RSPSSL:A novel high-fidelity Raman spectral preprocessing scheme to enhance biomedical applications and chemical resolution visualization

Raman spectroscopy has tremendous potential for material analysis with its molecular fingerprinting capability in many branches of science and technology.It is also an emerging omics technique for metabolic profiling to shape precision medicine.However,precisely attributing vibration peaks coupled with specific environmental,instrumental,and specimen noise is problematic.Intelligent Raman spectral preprocessing to remove statistical bias noise and sample-related errors should provide a powerful tool for valuable information extraction.Here,we propose a novel Raman spectral preprocessing scheme based on self-supervised learning(RSPSSL)with high capacity and spectral fidelity.It can preprocess arbitrary Raman spectra without further training at a speed of~1900 spectra per second without human interference.The experimental data preprocessing trial demonstrated its excellent capacity and signal fidelity with an 88%reduction in root mean square error and a 60%reduction in infinite norm(L__(∞))compared to established techniques.With this advantage,it remarkably enhanced various biomedical applications with a 400%accuracy elevation(ΔAUC)in cancer diagnosis,an average 38%(few-shot)and 242%accuracy improvement in paraquat concentration prediction,and unsealed the chemical resolution of biomedical hyperspectral images,especially in the spectral fingerprint region.It precisely preprocessed various Raman spectra from different spectroscopy devices,laboratories,and diverse applications.This scheme will enable biomedical mechanism screening with the label-free volumetric molecular imaging tool on organism and disease metabolomics profiling with a scenario of high throughput,cross-device,various analyte complexity,and diverse applications.

High-performance γ-MnO_(2) Dual-Core,Pair-Hole Fiber for Ultrafast Photonics

Manganese dioxide(MnO2)is a widely used and well-studied 3-dimensional(3D)transition metal oxide,which has advantages in ultrafast optics due to large specific surface area,narrow bandgap,multiple pores,superior electron transfer capability,and a wide range of light absorption.However,few studies have considered its excellent performance in ultrafast photonics.y-MnO2 photonics devices were fabricated based on a special dual-core,pair-hole fiber(DCPHF)carrier and applied in ultrafast optics fields for the first time.The results show that the soliton molecule with tunable temporal separation(1.84 to 2.7 ps)and 600-MHz harmonic solitons are achieved in the experiment.The result proves that this kind of photonics device has goodapplications in ultrafast lasers,high-performance sensors,fiber optical communications,etc.,which can help expand the prospect of combining 3D materials with novel fiber for ultrafast optics device technology.