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The logistic equation is ubiquitous in applied mathematics as a minimal model of saturating growth. Here, we examine a broad generalisation of the logistic growth model to discretely structured populations, motivated by examples that range from the ageing of individuals in a species to immune cell exhaustion by cancerous tissue. Through exploration of a range of concrete examples and a general analysis of polynomial kinetics, we derive necessary and sufficient conditions for the dependence of the kinetics on structure to result in closed, low-dimensional moment equations that are exact. Further, we showcase how coarse-grained moment information can be used to elucidate the details of structured dynamics, with immediate potential for model selection and hypothesis testing. This paper belongs to the special collection: Problems, Progress and Perspectives in Mathematical and Computational Biology.
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http://dx.doi.org/10.1007/s11538-025-01446-w | DOI Listing |
Phys Rev Lett
August 2025
California Institute of Technology, Division of Engineering and Applied Science, Pasadena, California 91125, USA.
Interlocked and polycatenated material systems, consisting of discrete, nonconvex particles linked to their nearest neighbors, such as chainmail fabrics, have been shown to undergo a jamming transition that increases their rigidity under boundary compression. This rigidity transition is associated with an increase in contact number between particles. In architected materials, rigidity is described by theories such as the Maxwell criterion.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
September 2025
Department of Zoology, Biodiversity Research Centre, University of British Columbia, Vancouver, BC V6T 1Z4.
The size and composition of local species pools are, in part, determined by past dispersal events. Predicting how communities respond to future disturbances, such as fluctuating environmental conditions, requires knowledge of such histories. We assessed the influence of a historical dispersal event on community assembly by simulating various scales of dispersal for 240 serpentine annual plant communities that experienced a large shift from drought to high rainfall conditions over three years.
View Article and Find Full Text PDFLangmuir
September 2025
Department of Mechanical and Industrial Engineering, Montana State University, Bozeman, Montana 59717, United States.
Global challenges posed by freshwater scarcity and the water-energy nexus drive demand for novel macromolecular design of tailored nanostructures endowed with a variety of hydrophilic and hydrophobic features. Offering potential to meet this demand, metal-organic framework (MOF) materials are synthesized from coordinated formations that create versatile reticular structures with variable water adsorption affinities. However, advances in the fundamental understanding of water interactions within these structures are impeded by the failure of classical analyses to identify mechanisms of interaction, connect fundamental isotherm types, and provide appropriate benchmarks for assessment.
View Article and Find Full Text PDFSmall
September 2025
Technische Universität Braunschweig, Institute for Particle Technology, Volkmaroder Straße 5, 38104, Braunschweig, Lower Saxony, Germany.
While the effects of new solid electrolytes and active materials in cathode composites for solid-state batteries are being intensively researched, little is known about the influence of mechanical processing on the properties of these composites. Here, the influence of mechanical process parameters on the production of LiPSCl and LiNiCoMnO composite cathodes applying a planetary ball milling process is systematically investigated. It is shown that the milling process has a significant influence on the microstructure of the composite by affecting the solid electrolyte particle size and the formation of electrolyte-active material aggregates.
View Article and Find Full Text PDFJ Optim Theory Appl
September 2025
Department of Mathematics, Linköping University, SE-581 83 Linköping, Sweden.
Single-level reformulations of (nonconvex) distributionally robust optimization (DRO) problems are often intractable, as they contain semi-infinite dual constraints. Based on such a semi-infinite reformulation, we present a safe approximation that allows for the computation of feasible solutions for DROs that depend on nonconvex multivariate simple functions. Moreover, the approximation allows to address ambiguity sets that can incorporate information on moments as well as confidence sets.
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