This book shows a panorama of sustainable development practices covering 70 major cities. This book has created the analysis framework of the "New Normal" of China's economy, demonstrated the features and connotation of the "New Normal", carried out in-depth analysis and systematic study on the connotation and extension of the "New Normal" of China's economy from ten aspects including growth shift, structural upgrading, innovation drive, regional synergy, moderate inflation, reform bonus, opening-up forced, risk exposure, sustainable development and macro-control in details and proposed targeted policy suggestions with practical application value that adapt to the new normal of China's economy and ensure the sustained, steady and healthy operation of the macro-economy.

This book is based on multidisciplinary research focusing on low-carbon healthy city planning, policy and assessment. This includes city-development strategy, energy, environment, healthy, land-use, transportation, infrastructure, information and other related subjects. This book begins with the current status and problems of low-carbon healthy city development in China. It then introduces the global experience of different regions and different policy trends, focusing on individual cases. Finally, the book opens a discussion of Chinese low-carbon healthy city development from planning and design, infrastructure and technology assessment-system perspectives. It presents a case study including the theory and methodology to support the unit city theory for low-carbon healthy cities. The book lists the ranking of China's 269 high-level cities, with economic, environmental, resource, construction, transportation and health indexes as an assessment for creating a low-carbon healthy future. The book provides readers with a comprehensive overview of building low-carbon healthy cities in China.

This book will cover the most recent progress on the use of low-cost nanomaterials and development of low-cost/large scale processing techniques for greener and more efficient energy related applications, including but not limited to solar cells, energy storage, fuel cells, hydrogen generation, biofuels, etc.

Leading researchers will be invited to author chapters in the field with their expertise. Each chapter will provide general introduction to a specific topic, current status of research and development, research challenges and outlook for future direction of research.

This book aims to benefit a broad readership, from undergraduate/graduate students to researchers working on renewable energy.

This book is a part of the Proceedings of the Seventh International Symposium on Neural Networks (ISNN 2010), held on June 6-9, 2010 in Shanghai, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural networks and related fields, with a successful sequence of ISNN series in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), Beijing (2008), and Wuhan (2009). Following the tradition of ISNN series, ISNN 2010 provided a high-level international forum for scientists, engineers, and educators to present the state-of-the-art research in neural networks and related fields, and also discuss the major opportunities and challenges of future neural network research. Over the past decades, the neural network community has witnessed significant breakthroughs and developments from all aspects of neural network research, including theoretical foundations, architectures, and network organizations, modeling and simulation, empirical studies, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, has provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large scale, and networked brain-like intelligent systems. This long-term goals can only be achieved with the continuous efforts from the community to seriously investigate various issues on neural networks and related topics.

This book describes systematically the theory and technology of the precision forming of large, complex and thin-walled superalloy castings for aircraft engines, covering all the important basic aspects of the manufacturing process, including process design, wax pattern, ceramic molds, casting and solidification, heat treatment, repair casting and dimension precision control. The correlation of casting defects, structural characteristics and performance of castings is revealed through a range of tests. It also discusses the latest technologies and advances in this field - such as imaging the solidification process by means of synchrotron radiography, 3D computerized tomography and reconstruction of microporosity defects, analysis and diagnosis of error sources for dimension over-tolerance and adjusted pressure casting technology - which are of particular interest. Providing essential insights, the book offers a valuable guide to the design and manufacture of superalloy casting parts for aircraft engines.

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This "big data" provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

Airborne Microplastics: Analysis, Fate and Human Health Effects, Volume 105 in the Comprehensive Analytical Chemistry series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors.

This book describes systematically the theory and technology of the precision forming of large, complex and thin-walled superalloy castings for aircraft engines, covering all the important basic aspects of the manufacturing process, including process design, wax pattern, ceramic molds, casting and solidification, heat treatment, repair casting and dimension precision control. The correlation of casting defects, structural characteristics and performance of castings is revealed through a range of tests. It also discusses the latest technologies and advances in this field - such as imaging the solidification process by means of synchrotron radiography, 3D computerized tomography and reconstruction of microporosity defects, analysis and diagnosis of error sources for dimension over-tolerance and adjusted pressure casting technology - which are of particular interest. Providing essential insights, the book offers a valuable guide to the design and manufacture of superalloy casting parts for aircraft engines.

Nuclear Power Plant Design and Analysis Codes: Development, Validation, and Application presents the latest research on the most widely used nuclear codes and the wealth of successful accomplishments which have been achieved over the past decades by experts in the field. Editors Wang, Li,Allison, and Hohorst and their team of authors provide readers with a comprehensive understanding of nuclear code development and how to apply it to their work and research to make their energy production more flexible, economical, reliable and safe. Written in an accessible and practical way, each chapter considers strengths and limitations, data availability needs, verification and validation methodologies and quality assurance guidelines to develop thorough and robust models and simulation tools both inside and outside a nuclear setting. This book benefits those working in nuclear reactor physics and thermal-hydraulics, as well as those involved in nuclear reactor licensing. It also provides early career researchers with a solid understanding of fundamental knowledge of mainstream nuclear modelling codes, as well as the more experienced engineers seeking advanced information on the best solutions to suit their needs.

Nuclear Power Reactor Designs: From History to Advances analyzes nuclear designs throughout history and explains how each of those has helped to shape and inform the nuclear reactor designs of today and the future. Focused on the structure, systems and relevant components of each reactor design, this book provides the readers with answers to key questions to help them understand the benefits of each design. Each reactor design is introduced, their origin defined, and the relevant research presented before an analysis of its successes, what was learned, and how research and technology advanced as a result are presented. Students, researchers and early career engineers will gain a solid understanding of how nuclear designs have evolved, and how they will continue to develop in the future.

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization, control and resilience management that can be applied to further success. In both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. This "big data" provides new opportunities to improve decision making and addresses risk for individuals as well in organizations. While utilizing data smartly can enhance decision making, how to use and incorporate data into the decision making framework remains a challenging topic. Ultimately the chapters in this book present new models and frameworks to help overcome this obstacle. Optimization and Control for Systems in the Big-Data Era: Theory and Applications is divided into five parts. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications. Part III provides novel insights and new findings in the area of financial optimization analysis. The chapters in Part IV deal with operations analysis, covering flow-shop operations and quick response systems. The book concludes with final remarks and a look to the future of big data related optimization and control problems.

This book is based on multidisciplinary research focusing on low-carbon healthy city planning, policy and assessment. This includes city-development strategy, energy, environment, healthy, land-use, transportation, infrastructure, information and other related subjects. This book begins with the current status and problems of low-carbon healthy city development in China. It then introduces the global experience of different regions and different policy trends, focusing on individual cases. Finally, the book opens a discussion of Chinese low-carbon healthy city development from planning and design, infrastructure and technology assessment-system perspectives. It presents a case study including the theory and methodology to support the unit city theory for low-carbon healthy cities. The book lists the ranking of China's 269 high-level cities, with economic, environmental, resource, construction, transportation and health indexes as an assessment for creating a low-carbon healthy future. The book provides readers with a comprehensive overview of building low-carbon healthy cities in China.

In the face of increasingly serious resource and environmental challenges, the world has already accepted low-carbon development as the main way forward for future city construction. Chinese cities have encountered many problems during their development, including land constraints, energy shortages, traffic congestion and air pollution. For this reason, the national meeting of the Central Work Conference on Urbanization made the strategic decision to take a new approach to urbanization and indicated that in future the key features of urbanization in China will be low-carbon development and harmony between the environment and resources. This book discusses the "low-carbon city" as the new pattern of Chinese urbanization. This represents a major change and takes "intensive land use," "intelligent," "green" and "low carbon" as its key words. Low carbon will become an important future development direction for Chinese urbanization development. In the twenty-first Century in response to the global climate change, countries have started a wave of low-carbon city construction. But in China, there are still many disputes and misunderstandings surrounding the issue. Due to a lack of research, low-carbon city construction in China is still in the early stages, and while there have been successes, there have also been failures. There are complex and diverse challenges in applying low-carbon development methods in the context of today's Chinese cities. The construction of low-carbon cities requires efficient government, the technological innovation of enterprises, and professional scholars, but also efforts on the part of the public to change their daily activities. Based on the above considerations, the collection brings together experts from urban planning and design, clean-energy systems, low-carbon transportation, new types of city infrastructure and smart cities etc., in the hope of forming some solutions for Chinese low-carbon city development.

Serum Pharmacochemistry of Traditional Chinese Medicine: Technologies, Strategies and Applications provides a valuable and indispensable guide on the latest methods, research advances, and applications in this area. Chapters offer cutting-edge information on pharmacokinetics and pharmacodynamics, analytical chemistry, traditional medicine, natural products, bioinformatics, new technologies, therapeutic applications, and more. For researchers and students in academia and industry, this book provides a hands-on description of experimental techniques, along with beneficial guidelines to help advance research in the fields of Traditional Chinese Medicine and drug development.

This book will cover the most recent progress on the use of low-cost nanomaterials and development of low-cost/large scale processing techniques for greener and more efficient energy related applications, including but not limited to solar cells, energy storage, fuel cells, hydrogen generation, biofuels, etc. Leading researchers will be invited to author chapters in the field with their expertise. Each chapter will provide general introduction to a specific topic, current status of research and development, research challenges and outlook for future direction of research. This book aims to benefit a broad readership, from undergraduate/graduate students to researchers working on renewable energy.

This book is a part of the Proceedings of the Seventh International Symposium on Neural Networks (ISNN 2010), held on June 6-9, 2010 in Shanghai, China. Over the past few years, ISNN has matured into a well-established premier international symposium on neural networks and related fields, with a successful sequence of ISNN series in Dalian (2004), Chongqing (2005), Chengdu (2006), Nanjing (2007), Beijing (2008), and Wuhan (2009). Following the tradition of ISNN series, ISNN 2010 provided a high-level international forum for scientists, engineers, and educators to present the state-of-the-art research in neural networks and related fields, and also discuss the major opportunities and challenges of future neural network research. Over the past decades, the neural network community has witnessed significant breakthroughs and developments from all aspects of neural network research, including theoretical foundations, architectures, and network organizations, modeling and simulation, empirical studies, as well as a wide range of applications across different domains. The recent developments of science and technology, including neuroscience, computer science, cognitive science, nano-technologies and engineering design, among others, has provided significant new understandings and technological solutions to move the neural network research toward the development of complex, large scale, and networked brain-like intelligent systems. This long-term goals can only be achieved with the continuous efforts from the community to seriously investigate various issues on neural networks and related topics.

Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.

The two-volume set LNCS 7367 and 7368 constitutes the refereed proceedings of the 9th International Symposium on Neural Networks, ISNN 2012, held in Shenyang, China, in July 2012. The 147 revised full papers presented were carefully reviewed and selected from numerous submissions. The contributions are structured in topical sections on mathematical modeling; neurodynamics; cognitive neuroscience; learning algorithms; optimization; pattern recognition; vision; image processing; information processing; neurocontrol; and novel applications.

The two-volume set LNCS 7367 and 7368 constitutes the refereed proceedings of the 9th International Symposium on Neural Networks, ISNN 2012, held in Shenyang, China, in July 2012. The 147 revised full papers presented were carefully reviewed and selected from numerous submissions. The contributions are structured in topical sections on mathematical modeling; neurodynamics; cognitive neuroscience; learning algorithms; optimization; pattern recognition; vision; image processing; information processing; neurocontrol; and novel applications.

The 2008 IEEE World Congress on Computational Intelligence (WCCI 2008), held during June 1-6, 2008 in Hong Kong, China, marked an important milestone in advancing the paradigms of the new fields of computational intelligence. As the fifth event in the series that has spanned the globe (Orlando-1994, Anchorage-1998, Honolulu-2002, Vancouver-2006), the congress offered renewed and refreshing focus on the progress in nature-inspired and linguistically motivated computation. Most of the congress's program featured regular and special technical sessions that provided participants with new insights into the most recent developments in the field. As a tradition, in addition to the parallel technical sessions, WCCI holds a series of plenary and invited lectures which are not included in the congress proceedings. As its predecessors, at WCCI 2008, 20 expert speakers shared their expertise on broader, if not panoramic, topics spanning a diverse spectrum of computational intelligence in the areas of neurocomputing, fuzzy systems, evolutionary computation, and adjacent areas. Thanks to their time and expertise, we endeavored to offer this volume to attendees directly at the congress and the general public afterwards.

The three volume set LNCS 3496/3497/3498 constitutes the refereed proceedings of the Second International Symposium on Neural Networks, ISNN 2005, held in Chongqing, China in May/June 2005.

The 483 revised papers presented were carefully reviewed and selected from 1.425 submissions. The papers are organized in topical sections on theoretical analysis, model design, learning methods, optimization methods, kernel methods, component analysis, pattern analysis, systems modeling, signal processing, image processing, financial analysis, control systems, robotic systems, telecommunication networks, incidence detection, fault diagnosis, power systems, biomedical applications, industrial applications, and other applications.

The three volume set LNCS 3496/3497/3498 constitutes the refereed proceedings of the Second International Symposium on Neural Networks, ISNN 2005, held in Chongqing, China in May/June 2005.

The 483 revised papers presented were carefully reviewed and selected from 1.425 submissions. The papers are organized in topical sections on theoretical analysis, model design, learning methods, optimization methods, kernel methods, component analysis, pattern analysis, systems modeling, signal processing, image processing, financial analysis, control systems, robotic systems, telecommunication networks, incidence detection, fault diagnosis, power systems, biomedical applications, industrial applications, and other applications.

This book and its sister volumes constitute the proceedings of the 2nd International Symposium on Neural Networks (ISNN 2005). ISNN 2005 was held in the beautiful mountain city Chongqing by the upper Yangtze River in southwestern China during May 30-June 1, 2005, as a sequel of ISNN 2004 successfully held in Dalian, China. ISNN emerged as a leading conference on neural computation in the region with - creasing global recognition and impact. ISNN 2005 received 1425 submissions from authors on ?ve continents (Asia, Europe, North America, South America, and Oc- nia), 33 countries and regions (Mainland China, Hong Kong, Macao, Taiwan, South Korea, Japan, Singapore, Thailand, India, Nepal, Iran, Qatar, United Arab Emirates, Turkey, Lithuania, Hungary, Poland, Austria, Switzerland, Germany, France, Sweden, Norway, Spain, Portugal, UK, USA, Canada, Venezuela, Brazil, Chile, Australia, and New Zealand). Based on rigorous reviews, 483 high-quality papers were selected by the Program Committee for presentation at ISNN 2005 and publication in the proce- ings, with an acceptance rate of less than 34%. In addition to the numerous contributed papers, 10 distinguished scholars were invited to give plenary speeches and tutorials at ISNN 2005.

This book constitutes the proceedings of the International Symposium on Neural N- works (ISNN 2004) held in Dalian, Liaoning, China during August 19-21, 2004. ISNN 2004 received over 800 submissions from authors in ?ve continents (Asia, Europe, North America, South America, and Oceania), and 23 countries and regions (mainland China, Hong Kong, Taiwan, South Korea, Japan, Singapore, India, Iran, Israel, Turkey, H- gary, Poland, Germany, France, Belgium, Spain, UK, USA, Canada, Mexico, Venezuela, Chile, and Australia). Based on reviews, the Program Committee selected 329 hi- quality papers for presentation at ISNN 2004 and publication in the proceedings. The papers are organized into many topical sections under 11 major categories (theore- cal analysis; learning and optimization; support vector machines; blind source sepa- tion, independent component analysis, and principal component analysis; clustering and classi?cation; robotics and control; telecommunications; signal, image and time series processing; detection, diagnostics, and computer security; biomedical applications; and other applications) covering the whole spectrum of the recent neural network research and development. In addition to the numerous contributed papers, ?ve distinguished scholars were invited to give plenary speeches at ISNN 2004. ISNN 2004 was an inaugural event. It brought together a few hundred researchers, educators, scientists, and practitioners to the beautiful coastal city Dalian in northeastern China.