Exploring the Dynamics of Industrial Convergence Among RCEP Member Countries: An Empirical Study

The evolving dynamics of industrial convergence among the member countries of the Regional Comprehensive Economic Partnership(RCEP)framework have emerged as a significant subject that merits in-depth consideration and analysis.This study initially employs multi-regional input-output(MRIO)data and the social network analysis(SNA)method to delineate the levels and variation trends of this industrial convergence across the RCEP member countries.It then delves into the positive effects of this convergence phenomenon on the trade and investment fields of the member countries.The research findings indicate:(a)In 2006 and 2015,before the implementation of the RCEP,the RCEP member countries displayed a relatively close industrial convergence.The convergence levels exhibited a general upward trend on both the supply and the demand sides,but there were significant disparities in the levels of industrial convergence among the member countries.Furthermore,while the convergence in the three economic sectors showed an increasing trend,the development was uneven across the board.(b)Since the implementation of the RCEP,the trade ties among the member countries within the region have strengthened significantly,and the interplay between the countries’industrial and supply chains has been characterized by high-quality collaboration and demonstrated remarkable resilience.In addition,the convergence in the investment fields of the RCEP member countries and their respective industries has unleashed a wave of positive synergies.These findings offer valuable insights that can serve as a robust foundation for formulating effective policies to advance the growth and prosperity of the RCEP region.

Identification of the Credit Guarantee Network of Steel Trade Enterprises in China

The risk points in the credit guarantee network of steel trade enterprises were identified by using the network analysis method in this paper. Firstly, the formation and operation mechanism of steel trade credit guarantee network was analyzed.Secondly,a guarantee network was established to analyze the related network structure indexes based on the mutual guarantee data of 83 enterprises in a steel trade market. These indexes included centrality,honest broker,and structural hole. The results suggest that network analysis method can be used to find out the risk points of the guarantee network. Additionally,some recommendations are brought forth to reduce or prevent future crises.

Numerical analysis on thermoacoustic engine using network method

The network method for modeling thermoacoustic engines is described. Some simulation results on acoustic fields and phases in engine, especially in the thermoacoustic stack are presented and analyzed. The effects of some key factors on performance of stack and engine system are simulated and discussed. These effect factors include the spaces of plates of stack, the position of stack in engine system, the source parameter of stack, and the mean working pressure of the engine system.

SEIR-SW, Simulation Model of Influenza Spread Based on the Small World Network

This study modeled the spread of an influenza epidemic in the population of Oran, Algeria. We investigated the mathematical epidemic model, SEIR（Susceptible-Exposed-Infected-Removed）, through extensive simulations of the effects of social network on epidemic spread in a Small World（SW） network, to understand how an influenza epidemic spreads through a human population. A combined SEIR-SW model was built, to help understand the dynamics of infectious disease in a community, and to identify the main characteristics of epidemic transmission and its evolution over time. The model was also used to examine social network effects to better understand the topological structure of social contact and the impact of its properties. Experiments were conducted to evaluate the combined SEIR-SW model. Simulation results were analyzed to explore how network evolution influences the spread of desease, and statistical tests were applied to validate the model. The model accurately replicated the dynamic behavior of the real influenza epidemic data, confirming that the susceptible size and topological structure of social networks in a human population significantly influence the spread of infectious diseases. Our model can provide health policy decision makers with a better understanding of epidemic spread,allowing them to implement control measures. It also provides an early warning of the emergence of influenza epidemics.