Dynamical Interaction Between Information and Disease Spreading in Populations of Moving Agents

Considering dynamical disease spreading network consisting of moving individuals,a new double-layer network is constructed,one where the information dissemination process takes place and the other where the dynamics of disease spreading evolves.On the basis of Markov chains theory,a new model characterizing the coupled dynamics between information dissemination and disease spreading in populations of moving agents is established and corresponding state probability equations are formulated to describe the probability in each state of every node at each moment.Monte Carlo simulations are performed to characterize the interaction process between information and disease spreading and investigate factors that influence spreading dynamics.Simulation results show that the increasing of information transmission rate can reduce the scale of disease spreading in some degree.Shortening infection period and strengthening consciousness for self-protection by decreasing individual’s scope of activity both can effectively reduce the final refractory density for the disease but have less effect on the information dissemination.In addition,the increasing of vaccination rate or decreasing of long-range travel can also reduce the scale of disease spreading.

Epidemic Spreading Model Based on Social Active Degree in Social Networks

In this paper,an improved Susceptible-Infected-Susceptible(SIS) epidemic spreading model is proposed in order to provide a theoretical method to analyze and predict the spreading of diseases.This model is based on the following ideas:in social networks,the contact probability between nodes is decided by their social distances and their active degrees.The contact probability of two indirectly connected nodes is decided by the shortest path between them.Theoretical analysis and simulation experiment were conducted to evaluate the performance of this improved model.Because the proposed model is independent of the network structure,simulation experiments were done in several kinds of networks,namely the ER network,the random regular network,the WS small world network,and the BA scale-free network,in order to study the influences of certain factors have on the epidemic spreading,such as the social contact active degree,the network structure,the average degree,etc.This improved model provides an idea for studying the spreading rule of computer virus,attitudes,fashion styles and public opinions in social networks.

Influence fast or later:Two types of influencers in social networks

In real-world networks,there usually exist a small set of nodes that play an important role in the structure and function of networks.Those vital nodes can influence most of other nodes in the network via a spreading process.While most of the existing works focused on vital nodes that can maximize the spreading size in the final stage,which we call final influencers,recent work proposed the idea of fast influencers,which emphasizes nodes’spreading capacity at the early stage.Despite the recent surge of efforts in identifying these two types of influencers in networks,there remained limited research on untangling the differences between the fast influencers and final influencers.In this paper,we firstly distinguish the two types of influencers:fast-only influencers and final-only influencers.The former is defined as individuals who can achieve a high spreading effect at the early stage but lose their superiority in the final stage,and the latter are those individuals that fail to exhibit a prominent spreading performance at the early stage but influence a large fraction of nodes at the final stage.Further experiments are based on eight empirical datasets,and we reveal the key differences between the two types of influencers concerning their spreading capacity and the local structures.We also analyze how network degree assortativity influences the fraction of the proposed two types of influencers.The results demonstrate that with the increase of degree assortativity,the fraction of the fast-only influencers decreases,which indicates that more fast influencers tend to keep their superiority at the final stage.Our study provides insights into the differences and evolution of different types of influencers and has important implications for various empirical applications,such as advertisement marketing and epidemic suppressing.

Comparative Effects of Avoidance and Immunization on Epidemic Spreading in a Dynamic Small-World Network with Community Structure

Considering the actual behavior of people’s short-term travel,we propose a dynamic small-world community network model with tunable community strength which has constant local links and time varying long-range jumps.Then an epidemic model of susceptible-infected-recovered is established based on the mean-field method to evaluate the inhibitory effects of avoidance and immunization on epidemic spreading.And an approximate formula for the epidemic threshold is obtained by mathematical analysis.The simulation results show that the epidemic threshold decreases with the increase of inner-community motivation rate and inter-community long-range motivation rate,while it increases with the increase of immunization rate or avoidance rate.It indicates that the inhibitory effect on epidemic spreading of immunization works better than that of avoidance.

Social influence and spread dynamics in social networks

Social networks often serve as a critical medium for information dissemination, diffusion of epidemics, and spread of behavior, by shared activities or similarities be- tween individuals. Recently, we have witnessed an explosion of interest in studying social influence and spread dynamics in social networks. To date, relatively little material has been provided on a comprehensive review in this field. This brief survey addresses this issue. We present the current significant empirical studies on real social systems, including network construction methods, measures of network, and newly em- pirical results. We then provide a concise description of some related social models from both macro- and micro-level per- spectives. Due to the difficulties in combining real data and simulation data for verifying and validating real social sys- tems, we further emphasize the current research results of computational experiments. We hope this paper can provide researchers significant insights into better understanding the characteristics of personal influence and spread patterns in large-scale social systems.

Long dynamic range spread spectrum optical domain reflectometer

The performance of an optical time domain reflectometer(OTDR) is significantly improved using spread spectrum technology. The concept of spread spectrum OTDR(SSOTDR) is proposed, the theoretical basis and simulation results of the new method are given, and the problem of direct application of bipolar spread spectrum codes to OTDR and despreading in the optical domain are solved. The simulation results show the feasibility of the SSOTDR, which exhibits better dynamic range reported to date for a practical long-haul OTDR system without using conventional average technique.

Effects of xanthan gum on atomization and deposition characteristics in water and Silwet 408 aqueous solution

In order to investigate the effects of viscosity on spray formation and utilization of pesticide,different concentrations of xanthan gum(XG)were added into water and 0.1%Silwet 408 aqueous solution.Droplet size,relative span(RS),fan angle,length of breakup and maximum retention(Rm)were measured with the LU120-02 nozzle spraying under the pressure of 0.3 MPa.The dynamic spreading of the different solutions on maize leaves was tested using a 5μL micro-injector.The results showed:VMD,RS,length of breakup and Rm went up as the increasing of XG concentration in the range of 0-0.5%with the same solution,while the fan angle of nozzle and spreading area on maize leaf showed the opposite tendency.Silwet 408 could reduce the surface tension of liquid,which could alter the dominant mode of spray formation and lead to earlier sheet breakup,especially in low viscosity solutions.Under the same concentration of XG the addition of Silwet 408 could reduce the RS of drop size spectrum but has no effect on VMD or fan angle.In water solution,there was no difference with different concentrations of XG in the spreading time on maize leaf.Besides,in the 0.1%Silwet 408 aqueous solution,the spraying time and area were several-fold of that in water with same XG concentration.Moreover,with the same XG concentration,the smaller surface tension liquid indicated lower Rm,and the difference was magnified as the concentration increases.This work has demonstrated that initial spray characteristics such as droplet size and RS,fan angle,length of breakup,Rm and spreading area can vary depending on the viscosity of spray liquids.Therefore,by transforming the viscosity of the spray liquid to adjust the droplet spectrum to reduce drift,increasing the Rm and spreading area to improve liquid utilization and reduce the usage of pesticides.