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.

ENHANCING MULTISCALE FRACTAL DESCRIPTORS USING FUNCTIONAL DATA ANALYSIS

This work presents a novel approach in order to increase the recognition power of Multiscale Fractal Dimension (MFD) techniques, when applied to image classification. The proposal uses Functional Data Analysis (FDA) with the aim of enhancing the MFD technique precision achieving a more representative descriptors vector, capable of recognizing and characterizing more precisely objects in an image. FDA is applied to signatures extracted by using the Bouligand-Minkowsky MFD technique in the generation of a descriptors vector from them. For the evaluation of the obtained improvement, an experiment using two datasets of objects was carried out. A dataset was used of characters shapes (26 characters of the Latin alphabet) carrying different levels of controlled noise and a dataset of fish images contours. A comparison with the use of the well-known methods of Fourier and wavelets descriptors was performed with the aim of verifying the performance of FDA method. The descriptor vectors were submitted to Linear Discriminant Analysis (LDA) classification method and we compared the correctness rate in the classification process among the descriptors methods. The results demonstrate that FDA overcomes the literature methods (Fourier and wavelets) in the processing of information extracted from the MFD signature. In this way, the proposed method can be considered as an interesting choice for pattern recognition and image classification using fractal analysis.

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.

Head shape evolution in Tropidurinae lizards: does locomotion constrain diet?

Different components of complex integrated systems may be specialized for different functions, and thus the selective pressures acting on the system as a whole may be conflicting and can ultimately constrain organismal performance and evolution. The vertebrate cranial system is one of the most striking examples of a complex system with several possible functions, being associated to activities as different as locomotion, prey capture, display and defensive behaviours. Therefore, selective pressures on the cranial system as a whole are possibly complex and may be conflicting. The present study focuses on the influence of potentially conflicting selective pressures (diet vs. locomotion) on the evolution of head shape in Tropidurinae lizards. For example, the expected adaptations leading to flat heads and bodies in species living on vertical structures may conflict with the need for improved bite performance associated with the inclusion of hard or tough prey into the diet, a common phenomenon in Tropidurinae lizards. Body size and six variables describing head shape were quantified in preserved specimens of 23 species, and information on diet and substrate usage was obtained from the literature. No phylogenetic signal was observed in the morphological data at any branch length tested, suggesting adaptive evolution of head shape in Tropidurinae. This pattern was confirmed by both factor analysis and independent contrast analysis, which suggested adaptive co-variation between the head shape and the inclusion of hard prey into the diet. In contrast to our expectations, habitat use did not constrain or drive head shape evolution in the group.

Shape and size of red blood cells from the Pygoscelid penguins of Antarctica using atomic force microscopy

Antarctic biodiversity is evolutionarily complex, reflecting the extreme ambient conditions. Therefore, Antarctic organisms exhibit sophisticated adaptations in all organization levels, including organs, tissues, and cells. Since red blood cells (RBCs) travel through the vertebrates blood delivering O(2) to all tissues and organs and purging the unwanted CO(2), they represent an interesting model to investigate biological adaptations. We have used atomic force microscopy (AFM) to compare the shape and size of RBCs of the Pygoscelid penguins. A total of 18 landmarks were measured in AFM images. When analyzed individually, the parameters were not capable of discriminating the RBCs of each species. However, the simultaneous use of multiple parameters discriminated (74%) among the RBCs. In addition, the use of RBC measurements was sufficient to hierarchically cluster the species in accordance to other common and reliable phylogenetic strategies. In light of these results, the use of RBC characters could effectively benefit taxonomic inferences.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Joint Experimental and Theoretical Analysis of Order Disorder Effects in Cubic BaZrO(3) Assembled Nanoparticles under Decaoctahedral Shape

Periodic first-principles calculations based on density functional theory at the B3LYP level has been carried out to investigate the photoluminescence (PL) emission of BaZrO(3) assembled nanoparticles at room temperature. The defect created in the nanocrystals and their resultant electronic features lead to a diversification of electronic recombination within the BaZrO(3) band gap. Its optical phenomena are discussed in the light of photoluminescence emission at the green-yellow region around 570 nm. The theoretical model for displaced atoms and/or angular changes leads to the breaking of the local symmetry, which is based on the refined structure provided by Rietveld methodology. For each situation a band structure, charge mapping, and density of states were built and analyzed. X-ray diffraction (XRD) patterns, UV-vis measurements, and field emission scanning electron microscopy (FE-SEM) images are essential for a full evaluation of the crystal structure and morphology.

Plant Leaf Identification Using Gabor Wavelets

This article presents a novel method of plant classification using Gabor wavelet filters to extract texture filters in a foliar surface. The aim of this promising method is to add to the results obtained by other leaf attributes (such as shape, contour, color, among others), increasing, therefore, the percentage of classification of plant species. To corroborate the efficiency of the technique, an experiment using 20 species from Brazilian flora was done and discussed. The results are also compared with texture Fourier descriptors and cooccurrence matrices. (C) 2009 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 19, 236-243, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20201

Two- and three-dimensional shape fabric analysis by the intercept method in grey levels

The count intercept is a robust method for the numerical analysis of fabrics Launeau and Robin (1996). It counts the number of intersections between a set of parallel scan lines and a mineral phase, which must be identified on a digital image. However, the method is only sensitive to boundaries and therefore supposes the user has some knowledge about their significance. The aim of this paper is to show that a proper grey level detection of boundaries along scan lines is sufficient to calculate the two-dimensional anisotropy of grain or crystal distributions without any particular image processing. Populations of grains and crystals usually display elliptical anisotropies in rocks. When confirmed by the intercept analysis, a combination of a minimum of 3 mean length intercept roses, taken on 3 more or less perpendicular sections, allows the calculation of 3-dimensional ellipsoids and the determination of their standard deviation with direction and intensity in 3 dimensions as well. The feasibility of this quick method is attested by numerous examples on theoretical objects deformed by active and passive deformation, on BSE images of synthetic magma flow, on drawing or direct analysis of thin section pictures of sandstones and on digital images of granites directly taken and measured in the field. (C) 2010 Elsevier B.V. All rights reserved.

Improved likelihood inference for the shape parameter in Weibull regression

We obtain adjustments to the profile likelihood function in Weibull regression models with and without censoring. Specifically, we consider two different modified profile likelihoods: (i) the one proposed by Cox and Reid [Cox, D.R. and Reid, N., 1987, Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society B, 49, 1-39.], and (ii) an approximation to the one proposed by Barndorff-Nielsen [Barndorff-Nielsen, O.E., 1983, On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70, 343-365.], the approximation having been obtained using the results by Fraser and Reid [Fraser, D.A.S. and Reid, N., 1995, Ancillaries and third-order significance. Utilitas Mathematica, 47, 33-53.] and by Fraser et al. [Fraser, D.A.S., Reid, N. and Wu, J., 1999, A simple formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 655-661.]. We focus on point estimation and likelihood ratio tests on the shape parameter in the class of Weibull regression models. We derive some distributional properties of the different maximum likelihood estimators and likelihood ratio tests. The numerical evidence presented in the paper favors the approximation to Barndorff-Nielsen`s adjustment.

Use of self-organizing maps and molecular descriptors to predict the cytotoxic activity of sesquiterpene lactones

Some sesquiterpene lactones (SLs) are the active compounds of a great number of traditionally medicinal plants from the Asteraceae family and possess considerable cytotoxic activity. Several studies in vitro have shown the inhibitory activity against cells derived from human carcinoma of the nasopharynx (KB). Chemical studies showed that the cytotoxic activity is due to the reaction of alpha,beta-unsaturated carbonyl structures of the SLs with thiols, such as cysteine. These studies support the view that SLs inhibit tumour growth by selective alkylation of growth-regulatory biological macromolecules, such as key enzymes, which control cell division, thereby inhibiting a variety of cellular functions, which directs the cells into apoptosis. In this study we investigated a set of 55 different sesquiterpene lactones, represented by 5 skeletons (22 germacranolides, 6 elemanolides, 2 eudesmanolides, 16 guaianolides and nor-derivatives and 9 pseudoguaianolides), in respect to their cytotoxic properties. The experimental results and 3D molecular descriptors were submitted to Kohonen self-organizing map (SOM) to classify (training set) and predict (test set) the cytotoxic activity. From the obtained results, it was concluded that only the geometrical descriptors showed satisfactory values. The Kohonen map obtained after training set using 25 geometrical descriptors shows a very significant match, mainly among the inactive compounds (similar to 84%). Analyzing both groups, the percentage seen is high (83%). The test set shows the highest match, where 89% of the substances had their cytotoxic activity correctly predicted. From these results, important properties for the inhibition potency are discussed for the whole dataset and for subsets of the different structural skeletons. (C) 2008 Elsevier Masson SAS. All rights reserved.

Volsurf Descriptors to Analyse Anti-HCV and Cytotoxic Activities of Sesquiterpene Lactones from Asteraceae Family

Various significant anti-HCV and cytotoxic sesquiterpene lactones (SLs) have been characterized. In this work, the chemometric tool Principal Component Analysis (PCA) was applied to two sets of SLs and the variance of the biological activity was explored. The first principal component accounts for as much of the variability in the data as possible, and each succeeding component accounts for as much of the remaining variability as possible. The calculations were performed using VolSurf program. For anti-HCV activity, PC1 (First Principal Component) explained 30.3% and PC2 (Second Principal Component) explained 26.5% of matrix total variance, while for cytotoxic activity, PC1 explained 30.9% and PC2 explained 15.6% of the total variance. The formalism employed generated good exploratory and predictive results and we identified some structural features, for both sets, important to the suitable biological activity and pharmacokinetic profile.

Perpendicularly self-oriented and shape-controlled L1(0)-FePt nanorods directly synthesized by a temperature-modulated process

The synthesis and self-assembly of tetragonal phase-containing L1(0)-Fe(55)Pt(45) nanorods with high coercive field is described. The experimental procedure resulted in a tetragonal/cubic phase ratio close to 1:1 for the as-synthesized nanoparticles. Using different surfactant/solvent proportions in the process allowed control of particle morphology from nanospheres to nanowires. Monodisperse nanorods with lengths of 60 +/- 5 nm and diameters of 2-3 nm were self-assembled in a perpendicular oriented array onto a substrate surface using hexadecylamine as organic spacer. Magnetic alignment and properties assigned, respectively, to the shape anisotropy and the tetragonal phase suggest that the self-assembled materials are a strong candidate to solve the problem of random magnetic alignment observed in FePt nanospheres leading to applications in ultrahigh magnetic recording (UHMR) systems capable of achieving a performance of the order of terabits/in(2).