34 resultados para COMPARATIVE CALIBRATION MODELS
em Scielo Saúde Pública - SP
Resumo:
The aim of this present work was to provide a more fast, simple and less expensive to analyze sulfur content in diesel samples than by the standard methods currently used. Thus, samples of diesel fuel with sulfur concentrations varying from 400 and 2500 mgkg-1 were analyzed by two methodologies: X-ray fluorescence, according to ASTM D4294 and by Fourier transform infrared spectrometry (FTIR). The spectral data obtained from FTIR were used to build multivariate calibration models by partial least squares (PLS). Four models were built in three different ways: 1) a model using the full spectra (665 to 4000 cm-1), 2) two models using some specific spectrum regions and 3) a model with variable selected by classic method of variable selection stepwise. The model obtained by variable selection stepwise and the model built with region spectra between 665 and 856 cm-1 and 1145 and 2717 cm-1 showed better results in the determination of sulfur content.
Resumo:
The objective of this work was to accomplish the simultaneous determination of some chemical elements by Energy Dispersive X-ray Fluorescence (EDXRF) Spectroscopy through multivariate calibration in several sample types. The multivariate calibration models were: Back Propagation neural network, Levemberg-Marquardt neural network and Radial Basis Function neural network, fuzzy modeling and Partial Least Squares Regression. The samples were soil standards, plant standards, and mixtures of lead and sulfur salts diluted in silica. The smallest Root Mean Square errors (RMS) were obtained with Back Propagation neural networks, which solved main EDXRF problems in a better way.
Resumo:
A method is presented for the choice of spectral regions when absorption measurements are coupled to chemometric tools to perform quantitative analyses. The method is based on the spectral distribution of the relative standard deviation of concentration (s c/c). It has been applied to the development of PLS-FTNIR calibration models for the determination of density and MON of gasoline, and ethanol content and density of ethanol fuel. The new method was also compared with the correlation (R²) method and has proved to generate PLS calibration models that present better accuracy and precision than those based on R².
Resumo:
The application of analytical procedures based on multivariate calibration models has been limited in several areas due to requirements of validation and certification of the model. Procedures for validation are presented based on the determination of figures of merit, such as precision (mean, repeatability, intermediate), accuracy, sensitivity, analytical sensitivity, selectivity, signal-to-noise ratio and confidence intervals for PLS models. An example is discussed of a model for polymorphic purity control of carbamazepine by NIR diffuse reflectance spectroscopy. The results show that multivariate calibration models can be validated to fulfill the requirements imposed by industry and standardization agencies.
Resumo:
In this work, a partial least squares regression routine was used to develop a multivariate calibration model to predict the chemical oxygen demand (COD) in substrates of environmental relevance (paper effluents and landfill leachates) from UV-Vis spectral data. The calibration models permit the fast determination of the COD with typical relative errors lower by 10% with respect to the conventional methodology.
Resumo:
Calibration transfer has received considerable attention in the recent literature. Several standardization methods have been proposed for transferring calibration models between equipments. The goal of this paper is to present a general revision of calibration transfer techniques. Basic concepts will be reviewed, as well as the main advantages and drawbacks of each technique. A case study based on a set of 80 NIR spectra of maize samples recorded on two different instruments is used to illustrate the main calibration transfer techniques (direct standardization, piecewise direct standardization, orthogonal signal correction and robust variable selection).
Resumo:
In this work the antioxidant capacity of red wine samples was characterized by conventional spectroscopic and chromatographic methodologies, regarding chemical parameters like color, total polyphenolic and resveratrol content, and antioxidant activity. Additionally, multivariate calibration models were developed to predict the antioxidant activity, using partial least square regression and the spectral data registered between 400 and 800 nm. Even when a close correlation between the evaluated parameters has been expected many inconsistencies were observed, probably on account of the low selectivity of the conventional methodologies. Models developed from mean-centered spectra and using 4 latent variables allowed high prevision capacity of the antioxidant activity, permitting relative errors lower than 3%.
Resumo:
The aim of this study was to calibrate the CENTURY, APSIM and NDICEA simulation models for estimating decomposition and N mineralization rates of plant organic materials (Arachis pintoi, Calopogonium mucunoides, Stizolobium aterrimum, Stylosanthes guyanensis) for 360 days in the Atlantic rainforest bioma of Brazil. The models´ default settings overestimated the decomposition and N-mineralization of plant residues, underlining the fact that the models must be calibrated for use under tropical conditions. For example, the APSIM model simulated the decomposition of the Stizolobium aterrimum and Calopogonium mucunoides residues with an error rate of 37.62 and 48.23 %, respectively, by comparison with the observed data, and was the least accurate model in the absence of calibration. At the default settings, the NDICEA model produced an error rate of 10.46 and 14.46 % and the CENTURY model, 21.42 and 31.84 %, respectively, for Stizolobium aterrimum and Calopogonium mucunoides residue decomposition. After calibration, the models showed a high level of accuracy in estimating decomposition and N- mineralization, with an error rate of less than 20 %. The calibrated NDICEA model showed the highest level of accuracy, followed by the APSIM and CENTURY. All models performed poorly in the first few months of decomposition and N-mineralization, indicating the need of an additional parameter for initial microorganism growth on the residues that would take the effect of leaching due to rainfall into account.
Resumo:
A close relationship exists between calcium concentration in the central nervous system and nociceptive processing. Aminoglycoside antibiotics and magnesium interact with N- and P/Q-type voltage-operated calcium channels. In the present study we compare the antinociceptive potency of intrathecal administration of aminoglycoside antibiotics and magnesium chloride in the tail-flick test and on incisional pain in rats, taken as models of phasic and persistent post-surgical pain, respectively. The order of potency in the tail-flick test was gentamicin (ED50 = 3.34 µg; confidence limits 2.65 and 4.2) > streptomycin (5.68 µg; 3.76 and 8.57) = neomycin (9.22 µg; 6.98 and 12.17) > magnesium (19.49 µg; 11.46 and 33.13). The order of potency to reduce incisional pain was gentamicin (ED50 = 2.06 µg; confidence limits 1.46 and 2.9) > streptomycin (47.86 µg; 26.3 and 87.1) = neomycin (83.17 µg; 51.6 and 133.9). The dose-response curves for each test did not deviate significantly from parallelism. We conclude that neomycin and streptomycin are more potent against phasic pain than against persistent pain, whereas gentamicin is equipotent against both types of pain. Magnesium was less potent than the antibiotics and effective in the tail-flick test only.
Resumo:
ABSTRACT Earlier studies of cross-national differences in consumer behavior in different consumption sectors have verified that cultural differences have a strong influence on consumers. Despite the importance of cross-national analysis, no studies in the literature examine the moderating effects of nationality on the construction of behavioral intentions and their antecedents among cruise line passengers. This study investigates the moderating effects of nationality on the relationships between perceived value, satisfaction, trust and behavioral intentions among Spanish and (U.S.) American passengers of cruise lines that use Barcelona as home port and port-of-call. A theoretical model was tested with a total of 968 surveys. Structural equation models (SEMs) were used, by means of a multigroup analysis. Results of this study indicated that Spaniards showed stronger relationships between trust and behavioral intentions, and between emotional value and satisfaction. Americans presented stronger relationships between service quality and satisfaction, and between service quality and behavioral intentions.
Resumo:
In this study, we concentrate on modelling gross primary productivity using two simple approaches to simulate canopy photosynthesis: "big leaf" and "sun/shade" models. Two approaches for calibration are used: scaling up of canopy photosynthetic parameters from the leaf to the canopy level and fitting canopy biochemistry to eddy covariance fluxes. Validation of the models is achieved by using eddy covariance data from the LBA site C14. Comparing the performance of both models we conclude that numerically (in terms of goodness of fit) and qualitatively, (in terms of residual response to different environmental variables) sun/shade does a better job. Compared to the sun/shade model, the big leaf model shows a lower goodness of fit and fails to respond to variations in the diffuse fraction, also having skewed responses to temperature and VPD. The separate treatment of sun and shade leaves in combination with the separation of the incoming light into direct beam and diffuse make sun/shade a strong modelling tool that catches more of the observed variability in canopy fluxes as measured by eddy covariance. In conclusion, the sun/shade approach is a relatively simple and effective tool for modelling photosynthetic carbon uptake that could be easily included in many terrestrial carbon models.
Resumo:
A variety of host immunogenetic factors appear to influence both an individual's susceptibility to infection with Mycobacterium leprae and the pathologic course of the disease. Animal models can contribute to a better understanding of the role of immunogenetics in leprosy through comparative studies helping to confirm the significance of various identified traits and in deciphering the underlying mechanisms that may be involved in expression of different disease related phenotypes. Genetically engineered mice, with specific immune or biochemical pathway defects, are particularly useful for investigating granuloma formation and resistance to infection and are shedding new light on borderline areas of the leprosy spectrum which are clinically unstable and have a tendency toward immunological complications. Though armadillos are less developed in this regard, these animals are the only other natural hosts of M. leprae and they present a unique opportunity for comparative study of genetic markers and mechanisms associable with disease susceptibility or resistance, especially the neurological aspects of leprosy. In this paper, we review the recent contributions of genetically engineered mice and armadillos toward our understanding of the immunogenetics of leprosy.
Resumo:
One of the problems that slows the development of off-line programming is the low static and dynamic positioning accuracy of robots. Robot calibration improves the positioning accuracy and can also be used as a diagnostic tool in robot production and maintenance. A large number of robot measurement systems are now available commercially. Yet, there is a dearth of systems that are portable, accurate and low cost. In this work a measurement system that can fill this gap in local calibration is presented. The measurement system consists of a single CCD camera mounted on the robot tool flange with a wide angle lens, and uses space resection models to measure the end-effector pose relative to a world coordinate system, considering radial distortions. Scale factors and image center are obtained with innovative techniques, making use of a multiview approach. The target plate consists of a grid of white dots impressed on a black photographic paper, and mounted on the sides of a 90-degree angle plate. Results show that the achieved average accuracy varies from 0.2mm to 0.4mm, at distances from the target from 600mm to 1000mm respectively, with different camera orientations.
Resumo:
The main objective of the paper is to assess the impact of fiscal variables on private investment comparing some Latin-American economies to other advanced ones. For such purposes, the authors carry out an econometric analysis for the period 1990-2008. They make use of two dynamic panel models in which they group countries with similar characteristics and development levels. In one of them, they include Mexico, Brazil, Chile, Colombia and Uruguay; whereas in the second one the countries accounted for are the U.S., Canada, Spain, Korea, Ireland and Japan. They specify in both models an investment function using as arguments a wide range of variables, including those related with fiscal policy. From their results the authors infer that governments can, with higher spending, boost up the economy even when they finance spending with higher taxes. In Latin America, where income concentration is enormous, a proposal to boost up the economy through higher government expenditure financed with a progressive income tax, is even more justified.