Climate change is a key problem of the 21st century. China, as the largest emitter of greenhouse gases, has committed to stabilize its current emissions and dramatically increase the share of electricity production from non-fossil fuels by 2030. However, this is only a first step: in the longer term, China needs to aggressively strive to reach a goal of zero-emissions. Through detailed discussions of electricity pricing, electric vehicle policies, nuclear energy policies, and renewable energy policies, this book reviews how near-term climate and energy policies can affect long-term decarbonization pathways beyond 2030, building the foundations for decarbonization in advance of its realization. Focusing primarily on the electricity sector in China - the main battleground for decarbonization over the next century - it provides a valuable resource for researchers and policymakers, as well as energy and climate experts.

Peng outlines a plausible structure for Romans 12.1 to 15.13. After a brief survey of scholars' opinions about the structure of this passage, three methodologies (structural exegesis, discourse analysis, and rhetorical criticism) are analysed. Having acknowledged that each of these methodologies has its own limitations, an eclectic approach, which is analogous with 'putting together a jigsaw puzzle without the final picture', is suggested. Peng also includes two appendices - the first is an assessment of the historical background of chapter 13.1 to 13.7 in light of the analysis presented; and the second is a short assessment of interpretations of the word 'pistis' in chapter 12.3 and 12.6, in which the rationale behind the interpretation of this term is discussed.

This book constitutes the refereed proceedings of the 30th Australasian Joint Conference on Artificial Intelligence, AI 2017, held in Melbourne, VIC, Australia, in August 2017. The 29 full papers were carefully reviewed and selected from 58 submissions. This volume covers a wide spectrum of research streams in artificial intelligence ranging from machine learning, optimization to big data science and their practical applications.