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  1. 761

    Urban Air Mobility Vertiport’s Capacity Simulation and Analysis by Antoni Kopyt, Sebastian Dylicki

    Published 2025-06-01
    “…The simulation evaluates critical variables such as vertiport dimensions, UAS fleet composition, and mission duration ranges while emphasizing scalability, safety, and compliance with evolving regulatory standards. …”
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  2. 762

    Formation of forest mensuration indicators of Pseudotsuga menziesii (Mirb.) Franco in artificial plantations of the western region of Ukraine by Iurii Debryniuk, Stepan Myklush, Yuriy Myklush

    Published 2024-10-01
    “…Due to the significant variability of the share of P. menziesii in the stand composition, the plantations were divided into four groups based on the share percentage of the tree species (10-20%; 30-40%; 50-70%; 80-100%). …”
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  3. 763

    'Selección e implementación de un modelo para el inicio de la transformación perlítica durante el enfriamiento en los aceros con baja aleación. R. // Selection and use of a model f... by R. Lobaina Sánchez, L. Goyos Pérez

    Published 2007-01-01
    “…As a result, we show a model for the starting pearlitic<br />transformation curves, depending of the steel composition, the grain size, the undercooling temperature, and the activation<br />energy. …”
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  4. 764

    The Upper Stratospheric Solar Cycle Ozone Response by W. T. Ball, E. V. Rozanov, J. Alsing, D. R. Marsh, F. Tummon, D. J. Mortlock, D. Kinnison, J. D. Haigh

    Published 2019-02-01
    “…We recommend the BASICv2 ozone composite to best represent historical upper stratospheric solar variability, and that those based on SBUV alone should not be used.…”
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  5. 765

    The impact of knowledge management on business performance with emphasis on the role of accounting information quality (Case study: financial institutions listed on the Tehran Capi... by Rahele Mashaykhi, Ahmad Pifeh, Hamed Ahmadzade

    Published 2025-03-01
    “…Also, the value of the Q2 index for the main endogenous variable of business performance is 0.419, which indicates that the predictive power of the model regarding this variable is at a desirable and strong level. …”
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  6. 766

    Responses of grassland soil mesofauna to induced climate change by Iwona Gruss, Marta Czarniecka-Wiera, Sebastian Świerszcz, Magdalena Szymura, Tomasz Szymura, Małgorzata W. Raduła

    Published 2025-05-01
    “…This study aimed to test the effects of induced climate change on the composition of soil mesofauna and vascular plant species in semi-natural grasslands. …”
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  7. 767

    The significance of green innovation efficiency of green low-carbon circular economy for sustainable cities in western China—Empirical evidence from Chongqing municipality by Panfeng Li

    Published 2025-07-01
    “…In this model, SO2 concentration was the dependent variable, GIE was the core explanatory variable, and control variables included openness to external trade (EXT), information technology level (ITL), urban cultural level (CUL), and research and development investment (RDI).ResultsThe entropy weight-TOPSIS model revealed that Chongqing's GLCCE composite index increased from 0.405 in 2014 to 0.684 in 2023, with a peak of 0.866 in 2020, indicating significant overall progress in GLCCE implementation. …”
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  8. 768

    Beta Diversity Patterns and Drivers of Macroinvertebrate Communities in Major Rivers of Ningxia, China by Qiangqiang Yang, Zeyu Wei, Xiaocong Qiu, Zengfeng Zhao

    Published 2025-07-01
    “…The findings demonstrate that the optimal parameter-based geographical detector (OPGD) model identified a 3000 m circular buffer as the spatial scale at which landscape structure most significantly influences water quality. …”
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  9. 769

    Sustainable Mineral Processing Technologies Using Hybrid Intelligent Algorithms by Olga Shiryayeva, Batyrbek Suleimenov, Yelena Kulakova

    Published 2025-06-01
    “…The objective is to enhance separation efficiency and reduce chromium losses through real-time optimization of process parameters under variable feed conditions. The method addresses ore composition fluctuations by integrating three components: Physical modeling of particle motion, regression analysis, and neural network-based prediction. …”
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  10. 770

    Evaluation of machine learning algorithms in tunnel boring machine applications: a case study in Mashhad metro line 3 by Morteza Abbasi, Amir Hossein Namadchi, Mehdi Abbasi, Mohsen Abbasi

    Published 2024-12-01
    “…This study investigates Mashhad Metro Line 3, where a TBM was employed to excavate a 1831-m section through variable soil compositions, including significant cobble and boulder content, presenting unique challenges to performance prediction. …”
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  11. 771
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    Improving Mechanical Properties of Nanocomposite-based Epoxy by High-impact Polystyrene and Multiwalled Carbon Nanotubes: Optimizing by a Mixture Design Approach by Yasser Rostamiyan

    Published 2017-04-01
    “…In the current study the influence of weight percentage of HIPS, weight percentage of CNT and hardener content on damping 1st and damping 2nd properties of epoxy/HIPS/CNT hybrid composite wase valuated. Mixture design methodology was employed to generate mathematical models for predicting damping 1st and damping 2nd behaviors of new mentioned hybrid nanocomposite as function of physical factors and optimizing desired mechanical properties. …”
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    TemDeep: a self-supervised framework for temporal downscaling of atmospheric fields at arbitrary time resolutions by L. Wang, Q. Li, Q. Li, Q. Lv, Q. Lv, X. Peng, X. Peng, W. You

    Published 2025-04-01
    “…However, the acquisition of high-resolution data is limited due to excessive computational demands and substantial storage needs in numerical models. Current deep learning methods for statistical downscaling still require massive ground truth with high temporal resolution for model training. …”
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    Do water–energy dynamics drive plant species richness patterns on the high alpine Tibetan plateau? by Prakash Bhattarai, Ole R. Vetaas, Guang Zhao

    Published 2025-05-01
    “…We performed detrended correspondence analysis and generalized linear models to explore the effect of energy and water variables on species composition and species richness, respectively. …”
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  20. 780

    Crop, semi-natural, and water features of the cotton agroecosystem as indicators of risk of infestation of two plant bug (Hemiptera: Miridae) pests by Michael J. Brewer

    Published 2024-11-01
    “…The smallest scale (2.5 km radius) models had the greatest number of variables selected and highest R2, while two broader scales (5 and 10 km) and truncating the models to three variables produced a narrower range of R2s (0.49 to 0.62) and more consistent entry of variables. …”
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