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Depiction of a red blood cell in an isotonic solution. A solution is isotonic when its effective osmole concentration is the same as that of another solution. In biology, the solutions on either side of a cell membrane are isotonic if the concentration of solutes outside the cell is equal to the concentration of solutes inside the cell.
Isotonic regression is also used in probabilistic classification to calibrate the predicted probabilities of supervised machine learning models. [2] Isotonic regression for the simply ordered case with univariate , has been applied to estimating continuous dose-response relationships in fields such as anesthesiology and toxicology.
Plasma osmolality measures the body's electrolyte–water balance. [1] There are several methods for arriving at this quantity through measurement or calculation. Osmolality and osmolarity are measures that are technically different, but functionally the same for normal use.
For example, some authors use s, indicating species. [ 2 ] x is used here to match the state space notation used in control theory but either notation is acceptable. N {\displaystyle {\bf {N}}} is the stoichiometry matrix which is an m {\displaystyle m} by n {\displaystyle n} matrix of stoichiometry coefficient.
The osmol gap is typically calculated with the following formula (all values in mmol/L): = = ([+] + [] + []) In non-SI laboratory units: Calculated osmolality = 2 x [Na mmol/L] + [glucose mg/dL] / 18 + [BUN mg/dL] / 2.8 + [ethanol/3.7] [3] (note: the values 18 and 2.8 convert mg/dL into mmol/L; the molecular weight of ethanol is 46, but empiric data shows that it does not act as an ideal ...
The crab-eating frog, or Rana cancrivora, is an example of a vertebrate osmoconformer. The crab-eating frog also regulates its rates of urea retention and excretion, which allows them to survive and maintain their status as osmoconformers in a wide range of external salinities. [ 3 ]
In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]
Initial requirements of such a system of procedures for inference and induction are that the system should produce reasonable answers when applied to well-defined situations and that it should be general enough to be applied across a range of situations. Inferential statistics are used to test hypotheses and make estimations using sample data.
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