Researchers introduce a novel generative AI-driven framework, MMCN (Memory-aware Multi-Conditional generation Network), for forecasting future urban layouts by jointly considering building density, building height, transportation networks, and historical development patterns. Leveraging a generative architecture-enhanced diffusion model with multi-conditional control, semantic prompt fusion, and spatial memory embedding, MMCN offers a novel approach to modeling complex urban evolution. This framework provides a powerful tool to explore sustainable urban development, demonstrating AI’s transformative potential in urban design.

Maize, rice and cassava drive more deforestation than major export-oriented crops like cocoa, coffee, and rubber. This has been shown by researchers from Chalmers University of Technology, Sweden, in the most comprehensive global survey of how different commodities are causing deforestation. The study confirms the major impact of meat production, but reveals several overlooked drivers of deforestation.

CHANGWON, South Korea — Korea Institute of Materials Science (KIMS), led by President Chuljin Choi, announced that a research team led by Dr. Dahee Park at the Hydrogen Energy Materials Research Center has successfully developed a high-performance catalyst that significantly enhances the oxygen evolution reaction (OER), a key process in alkaline water electrolysis. The team achieved this by partially substituting molybdenum oxide (MoOx) with iron (Fe), enabling simultaneous control of lattice structure and oxygen vacancies. The study presents a new catalyst design strategy that delivers performance and stability comparable to precious metal catalysts while utilizing low-cost materials.