We investigate η-Ricci-Bourguignon solitons on hyperbolic spaces Hn, with a focus on the Poincaré half-plane H2. Building upon recent advances on classical Ricci-Bourguignon solitons in this geometric setting, we establish necessary and sufficient conditions for the existence of such structures and analyze the properties of the underlying potential vector fields. The results obtained on H2 are subsequently extended to higher-dimensional hyperbolic spaces.
In this study, we introduce generalized osculating-type curves with Frenet-type frame in Myller configuration for Euclidean 4-space E4. This study especially improves the theory of curves with respect to the osculating-type curves and gives the relationships between the special cases and general form related to the osculating-type curves. We examine some characterizations of the first kind and second kind osculating-type curves. Then, we obtain some correlations between curvatures and invariants of the generalized osculating-type curves, as well. The osculating curves with Frenet frame in E4 are one of the natural special cases for the generalized osculating-type curves with Myller configuration in E4 since the geometry of versor fields along a curve with Myller configuration in E4 is a generalization of the usual theory of curves in E4. Also, we give some new theorems that are not valid for osculating curves with Frenet frame in E4. Then, we give a numerical example with respect to the studied concept.
Multistable behavior typically refers to a system that has multiple stable states. To achieve multistability using speed feedback controller, we consider two different Lorenz and Rossler chaotic systems respectively and also find extreme multistability by considering identical coupled chaotic Chen system with mismatch parameters. Numerical simulation outcomes are explained to exhibit the functional capability of the recommended framework to create highly stable multi-state synchronization performance. This work displays a theoretical base for building utmost multistable system for continuous system.
In this brief report we have presented two logical approaches to the work of Bhardwaj et al. [1]) having an issue of non-retrieval of GR from the f(Q) gravity theory. Basically, we have dealt with two distinct schemes to resolve the issue via the following two approaches: (i) when the f(Q) gravity follows the functional relation f(Q) = -Q, and (ii) when one considers the late lime acceleration of the universe. It has been shown that under any one of the logical approaches one can resolve the issue of the coupling parameter (or constant) which was apparently not always getting null or vanishing.
Travel time estimation is a challenging task due to the lots of influential factors. The most preexisting travel time literature assumes travel time follows a specified distribution. Their goal is to find the best fit distribution of travel time based on the observed travel times. Obviously, the role of some influential factors such as intersection signal times, demand variations, supply variations (changing network topology) etc., are neglected. In this paper, the uncertainty of time and its variations which are consequences of numerous stochastic elements such as uncertain travel demand, uncertain driver behaviors, and random arrival time is modelled by calculating the probability density function of travel time on each arterial link. Also, the concept of queuing theory is used to take the stochastic features and queue formation behind intersection signals into account; Additionally, unlike previous model-based methods, the queue of vehicles is modeled as a horizontal queue, and its effects on the travel time are accurately calculated. Also this method is particularly useful in scenarios where, due to changes in the network, the previous data may not be highly reliable or in special situations which there is only an estimate of supply and demand such time Travel time Distribution as, the closure of a street or changes in traffic signal timing or large sporting events or emergency situations etc. Eventually, the proposed model is validated and examined by comparison with micro-simulation experiments.
