Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
CO2 Human Emissions (CHE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling exploitation of space data
Action type: Coordination and support actions
Countries involved: Germany,Germany,Germany,Germany,Germany,Italy,Germany,Switzerland,Sweden,Norway,Belgium,France,France,Netherlands,Netherlands,Netherlands,United Kingdom,United Kingdom,United Kingdom
Call: Preparation for a European capacity to monitor CO2 anthropogenic emissions (H2020-EO-2017, 2017)
Start date: 2017-10-01
End date: 2020-12-31
Duration (months): 39.0
Total project cost (EUR): 3765190.0
EU funding (EUR): 3765190.0
Participants: 23
Project status: CLOSED

The CO2 Human Emissions (CHE) project will coordinate efforts towards developing a European monitoring capacity for anthropogenic CO2 emissions. This challenging target is aligned with the European Commission’s stepwise approach for a requirement-driven integration of Earth observations, from remote sensing and in situ, with enhanced modelling capabilities for CO2 fossil fuel emissions, along with other natural and anthropogenic CO2 emissions and transport. The project will pursue a consolidated methodology for integrating the monitoring system components, as well as innovation for estimating fossil fuel CO2 fluxes. These include reconciling bottom-up and top-down constraints and handling systematic errors of satellite sensors. Earth observations from satellites will be combined with in situ CO2 observations and information from co-emitters or isotopes to support the attribution of fossil fuel emissions and uncertainty reduction. Methodological advances will include a representation of anthropogenic CO2 variability in space and time, responding to documented shortcomings and needs, and a carbon cycle data assimilation system extended to enable estimates of emission uncertainties. Strategies to separate anthropogenic CO2 emissions from biogenic fluxes at country to global scales using observations and models will be documented. CHE will support a large community by providing a library of realistic CO2 simulations from global to city scale to examine the capacity for monitoring future fossil fuel emissions and to adequately dimension space mission requirements. Community building will include direct collaboration across 22 European institutions, and communication and liaison with key European and international stakeholders. These coordination efforts will ensure the transfer of science and technology requirements and recommendations for strengthening existing assets with a view to developing an anthropogenic CO2 monitoring service.

Keywords: capacity building,coordination,liaison,top down estimates reconciliation,simulations library,in situ measurements,anthropogenic emissions monitoring system
Deep Learning for Holistic Inference (HOLI)

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: Israel
Call: ERC Consolidator Grant (ERC-2018-COG, 2018)
Start date: 2019-02-01
End date: 2025-01-31
Duration (months): 72.0
Total project cost (EUR): 1932500.0
EU funding (EUR): 1932500.0
Participants: 1
Project status: SIGNED

Machine learning has rapidly evolved in the last decade, significantly improving accuracy on tasks such as image classification. Much of this success can be attributed to the re-emergence of neural nets. However, learning algorithms are still far from achieving the capabilities of human cognition. In particular, humans can rapidly organize an input stream (e.g., textual or visual) into a set of entities, and understand the complex relations between those. In this project I aim to create a general methodology for semantic interpretation of input streams. Such problems fall under the structured-prediction framework, to which I have made numerous contributions. The proposal identifies and addresses three key components required for a comprehensive and empirically effective approach to the problem. First, we consider the holistic nature of semantic interpretations, where a top-down process chooses a coherent interpretation among the vast number of options. We argue that deep-learning architectures are ideally suited for modeling such coherence scores, and propose to develop the corresponding theory and algorithms. Second, we address the complexity of the semantic representation, where a stream is mapped into a variable number of entities, each having multiple attributes and relations to other entities. We characterize the properties a model should satisfy in order to produce such interpretations, and propose novel models that achieve this. Third, we develop a theory for understanding when such models can be learned efficiently, and how well they can generalize. To achieve this, we address key questions of non-convex optimization, inductive bias and generalization. We expect these contributions to have a dramatic impact on AI systems, from machine reading of text to image analysis. More broadly, they will help bridge the gap between machine learning as an engineering field, and the study of human cognition.

Keywords: structured prediction,graphical models,deep learning,approximate inference
A digital guardian angel enhancing cancer patient’s wellbeing and health status improvement following treatment. (ONCORELIEF)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Treating and managing disease
Action type: Research and Innovation actions
Countries involved: Germany,Italy,Italy,Germany,Italy,Germany,Cyprus,Greece,Belgium,Greece,Greece,Portugal,United Kingdom,United Kingdom
Call: Big data and Artificial Intelligence for monitoring health status and quality of life after the cancer treatment (H2020-SC1-DTH-2019, 2019)
Start date: 2020-01-01
End date: 2023-06-30
Duration (months): 42.0
Total project cost (EUR): 4872250.0
EU funding (EUR): 4872250.0
Participants: 14
Project status: SIGNED

The burden of cancer is rising globally and is estimated to have reached 18.1 million new cases and 9.6 million cancer deaths in 2018. Despite the rising cancer incidence, improvements in early detection and therapeutic treatment have improved cancer survival. As a consequence, the number of cancer survivors is increasing globally, creating the need to improve not only treatment but also wellness and follow‐up care. Cancer treatment often involves combined modalities such as surgery, chemotherapy, and radiotherapy. In the past decades, more effective and targeted therapeutic modalities and less destructive cancer treatments have been developed such as immunotherapy and drug‐targeted therapy. Even so, cancer and its treatment have important physical and psychosocial sequelae. ONCORELIEF is a 36-month action that will leverage the above 6 drivers in order to skillfully and methodologically overcome technical challenges, by introducing new approaches that will allow the utilization of big datasets in order to develop a user-centered AI System to facilitate the integration of QoL assessment instruments through the use of PROMs and PREMs in order to improve post-treatment health status, increase the wellbeing, and follow‐up care of cancer patients. This will be achieved through an intuitive smart digital assistant (Guardian Angel), able to provide personalized support in post-treatment activities and tasks, suggest actions regarding the patients' overall health-status, improved wellbeing and active health-care and ultimately maintain him/her engaged on a wellness journey that will safeguard his/her health over the foreseeable prolonged post-cancer treatment period. To achieve this, ONCORELIEF builds on the combined knowhow of its interdisciplinary industry-driven consortium that brings together state-of-the-art technological skills, design thinking methodology and occupational psychology/health sciences.

Keywords: big data analytics,artificial intelligence,wellbeing
Continuation of the EEN activities on behalf of H2020 cq. Horizon Europe in the region of Flanders (Belgium) (VEBIN SME 3.1)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Specific Grant agreement
Countries involved: Belgium
Call: H2020 ENTREPRISE EUROPE NETWORK SGA4 2020-2021 (H2020-EEN-SGA4-2020-2021, 2019)
Start date: 2020-01-01
End date: 2021-12-31
Duration (months): 24.0
Total project cost (EUR): 325000.0
EU funding (EUR): 325000.0
Participants: 2
Project status: CLOSED

VEBIN SME 3.1 secures the continuation of the EEN services on behalf of H2020 cq. Horizon Europe in the region of Flanders in the years 2020-2021 and the embedding of these activities into the EEN client journeys in Flanders by continuing the services of enhancing the innovation management capacity of SME's by the Enterprise Europe Network in Flanders and ensuring the KAM services for SMEi, FET and FTI on behalf of H2020 cq. EIC for Flemish SME participants during 2020-2021. The present project aims at continuing the services of EEN in Flanders with regard to the key account management for the SME instrument under H2020 cq. Horizon Europe (EIC) as entrusted by the European Commission to the Enterprise Europe network. It also concerns the additional support services that EEN will deliver with regard to the enhancement of the innovation management capacities of SMEs as decided under the mandate the EEN received from H2020 cq Horizon Europe. The present proposal describes how the Flemish VEBIN consortium will continue to realise these services in the region of Flanders and extend also to SMEs that will be beneficiaries of FTI and FET under H2020 cq. EIC, how these will be embedded in the regional innovation support system to the benefit of Flemish SMEs, how the consortium will manage the services and how feedback will be organised in order to ensure a high quality service provision and an added European value. Particular attention will also be given to guarantee the synergies between the activities in this present proposal and the regular EEN services that the consortium is providing in the region so as to realise the EEN client journeys, with special attention to Flemish scale-ups.

Keywords: vebin,kam services,eimc services,scale ups,een client journey
COhort cOmmunity Research and Development Infrastructure Network for Access Throughout Europe (COORDINATE)

Framework: Horizon 2020 — Excellent Science
Programme: Research Infrastructures
Theme: Research infrastructures
Destination: Integrating activities and infrastructures
Action type: Research and Innovation actions
Countries involved: Austria,Spain,Ireland,Italy,Germany,Germany,Finland,Finland,Croatia,Slovenia,Belgium,Norway,Slovenia,France,Netherlands,Netherlands,United Kingdom,United Kingdom,Portugal,United Kingdom,United Kingdom
Call: Integrating Activities for Starting Communities (H2020-INFRAIA-2020-1, 2020)
Start date: 2021-04-01
End date: 2025-03-31
Duration (months): 48.0
Total project cost (EUR): 4988915.0
EU funding (EUR): 4988914.99
Participants: 22
Project status: SIGNED

The aspiration to secure the wellbeing of children and young people is explicit in Grand Challenges such as the UN’s Sustainable Development Goals. The EU has similarly highlighted the importance of securing the future of children and young people. It has become accepted that inequalities must be thought of longitudinally and not regarded as static events unrelated to prior events and future likelihoods. Policy makers must ensure that they base their policy interventions and adjustments on the best evidence available and this must include, inter alia, cohort survey data. COORDINATE will begin to fill the serious and extensive gaps in the availability of robust and suitable data for the monitoring and evaluation of child wellbeing in Europe. The COORDINATE project brings together 22 partners from 14 countries who will initiate the community of researchers and organisations that will drive forwards the coordinated development of comparative birth cohort panel survey research in Europe. COORDINATE will: • Facilitate improved access to international birth cohort panel and cross-sectional survey data • Extend the consortium network to maximise EU and European coverage for a future Europe wide accelerated birth cohort survey • Undertake joint research in the form of a large-scale cohort pilot survey using a harmonised instrument and research design in key European countries The infrastructural community initiated by COORDINATE will benefit from enhanced access to current infrastructural data platforms, and will promote the harmonisation of and improve access to international cohort panel survey data in the study of children as they grow up. COORDINATE continues the research initiated in the FP7 Measuring Youth Well Being project (GA613368) and the H2020 European Cohort Development Project (GA777449) to prepare the next phases of Europe’s first cross-national accelerated birth cohort survey: EuroCohort - Growing Up in Digital Europe (GUIDE).
A diagnostic device for personalized determination of vitamin B6 status and health (B6VitaStat)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Synthetic Chemistry and Materials
Panel description: New materials and new synthetic approaches, structure-properties relations, solid state chemistry, molecular architecture, organic chemistry
Countries involved: Germany
Call: ERC Proof of Concept Grant (ERC-2019-PoC, 2019)
Start date: 2019-12-01
End date: 2021-11-30
Duration (months): 24.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Vitamin B6 is an essential nutrient and part of a well-balanced diet. However, B6 deficiency is often observed in elderly people, diabetes patients and alcoholics and associated with higher rates of cardiovascular disease, stroke and cancer. All these risk populations need a stringent and continuous monitoring of B6 levels. At present B6 detection systems suffer from limited speed, scope, convenience and reliability. These tests require a medical doctor as well as external laboratories with expensive and specialized equipment for analysis increasing the overall costs. We here develop a customized assay for vitamin B6 detection with a desired application as reliable, cheap and easy-to-use point-of-care device. This assay system, termed B6VitaStat, is based on the direct monitoring of cofactor binding into diverse enzyme active sites which will be performed in erythrocytes drawn from blood. Key to B6VitaStat is a tailored probe which mimics the structure of the cofactor. This probe is equipped with a recognition tag allowing to visualize binding to B6-dependent enzymes. The less B6 is bound, the stronger the signal, the higher the overall deficiency. This principle will be incorporated in an easy-to-use device that is based on an antibody printed microarray hallmarked by its cheap and reproducible production. The robust array can be used world-wide including developing countries with less pronounced medical infrastructure. The B6VitaStat team combines complementary expertise including chemistry, engineering and entrepreneurship, which will provide a basis for the envisioned commercialization. Given that B6VitaStat will be the first device of this class we estimate a significant cost reduction compared to current clinical procedures. Overall, we aim to introduce a new device for constant monitoring B6 vitamin status in risk patients and provide a cheap, easy-to-use and reliable method suited for all kinds of applications including those in less-developed countries.

Keywords: point of care device,vitamin b6 determination,microarray,fluorescent probe
Trusted Secure Data Sharing Space (TRUSTS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Countries involved: Austria,Austria,Germany,Ireland,Israel,Germany,Germany,Austria,Germany,Spain,Germany,Cyprus,Belgium,Greece,Greece,Romania,Netherlands
Call: Supporting the emergence of data markets and the data economy (H2020-ICT-2019-2, 2019)
Start date: 2020-01-01
End date: 2022-12-31
Duration (months): 36.0
Total project cost (EUR): 7103700.0
EU funding (EUR): 5977631.25
Participants: 22
Project status: SIGNED

The lack of trusted and secure platforms and privacy-aware analytics methods for secure sharing of personal data and proprietary/commercial/industrial data hampers the creation of a data market and data economy by limiting data sharing mostly to open data. This trend will continue if different technical standards, quality levels, and legal aspects are allowed to diverge uncontrollably. TRUSTS will ensure trust in the concept of data markets as a whole via its focus on developing a platform based on the experience of two large national projects, while allowing the integration and adoption of future platforms. The TRUSTS platform will act independently and as a platform federator, while investigating the legal and ethical aspects that apply on the entire data valorification chain, from data providers to consumers, i.e. it will (a) Set up a fully operational and GDPR-compliant European Data Marketplace for personal related data and non-personal related data targeting both personal and industrial use by leveraging existing data marketplaces (International Data Space and Data Market Austria) and enriching them with new functionalities and services. (b) Demonstrate and realise the potential of the TRUSTS Platform in 3 use cases targeting the industry sectors of corporate business data, specifically in the financial and telecom operator industries while ensuring it is supported by a viable, compliant and impactful governance, legal and business model. To create a European Data Market based on secure and trustworthy data exchanges, the TRUSTS consortium brings together technology providers that are already deeply involved in major national data market projects. This integration will be tested in practice by 6 companies, including 2 data providers, addressing 3 different use-cases. The TRUSTS technology and use-cases will be accompanied by business and legal and ethical considerations, which will ensure that the results of the project are sustainable beyond its duration

Keywords: data market,platforms,data economy,interoperability,analytics,privacy,business models,artificial intelligence,machine learning,digitalisation,scalability,digital single market,big data
Second-Generation Hybrid Electrolyte Supercapacitor (SGHES)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Denmark
Call: European SME innovation Associate - pilot (H2020-INNOSUP-2019-02, 2019)
Start date: 2019-11-01
End date: 2021-02-28
Duration (months): 16.0
Total project cost (EUR): 111500.0
EU funding (EUR): 111500.0
Participants: 1
Project status: CLOSED

The transition from fossil fuels to renewable energy has created an eminent demand for energy-storage solutions because of the intermittent nature of these energy sources. Batteries are the most common solution but other less known technologies like fuel cells and supercapacitors are also used where their characteristics are more suited for the given application. E.g. supercapacitors for high power energy storage to utilize regenerative braking more efficiently. The prevalence of such technologies is to a large extent limited by their cost-effectiveness. Today’s supercapacitors are based on an electrolyte system which was established in the 80s. This pure organic electrolyte system has a significantly higher potential stability window compared to classical aqueous electrolytes, but at the same time a much higher cost and a high impact on the environment if accidently released. A recent discovery of the exact nature which limits the potential stability of aqueous supercapacitor electrolytes has formed the foundation of an invention of a new hybrid electrolyte system which combines the advantages of both organic and aqueous electrolytes. This invention has formed the basis for the formation of the company Innocell ApS which purpose is to bring the first generation of hybrid electrolyte supercapacitors to the market. Currently the cell voltage achieved with the first-generation electrolyte is 2.3 V which results in comparable performance with today’s supercapacitors because of the increased capacitance and conductivity that is a characteristic of the hybrid electrolyte. However, it is expected that a further development of electrolyte system could result in a voltage of 2.8 V which combined with the higher capacitance, conductivity and lower cost of the hybrid electrolyte would revolutionize the supercapacitor industry. It would be the core task of the innovation associate to device a strategy and help Innocell develop this second-generation electrolyte.

Keywords: energy storage,supercapacitor,ultracapacitor,electrolyte,edlc
Injection moulding, casting and coating PILOTS for the production of improved components with nano materials for automotive, construction and agricultural machinery. (IZADI-NANO2INDUSTRY)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Developing and standardisation of capacity-enhancing techniques, measuring methods and equipment
Action type: Innovation actions
Countries involved: Spain,Spain,Italy,Italy,Italy,Romania,France,Denmark,Denmark,Denmark,Denmark
Call: Integration of novel nano materials into existing production lines (H2020-NMP-PILOTS-2015, 2015)
Start date: 2015-11-01
End date: 2018-10-31
Duration (months): 36.0
Total project cost (EUR): 7468976.25
EU funding (EUR): 6027653.0
Participants: 16
Project status: CLOSED

In the frame of previous FP6 and FP7 projects with involvement of IZADI-NANO2INDUSTRY consortium members nanotechnologies have demonstrated their effectiveness for enhancing materials and manufacturing processes performance up to a certain level tested in intended environment (TRL 5). Different nanotechnology based strategies have been addressed to develop methods to improve thermoplastics and metallic parts using current industrial manufacturing processes. Three strategies appear promising to be further implemented in real component manufacturing production plants: master-batches for thermoplastics, master-pellets for metals and nanostructured powders for metallic coatings. IZADI-NANO2INDUSTRY project proposes different solutions based on KETs such as nanotechnology, advanced materials and advanced manufacturing. The project aims to implement the master-batches, the master-pellets and the nanostructured powders in three innovative PILOTS, developed and installed at three existing production plants that will effectively manufacture real components (B-pillar, Swash plate and Valve plate) integrating safe-by-design approaches into the developments stages. The project follows to develop inherently safer production methods. IZADI-NANO2INDUSTRY is an industry driven project with up to 44% of the budget devoted to SMEs. It proposes solutions that will generate new market opportunities for European Automotive, Construction and Agricultural Machinery sectors offering to OEMs new added-value products. IZADI-NANO2INDUSTRY project is supported by the government of the regions where the PILOTS will be installed. The project addresses an innovation action that is in line with the Basque Country, Lombardy and Emilia-Romagna region’s RIS-3 Smart Specialization Strategy.

Keywords: nanomaterials,advanced manufacturing,advance materiales,casting,thermoplastic inyection moulding,nanotexturing,nanoreinforcements,nanoestructures,coatings,automotive,construction,agricultur