基于X射线吸收谱的不同生物组织的辨识

为了验证X射线吸收光谱法对生物组织的辨识能力,选取猪的心脏、肝、肾、胃、瘦肉以及肥肉作为实验样本,以55 k V的电压激发X射线管,利用X射线探测器获取这6类生物组织样本的X射线吸收光谱.将采集到的光谱数据分为测试集与训练集,利用主成分分析法提取光谱主成分,以训练集为输入建立径向基函数(RBF)神经网络分类预测模型,对测试集样本进行分类预测.通过交叉验证法对所有样本进行辨识的识别正确率达到90.22%.实验结果表明,X射线光谱技术结合主成分分析法和RBF神经网络能够很好地用于猪的组织分类,对将X射线光谱技术应用于生物组织辨识具有重要的指导意义.     

X射线荧光光谱法对橡胶鞋底的分类

为建立案件现场常见橡胶鞋底物证的分类方法,利用X射线荧光光谱,对40个不同品牌、不同系列的橡胶鞋底样品中的无机元素进行了检验。并结合多元统计学,分别选用主成分分析法、k均值聚类法及判别分析法等对实验结果进行分析。结果表明,该方法简便快速、结果准确可靠且无损检材,对样品的分类效果较好。利用该方法可以对橡胶鞋底物证进行分类。     

小角X射线散射技术在高分子表征中的应用

小角X射线散射(SAXS)技术是表征高分子材料微观结构的一种重要手段.当X射线穿过材料时,在材料不均一的电子云密度分布作用下,发生散射并形成特定的散射图案,使得我们可以根据特定的模型来反推材料的微观结构,并计算相关结构参数.SAXS特有的对微观结构的统计平均及无损探测使其成为了一种不可或缺的高分子材料微观结构分析手段....     

健康和病变关节软骨的傅里叶变换红外光谱显微成像及Fisher判别

傅里叶变换红外光谱显微成像(FTIRI)可同时获得样品的红外光谱和形貌信息,其与化学计量学方法结合,可实现生物组织中主成分含量及分布的定量研究.本研究采用FTIRI技术结合主成分分析(PCA)以及Fisher判别算法对正常和病变的关节软骨进行鉴别分析.对关节软骨切片进行实现FTIR扫描及光谱分析,再利用SPSS软件对软骨的光谱(矩阵)进行主成分分析,根据主成分得分矩阵构造分类函数,结合Fisher判别算法对样本进行分类识别.正常和病变的关节软骨样品识别准确率高达95.7％(初始案例)和94.3％(交互验证案例).本方法可准确有效地辨别关节软骨是否发生病变,为监测骨关节炎的发生和修复提供参考.     

基于能量色散X射线散射方法的液体物质探测与识别研究

固定散射角θ,采用连续波长的X射线对3类纯液体物质（伯醇、苯同系物与氯代甲烷）进行了能量色散X射线散射实验,得到了上述纯液体物质的能量色散X射线散射图谱。结果表明,每种液体物质的能量色散X射线散射图谱的峰形与峰位置彼此不同。伯醇随着碳链长度的增加,散射峰宽变窄,主峰位置向小的散射参数动量转移（q）值方向移动。苯同系物的...     

MoS2/C复合纳米管的合成

在900℃氢气气氛下,通过热分解载有硫代钼酸铵的碳纳米管前驱物得到MoS₂/C复合纳米管.通过粉末X射线衍射(XRD)、拉曼光谱(Raman)、高分辨透射电镜(HRTEM)和X射线能量散射仪(EDS)等方法对其形貌、结构和成分进行了表征.结果表明,所合成物质是一种由两种材料组成管壁的新型纳米管.     

基于软X射线光谱的锂电池材料的电子结构与演变的研究进展

开发新型高能量密度以及低成本的锂离子电池, 是有效应对能源危机和环境挑战的可行路径之一. 锂离子电池材料的电子结构与电子态的演化决定了材料诸多本征性质以及电池综合性能. 探测并操控电极材料电子态的演化对探求电极反应的物理机理、 促进电池材料发展具有重要意义. 基于同步辐射的软X射线光谱技术可以直接探测费米能级附近的电子态. 本文从阴阳离子氧化还原反应的不同角度对利用软X射线光谱对电子态演变的研究进行了总结, 获得了电极材料电化学循环过程中过渡金属与氧的电子态演化信息, 系统阐述并总结了不同锂离子电池材料中电子态的演化以及氧化还原反应机理的最新研究进展.     

M0s2／C复合纳米管的合成

在900℃氢气气氛下，通过热分解载有硫代钼酸铵的碳纳米管前驱物得到MoS2／C复合纳米管．通过粉末X射线衍射(XRD)、拉曼光谱(Ramart)、高分辨透射电镜(HRTEM)和X射线能量散射仪(EDS)等方法对其形貌、结构和成分进行了表征．结果表明，所合成物质是一种由两种材料组成管壁的新型纳米管.     

基于主成分分析-Fisher判别分析的食品类塑料瓶物证差分拉曼光谱分类

食品类塑料瓶物证携带许多潜在证据信息,目前针对此类物证的检验研究尚处于探索阶段。利用差分拉曼光谱对46个食品类塑料瓶样品进行检验,依据样品材质及光谱特征峰可将样品分为三类。利用主成分分析（Principal component analysis, PCA）-Fisher判别分析,绘制主成分得分图,构建判别函数,建立分类模型。结果表明,食品类塑料瓶样品具有明显的聚类关系,原始分类与交叉验证分类准确率达到100 %。差分拉曼光谱结合PCA-Fisher判别分析,检验鉴别食品类塑料瓶物证具有一定的科学性。     

基于光谱融合-特征提取的海洛因及其添加剂无损分类研究

在近年来的多数治安案件中,有不少是由形形色色的毒品所引起的.为了提高检验的效率,降低检验成本,实现对海洛因样本主成分及添加剂的无损分类,提出了一种基于光谱融合,主成分分析和判别分析的鉴别方法.采集并获取了不同质量分数和添加剂共计45个海洛因样本的红外光谱,选择一阶求导、多元散射校正、Savitzky-Golay平滑和峰...     

Real-Time Distinguishing of the Xylene Isomers Using Photoionization and Dissociation Mass Spectra Obtained by Femtosecond Laser Mass Spectrometry (FLMS)

Abstract

Distinguishing chemicals and improvement on analytical methods has a direct impact on modern chemical analysis. In this work, the dissociative ionization of xylene isomers was investigated using a femtosecond laser mass spectrometry (FLMS) method with a custom-built linear time-of-flight (TOF) instrument. Laser beams at 800?nm and 400?nm were used and intensity-dependent analysis of the obtained mass spectra was performed using principal component analysis (PCA) to distinguish the xylene isomers, which give identical mass spectra in appearance that cannot be distinguished using normal mass spectrometry methods. The results show that there is a statistically highly significant difference between the xylene isomers for two principal components (1 ? α?>?99.99%) and minimal information loss (<5%) took place during the PCA procedure. Also, the use of the k-medoid clustering method showed that the isomers may be distinguished in real-time for a wide range of ionization laser pulse powers with approximately 99% accuracy. The results suggest that real-time isomer analysis by the FLMS method is suitable for mass spectral identification applications. The FLMS method has been shown to be an important alternative to other mass spectrometric methods that use different ionization mechanisms.     

Application of near infrared spectroscopy (NIR), X-ray fluorescence (XRF) and chemometrics to the differentiation of marmora samples from the Mediterranean basin

Abstract

Near-infrared (NIR) and X-ray fluorescence spectra were recorded for 15 different samples of marmora, from the Mediterranean Basin and of different colours. After appropriate pretreatment (SNV transform + second derivative), the results were subjected to principal component analysis (PCA) treatment with a view to differentiating them. The observed differences among the samples were chemically interpreted by highlighting the NIR wavelengths and minerals, respectively, contributing the most to the PCA models. Moreover, a mid-level data fusion protocol allowed integrating the information from the different techniques and, in particular, to correctly identify (based on the distance in the score space) three test samples of known type. Moreover, it should be stressed that positive results on the differentiation and identification of marmora were obtained using two completely non-invasive, non-destructive and relatively inexpensive techniques, which can also be used in situ.     

Multivariate statistical analysis of tobacco of different origin, grade and variety according to polyphenols and organic acids

The aim of this work was to determine the concentration of polyphenols, organic acids in tobacco of different areas, grades and varieties by ultra-performance liquid chromatography tandem mass spectrometry (UPLC/MS/MS) and to achieve statistical classification by principal component analysis (PCA) and linear discriminant analysis (LDA). The obtained results revealed that tobacco of different varieties can be correctly classified according to the contents of polyphenols or organic acid. The results of PCA showed that different grades and geographic regions cannot completely be discriminated using polyphenols or organic acid as independent variables. However, there were marked differences in special class from the same type or grade tobacco. At the same time, the results of LDA also showed that the samples were correctly classified at 100% for different varieties of tobacco, but only 55.3% and 60% for different grades and areas, respectively. These results demonstrated that the composition of polyphenols and organic acids can be used as the useful variables to characterize the type and the special class or grade of tobacco.     

Determination of the Mo surface environment of Mo/TiO2 catalysts by EXAFS,XANES and PCA

The local structure of oxidic Mo/TiO₂ catalysts (0.5 to 13.5 wt.% Mo) has been studied using EXAFS and XANES. Both EXAFS and XANES results suggest that the Mo surface phase is octahedrally coordinated for all Mo loadings. The EXAFS results were also examined using principal component analysis (PCA) to determine the number of Mo species present on the Mo/TiO₂ catalysts. Results from PCA of the Mo EXAFS spectra suggested the presence of three Mo species: two surface species and bulk MoO₃.     

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.     

A new regression method based on independent component analysis

Based on independent component analysis (ICA), a new regression method, independent component regression (ICR), was developed to build the model of NIR spectra and the routine components of plant samples. It is found that ICR and principal component regression (PCR) are completely equivalent when they are applied in quantitative prediction. However, independent components (ICs) can give more chemical explanation than principal components (PCs) because independence is a high-order statistic that is a much stronger condition than orthogonality. Three ICs are obtained by ICA from the NIR spectra of plant samples; it is found that they are strongly correlated to the NIR spectra of water, hydrocarbons and organonitrogen compounds, respectively. Therefore, ICA may be a promising tool to retrieve both quantitative and qualitative information from complex chemical data sets.     

Multivariate evaluation of doxorubicin surface-enhanced Raman spectra

Multivariate evaluation of surface-enhanced Raman spectra of doxorubicin in plasma was performed. In a principal component analysis (PCA) all spectral features were modelled into three principal components. The major variation of the data was shown to be the variation of doxorubicin Raman signal together with the doxorubicin fluorescence, whereas the variation due to plasma was of minor importance. It was also shown that the surface-enhanced Raman scattering (SERS) measurements were independent on such factors as measurement occasion and silver colloids. The presented results show that with some improvements, quantification of doxorubicin directly in plasma could be possible.     

Qualitative study of ethanol content in tequilas by Raman spectroscopy and principal component analysis

Using Raman spectroscopy, with an excitation radiation source of 514.5 nm, and principal component analysis (PCA) was elaborated a method to study qualitatively the ethanol content in tequila samples. This method is based in the OH region profile (water) of the Raman spectra. Also, this method, using the fluorescence background of the Raman spectra, can be used to distinguish silver tequila from aged tequilas. The first three PCs of the Raman spectra, that provide the 99% of the total variance of the data set, were used for the samples classification. The PCA1 and PCA2 are related with the water (or ethanol) content of the sample, whereas the PCA3 is related with the fluorescence background of the Raman spectra.     

Chemometric quality control of chromatographic purity

It is common practice in chromatographic purity analysis of pharmaceutical manufacturing processes to assess the quality of peak integration combined by visual investigation of the chromatogram. This traditional method of visual chromatographic comparison is simple, but is very subjective, laborious and seldom very quantitative. For high-purity drugs it would be particularly difficult to detect the occurrence of an unknown impurity co-eluting with the target compound, which is present in excess compared to any impurity. We hypothesize that this can be achieved through Multivariate Statistical Process Control (MSPC) based on principal component analysis (PCA) modeling. In order to obtain the lowest detection limit, different chromatographic data preprocessing methods such as time alignment, baseline correction and scaling are applied. Historical high performance liquid chromatography (HPLC) chromatograms from a biopharmaceutical in-process analysis are used to build a normal operation condition (NOC) PCA model. Chromatograms added simulated 0.1% impurities with varied resolutions are exposed to the NOC model and monitored with MSPC charts. This study demonstrates that MSPC based on PCA applied on chromatographic purity analysis is a powerful tool for monitoring subtle changes in the chromatographic pattern, providing clear diagnostics of subtly deviating chromatograms. The procedure described in this study can be implemented and operated as the HPLC analysis runs according to the process analytical technology (PAT) concept aiming for real-time release.     

基于液相色谱-质谱联用技术的代谢组学方法研究薄荷烟对大鼠代谢的影响

将基于液相色谱-质谱联用(LC-MS)技术的代谢组学分析平台用于薄荷烟对大鼠代谢影响的研究。分析了3组大鼠的尿样,包括对照大鼠、吸食普通烟大鼠和吸食薄荷烟大鼠,并采用主成分分析(PCA)方法对数据进行模式识别。PCA得分图表明吸食薄荷烟大鼠与对照组大鼠尿样的代谢差异要小于吸食普通烟大鼠。从PCA载荷图中找到并鉴定了犬尿喹啉酸等8种重要代谢物。通过考察代谢物在对照大鼠、吸食薄荷烟大鼠和吸食普通烟大鼠尿样中的相对含量变化,进一步说明了烟草中添加薄荷醇可减少烟草对大鼠代谢的影响。