Data-Gouv-ML/pcri-actions-marie-curie-participations-et-projets-laureats huggingface dataset:
Projet 3DInAction (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - Global Fellowships
Panel : Information Science and Engineering
Statut du projet : SIGNED

Human action recognition and forecasting is an integral part of autonomous robotic systems that require human-robot interaction as well as other engineering problems. Action recognition is typically achieved using video data and deep learning methods. However, other tasks, e.g. classification, showed that it is often beneficial to additionally use 3D data. Namely, 3D point clouds that are sampled on the surfaces of objects and agents in the scene. Unfortunately, existing human action recognition methods are somewhat limited, motivating the following research. In this action, we describe a new class of algorithms for 3D human action recognition and forecasting using a deep learning-based approach. Our approach is novel in that it extends a recent body of work on action recognition from 2D to the 3D domain which is particularly challenging due to the unstructured, unordered and permutation invariant nature of 3D point clouds. Our algorithms use the global and local statistical properties of 3D point clouds along with a 3D convolutional neural network to devise novel multi-modal representation of human action. It is inherently robust to spatial changes in the 3D domain, unlike previous works which rely on the 2D projections. In practice, deep learning methods allow us to learn an inference model from real-world examples. A common methodology for action recognition includes creating an annotated dataset, training an inference model and testing its generalization. Our research objectives cover all of these tasks and suggest novel methods to tackle them. Overall, the proposed research offers a new point of view for these long-standing problems, and with the vast related work in other domains, it may bridge the gap to arrive at a generalizable, effective and efficient 3D human action recognition and forecasting machinery. The resulting algorithms may be used in several scientific and engineering domains such as human-robot interaction among other applications.

Mots clés : 3d point clouds, action recognition

Participants :
- Australian National University (Australie) — Partner, organization partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Technion – Israel Institute of Technology (Israël) — Coordinator, beneficiary, Organismes privés (hors enseignement), subvention : 276205.44 €
Projet W2W (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : CLOSED

Human activities and urban lifestyle creates municipal solid waste (MSW) all over the world in huge volume. Proper management of MSW is one of the important requirements/ responsibilities for a healthy environment of future generation. The proposed project aims at utilizing the MSW Incinerated (MSWI) products as secondary raw materials in geopolymer concrete, thereby converting these wastes in to wealth (W2W). This also helps in satisfying the demand for raw materials in infrastructure industries. The main objectives of this project are, to optimize the treatment method for MSWI bottom ash and to understand the enhancement in the properties of treated MSWI bottom ash with advanced treatment technology, to manufacture the artificial aggregate from the treated MSWI bottom ash and to study the performance of the MSWI bottom ash aggregate as a secondary raw material in the geopolymer concrete application. This proposal involves extensive training of the candidate on treatment techniques of bottom ash in the premises of industrial secondment and advanced characterization of the treated materials in the academic secondment. The host institute helps in geopolymeric technology on pelletization of the treated bottom ash. With inter-sectoral collaboration, life cycle assessment of the products will be studied to highlight the environmental impact of the material processing. The research activities and the training of the present project will firstly provide the applicant a high scientific profile. The candidate will handle the entire project management with the support from the host. In addition to the new analytical skills, the candidate learns teaching and supervision by handling two masters thesis under this project. The obtained results will be communicated to high-impact journal which improves the profile of the candidate and makes her a competitive person in the field of 'waste utilization in civil engineering applications'.

Mots clés : municipal solid waste, bottom ash, artificial aggregate, pelletization, geopolymer, waste treatment, construction material, concrete

Participants :
- University of Oulu (Finlande) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 202680.96 €
Projet AutoMIND (Horizon 2020, appel à projets 2020)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : SIGNED

Human cognition depends on complex coordinated dynamics of neural populations, which is shaped by a rich heterogeneity in cellular properties and network connectivity patterns of neural circuits. While cognitive neuroscience leverages macroscopic brain signals to relate neural activity to behavioral states, we currently cannot dissect them for their physiological contributions, hindering mechanistic interpretations of experimental data. One way to systematically study how physiological parameters shape neural dynamics is through mechanistic modeling of spiking neural networks. However, current modeling approaches are not quantitatively constrained by observed electrophysiological data, and often require painstaking and ad-hoc parameter-tuning by hand. Efficient discovery of mechanistic models that are consistent with experimental data would dramatically accelerate our understanding of how cellular and network properties impact cognition, and why it breaks down in pathological states, representing a radical departure from how neural data is analyzed in cognitive neuroscience. To this end, I propose to develop a machine learning-assisted model inference tool—Automated Model Inference from Neural Dynamics (AutoMIND)—that can identify parameters of candidate spiking neural network models that could capture arbitrary target neural dynamics from human brain recordings. AutoMIND extends on recent advances in simulation-based inference techniques, incorporating simultaneous parameter manifold-learning and gradient-based simulations. AutoMIND has broad utility for tackling neuroscientific questions by enabling expedited in-silico experiments. Here, I apply it to multiscale neural data to study how cellular and network properties shape: 1) the emergence of synchronous network oscillations during early neurodevelopment, and 2) the difference in neural dynamics and computation between sensory and association cortices—two questions of fundamental importance to neuroscience.

Mots clés : simulation based inference, likelihood free inference, mechanistic modeling, spiking neural networks

Participants :
- University of Tübingen (Allemagne) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 162806.4 €
Projet BioMASCE (Horizon 2020, appel à projets 2014)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Human mesenchymal stem cells (hMSCs) are a promising cell source for regenerative therapies. In part, their capacity for multi-lineage differentiation and subsequent therapeutic efficacy is controlled by the epigenetic status of the DNA. The Stevens Group at Imperial College London (ICL) has recently developed a novel material platform of porous silicon (pSi) nanoneedles (nNs) that penetrate the cell membrane, stimulating physical changes in the nucleus. Interestingly, nuclear mechanics and shape parameters have been shown to control epigenetic status in various cell types, but this remains under-investigated in hMSC. Therefore, in the present study, pSi nNs will be used to manipulate hMSC nuclear size and shape, as well as the resulting epigenetic status, as a means to identify novel mechanisms for enhancing differentiation capacity. The inherent porosity of the nNs, coupled with their ability for cell penetration, will be exploited as a delivery tool for a cutting-edge class of non-coding RNAs into hMSCs to interfere with, and further regulate, epigenetic status and resulting therapeutic potential. This discovery-driven project leverages a one-of-a-kind engineering tool for investigating and manipulating hMSC behaviour. In parallel, the applicant has proposed to undergo a secondment to a UK-based, non-academic partner organisation to enhance his knowledge of intellectual property protection, technology development, and product commercialisation in order to translate his research findings for clinical benefit. The applicant will increase his knowledge base during the project, creating new contacts in his personal network, as well as for the Stevens Group and ICL. This project represents a multidisciplinary, cutting-edge approach to stem cell biology and biomedical engineering, utilising cross-sectoral collaboration for enhanced training and potential for industrial translation of basic research findings.

Mots clés : human mesenchymal stem cells, cell biomaterial interactions, nuclear mechanotransduction, intracellular rna delivery, tissue engineering, clinical translation, cross sectoral collaboration

Participants :
- Imperial College London (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 183454.8 €
Projet LACONIA (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : SIGNED

Human population has wide ranging and often negative consequences for the natural environment. Population stability and decreasing fertility have thus been heralded as promising for sustainability. However, household size has been decreasing steadily in both developed and developing countries, at an accelerating pace, since the 1980s. The European Union (EU) leads this trend, with nearly a third of total households consisting of single residents. As a result of more people living alone with associated higher consumption, slowing population growth has resulted in neither fewer residences nor decelerating human impact on the environment. This MC-IF aims to investigate the trend toward living alone and create new knowledge about environmental impacts of different household configurations, drivers for different occupancy trends and alternative sustainable housing configurations. The research will be carried out in three phases, firstly by using existing population, housing and consumption databases; secondly be interviewing both high and low impact single resident households and finally by studying low impact household configurations in-depth. This will provide new knowledge on: how different household configurations impact sustainability; why people choose to live in different various configurations; and drivers and barriers for emerging sustainable alternatives. This knowledge will be valuable for policy makers planning sustainable urban environments. During period of training the ER will: Acquire specialised knowledge on sociology of consumption; deepen her mixed methods analysis; improve her multicultural and team communications skills; have policy impact; and publish scientific articles in international journals. Thus the MSCA-IF will allow her to consolidate her academic profile in order to enter the EU academic job market in a tenure-track position.

Mots clés : sociology of consumption, social practices, sustainability, housing, water, energy, transitions

Participants :
- Aalborg University (Danemark) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 219312.0 €
Projet SCHEME (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : CLOSED

Human populations worldwide are exposed to a large number of chemical pollutants from contaminated food, personal care products and the surrounding environment. Exposure to these compounds is generally assessed by human biomonitoring - the analysis of biomarkers (excreted parent compounds or metabolic products) in biological matrices from individuals, mostly urine. Due to the several limitations of this approach, a novel concept - sewage chemical information mining (SCIM), has been proposed. This approach is based on the analysis of specific human biomarkers in urban wastewater, but its potential in studying human exposure to pollutants has been scarcely investigated. The SCHEME project aims to contribute to the practical development and broadening of the SCIM field by developing a comprehensive analytical methodology for the determination of biomarkers of exposure to a wide range of organic pollutants, including different classes of personal care products and industrial chemicals. The biomarkers will be selected using the pharmacokinetics data and Human Metabolome Database and analysed by ultrahigh performance liquid chromatography - tandem mass spectrometry. The developed methodology will be applied in four European cities as case studies. However, the results of this exploratory study could lead to implementation of this novel, relatively inexpensive and near real-time approach for the assessment of human exposure to pollutants. By monitoring temporal and spatial trends, communities with the highest exposure could be promptly identified. Therefore, the results of the SCHEME project will be highly valuable for obtaining relevant epidemiological information and will contribute to preventing human health problems related to pollutants exposure. The fellow’s expertise, gathered in top international research institutions, and the outstanding infrastructure and capabilities available at ICRA, makes an ideal conjunction for the successful completion of the project.

Mots clés : organic pollutants, wastewater analysis, wastewater based epidemiology

Participants :
- CERCA Institution (Espagne) — Coordinator, beneficiary, Recherche, subvention : 160932.48 €
Projet GERMINOID (Horizon 2020, appel à projets 2018)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Human primordial germ cells (hPGCs), the precursors of sperm and eggs, originate in early pre-gastrulation post-implantation embryos (~wk2). Thereafter, hPGCs undergo wide epigenetic reprogramming during their migration to the primitive gonads (~wk3–7). While technical and ethical constraints preclude direct studies on early human embryos, recent development of 2D models using human pluripotent stem cells (hPSC), which simulate early post-implantation development, have been used to investigate the specification of hPGC-like cells (PGCLCs) equivalent to wk2 hPGCs. These models however cannot support extended maturation of hPGCLCs beyond this early stage. Here, we propose a novel 3D in vitro system to advance development of hPGCLCs up to the onset of gametogenesis, extending our knowledge of the key events of early human germline development. This project will benefit from the cell culture capabilities of the three-layer gradient system (3-LGS), a 3D cell culture method that I invented during my PhD, combined with the expertise of Prof. Surani’s lab in generating hPGCLCs from hPSCs. The 3-LGS will be used to create gonadal organoids from human fetal primary cells, which we call “germinoids”, in order to support further development of hPGCLCs beyond the in vivo equivalent 2-wk stage. During this innovative project, we intend to achieve our objectives to create firstly, the novel co-culture germinoid conditions, and secondly to use the model to advance hPGCLCs differentiation. The generation and characterization of germinoids will be conducted in a collaborative team of experienced scientists and students, under renowned supervision and within a supportive and available work environment and infrastructure. This project will extend my expertise and contribute to the host’s work on early human germ cell development. The outcome will be a breakthrough in the field of human germ cell biology, which will contribute to my ambition to progress my independent research career.

Mots clés : primordial germ cells, germ line, organoids

Participants :
- University of Cambridge (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 212933.76 €
Projet ToMSelfLink (Horizon 2020, appel à projets 2017)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Social Sciences and Humanities
Statut du projet : TERMINATED

Human social interaction crucially depends on our ability to understand what others think or believe, an ability referred to as Theory of Mind (ToM). While decades of research assumed that this milestone is reached around the age of 4 years, recently, novel infant ToM tasks have shown that already infants younger than 2 years expect people to act according to their beliefs - even if these differ from the infant’s own beliefs. This has created one of the biggest puzzles of developmental psychology: Why do children consistently fail traditional ToM tasks until the age of 4 years, if already infants understand others' beliefs? The supervisor has recently suggested how the emergence of a self-concept (SELF) and ability to distinguish between self and other might build a link between early- and later-developing ToM abilities. Here, we want to address these questions with cognitive neuroscience, by combining behavioral and infant functional neuroimaging (fNIRS) tasks of ToM and SELF with brain-structural magnetic resonance imaging (MRI). This combination of methods will allow us to compare the brain regions involved in the novel infant and later-developing traditional ToM tasks, and to study their link to the brain regions involved in SELF. I have a strong background in combining brain-structural MRI with behavioral ToM tasks in preschool-aged children. My supervisor is a world-leading expert in early ToM and developing cutting-edge neurocognitive tasks for preverbal infants. She was recently awarded an ERC grant to test her theory on the role of SELF for ToM. The current action importantly complements that project by an innovative neuroimaging approach, which uniquely becomes possible through our combined expertise. I will strongly benefit from the infrastructure and expertise in that project, and will be able to learn cutting-edge infant neurocognitive testing methods, crucial for my future career goal of becoming a leading researcher in early-childhood development.

Mots clés : theory of mind, mentalizing, self awareness, neurocognitive development, infant cognition, developmental psychology, social cognition

Participants :
- University of Copenhagen (Danemark) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 200194.8 €
Projet MATESI (Horizon 2020, appel à projets 2016)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Life Sciences
Statut du projet : CLOSED

Human survival is dependent on swallowing because it underpins oral nutrition (eating/drinking) and protection of the respiratory tract. Swallowing difficulties (dysphagia) are a common consequence of a wide range of disorders (eg. stroke, head & neck cancers, ageing) with the results (dehydration/malnutrition/weight loss/increased susceptibility to pneumonia) linked to significant decline in quality of life. There is significant need to improve diagnosis, monitoring and rehabilitation (eg. by developing novel stimulation devices). However, existing gaps in understanding of the co-ordination of muscle activity significantly limit current advances. The proposed research is structured to exploit a novel combination of imaging and neurophysiology methods to develop a new framework for non-invasive study of swallowing muscle function, which will support development and application of new tools for diagnosing, monitoring and treating swallowing disorders. Ultrasound/elastography/MR/videofluoroscopy imaging and myoelectric data will be combined with finite element modelling to provide state-of-the-art methods for analysis of the integration between muscle anatomical and mechanical properties and neural input. This will provide a paradigm shift in understanding the translation of neural commands to co-ordinated movement. It will underpin development of next generation computer simulations which are required for technology/diagnosis/treatment advances; improvements in patient care; reduced clinical/economic burden and sustainable healthcare systems. The multi-disciplinary skills the Fellowship is designed to develop are fundamental to the growth of the most promising researchers. They are also essential for advances in better disease diagnosis/more effective therapies/interventions and underpin the European Commission’s quest to keep older people independent for longer and promote personal health; a healthy workforce/economy and lower public health bill.

Mots clés : dysphagia, finite element modelling, medical imaging

Participants :
- Manchester Metropolitan University (Royaume-Uni) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 195454.8 €
Projet WildFishGenes (Horizon 2020, appel à projets 2019)
Action : Postdoctoral Fellowships - European Fellowships
Panel : Environment and Geosciences
Statut du projet : SIGNED

Humans depend on great measure on the welfare of marine ecosystems, not only from the retribution obtained directly from resource harvesting but also from the benefits derived from healthy ecosystems (i.e. quality of natural resources, biodiversity maintenance, and ecosystem resilience to anthropogenic challenges). Traditionally, management efforts to preserve marine resources only contemplated morphological traits of the individuals (e.g. body size). However, more evidence is piling up on the importance of behaviour on biodiversity conservation. Traits such as exploration, boldness, and activity have a strong impact on the individual`s reproductive success, thus determining species survival. As other phenotypical traits, fish behaviour is determined in great measure by its genetic basis. In this project, we propose studying the genetic mechanisms underlying fish behavioural types. We will use a unique dataset based on state-of-the-art fish-tracking data that provides long-term behavioural data in situ for hundreds of free-living fish at unprecedented spatio-temporal resolution. We will complement the behavioural data set with advanced genetic and genomic techniques to find phenotype-genotype associations by: i) studying the sequence variants of candidate genes, ii) studying the location and abundance of target proteins in fish brain structures, iii) obtaining multiple brain transcriptomes from individuals showing distinct behavioural types. The multidisciplinary nature of the project, combining novel behavioural data collection with next generation genomic techniques, will provide a broad overview of the molecular basis of behavioural characterization. The proposed activities will open a new line of research in behavioural molecular ecology unprecedented in marine ecosystems. Our results will provide insight into the molecular basis of behaviour in marine fish, thus leading to a qualitative jump forward in fisheries management and behavioural biology.

Mots clés : acoustic tracking, fish genetics, fish movement, fisheries induced evolution, fisheries management, marine protected areas, transcriptomics

Participants :
- Spanish National Research Council (Espagne) — Coordinator, beneficiary, Recherche, subvention : 160932.48 €