Unsupervised Domain Adaptation with Optimal Transport in multi-site segmentation of Multiple Sclerosis lesions from MRI data: Preprint

Automatic segmentation of Multiple Sclerosis (MS) lesions from Magnetic Resonance Imaging (MRI) images is essential for clinical assessment and treatment planning of MS. Recent years have seen an increasing use of Convolutional Neural Networks (CNNs) for this task. Although these methods provide accurate segmentation, their applicability in clinical settings remains limited due to a reproducibility issue across different image domains. MS images can have highly variable characteristics across patients, MRI scanners and imaging protocols; retraining a supervised model with data from each new domain is not a feasible solution because it requires manual annotation from expert radiologists. In this work, we explore an unsupervised solution to the problem of domain shift. We present a framework, Seg-JDOT, which adapts a deep model so that samples from a source domain and samples from a target domain sharing similar representations will be similarly segmented. We evaluated the framework on a multi-site dataset, MICCAI 2016, and showed that the adaptation towards a target site can bring remarkable improvements in a model performance over standard training

Immunité anti-Trichinella (étude de l'activation mastocytaire par les antigènes parasitaires et application à une stratégie vaccinale)

L épithélium intestinal est la porte d entrée de Trichinella lors de l invasion de l hôte. Parmi les cellules immunitaires du GALT (gut associated lymphoid tissue), les mastocytes jouent un rôle clé dans la phase innée d expulsion de Trichinella. Cependant leur rôle dans l initiation de la réponse spécifique reste mal connu. Dans ce cadre, différents antigènes du stade intestinal du cycle de T. spiralis ont été produits. L analyse in vitro de la stimulation par l antigène 411 de mastocytes murins génère la libération du TNF-a et de l histamine. De plus, ces cellules montrent une régulation positive d ARNm pour des molécules de co-stimulation, des molécules du CMH I et II et des cytokines (IL-1a, IL-1b, CXCL-1, CCL-5). Ces résultats indiquent que les mastocytes stimulés pourraient communiquer avec les lymphocytes T. Afin de mieux comprendre le rôle des mastocytes et de 411 dans la protection, des études in vivo d efficacité vaccinale après test d épreuve ont été effectuées avec évaluation de la charge parasitaire musculaire finale. Les souris vaccinées avec l antigène 411, présentent un taux de protection d environ 25 % par rapport aux souris non vaccinées. Lorsque ce même vaccin contient l adjuvant Montanide ISA 70 VG, ce taux augmente à 40 %. Le suivi sérologique démontre en outre, une bonne réponse anticorps IgG1 et IgG2a amplifiée en présence d adjuvant. L analyse des coupes de tissus intestinaux n a pas révélé de mastocytose après vaccination, comme cela peut être observé lors d une infection naturelle. Ces résultats montrent un rôle protecteur de 411 dans un vaccin anti-Trichinella avec induction d une fonction immunostimulante modérée des mastocytesThe intestinal epithelium is the gateway of Trichinella during host infection. Among immune cells of the gut associated lymphoid tissue, mast cells play a key role in the expulsion of T. spiralis. However, mast cells roles in the initiation of the specific immune response against T. spiralis remains poorly understood. Here, different antigens of the intestinal stage of T. spiralis were generated. Murine bone marrow mast cells (mBMMC) stimulated with antigen 411 induced the release of TNF- a and histamine. Moreover, stimulated mBMMC showed an upregulation of mRNA for several costimulatory molecules, MHC class I and II molecules and cytokines (IL-1a, IL-1b, CXCL-1, CCL-5). These results indicate that stimulated mast cells could directly communicate with T cells. In vivo studies based on vaccine trials with challenge, were also performed to explore the role played by mast cells and antigen 411 in protection. Mice vaccinated with antigen 411 exhibited a protection rate of 25 % compared with unvaccinated mice. When vaccine containing 411 and the adjuvant Montanide ISA 70 VG were tested, the protection rate reached 40%. Serological analysis demonstrates a good IgG1 and IgG2a response amplified in adjuvanted group. Intestinal tissue sections did not show mastocytosis after vaccination, as observed in a natural infection. These results demonstrated that 411 antigen induced both a protective role in anti-Trichinella vaccine and a moderate immunostimulation of mast cells in vivoPARIS-BIUSJ-Biologie recherche (751052107) / SudocSudocFranceF

Conception d'un outil de débogage formel pour systèmes logiciels et matériels selon l'approche "Debug as Design"

PARIS7-Bibliothèque centrale (751132105) / SudocSudocFranceF

Analyse d'une consultation conjointe de neuropédiatrie et pédopsychiatrie au CHRU de Lille (réflexion et perspectives)

LILLE2-BU Santé-Recherche (593502101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

DISTRICTLAB-H: A new tool to optimize the design and operation of district heating and cooling networks

International audienceThis article introduces a new scalable thermo-hydraulic modeling framework for dynamic simulation of small to large-scale District Heating (DH) and Cooling (DC) networks. The roots of this new development are to be found in the need for a more efficient solver including an accurate substation model. Following a comprehensive literature review, the solver is presented and validated using existing dynamic experimental data for a straight pipe. In a following step, a real large DH network, from the city of Metz (FR), is modeled and simulated, with results showing good consistency with field data. The numerical efficiency of the proposed approach is then assessed, leading to a quasi-linear scaling of the algorithm up to sizes comparable to the largest DH systems in Europe and to performances that compares very favorably to other models described in the literature. This work opens pathways towards the definition of advanced network architecture and the optimization of design and control strategies. To illustrate these new possibilities, the last section briefly presents real life use cases addressed with the tool such as the evaluation of an innovative 3-tubes architecture, the network resizing for lowering the temperature and the real time control optimization of the supply temperature

DISTRICTLAB-H: A new tool to optimize the design and operation of district heating and cooling networks

International audienceThis article introduces a new scalable thermo-hydraulic modeling framework for dynamic simulation of small to large-scale District Heating (DH) and Cooling (DC) networks. The roots of this new development are to be found in the need for a more efficient solver including an accurate substation model. Following a comprehensive literature review, the solver is presented and validated using existing dynamic experimental data for a straight pipe. In a following step, a real large DH network, from the city of Metz (FR), is modeled and simulated, with results showing good consistency with field data. The numerical efficiency of the proposed approach is then assessed, leading to a quasi-linear scaling of the algorithm up to sizes comparable to the largest DH systems in Europe and to performances that compares very favorably to other models described in the literature. This work opens pathways towards the definition of advanced network architecture and the optimization of design and control strategies. To illustrate these new possibilities, the last section briefly presents real life use cases addressed with the tool such as the evaluation of an innovative 3-tubes architecture, the network resizing for lowering the temperature and the real time control optimization of the supply temperature

Narcose à l'azote (modulation de la neurotransmission striatale chez le rat et implication des canaux potassiques TREK-1 chez la souris)

AIX-MARSEILLE2-BU Méd/Odontol. (130552103) / SudocSudocFranceF

Generation and evaluation of a synthetic dataset to improve fault detection in district heating and cooling systems

International audienceThis paper investigates various types of faults in District Heating & Cooling (DHC) systems. Many authors point out that the lack of data hinders the development of good data-driven models for fault detection and diagnosis (FDD). This work aims at providing the research community with a reference dataset of simulated faults for DHC components, as well as demonstrating the usefulness of the approach. The dataset itself covers six types of DHC system components, covering production, distribution and storage. It is provided as Open Data with corresponding documentation. The models used for generating the dataset are mostly based on Open Source Modelica libraries, and are provided as Open Source code. To assess the usefulness of the dataset, we provide evaluation of five Machine Learning (ML) models. The results highlight discrepancies among the considered tasks, with faults related to global energy efficiency being easier to handle than those related specifically to thermal losses. We also observe that three of the investigated models (Logistic Regression, Support Vector Machine, and XGBoost) provide consistent performance on the considered tasks. The key novelty of this paper is to present, document and evaluate a consistent and reusable framework for boosting research on FDD in DHC systems

Assessment of varying coupling levels between electric and thermal networks at district level using Co-simulation and model-predictive Control

International audienceThis study focuses on the co-simulation of the heating and electrical systems of a district. A heat pump, a gas boiler, a biomass cogeneration, a photovoltaic plant and the national electric grid provide electricity and heat consumed by thirteen residential buildings. Two storage units are present: a heat storage (hot water tank) and an electric storage (chemical battery). Architecture design and pre-sizing of components have previously been computed by MILP optimizations. As part of the Trilogy platform, a co-simulation platform Pegase runs the grid control and the detailed physical models developed using Modelica (heat system) and Simulink (electric system). A model predictive control (MPC) based on sliding time window MILP optimisations manages the flexibility of the multi energy system and insures the balance between production and consumption. The objective of the optimizations is to minimise CO2 equivalent emission costs and operational costs of each component, including the purchase of gas, biomass and electricity. A parametric study on the coupling strength between the electric and the heat system is performed by modifying the price of the electricity purchased from the national grid. Multiple scenarios with different thermoelectric coupling strength are analysed to show the dependency of the energy mix on the coupling strength. With increasing coupling, photovoltaic self-consumption increases and heat generation gradually shifts from the heat pump to the biomass cogeneration and to the gas boiler. This study also demonstrates how the Trilogy platform tools enable easy implementation of optimal control on cosimulations of multi energy detailed physical models

Assessment of varying coupling levels between electric and thermal networks at district level using Co-simulation and model-predictive Control

International audienceThis study focuses on the co-simulation of the heating and electrical systems of a district. A heat pump, a gas boiler, a biomass cogeneration, a photovoltaic plant and the national electric grid provide electricity and heat consumed by thirteen residential buildings. Two storage units are present: a heat storage (hot water tank) and an electric storage (chemical battery). Architecture design and pre-sizing of components have previously been computed by MILP optimizations. As part of the Trilogy platform, a co-simulation platform Pegase runs the grid control and the detailed physical models developed using Modelica (heat system) and Simulink (electric system). A model predictive control (MPC) based on sliding time window MILP optimisations manages the flexibility of the multi energy system and insures the balance between production and consumption. The objective of the optimizations is to minimise CO2 equivalent emission costs and operational costs of each component, including the purchase of gas, biomass and electricity. A parametric study on the coupling strength between the electric and the heat system is performed by modifying the price of the electricity purchased from the national grid. Multiple scenarios with different thermoelectric coupling strength are analysed to show the dependency of the energy mix on the coupling strength. With increasing coupling, photovoltaic self-consumption increases and heat generation gradually shifts from the heat pump to the biomass cogeneration and to the gas boiler. This study also demonstrates how the Trilogy platform tools enable easy implementation of optimal control on cosimulations of multi energy detailed physical models