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Institution

Technical University of Dortmund

EducationDortmund, Nordrhein-Westfalen, Germany
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: Context (language use) & Large Hadron Collider. The organization has 13028 authors who have published 27666 publications receiving 615557 citations. The organization is also known as: Dortmund University & University of Dortmund.


Papers
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Journal ArticleDOI
TL;DR: A novel approach is presented that fits a restricted class of phase-type distributions, namely, mixtures of Erlang distributions, to trace data and an algorithm of the expectation maximization type is developed, which yields phase- type approximations for a wide range of data traces that are as good or better than approximation computed with other less efficient and less stable fitting methods.
Abstract: The representation of general distributions or measured data by phase-type distributions is an important and nontrivial task in analytical modeling. Although a large number of different methods for fitting parameters of phase-type distributions to data traces exist, many approaches lack efficiency and numerical stability. In this paper, a novel approach is presented that fits a restricted class of phase-type distributions, namely, mixtures of Erlang distributions, to trace data. For the parameter fitting, an algorithm of the expectation maximization type is developed. This paper shows that these choices result in a very efficient and numerically stable approach which yields phase-type approximations for a wide range of data traces that are as good or better than approximations computed with other less efficient and less stable fitting methods. To illustrate the effectiveness of the proposed fitting algorithm, we present comparative results for our approach and two other methods using six benchmark traces and two real traffic traces as well as quantitative results from queuing analysis

194 citations

Journal ArticleDOI
TL;DR: In this paper, various vibrational spectroscopic techniques are applied to comprehensively characterize, on a molecular level, bacteria of the strain Staphylococcus epidermidis, an opportunistic pathogen which has evolved to become a major cause of nosocomial infections.
Abstract: Bacteria are a major cause of infection. To fight disease and growing resistance, research interest is focused on understanding bacterial metabolism. For a detailed evaluation of the involved mechanisms, a precise knowledge of the molecular composition of the bacteria is required. In this article, various vibrational spectroscopic techniques are applied to comprehensively characterize, on a molecular level, bacteria of the strain Staphylococcus epidermidis, an opportunistic pathogen which has evolved to become a major cause of nosocomial infections. IR absorption spectroscopy reflects the overall chemical composition of the cells, with major focus on the protein vibrations. Smaller sample volumes-down to a single cell-are sufficient to probe the overall chemical composition by means of micro-Raman spectroscopy. The nucleic-acid and aromatic amino-acid moieties are almost exclusively explored by UV resonance Raman spectroscopy. In combination with statistical evaluation methods [hierarchical cluster analysis (HCA), principal component analysis (PCA), linear discriminant analysis (LDA)], the protein and nucleic-acid components that change during the different bacterial growth phases can be identified from the in vivo vibrational spectra. Furthermore, tip-enhanced Raman spectroscopy (TERS) provides insight into the surface structures and follows the dynamics of the polysaccharide and peptide components on the bacterial cells with a spatial resolution below the diffraction limit. This might open new ways for the elucidation of host-bacteria and drug-bacteria interactions.

194 citations

Journal ArticleDOI
Roel Aaij1, Gregory Ciezarek, P. Collins1, G. Collazuol  +772 moreInstitutions (55)
TL;DR: Four J/ψϕ structures are observed, each with significance over 5 standard deviations, and the quantum numbers of these structures are determined with significance of at least 4 standard deviations.
Abstract: The first full amplitude analysis of B+→J/ψϕK+ with J/ψ→μ+μ−, ϕ→K+K− decays is performed with a data sample of 3 fb−1 of pp collision data collected at s√=7 and 8 TeV with the LHCb detector. The data cannot be described by a model that contains only excited kaon states decaying into ϕK+, and four J/ψϕ structures are observed, each with significance over 5 standard deviations. The quantum numbers of these structures are determined with significance of at least 4 standard deviations. The lightest is best described as a D±sD∗∓s cusp, but a resonant interpretation is also possible with mass consistent with, but width much larger than, previous measurements of the claimed X(4140) state.

194 citations

Journal ArticleDOI
TL;DR: Light is shed on the continuum modeling of growth and remodeling of living matter, and a state-of-the-art review of current research highlights is provided, and challenges and potential future directions are discussed.

194 citations

Journal ArticleDOI
TL;DR: In this article, the carbon-13 NMR spectra of 49 organotin compounds have been recorded and analysed, and large variations are observed for the coupling constant 1 J( 119 Sn-13 C, which, for the compounds investigated, lies between 240 and 1120 Hz.

193 citations


Authors

Showing all 13240 results

NameH-indexPapersCitations
Hermann Kolanoski145127996152
Marc Besancon1431799106869
Kerstin Borras133134192173
Emmerich Kneringer129102180898
Achim Geiser129133184136
Valerio Vercesi12993779519
Jens Weingarten12889674667
Giuseppe Mornacchi12789475830
Kevin Kroeninger12683670010
Daniel Muenstermann12688570855
Reiner Klingenberg12673370069
Claus Gössling12677571975
Diane Cinca12682270126
Frank Meier12467764889
Daniel Dobos12467967434
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023131
2022306
20211,694
20201,773
20191,653
20181,579