Principal component analysis -based application

Miller, W.G., Alberty, R.A. Kinetics of the reversible Michaelis-Menten mechanism and the applicability of the Steady-state Approximation. J. Am. Chem. Soc. 80, 5146-5151 (1958) Mirgolbabaei, H., Echekki, T. A novel principal component analysis-based acceleration scheme forLES-ODT An a priori study. Combust. Elame 160, 898-908 (2013)... 

An important application field of factor and principal component analysis is environmental analysis. Einax and Danzer [1989] used FA to characterize the emission sources of airborne particulates which have been sampled in urban screening networks in two cities and one single place. The result of factor analysis basing on the contents of 16 elements (Al, B, Ba, Cr, Cu, Fe, Mg, Mn, Mo, Ni, Pb, Si, Sn, Ti, V, Zn) determined by Optical Atomic Emission Spectrography can be seen in Fig. 8.17. In Table 8.3 the common factors, their essential loadings, and the sources derived from them are given. 

The extent of homogeneous mixing of pharmaceutical components such as active drug and excipients has been studied by near-IR spectroscopy. In an application note from NIRSystems, Inc. [47], principal component analysis and spectral matching techniques were used to develop a near-IR technique/algorithm for determination of an optimal mixture based upon spectral comparison with a standard mixture. One advantage of this technique is the use of second-derivative spectroscopy techniques to remove any slight baseline differences due to particle size variations. 

To illustrate the environmental application of the SIMCA method we examined a set of isomer specific analyses of sediment samples. The data examined were derived from more than 200 sediment samples taken from a study site on the Upper Mississippi River (41). These analytical data were transferred via magnetic tape from the laboratory data base to the Cyber 175 computer where principal component analysis were conducted on the isomer concentration data (ug/g each isomer). 

The molecular specificity of Fourier transform infrared (FTIR) lends itself quite well to applications in pharmaceutical development labs, as pointed out in a review article with some historical perspective.10 One of the more common applications of mid-IR in development is a real-time assessment of reaction completion when used in conjunction with standard multivariate statistical tools, such as partial least squares (PLS) and principal component analysis (PCA).18,19 Another clever use of FTIR is illustrated in Figure 9.1, where the real-time response of a probe-based spectroscopic analyzer afforded critical control in the charge of an activating agent (trifluoroacetic anhydride) to activate lactol. Due to stability and reactivity concerns, the in situ spectroscopic approach was... 

Clearly, what is required for a reliable recognition of all the peaks during the optimization procedure is information on the pure component spectra and the pure component peaks (elution profiles). A method to obtain both the spectral and the chromatographic data involves the application of a mathematical technique called principal component analysis (PCA) [592]. This method is based on the additivity of spectra according to Beer s law. The absorption (A) at a time / and wavelength A is given by... 

To establish a correlation between the concentrations of different kinds of nucleosides in a complex metabolic system and normal or abnormal states of human bodies, computer-aided pattern recognition methods are required (15, 16). Different kinds of pattern recognition methods based on multivariate data analysis such as principal component analysis (PCA) (8), partial least squares (16), stepwise discriminant analysis, and canonical discriminant analysis (10, 11) have been reported. Linear discriminant analysis (17, 18) and cluster analysis were also investigated (19,20). Artificial neural network (ANN) is a branch of chemometrics that resolves regression or classification problems. The applications of ANN in separation science and chemistry have been reported widely (21-23). For pattern recognition analysis in clinical study, ANN was also proven to be a promising method (8). 

In QSAR and QSPR studies, the standard ways of removing redundancy from large numbers of topological and topographical indices include principal component analysis, chi-squared analysis, and multiple regression analysis (MRA). Most QSAR and QSPR applications deal with very small datasets, and so the dimensionality does not cause a problem for PCA or chi-squared analysis. MRA does not impose any restrictions on the type and number of descriptors. The selection process is based on two principles, namely, to cover as much of parametric space as possible (principle of variance) while choosing independent descriptors (principle of orthogonality). 

A report where quantitative 2D NMR was applied to differentiation of beer brands was published by Khatib et al. They used 2D /-resolved NMR to improve resolution of components present in 2-butanol extracts of several beer brands. With application of principal component analysis they distinguished six lagers from each other based on their amino acid contents. They also discussed how the amount of compounds that have an important effect to the taste, like tyrosol, can be estimated with the method. 

With a large data set of structures and properties, it is possible to use multivariate statistical methods such as principal components analysis to try to identify patterns. The applications of statistics to chemistry is known as chemometrics and an internet search for this keyword will lead to a variety of useful sources of information on the field. Some QSAR methods are based on the molecular orbitals of the compounds in the... 

Traces of VOCs in human breath can be a symptom of diabetes, kidney failure, asthma or breast cancer. VOCs were mainly detected by mass spectroscopy with a ppb detection limit. The most advanced VOC sensor based on SWCNTs for medical application was introduced by Peng et al. (2008a, 2008b). This device is designed as an array of ten SWCNT chemiresistors coated with different non-polymeric organic layers. Since the responses of each chemiresistor are different, a principal component analysis of the measurement allows the direct discrimination between a healthy patient and a patient with cancer or renal diseases. The same authors have also highlighted the dramatic effect of humidity on the sensor response and have proposed coupling the device with a water extractor (Fig. 10.8). 

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