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Main conclusions and perspectives from the collective scientific assessment of the effects of plant protection products on biodiversity and ecosystem services along the land–sea continuum in France and French overseas territories
No full textInternational audiencePreservation of biodiversity and ecosystem services is critical for sustainable development and human well-being. However, an unprecedented erosion of biodiversity is observed and the use of plant protection products (PPP) has been identified as one of its main causes. In this context, at the request of the French Ministries responsible for the Environment, for Agriculture and for Research, a panel of 46 scientific experts ran a nearly 2-year-long (2020-2022) collective scientific assessment (CSA) of international scientific knowledge relating to the impacts of PPP on biodiversity and ecosystem services. The scope of this CSA covered the terrestrial, atmospheric, freshwater, and marine environments (with the exception of groundwater) in their continuity from the site of PPP application to the ocean, in France and French overseas territories, based on international knowledge produced on or transposable to this type of context (climate, PPP used, biodiversity present, etc.). Here, we provide a brief summary of the CSA's main conclusions, which were drawn from about 4500 international publications. Our analysis finds that PPP contaminate all environmental matrices, including biota, and cause direct and indirect ecotoxicological effects that unequivocally contribute to the decline of certain biological groups and alter certain ecosystem functions and services. Levers for action to limit PPP-driven pollution and effects on environmental compartments include local measures from plot to landscape scales and regulatory improvements. However, there are still significant gaps in knowledge regarding environmental contamination by PPPs and its effect on biodiversity and ecosystem functions and services. Perspectives and research needs are proposed to address these gaps
Solitons and coherent structures in optics: 50th anniversary of the prediction of optical solitons in fiber
No full textInternational audienceNonlinear optics is a continuously expanding field due to its wide range of applications covering temporal, spectral, polarization or spatial features of the light signals. 2023 was the celebration of 50 years since the numerical prediction of the existence of solitons in optical fiber by Hasegawa and Tappert and, to celebrate this milestone, Optics Communications invited submissions related to nonlinear coherent structures in optical waveguides involving the Kerr nonlinearity. The purpose of this Special Issue was to provide an overview of recent ongoing progress and trends in advancing the knowledge, understanding, and novel applications of optical solitons and other related nonlinear structures. Both theoretical and experimental reports or discussions were welcomed
Convergence of population processes with small and frequent mutations to the canonical equation of adaptive dynamics
No full textInternational audienceIn this article, a stochastic individual-based model describing Darwinian evolution of asexual, phenotypic trait-structured population, is studied. We consider a large population with constant population size characterised by a resampling rate modeling competition pressure driving selection and a mutation rate where mutations occur during life. In this model, the population state at fixed time is given as a measure on the space of phenotypes and the evolution of the population is described by a continuous time, measure-valued Markov process. We investigate the asymptotic behavior of the system, where mutations are frequent, in the double simultaneous limit of large population (K → +∞) and small mutational effects (σK → 0) proving convergence to an ODE known as the canonical equation of adaptive dynamics. This result holds only for a certain range of σK parameters (as a function of K) which must be small enough but not too small either. The canonical equation describes the evolution in time of the dominant trait in the population driven by a fitness gradient. This result is based on an slow-fast asymptotic analysis. We use an averaging method, inspired by (Kurtz, 1992), which exploits a martingale approach and compactness-uniqueness arguments. The contribution of the fast component, which converges to the centered Fleming-Viot process, is obtained by averaging according to its invariant measure, recently characterised in (Champagnat-Hass, 2022)
Fully guaranteed and computable error bounds on the energy for periodic Kohn-Sham equations with convex density functionals
No full textInternational audienceIn this article, we derive fully guaranteed error bounds for the energy of convex nonlinear mean-field models. These results apply in particular to Kohn-Sham equations with convex density functionals, which includes the reduced Hartree-Fock (rHF) model, as well as the Kohn-Sham model with exact exchange-density functional (which is unfortunately not explicit and therefore not usable in practice). We then decompose the obtained bounds into two parts, one depending on the chosen discretization and one depending on the number of iterations performed in the self-consistent algorithm used to solve the nonlinear eigenvalue problem, paving the way for adaptive refinement strategies. The accuracy of the bounds is demonstrated on a series of test cases, including a Silicon crystal and an Hydrogen Fluoride molecule simulated with the rHF model and discretized with planewaves. We also show that, although not anymore guaranteed, the error bounds remain very accurate for a Silicon crystal simulated with the Kohn-Sham model using nonconvex exchangecorrelation functionals of practical interest
What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA
No full textInternational audienceModelling population connectivity is central to biodiversity conservation and often relies on resistance surfaces reflecting multi-generational gene flow. ResistanceGA (RGA) is a common optimization framework for parameterizing these surfaces by maximizing the fit between genetic distances and cost distances using maximum likelihood population effect models. As the reliability of this framework has rarely been studied, we investigated the conditions maximizing its accuracy for both prediction and interpretation of landscape features' permeability. We ran demo-genetic simulations in contrasted landscapes for species with distinct dispersal capacities and specialization levels, using corresponding reference cost scenarios. We then optimized resistance surfaces from the simulated genetic distances using RGA. First, we evaluated whether RGA identified the drivers of the genetic patterns, that is, distinguished Isolation-by-Resistance (IBR) patterns from either Isolation-by-Distance or patterns unrelated to ecological distances. We then assessed RGA predictive performance using a cross-validation method, and its ability to recover the reference cost scenarios shaping genetic structure in simulations. IBR patterns were well detected and genetic distances were predicted with great accuracy. This performance depended on the strength of the genetic structuring, sampling design and landscape structure.Matching the scale of the genetic pattern by focusing on population pairs connected through gene flow and limiting overfitting through cross-validation further enhanced inference reliability. Yet, the optimized cost values often departed from the reference values, making their interpretation and extrapolation potentially dubious. While demonstrating the value of RGA for predictive modelling, we call for caution and provide additional guidance for its optimal use.</p
Coverage of elbow and forearm soft tissue defects with the posterior ulnar recurrent artery perforator flap (PURAP): an anatomical study
No full textInternational audienceIntroduction: Covering soft tissue defects from the elbow and forearm is challenging for the plastic surgeon. The posterior ulnar recurrent artery perforator flap is a fasciocutaneous perforator flap vascularized by the perforators emerging from the posterior ulnar recurrent artery. It has multiple functional and aesthetic advantages but has not yet been well studied. This work aimed to examine the number, caliber, and topography of the posterior ulnar recurrent artery's perforators.Methods: Perforator mapping was performed by blue latex injection on 20 fresh cadavers' upper extremities. Thermal mapping by TIRD was used to identify the \"hot spots\" of these perforators, and the 4D vascular network of the ulnar recurrent artery was scanned. The preoperative design and dissection of the flap were adapted based on the results of this anatomical study. A case study was performed to illustrate the clinical application.Results: On average, we located 7.7 ± 1.7 perforators per upper extremity with an average caliber of 0.77 ± 0.19 mm (3.5 ± 1.2 in the forearm and 4.2 ± 1.5 in the arm). On average, the arm perforators were located 3.2 ± 1.6 cm proximally from the medial epicondyle. Thermal mapping showed three perforator \"hot spots,\" two in the forearm (directly at the artery origin level and one more posteriorly) and one in the arm. The 4D CT reconstructions allowed us to estimate the vascular territory at the level of the medial epicondyle and the distal half of the medial aspect of the arm, as well as the ascending course of the artery.Conclusion: The posterior ulnar recurrent artery perforator flap can be harvested efficiently and reliably, as the posterior ulnar recurrent artery has constant perforators, especially around 3 cm proximal to the medial epicondyle. This reinforces this flap's status as a potential elbow and forearm tissue defect coverage alternative
The nuclear dynamic of CDC48 is affected during the immune response in plants
No full textInternational audiencePlants are continuously challenged by a myriad of pathogenic microorganisms, including bacteria, viruses, fungi and oomycetes, against which they must defend themselves. The protein Cell Division Cycle 48 (CDC48), a key player of ubiquitin-proteasome system which segregates and remodels ubiquitinated proteins for degradation, is known to be mobilized during plant immunity. Moreover, the characterization of the nuclear role of CDC48 is of interest, in particular its regulation in nuclear processes such as chromatin remodeling, DNA repair and gene expression. In this regard, its nuclear functions during plant immunity remain underexplored. This study investigates the dynamics of CDC48 during plant immune responses. The biophysical analysis using the Fluorescence Correlation Spectroscopy (FCS) on tobacco leaves stably overexpressing GFP-CDC48 revealed that the nuclear dynamics of CDC48 changed after treatment with cryptogein, an elicitor of immune responses. FCS analysis revealed an increase of the nuclear mobility of CDC48 and a faster interaction of CDC48 with a wide range of nuclear partners shortly after cryptogein treatment. Overall, our study shows a nuclear regulation of the interaction of CDC48 with its potential partners and sheds new light on potential nuclear involvements of CDC48 following the triggering of defense mechanisms
Approches numériques pour les modèles d'EDP non locaux dominés par le transport avec applications en biologie
No full textInternational audienceTransport-dominated partial differential equation models have been used extensively over the past two decades to describe various collective migration phenomena in cell biology and ecology. To understand the behaviour of these models (and the biological systems they describe) different analytical and numerical approaches have been used. While the analytical approaches have been discussed by different recent review studies, the numerical approaches are still facing different open problems, and thus are being employed on a rather ad-hoc basis for each developed non-local model. The goal of this review is to summarise the basic ideas behind these transport-dominated non-local models, to discuss the current numerical approaches used to simulate these models, and finally to discuss some open problems related to the applications of these numerical methods, in particular the finite element method. This allows us to emphasize the opportunities offered by this numerical method to advance the research in this field. In addition, we present in detail some numerical schemes that we used to discretize these non-local equations; in particular a new semi-implicit scheme we introduced to stabilize the oscillations obtained with classical schemes.</div
Innovative battery-free wireless piezoresistive sensor for green-IoT applications
No full textInternational audienceThis paper unveils an innovative wireless piezoresistive sensor designed to operate autonomously without batteries, addressing the critical challenge of energy sustainability in Internet of Things (IoT) applications. Traditional sensor systems often rely on batteries, which pose significant limitations in maintenance, environmental impact, and operational lifespan. Our proposed solution integrates an energy-harvesting system that efficiently converts ambient light into electrical energy, enabling continuous operation in various environments. The findings demonstrate that the developed sensor exhibits high sensitivity and accuracy in measuring mechanical strain, with a coefficient of determination (r2) of 0.99 and a root mean square error (RMSE) of 1.17 N, making it suitable for real-time monitoring applications. The integration of Time Domain to Digital Conversion (TDDC) technology significantly reduces power consumption by eliminating the need for conventional analog-to-digital converters, thus enhancing the overall energy efficiency of the wireless sensor network (WSN). The contributions of this work are multifaceted: we present the first demonstration of TDDC for force and resistive measurements in battery-free sensor nodes, propose a mathematical model for resistance to time domain digital conversion, and develop two calibration methods tailored for force and resistance measurements. These innovations advance the field of green wireless sensor technologies and pave the way for scalable and sustainable IoT solutions. The implications of this research extend to various applications, including structural health monitoring, industrial condition monitoring, and environmental sensing, where long-term data collection is essential for proactive maintenance and fault detection