Determinação dos valores de referência da excursão sistólica do plano do anel tricúspide (TAPSE) em crianças saudáveis

Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular - Área de especialização: Ultrassonografia cardiovascular

Y Trinuclear Cu-II structural isomers coordination, magnetism, electrochemistry and catalytic activity towards the oxidation of alkanes

The reaction of the Schiff base (3,5-di-tert-butyl-2-hydroxybenzylidene)-2-hydroxybenzohydrazide (H3L) with copper(II) nitrate, acetate or metaborate has led to the isomeric complexes [Cu-3(L)(2)(MeOH)(4)] (1), [Cu-3(L)(2)(MeOH)(2)]2MeOH (2) and [Cu-3(L)(2)(MeOH)(4)] (3), respectively, in which the ligand L exhibits dianionic (HL2-, in 1) or trianionic (L3-, in 2 and 3) pentadentate 1O,O,N:2N,O chelation modes. Complexes 1-3 were characterized by elemental analysis, IR spectroscopy, single-crystal X-ray crystallography, electrochemical methods and variable-temperature magnetic susceptibility measurements, which indicated that the intratrimer antiferromagnetic coupling is strong in the three complexes and that there exists very weak ferromagnetic intermolecular interactions in 1 but weak antiferromagnetic intermolecular interactions in both 2 and 3. Electrochemical experiments showed that in complexes 1-3 the Cu-II ions can be reduced, in distinct steps, to Cu-I and Cu-0. All the complexes act as efficient catalyst precursors under mild conditions for the peroxidative oxidation of cyclohexane to cyclohexyl hydroperoxide, cyclohexanol and cyclohexanone, leading to overall yields (based on the alkane) of up to 31% (TON = 1.55x10(3)) after 6 h in the presence of pyrazinecarboxylic acid.

GPU implementation of the simplex identification via split augmented Lagrangian

Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.

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.

Comparing wind generation profiles: A circular data approach

The importance of wind power energy for energy and environmental policies has been growing in past recent years. However, because of its random nature over time, the wind generation cannot be reliable dispatched and perfectly forecasted, becoming a challenge when integrating this production in power systems. In addition the wind energy has to cope with the diversity of production resulting from alternative wind power profiles located in different regions. In 2012, Portugal presented a cumulative installed capacity distributed over 223 wind farms [1]. In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.In this work the circular data statistical methods are used to analyze and compare alternative spatial wind generation profiles. Variables indicating extreme situations are analyzed. The hour (s) of the day where the farm production attains its maximum daily production is considered. This variable was converted into circular variable, and the use of circular statistics enables to identify the daily hour distribution for different wind production profiles. This methodology was applied to a real case, considering data from the Portuguese power system regarding the year 2012 with a 15-minutes interval. Six geographical locations were considered, representing different wind generation profiles in the Portuguese system.