Every connection request, i∈I is specified by a source (s i ), a destination (d i ), requested start time (r i ) and connection duration (t i ).
( x ~ i − c ~ i − ln ( p i ) − ∑ j ≠ i ln ( 1 − p j ) ) is a subgradient of D where x ~ i and p i are specified by (17) and (18), respectively.
In addition to a vector of variables x it and their constant coefficients β, a vector of random coefficients γ i are specified for a vector of variables z it in the utility function.
To incorporate the set of explanatory variables x and Y stated in Eq. 21 into Eq. 23, and to ensure a non-negative mean y i, the parameter λ i is specified as: Eleft{left.{y}_iright|{Y}_i,{x}_{i k}right}={uplambda}_i= exp left phi {Y}_i, xhboxbeta right)= exp left({psi}_0+phi {mathrm{Y}}_i+{beta}_1{x}_kright.{beta}_k{x}_kright) (24).
where q 1 is the probability that the next transition is a recovery (from A to Q) given 1 active neurone (as defined earlier), λ i are the eigenvalues of the transition matrix A and d i are specified by the eigenvectors of the transition matrix and the initial conditions.
Each measurement, which we denote by y ˜ i, is specified by the time t i when the c i -th component of the state vector y is measured.
Let Y be the (label) set of taxa with nonmissing data for some locus (Y i if locus i is specified).
The presumed photosynthesis growth equation allows for the direct calculation of the stoichiometric coefficients in terms of biomass composition (x, y, and z) once a nitrogen source N i is specified (Equation 1).
The c variables: Of the 19 Boolean variables c i (t), 15 depend only on the configuration of a subset of TFs and external metabolites at time t, i.e., c i (t) = C i (t(t), m(t)), i = 1, 2,...,15, where the C i are specified Boolean functions in the database.
Given this definition of expected state, ϕ i (x i, Parents(x i )) is specified as: For the results shown here, ϵ was set to 0.001, but orders of magnitude differences in the choice of epsilon did not significantly affect results.
