Template-based quadrilateral mesh generation from imaging data

This paper describes a novel template-based meshing approach for generating good quality quadrilateral meshes from 2D digital images. This approach builds upon an existing image-based mesh generation technique called Imeshp, which enables us to create a segmented triangle mesh from an image without the need for an image segmentation step. Our approach generates a quadrilateral mesh using an indirect scheme, which converts the segmented triangle mesh created by the initial steps of the Imesh technique into a quadrilateral one. The triangle-to-quadrilateral conversion makes use of template meshes of triangles. To ensure good element quality, the conversion step is followed by a smoothing step, which is based on a new optimization-based procedure. We show several examples of meshes generated by our approach, and present a thorough experimental evaluation of the quality of the meshes given as examples.

Generating segmented meshes from textured color images

This paper presents a new framework for generating triangular meshes from textured color images. The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images. An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV channels and Sequential Floating Forward Search guided by mean conditional entropy criterion to extract features from the training data. The W-operator is built into the local error estimation used by Imesh to choose the mesh vertices. Furthermore, the W-operator also enables to assign a label to the triangles during the mesh construction, thus allowing to obtain a segmented mesh at the end of the process. The presented results show that the combination of W-operators with Imesh gives rise to a texture classification-based triangle mesh generation framework that outperforms pixel based methods. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.

Generating Segmented Quality Meshes from Images

Techniques devoted to generating triangular meshes from intensity images either take as input a segmented image or generate a mesh without distinguishing individual structures contained in the image. These facts may cause difficulties in using such techniques in some applications, such as numerical simulations. In this work we reformulate a previously developed technique for mesh generation from intensity images called Imesh. This reformulation makes Imesh more versatile due to an unified framework that allows an easy change of refinement metric, rendering it effective for constructing meshes for applications with varied requirements, such as numerical simulation and image modeling. Furthermore, a deeper study about the point insertion problem and the development of geometrical criterion for segmentation is also reported in this paper. Meshes with theoretical guarantee of quality can also be obtained for each individual image structure as a post-processing step, a characteristic not usually found in other methods. The tests demonstrate the flexibility and the effectiveness of the approach.

The B0.5IVe CoRoT target HD 49330 I. Photometric analysis from CoRoT data

Context. Be stars undergo outbursts producing a circumstellar disk from the ejected material. The beating of non-radial pulsations has been put forward as a possible mechanism of ejection. Aims. We analyze the pulsational behavior of the early B0.5IVe star HD 49330 observed during the first CoRoT long run towards the Galactical anticenter (LRA1). This Be star is located close to the lower edge of the beta Cephei instability strip in the HR diagram and showed a 0.03 mag outburst during the CoRoT observations. It is thus an ideal case for testing the aforementioned hypothesis. Methods. We analyze the CoRoT light curve of HD 49330 using Fourier methods and non-linear least square fitting. Results. In this star, we find pulsation modes typical of beta Cep stars (p modes) and SPB stars (g modes) with amplitude variations along the run directly correlated with the outburst. These results provide new clues about the origin of the Be phenomenon as well as strong constraints on the seismic modelling of Be stars.

Direct evidence of singlet molecular oxygen generation from peroxynitrate, a decomposition product of peroxynitrite

The decomposition of peroxynitrite to nitrite and dioxygen at neutral pH follows complex kinetics, compared to its isomerization to nitrate at low pH. Decomposition may involve radicals or proceed by way of the classical peracid decomposition mechanism. Peroxynitrite (ONOOH/ONOO(-)) decomposition has been proposed to involve formation of peroxynitrate (O(2)NOOH/O(2)NOO(-)) at neutral pH (D. Gupta, B. Harish, R. Kissner and W. H. Koppenol, Dalton Trans., 2009, DOI: 10.1039/b905535e, see accompanying paper in this issue). Peroxynitrate is unstable and decomposes to nitrite and dioxygen. This study aimed to investigate whether O(2)NOO(-) formed upon ONOOH/ONOO(-) decomposition generates singlet molecular oxygen [O(2) ((1)Delta(g))]. As unequivocally revealed by the measurement of monomol light emission in the near infrared region at 1270 nm and by chemical trapping experiments, the decomposition of ONOO(-) or O(2)NOOH at neutral to alkaline pH generates O(2) ((1)Delta(g)) at a yield of ca. 1% and 2-10%, respectively. Characteristic light emission, corresponding to O(2) ((1)Delta(g)) monomolecular decay was observed for ONOO(-) and for O(2)NOOH prepared by reaction of H(2)O(2) with NO(2)BF(4) and of H(2)O(2) with NO(2)(-) in HClO(4). The generation of O(2) ((1)Delta(g)) from ONOO(-) increased in a concentration-dependent manner in the range of 0.1-2.5 mM and was dependent on pH, giving a sigmoid pro. le with an apparent pK(a) around pD 8.1 (pH 7.7). Taken together, our results clearly identify the generation of O(2) ((1)Delta(g)) from peroxynitrate [O(2)NOO(-) -> NO(2)(-) + O(2) ((1)Delta(g))] generated from peroxynitrite and also from the reactions of H(2)O(2) with either NO(2)BF(4) or NO(2)(-) in acidic media.

Corneal myofibroblast generation from bone marrow-derived cells

The purpose of this study was to determine whether bone marrow-derived cells can differentiate into myofibroblasts, as defined by alpha-smooth muscle actin (SMA) expression, that arise in the corneal stroma after irregular phototherapeutic keratectomy and whose presence within the cornea is associated with corneal stromal haze. C578L/6J-GFP chimeric mice were generated through bone marrow transplantation from donor mice that expressed enhanced green fluorescent protein (GFP) in a high proportion of their bone marrow-derived cells. Twenty-four GFP chimeric mice underwent haze-generating corneal epithelial scrape followed by irregular phototherapeutic keratectomy (PTK) with an excimer laser in one eye. Mice were euthanized at 2 weeks or 4 weeks after PTK and the treated and control contralateral eyes were removed and cryo-preserved for sectioning for immunocytochemistry. Double immunocytochemistry for GFP and myofibroblast marker alpha-smooth muscle actin (SMA) were performed and the number of SMA+GFP+, SMA+GFP, SMA-GFP+ and SMA GFP cells, as well as the number of DAPI+ cell nuclei, per 400x field of stroma was determined in the central, mid-peripheral and peri-limbal cornea. In this mouse model, there were no SMA+ cells and only a few GFP+ cells detected in unwounded control corneas. No SMA+ cells were detected in the stroma at two weeks after irregular PTK, even though there were numerous GFP+ cells present. At 4 weeks after irregular PTK, all corneas developed mild to moderately severe corneal haze. In each of the three regions of the corneas examined, there were on average more than 9x more SMA+GFP+ than SMA+GFP myofibroblasts. This difference was significant (p < 0.01). There were significantly more (p < 0.01) SMA GFP+ cells, which likely include inflammatory cells, than SMA+GFP+ or SMA+GFP cells, although SMA GFP cells represent the largest population of cells in the corneas. In this mouse model, the majority of myofibroblasts developed from bone marrow-derived cells. It is possible that all myofibroblasts in these animals developed from bone marrow-derived cells since mouse chimeras produced using this method had only 60-95% of bone marrow-derived cells that were GFP+ and it is not possible to achieve 100% chimerization. This model, therefore, cannot exclude the possibility of myofibroblasts also developed from keratocytes and/or corneal fibroblasts. (C) 2010 Elsevier Ltd. All rights reserved.

Genetic Algorithm for the Determination of Linear Viscoelastic Relaxation Spectrum from Experimental Data

Conventional procedures employed in the modeling of viscoelastic properties of polymer rely on the determination of the polymer`s discrete relaxation spectrum from experimentally obtained data. In the past decades, several analytical regression techniques have been proposed to determine an explicit equation which describes the measured spectra. With a diverse approach, the procedure herein introduced constitutes a simulation-based computational optimization technique based on non-deterministic search method arisen from the field of evolutionary computation. Instead of comparing numerical results, this purpose of this paper is to highlight some Subtle differences between both strategies and focus on what properties of the exploited technique emerge as new possibilities for the field, In oder to illustrate this, essayed cases show how the employed technique can outperform conventional approaches in terms of fitting quality. Moreover, in some instances, it produces equivalent results With much fewer fitting parameters, which is convenient for computational simulation applications. I-lie problem formulation and the rationale of the highlighted method are herein discussed and constitute the main intended contribution. (C) 2009 Wiley Periodicals, Inc. J Appl Polym Sci 113: 122-135, 2009

Can mass dissociation patterns of transition-metal complexes be predicted from electrochemical data?

The Cooks kinetic method has been very convenient to correlate the relative dissociation rates obtained by collision-induced fragmentation experiments with the energies of two related bonds in molecules and complexes in the gas phase. Reliable bond energy data are, however, not always available, particularly for polynuclear transition-metal complexes, such as the triruthenium acetate clusters of the general formula [Ru(3) (mu(3)-O)(mu-CH(3)COO)(6)(py)(2)(L)](+), where L = ring substituted N-heterocyclic ligands. Accordingly, their gas-phase collision-induced tandem mass spectrometry (CID MS/MS) dissociation patterns have been analyzed pursuing a relationship with the more easily accessible redox potentials (E(1/2)) and Lever`s E(L) parameters. In fact, excellent linear correlations of In(1/2A(L)/A(py)), where A(py) and A(L) are the abundance of the fragments retaining the pyridine (py) and L ligand, respectively, with E(1/2) and E(L) were found. This result shows that those electrochemical parameters are correlated with bond energies and can be used in the analysis of the dissociation data. Such modified Cooks method can be used, for example, to determine the electronic effects of substituents on the metal-ligand bonds for a series of transition-metal complexes. Copyright (C) 2008 John Wiley & Sons, Ltd.

A 2-D Delaunay refinement algorithm using an initial prerefinement from the boundary mesh

An improvement to the quality bidimensional Delaunay mesh generation algorithm, which combines the mesh refinement algorithms strategy of Ruppert and Shewchuk is proposed in this research. The developed technique uses diametral lenses criterion, introduced by L. P. Chew, with the purpose of eliminating the extremely obtuse triangles in the boundary mesh. This method splits the boundary segment and obtains an initial prerefinement, and thus reducing the number of necessary iterations to generate a high quality sequential triangulation. Moreover, it decreases the intensity of the communication and synchronization between subdomains in parallel mesh refinement.

Paleointensity data from Early Cretaceous Ponta Grossa dikes (Brazil) using a multisample method

Definition of the long-term variation of the geomagnetic virtual dipole moment requires more reliable paleointensity results. Here, we applied a multisample protocol to the study of the 130.5 Ma Ponta Grossa basaltic dikes (southern Brazil) that carry a very stable dual-polarity magnetic component. The magnetic stability of the samples wits checked using thermomagnetic curves and by monitoring the magnetic Susceptibility evolution through the paleointensity experiments. Twelve sites containing the least alterable samples were chosen for the paleointensity measurements. Although these rocks failed stepwise double-heating experiments, they yielded coherent results in the multisample method for all sites but one. The coherent sites show low to moderate field intensities between 5.7 +/- 0.2 and 26.4 +/- 0.7 mu T (average 13.4 +/- 1.9 mu T). Virtual dipole moments for these sites range from 1.3 +/- 0.04 to 6.0 +/- 0.2 x 10(22) A m(2) (average 2.9 +/- 0.5 x 10(22) A m(2)). Our results agree with the tendency for low dipole moments during the Early Cretaceous, immediately prior to the Cretaceous Normal Superchron (CNS). The available paleointensity database shows a strong variability of the field between 80 and 160 Ma. There seems to be no firm evidence for a Mesozoic Dipole Low, but a long-term tendency does emerge from the data with the highest dipole moments Occurring at the middle of the CNS.

Application of chemometric methods in the evaluation of chemical and spectroscopic data on organic matter from Oxisols in sewage sludge applications

Chemometric methods can contribute to soil research by permitting the extraction of more information from the data. The aim of this work was to use Principal Component Analysis to evaluate data obtained through chemical and spectroscopic methods on the changes in the humification process of soil organic matter from two tropical soils after sewage sludge application. In this case, humic acids extracted from Typic Eutrorthox and Typic Haplorthox soils with and without sewage sludge application for 7 consecutive years were studied. The results obtained for all of the samples and methods showed two clusters: samples extracted from the two soil types. These expected results indicated the textural difference between the two soils was more significant than the differences between treatments (control and sewage sludge application) or between depths. In this case, an individual chemometric treatment was made for each type of soil. It was noted that the characterization of the humic acids extracted from soils with and without sewage sludge application after 7 consecutive years using several methods supplies important results about changes in the humification degree of soil organic matter, These important result obtained by Principal Component Analysis justify further research using these methods to characterize the changes in the humic acids extracted from sewage sludge-amended soils. (C) 2009 Elsevier B.V. All rights reserved.

Recovery of the star formation history of the LMC from the VISTA survey of the Magellanic system

The VISTA near infrared survey of the Magellanic System (VMC) will provide deep YJK(s) photometry reaching stars in the oldest turn-off point throughout the Magellanic Clouds (MCs). As part of the preparation for the survey, we aim to access the accuracy in the star formation history (SFH) that can be expected from VMC data, in particular for the Large Magellanic Cloud (LMC). To this aim, we first simulate VMC images containing not only the LMC stellar populations but also the foreground Milky Way (MW) stars and background galaxies. The simulations cover the whole range of density of LMC field stars. We then perform aperture photometry over these simulated images, access the expected levels of photometric errors and incompleteness, and apply the classical technique of SFH-recovery based on the reconstruction of colour-magnitude diagrams (CMD) via the minimisation of a chi-squared-like statistics. We verify that the foreground MW stars are accurately recovered by the minimisation algorithms, whereas the background galaxies can be largely eliminated from the CMD analysis due to their particular colours and morphologies. We then evaluate the expected errors in the recovered star formation rate as a function of stellar age, SFR(t), starting from models with a known age-metallicity relation (AMR). It turns out that, for a given sky area, the random errors for ages older than similar to 0.4 Gyr seem to be independent of the crowding. This can be explained by a counterbalancing effect between the loss of stars from a decrease in the completeness and the gain of stars from an increase in the stellar density. For a spatial resolution of similar to 0.1 deg(2), the random errors in SFR(t) will be below 20% for this wide range of ages. On the other hand, due to the lower stellar statistics for stars younger than similar to 0.4 Gyr, the outer LMC regions will require larger areas to achieve the same level of accuracy in the SFR( t). If we consider the AMR as unknown, the SFH-recovery algorithm is able to accurately recover the input AMR, at the price of an increase of random errors in the SFR(t) by a factor of about 2.5. Experiments of SFH-recovery performed for varying distance modulus and reddening indicate that these parameters can be determined with (relative) accuracies of Delta(m-M)(0) similar to 0.02 mag and Delta E(B-V) similar to 0.01 mag, for each individual field over the LMC. The propagation of these errors in the SFR(t) implies systematic errors below 30%. This level of accuracy in the SFR(t) can reveal significant imprints in the dynamical evolution of this unique and nearby stellar system, as well as possible signatures of the past interaction between the MCs and the MW.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Improvements on ICA mixture models for image pre-processing and segmentation

Today several different unsupervised classification algorithms are commonly used to cluster similar patterns in a data set based only on its statistical properties. Specially in image data applications, self-organizing methods for unsupervised classification have been successfully applied for clustering pixels or group of pixels in order to perform segmentation tasks. The first important contribution of this paper refers to the development of a self-organizing method for data classification, named Enhanced Independent Component Analysis Mixture Model (EICAMM), which was built by proposing some modifications in the Independent Component Analysis Mixture Model (ICAMM). Such improvements were proposed by considering some of the model limitations as well as by analyzing how it should be improved in order to become more efficient. Moreover, a pre-processing methodology was also proposed, which is based on combining the Sparse Code Shrinkage (SCS) for image denoising and the Sobel edge detector. In the experiments of this work, the EICAMM and other self-organizing models were applied for segmenting images in their original and pre-processed versions. A comparative analysis showed satisfactory and competitive image segmentation results obtained by the proposals presented herein. (C) 2008 Published by Elsevier B.V.

Changes in optical properties caused by UV-irradiation of aquatic humic substances from the amazon river basin: Seasonal variability evaluation

Aquatic humic substances (AHS) isolated from two characteristic seasons of the Negro river, winter and summer corresponding to floody and dry periods, were structurally characterized by (13)C nuclear magnetic ressonance. Subsequently, AHS aqueous solutions were irradiated with a polychromatic lamp (290-475 nm) and monitored by its total organic carbon (TOC) content, ultraviolet-visible (UV-vis) absorbance, fluorescence and Fourier transformed infrared spectroscopy (FTIR). As a result, a photobleaching upto 80% after irradiation of 48 h was observed. Conformational rearrangements and formation of low molecular complexity structures were formed during the irradiation, as deduced from the pH decrement and the fluorescence shifting to lower wavelengths. Additionally a significant mineralization with the formation Of CO(2), CO, and inorganic carbon compounds was registered, as assumed by TOC losses of up to 70%. The differences in photodegradation between samples expressed by photobleaching efficiency were enhanced in the summer sample and related to its elevated aromatic content. Aromatic structures are assumed to have high autosensitization capacity effects mediated by the free radical generation from quinone and phenolic moieties.