压电晶体传感器阵列用于混合有机溶剂蒸气中官能团的识别

为模拟生物化学传感体系, 提出了可用于识别有机官能团的传感器阵列, 用作人工气味识别系统。该阵列由八个压电晶体传感器组成, 每个传感器涂以具有广谱响应性能的不同吸附活性材料, 阵列对常见小分子有机溶剂混合蒸气的响应频移数据采用逐步判别分析(SDA)处理, 选出五个供信能力最佳的判别变量, 以此构成的阵列用于小分子有机溶剂混合蒸气中醇羟基、羰基与其它官能团的识别, 并采用主成分分析(PCA)法降维投影, 在二维空间含相同官能团的物质聚为一类; 阵列可用于酒类、软饮料的识别。     

A general treatment of solubility. 3. Principal component analysis (PCA) of the solubilities of diverse solutes in diverse solvents

A phenomenological study of solubility has been conducted using a combination of quantitative structure-property relationship (QSPR) and principal component analysis (PCA). A solubility database of 4540 experimental data points was used that utilized available experimental data into a matrix of 154 solvents times 397 solutes. Methodology in which QSPR and PCA are combined was developed to predict the missing values and to fill the data matrix. PCA on the resulting filled matrix, where solutes are observations and solvents are variables, shows 92.55% of coverage with three principal components. The corresponding transposed matrix, in which solvents are observations and solutes are variables, showed 62.96% of coverage with four principal components.     

基于显微共聚焦拉曼光谱技术快速检测3种梭菌中肉毒梭菌

提出了一种基于显微共聚焦拉曼光谱技术的肉毒梭菌快速鉴别方法.利用共聚焦显微拉曼光谱技术(CRM)采集了肉毒梭菌、艰难梭菌和产气荚膜梭菌的拉曼光谱,比较了3种梭菌的平均拉曼光谱,采用基线校正、标准正态变换、Savitzky-Golay 5点平滑和最大最小值归一化预处理后,借助主成分分析(PCA)降维并提取特征变量,对样本...     

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.     

Solvent colorimetric paper-based polydiacetylene sensors from diacetylene lipids

A well known unique property of polydiacetylenes (PDAs) is the colorimetric response to external stimuli making it one of the most studied conjugated polymers for sensing applications. Here we report the synthesis of a novel series of diacetylene acids from the condensation of pentacosa-10,12-diynylamine (PCDAmine) and dicarboxylic acid or its anhydrides. One of these diacetylene lipids, 4-(pentacosa-10,12-diynylamino)-4-oxobutanoic acid (PCDAS), is used in combination with pentacosa-10,12-diynoic acid (PCDA) for dropcasting on pieces of filter paper which are consequently irradiated by UV light to generate a paper based sensor array for solvent detection and identification. Upon the exposure to various types of organic solvents, the blue colored sensors colorimetrically respond to give different shades of colors between blue to red. The color patterns of the sensor array are recorded as RedGreenBlue (RGB) values and statistically analyzed by principal component analysis (PCA). The PCA score plot reveals that the array is capable of identifying eleven common organic solvents.     

FTIR, XRD, and DSC analysis of the rosemary extract effect on polyethylene structure and biodegradability

The purpose of this research study was evaluation of the utility of two common multivariate techniques, agglomerative cluster analysis (CA) and principal component analysis (PCA), as supplementary means of detecting incompatibilities, which can occur between active pharmaceutical ingredients and excipients at the preformulation stage of a solid dosage form. For the detection of incompatibilities between atenolol (beta blocker) and selected excipients (mannitol, lactose, starch, methylcellulose, β-cyclodextrin, meglumine, chitosan, polyvinylpyrrolidone and magnesium stearate), the thermogravimetry (TG), differential scanning calorimetry (DSC) and Fourier transform infrared spectroscopy (FTIR) were chosen. The results have shown that compatibility between atenolol and an excipient can be identified in a CA dendrogram by two large clusters, from which one groups an excipient and physical mixtures with a high concentration of the excipient. Another cluster encompasses atenolol and mixtures with a high content of the drug. In the PCA plot, all samples are located along the first principal component axis (PC1), beginning from a single component located with the most negative PC1 value, through mixtures with gradually varying concentration of both ingredients, till the second component located close to the most positive PC1 values. The results have shown that CA and PCA fulfil their role as supporting techniques in the interpretation of the data acquired from the TG curves, and the obtained data are compatible with the results of DSC and FTIR analyses.     

Mixed Supports in the Reversed-Phase Thin-Layer Chromatography of Amino Acids

Abstract

Lipophilicity of amino acids was determined by reversed-phase thin-layer chromatography using silica, aluminium oxide, cellulose, diatomaceous earth and their mixtures as supports with water as eluent.

To compare the retention behaviour of supports principal component analysis /PCA/ was applied. The potency order and the selectivity of support mixtures was calculated by the spectral map technique. Linear and logarithmic correlations were calculated between the first PCA loadings and the potency values as dependent variables and the composition of supports as independent variables.

The first eigenvalue explained more than 90% of the total variance that is only one hidden factor influenced decisively the retention. On the basis of structural differences the retention strength of amino acids on support mixtures can not be explained adequately. The first principal component responsible for the 90% of change in the retention of amino acids is related to the logarithm of support composition that is the sorbents retain their original adsorptive character also after impregnation.     

Multivariate analysis of chromatographic retention data and lipophilicity of phenylacetamide derivatives

One of the most important physicochemical parameters of a molecule that determines its bioactivity is its lipophilicity. Cluster analysis (CA), principal component analysis (PCA), and sum of ranking differences (SRD) were used to compare the lipophilic parameters of twenty phenylacetamide derivatives, obtained experimentally as chromatographic retention data in the presence of different solvents and calculated by different mathematical methods. All the applied methods of multivariate analysis gave approximately similar grouping of the studied lipophilic parameters. In the attempt to group the investigated compounds in respect of their lipophilicity, the obtained results appeared to be dependent on the applied chemometric method. The CA and PCA, grouped the compounds on the basis of the nature of the substituents R₁ and R₂, indicating that they determine to a great extent the lipophilicity of the investigated molecules. Unlike them, the SRD method could not be used to group the studied compounds on the basis of their lipophilic character.     

SVD-based principal component analysis of geochemical data

Principal Component Analysis (PCA) was used for the mapping of geochemical data. A testing data matrix was prepared from the chemical and physical analyses of the coals altered by thermal and oxidation effects. PCA based on Singular Value Decomposition (SVD) of the standardized (centered and scaled by the standard deviation) data matrix revealed three principal components explaining 85.2% of the variance. Combining the scatter and components weights plots with knowledge of the composition of tested samples, the coal samples were divided into seven groups depending on the degree of their oxidation and thermal alteration. The PCA findings were verified by other multivariate methods. The relationships among geochemical variables were successfully confirmed by Factor Analysis (FA). The data structure was also described by the Average Group dendrogram using Euclidean distance. The found sample clusters were not defined so clearly as in the case of PCA. It can be explained by the PCA filtration of the data noise.     

顶空固相微萃取-全二维气相色谱/飞行时间质谱法分析闽南乌龙茶中的挥发性成分及其在分类中的应用

采用顶空固相微萃取(HS-SPME)结合全二维气相色谱/飞行时间质谱(GC×GC-TOF MS)分析了闽南乌龙茶中的挥发性成分。从48份不同等级和产季的乌龙茶(铁观音、黄金桂、本山、毛蟹和梅占)中获得了2000余种挥发性化合物,经筛选得到51种共有组分,并结合质谱数据库、保留指数与结构谱图等进行了初步鉴定。在此基础上采用主成分分析法(PCA)获得得分投影图,直观给出了不同样品的分类趋势。通过逐步判别获得9种对分类结果有显著影响的组分,并以此为变量通过Fisher判别法(FDA)建立了4个判别函数,对样品的分类准确率达到97.9%。本试验证实了以挥发性成分识别闽南乌龙茶的可行性。     

Classification of byzantine glass samples by principal component analysis

Summary Nine samples of byzantine glass classified previously by cluster analysis are classified by principal component analysis (PCA). A visual inspection of plots in coordinates of the first two principal components gives essentially the same results as cluster analysis. In addition, PCA indicates relationships among the classification variables.

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Klassifizierung byzantinischer Glasproben durch Analyse der Hauptbestandteile

     

Effect of solvent extraction on the atomic-absorption spectrophotometry in determination of ppM levels of cadmium with dithizone

Various organic solvents for cadmium dithizonate extraction have been examined for their suitability for subsequent absorption spectrophotometry. The solvents are discussed on the basis of their physical properties. Much enhanced sensitivity is achieved by use of a large aqueous phase/solvent volume ratio. Conditions for the determination of ppM levels of cadmium are described for nitrobenzene and n-butyl acetate as solvents. Dithizone and cadmium dithizonate are very stable in nitrobenzene. The extraction is completely quantitative over the pH range 3.5-10.0. Interference by diverse ions was studied, and their tolerance levels are given.     

能量色散X射线散射结合主成分分析对液体易制毒化学品的探测与鉴别分类

采用能量色散X射线散射(EDXRS)技术探测了8种液体易制毒化学品的X射线散射光谱, 结果显示液体易制毒物质具有各自特征的EDXRS散射图谱. 将液体易制毒化学品的EDXRS散射信息与主成分分析结合, 发现前2个主成分可以表达X射线散射光谱的主要信息, 在PC1～PC2得分分布图上可将液体易制毒化学品进行分类. 研究结果表明, EDXRS光谱技术结合主成分分析法可以实现探测、 鉴别分类液体易制毒化学品, 为隐藏液体易制毒化学品的监管控制提供一个可行的鉴别方法.     

Principal component analysis of polarity and interaction parameters in inverse gas chromatography

Inverse gas chromatography is used in the characterization of aliphatic-aromatic and aromatic ketones, their oximes, and ketone-oxime or oxime-oxime mixtures. All these organic materials are used as liquid stationary phases in gas chromatographic columns. A series of polarity and Flory-Huggins interaction parameters are determined and used to describe the physicochemical properties of examined materials, metal extractants, and products of their degradation. Principal component analysis (PCA) is performed on a data matrix consisting of polarity and interaction parameters for ketones, their oximes, and mixtures. The calculations are carried out on the correlation matrix. It is found that seven principal components account for more than 95% of the total variance in the data, indicating that the polarity (interaction) parameters are not correlating well. Physical meanings are attributed to the principal components, the most influential ones being that the first and the second principal components account for several Flory-Huggins interaction parameters, whereas the fifth is correlated with criterion "A". The plots of component loadings show characteristic groupings of polarity indicators, whereas that of component scores show several groupings of stationary phases. Cluster analysis provides mainly the same groupings. PCA allows for the grouping of polarity and solubility parameters based on the information carried within those parameters. There is no need to use more than one parameter from each cluster. McReynolds polarity and the partial molar excess Gibbs free energy of solution per methylene group carry the same information. The groups of ketones, oximes, and their mixtures can be distinguished with the use of PCA on the basis of the measured polarity, solubility parameters, or both.     

Rime samples characterization and comparison using classical and fuzzy principal components analysis

The main objective of this paper is to introduce principal component analysis and two robust fuzzy principal component algorithms as useful tools in characterizing and comparing rime samples collected in different locations in Poland (2004–2007). The efficiency of the applied procedures was illustrated on a data set containing 108 rime samples and concentration of anions, cations, HCHO, as well as pH and conductivity. The fuzzy principal component algorithms achieved better results mainly because they are more compressible than classical PCA and very robust to outliers. For example, a three component model, fuzzy principal component analysis-first component (FPCA-1) accounts for 62.37% of the total variance and fuzzy principal component analysis-orthogonal (FPCA-o) 90.11%; PCA accounts only for 58.30%. The first two principal components explain 51.41% of the total variance in the case of FPCA-1 and 79.59% in the case of FPCA-o as compared to only 47.55% for PCA. As a direct consequence, PCA showed only a partial differentiation of rime samples onto the plane or in the space described by different combination of two or three principal components, whereas a much sharper differentiation of the samples, regarding their origin and location, is observed when FPCAs are applied.      

碳纳米管的共价修饰

碳纳米管(carbon nanotubes, CNTs)的溶解性和分散性较差是目前制约其广泛应用及在一些有特殊要求的领域(如生物技术)应用的主要原因之一. 对CNTs进行共价修饰是改善其溶解性和分散性的有效方法之一. 目前CNTs的共价修饰主要通过两类反应来实现: 羧基的衍生反应和直接加成反应. 介绍了基于这两种反应的几种共价修饰方法, 比较了各种修饰方法的优缺点及其对CNTs的溶解性和分散性的改善效果.     

Use of Byproducts of Acidic Processing of Aluminium – Bearing Raw Materials in Production of Heat Insulating Materials

The principal possibility to use byproducts of acidic processing of aluminium-bearing raw materials as the main component of batch to obtain a heat insulating material using low-temperature technology is established. The compositions suitable to obtain low-temperature frit and a foam glass material on its basis are developed. The obtained material has improved physical – mechanical properties in comparison with conventional foam glass from broken glass.     

Chemometrics characterisation of the quality of river water

Within the period from autumn 1990 to spring 1999 (from October to April in each period) 207 samples were collected and the measurement of 19 physical and chemical variables of the Mura river, Slovenia, were carried out. These variables are: river flow, water temperature, air temperature, dissolved oxygen, deficit of oxygen, oxygen saturation index, chemical oxygen demand (COD) in unfiltered and filtered samples, and biochemical oxygen demand after 5 days (BOD5) in unfiltered and filtered samples, pH, conductivity, ammonium, nitrite, nitrate, and phosphate concentrations, adsorbable organic halogens (AOX), dissolved organic carbon (DOC), and suspended solids. For handling the results of all measurements different chemometrics methods were employed: (i) the basic statistical methods for the determination of mean and median values, standard deviations, minimal and maximal values of measured variables, and their mutual correlation coefficients, (ii) the principal component analysis (PCA), and (iii) the clustering method based on Kohonen neural network. The influences of season, month, sampling site, and sampling time on the pollutant levels were examined. Before 1993, the pulp and paper industry was the main source of pollutants because of large amounts of chlorine emission as a consequence of industrial treatment, the leaching of cellulose. After the year 1993, the technology was changed and the quality of the river water has improved. The improvement could be detected 1 year after the change of technology. For one part of water samples the river quality classes based on biological parameters were also determined. The correlation between the biologically determined quality classes and chemical measurements was sought. Consequently, the biological classification for the water samples based on the chemical analyses was studied.