Sentence examples for model better represents from inspiring English sources

We will create a rendering of the heart chambers and the vasculature wall rather than the opacified intraluminal blood pool so that the printed model better represents the septal wall.

The HAE model better represents the human airway (compared to cell line models) in that it contains all the functional cell types found in the airway (ciliated, secretory, and basal cells) and more accurately represents the expression pattern of sialic acids found in the upper human respiratory tract [25] [30].

Hence, it could be concluded that the pseudo-second-order model better represented the adsorption kinetics.

MPM spheroids have been used to investigate new therapeutic options and have shown that this model better represent biological complexity existing in patients' tumor.

The higher-order models better represent the wave heights and forces on an off-centre screen.

Patient-derived xenograft (PDX) models better represent human cancer than traditional cell lines.

Whether conventional HTS encompasses the assessment of experimental conditions mostly in two-dimensional (2D) cultures, the advent of biofabrication technologies allowed screening to take over the third dimension, thus resulting in culture models better representing the physiological environment.

Additionally, 3D in vitro cell culture models better represent in vivo tumor drug response, which would facilitate efficacious therapy development at the preclinical stage [ 29].

The interpolation approach better represented historical PM2.5 concentrations, potentially due to the larger spatial scale of PM2.5, while the linear regression models better represented historical NO2 and O3 concentration, which have finer spatial resolutions.

During a study design, it is also important to adopt the model that better represents the pathology of interest so that the most suitable analyses can be performed.

An improved Hermite model that better represents the translation function at upper tail is proposed, and its improved performance in the estimated extreme value distribution of strongly non-Gaussian response process is achieved.