The increase in the use of the Internet, strongly boosted by the spread of COVID-19, has amplified the risk of involvement in cyberbullying and online grooming among minors. To date, most research on these phenomena has focused on middle and high school students, with fewer studies on younger children. The present study aims to fill this knowledge gap by measuring the spread of cyberbullying and online grooming in a sample of 410 primary school students in the city of Rome and by identifying the main individual and environmental predictors associated with the involvement of children in these phenomena using factor analysis. Results indicate that both cyberbullying and online grooming are widespread among respondents, showing common traits within the four latent dimensions identified. Screen time is among the main predictors of children’s involvement, together with parental supervision, phubbing behaviours, prosocial tendencies and family socio-economic background. These findings highlight the need for further studies on representative samples of this age group, as well as for a greater cooperative effort among schools, parents and caregivers to keep children safe in the virtual world.

Global wood fuel production can indicate opportunities and also challenges in sustainable development, forest management, and energy access. Estimates of wood fuel removals and charcoal production are essential for tracking global goals yet reliable measurements are rare. We synthesize existing understanding through a mechanistic, conceptual model and build on it to develop statistical models from official statistics and over 2000 newly identified data points. For 2019, we estimate 2525.7 million m³ of wood fuel removals globally, approximately 30% higher than previously understood. Our estimates are 50% higher in Africa and 40% higher in Asia, 10% lower in the Americas and 20% lower in Europe. Global production of wood charcoal is estimated at 70.5 million tonnes, approximately 50% higher than previous values; our estimates are 20% higher in Africa and 200% higher in Asia. These estimates describe global shifts in wood fuel removals and charcoal production and improve our understanding of the forest sector; they will likely underlie global models used to forecast future trends.

Methodology is described for fitting a fuzzy partition and a parsimonious consensus hierarchy (ultrametric matrix) to a set of hierarchies of the same set of objects. A model defining a fuzzy partition of a set of hierarchical classifications, with every class of the partition synthesized by a parsimonious consensus hierarchy is described. Each consensus includes an optimal consensus hard partition of objects and all the hierarchical agglomerative aggregations among the clusters of the consensus partition. The performances of the methodology are illustrated by an extended simulation study and applications to real data. A discussion is provided on the new methodology and some interesting future developments are described.