport.

The combination of the whole techniques devotes to railway benefit improvement and transit resource utilization and has been applied into the practical operation and organization of railway passenger transport.

The development of RMRPT would provide theoretical and technical support for the improvement of service quality as well as railway benefits and efficiency.

This study investigates the impact of internal expectations, such as fantasy of success and fear of failure and external factors, such as social environment and past experiences, on entrepreneurial choice.

Based on achievement motivation and social cognitive theories, the authors construct hypotheses and use secondary data from the Global Entrepreneurship Monitor (GEM) database and Economic Freedom Index report to empirically test the hypotheses. The authors also use propensity score matching to solve the endogeneity issue and test the robustness.

Internal expectations (fantasy of success and fear of failure) on business outcomes inversely affect entrepreneurial choices, with a vibrant business environment amplifying and past failure experience mitigating these effects.

Due to the economic recession, governments encourage small businesses. Thus, the complexity of individual entrepreneurial motivations and influencing factors necessitate deeper exploration. This study is one of the first research offering insights into entrepreneurial motivations from combined dimensions and providing theoretical support for strategies promoting public entrepreneurship.