Aplicação de técnicas multivariadas e inteligência artificial na análise de espectros de infravermelho para determinação de matéria orgânica em amostras de solos

In this paper studies based on Multilayer Perception Artificial Neural Network and Least Square Support Vector Machine (LS-SVM) techniques are applied to determine of the concentration of Soil Organic Matter (SOM). Performances of the techniques are compared. SOM concentrations and spectral data from Mid-Infrared are used as input parameters for both techniques. Multivariate regressions were performed for a set of 1117 spectra of soil samples, with concentrations ranging from 2 to 400 g kg-1. The LS-SVM resulted in a Root Mean Square Error of Prediction of 3.26 g kg-1 that is comparable to the deviation of the Walkley-Black method (2.80 g kg-1).

Comparison between hydrographically conditioned digital elevation models in the morphometric charaterization of watersheds

The aim of this study was to compare the hydrographically conditioned digital elevation models (HCDEMs) generated from data of VNIR (Visible Near Infrared) sensor of ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), of SRTM (Shuttle Radar Topography Mission) and topographical maps from IBGE in a scale of 1:50,000, processed in the Geographical Information System (GIS), aiming the morphometric characterization of watersheds. It was taken as basis the Sub-basin of São Bartolomeu River, obtaining morphometric characteristics from HCDEMs. Root Mean Square Error (RMSE) and cross validation were the statistics indexes used to evaluate the quality of HCDEMs. The percentage differences in the morphometric parameters obtained from these three different data sets were less than 10%, except for the mean slope (21%). In general, it was observed a good agreement between HCDEMs generated from remote sensing data and IBGE maps. The result of HCDEM ASTER was slightly higher than that from HCDEM SRTM. The HCDEM ASTER was more accurate than the HCDEM SRTM in basins with high altitudes and rugged terrain, by presenting frequency altimetry nearest to HCDEM IBGE, considered standard in this study.

Estimation of aircraft aerodynamic derivatives using Extended Kalman Filter

Design of flight control laws, verification of performance predictions, and the implementation of flight simulations are tasks that require a mathematical model of the aircraft dynamics. The dynamical models are characterized by coefficients (aerodynamic derivatives) whose values must be determined from flight tests. This work outlines the use of the Extended Kalman Filter (EKF) in obtaining the aerodynamic derivatives of an aircraft. The EKF shows several advantages over the more traditional least-square method (LS). Among these the most important are: there are no restrictions on linearity or in the form which the parameters appears in the mathematical model describing the system, and it is not required that these parameters be time invariant. The EKF uses the statistical properties of the process and the observation noise, to produce estimates based on the mean square error of the estimates themselves. Differently, the LS minimizes a cost function based on the plant output behavior. Results for the estimation of some longitudinal aerodynamic derivatives from simulated data are presented.

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.

Dimensionality of the premenstrual syndrome: confirmatory factor analysis of premenstrual dysphoric symptoms among college students

Premenstrual syndrome and premenstrual dysphoric disorder (PMDD) seem to form a severity continuum with no clear-cut boundary. However, since the American Psychiatric Association proposed the research criteria for PMDD in 1994, there has been no agreement about the symptomatic constellation that constitutes this syndrome. The objective of the present study was to establish the core latent structure of PMDD symptoms in a non-clinical sample. Data concerning PMDD symptoms were obtained from 632 regularly menstruating college students (mean age 24.4 years, SD 5.9, range 17 to 49). For the first random half (N = 316), we performed principal component analysis (PCA) and for the remaining half (N = 316), we tested three theory-derived competing models of PMDD by confirmatory factor analysis. PCA allowed us to extract two correlated factors, i.e., dysphoric-somatic and behavioral-impairment factors. The two-dimensional latent model derived from PCA showed the best overall fit among three models tested by confirmatory factor analysis (c²53 = 64.39, P = 0.13; goodness-of-fit indices = 0.96; adjusted goodness-of-fit indices = 0.95; root mean square residual = 0.05; root mean square error of approximation = 0.03; 90%CI = 0.00 to 0.05; Akaike's information criterion = -41.61). The items "out of control" and "physical symptoms" loaded conspicuously on the first factor and "interpersonal impairment" loaded higher on the second factor. The construct validity for PMDD was accounted for by two highly correlated dimensions. These results support the argument for focusing on the core psychopathological dimension of PMDD in future studies.

Manipulating Greek musical modes and tempo affects perceived musical emotion in musicians and nonmusicians

The combined influence of tempo and mode on emotional responses to music was studied by crossing 7 changes in mode with 3 changes in tempo. Twenty-four musicians aged 19 to 25 years (12 males and 12 females) and 24 nonmusicians aged 17 to 25 years (12 males and 12 females) were required to perform two tasks: 1) listening to different musical excerpts, and 2) associating an emotion to them such as happiness, serenity, fear, anger, or sadness. ANOVA showed that increasing the tempo strongly affected the arousal (F(2,116) = 268.62, mean square error (MSE) = 0.6676, P < 0.001) and, to a lesser extent, the valence of emotional responses (F(6,348) = 8.71, MSE = 0.6196, P < 0.001). Changes in modes modulated the affective valence of the perceived emotions (F(6,348) = 4.24, MSE = 0.6764, P < 0.001). Some interactive effects were found between tempo and mode (F (1,58) = 115.6, MSE = 0.6428, P < 0.001), but, in most cases, the two parameters had additive effects. This finding demonstrates that small changes in the pitch structures of modes modulate the emotions associated with the pieces, confirming the cognitive foundation of emotional responses to music.

Drying kinetics of potato pulp waste

Potato pulp waste (PPW) drying was investigated under different experimental conditions (temperatures from 50 to 70 °C and air flow from 0.06 to 0.092 m³ m- 2 s- 1) as a possible way to recover the waste generated by potato chip industries and to select the best-fit model to the experimental results of PPW drying. As a criterion to evaluate the fitting of mathematical models, a method based on the sum of the scores assigned to the four evaluated statistical parameters was used: regression coefficient (R²), relative mean error P (%), root mean square error (RMSE), and reduced chi-square (χ²). The results revealed that temperature and air velocity are important parameters to reduce PPW drying time. The models Midilli and Diffusion had the lowest sum values, i.e., with the best fit to the drying data, satisfactorily representing the drying kinetics of PPW.

Analysis of experiments in square lattice with emphasis on variance components. i. Individual analysis

This paper focused on four alternatives of analysis of experiments in square lattice as far as the estimation of variance components and some genetic parameters are concerned: 1) intra-block analysis with adjusted treatment and blocks within unadjusted repetitions; 2) lattice analysis as complete randomized blocks; 3) intrablock analysis with unadjusted treatment and blocks within adjusted repetitions; 4) lattice analysis as complete randomized blocks, by utilizing the adjusted means of treatments, obtained from the analysis with recovery of interblock information, having as mean square of the error the mean effective variance of this same analysis with recovery of inter-block information. For the four alternatives of analysis, the estimators and estimates were obtained for the variance components and heritability coefficients. The classification of material was also studied. The present study suggests that for each experiment and depending of the objectives of the analysis, one should observe which alternative of analysis is preferable, mainly in cases where a negative estimate is obtained for the variance component due to effects of blocks within adjusted repetitions.

Heart Rate and Systolic Blood Pressure Variability on Recently Diagnosed Diabetics

Background:Diabetes affects approximately 250 million people in the world. Cardiovascular autonomic neuropathy is a common complication of diabetes that leads to severe postural hypotension, exercise intolerance, and increased incidence of silent myocardial infarction.Objective:To determine the variability of heart rate (HR) and systolic blood pressure (SBP) in recently diagnosed diabetic patients.Methods:The study included 30 patients with a diagnosis of type 2 diabetes of less than 2 years and 30 healthy controls. We used a Finapres® device to measure during five minutes beat-to-beat HR and blood pressure in three experimental conditions: supine position, standing position, and rhythmic breathing at 0.1 Hz. The results were analyzed in the time and frequency domains.Results:In the HR analysis, statistically significant differences were found in the time domain, specifically on short-term values such as standard deviation of NN intervals (SDNN), root mean square of successive differences (RMSSD), and number of pairs of successive NNs that differ by more than 50 ms (pNN50). In the BP analysis, there were no significant differences, but there was a sympathetic dominance in all three conditions. The baroreflex sensitivity (BRS) decreased in patients with early diabetes compared with healthy subjects during the standing maneuver.Conclusions:There is a decrease in HR variability in patients with early type 2 diabetes. No changes were observed in the BP analysis in the supine position, but there were changes in BRS with the standing maneuver, probably due to sympathetic hyperactivity.

Comparação entre métodos compostos no cálculo de afinidades por próton e elétron em sistemas moleculares

The CBS-4M, CBS-QB3, G2, G2(MP2), G3 and G3(MP2) model chemistry methods have been used to calculate proton and electron affinities for a set of molecular and atomic systems. Agreement with the experimental value for these electronic properties is quite good considering the uncertainty in the experimental data. A comparison among the six theories using statistical analysis (average value, standard deviation and root-mean-square) showed a better performance of CBS-QB3 to obtain these properties.

Avaliação do perfil de dissolução de medicamentos utilizando-se espectroscopia eletrônica multivariada

In this work the evaluation of the dissolution profile of captopril-hydrochlorothiazide and zidovudine-lamivudine associations were carried out by multivariate spectroscopic method. The models were developed by partial least square regression from 20 synthetic mixtures using mean-centered spectral data. The external validation was accomplished with 5 synthetic mixtures shown mean prevision error of about 1%. Good agreement was observed in the analyses of commercial drugs (content uniformity and dissolution profile), considering the results obtained by the standard chromatographic method, with prevision error lower than 10%.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Description of epidemics of coffee rust with neural networks

The objective of this paper was to evaluate the potential of neural networks (NN) as an alternative method to the basic epidemiological approach to describe epidemics of coffee rust. The NN was developed from the intensities of coffee (Coffea arabica) rust along with the climatic variables collected in Lavras-MG between 13 February 1998 and 20 April 2001. The NN was built with climatic variables that were either selected in a stepwise regression analysis or by the Braincel® system, software for NN building. Fifty-nine networks and 26 regression models were tested. The best models were selected based on small values of the mean square deviation (MSD) and of the mean prediction error (MPE). For the regression models, the highest coefficients of determination (R²) were used. The best model developed with neural networks had an MSD of 4.36 and an MPE of 2.43%. This model used the variables of minimum temperature, production, relative humidity of the air, and irradiance 30 days before the evaluation of disease. The best regression model was developed from 29 selected climatic variables in the network. The summary statistics for this model were: MPE=6.58%, MSE=4.36, and R²=0.80. The elaborated neural networks from a time series also were evaluated to describe the epidemic. The incidence of coffee rust at four previous fortnights resulted in a model with MPE=4.72% and an MSD=3.95.

Estimation of Fetal Weight during Labor: Still a Challenge

Objective To evaluate the accuracy of fetal weight prediction by ultrasonography labor employing a formula including the linear measurements of femur length (FL) and mid-thigh soft-tissue thickness (STT). Methods We conducted a prospective study involving singleton uncomplicated term pregnancies within 48 hours of delivery. Only pregnancies with a cephalic fetus admitted in the labor ward for elective cesarean section, induction of labor or spontaneous labor were included. We excluded all non-Caucasian women, the ones previously diagnosed with gestational diabetes and the ones with evidence of ruptured membranes. Fetal weight estimates were calculated using a previously proposed formula [estimated fetal weight = [1] 1687.47 + (54.1 x FL) + (76.68 x STT). The relationship between actual birth weight and estimated fetal weight was analyzed using Pearson's correlation. The formula's performance was assessed by calculating the signed and absolute errors. Mean weight difference and signed percentage error were calculated for birth weight divided into three subgroups: < 3000 g; 3000-4000g; and > 4000 g. Results We included for analysis 145 cases and found a significant, yet low, linear relationship between birth weight and estimated fetal weight (p < 0.001; R2 = 0.197) with an absolute mean error of 10.6%. The lowest mean percentage error (0.3%) corresponded to the subgroup with birth weight between 3000 g and 4000 g. Conclusions This study demonstrates a poor correlation between actual birth weight and the estimated fetal weight using a formula based on femur length and mid-thigh soft-tissue thickness, both linear parameters. Although avoidance of circumferential ultrasound measurements might prove to be beneficial, it is still yet to be found a fetal estimation formula that can be both accurate and simple to perform.

Sex-Specific Equations to Estimate Maximum Oxygen Uptake in Cycle Ergometry

AbstractBackground:Aerobic fitness, assessed by measuring VO2max in maximum cardiopulmonary exercise testing (CPX) or by estimating VO2max through the use of equations in exercise testing, is a predictor of mortality. However, the error resulting from this estimate in a given individual can be high, affecting clinical decisions.Objective:To determine the error of estimate of VO2max in cycle ergometry in a population attending clinical exercise testing laboratories, and to propose sex-specific equations to minimize that error.Methods:This study assessed 1715 adults (18 to 91 years, 68% men) undertaking maximum CPX in a lower limbs cycle ergometer (LLCE) with ramp protocol. The percentage error (E%) between measured VO2max and that estimated from the modified ACSM equation (Lang et al. MSSE, 1992) was calculated. Then, estimation equations were developed: 1) for all the population tested (C-GENERAL); and 2) separately by sex (C-MEN and C-WOMEN).Results:Measured VO2max was higher in men than in WOMEN: -29.4 ± 10.5 and 24.2 ± 9.2 mL.(kg.min)-1 (p < 0.01). The equations for estimating VO2max [in mL.(kg.min)-1] were: C-GENERAL = [final workload (W)/body weight (kg)] x 10.483 + 7; C-MEN = [final workload (W)/body weight (kg)] x 10.791 + 7; and C-WOMEN = [final workload (W)/body weight (kg)] x 9.820 + 7. The E% for MEN was: -3.4 ± 13.4% (modified ACSM); 1.2 ± 13.2% (C-GENERAL); and -0.9 ± 13.4% (C-MEN) (p < 0.01). For WOMEN: -14.7 ± 17.4% (modified ACSM); -6.3 ± 16.5% (C-GENERAL); and -1.7 ± 16.2% (C-WOMEN) (p < 0.01).Conclusion:The error of estimate of VO2max by use of sex-specific equations was reduced, but not eliminated, in exercise tests on LLCE.