DECEA - Departamento de Ciências Exatas e Aplicadas
URI permanente desta comunidadehttp://www.hml.repositorio.ufop.br/handle/123456789/551
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Resultados da Pesquisa
Item The diffusive epidemic process on Barabasi–Albert networks.(2021) Alves, Tayroni Francisco de Alencar; Alves, Gladstone de Alencar; Macedo Filho, Antonio de; Ferreira, Ronan Silva; Lima, Francisco Welington de SousaWe present a modified diffusive epidemic process (DEP) that has a finite threshold on scale-free graphs, motivated by the COVID-19 pandemic. The DEP describes the epidemic spreading of a disease in a non-sedentary population, which can describe the spreading of a real disease. Our main modification is to use the Gillespie algorithm with a reaction time tmax, exponentially distributed with mean inversely proportional to the node population in order to model the individuals’ interactions. Our simulation results of the modified model on Barabasi–Albert networks are compatible with a continuous absorbing-active phase transition when increasing the average concentration. The transition obeys the mean-field critical exponents β = 1, γ = 0 and ν⊥ = 1/2. In addition, the system presents logarithmic corrections with pseudo-exponents β = γ = −3/2 on the order parameter and its fluctuations, respectively. The most evident implication of our simulation results is if the individuals avoid social interactions in order to not spread a disease, this leads the system to have a finite threshold in scale-free graphs.Item q-Weibull distributions describing commercial service routes.(2020) Ferreira, Ronan Silva; Silva, Priscila Caroline Albuquerque daWe present an investigation of the mode of road transport in Brazil combining tools of complex networks and real-data. Our analysis involves a dataset based on the service routes inscribed on the Brazilian Transport Agency database. Although connectivity distributions of road networks worldwide are usually claimed as described by a power-law fashion, we report a better fit for the Brazilian case offered by the q-Weibull distribution. In our approach nodes assume the role of localities, whereas links represent service routes among them. Interestingly, a rapid drop takes place on the tail of the data distribution for a particular range of the number of outgoing connections. The mechanism responsible for driving this drop is revealed by investigating the spectral centrality of the network and different patterns of disassortative mixture, for both incoming and outgoing distributions. Besides a discussion about a power law description, we report a contrast with two different distributions. They are interpolated by the q-Weibull one: the Weibull and the q-exponential distributions. Moreover, we study the reciprocity of this network, which reflects the influence of mutual links over dynamical processes. This kind of analysis is indispensable for studies on human mobility, shipping, and a multi-modal perspective