Mechanical cues like the rigidity of the substrate are main determinants for the decision-making of adherent cells. Here we use a mechano-chemical model to predict the cellular response to varying substrate stiffnesses. The model equations combine the mechanics of contractile actin filament bundles with a model for the Rho-signaling pathway triggered by forces at cell-matrix contacts. A bifurca...

Stability of the spinal column is critical to bear loads, allow movement, and at the same time avoid injury and pain. However, there has been a debate in recent years as to how best to define and quantify spine stability, with the outcome being that different methods are used without a clear understanding of how they relate to one another. Therefore, the goal of the present study was to directl...

this paper presents a new observer design methodology for a time varying actuator fault estimation. a new linear matrix inequality (lmi) design algorithm is developed to tackle the limitations (e.g. equality constraint and robustness problems) of the well known so called fast adaptive fault estimation observer (fafe). the fafe is capable of estimating a wide range of time-varying actuator fault...

In this article, we address the problem of controlling unknown flexible-joint robots with unknown time-varying stiffness and damping parameters. We propose a Robust Direct Adaptive Fuzzy Control (RDAFC) strategy that accommodates the dynamics anonymity and joints stiffness/damping variations. The RDAFC strategy relies on the synergy of the concepts of fuzzy logic approximation and the Sliding M...

in this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.based on the backstepping technique, the adaptive fuzzy controller is constructed. the main contributions of the paper...

in this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the takagi-sugeno (t-s) fuzzy models is considered. a novel linear matrix inequality (lmi)-based stability criterion is obtained by using lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

in this study, 3 models of time-varying parameters (tvp), dynamic model selection (dms) and dynamic model averaging (dma) and a comparison with the ordinary least squares (ols) method in matlab in the time period 2003-2013 (with data on a monthly basis) are discussed. in the present study, the variables of unofficial exchange rate changes, interest rate changes and inflation in oil price foreca...