Dynamics of a superconducting bearing with a high-T//c superconductor and a setof alternating-polarity magnets are discussed. The superconductor used is prepared by the quench and melt growth process. The set of magne...
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Dynamics of a superconducting bearing with a high-T//c superconductor and a setof alternating-polarity magnets are discussed. The superconductor used is prepared by the quench and melt growth process. The set of magnets levitates over thesuperconductor which is field cooled in liquid nitrogen. To construct a dynamicmodel of the superconducting bearing, responses for impulse forces given to thelevitating magnets in vertical direction are investigated. Damped free-vibration curves of the levitating magnets are observed. Dynamic stiffness and viscous damping coefficient can be defined by using the periodical vibration curves. It isalso found that the stiffness andthe damping coefficient depend on the width ofa bar magnet. The resultant energy loss of the superconducting bearing is evaluated by using the force-displacement relationship and Bean's critical state model [Phys. Rev. Lett. 8, 250 (1962)].
Diffusional and electrostatic effects on the apparent maximum reaction rate V-m(app) and the apparent Michaelis constant K-m(app) were investigated theoretically for a system in which an enzyme immobilized on the exte...
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Diffusional and electrostatic effects on the apparent maximum reaction rate V-m(app) and the apparent Michaelis constant K-m(app) were investigated theoretically for a system in which an enzyme immobilized on the external surface of a solid support catalyzes a reaction according to Michaelis-Menten kinetics. In such a system, the dependence of V-m(app) and K-m(app) on the substrate concentration can be expressed analytically. When the support and substrate carry charges of the same sign, resulting in a repulsive force between them, both V-m(app) and K-m(app) decrease with increasing substrate concentration, but they never decrease below the respective intrinsic values. On the other hand, when the support and substrate carry charges of opposite sign and therefore an attractive force occurs, V-m(app) decreases towards its intrinsic value, while K-m(app) decreases to values below its intrinsic value in the region of high substrate concentration.
In a presynaptic terminal, neurotransmitters are stored in synaptic vesicles and secreted into the synaptic cleft as a final step of cell signal transduction. At a static state, the vesicles are retained in the highly...
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In a presynaptic terminal, neurotransmitters are stored in synaptic vesicles and secreted into the synaptic cleft as a final step of cell signal transduction. At a static state, the vesicles are retained in the highly dense actin network. Prior to exocytosis, the dense actin network must disassemble or largely be organized. Actin networks are formed in vitro which retain synaptic vesicles prepared from rat cerebral cortex. Dynamic behaviors of synaptic vesicles are measured by the dynamic light scattering method. The D-app values of synaptic vesicles confined in actin network became less than 1/4 those of free vesicles. The motions of synaptic vesicles are substantially restricted. This means that synaptic vesicles which are liberated from the actin network by detachment of synapsin 1 molecules are still trapped in the cage-like space of actin filaments. The actin network is disassembled by the actin severing protein, gelsolin, which is activated in the presence of mu M level free Ca2+ ions. The D-app(v) values of synaptic vesicles after severing the actin network return to those of free vesicles in the presence of short actin fragments. A molecular model for exocytosis in the synaptic terminal is constructed on the basis of these results.
This paper considers the analog neural solution of the combinatorial optimization problem. The solution method is analyzed based on the Lagrange multiplier method for the continuous relaxation problem of 0-1 integer p...
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This paper considers the analog neural solution of the combinatorial optimization problem. The solution method is analyzed based on the Lagrange multiplier method for the continuous relaxation problem of 0-1 integer programming. It is shown that the solution process can be interpreted as the solution by the gradient method for the saddle point of the Lagrange function. An improved Hopfield net is derived from the formulation as the pure integer programming. The elastic net and the generalized deformable model are derived from the mixed integer programming problem. Based on those results, an interpretation of the deterministic annealing is derived from the viewpoint of mathematical programming. It is shown that the Lagrange function can work as the Lyapunov function for the solution process and the convergence property of those neural methods of solution is analyzed.
We have developed a machine discovery system BONSAI which receives positive and negative examples as inputs and produces as a hypothesis a pair of a decision tree over regular patterns and an alphabet indexing. This s...
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In this paper an adaptive way of mainsteam temperature control is proposed for a thermal power plant at the ramping stage. A physical model of the super-heater system is built up based on the experimental knowledge on...
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In this paper an adaptive way of mainsteam temperature control is proposed for a thermal power plant at the ramping stage. A physical model of the super-heater system is built up based on the experimental knowledge on actual thermal power plants. The model yields a continuous time nonlinear system with several unknown varying parameters. A quick identification method is Introduced to estimate online the model parameters. The identified model is used for designing a control signal to raise the mainsteam temperature at the outlet of the super- heater along a reference curve. In this way, an adaptive control of thermal power plant can be realized in the framework of MRACS. The effectiveness of the method has been confirmed through simulation studies.
High spectrum efficiency is promised by reuse partitioning in a cellular system. We propose an improved algorithm for self-organized reuse partitioning (SORP), a distributed dynamic channel assignment scheme, in order...
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High spectrum efficiency is promised by reuse partitioning in a cellular system. We propose an improved algorithm for self-organized reuse partitioning (SORP), a distributed dynamic channel assignment scheme, in order to obviate the need for broadcasting transmit power level information of each mobile terminal. The concept of the improved scheme is simple: a mobile terminal with low transmit power uses a low numbered channel throughout the system. Reuse partitioning can be achieved owing to such a channel segmentation. The algorithm is designed to realize the channel segmentation without the broadcasting of the transmit power level. computer simulation results show that a high capacity and short delay time in finding an appropriate channel can be obtained. Furthermore, a higher capacity can be obtained by introducing quality based power control into this algorithm.
Designs a control system for shaping the low frequency characteristics of a new type of hydraulic speaker, so as to-make a louder sound at low frequencies than the usual type of speaker. In this design, the authors us...
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Designs a control system for shaping the low frequency characteristics of a new type of hydraulic speaker, so as to-make a louder sound at low frequencies than the usual type of speaker. In this design, the authors use H/sub /spl infin// control design method, which is capable of treating both frequency shaping and robust stabilization. The authors also illustrate the validity of the resulting controller by showing some experimental results.
This work shows a new method for parameter estimation in the NARMAX (Non-linear AutoRegressive Moving Average with eXogenous inputs) model using neural computation. A three-layered feedforward neural network is traine...
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This work shows a new method for parameter estimation in the NARMAX (Non-linear AutoRegressive Moving Average with eXogenous inputs) model using neural computation. A three-layered feedforward neural network is trained to describe a system. The actual input of the system and the computed output of the network are used as the input data set of the network for training. Parameters in the NARMAX model are calculated from the values of weights and the sigmoid functions in neural units expanded in a series by Maclaurin's formula. The structure of the NARMAX model is finally determined by the Baysian information criteria. The proposed method, therefore, requires no prior knowledge of the structure of the NARMAX model.
The plane problem of an infinite plate containing an inclusion is considered. The singular stress field around the inclusion corner tip is expressed as a sum of two independent types: a symmetric type with a stress si...
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The plane problem of an infinite plate containing an inclusion is considered. The singular stress field around the inclusion corner tip is expressed as a sum of two independent types: a symmetric type with a stress singularity 1/r(I-lambda1) and a skew-symmetric type with a stress singularity 1/r(I-lambda2). The intensities of the symmetric and skew-symmetric singular stress fields are defined in terms of constants K(I,lambda1) and K(II,lambda2), respectively. The body force method is used to calculate the values of K(I,lambda1) and K(II,lambda2). In numerical analysis, basic density functions of the body forces are introduced to characterize the stress singularity at the inclusion corner. The advantages of this technique are the high accuracy of results, due to the smoothness of the unknown weight functions, and the presence of the direct relation between the values of K(I,lambda1), K(II,lambda2) and the values of unknown weight functions at the corner tip.
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