Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
XnFinity Artificial Intelligence for Retail (X-AIR)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Coordination and support actions
Countries involved: Portugal
Call: European SME innovation Associate - pilot (H2020-INNOSUP-2020-02, 2020)
Start date: 2020-09-01
End date: 2021-12-31
Duration (months): 16.0
Total project cost (EUR): 191812.5
EU funding (EUR): 134268.75
Participants: 1
Project status: CLOSED

Retail sales amounts to 41 billion euros per day all over the globe; e-commerce revenue in Europe is expected to grow from 292.2 billion U.S. dollars in 2017 to 499.5 billion U.S. dollars in 2024. To help our retail clients tackle the problems mentioned and also seize these opportunities, we are set to democratize Artificial Intelligence innovation in retail, by developing a technology capable of handling together small data bundles and produce valuable high quality customer knowledge, spending patterns, and an overall array of information potentially predictive and thus strategic. Our innovation idea, X-AIR, is to explore the feasibility of this network’s potential to be a source of knowledge, by leveraging PaperVault’s technology with AI & Machine Learning (ML) tools and expertise, and to become a vehicle for an affordable AI integration in retail stores, offering them new ways to improve the customer experience and to optimize operational efficiency and productivity. In short, X-AIR goal is to expand our current portfolio, gain market share but also to reach new markets, offering solutions not yet available. The IA will report to the CEO and lead the research into the potential of our current technology to help retailers overcome access barriers to customer knowledge.

Keywords: artificial intelligence,retail,paperless,big data,analytics,digitazation
Assay for cancer diagnostics by quantification of 5hmC (OR-HMC)

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: Israel
Call: ERC-Proof of Concept (ERC-2017-PoC, 2017)
Start date: 2017-08-01
End date: 2019-01-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Assay for cancer diagnostics by quantification of 5hmC 5-hydroxymethylcytosine (5hmC) is a modified form of the DNA base cytosine and is an important epigenetic marker linked to regulation of gene expression in development and tumorigenesis. The loss of 5hmC is observed across a wide spectrum of malignant tumours. The goal of the proposed project is to utilize a novel chemo-enzymatic labelling scheme developed within the framework of my ERC project in order to develop a high-throughput assay capable of quantifying 5hmC levels for cancer diagnostics. We have developed a spectroscopic method for global quantification of 5hmC in genomic DNA, which can be performed in multi-well plates for high throughput analysis, or on individual DNA molecules for ultimate sensitivity. We aim to combine these two approaches and further develop a simple and rapid multi-well slide assay which measures 5hmC levels in DNA, and combines both high throughput and high sensitivity. This slide will be compatible with a standard microarray scanner, lowering the development barriers for commercialisation of specific diagnostic applications. In parallel, we aim to establish the relationship between 5hmC levels in colorectal cancer and the state of disease. Preliminary results show significant decrease of 5hmC in colorectal cancer samples relative to that of healthy colon. This assay will potentially offer earlier diagnosis of cancer as well as means for easy monitoring of disease and response to treatment. The project aims to establish preliminary analysis of colorectal cancer samples but the general approach may be directly extended to other types of malignancies.

Keywords: 5 hydroxymethylcytosine,colorectal cancer,diagnostics,epigenetics
Embedded Neuromorphic Sensory Processor (NeuroPsense)

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: Switzerland
Call: ERC Proof of Concept Grant (ERC-2015-PoC, 2015)
Start date: 2016-06-01
End date: 2017-11-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 32512.5
Participants: 2
Project status: CLOSED

Neuromorphic computing has demonstrated high potential for creating computing systems with order-of-magnitude improvements in energy efficiency and robustness to noisy or unreliable sensory signals, such as those inherent in vision. However, a significant roadblock to realizing the full potential of this emerging brain-inspired technology is the current practical need to use inefficient and slow (high latency) legacy von Neumann architectures to convert the input data that needs to be processed, and supply it to the neuromorphic system for further processing. A promising solution to this problem is the recent availability of state-of-the-art neuromorphic sensors, which produce asynchronous event-based output in a form for neuromorphic processing. In parallel, we have developed state-of-the-art neuromorphic processors in the ERC NeuroP project, opening the path to creating fully neuromorphic combined sensing and processing systems. Here we will demonstrate the potential of this technology by building a proof of concept Neuromorphic Sensory Processor (NSP), which will directly interface the neuromorphic Dynamic Vision Sensor with one of the neuromorphic processor devices developed in the ERC NeuroP project. This will represent the first ever general-purpose, end-to-end, fully neuromorphic vision sensing and processing system available for general usage. In this project we will build a technology demonstrator and a detailed commercial business case for this technology, and demonstrate both its technological and commercial advantages. Possible applications for the technology include ultra-high performance and ultra-low power visual processing in ambient surveillance, driver assistance, mobile/wearable devices and robotics.

Keywords: neuromorphic,dynamic vision sensor,non von neumann,beyond moore,ultra low power,deep networks,pattern recognition
Artificial Molecular Machines (ArtMoMa)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Innovative Training Networks (ITN)-European Training Networks
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Germany,Italy,France,France,Netherlands,United Kingdom,United Kingdom
Call: Innovative Training Networks (H2020-MSCA-ITN-2019, 2019)
Start date: 2020-03-01
End date: 2024-02-29
Duration (months): 48.0
Total project cost (EUR): 4146516.36
EU funding (EUR): 4146516.36
Participants: 8
Project status: SIGNED

Artificial molecular machines have the potential to revolutionise medical treatment, material design, and energy conversion for the benefit of the European and global community. Key fundamental aspects have been studied and the findings were awarded with the 2016 Nobel Prize for Chemistry. Now it is time to guide the research further towards game-changing implementations that utilise artificial movement of molecules and orchestrate them in large systems. Therefore, we propose the ITN project ArtMoMa, which aims a) to push the current scientific boundaries further and to explore entirely new directions of fundamental research towards technologically relevant implementations; and b) to educate and mentor 15 curious and highly capable ESRs to form a critical mass of fully skilled young professionals acting as multipliers to develop technologies across Europe. The network is built on synergies and complementarities between leading scientists (with for instance the involvement of 4 Nobel Prize Laureates), world-class institutions, different disciplines, and the incorporation of several industries as drivers – ranging from start-ups to SMEs to global players – from all over Europe. In the medium- to long-term, we have the joint vision to create new and sustainable education structures with strong involvement from key stakeholders and including industry. This will build a continuous stream of leading European scientists who will create further knowledge and innovations in the future, ranging from processes to products to services and resulting in economic growth and leadership in this field.

Keywords: molecular motors,nanomachines
Reliable Predictive Control Exploiting Operational Data with Real-time Applications (ReConDa)

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: Slovakia
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-01-01
End date: 2022-12-31
Duration (months): 24.0
Total project cost (EUR): 155364.48
EU funding (EUR): 155364.48
Participants: 1
Project status: CLOSED

Model predictive control (MPC) is widely used in process industries to control constrained systems with multiple input and outputs. Traditionally, the MPC is used in a two layer architecture where the upper layer gives the economic optimal operating point and the MPC is used in the lower layer tracks the optimal operating point. Recent studies shows that a significant improvement in the economic performance of the plant can be obtained if both the layers are combined together. One of the pressing issues preventing the process industries from adopting the aforementioned control scheme is the presence of plant-model mismatch. The work on this project uses ideas form the linear control theory to handle the structural plant-model mismatch in a robust NMPC framework, efficiently. We develop a model-error model (MEM) which uses plant measurements to improve the knowledge of the plant. We focus on developing a systematic way of choosing the MEM structure based on the data collected from an industrial production plant and use them for monitoring and control purposes. We develop an algorithm which works in parallel with the commercially available advanced process control solutions and makes them robust to plant model mismatch. Our project builds a computationally tractable scheme for model-based NMPC robust against the plant-model mismatch. As a result, a safe, reliable and resource-efficient operation is established. The theoretical developments of the project are implemented into a software package and released as an open-source project such that the collaboration with academia and industrial stakeholders is fostered. A demonstration on an industrial production plant and a laboratory pilot plant is also planned to showcase the benefits of the developed techniques in the real-world environment. A sound dissemination plan of the project ensures that the project reaches its target audience.

Keywords: predictive control,robust control,optimal control,chemical process control,data based learning
The Research Infrastructures Consortium of NCPs for H2020 (RICH-2)

Framework: Horizon 2020 — Excellent Science
Programme: Research Infrastructures
Theme: Research infrastructures
Action type: Coordination and support actions
Countries involved: Austria,Iceland,Germany,Spain,Italy,Switzerland,Greece,Poland,Latvia,France,Czechia
Call: Fostering transnational cooperation between National Contact Points (NCP) in the area of Research Infrastructures: follow-up project (H2020-IBA-INFRA-NCP-2018, 2018)
Start date: 2019-05-01
End date: 2020-11-30
Duration (months): 19.0
Total project cost (EUR): 349565.63
EU funding (EUR): 349565.63
Participants: 12
Project status: CLOSED

The overall objective of RICH-2 is to strengthen the capacities of and cooperation among NCPs in the area of Research Infrastructures (including e-infrastructures) and to provide high quality support and services to programme applicants and the Research Infrastructure (RI) community at large with the view to increase the quality of RI proposals in the area. The RICH-2 overall approach starts from the main idea that the NCP role requires both good knowledge about Horizon 2020 and scientific priorities as well as skills and competences to convey a message in a multicultural and multi-disciplinary environment. RICH-2 is in continuity with the RICH project, building on its experience and achievements. RICH-2 continues giving full and sound support to help RIs NCPs being reliable and concrete sources of knowledge. All activities are tailored according to the nature of the area, and the priorities of the RI NCPs through various mechanisms (seminars and conferences, specific and horizontal trainings, exchange scheme). Special attention is given to further enhance the competence of NCPs, including helping new/less experienced NCPs and NCPs in those countries with low levels participation in the RI programme to rapidly acquire the know-how accumulated already in other countries. The promotion of trans-national and virtual access (TA/VA), the synergies within the RIs network and with other NCPs networks, and understanding RIs relevant policies and international cooperation oriented measures for research infrastructures remain the core activities, as well as to spread awareness on the importance of the RI opportunities in the RI Programme and beyond. Specific services (Joint Proposal Check Service, Webinars on TA/VA open calls, evetns) for RI applicants are scheduled in order to contribute improving the quality of RI proposals.

Keywords: ncp synergies,professional support services,high quality services,research infrastructures national contacts points network,proposal check services,research infrastructure symposium
Optical imaging platform to unravel metabolic reprogramming of cancer: a path for improved treatments (METABOLIGHT)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Synthetic Chemistry and Materials
Panel description: New materials and new synthetic approaches, structure-properties relations, solid state chemistry, molecular architecture, organic chemistry
Countries involved: Switzerland
Call: ERC Consolidator Grant (ERC-2019-COG, 2019)
Start date: 2020-06-01
End date: 2025-05-31
Duration (months): 60.0
Total project cost (EUR): 1997375.0
EU funding (EUR): 1997375.0
Participants: 2
Project status: SIGNED

Recent investigations revealed that cancer tissue possesses several important metabolic features, such as differential utilization of many essential metabolites. This phenomenon is now referred to as "metabolic reprogramming" and is known to be required for malignant transformation, tumor development, invasion and metastasis. Its complex and dynamic nature has been recognized as one of the major challenges for effective cancer treatment. Therefore, a better understanding of metabolic dependencies in specific tumor types can provide a path for improved cancer treatments. However, no efficient methodologies currently exist that allow noninvasive imaging and quantification of the uptake of essential metabolites in animal models of disease. Current strategies rely on either nuclear imaging techniques such as PET/SPECT/MRI or endpoint ex vivo quantification of metabolites (ex. MS). All of these methods have significant limitations, resulting in a lack of understanding of tumor metabolism and, consequently, poor predictability and efficacy of cancer therapies. To address the unmet need for nutrient uptake imaging tools, we propose to develop a novel platform based on a combination of versatile “click” chemistry reactions with noninvasive, ultrasensitive bioluminescent imaging techniques. The applications of the novel platform will focus on tumor uptake measurements of glucose, fatty acids, amino acids, and nucleosides previously reported to play important roles in cancer metabolism. We will then use this platform to investigate the metabolic reprogramming of different liver cancers, which may lead to the generation of novel, effective treatments; therefore, this novel platform has high clinical applicability. Due to its versatile nature, application of the platform can be expended to studies of many other important human pathologies in which changes in metabolism play a key role, such as diabetes, neurodegenerative diseases, nonalcoholic steatohepatitis, and many others

Keywords: optical imaging,cancer metabolic reprogramming,metabolite uptake
Quantum characterization and control of single molecules (QCOSMO)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Fundamental constituents of matter
Panel description: Particle, nuclear, plasma, atomic, molecular, gas, and optical physics
Countries involved: Austria
Call: ERC STARTING GRANTS (ERC-2020-STG, 2020)
Start date: 2021-02-01
End date: 2026-01-31
Duration (months): 60.0
Total project cost (EUR): 1499240.0
EU funding (EUR): 1499240.0
Participants: 1
Project status: SIGNED

Reaching a fundamental understanding of complex quantum systems and fully harnessing their computational power for information processing is one of today’s greatest scientific challenges. The quest to build a quantum information processor has triggered unprecedented efforts to control and characterize dynamics in quantum systems. Here, trapped ion systems are one of the most promising architectures to realize large-scale quantum information processors. In this project I aim to explore the physics and harness the computational potential of a novel trapped ion system with more complex individual constituents: polyatomic molecules. The proposed research tackles the long standing challenge of preparing, controlling and characterizing single polyatomic molecules at the quantum level. The path towards these ambitious goals is centered around two high-level objectives: First, I will develop novel techniques to characterize quantum dynamics of polyatomic systems. In particular, I will quantify quantum coherence in ultrafast intra-molecular processes. This research will open a new window into intra-molecular processes with applications in quantum chemistry as well as biology. Second, I will develop and implement quantum control techniques for polyatomic molecules by coupling them to an atomic quantum information processor. Here, I will demonstrate the building blocks for a new scalable hybrid atom-molecule quantum information processor with ultrafast gate operations. I am convinced that these new control techniques will lay the groundwork for research beyond the immediate project goals such as state-selective chemistry, precision measurements of fundamental constants, as well as scalable and ultrafast quantum computing. My strong interdisciplinary background in experiment design and characterization of quantum systems, and my track record in experimental quantum computation, put me in a unique position to reach the ambitious goals.
Tackling informal employment in Asia: building post-COV19 solutions to precariousness through case-study based evidence on Bhutan, Laos, Maldives, Myanmar, Philippines, Thailand and Vietnam (LABOUR)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Research and innovation staff exchange
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Ireland,Estonia,Moldova, Republic of,Türkiye,Belgium,Sweden,Thailand,Myanmar,Latvia,Philippines,Maldives,Cambodia,Portugal,Lao People's Democratic Republic,Bhutan,Viet Nam
Call: Research and Innovation Staff Exchange (H2020-MSCA-RISE-2020, 2020)
Start date: 2022-01-01
End date: 2025-12-31
Duration (months): 48.0
Total project cost (EUR): 1545600.0
EU funding (EUR): 1545600.0
Participants: 16
Project status: SIGNED

According to the last WESO report, there are over 1.4bn workers in vulnerable jobs worldwide, with numbers expected to rise in 2020 due to COVID-19. Several attempts have been made at both domestic and international levels to address these concerns. This includes efforts through the Sustainable Development Goals process, which includes a specific statistical indicator to measure informal employment (8.3.1), the formulation of SDG8 (decent work) and SDG9 (sustainable industrialization). Across countries and world regions, the degree to which SDGs have been used to address youth issues and inform national policies varies significantly. Indeed, in spite of the fact that the great majority of states have formally committed to addressing the SDGs, including those related to insecure employment, there is little evidence to indicate that developing regions currently have the capacity to systematically study the problems if informal employment and vulnerability in ways that facilitate the development and implementation of concrete viable solutions. This is due, in our view, to two major challenges. First, although a number of approaches that have been used inside the EU, there has been little, if any, attempt to adapt the existing framework elsewhere. Second, no systematic review of anti-precariousness policy has been attempted beyond the EU region. LABOUR is a research and training programme designed to address the above-mentioned shortfalls of research and development approaches with particular attention to a region where this is particularly worrying concern. Informal employment in Asia is estimated to account for 68.2% of the active population. By gathering a team of 14 participants that includes academic and non-academic partners working on labour insecurity, we aim not only at producing specialists on the topic and on the region but also at proposing concrete mitigation measures that can be taken into account by decision-makers and development organisations.

Keywords: precariousness,asia,southeast asia,informal labour,employment,informality,sdgs