980 resultados para China--Beijing


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On the ALEA Study Tour to China, Beryl Exley and her roomie Kathryn O’Sullivan pondered over their first night dilemma whilst staying at a hotel in Beijing. They read the room service guide (in English) which advised against drinking the tap water and confirming the supply of one bottle of complementary water per guest per day. The room service guide listed ‘special’ bottled water was the equivalent of $AUS7 per bottle. However the dilemma was this: sitting on the shelf above the fridge were three different kinds of water-like bottles. Each had a different label, written mainly in Chinese characters. Not wanting to mistake the bottles, Beryl and Kathryn set about decoding the text of the three bottles in question.

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This study investigates the key drivers affecting emission increases in terms of population growth, economic growth, industrial transformation, and energy use in six Chinese megacities: Beijing, Shanghai, Tianjin, Chongqing, Guangzhou, and Hong Kong. The six cities represent the most-developed regions in China and they have similar per capita carbon dioxide (CO 2) emissions as many developed countries. There is an urgent need to quantify the magnitude of each factor in driving the emissions changes in those cities so that a potential bottom-up climate mitigation policy design at the city and sectoral levels can be initiated. We adopt index decomposition analysis and present the results in both additive and multiplicative approaches to reveal the absolute and relative levels of each factor in driving emission changes during 1985-2007. Among all cities, economic effect and energy intensity effect have always been the two dominant factors contributing to the changes in carbon emissions. This study reveals that there are large variations in the ways driving forces contribute to emission levels in different cities and industrial sectors. © 2012 by Yale University.

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A new model of pattern recognition principles-Biomimetic Pattern Recognition, which is based on "matter cognition" instead of "matter classification", has been proposed. As a important means realizing Biomimetic Pattern Recognition, the mathematical model and analyzing method of ANN get breakthrough: a novel all-purpose mathematical model has been advanced, which can simulate all kinds of neuron architecture, including RBF and BP models. As the same time this model has been realized using hardware; the high-dimension space geometry method, a new means to analyzing ANN, has been researched.

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The present status and future prospects of functional information materials, mainly focusing on semiconductor microstructural materials, are introduced first in this paper. Then a brief discussion how to enhance the academic level and innovation capability of research and development of functional information materials in China are made. Finally the main problems concerning the studies of materials science and technology are analyzed, and possible measures for promoting its development are proposed.

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IEECAS SKLLQG

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Funding and support for this project was provided by NSFC (Grant No. 40771015), and Key International Science and Technology Cooperation Projects (Grant No. 22007DFC20180). The authors also gratefully acknowledge the support of Key Projects in the National Science & Technology Pillar Program in the Eleventh Five-year Plan Period (Grant No. 2006BAD01B06-02). The authors thank the CDCs of Daqing, Beijing, Tianjin, Zhengzhou, Changsha and Shenzhen cities for field and laboratory technical support.