Sample recognition

In principle, odors may be determined by means of sample recognition with the help of arrays of gas sensors, so-called electronic noses. Unknown samples are compared with known samples. Hence, olfactometric investigations need to precede. Such a measuring device is applicable only in a specific case and has to be trained prior to use. Odor can become a controllable quality feature of a product. Samples of good quality can be made distinguishable from samples of bad quality. 

The computer system SARD-21 (Structure Activity Relationship Design) that implements the basic principles of sample recognition theory was used to investigate the structure-activity relationship [6]. Two models for predicting and recognizing interval levels of inhibiting activity of potential different classes of N-. 0-. and S-containing 5-LOX inhibitors were constructed in terms of the basic procedures of the SARD-21 system. 

A significant advantage of the PLM is in the differentiation and recognition of various forms of the same chemical substance polymorphic forms, eg, brookite, mtile, and anatase, three forms of titanium dioxide calcite, aragonite and vaterite, all forms of calcium carbonate Eorms I, II, III, and IV of HMX (a high explosive), etc. This is an important appHcation because most elements and compounds possess different crystal forms with very different physical properties. PLM is the only instmment mandated by the U.S. Environmental Protection Agency (EPA) for the detection and identification of the six forms of asbestos (qv) and other fibers in bulk samples. 

A study was conducted to measure the concentration of D-fenfluramine HCl (desired product) and L-fenfluramine HCl (enantiomeric impurity) in the final pharmaceutical product, in the possible presence of its isomeric variants (57). Sensitivity, stabiUty, and specificity were enhanced by derivatizing the analyte with 3,5-dinitrophenylisocyanate using a Pirkle chiral recognition approach. Analysis of the caUbration curve data and quaUty assurance samples showed an overall assay precision of 1.78 and 2.52%, for D-fenfluramine HCl and L-fenfluramine, with an overall intra-assay precision of 4.75 and 3.67%, respectively. The minimum quantitation limit was 50 ng/mL, having a minimum signal-to-noise ratio of 10, with relative standard deviations of 2.39 and 3.62% for D-fenfluramine and L-fenfluramine. 

Rules of matrix algebra can be appHed to the manipulation and interpretation of data in this type of matrix format. One of the most basic operations that can be performed is to plot the samples in variable-by-variable plots. When the number of variables is as small as two then it is a simple and familiar matter to constmct and analyze the plot. But if the number of variables exceeds two or three, it is obviously impractical to try to interpret the data using simple bivariate plots. Pattern recognition provides computer tools far superior to bivariate plots for understanding the data stmcture in the //-dimensional vector space. 

The successful appHcation of pattern recognition methods depends on a number of assumptions (14). Obviously, there must be multiple samples from a system with multiple measurements consistendy made on each sample. For many techniques the system should be overdeterrnined the ratio of number of samples to number of measurements should be at least three. These techniques assume that the nearness of points in hyperspace faithfully redects the similarity of the properties of the samples. The data should be arranged in a data matrix with one row per sample, and the entries of each row should be the measurements made on the sample, as shown in Figure 1. The information needed to answer the questions must be implicitly contained in that data matrix, and the data representation must be conformable with the pattern recognition algorithms used. 

Often the goal of a data analysis problem requites more than simple classification of samples into known categories. It is very often desirable to have a means to detect oudiers and to derive an estimate of the level of confidence in a classification result. These ate things that go beyond sttictiy nonparametric pattern recognition procedures. Also of interest is the abiUty to empirically model each category so that it is possible to make quantitative correlations and predictions with external continuous properties. As a result, a modeling and classification method called SIMCA has been developed to provide these capabihties (29—31). 

Studies of shock-compressed matter have progressed to a point for which detailed, sophisticated technology can probe mechanical responses in considerable detail. The detailed measurements now available appear to provide descriptions beyond that which can be predicted or fully interpreted on an established theoretical basis. As the conditions encountered are so unusual, a heavy reliance must be placed on the credibility of the experiments. Of particular importance is a recognition of the restricted view provided by a particular experiment, from both loading and sample response capabilities. 

V. Pichon, M. Bouzige, C. Miege and M. C. Hennion, Immunosorbents natural molecular recognition materials for sample preparation of complex environmental matrices . Trends. Anal. Chem. 18 219-235 (1999). 

In order to reduce or eliminate off-line sample preparation, multidimensional chromatographic techniques have been employed in these difficult analyses. LC-GC has been employed in numerous applications that involve the analysis of poisonous compounds or metabolites from biological matrices such as fats and tissues, while GC-GC has been employed for complex samples, such as arson propellants and for samples in which special selectivity, such as chiral recognition, is required. Other techniques include on-line sample preparation methods, such as supercritical fluid extraction (SFE)-GC and LC-GC-GC. In many of these applications, the chromatographic method is coupled to mass spectrometry or another spectrometiic detector for final confirmation of the analyte identity, as required by many courts of law. 

GC-GC has typically been employed for complex samples or those requiring additional chemistry, such as chiral recognition, to be employed along with classical GC separation. Typical GC-GC systems employ multiple capillary columns connected... 

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