The proportion of global education aid being committed to early childhood education - which was already well below international targets - has started to fall, according to new research which suggests that the internatonal community is starting to turn its back on the world's most vulnerable children. These findings are from the annual donor 'scorecard' produced by University of Cambridge researchers for the charity Theirworld. This tracks how much international aid is being spent on education for the critical early years, up to age five. The authors suggest the true picture could be far worse than that presented in the report, as the latest available data are from 2023, the beginning of what they describe as a new era of "cuts and conflict". Since then, 99% of United States funding for basic education has been axed by the Trump administration and Britain and Switzerland have also scaled back spending.  

The Transdisciplinary Research Areas (TRAs) Modelling and Life and Health at the University of Bonn have presented their €100,000 research prize, entitled “Modelling for Life and Health,” for the second time. The winners—Argelander Professor Ana Ivonne Vazquez-Armendariz and Schlegel Professor Jan Hasenauer—will be using their prize money to study the functions of “scavenger cells” in the lungs at the interface between mathematics and medicine.

An advanced genomic analysis of a multigenerational family is providing new knowledge about genetic mutations and their transmission, both the variants that are inherited and those that arise anew.

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, MIT researchers organized them into a “periodic table of machine learning” that can help scientists combine elements of different methods to improve algorithms or create new ones.

Given the multitude of conditions that must be optimized in synthesis routes, chemical synthesis remains a complex and multidimensional challenge. The rapid development of computational guidelines and machine learning (ML) techniques has brought exciting hope to this dilemma. A new study published in the journal National Science Review highlights the advancement of computationally guided and ML-assisted approaches in inorganic material synthesis.