作者单位
摘要
1 南京信息工程大学气象灾害教育部重点实验室,气候与环境变化国际合作联合实验室,气象灾害预报预警与评估协同创新中心,中国气象局气溶胶与云降水重点开放实验室,江苏 南京 210044
2 中国气象科学研究院灾害天气国家重点实验室,北京 100081
3 中国气象局广州热带海洋气象研究所,广东 广州 510641
4 中国科学院大气物理研究所,中层大气和全球环境探测重点实验室,北京 100029
利用广州高建筑物雷电观测站获得的600 m高广州塔上一次闪电3个回击放电过程的光谱资料,详细分析了广州塔上闪电光谱随时间的演化和随高度的变化特性,并通过对比实测的一组氮原子(NI)[856.8 nm,859.4 nm,862.9 nm]多重态的谱线强度比和理论计算值之比,验证了闪电近红外光辐射满足光学薄条件。结果表明:3个回击放电通道约在200 m以下发光较强;在回击放电初期,当向上传输的电流波还未到达通道顶部时,底部通道径向辐射光谱由较强的离子线和较弱的中性原子线组成,而通道顶部径向辐射光谱主要取决于下行先导,由较弱的离子线和较强的中性原子线组成;当回击电流波向上传输到通道顶部后,整个通道径向辐射出很强的离子线和很强的中性原子线,且离子线总强度和原子线总强度均随通道高度的增加而减小;在回击放电70 μs以后,200 m以上通道离子线总强度和原子线总强度随通道高度的增加基本保持不变。此观测结果也直接证实了闪电放电通道由一个辐射离子线的高温核心和一个辐射中性原子线温度相对较低的外围电晕组成。
光谱学 可见光谱 近红外光谱 广州塔闪电 放电通道 光学薄 
光学学报
2023, 43(12): 1230001
Author Affiliations
Abstract
1 Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Department of Optoelectronic Engineering, Jinan University, Guangzhou, China
2 Department of Biological Engineering, Jinan University, Guangzhou, China
The moving-window bis-correlation coe±cients (MW-BiCC) was proposed and employed for the discriminant analysis of transgenic sugarcane leaves and --thalassemia with visible and nearinfrared (Vis–NIR) spectroscopy. The well-performed moving-window principal component analysis linear discriminant analysis (MW-PCA–LDA) was also conducted for comparison. A total of 306 transgenic (positive) and 150 nontransgenic (negative) leave samples of sugarcane were collected and divided to calibration, prediction, and validation. The diffuse reflection spectra were corrected using Savitzky–Golay (SG) smoothing with first-order derivative (d=1), third-degree polynomial (p=3) and 25 smoothing points (m=25). The selected waveband was 736–1054 nm with MW-BiCC, and the positive and negative validation recognition rates (V REC+, V REC-T were 100%, 98.0%, which achieved the same effect as MW-PCA–LDA. Another example, the 93 --thalassemia (positive) and 148 nonthalassemia (negative) of human hemolytic samples were collected. The transmission spectra were corrected using SG smoothing with d=1, p=3 and m=53. Using MW-BiCC, many best wavebands were selected (e.g., 1116–1146, 1794–1848 and 2284–2342nm). The V REC+ and V REC- were both 100%, which achieved the same effect as MW-PCA–LDA. Importantly, the BiCC only required calculating correlation coe±cients between the spectrum of prediction sample and the average spectra of two types of calibration samples. Thus, BiCC was very simple in algorithm, and expected to obtain more applications. The results first confirmed the feasibility of distinguishing --thalassemia and normal control samples by NIR spectroscopy, and provided a promising simple tool for large population thalassemia screening.
Visible and near-infrared spectroscopic discrimina transgenic sugarcane leaves β-thalassemia moving-window bis-correlation coe±cients moving-window principal component analysis linear 
Journal of Innovative Optical Health Sciences
2018, 11(2): 1850005

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