J. R. Norris – författare

The availability of the photosynthetic reaction center''s structure at an atomic resolution of less than three angstroms has revolutionized research. This protein is the first integral membrane protein whose structure has been determined with such precision. Each volume of the Photosynthetic Reaction Center contains original research, methods, and reviews. Together, these volumes cover our current understanding of how photosynthesis converts light energy into stored chemical energy.Volume I describes the chemistry and biochemistry of photosynthesis, including green plant photosynthesis; it is devoted to the overall features and implications of the bacterial reaction center for green plant research. It features a new description of the structure of the reaction center, followed by coverage of the antenna and light functions. Volume I also details new manipulations of the reaction center including chemical and genetic modifications. It describes how the reaction center provides reducing power via electron transfer chemistry coupled to proton uptake and release; coupling of electron transport between the oxidized reaction center and the aqueous periplasm; and the general operation of membrane-bound proteins. Additionally, this volume contains five chapters detailing facets of green plant photosynthesis important for future research.

Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing also how actually to apply it. Both discrete-time and continuous-time chains are studied. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice. It will therefore be an ideal text either for elementary courses on random processes or those that are more oriented towards applications.

Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing also how actually to apply it. Both discrete-time and continuous-time chains are studied. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice. It will therefore be an ideal text either for elementary courses on random processes or those that are more oriented towards applications.

Markov chains are central to the understanding of random processes. This is not only because they pervade the applications of random processes, but also because one can calculate explicitly many quantities of interest. This textbook, aimed at advanced undergraduate or MSc students with some background in basic probability theory, focuses on Markov chains and quickly develops a coherent and rigorous theory whilst showing also how actually to apply it. Both discrete-time and continuous-time chains are studied. A distinguishing feature is an introduction to more advanced topics such as martingales and potentials in the established context of Markov chains. There are applications to simulation, economics, optimal control, genetics, queues and many other topics, and exercises and examples drawn both from theory and practice. It will therefore be an ideal text either for elementary courses on random processes or those that are more oriented towards applications.