We present a homogeneous set of stellar atmospheric parameters (Teff, logg, [Fe/H]) for a sample of about 700 field and cluster stars which constitute a new stellar library in the near-IR developed for stellar population synthesis in this spectral region (λ8350-9020). Having compiled the available atmospheric data in the literature for field stars

A new stellar library at the near-IR spectral region developed for the empirical calibration of the Caii triplet and stellar population synthesis modelling is presented. The library covers the range λλ8348-9020 at 1.5-Å (FWHM) spectral resolution, and consists of 706 stars spanning a wide range in atmospheric parameters. We have defined a new set

The goal of this paper is to present the Transmission Matrix of the SPI Mask STM/QM Model. The experimental set-up used to determine INTEGRAL Spectrometer (SPI) Mask Transmission Matrix is hereafter described: collimation system, radioactive sources, energy ranges covered and pitch angles covering the expected SPI Field of View. The QM results

We present the results of the multisite differential CCD photometry for the two delta Scuti stars, BN and BV Cnc, in the open cluster Praesepe. The main objective was to identify the character of the pulsation modes in BN Cnc deriving their accurate periods, amplitudes and phases. These parameters are essential for the mode identification which

Recent observations of galaxy luminosity profiles and dark matter simulations find luminosity and mass distributions characterized by central cusps rather than finite core radii. We introduce and implement a set of cusped ellipsoidal lens models that include limits similar to the Jaffe, Hernquist, η and NFW models and apply them to the

Evolutionary synthesis models are a fundamental tool to interpret the properties of observed stellar systems. In order to achieve a meaningful comparison between models and real data, it is necessary to calibrate the models themselves, i.e. to evaluate the dispersion due to the discreteness of star formation as well as the possible model errors. In