Hierarchical Community Detection Based on Partial Matrix Convergence Using Random Walks

Random walks are a standard tool for modeling the spreading process in social and biological systems.But in the face of large-scale networks,to achieve convergence,iterative calculation of the transition matrix in random walk methods consumes a lot of time.In this paper,we propose a three-stage hierarchical community detection algorithm based on Partial Matrix Approximation Convergence(PMAC) using random walks.First,this algorithm identifies the initial core nodes in a network by classical measurement and then utilizes the error function of the partial transition matrix convergence of the core nodes to determine the number of random walks steps.As such,the PMAC of the core nodes replaces the final convergence of all the nodes in the whole matrix.Finally,based on the approximation convergence transition matrix,we cluster the communities around core nodes and use a closeness index to merge two communities.By recursively repeating the process,a dendrogram of the communities is eventually constructed.We validated the performance of the PMAC by comparing its results with those of two representative methods for three real-world networks with different scales.     

The modernity of Dedekind’s anticipations contained in What are numbers and what are they good for?

Archive for History of Exact Sciences - We show that Dedekind, in his proof of the principle of definition by mathematical recursion, used implicitly both the concept of an inductive cone from an...     

The expansion of GPCR transactivation-dependent signalling to include serine/threonine kinase receptors represents a new cell signalling frontier

G protein-coupled receptor (GPCR) signalling is mediated through transactivation-independent signalling pathways or the transactivation of protein tyrosine kinase receptors and the recently reported activation of the serine/threonine kinase receptors, most notably the transforming growth factor-β receptor family. Since the original observation of GPCR transactivation of protein tyrosine kinase receptors, there has been considerable work on the mechanism of transactivation and several pathways are prominent. These pathways include the “triple membrane bypass” pathway and the generation of reactive oxygen species. The recent recognition of GPCR transactivation of serine/threonine kinase receptors enormously broadens the GPCR signalling paradigm. It may be predicted that the transactivation of serine/threonine kinase receptors would have mechanistic similarities with transactivation of tyrosine kinase pathways; however, initial studies suggest that these two transactivation pathways are mechanistically distinct. Important questions are the relative importance of tyrosine and serine/threonine transactivation pathways, the contribution of transactivation to overall GPCR signalling, mechanisms of transactivation and the range of cell types in which this phenomenon occurs. The ultimate significance of transactivation-dependent signalling remains to be defined but it appears to be prominent and if so will represent a new cell signalling frontier.     

Pierre Duhem’s virtue epistemology

Duhem’s concept of ‘good sense’ is central to his philosophy of science, given that it is what allows scientists to decide between competing theories. Scientists must use good sense and have intellectual and moral virtues in order to be neutral arbiters of scientific theories, especially when choosing between empirically adequate theories. I discuss the parallels in Duhem’s views to those of virtue epistemologists, who understand justified belief as that arrived at by a cognitive agent with intellectual and moral virtues, showing how consideration of Duhem as a virtue epistemologist offers insights into his views, as well as providing possible answers to some puzzles about virtue epistemology. The extent to which Duhem holds that the intellectual and moral virtues of the scientist determine scientific knowledge has not been generally noticed.