Separability by two lines and by flat polygonals∗

Intrinsic Characterizations of Orthogonal Separability for Natural Hamiltonians with Scalar Potentials on Pseudo-Riemannian Spaces

Orthogonal separability of finite-dimensional Hamiltonians is characterized by using various geometrical concepts, including Killing tensors, moving frames, the Nijenhuis tensor, bi-Hamiltonian and quasi-bi-Hamiltonian representations. In addition, a complete classification of separable metrics defined in two-dimensional locally flat Lorenzian spaces is presented.

Evaluation of Tests for Separability and Symmetry of Spatio-temporal Covariance Function

In recent years, some investigations have been carried out to examine the assumptions like stationarity, symmetry and separability of spatio-temporal covariance function which would considerably simplify fitting a valid covariance model to the data by parametric and nonparametric methods. In this article, assuming a Gaussian random field, we consider the likelihood ratio separability test, a va...

Short communication-Cadmium determination in two flat fishes from two fishery regions in north of the Persian Gulf

Separability by two lines and by nearly straight polygonal chains

In this paper we study the separability in the plane by two criteria: double-wedge separability and Θ-separability. We give an O(N logN)-time optimal algorithm for computing all the vertices of separating double wedges of two disjoint sets of objects (points, segments, polygons and circles) and an O((N/Θ0) logN)-time algorithm for computing a nearly-straight minimal Θ-polygonal chain separating...

Circle of Willis in adults.

OBJECTIVE This study was carried out to describe the main variations of the Circle of Willis and to clarify the clinical importance of these variations, so that practitioners and the students are more alert when dealing with this subject. METHODS This work is based on the study of 50 Circles of Willis from adult Jordanians who died from diverse causes without signs of cerebrovascular diseases...