小波变换作为预处理的多元线性回归法

多元线性回归法是一种应用非常广泛的多变量分析方法，用于多组分同时定量分析。然而，噪声的存在影响了多元线性回归法分析的准确度。近年来小波变换以其多分辨率分析的特性、方法简单、快速等优点成为一种有效的去除分析信号噪声的方法。本实验就噪声对多元线性回归法的影响以及小波变换与多元线性回归法结合提高多元线性回归法分析准确性的有效性进行了研究。     

小波变换法在X射线能谱去噪声中的应用

阐述了二进小波变换法的去噪声原理和方法,并将其应用于X射线能谱分析中噪声的去除。实验结果表明,该去噪方法能够解决传统平滑方法的滑方法的不足,改善X射线能谱的定性、定量分析结果。     

小波变换-主成分回归分光光度法同时测定邻苯二酚、间苯二酚和对苯二酚三组分

根据小波变换具有将信号分频的特点,本文提出了将小波变换与主成分回归(PCR)相结合的一种多元校正算法。该法能更有效地去除噪声,提取有用信息,并将其用于分析邻苯二酚、间苯二酚、对苯二酚三组分体系。实验结果表明,本法比直接用主成分回归处理效果好,得到的平均相对误差从2．24％降低到1．19％。     

一种基于二进小波变换的自适应滤波方法

根据信号和噪声经小波变换后在不同尺度上有不同的特征，将相邻尺度二进小波变换值的相关量进行归一化处理并与小波变换值比较来判断信号与噪声，以噪声在各尺度的方差作为终止迭代的标准，提出了一种基于二进小波变换小波域选择噪声的自适应滤波方法。研究了模拟信号的去噪过程、半峰宽和信噪比对去噪结果的影响，并对模拟含噪信号和含噪毛细管电泳信号去噪前后的结果进行了比较。实验结果表明：由于该方法具有良好的自适应性和显著的滤波效果，必将得到广泛的应用。     

代谢组学分析技术及其在几类重大疾病研究中的应用

代谢组学正成为生物医学研究领域的新热点。各种代谢组学分析技术各有优缺点,配有低温探头的核磁共振、混合型串联傅里叶变换质谱以及多种联用技术将成为代谢组学研究的关键技术。目前,大量多维代谢组学数据的分析方法和专用软件急待开发完善。代谢组学在肿瘤,老年痴呆症、心血管疾病、肝肾脏类疾病等研究中的应用取得一定进展,疾病代谢组学具有良好的发展前景。     

基于提升格式的小波变换用于处理化学信号

将提升haar小波变换应用于对不同类型含高噪声化学信号的处理,提出1种用于高噪声化学信号中滤除噪声的快速新方法——提升小波滤噪法,并使之与重叠峰分辨技术联用;以优选的小波分解层数对低信噪比的分析化学信号进行基于提升格式的小波变换处理,取得满意的结果;方法简单、快捷、准确、易行．运算速度是传统小波变换的一半,对高噪声化学信号的处理结果信噪比提高几百倍,峰位置相对误差小于1．5％;应用于氨基酸体系毛细管电泳检测信号的处理,有效降低了实验噪声的影响,分辨提取了难以察觉的信号．结果峰形变窄,峰高增加．大大提高了峰的分辨率．验证和显示了方法的可行性和优越性。     

Daubechies小波主成分回归法机理及算法研究

将小波变换与主成分回归相结合,提出一种新型多元校正算法---小波基主成分回归法。理论分析和仿真实验表明,该法可更有效地去除噪声,提取有用信息。将其用于氯霉素及甲硝唑实际药物体系分析,与主成分回归法(PCR)相比,得到的回收率总平均相对误差由1.70%下降到0.90%。此外,通过将统计判据和小波多尺度分析相结合,发展了一种新的因子数判定方法。理论和实验研究表明,该法比传统因子数判定法具有更高的可靠性。     

结合方差稳定变换和PGPD去除磁共振图像Rician噪声

基于非局部自相似性块组学习的图像去噪(PGPD)算法去除高斯噪声效果优异,但是对于磁共振(MR)图像中Rician噪声的去除效果不理想。为此本文提出一种结合方差稳定变换和PGPD的新去噪算法FPGPD。该算法首先对含有Rician噪声的MR图像进行方差稳定变换,使噪声在变换域中近似服从高斯分布。用PGPD算法在变换域中去噪,最后经过方差稳定逆变换得到无偏去噪图像。理论分析和实验结果表明,FPGPD算法在去除MR图像中Rician噪声时比PGPD算法去噪性能好,具体体现为对图像细节和轮廓边缘保护得更好。     

小波变换-偏最小二乘算法及其在复方甲硝唑注射液分析中的应用

提出了结合小波变换的偏最小二乘法（ＷＰＬＳ）,即先对光谱信号进行小波变换,去除噪声,再用偏最小二乘法对多组分同时测定。将该法用于模拟体系及复方甲硝唑注射液体系,结果表明,该法优于偏最小二乘法。     

连续样条小波变换用于分解重叠峰的研究

以B-样条小波为分析小波，提出了用于分析化学重叠信号解析的新方法——连续样条小波变换，结果表明：连续样条小波变换应用于分析化学信号的处理，能使峰变窄同时还能提高信号的信噪比，是一种新型有效的重叠信号解析方法，能从含噪声重叠信号中直接得到重叠峰的峰数目及其相应的峰位置。     

Unambiguous structural characterization of hydantoin reaction products using 2D HMBC NMR spectroscopy

Data from two-dimensional (2D) NMR experiments were used to identify the reaction products resulting from the opening of pyroglutamates with isocyanates or thioisocyanates. The reaction has the potential to produce compounds that would have very similar one-dimensional proton ((1)H) or carbon-13 ((13)C) NMR spectra. Careful analysis of (1)H--(1)H COSY, (1)H--(1)H NOESY, and HMBC data, including chemical shifts and coupling constants, were used to distinguish correctly between carbamoyl-2-pyrrolidinone, hydantoin, and perhydro-1,3-diazepine-2,4-dione type structures that could result from this reaction. This work describes their preparation and subsequent identification using 2D NMR spectroscopy, and includes complete (13)C assignments of the reaction products. The 2D NMR techniques and analysis described here can be applied successfully to other synthetic reactions with the potential to produce isomeric products.     

Enhancement of the Nuclear Spin Noise Signal Using Wavelet Transform

Spin noise spectroscopy has attracted considerable attention recently owing partly to intrinsic interest in the phenomenon and partly to its significant application potential. Here, we address the inherent problem of low sensitivity of nuclear spin noise and examine the utility of wavelet transform to mitigate this problem by distinguishing real peaks from the noise contaminated data. Suppression of the random circuit noise and the consequent enhancement of the correlated nuclear spin noise signal have been demonstrated with discrete wavelet transform. Spectra of both ¹H and ¹³C nuclear spins have been considered and significant signal enhancements in both the cases have been observed. A detailed analysis of several possible wavelet, thresholding and decomposition solutions have been made to obtain the optimum condition for signal enhancement. It is observed that the application of wavelet transform leaves the spin noise signal line shape essentially unchanged, which is an advantage for several applications involving spin noise spectra.     

Application of chemometrics to 1H NMR spectroscopic data to investigate a relationship between human serum metabolic profiles and hypertension

The application of chemometric methods to 1H NMR spectroscopic data has been documented for pathophysiological processes. In this study we show the application of 1H NMR-based metabonomics to investigate a relationship between serum metabolic profiles and hypertension. Although hypertension can be defined using blood pressure measurements, the underlying aetiology and metabolic effects are not so readily identified. Serum profiles for patients with low/normal systolic blood pressure (SBP < or = 130 mm Hg; n = 28), borderline SBP (131-149 mm Hg; n = 19) and high SBP (> or = 150 mm Hg; n = 17) were acquired using 1H NMR spectroscopy. Orthogonal signal correction followed by principal components analysis were applied to these NMR data in order to facilitate interpretation, and the resulting chemometric models were validated using Soft Independent Modelling of Class Analogy. Using 1H NMR-based metabonomics, it was possible to distinguish low/ normal SBP serum samples from borderline and high SBP samples. Borderline and high SBP samples, however, were indiscriminate from each other. Our preliminary results showed that there was a relationship between serum metabolic profiles and blood pressure which, in part, was due to lipoprotein particle composition differences between the samples. Furthermore, our results indicated that serum pathology associated with blood pressure is apparent at SBP values > 130 mm Hg, which the WHO and ISH currently define as the limit between normal and high-normal.     

Extraction of multiple pure component H and C NMR spectra from two mixtures: Novel solution obtained by sparse component analysis-based blind decomposition

Sparse component analysis (SCA) is demonstrated for blind extraction of three pure component spectra from only two measured mixed spectra in ¹³C and ¹H nuclear magnetic resonance (NMR) spectroscopy. This appears to be the first time to report such results and that is the first novelty of the paper. Presented concept is general and directly applicable to experimental scenarios that possibly would require use of more than two mixtures. However, it is important to emphasize that number of required mixtures is always less than number of components present in these mixtures. The second novelty is formulation of blind NMR spectra decomposition exploiting sparseness of the pure components in the wavelet basis defined by either Morlet or Mexican hat wavelet. This enabled accurate estimation of the concentration matrix and number of pure components by means of data clustering algorithm and pure components spectra by means of linear programming with constraints from both ¹H and ¹³C NMR experimental data. The third novelty is capability of proposed method to estimate number of pure components in demanding underdetermined blind source separation (uBSS) scenario. This is in contrast to majority of the BSS algorithms that assume this information to be known in advance. Presented results are important for the NMR spectroscopy-associated data analysis in pharmaceutical industry, medicine diagnostics and natural products research.     

Wavelet transform-based analysis for electrochemical noise

Wavelet transforms are presented as a useful tool to analyse electrochemical noise data. Various concepts developed in the framework of wavelet transforms have been adapted to study electrochemical noise measurements. The most relevant feature of this method of analysis is its capability of decomposing electrochemical noise records into different sets of wavelet coefficients, which contain information about corrosion events occurring at a determined time-scale. Thus, this mathematical approach could become an alternative tool which solves the limitations of other more established procedures for the analysis of electrochemical noise data, such as statistical or Fourier transform-based methods.     

Enhanced sensitivity and resolution in (1)H solid-state NMR spectroscopy of paramagnetic complexes under very fast magic angle spinning

High-resolution NMR spectroscopy for paramagnetic complexes in solids has been rarely performed because of its limited sensitivity and resolution due to large paramagnetic shifts and associated technical difficulties. The present study demonstrates that magic angle spinning (MAS) at speeds exceeding 20 kHz provides unusually high sensitivity and excellent resolution in 1H solid-state NMR (SSNMR) for paramagnetic systems. Spinning-speed dependence of 1H MAS spectra showed that very fast MAS (VFMAS) at 24-28 kHz enhanced sensitivity by a factor of 12-18, compared with the sensitivity of 1H SSNMR spectra under moderate MAS at 10 kHz, for Cu(dl-alanine)2.H2O and Mn(acac)3, for which the spectral ranges due to 1H paramagnetic shifts reach 200 and 1000 ppm, respectively. It was theoretically and experimentally confirmed that the absolute sensitivity of 1H VFMAS for small paramagnetic complexes such as Cu(dl-alanine)2 can be an order of magnitude higher than that of equimolar diamagnetic ligands because of short 1H T1 ( approximately 1 ms) of the paramagnetic systems and improved sensitivity under VFMAS. On the basis of this demonstrated high sensitivity, 1H SSNMR micro analysis of paramagnetic systems in a nanomole scale is proposed. Applications were performed on two polymorphs of Cu(II)(8-quinolinol)2, which is a suppressor of human cancer cells. It was demonstrated that 1H VFMAS SSNMR spectra accumulated for 20 nmol of the polycrystalline samples in 10 min enabled one to distinguish alpha- and beta-forms of Cu(II)(8-quinolinol)2 on the basis of shift positions and line widths.     

Synthesis and characterization of a new asymmetric bis-porphyrinato lanthanide complex presenting mixed hydrophilic-hydrophobic properties and its precursor form

The synthesis and spectroscopic characterization of a new family of heteroleptic porphyrinate double-deckers are reported. The investigated compounds are represented by the formulae La(III)H(TPyP)(TPP) and [La(III)(TMePyP)(TPP)]I(3). UV-vis spectroscopy of the title complexes confirms the presence of a strong pi-pi interaction between the macrocycles in each derivative. With (1)H and 2-D NMR data, we were able to distinguish two major NMR regions: the endo, between the bonded macrocycles, and the exo, outside the macrocycles, which are characteristic features of porphyrinic double-deckers. Finally, the electrochemical study confirms the strong pi-pi interaction for La(III)H(TPyP)(TPP) and completes this first approach for the investigation of this new family of derivatives.     

Automated structure verification based on a combination of 1D (1)H NMR and 2D (1)H - (13)C HSQC spectra

A method for structure validation based on the simultaneous analysis of a 1D (1)H NMR and 2D (1)H - (13)C single-bond correlation spectrum such as HSQC or HMQC is presented here. When compared with the validation of a structure by a 1D (1)H NMR spectrum alone, the advantage of including a 2D HSQC spectrum in structure validation is that it adds not only the information of (13)C shifts, but also which proton shifts they are directly coupled to, and an indication of which methylene protons are diastereotopic. The lack of corresponding peaks in the 2D spectrum that appear in the 1D (1)H spectrum, also gives a clear picture of which protons are attached to heteroatoms. For all these benefits, combined NMR verification was expected and found by all metrics to be superior to validation by 1D (1)H NMR alone. Using multiple real-life data sets of chemical structures and the corresponding 1D and 2D data, it was possible to unambiguously identify at least 90% of the correct structures. As part of this test, challenging incorrect structures, mostly regioisomers, were also matched with each spectrum set. For these incorrect structures, the false positive rate was observed as low as 6%.     

Sensitivity of 2H NMR spectroscopy to motional models: proteins and highly viscous liquids as examples

In order to study to what extent mechanisms of molecular motion can be unambiguously revealed by (2)H NMR spectroscopy, (2)H spectra for proteins (chicken villin protein headpiece HP36, selectively methyl-deuterated at leucine-69, C(δ) D(3)) and binary systems of high viscosity (benzene-d(6) in tricresyl phosphate) have been carefully analyzed as illustrative examples (the spectra are taken from the literature). In the first case, a model of restricted diffusion mediated by jumps between rotameric orientations has been tested against jump- and free diffusion models which describe rotational motion combined with jump dynamics. It has been found that the set of (2)H spectra of methyl-deuterated at leucine-69 chicken villin protein headpiece HP36 can be consistently explained by different motional models as well as by a gaussian distribution of correlation times assuming isotropic rotation (simple brownian diffusion model). The last finding shows that when the possible distribution of correlation times is not very broad one might not be able to distinguish between heterogeneous and homogenous (but more complex) dynamics by analyzing (2)H lineshapes. For benzene-d(6) in tricresyl phosphate, the dynamics is heterogeneous and it has been demonstrated that a gaussian distribution of correlation times reproduces well the experimental lineshapes, while for a Cole-Davidson distribution the agreement is somewhat worse. For inquires into the sensitivity of quadrupolar NMR spectral analysis (by "quadrupolar NMR spectroscopy we understand NMR spectroscopy of nuclei possessing quadrupole moment), the recently presented theoretical approach [Kruk et al., J. Chem. Phys. 135, 224511 (2011)] has been used as it allows simulating quadrupolar spectra for arbitrary motional conditions by employing the stochastic Liouville equation.     

Controlling the rate of shuttling motions in [2]rotaxanes by electrostatic interactions: a cation as solvent-tunable brake

A series of rotaxanes, with phenolic axle centerpieces and tetralactam macrocycles as the wheels, has been prepared in good yields. The threaded rotaxane structure is confirmed in the gas phase by tandem mass spectrometric experiments through a detailed fragmentation pattern analysis, in solution by NMR spectroscopy, and in the solid state through X-ray crystallography. A close inspection of the 1H,1H NOESY and 1H,1H ROESY NMR data reveals the wheel to travel along the axle between two degenerate diamide "stations" close to the two stoppers. By deprotonation of a phenolic OH group in the axle centerpiece with Schwesinger's P1 base, surprisingly no additional shuttling station is generated at the axle center, although the wheel could form rather strong hydrogen bonds with the phenolate. Instead, the wheel continues to travel between the two diamide stations. Experimental data from 1H,1H NOESY spectra, together with theoretical calculations, show that strong electrostatic interactions between the phenolate moiety and the P1 cation displace the wheel from the "phenolate station". The cation acts as a "brake" for the shuttling movement. Instead of suppressing the shuttling motion completely, as observed in other rotaxanes, our rotaxane is the first system in which electrostatic interactions modulate the speed of the mechanical motion between a fast and a slow motion state as a response to a reversible external stimulus. By tuning these electrostatic interactions through solvent effects, the rate of movement can be influenced significantly, when for example different amounts of DMSO are added to dichloromethane. Besides the shuttling motion, circumrotation of the wheel around the axle is observed and analyzed by variable temperature NMR spectroscopy. Force field and AM1 calculations are in good agreement with the experimental findings.