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Statistical Representation (statistical + representation)

Distribution by Scientific Domains

Life Sciences	50%

Selected Abstracts

FROM MICRO- TO MACROEVOLUTION THROUGH QUANTITATIVE GENETIC VARIATION: POSITIVE EVIDENCE FROM FIELD CRICKETS

EVOLUTION, Issue 10 2004
Mattieu Bégin
Abstract . -Quantitative genetics has been introduced to evolutionary biologists with the suggestion that microevolution could be directly linked to macroevolutionary patterns using, among other parameters, the additive genetic variance/ covariance matrix (G) which is a statistical representation of genetic constraints to evolution. However, little is known concerning the rate and pattern of evolution of G in nature, and it is uncertain whether the constraining effect of G is important over evolutionary time scales. To address these issues, seven species of field crickets from the genera Gryllus and Teleogryllus were reared in the laboratory, and quantitative genetic parameters for morphological traits were estimated from each of them using a nested full-sibling family design. We used three statistical approaches (T method, Flury hierarchy, and Mantel test) to compare G matrices or genetic correlation matrices in a phylogenetic framework. Results showed that G matrices were generally similar across species, with occasional differences between some species. We suggest that G has evolved at a low rate, a conclusion strengthened by the consideration that part of the observed across-species variation in G can be explained by the effect of a genotype by environment interaction. The observed pattern of G matrix variation between species could not be predicted by either morphological trait values or phylogeny. The constraint hypothesis was tested by comparing the multivariate orientation of the reconstructed ancestral G matrix to the orientation of the across-species divergence matrix (D matrix, based on mean trait values). The D matrix mainly revealed divergence in size and, to a much smaller extent, in a shape component related to the ovipositor length. This pattern of species divergence was found to be predictable from the ancestral G matrix in agreement with the expectation of the constraint hypothesis. Overall, these results suggest that the G matrix seems to have an influence on species divergence, and that macroevolution can be predicted, at least qualitatively, from quantitative genetic theory. Alternative explanations are discussed. [source]

Determination of rock mass strength properties by homogenization

INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS, Issue 13 2001
A. Pouya
Abstract A method for determining fractured rock mass properties is presented here on the basis of homogenization approach. The rock mass is considered to be a heterogeneous medium composed of intact rock and of fractures. Its constitutive model is studied numerically using finite element method and assimilating the fractures to joint elements (Coste, Comportement Thermo-Hydro-Mécanique des massifs rocheux fracturés. Thèse de Doctorat, Ecole Nationale des Ponts et Chaussées, Paris, 1997). The method has been applied to a granite formation in France. Geological data on different families of fractures have been used for the statistical representation of the fractures. A mesh-generating tool for the medium with high density of fractures has been developed. The mechanical behaviour of the rock mass (elasticity, ultimate strength and hardening law) has been determined assuming linear elasticity and Mohr,Coulomb strength criterion both for the intact rock and the fractures. Evolution of the mechanical strength in different directions has been determined as a function of the mean stress, thanks to various numerical simulations. The mechanical strength appears to be anisotropic due to the preferential orientation of the fractures. The numerical results allowed us to determine an oriented strength criterion for the homogenized rock mass. A 2D constitutive law for the homogenized medium has been deduced from numerical data. A 3D extension of this model is also presented. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Monitoring of batch processes through state-space models

AICHE JOURNAL, Issue 6 2004
Jay H. Lee
Abstract The development of a state-space framework for monitoring batch processes that can complement the existing multivariate monitoring methods is presented. A subspace identification method will be used to extract the dynamic and batch-to-batch trends of the process and quality variables from historical operation data in the form of a "lifted" state-space stochastic model. A simple monitoring procedure can be formed around the state and residuals of the model using appropriate scalar statistical metrics. The proposed state-space monitoring framework complements the existing multivariate methods like the multi-way PCA method, in that it allows us to build a more complete statistical representation of batch operations and use it with incoming measurements for early detection of not only large, abrupt changes but also subtle changes. In particular, it is shown to be effective for detecting changes in the batch-to-batch correlation structure, slow drifts, and mean shifts. Such information can be useful in adapting the prediction model for batch-to-batch control. The framework allows for the use of on-line process measurements and/or off-line quality measurements. When both types of measurements are used in model building, one can also use the model to predict the quality variables based on incoming on-line measurements and quality measurements of previous batches. © 2004 American Institute of Chemical Engineers AIChE J, 50: 1198,1210, 2004 [source]

Computational cardiac atlases: from patient to population and back

EXPERIMENTAL PHYSIOLOGY, Issue 5 2009
Alistair A. Young
Integrative models of cardiac physiology are important for understanding disease and planning intervention. Multimodal cardiovascular imaging plays an important role in defining the computational domain, the boundary/initial conditions, and tissue function and properties. Computational models can then be personalized through information derived from in vivo and, when possible, non-invasive images. Efforts are now established to provide Web-accessible structural and functional atlases of the normal and pathological heart for clinical, research and educational purposes. Efficient and robust statistical representations of cardiac morphology and morphodynamics can thereby be obtained, enabling quantitative analysis of images based on such representations. Statistical models of shape and appearance can be built automatically from large populations of image datasets by minimizing manual intervention and data collection. These methods facilitate statistical analysis of regional heart shape and wall motion characteristics across population groups, via the application of parametric mathematical modelling tools. These parametric modelling tools and associated ontological schema also facilitate data fusion between different imaging protocols and modalities as well as other data sources. Statistical priors can also be used to support cardiac image analysis with applications to advanced quantification and subject-specific simulations of computational physiology. [source]