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Big Data offers opportunities in many fields. Healthcare is not an exception. In this paper we summarize the possibilities of Big Data and Big Data technologies to offer useful information to policy makers. In a world with tight public budgets and ageing populations we feel necessary to save costs in any production process. The use of outcomes from Big Data could be in the future a way to improve decisions at a lower cost than today. In addition to list the advantages of properly using data and technologies from Big Data, we also show some challenges and risks that analysts could face. We also present an hypothetical example of the use of administrative records with health information both for diagnoses and patients.

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This paper deals with the optimization of technical indicators for stock market investment. Price prediction is a problem of great complexity and usually some technical indicators are used to predict the markets trends. The main difficulty in the use of technical indicators lies in deciding the parameters values. We proposed the use of Evolutionary Algorithms (EAs) to obtain the best parameter values belonging to a collection of indicators that will help in the buying and selling of shares. This paper extends the work presented on previous works by including additional indicators and applying them to more complex problems. In this way the Moving Averages Convergence-Divergence (MACD) indicator and the Relative Strength Index (RSI) oscillator have been selected to obtain the buying/selling signals. The experimental results indicate that our EAs offer a solution to the problem obtaining results that improve those obtained through technical indicators with their standard parameters.

-The growing demand for affordable, reliable, domestically sourced, and low-carbon electricity is a matter of concern and it is driven by several causes including public policy priorities. Policy objectives and new technologies are changing wholesale market design. The analysis of different aspects of energy markets is increasingly on the agendas of academics, firms' managers or policy makers. Some concerns are global and are related to the evolution of climate change phenomena. Others are regional or national and they strongly appear in countries like Spain with a high dependence on foreign energy sources and high potential of domestic renewable energy sources. We can find a relevant case in Spanish solar energy policy. A series of regulatory reforms since 2010 reduce revenues to existing renewable power generators and they end up the previous system of support to new renewable generation. This policy change has altered the composition of the energy market affecting investment decisions.In this paper, we analyze the public opinion about energy policy of the Spanish Government using the Global Database of Events, Language, and Tone (GDELT). The GDELT Project consists of over a quarter-billion event records in over 300 categories covering the entire world from 1979 to present, along with a massive network diagram connecting every person, organization, location, and theme to this event database. Our aim is to build sentiment indicators arising from this source of information and, in a final step, evaluate if positive and negative indexes have any effect on the evolution of key market variables as prices and demand.