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Готові списки джерел за темами / Reconstruction and flux simulations

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Добірка наукової літератури з теми "Reconstruction and flux simulations"

Автор: Grafiati

Опубліковано: 25 січня 2025

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Статті в журналах з теми "Reconstruction and flux simulations"

1

Zerrik, E., and H. Bourray. "Flux reconstruction: sensors and simulations." Sensors and Actuators A: Physical 109, no. 1-2 (2003): 34–46. http://dx.doi.org/10.1016/s0924-4247(03)00358-3.

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2

Khazari, Adil, and Ali Boutoulout. "Flux reconstruction for hyperbolic systems: Sensors and simulations." Evolution Equations & Control Theory 4, no. 2 (2015): 177–92. http://dx.doi.org/10.3934/eect.2015.4.177.

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3

Cruz, Fernando, José P. Faria, Miguel Rocha, Isabel Rocha, and Oscar Dias. "A review of methods for the reconstruction and analysis of integrated genome-scale models of metabolism and regulation." Biochemical Society Transactions 48, no. 5 (2020): 1889–903. http://dx.doi.org/10.1042/bst20190840.

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The current survey aims to describe the main methodologies for extending the reconstruction and analysis of genome-scale metabolic models and phenotype simulation with Flux Balance Analysis mathematical frameworks, via the integration of Transcriptional Regulatory Networks and/or gene expression data. Although the surveyed methods are aimed at improving phenotype simulations obtained from these models, the perspective of reconstructing integrated genome-scale models of metabolism and gene expression for diverse prokaryotes is still an open challenge.

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4

Zunz, V., and H. Goosse. "Influence of freshwater input on the skill of decadal forecast of sea ice in the Southern Ocean." Cryosphere 9, no. 2 (2015): 541–56. http://dx.doi.org/10.5194/tc-9-541-2015.

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Abstract. Recent studies have investigated the potential link between the freshwater input derived from the melting of the Antarctic ice sheet and the observed recent increase in sea ice extent in the Southern Ocean. In this study, we assess the impact of an additional freshwater flux on the trend in sea ice extent and concentration in simulations with data assimilation, spanning the period 1850–2009, as well as in retrospective forecasts (hindcasts) initialised in 1980. In the simulations with data assimilation, the inclusion of an additional freshwater flux that follows an autoregressive pro

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5

Trojak, W., N. R. Vadlamani, J. Tyacke, F. D. Witherden, and A. Jameson. "Artificial compressibility approaches in flux reconstruction for incompressible viscous flow simulations." Computers & Fluids 247 (October 2022): 105634. http://dx.doi.org/10.1016/j.compfluid.2022.105634.

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6

Wilson, David J., Allison Youngblood, Odette Toloza та ін. "Testing Lyα Emission-line Reconstruction Routines at Multiple Velocities in One System". Astrophysical Journal 936, № 2 (2022): 189. http://dx.doi.org/10.3847/1538-4357/ac87a8.

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Abstract The 1215.67 Å H i Lyα emission line dominates the ultraviolet flux of low-mass stars, including the majority of known exoplanet hosts. Unfortunately, strong attenuation by the interstellar medium (ISM) obscures the line core in most stars, requiring the intrinsic Lyα flux to be reconstructed based on fits to the line wings. We present a test of the widely used Lyα emission-line reconstruction code lyapy using phase-resolved, medium-resolution STIS G140M observations of the close white dwarf–M dwarf binary EG UMa. The Doppler shifts induced by the binary orbital motion move the Lyα emi

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7

Huang, Lawrence, Rupert A. C. Croft та Hitesh Arora. "Deep forest: Neural network reconstruction of the Lyman-α forest". Monthly Notices of the Royal Astronomical Society 506, № 4 (2021): 5212–22. http://dx.doi.org/10.1093/mnras/stab2041.

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ABSTRACT We explore the use of Deep Learning to infer physical quantities from the observable transmitted flux in the Ly α forest. We train a Neural Network using redshift z = 3 outputs from cosmological hydrodynamic simulations and mock data sets constructed from them. We evaluate how well the trained network is able to reconstruct the optical depth for Ly α forest absorption from noisy and often saturated transmitted flux data. The Neural Network outperforms an alternative reconstruction method involving log inversion and spline interpolation by approximately a factor of 2 in the optical dep

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8

Zhou, Bowen, and Fotini Katopodes Chow. "Large-Eddy Simulation of the Stable Boundary Layer with Explicit Filtering and Reconstruction Turbulence Modeling." Journal of the Atmospheric Sciences 68, no. 9 (2011): 2142–55. http://dx.doi.org/10.1175/2011jas3693.1.

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Abstract Large-eddy simulation (LES) of the stably stratified atmospheric boundary layer is performed using an explicit filtering and reconstruction approach with a finite difference method. Turbulent stresses are split into the resolvable subfilter-scale and subgrid-scale stresses. The former are recovered from a reconstruction approach, and the latter are represented by a dynamic eddy-viscosity model. The resulting dynamic reconstruction model (DRM) can sustain resolved turbulence with less stringent resolution requirements than conventional closure models, even under strong atmospheric stab

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9

Zorrilla, Francisco, Filip Buric, Kiran R. Patil, and Aleksej Zelezniak. "metaGEM: reconstruction of genome scale metabolic models directly from metagenomes." Nucleic Acids Research 49, no. 21 (2021): e126-e126. http://dx.doi.org/10.1093/nar/gkab815.

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Abstract Metagenomic analyses of microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts mainly rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here, we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end pipeline enabling metabolic modeling of multi-species com

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10

Liu, Chunlei, and Richard P. Allan. "Unrealistic Increases in Wind Speed Explain Reduced Eastern Pacific Heat Flux in Reanalyses." Journal of Climate 31, no. 8 (2018): 2981–93. http://dx.doi.org/10.1175/jcli-d-17-0642.1.

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Abstract Tropical eastern Pacific sea surface temperature plays a pivotal role in mechanisms that determine global mean surface temperature variability. In this study, the surface flux contribution to recent cooling of the tropical eastern Pacific is investigated using data from three atmospheric reanalyses with full assimilation of observations, an observation-based net surface energy flux reconstruction, and 15 atmosphere-only climate model simulations. For ERA-Interim, 78% of the decrease in net surface flux (−0.65 W m−2 yr−1 over 1988–2008) is explained by the latent heat flux variability.

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