Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Extreme Precipitation Modelling Using Geostatistics and Machine Learning Algorithms

The paper presents an approach for mapping of precipitation data. The main goal is to perform spatial predictions and simulations of precipitation fields using geostatistical methods (ordinary kriging, kriging with external drift) as well as machine learning algorithms (neural networks). More practically, the objective is to reproduce simultaneously both the spatial patterns and the extreme values. This objective is best reached by models integrating geostatistics and machine learning algorithms. To demonstrate how such models work, two case studies have been considered: first, a 2-day accumulation of heavy precipitation and second, a 6-day accumulation of extreme orographic precipitation. The first example is used to compare the performance of two optimization algorithms (conjugate gradients and Levenberg-Marquardt) of a neural network for the reproduction of extreme values. Hybrid models, which combine geostatistical and machine learning algorithms, are also treated in this context. The second dataset is used to analyze the contribution of radar Doppler imagery when used as external drift or as input in the models (kriging with external drift and neural networks). Model assessment is carried out by comparing independent validation errors as well as analyzing data patterns.

La formació permanent en el context de l'Espai Europeu de la Formació Permanent

La importància de la formació permanent és indiscutible en qualsevol context laboral i molt especialment en les actuals circumstàncies de crisi econòmica mundial. Però en l'actual espai europeu d'educació superior (EEES), les tendències i els plans de formació contínua adquireixen una dimensió global, que supera o, millor dit, hauria de superar els plantejaments reduccionistes. Per això, la construcció i el desenvolupament de l'espai europeu de formació permanent, EEFP (Comissió de les Comunitats Europees, 2001a), ha d'entendre's com un procés que està immers en un teixit més ampli. Es tracta d'una acció en xarxa on és necessària la implicació de molts agents actius professionals i on la convergència, el reconeixement i la cohesió han de ser els seus màxims elements qualitatius

Cinéma, machine à mondes : essai sur les films à univers multiples

Dans cet ouvrage, l'auteur propose une conceptualisation théorique de la coprésence en un même film de mondes multiples en abordant différents paramètres (hétérogénéité de la facture de l'image, pratiques du montage alterné, typologie des enchâssements, expansion sérielle, etc.) sur la base d'un corpus de films de fiction récents qui appartiennent pour la plupart au genre de la science-fiction (Matrix, Dark City, Avalon, Resident Evil, Avatar,...). Issue de la filmologie, la notion de « diégèse » y est développée à la fois dans le potentiel d'autonomisation dont témoigne la conception mondaine qui semble dominer aujourd'hui à l'ère des jeux vidéo, dans ses liens avec le récit et dans une perspective intermédiale. Les films discutés ont la particularité de mettre en scène des machines permettant aux personnages de passer d'un monde à l'autre : les modes de figuration de ces technologies sont investigués en lien avec les imaginaires du dispositif cinématographique et les potentialité du montage. La comparaison entre les films (Tron et son récent sequel, Totall Recall et son remake) et entre des oeuvres filmiques et littéraires (en particulier les nouvelles de Philip K. Dick et Simlacron 3 de Galouye) constitue un outil d'analyse permettant de saisir la contemporanéité de cette problématique, envisagée sur le plan esthétique dans le contexte de l'imagerie numérique.

Sunk costs, extensive R&D subsidies and permanent inducement effects

We study whether there is scope for using subsidies to smooth out barriers to R&D performance and expand the share of R&D firms in Spain. We consider a dynamic model with sunk entry costs in which firms’ optimal participation strategy is defined in terms of two subsidy thresholds that characterise entry and continuation. We compute the subsidy thresholds from the estimates of a dynamic panel data type-2 tobit model for an unbalanced panel of about 2,000 Spanish manufacturing firms. The results suggest that “extensive” subsidies are a feasible and efficient tool for expanding the share of R&D firms.

Biometal muscle to restore atrial transport function in a permanent atrial fibrillation animal model: a potential tool in the treatment of end-stage heart failure.

BACKGROUND: Half of the patients with end-stage heart failure suffer from persistent atrial fibrillation (AF). Atrial kick (AK) accounts for 10-15% of the ejection fraction. A device restoring AK should significantly improve cardiac output (CO) and possibly delay ventricular assist device (VAD) implantation. This study has been designed to assess the mechanical effects of a motorless pump on the right chambers of the heart in an animal model. METHODS: Atripump is a dome-shaped biometal actuator electrically driven by a pacemaker-like control unit. In eight sheep, the device was sutured onto the right atrium (RA). AF was simulated with rapid atrial pacing. RA ejection fraction (EF) was assessed with intracardiac ultrasound (ICUS) in baseline, AF and assisted-AF status. In two animals, the pump was left in place for 4 weeks and then explanted. Histology examination was carried out. The mean values for single measurement per animal with +/-SD were analysed. RESULTS: The contraction rate of the device was 60 per min. RA EF was 41% in baseline, 7% in AF and 21% in assisted-AF conditions. CO was 7+/-0.5 l min(-1) in baseline, 6.2+/-0.5 l min(-1) in AF and 6.7+/-0.5 l min(-1) in assisted-AF status (p<0.01). Histology of the atrium in the chronic group showed chronic tissue inflammation and no sign of tissue necrosis. CONCLUSIONS: The artificial muscle restores the AK and improves CO. In patients with end-stage cardiac failure and permanent AF, if implanted on both sides, it would improve CO and possibly delay or even avoid complex surgical treatment such as VAD implantation.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Identification of early metabolic markers of various degrees of ischemia in the mouse brain by localized H-1 magnetic resonance spectroscopy

Objectives: Magnetic resonance (MR) imaging and spectroscopy (MRS) allow the establishment of the anatomical evolution and neurochemical profiles of ischemic lesions. The aim of the present study was to identify markers of reversible and irreversible damage by comparing the effects of 10-mins middle cerebral artery occlusion (MCAO), mimicking a transient ischemic attack, with the effects of 30-mins MCAO, inducing a striatal lesion. Methods: ICR-CD1 mice were subjected to 10-mins (n = 11) or 30-mins (n = 9) endoluminal MCAO by filament technique at 0 h. The regional cerebral blood flow (CBF) was monitored in all animals by laser- Doppler flowmetry with a flexible probe fixed on the skull with < 20% of baseline CBF during ischemia and > 70% during reperfusion. All MR studies were carried out in a horizontal 14.1T magnet. Fast spin echo images with T2-weighted parameters were acquired to localize the volume of interest and evaluate the lesion size. Immediately after adjustment of field inhomogeneities, localized 1H MRS was applied to obtain the neurochemical profile from the striatum (6 to 8 microliters). Six animals (sham group) underwent nearly identical procedures without MCAO. Results: The 10-mins MCAO induced no MR- or histologically detectable lesion in most of the mice and a small lesion in some of them. We thus had two groups with the same duration of ischemia but a different outcome, which could be compared to sham-operated mice and more severe ischemic mice (30-mins MCAO). Lactate increase, a hallmark of ischemic insult, was only detected significantly after 30-mins MCAO, whereas at 3 h post ischemia, glutamine was increased in all ischemic mice independently of duration and outcome. In contrast, glutamate, and even more so, N-acetyl-aspartate, decreased only in those mice exhibiting visible lesions on T2-weighted images at 24 h. Conclusions: These results suggest that an increased glutamine/glutamate ratio is a sensitive marker indicating the presence of an excitotoxic insult. Glutamate and NAA, on the other hand, appear to predict permanent neuronal damage. In conclusion, as early as 3 h post ischemia, it is possible to identify early metabolic markers manifesting the presence of a mild ischemic insult as well as the lesion outcome at 24 h.

Darrera de la màscara de Comediants. L'imaginari d'un grup de teatre català : Creació d'una exposició permanent per a museu Comediants

TFC que segueix l'esquema d'un projecte cultural. D'una banda, s'analitzen els factors interns i externs de l'organització que poden influir en l'execució d'aquest projecte. El clímax és la creació d'una exposició permanent per a un museu Comediants. Interpretant el discurs de Comediants es proposa un discurs expositiu. Interessant elecció de missatges i divertits recursos expositius. Des del començament s'ha volgut fugir de la idea d'elaborar un TFC on solament se sintetitzessin dades i informació. Tanmateix, aquest TFC és un treball de recerca i, com a tal, la major part és la síntesi de dades i informacions obtingudes mitjançant investigació. No obstant això, hi ha una altra part molt important amb aportacions personals on s'ha posat a prova la pròpia creativitat i la capacitat de proporcionar aspectes innovadors, els quals, al cap i a la fi, han sorgit arran del treball en grup.

Love machine

This poster provides advice on the use of condoms as a method of protection from unplanned pregnancy and sexually transmitted infections (STIs). It also provides contact details for the�Genito Urinary Medicine (GUM) clinics in Northern Ireland.

Formació Permanent del professorat a la xarxa : una experiència de treball cooperatiu

Aquest projecte s'insereix en l'àmbit de les TIC. La participació en aquest entorn virtual cooperatiu s'ofereix com a complement a les reunions presencials de formació per a donar continuïtat al treball elaborat. La intervenció psicopedagògica es centra en dos objectius: a) dinamitzar l'entorn virtual per a afavorir el treball cooperatiu entre docents en xarxa oferint-los els medis per a participar-hi; b) dissenyar un entorn de participació que faciliti l'intercanvi i la cooperació entre docents i que, alhora, ajudi els professors a assumir una actitud positiva davant les TIC.