The “Wakuwaku Aira Dinosaur Museum Exhibition,” organized by Aira City in cooperation with Okayama University of Science, concluded successfully on December 27, 2025, attracting a total of 11,580 visitors over eight days. Held at Aira Square in the city’s newly completed municipal office building, the exhibition showcased approximately 20 dinosaur-related specimens, including a full-body tyrannosaurid skeletal reconstruction, a Triceratops skull, and Tarbosaurus fossils.

The exhibition emphasized hands-on learning and research outreach, featuring a recreated excavation site from the Gobi Desert in Mongolia, along with panels and videos introducing paleontological fieldwork. Daily workshops allowed children to experience fossil replica making and fossil cleaning activities. Students from the Faculty of Biosphere-Geosphere Science served as guides, providing accessible explanations of dinosaur research to visitors.

On the final day, an educational lecture titled “Digging for Dinosaurs in Mongolia!” was delivered by Masato Fujita, professor of dinosaur paleontology and director of the Museum of Dinosaur Research at Okayama University of Science, attracting approximately 150 attendees.

Originally expected to draw around 5,000 visitors, the exhibition’s turnout more than doubled projections, highlighting strong public interest in dinosaurs and science education. Organizers noted that the combination of authentic research content, interactive experiences, and student-led explanations contributed significantly to the exhibition’s success.

As the FDA moves to finalize a rule requiring front-of-package (FOP) nutrition labels on most packaged foods and beverages in the US, new research suggests that while the proposed “Nutrition Info Box,” showing levels of saturated fat, sodium, and added sugar, was found to work best for consumers who had higher nutrition literacy, it may not be the most effective choice for all Americans. The findings from the study in the American Journal of Preventive Medicine, published by Elsevier, provide timely evidence on how FOP labels will help consumers identify healthier foods, which could ultimately support healthier eating.

Grammatical error correction (GEC) is a key task in natural language processing (NLP), widely applied in education, news, and publishing. Traditional methods mainly rely on sequence-to-sequence (Seq2Seq) and sequence-to-edit (Seq2Edit) models, while large language models (LLMs) have recently shown strong performance in this area.

Researchers have developed a novel generative AI model, called Collaborative Competitive Agents (CCA), that significantly improves the ability to handle complex image editing tasks. This new approach utilizes multiple Large Language Model (LLM)-based agents that work both collaboratively and competitively, resulting in a more robust and accurate editing process compared to existing methods. This breakthrough allows for a more transparent and iterative approach to image manipulation, enabling a level of precision previously unattainable. The findings were published on 15 November 2025 in Frontiers of Computer Science, co-published by Higher Education Press and Springer Nature.