Ingredient classification according to the digestible amino acid profile: an exploratory analysis

This study aimed: 1) to classify ingredients according to the digestible amino acid (AA) profile; 2) to determine ingredients with AA profile closer to the ideal for broiler chickens; and 3) to compare digestible AA profiles from simulated diets with the ideal protein profile. The digestible AA levels of 30 ingredients were compiled from the literature and presented as percentages of lysine according to the ideal protein concept. Cluster and principal component analyses (exploratory analyses) were used to compose and describe groups of ingredients according to AA profiles. Four ingredient groups were identified by cluster analysis, and the classification of the ingredients within each of these groups was obtained from a principal component analysis, showing 11 classes of ingredients with similar digestible AA profiles. The ingredients with AA profiles closer to the ideal protein were meat and bone meal 45, fish meal 60 and wheat germ meal, all of them constituting Class 1; the ingredients from the other classes gradually diverged from the ideal protein. Soybean meal, which is the main protein source for poultry, showed good AA balance since it was included in Class 3. on the contrary, corn, which is the main energy source in poultry diets, was classified in Class 8. Dietary AA profiles were improved when corn and/or soybean meal were partially or totally replaced in the simulations by ingredients with better AA balance.

Feature selection through gravitational search algorithm

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.

Evaluation of development traits of beef buffalo in Brazil using multivariate analysis

The buffalo population in Brazil increased about 12.9% between 1998 and 2003, to 2.8 million head, evidencing the importance of this species for the country. The objective this work was evaluation of animal growth using multivariate analysis. The data were from 2,944 water buffalo from 10 herds raised in pasture conditions in Brazil. Principal components and genetic distances were estimated using proc PRINCOMP and proc CANDISC in SAS (SAS Inst. Inc. Cary, NC, USA). Variables analyzed were birth weight (BW), age at weaning (AW), weaning weight (WT), weight adjusted to 205 d (W205), total gain between BW and WT (TG), daily gain between BW and WT (DG), weight adjusted to 365 d (W365), total gain between WT and W365 (TG3), daily gain between WT and W365 (TGD3), weight adjusted to 550 d (W550) and weight adjusted to 730 d (W730). Means and standard deviations for each variable were 39.4 +/- 3.2 kg, 225.6 +/- 38.8 d, 209.4 +/- 39.4 kg, 195.4 +/- 30.2 kg, 157.4 +/- 32.0 kg, 0.77 +/- 0.16 kg/d, 282.0 +/- 43.5 kg, 73.9 +/- 33.9 kg, 0.53 +/- 0.21 kg/d, 406.8 +/- 67.9 kg, and 468.2 +/- 70.6 kg, respectively. The eigenvalues to four first principal components were 5.29, 2.54, 1.66, 1.01, and justify 48%, 23%, 15% and 9%, respectively, with a total cumulative 95%. We created an index using the first principal component which is Y. 0.0552 BW + 0.0438 AW + 0.3142 WT + 0.3549 W205 + 0.3426 TG + 0.3426 DG + 0.4070 W365- 0.1531 TG3 - 0.2059 TGD3 - 0.3833 W550 - 0.3966 W730. This index accounted for 48% the variation in the correlation matrix. This principal component emphasizes early growth of the animal. Estimates the pair-wise squared distances between herds, D2(i vertical bar j)= ((x) over bar (i)-(x) over bar (j))' cov(-1)((x) over bar (i)-(x) over bar (j)), using with basis the average of weight of animals, showed the largest distance between herds eight (Murrah: DF) and seven (Murrah: Amazon) and the closest distance between herds one (Mediterranean - RS) and five (Jafarabadi - SP).

(1)H NMR Fingerprinting of Brazilian Commercial Gasoline: Pattern-Recognition Analyses for Origin Authentication Purposes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An analysis of the Hygiea asteroid family orbital region

(10) Hygiea is the fourth largest asteroid of the main belt, by volume and mass, and it is the largest member of its family, that is made mostly by low-albedo, C-type asteroids, typical of the outer main belt. Like many other large families, it is associated with a 'halo' of objects, that extends far beyond the boundary of the core family, as detected by traditional hierarchical clustering methods (HCM) in proper element domains. Numerical simulations of the orbital evolution of family members may help in estimating the family and halo family age, and the original ejection velocity field. But, in order to minimize the errors associated with including too many interlopers, it is important to have good estimates of family membership that include available data on local asteroid taxonomy, geometrical albedo and local dynamics. For this purpose, we obtained synthetic proper elements and frequencies of asteroids in the Hygiea orbital region, with their errors. We revised the current knowledge on asteroid taxonomy, including Sloan Digital Sky Survey-Moving Object Catalog 4th release (SDSS-MOC 4) data, and geometric albedo data from Wide-field Infrared Survey Explorer (WISE) and Near-Earth Object WISE (NEOWISE). We identified asteroid family members using HCM in the domain of proper elements (a, e, sin (i)) and in the domains of proper frequencies most appropriate to study diffusion in the local web of secular resonances, and eliminated possible interlopers based on taxonomic and geometrical albedo considerations. To identify the family halo, we devised a new hierarchical clustering method in an extended domain that includes proper elements, principal components PC1, PC2 obtained based on SDSS photometric data and, for the first time, WISE and NEOWISE geometric albedo. Data on asteroid size distribution, light curves and rotations were also revised for the Hygiea family. The Hygiea family is the largest group in its region, with two smaller families in proper element domain and 18 families in various frequencies domains identified in this work for the first time. Frequency groups tend to extend vertically in the (a, sin (i)) plane and cross not only the Hygiea family but also the near C-type families of Themis and Veritas, causing a mixture of objects all of relatively low albedo in the Hygiea family area. A few high-albedo asteroids, most likely associated with the Eos family, are also present in the region. Finally, the new multidomains hierarchical clustering method allowed us to obtain a good and robust estimate of the membership of the Hygiea family halo, quite separated from other asteroids families halo in the region, and with a very limited (about 3 per cent) presence of likely interlopers. © 2013 The Author Published by Oxford University Press on behalf of the Royal Astronomical Society.

Descrição morfológica e análise da variabilidade genética para caracteres de frutos, sementes e processo germinativo associado à produtividade de óleo em matrizes de Carapa guianensis Aublet., uma meliaceae da Amazônia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multivariate curve resolution analysis applied to time-resolved synchrotron X-ray Absorption Spectroscopy monitoring of the activation of copper alumina catalyst

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Multivariate analysis of the temporal variability of sugarcane ripening in south-eastern Brazil

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Risk evaluation of diabetes mellitus by relation of chaotic globals to HRV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Solvent-Resistant Polymeric Sensors for Adulteration Detection in Liquid Fuels

Polymeric sensors with improved resistance to organic solvents were produced via the layer-by-layer thin film deposition followed by chemical cross-linking. According to UV-vis spectroscopy, the mass loss of polyaniline/poly(vinyl alcohol) and polyaniline/novolac-type resin based films deposited onto glass slides was less than 20% when they were submitted to successive immersions (up to 3,000 immersion cycles) into commercially available ethanol and gasoline fuel samples. Polyallylamine hydrochloride/nickel tetrasulfonated phthalocyanine films presented similar stability. The electrical responses assessed by impedance spectroscopy of films deposited onto Au-interdigitated microelectrodes were relatively unaffected after continuous or cyclic immersions into both fuels. After these studies, an array including these polymeric sensors was employed to detect adulteration in ethanol and gasoline samples. After principal component analysis, it was possible to conclude that the proposed sensor array is capable to discriminate with remarkable reproducibility ethanol samples containing different amounts of water or else gasoline samples containing different amounts of ethanol. In both examples, more than 90% of data variance was retained in the first principal component. For each type of sample, ethanol and gasoline, it was found a linear correlation between one of the principal components and the sample's composition. These findings allow one to conclude that these films present great potential for the development of reliable and low-cost sensors for fuel analysis in liquid phase.

Extensive cross-talk and global regulators identified from an analysis of the integrated transcriptional and signaling network in Escherichia coli

To understand the regulatory dynamics of transcription factors (TFs) and their interplay with other cellular components we have integrated transcriptional, protein-protein and the allosteric or equivalent interactions which mediate the physiological activity of TFs in Escherichia coli. To study this integrated network we computed a set of network measurements followed by principal component analysis (PCA), investigated the correlations between network structure and dynamics, and carried out a procedure for motif detection. In particular, we show that outliers identified in the integrated network based on their network properties correspond to previously characterized global transcriptional regulators. Furthermore, outliers are highly and widely expressed across conditions, thus supporting their global nature in controlling many genes in the cell. Motifs revealed that TFs not only interact physically with each other but also obtain feedback from signals delivered by signaling proteins supporting the extensive cross-talk between different types of networks. Our analysis can lead to the development of a general framework for detecting and understanding global regulatory factors in regulatory networks and reinforces the importance of integrating multiple types of interactions in underpinning the interrelationships between them.

Multivariate analysis of fresh-cut carambola slices stored under different temperatures

Quality of fresh-cut carambola (Averrhoa carambola L) is related to many chemical and biochemical variables especially those involved with softening and browning, both influenced by storage temperature. To study these effects, a multivariate analysis was used to evaluate slices packaged in vacuum-sealed polyolefin bags, and stored at 2.5 degrees C, 5 degrees C and 10 degrees C, for up to 16 d. The quality of slices at each temperature was correlated with the duration of storage, O(2) and CO(2) concentration in the package, physical chemical constituents, and activity of enzymes involved in softening (PG) and browning (PPO) metabolism. Three quality groups were identified by hierarchical cluster analysis, and the classification of the components within each of these groups was obtained from a principal component analysis (PCA). The characterization of samples by PCA clearly distinguished acceptable and non-acceptable slices. According to PCA, acceptable slices presented higher ascorbic acid content, greater hue angles ((o)h) and final lightness (L-5) in the first principal component (PC1). On the other hand, non-acceptable slices presented higher total pectin content. PPO activity in the PC1. Non-acceptable slices also presented higher soluble pectin content, increased pectin solubilisation and higher CO(2) concentration in the second principal component (PC2) whereas acceptable slices showed lower total sugar content. The hierarchical cluster and PCA analyses were useful for discriminating the quality of slices stored at different temperatures. (C) 2011 Elsevier B.V. All rights reserved.

Brain activity and medical diagnosis: an EEG study

Abstract Background Despite new brain imaging techniques that have improved the study of the underlying processes of human decision-making, to the best of our knowledge, there have been very few studies that have attempted to investigate brain activity during medical diagnostic processing. We investigated brain electroencephalography (EEG) activity associated with diagnostic decision-making in the realm of veterinary medicine using X-rays as a fundamental auxiliary test. EEG signals were analysed using Principal Components (PCA) and Logistic Regression Analysis Results The principal component analysis revealed three patterns that accounted for 85% of the total variance in the EEG activity recorded while veterinary doctors read a clinical history, examined an X-ray image pertinent to a medical case, and selected among alternative diagnostic hypotheses. Two of these patterns are proposed to be associated with visual processing and the executive control of the task. The other two patterns are proposed to be related to the reasoning process that occurs during diagnostic decision-making. Conclusions PCA analysis was successful in disclosing the different patterns of brain activity associated with hypothesis triggering and handling (pattern P1); identification uncertainty and prevalence assessment (pattern P3), and hypothesis plausibility calculation (pattern P2); Logistic regression analysis was successful in disclosing the brain activity associated with clinical reasoning success, and together with regression analysis showed that clinical practice reorganizes the neural circuits supporting clinical reasoning.

Determination of bioactive and potentially toxic compounds in food: raw material analysis and shelf life evaluation

"Bioactive compounds" are extranutritional constituents that typically occur in small quantities in food. They are being intensively studied to evaluate their effects on health. Bioactive compounds include both water soluble compounds, such as phenolics, and lipidic substances such as n-3 fatty acids, tocopherols and sterols. Phenolic compounds, tocopherols and sterols are present in all plants and have been studied extensively in cereals, nuts and oil. n-3 fatty acids are present in fish and all around the vegetable kingdom. The aim of the present work was the determination of bioactive and potentially toxic compounds in cereal based foods and nuts. The first section of this study was focused on the determination of bioactive compounds in cereals. Because of that the different forms of phytosterols were investigated in hexaploid and tetraploid wheats. Hexaploid cultivars were the best source of esterified sterols (40.7% and 37.3% of total sterols for Triticum aestivum and Triticum spelta, respectively). Significant amounts of free sterols (65.5% and 60.7% of total sterols for Triticum durum and Triticum dicoccon, respectively) were found in the tetraploid cultivars. Then, free and bound phenolic compounds were identified in barley flours. HPLCESI/ MSD analysis in negative and positive ion mode established that barley free flavan-3- ols and proanthocyanidins were four dimers and four trimers having (epi)catechin and/or (epi)gallocatechin (C and/or GC) subunits. Hydroxycinnamic acids and their derivatives were the main bound phenols in barley flours. The results obtained demonstrated that barley flours were rich in phenolic compounds that showed high antioxidant activity. The study also examined the relationships between phenolic compounds and lipid oxidation of bakery. To this purpose, the investigated barley flours were used in the bakery production. The formulated oven products presented an interesting content of phenolic compounds, but they were not able to contain the lipid oxidation. Furthermore, the influence of conventional packaging on lipid oxidation of pasta was evaluated in n-3 enriched spaghetti and egg spaghetti. The results proved that conventional packaging was not appropriated to preserve pasta from lipid oxidation; in fact, pasta that was exposed to light showed a high content of potentially toxic compounds derived from lipid oxidation (such as peroxide, oxidized fatty acids and COPs). In the second section, the content of sterols, phenolic compounds, n-3 fatty acids and tocopherols in walnuts were reported. Rapid analytical techniques were used to analyze the lipid fraction and to characterize phenolic compounds in walnuts. Total lipid chromatogram was used for the simultaneous determination of the profile of sterols and tocopherols. Linoleic and linolenic acids were the most representative n-6 and n-3 essential dietary fatty acids present in these nuts. Walnuts contained substantial amounts of γ- and δ-tocopherol, which explained their antioxidant properties. Sitosterol, Δ5-avenasterol and campesterol were the major free sterols found. Capillary electrophoresis coupled to DAD and microTOF was utilized to determine phenolic content of walnut. A new compound in walnut ((2E,4E)- 8-hydroxy-2,7-dimethyl-2,4-decadiene-1,10-dioic acid 6-O-β-D-glucopiranosyl ester, [M−H]− 403.161m/z) with a structure similar to glansreginins was also identified. Phenolic compounds corresponded to 14–28% of total polar compounds quantified. Aglycone and glycosylated ellagic acid represented the principal components and account for 64–75% of total phenols in walnuts. However, the sum of glansreginins A, B and ((2E,4E)-8-hydroxy- 2,7-dimethyl-2,4-decadiene-1,10-dioic acid 6-O-β-D-glucopiranosyl ester was in the range of 72–86% of total quantified compounds.

Automatic Reduction of Artifacts in EEG-Signals

Electroencephalograms (EEG) are often contaminated with high amplitude artifacts limiting the usability of data. Methods that reduce these artifacts are often restricted to certain types of artifacts, require manual interaction or large training data sets. Within this paper we introduce a novel method, which is able to eliminate many different types of artifacts without manual intervention. The algorithm first decomposes the signal into different sub-band signals in order to isolate different types of artifacts into specific frequency bands. After signal decomposition with principal component analysis (PCA) an adaptive threshold is applied to eliminate components with high variance corresponding to the dominant artifact activity. Our results show that the algorithm is able to significantly reduce artifacts while preserving the EEG activity. Parameters for the algorithm do not have to be identified for every patient individually making the method a good candidate for preprocessing in automatic seizure detection and prediction algorithms.