213 research outputs found

    Geldpolitik in der 'Bubble-Economy'

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    Die Aktienkurse eilen derzeit von einem Rekord zum nĂ€chsten. Dieser schon lange anhaltende Höhenflug der Kurse ist mit einem im historischen Vergleich hohen Kurs-Gewinn-VerhĂ€ltnis verbunden. Handelt es sich um eine spekulative Blase? Welche Folgen hĂ€tte ein plötzlicher KursrĂŒckgang fĂŒr die Realwirtschaft? Wann sollte die Geldpolitik eingreifen? --

    GlĂŒcklose Medienfusionen

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    Weltweit verabschieden sich Medienunternehmen von ihrer Strategie eines integrierten Medienkonzerns und verkaufen ihre Beteiligungen. Die Argumente fĂŒr eine Multimedia-Strategie klangen ĂŒberzeugend, sie scheinen aber in der RealitĂ€t nicht gegriffen zu haben. Was ist passiert? --

    Sport im Pay-TV: ein Fall fĂŒr die Medienpolitik?

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    KĂŒrzlich haben die MinisterprĂ€sidenten der LĂ€nder beschlossen, im Rahmen der vierten Novellierung des Rundfunkstaatsvertrages eine Grundversorung bei der Übertragung großer Sportveranstaltungen im freien Fernsehen sicherzustellen. Sind staatliche Eingriffe in diesem Bereich aus ökonomischer Sicht angebracht? --

    A Probabilistic Model for LCF

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    Fatigue life of components or test specimens often exhibit a significant scatter. Furthermore, size effects have a non-negligible influence on fatigue life of parts with different geometries. We present a new probabilistic model for low-cycle fatigue (LCF) in the context of polycrystalline metal. The model takes size effects and inhomogeneous strain fields into account by means of the Poisson point process (PPP). This approach is based on the assumption of independently occurring LCF cracks and the Coffin-Manson-Basquin (CMB) equation. Within the probabilistic model, we give a new and more physical interpretation of the CMB parameters which are in the original approach no material parameters in a strict sense, as they depend on the specimen geometry. Calibration and validation of the proposed model is performed using results of strain controlled LCF tests of specimens with different surface areas. The test specimens are made of the nickel base superalloy RENE 80.Comment: 20 pages, 6 figure

    Probabilistic modeling of LCF failure times using a epidemiological crack percolation model

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    The analysis of standardized low cycle fatigue (LCF) experiments shows that the failure times widely scatter. Furthermore, mechanical components often fail before the deterministic failure time is reached. A possibility to overcome these problems is to consider probabilistic failure times. Our approach for probabilistic life prediction is based on the microstructure of the metal. Since we focus on nickel-base alloys we consider a coarse grained microstructure, with random oriented FCC grains. This leads to random distributed Schmid factors and different anisotropic stress in each grain. To gain crack initiation times, we use Coffin-MansonBasquin and Ramberg-Osgood equation on stresses corrected with probabilistic Schmid factors. Using these single grain crack initiation times, we have developed an epidemiological crack growth model over multiple grains. In this mesoscopic crack percolation model, cracked grains induce a stress increase in neighboring grains. This stress increase is realized using a machine learning model trained on data generated from finite element simulations. The resulting crack clusters are evaluated with a failure criterion based on a multimodal stress intensity factor. From the generated failure times, we calculate surface dependent hazard rates using a Monte Carlo framework. We compare the obtained failure time distributions to data from LCF experiments and find good coincidence of predicted and measured scatter bands

    Paying with Cash – an Outdated Model?

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    Sarcoma classification by DNA methylation profiling

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    Sarcomas are malignant soft tissue and bone tumours affecting adults, adolescents and children. They represent a morphologically heterogeneous class of tumours and some entities lack defining histopathological features. Therefore, the diagnosis of sarcomas is burdened with a high inter-observer variability and misclassification rate. Here, we demonstrate classification of soft tissue and bone tumours using a machine learning classifier algorithm based on array-generated DNA methylation data. This sarcoma classifier is trained using a dataset of 1077 methylation profiles from comprehensively pre-characterized cases comprising 62 tumour methylation classes constituting a broad range of soft tissue and bone sarcoma subtypes across the entire age spectrum. The performance is validated in a cohort of 428 sarcomatous tumours, of which 322 cases were classified by the sarcoma classifier. Our results demonstrate the potential of the DNA methylation-based sarcoma classification for research and future diagnostic applications

    Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

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    A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements
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