Effects of confinement on the electron-phonon interaction in Al(0.18)Ga(0.82)As/GaAs quantum wells

Photoluminescence measurements at different temperatures have been performed to investigate the effects of confinement on the electron-phonon interaction in GaAs/AlGaAs quantum wells (QWs). A series of samples with different well widths in the range from 150 up to 750 A was analyzed. Using a fitting procedure based on the Passler-p model to describe the temperature dependence of the exciton recombination energy, we determined a fit parameter which is related to the strength of the electron-phonon interaction. On the basis of the behavior of this fit parameter as a function of the well width thickness of the samples investigated, we verified that effects of confinement on the exciton recombination energy are still present in QWs with well widths as large as 450 angstrom. Our findings also show that the electron-phonon interaction is three times stronger in GaAs bulk material than in Al(0.18)Ga(0.82)As/GaAs QWs.

Determination of controls on Holocene barrier progradation through application of OSL dating: The Ilha Comprida Barrier example, Southeastern Brazil

Barrier development during the Holocene is studied using the example of the Ilha Comprida, Southeastern Brazil. Aerial photos, facies analysis, and optically stimulated luminescence dating are used to define the barrier emergence and evolution. Optically stimulated luminescence ages and facies successions indicate that the Ilha Comprida probably began as a Holocene transgressive barrier island 6000 years ago, just before the last relative sea-level maximum. Since then the barrier has progradated through the addition of curved beach ridges. Based on beach ridge alignments, six units of growth are identified with two growth directions, transverse and longitudinal. Rates of progradation with transverse growth vary from 0.13 to 4.6 m/year. Rates of longitudinal growth to NE range from 5.2 to 30 m/year. Variation in coastal progradation rates and sediment retention during the last 6000 years is compared with climate, physiography and relative sea-level changes. The physiography, represented by pre-Cenozoic hills, is the major control on sediment retention and alternation between longitudinal and transverse growth. Climate variations, such as the Little Ice Age event, apparently control the formation of ridges types: beach ridges, foredunes, and blowouts. These results allow the use of the Ilha Comprida Barrier as an example to analyze the major controls on barriers progradation. (C) 2011 Elsevier B.V. All rights reserved.

Magnetic linear dichroism in absorption spectroscopy of EuTe

The magnetic linear dichroism (MLD) at band-edge photon energies in the Voigt geometry was calculated for EuTe. At the spin-flop transition, MLD shows a step-like increase. Above the spin-flop transition MLD slowly decreases and becomes zero when the averaged electronic charge becomes symmetric relative to the axis of light propagation. Further increase of the magnetic field causes ferromagnetic alignment of the spins along the magnetic field direction, and MLD is recovered but with an opposite sign, and reaches maximum absolute values. These results are explained by the rearrangement of the Eu(2+) spin distribution in the crystal lattice as a function of magnetic field, due to the Zeeman interaction, demonstrating that MLD can be a sensitive probe of the spin order in EuTe, and provides information that is not accessible from other magneto-optical techniques, such as magnetic circular dichroism measurement studies.

Medical image retrieval based on complexity analysis

Texture is one of the most important visual attributes used in image analysis. It is used in many content-based image retrieval systems, where it allows the identification of a larger number of images from distinct origins. This paper presents a novel approach for image analysis and retrieval based on complexity analysis. The approach consists of a texture segmentation step, performed by complexity analysis through BoxCounting fractal dimension, followed by the estimation of complexity of each computed region by multiscale fractal dimension. Experiments have been performed with MRI database in both pattern recognition and image retrieval contexts. Results show the accuracy of the method and also indicate how the performance changes as the texture segmentation process is altered.

Texture analysis and classification using deterministic tourist walk

In this paper, we present a study on a deterministic partially self-avoiding walk (tourist walk), which provides a novel method for texture feature extraction. The method is able to explore an image on all scales simultaneously. Experiments were conducted using different dynamics concerning the tourist walk. A new strategy, based on histograms. to extract information from its joint probability distribution is presented. The promising results are discussed and compared to the best-known methods for texture description reported in the literature. (C) 2009 Elsevier Ltd. All rights reserved.

Texture analysis using graphs generated by deterministic partially self-avoiding walks

Texture is one of the most important visual attributes for image analysis. It has been widely used in image analysis and pattern recognition. A partially self-avoiding deterministic walk has recently been proposed as an approach for texture analysis with promising results. This approach uses walkers (called tourists) to exploit the gray scale image contexts in several levels. Here, we present an approach to generate graphs out of the trajectories produced by the tourist walks. The generated graphs embody important characteristics related to tourist transitivity in the image. Computed from these graphs, the statistical position (degree mean) and dispersion (entropy of two vertices with the same degree) measures are used as texture descriptors. A comparison with traditional texture analysis methods is performed to illustrate the high performance of this novel approach. (C) 2011 Elsevier Ltd. All rights reserved.

Shape classification using complex network and Multi-scale Fractal Dimension

Shape provides one of the most relevant information about an object. This makes shape one of the most important visual attributes used to characterize objects. This paper introduces a novel approach for shape characterization, which combines modeling shape into a complex network and the analysis of its complexity in a dynamic evolution context. Descriptors computed through this approach show to be efficient in shape characterization, incorporating many characteristics, such as scale and rotation invariant. Experiments using two different shape databases (an artificial shapes database and a leaf shape database) are presented in order to evaluate the method. and its results are compared to traditional shape analysis methods found in literature. (C) 2009 Published by Elsevier B.V.

PLANT LEAF IDENTIFICATION BASED ON VOLUMETRIC FRACTAL DIMENSION

Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characterize it. The proposed method produces a texture signature which is able to efficiently characterize different texture classes. The paper also illustrates a novel method performance on an experiment using texture images of leaves. Leaf identification is a difficult and complex task due to the nature of plants, which presents a huge pattern variation. The high classification rate yielded shows the potential of the method, improving on traditional texture techniques, such as Gabor filters and Fourier analysis.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

On the effects of geographical constraints on task execution in complex

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.

Protecting clean critical points by local disorder correlations

We show that a broad class of quantum critical points can be stable against locally correlated disorder even if they are unstable against uncorrelated disorder. Although this result seemingly contradicts the Harris criterion, it follows naturally from the absence of a random-mass term in the associated order parameter field theory. We illustrate the general concept with explicit calculations for quantum spin-chain models. Instead of the infinite-randomness physics induced by uncorrelated disorder, we find that weak locally correlated disorder is irrelevant. For larger disorder, we find a line of critical points with unusual properties such as an increase of the entanglement entropy with the disorder strength. We also propose experimental realizations in the context of quantum magnetism and cold-atom physics. Copyright (C) EPLA, 2011

An entropy-based approach to automatic image segmentation of satellite images

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.

Texture analysis based on maximum contrast walker

Recently, the deterministic tourist walk has emerged as a novel approach for texture analysis. This method employs a traveler visiting image pixels using a deterministic walk rule. Resulting trajectories provide clues about pixel interaction in the image that can be used for image classification and identification tasks. This paper proposes a new walk rule for the tourist which is based on contrast direction of a neighborhood. The yielded results using this approach are comparable with those from traditional texture analysis methods in the classification of a set of Brodatz textures and their rotated versions, thus confirming the potential of the method as a feasible texture analysis methodology. (C) 2010 Elsevier B.V. All rights reserved.

Dependence of the product on the P-P ligand in reactions of [RuCl(3)(NO)(P-P)] complexes (P-P = aromatic diphosphines) with 2-mercaptopyridine

This study presents the syntheses and characterization of 2-mercaptopyridine (pyS(-)) complexes containing ruthenium(II) with the following general formula [Ru(pyS)(2)(P-P)], P-P = (c-dppen) = cis-1,2-bis(diphenylphosphino)ethylene) (1); (dppe)=1,2-bis(diphenylphosphino)ethane (2); (dppp)=1,3-bis(diphenylphosphino)propane (3) and (dppb) = 1,4-bis(diphenylphosphino)butane (4). The complexes were synthesized from the mer- or fac-[RuCl(3)(NO)(P-P)] precursors in the presence of triethylamine in methanol solution with dependence of the product on the P-P ligand. The reaction of pyS- with a ruthenium complex containing a bulky aromatic diphosphine dppb disclosed a major product with a dangling coordinated dppbO-P, the [Ru(pyS)(2)(NO)(eta(1)-dppbO-P)]PF(6) (5). In addition, this work also presents and discusses the spectroscopic and electrochemical behavior of 1-5. and report the X-ray structures for I and S. (C) 2009 Elsevier Ltd. All rights reserved.

Characterisation, immunolocalisation and antifungal activity of a lipid transfer protein from chili pepper (Capsicum annuum) seeds with novel alpha-amylase inhibitory properties

Lipid transfer proteins (LTPs) were thus named because they facilitate the transfer of lipids between membranes in vitro. This study was triggered by the characterization of a 9-kDa LTP from Capsicum annuum seeds that we call Ca-LTP(1). Ca-LTP(1) was repurified, and in the last chromatographic purification step, propanol was used as the solvent in place of acetonitrile to maintain the protein`s biological activity. Bidimensional electrophoresis of the 9-kDa band, which corresponds to the purified Ca-LTP(1), showed the presence of three isoforms with isoelectric points (pIs) of 6.0, 8.5 and 9.5. Circular dichroism (CD) analysis suggested a predominance of alpha-helices, as expected for the structure of an LTP family member. LTPs immunorelated to Ca-LTP(1) from C. annuum were also detected by western blotting in exudates released from C. annuum seeds and also in other Capsicum species. The tissue and subcellular localization of Ca-LTP(1) indicated that it was mainly localized within dense vesicles. In addition, isolated Ca-LTP(1) exhibited antifungal activity against Colletotrichum lindemunthianum, and especially against Candida tropicalis, causing several morphological changes to the cells including the formation of pseudohyphae. Ca-LTP(1) also caused the yeast plasma membrane to be permeable to the dye SYTOX green, as verified by fluorescence microscopy. We also found that Ca-LTP(1) is able to inhibit mammalian alpha-amylase activity in vitro.