146 resultados para Power law model
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Lithium ion conducting polymer electrolytes based on polyvinyl Alcohol (PVA-OH) complexed with salt Li2SO4 and different weight percent ratios of PEG(400) plasticizer have been prepared by solution cast technique using deionized water as solvent. The thermogravimetric analysis (TGA) showed that the thermal stability of the materials depended on the plasticizer content. The FTIR study confirmed the polymer salt complex formation. The modulus spectra indicated the non-Debye nature of the material; a dominant relaxation process is visible being associated with the dynamic glass transition, relaxation-a. The maximum of each peak is shifted to higher frequencies as the plasticizer increases due to an enhancement of dipolar mobility in the origin of cooperative motions. A power law frequency dependence of the real part of the electrical conductivity is observed, which is characteristic of the effects of ion-ion and/or ion-chain correlations in ion motion. This variation is well fitted to a Jonscher's expression.
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Pós-graduação em Engenharia Elétrica - FEIS
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Biological processes are complex and possess emergent properties that can not be explained or predict by reductionism methods. To overcome the limitations of reductionism, researchers have been used a group of methods known as systems biology, a new interdisciplinary eld of study aiming to understand the non-linear interactions among components embedded in biological processes. These interactions can be represented by a mathematical object called graph or network, where the elements are represented by nodes and the interactions by edges that link pair of nodes. The networks can be classi- ed according to their topologies: if node degrees follow a Poisson distribution in a given network, i.e. most nodes have approximately the same number of links, this is a random network; if node degrees follow a power-law distribution in a given network, i.e. small number of high-degree nodes and high number of low-degree nodes, this is a scale-free network. Moreover, networks can be classi ed as hierarchical or non-hierarchical. In this study, we analised Escherichia coli and Saccharomyces cerevisiae integrated molecular networks, which have protein-protein interaction, metabolic and transcriptional regulation interactions. By using computational methods, such as MathematicaR , and data collected from public databases, we calculated four topological parameters: the degree distribution P(k), the clustering coe cient C(k), the closeness centrality CC(k) and the betweenness centrality CB(k). P(k) is a function that calculates the total number of nodes with k degree connection and is used to classify the network as random or scale-free. C(k) shows if a network is hierarchical, i.e. if the clusterization coe cient depends on node degree. CC(k) is an indicator of how much a node it is in the lesse way among others some nodes of the network and the CB(k) is a pointer of how a particular node is among several ...(Complete abstract click electronic access below)
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Pós-graduação em Engenharia Mecânica - FEG
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Pós-graduação em Engenharia Elétrica - FEIS
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Pós-graduação em Engenharia e Ciência de Alimentos - IBILCE
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)