Link prediction in very large directed graphs: Exploiting hierarchical properties in parallel

Link prediction is a link mining task that tries to find new edges within a given graph. Among the targets of link prediction there is large directed graphs, which are frequent structures nowadays. The typical sparsity of large graphs demands of high precision predictions in order to obtain usable results. However, the size of those graphs only permits the execution of scalable algorithms. As a trade-off between those two problems we recently proposed a link prediction algorithm for directed graphs that exploits hierarchical properties. The algorithm can be classified as a local score, which entails scalability. Unlike the rest of local scores, our proposal assumes the existence of an underlying model for the data which allows it to produce predictions with a higher precision. We test the validity of its hierarchical assumptions on two clearly hierarchical data sets, one of them based on RDF. Then we test it on a non-hierarchical data set based on Wikipedia to demonstrate its broad applicability. Given the computational complexity of link prediction in very large graphs we also introduce some general recommendations useful to make of link prediction an efficiently parallelized problem.Peer ReviewedPostprint (published version

Evidence of chaotic modes in the analysis of four delta Scuti stars

Since CoRoT observations unveiled the very low amplitude modes that form a flat plateau in the power spectrum structure of delta Scuti stars, the nature of this phenomenon, including the possibility of spurious signals due to the light curve analysis, has been a matter of long-standing scientific debate. We contribute to this debate by finding the structural parameters of a sample of four delta Scuti stars, CID 546, CID 3619, CID 8669, and KIC 5892969, and looking for a possible relation between these stars' structural parameters and their power spectrum structure. For the purposes of characterization, we developed a method of studying and analysing the power spectrum with high precision and have applied it to both CoRoT and Kepler light curves. We obtain the best estimates to date of these stars' structural parameters. Moreover, we observe that the power spectrum structure depends on the inclination, oblateness, and convective efficiency of each star. Our results suggest that the power spectrum structure is real and is possibly formed by 2-period island modes and chaotic modes

Reducing fall risk with combined motor and cognitive training in elderly fallers

Background. Falling is a major clinical problem in elderly people, demanding effective solutions. At present, the only effective intervention is motor training of balance and strength. Executive function-based training (EFt) might be effective at preventing falls according to evidence showing a relationship between executive functions and gait abnormalities. The aim was to assess the effectiveness of a motor and a cognitive treatment developed within the EU co-funded project I-DONT-FALL. Methods. In a sample of 481 elderly people at risk of falls recruited in this multicenter randomised controlled trial, the effectiveness of a motor treatment (pure motor or mixed with EFt) of 24 one-hour sessions delivered through an i-Walker with a non-motor treatment (pure EFt or control condition) was evaluated. Similarly, a 24 one-hour session cognitive treatment (pure EFt or mixed with motor training), delivered through a touch-screen computer was compared with a non-cognitive treatment (pure motor or control condition). Results. Motor treatment, particularly when mixed with EFt, reduced significantly fear of falling (F(1,478) = 6.786, p = 0.009) although to a limited extent (ES -0.25) restricted to the period after intervention. Conclusions. This study suggests the effectiveness of motor treatment empowered by EFt in reducing fear of falling.Peer ReviewedPostprint (published version

Wind energy forecasting with neural networks: a literature review

Renewable energy is intermittent by nature and to integrate this energy into the Grid while assuring safety and stability the accurate forecasting of there newable energy generation is critical. Wind Energy prediction is based on the ability to forecast wind. There are many methods for wind forecasting based on the statistical properties of the wind time series and in the integration of meteorological information, these methods are being used commercially around the world. But one family of new methods for wind power fore castingis surging based on Machine Learning Deep Learning techniques. This paper analyses the characteristics of the Wind Speed time series data and performs a literature review of recently published works of wind power forecasting using Machine Learning approaches (neural and deep learning networks), which have been published in the last few years.Peer ReviewedPostprint (published version

The envelope of the power spectra of over a thousand \delta Scuti stars. The Tˉeff\bar{T}_{eff}-νmax\nu_{max} scaling relation

CoRoT and Kepler high-precision photometric data allowed the detection and characterization of the oscillation parameters in stars other than the Sun. Moreover, thanks to the scaling relations, it is possible to estimate masses and radii for thousands of solar-type oscillating stars. Recently, a \Delta\nu - \rho relation has been found for \delta Scuti stars. Now, analyzing several hundreds of this kind of stars observed with CoRoT and Kepler, we present an empiric relation between their frequency at maximum power of their oscillation spectra and their effective temperature. Such a relation can be explained with the help of the \kappa-mechanism and the observed dispersion of the residuals is compatible with they being caused by the gravity-darkening effect

Heterotopies of contemporary landscape

Los aspectos tecnológicos que definen nuestro tiempo tienen especial relevancia en la forma de relacionarnos con el paisaje y percibir los elementos que definen nuestra experiencia como parte integrante de un espacio heterotópico. En un plano en que la información visual que nos ofrecen los dispositivos virtuales cotidianos sobre referencias geográficas es capaz de sustituir la percepción polisensorial que proporciona la experiencia on site, el arte actúa como ventana hacia nuevas formas de interpretación sobre las confluencias, hibridaciones y desencuentros que se producen en la interrelación de la multiplicidad de datos que construyen diferentes enfoques y el artista produce nuevas herramientas topográficas, ya que la geografía es también asunto suyo y pretende, de este modo, acercarse al paisaje desde la poética y la crítica.The technological aspects that define our time have special relevance in the way we relate to the landscape and perceive the elements that make up our experience our experience as an integral part of a heterotopic space. In a plane in which the visual information offered by everyday virtual devices on geographical references is able to replace the polysensory perception that the on‐site experience provides, art acts as a window towards new forms of interpretation on the confluences, hybridizations and disagreements that they occur in the interrelation of the multiplicity of data that build different approaches and the artist produces new topographical tools, since geography is also geography also concerns him and aims, in this way, to approach the landscape from poetics and criticism

Generación de un modelo celular de síndrome PAPA utilizando la técnica CRISPR/Cas9.

Con los datos proporcionados previamente, podemos definir como objetivo del trabajo la obtención de un modelo celular del síndrome PAPA, analizando los efectos a pequeña escala de las mutaciones que provocan la enfermedad, usando una línea celular de estirpe monocítica. Para ello se seleccionan las dos mutaciones más recurrentes encontradas en pacientes con el síndrome PAPA (A230T y E250Q), y se introducen en una línea celular humana a través del sistema de endonucleasas CRISPR/Cas9. Para este fin, se plantean los siguientes objetivos: - Construcción de vectores que contengan el gen de la nucleasa Cas9 nickasa y las secuencias guía específicas, con el fin de obtener cortes de cadena simple en lugares específicos del genoma en el gen CD2BP1 en las células diana. - Construcción de dos plásmidos donantes que contengan parte del gen CD2BP1 con sendas mutaciones que causan el síndrome PAPA. - Introducción de los plásmidos CRISPR junto con los plásmidos donantes en células THP-1 mediante nucleofección. - Selección de los clones celulares modificados que incorporan la mutación mediante PCR y dilución límite.Instituto de Biología y Genética Molecular (IBGM)Máster en Investigación Biomédic

Never retreat, never surrender: The bargaining power of commitment in the Hawk-Dove game

This paper studies experimentally the conditions that improve bargaining power using threats in a negotiation process. Following Schelling’s (1960) ideas we choose the hawk-dove game because is the simplest negotiation environment with inequity distribution in equilibrium. The analysis is focused on three essential elements of commitment: the possibility of a player to announce his own actions, the credibility of these messages and the experience acquired in the negotiation process. The empirical evidence shows that, in the first period, subjects do not realize the bargaining power of commitment. When the game is repeated and experience increases, subjects gradually understand the advantages of a threat, turning the payoffs into their favor. Credibility is also relevant for the relation, if subjects can choose their message, it is common to find strategic liars, and their rivals punish this behavior.Credible threats, negotiation, experiments

Sustainable limestone and EAF aggregate concretes through particle packing models (PPMs) and life cycle assessment (LCA)

V.I. 226p. V.II 131 p.In view of the current concern about environmental problems, the use of slags from the Electric Arc Furnace (EAF) as aggregates in the concrete has been proved to be successful for multiple applications avoiding the use of natural aggregates. Hence, the range of aggregates available for designing concretes is continuously growing.The main objective of this thesis is to design economic and environmentally sustainable concrete mixes made with natural limestone (NL) aggregates and electric arc furnace (EAF) aggregate through a particle packing density perspective without compromising their compressive strength and workability.In order to verify the potential of particle packing theories to design more economical and environmentally sustainable NL aggregate and EAF aggregate concrete mixes, two traditional optimal curves and two current discrete packing models were validated with experimental packing results to demonstrate its feasibility in the prediction of the most compacted structure. Several (17) NL and EAF aggregate concrete mixes were then designed by varying the aggregate proportion and the content of cement paste to analyse the effect of aggregate packing density on the fresh and hardened concrete properties. Finally, the economic and environmental impact of the different concrete mixes were assessed to evaluate the potential of the particle packing methods in the development of more sustainable concrete.It was concluded that the concrete mixtures designed by maximizing the coarse aggregates content in the range of the maximum packing density present the highest compressive strength and workability and the low environmental and economic impact. In addition, due to the higher compressive strength and the low contribution of aggregate in the concrete environmental impact, the EAF aggregate concrete contributes to a greater reduction of the environmental and economic impact.Tecnali

Facts and limits of the AI. An ELSEC Approach

Ética en la investigación con inteligencia artificial y “big data”. Ulises Cortés García. Catedrático e investigador de la Universidad Politécnica de Cataluña. Director científico del Grupo de Inteligencia Artificial de Alto Rendimiento del Centro de Supercomputación de Barcelona.N