双序列比对基础和应用实例

首先介绍序列比对的分子生物学基础,即核酸序列基本单元核苷酸和蛋白质序列基本单元氨基酸。文中以精心设计的图表列出四种核苷酸和二十种氨基酸的名称、性质和分类。第2节简述序列比对基础,包括相似性和同源性基本概念、整体比对和局部比对、点阵图方法、动态规划和启发式算法、计分矩阵和空位罚分,以及常用软件和分析平台。第3节介绍核酸序列比对中常用计分矩阵DNAfull,蛋白质序列比对中常用计分矩阵BLOSUM62和PAM250。第4-8节则以血红蛋白、多肽毒素、植物转录因子、癌胚抗原和唾液酸酶为例,介绍双序列比对的具体应用。通过这些实例,说明如何选择分析平台和比对程序、如何设置计分矩阵和空位罚分,如何分析比对结果及其生物学意义。文末进行简要总结。

Quantum Logic Networks for Probabilistic Teleportation of an Arbitrary Three-Particle State

The scheme for probabilistic teleportation of an arbitrary three-particle state is proposed. By using single qubit gate and three two-qubit gates, efficient quantum logic networks for probabilistic teleportation of an arbitrary three-particle state are constructed.

Security Analysis and Enhanced Design of a Dynamic Block Cipher

There are a lot of security issues in block cipher algorithm.Security analysis and enhanced design of a dynamic block cipher was proposed.Firstly,the safety of ciphertext was enhanced based on confusion substitution of S-box,thus disordering the internal structure of data blocks by four steps of matrix transformation.Then,the diffusivity of ciphertext was obtained by cyclic displacement of bytes using column ambiguity function.The dynamic key was finally generated by using LFSR,which improved the stochastic characters of secret key in each of round of iteration.The safety performance of proposed algorithm was analyzed by simulation test.The results showed the proposed algorithm has a little effect on the speed of encryption and decryption while enhancing the security.Meanwhile,the proposed algorithm has highly scalability,the dimension of S-box and the number of register can be dynamically extended according to the security requirement.

Acoustic design sensitivity analysis of structural sound radiation

This paper presents an acoustic design sensitivity(ADS)analysis on sound radiation of structures by using the boundary element method(BEM).We calculated the velocity distribution of the thin plate by analytical method and the surface sound pressure by Rayleigh integral,and expressed the sound radiation power of the structure in a positive definite quadratic form of the Hermitian with an impedance matrix.The ADS analysis of the plate was thus translated into the analysis of structure dynamic sensitivity and ...

Study on Complete Analysis of LRE Test Samples Based on PCA

Incomplete data samples have a serious impact on the effectiveness of data mining.Aiming at the LRE historical test samples,based on correlation analysis of condition parameter,this paper introduced principle component analysis(PCA)and proposed a complete analysis method based on PCA for incomplete samples.At first,the covariance matrix of complete data set was calculated;Then,according to corresponding eigenvalues which were in descending,a principle matrix composed of eigen-vectors of covariance matrix was made;Finally,the vacant data was estimated based on the principle matrix and the known data.Compared with traditional method validated the method proposed in this paper has a better effect on complete test samples.An application example shows that the method suggested in this paper can update the value in use of historical test data.

Independent Component Analysis Based Blind Adaptive Interference Reduction and Symbol Recovery for OFDM Systems

To overcome the inter-carrier interference （ICI） of orthogonal frequency division multiplexing （OFDM） systems subject to unknown carrier frequency offset （CFO） and multipath, this paper develops a blind adaptive interference suppression scheme based on independent component analysis （ICA）. Taking into account statistical independence of subcarriers＇ signals of OFDM, the signal recovery mechanism is investigated to achieve the goal of blind equalization. The received OFDM signals can be considered as the mixed observation signals. The effect of CFO and multipath corresponds to the mixing matrix in the problem of blind source separation （BSS） framework. In this paper, the ICA- based OFDM system model is built, and the proposed ICA-based detector is exploited to extract source signals from the observation of a received mixture based on the assumption of statistical independence between the sources. The blind separation technique can increase spectral efficiency and provide robustness performance against erroneous parameter estimation problem. Theoretical analysis and simulation results show that compared with the conventional pilot-based scheme, the improved performance of OFDM systems is obtained by the proposed ICA-based detection technique.

A Nonlinear Restoring Effect Study of Mooring System and its Application

Mooring system plays an important role in station keeping of floating offshore structures. Coupled analysis on mooring-buoy interactions has been increasingly studied in recent years. At present, chains and wire ropes are widely used in offshore engineering practice. On the basis of mooring line statics, an explicit formulation of single mooring chain/wire rope stiffness coefficients and mooring stiffness matrix of the mooring system were derived in this article, taking into account the horizontal restoring force, vertical restoring force and their coupling terms. The nonlinearity of mooring stiffness was analyzed, and the influences of various parameters, such as material, displacement, pre-tension and water depth, were investigated. Finally some application cases of the mooring stiffness in hydrodynamic calculation were presented. Data shows that this kind of stiffness can reckon in linear and nonlinear forces of mooring system. Also, the stiffness can be used in hydrodynamic analysis to get the eieenfrequencv of slow drift motions.

A Class of Biased Estimators Based on SVD in Linear Model

In this paper, a class of new biased estimators for linear model is proposed by modifying the singular values of the design matrix so as to directly overcome the difficulties caused by ill_conditioning in the design matrix. Some important properties of these new estimators are obtained. By appropriate choices of the biased parameters, we construct many useful and important estimators. An application of these new estimators in three_dimensional position adjustment by distance in a spatial coordiate surveys is given. The results show that the proposed biased estimators can effectively overcome ill_conditioning and their numerical stabilities are preferable to ordinary least square estimation.

Mixing matrix estimation of underdetermined blind source separation based on the linear aggregation characteristic of observation signals

Under the underdetermined blind sources separation(UBSS) circumstance,it is difficult to estimate the mixing matrix with high-precision because of unknown sparsity of signals.The mixing matrix estimation is proposed based on linear aggregation degree of signal scatter plot without knowing sparsity,and the linear aggregation degree evaluation of observed signals is presented which obeys generalized Gaussian distribution(GGD).Both the GGD shape parameter and the signals' correlation features affect the observation signals sparsity and further affected the directionality of time-frequency scatter plot.So a new mixing matrix estimation method is proposed for different sparsity degrees,which especially focuses on unclear directionality of scatter plot and weak linear aggregation degree.Firstly,the direction of coefficient scatter plot by time-frequency transform is improved and then the single source coefficients in the case of weak linear clustering is processed finally the improved K-means clustering is applied to achieve the estimation of mixing matrix.The proposed algorithm reduces the requirements of signals sparsity and independence,and the mixing matrix can be estimated with high accuracy.The simulation results show the feasibility and effectiveness of the algorithm.

AN NMF ALGORITHM FOR BLIND SEPARATION OF CONVOLUTIVE MIXED SOURCE SIGNALS WITH LEAST CORRELATION CONSTRAINS

Most of the existing algorithms for blind sources separation have a limitation that sources are statistically independent. However, in many practical applications, the source signals are non- negative and mutual statistically dependent signals. When the observations are nonnegative linear combinations of nonnegative sources, the correlation coefficients of the observations are larger than these of source signals. In this letter, a novel Nonnegative Matrix Factorization (NMF) algorithm with least correlated component constraints to blind separation of convolutive mixed sources is proposed. The algorithm relaxes the source independence assumption and has low-complexity algebraic com- putations. Simulation results on blind source separation including real face image data indicate that the sources can be successfully recovered with the algorithm.

Analyzing inspection results of Port State Control by using PCA

The paper applied Principal Components Analysis Method to analyze the PSC inspection results in the area of T-MOU and P-MOU. Set up the assessment of ship detention, the ships＇ main deficiencies of detentions were found out by the standardization of data processing and correlation matrix calculating. Provide the basis for shipping company to master the safety management focus and pass the PSC inspection.

Analysis of telescopic beam structure using couple of DOF technique and its application

Couple of DOF technique in FEM and the algorithm for equation group solution in the whole stiffness matrix is studied in this paper. A new procedure is developed for the analysis of telescope beam structure. This method can solve most of the complex structural problems in engineering practice. This method has been used in the FEM analysis of pile frame of muhifunetion drilling machine, which is designed and manufactured by our research group. The right analysis result can improves the design efficiency and the reliability of the structure and reduce the design cost.

Matrix Decomposition and Calculation of Chrestenson Spectra

Calculation of a variation of discrete Fourier transform.Chrestenson spectraof functions of n indeterminates over integer modulo m(composite integer),is con-sidered.Based on sparse matrix decomposition,two fast algorithms with complexityO(mnn∑ri=1pi)are given to calculate the Chrestenson spectra,where p1p2…p2 is theprime factor decomposition of m.

Singular value diagnosis in dam safety monitoring effect values

Based on the principal component analysis, principal components that have major influence on data variance are determined by the energy percentage method according to the correlation between monitoring effects. Then principal components are extracted through reconstructing multi effects. Moreover, combining with the optimal estimation theory, the method of singular value diagnosis in dam safety monitoring effect values is proposed. After dam monitoring information matrix is obtained, single effect state estimation matrix and multi effect fusion estimation matrix are constructed to make diagnosis on singular values to reduce false alarm rate. And the diagnosis index is calculated by PCA. These methods have already been applied to an actual project and the result shows the ability of the monitoring effect reflecting dam evolution behavior is improved as dam safety monitoring effect fusion estimation can take accurate identification on singular values and achieve data reduction, filter out noise and lower false alarm rate effectively.

Orthogonal arrays obtained by generalized difference matrices with g levels

Nowadays orthogonal arrays play important roles in statistics, computer science, coding theory and cryptography. The usual difference matrices are essential for the construction for many mixed orthogonal arrays. But there are also orthogonal arrays which cannot be obtained by the usual difference matrices, such as mixed orthogonal arrays of run size 60. In order to construct these mixed orthogonal arrays, a class of special so-called generalized difference matrices were discovered by Zhang (1989,1990,1993,2006) from the orthogonal decompositions of projection matrices. In this article, an interesting equivalent relationship between orthogonal arrays and the generalized difference matrices is presented and proved. As an application, a lot of new orthogonal arrays of run size 60 have been constructed.

Corrected-loss estimation for Error-in-Variable partially linear model

We consider an Error-in-Variable partially linear model where the covariates of linear part are measured with error which follows a normal distribution with a known covariance matrix. We propose a corrected-loss estimation of the covariate effect. The proposed estimator is asymptotically normal. Simulation studies are presented to show that the proposed method performs well with finite samples, and the proposed method is applied to a real data set.

Convergence and error estimate of cascade algorithms with infinitely supported masks in L_p(R^s)

The cascade algorithm plays an important role in computer graphics and wavelet analysis.In this paper,we first investigate the convergence of cascade algorithms associated with a polynomially decaying mask and a general dilation matrix in L p (R s) (1 p ∞) spaces,and then we give an error estimate of the cascade algorithms associated with truncated masks.It is proved that under some appropriate conditions if the cascade algorithm associated with a polynomially decaying mask converges in the L p-norm,then the cascade algorithms associated with the truncated masks also converge in the L p-norm.Moreover,the error between the two resulting limit functions is estimated in terms of the masks.

ADMISSIBLE ESTIMATES IN THE IMPORTANT CLASS OF ESTIMATES OF THE COVARIANCE MATRIX

Let X1,X2(where N>m)be independent Nm(μ,∑) random vectors, and putwhere T is upper- triangular with positive diagonal elements. The author considers the problemof estimating ∑,and restricts his attention to the class of estimates is any diagonal matrix and b* is any nonnegative constant} because it has the following attractive features:(a) Its elements are all quadratic forms of the sufficient and complete statistics (X, T).(b) It contains all estimates of the form(and), which constructa complete subclass of the class of nonnegative quadratic estimates (where X = (X1,…, XN)') for any strict convex loss function.(c)It contains all invariant estimates under the transformation group of upper-triangularmatrices.The author obtains the Characteristics for an estimate of the formof ∑ to be admissible in when the loss function is chosed as tr(∑-1∑-Ⅰ)2, and shows,by an example, that(and)is admissible in can not imply itsadmissibility in .

Calculation of the Mass of X（3872） by the Mandelstam Generalization of the Gell-Mann-Low Method

On the basis of assuming that the narrow state X（3872） is a molecule state consisting of D0 and D＊0, we apply the Mandelstam generalization of the Ge11-Mann-Low method to calculate the matrix element of quark current between the heavy meson states described by Bether-Salpeter wave function. In calculation of the matrix element of quark current the operator product expansion is used in order to include the nonperturbative contribution of the vacuum condensates. In this scheme we calculate the mass of X（3872）. We believe that this scheme is closer to QCD than the previous work.