Multilevel Training of Binary Morphological Operators

The design of binary morphological operators that are translation-invariant and locally defined by a finite neighborhood window corresponds to the problem of designing Boolean functions. As in any supervised classification problem, morphological operators designed from a training sample also suffer from overfitting. Large neighborhood tends to lead to performance degradation of the designed operator. This work proposes a multilevel design approach to deal with the issue of designing large neighborhood-based operators. The main idea is inspired by stacked generalization (a multilevel classifier design approach) and consists of, at each training level, combining the outcomes of the previous level operators. The final operator is a multilevel operator that ultimately depends on a larger neighborhood than of the individual operators that have been combined. Experimental results show that two-level operators obtained by combining operators designed on subwindows of a large window consistently outperform the single-level operators designed on the full window. They also show that iterating two-level operators is an effective multilevel approach to obtain better results.

Automatic contour extraction from 2D neuron images

This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

Characterization of a beta-1,3-glucanase active in the alkaline midgut of Spodoptera frugiperda larvae and its relation to beta-glucan-binding proteins

Spodoptera frugiperda beta-1,3-glucanase (SLam) was purified from larval midgut. It has a molecular mass of 37.5 kDa, an alkaline optimum pH of 9.0, is active against beta-1,3-glucan (laminarin), but cannot hydrolyze yeast beta-1,3-1,6-glucan or other polysaccharides. The enzyme is an endoglucanase with low processivity (0.4), and is not inhibited by high concentrations of substrate. In contrast to other digestive beta-1,3-glucanases from insects, SLam is unable to lyse Saccharomyces cerevisae cells. The cDNA encoding SLam was cloned and sequenced, showing that the protein belongs to glycosyl hydrolase family 16 as other insect glucanases and glucan-binding proteins. Multiple sequence alignment of beta-1,3-glucanases and beta-glucan-binding protein supports the assumption that the beta-1,3-glucanase gene duplicated in the ancestor of mollusks and arthropods. One copy originated the derived beta-1,3-glucanases by the loss of an extended N-terminal region and the beta-glucan-binding proteins by the loss of the catalytic residues. SLam homology modeling suggests that E228 may affect the ionization of the catalytic residues, thus displacing the enzyme pH optimum. SLam antiserum reacts with a single protein in the insect midgut. Immunocytolocalization shows that the enzyme is present in secretory vesicles and glycocalyx from columnar cells. (C) 2010 Elsevier Ltd. All rights reserved.

Computer-aided Structure Elucidation of Neolignans

This paper describes a new module of the expert system SISTEMAT used for the prediction of the skeletons of neolignans by (13)C NMR, (1)H NMR and botanical data obtained from the literature. SISTEMAT is composed of MACRONO, SISCONST, C13MACH, H1MACH and SISOCBOT programs, each analyzing data of the neolignan in question to predict the carbon skeleton of the compound. From these results, the global probability is computed and the most probable skeleton predicted. SISTEMAT predicted the skeletons of 75% of the 20 neolignans tested, in a rapid and simple procedure demonstrating its advantage for the structural elucidation of new compounds.

Use of copper and gold electrodes as sensitive elements for fabrication of an electronic tongue: Discrimination of wines and whiskies

A low-cost method is proposed to classify wine and whisky samples using a disposable voltammetric electronic tongue that was fabricated using gold and copper substrates and a pattern recognition technique (Principal Component Analysis). The proposed device was successfully used to discriminate between expensive and cheap whisky samples and to detect adulteration processes using only a copper electrode. For wines, the electronic tongue was composed of copper and gold working electrodes and was able to classify three different brands of wine and to make distinctions regarding the wine type, i.e., dry red, soft red, dry white and soft white brands. Crown Copyright (C) 2011 Published by Elsevier B.V. All rights reserved.

Quantitative ester analysis in cachaca and distilled spirits by gas chromatography-mass spectrometry (GC-MS)

An analytical procedure for the separation and quantification of ethyl acetate, ethyl butyrate, ethyl hexanoate, ethyl lactate, ethyl octanoate, ethyl nonanoate, ethyl decanoate, isoamyl octanoate, and ethyl laurate in cachaca, rum, and whisky by direct injection gas chromatography-mass spectrometry was developed. The analytical method is simple, selective, and appropriated for the determination of esters in distilled spirits. The limit of detection ranged from 29 (ethyl hexanoate) to 530 (ethyl acetate) mu g L-1, whereas the standard deviation for repeatability was between 0.774% (ethyl hexanoate) and 5.05% (isoamyl octanoate). Relative standard deviation values for accuracy vary from 90.3 to 98.5% for ethyl butyrate and ethyl acetate, respectively. Ethyl acetate was shown to be the major ester in cachaca (median content of 22.6 mg 100 mL(-1) anhydrous alcohol), followed by ethyl lactate (median content of 8.32 mg 100 mL(-1) anhydrous alcohol). Cachaca produced in copper and hybrid alembic present a higher content of ethyl acetate and ethyl lactate than those produced in a stainless-steel column, whereas cachaca produced by distillation in a stainless-steel column present a higher content of ethyl octanoate, ethyl decanoate, and ethyl laurate. As expected, ethyl acetate is the major ester in whiskey and rum, followed by ethyl lactate for samples of rum. Nevertheless, whiskey samples exhibit ethyl lactate at contents lower or at the same order of magnitude of the fatty esters.