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Exit Incentives for Carbon Emissive Firms
No full textInternational audienceWe develop a continuous-time model of incentives for carbon emissive firms to exit the market based on a compensation payment identical to all firms. In our model, firms enjoy profits from production modeled as a simple geometric Brownian motion and do not bear any environmental damage from production. A regulator maximizes the expected discounted value of firms profits from production minus environmental damages caused by production and proposes a compensation payment whose dynamics is known to the firms. We provide in both situations closed-form expressions for the compensation payment process and the exit thresholds of each firms. We apply our model to the crude oil market. We show that market concentration increases the total expected discounted payments to firms and reduces the expected closing time of polluting assets. A certain degree of market concentration can enable the regulator to halt production in a shorter time but at a higher cost. We extend this framework to the case of two countries each regulating its own market. We analyze scenarios involving two large producers and a combination of large and small producers. Our findings indicate that the proposed model facilitates an earlier exit of brown energy from the market compared to the scenario where each country independently regulates its market. This has significant implications for regulatory strategies aimed at accelerating the transition to cleaner energy sources
Molecular and biophysical characterization of cultured DRG neurons in response to focused ultrasound
No full textInternational audienceDorsal root ganglion (DRG) neurons have a wide range of functions, including touch, pain and itch. These neurons have recently emerged as promising targets for non-invasive focused ultrasound (FUS) neuromodulation. However, our understanding of the molecular and physical mechanisms underlying FUS-evoked responses in DRG neurons remains limited. Here, we explore the neuromodulatory effects of FUS on cultured DRG neurons using calcium imaging to track neural responses. We find that a 20-MHz FUS burst of 1-ms duration at an acoustic pressure of 5 MPa elicited calcium responses in 52% of DRG neurons. Single-cell RNA sequencing reveals that more than half of FUS-sensitive neurons belong to two subsets: the TH-expressing C low-threshold mechanoreceptors (C-LTMRs) and the MRGPRDexpressing C high-threshold mechanoreceptors (C-HTMRs), both of which express the G αi -interacting protein (GINIP). This finding was further confirmed by using a ginip mouse model. We demonstrate that FUS excites both GINIP + and GINIP-neurons through membrane deformation, likely mediated by mechanosensitive ion channels. Our findings identify specific FUS parameters that activate distinct subsets of DRG neurons, opening new possibilities for using FUS to modulate DRG neuron activity
Decision analysis rooted in Indigenous and Western scientific knowledge identifies cost‐effective strategies for managing hyperabundant deer to restore keystone places
No full textInternational audienceThe hyperabundance of herbivores—a result of altered human relationality with the land and the extirpation of predators—is leading to large‐scale degradation of keystone ecosystems across the globe. Designing and implementing socially acceptable and cost‐effective strategies that meaningfully reduce herbivore populations while allowing for the recovery of ecological function and cultural relationality is an inherently complex issue. As a result, decision paralysis is common, leading to delayed or avoided action and continued ecosystem loss and degradation. Using a structured decision‐making process that incorporated expert elicitation, population modelling and cost‐effectiveness analyses while honouring multiple knowledge systems, we identified five discrete and four portfolio strategies for managing hyperabundant black‐tailed deer ( Odocoileus hemionus columbianus ) in the Southern Gulf Islands of British Columbia, Canada, with consideration to benefit, feasibility and cost objectives. Hunting led by local Indigenous Nations was ranked the most cost‐effective strategy when benefits considered well‐being of peoples and place holistically, and accounted for both Indigenous and Western science worldviews. When only Western perspectives were included, increased licensed hunting by local communities and hiring professional deer reduction specialists were ranked the most cost‐effective. However, while increased licensed hunting had a >50% likelihood of project uptake and success (i.e. feasibility), the strategy had <50% likelihood of achieving any benefit objective. In comparison, Indigenous‐led hunting, professional deer reduction specialists, and all portfolio strategies had >50% likelihood of meeting at least one benefit objective, although only Indigenous‐led hunting also had >50% likelihood of achieving feasibility objectives. Synthesis and applications . We provide a roadmap for decision‐makers across the globe to robustly and transparently assess the problem of herbivore hyperabundance and inform solutions within their context. Within the Salish Sea, our work highlights the need to support hunting, and in particular, Indigenous‐led hunting, as cost‐effective strategies to promote revitalization of well‐being of peoples and place. Read the free Plain Language Summary for this article on the Journal blog
Tara Polaris expeditions: seasonal and long-term contaminant monitoring in the changing central Arctic
No full textInternational audienceThe central Arctic atmosphere, cryosphere, hydrosphere and biosphere, is heavily impacted by anthropogenic activities. While some contaminants originate from local activities, the majority are transported over long distances via rivers, ocean currents, and atmospheric pathways. Contaminants can have adverse effects on the environment, ecosystems, and human health, which are expected to intensify with continued emissions and warming climate. This article outlines the objectives for new studies on contaminants in the Arctic Ocean, in particular during the Tara Polaris expedition, with an emphasis on year-round long-term contaminant dynamics and associated ecotoxicological risks. Mercury contamination remains a major concern in the Arctic, especially in the form of methylmercury, which is primarily produced by marine microbes. Methylmercury bioconcentrates, bioaccumulates and biomagnifies to harmful levels in Arctic wildlife and threatens indigenous communities. Anthropogenic lead (Pb), though low in Arctic waters, remains toxic and may be remobilized by climate change. Plastic pollution, from nano-to macro-scales, is widespread across all Arctic compartments, closely interacting with planktonic communities and posing ingestion risks to invertebrates, fish, seabirds and mammals (including humans). Chemicals of Emerging Arctic Concern (CEAC), including newly recognized persistent organic pollutants inherited from past industrial activities (e.g., per-and polyfluoroalkyl substances (PFAS)), are more recalcitrant in the environment than many other synthetic compounds, raising serious questions about their long-term ecological and health effects. In this context, the Tara Polaris expeditions aim to produce high-resolution, year-round observational data in the central Arctic to deepen our understanding of contaminant sources, transport, internal cycling and environmental fate. These data will also support the development and refinement of numerical models for contaminant dynamics in the context of both Arctic and global environmental change
Regime-aware time weighting for physics-informed neural networks
No full textInternational audienceWe introduce a novel method to handle the time dimension when Physics-Informed Neural Networks (PINN) are used to solve time-dependent differential equations; our proposal focuses on how time sampling and weighting strategies affect solution quality. While previous methods proposed heuristic time-weighting schemes, our approach is grounded in theoretical insights derived from the Lyapunov exponents, which quantify the sensitivity of solutions to perturbations over time. This principled methodology automatically adjusts weights based on the stability regime of the system — whether chaotic, periodic, or stable. Numerical experiments on challenging benchmarks, including the chaotic Lorenz system and the Burgers’ equation, demonstrate the effectiveness and robustness of the proposed method. Compared to existing techniques, our approach offers improved convergence and accuracy without requiring additional hyperparameter tuning. The findings underline the importance of incorporating causality and dynamical system behavior into PINN training strategies, providing a robust framework for solving time-dependent problems with enhanced reliability
Multiparameter estimation with an array of entangled atomic sensors
No full textInternational audienceIn quantum metrology, entangled states of many-particle systems are investigated to enhance measurement precision of the most precise clocks and field sensors. While single-parameter quantum metrology is well established, many metrological tasks require joint multiparameter estimation, which poses new conceptual challenges that have so far only been explored theoretically. We experimentally demonstrate multiparameter quantum metrology with an array of entangled atomic ensembles. By splitting a spin-squeezed ensemble, we create an atomic sensor array featuring inter-sensor entanglement that can be flexibly configured to enhance measurement precision of multiple parameters jointly. Using an optimal estimation protocol, we achieve significant gains over the standard quantum limit in key multiparameter estimation tasks, thus grounding the concept of quantum enhancement of field sensor arrays and imaging devices
Euclid Quick Data Release (Q1). First detections from the galaxy cluster workflow
No full textInternational audienceThe first survey data release by the Euclid mission covers approximately in the Euclid Deep Fields to the same depth as the Euclid Wide Survey. This paper showcases, for the first time, the performance of cluster finders on Euclid data and presents examples of validated clusters in the Quick Release 1 (Q1) imaging data. We identify clusters using two algorithms (AMICO and PZWav) implemented in the Euclid cluster-detection pipeline. We explore the internal consistency of detections from the two codes, and cross-match detections with known clusters from other surveys using external multi-wavelength and spectroscopic data sets. This enables assessment of the Euclid photometric redshift accuracy and also of systematics such as mis-centring between the optical cluster centre and centres based on X-ray and/or Sunyaev--Zeldovich observations. We report 426 joint PZWav and AMICO-detected clusters with high signal-to-noise ratios over the full Q1 area in the redshift range . The chosen redshift and signal-to-noise thresholds are motivated by the photometric quality of the early Euclid data. We provide richness estimates for each of the Euclid-detected clusters and show its correlation with various external cluster mass proxies. Out of the full sample, 77 systems are potentially new to the literature. Overall, the Q1 cluster catalogue demonstrates a successful validation of the workflow ahead of the Euclid Data Release 1, based on the consistency of internal and external properties of Euclid-detected clusters
Stochastic Coefficient of Variation: Assessing the Variability and Forecastability of Solar Irradiance
No full textInternational audienceThis work presents a robust framework for quantifying solar irradiance variability and forecastability through the Stochastic Coefficient of Variation () and the Forecastability (). Traditional metrics, such as the standard deviation, fail to isolate stochastic fluctuations from deterministic trends in solar irradiance. By considering clear-sky irradiance as a dynamic upper bound of measurement, provides a normalized, dimensionless measure of variability that theoretically ranges from 0 to 1. extends by integrating temporal dependencies via maximum autocorrelation, thus linking with . The proposed methodology is validated using synthetic cyclostationary time series and experimental data from 68 meteorological stations (in Spain). Our comparative analyses demonstrate that and proficiently encapsulate multi-scale fluctuations, while addressing significant limitations inherent in traditional metrics. This comprehensive framework enables a refined quantification of solar forecast uncertainty, supporting improved decision-making in flexibility procurement and operational strategies. By assessing variability and forecastability across multiple time scales, it enhances real-time monitoring capabilities and informs adaptive energy management approaches, such as dynamic outage management and risk-adjusted capacity allocatio
Coats of Arms in Urban Space. An Introduction to the Use of Heraldry in Medieval and Early Modern Cities and Towns in Italy and Europe
No full textInternational audienceThis article presents a thorough exploration and initial discussion of the widespread use ofcoats of arms in urban spaces during the medieval and early Renaissance periods in Italy and Europe.It starts with a detailed examination of the field’s research history, investigates the diverse monumentalapplications of heraldry in various urban locations and analyses the range of entities that utilizedcoats of arms for communication in these settings. The study places particular emphasis on theephemer al use of heraldic symbols, which enhances our understanding of this phenomenon beyondwhat we may glean from surviving sources, whether they are monumental or depicted in manuscripts.Additionally, the paper discusses the different practices employed when dealing with heraldic symbolsin urban settings, especially in cases of shifting allegiances. It contends that the convergence of diverseinterests and spheres of influence from multiple groups, individuals, and institutions makes the cityan exceptionally fertile place for the development and application of heraldic communication, anddiscusses whether Italy, particularly its northern cities characterized by distinct governance structures,nevertheless exhibits unique characteristics in this context that set it apart from the rest of Europe