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The Nile Basin: National Determinants of Collective Action

The supply and management of fresh water for the world's billions of inhabitants is likely to be one of the most daunting challenges of the 21st century. For countries that share river basins with others, questions of how best to use and protect precious water resources always become entangled in complex political, legal, environmental, and economic considerations. This text focuses on the issues that face all international river basins by examining in detail the Nile Basin and the ten countries that lay claim to its waters. John Waterbury applies collective action theory and international relations theory to the challenges of the ten Nile nations. Confronting issues ranging from food security and famine prevention to political stability, these countries have yet to arrive at a comprehensive understanding of how to manage the Nile's resources. Waterbury proposes a series of steps leading to the formulation of environmentally sound policies and regulations by individual states, the establishment of accords among groups of states, and the critical participation of third-party sources of funding like the World Bank. He concludes that if there is to be a solution to the dilemmas of the Nile Basin countries, it must be based upon contractual understandings, brokered by third-party funders, and based on the national interests of each basin state.

Fast forward 15-20 years:

Me: Hey kids! Let's play a board game!
My Kids: Awwwwwwww, MOM! Do we have to play the Social Determinants of Health Board Game AGAIN???!? Can't we play something FUN for once?
Me: NO!!!! Not until you fully understand the effects of environment, social cohesion, structural factors, and community changes on your health!

.... my kids are going to hate me. But at least they will have a rich understanding of the causes of health inequalities!

Voici le jour , ce 28/01/2005 que la main de DIEU ne m'a plus jamais quittee .
C'est pour cela que chaque occasion pour moi est bon pour le louer.

Boost Your grades with this illustrated study guide. You will use it from college all the way to graduate school and beyond. FREE chapters on Linear equations, Determinant, and more in the trial version.

Features:

- Clear and concise explanations
- Difficult concepts are explained in simple terms
- Illustrated with graphs and diagrams


List of Chapters:
1. Linear equations
2. Matrices
3. Matrix decompositions
4. Computations
5. Vectors
6. Vector spaces
7. Affine space
Table of Mathematical Symbols

Table of Contents:

1. Linear equations

System of linear equations
Determinant
Minor
Cauchy-Binet formula
Cramer's rule
Gaussian elimination
Gauss-Jordan elimination
Strassen algorithm
2. Matrices

Matrix addition
Matrix multiplication
Basis transformation matrix
Characteristic polynomial, Characteristic Equation
Trace
Eigenvalue, eigenvector and eigenspace
Cayley-Hamilton theorem
Spread of a matrix
Symbolic Computation of Matrix Eigenvalues
Jordan normal form
Rank
Matrix inversion,
Pseudoinverse
Adjugate
Transpose
Dot product
Symmetric matrix
Matrix congruence
Congruence relation
Orthogonal matrix
Skew-symmetric matrix
Conjugate transpose
Unitary matrix
Hermitian matrix, Antihermitian
Positive definite: matrix, function, bilinear form
Identity matrix
Pfaffian
Projection
Diagonal matrix, main diagonal
Diagonalizable matrix
Similar matrix
Tridiagonal matrix
Hessenberg matrix
Triangular matrix
Spectral theorem
Stochastic matrix
Toeplitz matrix
Circulant matrix
Hankel matrix
Vandermonde matrix
Block matrix
(0,1)-matrix
Normal Matrix
Sparse matrix
Woodbury matrix identity
Perron-Frobenius theorem
List of Matrices
3. Matrix decompositions

Block LU Decomposition
Cholesky decomposition
LU decomposition
QR decomposition
Spectral theorem
Singular value decomposition
Schur decomposition
Schur complement
4. Computations

Transformation Matrix
Householder transformation
Least squares, linear least squares
Gram-Schmidt process
5. Vectors

Unit Vector
Pseudovector
Normal Vector
Tangential and Normal Components
Scalar multiplication
Linear combination
Linear span
Linear independence
Basis
6. Vector spaces

Basis (Hamel basis)
Dimension theorem for vector spaces (Hamel dimension)
Examples of vector spaces
Linear map
Galilean transformation, Lorentz transformation
Row and Column space
Null space
Rank-nullity theorem
Dual space
Linear function
Linear functional
Orthogonality
Orthogonal complement
Orthogonal projection
Improper rotation
Category of vector spaces
Subspace
Linear Subspace
Normed vector space
Inner product space
7. Affine space

Affine transformation
Affine group

Boost Your grades with this illustrated study guide. You will use it from college all the way to graduate school and beyond. FREE chapters on Linear equations, Determinant, and more in the trial version.

Features:

- Clear and concise explanations
- Difficult concepts are explained in simple terms
- Illustrated with graphs and diagrams


List of Chapters:
1. Linear equations
2. Matrices
3. Matrix decompositions
4. Computations
5. Vectors
6. Vector spaces
7. Affine space
Table of Mathematical Symbols

Table of Contents:

1. Linear equations

System of linear equations
Determinant
Minor
Cauchy-Binet formula
Cramer's rule
Gaussian elimination
Gauss-Jordan elimination
Strassen algorithm
2. Matrices

Matrix addition
Matrix multiplication
Basis transformation matrix
Characteristic polynomial, Characteristic Equation
Trace
Eigenvalue, eigenvector and eigenspace
Cayley-Hamilton theorem
Spread of a matrix
Symbolic Computation of Matrix Eigenvalues
Jordan normal form
Rank
Matrix inversion,
Pseudoinverse
Adjugate
Transpose
Dot product
Symmetric matrix
Matrix congruence
Congruence relation
Orthogonal matrix
Skew-symmetric matrix
Conjugate transpose
Unitary matrix
Hermitian matrix, Antihermitian
Positive definite: matrix, function, bilinear form
Identity matrix
Pfaffian
Projection
Diagonal matrix, main diagonal
Diagonalizable matrix
Similar matrix
Tridiagonal matrix
Hessenberg matrix
Triangular matrix
Spectral theorem
Stochastic matrix
Toeplitz matrix
Circulant matrix
Hankel matrix
Vandermonde matrix
Block matrix
(0,1)-matrix
Normal Matrix
Sparse matrix
Woodbury matrix identity
Perron-Frobenius theorem
List of Matrices
3. Matrix decompositions

Block LU Decomposition
Cholesky decomposition
LU decomposition
QR decomposition
Spectral theorem
Singular value decomposition
Schur decomposition
Schur complement
4. Computations

Transformation Matrix
Householder transformation
Least squares, linear least squares
Gram-Schmidt process
5. Vectors

Unit Vector
Pseudovector
Normal Vector
Tangential and Normal Components
Scalar multiplication
Linear combination
Linear span
Linear independence
Basis
6. Vector spaces

Basis (Hamel basis)
Dimension theorem for vector spaces (Hamel dimension)
Examples of vector spaces
Linear map
Galilean transformation, Lorentz transformation
Row and Column space
Null space
Rank-nullity theorem
Dual space
Linear function
Linear functional
Orthogonality
Orthogonal complement
Orthogonal projection
Improper rotation
Category of vector spaces
Subspace
Linear Subspace
Normed vector space
Inner product space
7. Affine space

Affine transformation
Affine group