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Biochemistry and Physiology of Polyamines in Plants provides a comprehensive introduction to commonly used methods in polyamine research and the problems unique to plant studies. Topics discussed include polyamine metabolism in plants, the functions of polyamines in plant growth and development, and an examination of analytical methods for polyamines and enzymes of polyamine metabolism. Agronomists, plant physiologists, and biochemists interested in polyamines in plants will find this book to be a valuable reference resource.

The 9th edition of Maudsley and Burn's Land Law Cases and Materials continues to provide an essential reference work for students and practitioners. It includes a wide range of extracts from cases, statutes, Law Commission reports and other literature, which highlight the key issues to understand the present law and its continuing development.

In this thesis we study the performance of update algorithms for replicated data in a distributed database. In doing so, we also investigate several other related issues. We start by presenting a simple model of a distributed database which is suitable for studying updates and concurrency control. We also develop a performance model and a set of parameters which represent the most important performance features of a distributed database. The distributed database models are used to study the performance of update algorithms for replicated data. This is done in two steps. First the algorithms are analyzed in the case of completely replicated databases in a no failure, update only environment. Then, the restrictions that we made are eliminated one at a time, and the impact on the system performance of doing this is evaluated. For the first step, we develop a new technique for analyzing the performance of update algorithms. This iterative technique is based on queueing theory. Several well known update algorithms are analyzed using this technique. The performance results are verified through detailed simulations of the algorithms. The results show that centralized control algorithms nearly always perform better than the more popular distributed control algorithms.