The Tree of Hubs Location Problem

This paper presents the Tree of Hubs Location Problem. It is a network hub location problem with single assignment where a fixed number of hubs have to be located, with the particularity that it is required that the hubs are connected by means of a tree. The problem combines several aspects of location, network design and routing problems. Potential applications appear in telecommunications and transportation systems, when set-up costs for links between hubs are so high that full interconnection between hub nodes is prohibitive. We propose an integer programming formulation for the problem. Furthermore, we present some families of valid inequalities that reinforce the formulation and we give an exact separation procedure for them. Finally, we present computational results using the well-known AP and CAB data sets.     

The capacitated single-allocation hub location problem revisited: A note on a classical formulation

In this paper a well-known formulation for the capacitated single-allocation hub location problem is revisited. An example is presented showing that for some instances this formulation is incomplete. The reasons for the incompleteness are identified leading to the inclusion of an additional set of constraints. Computational experiments are performed showing that the new constraints also help to decrease the computational time required to solve the problem optimally.     

Stochastic mechano-chemical kinetics of molecular motors: A multidisciplinary enterprise from a physicist’s perspective

A molecular motor is made of either a single macromolecule or a macromolecular complex. Just like their macroscopic counterparts, molecular motors “transduce” input energy into mechanical work. All the nano-motors considered here operate under isothermal conditions far from equilibrium. Moreover, one of the possible mechanisms of energy transduction, called Brownian ratchet, does not even have any macroscopic counterpart. But, molecular motor is not synonymous with Brownian ratchet; a large number of molecular motors execute a noisy power stroke, rather than operating as Brownian ratchet. We review not only the structural design and stochastic kinetics of individual single motors, but also their coordination, cooperation and competition as well as the assembly of multi-module motors in various intracellular kinetic processes. Although all the motors considered here execute mechanical movements, efficiency and power output are not necessarily good measures of performance of some motors. Among the intracellular nano-motors, we consider the porters, sliders and rowers, pistons and hooks, exporters, importers, packers and movers as well as those that also synthesize, manipulate and degrade “macromolecules of life”. We review mostly the quantitative models for the kinetics of these motors. We also describe several of those motor-driven intracellular stochastic processes for which quantitative models are yet to be developed. In part I, we discuss mainly the methodology and the generic models of various important classes of molecular motors. In part II, we review many specific examples emphasizing the unity of the basic mechanisms as well as diversity of operations arising from the differences in their detailed structure and kinetics. Multi-disciplinary research is presented here from the perspective of physicists.     

Accounting for the energies and entropies of kinesin’s catalytic cycle

When the processive motor protein kinesin walks along the biopolymer microtubule it can occasionally make a backward step. Recent single molecule experiments on moving kinesin have revealed that the forward-to-backward step ratio decreases exponentially with the load force. Carter and Cross (Nature 435, 308-312, 2005) found that this ratio tightly followed 802 × exp[−0.95F], where F is the load force in piconewtons. A straightforward analysis of a Brownian step leads to L/(2k _B T) as the factor in front of the load force, where L is the 8 nm stepsize, k _B is the Boltzmann constant, and T is the temperature. The factor L/(2k _B T) does indeed equal 0.95 pN⁻¹. The same analysis shows how the 802 prefactor derives from the power stroke energy G as exp[G/(2k _B T)]. There are indications that the power stroke derives from the entropically driven coiling of the 30 amino acid neck linker that connects the two kinesin heads. This idea is examined and consequences are deduced.     

输入—状态线性化控制永磁同步电动机混沌系统

采用输入-状态线性化方法控制永磁同步电动机系统中出现的混沌现象,利用输入-状态可线性化的能控条件和对合条件对施加控制的混沌系统进行判断,当满足线性化条件时,运用微分几何中的Lie导数和Lie括号运算将非线性系统模型转化为线性模型,然后对线性化后的系统设计控制器,使系统的三个状态变量均稳定的收敛于零,从而消除了混沌,仿真结果证明了该方法的有效性。     

基于神经网络模糊控制理论的转台伺服系统控制设计

针对三轴飞行仿真转台伺服系统非线性、模型不精确等特点,在分析转台系统结构的基础上,采用模糊PID控制的方法对转台伺服系统进行仿真控制,得到较好的控制效果。模糊控制控制规则的获得带有很大的人为因素,并且在控制过程中对规则采用查表法占用大量的内存。基于以上原因,设计了神经网络模糊控制器(NNSOC),利用神经网络控制自学习、自调整的能力,为模糊控制器提供自动生成控制规则的能力;同时由于神经网络具有联系记忆能力,可对未训练的样本做出决策。对NNSOC的控制效果进行了仿真。结果表明：其具有很好的动态性能和鲁棒性,对转台的控制效果良好。     

基于粒子群优化支持向量机康复下肢外骨骼的脑电控制研究

为解决失能人群自主移动的问题,脑机接口(brain computer interface, BCI)已广泛应用于外骨骼领域,但脑电(electroencephalogram, EEG)信号因信噪比低等原因导致识别率一直难以提高。为提高基于脑机接口下肢外骨骼的信号识别率,采用粒子群优化支持向量机(particle swarm optimization-support vector machine, PSO-SVM)算法提高脑电信号识别率,取得了86.52%的脑电信号识别率。首先建立共空间模式(common spatial pattern, CSP)数学模型对脑电信号进行特征提取,随后建立基于粒子群优化的支持向量机分类模型,优化脑电信号分类关键参数,将最终的实验数据与传统的支持向量机分类方法比较,最后进行算法的验证及下肢外骨骼实验。实验结果表明：经过粒子群优化的支持向量机分类准确明显高于传统支持向量机分类。所提出粒子群优化支持向量机对脑电信号的特征识别方法可实现运动想象(motor imagery, MI)的精确识别,为脑机接口技术在康复外骨骼领域的应用提供理论基础和技术支持。     

Collective alignment of polar filaments by molecular motors

We study the alignment of polar biofilaments, such as microtubules and actin, subject to the action of multiple molecular motors attached simultaneously to more than one filament. Focusing on a paradigm model of only two filaments interacting with multiple motors, we were able to investigate in detail the alignment dynamics. While almost no alignment occurs in the case of a single motor, the filaments become rapidly aligned due to the collective action of the motors. Our analysis shows that the alignment time is governed by the number of bound motors and the magnitude of the motors’ stepping fluctuations. We predict that the time scale of alignment is in the order of seconds, much faster than that reported for passive crosslink-induced bundling. In vitro experiments on the alignment of microtubules by multiple-motor covered beads are in qualitative agreement. We also discuss another mode of fast alignment of filaments, namely the cooperation between motors and passive crosslinks.     

Transport by Molecular Motors in the Presence of Static Defects

The transport by molecular motors along cytoskeletal filaments is studied theoretically in the presence of static defects. The movements of single motors are described as biased random walks along the filament as well as binding to and unbinding from the filament. Three basic types of defects are distinguished, which differ from normal filament sites only in one of the motors’ transition probabilities. Both stepping defects with a reduced probability for forward steps and unbinding defects with an increased probability for motor unbinding strongly reduce the velocities and the run lengths of the motors with increasing defect density. For transport by single motors, binding defects with a reduced probability for motor binding have a relatively small effect on the transport properties. For cargo transport by motors teams, binding defects also change the effective unbinding rate of the cargo particles and are expected to have a stronger effect.