Identifying multiple influential spreaders in complex networks based on spectral graph theory

One of the hot research topics in propagation dynamics is identifying a set of critical nodes that can influence maximization in a complex network.The importance and dispersion of critical nodes among them are both vital factors that can influence maximization.We therefore propose a multiple influential spreaders identification algorithm based on spectral graph theory.This algorithm first quantifies the role played by the local structure of nodes in the propagation process,then classifies the nodes based on the eigenvectors of the Laplace matrix,and finally selects a set of critical nodes by the constraint that nodes in the same class are not adjacent to each other while different classes of nodes can be adjacent to each other.Experimental results on real and synthetic networks show that our algorithm outperforms the state-of-the-art and classical algorithms in the SIR model.

Analysis of terrestrial water storage changes in the Shaan-Gan-Ning Region using GPS and GRACE/GFO

Both the Global Positioning System(GPS)and Gravity Recovery and Climate Experiment(GRACE)/GRACE Follow-On(GFO)provide effective tools to infer surface mass changes.In this paper,we combined GPS,GRACE/GFO spherical harmonic(SH)solutions and GRACE/GFO mascon solutions to analyze the total surface mass changes and terrestrial water storage(TWS)changes in the Shaan-Gan-Ning Region(SGNR)over the period from December 2010 to February 2021.To improve the reliability of GPS inversion results,an improved regularization Laplace matrix and monthly optimal regularization parameter estimation strategy were employed to solve the ill-posed problem.The results show that the improved Laplace matrix can suppress the edge effects better than that of the traditional Laplace matrix,and the corre-lation coefficient and standard deviation(STD)between the original signal and inversion results from the traditional and improved Laplace matrix are 0.84 and 0.88,and 17.49 mm and 15.16 mm,respectively.The spatial distributions of annual amplitudes and time series changes for total surface mass changes derived from GPS agree well with GRACE/GFO SH solutions and mascon solutions,and the correlation coefficients of total surface mass change time series between GPS and GRACE/GFO SH solutions,GPS and GRACE/GFO mascon solutions are 0.80 and 0.77.However,the obvious differences still exist in local regions.In addition,the seasonal characteristics,increasing and decreasing rate of TWS change time series derived from GPS,GRACE/GFO SH and mascon solutions agree well with the Global Land Data Assimilation System(GLDAS)hydrological model in the studied area,and generally consistent with the precipitation data.Meanwhile,TWS changes derived from GPS and GRACE mascon solutions in the SGNR are more reliable than those of GRACE SH solutions over the period from January 2016 to June 2017(the final operation phase of the GRACE mission).

Some Applications on the Method of Eigenvalue Interlacing for Graphs

The Method of Eigenvalue Interlacing for Graphs is used to investigate some problems on graphs, such as the lower bounds for the spectral radius of graphs. In this paper, two new sharp lower bounds on the spectral radius of graphs are obtained, and a relation between the Laplacian spectral radius of a graph and the number of quadrangles in the graph is deduced.