Sentence examples for the inverse when from inspiring English sources

On the other hand, there is no linear technique in the literature that can invert the sparse aggregated channel matrix and preserve the zeros in the transposed version of the inverse, when the aggregated channel matrix is not diagonal or block-diagonal.

This may be a reflection of higher food consumption in general as the association became inverse when adjusted for energy intake and as the relationship also applied to protein.

The fact that the mothers with more schooling more frequently reported the perception that their children's diet was healthy while the association was inverse when reporting on their own diets (i.e., they more frequently reported the perception that their own diet was not healthy) may initially seem discrepant but plausible.

Mathematically, the ({mathbf{G}}^{text{T}} {mathbf{G}}) has an inverse when the determinant of the matrix is different from zero and it is not zero for both datasets (sand and shale).

17 A study from Finland found positive associations between body size in early childhood and adult liver fat score at age 60 years, but the association became inverse when adjusted for concurrent BMI at that age.

The results were more inverse when only including the studies adjusting for caffeinated and decaffeinated coffee simultaneously in the model.

A relationship was defined as "inverse" when the measure of weight status displayed the highest and lowest magnitudes in participants of low and high SEP, respectively, and in addition, when there was a statistically significant difference between them, and/or the p-value for linear trend across the different SEP categories was statistically significant.

The isotopic effect is inverse when compounds containing heavier isotopes have greater vapour pressure.

The yeast worked well when ChCl/Gly (1 2) was added into an aqueous buffer, and even enantioselectivity had a complete inverse when altering the proportion of DES used.

It should be noted that using 13 leads to an approximation of the covariance matrix and its inverse when marker data are not complete.

For this reason, when creating the mathematical models, researchers are usually faced with the inverse problem when the number of samples or dimensions in the data is smaller than the number of parameters (so-called ill-posed inverse problem).