Eigencentrality based on dissimilarity measures reveals central nodes in complex networks.

One of the most important problems in complex network's theory is the location of the entities that are essential or have a main role within the network. For this purpose, the use of dissimilarity measures (specific to theory of classification and data mining) to enrich the centrality measures in complex networks is proposed. The centrality method used is the eigencentrality which is based on the heuristic that the centrality of a node depends on how central are the nodes in the immediate neighbourhood (like rich get richer phenomenon). This can be described by an eigenvalues problem, however the information of the neighbourhood and the connections between neighbours is not taken in account, neglecting their relevance when is one evaluates the centrality/importance/influence of a node. The contribution calculated by the dissimilarity measure is parameter independent, making the proposed method is also parameter independent. Finally, we perform a comparative study of our method versus other methods reported in the literature, obtaining more accurate and less expensive computational results in most cases.

Comment on "Similarity between quantum mechanics and thermodynamics: Entropy, temperature, and Carnot cycle".

In the paper by Abe and Okuyama [Phys. Rev. E 83, 021121 (2011)], the quantum Carnot cycle of a simple two-state model of a particle confined in a one-dimensional infinite potential well is discussed. It is claimed that the state at the beginning of the quantum Carnot cycle is pure. After that, it is apparently transmuted to a mixed state if Clausius equality is imposed. We prove that this statement is incorrect. In particular, we prove that the state at the beginning of the cycle is mixed due to the process of measuring energy.

Winnerless competition in coupled Lotka-Volterra maps.

Winnerless competition is analyzed in coupled maps with discrete temporal evolution of the Lotka-Volterra type of arbitrary dimension. Necessary and sufficient conditions for the appearance of structurally stable heteroclinic cycles as a function of the model parameters are deduced. It is shown that under such conditions winnerless competition dynamics is fully exhibited. Based on these conditions different cases characterizing low, intermediate, and high dimensions are therefore computationally recreated. An analytical expression for the residence times valid in the N-dimensional case is deduced and successfully compared with the simulations.