Towards Formal Interaction-Based Models of Grid Computing Infrastructures

Grid computing (GC) systems are large-scale virtual machines, built upon a massive pool of resources (processing time, storage, software) that often span multiple distributed domains. Concurrent users interact with the grid by adding new tasks; the grid is expected to assign resources to tasks in a fair, trustworthy way. These distinctive features of GC systems make their specification and verification a challenging issue. Although prior works have proposed formal approaches to the specification of GC systems, a precise account of the interaction model which underlies resource sharing has not been yet proposed. In this paper, we describe ongoing work aimed at filling in this gap. Our approach relies on (higher-order) process calculi: these core languages for concurrency offer a compositional framework in which GC systems can be precisely described and potentially reasoned about.Comment: In Proceedings DCM 2013, arXiv:1403.768

Puesta en valor de infraestructuras logísticas con utilización de la metodología DAFO-Delphi-CAME. El caso de la plataforma logística ferroviaria de Albacete.

La metodología empresarial que se presenta en este artículo refleja un análisis metodológico completo para la evaluación de la situación o punto de partida de una empresa, o en este caso una plataforma logística ferroviaria; y las actuaciones y estrategias que se deben seguir para lograr los objetivos propuestos. Se realiza mediante un panel de expertos previo para conocer la situación y delimitar los aspectos a tener en cuenta en el análisis DAFO. Posteriormente se ponderan numéricamente, enfrentado los aspectos del DAFO para obtener un resultado por enfrentamientos y cuadrantes (Panel Delphi). Con ello, y un análisis empresarial CAME se delimitan las estrategias a seguir de los dos cuadrantes significativos (mayor y menor en puntuación). Esta metodología ha sido utilizada satisfactoriamente en el caso de la plataforma logística ferroviaria de Albacete

Special Issue: Infant and Child Nutrition and Foods

Milk is a natural fluid and as such contains small amounts of naturally occurring steroids. Human milk is recommended as the optimal source of nutrients for infants and young children, and it has been associated to several short- and long-term benefits. For this reason, its composition is used as a reference for designing infant formulas. However, the available information on the hormonal levels of these dairy products is scarce, and it is usually limited to estradiol and estrone. In the present study, six natural sex hormones (pregnenolone, progesterone, estrone, dehydroepiandrosterone, testosterone and androstenedione) have been extracted from sixteen milk-based infant formulas and analyzed with liquid chromatography tandem mass spectrometry (HPLC-MS/MS). The purpose of this research was to quantify natural steroid hormones in various infant formulas, to provide food and nutrition practitioners with information to estimate intakes in children. In addition, data found in the literature was used for comparison. The findings suggest that there are certain similarities between bovine milk and dairy products for infants. Furthermore, the detected levels were in general lower than those observed in human milk and/or colostrum. The reported results represent a valuable addition to the current knowledge on natural hormone content of infant foods

A dark energy multiverse

We present cosmic solutions corresponding to universes filled with dark and phantom energy, all having a negative cosmological constant. All such solutions contain infinite singularities, successively and equally distributed along time, which can be either big bang/crunchs or big rips singularities. Classicaly these solutions can be regarded as associated with multiverse scenarios, being those corresponding to phantom energy that may describe the current accelerating universe

Do directionality effects influence expected damage? A case study of the 2017 central Mexico earthquake

We analyze the case of a building that collapsed in a multifamily complex of Tlalpan borough in Mexico City during the 19 September 2017 Central Mexico earthquake. Despite having similar materials and similar structural and geometric properties, this was the only building that collapsed in the complex. A structural analysis of the building and a study of the soils’ predominant periods indicated that resonance effects, if any, would not be significant. However, phenomena related to the anomalous performance of buildings in dense urban areas such as geological soil, soil–structure interaction, and soil–city interaction effects were also investigated. A detailed analysis of the directionality of seismic actions recorded at nearby accelerometric stations and of the azimuths of sound and damaged buildings indicates that directionality effects were responsible for the collapse of the building. Subsequently, a set of 58, two-component acceleration records of the earthquake was used to perform a thorough directionality analysis. The results were then compared with the foreseen uniform hazard response spectra and the design spectra in the city. Seismic actions in the city due to this earthquake were stronger than those corresponding to the uniform hazard response spectra. In addition, although design spectra have been significantly improved in the new 2017 Mexican seismic regulations, they were exceeded in 11 of 58 analyzed spectra. In 4 of these 11 cases, the design spectra were exceeded due to directionality effects. These results confirm the necessity of considering directionality effects in damage assessments, strong-motion prediction equations, and design regulations.Peer ReviewedPostprint (author's final draft

Ocean acidification increases fatty acids levels of larval fish

Rising levels of anthropogenic carbon dioxide in the atmosphere are acidifying the oceans and producing diverse and important effects on marine ecosystems, including the production of fatty acids (FAs) by primary producers and their transfer through food webs. FAs, particularly essential FAs, are necessary for normal structure and function in animals and influence composition and trophic structure of marine food webs. To test the effect of ocean acidification (OA) on the FA composition of fish, we conducted a replicated experiment in which larvae of the marine fish red drum (Sciaenops ocellatus) were reared under a climate change scenario of elevated CO levels (2100 matm) and under current control levels (400 matm). We found significantly higher whole-body levels of FAs, including nine of the 11 essential FAs, and altered relative proportions of FAs in the larvae reared under higher levels of CO. Consequences of this effect of OA could include alterations in performance and survival of fish larvae and transfer of FAs through food webs.CDG was funded by FPI‐INIA-2012, this manuscript was financed by the research project REC2  (grant#CTM2011‐23835). Contribution 1705 of the University of Texas Marine Science InstitutePeer Reviewe

Modeling of energy efficiency for residential buildings using artificial neuronal networks

The energy efficiency dataset used to support the findings of this study has been deposited in the GitHub repository https://github.com/mereshow/ann-energy-efficiency.git.[Abstract] Increasing the energy efficiency of buildings is a strategic objective in the European Union, and it is the main reason why numerous studies have been carried out to evaluate and reduce energy consumption in the residential sector. The process of evaluation and qualification of the energy efficiency in existing buildings should contain an analysis of the thermal behavior of the building envelope. To determine this thermal behavior and its representative parameters, we usually have to use destructive auscultation techniques in order to determine the composition of the different layers of the envelope. In this work, we present a nondestructive, fast, and cheap technique based on artificial neural network (ANN) models that predict the energy performance of a house, given some of its characteristics. The models were created using a dataset of buildings of different typologies and uses, located in the northern area of Spain. In this dataset, the models are able to predict the U-opaque value of a building with a correlation coefficient of 0.967 with the real U-opaque measured value for the same building

Back to the future: restoring historical communities

En prens

Experiencia con un repositorio de ejercicios de programación en un campus virtual: de una colección de libre acceso a otra guiada por la progresión del estudiante

El Campus Virtual es el entorno en el que se ha implementado una Virtualización de Casos Prácticos para facilitar el aprendizaje activo de la materia “Introducción a la programación” en la Universidad Complutense de Madrid. El carácter multidisciplinar de esta colección de casos prácticos los hace útiles en diversas titulaciones de la citada universidad. En este artículo se presenta la evolución que ha experimentado la Virtualización de Casos Prácticos, desde una colección de libre acceso a contenidos hasta la actual con un acceso controlado por la progresión del estudiante.Peer Reviewe