951 resultados para Principal Component Analysis (pca)


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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.

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The carcinogenic potential of carbendazim and its metabolites was analyzed using statistical treatment of electronic parameters obtained from DFT/ 6-311++G(d,p) and AM1 calculations. The carcinogen-DNA interaction is described in the framework of the theory of unsynchronized resonance of covalent bond as a process of electron transfer involving the HOMO and LUMO frontier orbitals. Through a Principal Component Analysis (PCA) of the electron affinity, carcinogen-DNA interaction energy, electrostatic attraction and cell membrane permeability (dipole moment m and partition coefficient LogP) evidence was obtained showing carbendazim displays carcinogenic activity. For the metabolites of carbendazim, no evidence was found in the literature of their carcinogenic activities. However, the electronic parameters for these metabolites exhibited similarity to known carcinogens, thereby showing the importance of the results obtained in this study for a policy based on the precautionary principle.

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The application of automated correlation optimized warping (ACOW) to the correction of retention time shift in the chromatographic fingerprints of Radix Puerariae thomsonii (RPT) was investigated. Twenty-seven samples were extracted from 9 batches of RPT products. The fingerprints of the 27 samples were established by the HPLC method. Because there is a retention time shift in the established fingerprints, the quality of these samples cannot be correctly evaluated by using similarity estimation and principal component analysis (PCA). Thus, the ACOW method was used to align these fingerprints. In the ACOW procedure, the warping parameters, which have a significant influence on the alignment result, were optimized by an automated algorithm. After correcting the retention time shift, the quality of these RPT samples was correctly evaluated by similarity estimation and PCA. It is demonstrated that ACOW is a practical method for aligning the chromatographic fingerprints of RPT. The combination of ACOW, similarity estimation, and PCA is shown to be a promising method for evaluating the quality of Traditional Chinese Medicine.

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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.

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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.

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The calyxes of Hibiscus sabdariffa are used in traditional medicine around the world. However, quality assurance protocols and chemical variability have not been previously analyzed. In the present study, chemical characterization of a set of samples of H. sabdariffa calyxes commercialized in Colombia was accomplished with the aim to explore the chemical variability among them. Chemometrics-based analyses on the data obtained from the HPLC-UV-DAD-derived profiles were then performed. Thus, the pre-processed single-wavelength data were subjected to principal component analysis (PCA). The PCA-derived results evidenced different groups which were well-correlated to the corresponding total phenolic and total anthocyanin contents. Multi-wavelength chromatographic (HPLC-UV-DAD surfaces) data were additionally examined via parallel factor analysis (PARAFAC) as data reduction method and the obtained loadings were subsequently submitted to PCA and orthogonal partial least squares discriminant analysis (OPLS-DA). Results were thus consistent with those from single-wavelength data. PCA loadings were employed to determine those chemical components responsible for the data variance and OPLS-DA model, constructed from PARAFAC loadings, and indicated differentiation according total anthocyanin contents among samples. The present chemometric analysis therefore demonstrated to be an excellent tool for differentiation of H. sabdariffacalyxes according to their chemical composition.

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Principal component analysis (PCA) is a chemometric method that allows for the extraction of chemical information that would otherwise be impossible to determine. Teaching chemometrics to undergraduates can contribute to the overall professional development and training of new teachers, whose profiles have been gaining attention due to the current demand for data interpretation. In this study, a didactic experiment involving PCA is proposed. Spectrophotometry was used in the ultraviolet-visible (UV-Vis) region to assess the behavior of anthocyanins extracted from red cabbage at different pH values. The results suggest the possible separation of anthocyanin structures into three distinct groups, according to their chemical characteristics displayed in acid, neutral, and basic media. The objective is to develop educational materials targeted to undergraduate courses, which encompass a larger number of concepts and introduce instrumental techniques currently being employed in both academic research and the industrial sector. Specifically, the proposed experiment introduces concepts related to spectrophotometry in the UV-Vis range and the PCA chemometric method. The materials used are easily accessible, and UV-Vis spectroscopy equipment is less expensive in comparison with other spectroscopy methods.

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The characterization of different ecological groups in a forest formation/succession is unclear. To better define the different successional classes, we have to consider ecophysiological aspects, such as the capacity to use or dissipate the light energy available. The main objective of this work was to assess the chlorophyll fluorescence emission of tropical tree species growing in a gap of a semi-deciduous forest. Three species of different ecological groups were selected: Croton floribundus Spreng. (pioneer, P), Astronium graveolens Jacq. (early secondary, Si), and Esenbeckia febrifuga A. Juss. (late secondary, St). The potential (Fv/Fm) and effective (deltaF/Fm') quantum efficiency of photosystem II, apparent electron transport rate (ETR), non-photochemical (qN) and photochemical (qP) quenching of fluorescence were evaluated, using a modulated fluorometer, between 7:30 and 11:00 h. Values of Fv/Fm remained constant in St, decreasing in P and Si after 9:30 h, indicating the occurrence of photoinhibition. Concerning the measurements taken under light conditions (deltaF/Fm', ETR, qP and qN), P and Si showed better photochemical performance, i.e., values of deltaF/Fm', ETR and qP were higher than St when light intensity was increased. Values of qN indicated that P and Si had an increasing tendency of dissipating the excess of energy absorbed by the leaf, whereas the opposite was found for St. The principal component analysis (PCA), considering all evaluated parameters, showed a clear distinction between St, P and Si, with P and Si being closer. The PCA results suggest that chlorophyll fluorescence may be a potential tool to differentiate tree species from distinct successional groups.

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This work is devoted to the analysis of signal variation of the Cross-Direction and Machine-Direction measurements from paper web. The data that we possess comes from the real paper machine. Goal of the work is to reconstruct the basis weight structure of the paper and to predict its behaviour to the future. The resulting synthetic data is needed for simulation of paper web. The main idea that we used for describing the basis weight variation in the Cross-Direction is Empirical Orthogonal Functions (EOF) algorithm, which is closely related to Principal Component Analysis (PCA) method. Signal forecasting in time is based on Time-Series analysis. Two principal mathematical procedures that we used in the work are Autoregressive-Moving Average (ARMA) modelling and Ornstein–Uhlenbeck (OU) process.

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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.

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Singular Value Decomposition (SVD), Principal Component Analysis (PCA) and Multiple Linear Regression (MLR) are some of the mathematical pre- liminaries that are discussed prior to explaining PLS and PCR models. Both PLS and PCR are applied to real spectral data and their di erences and similarities are discussed in this thesis. The challenge lies in establishing the optimum number of components to be included in either of the models but this has been overcome by using various diagnostic tools suggested in this thesis. Correspondence analysis (CA) and PLS were applied to ecological data. The idea of CA was to correlate the macrophytes species and lakes. The di erences between PLS model for ecological data and PLS for spectral data are noted and explained in this thesis. i

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In this study, cantilever-enhanced photoacoustic spectroscopy (CEPAS) was applied in different drug detection schemes. The study was divided into two different applications: trace detection of vaporized drugs and drug precursors in the gas-phase, and detection of cocaine abuse in hair. The main focus, however, was the study of hair samples. In the gas-phase, methyl benzoate, a hydrolysis product of cocaine hydrochloride, and benzyl methyl ketone (BMK), a precursor of amphetamine and methamphetamine were investigated. In the solid-phase, hair samples from cocaine overdose patients were measured and compared to a drug-free reference group. As hair consists mostly of long fibrous proteins generally called keratin, proteins from fingernails and saliva were also studied for comparison. Different measurement setups were applied in this study. Gas measurements were carried out using quantum cascade lasers (QLC) as a source in the photoacoustic detection. Also, an external cavity (EC) design was used for a broader tuning range. Detection limits of 3.4 particles per billion (ppb) for methyl benzoate and 26 ppb for BMK in 0.9 s were achieved with the EC-QCL PAS setup. The achieved detection limits are sufficient for realistic drug detection applications. The measurements from drug overdose patients were carried out using Fourier transform infrared (FTIR) PAS. The drug-containing hair samples and drug-free samples were both measured with the FTIR-PAS setup, and the measured spectra were analyzed statistically with principal component analysis (PCA). The two groups were separated by their spectra with PCA and proper spectral pre-processing. To improve the method, ECQCL measurements of the hair samples, and studies using photoacoustic microsampling techniques, were performed. High quality, high-resolution spectra with a broad tuning range were recorded from a single hair fiber. This broad tuning range of an EC-QCL has not previously been used in the photoacoustic spectroscopy of solids. However, no drug detection studies were performed with the EC-QCL solid-phase setup.

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This thesis describes the occurrence and sources of selected persistent organic pollutants (POPs) such as polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs), polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs) and hexachlorocyclohexanes (HCHs) in the northern watershed of Lake Victoria. Sediments and fish were collected from three highly polluted embayments (i.e. Murchison Bay, Napoleon Gulf and Thurston Bay) of the lake. The analysis for PCDD/Fs, PCBs and PBDEs was done using a high resolution mass spectrometer coupled to a gas chromatograph (GC), and a GC equipped with an electron capture detector was used for HCHs. Total (Σ) PCDD/Fs, PCBs and PBDEs in sediments ranged from 3.19 to 478, 313 to 4325 and 60.8 to 179 pg g-1 dry weight (dw), respectively. The highest concentrations of pollutants were found at sites close to industrial areas and wastewater discharge points. The maximum concentrations of PCDD/Fs, PCBs, PBDEs and HCHs in fish muscle homogenates were 49, 779, 495 and 45,900 pg g-1 wet weight (ww), respectively. The concentrations of the pollutants in Nile perch (Lates niloticus) were significantly greater than those in Nile tilapia (Oreochromis niloticus), possibly due to differences in trophic level and dietary feeding habits among fish species. World Health Organization-toxic equivalency quotient (WHO2005-TEQ) values in the sediments were up to 4.24 pg g-1 dw for PCDD/Fs and 0.55 pg TEQ g-1 dw for the 12 dioxin-like PCBs (dl-PCBs). 23.1% of the samples from the Napoleon Gulf were above the interim sediment quality guideline value of 0.85 pg WHO-TEQ g-1 dw set by the Canadian Council for Ministers of the Environment. The WHO2005-TEQs in fish were 0.001-0.16 pg g-1 for PCDD/Fs and 0.001-0.31 pg g-1 ww for dl- PCBs. The TEQ values were within a permissible level of 3.5 pg g−1 ww recommended by the European Commission. Based on the Commission set TEQs and minimum risk level criteria formulated by the Agency for Toxic Substances and Disease Registry, the consumption of fish from Lake Victoria gives no indication of health risks associated to PCDD/Fs and PCBs. Principal component analysis (PCA) indicated that anthropogenic activities such as agricultural straw open burning, medical waste incinerators and municipal solid waste combustors were the major sources of PCDD/Fs in the watershed of Lake Victoria. The ratios of α-/γ-HCH varied from 0.89 to 1.68 suggesting that the highest HCH residues mainly came from earlier usage and fresh γ-HCH (lindane). In the present study, the concentration of POPs in fish were not significantly related to those in sediments, and the biota sediment accumulation factor (BSAF) concept was found to be a poor predictor of the bioavailability and bioaccumulation of environmental pollutants.

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This work evaluated the physicochemical composition of 171 red Brazilian wines from the 2006 vintage, which were represented by 21 varietals. These wines were produced by 58 Brazilian wineries in different regions of the country, with latitudes varying from 9º to 31º South. Physicochemical wine analysis was performed in the same year and discrimination in the viticultural regions, varietal wines, and wineries was performed by means of the principal component analysis (PCA). The main results show that wines from São Joaquim had higher values of A420, A520, A620, color intensity, total phenolic compounds, anthocyanins, and dry extracts, while those from Toledo had lower values of these variables; those from Vale do São Francisco had higher values of potassium, pH, density, and volatile acidity; from Serra do Nordeste A, they had higher titratable acidity; and from Planalto Superior B, higher hue. Regarding the varietal wines, PCA mainly discriminated the wines produced from the varieties Ancellotta, Teroldego, Egiodola, Refosco, Marselan, Cabernet Sauvignon, Pinotage, Pinot Noir, Malbec, Arinarnoa, Barbera, and Alfrocheiro. In relation to wineries, twenty two of them were discriminated by their higher values of some variables, i.e., three were characterized by color intensity; three by hue; eight by alcohol content; six by potassium, dry extract, density, and pH; and two by titratablel acidity.

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The aim of this study was to determine the influence of process parameters and Passion Fruit Fiber (PFF) addition on the Glycemic Index (GI) of an extruded breakfast cereal. A 2³ Central Composite Rotational Design (CCRD) was used, with the following independent variables: raw material moisture content (18-28%), 2nd and 3rd barrel zone temperatures (120-160 ºC), and PFF (0-30%). Raw materials (organic corn flour and organic PFF) were characterized as to their proximate composition, particle size, and in vitro GI. The extrudates were characterized as to their in vitro GI. The Response Surface Methodology (RSM) and Principal Component Analysis (PCA) were used to analyze the results. Corn flour and PFF presented 8.55 and 7.63% protein, 2.61 and 0.60% fat, 0.52 and 6.17% ash, 78.77 and 78.86% carbohydrates (3 and 64% total dietary fiber), respectively. The corn flour particle size distribution was homogeneous, while PFF presented a heterogeneous particle size distribution. Corn flour and PFF presented values of GI of 48 and 45, respectively. When using RSM, no effect of the variables was observed in the GI of the extrudates (average value of 48.41), but PCA showed that the GI tended to be lower when processing at lower temperatures (<128 ºC) and at higher temperatures (>158 ºC). When compared to white bread, the extrudates showed a reduction of the GI of up to 50%, and could be considered an interesting alternative in weight and glycemia control diets.