Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
INTELLIGENT PROSTHESIS SYSTEM (IPS)

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: 2018-08-01
End date: 2019-01-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Phantom pain and the risk of falling are the two major unsolved problems of leg and foot amputees. The Austrian company Saphenus Medical Technology is developing a sensory feedback system (IPS) that solves these two problems. The novelty of IPS is the «feeling prosthesis» for the leg: The authentic capturing of the gait image represents a breakthrough innovation which does not exist in the global market so far. The key market application of IPS is cost-efficient, affordable, and an optimized care for amputees. The factor of pain in the form of phantom, neuroma or stump pain puts more than 50 percent of the amputees under pressure, and more than 2 million people throughout Europe are affected by a loss of their limbs. Saphenus brings to market a prosthesis solution that reduces or makes disappear phantom pains and brings cost savings of 50-85% to existing models. Social and health insurance institutions have recognized the socio-economic benefits of this breakthrough innovation of a direct cost saving of more than EUR 24,000 per year per pain-induced prosthesis wearers.
Combining Simulation Models and Big Data Analytics for ATM Performance Analysis (SIMBAD)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Single European Sky Air Traffic Management Research
Action type: Research and Innovation actions
Partnership: SESAR (Art-187)
Countries involved: Spain,Germany,Spain,Greece
Call: Complexity and Data Science for ATM Performance (H2020-SESAR-2019-2, 2019)
Start date: 2021-01-01
End date: 2022-12-31
Duration (months): 24.0
Total project cost (EUR): 999937.5
EU funding (EUR): 999937.5
Participants: 5
Project status: CLOSED

The development of performance modelling methodologies able translate new ATM concepts and technologies into their impact on high-level, system wide KPIs has been a long-time objective of the ATM research community. Bottom-up, microsimulation models are often the only feasible approach to address this problem in a reliable manner. However, the practical application of large-scale simulation models to strategic ATM performance assessment is often hindered by their computational complexity. The goal of SIMBAD is to develop and evaluate a set of machine learning approaches aimed at providing state of-the-art ATM microsimulation models with the level of reliability, tractability and interpretability required to effectively support performance evaluation at ECAC level. The specific objectives of the project are the following: 1. Explore the use of machine learning techniques for the estimation of hidden variables from historical air traffic data, with particular focus on airspace users’ preferences and behaviour, in order to enable a more robust calibration of air traffic microsimulation models. 2. Develop new machine learning algorithms for the classification of traffic patterns that enable the selection of a sufficiently representative set of simulation scenarios allowing a comprehensive assessment of new ATM concepts and solutions. 3. Investigate the use of active learning metamodelling to facilitate a more efficient exploration of the input output space of complex simulation models through the development of more parsimonious performance metamodels, i.e., analytical input/output functions that approximate the results of a more complex function defined by the microsimulation models. 4. Demonstrate and evaluate the newly developed methods and tools through a set of case studies in which the proposed techniques will be integrated with existing, state-of-the-art ATM simulation tools and used to analyse a variety of ATM performance problems.

Keywords: big data,machine learning,data driven simulation,atm performance
Scaling Up Innovation through Analogy Mining (SIAM)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting 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 Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-01-01
End date: 2024-12-31
Duration (months): 60.0
Total project cost (EUR): 1373057.0
EU funding (EUR): 1373057.0
Participants: 1
Project status: SIGNED

Many world-changing breakthroughs in science and technology were enabled by analogical transfer, as ideas from one domain were used to solve a problem in another. Observing water led the Greek philosopher Chrysippus to speculate that sound was a wave phenomenon; an analogy to twisting a cardboard box allowed the Wright brothers to design a steerable aircraft. Despite its value for innovation, very little progress has been made towards automating the process of analogy-finding in real-world settings, and the problem has maintained a longstanding status as a "holy grail" in artificial intelligence (AI). The goal of this proposal is to tackle head-on this important problem and develop principled tools for automatically discovering analogies in large, unstructured, natural-language datasets such as patents and scientific papers. Such tools could revolutionize a variety of fields, allowing scientists and inventors to retrieve useful content based on deep structural similarity rather than simple keywords. The explosion of data available online, coupled with novel machine learning and crowdsourcing techniques, creates an unprecedented opportunity to develop novel methods to accelerate innovation and discovery. My approach explores the multiple roles AI and machine learning can play in the analogical innovation pipeline. This research will focus on the three core components of the pipeline -- (1) developing representations and similarity metrics to facilitate comparison between potential analogs, (2) imbuing the algorithms with commonsense knowledge and abstraction capabilities, and (3) guiding the adaptation of the discovered analogies to solve the original problem. For each component, the proposal demonstrates how recent advances suggest effective approaches, and describes our concrete preliminary results and ideas to serve as starting points and indicate the feasibility of this challenging project.

Keywords: analogy,innovation,data mining,text mining
Peptidomimetics with photocontrolled biological activity (PELICO)

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: Chemistry
Countries involved: Germany,Ukraine,Latvia,United Kingdom
Call: Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) (H2020-MSCA-RISE-2015, 2015)
Start date: 2016-01-01
End date: 2019-12-31
Duration (months): 48.0
Total project cost (EUR): 688500.0
EU funding (EUR): 688500.0
Participants: 4
Project status: CLOSED

The expertise, resources and specific knowledge of all participating parties will be combined to achieve a breakthrough in design, synthesis and application of peptide analogues (peptidomimetics) possessing photo-controlled biological activities, with special emphasis on anti-microbial and anti-cancer activities. The main idea behind the Project consists in chemical incorporation of artificial photo-controllable building blocks into known biologically active peptides by replacing their natural building blocks – the amino acid residues. Such a modification would provide photocontrolled peptidomimetics which can reversibly change their structure between two different photo-forms upon irradiation with light of different wavelength. The participating parties possess general know-how for design of the peptidomimetics which can exist in two photo-forms, biologically active and inactive ones, reversibly interconvertible by light of different wavelength. This opens a possibility to convert inactive peptidomimetics to active compounds by irradiation with physiologically benign light directly in tissues with very high spatiotemporal precision and can be a fundamental basis of new therapeutic strategies. The research staff exchange and other activities planned under the Project will be dedicated to accomplish four complementary work packages: (i) carrying out pharmacokinetic and toxicity studies of the photocontrolled peptidomimetics synthesized by the parties previously; (ii) evaluation of novel photocontrolled building block chemotypes for their compatibility with peptides; (iii) creation of new photocontrolled peptidomimetics, especially based on the novel building blocks and the know-how developed by the parties (e.g. using “stapled peptides” technology); (iv) multidisciplinary training of the researchers whose future work will be aimed at further development of the most advanced photocontrolled peptidomimetics as drugs suitable for photodynamic therapy.

Keywords: anticancer peptides,antimicrobial peptides,molecular photoswitches,photodynamic therapy,photocontrolled drug candidates
Enough to feed an army. Carthaginian rural exploitation during the late third century BC (ETFA)

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: Belgium
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-09-01
End date: 2017-08-31
Duration (months): 24.0
Total project cost (EUR): 160800.0
EU funding (EUR): 160800.0
Participants: 1
Project status: CLOSED

Between 237 and 202 BC, the Carthaginian Empire due to both its territorial ambitions and, above all, its conflicts with Rome and several indigenous peoples of the Iberian Peninsula and North Africa, was forced to keep large numbers of troops permanently mobilized. This military-political circumstance led to a series of major changes in many areas of the Carthaginian economic, political and social system. Through this project we will analyze in detail the extent to which the military mobilization affected agriculture, the very basis of the ancient economy, and the related politics adopted by the ruling elites of the Carthaginian Empire. This project, therefore, includes a quantitative study of the productive capacity of the Carthaginian empire in the late third century BC; an analysis of the logistics during the Second Punic War (218-201 BC); an appreciation of the relationship of war veterans with agricultural production at this chronological context; and a comparison of these results with those obtained in a specific casus: a survey of part of the territory under the rule of the Phoenician city of Utica, a North-African city under the Carthaginian rule.

Keywords: rural archaeology,second punic war,carthage,western mediterranean,economy,society
Delivering services on behalf of H2020 for enhancing the innovation management capacity of SMEs by the Enterprise Europe Network in Flanders (VEBIN SME 2.0)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Specific Grant agreement
Countries involved: Belgium
Call: Enhancing the innovation management capacity of SMEs (H2020-Adhoc-2014-20, 2014)
Start date: 2015-01-01
End date: 2016-12-31
Duration (months): 24.0
Total project cost (EUR): 273195.0
EU funding (EUR): 273195.0
Participants: 2
Project status: CLOSED

This proposal aims at continuing the services of EEN in Flanders with regard to the key account management for the SME instrument under the H2020 programme as entrusted by the European Commission to the Enterprise Europe network. It also concerns the additional support services that EEN will deliver in Flanders with regard to the enhancement of the innovation management capacities of SMEs as decided in the H2020 programme. The present proposal describes how the Flemish VEBIN consortium - being selected for delivering the EEN services in Flanders -will deliver the services concerned in their region in 2015 and 2016, how these will be coordinated with the H2020 NCP for SMES in Flanders, how the services will be embedded in the regional innovation support system to the benefit of Flemish companies, how the consortrium will manage the services and how feedback will be organised in order to ensure a high quality service provision and an added European value, while respecting the principles of additionality. It particularly reflects on the signposting of clients among all relevant support stakeholders and to the efficient use of resources and tools. It also confirms the consortium's willingness to cooperate whenever requested by EAME or the Commission to share best practices among the participating EEN consortia and to give feedback on the implementation of the services in the region of Flanders (Belgium).

Keywords: innovation management capacity enhancement,key account management sme instrument
Engineering Biohybrid MicroRobots from Magnetic Swimmers and S-layers (Microrobots)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Biotechnology and Biosystems Engineering
Panel description: Biotechnology using all organisms, biotechnology for environment and food applications, applied plant and animal sciences, bioengineering and synthetic biology, biomass and biofuels, biohazards
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2018-STG, 2018)
Start date: 2018-11-01
End date: 2024-04-30
Duration (months): 66.0
Total project cost (EUR): 1766481.0
EU funding (EUR): 1766481.0
Participants: 1
Project status: SIGNED

Biohybrid MicroRobots (BMRs) are conceptual microscopic robotic devices that combine synthetic and biological components and can be remote controlled to a specific destination, attach to a target and perform a bespoke biochemical operation at nanoscale precision. Within the 5-year Microrobots project, I intend to develop innovative BMRs by combining magnetic swimmers (MSs) with prokaryotic S-layers (SLs). MSs are microscopic devices that consist of two flexibly linked metallic beads with different magnetic properties and can be remote controlled through liquid media, simply by applying oscillating magnetic fields. SLs are highly stable 2-dimensional protein arrays that form resilient cell wall components in archaea and bacteria and can be genetically modified and reassembled on inorganic surfaces. I will introduce affinity tags into selected archaeal and bacterial SLs and reassemble them on the surfaces of MSs. This will coat MSs with unique affinity matrices, on which bioactive molecules can be conjugated at regular arrays, high density and defined distance. Through this strategy, I will generate BMRs that can be equipped with any bioactive functionality provided by nature, such as adhesive filaments, enzymes, antibodies, reporters, drug cargo or any other thinkable functional molecule. The BMRs that I will develop will elegantly miniaturise robotics and enable us to deliver bioactivity at nanometre precision. This will provide a revolutionary platform technology that will be applicable in a plethora of fields, such as medicine, nanotechnology, environmental engineering or scientific exploration and generate a real step change in the ways in which we build new materials, engineer our environment, fight disease and explore the universe in the 21st century.

Keywords: cryoem,magnetic swimmers,s layers,adhesive filaments,affinity tags
Flying Electromagnetic Toroids (FLEET)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: United Kingdom
Call: ERC Advanced Grant (ERC-2017-ADG, 2017)
Start date: 2018-10-01
End date: 2024-03-31
Duration (months): 66.0
Total project cost (EUR): 2570198.0
EU funding (EUR): 2570198.0
Participants: 1
Project status: SIGNED

In this project I will study the generation, detection, and interaction with matter of Flying Toroids, a new type of light pulses never experimentally studied before. This represents an exciting opportunity to advance optics and electromagnetism in a radically new direction since Hertz, Marconi, Popov and Tesla developed technology for generating, detecting, and communicating with transverse electromagnetic waves. Conventional transverse electromagnetic waves propagate in free-space with the electric and magnetic field vectors perpendicular to the wave propagation direction, forming the famous triad. Theoretical analysis of recent years has shown that another, very different type of waves exists, which propagate at the speed of light, but only occur as short bursts of electromagnetic energy in the form of Flying Toroids. Flying Toroids are inseparable solutions of Maxwell equations with a unique, doughnut-like configuration of the electric and magnetic fields. Flying Toroids interact with matter in unique ways, drastically different from that of conventional electromagnetic pulses. In a broader context, the electrodynamics of Flying Toroids is an exciting emerging field of optical science linked to intriguing recent developments in physics such as toroidal dipoles and anapoles, and, due to their topology, to Majorana fermions and skyrmions. Building on my recent proof-of-principle demonstration of Flying Toroid generation through conversion of few-cycle conventional transverse light pulses in artificial photonic nanostructures, my goal for this project is to experimentally study and understand the fundamental properties of Flying Toroids and their interaction with matter at optical frequencies, and to assess their potential for developing new technologies. In my vision this project can lead to spectacular new opportunities for spectroscopic and light-enabled applications, and will impact on other branches of science, from astronomy to solid-state physics.
Developing the predictive ecology of plant-animal interactions across space and time (Ecol of interactions)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced 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
Call: ERC Advanced Grant (ERC-2017-ADG, 2017)
Start date: 2018-10-01
End date: 2025-03-31
Duration (months): 78.0
Total project cost (EUR): 2499930.0
EU funding (EUR): 2499930.0
Participants: 1
Project status: SIGNED

In the face of the alarming pace of recent environmental change we lack the tools to accurately predict how biodiversity and ecosystem services will respond. One key gap in knowledge that limits our predictive ability is uncertainty concerning how the biotic interactions will change. Developing a predictive science of species interactions requires integrating evolutionary, biogeographic and ecological mechanisms acting at different spatial and temporal scales. We will use a hierarchical cross-scale approach, combining phylogeography, network ecology, statistical modelling and experiments, to disentangle the mechanisms governing species richness and mutualistic interactions in tropical hummingbirds and their food plants. Hummingbirds and their food plants are an excellent model system because they are highly diverse, highly specialized, and logistically feasible to study. Our objectives are to (1) evaluate the influence of factors, such as trait-matching, environmental conditions and relatedness, on network structure; (2) quantify how and why interaction beta-diversity (i.e., reflecting the change in both species composition, and in interacting partners) changes across elevation gradients in each of three biogeographic regions with distinct evolutionary histories (mountain regions in Costa Rica, Ecuador, Brazil); (3) evaluate the importance of multiple factors, such as trait-matching, environmental conditions, relatedness and abundance, on species interactions and network structure; and (4) develop a predictive model of species interactions and evaluate its performance using cross-validation and experimentation. Together, these tasks will provide new insight into one of the central enigmas in ecology, namely, why species diversity and its interaction architecture change across space and time. We will also be able predict how species interactions will change from present to the future, which is essential for the conservation of biodiversity and ecosystem services.

Keywords: tropical ecology,avian ecology,network ecology,beta diversity,species interactions,maintenance of diversity,spatial variation
“Swiss EEN Innovation Support actions for SMEs” in the frame of the European Innovation Council programme 2020-2021. (SwissEENissme3.0)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Switzerland,Switzerland
Call: H2020 ENTREPRISE EUROPE NETWORK GA4 2020-2021 (H2020-EEN-GA4, 2019)
Start date: 2020-01-01
End date: 2021-12-31
Duration (months): 24.0
Total project cost (EUR): 681047.5
EU funding (EUR): 681047.0
Participants: 2
Project status: CLOSED

Innovation support and enhancement measures for Swiss SMEs in the frame of the European Innovation Council Program and delivered by the Swiss EEN consortium in the years 2020 and 2021.