Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Distributed Digital Twins for industrial SMEs: a big-data platform (IoTwins)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Spain,Italy,Germany,Austria,Austria,Germany,Germany,Spain,Italy,Italy,Italy,Belgium,France,France,France,France,Denmark,United Kingdom,Luxembourg
Call: HPC and Big Data enabled Large-scale Test-beds and Applications (H2020-ICT-2018-3, 2018)
Start date: 2019-09-01
End date: 2022-08-31
Duration (months): 36.0
Total project cost (EUR): 20027113.44
EU funding (EUR): 16422552.01
Participants: 30
Project status: SIGNED

The IOTWINS project will deliver large-scale industrial test-beds leveraging and combining data related to the manufacturing and facility management optimization domains, coming from diverse sources, such as data APIs, historical data, embedded sensors, and Open Data sources. The goal is to build a reference architecture for the development and deployment of distributed and edge-enabled digital twins of production plants and processes. Digital Twins collect data from manufacturing, maintenance, operations, facilities and operating environments, and use them to create a model of each specific asset, system, or process. These models are then used to detect and diagnose anomalies, to determine an optimal set of actions that maximize key performance metrics. IOTWINS proposes a hierarchical organization of digital twins modeling manufacturing production plants and facility management deployment environments at increasing accuracy levels: • IoT twins: featuring lightweight models of specific components performing big-data stream processing and local control for quality management operations (low latency and high reliability); • Edge twins: deployed at plant gateways and/or at emerging Multi-access Edge Computing nodes, providing higher level control knobs and orchestrating IoT sensors and actuators in a production locality, thus fostering local optimizations and interoperability; • Cloud twins: performing time-consuming and typically off-line parallel simulation and deep-learning, feeding the edge twin with pre-elaborated predictive models to be efficiently executed in the premises of the production plant for monitoring/control/tuning purposes

Keywords: edge computing,digital twins,industry 4 0,facility management,predictive maintenance
Decomposition methods for discrete problems (BOBR)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Poland
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2021-04-01
End date: 2026-03-31
Duration (months): 60.0
Total project cost (EUR): 1355688.0
EU funding (EUR): 1355688.0
Participants: 1
Project status: SIGNED

The main goal of the project is to radically expand our understanding of decomposition methods for discrete problems, with a particular focus on the design of parameterized and approximation algorithms on graphs. We will concentrate on four topics where we see a potential for either establishing new directions, or reaching far beyond the current state of the art. (Beyond) Sparsity: The field of Sparsity is a rapidly developing area of graph theory that studies abstract notions of uniform sparseness in graphs and provides a wealth of tools for algorithm design. While there are still many unknowns within this field, we would like to reach beyond sparse graphs by developing a theory of well-structured dense graphs, inspired by the advances in Sparsity. Parameterized dynamic algorithms: The idea of parameterization has so far received little attention in the field of dynamic algorithms. Our goal is to establish solid foundations for the direction of parameterized dynamic algorithms by providing dynamic variants of basic decomposition tools used in parameterized complexity. Parameterization and approximation on planar graphs: The areas of parameterized algorithms and of approximation schemes on planar graphs share a core set of decomposition techniques and benefit from extensive cross-inspiration. We will approach several intriguing questions in this area while focusing on the idea of parameterized approximation schemes, where parameterization and approximation is explicitly combined. Forbidding induced subgraphs: Structural graph theory offers a wealth of tools for understanding structure in graph classes characterized by forbidding induced subgraphs. This structure, while elusive and difficult to exploit, often leads to surprising tractability results. Motivated by recent advances, we propose to focus on finding general-use techniques for designing subexponential-time, approximation, and parameterized algorithms in this setting.

Keywords: parameterized complexity,approximation algorithms,approximation schemes,dynamic algorithms,planar graphs,sparse graphs,model checking,hereditary graph classes
Development of Copper Catalyzed Strategies for the Amination of Alkyl Halides Using Halogen-Atom Tranfer: Going Beyond SN2 Chemistry (Cu-XAT)

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-2020, 2020)
Start date: 2021-08-04
End date: 2023-08-03
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: SIGNED

The formation of carbon–nitrogen bonds is crucial to the preparation of molecules that impact almost every aspects of our lives like drugs, agrochemicals and food additives. In text-books, creating C–N bonds is approached considering the natural nucleophilic character of N-molecules in substitution reactions with alkyl halides. In practice, these reactions are only used in the case of highly reactive substrates with low steric hinderance (e.g. primary amines + primary alkyl halides). The vast majority of substrates require forcing conditions which lead to side reactions like elimination or poly alkylation. To by-pass these issues multi-step approaches, based on extensive functional group manipulations, are still required. There is an urgent need of methods enabling to directly “plug” complex N-molecules into complex alkyl halides. This project aims at providing a conceptually novel approach to perform substitution reactions between N-nucleophiles and alkyl halides. This will be achieved by developing a radical reactivity where alpha-aminoalkyl radicals convert alkyl halides into C-radicals by halogen-atom transfer (XAT) and a copper catalyst binds the N-nucleophiles and enables amination. Upon achieving this initial goal, I aim to extend and engineer this reactivity as part of complex radical cascades leading to structurally complex chemotypes. The proposal capitalizes on recent developments of the host group that has experience in XAT and the development of catalytic reactions for the formation of C–N bonds. The development of this innovative project at the University of Manchester will create new tools in bio-organic chemistry and facilitate the preparation of high-value materials. Its implementation will be facilitated by generating, transferring, sharing and disseminating knowledge, and will enhance my future career following the training plan envisioned.

Keywords: radical,copper catalysis,halogen atom transfer,amination,synthesis,radical cascade,electron transfer
Woodoo Augmented Wood - scaling up translucent wood for sustainable buildings and vehicles (WOODOO)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: France
Call: SME instrument (H2020-EIC-SMEInst-2018-2020-3, 2020)
Start date: 2021-03-01
End date: 2023-02-28
Duration (months): 24.0
Total project cost (EUR): 821182.5
EU funding (EUR): 574827.75
Participants: 1
Project status: SIGNED

Woodoo transforms natural wood into an augmented material that is strong, light, durable and stunningly translucent. It uses a patented process to replace wood’s lignin with a unique bio-polymer. The result is a material as strong as concrete and steel, and as luminous as amber. It can be used to create: (A) Unique auto interiors; (B) Wooden touchscreens; (C) Light wooden car bodies; (D) Sustainable wooden buildings reaching 48 storeys. The innovation is needed as traditional construction materials severly impact the environment: Steel and concrete produce 10.5% of all CO2 emissions. The construction and auto industries must eliminate emissions by 2050 to meet EU targets. The process is highly scalable. It uses standard industrial equipment (solvent tanks, pressure vessels), combined with Woodoo's patented bio-polymers. It can be contracted to wood processing facilities worldwide. Woodoo’s market entry begins in the automotive sector. It already has partnerships with large auto manufacturers and suppliers. A global player in consumer electronics is interested in wooden touch screens. Woodoo will later scale up to supplying the construction industry. Woodoo has a team of 20 experts, HQ in Paris and R&D in Troyes. It holds 17 patents. It targets markets worth over €375 billion. Woodoo has carried out an SME Phase 2 project, meeting all objectives. It is now applying for an EIC blended equity project. The outcome will be: (1) Scale up production output ; (2) Reduce production time and costs, reduce scrap wastage; (3) Produce a series auto component; (4) Secure contracts for large-scale commercialization; (5) Target private investments. Woodoo meets multiple EU Green Deal objectives. By 2027 it will eliminate 1.6M tons of CO2. EIC funding is needed to achieve this.

Keywords: enhanced wood,construction,automotive,co2 reduction,buildings
SETA: An open, sustainable, ubiquitous data and service ecosystem for efficient, effective, safe, resilient mobility in metropolitan areas (SETA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Spain,Italy,Spain,Poland,Netherlands,Netherlands,United Kingdom,United Kingdom
Call: Big data - research (H2020-ICT-2015, 2015)
Start date: 2016-02-01
End date: 2019-01-31
Duration (months): 36.0
Total project cost (EUR): 5565247.5
EU funding (EUR): 5565247.5
Participants: 16
Project status: CLOSED

Around 50% of the global population lives in metropolitan areas, and this is expected to grow to 75% by 2050. Mobility within these areas is complex as it involves multiple modalities of transport, multiple managing authorities, as well as several millions of citizens. The cost of inefficiency in transport and mobility are enormous. For example, inefficiency costs the UK economy €5.8 billion each year. €583 million is wasted on fuel (e.g. traffic congestion) alone each year, which attributes to increased urban pollution and CO2. Hold-ups to business or freight vehicles amounts to €1.5bn annually. Mobility generates huge amounts of data thought thousands of sensors, city cameras, and connected cars, as well as millions of citizens connected through their mobile devices. If properly managed, this data can be used to understand, optimise and manage mobility and make it more efficient, sustainable and resilient. SETA will address this challenge, creating a technology and methodology able to use this wealth of data to change the way mobility is organised, monitored and planned in large metropolitan areas. The solution will be able to collect, process, link and fuse high-volume, high-velocity, multi-dimensional, heterogeneous, cross-media, cross-sectorial data and to use it to model mobility with a precision, granularity and dynamicity that is impossible with today’s technologies. Such models will be the basis of pervasive services to citizens and business, as well as decision makers to support safe, sustainable, effective, efficient and resilient mobility. The project has the potential to impact the everyday lives of millions of people, their health and the environment with enormous financial and social impact. SETA’s solution will be evaluated rigorously by citizens, business and decision makers in 3 cities across Europe. The proposal includes a commercialisation plan and describes the economy of managing the SETA ecosystem in a metropolitan area.

Keywords: sensing,fusing,linking and modelling high volume,high velocity,multi dimensional,heterogeneous,cross media,cross sectorial data,mobility in smart cities
MEchanisms of Coupling of Ocean Dynamics and Intermediate trophic levels: High Resolution study (MECODIHR)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: France,United States
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2018-10-01
End date: 2021-09-30
Duration (months): 36.0
Total project cost (EUR): 246668.4
EU funding (EUR): 246668.4
Participants: 2
Project status: CLOSED

The open ocean is the largest biome on Earth, yet it is the least protected. A major obstacle to its conservation lies in the fine-grained understanding of how marine organisms are affected by the ocean dynamics. In the last decades remote sensing and bio-logging drastically increased our understanding to how phytoplankton (that can be observed from space as ocean color) and large marine animals (that can be followed with sensors directly attached to them) responds to oceanic turbulence down to the mesoscale (few weeks-months, 10-100 km). A major knowledge gap still concerns the so-called "intermediate trophic levels" (ITLs, i.e. zooplankton and micronekton,) and how mesoscale currents (such as fronts and eddies) affect them. This is the focus of the MECODIHR project. The project uses an unprecedented combination of remote-sensing, and modelling on a multi-disciplinary in-situ database collected in the North-West Atlantic to identify patterns in the distribution of ITLs, relate them to physical structures and biogeochemical observations and make hypotheses about why such relationships arise. High-resolution state-of-the-art modelling allows to test the validity of the formulated hypotheses, clarify the mechanisms behind observed co-localisations and expand the extent of findings. High resolution in-situ measurements and modelling allows to approach how submesoscale dynamics (and its inter-seasonal variability) affect the distribution of ITLs. The MECODIHR results, acquired between the two multidisciplinary highly-reknown oceanographic laboratory of the University of Washington (outgoing phase : 2 years) and the Université de Bretagne Occidentale (incoming phase : 1 year), will provide critical information for open ocean conservation. The MECODIHR project will also train Dr. Della Penna with a rare combination of skills (including scientific, communicative, technical and transferable skills) that are fundamental to face the future challenges of marine sciences.
Better Agri-food Trade Modelling for Policy Analysis (BATModel)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Theme: Sustainable agriculture and forestry
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Italy,Italy,Spain,Switzerland,Hungary,Sweden,Belgium,Poland,France,Netherlands,Portugal
Call: Analytical tools and models to support policies related to agriculture and food (H2020-RUR-2019-2, 2019)
Start date: 2020-09-01
End date: 2024-08-31
Duration (months): 48.0
Total project cost (EUR): 5000001.25
EU funding (EUR): 5000000.0
Participants: 17
Project status: SIGNED

Economy-wide assessments of regional trade agreements often fall short of capturing the complexity of agri-food trade policies especially in the case of major structural changes (as market concentration and global value chain issues). “New generation” trade agreements include many aspects beyond traditional trade policies. Consumer concerns are increasing about food quality and safety, environmental implications, as well as ethical concerns about the way food is produced and its impact on poverty, job destruction and increasing inequality. BATModel will advance assessments of agri-food trade policies as follows: (1) by improving the theoretical underpinning and methodologies of partial and general equilibrium models in ex-ante trade assessments; (2) based on micro-level evidence, by improving our understanding and modelling of value chain to enable more precise impact assessments (gains and losses, between and within member states, between and within groups of agents); and (3) by integrating econometric estimations into existing simulation models at micro- and macro-level, which will allow the analysis of extended welfare effects, like inclusiveness and sustainable development goals. The core contribution will be the BATModel Modular Platform for agri-food trade modelling that will equip the analytical tools, in particular the simulation models currently used by the European Commission (EC), for the analysis of 21st-century agri-food trade issues. BATModel will provide a new modular generation of trade models to support the EC, policy-makers and other stakeholders to better account for specific issues such as non-tariff measures, geographical indications, zero trade flows, quality differentiation and global value chains. The BATModel Modular Platform will ensure long-term impact of the project. The dedicated BATModel Dissemination and Stakeholder Platform will ensure close interactions with stakeholders to provide and disseminate relevant trade policy analyses.

Keywords: partial and general equilibrium models,regional trade agreements,firm or agent heterogeneity,non tariff measures,geographical indications,quality differentiation,global value chains
5G for future RAILway mobile communication system (5GRAIL)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Partnership: 5G PPP (cPPP)
Countries involved: Austria,Germany,Germany,Germany,Germany,Spain,Italy,Switzerland,Belgium,Belgium,Finland,Finland,Hungary,Poland,Belgium,France,France,France,France,France,France,Denmark,United Kingdom,Portugal
Call: 5G PPP – 5G for Connected and Automated Mobility (CAM) (H2020-ICT-2019-3, 2019)
Start date: 2020-11-01
End date: 2023-12-31
Duration (months): 38.0
Total project cost (EUR): 13323105.59
EU funding (EUR): 9994713.379999999
Participants: 29
Project status: SIGNED

The Future Railway Mobile Communication System (FRMCS) will be the 5G worldwide standard for railway operational communications, conforming to European regulation as well as responding to the needs and obligations of rail organisations outside of Europe. The work on functional & technical requirements, specification & standardisation in 3GPP as well as regarding harmonised spectrum solutions is currently led by UIC, in cooperation with the whole railway sector. A major challenge is the update by European Railway Agency of the Technical Specifications for Interoperability of Control Command and Signalling (CCS TSI) by the end of 2022 with a full description of FRMCS with respect to interoperability functions. Therefore, the 5GRAIL project aims to verify the first set of FRMCS specifications and standards (FRMCS V1) by developing and testing prototypes of the FRMCS ecosystem. The validation of the latest available railway-relevant 5G specifications will be achieved through cross-border emulation trials covering significant portions of railway operational communication requirements and including the core technological innovations for rail expected from 5G release 16 and pre-release 17. The project will first define functional tests and then work towards the development and evaluation of prototypes, for both on-board and infrastructure, including vital (ETCS, ATO) and essential (voice specific services, TCMS and video) applications. Prototypes will be then tested in simulated and real environments, with pilots in labs and in the field rolled out in various European sites (France, Hungary and Germany), to ensure compliancy and validation for FRMCS specifications, standards and performance, and consequently guarantee the time to market for FRMCS deployments, planned for 2025 as per European timeline. 5GRAIL will finally deliver test report conclusions to potentially update FRMCS V1 specifications and to identify technical constraints related to implementation issues.

Keywords: rail,railways,frmcs,gsm r,etcs,toba,ccs tsi,3gpp,etsi,tcms,spectrum,test
Uncertainty Quantification and Modern Statistical Inference (UQMSI)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2014-CoG, 2014)
Start date: 2015-09-01
End date: 2021-02-28
Duration (months): 66.0
Total project cost (EUR): 1733767.0
EU funding (EUR): 1733767.0
Participants: 1
Project status: CLOSED

Some of the most important and exciting challenges of our ‘information age’ have led to the development of novel statistical methodology and algorithms that are designed to deal with inference settings involving high-dimensionality, graphical and network structures, inverse problems, ‘big data’, stochastic differential equations, diffusion processes, cosmic microwave background maps, brain tomography etc. While an abundance of algorithms is now available, a scientifically rigorous theory of uncertainty quantification and statistical decision making for such procedures has not been developed yet. Traditional approaches such as maximum likelihood estimation or parametric Bayesian inference cannot be used naively in increasingly complex contemporary statistical models. The construction of confidence statements and critical values for significant hypothesis tests is, however, of crucial importance for all applications of the statistical sciences to the modern world. In this research we propose an objective, mathematically rigorous, and practical paradigm for uncertainty quantification in modern statistical inference problems, and illustrate how this approach can be used in some of the recently emerged areas of statistics. Our theory can validate both Bayesian and frequentist approaches to statistical inference, and can be expected to be optimal in an information-theoretic sense. It has potential impact on all areas of scientific theory building, on legal and medical practice, public management of the internet, modern media and other information structures, and also on the foundations of the mathematical discipline of statistics in itself.