An AI-Based Digital Scanner for Detection in Beekeeping.

Beekeeping is a crucial agricultural practice that significantly enhances environmental health and food production through effective pollination by honey bees. However, honey bees face numerous threats, including exotic parasites, large-scale transportation, and common agricultural practices that may increase the risk of parasite and pathogen transmission. A major threat is the mite, which feeds on honey bee fat bodies and transmits viruses, leading to significant colony losses.

Residues of agrochemicals in beebread as an indicator of landscape management.

The agricultural intensification represents a major threat to biodiversity, with negative effects on the ecosystem. In particular, habitat loss and degradation, along with pesticide use have been recognised as primary factors contributing to the actual global decline of pollinators. Here we investigated the quality of agroecosystems in the Emilia-Romagna region (Northern Italy) within the national monitoring project BeeNet.

Glucosinolate Bioactivation by Workers and Its Impact on Infection at the Colony Level.

The microsporidian fungus represents one of the primary bee infection threats worldwide and the antibiotic fumagillin is the only registered product for nosemosis disease control, while few alternatives are, at present, available. Natural bioactive compounds deriving from the glucosinolate-myrosinase system (GSL-MYR) in Brassicaceae plants, mainly isothiocyanates (ITCs), are known for their antimicrobial activity against numerous pathogens and for their health-protective effects in humans. This work explored the use of and defatted seed meal (DSM) GSL-containing diets against natural infection in colonies.

Optimal percentage of inhibitory synapses in multi-task learning.

Performing more tasks in parallel is a typical feature of complex brains. These are characterized by the coexistence of excitatory and inhibitory synapses, whose percentage in mammals is measured to have a typical value of 20-30%. Here we investigate parallel learning of more Boolean rules in neuronal networks.