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Institution

University of Tübingen

EducationTübingen, Germany
About: University of Tübingen is a education organization based out in Tübingen, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 40555 authors who have published 84108 publications receiving 3015320 citations. The organization is also known as: Eberhard Karls University & Eberhard-Karls-Universität Tübingen.


Papers
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Journal ArticleDOI
TL;DR: A survey on the current status and future prospects in research and development of SnO2-based sensors is given in this paper, where the influence of contact geometry and crystallinity on the sensor response signal is outlined.
Abstract: A survey is given on the current status and future prospects in research and development of SnO2-based sensors. Atomistic models of molecular recognition are discussed first. They include physisorption, chemisorption, surface reaction, catalytic reaction, grain boundary reaction, bulk reaction and three-phase boundary reaction steps. The influence of contact geometry and crystallinity on the sensor response signal is outlined. A brief summary is given of the current status of sensor research and development with emphasis on ceramic, thick-film and thin-film sensors based on crystalline, polycrystalline and nanocrystalline SnO2. Three different aspects are mentioned in the outline which are expected to lead to significantly improved performances of future sensors: the improved selectivity through the modulation frequency in a.c. measurements, the improved stability through the better control of structures, and the improved selectivity and drift compensation through pattern recognition.

891 citations

Journal ArticleDOI
13 Jun 2003-Cell
TL;DR: Evidence is presented that apoptotic cells secrete chemotactic factor(s) that stimulate the attraction of monocytic cells and primary macrophages and that lysophosphatidylcholine was released from apoptotic Cells due to the caspase-3 mediated activation of the calcium-independent phospholipase A(2).

890 citations

Journal ArticleDOI
TL;DR: In this paper, finite element Galerkin schemes for a number of linear model problems in electromagnetism were discussed, and the finite element schemes were introduced as discrete differential forms, matching the coordinate-independent statement of Maxwell's equations in the calculus of differential forms.
Abstract: This article discusses finite element Galerkin schemes for a number of linear model problems in electromagnetism. The finite element schemes are introduced as discrete differential forms, matching the coordinate-independent statement of Maxwell's equations in the calculus of differential forms. The asymptotic convergence of discrete solutions is investigated theoretically. As discrete differential forms represent a genuine generalization of conventional Lagrangian finite elements, the analysis is based upon a judicious adaptation of established techniques in the theory of finite elements. Risks and difficulties haunting finite element schemes that do not fit the framework of discrete differential forms are highlighted.

890 citations

Posted Content
TL;DR: This work shows that failure to converge typically is not due to a suboptimal estimation algorithm, but is a consequence of attempting to fit a model that is too complex to be properly supported by the data, irrespective of whether estimation is based on maximum likelihood or on Bayesian hierarchical modeling with uninformative or weakly informative priors.
Abstract: The analysis of experimental data with mixed-effects models requires decisions about the specification of the appropriate random-effects structure. Recently, Barr, Levy, Scheepers, and Tily, 2013 recommended fitting `maximal' models with all possible random effect components included. Estimation of maximal models, however, may not converge. We show that failure to converge typically is not due to a suboptimal estimation algorithm, but is a consequence of attempting to fit a model that is too complex to be properly supported by the data, irrespective of whether estimation is based on maximum likelihood or on Bayesian hierarchical modeling with uninformative or weakly informative priors. Importantly, even under convergence, overparameterization may lead to uninterpretable models. We provide diagnostic tools for detecting overparameterization and guiding model simplification.

889 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present new analytical data of major and trace elements for the geological MPI-DING glasses KL2-G, ML3B-G and ATHO-G.
Abstract: We present new analytical data of major and trace elements for the geological MPI-DING glasses KL2-G, ML3B-G, StHs6/80-G, GOR128-G, GOR132-G, BM90/21-G, T1-G, and ATHO-G. Different analytical methods were used to obtain a large spectrum of major and trace element data, in particular, EPMA, SIMS, LA-ICPMS, and isotope dilution by TIMS and ICPMS. Altogether, more than 60 qualified geochemical laboratories worldwide contributed to the analyses, allowing us to present new reference and information values and their uncertainties (at 95% confidence level) for up to 74 elements. We complied with the recommendations for the certification of geological reference materials by the International Association of Geoanalysts (IAG). The reference values were derived from the results of 16 independent techniques, including definitive (isotope dilution) and comparative bulk (e.g., INAA, ICPMS, SSMS) and microanalytical (e.g., LA-ICPMS, SIMS, EPMA) methods. Agreement between two or more independent methods and the use of definitive methods provided traceability to the fullest extent possible. We also present new and recently published data for the isotopic compositions of H, B, Li, O, Ca, Sr, Nd, Hf, and Pb. The results were mainly obtained by high-precision bulk techniques, such as TIMS and MC-ICPMS. In addition, LA-ICPMS and SIMS isotope data of B, Li, and Pb are presented.

889 citations


Authors

Showing all 41039 results

NameH-indexPapersCitations
John Q. Trojanowski2261467213948
Lily Yeh Jan16246773655
Monique M.B. Breteler15954693762
Wolfgang Wagner1562342123391
Thomas Meitinger155716108491
Hermann Brenner1511765145655
Amartya Sen149689141907
Bernhard Schölkopf1481092149492
Niels Birbaumer14283577853
Detlef Weigel14251684670
Peter Lang140113698592
Marco Colonna13951271166
António Amorim136147796519
Alexis Brice13587083466
Elias Campo13576185160
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023206
2022854
20214,700
20204,480
20194,045
20183,634