Chemical fingerprinting sources

Analyses conducted at LBNL (41-42) on artifacts from on a multi-component site known as Waywaka in the town of Andahuaylas in the Department of Apurimac exhibited two chemical fingerprints rarely detected outside the Andahuaylas area. The chemical types were assigned the names Andahuaylas A and Andahuaylas B by Burger and Asaro who were strongly convinced that the sources were located in this region. 

Many other important application areas of chemometrics have been the subject of reviews and are too numerous to list here. A sampling of reviews in this category illustrates the breadth and diversity of chemometrics application areas. A review of applications in smart sensors [54] describes how chemometrics is an important enabling technology for the development of smart and reliable sensor systems. A review of environmental forensics [55] describes how numerical methods are critical in the process of identifying the chemical fingerprints of complex contaminant sources in environmental systems. Often, multiple sources are present at different geographic sites. By use of appropriate chemometric methods, these mixtures of different sources can be mathematically resolved to identify them and map their temporal and spatial distributions. 

As for the non-uniqueness of the solution, there is no method that can bypass this inherent problem. In inverse problems, one of the common practices to overcome the stability and non-uniqueness criteria is to make assumptions about the nature of the unknown function so that the finite amount of data in observations is sufficient to determine that function. This can be achieved by converting the ill-posed problem to a properly posed one by stabilization or regularization methods. In the case of groundwater pollution source identification, most of the time we have additional information such as potential release sites and chemical fingerprints of the plume that can help us in the task at hand. 

Modeling of the whole-rock and mineral trace-element compositions in xenoliths that have experienced metasomatic infiltration of melts led Ionov et al. (2002a) to conclude that the REE and HFSE element compositions of peridotites adjacent to veins bear the chemical fingerprints of the metasomatic agent closest to its source (e.g., a melt vein). Further away, signatures are increasingly dominated by fractionation processes related to melt percolation. 

Since Sleeter s review, several cases have been tried using chemical fingerprinting to determine the source of an oil spill. The three cases tried in 1977 emphasized the importance of documentation, beginning with the taking of the sample (long before the chemist becomes involved) and requiring an unbroken chain of custody until the sample is disposed of. 

Authentication of pjropohs material may be possible by a chemical fingerprint of it and, if possible, of its botanical sources. Thus, chemical fingerprinting, i.e., metabolomics and chemometrics, is an additional method that has been claimed to be included as a quality control method in order to confirm or deny the ptropohs sample being used for the manufacturing of a derived product of that resinous and complex matrix. 

Hinselmann G, Rosenbaum L, Jahn A, Fechner N, Zell AJ (2011) Compound Mapper an open source JAVA library and command line tool for chemical fingerprints. J Chemoinformatics 3 3... 

In a similar vein, it was hoped that a correlation would be found between higher antimony levels and the Annamese coins, as well as the Chinese coins of the southern mints, especially Hunan, since this province is a major source of antimony today. The presence of antimony could then be used as a chemical fingerprint for the ores from which the coins metals were produced. That correlation does not appear to be readily apparent however. In the Chinese series, less than five coins have higher than 5% antimony concentration, while in the Annamese series, the antimony concentration only rises above 1% once. In like fashion, arsenic occurs as only a trace component of the coins. 

Classification problems are numerous in food sdenee, for example, classification methods are nsed to determine a food s origin based on chemical fingerprints [9], but can also discriminate among different fig cultivars with sensory attributes, independent of the source and harvest date of the different cultivars [10]. CVA is just one of maity classification techniques, and the reader is referred to specific articles, e.g., partial least squares discriminant analysis (PLS-DA) [11], artificial neural networks (ANNs) [12], and support vector machines (SVMs) [13]. 

If the source fingerprints, for each of n sources are known and the number of sources is less than or equal to the number of measured species (n < m), an estimate for the solution to the system of equations (3) can be obtained. If m > n, then the set of equations is overdetermined, and least-squares or linear programming techniques are used to solve for L. This is the basis of the chemical mass balance (CMB) method (20,21). If each source emits a particular species unique to it, then a very simple tracer technique can be used (5). Examples of commonly used tracers are lead and bromine from mobile sources, nickel from fuel oil, and sodium from sea salt. The condition that each source have a unique tracer species is not often met in practice. 

The hormone itself can introduce complexity into bioassays. Many hormones must now be seen and understood not as chemical entities but as chemical pathways where hormonal activity is distributed across a number of chemical species. The more we learn about the pharmacological properties of members of a pathway, the more we are realizing that each one has a mix of common and unique properties. The practical point is that we must be careful about which hormone we choose to drive our bioassays. A hormonal chemical pathway may contain sinks as well as sources. Metabolism and uptake of a hormone can introduce significant distortions into bioassays. All of these factors leave their fingerprints on dose-response curves, and a pharmaceutical researcher developing a new bioassay has to learn to read the signs. 

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