Estimates of genetic parameters for growth traits of the sea urchin, Strongylocentrotus intermedius

Heritabilities and genetic and phenotypic correlations were estimated for body weight, test diameter, and test height of the sea urchin from measurements on progeny resulting from 11 sires and 33 dams by artificial fertilization of 3 females by single males, and measurements at 8, 10, and 12 months after metamorphism. Point estimate for heritabilities based on the sire components of variance were moderate to high for body weight (0.21-0.49), test diameter (0.21-0.47), and test height (0.22-0.37). Genetic correlations were significant for body weight with test diameter (0.30similar to0.65) and test height (0.30similar to0.54) and test diameter with test height (0.31similar to0.65). Genetic correlation estimates, derived the nested design and half-sib correlation analysis used in this study, appear to provide reliable estimates. Significant phenotypic correlations were found for body weight with test diameter (0.82similar to0.86) and test height (0.49similar to0.83), and test diameter with test height (0.47similar to0.84). The phenotypic correlations for test height with body weight (0.491) and test diameter (0.467) at 12 months' of age were smaller than those earlier sampling periods.(C) 2004 Published by Elsevier B.V.

Genetic parameter estimates for growth traits at early stage of Pacific abalone, Haliotis discus hannai Ino

Heritability and genetic and phenotypic correlations were estimated for juvenile growth traits of Pacific abalone Haliotis discus hannai Ino. The estimates were calculated from shell length and shell width measurements on progeny resulting from 12 half-sib families and 36 full-sib families obtained using artificial fertilization of mating three females to each male. The measurements were taken at 10, 20 and 30 d after fertilization. It was found that heritability estimates based on sire component ranged from 0.23 to 0.36 for shell length and 0.21 to 0.32 for shell width. Heritability estimates from dam component were larger than those from sire component at three ages, indicating presence of maternal effects, non-additive genetic effects and common environmental effects. Phenotypic correlations were significant at three ages (P < 0.05), with values of 0.92, 0.93 and 0.92, respectively. Genetic correlations from the paternal half-sib correlation analysis were highly positive at three ages, with values of 0.50, 0.78 and 0.81, respectively. The results suggest that selective breeding is an effective approach to improving growth traits of Pacific abalone stocks.

Effects of Subgrid-Scale Modeling on Time Correlations in Large Eddy Simulation

The effects of the unresolved subgrid-scale (SGS) motions on the energy balance of the resolved scales in large eddy simulation (LES) have been investigated actively because modeling the energy transfer between the resolved and unresolved scales is crucial to constructing accurate SGS models. But the subgrid scales not only modify the energy balance, they also contribute to temporal decorrelation of the resolved scales. The importance of this effect in applications including the predictability problem and the evaluation of sound radiation by turbulent flows motivates the present study of the effect of SGS modeling on turbulent time correlations. This paper compares the two-point, two-time Eulerian velocity correlation in isotropic homogeneous turbulence evaluated by direct numerical simulation (DNS) with the correlations evaluated by LES using a standard spectral eddy viscosity. It proves convenient to express the two-point correlations in terms of spatial Fourier decomposition of the velocity field. The LES fields are more coherent than the DNS fields: their time correlations decay more slowly at all resolved scales of motion and both their integral scales and microscales are larger than those of the DNS field. Filtering alone is not responsible for this effect: in the Fourier representation, the time correlations of the filtered DNS field are identical to those of the DNS field itself. The possibility of modeling the decorrelating effects of the unresolved scales of motion by including a random force in the model is briefly discussed. The results could have applications to the problem of computing sound sources in isotropic homogeneous turbulence by LES

Time Correlations Of Pressure In Isotropic Turbulence

The time correlations of pressure modes in stationary isotropic turbulence are investigated under the Kraichnan and Tennekes "random sweeping" hypothesis. A simple model is obtained which predicts a universal form for the time correlations. It implies that the decorrelation process of pressure fluctuations in time is mainly dominated by the sweeping velocity, and the pressure correlations have the same decorrelation time scales as the velocity correlations. These results are verified using direct numerical simulations of isotropic turbulence at two moderate Reynolds numbers; the mode correlations collapse to the universal form when the time separations are scaled by wavenumber times the sweeping velocity, and the ratios of the correlation coefficients of pressure modes to those of velocity modes are approximately unity for the entire range of time separation. (c) 2008 American Institute of Physics.

On the computation of space-time correlations by large-eddy simulation

The effect of subgrid-scale (SGS) modeling on velocity (space-) time correlations is investigated in decaying isotropic turbulence. The performance of several SGS models is evaluated, which shows superiority of the dynamic Smagorinsky model used in conjunction with the multiscale large-eddy simulation (LES) procedure. Compared to the results of direct numerical simulation, LES is shown to underpredict the (un-normalized) correlation magnitude and slightly overpredict the decorrelation time scales. This can lead to inaccurate solutions in applications such as aeroacoustics. The underprediction of correlation functions is particularly severe for higher wavenumber modes which are swept by the most energetic modes. The classic sweeping hypothesis for stationary turbulence is generalized for decaying turbulence and used to analyze the observed discrepancies. Based on this analysis, the time correlations are determined by the wavenumber energy spectra and the sweeping velocity, which is the square root of the total energy. Hence, an accurate prediction of the instantaneous energy spectra is most critical to the accurate computation of time correlations. (C) 2004 American Institute of Physics.

Analytical calculations of Eulerian and Lagrangian time correlations in turbulent shear flows

The Taylor series expansion method is used to analytically calculate the Eulerian and Lagrangian time correlations in turbulent shear flows. The short-time behaviors of those correlation functions can be obtained from the series expansions. Especially, the propagation velocity and sweeping velocity in the elliptic model of space-time correlation are analytically calculated and further simplified using the sweeping hypothesis and straining hypothesis. These two characteristic velocities mainly determine the space-time correlations.

Scale-similarity model for Lagrangian velocity correlations in isotropic and stationary turbulence

A scale-similarity model for Lagrangian two-point, two-time velocity correlations LVCs in isotropic turbulence is developed from the Kolmogorov similarity hypothesis. It is a second approximation to the isocontours of LVCs, while the Smith-Hay model is only a first approximation. This model expresses the LVC by its space correlation and a dispersion velocity. We derive the analytical expression for the dispersion velocity from the Navier-Stokes equations using the quasinormality assumption. The dispersion velocity is dependent on enstrophy spectra and shown to be smaller than the sweeping velocity for the Eulerian velocity correlation. Therefore, the Lagrangian decorrelation process is slower than the Eulerian decorrelation process. The data from direct numerical simulation of isotropic turbulence support the scale-similarity model: the LVCs for different space separations collapse into a universal form when plotted against the separation axis defined by the model.

Space-time correlations of fluctuating velocities in turbulent shear flows

Space-time correlations or Eulerian two-point two-time correlations of fluctuating velocities are analytically and numerically investigated in turbulent shear flows. An elliptic model for the space-time correlations in the inertial range is developed from the similarity assumptions on the isocorrelation contours: they share a uniform preference direction and a constant aspect ratio. The similarity assumptions are justified using the Kolmogorov similarity hypotheses and verified using the direct numerical simulation DNS of turbulent channel flows. The model relates the space-time correlations to the space correlations via the convection and sweeping characteristic velocities. The analytical expressions for the convection and sweeping velocities are derived from the Navier-Stokes equations for homogeneous turbulent shear flows, where the convection velocity is represented by the mean velocity and the sweeping velocity is the sum of the random sweeping velocity and the shearinduced velocity. This suggests that unlike Taylor’s model where the convection velocity is dominating and Kraichnan and Tennekes’ model where the random sweeping velocity is dominating, the decorrelation time scales of the space-time correlations in turbulent shear flows are determined by the convection velocity, the random sweeping velocity, and the shear-induced velocity. This model predicts a universal form of the spacetime correlations with the two characteristic velocities. The DNS of turbulent channel flows supports the prediction: the correlation functions exhibit a fair good collapse, when plotted against the normalized space and time separations defined by the elliptic model.

Subgrid-scale contributions to Lagrangian time correlations in isotropic turbulence

The application of large-eddy simulation (LES) to particle-laden turbulence raises such a fundamental question as whether the LES with a subgrid scale (SGS) model can correctly predict Lagrangian time correlations (LTCs). Most of the currently existing SGS models are constructed based on the energy budget equations. Therefore, they are able to correctly predict energy spectra, but they may not ensure the correct prediction on the LTCs. Previous researches investigated the effect of the SGS modeling on the Eulerian time correlations. This paper is devoted to study the LTCs in LES. A direct numerical simulation (DNS) and the LES with a spectral eddy viscosity model are performed for isotropic turbulence and the LTCs are calculated using the passive vector method. Both a priori and a posteriori tests are carried out. It is observed that the subgrid-scale contributions to the LTCs cannot be simply ignored and the LES overpredicts the LTCs than the DNS. It is concluded from the straining hypothesis that an accurate prediction of enstrophy spectra is most critical to the prediction of the LTCs.

CpG island density and its correlations with genomic features in mammalian genomes

Background: CpG islands, which are clusters of CpG dinucleotides in GC-rich regions, are considered gene markers and represent an important feature of mammalian genomes. Previous studies of CpG islands have largely been on specific loci or within one geno

Cardioviral RNA structure logo analysis: entropy, correlations, and prediction

In recent years, there has been an increased number of sequenced RNAs leading to the development of new RNA databases. Thus, predicting RNA structure from multiple alignments is an important issue to understand its function. Since RNA secondary structures are often conserved in evolution, developing methods to identify covariate sites in an alignment can be essential for discovering structural elements. Structure Logo is a technique established on the basis of entropy and mutual information measured to analyze RNA sequences from an alignment. We proposed an efficient Structure Logo approach to analyze conservations and correlations in a set of Cardioviral RNA sequences. The entropy and mutual information content were measured to examine the conservations and correlations, respectively. The conserved secondary structure motifs were predicted on the basis of the conservation and correlation analyses. Our predictive motifs were similar to the ones observed in the viral RNA structure database, and the correlations between bases also corresponded to the secondary structure in the database.

Factors affecting leaf morphology: a case study of Ranunculus natans C. A. Mey. (Ranunculaceae) in the arid zone of northwest China

In order to examine the role of environmental factors affecting foliar morphology, we performed a case study of leaf morphological variation of Ranunculus natans found in the arid zone of northwest China. We found that foliar phenotypic variation differed significantly between populations. We described substantial positive correlations between altitude and leaf area (LA) as well as leaf perimeter (LP), and also between longitude and number of teeth, along with dissection index (DI). The pH, conductivity, and salinity of the environment caused a significant decrease in both LA and LP. Ranked in terms of their impacts on leaf morphology, the six selected factors were: altitude > pH > conductivity > salinity > longitude > latitude. We found that foliar morphological variations are functional responses to water-quantity factors (e.g., altitude and longitude at regional scales) and water-availability relation factors (e.g., pH, conductivity, and salinity at local scales), rather than to temperature-relation factors (latitude). Therefore, altitude and longitude, along with pH, conductivity, and salinity, are the main factors that significantly influence foliar morphology in the arid zone of China. We found that main factors played major roles in plant phenotypic plasticity in a complex ecosystem, although different combinations and interactions of environmental and geographical factors in each local environment may obscure the general trends in trait changes along environmental gradients.