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Groups may overlap in order to make each one larger. The optimal groupings in the example below are marked by the green, red and blue lines, and the red and green groups overlap. The red group is a 2 × 2 square, the green group is a 4 × 1 rectangle, and the overlap area is indicated in brown.
The Punnett square is a tabular summary of possible combinations of maternal alleles with paternal alleles. [9] These tables can be used to examine the genotypical outcome probabilities of the offspring of a single trait (allele), or when crossing multiple traits from the parents.
Matrix-free conjugate gradient method has been applied in the non-linear elasto-plastic finite element solver. [7] Solving these equations requires the calculation of the Jacobian which is costly in terms of CPU time and storage. To avoid this expense, matrix-free methods are employed.
For each square, cells with the same colour (excluding grey) sum to the magic constant. Note *: The second requirement of most-perfect magic squares imply that any 2 cells that are 2 cells diagonally apart (including wraparound) sum to half the magic constant, hence any 2 such pairs also sum to the magic constant.
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Punnett squares for each combination of parents' colour vision status giving probabilities of their offsprings' status, each cell having 25% probability in theory. Normal text denotes a person (or chromosome from a person) who has normal colour vision and no defective gene, italics: has normal colour vision and a defective gene, and bold: is ...
In mathematics, the Kronecker product, sometimes denoted by ⊗, is an operation on two matrices of arbitrary size resulting in a block matrix.It is a specialization of the tensor product (which is denoted by the same symbol) from vectors to matrices and gives the matrix of the tensor product linear map with respect to a standard choice of basis.
Let A be a 4 × 4 skew-symmetric matrix. The skew-symmetric matrix A can be uniquely decomposed as = + into two skew-symmetric matrices A 1 and A 2 satisfying the properties A 1 A 2 = 0, A 1 3 = −A 1 and A 2 3 = −A 2, where ∓θ 1 i and ∓θ 2 i are the eigenvalues of A.