Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Sea-More-Yield: A Blue Biotechnology Solution for the Reduction of Pod Shatter in Bio-Oil Producing Crops (SEA-MORE-YIELD)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Action type: SME instrument
Countries involved: Ireland
Call: Supporting SMEs efforts for the development - deployment and market replication of innovative solutions for blue growth (H2020-SMEINST-1-2014, 2014)
Start date: 2014-11-01
End date: 2015-04-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The objective of the Sea-More-Yield proposal is to commercialise a disruptive blue biotechnology solution to address a bio-oil crop productivity challenge. Three years of independant trials have consistently demonstrated a 20% increase in yield over the current market leading product. Sea-More-Yield powered by Plant Signal Induction (PSI) is a novel patent pending blue biotech innovation to reduce pod shatter in Oilseed Rape (OSR) delivering €5.5bn at the farm gate if implemented across the EU-27. End result, more food and energy security, a theme underscored by Horizon 2020.Sea-More-Yield represents an excellent opportunity for the H2020 SME instrument as it will launch the participating SME Brandon Products into new markets, promote growth, and create high returns of investment. Sea-More-Yield is aligned with the call topic supporting SMEs efforts for the development - deployment and market replication of innovative biotechnology solutions for blue growth. Sea-More-Yield is a perfect example of such an opportunity. The basis of the Sea-More-Yield technology is the seaweed bioresource used in biostimulant manufacture, which is a complex and unique resource whose chemical, biochemical and biological properties provides major undiscovered potential. The main beneficiaries of the development of Sea-More-Yield will be Brandon Products; Growers of OSR gain from increased net margins, increased yield, increased quality premiums; Oil processors will have a larger quantity of high quality oil; Product distributors will have a disruptive technology with a proven mode of action; Consumers will benefit from a predictable harvest = predictable production costs = more stable pricing; The environment less agrochemicals, fertiliser more biofuel and leading to more sustainable biofuel production.

Keywords: oil seed rape,pod shatter,seaweed,biostimulants
Resistance evolution in response to spatially variable pathogen communities (RESISTANCE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: Switzerland,Finland
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-03-01
End date: 2022-08-31
Duration (months): 66.0
Total project cost (EUR): 1999995.0
EU funding (EUR): 988041.25
Participants: 2
Project status: SIGNED

Pathogens are prevalent across all ecosystems. Given the threats imposed by pathogens on their hosts, the ability to resist infection is one key determinant of an individual’s reproductive success and survival. According to theory, resistance evolution is driven by pathogen-imposed selection and constrained by host life-history trade-offs. However, resistance evolution is traditionally studied within the “one host-one pathogen” framework, although it is becoming increasingly clear that a single host individual is exploited by diverse pathogen communities. Unravelling this diversity is the key to understanding selection for resistance, and the key aim of this proposal is to bridge this gap between theory and data. The specific objectives of this proposal are to: i) Assess spatio-temporal variation in pathogen communities and their determinants through community modeling; ii) Quantify the role of host resistance in shaping its pathogen community; iii) Unravel resistance mechanisms that determine pathogen communities by combining experimental and molecular approaches; iv) Quantify immediate and cross-generational fitness consequences that different pathogen communities inflict on their host, and v) Validate the experimental results by assessing how past disease communities have shaped host resistance in natural populations. This ambitious goal is now attainable for the first time because over the past decade my research group has amassed long-term data on hundreds of Plantago lanceolata populations in the Åland Islands, and an extensive genetic sample and seed collection that allow estimating past disease communities and resistance evolution through time. Jointly the objectives of this proposal will provide an unprecedented synthesis of how resistance functions and evolves under realistic pathogen loads, with far reaching implications for both redefining the conceptual framework for resistance evolution and for tackling real-world health and food security problems.

Keywords: coinfection,plant pathogen interactions,resistance evolution
Stepping-up IPM decision support for crop protection (IPM Decisions)

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: Italy,Germany,Greece,Slovenia,Sweden,Greece,Norway,Norway,Finland,Lithuania,France,France,France,France,Netherlands,Denmark,Denmark,United Kingdom,United Kingdom,United Kingdom,United Kingdom,Denmark,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: Stepping up integrated pest management (H2020-SFS-2018-2, 2018)
Start date: 2019-06-01
End date: 2024-05-31
Duration (months): 60.0
Total project cost (EUR): 5058399.94
EU funding (EUR): 4998096.19
Participants: 32
Project status: SIGNED

The ‘IPM Decisions’ project proposed here will accelerate impact from farm Decision Support Systems (DSS) for IPM, as advocated in the Sustainable Use Directive. The impact of DSS in crop protection has been constrained by regional and sectoral fragmentation of actors, inadequate testing of DSS and quantification of their benefits, DSS addressing single pests whilst farmer decisions need to account for multiple pests, and DSS which are insufficiently risk-averse. We will address these constraints and enable innovation by creating a ‘one stop shop’ delivering DSS, data, tools and resources through a pan-European online Platform and an ‘IPM Decisions Network’. The latter forming a community of users and stakeholders. Users will be farmers and advisers, and applied research or industry organisations that deliver or develop DSS. Each type of user will access the Platform via a tailored Dashboard, specific to their requirements. The project consortium brings together multi-actor participants from research, crop protection industry, ICT, meteorological services, policy, farming, advisory and extension organisations. Participants in IPM Decisions are also participants in relevant European projects and networks, enabling efficient engagement and impact. The focus will be on delivering DSS for key pests of major outdoor crops. Integrating key examples of contrasting DSS on the Platform will address urgent needs and demonstrate that the Platform has the functionality required for wide impact. Longevity of the Platform and Dashboards beyond the life of the project will be aided by minimizing the resources required to maintain and update the system, and a realistic business plan. Software, scientific publications and research data will be open access. IPM Decisions addresses all the requirements of part A of SFS-06-2018-2020. The outcomes from this project will support the EU wide demonstration farm network to be established under part B of the call.

Keywords: agro meteorological network,open source,multi actor
Developing Natural Language Processing and machine learning algorithms for the most comprehensive knowledge base to speed up diagnosis of rare disease patients (Mendel KBASE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: United Kingdom
Call: European SME innovation Associate - pilot (H2020-INNOSUP-2019-02, 2019)
Start date: 2019-11-15
End date: 2020-11-14
Duration (months): 12.0
Total project cost (EUR): 123875.0
EU funding (EUR): 123875.0
Participants: 1
Project status: CLOSED

Collectively, rare diseases affect the lives of an estimated 30 million people across the European Union. The majority of rare diseases have a genetic origin, are chronic, highly disabling and life threatening. As a consequence, rare diseases pose a substantial medical burden for patients and an economic burden for society and healthcare systems. Correct diagnosis is highly challenging due to the rarity and sheer number of rare diseases. As a result, it takes an average of five to six years for patients to get their definitive diagnosis which can lead to serious consequences for their health. Mendelian is an innovative start-up with a mission to speed up diagnosis of rare disease patients by developing intelligent clinical decision support tools. For this, we have launched Mendelian’s search engine where medical professionals receive a ranked list of rare diseases and causative genes based on a patient’s symptoms entered. Building on the technology and knowledge gained during the development of Mendelian’s prototype search engine, we now aim to develop a highly detailed and comprehensive rare disease knowledge base that will improve the accuracy of our search engine and support the development of an automated scanning platform. For this, Mendelian is searching for a highly specialised PhD with expertise in state of the art methods in clinical Natural Language Processing (NLP) and Machine Learning (ML) so that features that are useful for diagnosis can be extracted and processed from medical literature and electronic health records in an automated fashion. Developing a comprehensive rare disease knowledge base in house is highly challenging but would have huge benefits by providing us with the flexibility to adjust and optimize NLP pipelines to optimally meet the needs of the physicians using our tools. With EU support, Mendelian can widen its recruitment market from the UK to EU, increase its visibility and offer the innovation associate a competitive salary.

Keywords: rare diseases,natural language processing,machine learning,health,ehealth,diagnostic tools,algorithms
Intelligent, distributed, human-centered and trustworthy IoT environments (IntellIoT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Austria,Austria,Austria,Germany,Germany,Germany,Cyprus,Switzerland,Finland,Greece,Greece,Greece,France,Netherlands,Denmark
Call: Next Generation Internet of Things (H2020-ICT-2020-1, 2020)
Start date: 2020-10-01
End date: 2024-01-31
Duration (months): 40.0
Total project cost (EUR): 7997615.0
EU funding (EUR): 7997615.0
Participants: 17
Project status: SIGNED

The traditional cloud centric IoT has clear limitations, e.g. unreliable connectivity, privacy concerns, or high round-trip times. IntellIoT overcomes these challenges in order to enable NG IoT applications. IntellIoT’s objectives aim at developing a framework for intelligent IoT environments that execute semi-autonomous IoT applications, which evolve by keeping the human-in-the-loop as an integral part of the system. Such intelligent IoT environments enable a suite of novel use cases. IntellIoT focuses on: Agriculture, where a tractor is semi-autonomously operated in conjunction with drones. Healthcare, where patients are monitored by sensors to receive advice and interventions from virtual advisors. Manufacturing, where highly automated plants are shared by multiple tenants who utilize machinery from third-party vendors. In all cases a human expert plays a key role in controlling and teaching the AI-enabled systems. The following 3 key features of IntellIoT’s approach are highly relevant for the work programme as they address the call’s challenges: (1) Human-defined autonomy is established through distributed AI running on intelligent IoT devices under resource-constraints, while users teach and refine the AI via tactile interaction (with AR/VR). (2) De-centralised, semi-autonomous IoT applications are enabled by self-aware agents of a hypermedia-based multi-agent system, defining a novel architecture for the NG IoT. It copes with interoperability by relying on W3C WoT standards and enabling automatic resolution of incompatibility constraints. (3) An efficient, reliable computation & communication infrastructure is powered by 5G and dynamically manages and optimizes the usage of network and compute resources in a closed loop. Integrated security assurance mechanisms provide trust and DLTs are made accessible under resource constraints to enable smart contracts and show transparency of performed actions.
Socially Distanced Solidarity: Far Right Recruitment and Enrolment During the COVID-19 Pandemic (SODIS)

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: Social Sciences and Humanities
Countries involved: Norway
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-09-06
End date: 2023-09-05
Duration (months): 24.0
Total project cost (EUR): 214158.72
EU funding (EUR): 214158.72
Participants: 1
Project status: SIGNED

The questions at the centre of the project Socially Distanced Solidarity: Far Right Recruitment and Enrolment During the COVID-19 Pandemic (SODIS) are how far right organisations have adapted recruitment strategies in time of crisis, namely the Covid-19 pandemic, how successful these strategies have been, and how pathways to joining have shifted as a result of the pandemic. The Covid-19 pandemic provides an unprecedented opportunity to examine changes in collective action and political protest, providing a natural experiment for policy intended to tackle radicalism. Due to lockdowns and partial lockdowns across the world, organisations have had to cancel protest activities and other events at the centre of many recruitment strategies; the ongoing threat of Covid-19 well into 2021 means that organisations must alter their strategies. The subsequent change, or lack-there-of, in recruitment numbers can have implications for counter-radicalisation strategies moving forward. SODIS relies on a modern research design focusing on various perspectives of organisation recruiters and new organisation members, and different national contexts, while taking advantage of this exceptional time in history. A quantitative online survey will lend to a better understanding of motives and attitudes of organisations members in four national contexts and to gain a better understanding of motives for joining organisations, qualitative interviews will be conducted in each country. SODIS will elucidate drivers of far right mobilisation and pathways to radicalisation, contributing to scholarship on social movements, collective action, and radicalisation studies. It will provide insight for practitioners working on countering radicalism and recruitment into such organisations, engaging with the conversation of how liberal and illiberal democracies deal with right-wing extremism .

Keywords: far right,social movements,hate groups,radicalism,recruitment,pathways,protest,europe,covid 19,xenophobia,security
Video analysis for Investigation of Criminal and TerrORIst Activities (VICTORIA)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Theme: Fight crime, illegal trafficking and terrorism, including understanding and tackling terrorist ideas and beliefs
Action type: Research and Innovation actions
Countries involved: Germany,Spain,Germany,Spain,Austria,Germany,Belgium,Romania,Hungary,France,France,France,France,United Kingdom,United Kingdom
Call: Technologies for prevention, investigation, and mitigation in the context of fight against crime and terrorism (H2020-SEC-2016-2017-1, 2016)
Start date: 2017-05-01
End date: 2020-11-30
Duration (months): 43.0
Total project cost (EUR): 5007125.0
EU funding (EUR): 5007125.0
Participants: 19
Project status: CLOSED

Video recordings have become a major resource for legal investigations. Since no mature video investigation tools are available and trusted by LEAs, investigators still need to carry out the analysis of videos almost exclusively manually. Current practices are too resource intensive to handle the yet huge and steadily increasing volume of videos that need to be analysed after crimes and terrorist acts. The consequence is that LEAs cannot analyse all available videos because of the huge effort needed, and the extraction of first clues from videos after a terrorist attack takes more time. VICTORIA will address this need and deliver a Video Analysis Platform (VAP) that will accelerate video analysis tasks by a factor of 15 to 100 (depending on the use case), while providing very reliable results. To achieve this, VICTORIA will 1) develop a set of TRL-6 video analytics selected for their relevance in video investigation related to crimes and terrorist acts, 2) increase significantly the usability of delivered tools by involving LEAs directly in all stages of the development process, from specifications, over assessment of several VAP prototype versions, up to field trials in LEA operational conditions, 3) create an ecosystem around an open VAP concept, that will facilitate sustainable innovation and market growth for video investigation products, 4) train LEA investigators in the use of the VAP, 5) ensure that VICTORIA activities and results meet EU Legal-Ethical-Privacy rules. The VAP will have a scalable architecture based on big data technologies, feature new user interface paradigms allowing complex semantic investigation queries and 4D crime scene reconstruction, be adaptable to specific user needs, and be future proof thanks to an open analytics plug-in feature, based on standardized interfaces and open to third party suppliers. The consortium includes 4 LEAs, 6 renowned research groups, 2 SMEs and 2 industrial companies, world-leaders in security markets.

Keywords: video analytics,legal investigation,law enforcement,forensic,video metadata
Imprints of Magnetic fields in Exoplanets (IMAGINE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Universe sciences
Panel description: Astro-physics/-chemistry/-biology; solar system; planetary systems; stellar, galactic and extragalactic astronomy; cosmology; space sciences; astronomical instrumentation and data
Countries involved: Spain
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2021-05-01
End date: 2026-04-30
Duration (months): 60.0
Total project cost (EUR): 1495046.0
EU funding (EUR): 1495046.0
Participants: 1
Project status: SIGNED

The fast-growing sample of thousands of extrasolar planets is unveiling an amazing variety of properties. It represents an opportunity to shed light on long-standing physics and astrobiology issues from a much wider sample than our Solar neighbours, especially for what concerns the still unclear internal structure, only grossly constrained by observable values of mass and/or radii. Planetary magnetism and its long-term evolution is currently understood only partially for the Earth, at a lesser extent for Jupiter and other Solar planets, and is still elusive in exoplanets. The project focuses on magnetic fields as a key factor in shaping habitability and as a messenger of the internal composition and dynamics. For terrestrial planets, long-lasting, strong enough magnetic fields are arguably a key factor to guarantee habitability, but we are not even sure about how the Earth’s magnetic field has survived for so long. Magnetism leaves other detectable imprints in giant planets. A quest for the first exoplanetary Jupiter-like magnetospheric emission in radio is on-going, but the search needs to be driven by a reliable prediction of the most likely emitters. Magnetic fields can delay the cooling via Ohmic dissipation and could explain the often observed inflated radii in hot Jupiters, but models are still incomplete. IMAGINE will simulate the long-term (Gyr) evolution of the exoplanetary magnetic fields, coupled with a cooling model, and will assess the relevant imprints on their observables for a broad range of distinctive features mass, composition, irradiation, rotation. Combining a novel formulation, emission models and advanced numerical techniques partially imported and adapted from the scenario of magnetized neutron stars, on which the PI is expert, IMAGINE will predict values of magnetic fields for different exoplanets, comparing the associated observable properties of gas giants and contributing to identify the best rocky worlds candidates to habitability.

Keywords: magnetic fields,cooling,habitability,hot jupiters,auroral radio emission