99 resultados para Stochastic sequences.


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Phylogenetic hypotheses for the largely South African genus Pelargonium L'Hér. (Geraniaceae) were derived based on DNA sequence data from nuclear, chloroplast and mitochondrial encoded regions. The datasets were unequally represented and comprised cpDNA trnL-F sequences for 152 taxa, nrDNA ITS sequences for 55 taxa, and mtDNA nad1 b/c exons for 51 taxa. Phylogenetic hypotheses derived from the separate three datasets were overall congruent. A single hypothesis synthesising the information in the three datasets was constructed following a total evidence approach and implementing dataset specific stepmatrices in order to correct for substitution biases. Pelargonium was found to consist of five main clades, some with contrasting evolutionary patterns with respect to biogeographic distributions, dispersal capacity, pollination biology and karyological diversification. The five main clades are structured in two (subgeneric) clades that correlate with chromosome size. One of these clades includes a "winter rainfall clade" containing more than 70% of all currently described Pelargonium species, and all restricted to the South African Cape winter rainfall region. Apart from (woody) shrubs and small herbaceous rosette subshrubs, this clade comprises a large "xerophytic" clade including geophytes, stem and leaf succulents, harbouring in total almost half of the genus. This clade is considered to be the result of in situ proliferation, possibly in response to late-Miocene and Pliocene aridification events. Nested within it is a radiation comprising c. 80 species from the geophytic Pelargonium section Hoarea, all characterised by the possession of (a series of) tunicate tubers.

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BACKGROUND: Chronic fatigue syndrome (CFS) is an increasing medical phenomenon of unknown aetiology leading to high levels of chronic morbidity. Of the many hypotheses that purport to explain this disease, immune system activation, as a central feature, has remained prominent but unsubstantiated. Supporting this, a number of important cytokines have previously been shown to be over-expressed in disease subjects. The diagnosis of CFS is highly problematic since no biological markers specific to this disease have been identified. The discovery of genes relating to this condition is an important goal in seeking to correctly categorize and understand this complex syndrome. OBJECTIVE: The aim of this study was to screen for changes in gene expression in the lymphocytes of CFS patients. METHODS: 'Differential Display' is a method for comparing mRNA populations for the induction or suppression of genes. In this technique, mRNA populations from control and test subjects can be 'displayed' by gel electrophoresis and screened for differing banding patterns. These differences are indicative of altered gene expression between samples, and the genes that correspond to these bands can be cloned and identified. Differential display has been used to compare expression levels between four control subjects and seven CFS patients. RESULTS: Twelve short expressed sequence tags have been identified that were over-expressed in lymphocytes from CFS patients. Two of these correspond to cathepsin C and MAIL1 - genes known to be upregulated in activated lymphocytes. The expression level of seven of the differentially displayed sequences have been verified by quantifying relative level of these transcripts using TAQman quantitative PCR. CONCLUSION: Taken as a whole, the identification of novel gene tags up-regulated in CFS patients adds weight to the idea that CFS is a disease characterized by subtle changes in the immune system.

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The self-assembly in aqueous solution of hybrid block copolymers consisting of amphiphilic β-strand peptide sequences flanked by one or two PEG chains was investigated by means of circular dichroism spectroscopy, small-angle X-ray scattering, and transmission electron microscopy. In comparison with the native peptide sequence, it was found that the peptide secondary structure was stabilized against pH variation in the di-and tri-block copolymers with PEG. Small-angle X-ray scattering indicated the presence of fibrillar structures, the dimensions of which are comparable to the estimated width of a β-strand (with terminal PEG chains in the case of the copolymers). Transmission electron microscopy on selectively stained and dried specimens shows directly the presence of fibrils. It is proposed that these fibrils result from the hierarchical self-assembly of peptide β-strands into helical tapes, which then stack into fibrils.

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A technique is presented for locating and tracking objects in cluttered environments. Agents are randomly distributed across the image, and subsequently grouped around targets. Each agent uses a weightless neural network and a histogram intersection technique to score its location. The system has been used to locate and track a head in 320x240 resolution video at up to 15fps.

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In this paper, an improved stochastic discrimination (SD) is introduced to reduce the error rate of the standard SD in the context of multi-class classification problem. The learning procedure of the improved SD consists of two stages. In the first stage, a standard SD, but with shorter learning period is carried out to identify an important space where all the misclassified samples are located. In the second stage, the standard SD is modified by (i) restricting sampling in the important space; and (ii) introducing a new discriminant function for samples in the important space. It is shown by mathematical derivation that the new discriminant function has the same mean, but smaller variance than that of standard SD for samples in the important space. It is also analyzed that the smaller the variance of the discriminant function, the lower the error rate of the classifier. Consequently, the proposed improved SD improves standard SD by its capability of achieving higher classification accuracy. Illustrative examples axe provided to demonstrate the effectiveness of the proposed improved SD.

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We present a stochastic approach for solving the quantum-kinetic equation introduced in Part I. A Monte Carlo method based on backward time evolution of the numerical trajectories is developed. The computational complexity and the stochastic error are investigated numerically. Variance reduction techniques are applied, which demonstrate a clear advantage with respect to the approaches based on symmetry transformation. Parallel implementation is realized on a GRID infrastructure.

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An analysis of Stochastic Diffusion Search (SDS), a novel and efficient optimisation and search algorithm, is presented, resulting in a derivation of the minimum acceptable match resulting in a stable convergence within a noisy search space. The applicability of SDS can therefore be assessed for a given problem.

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An information processing paradigm in the brain is proposed, instantiated in an artificial neural network using biologically motivated temporal encoding. The network will locate within the external world stimulus, the target memory, defined by a specific pattern of micro-features. The proposed network is robust and efficient. Akin in operation to the swarm intelligence paradigm, stochastic diffusion search, it will find the best-fit to the memory with linear time complexity. information multiplexing enables neurons to process knowledge as 'tokens' rather than 'types'. The network illustrates possible emergence of cognitive processing from low level interactions such as memory retrieval based on partial matching. (C) 2007 Elsevier B.V. All rights reserved.