An AI tool can quickly suggest possible candidates for the chemical structures of psychoactive "designer drugs" from a simple analysis. The tool could fast-track the development of lab tests which screen the use of drugs that have similar effects to substances such as cocaine and heroin, but have been designed to evade detection. "Our method could cut down the time required to identify a new designer drug from weeks or months to just hours," says Michael Skinnider at the University of British Columbia in Vancouver. Skinnider and his colleagues created a machine learning tool called DarkNPS by training it with chemical structures of around 1700 known designer drugs, collected from forensic labs around the world. The training set included tandem mass spectrometry results for each drug, which is a common technique that provides information on the mass of a molecule and the elements it contains.

Scanning an empty field that once housed a Shaker village in New Hampshire, Jesse Casana had come in search of the foundations of stone buildings, long-forgotten roadways and other remnants of this community dating to the 1790s. But instead of a trowel and shovel, Casana and his Dartmouth College colleague Chad Hill are using a drone equipped with a thermal imaging camera and mapping instruments. The camera can identify remnants of buildings and other structures up to several feet below the surface, since the temperatures of that brick or stone material is often warmer than the soil around it. Dartmouth's Chad Hill readies a drone to be flown over a site of a Shaker Village in Enfield, NH. The team was able to recognize traces of long-removed historic buildings and pathways at the Shaker Village in Enfield, N.H. The community once housed nearly 100 buildings but was sold in the 1920s and is now an outdoor history museum.