Big Chemical Encyclopedia

Chemical substances, components, reactions, process design ...

Articles Figures Tables About

Principal stepwise

Only one exception to the clean production of two monomer molecules from the pyrolysis of dimer has been noted. When a-hydroxydi-Zvxyljlene (9) is subjected to the Gorham process, no polymer is formed, and the 16-carbon aldehyde (10) is the principal product in its stead, isolated in greater than 90% yield. This transformation indicates that, at least in this case, the cleavage of dimer proceeds in stepwise fashion rather than by a concerted process in which both methylene—methylene bonds are broken at the same time. This is consistent with the predictions of Woodward and Hoffmann from orbital symmetry considerations for such [6 + 6] cycloreversion reactions in the ground state (5). [Pg.428]

As a preparative route to A -3-ketones, the anhydrous reaction in benzene at room temperature gives 40-55 % of product after chromatography and is inferior to a stepwise conversion (via A -3-ketone). The principal side reaction (which also occurs in the acid catalyzed reaction of A -3-ketones with two moles of DDQ) appears to be addition of the hydroquinone ... [Pg.312]

Principal component analysis (PCA) of the soil physico-chemical or the antibiotic resistance data set was performed with the SPSS software. Before PCA, the row MPN values were log-ratio transformed (ter Braak and Smilauer 1998) each MPN was logio -transformed, then, divided by sum of the 16 log-transformed values. Simple linear regression analysis between scores on PCs based on the antibiotic resistance profiles and the soil physico-chemical characteristics was also performed using the SPSS software. To find the PCs that significantly explain variation of SFI or SEF value, multiple regression analysis between SFI or SEF values and PC scores was also performed using the SPSS software. The stepwise method at the default criteria (p=0.05 for inclusion and 0.10 for removal) was chosen. [Pg.324]

In this paper the PLS method was introduced as a new tool in calculating statistical receptor models. It was compared with the two most popular methods currently applied to aerosol data Chemical Mass Balance Model and Target Transformation Factor Analysis. The characteristics of the PLS solution were discussed and its advantages over the other methods were pointed out. PLS is especially useful, when both the predictor and response variables are measured with noise and there is high correlation in both blocks. It has been proved in several other chemical applications, that its performance is equal to or better than multiple, stepwise, principal component and ridge regression. Our goal was to create a basis for its environmental chemical application. [Pg.295]

To avoid over-fitting, a commonly used approach is to select a subset of descriptors to build models. GAs are widely used to select descriptors prior to using other statistical tools, such as MLR, to build models. Certainly, principal component analysis and PLS fitting are also widely used in reducing the dimensions of descriptors. Traditionally, stepwise linear regression is used to select certain descriptors to enter the regression equations. [Pg.120]

Two basic mechanisms have been proposed to interpret methanol formation in the CO + H2 reaction. When carbon monoxide adsorbed on the copper surface is hydrogenated by the stepwise addition of hydrogen atoms [Eq. (3.42)], the principal intermediate is a surface formyl species (5) ... [Pg.115]

There are two principal modes for introducing the photophore into a peptide (1) Coupling a photoreactive N-protected amino acid during the stepwise assembly of the peptide e.g. in Scheme 3, the amino acid 4-benzoylphenylalanine (3) is incorporated into position 8 of substance P (9). (2) Post-synthetic modification of a fully assembled peptide, at either a free N-terminal a-amino group or a side-chain functionality, by the photophore in a site-specific or nonspecific manner e.g. in Scheme 3, treatment of cyclic R-G-D-containing peptide 10 with 4-benzoylbenzoic anhydride (11) gives the modified peptide 12. [Pg.88]

The principal exothermic term in a stepwise thermochemical analysis (such as we found useful in Chapter 5) will be the lattice energy of the product. This is not readily obtainable experimentally (unlike the lattice energies of simple ionic solids) and its magnitude is not amenable to any simple analysis. As we shall see a little later, a purely ionic description of such products is often inappropriate anyway. Let us focus attention on the ease of formation of AX x and BX +1. The removal of X- from AXm will be favoured by ... [Pg.323]

The search for alternatives to the stepwise addition of new addends to a mono-, bis-, or tris-adduct of Cr,o for the preparation of highly functionalized fullerenes has been a challenge since the beginning of fullerene chemistry. Here we present the principal approaches introduced to control the regiochemistry of multiple additions to fullerenes by the use of tethered addend systems. The tethered macro-cyclization method proved to be a major breakthrough and has provided relatively facile access to otherwise strongly disfavored addition patterns. [Pg.139]

Figure 2. Comparison of the- stepwise excitation results (O) with the model calculation ( ). The enhancement (the two-photon signal divided by the one-photon signal) normalized for laser energy is plotted against the absorption coefficient for the 3p -> nd transitions. For visual clarity a curve is drawn through the points of the model calculation and a dashed line of unit slope is drawn through the data at high principal quantum number, n. Figure 2. Comparison of the- stepwise excitation results (O) with the model calculation ( ). The enhancement (the two-photon signal divided by the one-photon signal) normalized for laser energy is plotted against the absorption coefficient for the 3p -> nd transitions. For visual clarity a curve is drawn through the points of the model calculation and a dashed line of unit slope is drawn through the data at high principal quantum number, n.
Figure 7.5 Principal components analysis applied to volatile compounds selected by stepwise linear discriminant analysis (source SEXIA Group-Instituto de la Grasa, Seville, Spain). Figure 7.5 Principal components analysis applied to volatile compounds selected by stepwise linear discriminant analysis (source SEXIA Group-Instituto de la Grasa, Seville, Spain).
Nielsen, B.R., Stapelfeldt, H., Skibsted, L.H. 1997. Early prediction of the shelf-life of medium-heat whole milk powders using stepwise multiple regression and principal component analysis. Int. Dairy J. 7, 341-348. [Pg.595]


See other pages where Principal stepwise is mentioned: [Pg.277]    [Pg.277]    [Pg.426]    [Pg.426]    [Pg.20]    [Pg.566]    [Pg.609]    [Pg.53]    [Pg.147]    [Pg.482]    [Pg.38]    [Pg.25]    [Pg.34]    [Pg.27]    [Pg.79]    [Pg.129]    [Pg.151]    [Pg.155]    [Pg.7]    [Pg.225]    [Pg.624]    [Pg.1442]    [Pg.254]    [Pg.624]    [Pg.445]    [Pg.318]    [Pg.1037]    [Pg.293]    [Pg.62]    [Pg.50]    [Pg.224]    [Pg.223]    [Pg.225]    [Pg.176]    [Pg.536]    [Pg.169]    [Pg.25]   
See also in sourсe #XX -- [ Pg.141 ]




SEARCH



Stepwise

Stepwise principal component regression

© 2024 chempedia.info