Science News for January 10, 2026

Clearing the 'traffic jam' in nuclear detection: fast FPGA algorithm enhances neutron-gamma discrimination

A new bipolar cusp-like pulse-shaping algorithm has been proposed to reduce pile-up events and improve energy spectrum accuracy. The algorithm achieves real-time processing of millions of signals per second and demonstrates high precision in neutron counting.

SourceNuclear Science and Techniques·JournalNuclear Science and Techniques·TypeExperimental study·DateJan 10, 2026

Bayesian neural network evaluation method on the neutron-induced fission product yields of Thorium-232

Researchers developed a Bayesian neural network framework to predict thorium-232 fission yields, addressing sparse data gaps and incorporating physical constraints. The approach demonstrates strong agreement with experimental measurements and offers a systematic method for nuclear data evaluation with quantified uncertainties.

SourceNuclear Science and Techniques·JournalNuclear Science and Techniques·TypeComputational simulation/modeling·DateJan 10, 2026

Eye for trouble: Automated counting for chromosome issues under the microscope

A machine-learning-based algorithm developed by Tokyo Metropolitan University researchers can accurately count sister chromatid exchanges (SCEs) in chromosomes, giving a more objective measurement. The accuracy rate is 84%, which could help diagnose disorders like Bloom syndrome with greater consistency.

SourceTokyo Metropolitan University·JournalScientific Reports·DateJan 10, 2026