Shuai Li – författare

Twin and Family Studies of Epigenetics, Volume 27, the latest release in the Translational Epigenetics series, gathers expert opinions on epigenetic twin and family study research methods, recent findings across various disease areas, and future directions. The book provides in-depth coverage of epigenetics fundamentals, twin and family epigenetic study design, and the broader role of epigenetics in answering questions on the developmental origins of health and disease. Throughout the volume, twin and family studies are employed to examine causes of epigenetic variation, the relationship between epigenetic modifications and mental illness, cancers, cardiovascular disease, diabetes, obesity, high blood pressure, and more.

Emerging research methods applied in twin and family studies discussed include imaging epigenetics, exposure-specific DNA methylation changes, and unravelling time trends in epigenetic effects.

Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks

This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations.

Kinematic Control of Redundant Robot Arms Using Neural Networks is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation.

By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, Kinematic Control of Redundant Robot Arms Using Neural Networks is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.

Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks

This book presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations.

Kinematic Control of Redundant Robot Arms Using Neural Networks is divided into three parts: Neural Networks for Serial Robot Arm Control; Neural Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control, and follows up with chapters on adaptive dynamic programming neural networks for control; projection neural networks for robot arm control; and neural learning and control co-design for robot arm control. Next, it looks at robust neural controller design for robot arm control and teaches readers how to use neural networks to avoid robot singularity. It then instructs on neural network based Stewart platform control and neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for robot arm motion generation.

By focusing on robot arm control aided by neural networks whilst examining central topics surrounding the field, Kinematic Control of Redundant Robot Arms Using Neural Networks is an excellent book for graduate students and academic and industrial researchers studying neural dynamics, neural networks, analog and digital circuits, mechatronics, and mechanical engineering.

This collection brings together a series of empirical studies on topics surrounding classrooms of Chinese as a second language (L2) by drawing on a range of theoretical frameworks, methodological strategies, and pedagogical perspectives. Over the past two decades, research on classroom-based second language acquisition (SLA) has emerged and expanded as one of the most important sub-domains in the general field of SLA. In Chinese SLA, however, scarce attention has been devoted to this line of research. With chapters written by scholars in the field of SLA—many of whom are experienced in classroom teaching, teacher education, or program administration in Chinese as a second language—this book helps disentangle the complicated relationships among linguistic targets, pedagogical conditions, assessment tools, learner individual differences, and teacher variables that exist in the so-called "black-box" classrooms of L2 Chinese.

This collection brings together a series of empirical studies on topics surrounding classrooms of Chinese as a second language (L2) by drawing on a range of theoretical frameworks, methodological strategies, and pedagogical perspectives. Over the past two decades, research on classroom-based second language acquisition (SLA) has emerged and expanded as one of the most important sub-domains in the general field of SLA. In Chinese SLA, however, scarce attention has been devoted to this line of research. With chapters written by scholars in the field of SLA—many of whom are experienced in classroom teaching, teacher education, or program administration in Chinese as a second language—this book helps disentangle the complicated relationships among linguistic targets, pedagogical conditions, assessment tools, learner individual differences, and teacher variables that exist in the so-called "black-box" classrooms of L2 Chinese.

This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances.

It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution.

Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.

This book comprehensively covers the topics of origin and distribution, evolution and types, regional and global importance, biodiversity conservation, plant-soil interfaces, ecosystem functions and services, social-ecological systems, climate change adaptations, land degradation and restoration, grazing management and pastoral production, and sustainable future of the grasslands on the Qinghai-Tibetan Plateau (QTP), which is a globally unique eco-region called the "Roof of the World" because of its high elevation, “Third Pole on Earth" because of its alpine environment and the "Water Tower in Asia" because of its headwater location. The grassland ecosystem covers above 60% of QTP, which is about 2.5 million km2, 1/4 of Chinese total territorial lands.

The grassland ecosystem of the QTP (the Third Pole) is an important part of the palaearctic region, which features alpine cover and low oxygen. The Third Pole''s grasslands not only provide important ecosystem functions such as biodiversity conservation, carbon storage, water resource regulation, climate control, and natural disaster mitigation at a global scale, but also provide critical ecosystem services such as pastoral production, cultural inheritance, and tourism and recreation at local and regional scales.

The purposes of this monograph are to address the following questions: (1) What are the special features of the Third Pole''s grasslands? (2) How have climate changes and human activities changed the structures and functions of the Third Pole''s grasslands? (3) How can we cope with land degradation and climate change through innovative restoration and protective actions for Third Pole''s grasslands? And (4) How can we promote the sustainable development of social-ecological systems of the Third Pole''s grasslands through best management practices including grazing. The goal of this book is to attract the attention of international audiences to realize the importance of the Third Pole’s grasslands, and to call for the actions of global communities to effectively protect and sustainably use the Third Pole''s grasslands. This book can be served as textbooks, teaching materials and documentaries for different audiences. The target audiences include students, teachers, researchers, policy makers, planners, government officials, and NGOs in agricultural, environmental and natural resources sectors.

Focused on solving competition-based problems, this book designs, proposes, develops, analyzes and simulates various neural network models depicted in centralized and distributed manners. Specifically, it defines four different classes of centralized models for investigating the resultant competition in a group of multiple agents. With regard to distributed competition with limited communication among agents, the book presents the first distributed WTA (Winners Take All) protocol, which it subsequently extends to the distributed coordination control of multiple robots.

Illustrations, tables, and various simulative examples, as well as a healthy mix of plain and professional language, are used to explain the concepts and complex principles involved. Thus, the book provides readers in neurocomputing and robotics with a deeper understanding of the neural network approach to competition-based problem-solving, offers them an accessible introduction to modeling technology and the distributed coordination control of redundant robots, and equips them to use these technologies and approaches to solve concrete scientific and engineering problems.

This is the first book to focus on solving cooperative control problems of multiple robot arms using different centralized or distributed neural network models, presenting methods and algorithms together with the corresponding theoretical analysis and simulated examples. It is intended for graduate students and academic and industrial researchers in the field of control, robotics, neural networks, simulation and modelling.

In this book, we present our systematic investigations into consensus in multi-agent systems. We show the design and analysis of various types of consensus protocols from a multi-agent perspective with a focus on min-consensus and its variants. We also discuss second-order and high-order min-consensus. A very interesting topic regarding the link between consensus and path planning is also included. We show that a biased min-consensus protocol can lead to the path planning phenomenon, which means that the complexity of shortest path planning can emerge from a perturbed version of min-consensus protocol, which as a case study may encourage researchers in the field of distributed control to rethink the nature of complexity and the distance between control and intelligence. We also illustrate the design and analysis of consensus protocols for nonlinear multi-agent systems derived from an optimal control formulation, which do not require solving a Hamilton-Jacobi-Bellman (HJB) equation.

The book was written in a self-contained format. For each consensus protocol, the performance is verified through simulative examples and analyzed via mathematical derivations, using tools like graph theory and modern control theory. The book’s goal is to provide not only theoretical contributions but also explore underlying intuitions from a methodological perspective.