Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
What makes us cognitively flexible? A new learning perspective (CoCoFlex)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: Belgium
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-05-01
End date: 2025-10-31
Duration (months): 66.0
Total project cost (EUR): 1476812.0
EU funding (EUR): 1476812.0
Participants: 1
Project status: SIGNED

Much of human behavior is characterized by the extraordinary ability to quickly reconfigure our mind, and switch between different tasks, often referred to as cognitive flexibility. While most psychologists agree on the kind of behaviors that fall under the term cognitive flexibility, we have only a poor understanding on what drives cognitive flexibility. When defining cognitive flexibility, its putative underlying processes are often distinguished from other functions of the brain by opposing them to low-level learning. In contrast, this project starts from the idea that cognitive flexibility is grounded in reinforcement learning and associative learning, and thus sensitive to the same rules that low-level learned behavior is subject to. Therefore, the first two aims of this project will be to demonstrate that the processes behind cognitive flexibility can be conditioned by reward and controlled by the context. This approach breaks with a traditional view on cognitive flexibility as originating from a vague, independent supervisory system. Instead, it allows us to get a grip on cognitive flexibility, and study its neural mechanisms more closely. To this end, a third aim will be to test the counterintuitive hypothesis that increased neural variability (or "noise") in control regions of the brain is what allows for cognitive flexibility. Finally, I will apply this fundamentally different way of understanding cognitive flexibility to the clinical domain. Autism spectrum disorder (ASD) has been linked to deficits in cognitive flexibility, but studies have shown mixed results. Accordingly, a fourth aim will be to further the understanding of the assumed deficits in cognitive flexibility related to ASD. Overall, this project intends to change the current way of thinking about cognitive flexibility, and cognitive control more generally, and to cause a paradigmatic shift in how we go about assessing its neural mechanisms and deficits in clinical conditions like ASD.

Keywords: cognitive control,cognitive flexibility,executive functions,task switching,reward
Mapping the Interaction between Semantic Representation and Control Systems: The Controlled Semantic Cognition (MapInCSC)

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-2019, 2019)
Start date: 2020-08-01
End date: 2023-04-30
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: SIGNED

People, places and things have "meaning" that we use to know who/what they are and what we can do with them. Our ability to use that knowledge –our "Semantic Cognition"– is essential for making sense of what we see, enabling us to interact appropriately with the world. This important ability depends on two separate brain systems: the system of representations that encodes our conceptual knowledge and the system of control that manipulates activation within the representational system, generating appropriated behaviours. However, we do not yet know how the two systems interact. A fuller understanding of the semantic cognition depends on us uncovering this relationship in healthy behaviours and to know how is reshaped after brain damage/disruption. A joint account of both subsystems has been recently proposed by my supervisor: the Controlled Semantic Cognition (CSC). The key goal of this project is the neural computational modelling of the CSC and its disorders. I will model both semantic subsystems jointly for the first time by testing one healthy group and two patient groups with dissociated semantic disorders: semantic dementia (impaired in semantic representations); and semantic aphasia (impaired in semantic control). I will use different neuroimaging techniques such as DWMRI, fMRI and TMS in combination with the comparison between healthy controls and patients to model the dynamical causal networks, cross-validate the models and pinpoint the interactions between the semantic subnetworks, understanding how and under what circumstances they recruit each other. Our results will bring insights into how the brain manipulates information that gives rise semantic behaviours, advancing knowledge about a critical part of the human experience. Also in the implementation of methods for multimodal neuroimaging integration in the study of dynamics and plasticity in highly-distributed cognitive systems, such as CSC, in healthy and dysfunctional brains.

Keywords: semantic representation and control,resting state fmri,dw mri,structural and effective connectivity,dynamic causal modelling,network based statistic,multimodal neuroimaging integration
Medical Hyperspectral Image and Video Processing and Interpretation via Constrained Matrix and Tensor Factorization (HyPPOCRATES)

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: Information Science and Engineering
Countries involved: Greece,United States
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-10-07
End date: 2022-10-06
Duration (months): 36.0
Total project cost (EUR): 259808.64
EU funding (EUR): 259808.64
Participants: 2
Project status: CLOSED

Over the past few years hyperspectral (HS) imaging has been broadly applied in a wealth of different applications with remote sensing of the environment being the most prominent one. HS imaging provides a rich amount of information by generating images and videos of high spectral resolution captured at a wide range of the electro-magnetic spectrum. Recently, HS data have been shown to offer remarkable advances to a new field of significant interest i.e., medical HS (mHS) imaging. The high spectral resolution of HS data makes them amenable to identifying even subtle spectral differences related to various pathological conditions. In view of that, mHS images and videos have received considerable attention lately. mHS data have already been used for non-invasive diagnosis of several types of cancer e.g. brain, tongue cancer, as well as for diabetic foot diagnosis and surgical guidance. mHS imaging is anticipated to remarkably flourish in the years to come taking into account the recent advances that have occurred in the development of micro-size and low-cost HS cameras. However, despite this large progress in HS imaging hardware, sophisticated algorithms capable to interpret these data are still missing. HyPPOCRATES aims at deriving new powerful mHS image and video interpretation schemes tailored to mHS data processing, by applying novel machine learning ideas. To this end, the problems of subspace clustering and unmixing will be investigated for performing refined mHS image and video understanding. Along those lines, constrained matrix and tensor factorization approaches will be explored for devising computationally efficient and scalable machine learning algorithms. Overall, the main objective of the project is to bridge the gap between the recent advances in mHS imaging and those in machine learning research. This way, the researcher aspires to go the diagnostic process of several serious diseases, such as various types of cancer, one step further.

Keywords: machine learning,medical imaging,hyperspectral images and videos,matrix factorization,tensor decompositions
Maximizing freshness and minimizing losses of agriculture products through automated atmosphere management in storage facilities (MAX-FRESH)

Framework: Horizon 2020 — Industrial Leadership
Action type: Innovation actions
Countries involved: Sweden,Belgium,Netherlands,Denmark
Call: Fast Track to Innovation (FTI) (H2020-EIC-FTI-2018-2020, 2020)
Start date: 2020-10-01
End date: 2024-03-31
Duration (months): 42.0
Total project cost (EUR): 2817697.5
EU funding (EUR): 2165893.5
Participants: 4
Project status: SIGNED

Today, the fresh produce supply chain is highly unsustainable: 33% of the produced fruit and vegetables is either lost or wasted, of which 10% occurs during long-term storage. This loss also has a major financial impact on the food industry. For stored apples, pears and blueberries alone, the global economic loss equals €6.1 billion per year. However, a significant part of current storage losses could be prevented if only continuous monitoring of stored products was possible so that appropriate measures can be taken. In the MAX-FRESH project, we will develop the innovative ISS-Monitor: world’s first automated multi-species trace gas sensor that can simultaneously and in real-time detect low levels of 7 volatile gases that indicate ripening, fermentation, damage or rotting of stored fruit. Once unfavorable conditions are detected, the ISS-Monitor will provide automated alerts to enable timely and effective interventions by its customers. The ISS-Monitor has the potential to reduce losses of stored fresh food by 50%, extend storage life with 20%, and reduce post-harvest chemical treatments with 50%. The MAX-FRESH project builds on a functional prototype of the ISS-Monitor which demonstrated proof-of-performance in a relevant environment. During the MAX-FRESH project, we will take the final steps required to launch the ISS-Monitor on the market. To do so, we apply for €2.2 million (77%) from the EC. The MAX-FRESH project will be performed by a complementary consortium of 3 market-leading industrial partners and 1 academic partner, combining cutting-edge technologies with unique expertise. After completing the MAX-FRESH project in 2023, the ISS-Monitor wil be ready for market launch. By doing so, the ISS-Monitor will make an impact on the global food production system by contributing to sustainable food production for the ever-growing world population. Sales of the ISS-Monitor will generate cumulative revenues of €110 million for the MAX-FRESH consortium.

Keywords: trace gas detection,volatiles,real time monitoring,food waste management,fresh produce,sustainable food production,food quality,food safety,autonomous food storage control,world hunger
Ice-binding proteins: from antifreeze mechanism to resistant soft materials (PRISM)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting 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: Netherlands
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2015-05-01
End date: 2021-04-30
Duration (months): 72.0
Total project cost (EUR): 1661605.0
EU funding (EUR): 1661605.0
Participants: 1
Project status: CLOSED

Crystallization of water into ice is lethal to most organisms and detrimental to many soft materials. Freeze-tolerant fish living in polar seas evolved to tackle this problem with an unusual coping strategy. They produce ‘antifreeze’ proteins that block the growth of nascent ice crystals within a narrow temperature range known as the ‘thermal hysteresis gap’ enabling survival under extreme conditions. Encoding this functionality into synthetic polymers would open up new avenues in biomedicine, agrifood and materials science for e.g. cryopreservation, crop hardiness, ice-templating, dispersion stability, and advanced coatings. Progress requires a profound understanding of the mechanism of non-colligative freezing point depression at the molecular level and allows for efficient strategies for the design and preparation of powerful macromolecular antifreezes. I propose to unravel how antifreeze proteins work and to build upon these insights to explore effective routes towards ice-binding polymers aiming to make sensitive soft materials freeze-resistant. Within this challenge we first focus on single-molecule experiments to visualize bound proteins and study the strength of the non-covalent interaction with ice. We will study if and when adsorption on ‘foreign’ interfaces and solution assembly impact activity. These fundamental insights will guide our research towards synthetic antifreeze agents with superior functionality to achieve record supercooling in complex environments. This knowledge-based design of polymers with high affinity for crystalline interfaces holds great promise for many areas of science and technology in which crystallization plays a decisive role.

Keywords: soft materials,experimental soft matter,antifreeze protein,ice binding polymer,interface science,surface activity,adsorption,self assembly
Recombination, sex-specific adaptation and evolution of the poeciliid sex chromosomes (GuppY)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: United Kingdom,United Kingdom
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-08-01
End date: 2022-07-31
Duration (months): 72.0
Total project cost (EUR): 1999665.0
EU funding (EUR): 372784.09
Participants: 2
Project status: CLOSED

Sex chromosomes have evolved independently countless times throughout the eukaryotes. As such, sex chromosomes represent one of the most pervasive examples of convergent evolution, as analogous yet unrelated sex chromosomes share many unique features that distinguish them from the rest of the genome. Although models for sex chromosome evolution have been proposed, they have been difficult to empirically test, largely because most model systems are at a terminal phase of sex chromosome divergence, and the majority of studies have therefore focused on the consequences of sex chromosome evolution. In order to understand the forces catalyzing sex chromosome evolution, we require a study system at earlier stages of sex chromosome divergence, ideally one where there is still extensive polymorphism among populations and closely related species in the degree and region of recombination suppression, and with easily identified sexually antagonistic traits. These traits are all exhibited by the Poeciliid fishes, the focus of GuppY, which is designed to test long-standing theories about sex chromosome evolution. The overarching goals of the project are to: 1) identify the mechanisms, catalysts and consequences of recombination suppression between the sex chromosomes, and 2) to quantify the role of sex-specific selection and sexual conflict in sex chromosome evolution and subsequent divergence. These goals will be accomplished through the synthesis of phenotypic, experimental and next-generation molecular genetic approaches in order to provide a cohesive and multi-faceted understanding of sex chromosome evolution. Moreover, these goals will be performed across three evolutionary levels, integrating patterns of variation within populations, among populations, and across related species, permitting insights encompassing short, medium and long time-spans and yielding unprecedented insight into multiple stages of evolutionary history.

Keywords: sex chromosomes,sexual selection,recombination
Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change (APPLICATE)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Fighting and adapting to climate change
Action type: Research and Innovation actions
Countries involved: Spain,Iceland,Germany,Norway,Norway,Belgium,Sweden,Norway,Russian Federation,France,France,France,United Kingdom,United Kingdom
Call: Impact of Arctic changes on the weather and climate of the Northern Hemisphere (H2020-BG-2016-1, 2016)
Start date: 2016-11-01
End date: 2021-04-30
Duration (months): 54.0
Total project cost (EUR): 8715066.25
EU funding (EUR): 7999591.25
Participants: 18
Project status: CLOSED

Arctic climate change increases the need of a growing number of stakeholders for trustworthy weather and climate predictions, both within the Arctic and beyond. APPLICATE will address this challenge and develop enhanced predictive capacity by bringing together scientists from academia, research institutions and operational prediction centres, including experts in weather and climate prediction and forecast dissemination. APPLICATE will develop a comprehensive framework for observationally constraining and assessing weather and climate models using advanced metrics and diagnostics. This framework will be used to establish the performance of existing models and measure the progress made within the project. APPLICATE will make significant model improvements, focusing on aspects that are known to play pivotal roles in both weather and climate prediction, namely: the atmospheric boundary layer including clouds; sea ice; snow; atmosphere-sea ice-ocean coupling; and oceanic transports. In addition to model developments, APPLICATE will enhance predictive capacity by contributing to the design of the future Arctic observing system and through improved forecast initialization techniques. The impact of Arctic climate change on the weather and climate of the Northern Hemisphere through atmospheric and oceanic linkages will be determined by a comprehensive set of novel multi-model numerical experiments using both coupled and uncoupled ocean and atmosphere models. APPLICATE will develop strong user-engagement and dissemination activities, including pro-active engagement of end-users and the exploitation of modern methods for communication and dissemination. Knowledge-transfer will also benefit from the direct engagement of operational prediction centres in APPLICATE. The educational component of APPLICATE will be developed and implemented in collaboration with the Association of Early Career Polar Scientists (APECS).

Keywords: weather and climate prediction,impact of arctic climate change on mid latitudes,arctic observing system design,knowledge transfer,education
5G HarmoniseD Research and TrIals for serVice Evolution between EU and China (5G-DRIVE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Belgium,Greece,Croatia,Poland,Switzerland,Finland,Switzerland,Finland,Greece,Greece,Netherlands,United Kingdom,United Kingdom,Luxembourg,Portugal
Call: EU-China 5G Collaboration (H2020-ICT-2018-1, 2018)
Start date: 2018-09-01
End date: 2021-06-30
Duration (months): 34.0
Total project cost (EUR): 6007128.28
EU funding (EUR): 5999130.0
Participants: 21
Project status: CLOSED

5G-DRIVE will trial and validate the interoperability between EU & China 5G networks operating at 3.5 GHz bands for enhanced Mobile Broadband (eMBB) and 3.5 & 5.9 GHz bands for V2X scenarios. The key objectives are to boost 5G harmonisation & R&I cooperation between EU & China through strong connected trials & research activities, with a committed mutual support from the China “5G Product R&D Large-scale Trial” project led by China Mobile. To achieve these objectives and to deliver the impact for early 5G adoption, 5G-DRIVE structures its main activities into three pillars. The first one will test and demonstrate the latest 5G key technologies in eMBB and V2X scenarios in pre-commercial 5G networks. 5G-DRIVE will run three extensive trials in Finland, Italy and UK. The Chinese project will run large-scale trials in five cities. These twinned trials aim to evaluate synergies and interoperability issues and provide recommendations for technology and spectrum harmonisation. The second one focuses on researching key innovations in network slicing, network virtualisation, 5G transport network, edge computing and New Radio features to fill gaps between standards and real-world deployment. The third one will push EU-China 5G collaboration at all levels thru extensive dissemination and exploitation actions. The project formed a strong team of mobile operators and industry, including a prominent car manufacturer, SMEs, research institutes and universities. This well-balanced consortium has the necessary skills with an established close cooperation with the Chinese consortium will provide first class expertise to achieve full interoperability of the 5G networks and V2X between the EU and China. 5G-DRIVE is ideally set to instill tremendous impact on the validation of standards and trigger the roll-out of real 5G networks and V2X innovative solutions driving new business opportunities and creating thereby new jobs and brand new business models.

Keywords: 5g networks,enhanced mobile broadband embb,internet of vehicles iov,vehicle to vehicle v2v communications,vehicle to network v2n communications,service orchestration and management
Keel beam manufacturing oriented solution (KEELBEMAN)

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: Spain,Italy,Spain,France
Call: Manufacturing oriented solution keel beam (H2020-CS2-CFP06-2017-01, 2017)
Start date: 2018-03-01
End date: 2019-12-31
Duration (months): 22.0
Total project cost (EUR): 653432.5
EU funding (EUR): 598335.26
Participants: 4
Project status: CLOSED

The Project address the manufacturing of a keelbeam using thermoplastic resin reinforced with carbon fiber. The use of manufacturing technologies with a lot of potential for automation is also explored. The Main target of reducing assembly cost is addressed with minimizing the use of fasteners.and use of very innovative welding technology

Keywords: thermoplastics,compression moulding,induction welding,joining,pekk,carbon fiber,keel beam,testing,continuos moulding