Planting under plastic-film mulches is widely used in spring maize production in arid-cold regions for water conservation and warming the soil.To ameliorate the associated issues such as plastic-film residues and addi...Planting under plastic-film mulches is widely used in spring maize production in arid-cold regions for water conservation and warming the soil.To ameliorate the associated issues such as plastic-film residues and additional labor during the“seedling release”in spring maize production,we have developed a plastic-film-side seeding(PSS)technology with the supporting machinery.In the semi-arid regions of Northwest China,a 7-year trial demonstrated that PSS increased plant number per hectare by 6547 and maize yield by 1686 kg ha–1compared with the traditional method of seeding under plastic-film mulch(PM).Two-year experiments were conducted in two semi-arid regions to further understand the effects of PSS on three important aspects of production:(i)the moisture and temperature of soil,(ii)maize development,yield output,and water use efficiency(WUE),and(iii)the revenue and plastic-film residuals in comparison with that of flat planting(CK)and PM.Continuous monitoring of the soil status demonstrated that,compared with CK,the PSS treatment significantly increased the temperature and moisture of the 0–20 cm soil in the seeding row at the early stage of maize development,and it also promoted grain yield(at 884–1089 kg ha^(–1))and WUE,achieving a similar effect as the PM treatment.Economically,the labor inputs of PSS were equal to CK,whereas the PM cost an additional 960 CNY ha–1in labor for releasing the seedlings from below the film.Overall,the PSS system increased profits by 5.83%(547 CNY ha^(–1)yr^(–1))and 8.16%(748 CNY ha^(–1)yr^(–1))compared with CK and PM,respectively.Environmentally,PSS achieved a residual film recovery rate of nearly 100%and eliminated 96 to 130 kg ha^(–1)of residual plastic-film in PM in 3–5 years of maize production.Collectively,these results show that PSS is an eco-friendly technique for improving yield stability and incomes for the sustainable production of maize in semi-arid regions.展开更多
学术全文本中包含了多种知识元,对这些知识元进行挖掘与组织,可以有效提升学术资源的利用效率。通过学术知识图谱的构建,将论文中各类隐性“知识元”串联起来,不但可以节省研究者获取知识点的时间,还可以通过知识图谱内的网络社区进行...学术全文本中包含了多种知识元,对这些知识元进行挖掘与组织,可以有效提升学术资源的利用效率。通过学术知识图谱的构建,将论文中各类隐性“知识元”串联起来,不但可以节省研究者获取知识点的时间,还可以通过知识图谱内的网络社区进行知识点的扩充。通过系统而全面的文献调研,本文从宏观、中观和微观3个维度出发,确定了18种学术论文中的关键知识元,并将学术全文本中的描述信息作为知识元对象,设计出学术知识图谱概念框架。然后,选取Journal of the Association for Information Science and Technology(JASIST)期刊的515篇学术全文本,对每篇论文中的关键知识元进行人工标注与基于深度学习的知识元抽取研究。研究内容包括该类知识元在人工标注过程中是否会遇到问题、在自动抽取时是否会达到预期值,从而对参与图谱构建的知识元进行筛选。最终筛选出9种知识元,包括数学公式、软件工具、数据源、具体模型、表、图、研究展望、研究问题和研究结果,与题录数据中的知识元共同生成由头知识元、关系、尾知识元组成的三元组,存入图数据库。最后,对该图谱进行可视化的评估与知识元检索研究,证明了其可行性与可扩展性。研究结果表明,学术全文本中的部分知识元适合大规模的自动化标注,而且各类知识元可以通过互相链接形成密集的知识社区,并具备知识元搜索等功能。展开更多
Based on historical runs,one of the core experiments of the fifth phase of the Coupled Model Intercomparison Project （CMIP5）,the snow depth （SD） and snow cover fraction （SCF） simulated by two versions of the Fle...Based on historical runs,one of the core experiments of the fifth phase of the Coupled Model Intercomparison Project （CMIP5）,the snow depth （SD） and snow cover fraction （SCF） simulated by two versions of the Flexible Global OceanAtmosphere-Land System （FGOALS） model,Grid-point Version 2 （g2） and Spectral Version 2 （s2）,were validated against observational data.The results revealed that the spatial pattern of SD and SCF over the Northern Hemisphere （NH） are simulated well by both models,except over the Tibetan Plateau,with the average spatial correlation coefficient over all months being around 0.7 and 0.8 for SD and SCF,respectively.Although the onset of snow accumulation is captured wellby the two models in terms of the annual cycle of SD and SCF,g2 overestimates SD/SCF over most mid-and high-latitude areas of the NH.Analysis showed that g2 produces lower temperatures than s2 because it considers the indirect effects of aerosols in its atmospheric component,which is the primary driver for the SD/SCF difference between the two models.In addition,both models simulate the significant decreasing trend of SCF well over （30°-70°N） in winter during the period 1971-94.However,as g2 has a weak response to an increase in the concentration of CO2 and lower climate sensitivity,it presents weaker interannual variation compared to s2.展开更多
To improve efficiency in the use of water resources in water-limited environments such as the North China Plain（NCP）, where winter wheat is a major and groundwater-consuming crop, the application of water-saving irr...To improve efficiency in the use of water resources in water-limited environments such as the North China Plain（NCP）, where winter wheat is a major and groundwater-consuming crop, the application of water-saving irrigation strategies must be considered as a method for the sustainable development of water resources. The initial objective of this study was to evaluate and validate the ability of the CERES-Wheat model simulation to predict the winter wheat grain yield, biomass yield and water use efficiency（WUE） responses to different irrigation management methods in the NCP. The results from evaluation and validation analyses were compared to observed data from 8 field experiments, and the results indicated that the model can accurately predict these parameters. The modified CERES-Wheat model was then used to simulate the development and growth of winter wheat under different irrigation treatments ranging from rainfed to four irrigation applications（full irrigation） using historical weather data from crop seasons over 33 years（1981–2014）. The data were classified into three types according to seasonal precipitation： 〈100 mm, 100–140 mm, and 〉140 mm. Our results showed that the grain and biomass yield, harvest index（HI） and WUE responses to irrigation management were influenced by precipitation among years, whereby yield increased with higher precipitation. Scenario simulation analysis also showed that two irrigation applications of 75 mm each at the jointing stage and anthesis stage（T3） resulted in the highest grain yield and WUE among the irrigation treatments. Meanwhile, productivity in this treatment remained stable through different precipitation levels among years. One irrigation at the jointing stage（T1） improved grain yield compared to the rainfed treatment and resulted in yield values near those of T3, especially when precipitation was higher. These results indicate that T3 is the most suitable irrigation strategy under variable precipitation regimes for stable yield of winter wheat with maximum water savings in the NCP. The application of one irrigation at the jointing stage may also serve as an alternative irrigation strategy for further reducing irrigation for sustainable water resources management in this area.展开更多
This paper extends the dimension-reduced projection four-dimensional variational assimilation method(DRP-4DVar) by adding a nonlinear correction process,thereby forming the DRP-4DVar with a nonlinear correction, which...This paper extends the dimension-reduced projection four-dimensional variational assimilation method(DRP-4DVar) by adding a nonlinear correction process,thereby forming the DRP-4DVar with a nonlinear correction, which shall hereafter be referred to as the NC-DRP-4DVar. A preliminary test is conducted using the Lorenz-96 model in one single-window experiment and several multiple-window experiments. The results of the single-window experiment show that compared with the adjoint-based traditional 4DVar, the final convergence of the cost function for the NC-DRP-4DVar is almost the same as that using the traditional 4DVar, but with much less computation. Furthermore, the 30-window assimilation experiments demonstrate that the NC-DRP-4DVar can alleviate the linearity approximation error and reduce the root mean square error significantly.展开更多
随着深度学习的迅速发展和领域数据的快速积累,领域化的预训练模型在知识组织和挖掘中发挥了越来越重要的支撑作用。面向海量的中文政策文本,结合相应的预训练策略构建中文政策文本预训练模型,不仅有助于提升中文政策文本智能化处理的水...随着深度学习的迅速发展和领域数据的快速积累,领域化的预训练模型在知识组织和挖掘中发挥了越来越重要的支撑作用。面向海量的中文政策文本,结合相应的预训练策略构建中文政策文本预训练模型,不仅有助于提升中文政策文本智能化处理的水平,而且为政策文本数据驱动下的精细化和多维度分析与探究奠定了坚实的基础。面向国家级、省级和市级平台上的政策文本,通过自动抓取和人工辅助相结合的方式,在去除非政策文本的基础上,确定了131390份政策文本,总字数为305648206。面向所构建的中文政策文本语料库,基于BERT-base-Chinese和Chinese-RoBERTa-wwm-ext,本研究利用MLM(masked language model)和WWM(whole word masking)任务构建了中文政策文本预训练模型(ChpoBERT),并在Github上对该模型进行了开源。在困惑度评价指标和政策文本自动分词、词性自动标注、命名实体识别下游任务上,ChpoBERT系列模型均表现出了较优的性能,可为政策文本的智能知识挖掘提供领域化的基础计算资源支撑。展开更多
基金supported by the earmarked fund for China Agriculture Research System(CARS-02-16 and CARS-02-75)the National Key Research and Development Program of China(2016YFD0300301)。
文摘Planting under plastic-film mulches is widely used in spring maize production in arid-cold regions for water conservation and warming the soil.To ameliorate the associated issues such as plastic-film residues and additional labor during the“seedling release”in spring maize production,we have developed a plastic-film-side seeding(PSS)technology with the supporting machinery.In the semi-arid regions of Northwest China,a 7-year trial demonstrated that PSS increased plant number per hectare by 6547 and maize yield by 1686 kg ha–1compared with the traditional method of seeding under plastic-film mulch(PM).Two-year experiments were conducted in two semi-arid regions to further understand the effects of PSS on three important aspects of production:(i)the moisture and temperature of soil,(ii)maize development,yield output,and water use efficiency(WUE),and(iii)the revenue and plastic-film residuals in comparison with that of flat planting(CK)and PM.Continuous monitoring of the soil status demonstrated that,compared with CK,the PSS treatment significantly increased the temperature and moisture of the 0–20 cm soil in the seeding row at the early stage of maize development,and it also promoted grain yield(at 884–1089 kg ha^(–1))and WUE,achieving a similar effect as the PM treatment.Economically,the labor inputs of PSS were equal to CK,whereas the PM cost an additional 960 CNY ha–1in labor for releasing the seedlings from below the film.Overall,the PSS system increased profits by 5.83%(547 CNY ha^(–1)yr^(–1))and 8.16%(748 CNY ha^(–1)yr^(–1))compared with CK and PM,respectively.Environmentally,PSS achieved a residual film recovery rate of nearly 100%and eliminated 96 to 130 kg ha^(–1)of residual plastic-film in PM in 3–5 years of maize production.Collectively,these results show that PSS is an eco-friendly technique for improving yield stability and incomes for the sustainable production of maize in semi-arid regions.
文摘学术全文本中包含了多种知识元,对这些知识元进行挖掘与组织,可以有效提升学术资源的利用效率。通过学术知识图谱的构建,将论文中各类隐性“知识元”串联起来,不但可以节省研究者获取知识点的时间,还可以通过知识图谱内的网络社区进行知识点的扩充。通过系统而全面的文献调研,本文从宏观、中观和微观3个维度出发,确定了18种学术论文中的关键知识元,并将学术全文本中的描述信息作为知识元对象,设计出学术知识图谱概念框架。然后,选取Journal of the Association for Information Science and Technology(JASIST)期刊的515篇学术全文本,对每篇论文中的关键知识元进行人工标注与基于深度学习的知识元抽取研究。研究内容包括该类知识元在人工标注过程中是否会遇到问题、在自动抽取时是否会达到预期值,从而对参与图谱构建的知识元进行筛选。最终筛选出9种知识元,包括数学公式、软件工具、数据源、具体模型、表、图、研究展望、研究问题和研究结果,与题录数据中的知识元共同生成由头知识元、关系、尾知识元组成的三元组,存入图数据库。最后,对该图谱进行可视化的评估与知识元检索研究,证明了其可行性与可扩展性。研究结果表明,学术全文本中的部分知识元适合大规模的自动化标注,而且各类知识元可以通过互相链接形成密集的知识社区,并具备知识元搜索等功能。
基金supported by the Key Projects in the National Science & Technology Pillar Program during the Twelfth Five-Year Plan Period (Grant No. 2012BAC22B02)the National Key Basic Research Program of China (Grant No. 2013CB956603)the Ministry of Science and Technology of China (Grant No. 2013CBA01805)
文摘Based on historical runs,one of the core experiments of the fifth phase of the Coupled Model Intercomparison Project （CMIP5）,the snow depth （SD） and snow cover fraction （SCF） simulated by two versions of the Flexible Global OceanAtmosphere-Land System （FGOALS） model,Grid-point Version 2 （g2） and Spectral Version 2 （s2）,were validated against observational data.The results revealed that the spatial pattern of SD and SCF over the Northern Hemisphere （NH） are simulated well by both models,except over the Tibetan Plateau,with the average spatial correlation coefficient over all months being around 0.7 and 0.8 for SD and SCF,respectively.Although the onset of snow accumulation is captured wellby the two models in terms of the annual cycle of SD and SCF,g2 overestimates SD/SCF over most mid-and high-latitude areas of the NH.Analysis showed that g2 produces lower temperatures than s2 because it considers the indirect effects of aerosols in its atmospheric component,which is the primary driver for the SD/SCF difference between the two models.In addition,both models simulate the significant decreasing trend of SCF well over （30°-70°N） in winter during the period 1971-94.However,as g2 has a weak response to an increase in the concentration of CO2 and lower climate sensitivity,it presents weaker interannual variation compared to s2.
基金funded by the Special Fund for Agro-scientific Research in the Public Interest of China (201203031,201303133)the National Natural Science Foundation of China (31071367)
文摘To improve efficiency in the use of water resources in water-limited environments such as the North China Plain（NCP）, where winter wheat is a major and groundwater-consuming crop, the application of water-saving irrigation strategies must be considered as a method for the sustainable development of water resources. The initial objective of this study was to evaluate and validate the ability of the CERES-Wheat model simulation to predict the winter wheat grain yield, biomass yield and water use efficiency（WUE） responses to different irrigation management methods in the NCP. The results from evaluation and validation analyses were compared to observed data from 8 field experiments, and the results indicated that the model can accurately predict these parameters. The modified CERES-Wheat model was then used to simulate the development and growth of winter wheat under different irrigation treatments ranging from rainfed to four irrigation applications（full irrigation） using historical weather data from crop seasons over 33 years（1981–2014）. The data were classified into three types according to seasonal precipitation： 〈100 mm, 100–140 mm, and 〉140 mm. Our results showed that the grain and biomass yield, harvest index（HI） and WUE responses to irrigation management were influenced by precipitation among years, whereby yield increased with higher precipitation. Scenario simulation analysis also showed that two irrigation applications of 75 mm each at the jointing stage and anthesis stage（T3） resulted in the highest grain yield and WUE among the irrigation treatments. Meanwhile, productivity in this treatment remained stable through different precipitation levels among years. One irrigation at the jointing stage（T1） improved grain yield compared to the rainfed treatment and resulted in yield values near those of T3, especially when precipitation was higher. These results indicate that T3 is the most suitable irrigation strategy under variable precipitation regimes for stable yield of winter wheat with maximum water savings in the NCP. The application of one irrigation at the jointing stage may also serve as an alternative irrigation strategy for further reducing irrigation for sustainable water resources management in this area.
基金supported by the National Basic Research Program of China (973 Program, Grant No. 2010CB951604)the National Key Technologies Research and Development Program of China (Grant No. 2012BAC22B02)the National Natural Science Foundation of China (Grant No. 41105120)
文摘This paper extends the dimension-reduced projection four-dimensional variational assimilation method(DRP-4DVar) by adding a nonlinear correction process,thereby forming the DRP-4DVar with a nonlinear correction, which shall hereafter be referred to as the NC-DRP-4DVar. A preliminary test is conducted using the Lorenz-96 model in one single-window experiment and several multiple-window experiments. The results of the single-window experiment show that compared with the adjoint-based traditional 4DVar, the final convergence of the cost function for the NC-DRP-4DVar is almost the same as that using the traditional 4DVar, but with much less computation. Furthermore, the 30-window assimilation experiments demonstrate that the NC-DRP-4DVar can alleviate the linearity approximation error and reduce the root mean square error significantly.
文摘随着深度学习的迅速发展和领域数据的快速积累,领域化的预训练模型在知识组织和挖掘中发挥了越来越重要的支撑作用。面向海量的中文政策文本,结合相应的预训练策略构建中文政策文本预训练模型,不仅有助于提升中文政策文本智能化处理的水平,而且为政策文本数据驱动下的精细化和多维度分析与探究奠定了坚实的基础。面向国家级、省级和市级平台上的政策文本,通过自动抓取和人工辅助相结合的方式,在去除非政策文本的基础上,确定了131390份政策文本,总字数为305648206。面向所构建的中文政策文本语料库,基于BERT-base-Chinese和Chinese-RoBERTa-wwm-ext,本研究利用MLM(masked language model)和WWM(whole word masking)任务构建了中文政策文本预训练模型(ChpoBERT),并在Github上对该模型进行了开源。在困惑度评价指标和政策文本自动分词、词性自动标注、命名实体识别下游任务上,ChpoBERT系列模型均表现出了较优的性能,可为政策文本的智能知识挖掘提供领域化的基础计算资源支撑。
