Nonlocal formulations are currently adopted to assess size effects in nanostructures.
Here, to describe the central tendency of intron size distribution, we calculate the median intron size rather than the mean size, which is adopted to measure the insert size distribution in existing scaffolders.
A hydraulic drive system is adopted to reduce the size, weight, and cost of the structure.
Ultrasonic irradiation was adopted to control the size and homogenize the LiFePO4/C particles.
An iteration algorithm is proposed to evaluate K η distance and a pruning strategy is adopted to reduce the size of candidate set of nearest-neighbors.
To obtain suitable patterns for neural network training, principal component analysis (PCA) techniques are adopted to reduce the size of the residual FRF data and to filter noise.
Different analysis techniques, such as scanning electron microscopy (SEM), X-ray powder diffraction, N2 adsorption-desorption isotherms, and magnetization curves were adopted to characterize the size, morphology, and magnetic property of the obtained microspheres.
While the member grouping strategy is adopted to reduce the size of the problem, the initial population strategy is applied to reduce the number of search to reach the optimum design in the solution space.
Accordingly, two composite parameters incorporating the cumulative probability of failure and the volume of fracture process zone are identified and adopted to characterize the size effect on the strength of concrete.
Mid-infrared measurements with a partial least squares regression model were adopted to quantify the size and distribution of SOC fractions (i.e., particulate organic carbon (POC) fraction, humus organic carbon (HOC) and resistant organic carbon (ROC; representing PyC fraction) along the two hillslopes.
