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Institution

University of Duisburg-Essen

EducationEssen, Nordrhein-Westfalen, Germany
About: University of Duisburg-Essen is a education organization based out in Essen, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 16072 authors who have published 39972 publications receiving 1109199 citations.


Papers
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Journal ArticleDOI
TL;DR: In this review potential alterations with focus on N-glycosylation of mAbs and Fc fusion proteins and the possible effects on the pharmacokinetics are reviewed and the current understandings of the underlying mechanisms are described.

266 citations

Journal ArticleDOI
TL;DR: An overview on recent development of spacecraft attitude FTC system design is presented, and a brief review of some open problems in the general area of spacecraft attitudes control design subject to components faults/failures is concluded.
Abstract: Motivated by several accidents, attitude control of a spacecraft subject to faults/failures has gained considerable attention in a wider range of aerospace engineering and academic communities. This paper is concerned with industrial practices and theoretical approaches for fault tolerant control (FTC) and fault detection and diagnosis (FDD) in spacecraft attitude control system. An overview on recent development of spacecraft attitude FTC system design is presented. The basis of a FTC system is introduced. The existing engineering FTC techniques and theoretical methodologies, including their advantages and disadvantages, are discussed. Moreover, closely associated with the reliability-relevant issues, recent progress in attitude FTC design strategies is reviewed. A brief review of some open problems in the general area of spacecraft attitude control design subject to components faults/failures is further concluded.

266 citations

Journal ArticleDOI
TL;DR: In this paper, absolute atomic oxygen density measurements by two-photon absorption laser-induced fluorescence (TALIF) spectroscopy in the jet effluent were performed with the aid of a comparative TALIF measurement with xenon.
Abstract: The atmospheric pressure plasma jet is a capacitively coupled radio frequency discharge (13.56 MHz) running with a high helium flux (2 m3 h−1) between concentric electrodes. Small amounts (0.5%) of admixed molecular oxygen do not disturb the homogeneous plasma discharge. The jet effluent leaving the discharge through the ring-shaped nozzle contains high concentrations of radicals at a low gas temperature—the key property for a variety of applications aiming at treatment of thermally sensitive surfaces. We report on absolute atomic oxygen density measurements by two-photon absorption laser-induced fluorescence (TALIF) spectroscopy in the jet effluent. Calibration is performed with the aid of a comparative TALIF measurement with xenon. An excitation scheme (different from the one earlier published) providing spectral matching of both the two-photon resonances and the fluorescence transitions is applied.

265 citations

Proceedings ArticleDOI
27 Aug 2017
TL;DR: This paper extends Recurrent Neural Networks by considering unique characteristics of the Recommender Systems domain and shows how individual users can be represented in addition to sequences of consumed items in a new type of Gated Recurrent Unit to effectively produce personalized next item recommendations.
Abstract: Recurrent Neural Networks are powerful tools for modeling sequences. They are flexibly extensible and can incorporate various kinds of information including temporal order. These properties make them well suited for generating sequential recommendations. In this paper, we extend Recurrent Neural Networks by considering unique characteristics of the Recommender Systems domain. One of these characteristics is the explicit notion of the user recommendations are specifically generated for. We show how individual users can be represented in addition to sequences of consumed items in a new type of Gated Recurrent Unit to effectively produce personalized next item recommendations. Offline experiments on two real-world datasets indicate that our extensions clearly improve objective performance when compared to state-of-the-art recommender algorithms and to a conventional Recurrent Neural Network.

265 citations

Journal ArticleDOI
TL;DR: Recommendations for pathology and molecular biomarkers in relation to the diagnosis of lung cancer, primarily non-small-cell carcinomas are focused on.

265 citations


Authors

Showing all 16364 results

NameH-indexPapersCitations
Rui Zhang1512625107917
Olli T. Raitakari1421232103487
Anders Hamsten13961188144
Robert Huber13967173557
Christopher T. Walsh13981974314
Patrick D. McGorry137109772092
Stanley Nattel13277865700
Luis M. Liz-Marzán13261661684
Dirk Schadendorf1271017105777
William Wijns12775295517
Raimund Erbel125136474179
Khalil Amine11865250111
Hans-Christoph Diener118102591710
Bruce A.J. Ponder11640354796
Andre Franke11568255481
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023117
2022496
20213,694
20203,449
20193,155
20182,761