In the present paper different external surface treatments published in the literature as preventive solutions for improving the performance of existing concrete constructions are presented and discussed. They are categorized as repair materials for concrete conservation, protection surface methods against moisture and aggressive agent penetration, injection techniques for crack sealing and preventive repair solutions with smart functionalities. In a final section, the most extended testing methods for evaluating the effectiveness of the different repair solutions are summarized depending on the property to be enhanced: moisture control and resistance against penetration of aggressive agents. The review shows that although several possibilities exist for the repair of the existing constructions, there is a lack of comparative analysis between the different methodologies. SARCOS COST Action CA15202 stablishes as scientific objectives to carry out comparative studies including the most advanced solutions for the external repair of concrete, giving criteria for effectiveness assessment and defining robust and reliable methods for charactering the performance of the repaired structures.@en

We adopt an emerging and prominent vision of human-centred Artificial Intelligence that requires building trustworthy intelligent systems. Such systems should be capable of dealing with the challenges of an interconnected, globalised world by handling plurality and by abiding by human values. Within this vision, pluralistic value alignment is a core problem for AI– that is, the challenge of creating AI systems that align with a set of diverse individual value systems. So far, most literature on value alignment has considered alignment to a single value system. To address this research gap, we propose a novel method for estimating and aggregating multiple individual value systems. We rely on recent results in the social choice literature and formalise the value system aggregation problem as an optimisation problem. We then cast this problem as an ℓp-regression problem. Doing so provides a principled and general theoretical framework to model and solve the aggregation problem. Our aggregation method allows us to consider a range of ethical principles, from utilitarian (maximum utility) to egalitarian (maximum fairness). We illustrate the aggregation of value systems by considering real-world data from two case studies: the Participatory Value Evaluation process and the European Values Study. Our experimental evaluation shows how different consensus value systems can be obtained depending on the ethical principle of choice, leading to practical insights for a decision-maker on how to perform value system aggregation.@en