Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Innovative Enterprise Vienna 2018 (IE-2018-Vienna)

Framework: Horizon 2020 — Industrial Leadership
Programme: Access to risk finance
Action type: Coordination and support actions
Countries involved: Austria
Call: 10. Innovative Enterprise Week 2018 - Austria (H2020-IBA-ARF-Austria-2018, 2018)
Start date: 2018-08-01
End date: 2019-03-31
Duration (months): 8.0
Total project cost (EUR): 349952.5
EU funding (EUR): 349952.5
Participants: 1
Project status: CLOSED

Objective of the project is a 2 full day international conference (21-22/11/2018), including a restricted Pre-conference Dinner in the evening prior to the conference The conference will focus on financial instruments for highly innovative enterprises. The event is rooted in the Work Programm 2018-2020 of ‚Access to Risk Finance/Horizon 2020‘ and is listed as an official event of the Austrian EU Council Presidency in the second semester of 2018. The conference ‚Innovative Enterprise Vienna 2018‘ will help companies and organisations engaged in research and innovation (R&I) to better understand how to gain access to financial capital - in the form of loans, guarantees, counter-guarantees and hybrid, mezzanine and equity finance - which is necessary for company/entity to fully exploit its innovative capacity and - basically - turn it into market success. The pallet of InnovFin instruments are of central importance for the event. The conference will take place at a very decisive moment of time with respect to the planning process of the forthcoming financial period. In this context, a prospective view on the plans for the ‚European Innovation Council/EIC‘ of Horizon Europe will be a most important element of the conference. Similarly, also prospects on Invest EU (with respect to R&I-relevant activities) will also be dealt with. In addition to a full-2-day event for ca. 500 participants with series of keynotes and consecutive panel sessions, the event will also demonstrate equity finance in practice - by integrating 2 ‚investment pitching‘ formats for highly innovative companies. These pitching formats are foreseen for around 120 persons. Obviously, a most professional, smooth, hospitable, thematically well composed and technically well equipped event with integrative and participative elements for the audience is the main target of this project. This will include all aspects of professional event management, including also evening receptions and media management.

Keywords: conference innovative enterprise 21,22 november 2018,vienna access to finance for research,innovation and smes 2018
Energy Landscapes from Cryo-EM and Simulations (EnLaCES)

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: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-10-01
End date: 2023-09-30
Duration (months): 24.0
Total project cost (EUR): 160932.48
EU funding (EUR): 160932.48
Participants: 1
Project status: SIGNED

Proteins are dynamic entities that undergo many structural transitions and fluctuations, which are essential to their biological functions. We, therefore, need continuous descriptions of protein conformational space in the form of energy landscapes in order to properly understand their mechanisms of action. This is now becoming possible through the use of hybrid methods, which combine computational biophysics with experimental structural biology and overcome the limitations of either approach alone. In this proposal, we present a new hybrid methodology that leverages recent innovations in cryo-electron microscopy image analysis to examine continuous dynamics and free energy landscapes of large, multi-domain proteins, which are not achievable with existing methods. Our novel interdisciplinary pipeline will involve the use of efficient coarse-grained representations of proteins from computational biophysics coupled with sophisticated image processing tools including 3D reconstruction, classification, and dimensionality reduction. The specific objective is to extract reaction coordinates from 3D class averages and use them to generate conformational landscapes onto which the raw 2D images can be mapped. The resulting free energy landscapes will reveal all conformational states with physiological relevance and the preferred transition pathways, which can be analysed further using molecular dynamics simulations. We will apply our pipeline to ionotropic glutamate receptors, which are tetrameric ligand-gated ion channels with large, dynamic, multi-domain architectures that are critical to synaptic transmission and plasticity in the mammalian central nervous system. We expect our results to be of great benefit to the broad structural biology community and to be instrumental in understanding brain physiology and designing treatments for a wide range of diseases.

Keywords: cryo electron microscopy,continuous heterogeneity,molecular dynamics,ionotropic glutamate receptors
Unraveling the Physics of Light at Scale (UNRAVEL)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Switzerland
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2022-09-01
End date: 2027-08-31
Duration (months): 60.0
Total project cost (EUR): 1496955.0
EU funding (EUR): 1496955.0
Participants: 1
Project status: SIGNED

Earth climate research crucially depends on measurements of the atmospheric distribution of CO2, which is largely obtained using satellites. But satellites cannot directly measure CO2—they capture photographs at different wavelengths that must be mathematically processed to obtain this information. Current methods for solving this inverse problem are unaware of many aspects of the images including topography, cloud shape, shadowing, etc. The UN Intergovernmental Panel on Climate Change (IPCC) has identified the resulting errors as the main cause of discrepancies between different climate sensitivity models. This proposal in the area of computer graphics introduces methods for inverting the physics of light at unprecedented scales that will address these inaccuracies. However, the scope of our contribution extends far beyond climate modeling: it will have a revolutionary impact on all scientific disciplines that involve the analysis of images, including biology, computer vision, architecture, and many others. In this project, - we will establish the first framework for inverting light simulations with billions of parameters. To demonstrate its generality, and to realize the impact of this framework, we will specialize it to three areas: - we will develop the first invertible atmospheric optics simulator for earth climate monitoring that accounts for 3D structures, addressing severe inaccuracies of current methods. - we will create an invertible virtual microscope that will open the door to fundamentally new reconstruction techniques in the area of biology. - we will design architectural light simulations that are able to adapt buildings so that they make ideal use of naturally available daylight. To achieve these goals, we must unravel the messy physics of light to either reveal or control the properties of visible and invisible objects. Our approach will solve this impossible-seeming problem at large scales with substantial impact across disciplines.

Keywords: computer graphics,differentiable rendering,inverse rendering,atmospheric optics,microscopy,architecture,automatic differentiation
AI-POWERED GROUND SEGMENT CONTROL FOR FLEXIBLE PAYLOADS (ATRIA)

Framework: Horizon 2020 — Industrial Leadership
Programme: Space
Theme: Enabling advances in space technology
Action type: Research and Innovation actions
Countries involved: Germany,Italy,Germany,Spain,Spain,France
Call: Satellite communication technologies (H2020-SPACE-2020, 2020)
Start date: 2021-04-01
End date: 2024-03-31
Duration (months): 36.0
Total project cost (EUR): 2999490.0
EU funding (EUR): 2999490.0
Participants: 8
Project status: SIGNED

A new generation of completely flexible satellites in terms of mission definition is currently appearing in the space segment as a response to the 5G revolution, resulting in an unprecedented integration of the satellite services with the terrestrial deployments. In this context, the Digital Transparent Processor (DTP) is aimed to constitute the core of these digital payload, providing them with new capabilities unthinkable to achieve with the traditional analogue ones, such as adaptive bandwidth (BW) and power allocation, or flexibility in the connectivity and coverage. As a consequence, the flexibility offered by these kind of satellites leads to the increased complexity in their management. Then, the optimum reconfiguration of these complex payloads to fulfil the users requirements is no longer an achievable task for a payload engineer due to the real-time constraints and the number of possibilities. To solve this, these satellites require new and intelligent tools capable of optimally allocating the satellite resources, while monitoring the interferences in such a dynamic scenario. In this point, Artificial Intelligence/Machine Learning (AI/ML) algorithms appear to substitute the operator decisions and manual operations while configuring the payloads. In atria project, these algorithms will compose an AI/ML module in a Payload optimization Control System (AI-PCS). The algorithms are to be trained with both real data sets of former manual operations and synthetic data. Also, the algorithms will receive information from external services to provide them with inputs regarding meteorology, traffic, availability, etc. in order to achieve the optimum decisions. AI-PCS is to be validated using both a flexible payload emulator and real satellite environments. AI-PCS is aimed to be a generic tool, transparent to the payload, providing the satcom operators with added value and turning it into a cost-effective solution for the future of the ground segment.

Keywords: artificial intelligence,flexible payload control software,satellite integration into 5g networks
A range of economically viable, innovative and proven HydroKinetic turbines that will enable users to exploit the huge potential of clean, predictable energy in the world’s rivers, canals and estuarie (DP Renewables)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Action type: SME instrument
Countries involved: Ireland
Call: Stimulating the innovation potential of SMEs for a low carbon and efficient energy system (H2020-SMEINST-2-2016-2017, 2017)
Start date: 2017-07-01
End date: 2020-03-31
Duration (months): 33.0
Total project cost (EUR): 2927031.25
EU funding (EUR): 1934656.5
Participants: 1
Project status: CLOSED

The DP Renewables project aims to commercialise a range of innovative, hydrokinetic turbines that will offer a reliable solution for generating zero-carbon energy from rivers, estuaries and canals. The range of products to be launched on the market in February 2020 comprises of two different sized turbine devices, 25Kw and 60Kw respectively, which are specifically designed to cater to a niche, ‘low-power’, small-scale energy generation market. DP Renewables stems from the success of ‘HydroKinetic-25’, the SME Instrument Phase 1 project implemented by DesignPro in March-September 2016 that served to prove this innovative idea’s economic viability and define a business plan to bring it to market. Phase 2 will see this strategic and validated business plan implemented and the realisation of a project that will have significant positive impact on societal, economic and environmental issues. The project will cater to those with a suitable deployment site, meeting their need for energy security and independence, reducing reliance on imported fossil fuels and lowering carbon emissions. The project is fully aligned with the growth strategy of the SME and is regarded as a major stepping-stone towards consolidating its international presence while becoming a recognised contributor to the renewable energy spectrum. Despite its large resource potential, hydrokinetic energy is still largely untapped with only 5% exploited to date. Europe, as well as many countries around the world, is rich of small and medium-sized rivers and straits between islands. Existing technologies require very fast flow speeds and large deployment spaces in order to make turbine outputs viable. This cuts off a large majority of the available market from having a feasible solution to use. Our project, DP Renewables, offers this solution, enabling Europe and the world to utilise an abundant, highly accessible resource by harnessing cost-efficient, clean and reliable energy for users.

Keywords: energy,renewable,power,turbine,river,electricity,generation,sustainability,hydro,kinetic,patented,tidal,in stream,stream,estuary,estuarine,low carbon,efficient,green
Digital Single Cell Immunology: Decoding Cellular Interactions for Improved Immunotherapy (ImmunoCode)

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: Netherlands
Call: ERC Starting Grant (ERC-2018-STG, 2018)
Start date: 2018-11-01
End date: 2024-06-30
Duration (months): 68.0
Total project cost (EUR): 1812143.0
EU funding (EUR): 1812143.0
Participants: 1
Project status: SIGNED

Successful immunotherapy against cancer is the result of a multitude of cellular interactions within the immune system. It is highly exciting how vaccination with small numbers of human plasmacytoid dendritic cells (pDCs) can induce anti-tumour immunity in metastatic cancer patients. Remarkably, how pDCs, as an extremely rare subset of cells, can act as Swiss army knives to regulate the tight balance between tolerance and immunity: i.e. secrete massive amounts of type I IFNs, prime T cells and exert cytotoxic effector functions, is still elusive. Do pDCs possess all functions or comprises the population distinct functional subsets all with their specialized roles. I will unravel which pDC is superior in inducing cytotoxic T cells (CTLs) for augmented cancer immunity. Despite advances in single cell technologies, understanding the role of heterogeneity in immune cell populations, remains poorly understood. In ImmunoCode, I will develop a novel and ambitious single cell technology platform, wherein innovative microfluidic approaches and single cell transcriptomics allow 1) functional analysis of single (pairs of) immune cells and 2) design of minimal environments under the omission of external factors that could influence cellular behaviour. This approach will provide me with the unique opportunity to unravel pDC function and plasticity. Although in this ERC proposal I will focus on understanding pDCs heterogeneity, my technology can in fact be exploited to any cell type that shows heterogeneous function. My unique and high-risk technical approach allows for decoding immune cell-cell or cell-pathogen interactions longitudinally and in great detail which will revolutionise the fields of immunology and cellular immunotherapy. Ultimately, ImmunoCode will have a tremendous impact by refining the design of vaccine strategies and the development of differently composed cellular vaccines to battle cancer and infectious and auto-immune diseases.
Identification of nano-mechanical fingerprints as a biomarker for cancer treatment prognosis (CancerFingerPrints)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Cyprus
Call: ERC Proof of Concept Grant (ERC-2018-PoC, 2018)
Start date: 2019-05-01
End date: 2020-10-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

In the fight against cancer, it is well recognized that tumors are highly heterogeneous and they might differ considerably not only between tumors types but also among tumors of the same type or even for the same tumor during progression. As a result, the efficacy of standard cancer chemotherapies varies, and while some patients respond to a particular treatment, other patients do not gain any benefit and in many cases, the condition of the patient deteriorates due to adverse effects. Consequently, crucial in cancer therapy is the prediction of a patient’s response to treatment. Failure of standard therapies has led to the introduction of a new era of personalized, patient-specific treatments, which are based on the identification of biomarkers that characterize the state of a particular tumor. Many solid tumors (e.g., breast cancers and sarcomas) stiffen as they grow in a host’s normal tissue. Stiffening is caused by an increase in the structural components of the tumor. As tumor tissue becomes stiffer, mechanical forces are generated within the tumor, that cause the compression of intratumoral blood vessels, resulting in compromised vessel functionality, which leads to poor drug delivery and therapeutic outcomes. Recently, it has been demonstrated that “stress-alleviation” strategy, which uses anti-fibrotic agents to promote tumor softening, improves uniform delivery of drugs and enhances therapy. Here, we propose the use of state-of-the-art Atomic Force Microscopy-AFM techniques for the development of a NanoMechanical biomarker, which will quantify the mechanical FingerPrints of Cancer. This biomarker will aim to: (i)predict the patient’s response to treatment with chemotherapy and (ii)monitor treatment outcomes, in the case of strategies that target tumor mechanical properties (e.g., stress-alleviation therapy). Furthermore, we propose to develop an AFM-based software product to be used as a commercial tool for the measurement of the NanoMechanical biomarker.

Keywords: atomic force microscopy,tumor mechanics,cancer treatment prediction,biomechanics,cancer pathophysiology
Characterizing Atrial fibrillation by Translating its Causes into Health Modifiers in the Elderly (CATCH ME)

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,Germany,Spain,France,France,Netherlands,United Kingdom,United Kingdom,United Kingdom
Call: Understanding health, ageing and disease: determinants, risk factors and pathways (H2020-PHC-2014-two-stage, 2014)
Start date: 2015-05-01
End date: 2019-04-30
Duration (months): 48.0
Total project cost (EUR): 4944773.0
EU funding (EUR): 4944773.0
Participants: 11
Project status: CLOSED

Atrial fibrillation (AF) is the most common cardiac arrhythmia, with a prevalence of 1.5-2% in European populations. By being a major cause of stroke, dementia, heart failure, and premature death, AF is a major threat to healthy ageing. Despite increasing knowledge on the diverse mechanisms that cause the AF substrate in individual patients, current strategies for prevention and therapy of AF remain largely unguided by mechanistic insights. As a result - with the exception of anticoagulation for the prevention of AF-related stroke – treatment of AF has thus far failed to improve patients’ outcome. The CATCH ME consortium will bridge the present disconnect between our understanding of the molecular and electrophysiological mechanisms of AF and the current unstructured approach to its prevention and treatment. The consortium combines clinical, molecular, ECG engineering, and biostatistical expertise, and has access to large sets of human biological material (atrial tissue and bloods samples) and carefully phenotyped patient populations. Together, we will identify and integrate the main drivers of prevalent and incident AF in patients, and validate new ECG- and blood based markers in well-characterized cohorts. The results of these investigations will provide a quantitative estimate of the prevalence and impact of new and established risk factors for AF in Europe and uncover potential new targets and strategies for the prevention and treatment of this arrhythmia. We will integrate these factors into a new clinical classification of AF that will be externally validated in two large patient cohorts, including response to current treatment strategies, and AF-related complications. In summary, CATCH ME will 1. identify major AF-related modifiers of health in the elderly in Europe, 2. develop clinical tools that have the potential of transforming the management of AF in individual patients, and 3. inform future personalized strategies to prevent and treat AF in Europe.

Keywords: atrial fibrillation,disease mechanism,stratified therapy,personalized medicine,clinical management,stroke,physiology,biological risk factors,risk prediction,model,competing risk,biomarker