164 research outputs found
Predicting dislocation climb: Classical modeling versus atomistic simulations
The classical modeling of dislocation climb based on a continuous description
of vacancy diffusion is compared to recent atomistic simulations of dislocation
climb in body-centered cubic iron under vacancy supersaturation [Phys. Rev.
Lett. 105 095501 (2010)]. A quantitative agreement is obtained, showing the
ability of the classical approach to describe dislocation climb. The analytical
model is then used to extrapolate dislocation climb velocities to lower
dislocation densities, in the range corresponding to experiments. This allows
testing of the validity of the pure climb creep model proposed by Kabir et al.
[Phys. Rev. Lett. 105 095501 (2010)]
Screw dislocation in zirconium: An ab initio study
Plasticity in zirconium is controlled by 1/3 screw dislocations
gliding in the prism planes of the hexagonal close-packed structure. This
prismatic and not basal glide is observed for a given set of transition metals
like zirconium and is known to be related to the number of valence electrons in
the d band. We use ab initio calculations based on the density functional
theory to study the core structure of screw dislocations in zirconium.
Dislocations are found to dissociate in the prism plane in two partial
dislocations, each with a pure screw character. Ab initio calculations also
show that the dissociation in the basal plane is unstable. We calculate then
the Peierls barrier for a screw dislocation gliding in the prism plane and
obtain a small barrier. The Peierls stress deduced from this barrier is lower
than 21 MPa, which is in agreement with experimental data. The ability of an
empirical potential relying on the embedded atom method (EAM) to model
dislocations in zirconium is also tested against these ab initio calculations
Current preventive strategies and management of Epstein-Barr virus-related post-transplant lymphoproliferative disease in solid organ transplantation in Europe. Results of the ESGICH Questionnaire-based Cross-sectional Survey
There is limited clinical evidence on the utility of the monitoring of Epstein-Barr virus (EBV) DNAemia in the pre-emptive management of post-transplant lymphoproliferative disease (PTLD) in solid organ transplant (SOT) recipients. We investigated current preventive measures against EBV-related PTLD through a web-based questionnaire sent to 669 SOT programmes in 35 European countries. This study was performed on behalf of the ESGICH study group from the European Society of Clinical Microbiology and Infectious Diseases. A total of 71 SOT programmes from 15 European countries participated in the study. EBV serostatus of the recipient is routinely obtained in 69/71 centres (97%) and 64 (90%) have access to EBV DNAemia assays. EBV monitoring is routinely used in 85.9% of the programmes and 77.4% reported performing pre-emptive treatment for patients with significant EBV DNAemia levels. Pre-emptive treatment for EBV DNAemia included reduction of immunosuppression in 50.9%, switch to mammalian target of rapamycin inhibitors in 30.9%, and use of rituximab in 14.5% of programmes. Imaging by whole-body 18-fluoro-deoxyglucose positron emission tomography (FDG-PET) is used in 60.9% of centres to rule out PTLD and complemented computer tomography is used in 50%. In 10.9% of centres, FDG-PET is included in the first-line diagnostic workup in patients with high-risk EBV DNAemia. Despite the lack of definitive evidence, EBV load measurements are frequently used in Europe to guide diagnostic workup and pre-emptive reduction of immunosuppression. We need prospective and controlled studies to define the impact of EBV monitoring in reducing the risk of PTLD in SOT recipients
Desynchronization of Neocortical Networks by Asynchronous Release of GABA at Autaptic and Synaptic Contacts from Fast-Spiking Interneurons
An activity-dependent long-lasting asynchronous release of GABA from identified fast-spiking inhibitory neurons in the neocortex can impair the reliability and temporal precision of activity in a cortical network
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