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Showing 2,061 - 2,080 results of 53,535 for search '((unstructures OR structured) OR (structures OR structural)) data', query time: 0.50s Refine Results
  1. 2061

    Structural and Dynamical Effects of the CaO/SrO Substitution in Bioactive Glasses by Margit Fabian, Matthew Krzystyniak, Atul Khanna, Zsolt Kovacs

    Published 2024-10-01
    “…Motivated by these recent developments, the effect of SrO/CaO–CaO/SrO substitution on the local structure and dynamics of Si-Na-P-Ca-O oxide glasses has been studied in this work. …”
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    Article
  2. 2062

    Determinants of child malnutrition and morbidity in Ethiopia: a structural equation modeling approach by Birhanu Betela Warssamo, Denekew Bitew Belay, Denekew Bitew Belay, Ding-Geng Chen, Ding-Geng Chen

    Published 2025-04-01
    “…Thus, this study aims to investigate the underlying risk factors by employing a structural equation model to analyze malnutrition as a mediator in the relationship between selected factors and morbidity.MethodsThe study utilized data from the 2016 Ethiopia Demographic and Health Survey and a sample of 8,560 under-five children were considered. …”
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  3. 2063

    Choroid plexus aging: structural and vascular insights from the HCP-aging dataset by Zhe Sun, Chenyang Li, Jiangyang Zhang, Thomas Wisniewski, Yulin Ge

    Published 2024-12-01
    “…Abstract Background The choroid plexus (ChP), a highly vascularized structure within the ventricles, is essential for cerebrospinal fluid (CSF) production and metabolic waste clearance, crucial for neurofluid homeostasis and cognitive function. …”
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  4. 2064

    High Resolution Mass Spectrometry Fragmentation Rules of Etomidate and Its Structural Analogues by FAN Xian-yu, ZHU Xue-yan, WANG Xin, XIANG Ping, ZHAO Jun-bo

    Published 2024-12-01
    “…ObjectiveTo explore the characteristic fragment ions, ion abundance ratios and mass spectrometry fragmentation rules of etomidate and its structural analogues by using gas chromatography-quadrupole/orbitrap mass spectrometry (GC-Q/Orbitrap MS) and liquid chromatography-linear ion trap quadrupole-orbitrap mass spectrometry (LC-LTQ-Orbitrap MS) techniques, providing important data support for the identification and prediction of etomidate structural analogues.MethodsGC-Q/Orbitrap MS and LC-LTQ-Orbitrap MS were used to analyze metomidate, etomidate, isopropoxate and propoxate, to obtain their GC high resolution mass spectra and LC high resolution mass spectra.ResultsUnder the electron impact (EI) ion source mode, etomidate, metomidate and the other two analogues all produced their molecular ions and seven identical fragment ions (m/z 77.038 6, 79.054 2, 95.024 0, 105.069 9, 143.073 0, 172.099 5 and 199.086 6), among which isopropoxate and propoxate also produced characteristic fragment ions m/z 216.089 3. …”
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  5. 2065

    Modeling factors related to earthquake preparedness: a structural equation modeling approach by Azadeh Fatehpanah, Elham Maraghi, Anthony Coetzer-Liversage, Mahmood Karimy, Amir H. Pakpour, Majed Maripour, Nematollah Jaafarzadeh Haghighi Fard, Marzieh Araban

    Published 2025-02-01
    “…Structural equation modeling (SEM) was employed to analyze TPB constructs, including attitudes, subjective norms, perceived behavioral control, and intentions, in relation to earthquake preparedness behaviors. …”
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    Article
  6. 2066

    L-Ornithine derivatives with structural hetaryl and alkyl moiety: Synthesis and antibacterial activity by T. G. Bodrova, U. A. Budanova, Yu. L. Sebyakin

    Published 2024-07-01
    “…Nine new lipoamino acid cationic bivalent amphiphiles based on L-ornithine were synthesized. The structure of the obtained compounds was confirmed by nuclear magnetic resonance 1H spectroscopy and mass spectrometry data. …”
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  7. 2067
  8. 2068

    Semantic SLAM using laser-vision data fusion: Enhancing autonomous navigation in unstructured environments by Ning Chen, Dong Wei, Dongsheng Lin, Linhan Lin

    Published 2025-08-01
    “…Semantic maps, which embed semantic information into spatial representations, enable robots to better interpret complex environments and improve their autonomous operation in unstructured, GPS-denied, and extreme settings. In this context, an advanced semantic SLAM algorithm, termed NN-SLAM, is proposed based on the fusion of visual and laser data. …”
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  9. 2069

    Research on Data Transfer Method for Multi-physics Coupling Based on Unstructured Mesh Monte Carlo by LI Rui1, LIU Shichang1, , WANG Lipeng2, WANG Zhenyu1, CHEN Yixue1

    Published 2025-06-01
    “…Among these, the neutronic-thermal-mechanical coupling and neutronic-thermal-fluid coupling analyses have a significant impact on the reactor design. In addressing the data transfer issues in the multiphysics coupling process of reactors, this study employs a hybrid approach that integrates unstructured mesh (UM) Monte Carlo with finite element methods. …”
    Article
  10. 2070

    Cancer pain and quality of life structural equation model based on the biopsychosocial model by Xiaoyu Hu, Jingjing Lü, Chang Qin, Xiaoxuan Liu, Jianbiao Zhu, Yongchun Cui

    Published 2025-07-01
    “…Abstract Objective This study employed a biopsychosocial framework to develop structural equation models(SEM)quantifying the multidimensional impact of pain on quality of life in cancer patients, aiming to provide scientific evidence and novel clinical perspectives for evidence-based pain management strategies. …”
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  11. 2071
  12. 2072

    STRUCTURAL FEATURES OF PURULENT INFLAMMATORY DISEASES OF THE MAXILLOFACIAL REGION IN RESIDENTS OF THE POLTAVA REGION by D.V. Steblovskyi, M.G. Skikevich, V.V. Bondarenko

    Published 2020-12-01
    “…The aim of the study. Investigate the structure and frequency of purulent inflammatory diseases in residents of Poltava region. …”
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  13. 2073

    Structural Geomorphology and Tectonic Dynamism of the Lolodorf Segment, Nyong Complex, SW Cameroon by Messi Ottou Eric José, Etoundi Akoa Philémon Rémi, Ntieche Benjamin, Ntomba Sylvestre Martial, Evina Aboula Yannick Saturnin, Ndjigui Paul-Désiré

    Published 2025-06-01
    “… The study of the structural geomorphology and tectonic dynamism of the Lokoundjé and Nyong watersheds has made possible to discriminate the essential geological objects of the Lolodorf region (3°10’- 3°25’N, 10°40’- 10°55’E), in Southern Cameroon. …”
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  14. 2074

    Structural and morphological features of microcrystalline сellulose from industrial hemp hurd by L. O. Barybina, T. V. Tkachenko, O. O. Haidai, V. S. Sokol, B. V. Korinenko, D. S. Kamenskyh, Y. V. Sheludko, V. A. Povazhny, V. A. Bohatyrenko, S. V. Ruban, V. O. Yevdokymenko

    Published 2024-11-01
    “…To obtain microcrystalline cellulose, the hemp hurd was subjected to organo-solvent cooking. The structure and morphology of the MCC were studied using methods such as XRD, XRF, FTIR-ATR, low-temperature nitrogen sorption-desorption, AFM, TGA, and DSC. …”
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  15. 2075
  16. 2076

    The arabic version of the fat phobia scale—short form: reliability and structural validity by Hadeel Ghazzawi, Ahmad Alenezi, Sally Souraya, Omar Alhaj, Khaled Trabelsi, Adam Amawi, Mai Helmy, Zahra Saif, Beatrice “Bean” E. Robinson, Haitham Jahrami

    Published 2025-02-01
    “…According to the fit indices, the F-Scale 14 demonstrated a satisfactory level of structural validity in Arab cultures. Fit indices are statistical measures used in confirmatory factor analysis (CFA) to assess how well a proposed model fits the observed data. …”
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  17. 2077

    Structural abnormalities of the cerebellar gray matter and cerebellar peduncles in cervical dystonia patients by Mingjing Qiu, Yongsheng Xiang, Lixi Li, Lizhen Pan, Yunping Song, Liang Feng, Lingjing Jin

    Published 2025-09-01
    “…Between-group differences in gray matter volumes of cerebellar subregions and fiber morphometric properties of the cerebellar peduncles (CP) were investigated using voxel-based, region of interest-based and fixel-based analysis, respectively. The significant structural changes were correlated with clinical data, including disease duration and the first section of TWSTRS. …”
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  18. 2078

    Structural Variations Associated with Adaptation and Coat Color in Qinghai‐Tibetan Plateau Cattle by Xiaoting Xia, Fuwen Wang, Xiaoyu Luo, Shuang Li, Yang Lyu, Yining Zheng, Zhijie Ma, Kaixing Qu, Rende Song, Jianyong Liu, Jicai Zhang, Basang Wangdui, Basang Zhuzha, Suolang Quji, Li Zhao, Silang Wangmu, Ciren Luobu, Nima Cangjue, Danzeng Luosang, Suolang Sizhu, Haijian Cheng, Ruizhe Li, Zhipeng Wu, Ruihua Dang, Yongzhen Huang, Xianyong Lan, Luohao Xu, Haifei Hu, WaiYee Low, Zhuqing Zheng, Yu Wang, Yuanpeng Gao, Lu Deng, Johannes A. Lenstra, Jianlin Han, Xueyi Yang, Wenfa Lyu, Bizhi Huang, Chuzhao Lei, Ningbo Chen

    Published 2025-08-01
    “…Abstract Structural variations (SVs) play crucial roles in the evolutionary adaptation of domesticated animals to natural and human‐controlled environments, but SVs have not been explored in Tibetan cattle, which recently migrated and rapidly adapted to the high altitudes of the Qinghai‐Tibetan Plateau (QTP). …”
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  19. 2079

    The Structural and Kinematical Properties of NGC 5634, a Globular Cluster Associated with the Sagittarius Dwarf Galaxy? by Shouzhi Wang, Jundan Nie, Biwei Jiang, Hao Tian, Chao Liu, Ying-Hua Zhang

    Published 2025-01-01
    “…We investigate the origin of NGC 5634 through a comprehensive analysis of its morphology, kinematics, and dynamics. Utilizing data from the DESI Legacy Survey, we refined its fundamental parameters (age τ = 12.8 ± 0.3 Gyr, metallicity [Fe/H] = −1.8 ± 0.1 dex, distance modulus dm = 17.0 ± 0.1 mag) and constructed a matched-filter template based on the combination of these parameters to search for extra-tidal structures. …”
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  20. 2080

    Beyond Euclid: an illustrated guide to modern machine learning with geometric, topological, and algebraic structures by Mathilde Papillon, Sophia Sanborn, Johan Mathe, Louisa Cornelis, Abby Bertics, Domas Buracas, Hansen J Lillemark, Christian Shewmake, Fatih Dinc, Xavier Pennec, Nina Miolane

    Published 2025-01-01
    “…The enduring legacy of Euclidean geometry underpins classical machine learning, which, for decades, has been primarily developed for data lying in Euclidean space. Yet, modern machine learning increasingly encounters richly structured data that is inherently non-Euclidean. …”
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