7 resultados para Spatially

em Universidad Politécnica de Madrid


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Neuronal growth is a complex process involving many intra- and extracellular mechanisms which are collaborating conjointly to participate to the development of the nervous system. More particularly, the early neocortical development involves the creation of a multilayered structure constituted by neuronal growth (driven by axonal or dendritic guidance cues) as well as cell migration. The underlying mechanisms of such structural lamination not only implies important biochemical changes at the intracellular level through axonal microtubule (de)polymerization and growth cone advance, but also through the directly dependent stress/stretch coupling mechanisms driving them. Efforts have recently focused on modeling approaches aimed at accounting for the effect of mechanical tension or compression on the axonal growth and subsequent soma migration. However, the reciprocal influence of the biochemical structural evolution on the mechanical properties has been mostly disregarded. We thus propose a new model aimed at providing the spatially dependent mechanical properties of the axon during its growth. Our in-house finite difference solver Neurite is used to describe the guanosine triphosphate (GTP) transport through the axon, its dephosphorylation in guanosine diphosphate (GDP), and thus the microtubules polymerization. The model is calibrated against experimental results and the tensile and bending mechanical stiffnesses are ultimately inferred from the spatially dependent microtubule occupancy. Such additional information is believed to be of drastic relevance in the growth cone vicinity, where biomechanical mechanisms are driving axonal growth and pathfinding. More specifically, the confirmation of a lower stiffness in the distal axon ultimately participates in explaining the controversy associated to the tensile role of the growth cone.

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Numerical investigations on mutual interactions between two spatially overlapping standing electromagnetic solitons in a cold unmagnetized plasma are reported. It is found that an initial state comprising of two overlapping standing solitons evolves into different end states, depending on the amplitudes of the two solitons and the phase difference between them. For small amplitude solitons with zero phase difference, we observe the formation of an oscillating bound state whose period depends on their initial separation. These results suggest the existence of a bound state made of two solitons in the relativistic cold plasma fluid model.

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Within our study of the plausibility of a subglacial lake under the Amundsenisen Icefield in Southern Spitzbergen, Svalbard achipelago (Glowacki et al., 2007), here we focus on the sensitivity of the system to the thermal effect of the firn and snow layers. Rough heat balance analysis shows that the firn layer plays an important role by driving the heat release to the atmosphere, so that its influence on the ice-water phase transition cannot be neglected (Bucchignani et al., 2012).

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Contact Spatially Resolved Spectroscopy (SRS) measurements by means of a fiber-optics probe were employed for nondestructive assessment and monitoring of Braeburn apples during shelflife storage. SRS measurements and estimation of optical properties were calibrated and validated by means of liquid optical phantoms with known optical properties and a metamodeling method. The acquired optical properties (absorption and reduced scattering coefficients) for the apples during shelf-life storage were found to provide useful information for nondestructive evaluation of apple quality attributes (firmness and SSC) and for monitoring the changes in their microstructure and chemical composition. On-line SRS measurement was achieved by mounting the SRS probe over a conveyor system

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This article presents a new and computationally efficient method of analysis of a railway track modelled as a continuous beam of 2N spans supported by elastic vertical springs. The main feature of this method is its important reduction in computational effort with respect to standard matrix methods of structural analysis. In this article, the whole structure is considered to be a repetition of a single one. The analysis presented is applied to a simple railway track model, i.e. to a repetitive beam supported on vertical springs (sleepers). The proposed method of analysis is based on the general theory of spatially periodic structures. The main feature of this theory is the possibility to apply Discrete Fourier Transform (DFT) in order to reduce a large system of q(2N + 1) linear stiffness equilibrium equations to a set of 2N + 1 uncoupled systems of q equations each. In this way, a dramatic reduction of the computational effort of solving the large system of equations is achieved. This fact is particularly important in the analysis of railway track structures, in which N is a very large number (around several thousands), and q = 2, the vertical displacement and rotation, is very small. The proposed method allows us to easily obtain the exact solution given by Samartín [1], i.e. the continuous beam railway track response. The comparison between the proposed method and other methods of analysis of railway tracks, such as Lorente de Nó and Zimmermann-Timoshenko, clearly shows the accuracy of the obtained results for the proposed method, even for low values of N. In addition, identical results between the proposed and the Lorente methods have been found, although the proposed method seems to be of simpler application and computationally more efficient than the Lorente one. Small but significative differences occur between these two methods and the one developed by Zimmermann-Timoshenko. This article also presents a detailed sensitivity analysis of the vertical displacement of the sleepers. Although standard matrix methods of structural analysis can handle this railway model, one of the objectives of this article is to show the efficiency of DFT method with respect to standard matrix structural analysis. A comparative analysis between standard matrix structural analysis and the proposed method (DFT), in terms of computational time, input, output and also software programming, will be carried out. Finally, a URL link to a MatLab computer program list, based on the proposed method, is given

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A novel GPU-based nonparametric moving object detection strategy for computer vision tools requiring real-time processing is proposed. An alternative and efficient Bayesian classifier to combine nonparametric background and foreground models allows increasing correct detections while avoiding false detections. Additionally, an efficient region of interest analysis significantly reduces the computational cost of the detections.

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Mapping aboveground carbon density in tropical forests can support CO2 emissionmonitoring and provide benefits for national resource management. Although LiDAR technology has been shown to be useful for assessing carbon density patterns, the accuracy and generality of calibrations of LiDAR-based aboveground carbon density (ACD) predictions with those obtained from field inventory techniques should be intensified in order to advance tropical forest carbon mapping. Here we present results from the application of a general ACD estimation model applied with small-footprint LiDAR data and field-based estimates of a 50-ha forest plot in Ecuador?s Yasuní National Park. Subplots used for calibration and validation of the general LiDAR equation were selected based on analysis of topographic position and spatial distribution of aboveground carbon stocks. The results showed that stratification of plot locations based on topography can improve the calibration and application of ACD estimation using airborne LiDAR (R2 = 0.94, RMSE = 5.81 Mg?C? ha?1, BIAS = 0.59). These results strongly suggest that a general LiDAR-based approach can be used for mapping aboveground carbon stocks in western lowland Amazonian forests.