Community structure in directed networks

We consider the problem of finding communities or modules in directed networks. The most common approach to this problem in the previous literature has been simply to ignore edge direction and apply methods developed for community discovery in undirected networks, but this approach discards potentially useful information contained in the edge directions. Here we show how the widely used benefit function known as modularity can be generalized in a principled fashion to incorporate the information contained in edge directions. This in turn allows us to find communities by maximizing the modularity over possible divisions of a network, which we do using an algorithm based on the eigenvectors of the corresponding modularity matrix. This method is shown to give demonstrably better results than previous methods on a variety of test networks, both real and computer-generated.Comment: 5 pages, 3 figure

Mixture models and exploratory analysis in networks

Networks are widely used in the biological, physical, and social sciences as a concise mathematical representation of the topology of systems of interacting components. Understanding the structure of these networks is one of the outstanding challenges in the study of complex systems. Here we describe a general technique for detecting structural features in large-scale network data which works by dividing the nodes of a network into classes such that the members of each class have similar patterns of connection to other nodes. Using the machinery of probabilistic mixture models and the expectation-maximization algorithm, we show that it is possible to detect, without prior knowledge of what we are looking for, a very broad range of types of structure in networks. We give a number of examples demonstrating how the method can be used to shed light on the properties of real-world networks, including social and information networks.Comment: 8 pages, 4 figures, two new examples in this version plus minor correction

Vertex similarity in networks

We consider methods for quantifying the similarity of vertices in networks. We propose a measure of similarity based on the concept that two vertices are similar if their immediate neighbors in the network are themselves similar. This leads to a self-consistent matrix formulation of similarity that can be evaluated iteratively using only a knowledge of the adjacency matrix of the network. We test our similarity measure on computer-generated networks for which the expected results are known, and on a number of real-world networks

Large-scale structure of time evolving citation networks

In this paper we examine a number of methods for probing and understanding the large-scale structure of networks that evolve over time. We focus in particular on citation networks, networks of references between documents such as papers, patents, or court cases. We describe three different methods of analysis, one based on an expectation-maximization algorithm, one based on modularity optimization, and one based on eigenvector centrality. Using the network of citations between opinions of the United States Supreme Court as an example, we demonstrate how each of these methods can reveal significant structural divisions in the network, and how, ultimately, the combination of all three can help us develop a coherent overall picture of the network's shape.Comment: 10 pages, 6 figures; journal names for 4 references fixe

LOWER LEG MORPHOLOGY AND STRETCH-SHORTENING CYCLE PERFORMANCE IN YOUNG AND ELDERLY MALES

The purpose of this investigation was to examine bone and muscle characteristics of the lower leg and stretch-shortening cycle capabilities of the ankle in young (22.3 ± 1.3 yrs) and elderly (67.5 ± 3.3 yrs) males. Peripheral quantitiative computed tomography (pQCT) was utilized to assess bone stress-strain index, bone ultimate fracture load, muscle density, muscle cross-sectional area (CSA), fat CSA and muscle+bone CSA. Maximal voluntary isometric plantarflexion (MVIP) force and force-velocity measurments during a countermovement hop (CMH) and drop hops from 20, 30 and 40 cm (DH20, DH30, DH40) were also measured. Bone stress-strain index was significantly higher in young males as well as muscle density, muscle CSA and muscle+bone CSA in comparison to elderly males. MVIP peak force and rate of force development was significantly higher in young males in comparsion to elderly males as well. An analysis of the force-velocity curves indicated that young males had significanlty higher levels of force and velocity in both the eccentric and concentric phase during the CMH, DH20, DH30 and DH40 in comparsion to elderly males. The data from this investigation indicate that aging potentially negatively influences lower leg bone and muscle strength and this may be reflected in lower stretch-shortening cycle capabilities of the ankle

Editorial: Adapted sports:Wheeled-mobility, exercise and health

Editorial on the Research Topic Adapted sports: wheeled-mobility, exercise and health by Vegter RJK, Veeger DHEJ, Goosey-Tolfrey VL and Leicht CA. (2002) Front. Rehabilit. Sci. 3: 1015179. doi: 10.3389/fresc.2022.1015179.</p

Epidemic spreading and bond percolation on multilayer networks

The Susceptible-Infected-Recovered (SIR) model is studied in multilayer networks with arbitrary number of links across the layers. By following the mapping to bond percolation we give the analytical expression for the epidemic threshold and the fraction of the infected individuals in arbitrary number of layers. These results provide an exact prediction of the epidemic threshold for infinite locally tree-like multilayer networks, and an lower bound of the epidemic threshold for more general multilayer networks. The case of a multilayer network formed by two interconnected networks is specifically studied as a function of the degree distribution within and across the layers. We show that the epidemic threshold strongly depends on the degree correlations of the multilayer structure. Finally we relate our results to the results obtained in the annealed approximation for the Susceptible-Infected-Susceptible (SIS) model.Comment: 8 pages, 2 figure

Generation of energy selective excitations in quantum Hall edge states

We operate an on-demand source of single electrons in high perpendicular magnetic fields up to 30T, corresponding to a filling factor below 1/3. The device extracts and emits single charges at a tunable energy from and to a two-dimensional electron gas, brought into well defined integer and fractional quantum Hall (QH) states. It can therefore be used for sensitive electrical transport studies, e.g. of excitations and relaxation processes in QH edge states

Bond percolation on a class of correlated and clustered random graphs

We introduce a formalism for computing bond percolation properties of a class of correlated and clustered random graphs. This class of graphs is a generalization of the Configuration Model where nodes of different types are connected via different types of hyperedges, edges that can link more than 2 nodes. We argue that the multitype approach coupled with the use of clustered hyperedges can reproduce a wide spectrum of complex patterns, and thus enhances our capability to model real complex networks. As an illustration of this claim, we use our formalism to highlight unusual behaviors of the size and composition of the components (small and giant) in a synthetic, albeit realistic, social network.Comment: 16 pages and 4 figure