Toward partial redirection of energy policy for responsible development

This paper addresses the surprising lack of quality control on the analysis and selection on energy policies observable in the last decades. As an example, we discuss the delusional idea that it is possible to replace fossil energy with large scale ethanol production from agricultural crops. But if large scale ethanol production is not practical in energetic terms, why huge amount of money has been invested in it and is it still being invested? In order to answer this question we introduce two concepts useful to frame, in general terms, the predicament of quality control in science: (i) the concept of “granfalloons” proposed by K. Vonnegut (1963) flagging the danger of the formation of “crusades to save the world” void of real meaning. These granfalloons are often used by powerful lobbies to distort policy decisions; and (ii) the concept of Post-Normal science by S. Funtowicz and J. Ravetz (1990) indicating a standard predicament faced by science when producing information for governance. When mixing together uncertainty, multiple-scale and legitimate but contrasting views it becomes impossible to deal with complex issue using the conventional scientific approach based on reductionism. We finally discuss the implications of a different approach to the assessment of alternative energy sources by introducing the concept of Promethean technology.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Angular distributions of leptons from J/ ψ's produced in 920 GeV fixed-target proton-nucleus collisions

A study of the angular distributions of leptons from decays of J/ψ"s produced in p-C and p-W collisions at s√=41.6~GeV has been performed in the J/ψ Feynman-x region −0.341 GeV/c a significant dependence on the reference frame is found: the polar anisotropy is more pronounced in the Collins-Soper frame and almost vanishes in the helicity frame, where, instead, a significant azimuthal anisotropy arises.

Reconstruction of Fresnel Holograms using partial wave front information

n this work we analyze the behavior of complex information in Fresnel domain taking into account the limited capability to display complex transmittance values of current liquid crystal devices, when used as holographic displays. In order to do this analysis we compute the reconstruction of Fresnel holograms at several distances using the different parts of the complex distribution (real and imaginary parts, amplitude and phase) as well as using the full complex information adjusted with a method that combines two configurations of the devices in an adding architecture. The RMS error between the amplitude of these reconstructions and the original amplitude is used to evaluate the quality of the information displayed. The results of the error analysis show different behavior for the reconstructions using the different parts of the complex distribution and using the combined method of two devices. Better reconstructions are obtained when using two devices whose configurations densely cover the complex plane when they are added. Simulated and experimental results are also presented.

Beyond pure public and pure private management models: Partial privatization in the European airport industry

The use of private funding and management is enjoying an increasing trend in airports. The literature has not paid enough attention to the mixed management models in this industry, although many European airports take the form of mixed public-private companies, where ownership is shared between public and private sectors. We examine the determinants of the degree of private participation in the European airport sector. Drawing on a sample of the 100 largest European airports, we estimate a multivariate equation in order to determine the role of airport characteristics, fiscal variables, and political factors on the extent of private involvement. Our results confirm the alignment between public and private interests in partially privatized airports. Fiscal constraints and market attractiveness promote private participation. Integrated governance models and the share of network carriers prevent the presence of private ownership, while the degree of private participation appears to be pragmatic rather than ideological.