Portail des publications scientifiques IMT Mines Alès
Not a member yet
5198 research outputs found
Sort by
Capacité Vs Efficience : Quel Choix pour l’Utilisation du Bras Parétique dans les Activités de la Vie Quotidienne
No full textInternational audienc
Peeling the dynamical layers of the interacting self: impact of aversive electrodermal stimulations on the affective, physiological and motor components of social interactions
No full textInternational audienceThe self is a multidimensional construct interacting with the external (and social) world. Emotional experiences color the way we interact with the world and pain is one of the most archaic emotions that trigger stereotypical physiological and behavioral responses. Accumulative evidence shows that behavioural synchrony influences pain threshold by increasing social connectedness, yet those studies have neglected to consider the emotional component of pain and its consequences on physiological and behavioural rhythms. This study investigated the impact of aversive electrodermal stimulations on the phenomenological, physiological and motor components of social interactions.10 mixed-gender quartets (N = 40) performed oscillatory movement with their arm under three conditions: (i) SOLO (i.e., without visual coupling), (ii) TOGETHER (i.e., with visual coupling) and (iii) SYNCHRO (i.e., with the instruction to synchronize). Electrocardiograms and motion tracking were recorded while aversive electrodermal stimulations were delivered to half of the participants. Between experimental conditions, participants completed self-reports of emotional states, social connectedness, unpleasant experiences, and the fear of experiencing the stimulation.The administration of the aversive stimulation induced localized unpleasant sensations, associated with a decrease of emotional valence and an increase of the fear of stimulation. The aversive stimulation also led to an increase in participants’ heart rates when there was a threat of stimulations or when stimulations were effectively delivered. However, the stimulation did not influence social connectedness and behavioural synchrony, but individual movement’s variability. Altogether, these results stress the distinct sensitivity of the rhythmic components of the self to emotional and social context
A Muscle Physiology-Based Framework for Quantifying Training Load in Resistance Exercises
No full textInternational audienceBackground: Objective training load (TL) indexes used in resistance training lack physiological significance. This study was aimed to provide a muscle physiology-based approach for quantifying TL in resistance exercises (REs). Methods: Following individual torque–velocity profiling, fifteen participants (11 healthy males, stature: 178.36 ± 3.95 cm, and body mass (BM): 77.48 ± 7.74 kg; 4 healthy females, stature: 169.25 ± 5.03 cm, and body mass: 60.62 ± 3.91 kg) performed isokinetic leg extension exercise sessions at low, moderate, and high intensities (LI, MI, and HI, respectively). Systemic and local physiological responses were measured, and sessions were volume-equated according to the “volume-load” (VL) method. Results: Significant differences were found between sessions in terms of mechanical work (p<0.05 and p<0.001, for LI-MI and MI-HI, respectively), averaged normalised torque (p<0.001), mechanical impulse (p<0.001), and rate of force development (RFD, p<0.001 for LI-MI). RFD was mainly impacted by the accumulation of repetitions. Muscle function impairments mainly occurred at low intensities–long series, and high intensities, supported by greater RFD rate decay and changes in electromyographic activity. Therefore, accounting for muscle fatigue kinetics within objective TL indexes and using dimension reduction methods better described physiological responses to RE. Conclusions: A generic equation of muscle fatigue rise could add value to TL quantification in RE. Considering other training-related information and TL indexes stands essential, applicable to field situations and supports the multidimensional facet of physiological responses to RE
Stokes-darcy fluid flow simulations within 3D interlock fabrics with capillary effects – experimental input influence and comparison with experimental output
No full textInternational audienceResin Transfer Molding (RTM) is a widely used process in composite material manufacturing, involving the compaction of a fibrous 3D interlock preform to achieve targeted Fiber Volume Fraction (FVF), followed by impregnation with liquid resin. Dual-scale flows within and between homogeneous equivalent porous yarns must be modeled for predicting impregnation schemas and defects. At the mesoscopic scale, fabric unit cells are characterized by yarn morphology and intra-yarn FVF fields. Those parameters shall be linked to a permeability tensor field for application of the Darcy law at a larger scale. The dual-scale nature significantly affects saturated and unsaturated fluid flows, especially due to capillary phenomena within yarns, which are modeled as an addition to Darcy’s law via a capillary pressure. The effect on the effective value of the calculated permeability has yet to be assessed. The aim of the numerical approach is to develop a robust numerical framework for simulating fibrous media impregnation at the mesoscopic scale [1-3] and then to compare the results with experimental characterizations. Fluid flow is modeled by the Darcy equation within porous yarns and by the Stokes equation between yarns, employing a monolithic approach with a mixed velocity-pressure formulation stabilized by a Variable Multi-Scale (VMS) method. Accurate description of resin flow within porous yarns requires locally oriented intra-yarn permeability tensor fields and capillary stress tensor (the “orthotropic capillary pressure” [4]) at the resin-air interface. Additionally, pressure enrichment is introduced at the fluid front, represented by a level set function, to capture pressure discontinuity in Darcy domains. Saturated and unsaturated Stokes-Darcy fluid flow simulations are conducted to determine fabric permeability as a function of global FVF, corresponding to different compaction levels, evaluating hence the influence of capillary phenomena on the impregnation scenario (Figure 1).Experimental estimations of permeabilities have been performed at different scales and regimes [5]. The intra-yarn permeability and capillary stresses have been estimated to be fed to simulations. At the scale of the process, permeabilities with steady and transient flows have been estimated with a set-up complying with the standard ISO 4410:2023[6] (Figure 2)
Phosphorus-containing polycarbosilazanes: Synthesis via dehydrocoupling catalysis and flame-retardant properties
No full textInternational audienceThe barium complex [Ba{N(SiMe3)2}2]2 has been used to catalyse the dehydropolymerisation of the phosphine-functionalised hydrosilane 4-Ph2P-C6H4SiH3 (A) with the α,ω-diamine 1,4-(CH2NHMe)2-C6H4 (C), for the production of -[Si(4-C6H4PPh2)H-N(Me)CH2-C6H4-CH2N(Me)]n- polycarbosilazanes that contain dangling phosphino groups along the polymer backbone. The comonomers A and C, specifically prepared for this purpose and comprehensively characterised, lend themselves well to barium-promoted dehydrocoupling catalysis. They allow for the formation of linear, amine-capped polymers with molecular weights in the range 4000-8000 g mol-1, as estimated by DOSY and 1H end-group NMR analyses. The terpolymerisation of C with various mixtures of A and PhSiH2R (R = H or Ph) led to the formation of terpolymers featuring various contents of phosphine-functionalised silazane groups, with an overall composition that reflects well the initial feed ratio of the comonomers. Thermal decomposition and flammability were studied at the microscale on a series of polycarbosilazanes to assess the effect of molecular groups on thermal stability and heat release. The SiCN backbone containing the silazane group significantly contributes to the \"charring\" of the polymer. By contrast, PPh2, as other groups bearing a phosphorus atom in a low oxidation state, is not an effective char promoter
Une approche ingénierie système basée-modèle pour la construction de jumeaux numériques de procédés de vitrification pour le conditionnement de déchets nucléaires
No full textInternational audienceIl s’agit de la solution de confinement des déchets nucléaires développée à l’échelle industrielle en France, notamment pour ses propriétés à long terme. Le principe est de confiner les PF dans une matrice de verre avant stockage au moyen d’un procédé de vitrification. Cependant, cette vitrification pose de nombreux problèmes liés à la complexité même du procédé, des différentes implémentations de ce procédé qui sont alors à développer, tester et valider avant de les industrialiser. A ces fins, mais aussi pour former des opérateurs ou encore piloter en temps réel ces implémentations, le jumeau numérique est aujourd’hui une solution pertinente. [3] définit un jumeau numérique comme « une représentation virtuelle intégrée, basée sur des données, d'entités et de processus du monde réel, avec une interaction synchronisée à une fréquence et une fidélité spécifiées ». Le travail proposé dans ce poster vise à proposer un guide de conception de jumeaux numériques d’un tel procédé et de ses différentes implémentations. Entre autres attentes, ce jumeau numérique devra répondre aux cas d’usages identifiés pour répondre aux besoins du CEA et s’appuyer sur deux types de représentation, i.e. deux types de modélisation : au niveau système et au niveau des disciplines impliquées, devant à terme se fédérer pour offrir une modélisation la plus réaliste possible. Les éléments de cette approche d’ingénierie se basent sur l’analyse des standards de définitions des jumeaux numériques [3] [4] et [5] et sur l’exploitation de l’approche ingénierie système basée modèles telle que définie par [6] et [7]. Ce guide prend aujourd’hui la forme d’un cadre de conception outillé, et d’une démarche opératoire en cours de formalisation. [1] https://www.cea.fr/comprendre/Pages/energies/nucleaire/essentiel-sur-cycle-du-combustible-nucleaire.aspx [2] T. Advocat, J-L. Dussossoy, V. Petitjean, Vitrification des déchets radioactifs, Techniques de l’ingénieurs, 2008 [3] https://www.digitaltwinconsortium.org/initiatives/the-definition-of-a-digital-twin/ [4] ISO 23247:2021 - Automation systems and integration — Digital twin framework for manufacturing [5] ISO/IEC 30173:2023 - Digital twin – Concepts and terminology [6] ISO/IEC/IEEE 15288:2023 - Systems and software engineering System life cycle processes [7] ISO/IEC/IEEE 24641:2023 - Method and tools for model-based system and software engineerin
Modelling of pheromone release from solid matrix dispenser for integrated pest management
No full textInternational audienceSex pheromones are introduced in the cultivated areas to create mating disruption and thus to protect crops from pests. This article deals with the release characteristics of a model pheromone (dodecyl acetate) encapsulated in a solid matrix developed as a passive dispenser. Released kinetics were obtained both in the field by extracting and quantifying the remaining pheromone in the dispenser over time and in laboratory by emission chamber tests under controlled conditions. Results showed that the release profiles follow pseudo-zero-order kinetics with a quasi-constant release rate of 1.53 mg day-1 under field conditions for the first sixty days. Emission data showed that two key parameters, i.e., the matrix/air partition coefficient (Kma) and the convective transfer coefficient in the gas phase (hm) govern the release rate of the dispenser. Estimates of Kma varied from 1×106 to 4.55×106 and hm from 3.2×10-3 to 5×10-3 m s-1 depending on the air velocity and temperature conditions. Temperature dependence of Kma was most significant and was addressed by estimating the enthalpy of the pheromone partitioning between the matrix dispenser and air (102 kJ mol-1). The results led to the development of a model based on Kma and hm as the main parameters describing pheromone release from the matrix dispenser. A good agreement was found between the measurements obtained in field and model predictions. This model could be an effective tool for adjusting the release rate of pheromone dispensers under practise conditions
Emotional mimicry and smiling behaviors in schizophrenia: An ecological approach
No full textInternational audienceIndividuals with schizophrenia often experience social skill deficits, leading to reduced social interaction quality. Emotional mimicry, the automatic imitation of a counterpart’s expression, plays a crucial role in social interactions. This study introduces a novel methodology for assessing positive emotional mimicry during a naturalistic conversation. We recruited interacting partners ( n = 20), each engaging in two interactions: one with an individual diagnosed with schizophrenia ( n = 20) and one with a matched healthy control ( n = 20). Participants were video recorded while taking turns sharing happy personal memories during six minutes. Using OpenFace, we detected participants’ emotional expressions and computed mimicry scores based on their temporal alignment. Consistent with our hypotheses, individuals with schizophrenia exhibited reduced smiling and positive emotion mimicry. Furthermore, interacting partners reported lower willingness to continue interacting with individuals with schizophrenia compared to healthy controls. This study stands out for its innovative methodology, assessing a key social skill in an ecological setting. Our findings highlight the potential of emotional mimicry training as an important intervention to improve social interaction in schizophrenia
Use of Modelling as an Enabler for Cross-Topic Knowledge Management and Ontologies to Support Return of Experience and Replicability of Large Nuclear Projects
No full textInternational audienceNuclear projects often produce and consume a large amount of knowledge. Capitalization on this knowledge constitutes a significant way to increase efficiency on subsequent projects for any stakeholder. In this study, modelling is used as a main approach to support this capitalization. It constitutes, through graphical layout, a more reliable and robust way to transfer information. Moreover, the use of an interconnected set of models enables organizations to break the silos between the disciplines. The approach proposed is based on the declination of existing "on-the-shelf" elements to benefit from previous implementations. The presented example illustrates how, on a nuclear project, engineering processes have been modelled from knowledge of previous projects. These implementations are all interconnected to constitute a self-supporting set of models as a body of knowledge. This approach has enabled significant time and costs savings during project preparatory and initial phases
Neural Networks for Seasonal Groundwater Level Forecasting
No full textInternational audienceReliable and sustainable water resource management largely depends on the accurate prediction of groundwater levels, a challenge that has become increasingly critical due to climate change, and the growing exploitation of aquifers due to human activities . Reliable forecasts are essential for effective decision - making in water resource management, particularly in regions facing seasonal fluctuations or long - term declines in groundwater availability. The hidden nature of underground reservoirs makes it impossible to gain detailed knowledge of structural variability and water paths. Apart from large homogeneous basins, the physical properties of aquifers are thus poorly understood, making them difficult to model using physical or physically based models. Also, difficulties encountered in delimiting their feeding basin make it a challenge to fully understand them and accurately simulate and forecast their evolution. Thus, the lack of physical knowledge of underground hydrosystems encourages the use of systemic modeling methods, based on statistical approaches that do not require such knowledge. These include models based on artificial neural networks, particularly multilayer perceptrons (MLPs), that have proven to be a promising approach for improving the accuracy of hydrogeological forecasts. These models offer the advantage of capturing complex, nonlinear relationships between meteorological variables and groundwater level fluctuations, often outperforming traditional statistical methods. Although IA methods need a sufficient volume of data, they do not require extensive information about the hydrodynamics of the aquifer, making them easier to implement in poorly known contexts. In this study, we develop a seasonal groundwater level forecasting model for 30, 60, and 90 days ahead, for a piezometer located in the basement of the Sélune River watershed, in the Manche region of France. To achieve this, we use a multilayer perceptron (MLP) neural network while integrating regularization techniques to prevent overfitting and enhance generalization capabilities. The model is trained on a historical dataset covering a 15 - year period with a decadal time step, incorporating several input variables, including temperature, actual evapotranspiration, precipitation, and the discharge of the nearby river. Cross validation and a separated test set are used to ensure the robustness of the model. Furthermore, the impact of future meteorological data on forecast quality is analyzed to assess its contribution to improving model performance. The results show a variation in forecasting accuracy depending on the lead time, with a general tendency toward reduced accuracy over longer periods. However, the integration of available future meteorological data significantly enhances model performance, highlighting its importance in hydro geo logical forecasting and resource planning, opening new paths of inquiry for future developments. Estimating future trends in meteorological variables, even if uncertain, therefore appears to be a significant way of improving seasonal water level forecasts