RESUMO
We analyze the existence of community structures in two different social networks using data obtained from similarity and collaborative features between musical artists. Our analysis reveals some characteristic organizational patterns and provides information about the driving forces behind the growth of the networks. In the similarity network, we find a strong correlation between clusters of artists and musical genres. On the other hand, the collaboration network shows two different kinds of communities: rather small structures related to music bands and geographic zones, and much bigger communities built upon collaborative clusters with a high number of participants related through the period the artists were active. Finally, we detect the leading artists inside their corresponding communities and analyze their roles in the network by looking at a few topological properties of the nodes.
Assuntos
Algoritmos , Comunicação , Comportamento Cooperativo , Modelos Biológicos , Música , Reconhecimento Automatizado de Padrão/métodos , Apoio Social , Simulação por ComputadorRESUMO
The self-similar decay of energy in a turbulent flow is studied in direct numerical simulations with and without rotation. Two initial conditions are considered: one nonhelical (mirror symmetric) and one with maximal helicity. While in the absence of rotation the energy in the helical and nonhelical cases decays with the same rate, in rotating flows the helicity content has a major impact on the decay rate. These differences are associated with differences in the energy and helicity cascades when rotation is present. The properties of the structures in the flow at late times are also discussed.