35 research outputs found

    Non-heat related impacts of climate change on working populations

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    Environmental and social changes associated with climate change are likely to have impacts on the well-being, health, and productivity of many working populations across the globe. The ramifications of climate change for working populations are not restricted to increases in heat exposure. Other significant risks to worker health (including physical hazards from extreme weather events, infectious diseases, under-nutrition, and mental stresses) may be amplified by future climate change, and these may have substantial impacts at all scales of economic activity. Some of these risks are difficult to quantify, but pose a substantial threat to the viability and sustainability of some working populations. These impacts may occur in both developed and developing countries, although the latter category is likely to bear the heaviest burden

    Search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks in proton-proton collisions at root s=13TeV

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    A search for dark matter produced in association with a Higgs boson decaying to a pair of bottom quarks is performed in proton-proton collisions at a center-of-mass energy of 13 TeV collected with the CMS detector at the LHC. The analyzed data sample corresponds to an integrated luminosity of 35.9 fb(-1). The signal is characterized by a large missing transverse momentum recoiling against a bottom quark-antiquark system that has a large Lorentz boost. The number of events observed in the data is consistent with the standard model background prediction. Results are interpreted in terms of limits both on parameters of the type-2 two-Higgs doublet model extended by an additional light pseudoscalar boson a (2HDM+a) and on parameters of a baryonic Z simplified model. The 2HDM+a model is tested experimentally for the first time. For the baryonic Z model, the presented results constitute the most stringent constraints to date.Peer reviewe

    A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

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    We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ÂŻ

    Search for dark matter produced in association with a leptonically decaying Z boson in proton–proton collisions at s√=13TeV

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    A search for dark matter particles is performed using events with a Z boson candidate and large missing transverse momentum. The analysis is based on proton–proton collision data at a center-of-mass energy of 13TeV, collected by the CMS experiment at the LHC in 2016–2018, corresponding to an integrated luminosity of 137fb−1. The search uses the decay channels Z→ee and Z→ΌΌ. No significant excess of events is observed over the background expected from the standard model. Limits are set on dark matter particle production in the context of simplified models with vector, axial-vector, scalar, and pseudoscalar mediators, as well as on a two-Higgs-doublet model with an additional pseudoscalar mediator. In addition, limits are provided for spin-dependent and spin-independent scattering cross sections and are compared to those from direct-detection experiments. The results are also interpreted in the context of models of invisible Higgs boson decays, unparticles, and large extra dimensions.SCOAP
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