University of Sydney and startup Dewpoint Innovations have developed paint-like substance that reflects 97 percent of sunlight and can cool the painted surface by up to six degrees below ambient temperature, cooling building and passively extracting water. The innovation could help cool urban heat islands and supplement tank water.

A team of researchers from the Federal University of Technology Owerri in Nigeria has highlighted a promising new way to cut diesel engine pollution without sacrificing performance. Their review of global research on Water-in-Diesel Emulsion (WiDE) technology shows that blending small amounts of water into diesel fuel can dramatically reduce harmful emissions while maintaining or even improving engine efficiency.

A sweeping new study has uncovered global patterns in how bacteria thrive and interact within lakes and reservoirs, offering new insights into the invisible forces that sustain freshwater ecosystems. The research, led by scientists from Xi’an University of Architecture and Technology, analyzed hundreds of samples from around the world to understand how geography, temperature, and nutrients shape bacterial communities in water and sediments.

A research team has developed pioneering technology that enables human kidney organoids to be produced on a scalable basis. These organoids can then be combined with pig kidneys outside the body and transplanted back into the same animal in a viable manner.

The experiment, led by the Institute for Bioengineering of Catalonia (IBEC), is in the preclinical phase. It confirms the safety and viability of the procedure, paving the way for future trials involving humans.

In the long term, this approach could help to extend the useful life of organs intended for transplantation and provide an alternative therapy for patients with chronic kidney disease.

Critical concerns regarding the security and privacy of information transmitted within Internet of Medical Things systems have increased greatly, since these systems manage and generate substantial amounts of sensitive private data. Current traditional security methods have not yet adapted to evolving cyber threats, making the need for data security in medical settings crucial. Recently, a security framework based on blockchain technology and distributed reinforcement learning has been presented to address these challenges. The new framework ensures that data are stored securely and transmitted reliably while minimizing resource usage, and it also enables security measures to adapt to changing threat patterns and enhance system resilience against attacks. In summary, the new methods demonstrated improved memory consumption and transaction latency compared to existing approaches, while maintaining high data throughput. This work was published in Intelligent Computing, a Science Partner Journal, under the title “Privacy-Preserving Strategies in the Internet of Medical Things Using Reinforcement Learning and Blockchain” by Dounia Doha and Ping Guo.

University of Texas at Dallas researchers have taken an important step forward in building a neuromorphic computer by creating a small-scale prototype that learns patterns and makes predictions using fewer training computations than conventional AI systems. Their next challenge is to scale up the proof-of-concept to larger sizes.