Technical University of Dortmund

About: Technical University of Dortmund is a education organization based out in Dortmund, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Large Hadron Collider & Neutrino. The organization has 13028 authors who have published 27666 publications receiving 615557 citations. The organization is also known as: Dortmund University & University of Dortmund.

Predictors of teachers' use of ICT in school --- the relevance of school characteristics, teachers' attitudes and teacher collaboration

Abstract: This paper is based on the research question of what predictors (school characteristics, teachers' attitudes, teacher collaboration and background characteristics) determine secondary school teachers' frequency of computer use in class. The use of new technologies by secondary school teachers for educational purposes is an important factor regarding school and teaching processes. The use of digital media in schools is, among other things, associated with the goal of supporting learning processes and improving the quality of education. This contribution identifies relevant factors by means of multiple regression analyses of the teachers' frequency of computer use for instruction in five countries (the Netherlands, Denmark, Australia, Poland and Germany) to get an idea of how to support the frequency of the use of computers in class. The analyses and findings are based on the International Association for the Evaluation of Educational Achievement (IEA) study of International Computer and Information Literacy Study 2013 (ICILS), which investigates the computer and information literacy (CIL) of secondary school students and the contexts in which students develop CIL in 21 countries. Antecedents concerning school characteristics, teachers' attitudes and teacher collaboration on the process level and background characteristics of secondary school teachers (N = 8.920) are examined in order to gain further insight into the nature and effect of predictors for secondary school teachers' in-class use of information and communications technology. The analyses show that there are more country-specific results than similarities between the countries selected. In all countries, antecedents concerning teachers' attitudes are more relevant for teachers' in-class use of computers than school characteristics or teacher collaboration on the process level.

Deep Graph Matching Consensus

Abstract: This work presents a two-stage neural architecture for learning and refining structural correspondences between graphs. First, we use localized node embeddings computed by a graph neural network to obtain an initial ranking of soft correspondences between nodes. Secondly, we employ synchronous message passing networks to iteratively re-rank the soft correspondences to reach a matching consensus in local neighborhoods between graphs. We show, theoretically and empirically, that our message passing scheme computes a well-founded measure of consensus for corresponding neighborhoods, which is then used to guide the iterative re-ranking process. Our purely local and sparsity-aware architecture scales well to large, real-world inputs while still being able to recover global correspondences consistently. We demonstrate the practical effectiveness of our method on real-world tasks from the fields of computer vision and entity alignment between knowledge graphs, on which we improve upon the current state-of-the-art.

Scaling of decoherence in wide NMR quantum registers.

Abstract: Among the most important parameters for the usefulness of quantum computers are the size of the quantum register and the decoherence time for the quantum information. The decoherence time is expected to get shorter with the number of correlated qubits, but experimental data are only available for small numbers of qubits. Solid-state nuclear magnetic resonance allows one to correlate large numbers of qubits (several hundred) and measure their decoherence rates. We use a modified magnetic dipole-dipole interaction to correlate the proton spins in a solid sample and observe the decay of the resulting highly correlated states. By systematically varying the number of correlated spins, we measure the increase of the decoherence rate with the size of the quantum register.

Ruthenium-catalyzed olefin metathesis double-bond isomerization sequence.

Abstract: A novel ruthenium-catalyzed tandem ring-closing metathesis (RCM) double-bond isomerization reaction is described in this paper. The utility of this method for the efficient syntheses of five-, six-, and seven-membered cyclic enol ethers is demonstrated. It relies on the conversion of a metathesis-active ruthenium carbene species to an isomerization-active ruthenium−hydride species in situ. This conversion is achieved by using various additives. Scope and limitations of the different protocols are discussed, and some mechanistic considerations based on 31P and 1H NMR spectroscopic studies are presented.