This paper aims to generate a universal well-fitted mathematical model to aid global representation of the spread of the coronavirus (COVID-19) disease. The model aims to identify the importance of the measures to be taken in order to stop the spread of the virus. It describes the diffusion of the virus in normal life with and without precaution. It is a data-driven parametric dependent function, for which the parameters are extracted from the data and the exponential function derived using multiplicative calculus. The results of the proposed model are compared to real recorded data from different countries and the performance of this model is investigated using error analysis theory. We stress that all statistics, collected data, etc., included in this study were extracted from official website of the World Health Organization (WHO). Therefore, the obtained results demonstrate its applicability and efficiency.
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http://dx.doi.org/10.1007/s00500-022-06996-y | DOI Listing |
R Soc Open Sci
December 2024
Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-cho, Toyonaka, Osaka 560-8531, Japan.
The existence of stress singularities and reliance on linear approximations pose significant challenges in comprehending the stress field generation mechanism around dislocations. This study employs differential geometry and calculus of variations to mathematically model and numerically analyse screw dislocations. The kinematics of the dislocation are expressed by the diffeomorphism of the Riemann-Cartan manifold, which includes both the Riemannian metric and affine connection.
View Article and Find Full Text PDFSci Total Environ
January 2024
University of Florence, Dept. of Earth Sciences, Via G. La Pira 4, 50121 Firenze, Italy; NBFC, National Biodiversity Future Center, Palermo 90133, Italy; National Centre for HPC, Big Data and Quantum Computing, PNRR, Italy.
The chemical composition of river waters represents an important matter of investigation to understand environment modifications in response to climate changes and global warming. Prolonged dry periods, heavy flood events, degradation of the lands and ice thawing, modify the chemical composition of river waters influencing the drivers governing the complex dynamics of river catchments where everything comes together. In this framework, Compositional Data Analysis (CoDA) offers methods in which the complex structure of the river water composition and the interrelationships among the various components are put into the proper context for their statistical analysis.
View Article and Find Full Text PDFProbab Theory Relat Fields
May 2022
Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland.
We consider the imaginary Gaussian multiplicative chaos, i.e. the complex Wick exponential for a log-correlated Gaussian field in dimensions.
View Article and Find Full Text PDFAm J Prev Med
July 2022
Department of Pediatrics, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama.
Introduction: Obesity is associated with kidney stone disease, but it is unknown whether this association differs by SES. This study assessed the extent to which obesity and neighborhood characteristics jointly contribute to urinary risk factors for kidney stone disease.
Methods: This was a retrospective analysis of adult patients with kidney stone disease evaluated with 24-hour urine collection (2001-2020).
Soft comput
April 2022
Department of Mathematics, Mersin University, Mersin, Turkey.
This paper aims to generate a universal well-fitted mathematical model to aid global representation of the spread of the coronavirus (COVID-19) disease. The model aims to identify the importance of the measures to be taken in order to stop the spread of the virus. It describes the diffusion of the virus in normal life with and without precaution.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!