A Background and noise elimination method for quantitative calibration of near infrared spectra

A new hybrid algorithm is proposed to eliminate the varying background and noise simultaneously for multivariate calibration of near infrared (NIR) spectral signals. The method is based on the use of multi-resolution, which is one of the main advantages provided by wavelet transform. The signals are firstly split into different frequency components, which keep the same data points of the original signals. In conjunction with a modified uninformative variable elimination (mUVE) criterion, the new method can be used to remove the low-frequency varying background and the high-frequency noise simultaneously. The method is successfully applied to simulated spectral data set and experimental NIR spectral data, resulting in more parsimonious multivariate models with higher precision. In addition, the proposed strategy can be applied to other spectral signals as well.     

基于迭代小波变换的光谱信号本底扣除方法研究

本底会对光谱分析结果产生很大的干扰作用,为获取特征峰的有效信息,必须首先去除本底。该文提出了一种基于小波变换的本底扣除算法,通过对光谱及后续光谱迭代进行小波变换,利用逼近系数估计本底,直到本底收敛。提出了判断多次估计的本底最大误差是否足够小的收敛准则。利用该算法去除本底后,即可进行特征峰信息的提取。分别利用仿真光谱和实验能量色散X射线荧光光谱对算法进行了验证,并与传统小波变换和多项式拟合法进行了对比。结果表明,该算法能够更准确扣除光谱本底,对其他光谱的本底扣除也具有借鉴意义。     

Wiener distributions and white noise analysis

The paper describes the structure of a new space of generalized Wiener functionals, , called the Wiener algebra, or space of Wiener distributions, and demonstrates its use in the white noise analysis. The concepts of derivatives and integrals for multi-time parameter generalized stochastic process:^N are introduced, and a derivative version of Itô's lemma is proved. The algebraic structure of and its lattice of subspaces is elaborated, and within this framework a generalized version of the Malliavin calculus is presented.     

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.     

The validity of nonlinear Langevin equations

In the presence of internal noise the variables describing a system are intrinsically stochastic. If they constitute a Markov process the expansion enables one to extract a deterministic macroscopic equation and to compute the fluctuations in successive approximations. In the lowest or linear noise approximation the fluctuations can be represented by a Langevin equation, provided it is handled appropriately. Higher orders cannot be described by any white noise Langevin equation. The question whether the equation has to be interpreted according to Itô or Stratonovich concerns these higher orders, for which the equation is not valid anyway.     

Synthesis,characterization, and application of griseofulvin surface molecularly imprinted polymers as the selective solid phase extraction sorbent in rat plasma samples

In present study, an investigation was carried out to develop and validate an analytical method for the selective extraction and determination of griseofulvin (GSF) from plasma samples. For this purpose, a rational approach was made to synthesize and characterize the surface molecularly imprinted polymers (SMIPs). The SMIPs were utilized as solid phase extraction (SPE) sorbents. The SMIPs were prepared by using GSF as template molecule on the surface of modified silica particles through a non-covalent technique. The particles demonstrated high adsorption capacity (119.1 µg/mL), fast adsorption equilibrium time (30 min) and good recognition selectivity for the template drug. The scanning electron microscopy and infrared spectroscopy were used to explain the structural and morphological characteristics of the SMIPs and surface non-imprinted polymers. The SPE method was combined with HPLC for plasma analysis. The method validation results demonstrated that the established method possessed good linearity for GSF ranging from 0.1 to 50 µg/mL (R² = 0.997). The limit of detection for this method was 0.02 µg/mL for rat plasma samples. The recoveries of GSF from spiked plasma samples were (90.7–97.7%) and relative standard deviations were (0.9–4.5%). Moreover, the SMIPs as selective SPE sorbent can be reused more than 8 times which is a clear advantage over commercial SPE sorbents. Finally, the usefulness of the proposed strategy was assessed by extraction and detection of GSF in real rat plasma samples.     

Energy Transfer from the Upper Triplet States of Aromatic Molecules

The energy transfer from the upper triplet states of diphenylamine, naphthalene and triphenylene to toluene and hexene-1 is studed. Two mechanisms of dissipation transferred energy in solvents are discussed.     

Limit theorems for the pre-averaged Hayashi–Yoshida estimator with random sampling

We will focus on estimating the integrated covariance of two diffusion processes observed in a nonsynchronous manner. The observation data is contaminated by some noise, which possibly depends on the time and the latent diffusion processes, while the sampling times also possibly depend on the observed processes. In a high-frequency setting, we consider a modified version of the pre-averaged Hayashi–Yoshida estimator, and we show that such a kind of estimator has the consistency and the asymptotic mixed normality, and attains the optimal rate of convergence.     

A central limit theorem in nonlinear filtering

It is shown that the probability law of a diffusion process conditioned on weakly corrupted observations is asymptotically Gaussian when properly scaled. The method of proof involves Fisher information matrices and a Cramér-Rao inequality.     

Moving grid method for numerical simulation of stratified flows

We develop a second‐order accurate Navier–Stokes solver based on r‐adaptivity of the underlying numerical discretization. The motion of the mesh is based on the fluid velocity field; however, certain adjustments to the Lagrangian velocities are introduced to maintain quality of the mesh. The adjustments are based on the variational approach of energy minimization to redistribute grid points closer to the areas of rapid solution variation. To quantify the numerical diffusion inherent to each method, we monitor changes in the background potential energy, computation of which is based on the density field. We demonstrate on a standing interfacial gravity wave simulation how using our method of grid evolution decreases the rate of increase of the background potential energy compared with using the same advection scheme on the stationary grid. To further highlight the benefit of the proposed moving grid method, we apply it to the nonhydrostatic lock‐exchange flow where the evolution of the interface is more complex than in the standing wave test case. Naive grid evolution based on the fluid velocities in the lock‐exchange flow leads to grid tangling as Kelvin–Helmholtz billows develop at the interface. This is remedied by grid refinement using the variational approach. Copyright © 2012 John Wiley & Sons, Ltd.