On the Introduction of Guarded Lists in Bach: Expressiveness, Correctness, and Efficiency Issues

Concurrency theory has received considerable attention, but mostly in the scope of synchronous process algebras such as CCS, CSP, and ACP. As another way of handling concurrency, data-based coordination languages aim to provide a clear separation between interaction and computation by synchronizing processes asynchronously by means of information being available or not on a shared space. Although these languages enjoy interesting properties, verifying program correctness remains challenging. Some works, such as Anemone, have introduced facilities, including animations and model checking of temporal logic formulae, to better grasp system modelling. However, model checking is known to raise performance issues due to the state space explosion problem. In this paper, we propose a guarded list construct as a solution to address this problem. We establish that the guarded list construct increases performance while strictly enriching the expressiveness of data-based coordination languages. Furthermore, we introduce a notion of refinement to introduce the guarded list construct in a correctness-preserving manner.Comment: In Proceedings ICE 2023, arXiv:2308.0892

Deciphering peculiar protein-protein interacting modules in Deinococcus radiodurans

Interactomes of proteins under positive selection from ionizing-radiation-resistant bacteria (IRRB) might be a part of the answer to the question as to how IRRB, particularly Deinococcus radiodurans R(1 )(Deira), resist ionizing radiation. Here, using the Database of Interacting Proteins (DIP) and the Protein Structural Interactome (PSI)-base server for PSI map, we have predicted novel interactions of orthologs of the 58 proteins under positive selection in Deira and other IRRB, but which are absent in IRSB. Among these, 18 domains and their interactomes have been identified in DNA checkpoint and repair; kinases pathways; energy and nucleotide metabolisms were the important biological processes that were found to be involved. This finding provides new clues to the cellular pathways that can to be important for ionizing-radiation resistance in Deira

GLOBAL INDEX CONSTRUCTION FOR DATA INTEGRATION IN LARGE SCALE SYSTEM

Several scientific projects focused on the creation of Peer-to-Peer data management system. The main objective of these systems is to allow data sharing and integration among a large set of distributed, heterogeneous data sources. The emergence of large scale systems provides solutions and brings to surface new challenging unsolved problems, among which, we address the data integration problem. In order to address this problem, we propose a new data integration approach that allows the semantic integration of heterogeneous and distributed data sources in a Peer-to-Peer environment with high distribution and evolution support. In this paper, we provide an introduction to the approaches; problems and research issues encountered when dealing with data integration.We present our approach and describe the several methods for constructing a global index that is the core of our approach by using semantic similarities. We end our work by an application example

Conception et évaluation d'un instrument de mesure pour la détection des postures et des mouvements contraignants menant à l’apparition des troubles musculosquelettiques en milieu de travail à l'aide de réseaux de neurones

Notre projet de recherche consiste à détecter des postures et des mouvements contraignants menant à l’apparition des troubles musculo-squelettiques en milieu de travail. Ce problème de détection a été considéré comme étant un problème de classification supervisée dont le classificateur est un réseau de neurones et les classes sont les différentes postures et mouvements adoptés par un opérateur lors de la réalisation de ses tâches quotidiennes en milieu de travail. Un problème de classification supervisée se réalise en général en trois étapes : 1) l’étape de l’acquisition des signaux, 2) celle du prétraitement, et enfin, 3) celle de la classification. À la première étape, l’acquisition des signaux consiste à mesurer les postures et les mouvements de l’opérateur à l’aide d’un instrument de mesure non-invasif, non-intrusif capable de fonctionner dans son milieu de travail in-situ. L’étape de prétraitement consiste à réduire les signaux acquis à un ensemble de caractéristiques permettant de bien distinguer entre les différentes classes. Pour recueillir les caractéristiques, nous avons utilisé une méthode directe, qui regroupe les caractéristiques globales du déplacement du centre de pression utilisées généralement dans les études de posturologie et d’autres caractéristiques relatives aux accélérations de la tête. Nous avons également proposé une nouvelle méthode, dite graphique qui consiste à discrétiser la surface de la semelle sur laquelle le centre de pression se déplace. D’autre part, afin de réduire le nombre de ces caractéristiques et n’en retenir que les plus pertinentes, nous avons mis en place un nouveau modèle hybride de sélection des caractéristiques dont la singularité réside dans la combinaison de techniques utilisées. Enfin, lors de l’étape de classification, il s’agit d’utiliser les caractéristiques retenues à l’étape de prétraitement comme entrées pour le réseau de neurones. Les résultats de classification obtenus à la fin sont de 95% avec 11 caractéristiques (huit (8) provenant de la méthode directe et trois (3) de la méthode graphique). Bien qu’utilisées seules, les caractéristiques de la méthode graphique ne nous donnent pas les meilleurs résultats de classification (près de 60%), en les ajoutant aux caractéristiques de la méthode directe, le taux de reconnaissance est passé de 90% à 95%. Sans l’étape de réduction de dimensionnalité, nous n’aurions pas pu dépasser un taux de reconnaissance de 70% avec seulement huit (8) caractéristiques de la méthode directe. Enfin, nous avions également développé nos propres fonctions de validation croisée et de sélection de caractéristiques sur MatLAB, ce qui a nettement amélioré nos résultats, en passant de 85% (comme étant le meilleur taux de classification obtenu), à 95% à l’aide de nos propres fonctions

Basal DNA repair machinery is subject to positive selection in ionizing-radiation-resistant bacteria

<p>Abstract</p> <p>Background</p> <p>Ionizing-radiation-resistant bacteria (IRRB) show a surprising capacity for adaptation to ionizing radiation and desiccation. Positive Darwinian selection is expected to play an important role in this trait, but no data are currently available regarding the role of positive adaptive selection in resistance to ionizing-radiation and tolerance of desiccation. We analyzed the four known genome sequences of IRRB (<it>Deinococcus geothermalis</it>, <it>Deinococcus radiodurans</it>, <it>Kineococcus radiotolerans</it>, and <it>Rubrobacter xylanophilus</it>) to determine the role of positive Darwinian selection in the evolution of resistance to ionizing radiation and tolerance of desiccation.</p> <p>Results</p> <p>We used the programs MultiParanoid and DnaSP to deduce the sets of orthologs that potentially evolved due to positive Darwinian selection in IRRB. We find that positive selection targets 689 ortholog sets of IRRB. Among these, 58 ortholog sets are absent in ionizing-radiation-sensitive bacteria (IRSB: <it>Escherichia coli </it>and <it>Thermus thermophilus</it>). The most striking finding is that all basal DNA repair genes in IRRB, unlike many of their orthologs in IRSB, are subject to positive selection.</p> <p>Conclusion</p> <p>Our results provide the first <it>in silico </it>prediction of positively selected genes with potential roles in the molecular basis of resistance to γ-radiation and tolerance of desiccation in IRRB. Identification of these genes provides a basis for future experimental work aimed at understanding the metabolic networks in which they participate.</p

Conception d’un profil UML spécifique à la méthode COSMIC - ISO 19761 pour supporter la mesure de la taille fonctionnelle des logiciels

La mesure de la taille fonctionnelle des logiciels joue un rôle important dans la discipline du génie logiciel et des technologies de l’information. En effet, elle sert principalement à établir des estimations et calculer l’effort de développement d’un projet. COSMIC - ISO 19761, la nouvelle génération des méthodes de mesure de la taille fonctionnelle, est une méthode rigoureuse qui a connu beaucoup d’intérêt. Son principe consiste à mesurer la taille du logiciel à travers les besoins fonctionnels de ses utilisateurs appelés fonctionnalités utilisateurs requises (FUR). Elle permet notamment de mesurer différents types de logiciels (Affaire, Temps Réel, Embarqué, etc.). L’objectif de cette recherche est d’étudier l’aspect d’automatisation de la mesure de la taille fonctionnelle avec COSMIC partant des spécifications écrites avec UML. L’idée consiste à rapprocher les concepts de la méthode COSMIC et les concepts UML afin de trouver un moyen qui facilite la mesure. Partant de cette idée, nous avons tout d’abord présenté une revue de littérature des travaux de recherche antérieurs qui ont porté sur la mesure des logiciels avec COSMIC basée sur les modèles UML. Cette étude nous a montré qu’une extension appropriée d’UML pour la méthode COSMIC utilisant les mécanismes d’extension inhérents d’UML (profil UML) est encore manquante. Nous entreprenons dans cette recherche le défi de définir et concevoir un profil UML spécifique pour la méthode COSMIC. Grâce à ce profil, la tâche de mesure peut devenir moins fastidieuse puisque le profil permet de capturer toute l’information nécessaire pour établir la mesure. L’approche comprend deux volets. Proposer d’abord un méta-modèle qui décrit la méthode COSMIC. Ensuite, mapper les différents concepts du domaine sous forme de stéréotypes qui sont la base du profil P-COSMIC. Enfin et afin de soulever l’applicabilité du profil conçu, nous avons procédé à une étude de cas de type temps réel

First detection of Waddlia chondrophila in Africa using SYBR Green real-time PCR on veterinary samples.

Waddlia chondrophila is a strict intracellular microorganism belonging to the order Chlamydiales that has been isolated twice from aborted bovine fetuses, once in USA and once in Germany. This bacterium is now considered as an abortigenic agent in cattle. However, no information is available regarding the presence of this bacterium in Africa. Given the low sensitivity of cell culture to recover such an obligate intracellular bacterium, molecular-based diagnostic approaches are warranted. This report describes the development of a quantitative SYBR Green real-time PCR assay targeting the recA gene of W. chondrophila. Analytical sensitivity was 10 copies of control plasmid DNA per reaction. No cross-amplification was observed when testing pathogens that can cause abortion in cattle. The PCR exhibited a good intra-run and inter-run reproducibility. This real-time PCR was then applied to 150 vaginal swabs taken from Tunisian cows that have aborted. Twelve samples revealed to be Waddlia positive, suggesting a possible role of this bacterium in this setting. This new real-time PCR assay represents a diagnostic tool that may be used to further study the prevalence of Waddlia infection

Measuring operator’s pain : toward evaluating Musculoskeletal disorder at work

Musculoskeletal disorders (MSDs) have affected an increasing number of people in the active general population. In this perspective, we developed a measuring tool taking muscle activities in certain regions of the body, standing posture taking the center of pressure under the feet and feet positions. This tool also comprises an instrumented helmet containing an electroencephalogram (EEG) to measure brain activity, and an accelerometer reporting the movements of the head. Then, our tool comprises both non-invasive instrumented insole and safety helmet. Moreover, the same tool measures muscular activities in specific regions of the body using an electromyogram (EMG). The aim is to combine all the data in order to identify consistent patterns between brain activity, postures, movements and muscle activity, and then, understand their connection to the development of MSDs. This paper presents three situations reported to be a risk for MSDs and an analysis of the signals is presented in order to differentiate adequate or abnormal posture

System Engineering for dependency analysis - a Bayesian approach: application to obsolescence study

International audienceThroughout its life cycle, systems undergo several modifications in their architecture. These changes target at remaining competitive and responding quickly to new customer requirements. However, any entity change (i.e. component, function or functionality) can produce unexpected consequences, propagated throughout the whole system architecture. It is then necessary to model, predict and control them. System engineering tools and techniques allow dealing with complex systems design. That is why we have developed a novel methodology to analyze changes using a system engineering methodology called ARCADIA, developed by Thales and its associated software Capella. The obtained models allow mapping various kinds of dependencies within a system architecture. The method, presented in this paper, shows how these models are used to integrate change propagation and transform them into Bayesian networks. A set of experiments allows then to obtain insightful pieces of knowledge about the changes propagation. An illustrative case is developed with a focus of particular changes caused by obsolescence of component, function or functionality

Wearable devices for classification of inadequate posture at work using neural networks

Inadequate postures adopted by an operator at work are among the most important risk factors in Work-related Musculoskeletal Disorders (WMSDs). Although several studies have focused on inadequate posture, there is limited information on its identification in a work context. The aim of this study is to automatically differentiate between adequate and inadequate postures using two wearable devices (helmet and instrumented insole) with an inertial measurement unit (IMU) and force sensors. From the force sensors located inside the insole, the center of pressure (COP) is computed since it is considered an important parameter in the analysis of posture. In a first step, a set of 60 features is computed with a direct approach, and later reduced to eight via a hybrid feature selection. A neural network is then employed to classify the current posture of a worker, yielding a recognition rate of 90%. In a second step, an innovative graphic approach is proposed to extract three additional features for the classification. This approach represents the main contribution of this study. Combining both approaches improves the recognition rate to 95%. Our results suggest that neural network could be applied successfully for the classification of adequate and inadequate posture