Provides a review of introductory noncalculus-based physics for those who do not have a strong background in mathematics.

    David Peat explains the development and meaning of this Superstring Theory in a thoroughly readable, dramatic manner accessible to lay readers with no knowledge of mathematics. The consequences of the Superstring Theory are nothing less than astonishing.

    With amusing examples from film, TV, and history, learn how physics affects everything in your surroundings--without the use of mind-bending math or the need for a particle accelerator. With E=MC2, you'll learn: When forces balance: Simple answers to questions such as, "Why do balloons rise while apples fall?" The Good, the Bad, and the Impossible: Why The Good, the Bad, and the Ugly is full of absurdities. (For someone whose characters often uphold the law, Clint Eastwood certainly defies the laws of physics in this film.) AC/DC: but only AC really rocks: Alternating current (AC) is much more complicated than direct current (DC). The voltage is constantly moving between positive and negative; the current therefore flows one way, and then the other (rocking back and forth). Why do I feel this warm glow?: The theory behind how the first stars were born General Relativity and GPS: The strange result of gravity on time is well proven. Compared to the interminable time you experience while stuck in a traffic jam, time literally runs faster (because gravity is weaker) in the orbiting GPS satellites that help your GPS system get its fix. At the speed of light: A refresher on the theory of relativity and an understanding of why--a hundred years later--Einstein's physics still points the way in cutting-edge research. Yu again: In the martial arts movie Crouching Tiger, Hidden Dragon, the rebellious young heroine, Jen Yu, blocks an attacker with her hand without standing or bracing herself. All the while, she holds a cup of tea in her other hand and doesn't spill a drop. Find out why kinetic energy and scalar quantity make her move impossible. It's physics for the rest of us. So why not come along for the ride? Advance at the speed of light through the fundamental laws of physics as they were discovered, proven wrong, and revolutionized. Make this and all of the Blackboard Books(tm) a permanent fixture on your shelf, and you'll have instant access to a breadth of knowledge. Whether you need homework help or want to win that trivia game, this series is the trusted source for fun facts.

     Offers extensively updated coverage, new problem sets, and chapter-ending material to enhance the book’s relevance to today’s engineers and scientists. Includes new problem sets demonstrating updated applications to engineering as well as biological, physical, and computer science. Emphasizes key ideas as well as the risks and hazards associated with practical application of the material. Includes new material on topics including: difference between discrete and continuous measurements; binary data; quartiles; importance of experimental design; “dummy” variables; rules for expectations and variances of linear functions; Poisson distribution; Weibull and lognormal distributions; central limit theorem, and data plotting. Introduces Bayesian statistics, including its applications to many fields. For those interested in learning more about probability and statistics.

    KEY TOPICS: This classic book enables readers to make connections between classical and modern physics - an indispensable part of a physicist's education. In this new edition, Beams Medal winner Charles Poole and John Safko have updated the book to include the latest topics, applications, and notation, to reflect today's physics curriculum. They introduce readers to the increasingly important role that nonlinearities play in contemporary applications of classical mechanics. New numerical exercises help readers to develop skills in how to use computer techniques to solve problems in physics. Mathematical techniques are presented in detail so that the book remains fully accessible to readers who have not had an intermediate course in classical mechanics. MARKET: For college instructors and students.

    Subsequent sections deal with integrating factors; dilution and accretion problems; linearization of first order systems; Laplace Transforms; Newton's Interpolation Formulas, more.

    According to theorists, the missing six are curled up in bizarre structures known as Calabi-Yau manifolds. In The Shape of Inner Space, Shing-Tung Yau, the man who mathematically proved that these manifolds exist, argues that not only is geometry fundamental to string theory, it is also fundamental to the very nature of our universe.Time and again, where Yau has gone, physics has followed. Now for the first time, readers will follow Yau’s penetrating thinking on where we’ve been, and where mathematics will take us next. A fascinating exploration of a world we are only just beginning to grasp, The Shape of Inner Space will change the way we consider the universe on both its grandest and smallest scales.

    The analytic material is accompanied by many applications, examples, and exercises. The theory of noncooperative games studies the behavior of agents in any situation where each agent's optimal choice may depend on a forecast of the opponents' choices. "Noncooperative" refers to choices that are based on the participant's perceived selfinterest. Although game theory has been applied to many fields, Fudenberg and Tirole focus on the kinds of game theory that have been most useful in the study of economic problems. They also include some applications to political science. The fourteen chapters are grouped in parts that cover static games of complete information, dynamic games of complete information, static games of incomplete information, dynamic games of incomplete information, and advanced topics.--mitpress.mit.edu

    Mark Plaster takes readers beyond the ambulance bay doors into the stranger-than-fiction world of the Emergency Department. By turns heart-warming and gut-wrenching, "Night Shift" chronicles the ebb and flow of human life, in all of its unvarnished glory, as it passes through the doors of the ED.

    Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning.

    The concept of speaking to mountains and trees may not be religious metaphor, but laws of a new physics that have not been fully understood. Jesus taught that our words are powerful enough to move physical matter. Quantum physics has discovered that subatomic particles respond to the observer. In this book, you will discover that your words and your faith (beliefs) are unseen forces that affect everything in your world. You are the one giving substance to your world through words!

    A.A. members know of Dr. Paul's wisdom through the often-quoted passage from his story in A.A.'s Big Book, Alcoholics Anonymous. Dr. Paul continues sharing his astute insight and gentle humor with discussions of the physical, mental, emotional, interpersonal and spiritual aspects of sobriety.

    Based on a course of lectures delivered by the author at Columbia University, the text is elementary in treatment and remarkable for its clarity and organization. Although it is assumed that the reader is familiar with the fundamental facts of thermometry and calorimetry, no advanced mathematics beyond calculus is assumed.Partial contents: thermodynamic systems, the first law of thermodynamics (application, adiabatic transformations), the second law of thermodynamics (Carnot cycle, absolute thermodynamic temperature, thermal engines), the entropy (properties of cycles, entropy of a system whose states can be represented on a (V, p) diagram, Clapeyron and Van der Waals equations), thermodynamic potentials (free energy, thermodynamic potential at constant pressure, the phase rule, thermodynamics of the reversible electric cell), gaseous reactions (chemical equilibria in gases, Van't Hoff reaction box, another proof of the equation of gaseous equilibria, principle of Le Chatelier), the thermodynamics of dilute solutions (osmotic pressure, chemical equilibria in solutions, the distribution of a solute between 2 phases vapor pressure, boiling and freezing points), the entropy constant (Nernst's theorem, thermal ionization of a gas, thermionic effect, etc.).

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

    Written for a senior-level course, this engineering textbook presents the concepts of feedback control system theory as they have been developed in the frequency and time domains, discussing such topics as robust control systems, state variable models, computer control systems, internal model contro