With great theoretical and practical significance, identifying the node spreading influence of complex network is one of the most promising domains. So far, various topology-based centrality measures have been proposed to identify the node spreading
influence in a network. However, the node spreading influence is a result of the interplay between the network topology structure and spreading dynamics. In this paper, we build up the systematic method by combining the network structure and spreading dynamics to identify the node spreading influence. By combining the adjacent matrix $A$ and spreading parameter $beta$, we theoretical give the node spreading influence with the eigenvector of the largest eigenvalue. Comparing with the Susceptible-Infected-Recovered (SIR) model epidemic results for four real networks, our method could identify the node spreading influence more accurately than the ones generated by the degree, K-shell and eigenvector centrality. This work may provide a systematic method for identifying node spreading influence.
Carbon nanotubes are the focus of considerable research efforts due to their fascinating physical properties. They provide an excellent model system for the study of one dimensional materials and molecular electronics. The chirality of nanotubes can
lead to very different electronic behaviours, either metallic or semiconducting. Their electronic spectrum consists of a series of Van Hove singularities defining a bandgap for semiconducting tubes and molecular orbitals at the corresponding energies. A promising way to tune the nanotubes electronic properties for future applications is to use doping by heteroatoms. Here we report on experimental investigation of the role of many-body interactions in nanotube bandgaps, the visualization in direct space of the molecular orbitals of nanotubes and the properties of nitrogen doped nanotubes using scanning tunneling microscopy and transmission electron microscopy as well as electron energy loss spectroscopy.
