Superconductivity in a magnetically ordered background

Borocarbide compounds with the formula RNi2B2C show interesting superconducting and magnetic properties and the coexistence of the two phenomena. BCS theory is extended to systems with underlying commensurate magnetic order. In the case of helical phases the technique may be extended to any Q-vector and there exists a well defined limit for incommensurate values. The way magnetic order influences superconductivity depends crucially on the details of both the magnetic structure and the electron bands, but some qualitative criteria may be given. As an example we give a brief analysis of the compound HoNi2B2C.Comment: 3 pages, 1 figure, proceedings to the conference "Anomalous Complex Superconductors", Crete 199

Gravitational clustering in N-body simulations

In this talk we discuss some of the main theoretical problems in the understanding of the statistical properties of gravity. By means of N-body simulations we approach the problem of understanding the r\^ole of gravity in the clustering of a finite set of N-interacting particles which samples a portion of an infinite system. Through the use of the conditional average density, we study the evolution of the clustering for the system putting in evidence some interesting and not yet understood features of the process.Comment: 5 pages, 1 figur

Clustering in N-Body gravitating systems

Self-gravitating systems have acquired growing interest in statistical mechanics, due to the peculiarities of the 1/r potential. Indeed, the usual approach of statistical mechanics cannot be applied to a system of many point particles interacting with the Newtonian potential, because of (i) the long range nature of the 1/r potential and of (ii) the divergence at the origin. We study numerically the evolutionary behavior of self-gravitating systems with periodical boundary conditions, starting from simple initial conditions. We do not consider in the simulations additional effects as the (cosmological) metric expansion and/or sophisticated initial conditions, since we are interested whether and how gravity by itself can produce clustered structures. We are able to identify well defined correlation properties during the evolution of the system, which seem to show a well defined thermodynamic limit, as opposed to the properties of the ``equilibrium state''. Gravity-induced clustering also shows interesting self-similar characteristics.Comment: 6 pages, 5 figures. To be published on Physica

Theoretical model for the superconducting and magnetically ordered borocarbides

We present a theory of superconductivity in presence of a general magnetic structure in a form suitable for the description of complex magnetic phases encountered in borocarbides. The theory, complemented with some details of the band structure and with the magnetic phase diagram, may explain the nearly reentrant behaviour and the anisotropy of the upper critical field of HoNi2B2C. The onset of the helical magnetic order depresses superconductivity via the reduction of the interaction between phonons and electrons caused by the formation of magnetic Bloch states. At mean field level, no additional suppression of superconductivity is introduced by the incommensurability of the helical phase.Comment: 8 pages, 2 figures. Published version, one important reference adde

Estimation of Signal to Noise Ratio for Unsupervised Hyperspectral Images

Hyperspectral sensors have become a standard technology used in the techniques of observation by satellite and aerial platform for observing the terrestrial ecosystem with particular interest in the detection and identification of minerals, vegetation, materials and artificial environments. The detection of real materials depends on the coverage spectral resolution and signal to noise ratio of the spectrometer itself, as well as the density of the material and the absorption characteristics for the material in the region of wavelength measured. The signal to noise ratio in particular is one of the parameters that need to be estimated to establish the quality of images acquired by these systems. In this contribution a method to estimate the Signal to Noise Ratio (SNR) for unsupervised hyperspectral images has been investigated. The method uses the computation of local means and local standard deviations of small homogeneous blocks in order to define respectively the average signal and the mean noise of the images. If the noise may be considered mainly addictive the local standard deviation may be considered as the mean noise of image. This method uses all the spatial information contained in the image scene giving a representative SNR of entire image. The technique has been engineered in IDL environment and applied to hyperspectral data of HYPER-SIMGA sensor, developed in the frame of AIRFIRE Project for wildfire detection by airborne remote sensing data. The SNR results point out that HYPER-SIMGA SWIR images are quite noisy and the spectral range that has to be taken into account for data analysis is from 1000 to 1700 nm

Study on the presence and perception of coypu (Myocastor coypus Molina, 1782) in three areas of Lazio region (Italy)

Adriani, S., Bonanni, M., Amici, A

Is the Italian strategy to face the problem of stray dogs sustainable? A case study of two small municipalities in central Italy

Adriani, S., Bonanni, M., Amici, A