Spiking neural network (SNN) is considered to be the brain-like model that best conforms to the biological mechanism of the brain.Due to the non-differentiability of the spike, the training method of SNNs is still incomplete.This paper proposes a supervised learning method for SNNs based on associative learning: ALSA.The method is based soiebiologi
On-demand, hospital-based, severe acute respiratory coronavirus virus 2 (SARS-CoV-2) genomic epidemiology to support nosocomial outbreak investigations: A prospective molecular epidemiology study
Abstract Objectives: We evaluated the added value of infection control-guided, on demand, and locally performed severe acute respiratory coronavirus virus 2 (SARS-CoV-2) genomic sequencing to support outbreak investigation and control in acute-care settings.Design and setting: This 18-month prospective molecular epidemiology study was conducted at
Ultrahigh Purcell Factor, Improved Sensitivity, and Enhanced Optical Force in Dielectric Bowtie Whispering-Gallery-Mode Resonators
We propose and theoretically investigate an all-dielectric bowtie whisperinggallery-mode (WGM) resonator which consists of two tip-to-tip coupled semiconductor nanorings with triangular cross section separated by low refractive index material gap.Mode splitting of symmetric WGM and antisymmetric WGM is observed and analyzed.Due to extremely field e
Identification of fragment ions produced by the decomposition of tetramethyltin and the production of low-energy Sn+ ion beam.
Tetramethyltin was decomposed in an ion source and the fragment ions produced were identified using a low-energy mass-selected ion beam machine.Dominant fragment ions were found to be H+, CH2+, and Sn+.Subsequently, fragment ions were mass-selected.The mass spectrum of the selected ions indicated that only a single peak appeared at the mass number