CYBELE generates innovation and create value in the domain of agri-food, and its verticals in the sub-domains of PA and PLF in specific, as demonstrated by the real-life industrial cases to be supported, empowering capacity building within the industrial and research community. Since agriculture is a high volume business with low operational efficiency, CYBELE aspires at demonstrating how the convergence of HPC, Big Data, Cloud Computing and the IoT can revolutionize farming, reduce scarcity and increase food supply, bringing social, economic, and environmental benefits. CYBELE intends to safeguard that stakeholders have integrated, unmediated access to a vast amount of large scale datasets of diverse types from a variety of sources, and they are capable of generating value and extracting insights, by providing secure and unmediated access to large-scale HPC infrastructures supporting data discovery, processing, combination and visualization services, solving challenges modelled as mathematical algorithms requiring high computing power. CYBELE develops large scale HPC-enabled test beds and delivers a distributed big data management architecture and a data management strategy providing 1) integrated, unmediated access to large scale datasets of diverse types from a multitude of distributed data sources, 2) a data and service driven virtual HPC-enabled environment supporting the execution of multi-parametric agri-food related impact model experiments, optimizing the features of processing large scale datasets and 3) a bouquet of domain specific and generic services on top of the virtual research environment facilitating the elicitation of knowledge from big agri-food related data, addressing the issue of increasing responsiveness and empowering automation-assisted decision making, empowering the stakeholders to use resources in a more environmentally responsible manner, improve sourcing decisions, and implement circular-economy solutions in the food chain.

Nowadays, there is a trend towards the More-Electric Aircraft (MEA) concept. MEA would replace the secondary aircraft power systems (electric, hydraulic and pneumatic) with a globally optimized electrical system. However, the architecture of the electric system must be carefully selected to optimize the whole aircraft. Actual research in MEA technology is focused on new advances in power electronics, fault-tolerant electric machines, digital control, electro-mechanical actuators and communications. Modern technologies involved in MEA are being taken in two different paths: i) elimination of bleed-air systems and hydraulic engines with further improvements in electrical power generation capability. It requires changes in both electrical generation and distribution network, and ii) replacement of hydraulics actuators with electro-mechanical actuators with the same level of safety and reliability, reducing weight, fuel usage, maintenance and production costs. Several studies have been recently carried out emphasizing the interest on the replacement of the traditional electro-hydrostatic actuators used in flight control surfaces by electro-mechanical actuators (EMAs). The reasons for such a choice are: weight and maintenance reduction, elimination of pipes vibration problems, increase of reliability, increase of the system performance and pressure losses thanks to the absence of valves. The EMA4FLIGHT project will design, manufacture and tune innovative electro-mechanical actuator sub-systems for aileron/spoiler and winglet/flap-tab flight control surfaces, with clearance for flight. The designed sub-systems will be improved by electric motor and ballscrew innovative architecture, advanced control strategies and smart safety, diagnostic and maintenance functions.

The objective of the VALEMA project is twofold: - On the one hand it is required to manufacture and assembly units (EMAs and ECUs) previously designed and developed according to the JTI-CS2-2016-CFP03-SYS-02-14 Call (Development of electromechanical actuators and electronic control units for flight control systems) for in flight tests activities. - On the other hand it is required to perform certification activities regarding both the HW and SW of the ECUs in order to obtain a permit to fly in the FTB2 demonstrator of the Regional Aircraft. The manufacturing part will include a deep analysis of manufacturing routes, materials to be used and applicable qualification tests, searching for innovative processes, in order to ensure that the processes optimize the manufacturing time, minimize the raw material used and minimize the environmental impact. The certification activities will be aimed at obtaining the permit to fly from the applicable Airworthiness Authorities for the aileron/spoiler ECU HW design (according to DO-254) and for the aileron/spoiler ECU SW design (according to DO-178B). These activities can be considered as the last step within the HW and SW design of the aileron/spoiler ECU development to be undertaken in EMA4FLIGHT according to the JTI-CS2-2016-CFP03-SYS-02-14 Call and, as such, the innovations developed within that call also apply herein.

The need for levels of availability and scalability beyond those supported by relational databases has led to the emergence of a new generation of purpose-specific databases grouped under the term NoSQL. In general, NoSQL databases are designed with horizontal scalability as a primary concern and deliver increased availability and fault-tolerance at a cost of temporary inconsistency and reduced durability of data. To balance the requirements for data consistency and availability, organisations increasingly migrate towards hybrid data persistence architectures comprising both relational and NoSQL databases. The consensus is that this trend will only become stronger in the future; critical data will continue to be stored in ACID (predominately relational) databases while non-critical data will be progressively migrated to high-availability NoSQL databases. Moreover, as the volume and the value of natural language content constantly grows, built-in support for sophisticated text processing in data persistence architectures is increasingly becoming essential. The aim of TYPHON is to provide a methodology and an integrated technical offering for designing, developing, querying and evolving scalable architectures for persistence, analytics and monitoring of large volumes of hybrid (relational, graph-based, document-based, natural language etc.) data. TYPHON brings together research partners with a long track record of conducting internationally-leading research on software modelling, domain-specific languages, text mining and data migration, and of delivering research results in the form of robust and widely-used open-source software, industrial partners active in the automotive, earth observation, banking, and motorway operation domains, an industrial advisory board of world-class experts in the fields of databases, business intelligence and analytics, and large-scale data management, and a global consortium including more than 400 organisations from all sectors of IT.