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The Emergence of Human Modernity

What is the origin of music? In the last few decades this centuries-old puzzle has been reinvigorated by new archaeological evidence and developments in the fields of cognitive science, linguistics, and evolutionary theory. In this path-breaking book, renowned musicologist Gary Tomlinson draws from these areas to construct a new narrative for the emergence of human music.

A Multidisciplinary Perspective

Over the past decade, an explosion of empirical research in a variety of fields has allowed us to understand human moral sensibility as a sophisticated integration of cognitive, emotional, and motivational mechanisms shaped through evolution, development, and culture. Evolutionary biologists have shown that moral cognition evolved to aid cooperation; developmental psychologists have demonstrated that the elements that underpin morality are in place much earlier than we thought; and social neuroscientists have begun to map brain circuits implicated in moral decision making.

Patents, HIV/AIDS, and Race

In The Genealogy of a Gene, Myles Jackson uses the story of the CCR5 gene to investigate the interrelationships among science, technology, and society. Mapping the varied “genealogy” of CCR5—intellectual property, natural selection, Big and Small Pharma, human diversity studies, personalized medicine, ancestry studies, and race and genomics—Jackson links a myriad of diverse topics.

Marshall Nirenberg and the Discovery of the Genetic Code

The genetic code is the Rosetta Stone by which we interpret the 3.3 billion letters of human DNA, the alphabet of life, and the discovery of the code has had an immeasurable impact on science and society. In 1968, Marshall Nirenberg, an unassuming government scientist working at the National Institutes of Health, shared the Nobel Prize for cracking the genetic code. He was the least likely man to make such an earth-shaking discovery, and yet he had gotten there before such members of the scientific elite as James Watson and Francis Crick.

Grain Vapor Ray

We have entered the Anthropocene era—a geological age of our own making, in which what we have understood to be nature is made by man. We need a new way to understand the dynamics of a new epoch. These volumes offer writings that approach the Anthropocene through the perspectives of grain, vapor, and ray—the particulate, the volatile, and the radiant. The first three volumes—each devoted to one of the three textures—offer a series of paired texts, with contemporary writers responding to historic writings. A fourth volume offers a guide to the project as a whole.

From Subtle Fluids to Molecular Biology

In 1809—the year of Charles Darwin’s birth—Jean-Baptiste Lamarck published Philosophie zoologique, the first comprehensive and systematic theory of biological evolution. The Lamarckian approach emphasizes the generation of developmental variations; Darwinism stresses selection. Lamarck’s ideas were eventually eclipsed by Darwinian concepts, especially after the emergence of the Modern Synthesis in the twentieth century.

The goal of structured prediction is to build machine learning models that predict relational information that itself has structure, such as being composed of multiple interrelated parts. These models, which reflect prior knowledge, task-specific relations, and constraints, are used in fields including computer vision, speech recognition, natural language processing, and computational biology. They can carry out such tasks as predicting a natural language sentence, or segmenting an image into meaningful components.

Mastering Complexity

In this book, Sanjoy Mahajan shows us that the way to master complexity is through insight rather than precision. Precision can overwhelm us with information, whereas insight connects seemingly disparate pieces of information into a simple picture. Unlike computers, humans depend on insight. Based on the author’s fifteen years of teaching at MIT, Cambridge University, and Olin College, The Art of Insight in Science and Engineering shows us how to build insight and find understanding, giving readers tools to help them solve any problem in science and engineering.

Category theory was invented in the 1940s to unify and synthesize different areas in mathematics, and it has proven remarkably successful in enabling powerful communication between disparate fields and subfields within mathematics. This book shows that category theory can be useful outside of mathematics as a rigorous, flexible, and coherent modeling language throughout the sciences.

Sparse modeling is a rapidly developing area at the intersection of statistical learning and signal processing, motivated by the age-old statistical problem of selecting a small number of predictive variables in high-dimensional datasets. This collection describes key approaches in sparse modeling, focusing on its applications in fields including neuroscience, computational biology, and computer vision.

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