小波变换在膜蛋白跨膜螺旋区段预测中的应用

膜蛋白跨膜螺旋区段的预测是当前生物信息学研究的一个重要领域.提出了一种基于离散小波变换的预测膜蛋白跨膜螺旋区段数目和位置的方法.以PDB代码为1KQG的膜蛋白为例,描述了该方法对跨膜螺旋区段的数目和位置的预测分析过程.为了测试方法的实际效果,从最新的MPtopo数据库中随机抽取80条三维结构已知的膜蛋白序列作为测试集(含325个跨膜螺旋区),采用该方法对跨膜螺旋区段进行预测,其中308个跨膜螺旋区被准确预测到,预测准确率为96.3%.并且按照膜蛋白的功能和类型,把80条序列划分成13组,对每一组膜蛋白序列进行跨膜螺旋区段预测,达到了令人满意的结果.     

环境自然激励下一种结构损伤在线识别方法

提出了一种环境自然激励下工程结构损伤识别方法,该法仅仅通过结构的输出数据识别结构的损伤．首先在结构完好的情况下,通过结构的输出数据识别外部统计参数;然后在结构损伤情况下,通过结构的输出数据识别结构的损伤分布函数．给出了识别结构损伤的理论模型和计算方法．数值仿真结果表明,该方法具有较高的辨别率和计算精度,能够使用在桥梁和建筑的健康监测中．     

Comparison of biosequences

Homology and distance measures have been routinely used to compare two biological sequences, such as proteins or nucleic acids. The homology measure of Needleman and Wunsch is shown, under general conditions, to be equivalent to the distance measure of Sellers. A new algorithm is given to find similar pairs of segments, one segment from each sequence. The new algorithm, based on homology measures, is compared to an earlier one due to Sellers.     

Some operations research methods for analyzing protein sequences and structures

The operations research is probably one of the most successful field of applied mathematics used in economics, physics, chemistry, almost everywhere where one has to analyze huge amounts of data. Lately, these techniques of operations research were introduced in biology, especially in the protein analysis area to support biologists. The fast growth of protein data makes operations research an important issue in bioinformatics, a science which lays on the border between computer science and biology. This paper gives a short overview of the operations research techniques currently used to support structural and functional analysis of proteins.     

Some operations research methods for analyzing protein sequences and structures

Operations Research is probably one of the most successful fields of applied mathematics used in Economics, Physics, Chemistry, almost everywhere one has to analyze huge amounts of data. Lately, these techniques were introduced in biology, especially in the protein analysis area to support biologists. The fast growth of protein data makes operations research an important issue in bioinformatics, a science which lays on the border between computer science and biology. This paper gives a short overview of the operations research techniques currently used to support structural and functional analysis of proteins. Received: February 2006, Revised: May 2006     

Parallel Schur complement method for large-scale systems on distributed memory computers

The Schur complement method, also known as substructuring technique, was widely used in structural mechanics to solve large-scale systems with limited memory computers for more than three decades [J.S. Przemieniecki, AIAA J. 1 (1963) 138]. Currently, due to developments in computer technology, the available on-board memory has increased considerably. Despite the existence of these high-memory systems, the Schur complement method still finds its applications in structural mechanics through parallel computing. When developing a computer program, the Schur method has a significant book-keeping load in comparison to other parallel algorithms used, e.g., Schwarz alternating domain decomposition method [H.A. Schwarz, Gesammelte Mathematiche Abhandlungen, vol. 2, Springer, Berlin, 1890, p. 133]. This results in memory usage. Although parallel systems are used, global coefficient matrices require a large amount of memory. Therefore, significant memory is reserved for the solution of large-scale systems. In this paper, we present an efficient algorithm for the assemblage and solution of interface equations which facilitates the solution of large-scale systems via the Schur complement method on multiple instruction multiple data (MIMD) distributed memory architectures. In this method, we assemble the subdomain and interface coefficient matrices in such a manner that the memory requirements decrease significantly, resulting in the solution of large-scale systems with reasonable memory usage. The computer program is tested on distributed memory architectures with UNIX, WINDOWS NT, and LINUX operating systems.     

基于统计方法的汽车行驶工况构建

基于福州市汽车路况数据,研究汽车行驶工况构建方法.用运动学片段分析法对GPS车速划分运动学片段,构建14个与速度相关的运动学特征.采用主成分分析和k均值聚类对运动学片段进行特征分析和分类.针对分类的运动学片段分别采用MH抽样算法,抽取新的速度时间序列,以划分新的运动学片段.基于短行程法对聚类的运动学片段和抽样的运动学片...     

Experiments on the practical I/O efficiency of geometric algorithms: Distribution sweep versus plane sweep

We present an extensive experimental study comparing the performance of four algorithms for the following orthogonal segment intersection problem: given a set of horizontal and vertical line segments in the plane, report all intersecting horizontal-vertical pairs. The problem has important applications in VLSI layout and graphics, which are large-scale in nature. The algorithms under evaluation are our implementations of distribution sweep and three variations of plane sweep. Distribution sweep is specifically designed for the situations in which the problem is too large to be solved in internal memory, and theoretically has optimal I/O cost. Plane sweep is a well-known and powerful technique in computational geometry, and is optimal for this particular problem in terms of internal computation. The three variations of plane sweep differ by the sorting methods (external versus internal sorting) used in the preprocessing phase and the dynamic data structures (B-tree versus 2-3-4-tree) used in the sweeping phase. We generate the test data by three programs that use a random number generator while producing some interesting properties that are predicted by our theoretical analysis. The sizes of the test data range from 250 thousand segments to 2.5 million segments. The experiments provide detailed quantitative evaluation of the performance of the four algorithms, and the observed behavior of the algorithms is consistent with their theoretical properties. This is, to the best of our knowledge, the first experimental algorithmic study comparing the practical performance between external-memory algorithms and conventional algorithms with large-scale test data.     

An Artificial Immune System for Clustering Amino Acids in the Context of Protein Function Classification

This paper addresses the classification task of data mining (a form of supervised learning) in the context of an important bioinformatics problem, namely the prediction of protein functions. This problem is cast as a hierarchical classification problem. The protein functions to be predicted correspond to classes that are arranged in a hierarchical structure (this takes the form of a class tree). The main contribution of this paper is to propose a new Artificial Immune System that creates a new representation for proteins, in order to maximize the predictive accuracy of a hierarchical classification algorithm applied to the corresponding protein function prediction problem.      

Adaptive surrogate-based design optimization with expected improvement used as infill criterion

A prominent advantage of using surrogate models in structural design optimization is that computational effort can be greatly reduced without significantly compromising model accuracy. The essential goal is to perform the design optimization with fewer evaluations of the typically finite element analysis and ensuring accuracy of the optimization results. An adaptive surrogate based design optimization framework is proposed, in which Latin hypercube sampling and Kriging are used to build surrogate models. Accuracy of the models is improved adaptively using an infill criterion called expected improvement (EI). It is the anticipated improvement that an interpolation point will lead to the current surrogate models. The point that will lead to the maximum EI is searched and used as infill points at each iteration. For constrained optimization problems, the surrogate of constraint is also utilized to form a constrained EI as the corresponding infill criterion. Computational trials on mathematical test functions and on a three-dimensional aircraft wing model are carried out to test the feasibility of this method. Compared with the traditional surrogate base design optimization and direct optimization methods, this method can find the optimum design with fewer evaluations of the original system model and maintain good accuracy.     

Free vibration and buckling analysis of plates using B-spline wavelet on the interval Mindlin element

A finite element method (FEM) of B-spline wavelet on the interval (BSWI) is used in this paper to solve the free vibration and buckling problems of plates based on Reissner–Mindlin theory. By aid of the high accuracy of B-spline functions approximation for structural analysis, the proposed method could obtain a fast convergence and a satisfying numerical accuracy with fewer degrees of freedoms (DOF). The numerical examples demonstrate that the present BSWI method achieves the high accuracy compared to the exact solution and others existing approaches in the literatures. The BSWI finite element has potential to be used as a numerical method in analysis and design.     

Improved starting methods for two-step Runge–Kutta methods of stage-order p−3

In [Japan JIAM 19 (2002) 227], Jackiewicz and Verner derived formulas for, and tested the implementation of two-step Runge–Kutta (TSRK) pairs. For pairs of orders 3 and 4, the error estimator accurately tracked the exact local truncation error on several nonlinear test problems. However, for pairs designed to achieve order 8, the results appeared to be only of order 6.This deficiency was identified in [SIAM J. Numer. Anal. 34 (1997) 2087 [2]] by Hairer and Wanner who used B-series to formulate a complete set of order conditions for TSRK methods, and showed that if the order of a TSRK method is at least two greater than its stage-order, special starting values are necessary for the first step.In forthcoming paper [Starting methods for two-step Runge–Kutta methods of stage-order 3 and order 6, J. Comput. Appl. Math.], Verner showed that such starting values have to be perturbed from their asymptotically correct values to include errors of precisely the form which the selected TSRK formula is designed to propagate from step to step. For TSRK methods of order 6, it was shown that a complementary set of Runge–Kutta methods could be utilized to obtain suitably perturbed starting values, and that each method of the set could be derived by solving appropriately modified order conditions directly. The design used there required solving an intricate polynomial equation. Here, the design is improved, and new starting methods are simpler to derive, and perhaps may lead to starting methods for TSRK methods of order 8.     

基于重构边界光滑离散剪切间隙法的复合材料层合板自由振动分析

重构边界光滑离散剪切间隙（RES-DSG3）法,利用边界光滑技术将域积分转化为沿光滑域边界的边界积分,结合基于全局坐标系的非等参离散剪切间隙（DSG）法,避免了坐标映射和Jacobi矩阵的计算,同时克服了“剪切自锁”现象,提高了计算的精度。基于一阶剪切变形理论,采用该文给出的方法,从不同材料参数、边厚比、边界条件等几个方面对复合材料层合板自由振动固有频率进行了数值分析,通过典型算例的计算,验证了该方法的可行性和有效性。     

Genetic algorithm based wireless vibration control of multiple modal for a beam by using photostrictive actuators

The lanthanum-modified lead zirconate titanate (PLZT) actuator, which are capable of converting photonic energy to mechanical motion, have great potential in applications of remote structural vibration control of smart structures and machines. In this paper, a novel genetic algorithm based controlling algorithm for multi-modal vibration control of beam structures via photostrictive actuators is proposed. Two pairs of photostrictive actuators are laminated with the beams and the alternation of light irradiation is in accordance with the changing of the corresponding modal velocity direction. The modal force indexes for beams with different boundary conditions are derived and a binary-coded GA is used to optimize the locations and sizes of photostrictive actuators to maximize the modal force index and guarantee the overall modal force index induced by two pairs of photostrictive actuators is positive. The control effect of multiple vibration modes of beams under irradiation of set/variable light intensity is analyzed. Numerical results demonstrate that the method is robust and efficient, and the use of strategically positioned actuator patches can effectively control the first two bending modes that dominate the structural vibration.     

A collocation method for parabolic quasilinear problems on general domains

A collocation method is described which obtains approximate solutions to quasilinear parabolic problems on a general two-dimensional domain. The method is best suited for obtaining robust solutions to smooth problems with the accuracy required in most engineering applications. The solution is obtained in terms of a finite element, B-spline basis. An interactive computer graphics system is used for both problem formulation and the subsequent display of selected results. The theoretical basis for the method is discussed, and some typical computational results are presented.     

Machine learning aided static structural reliability analysis for functionally graded frame structures

A novel machine learning aided structural reliability analysis for functionally graded frame structures against static loading is proposed. The uncertain system parameters, which include the material properties, dimensions of structural members, applied loads, as well as the degree of gradation of the functionally graded material (FGM), can be incorporated within a unified structural reliability analysis framework. A 3D finite element method (FEM) for static analysis of bar-type engineering structures involving FGM is presented. By extending the traditional support vector regression (SVR) method, a new kernel-based machine learning technique, namely the extended support vector regression (X-SVR), is proposed for modelling the underpinned relationship between the structural behaviours and the uncertain system inputs. The proposed structural reliability analysis inherits the advantages of the traditional sampling method (i.e., Monte-Carlo Simulation) on providing the information regarding the statistical characteristics (i.e., mean, standard deviations, probability density functions and cumulative distribution functions etc.) of any concerned structural outputs, but with significantly reduced computational efforts. Five numerical examples are investigated to illustrate the accuracy, applicability, and computational efficiency of the proposed computational scheme.     

Using data mining to identify structural rules in proteins

The progress in bioinformatics and biotechnology area has generated a huge amount of sequences that requires a detailed analysis. There are several data mining techniques that can be used to discovery patterns in large databases. This paper describes the development of a tool/methodology to extract hydrophobicity patterns/profiles that archives a specific secondary structure in proteins. The results indicate that association rules can be efficient method to investigate this kind of problem. This work contributes for two areas: prediction of protein structure and protein folding.     

Numerically optimal Runge–Kutta pairs with interpolants

Explicit Runge–Kutta pairs are known to provide efficient solutions to initial value differential equations with inexpensive derivative evaluations. Two criteria for selection are proposed with a view to deriving pairs of all orders 6(5) to 9(8) which minimize computation while achieving a user-specified accuracy. Coefficients of improved pairs, their stability regions and coefficients of appended optimal interpolatory Runge–Kutta formulas are provided on the author’s website (www.math.sfu.ca/~jverner). This note reports results of tests on these pairs to illustrate their effectiveness in solving nonstiff initial value problems. These pairs and interpolants may be used for implementation, or else to provide comparison targets for other new types of methods such as explicit general linear methods.