Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Continuous real-time monitoring of water toxicity (ToxMate)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: France
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2020-01-01
End date: 2022-06-30
Duration (months): 30.0
Total project cost (EUR): 1763593.75
EU funding (EUR): 1234515.63
Participants: 1
Project status: CLOSED

Urban centres, industries and agriculture produce large volumes of wastewater; in addition, the current population growth, accelerated urbanization and economic development are increasing the quantity and pollution of wastewater globally. Being a by-product of human activities, wastewater contains chemical, biological and physical pollutants, so it must be treated to remove all contaminants before it is released in the environment. Releasing untreated or inadequately treated wastewater is dangerous and has harmful effects on human health, the environment, and economic activities. Water quality after wastewater purification varies over time, even and especially during one single day, but managers do not have the necessary tools to monitor these variations. Currently available methods based on bioassays or physical and chemical parameters require sampling, conservation and transport, and are based on spot-sampling (1-2 times/year). These methods are not able to provide information on temporal variability and have low efficiency, durability, and specificity; they are also slow in providing results (at least 72 hours) and can’t allow real time monitoring. To overcome these limitations, ViewPoint has developed ToxMate: a tool for the automated real-time, on-site and on-line monitoring of wastewater toxicity. It is based on the simultaneous analysis of the locomotor behaviour of 3 different species of aquatic invertebrates and it uses infrared light and powerful and precise cameras to record continuously the activity of the animals. The system is composed of 3 panels, each containing 16 animals, so 48 animals can be analysed at the same time and for up to 30 days. ToxMate is fast: it can provide a result on water toxicity in just one hour, so it allows public authorities and water managers to measure the variation in wastewater and identify abnormal episodes, thus allowing quick interventions to optimize water purification and control treatment plants more efficiently.

Keywords: real time monitoring,water toxicity,automated
A novel genetic assay for risk assessment of cognitive decline in Alzheimer’s Disease (variaTECT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: United Kingdom
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-02-01
End date: 2019-05-31
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Alzheimer’s Disease (AD) is the most prevalent cognitive disorder and progressively leads to complete brain dysfunction and degeneration. The number of people living with Alzheimer’s worldwide is now estimated at 46M, with this figure set to almost double by 2030 and more than triple by 2050 due to population aging. Current methods for early assessment of AD are based on detection of β-amyloid in the brain Positron Emission Tomography (PET) scans, blood plasma tests or in cerebrospinal fluid (CSF) (via lumbar puncture). However, these solutions present some unresolved issues for broad market deployment. Cytox has developed the variaTECT platform to stratify AD risk in individuals by using a fast, accurate, reliable and cost-effective way to generate specific genetic information. The variaTECT comprises a proprietary 130K single nucleotide polymorphism (SNP) variaTECT array and the proprietary SNPfitRTM software to analyse data generated from the array. DNA extracted from a patient’s blood or saliva sample is collected and analyzed on the variaTECT array. The primary genetic data are then processed by the SNPfitR software, which provides a risk score associated with the probability to develop AD. variaTECT has an 85% accuracy, it can save up to €10k person-year for the healthcare systems and it can generate new revenues (up to €10M) for genetic labs. During the feasibility assessment, a go-to-market strategy and a supply chain will be established, as well as further development plan will be drafted. During the second phase of innovation project, Cytox will upgrade the array design to increase the number of SNPs and the SNPfitR software to stratify subjects into different dementia types. Production capacity will be increased up to 100,000 pieces per year. Multiple clinical trials will be then initiated to obtain CE mark as In-Vitro Diagnostic (IVD) device.

Keywords: genetic assay,biomarker diagnostic,polygenic risk score algorithm,cognitive impairment,alzheimer s disease
Interlinked Process, Product and Data Quality framework for Zero-Defects Manufacturing (InterQ)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Technologies for Factories of the Future
Action type: Innovation actions
Countries involved: Germany,Spain,Ireland,Spain,Spain,Italy,Austria,Germany,Germany,Germany,Italy,Hungary,Norway,Norway,Romania,Greece,France,France,France,Luxembourg
Call: Quality control in smart manufacturing (IA) (H2020-NMBP-TR-IND-2020-singlestage, 2020)
Start date: 2020-11-01
End date: 2023-10-31
Duration (months): 36.0
Total project cost (EUR): 10888317.84
EU funding (EUR): 8988750.0
Participants: 26
Project status: SIGNED

InterQ project proposes a new generation of digital solutions based on intelligent systems, hybrid digital twins and AI-driven optimization tools to assure the quality in smart factories in a holistic manner, including process, product and data (PPD quality). The broad vision of InterQ project will allow controlling the quality of a smart manufacturing environment in an end-to-end approach by means of a PPD quality hallmark stored in a distributed ledger. The concepts of InterQ will be applied in three high-added value industrial applications. The main objective of InterQ project is to measure, predict and control the quality of the manufactured products, manufacturing processes and gathered data to assure Zero-Defect-Manufacturing by means of AI-driven tools powered with meaningful and reliable data. The project develops five modules: 1) Thanks to the InterQ PPD quality hallmark, the quality of the process, product and data are interlinked, integrated and time stamped. A hallmark will be created after each stage, and the quality will be traced across the supply chain. A trusted framework will be implemented using distributed ledger (InterQ-TrustedFramework module) to exchange quality information. 2) The InterQ-Process module of the project will obtain more meaningful process data for quality optimization. This data will be obtained using new sensors close to the tool and by AI-driven virtual sensors. 3) The project presents new solutions (InterQ-Product module) to predict the final quality of the processes using digital twins fed by experimental data and new digital sensors to measure the product quality. 4) The reliability of data will be checked in two layers: in real time and based on historical and statistical analysis of the data streams (InterQ-Data module). 5) Finally, InterQ-ZeroDefect module will use the reliable information about the process and product quality to improve the production for Zero-Defect-Manufacturing by means of AI-driven applications.

Keywords: data reliability,quality hallmark,digital twin,zero defect manufacturing,supply chain traceability,process optimization,data quality,artificial intelligence,distributed ledger and virtual sensor
Random Geometry (RANDGEOM)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Mathematics
Panel description: All areas of mathematics, pure and applied, plus mathematical foundations of computer science, mathematical physics and statistics
Countries involved: Israel
Call: ERC Starting Grant (ERC-2015-STG, 2015)
Start date: 2016-01-01
End date: 2021-12-31
Duration (months): 72.0
Total project cost (EUR): 1286150.0
EU funding (EUR): 1286150.0
Participants: 1
Project status: CLOSED

The objective of this proposal is an investigation of the geometric structure of random spaces that arise in critical models of statistical physics. The proposal is motivated by inspiring yet non-rigorous predictions from the physics community and the models studied are some of the most popular models in contemporary probability theory such as percolation, random planar maps and random walks. One set of problems are on the topic of random planar maps and quantum gravity, a thriving field on the intersection of probability, statistical physics, combinatorics and complex analysis. Our goal is to develop a rigorous theory of these maps viewed as surfaces (rather than metric spaces) via their circle packing. The circle packing structure was recently used by the PI and Gurel-Gurevich to show that these maps are a.s. recurrent, resolving a major conjecture in this area. Among other consequences, this research will hopefully lead to progress on the most important open problem in this field: a rigorous proof of the mysterious KPZ correspondence, a conjectural formula from the physics literature allowing to compute dimensions of certain random sets in the usual square lattice from the corresponding dimension in the random geometry. Such a program will hopefully lead to the solution of the most central problems in two-dimensional statistical physics, such as finding the typical displacement of the self-avoiding walk, proving conformal invariance for percolation on the square lattice and many others. Another set of problems is investigating aspects of universality in critical percolation in various high-dimensional graphs. These graphs include lattices in dimension above 6, Cayley graphs of finitely generated non-amenable groups and also finite graphs such as the complete graph, the Hamming hypercube and expanders. It is believed that critical percolation on these graphs is universal in the sense that the resulting percolated clusters exhibit the same mean-field geometry.

Keywords: random planar maps,percolation,random walk,statistical physics
Incomaker - intelligent marketing management automation for SME (INCMAK)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Czechia
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2016)
Start date: 2016-07-01
End date: 2016-12-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

NetCampaigner was established as a Czech SME company by the group of experts with about 50 years of combined experience in marketing, small-business, and statistical data analysis. It develops Incomaker, an innovative marketing automation tool for SMEs that uses our artificial intelligence technology to suggest, plan and perform marketing management activities. Just 34% of SMEs use CRM, 14% use acquisition marketing, and 56% don’t measure their marketing performance. The quality of marketing processes and abilities among SMEs is typically far behind large corporations. The problem is that state-of-the-art marketing software is based on principles reflecting the needs of corporations. They usually have skilled marketing experts to plan marketing actions and the idea behind their information systems is to alleviate the workload and automate tasks. SMEs, on the other hand, are often lacking the advanced marketing expertise and hence conventional marketing information systems solve different problems and often can hardly help SMEs as they expect. Our Incomaker, a unique intelligent marketing system solves the problem the following way. The marketing must be information driven. Incomaker collects data from various sources, both internal and external and performs advanced analysis of it using marketing best practices and former knowledge gained by autolearning. The results are suggestions for marketing decision making and actions that could be directly confirmed and executed. As Facebook changed the way how people e.g. quickly publish their photos on the internet, Incomaker has the ambition to establish a new category of marketing software and to modify the way how SMEs perform their marketing. Incomaker can replace most of the work of marketing manager In SME. This way it could save considerable costs and bring nearly the same maturity of marketing management as if a marketing professional would perform it. It will help SMEs grow and create new job positions.

Keywords: marketing,automation,process,artificial intelligence,big data
Neural circuitry and health consequences of cognitive bias (COGBIAS)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Global Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Portugal,Japan
Call: Individual Fellowships (H2020-MSCA-IF-2017, 2017)
Start date: 2019-02-01
End date: 2022-01-31
Duration (months): 36.0
Total project cost (EUR): 270862.2
EU funding (EUR): 270862.2
Participants: 2
Project status: CLOSED

Stress has long been a major concern among researchers interested in health and welfare. Most of their work has considered stress from either a biological or an environmental perspective, focusing on the activation of the physiological systems involved in the stress process or the role of stressful life events in specific diseases. While interesting, if we are to fully understand the effects of stress on health, we must also take into account a psychological perspective that considers an individual’s perception of stress. Indeed, a deep understanding of the neural circuitry underlying psychological stress and its physiological consequences is crucial to meaningfully explain inter-individual variations in vulneraibility to stress. In this way, my ongoing research has revealed some preliminary results which indicate ‒ for the first time ‒ that cognitive bias towards pessimistic judgments (i.e. some individuals consistently evaluate ambiguous stimuli as negative) may predict an individual’s susceptibility to the detrimental effects of chronic stress. These groundbreaking results shed light on a completely unexplored and highly promising avenue of research, based on the potential impact of evaluation biases regarding stress on an individual’s vulnerability to stress-associated diseases. In this framework, COGBIAS firstly aims to characterise the specific neural circuits underlying cognitive bias by which stress is perceived, processed, and transduced into a neuroendocrine response, using zebrafish (Danio rerio) as a model. Secondly, COGBIAS aims to unravel the role of subjective stress on resilience to stress-associated diseases. Hence, the multidisciplinary and unique perspective of this project, combining behavioural, neural, genetic, and physiological sciences, has the potential to reinforce the already European competitiveness in the area of stress-related health and management.

Keywords: animal behaviour,animal welfare,comparative neurobiology
The Energetics and Habitat of Metabolic Origin (EcolMetabOrigin)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: Germany
Call: ERC ADVANCED GRANT (ERC-2020-ADG, 2020)
Start date: 2021-11-01
End date: 2026-10-31
Duration (months): 60.0
Total project cost (EUR): 2490000.0
EU funding (EUR): 2490000.0
Participants: 1
Project status: SIGNED

Life is a chemical reaction. Over 1000 individual reactions are driven in the direction of cell growth by the coupling of biosyntheses to environmentally available exergonic reactions that are harnessed by a handful of enzymes in energy metabolism. How, where, and from what the chemical reaction of life arose, and how the primordial diversification of metabolism proceeded are the topics of this proposal. Evidence for the process of metabolic origin and traces from the very early course of microbial evolution should be preserved in the chemical reactions of metabolism itself. This concept, traditionally germane to thoughts on biochemical evolution, is (almost) self evident: Enzymes do not perform feats of magic, they just accelerate reactions that tend to occur anyway. Biochemical reactions can therefore themselves harbor relics of, or be holdovers from, metabolic origin. Yet not all reactions are equally old, metabolism has evolved — but how? In this proposal, the tools of comparative physiology, thermodynamics, and comparative genomics, will be applied to investigate the process of early metabolic evolution. Three kinds of data stand central to the work: i) thermodynamic properties of reactions that comprise modern metabolic networks, ii) information contained in the ability of H2 in the presence of Ni3Fe and magnetite catalysts to substitute for ferredoxin and enzymes in biochemical reactions, and iii) information about the evolutionary origin and phylogenetic spread of heme and cytochromes as well as the ecophysiological context of cytochrome origin. The proposed work will deliver groundbreaking insights into the chemical environment at the site of biochemical origins, inform about the pre-enzymatic nature of catalysts and reductants at the origin of metabolism, and offer insights into the course of bioenergetic evolution before and after heme as well as the ancestral function of cytochromes in accessing extracellular electron acceptors.

Keywords: anaerobes,autotrophes,comparative physiology,hydrogen,serpentinization,hydrothermal vents,heme,thermodynamics,metabolic networks,verticality
Epistemic Utility for Imprecise Probability (EPIMP)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: The Human Mind and Its Complexity
Panel description: Cognitive science, psychology, linguistics, theoretical philosophy
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-02-01
End date: 2025-01-31
Duration (months): 60.0
Total project cost (EUR): 1490433.0
EU funding (EUR): 1490433.0
Participants: 1
Project status: SIGNED

Scientific inference is principally a matter of using observable data to estimate the parameters of models of interest, e.g., models of the climate system. In traditional Bayesian statistics, uncertainty about model parameters is quantified using a single, precise probability distribution. This approach has proved extremely successful in applications where data is plentiful and model parameters are few. But many models are high dimensional (thousands of parameters), and relevant data is comparatively sparse. In such contexts, imprecise probabilities are required to adequately capture uncertainty. The mathematical foundations of imprecise probability theory (IP) have been in place for 25 years, and IP has proved successful in practice. But IP methods lack rigorous accuracy-centered, philosophical justifications. Traditional Bayesian methods can be justified using epistemic scoring rules, which measure the accuracy of the estimates that they produce. But there has been little work extending these justifications to the IP framework. Thus, the key aim of the proposed research is to develop scoring rules for IP distributions (IP scoring rules), and use them to justify and extend IP methods. There are four main objectives: (1) characterise reasonable IP scoring rules; (2) derive scoring-rule based justifications for existing IP methods; (3) use IP scoring rules to discover novel methods for selecting and updating IP distributions; (4) use IP scoring rules to engineer new deference and aggregation principles for IP distributions. Objectives 1 and 2 will deliver firm foundations for existing IP methods. Objectives 3 and 4 will extend the range of IP methods available for both individual and group inquiry. The results of this project will not only make IP a central focus in contemporary epistemology, and shape ongoing philosophical debates about IP’s role in inference and decision-making, but also furnish new tools aimed at influencing how IP methods are used in practice.

Keywords: imprecise probability,epistemic utility theory,scoring rules,scientific inference
Rearm cultivated tomato with natural and durable resistance mechanisms from wild tomato species (DURETO)

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: Netherlands
Call: Marie Skłodowska-Curie Individual Fellowships (IF-EF) (H2020-MSCA-IF-2014, 2014)
Start date: 2015-05-01
End date: 2017-04-30
Duration (months): 24.0
Total project cost (EUR): 165598.8
EU funding (EUR): 165598.8
Participants: 1
Project status: CLOSED

Insects are gaining resistance to commercially available pesticides and effective insecticides (e.g. neonicotinoids) are currently being banned. Consequently, there is a real threat that the EU vegetable production will be affected. Wild tomato species have the ability to defend themselves by producing natural defence compounds that have a toxic or repellent effect on insects. These compounds are produced and stored in glandular hairs (trichomes) on the plant stem and leaf surface. Extensive breeding in protected environments led to the loss of these defence compounds in cultivated tomatoes. It was previously shown that the introduction of the terpene 7-epizingiberene biosynthetic pathway from a wild tomato in trichomes of cultivated tomato results in an enhanced resistance to insects. However, the regulatory factors that govern the production of these defence compounds seem also essential for successful incorporation of ‘wild resistance’ into breeding material. Here, I aim to discover metabolic defence mechanisms present in the trichomes of wild tomato species that can be re-introduced into cultivated tomato with a focus on post-transcriptional regulation of biosynthetic pathways. I will evaluate insect resistance in a collection of wild and cultivated tomato accessions and associate phenotypic and transcriptional data via a Systems Biology approach. I will also sequence small RNAs and compare them quantitatively with messenger RNAs to identify post-transcriptional regulations. Next, I will follow a comparative genomic approach by mapping the selected transcripts to their corresponding tomato genomes to associate polymorphisms and resistance phenotypes. These results will be directly translated into molecular markers that the industry can implement in breeding programmes. This proposal will help me become an independent researcher, combining my background in plant biology with knowledge on bioinformatics, biostatistics and state-of-the-art technology.

Keywords: tomato,insect resistance,domestication syndrome,genetical diversity,trichomes,terpenoids,transcriptional network,systems biology,breeding,molecular marker