3 resultados para Elasticity Imaging Techniques

em Universidade Complutense de Madrid


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Context. The young associations offer us one of the best opportunities to study the properties of young stellar and substellar objects and to directly image planets thanks to their proximity (<200 pc) and age (≈5−150 Myr). However, many previous works have been limited to identifying the brighter, more active members (≈1 M_⊙) owing to photometric survey sensitivities limiting the detections of lower mass objects. Aims. We search the field of view of 542 previously identified members of the young associations to identify wide or extremely wide (1000−100 000 au in physical separation) companions. Methods. We combined 2MASS near-infrared photometry (J, H, K) with proper motion values (from UCAC4, PPMXL, NOMAD) to identify companions in the field of view of known members. We collated further photometry and spectroscopy from the literature and conducted our own high-resolution spectroscopic observations for a subsample of candidate members. This complementary information allowed us to assess the efficiency of our method. Results. We identified 84 targets (45: 0.2−1.3 M_⊙, 17: 0.08−0.2 M_⊙, 22: <0.08 M_⊙) in our analysis, ten of which have been identified from spectroscopic analysis in previous young association works. For 33 of these 84, we were able to further assess their membership using a variety of properties (X-ray emission, UV excess, Hα, lithium and K I equivalent widths, radial velocities, and CaH indices). We derive a success rate of 76–88% for this technique based on the consistency of these properties. Conclusions. Once confirmed, the targets identified in this work would significantly improve our knowledge of the lower mass end of the young associations. Additionally, these targets would make an ideal new sample for the identification and study of planets around nearby young stars. Given the predicted substellar mass of the majority of these new candidate members and their proximity, high-contrast imaging techniques would facilitate the search for new low-mass planets.

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Over the last few decades, the importance of ophthalmic examination in neurodegenerative diseases of the CNS has reportedly increased. The retina is an extension of the CNS and thus should not be surprising to find abnormal results in both the test exploring visual processing and those examining the retina of patients with CNS degeneration. Current in vivo imaging techniques are allowing ophthalmologists to detect and quantify data consistent with the histopathological findings described in the retinas of Alzheimer’s disease (AD) patients and may help to reveal unsuspected retinal and optic‐nerve repercussions of other CNS diseases. In this chapter, we perform an analysis of the physiological changes in ocular and cerebral ageing. We analyse the ocular manifestations in CNS disorders such as stroke, AD and Parkinson’s disease. In addition, the pathophysiology of both the eye and the visual pathway in AD are described. The value of the visual psychophysical tests in AD diagnosis is reviewed as well as the main findings of the optical coherence tomography as a contribution to the diagnosis and monitoring of the disease. Finally, we examine the association of two neurodegenerative diseases, AD and glaucoma, as mere coincidence or possible role in the progression of the neurodegeneration.

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Photothermal imaging allows to inspect the structure of composite materials by means of nondestructive tests. The surface of a medium is heated at a number of locations. The resulting temperature field is recorded on the same surface. Thermal waves are strongly damped. Robust schemes are needed to reconstruct the structure of the medium from the decaying time dependent temperature field. The inverse problem is formulated as a weighted optimization problem with a time dependent constraint. The inclusions buried in the medium and their material constants are the design variables. We propose an approximation scheme in two steps. First, Laplace transforms are used to generate an approximate optimization problem with a small number of stationary constraints. Then, we implement a descent strategy alternating topological derivative techniques to reconstruct the geometry of inclusions with gradient methods to identify their material parameters. Numerical simulations assess the effectivity of the technique.