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    Relações empíricas entre a estrutura da vegetação e dados do sensor TM/LANDSAT Empirical relationship between vegetation structure and TM/LANDSAT data by Luciano J. de O. Accioly, Admilson Pachêco, Thomaz C. e C. da Costa, Osvaldo F. Lopes, Maria A. J. de Oliveira

    Published 2002-12-01
    “…<br>The use of spectral data to estimate the structural parameters of vegetation has been considered as one of the most important applications of the remote sensing of ecosystems. …”
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    LOW AND MEAN RADIATION DOSES IMPACT ON THE CEREBRAL TRACTS STRUCTURE OF THE CHERNOBYL ACCIDENT LIQUIDATORS IN THE REMOTE PERIOD (BASED ON ROUTINE AND DIFFUSION-TENSOR MAGNETIC RESONANCE IMAGING DATA) by I. M. Levashkina, S. S. Aleksanin, S. V. Serebryakova, T. G. Gribanova

    Published 2018-01-01
    “…To evaluate correlation between brain structural damages and radiation exposure level for the Chernobyl nuclear power plant accident liquidators, routine and diffusion tensor magnetic resonance imaging methods are efficient to visualize and evaluate those damages; it is also important to compare magnetic resonance imaging data of liquidators with results, received for people of the same age and the same stage of cerebral vascular disease (the discirculatory encephalopathy of I and II stage), but who did not participate in the Chernobyl accident liquidation and did not suffer from other liquidation factors and radiation catastrophe aftermaths. …”
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  6. 1546

    CrystalShift: A Versatile Command-Line Tool for Crystallographic Structural Data Analysis, Modification, and Format Conversion Prior to Solid-State DFT Calculations of Organic Crystals by Ilona A. Isupova, Denis A. Rychkov

    Published 2025-06-01
    “…<i>CrystalShift</i> is an open-source computational tool tailored for the analysis, transformation, and conversion of crystallographic data, with a particular emphasis on organic crystal structures. …”
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    Stream Members Only: Data-driven Characterization of Stellar Streams with Mixture Density Networks by Nathaniel Starkman, Jacob Nibauer, Jo Bovy, Jeremy J. Webb, Kiyan Tavangar, Adrian Price-Whelan, Ana Bonaca

    Published 2025-01-01
    “…A precise characterization of streams from potentially noisy data marks a crucial step in inferring galactic structure, including the dark matter, across orders of magnitude in mass scales. …”
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    Parcel-scale crop planting structure extraction combining time-series of Sentinel-1 and Sentinel-2 data based on a semantic edge-aware multi-task neural network by Zhiguang Tang, Xiangdong Wang, Qin Jiang, Haizhu Pan, Gang Deng, He Chen, Yuanhong You, Sijia Li, Haiyan Hou

    Published 2025-08-01
    “…Ultimately, a parcel-scale random forest (RF) model was developed to enable accurate crop type classification and spatial delineation of crop planting structures. Results show: 1) SEANet achieves accurate extraction of parcel boundaries, extracting a total of 175,000 parcels, and demonstrates a relative error of 6.98% compared to statistical yearbook data. …”
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    Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structure by Geunsoo Jang, Jihyeon Kim, Robin N. Thompson, Hyojung Lee

    Published 2025-04-01
    “…Methods: We used mathematical modeling to assess the effectiveness of alternative vaccination strategies under different assumptions about the number of available vaccine doses. An age-structured transmission model was developed using vaccination and seropositivity data. …”
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    Crystallinity Changes in Modified Cellulose Substrates Evidenced by Spectral and X-Ray Diffraction Data by Magdalena-Cristina Stanciu, Fulga Tanasă, Carmen-Alice Teacă

    Published 2025-04-01
    “…Due to their specific methodology, they can be used to analyze not only starting materials and their final products but also intermediates. Data obtained by these methods substantiated the structural changes in cellulose substrates, as well as the alterations that occurred in their supramolecular architectures. …”
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