Sound generated by rubbing objects

In the present paper, we investigate the properties of the sound generated by rubbing two objects. It is clear that the sound is generated because of the rubbing between the contacting rough surfaces of the objects. A model is presented to account for the role played by the surface roughness. The results indicate that tonal features of the sound can be generated due to the finiteness of the rubbing surfaces. In addition, the analysis shows that with increasing rubbing speed, more and more high frequency tones can be excited and the frequency band gets broader and broader, a feature which appears to agree with our intuition or experience.Comment: 3 pages, 2 figure

Mechanism of unidirectional movement of kinesin motors

Kinesin motors have been studied extensively both experimentally and theoretically. However, the microscopic mechanism of the processive movement of kinesin is still an open question. In this paper, we propose a hand-over-hand model for the processivity of kinesin, which is based on chemical, mechanical, and electrical couplings. In the model the processive movement does not need to rely on the two heads' coordination in their ATP hydrolysis and mechanical cycles. Rather, the ATP hydrolyses at the two heads are independent. The much higher ATPase rate at the trailing head than the leading head makes the motor walk processively in a natural way, with one ATP being hydrolyzed per step. The model is consistent with the structural study of kinesin and the measured pathway of the kinesin ATPase. Using the model the estimated driving force of ~ 5.8 pN is in agreements with the experimental results (5~7.5 pN). The prediction of the moving time in one step (~10 microseconds) is also consistent with the measured values of 0~50 microseconds. The previous observation of substeps within the 8-nm step is explained. The shapes of velocity-load (both positive and negative) curves show resemblance to previous experimental results.Comment: 22 pages, 6 figure

Control of spiral waves and turbulent states in a cardiac model by travelling-wave perturbations

We propose a travelling-wave perturbation method to control the spatiotemporal dynamics in a cardiac model. It is numerically demonstrated that the method can successfully suppress the wave instability (alternans in action potential duration) in the one-dimensional case and convert spiral waves and turbulent states to the normal travelling wave states in the two-dimensional case. An experimental scheme is suggested which may provide a new design for a cardiac defibrillator.Comment: 9 pages, 5 figure

Model for processive movement of myosin V and myosin VI

Myosin V and myosin VI are two classes of two-headed molecular motors of the myosin superfamily that move processively along helical actin filaments in opposite directions. Here we present a hand-over-hand model for their processive movements. In the model, the moving direction of a dimeric molecular motor is automatically determined by the relative orientation between its two heads at free state and its head's binding orientation on track filament. This determines that myosin V moves toward the barbed end and myosin VI moves toward the pointed end of actin. During the moving period in one step, one head remains bound to actin for myosin V whereas two heads are detached for myosin VI: The moving manner is determined by the length of neck domain. This naturally explains the similar dynamic behaviors but opposite moving directions of myosin VI and mutant myosin V (the neck of which is truncated to only one-sixth of the native length). Because of different moving manners, myosin VI and mutant myosin V exhibit significantly broader step-size distribution than native myosin V. However, all three motors give the same mean step size of 36 nm (the pseudo-repeat of actin helix). Using the model we study the dynamics of myosin V quantitatively, with theoretical results in agreement with previous experimental ones.Comment: 18 pages, 7 figure

Probabilistic Monte-Carlo method for modelling and prediction of electronics component life

Power electronics are widely used in electric vehicles, railway locomotive and new generation aircrafts. Reliability of these components directly affect the reliability and performance of these vehicular platforms. In recent years, several research work about reliability, failure mode and aging analysis have been extensively carried out. There is a need for an efficient algorithm able to predict the life of power electronics component. In this paper, a probabilistic Monte-Carlo framework is developed and applied to predict remaining useful life of a component. Probability distributions are used to model the component’s degradation process. The modelling parameters are learned using Maximum Likelihood Estimation. The prognostic is carried out by the mean of simulation in this paper. Monte-Carlo simulation is used to propagate multiple possible degradation paths based on the current health state of the component. The remaining useful life and confident bounds are calculated by estimating mean, median and percentile descriptive statistics of the simulated degradation paths. Results from different probabilistic models are compared and their prognostic performances are evaluated