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Showing 621 - 640 results of 1,868 for search 'variable model (decomposition OR composition)', query time: 0.17s Refine Results
  1. 621
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    La déforestation au prisme des terroirs villageois en situation de mosaïque forêt-savane, République Démocratique du Congo by Christophe Demichelis, Johan Oszwald, Clélia Gasquet-Blanchard, Victor Narat, Jean-Christophe Bokika, Tamara Giles-Vernick

    Published 2022-09-01
    “…This inter-village variability made it possible to highlight a village typology directly linked to the landscape composition of the terroirs, and thus to highlight different socio-ecological situations within a small area. …”
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    Inadequacies in the representation of sub-seasonal phytoplankton dynamics in Earth system models by M. G. Keerthi, M. G. Keerthi, O. Aumont, L. Kwiatkowski, M. Levy

    Published 2025-05-01
    “…<p>Sub-seasonal phytoplankton dynamics on timescales between 8 d and 3 months significantly contribute to annual fluctuations, making it essential to accurately represent this variability in ocean models to avoid distorting long-term trends. …”
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  5. 625

    A Review of Sensors for the Monitoring, Modeling, and Control of Commercial Wine Fermentations by Roger Boulton, James Nelson, André Knoesen

    Published 2025-06-01
    “…Large-scale commercial wine fermentation requires the monitoring and control of multiple variables to achieve optimal results. Challenges in measurement arise from turbidity, stratification in large unmixed volumes, the presence of grape skins and solids during red wine fermentations, the small changes in variables that necessitate precise sensors, and the unique composition of each juice, which makes every fermentation distinct. …”
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  6. 626

    Modeling, Simulation, and Kinetic Studies of Solvent-Free Biosynthesis of Benzyl Acetate by Vijay Kumar Garlapati, Annapurna Kumari, Paramita Mahapatra, Rintu Banerjee

    Published 2013-01-01
    “…A nonlinear response surface model has been successfully developed based on central composite design with transesterification variables, namely, molarity of alcohol, reaction time, temperature, and immobilized lipase amount as input variables and molar conversion (%) as an output variable. …”
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  7. 627

    Modeling Trophic Cascades to Identify Key Mammalian Species for Ecosystem Stability by Idung Risdiyanto, Yanto Santosa, Nyoto Santoso, Arzyana Sunkar

    Published 2024-11-01
    “…Known as KVT version 1.0, the model explains the role of each characteristic variable of mammalian species, predicts population growth, elucidates species interactions at trophic levels, and assesses species-specific dietary compositions, including food requirements, reproduction, and activity. …”
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    Minimal mesoscale model for protein-mediated vesiculation in clathrin-dependent endocytosis. by Neeraj J Agrawal, Jonathan Nukpezah, Ravi Radhakrishnan

    Published 2010-09-01
    “…Based on the observed strong dependence of the vesicle diameter on the bending rigidity, we suggest that the variability in bending stiffness due to variations in membrane composition with cell type can explain the experimentally observed variability on the size of clathrin-coated vesicles, which typically range 50-100 nm. …”
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  10. 630

    Significant Serpents: Predictive Modelling of Bioclimatic Venom Variation in Russell's Viper. by Navaneel Sarangi, R R Senji Laxme, Kartik Sunagar

    Published 2025-04-01
    “…Our models effectively captured regional differences in venom composition and linked climatic conditions with functional variations.…”
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    Global, regional, and national burden of endocrine, metabolic, blood, and immune disorders from 1990 to 2021, and projections to 2050: a systematic analysis of the global burden of... by Jinpai Liang, Hongyan Leng, Xuelian Bai, Linling Li, Tao Qin, Jiazhi Ruan, Guoxing Wang, Wenjuan Zhang

    Published 2025-07-01
    “…Bayesian age-period-cohort (BAPC) models were applied for projections to 2050. Decomposition analysis attributed changes in disease burden to population growth, aging, and epidemiological shifts.ResultsIn 2021, the global incidence of EMBID was 79.47 million (95% UI 63.34–98.63 million), with an age-standardized rate of 957.58 (95% UI 766.99–1,183.95) per 100,000, showing a slight decline (EAPC: -0.24% [95% CI -0.35 – -0.12]). …”
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    Modeling actinic flux and photolysis frequencies in dense biomass burning plumes by J.-L. Tirpitz, S. F. Colosimo, N. Brockway, R. Spurr, M. Christi, S. Hall, K. Ullmann, J. Hair, T. Shingler, R. Weber, J. Dibb, R. Moore, E. Wiggins, V. Natraj, N. Theys, J. Stutz

    Published 2025-02-01
    “…Systematic biases between the model and observations are within 2 %, indicating that the uncertainties are most likely due to variability in the input data caused by the inhomogeneity of the plume as well as 3D RT effects not captured in the model. …”
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    Examination of Strength Modeling Reliability of Physical Tests on Structural Concrete Columns by Sher Ali Mirza

    Published 2011-01-01
    “…The columns were subjected to short-term loads producing pure axial force, axial force combined with symmetrical single-curvature bending, or pure bending. Major variables included the concrete strength, the end eccentricity ratio, the slenderness ratio, the longitudinal reinforcing steel index for reinforced concrete or the structural steel index for composite columns, and the transverse reinforcement (tie/hoop) volumetric ratio. …”
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  18. 638

    The Weight Minimization of a UAV Wing Component Through Structural Optimization by Andreas Psarros, Georgios Savaidis

    Published 2025-03-01
    “…This study focuses on the structural optimization of a composite wing element for an unmanned aerial vehicle. …”
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    Carbon emission forecasting in Zhejiang Province based on LASSO algorithm and grey model by HONG Jingke, DU Wei, SHAO Jin*, LAO Huimin

    Published 2024-06-01
    “…This paper investigates carbon emissions in Zhejiang Province. First, the variable mode decomposition method is used to decompose the historical data of carbon emissions in Zhejiang Province, enabling an analysis of its cyclicality fluctuations. …”
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