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Xiaorui Wang
Jiangsu Institute for Land Development and Consolidation, Nanjing 210017, China

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Journal article
Published: 31 March 2021 in Land
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An in-depth exploration of the dynamics and existing problems in farmland morphology is crucial to formulate targeted protection policies. In this study, we constructed a morphological evaluation index system to identify the characteristics of farmland use transition in Sihong County of the Huang-Huai-Hai Plain, China. The dominant morphology in terms of area and landscape pattern and the recessive morphology focusing on function were considered in this work. Based on this information, the driving factors of farmland use transition were quantitatively analyzed via the mixed regression model. The following major findings were determined: (1) The area showed a U-shaped change trend during 2009–2018. The patch density (PD) showed an upward trend, and the mean patch size (MPS) showed a downward trend, indicating that the degree of farmland fragmentation increased. The implementation of land consolidation projects increased the area and aggregation of farmland, while urbanization and road construction occupied and divided the farmland, leading to a reduction in area and increase in the degree of fragmentation. (2) The crop production, living security, and eco-environmental function of farmland showed a trend of first decreasing and then increasing. Urbanization increased the demand for agricultural products and the degree of large-scale agricultural production and had a positive impact on the crop production and eco-environmental function of farmland. Our research highlights that increasing farmland fragmentation should be addressed in the farming area. Therefore, the government should formulate efficient policies to curb farmland occupation for urban and traffic utilization.

ACS Style

Ligang Lyu; Zhoubing Gao; Hualou Long; Xiaorui Wang; Yeting Fan. Farmland Use Transition in a Typical Farming Area: The Case of Sihong County in the Huang-Huai-Hai Plain of China. Land 2021, 10, 347 .

AMA Style

Ligang Lyu, Zhoubing Gao, Hualou Long, Xiaorui Wang, Yeting Fan. Farmland Use Transition in a Typical Farming Area: The Case of Sihong County in the Huang-Huai-Hai Plain of China. Land. 2021; 10 (4):347.

Chicago/Turabian Style

Ligang Lyu; Zhoubing Gao; Hualou Long; Xiaorui Wang; Yeting Fan. 2021. "Farmland Use Transition in a Typical Farming Area: The Case of Sihong County in the Huang-Huai-Hai Plain of China." Land 10, no. 4: 347.

Journal article
Published: 23 November 2018 in International Journal of Environmental Research and Public Health
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In order to quantitatively study the effect of environmental protection in China since the twenty-first century and the environmental pollution projected for the next ten years (under the model of extensive economic development), this paper establishes a Bayesian regulation back propagation neural network (BRBPNN) to analyze the typical pollutants (i.e., cadmium (Cd) and benzopyrene (BaP)) for Taihu Lake, a typical Chinese freshwater lake. For the periods 1950–2003 and 1950–2015, the neural network model estimated the BaP concentration for the database with Nash-Sutcliffe model efficiency (NS) = 0.99 and 0.99 and root-mean-square error (RMSE) = 3.1 and 9.3 for the total database and the Cd concentration for the database with NS = 0.93 and 0.98 and RMSE = 45.4 and 65.7 for the total database, respectively. In the model of extensive economic development, the concentration of pollutants in the sediments of Taihu reached the maximum value at the end of the twentieth century and early twenty-first century, and there was an inflection point. After the early twenty-first century, the concentration of pollutants was controlled under various environmental policies and measures. In 2015, the environmental protection ratio of Cd and BaP reached 52% and 89%, respectively. Without environmental protection measures, the concentrations of Cd and BaP obtained from the neural network model is projected to reach 2015.5 μg kg−1 and 407.8 ng g−1, respectively, in 2030. Based on the results of this study, the Chinese government will need to invest more money and energy to clean up the environment.

ACS Style

Yan Li; Shenglu Zhou; Zhenyi Jia; Liang Ge; Liping Mei; Xueyan Sui; Xiaorui Wang; Baojie Li; Junxiao Wang; Shaohua Wu. Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China. International Journal of Environmental Research and Public Health 2018, 15, 2628 .

AMA Style

Yan Li, Shenglu Zhou, Zhenyi Jia, Liang Ge, Liping Mei, Xueyan Sui, Xiaorui Wang, Baojie Li, Junxiao Wang, Shaohua Wu. Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China. International Journal of Environmental Research and Public Health. 2018; 15 (12):2628.

Chicago/Turabian Style

Yan Li; Shenglu Zhou; Zhenyi Jia; Liang Ge; Liping Mei; Xueyan Sui; Xiaorui Wang; Baojie Li; Junxiao Wang; Shaohua Wu. 2018. "Influence of Industrialization and Environmental Protection on Environmental Pollution: A Case Study of Taihu Lake, China." International Journal of Environmental Research and Public Health 15, no. 12: 2628.

Conference paper
Published: 02 September 2018 in Interspeech 2018
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ACS Style

Jie Li; Xiaorui Wang; Yuanyuan Zhao; Yan Li. Gated Recurrent Unit Based Acoustic Modeling with Future Context. Interspeech 2018 2018, 1 .

AMA Style

Jie Li, Xiaorui Wang, Yuanyuan Zhao, Yan Li. Gated Recurrent Unit Based Acoustic Modeling with Future Context. Interspeech 2018. 2018; ():1.

Chicago/Turabian Style

Jie Li; Xiaorui Wang; Yuanyuan Zhao; Yan Li. 2018. "Gated Recurrent Unit Based Acoustic Modeling with Future Context." Interspeech 2018 , no. : 1.

Preprint
Published: 18 May 2018
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The use of future contextual information is typically shown to be helpful for acoustic modeling. However, for the recurrent neural network (RNN), it's not so easy to model the future temporal context effectively, meanwhile keep lower model latency. In this paper, we attempt to design a RNN acoustic model that being capable of utilizing the future context effectively and directly, with the model latency and computation cost as low as possible. The proposed model is based on the minimal gated recurrent unit (mGRU) with an input projection layer inserted in it. Two context modules, temporal encoding and temporal convolution, are specifically designed for this architecture to model the future context. Experimental results on the Switchboard task and an internal Mandarin ASR task show that, the proposed model performs much better than long short-term memory (LSTM) and mGRU models, whereas enables online decoding with a maximum latency of 170 ms. This model even outperforms a very strong baseline, TDNN-LSTM, with smaller model latency and almost half less parameters.

ACS Style

Jie Li; Xiaorui Wang; Yuanyuan Zhao; Yan Li. Gated Recurrent Unit Based Acoustic Modeling with Future Context. 2018, 1 .

AMA Style

Jie Li, Xiaorui Wang, Yuanyuan Zhao, Yan Li. Gated Recurrent Unit Based Acoustic Modeling with Future Context. . 2018; ():1.

Chicago/Turabian Style

Jie Li; Xiaorui Wang; Yuanyuan Zhao; Yan Li. 2018. "Gated Recurrent Unit Based Acoustic Modeling with Future Context." , no. : 1.

Journal article
Published: 30 September 2016 in International Journal of Environmental Research and Public Health
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With China’s rapid economic development, the reduction in arable land has emerged as one of the most prominent problems in the nation. The long-term dynamic monitoring of arable land quality is important for protecting arable land resources. An efficient practice is to select optimal sample points while obtaining accurate predictions. To this end, the selection of effective points from a dense set of soil sample points is an urgent problem. In this study, data were collected from Donghai County, Jiangsu Province, China. The number and layout of soil sample points are optimized by considering the spatial variations in soil properties and by using an improved simulated annealing (SA) algorithm. The conclusions are as follows: (1) Optimization results in the retention of more sample points in the moderate- and high-variation partitions of the study area; (2) The number of optimal sample points obtained with the improved SA algorithm is markedly reduced, while the accuracy of the predicted soil properties is improved by approximately 5% compared with the raw data; (3) With regard to the monitoring of arable land quality, a dense distribution of sample points is needed to monitor the granularity.

ACS Style

Junxiao Wang; Xiaorui Wang; Shenglu Zhou; Shaohua Wu; Yan Zhu; Chunfeng Lu. Optimization of Sample Points for Monitoring Arable Land Quality by Simulated Annealing while Considering Spatial Variations. International Journal of Environmental Research and Public Health 2016, 13, 980 .

AMA Style

Junxiao Wang, Xiaorui Wang, Shenglu Zhou, Shaohua Wu, Yan Zhu, Chunfeng Lu. Optimization of Sample Points for Monitoring Arable Land Quality by Simulated Annealing while Considering Spatial Variations. International Journal of Environmental Research and Public Health. 2016; 13 (10):980.

Chicago/Turabian Style

Junxiao Wang; Xiaorui Wang; Shenglu Zhou; Shaohua Wu; Yan Zhu; Chunfeng Lu. 2016. "Optimization of Sample Points for Monitoring Arable Land Quality by Simulated Annealing while Considering Spatial Variations." International Journal of Environmental Research and Public Health 13, no. 10: 980.