Advanced architectural descriptors in foams: novel 3D computational methods

This work presents 3D computational strategies aimed at providing foam de-structuration of the basic components of a cellular material (struts and cell walls) offering the possibility of analysing separately the structural elements that play an important role in the physical properties of thee materials. Two different methodologies have been used depending on the topological similarities existing between the struts and cell walls: 3D erosion-dilation procedure (thick struts) and solid classification algorithm (thin struts). In a second step, analysis of cell walls is performed in order to show the advantages of analysing separately the two foams components. Particularly, cell wall thickness distribution reveals differences that could not be found prior to the de-structuration

Portable low profile antenna at X-band

An antenna which has been conceived as a portable system for satellite communications based on the recommendations ITU-R S.580-6 and ITU-R S.465-5 for small antennas, i.e., with a diameter lower than 50 wavelengths, is introduced. It is a planar and a compact structure with a size of 40×40×2 cm. The antenna is formed by an array of 256 printed elements covering a large bandwidth (14.7%) at X-Band with a VSWR of 1.4:1. The specification includes transmission (Tx) and reception (Rx) bands simultaneously. The printed antenna has a radiation pattern with a 3dB beamwidth of 5°, over a 31dBi gain, and a dual and an interchangeable circular polarization

Crossover in the nature of the metallic phases in the perovskite-type RNiO_3

We have measured the photoemission spectra of Nd$_{1-x}$Sm$_{x}$NiO$_{3}$, where the metal-insulator transition and the N\'{e}el ordering occur at the same temperature for $x \lesssim 0.4$ and the metal-insulator transition temperature ($T_{MI}$) is higher than the N\'{e}el temperature for $x \gtrsim 0.4$. For $x \le 0.4$, the spectral intensity at the Fermi level is high in the metallic phase above $T_{MI}$ and gradually decreases with cooling in the insulating phase below $T_{MI}$ while for $x > 0.4$ it shows a pseudogap-like behavior above $T_{MI}$ and further diminishes below $T_{MI}$. The results clearly establish that there is a sharp change in the nature of the electronic correlations in the middle ($x \sim 0.4$) of the metallic phase of the $R$NiO$_3$ system.Comment: 4 pages, 4 figure, submitted to Phys. Rev.

Self-organization of ultrasound in viscous fluids

We report the theoretical and experimental demonstration of pattern formation in acoustics. The system is an acoustic resonator containing a viscous fluid. When the system is driven by an external periodic force, the ultrasonic field inside the cavity experiences different pattern-forming instabilities leading to the emergence of periodic structures. The system is also shown to possess bistable regimes, in which localized states of the ultrasonic field develop. The thermal nonlinearity in the viscous fluid, together with the far-from-equilibrium conditions, are is the responsible of the observed effects

Friedel Oscillations in Relativistic Nuclear Matter

We calculate the low-momentum N-N effective potential obtained in the OBE approximation, inside a nuclear plasma at finite temperature, as described by the relativistic $\sigma$-$\omega$ model. We analyze the screening effects on the attractive part of the potential in the intermediate range as density or temperature increase. In the long range the potential shows Friedel-like oscillations instead of the usual exponential damping. These oscillations arise from the sharp edge of the Fermi surface and should be encountered in any realistic model of nuclear matter.Comment: 11 pages in preprint format, typeset using REVTEX, 3 included figures in tar, compressed, uuencoded forma

The derived category of quasi-coherent sheaves and axiomatic stable homotopy

We prove in this paper that for a quasi-compact and semi-separated (non necessarily noetherian) scheme X, the derived category of quasi-coherent sheaves over X, D(A_qc(X)), is a stable homotopy category in the sense of Hovey, Palmieri and Strickland, answering a question posed by Strickland. Moreover we show that it is unital and algebraic. We also prove that for a noetherian semi-separated formal scheme X, its derived category of sheaves of modules with quasi-coherent torsion homologies D_qct(X) is a stable homotopy category. It is algebraic but if the formal scheme is not a usual scheme, it is not unital, therefore its abstract nature differs essentially from that of the derived category of a usual scheme.Comment: v2: 31 pages, some improvements in exposition; v3 updated bibliography, to appear Adv. Mat

Modular Planar Antenna at X-band for satellite communications

An antenna which has been conceived as a portable system for satellite communications based on the recommendations ITU-R S.580-6 [1] and ITU-R S.465-5 [2] for small antennas, i.e., with a diameter lower than 50 wavelengths, is introduced. It is a planar and a compact structure with a size of 40×40×2 cm. The antenna is formed by an array of 256 printed elements covering a large bandwidth (14.7%) at X-Band. The specification includes transmission (Tx) and reception (Rx) bands simultaneously. The printed antenna has a radiation pattern with a 3dB beamwidth of 5°, over a 31dBi gain, and a dual and an interchangeable circular polarizatio

Stochastic reserving with a stacked model based on a hybridized Artificial Neural Network

Currently, legal requirements demand that insurance companies increase their emphasis on monitoring the risks linked to the underwriting and asset management activities. Regarding underwriting risks, the main uncertainties that insurers must manage are related to the premium sufficiency to cover future claims and the adequacy of the current reserves to pay outstanding claims. Both risks are calibrated using stochastic models due to their nature. This paper introduces a reserving model based on a set of machine learning techniques such as Gradient Boosting, Random Forest and Artificial Neural Networks. These algorithms and other widely used reserving models are stacked to predict the shape of the runoff. To compute the deviation around a former prediction, a log-normal approach is combined with the suggested model. The empirical results demonstrate that the proposed methodology can be used to improve the performance of the traditional reserving techniques based on Bayesian statistics and a Chain Ladder, leading to a more accurate assessment of the reserving risk