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Density, viscosity and excess properties of aqueous solution of 2-(2-Diethylaminoethoxy)ethanol (DEAE-EO)
No full textInternational audienceA complete study of thermophysical properties concerning the 2-(2diethylaminoethoxy)ethanol (DEAE-EO) + water binary system is realized. Density, speed of sound, dynamic and kinematic viscosities and refractive index measurements have been performed at atmospheric pressure, using a vibrating tube densitometer, a falling ball viscosimeter, and a refractometer, for pure DEAE-EO, pure water, and for aqueous solutions of DEAE-EO, from 278.15 to 323.15 K. The thermal expansion was calculated from density data. Excess Gibbs energy of flow and the corresponding excess entropy of flow were also calculated considering dynamic viscosity and density data. Excess molar properties (volume, isobaric expansion coefficient, Gibbs energy of flow and square of refractive index) were calculated and the Redlich-Kister equations were applied to correlate the data. Thermophysical properties of aqueous DEAE-EO (50 mol%) and Methyldiethanolamine (MDEA) (50 mol%) solutions were compared for their application in absorption of acid gases
Minerali: Asteroidi di tipo S
No full texthttps://www.astecenter.it/As we explore the possibilities of space exploration, the concept of manufacturing in space emerges as a potentially revolutionary development. In this article, we explore the potential sources of energy exploited in space and their developments.Alors que nous explorons les possibilités de l'exploration spatiale, le concept de production dans l'espace apparaît comme une avancée potentiellement révolutionnaire. Cet article examine les sources d'énergie potentielles exploitables dans l'espace et leurs développements.Man mano che ci avventuriamo nelle possibilità dell'esplorazione spaziale, emerge il concetto di produzione nello spazio come un potenziale elemento rivoluzionario. In questo articolo esploriamo le sorgenti potenzialmente sfruttabili nello spazio e i suoi sviluppi
Leveraging Service Supply Dynamics in Senselife: Building an Explainable Recommender System for Tailored Frailty Prevention
No full textInternational audienceThe growing elderly population in developed countries highlights the critical need for preventing frailty, which poses significant challenges to health systems due to increased risks of severe health issues. This paper introduces Senselife, a framework that provides explainable service recommendations specifically tailored for frailty prevention. It begins by outlining the medical context and challenges associated with aging, followed by an overview of existing recommender systems with similar objectives. We detail the integration of three key resources-ROR, RNA, and Data Laregion-within the Senselife framework to represent service supply. The paper explains how service supply is structured and the transformation of available data for use within our recommender engine. We introduce the concept of operational activities derived from the ROR and leverage the capabilities of LLMs to incorporate RNA data into Senselife. Additionally, we illustrate how these services are ultimately compiled into recommended service packages. Finally, the paper concludes by summarizing key findings and suggesting potential directions for future research
Automated Processing of Medication Error Reports with a GPT Transformer Model
No full textInternational audienceBecause of their potentially serious consequences, Medication errors (ME) represent a major challenge for health-care facilities. To manage these errors and minimize their seriousness, healthcare professionals follow a collaborative management process that relies on reporting and then analyzing the reports filled in by them via various reporting tools, both digital and paper-based. These tools can be customized requiring specific information to be entered in multiple forms with commonly the presence of textual descriptions to fill in a free-text field. Therefore, text analysis is crucial for thoroughly understanding and effectively analyzing medication errors. Given the large volume of reports to be quickly processed, it is essential to help healthcare professionals prioritize which ME to analyze. In this context, we propose, in this work, processing ME reports with natural language processing tasks using Transformer models such as GPT. In this study, we present the extraction of key information from the reports to help structure textual descriptions of ME with the GPT-4 transformer model. The results obtained show the potential of this model to extract relevant information from ME descriptions in French language without any deep fine-tuning
An Optimization Model for Patient Transportation Problem Within Stretchers Activity in Hospitals
No full text© © 2025 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”International audienceEfficient patient transport is crucial for the smooth operation of hospitals, as it directly impacts the timely delivery of medical care and the overall patient experience. The complexity of managing transport logistics, especially with limited resources, necessitates advanced optimization techniques. In this paper, we present an optimization model designed to enhance the scheduling of patient transportation missions and improve the organization of transport activities. Our primary objective is to minimize delays and reduce the number of unaccomplished missions, even when transporter availability is constrained. Using historical data from a hospital in France and the CPLEX solver, we compare our model's performance with existing models in the literature. The results demonstrate that our model significantly improves efficiency and reliability, ensuring timely patient transport and better resource utilization
Enhancing decision-making and production monitoring in assembly lines: visualizing performance evolution using KPI trajectories
No full text"© © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”International audienceThis study enhances decision-making and production monitoring in aeronautical assembly lines, focusing on visualizing performance evolution using a KPI tree and varied aggregation methods. By representing trajectory in a three-dimensional space, it facilitates effective risk and opportunities detection, pattern recognition, and trend analysis. The aim is to contribute valuable insights for mitigating disruptions and improving production rates in the aerospace industry, leveraging immersive technologies for comprehensive understanding and advancing decision support systems
Senselife: Service Recommendation and Frailty Prevention Through Knowledge Models
No full textInternational audienceThe aging global population presents unique challenges, particularly in managing frailty—a condition defined by declines in physical, cognitive, and social capacities. This paper introduces Senselife, a recommender system tailored for frailty management in elderly individuals. Senselife leverages hypergraph-based knowledge models to intelligently recommend personalized services aimed at mitigating frailty and enhancing life quality. Our methodology integrates diverse data types through Heterogeneous Information Networks (HINs), allowing for nuanced user-service interactions that significantly improve recommendation accuracy and relevance. This paper details the development of these models, emphasizing the transition from conventional data handling to advanced, knowledge-driven approaches that consider both user and service complexities. By incorporating these sophisticated models, Senselife aims to provide a scalable solution for frailty prevention, offering a significant contribution to personalized elderly care
Recent Advances in the Application of Engineered Biochar for Wastewater Treatment
No full textInternational audienceWastewater management has emerged as a critical environmental challenge, with the release of unprocessed or incompletely treated wastewater leading to severe ecological and public health consequences. Recently, there has been an increasing demand for biochar, a porous and hierarchical carbonaceous material, for its promising applications as an efficient agent in wastewater treatment. Nevertheless, the effectiveness of pristine and unmodified biochar alone is considered inadequate to address the severity of the present water pollution challenges. As a result, new engineering approaches have been designed and executed to widen the range of applications for biochar. This chapter provides a concise overview of preparation methods, factors influencing biochar properties and adsorption mechanisms of biochar, with a major emphasis on highlighting various methods for producing engineered biochar and their subsequent use in treating wastewater
Comportement dynamique des composites à fibres naturelles et résines thermoplastiques : étude de la sensibilité à la vitesse de déformation
No full textThese works aim to explore the behavior of thermoplastic matrix composites reinforced with natural fibers by examining their strain rate response under tensile loading, focusing particularly on the variation of the longitudinal elastic modulus for 0° composites and the shear modulus for ±45° laminates. Using bamboo, flax, and basalt fibers as unidirectional reinforcements and semi-crystalline polyamide-11 as well as amorphous ELIUM resin as matrices, various experimental campaigns were conducted to characterize the materials. Static and dynamic tensile tests were performed using electromechanical equipment, DMA, and drop towers. Numerous explicit numerical simulations were employed to analyze the experimental data. The results reveal that 0° plies exhibit limited sensitivity to strain rates below 100 s⁻¹, with bamboo and flax composites showing little variation in Young's modulus, while basalt-reinforced composites display a slight increase. However, composites with ±45° stacking exhibit increased sensitivity, primarily influenced by the resin. This comprehensive investigation provides insights into the behavior of these natural fiber-reinforced thermoplastic polymer composites under different loading rates, guiding their optimization and application.Ces travaux visent à explorer le comportement des composites à matrice thermoplastique renforcée de fibres naturelles en examinant leur réponse à la vitesse de déformation lors de sollicitations en traction, en se concentrant particulièrement sur la variation du module d'élasticité longitudinal pour les composites à 0° et du module d'élasticité en cisaillement pour les stratifiés à ±45°. En utilisant des fibres de bambou, de lin et de basalte comme renforts unidirectionnels et le polyamide-11 semi-cristallin ainsi que la résine amorphe ELIUM comme matrices, diverses campagnes expérimentales ont été menées pour caractériser les matériaux. Des tests de traction statiques et dynamiques sont effectués à l'aide d'équipements électromécaniques, DMA et tours de chute. De nombreuses simulations numériques explicites sont utilisées afin d'analyser les données expérimentales. Les résultats révèlent que les composites avec des plis à 0° montrent une sensibilité limitée aux vitesses de déformation inférieurs à 100 s-1, les composites en bambou et en lin présentant peu de variations du module de Young, tandis que les composites renforcés de basalte montrent une légère augmentation. Cependant, les composites avec un empilement à ±45° affichent une sensibilité accrue, principalement influencée par la résine. Cette investigation exhaustive fournit des informations sur le comportement de ces composites à fibres naturelles et polymères thermoplastiques sous différentes vitesses de chargement, guidant leur optimisation et application
Towards a Risk-Focused Sales and Operations Planning Process
No full textInternational audienceSales and Operations Planning (S&OP) is a vital business process that establishes a connection between the strategic plan of a company and its daily operational plans, facilitating the alignment of demand and supply for its products. However, in the face of dynamic and volatile business environments characterized by constant changes, achieving the desired objectives of S&OP becomes increasingly challenging.The explicit inclusion of a comprehensive understanding of uncertainties and decision options within the S&OP process has not been adequately addressed. In this context, the traditional S&OP process often falls short in addressing the unpredictable factors like demand fluctuations, supply disruptions, market changes, and other uncertainties.This paper aims to enhance the S&OP process, encompassing sub-processes such as demand planning, supply planning, and financial integration, with a dedicated focus on effective uncertainty management. The Risk-Focused S&OP Process proposed in this paper aims to equip organizations with a comprehensive set of strategies that will enable them to navigate the complicated supply chain road successfully. This approach seeks to address the critical need for strategies that can adapt to evolving uncertainties. The Risk-Focused S&OP Process enables organizations to address uncertainties and capitalize on opportunities, thereby promoting long-term sustainability and competitiveness.One of the limitations of this study is that the Risk-Focused S&OP Process, although introduced in this article, has not undergone validation. Consequently, future research should implement and validate this study to ensure its broader applicability