A new NASA-funded project led by UT San Antonio will examine how icy lunar soil, or regolith, behaves in the extreme cold found in the Moon’s permanently shadowed regions, primarily found in craters around the poles. The findings could help inform methods for extracting, transporting and processing resources on the Moon.

The work addresses a critical challenge for future missions that rely on in-situ resource utilization, or using resources found on the Moon rather than transporting them from Earth. Water ice in permanently shadowed regions is a potentially important resource, but researchers need to better understand how icy regolith will respond to excavation and handling.

The project, “Characterizing Physical and Mechanical Properties of Regolith at Cryogenic Conditions using the Multi-Planetary Surface Simulator (MPS2),” began this month and will receive $1 million over two years through NASA’s MUREP Space Technology Artemis Research (M-STAR) program, which supports research and workforce development at minority-serving institutions. NASA selected only 12 institutions nationwide for the highly competitive award.

As COP31 gets underway in Türkiye, new research led by the University of Plymouth has found that unclear regulations are preventing authorities from acting on evidence of suspicious vessel activity. The study analysed the rules governing almost 10,000 MPAs covering parts of Africa, Asia, Europe, North and South America, and Oceania, as well as around 120 pieces of national legislation - it found such clarity was not being provided in the vast majority of cases with only 4% of the legislation they examined containing specific reference to satellites and vessel tracking.

A new framework from Cambridge scholars argues that the real question for universities isn’t what AI can do, but whether teaching is designed so that AI enriches—rather than erodes—the space where educators exercise professional judgement.

For their work in rethinking sustainable farming in Africa and understanding what drives behavioral change in addition, Willy Mulimbi and Peter Soyster, respectively, are each a winner of the 2026 NOMIS & Science Young Explorer Award.

Conventional tillage remains deeply embedded in African smallholder agriculture, despite its association with soil degradation, lowered productivity, and biodiversity loss. Willy Mulimbi’s prize-winning essay examines how conservation agriculture, which emphasizes soil preservation and crop diversity, could improve agricultural sustainability and food security among African smallholder farmers. His research in the Democratic Republic of the Congo (DRC) shows that adopting these practices depends not only on economic and environmental conditions but also on access to training, credit, farmer networks, cultural traditions, and gender-related risks. Field experiments found that CA improved soil health and cowpea yields without requiring fertilizers or herbicides, while also reducing pressure on forests and potentially protecting women from dangers associated with traveling long distances to find farmland. However, urban consumers showed no significant willingness to pay more for sustainably produced crops, suggesting that wider adoption will depend on government support and education rather than consumer demand. Ultimately, Mulimbi argues that expanding CA requires addressing deeply rooted farming traditions and socioeconomic barriers to help farmers build more resilient and productive agricultural systems. “Resilience emerges not from forcefully shaping the land, but from working with natural processes,” writes Mulimbi. “I seek to map how African farmers can transition from tradition-bound tillage to an ecological stewardship mindset to enable them to adapt to climate change, strengthen food security, and reclaim autonomy over their landscapes and livelihoods.”

In the other prize-winning essay, Peter Soyster argues that traditional addiction research, which relies on group averages to develop treatments, often fails to account for the differences in individual behavior and real-world experiences. To address this, Soyster’s research uses a precision-medicine approach to addiction psychology, combining frequent smartphone-based surveys with machine learning to develop predictive behavioral models tailored to each person. In a study of cannabis use, these individualized models predicted future use with substantially greater accuracy than conventional group-based models (average accuracy score of 0.87 versus 0.68), while revealing that the factors influencing substance use can vary considerably between individuals. Soyster suggests that personalized models could help clinicians identify specific behavioral triggers and develop more targeted interventions that move addiction treatment beyond one-size-fits-all strategies. “Decades of group-based research have given us a vital, generalized understanding of the possibility space of human psychology,” Soyster writes. "By bridging the humanistic methods of community-partnered social science with the mathematical precision and personalized modeling of the life sciences, we can take the necessary next step.”

A new theory predicts how a particle moving at close to the speed of light is likely to be pushed and pulled by a fluid as it flies through it. The research could help scientists understand the quark-gluon plasma that existed in the universe’s first moments.