Exploratory factor analysis of the Brazilian OHIP for edentulous subjects

P>The use of seven domains for the Oral Health Impact Profile (OHIP)-EDENT was not supported for its Brazilian version, making data interpretation in clinical settings difficult. Thus, the aim of this study was to assess patients` responses for the translated OHIP-EDENT in a group of edentulous subjects and to develop factor scales for application in future studies. Data from 103 conventional and implant-retained complete denture wearers (36 men, mean age of 69 center dot 1 +/- 10 center dot 3 years) were assessed using the Brazilian version of the OHIP-EDENT. Oral health-related quality of life domains were identified by factor analysis using principal component analysis as the extraction method, followed by varimax rotation. Factor analysis identified four factors that accounted for 63% of the 19 items total variance, named masticatory discomfort and disability (four items), psychological discomfort and disability (five items), social disability (five items) and oral pain and discomfort (five items). Four factors/domains of the Brazilian OHIP-EDENT version represent patient-important aspects of oral health-related quality of life.

Paleomagnetic data and K-Ar ages from Mesozoic units of the Santa Marta massif: A preliminary interpretation for block rotation and translations

We report 6 K-Ar ages and paleomagnetic data from 28 sites collected in Jurassic, Lower Cretaceous and Paleocene rocks of the Santa Marta massif, to test previous hypothesis of rotations and translations of this massif, whose rock assemblage differs from other basement-cored ranges adjacent to the Guyana margin. Three magnetic components were identified in this study. A first component has a direction parallel to the present magnetic field and was uncovered in all units (D 352, I = 25.6, k = 57.35, a95 = 5.3, N = 12). A second component was isolated in Cretaceous limestone and Jurassic volcaniclastic rocks (D = 8.8, I = 8.3, k = 24.71, a95 = 13.7, N = 6), and it was interpreted as of Early Cretaceous age. In Jurassic sites with this component, Early Cretaceous K-Ar ages obtained from this and previous studies are interpreted as reset ages. The third component was uncovered in eight sites of Jurassic volcaniclastic rocks, and its direction indicates negative shallow to moderate inclinations and northeastward declinations. K-Ar ages in these sites are of Early (196.5 +/- 4.9 Ma) to early Late Jurassic age (156.6 +/- 8.9 Ma). Due to local structural complexity and too few Cretaceous outcrops to perform a reliable unconformity test, we only used two sites with (1) K-Ar ages, (2) less structural complexity, and (3) reliable structural data for Jurassic and Cretaceous rocks. The mean direction of the Jurassic component is (D = 20.4, I = -18.2, k = 46.9, a95 = 5.1, n = 18 specimens from two sites). These paleomagnetic data support previous models of northward along-margin translations of Grenvillian-cored massifs. Additionally, clockwise vertical-axis rotation of this massif, with respect to the stable craton, is also documented; the sense of rotation is similar to that proposed for the Perija Range and other ranges of the southern Caribbean margin. More data is needed to confirm the magnitudes of rotations and translations. (C) 2009 Elsevier Ltd. All rights reserved.

PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

Groundwater favorability map using GIS multicriteria data analysis on crystalline terrain, Sao Paulo State, Brazil

This paper presents the groundwater favorability mapping on a fractured terrain in the eastern portion of Sao Paulo State, Brazil. Remote sensing, airborne geophysical data, photogeologic interpretation, geologic and geomorphologic maps and geographic information system (GIS) techniques have been used. The results of cross-tabulation between these maps and well yield data allowed groundwater prospective parameters in a fractured-bedrock aquifer. These prospective parameters are the base for the favorability analysis whose principle is based on the knowledge-driven method. The mutticriteria analysis (weighted linear combination) was carried out to give a groundwater favorabitity map, because the prospective parameters have different weights of importance and different classes of each parameter. The groundwater favorability map was tested by cross-tabulation with new well yield data and spring occurrence. The wells with the highest values of productivity, as well as all the springs occurrence are situated in the excellent and good favorabitity mapped areas. It shows good coherence between the prospective parameters and the well yield and the importance of GIS techniques for definition of target areas for detail study and wells location. (c) 2008 Elsevier B.V. All rights reserved.