Theoretical and computational studies of vectorial processes in biomolecular systems

Efficient vectorial processes such as the transduction of bioenergy and signals are characteristics that strikingly distinguish living systems from inanimate materials. Recent developments in biophysical and biochemical techniques have provided new information about the structure, dynamics and interaction of biomolecules involved in vectorial life processes at multiple length and temporal scales. This wealth of data makes it possible to carry out theoretical and computational studied of key mechanistic questions associated with complex life processes at an unprecedented level. Using two “vectorial biomolecular machines”, myosin and cytochrome c oxidase, as examples, we discuss the identification of interesting and biologically relevant questions that require thorough theoretical analysis. Technical challenges and recent progress related to these theoretical investigations are briefly summarized     

在光敏性三元聚合物混合物中构造 多尺度有序图案

由多组分聚合物混合物所形成的多尺度有序结构能够展现出许多新奇的物理化学性质, 从而使其在材料工程领域具有十分重要的潜 在应用价值. 本文通过计算机模拟, 在光敏性不相容三元混合物体系中创建了多尺度有序结构. 通过调节光照区域和掩膜形状, 获得了棋盘形、箭靶状等十分独特的形貌, 并且这些结构可以在实验上通过在适当的时间淬火而稳定较长的时间. 详细探讨了组分比、掩膜宽度、间距以及光照强度对体系的影响, 从而为实现多尺度长程序花样薄膜的制备提供了一个简便的途径, 同时也为纳米器件的制备提供了一定的指导.     

锂离子电池多孔电极理论的回顾与新思考

本文总结了Newman多孔电极理论的基本内容,提出若干改进思路. 提出基于离子-空穴耦合传输机制描述浓电解质中的离子输运过程,在此基础上引入离子-电子耦合转移反应的思想处理电极材料中的离子传输问题,并通过计算嵌锂材料的离子扩散系数验证其合理性. 总结了描述多孔电极多尺度结构的相关理论和技术,表明均质化方法和基于结构重建的介观模拟方法均能给出比较合理的有效输运参数,从而提高多孔电极理论模拟结果的准确性.     

Retinex彩色图像增强理论的物理思考及其截断区间对图像质量的影响

指出了Retinex彩色图像增强理论的物理意义,在对数空间中,将原图像减去高斯函数与原图像的卷积,其物理本质是除去了原图像中的平滑的部分,突出了原图像中的快速变化的部分,而且高斯函数越尖锐,越是突出图像中的细节,高斯函数越平坦,图像色调保持得越好,多尺度Retinex综合了不同高斯函数与原图像进行卷积的优点。研究了多尺度Retinex标准差截断法,结果是,以多尺度Retinex处理后的图像强度在其平均值附近1倍标准差截断后再拉伸得到的图像,普遍好于以2倍、3倍标准差截断后再拉伸得到的图像。     

MULTI-SCALE NUMERICAL MODEL FOR SIMULATING CONCRETE MATERIAL BASED ON FRACTAL THEORY

A new multi-scale numerical model is presented using the fractal theory and adopting FEM to simulate the failure of concrete.The relation between the fractal box dimension in large scale and the damage to concrete in small scale is deduced.And the evolutionary process of elastic modulus and strength in small scale is given.Consequently,the multi-scale numerical model is proposed to describe the constitutive relation of concrete between small scale and large scale.A two-dimensional static analysis of a concrete block is performed by using this model and the calculation result is discussed.The propagation of cracks of the concrete block is also studied.     

Refined Composite Multi-Scale Reverse Weighted Permutation Entropy and Its Applications in Ship-Radiated Noise

Ship-radiated noise is one of the important signal types under the complex ocean background, which can well reflect physical properties of ships. As one of the valid measures to characterize the complexity of ship-radiated noise, permutation entropy (PE) has the advantages of high efficiency and simple calculation. However, PE has the problems of missing amplitude information and single scale. To address the two drawbacks, refined composite multi-scale reverse weighted PE (RCMRWPE), as a novel measurement technology of describing the signal complexity, is put forward based on refined composite multi-scale processing (RCMP) and reverse weighted PE (RWPE). RCMP is an improved method of coarse-graining, which not only solves the problem of single scale, but also improves the stability of traditional coarse-graining; RWPE has been proposed more recently, and has better inter-class separability and robustness performance to noise than PE, weighted PE (WPE), and reverse PE (RPE). Additionally, a feature extraction scheme of ship-radiated noise is proposed based on RCMRWPE, furthermore, RCMRWPE is combined with discriminant analysis classifier (DAC) to form a new classification method. After that, a large number of comparative experiments of feature extraction schemes and classification methods with two artificial random signals and six ship-radiated noise are carried out, which show that the proposed feature extraction scheme has better performance in distinguishing ability and stability than the other three similar feature extraction schemes based on multi-scale PE (MPE), multi-scale WPE (MWPE), and multi-scale RPE (MRPE), and the proposed classification method also has the highest recognition rate.     

槽道湍流近壁区多尺度输运特性研究

利用槽道湍流直接数值模拟的数据库和离散正交子波，对近壁湍流的多尺度输运特性进 行了研究. 通过在流向和展向分别进行子波多尺度分解，得到了近壁区湍动能在流向和展向 多尺度传输的不同性质，发现流向传输以能量的反传为主，而在展向能量存在明显的正传， 并且当过滤尺度较大时以正传为主. 近壁湍流能量传输的各向异性为进一步构造各向异 性大涡模拟亚格子模式提供了必要的参考.     

在线协同写作的人类动力学分析

对人类在线行为模式的探讨是近年来人类动力学研究的热点.基于维基百科数据,文章针对一类重要且普遍的在线行为--在线协同写作,进行时间统计特性分析和内容更新统计分析.实证显示在线协同写作时间间隔分布呈多尺度特征,1 min到30 min和30 min到24 h两个时间段上时间间隔分别服从指数为1.62和1.16的幂律分布,而大于24 h的时间间隔服从形如F(τ)∝τ^{－b－alog(τ)}的累积分布.分析表明 关键词： 在线协同写作 人类动力学 多尺度特征 维基百科     

A local error estimate of the method of multi-scale asymptotic expansions for elliptic problems with rapidly oscillatory coefficients

In this paper, on basis of [O.A. Oleinik, A.S. Shamaev, G.A. Yosifian, Mathematical Problems in Elasticity and Homogenization, North-Holland, Amsterdam, 1992], we present a local error estimate of the method of multi-scale asymptotic expansions for second order elliptic problems with rapidly oscillatory coefficients.     

Multivariate dynamic modeling for Bayesian forecasting of business revenue

Forecasting enterprise-wide revenue is critical to many companies and presents several challenges and opportunities for significant business impact. This case study is based on model developments to address these challenges for forecasting in a large-scale retail company. Focused on multivariate revenue forecasting across collections of supermarkets and product categories, hierarchical dynamic models are natural: these are able to couple revenue streams in an integrated forecasting model, while allowing conditional decoupling to enable relevant and sensitive analysis together with scalable computation. Structured models exploit multi-scale modeling to cascade information on price and promotion activities as predictors relevant across categories and groups of stores. With a context-relevant focus on forecasting revenue 12 weeks ahead, the study highlights product categories that benefit from multi-scale information, defines insights into when, how, and why multivariate models improve forecast accuracy, and shows how cross-category dependencies can relate to promotion decisions in one category impacting others. Bayesian modeling developments underlying the case study are accessible in custom code for interested readers.