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There has been a recent surge of interest in theory and methods for calculating the entropy of landscape patterns, but relatively little is known about the thermodynamic consistency of these approaches. I posit that for any of these methods to be fully thermodynamically consistent, they must meet three conditions. First, the computed entropies must lie along the theoretical distribution of entropies as a function of total edge length, which Cushman showed was a parabolic function following from the fact that there is a normal distribution of permuted edge lengths, the entropy is the logarithm of the number of microstates in a macrostate, and the logarithm of a normal distribution is a parabolic function. Second, the entropy must increase over time through the period of the random mixing simulation, following the expectation that entropy increases in a closed system. Third, at full mixing, the entropy will fluctuate randomly around the maximum theoretical value, associated with a perfectly random arrangement of the lattice. I evaluated these criteria in a test condition involving a binary, two-class landscape using the Cushman method of directly applying the Boltzmann relation (s = klogW) to permuted landscape configurations and measuring the distribution of total edge length. The results show that the Cushman method directly applying the classical Boltzmann relation is fully consistent with these criteria and therefore fully thermodynamically consistent. I suggest that this method, which is a direct application of the classical and iconic formulation of Boltzmann, has advantages given its direct interpretability, theoretical elegance, and thermodynamic consistency.
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http://dx.doi.org/10.3390/e23111420 | DOI Listing |
Environ Monit Assess
September 2025
Indira Gandhi Conservation Monitoring Centre, World Wide Fund-India, New Delhi, 110003, India.
Understanding the intricate relationship between land use/land cover (LULC) transformations and land surface temperature (LST) is critical for sustainable urban planning. This study investigates the spatiotemporal dynamics of LULC and LST across Delhi, India, using thermal data from Landsat 7 (2001), Landsat 5 (2011) and Landsat 8 (2021) resampled to 30-m spatial resolution, during the peak summer month of May. The study aims to target three significant aspects: (i) to analyse and present LULC-LST dynamics across Delhi, (ii) to evaluate the implications of LST effects at the district level and (iii) to predict seasonal LST trends in 2041 for North Delhi district using the seasonal auto-regressive integrated moving average (SARIMA) time series model.
View Article and Find Full Text PDFFood Res Int
November 2025
College of Biomass Science and Engineering, Sichuan University, Chengdu 610065, China. Electronic address:
High-temperature Daqu (HTD), an essential fermentation starter in sauce-aroma Baijiu, is characterized by complex microbial communities that vary significantly across production regions. Traditional HTD production faces challenges in consistency and quality control, hindering industrial scalability. This study compared 54 synthetic microbial communities (SynMC)-fortified HTD samples with 39 traditional HTD samples from core production regions, which are Renhuai, Luzhou, and Jinsha, respectively, to elucidate their microbial and metabolic profiles.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Geballe Laboratory for Advanced Materials, Stanford University, Stanford, CA 94305.
The iron-based high-[Formula: see text] superconductors (SCs) exhibit rich phase diagrams with intertwined phases, including magnetism, nematicity, and superconductivity. The superconducting [Formula: see text] in many of these materials is maximized in the regime of strong nematic fluctuations, making the role of nematicity in influencing the superconductivity a topic of intense research. Here, we use the AC elastocaloric effect (ECE) to map out the phase diagram of Ba(FeCo)As near optimal doping.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Chinese Academy of Sciences Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China.
Vegetation phenology, i.e., seasonal biological events such as leaf-out and leaf-fall, regulates local climate through biophysical processes like evapotranspiration (ET) and albedo.
View Article and Find Full Text PDFJ Chem Phys
September 2025
Department of Chemistry, Chicago Center for Theoretical Chemistry, Institute for Biophysical Dynamics, and James Franck Institute, The University of Chicago, 5735 S. Ellis Ave., SCL 123, Chicago, Illinois 60637, USA.
Molecular dynamics simulations are essential for studying complex molecular systems, but their high computational cost limits scalability. Coarse-grained (CG) models reduce this cost by simplifying the system, yet traditional approaches often fail to maintain dynamic consistency, compromising their reliability in kinetics-driven processes. Here, we introduce an adversarial training framework that aligns CG trajectory ensembles with all-atom (AA) reference dynamics, ensuring both thermodynamic and kinetic fidelity.
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