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We have studied the adhesion state (also denoted by docking state) of lipid vesicles as induced by the divalent ions Ca or Mg at well-controlled ion concentration, lipid composition, and charge density. The bilayer structure and the interbilayer distance in the docking state were analyzed by small-angle x-ray scattering. A strong adhesion state was observed for DOPC:DOPS vesicles, indicating like-charge attraction resulting from ion correlations. The observed interbilayer separations of ∼1.6 nm agree quantitatively with the predictions of electrostatics in the strong coupling regime. Although this phenomenon was observed when mixing anionic and zwitterionic (or neutral) lipids, pure anionic membranes (DOPS) with highest charge density σ resulted in a direct phase transition to a multilamellar state, which must be accompanied by rupture and fusion of vesicles. To extend the structural assay toward protein-controlled docking and fusion, we have characterized reconstituted N-ethylmaleimide-sensitive factor attachment protein receptors in controlled proteoliposome suspensions by small-angle x-ray scattering.

Based on both adaptive and fuzzy control techniques, this paper proposes a faulttolerant control (FTC) approach for near space vehicle (NSV) re-entry attitude dynamics with a stuck actuator fault. A Takagi-Sugeno fuzzy model is used to describe complex NSV attitude dynamics. The principle of this FTC approach is to design an iterative learning observer, which is used to estimate the system state and produce control input adjustment and then to reconfigure the control law to compensate for the effect of the stuck actuator. The FTC scheme ensures that the NSV output dynamics asymptotically track that of a reference model under both fault-free conditions and with a stuck actuator. The boundedness of the error dynamics is analysed using the Lyapunov stability theory. Finally, simulation results are given to illustrate the effectiveness and potential of the proposed FTC technique.

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Abstract-Functional coupling between the motor cortex and muscle activity is usually detected and characterised using the spectral method of cortico-muscular coherence (CMC). This functional coupling occurs with a time delay which, if not properly accounted for, may decrease the coherence and make the synchrony difficult to detect. In this paper we introduce the concept of cortico-muscular coherence with time lag (CMCTL), that is the coherence between segments of motor cortex electroencephalogram (EEG) and electromyography (EMG) signals displaced from a central observation point. This concept is motivated by the need to compensate for the unknown delay between coupled cortex and muscle processes. We demonstrate using simulated data that under certain conditions the time lag between EEG and EMG segments at points of local maxima of CMCTL corresponds to the average delay along the involved cortico-muscular conduction pathways. Using neurophysiological data, we then show that CMCTL with appropriate time lag enhances the coherence between cortical and muscle signals, and that time lags which correspond to local maxima of CMCTL provide estimates of delays involved in cortico-muscular coupling that are consistent with the underlying physiology.