The assessment of the number of people exposed to natural hazards, especially in countries with strong urban growth, is difficult to be updated at the same rate as land use develops. This paper presents a remote sensing-based procedure for quickly updating the assessment of the population exposed to natural hazards. A relationship between satellite nightlights intensity and urbanization density from global available cartography is first assessed when all data are available. This is used to extrapolate urbanization data at different time steps, updating exposure each time new nightlights intensity maps are available. To test the reliability of the proposed methodology, the number of people exposed to riverine flood in Italy is assessed, deriving a probabilistic relationship between DMSP nightlights intensity and urbanization density from the GUF database for the year 2011. People exposed to riverine flood are assessed crossing the population distributed on the derived urbanization density with flood hazard zones provided by ISPRA. The validation against reliable exposures derived from ISTAT data shows good agreement. The possibility to update exposure maps with a higher refresh rate makes this approach particularly suitable for applications in developing countries, where urbanization and population densities may change at a sub-yearly time scale.

This article explores the use of participatory approaches to promote gender equality in academia, focusing on initiatives implemented in two universities. First, we look at the experience of the University of Deusto (Spain) in developing a handbook to integrate a gender perspective into teaching and research practises through an equality, diversity and inclusion lens (EDI). This initiative, carried out as part of the university’s Gender Equality Plan, featured active involvement from scholars representing the faculties of Law, Psychology, Social Sciences and Humanities, Engineering, Business, and Theology, as well as the university’s Social Responsibility Unit. It serves as a valuable example of how participatory strategies can effectively engage a wide array of institutional stakeholders in change-oriented actions. Promoting increased participation fosters a sense of ownership of the process and outcomes among stakeholders and strengthens institutional recognition. Second, we analyse the introduction of a "gender+-responsive curriculum" developed at the University of Genoa (Italy), as part of the university’s Gender Equality Plan. This initiative seeks to promote inclusion across all disciplinary subjects by incorporating current research that examines subject matters through the lens EDI, where relevant. The pilot implementation was undertaken in an undergraduate course focused on hydraulic engineering and hydrology, drawing guidance from various resources, including academic publications and EU-funded project reports. This initiative highlights the practical implications and challenges associated with interventions aiming to challenge conventional teaching and research norms from an EDI perspective, particularly in STEM fields. By exploring the experiences, obstacles and solutions associated with a gender+-responsive curriculum, we broaden our understanding of academia’s potential to advance gender equality, diversity, and inclusion. In examining the two experiences, we emphasise the theoretical underpinnings that underscore the importance of participatory approaches for promoting meaningful and enduring changes in academic institutions. Additionally, we highlight the ongoing challenges associated with implementing such changes and offer initial insights into potential strategies for overcoming these obstacles. Our goal is to ensure that gender and other intersecting diversity factors are not relegated to the edges of institutional priorities, but are instead mainstreamed into wider institutional practices.

Waste management under emergency conditions requires proper handling. The sudden closure of a strategic final disposal site can result in serious environmental and health hazards which need to be addressed. Furthermore, this situation requires the identification of new sites to be used for waste disposal. This study analysed the case-study of Genoa, Northern Italy, following the closure of the Scarpino landfill previously dedicated to the disposal of waste generated in this municipality. A multi-objective tool was developed and applied from long-term planning to day-to-day scheduling. A sensitivity analysis was performed on the basis of collected waste volumes, in order to study the utilization and actual rate of fulfilling of the plants according to the leading objective function. Considering all of the objective functions, the emissions optimization shows better behaviour in terms of simultaneous global accomplishment of each function. In this context, the introduction of a decision support system for waste management shows its usefulness in setting and effectively pursuing long-term targets in term of total costs, emissions generated by waste transport, and exploitation of single plants from a sustainability perspective.

The rapid deployment of AI reveals persistent socio-technical and data-driven biases that reflect profound epistemic limitations in knowledge production. These biases are not accidental, but symptomatic of deeper epistemic limitations in the way AI knowledge is produced — often by homogeneous teams within technocentric paradigms that exclude alternative perspectives. This paper argues that the underrepresentation of diverse social actors in AI development not only perpetuates inequality, but also severely limits the epistemic and ethical robustness of AI systems. The focus of this paper arises in particular from the preliminary findings obtained in the Horizon Europe project STEP, which highlight the potential of the framework to improve the inclusivity and trustworthiness of AI. The central thesis is that social diversity must be considered as an epistemic condition and not just an ethical or demographic ideal. Drawing on sociology, psychology and educational science, the authors show how integrating plural forms of knowledge, lived experiences and cultural perspectives into the design and development process can lead to AI systems that are more context-sensitive, equitable and trustworthy. Rather than proposing inclusion as an external corrective, this paper discusses a paradigm shift in AI development - a paradigm shift that embeds diversity into the infrastructure of knowledge production itself. The contribution of this paper is twofold. First, it proposes a theoretical model of integrative knowledge production that identifies mechanisms through which interdisciplinary collaboration can challenge dominant epistemologies and promote systemic reflexivity. Second, a participatory design framework is outlined to operationalise this model through concrete methodological tools, including dialogic co-design workshops, ethnographic participation in data selection and cross-functional team structuring. These practises aim to break through technocratic compartmentalisation by creating space for social critique and situated intelligence within AI development cycles. Finally, the authors reflect on the transformative potential of this approach and suggest that rethinking who is involved in AI knowledge production will not only change the outcomes of AI systems, but also the normative foundations of the technological future. From this perspective, ethical AI is not just explainable or compliant — it is structurally inclusive, responsive to different lifeworlds and open to critical reinvention.