Results 121 to 130 of about 2,523,007 (359)

Estimating strongly wetting to non‐wetting contact angles for pure and mixed liquids on solids by considering film pressure

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Abstract In solid–liquid–vapour systems, the effect of film pressure (πe$$ {\pi}_e $$) by vapour adsorbate molecules becomes significant when the solid surface energy is similar to or larger than that of the liquid. We extend Young equation applicability to estimate contact angles of pure and mixed liquids on smooth solids by including πe$$ {\pi}_e $$,
Aliakbar Roosta, Nima Rezaei
wiley   +1 more source

Vector-Valued Polynomials and a Matrix Weight Function with B2-Action. II

open access: yesSymmetry, Integrability and Geometry: Methods and Applications, 2013
This is a sequel to [SIGMA 9 (2013), 007, 23 pages], in which there is a construction of a 2×2 positive-definite matrix function K(x) on R^2. The entries of K(x) are expressed in terms of hypergeometric functions. This matrix is used in the formula for a
Charles F. Dunkl
doaj   +1 more source

Learning hydrocracking reaction dynamics via neural ODEs: A data‐driven, gradient‐interpretable lumped modelling framework

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
This work demonstrates the application of neural ordinary differential equations (neural ODEs) for learning hydrocracking reaction kinetics directly from data, achieving robust predictions under noise and sparsity while preserving mechanistic interpretability through gradient‐based analysis of temperature‐ and concentration‐dependent reaction rates ...
Souvik Ta   +2 more
wiley   +1 more source

The First Hochschild Cohomology of Square Algebras With it's Stability

open access: yes, 2017
In this paper, we study on a special case of generalized matrix algebra that we call it square algebra. According to that Hochschild cohomology play a significant role in Geometry for example in orbifolds, we study the first Hochschild cohomology of the ...
F. Hassani, Negin Salehi Oroozaki
semanticscholar   +1 more source

A probabilistic diagnostic for Laplace approximations: Introduction and experimentation

open access: yesCanadian Journal of Statistics, EarlyView.
Abstract Many models require integrals of high‐dimensional functions: for instance, to obtain marginal likelihoods. Such integrals may be intractable, or too expensive to compute numerically. Instead, we can use the Laplace approximation (LA). The LA is exact if the function is proportional to a normal density; its effectiveness therefore depends on ...
Shaun McDonald, Dave Campbell
wiley   +1 more source

Sharp commutator estimates of all order for Coulomb and Riesz modulated energies

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
Abstract We prove functional inequalities in any dimension controlling the iterated derivatives along a transport of the Coulomb or super‐Coulomb Riesz modulated energy in terms of the modulated energy itself. This modulated energy was introduced by the second author and collaborators in the study of mean‐field limits and statistical mechanics of ...
Matthew Rosenzweig, Sylvia Serfaty
wiley   +1 more source

An analogue of Serre’s conjecture for a ring of distributions

open access: yesTopological Algebra and its Applications, 2020
The set 𝒜 := 𝔺δ0+ 𝒟+′, obtained by attaching the identity δ0 to the set 𝒟+′ of all distributions on 𝕉 with support contained in (0, ∞), forms an algebra with the operations of addition, convolution, multiplication by complex scalars.
Sasane Amol
doaj   +1 more source

Convergence properties of dynamic mode decomposition for analytic interval maps

open access: yesCommunications on Pure and Applied Mathematics, EarlyView.
Abstract Extended dynamic mode decomposition (EDMD) is a data‐driven algorithm for approximating spectral data of the Koopman operator associated to a dynamical system, combining a Galerkin method with N$N$ functions and a quadrature method with M$M$ quadrature nodes.
Elliz Akindji   +3 more
wiley   +1 more source

A General Approach to Dropout in Quantum Neural Networks

open access: yesAdvanced Quantum Technologies, EarlyView., 2023
Randomly dropping artificial neurons and all their connections in the training phase reduces overfitting issues in classical neural networks, thus improving performances on previously unseen data. The authors introduce different dropout strategies applied to quantum neural networks, learning models based on parametrized quantum circuits.
Francesco Scala   +3 more
wiley   +1 more source

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