Seaborne trade underpins global logistics chains and regional economic resilience, yet maritime piracy continues to impose significant safety, security, and operational risks on maritime transport systems. This study advances piracy risk analysis by developing a cost-sensitive multi-graphs attention network (CSmGAT) that explicitly accounts for the spatio-temporal heterogeneity of piracy behaviour and the pronounced class imbalance across attack types. Multiple complementary graph structures are formulated to represent geopolitical conditions, regional economic activity, and spatial proximity, allowing the underlying risk environment to be modelled as a multi-layered interaction network. A multi-graph attention mechanism is employed to adaptively refine these structures by down-weighting weak or spurious dependencies, thereby improving the fidelity of the learned risk representations. To address the unequal distribution of piracy categories, a cost-sensitive learning formulation is integrated to enhance minority-class recognition without compromising overall system performance. Using a global maritime piracy dataset containing 7391 records covering 1994-2020, the CSmGAT model achieves superior performance relative to nineteen state-of-the-art statistical and machine-learning baselines in terms of evaluation metrics such as overall summary score (SS), Macro-F1 (mF1), and Macro-Gmean (mGmean). In addition, the framework yields interpretable risk insights by quantifying the relative influence of key explanatory factors through pseudo-elasticity analysis. The resulting approach provides a robust, interpretable, and operationally relevant tool for analysing piracy risks, supporting maritime security planning, and strengthening the reliability and resilience of international shipping systems.
The mid-Holocene decline in elm (Ulmus) pollen frequencies is perhaps the most debated and researched pollen-analytical feature of vegetation history in northwest Europe, with various causes or combination of causes proposed to explain it. It has a significant radiocarbon age range in Britain, but its timing in the early stages of Neolithic settlement suggests that subsistence farming activities probably played a role as well as factors such as disease and climate change. With these variables unproven, we have investigated ascospores of the wood-rot fungus Ustulina deusta as an independent proxy indicator of elm tree mortality, as the distinctive spores are often stratified in Elm Decline levels. Inspection of 20 sites in north Britain shows the distinct association of U. deusta with the Elm Decline, although with considerable variation between sites in the amplitude and shape of the U. deusta curve across the Elm Decline levels. U. deusta relies for successful infection on physically damaged trees, and we contend that girdling of elms by early Neolithic farmers to provide clearings for cereal cultivation and cattle grazing provided the conditions for U. deusta infection. Curves for Plantago lanceolata and Sporormiella, other indicators of herbivore presence, mirror the U. deusta curve, supporting this hypothesis. We conclude that the behaviour of the U. deusta curve at the Elm Decline supports early Neolithic animal husbandry and woodland manipulation as a primary cause of the mid-Holocene fall in elm populations.
Mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) lead to accumulation of proteins aggregates in airways. Mutated CFTR promotes transglutaminases-mediated crosslinking of beclin 1, a positive regulator of autophagy, to induce accumulation of LC3-binding protein p62 and prevent autophagic degradation of aggregates.
The origin of obscuration in active galactic nuclei (AGN) is still a matter of contention. It is unclear whether obscured AGN are primarily due to line-of-sight effects (Orientation model), a transitory, dust-enshrouded phase in galaxy evolution (Evolution models), or a combination of both. The role of an inner torus around the central supermassive black hole also remains unclear in pure Evolution models. We use cosmological semi-analytic models and semi-empirical prescriptions to explore obscuration effects in AGN at cosmic noon, in the range 1 < z < 3. We consider a realistic object-by-object modelling of AGN evolution including different AGN light curves (LCs) composed of phases of varying levels of obscuration, usually (but not uniquely) with a larger degree of obscuration before the peak of AGN activity, mimicking the possible clearing effects of strong AGN feedback. Evolution models characterized by AGN LCs with relatively short pre-peak obscured phases followed by more extended optical/ultraviolet (UV) visible post-peak phases, struggle to reproduce the high fraction of obscured AGN at z similar to 2-3 inferred from X-ray surveys. Evolution models characterized by AGN LCs with sharp post-peak declines or persistent or multiple obscuration phases are more successful, although they still face challenges in reproducing the steady drop in the fractions of obscured AGN with increasing luminosity measured by some groups. Invoking a fine-tuning in the input LCs, with more luminous AGN defined by longer optical/UV visible windows, can improve the match to the decreasing fractions of obscured AGN with luminosity. Alternatively, a long-lived central torus-like component, with thickness decreasing with increasing AGN power, naturally boosts the luminosity-dependent fractions of obscured AGN, suggesting that small-scale orientation effects may still represent a key component even in Evolution models. We also find that in our models major mergers and starbursts, when considered in isolation, fall short in accounting for the large fractions of highly obscured faint AGN detected at cosmic noon.
