ECHO delivers an organized and coordinated approach to improve proactive cyber defence of the European Union, through effective and efficient multi-sector collaboration. The Partners will execute on a 48-month work plan to develop, model and demonstrate a network of cyber research and competence centres, with a central competence at the hub. The Central Competence Hub serves as the focal point for the ECHO Multi-sector Assessment Framework enabling multi-sector dependencies management, provision of an ECHO Early Warning System, an ECHO Federation of Cyber Ranges and management of an expanding collection of Partner Engagements. The ECHO Multi-sector Assessment Framework refers to the analysis of challenges and opportunities derived from sector specific use cases, transversal cybersecurity needs analysis and development of inter-sector Technology Roadmaps involving horizontal cybersecurity disciplines. The Early Warning System, Federation of Cyber Ranges and Inter-sector Technology Roadmaps will then be subject of Demonstration Cases incorporating relevant involvement of inter-dependent industrial sectors. The ECHO Cyber-skills Framework provides the foundation for development of cybersecurity education and training programmes including a common definition of transversal and inter-sector skills and qualifications needed by cybersecurity practitioners. The ECHO Cybersecurity Certification Scheme provides a sector specific and inter-sector process for cybersecurity certification testing of new technologies and products resulting from the proposed technology roadmaps. The project will develop and operate under an ECHO Governance Model, by which the efforts across the EU Network of Cybersecurity Competence Centres can be coordinated and optimized to provide lasting and sustainable excellence in cybersecurity skills development; research and experimentation; technology roadmaps delivery; and certified security products for improved cybersecurity resilience.

Productive land resources in Egypt are under multiple natural and human pressure that are leading to soil degradation and desertification. Agriculture land conservation is a high priority for Egypt. Several efforts have been undertaken by the government authorities of Egypt to reduce desertification processes and preserve land productivity but they have faced a wide range of obstacles, mostly related to : i) improper and irrational land use policy and planning; ii) lack of scientific knowledge and technical expertise to cope with complex problems; iii) absence of national, regional and international networking and an ineffective mechanisms for technology transfer, exchange of experience and cooperation at different levels. ILHAMEC project is intended to develop a postgraduate Master on Sustainable Land Management (SLM) within the curricula of four Egyptian universities supported by three EU ones adopting the strategy to first train teachers. During its life time, the consortium envisages to reach many results such as: studies, surveys, access to open digital contents, web learning tools, teachers training materials, an educational web-based simulation game on SLM, educational innovative video-lessons, new Master curricula, workshops and seminars. All the resources will be accessed easily, reused and adapted by the project target groups (mainly teachers, students and HEIs) at local, regional, national and European levels. Sustainability will be ensured by identifying individuals and groups or institutions that will take over its animation and moderation. ILHAMEC will have a strong impact within the same partners of the Consortium through the process of sharing knowledge, challenges and solutions. Additional stakeholders will benefit from the project as the main outcome is to spread knowledge and awareness on SLM issues and on the importance to improve quality in HEIs for increasing technical and analytic skills of young students.

The BRIDGITISE doctoral network will focus on the digitalisation of bridge management across the lifecycle through the development of innovative approaches to information management. The basic idea underlying the project is that the achievement of excellence in this field requires the development and validation onsite of innovative technologies for the cost-effective management of bridge information and their use to support decisions relevant to bridge integrity management across the lifecycle. To this aim, a network of 15+1 PhD projects is structured around three main research and training clusters focused on the development and validation of: -innovative low-cost, large scale and automatic technologies, to collect bridge information - Artificial Intelligence and IoT technologies specifically tailored to bridges to process and share information, - digital decision support tools able to manage bridges across their lifecycle The project will combine the expertise of six universities, one research center, and seventeen industrial companies and end-users who will provide case studies to apply and validate the project results thereby fostering the technological transfer of the research findings. This powerful combination of expertise from industry and academia will introduce the DCs to the topics of the project and add to their inter-sectoral employability, enabling Europe to build world-class competitive capacity in a strategic market. Deliverables of the BRIDGITISE DN will be technology-enhanced training and dissemination tools, international workshops, and Training Schools. Furthermore, an Open platform for sharing data related to bridge management will be built to develop collaborative and information-sharing skills of the DCs and to increase the impact of the project.

SMARTool aims at developing a platform based on cloud technology, for the management of patients with coronary artery disease (CAD) by standardizing and integrating heterogeneous health data, including those from key enabling technologies. The platform includes existing multiscale and multilevel ARTreat (FP7-224297) models of coronary plaque progression based on non-invasive coronary CT angiography (CCTA) and fractional flow reserve computation, refined by heterogeneous patient-specific non-imaging data (history, lifestyle, exposome, biohumoral data, genotyping) and cellular/molecular markers derivable from a microfluidic device for on-chip blood analysis. SMARTool models will be applied and validated by historical and newly acquired CCTA imaging plus non-imaging health data from the EVINCI project (FP7-222915) population. SMARTool cloud-based platform, through Human Computer Interaction techniques, 3D visual representation and artery models, will use heterogeneous data in a standardized format as input, providing as output a CDSS - assisted by a microfluidic device as a point of care testing of inflammatory markers – for: i) Patient specific CAD stratification - existing models, based on clinical risk factors, will be implemented by patient genotyping and phenotyping to stratify patients with non-obstructive CAD, obstructive CAD and those without CAD, ii) site specific plaque progression prediction - existing multiscale and multilevel ARTreat tools of CAD progression prediction will be refined by genotyping and phenotyping parameters and tested by baseline and follow CCTA and integrated by non-imaging patient-specific data, iii) patient-specific CAD diagnosis and treatment - life style changes, standard or high intensity medical therapy and a virtual angioplasty tool to provide the optimal stent type(s) and site(s) for appropriate deployment.