Charles W. Fox – författare

Phenotypic variation is influenced by both genetic and environmental variation. One important source of environmental variation is the maternal effect: influences of the maternal environment on offspring phenotype. Heritable maternal effects have been shown to influence the life histories, behaviour, and population dynamics of a wide variety of plants and animals. They are likely to have evolved as a mechanism for cueing offspring to appropriate development for predicted environmental conditions. This will be the first book dealing with the broad range of maternal effects.

This text unifies conceptual and empirical advances in evolutionary ecology and provides a volume that can be used as a primary textbook or supplemental reading in an advanced undergraduate or graduate course. The focus is on current concepts in evolutionary ecology and the empirical study of these concepts. Chapters are written by prominent biologists who have made significant contributions to this field and both synthesize the current state of knowledge and identify areas for future investigation. It is divided into five major sections: an overview of the major topics in evolutionary biology for ecologists, and sections on life histories, behaviour, co-evolution, and adaptation to anthropogenic change.

The diverse field of evolutionary genetics is unified by two goals: to understand the impact that evolutionary processes have on genetic variation, and to understand the consequences of these patterns for various evolutionary process. Research in evolutionary genetics stretches across a continuum of scale, from studies of DNA sequence evolution (Ch.7 and 9), to studies of multivariate species diversity (ch.28), to rapid evolution seen over relatively short time scales in experimental evolution studies (Ch.31).

The diverse field of evolutionary genetics is unified by two goals: to understand the impact that evolutionary processes have on genetic variation, and to understand the consequences of these patterns for various evolutionary process. Research in evolutionary genetics stretches across a continuum of scale, from studies of DNA sequence evolution (Ch. 7 and 9), to studies of multivariate phenotypic evolution (Ch. 20), across a continuum of time, from ancient events that lead to current species diversity (Ch. 28), to rapid evolution seen over relatively short time scales in experimental evolution studies (Ch. 31).

The main goal of this book is to encourage and formalize the infusion of evolutionary thinking into mainstream conservation biology. It reviews the evolutionary foundations of conservation issues, and unifies conceptual and empirical advances in evolutionary conservation biology. The book can be used either as a primary textbook or as a supplementary reading in an advanced undergraduate or graduate level course - likely to be called Conservation Biology or in some cases Evolutionary Ecology. The focus of chapters is on current concepts in evolution as they pertain to conservation, and the empirical study of these concepts. The balanced treatment avoids exhaustive reviews and overlapping duplication among the chapters. Little background in genetics is assumed of the reader.

The main goal of this book is to encourage and formalize the infusion of evolutionary thinking into mainstream conservation biology. It reviews the evolutionary foundations of conservation issues, and unifies conceptual and empirical advances in evolutionary conservation biology. The book can be used either as a primary textbook or as a supplementary reading in an advanced undergraduate or graduate level course - likely to be called Conservation Biology or in some cases Evolutionary Ecology. The focus of chapters is on current concepts in evolution as they pertain to conservation, and the empirical study of these concepts. The balanced treatment avoids exhaustive reviews and overlapping duplication among the chapters. Little background in genetics is assumed of the reader.

This book introduces readers to graduate-level study of robotics through an integrated, interdisciplinary approach that spans mechatronics, control theory, computer science, and AI. It is designed to unite students from these fields, equipping them with the collaborative skills needed to excel in robotics.It is structured around three core pillars: Mechatronics, Cybernetics, and AI. Mechatronics introduces practical tools and materials for robot building, programming, and design, covering open-source hardware, sensors, actuators, and embedded systems like ROS2. Cybernetics explores feedback, control, kinematics, and dynamics, enabling the execution of complex trajectories for robots such as drones, mobile robots, and robotic arms, grounded in linear algebra and Lagrangian mechanics. AI explores modern transformer-based models, including GPTs and diffusion models, teaching robots to perceive, learn, and plan using Bayesian probability, neural networks, and PyTorch programming. Together, these sections provide a comprehensive foundation for understanding and innovating in robotics.Bridging foundational theory and real-world applications, this book is core course reading for advanced undergraduate and graduate students of robotics, mechatronics, and artificial intelligence. It is also a valuable resource for maker communities, equipping them with the skills needed to succeed in this cutting-edge field.

This book introduces readers to graduate-level study of robotics through an integrated, interdisciplinary approach that spans mechatronics, control theory, computer science, and AI. It is designed to unite students from these fields, equipping them with the collaborative skills needed to excel in robotics.It is structured around three core pillars: Mechatronics, Cybernetics, and AI. Mechatronics introduces practical tools and materials for robot building, programming, and design, covering open-source hardware, sensors, actuators, and embedded systems like ROS2. Cybernetics explores feedback, control, kinematics, and dynamics, enabling the execution of complex trajectories for robots such as drones, mobile robots, and robotic arms, grounded in linear algebra and Lagrangian mechanics. AI explores modern transformer-based models, including GPTs and diffusion models, teaching robots to perceive, learn, and plan using Bayesian probability, neural networks, and PyTorch programming. Together, these sections provide a comprehensive foundation for understanding and innovating in robotics.Bridging foundational theory and real-world applications, this book is core course reading for advanced undergraduate and graduate students of robotics, mechatronics, and artificial intelligence. It is also a valuable resource for maker communities, equipping them with the skills needed to succeed in this cutting-edge field.

This fourth installment of "The Year in Evolutionary Biology" series includes reviews on competition and the evolutionary dynamics of mutualism; rapid Hox gene evolution and the evolution of body plans; the evolutionary and conservation consequences of inbreeding-environment interactions; evolution and development of character displacement; applications of information theory to evolution; and gene duplications.NOTE: Annals volumes are available for sale as individual books or as a journal. For information on institutional journal subscriptions, please visit http://ordering.onlinelibrary.wiley.com/subs.asp?ref=1749-6632&doi=10.1111/(ISSN)1749-6632.ACADEMY MEMBERS: Please contact the New York Academy of Sciences directly to place your order (www.nyas.org). Members of the New York Academy of Science receive full-text access to Annals online and discounts on print volumes. Please visit http://www.nyas.org/MemberCenter/Join.aspx for more information about becoming a member.