Effects of information transmission delay and channel blocking on synchronization in scale-free Hodgkin-Huxley neuronal networks

In this paper,we investigate the evolution of spatiotemporal patterns and synchronization transitions in dependence on the information transmission delay and ion channel blocking in scale-free neuronal networks.As the underlying model of neuronal dynamics,we use the Hodgkin-Huxley equations incorporating channel blocking and intrinsic noise.It is shown that delays play a significant yet subtle role in shaping the dynamics of neuronal networks.In particular,regions of irregular and regular propagating excitatory fronts related to the synchronization transitions appear intermittently as the delay increases.Moreover,the fraction of working sodium and potassium ion channels can also have a significant impact on the spatiotemporal dynamics of neuronal networks.As the fraction of blocked sodium channels increases,the frequency of excitatory events decreases,which in turn manifests as an increase in the neuronal synchrony that,however,is dysfunctional due to the virtual absence of large-amplitude excitations.Expectedly,we also show that larger coupling strengths improve synchronization irrespective of the information transmission delay and channel blocking.The presented results are also robust against the variation of the network size,thus providing insights that could facilitate understanding of the joint impact of ion channel blocking and information transmission delay on the spatiotemporal dynamics of neuronal networks.

Can increased economic complexity and reduced carbon emissions of the logistics industry go hand in hand?Evidence from countries along the Belt and Road

At present,the main focus of research lies in examining the connection between economic complexity and carbon emissions as a whole,but there is a scarcity of quantitative investigations on the link between the above variables within specific industries.Therefore,this study introduces economic complexity as a new variable to build a panel model within the traditional Environmental Kuznets Curve framework.Based on the data of the countries along the Belt and Road from 1998 to 2018,we used the Granger causality test to examine the causal relationship between variables,and use the Fully Modified Ordinary Least Square and Dynamic Ordinary Least Square methods to estimate the coefficients of variables.The key factor linking economic complexity and carbon emissions in the logistics industry is technology innovation Economic complexity can explain and predict the changes in carbon emissions of logistics industry more reasonably,and the relationship between them in line with the environmental kuznets curve hypothesis.Only high-income countries can increase economic complexity while reducing carbon emissions of logistics industry.Based on the empirical analysis,it is suggested that upper-middle income and lower middle-income countries can formulate relevant policies and regulations,and high-income countries can improve the relevant policies and regulations to promote the reduction of carbon emissions of the logistics industry.Studying the impact of economic complexity on carbon emissions in the logistics industry can help better predict and respond to the impact of climate change on the logistics industry.