Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Next generation meta-material based SMART and FLEXible optical solar reflectors (SMART-FLEX)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling advances in space technology
Action type: Research and Innovation actions
Countries involved: Italy,Spain,Italy,Italy,United Kingdom,Denmark
Call: Generic space technologies (H2020-SPACE-2018, 2018)
Start date: 2019-01-01
End date: 2021-12-31
Duration (months): 36.0
Total project cost (EUR): 2047657.5
EU funding (EUR): 2047657.5
Participants: 7
Project status: CLOSED

SMART-FLEX aims at developing a radically new type of Optical Solar Reflector (OSR), that combines the flexibility and ease of use of Silver / Teflon foils with the performance and durability of quartz tile OSRs and with the temperature variable emissivity of Smart Radiation Devices. The new OSR will consist of an extremely thin, fully inorganic, metamaterial coating deposited on the first, space-facing surface of a flexible foil. The SMART-FLEX product that we envision is implemented on a 2 MIL foil of A4 or larger format, with an integrated pressure sensitive and conductive adhesive on the back side, and can be easily applied on the outer skin of radiator panels, or on other planar, curved or bendable structure directly exposed to the space environment.

Keywords: temperature variable emitters,flexible optical solar reflectors,metamaterials,thermochromic materials,perfect metamaterial absorbers,smart radiation devices,thin film multi layers
GaN Transistor Integrated Circuits (EleGaNT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling European competitiveness, non-dependence and innovation of the European space sector
Action type: Research and Innovation actions
Countries involved: Germany,Belgium,Belgium,France,France
Call: Technologies for European non-dependence and competitiveness (H2020-SPACE-2020, 2020)
Start date: 2021-01-01
End date: 2023-12-31
Duration (months): 36.0
Total project cost (EUR): 2475024.25
EU funding (EUR): 2473774.25
Participants: 6
Project status: SIGNED

Discrete GaN power electronic devices have penetrated the consumer market and first products have amply demonstrated a disruptive improvement of the performance and reduction of the form factor. With demonstrated robustness for heavy ion radiation and neutron radiation, p-GaN enhancement mode HEMTs allow disruptive innovative designs for space applications. However, to unlock the full potential of the technology for point of load convertors, three important limitations need to be solved, as addressed in this project, i.e. 1) the reduction of the inductive parasitics through monolithic integration of drivers and power devices (GaN-IC) 2) optimization of the inductive passive components together with the active devices 3) a strong interaction between point of load convertor design and GaN-IC design. Electrical performance and radiation robustness will be evaluated and assessed for space applications in the upcoming frame of satellites massive digitalization. The project with duration of 36 months, comprises of two learning cycles in definition and refinement of the application requirements, design and manufacturing of the GaN-ICs and passive devices, and development of the point of load convertor boards, first with focus on the basic building blocks and initial prototypes, followed by further optimization towards the target requirements. The consortium has been joined by Thales Alenia Space (France and Belgium) and Würth Elektronik as space and terrestrial point of load convertor manufacturers. IMEC contributes with its state-of-art GaN-IC platform technology and Würth Elektronik with the design and prototype manufacturing of the passives. MinDCet designs the optimized GaN-ICs and contributes with a state-of-art controller. This project contributes to EU non-dependence of GaN technology as discrete GaN transistors are, so far, mostly produced by Asian and/or North American manufacturers and pushes the state-of-the-art with higher level of integration (GaN-IC).

Keywords: gallium nitride gan,gan ic,point of load convertors pol,space applications
Monitoring Biodiversity from Space (BIOSPACE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Institutions, Governance and Legal Systems
Panel description: Political science, international relations, law
Countries involved: Netherlands,Netherlands
Call: ERC Advanced Grant (ERC-2018-ADG, 2018)
Start date: 2019-09-01
End date: 2024-08-31
Duration (months): 60.0
Total project cost (EUR): 2470315.0
EU funding (EUR): 2252676.25
Participants: 2
Project status: SIGNED

Life, with all its diversity, is in crisis. As humans increasingly encroach on biologically complex semi- natural landscapes, no organism, place or ecological function remains unaffected. While all 196 parties (195 countries plus the European Union) to the UN Convention on Biodiversity (CBD) have agreed to monitor the state of biodiversity, the currently available methods to do so leave much to be desired. Traditional monitoring involves the field observation of species by trained specialists, aided by skilled volunteers, whose expertise is restricted to specific biotic groupings. In a process that is both time consuming and inconsistent across time and space, botanists identify and record the presence of plant species and ornithologists the bird biota, resulting in 'unpopular' biotic groups such as fungi, bacteria and insects being under-observed or escaping identification altogether. In this project, a fundamentally different approach to terrestrial biodiversity monitoring couples next generation satellite remote sensing with environmental DNA (eDNA) profiling, complemented where available by legacy human-observed datasets. Satellite remote sensing is able to survey the environment as a single, continuous, fine-resolution map, while eDNA profiling can rapidly quantify much greater taxonomical and functional breadth and depth than human field observation. This project combines, for the first time, these two powerful, cutting-edge techniques for monitoring biodiversity at the global level in a consistent manner. Following from this, another key innovation will be the deepening of our scientific understanding of how biodiversity is impacted by anthropogenic pressure as well as by natural environmental gradients. In concert, these scientific developments will enable the accurate and fine grain monitoring of biodiversity from space – a ground-breaking contribution to the quest to meet the UN Sustainable Development Goals and CBD Aichi targets.
Learning from Big Code: Probabilistic Models, Analysis and Synthesis (BIGCODE)

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: Switzerland
Call: ERC Starting Grant (ERC-2015-STG, 2015)
Start date: 2016-04-01
End date: 2021-03-31
Duration (months): 60.0
Total project cost (EUR): 1500000.0
EU funding (EUR): 1500000.0
Participants: 1
Project status: CLOSED

The goal of this proposal is to fundamentally change the way we build and reason about software. We aim to develop new kinds of statistical programming systems that provide probabilistically likely solutions to tasks that are difficult or impossible to solve with traditional approaches. These statistical programming systems will be based on probabilistic models of massive codebases (also known as ``Big Code'') built via a combination of advanced programming languages and powerful machine learning and natural language processing techniques. To solve a particular challenge, a statistical programming system will query a probabilistic model, compute the most likely predictions, and present those to the developer. Based on probabilistic models of ``Big Code'', we propose to investigate new statistical techniques in the context of three fundamental research directions: i) statistical program synthesis where we develop techniques that automatically synthesize and predict new programs, ii) statistical prediction of program properties where we develop new techniques that can predict important facts (e.g., types) about programs, and iii) statistical translation of programs where we investigate new techniques for statistical translation of programs (e.g., from one programming language to another, or to a natural language). We believe the research direction outlined in this interdisciplinary proposal opens a new and exciting area of computer science. This area will combine sophisticated statistical learning and advanced programming language techniques for building the next-generation statistical programming systems. We expect the results of this proposal to have an immediate impact upon millions of developers worldwide, triggering a paradigm shift in the way tomorrow's software is built, as well as a long-lasting impact on scientific fields such as machine learning, natural language processing, programming languages and software engineering.

Keywords: programming languages,program synthesis,machine learning,natural language processing
The evolutionary significance of synonymous variations: Can codon usage preferences drive the propagation of antibiotic resistance? (HGTCODONUSE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: France
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-06-01
End date: 2022-05-31
Duration (months): 72.0
Total project cost (EUR): 1992366.0
EU funding (EUR): 1992366.0
Participants: 1
Project status: CLOSED

The intensive use of antibiotics provided an unprecedented improvement in infectious disease treatments but at the expense of creating ideal conditions for the selection of widespread resistance. Propagation of antibiotic resistances is favoured by horizontal gene transfer and by bacterial life in multispecies community. However, compositions of resistome and bacterial communities are often correlated, suggesting that propagation of resistances does not occur at random. This project will test the hypothesis that mismatch in codon preferences between the transferred genes and the receiving genome is a fundamental factor shaping resistome structure and evolution. Such central role of codon preferences may have been hitherto overlooked. The project combines mutant collection characterization, experimental evolution approaches –one in a multispecies context and one in a variable environment context-, full genome sequencing of evolved populations, phylogenomics and mathematical modelling integrating the experimental results of the other approaches, and generating a predictive tool about the evolutionary outcome of various real-life situations.

Keywords: horizontal gene transfer,antibiotic resistance,codon usage preferences,microbiota,experimental evolution
Guiding European Policy toward a low-carbon economy. Modelling Energy system Development under Environmental And Socioeconomic constraints (MEDEAS)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Robust decision making and public engagement
Action type: Research and Innovation actions
Countries involved: Austria,Spain,Austria,Spain,Italy,Spain,Bulgaria,Greece,Belgium,Czechia,United Kingdom
Call: Modelling and analysing the energy system, its transformation and impacts (H2020-LCE-2015-2, 2015)
Start date: 2016-01-01
End date: 2019-12-31
Duration (months): 48.0
Total project cost (EUR): 3735308.75
EU funding (EUR): 3735308.75
Participants: 12
Project status: CLOSED

The transition to a low carbon economy needs to achieve multiple aims: competitiveness, protection of the environment, creation of quality jobs, and social welfare. Thus policy-makers and other key stakeholders require tools that need to focus beyond the energy sector by including these other domains of economy, society and the environment. Currently, most available tools lack integration of these important areas despite being tightly connected to the energy sector. Moreover, current energy modelling tools often lack documentation, transparency and have been developed for a specialized insider audience, which makes validation and comparison of results as well as independent review impossible. Our project aims to solve the current needs of integration and transparency by developing a leading-edge policy modelling tool based on WoLiM, TIMES and LEAP models and incorporating Input-Output Analysis, that allows for accounting of environmental, social and economic impacts. The modular design of the tool will take into account the necessary flexibility to deal with different levels and interests of stakeholders at great sectorial and spatial detail. Finally, transparency will be achieved through an open access freeware distribution of the model based on the open access programming language (Python), providing a detailed user manual, addressed to a wider non-specialist audience, and including free internet courses and learning materials.

Keywords: transition,modelling,low carbon economy,environment,society
USER-CENTRIC MANAGEMENT OF SECURITY AND DEPENDABILITY IN CLOUDS OF CLOUDS (SUPERCLOUD)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Theme: Future Internet: Software, hardware, Infrastructures, technologies and services
Action type: Research and Innovation actions
Countries involved: Germany,Austria,Switzerland,France,France,Netherlands,Portugal,Portugal
Call: Advanced Cloud Infrastructures and Services (H2020-ICT-2014-1, 2014)
Start date: 2015-02-01
End date: 2018-01-31
Duration (months): 36.0
Total project cost (EUR): 6863279.0
EU funding (EUR): 5398280.0
Participants: 12
Project status: CLOSED

Today, despite its unravelling business benefits, distributed cloud computing raises many security and dependability concerns. Root causes include increase in complexity and lack of interoperability between heterogeneous, often proprietary infrastructure technologies. SUPERCLOUD thus proposes new security and dependability infrastructure management paradigms that are : 1) user-centric, for self-service clouds-of-clouds where customers define their own protection requirements and avoid lock-ins; and 2) self-managed, for self-protecting clouds-of-clouds that reduce administration complexity through automation. SUPERCLOUD will reach the following objectives: -Self-Service Security: Implementation of a cloud architecture that gives users the flexibility to define their own protection requirements and instantiate policies accordingly. -Self-Managed Security: Development of an autonomic security management framework that operates seamlessly over compute, storage and network layers, and across provider domains to ensure compliance with security policies. -End-to-End Security: Proposition of trust models and security mechanisms that enable composition of services and trust statements across different administrative provider domains. -Resilience: Implementation of a resource management framework that composes provider-agnostic resources in a robust manner using primitives from diverse cloud providers. The SUPERCLOUD methodology will be validated by testbed integration for real-world use cases in the healthcare domain, ranging from deploying a distributed medical imaging platform to running a full laboratory information system. The consortium is industry-led with partners actively involved in promotion of open source cloud technologies and contributing to major standardization bodies in cloud security, inter-cloud architectures, security protocols, and SDN. SUPERCLOUD will leverage its expertise in these domains to promote and ensure market validity of the research findings.

Keywords: cloud security,hybrid clouds,clouds of clouds,cloud infrastructure,self service security,self managed security,end to end security,resilience,user centric management
Sustainable Design and Management of Industrial Assets through Total Value and Cost of Ownership (Sustain-Owner)

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: Information Science and Engineering
Countries involved: Spain,India,South Africa,Italy,United States,United Kingdom,Chile,Peru
Call: Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) (H2020-MSCA-RISE-2014, 2014)
Start date: 2015-01-01
End date: 2018-12-31
Duration (months): 48.0
Total project cost (EUR): 450000.0
EU funding (EUR): 450000.0
Participants: 10
Project status: CLOSED

SoThe project will examine the potential of Total Value and Cost of Ownership (TVO, TCO) for supporting the design and through-life management of industrial assets. Until now, some leading companies that are aware of all the costs throughout the asset life cycle use TCO to support procurement, operations and maintenance decisions. The benefit of using TCO is that a decision maker could be incentivised to go beyond the consideration of capital expenditure, and think of the potential whole-life cost arising through the use of their assets. In this regard, TCO helps achieving a cost-efficient life cycle management of the assets owned by the company. But TCO models are still poorly practiced in industry, in spite of their advantages. Further on, the flavour of the day in the industrial and academic world is to encourage innovative thinking to extract the maximum value from the assets, instead of thinking only about cost. Value can be tangible or intangible, and is determined by the organization and its stakeholders, thus TVO extends cost-based decisions. Although the importance of value maximisation in physical asset management is currently accepted, there are few works clarifying what value means, how to identify and quantify value, how to base decisions on it. The purpose of the project is to study the evolution of TVO and TCO as used in industry and understood by academics, with the aim to develop a framework for understanding, quantifying, and using TVO / TCO for decision-making. Overall, we aim at studying how asset life cycle management is possible thanks to TVO / TCO, providing the asset owner the capability to develop a sustainable factory according to the economic, social and environmental requirements of the local industry.Cross-fertilization of research and industry will be achieved through knowledge sharing between academics and industrial experts involved through interviews and workshops. Publications will provide outputs to promote knowledge sharing.

Keywords: asset management,asset lifecycle,maintenance management,design and maintenance of industrial plants,sustainable manufacturing
Improving hearing device fitting with virtual reality (VR-FIT)

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: Netherlands
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-05-10
End date: 2023-05-09
Duration (months): 24.0
Total project cost (EUR): 175572.48
EU funding (EUR): 175572.48
Participants: 1
Project status: SIGNED

Hearing impairment is a common disease with a large impact on social interaction and psychosocial well-being. Partial rehabilitation is possible by providing hearing devices. The settings of hearing aids and cochlear implants have to be adjusted to fit individual needs. This fitting process normally takes place in the relatively quiet clinic or acoustician’s store, whereas hearing devices are most needed in noisy and reverberant situations in daily life. This mismatch may lead to inefficiency and suboptimal settings. Mainly because the current fitting process is based on trial-and-error: adjustments made in the clinic have to be evaluated in daily life, after which further adjustment (fine-tuning) is needed. Recent advances in virtual reality would allow for an accurate simulation of daily life situations in virtual environments (VEs) in the clinic. Using such VEs, adjustments could be tested immediately. It is hypothesized that using VEs makes the fitting process more efficient, allows for better counselling of the patient, and will lead to better final settings and a higher patient satisfaction. The proposed project aims to investigate these hypotheses. The work plan of the proposed project entails designing VEs for hearing device fine-tuning (thanks to the collaboration with University of Oldenburg, previously developed VEs can be used as a basis) and establishing the new fine-tuning procedure, in close collaboration with clinicians and patients to maximize the usability. Furthermore, an experiment is planned that compares the standard and new fine-tuning procedures between groups of hearing aid users and cochlear implant users. The project is unique by introducing VEs in a clinical setting to improve the outcome of the hearing rehabilitation process. It is also one of the few studies of the fitting process in both hearing-aid users and cochlear implant users, which is possible thanks to the unique patient population in the host institution, Erasmus MC.

Keywords: audiology,hearing aids,cochlear implants