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Flight-time equivalent dose (FED) is an informal unit of measurement of ionizing radiation exposure. Expressed in units of flight-time (i.e., flight-seconds, flight-minutes, flight-hours), one unit of flight-time is approximately equivalent to the radiological dose received during the same unit of time spent in an airliner at cruising altitude.
The CIPM also says that "in order to avoid any risk of confusion between the absorbed dose D and the dose equivalent H, the special names for the respective units should be used, that is, the name gray should be used instead of joules per kilogram for the unit of absorbed dose D and the name sievert instead of joules per kilogram for the unit ...
[6] Overall, individuals were exposed to a wide dose range (from less than 0.005 Gy to 4 Gy). [7] There is also a wide range in age. [7] About 45,000 people were exposed to 0.005 Gy or 5mSv. [6] The study shows a linear dose response for all solid tumors. [6] This means the relationship between dose and human body response is a straight line. [6]
[9] [failed verification] Each degree was subdivided into 60 minutes and each minute into 60 seconds. [10] [11] Thus, one Babylonian degree was equal to four minutes in modern terminology, one Babylonian minute to four modern seconds, and one Babylonian second to 1 / 15 (approximately 0.067) of a modern second.
A mathematical coincidence is said to occur when two expressions with no direct relationship show a near-equality which has no apparent theoretical explanation.. For example, there is a near-equality close to the round number 1000 between powers of 2 and powers of 10:
The standard liter per minute (SLM or SLPM) is a unit of (molar or) mass flow rate of a gas at standard conditions for temperature and pressure (STP), which is most commonly practiced in the United States, whereas European practice revolves around the normal litre per minute (NLPM). [1]
Now, we can rewrite the base (1/2) with only 4s and the exponent (1/2) back to a square root: = / ⏟ We have used four fours and now the number of square roots we add equals whatever non-negative integer we wanted.
For example, 1.6 would be rounded to 1 with probability 0.4 and to 2 with probability 0.6. Stochastic rounding can be accurate in a way that a rounding function can never be. For example, suppose one started with 0 and added 0.3 to that one hundred times while rounding the running total between every addition.