Estimation bayésienne de fréquences alléliques dans un modèle de métapopulation

This work aims at studying the meta-population genetic structure along with the dispersal ability of individuals among local populations by estimating the heterogeneity of allelic frequencies based on ”multinomial-Dirichlet” distributions, and implemented on the JAGS software (R package rjags). The number of copies of the different alleles are sampled in a multinomial distribution with parameters depending on population allelic frequencies. The population allelic frequencies are sampled in a Dirichlet distribution with parameter equal to the product of the metapopulation allelic frequencies and a F–parameter measuring differentiation (F-model, Gaggiotti and Foll 2010). This model was applied to an insect pest (Cydia pomonella), collected in several orchards in South of France at landscape scale

More pests but less pesticide applications: Ambivalent effect of landscape complexity on conservation biological control

International audienceIn agricultural landscapes, the amount and organization of crops and semi-natural habitats (SNH) have the potential to promote a bundle of ecosystem services due to their influence on ecological community at multiple spatio-temporal scales. SNH are relatively undisturbed and are often source of complementary resources and refuges, therefore supporting more diverse and abundant natural pest enemies. However, the nexus of SNH proportion and organization with pest suppression is not trivial. It is thus crucial to understand how the behavior of pest and natural enemy species, the underlying landscape structure, and their interaction, may influence conservation biological control (CBC). Here, we develop a generative stochastic landscape model to simulate realistic agricultural landscape compositions and configurations of fields and linear elements. Generated landscapes are used as spatial support over which we simulate a spatially explicit predator-prey dynamic model. We find that increased SNH presence boosts predator populations by sustaining high predator density that regulates and keeps pest density below the pesticide application threshold. However, predator presence over all the landscape helps to stabilize the pest population by keeping it under this threshold, which tends to increase pest density at the landscape scale. In addition, the joint effect of SNH presence and predator dispersal ability among hedge and field interface results in a stronger pest regulation, which also limits pest growth. Considering properties of both fields and linear elements, such as local structure and geometric features, provides deeper insights for pest regulation; for example, hedge presence at crop field boundaries clearly strengthens CBC. Our results highlight that the integration of species behaviors and traits with landscape structure at multiple scales is necessary to provide useful insights for CBC

Simulations of corrosion product transfer with the OSCAR v1.2 code

International audienceActivated Corrosion Products (ACPs) generate a radiation field in PWRs, which is the major contributor to the dose absorbed by nuclear power plant staff working during shutdown operations and maintenance. Therefore, a thorough understanding of the mechanisms that control the corrosion product transfer is of the highest importance. Since the 1970's, the R&D strategy in France has been based on experiments in test loops representative of PWR conditions, on in-situ gamma spectrometry measurements of the PWR primary system contamination and on simulation code development. The simulation of corrosion product transfers in PWR primary circuits is a major challenge since it involves many physical and chemical phenomena including: corrosion, dissolution, precipitation, erosion, deposition, convection, activation… In addition to the intrinsic difficulty of multi-physics modelling, the primary systems present severe operating conditions (300 °C, 150 bar, neutron flux, fluid velocity up to 15 m.s-1 and very low corrosion product concentrations). The purpose of the OSCAR code, developed by the CEA in cooperation with EDF and AREVA NP, is to predict the PWR primary system contamination by corrosion and fission products. The OSCAR code is considered to be not only a tool for numerical simulations and predictions (operational practices improvements and new-built PWRs design) but also one that might combine and organise all new knowledge useful to progress on contamination. The OSCAR code for Products of Corrosion, OSCAR PC, allows researchers to analyse the corrosion product behaviour and to calculate the ACP volume and surface activities of the primary and auxiliary systems. In the new version, OSCAR PC V1.2, the corrosion product transfer in the particulate form is enhanced and a new feature is the possibility to simulate cold shutdowns. In order to validate this version, the contamination transfer has been simulated in 5 French PWRs with different operating and design characteristics. After a description of the models of the main transfer mechanisms, the paper presents the calculated ACP surface and volume activities, the calculated concentrations of metallic elements and their comparisons with on-site measurements for one of the 5 validation cases. The simulations of a steam generator replacement and a cold shutdown are also presented. There is a good agreement between the OSCAR PC V1.2 results and the measured values during power operation and cold shutdown as well. Furthermore, the variations with operating cycle of the surface activities are correctly reproduced. Compared to the previous versions, these improvements are mainly due to the improvement of the thermodynamic database of the OSCAR chemistry module, PHREEQCEA, and to the enhancement of the corrosion product transfer in the particulate form

The OSCAR code package : A unique tool for simulating PWR contamination

International audienceUnderstanding the PWR primary circuit contamination by corrosion products, fission productsand actinides is a crucial issue for reactor operation and design. The main challenges aredecreasing the impact on personnel exposure to radiation, optimizing the plant operation,limiting the activity of the wastes produced during the reactor lifetime and preparingdecommissioning.In cooperation with EDF and AREVA NP, CEA has developed the OSCAR code package, aunique tool for simulating PWR contamination. The OSCAR package results from the mergingof two codes, which simulate PWR contamination by fission products and actinides (PROFIPcode) and by activated corrosion products (PACTOLE code).These two codes have been validated separately against an extensive set of data obtained over 40years from in-situ gamma spectrometry measurements, sampling and analysing campaigns ofprimary coolant, as well as experiments in test loops or experimental reactors, which arerepresentative of PWR conditions.In this paper, a new step is presented with the OSCAR code package, combining the features ofthe two codes and motivated by the fact that, wherever they originate from, the contaminationproducts are subject to the same severe conditions (300 °C, 150 bar, neutron flux, water velocityup to 15 m.s-1) and follow the same transport mechanisms in the primary circuit. The main processes involved are erosion/deposition, dissolution/precipitation, adsorption/desorption,convection, purification, neutron activation, radioactive decrease.The V1.1 version of the OSCAR package is qualified for fission products (Xe, Kr, I, Sr),actinides (U, Np, Pu, Am, Cm) and corrosion products (Ni, Fe, Co, Cr).This paper presents the different release modes (defective fuel rod release, fissile materialdissemination, material corrosion and release), then the processes which govern contaminationtransfer, and finally, we give examples of the comparison of the OSCAR package results withmeasurements in French PWR primary circuit obtained for representative radioisotopes : $^{133}$Xe,$^{90}$Sr, $^{58}$Co, $^{60}$Co. In particular, we focus on the main upgrades in the OSCAR simulations compared to thePROFIP and PACTOLE codes : adaptation of the MARGARET module to assess fission productrelease out of fuel pellets in a defective rod, adsorption/desorption model development forstrontium behaviour, multi-criteria calibration of input data which are not well known forcorrosion product simulation

A data science platform to enable time-domain astronomy

International audienceSkyPortal is an open-source platform designed to efficiently discover interesting transients, manage follow-up, perform characterization, and visualize the results, all in one application. By enabling fast access to archival and catalog data, cross-matching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, SkyPortal has been operating at scale for > 2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. While SkyPortal emphasizes rich user experiences (UX) across common frontend workflows, recognizing that scientific inquiry is increasingly performed programmatically, SkyPortal also surfaces an extensive and well-documented API system. From backend and frontend software to data science analysis tools and visualization frameworks, the SkyPortal design emphasizes the re-use and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance, SkyPortal now leverages ChatGPT large-language models (LLMs) to automatically generate and surface source-level human-readable summaries. With the imminent re-start of the next-generation of gravitational wave detectors, SkyPortal now also includes dedicated multi-messenger features addressing the requirements of rapid multi-messenger follow-up: multi-telescope management, team/group organizing interfaces, and cross-matching of multi-messenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for the newcomers to the field. (abridged

A data science platform to enable time-domain astronomy

SkyPortal is an open-source platform designed to efficiently discover interesting transients, manage follow-up, perform characterization, and visualize the results, all in one application. By enabling fast access to archival and catalog data, cross-matching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, SkyPortal has been operating at scale for > 2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. While SkyPortal emphasizes rich user experiences (UX) across common frontend workflows, recognizing that scientific inquiry is increasingly performed programmatically, SkyPortal also surfaces an extensive and well-documented API system. From backend and frontend software to data science analysis tools and visualization frameworks, the SkyPortal design emphasizes the re-use and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance, SkyPortal now leverages ChatGPT large-language models (LLMs) to automatically generate and surface source-level human-readable summaries. With the imminent re-start of the next-generation of gravitational wave detectors, SkyPortal now also includes dedicated multi-messenger features addressing the requirements of rapid multi-messenger follow-up: multi-telescope management, team/group organizing interfaces, and cross-matching of multi-messenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for the newcomers to the field. (abridged

A data science platform to enable time-domain astronomy

International audienceSkyPortal is an open-source platform designed to efficiently discover interesting transients, manage follow-up, perform characterization, and visualize the results, all in one application. By enabling fast access to archival and catalog data, cross-matching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, SkyPortal has been operating at scale for > 2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. While SkyPortal emphasizes rich user experiences (UX) across common frontend workflows, recognizing that scientific inquiry is increasingly performed programmatically, SkyPortal also surfaces an extensive and well-documented API system. From backend and frontend software to data science analysis tools and visualization frameworks, the SkyPortal design emphasizes the re-use and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance, SkyPortal now leverages ChatGPT large-language models (LLMs) to automatically generate and surface source-level human-readable summaries. With the imminent re-start of the next-generation of gravitational wave detectors, SkyPortal now also includes dedicated multi-messenger features addressing the requirements of rapid multi-messenger follow-up: multi-telescope management, team/group organizing interfaces, and cross-matching of multi-messenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for the newcomers to the field. (abridged

A Data Science Platform to Enable Time-domain Astronomy

SkyPortal is an open-source software package designed to discover interesting transients efficiently, manage follow-up, perform characterization, and visualize the results. By enabling fast access to archival and catalog data, crossmatching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, a SkyPortal-based platform has been operating at scale for >2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. While SkyPortal emphasizes rich user experiences across common front-end workflows, recognizing that scientific inquiry is increasingly performed programmatically, SkyPortal also surfaces an extensive and well-documented application programming interface system. From back-end and front-end software to data science analysis tools and visualization frameworks, the SkyPortal design emphasizes the reuse and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance, SkyPortal now leverages ChatGPT large language models to generate and surface source-level human-readable summaries automatically. With the imminent restart of the next generation of gravitational-wave detectors, SkyPortal now also includes dedicated multimessenger features addressing the requirements of rapid multimessenger follow-up: multitelescope management, team/group organizing interfaces, and crossmatching of multimessenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for newcomers to the field. This paper focuses on the detailed implementations, capabilities, and early science results that establish SkyPortal as a community software package ready to take on the data science challenges and opportunities presented by this next chapter in the multimessenger era

A Data Science Platform to Enable Time-domain Astronomy

SkyPortal is an open-source software package designed to discover interesting transients efficiently, manage follow-up, perform characterization, and visualize the results. By enabling fast access to archival and catalog data, crossmatching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, a SkyPortal -based platform has been operating at scale for >2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. While SkyPortal emphasizes rich user experiences across common front-end workflows, recognizing that scientific inquiry is increasingly performed programmatically, SkyPortal also surfaces an extensive and well-documented application programming interface system. From back-end and front-end software to data science analysis tools and visualization frameworks, the SkyPortal design emphasizes the reuse and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance, SkyPortal now leverages ChatGPT large language models to generate and surface source-level human-readable summaries automatically. With the imminent restart of the next generation of gravitational-wave detectors, SkyPortal now also includes dedicated multimessenger features addressing the requirements of rapid multimessenger follow-up: multitelescope management, team/group organizing interfaces, and crossmatching of multimessenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for newcomers to the field. This paper focuses on the detailed implementations, capabilities, and early science results that establish SkyPortal as a community software package ready to take on the data science challenges and opportunities presented by this next chapter in the multimessenger era

A data science platform to enable time-domain astronomy

International audienceSkyPortal is an open-source platform designed to efficiently discover interesting transients, manage follow-up, perform characterization, and visualize the results, all in one application. By enabling fast access to archival and catalog data, cross-matching heterogeneous data streams, and the triggering and monitoring of on-demand observations for further characterization, SkyPortal has been operating at scale for > 2 yr for the Zwicky Transient Facility Phase II community, with hundreds of users, containing tens of millions of time-domain sources, interacting with dozens of telescopes, and enabling community reporting. While SkyPortal emphasizes rich user experiences (UX) across common frontend workflows, recognizing that scientific inquiry is increasingly performed programmatically, SkyPortal also surfaces an extensive and well-documented API system. From backend and frontend software to data science analysis tools and visualization frameworks, the SkyPortal design emphasizes the re-use and leveraging of best-in-class approaches, with a strong extensibility ethos. For instance, SkyPortal now leverages ChatGPT large-language models (LLMs) to automatically generate and surface source-level human-readable summaries. With the imminent re-start of the next-generation of gravitational wave detectors, SkyPortal now also includes dedicated multi-messenger features addressing the requirements of rapid multi-messenger follow-up: multi-telescope management, team/group organizing interfaces, and cross-matching of multi-messenger data streams with time-domain optical surveys, with interfaces sufficiently intuitive for the newcomers to the field. (abridged