The COVID-19 pandemic has underscored the importance of wearing effective facepiece filtering respirators (FFRs) to reduce infection and disease transmission.One of the reasons causing the widespread prevalence was found to be the failure of N95-Equivalent FFRs (N95-EFs), i.e., efficiency <<95%, during the pandemic.To investigate the reasons
Volumetric medical image datasets contain vital information for noninvasive diagnosis, treatment planning and prognosis.However, direct and unlimited query of such datasets is hindered due to the unstructured nature of the imaging data.This study is a step towards the unlimited query of medical image datasets by focusing on specific Structures of I
During the past decades, convolutional neural network (CNN)-based models have achieved notable success in remote sensing image classification due to their powerful feature representation ability.However, the lack of explainability during the decision-making process is a common criticism of these high-capacity networks.Local explanation methods that
The standard model left-handed neutrinos and several right-handed neutrinos can obtain a tiny Dirac mass matrix through their mixings with relatively heavy Dirac fermions.In this Dirac seesaw scenario, the mixings involving the left-handed neutrinos can be allowed much larger than those involving the right-handed neutrinos.This undemocratic paramet