Chiral discrimination of a helically organized crown ether array parallel to the helix axis of polyisocyanate

The asymmetric polymerization of 4′‐isocyanatobenzo‐18‐crown‐6 with the lithium amide of (S)‐(2‐methoxymethyl)pyrrolidine successfully proceeded to afford end‐functionalized poly(4′‐isocyanatobenzo‐18‐crown‐6) with (S)‐(2‐methoxymethyl)pyrrolidine (polymer 2 ). In the circular dichroism (CD) spectrum of 2 , a clear positive Cotton effect was observed in the range of 240–350 nm corresponding to the absorption of the polymer backbone, indicating that 2 partially formed a one‐handed helical structure, which was preserved by the chirality of (S)‐(2‐methoxymethyl)pyrrolidine bonding to the terminal end in 2 . In the titration experiments for the CD intensity of 2 in the presence of D ‐ and L ‐Phe·HClO₄ (where Phe is phenylalanine), a small but remarkable difference was observed in the amount of the chiral guest needed for saturation of the CD intensity and in the saturated CD intensity, indicating that the extremely stable, one‐handed helical part should exist in the main chain of 2 , which was not inverted even when the unfavorable chiral guest for the predominant helical sense, L ‐Phe·HClO₄, was added. In addition, helical polymer 2 exhibited a chiral discrimination ability toward racemic guests; that is, the guests were extracted from the aqueous phase into the organic phase with enantiomeric excess. The driving force of the chiral discrimination ability of 2 should certainly be attributed to the one‐handed helical structure in 2 . © 2005 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 325–334, 2006     

近红外光谱技术对闽南乌龙茶品种的识别研究

采用近红外光谱技术建立了一种快速无损的乌龙茶品种识别方法。收集闽南地区不同茶场中铁观音、黄金桂、本山、毛蟹与梅占等5个品种共210份具有代表性的乌龙茶样品,采集近红外光谱数据,选用1 100~1 300nm,1 640~2 498nm作为检测波长范围,利用主成分分析法(principal component analysis,PCA)建立模型,并在实验过程中比较多元散射校正(multiplicative scatter correction,MSC)与标准正态变量校正(standard normal variate,SNV)两种数据预处理方法对模型的影响。实验结果表明,多元散射校正对模型的影响优于标准正态变量校正,对校正集的识别准确率达到了96%,对预测集中样品的识别准确率达到了90%。实验结果证明了采用近红外光谱技术可以快速无损识别闽南地区乌龙茶,具有较强的实用价值和推广价值。     

Ambiguous Discrimination of General Quantum Operations

We consider the problem of discriminating general quantum operations. Using the definition of mapping operator to vector, and by some calculating skills, we derive an explicit formulation as a new bound on the minimum-error probability for ambiguous discrimination between arbitrary m quantum operations. This formulation consists only of Kraus-operators, the dimension, and the priori probabilities of the discriminated quantum operations, and is independent of input states. To some extent, we further generalize the bounds on the minimum-error probability for discriminating mixed states to quantum operations.     

Demixing of severely overlapped H NMR resonances and interpretation of anomalous intensity pattern of dipolar coupled A3 spins in a weakly aligning medium

The increasing scientific and industrial interest towards metabonomics takes advantage from the high qualitative and quantitative information level of nuclear magnetic resonance (NMR) spectroscopy. However, several chemical and physical factors can affect the absolute and the relative position of an NMR signal and it is not always possible or desirable to eliminate these effects a priori. To remove misalignment of NMR signals a posteriori, several algorithms have been proposed in the literature. The icoshift program presented here is an open source and highly efficient program designed for solving signal alignment problems in metabonomic NMR data analysis. The icoshift algorithm is based on correlation shifting of spectral intervals and employs an FFT engine that aligns all spectra simultaneously. The algorithm is demonstrated to be faster than similar methods found in the literature making full-resolution alignment of large datasets feasible and thus avoiding down-sampling steps such as binning. The algorithm uses missing values as a filling alternative in order to avoid spectral artifacts at the segment boundaries. The algorithm is made open source and the Matlab code including documentation can be downloaded from www.models.life.ku.dk.     

An efficient statistics-based method for the automated detection of sperm whale clicks

In this paper, we present a new method for the automated detection of sperm whale regular clicks and creaks based on statistical computations. In the first stage, a spectrogram is computed from the input waveform, followed by a noise normalisation process. A frequency domain filter is then applied, and the energy accumulated in each time frame is calculated. Two-second time-windows are then classified as containing either regular clicks, creaks, or noise based on statistical parameters using a neural network classifier. Finally, previously obtained statistical parameters are used to implement an energy-based detection criterion for the classified time-windows. Individual regular clicks and creaks are isolated by linking contiguous detected time frames. The proposed method was tested on five recordings of sperm whale sounds. Comparison of the detection performances to hand-labelled regular clicks and creaks revealed that this method outperforms two recently reported waveform-based methods when working with the same recordings files. An average percentage of detection of 86.97% was attained for the set of files. This method consumes also little computation time.     

Development of highly potent chiral discrimination methods that solve the problems of the diastereomer method

The development of highly potent chiral discrimination methods that solve the problems of the diastereomer method, in which it is impossible to discriminate the diastereomers having chiral centers separated by more than four bonds, is described. On the basis of the results obtained, a new hypothesis, Induced Chiral Fields that the achiral reversed phase can provide chiral fields depending on the structures of the eluents, is proposed to explain the significant results of separation of the diastereomers derived from newly developed chiral and fluorescent labeling reagents and optical isomers by reversed-phase HPLC, which was hitherto impossible.     

Year Discrimination of Mild Aroma Chinese Liquors Using Three-Dimensional Fluorescence Spectroscopy Combined with Parallel Factor and Neural NetworkSCIEI北大核心CSCD

Three-dimensional fluorescence spectroscopy coupled with parallel factor analysis and neural network was applied to the year discrimination of mild aroma Chinese liquors. The excitation-emission fluorescence matrices (EEMs) of 120 samples with various years were measured by FLS920 fluorescence spectrometer. The trilinear decomposition of the data array was performed and the loading scores of and the excitation-emission profiles of four components were also obtained. The scores were employed as the inputs of the BP neural networks and the PARAFAC-BP identification model was constructed. 10 samples were collected from 10, 20 and 30 years of liquors respectively, and 30 samples were selected as the test sets. The remaining 90 samples were used as the training sets to build the training model. The year prediction of unknown samples was also carried out, and the prediction accuracy was 90%, 100% and 100%, respectively. Meanwhile, the discrimination analysis method and the multi way partial least squares discriminant analysis were compared, namely PARAFAC-BP and NPLS-DA. The results indicated that parallel factor combined with the neural network (PARAFAC-BP) has higher prediction accuracy. The proposed method can effectively extract the spectral characteristics, and also reduce the dimension of the input variables of neural network. A good year discrimination result was finally achieved.     

Extended Fan's Algebraic Method and Its Application to KdV and Variant Boussinesq Equations

An extended Fan's algebraic method is used for constructing exact traveling wave solution of nonlinear partial differential equations. The key idea of this method is to introduce an auxiliary ordinary differential equation which is regarded as an extended elliptic equation and whose degree r is expanded to the case of r>4. The efficiency of the method is demonstrated by the KdV equation and the variant Boussinesq equations. The results indicate that the method not only offers all solutions obtained by using Fu's and Fan's methods, but also some new solutions.     

提高综合滤波器鉴别率的一种有效方法

提出一种提高综合滤波器鉴别率的有效方法，其做法是：对样本集在等相关峰条件下求解综合滤波器的同时，使样本集的互补样本满足零件相关峰条件，此方法把训练模式类同所有其它模式类在映射空间的距离拉大，有效地提高了综合滤波器的鉴别率，以取自同一手指纹为样本集，求解综合鉴别函数后，建立了指纹的实时模式识别系统，实验结果表明本文提出的改进方法对提高综合滤波器的鉴别率是非常有效的。     

鉴别玉米杂交种纯度的近红外光谱分析技术研究

以不同产地和年份的农华101(NH101)玉米杂交种和母本种子为对象,研究了鉴别玉米杂交种子纯度的近红外光谱分析方法。 光谱采集时间跨度达10个月,运用傅里叶变换(FT)近红外光谱仪器,在不同季节用23天(分五个时间段)采集了这些样品共920条玉米单子粒近红外漫反射光谱。 全部原始光谱用移动窗口平均、 一阶差分导数和矢量归一化进行预处理,使用主成分分析(PCA)方法和线性判别分析(LDA)方法降维,采用仿生模式识别(BPR)方法建立模型。 通过对光谱预处理校正光谱失真,使样品光谱集在特征空间分布的范围收缩,相对距离增大了近70倍,实现了母本和杂交种子的鉴别。 通过代表性样品的选择,提高了模型对光谱采集时间、 地点、 环境等条件变动的应变能力,也提高了模型对样品种子制种时间与地点变动的应变能力,增强了模型的稳健性,使测试集玉米单子粒杂交种和母本种子的平均正确识别率达到95%以上,而平均正确拒识率也达到85%以上。