Ultrasound imaging can be deeply enhanced by means of algorithms developed in the field of geophysical imaging. Such algorithms, based upon adjoint-state modelling and iterative optimization, provide quantitative images of human tissue with very high resolution. At present time, such images can only be attained by means of high-performance computing and using specific ultrasound data acquisition devices. When combined, hardware and software have a huge impact potential for soft-tissue imaging, such as in breast cancer imaging. Nevertheless, and as is customary in medical imaging, the obtained images only provide with the mean, or most likely, values of tissue at each pixel, being uncertainty quantification an extremely expensive process, typically deemed as unfeasible for practical purposes. A revolutionary development in adjoint-based ultrasound imaging allows us to potentially obtain images of uncertainties at the cost of a single, mean-value, image. Such development will be the basis of transformative implications in terms of confidence-estimates for diagnosis. We aim at disrupting the breast cancer screening paradigm by means of a safe (radiation-free), accurate (quantitative) and reliable (uncertainty-aware) novel breast imaging modality. Within QUSTom we will investigate the fundamental science behind adjoint-based uncertainty imaging and establish its potential suitability for breast cancer diagnosis. The feasibility of the technology as a diagnosis tool relies on 1) adapting the data acquisition hardware for optimal resolution, 2) implementing the algorithms in high-performance computers in order to obtain a short time-to-solution and 3) feasibility analysis by expert radiologists in comparison with the state-of-the-art in breast imaging. This proposal covers the three aspects and opens the possibility of applying similar principles in other imaging fields, both in medicine and elsewhere.

The FF4EuroHPC proposal addresses the need for outreach to, and support of, Europe’s Small and Medium-sized Enterprises (SMEs) in order that they can profit from the innovation advantages offered by advanced High Performance Computing (HPC) technologies and services. FF4EuroHPC takes core team members from the highly successful Fortissimo and Fortissimo-2 projects (hereinafter simply Fortissimo projects) which executed 92 business experiments. They will use the lessons learned and best practices developed in those projects to create a portfolio of business-oriented “application experiments” that allow agile SMEs to investigate and solve business challenges and develop innovative business opportunities. The application experiment framework ensures that they receive the necessary, appropriate support to enter into the HPC ecosystem. FF4EuroHPC will lower the barriers for the participating SMEs to commence HPC-related innovation in their existing or newly identified markets either by using HPC systems for their business needs or by providing new HPC-based services. The outcome will be improved design and development processes, better products and services, and improved competitiveness in the global marketplace. Fundamentally, FF4EuroHPC is focussed on the creation of economic growth and jobs for the European Union.

<< Objectives >>MEDS aims to build on the key concepts and practices of the European Capitals of Smart Tourism (Accessibility, Sustainability, Digitalisation, Cultural heritage & creativity) to a novel cohort of Destination Managers capable of working in and with public administrations. They will encourage the digitalization of tourism and social innovation of small European destinations, contributing to making them evolve with a common purpose and a strong sense of place shared by visitors and residents.<< Implementation >>MEDS offers a learning approach that combines digital microlearning with physical co-creation labs to expedite smart tourism in European destinations. Learners will immerse into work-based learning experiences in which they will act as Budding Managers of Smart Destinations and will develop new projects and actions of sustainable tourism that can be driven and led by public authorities, also by activating public-private partnerships, and by using public and private resources.<< Results >>At the end of the transformative learning journey of MEDS, participants will be ready to better understand and manage evolutions brought about by the twin green and digital transitions, and overcome the old idea of tourism as a separate and stagnant sector in favor of a more inclusive and integrated approach. They will be empowered to ignite new models of tourism governance participated by the private sector and local communities.

"The socio-economic aspect of data and data related industries are crucial for the further development of the European Union and its competitiveness capacities in the global economy. Every day 2.5 quintillion bytes of data are created by different sources while 6.16 million people in Europe worked in data-related jobs in 2016, with a perspective to see the number of workers increasing up to 10.43 million by 2020. On the other side, the overall value of the EU data economy reached almost 300 billion EUR in 2016 and according to the ""high grow"" scenario the value will reach 739 billion by 2020, with an overall impact of 4% in the EU GDP.However, there is an existing gap between total demand and supply of data workers of 420.000 in EU in 2016, with a forecast to face a data skills gap corresponding to 769.000 unfilled positions by 2020. In order to mitigate potential unbalances and to sustain changes in policy making, regulatory framework and educational approach requested by this rapid deployment of new data technologies, EU has shaped its recommendations which underline the importance of reskilling work force developing digital skills for industry and launched its Agendas to boost human capital, employability and competitiveness by modernising education and training curricula/study programs.Facing stated challenges, universities and other HEIs are often lagging behind in their role of developing and offering educational programmes and materials, providing students with skills which market demands, thus indirectly creating a consistent gap between demand and supply of qualified workers. This is even more evident in non-technical sectors where domain-specific data skills are in high demand. The main objective of the ADSEE project is to deliver useful educational and training programme in data science (DS) through: development of educational modules, adaption of contents and methods according to envisaged needs of the target groups, creation of interactive didactic tools and production of guidelines and recommendations on innovative education approaches in DS. Special attention will be paid to data science in non-technical universities and its application in non-technical business, were previous knowledge in this area is not mandatory. The innovativeness of the project lies in the modular approach allowing tailor-made courses development, according to the participants' specific prior knowledge and competences (or in absence of that knowledge/competences) and in a fully functioning online piloting repository which will contribute to the development of participants' new skills and experiences by delivering material in full-scale training case (""from business problem to business usage"") and to fill the gap between increasing demand and limited supply of business sector for practical training methods and approaches. Thanks to a modular approach used to develop educational and training material, all modules will be transferable and applicable in any study program since they will be structured in flexible end-to-end business case avoiding a pure data scientific approach. The partnership comprises 5 partners : Algebra University College Croatia; University of Amsterdam, The Netherlands; German National Library and Leibniz Information Centre for Science and Technology, Germany; Faculty of Information Studies, Slovenia; Arctur ltd, Slovenia.Whereas the project will contribute to the popularisation of Data Science among wider public, the main target groups are higher education institutions and HEIs employees, students, business/industry sector, institutions (ministries of labour, national employment agencies, employers' associations), Digital Innovation Hubs (DIH). ADSEE project addresses individuals with in-depth knowledge about data science, those who are attending technical universities or are working in DS related sectors and individuals who know DS exists, are aware of its potential but still without an expertise to make decisions based on data science. In order to achieve the main objective, project partners have set up a set of activities that will result with five main intellectual outputs. - Report including a repository of existing DS training courses/study programmes and market needs in respect to relevant occupations, with a special attention to the non-technical sectors;- Interactive online repository as a focus point of the full learning materials, a tool for piloting and simulating use-cases in DS;- Transferable educational/training materials/modules covering wide range of different industries and cross-domain topics - At least four piloted and simulated use-cases - Guidelines for DS studies and for a non DS studies (studies that have implemented DS as horizontal element in curricula and studies that haven't implemented DS in curricula at all) including tailoring recommendations in relation to institutions specificities."

<< Objectives >>While blockchain is transforming business models, productivity, competitiveness and growth, blockchain education in agrifood s is still in an early stage. B-CHAIN AGRI-FOOD EDU will improve the incidence and quality of higher educator’s provision of education by developing new pedagogies in blockchain technologies spanning theories, methods, processes, and teaching concepts, to tackle societal challenges in the food supply chain and accelerate the digitisation of the food sector.<< Implementation >>The Guide to Blockchain Education in the Agrifood Sector will research and put forward recommendations for the pedagogic (andragogic) strategies best suited to teaching the digital skills required for blockchain integration in agrifood education. Blockchain Education in the Agrifood Sector OER’s will be the 1st open source resource to teach agrifood blockchain while Dissemination and Sustainability will ensure the widespread adoption of B-CHAIN AGRI-FOOD EDU across Europe and target groups.<< Results >>Results will empower over 1000 academics and lecturers in HEI from facilities of agribusiness, food science and engineering, and nutrition departments to unlock the power of Blockchain for their agrifood student population, while also providing leadership for industry players in their regions. We will responsibly lead the education of our thousands of students/ future workforce in a way that allows them to successfully meet the requirements of the job market.