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,

First order reversal curve analysis of nanocrystalline Pd(80)Co(20) alloy films

Films of isotropic nanocrystalline Pd(80)Co(20) alloys were obtained by electrodeposition onto brass substrate in plating baths maintained at different pH values. Increasing the pH of the plating bath led to an increase in mean grain size without inducing significant changes in the composition of the alloy. The magnetocrystalline anisotropy constant was estimated and the value was of the same order of magnitude as that reported for samples with perpendicular magnetic anisotropy. First order reversal curve (FORC) analysis revealed the presence of an important component of reversible magnetization. Also, FORC diagrams obtained at different sweep rate of the applied magnetic field, revealed that this reversible component is strongly affected by kinetic effect. The slight bias observed in the irreversible part of the FORC distribution suggested the dominance of magnetizing intergrain exchange coupling over demagnetizing dipolar interactions and microstructural disorder. (c) 2009 Elsevier B.V. All rights reserved.

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.

Measurement of shrinkage of composite resin by laser speckle contrast analysis

The aim of this study was to evaluate the shrinkage of a microhybrid dental composite resin photo-activated by one LED with different power densities by means of speckle technique. The dental composite resin Filtek (TM) Z-250 (3M/ESPE) at color A(2) was used for the samples preparation. Uncured composite was packed in a metallic mold and irradiated during 20 s from 100 to 1000 mW cm(-2). For the photo-activation of the samples, it was used a LED prototype (Light Emission Diode) with wavelength centered at 470 nm and adjustable power density until 1 W cm(-2). The speckle patterns obtained from the bottom composite surfaces were monitored using a CCD camera without lens. The speckle field is recorded in a digital picture and stored by CCD camera as the carrier of information on the displacement of the tested surface. The calculated values were obtained for each pair of adjacent patterns and the changes in speckle contrast as a function of time were obtained from six repeated measurements. The speckle contrasts obtained from the bottom surface with 100 mW cm(-1) were smaller than those than the other power densities. The higher power densities provided the higher shrinkage.

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.

Cellular and tissue effects induced by photogemA (R) and red LED in photodynamic therapy

In order to consider the photodynamic therapy (PDT) as a clinical treatment for candidosis, it is necessary to know its cytotoxic effect on normal cells and tissues. Therefore, this study evaluated the toxicity of PDT with PhotogemA (R) associated with red light-emitting diode (LED) on L929 and MDPC-23 cell cultures and healthy rat palatal mucosa. In the in vitro experiment, the cells (30000 cells/cm(2)) were seeded in 24-well plates for 48 h, incubated with PhotogemA (R) (50, 100, or 150 mg/l) and either irradiated or not with a red LED source (630 +/- 3 nm; 75 or 100 J/cm(2); 22 mW/cm(2)). Cell metabolism was evaluated by the MTT assay (ANOVA and Dunnet`s post hoc tests; p < 0.05) and cell morphology was examined by scanning electron microscopy. In the in vivo evaluation, PhotogemA (R) (500 mg/l) was applied to the palatal mucosa of Wistar rats during 30 min and exposed to red LED (630 nm) during 20 min (306 J/cm(2)). The palatal mucosa was photographed for macroscopic analysis at 0, 1, 3, and 7 days posttreatment and subjected to histological analysis after sacrifice of the rats. For both cell lines, there was a statistically significant decrease of the mitochondrial activity (90-97%) for all PhotogemA (R) concentrations associated with red LED regardless of the energy density. However, in the in vivo evaluation, the PDT-treated groups presented intact mucosa with normal characteristics both macroscopically and histologically. From these results, it may be concluded that the association of PhotogemA (R) and red LED caused severe toxic effects on normal cell cultures, characterized by the reduction of mitochondrial activity and morphological alterations, but did not cause damage to the rat palatal mucosa in vivo.

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.

Sequence and Structural Analysis of the 5 ` Noncoding Region of Hepatitis C Virus in Patients With Chronic Infection

Hepatitis C virus (HCV), exhibits considerable genetic diversity, but presents a relatively well conserved 5 ` noncoding region (5 ` NCR) among all genotypes. In this study, the structural features and translational efficiency of the HCV 5 ` NCR sequences were analyzed using the programs RNAfold, RNAshapes and RNApdist and with a bicistronic dual luciferase expression system, respectively. RNA structure prediction software indicated that base substitutions will alter potentially the 5 ` NCR structure. The heterogeneous sequence observed on 5 ` NCR led to important changes in their translation efficiency in different cell culture lines. Interactions of the viral RNA with cellular transacting factors may vary according to the cell type and viral genome polymorphisms that may result in the translational efficiency observed. J. Med. Virol. 81: 1212-1219, 2009. (C) 2009 Wiley-Liss, Inc.

Global Gene Expression Analysis during Sporulation of the Aquatic Fungus Blastocladiella emersonii

The Blastocladiella emersonii life cycle presents a number of drastic biochemical and morphological changes, mainly during two cell differentiation stages: germination and sporulation. To investigate the transcriptional changes taking place during the sporulation phase, which culminates with the production of the zoospores, motile cells responsible for the dispersal of the fungus, microarray experiments were performed. Among the 3,773 distinct genes investigated, a total of 1,207 were classified as differentially expressed, relative to time zero of sporulation, at at least one of the time points analyzed. These results indicate that accurate transcriptional control takes place during sporulation, as well as indicating the necessity for distinct molecular functions throughout this differentiation process. The main functional categories overrepresented among upregulated genes were those involving the microtubule, the cytoskeleton, signal transduction involving Ca(2+), and chromosome organization. On the other hand, protein biosynthesis, central carbon metabolism, and protein degradation were the most represented functional categories among downregulated genes. Gene expression changes were also analyzed in cells sporulating in the presence of subinhibitory concentrations of glucose or tryptophan. Data obtained revealed overexpression of microtubule and cytoskeleton transcripts in the presence of glucose, probably causing the shape and motility problems observed in the zoospores produced under this condition. In contrast, the presence of tryptophan during sporulation led to upregulation of genes involved in oxidative stress, proteolysis, and protein folding. These results indicate that distinct physiological pathways are involved in the inhibition of sporulation due to these two classes of nutrient sources.

New insights on surface-enhanced Raman scattering based on controlled aggregation and spectroscopic studies, DFT calculations and symmetry analysis for 3,6-bi-2-pyridyl-1,2,4,5-tetrazine adsorbed onto citrate-stabilized gold nanoparticles

Asystematic study on the surface-enhanced Raman scattering (SERS) for 3,6-bi-2-pyridyl-1,2,4,5-tetrazine (bptz) adsorbed onto citrate-modified gold nanoparticles (cit-AuNps) was carried out based on electronic and vibrational spectroscopy and density functional methods. The citrate/bptz exchange was carefully controlled by the stepwise addition of bptz to the cit-AuNps, inducing flocculation and leading to the rise of a characteristic plasmon coupling band in the visible region. Such stepwise procedure led to a uniform decrease of the citrate SERS signals and to the rise of characteristic peaks of bptz, consistent with surface binding via the N heterocyclic atoms. In contrast, single addition of a large amount of bptz promoted complete aggregation of the nanoparticles, leading to a strong enhancement of the SERS signals. In this case, from the distinct Raman profiles involved, the formation of a new SERS environment became apparent, conjugating the influence of the local hot spots and charge-transfer (CT) effects. The most strongly enhanced vibrations belong to a(1) and b(2) representations, and were interpreted in terms of the electromagnetic and the CT mechanisms: the latter involving significant contribution of vibronic coupling in the system. Copyright (C) 2010 John Wiley & Sons, Ltd.

Monodisperse lignin fractions as standards in size-exclusion analysis Comparison with polystyrene standards

The difficulty of preparing monodisperse lignin fractions on a large scale is a limiting factor in many applications. The present paper addresses this problem by examining the properties and size-exclusion behavior of lignin isolated by the acetosolv pulping process from post-extraction crushed sugarcane bagasse. The isolated lignin was subjected to a solvent pretreatment, followed by preparative gel permeation chromatography fractionation. The fractions were analyzed by high-performance size-exclusion chromatography (HPSEC) and these samples showed a great decrease in polydispersity, compared to the original acetosolv lignin. Several fractions of very low polydispersity, close to unity, were employed as calibration curve standards in HPSEC analysis. This original analytical approach allowed calibration with these lignin fractions to be compared with the polystyrene standards that are universally employed for lignin molecular mass determination. This led to a noteworthy result, namely that the lignin fractions and polystyrene standards showed very similar behavior over a large range of molecular masses in a typical HPSEC analysis of acetosolv lignin. (C) 2009 Elsevier B.V. All rights reserved.

Dereplication of Bromotyrosine-derived Metabolites by LC-PDA-MS and Analysis of the Chemical Profile of 14 Aplysina Sponge Specimens from the Brazilian Coastline

In order to investigate the chemical profile of 14 specimens of Aplysina spp. marine sponges, we have developed a method based on LC-PDA-MS for the detection of bromotyrosine-derived metabolites. The method enabled the dereplication of three distinct chemotypes of bromotyrosine-derived compounds based on UV absorptions, which were further refined by electrospray ionization-mass spectrometry analysis of the brominated quasi-molecular ion clusters. This procedure led to either a single compound assignment, or a maximum of two possible isobaric compounds. The dereplication study indicated that the chemical profile of the 14 specimens of Aplysina spp. analyzed presented practically the same dibromotyrosine-derived compounds. The results obtained suggested a possible biogenetic pathway for the formation of dibromotyrosine-derived compounds of wide occurrence in Verongida sponges.

Financial time series analysis : Chaos and neurodynamics approach

This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.