Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : ImmunityByPairDesign (Horizon 2020, appel 2014, Advanced grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : UK Research and Innovation — Pays : Royaume-Uni — Rôle : Partner
Acronyme de l'entité : UKRI
Type d'entité : Recherche
Financement ERC de l'entité : 527329.0 €

This project will (1) reveal design principles of paired immune receptor complexes and (2) elevate plant disease resistance by enabling design of immune receptors with new recognition capacities. Plant immunity is triggered upon pathogen detection by dedicated immune receptors. Like animal Nod-like receptors (NLRs), plant immune receptors have a modular structure and can work in pairs, both of which are required for defence activation upon recognition of specific pathogen proteins. How such intracellular immune receptor complexes activate defence solely upon recognition of microbial molecules is poorly understood. Using novel high risk/high gain methods such as domain/domain cross-linking with mass spectrometry (XL-MS) and cryo-electron microscopy, as well as X-ray crystallography, genetics and cell biology, we will define at a structural level the domain/domain interactions within an immune receptor complex, and how these change upon pathogen perception. The Arabidopsis RPS4/RRS1 immune receptor acts in the cell nucleus to detect when pathogen effectors target WRKY transcription factors, converting effector interactions with the RRS1 WRKY domain into defence activation via RPS4. We will reveal the intra-molecular reconfigurations required for signalling and thus tackle a problem of broad significance, both for immune receptors, and for other intracellular receptors that are activated by ligand-dependent release from negative regulation. We will also create and test derivatives of RPS4/RRS1 or related complexes that are designed to respond to effectors that target other host protein domains. As Richard Feynman said, “What I cannot create, I do not understand”. By designing immune receptors to recognize other pathogen effectors, we will test models of how plant immune receptors activate defence, but only upon effector recognition. This second objective is ambitious and high risk/high gain, but potentially game-changing for crop disease control.

Mots-clés : plant disease resistance,immune receptors,receptor biology,pathogens,pathogen effectors
Projet ERC : GLAD (Horizon 2020, appel 2019, Starting 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 : 1493343.0 €

This project will address fundamental gaps in our understanding of how clouds form, how they interact with the atmospheric flow and how they need to be simulated in weather and climate models. Our inability to improve the representation of clouds and their interactions with the atmospheric flow is the leading cause of the high level of uncertainty associated with projections of future changes in storm tracks, precipitation bands and weather extremes. The representation of clouds in models is poor, largely because clouds are unresolved. Given the potentially significant impacts of projected global warming and the significant benefits of improved weather predictions, it is imperative to improve the representation of cloud-circulation interactions in models. However, how do we acquire the necessary process understanding to close existing knowledge gaps? I propose a fundamentally new perspective on clouds and their control of the large-scale flow leading ultimately to a unique cloud classification system. Instead of studying clouds based on the traditional Eulerian perspective, I suggest analysing cloud-circulation couplings based on the history of air parcels (Lagrangian perspective). A systematic Lagrangian-based investigation of cloud-circulation couplings in ultra-high-resolution simulations is a true novelty and has never been attempted. Based on convection-permitting simulations over a climatological period, which exploit recent advances in supercomputing architectures, the cloud parcels are classified according to their circulation impact and feed into a machine learning algorithm that is trained using the physical processes acting along their pathways. This approach has the potential to drastically improve our mechanistic understanding of how to represent clouds in models and to identify the leading cloud-related processes that control regional to large-scale flow variability, which is one of the Grand Challenges defined by the World Climate Research Programme.

Mots-clés : diabatic processes,storm tracks,jet stream,clouds,lagrangian perspective,potential vorticity
Projet ERC : SILVER (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Oulu — Pays : Finlande — Rôle : Partner
Acronyme de l'entité : U. Oulu
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 269824.25 €

This project will address one of the enduring questions of medieval studies - the origins of the Viking Age (c. 750-1050 AD) - through an interdisciplinary (archaeological, archaeometric and numismatic) study of silver from early Viking-Age Scandinavia. In doing so, it will provide the first large-scale, systematic and empirically-based answers to the outstanding questions of where, when and why the Viking Age began, casting vital new light on what is widely recognised to be a pivotal episode of cultural expansion in Eurasia. As the only surviving physical evidence from the spoils of Viking expansion, silver has unique potential to elucidate the early development of the Viking Age. Its geographic origins can reveal where Viking activity was concentrated (Western Europe vs. Baltic/ Russia); its uses can indicate why the Vikings were prepared to risk their lives acquiring it (social vs. monetary function); and its chronology can unlock the timings of the main periods of expansion (ninth century, as widely believed, vs. a century earlier). Yet, due to its poor characterisation and the lack of scientific approaches to its study, silver has never before been harnessed to address these fundamental topics. This project will build an entirely new dataset of the ninth-century ‘silver record’ from a combination of access to museum collections and fresh artefact and coin identifications made by the project team. We will analyse this material in new ways. First-hand archaeological and numismatic study will be combined with pioneering methods in archaeometric analysis, the enormous potential of which for revealing Viking silver sources has recently been demonstrated by the PI. The PI has negotiated unprecedented permissions from national museums to extend scientific analyses to early Viking silver objects from across Northern Europe. There is now a tremendous opportunity to transform understanding of one of Europe’s most significant cultural movements.

Mots-clés : early medieval archaeology
Projet ERC : 3D-In-Macro (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : BI Norwegian Business School — Pays : Norvège — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1376875.0 €

This project will contribute toward a better understanding of inequality and its macroeconomic implications. We will study inequality and its dynamics along three dimensions: Consumption, Income and Wealth, “3D Inequality.” With novel microdata we can measure the entirety of the economy down to the single household along the 3 dimensions. In macroeconomics, much theoretical progress has been made in understanding when distributions matter for aggregates. Newer heterogeneous agent models deliver strikingly different implications for monetary and fiscal policies than what the traditional representative agent models do, and also allow us to study the distributional implications of different policies across households. In principle, this class of models can incorporate the potentially rich interactions between inequality and the macroeconomy: on the one hand, inequality shapes macroeconomic aggregates; on the other hand, macroeconomic shocks and policies affect inequality. However, absent precise micro-level facts it is difficult to establish which of the potential mechanisms highlighted by these models are the most important in reality. Our empirical efforts will be disciplined by these recent developments in modelling macroeconomic phenomena with microeconomic heterogeneity. Our overarching motivation is to quantify the type of micro heterogeneity that matters for macroeconomic theory and thereby inform the development of current and future macroeconomic models. The novel insights we aim to provide could lead to substantial improvements in both fiscal and monetary policy tools. Furthermore, a better understanding of the forces behind growing inequality will inform the current debate on this issue and provide important lessons to policy makers who see economic inequality as a problem in itself.

Mots-clés : inequality,heterogeneous agent models,microeconomic heterogeneity,consumption,income,wealth
Projet ERC : GEM (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Copenhagen — Pays : Danemark — Rôle : PI
Acronyme de l'entité : UCPH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2060000.0 €

This project will create a new category of models that can be used for describing a wide range of spatial choice problems in the social sciences. Spatial settings often have a very large number of choice alternatives. Discrete choice models are used extensively to make counterfactual predictions based on observations of individual choices. Despite forty years of research, current spatial choice models still have two major generic short-comings that seriously limit their ability to make counterfactual predictions. The new category of models will address these two short-comings. The first issue is that substitution patterns between choice alternatives are very complex. The new models will allow substitution patterns to be specified in a general and transparent way. The second issue is that so-called endogeneity issues are pervasive, which violates the underlying statistical assumptions of common models and leads to inconsistent results. The new models will enable endogeneity issues to be dealt with in a simple way. The new models rely on a concept of generalised entropy and are related via duality to classical discrete choice models. A generalised entropy model, or just GEM, will be specified in terms of a transformation from choice probabilities to utilities. This idea is completely new. It is the exact opposite of classical discrete choice models and makes available a whole universe of new models. Early results suggest that GEM will enable the short-comings of the standard models to be overcome. The project develops GEM in three prototypical spatial contexts: equilibrium sorting of households, travel demand modelling, and network route choice. Classical discrete choice models are extensively used for policy analysis and planning. Replacing these by GEM will therefore influence a multitude of decisions across a range of sectors of great societal importance with environmental, economic and welfare consequences that reach far into the future.

Mots-clés : spatial choice,discrete choice,generalised entropy,substitution,endogeneity,travel demand,residential sorting,traffic networks
Projet ERC : FunMagResBeacons (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Southampton — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2762223.0 €

This project will develop and demonstrate molecular agents called functional magnetic resonance beacons (fMRBs). These will provide a new set of versatile spectroscopic tools for the spatially resolved study of chemistry, biochemistry, diffusion, flow and percolation inside opaque objects. The fMRB agents support hyperpolarized nuclear spin order, which generates enormously enhanced nuclear magnetic resonance (NMR) signals. The agents are designed to maintain such order for long times (between 5 minutes and several hours) in ambient temperature solution, enabling their transport deep inside opaque objects. The molecules are functionalized, so that they “light up" in an NMR or magnetic resonance imaging (MRI) experiment, upon triggering by specific chemical signals or physical conditions (sensory functionality), and may also to bind to selected molecular targets (binding functionality). One set of proposed realisations possesses “lock-and-key” functionality, meaning that the hyperpolarized nuclear spin order is “locked” into a form which is invisible in the NMR spectrometer, but which may be “unlocked” at any chosen time by applying a suitable radiofrequency pulse sequence. The following molecular moieties are proposed as storage modules: (1) molecular cages, such as functionalized C60 fullerenes, encapsulating noble gas atoms such as 3He; (2) spin clusters supporting long-lived states, such as pairs of 13C or 15N nuclei, in shielded molecular environments. The sensory moieties include tailored peptide sequences, which may be activated by the presence of particular proteases, while binding modules include moieties such as biotin. The agents are designed to be conveniently transportable in a hyperpolarized state. Potential long-term applications include in vivo molecular imaging by MRI.

Mots-clés : nuclear magnetic resonance,hyperpolarization,long lived states,endofullerenes,molecular imaging
Projet ERC : SLING (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Genoa — Pays : Italie — Rôle : PI
Acronyme de l'entité : UniGe
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1977500.0 €

This project will develop and integrate the latest optimization and statistical advances into a new generation of resource-efficient algorithms for large-scale machine learning. State-of-the-art machine learning methods provide impressive results, opening new perspectives for science, technology, and society. However, they rely on massive computational resources to process huge manually annotated data-sets. The corresponding costs in terms of energy consumption and human efforts are not sustainable. This project builds on the idea that improving efficiency is a key to scale the ambitions and applicability of machine learning. Achieving efficiency requires overcoming the traditional boundaries between statistics and computations, to develop new theory and algorithms. Within a multidisciplinary approach, we will establish a new regularization theory of efficient machine learning. We will develop models that incorporate budgeted computations, and numerical solutions with resources tailored to the statistically accuracy allowed by the data. Theoretical advances will provide the foundations for novel and sound algorithmic solutions. Close collaborations in diverse applied fields will ensure that our research results and solutions will be apt and immediately applicable to real world scenarios. The new algorithms developed in the project will contribute to boost the possibilities of Artificial Intelligence, modeling and decision making in a world of data with ever-increasing size and complexity.
Projet ERC : MICROTOMACROANDBACK (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Stockholm University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1299165.0 €

This project will develop macroeconomic models with household heterogeneity and partially demand-determined output to study how the economy is affected by monetary and fiscal policy, and to investigate the importance of housing in macroeconomic fluctuations and the transmission and efficacy of policy. The objective is to provide a modelling framework that simultaneously is consistent with both empirical micro evidence on household consumption and savings behaviour, and macro evidence on the response of the aggregate economy to a variety of economic shocks. The ultimate goal is to help make these models the new standard for the study of fluctuations and policy evaluation in macro. Inequality and incomplete markets will be a central theme. The first objective of the project is to establish the importance of incomplete financial markets for the response of the economy to changes in monetary policy. The framework will then be used to evaluate the size of the fiscal multiplier and quantitatively evaluate the stimulative effect of extensions to unemployment benefits. The second theme of the project will focus on housing and mortgage debt as an amplification and propagation mechanism. The recent Great Recession–preceded by an unparalleled boom and bust in house prices – has brought to light the importance of housing for the economy. The project will develop a rich benchmark model of housing and the aggregate economy for policy evaluation. First, the project will investigate how heterogeneity in housing and debt affects the transmission of monetary policy. Next, a cross-country analysis will be performed to quantify the importance of different arrangements in the mortgage market for the response of the economy to shocks. Finally, I will introduce imperfect information above the driving forces of the economy to study booms and busts in the housing market and real economic activity, with the goal of evaluating macroprudential policies geared at the housing market.

Mots-clés : heterogenous agents,incomplete markets,monetary policy,fiscal policy,inequality,unemployment,housing,mortgages,default,consumption
Projet ERC : ERC-SciPost-2019 (Horizon 2020, appel 2019, Low value grant)
Entité participante : Stichting scipost — Pays : Pays-Bas — Rôle : PI
Type d'entité : Autres
Financement ERC de l'entité : 60000.0 €

This project will enable SciPost to enhance its metadata handling facilities. In accordance with the goals stated in the Work Programme, we hope to develop the "backend" of our metadata-related publishing services, enabling us by extension to offer new tools for different classes of academic users. Overall objective: To enhance our already industry-leading extended metadata handling facilities for all facets of our scientific publishing activities, to extend their content coverage, and to enlarge their user base by providing tools targeted at authors, funders and the broader community. Specific objectives: • To enhance our existing metadata schema and handling infrastructure for researcher profiles, publications, organizations and funder-related data (funder instances, grant instruments, funding rounds, grant instances); • To widen the coverage of this data, and make it as universal as possible; • To interlink this data and provide open online facilities for using it, thereby creating a set of useful tools for the community (curated researcher disambiguator; publication listing; affiliations; coauthorships/conflict of interest checker; referee finder; grant reporting); • To promote these tools as useful additions to scientific and administrative workflows in general, and facilitate the implementation of our business model in particular.

Mots-clés : open access publishing,metadata,publishing business models
Projet ERC : PLANTGROWTH (Horizon 2020, appel 2018, Advanced grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : Spanish National Research Council — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CSIC
Type d'entité : Recherche
Financement ERC de l'entité : 2497800.0 €

This project will identify the principles governing genome replication in relation to the chromatin landscape and how they impact on plant organ growth. The results will provide the basis to design novel strategies to improve plant growth performance. The large plant genomes, as in all eukaryotes, must be faithfully duplicated every cell cycle, a process regulated at the level of DNA replication origins (ORIs). Our understanding of how ORIs are determined is still very limited. Most of our knowledge comes from cultured cells, precluding the identification of regulatory layers operating at the organism level. Importantly, genome replication can offer unexplored possibilities to modulate plant architecture and growth and, consequently, plant performance. Results generated so far unable us to address a fundamental question: what are the regulatory mechanisms of DNA and genome replication and how they can be exploited to design improved plant growth strategies. This innovative perspective will reveal how genome replication is regulated by DNA sequence context, replication factors and chromatin landscape. Integration of molecular, cellular, genomic and genetic approaches in a whole organism will serve to evaluate the phenotypic effects of modulating genome replication on organ growth. We will also learn how DNA replication control is exerted during endoreplication and in coordination with transcriptional programs, both crucial for plant organogenesis, growth and response to environmental stresses. This program goes beyond incremental research, is timely, innovative, ambitious but realistic, and high risk/high gain, combining different approaches to address a fundamental process. Given the conservation of proteins and pathways, and the availability of well-annotated genomic information for many plant species, PLANTGROWTH will pave the way to translate the technological and conceptual know-how derived from this program to crop species to improve yield.

Mots-clés : plant,organ growth,dna replication,endoreplication,dna replication proteins,cell cycle,chromatin,epigenetics,histone marks