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. Using the spatial econometric model, we apply the undesirable slacks-based measure model and examine the impact of the spatial network characteristics of carbon information disclosure on carbon emission performance. Results show that the overall density of carbon information disclosure networks of industrial enterprises in Chinese provinces is low, so there is much room for improvement. Additionally, there is spatial dependence on carbon emission performance among neighbouring provinces. Moreover, the out-degree centrality and betweenness centrality of carbon information disclosure networks significantly negatively affect carbon emission performance. However, the inhibitory effect of the in-degree centrality of carbon information disclosure networks on carbon emission performance is not significant. The unique findings of this paper are relevant to environmental policy formulation and assessment.

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. Numerical simulation results demonstrate that the risk resistance parameter θ can inhibit the propagation of congestion risk during traffic congestion. The highest efficiency in controlling risk propagation is achieved when θ reaches a threshold value θ*. Furthermore, the average degree of intersection risk capacity α shows a positive correlation with θ* and a negative correlation with control efficiency. However, the degree of association ω has a negative effect on risk propagation control, decreasing the degree of association between nodes aids in risk propagation control.

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. Second, the control strategy was expressed as a state delayed feedback and solved using the exact linearization method of nonlinear control system; the control law for the system was determined, and its stability was proven. The aim was to eradicate panic from the group so that the recovered group tracks the whole group asymptotically. Finally, we simulated the proposed strategy of controlling the spread of panic to illustrate our theoretical results.

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 research results show that the strategy dependency among the same game group has positive and negative effects on the evolution process. The evolution of the dynamic delayed panic SEIR evolutionary game spread model under the effect of a positive effect is simulated. The results suggest that the official opinion field and the public opinion field should actively deal with emergencies, formulate effective control strategies to make the panic within the group disappear, and provide theoretical guidance for the relevant government to formulate plans.

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. (2) Mechanistic tests show that the NET can promote RISK through two channels: alleviating financing constraints and increasing R&D investment. (3) Further analysis reveals the promotion of NET on RISK is more significant in non-state-owned enterprises and enterprises with higher industry competition intensity. These findings have positive implications for the construction of an inter-enterprise interlocking director network and the enhancement the of the risk-taking level.

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. The equilibrium strategies, local optimal benefits, and overall optimal benefits of the system achieve Pareto improvement. Given the goal of maximizing the benefits to the system under centralized decision-making, the equilibrium results are Pareto-optimal. The research here provides a theoretical basis for dealing with the mechanism of correcting false information arising from major emergencies, and our conclusions provide methodological support for the government to effectively deal with such scenarios.

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. Although subsidized decision-making fails to achieve Pareto optimality, with opinion leaders providing cost subsidies for Internet users, it is possible to reach relative Pareto improvement compared with decentralized decision-making.

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. In the results of simulations, we find various types of collective behavior and fission behavior and discover the threshold for the emergence of collective behavior, which is the range five to seven for the number of topology K. According to the analysis of network properties of the model, the in-degree of individuals is always equal to the number of topology. In the stable state, the out-degrees of individuals distribute around the value of the number of topology K, except that the out-degree of a single individual is approximately double the out-degrees of the other individuals. In addition, under different initial conditions, some features of different kinds of networks emerge from the model. We also find the leader and herd mentality effects in the characteristics of the behaviors of human beings in our model. Thus, this work could be used to discover how to promote the emergence of beneficial group behaviors and prevent the emergence of harmful behaviors.

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. A rapid on-line SFE-IR calibration method has been implemented. With this calibration method, SFE-IR accuracy for determining diesel oil in 500 mL spiked water samples using single wave number measurement was 86.0%-98.8% with precision (RSD) ranging from 2.5%-7.0%. Using a general purpose calculation which involves measuring infrared absorbance values at three different wave numbers, SFE-IR method accuracy for determining diesel oil in 500 mL spiked water samples was 83.7%-92.2% with RSD 1.0%-9.3%. Data is presented that indicates current long established national standard IR reference methods involving three wave number calculations should be reviewed since, without careful consideration, the inclusion of calculated aromatic hydrocarbon species contributions to final oil-in-water concentration values may provide less accurate results.

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. Examples of the industries include: chemical extraction and purification, synthetic chemical reactions including polymerization and inorganic catalytic processes. Biochemical reactions involving enzymes, particle size engineering, textile dyeing and advanced material manufacture provide further illustrations of vital industrial activities where supercritical fluid technology processes are being implemented or developed. Some aspects relating to the economics of sustainable supercritical fluid carbon dioxide processes are also considered.