Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Spatio-Temporal Methods for Data-driven Computer Animation and Simulation (SpaTe)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-09-01
End date: 2025-08-31
Duration (months): 60.0
Total project cost (EUR): 1998750.0
EU funding (EUR): 1998750.0
Participants: 1
Project status: SIGNED

Numerical simulations are of tremendous importance for a wide range of scientific disciplines and commercial enterprises. For the majority of these natural phenomena, we not only need to consider the three spatial dimensions, but additionally we need to resolve how these phenomena develop over time. Thus, most natural simulations inherently need to resolve four dimensional functions, and most effects at human scales require fine discretizations along all four axes. As a consequence, these functions require large amounts of resources to compute and store. This problem becomes even more pronounced with the advent of data-driven techniques and machine learning. The learning algorithms effectively add additional dimensions, and the complexity and dimensionality of the corresponding functions explains the current lack of data-driven algorithms for space-time functions despite their enormous potential. Within this research project I plan to address the fundamental difficulties that arise in this setting: I will develop novel algorithms to infer spatio-temporal functions, and to construct efficient representations to tame their complexity and high dimensionality. This project combines numerical simulations with computer vision, and machine learning, and has the potential to radically change the way we work with physical simulations. Not only will it break new ground for fast and controllable VFX animations, but it will additionally facilitate the development of new ways to capture physical effects, in conjunction with algorithms to make physical predictions based on observations. Ultimately, this direction will allow us to better understand the physical world around us. It will help us to analyze sparse and ambiguous measurements such as videos and 3D scans automatically and reliably, with a vast range of practical applications from social-media apps to autonomous vehicles.

Keywords: computer animation,physics based simulation,inverse problems,physical scene understanding
Connected and Shared X-in-the-loop Environment for Electric Vehicles Development (XILforEV)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Partnership: EGVI (cPPP)
Countries involved: Germany,Germany,Spain,Germany,Belgium,Belgium,Slovenia,France,Netherlands
Call: Virtual product development and production of all types of electrified vehicles and components (H2020-LC-GV-2018, 2018)
Start date: 2019-01-01
End date: 2021-12-31
Duration (months): 36.0
Total project cost (EUR): 3575078.75
EU funding (EUR): 3575078.75
Participants: 9
Project status: CLOSED

Overall goal of the XILforEV project strives for developing a complex experimental environment for designing electric vehicles and their systems, which connects test platforms and setups from different domains and situated in different geographical locations. The domains under discussion can cover (but not limited by) hardware-in-the-loop test rigs, dynamometers, material analysers, and other variants of experimental infrastructures. Real-time running of specific test scenarios simultaneously on (i) all connected platforms/devices with (ii) the same real-time models of objects and operating environments allows exploring interdependencies between various physical processes that can be hardly identified or investigated in the process of EV development. However, the realization of connected and shared XIL experimental environment is characterized by a number of steps to be solved, e.g. communication concepts ensuring real-time capability of connected experiments, reliable methods for real-time handling of big experimental data et al. With this in mind, a strong consortium has been built, encompassing a wide spectrum of competences. In summary, the XILforEV project brings together seven complementary participants from industry and academia, to address the new design and testing tool for electric vehicles and their systems, based on a sound and objective analysis of the distributed XIL technologies, at a level of depth never attempted by any previous research on the subject. To this purpose the XILforEV activity will include novel techniques for connecting experimental labs and dedicated case studies for designing EV motion control and EV fail-safe control. In addition, considering the importance of virtual models in XIL procedures and the availability of different test benches interconnected, the proposal also addresses the development of high-confidence, real-time capable models with automatic validation using experimental data.

Keywords: x in the loop,electric vehicle chassis systems,machine learning,fault tolerance
From bio-based feedstocks via di-acids to multiple advanced bio-based materials with a preference for polyethylene furanoate (PEFerence)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Theme: Public-private partnerships
Destination: Bio-based Industries
Action type: Innovation actions
Partnership: BBI (Art-187)
Countries involved: Austria,Germany,Germany,Italy,Austria,Germany,Switzerland,Norway,Belgium,Norway,Norway,Finland,France,France,France,France,Netherlands,Netherlands,Netherlands,Netherlands,Denmark,Denmark
Call: Converting bio-based feedstocks via chemical building blocks into advanced materials for market applications (H2020-BBI-JTI-2016, 2016)
Start date: 2017-09-01
End date: 2025-02-28
Duration (months): 90.0
Total project cost (EUR): 45188712.99
EU funding (EUR): 24999610.0
Participants: 32
Project status: SIGNED

The PEFerence project will establish a globally first-of-a-kind, industrial scale (50 000 tonnes/year), cost-effective FDCA (diacid) biorefinery flagship plant producing bio-based chemicals and materials (bottles, films, Lego Bricks, polyurethanes) using also existing facilities in industrial symbiosis. The consortium aims to replace a significant part of fossil based polyesters (such as PET), but also technologically superior packaging materials like glass and aluminum with 100 % bio-based polyesters (such as PEF). The unique properties of PEF (excellent barrier and strength) make it a material that can be applied in areas where PET is less suitable. The initial market focus will be on high value applications such as replacement of multilayer packaging, aluminum cans and small size PET bottles where PEF brings most value. On the longer term, when FDCA is produced at large scale and technology is further matured, FDCA based polyesters are expected to penetrate further into markets which allow smaller or no price premium. The potential significant reductions in non-renewable energy usage and greenhouse gas emissions compared to fossil based PET or aluminum based cans for PEF based packaging solutions will be assessed. Furthermore, PEF bottles can be recycled and used again as raw material for bottles, as well as in a cascading approach for packaging and textiles. During the project, fructose produced via an enzymatic isomerisation process from 2nd generation glucose will be assessed. The full value chain will be optimized ensuring cost-effective and environmentally sustainable raw material sourcing and production of FDCA, PEF/PBF and polyurethane products. Finally, together with customers and brand owners (Lego, Nestle), 100% bio-based end-products will be demonstrated and validated to ensure fast market deployment.

Keywords: biomass,bioproduct,fdca,sustainability,biorefinery,di acids,polyester
Physics of Extreme Massive Stars (POEMS)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Germany,Estonia,Argentina,Azerbaijan,Belgium,Czechia,United Kingdom,Chile,Brazil
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2018, 2018)
Start date: 2019-01-01
End date: 2024-08-31
Duration (months): 68.0
Total project cost (EUR): 952200.0
EU funding (EUR): 920000.0
Participants: 11
Project status: SIGNED

Massive stars are extreme cosmic engines, enriching their environments with chemically processed material throughout their entire life-time, and triggering star and planet formation. Despite their importance for the cosmic evolution, their evolutionary path up to their deaths as spectacular supernova explosions is most uncertain due to the lack of precise knowledge of the physical mechanisms behind mass eruptions. We wish to establish a multidisciplinary, international network of researchers from Europe, Asia, and South America with expertise in a variety of disciplines, and with background in both theory and observations. Our ultimate goal is to enlighten the processes that trigger mass loss in massive stars during extreme phases of their evolution. We will develop cutting-edge numerical codes suitable to describe the chemical and dynamical evolution of the stars, their winds, and their large-scale environments. In addition, we will initiate global observing campaigns utilizing facilities at major renowned observatories in combination with our national facilities, and exploit public archives from ground-based and space missions to acquire an outstanding set of urgently needed highest quality data. Confronting predictions from the numerical models with the observations will empower us to derive the first extensive and comprehensive set of precise physical parameters. The acquired results will significantly enhance our knowledge and lead to major advancements in all related fields. The bulk of exchanges will be undertaken by Early Stage Researchers and young Post-docs, who will be educated and trained in modern observing and data analyzing techniques and in high-performance computation, equipping them with excellent skills for their future careers. We will organize schools and workshops to share knowledge and to communicate and disseminate our results, which will be major breakthroughs and support the leading role of Europe in Astronomy.

Keywords: massive stars,stellar winds,mass loss,stellar pulsations,circumstellar medium,stellar evolution
Integrated Components for Complexity Control in affordable electrified cars (3Ccar)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Public-private partnerships
Destination: Electronic Components and Systems
Action type: Research and Innovation actions
Partnership: ECSEL (Art-187)
Countries involved: Austria,Germany,Germany,Italy,Austria,Austria,Germany,Germany,Germany,Spain,Germany,Spain,Italy,Italy,Germany,Germany,Spain,Italy,Germany,Taiwan, Province of China,Lithuania,Belgium,Belgium,Finland,Romania,Romania,Latvia,France,France,France,France,Czechia,Czechia,Netherlands,Netherlands,United Kingdom
Call: ECSEL Key Applications and Essential Technologies (RIA) (ECSEL-2014-1, 2014)
Start date: 2015-06-01
End date: 2018-10-31
Duration (months): 41.0
Total project cost (EUR): 52401675.84
EU funding (EUR): 17320843.96
Participants: 47
Project status: CLOSED

The 3Ccar project will provide highly integrated ECS Components for Complexity Control in thereby affordable electrified cars. The new semiconductors for Complexity management (Control, reduction) will offer the next level of energy efficiency in transportation systems. 3Ccar’s impact is maximizing pragmatic strategy: Use semiconductor technology innovations to manage functionality & complexity increase. This leads also to cheaper, efficient, robust, comfortable, reliable and usable automotive systems. This strengthens Europe as a whole (OEM, Tier1, Semiconductor) generating economic growth and new jobs in Europe. The impact of 3Ccar is driven vertically by innovations and horizontally enabling growth and deployment in the industry based on what we see as European Values. We recognized that European engineers develop for highest efficiency, convergence and manageable complexity. Our society appreciates long life products to avoid waste. 50 partners and 55 Mio€ budget give the mass for innovative products such as functional integrated powertrains, smart battery cells with unique selling features allowing Europe to advance to global leadership. An important feature of the project has been the recognition and exploitation of synergies with other EV projects, enabling fast innovation cycles between such aligned projects. With 55 Mio€ budget and 10 b€ impact the R&D expenditure ratio is 200 which is 10x higher than the semiconductor average and corresponds to very strong innovation potential which will be translated into automotive and semiconductor industry. The technologies developed in 3Ccar will be commercialized all over the world while giving advantages to Europe’s OEMs willing to manufacture in Europe. 3Ccar will be involved in standardization needed to ensure that large vertical supply chains can be established. The 3Ccar project shows that collaboration between industry, research institutes, governments and customers is pivotal for excellence in Europe.

Keywords: power electronics,energy efficiency,automotive powertrain,electrified vehicles,complexity control
Unraveling the protein glycosylation of Plasmodium falciparum is crucial for development of novel therapeutics against malaria (SugarBlock)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Spain
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-08-29
End date: 2018-08-28
Duration (months): 24.0
Total project cost (EUR): 158121.6
EU funding (EUR): 158121.6
Participants: 1
Project status: CLOSED

Annually, malaria causes 200 million clinical cases and more than half a million deaths. Works carried out more than 40 years ago demonstrated that a malaria vaccine offering sterile protective immunity in humans was possible, but the efforts to develop a modern, recombinant ‘subunit’ malaria vaccine only confer short term protection against clinical malaria in 35-50% of recipients. Several evidences support the presence of foreign short N-glycans and other minor glycosylations in the surfaces of the parasite, Plasmodium faciparum, the causative agent of malaria. In addition, recent studies show that Plasmodium sporozoites present also unknown α-galactose containing antigens in their surface and that antibodies against them provide sterile protection against malaria in mice. We propose to completely characterize the protein glycosylation present in the surface of the extracellular sporozoites, that travel from the mosquito to the liver, and merozoites, that invade human erythrocytes. We will use different quasi-targeted glycoproteomic approaches, based on the expected simplicity and low variability of these glycosylations in the parasite surface and their affinity to well characterized lectins. The investigation of these uncommon parasitic glycosylations may expose an unexpected Achilles’ heel in the Plasmodium parasite that could be exploited to halt sporozoite development and/or stop merozoite invasion and induce protection against malaria, mimicking what has already been achieved using carbohydrate-protein conjugate vaccines against bacterial infections.

Keywords: glycosylation,sporozoites,merozoites,alpha galactose,glycoproteomics,immunogenic,malaria,analytical glycobiology,xeno glycans
Baryons in extreme QCD matter (XQCDBaryons)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-10-01
End date: 2019-12-31
Duration (months): 24.0
Total project cost (EUR): 171460.8
EU funding (EUR): 171460.8
Participants: 1
Project status: CLOSED

Quantum Chromodynamics (QCD) undergoes a crossover from the hadronic phase at low temperatures T to a quark-gluon plasma (QGP) phase at high T. This crossover and properties of the QGP phase are important for understanding the evolution of the early universe and are being studied by major Heavy Ion Collision (HIC) experiments at RHIC and LHC. The transition temperature and many QGP properties have been determined by Lattice QCD simulations. However, connecting these to experimental remnants of QGP fireballs produced at HICs is not straightforward. Thermal effects will modify the properties of the excitations (mesons and baryons) within the medium. We propose to investigate these in-medium changes using lattice QCD methods, shedding light onto the dynamics of HIC fireballs. Low temperature, high chemical potential phases are another region of the QCD phase diagram, interesting, e.g., for the physics of neutron stars. While this region is not accessible to numerical methods at present, we address the situation of an isospin chemical potential mu_I on the lattice, which also describes important aspects of neutron star cores. We propose to determine baryonic excitations for non-zero mu_I, which can provide a deeper understanding of possible quark matter cores in neutron stars.

Keywords: lattice qcd,qcd thermodynamics,heavy ion collisions,hadron physics,particle physics
Transport of Engineered Nanomaterials across the blood-brain-barrier (NanoBBB)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-04-01
End date: 2020-10-01
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

Engineered nanomaterials (ENMs) offer unique potential for innovation in a diversity of applications, but have also been linked to potential adverse effects on human health and biota. A particular concern is the accumulating evidence implicating ENMs in neurotoxicity, with a potential mechanism involving crossing the blood brain barrier (BBB) and then directly or indirectly acting on the central nervous system. Currently, two key questions pertain to this uncertainty: (1) What conditions favour ENMs crossing the BBB? This is most likely related to the physicochemical properties of the ENMs but the current understanding is limited and inconclusive, primarily due to limited or irreproducible characterisation of ENMs. Therefore, a systematic investigation on the BBB-penetrating ability and association with the intrinsic properties of ENMs is urgently needed. (2) What is the fate of ENMs within and beyond the BBB? i.e. the deposition, translocation, and transformation of ENMs after crossing the BBB. Given that the accumulation of ENMs in BBB might be low, localizing the ENMs in the system would be a challenging task, especially for ENMs with high elemental backgrounds (e.g., C-based and Fe-based ENMs). Thus, novel approaches are urgently needed to enable a breakthrough in our understanding of ENM ability to cross the BBB and trace their path beyond. Project NanoBBB proposes combining novel labelling techniques with an on-a-chip brain model and in vivo experiments enabling a uniquely novel approach to solve this problem. This project will allow us to systematically understand the behaviour and fate of certain ENMs in brain and contribute to safer design of ENMs. The ER brings her extensive biological expertise to the host lab, which in turn offers world-class analytical and labelling facilities and expertise. NanoBBB also offers placements in industry for the on-a-chip technology development and an NGO to host the in-vivo experiments enabling validation of the model.

Keywords: nanomaterials,blood brain barrier,isotope labeling,in vitro bbb model
FOSTERING PRECISION AGRICULTURE AND LIVESTOCK FARMING THROUGH SECURE ACCESS TO LARGE-SCALE HPC-ENABLED VIRTUAL INDUSTRIAL EXPERIMENTATION ENVIRONMENT EMPOWERING SCALABLE BIG DATA ANALYTICS (CYBELE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Spain,Germany,Spain,Italy,Spain,Italy,Austria,Ireland,Cyprus,Finland,Greece,Serbia,Belgium,Greece,Greece,Poland,Belgium,Belgium,Greece,Greece,France,France,Netherlands,Netherlands,Denmark,United Kingdom,Luxembourg,United Kingdom
Call: HPC and Big Data enabled Large-scale Test-beds and Applications (H2020-ICT-2018-2, 2018)
Start date: 2019-01-01
End date: 2022-03-31
Duration (months): 39.0
Total project cost (EUR): 14241889.77
EU funding (EUR): 12407673.63
Participants: 34
Project status: CLOSED

CYBELE generates innovation and create value in the domain of agri-food, and its verticals in the sub-domains of PA and PLF in specific, as demonstrated by the real-life industrial cases to be supported, empowering capacity building within the industrial and research community. Since agriculture is a high volume business with low operational efficiency, CYBELE aspires at demonstrating how the convergence of HPC, Big Data, Cloud Computing and the IoT can revolutionize farming, reduce scarcity and increase food supply, bringing social, economic, and environmental benefits. CYBELE intends to safeguard that stakeholders have integrated, unmediated access to a vast amount of large scale datasets of diverse types from a variety of sources, and they are capable of generating value and extracting insights, by providing secure and unmediated access to large-scale HPC infrastructures supporting data discovery, processing, combination and visualization services, solving challenges modelled as mathematical algorithms requiring high computing power. CYBELE develops large scale HPC-enabled test beds and delivers a distributed big data management architecture and a data management strategy providing 1) integrated, unmediated access to large scale datasets of diverse types from a multitude of distributed data sources, 2) a data and service driven virtual HPC-enabled environment supporting the execution of multi-parametric agri-food related impact model experiments, optimizing the features of processing large scale datasets and 3) a bouquet of domain specific and generic services on top of the virtual research environment facilitating the elicitation of knowledge from big agri-food related data, addressing the issue of increasing responsiveness and empowering automation-assisted decision making, empowering the stakeholders to use resources in a more environmentally responsible manner, improve sourcing decisions, and implement circular-economy solutions in the food chain.

Keywords: precision agriculture,precision livestock farming,hpc testbeds,hpc empowered big data analytics,large scale datasets,semantic enrichment,harmonisation,interoperability