Une Sibylle égarée au XIVe siècle. La prophétie d’Abulnée dans l’Ovide moralisé

International audienceL’article étudie la digression sur les dix Sibylles médiévales qu’on trouve au livre XIV de l’Ovide moralisé. L’auteur anonyme du XIVe siècle interrompt en effet dans ce livre la trame des Métamorphoses, qu’il translate en moyen français, pour mener un long développement où il énumère ces dix sibylles avant de livrer l’intégralité d’une prophétie attribuée à la dixième d’entre elles, Abulnée. Après avoir rappelé la source de cette digression (un oracle latin du IVe siècle, intégralement translaté), l’article s’interroge sur les rai-sons qui ont conduit l’auteur à introduire cette digression dans son œuvre. Le traitement qui est fait des Sibylles dans le texte, et plus particulièrement d’Abulnée, repose sur la conception médiévale de l’histoire comme translatio imperii et studii : les plus grandes civilisations détentrices du pouvoir et du savoir sont appelées à se succéder les unes aux autres depuis l’Orient vers l’Occident. Les Sibylles, détentrices de la sagesse des anciens, servent de fait de point de jonction entre Orient et Occident, entre Antiquité et Moyen Âge, entre paganisme et christianisme. C’est pourquoi la prophétie d’Abulnée retrace toute l’histoire du monde, depuis l’origine de l’humanité jusqu’à la fin des temps et le Jugement Dernier, en passant par le temps de l’Avènement du Christ. L’auteur va même jusqu’à faire d’elle le premier maillon de la chaîne de transmission des prophètes judéo-chrétiens

Tous les poins et tous les passages. Le périple d’Énée comme itinéraire mnémonique de l’Ovide moralisé

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Impact of lymph node staging on survival in presumed early-stage ovarian cancer: a multicentric retrospective study

International audienceObjective:This study aimed to assess the impact of comprehensive staging on survival outcomes in this population.Methods:Patients who underwent surgery for epithelial ovarian cancer in one of the 14 Francogyn cancer centers between 2000 and 2020 were included in the study. The primary analysis evaluated the impact of lymphadenectomy on overall survival and recurrence-free survival. Lymph node count was analyzed as a continuous variable, and its association with survival, considered as a continuous outcome was assessed using linear regression (secondary analysis). Survival was compared using the log-rank test, and multivariate analysis was performed using a Cox model.Results:A total of 467 patients with presumed early-stage epithelial ovarian cancer were included, of which 198 underwent complete lymphadenectomy and 266 did not. No significant association was found between lymph node staging and survival in the primary analysis, possibly due to limited statistical power and a selection bias, as patients without lymphadenectomy had more favorable disease profiles (p=0.600 and p=0.700, respectively). Complete lymphadenectomy was associated with a significantly higher risk of complications (34.5% vs. 14%, p<0.001). In secondary analysis, the number of para-aortic lymph nodes harvested was identified as an independent predictor of both overall survival and recurrence-free survival (p=0.007 and p=0.002, respectively). Histological characteristics and adjuvant chemotherapy also showed a significant correlation with improved survival outcomes.Conclusion:Extensive para-aortic lymphadenectomy in early-stage epithelial ovarian cancer is associated with better overall and recurrence-free survival but comes with an increased risk of complications

Multiple sclerosis, fertility, pregnancy, and assisted reproductive technology: Current knowledge

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Seasonal and spatial shifts in the volatile chemical profile of Cymodocea nodosa across marine and lagoon ecosystems

International audienceBiogenic volatile organic compounds (BVOCs) are produced by marine organisms but remain largely understudied in seagrasses. To address this gap, this study investigates BVOC profiles from Cymodocea nodosa across seasons and between two ecosystem types: open-sea sites (Antibes, Saint Tropez, Porto Vecchio) and coastal lagoons (Thau, Urbino, Carteau). BVOCs were collected using headspace solid-phase microextraction (HS-SPME) and analyzed by gas chromatography-mass spectrometry (GC-MS). A total of 171 compounds were identified (145 in summer, 117 in spring, 115 in winter, and 103 in autumn).Volatilome composition varied significantly with season, explaining 26.1% of the explained variance, followed by site differences (14.1%), while ecosystem type had minor effects (&lt;5%). Functional diversity indices supported these patterns, indicating higher richness and abundance in summer, including 31 volatile compounds solely detected in summer. C. nodosa exhibited stress-related profiles, with geranyl acetone, β-cyclocitral, β-ionone, dimethylsulfide (DMS), and dihydroactinidiolide positively correlating with light, temperature, and salinity.Molecular networking showed the highest metabolite diversity and abundance in Urbino, including additional terpenoids and chlorinated and nitrogen-containing compounds. These findings highlight a haline-and heat-responsive phenotype and demonstrate strong seasonal and spatial variability in C. nodosa BVOC profiles,</div

Graph neural networks for water level modelling in floodplains: application to the Severn floodplain with HydroGCN

Séminaire invité dans le cadre d’un groupe de travail sur l’intelligence artificielle organisé au laboratoire IRPHÉ (Aix-Marseille Université) par Aurore Loisy

Amélioration de l'application spatio-temporelle Chrono-Rhône et transférabilité à d'autres territoires

International audienceThis project builds on two previous research projects that resulted in the development of an interactive web application (https://chrono-rhone.ens-lyon.fr/) showcasing key historical events in the socio-environmental trajectory of the Rhône River. This app integrates a timeline coupled with a map, and descriptive event sheets. Since 2020, its use for research, river management, and communication purposes has revealed needs for improvement and transferability to other territories, within the Rhône basin and across the Human-Environment Observatories (LabEx DRIIHM). The objective of the project is to develop a second version of the app that is more ergonomic, generic, and adaptable. Training and content enrichment workshops will be organized for future users. The tool fosters dialogue between disciplines and stakeholders, and has the potential to generate new research and training perspectives

Large-scale streamflow regionalization in ungauged West African catchments: How do classical and deep learning approaches compare?

International audienceIn West Africa, limited access to hydrometric data remains a major challenge for advancing surface water research and improving water management. Since the early 1980s, many gauging stations have been decommissioned, leaving gaps in reliable streamflow records across numerous catchments. Parameter regionalization of hydrological models is commonly employed to enable runoff prediction in ungauged catchments. This study represents an assessment of rainfall-runoff model regionalization across West Africa. We used an unprecedented dataset of 189 near-natural catchments to compare two contrasting approaches: (i) a benchmark conceptual modeling framework using the GR4J model, regionalized with three parameter-transfer techniques (spatial proximity, physiographic similarity, and Random Forest), and (ii) a data-driven framework based on Long Short-Term Memory (LSTM) neural networks. Using a leave-one-out resampling approach, regionalization approaches were evaluated using different performance metrics: (i) the Kling-Gupta Efficiency (KGE), calculated between simulated and observed streamflows, (ii) the relative bias (rBias) on several hydrological signatures computed with observed or simulated discharge and (iii) the difference between observed and simulated flood quantiles. Results show that the conceptual modeling approach with traditional parameter-transfer techniques consistently underperforms compared to the LSTM, failing to reproduce key hydrological signatures. In contrast, the LSTM model showed better generalization performance, accurately simulating streamflow with a median KGE of 0.67 and reliably capturing hydrological signatures and flood quantiles across West Africa’s diverse climates and landscapes with lower biases. These findings highlight the potential of data-driven approaches to enhance hydrological prediction in data-scarce regions, supporting more effective flood risk management and water resource planning

Table ronde : Le Common good constitutionalism au pouvoir ?

Table ronde organisée par la faculté de droit, le CDC et l'EDPL, Université Lyon 3 sous la dir; de Jérôme Couillerot

Quand l'écriture créative et artistique devient un outil pour comprendre et interpréter les textes

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