Reconhecimento de padrões por métodos não supervisionados: explorando procedimentos quimiométricos para tratamento de dados analíticos

An activity for introducing hierarchical cluster analysis (HCA) and principal component analysis (PCA) during the Instrumental Analytical Chemistry course is presented. The posed problem involves the discrimination of mineral water samples according to their geographical origin. Thirty-seven samples of 9 different brands were considered and the results from the determination of Na, K, Mg, Ca, Sr and Ba were taken into account. Non-supervised methods for pattern recognition were explored to construct a dendrogram, score and loading plots. The devised activity can be adopted for introducing Chemometrics devoted to data handling, stressing its importance in the context of modern Analytical Chemistry.

Hidrocarbonetos policíclicos aromáticos como traçadores da queima de cana-de-açúcar: uma abordagem estatística

In this study atmospheric particulates of PAHs were measured in Araraquara, Piracicaba and São Paulo in July 2003 (sugarcane harvest season in Araraquara and Piracicaba) and in Araraquara in March of 2003. The results were normalized to the total PAH concentrations. Comparison among the sites and principal component analysis (PCA) were used to investigate possible tracers of emission. Fluoranthene and pyrene concentrations were higher in Piracicaba and Araraquara samples. These PAH were also responsible for the largest negative loadings on the second principal component and account for the negative scores and for the formation of the Araraquara and Piracicaba group.

Análise arqueométrica de cerâmica Tupiguarani da região central do Estado do Rio Grande do Sul, Brasil, usando fluorescência de raios X por dispersão de energia (EDXRF)

Energy dispersive X-ray fluorescence methodology (EDXRF) was used to determine Al, Ba, Ca, Cr, Fe, K, Mn, Pb, Rb, S, Si, Sr, Ti, V, Zn in pottery sherds from seven archaeological sites in the central region of Rio Grande do Sul State, Brazil. The potteries' chemical fingerprints from Ijuí River, Ibicuí Mirim River, Vacacaí Mirim River and Jacuí River were identified. Interactions between sites from the Jacuí River, Vacacaí Mirim River and Ibicui Mirim River could have occurred because some samples from these sites are overlapping in a principal component analysis (PCA) graphic. The pottery provenance could be the same.

Tratamento estatístico dos parâmetros da qualidade das águas da bacia do alto curso do Rio das Velhas

Water quality was monitored at the upper course of the Rio das Velhas, a major tributary of the São Francisco basin located in the state of Minas Gerais, over an extension of 108 km from its source up to the limits with the Sabara district. Monitoring was done at 37 different sites over a period of 2 years (2003-2004) for 39 parameters. Multivariate statistical techniques were applied to interpret the large water-quality data set and to establish an optimal long-term monitoring network. Cluster analysis separated the sampling sites into groups of similarity, and also indicated the stations investigated for correlation and recommended to be removed from the monitoring network. Principal component analysis identified four components, which are responsible for the data structure explaining 80% of the total variance of the data. The principal parameters are characterized as due to mining activities and domestic sewage. Significant data reduction was achieved.

Estudo comparativo de métodos para a determinação da concentração de carbono em solos com altos teores de Fe (Latossolos)

Soil organic matter (SOM) plays an important role in physical, chemical and biological properties of soil. Therefore, the amount of SOM is important for soil management for sustainable agriculture. The objective of this work was to evaluate the amount of SOM in oxisols by different methods and compare them, using principal component analysis, regarding their limitations. The methods used in this work were Walkley-Black, elemental analysis, total organic carbon (TOC) and thermogravimetry. According to our results, TOC and elemental analysis were the most satisfactory methods for carbon quantification, due to their better accuracy and reproducibility.

Análise multivariada de parâmetros físico-químicos em amostras de vinhos tintos comercializados na região metropolitana do Recife

The Brazilian legislation requires analysis of certain parameters to classify a wine and allow its commercialization. Some physico-chemical and some color parameters were determined in this work in samples of different red wines sold in the metropolitan area of Recife. Multivariate analysis comprising principal component analysis and hierarchical cluster analysis was employed to distinguish the analyzed wines. The results for pH, chloride concentration, color parameters and ammonium content were the most important variables for sample classification. It was also possible to classify the wines as soft or dry wines and amongst the soft wines we could determine two out of four winegrowing producers.

Advanced chemometric methods: Applicability on industrial data

Recent years have produced great advances in the instrumentation technology. The amount of available data has been increasing due to the simplicity, speed and accuracy of current spectroscopic instruments. Most of these data are, however, meaningless without a proper analysis. This has been one of the reasons for the overgrowing success of multivariate handling of such data. Industrial data is commonly not designed data; in other words, there is no exact experimental design, but rather the data have been collected as a routine procedure during an industrial process. This makes certain demands on the multivariate modeling, as the selection of samples and variables can have an enormous effect. Common approaches in the modeling of industrial data are PCA (principal component analysis) and PLS (projection to latent structures or partial least squares) but there are also other methods that should be considered. The more advanced methods include multi block modeling and nonlinear modeling. In this thesis it is shown that the results of data analysis vary according to the modeling approach used, thus making the selection of the modeling approach dependent on the purpose of the model. If the model is intended to provide accurate predictions, the approach should be different than in the case where the purpose of modeling is mostly to obtain information about the variables and the process. For industrial applicability it is essential that the methods are robust and sufficiently simple to apply. In this way the methods and the results can be compared and an approach selected that is suitable for the intended purpose. Differences in data analysis methods are compared with data from different fields of industry in this thesis. In the first two papers, the multi block method is considered for data originating from the oil and fertilizer industries. The results are compared to those from PLS and priority PLS. The third paper considers applicability of multivariate models to process control for a reactive crystallization process. In the fourth paper, nonlinear modeling is examined with a data set from the oil industry. The response has a nonlinear relation to the descriptor matrix, and the results are compared between linear modeling, polynomial PLS and nonlinear modeling using nonlinear score vectors.

Sampling in chemical analysis

The uncertainty of any analytical determination depends on analysis and sampling. Uncertainty arising from sampling is usually not controlled and methods for its evaluation are still little known. Pierre Gy’s sampling theory is currently the most complete theory about samplingwhich also takes the design of the sampling equipment into account. Guides dealing with the practical issues of sampling also exist, published by international organizations such as EURACHEM, IUPAC (International Union of Pure and Applied Chemistry) and ISO (International Organization for Standardization). In this work Gy’s sampling theory was applied to several cases, including the analysis of chromite concentration estimated on SEM (Scanning Electron Microscope) images and estimation of the total uncertainty of a drug dissolution procedure. The results clearly show that Gy’s sampling theory can be utilized in both of the above-mentioned cases and that the uncertainties achieved are reliable. Variographic experiments introduced in Gy’s sampling theory are beneficially applied in analyzing the uncertainty of auto-correlated data sets such as industrial process data and environmental discharges. The periodic behaviour of these kinds of processes can be observed by variographic analysis as well as with fast Fourier transformation and auto-correlation functions. With variographic analysis, the uncertainties are estimated as a function of the sampling interval. This is advantageous when environmental data or process data are analyzed as it can be easily estimated how the sampling interval is affecting the overall uncertainty. If the sampling frequency is too high, unnecessary resources will be used. On the other hand, if a frequency is too low, the uncertainty of the determination may be unacceptably high. Variographic methods can also be utilized to estimate the uncertainty of spectral data produced by modern instruments. Since spectral data are multivariate, methods such as Principal Component Analysis (PCA) are needed when the data are analyzed. Optimization of a sampling plan increases the reliability of the analytical process which might at the end have beneficial effects on the economics of chemical analysis,

Análisis psicométrico de la escala multidimensional de autoconcepto AF5 en una muestra de adolescentes y adultos de Cataluña

Psychometric analysis of the AF5 multidimensional scale of self-concept in a sample of adolescents and adults in Catalonia. The aim of this study is to carry out a psychometric study of the AF5 scale in a sample of 4.825 Catalan subjects from 11 to 63 years-old. They are students from secondary compulsory education (ESO), from high school, middle-level vocational training (CFGM) and from the university. Using a principal component analysis (PCA) the theoretical validity of the components is established and the reliability of the instrument is also analyzed. Differential analyses are performed by gender and normative group using a 2 6 factorial design. The normative group variable includes the different levels classifi ed into 6 sub-groups: university, post-compulsory secondary education (high school and CFGM), 4th of ESO, 3rd of ESO, 2nd of ESO and 1st of ESO. The results indicate that the reliability of the Catalan version of the scale is similar to the original scale. The factorial structure also fi ts with the original model established beforehand. Signifi cant differences by normative group in the four components of self-concept explored (social, family, academic/occupational and physical) are observed. By gender, signifi cant differences appear in the component of physical self-concept, academic and social but not in the family component

Estudo sobre a utilização da lama vermelha para a remoção de corantes em efluentes têxteis

Red mud is the principal residue of the alumina (Al2O3) industry. Generated during the Bayer process, it is characterized by strong alkalinity and ion exchange. Iron oxides are the principal component (30 to 60%). Annually millions of tons of red mud are generated in the world. Red mud disposal is responsible for a large part of the cost of alumina production. On the other hand, textile industry wastewaters containing dyes have a great impact on the environment and on human health. In this paper the possibility of applying red mud for the removal of dyes was investigated by two processes: adsorption and degradation by the Fenton reagent.

Estudo da mobilização de metais e elementos traços em ambientes aquáticos do semi-árido brasileiro aplicando análises de componentes principais

The spatial and temporal retention of metals has been studied in water and sediments of the Gavião River, Anagé and Tremedal Reservoirs, located in the semi-arid region, Bahia - Brazil, in order to identify trends in the fluxes of metals from the sediments to the water column. The determination of metals was made by ICP OES and ET AAS. The application of statistical methods showed that this aquatic system presents suitable conditions to move Cd2+ and Pb2+ from the water column to the sediment.

Classificação de refrigerantes através de análise de imagens e análise de componentes principais (PCA)

This paper describes an approach for the colour-based classification of RGB (red-green-blue) images, acquired using a common scanner, of commercial carbonated soft drinks. Mean histograms of image colour channels were evaluated for the PCA classification of 29 brands of Guaraná, Cola, and orange flavors. Loadings for principal component axes resulted in different patterns for sample grouping on score plots according to RGB histograms. pH, sorbic acid and sucrose measurements were also correlated to the analyzed brands through PCA score plots of the digitalized images.

Efeitos dos escoamentos urbanos e rurais na qualidade das águas do córrego verruga em vitória da conquista - Bahia, Brasil

This study examined the spatial and temporal variations of 13 physico-chemical parameters in water and sediment samples collected along the rural and urban section of Verruga Stream. The metal concentrations were determined by FAAS. The conductivity and the concentration of Na+, Cl-, and Ca2+ showed the largest variations in the urban area demonstrating that these parameters are appropriate indicators of urban contamination. The application of cluster and principal component analysis showed that the Cd2+ and Mn2+ are associated with the use of fertilizers in the rural area.

Caracterização de contaminantes presentes em sistemas de tratamento de esgotos, por cromatografia líquida acoplada à espectrometria de massas tandem em alta resolução

This work shows results on the characterization, by liquid chromatography coupled to high resolution tandem mass spectrometry (LC-IT-TOF-MS) with electrospray ionization, of organic compounds present in raw and treated effluents from a combined sewage treatment systems (upflow anaerobic sludge blanket-trickling filter). The sewage samples were prepared by C18 solid phase extraction and the spectra obtained from the various extracts were submitted to principal component analysis to evaluate their pattern and identify the major deprotonated species. Some target compounds were submitted to semiquantitative analysis, using phenolphtalein as internal standard. The results showed the anaerobic step had little impact on the removal of anionic surfactants (LAS), fatty acids, and some contaminantes such as bisphenol A and bezafibrate, whereas the aerobic post-treatment was very efficient in removing these organics.

Aplicación de una lengua electrónica voltamétrica para la clasificación de vinos y estudio de correlación con la caracterización química y sensorial

This paper presents the analytical application of a novel electronic tongue based on voltammetric sensors array. This device was used in the classification of wines aged in barrels of different origins and toasting levels. Furthermore, a study of correlation between the response of the electronic tongue and the sensory and chemical characterization of samples was carried out. The results were evaluated by applying both principal component analysis and cluster analysis. The samples were clearly classified. Their distribution showed a high correspondence degree with the characteristics of the analyzed wines, it also showed similarity with the classification obtained from organoleptic analysis.