A Feiticeira de Florença by Salman Rushdie

By Salman Rushdie

Title note: unique identify: The Enchantress of Florence
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A Feiticeira de Florença é a história de uma mulher que procura ser senhora do seu próprio destino num mundo de homens. Irmana duas cidades que quase não se conhecem: a hedonista capital mogol, onde o inteligente imperador se debate diariamente com questões de crenças, desejos e a traição dos filhos, e o mundo florentino, igualmente sensual, de poderosos cortesãos, filosofia humanista e desumana tortura.
Estes dois mundos, tão distantes, acabam por se revelar estranhamente semelhantes, e ambos são dominados pelos encantamentos das mulheres.

Literary Awards
Man Booker Prize Nominee for Longlist (2008)

Críticas de imprensa
« “A Feiticeira de Florença” é um festim exótico, supra abundante, coberto de ouro e pedrarias, tão vertiginoso como cómico, tão inventivo, irreal e irónico como os contos da Mil e Uma Noites. [ ... Rushdie] leva-nos aos sonhos e visões de muitos séculos, desde a magnificência das cidades italianas do Renascimento e dos feitos dos Médicis e dos Sforzas; às naus das Índias e ao naufrágio de Camões, do Al-Andaluz à Pérsia, numa infindável viagem de memórias exóticas e surreais.»
Helena Vasconcelos, Público

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Extra resources for A Feiticeira de Florença

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20) where a0( 0), a1 and a2 are three arbitrary parameters. In this convergence approach, three values of the unknown x variable are guessed. Let, xk–2, xk–1 and xk are three approximations to the actual root r of f(x) = 0. 21c), pk–2 = p(xk–2), pk–1 = p(xk–1) and pk = p(xk). 23) where g = x – xk, gk = xk – xk–1 and gk–1 = xk–1 – xk–2. 24) where................. 26) should be such that k+1 has the smallest absolute value. Recall the assumption,  = g/gk. 5 Illustration of the Muller method. 29) This equation represents the Muller method.

This integration technique provides better accuracy than the Explicit Euler method but the Euler approach runs almost two times faster. Fourth-order Runge–Kutta (RK4) approach The concepts involved in the fourth-order Runge–Kutta approach (Lapidus and Seinfeld, 1971) for estimating xk+1 are outlined below. , xk + (t/2)k1]. Secondly, the first estimate of x is used to find the slope k2 at the midpoint. Subsequently, a corrected midpoint slope k3 is evaluated by using k2. Slope k4 is then found at the end of integration interval.

1 Illustration of the Bisection method. The Bisection method actually locates a root by repeatedly narrowing the distance between the two guesses. When an interval contains a root, this simple numerical method never fails. However, the main drawback of the Bisection technique is the slow convergence rate. Also, it is not easily extended to multivariable systems. 2 Secant Method Because of the slow convergence provided by the Bisection approach, the Secant method (Finlayson, 1980; Riggs, 1988; Burden and Faires, 1985) receives the attention as an alternative iterative technique.

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