8 resultados para multiple discriminant analysis
em Universidad de Alicante
Resumo:
A microwave-assisted extraction (MAE) procedure to isolate phenolic compounds from almond skin byproducts was optimized. A three-level, three-factor Box–Behnken design was used to evaluate the effect of almond skin weight, microwave power, and irradiation time on total phenolic content (TPC) and antioxidant activity (DPPH). Almond skin weight was the most important parameter in the studied responses. The best extraction was achieved using 4 g, 60 s, 100 W, and 60 mL of 70% (v/v) ethanol. TPC, antioxidant activity (DPPH, FRAP), and chemical composition (HPLC-DAD-ESI-MS/MS) were determined by using the optimized method from seven different almond cultivars. Successful discrimination was obtained for all cultivars by using multivariate linear discriminant analysis (LDA), suggesting the influence of cultivar type on polyphenol content and antioxidant activity. The results show the potential of almond skin as a natural source of phenolics and the effectiveness of MAE for the reutilization of these byproducts.
Resumo:
Se estudia la relación entre variables sociodemográficas, médicas y psicológicas y el comportamiento de fumar y los intentos de dejar de fumar. La muestra (n=291) se ha extraído al azar de una población comunitaria rural de 4300 habitantes. Todas las variables se han medido con un único cuestionario, a través de entrevista personal domiciliaria. Mediante análisis discriminantes las variables sexo, consumo de bebidas alcohólicas y el uso de medicamentos son las que más explican estadísticamente el comportamiento de fumar. Sorprendentemente, sólo una variable, haber visitado al médico en los últimos 12 meses, se asoció, bivariadamente, con los intentos de dejar de fumar, y no se procedía, lógicamente, con el análisis multivariante. Por último, se discuten los hallazgos a la luz de la literatura internacional y nacional.
Resumo:
The literature states that project duration is affected by various scope factors. Using 168 building projects carried out in Spain, this paper uses the multiple regression analysis to develop a forecast model that allows estimating project duration of new builds. The proposed model uses project type, gross floor area (GFA), the cost/GFA relationship and number of floors as predictor variables. The research identified the logarithmic form of construction speed as the most appropriate response variable. GFA has greater influence than cost on project duration but both factors are necessary to achieve a forecast model with the highest accuracy. We developed an analysis to verify the stability of forecasted values and showed how a model with high values of fit and accuracy may display an anomalous behavior in the forecasted values. The sensitivity of the proposed forecast model was also analyzed versus the variability of construction costs.
Resumo:
Purpose: To evaluate the correlation of the mean curvature and shape factors of both corneal surfaces for different corneal diameters measured with the Scheimpflug photography–based system in keratoconus eyes. Methods: A total of 61 keratoconus eyes of 61 subjects, aged 14 to 64 years, were included in this study. All eyes received a comprehensive ophthalmologic examination including anterior segment and corneal analysis with the Sirius system (CSO): anterior and posterior mean corneal radius for 3, 5, and 7 mm (aKM, pKM), anterior and posterior mean shape factor for 4.5 and 8 mm (ap, pp), central and minimal corneal thickness, and anterior chamber depth. Results: Mean aKM/pKM ratio around 1.20 (range, 0.95–1.48) was found for all corneal diameters (P = 0.24). Weak but significant correlations of this ratio with pachymetric parameters were found (r between −0.28 and −0.34, P < 0.04). The correlation coefficient between aKM and pKM was ≥0.92 for all corneal diameters. A strong and significant correlation was also found between ap and pp (r ≥ 0.86, P < 0.01). The multiple regression analysis revealed that central pKM was significantly correlated with aKM, central corneal thickness, anterior chamber depth, and spherical equivalent (R2 ≥ 0.88, P < 0.01) and that 8 mm pp was significantly correlated with 8 mm ap and age (R2 = 0.89, P < 0.01). Conclusions: Central posterior corneal curvature and shape factor in the keratoconus eye can be consistently predicted from the anterior corneal curvature and shape factor, respectively, in combination with other anatomical and ocular parameters.
Resumo:
AIM: To evaluate the prediction error in intraocular lens (IOL) power calculation for a rotationally asymmetric refractive multifocal IOL and the impact on this error of the optimization of the keratometric estimation of the corneal power and the prediction of the effective lens position (ELP). METHODS: Retrospective study including a total of 25 eyes of 13 patients (age, 50 to 83y) with previous cataract surgery with implantation of the Lentis Mplus LS-312 IOL (Oculentis GmbH, Germany). In all cases, an adjusted IOL power (PIOLadj) was calculated based on Gaussian optics using a variable keratometric index value (nkadj) for the estimation of the corneal power (Pkadj) and on a new value for ELP (ELPadj) obtained by multiple regression analysis. This PIOLadj was compared with the IOL power implanted (PIOLReal) and the value proposed by three conventional formulas (Haigis, Hoffer Q and Holladay). RESULTS: PIOLReal was not significantly different than PIOLadj and Holladay IOL power (P>0.05). In the Bland and Altman analysis, PIOLadj showed lower mean difference (-0.07 D) and limits of agreement (of 1.47 and -1.61 D) when compared to PIOLReal than the IOL power value obtained with the Holladay formula. Furthermore, ELPadj was significantly lower than ELP calculated with other conventional formulas (P<0.01) and was found to be dependent on axial length, anterior chamber depth and Pkadj. CONCLUSION: Refractive outcomes after cataract surgery with implantation of the multifocal IOL Lentis Mplus LS-312 can be optimized by minimizing the keratometric error and by estimating ELP using a mathematical expression dependent on anatomical factors.
Resumo:
A new classification of microtidal sand and gravel beaches with very different morphologies is presented below. In 557 studied transects, 14 variables were used. Among the variables to be emphasized is the depth of the Posidonia oceanica. The classification was performed for 9 types of beaches: Type 1: Sand and gravel beaches, Type 2: Sand and gravel separated beaches, Type 3: Gravel and sand beaches, Type 4: Gravel and sand separated beaches, Type 5: Pure gravel beaches, Type 6: Open sand beaches, Type 7: Supported sand beaches, Type 8: Bisupported sand beaches and Type 9: Enclosed beaches. For the classification, several tools were used: discriminant analysis, neural networks and Support Vector Machines (SVM), the results were then compared. As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer. Finally, an architecture with 30 neurons was chosen. Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid). The results obtained for the discriminant analysis were not as good as those obtained for the other two methods (ANN and SVM) which showed similar success.
Resumo:
Purpose: To evaluate the predictability of the refractive correction achieved with a positional accommodating intraocular lenses (IOL) and to develop a potential optimization of it by minimizing the error associated with the keratometric estimation of the corneal power and by developing a predictive formula for the effective lens position (ELP). Materials and Methods: Clinical data from 25 eyes of 14 patients (age range, 52–77 years) and undergoing cataract surgery with implantation of the accommodating IOL Crystalens HD (Bausch and Lomb) were retrospectively reviewed. In all cases, the calculation of an adjusted IOL power (PIOLadj) based on Gaussian optics considering the residual refractive error was done using a variable keratometric index value (nkadj) for corneal power estimation with and without using an estimation algorithm for ELP obtained by multiple regression analysis (ELPadj). PIOLadj was compared to the real IOL power implanted (PIOLReal, calculated with the SRK-T formula) and also to the values estimated by the Haigis, HofferQ, and Holladay I formulas. Results: No statistically significant differences were found between PIOLReal and PIOLadj when ELPadj was used (P = 0.10), with a range of agreement between calculations of 1.23 D. In contrast, PIOLReal was significantly higher when compared to PIOLadj without using ELPadj and also compared to the values estimated by the other formulas. Conclusions: Predictable refractive outcomes can be obtained with the accommodating IOL Crystalens HD using a variable keratometric index for corneal power estimation and by estimating ELP with an algorithm dependent on anatomical factors and age.
Resumo:
We examined the psychometric properties of the School Attitude Assessment Survey–Revised in a Spanish population (n = 1,398). Confirmatory factor analysis procedures supported the instrument’s five-factor structure. The results of discriminant analysis demonstrated the predictive power of the School Attitude Assessment Survey–Revised scales as regards academic performance. Implications for education and assessment are discussed.