913 resultados para INDEPENDENT COMPONENT ANALYSIS
Resumo:
The ¹H NMR data set of a series of 3-aryl (1,2,4)-oxadiazol-5-carbohydrazide benzylidene derivatives synthesized in our group was analyzed using the chemometric technique of principal component analysis (PCA). Using the original ¹H NMR data PCA allowed identifying some misassignments of the proton aromatic chemical shifts. As a consequence of this multivariate analysis, nuclear Overhauser difference experiments were performed to investigate the ambiguity of other assignments of the ortho and meta aromatic hydrogens for the compound with the bromine substituent. The effect of the 1,2,4-oxadiazol group as an electron acceptor, mainly for the hydrogens 12,13, has been highlighted.
Resumo:
The concentrations of Cu, Pb, Zn, Cr, Ni, Al, Mn and Fe were measured by atomic absorption spectrometry, of 19 topsoil samples collected in the Teresina city urban area to discriminate natural and anthropic contributions and identify possible sources of pollution. The average concentrations of Cu, Zn, Pb and Cr of the urban soils were 6.11, 8.56, 32.12 and 7,17 mg/kg-1, respectively. Statistical analysis techniques, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA), were used to analyze the data. Mn, Ni and Cr levels were interpreted as natural contributions, whereas Pb, Zn and, in part, Cu were accounted for mainly by anthropic activities. High Pb levels were observed in the ancient avenues.
Resumo:
Inductively Coupled Plasma Optical Emission Spectrometry was used to determine Ca, Mg, Mn, Fe, Zn and Cu in samples of processed and natural coconut water. The sample preparation consisted in a filtration step followed by a dilution. The analysis was made employing optimized instrumental parameters and the results were evaluated using methods of Pattern Recognition. The data showed common concentration values for the analytes present in processed and natural samples. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) indicated that the samples of different kinds were statistically different when the concentrations of all the analytes were considered simultaneously.
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This study presents a catalogue of synoptic patterns of torrential rainfall in northeast of the Iberian Peninsula (IP). These circulation patterns were obtained by applying a T-mode Principal Component Analysis (PCA) to a daily data grid (NCEP/NCAR reanalysis) at sea level pressure (SLP). The analysis made use of 304 days which recorded >100 mm in one or more stations in provinces of Barcelona, Girona and Tarragona (coastland area of Catalonia) throughout the 1950-2005 period. The catalogue comprises 7 circulation patterns showing a great variety of atmospheric conditions and seasonal or monthly distribution. Likewise, we computed the mean index value of the Western Mediterranean Oscillation index (WeMOi) for the synoptic patterns obtained by averaging all days grouped in each pattern. The results showed a clear association between the negative values of this teleconnection index and torrential rainfall in northeast of the IP. We therefore put forward the WeMO as an essential tool for forecasting heavy rainfall in northeast of Spain
Resumo:
Soils play an important role in the biogeochemical cycle of mercury as a sink for and source of this metallic species to atmospheric and hydrological compartments. In the study reported here, various types of soil were evaluated to ascertain the influence of parameters such as pH, organic matter content, Fe, Al, sand, silt, clay, C/H, C/N, C/O atomic ratios, and cation exchange capacity on the distribution of Hg in Amazonia's mid-Negro River basin. The data obtained were interpreted by multivariate exploratory analyses (hierarchical cluster analysis and principal component analysis), which indicated that organic matter plays an important role in mercury uptake in the various soils studied. The soils in floodable areas were found to contain 1.5 to 2.8-fold higher Hg concentrations than those in non-floodable areas. Since these soils are flooded almost year-round, they are less available to participate in redox processes at the soil/atmosphere interface. Hence, floodable areas, which comprise humic-rich soils, accumulate more mercury than non-floodable soils, thus playing an important role in the biogeochemical cycle of Hg in Amazonia's mid-Negro River basin.
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
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.
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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.
Resumo:
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.
Resumo:
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.
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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
Resumo:
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.
Resumo:
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.