Scientists at NYU Abu Dhabi have created an AI model that forecasts solar wind speeds up to four days in advance with far greater accuracy than existing methods. The breakthrough, published in The Astrophysical Journal Supplement Series, could protect satellites, navigation systems, and power grids from harmful space weather events.

Scientists created the most accurate three-dimensional map of star-formation regions in our Milky Way galaxy, based on data from the European Space Agency’s Gaia space telescope. This map will teach us more about these obscure cloudy areas, and the hot young stars that shape them.  

The first ab initio calculation of the rarest electromagnetic transition in atomic nuclei, the hexacontatetrapole E6 transition in ⁵³Fe, has been performed. Using the valence-space in-medium similarity renormalization group (VS-IMSRG) methods with realistic nuclear force and bare nucleon charges, the study has successfully explained both the excitation energies and electromagnetic decay rates of the unique T_1/2 = 2.54-minutes J^π = 19/2^- isomer at 3.0 MeV. This study provides unprecedented insights into nuclear structure under extreme conditions and validates ab initio approaches for describing the high-multipole electromagnetic transitions in atomic nuclei. The research demonstrates that the formation of 19/2^- isomer arises from the pure 0f_7/2 orbital configuration.

Pharmaceutical scientists at the National University of Singapore (NUS) have developed a method that can measure the kinetic efficiency of an enzyme against more than 200,000 potential peptide substrates in a single experiment. 

Characterising the interactions between enzymes and their substrates is a fundamental task in biochemistry, essential for engineering new biocatalysts, understanding disease mechanisms, and designing therapeutics. While existing techniques can study many enzymatic reactions in parallel, scaling such methods to comprehensively analyse an enzyme's preferences across a vast space of possible substrates remains a practical challenge.

Assistant Professor Alexander Vinogradov from the NUS Department of Pharmacy and Pharmaceutical Sciences has developed a strategy called DOMEK (mRNA-display-based one-shot measurement of enzymatic kinetics) that addresses this need.

If you think a galaxy is big, compare it to the size of the Universe: it’s just a tiny dot which, together with a huge number of other tiny dots, forms clusters that aggregate into superclusters, which in turn weave into filaments threaded with voids—an immense 3D skeleton of our Universe.

If that gives you vertigo and you’re wondering how one can understand or even “see” something so vast, the answer is: it isn’t easy. Scientists combine the physics of the Universe with data from astronomical instruments and build theoretical models, such as EFTofLSS (Effective Field Theory of Large-Scale Structure). Fed with observations, these models describe the “cosmic web” statistically and allow its key parameters to be estimated.

Models like EFTofLSS, however, demand a lot of time and computing resources. Since the astronomical datasets at our disposal are growing exponentially, we need ways to lighten the analysis without losing precision. This is why emulators exist: they “imitate” how the models respond, but operate much faster.

Since this is a kind of “shortcut,” what’s the risk of losing accuracy? An international team including, among others, INAF (Italy), The University of Parma (Italy) and the University of Waterloo (Canada) has published in the Journal of Cosmology and Astroparticle Physics (JCAP) a study testing the emulator Effort.jl, which they designed. It shows that Effort.jl delivers essentially the same correctness as the model it imitates—sometimes even finer detail—while running in minutes on a standard laptop instead of a supercomputer.