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Spallation reactions on fissile nuclei represent an appropriate tool to investigate dissipative effects in nuclear fission. In this work, we have studied transient and dissipative effects in proton-and deuteron-induced fission on 208 Pb at 500A MeV. A dedicated experimental setup optimized for inverse kinematics measurements made it possible to identify in atomic number both fission fragments with high resolution, and reconstruct the charge of the fissioning system. We could then determine the width of the fission fragments charge distribution as well as partial fission cross sections, both as a function of the charge of the fissioning system. These two complementary observables permitted us to investigate the dynamics of the process at small deformation, i.e., from the ground state to the saddle point. The description of these observables with advanced model calculations reveals the influence of the nuclear dissipation in the fission process at high excitation energy and in particular its manifestation through transient time effects.

International audienceThe aim of this paper is to simulate the nonlinear wave propagation in granular chains of beads using a recently introduced multiple impact model and to compare numerical results to experimental ones. Different kinds of granular chains are investigated: monodisperse chains, tapered chains and stepped chains. Particular attention is paid to the dispersion effect, and the wave propagation in tapered chains, the interaction of two solitary waves in monodisperse chains, and the formation of solitary wave trains in stepped chains. We show that the main features of the wave propagation observed experimentally in these granular chains are very well reproduced. This proves that the considered multiple impact model and numerical scheme are able to encapsulate the main physical effects that occur in such multibody systems

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This study investigated the content of aflatoxin, ochratoxin A, zearalenone, deoxynivalenol and fumonisin B1 in some food product. Samples were extracted and cleaned by QUEChERS approach. The extract was measured by liquid chromatography tandem mass spectrometry. The positive samples were reconfirmed by standard methods using immunoaffinity extraction. The detection limit of the method for aflatoxin, fumonisin B1, ochratoxin A, deoxynivalenol, zearalenone were 0.5, 30, 0.5, 60, and 3.0 µg/kg, respectively. The recoveries of all analytes were in the range of 70 - 110%. The repeatability coefficient of variation were in the range of 5,1 - 13%. Among the 300 food samples tested, there were 43 samples detected with studied mycotoxins, accounting for 14.3%, mainly focusing on unprocessed cereals. In which, 10 spice samples, 04 peanuts and sesame samples, 01 candy sample, 01 sample of nutritious cereal flour, and 01 food supplement sample were found to be contaminated with aflatoxin, ochratoxin A exceeding the maximum level of Ministry Of Health according to QCVN 8-1 : 2011/BYT.

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Abstract-In this paper, an adaptive MIMO neural network model is used for simultaneously modeling and identifying the forward kinematics of a 3-DOF robot manipulator. The nonlinear features of the robot manipulator kinematics system are modeled by an adaptive MIMO neural network model based on differential evolution algorithm. A differential evolution algorithm is used to optimally generate the appropriate neural weights so as to perfectly characterize the nonlinear features of the forward kinematics of a 3-DOF robot manipulator. This paper supports the performance of the proposed differential evolution algorithm in comparison with the conventional back-propagation algorithm. The results show that the proposed adaptive MIMO neural network model trained by the differential evolution algorithm for identifying the forward kinematics of a 3-DOF robot manipulator is successfully modeled and performed well.