Elastically coupled molecular motors

We study the influence of filament elasticity on the motion of collective molecular motors. It is found that for a backbone flexibility exceeding a characteristic value (motor stiffness divided through the mean displacement between attached motors), the ability of motors to produce force reduces as compared to rigidly coupled motors, while the maximum velocity remains unchanged. The force-velocity-relation in two different analytic approximations is calculated and compared with Monte-Carlo simulations. Finally, we extend our model by introducing motors with a strain-dependent detachment rate. A remarkable crossover from the nearly hyperbolic shape of the Hill curve for stiff backbones to a linear force-velocity relation for very elastic backbones is found. With realistic model parameters we show that the backbone flexibility plays no role under physiological conditions in muscles, but it should be observable in certain in vitro assays. Received: 27 November 1997 / Revised: 20 February 1998 / Accepted: 27 March 1998     

具有外部输入和偏差的细胞神经网络的完全稳定性

本文证明了对于由两个细胞组成的细胞神经网络，外部输入和偏差不影响网络的稳定平衡点的存在性和完全稳定性．     

A note on the conservation law for continuous reflected processes and its application to queues with fluid inputs

In this note we provide a new derivation of a conservation law for stationary continuous reflected processes which arise in the context of fluid queueing models. This readily gives the so-called Little's law for fluid queues as a special case. We then apply the result to compute the Laplace transform of the stationary workload distribution for a queue with fluid ON-OFF inputs in terms of the Palm distribution associated with the beginning of ON periods. This revised version was published online in June 2006 with corrections to the Cover Date.     

Artificial synaptic behavior of the SBT-memristor

The synapse of human brain neurons is not only the transmission channel of information, but also the basic unit of human brain learning and information storing. The artificial synapse is constructed based on the Sr_(0.97)Ba_(0.03) TiO_(3-x)(SBT) memristor, which realizes the short-term and long-term plasticity of the synapse. The experiential learning and non-associative learning behavior in accordance with human cognitive rules are realized by using the SBT-memristor-based synapse. The process of synaptic habituation and sensitization is analyzed. This study provides insightful guidance for realization of artificial synapse and the development of artificial neural network.     

Strength and precision of neurotransmission at mammalian presynaptic terminals

Classically, the basic concept of chemical synaptic transmission was established at the frog neuromuscular junction, and direct intracellular recordings from presynaptic terminals at the squid giant presynaptic terminal have further clarified principles of neurotransmitter release. More recently, whole-cell patch-camp recordings from the calyx of Held in rodent brainstem slices have extended the classical concept to mammalian synapses providing new insights into the mechanisms underlying strength and precision of neurotransmission and developmental changes therein. This review summarizes findings from our laboratory and others on these subjects, mainly at the calyx of Held, with a particular focus on precise, high-fidelity, fast neurotransmission. The mechanisms by which presynaptic terminals acquire strong, precise neurotransmission during postnatal development are also discussed.     

基于抑制性突触可塑性的反馈神经回路兴奋性与抑制性动态平衡

大脑皮层的兴奋性与抑制性平衡是维持正常脑功能的前提, 而其失衡会诱发癫痫、帕金森、抑郁症等多种神经疾病, 因此兴奋性与抑制性平衡的研究是脑科学领域的核心科学问题. 反馈神经回路是脑皮层网络的典型连接模式, 抑制性突触可塑性在兴奋性与抑制性平衡中扮演关键角色. 本文首先构建具有抑制性突触可塑性的反馈神经回路模型; 然后通过计算模拟研究揭示在抑制性突触可塑性的调控下反馈神经回路的兴奋性与抑制性可取得较高程度的动态平衡, 并且二者的平衡对输入扰动具有较强的鲁棒性; 其次给出了基于抑制性突触可塑性的反馈神经回路兴奋性与抑制性平衡机理的解释; 最后发现反馈回路神经元数目有利于提高兴奋性与抑制性平衡的程度, 这在一定程度上解释了为何神经元之间会存在较多的连接. 本文的研究对于理解脑皮层的兴奋性与抑制性动态平衡机理具有重要的参考价值.     

A one-model approach based on relaxed combinations of inputs for evaluating input congestion in DEA

This paper provides a one-model approach of input congestion based on input relaxation model developed in data envelopment analysis (e.g. [G.R. Jahanshahloo, M. Khodabakhshi, Suitable combination of inputs for improving outputs in DEA with determining input congestion — Considering textile industry of China, Applied Mathematics and Computation (1) (2004) 263–273; G.R. Jahanshahloo, M. Khodabakhshi, Determining assurance interval for non-Archimedean ele improving outputs model in DEA, Applied Mathematics and Computation 151 (2) (2004) 501–506; M. Khodabakhshi, A super-efficiency model based on improved outputs in data envelopment analysis, Applied Mathematics and Computation 184 (2) (2007) 695–703; M. Khodabakhshi, M. Asgharian, An input relaxation measure of efficiency in stochastic data analysis, Applied Mathematical Modelling 33 (2009) 2010–2023]. This approach reduces solving three problems with the two-model approach introduced in the first of the above-mentioned reference to two problems which is certainly important from computational point of view. The model is applied to a set of data extracted from ISI database to estimate input congestion of 12 Canadian business schools.     

Quasistatic evolution of damage in an elastic body with random inputs

Abstract

A model for the quasistatic evolution of the motion of an elastic body which is subject to material damage is presented and analyzed. The model takes the form of an elliptic system for the displacements coupled with a parabolic inclusion for the damage field. In both the system and the inclusion the coefficient and input functions that are present are assumed to be stochastic processes dependent on a random variable. The existence of a weak solution to the model is established using a sequence of approximate problems and passage to a limit. Moreover, the weak solution is shown to be product measurable.     

Optimal input for identification versus sensitivity reduction of systems with large parameter variations

In this article, we present an algorithm leading to an optimal controller gain for the automatic regulation of a linear system (closed-loop policy) and to an optimal auxiliary input. This is used for the purpose of either system identification, resulting in the maximum sensitivity measure and thus increased accuracy (Refs. 1–25), or system sensitivity reduction, resulting in the minimum sensitivity measure and thus reliable operation (Refs. 26–46). These results, which are robust in terms of parameter variations, are developed without constraints on the input functions.