Sentence examples for distribution varying from inspiring English sources

Our data show that polymer semiconductors can simultaneously exhibit field-effect and electrochemical operation regimes, with the operation modality and its distribution varying locally as a function of nanoscale film morphology, ion concentration and potential.

The polymerisations remain isotropic, with both the chemical composition and physical architecture distribution varying systematically as a function of monomer conversion and copolymer molecular weight.

The curves of the output power, the power conversion efficiency and the thermal stress distribution varying with different geometric dimensions are discussed in detail.

Columns with non-uniform distribution of geometrical or material parameters i.e. functionally graded material distribution, varying cross-sectional area and flexural stiffness provide an economical solution to carry the desired higher compressive loads in engineering structures.

The results show that the power distribution varying with burnup leads to large differences in temperature responds during transients, while the impacts of kinetic parameters and feedback coefficients are not very obvious.

The material properties of each FGM layer are assumed to obey either a power-law distribution of the volume fractions of the constituents through the thickness coordinate or an exponential law distribution varying exponentially through this.

Example photos are presented that show how aerosols with different physio-optical characteristics and spatial distributions, varying relative humidity, and cloud cover affect the seeing of landscape features.

A study by the US National Science Foundation (NSF), published in July 2008, shows that tenured and tenure-track women faculty increased from less than 10 percent in 1979 to 28 percent in 2006, with distributions varying considerably by field.

The list of attributes consists of both continuous-type and discrete type variables, with statistical distributions varying drastically from each other, which makes the intrusion detection a very challenging task.

This tool confirmed that both P. chrysogenum and P. rubens are common fungi with their distributions varying between sample locations.

Data were generated from the Uniform distribution or varying mixtures of Beta distributions based on the inference regarding the patterns of p-values as described in Section Global tests and Figure 1.