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Diversification and biogeographic history of African dormice (genus Graphiurus) revealed by ultraconserved elements and mitochondrial data
No full textInternational audienceThe sub-Saharan Africa endemic dormouse genus Graphiurus is a morphologically diverse group of rodents that has lacked a genus-wide genetic framework, hindering inference of their evolution and biogeography. Here, we assembled the first comprehensive, range-wide genomic dataset for Graphiurus, including ultraconserved elements and the cytochrome b gene. We used phylogenetic reconstruction, divergence-time estimation, and ancestral area reconstruction to clarify biogeographic histories and evaluate how historical range dynamics may have influenced lineage diversification. Graphiurus is the earliest-diverging lineage within Gliridae sister to all other extant genera. Within Graphiurus, we recovered 24 molecular operational taxonomic units (MOTUs) forming two reciprocally monophyletic, deeply divergent clades: a West African lineage comprising three MOTUs and a pan-sub-Saharan Africa lineage comprising 21 MOTUs. Genetic distances between these clades are equal to or greater than those used to distinguish genera. Diversification within Graphiurus started in the middle Miocene, peaking in a rapid radiation during the Plio-Pleistocene. These diversification events coincided with increased climatic instability that fragmented forests into isolated refugia. Ancestral-area reconstructions suggest a Graphiurus origin in the Upper Guinean rainforest, followed by jump dispersal across the Afrotropics, with most subsequent divergences occurring in East Africa. As the first comprehensive phylogenetic analysis of Graphiurus, our study underscores the urgent need for an integrated taxonomic revision of the genus that couples genomic data with detailed morphology and critical re-examination of type material to resolve species limits and formally describe the recovered MOTUs. Many MOTUs appear range restricted, underscoring vulnerability to ongoing habitat loss within montane refugia
IPSL-Perm-LandN: improving the IPSL Earth System Model to represent permafrost carbon-nitrogen interactions
No full textInternational audienceAbstract. Permafrost soils have the potential to release large amounts of soil carbon to the atmosphere under climate change. However, in the Sixth Coupled Model Intercomparison Project (CMIP6), only two Earth System Models (ESM) represented permafrost carbon, both sharing the same land surface model. This makes future permafrost carbon dynamics highly uncertain and underscores the urgent need to include permafrost carbon in ESMs to enable more reliable future projections of climate change and remaining carbon budget estimates. Here, we present IPSL-Perm-LandN, an improved version of the Institut Pierre-Simon Laplace (IPSL) ESM (used for CMIP6) aiming at better representing high-latitude land ecosystems. The main developments are the inclusion of an explicit nitrogen cycle and of key permafrost physical and biogeochemical processes. The latent heat associated with soil water freeze/thaw is taken into account in the energy budget, as well as soil thermal insulation by soil organic matter and a surface organic layer (e.g. litter or moss). Soil organic carbon and nitrogen are vertically resolved with depth-dependent decomposition dynamics, a key feature for representing the effect of gradual permafrost thaw on soil biogeochemistry. Cryoturbation is represented as a diffusion process that buries organic matter in the deeper soil layers. Compared to the previous version of the model used for CMIP6, we show that the extent of the permafrost region has improved significantly and that the simulated active layer thickness in the Arctic is in better agreement with observations. Permafrost soil carbon stocks have increased 20-fold to reach 1006 PgC in the top 3 m of soil, which is consistent with observation-based estimates. We simulate that the permafrost region has been a net carbon sink over the past 150 years (+0.32 ± 0.04 PgC yr−1 on average between 2005 and 2014), primarily due to carbon uptake from boreal forests. This is comparable with recent pan-Arctic carbon balance estimates, when accounting for unrepresented processes in our model (fire and riverine carbon losses). Overall, the inclusion of permafrost processes has improved the response of the model to anthropogenic perturbations in high latitudes over the past century, marking a step forward in the representation of Arctic ecosystems
Terahertz Fourier Ptychographic Imaging
No full textInternational audienceHigh-resolution imaging in the terahertz (THz) spectral range remains fundamentally constrained by the limited numerical apertures of currently existing state-of-the-art imagers, which restricts its applicability across many fields, such as imaging in complex media or nondestructive testing. To address this challenge, we introduce a proof-of-concept implementation of THz Fourier Ptychographic imaging to enhance spatial resolution without requiring extensive hardware modifications. Our method employs a motorized kinematic mirror to generate a sequence of controlled, multi-angle plane-wave illuminations, with each resulting oblique-illumination intensity image encoding a limited portion of the spatial-frequency content of the target imaging sample. These measurements are combined in the Fourier domain using an aberration-corrected iterative phase-retrieval algorithm integrated with an efficient illumination calibration scheme, which enables the reconstruction of resolution-enhanced amplitude and phase images through the synthetic expansion of the effective numerical aperture. Our work establishes a robust framework for high-resolution THz imaging and paves the way for a wide array of applications in materials characterization, spectroscopy, and non-destructive evaluation
L’émission d’une facture d’honoraires par une SELARL d’avocats est un acte de gestion (Cass. com. 26 nov. 2025)
No full textInternational audienceLa Cour de cassation décide, à propos de l’émission d’une facture d’honoraires par l’associé-gérant d’une SELARL d’avocats, que l’émission d’une facture par une société constitue un acte de gestion susceptible comme tel d’engager la responsabilité de son dirigeant. Tout en expliquant son fondement, le commentaire discute la solution retenue en montrant qu'elle n'est pas aussi évidente qu'il n'y paraît. Puis il analyse la portée de cette solution au-delà des SELARL d'avocats
Integrated optimization and machine learning through hyperparameter selection: an application to predictive maintenance of wind turbines
No full textInternational audienceNumerous real-life problems involve two complex challenges: prediction, because of unknown or uncertain parameters or variables, and decision, because of the need to make a good one or the best one. These two challenges are not solved with the same tools: the firstone requires learning and the second one constrained optimization. The literature proposes various ways to link decision and prediction problems. The most common and obvious way is to perform the prediction first and then to optimize the decision based on this prediction. This sequential paradigm is called predict-then-optimize (PtO). Even though this paradigm is widespread, it often leads to sub-optimal decisions becausethe learning model used for the prediction aims at minimizing a loss function on the object to predict and not on the decision that will be taken based on this prediction (2).More recently, authors proposed a new paradigm, called Decision-Focused Learning (DFL), including the decision problem into the prediction problem by changing the loss function of the learning task to minimize the loss on the final decision. It supposes several conditions to be satisfied, because of the need to be able to compute the derivative, or a substitute, of the loss function. This is not immediate when considering a constrained optimization problem, in particular with integer variables (3).The model we propose optimizes the hyperparameter search of the learning model not with a traditional score, such as mean squared error or f1-score, but with a customized score being the objective function of the constrained optimization model of the decision problem. The decision is then integrated into the learning phase. As the scoring function of the hyperparameter search is not subject to the assumptions of derivability, which is the case for the loss function used in DFL, it requires much less effort to integrate the decision and the prediction phases.Predictive maintenance (PdM) is a case involving a decision problem, using constrained optimization, and a prediction problem, using learning. This paper examines how optimization and machine learning can be combined to improve PdM in wind farms. PdM is a maintenance strategy that aims at performing maintenance tasks little before a failure is likely to occur. Being able to schedule a task a little before a failure occurs assumes having information on the future operational state of the equipment. This information can be under the form of remaining useful life, ie. the time remaining before a failure, or of a binary information on the likeliness of a failure occurring the next period of time (4). Having these kinds of forecasts is a prediction problem. Wind turbines are equipped with multiple sensors monitoring and storing various quantities, such as temperatures, angles, rotation speeds, etc. The availability of data makes it suitable to use learning for failures prediction (1).Operation and Maintenance decision-makers wish to elaborate a good maintenance schedule, or even the best one, in the sense that it should minimize the maintenance costs and both the planned and unplanned downtime. The goal is to achieve a compromise between curative maintenance, that systematically causes unplanned downtime and high maintenance costs but guarantees a maximal use of the components, and preventive maintenance, that avoids some of the failures by planning operation at regular time interval with lower maintenance costs but still cause planned downtime, may lead to over-maintaining and does not erase the risk of failures. Predictive tasks should then replace preventive and curativeones.Maintenance planning is thus a decision problem. The maintenance planning is constrained by field rules such as potentiality, security, etc. (5). The tool used to find the best planning while satisfying the filed rules is constrained optimization.In the case of PdM for wind turbines, the constrained optimization program seeks to minimize a cost function composed of maintenance costs and of downtime costs, both planned and unplanned. The decision variables are the beginning of each maintenance task and is a Mixed Integer Linear Program (MILP). The tasks to schedule can be curative, preventive or curative tasks. A predictive task can replace a preventive or curative task if it is scheduled closely enough before this task’s due date. The data we work with to predict the failures is labeled with historical failures, thus thelearning task is not anomaly detection but supervised machine learning. Due to the fact that the failures do not happen as often as normal functioning, the dataset is highly skewed. We use a gradient boosting classification model for the prediction, as it is robust to skewed datasets. This still leads to an excessive amount of false positive, even using the f1-score as scoring function to find the best hyper-parameters, which combines precision and recall to ensure the quality of the prediction of a classifier.This paper proposes a model integrating the failure predictions, using a classification gradient boosting learning algorithm, and the planning optimization, using a scheduling MILP. The integration is done through the hyperparameters selection of the learning model as thescoring function of the grid search is a loss function based on the objective function of the scheduling MILP. Experimentations were carried out on industrial data shared by a partner. We compared the integrated predictive approach to a maintenance strategy purely preventive and curative and to a second maintenance strategy including predictive maintenance according to a PtO model, ie. without the loop on the learning-decision phases. Results show that the integrated model reduces the amount of false negative predictions, as expected. This has the effect of scheduling a number of predictive tasks that is closer to what is in fact needed, replacing preventive tasks and not performing too many predictive tasks. Results are convincing: the integrated predictive approach allows to gain up to 30% compared to the purely preventive and curative strategy and from 10% to 20% compared to the PtO predictive strategy, in maintenance costs
Beyond phonemic awareness: The alphabetic principle predicts reading acquisition in a nationwide longitudinal study
No full textInternational audiencePhoneme awareness (PA) is undoubtably the most important and well-studied predictor of reading development. Yet, 20 years ago, Castles and Coltheart made the provocative claim that there was no convincing evidence for the causal role of PA in learning-to-read because previous studies typically failed to control for pre-reading skills. In the present study, we leveraged a unique opportunity to analyze data from a large-scale longitudinal investigation of reading development conducted nation-wide among all first graders in France (i.e., N = 810,328 children). We estimated not only the direct effect of PA on reading fluency measured one year later, but also its interaction effects with letter-knowledge (LK), knowledge of the alphabetic principle (KAP), and oral comprehension (OC). Our results show that the direct effects of PA on later reading fluency are moderated by OC, LK and KAP. Specifically, PA contributes to later reading outcomes only among children with strong KAP, and good LK and OC. We highlight the central role of KAP as a key predictor that has often been acknowledged in theory but rarely measured in empirical research. These findings indicate that phoneme awareness supports reading development only in the context of sufficient alphabetic knowledge, challenging strong causal accounts of PA in early reading acquisition
Why should I comply with taxes if others don’t? Social information and behavioral convergence: An experimental study
No full textInternational audienceThis experimental study investigates the impact of social information about others’ tax behavior on individuals’subsequent tax decisions. Two types of social information are introduced: (i) the average income reportedwithin the subject’s entire group, and (ii) the average income reported within a reference subgroup made ofeither peers or non-peers and chosen by the subject. Our results show that social information significantlyaffects subsequent tax decisions, with a change in reported income ranging from 15% to 30% of total incomeon average. Moreover, the influence of whole-group information on tax behavior appears to be stronger thanthat of chosen-group information. Quite strikingly, a majority of subjects show more interest in the tax behaviorof non-peers than in that of peers. Finally, our data provide strong evidence of behavioral convergence towardsthe average tax behavior of others
Composer sans écriture : textualisation orale et forme musicale dans une performance du chanteur dahoméen Ajaxùi: textualisation orale et forme musicale dans une performance du chanteur dahoméen Ajaxùi
No full textThis article offers a formal analysis of a musical performance by the Dahomean singer Yeɖenù Ajaxùi, situated within the framework of orality and performance studies. Drawing on two complementary ethnographic descriptions, the study examines how a sung text is composed, structured, and stabilized in performance, without recourse to writing. The analysis brings to light a logic of oral textualization grounded in specific formal procedures: performative signals functioning as oral punctuation, the use of proverbs as memorizable and structuring units, dialogic polyphony as a principle of enunciation, and trance sequences understood as controlled compositional suspensions. The article proposes an original formal model-the spiral form with performative regulation-which conceptualizes musical composition as a dynamic process of text-making in performance. This contribution invites a reconsideration of musical form beyond the paradigm of writing, recognizing oral performance as a fully developed mode of formal organization and aesthetic thought.</div
Afa tarik - Histoire orale de l'Éthiopie chrétienne
No full textCe dépôt est constitué d'enregistrements réalisés en Ethiopie et de leur traduction en français.This collection brings together interviews conducted in Ethiopia, on the Christian highlands in the regions of Goǧǧam, Gondar, Begamder, and Tigrāy, by the historian Anaïs Wion (CNRS Research Director), between the late 1990s and 2018. Although her work focuses on the medieval and early modern periods, she has carried out extensive field research in Ethiopia to meet with historians, intellectuals, and leaders of religious institutions. These institutions still hold the vast majority of manuscripts and archives to this day. Anaïs Wion was thus able to consult local historical documents on-site, reading and interpreting them with their custodians. The discussions gathered here are the result of these encounters.The collection will include sub-collections organized according to the research sites. As of January 2026, it contains only one sub-collection, recorded in Aksum.Cette collection rassemble les entretiens réalisés en Éthiopie, sur les hauts plateaux chrétiens dans les régions du Goǧǧam, de Gondar, du Begamder et du Tigrāy, par l'historienne Anaïs Wion (directrice de recherche au CNRS), entre la fin des années 1990 et 2018. Bien que travaillant sur les périodes médiévales et modernes, elle a réalisé de nombreux terrains de recherche en Éthiopie afin de rencontrer les historiens, les intellectuels et les responsables des institutions religieuses. Ces dernières conservent jusqu’à aujourd’hui l’immense majorité des manuscrits et des archives. Anaïs Wion a ainsi pu consulter des documents d’histoire locale sur place, en les lisant et les interprétant avec leurs détenteurs. Ce sont ces discussions qui sont rassemblées ici. La collection comportera des sous-collections organisées en fonction des terrains de recherche. Elle ne comporte pour l’instant (janvier 2026) qu’une seule sous-collection, celle enregistrée à Aksum
Dancing to the wrong tune: How rational myopia, belief heterogeneity, and adjustment costs shape financial bubbles
No full textInternational audienceWe introduce the Anticipations-Based Production Equilibrium (ABPE) as a minimal extension of the Arrow–Radner Production Equilibrium (ARPE). Whereas ARPE requires optimality and rational expectations, ABPE relies only on local optimization and locally coherent expectations. This mild departure preserves internal consistency, coincides with ARPE in discrete time, while in continuous time allows for speculative bubbles, defined intrinsically as price trajectories that rise explosively before collapsing in finite time. To illustrate the concept, we develop a continuous-time production economy with heterogeneous beliefs and convex adjustment costs, where bubbles emerge endogenously from the interplay of nonlinear price dynamics, and belief-driven momentum. We characterize the precise conditions under which bubbles emerge, and distinguish between financial bubbles, which affect only asset prices, and real bubbles, which also impact production and growth. The ABPE framework is general and accommodates a variety of belief formation mechanisms, which we illustrate with anticipations constructed through backward inference and regret minimization