Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Nonlinear Approaches for the Design of Active Piezoelectric Metamaterials (METACTIVE)

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: Information Science and Engineering
Countries involved: United Kingdom
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-01-03
End date: 2021-01-02
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

Mechanical metamaterials have surged to the forefront over the past five years against the backdrop of the unprecedented developments in optical, electromagnetic and acoustic metamaterials. Metamaterials are designer media with periodic units comprised of tailor-made geometry and pattern aimed at accomplishing exceptional bulk properties which are unprecedented in conventional materials. This proposal aims at taking the functionality of metamaterials to the next level by combining mechanical metamaterials with piezoelectrics. This, in turn, will give rise to active metamaterials which can be used for vibration energy harvesting and control. Radically new analytical and computational frameworks will be developed for dynamic homogenization and wave propagation in piezoelectric metamaterials with sub wave-length scale resonators. Linear and nonlinear resonators combined with a multiphysics approach will be adopted. Theoretical models will involve one and two-dimensional metamaterials. Experimental analysis of these models will be carried out at the host institution. This will validate the theoretical results and will also generate new insights. The proposed research inherently depended on ideas from fundamentally different expertise and will be achieved through supervision of three complimentary experts in different institutions and in two EU member of states. The pathway originating from this work will instill the essential confidence to take the leap from scientific curiosity to engineered active mechanical metamaterials. The combination of an outstanding multi-skilled scientific methodology and corresponding bespoke knowledge transfer approach will result in an unprecedented training framework which will result in a transformative impact on the applicant's scientific career.

Keywords: metamaterials,energy harvesters,nonlinear dynamics,piezoelectricity
Personalised Body Sensor Networks with Built-In Intelligence for Real-Time Risk Assessment and Coaching of Ageing workers, in all types of working and living environments (BIONIC)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Active ageing and self-management of health
Action type: Research and Innovation actions
Countries involved: Spain,Germany,Germany,Germany,Germany,Spain,Greece,Greece,Netherlands
Call: Adaptive smart working and living environments supporting active and healthy ageing (H2020-SC1-DTH-2018-1, 2018)
Start date: 2019-01-01
End date: 2022-03-31
Duration (months): 39.0
Total project cost (EUR): 3995195.0
EU funding (EUR): 3995195.0
Participants: 12
Project status: CLOSED

Our overall objective is to develop a holistic, unobtrusive, autonomous and privacy preserving platform for real-time risk alerting and continuous coaching, enabling the design of workplace interventions adapted to the needs and fitness levels of specific ageing workforce. Gamification strategies adapted to the needs and wishes of the elderly workers will ensure optimal engagement for prevention and self-management of musculoskeletal health in any working/living environment. The BIONIC concept will be a game changer in medical wearable technology integrating sensor modules in multi-purpose, configurable Body Sensor Networks (BSNs) introducing key enablers of user acceptance based on value, comfort, confidence and trust. BIONIC consists of a multidisciplinary team of researchers in the field of Wearable Electronics (IAW), Artificial Intelligence, Wearables for Health applications, and experts in Ergonomics and Anthropometry, Occupational Safety and Health, Data Analytics and System Security and Personal Data Protection. Results will be validated n real workplace environments by two prominent European Enterprises from the Construction and the Manufacturing sectors.

Keywords: persuasive gamified coaching,nfmi,personal data protection,gdpr,age adapted biomechanical models
Enhanced URBAN planning for AGE-friendly cities through disruptive technologies (URBANAGE)

Framework: Horizon 2020 — Societal Challenges
Programme: Europe in a changing world - inclusive, innovative and reflective societies
Theme: Innovative societies
Action type: Research and Innovation actions
Countries involved: Spain,Spain,Italy,Belgium,Finland,Belgium,Greece,United Kingdom
Call: Transformative impact of disruptive technologies in public services (H2020-SC6-TRANSFORMATIONS-2020, 2020)
Start date: 2021-02-01
End date: 2024-01-31
Duration (months): 36.0
Total project cost (EUR): 3711653.75
EU funding (EUR): 3711653.75
Participants: 12
Project status: SIGNED

Adapting urban environments to current challenges requires a multidisciplinary understanding of interrelated and complex phenomena. In the context of digital-era massive data production and enhanced analytical capacities, there is still enormous untapped potential in the use of disruptive technologies to support evidence-based decision-making processes in the field of urban planning. Moreover, the impact that such technologies may have in the current urban planning practice is yet to be assessed. Urban planning decision-making involves multiple stakeholders in complex governance settings. Such decisions should be evidence-based, and their results continuously evaluated to correct unwanted impacts, but this is not yet the prevalent paradigm. Using disruptive technologies in the urban planning decision-making process bears the risk of excluding some parts of the population; in particular, older adults, who are less digitally literate and might show distrust of decisions and engagement based on technology. At the same time, European cities are facing the challenge of adapting to an increasing aging population, so it is crucial to engage this part of the population in decision making processes. In this context, URBANAGE aims at assessing the potential benefits, risks and impact of implementing a long-term sustainable framework for data-driven decision-making in the field of urban planning for aging well in cities. This model will be developed through an inclusive co-creation strategy with relevant stakeholders (public servants) and users (older adults) and based on a decision-support Ecosystem that integrates multidimensional Big Data analysis; modelling and simulation with Artificial Intelligence algorithms, visualization through Urban Digital twins and gamification for enhanced engagement purposes. Based on a thorough understanding of users’ needs, it will be validated by piloting use-cases in three local planning systems in Europe (Helsinki, Santander and Flander).

Keywords: urban planning,ageing,digital twin,big bata,artificial intelligence
Programmable Readers, Writers, and Erasers of the Epigenetic Cytosine Code (EPICODE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Physical and analytical chemical sciences
Panel description: Analytical chemistry, chemical theory, physical chemistry/chemical physics
Countries involved: Germany
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-11-01
End date: 2023-04-30
Duration (months): 66.0
Total project cost (EUR): 1979679.0
EU funding (EUR): 1979679.0
Participants: 1
Project status: SIGNED

Human DNA contains two types of biologically instructive information: the canonical nucleobases A, G, T, C, and the epigenetic nucleobases mC, hmC, fC, and caC. Canonical nucleobases encode the identity of all RNAs and proteins that are synthesized by a cell, whereas epigenetic nucleobases regulate this synthesis. This regulation shapes the phenotype of cells, and its perturbation is a key trigger of cancer. Canonical nucleobases can be decoded in a programmable manner by nucleic acids and their analogs via Watson-Crick-base pairing, and the simplicity of this recognition has enabled revolutionary developments in the biological sciences. In contrast, comparable developments in epigenetics have not yet been possible, since a molecular scaffold with programmable recognition of epigenetic nucleobases does not exist. We will establish the first class of molecules capable of the expanded programmable recognition of both canonical and epigenetic DNA nucleobases in vitro and in vivo. This is based on transcription-activator-like effectors (TALEs) that consist of four types of concatenated modules, each of which recognizes a canonical nucleobase. We have recently reported the detection of single epigenetic nucleobases by TALEs. In this project, we will 1. engineer a toolbox of TALE modules with selectivity for C, mC, hmC, fC, and caC, 2. employ them for TALE-based in vitro typing and profiling (reading) of cancer biomarker mC/hmC, and 3. design photoactivatable TALE-fusions that enable the writing and erasing of mC at user-defined genomic loci in vivo with spatiotemporal resolution. This will provide the first insights into the dynamic effects of de novo editing on chromatin regulation, and enables the imprinting of regulatory states. Given the central role of epigenetic nucleobases in cancer and the universality of our approach, this project will provide enabling and broadly applicable methodology for cancer epigenetics research, diagnosis and therapy.

Keywords: nucleic acid chemistry,dna recognition,chemical biology,directed evolution,optogenetics
Systems Biology of Alcohol Addiction: Modeling and validating disease state networks in human and animal brains for understanding pathophysiolgy, predicting outcomes and improving therapy (SyBil-AA)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Understanding health, wellbeing and disease
Action type: Research and Innovation actions
Countries involved: Germany,Israel,Germany,Germany,Spain,Italy,Germany,Finland,Sweden,Romania,Netherlands,United Kingdom,United Kingdom
Call: Understanding disease: systems medicine (H2020-PHC-2015-two-stage, 2015)
Start date: 2016-01-01
End date: 2019-12-31
Duration (months): 48.0
Total project cost (EUR): 5759923.75
EU funding (EUR): 5759923.75
Participants: 16
Project status: CLOSED

Alcohol addiction ranks among the primary global causes of preventable death and disabilities in human population, but treatment options are very limited. Rational strategies for design and development of novel, evidence based therapies for alcohol addiction are still missing. Within this project, we will utilize a translational approach based on clinical studies and animal experiments to fill this gap. We will provide a novel discovery strategy based on systems biology concepts that uses mathematical and network theoretical models to identify brain sites and functional networks that can be targeted specifically by therapeutic interventions. To build predictive models of the ‘relapse-prone’ state of brain networks we will use magnetic resonance imaging and neurochemical data from patients and laboratory animals. The mathematical models will be rigorously tested through experimental procedures aimed to guide network dynamics towards increased resilience. We expect to identify hubs that promote ‘relapse-proneness’ and to predict how aberrant network states could be normalized. Proof of concept experiments in animal will need to demonstrate this possibility by showing directed remodeling of functional brain networks by targeted interventions prescribed by the theoretical framework. Thus, our translational goal will be achieved by a theoretical and experimental framework for making predictions based on fMRI and mathematical modeling, which is verified in animals, and which can be transferred to humans. To achieve this goal we have assembled an interdisciplinary consortium (eight European countries) of world-class expertise in all complementary skills required for the project. If successful this project will positively impact on the development of new therapies for a disorder with largely unmet clinical needs, and thus help to address a serious and widespread health problem in our societies.

Keywords: functional connectivity,neurochemical connectom,brain network,graph theory,mathematical model,alcoholism,patients,animal model,treatment
Virtual IoT Maintenance System (VIMS)

Framework: Horizon 2020 — Industrial Leadership
Action type: Innovation actions
Countries involved: Germany,Spain,Spain,Switzerland,Portugal,Portugal
Call: Fast Track to Innovation (FTI) (H2020-EIC-FTI-2018-2020, 2019)
Start date: 2019-11-01
End date: 2022-04-30
Duration (months): 30.0
Total project cost (EUR): 3351186.25
EU funding (EUR): 2345830.38
Participants: 7
Project status: CLOSED

The objective of the VIMS (Virtual IoT Maintenance System) project consists in developing and industrializing a new, complete, and integrated digital ecosystem for industrial and manufacturing environments. The core of the VIMS system combines an IIoT (Industrial Internet of Things) platform with a digital twin (DT) of the factory or production line. On one hand, the IIoT platform allows to collect and organize data which is harvested directly from the manufacturing process at the shop-floor (from PLC, SCADA, smart sensors…) as well as from other information systems (MES, ERP…). In addition, the data can be post-processed using advanced data analysis tools based on machine learning (ML) and artificial intelligence (AI) methods in order to obtain meaningful information about the manufacturing process. On the other hand, the DT yields a fully immersive and bi-directional experience in the factory or production line thanks to virtual reality (VR) and augmented reality (AR) technologies. Thanks to the DT, operators, engineers and managers will be able to receive and experience the relevant information about the production process even at a different location; in addition, they will be able to control remotely the manufacturing and maintenance processes via the DT. Moreover, several vertical business applications shall be implemented leveraging the core of the VIMS system. These applications are intended to address particular production and maintenance challenges, namely: a) Advanced operation and maintenance solutions (monitorization system in real time, predictive maintenance, asset tracking & optimized inventory) and b) Advanced AR/VR solutions (virtual training, operative guidance, remote assistance and path finding). VIMS system will be developed considering the compatibility with the maximum number of industries and factories, therefore we will assess the performance of the system in 3 real use cases of 2 different industries (aeronautic and pharmaceutical).
Longitudinal Integrative Models for Online Relapse Detection (LIMORD)

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: Mathematics
Countries involved: Australia,France
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2022-08-01
End date: 2024-07-31
Duration (months): 24.0
Total project cost (EUR): 125645.28
EU funding (EUR): 125645.28
Participants: 2
Project status: SIGNED

The goal of my project is to propose a novel statistical tool allowing patient classification, earlier relapse detection and better prognosis estimation in order to move forward into personalized medicine in Multiple Myeloma. To this aim, I will develop new statistical models and computational schemes to incorporate large follow-up omics datasets in a decision framework. As a statistician coming from theoretical mathematics, this project will provide me a unique opportunity to acquire new knowledge in biology and new supervision skills in order to translate theoretical mathematical results into real added value in the way we treat patients. The first challenge I will address is the development of statistical methods based on Variational Auto-Encoders to integrate multiple omics data-type at multiple time-points. My model will have to be flexible enough to allow for missing data (for instance a full omic dataset missing at a given time point due to experiment failure) and to accommodate for data acquired in an online manner. The second challenge I will address is the development of quality metrics and analysis methods for direct RNA sequencing data from patient samples. The third challenge I will address concerns the numerical inference difficulties of Partially Observable Markov Decision Processes when the dimension of the data increases. Approximation strategies will be investigated to make use of the high-dimensional, heterogeneous biological data in a relapse detection framework. Finally, I will develop a software package incorporating our results intended to help clinicians take the optimal decision when treating their patients. An important aspect of my project is to integrate it both to a biological laboratory in Australia and a mathematical group in France, together with a collaboration with clinicians in a French hospital, hence I will carry out the entire process of designing the statistical tool and its software package for a concrete use in the clinic.

Keywords: machine learning,markov decision processes
Control of cell identity in pluripotent and germline cells by OCT4 orchestration of chromatin binding and enhancer regulation (OCTOBER)

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: 2019-10-28
End date: 2021-10-27
Duration (months): 24.0
Total project cost (EUR): 212933.76
EU funding (EUR): 212933.76
Participants: 1
Project status: CLOSED

The development of an organism requires the fine-tuned balance between self-renewal and differentiation of pluripotent cells. Pluripotency is controlled by a group of transcription factors (TFs) that constitute the Pluripotency Gene Regulatory Network (PGRN). OCT4 is a core component of the PGRN and is required to specify pluripotency in vivo and to maintain pluripotency in vitro in embryonic stem cells (ESCs). OCT4 is also required for survival of unipotent primordial germ cells (PGCs). However, it is still not clear how a pluripotency-associated TF like OCT4 can also be required in both ESCs and in more differentiated cells. In this proposal, I will address the hypothesis that OCT4 function in ESCs and PGCs requires the targeting of distinct cis-regulatory elements (CREs - enhancers and promoters) in the two systems. By comparing the genome-wide distribution of OCT4 in ESCs and PGCs, I will identify the OCT4-bound CREs specific for each cell type. Using bioinformatic tools, I will identify genes associated with these elements that distinguish between the transcriptional networks regulated by OCT4 in each cell type. In ESCs a decrease of OCT4 expression correlates with an increase in OCT4 binding to chromatin. To unveil the mechanisms underpinning this phenotype, I will perturb the OCT4 concentration in ESCs by combining targeted genome editing and protein degradation assays. I will extend studies of altering OCT4 concentration to PGCs using similar approaches. In addition, I will assess the hypothesis that physical interactions between CREs play a defining role in cell-specific gene expression. I will use 3D genome assays to determine whether the context-dependent function of OCT4 in ESCs and PGCs depends upon the regulation of distinct interactions between different sets of CREs in each cell type. Using cutting-edge assays, this action will shed light on the dual activity of OCT4 in ESCs and PGCs, providing new insights into stem cell biology.

Keywords: embryonic stem cells,primordial germ cells,oct4,cis regulatory elements
Integrated porous cementitious Nanocomposites in non-Residential building envelopes for Green active/passive energy STORAGE (NRG-STORAGE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Technologies enabling energy-efficient systems and energy-efficient buildings with a low environmental impact
Action type: Innovation actions
Countries involved: Argentina,Germany,Spain,Spain,Spain,Germany,Italy,Germany,Poland,Bulgaria,Czechia,Netherlands
Call: Integration of energy smart materials in non-residential buildings (IA) (H2020-NMBP-EEB-2019, 2019)
Start date: 2020-04-01
End date: 2024-03-31
Duration (months): 48.0
Total project cost (EUR): 6846750.0
EU funding (EUR): 5602934.26
Participants: 13
Project status: SIGNED

The NRG-STORAGE project will launch a novel breakthrough solution that replaces the currently available insulation materials used in building envelopes, by proposing a multi-functional and eNeRGy saving cementitious Foam (NRG-Foam). The heat-activated foam will be used for passive/active management of energy transfer and will be applied to new building envelopes and to retrofit existing ones. Graphene-based nano-additives will be doped in both cementitious foam matrix and bio-based PCM fraction for improving the thermal storage capacity, volume stability and mechanical properties of the resulting composite. Two active/passive systems will be prototyped and validated. First, an implicit heating system for thermal activation of the added nano-graphene will be installed representing a material-based approach, and, second, a multi-functional energy efficient façade system (MeeFS) will be installed, to diverse and direct the thermal absorption capacity and shadowing of the external building walls for optimizing the NRG-Foam’s. NRG-Foam composites will be optimized to achieve the best compromise between thermal insulating properties (air bubbles) and heat storage capacity (bio-PCMs). A highly conductive cementitious paste will be designed and produced, targeting on an increase in thermal conductivity (once activated up to 10 times for bio-PCM, and 2 times for cement matrix), and an enhanced efficiency of bio-PCM heat storing performance (> 5 times). With this project, the partners will develop an innovative functional material that combines high insulation capabilities (more than 25% of classical layers) and high energy-storage capacity (more than 10% of improvement in active applications). Furthermore, the NRG-Foam layer will be characterized by a high water and air tightness (between 10% and 25% higher than existing solutions) and at least 15% lower costs than the actual solutions available in Europe for insulation purposes of non-residential buildings.

Keywords: energy saving,smart materials,bio based pcm,ultra lightweight cementitious foam,nano additions,graphene,active,passive systems,meta material,optimization,prototyping,building envelopes