The aim of this project is to bring together subject matter experts from the academic and non-academic sectors to create a holistic informatics platform for rapidly integrating genomic sequences, electronic health records (EHRs) and research repositories to enable personalised medicine strategies for malignant melanoma treatment. The consortium has engaged in a pre-proposal process with active clinical end users who have highlighted the need for more innovative approaches for the treatment of cancer - in particular the treatment of malignant melanoma, including inter alia the ability to rapidly query of geno-phenotype associations in melanoma such as the recently discovered rs2301641 SNP variability with ABCB5 function and CDK4 gene indicators . Hence we aim to develop a scalable HPC framework that allows the semantic interlinking between spatially distributed electronic patients’ health records, associated genomic sequences and published research, thereby allowing clinicians to make reasoned queries over vast knowledge bases for the diagnosis, treatment and management of malignant melanoma.

"<< Objectives >>No one is left behind in the digital transformation. Artificial Intelligence (AI) is changing the nature of work: jobs will be created, others will disappear, most will be transformed. Modernisation of education, at all levels, should be a priority for governments. All Europeans should have every opportunity to acquire the skills they need. Talent should be nurtured, gender balance and diversity encouraged"" while at the same time ensuring a high level of data protection, digital rights and ethic<< Implementation >>Handbook for Understanding Ethics in the field data and AIBased on a research on several levels to identify the gaps in adult education with regard to AI and data ethics in particular. E-learning platform - Ethics in AI dataCourse 1: Ethic and Big Data in the adult learning environmentCourse 2: AI and data driven Methodology in the Learning EnvironmentCourse 3: Learning AnalyticsCourse 4: Methods and Use of Learning Analytics and Big Data for an Individual Educational Approach in an ethics<< Results >>Increasing usage of AI in adult teaching and learning in the project countries.Increasing the competences in the field of AI and data ethics in the process of education for educators and learners 15,000learners from the EU and beyond over five yearsSuccessful project implementation at EU level in line with the EU AI initiative and in particular the EU guidelines on ethicsin artificial intelligenceCreating 7 new projects in the field of AICreating digital OERs"

Overall goal is to use GNSS as an support for IMU to track whole body movements in the wild, for healthcare and wellness applications. The GESTUS proposal aims to address a clear need of movement workers, physicians, physical therapists, and athletic trainers. The need is to have a tool that allows for highly accurate tracking of the kinematics of the human body, for the entire duration of the activity. GESTUS proposes a solution based on the integration of GNSS and IMU within ad-hoc wearable devices, which allow for high accuracy for a long duration of time in the real environment. The solution then consists of an ad-hoc created data processing algorithm and a cloud platform, with associated communication infrastructure, to automate sensor management, data downloading, processing itself, and results fruition, analysis and sharing. The project and the solution it proposes is primarily aimed at remote monitoring of patients with, or potentially affected by, degenerative and neurological diseases such as multiple sclerosis or Parkinson's. In such patients, it is very important to monitor with great accuracy the movements of every part of the body, both for possible early diagnosis and to monitor the evolution of the disease, to evaluate the effect of ongoing treatments, and to plan in advance actions to mitigate symptoms.

Given the inability of Highly-Distributed-Application-Developers to foresee the changes as well as the heterogeneity on the underlying infrastructure, it is considerable crucial the design and development of novel software paradigms that facilitate application developers to take advantage of the emerging programmability of the underlying infrastructure and therefore develop Reconfigurable-by-Design applications. In parallel, it is crucial to design solutions that are scalable, support high performance, are resilient-to-failure and take into account the conditions of their runtime environment. Towards this direction, the ARCADIA project aims to design and validate a Novel Reconfigurable-By-Design Highly Distributed Applications Development Paradigm over Programmable Infrastructure. The proposed framework will rely on the development of an extensible Context Model which will be used by developers directly at the source-code level. Proper Context-Model will be assisted and validated by IDE-plugins (for many IDEs) in order to re-assure that the generated executable files contain meaningful semantics. According to ARCADIA’s vision, the generated executables should be on-boarded by a Smart Controller which will undertake the tasks of translating annotations to optimal infrastructural configuration. Such a controller will enforce an optimal configuration to the registered programmable resources and will pro-actively adjust the configuration plan based on the Infrastructural State and the Application State. The Context-Model and the aforementioned ARCADIA toolset will be complemented by a Development Methodology that will assure that developed Highly Distributed Applications are Reconfigurable-By-Design. The framework is planned to be validated and evaluated on three use cases that will be deployed over testbeds that host heterogeneous programmable infrastructure.