Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PRE-COLLAPSE (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : GEOMAR Helmholtz Centre for Ocean Research Kiel — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : IFM-GEOMAR
Type d'entité : Recherche
Financement ERC de l'entité : 1500000.0 €

The geological record shows that volcanic flank collapses and their associated tsunamis are among the largest and most disastrous natural processes on Earth, because of the huge energies involved. The potential impact of such rare but devastating natural disasters is largely ignored by society, leaving us totally unprepared even to detect the precursors of impending catastrophe. Geodetic monitoring documents gradual (cm/yr) down-sliding of individual flanks at many volcanoes worldwide. Such movements express structural instability, and the majority of volcanoes exhibiting slow flank sliding today have experienced flank collapses in the geological past. There is mounting evidence that such collapses were preceded by slow sliding, leading to the hypothesis that gradual flank movement at some point transitions into collapse. This link, however, lacks a physical explanation, and so identifying which slow-sliding precursors might indicate imminent collapse (and therefore what indicators might be used for hazard mitigation measures) is presently impossible. There appear to be two testable mechanisms by which slow sliding could turn into collapse: (i) it results from decrease in the flank’s shearing resistance, or (ii) enhanced activity in the magma system leads to a run-away feedback situation between sliding and depressurization. PRE-COLLAPSE will test these mechanisms on four volcanoes (Anak-Krakatau, Ritter, Etna, Kilauea) by employing advanced computer models capable of simulating both flank sliding and its interaction with the magma system, incorporating rock mechanical behaviours at shear velocities matching those of slowly sliding flanks, and detailed shoreline-crossing interior structures of the volcanoes based on observational data. The outcome will revolutionize how we assess volcanic flank collapse risk, a Gaussian improbability but a societal catastrophe. It will enable us to develop monitoring strategies to detect precursory signals to catastrophic collapse.

Mots-clés : volcano flank collapse,shoreline crossing processes,seafloor geodesy,marine geophysics,numerical modelling
Projet ERC : ROC-CO2 (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : University of Oxford — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 221303.96 €

The global carbon cycle controls Earth’s climate by the emission and drawdown of carbon dioxide (CO2) from the atmosphere. One of the major sources of CO2 is thought to be the oxidation of organic carbon contained in rocks during chemical weathering. Since the industrial revolution, this flux has been accelerated by burning fossil fuels. However, the natural rates of CO2 emission by rock-derived organic carbon oxidation are very poorly constrained – the only major CO2 source that has not been properly quantified – and the dominant controls on this flux remain unclear. The CO2 release is likely to be ~100 TgC/yr, similar to degassing from volcanoes. Without knowing the rate of CO2 emission and the controls on this flux, it is not possible to fully understand the evolution of atmospheric CO2 and global climate over geological timescales, nor to project future changes over hundreds to thousands of years. To address this deficit and quantify a major geological CO2 source, the proposal will: 1) Assess which factors govern rock-derived organic carbon oxidation. 2) Determine how environmental changes impact oxidation rates and CO2 release. 3) Quantify the global CO2 emissions by rock-derived organic carbon oxidation during chemical weathering, and assess how they may have varied both over Earth history and via anthropogenic change. By quantifying a major CO2 emission for the first time, this project will provide a step change in our understanding of the geological, as opposed to the anthropogenically-modified, carbon cycle. Measurement of rock-derived organic carbon oxidation will require a new approach, harnessing state-of-the-art geochemical proxies carried by rivers (rhenium). Data from river catchments spanning large gradients in the likely environmental controls (erosion, temperature), will elucidate the main factors governing this process, and enable construction of a data-driven numerical model to provide the first quantification of CO2 emissions by this process.

Mots-clés : carbon cycle,chemical weathering,physical erosion,trace elements,rhenium,rivers
Projet ERC : DiRECT (Horizon 2020, appel 2018, Starting grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : University of Zurich — Pays : Suisse — Rôle : PI
Acronyme de l'entité : UZH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499917.0 €

The global incidence of kidney disease is on the rise, but little progress has been made to develop novel therapies or preventative measures. New methods to generated renal tissue in vitro hold great promise for regenerative medicine and the prospect of organ replacement. Most of the strategies employed differentiate induced pluripotent stem cells (iPSCs) into kidney organoids, which can be derived from patient tissue. Direct reprogramming is an alternative approach to convert one cell type into another using cell fate specifying transcription factors. We were the first to develop a method to directly reprogram mouse and human fibroblasts to kidney cells (induced renal tubular epithelial cells - iRECs) without the need for pluripotent cells. Morphological, transcriptomic and functional analyses found that directly reprogrammed iRECs are remarkably similar to native renal tubular cells. Direct reprogramming is fast, technically simple and scalable. This proposal aims to establish direct reprogramming in nephrology and develop novel in vitro models for kidney diseases that primarily affect the renal tubules. We will unravel the mechanics of how only four transcription factors can change the morphology and function of fibroblasts towards a renal tubule cell identity. These insights will be used to identify alternative routes to directly reprogram tubule cells with increased efficiency and accuracy. We will identify cell type specifying factors for reprogramming of tubular segment specific cell types. Finally, we will use of reprogrammed kidney cells to establish new in vitro models for autosomal dominant polycystic kidney disease and nephronophthisis. Direct reprogramming holds enormous potential to deliver patient specific disease models for diagnostic and therapeutic applications in the age of personalized and targeted medicine.

Mots-clés : direct reprogramming,renal tubule cells,kidney development
Projet ERC : PLAS-OLED (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Turku — Pays : Finlande — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1493137.0 €

The global lighting market consumes 20 % of total electric power generated, producing an enormous 400 million metric tons of CO2 annually. The need for more efficient light sources has driven the blossoming of light-emitting diode (LED) research and technology. However, inorganic LEDs for solid-state lighting contain rare earth and toxic heavy metal traces that have negative environmental impacts. Recently, organic LEDs (OLEDs) have been introduced as promising general lighting sources. Unlike LEDs, OLEDs can be fabricated using energy-efficient processes and ecological materials. Therefore, the hazards of LEDs can be addressed by shifting to OLED lighting. Currently, the best OLED lamps are limited to 50 lm/W and lifetimes of around 5000 hours. To convince the market to embrace OLED for general lighting, white OLEDs (WOLEDs) need to reach the luminous efficacy and luminance of inorganic white LEDs (100 lm/W, 10000 hours lifespan). In the PLAS-OLED project, to address this need, I propose the fabrication of a novel WOLED architecture. The new idea here is the conversion of monochromatic OLEDs into WOLEDs with polariton modes. Polariton modes are exciton-dressed degenerate states, meaning that polaritons can be utilized to convert a single-color emitting exciton (e.g., green color) to multi-color emission (e.g., blue and red). Moreover, polaritons states have been reported to accelerate emission rates in organic semiconductors, and to induce reverse intersystem crossing (RISC) for harvesting non-radiative triplet excitons or converting slow phosphorescence to fast fluorescence. Thus, polaritons can also increase the luminous efficacy and luminance of WOLEDs. By conducting comprehensive photoluminescence and electroluminescence experiments, I aim to demonstrate that polaritonics is a disruptive technology for converting monochromatic OLED into inexpensive, efficient, stable, and bright WOLEDs.

Mots-clés : strong light matter interactions for manipulating electronically excited states in organic semiconductors,organic semiconductor polaritons,organic light emitting diodes,oleds,reverse intersystem crossing  risc,thermally activated delayed fluorescence,tadf,harvesting triplets with polaritons,microcavities,strong light matter interactions,electrical injection in organic semiconductors
Projet ERC : LeDNA (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems 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 : 1500000.0 €

The global loss and redistribution of biodiversity is a hallmark of the Anthropocene. Our challenge is to generate information about how altered biodiversity influences ecosystems and use this information to change our impact on the biosphere. To meet this challenge, we must know where species are, how their distributions change in time and why. However, current methods for determining species distributions is expensive, time intensive and hard to do for multiple species and large geographic regions- rendering global trend analysis near infeasible. We therefore need a paradigm shift. I will utilize the biotechnology of the fourth industrial revolution (i.e., inexpensive sequencing and computational power) to empirically change how we sample animal and plant biodiversity to solve the infeasibility problem of tracking multiple species distributions on large spatial scales. I am among the first to show that DNA shed from animals into the environment (‘eDNA’) is transported in rivers (10-12 km) and that it is from aquatic and terrestrial species. Building on these observations, I hypothesize that transported eDNA allows for sampling multiple species on large spatial scales and will test my hypothesis by determining if lakes act as accumulators of eDNA in the landscape by receiving transported eDNA from rivers. Thus, my proposed research will investigate (1) how chemical, physical, and biotic processes cause eDNA decay to understand its transport potential in the environment, (2) how much eDNA from a catchment is transported into a lake, and (3) in a global set of lakes, test whether eDNA measures seasonal turnover of biodiversity for large spatial scales. If lakes accumulate eDNA from their catchments, sampling them will provide the paradigm shift needed to vastly change the cost, speed and geographic scale with which species can be surveyed through time to understand what effect their change has on the biosphere.

Mots-clés : environmental dna,animals and plants,metabarcoding
Projet ERC : NEUCosmoS (Horizon 2020, appel 2020, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Universe sciences
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 : 1971587.0 €

The goal of NEUCosmoS is to unravel some of the most severe inconsistencies that are currently threatening the so-far very successful standard model of cosmology (ΛCDM). The most critical one is the steadily growing 5σ difference in the measurement of the expansion rate of the universe today, the Hubble constant, from early-time probes (CMB) versus late-time ones (supernovae Ia). Additional discrepancies persist in the amplitude of matter perturbations, σ8, and in other fundamental parameters, such as the curvature of the universe. These anomalies, if confirmed, will have revolutionary implications for physics. In this context, NEUCosmoS will provide new, ground-breaking insight through the development of a robust analysis pipeline, allowing us to extract the most precise cosmological information from one of the forefront, post-Planck CMB experiments: the South Pole Telescope 3rd-Generation (SPT-3G). SPT-3G will measure the CMB small-scale polarization with unprecedented accuracy over the next 5 years, opening an entirely new window in CMB cosmology, with potentially original discoveries on its own. However, this statistical power will be useless without an analysis able to guarantee robustness against systematic effects, which the PI of this proposal is an expert on. For this reason, she was invited by the SPT collaboration to lead this effort, opening a unique opportunity of European access to the SPT-3G data. NEUCosmoS will provide a framework to transform the existing SPT-3G pipeline into one with quality comparable to satellite missions, building upon the PI’s Planck experience and tools, adapting them to the new challenge. The NEUCosmoS team will drive the interpretation of current and future hints of new physics in a reliable way, with statistical power comparable to the Planck satellite, and in combination with it, almost doubling the constraining capability. This will pave the way to a future contribution by Europe to the next-generation of CMB experiments.

Mots-clés : data analysis,hubble constant
Projet ERC : SYMBIOSYS (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : RWTH Aachen University — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : RWTH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1988750.0 €

The goal of SYMBIOSYS is to assure the reliability and interoperability of networked (software) systems, a crucial requirement in today’s networked information society. To this end, we devise a software and systems analysis methodology that – for the first time – considers the vital influence factors that determine the behavior of networked systems, especially including input and temporal uncertainty of network interactions. With SYMBIOSYS, we will be able to automatically and effciently explore and analyze the vast amount of distributed execution paths in networked systems in a highly structured manner inspired by Symbolic Execution (SE). The combination of the benefits of model checking (rigorous exploration) and of dynamic software testing (analyzing real systems’ code) represents a quantum leap in the field of network analysis. Orthogonal to and complementing formal model-based approaches, which target the design of reliable systems on an abstract (model-) level, we also address system- and implementation-level aspects of (typically heterogeneous) implementations that interact via unpredictable networks. To achieve this, we introduce the fundamentally new approaches Symbolic Distributed Execution (SDE), Symbolic Temporal Execution (STE) and their symbiosis (SDTE). This is a breakthrough in the symbolic analysis of real systems and significantly widens the scope of SE to new analysis domains. Our novel approach raises the issue of complexity and path explosion. Yet, our experience from early work on SDE strongly suggests that the use of domain-specific knowledge and further general optimization strategies allow to significantly reduce this complexity and enable an efficient analysis. SYMBIOSYS also enables and fosters the design of new methods and tools to ensure reliability, interoperability, and other vital properties of networked systems. We demonstrate our new methodology through examples from Cyber-Physical Systems and low-latency communication.
Projet ERC : A-TO-B (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Physical and analytical chemical sciences
Entité participante : University of Liverpool — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2257300.0 €

The goal of bioelectronics is to interface electrical devices with living tissues, cells and biological fluids to achieve a range of functions: from monitoring biological activity to controlling neuron signals and administering drugs. The materials developed to build these interfaces are typically organic materials containing polymeric conjugated chains combined with ionic components in water. At the moment there is no clear structure-function theory for these materials and no microscopic understanding of how they operate or why some of them perform better. The overall goal of this proposal is (i) to lay the foundations for atomistic modelling of organic bioelectronics materials, (ii) to derive structure-property relations from the study a range of experimentally relevant systems and (iii) to address some of the most pressing scientific questions arising in the field. These objectives cannot be achieved with any of the existing methodologies. The physics of ion dynamics coupled with the dynamics of very fast electrons is new and outside the capabilities of current classical or quantum simulation tools. The materials are chemically too complex and diverse to simulate a sufficient number of them with the common methods of soft matter simulations. This proposal addresses both the physical aspects (developing a new method to describe ion-electron coupled dynamics) and the computational aspects (devising a scheme for accelerated simulations of polymeric materials), providing this research field with a robust and predictive theory.
Projet ERC : MUTANOMICS (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : Centre for Genomic Regulation — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CRG;CRG-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 2333279.0 €

The goal of my research is to understand mutations and how they interact to alter phenotypes and disease. We recently initiated a new research direction that uses systematic (‘deep’) mutagenesis to quantify, understand, and predict how diverse mutations interact non-additively within and between molecules to affect phenotypes at multiple scales. Very excitingly, we have also shown that quantifying genetic interactions by deep mutagenesis provides sufficient information to determine the 3D structures of proteins. In this project we will leverage this experience in deep mutagenesis and computational modelling to address three specific aims: 1. To develop simple generic experimental and computational methods to determine the in vivo structures of proteins using deep mutagenesis and to apply these methods to solve the structures of domains of unknown structure. 2. To use deep mutagenesis and computational modelling to understand how mutations globally interact within and between molecules, when these interactions can – and cannot – be predicted from phenotypic measurements alone, and how these interactions alter in response to changes in gene expression. 3. To use deep mutagenesis to understand the cellular toxicity of pathological prion-like domains and to reveal the in vivo structures of these ‘unstructured’ regions, as well as those of disordered proteins that function as agents of protein-based epigenetic inheritance. Taken together, this will provide rich insights into how mutations combine to alter phenotypes, a question of central importance to evolution, engineering, and human disease. It will also develop methods that use deep mutagenesis to determine protein structures, including of intrinsically disordered proteins relevant to disease and epigenetic inheritance. Our goal is to develop techniques that will allow labs across the world to use deep mutagenesis to solve protein structures, including potentially in large-scale systematic projects.

Mots-clés : genetic interactions,deep mutagenesis,epistasis,genotype phenotype maps,intrinsically disordered proteins,structure determination,epigenetic inheritance
Projet ERC : ARS (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : University of Verona — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2750000.0 €

The goal of the ARS project is the derivation of a unified framework for the autonomous execution of robotic tasks in challenging environments in which accurate performance and safety are of paramount importance. We have chosen surgery as the research scenario because of its importance, its intrinsic challenges, and the presence of three factors that make this project feasible and timely. In fact, we have recently concluded the I-SUR project demonstrating the feasibility of autonomous surgical actions, we have access to the first big data made available to researchers of clinical robotic surgeries, and we will be able to demonstrate the project results on the high performance surgical robot “da Vinci Research Kit”. The impact of autonomous robots on the workforce is a current subject of discussion, but surgical autonomy will be welcome by the medical personnel, e.g. to carry out simple intervention steps, react faster to unexpected events, or monitor the insurgence of fatigue. The framework for autonomous robotic surgery will include five main research objectives. The first will address the analysis of robotic surgery data set to extract action and knowledge models of the intervention. The second objective will focus on planning, which will consist of instantiating the intervention models to a patient specific anatomy. The third objective will address the design of the hybrid controllers for the discrete and continuous parts of the intervention. The fourth research objective will focus on real time reasoning to assess the intervention state and the overall surgical situation. Finally, the last research objective will address the verification, validation and benchmark of the autonomous surgical robotic capabilities. The research results to be achieved by ARS will contribute to paving the way towards enhancing autonomy and operational capabilities of service robots, with the ambitious goal of bridging the gap between robotic and human task execution capability.

Mots-clés : robotic surgery,service robotics