986 resultados para Braun, Lily.


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Asthma is a disease in which both genetic and environmental factors play important roles. The farming environment has consistently been associated with protection from childhood asthma and atopy, and interactions have been reported with polymorphisms in innate immunity genes.

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Exposure to farming environments has been shown to protect substantially against asthma and atopic disease across Europe and in other parts of the world. The GABRIEL Advanced Surveys (GABRIELA) were conducted to determine factors in farming environments which are fundamental to protecting against asthma and atopic disease. The GABRIEL Advanced Surveys have a multi-phase stratified design. In a first-screening phase, a comprehensive population-based survey was conducted to assess the prevalence of exposure to farming environments and of asthma and atopic diseases (n = 103,219). The second phase was designed to ascertain detailed exposure to farming environments and to collect biomaterial and environmental samples in a stratified random sample of phase 1 participants (n = 15,255). A third phase was carried out in a further stratified sample only in Bavaria, southern Germany, aiming at in-depth respiratory disease and exposure assessment including extensive environmental sampling (n = 895). Participation rates in phase 1 were around 60% but only about half of the participating study population consented to further study modules in phase 2. We found that consenting behaviour was related to familial allergies, high parental education, wheeze, doctor diagnosed asthma and rhinoconjunctivitis, and to a lesser extent to exposure to farming environments. The association of exposure to farm environments with asthma or rhinoconjunctivitis was not biased by participation or consenting behaviour. The GABRIEL Advanced Surveys are one of the largest studies to shed light on the protective 'farm effect' on asthma and atopic disease. Bias with regard to the main study question was able to be ruled out by representativeness and high participation rates in phases 2 and 3. The GABRIEL Advanced Surveys have created extensive collections of questionnaire data, biomaterial and environmental samples promising new insights into this area of research.

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This Letter presents a measurement of the W+ W- production cross section in sqrt(s) = 7  TeV pp collisions by the ATLAS experiment, using 34  pb(-1) of integrated luminosity produced by the Large Hadron Collider at CERN. Selecting events with two isolated leptons, each either an electron or a muon, 8 candidate events are observed with an expected background of 1.7 ± 0.6 events. The measured cross section is 41(-16)(+20)(stat) ± 5(syst)±1(lumi)  pb, which is consistent with the standard model prediction of 44 ± 3  pb calculated at next-to-leading order in QCD.

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This Letter presents the first search for a heavy particle decaying into an e ± μ(-/+) final state in sqrt[s] = 7 TeV pp collisions at the LHC. The data were recorded by the ATLAS detector during 2010 and correspond to a total integrated luminosity of 35 pb(-1). No excess above the standard model background expectation is observed. Exclusions at 95% confidence level are placed on two representative models. In an R-parity violating supersymmetric model, tau sneutrinos with a mass below 0.75 TeV are excluded, assuming all R-parity violating couplings are zero except λ(311)' = 0.11 and λ312 = 0.07. In a lepton flavor violating model, a Z'-like vector boson with masses of 0.70-1.00 TeV and corresponding cross sections times branching ratios of 0.175-0.183 pb is excluded. These results extend to higher mass R-parity violating sneutrinos and lepton flavor violating Z's than previous constraints from the Tevatron.

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Azimuthal decorrelations between the two central jets with the largest transverse momenta are sensitive to the dynamics of events with multiple jets. We present a measurement of the normalized differential cross section based on the full data set (∫Ldt=36  pb(-1)) acquired by the ATLAS detector during the 2010 sqrt(s)=7  TeV proton-proton run of the LHC. The measured distributions include jets with transverse momenta up to 1.3 TeV, probing perturbative QCD in a high-energy regime.

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This Letter presents the first search for supersymmetry in final states containing one isolated electron or muon, jets, and missing transverse momentum from √s=7  TeV proton-proton collisions at the LHC. The data were recorded by the ATLAS experiment during 2010 and correspond to a total integrated luminosity of 35  pb(-1). No excess above the standard model background expectation is observed. Limits are set on the parameters of the minimal supergravity framework, extending previous limits. Within this framework, for A(0)=0 GeV, tanβ=3, and μ>0 and for equal squark and gluino masses, gluino masses below 700 GeV are excluded at 95% confidence level.

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A search for diphoton events with large missing transverse energy is presented. The data were collected with the ATLAS detector in proton-proton collisions at √s=7 TeV at the CERN Large Hadron Collider and correspond to an integrated luminosity of 3.1 pb⁻¹. No excess of such events is observed above the standard model background prediction. In the context of a specific model with one universal extra dimension with compactification radius R and gravity-induced decays, values of 1/R<729 GeV are excluded at 95% C. L., providing the most sensitive limit on this model to date.

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A search for a heavy standard model Higgs boson decaying via H→ZZ→→ℓ(+)ℓ(-)νν, where ℓ=e, μ, is presented. It is based on proton-proton collision data at √s=7 TeV, collected by the ATLAS experiment at the LHC in the first half of 2011 and corresponding to an integrated luminosity of 1.04 fb(-1). The data are compared to the expected standard model backgrounds. The data and the background expectations are found to be in agreement and upper limits are placed on the Higgs boson production cross section over the entire mass window considered; in particular, the production of a standard model Higgs boson is excluded in the region 340

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This paper examines the accuracy of software-based on-line energy estimation techniques. It evaluates today’s most widespread energy estimation model in order to investigate whether the current methodology of pure software-based energy estimation running on a sensor node itself can indeed reliably and accurately determine its energy consumption - independent of the particular node instance, the traffic load the node is exposed to, or the MAC protocol the node is running. The paper enhances today’s widely used energy estimation model by integrating radio transceiver switches into the model, and proposes a methodology to find the optimal estimation model parameters. It proves by statistical validation with experimental data that the proposed model enhancement and parameter calibration methodology significantly increases the estimation accuracy.

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Our society uses a large diversity of co-existing wired and wireless networks in order to satisfy its communication needs. A cooper- ation between these networks can benefit performance, service availabil- ity and deployment ease, and leads to the emergence of hybrid networks. This position paper focuses on a hybrid mobile-sensor network identify- ing potential advantages and challenges of its use and defining feasible applications. The main value of the paper, however, is in the proposed analysis approach to evaluate the performance at the mobile network side given the mixed mobile-sensor traffic. The approach combines packet- level analysis with modelling of flow-level behaviour and can be applied for the study of various application scenarios. In this paper we consider two applications with distinct traffic models namely multimedia traffic and best-effort traffic.

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With research on Wireless Sensor Networks (WSNs) becoming more and more mature in the past five years, researchers from universities all over the world have set up testbeds of wireless sensor networks, in most cases to test and evaluate the real-world behavior of developed WSN protocol mechanisms. Although these testbeds differ heavily in the employed sensor node types and the general architectural set up, they all have similar requirements with respect to management and scheduling functionalities: as every shared resource, a testbed requires a notion of users, resource reservation features, support for reprogramming and reconfiguration of the nodes, provisions to debug and remotely reset sensor nodes in case of node failures, as well as a solution for collecting and storing experimental data. The TARWIS management architecture presented in this paper targets at providing these functionalities independent from node type and node operating system. TARWIS has been designed as a re-usable management solution for research and/or educational oriented research testbeds of wireless sensor networks, relieving researchers intending to deploy a testbed from the burden to implement their own scheduling and testbed management solutions from scratch.

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Costly on-site node repairs in wireless mesh networks (WMNs) can be required due to misconfiguration, corrupt software updates, or unavailability during updates. We propose ADAM as a novel management framework that guarantees accessibility of individual nodes in these situations. ADAM uses a decentralised distribution mechanism and self-healing mechanisms for safe configuration and software updates. In order to implement the ADAM management and self-healing mechanisms, an easy-to-learn and extendable build system for a small footprint embedded Linux distribution for WMNs has been developed. The paper presents the ADAM concept, the build system for the Linux distribution and the management architecture.