The amoeba is made of one cell.
Answer:
The short answers are Yes, it's random, and Yes, it "waits" for some time.
Different tRNA's just float around in the cytoplasma, and diffuse more or less freely around. When one happens to bump into the ribosome, at the right spot, right orientation, and of course which has an anticodon matching the codon in frame of the mRNA being translated, it gets bound and takes part in the synthesis step that adds the amino acid to the protein that is being synthesized.
The concentration of the various species of tRNA is such that translation occurs in a steady fashion, but there is always some waiting involved for a suitable tRNA to be bound. In that waiting time, the ribosome and mRNA stay aligned - that's because the energy that is required to move the to the next position is delivered as part of the same chemical reaction that transfers the amino acid from the tRNA to the protein that is being synthesized.
I'm not entirely sure what happens if there is significant depletion of a particular species of tRNA, but I think it's likely the ribosome / RNA complex can disassemble spontaneously. But spontaneous disassembly can't be something that occurs very easily after translation was initiated, since we would end up with lots of partial proteins which I expect would be lethal very soon.
(Can't know for sure though, but it would be very hard to set up an experiment to measure just what will happen and even if you got a measurement it would be hard to figure out how it applies to normal, living cells. I can't imagine tRNA depletion occurs in normal, healthy living cells.)
Answer & Explanation:
First, correlation and causation both need an independent and dependent variable. An independent variable is a condition or piece of data in an experiment that can be controlled or changed. A dependent variable is a condition or piece of data in an experiment that is controlled or influenced by an outside factor, most often the independent variable.
If there is a correlation, then sometimes we can assume that the dependent variable changes solely because the independent variables change. This is where the debate between correlation and causation occurs. However, there is a difference between cause and effect (causation) and relationship (correlation). Sometimes these areas can be confused and muddled when analyzing data.
- You probably know that a correlation is the relationship between two sets of variables used to describe or predict information. There is an emphasis here on relationship. Sometimes we can use correlation to find causality, but not always. Remember that correlation can either be positive or negative.
A positive correlation, where the dependent variables and independent variables in a data set increase or decrease together. If the numbers sloped downward, then you have a data set with a negative correlation, where the dependent variables and independent variables in a data set either increase or decrease opposite from one another.
Whilst a negative correlation means if the independent variables decrease, then the dependent variable would increase, and vice versa.
- Causation, also known as cause and effect, is when an observed event or action appears to have caused a second event or action. For example, I bought a brand new bed comforter and placed it in my washing machine to be cleaned. After cleaning the comforter, my washing machine stopped working. I may assume that the first action, washing the comforter, caused the second action, broken washing machine.
<em>I hope this helped! :)</em>
Answer:
Donations should be encouraged to help needy peoples and build a better society. Donations also show the kidness of individual. Donating small amount also may save someones life and health. This is why donations should be encouraged to save the society.
the answer is B. because the Roman's were frequently conquering their surrounding territories for greater power, they found it necessary to document medical procedures for future generations to learn these skills and keep their armies in good health for the next battle.
