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Impacts of Production-Living-Ecological Space Transformation in the Heihe River Basin on Ecological Environment Quality in the Context of Climate Change
ZOU Yi, ZHAO Yiyang, MENG Jijun
Acta Scientiarum Naturalium Universitatis Pekinensis    2024, 60 (3): 528-538.   DOI: 10.13209/j.0479-8023.2024.009
Abstract3713)   HTML    PDF(pc) (3089KB)(346)       Save
Choosing the Heihe River Basin in the arid northwest of China as the study area, using ArcGIS 10.6 and Mathematica 8.0 as research platforms, the paper analyzes the spatio-temporal pattern of the transformation of the production-living-ecological spaces from 1990 to 2020. Combining the vegetation index (NDVI) and salinity index (SI), we investigate the spatiotemporal changes of eco-environmental quality and separate the contributions of explicit and implicit transformation of the production-living-ecological spaces to changes in eco-environmental quality by establishing a mixed effects model and attribution analysis model under the background of climate change. The results show that 1) the strong and weak ecological spaces in the Heihe River Basin account for 28.12% and 65% respectively, while the living and production space accounts for only 6.88%. The living and production spaces have each increased by 0.32% and 0.96% over the past 30 years, and frequent transformations occur between strong and weak ecological spaces (72.8%). The change in eco-environmental quality has transitioned from a decline to a sustained improvement trend since 2000. 2) The contributions of explicit transformation of the production-livingecological spaces and climate change to eco-environmental quality are 39.8% and 36.6%. Precipitation has the main contribution to the ecological environment of production and living spaces, while temperature has a nonlinear impact on the eco-environmental quality of ecological spaces. The contribution rate of implicit transformation to ecological environment changes is 23.6%. 3) The transformation of the three spatial sectors has a stronger spatial heterogeneity effect on ecological environment, while the temporal heterogeneity effect of climate change is stronger. The eco-environmental quality in the middle reaches of the river basin is simultaneously affected by explicit and implicit transformation, while the downstream is mainly affected by implicit transformation. The results provide a reliable theoretical basis for optimizing the land spatial development and ecosystem management in the Heihe River Basin.
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Research on Sentiment Analysis Based on Representation Learning
LI Xiaojun, SHI Hanxiao, CHEN Nannan, LIU Hong, ZOU Yi
Acta Scientiarum Naturalium Universitatis Pekinensis    2019, 55 (1): 105-112.   DOI: 10.13209/j.0479-8023.2018.066
Abstract4251)   HTML    PDF(pc) (931KB)(2227)       Save

The authors propose C&W-SP model — a text sentiment analysis model based on the representation learning. Firstly, an improved training model based on C&W model is proposed which can integrate emotional information and part of speech information in the training process of word embedding. The evaluation of data sets of NLP&CC’2013 is used to compare experimental results with different models. The experimental results show that the C&W-SP model which combines emotion information and part of speech information has the best performance and confirm the effectiveness of the proposed method.

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