384 research outputs found

    Contact Stiffness Study: Modelling and Identification

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    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

    Study of the BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} decay

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    The decay BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} is studied in proton-proton collisions at a center-of-mass energy of s=13\sqrt{s}=13 TeV using data corresponding to an integrated luminosity of 5 fb1\mathrm{fb}^{-1} collected by the LHCb experiment. In the Λc+K\Lambda_{c}^+ K^{-} system, the Ξc(2930)0\Xi_{c}(2930)^{0} state observed at the BaBar and Belle experiments is resolved into two narrower states, Ξc(2923)0\Xi_{c}(2923)^{0} and Ξc(2939)0\Xi_{c}(2939)^{0}, whose masses and widths are measured to be m(Ξc(2923)0)=2924.5±0.4±1.1MeV,m(Ξc(2939)0)=2938.5±0.9±2.3MeV,Γ(Ξc(2923)0)=0004.8±0.9±1.5MeV,Γ(Ξc(2939)0)=0011.0±1.9±7.5MeV, m(\Xi_{c}(2923)^{0}) = 2924.5 \pm 0.4 \pm 1.1 \,\mathrm{MeV}, \\ m(\Xi_{c}(2939)^{0}) = 2938.5 \pm 0.9 \pm 2.3 \,\mathrm{MeV}, \\ \Gamma(\Xi_{c}(2923)^{0}) = \phantom{000}4.8 \pm 0.9 \pm 1.5 \,\mathrm{MeV},\\ \Gamma(\Xi_{c}(2939)^{0}) = \phantom{00}11.0 \pm 1.9 \pm 7.5 \,\mathrm{MeV}, where the first uncertainties are statistical and the second systematic. The results are consistent with a previous LHCb measurement using a prompt Λc+K\Lambda_{c}^{+} K^{-} sample. Evidence of a new Ξc(2880)0\Xi_{c}(2880)^{0} state is found with a local significance of 3.8σ3.8\,\sigma, whose mass and width are measured to be 2881.8±3.1±8.5MeV2881.8 \pm 3.1 \pm 8.5\,\mathrm{MeV} and 12.4±5.3±5.8MeV12.4 \pm 5.3 \pm 5.8 \,\mathrm{MeV}, respectively. In addition, evidence of a new decay mode Ξc(2790)0Λc+K\Xi_{c}(2790)^{0} \to \Lambda_{c}^{+} K^{-} is found with a significance of 3.7σ3.7\,\sigma. The relative branching fraction of BΛc+ΛˉcKB^{-} \to \Lambda_{c}^{+} \bar{\Lambda}_{c}^{-} K^{-} with respect to the BD+DKB^{-} \to D^{+} D^{-} K^{-} decay is measured to be 2.36±0.11±0.22±0.252.36 \pm 0.11 \pm 0.22 \pm 0.25, where the first uncertainty is statistical, the second systematic and the third originates from the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb public pages

    Measurement of the ratios of branching fractions R(D)\mathcal{R}(D^{*}) and R(D0)\mathcal{R}(D^{0})

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    The ratios of branching fractions R(D)B(BˉDτνˉτ)/B(BˉDμνˉμ)\mathcal{R}(D^{*})\equiv\mathcal{B}(\bar{B}\to D^{*}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(\bar{B}\to D^{*}\mu^{-}\bar{\nu}_{\mu}) and R(D0)B(BD0τνˉτ)/B(BD0μνˉμ)\mathcal{R}(D^{0})\equiv\mathcal{B}(B^{-}\to D^{0}\tau^{-}\bar{\nu}_{\tau})/\mathcal{B}(B^{-}\to D^{0}\mu^{-}\bar{\nu}_{\mu}) are measured, assuming isospin symmetry, using a sample of proton-proton collision data corresponding to 3.0 fb1{ }^{-1} of integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The tau lepton is identified in the decay mode τμντνˉμ\tau^{-}\to\mu^{-}\nu_{\tau}\bar{\nu}_{\mu}. The measured values are R(D)=0.281±0.018±0.024\mathcal{R}(D^{*})=0.281\pm0.018\pm0.024 and R(D0)=0.441±0.060±0.066\mathcal{R}(D^{0})=0.441\pm0.060\pm0.066, where the first uncertainty is statistical and the second is systematic. The correlation between these measurements is ρ=0.43\rho=-0.43. Results are consistent with the current average of these quantities and are at a combined 1.9 standard deviations from the predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb public pages

    Automated Generation of Fixture Configuration Design

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    Numerical Simulation of the Moving Induction Heating Process with Magnetic Flux Concentrator

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    The induction heating with ferromagnetic metal powder bonded magnetic flux concentrator (MPB-MFC) demonstrates more advantages in surface heating treatments of metal. However, the moving heating application is mostly applied in the industrial production. Therefore, the analytical understanding of the mechanism, efficiency, and controllability of the moving induction heating process becomes necessary for process design and optimization. This paper studies the mechanism of the moving induction heating with magnetic flux concentrator. The MPB-MFC assisted moving induction heating for Inconel 718 alloy is studied by establishing the finite element simulation model. The temperature field distribution is analyzed, and the factors influencing the temperature are studied. The conclusion demonstrates that the velocity of the workpiece should be controlled properly and the heat transfer coefficient (HTC) has little impact on the temperature development, compared with other input parameters. In addition, the validity of the static numerical model is verified by comparing the finite element simulation with experimental results on AISI 1045 steel. The numerical model established in this work can provide comprehensive understanding for the process control in production
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