Validation of real-time properties of a robotic software architecture

National audienceIn this paper, we propose a mechanism allowing to evaluate the schedulability of a robotic software architecture, and then validate its real-time properties. The robotic software architecture is described through a Domain Specific Language (DSL), MAUVE, that allows to model communicating components. The evaluation of schedulability of the architecture consists in first computing the Worst-Case Execution Time (WCET) of the elementary functions of the components. Then the Worst Case Response Time (WCRT) of the component is computed from the elementary WCET and the component models, allowing to validate the schedulatiblity of the architecture. We illustrate our methodology on the evaluation of a control architecture for a ground mobile robot

Mauve: a Component-based Modeling Framework for Real-time Analysis of Robotic Applications.

Robots are more and more used in very diverse situations (services to persons, military missions, crisis management, . . . ) in which robots must give some guarantees of safety and reliability. To be really integrated in everyday life, robots must fulfil some requirements. Among these requirements, we focus on the nonfunctional requirements on embedded software [1], and more specifically on real-time software requirements. These requirements are most of the time fulfilled by proving the schedulability of the embedded software. Analysing and validating such properties on an existing hand-coded software requires some reverse modelling of the software, leading to approximations of its behaviour. These approximations may have certification authorities not be confident on the robot dependability. This paper proposes an integrated development methodology that starts from software component modelling, and leads to both validation of the embedded software and generation of deployable embedded software

A mission management system for a fleet of gliders

International audienceThe objective of AGLIMMS project, whose acronym stands for Acoustic GLIders Mission Management System, is to efficiently coordinate a fleet of underwater gliders whose missions are to obtain physical, chemical, biological and/or acoustic measurements on a large 3D sea area. This paper describes planning and supervision functions under development and their integration in a global centralised architecture. A demonstration with three SeaExplorer from Alseamar is planned late 2019

Corail, ROS 2 temps réel

Le package Corail propose une nouvelle implémentation des exécuteurs de ROS2 qui permet la réalisation de programmes temps réel. Corail s'appuie sur le standard POSIX, notamment son implémentation pthread, et l'ordonnanceur temps réel SCHED_FIFO pour permettre une gestion précise des différents paramètres d'ordonnancement, comme l'affinité ou la priorité, de chaque tâche. Il donne également la possibilité de gérer la synchronisation, ce qui n'est pas permis par les exécuteurs existants. Corail assure le déterminisme temporel de l'exécution des différents éléments du système. Ce déterminisme est essentiel pour permettre l'analyse d'ordonnançabilité, qui est obligatoire pour prouver que le système respecte ses spécifications

A multi-split mapping algorithm for circular RNA, splicing, trans-splicing and fusion detection

Numerous high-throughput sequencing studies have focused on detecting conventionally spliced mRNAs in RNA-seq data. However, non-standard RNAs arising through gene fusion, circularization or trans-splicing are often neglected. We introduce a novel, unbiased algorithm to detect splice junctions from single-end cDNA sequences. In contrast to other methods, our approach accommodates multi-junction structures. Our method compares favorably with competing tools for conventionally spliced mRNAs and, with a gain of up to 40% of recall, systematically outperforms them on reads with multiple splits, trans-splicing and circular products

Bayesian inference of accurate population sizes and FRET efficiencies from single diffusing biomolecules.

It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from single-molecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in solution. Experimental methods of increasing cost and complexity are being developed to improve the accuracy and precision of data collection. However, the analysis of smFRET data sets currently relies on simplistic, and often arbitrary methods, for the selection and denoising of fluorescent bursts. Although these methods are satisfactory for the analysis of simple, low-noise systems with intermediate FRET efficiencies, they display systematic inaccuracies when applied to more complex systems. We have developed an inference method for the analysis of smFRET data from solution studies based on rigorous model-based Bayesian techniques. We implement a Monte Carlo Markov chain (MCMC) based algorithm that simultaneously estimates population sizes and intramolecular distance information directly from a raw smFRET data set, with no intermediate event selection and denoising steps. Here, we present both our parametric model of the smFRET process and the algorithm developed for data analysis. We test the algorithm using a combination of simulated data sets and data from dual-labeled DNA molecules. We demonstrate that our model-based method systematically outperforms threshold-based techniques in accurately inferring both population sizes and intramolecular distances.This is the final published version. It's also available from ACS in Analytical Chemistry: http://pubs.acs.org/doi/pdf/10.1021/ac501188r

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing

The genomic and transcriptional landscape of primary central nervous system lymphoma

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations

A Design and Analysis Methodology for Component-Based Real-Time Architectures of Autonomous Systems

The integration of autonomous robots in real applications is a challenge. It needs that the behaviour of these robots is proved to be safe. In this paper, we focus on the real-time software embedded on the robot, and that supports the execution of safe and autonomous behaviours. We propose a methodology that goes from the design of component-based software architectures using a Domain Specific Language, to the analysis of the real-time constraints that arise when considering the safety of software applications. This methodology is supported by a code generation toolchain that ensures that the code eventually executed on the robot is consistent with the analysis performed. This methodology is applied on a ground robot exploring an area. Categories (2), (3