Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Molecular atlas of the brain across the human lifespan (BRAINTIME)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Understanding health, wellbeing and disease
Action type: Research and Innovation actions
Countries involved: Israel,Switzerland,Sweden,United States
Call: Pilot actions to build the foundations of a human cell atlas (H2020-SC1-2019-Single-Stage-RTD, 2019)
Start date: 2020-01-01
End date: 2022-06-30
Duration (months): 30.0
Total project cost (EUR): 4328051.25
EU funding (EUR): 4328051.25
Participants: 5
Project status: CLOSED

BRAINTIME brings together six laboratories that are international leaders in the field of single-cell genomics with the aim to apply their knowledge and expertise to understand the human brain. In BRAINTIME, we will: (1) Perform a comprehensive multi-omic analysis of the developing human midbrain and hindbrain to generate an atlas of key monoaminergic cell populations in healthy adulthood, ageing and neurodegenerative disease; (2) Embed our new cell type maps into 3D contexts and temporal developmental models by integrating new approaches for computational modelling, cell fate tracking, spatial analysis and capturing cell-cell interactions; (3) Establish single-cell genomics-empowered ex-vivo protocols and standardized ex-vivo/in-vivo projection algorithms to allow flexible model testing and perturbation analysis on midbrain and hindbrain tissues; (4) Establish an effective and sustainable technological and analytical pipeline for the analysis of brain tissue at the single-cell level that can be used by the community to probe other brain regions or states and be extended to other human tissues. Achieving these objectives will significantly advance the Human Cell Atlas initiative by contributing major new datasets on human brain development and ageing, and ensure a key role for European labs in the global effort. Through the US partner (Ed Lein / Allen Institute), a crucial connection to the NIH BRAIN initiative will be ensured, including access to significant computational and atlasing resources. Through the SME partner (CartaNA), we gain access to cutting edge in-situ sequencing methods and support the fledgling European biotech industry in the single-cell field.

Keywords: single cell rna brain neuroscience
Cyclone processes leading to extreme rainfall in the Mediterranean region (ExMeCy)

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: Greece
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2016-05-01
End date: 2018-04-30
Duration (months): 24.0
Total project cost (EUR): 152653.2
EU funding (EUR): 152653.2
Participants: 1
Project status: CLOSED

Mediterranean cyclones are among the most important natural hazards in the region, affecting more than 135 million people. The physical mechanisms that make Mediterranean cyclones evolve into severe storms are not yet fully understood due to many uncertainties in the underlying atmospheric processes. These processes are mainly associated with deep convection and air-sea interactions at meso-scales, as well as with large-scale atmospheric systems that affect the region. The scientific objective of the project is to show how these processes lead to extreme rainfall in the Mediterranean and contribute to the better forecasting of cyclones induced extreme rainfall. Analysis within ExMeCy is based on a multi-methodological approach that includes fundamental atmospheric dynamical analysis, analysis of lightning and satellite observational datasets, and modelling adapted to the project needs. First the Researcher will detect the cyclones causing extreme rainfall. Then, he will classify these cyclones according to the contribution of the main processes associated with extreme rainfall, namely the deep convection and the airstreams of warm conveyor belts. Different cyclone groups will be thus formed, which will be analyzed separately using new modelling and diagnostic techniques, applied for the first time to Mediterranean cyclones. The decomposition of the complex interactions of atmospheric processes that lead to cyclones intensification and extreme rainfall will constitute ExMeCy’s original results. These results will be eventually used to assess European services models to predict cyclones-related high impact weather in the Mediterranean. The project will be hosted at the Institute for Environmental Research & Sustainable Development (IERSD) of the National Observatory of Athens (NOA).

Keywords: mediterranean cyclones,extreme rainfall
Synchro-modal Supply Chain Eco-Net (SYNCHRO-NET)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Countries involved: Ireland,Italy,Germany,Germany,Spain,Ireland,Ireland,Germany,Italy,Spain,Norway,Greece,Switzerland,France,France,United Kingdom,United Kingdom,United Kingdom
Call: De-stressing the supply chain (H2020-MG-2014_TwoStages, 2014)
Start date: 2015-05-01
End date: 2018-10-31
Duration (months): 42.0
Total project cost (EUR): 7569195.0
EU funding (EUR): 7301194.5
Participants: 23
Project status: CLOSED

SYNCHRO-NET will demonstrate how a powerful and innovative SYNCHRO-modal supply chain eco-NET can catalyse the uptake of the slow steaming concept and synchro-modality, guaranteeing cost-effective robust solutions that de-stress the supply chain to reduce emissions and costs for logistics operations while simultaneously increasing reliability and service levels for logistics users. The core of the SYNCHRO-NET solution will be an integrated optimisation and simulation eco-net, incorporating: real-time synchro-modal logistics optimisation (e-Freight-enabled); slow steaming ship simulation & control systems; synchro-modal risk/benefit analysis statistical modelling; dynamic stakeholder impact assessment solution; and a synchro-operability communications and governance architecture. Perhaps the most important output of SYNCHRO-NET will be the demonstration that slow steaming, coupled with synchro-modal logistics optimisation delivers amazing benefits to all stakeholders in the supply chain: massive reduction in emissions for shipping and land-based transport due to modal shift to greener modes AND optimised planning processes leading to reduced empty kms for trucks and fewer wasted repositioning movements. This will lead to lower costs for ALL stakeholders – shipping companies and logistics operators will benefit from massive reduction in fuel usage, faster turnaround times in ports & terminals and increased resource utilisation/efficiency. Customers and end users will have greater control of their supply chain, leading to more reliable replenishment activity and therefore reduced safety stocks and expensive warehousing. Authorities and governmental organisations will benefit from a smoother, more controlled flow of goods through busy terminals, and reduction of congestion on major roads, thus maximising the utilisation of current infrastructure and making the resourcing of vital activities such as import/export control, policing and border security less costly.

Keywords: supply chain,synchro modality,slow steaming,ship modelling,e freight,real time scheduling,collaborative business models
BSN Anatolia supports to increase the innovation management capacities of SMEs (BSNinnoSME)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Türkiye,Türkiye
Call: INNOSUP (H2020-Adhoc-2014-20, 2014)
Start date: 2014-07-01
End date: 2014-12-31
Duration (months): 6.0
Total project cost (EUR): 36198.0
EU funding (EUR): 36198.0
Participants: 3
Project status: CLOSED

The proposed project addresses the action for “Establishing services “Enhancing the innovation management capacity of SMEs” in the Enterprise Europe Network” to improve the innovation management capacity of SMEs. In the period covering the years 2008-2014, Tier 1 and Tier 2 services were offered to SMEs by BSN Anatolia Consortium. (The contents of Tier 1 and Tier 2 were respectively generic promotion, networking services given by EEN staff and specialized advisory services given by innovation advisers). The activities foreseen under this proposal is to give Tier 3 services to SMEs. 14 full enhancing SMEs’ innovation management capacity service packages will be offered to SME’s till the end of 2014 and every service package is foreseen as 7 days in the proposal. Additionally, 5 day KAM services (2,5 days/SME) will be offered for successful beneficiaries of SME instrument Phase 1. Therefore, a total number of 103 work days will be spent in the second half of 2014 for tier3 activities.

Keywords: innovation management,key account management
Dynamic Origins of MHC class I Selector function (DynOMIS)

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: 2016-09-06
End date: 2018-09-05
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

DynOMIS aims to elucidate the antigen selection mechanisms of the adaptive immune system at the molecular level in the highly complex cellular environment. Major histocompatibility complex class I molecules (MHC-I) is a key mediator of adaptive immunity, the cell’s arsenal against infectious pathogens and malignant transformations. MHC-I present antigenic peptides to cytotoxic T lymphocytes at the cell surface, which in turn unleash their cytotoxic apparatus only when peptides from non-healthy proteins are recognized. This process is the result of an equally important peptide selecting function in the early secretory pathway, a mechanism that has not been clearly understood in spite of its fundamental role in vaccination. Deep understanding of the exact mechanisms that drive peptide selection by MHC-I will help to predict immunoprotective epitopes in infections and cancer, which will in turn pave the way for the development of more effective T cell-targeting vaccines and biomarkers to stratify patients’ suitability for immunotherapy. DynOMIS will employ a sophisticated, interdisciplinary approach that integrates quantitative computational systems modelling to identify molecular mechanism from cellular biochemical information, experimental investigation of the structure and dynamics of peptide-bound MHC-I over a large range of timescales, and state-of-the-art molecular dynamics simulations and free energy calculations to elucidate the thermodynamic basis of the peptide selection mechanism in the context of their interactions with cellular cofactors. To this end, DynOMIS will be carried out by an experienced researcher at a world-leading interdisciplinary group comprising molecular immunologists, structural biologists, computational chemists, and industrial partners with a strong focus on clinically relevant immunological research.

Keywords: tapasin,peptide loading complex,protein structure,nuclear magnetic resonance,enhanced sampling molecular dynamics,free energy calculations,quantitative computational systems modelling
COSMOS: Computational Shaping and Modeling of Musical Structures (COSMOS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Cultures and cultural production
Panel description: Literary studies, cultural studies, study of the arts, philosophy
Countries involved: France,United Kingdom,United Kingdom
Call: ERC Advanced Grant (ERC-2017-ADG, 2017)
Start date: 2019-06-01
End date: 2025-11-30
Duration (months): 78.0
Total project cost (EUR): 2495776.25
EU funding (EUR): 1510721.47
Participants: 3
Project status: SIGNED

Music performance is considered by many to be one of the most breath taking feats of human intelligence. That music performance is a creative act is no longer a disputed fact, but the very nature of this creative work remains illusive. Taking the view that the creative work of performance is the making and shaping of music structures, and that this creative thinking is a form of problem solving, COSMOS proposes an integrated programme of research to transform our understanding of the human experience of performed music, which is almost all music that we hear, and of the creativity of music performance, which addresses how music is made. The research themes are as follows: i) to find new ways to represent, explore, and talk about performance; ii) to harness volunteer thinking (citizen science) for music performance research by focussing on structures experienced and problem solving; iii) to create sandbox environments to experiment with making performed structures; iv) to create theoretical frameworks to discover the reasoning behind the structures perceived and made; and, v) to foster community engagement by training experts to provide feedback on structure solutions so as to increase public understanding of the creative work in music performance. Analysis of the perceived and designed structures will be based on a novel duality paradigm that turns conventional computational music structure analysis on its head to reverse engineer why a perceiver or a performer chooses a particular structure. Embedded in the approach is the use of computational thinking to optimise representations and theories to ensure accuracy, robustness, efficiency, and scalability. The PI is an established performer and a leading authority in music representation, music information research, and music perception and cognition. The project will have far reaching impact, reconfiguring expert and public views of music performance and time-varying music-like sequences such as cardiac arrhythmia.

Keywords: music performance studies,music perception and cognition
Dissipative self-assembly in synthetic systems: Towards life-like materials (LifeLikeMat)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Synthetic Chemistry and Materials
Panel description: New materials and new synthetic approaches, structure-properties relations, solid state chemistry, molecular architecture, organic chemistry
Countries involved: Israel
Call: ERC Consolidator Grant (ERC-2018-COG, 2018)
Start date: 2019-01-01
End date: 2023-12-31
Duration (months): 60.0
Total project cost (EUR): 1999572.0
EU funding (EUR): 1999572.0
Participants: 1
Project status: SIGNED

Living organisms are sophisticated self-assembled structures that exist and operate far from thermodynamic equilibrium and, as such, represent the ultimate example of dissipative self-assembly. They remain stable at highly organized (low-entropy) states owing to the continuous consumption of energy stored in "chemical fuels", which they convert into low-energy waste. Dissipative self-assembly is ubiquitous in nature, where it gives rise to complex structures and properties such as self-healing, homeostasis, and camouflage. In sharp contrast, nearly all man-made materials are static: they are designed to serve a given purpose rather than to exhibit different properties dependent on external conditions. Developing the means to rationally design dissipative self-assembly constructs will greatly impact a range of industries, including the pharmaceutical and energy sectors. The goal of the proposed research program is to develop novel principles for designing dissipative self-assembly systems and to fabricate a range of dissipative materials based on these principles. To achieve this goal, we will employ novel, unconventional approaches based predominantly on integrating organic and colloidal-inorganic building blocks. Specifically, we will (WP1) drive dissipative self-assembly using chemical reactions such as polymerization, oxidation of sugars, and CO2-to-methanol conversion, (WP2) develop new modes of intrinsically dissipative self-assembly, whereby the activated building blocks are inherently unstable, and (WP3&4) conceive systems whereby self-assembly is spontaneously followed by disassembly. The proposed studies will lead to new classes of "driven" materials with features such as tunable lifetimes, time-dependent electrical conductivity, and dynamic exchange of building blocks. Overall, this project will lay the foundations for developing new synthetic dissipative materials, bringing us closer to the rich and varied functionality of materials found in nature.

Keywords: self assembly,nanoparticles,nanoscience
Training Data-driven Experts in OPTimization (TraDE-OPT)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Training Networks
Action type: Marie Skłodowska-Curie actions
Panel: Mathematics
Countries involved: Austria,Germany,Italy,Belgium,Romania,Poland,France
Call: Innovative Training Networks (H2020-MSCA-ITN-2019, 2019)
Start date: 2020-06-01
End date: 2024-05-31
Duration (months): 48.0
Total project cost (EUR): 3774874.32
EU funding (EUR): 3774874.32
Participants: 8
Project status: SIGNED

The main goal of TraDE-Opt is the education of 15 experts in optimization for data science, with a solid multidisciplinary background, able to advance the state-of-the-art. This field is fast-developing and its reach on our life is growing both in pervasiveness and impact. The central task in data science is to extract meaningful information from huge amounts of collected observations. Optimization appears as the cornerstone of most of the theoretical and algorithmic methods employed in this area. Indeed, recent results in optimization, but also in related areas such as functional analysis, machine learning, statistics, linear algebra, signal processing, systems and control theory, graph theory, data mining, etc. already provide powerful tools for exploring the mathematical properties of the proposed models and devising effective algorithms. Despite these advances, the nature of the data to be analyzed, that are “big”, heterogeneous, uncertain, or partially observed, still poses challenges and opportunities to modern optimization. The key aspect of the TraDE-Opt research is the exploitation of structure, in the data, in the model, or in the computational platform, to derive new and more efficient algorithms with guarantees on their computational performance, based on decomposition and incremental/stochastic strategies, allowing parallel and distributed implementations. Advances in these directions will determine impressive scalability benefits to the class of the considered optimization methods, that will allow the solution of real world problems. To achieve this goal, we will offer an innovative training program, giving a solid technical background combined with employability skills: management, fund raising, communication, and career planning skills. Integrated training of the fellows takes place at the host institute and by secondments, workshops, and schools. As a result, TraDE-Opt fellows will be prepared for outstanding careers in academia or industry.

Keywords: convex optimization,large scale optimization,first order splitting methods,image processing,regularization approaches,incremental and stochastic algorithms,parallel and distributed computations
Establishing services enhancing the innovation management capacity of SME's in the Lithuanian Enterprise Europe Network consortia (SME CoachLT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Lithuania
Call: INNOSUP (H2020-Adhoc-2014-20, 2014)
Start date: 2014-07-01
End date: 2014-12-31
Duration (months): 6.0
Total project cost (EUR): 11812.5
EU funding (EUR): 9450.0
Participants: 1
Project status: CLOSED

The overall aim of SME CoachLT is to increase effectiveness and efficiency of investment in R&D and Innovation by enhancing innovation management capacity of Lithuanian SMEs -beneficiaries of the new dedicated SME instrument under Horizon 2020, and SMEs with significant innovation activities and a high potential for internationalisation. Specifically, the project will support SMEs - beneficiaries of the SME instrument- in identifying project-specific barriers and weaknesses and gaps in their innovation capacities that hinder realization of growth opportunities, and pointing to suitable coaches to address the identified weaknesses. The second specific objective is supporting SMEs with significant innovation activities and a high potential internationalization in enhancing their innovation management capacities. The Key Account Manager will support SMEs SME Instrument beneficiaries in identifying critical issues and gaps with regards to their innovation idea and guide them to relevant lead coach who will support the company throughout their innovation journey. The Key account Manager will use a holistic and dynamic business innovation model, supported by Business Innovation Roadmap Tool, available under Creative Commons License from smE-MPOWER network. Based on the systematic assessment logic embedded in the tool, the Key Account Manager will guide the company through a transparent and easy-to-use self-assessment process. When supporting companies having innovation and internationalization potential, but not part of SME instrument, we will use IMP3rove Academy’s diagnostic tool which measures the performance of the company’s innovation management system. However taking into account the SME context, we intend to use action- based (and case-driven) learning approach to addressing identified gaps in the innovation system. smE-MPOWER tools can support the coaching process.

Keywords: innovation management,sme instrument