Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Bond Activation and Catalysis by Transition Metal Frustrated Lewis Pairs (TM-FLPS)

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: Chemistry
Countries involved: Spain
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2015, 2015)
Start date: 2016-10-01
End date: 2018-09-30
Duration (months): 24.0
Total project cost (EUR): 170121.6
EU funding (EUR): 170121.6
Participants: 1
Project status: CLOSED

Catalysis is critical to the delivery of future growth in the manufacturing sector: ca. 75% of all chemicals currently require catalysts at some stage in their manufacture, with catalytic processes generating €1,000 Bn in products world-wide. This proposal targets a step-change in homogenous catalysis by approaching it from a new perspective. Frustrated Lewis Pairs (FLPs) are among the most promising new avenues for the development of future catalysts and offer important advantages in the context of sustainability. Thus the young field of FLP chemistry has experienced an enormous expansion since its founding discoveries one decade ago. However, this rapid development contrasts with the very limited number of examples in the literature in which one of the Lewis acid/base (LA/B) components is based on a transition metal. The current proposal aims to combine the rich chemistry of transition metals (ultimately Earth-abundant elements) with the powerful reactivity offered by FLP systems by substituting one of its LA/B components by a transition metal. The extraordinary structural diversity of transition metals, along with the rich variety of elementary reactions that take place over those centres, are attributes that will extend the usefulness of FLPs far beyond the present (mainly) hydrogenation reactions and should allow developing new catalytic processes unreachable for current homogeneous catalysts. The possibilities are as unexplored as unlimited. We aim to exploit Pt and Au systems, for which preliminary results are available in the host group and will give high confidence of short-term success. Subsequently we will build on the key principles so established to expand our approach to ecologically more benign first-row transition metals. The potential in bond activation and catalysis of the resulting transition metal FLP systems will be explored with the ultimate goal of developing novel catalytic cycles of industrial relevance.

Keywords: frustrated lewis pair,first row transition metals,bond activation,terphenyl phosphine,boryl ligands,gold,platinum
APERIM: Advanced bioinformatics platform for PERsonalised cancer IMmunotherapy (APERIM)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Health care provision and integrated care
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Spain,Austria,Germany,Germany,France,Czechia,Netherlands,Netherlands
Call: Advancing bioinformatics to meet biomedical and clinical needs (H2020-PHC-2014-two-stage, 2014)
Start date: 2015-05-01
End date: 2018-04-30
Duration (months): 36.0
Total project cost (EUR): 2999287.5
EU funding (EUR): 2999287.5
Participants: 11
Project status: CLOSED

Cancer treatment platforms that involve the use of the adaptive immune system have demonstrated profound tumour regressions including complete cure. Importantly, technological advances in next-generation sequencing (NGS) allow for the first time the development of personalised cancer immunotherapies that target patient specific mutations. However, clinical application is currently hampered by specific bottlenecks in bioinformatics, which we aim to address in this proposal. The overall objective of our trans-disciplinary network of leading experts in bioinformatics and cancer immunology is to develop an Advanced bioinformatics platform for PERrsonalised cancer IMmunotherapy (APERIM). Specifically we aim to develop: 1) database for the integration of NGS data, images of whole tissue slides of tumour sections, and clinical data. To enhance the usability and the data sharing we will use semantic web technologies, and will provide standardised interfaces to a set of analytical tools. 2) tools for automated quantification of tumour-infiltrating lymphocytes using whole tissue slide images and NGS data for patient stratification. 3) analytical pipeline for NGS-guided individualised cancer vaccines including crucial NGS data analysis and epitope selection components for the selection of vaccination targets. 4) a method for deriving T-cell receptor (TCR) sequences from NGS data and predicting TCR specificity. We will achieve these aims using unique training and validation datasets available to the consortium. We will develop user-friendly software modules as well as analytical standard operating procedures for clinical use, and apply the bioinformatics platform in clinical settings. The bioinformatics platform will considerably accelerate the clinical translation and maximise the accessibility and utility of biomedical data in research and medicine.

Keywords: cancer immunology
TeraHertz quasiOptical Receiver (THOR)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Sweden
Call: ERC-Proof of Concept (ERC-2017-PoC, 2017)
Start date: 2017-11-01
End date: 2019-04-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 122500.0
Participants: 2
Project status: CLOSED

Remote sensing and monitoring in various environments solves many scientific and societal problems. Examples are: industrial air pollution control, global atmosphere surveillance, our planet system and the universe exploration, process controls in industry, and material research in laboratories. Molecular absorption/emission feature, combined with a high penetration depth of THz waves through dust, short wavelength allowing for high pointing directivity, all these factors determine the uniqueness of the THz range of electro-magnetic wave spectrum (0.1-10THz) in the mentioned applications. High radiometric sensitivity of THz wave detectors is a vital selection criterion for a THz system to become attractive. Uncooled THz detectors/mixers show adequate sensitivity only for frequencies below 1THz, whereas “supra-THz” (>1THz) detectors require cooling down to 4K. This limitation hinders exploitation of THz spectroscopy for such important application as atmosphere monitoring, local and global pollution surveillance, security, as well as universal sciences, in full. Small-scale satellites, balloons, portable sensors, can’t afford LHe cooling or power thirsty 4K cryo-coolers. For large-scale space missions, 4K cooling has already been utilized (e.g. Herschel and Planck Space observatories, COBE, etc), however it limited the missions lifetime significantly. In the frame of ERC StG grant Teramix, we developed technology, where high sensitivity and large bandwidth THz detection can be achieved at 20-40K temperature range, which can be accessed with compact and low power consumption coolers. The THOR project will lead the new technology through pre-commercial prototyping, a real-world application in an existing (representative) system, and explore marketing opportunities in both commercial and research areas.

Keywords: terahertz detector,electronics,space industry
Collaborative production for the circular economy; a community approach (Pop-Machina)

Framework: Horizon 2020 — Societal Challenges
Programme: Climate action, environment,  resource efficiency and raw materials
Theme: Protection of the environment, sustainable management of natural resources, water , biodiversity and ecosystems
Action type: Innovation actions
Countries involved: Spain,Spain,Türkiye,Greece,Lithuania,Türkiye,Belgium,Greece,Lithuania,Greece,Belgium,Greece,Netherlands,Netherlands,United Kingdom,Luxembourg
Call: Demonstrating systemic urban development for circular and regenerative cities (H2020-SC5-2018-2, 2018)
Start date: 2019-06-01
End date: 2023-11-30
Duration (months): 54.0
Total project cost (EUR): 11057890.71
EU funding (EUR): 9999592.5
Participants: 25
Project status: SIGNED

POP-MACHINA aims to demonstrate the power and potential of the maker movement and collaborative production for the EU circular economy. We draw from a number of cut-edge technologies (factory-of-the-future, blockchain) and disciplines (urban planning, architecture) to provide the support necessary to overcome scaling issues; a typical drawback of collaborative production; to find the areas more in need of our intervention and to reconfigure unused spaces. We put forth an elaborate community engagement program to network, incentivize and stimulate through maker faires and events existing and new maker communities in all our municipalities. We build upon the current informal curriculum for maker skills development by nurturing the social side and we put educators and makers together to exchange ideas on the training modalities. A particular focus on the skill development of women and vulnerable groups will aim to empower these (underrepresented) segments to partake actively in collaborative production. In every pilot area we will demonstrate business oriented collaborative production of feasible and sustainable concepts from secondary raw material or other sustainable inputs, based on the needs and preferences of the local stakeholders. A thorough impact assessment framework with increased scope (e.g. social) will be co-designed with stakeholders after short basic assessment trainings and will be used in the assessment of our pilot work. Based on the findings we will kick-start a series of policy events to discuss openly – without pushing our results – the tax and legal barriers that hamper collaborative production.

Keywords: makers,collaborative production,factory of the future,urban planning,makerspaces
Co-production CeLL performing Human-Robot Collaborative AssEmbly (CoLLaboratE)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Technologies for Factories of the Future
Action type: Research and Innovation actions
Countries involved: Spain,Italy,Italy,Belgium,Greece,Türkiye,Poland,Romania,Slovenia,Switzerland,Greece,Slovenia,France,Denmark
Call: Effective Industrial Human-Robot Collaboration (RIA) (H2020-NMBP-FOF-2018, 2018)
Start date: 2018-10-01
End date: 2022-03-31
Duration (months): 42.0
Total project cost (EUR): 6864600.0
EU funding (EUR): 6864600.0
Participants: 17
Project status: CLOSED

Traditional manufacturing systems lack the necessary flexibility and reconfigurability that can allow short production cycles and fast deployment of the updated system. Although the use of automation technologies based on industrial robots can increase the adaptability of a production line, the desired flexibility cannot be achieved until abilities for genuine collaboration of the robots with the human workers are developed. CoLLaboratE will revolutionize the way industrial robots learn to cooperate with human workers for performing new manufacturing tasks, with a special focus on the challenging area of assembly operations. The envisioned system for collaborative assembly will be capable of allocating human and robotic resources for executing the production plan sharing the tasks according to the capabilities of the available actors. The CoLLaboratE project will build upon state-of-the-art methods for teaching the robot assembly tasks using human demonstration, extending them to facilitate genuine human-robot collaboration. To this end, a framework for equipping the robots and AGV mobile platforms with basic collaboration skills, such as load sharing, human touch recognition and human intention detection, will also be developed, coupled with deep reinforcement learning algorithms for increasing adaptability. Special attention will be paid to providing effective safety strategies allowing the use of a fenceless approach within the production cell. As a result, closer collaboration will be achievable and efficient production plans making optimal use of the available resources will be designed and executed. The proposed solution will be evaluated in four different pilot sites, which will be implemented as collaborative factory floors of the industrial partners in Italy, Slovenia, Turkey, and Romania.

Keywords: collaborative robots,automation,automotive industry,robotic assembly,co production cell,adaptive robot control,human tracking,self learning
Extracellular Vesicles for Bone Regeneration – alternatives to Stem-cell Therapy (EVEREST)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Prevention, Diagnosis and Treatment of Human Diseases
Panel description: Medical technologies and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions, pharmacology, preventative medicine, epidemiology and public health, digital medicine
Countries involved: Ireland,France
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-11-01
End date: 2025-10-31
Duration (months): 60.0
Total project cost (EUR): 1499925.0
EU funding (EUR): 1499925.0
Participants: 2
Project status: SIGNED

The therapeutic benefits of mesenchymal stem cells (MSCs), the state-of-the-art treatment for healing bone defects following trauma, resection of cancerous bone tumors, or metabolic bone diseases, has been attributed to their secreted factors. The regenerative potential of MSC-secreted extracellular vesicles (EVs), nanoparticles which deliver bioactive cargo (nucleic acids, proteins, and lipids) between cells, has recently been reported. The applicant will embark upon frontier research with the objective of progressing beyond the state-of-the-art, by harnessing the therapeutic effects of MSCs, but in a cutting-edge, cell-free manner, by developing high potency EV-based bone replacements. This objective will be addressed by firstly testing novel hypotheses to delineate how culture environments, specifically mechanical cues (substrate elasticity and 3D dynamic), hypoxia, and cell stress can modulate the cargo of EVs secreted by MSC. Size exclusion chromatography, which separates EVs from soluble proteins will be employed. Heterogeneity of EV cargo and functionality between human MSC donors will also be evaluated. Answering these hypotheses will permit the intelligent design of targeted EV therapies. The hypothesis that EV-functionalized constructs, fabricated by 3D-printing, will lead to controlled and sustained release of EVs and induce bone formation in vivo will best tested. Together, this will answer critical questions, namely the most favorable environment for collection of potent EVs for regenerative medicine, which secretome component (EV, soluble factors) is responsible for bone regeneration, and whether MSC cell therapy can be replaced by cell-free EVs. EVEREST will develop a platform for targeted EV delivery in ground-breaking, easy to transport and handle, ‘off-the-shelf’ anatomically correct constructs, which have the potential to reduce pain by elimination of bone or bone marrow harvest, and revolutionize the treatment of bone defects.

Keywords: regenerative medicine,bone regeneration,extracellular vesicles,tissue engineering,bioengineering,3d printing
Lubricating Cartilage: exploring the relation between lubrication and gene-regulation to alleviate osteoarthritis (CartiLube)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Physical and analytical chemical sciences
Panel description: Analytical chemistry, chemical theory, physical chemistry/chemical physics
Countries involved: Israel,United Kingdom
Call: ERC Advanced Grant (ERC-2016-ADG, 2016)
Start date: 2017-09-01
End date: 2023-08-31
Duration (months): 72.0
Total project cost (EUR): 2499944.0
EU funding (EUR): 1901058.0
Participants: 2
Project status: SIGNED

Can we exploit insights from the remarkably lubricated surfaces of articular cartilage, to create lubricants that may alleviate osteoarthritis (OA), the most widespread joint disease, affecting millions? These, succinctly, are the challenges of the present proposal. They are driven by our recent finding that lubrication of destabilised joints leads to changes in gene-regulation of the cartilage-embedded chondrocytes to protect against development of the disease. OA alleviation is known to arise through orthopedically suppressing shear-stresses on the cartilage, and a central premise of this project is that, by reducing friction at the articulating cartilage through suitable lubrication, we may achieve the same beneficial effect on the disease. The objectives of this project are to better understand the origins of cartilage boundary lubrication through examination of friction-reduction by its main molecular components, and exploit that understanding to create lubricants that, on intra-articular injection, will lubricate cartilage sufficiently well to achieve alleviation of OA via gene regulation. The project will examine, via both nanotribometric and macroscopic measurements, how the main molecular species implicated in cartilage lubrication, lipids, hyaluronan and lubricin, and their combinations, act together to form optimally lubricating boundary layers on model surfaces as well as on excised cartilage. Based on this, we shall develop suitable materials to lubricate cartilage in joints, using mouse models. Lubricants will further be optimized with respect to their retention in the joint and cartilage targeting, both in model studies and in vivo. The effect of the lubricants in regulating gene expression, in reducing pain and cartilage degradation, and in promoting stem-cell adhesion to the cartilage will be studied in a mouse model in which OA has been induced. Our results will have implications for treatment of a common, debilitating disease.

Keywords: boundary lubrication,biological lubrication,cartilage friction and lubrication,biolubrication and mechanotransduction,osteoarthritis,cartilage lubrication and gene regulation
Graphene-based High Resolution Neural Interfaces for ICT-inspired Neuro-treatment (MINERGRACE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: United Kingdom
Call: ERC-Proof of Concept (ERC-2017-PoC, 2017)
Start date: 2018-02-01
End date: 2019-07-31
Duration (months): 18.0
Total project cost (EUR): 149875.0
EU funding (EUR): 149875.0
Participants: 1
Project status: CLOSED

Electronic devices enabling communication with human nervous system are becoming increasingly prevalent, offering novel information and communication (ICT)-based treatment techniques to help people overcome various disorders ranging from spinal cord injuries (SCIs) to missing limbs. Millions of people worldwide suffer from such ailments with a cumulative cost to the society estimated in billions of Euros annually. Next-generation ICT-based treatment techniques demand for interfaces with higher spatial resolution compared to state-of-the-art. To address this demand, MINERGRACE aims to build a prototype transceiver with high spatial resolution based on nano-patterned graphene sheets (NPGSs), which can be utilised as high resolution neural interfaces (NIs) capable of differentiating and generating highly localised fluctuations in specific ion concentrations. As the project outcome, MINERGRACE will provide a proof-of-concept NPGS-based NI prototype, i.e., a portable electronic device that can be integrated with a microprocessor. High resolution aspects of the MINERGRACE project outcome will provide a very significant improvement to the state-of-the-art in terms of both the capacity of the communication and the complexity of data communicated with the nervous system, enabling the communication with individual neurons. The project outcome will have a wide spectrum of applications involving NIs, e.g., ICT-based SCI treatments and neuro-prosthesis, significantly contributing to their quality of service. Commercialisation process will involve investigation into other commercialisation activities towards other NI products, development of an understanding of intellectual property rights (IPR) positions, and strategies for patenting activities in light of the achieved understanding of IPR position. We will work with identified industrial partners and societal organisations to collaborate towards in-market positioning for delivering the product to potential end users.

Keywords: neural interfaces,graphene,neuro treatment,spinal cord injury,information and,communication technology
An ML Approach to IFIs: Determinants of IMF Lending (MLending)

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: Social Sciences and Humanities
Countries involved: Türkiye
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-12-01
End date: 2022-11-30
Duration (months): 24.0
Total project cost (EUR): 145355.52
EU funding (EUR): 145355.52
Participants: 1
Project status: CLOSED

The International Monetary Fund (IMF) is frequently argued to be an agent of its most powerful shareholders. Challenging the common belief that strategic allies of the US and/or G5 countries always get better deals from the IMF, whereas it is the IMF staff who has the main leverage over the design of conditionality when low-income countries are borrowing from the Fund, this project will develop a novel framework, drawing upon existing literature on the IMF, in order to present a comprehensive model that takes into account all actors having an impact on IMF program design. The following questions will be at the core of this research: What factors influence the terms of an IMF program? And how do those factors play into shaping the design of the programs? Through creating an original framework, the project will aim to provide an indispensable and extensible tool for international political economy researchers, policymakers, governments and IMF staff to model the program design and implementation process with high predictive power of the outcomes. The project will make a major contribution to the literature by creating a machine learning (ML) model for predicting the loan size, number of IMF conditions and waivers during program implementation, which complements traditional statistical models by integrating a larger number of variables and providing high accuracy of prediction. The project will also create a natural language processing (NLP) tool for automated, fast analysis of the IMF’s Executive Board meeting minutes, which is able to capture elements including individual board member sentiments, alliance between representatives of different countries and G5 stance with high accuracy. The research will take on board an eclectic approach, using mixed methods involving ML, NLP, statistical analyses, and process tracing of in-depth case studies (namely Romania and Greece) to account for the variation in the terms of IMF programs.

Keywords: international political economy,international organizations,international financial institutions,process tracing,machine learning,natural language processing,computational social science