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The objectives of this simulation study were to investigate whether the same design cooling load calculation methods can be used for radiant and air systems by studying the magnitude of the cooling load differences between the two systems over a range of design configurations.
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Basically, the objective of this simulation is to illustrate and to confirm proposed crack growth mechanism.
The objective of this simulation study is to investigate the influence of frequency-dependent stiffness and damping properties on the system identification, as performed by two standard modal analysis tools and one in-house updating algorithm.
The main objective of this simulation study is to compare the production characteristics between conventional gas and gas-hydrate reservoirs.
Main objective of this simulation study is to see how different versions of this method perform against each other and against most relevant published algorithms [23, 24] in the common setting.
The objective of this simulation was to verify the performance of the method in the presence of markers with only main effects, ie, in a controlled environment.
The objective of this simulation study was to investigate the benefits of applying GS to select purebred animals for CP, based on purebred phenotypic and genotypic information.
The objective of this simulation study was to compare the effect of the number of QTL and distribution of QTL variance on the accuracy of breeding values estimated with genomewide markers (MEBV).
The main objective of this simulation analysis is to explore how the unique features of miRNA datasets may impact the performance of the proposed Bayesian normalization method and the existing normalization methods.
The objective of this simulation study was to evaluate specific linear mixed effect (LME) models for biases, precisions, and qualities of inferences under different pharmacokinetic (PK) profile scenarios and study designs in the presence of biologically varying QTc.
For the null distribution, the effect size β is 0. The primary objective of this simulation was to test the type I error rates of ANOVA and both permutation testing methods under correct and incorrect modeling assumptions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com