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"I know what you're going to say, but it's nothing more than saying that you're a lot worse. Liu Fan, you're not what you used to be. I also asked Zhao Tian about your past. Again, you were right to be cautious before, and you were also right to have a sense of crisis. However, you should remember that from now on, you represent the Iron and Blood Military Academy, the Iron and Blood Empire and Dean Zhou! Show your fighting spirit, as long as you don't pierce the sky, no one can help you. Of course, you can't bully others! Otherwise, I won't let you go! "
In 1933, Shih-I Hsiung (1902–1991), a student from China, met with Allardyce Nicoll, a Shakespearean scholar at the University of London, to discuss his PhD study in English drama. After learning about Hsiung’s interest and background, Nicoll suggested that he should consider studying Chinese drama for his dissertation and writing a play of a Chinese subject. Hsiung took the advice to heart and set out to write Lady Precious Stream, a play based on a classical Beijing opera. In six weeks, the writing was completed; six months later, the manuscript was accepted for publication by Methuen; and not long after, Little Theater in London agreed to produce the play, which ran for 900 successive...
This paper provides new estimates of the housing stock, construction rates and price developments by city tier in China in order to understand where imbalances might be concentrated, and the implications of any significant contraction. We also update estimates of the size of China’s rapidly evolving real estate sector through 2021, allowing one to look at the initial impact of COVID-19, as well as extending the analysis to incorporate urban-expansion related infrastructure construction. We argue that China overall faces imbalances between supply and demand for housing stock, but the problem is significantly deeper outside tier 1 cities.
This book presents the proceedings of the 6th International Conference on Frontier Computing, held in Kuala Lumpur, Malaysia on July 3–6, 2018, and provides comprehensive coverage of the latest advances and trends in information technology, science and engineering. It addresses a number of broad themes, including communication networks, business intelligence and knowledge management, web intelligence, and related fields that inspire the development of information technology. The contributions cover a wide range of topics: database and data mining, networking and communications, web and internet of things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. Many of the papers outline promising future research directions. The book is a valuable resource for students, researchers and professionals, and also offers a useful reference guide for newcomers to the field.
The Handbook on Systemic Risk, written by experts in the field, provides researchers with an introduction to the multifaceted aspects of systemic risks facing the global financial markets. The Handbook explores the multidisciplinary approaches to analyzing this risk, the data requirements for further research, and the recommendations being made to avert financial crisis. The Handbook is designed to encourage new researchers to investigate a topic with immense societal implications as well as to provide, for those already actively involved within their own academic discipline, an introduction to the research being undertaken in other disciplines. Each chapter in the Handbook will provide researchers with a superior introduction to the field and with references to more advanced research articles. It is the hope of the editors that this Handbook will stimulate greater interdisciplinary academic research on the critically important topic of systemic risk in the global financial markets.
Anomaly detection is an important topic which has been well‐studied in diverse research areas and application domains. It generally involves detection of abnormal data, unhealthy status, fault diagnosis, and can be helpful to guarantee industrial systems’ stability, security, and economy. As development of intelligent industries and sensor systems grows, large amounts of data become easily available, and challenges arise in industrial systems’ anomaly detection. One typical case is the study within energy‐related systems, like thermal energy, renewable energy study (e.g., wind energy, photovoltaic), electric vehicles, and so on. These systems can involve various data formats and more complex data structures making anomaly data detection a challenge. Currently, under the development of deep learning and big data analytics, many promising results have been achieved in energy systems’ anomaly data detection. However, many challenging problems remain unsolved due to the complex nature of energy industries. New techniques and advanced engineering applications on anomaly detection in energy systems still appeal to a wide range of scholars and industries.
Demonstrations in the following categories: Street magic -- Exhibition -- Stage performance -- Flammable -- Toxic substances -- Corrosive substances.