Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Machine Learning applied to Reactivity: combination of HDNNs with ReaxFF (MaLeR)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Netherlands
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2018-12-01
End date: 2020-11-30
Duration (months): 24.0
Total project cost (EUR): 165598.8
EU funding (EUR): 165598.8
Participants: 1
Project status: CLOSED

Computational chemistry and materials science rely on accurate methods for calculating the thermodynamic and kinetic stabilities of different compounds. In order to model large and realistic chemical systems, computationally efficient methods like force-fields are needed. Force-fields have physically motivated functional forms, but are not flexible enough to accurately describe most chemical reactions. Here, we intend to alleviate this problem by combining a state-of-the-art reactive force field, ReaxFF, with artificial neural networks (NNs). NNs constitute an example of machine learning (ML) methods, and are extremely fast to compute. Due to their very flexible functional forms, NNs can be parameterized to reproduce any other target function, which here is the error made by ReaxFF. By combining ReaxFF with the variant of NNs known as high-dimensional neural networks (HDNNs), the resulting “ReaxFF+HDNN” method will provide an all-purpose computationally efficient method for applications in chemistry, biochemistry, and materials science. The developed method will first be applied to unravel high-temperature fullerene reconstruction mechanisms, a notorious case where the original ReaxFF functional form has been shown to be inadequate. The combination of HDNNs with the more computationally expensive semi-empirical density functional based tight-binding method, DFTB, will also be explored. The development and implementation will take place at SCM in Amsterdam, which has a long-standing history of modern ReaxFF method developments.

Keywords: molecular dynamics,reactive force fields,reaxff,machine learning,high dimensional neural network potentials,dftb
Data Assimilation for Agent-Based Models: Applications to Civil Emergencies (DUST)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Institutions, Governance and Legal Systems
Panel description: Political science, international relations, law
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2017-STG, 2017)
Start date: 2018-01-01
End date: 2023-12-31
Duration (months): 72.0
Total project cost (EUR): 1499840.0
EU funding (EUR): 1499840.0
Participants: 1
Project status: SIGNED

Civil emergencies such as flooding, terrorist attacks, fire, etc., can have devastating impacts on people, infrastructure, and economies. Knowing how to best respond to an emergency can be extremely difficult because building a clear picture of the emerging situation is challenging with the limited data and modelling capabilities that are available. Agent-based modelling (ABM) is a field that excels in its ability to simulate human systems and has therefore become a popular tool for simulating disasters and for modelling strategies that are aimed at mitigating developing problems. However, the field suffers from a serious drawback: models are not able to incorporate up-to-date data (e.g. social media, mobile telephone use, public transport records, etc.). Instead they are initialised with historical data and therefore their forecasts diverge rapidly from reality. To address this major shortcoming, this research will develop dynamic data assimilation methods for use in ABMs. These techniques have already revolutionised weather forecasts and could offer the same advantages for ABMs of social systems. There are serious methodological barriers that must be overcome, but this research has the potential to produce a step change in the ability of models to create accurate short-term forecasts of social systems. The project is largely methodological, and will evidence the efficacy of the new methods by developing a cutting-edge simulation of a city – entitled the Dynamic Urban Simulation Technique (DUST) – that can be dynamically optimised with streaming ‘big’ data. The model will ultimately be used in three areas of important policy impact: (1) as a tool for understanding and managing cities; (2) as a planning tool for exploring and preparing for potential emergency situations; and (3) as a real-time management tool, drawing on current data as they emerge to create the most reliable picture of the current situation.

Keywords: agent based modeling,data assimilation,simulation,smart cities,civil emergency
A diagnostics platform for dengue fever and mosquito-borne diseases (COMBO)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Denmark
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2018)
Start date: 2018-05-01
End date: 2021-04-30
Duration (months): 36.0
Total project cost (EUR): 2800671.25
EU funding (EUR): 1927219.0
Participants: 1
Project status: CLOSED

BluSense Diagnostics has developed an innovative nanotechnology-based point-of-care blood testing platform for detecting dengue fever. With a single drop of blood, we can within minutes and with very high accuracy, test whether patients have been infected with dengue fever. The technology will be a major step forward in the treatment of dengue in areas around the world, where dengue is a serious threat. In 2016, more than 330m people were tested positive for dengue, and the number is growing. Our first dengue diagnostic blood-test will be ready for sales in Q2 2018. The overall objective of the project is to enable BluSense to move from a single and narrow product (ViroTrack Dengue Acute) produced in low-volumes, to a full diagnostic dengue platform (Virotrack Dengue Combo) produced on a high-throughput automated line, and to facilitate the market entry with pre-sales activities in terms of e.g. local regulatory approval and training. With the Virotrack Dengue Combo platform we can not only diagnose if patients are infected with dengue, but also test the severity of the infection. Hence is becomes much easier to advice the right treatment. Beyond this project, the aim is to further develop the Virotrack Dengue Combo platform into a generic infectious diseases platform. If the project is successful, Virotrack Dengue Combo can be launched in the market right after the 24-month project period, mid 2020. We furthermore aim at going break-even in 2021 and at that time employ 53 full-time employees, up from approx. 30 today.

Keywords: point of care diagnostics,dengue,nanotechnology
Correlative smFRET/electrophysiology for long-term studies of protein dynamics (COSMO)

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: Belgium
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-04-13
End date: 2023-04-12
Duration (months): 24.0
Total project cost (EUR): 166320.0
EU funding (EUR): 166320.0
Participants: 1
Project status: CLOSED

The conformational dynamics of proteins are essential for their proper functioning, and impaired dynamics can lead to disease. However, it remains difficult to experimentally determine the multitude of conformations adopted by proteins, their lifetimes and the transitions between them. Single-molecule FRET (smFRET) is probably the most suitable technique available due to its ability to operate under ambient conditions while avoiding ensemble averaging. Yet the technique is limited by the short observation times (a few seconds) and the difficulty of measuring more than one molecular distance at the same time. The goal of this proposal is to develop an innovative correlative approach that can extend smFRET observations to much longer timescales, while also providing a way to integrate multiple measurements into a coherent molecular picture. I will do so by combining smFRET measurements with nanopore-based electrophysiological experiments that have a high temporal resolution and are also sensitive to conformational changes. Our corelative system will thus combine the speed and the sensitivity of electrical readout with the direct observation of molecular distances using smFRET. We will apply this methodology to map conformational dynamics of the biologically-important Ras proteins. We expect that this project will allow us to develop our innovative methodology and claim the novelty of the concept. This new methodology should open entirely new opportunities to monitor fast and long-term conformational dynamics of proteins or assembly processes of macromolecules.

Keywords: single molecule fret,nanopore,electrophysiology,protein dynamics
EEN Anatolia supports to increase the innovation management capacities of SMEs (EENinnoSMES4)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Specific Grant agreement
Countries involved: Türkiye,Türkiye,Türkiye,Türkiye
Call: H2020 ENTREPRISE EUROPE NETWORK SGA4 2020-2021 (H2020-EEN-SGA4-2020-2021, 2019)
Start date: 2020-01-01
End date: 2021-12-31
Duration (months): 24.0
Total project cost (EUR): 193250.0
EU funding (EUR): 193250.0
Participants: 5
Project status: CLOSED

The proposed project addresses the action for “Establishing services “Enhancing the innovation management capacity of SMEs” in the Enterprise Europe Network” to improve the innovation management capacity of SMEs. In the period covering the years 2015-2021, Tier 1 and Tier 2 services were offered to SMEs by EEN Anatolia Consortium. (The contents of Tier 1 and Tier 2 were respectively generic promotion, networking services given by EEN staff and specialized advisory services given by innovation advisers). The activities foreseen under this proposal is to give Tier 3 services to SMEs.106 full enhancing SMEs’ innovation management capacity service packages and 20 Key Account Management service packages will be offered to SME’s till the end of 2021 and every service package is foreseen. Partner 06 of EEN Anatolia Consortium, has undergone changes in the structure and staff of the organization and will be inactive in 2020-2021.

Keywords: innovation management,key account management,improve assessment,sme instrument,fast track innovation
Development of methods for deriving optimized shapes of morphing structures considering both aerodynamic performances and specific mechanical morphing boundary conditions (OPTIMOrph)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Clean Sky 2
Action type: Research and Innovation actions
Partnership: CS2 (Art-187)
Countries involved: Italy,United Kingdom
Call: Development of methods for deriving optimized shapes of morphing structures considering both aerodynamic performances and specific mechanical morphing boundary conditions (H2020-CS2-CFP04-2016-02, 2016)
Start date: 2017-06-01
End date: 2019-06-30
Duration (months): 25.0
Total project cost (EUR): 350725.0
EU funding (EUR): 350725.0
Participants: 2
Project status: CLOSED

The OPTIMOrph project addresses the development of a robust and reliable numerical optimization methodology able to identify target shapes for deflected positions of morphing structures based on optimal aerodynamic characteristics (i.e. basically lift and drag), while taking into account in a consistent way feasibility issues related to mechanical considerations and material properties. This is actually a requirement very specific to morphing structures, where the mechanical feasibility and complexity is one of the key features to be taken into consideration throughout the design process. The project objectives will be achieved through the implementation of a general multi-disciplinary, multi-objective, multi-constrained optimization procedure able to enhance aerodynamic performance in a compliant way with the pertinent morphing mechanisms and materials limitations, thus enabling the implementation of a step-change in the design of morphing structures. In OPTIMOrph, a multi-fidelity approach will be adopted, in which a high-fidelity FSI solver will be used for reconstruction of a surrogate model (low-fidelity), which in turn will assist a very advanced optimization engine where GAs featuring unique operators are included. This approach will ensure that the optimal solutions achieved are accurate and reliable, while keeping the computational effort within acceptable limits also for an industrial application. The methodology implemented in OPTIMOrph will contribute to the inclusion of morphing technologies since the very early stages of the aircraft design process and will open unprecedented design opportunities to be applied either to re-engineering of current aircraft or to completely new upcoming aircraft architectures. Although very general, the procedure will be applied to a morphing wing leading edge, and a series of optimal indications will be delivered for implementing an integrated aerodynamic/structural proof of concept.

Keywords: morphing wings,multi disciplinary and multi objective optimization,multiple constraint handling,morphing concepts and mechanisms,morphing materials properties
A LAB-ON-A-CHIP DEVICE FOR PURE CIRCULATING TUMOR CELL ISOLATION FROM WHOLE BLOOD FOR CANCER THERAPY (pureCTC)

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: Belgium
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-08-01
End date: 2019-07-31
Duration (months): 24.0
Total project cost (EUR): 172800.0
EU funding (EUR): 172800.0
Participants: 1
Project status: CLOSED

The overall objective of pureCTC is to realize a comprehensive lab-on-a-chip platform that redefines the state-of-the-art technology to address all the requirements for fast, efficient and reliable CTC isolation/purification from whole blood. CTCs are rare cells that originate from tumors, and which travel in the human circulatory system to eventually spread the disease to other organs. Consequently, analysis of CTCs is crucial for revealing the mechanisms of cancer and developing new treatments. However, only 1-10 CTCs are present per mL of blood against billions of peripheral blood cells. The extreme rarity and inherent heterogeneity of CTCs implies a single-cell analysis strategy. Therefore, a highly selective, efficient and reliable system yet providing high throughput is mandatory. Cell labeling based strategies are inefficient for CTC analysis, since CTCs express biomarkers with high heterogeneity. Label-free methods based on size lack the ability to distinguish CTCs from leukocytes, and methods based on electrical properties fail to provide sufficient enrichment or throughput levels. To address these challenges, pureCTC proposes the development a microfluidic platform for successive enrichment, identification, and isolation of CTCs at the single-cell level, where a blood sample taken from a patient is directly injected and utilized without any pre-treatment. Namely, the platform is composed of 3 modules that work in tandem, each of them having innovative aspects: enrichment via 2D hydrodynamic-dielectrophoretic separation, identification via synchronous electro-optical detection, and isolation via a dielectrophoretic valve. The proposed research will undoubtedly contribute to the knowledge-based economy and European society, specifically on cancer research by providing an instrumental platform for diagnosis, monitoring and treatment of diseases with unprecedented selectivity, and enabling the advancement of personalized treatments.

Keywords: circulating tumor cells ctcs,liquid biopsy,microchip flow cytometry,single cell analysis,integrated 3 d electrodes,dielectrophoresis,microfluidics,lab on a chip,cancer diagnostics
Advanced mechatronics devices for a novel turboprop Electric starter-generator and health monitoring system (ACHIEVE)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Clean Sky 2
Action type: Research and Innovation actions
Partnership: CS2 (Art-187)
Countries involved: France,United Kingdom,United Kingdom
Call: Advanced mechatronics devices for electrical management system of Turboprop (H2020-CS2-CFP03-2016-01, 2016)
Start date: 2017-01-16
End date: 2021-07-15
Duration (months): 54.0
Total project cost (EUR): 900591.25
EU funding (EUR): 900591.25
Participants: 3
Project status: CLOSED

The ACHIEVE Consortium will bring together their world-leading expertise in the design and manufacturing of electrical machines for aircraft Advanced Generation Systems (AGS), integrated Power Electronics (PE), advanced control systems and intelligent thermal management, to develop an innovative advanced mechatronic device for electrical power management system of Turboprop. The ACHIEVE Consortium will combine their world-leading expertise in the technical areas of PE, AGS and their control, as well as in modelling and simulation for aerospace applications. The aim of ACHIEVE is to develop an innovative mechatronic system with functions of generating, multi-functional, more efficient, reliable, compact and lighter and hence contributing towards higher performance and more efficient and greener turboprops The topic of advanced mechatronics devices is to support the CS2 Engine ITD WP3 “Business aviation / Short range reginal Turboprop Demonstrator” programme led by Turbomeca. The WP3 aims to acquisition of technologies for a high performance turboprop engine in the 1800-2000 shp class for business aviation and short range regional applications. This project will deliver a novel advanced mechatronics device which will be integrated to the developed engine. The developed mechatronic device is essentially an electrical starter/generator system with functions including motoring, generating, power transmission, health monitoring and communication. The concept of ACHIEVE is to design, manufacture and test an innovative and integrated mechatronic device which is capable of performing motoring, generating, power transmission, health monitoring and signal communications. The mechatronic device is essentially made of an electrical machine, an electronic power converter and associate controllers. Moving from the state-of-the-art brushed 28Vdc generator, the system developed within the ACHIEVE will be brushless with higher power density, lower weight and higher TBMO.

Keywords: mechatronic device,brushless electrical machine,power converter,health monitoring,high power density
Methodologies Yielding CLimate IMpact Assessments Through Economics (MYCLIMATE)

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: Economic Sciences
Countries involved: France
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2017-09-01
End date: 2020-06-29
Duration (months): 24.0
Total project cost (EUR): 185076.0
EU funding (EUR): 185076.0
Participants: 1
Project status: CLOSED

Humans rely for their food on agricultural products. Agricultural production relies on soil, climate, agricultural inputs, and farmers. The importance of climate and soil inputs has been recently reconsidered in agricultural production. However, the quantification of the impact of climate change on agricultural production has been conducted with regression methods that impose undesired assumptions on the obtained results. If it is true that climate is changing, an estimation of climate change impacts on agriculture free of undesired assumptions is the key to understanding a strategy towards a sustainable future. Going beyond the methodological approaches proposed in previous studies, in this action I bridge the gap between production economics and the agronomic and climate economics literature. The first contribution of this action will merge farm accountancy datasets with climatic and soil characteristics at the most disaggregate geographical level possible (at least NUTS3 or smaller location). The second contribution of this action will methodologically reconsider the impact of climate change on plant growth. The third contribution of this action proposes a generalized decomposition method that, either with econometric or nonparametric methods, can attribute changes in productivity and profitability to different groups of inputs and outputs, among which are soil and climate inputs. The fourth contribution evaluates the production practices of the farmers and shows how much climatic and soil inputs are implicitly valued.

Keywords: agricultural production,climate change,production economics,methodology,soil,economic impact,biological integration,productivity,shadow pricing,temperature,precipitation,carbon,clay
Bendable Bioplatform for Electrically stimulated Neuronal Differentiation (BEND)

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: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-08-15
End date: 2018-08-14
Duration (months): 24.0
Total project cost (EUR): 195454.8
EU funding (EUR): 195454.8
Participants: 1
Project status: CLOSED

Summary of Marie Curie Proposal for H2020-MSCA-IF-2015 “Bendable Bioplatform for Electrically stimulated Neuronal Differentiation” With western countries aging faster, the neurodegenerative diseases like Parkinson’s, Alzheimer’s, Huntington’s etc. pose serious threat to quality of life, especially for people over 65 years[1]. In Europe, number of people suffering with dementia, which results from neuronal degeneration, is on the rise it is expected to be double in the next 20 Years[2]. The neuronal degeneration is irreversible[3] and currently the cell therapy for regeneration of neuron network is the only option to compensate such a loss. Recently, the induced pluripotent stem cell (iPSC) derived NSC therapy has come up as an excellent opportunity in treating of neuro degenerative diseases. However, proliferation and differentiation of iPS cell population in neuronal replacement therapies poses many technical challenges such as targeted neurite differentiation to compensate desired loss with controlled differentiation[4]. Traditionally, the neuronal differentiation of iPSC is performed using several transcriptional and growth factors, which are complex, expensive and non-scalable processes[5]. For this reason, the research for a simple, robust and scalable method for generating large number of mature, differentiated neuronal cell deserves top priority. In addition, an accurate on/off system for scalable proliferation and neuronal differentiation is pivotal for the development of implantable bioelectronics circuit suitable for in vivo application. It is believed that the electrical stimulus controlled neuronal differentiation of stem cells on a soft, bendable electro conductive substrate can be suitable for bioelectronics application and also for compensating neuronal loss in the degenerative disease or injuries. This project is an ambitious endeavour in this direction. A bendable bioplatform will be developed for electrically stimulated neural differentiation t

Keywords: bendable bioplatform,electrical simulation,neuronal differentiation,nanoscale pattern,rgd peptide