Results 41 to 50 of about 527 (171)
The Hydrogenation of MNi3 Compounds (M = Si, Ge, Sn, Sb, Zr, V, Fe)
Hexagonal Ni3Sn takes up hydrogen to form α‐Ni3SnHx (filled Ni3Sn type, ΔV = 0.9%), followed by a transition to the cubic β‐Ni3SnHy (filled AuCu3 type, ΔV = 1.1% with respect to pristine Ni3Sn), while MNi3 (M = Zr, Si, Sb) compounds show no reaction toward hydrogen and MNi3 (M = V, Fe, Ge) compounds only a minute hydrogen uptake.
André Götze +6 more
wiley +1 more source
Characterization of the generalized Chebyshev-type polynomials of first kind
Orthogonal polynomials have very useful properties in mathematical problems, and in recent years there has been significant development in the field of approximation theory using orthogonal polynomials. In this paper, we characterize a sequence of generalized Chebyshev-type polynomials of the first kind {Tn(M,N)(x)}n∈N∪{0}\{T_n^{(M,N)}(x)\}_{n \in ...
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The Chebyshev Polynomials Of The First Kind For Analysis Rates Shares Of Enterprises
Chebyshev polynomials of the first kind have long been used to approximate experimental data in solving various technical problems. Within the framework of this study, the dynamics of shares of eight Czech enterprises was analyzed by the Chebyshev polynomial decomposition: CEZ A.S. (CEZP), Colt CZ Group SE (CZG), Erste Bank (ERST), Komercni Banka (BKOM)
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A highly accurate numerical method is given for the solution of boundary value problem of generalized Bagley‐Torvik (BgT) equation with Caputo derivative of order 0<β<2$$ 0<\beta <2 $$ by using the collocation‐shooting method (C‐SM). The collocation solution is constructed in the space Sm+1(1)$$ {S}_{m+1}^{(1)} $$ as piecewise polynomials of degree at ...
Suzan Cival Buranay +2 more
wiley +1 more source
ABSTRACT This study examines the combined impact of different thermal conductivity and viscosity on unsteady non‐Newtonian Casson fluid flow of incompressible, electrical conductivity in a porous vertical channel with convective cooling walls, uniform magnetic field, and constant pressure gradient.
A. S. Adeyemo +2 more
wiley +1 more source
The generalized time fractional Kolmogorov-Petrovsky-Piskunov equation (FKPP), D t α ω ( x , t ) = a ( x , t ) D x x ω ( x , t ) + F ( ω ( x , t ) ) , which plays an important role in engineering ...
Thanon Korkiatsakul +2 more
doaj +1 more source
ABSTRACT Purpose To improve the accuracy of diffusion‐weighted powder average signals for diffusion encoding with arbitrary b‐tensors. Methods We identify an intrinsic dihedral (D2$$ {D}_2 $$) symmetry of diffusion signals for arbitrary diffusion encoding, which defines their natural signal space (a quotient of 3D rotations).
Sune Nørhøj Jespersen +1 more
wiley +1 more source
Representation by several orthogonal polynomials for sums of finite products of Chebyshev polynomials of the first, third and fourth kinds [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Taekyun Kim +3 more
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A comparative large‐amplitude oscillatory shear analysis reveals how cationic surfactants progressively weaken xanthan gum networks. While conventional rheology identifies network softening, advanced LAOS methods uncover nonlinear deformation mechanisms and transient structural evolution that remain hidden in cycle‐averaged measurements.
Osita Sunday Nnyigide +2 more
wiley +1 more source
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma +4 more
wiley +1 more source

