1,567 research outputs found

    Scale invariant Green-Kubo relation for time averaged diffusivity

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    In recent years it was shown both theoretically and experimentally that in certain systems exhibiting anomalous diffusion the time and ensemble average mean squared displacement are remarkably different. The ensemble average diffusivity is obtained from a scaling Green-Kubo relation, which connects the scale invariant non-stationary velocity correlation function with the transport coefficient. Here we obtain the relation between time averaged diffusivity, usually recorded in single particle tracking experiments, and the underlying scale invariant velocity correlation function. The time averaged mean squared displacement is given by δ22DνtβΔνβ\overline{\delta^2} \sim 2 D_\nu t^{\beta}\Delta^{\nu-\beta} where tt is the total measurement time and Δ\Delta the lag time. Here ν>1\nu>1 is the anomalous diffusion exponent obtained from ensemble averaged measurements x2tν\langle x^2 \rangle \sim t^\nu while β1\beta\ge -1 marks the growth or decline of the kinetic energy v2tβ\langle v^2 \rangle \sim t^\beta. Thus we establish a connection between exponents which can be read off the asymptotic properties of the velocity correlation function and similarly for the transport constant DνD_\nu. We demonstrate our results with non-stationary scale invariant stochastic and deterministic models, thereby highlighting that systems with equivalent behavior in the ensemble average can differ strongly in their time average. This is the case, for example, if averaged kinetic energy is finite, i.e. β=0\beta=0, where δ2x2\langle \overline{\delta^2}\rangle \neq \langle x^2\rangle

    Firm Heterogeneity and Choice of Ownership Structure: An Empirical Analysis of German FDI in India

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    We contribute to the literature on the heterogeneity of multinational enterprises (MNEs) and the relevance of firm characteristics for analyzing the determinants of outward foreign direct investment (FDI). The focus is on the role of firm-level heterogeneity when MNEs decide on the share of ownership in foreign affiliates. We combine two firm-specific datasets on German MNEs with varying equity stakes in Indian affiliates. The impact of firm characteristics on ownership shares is assessed in the context of OLS and fractional logit models, controlling for industry and location characteristics. We show that the effect of several characteristics differs between the establishment of new affiliates by German MNEs and their engagement in already existing Indian firms. Most notably, the productivity of the German parents matters only for ownership shares in new affiliates.multinational enterprises, firm characteristics, Indian locations, German FDI; ownership share

    Anomalous diffusion and the Moses effect in a model of aging

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    We decompose the anomalous diffusive behavior found in a model of aging into its fundamental constitutive causes. The model process is a sum of increments that are iterates of a chaotic dynamical system, the Pomeau-Manneville map. The increments can have long-time correlations, fat-tailed distributions and be non-stationary. Each of these properties can cause anomalous diffusion through what is known as the Joseph, Noah and Moses effects, respectively. The model can have either sub- or super-diffusive behavior, which we find is generally due to a combination of the three effects. Scaling exponents quantifying each of the three constitutive effects are calculated using analytic methods and confirmed with numerical simulations. They are then related to the scaling of the distribution of the process through a scaling relation. Finally, the importance of the Moses effect in the anomalous diffusion of experimental systems is discussed.Comment: This is an author-created, un-copyedited version of an article accepted for publication in the New Journal of Physics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at https://doi.org/10.1088/1367-2630/aaeea

    A Markov Chain Model Checker

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    Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branching) temporal logic formula has been proposed for both the discrete [17,6] and the continuous time setting [4,8]. In this paper, we describe a prototype model checker for discrete and continuous-time Markov chains, the Erlangen Twente Markov Chain Checker (EMC2(E \vdash MC^2), where properties are expressed in appropriate extensions of CTL. We illustrate the general bene ts of this approach and discuss the structure of the tool. Furthermore we report on first successful applications of the tool to non-trivial examples, highlighting lessons learned during development and application of (EMC2(E \vdash MC^2)

    A simple decomposition of European temperature variability capturing the variance from days to a decade

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    We analyze European temperature variability from station data with the method of detrended fluctuation analysis. This method is known to give a scaling exponent indicating long range correlations in time for temperature anomalies. However, by a more careful look at the fluctuation function we are able to explain the emergent scaling behaviour by short time relaxation, the yearly cycle and one additional process. It turns out that for many stations this interannual variability is an oscillatory mode with a period length of approximately 7-8 years, which is consistent with results of other methods. We discuss the spatial patterns in all parameters and validate the finding of the 7-8 year period by comparing stations with and without this mode

    Chromosomal Aberrations Associated with Clonal Evolution and Leukemic Transformation in Fanconi Anemia: Clinical and Biological Implications

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    Fanconi anaemia (FA) is an inherited disease with congenital and developmental abnormalities, bone marrow failure, and extreme risk of leukemic transformation. Bone marrow surveillance is an important part of the clinical management of FA and often reveals cytogenetic aberrations. Here, we review bone marrow findings in FA and discuss the clinical and biological implications of chromosomal aberrations associated with leukemic transformation

    Model Unspecific Search in CMS

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    We present the results of a model independent analysis, which systematically scans the data taken by CMS for deviations from the Standard Model predictions. Due to the minimal theoretical bias this approach is sensitive to a variety of models for new physics. Events with at least one electron or muon are classified according to their content of reconstructed objects (muons, electrons, photons, jets and missing transverse energy). A broad scan of three kinematic distributions in those classes is performed by identifying deviations from Standard Model expectations, accounting for systematic uncertainties.Comment: Presented at the 2011 Hadron Collider Physics symposium (HCP-2011), Paris, France, November 14-18 2011, 2 pages, 3 figur

    Performance gains in an ESM using parallel ad-hoc file systems

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    Earth System Models (ESM) got much more demanding over the last years. Modelled processes got more complex and more and more processes are considered in models. In addition resolutions of the models got higher to improve weather and climate forecasts. This requires faster high performance computers (HPC) and better I/O performance. Within our Pilot Lab Exascale Earth System Modelling (PL-EESM) we do performance analysis of the ESM EMAC using a standard Lustre file system for output and compare it to the performance using a parallel ad-hoc overlay file system. We will show the impact for two scenarios: one for todays standard amount of output and one with artificial heavy output simulating future ESMs. An ad-hoc file system is a private parallel file system which is created on-demand for an HPC job using the node-local storage devices, in our case solid-state-disks (SSD). It only exists during the runtime of the job. Therefore output data have to be moved to a permanent file system before the job has finished. Quasi in-situ data analysis and post-processing allows to gain performance as it might result in a decreased amount of data which you have to store - saving disk space and time during the transfer of data to permanent storage. We will show first tests for quasi in-situ post-processing
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