Human cytidine deaminase: a three-dimensional homology model of a tetrameric metallo-enzyme inferred from the crystal structure of a distantly related dimeric homologue

Cytidine deaminase (CDA) is a cytosolic metalloprotein whose functional unit can be either a homotetramer (T-CDA) or a homodimer (D-CDA), depending on the species. In 1994, the first crystal structure of the dimeric Escherichia coli CDA has been published. However, a crystal structure of a tetrameric CDA was not determined until 2002. Prior to the disclosure of the experimentally elucidated structure of a tetrameric CDA, we derived a homology model of the human T-CDA employing the crystal structure of the dimeric E. coli CDA as a template. The comparison of our theoretical model with the crystal structure of the human T-CDA, subsequently published in 2004, validates our prediction: not only of the structural features of the monomer and the details of the binding site, but also the multimeric arrangement of the subunits were determined with high accuracy in our model. By means of a phylogenetic analysis conducted on CDAs from various organisms, we demonstrate that the E. coli CDA is one of the furthest known homologues of the human enzyme. Nonetheless, despite the evolutionary distance and, more importantly, the different multimeric arrangement of their functional units, the E. coli CDA proved to have all the necessary information to accurately infer the structure of its human homologue.     

Coordination components for collaborative virtual environments

This paper deals with the behavior of virtual environments from the collaboration point-of-view, in which actors (human or virtual beings) interact and collaborate by means of interdependent tasks. In this sense, actors may realize tasks that are dependent on tasks performed by other actors, while the interdependencies between tasks (through resource management and temporal relations) delineate the overall behavior of a virtual environment. Our main goal is to propose an approach for the coordination of those behaviors. Initially a generic study of possible interdependencies between collaborative tasks is presented, followed by the formal modeling (using Petri Nets) of coordination mechanisms for those dependencies. In order to implement such mechanisms, an architecture of reusable and pluggable coordination components is also introduced. These components are used in an implementation of a multi-user videogame. The presented approach is a concrete step to create virtual societies of actors that collaborate to reach common goals without the risk of getting involved in conflicting or repetitive tasks.     

Rules and Strategies for Contextual Specialization of Constraint Logic Programs

We address the problem of specializing a constraint logic program w.r.t. a constrained atom which specifies the context of use of the program. We follow an approach based on transformation rules and strategies. We introduce a novel transformation rule, called contextual constraint replacement, to be combined with variants of the traditional unfolding and folding rules. We present a general Partial Evaluation Strategy for automating the application of these rules, and two additional strategies: the Context Propagation Strategy which is instrumental for the application of our contextual constraint replacement rule, and the Invariant Promotion Strategy for taking advantage of invariance properties of the computation. We show through some examples the power of our method and we compare it with existing methods for partial deduction of constraint logic programs based on extensions of Lloyd and Shepherdson's approach.     

Robust quantification of the exposure to operational risk: Bringing economic sense to economic capital

Operational risk is commonly analyzed in terms of the distribution of aggregate yearly losses. Risk measures can then be computed as statistics of this distribution that focus on the region of extreme losses. Assuming independence among the operational risk events and between the likelihood that they occur and their magnitude, separate models are made for the frequency and for the severity of the losses. These are then combined to estimate the distribution of aggregate losses. While the detailed form of the frequency distribution does not significantly affect the risk analysis, the choice of model for the severity often has a significant impact on operational risk measures. For heavy-tailed distributions these measures are dominated by extreme losses, whose probability cannot be reliably extrapolated from the available data. With limited empirical evidence, it is difficult to distinguish among alternative models that produce very different values of the risk measures. Furthermore, the estimates obtained can be unstable and overly sensitive to the presence or absence of single extreme events. Setting a bound on the maximum amount that can be lost in a single event reduces the dependence on the distributional assumptions and improves the robustness and stability of the risk measures, while preserving their sensitivity to changes in the risk profile. This bound should be determined by expert assessment on the basis of economic arguments and validated by the regulator, so that it can be used as a control parameter in the risk analysis.     

Acoustic scattering solver based on single level FMM for multi-GPU systems

In this paper, we present a heterogeneous parallel solver of a high frequency single level Fast Multipole Method (FMM) for the Helmholtz equation applied to acoustic scattering. The developed solution uses multiple GPUs to tackle the compute bound steps of the FMM (aggregation, disaggregation, and near interactions) while the CPU handles a memory bound step (translation) using OpenMP. The proposed solver performance is measured on a workstation with two GPUs (NVIDIA GTX 480) and is compared with that of a distributed memory solver run on a cluster of 32 nodes (HP BL465c) with an Infiniband network. Some energy efficiency results are also presented in this work.     

A collaborative platform for cognitive decision making in the Knowledge Society

Two key aspects of the Knowledge Society are the interconnection between the actors involved in the decision making processes and the importance of the human factor, particularly the citizen’s continuous learning and education. This paper presents a new module devoted to knowledge extraction and diffusion that has been incorporated into a previously developed decision making tool concerning the Internet and related with the multicriteria selection of a discrete number of alternatives (PRIOR-Web). Quantitative and qualitative procedures using data and text mining methods have been employed in the extraction of knowledge. Graphical visualisation tools have been incorporated in the diffusion stage of the methodological approach suggested when dealing with decision making in the Knowledge Society. The resulting collaborative platform is being used as the methodological support for the cognitive democracy known as e-cognocracy.     

A Java simulator of Rescorla and Wagner's prediction error model and configural cue extensions

In this paper we present the "R&W Simulator" (version 3.0), a Java simulator of Rescorla and Wagner's prediction error model of learning. It is able to run whole experimental designs, and compute and display the associative values of elemental and compound stimuli simultaneously, as well as use extra configural cues in generating compound values; it also permits change of the US parameters across phases. The simulator produces both numerical and graphical outputs, and includes a functionality to export the results to a data processor spreadsheet. It is user-friendly, and built with a graphical interface designed to allow neuroscience researchers to input the data in their own "language". It is a cross-platform simulator, so it does not require any special equipment, operative system or support program, and does not need installation. The "R&W Simulator" (version 3.0) is available free.     

Petri net-based engine for adaptive learning

In this paper, an IMS LD engine based on a Petri net model that represents the operational semantics of units of learning based on this specification is presented. The Petri nets of this engine, which is called OPENET4LD, verify the structural properties that are desirable for a learning flow and also facilitate the adaptation of the engine if potential changes in the IMS LD specification were proposed. Furthermore, OPENET4LD has an open and flexible architecture based on a set of ontologies that describe both the semantics of the Petri nets execution and the semantics of each learning flow component of IMS LD. Furthermore, the implementation of this architecture has been exhaustively validated with a number of UoLs that are compliant with the levels A and B of IMS LD.     

Model of Precipitation Kinetics Induced by Strain for Microalloyed Steels

In microalloyed steels, static recrystallisation is temporarily inhibited by precipitation which is occurring at the same time. A high number of microalloyed steels containing various combinations of carbon, nitrogen and precipitate forming elements like V, Nb and Ti were recrystallised at different temperatures and strain rates. From these results recrystallisation‐precipitation–time‐temperature (RPTT) diagrams were established. The influence of grain size and strain rate on the RPTT diagrams was studied. The precipitation kinetics were mathematically described for isothermal conditions and converted to cooling conditions, which enables an application to hot rolling. Under cooling conditions, completion of recrystallisation is prevented, especially for Nb alloyed steels.