How biased is size fractionation derived mineral-associated organic carbon?
GeodermaMineral-associated organic carbon (MAOC) is regarded as the more persistent soil organic carbon (SOC) as opposed to the more fast-cycling particulate organic carbon (POC).
Christopher Poeplau +2 more
doaj +2 more sources
Development of a rapid fractionation tool for natural organic matter [PDF]
, 2010 A rapid natural organic matter (NOM) fractionation tool was developed to enable NOM to be classified by hydrophobicity at the water treatment works and in the catchment.
Piper, Claire
core +7 more sources
Physics of fractional imaging in biomedicine [PDF]
Progress in Biophysics and Molecular Biology, 2018 The mathematics of imaging is a growing field of research and is evolving rapidly parallel to evolution in the field of imaging. Imaging, which is a sub-field of biomedical engineering, considers novel approaches to visualize biological tissues with the general goal of improving health.
Ayesha Sohail +3 more
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Fraction ball: Playful and physically active fraction and decimal learning.
Journal of Educational Psychology, 2021 This study tested a novel approach to capitalizing on the benefits of play for informal math learning. Two experiments evaluated a platform called “Fraction Ball”, that provides an embodied, playful, and physically active learning experience by modifying the lines on a basketball court to support rational number learning.
Andres S. Bustamante +4 more
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Fractional physics-informed neural networks for time-fractional phase field models [PDF]
Nonlinear Dynamics, 2021 Abstract In this paper, a new fractional physics-informed neural networks (fPINNs) is proposed, which combines fPINNs with spectral collocation method to solve the time-fractional phase field models. Compared to fPINNs, it has large representation capacity due to the property of spectral collocation method, which reduces the number of ...
Shupeng Wang, Hui Zhang, Xiaoyun Jiang
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fPINNs: Fractional Physics-Informed Neural Networks [PDF]
SIAM Journal on Scientific Computing, 2019 Physics-informed neural networks (PINNs) are effective in solving integer-order partial differential equations (PDEs) based on scattered and noisy data. PINNs employ standard feedforward neural networks (NNs) with the PDEs explicitly encoded into the NN using automatic differentiation, while the sum of the mean-squared PDE-residuals and the mean ...
Guofei Pang +2 more
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Fractional authorship in nuclear physics [PDF]
Scientometrics, 2015 8 pages, 4 ...
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Fractional Calculus of Variations in Terms of a Generalized Fractional Integral with Applications to Physics [PDF]
Abstract and Applied Analysis, 2012 We study fractional variational problems in terms of a generalized fractional integral with Lagrangians depending on classical derivatives, generalized fractional integrals and derivatives. We obtain necessary optimality conditions for the basic and isoperimetric problems, as well as natural boundary conditions for free‐boundary value problems.
Odzijewicz, Tatiana +2 more
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Physical weathering by glaciers enhances silicon mobilisation and isotopic fractionation [PDF]
, 2021 Glacial meltwaters export substantial quantities of dissolved and dissolvable amorphous silicon (DSi and ASi), providing an essential nutrient for downstream diatoms.
Hendry, K.R. +23 more
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Carbon isotope fractionation during aerobic biodegradation of trichloroethene by Burkholderia cepacia G4: a tool to map degradation mechanisms [PDF]
, 2002 The strain Burkholderia cepacia G4 aerobically mineralized trichloroethene (TCE) to CO2 over a time period of similar to20 h. Three biodegradation experiments were conducted with different bacterial optical densities at 540 nm (OD(540)s) in order to test
Schuth, Christoph +25 more
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