Abstract In recent years, convolutional neural networks (CNNs) have made great achievements in the field of medical image segmentation, especially full convolutional neural networks based on U-shaped structures and skip connections.However, limited by the inherent limitations of convolution, CNNs-based methods usually exhibit limitations in modelin
The cosmological relevance of emptiness—that is, space without bodies—is not yet sufficiently appreciated in natural philosophy.This paper addresses two aspects of cosmic emptiness from the perspective of natural philosophy: the distances to the stars in the closer cosmic environment and the expansion of space as a result of the acceler
Abstract We introduce the Bioacoustic Cocktail Party Problem Network (BioCPPNet), a lightweight, modular, and kryolan anti shine powder robust U-Net-based machine learning architecture optimized for bioacoustic source separation across diverse biological taxa.Employing learnable or handcrafted encoders, BioCPPNet operates directly on the raw acoust
Vehicles travelling underwater experience drag and the frictional drag costs 60% of the total energy consumption.Using trapped air serving as a lubricant is a promising way to tokidoki x hello kitty blind box reduce drag.The trapped air plays a significant role in drag reduction, and most failures in drag reduction are related to instability, escap
Abstract Energy storage technologies (ESTs) play an important role in integrated, decentralized renewable energy systems.However, the lack of public acceptance and awareness of ESTs can significantly delay or block the implementation of renewable energy projects.This study aims to identify the societal and legislative barriers to implementing ESTs