23 resultados para contour map


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The paper focusses on the existence of higher open book structures defined by real map germs psi : (R(m), 0) -> (R(p), 0) such that Sing psi boolean AND psi(-1)(0) subset of {0}. A general existence criterion is proved, with view to weighted-homogeneous maps.

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The non-twist standard map occurs frequently in many fields of science specially in modelling the dynamics of the magnetic field lines in tokamaks. Robust tori, dynamical barriers that impede the radial transport among different regions of the phase space, are introduced in the non-twist standard map in a conservative fashion. The resulting non-twist standard map with robust tori is an improved model to study transport barriers in plasmas confined in tokamaks.

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We study a symplectic chain with a non-local form of coupling by means of a standard map lattice where the interaction strength decreases with the lattice distance as a power-law, in Such a way that one can pass continuously from a local (nearest-neighbor) to a global (mean-field) type of coupling. We investigate the formation of map clusters, or spatially coherent structures generated by the system dynamics. Such clusters are found to be related to stickiness of chaotic phase-space trajectories near periodic island remnants, and also to the behavior of the diffusion coefficient. An approximate two-dimensional map is derived to explain some of the features of this connection. (C) 2008 Elsevier Ltd. All rights reserved.

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In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

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This paper presents the groundwater favorability mapping on a fractured terrain in the eastern portion of Sao Paulo State, Brazil. Remote sensing, airborne geophysical data, photogeologic interpretation, geologic and geomorphologic maps and geographic information system (GIS) techniques have been used. The results of cross-tabulation between these maps and well yield data allowed groundwater prospective parameters in a fractured-bedrock aquifer. These prospective parameters are the base for the favorability analysis whose principle is based on the knowledge-driven method. The mutticriteria analysis (weighted linear combination) was carried out to give a groundwater favorabitity map, because the prospective parameters have different weights of importance and different classes of each parameter. The groundwater favorability map was tested by cross-tabulation with new well yield data and spring occurrence. The wells with the highest values of productivity, as well as all the springs occurrence are situated in the excellent and good favorabitity mapped areas. It shows good coherence between the prospective parameters and the well yield and the importance of GIS techniques for definition of target areas for detail study and wells location. (c) 2008 Elsevier B.V. All rights reserved.

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This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

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In this paper we study and present a complete classification of spacelike surfaces with degenerate Gauss map in the Lorentz-Minkowski space L(4).

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Accumulating evidence indicates that post-translational protein modifications by nitric oxide and its derived species are critical effectors of redox signaling in cells. These protein modifications are most likely controlled by intracellular reductants. Among them, the importance of the 12 kDa dithiol protein thioredoxin-1 (TRX-1) has been increasingly recognized. However, the effects of TRX-1 in cells exposed to exogenous nitrosothiols remain little understood. We investigated the levels of intracellular nitrosothiols and survival signaling in HeLa cells over-expressing TRX-1 and exposed to S-nitrosoglutahione (GSNO). A role for TRX-1 expression on GSNO catabolism and cell viability was demonstrated by the concentration-dependent effects of GSNO on decreasing TRX-1 expression, activation of capase-3, and increasing cell death. The over-expressaion of TRX-1 in HeLa cells partially attenuated caspase-3 activation and enhanced cell viability upon GSNO treatment. This was correlated with reduction of intracellular levels of nitrosothiols and increasing levels of nitrite and nitrotyrosine. The involvement of ERK, p38 and JNK pathways were investigated in parental cells treated with GSNO. Activation of ERK1/2 MAP kinases was shown to be critical for survival signaling. lit cells over-expressing TRX-1, basal phosphorylation levels of ERK1/2 MAP kinases were higher and further increased after GSNO treatment. These results indicate that the enhanced cell viability promoted by TRX-1 correlates with its capacity to regulate the levels of intracellular nitiosothiols and to up-regulate the survival signaling pathway mediated by the ERK1/2 MAP kinases.