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332 results on '"Ma, Xuejun"'

10. Optimizing nitrogen management in the food system for sustainable development: a case study of Quzhou County

Author

Fanlei MENG, Menru WANG, Yong HOU, Lin MA, Wenqi MA, Xuejun LIU, Fusuo ZHANG, Wen XU

Subjects
agriculture green development, food system, multi-objective, nitrogen management, Agriculture (General), S1-972
Abstract

● The framework of multi-objective nitrogen (N) management was developed.● Multi-objective targets were established to support agriculture sustainable production.● A food chain approach was developed to accurately quantify N flow in food system.● “3R” principle was used in developing N management strategy.● The collaboration with different stakeholders is crucial for promoting technologies.Nitrogen (N) is an essential nutrient for food production. The rapid increase in population requires high inputs of N to meet the growing food demand. If not managed well, the substantial loss of N from the food system has multiple impacts on grain yield, air and water pollution, and the economic benefits of agricultural. Multi-objective (food security, environmental sustainability and economic sustainability) synergistic consideration of N management in the food system is still lacking. This study employed strategies for optimizing N management in the food system, using Quzhou County as a typical example on the North China Plain. Firstly, a food chain approach was adopted to understand drivers and reasons behind N losses from the food system. Secondly, a top-down approach was used to define multi-objective N management, taking into consideration food security, environmental sustainability and economic sustainability. Multi-objective N management aims to reduce N losses to the environment and increase N use efficiencies, while simultaneously increasing yields and economic benefits. Thirdly, 3R (reduce-retain-recycle) N management strategies were identified for specific crops and animals through a bottom-up approach and then analyzed the potential of these strategies to achieve the multi-objectives. Finally, there is a discussion of how to engage different stakeholders to promote the technologies implementation. This study provides new insights into the synergistic achievement of multi-objective N management in the food system and the development of environmentally-friendly agriculture.

Published
2024
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18. Etoposide, dexamethasone, and pegaspargase with sandwiched radiotherapy in early-stage natural killer/T-cell lymphoma: A randomized phase III study

Author

Zhong, Huijuan, Cheng, Shu, Zhang, Xi, Xu, Bing, Chen, Jiayi, Jiang, Xufeng, Xiong, Jie, Hu, Yu, Cui, Guohui, Wei, Juying, Qian, Wenbin, Huang, Xiaobing, Hou, Ming, Yan, Feng, Wang, Xin, Song, Yongping, Hu, Jianda, Liu, Yuanhua, Ma, Xuejun, Li, Fei, Wu, Chongyang, Chen, Junmin, Yu, Li, Bai, Ou, Xu, Jingyan, Zhu, Zunmin, Liu, Li, Zhou, Xin, Huang, Li, Tong, Yin, Niu, Ting, Wu, Depei, Zhang, Hao, Wang, Chaofu, Ouyang, Binshen, Yi, Hongmei, Song, Qi, Cai, Gang, Li, Biao, Liu, Jia, Li, Zhifeng, Xiao, Rong, Wang, Luqun, Jiang, Yujie, Liu, Yanyan, Zheng, Xiaoyun, Xu, Pengpeng, Huang, Hengye, Wang, Li, Chen, Saijuan, and Zhao, Weili

Published
2023
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25. Spatial lag quantile regression for compositional data.

Author

Zhao, Yizhen, Ma, Xuejun, and Chao, Yue

Subjects
*LINEAR programming, *REGRESSION analysis, *COMPUTER simulation, *DATA modeling, *QUANTILE regression
Abstract

AbstractWhile research on spatial lag quantile regression models exists, the extension to incorporating compositional data within this framework remains unexplored. The unique characteristics of compositional data present significant issues in constructing such a model. In this paper, we investigate the estimation problems for the spatial lag quantile regression model in compositional data. We propose the constrained two-stage quantile regression (CTS-QR) and constrained instrumental variable quantile regression (CIV-QR) methods based on linear programming. Numerical simulations show that our proposed methods are more accurate than traditional unconstrained estimation methods. A real data application of our methods is also provided. [ABSTRACT FROM AUTHOR]

Published
2024
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29. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding

Author

Lu, Roujian, Zhao, Xiang, Li, Juan, Niu, Peihua, Yang, Bo, Wu, Honglong, Wang, Wenling, Song, Hao, Huang, Baoying, Zhu, Na, Bi, Yuhai, Ma, Xuejun, Zhan, Faxian, Wang, Liang, Hu, Tao, Zhou, Hong, Hu, Zhenhong, Zhou, Weimin, Zhao, Li, Chen, Jing, Meng, Yao, Wang, Ji, Lin, Yang, Yuan, Jianying, Xie, Zhihao, Ma, Jinmin, Liu, William J, Wang, Dayan, Xu, Wenbo, Holmes, Edward C, Gao, George F, Wu, Guizhen, Chen, Weijun, Shi, Weifeng, and Tan, Wenjie

Published
2020
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33. Identification of Histoplasma causing an unexplained disease cluster in Matthews Ridge, Guyana

Author

Wang, Ji, Zhou, Weimin, Ling, Hua, Dong, Xiaoping, Zhang, Yi, Li, Jiandong, Zhang, Yong, Song, Jingdong, Liu, William J., Li, Yang, Zhang, Ruiqing, Zhen, Wei, Cai, Kun, Zhu, Shuangli, Wang, Dongyan, Xiao, Jinbo, Tong, Yigang, Liu, Wenli, Song, Lihua, Wu, Wei, Liu, Yang, Zhao, Xiang, Wang, Ruihuan, Ye, Sheng, Wang, Jing, Lu, Roujian, Huang, Baoying, Ye, Fei, Lei, Wenwen, Gao, Rongbao, Shi, Qi, Chen, Cao, Han, Jun, Xu, Wenbo, Gao, George F., Ma, Xuejun, and Wu, Guizhen

Published
2019
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34. Fatty Liver Disease Caused by High-Alcohol-Producing Klebsiella pneumoniae

Author

Yuan, Jing, Chen, Chen, Cui, Jinghua, Lu, Jing, Yan, Chao, Wei, Xiao, Zhao, Xiangna, Li, NanNan, Li, Shaoli, Xue, Guanhua, Cheng, Weiwei, Li, Boxing, Li, Huan, Lin, Weishi, Tian, Changyu, Zhao, Jiangtao, Han, Juqiang, An, Daizhi, Zhang, Qiong, Wei, Hong, Zheng, Minghua, Ma, Xuejun, Li, Wei, Chen, Xiao, Zhang, Zheng, Zeng, Hui, Ying, Sun, Wu, JianXin, Yang, Ruifu, and Liu, Di

Published
2019
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36. Multi-Scale Habitat Selection by the Wintering Whooper Swan (Cygnus cygnus) in Manas National Wetland Park, Northwestern China.

Author

Yan, Han, Ma, Xuejun, Yang, Weikang, and Xu, Feng

Subjects
*HABITAT selection, *WATER birds, *SWANS, *NATIONAL parks & reserves, *ANIMAL ecology, *ARTIFICIAL satellite tracking, *HABITAT conservation
Abstract

Habitat selection has been a central focus of animal ecology, with research primarily concentrating on habitat choice, utilization, and evaluation. However, studies confined to a single scale often fail to reveal the habitat selection needs of animals fully and accurately. This paper investigates the wintering whooper swan (Cygnus cygnus) in Manas National Wetland Park, Xinjiang, using satellite tracking to determine their locations. The Maximum Entropy model (MaxEnt) was applied to explore the multi-scales habitat selection needs of Manas National Wetland Park's wintering whooper swans across nighttime, daytime, and landscape scales. This study showed that the habitat selection of the wintering whooper swans varied in different scales. At the landscape scale, wintering whooper swans prefer habitats with average winter precipitations of 6.9 mm and average temperatures of −6 °C, including water bodies and wetlands, indicating that climate (precipitation and temperature) and land type (wetlands and water bodies) influence their winter habitat selection. During daytime, whooper swans prefer areas close to wetlands, water bodies, and bare land, with a more dispersed distribution of water bodies. For nighttime, they tend to choose areas within the wetland park where human disturbance is minimal and safety is higher. This study can provide scientific basis and data support for habitat conservation and management of wintering waterbirds like whooper swans, recommending targeted conservation measures to effectively manage and protect the wintering grounds of whooper swans. [ABSTRACT FROM AUTHOR]

Published
2024
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41. Testing independence for multivariate time series via auto multivariate distance covariance.

Author

Chen, Jingren, Ma, Xuejun, and Chao, Yue

Abstract

Abstract.We propose the auto multivariate distance covariance for time series, which extends the concept of joint high distance covariance. Furthermore, we develop two new procedures for testing mutual independence in multivariate time series that combine the auto multivariate distance covariance with either the Box and Pierce (1970) or the Li and McLeod (1981) tests. Simulation results suggest that the proposed method is highly effective. We also apply our methods to analyze the relationships between the real gross domestic products of the United Kingdom, Canada, and the United States. [ABSTRACT FROM AUTHOR]

Published
2024
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42. Integrated information management of supply chain in logistics parks based on the IoT.

Author

Ma, Xuejun and Zhang, Jinzhen

Abstract

Logistics park is a strategic choice for the growth of logistics industry, and it needs to build a public platform for supply chain management (SCM) suitable for logistics parks. To solve the problems of poor adaptability, high investment risk, and incomplete functionality of the supply chain integrated information management (IM) platform in logistics parks, it is necessary to use Internet of Things (IoT) technology to improve the supply chain integrated IM platform, improve the timely interaction of logistics information and reduce logistics costs. This article analyzed the factors that affect the integrated management of logistics park supply chain, analyzed the architecture of logistics park supply chain, integrated IM under the IoT, and implemented the platform architecture using relevant technologies. In the experiment, the resource allocation, resource scheduling, and resource monitoring effects of the supply chain integrated IM platform were analyzed. The results showed that the supply chain IM platform of logistics parks under the IoT has improved infrastructure by 0.14 compared to traditional platform, resource allocation by 0.16, logistics service level by 0.14, and industrial layout by 0.14. The IoT can effectively enhance the resource allocation and industrial layout rationality of logistics parks and has important significance in improving logistics information security and information exchange. [ABSTRACT FROM AUTHOR]

Published
2024
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