Computational models of myocardial endomysial collagen arrangement

Collagen extracellular matrix is one of the factors related to high passive stiffness of cardiac muscle. However, the architecture and the mechanical aspects of the cardiac collagen matrix are not completely known. In particular, endomysial collagen contribution to the passive mechanics of cardiac muscle as well as its micro anatomical arrangement is still a matter of debate. In order to investigate mechanical and structural properties of endomysial collagen, we consider two alternative computational models of some specific aspects of the cardiac muscle. These two models represent two different views of endomysial collagen distribution: (1) the traditional view and (2) a new view suggested by the data obtained from scanning electron microscopy (SEM) in NaOH macerated samples (a method for isolating collagen from the other tissue). We model the myocardial tissue as a net of spring elements representing the cardiomyocytes together with the endomysial collagen distribution. Each element is a viscous elastic spring, characterized by an elastic and a viscous constant. We connect these springs to imitate the interconnections between collagen fibers. Then we apply to the net of springs some external forces of suitable magnitude and direction, obtaining an extension of the net itself. In our setting, the ratio forces magnitude /net extension is intended to model the stress /strain ratio of a microscopical portion of the myocardial tissue. To solve the problem of the correct identification of the values of the different parameters involved, we use an artificial neural network approach. In particular, we use this technique to learn, given a distribution of external forces, the elastic constants of the springs needed to obtain a desired extension as an equilibrium position. Our experimental findings show that, in the model of collagen distribution structured according to the new view, a given stress /strain ratio (of the net of springs, in the sense specified above) is obtained with much smaller (w.r.t. the other model, corresponding to the traditional view) elasticity constants of the springs. This seems to indicate that by an appropriate structure, a given stiffness of the myocardial tissue can be obtained with endomysial collagen fibers of much smaller size.     

Nonsmooth nonnegative matrix factorization (nsNMF)

We propose a novel nonnegative matrix factorization model that aims at finding localized, part-based, representations of nonnegative multivariate data items. Unlike the classical nonnegative matrix factorization (NMF) technique, this new model, denoted "nonsmooth nonnegative matrix factorization" (nsNMF), corresponds to the optimization of an unambiguous cost function designed to explicitly represent sparseness, in the form of nonsmoothness, which is controlled by a single parameter. In general, this method produces a set of basis and encoding vectors that are not only capable of representing the original data, but they also extract highly focalized patterns, which generally lend themselves to improved interpretability. The properties of this new method are illustrated with several data sets. Comparisons to previously published methods show that the new nsNMF method has some advantages in keeping faithfulness to the data in the achieving a high degree of sparseness for both the estimated basis and the encoding vectors and in better interpretability of the factors.     

Guidelines for the incremental identification of aspects in requirements specifications

The desired principle of separation of concerns in software development can be jeopardized by the so-called crosscutting concerns, which tend to be scattered over (and tangled with) the functionality of the modular units of a system. The correct identification of such concerns (and their encapsulation into separate artifacts) is thereby considered a way to improve software understanding and evolution. Pursuing a proper management of concerns from the requirements engineering stage can greatly benefit the entire software life-cycle. In this paper, we propose conceptual guidelines on how to perform the identification of crosscutting concerns in the process of building requirements specifications. We argue that the identification must be carried out in an incremental way, to encapsulate apart the crosscutting concerns even if they have not emerged completely yet.

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.