This study leverages advanced genomics and machine learning to refine the understanding of key fruit quality traits in peaches. Using whole-genome resequencing data from an F1 progeny of two distant peach cultivars, the researchers constructed an ultra-high-density genetic map, identifying key quantitative trait loci (QTLs) for traits such as fruit shape, color, and maturity. Notably, the study introduces machine learning models for more accurate phenotyping of fruit color, revealing two previously undetectable QTLs for peach flesh color variation. These innovations provide a new framework for precision breeding, enhancing peach quality and other complex traits through improved mapping and phenotyping strategies.

Researchers have developed a novel computational imaging system that integrates optical compression and deep learning to achieve high-speed video capture using only 5% of the data required by conventional cameras. The system successfully visualized Leidenfrost droplet dynamics at 1,200 frames per second, delivering performance comparable to commercial high-speed cameras while significantly reducing cost and storage requirements.

Tech startup Atomic Canyon used the Frontier supercomputer to train nuclear-specific AI models to radically speed up document search and analysis capabilities for nuclear reactors. The AI models are designed to radically reduce the time, labor and resources the nuclear industry spends searching the millions upon millions of complex nuclear documents related to parts, maintenance records, engineering evaluations, regulations and plant procedures. Once fully developed, the open-source AI models could be used in plants all across the country.

Recently, a team of researchers led by Prof. DU Zhixue from the Guangzhou Institute of Geochemistry of the Chinese Academy of Sciences (GIGCAS) has discovered that substantial amounts of water could have been efficiently "locked away" deep within the mantle as it crystallized from a molten state.

The SETI Institute’s Artist in Residency (AIR) program announced that American artist Adrien Segal is the recipient of the Planetary Futures Public Art Residency. This research-creation residency invites the artist to collaborate with scientists whose work advances planetary science, with a focus on climate research. By connecting artistic practice with scientific discovery, the residency aims to foster dialogue, raise awareness, and inspire collective action, emphasizing how the study of other planets can provide valuable perspectives to better understand and address climate-related issues here on Earth. This two-year residency includes a $30,000 stipend.

Based in Oakland, CA, Adrien Segal is an internationally exhibited artist with work featured in books, academic journals and galleries around the world. She has participated in numerous Artist Residencies across the US, Canada, and Europe, and has work in permanent collections including the City of Homer, Alaska, the Museum of Art in Wood in Philadelphia, and the National Academy of Science in Washington, D.C. In 2022, Segal was a US-UK Fulbright Scholar with the Duncan of Jordanstone College of Art and Design at the University of Dundee in Scotland. Past appointments include the Latham Fellowship at IIT Institute of Design in Chicago, a Visiting Artist at San Diego State University, Benchspace Cork in Ireland, and the University of Lethbridge in Canada.

"I'm excited to welcome Adrien into the SETI Institute's Artist in Residence program," said Bettina Forget, SETI AIR Program Director. "She weaves together science, landscape, data, and materiality to create cross-disciplinary sculptural works that evoke deep emotional responses and a unique sense of place. I look forward to working with Adrien as she starts diving into the research at the SETI Institute."