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.

Shape alterations in the striatum in chorea-acanthocytosis

Chorea-acanthocytosis (ChAc) is an uncommon autosomal recessive disorder due to mutations of the VPS13A gene, which encodes for the membrane protein chorein. ChAc presents with progressive limb and orobuccal chorea, but there is often a marked dysexecutive syndrome. ChAc may first present with neuropsychiatric disturbance such as obsessive-compulsive disorder (OCD), suggesting a particular role for disruption to striatal structures involved in non-motor frontostriatal loops, such as the head of the caudate nucleus. Two previous studies have suggested a marked reduction in volume in the caudate nucleus and putamen, but did not examine morphometric change. We investigated morphometric change in 13 patients with genetically or biochemically confirmed ChAc and 26 age- and gender-matched controls. Subjects underwent magnetic resonance imaging and manual segmentation of the caudate nucleus and putamen, and shape analysis using a non-parametric spherical harmonic technique. Both structures showed significant and marked reductions in volume compared with controls, with reduction greatest in the caudate nucleus. Both structures showed significant shape differences, particularly in the head of the caudate nucleus. No significant correlation was shown between duration of illness and striatal volume or shape, suggesting that much structural change may have already taken place at the time of symptom onset. Our results suggest that striatal neuron loss may occur early in the disease process, and follows a dorsal-ventral gradient that may correlate with early neuropsychiatric and cognitive presentations of the disease. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Fiedler trees for multiscale surface analysis

In this work we introduce a new hierarchical surface decomposition method for multiscale analysis of surface meshes. In contrast to other multiresolution methods, our approach relies on spectral properties of the surface to build a binary hierarchical decomposition. Namely, we utilize the first nontrivial eigenfunction of the Laplace-Beltrami operator to recursively decompose the surface. For this reason we coin our surface decomposition the Fiedler tree. Using the Fiedler tree ensures a number of attractive properties, including: mesh-independent decomposition, well-formed and nearly equi-areal surface patches, and noise robustness. We show how the evenly distributed patches can be exploited for generating multiresolution high quality uniform meshes. Additionally, our decomposition permits a natural means for carrying out wavelet methods, resulting in an intuitive method for producing feature-sensitive meshes at multiple scales. Published by Elsevier Ltd.

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.

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.

Parton energy loss in heavy-ion collisions via direct-photon and charged-particle azimuthal correlations

Charged-particle spectra associated with direct photon (gamma(dir)) and pi(0) are measured in p + p and Au + Au collisions at center-of-mass energy root(S)(NN) = 200 GeV with the STAR detector at the Relativistic Heavy Ion Collider. A shower-shape analysis is used to partially discriminate between gamma(dir) and pi(0). Assuming no associated charged particles in the gamma(dir) direction ( near side) and small contribution from fragmentation photons (gamma(frag)), the associated charged-particle yields opposite to gamma(dir) (away side) are extracted. In central Au + Au collisions, the charged-particle yields at midrapidity (vertical bar eta vertical bar < 1) and high transverse momentum (3 < (assoc)(PT) < 16 GeV/c) associated with gamma(dir) and pi(0) (vertical bar eta vertical bar < 0.9, 8 < (trig)(PT) < 16 GeV/c) are suppressed by a factor of 3-5 compared with p + p collisions. The observed suppression of the associated charged particles is similar for gamma(dir) and pi(0) and independent of the gamma(dir) energy within uncertainties. These measurements indicate that, in the kinematic range covered and within our current experimental uncertainties, the parton energy loss shows no sensitivity to the parton initial energy, path length, or color charge.

Mechanosensitivity of astrocytes on optimized polyacrylamide gels analyzed by quantitative morphometry

Cells are able to detect and respond to mechanical cues from their environment. Previous studies have investigated this mechanosensitivity on various cell types, including neural cells such as astrocytes. In this study, we have carefully optimized polyacrylamide gels, commonly used as compliant growth substrates, considering their homogeneity in surface topography, mechanical properties, and coating density, and identified several potential pitfalls for the purpose of mechanosensitivity studies. The resulting astrocyte response to growth on substrates with shear storage moduli of G` = 100 Pa and G` = 10 kPa was then evaluated as a function of coating density of poly-D-lysine using quantitative morphometric analysis. Astrocytes cultured on stiff substrates showed significantly increased perimeter, area, diameter, elongation, number of extremities and overall complexity if compared to those cultured on compliant substrates. A statistically significant difference in the overall morphological score was confirmed with an artificial intelligence-based shape analysis. The dependence of the cells` morphology on PDL coating density seemed to be weak compared to the effect of the substrate stiffness and was slightly biphasic, with a maximum at 10-100 mu g ml(-1) PDL concentration. Our finding suggests that the compliance of the surrounding tissue in vivo may influence astrocyte morphology and behavior.

Automatic contour extraction from 2D neuron images

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.

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.

Elongated shape isomers in the (36)Ar nucleus

A recent analysis of the (12)C + (24)Mg scattering [W. Sciani et al., Phys. Rev. C 80, 034319 (2009)] suggests the existence of a hyperdeformed band in the (36)Ar nucleus, completely in line with the predictions of alpha [W. D. M. Rae and A. C. Merchant, Phys. Lett. B279, 207 (1992)] and binary cluster calculations [J. Cseh et al., Phys. Rev. C 70, 034311 (2004)]. Here we review the structural understanding of the superdeformed and the hyperdeformed states of (36)Ar and present new results on the shape isomers as well. Special attention is paid to the clusterization of these states, which indicates the appropriate reaction channels for their formation.

Comparative analysis of triple band S-C-L erbium-doped fibre and semiconductor optical amplifier for CWDM applications

The authors present a comparative analysis between a triple-band S-C-L erbium-doped fibre amplifier and a commercial semiconductor optical amplifier in a CWDM application scenario. Both technologies were characterised for gain and noise figures from 1480 to 1610 nm (S, C and L bands) and their systemic performances were evaluated in terms of bit error rate measurements for a wide range of optical power levels.

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.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Evaluation of capillaries with different inner coatings for DNA analysis using dilute polymer solutions by capillary electrophoresis

In this work three capillary columns, one with uncoated inner wall and two with covalently-bound internal coatings - poly(vinyl alcohol) (PVA) and poly(dimethylacrylamide) (PDMA) - both covalently covered - were used to separate DNA fragments and compared to DNA separation using replaceable polymer solutions. The separations were performed using hydroxyethylcellulose (HEC) (90-105 kDa) in concentrations ranging from 0.00 to 2.00% m/v. The results indicated that the separation efficiency was higher in the PVA capillary than in the PDMA in all evaluated concentrations of HEC. In addition, higher resolution was also observed in PVA-coated capillary since in PDMA the shape of the peaks was not reproducible when subsequent runs were performed. Contrary to what has previously been reported in the literature, no reasonable separation was possible in bare fused silica.

Cytogenetic analysis of Astylus antis (Perty, 1830) (Coleoptera, Melyridae): Karyotype, heterochromatin and location of ribosomal genes

Cytogenetic analysis of Astylus antis using mitotic and meiotic cells was performed to characterize the haploid and diploid numbers, sex determination system, chromosome morphology, constitutive heterochromatin distribution pattern and chromosomes carrying nucleolus organizer regions (NORs). Analysis of spermatogonial metaphase cells revealed the diploid number 2n = 18, with mostly metacentric chromosomes. Metaphase I cells exhibited 2n = 8II+Xyp and a parachute configuration of the sex chromosomes. Spermatogonial metaphase cells submitted to C-banding showed the presence of small dots of constitutive heterochromatin in the centromeric regions of nearly all the autosomes and on the short arm of the X chromosome (Xp), as well as an additional band on one of the arms of pair 1. Mitotic cells submitted to double staining with base-specific fluorochromes (DAPI-CMA3) revealed no regions rich in A+T or G+C sequences. Analysis of spermatogonial mitotic cells after sequential Giemsa/AgNO3 staining did not reveal any specific mark on the chromosomes. Meiotic metaphase I cells stained with silver nitrate revealed a strong impregnation associated to the sex chromosomes, and in situ hybridization with an 18S rDNA probe showed ribosomal cistrons in an autosomal bivalent.