25,417 research outputs found

    Top pair cross section measurements at the LHC

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    The most recent results on the measurements of (tt) production and cross sections at 7 TeV are presented. These are obtained using CMS [1] and ATLAS [2] data collected in 2011. Recent results on the tt production cross section at 8 TeV using 2012 CMS data are also presented. The tt inclusive cross sections are measured in the lepton+jets, dilepton and fully hadronic channels, including the tau-dilepton and tau+jets modes. The results are combined and confronted with precise theory calculations.Comment: Proceedings of CKM 2012, the 7th International Workshop on the CKM Unitarity Triangle, University of Cincinnati, USA, 28 September - 2 October 201

    A Random Force is a Force, of Course, of Coarse: Decomposing Complex Enzyme Kinetics with Surrogate Models

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    The temporal autocorrelation (AC) function associated with monitoring order parameters characterizing conformational fluctuations of an enzyme is analyzed using a collection of surrogate models. The surrogates considered are phenomenological stochastic differential equation (SDE) models. It is demonstrated how an ensemble of such surrogate models, each surrogate being calibrated from a single trajectory, indirectly contains information about unresolved conformational degrees of freedom. This ensemble can be used to construct complex temporal ACs associated with a "non-Markovian" process. The ensemble of surrogates approach allows researchers to consider models more flexible than a mixture of exponentials to describe relaxation times and at the same time gain physical information about the system. The relevance of this type of analysis to matching single-molecule experiments to computer simulations and how more complex stochastic processes can emerge from a mixture of simpler processes is also discussed. The ideas are illustrated on a toy SDE model and on molecular dynamics simulations of the enzyme dihydrofolate reductase.Comment: 11 pages / 6 figure

    Infrastructure and growth in Africa

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    The goal of the paper is to provide a comprehensive assessment of the impact of infrastructure development on growth in African countries. Based on econometric estimates for a sample of 136 countries from 1960-2005, the authors evaluate the impact on per capita growth of faster accumulation of infrastructure stocks and of enhancement in the quality of infrastructure services for 39 African countries in three key infrastructure sectors: telecommunications, electricity, and roads. Using an econometric technique suitable for dynamic panel data models and likely endogenous regressors, the authors find that infrastructure stocks and service quality boost economic growth. The growth payoff of reaching the infrastructure development of the African leader (Mauritius) is 1.1 percent of GDP per year in North Africa and 2.3 percent in Sub-Saharan Africa, with most of the contribution coming from more, rather than better, infrastructure. Across Africa, infrastructure contributed 99 basis points to per capita economic growth, versus 68 points for other structural policies. Most of the contribution came from increases in stocks (89 basis points), versus quality improvements (10 basis points). The findings show that growth is positively affected by the volume of infrastructure stocks and the quality of infrastructure services; simulations show that our empirical findings are significant statistically and economically. Identifying areas of opportunity to generate productivity growth, the authors find that African countries are likely to gain more from larger stocks of infrastructure than from enhancements in the quality of existing infrastructure. The payoffs are largest for telephone density, electricity-generating capacity, road-network length, and road quality.Transport Economics Policy&Planning,Infrastructure Economics,E-Business,Private Participation in Infrastructure,Non Bank Financial Institutions

    Evolution of Communities with Focus on Stability

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    Community detection is an important tool for analyzing the social graph of mobile phone users. The problem of finding communities in static graphs has been widely studied. However, since mobile social networks evolve over time, static graph algorithms are not sufficient. To be useful in practice (e.g. when used by a telecom analyst), the stability of the partitions becomes critical. We tackle this particular use case in this paper: tracking evolution of communities in dynamic scenarios with focus on stability. We propose two modifications to a widely used static community detection algorithm: we introduce fixed nodes and preferential attachment to pre-existing communities. We then describe experiments to study the stability and quality of the resulting partitions on real-world social networks, represented by monthly call graphs for millions of subscribers.Comment: AST at 42nd JAIIO, September 16-20, 2013, Cordoba, Argentina. arXiv admin note: substantial text overlap with arXiv:1311.550
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