We give the exact critical frontier of the Potts model on bowtie lattices. For the case of q = 1, the critical frontier yields the thresholds of bond percolation on these lattices, which are exactly consistent with the results given by Ziff et al. [J. Phys. A 39, 15083 (2006)]. For the q = 2 Potts model on a bowtie A lattice, the critical point is in agreement with that of the Ising model on this lattice, which has been exactly solved. Furthermore, we do extensive Monte Carlo simulations of the Potts model on a bowtie A lattice with noninteger q. Our numerical results, which are accurate up to seven significant digits, are consistent with the theoretical predictions. We also simulate the site percolation on a bowtie A lattice, and the threshold is s(c) = 0.5479148(7). In the simulations of bond percolation and site percolation, we find that the shape-dependent properties of the percolation model on a bowtie A lattice are somewhat different from those of an isotropic lattice, which may be caused by the anisotropy of the lattice.
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http://dx.doi.org/10.1103/PhysRevE.86.021125 | DOI Listing |
Risk Manag Healthc Policy
December 2024
Belt and Road Initiative Center for Chinese-European Studies (BRICCES), Guangdong University of Petrochemical Technology, Maoming, People's Republic of China.
Introduction: Psychosocial risks (PSRs) are identified as one of the main modern occupational safety issues, primarily related to occupational stress, and need to be reduced to safe levels in accordance with international requirements. The research purpose is to improve the process of managing the PSRs in the occupational safety and health management systems of employees, taking into account the impact of psychosocial dangers in accordance with the requirements of ISO 45001:2018 and ISO 45003:2021 standards.
Methods: To develop the process of managing the PSRs, a system analysis method is applied, which allows determining the structural relationships between the variable elements of dangerous psychosocial factors described in the ISO 45003:2021 standard.
Qual Manag Health Care
October 2024
Author Affiliations: School of Management, Tianjin University of Technology, Tianjin, China (Dr Zhao); and College of Tourism and Service Management, Nankai University, Tianjin, China (Dr Liu).
Background And Objectives: Medical risks are considered to endanger patients and impact the health care system. Such iatrogenic risks necessitate hospitals taking a more proactive method to quantitatively analyze medical risk, and then to implement more targeted precautions. To address this problem, a novel quantitative risk assessment framework is proposed and further applied in radiotherapy risk assessment.
View Article and Find Full Text PDFPhys Med
November 2024
Department of Human Structure and Repair, Ghent University, Proeftuinstraat 86 - Building N7, 9000 Ghent, Belgium. Electronic address:
Purpose: For patient-specific CT dosimetry, Monte Carlo dose simulations require an accurate description of the CT scanner. However, quantitative spectral information and information on the bowtie filter material and shape from the manufacturer is often not available. In this study, the influence of different X-ray spectra and bowtie filter characterisation methods on simulated CT organ doses is studied.
View Article and Find Full Text PDFMar Pollut Bull
December 2024
Dokuz Eylul University, Maritime Faculty, Department of Marine Transportation Engineering, Tinaztepe Campus, Buca, Izmir 35390, Turkey. Electronic address:
Coal self-heating presents significant risks to maritime transportation, including spontaneous combustion, environmental damage, and economic losses. This study aims to apply a Fuzzy Bow-Tie analysis to assess and mitigate the risks associated with coal self-heating during transportation. By integrating expert judgments and addressing uncertainties in the data, the Fuzzy Bow-Tie model offers a comprehensive evaluation of risk factors and safety barriers.
View Article and Find Full Text PDFDis Colon Rectum
September 2024
Department of Gastroenterology, Shengjing Hospital of China Medical University, Shenyang, Liaoning Province, China.
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