Barbara Rolls, one of America's leading authorities on weight management, comes a much-anticipated lifestyle guide and cookbook that empowers and encourages her readers to quit "dieting" for good, to feel full on fewer calories, and to lose weight and keep it off while eating satisfying portions of delicious, nutritious foods. The Volumetrics Eating Plan doesn't eliminate food groups or overload you with rules. It's a commonsense approach to eating based on Dr. Rolls's hugely popular Volumetrics Weight-Control Plan and her respected research on satiety that shows you how to choose foods that control hunger while losing weight. Along with menu planners, charts, and sidebars on healthy food choices, the 125 recipes put her revolutionary research into real and tangible instructions for every meal. The full-color photographs make these delicious recipes irresistible. With this important new guide to healthy eating and living, everyone can enjoy tasty and satisfying meals that will help them maintain their weight or lose those extra pounds while learning the pleasures of cooking the Volumetrics way. Volumetrics, Dr. Rolls's rigorously tested and proven system for weight management, incorporates sound research findings from around the world into a nutritious plan and shows you how to personalize it to suit your preferences and goals. It's all about choices, and The Volumetrics Eating Plan helps you choose the right foods for every meal and every lifestyle, without giving up flavor or diversity in your diet. No more "forbidden foods" or monotonous meals -- The Volumetrics Eating Plan will revolutionize the way you think about managing your weight and will guide you to a lifetime of healthy food choices.

    The exposition is simple and leads to the most complete direct means of solving problems in mechanics. The final sections on adiabatic invariants have been revised and augmented. In addition a short biography of L D Landau has been inserted.

    It has an algebra and trigonometry prerequisite, but calculus is preferred.

    Could she use quantum tunnelling to get through the neighbour's fence and chase bunnies? What about quantum teleportation to catch squirrels before they climb out of reach? In this witty and informative book, Orzel and Emmy - the talking dog - discuss the key theories of Quantum Physics and its fascinating history. From quarks and gluons to Heisenberg's uncertainty principle, this is the perfect introduction to the fundamental laws which govern the universe.

    Organized around the central concept of a vector space, the book includes numerous physical applications in the body of the text as well as many problems of a physical nature. It is also one of the purposes of this book to introduce the physicist to the language and style of mathematics as well as the content of those particular subjects with contemporary relevance in physics.Chapters 1 and 2 are devoted to the mathematics of classical physics. Chapters 3, 4 and 5 — the backbone of the book — cover the theory of vector spaces. Chapter 6 covers analytic function theory. In chapters 7, 8, and 9 the authors take up several important techniques of theoretical physics — the Green's function method of solving differential and partial differential equations, and the theory of integral equations. Chapter 10 introduces the theory of groups. The authors have included a large selection of problems at the end of each chapter, some illustrating or extending mathematical points, others stressing physical application of techniques developed in the text.Essentially self-contained, the book assumes only the standard undergraduate preparation in physics and mathematics, i.e. intermediate mechanics, electricity and magnetism, introductory quantum mechanics, advanced calculus and differential equations. The text may be easily adapted for a one-semester course at the graduate or advanced undergraduate level.

    One can trace its roots to the Calculus of Variations and the work of Euler and Lagrange. This natural and reasonable approach to mathematical programming covers numerical methods for finite-dimensional optimization problems. It begins with very simple ideas progressing through more complicated concepts, concentrating on methods for both unconstrained and constrained optimization.

    But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like nonparametric curve estimation, bootstrapping, and clas- sification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analyzing data. For some time, statistics research was con- ducted in statistics departments while data mining and machine learning re- search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algo- rithms are more scalable than statisticians ever thought possible. Formal sta- tistical theory is more pervasive than computer scientists had realized.

    Includes many examples and figures. GENERAL TOPOLOGY. Set Theory and Logic. Topological Spaces and Continuous Functions. Connectedness and Compactness. Countability and Separation Axioms. The Tychonoff Theorem. Metrization Theorems and paracompactness. Complete Metric Spaces and Function Spaces. Baire Spaces and Dimension Theory. ALGEBRAIC TOPOLOGY. The Fundamental Group. Separation Theorems. The Seifert-van Kampen Theorem. Classification of Surfaces. Classification of Covering Spaces. Applications to Group Theory. For anyone needing a basic, thorough, introduction to general and algebraic topology and its applications.