In this article a nonnegative blind source separation technique, known as nonnegative matrix factorization, is applied to microdiffraction data in order to extract characteristic patterns and to determine their spatial distribution in tissue typing problems occurring in bone-tissue engineering. In contrast to other blind source separation methods, nonnegative matrix factorization only requires nonnegative constraints on the extracted sources and corresponding weights, which makes it suitable for the analysis of data occurring in a variety of applications. In particular, here nonnegative matrix factorization is hierarchically applied to two-dimensional meshes of X-ray diffraction data measured in bone samples with implanted tissue. Such data are characterized by nonnegative profiles and their analysis provides significant information about the structure of possibly new deposited bone tissue. A simulation and real data studies show that the proposed method is able to retrieve the patterns of interest and to provide a reliable and accurate segmentation of the given X-ray diffraction data.

The aim of this work is to analyze the hydroacoustic behavior of a marine propeller through the acoustic analogy and to test the versatility and effectiveness of this approach in dealing with the many (and relatively unexplored) issues concerning the underwater noise and its numerical prediction. In particular, a propeller in a noncavitating open water condition is examined here by coupling a Reynolds averaged Navier-Stokes hydrodynamic solver to a hydroacoustic code implementing different resolution forms of the Ffowcs Williams-Hawkings (FWH) equation. The numerical results suggest that unlike the analogous aeronautical problem, where the role played by the nonlinear quadrupole sources is known to be relevant just at high transonic or supersonic regime, the pressure field underwater seems to be significantly affected by the flow nonlinearities, while the contribution from the linear terms (the thickness and loading noise components) is dominant only in a spatially very limited region. Then, contrary to popular belief and regardless of the low blade rotational speed, a reliable hydroacoustic analysis of a marine propeller cannot put aside the contribution of the nonlinear noise sources represented by the turbulence and vorticity three-dimensional fields and requires the computation of the FWH quadrupole source terms.

The MIPAS instrument on the ENVISAT satellite has provided vertical profiles of the atmospheric composition on a global scale for almost ten years. The MIPAS mission is divided in two phases, the full resolution phase, from 2002 to 2004, and the optimized resolution phase, from 2005 to 2012, which is characterized by a finer vertical and horizontal sampling attained through a reduction of the spectral resolution. While the description and characterization of the products of the ESA processor for the full resolution phase has been already described in previous papers, in this paper we focus on the performances of the latest version of the ESA processor, named ML2PP V6, which has been used for reprocessing the entire mission. The ESA processor had to perform the operational near real time analysis of the observations and its products needed to be available for data assimilation. Therefore, it has been designed for fast, continuous and automated analysis of observations made in quite different atmospheric conditions and for a minimum use of external constraints in order to avoid biases in the products. The dense vertical sampling of the measurements adopted in the second phase of the MIPAS mission resulted in sampling intervals finer than the instantaneous field of view of the instrument. Together with the choice of a retrieval grid aligned with the vertical sampling of the measurements, this made ill-conditioned the retrieval formalism of the MIPAS operational processor. This problem has been handled with minimal changes to the original retrieval approach but with significant improvements nonetheless. The Levenberg-Marquardt method, already present in the retrieval scheme for its capability to provide fast convergence for non-linear problems, is now also exploited for the reduction of the ill-conditioning of the inversion. An expression specifically designed for the regularizing Levenberg-Marquardt method has been implemented for the computation of the covariance matrices and averaging kernels of the retrieved products. The regularization of the Levenberg-Marquardt method is controlled by the convergence criteria and is deliberately kept weak. The resulting oscillations of the retrieved profile are a-posteriori damped by an innovative self-adapting Tikhonov regularization. The convergence criteria and the weakness of the self-adapting regularization ensure that minimum constraints are used and the best vertical resolution obtainable from the measurements is achieved in all atmospheric conditions. Random and systematic errors, as well as vertical and horizontal resolution are compared in the two phases of the mission for all products, namely: temperature, H2O, O3, HNO3, CH4, N2O, NO2, CFC-11, CFC-12, N2O5 and ClONO2. The use in the two phases of the mission of different optimized sets of spectral intervals ensures that, despite the different spectral resolutions, comparable performances are obtained in the whole MIPAS mission in terms of random and systematic errors, while the vertical resolution and the horizontal resolution are significantly better in the case of the optimized resolution measurements.

In areas of difficult access, such as the arctic ones, the extraction of inter- est zones (e.g. glaciers) from satellite images may be a valuable way to study and monitor their status . This work faces in particular the prob- lem of detecting different zones of glaciers from SAR (Synthetic Aperture Radar) images. In the polar regions the use of the SAR system is funda- mental because it works independently of weather and daylight. Segmentation is a process that allows an image to be divided into disjoint zones in such a way that each extracted area contains homogeneous char- acteristics. The numerical approach, here applied to detect glacier zones, is based on moving boundary modelling and is described by the eikonal equation. The upwind finite difference approximation of the eikonal equa- tion is solved by a fast marching technique, that starts from seed points in the region of interest and generates a front which evolves until the bound- ary of the region is identified. Results from segmentation of glacier images in the Svalbard archipelago acquired by ERS2 SAR (Synthetic Aperture Radar) and Envisat (ESA Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) are presented and discussed.

The effect of the nitrification inhibitor 3,4-dimethylphyrazole phosphate (DMPP) on N-fertilized crop growth and soil N2O emissions were studied at two experimental sites in Southern Italy, characterised by a Mediterranean climate and different soil texture. The experiments were a randomized block design of two treatments: crop fertilized with NH4NO3 (considered the control treatment) or amended with DMPP plus NH4NO3 (considered the DMPP treatment). ANOVA was performed to assess differences between treatments and fertilization periods whereas simple and multiple linear regressions were performed in order to assess the effect of the soil-related in-dependent variables on soil gases emissions. Growth of potato plants fertilized with DMPP-added nitrogen was enhanced compared to control plants, whereas no benefit on maize plants grown during summer was observed. N2O emissions measured from soil to potato after the first fertilization with DMPP-added nitrogen was reduced during winter, but was higher than control after the second fertilizer application in spring, leading to comparable N2O emission factors (EF1) between treatments. In maize N2O emissions and EF1 were lower for DMPP compared to control treatment. The effectiveness of reduction in soil N2O emission was influenced by soil temperature and water-filled pore space (WFPS) in both experimental sites. However, the overall effect of WFPS was contrasting as N2O emissions were decreased in potato and enhanced in maize.

MIPAS measurements on ENVISAT represents a unique database for the study of atmospheric composition and of the time variation of atmospheric constituents and trends, in combination with other data. With the end of the ENVISAT mission, the importance of this decadal set of measurements justifies any efforts for their full exploitation. The maintenance and the upgrade of the ESA processor are made in the frame of the Quality Working Group, where a fruitful collaboration between L1, L2 and validation teams can be exploited. This collaboration is essential to pursue improvements in the accuracy of the products and their characterization. Recently a new version of the Level 2 processor (ML2PP V7) has been finalized, containing a new approach for handling continuum capable of making the retrieval more stable, a new selection of spectral intervals selected for the analysis of the full resolution measurements aimed to reduce the bias between full resolution and optimized resolution measurements, the regularization of the H2O profiles, the products of five new species (CFC-22, CFC-14, HCN, COF2, CCl4). The addition of these 5 species leads to 15 the number of species processed by the operational processor, but the list of retrieved species can be further enlarged. The latest improvements implemented in the ESA processor and the results of the feasibility studies for additional upgrades will be presented and discussed.

A new color quantization algorithm, CQ, is presented, which includes two phases. The first phase reduces the number of colors by reducing the spatial resolution of the input image. The second phase furthermore reduces the number of colors by performing color clustering guided by distance information. Then, color mapping completes the process. The algorithm has been tested on a large number of color images with different size and color distribution, and the performance has been compared to the performance of other algorithms in the literature.

We complete the analytical determination, at the 4th post-Newtonian approximation, of the main radial potential describing the gravitational interaction of two bodies within the effective one-body formalism. The (nonlogarithmic) coefficient a5(?) measuring this 4th post-Newtonian interaction potential is found to be linear in the symmetric mass ratio ?. Its ?-independent part a5(0) is obtained by an analytical gravitational self-force calculation that unambiguously resolves the formal infrared divergencies which currently impede its direct post-Newtonian calculation. Its ?-linear part a5(?)-a5(0) is deduced from recent results of Jaranowski and Schäfer, and is found to be significantly negative.

A color quantization algorithm is presented, which is based on the reduction of the spatial resolution of the input image. The maximum number of colors nf desired for the output image is used to fix the proper spatial resolution reduction factor. This is used to build a lower resolution version of the input image with size nf. Colors found in the lower resolution image constitute the palette for the output image. The three components of each color of the palette are interpreted as the coordinates of a voxel in the 3D discrete space. The Voronoi Diagram of the set of voxels corresponding to the colors of the palette is computed and is used for color mapping of the input image.

Efficient recovery of smooth functions which are s-sparse with respect to the basis of so-called prolate spheroidal wave functions from a small number of random sampling points is considered. The main ingredient in the design of both the algorithms we propose here consists in establishing a uniform L? bound on the measurement ensembles which constitute the columns of the sensingmatrix. Such a bound provides us with the restricted isometry property for this rectangular random matrix, which leads to either the exact recovery property or the "best s-term approximation" of the original signal by means of the 1 minimization program. The first algorithm considers only a restricted number of columns for which the L? holds as a consequence of the fact that eigenvalues of the Bergman's restriction operator are close to 1 whereas the second one allows for a wider system of PSWF by taking advantage of a preconditioning technique. Numerical examples are spread throughout the text to illustrate the results.

The ability of Well-Balanced (WB) schemes to capture very accurately steady-state regimes of non-resonant hyperbolic systems of balance laws has been thoroughly illustrated since its introduction by Greenberg and LeRoux (1996) [15] (see also the anterior WB Glimm scheme in E, 1992 [8]). This paper aims at showing, by means of rigorous C0 t (L1x ) estimates, that these schemes deliver an increased accuracy in transient regimes too. Namely, after explaining that for the vast majority of non-resonant scalar balance laws, the C0 t (L1x ) error of conventional fractional-step (Tang and Teng, 1995 [45]) numerical approximations grows exponentially in time like exp(max(g )t) ? x (as a consequence of the use of Gronwall's lemma), it is shown that WB schemes involving an exact Riemann solver suffer from a much smaller error amplification: thanks to strict hyperbolicity, their error grows at most only linearly in time (see also Layton, 1984 [30]). Numerical results on several testcases of increasing difficulty (including the classical LeVeque-Yee's benchmark problem (LeVeque and Yee, 1990 [34]) in the non-stiff case) confirm the analysis.

Indefinite symmetric matrices occur in many applications, such as optimization, least squares problems, partial differential equations, and variational problems. In these applications one is often interested in computing a factorization of the indefinite matrix that puts into evidence the inertia of the matrix or possibly provides an estimate of its eigenvalues. In this paper we propose an algorithm that provides this information for any symmetric indefinite matrix by transforming it to a block antitriangular form using orthogonal similarity transformations. We also show that the algorithm is backward stable and has a complexity that is comparable to existing matrix decompositions for dense indefinite matrices.