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DeConFCluster: Deep Convolutional Transform Learning based Multiview Clustering Fusion Framework
No full textInternational audienceMulti-view data clustering is essential for discovering patterns and exploiting information from different sources. In this context, we propose DeConFCluster, an unsupervised multi-view clustering fusion framework based on Deep Convolutional Transform Learning (CTL). Our approach has the advantage that it does not require an additional decoder network during the training phase. This makes our model less prone to overfitting in data-constrained scenarios, as opposed to several recent studies based on the encoder-decoder framework. Furthermore, our method incorporates a loss function inspired by K-Means, which enables it to learn more effective representations for the clustering task. Finally, we evaluate our framework on five standard multi-view clustering datasets, and show that it outperforms the state-of-the-art multi-view deep clustering techniques
Eosin Y derivatives for visible light-mediated free-radical polymerization: Applications in 3D-photoprinting and bacterial photodynamic inactivation
No full textInternational audienceThis study reports the design and the subsequent use of mono-allylated (EY-MA) and di-allylated (EY-DA) derivatives of eosin Y (EY) as highly efficient visible light-sensitive photosensitizers (PS) of bio-based H-donor molecules (cysteamine (Cys) or N-acetyl-L-cysteine (NAC)) and an electron donor (N-methyldiethanolamine, MDEA) for free-radical and thiol-acrylate polymerizations of a biobased monomer derived from soybean oil (SOA) upon exposure to visible light. High final acrylate conversions for SOA polymerization (up to 80 %) evidence the efficient photoinitiating properties of the eosin derivatives systems under irradiation with light emitting diodes (LEDs) centred at 405, 455 and 505 nm, and outperform those obtained with EY and other common photosensitizers such as camphorquinone or benzophenone. As described by fluorescence and phosphorescence analyses, laser flash photolysis (LFP) and electron paramagnetic resonance spin-trapping (EPR-ST) experiments, EY-MA and EY-DA can react via a proton/proton-coupled electron transfer reaction with Cys (or NAC) and MDEA respectively. The efficient singlet oxygen generation of the EY-MA-based materials upon exposure to visible light leads to excellent antibacterial properties, against both Gram-positive Staphylococcus aureus (S. aureus) and Gram-negative Escherichia coli (E. coli). A 3-log decrease of E. coli adhesion on the surface of the materials is observed and 100 % adhesion inhibition of S. aureus is also demonstrated. The co-polymerization of the eosin-derived PS with the polymer matrix ensures sustainable antibacterial properties against both bacteria strains upon visible light exposure as it prevents their leakage out of the polymer network. Finally, finely complex 3D structures are successfully obtained by a 3D-photoprinting technology with the investigated EY-MAbased formulation using LED@405 nm
Compte-rendu de l’ouvrage de Benjamin Ferron, Emilie Née et Claire Oger (dirs.), “Donner la parole aux « sans-voix » ? Construction sociale et mise en discours d’un problème public” (Rennes, Presses Universitaires de Rennes, 2022)
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Intergenerational equity and infinite-population ethics: A survey
No full textInternational audienceThis article surveys the recent literature on infinite-horizon intergenerational social welfare and infinite-population ethics, reviewing the negative and positive results about the existence or constructibility of social preference relations and social welfare functions for infinite populations. Impossibility results primarily refer to the tension between Pareto and Anonymity (or inequality aversion). Positive results include characterizations of core social preference relations with which any relation satisfying desirable properties must be compatible, as well as overtaking criteria, asymptotic criteria, averaging criteria, hyperreal criteria, and criteria that focus on the worst-off
Upscaling materials recycling to enhance sustainability and economic resilience
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Économie comportementale et psychologie clinique face aux défis contemporains. Entretien avec Pr Nicolas Jacquemet
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Les cycles de Titan avec un Modèle de Climat Global. Des observations de Cassini à l’exploration de Dragonfly
No full textTitan's atmosphere has one of the most complex chemistries in the Solar System. Its main compounds - nitrogen and methane - are dissociated at high altitudes, producing a complex set of molecules that generate a layer of photochemical haze enveloping Titan in its entirety. Titan also has a methane cycle similar to the hydrological cycle established on Earth (evaporation, condensation, precipitation). The haze, methane, and clouds are subject to coupled cycles, the mechanisms of which are not yet fully understood. The Cassini-Huygens mission (2004-2017) has revealed a complex climate system and varied surface structures on Titan. The instruments tracked the inversion of atmospheric circulation at the northern spring equinox and its effects on climate. In addition, Huygens' in situ survey measured a methane mixing ratio of 1.4% above the tropopause, increasing to over 5.5% at 5 km, and remaining constant down to the ground. A new NASA mission, Dragonfly, scheduled for 2028, will land a drone on Titan in 2034 to study the equatorial region in detail. This thesis is a continuation of previous research on Titan's climate and focuses on characterising the methane cycle in the troposphere, using a Global Climate Model (GCM) adapted to Titan. Methane controls Titan's climate through, amongst other things, radiative transfer and the formation of haze and clouds, and conditions the environment in the region where the Dragonfly mission's observations will take place. Understanding the methane cycle in the atmosphere (its sources, sinks and flows) is therefore fundamental to future research on Titan. The first part of this thesis focuses on the development of the Titan GCM, developed since the 1990s at the Laboratoire de Météorologie Dynamique, and renamed the Titan Planetary Climate Model (Titan PCM) during this thesis. A new microphysical cloud model adapted to Titan has been integrated. It takes into account phenomena such as the nucleation and condensation of chemical species present in Titan's atmosphere. In addition, interaction processes between the surface and the atmosphere have been added, making it possible to deal with exchanges between the different reservoirs. This enables to determine the fluxes of the different methane phases (solid, liquid, gas), which control the methane cycle in the troposphere, and to interpret the structures observed (distribution and composition of lakes, clouds and precipitation). This model is also capable of providing climate predictions for the season and region targeted by the Dragonfly mission. After the microphysical developments and the integration of processes linked to the methane cycle, the second part of this study exploits the model results to analyse the seasonal processes in Titan's atmosphere. The model can now predict the mapping of haze and clouds in Titan's atmosphere, as well as characterising these clouds in terms of opacity, drop size and composition. We are able to explain methane fluxes, its sources (surface evaporation) and sinks (precipitation), as well as net fluxes. This work has shown that Titan's troposphere is dominated by the complex interaction between methane, photochemical species, clouds, condensate mist and liquid reservoirs at the surface. In the stratosphere, the climate is mainly dominated by haze and by a strong feedback with atmospheric circulation. The organisation of climate cycles on Titan has also been studied. An analysis of seasonal processes, particularly at the poles, was also carried out, helping to explain the thermal structure of the atmosphere at the winter pole, initiating the formation of HCN clouds at very high altitudes (> 250 km).L'atmosphère de Titan possède l'une des chimies les plus complexes du système solaire. Ses principaux composés - l'azote et le méthane - sont dissociés à haute altitude, produisant un ensemble de molécules complexes qui génère une couche de brume photochimique enveloppant intégralement Titan. En outre, Titan possède un cycle du méthane similaire au cycle hydrologique établi sur Terre (évaporation, condensation, précipitations). La brume, le méthane, et les nuages sont soumis à des cycles couplés dont les mécanismes ne sont pas encore complètement compris. La mission Cassini-Huygens (2004-2017) a révélé un système climatique complexe et des structures de surface variées sur Titan. Les instruments ont suivi le basculement de la circulation atmosphérique à l'équinoxe et ses effets sur le climat. Aussi, les mesures in situ ont déterminé un rapport de mélange du méthane de 1,4 % au-dessus de la tropopause, augmentant jusqu'à 5,5 % à 5 km, et restant constant jusqu'au sol. Une nouvelle mission de la NASA, Dragonfly, prévue pour 2028, devrait poser un drone sur Titan en 2034 pour étudier en détail la région équatoriale. Cette thèse s'inscrit dans la continuité des recherches précédentes sur le climat de Titan et se concentre sur la caractérisation du cycle du méthane dans la troposphère, en utilisant un Modèle de Climat Global (GCM) adapté à Titan. Le méthane contrôle le climat de Titan, entre autres par le biais du transfert radiatif ou de la formation des brumes et des nuages, et conditionne l'environnement de la région où se dérouleront les observations de la mission Dragonfly. Il est donc fondamental pour les recherches futures sur Titan de comprendre le cycle du méthane dans l’atmosphère (sources, puits, et flux). La première partie de cette thèse se concentre sur le développement du GCM de Titan, développé depuis les années 1990 au Laboratoire de Météorologie Dynamique, et renommé Modèle de Climat Planétaire de Titan (PCM de Titan) au cours de cette thèse. Un nouveau modèle microphysique de nuages adapté à Titan y a été intégré. Il prend en compte les phénomènes de nucléation et de condensation des espèces chimiques présentes dans l'atmosphère de Titan. De plus, des processus d'interaction entre la surface et l'atmosphère ont été ajoutés, permettant de traiter les échanges entre les différents réservoirs. Cela permet de déterminer les flux des différentes phases du méthane (solide, liquide, gaz), qui contrôlent le cycle du méthane dans la troposphère, et d'interpréter les structures observées (distribution et composition des lacs, nuages et précipitations). Ce modèle est également capable de fournir des prédictions climatiques pour la saison et la région ciblées par la mission Dragonfly. Après les développements microphysiques et l'intégration des processus liés au cycle du méthane, la seconde partie de cette étude exploite les résultats du modèle pour analyser les processus saisonniers de l’atmosphère de Titan. Le modèle peut désormais prédire la cartographie des brumes et des nuages dans l’atmosphère, ainsi que caractériser ces nuages en termes d’opacité, de taille des gouttes et de composition. Nous sommes capables d’expliquer les flux de méthane, ses sources (évaporation à la surface), ses puits (précipitations), ainsi que les bilans nets. Ce travail a démontré que la troposphère de Titan est dominée par l'interaction complexe entre le méthane, les espèces photochimiques, les nuages, le brouillard de condensats, et les réservoirs liquides à la surface. Dans la stratosphère, le climat est principalement dominé par la brume et par une forte rétroaction avec la circulation atmosphérique. L’organisation des cycles climatiques sur Titan a également été étudiée. Une analyse des processus saisonniers, en particulier aux pôles, a également été effectuée, et a permis d’expliquer la structure thermique de l’atmosphère au pôle d’hiver, initiant la formation de nuages de HCN à très haute altitude (> 250 km)
Integrated Assessment Models and Input-Output Analysis : bridging fields for advancing sustainability scenarios research
No full textInternational audienceTechnology-rich Integrated assessment models (IAMs) and Environmentally-Extended Input-Output Analysis (EEIOA) are widely employed for sustainability analysis, each offering unique strengths. IAMs focus on forward-looking scenarios, exploring technological shifts and climate change mitigation costs. EEIOA provides more comprehensive but static assessments of environmental and socioeconomic impacts throughout supply chains, adopting a lifecycle perspective. I conduct a literature review to assess the current state of IAM-IO integration, paving the way for future research opportunities with advanced models. Existing studies have loosely linked IAM and IO models to improve one field or the other. This perspective highlights the potential for more advanced IAM-IO model linking and identifies three domains within sustainability scenarios research where IAM-IO integration could play a crucial role : the energy-industry nexus in decarbonization pathways, multi-dimensional sustainability impact assessment and demand-side solutions and post-growth climate mitigation scenarios. The expected research insights may be pivotal to design effective sustainable policies
COVID lockdown significantly impacted microplastic bulk atmospheric deposition rates
No full textInternational audienceHere, microplastic atmospheric deposition data collected at an urban site during the French national lockdown of spring 2020 is compared to deposition data from the same site in a period of normal activity. Bulk atmospheric deposition was collected on the vegetated roof of a suburban campus from the Greater Paris and analysed for microplastics using a micro-FTIR imaging methodology. Significantly lower deposition rates were measured overall during the lockdown period (median 5.4 MP m−2.d−1) than in a period of normal activity in spring 2021 (median of 29.2 MP m−2.d−1). This difference is however not observed for the smallest microplastic size class. The dominant polymers identified were PP, followed by PE and PS. Precipitation alone could not explain the differences between the two campaigns, and it is suggested that the temporary drop in human activity during lockdown is the primary cause of the reduced deposition rates. This study provides novel insight on the immediate impact of human activities on atmospheric microplastics, thus enhancing the global understanding on this topic
La convergence tarifaire
No full textLes tarifs du secteur privé représentent 45% à 50% des tarifs du secteur public après prise en compte des évolutions temporelles et des mouvements de convergence et divergence entre les secteurs. La différence sectorielle d’écart de tarif entre des soins médicaux et chirurgicaux, existe mais reste modérée. Pour la chirurgie ambulatoire, la tendance suit celle de la chirurgie dans son ensemble. Observe-t-on une convergence du rapport sectoriel des tarifs ? Les tarifs du secteur public et privé montrent des mouvements de divergence puis convergence sur la période 2009 à 2022. Par rapport à 2009, année de référence, l’écart des tarifs entre public et privé s’est accru de +2% en 2010 à 9% de 2018 à 2020 pour revenir à +8% en 2022. Une convergence sur ce rapport de tarifs entre secteur est à encourager car il s’appuie sur la partie de fonction de production qui est comparable entre secteur