Introduction: Dengue and Malaria are the most important mosquito-borne viral diseases affecting humans. Fever is transmitted between human hosts by infected female aedes mosquitoes. The modeling study of viral infections is very useful to show how the virus replicates in an infected individual and how the human antibody response acts to control that replication, which antibody playing a key role in controlling infection.
Objectives: Optimal control of a novel variable-order nonlinear model of dengue virus is studied in the present work. Bang-bang control is suggested to minimize the viral infection as well as quick clearance of the virus from the host. Necessary conditions for the control problem are given. The variable-order derivatives are given in the sense of Caputo. Moreover, the parameters of the proposed model are dependent on the same variable-order fractional power. Two numerical schemes are constructed for solving the optimality systems. Comparative studies and numerical simulations are implemented. The variable-order fractional derivative can be describe the effects of long variable memory of time dependent systems than the integer order and fractional order derivatives.
Methods: Both the nonstandard generalized fourth order Runge-Kutta and the nonstandard generalized Euler methods are presented.
Results: We have successfully applied a kind of Pontryagin's maximum principle with bang-bang control and were able to reduce the viraemia level by adding the dose of DI particles. The nonstandard generalized fourth order Runge-Kutta method has the best results than nonstandard generalized Euler method.
Conclusion: The combination of the variable-order fractional derivative and bang-bang control in the Dengue mathematical model improves the dynamics of the model. The nonstandard generalized Euler method and the nonstandard generalized fourth order Runge-Kutta method can be used to study the variable order fractional optimal control problem simply.
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http://dx.doi.org/10.1016/j.jare.2021.03.010 | DOI Listing |
PLoS One
January 2025
Biology Department, Faculty of Science, Islamic University of Madinah, Madinah, Saudi Arabia.
This study presents a novel approach to modeling breast cancer dynamics, one of the most significant health threats to women worldwide. Utilizing a piecewise mathematical framework, we incorporate both deterministic and stochastic elements of cancer progression. The model is divided into three distinct phases: (1) initial growth, characterized by a constant-order Caputo proportional operator (CPC), (2) intermediate growth, modeled by a variable-order CPC, and (3) advanced stages, capturing stochastic fluctuations in cancer cell populations using a stochastic operator.
View Article and Find Full Text PDFMethodsX
June 2025
Department of Statistics, Institut Teknologi Sepuluh Nopember, Surabaya 60111 Indonesia.
This research introduces the Generalized Extreme Value Mixture Autoregressive (GEVMAR) model as an innovative approach for examining non-standard actuarial datasets within general insurance. Information concerning claim reserves often reveals notable volatility and multimodal distributions, attributes that standard models, including previous method such as the Gaussian Mixture Autoregressive (GMAR) model and other autoregressive methodologies, find problematic to manage effectively. The GEVMAR model integrates the Generalized Extreme Value (GEV) distribution alongside Bayesian estimation techniques, augmented by a modified Signal-to-Noise Ratio (SNR) metric to improve predictive accuracy.
View Article and Find Full Text PDFBMC Cancer
January 2025
Department of Tumor Biology and Genetics, Medical University of Warsaw, Warsaw, Poland.
Aim: The study was designed to evaluate molecular alterations, relevant to the prognosis and personalized therapy of salivary gland cancers (SGCs).
Materials And Methods: DNA was extracted from archival tissue of 40 patients with various SGCs subtypes. A targeted next-generation sequencing (NGS) panel was used for the identification of small-scale mutations, focal and chromosomal arm-level copy number changes.
Biochemistry
January 2025
Department of Pharmaceutical Sciences, University of Shizuoka, Shizuoka 422-8526, Japan.
DtpC was isolated from the ditryptophenaline biosynthetic pathway found in filamentous fungi as a cytochrome P450 (P450) that catalyzes the dimerization of diketopiperazines. More recently, several similar P450s were discovered. While a vast majority of such P450s generate asymmetric diketopiperazine dimers, DtpC and other fungal P450s predominantly catalyze the formation of symmetric dimer products.
View Article and Find Full Text PDFmBio
December 2024
Shanghai Veterinary Research Institute, Chinese Academy of Agricultural Sciences, Shanghai, China.
Unlabelled: Recombination is a significant factor driving the evolution of RNA viruses. The prevalence and variation of porcine reproductive and respiratory syndrome virus (PRRSV) in China have been increasing in complexity due to extensive interlineage recombination. When this recombination phenomenon occurs in live vaccine strains, it becomes increasingly difficult to prevent and control PRRSV.
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