Using this new method we could elaborate SC lists much quicker than with the traditional method.
Employing this method we could classify flow regimes with 98% accuracy.
By this method, we could assign a putative function to nearly 80% (215/267) of the differentially expressed genes.
Combining with a Topological Derivative Method, we could reduce hot spot phenomena in a robust sense, see Figure 19.
With this method we could not distinguish between subspecies (wolf from dog, and pig from wild boar).
According to CREAM basic method, we could figure out that Contexts 1, 2, 3 belong to Tactical, Opportunistic and Scrambled control model, respectively.
By using PIV method, we could obtain accurate behavior of hysteresis, hole mobility, subthreshold swing, and threshold voltage with increasing temperature.
Using our method, we could build well-defined hierarchical nanostructures such as branched NWs or NWs directly grown on cadmium chalcogenide thin films.
Based on the signal-to-interference ratio of our signal (rather than the traditional signal-to-noise method), we could determine the target object behind the wall.
Using this method, we could effectively determine gene deletions by using the nonamplified genomic DNAs that were extracted from the MCF-7 as a breast cancer cell line.
In our new method we could improve the retention with pH elevation using a new type of stationary phases available for high pH applications.
