Monte Carlo simulations with few DOF’s in large molecules

This Technical Report introduces a data structure and an algorithm to efficiently to efficiently determine rigid clusters in a given molecule. This is a relevant problem in Monte Carlo simulations where the actuated DOFs change at each iteration. If the number of actuated DOFs is small, large temporary rigid groups appear during the time spanned by a MCS step. This document also provides a way of calculating the total energy in the molecules taking into account only inter-rigid energy terms. Thus, a large fraction of energy terms are not required to be computed, namely intra-rigid terms.Postprint (published version

On-line learning with minimal degradation in feedforward networks

Dealing with non-stationary processes requires quick adaptation while at the same time avoiding catastrophic forgetting. A neural learning technique that satisfies these requirements, without sacrifying the benefits of distributed representations, is presented. It relies on a formalization of the problem as the minimization of the error over the previously learned input-output (i-o) patterns, subject to the constraint of perfect encoding of the new pattern. Then this constrained optimization problem is transformed into an unconstrained one with hidden-unit activations as variables. This new formulation naturally leads to an algorithm for solving the problem, which we call Learning with Minimal Degradation (LMD). Some experimental comparisons of the performance of LMD with back-propagation are provided which, besides showing the advantages of using LMD, reveal the dependence of forgetting on the learning rate in back-propagation. We also explain why overtraining affects forgetting and fault-tolerance, which are seen as related problems.Peer Reviewe

Exploiting single-cycle symmetries in branch-and-prune algorithms

As a first attempt to exploit symmetries in continuous con- straint problems, we focus on permutations of the variables consisting of one single cycle. We propose a procedure that takes advantage of these symmetries by interacting with a Branch-and-Prune algorithm without interfering with it. A key concept in this procedure are the classes of symmetric boxes formed by bisecting a n-dimensional cube at the same point in all dimensions at the same time. We quantify these classes as a function of n. Moreover, we propose a simple algorithm to generate the representatives of all these classes for any number of variables at very high rates. A problem example from the chemical field and a kinematics solver are used to show the performance of the approach in practice.Peer Reviewe

Exploiting single-cycle symmetries in branch-and-prune algorithms

The final publication is available at link.springer.comAs a first attempt to exploit symmetries in continuous constraint problems, we focus on permutations of the variables consisting of one single cycle. We propose a procedure that takes advantage of these symmetries by interacting with a Branch-and-Prune algorithm without interfering with it. A key concept in this procedure are the classes of symmetric boxes formed by bisecting a n-dimensional cube at the same point in all dimensions at the same time. We quantify these classes as a function of n. Moreover, we propose a simple algorithm to generate the representatives of all these classes for any number of variables at very high rates. A problem example from the chemical field and a kinematics solver are used to show the performance of the approach in practice.Peer ReviewedPostprint (author's final draft

Rapid learning of humanoid body schemas with kinematic Bezier maps

Trabajo presentado al 9th IEEE-RAS celebrado en París del 7 al 10 de diciembre de 2009.This paper addresses the problem of hand-eye coordination and, more specifically, tool-eye recalibration of humanoid robots. Inspired by results from neuroscience, a novel method to learn the forward kinematics model as part of the body schema of humanoid robots is presented. By making extensive use of techniques borrowed from the field of computer-aided geometry, the proposed Kinematic Be ́zier Maps (KB-Maps) permit reducing this complex problem to a linearly-solvable, although high-dimensional, one. Therefore, in the absence of noise, an exact kinematic model is obtained. This leads to rapid learning which, unlike in other approaches, is combined with good extrapolation capabilities. These promising theoretical advantages have been validated through simulation, and the applicability of the method to real hardware has been demonstrated through experiments on the humanoid robot ARMAR-IIIa.This work was supported by projects: 'Perception, action & cognition through learning of object-action complexes.' (4915), 'Analysis and motion planning of complex robotic systems' (4802), 'Grup de recerca consolidat - Grup de Robòtica' (4810). The work described in this paper was partially conducted within the EU Cognitive Systems projects GRASP (FP7-215821) and PACO-PLUS (FP6-027657) funded by the European Commission. The authors acknowledge support from the Generalitat de Catalunya under the consolidated Robotics group, and from the Spanish Ministry of Science and Education, under the project DPI2007-60858Peer Reviewe

Variable symmetry breaking in numerical constraint problems

Symmetry breaking has been a hot topic of research in the past years, leading to many theoretical developments as well as strong scaling strategies for dealing with hard applications. Most of the research has however focused on discrete, combinatorial, problems, and only few considered also continuous, numerical, problems. While part of the theory applies in both contexts, numerical problems have specificities that make most of the technical developments inadequate. In this paper, we present the rlex constraints, partial symmetry-breaking inequalities corresponding to a relaxation of the famous lex constraints extensively studied in the discrete case. They allow (partially) breaking any variable symmetry and can be generated in polynomial time. Contrarily to lex constraints that are impractical in general (due to their overwhelming number) and inappropriate in the continuous context (due to their form), rlex constraints can be efficiently handled natively by numerical constraint solvers. Moreover, we demonstrate their pruning power on continuous domains is almost as strong as that of lex constraints, and they subsume several previous work on breaking specific symmetry classes for continuous problems. Their experimental behavior is assessed on a collection of standard numerical problems and the factors influencing their impact are studied. The results confirm rlex constraints are a dependable counterpart to lex constraints for numerical problems.Peer ReviewedPostprint (author's final draft

Relationship of Weather Types on the Seasonal and Spatial Variability of Rainfall, Runoff, and Sediment Yield in the Western Mediterranean Basin

Rainfall is the key factor to understand soil erosion processes, mechanisms, and rates. Most research was conducted to determine rainfall characteristics and their relationship with soil erosion (erosivity) but there is little information about how atmospheric patterns control soil losses, and this is important to enable sustainable environmental planning and risk prevention. We investigated the temporal and spatial variability of the relationships of rainfall, runoff, and sediment yield with atmospheric patterns (weather types, WTs) in the western Mediterranean basin. For this purpose, we analyzed a large database of rainfall events collected between 1985 and 2015 in 46 experimental plots and catchments with the aim to: (i) evaluate seasonal differences in the contribution of rainfall, runoff, and sediment yield produced by the WTs; and (ii) to analyze the seasonal efficiency of the different WTs (relation frequency and magnitude) related to rainfall, runoff, and sediment yield. The results indicate two different temporal patterns: the first weather type exhibits (during the cold period: autumn and winter) westerly flows that produce the highest rainfall, runoff, and sediment yield values throughout the territory; the second weather type exhibits easterly flows that predominate during the warm period (spring and summer) and it is located on the Mediterranean coast of the Iberian Peninsula. However, the cyclonic situations present high frequency throughout the whole year with a large influence extended around the western Mediterranean basin. Contrary, the anticyclonic situations, despite of its high frequency, do not contribute significantly to the total rainfall, runoff, and sediment (showing the lowest efficiency) because of atmospheric stability that currently characterize this atmospheric pattern. Our approach helps to better understand the relationship of WTs on the seasonal and spatial variability of rainfall, runoff and sediment yield with a regional scale based on the large dataset and number of soil erosion experimental stations

Gestión del conocimiento. Perspectiva multidisciplinaria. Volumen 9

El libro “Gestión del Conocimiento. Perspectiva Multidisciplinaria”, volumen 9, de la Colección Unión Global, es resultado de investigaciones. Los capítulos del libro, son resultados de investigaciones desarrolladas por sus autores. El libro es una publicación internacional, seriada, continua, arbitrada de acceso abierto a todas las áreas del conocimiento, que cuenta con el esfuerzo de investigadores de varios países del mundo, orientada a contribuir con procesos de gestión del conocimiento científico, tecnológico y humanístico que consoliden la transformación del conocimiento en diferentes escenarios, tanto organizacionales como universitarios, para el desarrollo de habilidades cognitivas del quehacer diario. La gestión del conocimiento es un camino para consolidar una plataforma en las empresas públicas o privadas, entidades educativas, organizaciones no gubernamentales, ya sea generando políticas para todas las jerarquías o un modelo de gestión para la administración, donde es fundamental articular el conocimiento, los trabajadores, directivos, el espacio de trabajo, hacia la creación de ambientes propicios para el desarrollo integral de las instituciones

Time to Switch to Second-line Antiretroviral Therapy in Children With Human Immunodeficiency Virus in Europe and Thailand.

Background: Data on durability of first-line antiretroviral therapy (ART) in children with human immunodeficiency virus (HIV) are limited. We assessed time to switch to second-line therapy in 16 European countries and Thailand. Methods: Children aged <18 years initiating combination ART (≥2 nucleoside reverse transcriptase inhibitors [NRTIs] plus nonnucleoside reverse transcriptase inhibitor [NNRTI] or boosted protease inhibitor [PI]) were included. Switch to second-line was defined as (i) change across drug class (PI to NNRTI or vice versa) or within PI class plus change of ≥1 NRTI; (ii) change from single to dual PI; or (iii) addition of a new drug class. Cumulative incidence of switch was calculated with death and loss to follow-up as competing risks. Results: Of 3668 children included, median age at ART initiation was 6.1 (interquartile range (IQR), 1.7-10.5) years. Initial regimens were 32% PI based, 34% nevirapine (NVP) based, and 33% efavirenz based. Median duration of follow-up was 5.4 (IQR, 2.9-8.3) years. Cumulative incidence of switch at 5 years was 21% (95% confidence interval, 20%-23%), with significant regional variations. Median time to switch was 30 (IQR, 16-58) months; two-thirds of switches were related to treatment failure. In multivariable analysis, older age, severe immunosuppression and higher viral load (VL) at ART start, and NVP-based initial regimens were associated with increased risk of switch. Conclusions: One in 5 children switched to a second-line regimen by 5 years of ART, with two-thirds failure related. Advanced HIV, older age, and NVP-based regimens were associated with increased risk of switch

Catastrophic interference: solutions and relation with other connectionist problems

We analyze the conditions under which a memory system is prone to interference between new and old items. Essentially, these are the distributedness of the representation and the lack of retraining. Both are, however, desirable features providing compactness and speed. Thus, a two-stage framework to palliate interference in this type of systems is proposed based on exploiting the information available at each moment. The two stages are separated by the instant at which a new item becomes known: a) interference prevention, prior to that instant, consists in preparing the system to minimize the impact of learning new items and b) retroactive interference minimization, posterior to that instant, seeks to learn the new item while minimizing the damages inflicted on the old items. The subproblems addressed at the two stages are stated rigorously and possible methods to solve each of them are presented.Peer Reviewe