2 resultados para principal components analysis (PCA) algorithm

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In this study, Evernia prunastri, a lichen growing in its natural habitat in Morocco was analysed for the concentration of five heavy metals (Fe, Pb, Zn, Cu and Cr) from eleven sites between Kenitra and Mohammedia cities. The control site was Dar Essalam, an isolated area with low traffic density and dense vegetation. In the investigated areas, the concentration of heavy metals was correlated with vehicular traffic, industrial activity and urbanization. The total metal concentration was highest in Sidi Yahya, followed by Mohammedia and Bouznika. The coefficient of variation was higher for Pb and lower for Cu, Zn and Fe. The concentrations of most heavy metals in the thalli differed significantly between sites (p<0.01). Principal component analysis (PCA) revealed a significant correlation between heavy metal accumulation and atmospheric purity index. This study demonstrated also that the factors most strongly affecting the lichen flora were traffic density, the petroleum industry and paper factories in these areas. Overall, these results suggest that the index of atmospheric purity and assessment of heavy metals in lichen thalli are good indicators of the air quality at the studied sites.

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Objective: To determine the psychometric properties of two scales designed to examine attitudes regarding palliative care: Comfort Scale in Palliative Care (CSPC, Pereira et al.) and Tanatophobia Scale (TS, Merrill et al.)Method: Seventy-seven students who completed an online course on psychosocial aspects of palliative care offered by the Latin American Association of Palliative Care participated in the study. They also completed the scales before and after the course. Construct validity and reliability of the CSPC and the TS were assessed using a Principal Components Analysis, internal reliability coefficient and test-retest reliability. Further, comparative statistics between the pre-course and post-course results were obtained in order to determine changes in attitudes.Results: The Principal Components Analysis showed satisfactory fit to the data. 3 components were extracted: two for the CSPC and one for the TS, which explained 55.37% of the variance. Internal consistency coefficients were satisfactory in all cases and Cronbach´s Alphas were satisfactory for all the scales, particularly for the CSPC. Test-retest reliability in t1 and t2 was found to be non significant, indicating that measures were not related in time. Regarding pre-course/post-course comparisons, significant changes in comfort assisting patients (p = 0.004) and comfort assisting families (p = 0.001) following the course were identified, but changes in thanatophobia were non significant (p > 0.05).Conclusions: both scales are valid and reliable. Attitudes regarding the practice of palliative care and how they change, particularly regarding psychosocial issues, can be accurately measured using the examined scales.