65 resultados para NIRS. Bactérias. PCA. SIMCA. PLS-DA


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The concentration of 15 polycyclic aromatic hydrocarbons (PAHs) in 57 samples of distillates (cachaça, rum, whiskey, and alcohol fuel) has been determined by HPLC-Fluorescence detection. The quantitative analytical profile of PAHs treated by Partial Least Square - Discriminant Analysis (PLS-DA) provided a good classification of the studied spirits based on their PAHs content. Additionally, the classification of the sugar cane derivatives according to the harvest practice was obtained treating the analytical data by Linear Discriminant Analysis (LDA), using naphthalene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene, benz[b]fluoranthene, and benz[g,h,i]perylene, as a chemical descriptors.

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One hundred fifteen cachaça samples derived from distillation in copper stills (73) or in stainless steels (42) were analyzed for thirty five itens by chromatography and inductively coupled plasma optical emission spectrometry. The analytical data were treated through Factor Analysis (FA), Partial Least Square Discriminant Analysis (PLS-DA) and Quadratic Discriminant Analysis (QDA). The FA explained 66.0% of the database variance. PLS-DA showed that it is possible to distinguish between the two groups of cachaças with 52.8% of the database variance. QDA was used to build up a classification model using acetaldehyde, ethyl carbamate, isobutyl alcohol, benzaldehyde, acetic acid and formaldehyde as chemical descriptors. The model presented 91.7% of accuracy on predicting the apparatus in which unknown samples were distilled.

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The aim of the present study was to evaluate the effect of soil characteristics (pH, macro- and micro-nutrients), environmental factors (temperature, humidity, period of the year and time of day of collection) and meteorological conditions (rain, sun, cloud and cloud/rain) on the flavonoid content of leaves of Passiflora incarnata L., Passifloraceae. The total flavonoid contents of leaf samples harvested from plants cultivated or collected under different conditions were quantified by high-performance liquid chromatography with ultraviolet detection (HPLC-UV/PAD). Chemometric treatment of the data by principal component (PCA) and hierarchic cluster analyses (HCA) showed that the samples did not present a specific classification in relation to the environmental and soil variables studied, and that the environmental variables were not significant in describing the data set. However, the levels of the elements Fe, B and Cu present in the soil showed an inverse correlation with the total flavonoid contents of the leaves of P. incarnata.

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The concentration of 14 organic acids of 50 sugarcane spirits samples was determined by gas chromatography using flame ionization detection. The organic acids analytical quantitative profile in stills and column distilled spirits from wines obtained from the same must were compared. The comparison was also carried in "head", "heart" and "tail fractions of stills distilled spirits. The experimental data were analyzed by Principal Components Analysis (PCA) and pointed out that the distillation process (stills and column) strongly influences the lead spirits' organic acid composition and that producers' operational "cuts off" to produce "tail", "heart" and "head", fractions should be optimized.

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This study evaluated the microbiological quality of hamburgers and the microbe community on the hands of vendors in Cuiabá, Mato Grosso, Brazil, in relation to vendors´ awareness as to what constitute acceptable food-handling practices as part of a broad-spectrum research programme on street foods in Brazil . Sale of the hamburger known as the 'baguncinha' is common and widespread in urban Cuiabá, Mato Grosso, Brazil. Food inspectors encounter various difficulties in carrying out inspections. One hundred and five hamburgers samples were evaluated using conventional methods including tests for facultative aerobic and/or anaerobic mesophytic bacteria, coliform counts at 45 °C, the coagulase test for Staphylococcus, Gram-staining for the presence of Bacillus cereus, Clostridium sulphite reductase and Salmonella spp. The hamburgers were categorized as unsuitable for human consumption in 31.4% of samples, with those testing positive for coliforms and Staphylococcus at unacceptably high levels by Brazilian standards. High levels of microbiological contamination were detected on the hands of the food handlers and mesophytic bacterial counts reached 1.8 × 10(4) CFU/hand. Interviews were carried out by means of questionnaires to evaluate levels of awareness as to acceptable food handling practices and it was found that 80,1% of vendors had never participated in any kind of training.

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Three comparative assays were performed seeking to improve the sensitivity of the diagnosis of Bordetella bronchiseptica infection analyzing swine nasal swabs. An initial assay compared the recovery of B. bronchiseptica from swabs simultaneously inoculated with B. bronchiseptica and some interfering bacteria, immersed into three transport formulations (Amies with charcoal, trypticase soy broth and phosphate buffer according to Soerensen supplemented with 5% of bovine fetal serum) and submitted to different temperatures (10ºC and 27ºC) and periods of incubation (24, 72 and 120 hours). A subsequent assay compared three selective media (MacConkey agar, modified selective medium G20G and a ceftiofur medium) for their recovery capabilities from clinical specimens. One last assay compared the polymerase chain reaction to the three selective media. In the first assay, the recovery of B. bronchiseptica from transport systems was better at 27ºC and the three formulations had good performances at this temperature, but the collection of qualitative and quantitative analysis indicated the advantage of Amies medium for nasal swabs transportation. The second assay indicated that MacConkey agar and modified G20G had similar results and were superior to the ceftiofur medium. In the final assay, polymerase chain reaction presented superior capability of B. bronchiseptica detection to culture procedures.

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O tratamento de esgotos de pequenas cidades por lagoas de estabilização é uma maneira simples, eficiente e de baixo custo. Os esgotos são uma fonte de contaminação das águas e solos e, conseqüentemente, contribuem para a transmissão de doenças, além de serem uma ameaça à preservação do meio ambiente. Surge a necessidade de investigar as condições dos efluentes lançados nos cursos d´água. O presente trabalho tem como objetivo realizar uma investigação da qualidade das águas residuárias tratadas por lagoas de estabilização de uma estação de tratamento de esgoto localizadas no município de São Lourenço da Serra no Vale da Ribeira no Estado de São Paulo e verificar os riscos sanitários e a comunidade aquática no Rio São Lourenço da Serra. Foram realizadas amostragens para avaliar o conjunto de lagoas anaeróbia e facultativa da estação de tratamento de esgoto do Município de São Lourenço da Serra. Os parâmetros utilizados foram pH, temperatura do ar e da água, condições climáticas, demanda bioquímica de oxigênio e nitrogênio amoniacal, bactérias termotolerantes, pigmentos fotossintéticos e comunidade zooplanctônica. Verificou-se que s sistemas de lagoa anaeróbia e facultativa foram eficientes na produção de efluente e apresentou alguns valores de acordo com a Resolução Conama nº 357, que estabelecem os valores limites para lançamento em corpos d´água. O rio São Lourenço está localizado em uma área de proteção ambiental. Os dados são comparados aos limites estabelecidos na Classe 1 e 2 e demonstram processo de eutrofização, colocando em risco à biodiversidade aquática e a saúde da população

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A susceptible-infective-recovered (SIR) epidemiological model based on probabilistic cellular automaton (PCA) is employed for simulating the temporal evolution of the registered cases of chickenpox in Arizona, USA, between 1994 and 2004. At each time step, every individual is in one of the states S, I, or R. The parameters of this model are the probabilities of each individual (each cell forming the PCA lattice ) passing from a state to another state. Here, the values of these probabilities are identified by using a genetic algorithm. If nonrealistic values are allowed to the parameters, the predictions present better agreement with the historical series than if they are forced to present realistic values. A discussion about how the size of the PCA lattice affects the quality of the model predictions is presented. Copyright (C) 2009 L. H. A. Monteiro et al.

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The aim of the present study was to examine the impact of polymorphisms in prostate-specific antigen (PSA) and androgen-related genes (AR, CYP17, and CYP19) on prostate cancer (PCa) risk in selected high-risk patients who underwent prostate biopsy. Blood samples and prostate tissues were obtained for DNA analysis. Single-nucleotide polymorphisms in the 50-untranslated regions (UTRs) of the PSA (substitution A > G at position -158) and CYP17 (substitution T > C at 50-UTR) genes were detected by polymerase chain reaction (PCR)-restriction fragment length polymorphism assays. The CAG and TTTA repeats in the AR and CYP19 genes, respectively, were genotyped by PCR-based GeneScan analysis. Patients with the GG genotype of the PSA gene had a higher risk of PCa than those with the AG or AA genotype (OR = 3.79, p = 0.00138). The AA genotype was associated with lower PSA levels (6.44 +/- 1.64 ng/mL) compared with genotypes having at least one G allele (10.44 +/- 10.06 ng/mL) (p = 0.0687, 95% CI - 0.3146 to 8.315, unpaired t-test). The multivariate analysis confirmed the association between PSA levels and PSA genotypes (AA vs. AG+GG; chi(2) = 0.0482) and CYP19 (short alleles homozygous vs. at least one long allele; chi(2) = 0.0110) genotypes. Genetic instability at the AR locus leading to somatic mosaicism was detected in one PCa patient by comparing the length of AR CAG repeats in matched peripheral blood and prostate biopsy cores. Taken together, these findings suggest that the PSA genotype should be a clinically relevant biomarker to predict the PCa risk.

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Three-dimensional spectroscopy techniques are becoming more and more popular, producing an increasing number of large data cubes. The challenge of extracting information from these cubes requires the development of new techniques for data processing and analysis. We apply the recently developed technique of principal component analysis (PCA) tomography to a data cube from the center of the elliptical galaxy NGC 7097 and show that this technique is effective in decomposing the data into physically interpretable information. We find that the first five principal components of our data are associated with distinct physical characteristics. In particular, we detect a low-ionization nuclear-emitting region (LINER) with a weak broad component in the Balmer lines. Two images of the LINER are present in our data, one seen through a disk of gas and dust, and the other after scattering by free electrons and/or dust particles in the ionization cone. Furthermore, we extract the spectrum of the LINER, decontaminated from stellar and extended nebular emission, using only the technique of PCA tomography. We anticipate that the scattered image has polarized light due to its scattered nature.

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We investigate the sensitivity of the composite cellular automaton of H. Fuks [Phys. Rev. E 55, R2081 (1997)] to noise and assess the density classification performance of the resulting probabilistic cellular automaton (PCA) numerically. We conclude that the composite PCA performs the density classification task reliably only up to very small levels of noise. In particular, it cannot outperform the noisy Gacs-Kurdyumov-Levin automaton, an imperfect classifier, for any level of noise. While the original composite CA is nonergodic, analyses of relaxation times indicate that its noisy version is an ergodic automaton, with the relaxation times decaying algebraically over an extended range of parameters with an exponent very close (possibly equal) to the mean-field value.

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Stavskaya's model is a one-dimensional probabilistic cellular automaton (PCA) introduced in the end of the 1960s as an example of a model displaying a nonequilibrium phase transition. Although its absorbing state phase transition is well understood nowadays, the model never received a full numerical treatment to investigate its critical behavior. In this Brief Report we characterize the critical behavior of Stavskaya's PCA by means of Monte Carlo simulations and finite-size scaling analysis. The critical exponents of the model are calculated and indicate that its phase transition belongs to the directed percolation universality class of critical behavior, as would be expected on the basis of the directed percolation conjecture. We also explicitly establish the relationship of the model with the Domany-Kinzel PCA on its directed site percolation line, a connection that seems to have gone unnoticed in the literature so far.

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P>Soil bulk density values are needed to convert organic carbon content to mass of organic carbon per unit area. However, field sampling and measurement of soil bulk density are labour-intensive, costly and tedious. Near-infrared reflectance spectroscopy (NIRS) is a physically non-destructive, rapid, reproducible and low-cost method that characterizes materials according to their reflectance in the near-infrared spectral region. The aim of this paper was to investigate the ability of NIRS to predict soil bulk density and to compare its performance with published pedotransfer functions. The study was carried out on a dataset of 1184 soil samples originating from a reforestation area in the Brazilian Amazon basin, and conventional soil bulk density values were obtained with metallic ""core cylinders"". The results indicate that the modified partial least squares regression used on spectral data is an alternative method for soil bulk density predictions to the published pedotransfer functions tested in this study. The NIRS method presented the closest-to-zero accuracy error (-0.002 g cm-3) and the lowest prediction error (0.13 g cm-3) and the coefficient of variation of the validation sets ranged from 8.1 to 8.9% of the mean reference values. Nevertheless, further research is required to assess the limits and specificities of the NIRS method, but it may have advantages for soil bulk density predictions, especially in environments such as the Amazon forest.

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A novel flow-based strategy for implementing simultaneous determinations of different chemical species reacting with the same reagent(s) at different rates is proposed and applied to the spectrophotometric catalytic determination of iron and vanadium in Fe-V alloys. The method relies on the influence of Fe(II) and V(IV) on the rate of the iodide oxidation by Cr(VI) under acidic conditions, the Jones reducing agent is then needed Three different plugs of the sample are sequentially inserted into an acidic KI reagent carrier stream, and a confluent Cr(VI) solution is added downstream Overlap between the inserted plugs leads to a complex sample zone with several regions of maximal and minimal absorbance values. Measurements performed on these regions reveal the different degrees of reaction development and tend to be more precise Data are treated by multivariate calibration involving the PLS algorithm The proposed system is very simple and rugged Two latent variables carried out ca 95% of the analytical information and the results are in agreement with ICP-OES. (C) 2010 Elsevier B V. All rights reserved.

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A rapid method for classification of mineral waters is proposed. The discrimination power was evaluated by a novel combination of chemometric data analysis and qualitative multi-elemental fingerprints of mineral water samples acquired from different regions of the Brazilian territory. The classification of mineral waters was assessed using only the wavelength emission intensities obtained by inductively coupled plasma optical emission spectrometry (ICP OES), monitoring different lines of Al, B, Ba, Ca, Cl, Cu, Co, Cr, Fe, K, Mg, Mn, Na, Ni, P, Pb, S, Sb, Si, Sr, Ti, V, and Zn, and Be, Dy, Gd, In, La, Sc and Y as internal standards. Data acquisition was done under robust (RC) and non-robust (NRC) conditions. Also, the combination of signal intensities of two or more emission lines for each element were evaluated instead of the individual lines. The performance of two classification-k-nearest neighbor (kNN) and soft independent modeling of class analogy (SIMCA)-and preprocessing algorithms, autoscaling and Pareto scaling, were evaluated for the ability to differentiate between the various samples in each approach tested (combination of robust or non-robust conditions with use of individual lines or sum of the intensities of emission lines). It was shown that qualitative ICP OES fingerprinting in combination with multivariate analysis is a promising analytical tool that has potential to become a recognized procedure for rapid authenticity and adulteration testing of mineral water samples or other material whose physicochemical properties (or origin) are directly related to mineral content.