Bearing estimation of radially propagating symmetric waves in solid structures typically requires a minimum of two sensors.
The design of well-damped structures typically requires significant numerical optimizations which rely on proper material characteristics.
This typically means that the protein's structure will also be preserved, because changes in protein structure typically require changes in many amino acid sequences and would thus not preserve function [48], [49].
The identification of the dynamic stability boundary that separate the non-snap and post-snap responses is hence necessary for the safe design of such structures, but typically requires extensive transient simulations that may lead to high computation cost.
Building codes in fire-prone areas typically require that structures be built of flame-resistant materials and a defensible space be maintained by clearing flammable materials within a prescribed distance from the structure.
A main reason for this is that biochemical methods used traditionally to assay changes in cytoplasmic cAMP concentration are limited in spatiotemporal resolution and typically require perturbing cellular structure and/or function for implementation.
Evolutionary algorithms (EAs) are popular in solving a diversity of problems, but current algorithm design approaches typically require formulating an algorithmic structure for each individual problem.
Unlike those in eukaryotic nuclear genes, they do not rely on spliceosomes for excision from RNA transcripts, and unlike the similarly structured self-splicing introns of prokaryotes, they typically require other trans-acting factors for efficient splicing in vivo[1], [2].
This resource is used primarily for de-novo assembly computations, which typically require large amounts of RAM for keeping data structures, for example, De Bruijn graphs [ 36], in memory.
