Human cryptosporidiosis in immunodeficient patients in France (2015-2017)

Cryptosporidiosis is a common disease in children and immunodeficient individuals. In 2006, a national network was set up on the surveillance of human cryptosporidiosis in France. Since January 2015, the 41 tertiary care hospitals and the 3 private laboratories of the French National Network on the surveillance of human cryptosporidiosis have been able to declare confirmed cases of cryptosporidiosis online. Between 2015 and 2017, 210 cases of cryptosporidiosis were declared in immunodeficient patients in France; Cryptosporidium parvum and Cryptosporidium hominis represented 66% and 22% of cases, respectively. A peak was observed in autumn. Cryptosporidiosis occurred mainly in a context of solid organ transplantation (SOT) (49%) and of HIV infection (30%). In SOT recipients, cryptosporidiosis appeared more frequently in the first 6 months post transplantation. Regarding cases declared in SOT recipients, mycophenolate mofetil was used in 68%. A mortality rate of 6% was observed. Present results underline the importance of screening for cryptosporidiosis in immunocompromised patients suffering from diarrhea, especially in the course of major cell mediated immunodeficiency or even systematic screening before SOT. Exclusive Cryptosporidium free water feeding could be suggested during major cell mediated immunodeficiency

Evaluation and mangement of fungal risk in cystic fibrosis: first results of a national French study

Date du colloque&nbsp;: 06/2009</p

Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods

An unprecedented spectroscopic data stream will soon become available with forthcoming Earth-observing satellite missions equipped with imaging spectroradiometers. This data stream will open up a vast array of opportunities to quantify a diversity of biochemical and structural vegetation properties. The processing requirements for such large data streams require reliable retrieval techniques enabling the spatiotemporally explicit quantification of biophysical variables. With the aim of preparing for this new era of Earth observation, this review summarizes the state-of-the-art retrieval methods that have been applied in experimental imaging spectroscopy studies inferring all kinds of vegetation biophysical variables. Identified retrieval methods are categorized into: (1) parametric regression, including vegetation indices, shape indices and spectral transformations; (2) nonparametric regression, including linear and nonlinear machine learning regression algorithms; (3) physically based, including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches; and (4) hybrid regression methods, which combine RTM simulations with machine learning regression methods. For each of these categories, an overview of widely applied methods with application to mapping vegetation properties is given. In view of processing imaging spectroscopy data, a critical aspect involves the challenge of dealing with spectral multicollinearity. The ability to provide robust estimates, retrieval uncertainties and acceptable retrieval processing speed are other important aspects in view of operational processing. Recommendations towards new-generation spectroscopy-based processing chains for operational production of biophysical variables are given

Data for: Ad hoc angular discretization of the radiative transfer equation

geometries considered for test cases 3 and

Data for: Ad hoc angular discretization of the radiative transfer equation

geometries considered for test cases 3 and 4THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

On the use of reduced models obtained through identification for feedback optimal control problems in a heat convection–diffusion problem

International audienceThis paper deals with the use of reduced models for solving some optimal control problems. More precisely, the reduced model is obtained through the modal identification method. The test case which the algorithms is tested on is based on the flow over a backward-facing step. Though the reduction for the velocity fields for different Reynolds numbers is treated elsewhere [1], only the convection–diffusion equation for the energy problem is treated here. The model reduction is obtained through the solution of a gradient-type optimization problem where the objective function gradient is computed through the adjoint-state method. The obtained reduced models are validated before being coupled to optimal control algorithms. In this paper the feedback optimal control problem is considered. A Riccati equation is solved along with the Kalman gain equation. Additionally, a Kalman filter is performed to reconstruct the reduced state through previous and actual measurements. The numerical test case shows the ability of the proposed approach to control systems through the use of reduced models obtained by the modal identification method

Méthodologies éléments finis pour modéliser le transport conducto-radiatif dans des céramiques macroporeuses aux échelles continues et discrètes

National audienceDans cet article, nous présentons et comparons trois modèles conducto-radiatifs distincts aux échelles mésoscopique et macroscopique qui peuvent être utilisés pour modéliser le transfert de chaleur à haute température en vue d'être intégrés dans un processus d'optimisation de la topologie. Nous uitilisons la méthode des éléments finis et nous traitons les non-linéarités à l'aide d'une méthode de point fixe couplée à une méthode de linéarisation Newton-Raphson. A tous les régimes conduction-rayonnement, et même lorsque le rayonnement prédomine, il apparaît que l'approche à échelle continue, qui a été mise en place grâce à de bonnes lois d'homogénéisation, donne des résultats satisfaisants, ce qui n'est pas le cas pour le modèle d'approximation de Rosseland. Le modèle homogénéisé à échelle continue semble être un bon candidat pour être utilisé à l'avenir dans des problèmes d'optimisation de la topologie

Deterministic radiative transfer equation solver on unstructured tetrahedral meshes: Efficient assembly and preconditioning

International audienceDue to its integro-differential nature, deriving schemes for numerically solving the radiative transfer equation (RTE) is challenging. Most solvers are efficient in specific scenarios: structured grids, simulations with low-scattering materials... In this paper, a full solver, from the discretization of the steady-state monochromatic RTE to the solution of the resulting system, is derived. Using a mixed matrix-ready/matrix-free approach, our solver is able to discretize and solve a 45.7 billion unknown problem on 27 thousand processes in three minutes for a full physics involving scattering, absorption, and reflection. Because of the high dimensionality of the continuous equation, the linear system would have had more than 6 ×1015 nonzero entries if assembled explicitly. Our approach allows for large memory gains by only storing lower dimension reference matrices. The finite element-based solver is wrapped around open-source software, FreeFEM for discretization, PETSc for linear algebra, and hypre for the algebraic multigrid infrastructure. Overall, deterministic results are presented on arbitrarily-decomposed unstructured grids for radiative transfer problems with scattering, absorbing, and reflecting heterogeneities on up to 27 thousand processes