变质量粒子系统的统计热力学公式

利用系综理论的一般原理,我们推导了变质量粒子系统的统计热力学公式。我们发现,由于粒子的质量艰密度相关,压强的表达式中将比通常的形式多出一项。然而,该项并不在能量的表达式中出现。应用新的热力学公式,我们计算奇异夸克物质的态方程,得到十分合理的结果。     

考虑碳排放成本的长江铁矿石运输研究

为降低钢铁企业采购和运输铁矿石的综合成本,考虑船型、航速和碳排放等因素,建立长江铁矿石运输的混合整数非线性规划模型。将模型中的非线性项转化为线性项,运用CPLEX求解器求解。针对CPLEX求解中大型规模算例的局限性,引入标准粒子群优化（particle swarm optimization, PSO）算法提高求解精度。针对标准PSO算法容易陷入局部最优的问题,提出一种基于自适应策略的改进PSO算法,动态调整惯性权重,提高算法的收敛性和全局寻优能力。通过数值实验发现,改进后的算法在全局寻优能力和收敛能力上有一定的提高。     

基于粒子群优化的神经网络实时交通信号配时

由于人工神经网络具有表征复杂输入输出系统的强大功能,将其用于城市道路交叉口的实时信号配时,是极有应用前景的尝试。文章采用三层人工神经网络建立城市道路交叉口信号配时模型,并把粒子群优化算法作为神经网络的学习算法。该算法具有极高的全局优化形态与计算效率。这种方法建立的模型将有助于降低交叉口的总延误,提高通行能力,使神经网络发挥更好的控制效果。     

英语情态动词研究

本教重对当代英语情态动词发展和应用过程中、语法界和教科书在其意义和用法上的分歧进行分析和计论，并提出如何在教学中处理这些分歧的建议。     

从情态补语的语境讲起

情态补语是汉语中特有的形式，雏语中没有对应的形式。因此，在对少数民族学生的汉语教学中，情态补语是一个绕不开的难点。论文从情态补语句的形式、意义以及训练方法入手，探讨了这一句型的教学规律。     

非球形粒子的检测与识别

激光相位多普勒技术 (PDA)是目前公认有效的多参数粒子测量技术之一 ,但是PDA对粒子的非球形特性极为敏感 .本文分析了粒子的非球形特性对PDA的影响 ,明确了PDA信号参数与粒子非球形特性的关系 ,表明非球形粒子条件下的PDA信号相位差是理想粒子条件下PDA信号相位差的无偏估计 .提出了基于对象分类识别的非球形粒子的检测方法 ,利用模糊模式识别中的群体识别技术 ,计算对象特性与参照物特性的贴近度 ,根据择近原则判断对象的类别及数量 .实验表明 ,不规则粒子的统计分类及其识别具有实用价值     

汉语句尾助词“了”英译中的“体”的相关分析——基于《骆驼祥子》两种英文译本的研究

以《骆驼祥子》两种英文译本为语言材料的翻译数据统计和比较分析表明：（1）句尾助词“了”并非“体”的标志；（2）在“状态的变化”解释不充分的语境中，必须考虑句尾助词“了”前的谓词的时间特征。谓词的起始性意义可能会促使译者选用具有“开始”意义的词进行显性翻译；终结性意义可能会促使译者选用完成体表达；（3）在对句尾助词“了”的“状态的变化”阐释中可以发现译者选用“now”等词汇手段，通过前后的对比突出状态的变化状况。     

Numerical and experimental investigations of human swimming motions

This paper reviews unsteady flow conditions in human swimming and identifies the limitations and future potential of the current methods of analysing unsteady flow. The capability of computational fluid dynamics (CFD) has been extended from approaches assuming steady-state conditions to consideration of unsteady/transient conditions associated with the body motion of a swimmer. However, to predict hydrodynamic forces and the swimmer’s potential speeds accurately, more robust and efficient numerical methods are necessary, coupled with validation procedures, requiring detailed experimental data reflecting local flow. Experimental data obtained by particle image velocimetry (PIV) in this area are limited, because at present observations are restricted to a two-dimensional 1.0 m² area, though this could be improved if the output range of the associated laser sheet increased. Simulations of human swimming are expected to improve competitive swimming, and our review has identified two important advances relating to understanding the flow conditions affecting performance in front crawl swimming: one is a mechanism for generating unsteady fluid forces, and the other is a theory relating to increased speed and efficiency.     

用分析力学方法研究质点在自由凹曲面上的下滑运动

用分析力学中的拉格朗日方程求解质点从可自由移动的凹曲面上下滑时的速度、加速度和时间,并举例加以应用,体现了用分析力学方法求解复杂问题的优越性．     

Multi-Objective Optimization of Water-Sedimentation-Power in Reservoir Based on Pareto-Optimal Solution

A multi-objective optimal operation model of water-sedimentation-power in reservoir is established with power-generation, sedimentation and water storage taken into account. Moreover, the inertia weight self-adjusting mechanism and Pareto-optimal archive are introduced into the particle swarm optimization and an improved multi-objective particle swarm optimization (IMOPSO) is proposed. The IMOPSO is employed to solve the optimal model and obtain the Pareto-optimal front. The multi-objective optimal operation of Wanjiazhai Reservoir during the spring breakup was investigated with three typical flood hydrographs. The results show that the former method is able to obtain the Pareto-optimal front with a uniform distribution property. Different regions (A, B, C) of the Pareto-optimal front correspond to the optimized schemes in terms of the objectives of sediment deposition, sediment deposition and power generation, and power generation, respectively. The level hydrographs and outflow hydrographs show the operation of the reservoir in details. Compared with the non-dominated sorting genetic algorithm-II (NSGA-II), IMOPSO has close global optimization capability and is suitable for multi-objective optimization problems. LI Hui, born in 1981, male, doctorate student. Supported by National Science Fund for Distinguished Young Scholars (No.50725929) and National Natural Science Foundation of China (No.50539060,50679052).