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  1. 361

    Automated Generation of Geometric FE Models for Timber Structures Using 3D Point Cloud Data by Lin Chen, Liufang Jiang, Haibei Xiong

    Published 2025-06-01
    “…Manual geometric modeling of timber structures is time-intensive and error-prone, impeding efficient structural analysis. …”
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    Article
  2. 362

    Higher-Order DNA Secondary Structures and Their Transformations: The Hidden Complexities of Tetrad and Quadruplex DNA Structures, Complexes, and Modulatory Interactions Induced by... by Jens Völker, Vera Gindikin, Kenneth J. Breslauer

    Published 2024-11-01
    “…First, strand invasion induces the disruption of DNA secondary structural elements in both the invading strand (which can assume an iDNA tetrad structure) and the invaded species (a G-quadruplex). …”
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    Article
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  5. 365

    Quantifying Tree Structural Change in an African Savanna by Utilizing Multi-Temporal TLS Data by Tasiyiwa Priscilla Muumbe, Jussi Baade, Pasi Raumonen, Corli Coetsee, Jenia Singh, Christiane Schmullius

    Published 2025-02-01
    “…Structural changes in savanna trees vary spatially and temporally because of both biotic and abiotic drivers, as well as the complex interactions between them. …”
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    Article
  6. 366

    Structural Damage Identification Method of Girder Bridges Based on Multilevel Data Fusion Theory by Chang-Sheng Xiang, Hai-Long Liu, Yu Zhou, Chen-Yu Liu, Li-Xian Wang

    Published 2022-01-01
    “…The first three order modes data of each index are fused in the first level, and their results are further fused between indexes in the second level, which will be applied for damage position judgement; moreover, results of the second level as input are last fused in the third level in order to predict structural damage degree. …”
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    Article
  7. 367

    RETRACTED: Simplicial Complex-Enhanced Manifold Embedding of Spatiotemporal Data for Structural Health Monitoring by Nan Xu, Zhiming Zhang, Yongming Liu

    Published 2023-03-01
    “…Structural Health Monitoring requires the continuous assessment of a structure’s operational conditions, which involves the collection and analysis of a large amount of data in both spatial and temporal domains. …”
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    Article
  8. 368

    Atypical structural tendencies among low-complexity domains in the Protein Data Bank proteome. by Sean M Cascarina, Mikaela R Elder, Eric D Ross

    Published 2020-01-01
    “…A variety of studies have suggested that low-complexity domains (LCDs) tend to be intrinsically disordered and are relatively rare within structured proteins in the Protein Data Bank (PDB). …”
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    Article
  9. 369

    Analyzing the function of metaverse technology in the retention and absorption of knowledge using the integrated approach of interpretive structural modeling and structural equatio... by Seyed Mojtaba Hosseinibamakan, Hajar Soleymanizadeh, Mehran Ziaeian

    Published 2024-10-01
    “…This problem affects the validity of interpretive structural modeling approach. To solve this problem and in order to validate the presented model resulting from the interpretive structural modeling approach, the structural equation modeling approach and Smart PLS software were used. …”
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    Article
  10. 370

    Local Structural Indices Changes During Different Periods of Postherpetic Neuralgia: A Graphical Study in Structural Covariance Networks by Xiong J, Gu L, Jiang X, Kuang H, Lv H, Li Z, Xie Y, Luo Q, Jiang J

    Published 2025-03-01
    “…Eglobal and Lp can be considered as potential imaging markers for future clinical restaging of PHN.Keywords: herpes zoster, postherpetic neuralgia, structural covariance network, graph theory, small world, cortical thickness…”
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    Article
  11. 371

    The Role of Sunspots Magnetic Configuration in the Formation of Umbral Fine-Structures by Hashem Hamedivafa

    Published 2023-10-01
    “…This new configuration causes the umbral fine-structures to form easily and more frequent.…”
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    Article
  12. 372

    Structural Fault Detection and Diagnosis for Combine Harvesters: A Critical Review by Haiyang Wang, Liyun Lao, Honglei Zhang, Zhong Tang, Pengfei Qian, Qi He

    Published 2025-06-01
    “…This paper provides a systematic and critical review and analysis of the latest advancements in research on data-driven FDD methods for structural faults in combine harvesters. …”
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    Article
  13. 373

    Modelling structural relations between financial, social-economic and healthcare factors by Iryna Pozovna, Karolina Hałuszko, Anna Polishchuk

    Published 2023-12-01
    “…To achieve this purpose, we used the following research methods: induction and deduction, analysis and synthesis, comparison and logical generalisation, table and diagram visualisation, observation and assessment, method of principal components, structural modelling. The research data are taken from the World Bank. …”
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    Article
  14. 374

    An Improved Man-Made Structure Detection Method for Multi-aspect Polarimetric SAR Data by Fabin Dong, Qiang Yin, Wen Hong

    Published 2025-01-01
    “…The comprehensive multiaspect scattering characteristics are valuable for man-made structure detection and classification. Typically, the anisotropic scattering of targets could be characterized by the differences in the statistical properties of polarimetric data across aspects. …”
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    STUDY OF THE PECULIARITIES OF THE STRUCTURE OF THE NASOLACRIMAL DUCT ORIFICE ACCORDING TO THE DATA OF MULTISLICE COMPUTED TOMOGRAPHY by E. L. At’kova, V. D. Yartsev, N. N. Krakhovetskiy, L. V. Reznikova, A. O. Root

    Published 2018-05-01
    “…To develop a method for investigating the perculiarities of the structure of the nasolacrimal duct orifice according to the data of multislice computed tomography (MSCT).Material and methods. …”
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    Article
  18. 378

    A comprehensive diagnostic framework for hepatitis C using structured data and predictive analytics by Behnaz Motamedi, Balázs Villányi

    Published 2025-12-01
    “…This study posits that a structured preprocessing and feature selection methodology might substantially improve the classification accuracy and generalizability of machine learning (ML) models in predicting stages of hepatitis C virus (HCV) using clinical and demographic data. …”
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    Article
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