Impact of Lévy Noise with Infinite Activity on the Dynamics of Measles Epidemics

This research article investigates the application of Lévy noise to understand the dynamic aspects of measles epidemic modeling and seeks to explain the impact of vaccines on the spread of the disease. After model formulation, the study utilises uniqueness and existence techniques to derive a positive solution to the underlying stochastic model. The Lyapunov function is used to investigate the stability results associated with the proposed stochastic model. The model’s dynamic characteristics are analyzed in the vicinity of the infection-free and endemic states of the associated ODEs model. The stochastic threshold Rs that ensures disease’s extinction whenever Rs1 is calculated. We utilized data from Pakistan in 2019 to estimate the parameters of the model and conducted simulations to forecast the future behavior of the disease. The results were compared to actual data using standard curve fitting tools

Impact of information intervention on stochastic dengue epidemic model

The investigated manuscript is devoted to the study of the dengue epidemic model. Generally, the infection of dengue occurs in extremely hot and humid conditions where the transmission and control depend on many factors like information intervention, humid weather, etc. With the help of the deterministic dengue model, we have taken the stochastic perturbed dengue model along with the factor of information intervention. The qualitative analysis for the positive solution of the stochastic differential equation based model is built. The scheme for basic reproduction number introduced for sure exponential stability by constructing the Lyapunov function. For the validity of our obtained results, we have simulated the proposed scheme and compare the stochastic model with its corresponding deterministic version

A Novel Stochastic Model for Human Norovirus Dynamics: Vaccination Impact with Lévy Noise

The epidemic norovirus causes vomiting and diarrhea and is a highly contagious infection. The disease is affecting human lives in terms of deaths and medical expenses. This study examines the governing dynamics of norovirus by incorporating Lévy noise into a stochastic SIRWF (susceptible, infected, recovered, water contamination, and food contamination) model. The existence of a non-negative solution and its uniqueness are proved after model formulation. Subsequently, the threshold parameter is calculated, and this number is used to explore the conditions under which disease tends to exist in the population. Likewise, additional conditions are derived that ensure the elimination of the disease from the community. It is proved that the norovirus is extinct whenever the threshold parameter is less than one and it persists for Rs>1. The work assumes two working examples to numerically explain the theoretical findings. Simulations of the study are visually presented, and comparisons are made. The results of this study suggest a robust approach for handling complex biological and epidemic phenomena

Numerical dynamics and fractional modeling of hepatitis B virus model with non-singular and non-local kernels

A fractional model for the transmission dynamics of Hepatitis B was designed. Hepatitis B disease has a great impact on global human health conditions and economical systems. The spreading of HBV disease has several phases, i.e., acute and chronicle carriers phases have a key role. The chronicle carrier’s cases do not have any signs and are capable of transmitting the Hepatitis B infection. In this article, we investigated the transmission due to different infection phases of the Hepatitis B virus and constructed a nonlinear epidemic. Next, a fractional hepatitis B virus model with Atangana–Baleanu derivative (AB derivative) is formulated with vaccine effects. Firstly, we calculated the basic reproductive value and equilibria of the proposed model. Qualitative analysis of the approximate root of the said problem has been derived with the help of Fixed Point Theory. The Iterative approximate technique with the help of the Adams–Bashforth predictor–corrector scheme for evaluating the considered fractional system having the ABC derivative is expressed. In the last, a graphical representation is established to show the obtained scheme findings and compare different non-integer orders of Ψ

Special Issue: Advanced Science and Technology of Polymer Matrix Nanomaterials

Nanotechnology has witnessed an incredible resonance and a substantial number of new applications in various areas during the past three decades [...

Calculation of Free Energy Consumption in Gene Transcription with Complex Promoter Structure

From the viewpoint of thermodynamics, gene transcription necessarily consumes free energy due to nonequilibrium processes. On the other hand, regulatory molecules present on the core promoter of a gene interact often in a dynamic, highly combinatorial, and possibly energy-dependent manner, leading to a complex promoter structure. This raises the question of how gene transcription with general promoter topology consumes free energy. We propose a biophysically intuitive approach to calculate energy consumption (quantified by the production rate of entropy) of a gene transcription process. Then, we show that the numbers of the ON and OFF states of a promoter can reduce energy consumption of the gene system and the Fano factor of mRNA, and in contrast to other regulatory ways, the cooperative binding of transcription factors to DNA sites always reduces energy consumption but amplifies the mRNA noise. While our proposed approach is general, our obtained qualitative results can in turn be used to the inference of complex promoter structure

Stochastic optimal control analysis for the hepatitis B epidemic model

Mathematical formulation of a stochastic hepatitis B virus (HBV) model with the application of optimal control and randomly noise transmission has been focused in this paper. For the ease of understanding, the model is divided into four different classes of healthy or susceptible, acute infected, chronically infected and the class of the recovered population. All four cases have been perturbed by the white noise. By applying optimal control techniques, we investigated both deterministic and stochastic model for control. The approximate solution method of the deterministic model has been used in the numerical solution of the required stochastic model. The simulation of both models has been drawn against the given data and compared with each other

Fabrication and Investigation of PE-SiO2@PZS Composite Separator for Lithium-Ion Batteries

Commercial polyolefin separators exhibit problems including shrinkage under high temperatures and poor electrolyte wettability and uptake, resulting in low ionic conductivity and safety problems. In this work, core–shell silica-polyphosphazene nanoparticles (SiO2@PZS) with different PZS layer thicknesses were synthesized and coated onto both sides of polyethylene (PE) microporous membranes to prepare composite membranes. Compared to pure silica-coated membranes and PE membranes, the PE-SiO2@PZS composite membrane had higher ionic conductivity. With the increase in the SiO2@PZS shell thickness, the electrolyte uptake, ionic conductivity and discharge capacity gradually increased. The discharge capacity of the PE-SiO2@PZS composite membrane at 8 C rate was 129 mAh/g, which was higher than the values of 107 mAh/g for the PE-SiO2 composite membrane and 104 mAh/g for the PE membrane

Learning the Spherical Harmonic Features for 3-D Face Recognition

International audienceIn this paper, a competitive method for 3D face recognition (FR) using Spherical Harmonic Features (SHF) is proposed. With this solution 3D face models are characterized by the energies contained in spherical harmonics with different frequencies, thereby enabling the capture of both gross shape and fine surface details of a 3D facial surface. This is in clear contrast to most 3D FR techniques which are either holistic or feature-based using local features extracted from distinctive points. First, 3D face models are represented in a canonical representation, namely Spherical Depth Map (SDM), by which SHF can be calculated. Then, considering the predictive contribution of each SHF feature, especially in the presence of facial expression and occlusion, feature selection methods are used to improve the predictive performance and provide faster and more cost-effective predictors. Experiments have been carried out on three public 3D face datasets, namely SHREC2007, FRGC v2.0 and Bosphorus, having increasing difficulties in terms of facial expression, pose and occlusion, and which demonstrate the effectiveness of the proposed method