145 resultados para Complete Information


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In this paper, we show that K-10n can be factored into alpha C-5-factors and beta 1-factors for all non-negative integers alpha and beta satisfying 2alpha + beta = 10(n) - 1.

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Our previous studies have shown that two distinct genotypes of Sindbis (SIN) virus occur in Australia. One of these, the Oriental/Australian type, circulates throughout most of the Australian continent, whereas the recently identified south-west (SW) genetic type appears to be restricted to a distinct geographic region located in the temperate south-west of Australia. We have now determined the complete nucleotide and translated amino acid sequences of a SW isolate of SIN virus (SW6562) and performed comparative analyses with other SIN viruses at the genomic level. The genome of SW6562 is 11,569 nucleotides in length, excluding the cap nucleotide and poly (A) tail. Overall this virus differs from the prototype SIN virus (strain AR339) by 23% in nucleotide sequence and 12.5% in amino acid sequence. Partial sequences of four regions of the genome of four SW isolates were determined and compared with the corresponding sequences from a number of SIN isolates from different regions of the World. These regions are the non-structural protein (nsP3), the E2 gene, the capsid gene, and the repeated sequence elements (RSE) of the 3'UTR. These comparisons revealed that the SW SIN viruses were more closely related to South African and European strains than to other Australian isolates of SIN virus. Thus the SW genotype of SIN virus may have been introduced into this region of Australia by viremic humans or migratory birds and subsequently evolved independently in the region. The sequence data also revealed that the SW genotype contains a unique deletion in the RSE of the 3'UTR region of the genome. Previous studies have shown that deletions in this region of the SIN genome can have significant effects on virus replication in mosquito and avian cells, which may explain the restricted distribution of this genotype of SIN virus.

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A theta graph is a graph consisting of three pairwise internally disjoint paths with common end points. Methods for decomposing the complete graph K-nu into theta graphs with fewer than ten edges are given.

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The absorption of fluid by unsaturated, rigid porous materials may be characterized by the sorptivity. This is a simple parameter to determine and is increasingly being used as a measure of a material's resistance to exposure to fluids (especially moisture and reactive solutes) in aggressive environments. The complete isothermal absorption process is described by a nonlinear diffusion equation, with the hydraulic diffusivity being a strongly nonlinear function of the degree of saturation of the material. This diffusivity can be estimated from the sorptivity test. In a typical test the cumulative absorption is proportional to the square root of time. However, a number of researchers have observed deviation from this behaviour when the infiltrating fluid is water and there is some potential for chemo-mechanical interaction with the material. In that case the current interpretation of the test and estimation of the hydraulic diffusivity is no longer appropriate. Kuntz and Lavallee (2001) discuss the anomalous behaviour and propose a non-Darcian model as a more appropriate physical description. We present an alternative Darcian explanation and theory that retrieves the earlier advantages of the simple sorptivity test in providing parametric information about the material's hydraulic properties and allowing simple predictive formulae for the wetting profile to be generated.

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Over the past decade or so, there has been increasing demand for greater clarity about the major causes of disease and injury, how these differentially affect populations, and how they are changing. In part, this demand has been motivated by resource constraints and a realisation that better health is possible with more informed allocation of resources. At the same time, there has been a change in the way population health and its determinants are quantified, with a much closer integration of the quantitative population sciences (such as epidemiology, demography and health economics) to strengthen and broaden the evidence base for healthcare policy.