Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Mechanisms of gradient decoding in fission yeast (SexYeast)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Cellular, Developmental and Regenerative Biology
Panel description: Structure and function of the cell, cell-cell communication, embryogenesis, tissue differentiation, organogenesis, growth, development, evolution of development, organoids, stem cells, regeneration, therapeutic approaches
Countries involved: Switzerland,Switzerland
Call: ERC ADVANCED GRANT (ERC-2020-ADG, 2020)
Start date: 2022-04-01
End date: 2027-03-31
Duration (months): 60.0
Total project cost (EUR): 2191927.0
EU funding (EUR): 1962105.0
Participants: 2
Project status: SIGNED

How does a cell orient in response to a chemical cue? This basic problem is at the core of how cells interact with their environment. Indeed, the ability to move towards the source of a chemical gradient underlies behaviours as diverse as feeding, identifying a foreign invader or building interconnected cellular networks. Furthermore, chemo-orientation forms the basis of gamete recognition, and is thus critical for genome diversification through sexual reproduction. This proposal makes use of one of the simplest eukaryotic models, the fission yeast S. pombe, to systematically dissect the mechanisms of gradient detection. Gradient sensing occurs during sexual reproduction in a speed-dating process for mate pairing, where dynamic cortical polarity patches secrete pheromones and become stabilized in response to those produced by the other mating type. Chemo-detection depends on a minimal kit of conserved eukaryotic proteins, suggesting that a complete understanding of gradient decoding is possible. We will work towards this goal through four specific aims: 1. to establish the rules of gradient decoding, using unbiased image analysis and caged pheromones; 2. to define the architecture of the communication site, by super-resolution and correlative light-electron microscopy; 3. to probe the molecular regulation of cellular speed-dating, which we hypothesize consists of a spatial decoder and dynamic oscillator; 4. to reveal natural modifiers of speed-dating for mate selection, by exploiting the diversity of wild strain isolates. By combining advanced live and correlative imaging with optogenetic, genetic, biochemical and genomic methods, this project will bring a conceptual and molecular understanding to the problem of gradient decoding. Due to the ancient and fundamental nature of gradient orientation, our discoveries will have impact on several fields of research, including those of immunity, wound healing, development, sexual reproduction and evolution.

Keywords: chemotropism,pheromone signalling,gpcr signalling,cdc42 gtpase,cell polarisation,fission yeast schizosaccharomyces pombe,fungi,sexual reproduction,mating,natural variation
Software Defined Storage for Big Data (IOSTACK)

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: Spain,Israel,Spain,Ireland,Slovenia,France
Call: Advanced Cloud Infrastructures and Services (H2020-ICT-2014-1, 2014)
Start date: 2015-01-01
End date: 2017-12-31
Duration (months): 36.0
Total project cost (EUR): 3318624.0
EU funding (EUR): 3318624.0
Participants: 8
Project status: CLOSED

The main objective is to create IOStack: a Software Defined Storage toolkit for Big Data on top of the OpenStack platform. IOStack will enable efficient execution of virtualized analytics applications over virtualized storage resources thanks to flexible, automated, and low cost data management models based on software defined storage (SDS). Major challenges are: 1) Storage and compute disaggregation and virtualization. Virtualizing data analytics to reduce costs implies disaggregation of existing hardware resources. This requires the creation a virtual model for compute, storage and networking that allows orchestration tools to manage resources in an efficient manner. We will provide policy-based provisioning tools so that the provisioning of virtual components for the analytics platform is made according to the set of QoS policies. 2) SDS Services for Analytics. The objective is to define, design, and build a stack of SDS data services enabling virtualized analytics services with improved performance and usability. Among these services we include native object store analytics that will allow running analytics close to the data without taxing initial migration, data reduction services, specialized persistent caching mechanisms, advanced prefetching, and data placement. 3) Orchestration and deployment of big data analytics services. The objective is to design and build efficient deployment strategies for virtualized analytic-as-a-service instances (both ephemeral and permanent). In particular, the focus of this work is on data-intensive systems such as Apache Hadoop and Apache Spark, which enable users to define both batch and latency-sensitive analytics. This objective includes the design of scalable algorithms that strive at optimizing a service-wide objective function (e.g., optimize performance, minimize cost) under different workloads. Finally, we will create a SDS toolkit for Big Data on top of the OpenStack projects Sahara, Cinder, Nova and Swift.

Keywords: software defined storage,big data analytics
Raising Innovation Capacity for Innovative Companies from Latvia (2019) (InnoSME-LV-2019)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Specific Grant agreement
Countries involved: Latvia
Call: EEN H2020 SGA3 (H2020-EEN-SGA3-2018, 2018)
Start date: 2019-01-01
End date: 2019-12-31
Duration (months): 12.0
Total project cost (EUR): 24757.5
EU funding (EUR): 24757.0
Participants: 2
Project status: CLOSED

The overall objective of the project is to contribute to smart growth in the European Union by increasing the efficiency and effectiveness of investments in research, development and innovation and by contributing to a better and more efficient connection of actors along the innovation chain. To achieve this objective the following measures are foreseen: • To support SMEs, as the beneficiaries of the SME Instrument, FTI and FET-Open to identify bottlenecks to the creation of economic impact in companies benefiting from grants by Horizon2020's SME instrument and address these bottlenecks with the help of capable coaches; • To increase the efficiency and effectiveness of innovation processes in small and medium sized enterprises with significant innovation activities that could potentially become beneficiaries of European support to research and innovation but would not have effective access to consulting services for innovation management. In practice at least 9 (nine) specialised service packages will be delivered to SMEs to assist them in successful participation in the Horizon 2020 SME support instruments and increase their innovation management capacity beyond this programme. The services addressed by the current proposal will be integrated in already existing Enterprise Europe Network services.

Keywords: sme instrument,key account manager,innovation management capacity
Peer Learning Innovation Services (PLIS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Italy,Spain,Denmark,United Kingdom
Call: Peer learning of innovation agencies (H2020-INNOSUP-05-2016-2017, 2016)
Start date: 2016-11-01
End date: 2017-10-31
Duration (months): 12.0
Total project cost (EUR): 50000.0
EU funding (EUR): 50000.0
Participants: 4
Project status: CLOSED

Peer Learning Innovation Services – PLIS aims at enabling innovation support institutions in regions across Europe to quickly and effectively develop initiatives that will engage, encourage and aid SMEs to use Service Innovation as a mean to maintaining or increasing competitiveness, profitability and jobs. A technology driven approach has prevailed for addressing innovation assessment. Given its critical contribution to increases in productivity and jobs, most of the resources within national and regional innovation policies are allocated to encouraging technology driven innovation resulting in the generation of new products and processes based on R&D. However other types of innovation such as Service Innovation are key to maximising economic development at local, regional and European level. Consequently, the members of the consortium will collaborate using a Twinning+ as a peer learning methodology in order to develop new approaches to foster Service Innovation among SMEs and improve the current innovation support programmes; enhance the quality, efficiency and customer satisfaction of services provided; increase the number of Service Innovation projects developed by SMEs; accelerate the learning process among the participants; foster the relationship between PLIS partners in innovation services; and, inspire and guide other agencies (and similar organisations) that become interested in how to foster Service Innovation among SMEs. All PLIS members are most relevant to participate in the peer-learning activities through the Twinning+ methodology given their role in designing and implementing SME innovation management support within their regions; their shared and common objectives; the commitment, motivation and experience of the people involved in the project; and, the capacity to disseminate PLIS findings in order to strengthen peer-learning and boost similar activities to relevant European organisations.

Keywords: peer learning,innovation agencies,business to business,business to consumers
A disruptive innovation for the minimisation of railway maintenance costs (DTD SYSTEM)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: SME instrument
Countries involved: Spain
Call: Small business innovation research for Transport and Smart Cities Mobility (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-06-01
End date: 2016-11-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Rail infrastructure managers in Europe invest yearly over €869 Million (from public funds) in repairing railway track damages caused by the poor conditions of train wheels. Nowadays, the most advanced systems to monitor the conditions of the train wheels (WID or Wheel Impact Detectors) to prevent/ minimise the damage produced to the railway track cannot anticipate accurately the occurrence of the failure or indicate to the train operating companies which maintenance operations must be performed and when it is the optimum moment. AMINSA have developed DTD System, an innovative system capable of detecting with high precision wheel defects at the onset of deterioration, and using this information to design a predictive maintenance plan. The added value of DTD SYSTEM compared to its competitors is based on: - Its superior accuracy thanks to the new filtering process carried out by its innovative analysis module (DTD system has been readily technically and operationally validated with a 99% success rate on the tracks of FGC-Spain). - Its ability to design an optimal preventive maintenance plan for wheel defects through a new software that works as a diagnosis module using artificial intelligence algorithms (train operator companies will reduce the number of failures and maintenance expenditures in their wheels by more than 20%). - Its lower price, up to 350,000 € less per unit than available WID systems in the market. DTD SYSTEM overcomes all limitations of the state-of the-art solutions available on the market, and looking at Europe only, opens the way to the market worth of nearly 61 M€ In Phase 1, we will focus on the elaboration of a comprehensive business plan and establish strategic alliances with key stakeholders, ensuring a quick market deployment through the development of a pilot or demonstration element in Phase 2. Additionally, we will choose the best intellectual property strategy to safeguard our competitive advantage.

Keywords: railway,wheel defects,wid systems,predictive maintenance,prognostic assessment,advisory generation
Polyphenols and Gut Microbiota interaction in Cardiovascular Health (PolyBiota)

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: Environment and Geosciences
Countries involved: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2020-07-16
End date: 2022-11-04
Duration (months): 24.0
Total project cost (EUR): 172932.48
EU funding (EUR): 172932.48
Participants: 1
Project status: CLOSED

Cardiovascular disease (CVD) is the main cause of mortality in Europe with an annual estimated cost of €210 billion. Different European Public Health strategies have targeted diet to prevent/treat CVDs. This multidisciplinary and multi-institutional project aims to provide new insights into the role of the gut microbiota as a key player in the beneficial effects against CVDs associated with the consumption of Polyphenols (PPs)-rich foods. PolyBiota will be developed through innovative research at one of the epicenters of PPs research (CEBAS-CSIC) and secondment at FISABIO (Valencia, Spain). Epidemiological, clinical, and preclinical studies suggest that the consumption of PPs-containing food protects against CVDs (i.e, modulating angiogenesis in atherosclerotic plaques) . However, these benefits are not always observed due to the high inter-individual variability. The gut microbiota has emerged as an essential player that regulates the bioactivity of PPs. Recent clinical trials indicate that the gut microbiota composition play a critical role in the activity of PPs improving CV biomarkers. These studies open a new door to investigate how the interaction PPs-gut microbiota can modulate mechanisms associated with the improvement of CVDs. PolyBiota will investigate: i) role of the gut microbiota as mediator of the effects of the consumption of Ellagitannins (ETs)-/urolithin (Uro)-A- and Isoflavones (IsoFlv)-/equol-enriched diets on angiogenesis/mechanisms related in untreated and antibiotic-treated animals, ii) the “prebiotic-like effect” of the ETs, Uro-A, IsoFlv and equol consumption on the gut microbiota population, iii) the effects of the gut microbiota-biosynthesized messenguers or the ETs- and IsoFlv-derived metabolites on in vitro tubulogenesis. PolyBiota shows an innovative approach combining cutting-edge techniques, “big data” management, endothelial cells, and in vivo animal models providing a holistic scene of the Diet-Gut Microbiota-Host interaction.

Keywords: diet,polyphenols,ellagitannins,urolithins,isoflavones,angiogenesis,cardiovascular diseases,microbiota
Advanced Light-weight BATteRy systems Optimized for fast charging, Safety, and Second-life applications. (ALBATROSS)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Innovation actions
Countries involved: Germany,Germany,Spain,Spain,Spain,Italy,Israel,Norway,Türkiye,Belgium,Sweden,Türkiye,Netherlands,United Kingdom,United Kingdom,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: Next generation and realisation of battery packs for BEV and PHEV (H2020-LC-BAT-2020, 2020)
Start date: 2021-01-01
End date: 2024-12-31
Duration (months): 48.0
Total project cost (EUR): 11818442.5
EU funding (EUR): 9991817.89
Participants: 22
Project status: SIGNED

ALBATROSS addresses the needs of European Electric and Hybrid-Electric passenger vehicle market by overcoming driver concerns relating to battery range and anxiety, cost, long-term reliability and excessive charging times. ALBATROSS will develop an integrated approach based on smart batteries combined with lightweight designs. Using innovative cooling technologies, we will achieve pack temperature range 5-40°C (30-40°C under ultra-fast charging), with <3°C variation between battery cells and optimal operating temperature 20-23°C. The light weighting solutions, based on modular multi-material systems for battery modules and trays, will be fabricated and joined using cutting edge, fast and cost-effective processes, with disassembly, recycling and reuse designed in as a part of an eco-design approach. The modular approach provides solutions for BEVs and PHEVs. The scalability to delivery vans and heavy-duty vehicles will be assessed. Using a BMW i3 passenger vehicle to base the developments on, ALBATROSS will achieve a Peak Energy Density >200Wh/kg, increase driving range to 480km and reduce charging times by 25%. Advanced sensing and control, as a part of a flexible advanced Battery Management System, will be utilised on-vehicle and using the cloud to conduct remote maintenance and troubleshooting ensuring safety even at these high energy densities. Using advanced analytics will enable the State of Health and State of Safety to be continuously and accurately measured. The system will be validated on-vehicle under real world, extreme environmental conditions. ALBATROSS represents a pan-European EU consortium of world leading organisations that are looking to commercialise these technologies of European origin. The coordinator (Yesilova) has a global presence in the automotive market and the consortium is strengthened by organisations that are part of the global Fiat-Chrysler, Ford and Mercedes-Benz groups as well as European SMEs with world leading technologies.

Keywords: electric vehicle,smart batteries,temperature control,lightweighting,battery management systems,state of health,state of safety,fast charging,battery safety,recycling,second life
Migration in cities of the global South: drivers, interactions and socio-demographic consequences (MIC)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Social World and Its Diversity
Panel description: Sociology, social psychology, social anthropology, education sciences, communication studies
Countries involved: Switzerland
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2021-07-01
End date: 2026-06-30
Duration (months): 60.0
Total project cost (EUR): 1499127.0
EU funding (EUR): 1499127.0
Participants: 1
Project status: SIGNED

Large scale rural-to-urban migration and associated urbanization in developing countries constitute an opportunity but also a risk for human development. In either case, urbanization may lead to increased international migration. Our understanding of the interactions between these two phenomena is constrained by the lack of evidence on subnational heterogeneity in international migration, and the traditional divide between internal and international flows in research. MIC provides the most comprehensive analysis of trends in both types of migration in more than 3000 cities and rural areas spanning all developing regions. We address three substantive research questions. In project A, we explore how internal and international migrations evolve over time across educational strata of population, the hierarchical distribution of settlements, and the national settings of urbanization. In project B, we examine why migration trends differ across these contexts. In project C, we investigate how migration transforms cities’ socio-demographic potential for human development. MIC is innovative in its global and comparative perspective on migration among metropolitan populations. This is enabled by the integration of spatial data and harmonized census records, creative use of indirect demographic estimation techniques, and advanced statistical methods for data analysis. Each of the three sub-projects has the potential for innovative results that are highly policy-relevant. Projects A & B will provide information on where and why we should expect increased international migration in rapidly urbanizing developing countries, and how this relates to the domestic movements. Project C identifies the consequences of migration for the processes of urbanization and human development. MIC will help governments to tailor their existing migration and development policies, to maximize the development impact of migration, and to make cities more sustainable.

Keywords: international migration,internal migration,urban hierarchy,urbanization,human development,metropolitan areas,global south
INtelligent Video analytics to analyse complex scenes and Enhance Security of critical infrastructure and urban soft Targets (Invest)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Action type: SME instrument
Countries involved: United Kingdom
Call: Critical infrastructure protection topic 7: SME instrument topic: “Protection of Urban soft targets and urban critical infrastructures” (H2020-SMEINST-1-2014, 2014)
Start date: 2015-01-01
End date: 2015-06-30
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

The INVEST project brings to market readiness innovative, disruptive, intelligent video analytics (IVA) technology to create a high performance system for threat detection to protect urban soft targets and critical infrastructure. It tackles a recognised need for advanced, retrofitable systems to enhance CCTV infrastructure performance. It will rapidly identify suspects in large volumes of video data, track them in real time across multiple video systems, with reliable re-identification of targets moving between CCTV systems across a city. The expected outcome of both phases will be a complete IVA platform transforming our TRL level 6 solution into a near market ready security product (with associated services), making high throughput detection and tracking of people in crowds for the first time a practical reality. This novel system has super resolution capability, automatic detection and machine learning algorithms to filter matches offering reliable re-identification and suspect tracking. The global security sector needs a game changing critical infrastructure surveillance solution for high throughput screening from CCTV data in reasonably real-time as security teams face increased volumes of video data as CCTV installations grow (up 21% 2011-2013). In 2011 CCTV cameras worldwide captured 1.4 trillion video-hours; most of which (84% in London) went unchecked. Our innovation is applicable to a global Homeland Security market valued at €5.8bn in 2012, trebling in size by 2020. End users include national security agencies, city police forces, private sector security firms, infrastructure owners and commercial businesses. This business innovation is aligned to SeeQuestor's strategy to profitably commercialise IVA technology increasing analyst productivity by a factor of 40, yielding 170% ROI within 1 Year for a metropolitan police force and generating revenue increasing from €0.375m (Year 2) to €55m (Year 6) with an EBITDA of €21m.

Keywords: video analysis,threat detection,identification and re identification,super resolution,video database,match and track