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Who gets to stay? How mass layoffs reshape firms' skills structure
No full textThis paper contests the traditional view of layoffs as solely reactive to negative economic conditions. Using survey and administrative French data, we provide evidence on how firms strategically utilize mass layoffs to restructure their workforce composition. First, we investigate if firms use layoffs to shift their skill requirements. Analyzing both layoff and matched non-layoff firms, we find firms significantly increase the requirements for social skills while decreasing dependence on manual and cognitive skills requirements after layoffs. This suggests a premeditated reshaping of the workforce instead of a costcutting practice. Secondly, we explore the factors influencing selection into displacement during layoffs. We focus on three key aspects: skills mismatch, relative worker quality, and perceived monetary cost. Our findings highlight the significant role of skill mismatch and worker quality in determining dismissal, suggesting firms actively select based on strategic needs. By revealing the strategic nature of mass layoffs and their impact on skills composition and worker selection, this paper offers valuable insights into the understanding of workforce adjustment. Such insights are relevant for policy design
Joint determination of Venus gravity and atmospheric density through EnVision radio science investigation
No full textInternational audienceThe ESA mission EnVision will address its main scientific questions through a detailed mapping of the surface and interior properties of Venus. A precise reconstruction of the spacecraft trajectory is a key requirement for the EnVision scientific investigations, including radio science. To precisely constrain the orbit evolution, refined models of the dynamical forces are included in the Precise Orbit Determination (POD) process. We developed a methodology based on a batch-sequential filter that enables a joint estimation of Venus gravity and atmospheric density. Our approach yields an accurate compensation of atmospheric mismodeling, simulated through semi-empirical predictions of the atmospheric density provided by general circulation models (GCM), e.g., Venus Climate Database (VCD). Numerical simulations of the EnVision radio science investigation were carried out by using a perturbative analysis of the dynamical forces, which accounts for atmospheric density errors ≥ 200%. By adjusting a set of atmospheric scale factors, our proposed strategy enables an estimation of the atmospheric density at the spacecraft altitudes with an accuracy of 25%. The improved dynamical model yields accuracies in the orbit reconstruction of 1-2 m, 30-40 m and 20-30 m in the radial, transverse and normal directions
Impact of solid road barriers on reactive pollutant dispersion in an idealized urban canyon: A large-eddy simulation coupled with chemistry
No full textInternational audienceThis study conducts chemistry-coupled large-eddy simulations on reactive gaseous and particulate pollutant dispersions in an idealized street canyon. Four road-barrier configurations are considered: barrier-free, side barriers, center barrier, and the combination of side and center barriers. Regarding the formation of secondary aerosols, the center barrier reduces the canyon-averaged mass concentration of particulate matter (PM) but increases the inorganic particle concentration. This is because nitric acid (HNO3) is limited in the formation of ammonium nitrate due to the long residence time in the street, and the center barrier increases the HNO3 inflow from the background air. The side barriers increase the canyon-averaged PM10 mass concentration but reduce PM number concentration due to sufficient time for coagulation. Using combined barriers reduces the most PM10 mass concentration and number concentration from the barrier-free case. Regarding the formation of secondary gases, the side barriers enhance the NO2 formation due to the worse ventilation. In contrast, the center barrier largely reduces the canyon-averaged NO concentration but slightly reduces the NO2 concentration from the barrier-free case, because the center barrier increases the O3 inflow from the background air favoring NO2 formation. Additionally, the combined barriers show smaller canyon-averaged NO2 and O3 concentrations than the center barrier. From the view of controlling reactive pollutants, urban planners are recommended to apply the combined barriers to enhance better air quality in street canyons, rather than using either side barriers or a center barrier alone
Ocean-related options for climate change mitigation and adaptation: A machine learning-based evidence map protocol
No full textBackground Ocean-related options (OROs) to mitigate and adapt to climate change are receiving increasing attention from practitioners, decision-makers, and researchers. In order to guide future ORO development and implementation, a catalogue of scientific evidence addressing outcomes related to different ORO types is critical. However, until now, such a synthesis has been hindered by the large size of the evidence base. Here, we detail a protocol using a machine learning-based approach to systematically map the extent and distribution of academic evidence relevant to the development, implementation, and outcomes of OROs. Method To produce this systematic map, literature searches will be conducted in English across two bibliographic databases using a string of search terms relating to the ocean, climate change, and OROs. A sample of articles from the resulting de-duplicated corpus will be manually screened at the title and abstract level for inclusion or exclusion against a set of predefined eligibility criteria in order to select all relevant literature on marine and coastal socio-ecological systems, the type of ORO and its outcomes. Descriptive metadata on the type and location of intervention, study methodology, and outcomes will be coded from the included articles in the sample. This sample of screening and coding decisions will be used to train a machine learning model that will be used to estimate these labels for all the remaining unseen publications. The results will be reported in a narrative synthesis summarising key trends, knowledge gaps, and knowledge clusters
Evaporation of Reservoir for Different Floating Photovoltaic Layouts
No full textInternational audienceIn recent years, the floating photovoltaic (FPV) market has undergone significant expansion, fueled by the multitude of advantages inherent in this installation method. Notably, it is an alternative to face the lack of available ground surface and it could lead to a substantial reduction in reservoir evaporation. Indeed, the components of FPV arrays partially cover the free surface, mitigating the effects of wind at the surface of the water which in turn should limit the evaporation.Given the increasing importance of water as a critical and scarce resource, the need to find ways to conserve water has never been more pronounced. Presently, the estimation of evaporation relies mainly on empirical laws, and variables such as local wind, ambient humidity, air and water temperature, as well as FPV array characteristics have a significant influence on evaporation dynamics.To address these challenges, our study introduces a novel approach utilizing Computational Fluid Dynamics (CFD) simulations to model micro-scale conditions above a reservoir partially covered by an FPV power-plant and surrounded by the ground. In this study, the plant is modeled by an equivalent rough surface and the water vapor transfer is taken into account through a mass exchange coefficient. These quantities are imposed using correlations derived from 2D bi-periodic models, primarily based on wind characteristics (friction velocity, wind directions).However, as the water flow in the reservoir is not modeled, the water surface temperature is a critical parameter because it is a boundary condition which is often an unknown variable. Therefore, this study aims at investigating the impact of water temperature on reservoir evaporation rates, considering scenarios with two distinct FPV layouts that are compared to the evaporation on a reservoir without FPV array. The first FPV layout entails a large footprint system, characterized by a ground-coverage ratio (GCR) of 75 %, while the second FPV layout represents a free footprint system with a GCR of 57 %. The water-coverage ratio (WCR, namely the surface in direct contact with the waterbody, including floats, structure, buoy, or even directly the panel in certain cases), set respectively at 60% and 10%, is also a key indicator. This study will therefore enable us to conclude on the efficiency of these two types of layouts in terms of evaporation reduction, with a view to geometric optimization. Also, the influence of bottom conditions providing insights that guide us in determining a better approach for incorporating water temperature into our model
Gibbs principle with infinitely many constraints: optimality conditions and stability
No full textWe extend the Gibbs conditioning principle to an abstract setting combining infinitely many linear equality constraints and non-linear inequality constraints, which need not be convex. A conditional large large deviation principle (LDP) is proved in a Wassersteintype topology, and optimality conditions are written in this abstract setting. This setting encompasses versions of the Schrödinger bridge problem with marginal non-linear inequality constraints at every time. In the case of convex constraints, stability results for perturbations both in the constraints and the reference measure are proved. We then specify our results when the reference measure is the path-law of a continuous diffusion process, whose law is constrained at each time. We obtain a complete description of the constrained process through an atypical mean-field PDE system involving a Lagrange multiplier
Se déplacer pour se faire opérer : géographie des mobilités hospitalières
No full textInternational audienc
Studying inclusive innovation with the right data: An empirical illustration from Ethiopia
No full textInternational audienceCONTEXTAgricultural innovations are inclusive when they are used by any member of society who wants to use them. Conversely, agricultural innovations that can only be used by a specific privileged group within society can be characterized as “exclusive”.OBJECTIVEThe first objective of this paper is to examine the inclusivity of agricultural innovations in Ethiopia, using national representative data and considering a wide portfolio of innovations resulting from the collaborative research between CGIAR and its national partners. Second, we also examine how measurement error may affect how we characterize the inclusivity of agricultural innovations.METHODSWe use nationally-representative survey data from Ethiopia (collected in 2018/19) in which best-practice measures of the adoption of a large number of agricultural innovations were embedded, including the adoption of CGIAR-related improved maize varieties measured using two different approaches: subjective, self-reported survey data; and objective DNA fingerprinting of crop samples taken from the same farmers' plots. A rich set of household variables is also collected in the survey, which allows characterizing the types of farmers that are adopting different innovations, and the extent to which conclusions regarding the inclusivity of innovations depends on the measurement of the latter.RESULTS AND CONCLUSIONSMany innovations are not disproportionately more likely to be adopted by male, larger, richer, or more connected farmers. When using self-reported data on adoption of improved maize varieties, adoption appears positively correlated with having larger landholdings and households with lower female participation in agriculture, and negatively correlated with poorer households (being among the bottom 40% of consumption distribution). Substituting survey responses with the results of DNA fingerprinting these correlations disappear, with farm size, gender and poverty status no longer predictive of adoption.SIGNIFICANCEThe results suggest the potential value of offering a menu of innovations to farmers to increase inclusivity, as it allows each farmer to be a critical consumer of potential innovations and select those that best correspond to their own needs and constraints. We also highlight how important data quality is in ensuring we have correct information about inclusive innovation
Indicators of Global Climate Change 2023: annual update of key indicators of the state of the climate system and human influence
No full textInternational audienceIntergovernmental Panel on Climate Change (IPCC) assessments are the trusted source of scientific evidence for climate negotiations taking place under the United Nations Framework Convention on Climate Change (UNFCCC). Evidence-based decision-making needs to be informed by up-to-date and timely information on key indicators of the state of the climate system and of the human influence on the global climate system. However, successive IPCC reports are published at intervals of 5–10 years, creating potential for an information gap between report cycles. We follow methods as close as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One (WGI) report. We compile monitoring datasets to produce estimates for key climate indicators related to forcing of the climate system: emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. The purpose of this effort, grounded in an open-data, open-science approach, is to make annually updated reliable global climate indicators available in the public domain (https://doi.org/10.5281/zenodo.11388387, Smith et al., 2024a). As they are traceable to IPCC report methods, they can be trusted by all parties involved in UNFCCC negotiations and help convey wider understanding of the latest knowledge of the climate system and its direction of travel. The indicators show that, for the 2014–2023 decade average, observed warming was 1.19 [1.06 to 1.30] °C, of which 1.19 [1.0 to 1.4] °C was human-induced. For the single-year average, human-induced warming reached 1.31 [1.1 to 1.7] °C in 2023 relative to 1850–1900. The best estimate is below the 2023-observed warming record of 1.43 [1.32 to 1.53] °C, indicating a substantial contribution of internal variability in the 2023 record. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.26 [0.2–0.4] °C per decade over 2014–2023. This high rate of warming is caused by a combination of net greenhouse gas emissions being at a persistent high of 53±5.4 Gt CO2e yr−1 over the last decade, as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track a change of direction for some of the indicators presented here
Estimation de la durée de vie pour une voie ferrée sur dalle au travers d'une approche d'endommagement cumulatif
No full textNational audienceL’estimation de la durée de vie des structures suscite un intérêt tant chez les industriels que chez les chercheurs. L’objectif revient à déterminer jusqu’à quel point l’utilisation des matériaux composant les structures peut se faire sans compromettre leur qualité. Cette étude se concentre sur l’estimation de la durée de vie d’une section spécifique de voie ferrée sur dalle soumise à des charges cycliques hétérogènes dues au passage des trains. Une attention particulière est portée à la détermination de sa durée de vie lorsqu’une section de la voie est endommagée, entrainant des surcharges dans le voisinage de cette section