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基于BOTDA的分布式光纤传感技术研究进展

文章阐述了布里渊光时域分析（BOTDA）的原理以及布里渊频移与温度和应变的关系,对目前国内外的研究现状,从研究方法、温度、应变和空间分辨率及测量动态范围等方面进行了详细介绍。分析了国外现有的基于BOTDA技术的商用化产品及具体指标,以及BOTDA技术存在的主要问题。最后给出了基于BOTDA技术的光纤传感技术的应用领域和发展趋势

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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