It's mathematically impossible to deduce mean or standard deviation from median/quartiles, because medians and quartiles discard most of the data on which the mean and standard deviation are based.
Example:
data frequency
0 50
1.4 4
2 50
That has a mean of 1.0 and standard deviation of 0.9. (I'm using 2 significant figures so I don't have to go into population versus sample standard deviation.)
data frequency
0 30
1.4 44
2 30
That data also has the median and quartiles the same as in your example, but now the mean is 1.2 and the standard deviation is 0.8.
data frequency
0 30
1.4 3
2 70
10000000 1
Now I've changed my maximum without changing the median or quartiles, you can see even more clearly how the median and quartiles exclude extreme data, because the mean is now 96000 and the standard deviation is 98000 (still 2 sig.fig.).
Best Answer
The median $Q_2$ is the point such that the area under the bars each side of $Q_2$ is equal.
The lower quartile $Q_1$ is the point such that the area up to $Q_1$ is one quarter of the total area.
The upper quartile $Q_3$ is the point such that the area up to $Q_3$ is three quarters of the total area.