Deep Learning Enabled Strain Mapping of Single-Atom Defects in Two-Dimensional Transition Metal Dichalcogenides with Sub-Picometer Precision.

Two-dimensional (2D) materials offer an ideal platform to study the strain fields induced by individual atomic defects, yet challenges associated with radiation damage have so far limited electron microscopy methods to probe these atomic-scale strain fields. Here, we demonstrate an approach to probe single-atom defects with sub-picometer precision in a monolayer 2D transition metal dichalcogenide, WSeTe. We utilize deep learning to mine large data sets of aberration-corrected scanning transmission electron microscopy images to locate and classify point defects.

The changing profile of schistosomiasis in a changing urban landscape.

Since 2007, most of humanity resides in urban areas, a trend which continues worldwide. Diseases usually associated with rural contexts are now emerging or newly recognised in cities. In the neighbourhood of São Bartolomeu in Salvador, Brazil, the prevalence of Schistosoma mansoni infection in 2011 was >20%.