Introduction to Nanoscience and Nanotechnology explains nanotechnology to an audience that does not necessarily have a scientific background. It covers all aspects, including the new areas of biomedical applications and the use of nanotechnology to probe the "quantum vacuum." After discussing the present state of the art in nanotechnology, the book makes estimates of where these technologies are going and what will be possible in the future.

This book provides knowledge of the basic theory, spectral analysis methods, chemometrics, instrumentation, and applications of near-infrared (NIR) spectroscopy—not as a handbook but rather as a sourcebook of NIR spectroscopy.

Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survial of the fittest, have made it possible to solve numerically many complex, non-standarard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modelling, neural networks,optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection, computer vision, semiconductor design, population biology, dynamic Bayesian networks, and time series analysis. This will be of great value to students, researchers and practicioners, who have some basic knowledge of probability. Arnaud Doucet received the Ph. D. degree from the University of Paris- XI Orsay in 1997. From 1998 to 2000, he conducted research at the Signal Processing Group of Cambridge University, UK. He is currently an assistant professor at the Department of Electrical Engineering of Melbourne University, Australia. His research interests include Bayesian statistics, dynamic models and Monte Carlo methods. Nando de Freitas obtained a Ph.D. degree in information engineering from Cambridge University in 1999. He is presently a research associate with the artificial intelligence group of the University of California at Berkeley. His main research interests are in Bayesian statistics and the application of on-line and batch Monte Carlo methods to machine learning.

This book presents the latest research results on plant genes controlling tolerance to abiotic stresses including heat, cold, drought, salt, nitrogen, metals, irradiation, and exogenous phytohormones.
The authors report the expression profiles, function/roles in physiological pathways, and chromosomal locations of tolerance genes. The studies involve cytogenetics, genomics, proteomics, and bioinformatics. The information is critical for food security in an environment experiencing global climate changes. Therefore, this book provides a useful reference to students and professionals in plant sciences encompassing genetics, physiology, chemistry, and breeding.

Die technischen Fortschritte und neuen Möglichkeiten der molekularen Biologie – Genomanalysen, Expressionsanalysen, konfokale Lasermikroskopie, Proteomics – lassen die Physiologie von Wirbeltieren, genauso wie die von Nicht-Wirbeltieren, in einem neuen Licht erscheinen.