Artificial light at night extends pollen season
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This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 7-May-2026 09:16 ET (7-May-2026 13:16 GMT/UTC)
20 January 2026 / Kiel. The renewal of deep waters in the North Atlantic has slowed markedly over the past three decades. This is shown by a new study from the GEOMAR Helmholtz Centre for Ocean Research Kiel, now published in the scientific journal Nature Communications. The study demonstrates that the “age” of water masses in the North Atlantic has been increasing continuously since the 1990s – an indication of a weakening of the Atlantic circulation system. The results suggest that this trend cannot be explained by natural variability alone, but instead represents a signal of anthropogenic climate change. A slowdown in ocean circulation has far-reaching consequences for climate regulation as well as for the ocean’s oxygen supply and its uptake of carbon.
Pūkeko use sound elements to create calls and combine them to create complex call sequences in order to expand the range of options for expressing themselves – these are the findings of an international team including Konstanz researchers. Until now, this behaviour had only been known in vocal learning animals, such as primates, whales or songbirds.
A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data networks for hidden connections – from gene functions and disease mechanisms to potential therapeutic approaches. BioPathNet was developed by teams at Helmholtz Munich and Mila – Quebec Artificial Intelligence Institute in Montreal, Canada. The researchers are now presenting the method in the journal Nature Biomedical Engineering.
Researchers developed ShapKAN, a deep learning model integrated into the AI4Min-PE platform (http://pe.ai4mineral.com), enabling instant prediction and visualization of key thermodynamic parameters up to 500 GPa. This open AI tool supports the discovery of new chemical behaviors of minerals and elements under extreme conditions.
In a study published in Earth and Planetary Physics, researchers analyzed atmospheric gravity wave (AGW) events observed in Dandong (northeastern China) and Lhasa (Tibetan Plateau) between 2015–2017. Using machine learning and ray-tracing methods, the team found significant differences in wave parameters and wave sources, driven by distinct geographical conditions and wind-filtering effects.
In a paper published in Earth and Planetary Physics, a scientific team presents a good correlation between temporal variations of the core magnetic field and the gravity field after separating the core mass transfer contributions in GRACE global gravity data combined with various global hydrological models. The correlation analysis between the main principal components of core magnetic and gravity signals reveals that the changes in the second time derivative of the core magnetic field coincide in trend with changes in the gravity field.