Human LAT blocking peptide

To simulate tire tread friction and wear, a variety of factors have to he taken into account. Among them, the local nonlinear constitutive equation for friction and wear in the contact interface and the related solving strategies, including the wear increment optimization and worn mesh update, are very critical to the predicting methodology. This two-part contribution addresses an integrated approach for friction and wear simulation of tire tread rubber. In Part I, a modified friction test scheme of rubber wheels with the Laboratory Abrasion and Skid Tester (LAT 100) is proposed. along with numerical verification, which greatly improved the distribution uniformities of the contact pressure and sliding velocity. In order to investigate the friction characteristics of tire tread rubber, various contact conditions were conducted, and then a unified friction model was put forward to describe the nonlinear relationship of rubber friction with contact pressure and sliding velocity. Based on the established frictional contact model, the locked traction and cornering rolling were simulated, and the calculated friction forces and lateral forces agree with the experimental results on the whole.

For various precise navigational applications using Indian NavIC system, it is imperative to have an accurate estimation of the ionospheric line-of-sight total electron content (TEC). In dual frequency TEC estimation from code and carrier phase measurements, the error is mainly caused by the satellite and receiver differential instrumental biases, which can be several TEC units. The reason for the existence of these biases is that the signals experience different delays within the satellite and receiver hardware at the two frequencies S1 and L5 of NavIC system. These biases are not stable over the time, maybe due to aging or change in the environment of the satellites and receiver. In this paper, the dynamics of the estimated biases of different satellites of NavIC system and receiver are presented, based on the data collected over 19 months time at Dehradun (Lat.31.26 degrees N, Long.77.99 degrees E), India. Five state Kalman filter algorithm was used for the estimation of differential biases. The initial receiver bias required to run Kalman filter algorithm was determined by applying fitted receiver bias (FRB) technique. The initial satellite biases needed for the purpose were supplied by Space Applications Centre (SAC), Indian Space Research Organization (ISRO), Ahmedabad, India.