更新日期: 共17条
Drivers of carbon emission intensity change in China

作者:Dong, Feng;Yu, Bolin;Hadachin, Tergel;Dai, Yuanju;Wang, Ying;Zhang, Shengnan;Long, Ruyin 来源: RESOURCES CONSERVATI... 收录类型: SCIE; EI; SSCI; SCOPUS; - 被引量:11 - 年份:2018

Carbon emissions per unit of GDP (also called carbon emission intensity, CEI) can be utilized to measure regional carbon emission performance. In this study, structural decomposition analysis (SDA) and quantile regression are employed to investigate the factors that drive changes in CEI in China. Based on input-output SDA, CEI in China during 1992-2012 is decomposed from the perspectives of the total economy and economic sectors. The results specify that the industrial sector is the key sector for energy. conservation and emission reduction. Energy efficiency contributes the most to CEI reduction, whereas input structure, final demand structure, and final product structure are factors that hinder reductions. Furthermore, energy mix, technical progress, industrialization index, and final consumption rate are introduced as proxy variables. To reveal the changes of influencing factors with CEI increasing, the effects of these proxy variables on CEI are explored by quantile regression with panel data of 30 provinces from 1999 to 2014. The results indicate that energy mix, industrialization index, and final consumption rate have positive effects on CEI. As CEI increases, the effect of energy mix increases gradually, whereas the effect of industrialization index tends to decrease, and the effect of final consumption rate increases initially and then decreases. Technical progress and urbanization are both effective in reducing CEI. With CEI increasing, the negative effect of technical progress presents a trend of decrease, then increase. Conversely, the negative effect of urbanization is through the process of increase, then decrease.

Alcoholism Detection by Data Augmentation and Convolutional Neural Network with Stochastic Pooling

作者:Wang, Shui-Hua;Lv, Yi-Ding;Sui, Yuxiu;Liu, Shuai;Wang, Su-Jing;Zhang, Yu-Dong 来源: JOURNAL OF MEDICAL S... 收录类型: SCIE; SCOPUS; PubMed; - 被引量:15 - 年份:2018

Alcohol use disorder (AUD) is an important brain disease. It alters the brain structure. Recently, scholars tend to use computer vision based techniques to detect AUD. We collected 235 subjects, 114 alcoholic and 121 non-alcoholic. Among the 235 image, 100 images were used as training set, and data augmentation method was used. The rest 135 images were used as test set. Further, we chose the latest powerful technique-convolutional neural network (CNN) based on convolutional layer, rectified linear unit layer, pooling layer, fully connected layer, and softmax layer. We also compared three different pooling techniques: max pooling, average pooling, and stochastic pooling. The results showed that our method achieved a sensitivity of 96.88%, a specificity of 97.18%, and an accuracy of 97.04%. Our method was better than three state-of-the-art approaches. Besides, stochastic pooling performed better than other max pooling and average pooling. We validated CNN with five convolution layers and two fully connected layers performed the best. The GPU yielded a 149x acceleration in training and a 166x acceleration in test, compared to CPU.

Discovery potentials of doubly charmed baryons

作者:于福升;蒋华玉;李润辉;吕才典;王伟;赵振兴 来源: CHINESE PHYSICS C 收录类型: SCOPUS; SCIE; - 被引量:9 - 年份:2018

The existence of doubly heavy flavor baryons has not been well established experimentally so far. In this Letter we systematically investigate the weak decays of the doubly charmed baryons, Ξ~(++)_(cc)and Ξ~+_(cc), which should be helpful for experimental searches for these particles. The long-dista...

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