A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects.

We define a method for incorporating strong prior shape information into a recently extended Markov point process model for the extraction of arbitrarily-shaped objects from images. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process defined in a space of multiple objects. The single objects considered are defined by both the image data and the prior information in a way that controls the computational complexity of the estimation problem. The method is tested via experiments on a very high resolution aerial image of a scene composed of tree crowns

Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours.

We extend the marked point process models that have been used for object extraction from images to arbitrarily shaped objects, without greatly increasing the computational complexity of sampling and estimation. The approach can be viewed as an extension of the active contour methodology to an a priori unknown number of objects. Sampling and estimation are based on a stochastic birth-and-death process defined in a space of multiple, arbitrarily shaped objects, where the objects are defined by the image data and prior information. The performance of the approach is demonstrated via experimental results on synthetic and real data

A marked point process model with strong prior shape information for extraction of multiple, arbitrarily-shaped objects

We define a method for incorporating strong prior shape information into a recently extended Markov point process model for the extraction of arbitrarily-shaped objects from images. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process defined in a space of multiple objects. The single objects considered are defined by both the image data and the prior information in a way that controls the computational complexity of the estimation problem. The method is tested via experiments on a very high resolution aerial image of a scene composed of tree crowns

Extraction of arbitrarily shaped objects using stochastic multiple birth-and-death dynamics and active contours

We extend the marked point process models that have been used for object extraction from images to arbitrarily shaped objects, without greatly increasing the computational complexity of sampling and estimation. The approach can be viewed as an extension of the active contour methodology to an a priori unknown number of objects. Sampling and estimation are based on a stochastic birth-and-death process defined in a space of multiple, arbitrarily shaped objects, where the objects are defined by the image data and prior information. The performance of the approach is demonstrated via experimental results on synthetic and real data

Measurement of CP asymmetries and branching fraction ratios of B− decays to two charm mesons

The $CP$ asymmetries of seven $B^-$ decays to two charm mesons are measured using data corresponding to an integrated luminosity of $9\text{fb}^{-1}$ of proton-proton collisions collected by the LHCb experiment. Decays involving a $D^{*0}$ or $D^{*-}_s$ meson are analysed by reconstructing only the $D^0$ or $D^-_s$ decay products. This paper presents the first measurement of $\mathcal{A}^{CP}(B^- \rightarrow D^{*-}_s D^0)$ and $\mathcal{A}^{CP}(B^- \rightarrow D^{-}_s D^{*0})$, and the most precise measurement of the other five $CP$ asymmetries. There is no evidence of $CP$ violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured.The CP asymmetries of seven B$^{−}$ decays to two charm mesons are measured using data corresponding to an integrated luminosity of 9 fb$^{−1}$ of proton-proton collisions collected by the LHCb experiment. Decays involving a D$^{*0}$ or ${D}_s^{\ast -}$ meson are analysed by reconstructing only the D$^{0}$ or ${D}_s^{-}$ decay products. This paper presents the first measurement of $\mathcal{A} ^{CP}$(B$^{−}$→${D}_s^{\ast -}$D$^{0}$) and $\mathcal{A} ^{CP}$(B$^{−}$→${D}_s^{-}$D$^{∗0}$), and the most precise measurement of the other five CP asymmetries. There is no evidence of CP violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured.[graphic not available: see fulltext]The $CP$ asymmetries of seven $B^-$ decays to two charm mesons are measured using data corresponding to an integrated luminosity of $9\text{ fb}^{-1}$ of proton-proton collisions collected by the LHCb experiment. Decays involving a $D^{*0}$ or $D^{*-}_s$ meson are analysed by reconstructing only the $D^0$ or $D^-_s$ decay products. This paper presents the first measurement of $\mathcal{A}^{CP}(B^- \rightarrow D^{*-}_s D^0)$ and $\mathcal{A}^{CP}(B^- \rightarrow D^{-}_s D^{*0})$, and the most precise measurement of the other five $CP$ asymmetries. There is no evidence of $CP$ violation in any of the analysed decays. Additionally, two ratios between branching fractions of selected decays are measured

Helium identification with LHCb

The identification of helium nuclei at LHCb is achieved using a method based on measurements of ionisation losses in the silicon sensors and timing measurements in the Outer Tracker drift tubes. The background from photon conversions is reduced using the RICH detectors and an isolation requirement. The method is developed using pp collision data at √(s) = 13 TeV recorded by the LHCb experiment in the years 2016 to 2018, corresponding to an integrated luminosity of 5.5 fb-1. A total of around 105 helium and antihelium candidates are identified with negligible background contamination. The helium identification efficiency is estimated to be approximately 50% with a corresponding background rejection rate of up to O(10^12). These results demonstrate the feasibility of a rich programme of measurements of QCD and astrophysics interest involving light nuclei

Curvature-bias corrections using a pseudomass method

Momentum measurements for very high momentum charged particles, such as muons from electroweak vector boson decays, are particularly susceptible to charge-dependent curvature biases that arise from misalignments of tracking detectors. Low momentum charged particles used in alignment procedures have limited sensitivity to coherent displacements of such detectors, and therefore are unable to fully constrain these misalignments to the precision necessary for studies of electroweak physics. Additional approaches are therefore required to understand and correct for these effects. In this paper the curvature biases present at the LHCb detector are studied using the pseudomass method in proton-proton collision data recorded at centre of mass energy √(s)=13 TeV during 2016, 2017 and 2018. The biases are determined using Z→μ + μ - decays in intervals defined by the data-taking period, magnet polarity and muon direction. Correcting for these biases, which are typically at the 10-4 GeV-1 level, improves the Z→μ + μ - mass resolution by roughly 18% and eliminates several pathological trends in the kinematic-dependence of the mean dimuon invariant mass

Momentum scale calibration of the LHCb spectrometer

For accurate determination of particle masses accurate knowledge of the momentum scale of the detectors is crucial. The procedure used to calibrate the momentum scale of the LHCb spectrometer is described and illustrated using the performance obtained with an integrated luminosity of 1.6 fb-1 collected during 2016 in pp running. The procedure uses large samples of J/ψ → μ + μ - and B+ → J/ψ K + decays and leads to a relative accuracy of 3 × 10-4 on the momentum scale

A marked point process model including strong prior shape information applied to multiple object extraction from images

Object extraction from images is one of the most important tasks in remote sensing image analysis. For accurate extraction from very high resolution (VHR) images, object geometry needs to be taken into account. A method for incorporating strong yet flexible prior shape information into a marked point process model for the extraction of multiple objects of complex shape is presented. To control the computational complexity, the objects considered are defined using the image data and the prior shape information. To estimate the optimal configuration of objects, the process is sampled using a Markov chain based on a stochastic birth-and-death process on the space of multiple objects. The authors present several experimental results on the extraction of tree crowns from VHR aerial images

The first synthesis of 6-(phenylethynyl)-substituted tetrahydroazocino[5,4-b]indoles

The reaction of 2-methyl-1-(phenylethynyl)-2,3,4,9-tetrahydro-1?-β-carboline with activated alkynes in acetonitrile led to the formation of 1-vinyl-substituted β-carbolines and condensed azocines. © 2016 Springer Science+Business Media New York