Relevant bibliographies by topics / Reconstruction and flux simulations

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Academic literature on the topic 'Reconstruction and flux simulations'

Author: Grafiati
Published: 25 January 2025

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Journal articles on the topic "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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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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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 process improves the reconstruction of the trend in ice extent and concentration between 1980 and 2009. This is linked to a better efficiency of the data assimilation procedure but can also be due to a better representation of the freshwater cycle in the Southern Ocean. The results of the hindcast simulations show that an adequate initial state, reconstructed thanks to the data assimilation procedure including an additional freshwater flux, can lead to an increase in the sea ice extent spanning several decades that is in agreement with satellite observations. In our hindcast simulations, an increase in sea ice extent is obtained even in the absence of any major change in the freshwater input over the last decades. Therefore, while the additional freshwater flux appears to play a key role in the reconstruction of the evolution of the sea ice in the simulation with data assimilation, it does not seem to be required in the hindcast simulations. The present work thus provides encouraging results for sea ice predictions in the Southern Ocean, as in our simulation the positive trend in ice extent over the last 30 years is largely determined by the state of the system in the late 1970s.
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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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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 emission line in and out of the region of strong ISM attenuation. Reconstructions of each spectrum should produce the same Lyα profile regardless of phase, under the well-justified assumption that there is no intrinsic line variability between observations. Instead, we find that the reconstructions underestimate the Lyα flux by almost a factor of 2 for the lowest velocity, most attenuated spectrum, due to a degeneracy between the intrinsic Lyα and ISM profiles. Our results imply that many stellar Lyα fluxes derived from G140M spectra reported in the literature may be underestimated, with potential consequences for, for example, estimates of extreme-ultraviolet stellar spectra and ultraviolet inputs into simulations of exoplanet atmospheres.
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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 depth root mean square error. We find no significant dependence in the improvement on input data signal to noise, although the gain is greatest in high optical depth regions. The Ly α forest optical depth studied here serves as a simple, one dimensional, example but the use of Deep Learning and simulations to approach the inverse problem in cosmology could be extended to other physical quantities and higher dimensional data.
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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 stability. This is achieved by proper representation of subfilter-scale (SFS) backscatter of turbulent kinetic energy (TKE). The flow structure and turbulence statistics for the moderately stable boundary layer (SBL) are analyzed with high-resolution simulations. The DRM simulations show good agreement with established empirical formulations such as flux and gradient-based surface similarity, even at relatively coarse resolution. Similar results can be obtained with traditional closure models at the cost of higher resolution. SBL turbulence under strong stability is also explored. Simulations show an intermittent presence of elevated TKE below the low-level jet. Overall, the explicit filtering and reconstruction approach is advantageous for simulations of the SBL. At coarse resolution, it can extend the working range of LES to stronger stability, while maintaining agreement to similarity theory; at fine resolution, good agreement with theoretical formulations provides confidence in the results and allows for detailed investigation of the flow structure under moderate to strong stability conditions.
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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 communities directly from metagenomes. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from MAGs to community level flux balance analysis (FBA) simulations. To demonstrate the capabilities of metaGEM, we analyzed 483 samples spanning lab culture, human gut, plant-associated, soil, and ocean metagenomes, reconstructing over 14,000 GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to isolated genomes. We demonstrate that metagenomic GEMs capture intraspecies metabolic diversity and identify potential differences in the progression of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, metaGEM enables FBA-ready metabolic model reconstruction directly from metagenomes, provides a resource of metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses.
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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. Latent heat flux variability differs between datasets, and this is investigated using a bulk formula. It is found that discrepancies in wind speed change explain contrasting latent heat flux trends across datasets. The significant increase in wind speed of 0.26 m s−1 decade−1 over the tropical eastern Pacific in ERA-Interim is not reproduced by satellite or buoy observations or atmosphere-only climate model simulations, casting questions on the reliability of reanalysis-based surface fluxes over the tropical eastern Pacific.
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