双波长相移光纤光栅的光谱特性及传感应用

建立了双波长相移光纤光栅的理论模型,对双波长相移光纤光栅的透射谱特性进行了数值仿真,结果表明透射波长间隔会分别随相移量、折射率调制深度和光栅长度的变化而有规律地增减.借助光纤布拉格光栅的法布里-珀罗腔谐振相位条件计算了透射峰间隔的表达式,该表达式得到的透射峰间距曲线与数值仿真得到的曲线相符合,验证了数值仿真结果的正确性.最后,在光栅透射谱波长间隔变化规律的基础上提出一种传感方案,并对光栅的温度传感特性进行分析,理论推导得到灵敏度约为60pm/℃.     

分子构象聚类中的K-means密度峰值搜索算法

分子构象的聚类是搜索分子动力学模拟轨迹中代表构象的主要方法。 它是分析复杂构象改变或分子间相互作用机制的关键步骤. 作为一种基于密度的聚类算法,密度峰值搜索算法因其聚类的准确度而被应用于分子聚类过程中. 但随着模拟时长的增长,密度峰值搜索算法较低的计算效率限制了其应用的可能. 本文提出K-means密度峰值搜索算法的聚类算法,它是密度峰值搜索算法在计算效率方面的一个扩展版本,用于解决密度峰值搜索算法中巨大的资源消耗问题. 在K-means密度峰值搜索算法中,首先,通过高效的聚类算法(例如K-means)进行初始聚类,得到的聚类中心被定义为具有权重的典型点. 然后,对加权的典型点通过密度峰值搜索算法实现二次聚类,并细化点为核心点、边界点、加细光晕点. 在与密度峰值搜索算法具有相似的精度的同时,计算复杂度由O(n²)降至O(n). 通过二面角,二级结构,关联图描述的分子构象,将KFDP用于多个模拟轨迹的聚类过程中. 并通过与K-means聚类算法,DBSCAN聚类算法的比较结果,验证了K-means密度峰值搜索算法的优势.     

The t‐U‐V‐J model in cuprates: Strengths of the interactions

The t‐U‐V‐J model fits together three major parts of the superconductivity puzzle of the cuprite compounds: (i) it describes the opening of a d‐wave pairing gap, (ii) it is consistent with the fact that the basic pairing mechanism arises from the antiferromagnetic exchange correlations, and (iii) it takes into account the charge fluctuations associated with double occupancy of a site which play an essential role in doped systems. The strengths of the interactions U, V and J in YBa₂Cu₃O_6.7 and La_2‐xSr_xCuO₄ (_x = 0.16) samples are obtained by requiring quantitative consistency between the angle‐resolved photoemission spectroscopy (ARPES) measurements, the sharp collective mode at the antiferromagnetic wave vector Q _AF=(π,π), and the observed inelastic neutron scattering resonance (INSR) positions of the incommensurate peaks at wave vectors Q _δ = ((1 ± δ)π,π) and Q _δ = (π(1 ± δ)π).     

Quantization of electromagnetic field in quadratic continuous nonlinear absorptive dielectrics

This paper reports that in the quantization of electromagnetic field in the dielectrics, the wave equation with regard to the Green function is analytically solved by a direct integral method for a quadratic continuous nonlinear absorptive dielectric medium. The quantization of the electromagnetic field in such a nonlinear absorptive dielectric is carried out for which the material dielectric function is assumed as a separable variable about the frequency and the space coordinate. The vacuum field fluctuations for different spatial continuous variations of dielectric function are numerically calculated, which shows that the present result is self-consistent.     

Wavelet-Fourier self-deconvolution

Using a wavelet function as the filter function of Fourier self-deconvolution, a new method of resolving overlapped peaks, wavelet-Fourier self-deconvolution, is founded. The properties of different wavelet deconvolution functions are studied. In addition, a cutoff value coefficient method of eliminating artificial peaks and wavelet method of removing shoulder peaks using the ratio of maximum peak to minimum peak is established. As a result, some problems in classical Fourier self-deconvolution are solved, such as the bad result of denoising, complicated processing, as well as usual appearance of artificial and shoulder peaks. Wavelet-Fourier self-deconvolution is applied to determination of multi-components in oscillographic chronopotentiometry. Experimental results show that the method has characteristics of simpler process and better effect of processing.     

The role of mass spectrometric methods in ionic reaction mechanistic studies

The role of various mass spectrometric methods, including electron ionization, collisional activation, metastable peak shapes, analysis of neutrals from ionic unimolecular dissociations, field ionization kinetics, drift cell, and Fourier transform ion cyclotron resonance spectrometry, in ionic reaction mechanistic studies is described. This is illustrated by selected examples of research performed in the author’s group over the last three decades. They comprise inter alia intramolecular acid–base, anchimeric assistance, nucleophilic attack, isomerization, cycloaddition, S_N2, and hydride ion transfer reactions.     

Perspective on “An extended Hückel theory. I. Hydrocarbons”

 The size-consistent self-consistent matrix dressing method has been applied on an open-shell single-configuration reference state. Once the reference state is converged, several low-lying roots can be obtained for the dressed configuration interaction (CI) matrices of appropriate symmetry. The CI matrices were built with a complete-active-space singles and doubles CI method in order to deal properly with multiconfiguration excited states. The vertical ionization and ionization–excitation transitions are obtained from the difference to the closed shell ground-state energy of the neutral molecule. The method has been applied to NH⁺ ₃ and N⁺ ₂ using atomic natural orbital basis sets and state-average adapted molecular orbitals. Two ²A₁ states, very similar and showing great mixing of the (2a _l ⁻¹) and (3a _l ⁻²5a _l ¹) determinants, can be assigned to the broad asymmetric band at 27.6 ± 2 eV in the photoelectron spectrum of NH₃. The possible contribution of a ²Π _g (3σ _g ⁻²1π _g ¹) state to the A shake-up peak of N₂ at 24.6 eV is also discussed. Other states, doublets and quadruplets, are reported for both systems up to 30 eV for NH₃ and 37 eV for N₂. Received: 16 September 1999 / Accepted: 3 February 2000 / Published online: 2 May 2000     

二维小波变换与子窗口因子分析法结合用于含噪声HPLC-DAD数据的解析

将二维小波变换与子窗口因子分析法相结合,用于模拟的高噪声HPLC-DAD数据的解析.首先应用二维小波变换滤除噪声,然后采用子窗口因子分析法解析重叠峰.结果表明,信噪比为10的高噪声基本被滤除掉.     

Combining classification and regression approaches for the quantification of highly overlapping capillary electrophoresis peaks by using evolutionary sigmoidal and product unit neural networks

This is a study of the potential of neural networks built by using different transfer functions (sigmoidal, product and sigmoidal–product units) designed by an evolutionary algorithm to quantify highly overlapping electrophoretic peaks. To test this approach, two aminoglycoside antibiotics, amikacin and paramomycin, were quantified from samples containing either only one component or mixtures of them though capillary zone electrophoresis (CZE) with laser‐induced fluorescence (LIF) detection. The three models assayed used as input data the four‐parameter Weibull curve associated with the profile of the electrophoretic peak and in some cases the class label for each sample estimated by cluster analysis. The combination of classification and regression approaches allowed the establishment of straightforward network topologies enabling the analytes to be quantified with great accuracy and precision. The best models for mixture samples were provided by product unit neural networks (PUNNs), 4:4:1 (14 weights) for both analytes, after discrimination by cluster analysis, allowing the analytes to be quantified with great accuracy: 8.2% for amikacin and 5.6% for paromomycin within the standard error of prediction for the generalization test, SEP_G. For comparison, partial least square regression was also used for the resolution of these mixtures; it provided a minor accuracy: SEP_G 11.8 and 15.7% for amikacin and paramomycin, respectively. The reduced dimensions of the neural networks models selected enabled the derivation of simple quantification equations to transform the input variables into the output variable. These equations can be more easily interpreted from a chemical point of view than those provided by other ANN models. Copyright © 2007 John Wiley & Sons, Ltd.