Results, analytical, interpretation

Clinical and analytical interpretation of false-negative and false-positive results. 

EXMAT - A Linked Network of Expert Systems for Materials Analysis. Seven individual expert systems comprise EXMAT (1) problem definition and analytical strategy (2) instrumental configuration and conditions (3) data generation (4) chemometric/search algorithms (5) results (6) interpretation (7) analytical goals. Dynamic headspace (DHS)/GC and pyrolysis GC (PGC)/concentrators... 

Preparation of the patient, sampling of specimens Pre-analytical handling of specimens Accurate and precise analytical performance Selection of appropriate, sensitive and specific methods Calibration of analytical systems Internal and external quality assurance Post-analytical handling of test results Clinical interpretation of test results Reporting process... 

Expression and Interpretation of Results. Archaeological interpretation of a radiocarbon age may depend critically on the error associated with that age. Errors are commonly expressed as a variance range attached to the central number (e.g., 2250 80 years). The 80 years in this example may correspond to the random error for a single analytical step. Both decay and direct-atom counting are statistical in nature, and lead to errors that vary as the square root of the number of counts. The error may also be expressed as the overall random experimental error (the sum of individual errors.) Overall random error can be determined only by analyzing replicate samples. 

J. D., Bernasconi, P., Chen, M., Coudurier, L., Galasinski, S., Jadhav, A.P., Janzen, W.P., Lagasca, D., Liu, D., Lewis, R.S., Mohney, R.P., Sepetov, N., Sparkman, D.A. and Hodge, C.N. (2004) Streamlined system for purifying and quantifying a diverse library of compounds and the effect of compound concentration measurements on the accurate interpretation of biological assay results. Analytical Chemistry, 76,7278—7287. 

Related to the difficulties associated with reproducibility, is the challenge presented by comparison of many—perhaps hundreds to tens of thousands of—complex spectra and the resulting data interpretation. Several groups have developed their own analytical and software solutions to this problem. Jarman et al. [33] and Bright et al. [29], for example, developed methods to automatically compare spectra of unknown bacteria with those of library entries to accomplish high-quality identifications. The recent emergence of bacteria as potential terror weapons will likely spur further efforts in the development... 

Additionally, sediment samples of the Lippe river (Germany) were investigated by non-target screening analyses. Within the present study so far unknown or rarely detected contaminants as well as anthropogenic molecular marker compounds were selected for quantification. The obtained qualitative and quantitative analytical results were interpreted in order to characterize the anthropogenic contamination of the particulate... 

Fullerenes. - Jonsson et al.234 have carried out analytical Hartree-Fock calculations, expected to be near the basis set limit, of a, and the magnetiz-ability for the C70 and C84 fullerenes. The results are compared with earlier calculations on ) and the electronic structures of the molecules discussed. Moore et al.235 have made semi-empirical AMI finite field calculations of the static y-hyperpolarizability of Qo, C70, five isomers of C78 and two isomers of C84. The results are interpreted in terms of bonding and structural features. 

Let us suppose that you are a representative working for an environmental consulting firm and you are asked to choose which company, Lab X or Lab Y, should be hired to analyze your contaminated soil samples from this hypothetical hazardous waste site. Let us also assume that the samples come from a Superfund site and that you are interested in the lab providing you with analytical results and interpretation for semivolatile organics using EPA Method 8270C. You receive analytical results from Lab X, and from Lab Y as shown in Table 2.2. Based on your interpretation of the reports from both companies, which lab would you choose to contract with for the analysis It should be obvious ... 

These analytical results are interpreted by a chain radical mechanism at zero time, the chains are propagated by the processes ... 

These considerations relate to inter- and intrasample variations that must be characterized before analytical results are interpreted. For example, suppose tfiat a questioned paper and a l wn paper had different concentratitHis of three elements, as shown in Table 14.1. There is not enough information in the table to interpret the... 

A theoretical study has taken place of the behaviour of nuclear quadrupole spin-lattice relaxation in the reorientational motion of molecules in a three-well potential field, with one deep and two identical shallow wells. Application of the results to interpretation of the C1 NQR data for Cl3P=NCCl(CF3)2 was discussed. An analytical expression has been obtained for a normalised function of the shape of an idealised NQR nutation line of a powdered sample, with I = and It was applied to the Cl resonance for TiCl4 at 77 K, enabling an q... 

Ireland TR (1995) Ion microprobe mass spectrometry. In Hyman M and Rowe M (eds) Techniques and Applications in Cosmochemistry, Geochemistry and Geochronology in Advances in Analytical Chemistry, Volume II, pp 51-118. Greenwich (UK) JAI Press. Krankowsky D and Eberhardt P (1990). In Mason JW and Horwood E (eds) Comet Halley Investigations, Results and Interpretations, Volume 1, pp. 273-296. New York Simon and Schuster. 

For interpretation and extrapolation of the experimental results the central role of a computer code as vital analytical tool has been emphasized. In Ref. 7 an attempt is made to identify areas of particular interest. For these great care should be exercised, when scaled experimental results are interpreted and extrapolated with the aid of dimensional analysis of a fypical set of conservation equations normally used in the lumped parameter codes. Two basic assumptions have been made in the course of the dimensional analysis. These are the geometrical similarity of the test fecilify and the prototype plant and performing the experiments with the same fluid compon ts, which are expected to dominate within the containment atmosphere of the prototype plant. Both of the two basic assumptions are valid in the VICTORIA test fecilify. 

It is the purpose of this and the following chapter to report the quantitative data concerning the relationship of structure to orientation and reactivity in aromatic nitration. Where data obtained by modern analytical methods are available they are usually quoted in preference to the results of older work. Many of the papers containing the latter are, however, noted in the brief discussion which is given of interpretations of the results. 

An analytical procedure is often tested on materials of known composition. These materials may be pure substances, standard samples, or materials analyzed by some other more accurate method. Repeated determinations on a known material furnish data for both an estimate of the precision and a test for the presence of a constant error in the results. The standard deviation is found from Equation 12 (with the known composition replacing /x). A calculated value for t (Eq. 14) in excess of the appropriate value in Table 2.27 is interpreted as evidence of the presence of a constant error at the indicated level of significance. 

The Vinland Map, supposed evidence of the Viking discovery of America long before Columbus, was proclaimed a forgery after the detection in the ink of titanium white, a modem pigment (see Pigments, inorganic) (13). Subsequendy, however, after another analytical study, the interpretation of the eadiet results has been questioned, and the matter of authenticity of this unique document stiU remains an open question (14,15). 

One of the main attractions of normal mode analysis is that the results are easily visualized. One can sort the modes in tenns of their contributions to the total MSF and concentrate on only those with the largest contributions. Each individual mode can be visualized as a collective motion that is certainly easier to interpret than the welter of information generated by a molecular dynamics trajectory. Figure 4 shows the first two normal modes of human lysozyme analyzed for their dynamic domains and hinge axes, showing how clean the results can sometimes be. However, recent analytical tools for molecular dynamics trajectories, such as the principal component analysis or essential dynamics method [25,62-64], promise also to provide equally clean, and perhaps more realistic, visualizations. That said, molecular dynamics is also limited in that many of the functional motions in biological molecules occur in time scales well beyond what is currently possible to simulate. 

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