Naringenin-responsive riboswitch-based fluorescent biosensor module for Escherichia coli co-cultures

11125Nsciescopu

Multilevel Monte Carlo methods and applications to elliptic PDEs with random coefficients

We consider the numerical solution of elliptic partial differential equations with random coefficients. Such problems arise, for example, in uncertainty quantification for groundwater flow. We describe a novel variance reduction technique for the standard Monte Carlo method, called the multilevel Monte Carlo method, and demonstrate numerically its superiority. The asymptotic cost of solving the stochastic problem with the multilevel method is always significantly lower than that of the standard method and grows only proportionally to the cost of solving the deterministic problem in certain circumstances. Numerical calculations demonstrating the effectiveness of the method for one- and two-dimensional model problems arising in groundwater flow are presented. © 2011 Springer-Verlag

Stochastic modeling and identification of an uncertain computational dynamical model with random fields properties and model uncertainties

International audienceThis paper is devoted to the construction and to the identification of a probabilistic model of random fields in presence of modeling errors, in high stochastic dimension and presented in the context of computational structural dynamics. Due to the high stochastic dimension of the random quantities which have to be identified using statistical inverse methods (challenging problem), a complete methodology is proposed and validated. The parametric-nonparametric (generalized) probabilistic approach of uncertainties is used to perform the prior stochastic models: (1) system-parameters uncertainties induced by the variabilities of the material properties are described by random fields for which their statistical reductions are still in high stochastic dimension and (2) model uncertainties induced by the modeling errors are taken into account with the nonparametric probabilistic approach in high stochastic dimension. The steps of the methodology are explained and illustrated through an application

Hypertonic saline resuscitation maintains a more balanced profile of T-lymphocyte subpopulations in a rat model of hemorrhagic shock

Objective: To investigate the potential and early effect of hypertonic saline resuscitation on T-lymphocyte subpopulations in rats with hemorrhagic shock. Methods: A model of rat with severe hemorrhagic shock was established in 18 Sprague-Dawley (SD) rats. The rats were randomly divided into Sham group, HTS group (hypertonic saline resuscitation group) and NS group (normal saline resuscitation group). Each group contained 6 rats. The CD4(+) and CD8(+) subpopulations of T-lymphocytes in peripheral blood were detected respectively before shock and after resuscitation by double antibody labelling and flow cytometry. Results: In the early stage after hemorrhagic shock, fluid resuscitation and emergency treatment, the CD4(+) lymphocytes of peripheral blood in HTS and NS groups markedly increased. Small volume resuscitation with HTS also induced peripheral CD8(+) lymphocytes to a certain extent, whereas NS resuscitation showed no effect in this respect. Consequently, compared with Sham and HTS groups, CD4(+)/CD8(+) ratio of peripheral blood in NS group was obviously increased, and showed statistically differences. Conclusion: In this model of rat with severe hemorrhagic shock, small volume resuscitation with HTS is more effective than NS in reducing immunologic disorders and promoting a more balanced profile of T-lymphocyte subpopulations regulating network