Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
THE FIRST EFFECTIVE BIOCIDE-FREE ENVIRONMENTALLY-HARMLESS ANTIFOULING COATING FOR THE BOATING INDUSTRY (ABIO)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Austria
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-11-01
End date: 2019-02-28
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Boat hulls submerged in both sea- and fresh-water environments are gradually colonised by natural organisms, a process called biofouling. Biofouling represents a significant problem for boat and ship operations, as it damages hulls, increases water drag leading to loss of manoeuvrability, delays in shipping and increased fuel consumption, inevitably increasing greenhouse emissions by up to 40%. Current antifouling products are most commonly biocidal, due to their 97% efficacy. These biocides accumulate in the environment and contain components harmful to humans and marine eco-systems in high quantities. Many biocides are gradually being banned in the EU. Although non-biocidal alternatives exist in the form of foul-release agents, these methods have limited efficacy. We, Acorros, have developed ABIO, the first non-biocidal antifouling coating, combining repellence with release to give 97% efficacy up to 2 years! ABIO is harmless to the marine and human environment and requires 44-56% less coating than existing solutions. ABIO readily adheres to hulls without the need for primers and can be removed using a high-pressure water hose, avoiding abrasion or sanding. ABIO offers effective savings in paint and labour costs of up to €720 per application per 10 m boat, in addition to being gentle on the hull and thus preserving its integrity for longer. ABIO can be used in salt- or fresh-water environments and on all hull types: steel, fibreglass, aluminium, wood, and rubber. Minor repairs/reapplication are uniquely possible underwater. ABIO, our most commercially-ready and innovative solution, is a first-mover in effective non-biocidal antifouling coatings, at a time when growth in the antifouling coatings industry is being slowed down by incoming regulations on biocides. We will enter this market via the recreational boating segment, expecting to sell through dealers and wholesalers to achieve a market share of 2.5% by 2025, by reaching 150,000 boat owners at 2,000 marinas.

Keywords: ecological antifouling,marine environment,boat surface protection
A handheld, ultra-sensitive device for rapid contactless explosive vapour detection in open air, based on Ion Mobility Universal Sensor Technology (I-MUST)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Action type: SME instrument
Countries involved: Netherlands
Call: Engaging SMEs in security research and development (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-12-01
End date: 2017-03-31
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Explosives detection currently represents the biggest security challenge, being easy to acquire with limited resources and difficult to be detected in real-time. Recommended procedures for explosive detection are inherently unsafe: due to current technological limitations, EU regulations only prescribe screenings on a variable percentage of randomly chosen passengers. Being not portable, such devices can only be installed at screening lines - but in Brussels 2016 explosions happened way before them. Moreover, existing devices just allow to analyse swabbed points instead of the passengers’ total body. In the meantime, those procedures are slow (up to 30 s/passenger) and intrusive, requiring physical contact (swabbing): two major drawbacks, considering that airports competition is based today on passenger experience. Eye on Air developed I-MUST, a handheld disruptive device based on a proprietary, ultra-thin and high sensitive Ion Mobility Spectrometry sensor. Embedded into I-MUST, it ensures the most secure detection of explosives, with a sensitivity 500 times higher than its competitors (0.1 ppb) and the detection of >150 compounds, i.e. 3 to 5 times more compounds than currently used technology. I-MUST can be used not only at screening lines, but everywhere in public places, allowing to introduce the concept of a “distributed security” and, thanks to the brief time of analysis (2 s), 100% passengers can be scanned. By using short ion beams and a small, annular drift space, Eye on Air obtained such performing, enabling technology, whose features have already been confirmed in October 2015 by TNO, the Dutch research institute devoted to the certification of airport screening devices. During Phase 1 project, Eye on Air will assess the scale-up industrialization plan and will evaluate a sound go-to-market strategy to ensure successful commercialization of the I-MUST device for airport explosive detection.

Keywords: security,explosive,explosive vapour detection,explosive trace detection,volatile organic compounds,ion mobility spectrometry,contactless,airport
Entrepreneurial Management for Fostering Innovation and Talents (EM4FIT)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Economic Sciences
Countries involved: Spain,Spain,Italy,Argentina,China,France,Japan,Morocco,Peru,Viet Nam,Denmark,Denmark
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2019, 2019)
Start date: 2020-01-01
End date: 2025-10-31
Duration (months): 70.0
Total project cost (EUR): 611800.0
EU funding (EUR): 611800.0
Participants: 17
Project status: SIGNED

Entrepreneurial management practices play a pivotal role in taking entrepreneurial knowledge and utilizing it towards innovation and talent development, ultimately creating growth and increasing the effectiveness of both new business venturing as well as small- and medium-sized enterprises (SMEs). EM4FIT investigates entrepreneurship and related management practices from an interdisciplinary and multi-level angel as important variables in the interplay between individual, organization and institutional contexts within and between advanced and emerging markets. EM4FIT aims to better understand entrepreneurial management practices both from an individual (intra-organisational) as well as comparative market perspective (inter-organisational). Research will be carried out with an emphasis on the impact of institutions and context on the EU. With the exchange among 16 partners from four continents and between the academic and non-academic sector, EM4FIT brings together knowledge from advanced as well as emerging markets to further understand how entrepreneurs and managers create successful businesses and foster growth. The generated knowledge will be disseminated around the world to enhance the impact of the European entrepreneurial spirit. Involving 67 researchers, managers, technical and administrative staff, the EM4FIT involves seven work packages (WP). In addition to project management and communication, dissemination and outreach activities, five WPs focus on research, training and dissemination at multiple levels: institutional-organizational-individual. With this project structure and the competitive capability of 16 partners involved, EM4FIT will generate high impact both in terms of research excellence and societal engagement. The mix between non-academic and academic participants is designed to create knowledge relevant for businesses and society alike.

Keywords: entrepreneurship,entrepreneurial management,innovation,context,talents
The Evolution Problem in General Relativity (EPGR)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: France
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-05-01
End date: 2022-10-31
Duration (months): 66.0
Total project cost (EUR): 1455000.0
EU funding (EUR): 1455000.0
Participants: 4
Project status: CLOSED

General relativity has been introduced by A. Einstein in 1915. It is a major theory of modern physics and at the same time has led to fascinating mathematical problems. The present proposal focusses on two aspects of the evolution problem for the Einstein equations which has been initiated by the pioneering work of Y. Choquet-Bruhat in 1952. The Einstein equations form a nonlinear system of partial differential equations of hyperbolic type whose complexity raises significant challenges to its mathematical analysis. The goal of this project is to strengthen our understanding of two important themes concerning the evolution problem in general relativity. On the one hand, the control of low regularity solutions of the Einstein equations, a topic which is intimately linked with the celebrated cosmic censorship conjectures of R. Penrose, a major open problem in the field. On the other hand, the question of the stability of particular solutions of the Einstein equations in the wake of the groundbreaking proof of the stability of the Minkowski space-time due to D. Christodoulou and S. Klainerman. These directions are extremely active and have recently led to impressive results. More specifically, this project proposes to consider the following two work packages -Going beyond the bounded L2 curvature theorem. This result has been recently obtained by the PI in collaboration with S. Klainerman and I. Rodnianski and is the sharpest result in so far as low regularity solutions of the Einstein equations are concerned. Yet, the fundamental quest towards a scale invariant well-posedness criterion for the Einstein equations remains wide open. -The black hole stability problem. This problem concerns the stability of the Kerr metrics which form a 2-parameter family of solutions to the Einstein vacuum equations. Many results have been obtained concerning various versions of linear stability, but significant challenges remain in order to tackle the nonlinear stability result.

Keywords: einstein equations,cauchy problem,low regularity solutions,black hole stability problem
Information Theory beyond Communications: Distributed Representations and Deep Learning (STRUDEL)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: France,Canada
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-09-01
End date: 2020-08-31
Duration (months): 24.0
Total project cost (EUR): 171349.2
EU funding (EUR): 171349.2
Participants: 2
Project status: CLOSED

Deep learning is an enormously successful recent paradigm with record-breaking performance in numerous applications. Individual autoencoders (AEs) of a multilayer neural network are trained to convert high-dimensional inputs into low-dimensional codes that allow the reconstruction of the input. Although some explanations appear to be solidly grounded, there is no mathematical understanding of the AE learning process. This project is a collaborative endeavor of researchers with strong complementary backgrounds. Its main innovation is the idea to capitalize on powerful and fertile concepts from information theory (expertise of researcher) in order to advance the state of the art in deep learning (expertise of supervisor at TC). The innovative research work is motivated by our recent insight that there is an intimate relationship between AEs, generative adversarial nets and the information bottleneck method. This method is a model-free approach for extracting information from observed variables that are relevant to hidden representations or labels and will serve as basic building block for an information theory of representation learning. The planned objectives are split into 3 workpackages: 1) information-theoretic criteria and statistical tradeoffs for extracting good representations, 2) structured architectures/algorithms for learning, 3) use of stochastic complexity to assess the descriptive power (model selection) of deep neural networks. Accomplishing the challenging goals of this proposal requires a variety of methodologies with a rich potential for transfer of knowledge between the involved fields of information theory, statistics and machine learning. Our new framework is expected to bridge the gap between theory and practice to facilitate a more thorough understanding and hence improved design of deep learning architectures. The fellow researcher is coordinating the LIA Lab of the CNRS (started in 2017) where he is collaborating with the supervisor at TC

Keywords: machine learning,deep learning,information theory,autoencoder,unsupervised learning,supervised learning,learning algorithms,distributed representations,neural networks
Harmless Respiration for Intensive Care Patients decreasing mortality and shortening stays – including COVID-19 patients (Jane)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Netherlands
Call: SME instrument (H2020-EIC-SMEInst-2018-2020-3, 2020)
Start date: 2020-08-01
End date: 2022-10-31
Duration (months): 27.0
Total project cost (EUR): 3608092.5
EU funding (EUR): 2498539.75
Participants: 1
Project status: CLOSED

The current outbreak of COVID-19 is incisively pointing towards the importance of optimal mechanical ventilation in Intensive Care. Improved mechanical ventilation saves lives. Last year, we have seen multiple cases in which our mechanical ventilator suited only for the Operating Room (OR), was used off-label in ICU to ventilate severely lung-ill patients. Doctors claim patients would have died if our device would not have been used. These case reports are supported by more fundamental evidence published in March 2020: in-vivo studies on pigs having similar lung-illness as with the current COVID-19 outbreak (called Acute Respiratory Distress Syndrome) have shown superior result with our disruptive ventilation method, called FCV®. Half of all patients on higher grade Intensive Care Units need mechanical ventilation. However, current ventilation methods are known to damage the lungs in these vulnerable patients. This significantly prolongs ICU stay and increases mortality. The damages relate to the passive expiratory phase during mechanical respiration, which is fast and uncontrolled resulting in shear stress and collapse of the distal lung parts. Prolonged ventilation then initiates inflammatory responses in the lungs. We have developed a new ventilation method controlling the expiration, preventing lung damage. In 2017 our innovative OR ventilator (Evone) was brought to the market. Having performed over 1,000 OR patient cases and 5 small clinical studies till date, clear superior ventilation and improved lung mechanics has been shown. However, the largest unmet medical need related to ventilation is on ICU. The objective of this proposal is to bring this superior ventilation technology to ICUs in Europe, the Middle East and in 2nd phase the USA and by that, lower ICU mortality by 20% and ICU stay with 15%. This means 44,800 lives to be saved in European ICUs, each year (valued at € 90 billion) and a reduction of €2 billion in annual European healthcare costs.

Keywords: covid 19,intensive care medicine,mechanical respiration,ards,lung damage,vili,health care economics
MuFFIN - Modelling Foraging Fitness in Marine predators (MuFFIN)

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: Environment and Geosciences
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-01-01
End date: 2022-12-31
Duration (months): 24.0
Total project cost (EUR): 196707.84
EU funding (EUR): 196707.84
Participants: 1
Project status: CLOSED

MuFFIN - Modelling Foraging Fitness in Marine predators Recent technological advances have permitted the collection of novel high-frequency information about animal behaviour, physiology and characteristics of the environment in which animals move. Such technology-driven achievements are exciting, but it is important to analyse these data with a view to their original objectives: understanding individual behaviour, predicting population processes and optimizing species monitoring and conservation programs. Despite a growing number of tracked animals, long term movement dataset are a present-day achievement. As a consequence, while many studies of animal movements are motivated by questions on population dynamics, the explicit connection between the two is rarely attained. Through MUFFIN, I will make use of nearly ten years of high resolution bio-logging datasets collected on three species of top marine predators moving in environments difficult to monitor: Little penguins, Adelie penguins and Southern elephant seals. With these unique data, MUFFIN will answer questions related to effects of changes of availability of marine resources on breeding success, predators foraging behaviour, decision making and habitat use. I will (I) quantify changes in foraging behaviour across spatio-temporal scales, characterise type of foraging patches visited and energy spent. I will (II) model the effect of foraging patches visited, energy spent and environment encountered aiming to understand animal decision making, use of environmental features and changes in space used. I will (III) link foraging behaviours, effort spent and type of patch to breeding success, highlighting fitness consequences of changes of behavioural patterns. In accomplishing MUFFIN's objectives I will open powerful new avenues for the use and analysis of large high resolution movement data. These approaches are key for research seeking to optimise strategies for habitat management, species monito

Keywords: foraging ecology,bio logging,movement ecology,animal decision making,marine predators,fitness,habitat use,population processes,marine spatial planning
Atomic Research for Topological Engineering (ARTE)

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: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-05-01
End date: 2017-04-30
Duration (months): 24.0
Total project cost (EUR): 158121.6
EU funding (EUR): 158121.6
Participants: 1
Project status: CLOSED

Topological quantum computation (TQC) deals with the transformations related to the overall shape (“topology”) of a quantum trajectory to perform operations on data and go beyond the limitations of quantum computation. It is a revolutionary technique because it will allow quantum operations to be error free and robust while taking advantage of the radically new approaches of quantum computation, which means smaller systems, less energy dissipation, and faster processing. TQC may be naturally implemented using atomic scale systems such as those created by atomic manipulations with scanning probe techniques. The present project is to lay the foundations to make TQC possible. These foundations are the discovery of new exotic states of matter by developing the science and technology of 1-D chains of magnetic moments on superconductors. This implies multi-disciplinary training in single-molecule chemistry, fabrication of superconducting materials, atomic scale magnetic devices and quantum-computation principles. The project is aimed at creating unique career perspectives by learning skills in the atomic engineering of topological superconductors which will grant Dr. Choi a leading independent position. Intersectoral secondments will be used to explore industry interest in developing TQC as a high-value added technology.

Keywords: topological quantum computation,majorana bound states,atom manipulation,superconducting surface,atomic and molecular spin chains
Airline Maintenance Operations implementation of an E2E Maintenance Service Architecture and its enablers (AIRMES)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Clean Sky 2
Action type: Research and Innovation actions
Partnership: CS2 (Art-187)
Countries involved: Germany,Switzerland,France,France,France,France,Netherlands,United Kingdom,United Kingdom,Portugal,Portugal
Call: Airline Maintenance Operations implementation of an E2E Maintenance Service Architecture and its enablers (H2020-CS2-CFP01-2014-01, 2014)
Start date: 2015-12-01
End date: 2019-11-30
Duration (months): 48.0
Total project cost (EUR): 5189207.5
EU funding (EUR): 4606046.0
Participants: 12
Project status: CLOSED

The AIRMES project focusses on optimising end-to-end maintenance activities within an operator’s environment. It will develop and validate an innovative, state-of-the-art, integrated maintenance service architecture that will be a key step in achieving the goal of no technically-induced aircraft operational disruptions in European air traffic. The AIRMES consortium is led by an airline / MRO that has a clear vision, and is keen to exploit radically new and challenging ways to achieve their objectives. They are supported by expertise in systems health monitoring, semantics, knowledge based engineering, architecture, diagnostics, prognostics, maintenance planning and optimisation, and mobile tools for remote support of maintenance activities. Truly a unique consortium. The service architecture will be structured around an operationally focused collaborative environment IT platform, integrating multiple functionalities and it will accelerate the shift in European aviation, from scheduled maintenance to condition-based maintenance. By blending this knowledge based environment with mobile tools for remote support, using augmented reality technologies and two way communication solutions, the resulting service architecture will provide contextualised, updated and integrated information to all members of the maintenance value chain. The impact of this project on European Air Traffic will be significant. In Europe, 5.8% of all flights are delayed due to direct aircraft technical causes and consequential delays on subsequent flights; the cost of this disruption is estimated at 2.8 B€. By reducing operational disruptions, reducing the average delay time and improving aircraft utilisation, through a grant value of 4.6 M€, the impact of this 48 month, 12 partner AIRMES project will be significant and assessed to around 1B€ per year.

Keywords: optimising end to end maintenance activities,systems health monitoring,prognostics,mobile tools,maintenance planning and performance optimisation,real life operational environment