The comparison of water balance in millet fields between terrace and flatland under dryland farming on the loess hill-gully region

依据田间试验资料,对比研究了黄土丘陵沟壑区川地和山地梯田两种土地类型条件下谷子水量平衡过程的差异。结果表明,川地谷子生育期总耗水量为544.1mm,山地为468.4mm,前者是后者的1.16倍;谷子全生育期日均耗水量川地为3.30mm/d,山地为2.76mm/d;山地谷子的水分利用效率(WUE)还略高于川地谷子。山地土壤含水量低以及叶面积指数等的不同是引起山地ET/E0偏低的主要原因

Similarities and differences of water balance among cropland, grassland and woodland in the Loess Plateau

水量平衡是说明生态系统功能和特征的重要指标之一。在黄土高原,降水通常是土壤水分的唯一来源,农、林、草地等不同土地利用类型在对土壤水分的利用时段、深度、利用率、水分的收支比以及土壤干燥化特征等方面存在着较大差异。水量平衡计算时,土壤深度农地通常需取到2m,多年生草地取到5m,林地则需到5m以下

太极计划激光链路构建地面模拟控制系统研究

太极计划需要通过激光捕获指向系统实现两颗卫星之间超长距离（3×10~6 km）的激光链路构建，并且实现1μrad的捕获精度以及■(1 mHz～1 Hz）的指向抖动控制精度。空间引力波探测提出利用星敏感器（STR）、互补金属氧化物半导体（CMOS）捕获相机以及四象限光电探测器（QPD）等三级探测器逐步构建双向激光链路的方案，并最终通过差分波前传感技术（DWS）测量的高精度姿态信息来实现超稳的激光指向抖动控制。目前该方案仍处于理论论证阶段。为了测试该方案，采用实验室现有激光捕获指向一体化的光学系统以及一块ZYNQ芯片的自研板卡，尝试实现整个激光链路构建过程的全自主控制流程。实验结果表明：在大气环境下，成功自主完成了双向激光链路的构建，最终对应到实际系统望远镜前的捕获精度达到了0.07μrad，指向控制过程的控制精度在太极计划的敏感频段内达到了■，能够满足任务需求。实验成功验证了激光链路构建方案的可行性，为下一步太极计划激光链路构建控制系统工程实施阶段的板级实现奠定了基础

国内8款常用植物识别软件的识别能力评价

随着智能手机和人工智能技术的发展,以手机app为载体的植物识别软件慢慢走进公众生活、科普活动和科研活动的各个方面。植物识别app的识别正确率是决定其使用价值和用户体验的关键因素。目前,国内应用市场上有许多植物识别app,它们的开发目的和应用范围各异,软件本身的关注点、数据库来源、算法、硬件要求也存在很大差异。对于不同人群,植物识别app有不同的意义,如对于科研人员来说,识别能力强的app是提高效率的一大工具;对植物爱好者来说,具一定准确率的识别app可以作为入门的工具。因此,对各app的识别能力进行分析与评价显得尤为重要。本文选取了8款常用的app,分别对400张已准确鉴定的植物图片进行识别,其中干旱半干旱区、温带、热带和亚热带4个区各选取100张。这些图片共计122科164属340种,涵盖了乔木、灌木、草本、草质藤本和木质藤本5种生长型,包含23种国家级保护植物。种、属、科准确识别正确分别计4分、2分、1分,以此标准对软件识别能力按总得分进行排序,正确率得分由高到低依次为花帮主、百度识图、花伴侣、形色、花卉识别、植物识别、发现识花、微软识花

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies