The Research Centre in Robotics and Underwater Technologies (CIRTESU) at the Universitat Jaume I conducted this week, at the PortCastelló facilities, wireless communication tests between a surface robot and the award-winning robot fish, recognized as the best work in marine automation nationwide during the Spanish Automation Committee conference held in early September in Cartagena.

The jury particularly valued the combination of advanced mechatronic design and the integration of different systems, which make the robot fish a leading research and aquatic environment inspection platform, tested in real experiments both in the CIRTESU pool and in the waters of the Port of Castelló. With this recognition, the UJI consolidates the research excellence of its teams and projects its impact on sustainable applications in the aquaculture sector.

According to CIRTESU researcher Raúl Marín, “It is essential for us to carry out cyclic and gradual research, first in university facilities and then in a realistic environment, like the Port of Castelló, where the collaboration of the Port Authority staff has been key to achieving the progress made.”

You might think adding crop straw to soil is a no-brainer: it enriches the earth, boosts organic matter, and supports sustainable farming. But what if the weather could turn this green practice into a hidden risk for heavy metal pollution? A groundbreaking new study, published on August 1, 2025, in Carbon Research—has uncovered the complex, climate-driven dance between straw incorporation, soil organic matter, and lead (Pb) mobility. And the results are reshaping how we think about safe soil remediation in a changing climate. Led by Dr. Song Cui from the International Joint Research Center for Persistent Toxic Substances (IJRC-PTS) and Research Center for Eco-Environment Protection of Songhua River Basin, Northeast Agricultural University, Harbin, China, in collaboration with Dr. Yongzhen Ding from the Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin, China, this research dives deep into the invisible world of dissolved organic matter (DOM)—and how it can either lock away or unleash toxic metals.

An automatic diagnosis system based on wearable augmented reality (AR) glasses and an artificial intelligence (AI)model was developed to assess leafminer damage levels, and it achieved 92.38% accuracy. The DeepLab-Leafminer model incorporated an edge-aware module and the Canny loss function into the DeepLabv3+ model, which enhanced its ability to segment the leafminer damaged area in leaves.A mobile application and a web platform were developed to display the diagnostic results of leafminer damage levels for surveyors to guide their scientific decisions for leafminer prevention and control.