125 resultados para PARTICLE


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In this work the independent particle model formulation is studied as a mean-field approximation of gauge theories using the path integral approach in the framework of quantum electrodynamics in 1 + 1 dimensions. It is shown how a mean-field approximation scheme can be applied to fit an effective potential to an independent particle model, building a straightforward relation between the model and the associated gauge field theory. An example is made considering the problem of massive Dirac fermions on a line, the so called massive Schwinger model. An interesting result is found, indicating a behaviour of screening of the charges in the relativistic limit of strong coupling. A forthcoming application of the method developed to confining potentials in independent quark models for QCD is in view and is briefly discussed.

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The Pechini method as well as the simultaneous addition of seeds particles and dopant solutions of BaTiO3 (BT) and PbTiO3 (PT) were used to prepare the perovskite phase 0.88 PZN-0.07 BT-0.05 PT. To study the influence of seed particle frequency on the synthesis of the PZN ceramic, two ranges of seed particle size were used: the range from 30 to 100 nm, termed small seed particles (frequency of 10(15) particles/cm(3)); and the range from 100 to 900 nm, termed large seed particles (frequency of 10(13) particles/cm(3)). The crystalline nuclei size influenced the calcining process, the sintering process and the microstructure. Samples prepared with lower seed frequency displayed more amount of pyroclore phase, need higher temperatures for sintering and showed a more heterogeneous microstructure with poor dielectric properties. (C) 2000 Elsevier B.V. Ltd and Techna S.r.l. All rights reserved.

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The controlled growth of SnO2 nanoparticles for gas sensor applications is reported by these authors. Nb2O5 additive is used to control nucleation and growth of the SnO2 (see Figure), which is synthesized by the polymeric precursor method. Preliminary gas sensing measurements are performed and it is demonstrated that the response time of the Nb2O5-doped SnO2 is faster than that of the undoped material.

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Multifractal analysis is now increasingly used to characterize soil properties as it may provide more information than a single fractal model. During the building of a large reservoir on the Parana River (Brazil), a highly weathered soil profile was excavated to a depth between 5 and 8 m. Excavation resulted in an abandoned area with saprolite materials and, in this area, an experimental field was established to assess the effectiveness of different soil rehabilitation treatments. The experimental design consisted of randomized blocks. The aim of this work was to characterize particle-size distributions of the saprolite material and use the information obtained to assess between-block variability. Particle-size distributions of the experimental plots were characterized by multifractal techniques. Ninety-six soil samples were analyzed routinely for particle-size distribution by laser diffractometry in a range of scales, varying from 0.390 to 2000 mu m. Six different textural classes (USDA) were identified with a clay content ranging from 16.9% to 58.4%. Multifractal models described reasonably well the scaling properties of particle-size distributions of the saprolite material. This material exhibits a high entropy dimension, D-1. Parameters derived from the left side (q > 0) of the f(alpha) spectra, D-1, the correlation dimension (D-2) and the range (alpha(0)-alpha(q+)), as well as the total width of the spectra (alpha(max) - alpha(min)) all showed dependence on the clay content. Sand, silt and clay contents were significantly different among treatments as a consequence of soil intrinsic variability. The D, and the Holder exponent of order zero, alpha(0), were not significantly different between treatments; in contrast, D-2 and several fractal attributes describing the width of the f(alpha) spectra were significantly different between treatments. The only parameter showing significant differences between sampling depths was (alpha(0) - alpha(q+)). Scale independent fractal attributes may be useful for characterizing intrinsic particle-size distribution variability. (c) 2006 Elsevier B.V. All rights reserved.

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In this work particles of ZnO of size range 33-56 Angstrom were prepared by a sol-gel method. The effect of reaction time on the particle size of ZnO or ZnO:Ce was investigated by transmission electron microscopy measurements, UV-vis absorption and luminescence spectroscopy. A linear increase of the mean particle size is observed as a function of reaction time. The cerium-doped particles are bigger than the pure ZnO ones obtained at the same reaction time. A shift to lower energy at the maximum of the bands is observed in all absorption, emission and excitation spectra as a function of particle growth. From the absorption spectra the optical energy gap values (Eg) for these particles were determined. In the quantum size regime, Eg was found to decrease with particle growth.

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Concept drift is a problem of increasing importance in machine learning and data mining. Data sets under analysis are no longer only static databases, but also data streams in which concepts and data distributions may not be stable over time. However, most learning algorithms produced so far are based on the assumption that data comes from a fixed distribution, so they are not suitable to handle concept drifts. Moreover, some concept drifts applications requires fast response, which means an algorithm must always be (re) trained with the latest available data. But the process of labeling data is usually expensive and/or time consuming when compared to unlabeled data acquisition, thus only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are also based on the assumption that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenge in machine learning. Recently, a particle competition and cooperation approach was used to realize graph-based semi-supervised learning from static data. In this paper, we extend that approach to handle data streams and concept drift. The result is a passive algorithm using a single classifier, which naturally adapts to concept changes, without any explicit drift detection mechanism. Its built-in mechanisms provide a natural way of learning from new data, gradually forgetting older knowledge as older labeled data items became less influent on the classification of newer data items. Some computer simulation are presented, showing the effectiveness of the proposed method.

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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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It is shown that the paper Wave functions for a Duffin-Kemmer-Petiau particle in a time-dependent potential by Merad and Bensaid [J. Math. Phys. 48, 073515 (2007)] is not correct in using inadvertently a non-Hermitian Hamiltonian in a formalism that does require Hermitian Hamiltonians.

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Morphologies of SrTiO3 particles and agglomerates synthesized by the traditional Pechini route and by the polymer precipitation route were characterized by the nitrogen adsorption/desorption technique and by transmission electron microscopy (TEM). A cluster structure of nanometric particles forming large agglomerates which are broken during pressing followed by cluster rearrangement was observed. The mean particle size is larger for SrTiO3 obtained by the Pechini route and is related to the precursor thermal decomposition and particle growth during calcination. The particle growth is controlled by neck growth among particles and further motion of the particle boundary. © 1995.

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We examine further astrophysical constraints on a light spinless particle coupled only to photons and proposed by Massó and Toldra. We consider constraints coming from measurements of extra galactic background and from ionization of HI clouds.

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The particle-growth kinetics of sodium niobate and zirconium titanate powders that were processed by the polymeric precursors method were studied. The growth kinetics that were studied for the particle, in the final stage of crystallization, showed that the growth process occurs in two different stages. For temperatures <800°C, the particle-growth mechanism is associated with surface diffusion, with an activation energy in the range of 40-80 KJ/mol. For temprratures >800°C, particle growth is controlled by densification of the nanometric particle cluster and by a neck-size-controlled particle-growth mechanism. The results suggest that this behavior was typical of the synthesis method, because two different polycation oxides presented the same behavior.

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By studying classical realizations of the sl(2, R-fraktur sign) algebra in a two dimensional phase space (q,π), we have derived a continuous family of new actions for free fractional spin particles in 2 + 1 dimensions. For the case of light-like spin vector (SμSμ = 0), the action is remarkably simple. We show the appearence of the Zitterbewegung in the solutions of the equations of motion, and relate the actions to others in the literature at classical level. © 1997 Elsevier Science B.V.

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The usual particle emission scenario used in hydrodynamics presupposes that particles instantaneously stop interacting (freeze-out) once they reach some three dimensional surface. Another formalism has been developed recently where particle emission occurs continuously during the whole expansion of thermalized matter. Here we compare both mechanisms in a simplified hydrodynamical framework and show that they lead to a drastically different interpretation of data.