Two-Dimensional J-Resolved NMR Analyses of Fish and Its Products via Spatially Encoded Intermolecular Double-Quantum Coherences

Abstract

Nuclear magnetic resonance (NMR) spectroscopy provides a powerful tool for food analyses due to its highthroughput information related to component analyses and its non-invasive property without altering detected samples. Current liquid NMR approaches, however, are subject to the influence of field inhomogeneity in direct measurements of biological foods, generally resorting to techniques of tissue extractions or magic-angle spin to eliminate the inhomogeneity. Therefore, we propose an NMR approach based on intermolecular double-quantum coherences (iDQCs) and spatial encoding technique to fast recover high-resolution two-dimensional (2D) J-resolved spectra in inhomogeneous fields. Inheriting from the immunity to field inhomogeneity of iDQCs and the enhancement in acquisition efficiency of the spatial encoding technique, the proposed method can resist the field inhomogeneity in biological foods without superfluous pretreatments and time-consuming shimming procedures, and yield satisfactory 2D J-resolved information for analyses within minutes. Fish and its products, which are closely related to human daily life, capture extensive attentions with the rapid development of the aquaculture. At first, experiments on cod liver oils are implemented in a purposely deshimmed magnetic field to demonstrate the feasibility of the proposed approach. Then, caviars and an intact fish are tested to further show the applicability of the proposed approach for direct measurements on intact biological food samples. Herein, the proposed method may constitute an effective technique in analyzing fish and its products.

Internet of things network intrusion detection model based on quantum artificial fish group and fuzzy kernel clustering algorithm

“…Among these measures, intrusion detection is a main aspect of 5G IoT security, which is the key to identify potential security incidents and the preliminary step before performing any other actions to counteract them 8 . The accuracy and timeliness of the attack detection are the key metrics to evaluate the performance of the attack detection methods.…”