Can public health experts make a forecast for the flu or another infectious disease as accurately as a computational model? 

Thomas McAndrew, assistant professor, Department of Biostatistics and Health Data Science in Lehigh University’s College of Health, has received an award from the National Science Foundation (NSF) to research and develop a novel approach to forecasting. His project, “IHBEM: Enhancing Influenza Forecasting Through an Integrated Platform for User-Generated Temporal Forecasts,” will help improve evidence-based public health decision making for infectious diseases.

Scientists from Sichuan University have developed a new platform that combines large language models and quantum computing to predict Salmonella antimicrobial resistance. Their research, published in Engineering, aims to address the inefficiencies of traditional prediction methods and the challenges posed by high-dimensional data and sample imbalance.

Quantum Base has become the first ever Lancaster University spin out to float on the London Stock Exchange following its successful fundraising and admission to trading.

Quantum Base’s ordinary shares are now trading on the LSE AIM market under the ticker “QUBE”. https://www.lse.co.uk/SharePrice.html?shareprice=QUBE&share=Quantum-Base

The successful listing on AIM follows £4.8 million fundraising.

Counterfeiting is estimated to cost businesses and tax authorities $2.8 trillion in lost revenue annually. Quantum Base’s atomic-level anti-counterfeit Q-ID solution can be utilised in a vast number of end markets without requiring a change of existing consumer behaviour, or any further hardware or infrastructure.

For the first time, ETH materials scientists are measuring the rolling friction of tiny, micrometre-sized particles. These measurements permit them to better understand everyday products such as concrete.

A new, exploratory study has revealed statistical links between the performance of medical detection dogs and their scores on behavioral and affective tests, finding that more “optimistic” dogs tended to perform better overall on detection tasks, but “pessimistic” dogs had higher scent detection specificity. Sharyn Bistre Dabbah of the University of Bristol, U.K., and colleagues present these findings in the open-access journal PLOS One on April 9, 2025.