The surface roughness of soil grains affects the mechanical behaviour of soils, but the characterization of real soil grain roughness is still limited in both quantity and quality. A new method is proposed, which applies the power spectral density (PSD), typically used in tribology, to optical interferometry measurements of soil grain surfaces. The method was adapted to characterize the roughness of soil grains separately from their shape, allowing the scale of the roughness to be determined in the form of a wavevector range. The surface roughness can be characterized by a roughness value and a fractal dimension, determined based on the stochastic formation process of the surface. When combined with other parameters, the fractal dimension provides additional information about the surface structure and roughness to the value of roughness alone. Three grain sizes of a quarzitic sand were tested. The parameters determined from the PSD analysis were input directly into a Weierstrass-Mandelbrot function to reconstruct successfully a fractal surface.

In the above article, we referred to effects of D 9 -THC with or without COX-2 signaling inhibition on spatial working memory. The behavioral paradigm employed-a water maze test with a fixed platform during training sessions, as described in the Experimental Procedures-assays spatial learning and memory, not working memory. The article has been corrected online. We regret this error and apologize for any inconvenience or confusion that the error may have caused.

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