131 research outputs found

    Evidence of the Purely Leptonic Decay B- --> tau- nu_tau-bar

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    We present the first evidence of the decay B- --> tau- nu_tau-bar using 414 fb^-1 of data collected at the Upsilon(4S) resonance with the Belle detector at the KEKB asymmetric-energy e+e- collider. Events are tagged by fully reconstructing one of the B mesons in hadronic modes. We detect the signal with a significance of 3.5 standard deviations including systematics, and measure the branching fraction to be Br(B- --> tau- nu_tau-bar) = (1.79 +0.56-0.49(stat) +0.46-0.51(syst))*10^-4. This implies that f_B = 0.229 +0.036-0.031(stat) +0.034-0.037(syst) GeV and is the first direct measurement of this quantity.Comment: 6 pages, 3 figures, to appear in Physical Review Letter

    Treatment Outcomes of Patients With Multidrug-Resistant and Extensively Drug-Resistant Tuberculosis According to Drug Susceptibility Testing to First- and Second-line Drugs: An Individual Patient Data Meta-analysis

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    The clinical validity of drug susceptibility testing (DST) for pyrazinamide, ethambutol, and second-line antituberculosis drugs is uncertain. In an individual patient data meta-analysis of 8955 patients with confirmed multidrug-resistant tuberculosis, DST results for these drugs were associated with treatment outcome

    Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

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    The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

    Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

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    A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

    Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC

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    Genome-wide association study identifies two susceptibility loci for osteosarcoma

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    Osteosarcoma is the most common primary bone malignancy of adolescents and young adults. To better understand the genetic etiology of osteosarcoma, we performed a multistage genome-wide association study consisting of 941 individuals with osteosarcoma (cases) and 3,291 cancer-free adult controls of European ancestry. Two loci achieved genome-wide significance: a locus in the GRM4 gene at 6p21.3 (encoding glutamate receptor metabotropic 4; rs1906953; P = 8.1 × 10⁻âč) and a locus in the gene desert at 2p25.2 (rs7591996 and rs10208273; P = 1.0 × 10⁻⁞ and 2.9 × 10⁻⁷, respectively). These two loci warrant further exploration to uncover the biological mechanisms underlying susceptibility to osteosarcoma

    The Physics of the B Factories

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    Whole-genome sequencing reveals host factors underlying critical COVID-19

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    A recent case study in system identification

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