949 resultados para LMS Structure, Ternary Filtering, Algorithm


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The data of nitrogen adsorption on pillared clays (PILC) are converted to comparison plots (t-plots) to derive their pore size distribution (PSD). As in the MP method, the surface area of a group of pores having similar pore sizes is calculated from the slopes of tangent lines at two succeeding points on a comparison plot. By the modified MP method in this work, the tangent line is extrapolated to the adsorption axis on the t-plot, and the difference between intercepts is used to obtain the volume of the group of pores. From the information of surface area and pore volume, the average width of the pore group can be calculated and hence the PSDs of PILCs are obtained by carrying out such calculation procedures from high to low t. With this method, PSDs of several pillared clays are calculated over a wide pore size range, from micropores to mesopores. It is found that the modified MP method could result in the underestimation of the width of ultramicropores due to the enhancement in adsorption energy in these pores. Nevertheless, the method can be very useful in calculating the surface area and pore volume, as well as a mean width of these pores. For super-micropores and mesopores, pore size can also be underestimated, due to deviation of the pore shape from a slit. The principles of the improved MP method, as well as problems associated with it are thoroughly discussed in this paper. In general, this modified method provides practically meaningful results which are consistent with the pore dimension obtained from powder X-ray diffraction measurements, but involves no complicated theoretical treatment or assumptions.

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Streptococcus pyogenes infections remain a health problem in several countries due to poststreptococcal sequelae. We developed a vaccine epitope (StreptInCor) composed of 55 amino acids residues of the C-terminal portion of the M protein that encompasses both T and B cell protective epitopes. The nuclear magnetic resonance (NMR) structure of the StreptInCor peptide showed that the structure was composed of two microdomains linked by an 18-residue alpha-helix. A chemical stability study of the StreptInCor folding/unfolding process using far-UV circular dichroism showed that the structure was chemically stable with respect to pH and the concentration of urea. The T cell epitope is located in the first microdomain and encompasses 11 out of the 18 alpha-helix residues, whereas the B cell epitope is in the second microdomain and showed no alpha-helical structure. The prediction of StreptInCor epitope binding to different HLA class II molecules was evaluated based on an analysis of the 55 residues and the theoretical possibilities for the processed peptides to fit into the P1, P4, P6, and P9 pockets in the groove of several HLA class II molecules. We observed 7 potential sites along the amino acid sequence of StreptInCor that were capable of recognizing HLA class II molecules (DRB1*, DRB3*, DRB4*, and DRB5*). StreptInCoroverlapping peptides induced cellular and humoral immune responses of individuals bearing different HLA class II molecules and could be considered as a universal vaccine epitope.

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The efficient and correct folding of bacterial disulfide bonded proteins in vivo is dependent upon a class of periplasmic oxidoreductase proteins called DsbA, after the Escherichia coli enzyme. In the pathogenic bacterium Vibrio cholerae, the DsbA homolog (TcpG) is responsible for the folding, maturation and secretion of virulence factors. Mutants in which the tcpg gene has been inactivated are avirulent; they no longer produce functional colonisation pill and they no longer secrete cholera toxin. TcpG is thus a suitable target for inhibitors that could counteract the virulence of this organism, thereby preventing the symptoms of cholera. The crystal structure of oxidized TcpG (refined at a resolution of 2.1 Angstrom) serves as a starting point for the rational design of such inhibitors. As expected, TcpG has the same fold as E. coli DsbA, with which it shares similar to 40% sequence identity. Ln addition, the characteristic surface features of DsbA are present in TcpG, supporting the notion that these features play a functional role. While the overall architecture of TcpG and DsbA is similar and the surface features are retained in TcpG, there are significant differences. For example, the kinked active site helix results from a three-residue loop in DsbA, but is caused by a proline in TcpG (making TcpG more similar to thioredoxin in this respect). Furthermore, the proposed peptide binding groove of TcpG is substantially shortened compared with that of DsbA due to a six-residue deletion. Also, the hydrophobic pocket of TcpG is more shallow and the acidic patch is much less extensive than that of E. coli DsbA. The identification of the structural and surface features that are retained or are divergent in TcpG provides a useful assessment of their functional importance in these protein folding catalysts and is an important prerequisite for the design of TcpG inhibitors. (C) 1997 Academic Press Limited.

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Genetic population structure in the catadromous Australian bass Macquaria novemaculeata was investigated using samples from four locations spanning 600 km along the eastern Australian coastline. Both allozymes and mtDNA control region sequences were examined. Population subdivision estimates based on allozymes revealed low levels of population structuring (G(st)=0.043, P<0.05). However, mtDNA indicated moderate levels of geographic population structure (G(st)=0.146, P<0.01). Phylogenetic analysis of mtDNA control region sequences (mean sequence divergence 1.9%) indicated little phylogeographic structuring. Results suggested that genotypic variation within each river population, while bring affected primarily by genetic drift, was also prevented from more significant divergence by homogenizing levels of gene flow-synonymous with a one-dimensional stepping-stone model of population structure. The catadromous life history of Macquaria novemaculeata was considered to br influential on the pattern of population structure displayed. Results were compared to the few population genetic studies involving catadromous fishes, indicating that catadromy alone is unlikely to be a good predictor of population structure. A more comprehensive suite of biological characteristics than simple life-history traits must be considered fully to allow reliable predictive models of population structure to be formulated. (C) 1997 The Fisheries Society of the British Isles.

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Background: The venoms of Conus snails contain small, disulfide-rich inhibitors of voltage-dependent sodium channels. Conotoxin GS is a 34-residue polypeptide isolated from Conus geographus that interacts with the extracellular entrance of skeletal muscle sodium channels to prevent sodium ion conduction. Although conotoxin GS binds competitively with mu conotoxin GIIIA to the sodium channel surface, the two toxin types have little sequence identity with one another, and conotoxin GS has a four-loop structural framework rather than the characteristic three-loop mu-conotoxin framework. The structural study of conotoxin GS will form the basis for establishing a structure-activity relationship and understanding its interaction with the pore region of sodium channels. Results: The three-dimensional structure of conotoxin GS was determined using two-dimensional NMR spectroscopy. The protein exhibits a compact fold incorporating a beta hairpin and several turns. An unusual feature of conotoxin GS is the exceptionally high proportion (100%) of cis-imide bond geometry for the three proline or hydroxyproline residues. The structure of conotoxin GS bears little resemblance to the three-loop mu conotoxins, consistent with the low sequence identity between the two toxin types and their different structural framework. However, the tertiary structure and cystine-knot motif formed by the three disulfide bonds is similar to that present in several other polypeptide ion channel inhibitors. Conclusions: This is the first three-dimensional structure of a 'four-loop' sodium channel inhibitor, and it represents a valuable new structural probe for the pore region of voltage-dependent sodium channels. The distribution of amino acid sidechains in the structure creates several polar and charged patches, and comparison with the mu conotoxins provides a basis for determining the binding surface of the conotoxin GS polypeptide.

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A family of potent insecticidal toxins has recently been isolated from the venom of Australian funnel web spiders. Among these is the 37-residue peptide omega-atracotoxin-HV1 (omega-ACTX-HV1) from Hadronyche versuta. We have chemically synthesized and folded omega-ACTX-HV1, shown that it is neurotoxic, ascertained its disulphide bonding pattern, and determined its three-dimensional solution structure using NMR spectroscopy. The structure consists of a solvent-accessible beta-hairpin protruding from a disulphide-bonded globular core comprising four beta-turns. The three intramolecular disulphide bonds form a cystine knot motif similar to that seen in several other neurotoxic peptides. Despite limited sequence identity, omega-ACTX-HV1 displays significant structural homology with the omega-agatoxins and omega-conotoxins, both of which are vertebrate calcium channel antagonists; however, in contrast with these toxins, we show that omega-ACTX-HV1 inhibits insect, but not mammalian, voltage-gated calcium channel currents.

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The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

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Here, we examine morphological changes in cortical thickness of patients with Alzheimer`s disease (AD) using image analysis algorithms for brain structure segmentation and study automatic classification of AD patients using cortical and volumetric data. Cortical thickness of AD patients (n = 14) was measured using MRI cortical surface-based analysis and compared with healthy subjects (n = 20). Data was analyzed using an automated algorithm for tissue segmentation and classification. A Support Vector Machine (SVM) was applied over the volumetric measurements of subcortical and cortical structures to separate AD patients from controls. The group analysis showed cortical thickness reduction in the superior temporal lobe, parahippocampal gyrus, and enthorhinal cortex in both hemispheres. We also found cortical thinning in the isthmus of cingulate gyrus and middle temporal gyrus at the right hemisphere, as well as a reduction of the cortical mantle in areas previously shown to be associated with AD. We also confirmed that automatic classification algorithms (SVM) could be helpful to distinguish AD patients from healthy controls. Moreover, the same areas implicated in the pathogenesis of AD were the main parameters driving the classification algorithm. While the patient sample used in this study was relatively small, we expect that using a database of regional volumes derived from MRI scans of a large number of subjects will increase the SVM power of AD patient identification.

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An algorithm for explicit integration of structural dynamics problems with multiple time steps is proposed that averages accelerations to obtain subcycle states at a nodal interface between regions integrated with different time steps. With integer time step ratios, the resulting subcycle updates at the interface sum to give the same effect as a central difference update over a major cycle. The algorithm is shown to have good accuracy, and stability properties in linear elastic analysis similar to those of constant velocity subcycling algorithms. The implementation of a generalised form of the algorithm with non-integer time step ratios is presented. (C) 1997 by John Wiley & Sons, Ltd.

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Phytophthora cinnamomi isolates collected from 1977 to 1986 and 1991 to 1993 in two regions in South Africa were analyzed using isozymes. A total of 135 isolates was analyzed for 14 enzymes representing 20 putative loci, of which four were polymorphic. This led to the identification of nine different multilocus isozyme genotypes. Both mating types of P. cinnamomi occurred commonly in the Cape region, whereas, predominantly, the A2 mating type occurred in the Mpumalanga region of South Africa. A2 mating type isolates could be resolved into seven multilocus isozyme genotypes, compared with only two multilocus isozyme genotypes for the A1 mating type isolates. Low levels of gene (0.115) and genotypic (2.4%) diversity and a low number of alleles per locus (1.43) were observed for the South African P. cinnamomi population. The genetic distance between the Cape and Mpumalanga P. cinnamomi populations was relatively low (D-m = 0.165), and no specific pattern in regional distribution of multilocus isozyme genotypes could be observed. The genetic distance between the ''old'' (isolated between 1977 and 1986) and ''new'' (isolated between 1991 and 1993) P. cinnamomi populations from the Cape was low (D-m = 0.164), indicating a stable population over time. Three of the nine multilocus isozyme genotypes were specific to the ''old'' population, and only one multilocus isozyme genotype was specific to the ''new'' population. Significant differences in allele frequencies, a high genetic distance (D-m = 0.581) between the Cape A1 and A2 mating type isolates, significant deviations from Hardy-Weinberg equilibrium, a low overall level of heterozygosity, and a high fixation index (0.71) all indicate that sexual reproduction occurs rarely, if at all, in the South African P. cinnamomi population.

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Smoothing the potential energy surface for structure optimization is a general and commonly applied strategy. We propose a combination of soft-core potential energy functions and a variation of the diffusion equation method to smooth potential energy surfaces, which is applicable to complex systems such as protein structures; The performance of the method was demonstrated by comparison with simulated annealing using the refinement of the undecapeptide Cyclosporin A as a test case. Simulations were repeated many times using different initial conditions and structures since the methods are heuristic and results are only meaningful in a statistical sense.

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A cyclitol galactoside was isolated from the seeds of Vigna angularis and shown to be identical with galactosylononitol. However, detailed 2D NMR data and methylation analysis resulted in the revision of the structure of galactosylononitol to O-alpha-D-galactopyranosyl-(1-->3)-4-O-methyl-D-myo-inositol (1). Thus, compound 1 represents the only naturally occuring methylated derivative of galactinol.

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A new conceptual model for soil pore-solid structure is formalized. Soil pore-solid structure is proposed to comprise spatially abutting elements each with a value which is its membership to the fuzzy set ''pore,'' termed porosity. These values have a range between zero (all solid) and unity (all pore). Images are used to represent structures in which the elements are pixels and the value of each is a porosity. Two-dimensional random fields are generated by allocating each pixel a porosity by independently sampling a statistical distribution. These random fields are reorganized into other pore-solid structural types by selecting parent points which have a specified local region of influence. Pixels of larger or smaller porosity are aggregated about the parent points and within the region of interest by controlled swapping of pixels in the image. This creates local regions of homogeneity within the random field. This is similar to the process known as simulated annealing. The resulting structures are characterized using one-and two-dimensional variograms and functions describing their connectivity. A variety of examples of structures created by the model is presented and compared. Extension to three dimensions presents no theoretical difficulties and is currently under development.

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The popular Newmark algorithm, used for implicit direct integration of structural dynamics, is extended by means of a nodal partition to permit use of different timesteps in different regions of a structural model. The algorithm developed has as a special case an explicit-explicit subcycling algorithm previously reported by Belytschko, Yen and Mullen. That algorithm has been shown, in the absence of damping or other energy dissipation, to exhibit instability over narrow timestep ranges that become narrower as the number of degrees of freedom increases, making them unlikely to be encountered in practice. The present algorithm avoids such instabilities in the case of a one to two timestep ratio (two subcycles), achieving unconditional stability in an exponential sense for a linear problem. However, with three or more subcycles, the trapezoidal rule exhibits stability that becomes conditional, falling towards that of the central difference method as the number of subcycles increases. Instabilities over narrow timestep ranges, that become narrower as the model size increases, also appear with three or more subcycles. However by moving the partition between timesteps one row of elements into the region suitable for integration with the larger timestep these the unstable timestep ranges become extremely narrow, even in simple systems with a few degrees of freedom. As well, accuracy is improved. Use of a version of the Newmark algorithm that dissipates high frequencies minimises or eliminates these narrow bands of instability. Viscous damping is also shown to remove these instabilities, at the expense of having more effect on the low frequency response.

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We propose a simulated-annealing-based genetic algorithm for solving model parameter estimation problems. The algorithm incorporates advantages of both genetic algorithms and simulated annealing. Tests on computer-generated synthetic data that closely resemble optical constants of a metal were performed to compare the efficiency of plain genetic algorithms against the simulated-annealing-based genetic algorithms. These tests assess the ability of the algorithms to and the global minimum and the accuracy of values obtained for model parameters. Finally, the algorithm with the best performance is used to fit the model dielectric function to data for platinum and aluminum. (C) 1997 Optical Society of America.