AI Article Synopsis

  • The text discusses the global impact of diseases, particularly focusing on COVID-19 and its connection to tobacco-related illnesses, which weaken the immune system.
  • The research introduces the q-homotopy analysis transform method in conjunction with the Atangana-Baleanu-Caputo fractional operator to model the effects of tobacco use on infection spread.
  • Graphical representations and data are used to demonstrate the solution and predict behaviors in this mathematical model, illustrating the feasibility of applying fractional derivatives to real-world scenarios.

Article Abstract

In recent years, the world has faced many destructive diseases that have taken many lives across the globe. To resist these diseases, humankind needs medicine to control, cure, and predict the behaviour of such problems. Recently, the Corona virus, which primarily affects the lungs, has threatened the globe. Similarly, tobacco-related illnesses impair the immune system, and this reduces the ability to fight against Covid-19. This tobacco-smoking version is vital for the researchers to reap the solution by using the q-homotopy analysis transform method with the useful resource of the Atangana-Baleanu-Caputo impression. Hence, the graphical illustrations have been discussed to achieve a solution for this mathematical model. This work applies the q-homotopy analysis transform method to the preeminent fractional operator Atangana-Baleanu-Caputo to better comprehend the infectious model of tobacco snuffing and smoking. Figures and tables are used to display the outcomes. The paper also aids in the analysis of the practical theory by predicting how it would behave when compared to the rules when considering the replica. It offers accurate grid point outcomes and fixes. The system's accuracy in the convergent zone is shown by the curves. The smoking model has been illustrated using graphical findings and fractional derivatives for easier comprehension. It's feasible that applications in the real world will make use of fractional derivatives.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10590928PMC
http://dx.doi.org/10.1016/j.heliyon.2023.e20792DOI Listing

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