Infrasound Event Classification Fusion Model Based on Multiscale SE-CNN and BiLSTM

The classification of infrasound events has considerable importance in improving the capability to identify the types of natural disasters.The traditional infrasound classification mainly relies on machine learning algorithms after artificial feature extraction.However,guaranteeing the effectiveness of the extracted features is difficult.The current trend focuses on using a convolution neural network to automatically extract features for classification.This method can be used to extract signal spatial features automatically through a convolution kernel;however,infrasound signals contain not only spatial information but also temporal information when used as a time series.These extracted temporal features are also crucial.If only a convolution neural network is used,then the time dependence of the infrasound sequence will be missed.Using long short-term memory networks can compensate for the missing time-series features but induces spatial feature information loss of the infrasound signal.A multiscale squeeze excitation–convolution neural network–bidirectional long short-term memory network infrasound event classification fusion model is proposed in this study to address these problems.This model automatically extracted temporal and spatial features,adaptively selected features,and also realized the fusion of the two types of features.Experimental results showed that the classification accuracy of the model was more than 98%,thus verifying the effectiveness and superiority of the proposed model.

基于MSSA-XGBoost小样本核爆地震事件分类

核爆地震与天然地震事件的分类鉴别是全面禁止核试验条约中的一项重要任务。受限于核爆数据数量缺乏,论文研究了XGBoost模型在小样本场景下两类事件的分类问题,并利用SSA算法对模型关键超参数进行自主寻优。同时针对SSA算法的不足,采用高斯混沌映射方法、提出种群比例动态调整策略和引入步长调整因子进行改进,构建了MSSA-XGBoost分类模型。模型解决了初始种群分布不均匀,导致种群多样性减少,影响算法收敛速度的问题;解决了麻雀种群比例固定,容易陷入局部最优解的问题;以及解决了发现者位置更新步长固定,从而限制算法全局搜索能力与寻优效率的问题,实现了避免人工特征提取和XGBoost迭代次数、最大树深以及学习率三个重要超参数的自主寻优,在小样本地震事件分类中取得了优异的效果。实验结果表明,MSSA-XGBoost模型分类准确率达到了96.37%,优于原模型93.47%,也优于支持向量机与卷积神经网络,同时较原始模型计算效率提升了近30%。

Tung Tree(Vernicia fordii) Genome Provides A Resource for Understanding Genome Evolution and Improved Oil Production

Tung tree(Vernicia fordii) is an economically important woody oil plant that produces tung oil rich in eleostearic acid. Here, we report a high-quality chromosome-scale genome sequence of tung tree. The genome sequence was assembled by combining Illumina short reads, Pacific Biosciences single-molecule real-time long reads, and Hi-C sequencing data. The size of tung tree genome is 1.12 Gb, with 28,422 predicted genes and over 73% repeat sequences. The V. fordii underwent an ancient genome triplication event shared by core eudicots but no further wholegenome duplication in the subsequent ca. 34.55 million years of evolutionary history of the tung tree lineage. Insertion time analysis revealed that repeat-driven genome expansion might have arisen as a result of long-standing long terminal repeat retrotransposon bursts and lack of efficient DNA deletion mechanisms. The genome harbors 88 resistance genes encoding nucleotide-binding sites;17 of these genes may be involved in early-infection stage of Fusarium wilt resistance. Further, 651 oil-related genes were identified, 88 of which are predicted to be directly involved in tung oil biosynthesis. Relatively few phosphoenolpyruvate carboxykinase genes, and synergistic effects between transcription factors and oil biosynthesis-related genes might contribute to the high oil content of tung seed. The tung tree genome constitutes a valuable resource for understanding genome evolution, as well as for molecular breeding and genetic improvements for oil production.

Intermetallic PdBi aerogels with improved catalytic performance for the degradation of organic pollutants in water

It is always highly pursued to develop efficient and durable catalysts for catalytic applications.Herein,intermetallic PdBi aerogels with tunable activity were prepared successfully via a surfactant-free spontaneous gelation process.The prepared PdBi aerogels have a three-dimensional high porous structure and plentiful active sites pervaded on the ultrathin interlinked nanowires network.These unique structures,as well as the synergistic effect between Pd and Bi,can accelerate mass and electron transfer,and improve the atom utilization ratio of Pd atoms to promote the catalytic efficiency.As a proofof-concept application,the optimized Pd_(2) Bi_(1) aerogels exhibit 4.2 and 6.2 times higher catalytic activity for the reduction of 4-nitrophenol(4-NP)and methylene blue(MB)than those of commercial Pd/C,respectively.With the introduction of non-noble metal of Bi,the cost of the resulted Pd Bi aerogels can be dropped signi ficantly while the catalytic capability of Pd Bi aerogel will be improved sharply.This strategy will bring good hints to rationally design fine catalysts for various applications.

β-Cyclodextrin-modified AuBi metallic aerogels enable efficient peroxidase mimicking for colorimetric sensing of urease-positive pathogenic bacteria

The detection of pathogenic bacteria with improved accessibility,reduced analysis time,and increased sensitivity is of great importance for diagnosing the infected disease.Nanozymes have attracted rising attention in the bioassay field.Designing a model nanozyme needs the combined merit of sensible nanostructures and a large specific surface area to guarantee exceptional enzyme-mimic activity.Herein,aβ-cyclodextrin modified AuBi aerogel is prepared by a one-pot reduction strategy.The introduction ofβ-cyclodextrin(featured with a hydrophobic cavity and hydrophilic surface)enhances the catalytic activity of AuBi aerogels by engendering host-guest complex and improving dispersity/stability.Based on the specific urea hydrolysis,which could produce NH_(3)to raise pH by urease,the pH up-regulation would inhibit the peroxidase-mimicking performances ofβ-cyclodextrin/AuBi aerogels.Therefore,the sensitive colorimetric detection platform for urease activity could be constructed.Moreover,the sensing platform can detect straightforwardly urease-positive Proteus mirabilis in urine circumstances with a wide detection range and a low limit of detection(LOD)of 4 colony-forming unit(CFU)·mL^(-1).The reproducibility,stability,and specificity of this approach are verified to be satisfactory.Also,as an inhibitor of urease activity,the fluoride ion could be detected by the constructed sensing platform sensitively and specifically.Overall,this work provides a blueprint for designing an ideal nanozyme and paves a new roadway for detecting pathogenic bacteria.

Self-assembled all-inclusive organic-inorganic nanoparticles enable cascade reaction for the detection of glucose

Traditional colorimetric glucose biosensor generally involves complex assay procedures.Free labile enzymes and peroxidase substrates are used separately for triggering a chromogenic reaction.These limits result in inferior enzyme stability and defective enzymatic catalytic efficiency,making it hard to routinely utilize them for the direct and fast test of glucose.In this work,we provide an all-inclusive substrates/enzymes nanoparticle employed 3,3’5,5’-tetramethylbenzidine(TMB) as chromogenic substrates and glucose oxidase(GOx)/horseradish peroxidase(HRP) as signal amplifier enzymes(TMB-GH NPs) by the molecule self-assembly technique.The "all-inclusive" nanoparticles can realize the tandem colorimetric reactions,and the oxidation product of TMB(ox-TMB) exhibits a strong NIR laserdrive n photothermal effect,thus allowing qua ntitative photothermal detection of glucose.Owing to the restriction of the molecular motion of GOx,HRP,and TMB,the distance of mass transfer between substrates was s hortened largely,leading to improved catalytic activity for glucose.Overall,our strategy will simplify the analysis procedure,furthermore,these integrated nanoparticles not only display higher stability and activity than that of the free GOx/HRP system and possesses an excellent performance for colorimetric and photothermal bioassay of glucose simultaneously.We believe that this unique technique will give good inspirations to develop simple and precise methods for bioassay.

Fluorescent and colorimetric immunoassay of nuclear matrix protein 22 enhanced by porous Pd nanoparticles

A modified ELISA realizing fluorescent and colorimetric immunoassay of nuclear matrix protein 22 (NMP 22) was developed based on porous Pd nanoparticles. The unique structure and excellent enzyme mimetic activity of porous Pd nanoparticles favor to oxidize o-phenylenediamine (OPD) into 2,3-phenazinediamine (oxOPD) by H2O2, producing colorimetric and fluorescence dual-readout signal for the detection of NMP 22. The developed immunoassay method will offer great potential in clinical research and diagnostic applications.

pH Readout enhanced ELISA for point-of-care testing of cardiac troponin I

Enzyme-linked immunosorbent assay（ELISA） as a conventional method for protein quantification has its characteristic properties,however,it is challenging to implement excellent portability and sensitivity at the same time.In this study,we described a pH ELISA using synthetic melanin nanoparticles（SMNPs） for the co-immobilization of glucose oxidase（GOx） and second antibody（Ab_2） as signal labels,portable pH meter as signal readout device for point-of-care testing（POCT） of cardiac troponin I（cTnI）.In accordance with the varying amount of cTnI,following sandwich type immunoassay,proportional SMNPs-GOx-Ab_2 were immobilized specifically resulting in corresponding decrease of pH values owing to GOx loaded on SMNPs can high-efficiency convert glucose into gluconic acid.This assay is easy-to-use,portable,sensitive and able to realize POCT,affording a linear range from 0.5 pg/m L to 10 ng/m L and low limit of detection（LOD） of 0.15 pg/m L towards cTnI,which was demonstrated the significant promising in the early diagnosis and screening of acute myocardial infarction.