Springer nature jun 2001 (2 Ergebnisse)

Buch. Zustand: Neu. Neuware - List of Contributors. Foreword; R.F. Burk. Preface; D.L. Hatfield. Acknowledgements.1. Introduction; D.L. Hatfield. Part I: Biosynthesis of selenocysteine and its incorporation into protein: 2. Selenium metabolism in bacteria; A. Böck. 3. Mammalian selenocysteine tRNA; B.A. Carlson, et al. 4. Selenophosphate selenium donor for protein and tRNA; G.M. Lacourciere. 5. SECIS elements; G.W. Martin III, M.J. Berry. 6. SECIS binding proteins; P.R. Copeland, D.M. Driscoll. 7. Towards a mechanism for selenocysteine incorporation in eukaryotes; J.B. Mansell, M.J. Berry. 8.Regulation of selenoprotein expression; R.A. Sunde. Part II: Selenium-containing proteins: 9. Identity, evolution and function of selenoproteins and selenoprotein genes; V.N. Gladyshev. 10. Bacterial selenoenzymes and mechanisms of action; T.C. Stadtman. 11. Selenoprotein P; K.E. Hill, R.F. Burk. 12. Selenoprotein W: A muscle protein in search of a function; L. Walt Ream, et al. 13. The 15 kDa selenoprotein (Sep15): functional studies and a role in cancer etiology; V.N. Gladyshev, et al. 14. Selenoproteins of the glutathione system; L. Flohé, R. Brigelius-Flohé. 15. Selenoproteins of the thioredoxin system; A. Holmgren. 16. Selenium, deiodinases and endocrine function; D.L. St. Germain. Part III: Selenium and human health: 17. Selenium as a cancer preventive agent; G.F. Combs Jr., Junxuan Lü. 18.Selenium deficiency and human disease; R.Th.J. Coppinger, A.M. Diamond. 19. Selenium as an antiviral agent; M.A. Beck. 20. Role of selenium in HIV/AIDS; M.K. Baum, et al. 21. Effects of selenium on immunity and aging; R.C. McKenzie, et al. 22. Selenium and male reproduction; L. Flohé, et al. 23. Role of low molecular weight, selenium-containing compounds in human health; H.J. Thompson. 24. Evolution of human dietary standards for selenium; O.A. Levander. 25. Selenium in Biology and human health: controversies and perspectives; V.N. Gladyshev. Index. …

Buch. Zustand: Neu. Neuware - Face Image Analysis by Unsupervised Learning explores adaptive approaches to image analysis. It draws upon principles of unsupervised learning and information theory to adapt processing to the immediate task environment. In contrast to more traditional approaches to image analysis in which relevant structure is determined in advance and extracted using hand-engineered techniques, Face Image Analysis by Unsupervised Learning explores methods that have roots in biological vision and/or learn about the image structure directly from the image ensemble. Particular attention is paid to unsupervised learning techniques for encoding the statistical dependencies in the image ensemble. The first part of this volume reviews unsupervised learning, information theory, independent component analysis, and their relation to biological vision. Next, a face image representation using independent component analysis (ICA) is developed, which is an unsupervised learning technique based on optimal information transfer between neurons. The ICA representation is compared to a number of other face representations including eigenfaces and Gabor wavelets on tasks of identity recognition and expression analysis. Finally, methods for learning features that are robust to changes in viewpoint and lighting are presented. These studies provide evidence that encoding input dependencies through unsupervised learning is an effective strategy for face recognition. Face Image Analysis by Unsupervised Learning is suitable as a secondary text for a graduate-level course, and as a reference for researchers and practitioners in industry.…