Scientists have studied a new target for antibiotics in the greatest detail yet – in the fight against antibiotic resistance.

Saline–alkali stress disrupts the delicate chemistry of rose petals, reshaping both their color and aroma profiles. 

In Applied Physics Letters, researchers in China created a machine vision sensor that uses quantum dots to adapt to extreme changes in light far faster than the human eye can — in about 40 seconds — by mimicking eyes’ key behaviors. The sensor’s fast adaptive speed stems from its unique design: lead sulfide quantum dots embedded in polymer and zinc oxide layers. The device responds dynamically by either trapping or releasing electric charges depending on the lighting, similar to how eyes store energy for adapting to darkness.

Moving mesh adaptation provides optimal resource allocation to computational fluid dynamics for the capture of different key physical features, i.e., high-resolution flow field solutions on low-resolution meshes. Although many moving mesh methods are available, they require artificial experience as well as computation of a posteriori information about the flow field, which poses a significant challenge for practical applications. Para2Mesh uses a double-diffusion framework to accomplish accurate flow field reconstruction through iterative denoising to provide flow field features as supervised information for fast and reliable mesh movement, thus enabling adaptive mesh prediction from design parameters.