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Curve Resolution (curve + resolution)
Kinds of Curve Resolution Selected AbstractsApplication of Multivariate curve resolution-alternating least square methods on the resolution of overlapping CE peaks from different separation conditionsELECTROPHORESIS, Issue 20 2007Fang Zhang Abstract Discussed in this paper is the development of a new strategy to improve resolution of overlapping CE peaks by using second-order multivariate curve resolution with alternating least square (second-order MCR-ALS) methods. Several kinds of organic reagents are added, respectively, in buffers and sets of overlapping peaks with different separations are obtained. Augmented matrix is formed by the corresponding matrices of the overlapping peaks and is then analyzed by the second-order MCR-ALS method in order to use all data information to improve the precision of the resolution. Similarity between the resolved unit spectrum and the true one is used to assess the quality of the solutions provided by the above method. 3,4-Dihydropyrimidin-2-one derivatives (DHPOs) are used as model components and mixed artificially in order to obtain overlapping peaks. Three different impurity levels, 100, 20, and 10% relative to the main component, are used. With this strategy, the concentration profiles and spectra of impurities, which are no more than 10% of the main component, can be resolved from the overlapping peaks without pure standards participant in the analysis. The effects of the changes in the components spectra in the buffer with different organic reagents on the resolution are also evaluated, which are slight and can thus be ignored in the analysis. Individual data matrices (two-way data) are also analyzed by using MCR-ALS and heuristic evolving latent projections (HELP) methods and their results are compared with those when MCR-ALS is applied to augmented data matrix (three-way data) analysis. [source] In situ X-ray diffraction analysis of (CFx)n batteries: signal extraction by multivariate analysisJOURNAL OF APPLIED CRYSTALLOGRAPHY, Issue 6 2007Mark A. Rodriguez (CFx)n cathode reaction during discharge has been investigated using in situ X-ray diffraction (XRD). Mathematical treatment of the in situ XRD data set was performed using multivariate curve resolution with alternating least squares (MCR,ALS), a technique of multivariate analysis. MCR,ALS analysis successfully separated the relatively weak XRD signal intensity due to the chemical reaction from the other inert cell component signals. The resulting dynamic reaction component revealed the loss of (CFx)n cathode signal together with the simultaneous appearance of LiF by-product intensity. Careful examination of the XRD data set revealed an additional dynamic component which may be associated with the formation of an intermediate compound during the discharge process. [source] Model-based biological Raman spectral imagingJOURNAL OF CELLULAR BIOCHEMISTRY, Issue S39 2002Karen E. Shafer-Peltier Abstract Raman spectral imaging is a powerful tool for determining chemical information in a biological specimen. The challenge is to condense the large amount of spectral information into an easily visualized form with high information content. Researchers have applied a range of techniques, from peak-height ratios to sophisticated models, to produce interpretable Raman images. The purpose of this article is to review some of the more common imaging approaches, in particular principal components analysis, multivariate curve resolution, and Euclidean distance, as well as to present a new technique, morphological modeling. How to best extract meaningful chemical information using each imaging approach will be discussed and examples of images produced with each will be shown. J. Cell. Biochem. Suppl. 39: 125,137, 2002. © 2002 Wiley-Liss, Inc. [source] Deconvolution of femtosecond time-resolved spectroscopy data in multivariate curve resolution.JOURNAL OF CHEMOMETRICS, Issue 7-8 2010Application to the characterization of ultrafast photo-induced intramolecular proton transfer Abstract In femtosecond absorption spectroscopy, deconvolution of the measured kinetic traces is still an important issue as photochemical processes that may possess shorter characteristic times than the time resolution of the experiment are usually considered. In this work, we propose to perform deconvolution of the time-dependent concentration profiles extracted from multivariate curve resolution (MCR) applied to spectrokinetic data. The profiles are fitted with a model function including a description of the instrumental response function (IRF) of the experiment. The method combines the potential benefits of soft-modeling data analysis with the ones of hard-modeling for parameter estimation. The potential of the method is demonstrated first analyzing five synthetic data sets for which IRF of different widths are simulated. It is then successfully applied to resolve femtosecond UV-visible transient absorption spectroscopy data investigating the photodynamics of salicylidene aniline, a photochromic molecule of wide interest. Considering a time resolution of 150,fs for the IRF, a characteristic time of 45,fs is recovered for the first step of the photo-induced process which consists of an ultrafast intramolecular proton transfer. Our results also confirm the existence of an intermediate species with a characteristic time of 240,fs. Copyright © 2010 John Wiley & Sons, Ltd. [source] Studies on the adaptability of different Borgen norms applied in self-modeling curve resolution (SMCR) methodJOURNAL OF CHEMOMETRICS, Issue 6 2009Róbert Rajkó Abstract Lawton and Sylvestre, and later Borgen et al. provided first the analytical solution for determining feasible regions of self-modeling curve resolution (SMCR) method for two- and three-component systems, respectively. After 20 years, Rajkó and István recently revitalized Borgen's method given a clear interpretation and algorithm how to draw Borgen plots using computer geometry tools; later Rajkó proved the existence of the natural duality in minimal constrained SMCR. In both latter cases, 1-norm was used to normalize raw data; however Borgen et al. introduced a more general class of normalization. In this paper, the definition and detailed descriptions of Borgen norms are given firstly appearing in the chemical literature. Some theoretical and practical studies on the adaptability of some Borgen norms used for SMCR method are also provided. Copyright © 2009 John Wiley & Sons, Ltd. [source] Focus on the potential of hybrid hard- and soft-MCR,ALS in time resolved spectroscopyJOURNAL OF CHEMOMETRICS, Issue 11-12 2008Lionel Blanchet Abstract This work presents some strategies to obtain time-dependent concentration profiles and spectra from time resolved spectroscopic data of complex systems. Multivariate curve resolution,alternating least squares (MCR,ALS) has been of particular interest in this field because of the possibility to implement simultaneously soft-modeling constraints and kinetic models on a multibatch resolution. This approach allows circumventing a rank deficiency inherent to time resolved difference data, even in presence of interferent species. The methodology is illustrated using examples from femtosecond photochemistry and biochemistry. Copyright © 2008 John Wiley & Sons, Ltd. [source] Weighting hyperspectral image data for improved multivariate curve resolution resultsJOURNAL OF CHEMOMETRICS, Issue 9 2008Howland D. T. Jones Abstract The combination of hyperspectral confocal fluorescence microscopy and multivariate curve resolution (MCR) provides an ideal system for improved quantitative imaging when multiple fluorophores are present. However, the presence of multiple noise sources limits the ability of MCR to accurately extract pure-component spectra when there is high spectral and/or spatial overlap between multiple fluorophores. Previously, MCR results were improved by weighting the spectral images for Poisson-distributed noise, but additional noise sources are often present. We have identified and quantified all the major noise sources in hyperspectral fluorescence images. Two primary noise sources were found: Poisson-distributed noise and detector-read noise. We present methods to quantify detector-read noise variance and to empirically determine the electron multiplying CCD (EMCCD) gain factor required to compute the Poisson noise variance. We have found that properly weighting spectral image data to account for both noise sources improved MCR accuracy. In this paper, we demonstrate three weighting schemes applied to a real hyperspectral corn leaf image and to simulated data based upon this same image. MCR applied to both real and simulated hyperspectral images weighted to compensate for the two major noise sources greatly improved the extracted pure emission spectra and their concentrations relative to MCR with either unweighted or Poisson-only weighted data. Thus, properly identifying and accounting for the major noise sources in hyperspectral images can serve to improve the MCR results. These methods are very general and can be applied to the multivariate analysis of spectral images whenever CCD or EMCCD detectors are used. Copyright © 2008 John Wiley & Sons, Ltd. [source] Interactive curve resolution by using latent projections in polar coordinatesJOURNAL OF CHEMOMETRICS, Issue 1-2 2007J. von Frese Abstract The problem of resolving bilinear two-way data into the contributions from the underlying mixture components is of great interest for all hyphenated analytical techniques. The fact that the optimal solution to this problem at least to some extent depends on the nature of the data under study has lead to a numerous different approaches. One of the seminal publications in this area was contributed by Olav M. Kvalheim and Yi-Zeng Liang in 1992. They not only provided valuable Heuristic Evolving Latent Projections (HELP) but also enlightened many important aspects of curve resolution in this and numerous subsequent publications. Here we extend their key concept of HELP, that is the use of latent projective graphs for identifying one-component regions, by using polar coordinates for these analyses and thereby creating a simple, intuitive exploratory tool for directly solving the curve resolution problem for two and three components graphically. Our approach is demonstrated with simulated data, an example from reaction monitoring with broadband ultrafast spectroscopy and one chemometric standard data set. Copyright © 2007 John Wiley & Sons, Ltd. [source] Fast algorithm for the solution of large-scale non-negativity-constrained least squares problemsJOURNAL OF CHEMOMETRICS, Issue 10 2004Mark H. Van Benthem Abstract Algorithms for multivariate image analysis and other large-scale applications of multivariate curve resolution (MCR) typically employ constrained alternating least squares (ALS) procedures in their solution. The solution to a least squares problem under general linear equality and inequality constraints can be reduced to the solution of a non-negativity-constrained least squares (NNLS) problem. Thus the efficiency of the solution to any constrained least square problem rests heavily on the underlying NNLS algorithm. We present a new NNLS solution algorithm that is appropriate to large-scale MCR and other ALS applications. Our new algorithm rearranges the calculations in the standard active set NNLS method on the basis of combinatorial reasoning. This rearrangement serves to reduce substantially the computational burden required for NNLS problems having large numbers of observation vectors. Copyright © 2005 John Wiley & Sons, Ltd. [source] Noise propagation and error estimations in multivariate curve resolution alternating least squares using resampling methodsJOURNAL OF CHEMOMETRICS, Issue 7-8 2004Joaquim Jaumot Abstract Different approaches for the calculation of prediction intervals of estimations obtained in multivariate curve resolution using alternating least squares optimization methods are explored and compared. These methods include Monte Carlo simulations, noise addition and jackknife resampling. Obtained results allow a preliminary investigation of noise effects and error propagation on resolved profiles and on parameters estimated from them. The effect of noise on rotational ambiguities frequently found in curve resolution methods is discussed. This preliminary study is shown for the resolution of a three-component equilibrium system with overlapping concentration and spectral profiles. Copyright © 2004 John Wiley & Sons, Ltd. [source] Application of equality constraints on variables during alternating least squares proceduresJOURNAL OF CHEMOMETRICS, Issue 12 2002Mark H. Van Benthem Abstract We describe several methods of applying equality constraints while performing procedures that employ alternating least squares. Among these are mathematically rigorous methods of applying equality constraints, as well as approximate methods, commonly used in chemometrics, that are not mathematically rigorous. The rigorous methods are extensions of the methods described in detail in Lawson and Hanson's landmark text on solving least squares problems, which exhibit well-behaved least squares performance. The approximate methods tend to be easy to use and code, but they exhibit poor least squares behaviors and have properties that are not well understood. This paper explains the application of rigorous equality-constrained least squares and demonstrates the dangers of employing non-rigorous methods. We found that in some cases, upon initiating multivariate curve resolution with the exact basis vectors underlying synthetic data overlaid with noise, the approximate method actually results in an increase in the magnitude of residuals. This phenomenon indicates that the solutions for the approximate methods may actually diverge from the least squares solution. Copyright © 2002 John Wiley & Sons, Ltd. [source] Constrained least squares methods for estimating reaction rate constants from spectroscopic dataJOURNAL OF CHEMOMETRICS, Issue 1 2002Sabina Bijlsma Abstract Model errors, experimental errors and instrumental noise influence the accuracy of reaction rate constant estimates obtained from spectral data recorded in time during a chemical reaction. In order to improve the accuracy, which can be divided into the precision and bias of reaction rate constant estimates, constraints can be used within the estimation procedure. The impact of different constraints on the accuracy of reaction rate constant estimates has been investigated using classical curve resolution (CCR). Different types of constraints can be used in CCR. For example, if pure spectra of reacting absorbing species are known in advance, this knowledge can be used explicitly. Also, the fact that pure spectra of reacting absorbing species are non-negative is a constraint that can be used in CCR. Experimental data have been obtained from UV-vis spectra taken in time of a biochemical reaction. From the experimental data, reaction rate constants and pure spectra were estimated with and without implementation of constraints in CCR. Because only the precision of reaction rate constant estimates could be investigated using the experimental data, simulations were set up that were similar to the experimental data in order to additionally investigate the bias of reaction rate constant estimates. From the results of the simulated data it is concluded that the use of constraints does not result self-evidently in an improvement in the accuracy of rate constant estimates. Guidelines for using constraints are given. Copyright © 2002 John Wiley & Sons, Ltd. [source] Antimicrobial peptide interactions with silica bead supported bilayers and E. coli: buforin II, magainin II, and arenicin,JOURNAL OF PEPTIDE SCIENCE, Issue 8 2009Ryan W. Davis Abstract Using the unique quantitative capabilities of hyperspectral confocal microscopy combined with multivariate curve resolution, a comparative approach was employed to gain a deeper understanding of the different types of interactions of antimicrobial peptides (AMPs) with biological membranes and cellular compartments. This approach allowed direct comparison of the dynamics and local effects of buforin II, magainin II, and arenicin with nanoporous silica bead supported bilayers and living E. coli. Correlating between experiments and comparing these responses have yielded several important discoveries for pursuing the underlying biophysics of bacteriocidal specificity and the connection between structure and function in various cellular environments. First, a novel fluorescence method for direct comparison of a model and living system is demonstrated by utilizing the membrane partitioning and environmental sensitivity of propidium iodide. Second, measurements are presented comparing the temporal dynamics and local equilibrium concentrations of the different antimicrobial agents in the membrane and internal matrix of the described systems. Finally, we discuss how the data lead to a deeper understanding of the roles of membrane penetration and permeabilization in the action of these AMPs. Copyright © 2009 European Peptide Society and John Wiley & Sons, Ltd. [source] The analysis of pH-dependent protonated conformers of 1-hydroxyethylidene-1,1-diphosphonic acid by means of FT-Raman spectroscopy, multivariate curve resolution and DFT modellingJOURNAL OF RAMAN SPECTROSCOPY, Issue 12 2009Werner Barnard Abstract 1-Hydroxyethylidene-1,1-diphosphonic acid (HEDP) solutions in the pH range 0.98,13.00 were analysed using FT-Raman spectroscopy and 31P and 23Na NMR spectroscopy. Vibrational bands for different protonated species were observed in the Raman spectra, whereas only a single NMR signal that shifted with pH was observed for all samples over the entire pH range. No significant shift in the 23Na NMR signal was observed, confirming that formation of Na+(aq) complexes did not take place; hence, no interference with the different protonated forms of HEDP occurred. Vibrational bands were assigned using density functional theory(DFT)-calculated spectra of the most likely conformers in solution. Multivariate curve resolution was performed on the Raman spectra in the region containing the PO stretching vibrations to determine the number of protonated species formed over the entire pH range. Chemometric analysis compares very favourably with the experimental species distribution diagram which was generated using the reported log KH values. Copyright © 2009 John Wiley & Sons, Ltd. [source] Raman spectroscopy and multivariate curve resolution of concentrated Al2O3,Na2O,H2O solutionsJOURNAL OF RAMAN SPECTROSCOPY, Issue 6 2003Jon R. Schoonover Abstract Multivariate curve resolution was applied to a series of Raman spectra for samples representing highly concentrated alkaline aluminate slurries. Factors are extracted that represent the behavior of the dominant chemical species present, including aluminate monomer, aluminate oligomers, water and hydroxide. The analysis is particularly useful in unraveling the numerous overlapping contributions in the ,(OH) region of the spectrum. These extracted factors were further examined by comparing their scores with measured physiochemical properties such as density, relative humidity and molar concentrations of components, weight fractions and water activity. Published in 2003 by John Wiley & Sons, Ltd.. [source] Real-life applications of the MULVADO software package for processing DOSY NMR dataMAGNETIC RESONANCE IN CHEMISTRY, Issue 2 2006R. Huo Abstract MULVADO is a newly developed software package for DOSY NMR data processing, based on multivariate curve resolution (MCR), one of the principal multivariate methods for processing DOSY data. This paper will evaluate this software package by using real-life data of materials used in the printing industry: two data sets from the same ink sample but of different quality. Also a sample of an organic photoconductor and a toner sample are analysed. Compared with the routine DOSY output from monoexponential fitting, one of the single channel algorithms in the commercial Bruker software, MULVADO provides several advantages. The key advantage of MCR is that it overcomes the fluctuation problem (non-consistent diffusion coefficient of the same component). The combination of non-linear regression (NLR) and MCR can yield more accurate resolution of a complex mixture. In addition, the data pre-processing techniques in MULVADO minimise the negative effects of experimental artefacts on the results of the data. In this paper, the challenges for analysing polymer samples and other more complex samples will also be discussed. Copyright © 2005 John Wiley & Sons, Ltd. [source] | |||||||||||||