Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Modelling the genomic landscapes of selection and speciation (ModelGenomLand)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting 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: United Kingdom
Call: ERC Starting Grant (ERC-2017-STG, 2017)
Start date: 2018-02-01
End date: 2024-01-31
Duration (months): 72.0
Total project cost (EUR): 1497755.0
EU funding (EUR): 1497755.0
Participants: 1
Project status: SIGNED

Understanding how natural selection, random genetic drift and demographic events interact to generate and maintain genetic and species diversity has been the central focus of population genetics for many decades. We now have the necessary genome sequence data to make detailed and powerful inferences about the evolutionary past of populations and species, yet our ability to meaningfully interpret such data has remained fundamentally limited. This project will use a combination of theory, development of new inference tools and a large-scale comparative analyses of genome data and has two principal aims: First to develop a general, statistical framework for making inferences about the joint action of past selection and demography from genome sequence data. This will be achieved using analytic calculations and approximations for the joint distribution of linked polymorphic sites. We will use these results to develop new methods to quantify the genome-wide rates of positive and background selection and to scan for genomic outliers of divergence between and positive selection within species. The new methods will be tested using simulations and data from model insects (Drosophila and Heliconius). Second, we will apply the new inference approach to genome data for 20 species pairs of European butterflies and conduct a systematic comparison of the demographic and selective forces involved in speciation. This will reveal how repeatable speciation processes are both in terms of the demographic and selective events, and the genes and genomic architectures involved. Specifically, we will test whether selection during speciation is concentrated at chromosomal rearrangements and/or candidate gene families involved in mate recognition and host plant adaptation. This project will fundamentally improve both our understanding of speciation and selection and our ability to use sequence data to study population processes (be they selection, demography or both) in any system.

Keywords: theoretical population genetics,speciation
Industrial Micro Electrochemical Cell sensors for real-time quantification of H2S in wastewater (iMEC)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Action type: SME instrument
Countries involved: Denmark
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: 2017-04-01
End date: 2017-09-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Danish SME Unisense A/S has developed an industrial Micro Electrochemical Cell sensor (iMEC) for automatically quantifying dissolved gasses in liquids. In this project, Unisense will optimize their existing handmade sensors, customized for each client, to an auto-calibrated industrial version, targeting wastewater utility companies. In the sewer systems, the prevalence of the toxic H2S gas (sewage gas) causes sewer corrosion and collapse, while at the same time entailing odour nuisances for the population living nearby. The robust iMEC sensor can be installed directly in the sewer network to accurately map H2S contents in real-time, and provide feedback to pumping stations to adjust the chemicals dosed accordingly. This will allow utilities to effectively control H2S levels in wastewater, thereby avoiding corrossion and toxic H2S leaks, and bringing significant economical savings to utilities and municipalities.

Keywords: electrochemical sensors,h2s formation,sewer corrossion,wastewater management
Information services: competition and externalities (ISECO)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Individuals, Markets and Organisations
Panel description: Economics, finance and management
Countries involved: France,France
Call: ERC Advanced Grant (ERC-2014-ADG, 2014)
Start date: 2015-11-01
End date: 2021-04-30
Duration (months): 66.0
Total project cost (EUR): 1815938.0
EU funding (EUR): 1815938.0
Participants: 2
Project status: CLOSED

This application aims at fostering our knowledge of the economics of information services by studying the strategic interactions between agents involved in the production and exchange of information services. In this context, externalities play a key role explored by this proposal. Their increasing prevalence in information services can be traced to three features: - Many information services involve one-sided or two-sided network externalities. - Information is a public good and the production and exchange of information between two parties may affect other parties in a positive or negative manner. - Information services and physical infrastructures are complements. Externalities arise in the two layers of the information society, the content level and the physical infrastructure. The proposal is then organized around four parts: 1. Background theory: two-sided markets, network dynamics, contractual externalities 2. Virtual layer: recommendation systems, privacy, transaction costs 3. Physical layer: pricing , investment 4. Competition policy for two-sided markets The first part consists of the development of relevant theory with original and novel methods including for instance global games, coordination games and recent contract theory. The second part studies specific issues in information services such as the design of search engines and the right to privacy. It also includes empirical investigation of on-line transaction costs using proprietary data of transactions on e-commerce platforms. The third part is concerned with the infrastructure. It studies net-neutrality and the prices of data from the perspective of price theory, accounting for the gratuity of some services. It will also develop original dynamic investment models to understand the role of the complementarity between infrastructure and service innovation and the role of legacy. The last part will develop tools for competition policy makers.

Keywords: internet,information services,externality,two sided market,network,contract,investment,privacy,competition policy,game theory,microeconomics,net neutrality
Planning the Future of Research & Innovation in the European University Alliance UNITE! (UNITE.H2020)

Framework: Horizon 2020 — Science with and for Society
Action type: Coordination and support actions
Countries involved: Germany,Spain,Italy,Finland,Sweden,France,France,Portugal
Call: Support for the Research and Innovation Dimension of European Universities (Part I) (H2020-IBA-SwafS-Support-1-2020, 2020)
Start date: 2021-01-01
End date: 2023-12-31
Duration (months): 36.0
Total project cost (EUR): 2000165.0
EU funding (EUR): 2000165.0
Participants: 17
Project status: SIGNED

UNITE! is one of the first 17 European University Alliances. Back in 2019, our 7 universities decided to take institutional cooperation to the next level by developing a long-term joint strategy for education addressing societal challenges offering inter-university ‘campus’ curricula where students, doctoral candidates, faculty and staff are mobile at all levels. Through this UNITE!H2020 project, our Alliance looks even further and takes up the challenge launched by the EC to develop, in synergy with its education dimension, a shared, integrated, long-term research and innovation (R&I) strategy, while developing, during the 3-year of the project, several pilot initiatives in the field of Energy - with special reference to the Green Deal - and Industry 4.0. UNITE! universities are highly ranked in their shared focus areas - STEM, architecture and design, and all belong to the CLUSTER university network, which boasts three decades of close cooperation among its members. This gives us a position of strength in assuring tangible progress towards our institutional transformation and the identification of successful models for the modernization of R&I. To do so, UNITE!H2020 will: a) develop a common R&I 2030 agenda, emphasizing our common DNA and shared vocation to address major societal challenges; b) develop policies to strengthen our R&I human capital by, e.g., new career development initiatives; c) develop policies to share our research infrastructures (RIs) supported by, e.g., experimental tests of previously developed guidelines on a selection of Energy RIs; d) reinforce cooperation with non-academic R&I players by, e.g., developing a network of Grant Offices & TTOs; e) mainstream our comprehensive Open Science practices based on, e.g., a detailed experimental analysis on the approach of our R&I groups to OS; f) involve citizens, civil society and public authorities in R&I; g) develop relations with other Alliances for joint synergies/complementarities.

Keywords: european university alliances,unite,randi,stem,university networks,infrastructures,ecosystems,open science,society
aB-IniTio calculations and MAchine learning for suPerconducting collective phenomena in novel materials (BITMAP)

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: Physics
Countries involved: Italy,United States
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-02-01
End date: 2024-01-31
Duration (months): 36.0
Total project cost (EUR): 269002.56
EU funding (EUR): 269002.56
Participants: 2
Project status: SIGNED

The aim of the BITMAP project "aB-IniTio calculations and MAchine learning for suPerconducting collective phenomena in novel materials" is to propose a workflow based on the combination of realistic Density Functional Theory (DFT) calculations with the Renormalization Group (RG) approach to superconducting Fermi surface instabilities. The latter is based on the pioneering work of Kohn-Luttinger where one can integrate out the high energy degrees of freedom perturbatively, and obtain effective attractive BCS interactions in non-s-wave channels. Once the superconducting pairing is known, as encoded in the superconducting gap function, a machine learning-based diagnostic procedure of the topological properties will be performed, upon the creation of specific ad-hoc convolutional neural networks. The project will allow the experience researcher to merge his present skills in the computational modeling of complex materials with modern concepts of machine learning, a sector that nowadays is expanding fast enough to easily foresee its applications in everyday life.

Keywords: density functional theory,renormalization group,machine learning,topological materials
Setting up Armenian Euraxess Service Network (Euraxess-AM)

Framework: Horizon 2020 — Science with and for Society
Action type: Coordination and support actions
Countries involved: Armenia
Call: EURAXESS Armenia start-up (H2020-IBA-SWAFS-EURAXESS-AM-2019, 2019)
Start date: 2019-09-01
End date: 2022-08-31
Duration (months): 36.0
Total project cost (EUR): 201887.5
EU funding (EUR): 200000.0
Participants: 1
Project status: CLOSED

The overall objectives of Euraxess -AM project are: • to set-up the Armenian EURAXESS Service Network and web-portal where a comprehensive up-to-date information and personalized assistance to mobility researchers coming to and going from Armenia will be provided; • to provide access to a complete range of information and support services for European and non-European researchers wishing to develop their career, thus, contributing to better integration of Armenian research community into European Research Area. • to ensure an easier re-integration of returning researchers and access to adequate career development measures and opportunities. • to set-up a system facilitating researchers’ better career development and mobility through the netwrok of LoCPs; • to ensure quality assistance in career development and mobility related issues for researchers in dealing with legal and administrative matters like temporary stay, work and residence permits, visa issues, health and social security issues, etc.; • to support research organizations, universities and companies in recruiting outstanding researchers from abroad by setting-up the Euraxess Network Services in Armenia.

Keywords: euraxess service network,armenia,career development,mobility of researchers,information and service
VINYL AND HETEROARYL BORONIC ACIDS AS NON-STABILIZED NUCLEOPHILES IN RHODIUM-CATALYZED DYNAMIC KINETIC TRANSFORMATIONS (BORONDYKAT)

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: Chemistry
Countries involved: United Kingdom
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-08-01
End date: 2018-07-31
Duration (months): 24.0
Total project cost (EUR): 183454.8
EU funding (EUR): 183454.8
Participants: 1
Project status: CLOSED

The formation of carbon-carbon bonds in an asymmetric fashion is a very useful process in synthetic chemistry, since it generates single enantiomers of chiral molecules at the same time as the molecular framework is being assembled. In this context, two strategies for the generation of single enantiomer compounds using enantioselective catalysis have been widely emabraced: on the one hand, the use of prochiral substrates, and on the other hand, the use of racemic substrates in enantiomer resolution processes, which limits the yields up to 50%. An efficient variation of this second strategy is to couple enantiomer differentiation with interconversion of enantiomers. However, these dynamic kinetic asymmetric transformations (DYKAT) have been limited to the use of stabilized nucleophiles. Very recently, the group of Fletcher reported that alkylzirconium reagents can be employed as non-stabilized nucleophiles in combination with a copper-based catalytic system for this class of processes. Subsequently, the same group demonstrated that arylboronic acids are also suitable substrates in rhodium-catalyzed DYKATs. The project presented in this application aims to expand the scope of this powerful transformation by using vinyl- and heteroarylboronic acids as non-stabilized nucleophiles in the rhodium-catalyzed DYKAT. Moreover, a thorough study of the reaction mechanism will be conducted, as well as the investigation on alternative procedures for this process (catalytic systems, nature of the substrates, etc) that might result in useful applications for organic synthesis.

Keywords: dynamic asymmetry,homogeneous catalysis,cross coupling,rhodium,mechanisms
Personalised ICT-tools for the Active Engagement of Consumers Towards Sustainable Energy (Eco-Bot)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Reducing energy consumption and carbon foorpint by smart and sustainable use
Action type: Innovation actions
Countries involved: Germany,Spain,Poland,Türkiye,Greece,Greece,United Kingdom
Call: Behavioural change toward energy efficiency through ICT (H2020-EE-2017-RIA-IA, 2017)
Start date: 2017-10-01
End date: 2021-06-30
Duration (months): 45.0
Total project cost (EUR): 2521566.1
EU funding (EUR): 1964145.38
Participants: 10
Project status: CLOSED

Eco-Bot aims to utilize recent advances in chatbot tools and advanced signal processing (i.e. energy disaggregation) using low-resolution smart meter-type data with the goal of changing their behaviour towards energy efficiency. Eco-Bot targets to a personalized virtual energy assistant to deliver information on itemized (appliance-level) energy usage through a chat-bot tool. The "chat-bot" functionality will be use an attractive frontend interface, permitting seamless communication in a more natural and interactive way than a traditional mobile application. This way, Eco-Bot aims to achieve a higher level of engagement with consumers than previous efforts (i.e. serious games, gamification, competitions or other interactive ICT), by adding a more engaging form of interaction with existing platforms that has been proven in different market settings. The proposed system considers knowledge of the delivered multi-factorial models, including rebound-effects, as a result of the baseline research on both European and International activities. Then, based on advanced ICT, such as knowledge engineering, machine learning, expert systems, the project transforms the multi-factorial models for energy reduction to interactive, personalized and targeted recommendations to consumers on how to save energy. Eco-Bot uses also existing NILM, e.g. energy disaggregation methods, and data analytics to break down consumption to the appliance level, where this is possible (smart meters at reasonable granularity, adequate number of information collected) so as to make consumers aware of their most energy-consuming devices. The project will demonstrate the system in three different use cases, each one representing a different business model (B2B / B2B2C /B2C). We aim to validate our system across real and diverse conditions such as socio-cultural, environmental, demographic, climate and consumption, so as to draw concrete conclusions regarding performance, effectiveness, affordability, etc.

Keywords: personalised virtual energy assistant,itemised billing options,energy disaggregation,multi factorial energy efficiency models,consumers engagement,validation of new business models
INNOvative mapping, reporting and forecasting of CYANObacteria blooms applying the synergistic use of advanced in situ optical data, satellite imagery and statistical modelling (INNO-CYANO)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Netherlands
Call: European SME innovation Associate - pilot (H2020-INNOSUP-02-2016, 2016)
Start date: 2017-09-01
End date: 2018-08-31
Duration (months): 12.0
Total project cost (EUR): 83042.5
EU funding (EUR): 83042.5
Participants: 1
Project status: CLOSED

Water Insight (WI) specialises in high quality spatial information products for monitoring surface water quality applying the synergistic use of Earth Observation (EO) and optical in situ measurements. Based on a close interaction with users, WI wants to add a new user-tailored service branch to their portfolio: forecasting of cyanobacteria blooms. Due to climate change and anthropogenic activity, massive blooms of cyanobacteria become an increasing problem for lakes world-wide. Cyanobacteria may be toxic for animals and humans, change the water quality and ecosystems. The consequences are visible in social, economic and industrial levels. While WI's technology has been proven to be very suitable for monitoring the development of cyanobacteria blooms, water managers also require quick and precise forecasts of the blooms development to take timely measures or mitigating actions. Existing process-based forecasting models are complex, need a too long processing time and more input data than is operationally available. WI has an extensive dataset of EO and in situ data on affected lakes. A data-driven statistical model could be developed based on these data, and significantly reduce the processing time for a forecast. To develop such a model, a highly-skilled searcher (PhD) is required, with specialised knowledge of EO data, proven skills in statistical modelling, cyanobacterial ecology and water quality. It is difficult for WI to recruit such a specialist as there is a lack of university graduates, particularly on the PhD level, in this field in the Netherlands. INNO-CYANO will be beneficial for all: WI will get the chance to hire a specialist to develop our innovative ideas, the candidate will get the chance to get an insight in the practice of a commercial company and to develop in the field of business innovation, and the ‘INNO-CYANO’ model will serve water managers with a precise forecast of the blooms and therefore improve the management of cyanobacteria blooms.

Keywords: cyanobacteria,scum,water quality,statistical model,earth observation,in situ,integrated service,innovation
Large Riblet Surface with Super Hardnesss, Mechanical and Temperature Resistance by Nano Functionalization (ReSiSTant)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Nanotechnologies
Action type: Innovation actions
Countries involved: Austria,Germany,Germany,Germany,Italy,Italy,Germany,Spain,Israel,Switzerland,Poland
Call: Pilot Lines for Manufacturing of Nanotextured surfaces with mechanically enhanced properties (H2020-NMBP-PILOTS-2017, 2017)
Start date: 2018-01-01
End date: 2022-12-31
Duration (months): 60.0
Total project cost (EUR): 6286918.22
EU funding (EUR): 5485000.0
Participants: 12
Project status: CLOSED

“ReSiSTant” targets the optimization of two industrial pilot lines by using micro- and nanostructured surfaces for drag reduction. The objectives are to implement new developed surfaces into 1) Aircraft Turbofan Engines and 2) Industrial Compressors. Positive effects by usage of such surface could give benefits in terms of efficiency, CO2 reduction and noise emission and further on a positive economical and ecological impact. To enable the usage of such micro- and nanostructures, special development on the surface material for better durability in rough conditions has do be done. It is planned to do nano-functionalization, like implementing nanostructures and nanoparticles for better resistance in rough conditions. Riblets basically consist of tiny streamwise grooved surfaces which reduce the drag in the turbulent boundary layer of up to 8%. Surface modifications such as riblets are the most promising technology that could be applied without additional external energy or additional amount of air. An additional key outcome of the proposed project is a detailed database of experimental data for cases with and without riblets, which can be leveraged to validate tools for forced response and aero-acoustic predictions of an aircraft engine and its low-pressure turbine components. At industrial gas compressors the riblet structures reduce the aerodynamic shear stress losses. An efficiency increase of 1% of a single stage system shall be achieved. During the project a riblet coating that includes a corrosion protection should be developed. Beside the resistant hardness of the coating also a self-cleaning mechanism by usage of nanostructures should be implemented. The new surface manufacturing processes shall be completed in less than 5 hours and a higher process reliability and predictability of the performance results is sought. As a whole, the success of the project will therefore contribute to significantly increasing the level of maturity for these pilot lines to TRL7

Keywords: riblets,drag reduction,turbulent friction,nano technologies,nano functionalization,super hard riblet surface,aircraft turbofan engines,compressors