A Parallel and Adaptive Space-Time Method for Maxwell\u27s Equations

In this work a space-time discretization for linear hyperbolic evolution systems is introduced. A discontinuous Galerkin approximation in space is combined and analyzed together with a Petrov-Galerkin scheme in time. The idea of DWR methods is applied to derive a p-adaptive strategy. The full linear system is solved in parallel in space and time by using a multilevel preconditioner. Numerical test validate the efficiency of the method in case of linear transport and Maxwell\u27s equations in 2D

Numerical Optimization of a Waveguide Transition Using Finite Element Beam Propagation

We develop a general convergence analysis for a class of inexact Newton-type regularizations for stably solving nonlinear ill-posed problems. Each of the methods under consideration consists of two components: the outer Newton iteration and an inner regularization scheme which, applied to the linearized system, provides the update. In this paper we give a novel and unified convergence analysis which is not confined to a specific inner regularization scheme but applies to a multitude of schemes including Landweber and steepest decent iterations, iterated Tikhonov method, and method of conjugate gradients

Space-time discontinuous Galerkin discretizations for linear first-order hyperbolic evolution systems

We introduce a space-time discretization for linear first-order hyperbolic evolution systems using a discontinuous Galerkin approximation in space and a Petrov-Galerkin scheme in time. We show well-posedness and convergence of the discrete system. Then we introduce an adaptive strategy based on goal-oriented dual-weighted error estimation. The full space-time linear system is solved with a parallel multilevel preconditioner. Numerical experiments for the linear transport equation and the Maxwell equation in 2D underline the effciency of the overall adaptive solution process

Space-time discontinuous Galerkin discretizations for linear first-order hyperbolic evolution systems. Revised March 2016

We introduce a space-time discretization for linear first-order hyperbolic evolution systems using a discontinuous Galerkin approximation in space and a Petrov-Galerkin scheme in time. We show well-posedness and convergence of the discrete system. Then we introduce an adaptive strategy based on goal-oriented dual-weighted error estimation. The full space-time linear system is solved with a parallel multilevel preconditioner. Numerical experiments for the linear transport equation and the Maxwell equation in 2D underline the effciency of the overall adaptive solution process

Parallel adaptive discontinuous Galerkin discretizations in space and time for linear elastic and acousticwaves

We introduce a space-time discretization for elastic and acoustic waves using a discontinuous Galerkin approximation in space and a Petrov–Galerkin scheme in time. For the dG method, the upwind flux is evaluated by explicitly solving a Riemann problem. Then we show well-posedness and convergence of the discrete system. Based on goal-oriented dualweighted error estimation an adaptive strategy is introduced. The full space-time linear system is solved with a parallel multilevel preconditioner. Numerical experiments for acoustic and elastic waves underline the efficiency of the overall adaptive solution process

Metabolic syndrome predicts vascular changes in whole body magnetic resonance imaging in patients with long standing diabetes mellitus

<p>Abstract</p> <p>Background</p> <p>Although diabetic patients have an increased rate of cardio-vascular events, there is considerable heterogeneity with respect to cardiovascular risk, requiring new approaches to individual cardiovascular risk factor assessment. In this study we used whole body-MR-angiography (WB-MRA) to assess the degree of atherosclerosis in patients with long-standing diabetes and to determine the association between metabolic syndrome (MetS) and atherosclerotic burden.</p> <p>Methods</p> <p>Long standing (≥10 years) type 1 and type 2 diabetic patients (n = 59; 31 males; 63.3 ± 1.7 years) were examined by WB-MRA. Based on the findings in each vessel, we developed an overall score representing the patient's vascular atherosclerotic burden (MRI-score). The score's association with components of the MetS was assessed.</p> <p>Results</p> <p>The median MRI-score was 1.18 [range: 1.00-2.41] and MetS was present in 58% of the cohort (type 2 diabetics: 73%; type 1 diabetics: 26%). Age (p = 0.0002), HDL-cholesterol (p = 0.016), hypertension (p = 0.0008), nephropathy (p = 0.0093), CHD (p = 0.001) and MetS (p = 0.0011) were significantly associated with the score. Adjusted for age and sex, the score was significantly (p = 0.02) higher in diabetics with MetS (1.450 [1.328-1.572]) compared to those without MetS (1.108 [0.966-1.50]). The number of MetS components was associated with a linear increase in the MRI-score (increase in score: 0.09/MetS component; r²= 0.24, p = 0.038). Finally, using an established risk algorithm, we found a significant association between MRI-score and 10-year risk for CHD, fatal CHD and stroke.</p> <p>Conclusion</p> <p>In this high-risk diabetic population, WB-MRA revealed large heterogeneity in the degree of systemic atherosclerosis. Presence and number of traits of the MetS are associated with the extent of atherosclerotic burden. These results support the perspective that diabetic patients are a heterogeneous population with increased but varying prevalence of atherosclerosis and risk.</p

A TNF-Regulated Recombinatorial Macrophage Immune Receptor Implicated in Granuloma Formation in Tuberculosis

Macrophages play a central role in host defense against mycobacterial infection and anti- TNF therapy is associated with granuloma disorganization and reactivation of tuberculosis in humans. Here, we provide evidence for the presence of a T cell receptor (TCR) αβ based recombinatorial immune receptor in subpopulations of human and mouse monocytes and macrophages. In vitro, we find that the macrophage-TCRαβ induces the release of CCL2 and modulates phagocytosis. TNF blockade suppresses macrophage-TCRαβ expression. Infection of macrophages from healthy individuals with mycobacteria triggers formation of clusters that express restricted TCR Vβ repertoires. In vivo, TCRαβ bearing macrophages abundantly accumulate at the inner host-pathogen contact zone of caseous granulomas from patients with lung tuberculosis. In chimeric mouse models, deletion of the variable macrophage-TCRαβ or TNF is associated with structurally compromised granulomas of pulmonary tuberculosis even in the presence of intact T cells. These results uncover a TNF-regulated recombinatorial immune receptor in monocytes/macrophages and demonstrate its implication in granuloma formation in tuberculosis

Massively Parallel RNA Sequencing Identifies a Complex Immune Gene Repertoire in the lophotrochozoan Mytilus edulis

The marine mussel Mytilus edulis and its closely related sister species are distributed world-wide and play an important role in coastal ecology and economy. The diversification in different species and their hybrids, broad ecological distribution, as well as the filter feeding mode of life has made this genus an attractive model to investigate physiological and molecular adaptations and responses to various biotic and abiotic environmental factors. In the present study we investigated the immune system of Mytilus, which may contribute to the ecological plasticity of this species. We generated a large Mytilus transcriptome database from different tissues of immune challenged and stress treated individuals from the Baltic Sea using 454 pyrosequencing. Phylogenetic comparison of orthologous groups of 23 species demonstrated the basal position of lophotrochozoans within protostomes. The investigation of immune related transcripts revealed a complex repertoire of innate recognition receptors and downstream pathway members including transcripts for 27 toll-like receptors and 524 C1q domain containing transcripts. NOD-like receptors on the other hand were absent. We also found evidence for sophisticated TNF, autophagy and apoptosis systems as well as for cytokines. Gill tissue and hemocytes showed highest expression of putative immune related contigs and are promising tissues for further functional studies. Our results partly contrast with findings of a less complex immune repertoire in ecdysozoan and other lophotrochozoan protostomes. We show that bivalves are interesting candidates to investigate the evolution of the immune system from basal metazoans to deuterostomes and protostomes and provide a basis for future molecular work directed to immune system functioning in Mytilus

Probabilistic and Set-based Model Invalidation and Estimation using LMIs

International audienceProbabilistic and set-based methods are two approaches for model invalidation, parameter and state estimation. Both classes of methods use different types of data, \ie deterministic or probabilistic data, which allow different statements and applications. Ideally, however, all available data should be used in estimation and model invalidation methods. This paper presents an estimation and model invalidation framework combining set-based and probabilistically uncertain data for polynomial continuous-time systems. In particular, uncertain data on the moments and the support is used without the need to make explicit assumptions on the type of probability densities. The paper derives pointwise-in-time outer approximations of the moments of the probability densities associated with the states and parameters of the system. These approximations can be interpreted as guaranteed confidence intervals for the moment estimates. Furthermore, guaranteed bounds on the probability masses on subsets are derived and allow an estimation of the unknown probability densities. To calculate the estimates, the dynamics of the probability densities of the state trajectories are found by occupation measures of the nonlinear dynamics. This allows the construction of an infinite-dimensional linear program which incorporates the set- and moment-based data. This linear program is relaxed by a hierarchy of LMI problems providing, as shown elsewhere, an almost uniformly convergent sequence of outer approximations of the estimated sets. The approach is demonstrated with numerical examples