Marcel J. E. Golay

Bio: Marcel J. E. Golay is an academic researcher from PerkinElmer. The author has contributed to research in topics: Gas chromatography & Hagen–Poiseuille equation. The author has an hindex of 23, co-authored 52 publications receiving 17245 citations.

Height Equivalent to a Theoretical Plate of Tubular Gas Chromatographic Columns lined with a Porous Layer

Abstract: IN a former publication1 the following expression was derived for the height equivalent to a theoretical plate (HETP), h, of a tubular column of radius r: where: v = average carrier gas velocity; Dg = molecular diffusion coefficient of component in the gas phase; Dl = molecular diffusion coefficient of component in the liquid phase; k = capacity ratio of liquid over gas phase; r = radius of tubular column; K = partition coefficient.

Note on gas chromatographic injection.

Abstract: IN the course of investigations of the accurate determination of gas chromatographic retention times, several causes of errors in these measurements have been examined; this communication is concerned with the errors which may be due to the finite concentration of any one component observed, even when the isotherms are practically linear for that concentration.

Monochromaticity and Noise in a Regenerative Electrical Oscillator

Abstract: The regenerative oscillator is postulated to be equivalent to an RLC circuit in which a negative resistance-RB, placed parallel with R, has a value which is a slowly varying function of the mean-square voltage across it. Expressions are derived for the departure from monochromaticity of the regenerative oscillator so represented, as well as for the intensity and bandwidth of the thermal noise generated in the oscillator by the resistance R.

Contour Detection and Hierarchical Image Segmentation

Abstract: This paper investigates two fundamental problems in computer vision: contour detection and image segmentation. We present state-of-the-art algorithms for both of these tasks. Our contour detector combines multiple local cues into a globalization framework based on spectral clustering. Our segmentation algorithm consists of generic machinery for transforming the output of any contour detector into a hierarchical region tree. In this manner, we reduce the problem of image segmentation to that of contour detection. Extensive experimental evaluation demonstrates that both our contour detection and segmentation methods significantly outperform competing algorithms. The automatically generated hierarchical segmentations can be interactively refined by user-specified annotations. Computation at multiple image resolutions provides a means of coupling our system to recognition applications.

Using circular dichroism spectra to estimate protein secondary structure

Abstract: Circular dichroism (CD) is an excellent tool for rapid determination of the secondary structure and folding properties of proteins that have been obtained using recombinant techniques or purified from tissues. The most widely used applications of protein CD are to determine whether an expressed, purified protein is folded, or if a mutation affects its conformation or stability. In addition, it can be used to study protein interactions. This protocol details the basic steps of obtaining and interpreting CD data, and methods for analyzing spectra to estimate the secondary structural composition of proteins. CD has the advantage that measurements may be made on multiple samples containing < or =20 microg of proteins in physiological buffers in a few hours. However, it does not give the residue-specific information that can be obtained by x-ray crystallography or NMR.

Orthogonal projections to latent structures (O-PLS)

Abstract: A generic preprocessing method for multivariate data, called orthogonal projections to latent structures (O-PLS), is described. O-PLS removes variation from X (descriptor variables) that is not correlated to Y (property variables, e.g. yield, cost or toxicity). In mathematical terms this is equivalent to removing systematic variation in X that is orthogonal to Y. In an earlier paper, Wold et al. (Chemometrics Intell. Lab. Syst. 1998; 44: 175-185) described orthogonal signal correction (OSC). In this paper a method with the same objective but with different means is described. The proposed O-PLS method analyzes the variation explained in each PLS component. The non-correlated systematic variation in X is removed, making interpretation of the resulting PLS model easier and with the additional benefit that the non-correlated variation itself can be analyzed further. As an example, near-infrared (NIR) reflectance spectra of wood chips were analyzed. Applying O-PLS resulted in reduced model complexity with preserved prediction ability, effective removal of non-correlated variation in X and, not least, improved interpretational ability of both correlated and non-correlated variation in the NIR spectra.

Review of the most common pre-processing techniques for near-infrared spectra

Abstract: Pre-processing of near-infrared (NIR) spectral data has become an integral part of chemometrics modeling. The objective of the pre-processing is to remove physical phenomena in the spectra in order to improve the subsequent multivariate regression, classification model or exploratory analysis. The most widely used pre-processing techniques can be divided into two categories: scatter-correction methods and spectral derivatives. This review describes and compares the theoretical and algorithmic foundations of current pre-processing methods plus the qualitative and quantitative consequences of their application. The aim is to provide NIR users with better end-models through fundamental knowledge on spectral pre-processing.

Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR.

Abstract: Respiration effects and cardiac pulsatility can induce signal modulations in functional MR image time series that increase noise and degrade the statistical significance of activation signals. A simple image-based correction method is described that does not have the limitations of k-space methods that preclude high spatial frequency correction. Low-order Fourier series are fit to the image data based on time of each image acquisition relative to the phase of the cardiac and respiratory cycles, monitored using a photoplethysmograph and pneumatic belt, respectively. The RETROICOR method is demonstrated using resting-state experiments on three subjects and compared with the k-space method. The method is found to perform well for both respiration- and cardiac-induced noise without imposing spatial filtering on the correction. Magn Reson Med 44:162‐167, 2000. © 2000 Wiley-Liss, Inc.