From the perspective of local decision makers, this study is an important basis when local environment and energy policies are making. Expansion of industrial scale has been the main driving factor of energy consumption and carbon emissions. While the change of industrial kinase inhibitor Trichostatin A structure and maximize energy efficiency are effective measures to conserve energy and reduce emissions. Specific measures are as follows: (1) In terms of energy efficiency, local government continuously eliminates high-energy-consumption industries and backward production capacity. In the meantime, they should in favor of high and advanced production technology to maximize energy efficiency, especially for some high-energy-consumption or high-resource-consumption industries, such as Sectors 23 (Electric Power/Steam and Hot Water Production and Supply), 14 (Smelting and Pressing of Ferrous and Nonferrous Metals), etc.

(2) Industrial structural change makes great impact on carbon emissions structure. Beijing has made great efforts for industrial structural change, for example, Beijing is greatly developing the tertiary industries and reducing the proportion of primary industries and secondary industries. However, detailed industrial structure should be adjusted based on the carbon consuming responsibilities. Acknowledgments This study has been supported by Innovation Project Foundation of Beijing Academy of Science and Technology (Grant no. PXM2011_178215_000003).
Electromyography (EMG) is the electrical activity of muscle cells and has been used for the classification of actions [1�C7], disease detection [8], prosthetic hand control [9], and emotion detection [10].

In this study, 8 channels recorded the EMG signals of 10 aggressive and 10 normal Dacomitinib actions of 3 males and 1 female, which were then analyzed for classifying normal and aggressive actions. With this purpose in mind, a composed model of higher-order spectra (HOS) and the learning machine algorithm was proposed. In signal processing, 2nd-order statistics methods such as the power spectrum have gained significant importance. However, many signals have nonlinearity and non-Gaussian behavior, and such signals cannot be examined properly by 2nd-order statistical methods. Thus, higher-order statistical methods have been proved.