Use of prediction methods for patent and trademark applications in Spain

Patent and trademark offices which run according to principles of new management have an inherent need for dependable forecasting data in planning capacity and service levels. The ability of the Spanish Office of Patents and Trademarks to carry out efficient planning of its resource needs requires the use of methods which allow it to predict the changes in the number of patent and trademark applications at different time horizons. The approach for the prediction of time series of Spanish patents and trademarks applications (1979e2009) was based on the use of different techniques of time series prediction in a short-term horizon. The methods used can be grouped into two specifics areas: regression models of trends and time series models. The results of this study show that it is possible to model the series of patents and trademarks applications with different models, especially ARIMA, with satisfactory model adjustment and relatively low error.

Downscaling of global solar irradiation in R

A methodology for downscaling solar irradiation from satellite-derived databases is described using R software. Different packages such as raster, parallel, solaR, gstat, sp and rasterVis are considered in this study for improving solar resource estimation in areas with complex topography, in which downscaling is a very useful tool for reducing inherent deviations in satellite-derived irradiation databases, which lack of high global spatial resolution. A topographical analysis of horizon blocking and sky-view is developed with a digital elevation model to determine what fraction of hourly solar irradiation reaches the Earth's surface. Eventually, kriging with external drift is applied for a better estimation of solar irradiation throughout the region analyzed. This methodology has been implemented as an example within the region of La Rioja in northern Spain, and the mean absolute error found is a striking 25.5% lower than with the original database.

Origin of the gases released from the Acqua Passante and Ermeta wells (Mt. Amiata, central Italy) and possible environmental implications for their closure

The Mt. Amiata volcano (Tuscany, central Italy) hosts the second largest geothermal field of Italy. Its SW and NE sectors are characterized by the presence of several CO2-rich (mayor que95% by vol.) gas discharges. An intense Hg mining activity had taken place from the 19th century up to the end of the ?70s, particularly close to Abbadia San Salvatore, during which two drillings (Acqua Passante and Ermeta) intercepted a CO2-rich gas fertile horizon. The related gases are emitted in the atmosphere since 1938 and 1959, respectively, causing severe concerns for the local air quality. In this work the results of a geochemical and isotopic survey carried out on these gas emissions from March 2009 to January 2014 are presented. CO2 fluxes from both the two wells and soil from an area of about 653,500 m2 located between them were measured. The two wells are emitting up to 15,000, 92 and 8 tons y-1 of CO2, CH4 and H2S, respectively, while the computed soil CO2 output was estimated at 4,311 ton y-1. The spatial distribution of the CO2 soil flux suggests the presence of preferential patterns, indicating sites of higher permeability. Since the local municipality is evaluating the possibility to plug the Ermeta vent, a temporarily closure should first be carried out to test the possible influence of this operation on the diffuse soil degassing of deep-originated CO2 in the surrounding area. This implies that diffuse soil gases should carefully be monitored before proceeding with its definitive closure.