Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Cortical hierarchy of memories - deciphering the neuronal mechanisms of serial dependence in the human brain (CHROME)

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: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-09-01
End date: 2025-07-20
Duration (months): 24.0
Total project cost (EUR): 174806.4
EU funding (EUR): 174806.4
Participants: 1
Project status: SIGNED

“Perception is never purely in the present–it has to draw on experience of the past.” O. Sacks illustrates a grounding principle in cognitive neuroscience: Eyes are not vision. Instead, seeing is an inferential process, with the brain integrating incoming with past sensory information. This idea, that perception and memory are deeply intertwined, has shaped many theories of neural computation. Yet research on these building blocks of cognition has largely evolved in separate fields. In the long-term, I aim to overcome this conceptual divide and understand the mechanistic principles by which memory and perception shape each other. In this fellowship, I will lay the foundation for this research vision and acquire the skills necessary to lead a group on this innovative program. I will work with authorities in invasive electrophysiology (L. Melloni) and dynamical systems (V. Priesemann) to tackle a current frontier in the neurosciences and unravel the brain and circuit-level mechanisms of serial dependence. A perceptual memory integrating past with current percepts, serial dependence offers a unique window into the interplay of perception and memory: It comes in multiple flavors (attractive & repulsive effects) and occurs at multiple timescales. A simple, untested hypothesis may account for this diversity: I propose that there is a hierarchy of perceptual memories, with different integration times and tuning features, all acting jointly to shape perception. I will test this innovative framework with behavioral studies (to map the spatio-temporal tuning profile of serial dependence), computational modeling (to probe how intrinsic timescales of a hierarchically organized neural network affect serial dependence), and non-invasive and invasive electrophysiology (to identify the cortical & hippocampal brain mechanisms supporting serial dependence). If successful, this work will provide a unifying framework of how memory, in the form of serial dependence, alters perception.

Keywords: perceptual memories,serial dependence,ieeg,recurrent neural network
Is your heart aging well? A systems biology approach to characterize cardiac aging from the cell to the body surface (MODELAGE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Spain
Call: ERC Starting Grant (ERC-2014-STG, 2014)
Start date: 2015-10-01
End date: 2021-09-30
Duration (months): 72.0
Total project cost (EUR): 1498636.0
EU funding (EUR): 1498636.0
Participants: 1
Project status: CLOSED

Europe is facing a striking change in its demographics with an increasingly larger proportion of citizens aged 65 years and over. Aging is characterized by a progressive decline in the physiological functions of the body, with very notable effects on the heart. These effects are associated with a higher prevalence of arrhythmias, which, on top of deteriorating quality of life, increase the risk of other cardiovascular diseases like stroke, heart failure and neurological sequelae. Investigations targeting cardiac aging have often focused on assessing the effects of a specific contributing factor, at a single evaluation scale (molecular, cell, tissue, organ) and in many cases using animal species not relevant to humans in terms of aging mechanisms. MODELAGE proposes a multi-scale, multi-factorial research that is expected to make an important step in the characterization of human heart aging at both the population and individual levels. MODELAGE will work on an integrative methodological framework in which in silico modeling will be combined with in vitro cell and tissue analysis and in vivo electrocardiographic evaluation to investigate how cardiac aging manifests at a range of scales, from cell to body surface, and how electrical, structural and autonomic alterations contribute to such manifestations in humans. Indices describing spatio-temporal dynamics of cardiac electrophysiology will be evaluated in a population of young to senescent individuals using a novel feedback control approach. Inter-individual age-related variations in those indices will be assessed and correlated with markers of biological age (as opposed to chronological age). By investigating the mechanisms underlying inter-individual differences in cardiac dynamics, MODELAGE will set links to arrhythmia susceptibility and will propose novel non-invasive markers to identify high-risk senescent individuals for which preventive anti-arrhythmic treatment should be considered.

Keywords: in silico modeling,cardiac aging,signal processing,electrocardiogram,ventricular electrophysiology,arrhythmic risk markers,inter and intra individual variability
CarbonOrO (CarbonOrO)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Netherlands
Call: Stimulating the innovation potential of SMEs for a low carbon and efficient energy system (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-05-01
End date: 2016-09-30
Duration (months): 5.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Countries all over the world are trying to move towards a low-carbon economy, by cutting on CO2 production or CO2 emission. At the same time the digestion of biomass into biogas is developing all over Europe. This also gives huge amounts of CO2. Solutions to curb the amount of carbon dioxide (CO2) and mitigate climate change caused by burning fossil fuels and producing biogas are: - By capturing carbon dioxide out of the raw biogas and reuse the CO2 in greenhouses - by capturing CO2 at big emitting installations and by storing it permanently underground in geological formations or depleted oil and gas fields. CarbonOrO-technology CarbonOrO has developed an innovative low energy technology to capture CO2 from gasses. This technology is energy efficient (low desorber temperature) and highly cost efficient as it runs on (low-cost or zero-cost) waste heat. Energy savings are 10-25% and costs savings up to 50% in comparison with existing carbon capture technologies. Current applications are in improving biogas quality and in the production of CO2. Future use may include the capture of CO2 from flue gasses at e.g. power plant and steel mills, followed by underground storage, in order to mitigate climate change caused by burning fossil fuels. CarbonOrO is looking to expand its business internationally and therefore will explore the EU-market for carbon capture. Specific objectives in this H2020-SMEINT Phase 1 feasibility study are: - Explore at least 5 (up to 10) promising business cases for the CarbonOrO technology; - Evaluate the required specifications and characteristics of these applications with potential partners and clients; - Elaborate on a detailed business plan.

Keywords: climate action,environment resource efficiency and raw materials,carbon dioxide,carbon capture
EGNSS high Accuracy SYstem improving PhotoVoltaic plants maintenance (EASY Pv)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Action type: Innovation actions
Countries involved: Italy,Italy,Italy,Italy,Denmark,Denmark,United Kingdom
Call: Small and Medium Enterprise (SME) based EGNSS applications (H2020-Galileo-2015-1, 2015)
Start date: 2016-02-01
End date: 2018-01-31
Duration (months): 24.0
Total project cost (EUR): 1284068.75
EU funding (EUR): 935973.13
Participants: 7
Project status: CLOSED

EGNSS high Accuracy SYstem improving PhotoVoltaic plants maintenance. The purpose of the EASY PV proposal is to provide a time and cost effective service as direct response to the growing need expressed by several maintainers and PV field owners to enhance the energy production of their plants. As photovoltaic plants are aging, it is not uncommon that their production lowers due to inefficiency caused by unknown modules on the plant lowering the whole plant’s productivity. Thermal inspections are valuable for PV owners and maintainers, but relevant procedures (currently performed by operators with handheld cameras) are time demanding and sometimes expensive due to safety costs for the personnel involved in the operations (e.g.: PV modules on roofs, rough areas, …). It stands to reason that today such operations are not fully automated yet and the responsive recognition of a broken module might result very difficult in a large PV plant. As a first improved solution, the growing technology of RPAS (Remotely Piloted Aircraft Systems) is exploited to gather thermic images which are geo-referenced by GPS positioning and processed by computer vision algorithms. However this configuration is very respectful but still not enough in order to provide the required positioning accuracy for the automation and fast identification of the broken modules. Only the aid of accurate positioning allows a cost effective solution to reduce time, costs and risks for personnel involved: the added value provided by the employment of GNSS high accuracy solutions as novelty in the RPAS domain is the key driver for the EASY PV turnkey solution. Finally EASY PV solution is conceived to build up an automatic system for acquiring, georeferencing and processing both visible and thermal images captured by an RPAS equipped with a Galileo/EGNOS high accuracy receiver, flying over a photovoltaic field. In this way it is possible to easily detect the defective modules to be replaced.

Keywords: photovoltaic maintenance,rpas,egnss high accuracy,edas,computer vision
Deep uncertainties in bioethics: genetic research, preventive medicine, reproductive decisions (BIOUNCERTAINTY)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Cultures and cultural production
Panel description: Literary studies, cultural studies, study of the arts, philosophy
Countries involved: Poland
Call: ERC Starting Grant (ERC-2018-STG, 2018)
Start date: 2019-02-01
End date: 2024-01-31
Duration (months): 60.0
Total project cost (EUR): 1499625.0
EU funding (EUR): 1499625.0
Participants: 1
Project status: SIGNED

Uncertainty is everywhere, as the saying goes, but rarely considered in ethical reflections. This project aims to reinterpret ethical discussions on current advances in biomedicine: instead of understanding bioethical positions as extensions of classical normative views in ethics (consequentialism, deontologism, contractualism etc.), my project interprets them more accurately as involving various normative approaches to decision making under uncertainty. The following hard cases in bioethics provide the motivation for research: 1) Regulating scientific research under uncertainty about the ontological/moral status (e.g. parthenogenetic stem cells derived from human parthenotes) in the context of meta-reasoning under normative uncertainty. 2) The value of preventive medicine in healthcare (e.g. vaccinations) in the context of decision-making under metaphysical indeterminacy. 3) Population or reproductive decisions (e.g. preimplantation genetic diagnosis) in the context of valuing mere existence. The main drive behind this project is the rapid progress in biomedical research combined with new kinds of uncertainties. These new and “deep” uncertainties trigger specific forms of emotions and cognitions that influence normative judgments and decisions. The main research questions that will be addressed by conceptual analysis, new psychological experiments, and case studies are the following: how do the heuristics and biases (H&B) documented by behavioral scientists influence the formation of normative judgments in bioethical contexts; how to demarcate between distorted and undistorted value judgments; to what extent is it permissible for individuals or policy makers to yield to H&B. The hypothesis is that many existing bioethical rules, regulations, practices seem to have emerged from unreliable reactions, rather than by means of deliberation on the possible justifications for alternative ways to decide about them under several layers and types of uncertainty.

Keywords: philosophy,ethics,bioethics,uncertainty,risk,social psychology,decision making,research ethics,medical ethics,healthcare ethics,reproductive ethics
EXTREME EVENTS: ARTIFICIAL INTELLIGENCE FOR DETECTION AND ATTRIBUTION (XAIDA)

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: Germany,Spain,Germany,Germany,Switzerland,France,Netherlands,Netherlands,Netherlands,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: Advancing climate services (H2020-LC-CLA-2020-2, 2020)
Start date: 2021-09-01
End date: 2025-08-31
Duration (months): 48.0
Total project cost (EUR): 5999241.75
EU funding (EUR): 5999241.75
Participants: 17
Project status: SIGNED

Often, extreme events provide representations of the future climate, but not all extremes are harbingers of the future. Thus, in order to be useful for adaptation in support to future projections, a causal link between events and human influence on climate must be established or refuted. This is why the “Extreme event attribution” field has recently developed. However, extreme event detection, attribution and projections studies currently face major limitations. XAIDA will fill these gaps. Using new artificial intelligence techniques, and a strong two-way interaction with key stakeholders, it will (i) characterize, detect and attribute extreme events using a novel data-driven, impact-based approach, (ii) assess their underlying causal pathways and physical drivers using causal networks methods, and (iii) simulate high-intensity and as yet unseen events that are physically plausible in present and future climates. To achieve this, XAIDA brings together teams of specialists in extreme event attribution, atmospheric dynamics, climate modelling, machine learning and causal inference, to: ● Understand the effect of climate change on a variety of impacting atmospheric phenomena currently poorly understood or quantified (cyclones, convective storms, long-lived anomalies, or summer compound events), both for past and future evolutions; ● Develop, in co-design with a community of key stakeholders, a novel, broader and impacts-based attribution and projection framework which extracts causal pathways of extremes; ● Develop storylines of events of unseen intensity, based on machine learning methods; ● Provide new tools for model assessment of causal pathways leading to extreme events and investigate the causes of disagreements between models and observations; ● Develop an interaction and communication platform with stakeholders with the ambition to improve training and education on climate change and impacts and to bring these developments to future operational climate services

Keywords: future extreme event projections,causal networks,deep learning,climate change impacts
European Researchers' Night in Bosnia and Herzegovina 2014-2015 (RiNG-14-15)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: European researchers' Night
Action type: Marie Skłodowska-Curie actions
Countries involved: Italy,Bosnia and Herzegovina
Call: European Researchers' Night (NIGHT) (H2020-MSCA-NIGHT-2014, 2014)
Start date: 2014-06-01
End date: 2015-11-30
Duration (months): 18.0
Total project cost (EUR): 173000.0
EU funding (EUR): 150000.0
Participants: 3
Project status: CLOSED

The Researchers' Night 2014/2015 in Bosnia and Herzegovina – RiNG-14-15, will unite research communities from Republika Srpska and Federation of BiH, jointly promote scientific careers and enhance public recognition of researchers' work with the message "Researchers are amongst us" by engaging interactive communication with the public at large in whole BiH. RiNG 2014 will direct edutainment activities under slogan "Sign for Science", creating campaign with focus on "traffic signs" and developing real life roadmap on how to find science, how to investigate, and how to reach the innovations. The implementation of Night activities is based on idea to create sort of "science traffic school" in open area, creating traffic sign and traffic controllers that would direct participants to specific areas. RiNG 2015: "Chain Reaction" and celebration of 10th anniversary of EU Researchers' Nights. Promotion campaign will largely rely on European dimension and will be coordinated with other Researchers' Nights in EU and Western Balkan region. Specific activities will be organized in several cities in BiH, thus becoming "national" research promotion event in this country: - Edutainment parks with hands-on experiments, directly engaging general public into communication with researchers; - High school competitions for the best science projects; - Science coffee and talks to scientists, labelled as "RiNG ME"; - Various competitions, games and quizzes, especially directed to younger audience; - "Stand Up Science" lectures, presentations; - Large EU area: EU corners with policy and gender issues advisory, as well exhibition of EU-funded projects in BiH; - Thematic activities at supporting universities, research centres and museums; - Science Movie Night and Science Party. RiNG-14-15 quantitative targets per year are: - Number of people to be reached through awareness raising campaign in BiH: 300.000; - Expected number of direct attendees to organized events in whole BiH: 15.000.

Keywords: communication,science communication,public recognition of researchers,promotion of science careers,edutainment,researchers night
Synthetic biology for microbial lipids production from lignocellulosic biomass using multi-functional synthetic consortia (SynBioLipid)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Career Restart panel
Action type: Marie Skłodowska-Curie actions
Panel: Environment and Geosciences
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-03-01
End date: 2025-02-28
Duration (months): 36.0
Total project cost (EUR): 337400.64
EU funding (EUR): 337400.64
Participants: 1
Project status: SIGNED

Global transition towards a climate-neutral economy demands for the sustainable use of renewable biological resources. Microbial lipids are potential products of bio-based industries and sustainable alternatives to petroleum-derived fuels and chemicals. The commercial development of microbial lipids from inexpensive feedstocks such as lignocellulosic biomass is so far limited mainly due to the elevated production costs imposed by physicochemical pre-treatments and extraction of intracellular lipids. In addition, degradation of lignocellulose releases compounds which are toxic for most of the microorganisms. One solution is to construct engineered organisms with improved metabolic capabilities integrating pre-treatment, fermentation, detoxification and secretion of lipids. Hitherto, there is no successful research on an engineered organism which is able to do all these tasks. In fact, efficient transferring large heterologous pathways into one single microorganism is quite challenging and leads to high metabolic burden and less productivity. SynBioLipid will combine my expertise in metabolic modelling and fermentation using mixed microbial communities with the host experience in synthetic biology. It is aimed at using Yarrowia lipolytica, as a model microorganism for microbial lipids production from lignocellulosic biomass by presenting an innovative and original strategy to overcome the challenges associated with expression of large heterologous pathways. I first will generate synthetic microbial consortia comprised specialist strains, and second, will use these communities for the optimized production of microbial lipids. Each specialist strain is engineered to deliver an optimum output for one or more specific tasks. The metabolic network modelling will be integrated with synthetic biology and metabolic engineering to design and build multifunctional synthetic consortia, enabling efficient lipid production from lignocellulose.

Keywords: microbial lipids,microbial communities,synthetic consortia,yarrowia lipolytica,heterologous expression,metabolic engineering,metabolic model
Education Economics Network (EdEN)

Framework: Horizon 2020 — Spreading excellence and widening participation
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Action type: Coordination and support actions
Countries involved: Italy,Belgium,Hungary,Netherlands
Call: Twinning (H2020-TWINN-2015, 2015)
Start date: 2016-01-01
End date: 2018-12-31
Duration (months): 36.0
Total project cost (EUR): 681437.5
EU funding (EUR): 681437.5
Participants: 4
Project status: CLOSED

Education Economics Network – EdEN EdEN marks the start of an enhanced cooperation in the field of education economics between three top ranked economics of education research groups in EU-15 countries and a promising group in the Widening Countries. The deep cooperation will boost the publication and research capacities of the cooperating institutions in general, and the leading institution in particular. Education economics is one of the most important applied economics fields that provide direct evidence to policy makers on educational issues. The proposed project focuses on three clusters of methodologies – program evaluation, structural modeling and efficiency analysis – and fosters cooperation between the institutions along more specific research lines within these clusters. The project also increases the awareness of the education economics among Ph.D. students from the participating countries as well as at building a stronger network of already practicing education economists within the specific research lines.

Keywords: education economics,program evaluation,structural modeling,efficiency analysis