964 resultados para flame kernel


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Resolving a noted open problem, we show that the Undirected Feedback Vertex Set problem, parameterized by the size of the solution set of vertices, is in the parameterized complexity class Poly(k), that is, polynomial-time pre-processing is sufficient to reduce an initial problem instance (G, k) to a decision-equivalent simplified instance (G', k') where k' � k, and the number of vertices of G' is bounded by a polynomial function of k. Our main result shows an O(k11) kernelization bound.

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Brominated flame retardants, including hexabromocyclododecane (HBCD) and polybrominated diphenyl ethers (PBDEs) are used to reduce the flammability of a multitude of electrical and electronic products, textiles and foams. The use of selected PBDEs has ceased, however, use of decaBDE and HBCD continues. While elevated concentrations of PBDEs in humans have been observed in Australia, no data is available on other BFRs such as HBCD. This study aimed to provide background HBCD concentrations from a representative sample of the Australian population and to assess temporal trends of HBCD and compare with PBDE concentrations over a 16 year period. Samples of human milk collected in Australia from 1993 to 2009, primarily from primiparae mothers were combined into 12 pools from 1993 (2 pools); 2001; 2002/2003 (4 pools); 2003/2004; 2006; 2007/2008 (2 pools); and 2009. Concentrations of ∑HBCD ranged from not quantified (nq) to 19 ng g−1 lipid while α-HBCD and γ-HBCD ranged from nq to 10 ng g−1 lipid and nq to 9.2 ng g−1 lipid. β-HBCD was detected in only one sample at 3.6 ng g−1 lipid while ∑4PBDE ranged from 2.5 to 15.8 ng g−1 lipid. No temporal trend was apparent in HBCD concentrations in human milk collected in Australia from 1993 to 2009. In comparison, PBDE concentrations in human milk show a peak around 2002/03 (mean ∑4PBDEs = 9.6 ng g−1 lipid) and 2003/04 (12.4 ng g−1 lipid) followed by a decrease in 2007/08 (2.7 ng g−1 lipid) and 2009 (2.6 ng g−1 lipid). In human blood serum samples collected from the Australian population, PBDE concentrations did not vary greatly (p = 0.441) from 2002/03 to 2008/09. Continued monitoring including both human milk and serum for HBCD and PBDEs is required to observe trends in human body burden of HBCD and PBDEs body burden following changes to usage.

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Modelling video sequences by subspaces has recently shown promise for recognising human actions. Subspaces are able to accommodate the effects of various image variations and can capture the dynamic properties of actions. Subspaces form a non-Euclidean and curved Riemannian manifold known as a Grassmann manifold. Inference on manifold spaces usually is achieved by embedding the manifolds in higher dimensional Euclidean spaces. In this paper, we instead propose to embed the Grassmann manifolds into reproducing kernel Hilbert spaces and then tackle the problem of discriminant analysis on such manifolds. To achieve efficient machinery, we propose graph-based local discriminant analysis that utilises within-class and between-class similarity graphs to characterise intra-class compactness and inter-class separability, respectively. Experiments on KTH, UCF Sports, and Ballet datasets show that the proposed approach obtains marked improvements in discrimination accuracy in comparison to several state-of-the-art methods, such as the kernel version of affine hull image-set distance, tensor canonical correlation analysis, spatial-temporal words and hierarchy of discriminative space-time neighbourhood features.

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This project was a step forward in developing intrusion detection systems in distributed environments such as web services. It investigates a new approach of detection based on so-called "taint-marking" techniques and introduces a theoretical framework along with its implementation in the Linux kernel.

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A critical requirement for safe autonomous navigation of a planetary rover is the ability to accurately estimate the traversability of the terrain. This work considers the problem of predicting the attitude and configuration angles of the platform from terrain representations that are often incomplete due to occlusions and sensor limitations. Using Gaussian Processes (GP) and exteroceptive data as training input, we can provide a continuous and complete representation of terrain traversability, with uncertainty in the output estimates. In this paper, we propose a novel method that focuses on exploiting the explicit correlation in vehicle attitude and configuration during operation by learning a kernel function from vehicle experience to perform GP regression. We provide an extensive experimental validation of the proposed method on a planetary rover. We show significant improvement in the accuracy of our estimation compared with results obtained using standard kernels (Squared Exponential and Neural Network), and compared to traversability estimation made over terrain models built using state-of-the-art GP techniques.

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Human polybrominated diphenyl ether (PBDE) exposure occurs through a range of pathways including: ingestion of dust including hand-to-mouth contact; inhalation (air/particulate matter); and ingestion via food including the unique nutrition sources of human milk and placental transfer. While inhalation has been deemed a minor source of exposure, ingestion of food and dust make greater contributions to overall PBDE body burden with intake via dust reported to be much higher in infants than in adults. PBDEs have been detected in samples of human milk, blood serum, cord blood, and adipose tissue worldwide. Concentrations have been found to be highest in populations from North America, followed by Australia, Europe, and Asia. While factors such as gender and parity may not affect concentrations, occupational exposure and age (infants and children) are associated with higher PBDE concentrations. In contrast to “traditional” persistent organic pollutants, there is an inverse relationship between PBDE body burden and age. Predicted body burden calculated using available information on intake and elimination rates of BFRs appears to underestimate measured human body burden data obtained through analysis of BFRs in blood or human milk. This may be due to unknown exposure or inaccurate elimination data. Further exposure studies should focus on younger age groups and an investigation of human PBDE half-lives.

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Background Brominated flame retardants (BFRs), are chemicals widely used in consumer products including electronics, vehicles, plastics and textiles to reduce flammability. Experimental animal studies have confirmed that these compounds may interfere with thyroid hormone homeostasis and neurodevelopment but to date health effects in humans have not been systematically examined. Objectives To conduct a systematic review of studies on the health impacts of exposure to BFRs in humans, with a particular focus on children. Methods A systematic review was conducted using the Medline and EMBASE electronic databases up to 1 February 2012. Published cohort, cross-sectional, and case-control studies exploring the relationship between BFR exposure and various health outcomes were included. Results In total, 36 epidemiological studies meeting the pre-determined inclusion criteria were included. Plausible outcomes associated with BFR exposure include diabetes, neurobehavioral and developmental disorders, cancer, reproductive health effects and alteration in thyroid function. Evidence for a causal relationship between exposure to BFRs and health outcomes was evaluated within the Bradford Hill framework. Conclusion Although there is suggestive evidence that exposure to BFRs is harmful to health, further epidemiological investigations particularly among children, and long-term monitoring and surveillance of chemical impacts on humans are required to confirm these relationships.

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This paper proposes a highly reliable fault diagnosis approach for low-speed bearings. The proposed approach first extracts wavelet-based fault features that represent diverse symptoms of multiple low-speed bearing defects. The most useful fault features for diagnosis are then selected by utilizing a genetic algorithm (GA)-based kernel discriminative feature analysis cooperating with one-against-all multicategory support vector machines (OAA MCSVMs). Finally, each support vector machine is individually trained with its own feature vector that includes the most discriminative fault features, offering the highest classification performance. In this study, the effectiveness of the proposed GA-based kernel discriminative feature analysis and the classification ability of individually trained OAA MCSVMs are addressed in terms of average classification accuracy. In addition, the proposedGA- based kernel discriminative feature analysis is compared with four other state-of-the-art feature analysis approaches. Experimental results indicate that the proposed approach is superior to other feature analysis methodologies, yielding an average classification accuracy of 98.06% and 94.49% under rotational speeds of 50 revolutions-per-minute (RPM) and 80 RPM, respectively. Furthermore, the individually trained MCSVMs with their own optimal fault features based on the proposed GA-based kernel discriminative feature analysis outperform the standard OAA MCSVMs, showing an average accuracy of 98.66% and 95.01% for bearings under rotational speeds of 50 RPM and 80 RPM, respectively.

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Polybrominated diphenyl ethers (PBDEs), a common class of brominated flame retardants, are a ubiquitous part of our built environment, and for many years have contributed to improved public safety by reducing the flammability of everyday goods. Recently, PBDEs have come under increased international attention because of their potential to impact upon the environment and human health. Some PBDE compounds have been nominated for possible inclusion on the Stockholm Convention on Persistent Organic Pollutants, to which Australia is a Party. Work under the Stockholm Convention has demonstrated the capacity of some PBDEs to persist and accumulate in the environment and to be carried long distances. Much is unknown about the impact of PBDEs on living organisms, however recent studies show that some PBDEs can inhibit growth in colonies of plankton and algae and depress the reproduction of zooplankton. Laboratory mice and rats have also shown liver disturbances and damage to developing nervous systems as a result of exposure to PBDEs. In 2004, the Australian Government Department of the Environment and Water Resources began three studies to examine levels of PBDEs in aquatic sediments, indoor environments and human blood, as knowledge about PBDEs in Australia was very limited. The aim of these studies was to improve this knowledge base so that governments were in a better position to consider appropriate management actions. Due to the high costs for laboratory analysis of PBDEs, the number of samples collected for each study was limited and so caution is required when interpreting the findings. Nevertheless, these studies will provide governments with an indication of how prevalent PBDEs are in the Australian population and the environment and will also contribute to international knowledge about these chemicals. The Department of the Environment and Water Resources will be working closely with othergovernment agencies, industry and the community to investigate any further action that may be required to address PBDEs in Australia.

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The use of organophosphate esters (PFRs) as flame retardants and plasticizers has increased due to the ban of some brominated flame retardants. There is however some concern regarding the toxicity, particularly carcinogenicity and neurotoxicity, of some of the PFRs. In this study we applied wastewater analysis to assess use of PFRs by the Australian population. Influent samples were collected from eleven wastewater treatment plants (STPs) in Australia on Census day and analysed for PFRs using gas chromatography coupled with mass spectrometry (GC-MS). Per capita mass loads of PFRs were calculated using the accurate Census head counts. The results indicate that tris(2-butoxyethyl) phosphate (TBOEP) has the highest per capita input into wastewater followed by tris(2-chloroisopropyl) phosphate (TCIPP), tris(isobutyl) phosphate (TIBP), tris(2-chloroethyl) phosphate (TCEP) and tris(1,3-dichloroisopropyl) phosphate (TDCIPP). Similar PFR profiles were observed across the Australian STPs and a comparison with European and U.S. STPs indicated similar PFR concentrations. We estimate that approximately 2.1 mg person−1 day−1 of PFRs are input into Australian wastewater which equates to 16 tonnes per annum.

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In this paper, we aim at predicting protein structural classes for low-homology data sets based on predicted secondary structures. We propose a new and simple kernel method, named as SSEAKSVM, to predict protein structural classes. The secondary structures of all protein sequences are obtained by using the tool PSIPRED and then a linear kernel on the basis of secondary structure element alignment scores is constructed for training a support vector machine classifier without parameter adjusting. Our method SSEAKSVM was evaluated on two low-homology datasets 25PDB and 1189 with sequence homology being 25% and 40%, respectively. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies on these two data sets are 86.3% and 84.5%, respectively, which are higher than those obtained by other existing methods. Especially, our method achieves higher accuracies (88.1% and 88.5%) for differentiating the α + β class and the α/β class compared to other methods. This suggests that our method is valuable to predict protein structural classes particularly for low-homology protein sequences. The source code of the method in this paper can be downloaded at http://math.xtu.edu.cn/myphp/math/research/source/SSEAK_source_code.rar.

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Polybrominated diphenyl ethers (PBDEs) are a class of brominated flame retardants (BFRs) once extensively used in the plastics of a wide range of consumer products. The listing of certain congeners that are constituents of commercial PBDE mixtures (including c-octaBDE) in the Stockholm Convention and tightening regulation of many other BFRs in recent years have created the need for a rapid and effective method of identifying BFR-containing plastics. A three-tiered testing strategy comparing results from non-destructive testing (X-ray fluorescence (XRF)) (n = 1714), a surface wipe test (n = 137) and destructive chemical analysis (n = 48) was undertaken to systematically identify BFRs in a wide range of consumer products. XRF rapidly identified bromine in 92% of products later confirmed to contain BFRs. Surface wipes of products identified tetrabromobisphenol A (TBBPA), c-octaBDE congeners and BDE-209 with relatively high accuracy (> 75%) when confirmed by destructive chemical analysis. A relationship between the amounts of BFRs detected in surface wipes and subsequent destructive testing shows promise in predicting not only the types of BFRs present but also estimating the concentrations present. Information about the types of products that may contain persistent BFRs will assist regulators in implementing policies to further reduce the occurrence of these chemicals in consumer products.

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Lifted turbulent jet diffusion flame is simulated using Conditional Moment Closure (CMC). Specifically, the burner configuration of Cabra et al. [R. Cabra, T. Myhrvold, J.Y. Chen. R.W. Dibble, A.N. Karpetis, R.S. Barlow, Proc. Combust. Inst. 29 (2002) 1881-1887] is chosen to investigate H-2/N-2 jet flame supported by a vitiated coflow of products of lean H-2/air combustion. A 2D, axisymmetric flow-model fully coupled with the scalar fields, is employed. A detailed chemical kinetic scheme is included, and first order CIVIC is applied. Simulations are carried out for different jet velocities and coflow temperatures (T-c) The predicted liftoff generally agrees with experimental data, as well as joint-PDF results. Profiles of mean scalar fluxes in the mixture fraction space, for T-c = 1025 and 1080 K reveal that (1) Inside the flame zone, the chemical term balances the molecular diffusion term, and hence the Structure is of a diffusion flamelet for both cases. (2) In the pre-flame zone, the structure depends on the coflow temperature: for the 1025 K case, the chemical term being small, the advective term balances the axial turbulent diffusion term. However, for the 1080 K case. the chemical term is large and balances the advective term, the axial turbulent diffusion term being small. It is concluded that, lift-off is controlled (a) by turbulent premixed flame propagation for low coflow temperature while (b) by autoignition for high coflow temperature. (C) 2009 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

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Error estimates for the error reproducing kernel method (ERKM) are provided. The ERKM is a mesh-free functional approximation scheme [A. Shaw, D. Roy, A NURBS-based error reproducing kernel method with applications in solid mechanics, Computational Mechanics (2006), to appear (available online)], wherein a targeted function and its derivatives are first approximated via non-uniform rational B-splines (NURBS) basis function. Errors in the NURBS approximation are then reproduced via a family of non-NURBS basis functions, constructed using a polynomial reproduction condition, and added to the NURBS approximation of the function obtained in the first step. In addition to the derivation of error estimates, convergence studies are undertaken for a couple of test boundary value problems with known exact solutions. The ERKM is next applied to a one-dimensional Burgers equation where, time evolution leads to a breakdown of the continuous solution and the appearance of a shock. Many available mesh-free schemes appear to be unable to capture this shock without numerical instability. However, given that any desired order of continuity is achievable through NURBS approximations, the ERKM can even accurately approximate functions with discontinuous derivatives. Moreover, due to the variation diminishing property of NURBS, it has advantages in representing sharp changes in gradients. This paper is focused on demonstrating this ability of ERKM via some numerical examples. Comparisons of some of the results with those via the standard form of the reproducing kernel particle method (RKPM) demonstrate the relative numerical advantages and accuracy of the ERKM.

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Kernel weight is an important factor determining grain yield and nutritional quality in sorghum, yet the developmental processes underlying the genotypic differences in potential kernel weight remain unclear. The aim of this study was to determine the stage in development at which genetic effects on potential kernel weight were realized, and to investigate the developmental mechanisms by which potential kernel weight is controlled in sorghum. Kernel development was studied in two field experiments with five genotypes known to differ in kernel weight at maturity. Pre-fertilization floret and ovary development was examined and post-fertilization kernel-filling characteristics were analysed. Large kernels had a higher rate of kernel filling and contained more endosperm cells and starch granules than normal-sized kernels. Genotypic differences in kernel development appeared before stamen primordia initiation in the developing florets, with sessile spikelets of large-seeded genotypes having larger floret apical meristems than normal-seeded genotypes. At anthesis, the ovaries for large-sized kernels were larger in volume, with more cells per layer and more vascular bundles in the ovary wall. Across experiments and genotypes, there was a significant positive correlation between kernel dry weight at maturity and ovary volume at anthesis. Genotypic effects on meristem size, ovary volume, and kernel weight were all consistent with additive genetic control, suggesting that they were causally related. The pre-fertilization genetic control of kernel weight probably operated through the developing pericarp, which is derived from the ovary wall and potentially constrains kernel expansion.