Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Biogeographic and cultural adaptations of early humans during the first intercontinental dispersals (BICAEHFID)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: The study of the human past
Panel description: Archaeology, history and memory
Countries involved: Germany,Spain
Call: ERC Advanced Grant (ERC-2018-ADG, 2018)
Start date: 2019-10-01
End date: 2026-03-31
Duration (months): 78.0
Total project cost (EUR): 2499996.0
EU funding (EUR): 2220396.0
Participants: 2
Project status: SIGNED

Our understanding of the emergence and dispersal of the earliest tool-making hominins has been revolutionised in the last decade, with sites in eastern Africa and China pushing both events more than half a million years earlier than previously thought. Traditional models linking biological speciation, cultural innovation and migration events with climatic pulses have remained theoretical, and recent discoveries suggest that the picture of the earliest human colonization across the Old World is far more complex, demanding heuristic approaches to understand the biogeography and adaptive behaviours of early humans. This project will be the first substantive attempt to produce a global synthesis of earliest human occupation dynamics by comparing the world’s longest sequences of early archaeological sites, namely eastern Africa and China. Our objective is to understand the alternative evolutionary trajectories adopted by hominins that shared an overarching biological and cultural background, but who faced different climatic and biogeographic challenges and opportunities. The ambition of our global-scale objectives is accompanied by the unmatched quality of our datasets and the ground-breaking perspective we will adopt in their study. Fieldwork in the two most renowned sequences in each region alongside a primary study of additional top-quality assemblages in both subcontinents, will be combined with extensive metadata sets to produce comprehensive views of temporal trends and paleoecological patterns. Our state-of-the-art methodological sets (which combine an exceptionally diverse range of disciplines from geochemistry to niche modelling) and ground-breaking analytical perspective (which considers data from micro-stratigraphy to satellite imaging) will enable us to develop new approaches to challenge established paradigms and produce a new picture of the biogeographic adaptations of early stone-tool makers.

Keywords: palaeolithic archaeology,early stone age,human evolution
eDREAM - enabling new Demand REsponse Advanced, Market oriented and Secure technologies, solutions and business models (eDREAM)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: A single, smart European electricity grid
Action type: Research and Innovation actions
Countries involved: Spain,Italy,Italy,Italy,Italy,Romania,Greece,United Kingdom,United Kingdom
Call: Next generation innovative technologies enabling smart grids, storage and energy system integration with increasing share of renewables: distribution network (H2020-LCE-2017-SGS, 2017)
Start date: 2018-01-01
End date: 2021-06-30
Duration (months): 42.0
Total project cost (EUR): 3822125.0
EU funding (EUR): 3822125.0
Participants: 11
Project status: CLOSED

Smart automated Demand Response (DR) represents a valid alternative to grid reinforement for electricity Distribution System Operators (DSOs) to procure in a cost-effective way the necessary flexibility for integrating larger shares of intermittent RESs, while not compromising security of supply and network reliability. However DR potential has been exploited so far to a very limited extent due to a number of technological, regulatory, economic barriers. To cope with these challenges, eDREAM will develop and make available a novel near real time DR scalable secure blockchain-driven technological and business framework aimed to optimize aggregated system services flexibility provisioning to DSOs. The project will research and develop tools and services for: i) optimal DR system design, which includes early detection of flexibility potential via multimodal fusion of aerial, LIDAR and thermal imaging, end users profiling and segmentation by leveraging on big data clustering and large data sets visual interactive exploration and DR optimization services for energy end users; ii) optimal DSO-driven Demand Response management, including novel applications of blockchain decentralized ledger for secure data handling, market-based microgrid control and near real time closed loop DR verification aimed to improve system observability and enable fair DR financial settlement. Novel flexibility market and services/products design, as well as cooperative DSO-aggregator business models enabled by incentive sharing will validate the eDREAM DR technical concept from the economic perspective. The eDREAM technologies will be extensively validated in a lab-based pilot (Greece), followed by two field pilots, a C&I VPP-based optimal aggregated flexibility management in UK and a mixed stationary and movable (EVs) loads flexibility microgrid-level optimized flexibility management in Italy.

Keywords: community based virtual power plants,blockchain driven domand respons,graph based demand response optimization,closed loop demand response,system service flexibilty,big data for user profiling
Model-Based Construction And Optimisation Of Versatile Chassis Yeast Strains For Production Of Valuable Lipid And Aromatic Compounds (CHASSY)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Biotechnology
Action type: Research and Innovation actions
Countries involved: Ireland,Germany,Germany,Sweden,Switzerland,France,Netherlands
Call: Microbial chassis platforms with optimized metabolic pathways for industrial innovations through systems biology (H2020-NMBP-BIO-2016, 2016)
Start date: 2016-12-01
End date: 2021-05-31
Duration (months): 54.0
Total project cost (EUR): 5634610.0
EU funding (EUR): 5634610.0
Participants: 10
Project status: CLOSED

CHASSY will unlock the full potential of the yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus as cell factories for production of high value compounds which have applications in the cosmetic, nutraceutical and white biotechnology sectors. Current cell factory strains for these classes of product are restricted to proof-of-principle levels because of limited precursor supply, poor product tolerance and lack of versatility. CHASSY addresses these challenges by redesigning metabolic circuits and expanding the host range to include the oleaginous yeast, Y. lipolytica and the thermotolerant yeast, K. marxianus. The systems biology approach will integrate model-based design, construction and analysis of yeast strains, resulting in reconfigured metabolic networks optimised for the production of lipid and aromatic molecules. Construction of the chassis strains, using new and existing synthetic biology tools, will be directed by knowledge derived from a thorough systems biology comparison of the three yeast species, conducted using integrative data analysis and genome scale metabolic models. The chassis strains will be used to build cell factories to produce three specific high value products: the oleochemicals, Docosanol and Octanoic acid; and the aromatic molecule, Amorfrutin 1. These new cell factory strains will be evaluated under industrial conditions to produce data that will further improve the chassis platforms. The major outcomes of this project will be (1) a new set of chassis yeast strains that are widely applicable for development of industrial cell factories; (2) the knowledge and technology to readily build and evaluate new chassis tailored to specific applications; (3) prototype cell factory strains producing three high value metabolites for commercial exploitation; (4) a dissemination and exploitation strategy to ensure that European SMEs benefit from the knowledge base, platform chassis and resources generated in CHASSY.

Keywords: yeast,cell factory,oleochemical,aromatic
Support to the Realisation of the Ocean Energy Implementation Plan of the SET-Plan (OceanSET)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: Coordination and support actions
Countries involved: Spain,Spain,Italy,Ireland,Belgium,France,United Kingdom,Portugal,United Kingdom
Call: Support to the realisation of the Implementation Plans of the SET Plan (H2020-LC-SC3-2018-Joint-Actions-2, 2018)
Start date: 2019-03-16
End date: 2022-03-15
Duration (months): 36.0
Total project cost (EUR): 1043745.0
EU funding (EUR): 992028.5
Participants: 9
Project status: CLOSED

The SET Implementation Plan for Ocean Energy (IP) was adopted by the SET-Plan Steering Committee on the 21st of March 2018. The IP was prepared by a Temporary Working Group, with representatives from the European Commission, Member States and other stakeholders. For the execution of the IP, the TWG has evolved to assume the role of the Implementation Working Group (IWG). Support for the OE sector to date has focused on the development of research and roadmaps which have set out the aspirations of wave and tidal sector. The principle of the IP is to transform those aspirations into operational actions. The actions listed within the IP are primarily based upon the Ocean Energy Strategic Roadmap, which has been agreed by the EC, MS, Regions, stakeholders and the wider ocean energy sector. The ambition of the IP is to outline a structured approach that will enable wave and tidal technologies to follow a credible development path, with the ultimate destination of a commercially viable products and industry. The target timescale presented in the IP is 2025 for tidal technologies and 2030 for wave technologies. OceanSET will assist the IWG to continue their work to deliver on the targets set in the IP. In particular OceanSET will focus on assessing the progress of the ocean energy sector and will monitor the National and EU funded projects in delivering successful supports. Relevant data will be collected annually and will be used to inform MS and EU Commission on progress of the sector, it will also be used to review what works and what doesn’t and to assess how to maximise the benefit of the funding streams provided across the MS, Regions and the EC. The partners on this project include representatives from Ireland (SEAI), UK (WES, University of Edinburgh), France (FEM), Portugal (DGEG), Spain (EVE, PLOCAN), Italy (ENEA) and from the industry (OEE). The Sustainable Energy Authority of Ireland (SEAI) will be lead partner on the project.

Keywords: ocean energy,set plan,wave and tidal,implementation plan
QOOWEAR, Advanced Connected Worker Technologies: World’s first Smart Interconnected Heating Suite for sub-zero Oil&Gas workers. (SIHS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Italy
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-09-01
End date: 2020-02-29
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

QOOWEAR’s project aims at addressing the Oil& Gas industry technological challenge to create and adopt a technology that could process data from monitoring systems embedded in workers’ equipment – a concept known as "Connected Worker". In 2017 the World Economic Forum stated that “The Oil&Gas Industry entails risky activities and the potential for connected worker technologies to improve safety is particularly relevant”. QOOWEAR will bring to the market the World’s First Smart Interconnected Heating Suite (SIHS) to the Oil&Gas workers, a radically innovative system which recognizes the coldest points of the body, giving them the priority to be heated. It is a base-layer, worn in contact with the skin, 100% embeddable into existing equipment. The hardware embeds sensors to check the environment around the body in real time, to decide where and how much it needs to be heated. At the same time, the Suite embeds a Software as a Service (SAAS), representing a deep value proposition of the project, which will enable workers’ data bio-tracking. Thanks to the connected worker system, companies will be able to monitor state of health of workers in real time and in remote, based on pattern recognition’s algorithms (AI). Those algorithms allow the prediction and anticipation of safety risks on the field, generating automatic alarms in case of real emergency (pop-up alerts via Dashboard). This project aims at improving the living condition of people who work in subzero environments, that corresponds approximately to 9 Million workers worldwide. Specifically, QOOWEAR will address the North European Oil&Gas market, that is the Service Available Market (SAM) composed of 220.000 workers. Moreover, benchmark analysis has shown the lack of direct competitors. QOOWEAR’s Team has capabilities both in terms of technology track record and business administration, with members of the NASA and Co-founders with engineering background.

Keywords: oilandgas,artificial intelligence,connected worker,wereable technologies,data bio tracking,heavy industries,smart clothing
European Technology and Innovation Platform for Ocean Energy (ETIP OCEAN 2)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: Coordination and support actions
Countries involved: Spain,Belgium,United Kingdom,Portugal
Call: Support to sectorial fora (H2020-LC-SC3-2018-Joint-Actions-3, 2018)
Start date: 2019-01-01
End date: 2021-12-31
Duration (months): 36.0
Total project cost (EUR): 975260.0
EU funding (EUR): 975260.0
Participants: 4
Project status: CLOSED

ETIP Ocean 2 has 3 strategic objectives: - Ensure optimal use of existing resources for the sector and streamline sectoral activities; - Support and accelerate European and global deployment of ocean energy; - Ensure that the potential benefits for European industry and society are maximised. The European ocean energy sector has major potential. To reach this potential sectoral stakeholders must collaborate, share knowledge, and avoid the duplication of efforts. There is also a need for close cooperation between the public and private stakeholders. The ETIP Ocean 2 project has been designed to deliver this. Stakeholder exchanges via the ETIP Ocean platform will be strengthened. A series of structured and targeted webinars and workshops will be organised. These will cover the key challenges facing the ocean energy sector – in the domains of technology, finance, social and environmental – and will allow stakeholders from across the sector to exchange and coordinate. Based upon stakeholder exchanges, a series of accessible and information-based studies and reports will be released. The work to produce these publications will focus exchanges, and will help ensure that learnings from the project are widely disseminated. They will be accessible to those who did not participate directly, and will preserve learnings beyond the lifetime of the project. Finally, ETIP Ocean 2 will support the coordination of public and private stakeholders. By acting as a bridge to the SET Plan Ocean Energy Working Group, ETIP Ocean 2 will ensure that sectoral activities are aligned with the actions and objectives of the SET Plan Ocean Energy Implementation Plan. The ETIP Ocean 2 project will engage all stakeholders and foster cooperation; align stakeholders to commonly agreed goals; find novel approaches to the development of technological and social processes related to the energy transition, and coordinate stakeholders in the context of the SET Plan Ocean Energy Implementation Plan.

Keywords: etip ocean,ocean energy
Wind, Efficient, Light, Lifter (WELL)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Spain
Call: Stimulating the innovation potential of SMEs for a low carbon energy system (H2020-SMEINST-1-2015, 2015)
Start date: 2015-09-01
End date: 2016-02-29
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The “WELL” system, protected by patent in Europe and in the USA is an innovation and technological advancement on a global scope, that allows the assembly and replacement of the blades of a wind turbine on a wind farm without needing to use large tonnage cranes, by using a “telescopic lift” system that uses the turbine wind tower itself as a support system. It can be operated by no more than 3 workers (vs 14), work can be completed in less than 24 hours (vs. 72), and in winds of up to 12 metre/second (vs. <7m/s), thus minimizing the number of accidents, reducing the waiting period for blade replacements, reducing the cost of the operation by more than 90%, and also reducing the profit loss for wind farm operators (approximately €2000 per day). Leunamme Engineering has an agreement with Iberdrola to launch the WELL system. WELL is aligned with the global target «20-20-20» of the European Union. The main customer groups of WELL system are the wind farms operators, and manufacturers of wind turbines. They are interested in reducing maintenance costs and in maximizing the operational hours of the wind farm, because O&M expenses are becoming critical in order to be more competitive and less dependent on public support. Through this Feasibility Analysis, the design of a technological scalability and commercial expansion strategy of the company services at a European and global level have been approached, in order to include other generator models and other large components of wind turbines. Phase II would consider the implementation of the technological scaling development of WELL system. The WELL proposal was presented for the first time to the last call of the SME-Intrument program (18-03-2015, SIE-01-2015 1 P) achieving a total score of 12,88. The only weak point in the evaluation was the lack of a risks analyisis. An appropriate technical and business risks analysis, and their associated contingency plans, has been included in this new submission of the proposal.

Keywords: the project objective is to design the technological strategy,commercial scale and the financing and worldwide business launch of the new well system
Indigenous Knowledge in the Making of Science: Historia Naturalis Brasiliae (1648) (BRASILIAE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The study of the human past
Panel description: Archaeology, history and memory
Countries involved: Netherlands
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2018-01-01
End date: 2023-06-30
Duration (months): 66.0
Total project cost (EUR): 1475565.0
EU funding (EUR): 1475565.0
Participants: 1
Project status: SIGNED

This project is an interdisciplinary study of the role of indigenous knowledge in the making of science. Situated at the intersection of history and anthropology, its main research objective is to understand the transformation of information and practices of South American indigenous peoples into a body of knowledge that became part of the Western scholarly canon. It aims to explore, by means of a distinctive case-study, how European science is constructed in intercultural settings. This project takes the book Historia Naturalis Brasiliae (HNB), published in 1648 by Piso and Marcgraf, as its central focus. The HNB is the first product of the encounter between early modern European scholarship and South American indigenous knowledge. In an encyclopedic format, it brings together information about the natural world, linguistics, and geography of South America as understood and experienced by indigenous peoples as well as enslaved Africans. Its method of construction embodies the intercultural connections that shaped practices of knowledge production in colonial settings across the globe, and is the earliest example of such in South America. With my research team, I will investigate how indigenous knowledge was appropriated and transformed into European science by focusing on ethnobotanics, ethnozoology, and indigenous material culture. Since the HNB and its associated materials are kept in European museums and archives, this project is timely and relevant in light of the growing concern for the democratization of heritage. The current debate about the societal role of publicly-funded cultural institutions across Europe argues for the importance of multi-vocality in cultural and political processes. This project proposes a more inclusive interpretation and use of the materials in these institutions and thereby sets an example of how European heritage institutions can use their historical collections to reconnect the past with present-day societal concerns.

Keywords: indigenous knowledge
The reading brain as a statistical learning machine (STATLEARN)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: Italy
Call: ERC Starting Grant (ERC-2015-STG, 2015)
Start date: 2016-09-01
End date: 2022-02-28
Duration (months): 66.0
Total project cost (EUR): 1498210.0
EU funding (EUR): 1498210.0
Participants: 1
Project status: CLOSED

Despite written language is not part of our genetic endowment, literate adults process an impressive amount of information as they read, and do that extremely flawlessly and nearly error-free. How this happens is largely unknown, and represents a fundamental issue for theories of human learning. Building on data from nonhuman primates, human infants and psycholinguistic experiments on word internal structure, STATLEARN tests the hypothesis that one fundamental cognitive mechanism underlies visual word identification, i.e., statistical learning. Human infants learn to chunk smaller perceptual units (e.g., oriented lines) into larger, meaningful objects (e.g., tools, faces), taking advantage of recurrent patterns in their distribution. As developing readers, they would apply this very same mechanisms to a newly–encountered type of visual objects, i.e., letters. On this basis, they would build progressively higher–order orthographic units, which eventually make their visual word identification as adult readers astonishingly efficient. The project is composed of four work packages. One aims at identifying which principle(s) drive(s) statistical learning, and contrasts overall frequency, contextual diversity, and letter transitional probabilities. Because these factors co-vary in real languages, a second work package will involve adult readers in learning artificial languages, where we will build in any statistical properties we might need to test. A third package will seek signs of statistical learning directly into the performance of developing readers. A fourth package will assess positional constraints in the identification of morphemes (e.g., kind and ness in kindness). These work packages include behavioural, eye tracking, ERP, MEG and fMRI work. Bringing together evidence from such a wide array of approaches will allow to understand how statistical learning unfolds, and what kind of representations it brings into the human reading system.

Keywords: reading,visual word identification,statistical learning,orthographic coding