The phrase "applicable advance" is not commonly used in written English and may cause confusion.
It could be used in contexts where you are referring to an advance that is relevant or suitable to a particular situation or subject.
Example: "The applicable advance in technology has significantly improved our production processes."
Alternatives: "relevant progress" or "pertinent development".
Law No. 129/99 of 20 August 1999 approving the system applicable to advance payment by the State for indemnification due to the victims of marital violence.
We believe that this generic framework is widely applicable to advance our understanding of emergence and evolution of morphological instabilities for a rich variety of applications in soft materials and living systems.
Due to its compatibility with standard culture techniques, this approach should be broadly applicable in advancing our ability to generate hPSC-derived tissues in vitro with biomimetic anatomy.
Using the Pasteur's Quadrant approach to the conduct of resident-performed surgical research offers several advantages: It is clinically applicable; it advances goals of fundamental scientific research; it is provocative, productive, and retains high visibility; and it makes it attractive to funding agencies and industry alike.
Therefore, our studies in the mouse are directly applicable to advancing new knowledge in the treatment and prevention of diseases associated with progressive aging [ 27].
In general, the concept of preconstructing neural circuits in vitro together with the associated implantation technology is naturally applicable for advances being made in stem cells research [ 39– 43] and may begin to offer a new avenue for cell replacement strategies that aim to treat other CNS disorders which require the reestablishment of point-to-point contacts.
Another advance, applicable to the entire range of biological systems from cell culture to human, is molecular imaging [ 2, 3], which is the focus of this review.
The most recent of these reports, the 2010 EPI, provides national policymakers with a scientifically accurate and easily applicable tool for advancing data-driven environmental decisionmaking.
While designed for imitation and RL, our work is more generally applicable and also advanced the state of the art in standard few-shot classification benchmarks such as omniglot and mini-imagenet.
