Space debris endangers future space missions — but there’s a way to clean it up
Peer-Reviewed Publication
Updates every hour. Last Updated: 2-Apr-2026 12:16 ET (2-Apr-2026 16:16 GMT/UTC)
High up in the earth’s orbit, millions of human-made objects large and small are flying at speeds of over 15,000 miles per hour. The objects, which range from inactive satellites to fragments of equipment resulting from explosions or collisions of previously launched rockets, are space debris, colloquially referred to as space junk. No matter the size, all of them create danger for operational satellites and spacecraft. Cleaning up space junk is technologically challenging and expensive—and there are currently no incentives for countries or private companies to do so. Without binding international regulations or an enforceable "polluter pays” principle with consequences for non-compliance, the circumstances have led to a "cosmic free-for-all." A new study proposes a way to fix this problem.
A University of Texas at Dallas researcher and his collaborators have developed an artificial intelligence (AI)-assisted tool that makes it possible for visually impaired computer programmers to create, edit and verify 3D models independently.
The tool, A11yShape, addresses a challenge for blind and low-vision programmers by providing a method for editing and verifying complex models without assistance from sighted individuals. The first part of the tool’s name is a numeronym, a number-based contracted word that stands for “accessibility” and is pronounced “al-ee.”
Higher plant diversity in agricultural grasslands increases yields with lower inputs of nitrogen fertilizer. That is the headline finding of a landmark, international study led by Trinity College Dublin that paints a promising picture for more sustainable agriculture.
And in further good news, the research shows that under warmer temperatures, the yield benefits of more diverse grasslands further increase. This highlights the climate adaptation potential of multispecies mixtures in an era where the global climate crisis is driving rising temperatures in many countries.
In this study, the researchers considered whether adding more species (up to two grasses, two legumes, and two herbs) to these grasslands and creating ‘multispecies mixtures’ could maintain or improve yields while reducing the reliance of nitrogen fertilizers that have negative environmental impacts.
The results showed that multispecies mixtures achieved high yields due to strong grass-legume and legume-herb synergistic interactions – the yield of the mixtures was much greater than the sum of the parts.
MIT researchers developed a smarter way for an LLM to allocate computation while it reasons about a problem. Their method lets the model dynamically adjust its computational budget based on the difficulty of the question and the likelihood that each partial solution will lead to the correct answer.