917 resultados para correlation analysis


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Spectroscopic studies of complex clinical fluids have led to the application of a more holistic approach to their chemical analysis becoming more popular and widely employed. The efficient and effective interpretation of multidimensional spectroscopic data relies on many chemometric techniques and one such group of tools is represented by so-called correlation analysis methods. Typical of these techniques are two-dimensional correlation analysis and statistical total correlation spectroscopy (STOCSY). Whilst the former has largely been applied to optical spectroscopic analysis, STOCSY was developed and has been applied almost exclusively to NMR metabonomic studies. Using a 1H NMR study of human blood plasma, from subjects recovering from exhaustive exercise trials, the basic concepts and applications of these techniques are examined. Typical information from their application to NMR-based metabonomics is presented and their value in aiding interpretation of NMR data obtained from biological systems is illustrated. Major energy metabolites are identified in the NMR spectra and the dynamics of their appearance and removal from plasma during exercise recovery are illustrated and discussed. The complementary nature of two-dimensional correlation analysis and statistical total correlation spectroscopy are highlighted.

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In the present study, variable temperature FT-IR spectroscopic investigations were used to characterize the spectral changes in oleic acid during heating oleic acid in the temperature range from -30 degrees;C to 22 degrees C. In order to extract more information about the spectral variations taking place during the phase transition process, 2D correlation spectroscopy (2DCOS) was employed for the stretching (C?O) and rocking (CH2) band of oleic acid. However, the interpretation of these spectral variations in the FT-IR spectra is not straightforward, because the absorption bands are heavily overlapped and change due to two processes: recrystallization of the ?-phase and melting of the oleic acid. Furthermore, the solid phase transition from the ?- to the a-phase was also observed between -4 degrees C and -2 degrees C. Thus, for a more detailed 2DCOS analysis, we have split up the spectral data set in the subsets recorded between -30 degrees C to -16 degrees C, -16 degrees C to 10 degrees C, and 10 degrees C to 22 degrees C. In the corresponding synchronous and asynchronous 2D correlation plots, absorption bands that are characteristic of the crystalline and amorphous regions of oleic acid were separated.

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The utility of canonical correlation analysis (CCA) for domain adaptation (DA) in the context of multi-view head pose estimation is examined in this work. We consider the three problems studied in 1], where different DA approaches are explored to transfer head pose-related knowledge from an extensively labeled source dataset to a sparsely labeled target set, whose attributes are vastly different from the source. CCA is found to benefit DA for all the three problems, and the use of a covariance profile-based diagonality score (DS) also improves classification performance with respect to a nearest neighbor (NN) classifier.

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The structural properties for various SiCO isomers in the singlet and triplet states have been investigated using CASSCF methods with a 6-311 +G* basis set and also using three DFT and MP2 with same basis set for those systems except for the linear singlet state. The detailed bonding character is discussed, and the state-state correlations and the isomerization mechanism are also determined. Results indicate that there are four different isomers for each spin state, and for all isomers, the triplet state is more stable than the corresponding singlet state. The most stable is the linear SiCO ((3)Sigma(-)) species and may be refer-red to the ground state. At the CASSCF-MP2(full)/6-311+G* level, the state-state energy separations of the other triplet states relative to the ground state are 43.2 (cyclic), 45.2 (linear SiOC), and 75.6 kcal/mol (linear CSiO), respectively, whereas the triplet-singlet state excitation energies for each configuration are 17.3 (linear SiCO), 2.2 (cyclic SiCO), 10.2 (linear SiOC), and 18.5 kcal/mol (linear CSiO), respectively. SiCo ((3)Sigma(-)) may be classified as silene (carbonylsilene), and its COdelta- moiety possesses CO- property. The dissociation energy of the ground state is 42.5 kcal/mol at the CASSCF-MP2(full)/6-311+G* level and falls within a range of 36.5-41.5 kcal/mol at DFT level, and of 23.7-28.9 kcal/mol at the wave function-correlated level, whereas the vertical IP is 188.8 kcal/mol at the CASSCF-MP2(full)/6-311+G* level and is very close to the first IP of Si atom. Three linear isomers (SiCO, SiOC, and CSiO) have similar structural bonding character. SiOC may be referred to the iso-carbonyl Si instead of the aether compound, whereas the CSiO isomer may be considered as the combination of C (the analogue of Si) with SiO (the analogue of CO). The bonding is weak for all linear species, and the corresponding potential energy surfaces are flat, and thus these linear molecules are facile. Another important isomer is of cyclic structure, it may be considered as the combination of CO with Si by the side pi bond. This structure has the smallest triplet state-singlet state excitation energy (similar to2.2 kcal/mol); the C-O bonds are longer, and the corresponding vibrational frequencies are significantly smaller than those of the other linear species. This cyclic species is not classified as an epoxy compound. State-state correlation analysis and the isomerization pathway searches have indicated that there are no direct correlations among three linear structures for each spin state, but they may interchange by experiencing two transition states and one cyclic intermediate. The easiest pathway is to break the Si-O bond to go to the linear SiCO, but its inverse process is very difficult. The most difficult process is to break the C-O bond and to go to the linear CSiO.

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To simplify the abstraction of descriptors, for the correlation analysis of the stability constants of gadolinium(III) complexes and their ligand structures, aiming at gadolinium(III) complexes, we only considered the ligands and ignored the common parts of the structures, i.e., the metal ions. Quantum-chemical descriptors and topological indices were calculated to describe the structures of the ligands. Multiple regression analysis and neural networks were applied to construct the models between the ligands and the stability constants of gadolinium(III) complexes and satisfactory results were obtained.

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The quantum-chemical descriptors were used for QSPR study of the structures of carboxylic acids and their pK(a) values. The algorithm of "Leaps and Bounds" regression was performed for selection of the variables. The CoMFA method was carried out for 3D-QSPR. As the introduction of the charge of oxygen atom(Q(2)), the results obtained by CoMFA were improved greatly.

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Quantitative structure-retention relationship(QSRR) was studied for amines to gas-liquid chromatography on three stationary phases of different polarities with the topological indices A(m) (A(m1), A(m2), A(m3)) and gravitational index GI. The algorithm of "Leaps and Bounds" was performed for selection of the variables. And the multi-regression and the quasi-Newton neural networks were employed for the calculation with better results.

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This approach is undertaken to examine the correlation ability of the general a(N)-index (GAI) to predict chromatographic behavior. The test is performed on various types of organophosphorus compounds. The results demonstrate that the GAI possesses a good correlation with chromatographic properties.

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This paper introduces two new techniques for determining nonlinear canonical correlation coefficients between two variable sets. A genetic strategy is incorporated to determine these coefficients. Compared to existing methods for nonlinear canonical correlation analysis (NLCCA), the benefits here are that the nonlinear mapping requires fewer parameters to be determined, consequently a more parsimonious NLCCA model can be established which is therefore simpler to interpret. A further contribution of the paper is the investigation of a variety of nonlinear deflation procedures for determining the subsequent nonlinear canonical coefficients. The benefits of the new approaches presented are demonstrated by application to an example from the literature and to recorded data from an industrial melter process. These studies show the advantages of the new NLCCA techniques presented and suggest that a nonlinear deflation procedure should be considered. (c) 2006 Elsevier B.V. All rights reserved.