Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Association of air pollution with dementia risk: is it confounded and mediated by environmental tobacco smoke and consumption of fish? (DEMAIRPO)

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: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-07-30
End date: 2020-07-29
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

Air pollution (AP) remains prevalent globally. Its impact on dementia risk is unclear. We propose to investigate the association of dementia with AP and explore mediation effects on the association from other factors. We will examine data of 2776 participants aged >=60 years who were randomly recruited from urban and rural of China. Their baseline risk factors (including environmental tobacco smoke-ETS and fish consumption) were recorded and dementia was diagnosed in a standard interview package. They were followed up for 4 years to identify mortality and incident dementia. We will calculate the residential distance proximity to major roadways (REDPMR) for each cohort member (an approximate AP exposure), and also collect regional AP monitoring data to evaluate individual exposure to AP. We will employ multivariate adjusted Cox regression models to examine the association of AP with dementia and interaction and mediation effects from ETS and fish consumption on the association. In the UK we will recruit 200 elders aged>=75 years with newly diagnosed dementia and 200 without dementia from the Royal Wolverhampton hospital. We will document their disease risk factors, REDPMR and local residential AP. Using multivariate logistic regression models we will examine the associations of REDPMR with dementia. We will run 2 focus groups each in the UK and China to explore the effects of AP on dementia and preventive measures of AP and dementia. Our unique data, including participants with special characteristics from China will offer internationally applicable insights into the impact of AP on dementia. Throughout the research project, use of varied study and research methodologies and rigorous training courses, our Fellow will develop his leadership skills and further his career in public health research. The project will strengthen a long-term collaboration between EU and China partners, and will provide Europe with new data to prevent dementia and to reduce AP.

Keywords: air pollution,dementia
Are there rules to the game? Patterns of Genome Evolution in Paleopolyploid Plants (PGEPP)

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: Netherlands
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-04-01
End date: 2017-07-28
Duration (months): 24.0
Total project cost (EUR): 177598.8
EU funding (EUR): 177598.8
Participants: 1
Project status: CLOSED

Polyploidy events (i.e. the process of genome doubling that gives rise to organisms with multiple sets of chromosomes) have had a strong impact on land plants diversification, adaptation and speciation. Genomic investigations have found that polyploidy is ubiquitous among angiosperms and have identified independent lineage-specific ancient polyploidizations. Traces of these polyploidy events are still present, although duplication events are followed by massive gene loss and chromosome structural rearrangements. However, the mechanisms/principles that govern these genomic changes following polyploidization are still poorly understood. Our project aims to overcome this limitation by analyzing genomic changes following polyploidization in three plant families among which two are of particular agricultural and economical importance. Specifically I will test if common mechanisms (e.g. presence of repetitive elements) are involved in chromosomal rearrangements. I will combine physical mapping approaches (molecular cytogenetic and optical mapping) and sequence analysis to characterize and compare genomic collinearity (synteny) between genomes of Brassicaceae, Cleomaceae and Solanaceae species. This work will improve our understanding of genome evolution by looking mechanisms of chromosomal changes and will improve synteny analysis between model plants such as Arabidopsis and more distant crops for homolog identification.
Product identification using sequence-controlled oligomers (Sequence Barcodes)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: France
Call: ERC Proof of Concept Grant (ERC-2015-PoC, 2015)
Start date: 2015-11-01
End date: 2017-04-30
Duration (months): 18.0
Total project cost (EUR): 149784.0
EU funding (EUR): 149784.0
Participants: 1
Project status: CLOSED

The aim of the project Sequence Barcodes will be to study the market potential of sequence-encoded oligomers developed and patented in the frame of the ERC starting grant project SEQUENCES (grant agreement n°258593, End-date: October 2014). In particular, we propose to use monodisperse oligomers with defined chain-lengths and monomer sequences as molecular barcodes for product identification. A code can be written in the oligomers using different monomers as an alphabet, for example using two (i.e. binary code), three, four or more monomers. The barcodes can also be read using sequencing techniques such as tandem mass spectrometry and nanopore sequencing. All the fundamental knowledge for preparing and sequencing these polymers has been identified in the frame of the project SEQUENCES and is available for a technological transfer to industry. Moreover, these synthetic polymers possess valuable advantages over DNA, which is often used in product identification technologies. Indeed, they are much simpler to synthesize and to use than natural biomacromolecules. Perhaps more importantly, our chemistry is very versatile and the molecular structure of the oligomers can be adapted to a customer need. Among possible applications, these oligomers can be used as molecular labels to tag high-value products. At present, there is limited prior art in this area of research using synthetic polymers. Therefore, the present project may open up important technological and commercial opportunities. Practically speaking, a business manager and a post-doctoral researcher will be hired in this project in order to bridge the gap between fundamental research and commercialization. For instance, a detailed market analysis, including a survey of potential industrial partners, will be done by the business manager. This will help to identify the most appropriate solution for commercializing our technology.

Keywords: sequence controlled polymers,polymer chemistry,oligomers,identification technologies,high value products
Integrating morpho-phonology in speech recognition (MorSR)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: United Kingdom
Call: ERC Proof of Concept Grant (ERC-2018-PoC, 2018)
Start date: 2019-03-01
End date: 2020-08-31
Duration (months): 18.0
Total project cost (EUR): 149919.0
EU funding (EUR): 149919.0
Participants: 1
Project status: CLOSED

Automatic Speech Recognition (ASR) is considered to represent the most natural man-machine interface across the spectrum of technological space. Current commercial ASR systems rely on a ‘rich’ representation of an acoustic signal for words and their variants, resulting in major challenges in the deployment of ASR systems in areas where it could have substantial social impact. Our central goal is to translate research results from the ERC funded project MORPHON into a novel ASR system to remove such barriers. We have previously demonstrated that the use of a universal set of phonological features delivers an isolated word recognition system (FlexSR) with enhanced phoneme recognition accuracy. It is more robust under conditions of non-standard speech, dialect variation and can be easily adapted to new languages. These aspects are problematic for current ASR systems which rely on the probabilistic sequencing of whole words in their language model (LM) based on large written text corpora for training. Obtaining sufficient training data for a new LM is prohibitively expensive. Instead, MorSR will incorporate linguistic information about word-structure to reject improbable words. This reduces the search space and increases the probability of identifying correct words. A major outcome will be an innovative LM based on linguistic principles. Unlike existing approaches, it is based on speech data to capture crucial regularities that are lost in text corpora. Combined with FlexSR's key strengths in identifying subtle phonological contrasts, MorSR will not only enable improved predictions of word sequences in running speech, but also dramatically reduce the requirement for training data when adapting the system to a new language. MorSR's strengths include: (a) prediction of fine-grained possibilities of word sequences based on grammatical principles; (b) requiring considerably less training data; (c) easily adaptable to new languages; and (d) will be fast, secure and accurate.

Keywords: automatic speech recognition,language model,morpho phonological predictions
Perceptual encoding of high fidelity light fields (EyeCode)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-07-01
End date: 2023-03-31
Duration (months): 69.0
Total project cost (EUR): 1868855.0
EU funding (EUR): 1868855.0
Participants: 1
Project status: SIGNED

One of the grand challenges of computer graphics has been to generate images indistinguishable from photographs for a naïve observer. As this challenge is mostly completed and computer generated imagery starts to replace photographs (product catalogues, special effects in cinema), the next grand challenge is to produce imagery that is indistinguishable from the real-world. Tremendous progress in capture, manipulation and display technologies opens the potential to achieve this new challenge (at the research stage) in the next 5-10 years. Electronic displays offer sufficient resolution, frame rate, dynamic range, colour gamut and, in some configurations, can produce binocular and focal depth cues. However, most of the work done in this area ignores or does not sufficiently address one of the key aspects of this problem - the performance and limitations of the human visual system. The objective of this project is to characterise and model the performance and limitations of the human visual system when observing complex dynamic 3D scenes. The scene will span a high dynamic range (HDR) of luminance and provide binocular and focal depth cues. In technical terms, the project aims to create a visual model and difference metric for high dynamic range light fields (HDR-LFs). The visual metric will replace tedious subjective testing and provide the first automated method that can optimize encoding and processing of HDR-LF data. Perceptually realistic video will impose enormous storage and processing requirements compared to traditional video. The bandwidth of such rich visual content will be the main bottleneck for new imaging and display technologies. Therefore, the final objective of this project is to use the new visual metric to derive an efficient and approximately perceptually uniform encoding of HDR-LFs. Such encoding will radically reduce storage and bandwidth requirements and will pave the way for future highly realistic image and video content.

Keywords: high dynamic range,applied visual perception,computer graphics,computational photography
Identification of legal rules and administrative processes applicable to Fuel Cell and Hydrogen technologies’ deployment, identification of legal barriers and advocacy towards their removal. (HyLAW)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Public-private partnerships
Destination: Fuel Cells and Hydrogen
Action type: Coordination and support actions
Partnership: FCH2 (Art-187)
Countries involved: Austria,Germany,Spain,Italy,Bulgaria,Hungary,Norway,Finland,Poland,Romania,Belgium,Sweden,Belgium,Latvia,France,Netherlands,United Kingdom,Denmark,United Kingdom,United Kingdom,Denmark,Portugal
Call: Identification of legal-administrative barriers for the installation and operation of key FCH technologies (H2020-JTI-FCH-2016-1, 2016)
Start date: 2017-01-01
End date: 2019-03-31
Duration (months): 27.0
Total project cost (EUR): 1143000.0
EU funding (EUR): 1143000.0
Participants: 24
Project status: CLOSED

The fuel cells and hydrogen (FCH) industry has made considerable progress toward market deployment. However existing legal framework and administrative processes (LAPs) – covering areas such as planning, safety, installation and operation – only reflect use of incumbent technologies. The limited awareness of FCH technologies in LAPs, the lack of informed national and local administrations and the uncertainty on the legislation applicable to FCH technologies elicit delays and extra-costs, when they do not deter investors or clients. This project aims at tackling this major barrier to deployment as follows: • Systematically identifying and describing the LAPs applicable to FCH technologies in 18 national legal systems as well as in the EU proper legal system. • Assessing and quantifying LAP impacts in time and/or resource terms and identify those LAP constituting a legal barrier to deployment. • Comparing the 18 countries to identify best and bad practices • Raising awareness in the countries where a LAP creates a barrier to deployment. • Advocating targeted improvements in each of 18 countries + EU level • It will make all this work widely available through: (1) A unique online database allowing easy identification, description and assessment of LAPs by country and FCH application. (2) Policy papers by applications and by country with identification of best practice and recommendations for adapting LAP. (3) A series of national (18) and European (1) workshops with public authorities and investors. HyLAW sets up a National Association Alliance not just for the duration of the project, but for the long term consolidation of the sector under a single unified umbrella. By bringing together these national associations and all of Hydrogen Europe’s members, it’s the first time ever that the entire European FCH sector is brought together with a clear and common ambition.

Keywords: fuel cell and hydrogen fch technologies,legal and administrative processes laps,legal and administrative barriers removal,fch technologies market deployment,national associations alliance
EEN InnoSupp BG (EEN InnoSupp BG)

Framework: Horizon 2020 — EC Treaty
Action type: Specific Grant agreement
Countries involved: Bulgaria,Bulgaria,Bulgaria,Bulgaria,Bulgaria,Bulgaria,Bulgaria,Bulgaria
Call: EEN H2020 SGA2 2D BATCH (H2020-EEN-SGA2-2017-1, 2017)
Start date: 2017-03-01
End date: 2018-12-31
Duration (months): 22.0
Total project cost (EUR): 66905.0
EU funding (EUR): 66905.0
Participants: 12
Project status: CLOSED

The main objective of this project is to contribute to the implementation of the European policies in the field of innovation management capacity building in SMEs and their implementation in Bulgaria, resulting in effective and efficient investments in novelties leading to growth and quality jobs. As a major tool for improving global competitiveness of European companies, implementation of novelties in products, processes and society needs specially devoted attention and resources. This project will contribute to the better filtering and acceleration of innovation processes in Bulgarian SMEs, thus supporting growth and jobs. Supported companies are supposed to be better prepared for using Access to Finance instruments and attract investments in innovation.

Keywords: innovation management,innovation,smes
Color-enriching nano coating for mobile displays (COENCO Display)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Türkiye
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-12-01
End date: 2020-05-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Mobile phones and tablets have become an indispensable part of our lives. Mobile device users make many transactions with mobile phones and tablets during the day such as; sending emails, taking photos, reading newspapers, playing games, watching movies etc. According to the research, mobile device users prefer devices that are comfortable to use, do not threaten eye health and provide high quality images. Especially with the trends such as mobile phone gaming taking over from console gaming, the display quality has been a very decisive criteria behind the customers’ buying decision. While brands’ search on how to improve the display quality has been continuing, Quantum dot (QD) technology has created an atomic bomb effect among display suppliers. QD colour components are recognized as the next generation technology in displays. Display suppliers have begun to prefer the QD technology to improve color quality on screen when they discovered the advantages compared to existing technologies. CoENCo Display is a disruptive method that enables QD technology to be used in mobile phone and tablet displays. With its innovative method, it achieves to offer a wider variety of colors from nature on mobile phones and tablets. The global QD-based display market is expected to reach 9 billion USD in 2026 with a CAGR of 25.2%. Our target customers are quantum dot producers and component makers, which are the suppliers of brands like Samsung, Amazon and Apple. Our initial target markets are Germany and the UK. We have two types of sales models: Type A: Non-Exclusive Licensing, Type B: Material sales. Our target is to generate a revenue of 106 million Euro per year and create additional employment of 35 people by creating local and international partnerships by the fifth year of market introduction.

Keywords: display,tablets,quantum dots,mobile device
Modelling cell type evolution in animals (ModEvoCell)

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: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-04-01
End date: 2024-03-31
Duration (months): 24.0
Total project cost (EUR): 160932.48
EU funding (EUR): 160932.48
Participants: 1
Project status: SIGNED

Cell types with distinct functions coexist and cooperate within a single animal, eventually contributing to the endless forms most beautiful that define the animal kingdom. These cell types are complex phenotypes defined by multiple traits—ontogeny, morphology, regulatory and transcriptional states, etc.—that are ultimately encoded by the same genome, and are thus subject to the evolutionary process. Therefore, to study the diversity of cell types from an evolutionary perspective we need to first understand the patterns of conservation and divergence in the various traits that determine cell phenotypes. Among these traits, gene regulation is uniquely amenable to be systematically catalogued and compared across species, and it is an ideal candidates to support a model of cell type evolution. Here I propose to investigate the evolution of animal cell types in a multi-species comparative framework. I hypothesise that, by characterising the cell type and transcriptomic programmes of various species along a spectrum of phylogenetic divergence times, I will be able to infer a data-driven model to quantify the influence of regulatory divergence on cell type evolution. To that end, I will build cell type diversity atlases of six placozoan species and resolve their transcriptomic states at single-cell resolution using scRNA-seq, genome-wide profiling of regulatory regions (ATAC-seq and regulatory motif discovery), and gene regulatory network modelling. Placozoans are a uniquely well-suited model for this research: they have a strongly conserved yet profoundly simple bauplan, composed of few cell types, that can be fully resolve at the whole-organism level using single-cell transcriptomics. This taxon-rich survey across multiple species and cell types will allow me to address the fundamental question of how cell types emerge and diversify, and it will provide a theoretical basis to understand how regulatory divergence ultimately results in phenotypic innovation.
Scalable Linking and Integration of Big POI data (SLIPO)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Innovation actions
Partnership: Big Data PPP (cPPP)
Countries involved: Germany,Germany,Germany,Austria,Greece,Greece,Netherlands
Call: Big Data PPP: cross-sectorial and cross-lingual data integration and experimentation (H2020-ICT-2016-1, 2016)
Start date: 2017-01-01
End date: 2019-12-31
Duration (months): 36.0
Total project cost (EUR): 3087000.0
EU funding (EUR): 2635500.0
Participants: 8
Project status: CLOSED

POIs are the content of any application, service, and product even remotely related to our physical surroundings. From navigation applications, to social networks, to tourism, and logistics, we use POIs to search, communicate, decide, and plan our actions. The Big Data assets for POIs and the evolved POI value chain introduced opportunities for growth, but also complexity, intensifying the challenges relating to their quality-assured integration, enrichment, and data sharing. POI data are by nature semantically diverse and spatiotemporally evolving, representing different entities and associations depending on their geographical, temporal, and thematic context. Pioneered by the FP7 project GeoKnow, linked data technologies have been applied to effectively extract the maximum possible value from open, crowdsourced and proprietary Big Data sources. Validated in the domains of tourism and logistics, these technologies have proven their benefit as a cost-effective and scalable foundation for the quality-assured integration, enrichment, and sharing of generic-purpose geospatial data In SLIPO, we argue that linked data technologies can address the limitations, gaps and challenges of the current landscape in integrating, enriching, and sharing POI data. Our goal is to transfer the research output generated by our work in project GeoKnow, to the specific challenge of POI data, introducing validated and cost-effective innovations across their value chain

Keywords: data integration,linked data,geospatial data