Answer:
an external search
Explanation:
According to my research on the consumer buying process, I can say that based on the information provided within the question Nico is engaging in an external search. In Marketing, this term refers to when an individual has no knowledge of a product and therefore seeks out information from personal contacts or various public sources in order to make an informed decision. Which in this case is what Nico is doing by asking in different places about cameras.
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Answer:
False the right answer would be the fulcrum.
Explanation:
Your welcome<3
Answer:
Stars are classified by their spectra (the elements that they absorb) and their temperature. There are seven main types of stars. In order of decreasing temperature, O, B, A, F, G, K, and M.
Explanation:
O and B stars are uncommon but very bright. M stars are more common but dim.
Answer:
Results
We systematically analyze and compare how different modelling methodologies can be used to describe translation. We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected. Then a novel probabilistic Boolean network (PBN) model is proposed for modelling translation, which enjoys an exact numerical solution. This solution matches those of numerical simulation from other methods and acts as a complementary tool to analytical approximations and simulations. The advantages and limitations of various codon-based models are compared, and illustrated by examples with real biological complexities such as slow codons, premature termination and feedback regulation. Our studies reveal that while different models gives broadly similiar trends in many cases, important differences also arise and can be clearly seen, in the dependence of the translation rate on different parameters. Furthermore, the update rule affects the steady state solution.
Conclusions
The codon-based models are based on different levels of abstraction. Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise. This approach also allows for an optimal use of analysis tools, which is especially important when additional complexities or regulatory mechanisms are included. This approach can provide a robust platform for dissecting translation, and results in an improved predictive framework for applications in systems and synthetic biology.
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