Callibration in mathematical models that are based on differential equations is known to be of fundamental importance. For sophisticated models such as age-structured models that simulate biological agents, parameter estimation or fitting (callibration) that solves all cases of data points available presents a formidable challenge, as efficiency considerations need to be employed in order for the method to become practical. In the case of multiscale models of hepatitis C virus dynamics that deal with partial differential equations (PDEs), a fully numerical parameter estimation method was developed that does not require an analytical approximation of the solution to the multiscale model equations, avoiding the necessity to derive the long-term approximation for each model. However, the method is considerably slow because of precision problems in estimating derivatives with respect to the parameters near their boundary values, making it almost impractical for general use. In order to overcome this limitation, two steps have been taken that significantly reduce the running time by orders of magnitude and thereby lead to a practical method. First, constrained optimization is used, letting the user add constraints relating to the boundary values of each parameter before the method is executed. Second, optimization is performed by derivative-free methods, eliminating the need to evaluate expensive numerical derviative approximations. These steps that were successful in significantly speeding up a highly non-efficient approach, rendering it practical, can also be adapted to multiscale models of other viruses and other sophisticated differential equation models. The newly efficient methods that were developed as a result of the above approach are described. Illustrations are provided using a user-friendly simulator that incorporates the efficient methods for multiscale models. We provide a simulator called HCVMultiscaleFit with a Graphical User Interface that applies these methods and is useful to perform parameter estimation for simulating viral dynamics during antiviral treatment.
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http://dx.doi.org/10.1063/5.0026600 | DOI Listing |
Sci Rep
December 2024
School of Mechanical Engineering, Liaoning Engineering Vocational College, Tieling, 112008, Liaoning, People's Republic of China.
The paper proposes a multi-rigid-body system state identification method based on self-healing model in order to improve the accuracy and reliability of CNC machine tools. Firstly, considering the influence of the joint surface, the Lagrange method is used to establish the mechanical model of the multi-rigid-body system. We input acceleration information and use the second-order modulation function to complete the online real-time identification of the joint surface parameters, thereby establishing the self-healing mechanical model of the multi-rigid-body system.
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December 2024
Department of Pharmaceutics, College of Pharmacy, University of Ha'il, Ha'il, 81442, Saudi Arabia.
This research article presents a thorough and all-encompassing examination of predictive models utilized in the estimation of viscosity for ionic liquid solutions. The study focuses on crucial input parameters, namely the type of cation, the type of anion, the temperature (measured in Kelvin), and the concentration of the ionic liquid (expressed in mol%). This study assesses three influential machine learning algorithms that are based on the Decision Tree methodology.
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December 2024
School of Population Health, Faculty of Health Sciences, Curtin University, Bentley, WA, Australia.
While bacille-calmette-guerin (BCG) vaccination is one of the recommended strategies for preventing tuberculosis (TB), its coverage is low in several countries, including Ethiopia. This study investigated the spatial co-distribution and drivers of TB prevalence and low BCG coverage in Ethiopia. This ecological study was conducted using data from a national TB prevalence survey and the Ethiopian demographic and health survey (EDHS) to map the spatial co-distribution of BCG vaccination coverage and TB prevalence.
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December 2024
Department of Mathematics, Texas A&M University, College Station, TX, 77843, USA.
The northern Gulf of Mexico (nGoM) receives water from over 50 rivers which are highly influenced by humans and include the largest river in the United States, the Mississippi River. To support large-scale data-driven research centered on the dynamic river-ocean system in the region, this study consolidated hydrogeochemical river and ocean data from across the nGoM. In particular, we harmonized 35 chemical solute parameters from 54 rivers and incorporated river discharge data to derive daily solute concentration and flux estimates throughout the nGoM.
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December 2024
Condensed Matter Theory Group, School of Studies in Physics, Jiwaji University, Gwalior, 474 011, India.
This study presents a comprehensive investigation into the intrinsic properties of RNiP (where R = Sm, Eu) filled skutterudite, employing the full-potential linearized augmented plane wave method within density functional theory (DFT) simulations using the WIEN2k framework. Structural, phonon stability, mechanical, electronic, magnetic, transport, thermal, and optical properties are thoroughly explored to provide a holistic understanding of these materials. Initially, the structural stability of SmNiP and EuNiP is rigorously evaluated through ground-state energy calculations obtained from structural optimizations, revealing a preference for a stable ferromagnetic phase over competing antiferromagnetic and non-magnetic phases.
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