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Leonardo da Vinci is usually credited with conducting the first systematic study of friction in the late 15th century, a subfield now known as tribology that deals with the dynamics of interacting surfaces in relative motion. Da Vinci's notebooks depict how he pulled rows of blocks using weights and pulleys, an approach that is still used in frictional studies today, as well as examining the friction produced in screw threads, wheels, and axles. The authors of this latest paper used an experimental setup similar to da Vinci's.
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This approach shares a lot in common with the idea of multivariate interpolation over scattered data. Multivariate interpolation attempts to estimate values at unknown points within an existing data set and is often used in fields such as geostatistics or for geophysical analysis like elevation modelling. We can think of our colour palette as the set of variables we want to interpolate from, and our input colour as the unknown we’re trying to estimate. We can borrow some ideas from multivariate interpolation to develop more effective dithering algorithms.
Mariah Carey has been nominated for the past three years - could it be third time lucky?