Variabilidade espacial e temporal de parâmetros físico-químicos nos rios Turvo, Preto e Grande no estado de São Paulo, Brasil

This work aims to study spatial and seasonal variability of some chemical-physical parameters in the Turvo/Grande watershed, São Paulo State, Brazil. Water samples were taken monthly, 2007/07-2008/11, from fourteen sampling stations sited along the Turvo, Preto and Grande Rivers and its main tributaries. The Principal Component Analysis and hierarchical cluster analysis showed two distinct groups in this watershed, the first one associated for the places more impacted by domestic effluent (lower levels of dissolved oxygen in the studied region). The sampling places located to downstream (Turvo and Grande rivers) were discriminate by diffuse source of pollutants from flooding and agriculture runoffs in a second group.

Aplicação de métodos quimiométricos na caracterização de charutos utilizando extração por dispersão da matriz em fase sólida e análise por cromatografia gasosa acoplada à espectrometria de massas

In this work, the organic compounds of cigar samples from different brands were analyzed. The compound extraction was made using the matrix solid-phase dispersion (MSPD) technique, followed by gas chromatography and identification by mass spectrometry (GC-MS) and standards, when available. Thirty eight organic compounds were found in seven different brands. Finally, with the objective of characterizing and discriminating the cigar samples, multivariate statistical analyses were applied to data, e.g.; principal component analysis (PCA) and hierarchical cluster analysis (HCA). With such analyses, it was possible to discriminate three main groups of three quality levels.

Comparação do perfil químico entre cachaças de um mesmo vinho destiladas em alambiques e em colunas

Six wines were distilled in two different distillation apparatus (alembic and column) producing 24 distillates (6 for each alembic fraction - head, heart and tail; 6 column distillates). The chemical composition of distillates from the same wine was determined using chromatographic techniques. Analytical data were subjected to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) allowing discrimination of four clusters according to chemical profiles. Both distillation processes influenced the sugarcane spirits chemical quality since two types of distillates with different quantitative chemical profiles were produced after the elimination of fermentation step influence.

Classificação multivariada de ervas medicinais da Região Amazônica e suas infusões de acordo com sua composição mineral

In this study, the mineral composition of leaves and teas of medicinal plants was evaluated. Ca, Cu, Fe, Mg, Mn e Zn were determined in the samples using flame atomic absorption spectrometry. Principal component analysis was applied to discriminate the samples studied. The samples were divided within the 2 groups according to their mineral composition. Copper and iron were the variables that contributed most to the separation of the samples followed by Ca, Mg, Mn and Zn. The information in the principal component analysis was confirmed by the dendrogram obtained by hierarchical cluster analysis.

Chemical composition of volatiles from male and female specimens of Baccharis trimera collected in two distant regions of southern brazil: a comparative study using chemometrics

GC/MS/FID analyses of volatile compounds from cladodes and inflorescences from male and female specimens of Baccharis trimera (Less.) DC. collected in the states of Paraná and Santa Catarina, Brazil, showed that carquejyl acetate was the primary volatile component (38% to 73%), while carquejol and ledol were identified in lower concentrations. Data were subjected to hierarchical cluster analysis and principal component analysis, which confirmed that the chemical compositions of all samples were similar. The results presented here highlight the occurrence of the same chemotype of B. trimera in three southern states of Brazil.

Análise exploratória aplicada a espectros de reflexão total atenuada no infravermelho com transformada de Fourier (ATR-FTIR) de blendas de biodiesel/diesel

In this study, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to classify blends produced from diesel S500 and different kinds of biodiesel produced by the TDSP methodology. The different kinds of biodiesel studied in this work were produced from three raw materials: soybean oil, waste cooking oil and hydrogenated vegetable oil. Methylic and ethylic routes were employed for the production of biodiesel. HCA and PCA were performed on the data from attenuated total reflectance Fourier transform infrared spectroscopy, showing the separation of the blends into groups according to biodiesel content present in the blends and to the kind of biodiesel used to form the mixtures.

Variation of essential oil composition of Tapirira guianensis Aubl. (Anacardiaceae) from two sandbank forests, north of Brazil

Tapirira guianensis (Anacardiaceae) is used in traditional medicine and is important for the recovery of degraded areas and riparian forests because the T. guianensis fruits are highly consumed by wildlife. Volatile components from dried leaves and branches of five individual plants of T. guianensis were collected in two sandbank forests of the State of Pará (Extractive Reserve Maracanã and Area of Environmental Protection Algodoal/Maiandeua), extracted by hydrodistillation using a Clevenger-type apparatus, and analyzed by GC/MS. The ten oils obtained are comprised mostly of sesquiterpene hydrocarbons (58.49 to 100%), with (E)-caryophyllene, β-selinene, α-selinene, β-sesquiphellandrene, and α-zingiberene being the most prominent. The results of the oil compositions were processed by Hierarchical Component Analysis (HCA) allowing the establishment of three groups of essential oils for T. guianensis differentiated by the content of β-selinene/α-selinene (Type I), (E)-caryophyllene (Type II), and β-sesquiphellandrene/α-zingiberene (Type III).

CHEMOSTAT, UM SOFTWARE GRATUITO PARA ANÁLISE EXPLORATÓRIA DE DADOS MULTIVARIADOS

The objective of this work was to develop a free access exploratory data analysis software application for academic use that is easy to install and can be handled without user-level programming due to extensive use of chemometrics and its association with applications that require purchased licenses or routines. The developed software, called Chemostat, employs Hierarchical Cluster Analysis (HCA), Principal Component Analysis (PCA), intervals Principal Component Analysis (iPCA), as well as correction methods, data transformation and outlier detection. The data can be imported from the clipboard, text files, ASCII or FT-IR Perkin-Elmer “.sp” files. It generates a variety of charts and tables that allow the analysis of results that can be exported in several formats. The main features of the software were tested using midinfrared and near-infrared spectra in vegetable oils and digital images obtained from different types of commercial diesel. In order to validate the software results, the same sets of data were analyzed using Matlab© and the results in both applications matched in various combinations. In addition to the desktop version, the reuse of algorithms allowed an online version to be provided that offers a unique experience on the web. Both applications are available in English.

ANÁLISE EXPLORATÓRIA DAS CONCENTRAÇÕES DOS METAIS NA, CA, MG, SR E FE EM EXTRATO AQUOSO DE PETRÓLEO, DETERMINADOS POR ICP OES, APÓS OTIMIZAÇÃO EMPREGANDO PLANEJAMENTO DE EXPERIMENTOS

AbstractThe purpose of this study was to evaluate the best operating conditions of ICP OES for the determination of Na, Ca, Mg, Sr and Fe in aqueous extract of crude oil obtained after hot extraction with organic solvents (ASTM D 6470-99 modified). Thus, the full factorial design and central composite design were used to optimize the best conditions for the flow of nebulization gas, the flow of auxiliary gas, and radio frequency power. After optimization of variables, a study to obtain correct classification of the 18 samples of aqueous extract of crude oils (E1 to E18) from three production and refining fields was carried out. Exploratory analysis of these extracts was performed by principal component analysis (PCA), hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA), using the original variables as the concentration of the metals Na, Ca, Mg, Sr and Fe determined by ICP OES.

Management zones in agriculture acording to the soil and landscape variables

The study of spatial variability of soil and plants attributes, or precision agriculture, a technique that aims the rational use of natural resources, is expanding commercially in Brazil. Nevertheless, there is a lack of mathematical analysis that supports the correlation of these independent variables and their interactions with the productivity, identifying scientific standards technologically applicable. The aim of this study was to identify patterns of soil variability according to the eleven physical and seven chemical indicators in an agricultural area. It was used two multivariate techniques: the hierarchical cluster analysis (HCA) and the principal component analysis (PCA). According to the HCA, the area was divided into five management zones: zone 1 with 2.87ha, zone 2 with 0.8ha, zone 3 with 1.84ha, zone 4 with 1.33ha and zone 5 with 2.76ha. By the PCA, it was identified the most important variables within each zone: V% for the zone 1, CTC in the zone 2, levels of H+Al in the zone 4 and sand content and altitude in the zone 5. The zone 3 was classified as an intermediate zone with characteristics of all others. According to the results it is concluded that it is possible to separate into groups (management zones) samples with the same patterns of variability by the multivariate statistical techniques.

Quality evaluation of parmesan-type cheese: a chemometric approach

Parmesan-type cheeses are the most consumed special cheeses in Brazil. It is generally sold in retail shops, either grated or in wedge-shaped pieces, and its quality varies considerably, which is reflected directly in its price. There is lack of processing standardization and, since the ripening period is fundamental for the quality of this hard, semi-fat cooked cheese, this stage seems to be the thin line between low and high quality products. It is important to note that the Italian Parmegiano Reggiano is matured for a period of twelve months, as well as its rival Grana Padano, and this long ripening period causes changes making them gourmet, highly-valued cheeses. In the present study, twelve different Parmesan-type cheeses were purchased from the Brazilian retail market and evaluated for microbiological, physicochemical, and instrumental parameters. Heterogeneous quality was confirmed by microbiological problems detected in the samples and physicochemical composition that did not meet current Brazilian specifications. The use of principal component analysis and hierarchical cluster analysis made it possible to separate the samples into three distinct groups, mainly due to different acidity and moisture levels, water activity, and hardness values. The price per kg was also considered and was correlated with moisture, acidity, and texture.

Characterization of commercial cooked hams according to physicochemical, sensory, and textural parameters using chemometrics

Cooked ham is considered a high-value product due to the quality of its raw material. Although its consumption is still low in Brazil, it is increasing due to the rising purchasing power of sectors of the population. This study aimed to assess the microbiological, physicochemical, rheological, and sensory quality of cooked hams (n=11) marketed in Brazil. All samples showed microbiological results within the standards established by Brazilian legislation. Eight of the eleven samples studied met all the legal requirements; two samples violated the standards due to the addition of starch; one sample had lower protein content than the minimum required, and another one had sodium content higher than that stated on the label. The use of Hierarchical Cluster Analysis allowed the agglomeration of the samples into three groups with distinct quality traits and with significant differences in moisture content, chromaticity, syneresis, and heating and freezing loss. Principal Component Analysis showed that the samples which correlated to higher sensory acceptance regarding flavor and overall acceptability were those with higher moisture, protein, fat, and luminosity values. This study confirmed the efficacy of multivariate statistical techniques in assessing the quality of commercial cooked hams and in indicating the physicochemical parameters associated with the perception of product quality.

Drivers of human resource management competences development in Brazilian multinational subsidiaries: a multilevel research

This article aims to verify the factors associated with the development of human resource management (HRM) competences in foreign subsidiaries of Brazilian multinationals. These competences are essential in that they allow foreign units to adopt HRM practices that are consistent with the countries or markets in which they operate. A multilevel research was conducted, involving headquarters and subsidiaries of major Brazilian companies; the empirical analysis employed hierarchical linear modelling. Despite the recurrent debate on global standardisation versus local adaptation, it was identified that the integration of international HRM policies (addressing simultaneously global guidelines and local response) may stimulate competences development. In addition, interaction in external networks in the host country may enhance the development of HRM competences in the subsidiaries. However, specific cultural factors of the company may inhibit development activity in units abroad.

Blood glucose control in diabetes patients seen in primary health care centers

OBJECTIVE: To identify factors associated to poor glycemic control among diabetic patients seen at primary health care centers. METHODS: A cross-sectional study was carried out in a sample of 372 diabetic patients attending 32 primary health care centers in southern Brazil. Data on three hierarchical levels of health unit infrastructure, medical care and patient characteristics were collected. RESULTS: The frequency of poor glycemic control was 50.5%. Multivariate analysis (multilevel method) showed that patients with body mass indexes below 27 kg/m², patients on oral hypoglycemic agents or insulin, and patients diagnosed as diabetic over five years prior to the interview were more likely to present poor glycemic control when compared to their counterparts. CONCLUSIONS: Given the hierarchical data structuring, all associations found suggest that factors associated to hyperglycemia are related to patient-level characteristics.

Social control of public expenditures in a multilevel principal-agent approach

ABSTRACTThis study enhances the principal-agent model by incorporating a multilevel perspective and differences among agency situations. A theoretical discussion is developed using a proposed intersection of methodological focuses and a descriptive-exemplificative hypothetical analysis. The analysis is applied to public expenditure social control in representative democracies, and as a result, a principal-agent model unfolds that incorporates a decision-making perspective and focuses on formulation, negotiation, articulation, and implementation competencies. Thus, it is possible to incorporate elements into the principal-agent model to make it more permeable to individual, group, and societal idiosyncrasies with respect to public expenditure social control.