73 resultados para Stationary sequences


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The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

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The aim of this paper is to determine the suitability of solely stationary measurements for exposure assessment and management applications. For this purpose, quantified inhaled particle surface area (IPSA) doses using both stationary and personal particle exposure monitors were evaluated and compared.

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We report here the genome sequences of two alphabaculoviruses of Helicoverpa spp. from Australia: AC53, used in the biopesticides ViVUS and ViVUS Max, and H25EA1, used in in vitro production studies.

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Molecular phylogenetic studies of homologous sequences of nucleotides often assume that the underlying evolutionary process was globally stationary, reversible, and homogeneous (SRH), and that a model of evolution with one or more site-specific and time-reversible rate matrices (e.g., the GTR rate matrix) is enough to accurately model the evolution of data over the whole tree. However, an increasing body of data suggests that evolution under these conditions is an exception, rather than the norm. To address this issue, several non-SRH models of molecular evolution have been proposed, but they either ignore heterogeneity in the substitution process across sites (HAS) or assume it can be modeled accurately using the distribution. As an alternative to these models of evolution, we introduce a family of mixture models that approximate HAS without the assumption of an underlying predefined statistical distribution. This family of mixture models is combined with non-SRH models of evolution that account for heterogeneity in the substitution process across lineages (HAL). We also present two algorithms for searching model space and identifying an optimal model of evolution that is less likely to over- or underparameterize the data. The performance of the two new algorithms was evaluated using alignments of nucleotides with 10 000 sites simulated under complex non-SRH conditions on a 25-tipped tree. The algorithms were found to be very successful, identifying the correct HAL model with a 75% success rate (the average success rate for assigning rate matrices to the tree's 48 edges was 99.25%) and, for the correct HAL model, identifying the correct HAS model with a 98% success rate. Finally, parameter estimates obtained under the correct HAL-HAS model were found to be accurate and precise. The merits of our new algorithms were illustrated with an analysis of 42 337 second codon sites extracted from a concatenation of 106 alignments of orthologous genes encoded by the nuclear genomes of Saccharomyces cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, S. castellii, S. kluyveri, S. bayanus, and Candida albicans. Our results show that second codon sites in the ancestral genome of these species contained 49.1% invariable sites, 39.6% variable sites belonging to one rate category (V1), and 11.3% variable sites belonging to a second rate category (V2). The ancestral nucleotide content was found to differ markedly across these three sets of sites, and the evolutionary processes operating at the variable sites were found to be non-SRH and best modeled by a combination of eight edge-specific rate matrices (four for V1 and four for V2). The number of substitutions per site at the variable sites also differed markedly, with sites belonging to V1 evolving slower than those belonging to V2 along the lineages separating the seven species of Saccharomyces. Finally, sites belonging to V1 appeared to have ceased evolving along the lineages separating S. cerevisiae, S. paradoxus, S. mikatae, S. kudriavzevii, and S. bayanus, implying that they might have become so selectively constrained that they could be considered invariable sites in these species.

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Debates on gene patents have necessitated the analysis of patents that disclose and reference human sequences. In this study, we built an automated classifier that assigns sequences to one of nine predefined categories according to their functional roles in patent claims by applying natural language processing and supervised learning techniques. To improve its correctness, we experimented with various feature mappings, resulting in the maximal accuracy of 79%.

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MicroRNAs (miRNAs) are small non-coding RNAs of 20 nt in length that are capable of modulating gene expression post-transcriptionally. Although miRNAs have been implicated in cancer, including breast cancer, the regulation of miRNA transcription and the role of defects in this process in cancer is not well understood. In this study we have mapped the promoters of 93 breast cancer-associated miRNAs, and then looked for associations between DNA methylation of 15 of these promoters and miRNA expression in breast cancer cells. The miRNA promoters with clearest association between DNA methylation and expression included a previously described and a novel promoter of the Hsa-mir-200b cluster. The novel promoter of the Hsa-mir-200b cluster, denoted P2, is located 2 kb upstream of the 5′ stemloop and maps within a CpG island. P2 has comparable promoter activity to the previously reported promoter (P1), and is able to drive the expression of miR-200b in its endogenous genomic context. DNA methylation of both P1 and P2 was inversely associated with miR-200b expression in eight out of nine breast cancer cell lines, and in vitro methylation of both promoters repressed their activity in reporter assays. In clinical samples, P1 and P2 were differentially methylated with methylation inversely associated with miR-200b expression. P1 was hypermethylated in metastatic lymph nodes compared with matched primary breast tumours whereas P2 hypermethylation was associated with loss of either oestrogen receptor or progesterone receptor. Hypomethylation of P2 was associated with gain of HER2 and androgen receptor expression. These data suggest an association between miR-200b regulation and breast cancer subtype and a potential use of DNA methylation of miRNA promoters as a component of a suite of breast cancer biomarkers.

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Chlamydia pneumoniae is a ubiquitous intracellular pathogen, first associated with human respiratory disease and subsequently detected in a range of mammals, amphibians, and reptiles. Here we report the draft genome sequence for strain B21 of C. pneumoniae, isolated from the endangered Australian marsupial the western barred bandicoot.

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Biological sequences are an important part of global patenting, with unique challenges for their effective and equitable use in practice and in policy. Because their function can only be determined with computer-aided technology, the form in which sequences are disclosed matters greatly. Similarly, the scope of patent rights sought and granted requires computer readable data and tools for comparison. Critically, the primary data provided to the national patent offices and thence to the public, must be comprehensive, standardized, timely and meaningful. It is not yet. The proposed global Patent Sequence (PatSeq) Data platform can enable national and regional jurisdictions meet the desired standards.

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In the century since the description of the orthoclad genus Paratrichocladius Santos-Abreu (Diptera: Chironomidae), separation in any life stage from the cosmopolitan, diverse Cricotopus Wulp has been problematic. Molecular analysis reveals the presence of two species in Australia that conform in morphology to Paratrichocladius and which form a well-supported clade including Paratrichocladius micans (Kieffer) from Africa and a distinct southern African larva. This clade clusters with taxa allied with Cricotopus albitibia (Walker), in turn nested within all other sampled Australian Cricotopus. Relevant nodes strongly support Cricotopus as nonmonophyletic without inclusion of Paratrichocladius. We synonymize Paratrichocladius with Cricotopus syn.n, treating Paratrichocladius as a subgenus. Cricotopus (Paratrichocladius) australiensis Cranston sp.n. is described for Trichocladius pluriserialis Freeman from Australia, which is not the same species under that name in New Zealand. Cricotopus (Paratrichocladius) bifenestrus Cranston sp.n. from Australia is described, also in all life stages. The many new combinations, listed in an Appendix, include three replacement names for new secondary homonyms, namely: Cricotopus (Paratrichocladius) sinobicinctus Cranston & Krosch nom.n. for Paratrichocladius bicinctus Fu, Sæther & Wang, Cricotopus draysoni Cranston & Krosch nom.n. for Cricotopus brevicornis Drayson, Krosch & Cranston, and Cricotopus (Paratrichocladius) sikhotealinus Makarchenko & Makarchenko nom.n. for Cricotopus orientalis Kieffer. We conclude with comments on wider issues in the taxonomy of Paratrichocladius, especially concerning New Zealand species.

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This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

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Stationary processes are random variables whose value is a signal and whose distribution is invariant to translation in the domain of the signal. They are intimately connected to convolution, and therefore to the Fourier transform, since the covariance matrix of a stationary process is a Toeplitz matrix, and Toeplitz matrices are the expression of convolution as a linear operator. This thesis utilises this connection in the study of i) efficient training algorithms for object detection and ii) trajectory-based non-rigid structure-from-motion.

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In this manuscript, we consider the impact of a small jump-type spatial heterogeneity on the existence of stationary localized patterns in a system of partial dierential equations in one spatial dimension...

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Wild-type baculovirus isolates typically consist of multiple strains. We report the full genome sequences of seven alphabaculovirus strains derived by passage through tissue culture from Helicoverpa armigera SNPV-AC53 (KJ909666).