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Quantitative methods for optimizing product attribute levels using preference elicitation (e.g., conjoint) data are useful for many product types.
Also, the sensors' data are useful for predicting system operation and network failures.
These realistic data are useful for design engineers for outdoor assessment of PV system components.
These data are useful for future trial design in this unique population.
The preclinical data are useful for the design of clinical trials of felotaxel.
The data are useful for multiple purposes of assessment, including screening, eligibility determination, instructional development, and program evaluation.
The obtained data are useful for the design of cultivation schemes for pDNA production by E. coli.
These data are useful for the design of adsorption cooling and refrigeration systems and are unavailable in the literature.
However, the differences are not significant indicating that all these data are useful for ST modeling of spruce forest.
The pulling force data are useful for the purpose of theoretical and numerical draw bead model calibration.
The assembled data are useful for a number of epidemiological purposes, such as estimating the number of people infected with NTDs and predicting the distribution of infection in unsampled areas, using modern statistical methods.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com