BackgroundWell-characterized mice models will afford a cheaper, easy-handling opportunity for a more comprehensive understanding of 2009 influenza A (H1N1) virus’s pathogenesis potential. We aimed to provide a robust description of pulmonary immune responses in the mice infected by the virus.MethodsBALB/c mice were inoculated intranasally with A/Beijing/501/2009(H1N1) (BJ501) and A/PR/8/34(H1N1) (PR8) viruses and compared for survival rate, viral replication, and kinetics of pulmonary immune responses.ResultsBJ501 virus replicated less efficiently in the lungs than PR8, and both caused lethal illness in the mice. The transient increases of pulmonary TNF-α 2 days post infection for BJ501 and of INF-γ and IL-10 at 6 days post infection for PR8 were observed. IL-2+ and IL-4+ secreting cells showed significant increase 12 days post infection, while IFN-γ+, IgG+ and IgA+ secreting cells increased 6 days post infection. The different patterns of pulmonary immunological parameters between two viruses were at most seen in IL-6, IL-17 secretion and IgG1/IgG2a ratio.ConclusionsThe BALB/c mouse is evaluated as a good pathogenic model for studying BJ501 2009 H1N1 virus. The work provided some basic and detailed data, which might be referred when further evaluating innate and adapted pulmonary immune responses and local viral load in mice.

The development of automotive technology has become increasingly important for preventing car accidents. Hence, as a basic research of driver assistance systems, a novel control method has been proposed for steering support. In particular, the stability and limitation of such a system is investigated for the safe and comfortable drive. First, the particle swarm optimisation (PSO)-based algorithm is used to search the optimal feedback gain under practical constraints for achieving tracking control. Moreover, to reduce the convergence time further, the PSO algorithm is combined with the technique of quantum computing. Simulation results indicate that the proposed feedback controller based on quantum PSO has the ability to provide efficient computational performance for trajectory tracking and stabilisation.

In this study we give a feedback control method for steering support system. In this method we consider the stability of the path tracking control system under the limitation of steering angle, so that drivers can drive safer and more comfortable. In order to do this, we have derived linearized system from the nonholonomic kinematic system by the differential flatness consideration and linear control law which stabilizes the path tracking control system. Furthermore, feedback gains are tuned to satisfy the closed loop stability and the limitation of the steering angle by using Particle Swarm Optimization. Usefulness of the proposed control method has been demonstrated by experiments using a 1/10 scale robot car.

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