Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Neutron based Elemental Analysis Technology (NEAT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Germany
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-10-01
End date: 2019-03-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Accumulations of hazardous substances in soil, water or air, mean a serious threat for society. To prevent damage from population, there is a trend of applying stricter and stricter statutory thresholds, especially for heavy metals. AiNT has developed an innovative non-destructive and non-contact assay for multi-element detection using neutrons as probes. The technology enables the determination of heavy metal contents and other contaminats in large environmental samples in a minimal time. Potential customers for measurement services are companies in the agriculture industry, environmental authorities or industrial companies who need information on the elemental composition of their samples. The market of environmental analysis has a volume of approximately two billion € in Germany (2014) and has been steadily growing at an average rate of 10 % per year between 2003 and 2010. The measurement system is currently built in a technical centre of AiNT. Analysis results are created automatically by the developed evaluation software. Results are digitally available and can be uploaded to a cloud-based database for direct access and post-processing. Objectives of the feasibility study (phase 1) are the following. Firstly, an extensive market study will be conducted. From this study, the submarket for market entry is chosen. Furthermore, we choose a business partner for marketing and sales. We study measurement concepts and necessary adaptions of the design of the measuring system to general conditions and specific needs of the chosen submarket. All this leads to the elaboration of the business model. The preferred option is to offer measurements as a service. The feasibility study will clarify the chances of prospect of the development for environmental analysis and will identify the economically most attractive submarket for business activities. Alternatives to the preferred model, the direct marketing of the measurement system as a product, will also be investigated.

Keywords: detection of contaminations,elemental analysis,heavy metals in soil samples,water analysis,environmental analytics,detection of hazardous substances,measurement technology
MAximizing the UPscaling and replication potential of high level urban transformation strategies (MAtchUP)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Reducing energy consumption and carbon foorpint by smart and sustainable use
Action type: Innovation actions
Countries involved: Spain,Italy,Germany,Italy,Germany,Israel,Germany,Spain,Spain,Türkiye,Türkiye,North Macedonia,Belgium,Finland
Call: Smart Cities and Communities lighthouse projects (H2020-SCC-2017, 2017)
Start date: 2017-10-01
End date: 2023-09-30
Duration (months): 72.0
Total project cost (EUR): 19425922.74
EU funding (EUR): 17418339.0
Participants: 38
Project status: SIGNED

MAtchUP project aims at strengthening the planning processes for urban transformation, consolidating the benefits of deploying large scale demonstration projects of innovative technologies in the energy, mobility and ICT sectors, by means of substantially improved models for replication and upscaling, based on impacts evaluation, and ensuring the bankability of the solutions by means of innovative business models, which lead to achieve real deployment further than the pilots carried out in the lighthouse cities. With this, it is sought a high penetration of the validated technologies in those cities less prepared to adopt very innovative solutions and formalize it in a standard commitment, accompanied by capacity building strategies, to guarantee at least medium term implementation. The expected results will be achieved working in parallel in demonstration and upscaling/replication levels, so the lighthouse cities (Valencia-Spain, Dresden-Germany and Antalya-Turkey) and followers (Ostend-Belgium, Herzliya-Israel, Skopje-FYROM and Kerava-Finland) will assume a huge commitment in this project in order to: - deploy innovative solutions in the energy, mobility and ICT sectors with a strong monitoring program to validate all of them, - develop very rigorous upscaling and replication plans that will be the basis to update at least the SEAPs/SECAPs, that are the major standard commitment at European level that a city can assume in terms of city transformation, and other existing city plans as Sustainable Mobility Plans or Digital Agendas.

Keywords: smart cities,citizens,city challenges,urban transformation,demonstration,evaluation,integrated planning,upscaling,replication,lighthouse cities,follower cities,energy,mobility
Automatic Polyp Detection System (MagentiqEye)

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

The World Cancer Research Fund estimates the colorectal cancer to be the third-most occurring form of cancer around the world. In 2012, more than 1 Million people were diagnosed with colorectal cancer. These incidences of colorectal cancer have boosted demand for their diagnostics worldwide. In fact, colon cancer screening has increased greatly in first world countries with mature health care delivery systems. Despite this progress the problem of undetected or missed polyps during colonoscopy procedures remains a significant problem: about 8 -10% of the CR cancer cases, resulting in more than 44,500 of preventable cancer in Europe annually. MagentiqEye has developed an Automatic Polyp Detection System (the APDS) which uses mainly Deep Learning and Computer Vision techniques in order to detect the polyps which appear on the physician screen during the test. APDS is an AI system which works as additional eye, helping doctors to detect polyps. This decision support system can improve the quality and performance (less miss-rete) of the colonoscopy test, having a high impact in the prevention of cancer. MagentiqEye seeks funding to conduct a feasibility study to prove technical and commercial viability, conducting an analytical exercise to position the product. The objective is to test the economic viability of the system among a larger pool of potential clients (user-acceptance), and to assess if the chosen commercialisation approach will be conducive of the projected growth on the European level.

Keywords: healthcare system,health related biotechnology,colorectal cancer,colonoscopy test,preventable cancer,automatic polyp detection system
3D SMART MODELS FOR HERITAGE CONSERVATION An Open Science project for documentation, management and representation of Cultural Heritage (3D-SMoHC)

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: Social Sciences and Humanities
Countries involved: Portugal
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-06-05
End date: 2019-06-04
Duration (months): 24.0
Total project cost (EUR): 160635.6
EU funding (EUR): 160635.6
Participants: 1
Project status: CLOSED

In today’s society, three-dimensional models of the tangible heritage present the greatest potential for heritage conservation efforts, due to advances in display devices, capabilities, and infrastructure costs, etc. However, in reality, these models do not always provide the necessary accuracy; they require an arduous process of managing and transforming; and they are not set up for reuse and long-term archiving. Without such capabilities we are left with inadequate knowledge that leads to higher expenses and time costs during documentation of fieldwork, disconnected bodies of geospatial data, and over-dimensioned and disorganised information. These problems further limit the scope and efficiency of the use of digital heritage resources for professionals, and restrict the accessibility of these resources to a wider audience without technical literacy, therefore constraining conservation and reuse practices throughout society. Current 3D models are not enough to overcome these limitations unless they become smart. Therefore, 3D-SMoHC aims to remedy this gap through the creation of 3D Smart Models for Heritage Conservation. With these models, 3D representations of built heritage can be organised according to their semantic features and adapted to management and visualisation multi-platforms. To achieve such digital products and improve the way we address the conservation of our cultural heritage, we need more than technological development: technical advancements must be combined with in-depth knowledge of today’s uses and needs, sharing a common language, and integrated into the proper legal framework for the new data structures. To accomplish developments with such dimensions and scope, 3D-SMoHC is conceived within an Open Notebook Science strategy. It is intended that greater transparency should characterise the whole project and should impact not only on data sharing and dissemination of results, but also on the production process of the research itself.

Keywords: heritage,smart data,remote sensing,computer vision,e learning,open science
Bioengineered autonomous cell-biomaterials devices for generating humanised micro-tissues for regenerative medicine (ATLAS)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced 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: Portugal,Portugal
Call: ERC Advanced Grant (ERC-2014-ADG, 2014)
Start date: 2015-12-01
End date: 2021-10-31
Duration (months): 71.0
Total project cost (EUR): 2498987.5
EU funding (EUR): 2438987.5
Participants: 2
Project status: CLOSED

New generations of devices for tissue engineering (TE) should rationalize better the physical and biochemical cues operating in tandem during native regeneration, in particular at the scale/organizational-level of the stem cell niche. The understanding and the deconstruction of these factors (e.g. multiple cell types exchanging both paracrine and direct signals, structural and chemical arrangement of the extra-cellular matrix, mechanical signals…) should be then incorporated into the design of truly biomimetic biomaterials. ATLAS proposes rather unique toolboxes combining smart biomaterials and cells for the ground-breaking advances of engineering fully time-self-regulated complex 2D and 3D devices, able to adjust the cascade of processes leading to faster high-quality new tissue formation with minimum pre-processing of cells. Versatile biomaterials based on marine-origin macromolecules will be used, namely in the supramolecular assembly of instructive multilayers as nanostratified building-blocks for engineer such structures. The backbone of these biopolymers will be equipped with a variety of (bio)chemical elements permitting: post-processing chemistry and micro-patterning, specific/non-specific cell attachment, and cell-controlled degradation. Aiming at being applied in bone TE, ATLAS will integrate cells from different units of tissue physiology, namely bone and hematopoietic basic elements and consider the interactions between the immune and skeletal systems. These ingredients will permit to architect innovative films with high-level dialogue control with cells, but in particular sophisticated quasi-closed 3D capsules able to compartmentalise such components in a “globe-like” organization, providing local and long-range order for in vitro microtissue development and function. Such hybrid devices could be used in more generalised front-edge applications, including as disease models for drug discovery or test new therapies in vitro.

Keywords: regenerative medicine,soft matter,bioinstructive materials
Beyond Brands, Forms of Life. At the Heart of Marketing, the Experience. (BEYONDBRANDS)

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: Social Sciences and Humanities
Countries involved: United Kingdom,Peru
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-08-01
End date: 2024-07-31
Duration (months): 36.0
Total project cost (EUR): 249597.12
EU funding (EUR): 249597.12
Participants: 2
Project status: SIGNED

This project will demonstrate the significance of semiotics (the study of meaning-making) for science and society by developing a definition and conceptualisation of one of the most emblematic phenomena of Modernity: the brand. Indeed, although brands are of interest to us all, they remain multifaceted phenomena and defining them proves to be quite a difficult task: they are associated with entities that are not only very different to each other (e.g. an organisation, a product, a logo), but also hazy (e.g. a service, values). Whether one comes from marketing or social sciences, the quasi-ontological question of “what a brand is?” turns out to be a real intellectual challenge. Thus, drawing on and developing the theoretical and methodological apparatus of semiotics, the objective of this fellowship will be (O1) to define what a brand is semio-ontologically and what it produces semio-functionally. This involves determining how brands physically come into existence, and what they bring, in turn, to the social experience of the individuals who use them. The conclusions of my PhD thesis on the concept of “forms of life” will bring innovative hypotheses that will also enable me (O2) to create an alternative model for brand identity to those developed over the last 20 years in marketing, notably because it will place experience at the heart of all the issues. Finally, to refine the model and reveal its advantages, I will conduct a case study aimed at (O3) modelling the identity of Marca Perú, the Peruvian nation brand. By (O4) investigating the meaningful gap, that brands always raise, between promised experiences (in communication) and real-life experiences (in consumption), this case study will complete and conclude my principal objectives (O1-O2), as well as the global aim of this fellowship: to contribute to the development of the European semiotics in non-academic sectors (specifically the business one) and in other continents (mainly the American one).

Keywords: semiotics,brands,branding,peru
Unsupervised Perception (UNION)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: United Kingdom
Call: ERC CONSOLIDATOR GRANTS (ERC-2020-COG, 2020)
Start date: 2022-01-01
End date: 2027-05-31
Duration (months): 65.0
Total project cost (EUR): 2311847.0
EU funding (EUR): 2311847.0
Participants: 1
Project status: SIGNED

The aim of UNION is to liberate machine learning, enabling everyone to use it productively and creatively instead of being the demesne of experts. Today, machines must be explicitly taught any new skill via manual supervision, incurring a cost justifiable only for applications of general interest. Thus, as laypeople, we can benefit from powerful search engines, medical devices and personal assistants that are designed by means of machine learning, but we cannot easily teach machines to address our particular professional or personal needs. From recognizing illustrations on Greek vases to building catalogues of store products, machine learning could empower millions of individuals, but current technology cannot scale to these micro-tasks. The goal of UNION is thus to develop machines that can learn to understand audio-visual data with little to no manual supervision, opening up artificial intelligence to countless new applications. To this end, UNION will investigate two key hypotheses. The first is that concepts that reflect intrinsic properties of the natural world, such as detachable objects and their 3D geometry, physics and high-level class, can be learned without manual supervision, while still being interpretable to a human. The second hypothesis is that, given this ability, a machine can pick up new skills useful to specific stakeholders from no or just a few manually-annotated examples. These hypotheses will be validated (1) by developing algorithms that can learn without manual supervision, (2) by endowing machines with advanced general-purpose audio-visual analytical skills, and (3) by using the knowledge already acquired to learn new skills very efficiently, from little data and even less manual supervision. This will be delivered as an open-source package that will demonstrate how one can create open-ended audio-visual analysis software that can be taught a large variety of different tasks with at most lightweight manual assistance.

Keywords: image understanding,unsupervised learning,visual geometry
BUSINESS INTELLIGENCE SERVICE FOR THE MANAGEMENT OF CROPS BASED ON CLOUD AND BIG DATA (BYNSE)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Action type: SME instrument
Countries involved: Spain
Call: Resource-efficient eco-innovative food production and processing (H2020-SMEINST-1-2014, 2014)
Start date: 2015-06-01
End date: 2015-08-31
Duration (months): 3.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Agro-industrial companies face the necessity of acquiring more information and control over their crops and the operations they perform in order to produce them. The challenge lies in reducing the hydric and energy resources they use with the objective of increasing their competitiveness and reducing the impact on the environment. Under the brand name of bynse, our SME cubenube (www.cubenube.com) has developed the first big data solution for agriculture in the world. bynse allows managers and producers to analyse the current and future needs of their crops in real time, using an innovative and inexpensive microclimatic sensing system called bynsebox for collecting field data, and a cloud information service called bynsecloud for processing and displaying the information to the users. This data is intersected with data from weather forecasts and vegetative growth tasks (pruning, seeding, etc), and a number of recommendations are generated, leading to a 30% reduction in energy and water consumption, and up to 40% reduction in the use and subsequent cost of phytosanitary products. Other information, such as strength and vigour of the plants, cannot be extracted from sensors and require colour areal maps (providing data through chlorophyll levels). The combined information provided by these maps plus bynse sensor information has great market potential for our target market of owners and managers of high added-value crops with extensions of between 20 and 100 hectares of non-intensive, woody or extensive agriculture. The main goal of this innovation project is to evolve bynse offering a “universal” solution by linking big data to geographical data to provide a full Precision Agriculture solution by adding the capability of processing colour maps and geo-localization to the overall information analysis and recommendations.

Keywords: business intelligence service for the management of crops based on cloud,and big data
Unobtrusive printed piezoelectric sensors for non-invasive biosignal monitoring (UNOPIEZO)

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: Information Science and Engineering
Countries involved: Finland,United States
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-10-01
End date: 2024-03-13
Duration (months): 27.0
Total project cost (EUR): 198631.68
EU funding (EUR): 198631.68
Participants: 2
Project status: SIGNED

Goal: The goal of this project is to develop unobtrusive, affordable and accurate piezoelectric sensors for non-invasive biosignal monitoring. Background: Continuous large-scale health monitoring of risk population carries significant benefits to the society, but is hindered by the lack of unobtrusive, affordable and accurate biosignal sensors. As an example, continuous monitoring of radial arterial pulse wave (PW) signal could enable early detection of cardiovascular diseases (CVDs, most common cause of death) and lead to significant reductions in societal costs associated with their treatment and current screening methods, both of which require hospital visits. Ultra-thin (t < 10 µm) sensors have been recently proposed to enhance the user comfort by recording the PW-signal non-invasively from the skin deformation caused by the pulsating radial/carotid artery located directly underneath the skin. Although the proposed devices have high potential for continuous PW-monitoring due to their unobtrusiveness, they suffer from drawbacks such as high energy consumption, costly fabrication, biocompatibility issues and/or low sensitivity. Proposal: In order to meet the requirements of unobtrusiveness, affordability and accuracy, it is proposed that such biosignal sensors should be fabricated of piezoelectric polymer P(VDF-TrFE) using printed electronics fabrication technologies. The optical transparency and biocompatibility of P(VDF-TrFE) coupled with ultra-thin form factor of the device should result in sensors that are highly unobtrusive for the user. Furthermore, the ultra-thin form factor coupled with novel charge collector structure should maximize the sensor sensitivity, thereby increasing the accuracy of the biosignal measurement beyond the capabilities of conventional sensor structures. The sensor fabrication with additive and scalable printed electronics fabrication technologies should result in devices that are affordable for the user and for the environment.

Keywords: printed electronics,piezoelectric materials,p vdf trfe,ultra thin sensors,non invasive biosignal measurement,additive fabrication