Identification of protein coding regions using the modified Gabor-wavelet transform

An important topic in genomic sequence analysis is the identification of protein coding regions. In this context, several coding DNA model-independent methods based on the occurrence of specific patterns of nucleotides at coding regions have been proposed. Nonetheless, these methods have not been completely suitable due to their dependence on an empirically predefined window length required for a local analysis of a DNA region. We introduce a method based on a modified Gabor-wavelet transform (MGWT) for the identification of protein coding regions. This novel transform is tuned to analyze periodic signal components and presents the advantage of being independent of the window length. We compared the performance of the MGWT with other methods by using eukaryote data sets. The results show that MGWT outperforms all assessed model-independent methods with respect to identification accuracy. These results indicate that the source of at least part of the identification errors produced by the previous methods is the fixed working scale. The new method not only avoids this source of errors but also makes a tool available for detailed exploration of the nucleotide occurrence.

Pt-RuO(2) electrodes prepared by thermal decomposition of polymeric precursors as catalysts for direct methanol fuel cell applications

The electrocatalytic activity of Pt and RuO(2) mixed electrodes of different compositions towards methanol oxidation was investigated. The catalysts were prepared by thermal decomposition of polymeric precursors and characterized by energy dispersive X-ray, scanning electronic microscopy, X-ray diffraction and cyclic voltammetry. This preparation method allowed obtaining uniform films with controlled stoichiometry and high surface area. Cyclic voltammetry experiments in the presence of methanol showed that mixed electrodes decreased the potential peak of methanol oxidation by approximately 100 mV (RHE) when compared to the electrode containing only Pt. In addition, voltammetric experiments indicated that the Pt(0.6)Ru(0.4)O(y) electrode led to higher oxidation current densities at lower potentials. Chronoamperometry experiments confirmed the contribution of RuO(2) to the catalytic activity as well as the better performance of the Pt(0.6)Ru(0.4)O(y) electrode composition. Formic acid and CO(2) were identified as being the reaction products formed in the electrolysis performed at 400 and 600 mV. The relative formation of CO(2) was favored in the electrolysis performed at 400 mV (RHE) with the Pt(0.6)Ru(0.4)O(y) electrode. The presence of RuO(2) in Pt-Ru-based electrodes is important for improving the catalytic activity towards methanol electrooxidation. Moreover, the thermal decomposition of polymeric precursors seems to be a promising route for the production of catalysts applicable to DMFC. (C) 2009 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.

Characterization and voltammetric behavior of Pt(y)Mo(z)O(x)/C electrodes prepared by the thermal decomposition of polymeric precursors

Carbon-supported catalysts containing platinum and molybdenum oxide are prepared by thermal decomposition of polymeric precursors. The Pt(y)Mo(z)O(x)/C materials are characterized by energy dispersive X-ray spectroscopy, transmission electron microscopy, and X-ray diffraction. The catalysts present a well-controlled stoichiometry and nanometric particles. Molybdenum is present mainly as the MoO(3) orthorhombic structure, and no Pt alloys are detected. The voltammetric behavior of the electrodes is investigated; a correlation with literature results for PtMo/C catalysts prepared by other methods is established. The formation of soluble species and the aging effect are discussed. (C) 2009 Elsevier B.V. All rights reserved.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

EFFECTS OF A POTENT PEROXYNITRITE DECOMPOSITION CATALYST IN MURINE MODELS OF ENDOTOXEMIA AND SEPSIS

Excessive free-radical production due to various bacterial components released during bacterial infection has been linked to cell death and tissue injury. Peroxynitrite is a highly reactive oxidant produced by the combination of nitric oxide (NO) and superoxide anion, which has been implicated in cell death and tissue injury in various forms of critical illness. Pharmacological decomposition of peroxynitrite may represent a potential therapeutic approach in diseases associated with the overproduction of NO and superoxide. In the present study, we tested the effect of a potent peroxynitrite decomposition catalyst in murine models of endotoxemia and sepsis. Mice were injected i.p. with LPS 40 mg/kg with or without FP15 [Fe(III) tetrakis-2-(N-triethylene glycol monomethyl ether) pyridyl porphyrin] (0.1, 0.3, 1, 3, or 10 mg/kg per hour). Mice were killed 12 h later, followed by the harvesting of samples from the lung, liver, and gut for malondialdehyde and myeloperoxidase measurements. In other subsets of animals, blood samples were obtained by cardiac puncture at 1.5, 4, and 8 h after LPS administration for cytokine (TNF-alpha, IL-1 beta, and IL-10), nitrite/nitrate, alanine aminotransferase, and blood urea nitrogen measurements. Endotoxemic animals showed an increase in survival from 25% to 80% at the FP15 doses of 0.3 and 1 mg/kg per hour. The same dose of FP15 had no effect on plasma levels of nitrite/nitrate. There was a reduction in liver and lung malondialdehyde in the endotoxemic animals pretreated with FP15, as well as in hepatic myeloperoxidase and biochemical markers of liver and kidney damage (alanine aminotransferase and blood urea nitrogen). In a bacterial model of sepsis induced by cecal ligation and puncture, FP15 treatment (0.3 mg/kg per day) significantly protected against mortality. The current data support the view that peroxynitrite is a critical factor mediating liver, gut, and lung injury in endotoxemia and septic shock: its pharmacological neutralization may be of therapeutic benefit.

Decomposition in tropical forests: a pan-tropical study of the effects of litter type, litter placement and mesofaunal exclusion across a precipitation gradient

1. Litter decomposition recycles nutrients and causes large fluxes of carbon dioxide into the atmosphere. It is typically assumed that climate, litter quality and decomposer communities determine litter decay rates, yet few comparative studies have examined their relative contributions in tropical forests. 2. We used a short-term litterbag experiment to quantify the effects of litter quality, placement and mesofaunal exclusion on decomposition in 23 tropical forests in 14 countries. Annual precipitation varied among sites (760-5797 mm). At each site, two standard substrates (Raphia farinifera and Laurus nobilis) were decomposed in fine- and coarse-mesh litterbags both above and below ground for approximately 1 year. 3. Decomposition was rapid, with >95% mass loss within a year at most sites. Litter quality, placement and mesofaunal exclusion all independently affected decomposition, but the magnitude depended upon site. Both the average decomposition rate at each site and the ratio of above- to below-ground decay increased linearly with annual precipitation, explaining 60-65% of among-site variation. Excluding mesofauna had the largest impact on decomposition, reducing decomposition rates by half on average, but the magnitude of decrease was largely independent of climate. This suggests that the decomposer community might play an important role in explaining patterns of decomposition among sites. Which litter type decomposed fastest varied by site, but was not related to climate. 4. Synthesis. A key goal of ecology is to identify general patterns across ecological communities, as well as relevant site-specific details to understand local dynamics. Our pan-tropical study shows that certain aspects of decomposition, including average decomposition rates and the ratio of above- to below-ground decomposition are highly correlated with a simple climatic index: mean annual precipitation. However, we found no relationship between precipitation and effects of mesofaunal exclusion or litter type, suggesting that site-specific details may also be required to understand how these factors affect decomposition at local scales.

Relative effect of litter quality, forest type and their interaction on leaf decomposition in south-east Brazilian forests

Decomposition was studied in a reciprocal litter transplant experiment to examine the effects of forest type, litter quality and their interaction on leaf decomposition in four tropical forests in south-east Brazil. Litterbags were used to measure decomposition of leaves of one tree species from each forest type: Calophyllum brasiliense from restinga forest; Guapira opposita from Atlantic forest; Esenbeckia leiocarpa from semi-deciduous forest; and Copaifera langsdorffii from cerradao. Decomposition rates in rain forests (Atlantic and restinga) were twice as fast as those in seasonal forests (semi-deciduous and cerradao), suggesting that intensity and distribution of precipitation are important predictors of decomposition rates at regional scales. Decomposition rates varied by species, in the following order: E. leiocarpa > C. langsdorffii > G. opposita > C. brasiliense. However, there was no correlation between decomposition rates and chemical litter quality parameters: C:N, C:P, lignin concentration and lignin:N. The interaction between forest type and litter quality was positive mainly because C. langsdorffii decomposed faster than expected in its native forest. This is a potential indication of a decomposer`s adaptation to specific substrates in a tropical forest. These findings suggest that besides climate, interactions between decomposers and plants might play an essential role in decomposition processes and it must be better understood.

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,

HIERARCHICAL DECOMPOSITION OF MULTICLASS PROBLEMS

Several popular Machine Learning techniques are originally designed for the solution of two-class problems. However, several classification problems have more than two classes. One approach to deal with multiclass problems using binary classifiers is to decompose the multiclass problem into multiple binary sub-problems disposed in a binary tree. This approach requires a binary partition of the classes for each node of the tree, which defines the tree structure. This paper presents two algorithms to determine the tree structure taking into account information collected from the used dataset. This approach allows the tree structure to be determined automatically for any multiclass dataset.

Black-box decomposition approach for computational hemodynamics: One-dimensional models

Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. 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.

The role of citrate precursors on the morphology of lanthanide oxides obtained by thermal decomposition

Two series of lanthanide oxides with different morphologies were synthesized through calcinations of two types of citrate polymeric precursors. These oxides were characterized by XRD patterns, SEM electronic microscopy, and N(2) adsorption isotherms. SEM microscopy analysis showed that the calcination of crystalline fibrous precursors [Ln(2)(LH)(3)center dot 2H(2)O] (L = citrate) originated fibrous shaped particles. On the other hand, the calcination of irregular shaped particles of precursors [LnL center dot xH(2)O] originated irregular shaped particles of oxide, pointing out a morphological template effect of precursors on the formation of the respective oxides.

Many-body energy decomposition of hydrogen-bonded glycine clusters in gas-phase

A detailed analysis of the many-body contribution to the interaction energies of the gas-phase hydrogen-bonded glycine clusters, (Gly)(N), N = 1-4 is presented. The energetics of the hydrogen-bonded dimer, trimer and tetramer complexes have been analyzed using density-functional theory. The magnitude of the two-through four-body energy terms have been calculated and compared. The relaxation energy and the two-body energy terms are the principal contributors to the total binding energy. Four-body contribution is negligible. However, the three-body contribution is found to be sizable and the formation of the cyclic glycine trimer presents geometric strains that make it less favorable. (C) 2010 Elsevier B.V. All rights reserved.

Laurdan Spectrum Decomposition as a Tool for the Analysis of Surface Bilayer Structure and Polarity: a Study with DMPG, Peptides and Cholesterol

The highly hydrophobic fluorophore Laurdan (6-dodecanoyl-2-(dimethylaminonaphthalene)) has been widely used as a fluorescent probe to monitor lipid membranes. Actually, it monitors the structure and polarity of the bilayer surface, where its fluorescent moiety is supposed to reside. The present paper discusses the high sensitivity of Laurdan fluorescence through the decomposition of its emission spectrum into two Gaussian bands, which correspond to emissions from two different excited states, one more solvent relaxed than the other. It will be shown that the analysis of the area fraction of each band is more sensitive to bilayer structural changes than the largely used parameter called Generalized Polarization, possibly because the latter does not completely separate the fluorescence emission from the two different excited states of Laurdan. Moreover, it will be shown that this decomposition should be done with the spectrum as a function of energy, and not wavelength. Due to the presence of the two emission bands in Laurdan spectrum, fluorescence anisotropy should be measured around 480 nm, to be able to monitor the fluorescence emission from one excited state only, the solvent relaxed state. Laurdan will be used to monitor the complex structure of the anionic phospholipid DMPG (dimyristoyl phosphatidylglycerol) at different ionic strengths, and the alterations caused on gel and fluid membranes due to the interaction of cationic peptides and cholesterol. Analyzing both the emission spectrum decomposition and anisotropy it was possible to distinguish between effects on the packing and on the hydration of the lipid membrane surface. It could be clearly detected that a more potent analog of the melanotropic hormone alpha-MSH (Ac-Ser(1)-Tyr(2)-Ser(3)-Met(4)-Glu(5)-His(6)-Phe(7)-Arg(8)-Trp(9)-Gly(10)-Lys(11)-Pro(12)-Val(13)-NH(2)) was more effective in rigidifying the bilayer surface of fluid membranes than the hormone, though the hormone significantly decreases the bilayer surface hydration.

Decomposition of spectral density in individual eigenvalue contributions

The eigenvalue densities of two random matrix ensembles, the Wigner Gaussian matrices and the Wishart covariant matrices, are decomposed in the contributions of each individual eigenvalue distribution. It is shown that the fluctuations of all eigenvalues, for medium matrix sizes, are described with a good precision by nearly normal distributions.