Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Coinduction for Verification and Certification (CoVeCe)

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: France
Call: ERC Starting Grant (ERC-2015-STG, 2015)
Start date: 2016-04-01
End date: 2021-09-30
Duration (months): 66.0
Total project cost (EUR): 1407413.0
EU funding (EUR): 1407413.0
Participants: 1
Project status: CLOSED

Software and hardware bugs cost hundreds of millions of euros every year to companies and administrations. Formal methods like verification provide automatic means of finding some of these bugs. Certification, using proof assistants like Coq or Isabelle/HOL, make it possible to guarantee the absence of bugs (up to a certain point). These two kinds of tools are crucial in order to design safer programs and machines. Unfortunately, state-of-the art tools are not yet satisfactory. Verification tools often face state-explosion problems and require more efficient algorithms; certification tools need more automation: they currently require too much time and expertise, even for basic tasks that could be handled easily through verification. In recent work with Bonchi, we have shown that an extremely simple idea from concurrency theory could give rise to algorithms that are often exponentially faster than the algorithms currently used in verification tools. My claim is that this idea could scale to richer models, revolutionising existing verification tools and providing algorithms for problems whose decidability is still open. Moreover, the expected simplicity of those algorithms will make it possible to implement them inside certification tools such as Coq, to provide powerful automation techniques based on verification techniques. In the end, we will thus provide efficient and certified verification tools going beyond the state-of-the-art, but also the ability to use such tools inside the Coq proof assistant, to alleviate the cost of certification tasks.

Keywords: automata,coq proof assistant,coalgebra,model checking,proof theory,kleene algebra,linear logic
ACelerated COnvex OPTimization (ACCOPT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced 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: Belgium
Call: ERC Advanced Grant (ERC-2017-ADG, 2017)
Start date: 2018-09-01
End date: 2024-08-31
Duration (months): 72.0
Total project cost (EUR): 2090038.0
EU funding (EUR): 2090038.0
Participants: 1
Project status: SIGNED

The amazing rate of progress in the computer technologies and telecommunications presents many new challenges for Optimization Theory. New problems are usually very big in size, very special in structure and possibly have a distributed data support. This makes them unsolvable by the standard optimization methods. In these situations, old theoretical models, based on the hidden Black-Box information, cannot work. New theoretical and algorithmic solutions are urgently needed. In this project we will concentrate on development of fast optimization methods for problems of big and very big size. All the new methods will be endowed with provable efficiency guarantees for large classes of optimization problems, arising in practical applications. Our main tool is the acceleration technique developed for the standard Black-Box methods as applied to smooth convex functions. However, we will have to adapt it to deal with different situations. The first line of development will be based on the smoothing technique as applied to a non-smooth functions. We propose to substantially extend this approach to generate approximate solutions in relative scale. The second line of research will be related to applying acceleration techniques to the second-order methods minimizing functions with sparse Hessians. Finally, we aim to develop fast gradient methods for huge-scale problems. The size of these problems is so big that even the usual vector operations are extremely expensive. Thus, we propose to develop new methods with sublinear iteration costs. In our approach, the main source for achieving improvements will be the proper use of problem structure. Our overall aim is to be able to solve in a routine way many important problems, which currently look unsolvable. Moreover, the theoretical development of Convex Optimization will reach the state, when there is no gap between theory and practice: the theoretically most efficient methods will definitely outperform any homebred heuristics.

Keywords: convex optimization,complexity theory,structural optimization,fast gradient methods,large scale problems
Composite tooling for business jet lower wing stiffened panel manufacturing (COMBUSS)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Clean Sky 2
Action type: Innovation actions
Partnership: CS2 (Art-187)
Countries involved: Italy,United Kingdom,United Kingdom
Call: Prototype Tooling for manufacturing composite stiffened panel for a business jet lower wing (H2020-CS2-CFP07-2017-02, 2017)
Start date: 2018-11-01
End date: 2020-12-31
Duration (months): 26.0
Total project cost (EUR): 740956.26
EU funding (EUR): 599519.38
Participants: 3
Project status: CLOSED

The aim of the COMBUSS project is to develop, design, manufacture and deliver to the Topic Manager facilities, all the prototype subcomponent manufacturing tooling needed to manufacture the stiffeners and panel of lower wing (including all auxiliary tools). COMBUSS project will design the tooling system which will incorporate self-heated capability with multiple heating zones and advanced thermal management. The activities will start with the provision of definitions and specifications by the Topic Manager (TM). The mould materials will be optimised for long life and improved productivity. It will feature built-in quality assurance tools to guarantee reliable processing of the selected material systems according to technical specifications. After the TM’s approval of the design, the tool will be fabricated, checked for conformance with the specification, transported to the TM premises and commissioned. The partners will provide full documentation on the tooling system and its use and will support the TM with the demonstrator fabrication. The COMBUSS system, as the main output of the project, will be realized in line with the “most innovative expectations” of the call, as it will present a comprehensive tooling solution for improved cost (tooling materials and manufacturing method), eco-design (out-of-autoclave processing, low thermal mass and easy modification of tooling, waste reduction in process), energy savings (self-heating and multi-zone configuration of tooling), manufacturing process simplification (robust process thermal control), production time savings (faster heating rates, cure process optimization) and Aeronautical quality standards (on-line quality control) in composites manufacturing. The COMBUSS system is intended to be used directly at the flight-worthy demonstrator at the Topic Manager premises as a first step of the system exploitation.

Keywords: composite material processing,composite tooling,sensors,process monitoring
Plant lipidome remodelling during cold acclimation (PLICO)

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: Life Sciences
Countries involved: Spain
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-01-15
End date: 2018-01-14
Duration (months): 24.0
Total project cost (EUR): 170121.6
EU funding (EUR): 170121.6
Participants: 1
Project status: CLOSED

Extremely low temperatures influence plant development and crop productivity. Therefore, plants have evolved mechanisms to enhance tolerance to freezing (cold acclimation) involving physiological and biochemical modifications. A key side of this process is the biosynthesis and delivery mechanisms of the newly synthesized lipid species towards the appropriate subcellular membranes. Previous studies in Prof Botella´s lab (supervisor) have demonstrated that Arabidopsis SYT1 (Synaptotagmin 1) is an ER-PM (endoplasmic reticulum – plasma membrane) tether component essential for freezing tolerance, and they have characterized SYT3, a novel component of cold-acclimation. The research objective of this proposal is to determine the role that SYT1 and SYT3 have on lipid homeostasis related to cold acclimation at the cellular level, using a combination of mutant analysis, cellular biology, lipidomics and biochemical approaches. Additionally, the findings could have future applications since freezing temperatures are limiting the geographical locations for growing crop plants and periodically account for significant losses in plant productivity in Europe. Dr Ruiz-Lopez (researcher) has wide experience in Plant Lipids. In recent years she has successfully worked in the UK, in one of the world’s leading groups for plant lipids research. Moreover, the host group is one of the world-leading groups in plant responses to abiotic stress research. Their collective expertise represents a very strong team with a proven track-record to conduct world-class research. In addition, secondments are planned to carry out the most advanced lipidomic analysis. This inter-disciplinary Fellowship will exploit the complementary competencies and technologies available at the host to broaden the skills of the researcher, particularly in microscopy, proteomics and management skills, and will also increase the sharing of knowledge and technology transfer between the participant institutions.

Keywords: plant membranes,cold acclimatation,syt1,syt3,synaptotagmins,arabidopsis,lipidomics,lipid transfer
Novel GAsification REactor for combined heat and power Plant (GAREP)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Finland
Call: Stimulating the innovation potential of SMEs for a low carbon energy system (H2020-SMEINST-1-2014, 2014)
Start date: 2015-06-01
End date: 2015-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Drawbacks related to central large scale power production due to high cost of infrastructure and transmission loss resulting in high cost of energy have created a need for small scale local power production. By implementing combined head and power (CHP) solutions local biomass could be used to provide low cost energy. However large scale CHP plants (>10MWe) require large investments while technologies used for small scale CHP (<50kWe) are experiencing problems with scalability due to issues related to tar removal. This has created a strong market demand for small-to-medium scale (0,1MWe-3MWe) solutions. The main objective of the planned project is to develop a CHP unit in the 250-1500kWe range using the GasEK gasification reactor that would allow to use local biomass for producing heat and electricity. GasEK has the necessary level of innovation to dominate the market in the selected power range. At the heart of the development is a patented central nozzle system which makes it possible to develop larger gasifiers producing low tar level wood gas that has not been possible before. The unique aspect of the patented solution is the Electrical Control Unit with smart-control software giving the solution a distinct competitive advantage. As a result GasEK will offer a reliable and cost-effective CHP plant for distributed energy production using local biomass. Levelized Cost of Energy of 40EUR/MWh and 3 times lower payback than the current benchmark guarantee it a strong market advantage. GasEK has a strong team with main R&D persons having 50+ years of cumulative experience, complemented with business development experts. After a 4 year development period and 11MEUR invested by public and private funds, GasEK is now reaching the commercial phase with the given technology. The company is looking to generate an annual revenue of 10 MEUR by FY 2018 and a 20% market share of the small-to-medium scale (<5MWe) CHP market in the long run resulting in a total revenue of 100MEUR

Keywords: gasification,wood gas,combined heat and power,synthetic natural gas
Daylight Colour and Pattern in Built Environments: A latitudinal study of daylight and user responses to the varying colour of skies in built environments using spectral simulations. (DAYCOP)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Career Restart panel
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-09-01
End date: 2023-08-31
Duration (months): 24.0
Total project cost (EUR): 162806.4
EU funding (EUR): 162806.4
Participants: 1
Project status: SIGNED

Three-quarters of the global population will be urban by 2050. To ensure the liveability, sense of place, and quality of life in new expanding urban areas, urban planning policies should consider spectral characteristic of daylight and the built environment. The colours and patterns we see around us, at various scales of the urban environment (city, neighbourhood, or street), are a complex interplay between the spectral distribution of daylight and spectrally-specific reflectance of surfaces in the space. Daylight sculpts the colours and patterns of our environmental perception, giving architects, urban and city planners an effective strategy to create spatial experiences, visual impressions of character and behavioural responses. However, current daylight simulation workflows used by building professionals do not account for colour renditions nor associated patterns of daylight. Spectral sky data is not readily available. Spectral simulations (to accurately predict colour and patterns of daylight) are computationally intensive and require further research and validation. Finally, research is inconclusive on how colour and patterns of daylight influence our environmental perception. My proposal is threefold. First, validate spectral sky models in existing spectral simulation platforms for different latitudinal regions. Second, define spectral dynamics of daylight in diverse urban environments (plaster, brick, reflective facades or spaces with vegetation) and latitudes (polar, temperate or equatorial). Third, conduct user perception studies in built environments with varying regional skies. This will help formulate design guidelines that consider characteristic qualities of daylight (colour and patterns) with local preferences. At the end of the two-year fellowship, I aim to expand my publication record, research expertise and create local and international collaborations, to establish myself as an independent researcher ready for a tenure track position.

Keywords: daylight,spectral sky,spectral daylight simulations
An Analysis of Educational, Labor Market, Demographic and Health Outcomes of Syrian Refugees in Turkey (SYRREFTDHS)

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: Economic Sciences
Countries involved: Türkiye,United States
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-09-01
End date: 2023-08-31
Duration (months): 24.0
Total project cost (EUR): 155310.72
EU funding (EUR): 155310.72
Participants: 2
Project status: SIGNED

Turkey hosts the largest number of refugees worldwide. According to the Turkish Directorate General for Migration Management (TDGMM), 3.61 million Syrian refugees resided in Turkey as of August 2020. While studies examining the effect of refugees on natives’ outcomes have recently burgeoned both in the Turkish setting and elsewhere, we know very little about the Syrian refugees themselves— despite the massive size of this refugee influx. This is mostly due to the lack of representative datasets. A tremendous new opportunity comes up with the 2018 wave of Turkish Demographic and Health Survey (TDHS), which provides a representative sample of Syrian refugees based on a household screening procedure using the official registry records from the TDGMM. Using the representative and rich data provided by this dataset, the purpose of this project is to understand the key educational, labor market, demographic and health outcomes of Syrian refugees in Turkey. This project will significantly progress the research beyond the current state-of-art first by conducting a rigorous econometric analysis of key outcomes of the biggest refugee group in the world using a representative dataset for the first time, and second by uncovering the channels underlying the observed patterns in these outcomes. Particularly, this project will address four main topics: (i) schooling, (ii) employment and living conditions, (iii) marriage and fertility, (iv) infant and child health.

Keywords: refugees,education,employment,demography,child health,applied econometrics,demographic and health surveys,turkey,syria
PREdictiVe system to recommend Injection mold sEtup in Wireless sensor networks (PREVIEW)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Germany,Spain,Spain,Ireland,Italy,Hungary,Netherlands,United Kingdom
Call: Process optimisation of manufacturing assets (H2020-FoF-2014, 2014)
Start date: 2015-01-01
End date: 2017-12-31
Duration (months): 36.0
Total project cost (EUR): 3321852.5
EU funding (EUR): 3321852.5
Participants: 10
Project status: CLOSED

The objective of PREVIEW is to develop a Cyber Physical System (CPS) for plastic injection manufacturing processes monitoring, control and optimization, by incorporating several innovative and cutting edge technological solutions: advanced artificial intelligence and machine learning techniques, robust industrial wireless communication, IoT and indoor location. PREVIEW is a middleware solution that facilitates easy, ubiquitous, holistic and fast sharing of product and process information across the entire injection production process. PREVIEW development incorporates several innovative technological solutions: -PREVIEW Advanced Predictive system offers a powerful knowledge based system for data analysis. Based on the data analysis results compared to historical data, the system will provide feedback, closing the loop by recommending actions to improve productivity; -PREVIEW will develop and implement the Data acquisition modules to collect the data from the in-mould cavity pressure and temperature sensors as well to collect data from the injection machine PLC; -Thanks to the data acquisition modules and the industrial wireless communication capabilities developed in the project, mould and machine become IoT-capable, allowing for interoperability at intra-plant level with other devices, including the PREVIEW server, database and mobile devices such as tablets and smartphones; -PREVIEW system offers the possibility to share among the Cloud the mould-DNA functionalities as well as the Setup Predictive System. These functionalities enable to reuse historical data when setting up a mould in another location. PREVIEW deploys a set of technologies and enablers (Information and communication technologies, manufacturing strategies, modelling, simulation and forecasting methods and tools), for process optimization of manufacturing assets in the injection sector.

Keywords: cyber physical system,artificial intelligence,machine learning techniques,manufacturing processes monitoring,advanced predictive system,close loop,industrial wireless,middleware
Microbiota and Resolvins in Arthritis (MaRiA)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-09-21
End date: 2020-02-21
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

The proposed work will investigate the regulation of pro-resolving lipid mediators (LM) by pathobionts and dysbiotic microbiota in rheumatoid arthritis (RA). RA is a chronic inflammatory disease with considerable socioeconomic impact. Most treatment options carry severe side effects including immunosuppression. Recent studies found associations between RA and dysbiosis of the microbiota, with the underlying mechanisms leading to this dysbiosis remaining of interest. In addition, I recently found that in both mice during pathobiont-driven inflammatory arthritis and in plasma from patients with RA the levels of a novel family of host protective LM, termed n-3 docosapentaenoic acid-derived Resolvins (RvDn-3 DPA), were significantly altered. The novel hypothesis of this action is that pathobionts and pathobiont-induced gut-dysbiosis trigger local inflammatory responses and impair the production of RvDn-3 DPA, resulting in exacerbation and chronicity of local inflammation. This novel hypothesis will be addressed using a multi-pronged approach to: 1) Characterise the role of Porphyromonas gingivalis and Prevotella copri in regulating RvDn-3 DPA, local inflammation and their effects on intestinal microbiota and gut barrier function. 2) Assess the regulation of inflammatory arthritis and RvDn-3 DPA by RA patients’ microbiota. 3) Establish the protective actions of RvDn-3 DPA in pathobiont-driven inflammatory arthritis. This will provide insights into mechanisms of pathobiont- and dysbiotic microbiota-triggered arthritic inflammation, the regulation of tissue LM profiles and identify potential novel diagnostic markers for early RA-detection. In addition, this work will establish the therapeutic potential of RvDn-3 DPA in regulating exacerbated inflammation and dysbiosis in inflammatory arthritis, providing novel therapeutic opportunities for RA treatment.

Keywords: microbiota,resolvins,rheumatoid arthritis,omega 3,specialized pro resolving mediators,lipid mediators,lipid mediator profiling