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Endoreversible engine cycles are a cornerstone of finite-time thermodynamics. We show that endoreversible Stirling engines operating with a one-component plasma as a working medium run at maximal power output with the Curzon-Ahlborn efficiency. As a main result, we elucidate that this is actually a consequence of the fact that the caloric equation of state depends only linearly on temperature and only additively on volume. In particular, neither the exact form of the mechanical equation of state nor the full fundamental relation are required. Thus, our findings immediately generalize to a larger class of working plasmas, far beyond simple ideal gases. In addition, we show that for plasmas described by the photonic equation of state, the efficiency is significantly lower. This is in stark contrast to endoreversible Otto cycles, for which photonic engines have an efficiency larger than the Curzon-Ahlborn efficiency.
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http://dx.doi.org/10.3390/e27080807 | DOI Listing |
Sud Med Ekspert
January 2025
Samara State Medical University, Samara, Russia.
Objective: To develop and implement a method for determining the postmortem interval and the marginal errors of its estimates under conditions of linearly varying external temperature in the format of an online application.
Material And Methods: A computer-assissted numerical search for the absolute minimum point of the objective function obtained from a system of nonlinear equations reflecting the results of double rectal or cranioencephalic thermometry of a corpse under conditions of linearly varying external temperature was carried out. The search algorithm was generalized to possible marginal errors in measuring the initial indicators of temperature and time.
Bull Math Biol
September 2025
Department of Mathematics, Siena University, 515 Loudon Road, Loudonville, NY, 12211, USA.
Autonomous differential equation compartmental models hold broad utility in epidemiology and public health. However, these models typically cannot account explicitly for myriad factors that affect the trajectory of infectious diseases, with seasonal variations in host behavior and environmental conditions as noteworthy examples. Fortunately, using non-autonomous differential equation compartmental models can mitigate some of these deficiencies, as the inclusion of time-varying parameters can account for temporally varying factors.
View Article and Find Full Text PDFChaos
September 2025
The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, School of Internet, Anhui University, Hefei 230601, China.
A captivating challenge in network research is the reconstruction of complex network structures from limited binary-state time series data. Although some reconstruction approaches based on dynamical rules or sparse system of linear equations have been proposed, these approaches either rely on known dynamical rules, limiting their generality, or the system of linear equations is often empirically determined, with weak interpretability and the performance being sensitive to parameter settings. To address these limitations, we propose a network reconstruction method based on linearization grounded in mean-field approximation.
View Article and Find Full Text PDFJ Infect Dis
September 2025
Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
Introduction: Where surveillance data are limited, nationally-representative electronic health records allow for geographic, temporal, and demographic characterization of the fungal diseases blastomycosis and histoplasmosis.
Methods: We identified incident blastomycosis and histoplasmosis cases from 2013 to 2023 within Oracle EHR Real-World Data, which comprises 1.6 billion healthcare encounters nationally.
ACS Electrochem
September 2025
Liquid Sunlight Alliance, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States.
Reaction rate coefficients for electron-transfer processes at the electrode-electrolyte interface are commonly estimated by using the Butler-Volmer equation, but their values are inaccurate beyond a few tenths of volts of overpotential. The Marcus-Hush-Chidsey (MHC) formalism yields correct asymptotic behavior of the rate coefficients vs applied overpotential but has complex dependencies on the redox system's intrinsic parameters, which can be difficult to model or measure. In this work, we bridge the two kinetics formalisms to estimate the reorganization energy, one of the important parameters for the MHC formalism, and investigate its dependence on other intrinsic parameters such as activation barriers, electronic coupling strength, and the density of states of the electrode surface.
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