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This paper investigates the processing of Frequency Modulated-Continuos Wave (FM-CW) radar signals for vehicle classification. In the last years deep learning has gained interest in several scientific fields and signal processing is not one exception. In this work we address the recognition of the vehicle category using a Convolutional Neural Network (CNN) applied to range Doppler signature. The developed system first transforms the 1-dimensional signal into a 3-dimensional signal that is subsequently used as input to the CNN. When using the trained model to predict the vehicle category we obtain good performance.

The present work aims to assess the hazard for human health related to CO 2 anomalous concentrations in air emitted from dry gas vents located in the NE area of Mt. Amiata volcano (Tuscany, central Italy). A geochemical multi-methodological approach is adopted to determine the composition and the flux rate of the gas discharges in order to establish (1) the origin of the gas vents and (2) the behaviour of the discharged gases in the areas surrounding the emission sites. The gas vents are hosted within subcircular morphological depressions (∅∼10-30 m), which likely originated by the collapse of cavities formed at shallow depth in the ground by dissolution of Triassic anhydrite formations and recent travertine deposits. CaCO 3 and CaSO 4 dissolution is mainly related to the underground circulation of CO 2 -rich fluids whose hydrological pattern is regulated by local and regional tectonics. The CO 2 -rich (up to 996,070 μmol/mol) gases tend to accumulate within the topographic lows, thus creating a sort of CO 2 ponds, and the knowledge of their evolution in time and space is important to evaluate the related hazard. Consequently, a conceptual model of CO 2 diffusion in air is developed to understand the dynamic of the CO 2 accumulation/dispersion process based on (1) a 24-h continuous measurement of the CO 2 flux from one of the main emission sites and (2) the recording of the main meteoric parameters, i.e. air temperature, wind direction and speed to check their influence. The results indicate that the threshold of CO 2 concentrations considered dangerous for the human health is frequently overcome. Moreover, when meteoric conditions, i.e. low wind and cloudy weather, did not allow a rapid dispersion of the gas phase emitted from the dry vents, CO 2 -rich clouds periodically overflowed the morphological depressions for several tens of meters without any significant mixing with air. On the basis of these considerations, the monitoring of the output rate from the main gas emissions, combined with the continuous control of the local meteorological parameters, may be considered an efficient procedure to mitigate the CO 2 hazard deriving from dry gas vents. An improvement of the protocol can be achieved in case of installations of CO 2 sensors located in the most sensitive areas and Water Air Soil Pollut: Focus (

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