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A multivariate polynomial empirical model for evaluating the coefficient of performance (COP) of centrifugal chillers was proposed in this work.
The fitness of the model was determined by evaluating the coefficient of regression (R2) obtained from the analysis of variance (ANOVA).
We tested the strength of each interaction by including the corresponding multiplicative interaction term in the main adjusted statistical model and evaluating the coefficient using the Wald test.
Bias of the genomic predictions was assessed by evaluating the coefficient of the regression of phenotypes on EBV of the validation animals.
We examined if the risk of cancer mortality and each social risk factor was modified by sex by adding a cross-product term between each factor and sex to the model and evaluating the coefficient using a Wald Test.
Within-run imprecision was determined by evaluating the coefficient of variation (CV) for each sample using eight assays within a run and between-run imprecision by performing eight assays for 7 d was then determined.
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These models are obtained by expanding the linearized Boltzmann collision operator into series, and a practical algorithm is proposed for evaluating the coefficients in the series.
These data are used to evaluate the coefficient of friction.
The framework is validated through a residential building under occupancy where, a monitoring system is installed to evaluate the coefficient of performance of the space heating system.
Scratch tests, under both ramping and constant load modes, were conducted to evaluate the coefficient of friction (COF) and wear rate of the alloy.
All analyses were performed in triplicate to evaluate the coefficient of variance.
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