A possibility for non-invasive diagnosis of superficial scald in 'Rocha' pear based on chlorophyll a fluorescence, colorimetry, and the relation between alpha-farnesene and conjugated trienols

This study aimed to identify physiological markers in superficially scalded 'Rocha' pear (Pyrus communis L 'Rocha') that would relate to chlorophyll a fluorescence (CF), allowing a non-invasive diagnosis of the disorder. Conditions chosen before shelf life provided two fruit groups with different developing patterns and severity of superficial scald: T fruit fully developed the disorder in storage, while C fruit developed it progressively throughout shelf life. Principal component analysis (PCA) of all the measured variables, and simple linear correlations among several major parameters and scald index (SI)/shelf life showed that scald and ripening/aging were concurring processes, and that it was not possible to isolate a particular variable that could deliver a direct non-invasive diagnosis of the disorder. For both fruit groups the SI resulted from the balance between the reducing power (OD200) and the content of conjugated trienols (CTos) and alpha-farnesene (alpha-Farn) in the fruit peel. At OD200 > 150 there was a linear relationship between CTos and OD200, suggesting that the level of antioxidants was self-adjusted in order to compensate the CTos level. However, at OD200 < 150 this relationship disappeared. A consistent linear relationship between dos and alpha-Farn existed throughout shelf life in both fruit groups, contrarily to the early storage stage, when those compounds do not relate linearly. The CF variables F-0, F-v/F-m, and the colorimetric variables, L* and h degrees were used in multi-linear regressions with other physiological variables. The regressions were made on one of the fruit groups and validated through the other. Reliable regressions to alpha-Farn and CTos were obtained (R approximate to 0.6; rmsec approximate to rmsep). Our results suggest that a model based on CF and colorimetric parameters could be used to diagnose non-invasively both the contents and the relationship between alpha-Farn and CTos and hence the stage of scald development. (C) 2011 Elsevier By. All rights reserved.

Metodologias estatísticas aplicadas a dados de análises químicas da água produzida em um campo maduro de petróleo

Produced water is characterized as one of the most common wastes generated during exploration and production of oil. This work aims to develop methodologies based on comparative statistical processes of hydrogeochemical analysis of production zones in order to minimize types of high-cost interventions to perform identification test fluids - TIF. For the study, 27 samples were collected from five different production zones were measured a total of 50 chemical species. After the chemical analysis was applied the statistical data, using the R Statistical Software, version 2.11.1. Statistical analysis was performed in three steps. In the first stage, the objective was to investigate the behavior of chemical species under study in each area of production through the descriptive graphical analysis. The second step was to identify a function that classify production zones from each sample, using discriminant analysis. In the training stage, the rate of correct classification function of discriminant analysis was 85.19%. The next stage of processing of the data used for Principal Component Analysis, by reducing the number of variables obtained from the linear combination of chemical species, try to improve the discriminant function obtained in the second stage and increase the discrimination power of the data, but the result was not satisfactory. In Profile Analysis curves were obtained for each production area, based on the characteristics of the chemical species present in each zone. With this study it was possible to develop a method using hydrochemistry and statistical analysis that can be used to distinguish the water produced in mature fields of oil, so that it is possible to identify the zone of production that is contributing to the excessive elevation of the water volume.

Diagnóstico ecotoxicológico dos efluentes lançados no complexo estuarino do Jundiaí/Potengi, Natal/RN

Untreated effluents that reach surface water affect the aquatic life and humans. This study aimed to evaluate the wastewater s toxicity (municipal, industrial and shrimp pond effluents) released in the Estuarine Complex of Jundiaí- Potengi, Natal/RN, through chronic quantitative e qualitative toxicity tests using the test organism Mysidopsis Juniae, CRUSTACEA, MYSIDACEA (Silva, 1979). For this, a new methodology for viewing chronic effects on organisms of M. juniae was used (only renewal), based on another existing methodology to another testorganism very similar to M. Juniae, the M. Bahia (daily renewal).Toxicity tests 7 days duration were used for detecting effects on the survival and fecundity in M. juniae. Lethal Concentration 50% (LC50%) was determined by the Trimmed Spearman-Karber; Inhibition Concentration 50% (IC50%) in fecundity was determined by Linear Interpolation. ANOVA (One Way) tests (p = 0.05) were used to determinate the No Observed Effect Concentration (NOEC) and Low Observed Effect Concentration (LOEC). Effluents flows were measured and the toxic load of the effluents was estimated. Multivariate analysis - Principal Component Analysis (PCA) and Correspondence Analysis (CA) - identified the physic-chemical parameters better explain the patterns of toxicity found in survival and fecundity of M. juniae. We verified the feasibility of applying the only renewal system in chronic tests with M. Juniae. Most efluentes proved toxic on the survival and fecundity of M. Juniae, except for some shrimp pond effluents. The most toxic effluent was ETE Lagoa Aerada (LC50, 6.24%; IC50, 4.82%), ETE Quintas (LC50, 5.85%), Giselda Trigueiro Hospital (LC50, 2.05%), CLAN (LC50, 2.14%) and COTEMINAS (LC50, IC50 and 38.51%, 6.94%). The greatest toxic load was originated from ETE inefficient high flow effluents, textile effluents and CLAN. The organic load was related to the toxic effects of wastewater and hospital effluents in survival of M. Juniae, as well as heavy metals, total residual chlorine and phenols. In industrial effluents was found relationship between toxicity and organic load, phenols, oils and greases and benzene. The effects on fertility were related, in turn, with chlorine and heavy metals. Toxicity tests using other organisms of different trophic levels, as well as analysis of sediment toxicity are recommended to confirm the patterns found with M. Juniae. However, the results indicate the necessity for implementation and improvement of sewage treatment systems affluent to the Potengi s estuary

Ecomorfologia de dez espécies de peixes marinhos mais abundantes de Galinhos/RN

Ecomorphology is a science based on the idea that morphological differences among species could be associated with distinct biological and environmental pressures suffered by them. These differences can be studied employing morphological and biometric indexes denominated Ecomorphological attributes , representing standards that express characteristics of the individual in relation to its environment, and can be interpreted as indicators of life habits or adaptations suffered due its occupation of different habitats. This work aims to contribute for the knowledge of the ecomorphology of the Brazilian marine ichthyofauna, specifically from Galinhos, located at Rio Grande do Norte state. 10 different species of fish were studied, belonging the families Gerreidae (Eucinostomus argenteus), Haemulidae (Orthopristis ruber,Pomadasyscorvinaeformis,Haemulonaurolineatum,Haemulonplumieri,Haemulonsteindachneri), Lutjanidae (Lutjanus synagris), Paralichthyidae (Syaciummicrurum), Bothidae (Bothus ocellatus) and Tetraodontidae (Sphoeroidestestudineus), which were obtained during five collections, in the period time of September/2004 to April/2005, utilizing three special nets. The ecomorphological study was performed at the laboratory. Eight to ten samples of each fish specie were measured. Fifteen morphological aspects were considered to calculate twelve ecomorphological attributes. Multivariate statistical analysis methods such as Principal Component Analysis (PCA) and Cluster Analysis were done to identify ecmorphological patterns to describe the data set obtained. As results, H.aurolineatumwas the most abundant specie found (23,03%) and S.testudineusthe less one with 0,23%. The 1st Principal component showed variation of 60,03% with influence of the ecomorphological attribute related to body morphology, while the 2nd PC with 23,25% variation had influence of the ecomorphological attribute related to oral morphology. The Cluster Analiysis promoted the identification of three distinct groups Perciformes, Pleuronectiformes and Tetraodontiformes. Based on the obtained data, considering morphological characters differences among the species studied, we suggest that all of them live at the medium (E.argenteus,O.rubber, P.corvinaeformis,H.aurolineatum,H.plumieri,H.steindachneri,L.synagris) and bottom (S.micrurum,B.ocellatus,S.testudineus) region of column water.

Effects of season period, team quality, and playing time on basketball players' game-related statistics

The aim of this study was to identify within-season differences in basketball players' game-related statistics according to team quality and playing time. The sample comprised 5309 records from 198 players in the Spanish professional basketball league (2007-2008). Factor analysis with principal components was applied to the game-related statistics gathered from the official box-scores, which limited the analysis to five factors (free-throws, 2-point field-goals, 3-point field-goals, passes, and errors) and two variables (defensive and offensive rebounds). A two-step cluster analysis classified the teams as stronger (69 ± 8 winning percentage), intermediate (43 ± 5 winning percentage), and weaker teams (32 ± 5 winning percentage); individual players were classified based on playing time as important players (28 ± 4 min) or less important players (16 ± 4 min). Seasonal variation was analysed monthly in eight periods. A mixed linear model was applied to identify the effects of team quality and playing time within the months of the season on the previously identified factors and game-related statistics. No significant effect of season period was observed. A team quality effect was identified, with stronger teams being superior in terms of 2-point field-goals and passes. The weaker teams were the worst at defensive rebounding (stronger teams: 0.17 ± 0.05; intermediate teams: 0.17 ± 0.06; weaker teams: 0.15 ± 0.03; P = 0.001). While playing time was significant in almost all variables, errors were the most important factor when contrasting important and less important players, with fewer errors being made by important players. The trends identified can help coaches and players to create performance profiles according to team quality and playing time. However, these performance profiles appear to be independent of season period.

Condition assessment of timber utility poles based on a hierarchical data fusion model

This paper proposes a novel hierarchical data fusion technique for the non-destructive testing (NDT) and condition assessment of timber utility poles. The new method analyzes stress wave data from multisensor and multiexcitation guided wave testing using a hierarchical data fusion model consisting of feature extraction, data compression, pattern recognition, and decision fusion algorithms. The researchers validate the proposed technique using guided wave tests of a sample of in situ timber poles. The actual health states of these poles are known from autopsies conducted after the testing, forming a ground-truth for supervised classification. In the proposed method, a data fusion level extracts the main features from the sampled stress wave signals using power spectrum density (PSD) estimation, wavelet packet transform (WPT), and empirical mode decomposition (EMD). These features are then compiled to a feature vector via real-number encoding and sent to the next level for further processing. Principal component analysis (PCA) is also adopted for feature compression and to minimize information redundancy and noise interference. In the feature fusion level, two classifiers based on support vector machine (SVM) are applied to sensor separated data of the two excitation types and the pole condition is identified. In the decision making fusion level, the Dempster–Shafer (D-S) evidence theory is employed to integrate the results from the individual sensors obtaining a final decision. The results of the in situ timber pole testing show that the proposed hierarchical data fusion model was able to distinguish between healthy and faulty poles, demonstrating the effectiveness of the new method.

Multi-label approach for human-face classification

Single-label classification models have been widely used for human-face classification. In this paper, we present a multi-label classification approach for human-face classification. Multi-label classification is more appropriate in the real world because a human-face can be associated with multiple labels. Demographic information can be derived and utilized along with facial expression in the field of face classification to assist with multi label classification. Gabor filters; Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) methods, are used to extract and project representative demographic information from facial images. For evaluation, five classification algorithms were used. We evaluate the proposed approach by performing experiments on Yale face images database. Results show the effectiveness of multi-label classification algorithms.

Measuring the stigma surrounding Type 2 diabetes: development and validation of the Type 2 Diabetes Stigma Assessment Scale (DSAS-2)

OBJECTIVE: To develop and validate a self-report measure of perceived and experienced stigma for use with adults with type 2 diabetes: the Type 2 Diabetes Stigma Assessment Scale (DSAS-2). RESEARCH DESIGN AND METHODS: An item pool was drafted based on qualitative data from 25 adults with type 2 diabetes and content from other health-related stigma questionnaires. Thirteen adults with type 2 diabetes completed 57 draft diabetes stigma items and participated in cognitive debriefing interviews. Based on participant feedback, the pool was reduced to 48 items with a 5-point Likert scale (strongly disagree to strongly agree). A total of 1,064 adults with type 2 diabetes completed a survey including these 48 items and other validated measures. Data were subject to principal components analysis and Spearman ρ correlations. RESULTS: The scale was reduced to 19 items, with an unforced three-factor solution indicative of three subscales: Treated Differently (6 items, α = 0.88), Blame and Judgment (7 items, α = 0.90), and Self-stigma (6 items, α = 0.90). A forced one-factor solution supported the calculation of a total score (α = 0.95). Satisfactory concurrent, convergent, and discriminant validity were demonstrated. CONCLUSIONS: The 19-item DSAS-2 is a reliable and valid measure of type 2 diabetes stigma. A rigorous design and validation process has resulted in a relatively brief measure of perceived and experienced stigma in type 2 diabetes. The novel scale has satisfactory psychometric properties and is now available to facilitate much-needed research in this field.

Effet du climat viticole sur la perception sensorielle du vin: éléments méthodologiques pour une modélisation au niveau mondial.

Summary The objective of this study was to develop a methodology capable of modeling the effect of viticultural climate on wine sensory characteristics. The climate was defined by the Géoviticulture Multicriteria Climatic Classification System (Tonietto and Carbonneau, 2004), based on the Heliothermal index (HI), Cool Night index (CI) and Dryness index (DI). The sensory wine description was made according with the methodology established by Zanus and Tonietto (2007). In this study we focused on the 5 principal wine producing regions of Brazil: Serra Gaúcha, Serra do Sudeste, Campanha (Meridional and Central), Planalto Catarinense and Vale do Submédio São Francisco. The results from Principal Component Analysis (PCA) show the HI and CI opposed to the DI. High HI values were associated to a lower perception of acidity, as well as to a lower perception of concentration (palate) and persistence by mouth. For the red wines, high HI values were positively associated with alcohol (palate), conversely to the DI index, which showed high values related to the perception of tanins and acidity. The higher the CI, the lower were the color intensity, tanins, concentration and persistence by mouth. It may be concluded that viticultural climate - expressed by the HI, CI and DI indexes ? adequately explained much of the sensory differences of the wines made in different regions. The methodology proposed and the enlargement of the database it will maybe open the possibility of modeling the part of wine sensory characteristics as dependent variables of the viticultural climate, as defined by the Géoviticulture MCC System. Keywords: viticultural climate, modeling, wine, tipicity.

Analytical characteristics and discrimination of Brazilian commercial grape juice, nectar, and beverage.

The production and commercialization of Brazilian grape juice is increasing annually, mainly due to its typicality, quality, and nutritional value. The present research was carried out in view of the great significance of Brazilian grape juice for the grape and wine industry. The purpose of this study, therefore, was to assess its composition as well as the discrimination between grape juice and other beverages. Twenty four samples of whole, sweetened, and reprocessed grape juices, grape nectar, and grape beverage were evaluated. Classical variables were analyzed by means of physicochemical methods; tartaric and malic acids, by HPLC; methanol, by gas chromatography; minerals, by atomic absorption spectrophotometry. These products were discriminated by the Principal Component Analysis (PCA). Results show that whole and sweetened grape juices were discriminated from other grape products because they featured higher values of total soluble solids, tartaric and malic acids, most minerals, phenolic compounds, and K/Na ratio, whereas grape nectar and grape beverage presented higher values of ºBrix/titratable acidity ratio. Reprocessed juice was discriminated due to its higher concentrations of Li and Na and lower hue.

Uso da espectroscopia de reflectância do infravermelho próximo (NIRS) para previsão da composição bromatológica de vagens de algaroba e palma forrageira.

Espécies forrageiras adaptadas às condições semiáridas são uma alternativa para reduzir os impactos negativos na cadeia produtiva de ruminantes da região Nordeste brasileira devido à sazonalidade na oferta de forragem, além de reduzir custo com o fornecimento de alimentos concentrados. Dentre as espécies, a vagem de algaroba (Prosopis juliflora SW D.C.) e palma forrageira (Opuntia e Nopalea) ganham destaque por tolerarem o déficit hídrico e produzirem em períodos onde a oferta de forragem está reduzida, além de apresentam bom valor nutricional e serem bem aceitas pelos animais. Porém, devido à variação na sua composição, seu uso na alimentação animal exige o conhecimento profundo da sua composição para a elaboração de dietas balanceadas. No entanto, devido ao custo e tempo para análise, os produtores não fazem uso da prática de análise da composição químico-bromatológica dos alimentos. Por isto, a espectroscopia de reflectância no infravermelho próximo (NIRS) representa uma importante alternativa aos métodos tradicionais. Objetivou-se com este estudo desenvolver e validar modelos de predição da composição bromatológica de vagem de algaroba e palma forrageira baseados em espectroscopia NIRS, escaneadas em dois modelos de equipamentos e com diferentes processamentos da amostra. Foram coletadas amostras de vagem de algaroba nos estados do Ceará, Bahia, Paraíba e Pernambuco, e amostras de palma forrageira nos estados do Ceará, Paraíba e Pernambuco, frescas (in natura) ou pré-secas e moídas. Para obtenção dos espectros utilizaram-se dois equipamentos NIR, Perten DA 7250 e FOSS 5000. Inicialmente os alimentos foram escaneados in natura em aparelho do modelo Perten, e, com o auxílio do software The Unscrambler 10.2 foi selecionado um grupo de amostras para o banco de calibração. As amostras selecionadas foram secas e moídas, e escaneadas novamente em equipamentos Perten e FOSS. Os valores dos parâmetros de referência foram obtidos por meio de metodologias tradicionalmente aplicadas em laboratório de nutrição animal para matéria seca (MS), matéria mineral (MM), matéria orgânica (MO), proteína bruta (PB), estrato etéreo (EE), fibra solúvel em detergente neutro (FDN), fibra solúvel em detergente ácido (FDA), hemicelulose (HEM) e digestibilidade in vitro da matéria seca (DIVMS). O desempenho dos modelos foi avaliado de acordo com os erros médios de calibração (RMSEC) e validação (RMSECV), coeficiente de determinação (R2 ) e da relação de desempenho de desvio dos modelos (RPD). A análise exploratória dos dados, por meio de tratamentos espectrais e análise de componentes principais (PCA), demonstraram que os bancos de dados eram similares entre si, dando segurança de desenvolver os modelos com todas as amostras selecionadas em um único modelo para cada alimento, algaroba e palma. Na avaliação dos resultados de referência, observou-se que a variação dos resultados para cada parâmetro corroboraram com os descritos na literatura. No desempenho dos modelos, aqueles desenvolvidos com pré-processamento da amostra (pré-secagem e moagem) se mostraram mais robustos do que aqueles construídos com amostras in natura. O aparelho NIRS Perten apresentou desempenho semelhante ao equipamento FOSS, apesar desse último cobrir uma faixa espectral maior e com intervalos de leituras menores. A técnica NIR, associada ao método de calibração multivariada de regressão por meio de quadrados mínimos (PLS), mostrou-se confiável para prever a composição químico-bromatológica de vagem de algaroba e da palma forrageira. Abstract: Forage species adapted to semi-arid conditions are an alternative to reduce the negative impacts in the feed supply for ruminants in the Brazilian Northeast region, due to seasonality in forage availability, as well as in the reducing of cost by providing concentrated feedstuffs. Among the species, mesquite pods (Prosopis juliflora SW DC) and spineless cactus (Opuntia and Nopalea) are highlighted for tolerating the drought and producion in periods where the forage is scarce, and have high nutritional value and also are well accepted by the animals. However, its use in animal diets requires a knowledge about its composition to prepare balanced diets. However, farmers usually do not use feed composition analysis, because their high cost and time-consuming. Thus, the Near Infrared Reflectance Spectroscopy in the (NIRS) is an important alternative to traditional methods. The objective of this study to develop and validate predictive models of the chemical composition of mesquite pods and spineless cactus-based NIRS spectroscopy, scanned in two different spectrometers and sample processing. Mesquite pods samples were collected in the states of Ceará, Bahia, Paraiba and Pernambuco, and samples of forage cactus in the states of Ceará, Paraíba and Pernambuco. In order to obtain the spectra, it was used two NIR equipment: Perten DA 7250 and FOSS 5000. sSpectra of samples were initially obtained fresh (as received) using Perten instrument, and with The Unscrambler software 10.2, a group of subsamples was selected to model development, keeping out redundant ones. The selected samples were dried and ground, and scanned again in both Perten and FOSS instruments. The values of the reference analysis were obtained by methods traditionally applied in animal nutrition laboratory to dry matter (DM), mineral matter (MM), organic matter (OM), crude protein (CP), ether extract (EE), soluble neutral detergent fiber (NDF), soluble acid detergent fiber (ADF), hemicellulose ( HEM) and in vitro digestibility of dry matter (DIVDM). The performance of the models was evaluated according to the Root Mean Square Error of Calibration (RMSEC) and cross-validation (RMSECV), coefficient of determination (R2 ) and the deviation of Ratio of performance Deviation of the models (RPD). Exploratory data analysis through spectral treatments and principal component analysis (PCA), showed that the databases were similar to each other, and may be treated asa single model for each feed - mesquite pods and cactus. Evaluating the reference results, it was observed that the variation were similar to those reported in the literature. Comparing the preprocessing of samples, the performance ofthose developed with preprocessing (dried and ground) of the sample were more robust than those built with fresh samples. The NIRS Perten device performance similar to FOSS equipment, although the latter cover a larger spectral range and with lower readings intervals. NIR technology associate do multivariate techniques is reliable to predict the bromatological composition of mesquite pods and cactus.