A nanostructured thermoelectric device is designed by connecting a double-barrier resonant tunneling heterostructure to two electron reservoirs. Based on Landauers equation and Fermi-Dirac statistics, the exact solution of heat flow calculated. The maximum power output efficiency are calculated through optimizations several key parameters. optimum characteristic curve performance obtained. reas...

The basalar muscle of the beetle Cotinus mutabilis is a large, fibrillar flight muscle composed of approximately 90 fibers. The paired basalars together make up approximately one-third of the mass of the power muscles of flight. Changes in twitch force with changing stimulus intensity indicated that a basalar muscle is innervated by at least five excitatory axons and at least one inhibitory axo...

A method estimating the queue length in city street networks was proposed using the data of roll time occupancy. The key idea of this paper is that when the queue length in front of the queue detector becomes longer, the speeds of the following vehicles to pass through the detector will become smaller, resulting in higher occupancy with constant traffic intensity. Considering the relationship b...

piezoelectric microcantilevers (mcs) are a new generation of microbeams used in atomic force microscopes (afms). due to their miniaturization of afms as well as their increased imaging precision and speed, these mcs are more popular than their classical counterparts. given the widespread application of these beams in nanoparticle topography, analysis of their vibrating motion has attracted much...

Function approximation is essential to reinforcement learning, but the standard approach of approximating a value function and determining a policy from it has so far proven theoretically intractable. In this paper we explore an alternative approach in which the policy is explicitly represented by its own function approximator, independent of the value function, and is updated according to the ...

In this theoretical paper we are concerned with the problem of learning a value function by a smooth general function approximator, to solve a deterministic episodic control problem in a large continuous state space. It is shown that learning the gradient of the value-function at every point along a trajectory generated by a greedy policy is a sufficient condition for the trajectory to be local...

We present a data-driven, probabilistic trajectory optimization framework for systems with unknown dynamics, called Probabilistic Differential Dynamic Programming (PDDP). PDDP takes into account uncertainty explicitly for dynamics models using Gaussian processes (GPs). Based on the second-order local approximation of the value function, PDDP performs Dynamic Programming around a nominal traject...

Between the onset of projectile fragmentation and the assumption of rear wall failure due to an impulsive load, multi-wall ballistic limit equations are linearly interpolated to provide reasonable yet conservative predictions of perforation thresholds with conveniently simple mathematics. Although low velocity and hypervelocity regime predictions are based on analytical expressions, there is no...