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Singular Phenomena and Scaling in Mathematical Models

Overview of attention for book
Cover of 'Singular Phenomena and Scaling in Mathematical Models'

Table of Contents

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    Book Overview
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    Chapter 1 Ricci Bounds for Euclidean and Spherical Cones
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    Chapter 2 A Monotone Approximation to the Wasserstein Diffusion
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    Chapter 3 Adapted Function Spaces for Dispersive Equations
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    Chapter 4 A Note on Metastable Behaviour in the Zero-Range Process
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    Chapter 5 Convergence of the Two-Point Function of the Stationary TASEP
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    Chapter 6 Vortex Motion for the Landau-Lifshitz-Gilbert Equation with Applied Magnetic Field
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    Chapter 7 On Prandtl-Reuss Mixtures
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    Chapter 8 Modeling and Simulation of Lipid Monolayers as Surfactant in Lung Alveoli
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    Chapter 9 Fluid Mixtures and Applications to Biological Systems
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    Chapter 10 A Nested Variational Time Discretization for Parametric Anisotropic Willmore Flow
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    Chapter 11 Energy Scaling and Domain Branching in Solid-Solid Phase Transitions
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    Chapter 12 On a Multilevel Preconditioner and its Condition Numbers for the Discretized Laplacian on Full and Sparse Grids in Higher Dimensions
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    Chapter 13 Simulation of Droplet Impact with Dynamic Contact Angle Boundary Conditions
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    Chapter 14 A Parallel Multiscale Simulation Toolbox for Coupling Molecular Dynamics and Finite Elements
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    Chapter 15 A Moving Least Squares Approach to the Construction of Discontinuous Enrichment Functions
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    Chapter 16 Second Moment Analysis for Robin Boundary Value Problems on Random Domains
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    Chapter 17 Simulation of Q -Tensor Fields with Constant Orientational Order Parameter in the Theory of Uniaxial Nematic Liquid Crystals
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    Chapter 18 A Fast and Accurate Numerical Method for the Computation of Unstable Micromagnetic Configurations
Overall attention for this book and its chapters
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About this Attention Score

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  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

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Citations

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Readers on

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19 Mendeley
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Title
Singular Phenomena and Scaling in Mathematical Models
Published by
arXiv, November 2013
DOI 10.1007/978-3-319-00786-1
ISBNs
978-3-31-900785-4, 978-3-31-900786-1
Authors

Jinho Baik, Patrik L. Ferrari, Sandrine Péché

Editors

Griebel, Michael

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
China 1 5%
Korea, Republic of 1 5%
Belgium 1 5%
Unknown 16 84%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 32%
Student > Master 3 16%
Other 1 5%
Student > Doctoral Student 1 5%
Professor 1 5%
Other 3 16%
Unknown 4 21%
Readers by discipline Count As %
Engineering 5 26%
Physics and Astronomy 3 16%
Computer Science 2 11%
Mathematics 1 5%
Unspecified 1 5%
Other 2 11%
Unknown 5 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 March 2015.
All research outputs
#14,909,825
of 23,852,579 outputs
Outputs from arXiv
#297,801
of 990,619 outputs
Outputs of similar age
#179,096
of 307,804 outputs
Outputs of similar age from arXiv
#1,509
of 10,583 outputs
Altmetric has tracked 23,852,579 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 990,619 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 66% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 307,804 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10,583 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.