Kaon production from 1 to 40 AGeV

Kaon production is studied within the Giessen Boltzmann–Uehling–Uhlenbeck (GiBUU) model. Results are compared with experiment and with other models. The influence of the kaon potential on the kaon azimuthal distributions at SIS energies is considered. We also discuss the role of the many-body collisions at high-density phase of reaction.     

Solvothermal synthesis of TiO2: anatase nanocrystals and rutile nanofibres from TiCl4 in acetone

This work reports a new synthetic approach for single‐phase TiO₂ nanomaterials by solvothermal treatment of titanium tetrachloride in acetone at 80–110 °C. Small, uniform, and yet size‐tunable (5–10 nm) anatase titania nanocrystallites were obtained using a low concentration of TiCl₄ in acetone (i.e., at molar ratios of TiCl₄/acetone ≤ 1:15) in the temperature range of 80–110 °C, while rutile nanofibers were synthesized using a high concentration of TiCl₄ (e.g., TiCl₄/acetone = 1:10) at 110 °C. Copyright © 2007 John Wiley & Sons, Ltd.     

A novel approach based on recurrent neural networks applied to nonlinear systems optimization

This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.