3results about How to "Good quantitative effect" patented technology

The invention belongs to the technical field of drug detection, and particularly relates to a method for detecting lycium barbarum glycopeptide metabolites in rat plasma and tissues based on non-targeted metabonomics. According to the method, after rat lycium barbarum glycopeptides are administered through intragastric administration, blood, liver, intestine, lung and brain tissue samples after administration are collected. A UPLC-Q-TOF-MS (Ultra Performance Liquid Chromatography-Quadrupole Time of Flight Mass Spectrometry) analysis method is combined with a statistical analysis method comprising principal component analysis (PCA) and orthogonal-partial least squares discriminant analysis (OPLS-DA) to carry out in-vivo metabonomics analysis on the wolfberry glycopeptide. Then, based on a human metabolome database (HMDB), lycium barbarum glycopeptide differential metabolite is searched, so that the pharmacological action mechanism of the lycium barbarum glycopeptide is clarified from the perspective of metabolism, and a foundation is laid for deep research and development of the medicinal value of the lycium barbarum glycopeptide in future.

This invention discloses a method for fabricating and applying a formaldehyde SERS sensor based on an Au@ZIF-8 core-shell nanostructure, belonging to the field of gas detection technology. Formaldehyde has an extremely small intrinsic Raman cross section, and ordinary SERS substrates lack the ability to capture it, resulting in weak detection signals at low concentrations. This sensor uses Au@ZIF-8 core-shell nanoparticles to assemble a two-layer thin film as the SERS substrate. The Au nanoparticles (AuNPs) serve as the electromagnetic enhancement core, while the ZIF-8 shell layer enriches and sieves formaldehyde molecules. A layer-to-layer deposition method is used to construct the double-layer thin film structure to obtain optimal SERS performance. This invention solves the problems of low sensitivity, poor specificity, insufficient stability, and difficulty in rapid on-site detection in existing formaldehyde detection technologies. The detection limit is as low as 0.16 ppt, and within a wide range from 0.01 ppb to 100 ppm, the characteristic peak intensity exhibits an excellent linear relationship with the logarithm of formaldehyde concentration (R² ≥ 0.995). It can specifically identify formaldehyde and exclude interference from other VOCs, making it suitable for rapid quantitative detection of formaldehyde in practical scenarios such as indoor environments and cigarette smoke.

This invention discloses a multi-scale feature fusion method and system for atmospheric turbulence video correction. It extracts shallow texture, mid-level structure, and high-level semantic information through a multi-scale feature pyramid, and combines frequency adaptive enhancement and deformable attention alignment mechanisms to perform channel-weighted processing on different frequency components. Adaptive optimization is achieved to address differences in turbulence sensitivity, and feature-level alignment is completed under optical flow guidance to eliminate tilt distortion. Simultaneously, a gated reference update module dynamically maintains reference features to suppress turbulence noise accumulation. Furthermore, a multi-head temporal channel self-attention mechanism is used to achieve cross-frame spatiotemporal fusion, improving temporal consistency, and a two-stage decoder is used to progressively restore image geometry and high-frequency details. This invention can significantly improve the clarity of turbulence-degraded images, providing technical support for high-precision imaging.