Sentence examples for models enabling us from inspiring English sources
Data were analyzed using linear mixed models enabling us to display the effects of both the considered explanatory variables and their interactions.
Future dark energy experiments together with CMB data from experiments like Planck could dramatically improve our ability to constrain cosmic curvature under such models enabling us to probe possible imprints of quantum gravity.
Here we present new compilations of airborne magnetic and airborne gravity data, together with digital enhancements and 2D models, enabling us to re-evaluate the crustal architecture of the WSRS and its tectonic and kinematic evolution.
However, near-term efforts will require the co-development of experimental and in silico models, enabling us to work with the underlying complexity to gain more insightful answers to the questions we pose than would be possible at the bench alone.
These models enable us to use more powerful parametric statistical techniques for both estimating isoform and processing event frequencies and detecting DP genes between samples.
The use of ARIMA models enables us to create short-term predictions of injury mortality in China.
The use of preclinical models enabled us to study the outcome of bevacizumab in combination with chemotherapy on EOC progression (first end point) and survival (second end point).
Such models enabled us to address the electrical properties in a wider range of potential reservoir rocks through theoretical parameters related to key reservoir-defining petrophysical properties.
Using the best parameter sets deduced with our ODE models, multiple simulations for each of the one and two-population models enabled us to estimate confidence intervals of predictions (shaded areas of Figure 5).
The development of miniaturized and cost-effective 3D models enabled us to monitor growth, maturation, invasion and motility of prostaspheres in real-time and high resolution, by combined live cell and confocal microscopy.
Sensitivity analyses of computational models enable us to identify the effects of uncertainties in parameter values on the model output.
