921 resultados para phenotypic correlation


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Time correlation functions yield profound information about the dynamics of a physical system and hence are frequently calculated in computer simulations. For systems whose dynamics span a wide range of time, currently used methods require significant computer time and memory. In this paper, we discuss the multiple-tau correlator method for the efficient calculation of accurate time correlation functions on the fly during computer simulations. The multiple-tau correlator is efficacious in terms of computational requirements and can be tuned to the desired level of accuracy. Further, we derive estimates for the error arising from the use of the multiple-tau correlator and extend it for use in the calculation of mean-square particle displacements and dynamic structure factors. The method described here, in hardware implementation, is routinely used in light scattering experiments but has not yet found widespread use in computer simulations.

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Six strains of a previously undescribed catalase-positive coryneform bacterium isolated from clinical specimens from dogs were characterized by phenotypic and molecular genetic methods. Biochemical and chemotaxonomic studies revealed that the unknown bacterium belonged to the genus Corynebacterium sensu stricto. Comparative 16S rRNA gene sequencing showed that the six strains were genealogically highly related and constitute a new subline within the genus Corynebacterium; this subline is close to but distinct from C. falsenii, C. jeikeium, and C. urealyticum. The unknown bacterium from dogs was distinguished from all currently validated Corynebacterium species by phenotypic tests including electrophoretic analysis of whole-cell proteins. On the basis of phylogenetic and phenotypic evidence, it is proposed that the unknown bacterium be classified as a new species, Corynebacterium auriscanis. The type strain of C. auriscanis is CCUG 39938T.

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Genetic analysis of heat tolerance will help breeders produce rice (Oryza sativa L.) varieties adapted to future climates. An F6 population of 181 recombinant inbred lines of Bala (tolerant) × Azucena (susceptible) was screened for heat tolerance at anthesis by measuring spikelet fertility at 30°C (control) and 38°C (high temperature) in experiments conducted in the Philippines and the United Kingdom. The parents varied significantly for absolute spikelet fertility under control (79–87%) and at high temperature (2.9–47.1%), and for relative spikelet fertility (high temperature/control) at high temperature (3.7–54.9%). There was no correlation between spikelet fertility in control and high-temperature conditions and no common quantitative trait loci (QTLs) were identified. Two QTLs for spikelet fertility under control conditions were identified on chromosomes 2 and 4. Eight QTLs for spikelet fertility under high-temperature conditions were identified on chromosomes 1, 2, 3, 8, 10, and 11. The most significant heat-responsive QTL, contributed by Bala and explaining up to 18% of the phenotypic variation, was identified on chromosome 1 (38.35 mega base pairs on the rice physical genome map). This QTL was also found to influence plant height, explaining 36.6% of the phenotypic variation. A comparison with other studies of abiotic (drought, cold, salinity) stresses showed QTLs at similar positions on chromosomes 1, 3, 8, and 10, suggesting common underlying stress-responsive regions of the genome.

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The reactions of propene with [Zr(cyclopentadienyl)(2)Me](+) have been investigated using density functional theory in order to study the correlation between regioselectivity and site charge in propene polymerisation. The reaction paths of the 1,2 and 2,1 additions of the methyl group to propene have been established. The geometries and energies of the reactants, transition states and products have been obtained using both PBEPBE/LANL2DZ and B3LYP/LANL2DZ methodologies. The results with both density functionals show that the activation energy for 1,2-insertion is lower than that for 2,1-insertion (Fig. 5) and this is consistent with the experiment results. Also for both density functionals, the difference of the thermal dynamic driving forces between the 2,1 product named 2-21 and the 1,2 product named 2-12 is significantly lower than the difference between the energy barriers. It is noted that in the reactants, the Mulliken partial charge on the central carbon atom C2 is positive and it can be concluded that 1,2-insertion is favoured because it can proceed via a cationic reaction.

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The antioxidant capacity of oak wood used in the ageing of wine was studied by four different methods: measurement of scavenging capacity against a given radical (ABTS, DPPH), oxygen radical absorbance capacity (ORAC) and the ferric reducing antioxidant power (FRAP). Although, the four methods tested gave comparable results for the antioxidant capacity measured in oak wood extracts, the ORAC method gave results with some differences from the other methods. Non-toasted oak wood samples displayed more antioxidant power than toasted ones due to differences in the polyphenol compositon. A correlation analysis revealed that ellagitannins were the compounds mainly responsible for the antioxidant capacity of oak wood. Some phenolic acids, mainly gallic acid, also showed a significant correlation with antioxidant capacity.

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The meltabilities of 14 process cheese samples were determined at 2 and 4 weeks after manufacture using sensory analysis, a computer vision method, and the Olson and Price test. Sensory analysis meltability correlated with both computer vision meltability (R-2 = 0.71, P < 0.001) and Olson and Price meltability (R-2 = 0.69, P < 0.001). There was a marked lack of correlation between the computer vision method and the Olson and Price test. This study showed that the Olson and Price test gave greater repeatability than the computer vision method. Results showed process cheese meltability decreased with increasing inorganic salt content and with lower moisture/fat ratios. There was very little evidence in this study to show that process cheese meltability changed between 2 and 4 weeks after manufacture..

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This paper investigates how the correlations implied by a first-order simultaneous autoregressive (SAR(1)) process are affected by the weights matrix and the autocorrelation parameter. A graph theoretic representation of the covariances in terms of walks connecting the spatial units helps to clarify a number of correlation properties of the processes. In particular, we study some implications of row-standardizing the weights matrix, the dependence of the correlations on graph distance, and the behavior of the correlations at the extremes of the parameter space. Throughout the analysis differences between directed and undirected networks are emphasized. The graph theoretic representation also clarifies why it is difficult to relate properties ofW to correlation properties of SAR(1) models defined on irregular lattices.

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Novel imaging techniques are playing an increasingly important role in drug development, providing insight into the mechanism of action of new chemical entities. The data sets obtained by these methods can be large with complex inter-relationships, but the most appropriate statistical analysis for handling this data is often uncertain - precisely because of the exploratory nature of the way the data are collected. We present an example from a clinical trial using magnetic resonance imaging to assess changes in atherosclerotic plaques following treatment with a tool compound with established clinical benefit. We compared two specific approaches to handle the correlations due to physical location and repeated measurements: two-level and four-level multilevel models. The two methods identified similar structural variables, but higher level multilevel models had the advantage of explaining a greater proportion of variation, and the modeling assumptions appeared to be better satisfied.

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The success of any diversification strategy depends upon the quality of the estimated correlation between assets. It is well known, however, that there is a tendency for the average correlation among assets to increase when the market falls and vice-versa. Thus, assuming that the correlation between assets is a constant over time seems unrealistic. Nonetheless, these changes in the correlation structure as a consequence of changes in the market’s return suggests that correlation shifts can be modelled as a function of the market return. This is the idea behind the model of Spurgin et al (2000), which models the beta or systematic risk, of the asset as a function of the returns in the market. This is an approach that offers particular attractions to fund managers as it suggest ways by which they can adjust their portfolios to benefit from changes in overall market conditions. In this paper the Spurgin et al (2000) model is applied to 31 real estate market segments in the UK using monthly data over the period 1987:1 to 2000:12. The results show that a number of market segments display significant negative correlation shifts, while others show significantly positive correlation shifts. Using this information fund managers can make strategic and tactical portfolio allocation decisions based on expectations of market volatility alone and so help them achieve greater portfolio performance overall and especially during different phases of the real estate cycle.

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Practical applications of portfolio optimisation tend to proceed on a “top down” basis where funds are allocated first at asset class level (between, say, bonds, cash, equities and real estate) and then, progressively, at sub-class level (within property to sectors, office, retail, industrial for example). While there are organisational benefits from such an approach, it can potentially lead to sub-optimal allocations when compared to a “global” or “side-by-side” optimisation. This will occur where there are correlations between sub-classes across the asset divide that are masked in aggregation – between, for instance, City offices and the performance of financial services stocks. This paper explores such sub-class linkages using UK monthly stock and property data. Exploratory analysis using clustering procedures and factor analysis suggests that property performance and equity performance are distinctive: there is little persuasive evidence of contemporaneous or lagged sub-class linkages. Formal tests of the equivalence of optimised portfolios using top-down and global approaches failed to demonstrate significant differences, whether or not allocations were constrained. While the results may be a function of measurement of market returns, it is those returns that are used to assess fund performance. Accordingly, the treatment of real estate as a distinct asset class with diversification potential seems justified.

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Atmospheric aerosol acts to both reduce the background concentration of natural cluster ions, and to attenuate optical propagation. Hence, the presence of aerosol has two consequences, the reduction of the air’s electrical conductivity and the visual range. Ion-aerosol theory and Koschmieder’s visibility theory are combined here to derive the related non-linear variation of the atmospheric electric potential gradient with visual range. A substantial sensitivity is found under poor visual range conditions, but, for good visual range conditions the sensitivity diminishes and little influence of local aerosol on the fair weather potential gradient occurs. This allows visual range measurements, made simply and routinely at many meteorological sites, to provide inference about the local air’s electrical properties.

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The qnrS1 gene induces reduced susceptibility to fluoroquinolones in enterobacteria. We investigated the structure, antimicrobial susceptibility phenotype, and antimicrobial resistance gene characteristics of qnrS1 plasmids from hospitalized patients and community controls in southern Vietnam. We found that the antimicrobial susceptibilities, resistance gene characteristics, and plasmid structures of qnrS1 plasmids from the hospital differed from those from the community. Our data imply that the characteristics of the two plasmid groups are indicative of distinct selective pressures in the differing environments.