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Patients with inflammatory bowel disease (IBD) are at increased risk of thrombotic events. Therapies for IBD have the potential to modulate this risk. The aims of this Evidence-Based Guideline were to summarize available evidence and to provide practical recommendations regarding epidemiological aspects, prevention and drug-related risks of venous and arterial thrombotic events in patients with IBD. A virtual meeting took place in May 2020 involving 14 international IBD experts and 3 thrombosis experts from 12 countries. Proposed statements were voted upon in an anonymous manner. Agreement was defined as at least 75% of participants voting as ‘fully agree’ or ‘mostly agree’ with each statement. For each statement, the level of evidence was graded according to the Scottish Intercollegiate Guidelines Network (SIGN) grading system. Consensus was reached for 19 statements. Patients with IBD harbour an increased risk of venous and arterial thrombotic events. Thromboprophylaxis is indicated during hospitalization of any cause in patients with IBD. Disease activity is a modifiable risk factor in patients with IBD, and physicians should aim to achieve deep remission to reduce the risk. Exposure to steroids should be limited. Antitumour necrosis factor agents might be associated with a reduced risk of thrombotic events., Patients with inflammatory bowel disease (IBD) are at increased risk of thrombotic events. This Evidence-Based Guideline presents an international consensus on the prevention of venous and arterial thrombotic events in patients with IBD, and includes 19 recommendations for clinical practice.

Predictions of physical phenomena in buildings are carried out by using physical models formulated as a mathematical problem and solved by means of numerical methods, aiming at evaluating, for instance, the building thermal or hygrothermal performance by calculating distributions and fluxes of heat and moisture transfer. Therefore, the choice of the numerical method is crucial since it is a compromise among (i) the solution accuracy, (ii) the computational cost to obtain the solution and (iii) the complexity of the method implementation. An efficient numerical method enables to compute an accurate solution with a minimum computational run time (CPU). On that account, this article brings an investigation on the performance of three numerical methods. The first one is the standard and widely used finite-difference approach, while the second one is the so-called RC approach, which is a particular method brought to the building physics area by means of an analogy of electric circuits. The third numerical method is the spectral one, which has been recently proposed to solve nonlinear diffusive problems in building physics. The three methods are evaluated in terms of accuracy on the assessment of the dependent variable (temperature or vapor pressure) or of density of fluxes for three different cases: i) heat diffusion through a concrete slab, ii) moisture diffusion through an aerated concrete slab and iii) heat diffusion using measured temperatures as boundary conditions. Results highlight the spectral approach as the most accurate method. The RC based model with a few number of resistances does not provide accurate results for temperature and vapor pressure distributions neither to flux densities nor conduction loads., 35 pages, 19 figures, 2 tables, 42 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

International audience; The integration gap between the environment and urbanization is one of the major weaknesses of the Brazilian planning and management system. We understand that this gap is a result, among other factors, of the intersectional and intercalary articulation lack between the various existing planning instruments and the different scales. Using the overlapping boundaries related to the Sinos’ River Basin and other territorial structures belonging to the Porto Alegre Metropolitan Region, as an example, we guided this debate towards an approach that takes into account the scalar articulation of socioeconomic structures and environmental issues. We propose to consider scale flexibility through new forms of articulation between instruments, adapted to the different scales and their variability, through a preliminary drawing.; Le manque d'intégration entre l'environnement et l’urbanisation est l'un des plus gros problèmes du système de planification et de gestion brésilien. Nous comprenons que cet écart est une conséquence de l’absence d’articulation intersectorielle et interscalaire entre les différents instruments de planification existants. En utilisant comme illustration la superposition des limites liées au bassin hydrographique du Fleuve dos Sinos et aux autres périmètres pertinents à la région métropolitaine de Porto Alegre, nous orientons ce débat vers une approche qui prend en compte l'articulation scalaire des structures socioéconomiques et les questions environnementales. Nous proposons donc d'envisager la flexibilité scalaire à travers de nouvelles formes d'articulation entre instruments, adaptées à la multiplicité des échelles et à leur variabilité par un schéma provisoire.; A falta de integração entre meio ambiente e urbanização constitui um dos maiores problemas do sistema de planejamento e gestão brasileiros. Entendemos que essa lacuna é consequência, dentre outros fatores, da falta de articulação intersetorial e interescalar entre os diversos instrumentos de planejamento existentes nas diferentes escalas. Utilizando a sobreposição de limites relativos à Bacia Hidrográfica do Rio dos Sinos e demais estruturas territoriais pertencentes à Região Metropolitana de Porto Alegre como exemplo, orientamos este debate em direção a uma abordagem que leve em conta a articulação escalar das estruturas socioeconômicas e as questões ambientais. Propomos, assim, considerar a flexibilidade escalar através de novas formas de articulação entre instrumentos, adaptados à multiplicidade de escalas e sua variabilidade, por meio de um desenho preliminar.

A two-dimensional model is proposed for energy efficiency assessment through the simulation of heat transfer in building envelopes, considering the influence of the surrounding environment. The model is based on the \DF ~approach that provides an explicit scheme with a relaxed stability condition. The model is first validated using an analytical solution and then compared to three other standard schemes. Results show that the proposed model offers a good compromise in terms of high accuracy and reduced computational efforts. Then, a more complex case study is investigated, considering non-uniform shading effects due to the neighboring buildings. In addition, the surface heat transfer coefficient varies with wind velocity and height, which imposes an addition non-uniform boundary condition. After showing the reliability of the model prediction, a comparison over almost $120$ cities in France is carried out between the two- and the one-dimensional approaches of the current building simulation programs. Important discrepancies are observed for regions with high magnitudes of solar radiation and wind velocity. Last, a sensitivity analysis is carried out using a derivative-based approach. It enables to assess the variability of the solution according to the modeling of the two-dimensional boundary conditions. Moreover, the proposed model computes efficiently the solution and its sensitivity to the modeling of the urban environment.

Automatic detection of negated content is often a prerequisite in information extraction systems in various domains. In the biomedical domain especially, this task is important because negation plays an important role. In this work, two main contributions are proposed. First, we work with languages which have been poorly addressed up to now: Brazilian Portuguese and French. Thus, we developed new corpora for these two languages which have been manually annotated for marking up the negation cues and their scope. Second, we propose automatic methods based on supervised machine learning approaches for the automatic detection of negation marks and of their scopes. The methods show to be robust in both languages (Brazilian Portuguese and French) and in cross-domain (general and biomedical languages) contexts. The approach is also validated on English data from the state of the art: it yields very good results and outperforms other existing approaches. Besides, the application is accessible and usable online. We assume that, through these issues (new annotated corpora, application accessible online, and cross-domain robustness), the reproducibility of the results and the robustness of the NLP applications will be augmented.

41 pages, 13 figures, 2 tables, 32 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/; International audience; This article proposes an efficient explicit numerical model with a relaxed stability condition for the simulation of heat, air and moisture transfer in porous material. Three innovative approaches are combined to solve the system of three partial differential equations. The Du Fort-Frankel scheme is used to solve the diffusion equation, providing an explicit scheme with an extended stability region. The two advection--diffusion equations are solved using both Scharfetter-Gummel numerical scheme for the space discretisation and the two-step Runge-Kutta method for the time variable. This combination enables to relax the stability condition by one order. The proposed numerical model is evaluated on three case studies. The first one considers quasi-linear coefficients to confirm the theoretical results by numerical computations. The stability condition is relaxed by a factor of 40 compared to the standard approach. The second case provides an analytical solution for weakly nonlinear problem. A very satisfactory accuracy is observed between the reference solution and the one provided by the numerical model. The last case study assumes more realistic application with nonlinear coefficients and Robin-type boundary conditions. The computational time is reduced 10 times by using the proposed model in comparison with the explicit Euler method.

International audience; The present work deals with the application of coevolutionary algorithms and artificial neural networks to perform input selection and related parameter estimation for nonlinear black-box models in system identification. In order to decouple the resolution of the input selection and parameter estimation, we propose a problem decomposition formulation and solve it by a coevolutionary algorithm strategy. The novel methodology is successfully applied to identify a magnetorheological damper, a continuous polymerization reactor and a piezoelectric robotic micromanipulator. The results show that the method provides valid models in terms of accuracy and statistical properties. The main advantage of the method is the joint input and parameter estimation, towards automating a tedious and error prone procedure with global optimization algorithms.

Named entity recognition (NER) is key for biomedical applications as it allows knowledge discovery in free text data. As entities are semantic phrases, their meaning is conditioned to the context to avoid ambiguity. In this work, we explore contextualized language models for NER in French biomedical text as part of the Défi Fouille de Textes challenge. Our best approach achieved an F1 -measure of 66% for symptoms and signs, and pathology categories, being top 1 for subtask 1. For anatomy, dose, exam, mode, moment, substance, treatment, and value categories, it achieved an F1 -measure of 75% (subtask 2). If considered all categories, our model achieved the best result in the challenge, with an F1 -measure of 72%. The use of an ensemble of neural language models proved to be very effective, improving a CRF baseline by up to 28% and a single specialised language model by 4 La reconnaissance des entités nommées (NER) est essentielle pour les applications biomédicales car elle permet la découverte de connaissances dans des données en texte libre. Comme les entités sont des phrases sémantiques, leur signification est conditionnée par le contexte pour éviter toute ambiguïté. Dans ce travail, nous explorons les modèles de langage contextualisés pour la NER dans les textes biomédicaux français dans le cadre du Défi Fouille de Textes. Notre meilleure approche a obtenu une mesure F1 de 66% pour les symptômes et les signes, et les catégories de pathologie, en étant dans le top 1 pour la sous-tâche 1. Pour les catégories anatomie, dose, examen, mode, moment, substance, traitement et valeur, elle a obtenu une mesure F1 de 75% (sous-tâche 2). Si l’on considère toutes les catégories, notre modèle a obtenu le meilleur résultat dans le cadre de ce défi, avec une mesure F1 de 72%. L’utilisation d’un ensemble de modèles de langages neuronaux s’est révélée très efficace, améliorant une base de référence du CRF de 28% et un modèle de langage spécialisé unique de 4%.

Implicit schemes require important sub-iterations when dealing with highly nonlinear problems such as the combined heat and moisture transfer through porous building elements. The computational cost rises significantly when the whole-building is simulated, especially when there is important coupling among the building elements themselves with neighbouring zones and with HVAC (Heating Ventilation and Air Conditioning) systems. On the other hand, the classical Euler explicit scheme is generally not used because its stability condition imposes very fine time discretisation. Hence, this paper explores the use of an improved explicit approach - the Dufort-Frankel scheme - to overcome the disadvantage of the classical explicit one and to bring benefits that cannot be obtained by implicit methods. The Dufort-Frankel approach is first compared to the classical Euler implicit and explicit schemes to compute the solution of nonlinear heat and moisture transfer through porous materials. Then, the analysis of the Dufort-Frankel unconditionally stable explicit scheme is extended to the coupled heat and moisture balances on the scale of a one- and a two-zone building models. The Dufort-Frankel scheme has the benefits of being unconditionally stable, second-order accurate in time O(dt^2) and to compute explicitly the solution at each time step, avoiding costly sub-iterations. This approach may reduce the computational cost by twenty, as well as it may enable perfect synchronism for whole-building simulation and co-simulation., 38 pages, 19 figures, 3 tables, 28 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

Pixel counting (PxC) emerged as a powerful technique for external solar shading calculations of buildings, providing accurate results with great computational efficiency even for dense geometries. Motivated by this fact and because the technique can be also adapted to cope with interior surfaces without further ado, this paper aims at experimentally evaluating the PxC technique implemented in Domus software for calculating sun patch distribution within building enclosures. For the validation purpose, digital images were taken from the surfaces of an experimental house to compare with the simulation results obtained by using EnergyPlus and two PxC based tools: Domus and Shading II SketchUp plug-in. This first task has shown that the PxC presents results in good agreement with the experimental data, in terms of both location and area of the sun patch. Also, a second case study was constructed to evaluate the capability of PxC for simulating non-convex zones with perforated shading elements. The results, in general, have shown that the PxC can provide accurate results in situations where polygon clipping based algorithms cannot be applied.

This work presents a detailed mathematical model combined with an innovative efficient numerical model to predict heat, air and moisture transfer through porous building materials. The model considers the transient effects of air transport and its impact on the heat and moisture transfer. The achievement of the mathematical model is detailed in the continuity of Luikov's work. A system composed of two advection-diffusion differential equations plus one exclusively diffusion equation is derived. The main issue to take into account the transient air transfer arises in the very small characteristic time of the transfer, implying very fine discretisation. To circumvent these difficulties, the numerical model is based on the Du Fort-Frankel explicit and unconditionally stable scheme for the exclusively diffusion equation. It is combined with a two-step Runge-Kutta scheme in time with the Scharfetter-Gummel numerical scheme in space for the coupled advection-diffusion equations. At the end, the numerical model enables to relax the stability condition, and, therefore, to save important computational efforts. A validation case is considered to evaluate the efficiency of the model for a nonlinear problem. Results highlight a very accurate solution computed about 16 times faster than standard approaches. After this numerical validation, the reliability of the mathematical model is evaluated by comparing the numerical predictions to experimental observations. The latter is measured within a multi-layered wall submitted to a sudden increase of vapor pressure on the inner side and driven climate boundary conditions on the outer side. A very satisfactory agreement is noted between the numerical predictions and experimental observations indicating an overall good reliability of the proposed model., Comment: 46 pages, 12 figures, 3 tables, 46 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

Dual-fuel technology enables Diesel engines to use natural gas as fuel injected into the intake. Ignition is achieved through the injection of fuels with high cetane numbers. This technology offers a cleaner and more economical burning for commercial engines. However, this fuel change leads to an increase in the tip temperature of the injector nozzle, causing the formation of deposits and coking in this component. Here, experimental and numerical studies were carried out in an engine converted to operate in dual-fuel mode, with the aim of developing a model to predict the dome temperature of the diesel injector nozzle. The following relevant parameters were found: the rate of Diesel replacement by compressed natural gas, combustion center, air-fuel equivalence ratio, Diesel injection pressure, exhaust gases recirculation rate, plenum air temperature, and engine coolant temperature. The tip temperature results were analyzed and except for the Diesel injection pressure, every parameter was found to influence this temperature being optimized. The temperature obtained through a new model shows a good correlation with the values measured with a deviation of less than 2% when the amount of Diesel injected is varied, and less than 1% when the engine coolant temperature and combustion center are varied.

It is well known that thermal insulation is a leading strategy for reducing energy consumption associated to heating or cooling processes in buildings. Nevertheless, building insulation can generate high expenditures so that the selection of an optimum insulation thickness requires a detailed energy simulation as well as an economic analysis. In this way, the present study proposes an innovative non-uniform adaptive method to determine the optimal insulation thickness of external walls. First, the method is compared with a reference solution to properly understand the features of the method, which can provide high accuracy with less spatial nodes. Then, the adaptive method is used to simulate the transient heat conduction through the building envelope of buildings located in Brazil, where there is a large potential of energy reduction. Simulations have been efficiently carried out for different wall and roof configurations, showing that the innovative method efficiently provides a gain of 25% on the computer run time., 36 pages, 18 figures, 6 tables, 42 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

This paper deals with an inverse problem applied to the field of building physics to experimentally estimate three sorption isotherm coefficients of a wood fiber material. First, the mathematical model, based on convective transport of moisture, the Optimal Experiment Design (OED) and the experimental set-up are presented. Then measurements of relative humidity within the material are carried out, after searching the OED, which is based on the computation of the sensitivity functions and a priori values of the unknown parameters employed in the mathematical model. The OED enables to plan the experimental conditions in terms of sensor positioning and boundary conditions out of 20 possible designs, ensuring the best accuracy for the identification method and, thus, for the estimated parameter. Two experimental procedures were identified: i) single step of relative humidity from 10% to 75% and ii) multiple steps of relative humidity 10-75-33-75% with an 8-day duration period for each step. For both experiment designs, it has been shown that the sensor has to be placed near the impermeable boundary. After the measurements, the parameter estimation problem is solved using an interior point algorithm to minimize the cost function. Several tests are performed for the definition of the cost function, by using the L^2 or L^\infty norm and considering the experiments separately or at the same time. It has been found out that the residual between the experimental data and the numerical model is minimized when considering the discrete Euclidean norm and both experiments separately. It means that two parameters are estimated using one experiment while the third parameter is determined with the other experiment. Two cost functions are defined and minimized for this approach. Moreover, the algorithm requires less than 100 computations of the direct model to obtain the solution. In addition, the OED sensitivity functions enable to capture an approximation of the probability distribution function of the estimated parameters. The determined sorption isotherm coefficients calibrate the numerical model to fit better the experimental data. However, some discrepancies still appear since the model does not take into account the hysteresis effects on the sorption capacity. Therefore, the model is improved proposing a second differential equation for the sorption capacity to take into account the hysteresis between the main adsorption and desorption curves. The OED approach is also illustrated for the estimation of five of the coefficients involved in the hysteresis model. To conclude, the prediction of the model with hysteresis are compared with the experimental observations to illustrate the improvement of the prediction., 51 pages, 20 figures, 4 tables and 56 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

This work presents an efficient numerical method based on spectral expansions for simulation of heat and moisture diffusive transfers through multilayered porous materials. Traditionally, by using the finite-difference approach, the problem is discretized in time and space domains (Method of lines) to obtain a large system of coupled Ordinary Differential Equations (ODEs), which is computationally expensive. To avoid such a cost, this paper proposes a reduced-order method that is faster and accurate, using a much smaller system of ODEs. To demonstrate the benefits of this approach, tree case studies are presented. The first one considers nonlinear heat and moisture transfer through one material layer. The second case - highly nonlinear - imposes a high moisture content gradient - simulating a rain like condition - over a two-layered domain, while the last one compares the numerical prediction against experimental data for validation purposes. Results show how the nonlinearities and the interface between materials are easily and naturally treated with the spectral reduced-order method. Concerning the reliability part, predictions show a good agreement with experimental results, which confirm robustness, calculation efficiency and high accuracy of the proposed approach for predicting the coupled heat and moisture transfer through porous materials., Comment: 44 pages, 17 figures, 6 tables, 50 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

This paper presents a novel approach for image retrieval and pattern spotting in document image collections. The manual feature engineering is avoided by learning a similarity-based representation using a Siamese Neural Network trained on a previously prepared subset of image pairs from the ImageNet dataset. The learned representation is used to provide the similarity-based feature maps used to find relevant image candidates in the data collection given an image query. A robust experimental protocol based on the public Tobacco800 document image collection shows that the proposed method compares favorably against state-of-the-art document image retrieval methods, reaching 0.94 and 0.83 of mean average precision (mAP) for retrieval and pattern spotting (IoU=0.7), respectively. Besides, we have evaluated the proposed method considering feature maps of different sizes, showing the impact of reducing the number of features in the retrieval performance and time-consuming., Comment: Accepted for IJCNN 2019

WOS:000384783000064; International audience; In this work, a mathematical optimization procedure was used to improve the gas exchange process of a single-cylinder compression ignition naturally aspirated engine. Duct lengths and valve timing were chosen as optimization variables while volumetric efficiency was defined as the objective function. Calculations were carried out using a parallelized computational code consisting of (i) a one-dimensional model for the unsteady compressible gas flow taking place in intake and exhaust ducts; (ii) a single-zone combustion model for the in-cylinder processes; and (iii) an optimization routine based on the Differential Evolution technique. Three sets of optimization calculations were conducted. In the first one, the intake duct length was the only optimization variable and it was found that optimal inlet duct lengths vary becoming shorter as engine speed is increased. In the second set of calculations, both intake and exhaust duct lengths have been taken as the optimization variables, and the resulting optimal intake duct lengths were quite similar to those of the first set. In addition, optimal exhaust duct lengths resulted very close in value to optimal intake duct lengths, except at the highest speeds, when the decreasing tendency as engine speed is raised was supplanted by the opposite tendency. In the third set of calculations, the crank angles defining valve synchronism were the optimization variables. It was found that optimal valve timing produced a gain in volumetric efficiency, which is similar to that obtained with optimal duct lengths. (C) 2016 Elsevier Ltd. All rights reserved.

Innovative and efficient ways to carry out numerical simulations are worth of investigation to reduce the computational complexity of building models and make it possible to solve complex problems. This paper presents a reduced order model, based on Proper Generalised Decomposition (PGD), to assess 2-dimensional heat and moisture transfer in walls. This model is associated with the multizone model Domus using an indirect coupling method. Both models are co-simulated to perform whole-building hygrothermal simulation, considering 2D transfer in walls. The whole-building model is first validated with data from the IEA Annex 41. Then, a case study is considered taking into account a 2-zones building with an intermediary shared wall modelled in 2 dimensions to illustrate the importance of the technique to analyse the hygrothermal behaviour of the wall. It has been highlighted that the whole model enables to perform more precisely analyses such as mould growth on the internal surface. In addition, important theoretical numerical savings (90%) are observed when compared to the large original model. However, the effective numerical savings are not so important (40%) due to the limitations of the co-simulation method.

Moisture is one of the main issues in building disorders. It can lead to microorganism’s growth, material deterioration and impact on energy consumption. A comprehensive overview on the scale of the country considering climatic conditions may be an important starting point for potential moisture risks in building analyses. In this paper, we present a method in which weather-based indicators are developed for a first outline of the potential moisture risk in buildings considering the main climatic sources of moisture. The proposed method is related to weather parameters, comprising two new indicators - in a total of three - that are plotted in the country map using Geographic Information System to spatially represent the risk across the country territory. The method is applied for Brazil, and results indicate high weather-based moisture risks in highly densely populated areas. The case study highlights the importance of the presented methodology as a first analysis of potential moisture risk on a country scale.

This work presents an alternative view on the numerical simulation of diffusion processes applied to the heat and moisture transfer through porous building materials. Traditionally, by using the finite-difference approach, the discretization follows the Method Of Lines (MOL), when the problem is first discretized in space to obtain a large system of coupled Ordinary Differential Equations (ODEs). Thus, this paper proposes to change this viewpoint. First, we discretize in time to obtain a small system of coupled ODEs, which means instead of having a Cauchy (Initial Value) Problem (IVP), we have a Boundary Value Problem (BVP). Fortunately, BVPs can be solved efficiently today using adaptive collocation methods of high order. To demonstrate the benefits of this new approach, three case studies are presented, in which one of them is compared with experimental data. The first one considers nonlinear heat and moisture transfer through one material layer while the second one considers two material layers. Results show how the nonlinearities and the interface between materials are easily treated, by reasonably using a fourth-order adaptive method. Finally, the last case study compares numerical results with experimental measurements, showing a good agreement., Comment: 45 pages, 21 figures, 5 tables, 47 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

This paper proposes a novel approach for content based graphical object retrieval in document images. The chal- lenge is to search for occurrences of a queried graphical objects in document images that can vary in terms of color, shape, texture and quality, increasing considerably the level of difficulty of the retrieval process. To that end, the manual feature engineering is avoided by learning the image representation for the retrieval task using a Convolutional Neural Network (CNN). However, such a representation should be as compact as possible to allow a fast document image retrieval and storage. Thus, a pretrained CNN model is used to cope with the lack of training data, which is fine tuned to achieve a compact yet discriminant representation of the graphical objects. From experiments conducted on the public Tobacco800 document image collection, we show that the proposed method compares favorably against state-of-the- art document image retrieval methods, reaching 0.72 of average precision $(\mathrm {m}\mathrm {A}\mathrm {P})$. In addition, an increase of 4 percentage points in the average precision is observed using a compact deep representation in which the number of features is reduced by 16 times, thus allowing a reduction of 47% in terms of computation time by the image retrieval task.

International audience; Automatic detection of negated content is often a prerequisite in information extraction systems, especially in the biomedical domain. This paper proposes our contributions on negation scope detection in French and Brazilian Portuguese. We introduce two corpora mainly built with excerpts from clinical trial protocols, describing the inclusion criteria of patients. The corpora have been manually annotated for marking up the negation cues and their scope. Then, we propose a recurrent neural networks approach to acquire the scopes. MOTS-CLÉS : négation, français, portugais brésilien, apprentissage supervisé, réseau de neurones.; La détection automatique de la négation fait souvent partie des pré-requis dans les systèmes d'extraction d'information, notamment dans le domaine biomédical. Cet article présente nos contributions concernant la détection de la portée de la négation en français et portugais brésilien. Nous présentons d'une part deux corpus principalement constitués d'extraits de protocoles d'essais cliniques en français et portugais brésilien, dédiés aux critères d'inclusion de patients. Les marqueurs de négation et leurs portées y ont été annotés manuellement. Nous présentons d'autre part une approche par réseau de neurones récurrents pour extraire les portées.

Comparisons of experimental observation of heat and moisture transfer through porous building materials with numerical results have been presented in numerous studies reported in literature. However, some discrepancies have been observed, highlighting underestimation of sorption process and overestimation of desorption process. Some studies intend to explain the discrepancies by analysing the importance of hysteresis effects as well as carrying out sensitivity analyses on the input parameters as convective transfer coefficients. This article intends to investigate the accuracy and efficiency of the coupled solution by adding advective transfer of both heat and moisture in the physical model. In addition, the efficient Scharfetter and Gummel numerical scheme is proposed to solve the system of advection-diffusion equations, which has the advantages of being well-balanced and asymptotically preserving. Moreover, the scheme is particularly efficient in terms of accuracy and reduction of computational time when using large spatial discretisation parameters. Several linear and non-linear cases are studied to validate the method and highlight its specific features. At the end, an experimental benchmark from the literature is considered. The numerical results are compared to the experimental data for a pure diffusive model and also for the proposed model. The latter presents better agreement with the experimental data. The influence of the hysteresis effects on the moisture capacity is also studied, by adding a third differential equation., 51 pages, 21 figures, 3 tables, 44 references. Other author's publications can be downloaded at http://www.denys-dutykh.com/

This paper presents a practical application of the concept of Optimal Experiment Design (OED) for the determination of properties of porous materials with in-situ measurements and an identification method. First, an experimental set-up was presented and used for the measurement of relative humidity within a wood fibre material submitted to single and multiple steps of relative humidity variation. Then, the application of OED enabled to plan the experimental conditions in terms of sensor positioning and boundary conditions out of 20 possible designs. The OED search was performed using the Fisher information matrix and a priori knowledge of the parameters. It ensures to provide the best accuracy of the identification method and thus the estimated parameter. Optimal design results have been found for single steps from the relative humidity phi = 10 to 75%, with one sensor located at the position X between 4 and 6 cm, for the estimation of moisture permeability coefficients, while from phi = 75% to phi = 33%, with one sensor located at X{\deg} = 3 cm, for the estimation of the advection coefficient. The OED has also been applied for the identification of couples of parameters. A sample submitted to multiple relative humidity steps (phi = 10-75-33-75%) with a sensor placed at X{\deg} = 5 cm was found as the best option for determining both properties with the same experiment. These OED parameters have then been used for the determination of moisture permeability and advection coefficients. The estimated moisture permeability coefficients are twice higher than the a priori values obtained using standard methods. The advection parameter corresponds to the mass average velocity of the order of v = 0.01 mm/s within the material and may play an important role on the simulation of moisture front., Comment: 34 pages, 14 figures, 6 tables, 43 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/. arXiv admin note: text overlap with arXiv:1704.06565

International audience; Organizations faces the challenge to adapt their business process according changes that may occur in the dynamic environment in which they operate. These changes happen for different reasons, such as the introduction of new laws, changes in customers' attitudes, changes of legal regulations, among others. The result is the existence of different versions of the same process, known as process variants (Valença et al., 2013), which aim to represent all the related contexts that may differ in activities, resources, control flow and data. Thus, it is common organizations to maintain repositories containing a collection of related process variants, known as process family (Reichert & Weber, 2012). As designing and implementing each process variant from scratch and maintaining it separately would be inefficient and costly for companies (Ayora et al., 2013), several approaches emerged aiming to support the representation of a family of business process variants via a single model. Such model is known as customizable process model, from which each variant can be derived via certain model transformations such as add, delete or move. The element of the process model that can be customized via transformations is known as variation point (La Rosa et al., 2017). There are two approaches to variability management: by restriction and by extension. The first approach, also known as configurable process model, refers to a customizable process model that contains all behaviour of all process variants. In this approach, the customization is achieved by restricting the behaviour of the customizable process model using the delete operation. The second approach refers to a customizable process model that represents the most common behaviour, or the behaviour that is shared by most process variants. For the customization, the behaviour needs to be extended using the insert and modification operators to represent a particular situation (La Rosa et al., 2017; Asadi et al., 2014). These approaches permit redundancies to be eliminated by representing variant commonalities only once (Ayora et al., 2012) thus providing a global view of the business process variants (Assy et al., 2015). It also fosters model reuse, i.e., parts of the model can be shared among multiple variants (Reichert & Weber, 2012) and comparison (Buijs et al., 2013). In both approaches, selection of the most suitable variant is referred to as configuration or customization, which consists in selecting the alternatives available for each variation point. The goal of configuring a process model is to adapt the model such that it fits the model user's individual needs better than the original process model. Thus, configuring a process model means to limit the behaviour depicted by an existing process model in such a way that it only allows for the desired behaviour of the model (Gottschalk, 2009). When configuring process variants, one challenge is to design a single basic process model from which the process variants can be configured. Another challenge is to design, model, and structure the adjustments that may be applied to configure the different process variants to this basic process model (Hallerbach et al., 2010). Besides, the process variant need be correctly configured. For example, if a model element or an entire path is removed during the customization, the remaining model elements need to be reconnected to ensure the syntactic correctness. Also, the configuration of variation points attached to parallel splits, decision points and synchronization points may lead to the introduction of problems (e.g., deadlocks) (La Rosa, 2009; van der Aalst et al., 2008).

This paper presents a review of the use of model reduction techniques for building physics applications. The use of separated representations, the so called Proper Generalised Decomposition (PGD), is particularly investigated. This technique can be applied for efficient building physics modelling at different levels: the wall and multizone models, the whole-building (coupled envelope and air volumes) simulation and their practical applications. The PGD can be formulated as a space-time representation to provide fast and accurate solutions of 2- and 3-dimensional problems at the wall or the whole-building level. Furthermore, the PGD solution allows to treat efficiently parametric problems of practical building applications.

International audience; This paper presents a mobility-aware channel allocation strategy for clustered ad hoc network. Our main novelty is to consider the user mobility associated with traffic history and node popularity to guide the channel allocation process, while quickly responding to changes in the network topology. In our performance evaluation and contrarily to related works, we use a realistic mobility model based on user behavior and consider channels with largest spectral distance as well as the smallest number of occurrences. Obtained results show that our strategy presents throughput 15,43 % and 17,74% higher when compared with RANDOM and LD algorithms respectively, and lower overhead when compared with TABU algorithm.

Fulfils concisely traditional numerical methods that can be applied in the field of diffusion transport phenomena.; International audience; This book is the second edition of Numerical methods for diffusion phenomena in building physics: a practical introduction originally published by PUCPRESS (2016). It intends to stimulate research in simulation of diffusion problems in building physics, by providing an overview of mathematical models and numerical techniques such as the finite difference and finite-element methods traditionally used in building simulation tools. Nonconventional methods such as reduced order models, boundary integral approaches and spectral methods are presented, which might be considered in the next generation of building-energy-simulation tools. In this reviewed edition, an innovative way to simulate energy and hydrothermal performance are presented, bringing some light on innovative approaches in the field.

It is of great concern to produce numerically efficient methods for moisture diffusion through porous media, capable of accurately calculate moisture distribution with a reduced computational effort. In this way, model reduction methods are promising approaches to bring a solution to this issue since they do not degrade the physical model and provide a significant reduction of computational cost. Therefore, this article explores in details the capabilities of two model-reduction techniques - the Spectral Reduced-Order Model (Spectral-ROM) and the Proper Generalised Decomposition (PGD) - to numerically solve moisture diffusive transfer through porous materials. Both approaches are applied to three different problems to provide clear examples of the construction and use of these reduced-order models. The methodology of both approaches is explained extensively so that the article can be used as a numerical benchmark by anyone interested in building a reduced-order model for diffusion problems in porous materials. Linear and non-linear unsteady behaviors of unidimensional moisture diffusion are investigated. The last case focuses on solving a parametric problem in which the solution depends on space, time and the diffusivity properties. Results have highlighted that both methods provide accurate solutions and enable to reduce significantly the order of the model around ten times lower than the large original model. It also allows an efficient computation of the physical phenomena with an error lower than 10^{-2} when compared to a reference solution., 42 pages, 14 figures, 1 table, 69 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/. arXiv admin note: text overlap with arXiv:1704.07607

This paper proposes the use of a Spectral method to simulate diffusive moisture transfer through porous materials as a Reduced-Order Model (ROM). The Spectral approach is an a priori method assuming a separated representation of the solution. The method is compared with both classical Euler implicit and Crank-Nicolson schemes, considered as large original models. Their performance - in terms of accuracy, complexity reduction and CPU time reduction - are discussed for linear and nonlinear cases of moisture diffusive transfer through single and multi-layered one-dimensional domains, considering highly moisture-dependent properties. Results show that the Spectral reduced-order model approach enables to simulate accurately the field of interest. Furthermore, numerical gains become particularly interesting for nonlinear cases since the proposed method can drastically reduce the computer run time, by a factor of 100, when compared to the traditional Crank-Nicolson scheme for one-dimensional applications., 42 pages, 22 figures, 2 tables, 51 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

When comparing measurements to numerical simulations of moisture transfer through porous materials a rush of the experimental moisture front is commonly observed in several works shown in the literature, with transient models that consider only the diffusion process. Thus, to overcome the discrepancies between the experimental and the numerical models, this paper proposes to include the moisture advection transfer in the governing equation. To solve the advection-diffusion differential equation, it is first proposed two efficient numerical schemes and their efficiencies are investigated for both linear and nonlinear cases. The first scheme, Scharfetter-Gummel (SG), presents a Courant-Friedrichs-Lewy (CFL) condition but is more accurate and faster than the second scheme, the well-known Crank-Nicolson approach. Furthermore, the SG scheme has the advantages of being well-balanced and asymptotically preserved. Then, to conclude, results of the convective moisture transfer problem obtained with the SG numerical scheme are compared to experimental data from the literature. The inclusion of an advective term in the model may clearly lead to better results than purely diffusive models., 34 pages, 15 figures, 48 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

Published in Camarinha-Matos L., Afsarmanesh H., Fornasiero R. (eds), Collaboration in a Data-Rich World. PRO-VE 2017. IFIP Advances in Information and Communication Technology, vol 506, pp 333-340. Springer, Cham; International audience; Managing process variability enable the process model adaptability according changes in the application environment. In the healthcare area, flexibility is essential to provide a quality treatment because, even patients with the same diagnostic, may follow different paths and suffer different proceedings. Besides, there are many aspects to be considered for the selection of a path, as patient’s symptoms, and clinical guidelines, among others. In this context, this research presents a framework for the management of the process variants through semantic reasoning. The enrichment of the business process with semantics enables the automation of the configuration, thus promoting more flexible and adaptive solutions. The proposed framework helps selecting the appropriate process variant according the patient’s symptoms by reasoning on ontologies based known expertise. In our specific use case, we will use the expertise of the Brazilian guideline for acute ischemic stroke.

International audience; Clinical trials are fundamental for evaluating therapies and diagnosis techniques. Yet, recruitment of patients remains a real challenge. Eligibility criteria are related to terms but also to patient laboratory results usually expressed with numerical values. Both types of information are important for patient selection. We propose to address the processing of numerical values. A set of sentences extracted from clinical trials are manually annotated by four annotators. Four categories are distinguished: C (concept), V (numerical value), U (unit), O (out position). According to the pairs of annotators, the interannotator agreement on the whole annotation sequence CV U goes up to 0.78 and 0.83. Then, an automatic method using CFRs is exploited for creating a supervised model for the recognition of these categories. The obtained F-measure is 0.60 for C, 0.82forV, and 0.76 for U. © Springer International Publishing AG 2017.

International audience; This article presents a user behavior aware channel allocation scheme for mobile ad hoc networks. The proposed scheme uses a distributed approach to dynamically allocate the IEEE 802.11b/g spectrum. Our main contribution is to consider the user behavior, represented by the mobility, traffic, and node degree to guide the channel allocation process. In addition, we use a mobility model based on the social context found in people sharing common interests. The results show that our strategy presents throughput 15,43% and 17,74% higher when compared with RANDOM and LD algorithms, respectively.

In this paper, the use of Bayesian inference is explored for estimating both the thermal conductivity and the internal convective heat transfer coefficient of an old historic building wall. The room air temperature, as well as the temperatures at the surface and within the wall have been monitored during one year and then used to solve the identification problem. With Bayesian inference, the posterior distributions of the unknown parameters are explored based on their prior distributions and on the likelihood function that models the measurement errors. In this work, the Markov Chain Monte Carlo method is used to explore the posterior distribution. The error of the inadequacy of mathematical model are considered using the approximation error model. The distribution of the estimated parameters have a small standard deviation, which illustrates the accuracy of the method. The parameters have been compared to the standard values from the French thermal regulations. The heat flux at the internal surface has been calculated with the estimated parameters and the standard values. It is shown that the standard values underestimate the heat flux of an order by 10%. This study also illustrates the importance of the preliminary diagnosis of a building with the estimation of the thermal properties of the wall for model calibration.

The Planet Formation Imager (PFI) project aims to provide a strong scientific vision for ground-based optical astronomy beyond the upcoming generation of Extremely Large Telescopes. We make the case that a breakthrough in angular resolution imaging capabilities is required in order to unravel the processes involved in planet formation. PFI will be optimised to provide a complete census of the protoplanet population at all stellocentric radii and over the age range from 0.1 to about 100 Myr. Within this age period, planetary systems undergo dramatic changes and the final architecture of planetary systems is determined. Our goal is to study the planetary birth on the natural spatial scale where the material is assembled, which is the "Hill Sphere" of the forming planet, and to characterise the protoplanetary cores by measuring their masses and physical properties. Our science working group has investigated the observational characteristics of these young protoplanets as well as the migration mechanisms that might alter the system architecture. We simulated the imprints that the planets leave in the disk and study how PFI could revolutionise areas ranging from exoplanet to extragalactic science. In this contribution we outline the key science drivers of PFI and discuss the requirements that will guide the technology choices, the site selection, and potential science/technology tradeoffs., Comment: 13 pages, 5 figures, Proceedings of SPIE 2016

ISBN: 978-86-85525-18-6; International audience; Semantic interoperability plays an important role in healthcare domain, essentially it concerns the action of sharing the meaning between the involved entities. The enterprises store all the execution processes data as event log files. The process mining method is one among the possible methods that enable the processes analysis behavior in order to understand, optimize and improve them. However, the standard process mining approaches analyze the process based only on the event log label strings, without consider the semantics behind this label. A semantic approach on the event logs might overcome this problem and could enable the use, reuse and sharing of the embedded knowledge. Most of the research developed in this area focuses on the process dynamic behavior or in clarifying the meaning of the event log label. Therefore, less attention has been paid in the knowledge injection perspective. In this context, the objective of this paper is to show a procedure to enhance the semantic interoperability through the semantic enrichment of event logs with domain ontologies and the application of a formal approach, named Formal Concept Analysis.

In the context of estimating material properties of porous walls based on in-site measurements and identification method, this paper presents the concept of Optimal Experiment Design (OED). It aims at searching the best experimental conditions in terms of quantity and position of sensors and boundary conditions imposed to the material. These optimal conditions ensure to provide the maximum accuracy of the identification method and thus the estimated parameters. The search of the OED is done by using the Fisher information matrix and a priori knowledge of the parameters. The methodology is applied for two case studies. The first one deals with purely conductive heat transfer. The concept of optimal experiment design is detailed and verified with 100 inverse problems for different experiment designs. The second case study combines a strong coupling between heat and moisture transfer through a porous building material. The methodology presented is based on a scientific formalism for efficient planning of experimental work that can be extended to the optimal design of experiments related to other problems in thermal and fluid sciences., Comment: 32 pages, 14 figures, 3 tables, 34 references. Other author's papers can be downloaded at http://www.denys-dutykh.com/

International audience; In this work, we present a generic fast hue-preserving histogram equalization method based on the RGB color space for image contrast enhancement and two instantiation of that generic process. The first method uses R-red, G-green, and B-blue 1D histograms to estimate a RGB 3D histogram to be equalized, whereas the second method uses RG, RB, and GB 2D histograms. The histogram equalization is performed using shift hue-preserving transformations, avoiding unrealistic colors. Our methods have linear time and space complexities with respect to the size of the image and do not need to apply conversions from a color space to another in order to perform the image enhancement. Such design complies with real-time applications requirements. An objective assessment comparing our methods and others is performed using a contrast measure and a color image quality measure, where the quality is established as a weighting of the naturalness and colorfulness indexes. We analyze 300 images from the dataset of the University of Berkeley. Experiments show that the value of the image contrast produced by our methods is in average 50% greater than the original image value, keeping the quality of the produced images close to the original one.

Evaluating the efficiency of a ventilation system in providing a healthy indoor environment to building occupants requires the knowledge of the airflow inside the room prior to the calculation of the pollutant dispersal from their sources. Computational Fluid Dynamics (CFD) modeling is probably the most suitable method to achieve this as it provides detailed information about the airflow pattern but is still time-consuming although processor speed has tremendously increased during the past years. Consequently, parametric studies aimed at characterizing the influence of parameters such as the location of the air inlets and outlets or furniture on the air velocity, temperature and concentration distributions within the building are seldom achieved. Zonal, Coarse-grid CFD and Fast Fluid Dynamics (FFD) are intermediate models between CFD and single air node models; they can predict the airflow pattern in a room or group of rooms with less computational efforts but with a lower accuracy than CFD models. The present study aims at improving the zonal prediction for the case of forced convection in indoor spaces. Results show that the proposed alterations of zonal modeling greatly improve the prediction and that this model requires less computational efforts and returns more accurate results than Coarse-grid CFD and FFD.

International audience

Predicting the indoor air relative humidity evolution is of great importance to evaluate people thermal comfort, perceived air quality and energy consumption. In building environments, porous materials of the envelope and furniture act on the indoor air humidity by reducing its variations. Solving the physical processes involved inside the porous materials requires the knowledge of the material hygrothermal properties that needs multiple and, for some of them, time-consuming experimental procedures. Recently, both the NORDTEST Project and Japanese Industrial Standard described a new Moisture Buffer Capacity index that accounts for surrounding air vapor concentration variation. The Moisture Buffer Value (MBV) indicates the amount of water vapor that is transported in or out of a material, during a certain period of time, when the vapor concentration of the surrounding air varies. The MBV evaluation requires only one experimental procedure and its value permits a direct comparison of the building materials moisture performance. However, two limitations can be distinguished: first, no relation between the MBV and the usual material hygrothermal properties has been clearly identified and second, no model has been proposed to actually use the MBV in building simulation. The present study aims to solve these two problems. First, the MBV fundamentals are introduced and discussed; followed by its relation with the usual material properties. Then, a lumped model for building simulation, whose parameters can be determined from the MBV experimental procedure, is described. To finish, examples of the use of this MBV-based lumped model for moisture prediction in buildings are presented.

International audience; Les vésicules extracellulaires, sécrétées spontanément ou en réponse à un stress par tous les types cellulaires, sont proposés comme des biothérapies alternatives aux thérapies cellulaires et aux nanomédicaments synthétiques. Leurs atouts logistiques (stockage, stabilité, disponibilité, tolérance), leur capacité à franchir les barrières biologiques, à délivrer leurs contenus (protéines, lipides et acides nucléiques) pour modifier leurs cellules cibles, ainsi que leurs activités immunomodulatrice et régénérative, suscitent un intérêt grandissant pour un très large spectre de maladies. Cette synthèse présente les défis qui restent à relever pour appliquer ces biothérapies en clinique. Quelques applications prometteuses dans les domaines du cancer et de la médecine régénérative seront proposées.

International audience; This article presents a strategy for channel assignment in Internet of Things (IoT) networks. The proposed strategy uses opportunistic spectrum access via cognitive radios. The originality of this work resides in the use of traffic history to guide the channel allocation in a distributed manner. The channel assignment algorithm mitigates the interference in links with higher traffic history. Our performance evaluation shows that using the historical network traffic as a decision criterion leads to better results when compared with the simple use of the network topology as a criterion.

The objective of this work is to evaluate the quality of the zonal airflow predictions compared to those provided by computational fluid dynamics (CFD) tools for an isothermal airflow induced in a room by a linear ceiling diffuser. This comparative analysis was conducted for a typical rectangular office designed for two people, considering two different arrangements of obstacles within the room volume. The ventilation was provided by a four-way ceiling diffuser type with large aspect ratio slots, the outlet integrated into it, operating in a three-way mode with slot Reynolds number of 2700. As a result, the airflow was transitional or weakly turbulent. The airflow patterns obtained with the zonal models were first compared qualitatively with the CFD computations. A quantitative comparison based on the mean velocities at the interface of the zonal grid was then carried out. The characteristic features of the zonal predictions are shown and the limitations of the zonal and CFD approaches are discussed.

In order to improve the modeling of air conditioners in building simulation tools, the characteristic curves for total cooling capacity, sensible cooling capacity and energy efficiency ratio of two room units were determined. They were obtained by means of standard capacity tests on climatic chambers in a set of environmental conditions described by external dry- and internal wet bulb temperatures. Afterward, the performance of these two units and that of four other units, with and without taking into to account the thermodynamic variations of the surrounding environments on it, were compared using a whole building simulation program for simulating a conditioned space. The comparative analysis showed that the air conditioner with the higher energy efficiency rating not always provides the lowest power consumption in real conditions of use.

International audience; Since the late 1990s, with the raising of eGovernment concepts and the increase use of ICT by public administration entities, the need for collaboration among these organizations is a reality with which systems, managers and other stakeholders must deal. In order to increase performance, to supply the online services, and the search for cost reductions the governments paradigms focus, now more than ever, on how to better manage information. As the need of these 'inter operations' is real, interoperability is a key factor for organizations facing with collaborative-cooperative environments. The modern architecture of information systems (ISs) is based on distributed networks with a grand challenge of representing and sharing knowledge managed by ISs and consequently, to remove semantics interoperability barriers. This paper presents a literature review and a research method that defines the mechanisms for the creation of guidelines, attributes and an assessment methodology in public administration domain. The presented research strategy identifies the basic phases and activities, purposing a structure of how to collect and compose the guidelines, and how to define an assessment method through the help of semantic technologies.

International audience