Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
RECAP preterm: Research on European Children and Adults born Preterm (RECAP preterm)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Understanding health, wellbeing and disease
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Germany,Estonia,Italy,Germany,Norway,Belgium,Finland,Sweden,Finland,France,Netherlands,United Kingdom,United Kingdom,Denmark,Portugal
Call: Networking and optimising the use of population and patient cohorts at EU level (H2020-SC1-2016-RTD, 2016)
Start date: 2017-01-01
End date: 2021-09-30
Duration (months): 57.0
Total project cost (EUR): 9713230.0
EU funding (EUR): 9713230.0
Participants: 21
Project status: CLOSED

The project’s overall aim is to improve the health, development and quality of life of children and adults born very preterm (VPT, < 32 weeks of gestation) or very low birth weight (VLBW, < 1500g) – approximately 50 000 births each year in Europe – by establishing an ICT platform to integrate, harmonise and exploit the wealth of data from 20 European cohorts of VPT/VLBW children and adults and their families constituted from the early 1980s to the present, together with data from national registries. VPT/VLBW births have higher risks of cerebral palsy, visual and auditory deficits, impaired cognitive ability, psychiatric disorders and social problems than infants born at term and account for more than a third of the health and educational budgets for children. They may also face higher risks of non-communicable disease as they age. There is emerging evidence of reduced mental health, quality of life, partnering, family life and employment chances and wealth in adulthood. The platform will enable stratified sub-group analyses of sociodemographic and clinical characteristics, neonatal complications, and otherwise rare medical conditions that cannot be studied in national population cohorts. The broad temporal, geographic, cultural and health system diversity makes it possible to study the impact of socioeconomic and organisational contexts and determine the generalisability of outcomes for VPT/VLBW populations. The RECAP platform creates a value chain to promote research and innovation using population cohorts, beginning with the integration of VPT/VLBW cohorts to the translation and dissemination of new knowledge. It will be based on a sustainable governance framework, state-of-the art data management and sharing technologies, tools to strengthen research capacity, a hypothesis-driven research agenda and broad stakeholder participation, including researchers, clinicians, educators, policy makers and very preterm children and adults and their families.

Keywords: preterm birth,nicu,registry studies,developmental outcome,data sharing,data pooling,quality of life,mental and physical health,social inequalities,health economics,statistical methods
An innovative ECO inteRnal coverIng for metal and plastic conVEntionalS conTainers (ECO-RIVEST)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Action type: SME instrument
Countries involved: Italy
Call: Boosting the potential of small businesses in the areas of climate action, environment, resource efficiency and raw materials (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-08-01
End date: 2017-11-30
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Paint buckets containing leftover paints present an important economic and environmental challenge in Europe. As is known, the containers that are used for paints must be subjected to separate disposal because of the inevitably traces of the potentially hazardous liquid product that was originally contained remain inside them. While they are commonly made of material that could in theory be 100% recyclable, empty and almost empty paint buckets in such a current stream of waste treatment end up either landfilled, incinerated or separated out and disposed of as hazardous waste generating unnecessary large amount of waste at a considerable higher cost and obvious additional stress for the environment. Each year, approximatively 900,000 tonnes of leftover paint are wasted in containers and only few of them (less than 5%) are currently being recycled. With 12% of the environmental burden caused by paint and about €1 billion spent with regard to their disposal, there is growing need today to find more environmentally friendly and cost effective alternative to such current paint container waste treatment solution. In this course of action, we present Eco-RIVEST, an innovative paint container bag covering solution devised to reduce up to 85% of leftover "hazardous waste" from paint containers. Consisting of a covering system provided to cover the inner surface of a container with plastic bag that would be removed and disposed once the product is finished, Eco-RIVEST not only maintains the product quality intact, but also greatly minimize the amount of waste generated by paint containers. For our company, leader in the manufacturing of paint bucket solutions, we expect from Eco-RIVEST commercialization to provide us an important grow with an accumulated turnover of €7.14 million for €3.24 million profit and 11 foreseen jobs created by 2024.

Keywords: metal,plastic,containers,recycle,waste,special waste
BigDecisions – Data-driven decision making with cryptographic confidentiality (BigDecisions)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Estonia
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-06-01
End date: 2016-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Our objective in this innovation project is to disrupt data brokerage and analytics industries by introducing Sharemind, a security technology that enables previously impossible data analysis applications. Sharemind solves the problem where an organization wants to learn something from confidential data owned by a number of other people or organizations. Sharemind allows the data owners to protect their information during the analysis so that any leakage is controlled with machine-enforced means. For example, banks, retailers and governments can collect and share customer/citizen information without compromising privacy. Sharemind encourages rational behaviour in a society. By removing the barriers from information sharing, Sharemind lets governments, companies and researchers reach their full potential and become more efficient. We have validated this capability in multiple real-world prototypes and have achieved legal breakthroughs that make Sharemind a promising technology for Europe.

Keywords: privacy,confidentiality,cross border,disruptive,data sharing,analytics
New Scanning nearfield Microscopy method bAsed on Radio-frequency Trap and LANthanide nanoprobe for LIGHT matter interaction. (SMART-LANLIGHT)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: France
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-09-01
End date: 2018-08-31
Duration (months): 24.0
Total project cost (EUR): 173076.0
EU funding (EUR): 173076.0
Participants: 1
Project status: CLOSED

Measuring and controlling light-matter interactions at the nanoscale is critical for many applications affecting both science and society, ranging from disease detection and treatment to quantum-based information science. Performing studies of these interactions requires a nano source of light, high resolution detection and accurate three dimensional manipulation. However, most of the existing nano-optical techniques offer a subset, but not all, of these elements. We propose in this project to develop a system for measuring optical fields properties on nanostructures with nano-emitter levitating by a Paul also called radio-frequency trap. We will use -but not limited to- a lanthanide doped particle as the nano-emitter. Specifically, lanthanides are sensitive to both optical electric and magnetic field so that full understanding of the optical near-field properties is achievable, in an unprecedented way. We then plan to employ this new technique for investigating nanolight-matter interactions on technologically-important nanostructures such as optical antennas, nanophotonic circuits, metamaterials etc... This new and original probing technique will open the ways to a large variety of applications such as high resolution imaging of nanophotonics components (nano-optical circuiterie, spin domain, ...) or biological samples but also e.g cancer diagnostic and therapy since lanthanide can be used for tumor cell detection and photodynamic therapy.

Keywords: lanthanide nanoparticle,near field optics,paul traps,nano manipulation
Structural Models for Text and other Unstructured Data (UnStruct)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance and management
Countries involved: Spain,United Kingdom,United Kingdom
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-09-01
End date: 2026-08-31
Duration (months): 72.0
Total project cost (EUR): 1648551.0
EU funding (EUR): 889090.74
Participants: 3
Project status: SIGNED

Most usable data is unstructured. Examples include text, transaction data, images, and web browsing histories. Although rich and plentiful, most economists do not use unstructured data. The few that do generally quantify it with off-the-shelf algorithms that are unrelated to the economic environment in which it is generated, which makes connecting it to economic models difficult. I instead propose to build novel probabilistic models of unstructured data that link it directly to relevant economic parameters. This powerful approach will use the information in unstructured data to test and estimate economic models in a way that is not currently possible with existing methods. I will focus on three distinct themes. The first studies how information about economic conditions is dispersed among agents, and how they aggregate it through interactions. This process it at the heart of the policymaking process, and the use of text data provides a unique opportunity to structurally model this information in innovative ways. The second theme jointly models unstructured data and the evolution of an economy hit by multiple, unobserved shocks. This will provide a novel forecasting tool, which is of key interest to policymakers. But it will also use unstructured data to estimate equilibrium models of the macroeconomy, and hence recover economic fundamentals. The final theme will use transaction payments between firms, and extend probabilistic models of network formation to create new definitions of markets that go well beyond anything in the current literature. This will contribute to measuring market power and the transmission of economic shocks, both questions of fundamental importance. Beyond these specific themes, my research will also pave the way for the use of probabilistic machine learning that combines novel data with clear economic models. The frameworks I introduce will provide a template for others to follow in the future.

Keywords: unstructured data,probabilistic machine learning,bayesian inference,structural modeling
Towards a neural field theory for spiking neuron networks with electrical synapses (NeuralFieldTheoriES)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Physics
Countries involved: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-01-17
End date: 2024-01-16
Duration (months): 24.0
Total project cost (EUR): 160932.48
EU funding (EUR): 160932.48
Participants: 1
Project status: SIGNED

A major challenge in statistical physics, nonlinear dynamics and theoretical neuroscience over the last half century has been to understand the self-organizing principles governing the dynamics of large networks of neurons. Physicists and applied mathematicians have proposed simple mean-field descriptions of spatially-extended neural networks in terms of a relevant macroscopic observable, the firing rate. This approach has been particularly successful and so-called Neural Field Models (NFM) have become an extremely popular mathematical tool in neuroscience, physics and applied mathematics. Yet, to date, mean-field theories describe networks with chemical synapses, but it remains a major theoretical challenge to incorporate electrical synaptic interactions in such mathematical descriptions. Recently, a mean-field theory for large networks of spiking neurons has been proposed, which exactly links the dynamics of single neurons with that of two mean-field variables: The firing rate and the mean membrane potential. Remarkably, this theory permits to incorporate electrical interactions, but the mathematical derivation and the analysis of the dynamics of the first NFM is lagging. This project proposes the formal mathematical derivation of such NFM, as well as the thorough analysis of its dynamics and bifurcations. Towards this goal, at the host institution UPF in Barcelona, the ER will apply mean-field methods and nonlinear dynamical systems theory to derive the novel NFM (which we conjecture is of reaction-diffusion type). During a secondment at VU Amsterdam, the ER will be trained to become an expert in numerical analysis of partial differential equations, which will further allow him to perform extensive state-of-the-art computer simulations. The expected results will provide completely novel mechanistic insights on the emergence of complex spatio-temporal patterns of neuronal activity due to the intricate interplay between chemical and electrical synapses.

Keywords: collective synchronization,neuronal dynamics,neuronal oscillations,neural mass and neural field models
Delivering the future of urban water transportation with novel electric hydrofoil boats (Seabubbles)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: France
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2019-03-01
End date: 2021-10-31
Duration (months): 32.0
Total project cost (EUR): 2909825.0
EU funding (EUR): 2036877.5
Participants: 1
Project status: CLOSED

Many of the cities in EU are badly congested. Congestion increases air pollution, leads to more traffic accidents & makes the cities less accessible to its dwellers. A lot of cities were built and developed along some body of water—typically 30-40% of locations are within a 10 min walk from a river bank or canal. This creates an opportunity for water-based transport that was not exploited before due to low speeds of existing boats or high emissions of their diesel engines. SeaBubbles are small, fast & very efficient electric hydrofoil craft that that can carry a driver & four passengers with a max speed of 30 km/h, while producing no emissions or noise. SeaBubbles are designed by the same world-class team has previously built the unique sailing hydrofoil trimaran that broke the speed sailing record in 2009. SeaBubbles will be operated as a water taxi service, which requires a network of mooring stations for boarding/unboarding passengers and charging the vessels. These stations will produce electricity via solar panels & hydrokinetic turbines, with the goal to make them autonomous from the grid. SeaBubbles will carry passengers between two typical urban points 2x faster than a regular taxi and at a comparable price. Our goal is to have 60+ SeaBubbles operating by the end of 2018, active in 2-3 cities globally, as well as 12+ docks, with a total electricity production of ~100 MWh and a CO2 annual reduction of ~300+ tons with revenues of €10m+. By 2024 we want to be in 50+ cities globally. Once successful, SeaBubbles will be creating jobs in vessel and mooring station manufacturing, hydrofoil craft driving as well as software development SeaBubbles are supported by the Mayor of Paris, Anne Hidalgo, and received interest of other cities in EU, and positive media coverage from Bloomberg, The Telegraph, The Verge and many others. In this Phase 2 project we will industrialize SeaBubbles and trial them is several cities in EU and in the world.

Keywords: electric,zero pollution,taxi
AI-enabled robotics platform Robo Wunderkind (Robo Wunderkind)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Austria
Call: SME instrument (H2020-EIC-SMEInst-2018-2020-3, 2020)
Start date: 2020-09-01
End date: 2022-08-31
Duration (months): 24.0
Total project cost (EUR): 2515000.0
EU funding (EUR): 1759410.0
Participants: 1
Project status: SIGNED

Currently, Europe is lagging behind the US and China in programming and robotics education as well as producing graduates in the fields of science, technology, engineering and math (STEM). Robo Wunderkind is Austrian company seeking to revolutionise the way children learn about new technologies and to help them enter the world of robotics and coding, as well as to develop STEM skills, creativity and problem-solving – skills that are increasingly essential. We brought the first generation of our award-winning robotics kit to market in late 2017, following three years of development and a successful crowdfunding campaign. Today, Robo Wunderkind, as well as the curriculum we have developed, is already used in thousands of homes and more than 500 schools around the world. Now, we are seeking to take our product offering to the next level with the support of the Horizon 2020 program. Based on our existing technology, we will develop a product of the next generation: a robotics education platform that will offer users AI-based personalised learning and content sharing functionality. 1) We are going to launch a new application that will use artificial intelligence (AI) to evaluate children’s’ learning progress, and provide recommendations and feedback; 2) We are adding a content sharing platform where users – children as well as educators and parents – will be able to share projects and other content; 3) By adding new Internet of Things (IoT) functionality, we are expanding our target group up to the age of sixteen years; 4) By bringing down the price of our entry-level robotics kit to €79, we are making it more broadly accessible to schools, educational institutions and economically disadvantaged families. 5) By developing content for children with special needs, we will cater to this niche market. These steps will allow us to establish Robo Wunderkind as a market leader in STEM education, not only in Europe but also in other key global markets.

Keywords: education,digital literacy,toys,learning,stem
Experimenting with Circular Service Business Models (CIRCULAR X)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Institutions, Governance and Legal Systems
Panel description: Political science, international relations, law
Countries involved: Netherlands
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-06-01
End date: 2025-05-31
Duration (months): 60.0
Total project cost (EUR): 1499915.0
EU funding (EUR): 1499915.0
Participants: 1
Project status: SIGNED

With increasing pressures on resources and the climate it is clear that a new business paradigm is needed. The Circular Economy has been heralded as a driver for sustainability and competitiveness. In contrast to the current linear economy, materials are kept at their highest utility at all times. Despite great policy, business and academic interest, knowledge on how to move to a Circular Economy is lacking. CIRCULAR X addresses a new and urgent issue in sustainability research: experimentation with circular service business models (CSBMs). Examples include companies shifting from selling to leasing products and introducing lifelong warrantees to extend product lifetimes. CSBMs are far from mainstream and experimentation focused on trialling new CSBMs is little understood. CIRCULAR X will develop a new field in sustainability studies: CSBM experimentation. It aims to conduct boundary-pushing and cross-sectoral interdisciplinary research in 3 continents and 5 countries – the Netherlands, UK, Sweden, China and USA - with 4 objectives: 1. Advancing understanding of CSBMs; their emergence and impacts 2. Advancing knowledge on CSBM experimentation 3. Developing CSBM experimentation tools 4. Designing and deploying CSBM experimentation labs CIRCULAR X will bridge and expand disparate knowledge on experimentation approaches across disciplines such as sustainability, design, business and entrepreneurship research. It will develop novel CSBM and experimentation concepts, catalogues, tools and labs by bridging these yet disparate fields. Through its comprehensive international approach, CIRCULAR X will deeply advance understandings on how CSBMs manifest themselves and how these can be experimented with, which will ultimately advance business activities towards a circular economy transition.

Keywords: sustainability,circular economy,sustainable innovation,sustainable innovation tools,sustainable business experiments,sustainable business models,business experimentation,product service systems