New research has found that households with solar panels could boost their returns by selling surplus power directly to their neighbours, known as peer-to-peer (P2P) energy sharing, helping to stabilise the electricity grid and negotiating a better price than retailers currently offer.

Scientists from the Icahn School of Medicine at Mount Sinai, working in collaboration with a team from the University of Texas at El Paso, have developed a novel computational framework for understanding how a region of the brain known as the striatum is involved in the everyday decisions we make and, importantly, how it might factor into impaired decision-making by individuals with psychiatric disorders like post-traumatic stress disorder and substance use disorder.

While biofuels may be part of the solution to replace fossil fuels and reduce climate-warming carbon emissions, bioenergy needs a new “climate-smart” policy to ensure that it produces both low-carbon products and promotes carbon sequestration, according to Madhu Khanna and colleagues. In this Policy Forum, Khanna et al. note that current policies to promote bioenergy in the United States, such as the Renewable Fuel Standard and Low Carbon Fuel Standard, do not distinguish between carbon intensities (CI) of the different farming practices (from tillage to fertilizer use) used to produce biofuels. They also do not account for the carbon sequestration produced by biofuel feedstocks. They suggest that new biofuel policies should include accounting of farming and production practices that reduce direct emissions and increase soil carbon sequestration. “Such a policy could lower the barriers for farmers to obtain credit for their carbon sequestration by bundling the market value of the crop with its CI and being sold into a single market for a carbon-differentiated biofuel feedstock rather than in two separate markets (a feedstock market and a carbon market),” Khanna et al. write.

University of Oregon bioengineer Calin Plesa has developed technology that creates massive, high-quality biological datasets at unprecedented speed and scale, solving a critical bottleneck that has prevented AI from tackling biology's biggest challenges—from studying cancer-associated genes to designing new proteins to accelerating drug development.