This review synthesizes collective insights from the 1st China–Australia–New Zealand Water Quality Modeling Symposium (CANWaS 2024) and outlines a roadmap for strengthening international collaboration in surface water quality modeling. Organized by Jiping Jiang from Harbin Institute of Technology and Danlu Guo from Australian National University, an international research team identifies shared priorities, mutual interests, and actionable pathways—including best-practice guidelines, open knowledge sharing, and joint technological innovation—to advance predictive capacity and policy impact for global freshwater management.

A new Perspective in Science Bulletin explains why computational pathology must move beyond accurate algorithms. To help in real hospitals, AI tools need to be interpretable, reportable, cost-aware, and tested in routine clinical workflows.

A joint research team from Saitama University and the University of the Ryukyus has developed an energy management framework for recirculating aquaculture systems that coordinates renewable energy, battery storage, and aerator operation while maintaining dissolved oxygen levels needed to keep fish safe. By combining experimental data from Malabar grouper with model predictive control, the framework reduced annual electricity use by 17.8% and CO₂ emissions by 31.9% in simulations, while also helping maintain dissolved oxygen levels during power outages.