EBs appear therefore to be optimally positioned to sense nucleotide hydrolysis-dependent structural changes in the microtubule lattice.
The reconfigurability features of CR allow it to optimally adapt the operational parameters as a function of the sensed information.
Plants are able to sense and optimally respond to so many environmental variables — light, water, gravity, temperature, soil structure, nutrients, toxins, microbes, herbivores, chemical signals from other plants — that there may exist some brainlike information-processing system to integrate the data and coördinate a plant's behavioral response.
To grow and develop optimally, plants need to sense and process information from their surroundings.
Remotely sensed tracking technology has revealed remarkable migration patterns that were previously unknown; however, models to optimally use such data have developed more slowly.
Plants have evolved light sensing mechanisms to optimally adapt their growth and development to the ambient light environment.
For improving cooperative sensing, researchers focus on how to optimally fuse local sensing results.
The line is selected optimally in the sense of IAE criterion, considering constraint of the payload acceleration.
The researcher begins by assuming that natural selection works optimally, in the sense that the feature (or set of features) eventually selected represents the best adaptation for performing the function in question.
By optimally designing the sensing head structure and using the light sources with different bandwidths (8 nm, 30 nm and 47 nm), the temperature-dependent transmission spectra from the sensor are measured and investigated experimentally.
Parameters of the lines are selected optimally in the sense of two criteria, i.e. integral absolute error (IAE) and integral of the time multiplied by the absolute error (ITAE).
