Partial least-squares regression and fuzzy clustering — A joint approach

Chemical and physical analyses of malt, the main ingredient of beer, have been used to predict the concentration of certain volatile compounds in the finished beer.The prediction was done by means of the partial least squares regression (PLS2) in SIMCA. The total data set as well as individual malt clusters were submitted to PLS analysis. Best prediction was obtained by separating the total object matrix in classes according to similarity found by fuzzy pattern recognition (FCV). FCV was also used to separate the beer variables in classes and to select the subset of variables to be predicted.A joint approach of fuzzy pattern recognition to identify groups of samples and SIMCA-PLS2 to predict several dependent variables is suggested as a powerful tool in process-analytical chemistry.     

On the determination of crystallinity and cellulose content in plant fibres

A comparative study of cellulose crystallinity based on the sample crystallinity and the cellulose content in plant fibres was performed for samples of different origin. Strong acid hydrolysis was found superior to agricultural fibre analysis and comprehensive plant fibre analysis for a consistent determination of the cellulose content. Crystallinity determinations were based on X-ray powder diffraction methods using side-loaded samples in reflection (Bragg-Brentano) mode. Rietveld refinements based on the recently published crystal structure of cellulose Iβ followed by integration of the crystalline and amorphous (background) parts were performed. This was shown to be straightforward to use and in many ways advantageous to traditional crystallinity determinations using the Segal or the Ruland–Vonk methods. The determined cellulose crystallinities were 90–100 g/100 g cellulose in plant-based fibres and 60–70 g/100 g cellulose in wood based fibres. These findings are significant in relation to strong fibre composites and bio-ethanol production.     

The ETACS European project for testing the comparability of sensors and analysers

ETACS is the official acronym for the European project "European Testing and Assessment of Comparability of On-line Sensors/Analysers". This project has three main objectives to achieve the comparability of performance data for sensors and analysers in the environmental field. First, to develop a test protocol for validation and comparison of the performance of on-line sensors/analysers. The test protocol is intended to be generic, that is independent of the specific sensors/analysers and the specific parameters to be monitored. Second, the practical testing of this test protocol to assess its applicability and to develop the techniques used. Finally, to achieve widespread acceptance of the test protocol by producer/suppliers, users and relevant authorities to assist its early adoption as an agreed European standard. Laboratory tests for producing the test protocol have been carried out and completed to check the applicability of such a protocol.     

Procedure for background estimation in energy-dispersive X-ray fluorescence spectra

A method for semi-automatic background estimation in energy-dispersive x-ray fluorescence spectra is outlined. Two cubic splines were investigated and the spline called the Butland interpolant was chosen for further investigation. Prior to the calculation of the spline, peak regions are set up, and suitable knots are defined outside the peak regions. To set up the peak regions, an automatic peak-search routine and a calibration equation are used. For a given peak, the latter relates the full width at half maximum (FWHM) to the peak centre. In turn, the size of the peak regions are defined by the FWHM multiplied by a constant given by the user. The method was tested on several types of spectra. It was found that the optimal size of the peak region decreased with increasing peak density. Reproducibility tests showed that the standard deviation of the summation of counts within a peak region and after background subtraction was less than would be expected from the counting statistics.     

Polarographic determination of chlorpheniramine maleate in pharmaceuticals

The electroreduction of chlorpheniramine maleate has been investigated by a.c. and d.c. polarography, coulometry and cyclic voltammetry. Polarograms recorded from 0.2 M sulphuric acid exhibit a single well-defined 2-electron wave. The current is diffusion-controlled and proportional to the concentration in the entire range 0.3–400 μg ml^?1. A simple and rapid method for the determination of chlorpheniramine maleate in tablets is described.     

Using model complexes to augment and advance metalloproteinase inhibitor design

The tetrahedral zinc complex [(Tp(Ph,Me))ZnOH] (Tp(Ph,Me) = hydrotris(3,5-phenylmethylpyrazolyl)borate) was combined with 2-thenylmercaptan, ethyl 4,4,4-trifluoroacetoacetate, salicylic acid, salicylamide, thiosalicylic acid, thiosalicylamide, methyl salicylate, methyl thiosalicyliate, and 2-hydroxyacetophenone to form the corresponding [(Tp(Ph,Me))Zn(ZBG)] complexes (ZBG = zinc-binding group). X-ray crystal structures of these complexes were obtained to determine the mode of binding for each ZBG, several of which had been previously studied with SAR by NMR (structure-activity relationship by nuclear magnetic resonance) as potential ligands for use in matrix metalloproteinase inhibitors. The [(Tp(Ph,Me))Zn(ZBG)] complexes show that hydrogen bonding and donor atom acidity have a pronounced effect on the mode of binding for this series of ligands. The results of these studies give valuable insight into how ligand protonation state and intramolecular hydrogen bonds can influence the coordination mode of metal-binding proteinase inhibitors. The findings here suggest that model-based approaches can be used to augment drug discovery methods applied to metalloproteins and can aid second-generation drug design.     

Beta-sheet preferences from first principles

The natural amino acids have different preferences of occurring in specific types of secondary protein structure. Simulations are performed on periodic model beta-sheets of 14 different amino acids, at the level of density functional theory, employing the generalized gradient approximation. We find that the statistically observed beta-sheet propensities correlate very well with the calculated binding energies. Analysis of the calculations shows that the beta-sheet propensities are determined by the local flexibility of the individual polypeptide strands.     

Linear programs with an additional reverse convex constraint

A constraintg(x)0 is said to be a reverse convex constraint if the functiong is continuous and strictly quasi-convex. The feasible regions for linear programs with an additional reverse convex constraint are generally non-convex and disconnected. It is shown that the convex hull of the feasible region is a convex polytope and, as a result, there is an optimal solution on an edge of the polytope defined by only the linear constraints. The only possible edges which can contain such an optimal solution are characterized in relation to the best feasible vertex of the polytope defined by only the linear constraints. This characterization then provides a finite algorithm for finding a globally optimal solution.Research supported by NSF Grant ENG76-12250 and ONR Contract N00014-78-C-0428.