Multi-stage evolution of a sub-aerial volcanic ridge over the last 1.3 Myr: S. Jorge Island, Azores Triple Junction

New K/Ar dating and geochemical analyses have been carried out on the WNW-ESE elongated oceanic island of S. Jorge to reconstruct the volcanic evolution of a linear ridge developed close to the Azores triple junction. We show that S. Jorge sub-aerial construction encompasses the last 1.3 Myr, a time interval far much longer than previously reported. The early development of the ridge involved a sub-aerial building phase exposed in the southeast end of the island and now constrained between 1.32 +/- 0.02 and 1.21 +/- 0.02 Ma. Basic lavas from this older stage are alkaline and enriched in incompatible elements, reflecting partial melting of an enriched mantle source. At least three differentiation cycles from alkaline basalts to mugearites are documented within this stage. The successive episodes of magma rising, storage and evolution suggest an intermittent reopening of the magma feeding system, possibly due to recurrent tensional or trans-tensional tectonic events. Present data show a gap in sub-aerial volcanism before a second main ongoing building phase starting at about 750 ka. Sub-aerial construction of the S. Jorge ridge migrated progressively towards the west, but involved several overlapping volcanic episodes constrained along the main WNW-ESE structural axis of the island. Malic magmas erupted during the second phase have been also generated by partial melting of an enriched mantle source. Trace element data suggest, however, variable and lower degrees of partial melting of a shallower mantle domain, which is interpreted as an increasing control of lithospheric deformation on the genesis and extraction of primitive melts during the last 750 kyr. The multi-stage development of the S. Jorge volcanic ridge over the last 1.3 Myr has most likely been greatly influenced by regional tectonics, controlled by deformation along the diffuse boundary between the Nubian and the Eurasian plates, and the increasing effect of sea-floor spreading at the Mid-Atlantic Ridge.

Estudo comparativo da estereopsia: testando a aplicação digital Stereo TAB em estudantes do ensino superior

A estereopsia é o 3º grau da visão binocular. Define-se pela perceção de profundidade e baseia-se na disparidade retiniana. Estereopsia global – estereograma de pontos aleatórios (perceção necessita de disparidade retiniana). Estereopsia local – estereogramas com contornos percebidos monocularmente (processo de fusão facilitado). Objectivos do estudo: 1) comparar valores de estereopsia obtidos em cada teste e analisar valores de estereopsia local e global; 2) estudar a correlação de valores de estereopsia nos testes (TNO goldstandard); 3) estudar a associação entre o resultado dos testes; 4) comparar exatidão entre FlyTeste StereoTAB; 5) estudar a sensibilidade e a especificidade do FlyTeste StereoTAB; 6) averiguar a aplicabilidade do SteroTABna prática clínica.

Hyperspectral imagery framework for unmixing and dimensionality estimation

In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm.

Signal subspace identification in hyperspectral imagery

Terrestrial remote sensing imagery involves the acquisition of information from the Earth's surface without physical contact with the area under study. Among the remote sensing modalities, hyperspectral imaging has recently emerged as a powerful passive technology. This technology has been widely used in the fields of urban and regional planning, water resource management, environmental monitoring, food safety, counterfeit drugs detection, oil spill and other types of chemical contamination detection, biological hazards prevention, and target detection for military and security purposes [2-9]. Hyperspectral sensors sample the reflected solar radiation from the Earth surface in the portion of the spectrum extending from the visible region through the near-infrared and mid-infrared (wavelengths between 0.3 and 2.5 µm) in hundreds of narrow (of the order of 10 nm) contiguous bands [10]. This high spectral resolution can be used for object detection and for discriminating between different objects based on their spectral xharacteristics [6]. However, this huge spectral resolution yields large amounts of data to be processed. For example, the Airbone Visible/Infrared Imaging Spectrometer (AVIRIS) [11] collects a 512 (along track) X 614 (across track) X 224 (bands) X 12 (bits) data cube in 5 s, corresponding to about 140 MBs. Similar data collection ratios are achieved by other spectrometers [12]. Such huge data volumes put stringent requirements on communications, storage, and processing. The problem of signal sbspace identification of hyperspectral data represents a crucial first step in many hypersctral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction (DR) yelding gains in data storage and retrieval and in computational time and complexity. Additionally, DR may also improve algorithms performance since it reduce data dimensionality without losses in the useful signal components. The computation of statistical estimates is a relevant example of the advantages of DR, since the number of samples required to obtain accurate estimates increases drastically with the dimmensionality of the data (Hughes phnomenon) [13].

Comparative study of stereopsis with three different tests: TNO®, Stereo Acuity Test Fly® and StereoTAB® in students in higher school

Purpose: Stereopsis is the perception of depth based on retinal disparity. Global stereopsis depends on the process of random dot stimuli and local stereopsis depends on contour perception. The aim of this study was to correlate 3 stereopsis tests: TNO®, StereoTA B®, and Fly Stereo Acuity Test® and to study the sensitivity and correlation between them, using TNO® as the gold standard. Other variables as near convergence point, vergences, symptoms and optical correction were correlated with the 3 tests. Materials and Methods: Forty-nine students from Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL), aged 18-26 years old were included. Results: The stereopsis mean (standard-deviation-SD) values in each test were: TNO® = 87.04” ±84.09”; FlyTest® = 38.18” ±34.59”; StereoTA B® = 124.89’’ ±137.38’’. About the coefficient of determination: TNO® and StereoTA B® with R2 = 0.6 e TNO® and FlyTest® with R2 =0.2. Pearson correlation coefficient shows a positive correlation between TNO® and StereoTA B® (r = 0.784 with α = 0.01). Phi coefficient shows a strong and positive association between TNO® and StereoTA B® (Φ = 0.848 with α = 0.01). In the ROC Curve, the StereoTA B® has an area under the curve bigger than the FlyTest® with a sensivity of 92.3% for 94.4% of specificity, so it means that the test is sensitive with a good discriminative power. Conclusion: We conclude that the use of Stereopsis tests to study global Stereopsis are an asset for clinical use. This type of test is more sensitive, revealing changes in Stereopsis when it is actually changed, unlike the test Stereopsis, which often indicates normal Stereopsis, camouflaging a Stereopsis change. We noted also that the StereoTA B ® is very sensitive and despite being a digital application, possessed good correlation with the TNO®.

Estudo comparativo da estereopsia com três testes diferentes: TNO®, Fly Stereo Acuity Test® e StereoTAB® em estudantes do ensino superior

Estereopsia define-se como a perceção de profundidade baseada na disparidade retiniana. A estereopsia global depende do processamento de estímulos de pontos aleatórios e a estereopsia local depende da perceção de contornos. O objetivo deste estudo é correlacionar três testes de estereopsia: TNO®, StereoTAB® e Fly Stereo Acuity Test® e verificar a sensibilidade e correlação entre eles, tendo o TNO® como gold standard. Incluíram-se 49 estudantes da Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL) entre os 18 e 26 anos. As variáveis ponto próximo de convergência (ppc), vergências, sintomatologia e correção ótica foram correlacionadas com os três testes. Os valores médios (desvios-padrão) de estereopsia foram: TNO® = 87,04’’ ±84,09’’; FlyTest® = 38,18’’ ±34,59’’; StereoTAB® = 124,89’’ ±137,38’’. Coeficiente de determinação: TNO® e StereoTAB® com R2=0,6 e TNO® e FlyTest® com R2=0,2. O coeficiente de correlação de Pearson mostra uma correlação positiva de entre o TNO® e o StereoTAB® (r=0,784 com α=0,01). O coeficiente de associação de Phi mostrou uma relação positiva forte entre o TNO® e StereoTAB® (Φ=0,848 com α=0,01). Na curva ROC, o StereoTAB® possui uma área sob a curva maior que o FlyTest®, apresentando valor de sensibilidade de 92,3% para uma especificidade de 94,4%, tornando-o num teste sensível e com bom poder discriminativo.