Dynamic control and enhancement of laser-accelerated protons using multiple laser pulses

The use of schemes involving multiple laser pulses to enhance and control the properties of beams of protons accelerated in ultra-intense laser irradiation of planar foil targets is discussed. Specifically, the schemes include the use of a second laser pulse to produce and control preplasma expansion of the target to enhance energy coupling to the proton beam; the use of a second laser pulse to drive shock deformation of the target to change the direction of the proton beam; and a scheme involving dual high intensity laser pulses to change the properties of the sheath field, with the aim of modifying the proton energy spectrum. An overview of our recent experimental and theoretical results is given. The overall aim of this work is to determine the extent to which the properties of the sheath-accelerated proton beam can be optically controlled, to enable beam delivery at high repetition rates. To cite this article: D.C. Carroll et al., C. R. Physique 10 (2009). (C) 2009 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

Stress correlation between instrumentation and simulation analysis of the die for high pressure die casting

A strain gauge instrumentation trial on a high pressure die casting ‘HPDC’ die was compared to a corresponding simulation model using Magmasoft® casting simulation software at two strain gauge rosette locations. The strains were measured during the casting cycle, from which the von Mises stress was determined and then compared to the simulation model. The von Mises stress from the simulation model correlated well with the findings from the instrumentation trial, showing a difference of 5.5%, ~ 10 MPa for one strain gauge rosette located in an area of low stress gradient. The second rosette was in a region of steep stress gradient, which resulted in a difference of up to 40%, ~40 MPa between the simulation and instrumentation results. Factors such as additional loading from die closure force or metal injection pressure which are not modelled by Magmasoft® were seen to have very little influence on the stress in the die, less than 7%.

P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring

P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.

Generalized Laplacian Eigenmaps for Modeling and Tracking Human Motions

This paper presents generalized Laplacian eigenmaps, a novel dimensionality reduction approach designed to address stylistic variations in time series. It generates compact and coherent continuous spaces whose geometry is data-driven. This paper also introduces graph-based particle filter, a novel methodology conceived for efficient tracking in low dimensional space derived from a spectral dimensionality reduction method. Its strengths are a propagation scheme, which facilitates the prediction in time and style, and a noise model coherent with the manifold, which prevents divergence, and increases robustness. Experiments show that a combination of both techniques achieves state-of-the-art performance for human pose tracking in underconstrained scenarios.