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It is known that the iterative roots of continuous functions are not necessarily unique, if it exist. In this note, by introducing the set of points of coincidence, we study the iterative roots of order preserving homeomorphisms. In particular, we prove a characterization of identical iterative roots of an order preserving homeomorphism using the points of coincidence of functions.

The purpose of this paper is to develop a methodology for the existence and global exponential stability of the unique equilibrium point of a class of impulsive Cohen‐Grossberg neural networks.

The authors perform M‐matrix theory and homeomorphism mapping principle to investigate a class of impulsive Cohen‐Grossberg networks with time‐varying delays and distributed delays. The approach builds on new sufficient criterion without strict conditions imposed on self‐regulation functions.

The authors' approach results in new sufficient criteria easy to verify but without the usual assumption that the activation functions are bounded and the time‐varying delays are differentiable. An example shows the effectiveness and superiority of the obtained results over some previously known results.

The novelty of the proposed approach lies in removing the usual assumption that the activation functions are bounded and the time‐varying delays are differentiable, and the use of M‐matrix theory and homeomorphism mapping principle for the existence and global exponential stability of the unique equilibrium point of a class of impulsive Cohen‐Grossberg neural networks.

An abstract lattice of empty set cells is shown to be able to account for a primary substrate in a physical space. Space‐time is represented by ordered sequences of topologically closed Poincaré sections of this primary space. These mappings are constrained to provide homeomorphic structures serving as frames of reference in order to account for the successive positions of any objects present in the system. Mappings from one section to the next involve morphisms of the general structures, representing a continuous reference frame, and morphisms of objects present in the various parts of this structure. The combination of these morphisms provides space‐time with the features of a non‐linear generalized convolution. Discrete properties of the lattice allow the prediction of scales at which microscopic to cosmic structures should occur. Deformations of primary cells by exchange of empty set cells allow a cell to be mapped into an image cell in the next section as far as the mapped cells remain homeomorphic. However, if a deformation involves a fractal transformation to objects, there occurs a change in the dimension of the cell and the homeomorphism is not conserved. Then, the fractal kernel stands for a “particle” and the reduction of its volume (together with an increase in its area up to infinity) is compensated by morphic changes of a finite number of surrounding cells. Quanta of distances and quanta of fractality are demonstrated. The interactions of a moving particle‐like deformation with the surrounding lattice involves a fractal decomposition process, which supports the existence and properties of previously postulated inerton clouds as associated to particles. Experimental evidence of the existence of inertons is reviewed and further possibilities of experimental proofs proposed.

Some of the basic ideas of pursuit‐evasion games have been presented in an earlier paper. This paper is an extension and an elaboration of these ideas with emphasis on the determinability of pursuit‐evasion games.

Tolerance automata are defined and a decomposition theory for such entities is sought. It is shown that two major procedures of the classical algebraic theory produce difficulties in the tolerance case. A weaker approach, employing the idea of inertial tolerance, is presented. Finally, an explicit example is given which illustrates both the difficulties encountered and the theorems proved in the text.

Mesh Parameterization is central to reverse engineering, tool path planning, etc. This work synthesizes parameterizations with un-constrained borders, overall minimum angle plus area distortion. This study aims to present an assessment of the sensitivity of the minimized distortion with respect to weighed area and angle distortions.

A Mesh Parameterization which does not constrain borders is implemented by performing: isometry maps for each triangle to the plane Z = 0; an affine transform within the plane Z = 0 to glue the triangles back together; and a Levenberg–Marquardt minimization algorithm of a nonlinear F penalty function that modifies the parameters of the first two transformations to discourage triangle flips, angle or area distortions. F is a convex weighed combination of area distortion (weight: α with 0 ≤ α ≤ 1) and angle distortion (weight: 1 − α).

The present study parameterization algorithm has linear complexity [𝒪(n), n = number of mesh vertices]. The sensitivity analysis permits a fine-tuning of the weight parameter which achieves overall bijective parameterizations in the studied cases. No theoretical guarantee is given in this manuscript for the bijectivity. This algorithm has equal or superior performance compared with the ABF, LSCM and ARAP algorithms for the Ball, Cow and Gargoyle data sets. Additional correct results of this algorithm alone are presented for the Foot, Fandisk and Sliced-Glove data sets.

The devised free boundary nonlinear Mesh Parameterization method does not require a valid initial parameterization and produces locally bijective parameterizations in all of our tests. A formal sensitivity analysis shows that the resulting parameterization is more stable, i.e. the UV mapping changes very little when the algorithm tries to preserve angles than when it tries to preserve areas. The algorithm presented in this study belongs to the class that parameterizes meshes with holes. This study presents the results of a complexity analysis comparing the present study algorithm with 12 competing ones.

The rapprochement suggested by Arbib between continuity in control theory and tolerance in the theory of automata is discussed with reference to orbits, and in particular to the proof of Takens' version of Zeeman's tolerance stability conjecture. The corresponding result for tolerance automata is established.

The purpose of this paper is to study the dynamic behavior of complex-valued switched grey neural network models (SGNMs) with distributed delays when the system parameters and external input are grey numbers.

Firstly, by using the properties of grey matrix, M-matrix theory and Homeomorphic mapping, the existence and uniqueness of equilibrium point of the SGNMs were discussed. Secondly, by constructing a proper Lyapunov functional and using the average dwell time approach and inequality technique, the robust exponential stability of the SGNMs under restricted switching was studied. Finally, a numerical example is given to verify the effectiveness of the proposed results.

Sufficient conditions for the existence and uniqueness of equilibrium point of the SGNMs have been established; sufficient conditions for guaranteeing the robust stability of the SGNMs under restricted switching have been obtained.

(1) Different from asymptotic stability, the exponential stability of SGNMs which include grey parameters and distributed time delays will be investigated in this paper, and the exponential convergence rate of the SGNMs can also be obtained; (2) the activation functions, self-feedback coefficients and interconnected matrices are with different forms in different subnetworks; and (3) the results obtained by LMIs approach are complicated, while the proposed sufficient conditions are straightforward, which are conducive to practical applications.

This study aims to focus on electronic applications that have an effective role in raising the awareness of the dangers of viruses’ transmission from person-to-person and their positive and important impact on people’s lives.

The authors illustrated the effects of socializing with infected people on a human body by a model in geometry and how the prospected antibiotic annihilates the structure of the virus. The authors discussed vital operations inside the human body to expound the geometry of objects that are closed under their operations, such as viruses, especially Coronaviridae.

Also, the authors discussed some of the e-health applications in Jordan. As e-health activities, programs and applications have been given attention, the authors focused on potentials for constructing strategies that lead to create a featuring health technology.

Moreover, in this study, the authors explored the structure and geometry of Coronaviridae family, especially coronavirus that causes lots of diseases, and explained its movement mechanism using the mathematical structures.

The result of a true strategy applied by a (perfectly informed) player in positional games represents a sequence of consecutive choices from a given set. It is, therefore, subject to the axiom of choice or some equivalent selection principle. Our attention in this study is focused on the existence of finite sequences associated with winning strategies. It will be shown in the sequel that the use of the axiom of choice may lead to sets devoid of winning strategies, while the negation of this axiom produces winning strategies for both players. A modified axiom, the axiom of determination, is discussed which no longer admits such “paradoxes” in virtue of certain inherent restrictions.