Musical Tone Law Method for the Structural Damage Detection by Weisong Yang, Weixiao Xu, Xun Guo, Liguo Yang

“…The results show that the musical tone law method could be used in the damage detection of isotropic material structures with simple shape, like cables, pipes, plates, and shells. Having distinct spectral lines like a comb with a certain interval distribution rule is the main characteristic of the music tone law. …”
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Research of dispersion characteristics of optical glass by A.I. Yurin, G.N. Vishnyakov, V.L. Minaev

“…The refractive index measurements of optical glass samples are carried out at 3 wavelengths of He-Ne and Ar-Cr lasers, and values of the refractive index for spectral lines necessary for determining the dispersion characteristics are calculated. …”
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Spectral study of COVID-19 pandemic in Japan: The dependence of spectral gradient on the population size of the community. by Ayako Sumi, Masayuki Koyama, Manato Katagiri, Norio Ohtomo

“…For all prefectures, many spectral lines observed in each PSD can be fully assigned to a fundamental mode and its harmonics and subharmonics, or linear combinations of a few fundamental periods, suggesting that the COVID-19 data are substantially noise-free. …”
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A Systematic Study of Inverting Overlappograms: MaGIXS—A Case Study by P. S. Athiray, Arthur Hochedez, Amy R. Winebarger, Dyana Beabout

“…Depending on the size of the extended source, combined with the spatial resolution and spectral dispersion of the instrument, there may be locations in the focal plane where spectral lines from different spatial locations overlap on the detector. …”
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The Detection of Soybean Bacterial Blight Based on Polarization Spectral Imaging Techniques by Jia Yi, Huilin Jiang, Yong Tan

“…By synthesizing the spectral lines of the four polarization states and the non-polarization states, it was found that the physical parameters of <i>I</i> (135°, 90°) polarization state were the most suitable for identifying soybean bacterial blight disease, and other polarization states could also supplement the characteristic information. …”
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Spectroscopic aspects of underwater digital holography of plankton by Victor Dyomin, Igor Polovtsev, Alexandra Davydova, Nikolai Kirillov

“…The in situ experimental data suggest that the order and chaos of plankton biocenosis are reflected in the structure of the spectral lines of the ecosystem functions associated with plankton. …”
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DC/DC converter to power spectral lamps by M. Yu. Nikolshin, A. V. Frunze, V. K. Bityukov

“…The paper describes the creation of a DC/DC converter for powering hollow cathode lamps widely used currently as highly stable sources of spectral lines in spectral absorption analyzers and other applications. …”
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Spatiotemporal Evolution of the Water System’s Structure and Its Relationship with Urban System Based on Fractal Dimension: A Case Study of the Huaihe River Basin, China by Hailong Yu, Bin Yu, Xiangmin Zhang, Yong Fan, Sai Wen, Shanshan Jiao

“…Then, through a comparative analysis of fractal parameters and spectral lines, the characteristics and changing patterns of the “urban-water” relationship in the HRB from 1980 to 2019 were revealed. …”
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Peering into the Black Box: Forward Modeling of the Uncertainty Budget of High-resolution Spectroscopy of Exoplanet Atmospheres by Arjun B. Savel, Megan Bedell, Eliza M.-R. Kempton, Peter C. B. Smith, Jacob L. Bean, Lily L. Zhao, Kaze W. K. Wong, Jorge A. Sanchez, Michael R. Line

“…By resolving individual spectral lines, HRCCS can precisely measure chemical abundance ratios, directly constrain atmospheric dynamics, and robustly probe multidimensional physics. …”
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TransformerPayne: Enhancing Spectral Emulation Accuracy and Data Efficiency by Capturing Long-range Correlations by Tomasz Różański, Yuan-Sen Ting, Maja Jabłońska

“…Analysis of TransformerPayne's attention maps revealed that they encode interpretable features common across many spectral lines of chosen elements. While scaling up The Payne to a larger network reduced its MAE from 1.2% to 0.3% when trained on the full data set, TransformerPayne consistently achieved the lowest MAE across all tests. …”
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A pipeline for processing hyperspectral images, with a case of melanin-containing barley grains as an example by I. D. Busov, M. A. Genaev, E. G. Komyshev, V. S. Koval, T. E. Zykova, A. Y. Glagoleva, D. A. Afonnikov

“…The current version of the package implements the following methods: construction of a confidence interval of an arbitrary level for the difference of sample averages; verification of the similarity of intensity distributions of spectral lines for two sets of hyperspectral images on the basis of the Mann–Whitney U-criterion and Pearson’s criterion of agreement; visualization in two-dimensional space using dimensionality reduction methods PCA, ISOMAP and UMAP; classification using linear or ridge regression, random forest and catboost; clustering of samples using the EM-algorithm. …”
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