Applying transition rules to bitemporal deductive databases for integrity constraint checking

A bitemporal deductive database is a deductive database that supports valid and transaction time. A set of facts to be inserted and/or deleted in a bitemporal deductive database can be done in a past, present or future valid time. This circumstance causes that the maintenance of database consistency becomes more hard. In this paper, we present a new approach to reduce the difficulty of this problem, based on applying transition and event rules, which explicitly define the insertions and deletions given by a database update. Transition rules range over all the possible cases in which an update could violate some integrity contraint. Although, we have a large amount of transition rules, for each one we argue its utility or we eliminate it. We augment a database with this set of transition and event rules and then standard SLDNF resolution can be used to check satisfaction of integrity constraints.Peer ReviewedPostprint (author's final draft

Nidificación del Tadorna tadorna en Ibiza

Abstract not availabl

DReAM: Per-task DRAM energy metering in multicore systems

Interaction across applications in DRAM memory impacts its energy consumption. This paper makes the case for accurate per-task DRAM energy metering in multicores, which opens new paths to energy/performance optimizations, such as per-task energy-aware task scheduling and energy-aware billing in datacenters. In particular, the contributions of this paper are (i) an ideal per-task energy metering model for DRAM memories; (ii) DReAM, an accurate, yet low cost, implementation of the ideal model (less than 5% accuracy error when 16 tasks share memory); and (iii) a comparison with standard methods (even distribution and access-count based) proving that DReAM is more accurate than these other methods.This work has been partially supported by the Spanish Ministry of Science and Innovation under grant TIN2012-34557, the HiPEAC Network of Excellence, by the European Research Council under the European Union’s 7th FP, ERC Grant Agreement n. 321253, and by a joint study agreement between IBM and BSC (number W1361154). Qixiao Liu has also been funded by the Chinese Scholarship Council under grant 2010608015.Postprint (published version

DReAM: An approach to estimate per-Task DRAM energy in multicore systems

Accurate per-task energy estimation in multicore systems would allow performing per-task energy-aware task scheduling and energy-aware billing in data centers, among other applications. Per-task energy estimation is challenged by the interaction between tasks in shared resources, which impacts tasks’ energy consumption in uncontrolled ways. Some accurate mechanisms have been devised recently to estimate per-task energy consumed on-chip in multicores, but there is a lack of such mechanisms for DRAM memories. This article makes the case for accurate per-task DRAM energy metering in multicores, which opens new paths to energy/performance optimizations. In particular, the contributions of this article are (i) an ideal per-task energy metering model for DRAM memories; (ii) DReAM, an accurate yet low cost implementation of the ideal model (less than 5% accuracy error when 16 tasks share memory); and (iii) a comparison with standard methods (even distribution and access-count based) proving that DReAM is much more accurate than these other methods.Peer ReviewedPostprint (author's final draft

Average performance analysis of circular and hyperbolic geolocation

A comparative performance analysis of four geolocation methods in terms of their theoretical root mean square positioning errors is provided. Comparison is established in two different ways: strict and average. In the strict type, methods are examined for a particular geometric configuration of base stations(BSs) with respect to mobile position, which determines a given noise profile affecting the respective time-of-arrival (TOA) or timedifference- of-arrival (TDOA) estimates. In the average type, methods are evaluated in terms of the expected covariance matrix of the position error over an ensemble of random geometries, so that comparison is geometry independent. Exact semianalytical equations and associated lower bounds (depending solely on the noise profile) are obtained for the average covariance matrix of the position error in terms of the so-called information matrix specific to each geolocation method. Statistical channel models inferred from field trials are used to define realistic prior probabilities for the random geometries. A final evaluation provides extensive results relating the expected position error to channel model parameters and the number of base stations.Peer Reviewe

Frag’r’Us:Knowledge-based sampling of protein backbone conformations for de novo structure-based protein design

The remodeling of short fragment(s) of the protein backbone to accommodate new function(s), fine-tune binding specificities or change/create novel protein interactions is a common task in structure-based computational design. Alternative backbone conformations can be generated de novo or by redeploying existing fragments extracted from protein structures i.e. knowledge-based. We present Frag'r'Us, a web server designed to sample alternative protein backbone conformations in loop regions. The method relies on a database of super secondary structural motifs called smotifs. Thus, sampling of conformations reflects structurally feasible fragments compiled from existing protein structures. Availability and implementation Frag'r'Us has been implemented as web application and is available at http://www.bioinsilico.org/FRAGRUS

Gene Ontology Function prediction in Mollicutes using Protein-Protein Association Networks

<p>Abstract</p> <p>Background</p> <p>Many complex systems can be represented and analysed as networks. The recent availability of large-scale datasets, has made it possible to elucidate some of the organisational principles and rules that govern their function, robustness and evolution. However, one of the main limitations in using protein-protein interactions for function prediction is the availability of interaction data, especially for Mollicutes. If we could harness predicted interactions, such as those from a Protein-Protein Association Networks (PPAN), combining several protein-protein network function-inference methods with semantic similarity calculations, the use of protein-protein interactions for functional inference in this species would become more potentially useful.</p> <p>Results</p> <p>In this work we show that using PPAN data combined with other approximations, such as functional module detection, orthology exploitation methods and Gene Ontology (GO)-based information measures helps to predict protein function in <it>Mycoplasma genitalium</it>.</p> <p>Conclusions</p> <p>To our knowledge, the proposed method is the first that combines functional module detection among species, exploiting an orthology procedure and using information theory-based GO semantic similarity in PPAN of the <it>Mycoplasma </it>species. The results of an evaluation show a higher recall than previously reported methods that focused on only one organism network.</p