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In order to control the risks of Chinese enterprises in infrastructure investment in developing countries, the corresponding evaluation system is constructed through a structural equation model algorithm to analyze these risks, so as to achieve risk prediction and risk controllability. Structural equation modeling is a method to establish, estimate, and test causality. It can replace multiple regression, path analysis, factor analysis, covariance analysis, and other methods and clearly analyze the effect of individual indicators on the population and the interrelationship between individual indicators. It is a multivariate statistical modeling technology mainly applied to confirmatory model analysis. Due to the guidance of national policies, there are more and more opportunities for Chinese enterprises to invest abroad. However, due to the influence of political, economic, and environmental factors, overseas investment is facing many difficulties. This paper analyzes the risks from four aspects: bilateral policy risk, legal difference and litigation risk, international economic risk, and technical risk through structural equation model algorithm. Aiming at these risks, the simulation software of the algorithm is constructed in MATLAB big data analysis software, and the risk control measures are put forward. Finally, with the support of China's policies, in order to ensure the investment income, we should carry out risk intervention for the foreseeable risk and reduce the impact of risk on the investment income as much as possible, so as to improve the risk prevention and management awareness of overseas investment business. By analyzing the characteristics of venture capital and the various kinds of risks affecting venture capital, the risk structure model estimation of risk sneak attack is established by using the principle of structural equation model, and the impact of various risks on investment risks can be analyzed, so that the risk measurement and control of venture capital provides the basis of theoretical knowledge. [ABSTRACT FROM AUTHOR]

China's low-cost carriers (LCCs) are poised for fast growth, thanks to the changing competition dynamics and aviation policies in the domestic market. This new trend calls for an in-depth investigation of the characteristics and behavioral intentions of LCC passengers. In particular, passenger demographics must be carefully considered given the likely demographic diversity in China's emerging LCC market. This study performed a cluster analysis using age, education, and income as joint clustering variables to examine the demographic patterns of LCC passengers in China. The results indicate three distinct LCC passenger segments, which were labeled as Mature Travelers, Elite Travelers, and Young Starters based on the passenger characteristics in each segment. To further investigate the passengers' behavioral intensions, this study considered the role of control when passengers plan and conduct an LCC trip. Despite the importance of controllability on the passenger side to complete a low-cost trip, given the operational and service characteristics of LCCs, it has not been adequately studied in the literature. Specifically, this study examines the impact of three control-related factors—perceived behavioral control, technology self-efficacy, and uncertainty avoidance—on the intention to use LCCs across the three passenger segments. The findings demonstrate that technology self-efficacy significantly influenced the mode use intention of the three passenger groups, while perceived behavioral control and uncertainty avoidance only affected the Elite Travelers. This study contributes to our understanding of LCCs by providing a new perspective of the composition and behavioral intentions of LCC passengers. Practical implications for the LCC success in China are discussed. [ABSTRACT FROM AUTHOR]

Network control theory is first applied here to study the controllability of a High-speed Rail Network (HRN) in terms of delivering emergency supplies. The full controllability or target controllability of an HRN (i.e., controlling the amount of emergency supplies delivered at all stations or target control stations) can be achieved when the amount of emergency supplies transported from some appropriate stations is efficiently controlled. To identify the optimized controlling stations, a model is proposed for minimizing the number of controlling stations and maximizing the sum of trains departing from controlling stations, which effectively and quickly controls an HRN in terms of delivering emergency supplies. The proposed model is demonstrated in a case in which the delivery of emergency supplies by China's HRN is controlled during the COVID-19 epidemic. The result shows that the sum of trains departing from the optimized controlling stations obtained through the proposed method is higher than that of the optimized controlling stations obtained through the commonly used maximum match method, and thus, the proposed method can obtain a better solution. The proposed method helps operators to identify the optimized controlling stations for effectively controlling an HRN in terms of delivering emergency supplies, and thus helping respond to emergency events. • Achieves full or target controllability of a high-speed rail network in terms of delivering emergency supplies. • Optimizes the set of stations for the controllability of a high-speed rail network. • The model is effective in fully controlling China's high-speed rail network for delivering medical supplies during the COVID-19 epidemic. [ABSTRACT FROM AUTHOR]

Understanding and encouraging individuals to conduct PM2.5 reduction behavior is vital to reduce conventional energy consumption and promote low carbon development. This research aims to predict the impacts of psychological factors (i.e., subjective norm, attitude, self-efficacy and controllability) and policy factors (i.e., command and control policy, economic incentive policy and education guidance policy) on individual's PM2.5 reduction behavior using a comprehensive research model on the basis of planned behavior theory and attitude-behavior-context. The research model is empirically examined employing questionnaire survey data of 1007 urban residents who reside in severe smog regions in China. The research findings indicate that individual's subjective norm, attitude and self-efficacy are all important internal affecting factors of individual's PM2.5 reduction intention, and further influence actual behavior. However, controllability can significantly moderate the relationship between individual's intention and actual behavior towards reducing PM2.5. Furthermore, three types of policy measures all show significant moderating effects on the transformation from intention to actual behavior. In addition, the results highlight that controllability and three types of policy measures all activate the transformation from intention to behavior, whether at low or high levels but to different extent, which implies that controllability and policy factors play a critical role in narrowing the gap between individual's intention and actual behavior. According to the research findings, policy implications for encouraging individual's PM2.5 reduction behavior and mitigating smog pollution are provided. [ABSTRACT FROM AUTHOR]

• Assessment of open-loop growth rate for typical equilibria in HL-2 M is implemented. • We design an out-vessel active control system for vertical instability control. • Efficiency of each PF coil location for VDE control is investigated. • Control performance and power supply upgrade requirements are evaluated. • Further optimization of active control for advanced divertor plasma is done. Plasma vertical instability control is achieved by passive stabilization from induced currents flowing in surrounding structures and by active control using magnetic coils. Both aspects are numerically investigated for the medium-size copper tokamak HL-2 M, presently under construction in China. The double-shell vessel can provide some passive stabilization, with the longest wall penetration time of about 4 ms. We design an out-vessel active control system based on a single null divertor equilibria most demanding for vertical control and the maximum controllable vertical displacement dZmax ≥3.0 cm is required. Robust active control of the vertical instability can be achieved in HL-2 M, by the PF7U and PF7L coils connected in anti-phase and powered by an upgraded power supply with I max = 4.0 kA, V max =2 kV and f = 5 kHz. Safe control is possible for representative plasma configurations with growth rate ranging from 200 s−1 to 400 s−1. Efficiency of each PF coil location for VDE control is investigated, PF7U/L is most capable for single null and double null equilibria, but control capability of PF7U/L is not as good as PF2U/L for snowflake divertor plasma, PF7U/L and PF2U/L will be combined together to provide safe control of low βp 'close nulls' advanced divertor plasma in the future. [ABSTRACT FROM AUTHOR]