Transferência de calibração em métodos multivariados

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).

Least squares regression with errors in both variables: case studies

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.

APPLICATION OF PARAFAC AND OPLS-DA ANALYSES ON HPLC FINGERPRINTS FOR THE CHARACTERIZATION OF Hibiscus sabdariffaCALYXES

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.

Bound state solutions of schrödinger equation for a more general exponential screened coulomb potential via Nikiforov-Uvarov method

The arbitrary angular momentum solutions of the Schrödinger equation for a diatomic molecule with the general exponential screened coulomb potential of the form V(r) = (- a / r){1+ (1+ b )e-2b } has been presented. The energy eigenvalues and the corresponding eigenfunctions are calculated analytically by the use of Nikiforov-Uvarov (NU) method which is related to the solutions in terms of Jacobi polynomials. The bounded state eigenvalues are calculated numerically for the 1s state of N2 CO and NO

A temperature predicting model for manufacturing processes requiring coiling

A model for predicting temperature evolution for automatic controling systems in manufacturing processes requiring the coiling of bars in the transfer table is presented. Although the method is of a general nature, the presentation in this work refers to the manufacturing of steel plates in hot rolling mills. The predicting strategy is based on a mathematical model of the evolution of temperature in a coiling and uncoiling bar and is presented in the form of a parabolic partial differential equation for a shape changing domain. The mathematical model is solved numerically by a space discretization via geometrically adaptive finite elements which accomodate the change in shape of the domain, using a computationally novel treatment of the resulting thermal contact problem due to coiling. Time is discretized according to a Crank-Nicolson scheme. Since the actual physical process takes less time than the time required by the process controlling computer to solve the full mathematical model, a special predictive device was developed, in the form of a set of least squares polynomials, based on the off-line numerical solution of the mathematical model.

On the numerical simulation of machining processes

Numerical simulation of machining processes can be traced back to the early seventies when finite element models for continuous chip formation were proposed. The advent of fast computers and development of new techniques to model large plastic deformations have favoured machining simulation. Relevant aspects of finite element simulation of machining processes are discussed in this paper, such as solution methods, material models, thermo-mechanical coupling, friction models, chip separation and breakage strategies and meshing/re-meshing strategies.

Comparison of model-based above ground biomass predictions from LiDAR

In order to reduce greenhouse emissions from forest degradation and deforestation the international programme REDD (Reducing Emissions from Deforestation and forest Degradation) was established in 2005 by the United Nations Framework Convention on Climate Change (UNFCCC). This programme is aimed to financially reward to developing countries for any emissions reductions. Under this programm the project of setting up the payment system in Nepal was established. This project is aimed to engage local communities in forest monitoring. The major objective of this thesis is to compare and verify data obtained from di erect sources - remotely sensed data, namely LiDAR and field sample measurements made by two groups of researchers using two regression models - Sparse Bayesian Regression and Bayesian Regression with Orthogonal Variables.

Inhibitory effects in the detection of 1 cpd jo targets superimposed to angular frequency stimuli or sinewave gratings

Independence among channels processing different aspects of spatial information, including orthogonal stimuli, has been generally assumed in the literature. We tested independence between the processing of jo targets and the processing of either vertical sinusoidal gratings or angular frequency stimuli with suprathreshold summation. We found the detection of a jo target at 1 cpd to be affected in an inhibitory fashion by either background angular frequencies in the range of 3-96 cycles or sinewave gratings in the range of 0.8-3.0 cpd. These results demonstrate interactions both among orthogonal stimuli and among channels processing vertical sinewave gratings and jo target stimuli. Our discussion focuses on the hypothesis of frequency decomposition in polar coordinates

Factor structure of Bech's version of the Brief Psychiatric Rating Scale in Brazilian patients

The objective of the present study was to evaluate the factor structure of Bech's version of the Brief Psychiatric Rating Scale (BPRS), translated into Portuguese. The BPRS was administered to a heterogeneous group of psychiatric inpatients (N = 98) and outpatients (N = 62) in a University Hospital. Each patient was evaluated from one to eight times. The interval between consecutive interviews was one week for the inpatients and one month for the outpatients. The results were submitted to factorial analysis. The internal consistency of the total scale and of each factor was also estimated. Factorial analysis followed by normalized orthogonal rotation (Varimax) yielded four factors: Withdrawal-Retardation, Thinking Disorder, Anxious-Depression and Activation. Internal consistency measured by Cronbach's alpha coefficient ranged from 0.766 to 0.879. The data show that the factor structure of the present instrument is similar to that of the American version of the BPRS which contains 18 items, except for the absence of the fifth factor of the latter scale, Hostile-Suspiciousness.

Measuring higher order optical aberrations of the human eye: techniques and applications

In the present paper we discuss the development of "wave-front", an instrument for determining the lower and higher optical aberrations of the human eye. We also discuss the advantages that such instrumentation and techniques might bring to the ophthalmology professional of the 21st century. By shining a small light spot on the retina of subjects and observing the light that is reflected back from within the eye, we are able to quantitatively determine the amount of lower order aberrations (astigmatism, myopia, hyperopia) and higher order aberrations (coma, spherical aberration, etc.). We have measured artificial eyes with calibrated ametropia ranging from +5 to -5 D, with and without 2 D astigmatism with axis at 45º and 90º. We used a device known as the Hartmann-Shack (HS) sensor, originally developed for measuring the optical aberrations of optical instruments and general refracting surfaces in astronomical telescopes. The HS sensor sends information to a computer software for decomposition of wave-front aberrations into a set of Zernike polynomials. These polynomials have special mathematical properties and are more suitable in this case than the traditional Seidel polynomials. We have demonstrated that this technique is more precise than conventional autorefraction, with a root mean square error (RMSE) of less than 0.1 µm for a 4-mm diameter pupil. In terms of dioptric power this represents an RMSE error of less than 0.04 D and 5º for the axis. This precision is sufficient for customized corneal ablations, among other applications.

Serum metabolic profiling of human gastric cancer based on gas chromatography/mass spectrometry

Research on molecular mechanisms of carcinogenesis plays an important role in diagnosing and treating gastric cancer. Metabolic profiling may offer the opportunity to understand the molecular mechanism of carcinogenesis and help to non-invasively identify the potential biomarkers for the early diagnosis of human gastric cancer. The aims of this study were to explore the underlying metabolic mechanisms of gastric cancer and to identify biomarkers associated with morbidity. Gas chromatography/mass spectrometry (GC/MS) was used to analyze the serum metabolites of 30 Chinese gastric cancer patients and 30 healthy controls. Diagnostic models for gastric cancer were constructed using orthogonal partial least squares discriminant analysis (OPLS-DA). Acquired metabolomic data were analyzed by the nonparametric Wilcoxon test to find serum metabolic biomarkers for gastric cancer. The OPLS-DA model showed adequate discrimination between cancer and non-cancer cohorts while the model failed to discriminate different pathological stages (I-IV) of gastric cancer patients. A total of 44 endogenous metabolites such as amino acids, organic acids, carbohydrates, fatty acids, and steroids were detected, of which 18 differential metabolites were identified with significant differences. A total of 13 variables were obtained for their greatest contribution in the discriminating OPLS-DA model [variable importance in the projection (VIP) value >1.0], among which 11 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test. These metabolites potentially revealed perturbations of glycolysis and of amino acid, fatty acid, cholesterol, and nucleotide metabolism of gastric cancer patients. These results suggest that gastric cancer serum metabolic profiling has great potential in detecting this disease and helping to understand its metabolic mechanisms.

Form, size and volumetric expansion of Adzuki beans (Vigna angularis) during soaking

This study analyzed the variation in shape and size of Adzuki beans during soaking at different temperatures. In addition, different mathematical models were fitted to the experimental values of volumetric expansion, selecting the best one. Grains of Adzuki beans (Vigna angularis) with moisture content of approximately 0.25 (decimal d.b.) were manually harvested; they were, then, dried to 0.128 (decimal d.b.). The beans were subjected to soaking in distilled water at the temperatures 18 ± 1, 27 ± 1, 36 ± 1, and 45 ± 1 °C, in five repetitions. Recipients containing 80 mL of distilled water and 20 g of beans for each sample were used. The samples were periodically weighed in order to determine the water absorption. After that, the samples were removed from the recipients and placed on filter papers for two minutes to drain the surface water. Water absorption continued until the beans reached the saturation moisture content. It was concluded that, the form of the Adzuki beans was altered regularly, the orthogonal axes expanded differentially in the radial and axial directions, and that the linear model appropriately described the volumetric expansion of the Adzuki beans, among the series of models analyzed for the temperatures 18, 27, 36 and 45 °C.

Extraction optimization of antioxidant polysaccharides from leaves of Gynura bicolor (Roxb. & Willd.) DC

Orthogonal design was employed to study the effect of extraction time, temperature and liquid-to-solid ratio on the production of antioxidant polysaccharides from leaves of Gynura bicolor (PLG). Analysis of variance was performed on the data obtained. The most relevant variable was extraction time. A liquid-solid ratio of 30:1 (v/w), a temperature of 80 °C and an extraction time of 3 h were found to be optimal for PLG. The optimal extraction yield of 4.9% was obtained through additional verification test. Hydroxyl radical-scavenging activity, reducing power and ferrous ion chelating ability of PLG were determined. PLG possess concentration-dependent antioxidant potency and IC50 of PLG was 4.67, 0.24 and 4.31 mg/mL for hydroxyl radical-scavenging and ferric ion chelating abilities as well as reducing power, respectively. The results suggest that G. bicolor polysaccharides could be potential source of natural antioxidant and be contributor to the health benefits of G. bicolor.

Phonon spectra and temperature variation of thermodynamic properties of fcc metals via Finnis-Sinclair type many body potentials: Sutton-Chen and improved Sutton-Chen models

Volume(density)-independent pair-potentials cannot describe metallic cohesion adequately as the presence of the free electron gas renders the total energy strongly dependent on the electron density. The embedded atom method (EAM) addresses this issue by replacing part of the total energy with an explicitly density-dependent term called the embedding function. Finnis and Sinclair proposed a model where the embedding function is taken to be proportional to the square root of the electron density. Models of this type are known as Finnis-Sinclair many body potentials. In this work we study a particular parametrization of the Finnis-Sinclair type potential, called the "Sutton-Chen" model, and a later version, called the "Quantum Sutton-Chen" model, to study the phonon spectra and the temperature variation thermodynamic properties of fcc metals. Both models give poor results for thermal expansion, which can be traced to rapid softening of transverse phonon frequencies with increasing lattice parameter. We identify the power law decay of the electron density with distance assumed by the model as the main cause of this behaviour and show that an exponentially decaying form of charge density improves the results significantly. Results for Sutton-Chen and our improved version of Sutton-Chen models are compared for four fcc metals: Cu, Ag, Au and Pt. The calculated properties are the phonon spectra, thermal expansion coefficient, isobaric heat capacity, adiabatic and isothermal bulk moduli, atomic root-mean-square displacement and Gr\"{u}neisen parameter. For the sake of comparison we have also considered two other models where the distance-dependence of the charge density is an exponential multiplied by polynomials. None of these models exhibits the instability against thermal expansion (premature melting) as shown by the Sutton-Chen model. We also present results obtained via pure pair potential models, in order to identify advantages and disadvantages of methods used to obtain the parameters of these potentials.

An Eigenfunction Approach for Volatility Modeling.

In this paper, we introduce a new approach for volatility modeling in discrete and continuous time. We follow the stochastic volatility literature by assuming that the variance is a function of a state variable. However, instead of assuming that the loading function is ad hoc (e.g., exponential or affine), we assume that it is a linear combination of the eigenfunctions of the conditional expectation (resp. infinitesimal generator) operator associated to the state variable in discrete (resp. continuous) time. Special examples are the popular log-normal and square-root models where the eigenfunctions are the Hermite and Laguerre polynomials respectively. The eigenfunction approach has at least six advantages: i) it is general since any square integrable function may be written as a linear combination of the eigenfunctions; ii) the orthogonality of the eigenfunctions leads to the traditional interpretations of the linear principal components analysis; iii) the implied dynamics of the variance and squared return processes are ARMA and, hence, simple for forecasting and inference purposes; (iv) more importantly, this generates fat tails for the variance and returns processes; v) in contrast to popular models, the variance of the variance is a flexible function of the variance; vi) these models are closed under temporal aggregation.