Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : TACKLE (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Life Science
Panel : Environmental Biology, Ecology and Evolution
Entité participante : University of Vienna — Pays : Autriche — Rôle : PI
Acronyme de l'entité : Univie
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

The emergence of complex eukaryotic life forms on Earth from prokaryotic cells is one of the most fundamental questions in biology and also one of the least understood transitions in evolution. Phylogenomic studies recently indicated that the eukaryotic line of descent arose from within the TACK+L superphylum of Archaea. This proposal addresses the systematic analysis of two newly discovered, but largely uncharacterized lineages of Archaea from this superphylum that mark crucial evolutionary transitions. Thaumarchaeota harbor unique ‘eukaryotic’ features and represent the sole group of Archaea that has successfully radiated into virtually any moderate habitat on Earth. The Lokiarchaeota lineage found recently in deep marine sediments forms a direct sister group of Eukaryotes and exhibits an unprecedented array of genes that might have been instrumental for the ancestor of eukaryotes to develop its cellular and genomic complexity. Obviously, the molecular and biochemical investigation of both groups is timely and important, yet, it requires easy access and cultivation. We have now discovered Lokiarchaeota in local, accessible environments and were able to successfully cultivate thermophilic Thaumarchaeota. In this proposal, we will characterize the metabolic and structural traits of these two archaeal lineages and reconstruct their evolutionary ancestry in the context of the TACK+L superphylum. Beside the use of cutting edge techniques for cultivation, metagenomics and stable-isotope-based imaging, a novel method will be developed for in situ metatranscriptomic analyses of archaea. This project will give fundamental insights into the ecological success of Archaea in commonplace environments and into the biology of the closest living prokaryotic relatives of Eukaryotes. Reconstructing the ancestral gene repertoire and biological features of lineages of the TACK+L superphylum will help resolve the enigma of the emergence of eukaryotes.

Mots-clés : archaea,microbial comparative genomics,phylogenomics,single cell analysis,microbial cultivation,early eukaryotic evolution
Projet ERC : ASIAPAST (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : Kiel University — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : CAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1097990.0 €

The emergence of mobile pastoralism in the Eurasian steppe five thousand years ago marked a unique transformation in human lifeways where, for the first time, people relied almost exclusively on herd animals of sheep, goat, cattle, and horses for sustenance and as symbols. Mobile pastoralism also generated altogether new forms of socio-political organization exceptional to the steppe that ultimately laid the foundation for nomadic states and empires. However, there remain striking gaps in our knowledge of how the pastoralist niche spread and evolved across Eurasia in the past and influenced cultural trajectories that frame the human-herd systems of today. Little is known about the scale of pastoralist movements connected with the initial translocation of domesticated animals, how mobility became embedded in pastoralist life, or how movement contributed to the formation of sophisticated political networks. There is a poor understanding of the character of herd animal husbandry strategies that were central to pastoralist subsistence and how these co-evolved alongside pastoralist dietary intake and ritual use of herd animals. We have a remarkably poor understanding of what pastoralists ate, especially the dietary contribution of dairy products - the quintessential dietary cornerstone food of pastoralist societies. ASIAPAST addresses these gaps through a biomolecular approach that recovers the dietary and mobility histories of pastoralists and their animals recorded in bones, teeth, and pottery. This project pairs these methods to detailed analyses of the economic and symbolic use of herd animals preserved in zooarchaeological archives. These investigations draw from materials obtained from key sites that capture the transition to mobile pastoralism, its intensification, and emergence of trans-regional political structures located across the culturally connected regions of Mongolia, Kazakhstan, Russia, Kyrgyzstan, and Uzbekistan.

Mots-clés : stable isotopes,organic residue analysis,zooarchaeology,zooms proteomics
Projet ERC : ASIAPAST (Horizon 2020, appel 2017, Consolidator grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Manchester — Pays : Royaume-Uni — Rôle : Partner
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 234270.0 €

The emergence of mobile pastoralism in the Eurasian steppe five thousand years ago marked a unique transformation in human lifeways where, for the first time, people relied almost exclusively on herd animals of sheep, goat, cattle, and horses for sustenance and as symbols. Mobile pastoralism also generated altogether new forms of socio-political organization exceptional to the steppe that ultimately laid the foundation for nomadic states and empires. However, there remain striking gaps in our knowledge of how the pastoralist niche spread and evolved across Eurasia in the past and influenced cultural trajectories that frame the human-herd systems of today. Little is known about the scale of pastoralist movements connected with the initial translocation of domesticated animals, how mobility became embedded in pastoralist life, or how movement contributed to the formation of sophisticated political networks. There is a poor understanding of the character of herd animal husbandry strategies that were central to pastoralist subsistence and how these co-evolved alongside pastoralist dietary intake and ritual use of herd animals. We have a remarkably poor understanding of what pastoralists ate, especially the dietary contribution of dairy products - the quintessential dietary cornerstone food of pastoralist societies. ASIAPAST addresses these gaps through a biomolecular approach that recovers the dietary and mobility histories of pastoralists and their animals recorded in bones, teeth, and pottery. This project pairs these methods to detailed analyses of the economic and symbolic use of herd animals preserved in zooarchaeological archives. These investigations draw from materials obtained from key sites that capture the transition to mobile pastoralism, its intensification, and emergence of trans-regional political structures located across the culturally connected regions of Mongolia, Kazakhstan, Russia, Kyrgyzstan, and Uzbekistan.

Mots-clés : stable isotopes,organic residue analysis,zooarchaeology,zooms proteomics
Projet ERC : Domognostics (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Phoebe research and innovation ltd — Pays : Chypre — Rôle : Partner
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 68125.0 €

The emergence of networked cyber-physical systems, in which sensor/actuator networks are integrated with software algorithms, facilitates the development of advanced Building Management Systems (BMS) aimed at enhancing energy efficiency in buildings, which accounts for 40% of the energy consumption in the EU. When a fault arises in some of the components, or an unexpected event occurs in the building, this may lead to a serious degradation in performance or, even worse, to situations that would endanger people’s lives. Studies estimate that 20% of the energy consumed in commercial buildings for heating, ventilation, air conditioning, lighting and water heating can be attributed to various faults. Therefore, there is a market need for an intelligent building automation diagnostic system which integrates with existing BMS to facilitate continuous and effective monitoring of the buildings. The objective of the proposed proof of concept is to develop the Domognostics platform, a novel solution for monitoring building automation systems, detecting and diagnosing any component faults and/or unexpected events, and providing remedial reconfiguration actions, aiming at improving operational efficiency. Domognostics will interoperate with existing BMS to extend their capabilities, and will integrate directly with heterogeneous sensor types, such as IoT devices, mobile sensors, wearables, etc., to increase redundancy of the available information and measurements. The Domognostics platform will utilise intelligent fault diagnosis algorithms with machine learning capabilities to boost its capacity to learn from experience, and semantically enhanced reasoning to facilitate the flexibility of adding new sensors or replacing faulty components, as needed. The theoretical foundations of these techniques were developed as part of the ERC Advanced Grant project Fault-Adaptive, which started in April 2012, and is currently being carried out at the University of Cyprus.

Mots-clés : computational intelligence,fault diagnosis,anomaly detection,internet of things,building automation,smart buildings,cyber physical systems
Projet ERC : CODA (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : University of Bremen — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1922114.58 €

The emerging and vibrant area of ontology-based data access (OBDA) is currently establishing itself as an important paradigm for processing incomplete and heterogeneous data. The goal of the CODA project is to make OBDA radically more useful for real-world applications by taking a ground-breaking new perspective on its foundations, algorithms, and tools. The project will rest on an ultimately fine-grained complexity analysis that allows to identify islands of tractability inside practically important ontology and query languages that are otherwise intractable. Based on these islands, novel OBDA querying tools will be developed that are custom-made for ontologies from applications in the sense that high computational cost is incurred only when unavoidable for the concrete ontology used (`pay as you go' behaviour). The key deliverables of the project are a set of tailor-made OBDA querying tools that form a precision tool belt for real-world OBDA applications, theoretical results regarding the structure and computational complexity of important islands of tractability, efficient algorithms that allow to put these to work in practice, and optimization techniques and heuristics that support the algorithms in the tools developed. We will also collect and make available a a library of case studies for evaluating OBDA tools. The project is both timely and essential. It is timely because our economy and society are currently experiencing a revolution in data processing and availability, and dealing with incompleteness and heterogeneity is one of the major arising challenges. The project is essential because it has become apparent now that current OBDA tools cannot satisfy industry requirements. In particular, they do not adequately support the limited use of expressive features (`a little bit of disjunction') which intuitively should not result in high computational cost, but with current technology often does.

Mots-clés : ontology based data access,query answering,islands of tractability
Projet ERC : DEEP-RADAR (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Technion – Israel Institute of Technology — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

The emerging autonomous vehicle ecosystem is expected to grow with an almost 40% CAGR in the next decade hitting €485 billion by 2026 and exceeding €6 trillion in 2050. There is wide industry consensus that improved long-range depth sensing modalities are imperative for the viability of self-driving cars. State-of-the-art optical technologies are still prohibitively expensive, have insufficient temporal and spatial resolution, do not provide an accurate velocity reading, and are restricted to a shorter range in adverse weather conditions. Millimeter wave multiple-input multiple-output (MIMO) radars are an attractive alternative relying on a phased array of transmitting antennas and digital receivers, containing no moving parts, and able to penetrate adverse weather conditions. The weakness of this technology is the costly requirement for a large number of receiver channels to achieve sufficient spatial resolution. We will apply our novel methodology recently developed for medical imaging to overcome this challenge. We have demonstrated that learning the entire imaging pipeline in medical ultrasonography, including the shape of the transmitted pulses and the configuration of the receivers allows reducing the number of transmits by a factor of 3, while maintaining image quality comparable to traditional high-frame rate imaging protocols. Despite the different underlying physics, ultrasound and radar imaging share many conceptual similarities and have a similar mathematical description. Here, we intend to develop a proof-of-concept MIMO radar system demonstrating that by using the learned transmit patterns and image reconstruction pipeline, it is possible to halve the number of receive channels without compromising the image resolution and signal-to-noise ratio. Maintaining high resolution images using a smaller number of receiver channels will significantly reduce the cost of this technology and increase the commercial viability of automotive MIMO radars.

Mots-clés : rf imaging,mimo radar,autonomous vehicle,deep learning,beamforming,inverse problem
Projet ERC : DEPICODE (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : German Center for Neurodegenerative Diseases — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : DZNE
Type d'entité : Recherche
Financement ERC de l'entité : 1729125.0 €

The emerging field of neuroepigenetics investigates processes such as histone-acetylation in the context of neuronal plasticity, memory function and brain diseases. My group has significantly contributed to this novel research field. It is however fair to say that the role of “epigenetics” in memory function is still met with some skepticism in the neurosciences, which is in part due to the fact that many of the current studies have been describing phenomena and mechanistic data to explain how epigenetic processes control memory function in health and disease are comparatively sparse. The major objective of this research proposal is to address this issue and help to consolidate the field of neuroepigenetics by providing insight to the mechanisms by which epigenetic processes contribute to memory formation under physiological and pathological conditions. More specifically I will ask how the epigenetic code is translated into cellular changes that mediate memory formation in health and disease and how can epigenetic mechanisms contribute to the transmission of cognitive phenotypes even across generations. Our results will not only provide import insight to the mechanisms that underlie memory formation but will also lay the basis for the development of novel and improved therapies for age-related cognitive disorders.

Mots-clés : memory consolidation,epigenetic processes,neurodegenerative diseases,histone modifications
Projet ERC : ERCOPE (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Life Science
Panel : Cellular, Developmental and Regenerative Biology
Entité participante : Leiden University Medical Center — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : LUMC
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2383625.0 €

The endo-lysosomal system is critical to diverse processes, including protein homeostasis, signaling and antigen presentation. The vesicular compartment is organized as a collective unit wherein the bulk of endosomes derived from disparate origins resides in a cloud in the perinuclear region and extends outwards to include quickly moving vesicles in the periphery. At this busy intersection between the endocytic and biosynthetic pathways, lies the late endosomal compartment, responsible for protein degradation and antigen processing. In dendritic and other immune cells, this major constituent of the perinuclear cloud serves as a hub for MHC class II antigen loading. Previous work by us and others has elucidated key elements of MHC class II biology through the study of late endosomal transport to and from the cell periphery. It is clear that cell biology of endosomes is modulated by their proximity to other membrane compartments during transport, maturation, cargo selection and delivery and even during cytokinesis in cell division. However, how endosomal positioning in the perinuclear cloud and how their release for further transport is controlled remains largely unknown. The aim of this proposal is to define the molecular basis for endosomal positioning and then to interrogate the relationship between spatial regulation of the endocytic compartment and its functions with respect to i) MHC class II antigen presentation, ii) bacterial infection and iii) mitotic resolution. From a genome-wide siRNA screen for factors influencing MHC class II biology, we have identified a unique and previously uncharacterized ubiquitin ligase that resides in the ER membrane, from where it controls endosomal positioning and times their arrivals and departures as a function of its catalytic activity. On this basis, the work proposed herein is poised to resolve an entirely new molecular network in control of endosomal biology with implications for diverse biological processes.

Mots-clés : endosomal positioning,vesicle transport,mhc class ii
Projet ERC : L2C (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Université Catholique de Louvain — Pays : Belgique — Rôle : PI
Acronyme de l'entité : UCL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1911250.0 €

The engineered systems surrounding us are increasingly hard to control. Not only the complicated interaction of the physical processes with the machines that control them, but also specifications (cyber-security, safety, privacy, resilience, resource-efficiency, decentralization) are more and more complex, and critical. Last but not least, in an increasing number of situations, no model of the system is available (or the model is too complex), and one needs to ‘learn’ the optimal way of controlling the system by the mere observation of data. Our technological world is living a paradigm shift, which is often coined as the Cyber-Physical Revolution, or the Industry 4.0. In view of these specificities, the only sensible way of controlling these complex systems is often by discretizing the different variables, thus transforming the model into a simple combinatorial problem on a finite-state automaton, called an abstraction of this system. Until now, this approach has not been proved useful beyond academic, small examples, as it scales very poorly. The goal of L2C is to transform this approach into an effective, scalable, cutting-edge technology that will address the CPS challenges and unlock their potential. This ambitious goal will be achieved by leveraging powerful tools from Mathematical Engineering. Out of this research, a state-of-the-art software platform will promote our results and translate them into directly usable solutions for the scientific and industrial communities. L2C is a pluridisciplinary project at the frontier between Control Engineering, Computer Science and Applied Mathematics. It bridges the gap between rich innovative techniques and emerging challenges in Control. It impacts both fundamental Science and Engineering, as the theoretical research is driven and fostered by cutting edge technological challenges.

Mots-clés : hybrid systems,switching systems,formal methods,optimization and control
Projet ERC : CC-TOP (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Earth system science
Entité participante : Stockholm University — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2499756.0 €

The enormous quantities of frozen carbon in the Arctic, held in shallow soils and sediments, act as “capacitors” of the global carbon system. Thawing permafrost (PF) and collapsing methane hydrates are top candidates to cause a net transfer of carbon from land/ocean to the atmosphere this century, yet uncertainties abound. Our program targets the East Siberian Arctic Ocean (ESAO), the World’s largest shelf sea, as it holds 80% of coastal PF, 80% of subsea PF and 75% of shallow hydrates. Our initial findings (e.g., Science, 2010; Nature, 2012; PNAS; 2013; Nature Geoscience, 2013, 2014) are challenging earlier notions by showing complexities in terrestrial PF-Carbon remobilization and extensive venting of methane from subsea PF/hydrates. The objective of the CC-Top Program is to transform descriptive and data-lean pictures into quantitative understanding of the CC system, to pin down the present and predict future releases from these “Sleeping Giants” of the global carbon system. The CC-Top program combines unique Arctic field capacities with powerful molecular-isotopic characterization of PF-carbon/methane to break through on: The “awakening” of terrestrial PF-C pools: CC-Top will employ great pan-arctic rivers as natural integrators and by probing the δ13C/Δ14C and molecular fingerprints, apportion release fluxes of different PF-C pools. The ESAO subsea cryosphere/methane: CC-Top will use recent spatially-extensive observations, deep sediment cores and gap-filling expeditions to (i) estimate distribution of subsea PF and hydrates; (ii) establish thermal state (thawing rate) of subsea PF-C; (iii) apportion sources of releasing methane btw subsea-PF, shallow hydrates vs seepage from the deep petroleum megapool using source-diagnostic triple-isotope fingerprinting. Arctic Ocean slope hydrates: CC-Top will investigate sites (discovered by us 2008-2014) of collapsed hydrates venting methane, to characterize geospatial distribution and causes of destabilization.

Mots-clés : arctic,permafrost,organic carbon,methane,carbon dioxide,isotopes,compound specific isotope analysis,source apportionment