利用提升小波的蛋白质相互作用特征提取

利用提升小波从蛋白质序列中提取出它们相互作用的频谱特征,经支持向量机训练学习后,用于预测蛋白质间的相互作用.模拟计算结果表明,在阳性数据和阴性数据平衡的前提下,利用提升小波获取的低维蛋白质相互作用特征向量可以得到较高预测精度.进一步阐述了不同物种的蛋白质相互作用网络有着不同特征,为了得到更准确的预测结果,需要利用不同的方法提取蛋白质相互作用的特征.     

Local Rules: Emergence on Organizational Landscapes

This paper proposes that the theory of local rules provides a model for explaining organizational behavior as an emergent property of a fitness landscape. While local rule theory has its genesis in evolutionary biology, this paper links it to work in computational mathematical organizational theory. It further proposes that there are conditions, characterized by coadaptation, under which rules will survive in relatively stable forms, and other conditions, characterized by competition, under which local rules will change. The paper then discusses how catastrophe analysis can provide insights into changing patterns of organizational interactions. A discussion of methodology outline shows developments in agent-based simulation modeling can contribute to the development of local rule theory.     

Numerical determination of the density profile of an inhomogeneous membrane: solution of the inverse vibration problem

Given one or more vibrational modes of a membrane, the free vibration equation can be applied to infer the mass surface density. This paper considers determining the surface density of an inhomogeneous membrane from digitized holographic projections (interferograms) of the modeshapes. Spatially discrete numerical models of the membrane surface are presented, which can be used to solve both forward and inverse vibration problems. The accuracy of the discrete models is examined for exactly solvable free vibration problems involving inhomogeneous membranes. For the solution of the inverse problem, error estimates are given for the mass surface density deduced from modeshape interferograms. The practicability of the method is investigated using simulated experimental data for membranes with composite and continuously inhomogeneous density profiles. Strategies are discussed for reducing errors in the reconstructed densities.     

一种新型四硫富瓦烯衍生物的合成与表征

以二硫化碳和金属钠为基础物质合成了四硫富瓦烯（TTF）锌的配合物（TTF）Zn（NBu4）2。利用该化合物与苯甲酰氯反应得到的稳定化合物C17H10O2S5在甲醇钠溶液中与2,3-二溴丙醇反应成功合成出目标化合物（一种新配体）,其化学组成为C6H6OS5。利用IR谱、^1HNMR谱及元素分析对此化合物进行了表征。     

分光光度法测定蒙药中痕量铅

采用双硫腙显色分光光度法测定蒙药中痕量铅,该方法具有简单、快速、灵敏等特点,用以测定蒙药中的痕量铅,获得了满意的结果.该方法线性范围为0.00-0.40μg/mL Pb2 ,相关系数0.9993.回收率95%-ll0%.     

单矢量水听器估计目标方位的方法与实验

为评估基于单矢量水听器的方位估计能力,在黄海海域对矢量水听器进行实验。矢量水听器吊放于接收船尾部,采用平均声强器和复声强器方位估计方法,并提出以概率密度值最大的方位角作为目标方位估计值的具体处理准则,对恒定方向、匀速行驶的目标船方位进行估计,并求出两种方法的方位估计误差。结果表明,水听器布放深度10 m时,对正横距离为0.42 km的航速10 kn的目标船,平均声强器方法的水平方位角估计误差18°,极角估计误差为5°,可以在离目标船最远1.17 km处估计其方位;复声强法的水平方位角估计误差为13°,极角估计误差为8°,可以在离目标船最远2.35 km处估计其方位。在有接收船的噪声干扰情况下,复声强器比平均声强器方法估计的方位更准确,可以对更远处的噪声源进行方位估计。     

基于纯方位的浅海距离特征量解算分析

目标辐射噪声的LOFAR图中的干涉条纹包含了目标的运动参数和环境信息。当LOFAR图中的干涉条纹模糊或缺失时,其中的目标距离信息将无法提取。对于匀速直线运动的声源目标,仅利用方位信息,通过构造距离特征量和目标方位的关系模型,给出了一种浅海估计距离特征量的补充方法。浅海数值仿真和实验验证表明了该方法的可行性和有效性。     

Nonlinear Fourier analysis of localized wave fields

Summary The Fourier transform (FT) has long served as an indispensable means for analysing wave motion described by linear evlution equations. The methods are well known and include not only mathematical analysis but also the analysis of data as well. In recent years new spectral methods have been developed for analysing nonlinear evolution equations. Such methods are generalizations of the FT to specific nonlinear wave systems and are referred to as the spectral or scattering transform (ST). Herein we use numerical procedures for applying the ST directly to the analysis of localized data described by the Kortewegde Vries (KdV) equation on the infinite interval,i.e. the Cauchy problem in shallow water. In this context we emphasize the importance of the direct spectral transform (DST) as a wave number domain representation of nonlinear data. The numerical methods discussed for the KdV equation should be extendible to the large class of systems considered by Ablowitzet al., Calogero and Degasperis. We give examples of the spectral analysis of nonlinear, computer-generated data.

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Riassunto La ben nota trasformata di Fourier (FT) è di uso commune per analizzare moti ondosi descritti da equazioni di evoluzione lineari. Negli ultimi anni sono stati sviluppati nouvi metodi (detti trasformate spettrali o di scattering, ST) per l'analisi di equazioni di evoluzione non lineari basati sulla generalizzazione della FT agli specifici sistemi ondosi non lineari. Qui usiamo procedimenti numerici per applicare la ST direttamente all'analisi di dati localizzati descritti dall'equazione di Korteweg-deVries nell'intervallo infinito, cioè al problema di Cauchy in acqua bassa. In questo contesto sottolineiamo l'importanza della trasformata specttrale diretta come rappresentazione nel campo dei numeri d'onda di dati non lineari. I metodi numerici discussi, che a titolo di esempio sono qui applicati all'analisi spettrale di dati non lineari generati dal calcolatore, hanno l'interessante possibilità di essere estendibili ai problemi piú generali di propagazione ondosa.

     

Sparse asymptotic minimum variance based bearing estimation algorithm for a single vector hydrophone

For underwater target detection using a single vector hydrophone, sparse asymptotic minimum variance(SAMV) method is used to estimate the target bearing. The SAMV discretizes the entire scanning space and the target bearing is located at the position of the discrete direction. The SAMV algorithm utilizes the sparsity of the spatial signal to improve the estimation performance of the target bearing. Background noise level(BNL) of the bearing estimation of SAMV algorithm is lower than those of the conventional beam forming(CBF)method and minimum variance distortionless response(MVDR) method for different signal noise ratios(SNRs). When the SNR is higher than 0 d B, the direction-finding error of this algorithm is less than 2°. Moreover, the SAMV algorithm has a better dimensional orientation resolution capability. The experimental results show that the SAMV algorithm gives a bearing and time recording map with a lower BNL, which effectively verifies the effectiveness of SAMV algorithm in terms of underwater target detection.