Preparation, characterisation and testing of CuO/Ce0.8Zr0.2O2 catalysts for NO oxidation to NO2 and mild temperature diesel soot combustion

CuO/ceria-zirconia catalysts have been prepared, deeply characterised (N2 adsorption–desorption isotherms at −196 °C, XRD, Raman spectroscopy, XPS, TEM and H2-TPR) and tested for NO oxidation to NO2 in TPR conditions, and for soot combustion at mild temperature (400 °C) in a NOx/O2 stream. The behaviour has been compared to that of a reference Pt/alumina commercial catalyst. The ceria-zirconia support was prepared by the co-precipitation method, and different amounts of copper (0.5, 1, 2, 4 and 6 wt%) were loaded by incipient wetness impregnation. The results revealed that copper is well-dispersed onto the ceria-zirconia support for the catalysts with low copper loading and CuO particles were only identified by XRD in samples with 4 and 6% of copper. A very low loading of copper increases significantly the activity for the NO oxidation to NO2 with regard to the ceria-zirconia support and an optimum was found for a 4% CuO/ceria-zirconia composition, showing a very high activity (54% at 348 °C). The soot combustion rate at 400 °C obtained with the 2% CuO/ceria-zirconia catalyst is slightly lower to that of 1% Pt/alumina in terms of mass of catalyst but higher in terms of price of catalyst.

Computational approaches to subjectivity and sentiment analysis: Present and envisaged methods and applications

Recent years have witnessed a surge of interest in computational methods for affect, ranging from opinion mining, to subjectivity detection, to sentiment and emotion analysis. This article presents a brief overview of the latest trends in the field and describes the manner in which the articles contained in the special issue contribute to the advancement of the area. Finally, we comment on the current challenges and envisaged developments of the subjectivity and sentiment analysis fields, as well as their application to other Natural Language Processing tasks and related domains.

Export and import market-specific characteristics. How they drive the decision to trade and how much

Using a rich firm-level dataset on the Italian manufacturing industry, this paper provides a comprehensive analysis of the role that firms and market characteristics play in shaping firms’ trade activities. We enhance the previous analyses by considering firms’ engagement in international transactions, by focusing on either exports or imports. We show that the determinants of a firm’s export participation and value across countries also drive import behavior. Our research is consistent with the presence of country-specific sunk costs and with a qualitatively similar role of gravity forces and other country attributes on both sides of trading activities. Our evidence, however, militates in favor of a framework where variations in market characteristics have a larger impact on imports than exports.