Measurement of the differential cross-section of B⁺ meson production in pp collisions at sqrts = 7 TeV at ATLAS

The production cross-section of B+ mesons is measured as a function of transverse momentum p T and rapidity y in proton-proton collisions at centre-of-mass energy root s = 7 TeV, using 2.4 fb(-1) of data recorded with the ATLAS detector at the Large Hadron Collider. The differential production cross-sections, determined in the range 9 GeV < p(T) < 120 GeV and vertical bar y vertical bar < 2.25, are compared to next-to-leading-order theoretical predictions.

Evidence for the spin-0 nature of the Higgs boson using ATLAS data

Studies of the spin and parity quantum numbers of the Higgs boson are presented, based on protonproton collision data collected by the ATLAS experiment at the LHC. The Standard Model spin-parity J(P) = 0(+) hypothesis is compared with alternative hypotheses using the Higgs boson decays H -> gamma gamma, H -> ZZ* -> 4l and H -> WW* -> l nu l nu, as well as the combination of these channels. The analysed dataset corresponds to an integrated luminosity of 20.7 fb(-1) collected at a centre-of-mass energy of root s = 8 TeV. For the H -> ZZ* -> 4l decay mode the dataset corresponding to an integrated luminosity of 4.6 fb(-1) collected at root s = 7 TeV is included. The data are compatible with the Standard Model J(P) = 0+ quantum numbers for the Higgs boson, whereas all alternative hypotheses studied in this Letter, namely some specific J(P) = 0(-), 1(+), 1(-), 2(+) models, are excluded at confidence levels above 97.8%. This exclusion holds independently of the assumptions on the coupling strengths to the Standard Model particles and in the case of the J(P) = 2(+) model, of the relative fractions of gluon-fusion and quark-antiquark production of the spin-2 particle. The data thus provide evidence for the spin-0 nature of the Higgs boson, with positive parity being strongly preferred.

Flavor tagged time-dependent angular analysis of the B0s → J/ψΦ decay and extraction of Δ Γs and the weak phase Φs in ATLAS

A measurement of the B 0 s →J/ψϕ decay parameters, updated to include flavor tagging is reported using 4.9  fb −1 of integrated luminosity collected by the ATLAS detector from s √ =7  TeV pp collisions recorded in 2011 at the LHC. The values measured for the physical parameters are ϕ s 0.12±0.25(stat)±0.05(syst)  rad ΔΓ s 0.053±0.021(stat)±0.010(syst)  ps −1 Γ s 0.677±0.007(stat)±0.004(syst)  ps −1 |A ∥ (0)| 2 0.220±0.008(stat)±0.009(syst) |A 0 (0)| 2 0.529±0.006(stat)±0.012(syst) δ ⊥ =3.89±0.47(stat)±0.11(syst)  rad where the parameter ΔΓ s is constrained to be positive. The S -wave contribution was measured and found to be compatible with zero. Results for ϕ s and ΔΓ s are also presented as 68% and 95% likelihood contours, which show agreement with the Standard Model expectations.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Pretreatment and outcome correlates of past sexual and physical trauma in 118 bipolar I disorder patients with a first episode of psychotic mania

To assess the prevalence and correlates of childhood and adolescent sexual and/or physical abuse (SPA) in bipolar I disorder (BDI) patients treated for a first episode of psychotic mania.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.