461 research outputs found

    Search For Heavy Pointlike Dirac Monopoles

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    We have searched for central production of a pair of photons with high transverse energies in ppˉp\bar p collisions at s=1.8\sqrt{s} = 1.8 TeV using 70pb170 pb^{-1} of data collected with the D\O detector at the Fermilab Tevatron in 1994--1996. If they exist, virtual heavy pointlike Dirac monopoles could rescatter pairs of nearly real photons into this final state via a box diagram. We observe no excess of events above background, and set lower 95% C.L. limits of 610,870,or1580GeV/c2610, 870, or 1580 GeV/c^2 on the mass of a spin 0, 1/2, or 1 Dirac monopole.Comment: 12 pages, 4 figure

    Search for High Mass Photon Pairs in p-pbar --> gamma-gamma-jet-jet Events at sqrt(s)=1.8 TeV

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    A search has been carried out for events in the channel p-barp --> gamma gamma jet jet. Such a signature can characterize the production of a non-standard Higgs boson together with a W or Z boson. We refer to this non-standard Higgs, having standard model couplings to vector bosons but no coupling to fermions, as a "bosonic Higgs." With the requirement of two high transverse energy photons and two jets, the diphoton mass (m(gamma gamma)) distribution is consistent with expected background. A 90(95)% C.L. upper limit on the cross section as a function of mass is calculated, ranging from 0.60(0.80) pb for m(gamma gamma) = 65 GeV/c^2 to 0.26(0.34) pb for m(gamma gamma) = 150 GeV/c^2, corresponding to a 95% C.L. lower limit on the mass of a bosonic Higgs of 78.5 GeV/c^2.Comment: 9 pages, 3 figures. Replacement has new H->gamma gamma branching ratios and corresponding new mass limit

    Probabilistic machine learning and artificial intelligence.

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    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract

    Limits on WWZ and WW\gamma couplings from p\bar{p}\to e\nu jj X events at \sqrt{s} = 1.8 TeV

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    We present limits on anomalous WWZ and WW-gamma couplings from a search for WW and WZ production in p-bar p collisions at sqrt(s)=1.8 TeV. We use p-bar p -> e-nu jjX events recorded with the D0 detector at the Fermilab Tevatron Collider during the 1992-1995 run. The data sample corresponds to an integrated luminosity of 96.0+-5.1 pb^(-1). Assuming identical WWZ and WW-gamma coupling parameters, the 95% CL limits on the CP-conserving couplings are -0.33<lambda<0.36 (Delta-kappa=0) and -0.43<Delta-kappa<0.59 (lambda=0), for a form factor scale Lambda = 2.0 TeV. Limits based on other assumptions are also presented.Comment: 11 pages, 2 figures, 2 table

    The Dijet Mass Spectrum and a Search for Quark Compositeness in bar{p}p Collisions at sqrt{s} = 1.8 TeV

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    Using the DZero detector at the 1.8 TeV pbarp Fermilab Tevatron collider, we have measured the inclusive dijet mass spectrum in the central pseudorapidity region |eta_jet| < 1.0 for dijet masses greater than 200 Gev/c^2. We have also measured the ratio of spectra sigma(|eta_jet| < 0.5)/sigma(0.5 < |eta_jet| < 1.0). The order alpha_s^3 QCD predictions are in good agreement with the data and we rule out models of quark compositeness with a contact interaction scale < 2.4 TeV at the 95% confidence level.Comment: 11 pages, 4 figures, 2 tables, submitted to Phys. Rev. Let

    Zgamma Production in pbarp Collisions at sqrt(s)=1.8 TeV and Limits on Anomalous ZZgamma and Zgammagamma Couplings

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    We present a study of Z +gamma + X production in p-bar p collisions at sqrt{S}=1.8 TeV from 97 (87) pb^{-1} of data collected in the eegamma (mumugamma) decay channel with the D0 detector at Fermilab. The event yield and kinematic characteristics are consistent with the Standard Model predictions. We obtain limits on anomalous ZZgamma and Zgammagamma couplings for form factor scales Lambda = 500 GeV and Lambda = 750 GeV. Combining this analysis with our previous results yields 95% CL limits |h{Z}_{30}| < 0.36, |h{Z}_{40}| < 0.05, |h{gamma}_{30}| < 0.37, and |h{gamma}_{40}| < 0.05 for a form factor scale Lambda=750 GeV.Comment: 17 Pages including 2 Figures. Submitted to PR

    A Measurement of the W Boson Mass

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    We report a measurement of the W boson mass based on an integrated luminosity of 82 pb1^{-1} from \ppbar collisions at s=1.8\sqrt{s}=1.8 TeV recorded in 1994--1995 by the \Dzero detector at the Fermilab Tevatron. We identify W bosons by their decays to eνe\nu and extract the mass by fitting the transverse mass spectrum from 28,323 W boson candidates. A sample of 3,563 dielectron events, mostly due to Z to ee decays, constrains models of W boson production and the detector. We measure \mw=80.44\pm0.10(stat)\pm0.07(syst)~GeV. By combining this measurement with our result from the 1992--1993 data set, we obtain \mw=80.43\pm0.11 GeV.Comment: 11 pages, 5 figure

    Factors influencing gastrointestinal tract and microbiota immune interaction in preterm infants

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    The role of microbial colonization is indispensable for keeping a balanced immune response in life. However, the events that regulate the establishment of the microbiota, their timing, and the way in which they interact with the host are not yet fully understood. Factors such as gestational age, mode of delivery, environment, hygienic measures, and diet influence the establishment of microbiota in the perinatal period. Environmental microbes constitute the most important group of exogenous stimuli in this critical time frame. However, the settlement of a stable gut microbiota in preterm infants is delayed compared to term infants. Preterm infants have an immature gastrointestinal tract and immune system which predisposes to infectious morbidity. Neonatal microbial dynamics and alterations in early gut microbiota may precede and/or predispose to diseases such as necrotizing enterocolitis (NEC), late-onset sepsis or others. During this critical period, nutrition is the principal contributor for immunological and metabolic development, and microbiological programming. Breast milk is a known source of molecules that act synergistically to protect the gut barrier and enhance the maturation of the gut-related immune response. Host-microbe interactions in preterm infants and the protective role of diet focused on breast milk impact are beginning to be unveiled.M.C. acknowledges a “Rio Hortega” Research Fellowship Grant (CM13/0017) and M.V. acknowledges grants PI11/0313 and RD12/0026/0012 (Red SAMID) from the Instituto Carlos III (Spanish Ministry of Economy and Competitivity). M.C.C. and G.P-M. were supported by the grant AGL2013-47420-R from the Spanish Ministry of Science and Innovation.Peer reviewe

    Analysis of computational approaches for motif discovery

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    Recently, we performed an assessment of 13 popular computational tools for discovery of transcription factor binding sites (M. Tompa, N. Li, et al., "Assessing Computational Tools for the Discovery of Transcription Factor Binding Sites", Nature Biotechnology, Jan. 2005). This paper contains follow-up analysis of the assessment results, and raises and discusses some important issues concerning the state of the art in motif discovery methods: 1. We categorize the objective functions used by existing tools, and design experiments to evaluate whether any of these objective functions is the right one to optimize. 2. We examine various features of the data sets that were used in the assessment, such as sequence length and motif degeneracy, and identify which features make data sets hard for current motif discovery tools. 3. We identify an important feature that has not yet been used by existing tools and propose a new objective function that incorporates this feature

    Changing presentation of prostate cancer in a UK population--10 year trends in prostate cancer risk profiles in the East of England.

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    BACKGROUND: Prostate cancer incidence is rising in the United Kingdom but there is little data on whether the disease profile is changing. To address this, we interrogated a regional cancer registry for temporal changes in presenting disease characteristics. METHODS: Prostate cancers diagnosed from 2000 to 2010 in the Anglian Cancer Network (n=21,044) were analysed. Risk groups (localised disease) were assigned based on NICE criteria. Age standardised incidence rates (IRs) were compared between 2000-2005 and 2006-2010 and plotted for yearly trends. RESULTS: Over the decade, overall IR increased significantly (P<0.00001), whereas metastasis rates fell (P<0.0007). For localised disease, IR across all risk groups also increased but at different rates (P<0.00001). The most striking change was a three-fold increase in intermediate-risk cancers. Increased IR was evident across all PSA and stage ranges but with no upward PSA or stage shift. In contrast, IR of histological diagnosis of low-grade cancers fell over the decade, whereas intermediate and high-grade diagnosis increased significantly (P<0.00001). CONCLUSION: This study suggests evidence of a significant upward migration in intermediate and high-grade histological diagnosis over the decade. This is most likely to be due to a change in histological reporting of diagnostic prostate biopsies. On the basis of this data, increasing proportions of newly diagnosed cancers will be considered eligible for radical treatment, which will have an impact on health resource planning and provision
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