New strategic support for UK clean industry with £2 million funding boost
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Updates every hour. Last Updated: 2-Dec-2025 19:11 ET (3-Dec-2025 00:11 GMT/UTC)
A mathematician who has helped transform our understanding of population genetics, one of the most eminent chemical engineers in China, and leading international innovators in biotechnology and retail marketing have been awarded Honorary Degrees from Heriot-Watt University as part of its 2025 winter graduation programme.
New research finds that a combination of extreme climate events, sea-level rise and land subsidence could create larger and deeper floods in coastal cities in future.
The study focused on Shanghai in China, which is threatened with flooding by large and strong typhoons, or tropical storms, producing storm surges and waves. To avoid disaster a major adaptation effort is required - which will almost certainly include raising defences and constructing mobile flood barriers, like those seen at the Thames Barrier in London. However, the team warn there is also the risk of “catastrophic failure” of defences due to rising water levels, especially due to the combination of subsidence, sea-level rise and higher surges during typhoons, as occurred in New Orleans during Hurricane Katrina in 2005.
Overreliance on generative AI risks eroding new and future doctors’ critical thinking skills, while potentially reinforcing existing data bias and inequity, warns an editorial published in the online journal BMJ Evidence Based Medicine.
In a remarkable stride towards environmental sustainability, researchers at the Department of Biotechnology and Medical Engineering, National Institute of Technology Rourkela, India, have developed a novel approach to predict the adsorption capacity of biochar using machine learning. This breakthrough, detailed in their latest study titled "Machine Learning-Driven Prediction of Biochar Adsorption Capacity for Effective Removal of Congo Red Dye," offers a powerful solution to combat dye pollution.
Researchers examined five AI models on multiple genomic tasks to see how well they performed
Models performed well overall, with each having strengths and weaknesses based on the desired task
Study provides a framework for researchers to choose optimal AI models for specific genomic tasks