We propose a scaled gradient projection algorithm for the reconstruction of 3D X-ray tomographic images from limited data. The problem arises from the discretization of an ill-posed integral problem and, due to the incompleteness of the data, has infinite possible solutions. Hence, by following a regularization approach, we formulate the reconstruction problem as the nonnegatively constrained minimization of an objective function given by the sum of a fit-to-data term and a smoothed differentiable Total Variation function. The problem is challenging for its very large size and because a good reconstruction is required in a very short time. For these reasons, we propose to use a gradient projection method, accelerated by exploiting a scaling strategy for defining gradient-based descent directions and generalized Barzilaiâ\u80\u93Borwein rules for the choice of the step-lengths. The numerical results on a 3D phantom are very promising since they show the ability of the scaling strategy to accelerate the convergence in the first iterations

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Brain strokes are one of the leading causes of disability and mortality in adults in developed countries. The ischemic stroke (85% of total cases) and hemorrhagic stroke (15%) must be treated with opposing therapies, thus the nature of the stroke must be determined quickly in order to apply the appropriate treatment. Recent studies in biomedical imaging have shown that strokes produce variations in the complex electric permittivity of brain tissues, which can be detected by means of microwave tomography. Here we present some synthetic results obtained with an experimental microwave tomography-based portable system for the early detection and monitoring of brain strokes. The determination of electric permittivity first requires the solution of a coupled forwardinverse problem. We make use of massive parallel computation from domain decomposition method and regularization techniques for optimization methods. Synthetic data are obtained with electromagnetic simulations corrupted by noise, which have been derived from measurements errors of the experimental imaging system. Results demonstrate the possibility to detect hemorrhagic strokes with microwave systems when applying the proposed reconstruction algorithm with edge preserving regularization.

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Does fragment size influence significantly archaeological charcoal spectra? Does the floristic content of charcoal concentrations provide a representative image of the anthracological record? These taphonomy-related questions are as old as the first methodological groundwork in anthracology and therefore, they could be considered as solved. The aim of this paper is to show that they are still topical today, as depositional and post-depositional conditions vary between archaeological contexts, periods, and sites. With this in mind, we revisited the charcoal data of an Early Mesolithic occupation, level 6 of Escabasses cave, which had the particularity of yielding a significant amount of charcoal fragments over 4 mm size and numerous combustion features. This allowed to test the impact of different size classes (mainly ]2-4[ mm vs. > 4 mm) and types of deposits (concentrated vs. scattered charcoal) on taxonomic diversity and proportions, as well as on the abundance of a key-taxon, deciduous oak (Quercus). Our results show that (i) contrarily to what is generally assumed, at Escabasses the proportions between taxa showed more variability according to size class than to types of deposit; (ii) size class doesid not impact floristic diversity; (iii) however, the probability to find higher Quercus frequencies within the ]2-4[ mm size class is significant. These results allude to different stages in the taphonomy history of the charcoals, potentially ranging from the type of occupation and related human practices to a specific postdepositional behavior of Quercus, suggested by previous studies.

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