Tracker to help manage Long COVID energy levels created by researchers
Peer-Reviewed Publication
Updates every hour. Last Updated: 10-Jun-2026 05:15 ET (10-Jun-2026 09:15 GMT/UTC)
The first study to test a digital tool designed to help people with Long COVID manage their energy levels has been developed by a team of researchers.
The paper published in Nature Communications is entitled “A Digital Platform with Activity Tracking for Energy Management Support in Long COVID: A Randomised Controlled Trial”.
In this study, funded by the National Institute for Health and Care Research (NIHR), people with Long COVID tried out a new app called “Pace Me” to help manage their energy levels.MIT researchers created a model that suggests promising ways to synthesize new materials for faster experimentation.
With one in four Singaporeans expected to be 65 and above by 2030, Duke-NUS inaugural ageing conference addressed themes such as technology, dementia care and social connectedness.
Duke-NUS’ Centre for Ageing Research & Education marks its 10th anniversary, with the conference highlighting the need for innovative policies and practices to enhance the quality of life for Singapore's ageing population.
Most African countries have in-use steel stocks below 1 tonne per capita—less than one-twentieth of industrialised levels. Meanwhile, €10 billion in European subsidies for domestic green iron has yielded only one project reaching final investment decision. A new article in Technology Review for Carbon Neutrality argues these are not separate problems: they share a solution. Green iron produced in developing country "sweetspots" could supply European steelmakers at 27% lower cost—delivering a competitive decarbonised EU steel industry while providing the bankable anchor investment that developing countries need to build their own steel industries and infrastructure in parallel.
The Hebrew University of Jerusalem is proud to congratulate Prof. Benjamin Weiss of the Einstein Institute for Mathematics on being awarded the Israel Prize in the field of mathematics, computer science, and computer engineering research.
A research team led by Professor Fu Jin has developed an innovative method integrating Monte Carlo (MC) simulations with deep learning-based denoising technology to rapidly and accurately generate high-quality EPID transmission dose (TD) data. This breakthrough significantly enhances the efficiency of patient-specific quality assurance (PSQA), supporting the advancement of online adaptive radiation therapy (ART) in clinical practice.