--ZusammenfassungComputer Methods for Sampling from Gamma, Beta, Poisson and Binomial Distributions. Accurate computer methods are evaluated which transform uniformly distributed random numbers into quantities that follow gamma, beta, Poisson, binomial and negative-binomial distributions. All algorithms are designed for variable parameters. The known convenient methods are slow when the parameters are large. Therefore new procedures are introduced which can cope efficiently with parameters of all sizes. Some algorithms require sampling from the normal distribution as an intermediate step. In the reported computer experiments the normal deviates were obtained from a recent method which is also described.

This paper identifies institutional failure as the root cause for underdevelopment and susceptibility to disasters and explores their interdependent relationship. It is demonstrated that only if a country's governance structure enables the implementation and enforcement of public policies conducive to a country's economic and social development can sustainable livelihoods be achieved and susceptibility to disasters be reduced. Accountability, participation, predictability and transparency are identified as the key features of a governance structure that fosters development and supports risk reduction.

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Branch-and-bound algorithms are adequate for the solution of a wide range of 0-1 knapsack problems. It is shown that the simplest method of branching is as good as any. However, problems with highly correlated large weights and values quickly become unsolvable in a reasonable time. This paper develops algorithms that are aimed specifically at the hardest possible examples. The new methods use merging and sorting ideas and require a moderate amount of additional memory space. They are, however, faster by factors far in excess of 1,000 in many cases, thereby extending considerably the range of practically solvable 0-1 knapsack problems.