Bio-based flame retardants are of great significance for ecological environments, sustainable
development and human health. Herein, a novel DOPO-based furan-containing flame …

With the widespread application of 5G technology and the rapid development of electronic
device miniaturization, electromagnetic radiation interference has become an increasingly …

To obtain cotton fabrics with high-efficiency flame retardancy, a novel nanohybrid MXene
modified with phosphorylated chitosan (CS) was successfully prepared through a simple …

Recently, Spiking Neural Networks (SNNs) have demonstrated rich potential in computer
vision domain due to their high biological plausibility, event-driven characteristic and energy-…

Background Epoxy resin, one of the most commonly used thermosetting materials, suffers
from the more obvious defect of being flammable. Methods In this work, three new types of N-…

Spiking neural networks (SNNs) compute with discrete spikes and exploit temporal structure,
yet most adversarial attacks change intensities or event counts instead of timing. We study …

This study introduces a holistic approach to outcome prediction using multiple indicators. We
develop an innovative methodology that combines factor analysis for weight determination …

As one of the largest families of transcription factors in plants, the basic helix-loop-helix (bHLH)
transcription factor family regulates a wide range of functions in plants. However, little is …

In response to the urgent demand for lightweight, low-cost, and low-energy-consumption
radar systems for unmanned aerial and ground vehicles, this study conducts research on …

Brain-inspired Spiking neural networks (SNNs) promise energy-efficient intelligence via
event-driven, sparse computation, but deeper architectures inflate parameters and …