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Computational Molecular Modelling
In this chapter, we discuss the computational molecular modelling strategies. In particular, the CHARMM molecular mechanics force field of... -
Turbulence modelling in neutron star merger simulations
Observations of neutron star mergers have the potential to unveil detailed physics of matter and gravity in regimes inaccessible by other...
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Exact Solutions Modelling Nonlinear Atmospheric Gravity Waves
Exact solutions to the governing equations for atmospheric motion are derived which model nonlinear gravity wave propagation superimposed on...
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Ocean biogeochemical modelling
Ocean biogeochemical models describe the ocean’s circulation, physical properties, biogeochemical properties and their transformations using coupled...
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Modelling the mechanical behaviour of clay using particle-scale simulations
This paper demonstrates the latest developments in particle-scale modelling of a clay. It shows that by creating an initial sample of platelets...
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A systematic light pollution modelling bias in present night sky brightness predictions
Night sky brightness (NSB) measurements inform both the selection of new ground-based optical and near-infrared astronomical observatory sites and...
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Stresses in Silicon Dioxide Films Deposited from Dielectric Targets: Results of Atomistic Modelling
AbstractThe previously proposed method of molecular dynamics modelling for the sputter deposition of thin films from metal targets has been adapted...
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Stochastic modelling of diffused and specular reflector efficiencies for scintillation detectors
Scintillation detectors find wide application in detection of ionizing radiation. To prevent lateral loss of scintillation photons out of the...
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Reconstructing Sunspot Number by Forward-Modelling Open Solar Flux
The open solar flux (OSF) is the integrated unsigned magnetic flux leaving the top of the solar atmosphere to form the heliospheric magnetic field....
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Finite Element Modelling in Bones: A Review
This review explores the utilization of Finite Element Method (FEM) modelling in the field of bone biomechanics. It emphasizes the crucial... -
The role of particle shape in computational modelling of granular matter
Granular matter is ubiquitous in nature and is present in diverse forms in important engineering, industrial and natural processes. Particle-based...
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Detector Modelling Strategies for Precision EW Studies
This chapter describes the detector modelling challenges and strategies developed to overcome them in making precision electroweak measurements with... -
Coarse-Grain Modelling Strategies
In this chapter, the computational coarse-grain modelling strategies are discussed. Besides, different coarse-grained models (CGMs) will be described. -
Single station modelling of ionospheric irregularities using artificial neural networks
An empirical model of ionospheric irregularities over Mbarara (MBAR, 30.7 ∘ E geographic longitude, 0.6 ∘ S geographic latitude, 10.22 ∘ S geomagnetic...
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A concise guide to modelling the physics of embodied intelligence in soft robotics
Embodied intelligence (intelligence that requires and leverages a physical body) is a well-known paradigm in soft robotics, but its mathematical...
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Modelling DTPA therapy following Am contamination in rats
A major challenge in modelling the decorporation of actinides (An), such as americium (Am), with DTPA (diethylenetriaminepentaacetic acid) is the...
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Molecular Modelling of Pro-Gly Glyproline and Its Complexes
AbstractIn the present work, Pro-Gly glyproline and its biologically active complexes with heparin and with the antithrombin-heparin protein complex...
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Statistical modelling of century-long precipitation and temperature extremes in Himachal Pradesh, India: generalized extreme value approach and return level estimation
Climate variability, particularly, that of temperature and precipitation, has received a great deal of attention worldwide. In the present work, we...
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Modelling Pedestrian Collective Dynamics with Port-Hamiltonian Systems
Port-Hamiltonian systems (PHS) are increasingly popular modelling approaches for nonlinear physical systems. In this contribution, we identify a... -
Non-parametric data-driven background modelling using conditional probabilities
Background modelling is one of the main challenges in particle physics data analysis. Commonly employed strategies include the use of simulated...