Sentence examples for multiple transformations and from inspiring English sources

We reasoned that a single-plasmid based approach would simplify the experimental procedures by eliminating the need for multiple transformations and more than one resistance marker.

In such randomly varying situations, previous studies suggest that subjects cannot represent these multiple transformations and only learn the average [20 25].

Through the years, hardcore punk has weathered multiple transformations and redefinitions, peaking in mainstream popularity (possibly) in the mid-2000s, withethe rise of emo-crossover bands like Taking Back Sunday.

The defining feature of our processor is its reconfigurability supporting multiple transformations for many communication and signal processing standards with simple SW instructions, high SQNR, and relatively high throughput.

In the absence of mature institutions, although the tradition of being family-centered and the isomorphism of family and nation is doing everything possible to support family members and help them resist risks, the family is finding it increasingly challenging to cope with the structural assault from the multiple transformations of demography, family, and society.

This review introduces bifunctional materials used in one-pot multiple transformations of biomass into biofuels and related chemicals.

Since then, the franchise has gone through multiple transformations: first assuming the stealthy tones of Metal Gear, and later adopting the speed of the Jason Bourne movies, it now takes its cues from Jack Bauer (Fisher even allied with a faux CTU team).

But his band — which was augmented, for a few songs, by an Israeli oud player — carries simple vamps through multiple transformations, from meditations to shredding guitar solos.

Ireland's multiple transformations of the past 40 years, from backwater to tiger to debt-ridden basket-case to pioneer of recovery, certainly add up to an epic worthy of the literary greats.

Feature extractions involve multiple transformations, some of them nonlinear, which are performed jointly on multiple features of the same frame or by combining features from different time frames.

In the second method, the algorithm is trained on multiple transformations of the raw input data until the model learns invariance to that transformation.