稠杂环化合物的研究（XV）──6－取代－3－（1H－苯并三唑－1－亚甲基）－1，2，4－三唑并［3，4－b］－1，3，4－噻二唑的合成

研究了３－（１Ｈ－苯并三唑－１－亚甲基）－４－氨基－５－巯基－１，２，４－三唑与取代苯甲酸在三氯氧磷催化下的反应，制得１０种新的３－（１Ｈ－苯并三唑－１－亚甲基）－１，２，４．三唑并［３，４－ｂ］－１，３，４－噻二唑，通过元素分析、ＩＲ、￣１ＮＭＲ和ＭＳ确证了它们的结构并讨论了其波谱性质。     

Synthesis and structural characterization of cobalt(II) and zinc(II) complexes with 2-(indazol-1-yl)-2-thiazoline (TnInA). X-ray characterization of [CoCl2(TnInA)2] · C2H6O and [(M)(TnInA)2(H2O)2](NO3)2 (M = Co, Zn)

Several complexes of 2-(indazol-1-yl)-2-thiazoline (TnInA) with the divalent ions Co and Zn have been synthesized by the direct combination of the ligand and the metal chloride or nitrate hydrated salts in ethanol. These complexes have been characterized by a variety of physical–chemical techniques. Moreover, the structures of [CoCl₂(TnInA)₂] · C₂H₆O (1) and [(M)(TnInA)₂(H₂O)₂](NO₃)₂ (M = Co, 3; Zn, 4) were determined by single-crystal X-ray diffraction. In all the complexes, the ligand TnInA bonds to the metal ion through the indazole and thiazoline nitrogen atoms. In complex 1 the environment around the cobalt ion may be described as a distorted octahedron with two TnInA ligands and two chlorine ligands. Compounds 3 and 4 are isostructural with a distorted octahedral geometry around the metal center, being linked to two water molecules and two TnInA ligands. However, in complex [ZnCl₂(TnInA)] (2) the zinc atom is four-coordinated with a probable tetrahedral environment with two chloro ligands and one TnInA ligand bonded to the metal ion.     

Non-destructive and clean prediction of aviation fuel characteristics through Fourier transform-Raman spectroscopy and multivariate calibration

The combination of Fourier transform (FT)-Raman spectroscopy and partial least squares (PLS) regression is proposed to be used in off-line kerosene quality control. Here, six important physico-chemical properties have been studied: Abel flash point, initial boiling point (IBP), 10% of distilled sample, final boiling point (FBP), total percentage of aromatic compounds (% aromatics) and viscosity. The Raman spectra were obtained directly from standard 2 ml glass vials ( mm), using a Bruker RFS 100 FT-Raman spectrometer, equipped with a 1064 nm Nd:YAG laser and a Ge detector, in back-scattering mode and accumulating 25 scans (150 s acquisition time) with a laser power of 300 mW. All Raman spectra were unit normalized in order to avoid the influence of the laser power into the regression models. Different Raman shift spectral ranges have been evaluated, the 193.5-1688.1 cm⁻¹ region being the most satisfactory one. Corrected standard errors of prediction of 1.9, 2.3, 2.8 °C, 0.19 cSt and 0.7% were obtained for flash point, IBP, FBP, viscosity and % aromatics, respectively. The influences of the glass vials, sample positioning and laser power have been studied, as well.     

Preparation of polyaniline‐sulfate salt ­by emulsion and aqueous ­polymerization pathway without using ­protonic acid

Aniline was polymerized directly into polyaniline‐sulfate salt without using protonic acid in this work. Polyaniline‐sulfate salt was prepared by emulsion and aqueous polymerization pathways. The dopant i.e. sulfate ion in polyaniline‐sulfate salt was generated from ammonium persulfate which was used for oxidizing aniline. Ammonium persulfate acts both as oxidizing agent as well as protonating agent in the polymerization process of aniline to polyaniline salt. The efficiency of oxidizing and protonating power of ammonium persulfate is increased by the use of surfactant. The activity of ammonium persulfate is further increased by the use of sulfuric acid as protonic acid. It may be necessary to consider the effect of sulfate ion which is generated during the oxidation process of aniline in the chemical polymerization of aniline to polyaniline salt by ammonium persulfate either aqueous or emulsion polymerization pathway in the presence of protonic acid/functionalized protonic acid. Copyright © 2001 John Wiley & Sons, Ltd.     

Hyphenation of column liquid chromatography and Raman spectroscopy via a liquid-core waveguide: chemometrical elimination of spectral eluent background

In column liquid chromatography (LC) coupled to conventional Raman spectroscopy (RS) removal of the spectral background of the eluent is often demanding, because of the strong signals of the organic modifier. A new chemometrical method is proposed, called the eluent background subtraction (EBS) method, which can correct for small shape and intensity differences of the eluent spectra. The variations in the eluent spectra are modelled using principal component analysis (PCA). The PCA loading vectors are subsequently used for eluent background correction of the elution spectra of the analyte. The loading vectors are fitted under these spectra by an asymmetric least-squares method. This method was successfully applied under various experimental conditions and performed much better than conventional background correction methods. Analyte detectability was improved by (weighted) averaging of all elution spectra and smoothing via a p-spline function.     

Application de l'analyse spectrale autoregressive AU traitement de mesures de turbulence

The Autoregressive (AR) Spectral analysis (also called Maximum Entropy Method) is applied here to velocity turbulence measurements. The validity of such a spectral analysis is tested for classical turbulence data collected in a wind tunnel. The AR estimates are compared with classical Fourier estimates (average of short modified periodograms). Both Levinson's and Burg's algorithms are used for calculating the AR coefficient estimates, and Akaike's “FPE” criterion for choosing the length of the AR filter.Such a method shows much interest in processing some geophysical fluid dynamics phenomena which often are intermittent on a physical point of view. Power spectrum time evolution of some very short length (1 min.) data of oceanic turbulence — they cannot be analysed by Fourier techniques — is a fine example.

Abstract

L'Analyse Spectrale Autorégressive (AR) (dite aussi Méthode de l'Entropie Maximale) est appliquée ici à des mesures de turbulence de vitesse. La validité d'une telle analyse a été testée sur des données classiques de turbulence recueillies en soufflerie. On a comparé les estimations AR avec les estimations classiques (moyenne de courts périodogrammes modifiés). On a utilisé pour l'estimation des coefficients AR les algorithmes de Levinson et de Burg, et pour le choix de l'ordre du filtre AR le critère “FPE” d'Akaike.Ce genre de méthode présente un grand intérêt dans le cas du traitement de certains phénomènes de mécanique des fluides géophysiques qui sont souvent intermittents du point de vue physique. Le calcul de l'évolution spectrale de très courtes (1 mn) données de turbulence océanique en est un bon exemple (ces données ne peuvent être analysées par les techniques de Fourier).     

The a posteriori error estimates of Chebyshev–Petrov–Galerkin methods for second-order equations

In this paper, the a posteriori error estimates of Chebyshev–Petrov–Galerkin approximations are investigated. For simplicity, we choose the Poisson equation with Dirichlet boundary conditions to discuss the a posteriori error estimators, and deduce their efficient and reliable properties. Some numerical experiments are performed to verify the theoretical analysis for the a posteriori error estimators.     

A novel video abstraction method based on fast clustering of the regions of interest in key frames

Online video nowadays has become one of the top activities for users and has become easy to access. In the meantime, how to manage such huge amount of video data and retrieve them efficiently has become a big issue. In this article, we propose a novel method for video abstraction based on fast clustering of the regions of interest (ROIs). Firstly, the key-frames in each shot are extracted using the average histogram algorithm. Secondly, the saliency and edge maps are generated from each key-frame. According to these two maps, the key points for the visual attention model can be determined. Meanwhile, in order to expand the regions surrounding the key points, several thresholds are calculated from the corresponding key-frame. Thirdly, based on the key points and thresholds, several regions of interest are expanded and thus the main content in each frame is obtained. Finally, the fast clustering method is performed on the key frames by utilizing their ROIs. The performance and effectiveness of the proposed video abstraction algorithm is demonstrated by several experimental results.     

基于灰色聚类分析的风险评价方法研究——以江苏民间资本进入金融领域风险评价为例

运用灰色系统理论,结合AHP方法,建立灰色聚类分析模型,对风险进行评价,并以江苏民间资本进入金融领域风险评价为例进行研究.结果表明,民间资本进入金融领域的风险属于高风险范畴,其中进入风险中的产业风险和社会风险属于高风险,信用风险属于较高风险,政治风险属于中等风险.并针对上述风险的等级,提出了相应的政策建议.模型具有一定的实用价值,它对于正确认识民间资本进入金融领域的风险和有针对性地制定相应的政策措施具有一定的理论和现实意义.