The effect of a sharp low-level temperature inversion on flow over a mountain is investigated via a series of two-dimensional idealized numerical model simulations. The main focus of the study is the effect of the inversion on the formation of lee waves, lee-wave rotors, low-level hydraulic jumps and the occurrence of wave breaking aloft. The idealized problem considered consists of an upwind v...

In the title complex, {[Co(C(6)H(8)N(2)O(2))(C(9)H(7)NO(2))(H(2)O)(2)](ClO(4))(2)}(n), the Co(II) ion lies on an inversion centre and is coordinated in a slightly distorted octa-hedral environment. The 2,5-dimethyl-pyrazine 1,4-dioxide ligand, which also lies on an inversion center, acts as a bridging ligand, linking symmetry-related Co(II) ions [Co⋯Co = 8.669 (3) Å] and forming one-dimensional...

This paper deals with certain estimation problems involving the covariance matrix in large dimensions. Due to the breakdown of finite-dimensional asymptotic theory when the dimension is not negligible with respect to the sample size, it is necessary to resort to an alternative framework known as large-dimensional asymptotics. Recently, Ledoit and Wolf (2015) have proposed an estimator of the ei...

Recently, solutions to inverse problems have been required in various engineering fields. The neural network inversion method has been studied as one of the neural network-based solutions. On the other hand, the extension of the neural network to a higher-dimensional domain, e.g., complex-value or quaternion, has been proposed, and a number of higher-dimensional neural network models have been ...

In the crystal structure of the title compound, C5H6ClN3, mol-ecules are linked by pairs of N-H⋯N hydrogen bonds, forming inversion dimers. These dimers are linked via N-H⋯N hydrogen bonds, forming a two-dimensional network lying parallel to (100). Inversion-related mol-ecules are also linked via a slipped π-π inter-action, with a centroid-centroid distance of 3.5259 (11) Å, a normal separation...

Porosity is one of the key parameters associated with oil reservoirs. Determination of this petrophysical parameter is an essential step in reservoir characterization. Among different linear and nonlinear prediction tools such as multi-regression and polynomial curve fitting, artificial neural network has gained the attention of researchers over the past years. In the present study, two-dimensi...

where the weights k and nodes k are complex numbers, which depend on n, but do not depend on the transform f̂ or the time argument t. Many different algorithms can be put into this framework, because it remains to specify the weights and nodes. We examine three one-dimensional inversion routines in this framework: the Gaver-Stehfest algorithm, a version of the Fourier-series method with Euler su...