Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Papuans on the move. The linguistic prehistory of the West Papuan languages. (OUTOFPAPUA)

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: Netherlands
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-09-01
End date: 2025-08-31
Duration (months): 60.0
Total project cost (EUR): 1499684.0
EU funding (EUR): 1499684.0
Participants: 1
Project status: SIGNED

This project combines urgent documentation of endangered languages in Indonesia with rigorous investiga-tion of a linguistic puzzle that has important implications for our understanding of both Melanesian and Southeast Asian prehistory. Some two dozen Papuan languages, scattered over a 1000km on and around the Bird's Head of West Papua, show signs of sharing a common origin. The OUTOFPAPUA project uses cut-ting-edge methods in historical linguistics to test the hypothesis that these languages belong to a single West Papuan language family, and to investigate the possibility that their distribution reflects a migration of Papuan people, in relatively late prehistoric times, from the New Guinea mainland outward and westward into the Indonesian archipelago. The project will also address the question of what drove this putative expansion, in particular the possibility that it had to do with indigenous agricultural innovations. Thus, it contributes both to the difficult enterprise of uncovering genealogical relationships among the diverse languages of New Guinea, and to a growing body of research that questions the orthodox linguistic understanding of eastern Indonesia's prehistory in terms of an eastward expansion of Austronesian speakers at the expense of less dynamic Papuan populations. At a methodological level, the project furthers the development of techniques for establishing remote historical linguistic relationships in the absence of written records of relevant languages. The project will make innovative comparisons using a suite of techniques, including the application of new computational methods, the construction of a lexical database of unparalleled richness in Papuan linguistics, and by giving a prominent role to semantic shifts, paleolinguistics, and morphology and paradigms in the reconstructive project. This research aims at achieving a breakthrough in the study of human prehistory in one of world’s oldest areas of human settlement.

Keywords: papuan languages,linguistic prehistory,new guinea
Stretchable mesh-electrodes interfacing human iPSC brain organoids (STRELECOID)

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: Germany,Italy,United States
Call: Individual Fellowships (H2020-MSCA-IF-2018, 2018)
Start date: 2019-12-01
End date: 2023-07-19
Duration (months): 36.0
Total project cost (EUR): 246669.12
EU funding (EUR): 246669.12
Participants: 3
Project status: SIGNED

Recent advances in cellular engineering allow to recruit skin cells from donors and reprogram them into neural stem cells. These induced pluripotent stem cells (iPSC) bear the genetic code of the human patient. Efforts to culture these cells in-vitro have been successful in creating a wide variety of 3D arrangements called neurospheres. Because the human central nervous system is by and large inaccessible at all developmental stages, these functional tissue preparations are invaluable. Furthermore, clinical studies performed in animal models are known to translate poorly to humans and therefore these systems provide unprecedented advantages: human neurons in a controlled environment that have the genetic signature of psychiatric or mental disorders borne by the donor patient, such as Alzheimer’s or Parkinson’s disease. Finally, compared to animal studies where overwhelmingly only male animals are studied, stem cell research can operate on both sexes. The combination of new biomaterials, genome engineering and massively parallel single-cell transcriptomics opens opportunities to precisely study human brain disease A new exciting development is the possibility to form so-called assembloids, whereby organoids of different brain regions, as for example cortical and thalamic neural ensembles, are brought in proximity and self-assemble into anatomically correct brain regions. These approaches are necessary to study disorders like epilepsy. However these cultures lack physiological sensory input which are key in the development of mental plasticity. Here we plan to overcome this limitation by integrating new mesh-based electrodes that integrate seamlessly into brain tissue and expand symbiotically with the neurosphere as it grows, and thereby have a spatially refined mean to measure but also elicit neural activity. This will shed light on how electric maturation of these neurospheres comes about and help shape them to an anatomically more faithful brain model.

Keywords: multi electrode arrays
Neural & Computational Principles of Multisensory Integration during Active Sensing and Decision-Making (NeuCoDe)

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-2018, 2018)
Start date: 2019-04-01
End date: 2021-03-31
Duration (months): 24.0
Total project cost (EUR): 224933.76
EU funding (EUR): 224933.76
Participants: 1
Project status: CLOSED

Perceptual decisions rely on the integration of information from the environment, which typically involves the combination of stimuli from different senses. The quality of sensory evidence depends highly on our actions that affect how we acquire information from the external world. Importantly, the processing of this multisensory information requires the interaction of multiple neural processes over time. However, the neural mechanisms underlying this complex human behaviour remain elusive. In this project, I will employ a novel active sensing paradigm coupled with state-of-the-art neuroimaging and computational modelling to probe how the brain samples, processes and integrates multisensory information in order to make fast and accurate decisions. I will devise a reaction-time task where human subjects will actively sense and discriminate the amplitude of two texture stimuli a) using only visual information, b) using only haptic information and c) combining the two sensory cues, while electroencephalograms (EEG) will be recorded. To study this, I will develop a novel computational methodology for the joint analysis of brain activity (EEG), sensorimotor signals (movement kinematics) and behavioural measurements (choice and response time). First, behavioural modelling will provide a mechanistic account of the constituent processes underlying decision fomation. Then, model predictions will inform the joint analysis of neural and sensorimotor signals, to characterize the neural and behavioural basis of active multi-sensing and decision-making. To achieve this, I will devise an information-theoretic methodology that quantifies a) the contribution of each sensory modality to perception and b) the interaction of their neural representations to drive perceptual decisions. Ultimately, this project will elucidate the brain networks involved in active multisensory decision-making and characterize their respective functional roles in behavioural performance.

Keywords: perceptual decision making,active sensing,multisensory integration,information theory,drift diffusion model
Water Mist Fire Protection Systems for Engine Compartments in Buses and Coaches (SNIPER)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Italy
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-08-01
End date: 2019-11-30
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Transports’ fire protection systems have been undergoing significant changes in the last decade, in response to a number of fires, with devastating consequences, both in Europe and worldwide. This has led the European Union to review the Regulation nª 107, requiring that all new vehicles exceeding 22 passengers, should have an automatic fire detection and suppression system in the engine compartment. In this frame, Firing SRL, an Italian company well known in the fire industry, is developing SNIPER, an unrivalled water mist fire protection system, environmentally friendly and safe for human health, which has unique advantages. It secures (1) both cooling and extinguishing capabilities; (2) independence of the mounting position; (3) a total discharge of the extinguish agent 10-20 seconds; (4) the avoidance of false alarms; (5) an effective coating against reignition; (6) an extinguishing container depressurized; (7) antifreeze protection up to -50 °C and; (8) easy restoration after use. Thanks to its main innovative components: (1) a single multi-nozzle head which discharges water all over the engine compartment; (2) a unique valve to de-crease gas pressure and activate the system at the same time and (3) a water piston to re-lease the water, SNIPER is able to shorten the extinguish time by 40%, to reduce water consumption up to 90%, to decrease the gas and water pressure by 90% and 50% respectively and to avoid close to 400 kg CO2 emissions due to a bus burnout. SNIPER will be commercialized in Italy and Germany, in a first stage and gradually in all 28-EU countries, only for new buses. Then, SNIPER will be extended to buses retrofitting in other countries in and out of Europe and finally, it will be opened to new market niches (i.e., trucks and heavy machinery). This strategy will create 18 new positions in Firing, both internal and freelance. In three years, SNIPER will generate a cumulative profit of €7,72M translated into a IRR of 87% and NPV of €3,57M.

Keywords: fire detection,prevention,transport safety,vehicle engine,truck,heavy machinery,extinguish agent,multi head nozzle,valve,automation,vehicles registration,retrofitting
Spatiotemporal control of neuroinfection by meningeal macrophages (CNSentinels)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Immunity, Infection and Immunotherapy
Panel description: The immune system, related disorders and their mechanisms, biology of infectious agents and infection, biological basis of prevention and treatment of infectious diseases, innovative immunological tools and approaches, including therapies
Countries involved: France
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2021-05-01
End date: 2026-04-30
Duration (months): 60.0
Total project cost (EUR): 1912500.0
EU funding (EUR): 1912500.0
Participants: 1
Project status: SIGNED

Due to the vital importance of the Central Nervous System (CNS), its infection and inflammation have to be tightly controlled. The surface of the CNS is connected to the periphery by a rich and complex tissue, the meninges. They contain a vast network of macrophages subdivided in two populations endowed with elusive functions. Using innovative depletion strategies in experimental mouse models, I discovered that meningeal macrophage populations represent the first line of protection against neuroinvasive pathogens. In their absence, specific areas in the meninges become highly infected, leading to fatal brain disease. The goal of ‘CNSentinels’ is to understand 1/the mechanisms controlling the spatiotemporal distribution of macrophage populations at the brain surface and 2/the relative contribution of the two macrophage populations in protecting the CNS against neuroinvasive pathogens. To this aim, I developed innovative strategies to visualize and manipulate meningeal macrophages in vivo that I will combine with cutting-edge gene editing techniques, in mice infected with lymphocytic choriomeningitis virus (LCMV). This pioneer work will help understand the spatial organization of the brain defence system and the molecular mechanisms involved in CNS protection, and will provide new avenues to design therapeutic strategies.

Keywords: macrophages,meninges,neuroinvasion,meningitis
A diagnostic test to improve surveillance and care of COVID-19 patients (COVIRNA)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Action type: Innovation actions
Countries involved: Germany,Germany,Italy,Spain,Belgium,Bosnia and Herzegovina,Slovenia,Hungary,France,Netherlands,United Kingdom,United Kingdom,Luxembourg,Portugal
Call: Medical technologies, Digital tools and Artificial Intelligence (AI) analytics to improve surveillance and care at high Technology Readiness Levels (TRL) (H2020-SC1-PHE-CORONAVIRUS-2020-2-CNECT, 2020)
Start date: 2020-11-01
End date: 2023-04-30
Duration (months): 30.0
Total project cost (EUR): 4439772.25
EU funding (EUR): 3874497.25
Participants: 16
Project status: SIGNED

Coronavirus disease 2019 (COVID-19) caused by infection with SARS coronavirus 2 (SARS-CoV-2) has reached pandemic proportions with more than 7 million people infected and 0.4 million people killed worldwide. Death rates are accentuated by cardiovascular comorbidities and arrhythmias leading to unexpected major cardiovascular events. Being able to identify COVID-19 patients at risk of developing cardiovascular events leading to death would allow improving surveillance and care. Currently, there is no accurate method to predict outcome of COVID-19 patients. COVIRNA is a patient-centered Innovation Action aiming to satisfy this urgent and unmet need. COVIRNA will complete and deploy a prognostic system based on cardiovascular biomarkers of COVID-19 clinical outcomes combined with digital tools and artificial intelligence analytics (i.e. prediction model). Complementary expertise of 15 EU partners from the healthcare sector, academia, association and industry will allow conducting a large retrospective study on existing cohorts of COVID-19 patients. By upscaling the already validated and patented research use only FIMICS panel of cardiac-enriched long noncoding RNA biomarkers into an in-vitro diagnostic test (COVIRNA) adapted to COVID-19 patients, the project will quickly deliver a minimally-invasive, simple yet robust and affordable prognosis tool that can be used in the context of the current COVID-19 crisis as well as in further major health issues. By tackling the cardiovascular complications in COVID-19, known to contribute significantly to mortality, the project outputs are expected to have a major impact on the pandemic outcomes. The COVIRNA test will be CE-marked and prepared for commercialization, allowing to risk stratify patients, adapt therapies and to inform drug design.

Keywords: biomarkers,cardiovascular,long non coding rna,covid 19 prognosis,prediction model,patient stratification
Nano-physiology of small glutamatergic axon terminals (nanoAXON)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Neuroscience and Disorders of the Nervous System
Panel description: Nervous system development, homeostasis and ageing, nervous system function and dysfunction, systems neuroscience and modelling, biological basis of cognitive processes and of behaviour, neurological and mental disorders
Countries involved: Hungary
Call: ERC Consolidator Grant (ERC-2017-COG, 2017)
Start date: 2018-04-01
End date: 2024-03-31
Duration (months): 72.0
Total project cost (EUR): 1994025.0
EU funding (EUR): 1994025.0
Participants: 1
Project status: SIGNED

We will reveal the neuronal mechanisms of fundamental hippocampal and axonal functions using direct patch clamp recordings from the small axon terminals of the major glutamatergic afferent and efferent pathways of the dentate gyrus region. Specifically, we will investigate the intrinsic axonal properties and unitary synaptic functions of the axons in the dentate gyrus that originate from the entorhinal cortex, the hilar mossy cells and the hypothalamic supramammillary nucleus. The fully controlled access to the activity of individual neuronal projections allows us to address the crucial questions how upstream regions of the dentate gyrus convey physiologically relevant spike activities and how these activities are translated to unitary synaptic responses in individual dentate gyrus neurons. The successful information transfers by these mechanisms ultimately generate specific dentate gyrus cell activity that contributes to hippocampal memory functions. Comprehensive mechanistic insights are essential to understand the impacts of the activity patterns associated with fundamental physiological functions and attainable with the necessary details only with direct recordings from individual axons. For example, these knowledge are necessary to understand how single cell activities in the entorhinal cortex (carrying primary spatial information) contribute to spatial representation in the dentate (i.e. place fields). Furthermore, because the size of these recorded axon terminals matches that of the majority of cortical synapses, our discoveries will demonstrate basic biophysical and neuronal principles of axonal signaling that are relevant for universal neuronal functions throughout the CNS. Thus, an exceptional repertoire of methods, including recording from anatomically identified individual small axon terminals, voltage- and calcium imaging and computational simulations, places us in an advantaged position for revealing unprecedented information about neuronal circuits.

Keywords: electrophysiology,synaptic release,voltage sensitive sensors
Improved Nuclear SIte characterization for waste minimization in DD operations under constrained EnviRonment (INSIDER)

Framework: Horizon 2020 — Euratom
Programme: Nuclear fission and radiation protection
Theme: Radioactive waste management
Action type: Research and Innovation actions
Countries involved: Germany,Spain,Germany,Germany,Ukraine,Germany,Switzerland,Belgium,Hungary,France,France,France,Czechia,United Kingdom
Call: Research and innovation on the overall management of radioactive waste other than geological disposal. (NFRP-2016-2017-1, 2016)
Start date: 2017-06-01
End date: 2021-11-30
Duration (months): 54.0
Total project cost (EUR): 4173870.0
EU funding (EUR): 3781064.64
Participants: 18
Project status: CLOSED

Decommissioning and dismantling (D&D) operations are strongly dependent on the facilities history and the inventory of present radionuclides. The D&D processes are significant source of radioactive waste and their management is a major challenge from technical, economical, financial and societal point of view. This is recognized in a number of reference documents and studies on EU and international level. These challenges are naturally subject for further optimisation and the ambition of INSIDER project is to contribute to it as follows. For constrained environments new methodologies are necessary for more accurate initial estimation of contaminated materials, resulting waste volumes and timely planning. This will be based on advanced statistical processing and modelling, coupled with adapted and innovative analytical and measurement methods, with respect to sustainability and economic objectives. The envisaged project outcomes will enable building of a fit-for-purpose representation of the radiological status of facilities (or components), at a relevant precision level allowing making decisions concerning different D&D scenario options. The overall project methodology is based on common case studies in the form of interlaboratory comparisons on matrix representative reference samples and benchmarking. Industrial partners (selected D&D actors) in close cooperation with major EU R&D organisations will drive comprehensive and realistic conclusions formalised in guidelines, recommendations and elements for pre-standardisation initiatives. These will be validated at different scientific and industrial levels and widely disseminated to the broad D&D community and beyond.

Keywords: decommissioning,statistical modelling,standard,analytical chemistry,on site measurement
Next Generation Machine Intelligence for Medical Image Representation and Analysis (MIRA)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2017-STG, 2017)
Start date: 2018-02-01
End date: 2024-01-31
Duration (months): 72.0
Total project cost (EUR): 1499292.0
EU funding (EUR): 1499292.0
Participants: 1
Project status: SIGNED

Machines capable of analysing and interpreting medical scans with super-human performance would transform healthcare as much as medical imaging itself did over the last century. With an increasing complexity and volume of data the interpretation of images and extraction of clinically useful information push human abilities to the limit. There is high risk that critical patterns of disease go undetected. We require powerful and trustworthy computational tools based on machine intelligence to support experts and go beyond human performance to tackle the major challenges in clinical practice. Two key ingredients are currently missing: 1) interpretable statistical representations that capture important information while reducing complexity; 2) intelligent algorithms that leverage knowledge across multiple tasks to solve the most challenging problems such as early detection of pathology. This project is devoted to redefine the state-of-the-art in medical image analysis by developing a new generation of machine intelligence using powerful techniques of representation learning. Key to the project is its unique access to some of the largest and most comprehensive imaging databases combined with world-leading expertise in machine learning and medical imaging. An overarching objective is to harvest information from population data to construct what will be the most advanced statistical models of anatomy. In contrast to previous attempts that focus primarily on specific organs or pathology, here shared representations are learned from highly complex data by jointly solving multiple tasks. Linking the representations with demographics, lifestyle, genetics and disease allows probing of genetic and environmental determinants related to specific anatomical and pathological phenotypes across organs. This will provide insights into complex diseases, and enables a novel approach to abnormality detection that aims to automatically find subtle signs of pathology in new medical scans.

Keywords: medical image analysis