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This Open Access book covers the concept of umami, the unique taste imparted by the amino acid glutamate, was first described in 1908 by Dr. Kikunae Ikeda of Tokyo University. Over the past century, hundreds of studies have explored the mechanistic underpinnings of the taste, leading to the characterization of the umami taste receptor in 2002. How this fifth basic taste figures into nutrition and health, however, remains underexplored. Umami: Taste for Health provides an overview of the relationship between umami and human health. Authors explain how glutamate not only produces a characteristic oral sensation in the mouth but also functions as a signaling molecule to induce physiological responses. With the support of recent studies, the book demonstrates how the taste properties of umami make glutamate a promising substance to lower salt intake, promote satiation and support healthier aging. The text also covers practical culinary applications to increase umami flavor and practical usage of umami for promoting healthy eating. Provides an overview of the relationship between umami and human health; Explores the potential of glutamate to lower salt intake, promote satiation and support healthier aging; Covers practical culinary applications of umami flavor and practical usage of umami for promoting healthy eating.

This Open-Access-book examines the phenomenon of discrimination using a descriptive approach. Discrimination is omnipresent, whether it is people who discriminate against other people or, more recently, also machines that discriminate against people. The first part of the analysis employs decision theory on discrimination, leading to two fundamental subtypes: taste-based discrimination and statistical discrimination. The second part links taste-based discrimination to social identity theory, demonstrates that not all taste-based discrimination is ultimately statistical discrimination, and reveals the evolutionary origins of our tastes. The third part surveys how people get their beliefs for statistical discrimination and thereby shows that they often deviate from Bayesianism: they have inherent prior beliefs and do not exclusively update their beliefs according to Bayes’ law. Additionally, the analysis of belief formation highlights the importance of the learning environment. The last part reassembles the previously dissected aspects of discrimination, presents a new descriptive model of discrimination, and lists five implications for a normative theory of discrimination.

This is open access book provides plenty of pleasant mathematical surprises. There are many fascinating results that do not appear in textbooks although they are accessible with a good knowledge of secondary-school mathematics. This book presents a selection of these topics including the mathematical formalization of origami, construction with straightedge and compass (and other instruments), the five- and six-color theorems, a taste of Ramsey theory and little-known theorems proved by induction. Among the most surprising theorems are the Mohr-Mascheroni theorem that a compass alone can perform all the classical constructions with straightedge and compass, and Steiner's theorem that a straightedge alone is sufficient provided that a single circle is given. The highlight of the book is a detailed presentation of Gauss's purely algebraic proof that a regular heptadecagon (a regular polygon with seventeen sides) can be constructed with straightedge and compass. Although the mathematics used in the book is elementary (Euclidean and analytic geometry, algebra, trigonometry), students in secondary schools and colleges, teachers, and other interested readers will relish the opportunity to confront the challenge of understanding these surprising theorems.

This open access book makes quantum computing more accessible than ever before. A fast-growing field at the intersection of physics and computer science, quantum computing promises to have revolutionary capabilities far surpassing “classical” computation. Getting a grip on the science behind the hype can be tough: at its heart lies quantum mechanics, whose enigmatic concepts can be imposing for the novice. This classroom-tested textbook uses simple language, minimal math, and plenty of examples to explain the three key principles behind quantum computers: superposition, quantum measurement, and entanglement. It then goes on to explain how this quantum world opens up a whole new paradigm of computing. The book bridges the gap between popular science articles and advanced textbooks by making key ideas accessible with just high school physics as a prerequisite. Each unit is broken down into sections labelled by difficulty level, allowing the course to be tailored to the student’s experience of math and abstract reasoning. Problem sets and simulation-based labs of various levels reinforce the concepts described in the text and give the reader hands-on experience running quantum programs. This book can thus be used at the high school level after the AP or IB exams, in an extracurricular club, or as an independent project resource to give students a taste of what quantum computing is really about. At the college level, it can be used as a supplementary text to enhance a variety of courses in science and computing, or as a self-study guide for students who want to get ahead. Additionally, readers in business, finance, or industry will find it a quick and useful primer on the science behind computing’s future.

This open access textbook welcomes students into the fundamental theory of measure, integration, and real analysis. Focusing on an accessible approach, Axler lays the foundations for further study by promoting a deep understanding of key results. Content is carefully curated to suit a single course, or two-semester sequence of courses, creating a versatile entry point for graduate studies in all areas of pure and applied mathematics. Motivated by a brief review of Riemann integration and its deficiencies, the text begins by immersing students in the concepts of measure and integration. Lebesgue measure and abstract measures are developed together, with each providing key insight into the main ideas of the other approach. Lebesgue integration links into results such as the Lebesgue Differentiation Theorem. The development of products of abstract measures leads to Lebesgue measure on Rn. Chapters on Banach spaces, Lp spaces, and Hilbert spaces showcase major results such as the Hahn–Banach Theorem, Hölder’s Inequality, and the Riesz Representation Theorem. An in-depth study of linear maps on Hilbert spaces culminates in the Spectral Theorem and Singular Value Decomposition for compact operators, with an optional interlude in real and complex measures. Building on the Hilbert space material, a chapter on Fourier analysis provides an invaluable introduction to Fourier series and the Fourier transform. The final chapter offers a taste of probability. Extensively class tested at multiple universities and written by an award-winning mathematical expositor, Measure, Integration & Real Analysis is an ideal resource for students at the start of their journey into graduate mathematics. A prerequisite of elementary undergraduate real analysis is assumed; students and instructors looking to reinforce these ideas will appreciate the electronic Supplement for Measure, Integration & Real Analysis that is freely available online.