Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : sRNA-EMB (Horizon 2020, appel 2014, Starting grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Gregor Mendel Institute of Molecular Plant Biology — Pays : Autriche — Rôle : PI
Acronyme de l'entité : GMI
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 1499988.99 €

Small RNAs are short non-coding RNAs that regulate gene expression in plants and animals. Although small RNAs are essential for proper differentiation and epigenome regulation, little is known regarding their embryonic functions, especially in plants. Arabidopsis thaliana is a leading system to study the regulatory roles of small RNAs because of the abundance of genetic, genomic and epigenomic resources. Moreover, Arabidopsis embryos undergo invariant division patterns and rapidly differentiate to generate the most basic plant cell-types arranged in correct positions. Early Arabidopsis embryos are therefore morphologically simple structures composed of diverse cell types making them ideal for determining the influence of small RNAs on fundamental cellular differentiation and reprogramming events. The objectives of the proposed research are designed to assess the regulatory roles of small RNAs in establishing both the basic body plan and epigenome in plant embryos. We will utilize modified next-generation sequencing technologies to identify small RNAs present in developing embryos. Because we will generate these RNA profiles from a mixture of cell-types, we will also use a fluorescent protein-based approach to quantify specific miRNA repressive activities in individual cell-types. To determine the functions of individual miRNA/target interactions during embryogenesis, we will identify miRNAs required for embryo development and use genome-wide approaches to study specific miRNA/target interactions in greater detail. Lastly, we will use a fusion of genetic and genomic methods to determine how small RNAs influence the nascent epigenome during early embryogenesis.

Mots-clés : small rnas,micrornas,developmental biology,transcription factors,plant biology
Projet ERC : Oligomers (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : University of Cambridge — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : U. Cambridge
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499551.0 €

Small soluble protein aggregates play a key role in the onset and spreading of Alzheimer’s and Parkinson’s diseases. However, which oligomers are present in human disease and which are toxic remains unknown because ultrasensitive methods do not exist to detect and characterise the low concentration of oligomers, which are highly heterogeneous in size and structure. To address this problem we will develop fluorescence based methods to detect and characterise individual oligomers to measure the oligomer size, structure, proteinase K resistance, seeding capability and composition. We will also develop methods to enrich these oligomers so we can use mass spectrometry to determine post translational modifications and recover the oligomers to directly test their cytotoxicity and mechanism of damage. The capability to characterise these oligomers at this unprecedented level of detail will represent a major advance in the field. These methods will then be applied to stem cell models of Alzheimer’s disease and Parkinson’s disease and then clinical samples of CSF from patients. These experiments will determine how the number, composition or structure of the oligomers changes in the disease and if this results in increased cytotoxicity. Clinical samples of CSF from patients with genetic mutations will be used to determine if detectable changes in the oligomers occur early in the disease and samples of brain tissue used to determine the changes in oligomers during the spreading of the disease. By the end of the project we will have determined which oligomers play major roles in the onset and spreading of Alzheimer’s and Parkinson’s disease in humans, providing targets for therapies, and tested if the detection and characterisation of these oligomers can be used for early diagnosis of the disease.

Mots-clés : single molecule fluorescence
Projet ERC : HAZE (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : Imperial College London — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1958900.0 €

Smouldering megafires are the largest and longest-burning fires on Earth. They destroy essential peatland ecosystems, and are responsible for 15% of annual global greenhouse gas emissions. This is the same amount attributed to the whole of the European Union, and yet it is not accounted for in global carbon budgets. Peat fires also induce surges of respiratory emergencies in the population and disrupt shipping and aviation routes for long periods, weeks even months. The ambition of HAZE is to advance the science and create the technology that will reduce the burden of smouldering fires. Despite their importance, we do not understand how smouldering fires ignite, spread or extinguish, which impedes the development of any successful mitigation strategy. Megafires are routinely fought across the globe with techniques that were developed for flaming fires, and are thus ineffective for smouldering. Moreover, the burning of deep peat affects older soil carbon that has not been part of the active carbon cycle for centuries to millennia, and thus creates a positive feedback to the climate system. HAZE wants to turn the challenges faced by smouldering research into opportunities and has the following three novel aims: 1) To conduct controlled laboratory experiments and discover how peat fires ignite, spread and extinguish. 2) To develop multidimensional computational models for the field scale (~1 km) and simulate the real phenomena. 3) To create pathways for novel mitigation technologies in accurate prevention, quick detection systems, and simulation-driven suppression strategies. With my proposal, Europe has the chance to lead the way and pioneer technologies against this Earth-scale and important but unconventional source of emissions. I am confident that with the support of ERC, I can deliver the science and excellence needed to tackle this global challenge, and in doing so, I will advance the knowledge frontier, foster innovation and develop new young talent for Europe

Mots-clés : heat transfer,combustion,fire,carbon emissions,peat
Projet ERC : IVORI (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Météo-France — Pays : France — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 1799252.0 €

Snow is a pillar of the Earth’s climate system, affecting all its components with critical impacts for Nature and human societies. Perennial snow evolves to firn and ice, providing unique records of the past climate. Yet today no snow model adequately simulates relevant snow variables worldwide, not to mention their inability to represent firn processes and snow/permafrost interactions. I argue that this is because current models focus on a limited number of physical processes and none suitably consider snow microstructure. IVORI’s goal is to build a microstructure-based model encompassing all the relevant snow and firn physical variables. Drawing on advanced observations of snow and firn, the proposal has three objectives: (1) Understand the role of water vapour transport in snow and its subsequent impacts on the ground thermal regime governing permafrost evolution; (2) Understand how initial changes in surface snow microstructure are transferred deeper into the firn and affect ice core records; (3) Determine the contributions of snow-climate feedbacks, triggered by changes in the albedo and insulating capacity of snow to the past and future of snow cover and ground temperature. To this aim, I will build a microstructure-based model, with a novel physics core, unifying the evolution of snow and firn. IVORI will also deliver unprecedented season-long observations of snow microstructure in the Arctic, Alps and Antarctica using X-ray tomography. These observations will significantly advance our understanding of the physical processes involved and be used for a thorough evaluation of the model. The model will provide a reliable assessment of snow-climate feedbacks in a changing climate and a rigorous appraisal of the modelling uncertainties. When completed, this work will pave the way for crucial advances in our understanding of glaciers, ice sheets and past climate through ice core records, with many fallouts for sea ice and permafrost evolution.

Mots-clés : tomography
Projet ERC : HeteroPlates (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Synthetic Chemistry and Materials
Entité participante : Technion – Israel Institute of Technology — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1872500.0 €

Soaring demand for energy calls for out of the box thinking in research and design of materials to enable technology far beyond today’s standards. What would be the perfect material for light mater interaction? What if we could utilize natural processes and assemble such a material, monolayer by monolayer with exquisite control over the resulting electronic structure. HeteroPlates will address these challenges using halide perovskite two dimensional nanoplates as building blocks and test beds for these ideas. Metal halide perovskite are exciting the scientific community with high conversion efficiency and ease of device processability. But this is a double edge sword since it deems long term device stability an ongoing challenge, especially where perovskites interface other materials and create heterostructures. Perovskite heterostructures play a crucial role, they influence electronic structure and affect device functionality, efficiency and most importantly stability. It is therefore critical to understand hetero-epitaxial growth and develop methods to create perovskite heterostructures and interfaces in a controlled fashion and characterize them at these length scales. My research program HeteroPlates will employ a bottom-up approach, taking advantage of the natural stability of colloidal 2D nanoplates, their atomically flat surfaces and tendency to self-organize. By means of colloidal synthesis, perovskite will grow, be grown and self -assembled into uniform monolayer controlled heterostructures. Using specially developed characterization methods we will achieve ground breaking control over imaging resolution of heterostructures. These methods will be employed to create Proof-of-concept devices with new functionalities, aiming for translation of knowledge and methodologies garnered from colloidal heterostructures to higher hierarchy devices, serving future generations.

Mots-clés : 2d colloidal nano plates,halide perovskites,heterostructure,monolayer control
Projet ERC : EVILTONGUE (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : Linköping University — Pays : Suède — Rôle : PI
Acronyme de l'entité : LiU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1195919.61 €

Social norms in general, and norms of cooperation in particular, are the cement of all human societies. For the difficult problems of the maintenance and enforcement of social norms and of cooperation, humans have developed surprisingly complex solutions. Reputation mechanisms and gossip are certainly among the compound informal solutions. According to common wisdom, gossip channels mainly negative and often fictitious information. If it is so, how can dishonest gossip and the resulting biased reputations legitimize social order and promote cooperation? This is the main puzzle we tackle in the proposed project exploiting a wide scale of instruments. We use analytical modeling and agent-based simulation to derive hypotheses. We test simple hypotheses in small group experiments. We develop new methodological tools to appropriately analyze the triadic nature of gossip embedded in network flows of information. We utilize dynamic network datasets from primary and secondary school classes, and we gather qualitative and quantitative information from organizations to test conditional hypotheses about the role that gossip plays in reputation and cooperation in different developmental and social contexts of life. In addition, we apply new communication technologies currently under development to explore the hidden world of gossip and the dynamics of reputations in dormitories and organizations. With the insights gained, we can overcome common stereotypes about gossip and highlight how gossip is related to credible reputational signals, cooperation, and social order. Expected results will help us to outline the conditions that can promote cooperativeness in work groups, and they will help to construct successful prevention strategies of social exclusion and other potentially harmful consequences of the evil tongue.

Mots-clés : evolution of cooperation,reputation,gossip,social networks,signaling,honesty,agent based models,experiments,schools,organisations
Projet ERC : RELEVANCE (Horizon 2020, appel 2019, Synergy grants)
Entité participante : University of Tübingen — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2724968.0 €

Social species, and specifically human and nonhuman primates, rely heavily on conspecifics for survival. Considerable time is spent watching each other’s behavior because this is often the most relevant source of information for preparing adaptive social responses. The project RELEVANCE aims to understand how the brain evolved special structures to process highly relevant social stimuli like bodies and to reveal how social vision sustains adaptive behaviour. This requires a novel way of thinking about biological information processing, currently among the brains’ most distinctive and least understood characteristic that accounts for the biggest difference between brains and computers. The project will develop a mechanistic and computational understanding of the visual processing of bodies and interactions and show how this processing sustains higher abilities such as understanding intention, action and emotion. Relevance will accomplish this by integrating advanced methods from multiple disciplines: psychophysics and high-field functional imaging in combination with virtual reality and neural stimulation in humans; electrophysiology with optogenetics and laminar recordings in monkeys. Crosstalk between human and monkey methods will establish homologies between the species, revealing cornerstones of the theory. In a radical departure from current practice, we will develop novel deep neural network models that unify the data. These models will not only capture detailed mechanisms of neural processing of complex social stimuli and its dynamics, but also reproduce the modulation of brain activity during active behavior. RELEVANCE will reveal novel ways of understanding and diagnosing social communication deficits in neuropsychiatry, and suggest novel hypotheses about their genetic basis. It will motivate novel principles and architectures for processing of socially relevant information in computer and robotic systems.

Mots-clés : social vision,body representation,high level vision,neural modeling
Projet ERC : SAHR (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
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 : 2492036.0 €

Society is rapidly opening its doors to robots in our daily life with autonomous vehicles, rehabilitation devices and autonomous appliances. These robots will face unexpected changes in their environment, to which they will have to react immediately and appropriately. Even though robots exceed largely humans’ precision and speed of computation, they are far from matching humans’ capacity to adapt rapidly to unexpected changes. In the past decades, robotics has made leaps forward in the design of increasingly complex robotic platforms to meet these challenges. In this endeavour, it has benefited from advances in optimization for solving high-dimensional constrained problems and in machine learning (ML) to analyse vast amounts of data. These methods are powerful for planning in slow-paced tasks and when the environment is known. This project addresses a growing need for methods that show fast and on-line reactivity. We design controllers that can plan at run time and adapt to new environmental constraints. We offer a novel approach to robot learning that follows stages of skill acquisition in humans. To inform modelling, we conduct a longitudinal study of the acquisition of dexterous bimanual skills in craftsmanship. We study how humans exploit task uncertainty to overcome their sensory-motor noise, and how humans learn bimanual synergies to reduce the control variables. This study informs the design of novel learning strategies for robots that exploit failures as much as successes. We combine planning and ML to learn feasible control laws, retrievable at run time with no need for further optimization. We exploit properties of dynamical systems (DS), which have received little attention in robot control, and use ML to identify characteristics of DS, in ways that were not explored to date. The approach is assessed in live demonstrations of coordinated adaptation of a multi-arm/hand robotic system engaged in a fast-paced industrial task, in the presence of humans.

Mots-clés : robot learning,bimanual coordination
Projet ERC : HEY BABY (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The Social World and Its Diversity
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1999960.0 €

Society’s greatest problems are our most compelling social science challenges. This project will develop the first known theoretical framework of resilience for adolescent parents and their children in Africa. In doing so, we will achieve three major advances in prevention science: We will synthesise quasi-experimental, data pooling and qualitative methods to identify protective pathways. We will create the global South’s first multi-country study of parenting support. And we will combine pioneering research with embedded stakeholder engagement, thus directly impacting international policy. Globally, adolescent parenthood is a marker of intergenerational disadvantage. Africa has 11.4 million adolescent mothers and fathers, often arising from adversities such as abuse, poverty, HIV and orphanhood. In turn, their children are at risk for non-optimum development and poor health. Existing research has focused on pregnancy prevention, with little success. Whilst these efforts are important, no known studies investigate predictors of resilience for adolescent-parent families in African contexts. This marks a major evidence gap, and a compelling need. We will use three linked methodologies. First, we will build a longitudinal study of 450 parent-child dyads living in severe adversity in South Africa. Through this, we can examine protective socio-economic, education and healthcare pathways. Second, we will create a six-country pooled dataset of parenting program studies, and test effectiveness across 8,000 participants regionally. Third, we will integrate citizen social science: participatory research with young families in adversity. A final policy-inclusive synthesis stage will ensure impact and benefit-sharing. This is an ambitious research agenda, with theoretical and methodological innovation. It requires the elucidation of complex behaviours in precarious environments. It presents risks, but with the potential for groundbreaking scientific and societal impact.

Mots-clés : youth,parenting,children,families,adversity,aids,abuse,poverty,resilience,protective pathways,prevention science,evidence based policies,africa
Projet ERC : MAGIC (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : University of Trento — Pays : Italie — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Soft magnetoactive materials can change their properties and undergo extremely large deformations when excited by magnetic stimuli. These reconfigurable soft materials hold great potential for a large variety of applications from sensing devices to energy harvesting, noise and vibration mitigation, and soft robotics. However, these materials operate at high magnetic fields, thus, limiting potential application of the technology. A promising approach to significantly enhance the magnetomechanical performance, and reduce the required magnetic field, is to design soft magnetoactive composites through architectured microstructures. Highly ordered microstructures are an origin for multiscale magnetomechanical instabilities and possible failure of the materials. In this research proposal, we directly address this crucial aspect for MAE-based technology. Moreover, we declare an ambitious goal: Turning failure into functionalities. Our strategy is to take the risk of operating MAEs in the unstable regime with predesigned instability developments. This novel MAE design concept will capitalize on controllable cascade microstructure transformations while attempting to avoid catastrophic failure. If successful, this concept will open a new avenue in design of morphing magnetoactive materials with new functionalities and superior performance. To achieve this ambitious goal, we will develop multiscale theoretical and computational frameworks to reveal and to predict the behavior of possible advantageous microstructures in the extreme regimes. If successful, we will fill the gap in magnetomechanical multiscale instability phenomena, and will significantly advance the frontier of knowledge about the reconfigurable soft matter. We will probe our ideas experimentally, and will fabricate the revealed advantageous materials with engineered microstructures and properties. We envision revealing the fundamental multiphysics mechanisms of the multiscale magnetomechanical instabilities.

Mots-clés : soft materials,instabilities,magnetoactive materials,microstructures,3d printing