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作为中国为数不多的自主研发的开源地图引擎,Maptalks以其优良的性能和灵活的插件构建方式,在越来越多的项目中得以应用.鉴于其正处于稳步开发的阶段,部分功能还不够完善,还未实现实际项目中的草图绘制编辑所需的捕捉功能.针对此问题,开发了基于Maptalks的捕捉插件,实现了地图编辑中的捕捉功能.此成果一方面满足了外业草图绘制简单捕捉编辑的需求,另一方面完善了Map-talks的功能,扩大了它的应用范围.  相似文献   
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We measured the concentrations of dimethylsulfide (DMS), acrylic acid (AA), and dimethylsulfoniopropionate (DMSP) during growth of three microalgae: Prorocentrum micans, Gephyrocapsa oceanica, and Platymonas subcordiformis. The DMSP, AA, and DMS concentrations in culture media varied significantly among algal growth stages, with the highest concentrations in the late stationary growth stage or the senescent stage. In the stationary growth stage, the average DMSP concentration per cell in P. micans (0.066 5 pmol/cell) was 1.3 times that in G. oceanica (0.049 5 pmol/ cell) and 20.2 times that in P. subcordiformis (0.003 29 pmol/cell). The average concentrations of AA were 0.044 6, 0.026 9, and 0.003 05 pmol/cell in P. micans, G. oceanica, and P. subcordiformis, respectively, higher than the concentrations of DMS (0.272, 0.497, and 0.086 2 fmol/cell, respectively). There were significant positive correlations between cell density and AA, DMSP, and DMS concentrations. The ratios of DMS/AA and AA/(DMSP+AA) in the three algae differed significantly over the growth cycle. In all three microalgae, the DMS/AA ratios were less than 25% during the growth period, suggesting that the enzymatic cleavage pathway, which generates DMS, was not the main DMSP degradation pathway. The changes in the DMS/AA ratio indicated that there was a higher rate of enzymatic breakdown of DMSP in the early growth period and a lower rate during senescence. In all three microalgae, the AA/(DMSP+AA) ratio (degradation ratio of DMSP) decreased during the exponential growth phase, and then increased. The variations in these ratios can approximately indicate the cleavage mechanism of DMSP at different stages of algal growth.  相似文献   
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传统农业虫害测报存在时间、人力成本高,准确度难以保证等问题,难以适应现代农业发展。本文在微小农业害虫自动监控装置的基础上,结合时空分析原理和卷积神经网络识别技术,提出智慧农田害虫时空监测系统方案。文章从前端、服务器端、数据库端三方面阐述设计思路。基于设计的系统,智能识别害虫种类、数目,在此基础上进行时空分析,预测可能发生虫害的地点、趋势,最终达到农田害虫时空监测的自动化和智能化的效果。  相似文献   
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