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The Growth of Grammar

How do children begin to use language? How does knowledge of language emerge in early infancy, and how does it grow? This textbook offers a comprehensive introduction to knowledge acquisition, drawing on empirical evidence and linguistic theory. The theoretical framework used is the generative theory of Universal Grammar; students should have some familiarity with concepts in linguistic research. Aimed at upper-level undergraduate and graduate students, the book offers end-of-chapter summaries, key words, study questions, and exercises.

An Introduction with Readings

Vaccination has long been a familiar, highly effective form of medicine and a triumph of public health. Because vaccination is both an individual medical intervention and a central component of public health efforts, it raises a distinct set of legal and ethical issues—from debates over their risks and benefits to the use of government vaccination requirements—and makes vaccine policymaking uniquely challenging. This volume examines the full range of ethical and policy issues related to the development and use of vaccines in the United States and around the world.

This book introduces students to the growing research field of health economics. Rather than offer details about health systems without providing a theoretical context, Health Economics combines economic concepts with empirical evidence to enhance readers’ economic understanding of how health care institutions and markets function.

An Introduction to Inductive Logic

This textbook offers a thorough and practical introduction to inductive logic. The book covers a range of different types of inferences with an emphasis throughout on representing them as arguments. This allows the reader to see that, although the rules and guidelines for making each type of inference differ, the purpose is always to generate a probable conclusion.

A Cyber-Physical Systems Approach

The most visible use of computers and software is processing information for human consumption. The vast majority of computers in use, however, are much less visible. They run the engine, brakes, seatbelts, airbag, and audio system in your car. They digitally encode your voice and construct a radio signal to send it from your cell phone to a base station. They command robots on a factory floor, power generation in a power plant, processes in a chemical plant, and traffic lights in a city.

“Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.”
—Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX

This book offers an accessible guide to the financial aspects of launching and operating a high-tech business in such areas as engineering, computing, and science. It explains a range of subjects—from risk analysis to stock incentive programs for founders and key employees—for students and aspiring entrepreneurs who have no prior training in finance or accounting.

Photographs have been doctored since photography was invented. Dictators have erased people from photographs and from history. Politicians have manipulated photos for short-term political gain. Altering photographs in the predigital era required time-consuming darkroom work. Today, powerful and low-cost digital technology makes it relatively easy to alter digital images, and the resulting fakes are difficult to detect. The field of photo forensics—pioneered in Hany Farid’s lab at Dartmouth College—restores some trust to photography.

This textbook presents a wide range of subjects in neuroscience from a computational perspective. It offers a comprehensive, integrated introduction to core topics, using computational tools to trace a path from neurons and circuits to behavior and cognition. Moreover, the chapters show how computational neuroscience—methods for modeling the causal interactions underlying neural systems—complements empirical research in advancing the understanding of brain and behavior.

A Guide for the Practicing Neuroscientist

As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each chapter begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data.

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