Since musculoskeletal disorders of the upper extremities are believed to be associated with repetitive excessive muscle force production in the hands, understanding the time-dependent muscle forces during key tapping is essential for exploring the mechanisms of disease initiation and development.
For understanding the time-dependent nature of apoptosis signaling pathways, it is thus important to extract information on the temporal behavior of Ca2+ dynamics in real-time in living cells undergoing apoptosis.
The correspondence between model predictions and field data is remarkably good, and strongly supports our understanding of the time dependent evolution of glacial landscapes.
They have a very short time understanding the time.
If fibre reinforced concrete structures are to be accurately designed, an understanding of the time-dependent response under sustained loadings and in the cracked state must be well understood.
A basic understanding of the time-dependent behavior of the coating-based systems was achieved by using this model, which can be used to guide their design and fabrication.
Consequently, it is of utmost importance in food engineering research to develop a detailed understanding of the time-dependent transient changes in all of the structural aspects of food matrices from raw material harvesting, to product processing, to the point of breakdown during shelf-life, consumption and final digestion.
Precise knowledge of optimal gene regulatory pathways can provide an understanding of the time-dependent enhancement and suppression of gene activity and drug effectiveness [20] [22].
A better understanding of the time-dependent responses of intracellular signaling pathways could be very relevant in these situations.
The data and understanding gained in this work provide the basis for analysing the time-dependent mechanical behaviour during cure, e.g. build-up and relaxation of residual stresses.
In conclusion, we demonstrated that the time-dependent PRF model presented in this study provides an analytical tool for understanding the evolution of disease R genes in crop plants.
