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Models Lead (models + lead)

Distribution by Scientific Domains

Life Sciences	20%
Engineering	20%

Selected Abstracts

Bivariate combined linkage and association mapping of quantitative trait loci

GENETIC EPIDEMIOLOGY, Issue 5 2008
Jeesun Jung
Abstract In this paper, bivariate/multivariate variance component models are proposed for high-resolution combined linkage and association mapping of quantitative trait loci (QTL), based on combinations of pedigree and population data. Suppose that a quantitative trait locus is located in a chromosome region that exerts pleiotropic effects on multiple quantitative traits. In the region, multiple markers such as single nucleotide polymorphisms are typed. Two regression models, "genotype effect model" and "additive effect model", are proposed to model the association between the markers and the trait locus. The linkage information, i.e., recombination fractions between the QTL and the markers, is modeled in the variance and covariance matrix. By analytical formulae, we show that the "genotype effect model" can be used to model the additive and dominant effects simultaneously; the "additive effect model" only takes care of additive effect. Based on the two models, F -test statistics are proposed to test association between the QTL and markers. By analytical power analysis, we show that bivariate models can be more powerful than univariate models. For moderate-sized samples, the proposed models lead to correct type I error rates; and so the models are reasonably robust. As a practical example, the method is applied to analyze the genetic inheritance of rheumatoid arthritis for the data of The North American Rheumatoid Arthritis Consortium, Problem 2, Genetic Analysis Workshop 15, which confirms the advantage of the proposed bivariate models. Genet. Epidemiol. 2008. © 2008 Wiley-Liss, Inc. [source]

Dempster,Shafer models for object recognition and classification

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 3 2006
A.P. Dempster
We consider situations in which each individual member of a defined object set is characterized uniquely by a set of variables, and we propose models and associated methods that recognize or classify a newly observed individual. Inputs consist of uncertain observations on the new individual and on a memory bank of previously identified individuals. Outputs consist of uncertain inferences concerning degrees of agreement between the new object and previously identified objects or object classes, with inferences represented by Dempster,Shafer belief functions. We illustrate the approach using models constructed from independent simple support belief functions defined on binary variables. In the case of object recognition, our models lead to marginal belief functions concerning how well the new object matches objects in memory. In the classification model, we compute beliefs and plausibilities that the new object lies in defined subsets of an object set. When regarded as similarity measures, our belief and plausibility functions can be interpreted as candidate membership functions in the terminology of fuzzy logic. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 283,297, 2006. [source]

Robust design of countercurrent adsorption separation processes: 5.

AICHE JOURNAL, Issue 7 2000
Nonconstant selectivity
Operating conditions for the separation of a binary mixture using a nonadsorbable eluent through simulated moving-bed technology were designed. The results obtained using equilibrium theory for adsorption described by Langmuir models lead to the definition of explicit constraints on the operating parameters to operate the unit in the desired regime of separation. A more general approach was able to produce the same result for a larger class of isotherms. The physical and mathematical conditions defining this larger class of isotherms are discussed, as well as the algorithms necessary to calculate the region of complete separation. Applications to the bi-Langmuir isotherm and the ideal adsorbed solution model, which are more flexible than the Langmuir model and can describe systems where selectivity changes with composition, are discussed. A shortcut method to get an explicit, though approximate, solution is proposed and its accuracy is discussed. [source]

Microvascular Thrombosis Models in Venules and Arterioles In Vivo

MICROCIRCULATION, Issue 3 2005
ROLANDO E. RUMBAUT MD
ABSTRACT Platelets are intimately involved in hemostasis and thrombosis. Under physiological conditions, circulating platelets do not interact with microvascular walls. However, in response to microvascular injury, platelet adhesion and subsequent thrombus formation may be observed in venules and arterioles in vivo. Numerous intravital video microscopy techniques have been described to induce and monitor the formation of microvascular thrombi. The mechanisms of microvascular injury vary widely among different models. Some models induce platelet activation with minimal effects on endothelium, others induce endothelial inflammation or injury, while other models lead to thrombus formation associated with endothelial denudation. The molecular mechanisms mediating platelet,vessel wall adhesive interactions differ among various models. In some instances, differences in responses between venules and arterioles are described that cannot be explained solely by hemodynamic factors. Several models for induction of microvascular thrombosis in vivo are outlined in this review, with a focus on the mechanisms of injury and thrombus formation, as well as on differences in responses between venules and arterioles. Recognizing these characteristics should help investigators select an appropriate model for studying microvascular thrombosis in vivo. [source]

Origin and evolution of magnetars

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY: LETTERS (ELECTRONIC), Issue 1 2008
Lilia Ferrario
ABSTRACT We present a population synthesis study of the observed properties of the magnetars investigating the hypothesis that they are drawn from a population of progenitors that are more massive than those of the normal radio pulsars. We assume that the anomalous X-ray emission is caused by the decay of a toroidal or tangled up field that does not take part in the spin-down of the star. Our model assumes that the magnetic flux of the neutron star is distributed as a Gaussian in the logarithm about a mean value that is described by a power law , where Mp is the mass of the progenitor. We find that we can explain the observed properties of the magnetars for a model with ,0= 2 × 1025 G cm2 and ,= 5 if we suitably parametrize the time evolution of the anomalous X-ray luminosity as an exponentially decaying function of time. Our modelling suggests that magnetars arise from stars in the high-mass end (20 M,,Mp, 45 M,) of this distribution. The lower mass progenitors are assumed to give rise to the radio pulsars. The high value of , can be interpreted in one of two ways. It may indicate that the magnetic flux distribution on the main sequence is a strong function of mass and that this is reflected in the magnetic fluxes of the neutron stars that form from this mass range (the fossil field hypothesis). The recent evidence for magnetic fluxes similar to those of the magnetars in a high fraction (,25 per cent) of massive O-type stars lends support to such a hypothesis. Another possibility is that the spin of the neutron star is a strong function of the progenitor mass, and it is only for stars that are more massive than ,20 M, that magnetar-type fields can be generated by the ,,, dynamo mechanism (the convective dynamo hypothesis). In either interpretation, it has to be assumed that all or a subset of stars in the mass range ,20,45 M,, which on standard stellar evolution models lead to black holes via the formation of a fall-back disc, must give rise to magnetars. Unlike with the radio pulsars, the magnetars only weakly constrain the birth spin period, due to their rapid spin-down. Our model predicts a birthrate of ,1.5,3 × 10,3 yr,1 for the magnetars. [source]

Comparison of analytical and numerical methods for homogenization of nanotube-reinforced polymers

PROCEEDINGS IN APPLIED MATHEMATICS & MECHANICS, Issue 1 2009
Ina Schmidt
Carbon nanotubes are increasingly getting impact as reinforcing material for polymer based nanocomposites. Hence, new modeling strategies are necessary to calculate the behavior of these materials. In the last years some attempts have been made using and developing classical micromechanical models. On the other hand numerical homogenization methods are available to tackle this problem. Examples for both types of modeling strategies are presented with focus on the nanotube geometry. The nanotubes are modeled as hollow tubes as well as as isotropic and transversely isotropic cylinders. As expected the results of numerical and analytical methods are identical for isotropic cylinder inclusions. Small deviations occur for transversely isotropic cylinders in transverse direction. In the case of hollow tube inclusions, the analytical models lead to lower stiffness values in transverse direction and for shear. The largest deviations occur for longitudinal shear with magnitudes smaller than 10%. In contrast the effort to get numerical results is enormous, so that the analytical models are still useful. (© 2009 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]

Developing a critical load approach for national risk assessments of atmospheric metal deposition,

ENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 3 2006
Jane R. Hall
Abstract The critical load approach has been proposed for evaluation of the need to reduce atmospheric emissions of metals that lead to transboundary transport and deposition across Europe. The present study demonstrates and evaluates the application of a critical load approach for national-scale risk assessment of metal deposition in the United Kingdom. Critical load maps, calculated using critical limits based on pH-dependent free metal ion activities, are presented. Current concentrations of lead and cadmium in soils are compared with two sets of critical limit values: First, limits based on the reactive soil concentration, and second, a pH-dependent free ion critical limit function, which takes into account variable soil characteristics across the country. The use of these two models leads to different conclusions about which areas of the United Kingdom are at greatest risk, partly because of differences in the range of values of pH and organic matter in soils used in ecotoxicological experiments and in the national database. Critical loads were calculated based on free ion critical limits; the critical loads were lowest in the south and east of the country and were associated with higher soil pH, lower runoff, and lower soil organic matter. [source]

PP amplitude bias caused by interface scattering: are diffracted waves guilty?

GEOPHYSICAL PROSPECTING, Issue 2 2003
Nathalie Favretto-Cristini
ABSTRACT This paper is concerned with the problem of interpretation of anomalous seismic amplitudes, induced by the amplitude-scattering phenomenon. This phenomenon occurs in the vicinity of a crack distribution at the interface between elastic layers. The purpose of this work is to obtain a better understanding of the physics of this distinctive phenomenon, in order to interpret correctly the amplitudes of the reflected events. By analogy with studies in optics and in acoustics, we suggest that diffraction is widely involved in the amplitude-scattering phenomenon. Analytical evaluation of the amount of energy carried by the reflected and the diffracted waves shows that neglecting diffraction in numerical models leads to local underestimation of the amplitude of waves reflected at interfaces with gas-filled crack distribution. [source]

Bayesian estimation of traffic lane state

INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, Issue 1 2003
Ivan Nagy
Abstract Modelling of large transportation systems requires a reliable description of its elements that can be easily adapted to the specific situation. This paper offers mixture model as a flexible candidate for modelling of such element. The mixture model describes particular and possibly very different states of a specific system by its individual components. A hierarchical model built on such elements can describe complexes of big city communications as well as railway or highway networks. Bayesian paradigm is adopted for estimation of parameters and the actual component label of the mixture model as it serves well for the subsequent decision making. As a straightforward application of Bayesian method to mixture models leads to infeasible computations, an approximation is applied. For normal stochastic variations, the resulting estimation algorithm reduces to a simple recursive weighted least squares. The elementary modelling is demonstrated on a model of traffic flow state in a single point of a roadway. The examples for simulated as well as real data show excellent properties of the suggested model. They represent much wider set of extensive tests made. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Maximum Likelihood Estimation in Dynamical Models of HIV

BIOMETRICS, Issue 4 2007
J. Guedj
Summary The study of dynamical models of HIV infection, based on a system of nonlinear ordinary differential equations (ODE), has considerably improved the knowledge of its pathogenesis. While the first models used simplified ODE systems and analyzed each patient separately, recent works dealt with inference in non-simplified models borrowing strength from the whole sample. The complexity of these models leads to great difficulties for inference and only the Bayesian approach has been attempted by now. We propose a full likelihood inference, adapting a Newton-like algorithm for these particular models. We consider a relatively complex ODE model for HIV infection and a model for the observations including the issue of detection limits. We apply this approach to the analysis of a clinical trial of antiretroviral therapy (ALBI ANRS 070) and we show that the whole algorithm works well in a simulation study. [source]