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Multifractal comparison of three optical disdrometers and a mini vertically pointing Doppler radar, and consequences on rainfall extreme quantification in urban environment
No full textInternational audienc
Microplastics and tyre wear particles infiltration in the soil of a roadside biofiltration swale
No full textInternational audienceUrban roads stand as a major aspect of human activity. Understanding their contribution to microplastic pollution through the abrasion of macrolitter and the generation of tyre and road wear particles is crucial to better assess the sources and fate of microplastics in terrestrial environments. In particular, the microplastic infiltration into roadside soil and soils of sustainable urban drainage systems via urban runoff remains to be assessed.This study focuses on microplastic infiltration in the soil of a biofiltration swale alongside a high-traffic highway in the north of Paris, France. Ten soil cores were collected manually at a depth of 35 cm and were each subdivided by depth into four samples ([0-5[, [5–15[, [15–25[, [25–35[ cm). Each sample represented a mass of 10g, that was separated into 2 subsamples for separate quantification of microplastics and tyre wear particles.After specific treatment processes, the microplastic content of the samples was characterized and quantified using an automated micro-FTIR imaging analysis. The tyre wear particles content of the samples was indirectly assessed by quantifying the styrene-butadiene rubber (SBR) and butadiene rubber (BR) content of the samples by Pyr-GC/MS analysis. Results revealed a median concentration of 5.4 µg MP g-1, for a median abundance of 4MP/g. Surface samples presented a significantly higher microplastic abundance than deeper layers, with a median abundance of 47 MP g-1 against 1.8 MP g-1. SBR concentrations were significantly higher than microplastics for all samples, with a median concentration of 150 µg SBR g-1, suggesting a much higher tyre wear particles concentration in the roadside soils. Interestingly, SBR concentrations presented a similar vertical profile as microplastics, with a decrease in concentration in the deeper samples.These findings advocate for an increased attention to tyre wear particles in microplastic studies, particularly within urban contexts, as they likely represent high concentrations and follow similar transport pathways as other microplastics
UGV Charging Stations for UAV-Assisted AoI-Aware Data Collection
No full textInternational audienceMeeting the stringent requirements of real-time Internet of Things (IoT) is a bit challenging than expected. Indeed, IoT devices generate massive amounts of data through their sensing features and face some constraints in timely transmitting sensed data to collectors. To overcome this problem, Unmanned Aerial Vehicles (UAVs) are deployed to act as data collectors for IoT devices as they significantly improve the freshness of collected data in real-time applications. Nevertheless, IoT devices and UAVs have limited energy capacity. In this paper, we tackle the energy concern of IoT devices by utilizing UAVs as data collectors and energy transmitters and by promptly charging IoT devices whenever necessary. As for the energy concern of UAVs, we deploy a set of Unmanned Ground Vehicles (UGVs) to energy supply UAVs, allowing them to complete their tasks successfully. Our objective is to employ a multi-agent reinforcement learning method for optimally controlling the trajectories of both UGVs and UAVs so that it jointly decreases their energy consumption, reduces the Age of Information (AoI) of IoT devices, and timely charges UAVs and avoids their failures. We conducted a series of tests using a simulation tool to validate the effectiveness of the approach
MatAIRials: Inflatable Metamaterials for Freefrom Surface Design
No full textInflatable pads are used in multiple applications, e.g. as mattresses or protective equipment. In this work, we propose to treat these inflatables, made of two planar membranes sealed according to periodic patterns, typically parallel lines or dots, as metamaterials. By considering novel sealing patterns with 6-fold symmetry, we are able to generate a family of inflatable materials whose macroscale contraction is isotropic and can be modulated by controlling the parameters of the seals. We leverage this property of our inflatable materials family to propose a simple and effective algorithm based on conformal mapping that allows us to design the layout of inflatable structures that can be fabricated flat and whose inflated shapes approximate those of given target freeform surfaces
Les incitations fiscales à la recherche et développement et à l’innovation : état des lieux, effets et alternatives
No full textNous dressons un panorama des aides à la recherche et développement (R&D) et de leurs effets. On observe un peu partout dans le monde et en particulier en France un accroissement des aides indirectes, par rapport aux aides directes ces vingt dernières années. Pourtant, lesévaluations dénotent une efficacité variable des aides indirectes : si certaines ont un effet d’entrainement, notamment les aides ciblées sur les jeunes entreprises, d’autres semblent essentiellement générer un effet d’aubaine du fait d’un manque de ciblage. Les aides directesà la R&D sont une alternative aux incitations fiscales et ont été davantage mobilisées suite à la crise sanitaire. Ces aides apparaissent comme des compléments plutôt que des substituts aux aides indirectes, même si leur multiplication soulève la question de la complexité du paysage des aides à la R&D et de l’efficacité globale du soutien public à la R&D en France.Enfin le financement direct de la recherche publique semble être un levier efficace pour augmenter l’efficacité de la R&D privée, selon des études récentes, en raison des externalités positives qu’elle génère. Cela met en avant la nécessité d’un soutien diversifié afin de maximiser la R&D et l’innovation
Place-Based Policies: Opportunity for Deprived Schools or Zone-and-Shame Effect?
No full textInternational audienceEven though place-based policies involve large transfers toward low-income neighborhoods, they may also produce territorial stigmatization by spotlighting the targeted areas. This paper appeals to the quasi-experimental discontinuity in a French reform that redrew the zoning map of subsidized neighborhoods on the basis of a sharp poverty cut-off to assess the ``net" effect of place-based policies on school outcomes. Using a difference-in-differences approach, we find strong evidence of stigma effects from policy designation on public middle schools located in neighborhoods below the policy cut-off, which saw a significant decrease in their post-reform pupil enrollment compared to their counterfactual analogues in unlabeled areas lying just above the poverty threshold. This "zone-and-shame" effect is immediate, it persists up to five years after the reform, and it is triggered by the reactions of parents from all socioeconomic backgrounds, who avoided public schools in policy areas and shifted to those in other areas or, only for wealthy parents, to private schools. There is also evidence of a short-lived decrease in pupils' test-scores associated with this spatial resorting. We uncover, on the contrary, only weak evidence of stigma reversion after an area loses its designation, suggesting hysteresis in bad reputations conveyed by policy labeling
Sharp Propagation of Chaos for the Ensemble Langevin Sampler
No full textInternational audienceThe aim of this note is to revisit propagation of chaos for a Langevin-type interacting particle system used in the context of sampling. The interacting particle system we consider coincides, in the setting of a log-quadratic target distribution, with the ensemble Kalman sampler, for which propagation of chaos was first proved by Ding and Li. Like these authors, we prove propagation of chaos using a synchronous coupling as a starting point, as in Sznitman's classical argument. Instead of relying on a boostrapping argument, however, we use a technique based on stopping times in order to handle the lack of Lipschitz continuity of the coefficients in the dynamics. This approach originates from numerical analysis and was recently employed to prove mean field limits for consensus-based optimization and related interacting particle systems. In the context of ensemble Langevin sampling, it enables proving pathwise propagation of chaos with optimal rate, whereas previous results were optimal only up to a positive ε. It also allows relaxing the log-quadratic assumption on the target distribution
Multidimensional welfare indices and the IPCC 6th Assessment Report scenarios
No full textInternational audienc
Distinct Shortest Walk Enumeration for RPQs
No full text14 pagesInternational audienceWe consider the Distinct Shortest Walks problem. Given two vertices and of a graph database and a regular path query, enumerate all walks of minimal length from to that carry a label that conforms to the query. Usual theoretical solutions turn out to be inefficient when applied to graph models that are closer to real-life systems, in particular because edges may carry multiple labels. Indeed, known algorithms may repeat the same answer exponentially many times. We propose an efficient algorithm for multi-labelled graph databases. The preprocessing runs in and the delay between two consecutive outputs is in , where is a nondeterministic automaton representing the query and is the minimal length. The algorithm can handle -transitions in or queries given as regular expressions at no additional cost
Design and Evaluation of a Lightweight SDN Controller for Integrated Road and Rail Networks
No full textInternational audienceImplementing reliable communications is a major challenge for rail and road communications networks. Current V2X (Vehicle-To-Everything) technologies come up against major limitations. These include the existence of white zones and incomplete coverage by cellular networks (4G/5G). This implies the joint use of multiple access technologies at the level of each vehicle and a real-time and transparent transition between these radio access technologies. The definition of optimal handover mechanisms based on Artificial Intelligence (AI) tools is part of the answer to this problem. However, the definition of a high-performance network manager, guaranteeing low latencies, is also an important challenge. Therefore, this paper proposes a novel Software-Defined Network (SDN) controller designed to optimise dynamic handovers between wireless interfaces based on real-time network conditions. It also considers Machine Learning (ML) to determine performance parameter requirements. This approach improves the reliability, flexibility and adaptability of in-vehicle communication systems, helping to increase the efficiency of Cooperative Intelligent Transportation Systems