A multigrid perspective on the parallel full approximation scheme in space and time

For the numerical solution of time-dependent partial differential equations, time-parallel methods have recently shown to provide a promising way to extend prevailing strong-scaling limits of numerical codes. One of the most complex methods in this field is the "Parallel Full Approximation Scheme in Space and Time" (PFASST). PFASST already shows promising results for many use cases and many more is work in progress. However, a solid and reliable mathematical foundation is still missing. We show that under certain assumptions the PFASST algorithm can be conveniently and rigorously described as a multigrid-in-time method. Following this equivalence, first steps towards a comprehensive analysis of PFASST using block-wise local Fourier analysis are taken. The theoretical results are applied to examples of diffusive and advective type

Laudatio: Alphabetisierung als Aufgabenfeld der Medienpädagogik

Laudatio zur Verleihung des Promotionspreises der Sektion Medienpädagogik in der Deutschen Gesellschaft für Erziehungswissenschaft am 21.9.2017 in Magdeburg. Koppel, Ilka. 2017. Entwicklung einer Online-Diagnostik für die Alphabetisierung. Eine Design-Based Research-Studie. Wiesbaden: Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-15769-2

All-electrical measurement of spin injection in a magnetic pp-nn junction diode

Magnetic $p$-$n$ junction diodes are fabricated to investigate spin-polarized electron transport. The injection of spin-polarized electrons in a semiconductor is achieved by driving a current from a ferromagnetic injector (Fe), into a bulk semiconductor ($n$-GaAs) via schottky contact. For detection, a diluted magnetic semiconductor ($p$-GaMnAs) layer is used. Clear magnetoresistance was observed only when a high forward bias was applied across the $p$-$n$ junction.Comment: 4 pages, 4 figure

Numerical upscaling of parametric microstructures in a possibilistic uncertainty framework with tensor trains

A fuzzy arithmetic framework for the efficient possibilistic propagation of shape uncertainties based on a novel fuzzy edge detection method is introduced. The shape uncertainties stem from a blurred image that encodes the distribution of two phases in a composite material. The proposed framework employs computational homogenisation to upscale the shape uncertainty to a effective material with fuzzy material properties. For this, many samples of a linear elasticity problem have to be computed, which is significantly sped up by a highly accurate low-rank tensor surrogate. To ensure the continuity of the underlying mapping from shape parametrisation to the upscaled material behaviour, a diffeomorphism is constructed by generating an appropriate family of meshes via transformation of a reference mesh. The shape uncertainty is then propagated to measure the distance of the upscaled material to the isotropic and orthotropic material class. Finally, the fuzzy effective material is used to compute bounds for the average displacement of a non-homogenized material with uncertain star-shaped inclusion shapes

Low rank surrogates for polymorphic fields with application to fuzzy-stochastic partial differential equations

We consider a general form of fuzzy-stochastic PDEs depending on the interaction of probabilistic and non-probabilistic ("possibilistic") influences. Such a combined modelling of aleatoric and epistemic uncertainties for instance can be applied beneficially in an engineering context for real-world applications, where probabilistic modelling and expert knowledge has to be accounted for. We examine existence and well-definedness of polymorphic PDEs in appropriate function spaces. The fuzzy-stochastic dependence is described in a high-dimensional parameter space, thus easily leading to an exponential complexity in practical computations. To aleviate this severe obstacle in practise, a compressed low-rank approximation of the problem formulation and the solution is derived. This is based on the Hierarchical Tucker format which is constructed with solution samples by a non-intrusive tensor reconstruction algorithm. The performance of the proposed model order reduction approach is demonstrated with two examples. One of these is the ubiquitous groundwater flow model with Karhunen-Loeve coefficient field which is generalized by a fuzzy correlation length

Low rank surrogates for polymorphic fields with application to fuzzy-stochastic partial differential equations

We consider a general form of fuzzy-stochastic PDEs depending on the interaction of probabilistic and non-probabilistic ("possibilistic") influences. Such a combined modelling of aleatoric and epistemic uncertainties for instance can be applied beneficially in an engineering context for real-world applications, where probabilistic modelling and expert knowledge has to be accounted for. We examine existence and well-definedness of polymorphic PDEs in appropriate function spaces. The fuzzy-stochastic dependence is described in a high-dimensional parameter space, thus easily leading to an exponential complexity in practical computations. To aleviate this severe obstacle in practise, a compressed low-rank approximation of the problem formulation and the solution is derived. This is based on the Hierarchical Tucker format which is constructed with solution samples by a non-intrusive tensor reconstruction algorithm. The performance of the proposed model order reduction approach is demonstrated with two examples. One of these is the ubiquitous groundwater flow model with Karhunen-Loeve coefficient field which is generalized by a fuzzy correlation length

The Contribution of Trade to Wage Inequality: The Role of Skill, Gender, and Nationality

International trade has been cited as a source of widening wage inequality in industrial nations. Consistent with this claim, we find a significant export wage premium for high-skilled workers in German manufacturing and an export wage discount for lower skilled workers, using matched employer-employee data. Estimates suggest that the export wage premium to high-skilled workers represents up to one third of their overall skill premium. But, while an increase in exports increases wage inequality along the dimension of skill, it diminishes the wage inequality associated with both gender and nationality. In this way, trade contributes to narrowing wage gaps and mitigating wage inequality in German manufacturing.

Design of dual ligands using excessive pharmacophore query alignment : from 7th German Conference on Chemoinformatics: 25 CIC-Workshop Goslar, Germany, 6 - 8 November 2011

Dual- or multi-target ligands have gained increased attention in the past years due to several advantages, including more simple pharmacokinetic and phamarcodynamic properties compared to a combined application of several drugs. Furthermore multi-target ligands often possess improved efficacy. We present a new approach for the discovery of dual-target ligands using aligned pharmacophore models combined with a shape-based scoring. Starting with two sets of known active compounds for each target, a number of different pharmacophore models is generated and subjected to pairwise graph-based alignment using the Kabsch-Algorithm. Since a compound may be able to bind to different targets in different conformations, the algorithm aligns pairs of pharmacophore models sharing the same features which are not necessarily at the exactly same spatial distance. Using the aligned models, a pharmacophore search on a multi-conformation-database is performed to find compounds matching both models. The potentially “dual” ligands are scored by a shape-based comparison with the known active molecules using ShaEP. Using this approach, we performed a prospective fragment-based virtual screening for dual 5-LO/sEH inhibitors. Both enzymes play an important role in the arachidonic acid cascade and are involved in inflammatory processes, pain, cardiovascular diseases and allergic reactions. Beside several new selective inhibitors we were able to find a compound inhibiting both enzymes in low micromolar concentrations. The results indicate that the idea of aligned pharmacophore models can be successfully employed for the discovery of dual-target ligands