Ambiental volatile organic compounds in the megacity of São Paulo

In order to characterize the composition of the main urban air organic compounds in the megacity of Sao Paulo, analysis of samples collected during the winter of 2003 downtown was carried out. The samplings were performed on the roof of a building in the commercial center of São Paulo. Hydrocarbons and carbonyls compounds were collected on August 4, 5 and 6. Comparing to previous data, the concentration of hydrocarbons presented no decrease in the concentration, except for the aldehydes, which decreased when compared to previous data. Among the HCs species analyzed, the highest concentrations observed were those of toluene (7.5 ± 3.4 ppbv), n-decane (3.2 ± 2.0 ppbv), benzene (2.7 ± 1.4 ppbv) and 1,3,5-trimethylbenzene (2.2 ± 1.5 ppbv).

Saving our science from ourselves: the plight of biological classification

Saving our science from ourselves: the plight of biological classification. Biological classification ( nomenclature, taxonomy, and systematics) is being sold short. The desire for new technologies, faster and cheaper taxonomic descriptions, identifications, and revisions is symptomatic of a lack of appreciation and understanding of classification. The problem of gadget-driven science, a lack of best practice and the inability to accept classification as a descriptive and empirical science are discussed. The worst cases scenario is a future in which classifications are purely artificial and uninformative.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

Neural networks and statistical analysis for classification of corneal videokeratography maps based on Zernike coefficients: a quantitative comparison

PURPOSE: The main goal of this study was to develop and compare two different techniques for classification of specific types of corneal shapes when Zernike coefficients are used as inputs. A feed-forward artificial Neural Network (NN) and discriminant analysis (DA) techniques were used. METHODS: The inputs both for the NN and DA were the first 15 standard Zernike coefficients for 80 previously classified corneal elevation data files from an Eyesys System 2000 Videokeratograph (VK), installed at the Departamento de Oftalmologia of the Escola Paulista de Medicina, São Paulo. The NN had 5 output neurons which were associated with 5 typical corneal shapes: keratoconus, with-the-rule astigmatism, against-the-rule astigmatism, "regular" or "normal" shape and post-PRK. RESULTS: The NN and DA responses were statistically analyzed in terms of precision ([true positive+true negative]/total number of cases). Mean overall results for all cases for the NN and DA techniques were, respectively, 94% and 84.8%. CONCLUSION: Although we used a relatively small database, results obtained in the present study indicate that Zernike polynomials as descriptors of corneal shape may be a reliable parameter as input data for diagnostic automation of VK maps, using either NN or DA.

Screening process for activity determination of conductive oxide electrodes for organic oxidation

A modified method for the calculation of the normalized faradaic charge (q fN) is proposed. The method involves the simulation of an oxidation process, by cyclic voltammetry, by employing potentials in the oxygen evolution reaction region. The method is applicable to organic species whose oxidation is not manifested by a defined oxidation peak at conductive oxide electrodes. The variation of q fN for electrodes of nominal composition Ti/RuX Sn1-X O2 (x = 0.3, 0.2 and 0.1), Ti/Ir0.3Ti0.7O2 and Ti/Ru0.3Ti0.7O2 in the presence of various concentrations of formaldehyde was analyzed. It was observed that electrodes containing SnO2 are the most active for formaldehyde oxidation. Subsequently, in order to test the validity of the proposed model, galvanostatic electrolyses (40 mA cm-2) of two different formaldehyde concentrations (0.10 and 0.01 mol dm-3) were performed. The results are in agreement with the proposed model and indicate that this new method can be used to determine the relative activity of conductive oxide electrodes. In agreement with previous studies, it can be concluded that not only the nature of the electrode material, but also the organic species in solution and its concentration are important factors to be considered in the oxidation of organic compounds.

Development of a flow through photo-reactor to study degradation of organic compounds by Sequential Injection Analysis (SIA)

This work describes a photo-reactor to perform in line degradation of organic compounds by photo-Fenton reaction using Sequential Injection Analysis (SIA) system. A copper phthalocyanine-3,4',4²,4²¢-tetrasulfonic acid tetrasodium salt dye solution was used as a model compound for the phthalocyanine family, whose pigments have a large use in automotive coatings industry. Based on preliminary tests, 97% of color removal was obtained from a solution containing 20 µmol L-1 of this dye.

Molecular phylogeny of advanced snakes (Serpentes, Caenophidia) with an emphasis on South American Xenodontines: a revised classification and descriptions of new taxa

We present a molecular phylogenetic analysis of caenophidian (advanced) snakes using sequences from two mitochondrial genes (12S and 16S rRNA) and one nuclear (c-mos) gene (1681 total base pairs), and with 131 terminal taxa sampled from throughout all major caenophidian lineages but focussing on Neotropical xenodontines. Direct optimization parsimony analysis resulted in a well-resolved phylogenetic tree, which corroborates some clades identified in previous analyses and suggests new hypotheses for the composition and relationships of others. The major salient points of our analysis are: (1) placement of Acrochordus, Xenodermatids, and Pareatids as successive outgroups to all remaining caenophidians (including viperids, elapids, atractaspidids, and all other "colubrid" groups); (2) within the latter group, viperids and homalopsids are sucessive sister clades to all remaining snakes; (3) the following monophyletic clades within crown group caenophidians: Afro-Asian psammophiids (including Mimophis from Madagascar), Elapidae (including hydrophiines but excluding Homoroselaps), Pseudoxyrhophiinae, Colubrinae, Natricinae, Dipsadinae, and Xenodontinae. Homoroselaps is associated with atractaspidids. Our analysis suggests some taxonomic changes within xenodontines, including new taxonomy for Alsophis elegans, Liophis amarali, and further taxonomic changes within Xenodontini and the West Indian radiation of xenodontines. Based on our molecular analysis, we present a revised classification for caenophidians and provide morphological diagnoses for many of the included clades; we also highlight groups where much more work is needed. We name as new two higher taxonomic clades within Caenophidia, one new subfamily within Dipsadidae, and, within Xenodontinae five new tribes, six new genera and two resurrected genera. We synonymize Xenoxybelis and Pseudablabes with Philodryas; Erythrolamprus with Liophis; and Lystrophis and Waglerophis with Xenodon.

A new classification of foods based on the extent and purpose of their processing

This paper describes a new food classification which assigns foodstuffs according to the extent and purpose of the industrial processing applied to them. Three main groups are defined: unprocessed or minimally processed foods (group 1), processed culinary and food industry ingredients (group 2), and ultra-processed food products (group 3). The use of this classification is illustrated by applying it to data collected in the Brazilian Household Budget Survey which was conducted in 2002/2003 through a probabilistic sample of 48,470 Brazilian households. The average daily food availability was 1,792 kcal/person being 42.5% from group 1 (mostly rice and beans and meat and milk), 37.5% from group 2 (mostly vegetable oils, sugar, and flours), and 20% from group 3 (mostly breads, biscuits, sweets, soft drinks, and sausages). The share of group 3 foods increased with income, and represented almost one third of all calories in higher income households. The impact of the replacement of group 1 foods and group 2 ingredients by group 3 products on the overall quality of the diet, eating patterns and health is discussed.

Digestible lysine and organic zinc for male broiler from 1 to 11 days of age: performance and body composition

This study evaluated levels of digestible lysine and organic zinc for male Ross strain broilers from 1 to 11 days of age. It was used 1,050 chicks distributed in randomized block design, in 5 × 2 factorial scheme, with seven repetitions of 15 birds per experimental unit. The dietary concentrations of digestible lysine were 0.90; 1.00; 1.10; 1.20; and 1.40% combined with 43 and 253 ppm zinc chelate. The diets contained 2,965 ± 18 kcal/kg of apparent metabolizable energy (AME) and 21.48 ± 0.18% of CP. It was determined chemical composition, protein, lipid, mineral and water depositions on carcass and empty body. There was no interaction among the factors digestible lysine and organic zinc. Effect of zinc concentration increase was observed on greatest deposition of body fat, indicating that there is interference in lipid metabolism of the birds in the studied phase. The most pronounced effects resulted from the dietary inclusion of lysine. There was a linear effect on reconstituted body weight as a response to the increase of dietary lysine, which suggests equal or superior requirement to the greatest studied level. However, the deposition of water and protein on the carcass had a quadratic increase, characterizing higher muscle mass accumulation up to the levels 1.25 and 1.27 of this amino acid in the diet. Considering the studied strain, broiler chickens from the first to the 11th days of age require 1.28 ± 0.01% of digestible lysine, according to the deposition of muscle mass.

Carbon Stocks and Isotopic Composition of the Organic Matter in Soils Covered by Native Vegetation and Pasture in Sorocaba, SP, Brazil

Land cover change constitutes one of main way of alteration of soil organic matter in both quantitative and qualitative terms. The goal of this study was to compare the carbon stock and the isotopic signature of the organic matter in the soil of areas with different land use,covered with forest and grass (pasture). The study area is located at Sorocaba, SP, Brazil. Using un-deformed soil samples, we measured the carbon content and bulk density. The isotopic signature of soil carbon was determined through the analysis of isotopic ratio (12)C/(13)C. The pasture soil stocks 48% less carbon than the soil covered by natural forest. The isotopic signature indicated that 42.2% of organic matter of the soil covered by pasture is originated from grasses. This characterizes a highly degradation of organic matter in the environment, both quantitatively and qualitatively. Hence, some guidelines of recuperation are described in order to restore the soil organic matter, structure and porosity.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

Biochemical characterization of pulp of banana fruit: measurement of soluble sugars, organic acids, free ACC and in vitro ACC oxidase

Introduction. We present some protocols aiming at partially characterizing banana fruit quality through measurement of some key biochemical parameters. The principle, key advantages, starting plant material, time required and expected results are presented. Materials and methods. This part describes the required laboratory materials and the steps necessary for achieving four protocols making it possible to measure sugar, organic acids and free ACC contents, and in vitro ACC oxidase activity. Results. Standard results obtained by using the protocols described are presented in the figures.

Increased CLA content in organic milk fermented by bifidobacteria or yoghurt cultures

This study investigates the kinetics of acidification, fatty acid (FA) profile and conjugated linoleic acid (CLA, C18:2 c9, t11) content in fermented milks prepared from organic and conventional milk. Fermented milks were manufactured with five mixed cultures: four different strains of Bifidobacterium animalis subsp. lactis (BL04, B94, BB12 and HN019) and Lactobacillus delbrueckii subsp. bulgaricus LB340, in co-culture with Streptococcus thermophilus TA040. The composition of milk was evaluated, and the kinetics of acidification was followed by continuous pH measurement using the Cinac system. The profile of FA, including CLA, was analyzed by gas chromatography. The chemical composition of conventional and organic milk was similar, with the exception of protein and Fe, the concentrations of which were higher in the organic milk. The rate of acidification was significantly influenced by the type of milk and the bacterial strain used. Co-cultures St-HN019 and St-BB12 showed higher maximal acidification rates in both milks. Final counts of S. thermophilus (9.0-10.1 log(10) colony forming units (CFU) . mL(-1), L)actobacillus bulgaricus (8.2-8.5 log(10) CFU . mL(-1)) and B. animalis subsp. lactis strains (8.3-9.3 log(10) CFU . mL(-1)) did not differ significantly in either milk. Unexpectedly, all fermented organic milks contained significantly higher amounts of CLA than the same milk before fermentation, whereas CLA amounts did not change during fermentation of conventional milk. Regardless of the type of milk, CLA was found to be significantly positively correlated with trans-vaccenic acid and negatively correlated with linoleic acid. Moreover, the CLA contents were significantly higher in fermented milks showing shorter fermentation times.

Simplified Mathematical Model for an Anaerobic Sequencing Batch Biofilm Reactor Treating Lipid-Rich Wastewater Subject to Rising Organic Loading Rates

This study proposes a simplified mathematical model to describe the processes occurring in an anaerobic sequencing batch biofilm reactor (ASBBR) treating lipid-rich wastewater. The reactor, subjected to rising organic loading rates, contained biomass immobilized cubic polyurethane foam matrices, and was operated at 32 degrees C +/- 2 degrees C, using 24-h batch cycles. In the adaptation period, the reactor was fed with synthetic substrate for 46 days and was operated without agitation. Whereas agitation was raised to 500 rpm, the organic loading rate (OLR) rose from 0.3 g chemical oxygen demand (COD) . L(-1) . day(-1) to 1.2 g COD . L(-1) . day(-1). The ASBBR was fed fat-rich wastewater (dairy wastewater), in an operation period lasting for 116 days, during which four operational conditions (OCs) were tested: 1.1 +/- 0.2 g COD . L(-1) . day(-1) (OC1), 4.5 +/- 0.4 g COD . L(-1) . day(-1) (OC2), 8.0 +/- 0.8 g COD . L(-1) . day(-1) (OC3), and 12.1 +/- 2.4 g COD . L(-1) . day(-1) (OC4). The bicarbonate alkalinity (BA)/COD supplementation ratio was 1:1 at OC1, 1:2 at OC2, and 1:3 at OC3 and OC4. Total COD removal efficiencies were higher than 90%, with a constant production of bicarbonate alkalinity, in all OCs tested. After the process reached stability, temporal profiles of substrate consumption were obtained. Based on these experimental data a simplified first-order model was fit, making possible the inference of kinetic parameters. A simplified mathematical model correlating soluble COD with volatile fatty acids (VFA) was also proposed, and through it the consumption rates of intermediate products as propionic and acetic acid were inferred. Results showed that the microbial consortium worked properly and high efficiencies were obtained, even with high initial substrate concentrations, which led to the accumulation of intermediate metabolites and caused low specific consumption rates.

Automated supervised classification of variable stars in the CoRoT programme Method and application to the first four exoplanet fields

Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.