In the context of global warming, a substantial portion of global soil is in a state of degradation, which poses a significant threat to biodiversity and food production worldwide. Moreover, monitoring soil quality typically requires measuring numero...
Bacterial infections present a significant threat to human health, and accurate identification of infection type is crucial for both clinical and forensic applications. Although traditional diagnostic methods are reliable, they are often time-consumi...
International journal of legal medicine
Sep 1, 2025
In forensic practice, the estimation of postmortem interval has been a persistent challenge. Recently, there has been an increasing utilization of metabolomics techniques combined with machine learning methods for postmortem interval estimation. When...
Nano-confined binary mixtures are prevalent in the chemical industry, geology, and energy sectors. Investigating their mass transfer behavior can enhance process intensification. This study examines the confined self-diffusion coefficients of binary ...
The evolution of wetland ecosystems from the perspectives of landscape connectivity and fragmentation is a critical interdisciplinary topic in contemporary wetland science and landscape ecology. In the context of global warming, the mechanisms by whi...
Converting cellulose into 5-Hydroxymethylfurfural (HMF) provides a promising strategy for creating bio-based chemicals, offering sustainable alternatives to petroleum-based materials in polymers, biofuels, and pharmaceuticals. However, the efficient ...
Soil nitrous acid (HONO) emissions influence air quality by affecting atmospheric oxidizing capacity and secondary pollutant formation. However, estimating soil HONO emissions remains uncertain due to complex factors and limited data. Here, we presen...
An efficient machine learning model was developed to accurately predict the sintering temperature of ceramsite synthesized from various solid waste materials. Based on experimental data from 236 samples, eight key chemical components were defined as ...
Dual-mode sensors capable of detecting multiple physical stimuli simultaneously offer significant advantages for advanced applications in human-machine interaction, robotics, and healthcare. However, the flammability of conventional materials limits ...
Homeostatic control of neural networks is based on monitoring the activity level of neurons and adjusting excitability. A recent study demonstrates that the physical environment per se (temperature) can directly regulate the neural circuits underlyin...
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