Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : AWACA (Horizon 2020, appel 2020, Synergy grants)
Entité participante : École polytechnique — Pays : France — Rôle : PI
Acronyme de l'entité : X
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1195715.0 €

Climate models predict that precipitation will increase in Antarctica, which will moderate global sea-level rise. Meanwhile, the isotopic composition of snowfall records climate parameters which can be recovered in ice cores. However, there are still major gaps in our understanding of the atmospheric water cycle over Antarctica. For the first time, the AWACA project will provide a consistent and comprehensive combined observation and modeling framework to understand and predict the fate of atmospheric water all along the tropospheric column. Specifically adapted/designed instruments will be combined to form observation platforms deployed at 5 sites along a 1100 km coast-to-plateau transect aligned with the typical moisture-carrying air mass trajectories. The challenges of working in full autonomy in Antarctica, never addressed to such an extent before, will be tackled by collaborating with experts in polar technology and logistics. The resulting data set will make possible the study of the processes driving the water fluxes and composition to an unprecedented level, and the gained insights will be a strong basis to develop new physics parameterizations for regional and climate models. Once validated along the transect but also in other regions of Antarctica thanks to satellite observations and past campaigns, those models will enable us to decipher the past and future variability of the atmospheric water cycle over Antarctica.

Mots-clés : remote sensing,paleoclimatology,climate projection,cloud and precipitation observation and microphysics,water vapor,antarctica,surface flux,blowing snow
Projet ERC : AWACA (Horizon 2020, appel 2020, Synergy grants)
Entité participante : Commissariat à l’énergie atomique et aux énergies alternatives — Pays : France — Rôle : PI
Acronyme de l'entité : CEA
Type d'entité : Recherche
Financement ERC de l'entité : 2968617.5 €

Climate models predict that precipitation will increase in Antarctica, which will moderate global sea-level rise. Meanwhile, the isotopic composition of snowfall records climate parameters which can be recovered in ice cores. However, there are still major gaps in our understanding of the atmospheric water cycle over Antarctica. For the first time, the AWACA project will provide a consistent and comprehensive combined observation and modeling framework to understand and predict the fate of atmospheric water all along the tropospheric column. Specifically adapted/designed instruments will be combined to form observation platforms deployed at 5 sites along a 1100 km coast-to-plateau transect aligned with the typical moisture-carrying air mass trajectories. The challenges of working in full autonomy in Antarctica, never addressed to such an extent before, will be tackled by collaborating with experts in polar technology and logistics. The resulting data set will make possible the study of the processes driving the water fluxes and composition to an unprecedented level, and the gained insights will be a strong basis to develop new physics parameterizations for regional and climate models. Once validated along the transect but also in other regions of Antarctica thanks to satellite observations and past campaigns, those models will enable us to decipher the past and future variability of the atmospheric water cycle over Antarctica.

Mots-clés : remote sensing,paleoclimatology,climate projection,cloud and precipitation observation and microphysics,water vapor,antarctica,surface flux,blowing snow
Projet ERC : SCUBA CANCERS (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Universidade de Vigo — Pays : Espagne — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 503036.2 €

Clonally transmissible cancers are somatic cell lineages that are transmitted between individuals via the transfer of living cancer cells. There are only three known types of naturally occurring clonally transmissible cancers, one of which is a leukemia-like cancer found in marine bivalves, called hemic neoplasia (HN). HN in cockles Cerastoderma edule offers an unique opportunity, over the other naturally occurring transmissible cancers, for the discovery of the genetic drivers of cancer transmissibility because: (1) cockle HN has a polyphyletic origin, which allows the identification of recurrently mutated genes among different unrelated cockle HN lineages; (2) HN provides a reliable in vitro and in vivo model that could be used for driver gene discovery and validation by means of genetic engineering methods; (3) cockle HN represents a nearly endless source of biological resources for study and experimentation on the origins and development of natural clonally transmissible cancers, due to the ubiquity of cockles throughout the Western Atlantic coast of Europe and the high prevalence of HN (>20%). Using HN in cockles as a model for clonally transmissible cancers, this project intends to identify the genomic alterations and mutational processes that drive transmissible cancers to depart from their hosts and evolve as parasitic clonal lineages in the marine environment, for illuminating universal processes that make a cancer contagious, and to identify new/unexpected biological insights into the general mechanisms of cancer metastasis. We will first characterize the clonal structure of cockle transmissible cancers by phylogenetic approaches. Then, we will use NGS analysis to catalogue the somatic alterations that characterize different HN clonal lineages, figure out the mutational processes that operate in marine transmissible cancers, and identify the putative cancer genes that drive cancer transmissibility, which will be finally validated by genome editing approach

Mots-clés : cancer genomics,next generation sequencing
Projet ERC : CLOUDLAB (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 3499926.0 €

Clouds have been seeded since the 1940s. Aimed at inducing weather modification, the method uses chemicals to alter the microphysical processes within a cloud to enhance precipitation, suppress hail, or dissipate fog. While the concept of cloud seeding is not new, detailed knowledge about the underlying microphysical processes in clouds is still sparse. CLOUDLAB will tackle this gap by injecting different ice nucleating particle concentrations into supercooled stratus clouds to investigate related microphysical changes, including fundamental aspects of ice formation and growth. To achieve this, the project combines a multi-dimensional approach of targeted cloud seeding with a focus on wintertime stratus clouds in Switzerland, the least dynamic cloud type which best mimics laboratory conditions and allows repetition of field experiments under similar initial conditions. We will inject ice nucleating particles from a seeding drone and perform measurements with ground-based remote sensing, a tethered balloon system equipped with a holographic imager and a measurement drone. Combined with measured meteorological parameters, we aim to understand the impact of cloud inhomogeneities for precipitation initiation via the ice phase. The analysis of our cloud seeding events will be used to validate and improve cloud microphysics schemes in the Swiss weather forecast model in large eddy simulations mode. By coarsening the horizontal resolution to weather forecast mode, the simulations will be extended to include all cloud types where the same microphysical processes are at work to improve precipitation forecast skills in Switzerland. Hence, CLOUDLAB will further the understanding of ice microphysics and precipitation initiation which will also improve climate projections. In addition to pioneering of a new methodology of using drones for cloud seeding, our results will be of particular interest to the weather modification and climate intervention communities.

Mots-clés : ice formation,cloud seeding,cloud microphysics,mixed phase clouds,holographic imager,remote sensing,large eddy simulations,airborne field measurements,ice nucleating particles,tethered balloon,weather forecast
Projet ERC : CloudCT (Horizon 2020, appel 2018, Synergy grants)
Entité participante : Weizmann Institute of Science — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2233394.0 €

Clouds play a lead climatic role, controlling energy fluxes and regulating fresh water distribution. There is an acute need for cloud-resolving and global-climate models that accurately describe and parametrize the physics of warm convective and stratiform clouds, and the clouds’ sensitivity to environmental changes. Currently this requirement is not being met due to a gap in observational capabilities. Namely, there is a lack of sufficient sensing tailored to capture the 3D macro and microphysical properties of warm clouds, which are often spatially unresolved. Moreover, current retrievals use a plane-parallel radiative model, which is incompatible with the 3D heterogeneous nature of clouds. These gaps lead to uncertainties in climate models and prediction. We propose an innovative sensing approach: cloud scattering-tomography, relying on an unprecedented large formation of ten cooperating, high performance pico-satellites. They will simultaneously image cloud fields from multiple directions, at 50m resolution. Based on this data, the novel tomography approach will seek the 3D volumetric structure of cloud fields, base-to-top profiles of droplets' size and their variance, volumetric distribution of optical extinction and rain indicators. The required pointing accuracy, data size and coordinated control of a complex 10 pico-satellite formation demands advanced space engineering, beyond existing technologies of traditional single satellites and constellations of satellites. Realizing a large formation requires innovative, distributed, networked, cooperative control, including advanced sensors and actuators for pico-satellites, as well as in-orbit autonomy. On-board hardware and flexible software will be adapted to meet computational needs within the physical limitations of pico-satellites (energy, mass, volume). Using the acquired spaceborne images for tomography-based 3D atmospheric retrievals requires advancements in computer vision and efficient analysis based on three-dimensional radiative transfer. New information gained will improve and validate our cloud resolving models, leading to more realistic simulations of cloud fields. This will enable better understanding of how environmental changes affect warm clouds and help improve their representation in climate models. This multidisciplinary, synergic approach will establish and test critical and currently unconventional aspects of remote sensing and mathematical retrieval based on a pico-satellite formation. It will yield a database of 3D macro and micro structure of warm cloud fields, while setting the stage for next-generation distributed spaceborne global observations.

Mots-clés : satellite formations,distributed satellite systems,networked control,adaptive control,pico satellites,navigation sensors
Projet ERC : moreRNA (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : University of Regensburg — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1998316.0 €

Coding and non-coding RNAs are regulated at numerous levels. For example, microRNA (miRNA) expression can be influenced at various steps of biosynthesis. Furthermore, it has been reported that direct RNA methylation events can also affect gene expression in many different organisms and systems. The aim of this project is to identify and characterize factors that affect the maturation of miRNAs. We will employ biochemical pull down assays to isolate specific binding partners of different miRNA species. We will analyze the physiological role of these factors using molecular or cell biological approaches. Molecular details of pre-miRNA-protein interactions will be investigated by x-ray crystallography. In addition, we will decipher the role of the m6A methylation pathway on the regulation of coding and non-coding RNAs. Writers, readers and erasers of this modification have been identified. However, not much is known about the composition of specific protein complexes as well as the atomic structure of these factors. Thus, we will functionally and structurally characterize known and putative novel factors of the m6A methylation pathway in human cells. Furthermore, using our biochemical pull down approach employed for the identification of pre-miRNA processing factors, we will identify reader proteins of several types of RNA modification that have not been investigated so far. The proposed project will elucidate the regulation of gene expression by small RNAs or direct RNA methylation and will add so far unknown components to these important regulatory pathways.
Projet ERC : Set-to-change (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : Oslo University Hospital — Pays : Norvège — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 76000.0 €

Cognitive function in old age can be predicted from how you functioned when you were young. This is remarkable, as there are substantial cognitive age changes. Are we neurodevelopmentally set to change through life in certain ways? The objective of Set-to-change is to test whether and how early life environmental factors and genetic makeup interact to regulate neurocognitive plasticity through the lifespan. Neurocognitive plasticity; i.e. changes in brain and cognition in response to environmental demands over time, shows huge individual variability, for unknown reasons. Neurodevelopmental origins of functional variation through the lifespan are acknowledged, but the pathways need to be identified. As individual constitution and environment are intrinsically correlated, to make progress beyond state of the art, this can only be tested in an experimental setting. The novelty and ground-breaking nature of the project lies in the synthesis of a targeted experimental approach testing differences in neurocognitive plasticity by training of younger and older adult mono- (MZ) and dizygotic twins (total n = 400 individuals), with varying degrees of prenatal environmental variance, as indexed by their extent of discordance in birth weight (BW). BW discordance in MZ twins enables me to disentangle early environmental and genetic influences on neurocognitive plasticity. I will employ a novel ecologically valid memory intervention utilizing navigation with true locomotion and prospective memory in virtual reality. Twins will be assessed with brain MRI, cognitive, health and epigenetic measures at multiple time points spread across 2.5 years pre- and post- 3 months intervention in a AB/BA crossover design, to investigate neurocognitive plasticity and age change longitudinally, as well as possible lifestyle and epigenetic mediators. I hypothesize that early life environmental influences will interact with genetic makeup in determining neurocognitive plasticity in adulthood.

Mots-clés : lifespan,neuroimaging,plasticity
Projet ERC : UNIFY (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Human Mind and Its Complexity
Entité participante : University of Amsterdam — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : UvA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2493318.0 €

Cognitive models formalize substantive theory about how people reason, learn, decide, and act. Cognitive models also serve as measurement tools that explain observed behavior in terms of constituent psychological processes. Because of their unique ability to estimate latent processes, cognitive models are increasingly applied throughout cognitive neuroscience and clinical psychology. Despite their theoretical appeal and growing popularity, however, the field of cognitive modeling presents an often bewildering proliferation of ideas and techniques. Current applications appear idiosyncratic, and the state-of-the-art remains unclear. This lack of systematicity makes it difficult for researchers and practitioners to develop, understand, and apply important cognitive models. This proposal outlines a unified program for the assessment and application of cognitive models. Based on the foundations of Bayesian inference, a Quantitative Development Team develops new generic methods to assess absolute and relative goodness-of-fit, explores efficient algorithms to estimate model parameters, and examines how the models can be applied to data from popular experimental designs. A Core Application Team focuses on three classes of cognitive models of particular impact: the drift decision models, the stop-signal race models, and the reinforcement learning models. These model classes are enriched by the construction of plausible parameter priors, the development of diagnostic experiments, the assessment of Bayes factors for hierarchical designs, and the model-averaged assessment of changes in parameters. The proposed work aims to set a new standard for cognitive modeling. Practical relevance is enhanced by incorporating the techniques in JASP, a user-friendly statistical software package developed in my lab (jasp-stats.org). By adding the new techniques to JASP, the cognitive models and associated new methodology become available for students, researchers, and practitioners.

Mots-clés : bayesian inference,drift decision model,stop signal race models,reinforcement learning models
Projet ERC : NANOINFER (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 1499609.0 €

Cognitive tasks are increasingly necessary in modern electronics. The energy efficiency of associated algorithms, which rely on abundant stored parameters, is severely limited by the separation of computation and memory elements in conventional computers. In NANOINFER, I will directly address this challenge by developing intelligent memory chips that natively perform both memory and computing functions, using CMOS and emerging nanodevices. These chips will perform modern Bayesian inference algorithms, which allow cognitive-type reasoning. The project includes theoretical investigations as well as intelligent memory chip designs, which will be supported by proof-of-concept experimental demonstrations. The proposed architectures, based on spintronic and memristive memories, will maximize energy efficiency by leveraging the complex physics of these emerging devices for inference operations and the storage of model parameters, and by minimizing exchanges between computation units and memory. Inference will be performed using sampling algorithms that allow tackling difficult problems and are robust to nanodevice imperfections. The inference circuits will be composed of digital CMOS logic as well as spiking neurons circuits. Two standard Bayesian approaches will be employed to enable learning, permitting highly adaptive systems. Preliminary results on a system that performs naïve Bayesian inference have validated this concept and its use with novel memory technologies. NANOINFER will resolve critical interdisciplinary challenges to permit intelligent memories to perform non-naïve tasks, ensuring a correspondence between device physics and Bayesian concepts while maintaining a fusion between computation and memory. This project will deepen our understanding of novel memory technologies and develop a toolbox for creating intelligent memory chips. These will allow smart devices to perform cognitive/sensory-motor tasks at low energy without requiring large computing machines.

Mots-clés : emerging memories,memristors,nanoelectronics,intelligent memory,bayesian inference
Projet ERC : CLLS (Horizon 2020, appel 2016, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Tilburg University — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : TiU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1495625.0 €

Coherence of law is created in the writings of legal scholars who systematize rules and principles of law. Their pursuit of coherence is vital for the effectiveness of legal systems. However, coherence of law has almost not been analysed in a systematic, empirical way. The project will therefore develop a methodology that will address coherence across forms (‘sources’) of law (legislation, legal scholarship, case law, customs), across themes (e.g. criminal law and contracts) and across authors, and which will additionally encompass interaction with societal demand and contextual factors. The methodology will be ground-breaking because it will disentangle the concept of coherence into measurable modes of interconnectedness, weighing them together so as to assess (in)coherence at the level of the legal system. This methodology will constitute a stepping stone for a new field of dynamic coherence of law created through legal scholarship that will ultimately improve the quality of law. It will be founded on academic writings on law from the early modern period (ca. 1500 - ca. 1800) that concern the theme of collateral rights, that is, those rights facilitating expropriation of the assets of debtors in case of their default. Indications are that the impact of rules on collateral rights hinged on coherence as established in legal writings, and that in the period mentioned legal coherence for this theme was increasing. Coherence in development will be traced in the interpretations of legal scholars following on from interactions between scholarly writings, local law (bylaws, judgments) and commercial practice (contracts). Connections of rules and principles found will be presented in frames of analysis that cluster them along variables of context, time and source of law. The combination of legal analysis with a broad scope of coherence (cross-source, context-driven) will build bridges across gaps now existing between the different disciplines that study law.

Mots-clés : legal scholarship,coherence of law,legal complexity,legal history,commercial law,codifications