Showing 521 - 540 results of 53,535 for search '((structural OR (unstructures OR structural)) OR structures) data', query time: 0.47s Refine Results
  1. 521

    Conserved genome structure and phylogenetic insights for the heterogeneous subfamily of Convallarioideae (Asparagaceae) revealed from plastome data by Shao-De Wu, Ran Meng, Ze-Long Nie, Ming-Yang Song, Xing-Ru Chen, Jun Wen, Ying Meng

    Published 2025-05-01
    “…Despite its importance, chloroplast genome data for Convallarioideae remain limited, hindering a comprehensive understanding of their genome structural evolution and phylogenetic relationships. …”
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    Article
  2. 522

    Corticolimbic Structural Deficits in Violent Patients with Schizophrenia by Maria Athanassiou, Alexandre Dumais, Inès Zouaoui, Alexandra Fortier, Luigi de Benedictis, Olivier Lipp, Andràs Tikàsz, Stéphane Potvin

    Published 2025-02-01
    “…<b>Conclusions</b>: These findings underscore disruptions in the structural integrity of the dlPFC—responsible for inhibitory control—and the amygdala—central to emotional processing in violent patients with Sch. …”
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    Article
  3. 523

    Structural Changes in the Dynamics of China’s Exports and Imports by V. V. Narbut, T. I. Chinaeva, E. I. Larionova

    Published 2024-05-01
    “…During the work, dynamic, structural analysis of analytical and statistical information was used; methods of analytical, logical, systemic, correlation and regression analysis were used, as well as analysis of structural changes. …”
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    Article
  4. 524
  5. 525

    Morphological similarity and white matter structural mapping of new daily persistent headache: a structural connectivity and tract-specific study by Di Zhang, Fangrong Zong, Yanliang Mei, Kun Zhao, Dong Qiu, Zhonghua Xiong, Xiaoshuang Li, Hefei Tang, Peng Zhang, Mantian Zhang, Yaqing Zhang, Xueying Yu, Zhe Wang, Yong Liu, Binbin Sui, Yonggang Wang

    Published 2024-11-01
    “…The objective of this work is to explore the fiber tracts and structural connectivity, which can help reveal unique gray and white matter structural abnormalities in NDPH. …”
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    Article
  6. 526

    Structural Tectonic Scheme Creation Based on Seismic-Gravity Models and Isostasy Usage: Ural Case by Martyshko Petr, Ladovskii Igor, Byzov Denis, Tsidaev Aleksandr

    Published 2024-02-01
    “…They contain solution of non-linear (structural) inverse problem and the solution of the linear three-dimensional inverse problem taking note of the side sources. …”
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  7. 527

    The use of space geophysics data to establish a subsurface structural frameworks map on East Uweinat ring complexes province, Southwestern Desert, Egypt by Yaseen AAMER, Ashraf GHONEIMI, Salah HANAFY, Mohamed H. M. YOUSEF, Sara ZAMZAM

    Published 2025-03-01
    “…A qualitative and quantitative interpretation is used to highlight the subsurface geological picture and structure framework. The integration of these data helps to understand the subsurface structural framework and provide insights into the geological evolution of the region. …”
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  8. 528

    Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

    Published 2025-03-01
    “…This research employs agent-based models (ABM) to simulate spatial information and explore the spatial function distribution of planned sites under urban spatial function penetration, thereby guiding the structural morphology of scheduled sites.MethodsThis research adopts a spatial network analysis design method using slime mold intelligence based on mapping point of interest (POI) data. …”
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  9. 529
  10. 530

    Comparison of the capability and performance of “photosynthesis” and “structure” indices in retrieving vegetation phenology in the Northern Hemisphere by Bohan Jiang, Wei Chen, Shaoyi Chen, Xiaoyue Wang, Si-Liang Li

    Published 2025-12-01
    “…Focusing on the mid-high latitudes vegetation in the Northern Hemisphere, this study reported the differences in phenology extracted using “photosynthesis” and “structure” indices, specifically solar-induced chlorophyll fluorescence (SIF) and leaf area index (LAI), respectively. …”
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  11. 531
  12. 532

    Investigation of the Internal Structure of Hard-to-Reach Objects Using a Hybrid Algorithm on the Example of Walls by Rafał Brociek, Józef Szczotka, Mariusz Pleszczyński, Francesca Nanni, Christian Napoli

    Published 2025-05-01
    “…The approach presented in the article consists of a non-standard solution to the problem of reconstructing the internal structure of the tested object. The classical approach involves constructing an appropriate system of equations based on X-rays, the solution of which describes the structure. …”
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  13. 533
  14. 534

    Enceladus's internal ocean and ice shell constrained from Cassini gravity, shape, and libration data by Ondřej Čadek, Gabriel Tobie, Tim Van Hoolst, Marion Massé, Gaël Choblet, Axel Lefèvre, Giuseppe Mitri, Rose‐Marie Baland, Marie Běhounková, Olivier Bourgeois, Anthony Trinh

    Published 2016-06-01
    “…Here we develop an interior structure model consisting of a rocky core, an internal ocean, and an ice shell, which satisfies simultaneously the gravity, shape, and libration data. …”
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  18. 538

    SV-MeCa: an XGBoost-based meta-caller approach for structural variant calling from short-read data by Rudel Christian Nkouamedjo Fankep, Arda Söylev, Anna-Lena Kobiela, Jochen Blom, Corinna Ernst, Susanne Motameny

    Published 2025-08-01
    “…Abstract Background Calling structural variants (SVs), i.e., genomic alterations of $$\ge $$ 50bp, from whole genome short-read data remains challenging, as existing callers are known to lack accuracy and robustness. …”
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  19. 539

    scHiCSRS: a self-representation smoothing method with Gaussian mixture model for imputing single cell Hi-C data by Qing Xie, Wang Meng, Shili Lin

    Published 2025-05-01
    “…Results We propose scHiCSRS, a self-representation smoothing method that improves data quality, and a Gaussian mixture model that identifies structural zeros among observed zeros. scHiCSRS not only takes spatial dependencies of a scHi-C data matrix into account but also borrows information from similar single cells. …”
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    Article
  20. 540