71 resultados para Least mean squares methods

em Scielo Saúde Pública - SP


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A simple method was proposed for determination of paracetamol and ibuprofen in tablets, based on UV measurements and partial least squares. The procedure was performed at pH 10.5, in the concentration ranges 3.00-15.00 µg ml-1 (paracetamol) and 2.40-12.00 µg ml-1 (ibuprofen). The model was able to predict paracetamol and ibuprofen in synthetic mixtures with root mean squares errors of prediction of 0.12 and 0.17 µg ml-1, respectively. Figures of merit (sensitivity, limit of detection and precision) were also estimated. The results achieved for the determination of these drugs in pharmaceutical formulations were in agreement with label claims and verified by HPLC.

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The objective of this study was to test container of polyethylene bags and protected environments on the papaya seedlings production, from May to August of 2008, in Aquidauana state of Mato Grosso do Sul (MS), Brazil. Five bags of polyethylene were used: 7.5 cm x 11.5 cm, 205.9 cm³; 8.4 cm x 10.6 cm, 238.1cm³; 10.0 cm x 16.5 cm, 525.2 cm³; 12.0 cm x 12.0 cm, 550.0 cm³ and 15.0 cm x 21.5 cm, 1539.8 cm³. These containers were placed in three protected environments: greenhouse; screened nursery with Sombrite® and screened nursery with Aluminet®. Because there is no replication of growing environment, each one was considered an experiment. For each cultivation environment, it was adopted a completely randomized design with eight replications of two plants each. Initially, data were submitted to analysis of individual variance of the container (for each cultivation environment), then performing the evaluation of the residual mean squares and the combined analysis of these environments for comparison of protected environments. The greenhouse and nursery with thermal reflector screen produced the best seedlings. The bags of 15.0 x 21.5 cm produced the best papaya seedlings. The Dickson Quality Index pointed the nursery with screen of thermal reflector as the environment that produced the most vigorous seedlings, when using the best container.

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ABSTRACT The objective of this study was to evaluate the thermoregulatory response of dairy buffaloes in pre-milking and post-milking. To identify animal thermoregulatory capacity, skin surface temperatures were taken by an infrared thermometer (SST), a thermographic camera (MTBP) as well as respiratory rate records (RR). Black Globe and Humidity Index (BGHI), radiating thermal load (RTL) and enthalpy (H) were used to characterize the thermal environment. Artificial Neural Networks analyzed those indices as well as animal physiological data, using a single layer trained with the least mean square (LMS) algorithm. The results indicated that pre-milking and post-milking environments reached BGHI, RR, SST and MTBP values above thermal neutrality zone for buffaloes. In addition, limits of surface skin temperatures were mostly influenced by changing ambient conditions to the detriment of respiratory rates. It follows that buffaloes are sensitive to environmental changes and their skin temperatures are the best indicators of thermal comfort in relation to respiratory rate.

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Analytical curves are normally obtained from discrete data by least squares regression. The least squares regression of data involving significant error in both x and y values should not be implemented by ordinary least squares (OLS). In this work, the use of orthogonal distance regression (ODR) is discussed as an alternative approach in order to take into account the error in the x variable. Four examples are presented to illustrate deviation between the results from both regression methods. The examples studied show that, in some situations, ODR coefficients must substitute for those of OLS, and, in other situations, the difference is not significant.

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OBJECTIVE To evaluate the cross-cultural validity of the Demand-Control Questionnaire, comparing the original Swedish questionnaire with the Brazilian version. METHODS We compared data from 362 Swedish and 399 Brazilian health workers. Confirmatory and exploratory factor analyses were performed to test structural validity, using the robust weighted least squares mean and variance-adjusted (WLSMV) estimator. Construct validity, using hypotheses testing, was evaluated through the inspection of the mean score distribution of the scale dimensions according to sociodemographic and social support at work variables. RESULTS The confirmatory and exploratory factor analyses supported the instrument in three dimensions (for Swedish and Brazilians): psychological demands, skill discretion and decision authority. The best-fit model was achieved by including an error correlation between work fast and work intensely (psychological demands) and removing the item repetitive work (skill discretion). Hypotheses testing showed that workers with university degree had higher scores on skill discretion and decision authority and those with high levels of Social Support at Work had lower scores on psychological demands and higher scores on decision authority. CONCLUSIONS The results supported the equivalent dimensional structures across the two culturally different work contexts. Skill discretion and decision authority formed two distinct dimensions and the item repetitive work should be removed.

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Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

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Acetylation was performed to reduce the polarity of wood and increase its compatibility with polymer matrices for the production of composites. These reactions were performed first as a function of acetic acid and anhydride concentration in a mixture catalyzed by sulfuric acid. A concentration of 50%/50% (v/v) of acetic acid and anhydride was found to produced the highest conversion rate between the functional groups. After these reactions, the kinetics were investigated by varying times and temperatures using a 3² factorial design, and showed time was the most relevant parameter in determining the conversion of hydroxyl into carbonyl groups.

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This study developed and validated a method for moisture determination in artisanal Minas cheese, using near-infrared spectroscopy and partial-least-squares. The model robustness was assured by broad sample diversity, real conditions of routine analysis, variable selection, outlier detection and analytical validation. The model was built from 28.5-55.5% w/w, with a root-mean-square-error-of-prediction of 1.6%. After its adoption, the method stability was confirmed over a period of two years through the development of a control chart. Besides this specific method, the present study sought to provide an example multivariate metrological methodology with potential for application in several areas, including new aspects, such as more stringent evaluation of the linearity of multivariate methods.

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The objective of this study was to evaluate the relationships between the spectra in the Vis-NIR range and the soil P concentrations obtained from the PM and Prem extraction methods as well as the effects of these relationships on the construction of models predicting P concentration in Oxisols. Soil samples' spectra and their PM and Prem extraction solutions were determined for the Vis-NIR region between 400 and 2500 nm. Mineralogy and/or organic matter content act as primary attributes allowing correlation of these soil phosphorus fractions with the spectra, mainly at wavelengths between 450-550, 900-1100 nm, near 1400 nm and between 2200-2300 nm. However, the regression models generated were not suitable for quantitative phosphate analysis. Solubilization of organic matter and reactions during the PM extraction process hindered correlations between the spectra and these P soil fractions. For Prem,, the presence of Ca in the extractant and preferential adsorption by gibbsite and iron oxides, particularly goethite, obscured correlations with the spectra.

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A simple and sensitive spectrophotometric method is proposed for the simultaneous determination of protocatechuic acid and protocatechuic aldehyde. The method is based on the difference in the kinetic rates of the reactions of analytes with [Ag(NH3)2]+ in the presence of polyvinylpyrrolidone to produce silver nanoparticles. The data obtained were processed by chemometric methods using principal component analysis artificial neural network and partial least squares. Excellent linearity was obtained in the concentration ranges of 1.23-58.56 µg mL-1 and 0.08-30.39 µg mL-1 for PAC and PAH, respectively. The limits of detection for PAC and PAH were 0.039 and 0.025 µg mL-1, respectively.

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High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.

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n plant breeding programs that aim to obtain cultivars with nitrogen (N) use efficiency, the focus is on methods of selection and experimental procedures that present low cost, fast response, high repeatability, and can be applied to a large number of cultivars. Thus, the objectives of this study were to classify maize cultivars regarding their use efficiency and response to N in a breeding program, and to validate the methodology with contrasting doses of the nutrient. The experimental design was a randomized block with the treatments arranged in a split-plot scheme with three replicates and five N doses (0, 30, 60, 120 and 200 kg ha-1) in the plots, and six cultivars in subplots. We compared a method examining the efficiency and response (ER) with two contrasting doses of N. After that, the analysis of variance, mean comparison and regression analysis were performed. In conclusion, the method of the use efficiency and response based on two N levels classifies the cultivars in the same way as the regression analysis, and it is appropriate in plant breeding routine. Thus, it is necessary to identify the levels of N required to discriminate maize cultivars in conditions of low and high N availability in plant breeding programs that aim to obtain efficient and responsive cultivars. Moreover, the analysis of the interaction genotype x environment at experiments with contrasting doses is always required, even when the interaction is not significant.

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ABSTRACTAiming to compare three different methods for the determination of organic carbon (OC) in the soil and fractions of humic substances, seventeen Brazilian soil samples of different classes and textures were evaluated. Amounts of OC in the soil samples and the humic fractions were measured by the dichromate-oxidation method, with and without external heating in a digestion block at 130 °C for 30 min; by the loss-on-ignition method at 450 °C during 5 h and at 600 °C during 6 h; and by the dry combustion method. Dry combustion was used as reference in order to measure the efficiency of the other methods. Soil OC measured by the dichromate-oxidation method with external heating had the highest efficiency and the best results comparing to the reference method. When external heating was not used, the mean recovery efficiency dropped to 71%. The amount of OC was overestimated by the loss-on-ignition methods. Regression equations obtained between total OC contents of the reference method and those of the other methods showed relatively good adjustment, but all intercepts were different from zero (p < 0.01), which suggests that more accuracy can be obtained using not one single correction factor, but considering also the intercept. The Walkley-Black method underestimated the OC contents of the humic fractions, which was associated with the partial oxidation of the humin fraction. Better results were obtained when external heating was used. For the organic matter fractions, the OC in the humic and fulvic acid fractions can be determined without external heating if the reference method is not available, but the humin fraction requires the external heating.

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ABSTRACT Soils of tropical regions are more weathered and in need of conservation managements to maintain and improve the quality of its components. The objective of this study was to evaluate the availability of K, the organic matter content and the stock of total carbon of an Argisol after vinasse application and manual and mechanized harvesting of burnt and raw sugarcane, in western São Paulo.The data collection was done in the 2012/2013 harvest, in a bioenergy company in Presidente Prudente/SP. The research was arranged out following a split-plot scheme in a 5x5 factorial design, characterized by four management systems: without vinasse application and harvest without burning; with vinasse application and harvest without burning; with vinasse application and harvest after burning; without vinasse application and harvest after burning; plus native forest, and five soil sampling depths (0-10 10-20, 20-30, 30-40, 40-50 cm), with four replications. In each treatment, the K content in the soil and accumulated in the remaining dry biomass in the area, the levels of organic matter, organic carbon and soil carbon stock were determined. The mean values were compared by Tukey test. The vinasse application associated with the harvest without burning increased the K content in soil layers up to 40 cm deep. The managements without vinasse application and manual harvest after burning, and without vinasse application with mechanical harvesting without burning did not increase the levels of organic matter, organic carbon and stock of total soil organic carbon, while the vinasse application and harvest after burning and without burning increased the levels of these attributes in the depth of 0-10 cm.

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Between November 2001 and December 2002, 600 dog fecal samples were collected in main squares and public parks of 13 cities in Chile, from the extreme north to the extreme south of the country. The samples were processed in the laboratory by centrifugal sedimentation and the Harada-Mori methods. T. canis eggs were found in 12 cities. Detection rates ranged from 1.9 to 12.5% with an average of 5.2%. Seven percent of the samples had eggs and 9.5% had rhabditoid and/or filariform larvae of Ancylostomatidae. Strongyloides stercoralis were not found. Squares and public parks in Chile pose a potential risk of exposure to visceral, ocular, and/or cutaneous larva migrans syndromes.