To develop an innovativve cloud base buisness management system for the construction industry through the embedding of advanced user experience techniques.

This research will use storytelling as a methodology to develop our understanding of the impact of discrimination that BME nurses have experienced during the Covid19 crises. It will consider how this compares to their previous experiences of working in the NHS and their vision for a more equitable future. The project aims to collect direct testimonies from nursing and support staff to present detailed personal accounts of their experience both during the crisis and historically. The emerging discourse on the diverging impact of Covid19 by ethnicity has focused on pre-existing co-morbidities, cultural differences, possible genetics differences. While socio-economic factors have been referenced with comments on 'pre-existing inequalities in health and healthcare', there has been little address to questions of implicit and explicit racialised discriminations. It is however crucial to develop our understanding of the impact of racism. Feb 2020 BMJ special issue on Racism in Medicine highlighted continued inequalities and discrimination faced both by service users as well as staff in the NHS. Critical Race Theory suggests experiential knowledge, critical consciousness and centring research in the margins are essential strategies to further our understanding of structural inequalities. (Delgado & Stefancic 2017) Using an arts based approach that centres emotion as a resource for memory and recovery we will enable nurses to recount their experiences, visualise their traumas and those of communities worst affected by the crisis, and recognise their experience and insights as a crucial asset in creating significant change with which to support the building of a more inclusive society and a more equitable NHS capable of delivering the best patient care.

ODYSSEUS aims to increase the knowledge on explosive precursors and homemade explosives (HMEs), including precursors not previously studied, and develop effective and efficient prognostic, detection, and forensic tools to improve the capabilities of LEAs towards the prevention, countering, and investigation of terrorist incidents involving HMEs. ODYSSEUS will build upon relevant previous projects mainly HOMER, through the involvement ofHOMER’s core partners in this consortium, and will thus continue the work already done in HOMER on some precursors and further extend it to not previously studied precursors. To discover potentially hitherto unknown information, online HMEs recipes will be collected and their content will be analysed so as to extract knowledge about (possibly unknown) precursors and HMEs. Selected precursors will be then characterisedand analysed for determining their explosive properties, feasibility, and potential for becoming a threat.This knowledge will be leveraged for developing tools for(i) chemical supply chain monitoring for irregularity detection to enable prediction and localisation of potential threats; (ii) advanced sensors for detecting in (near) real-time explosive precursors through air emissions and sewerage networks; (iii) robotised tools for improved mobile detection and in-situ forensic support; and (iv) automated threat detection, localisation, and assessment; these tools will be integrated into a configurable platform that will assist LEAs’ operations in diverse scenarios. ODYSSEUS will be validated in lab and field tests and demonstrations in three operational use cases. Extensive training of LEAs' personnel, hands-on experience, joint exercises, and training material will boost the uptake of ODYSSEUS tools and technologies. With a Consortium of 4 LEAs, 9 Research/Academic partners, and 5 industry partners, ODYSSEUS delivers a strong representation of the challenges, requirements and tools to meet its objectives.

AI is transforming law enforcement, offering new tools for policing but also enabling advanced criminal tactics that challenge traditional methods. The global nature of crime, including cyber threats, trafficking, and terrorism, calls for innovative solutions as LEAs face vast data volumes and increasingly sophisticated criminal activities. AI has raised concerns with deepfakes—highly realistic but fake audio, video, or text that can depict individuals saying or doing things they never did. Deepfakes pose serious risks, impacting politics, economy, and social trust. Examples include fabricated videos of political figures and voice-cloned audio for financial fraud, often spread through social networks to deceive and defraud on a large scale. Forensic institutes and courts struggle to differentiate authentic evidence from AI fabrications, especially in cases involving national security. Despite promising detection research, existing methods fall short as current models rely on limited, non-diverse datasets and produce results with limited legal admissibility. The DETECTOR initiative aims to address these challenges, supporting LEAs and forensic experts in analyzing altered media. It offers an integrated solution through cross-border collaboration among AI researchers, LEAs, forensic scientists, legal experts, and ethicists. DETECTOR’s goals include: developing specialized tools for detecting media manipulation, creating comprehensive datasets, researching digital evidence exchange across borders, engaging stakeholders, informing policymakers, and training forensic experts in digital media and AI. Through these efforts, DETECTOR seeks to safeguard digital evidence authenticity and enhance forensic capabilities to counter AI-driven media manipulation across Europe

The ETN on PErsonalized Robotics as SErvice Oriented applications - PERSEO - aims at training a new generation of research and professional figures able to face the research challenges of the market of personal robots. The personal robotics domain presents several research challenges mainly related to the need for a high degree of personalization of the robot behaviour with respect to the specific user’s needs and preferences. Companies need to build solutions rooted in a deeper analysis of humans’ specificities before developing products for people. At the same time, academia needs to nurture the development of an extended research community with a set of interdisciplinary skills to investigate different robot’s capabilities for understanding and modelling the interaction with human beings, for adapting the robot’s behaviour to the context, and software integration mechanisms that allow an easy personalized configuration approach to limit the static and costly customization processes of a novel robotic system. The PERSEO’s research program is organized into three Research Themes aimed at investigating personalization of robot capabilities at different levels of possible human-robot interaction, namely “Physical”, “Cognitive”, and “Social”. This requires a set of research skills ranging from computer science and AI to automation, ethics, and psychology. Fellows will deepen their knowledge in projects covering a specific research theme but, through training events, secondments, and peer collaborations will gain extensive knowledge in other areas so leading to a multidisciplinary research programme and the integration with other projects to achieve the proposed Integration Milestones. The project also aims at training Early Stage Researchers to address social, legal, and ethical issues that arise by the uptake of personal robots, as such skills are fundamental to achieve technological innovation which aligns with European social, ethical al legal values.