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The paper deals with the problem of choosing the best O&M strategy for wind power plants. Current maintenance theory considers just production opportunities and minimizes the maintenance costs, but with the liberalization of the electricity market also the electricity price has become an important variable to take into account in the O&M scheduling. Another important variables that is often neglected by the existing maintenance theory is the weather condition. This paper proposes a new strategy that takes into account the electricity price and weather conditions, improves the expected profit of the systems, and reduce the overall maintenance and logistic costs. The maintenance schedule is formalized as an optimization problem where the discounted cumulative profit of a wind generation portfolio in a fixed-time horizon (e.g. two years ahead), subject to the technologically-derived maintenance time constraints is optimized. Both the theoretical and computational aspects of the proposed O&M strategy are discussed. Results show that taking into account market and weather opportunities in the design of the maintenance strategy, it is possible to achieve a more complete scheduling for a given set of wind power plants.

This article treats statues held in the Museum of Egyptian Antiquities in Turin that were discovered in Egypt by Jean Jacques Rifaud on behalf of the French consul Bernardino Drovetti. Research undertaken in Geneva on the unpublished manuscripts of Rifaud, as part of a PhD on the statues in the Turin museum, has permitted, as a first step, important information regarding the location of the standing statues of the goddess Sekhmet to be brought to light; in his report on the excavation, Rifaud says that he found the standing statues in the temple of Ptah, located north of the sacred precinct of the temple of Amun-Re at Karnak.

In this paper, an information-based multi-assets arti¯cial stock market is presented. The market is populated by heterogeneous agents that are seen as nodes of sparsely connected graphs. The market is characterized by di®erent types of stocks and agents trade risky assets in exchange for cash. Beside the amount of cash and of stocks owned, each agent is characterized by sentiments. Moreover, agents share their sentiments by means of interactions that are determined by graphs. A central market maker (clearing house mechanism) determines the price processes for each stock at the intersection of the demand and the supply curves. Within this frame- work, stock price processes exhibit volatility clustering and fat-tailed distribution of returns. Moreover, the cross-correlations between returns of di®erent stocks is studied using methods of random matrix theory. The probability distribution of eigenvalues of the cross-correlation matrix shows the presence of outliers, similar to those recently observed on real data for business sectors. These results suggest a signi¯cant structural in°uence on statistical properties of multi-assets stock market.