990 resultados para independent evolution
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The extensional process affecting Iberia during the Triassic and Jurassic times change from the end of the Cretaceous and, throughout the Palaeocene, the displacement between the African and European plates was clearly convergent and part of the future Internal Zone of the Betic Cordillera was affected. To the west, the Atlantic continued to open as a passive margin and, to the north, no significant deformation occurred. During the Eocene, the entire Iberian plate was subjected to compression. which caused major deformations in the Pyrenees and also in the Alpujarride and Nevado-Filabride, Internal Betic, complexes. In the Oligocene continued this situation, but in addition, the new extensional process ocurring in the western Mediterranean area, together with the constant eastward drift of Iberia due to Atlantic opening, compressed the eastern sector of Iberia, giving rise to the structuring of the Iberian Cordillera. The Neogene was the time when the Betic Cordillera reached its fundamental features with the westward displacement of the Betic-Rif Internal Zone, expelled by the progressive opening of the Algerian Basin, opening prolonged till the Alboran Sea. From the late Miocene onwards, all Iberia was affected by a N-S to NNW-SSE compression, combined in many points by a near perpendicular extension. Specially in eastern and southern Iberia a radial extension superposed these compression and extension.
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The Setúbal and São Vicente canyons are two major modern submarine canyons located in the southwest Iberian margin of Portugal. Although recognised as Pliocene to Quaternary features, their development during the Tertiary has not been fully understood up to date. A grid of 2D seismic data has been used to characterise the sedimentary deposits of the adjacent flanks to the submarine canyons. The relationship between the geological structure of the margin and the canyon's present location has been investigated. The interpretation of the main seismic units allowed the recognition of three generations of ravinements probably originated after middle Oligocene. Six units grouped in two distinctive seismic sequences have been identified and correlated with offshore stratigraphic data. Seismic Sequence 2 (SS2), the oldest, overlies Mesozoic and upper Eocene deformed units. Seismic Sequence I (SS1) is composed of four different seismic packages separated from SS2 by an erosional surface. The base of the studied sediment ridges is marked by an extensive erosional surface derived from a early/middle Oligocene relative sea-level fall. Deposition in the adjacent area to the actual canyons was reinitiated in late Oligocene in the form of transgressive and channel-fill deposits. A new depositional hiatus is recorded onshore during the Burdigalian, coincident with the unconformity separating SS1 and SS2. This can be correlated with the Arrábida unconformity and with the paroxysmal Burdigalian phase of the Betic domain. Presently, the Setúbal and São Vicente submarine canyons locally cut SS1 and SS2, forming distinctive channels from those recognised on the seismic data. On the upper shelf both dissect highly deformed areas subject to important erosion.
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The chemical features of the ground water in the Lower Tagus Cenozoic deposits are strongly influenced by lithology, by the velocity and direction of the water movement as well as by the localization of the recharge and discharge zones. The mineralization varies between 80 and 900 mg/l. It is minimal in the recharge zones and in the Pliocene sand and maximum in the Miocene carbonated and along the alluvial valley. Mineralization always reflects the time of permanence, the temperature and the pressure. The natural process of water mineralization is disturbed in agricultural areas because the saline concentration of the infiltration water exceeds that of the infiltrated rainwater. In the discharge zones, the rise of the more mineralized, some times thermal deep waters related to tectonic accidents give rise to anomalies in the distribution of the aquiferous system mineralization model. The diversity of the hydrochemical facies of the ground water may be related to several factors whose identification is some times difficult.
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MSc. Dissertation presented at Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa to obtain the Master degree in Electrical and Computer Engineering
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Climatic reconstructions based on palynological data from Aquitaine outcrops emphasize an important degradation phase during the Lower Serravallian. Climatic and environmental changes can be related to sea-level variations (Bur 5 / Lan 1, Lan 2 / Ser 1 and Ser 2 cycles). Transgressive phases feature warmer conditions and more open environments whereas regressive phases are marked by a cooler climate and an extent of the forest cover. From Langhian to Middle Serravallian, a general cooling is highlighted, with disappearance of most megathermic taxa and a transition from warm and dry climate to warm-temperate and much more humid conditions. Conclusions are consistent with studies on bordering areas and place the major degradation phase around 14 My. The palynologic data allow filling a gap in the climatic evolution of Southern France, as a connection between Lower and Upper Miocene, both well recorded. These results document, on Western Europe scale, latitudinal climatic gradient across Northern hemisphere while featuring a transition between Mediterranean area and northeastern Atlantic frontage.
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Extended-spectrum β-lactamases (ESBLs) prevalence was studied in the north of Portugal, among 193 clinical isolates belonging to citizens in a district in the boundaries between this country and Spain from a total of 7529 clinical strains. In the present study we recovered some members of Enterobacteriaceae family, producing ESBL enzymes, including Escherichia coli (67.9%), Klebsiella pneumoniae (30.6%), Klebsiella oxytoca (0.5%), Enterobacter aerogenes (0.5%), and Citrobacter freundii (0.5%). β-lactamases genes blaTEM, blaSHV, and blaCTX-M were screened by polymerase chain reaction (PCR) and sequencing approaches. TEM enzymes were among the most prevalent types (40.9%) followed by CTX-M (37.3%) and SHV (23.3%). Among our sample of 193 ESBL-producing strains 99.0% were resistant to the fourth-generation cephalosporin cefepime. Of the 193 isolates 81.3% presented transferable plasmids harboring genes. Clonal studies were performed by PCR for the enterobacterial repetitive intragenic consensus (ERIC) sequences. This study reports a high diversity of genetic patterns. Ten clusters were found for E. coli isolates and five clusters for K. pneumoniae strains by means of ERIC analysis. In conclusion, in this country, the most prevalent type is still the TEM-type, but CTX-M is growing rapidly.
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Three-dimensional (3D) nickel-copper (Ni-Cu) nanostructured foams were prepared by galvanostatic electrodeposition, on stainless steel substrates, using the dynamic hydrogen bubble template. These foams were tested as electrodes for the hydrogen evolution reaction (HER) in 8 M KOH solutions. Polarisation curves were obtained for the Ni-Cu foams and for a solid Ni electrode, in the 25-85 degrees C temperature range, and the main kinetic parameters were determined. It was observed that the 3D foams have higher catalytic activity than pure Ni. HER activation energies for the Ni-Cu foams were lower (34-36 kJ mol(-1)) than those calculated for the Ni electrode (62 kJ mol(-1)). The foams also presented high stability for HER, which makes them potentially attractive cathode materials for application in industrial alkaline electrolysers.
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Thesis presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Electrical and Computer Engineering
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The local fractional Poisson equations in two independent variables that appear in mathematical physics involving the local fractional derivatives are investigated in this paper. The approximate solutions with the nondifferentiable functions are obtained by using the local fractional variational iteration method.
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Shelves surrounding reefless volcanic ocean islands are formed by surf erosion of their slopes during changing sea levels. Posterosional lava flows, if abundant, can cross the coastal cliffs and fill partially or completely the accommodation space left by erosion. In this study, multibeam bathymetry, high-resolution seismic reflection profiles, and sediment samples are used to characterize the morphology of the insular shelves adjacent to Pico Island. The data show offshore fresh lava flow morphologies, as well as an irregular basement beneath shelf sedimentary bodies and reduced shelf width adjacent to older volcanic edifices in Pico. These observations suggest that these shelves have been significantly filled by volcanic progradation and can thus be classified as rejuvenated. Despite the general volcanic infilling of the shelves around Pico, most of their edges are below the depth of the Last Glacial Maximum, revealing that at least parts of the island have subsided after the shelves formed by surf erosion. Prograding lava deltas reached the shelf edge in some areas triggering small slope failures, locally decreasing the shelf width and depth of their edges. These areas can represent a significant risk for the local population; hence, their identification can be useful for hazard assessment and contribute to wiser land use planning. Shelf and subaerial geomorphology, magnetic anomalies and crustal structure data of the two islands were also interpreted to reconstruct the long-term combined onshore and offshore evolution of the Faial-Pico ridge. The subaerial emergence of this ridge is apparently older than previously thought, i.e., before approximate to 850 ka.
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Dissertação apresentada para obtenção do grau de Doutor em Biologia Celular pelo Instituto de Tecnologia Química e Biológica da Universidade Nova de Lisboa
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The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.
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Geociências, Museu Nac. Hist. Nat. Univ. Lisboa, nº 2, 35-84
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Optically transparent cocatalyst film materials is very desirable for improved photoelectrochemical (PEC)oxygen evolution reaction (OER) over light harvesting photoelectrodes which require the exciting light to irradiate through the cocatalyst side, i.e., front-side illumination. In view of the reaction overpotential at electrode/electrolyte interface, the OER electrocatalysts have been extensively used as cocatalysts for PEC water oxidation on photoanode. In this work, the feasibility of a one-step fabrication of the transparent thin film catalyst for efficient electrochemical OER is investigated. The Ni-Fe bimetal oxide films, 200 nm in thickness, are used for study. Using a reactive magnetron co-sputtering technique, transparent(> 50% in wavelength range 500-2000 nm) Ni-Fe oxide films with high electrocatalytic activities were successfully prepared at room temperature. Upon optimization, the as-prepared bimetal oxide film with atomic ratio of Fe/Ni = 3:7 demonstrates the lowest overpotential for the OER in aqueous KOH solution, as low as 329 mV at current density of 2 mA cm 2, which is 135 and 108 mV lower than that of as-sputtered FeOx and NiOx thin films, respectively. It appears that this fabrication strategy is very promising to deposit optically transparent cocatalyst films on photoabsorbers for efficient PEC water splitting.
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The recognition profile of the tissue cysts antigens by IgG antibodies was studied during acute and chronic human toxoplasmic infection. Thus the IgG response against Toxoplasma gondii was investigated by immunoblotting in two patients accidentally infected with the RH strain as well as in group of naturally infected patients at acute and chronic phase. There was an overall coincidence of molecular mass among antigens of tachyzoites and tissue cysts recognized by these sera, however, they appear not to be the same molecules. The response against tissue cysts starts early during acute infection, and the reactivity of antibodies is strong against a wide range of antigens. Six bands (between 82 and 151 kDa) were exclusively recognized by chronic phase sera but only the 132 kDa band was positive in more than 50% of the sera analysed. A mixture of these antigens could be used to discriminate between the two infection phases. The most important antigens recognized by the acute and the chronic phase sera were 4 clusters in the ranges 20-24 kDa, 34-39 kDa, 58-80 kDa and 105-130 kDa as well as two additional antigens of 18 and 29 kDa. Both accidentally infected patients and some of the naturally infected patients showed a weak specific response against tissue cyst antigens.