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PLS results

PLS results are presented In Tables V and VI. Loadings greater than 0.3 have been underlined. Loadings which may be Influenced by closure are flagged. The regression of Maple Leaf composition (fractional) on West Seattle composition reveals four components ... [Pg.47]

Three components are similar to the results for the West Seattle-Maple Leaf PLS model except that the acid aerosol component no longer has high a loading from nitrate. This specie Is ordinarily associated with automobile emissions. The Tolt site Is remote enough that auto emissions are not as Important an Influence on Che variability In rainwater composition as In Seattle. The fourth component for this PLS model might represent emissions from a cement plant which does not Influence Che West Seattle site. The soil factor is apparently local In nature since It appears In the PCA results but not the PLS results. [Pg.47]

Although the PCR and PLS algorithms are different, we do not feel there is overwhelming evidence to suggest that one method is superior to the other. Therefore, we do not have a strong recommendation when choosing between PCR and PLS. In practice, our tendency is to use PLS because of our experiences with it and the software tools we employ. Therefore, the examples discussed below only present the PLS results. [See Haaland and Thomas (1990) for additional readings.]... [Pg.325]

No conclusion could be reached from the global quenching of the signal after adsorption of methanol, but propyne can discriminate oxide ions of low coordination. Indeed, PL results indicate that Che- and Che2 ions are involved in propyne dissociation. On the basis of PL and IR (semiquantitative evaluation of the number of molecules dissociated per square meter) characterizing dissociative adsorption of propyne and in line with theoretical results showing that acetylene does not dissociate on CLc 2 (Nicholas et al., 1998), it is inferred that Mg3C—O and Mg —03c ion pairs are involved in propyne dissociation (Chizallet et al., 2006). [Pg.23]

Dermal exposure of mice to JP-8 in multiple small doses (50 pL/day for 4-5 days) or in larger single doses (300 pL) resulted in local and systemic effects on the immune system (e.g., suppressed contact- and delayed-hypersensitivity responses). [Pg.83]

Partial least squares Partial least squares (PLS) is a statistical technique often applied to relate physicochemical properties to one or several measurements of biological activity. The PLS results consist of two sets of computed factors which are, on the one hand, linear combinations of the chemical descriptors and, on the other hand, linear combinations of the biological activities. Partial least squares finds many applications in chemometrics and, e.g., in the Tripos CoMFA approach. Normally used in conjunction with cross-validation. [Pg.760]

The oxidative combustion wifli ion-selective electrode method described here can be used to accurately determine fluorine in liquid hydrocarbons and liquefied petroleum gases at levels down to 0.5 ng/pl. Results obtained are in good agreement with those achieved with the Wickbold Oxy-Hydrogen Combustion method. The oxidative combustion with ion-selective electrode method is less time consuming, less hazardous, and more sensitive than the Wickbold method. The analysis is also applicable to a range of sample types not discussed here, including aqueous based systems and solids. [Pg.238]

The increased PL results in an improved S/N ratio in oxygen monitoring, without any deterioration or change in the response time or the long-term stability of the sensor films (the particles affect t, independently of their concentration) [70]. The improved S/N can improve the analyte limit of detection (LOD), allow shortened data acquisition times, and enable the use of low-intensity excitation sources to minimize potential dye photobleaching. [Pg.70]

These pl< results are similar to such aUcyl analogues as 2-amino-2-mediylpropane (pJ a = 10.68 at 25°) and 3-amino-3-ediylpentane (pJ a = 10.59), and support the conclusion (96) that fliere is little strain in diis alicyclic molecule. [Pg.62]

Biological activities of new compounds can be predicted by transforming the PLS result into a multiple regression equation e.g. [608, 1010]). For a comparison... [Pg.167]

These polymers are then doped with 4-(dicyanomethylene)-2-methyl-6-(4-dimethylamino-styryl) H-pyran (DCM). The PL results mostly from the dopant. Namely, the optical spectra indicates that Forster energy transfer from the modified polymers to the dopant may occur and effect the light emission. ... [Pg.110]

Pressuremeter tests (PMT) were also carried out and the results obtained were shown in Figure 3.18. Based on the PL results above, the undrained shear strength, Su of the ground was determined following Amar et al. (1991). Together with the Su determined from Field Vane Shear (FVS) and Cone Penetration Test (CPT) for the same site, some statistical analysis was carried out to compare the scatter of the results as shown in Table 3.11. [Pg.64]

Figure 8 PLS analysis derives vectors u and t from the Y block (or y vector BA, = logarithms of relative affinities or other biological activities) and the X block (S,y = steric field variable of molecule i in the grid point j E,y = electrostatic field variable of molecule i in the grid point j) that are related to principal components. These latent variables are skewed within their confidence hyperboxes to achieve a maximum intercorrelation (diagram). SAMPLS is a PLS modification which first derives the covariance matrix of the X block and then the PLS result from this covariance matrix. Especially in cross-validation (see below), SAMPLS analysis is much faster than ordinary PLS analysis... Figure 8 PLS analysis derives vectors u and t from the Y block (or y vector BA, = logarithms of relative affinities or other biological activities) and the X block (S,y = steric field variable of molecule i in the grid point j E,y = electrostatic field variable of molecule i in the grid point j) that are related to principal components. These latent variables are skewed within their confidence hyperboxes to achieve a maximum intercorrelation (diagram). SAMPLS is a PLS modification which first derives the covariance matrix of the X block and then the PLS result from this covariance matrix. Especially in cross-validation (see below), SAMPLS analysis is much faster than ordinary PLS analysis...
ECVA consists of several steps that finally lead to the actual class membership prediction. First there is a matrix compression step using SVD (if number of variables exceed number of samples n>m)). This is followed by the calculation of covariance matrices, both for the within class variatiOTi and between class variation. Subsequently, a PLS is performed between these matrices and the class relationship and finally a linear discriminant analysis is performed on the PLS results. This indicates that ECVA is a very different classification technique than PLS-DA described above, which is why we have chosen to show how it performs in addition to the above-menti(Mied techniques. [Pg.492]

Compound Density Recommended Volume (pL) Resulting Concentration ... [Pg.339]


See other pages where PLS results is mentioned: [Pg.426]    [Pg.198]    [Pg.287]    [Pg.289]    [Pg.796]    [Pg.341]    [Pg.214]    [Pg.269]    [Pg.386]    [Pg.150]    [Pg.73]    [Pg.75]    [Pg.417]    [Pg.306]    [Pg.416]    [Pg.419]    [Pg.80]    [Pg.183]    [Pg.32]    [Pg.231]    [Pg.290]    [Pg.168]    [Pg.157]    [Pg.335]    [Pg.149]    [Pg.23]    [Pg.273]    [Pg.391]    [Pg.281]    [Pg.154]    [Pg.191]    [Pg.3342]    [Pg.203]    [Pg.413]    [Pg.414]   
See also in sourсe #XX -- [ Pg.102 ]




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