The Curves The Point of View of Max Noether Probably the oldest references to the problem of resolution of singularities are found in Max Noether's works on plane curves [cf. [148], [149]]. And probably the origin of the problem was to have a formula to compute the genus of a plane curve. The genus is the most useful birational invariant of a curve in classical projective geometry. It was long known that, for a plane curve of degree n having l m ordinary singular points with respective multiplicities ri, i E {1, . . . , m}, the genus p of the curve is given by the formula = (n - l)(n - 2) _ ~ "r. (r. _ 1) P 2 2 L. . ,. •• . Of course, the problem now arises: how to compute the genus of a plane curve having some non-ordinary singularities. This leads to the natural question: can we birationally transform any (singular) plane curve into another one having only ordinary singularities? The answer is positive. Let us give a flavor (without proofs) 2 on how Noether did it • To solve the problem, it is enough to consider a special kind of Cremona trans formations, namely quadratic transformations of the projective plane. Let ~ be a linear system of conics with three non-collinear base points r = {Ao, AI, A }, 2 and take a projective frame of the type {Ao, AI, A ; U}.

Coverage of matrix algebra for economists and students ofeconomics Matrix Algebra for Applied Economics explains the important tool ofmatrix algebra for students of economics and practicing economists.It includes examples that demonstrate the foundation operations ofmatrix algebra and illustrations of using the algebra for a varietyof economic problems. The authors present the scope and basic definitions of matrices,their arithmetic and simple operations, and describe specialmatrices and their properties, including the analog of division.They provide in-depth coverage of necessary theory and deal withconcepts and operations for using matrices in real-life situations.They discuss linear dependence and independence, as well as rank,canonical forms, generalized inverses, eigenroots, and vectors.Topics of prime interest to economists are shown to be simplifiedusing matrix algebra in linear equations, regression, linearmodels, linear programming, and Markov chains. Highlights include: * Numerous examples of real-world applications * Challenging exercises throughout the book * Mathematics understandable to readers of all backgrounds * Extensive up-to-date reference material Matrix Algebra for Applied Economics provides excellent guidancefor advanced undergraduate students and also graduate students.Practicing economists who want to sharpen their skills will findthis book both practical and easy-to-read, no matter what theirapplied interests.