Toward automatic phenotyping of developing embryos from videos.

We describe a trainable system for analyzing videos of developing C. elegans embryos. The system automatically detects, segments, and locates cells and nuclei in microscopic images. The system was designed as the central component of a fully automated phenotyping system. The system contains three modules 1) a convolutional network trained to classify each pixel into five categories: cell wall, cytoplasm, nucleus membrane, nucleus, outside medium; 2) an energy-based model, which cleans up the output of the convolutional network by learning local consistency constraints that must be satisfied by label images; 3) a set of elastic models of the embryo at various stages of development that are matched to the label images.     

Fatty acid composition of total lipids,neutral lipids and phospholipids in wild and farmed matrinxã (Brycon cephalus) in the Brazilian Amazon area

BACKGROUND: The chemical composition of Amazonian fish is extremely variable, being influenced by the season and the type and amount of food. A special interest in the fish oil composition has been developed owing to the presence of essential fatty acids, since this is directly related to human health. This study aimed to investigate the fatty acid composition (FAC) of the total lipid (TL), neutral lipid (NL) and phospholipid (PL) fractions of the dorsal muscle and orbital cavity of farmed and wild matrinxã in the Amazon area captured in different seasons. RESULTS: Fatty acids (FA) were analysed by high‐resolution gas chromatography/mass spectrometry. Sixty‐five FA were detected in the TL, 66 in the NL and 55 in the PL. The main FA found in farmed and wild fish were oleic, palmitic, stearic and linoleic acids. No distinctions in the quality or quantity of these fractions between dorsal muscle and orbital cavity were found. CONCLUSION: The season had a significant influence on the TL and FAC. Fish captured during the dry season showed lower levels of lipid and a higher percentage of long‐chain polyunsaturated fatty acids. Matrinxã farmed in a semi‐intensive system showed a nutritional quality comparable to that of wild matrinxã captured in the wet season. Copyright © 2007 Society of Chemical Industry     

Development of calibration models for quality control in the production of ethylene/propylene copolymers by FTIR spectroscopy,multivariate statistical tools,and artificial neural networks

Principal component regression (PCR), partial least squares (PLS), StepWise ordinary least squares regression (OLS), and back‐propagation artificial neural network (BP‐ANN) are applied here for the determination of the propylene concentration of a set of 83 production samples of ethylene–propylene copolymers from their infrared spectra. The set of available samples was split into (a) a training set, for models calculation; (b) a test set, for selecting the correct number of latent variables in PCR and PLS and the end point of the training phase of BP‐ANN; (c) a production set, for evaluating the predictive ability of the models. The predictive ability of the models is thus evaluated by genuine predictions. The model obtained by StepWise OLS turned out to be the best one, both in fitting and prediction. The study of the breakdown number of samples to be included in the training set showed that at least 52 experiments are necessary to build a reliable and predictive calibration model. It can be concluded that FTIR spectroscopy and OLS can be properly employed for monitoring the synthesis or the final product of ethylene–propylene copolymers, by predicting the concentration of propylene directly along the process line. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

In situ developed laminates with large microstructural differences between layers of similar composition

Fabrication of alumina-aluminium titanate laminates that combine high strength external layers with flaw tolerant internal layers is limited by the difficulty of the co-sintering of layers with large differences in the green state. This work describes a new method to obtain alumina-aluminium titanate layered materials constituted by layers with large differences in terms of grain size starting from green bodies with similar microstructures. The approach is based on the effect of small amounts of titania (TiO₂) as agents for alumina grain growth enhancement. Starting from a fine grained green body that combined alumina layers with composite layers made of mixtures of alumina and titania, a two step sintering schedule led to a layered structure with external layers of small grain sized alumina combined with internal alumina layers with large grain size due to the diffusion of titanium. The large grain sized alumina layers conferred flaw tolerant behaviour to the laminate due to crack branching and bridging.     

Linear mixture model applied to Amazonian vegetation classification

Many research projects require accurate delineation of different secondary succession (SS) stages over large regions/subregions of the Amazon basin. However, the complexity of vegetation stand structure, abundant vegetation species, and the smooth transition between different SS stages make vegetation classification difficult when using traditional approaches such as the maximum likelihood classifier (MLC). Most of the time, classification distinguishes only between forest/non-forest. It has been difficult to accurately distinguish stages of SS. In this paper, a linear mixture model (LMM) approach is applied to classify successional and mature forests using Thematic Mapper (TM) imagery in the Rondônia region of the Brazilian Amazon. Three endmembers (i.e., shade, soil, and green vegetation or GV) were identified based on the image itself and a constrained least-squares solution was used to unmix the image. This study indicates that the LMM approach is a promising method for distinguishing successional and mature forests in the Amazon basin using TM data. It improved vegetation classification accuracy over that of the MLC. Initial, intermediate, and advanced successional and mature forests were classified with overall accuracy of 78.2% using a threshold method on the ratio of shade to GV fractions, a 7.4% increase over the MLC. The GV and shade fractions are sensitive to the change of vegetation stand structures and better capture biophysical structure information.     

Mapping of Trellises Associated with General Encoders onto High-Performance VLSI Architectures

A rate 1/n binary generic convolutional encoder is a shift-register circuit where the inputs are information bits and the outputs are blocks of n bits generated as linear combinations on the appropriate shift register contents. The decoding of the outputs of a convolutional encoder can be carried out by the well-known Viterbi algorithm. The communication pattern of the Viterbi Algorithm is given as a graph, called trellis, associated to the state diagram of the corresponding encoder. In this paper we present a methodology that permits the efficient mapping of the Viterbi algorithm onto a column of an arbitrary number of processors. This is done through the representation of the data flow by using mathematical operators which present an inmediate hardware projection. A single operator string has been obtained to represent a generic encoder through the study of the data flow of free-forward encoders and feed-back encoders. The formal model developed is employed for the partitioning of the computations among an arbitrary number of processors in such a way that the data are recirculated opimizing the use of the processors and the communications. As a result, we obtain a highly regular and modular architecture suitable for VLSI implementation.     

Mathematical modelling of the alcoholic fermentation of glucose by Zymomonas mobilis mobilis

The kinetics of alcoholic fermentation of a strain of Zymomonas mobilis, isolated from sugarcane juice, has been studied with the objective of determining the constansts of a non-structured mathematical model that represents the fermentation process. Assays in batch and in continuous culture have been carried out with different initial concentrations of glucose. The final concentrations of glucose, ethanol and biomass were determined. The following kinetic parameters were obtained: μ_max, 0·5 h^?1; K_s, 4·64 g dm^?3; P_max, 106 g dm^?3; Y_x/s, 0·0265 g g^?1; m, 1·4 g g^?1 h^?1; α, 17·38 g g^?1; β, 0·69 g g^?1 h^?1.     

Equivalence between Ampere and Grassmann's forces

We calculate the force on part of a single closed circuit due to the remaining circuit in four different geometries according to the forces of Ampere and Grassmann. All analytical calculations are performed using surface or volume current elements in order to avoid the divergences which appear with linear current elements of zero diameter. We conclude that when we consider the action of a closed circuit as a whole and utilize only circuits with closed lines of current, there will be an equivalence between the expressions of Grassmann and Ampere. This means that both of them are compatible with the experimental findings related to Ampere's bridge, contrary to the opinion of some authors