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The distribution of predictions indicates that there is much more fear of a negative surprise than there is hope for a positive one.
Comparison of test results with code predictions indicates that the design strengths are lower than the experimental strengths, and that the deviation between test and predicted results reduces as the section plate slenderness coefficient increases.
A comparison of the test results with code predictions indicates that the design strengths are lower than the experimental strengths and that the deviation between the test and predicted results decreases as the section plate slenderness coefficient increases.
Comparison of the experimental shear storage modulus of the blends with theoretical predictions indicates that the stress transfer from the PS matrix to the PO core through the SBR shell depends on the modulus of the SBR envelope.
Due to the well established accuracy of the zone method of analysis, the closeness of the two sets of predictions indicates that the two-flux model should prove extremely useful in assessing the thermal effects of changes in design or operating conditions in process gas heaters, particularly because of its computational simplicity compared with the zone method.
The comparison between the numerical and analytical predictions indicates that great caution should be taken when the Gibson Ashby approach is used to estimate the stress enhancement in dynamic crushing, and numerical models may be necessary to realise the complex effect of the entrapped gas on the compressive behaviour of cellular solids.
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The predictions indicate that flow distribution and current production are affected significantly by each other.
These predictions indicate that variant distribution of martensitic blocks can be optimized to mitigate and potentially inhibit material failure.
Bioinformatic predictions indicate that miRNAs regulate >30% of protein-coding genes (Filipowicz et al, 2008).
Bioinformatic predictions indicate that miRNAs regulate >30% of the protein coding genes (Filipowicz et al, 2008).
Bioinformatic predictions indicate that miRNAs regulate >30% of protein-coding genes (Lewis et al, 2005).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com