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The MODS record has been designed to carry key data elements from the MARC record but does not define all of the MARC fields and does not use the field and subfield tagging from the MARC standard. There are data elements in MODS that are not compatible with the MARC record so there is some loss translating from MARC to MODS and from MODS to MARC.
Here is a little sample model written in MPS format (explained in more detail below): NAME TESTPROB ROWS N COST L LIM1 G LIM2 E MYEQN COLUMNS XONE COST 1 LIM1 1 XONE LIM2 1 YTWO COST 4 LIM1 1 YTWO MYEQN -1 ZTHREE COST 9 LIM2 1 ZTHREE MYEQN 1 RHS RHS1 LIM1 5 LIM2 10 RHS1 MYEQN 7 BOUNDS UP BND1 XONE 4 LO BND1 YTWO -1 UP BND1 YTWO 1 ENDATA
Case mix index (CMI) within health care and medicine, is a relative value assigned to a diagnosis-related group of patients in a medical care environment. The CMI value is used in determining the allocation of resources to care for and/or treat the patients in the group.
Normally the generated scanner contains references to the unistd.h header file, which is Unix specific. To avoid generating code that includes unistd.h , %option nounistd should be used. Another issue is the call to isatty (a Unix library function), which can be found in the generated code.
The second row is the same generator with a seed of 3, which produces a cycle of length 2. Using a = 4 and c = 1 (bottom row) gives a cycle length of 9 with any seed in [0, 8]. A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation.
This process is called raising the index. Raising and then lowering the same index (or conversely) are inverse operations, which is reflected in the metric and inverse metric tensors being inverse to each other (as is suggested by the terminology): = = =
where is the volume fraction of the fibers in the composite (and is the volume fraction of the matrix).. If it is assumed that the composite material behaves as a linear-elastic material, i.e., abiding Hooke's law = for some elastic modulus of the composite and some strain of the composite , then equations 1 and 2 can be combined to give
In statistics, a generalized linear mixed model (GLMM) is an extension to the generalized linear model (GLM) in which the linear predictor contains random effects in addition to the usual fixed effects. [1] [2] [3] They also inherit from generalized linear models the idea of extending linear mixed models to non-normal data.