98 resultados para Luciano de Samosata


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In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks.

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The comprehensive characterization of the structure of complex networks is essential to understand the dynamical processes which guide their evolution. The discovery of the scale-free distribution and the small-world properties of real networks were fundamental to stimulate more realistic models and to understand important dynamical processes related to network growth. However, the properties of the network borders (nodes with degree equal to 1), one of its most fragile parts, remained little investigated and understood. The border nodes may be involved in the evolution of structures such as geographical networks. Here we analyze the border trees of complex networks, which are defined as the subgraphs without cycles connected to the remainder of the network (containing cycles) and terminating into border nodes. In addition to describing an algorithm for identification of such tree subgraphs, we also consider how their topological properties can be quantified in terms of their depth and number of leaves. We investigate the properties of border trees for several theoretical models as well as real-world networks. Among the obtained results, we found that more than half of the nodes of some real-world networks belong to the border trees. A power-law with cut-off was observed for the distribution of the depth and number of leaves of the border trees. An analysis of the local role of the nodes in the border trees was also performed.

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In the present work, the effects of spatial constraints on the efficiency of task execution in systems underlain by geographical complex networks are investigated, where the probability of connection decreases with the distance between the nodes. The investigation considers several configurations of the parameters defining the network connectivity, and the Barabasi-Albert network model is also considered for comparisons. The results show that the effect of connectivity is significant only for shorter tasks, the locality of connection simplied by the spatial constraints reduces efficiency, and the addition of edges can improve the efficiency of the execution, although with increasing locality of the connections the improvement is small.

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The method employed to incorporate guest molecules onto phospholipid Langmuir monolayers plays an important role in the interaction between the monolayer and the guest molecules. In this paper, we show that for the interaction between horseradish peroxidase (HRP) and a monolayer of dipalmitoylphosphatidylglycerol (DPPG) does depend on the method of HRP incorporation. The surface pressure isotherms of the mixed DPPG/HRP monolayers, for instance, were less expanded when the two materials were co-spread than in the case where HRP was injected into the subphase. Therefore, the method for incorporation affected not only the penetration of HRP but also the changes in molecular packing caused to the DPPG monolayer. With experiments with the monolayer on a pendant drop, we observed that the incorporation of HRP affects the dynamic elasticity of the DPPG monolayer, on a way that varies with the surface pressure. At low pressures, HRP causes the monolayer to be more rigid, while the converse is true for surface pressures above 8 mN/m. Taken all the results together, we conclude that HRP is more efficiently incorporated if injected into the subphase on which a DPPG monolayer had been spread and that the interaction between HRP and DPPG is maintained even at high surface pressures. This is promising for the possible transfer of mixed films onto solid substrates and for applications in biosensors and drug delivery systems. (c) 2008 Elsevier B.V. All rights reserved.

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Inside the `cavernous sinus` or `parasellar region` the human internal carotid artery takes the shape of a siphon that is twisted and torqued in three dimensions and surrounded by a network of veins. The parasellar section of the internal carotid artery is of broad biological and medical interest, as its peculiar shape is associated with temperature regulation in the brain and correlated with the occurrence of vascular pathologies. The present study aims to provide anatomical descriptions and objective mathematical characterizations of the shape of the parasellar section of the internal carotid artery in human infants and its modifications during ontogeny. Three-dimensional (3D) computer models of the parasellar section of the internal carotid artery of infants were generated with a state-of-the-art 3D reconstruction method and analysed using both traditional morphometric methods and novel mathematical algorithms. We show that four constant, demarcated bends can be described along the infant parasellar section of the internal carotid artery, and we provide measurements of their angles. We further provide calculations of the curvature and torsion energy, and the total complexity of the 3D skeleton of the parasellar section of the internal carotid artery, and compare the complexity of this in infants and adults. Finally, we examine the relationship between shape parameters of the parasellar section of the internal carotid artery in infants, and the occurrence of intima cushions, and evaluate the reliability of subjective angle measurements for characterizing the complexity of the parasellar section of the internal carotid artery in infants. The results can serve as objective reference data for comparative studies and for medical imaging diagnostics. They also form the basis for a new hypothesis that explains the mechanisms responsible for the ontogenetic transformation in the shape of the parasellar section of the internal carotid artery.

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Many chitosan biological activities depend on the interaction with biomembranes, but so far it has not been possible to obtain molecular-level evidence of chitosan action. In this article, we employ Langmuir phospholipid monolayers as cell membrane models and show that chitosan is able to remove beta-lactoglobulin (BLG) from negatively charged dimyristoyl phosphatidic acid (DMPA) and dipalmitoyl phosphatidyl glycerol (DPPG). This was shown with surface pressure isotherms and elasticity and PM-IRRAS measurements in the Langmuir monolayers, in addition to quartz crystal microbalance and fluorescence spectroscopy measurements for Langmuir-Blodgett (LB) films transferred onto solid substrates. Some specificity was noted in the removal action because chitosan was unable to remove BLG incorporated into neutral dipalmitoyl phosphatidyl choline (DPPC) and cholesterol monolayers and had no effect on horseradish peroxidase and urease interacting with DMPA. An obvious biological implication of these findings is to offer reasons that chitosan can remove BLG from lipophilic environments, as reported in the recent literature.

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Complex networks have been increasingly used in text analysis, including in connection with natural language processing tools, as important text features appear to be captured by the topology and dynamics of the networks. Following previous works that apply complex networks concepts to text quality measurement, summary evaluation, and author characterization, we now focus on machine translation (MT). In this paper we assess the possible representation of texts as complex networks to evaluate cross-linguistic issues inherent in manual and machine translation. We show that different quality translations generated by NIT tools can be distinguished from their manual counterparts by means of metrics such as in-(ID) and out-degrees (OD), clustering coefficient (CC), and shortest paths (SP). For instance, we demonstrate that the average OD in networks of automatic translations consistently exceeds the values obtained for manual ones, and that the CC values of source texts are not preserved for manual translations, but are for good automatic translations. This probably reflects the text rearrangements humans perform during manual translation. We envisage that such findings could lead to better NIT tools and automatic evaluation metrics.

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Multidimensional scaling is applied in order to visualize an analogue of the small-world effect implied by edges having different displacement velocities in transportation networks. Our findings are illustrated for two real-world systems, namely the London urban network (streets and underground) and the US highway network enhanced by some of the main US airlines routes. We also show that the travel time in these two networks is drastically changed by attacks targeting the edges with large displacement velocities. (C) 2011 Elsevier By. All rights reserved.

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The potential profile for a model of squid axon membrane has been determined for two physiological states: resting and action states. The non-linear Poisson-Boltzmann equation has been solved by considering the volumetric charge densities due to charges dissolved in an electrolytic solution and fixed on both glycocalyx and cytoplasmatic proteins. Results showing the features of the potential profile along the outer electrolytic region are similar for both resting and action states. However, the potential fall along glycocalyx at action state is lower than at resting. A small variation in the Na+ concentration drastically affects the surface membrane potentials and vice versa. We conclude that effects on the potential profile due to surface lipidic bilayer charge and contiguous electric double layers are more relevant than those provoked by fixed charges distributed along the cell cytoplasm. (c) 2007 Elsevier B.V. All rights reserved.

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The immobilization of enzymes in organized two-dimensional matrices is a key requirement for many biotechnological applications. In this paper, we used the Langmuir-Blodgett (LB) technique to obtain controlled architectures of urease immobilized in solid supports, whose physicochemical properties were investigated in detail. Urease molecules were adsorbed at the air-water interface and incorporated into Langmuir monolayers of the phospholipid dipalmitoyl phosphatidyl glycerol (DPPG). Incorporation of urease made DPPG monolayers more flexible and caused the reduction of the equilibrium and dynamic elasticity of the film. Urease and DPPG-urease mixed monolayers could be transferred onto solid substrates, forming LB films. A close packing arrangement of urease was obtained, especially in the mixed LB films, which was inferred with nanogravimetry and electrochemistry measurements. From the blocking effect of the LB films deposited onto indium tin oxide (ITO) substrates, the electrochemical properties of the LB films pointed to a charge transport controlled by the lipid architecture. (c) 2007 Elsevier Inc. All rights reserved.

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Using digitized images of the three-dimensional, branching structures for root systems of bean seedlings, together with analytical and numerical methods that map a common susceptible-infected- recovered (`SIR`) epidemiological model onto the bond percolation problem, we show how the spatially correlated branching structures of plant roots affect transmission efficiencies, and hence the invasion criterion, for a soil-borne pathogen as it spreads through ensembles of morphologically complex hosts. We conclude that the inherent heterogeneities in transmissibilities arising from correlations in the degrees of overlap between neighbouring plants render a population of root systems less susceptible to epidemic invasion than a corresponding homogeneous system. Several components of morphological complexity are analysed that contribute to disorder and heterogeneities in the transmissibility of infection. Anisotropy in root shape is shown to increase resilience to epidemic invasion, while increasing the degree of branching enhances the spread of epidemics in the population of roots. Some extension of the methods for other epidemiological systems are discussed.

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This paper applies the concepts and methods of complex networks to the development of models and simulations of master-slave distributed real-time systems by introducing an upper bound in the allowable delivery time of the packets with computation results. Two representative interconnection models are taken into account: Uniformly random and scale free (Barabasi-Albert), including the presence of background traffic of packets. The obtained results include the identification of the uniformly random interconnectivity scheme as being largely more efficient than the scale-free counterpart. Also, increased latency tolerance of the application provides no help under congestion.

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We consider climate networks constructed from observed and model simulated fields of three climate variables and investigate their community structure. We find that for all fields the number of effective communities is rather small (four to five). We are able to trace the origin of these communities to certain dynamical properties of climate. Our results suggest that the complete complexity of the climate system condenses beyond the `weather` time scales into a small number of low-dimensional interacting components and provide clues as to the nature of the climate subsystems underlying these components.

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An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

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Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex networks. Specifically, we extend our previous work by employing additional metrics of complex networks, whose results were used as input for machine learning methods and allowed MT texts of distinct qualities to be distinguished. Also shown is that the node-to-node mapping between source and target texts (English-Portuguese and Spanish-Portuguese pairs) can be improved by adding further hierarchical levels for the metrics out-degree, in-degree, hierarchical common degree, cluster coefficient, inter-ring degree, intra-ring degree and convergence ratio. The results presented here amount to a proof-of-principle that the possible capturing of a wider context with the hierarchical levels may be combined with machine learning methods to yield an approach for assessing the quality of MT systems. (C) 2010 Elsevier B.V. All rights reserved.