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For all alloys, the α↔γ phase transformation introduces a volume change of 1.0%.
Moreover, the physical iterative transformation between crystalline and amorphous phase transformation introduces a swelling and deswelling effect.
The crucial step of transformation introduces a clear unbalance in the Vitamin D signalling and metabolic pathways.
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The transformation introduces an elliptic boundary value problem which is solved by a preconditioned conjugate gradient method.
Despite the benefits mentioned, this data transformation introduced a computational limitation due to the enormous amount of feature combinations to be processed, especially when N-feature model classifiers for N>4 are considered (If 100 features are selected, and 10-feature model classifier is investigated, the search space will be C10= 1.731030945644000 × 1013 different combination of features).
Please note, the experimental results in [10] also showed that the Pig transformation introduces performance degeneration with a performance ratio of 1.5 (the running time of Pig program/the running time of a Java Map-Reduce program) on average.
Although this transformation introduces many benefits, it arouses new challenges of data security due to the outsourcing storage on untrusted cloud servers.
This transformation introduces odd powers of x and y to this polynomial.
While replacing the native T-DNA of Agrobacterium with a novel T-DNA can be done with great precision, the overall process of transformation introduces many unpredictable and unwanted effects on genetic or epigenetic (hereafter, genomic) integrity.
The techniques we use build on a time transformation introduced in previous work.
We prove that the transformation introducing such coordinates maps analytically a complex ball of radius R/Nα (in discrete Sobolev-analytic norms) into a ball of radius R′/Nα (with R,R′>0 independent of N) if and only if α≥2.
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