Characteristics of individuals in a population, such as age and size, play a key role in determining how populations change over time. In contexts of population dynamics, identifying effective model features, such as fecundity and mortality rates, is...
The mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors. As the number of identified classes of spinal interneurons constituting the locomotor ...
Modeling microbiomes can provide predictive insights into microbial ecology, but current modeling approaches suffer from inherent limitations. In this study, a novel modeling approach was developed based on the intrinsic connection between the growth...
The fruit fly Anastrepha fraterculus (Wiedemann) (Diptera: Tephritidae) is one of the main pests in apple orchards. Artificial neural networks (ANNs) are tools with good ability to predict phenomena such as the seasonal dynamics of pest populations. ...
Proceedings of the National Academy of Sciences of the United States of America
Aug 29, 2025
Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially generated collective behaviors. However, the construction of such theo...
Proceedings of the National Academy of Sciences of the United States of America
Aug 18, 2025
Fish population biomass fluctuates through time in ways that may be either gradual or abrupt. While abrupt shifts in fish population productivity have been shown to be common, they are rarely integrated into stock assessment or fishery management, in...
Population prediction could provide effective data support for social and economic planning and decision-making, especially for the sub-national population forecasting accurately. In addition to realizing efficient smart population management, this r...
Rocky reef temperate mesophotic ecosystems (TMEs) are increasingly recognised for their spatial extent and high biodiversity. Platforms such as autonomous underwater vehicles (AUVs) allow large-scale collection of benthic imagery, facilitating descri...
Various modelling techniques are available to understand the temporal and spatial variations of the phenology of species. Scientists often rely on correlative models, which establish a statistical relationship between a response variable (such as spe...
Physics informed neural networks have been gaining popularity due to their unique ability to incorporate physics laws into data-driven models, ensuring that the predictions are not only consistent with empirical data but also align with domain-specif...
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