Structural characteristics of carbon information disclosure networks and the impact on carbon emission performance: Evidence from China.

Improving corporate carbon emission performance is an important driving force for realising the low-carbon development of China's economy. Carbon information disclosure is an environmental regulatory tool proposed in the context of carbon neutrality, this study examines whether carbon information disclosure effectively influences carbon emission performance. Based on the data from 30 provinces in China from 2012 to 2021, this paper examines the structural characteristics of carbon information disclosure using social network analysis, accounting for the carbon emission performance of industrial enterprises in each province in China.

Propagation and control of congestion risk in scale-free networks based on information entropy.

To study the propagation pattern of congestion risk in the traffic network and enhance risk control capabilities, a model has been developed. This model takes into account the probabilities of five threats (the risk occurrence probability; the risk of loss; the unpredictability of risk; the uncontrollability of risk; the transferability of risk) in the traffic network to define the risk entropy and determine the risk capacity, analyze the mechanism of congestion risk propagation, and explore the impact of risk resistance, the average degree of risk capacity at intersections, and the degree of correlation on congestion risk propagation. Further, a control method model for risk propagation is proposed.

Model of strategy control for delayed panic spread in emergencies.

In emergencies similar to virus spreading in an epidemic model, panic can spread in groups, which brings serious bad effects to society. To explore the transmission mechanism and decision-making behavior of panic, a government strategy was proposed in this paper to control the spread of panic. First, based on the SEIR epidemiological model, considering the delay effect between susceptible and exposed individuals and taking the infection rate of panic as a time-varying variable, a SEIR delayed panic spread model was established and the basic regeneration number of the proposed model was calculated.

Research on panic spread and decision behaviour in a delayed SEIR evolutionary game model under an emergency.

Taking major emergencies as the research background, the transmission mechanism for panic spread and the decision behaviour of the opinion field are explored in this paper. By using evolutionary game theory to explore the game relationship between the official opinion field and the public opinion field and by considering the existence of strategy dependency in the same game group, the dependence coefficient is introduced to improve replicator dynamics. The dynamic delayed SEIR evolutionary game model is built by combining the epidemic model with the delay effect within the group, and the stability of the proposed model is analysed.

The influence mechanism of interlocking director network on corporate risk-taking from the perspective of network embeddedness: Evidence from China.

The interlocking director network can not only help achieve low-cost information sharing and exchange learning among enterprises, but also provide essential resource support for corporate risk-taking behavior. This study aims to empirically analyze the impact, mechanism of action, and boundary of influence of interlocking director network (NET) on corporate risk-taking (RISK) using data of Chinese A-share listed companies from 2007 to 2020.The results show: (1) There is a significant positive correlation between NET and RISK, and the above results are still established after a series of robustness tests.

Research on false information clarification mechanism among government, opinion leaders, and Internet users - Based on differential game theory.

This article considers the government, opinion leaders, and Internet users to be a system for correcting false information, and it considers the problem of correcting false information that arises in the aftermath of major emergencies. We use optimal control theory and differential game theory to construct differential game models of decentralized decision-making, centralized decision-making, and subsidized decision-making. The solutions to these models and their numerical simulations show that the government, opinion leaders, and Internet users exercise cost-subsidized decision-making instead of decentralized decision-making.

Optimal Control of False Information Clarification System under Major Emergencies Based on Differential Game Theory.

To further study the issue of false information classification on social platforms after major emergencies, this study regards opinion leaders and Internet users as a false-information classification system and constructs three differential game models of decentralized, centralized, and subsidized decision-making based on optimal control and differential game theory. Comparison analyses and numerical simulations of optimal equilibrium strategies and the optimal benefit between opinion leaders and Internet users, the optimal trajectory and the steady-state value of the total volume of real information, and the optimal benefit of the false information clarification system are carried out. It is found that under centralized decision-making, equilibrium strategy and total benefit of opinion leaders and Internet users, system total benefit, and total volume of real information can achieve Pareto optimality.

Analysis of topological relationships and network properties in the interactions of human beings.

In the animal world, various kinds of collective motions have been found and proven to be efficient ways of carrying out some activities such as searching for food and avoiding predators. Many scholars research the interactions of collective behaviors of human beings according to the rules of collective behaviors of animals. Based on the Lennard-Jones potential function and a self-organization process, our paper proposes a topological communication model to simulate the collective behaviors of human beings.

Sustainable oil-in-water analysis using a supercritical fluid carbon dioxide extraction system directly interfaced with infrared spectroscopy.

A direct aqueous supercritical fluid extraction (SFE) system using carbon dioxide provides a sustainable means by which a vast range of industries may continue to depend on well established infrared (IR) techniques to determine oil-in-water. The SFE-IR method provides an environmentally friendly substitute for current national standard IR reference methods for measuring oil-in-water that rely on using increasingly restricted ozone depleting solvents whose manufacture is being phased out in accordance with international law. The SFE-IR analysis of a 500 mL water sample can be accomplished in 15 min.

Mini-review: green sustainable processes using supercritical fluid carbon dioxide.

Environmentally benign carbon dioxide offers significant potential in its supercritical fluid phase to replace current reliance on a range of hazardous, relatively expensive and environmentally damaging organic solvents that are used on an extensive global basis. The unique combination of the physical properties of supercritical fluids are being exploited and further researched to continue the development and establishment of high efficiency, compact plant to provide energy and water efficient manufacturing processes. This mini-review is focused on the use and potential applications of supercritical fluid carbon dioxide for a selected range of key and emerging industrial processes as a sustainable alternative to totally eliminate or greatly reduce the requirement of numerous conventional organic solvents.