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Related Experiment Video

Updated: Jul 12, 2025

Using Nicotine in a Silica-Exposed Mouse Model to Promote Lung Epithelial-Mesenchymal Transition
06:12

Using Nicotine in a Silica-Exposed Mouse Model to Promote Lung Epithelial-Mesenchymal Transition

Published on: March 3, 2023

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Tobacco smoking model containing snuffing class.

Viswanathan Padmavathi1, Kandaswami Alagesan2, Samad Noeiaghdam3,4

  • 1Department of Mathematics, Thangavel Womens Arts and Science College, Salem - 636 106, Tamil Nadu, India.

Heliyon
|October 25, 2023
PubMed
Summary
This summary is machine-generated.

Researchers used the q-homotopy analysis transform method with the Atangana-Baleanu-Caputo fractional derivative to model tobacco smoking and its impact on infectious diseases. This approach provides accurate solutions and graphical insights for understanding disease dynamics.

Keywords:
34F0537M0592D30Atangana-Baleanu-Caputo (ABC) derivativeEpidemic modelMathematical modelsTobacco smoking modelq-Homotopy analysis transform method (q-HATM)

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Area of Science:

  • Mathematical modeling
  • Epidemiology
  • Fractional calculus

Background:

  • Destructive diseases pose global threats, necessitating effective medical interventions.
  • Tobacco-related illnesses compromise the immune system, increasing vulnerability to infections like COVID-19.

Purpose of the Study:

  • To apply the q-homotopy analysis transform method (q-HAT) with the Atangana-Baleanu-Caputo (ABC) fractional derivative to model tobacco smoking.
  • To analyze the infectious disease model considering the impact of tobacco use.
  • To provide accurate solutions and graphical representations for understanding disease dynamics.

Main Methods:

  • Utilizing the q-homotopy analysis transform method (q-HAT).
  • Employing the Atangana-Baleanu-Caputo (ABC) fractional derivative operator.
  • Generating graphical illustrations and tables to present results.

Main Results:

  • The study presents accurate grid point outcomes and fixes for the mathematical model.
  • Graphical illustrations demonstrate the system's accuracy within the convergent zone.
  • The fractional derivative approach aids in comprehending the infectious model of tobacco use.

Conclusions:

  • The q-HAT method combined with the ABC fractional derivative offers a robust framework for analyzing infectious disease models related to tobacco use.
  • The findings facilitate a better understanding of disease behavior and potential real-world applications of fractional derivatives in public health.
  • Graphical and numerical results validate the model's accuracy and predictive capabilities.