Results 121 to 130 of about 23,025 (301)
Scatter-Limited Hybrid Monte Carlo, Deterministic Transport with Quasi-Monte Carlo Sampling
We present a hybrid method for time-dependent particle transport that combines Monte Carlo (MC) estimation with a deterministic discrete ordinates (\(S_N\)) solve, augmented by quasi-Monte Carlo (QMC) sampling. For spatial discretizations, the MC component computes a piecewise-constant (cell-averaged) solution, while the \(S_N\) stage employs bilinear ...
Krotz, Johannes, McClarren, Ryan G.
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Advanced Physics Research, EarlyView.Cd2SnO4 exhibits excellent thermoelectric properties with a high Seebeck coefficient, power factor, and figure of merit, surpassing Bi2Te3. It shows both positive and negative Seebeck coefficient values, making it suitable for diverse applications. Its high electrical conductivity and low thermal conductivity enhance efficiency, while its negative Hall
Adel Bandar Alruqi, Nicholas O. Ongwen
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Potential energy landscape and thermodynamic transitions of coarse-grained protein models revealed by the multicanonical generalized hybrid Monte Carlo method. [PDF]
Biophys Physicobiol, 2020 Mukuta N, Miura S.
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A hybrid approach to excited-state-specific variational Monte Carlo and doubly excited states [PDF]
, 2020 Leon Otis +2 more
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The hybrid monte carlo algorithm for quantum chromodynamics [PDF]
, 2008 11 pages, Latex with lamuphys.sty and postscript figures, to appear in Proc. of the Workshop of the Graduiertenkolleg at the university of Wuppertal on "Field Theoretical Tools for Polymer and Particle Physics"
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British Journal of Clinical Pharmacology, EarlyView.Aims Amoxicillin, a widely used β‐lactam antibiotic, requires improved pharmacokinetic characterization during breastfeeding. This study used a population pharmacokinetic (PopPK) approach to model amoxicillin concentrations in breast milk, identify variability sources and estimate infant exposure, applying worst‐case scenarios.
Sarah Baklouti +9 more
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AlgorithmsIn this article, we present a hybrid optimization methodology using the whale optimization algorithm and Markov Chain Monte Carlo sampling technique in a teachers’ training development program regarding creativity in technology-enhanced learning design ...
Kalliopi Rigopouli +2 more
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Hybrid Monte Carlo Metadynamics (hybridMC-MetaD)
We propose the powerful integration of the Hybrid Monte Carlo (hybridMC) algorithm and Well-Tempered Metadynamics. This new algorithm, hybridMC-MetaD, enhances the flexibility and applicability of metadynamics by allowing for the utilization of a wider range of collective variables (CVs), namely non-differentiable CVs.
Zhao, Charlotte Shiqi +2 more
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Learner emotions and performance in hypercasual VR games with adaptive AI difficulty
British Educational Research Journal, EarlyView.Abstract Hypercasual virtual reality games (HVRGs) are widely regarded as cost‐effective tools for rapid skill acquisition, yet the mechanisms that optimise their effectiveness and user acceptance remain insufficiently explored. This mixed‐methods empirical study investigates how playful emotions, characterised by engagement, enjoyment and anxiety ...
Zeeshan Ahmed, Faizan Ahmad, Chen Hui
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