Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Theseus (Theseus)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Action type: SME instrument
Countries involved: Italy
Call: Critical infrastructure protection topic 7: SME instrument topic: “Protection of Urban soft targets and urban critical infrastructures” (H2020-SMEINST-1-2014, 2014)
Start date: 2015-05-04
End date: 2015-09-03
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Theseus is designed to bring commercial aviation-grade reliability, engineering standards and extreme operation safety into an unmanned air vehicle platform. The area where UAV utility is greater is the one of the one of scarcely accessible infrastructure needing accurate monitoring such as high voltage electro ducts or waste repositories in urban environment. Medium size UAV with Hybrid (endothermic and electrical) motors and VTOL (Vertical Take-Off and Lamding), with long autonomy (> 8 hours), could discharge the task.

Keywords: environment monitoring
Medical Device for automatic preparation of high quality foam for sclerotherapy of varicose veins (VARIXIO)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-12-01
End date: 2020-03-31
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Approximately 25% of adults have varicose veins, with prevalence increasing to over 80% if spider veins are also considered. The rising geriatric population is further accelerating these figures, as one in two people over the age of 50 are affected by varicose veins. In recent years, due to the possibility of infection and other adverse effects during invasive surgeries, traditional surgical treatment (surgical ligation and stripping) has given way to minimally invasive procedures, which also reduce hospital stays and costs. Consequently, a growing number of doctors are adopting foam sclerotherapy, endovenous laser treatment, and radiofrequency ablation over conventional surgical practices. Within these new treatment approaches, foam sclerotherapy is the preferred approach given its favourable efficacy and safety profile coupled with simplicity and relatively low cost. Foam sclerotherapy involves transforming a chemical sclerosing agent into foam and injecting it into the affected vein. The sclerosant foam irritates the lining of the blood vessel, causing it to collapse and stick together. Current manual foam preparation method broadly utilized by doctors (Tessari’s method) presents substantial limitations in terms of quality, consistency, versatility, and safety. VARIXIO Sclerotherapy Microfoam System being developed by VB Devices addresses these limitations by automating, standardizing, and greatly simplifying foam preparation. VARIXIO adds versatility and safety to this obsolote treatment method. Having secured patent protection for the device and validated the concept at the prototype level, the company is seeking funding to pursue industrial, regulatory, and commercial feasibility of the VARIXIO device.

Keywords: varicose veins,sclerotherapy,foam preparation,medical device,minimal invasive procedure
Oko's mobile-centric micro insurance protecting small farmers in developing countries from climate risks (InsurFarm)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Israel
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-02-01
End date: 2019-07-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Agriculture is a source of income for 2 billion people globally who grow the food we desperately need – 60% more food will be needed by 2050. Of these, smallholder farmers provide 80% of the food in developing countries, and their sustainability is critical. These farmers are at ever increasing risk of losing their harvest due to adverse weather. Yet, due to this risk, most farmers are deprived from basic financial tools to insure their farms and have no access to loans needed to invest or adopt new technologies. They are locked in poverty. Crop insurance is a solution that effectively secures farming income, but it is not accessible to them, as most are un-banked and illiterate. OKO’s InsurFarm solution offers these farmers with an accessible, affordable and fully automated insurance solution. OKO leverages the ubiquity of mobile phones and mobile payment, and the availability of satellite and weather data to create a new kind of insurance product. Using weather prediction and automated contracts, InsurFarm’s unique insurance automatically compensates farmers located in areas affected by adverse weather. Farmers subscribe to this insurance via SMS and pay using any kind of mobile phone, no bank needed. The innovations brought by OKO are highly valuable for insurance companies as OKO creates a new market for them, estimated to be worth € 7.5 billion globally. It also represents a unique opportunity for OKO’s mobile operator partners to offer a new “mobile financial service” to rural users. After successful pilots in Mali, OKO seeks funding to conduct a feasibility study for a pan-African followed by a global commercial launch. During this project, it will conduct market and economic studies, engage with insurance companies and mobile operators, expose InsurFarm to farmers, validate its models and define an adaptation plan to allow global operations. This will lead to a plan to achieve strong growth and fast access to markets.

Keywords: insurance,micro insurance,micro finance,crop insurance,index insurance,mobile money,mobile financial services,big data,machine learning,complex algorithms,yield prediction,impact venture
Memory Enhancing and Learning System (MEMBOOST)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2019-03-01
End date: 2019-08-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Advances in neuroscience have returned the focus on learning, placing the relationship between sleep and consolidation of memory at the centre of academic debate. There are two types of sleep: rapid eye movements and slow wave sleep (SWS). Although both types of sleep have been related to memory consolidation, accumulated evidence points more to the relationship between SWS and memory (L. Marshall, et al., "Boosting slow oscillations during sleep potentiates memory", Nature, vol 444, No. 7119, pp. 610-613, Nov. 2006). In addition, it has recently been shown that the SWS promotes the formation of new synapses after learning (G. Yang, C. S. W. Lai, J. Cichon, L. Ma, W. Li, and W. B. Gan, "Sleep promotion branchspecific formation of dendritic spines after learning", Science, vol.344, no. 6188, pp. 1173-1178, 2014). The general objective of MemBoost is the modulation of sleep for the significant improvement of memory and learning process. The Hardware is a low cost wearable device, innocuous and very easy to use, which consists of a module for recording and processing the electrical signal (EEG) in real time that, by means of a software in a mobile device, is able to distinguish between different states of wakefulness and sleep and produce a non-invasive (audible) stimulus to be delivered to the user and thus produce sleep modulation. Sleep modulation is achieved by synchronized stimulation in phase with the brain's electrical activity. In this sense, modulation is understood as the process of modifying one of the qualities of sleep, in this specific case the duration and quality of slow wave sleep, SWS, are modified. Unlike other applications available on the market, MemBoost is based on solid and recent scientific and academic research that demonstrates improvements in learning up to 22% with the use of technology in a single night, it continued use could reduce the symptoms of memory loss associated with age or neurodegenerative diseases such as Alzheimer´s.

Keywords: memory,learning,enhancement
An INtegrated next generation PREParedness programme for improving effective inter-organisational response capacity in complex environments of disasters and causes of crises (IN-PREP)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure societies - protecting freedom and security of Europe and its citizens
Theme: Increase Europe's resilience to crises and disasters
Action type: Innovation actions
Countries involved: Germany,Ireland,Italy,Germany,Germany,Ireland,Greece,Greece,Greece,France,France,France,Netherlands,Netherlands,United Kingdom,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: Integrated tools for response planning and scenario building (H2020-SEC-2016-2017-1, 2016)
Start date: 2017-09-01
End date: 2021-02-28
Duration (months): 42.0
Total project cost (EUR): 9583827.11
EU funding (EUR): 7999556.25
Participants: 23
Project status: CLOSED

European countries confront the rising specter of transboundary crises, which cross national borders as well as policy boundaries with speed and ease, threatening the continuing functioning of critical infrastructures and the well-being of many citizens. Transboundary crises pose a specific set of complex challenges for which Europe is – despite recent policy initiatives (e.g. Decision No 1313/2013/EU) – still ill prepared. We recognize three challenges that need urgent attention. First, member states need to develop shared response planning. Second, countries need to share information in real time. This sense-making challenge requires a way to have multiple countries and agencies create a shared picture of an emerging crisis based on multiple sources (different countries, many agencies). Third, countries need to coordinate the use of critical resources to ensure a timely response and to avoid waste and misspending. These challenges are hard to meet in any type of crisis or disaster, but especially in a transboundary context that lacks a dominant actor. IN-PREP will establish and demonstrate a next generation programme by enabling a reference implementation of coordination operations (Handbook of Transboundary Preparedness and Response Operations that synthesises the lessons learnt, recommendations, check-lists from past incidents) and a training platform (Mixed Reality Preparedness Platform a novel IT-based tool, which holistically integrates Information Systems (IS) and Situational Awareness (SA) modules over a decision support mechanism and the visualisation of assets and personnel) to the entirety of civil protection stakeholders (firefighting units, medical emergency services, police forces, civil protection units, control command centres, assessment experts) to meet these challenges. The proposed framework will not only improve preparedness and planning but can be also applied during joint interventions, thus improving the joint capacity to respond.

Keywords: transboundary crises collaborative response planning,crisis training programme,mixed reality preparedness platform,coordination command and control systems c3 integration,dynamic scenario building
Energy-aware Factory Analytics for Process Industries (FACTLOG)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Sustainable, resource-efficient and low-carbon technologies in energy-intensive process industries
Action type: Innovation actions
Countries involved: Germany,Ireland,Italy,Italy,Switzerland,Greece,Greece,Greece,Türkiye,Romania,Romania,Slovenia,Serbia,Türkiye,United Kingdom,United Kingdom,Portugal
Call: Digital technologies for improved performance in cognitive production plants (IA) (H2020-NMBP-SPIRE-2019, 2019)
Start date: 2019-11-01
End date: 2023-04-30
Duration (months): 42.0
Total project cost (EUR): 9199249.5
EU funding (EUR): 7089837.0
Participants: 21
Project status: SIGNED

It becomes apparent particularly in process industries that cognition can improve the behaviour of a complex process system. One of the main expectations of the use of digital twins is to give us the capability to observe and monitor the behaviour of their respective physical twins. In order to make it happen, we need to combine digital twins, which are driven by domain models (i.e. knowledge), with the models derived from data (i.e. experience). In order to realize it, we need a real-time processing layer where observations (i.e. events), knowledge and experience interoperate to understand and control the behaviour of a complex system (i.e. cognition). FACTLOG offers such a layer and aims at deploying and adjusting it to several process industries. By incorporating different pipelines of machine learning and analytical tools at different levels (from machines to process steps and from processes to the whole production plant), FACTLOG enables the realization of the Cognitive Factory as an ensemble of independent but intertwined ECTs, that are (i) able to self-learn, and thus to effectively detect and react to anomalies and disruptions but also to opportunities that may arise, (ii) enjoy a local or global view of operations and (iii) are capable for short-, mid- and long-term reasoning and optimization. FACTLOG is driven by several specific, yet indicative, business cases in the process industry and focuses its innovation regarding analytics, AI and optimization on the deployment and assessment of coherent Enhanced Cognitive Twins for the specific sectors represented in FACTLOG and even for the plants in which it will be pilot tested and evaluated. It will be implemented by a just right consortium of twenty partners, five of which are manufacturers and a further three represent manufacturing clusters. Technology and scientific contributors from leading academic institute and focused ICT vendors (mostly SMEs) bring in all necessary knowledge and innovation.

Keywords: cognitive digital twins,cognitive manufacturing,energy efficient manufacturing,data driven and model driven analytics,energy aware optimisation
Large scale perturbations of the gene regulatory networks of E. coli (PERTURBATIONS)

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: Life Sciences
Countries involved: France
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-04-01
End date: 2023-03-31
Duration (months): 24.0
Total project cost (EUR): 184707.84
EU funding (EUR): 184707.84
Participants: 1
Project status: CLOSED

Although genome sequencing is well advanced, our understanding of the genome to phenotype to fitness relationship remains very poor. It is becoming very evident that the information stored in genes is not enough to understand their impact without knowing the phenotypic and environmental context. The fact that a gene is present in a genome tells very little about when it is expressed and its relationship to other genes and mutual effects on gene expression pattern. To understand how phenotypes emerge from a specific genotype, we need to understand gene regulatory networks and their mechanisms of regulation. In this project, I propose to study the relationships between genotype, phenotype, fitness, and environment using a microfluidic device coupled with transcriptomics with the goal of collecting high dimension high quality data for unprecedented level of understanding and predicting regulatory networks, evolution, and evolutionary constraints in the form of epistasis and pleiotropy. I will use programmable DNA binding protein called CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) to perturb gene expression of (1) combinatorial global regulators within the transcriptional regulatory network, (2) cascades of genes that form gene network hierarchy, and (3) single global regulators with low level mutations at many positions in their genetic code. I will then quantify the expression pattern of the transcriptome using RNA sequencing and the growth fitness of each strain. The environment will be highly controllable as we will create a cutting-edge microfluidic system to study many strains of bacteria in a high-throughput manner. Successful implementation of the strategies explored in this project will open the doors to plenty of other avenues to explore with fruitful outcomes wherever there is a need for combining genotypic, phenotypic, and fitness studies in highly controllable environments

Keywords: systems biology,evolutionary adaptations,transcriptional network,genotype to phenotype mapping,crispr editing,microfluidics,rna sequencing,biophysics
A scalable, low cost solution for healthy mineralization of drinking water (WMT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Israel
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2019)
Start date: 2019-08-01
End date: 2019-11-30
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Climate change & water stress are changing the way we source drinking water. Although we have the technology to “clean” our drinking water, the same processes also strip out minerals essential to maintaining human health – especially water from desalination plants. Calcium & magnesium are macrominerals essential to human health: insufficient intake of either can increase the likelihood of cardiovascular diseases, osteoporosis, colon cancer, Type 2 diabetes & neurodegenerative diseases. Water is not considered a major source of minerals, but it should be: the bioavailability of magnesium dissolved in water is 12 times higher than in solid tablets/capsule. As such, the WHO recommends that where possible the water should be re-mineralized with calcium and magnesium. Remineralization has proved to be prohibitively expensive, laborious & limited in impact due to creating significant waste streams. There are no available solutions to cost effectively add magnesium to water & adding calcium is fraught with issues. Watefy have revolutionized the water mineralization process through the exploitation of the little-known physical phenomenon of developed hydrodynamic cavitation & vaporous and gaseous supercavitation. To exploit this phenomenon, we have designed WMT – a simple, modular mineralization system, comprised of a Gasifier, Calcite/Magnesium Dissolver & Degasser. This revolutionary process, currently at TRL 6, overcomes the existing challenges of high cost in terms, reducing construction & maintenance costs by over 90%. This process is the first to recover & re-use CO2 generated during the initial carbonation phase, eliminating a waste stream that currently adds to the high cost of desalination. Operational costs are reduced by 95% for producing high quality, healthy water. The company is looking for funding to validate the technology at industrial scale & transform the water industry beginning with desalination plants, expected to reach €23.9 billion by 2025.

Keywords: water,water mineralization,desalination,bottled water,magnesium,calcium
SMART BIOHYBRID PHYTO-ORGANISMS FOR ENVIRONMENTAL IN SITU MONITORING (WATCHPLANT)

Framework: Horizon 2020 — Excellent Science
Programme: Future and Emerging Technologies (FET)
Theme: EIC Pathfinder
Destination: Emerging themes and communities
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Spain,Germany,Spain,Croatia,Sweden,Poland
Call: Environmental Intelligence (H2020-FETPROACT-2020-2, 2020)
Start date: 2021-01-01
End date: 2024-12-31
Duration (months): 48.0
Total project cost (EUR): 3744192.5
EU funding (EUR): 3744192.5
Participants: 8
Project status: SIGNED

WatchPlant will develop a new biohybrid system technology, a wireless wearable self-powered sensor for in-situ monitoring of urban environments. This system equips urban biological organisms -plants- with Artificial Intelligence (AI) to create a smart sensor for measuring both, environmental parameters and the responding physiological state of plants, in a very early stage by the use of a barely explored fluid, phloem sap, in combination with chemical, and physical sensors. It will be integrated into complex network that allows performing distributed information processing, decision making, modeling and data fitting, paving the way for the self-awareness or self-adaptation. Additionally, it will constitute a clean energy self-powered device due to the novel use of sap, not only for transforming plants into living sensors, but also for clean energy generation. A consortium of EU research, technology centers and ambitious high-tech SMEs will stretch and combine the limits of plant physiology and bioelectronics with microtechnology, multiphysics modelling, sensor engineering, AI and environmental modelling, to transform plant into living autonomous and self-powered sensors. The project has the ambition to solve how to extract sufficient sap volume in a healthy plant, how to make long-lasting bioelectronics, and how create a smart self-powered wearable phytosensor in a single device. It also has the challenge of modelling urban environments using novel combinations of exiting parameters and explores the future role of sap in this sense. Thus, it is a promising tool to carry out weather/pollution/pandemics development forecasting systems up to social networks for proving an ecological/environmental feedback to citizens. Thus it will be possible to perform specific actions and apply efficient use of resources and correct policies, which can have a great impact not only in urban monitoring but a huge range of plant-related sectors such as agro-food industry or forestry.

Keywords: in situ monitoring,urban monitoring,modelling,plants,clean energy harvesting,biohybrid,wireless wearable smart self powered sensor