Epimedium is commonly used to treat bone injury and kidney disease,with prenylated flavonol glycosides(PFGs)as its active ingredients.It has attracted much attention due to prominent healthcare and therapeutic effects...Epimedium is commonly used to treat bone injury and kidney disease,with prenylated flavonol glycosides(PFGs)as its active ingredients.It has attracted much attention due to prominent healthcare and therapeutic effects,but faces problems of adulteration with closely related species and confusion about geographical origins.In this study,multiple technical approaches were employed to identify its genetic characteristics and metabolic differences.Based on DNA barcoding,20 batches of samples were analyzed.The genetic distances of matK,ITS and psbA-trnH within species were all smaller than those between species,and psbA-trnH along with ITS+psbA-trnH proved most effective in distinguishing botanical sources.With Inter-simple sequence repeat(ISSR)technology,12 highly polymorphic and reproducible primers were selected from 21,and 189 alleles were detected.Epimedium sagittatum showed distinct genetic diversity.Samples with similar genetic distance and geographical location also tended to cluster together.Eight index components were analyzed,and their contents showed significant differences.The total content ranged from 0.50%to 7.09%,and icariin and epimedin C were identified as potential biomarkers.Integrative analysis revealed that the differences in index components were jointly driven by genetic diversity and ecological factors.Additionally,“mean temperature of driest quarter”,“precipitation seasonality”,and“temperature annual range”were identified as key environmental factors.This study provides a reliable experimental basis for the authenticity and quality evaluation of Epimedium.展开更多
[Objectives]To develop an HPLC fingerprint analysis method for the medicinal material of Lysimachia foenum-graecum Hance,thereby providing a foundation for its quality control.[Methods]Samples of L.foenum-graecum coll...[Objectives]To develop an HPLC fingerprint analysis method for the medicinal material of Lysimachia foenum-graecum Hance,thereby providing a foundation for its quality control.[Methods]Samples of L.foenum-graecum collected from 10 distinct locations in Guangxi were analyzed using HPLC,and chromatographic fingerprints were established.The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(2012 Edition)was employed for common peak calibration and similarity evaluation.Additionally,principal component analysis was performed on the common peak area data.[Results]An HPLC fingerprint of L.foenum-graecum was developed,identifying a total of 13 common peaks.Among these,four characteristic components were specifically identified:chlorogenic acid,myricetin,quercetin,and kaempferol.The kaempferol chromatographic peak,exhibiting good resolution and a stable peak shape,was selected as the reference peak.The similarity indices between the fingerprints of the 10 sample batches and the reference fingerprint ranged from 0.954 to 0.995,indicating a relatively high consistency in the chemical composition of L.foenum-graecum from different origins.Principal component analysis identified two principal components,which together accounted for 89.45%of the cumulative variance,effectively capturing the primary chemical differences among the samples.[Conclusions]The established HPLC fingerprint method is straightforward to implement,stable,reliable,and exhibits high specificity.When combined with similarity evaluation and principal component analysis,it offers a scientific basis for developing quality standards for L.foenum-graecum medicinal materials.展开更多
High-throughput single nucleotide polymorphism(SNP) arrays have emerged as essential genotyping tools,significantly accelerating breeding programs and advancing basic research.In this study,a high-throughput 10K SNP g...High-throughput single nucleotide polymorphism(SNP) arrays have emerged as essential genotyping tools,significantly accelerating breeding programs and advancing basic research.In this study,a high-throughput 10K SNP genotyping array for wax gourd was developed using genotyping by target sequencing(GBTS),featuring 10,722 SNPs evenly distributed across all 12 chromosomes,including 278 functional loci associated with key economic traits.To demonstrate its utility,genetic distances among 19 elite inbred lines were calculated from SNP data and correlated with heterosis for single fruit weight.The results revealed that greater genetic distance was associated with higher middle parent heterosis(MPH) for single fruit weight.Furthermore,56 commercial wax gourd cultivars collected from eight regions were selected and genotyped.Population structure analysis,phylogenetic analysis,and principal component analysis(PCA) collectively indicated that these cultivars fall into two major groups.Group I,comprising black or dark green skinned wax gourds,exhibited lower genetic diversity than Group II,which includes green or light green skinned varieties,reflecting shorter genetic distances within Group I.Finally,60 polymorphic SNPs were used to construct DNA fingerprints for distinguishing the 56 cultivars.As the first high-throughput genotyping platform for wax gourd,this SNP array provides an effective and powerful tool for genetic analysis.展开更多
Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao)...Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao),wheat(Xiaomai),and jujube(Dazao),it functions to nourish the heart and calm the mind,harmonize the middle burner and regulate Qi,and alleviate urgency and restlessness.As its clinical application has expanded from traditional emotional disorders to neurological,endocrine,and various psychosomatic diseases,establishing a scientifically precise quality control system and deeply elucidating its pharmacodynamic material basis and mechanism of action have become critical tasks.Modern analytical methods,typified by chromatography,spectroscopy,and their hyphenated techniques,with their high sensitivity,high resolution,and powerful substance characterization capabilities,have become the core driving force for standardizing the quality control and modernizing the clinical application research of this formula.This paper systematically reviews the progress of the aforementioned analytical techniques and chemometrics in interpreting the chemical composition,establishing fingerprint profiles,controlling process quality,and researching the pharmacodynamic material basis of Ganmai Dazao Decoction.Furthermore,it discusses integrated approaches combining analytical techniques with pharmacology and clinical medicine to reveal mechanisms of action and explore therapeutic biomarkers.Finally,it provides an outlook on future directions and challenges,including technological integration and innovation,standardization of whole-process quality control systems,and evidence-based research aimed at internationalization.展开更多
Organic-inorganic metal halides(OIMHs)have emerged as highly promising novel multifunctional optoelectronic materials,owing to their easily adjustable properties from a variety of combinations of different components....Organic-inorganic metal halides(OIMHs)have emerged as highly promising novel multifunctional optoelectronic materials,owing to their easily adjustable properties from a variety of combinations of different components.But it is still difficult and rare to realize highly tunable multicolor luminescence within the same material.In this work,we successfully incorporated three adjustable emission centers in OIMHs to synthesize a novel OIMH(NEA)_(2)MnBr_(4),with each emission center capable of emitting one of the primary colors—red,green,and blue.The green and red emissions originate from the tetrahedron and octahedron structures in the Mn-based frame,while the blue can be attributed to the contribution of organic components.Additionally,to achieve comparable emission intensity among the three primary colors,we enhanced the blue emission performance by optimizing the ratio of organic structure components and incorporating chirality in the OIMHs.The resulting high-quality films can be obtained by spin-coating method with a photoluminescence quantum yields of up to 96%.More interestingly,by the dual manipulation of excitation wavelength and temperature,the sample can be emitted at least seven distinct colors including a standard white luminescence at(0.33,0.33),opening up promising prospects for multicolor luminescence applications such as high-end anti-counterfeiting technology,light-emitting diodes,X-ray imaging,latent fingerprints,humidity detection,and so on.Therefore,based on application scenarios and requirements,our research on this highly tunable luminescent OIMH material lays a solid foundation for further development of various functional properties of related materials.展开更多
Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoo...Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoofing problems.However,the effects of circuit changes over time often lead to a decline in identification accuracy within open-time set.This paper proposes an ADS-B transmitter identification method to solve the degradation of identification accuracy.First,a real-time data processing system is established to receive and store ADS-B signals to meet the conditions for open-time set.The system possesses the following functionalities:data collection,data parsing,feature extraction,and identity recognition.Subsequently,a two-dimensional TimeFrequency Feature Diagram(TFFD)is proposed as a signal pre-processing method.The TFFD is constructed from the received ADS-B signal and the reconstructed signal for input to the recognition model.Finally,incorporating a frequency offset layer into the Swin Transformer architecture,a novel recognition network framework is proposed.This integration can enhance the network recognition accuracy and robustness by tailoring to the specific characteristics of ADSB signals.Experimental results indicate that the proposed recognition architecture achieves recognition accuracy of 95.86%in closed-time set and 84.33%in open-time set,surpassing other algorithms.展开更多
Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based me...Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based methods have shown promising results in molecular property prediction.However,traditional methods rely on expert knowledge and often fail to capture the complex structures and interactions within molecules.Similarly,graph-based methods typically overlook the chemical structure and function hidden in molecular motifs and struggle to effectively integrate global and local molecular information.To address these limitations,we propose a novel fingerprint-enhanced hierarchical graph neural network(FH-GNN)for molecular property prediction that simultaneously learns information from hierarchical molecular graphs and fingerprints.The FH-GNN captures diverse hierarchical chemical information by applying directed message-passing neural networks(D-MPNN)on a hierarchical molecular graph that integrates atomic-level,motif-level,and graph-level information along with their relationships.Addi-tionally,we used an adaptive attention mechanism to balance the importance of hierarchical graphs and fingerprint features,creating a comprehensive molecular embedding that integrated hierarchical mo-lecular structures with domain knowledge.Experiments on eight benchmark datasets from MoleculeNet showed that FH-GNN outperformed the baseline models in both classification and regression tasks for molecular property prediction,validating its capability to comprehensively capture molecular informa-tion.By integrating molecular structure and chemical knowledge,FH-GNN provides a powerful tool for the accurate prediction of molecular properties and aids in the discovery of potential drug candidates.展开更多
Cardiotoxicity is a critical issue in drug development that poses serious health risks,including potentially fatal arrhythmias.The human ether-à-go-go related gene(hERG)potassium channel,as one of the primary tar...Cardiotoxicity is a critical issue in drug development that poses serious health risks,including potentially fatal arrhythmias.The human ether-à-go-go related gene(hERG)potassium channel,as one of the primary targets of cardiotoxicity,has garnered widespread attention.Traditional cardiotoxicity testing methods are expensive and time-consuming,making computational virtual screening a suitable alternative.In this study,we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds,with the aim of improving prediction accuracy and efficiency.We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms,including Gaussian naive Bayes(NB),random forest(RF),support vector machine(SVM),K-nearest neighbors(KNN),eXtreme gradient boosting(XGBoost),and Transformer models,to build predictive models.Our models demonstrated advanced predictive performance.The best machine learning model,XGBoost Morgan,achieved an accuracy(ACC)value of 0.84,and the deep learning model,Transformer_Morgan,achieved the best ACC value of 0.85,showing a high ability to distinguish between toxic and non-toxic compounds.On an external independent validation set,it achieved the best area under the curve(AUC)value of 0.93,surpassing ADMETlab3.0,Cardpred,and CardioDPi.In addition,we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods,such as voting and stacking,provided slight improvements in model stability.Furthermore,the SHapley Additive exPlanations(SHAP)explanations revealed the relationship between benzene rings,fluorine-containing groups,NH groups,oxygen in ether groups,and cardiotoxicity,highlighting the importance of these features.This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment.Using computational methods,this study facilitates a more efficient drug development process,reduces costs,and improves the safety of new drug candidates,ultimately benefiting medical and public health.展开更多
To further advance the development of the fluorescent dyes for latent fingerprint imaging,two triphenylamine-based Schiff base compounds containing a benzimidazole group(TPA-BZI)and a phenyl unit(TPA-Ph)were designed ...To further advance the development of the fluorescent dyes for latent fingerprint imaging,two triphenylamine-based Schiff base compounds containing a benzimidazole group(TPA-BZI)and a phenyl unit(TPA-Ph)were designed and synthesized.Photoluminescence experiments revealed that both compounds exhibited solvatochromism and intramolecular charge transfer(ICT)characteristics in six organic solvents.Additionally,they showed aggregation-induced emission(AIE)in CH_(3)OH/water mixtures and solid-state fluorescence.These phenomena were further elucidated through time-dependent density functional theory(TD-DFT)calculations.It was also found that the two compounds could be used for latent fingerprints imaging,and could easily distinguish the details of fingerprints from Ⅰ to Ⅲ levels,which could provide the preliminary evidence to match personal identification.展开更多
DNA testing for biological relationships is becoming increasingly common in Burkina Faso. STR analysis remains the most reliable technique for resolving disputes or claims in court regarding biological relationships. ...DNA testing for biological relationships is becoming increasingly common in Burkina Faso. STR analysis remains the most reliable technique for resolving disputes or claims in court regarding biological relationships. This study aimed to establish the links of biological relationships between subjects by analyzing 21 STR loci. The participants were 14 individuals referred to CERBA by the Justice in 2022. Oral or blood samples were taken for each subject. DNA was extracted, and the analysis of DNA polymorphism by PowerPlex® 21 Kit (Part No. DC8902) was performed by capillary electrophoresis on the ABI PRISM 3130 sequencer. DNA profiles were compiled using the GeneMapper IDX software version 1.2. Of the fourteen subjects examined, twelve of these samples had complete genetic profiles, while the other two had partial and absent profiles. The results confirmed the inclusion of three cases of Paternity, one case of maternity, one case of a relationship of brotherhood, and the exclusion of one case of maternity and one case of a relationship of brotherhood. DNA tests improve the resolution of filiations, but they require ethical and cultural awareness and a strengthened legal framework to prevent and protect society.展开更多
Fluorescence-based imaging applications have been benefiting greatly from donor-acceptor(D-A)/donor-π-acceptor(D-π-A)fluorescent probes owing to their intramolecular charge transfer(ICT)nature and self-assembly beha...Fluorescence-based imaging applications have been benefiting greatly from donor-acceptor(D-A)/donor-π-acceptor(D-π-A)fluorescent probes owing to their intramolecular charge transfer(ICT)nature and self-assembly behavior.In this study,we design and synthesize a hydrophilic D-A fluorescent probe,namely CHBA,which would self-assemble into interlaced textures down to nanoscale but disassemble by trace amount of water in fingertip area.Upon finger-pressing,it enables fingerprint imaging and covers level-1/2/3 fingerprint information,wherein the sweat pores can be mapped in both bright field model and fluorescence mode,capable of naked-eye-based similarity analysis for personal identity verification(PIV).Spectroscopic analysis and morphology study show that the working mechanism can be attributed to the selective water-erosion effect on the solid-liquid interphase under physical contact.The sweat pore information can be digitized by polar coordinate conversion,further allowing machine-learning-based analysis for PIV application.The final PIV accuracy reaches 100%for all the involved machine-learning models,with no erroneous judgements.A prototype of PIV system is constructed by integrating CHBA with artificial intelligence hardware,wherein the sweat pore imaging,data processing and the decisionmaking could be run in parallel,suggesting high feasibility in real-world application.展开更多
This paper investigates how to achieve integrated sensing and communication(ISAC)based on a cell-free radio access network(CF-RAN)architecture with a minimum footprint of communication resources.We propose a new passi...This paper investigates how to achieve integrated sensing and communication(ISAC)based on a cell-free radio access network(CF-RAN)architecture with a minimum footprint of communication resources.We propose a new passive sensing scheme.The scheme is based on the radio frequency(RF)fingerprint learning of the RF radio unit(RRU)to build an RF fingerprint library of RRUs.The source RRU is identified by comparing the RF fingerprints carried by the signal at the receiver side.The receiver extracts the channel parameters from the signal and estimates the channel environment,thus locating the reflectors in the environment.The proposed scheme can effectively solve the problem of interference between signals in the same time-frequency domain but in different spatial domains when multiple RRUs jointly serve users in CF-RAN architecture.Simulation results show that the proposed passive ISAC scheme can effectively detect reflector location information in the environment without degrading the communication performance.展开更多
A leading position in the areas of testing,instrumentation and machine control has been established by members of the British Textile Machinery Association(BTMA)and a number of new developments in these fields will be...A leading position in the areas of testing,instrumentation and machine control has been established by members of the British Textile Machinery Association(BTMA)and a number of new developments in these fields will be showcased at this year’s ITMA Asia+CITME exhibition,which takes place in Singapore from October 28-31.“Many of our members are currently developing new technologies,either in-house or increasingly through joint projects,and there will be much to reveal by the time of ITMA Asia in Singapore,”says BTMA CEO Jason Kent.“Some of the most recent developments are really going beyond what has previously been possible.”展开更多
The integration of phytochemistry into forensic science has emerged as a groundbreaking frontier,providing unprecedented insights into nature's secrets through the precise application of phytochemical fingerprinti...The integration of phytochemistry into forensic science has emerged as a groundbreaking frontier,providing unprecedented insights into nature's secrets through the precise application of phytochemical fingerprinting of phytotoxins as a cutting-edge approach.This study explores the dynamic intersection of phytochemistry and forensic science,highlighting how the unique phytochemical profiles of toxic plants and their secondary metabolites,serve as distinctive markers for forensic investigations.By utilizing advanced techniques such as Ultra-High-Performance Liquid Chromatography(UHPLC)and High-Resolution Mass Spectrometry(HRMS),the detection and quantification of plant-derived are made more accurate in forensic contexts.Real-world case studies are presented to demonstrate the critical role of plant toxins in forensic outcomes and legal proceedings.The challenges,potential,and future prospects of integrating phytochemical fingerprinting of plant toxins into forensic science were discussed.This review aims to illuminate phytochemical fingerprinting of plant toxins as a promising tool to enhance the precision and depth of forensic analyses,offering new insights into the complex stories embedded in plant toxins.展开更多
Terpenoids,as crucial plant secondary metabolites in honey,possess various bioactivities.This study aimed at investigating terpenoids of longan,litchi,and schefflera honey.Our results reveal that these three species o...Terpenoids,as crucial plant secondary metabolites in honey,possess various bioactivities.This study aimed at investigating terpenoids of longan,litchi,and schefflera honey.Our results reveal that these three species of honey are characterized by abundant terpenoids,with eight terpenoids and one phenylpropanoid identified.Callunene,3,4,5-trimethoxyphenylpropanal,schefflerin(4-2'-(3',4'-dihydroxy-5'-methylfuran)-3,5,5-trimethyl-2-cyclohexenone)or abscisic acids may be as the characteristic components of longan,litchi,or schefflera honey.Abscisic acids were the most abundant components,average contents reached up to 53.67,96.89 and 21.11 mg/kg,respectively,and the content ranges in three types of honey were 13.75-85.40,19.93-177.31,14.69-28.38 mg/kg,respectively.To our knowledge,the presence of schefflerin,(6R,9S)-vomifoliol,and 3,4,5-trimethoxyphenylpropanal in honey is a novel finding.We distinguish Thailand from Chinese mainland and Taiwan longan honeys,based on the ratio of abscisic acid and callunene content.Overall,our proposal to combine terpenoids with standard fingerprints seems to provide a novel and reliable solution for evaluating the authenticity of commercial honey.展开更多
Generally,gaining fundamental insights into chain processes during the combustion of flame-retardant polymers relies on the qualitative and quantitative characterization of key chain carriers.However,polymer combustio...Generally,gaining fundamental insights into chain processes during the combustion of flame-retardant polymers relies on the qualitative and quantitative characterization of key chain carriers.However,polymer combustion processes based on conventional solid-fuel combustion strategies,due to the high coupling of pyrolysis,combustion,soot formation and oxidation,exhibit relatively high complexity and poor flame stability,and lead to a huge obstacle to the use of optical diagnostics.Herein,a spatial-confinement combustion strategy,which can produce a special staged flame with multi-jets secondary wave,is devised to provide a highly decoupled combustion environment.Glowing soot particles are therefore decoupled from main chemiluminescence region and confined to the flame tip to provide a well-controlled,opticalthin test environment for combustion diagnostic.Based on this strategy,a multi-nozzle-separation(MNS)burner is designed and fabricated,and the combustion processes associated with four model compounds,PVC,PS,PP/TBBA blends and PP/RP blends are investigated by spontaneous spectral diagnosis,and the chemiluminescence fingerprint of key diatomic/triatomic intermediates(such as OH,CH,C_(2),ClO,Br_(2),and PHO)are clearly observed.This encouraging result means that the strategy of spatial-confinement combustion we proposed shows promising prospect in many subjects associated with combustion chain regulation,such as efficient design of flame retardants.展开更多
With the rapid development of Internet of things technology,the efficiency of data transmission between devices has been significantly improved.However,the open network environment also poses serious security risks.Th...With the rapid development of Internet of things technology,the efficiency of data transmission between devices has been significantly improved.However,the open network environment also poses serious security risks.This paper proposes an innovative fingerprint template protection scheme,which generates key streams through an improved fourdimensional superchaotic system(4CSCS),uses the space-filling property of Hilbert curves to achieve pixel scrambling,and introduces dynamic DNA encoding to improve encryption.Experimental results show that this scheme has a large key space 2^(528),encrypts image information entropy of more than 7.9970,and shows excellent performance in defending against statistical attacks and differential attacks.Compared with existing methods,this scheme has significant advantages in terms of encryption performance and security,and provides a reliable protection mechanism for fingerprint authentication systems in the Internet of things environment.展开更多
A device is defined as a memristor if it exhibits a pinched hysteresis loop in the current–voltage plane,and the loop area shrinks with increasing driven frequency until it gets a single-valued curve.However,the expl...A device is defined as a memristor if it exhibits a pinched hysteresis loop in the current–voltage plane,and the loop area shrinks with increasing driven frequency until it gets a single-valued curve.However,the explaination of the underlying mechanism for these fingerprints is still limited.In this paper,we propose the differential form of the memristor function,and we disclose the dynamical mechanism of the memristor according to the differential form.The symmetry of the curve is only determined by the driven signal,and the shrinking loop area results from the shrinking area enclosed by driven signal and the time coordinate axis.Significantly,we find the condition for the phase transition of a memristor,and the resistance switches between the positive resistance,local zero resistance,and local negative resistance.This phase transition is confirmed in the HP memristor.These results advance the understanding of the dynamics mechanism and phase transition of a memristor.展开更多
Fingerprint features,as unique and stable biometric identifiers,are crucial for identity verification.However,traditional centralized methods of processing these sensitive data linked to personal identity pose signifi...Fingerprint features,as unique and stable biometric identifiers,are crucial for identity verification.However,traditional centralized methods of processing these sensitive data linked to personal identity pose significant privacy risks,potentially leading to user data leakage.Federated Learning allows multiple clients to collaboratively train and optimize models without sharing raw data,effectively addressing privacy and security concerns.However,variations in fingerprint data due to factors such as region,ethnicity,sensor quality,and environmental conditions result in significant heterogeneity across clients.This heterogeneity adversely impacts the generalization ability of the global model,limiting its performance across diverse distributions.To address these challenges,we propose an Adaptive Federated Fingerprint Recognition algorithm(AFFR)based on Federated Learning.The algorithm incorporates a generalization adjustment mechanism that evaluates the generalization gap between the local models and the global model,adaptively adjusting aggregation weights to mitigate the impact of heterogeneity caused by differences in data quality and feature characteristics.Additionally,a noise mechanism is embedded in client-side training to reduce the risk of fingerprint data leakage arising from weight disclosures during model updates.Experiments conducted on three public datasets demonstrate that AFFR significantly enhances model accuracy while ensuring robust privacy protection,showcasing its strong application potential and competitiveness in heterogeneous data environments.展开更多
Fraudulent website is an important car-rier tool for telecom fraud.At present,criminals can use artificial intelligence generative content technol-ogy to quickly generate fraudulent website templates and build fraudul...Fraudulent website is an important car-rier tool for telecom fraud.At present,criminals can use artificial intelligence generative content technol-ogy to quickly generate fraudulent website templates and build fraudulent websites in batches.Accurate identification of fraudulent website will effectively re-duce the risk of public victimization.Therefore,this study developed a fraudulent website template iden-tification method based on DOM structure extraction of website fingerprint features,which solves the prob-lems of single-dimension identification,low accuracy,and the insufficient generalization ability of current fraudulent website templates.This method uses an im-proved SimHash algorithm to traverse the DOM tree of a webpage,extract website node features,calcu-late the weight of each node,and obtain the finger-print feature vector of the website through dimension-ality reduction.Finally,the random forest algorithm is used to optimize the training features for the best combination of parameters.This method automati-cally extracts fingerprint features from websites and identifies website template ownership based on these features.An experimental analysis showed that this method achieves a classification accuracy of 89.8%and demonstrates superior recognition.展开更多
基金supported by Beijing Nova Program(20240484546)the Fundamental Research Funds for the Central Public Welfare Research Institutes(No.ZZ13-YQ-049,ZXKT22001)Shaanxi Province Key R&D Program Projects(2024SF-ZDCYL-03-10).
文摘Epimedium is commonly used to treat bone injury and kidney disease,with prenylated flavonol glycosides(PFGs)as its active ingredients.It has attracted much attention due to prominent healthcare and therapeutic effects,but faces problems of adulteration with closely related species and confusion about geographical origins.In this study,multiple technical approaches were employed to identify its genetic characteristics and metabolic differences.Based on DNA barcoding,20 batches of samples were analyzed.The genetic distances of matK,ITS and psbA-trnH within species were all smaller than those between species,and psbA-trnH along with ITS+psbA-trnH proved most effective in distinguishing botanical sources.With Inter-simple sequence repeat(ISSR)technology,12 highly polymorphic and reproducible primers were selected from 21,and 189 alleles were detected.Epimedium sagittatum showed distinct genetic diversity.Samples with similar genetic distance and geographical location also tended to cluster together.Eight index components were analyzed,and their contents showed significant differences.The total content ranged from 0.50%to 7.09%,and icariin and epimedin C were identified as potential biomarkers.Integrative analysis revealed that the differences in index components were jointly driven by genetic diversity and ecological factors.Additionally,“mean temperature of driest quarter”,“precipitation seasonality”,and“temperature annual range”were identified as key environmental factors.This study provides a reliable experimental basis for the authenticity and quality evaluation of Epimedium.
基金Supported by 2023 Self-funded Research Project of the Guangxi Zhuang Autonomous Region Administration of Traditional Chinese Medicine(GXZYL20230369)2022 Internal Talent Research Project of Affiliated Hospital of Youjiang Medical University for Nationalities(Y202210319).
文摘[Objectives]To develop an HPLC fingerprint analysis method for the medicinal material of Lysimachia foenum-graecum Hance,thereby providing a foundation for its quality control.[Methods]Samples of L.foenum-graecum collected from 10 distinct locations in Guangxi were analyzed using HPLC,and chromatographic fingerprints were established.The Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine(2012 Edition)was employed for common peak calibration and similarity evaluation.Additionally,principal component analysis was performed on the common peak area data.[Results]An HPLC fingerprint of L.foenum-graecum was developed,identifying a total of 13 common peaks.Among these,four characteristic components were specifically identified:chlorogenic acid,myricetin,quercetin,and kaempferol.The kaempferol chromatographic peak,exhibiting good resolution and a stable peak shape,was selected as the reference peak.The similarity indices between the fingerprints of the 10 sample batches and the reference fingerprint ranged from 0.954 to 0.995,indicating a relatively high consistency in the chemical composition of L.foenum-graecum from different origins.Principal component analysis identified two principal components,which together accounted for 89.45%of the cumulative variance,effectively capturing the primary chemical differences among the samples.[Conclusions]The established HPLC fingerprint method is straightforward to implement,stable,reliable,and exhibits high specificity.When combined with similarity evaluation and principal component analysis,it offers a scientific basis for developing quality standards for L.foenum-graecum medicinal materials.
基金supported by the Science and Technology Talent Support Project of Hunan Province,China (2022TJ-N15)the Hunan Agricultural Science and Technology Innovation Fund,China (2024CX90 and 2024CX65)the Science and Technology Innovation Program of Hunan Province,China (2021NK1006)。
文摘High-throughput single nucleotide polymorphism(SNP) arrays have emerged as essential genotyping tools,significantly accelerating breeding programs and advancing basic research.In this study,a high-throughput 10K SNP genotyping array for wax gourd was developed using genotyping by target sequencing(GBTS),featuring 10,722 SNPs evenly distributed across all 12 chromosomes,including 278 functional loci associated with key economic traits.To demonstrate its utility,genetic distances among 19 elite inbred lines were calculated from SNP data and correlated with heterosis for single fruit weight.The results revealed that greater genetic distance was associated with higher middle parent heterosis(MPH) for single fruit weight.Furthermore,56 commercial wax gourd cultivars collected from eight regions were selected and genotyped.Population structure analysis,phylogenetic analysis,and principal component analysis(PCA) collectively indicated that these cultivars fall into two major groups.Group I,comprising black or dark green skinned wax gourds,exhibited lower genetic diversity than Group II,which includes green or light green skinned varieties,reflecting shorter genetic distances within Group I.Finally,60 polymorphic SNPs were used to construct DNA fingerprints for distinguishing the 56 cultivars.As the first high-throughput genotyping platform for wax gourd,this SNP array provides an effective and powerful tool for genetic analysis.
文摘Ganmai Dazao Decoction,originating from“Jin Gui Yao Lue”(Synopsis of the Golden Chamber),is a classical prescription for treating visceral agitation.Composed of three medicinal and edible substances-licorice(Gancao),wheat(Xiaomai),and jujube(Dazao),it functions to nourish the heart and calm the mind,harmonize the middle burner and regulate Qi,and alleviate urgency and restlessness.As its clinical application has expanded from traditional emotional disorders to neurological,endocrine,and various psychosomatic diseases,establishing a scientifically precise quality control system and deeply elucidating its pharmacodynamic material basis and mechanism of action have become critical tasks.Modern analytical methods,typified by chromatography,spectroscopy,and their hyphenated techniques,with their high sensitivity,high resolution,and powerful substance characterization capabilities,have become the core driving force for standardizing the quality control and modernizing the clinical application research of this formula.This paper systematically reviews the progress of the aforementioned analytical techniques and chemometrics in interpreting the chemical composition,establishing fingerprint profiles,controlling process quality,and researching the pharmacodynamic material basis of Ganmai Dazao Decoction.Furthermore,it discusses integrated approaches combining analytical techniques with pharmacology and clinical medicine to reveal mechanisms of action and explore therapeutic biomarkers.Finally,it provides an outlook on future directions and challenges,including technological integration and innovation,standardization of whole-process quality control systems,and evidence-based research aimed at internationalization.
基金supported by supported by the Basic Research Project of State Key Laboratory of Photovoltaic Science and Technology(No.202401020302)funding support from the National Natural Science Foundation of China(No.62274040 and No.62304046)Shanghai science and technology innovation action plan(No.24DZ3001200)。
文摘Organic-inorganic metal halides(OIMHs)have emerged as highly promising novel multifunctional optoelectronic materials,owing to their easily adjustable properties from a variety of combinations of different components.But it is still difficult and rare to realize highly tunable multicolor luminescence within the same material.In this work,we successfully incorporated three adjustable emission centers in OIMHs to synthesize a novel OIMH(NEA)_(2)MnBr_(4),with each emission center capable of emitting one of the primary colors—red,green,and blue.The green and red emissions originate from the tetrahedron and octahedron structures in the Mn-based frame,while the blue can be attributed to the contribution of organic components.Additionally,to achieve comparable emission intensity among the three primary colors,we enhanced the blue emission performance by optimizing the ratio of organic structure components and incorporating chirality in the OIMHs.The resulting high-quality films can be obtained by spin-coating method with a photoluminescence quantum yields of up to 96%.More interestingly,by the dual manipulation of excitation wavelength and temperature,the sample can be emitted at least seven distinct colors including a standard white luminescence at(0.33,0.33),opening up promising prospects for multicolor luminescence applications such as high-end anti-counterfeiting technology,light-emitting diodes,X-ray imaging,latent fingerprints,humidity detection,and so on.Therefore,based on application scenarios and requirements,our research on this highly tunable luminescent OIMH material lays a solid foundation for further development of various functional properties of related materials.
基金supported by the National Key Research and Development Program of China(No.2022YFB4300902)。
文摘Radio Frequency Fingerprint Identification(RFFI)technology provides a means of identifying spurious signals.This technology has been widely used in solving Automatic Dependent Surveillance–Broadcast(ADS-B)signal spoofing problems.However,the effects of circuit changes over time often lead to a decline in identification accuracy within open-time set.This paper proposes an ADS-B transmitter identification method to solve the degradation of identification accuracy.First,a real-time data processing system is established to receive and store ADS-B signals to meet the conditions for open-time set.The system possesses the following functionalities:data collection,data parsing,feature extraction,and identity recognition.Subsequently,a two-dimensional TimeFrequency Feature Diagram(TFFD)is proposed as a signal pre-processing method.The TFFD is constructed from the received ADS-B signal and the reconstructed signal for input to the recognition model.Finally,incorporating a frequency offset layer into the Swin Transformer architecture,a novel recognition network framework is proposed.This integration can enhance the network recognition accuracy and robustness by tailoring to the specific characteristics of ADSB signals.Experimental results indicate that the proposed recognition architecture achieves recognition accuracy of 95.86%in closed-time set and 84.33%in open-time set,surpassing other algorithms.
基金supported by Macao Science and Technology Development Fund,Macao SAR,China(Grant No.:0043/2023/AFJ)the National Natural Science Foundation of China(Grant No.:22173038)Macao Polytechnic University,Macao SAR,China(Grant No.:RP/FCA-01/2022).
文摘Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials.Traditional methods based on manually crafted features and graph-based methods have shown promising results in molecular property prediction.However,traditional methods rely on expert knowledge and often fail to capture the complex structures and interactions within molecules.Similarly,graph-based methods typically overlook the chemical structure and function hidden in molecular motifs and struggle to effectively integrate global and local molecular information.To address these limitations,we propose a novel fingerprint-enhanced hierarchical graph neural network(FH-GNN)for molecular property prediction that simultaneously learns information from hierarchical molecular graphs and fingerprints.The FH-GNN captures diverse hierarchical chemical information by applying directed message-passing neural networks(D-MPNN)on a hierarchical molecular graph that integrates atomic-level,motif-level,and graph-level information along with their relationships.Addi-tionally,we used an adaptive attention mechanism to balance the importance of hierarchical graphs and fingerprint features,creating a comprehensive molecular embedding that integrated hierarchical mo-lecular structures with domain knowledge.Experiments on eight benchmark datasets from MoleculeNet showed that FH-GNN outperformed the baseline models in both classification and regression tasks for molecular property prediction,validating its capability to comprehensively capture molecular informa-tion.By integrating molecular structure and chemical knowledge,FH-GNN provides a powerful tool for the accurate prediction of molecular properties and aids in the discovery of potential drug candidates.
基金supported by National Key Research and Development Project,China(Grant No.:2021YFA1500403).
文摘Cardiotoxicity is a critical issue in drug development that poses serious health risks,including potentially fatal arrhythmias.The human ether-à-go-go related gene(hERG)potassium channel,as one of the primary targets of cardiotoxicity,has garnered widespread attention.Traditional cardiotoxicity testing methods are expensive and time-consuming,making computational virtual screening a suitable alternative.In this study,we employed machine learning techniques utilizing molecular fingerprints and descriptors to predict the cardiotoxicity of compounds,with the aim of improving prediction accuracy and efficiency.We used four types of molecular fingerprints and descriptors combined with machine learning and deep learning algorithms,including Gaussian naive Bayes(NB),random forest(RF),support vector machine(SVM),K-nearest neighbors(KNN),eXtreme gradient boosting(XGBoost),and Transformer models,to build predictive models.Our models demonstrated advanced predictive performance.The best machine learning model,XGBoost Morgan,achieved an accuracy(ACC)value of 0.84,and the deep learning model,Transformer_Morgan,achieved the best ACC value of 0.85,showing a high ability to distinguish between toxic and non-toxic compounds.On an external independent validation set,it achieved the best area under the curve(AUC)value of 0.93,surpassing ADMETlab3.0,Cardpred,and CardioDPi.In addition,we explored the integration of molecular descriptors and fingerprints to enhance model performance and found that ensemble methods,such as voting and stacking,provided slight improvements in model stability.Furthermore,the SHapley Additive exPlanations(SHAP)explanations revealed the relationship between benzene rings,fluorine-containing groups,NH groups,oxygen in ether groups,and cardiotoxicity,highlighting the importance of these features.This study not only improved the predictive accuracy of cardiotoxicity models but also promoted a more reliable and scientifically interpretable method for drug safety assessment.Using computational methods,this study facilitates a more efficient drug development process,reduces costs,and improves the safety of new drug candidates,ultimately benefiting medical and public health.
文摘To further advance the development of the fluorescent dyes for latent fingerprint imaging,two triphenylamine-based Schiff base compounds containing a benzimidazole group(TPA-BZI)and a phenyl unit(TPA-Ph)were designed and synthesized.Photoluminescence experiments revealed that both compounds exhibited solvatochromism and intramolecular charge transfer(ICT)characteristics in six organic solvents.Additionally,they showed aggregation-induced emission(AIE)in CH_(3)OH/water mixtures and solid-state fluorescence.These phenomena were further elucidated through time-dependent density functional theory(TD-DFT)calculations.It was also found that the two compounds could be used for latent fingerprints imaging,and could easily distinguish the details of fingerprints from Ⅰ to Ⅲ levels,which could provide the preliminary evidence to match personal identification.
文摘DNA testing for biological relationships is becoming increasingly common in Burkina Faso. STR analysis remains the most reliable technique for resolving disputes or claims in court regarding biological relationships. This study aimed to establish the links of biological relationships between subjects by analyzing 21 STR loci. The participants were 14 individuals referred to CERBA by the Justice in 2022. Oral or blood samples were taken for each subject. DNA was extracted, and the analysis of DNA polymorphism by PowerPlex® 21 Kit (Part No. DC8902) was performed by capillary electrophoresis on the ABI PRISM 3130 sequencer. DNA profiles were compiled using the GeneMapper IDX software version 1.2. Of the fourteen subjects examined, twelve of these samples had complete genetic profiles, while the other two had partial and absent profiles. The results confirmed the inclusion of three cases of Paternity, one case of maternity, one case of a relationship of brotherhood, and the exclusion of one case of maternity and one case of a relationship of brotherhood. DNA tests improve the resolution of filiations, but they require ethical and cultural awareness and a strengthened legal framework to prevent and protect society.
基金the financial support from National Natural Science Foundation of China(No.51703135)the technical support from Beijing Key Laboratory of Optical Materials and Photonic Devices。
文摘Fluorescence-based imaging applications have been benefiting greatly from donor-acceptor(D-A)/donor-π-acceptor(D-π-A)fluorescent probes owing to their intramolecular charge transfer(ICT)nature and self-assembly behavior.In this study,we design and synthesize a hydrophilic D-A fluorescent probe,namely CHBA,which would self-assemble into interlaced textures down to nanoscale but disassemble by trace amount of water in fingertip area.Upon finger-pressing,it enables fingerprint imaging and covers level-1/2/3 fingerprint information,wherein the sweat pores can be mapped in both bright field model and fluorescence mode,capable of naked-eye-based similarity analysis for personal identity verification(PIV).Spectroscopic analysis and morphology study show that the working mechanism can be attributed to the selective water-erosion effect on the solid-liquid interphase under physical contact.The sweat pore information can be digitized by polar coordinate conversion,further allowing machine-learning-based analysis for PIV application.The final PIV accuracy reaches 100%for all the involved machine-learning models,with no erroneous judgements.A prototype of PIV system is constructed by integrating CHBA with artificial intelligence hardware,wherein the sweat pore imaging,data processing and the decisionmaking could be run in parallel,suggesting high feasibility in real-world application.
基金supported in part by the National Key Research and Development Program under Grant(2021YFB2900300)by the National Natural Science Foundation of China(NSFC)under Grants 61971127,61871122by the Southeast University-China Mobile Research Institute Joint Innovation Center,and by the Major Key Project of PCL(PCL2021A01-2).
文摘This paper investigates how to achieve integrated sensing and communication(ISAC)based on a cell-free radio access network(CF-RAN)architecture with a minimum footprint of communication resources.We propose a new passive sensing scheme.The scheme is based on the radio frequency(RF)fingerprint learning of the RF radio unit(RRU)to build an RF fingerprint library of RRUs.The source RRU is identified by comparing the RF fingerprints carried by the signal at the receiver side.The receiver extracts the channel parameters from the signal and estimates the channel environment,thus locating the reflectors in the environment.The proposed scheme can effectively solve the problem of interference between signals in the same time-frequency domain but in different spatial domains when multiple RRUs jointly serve users in CF-RAN architecture.Simulation results show that the proposed passive ISAC scheme can effectively detect reflector location information in the environment without degrading the communication performance.
文摘A leading position in the areas of testing,instrumentation and machine control has been established by members of the British Textile Machinery Association(BTMA)and a number of new developments in these fields will be showcased at this year’s ITMA Asia+CITME exhibition,which takes place in Singapore from October 28-31.“Many of our members are currently developing new technologies,either in-house or increasingly through joint projects,and there will be much to reveal by the time of ITMA Asia in Singapore,”says BTMA CEO Jason Kent.“Some of the most recent developments are really going beyond what has previously been possible.”
文摘The integration of phytochemistry into forensic science has emerged as a groundbreaking frontier,providing unprecedented insights into nature's secrets through the precise application of phytochemical fingerprinting of phytotoxins as a cutting-edge approach.This study explores the dynamic intersection of phytochemistry and forensic science,highlighting how the unique phytochemical profiles of toxic plants and their secondary metabolites,serve as distinctive markers for forensic investigations.By utilizing advanced techniques such as Ultra-High-Performance Liquid Chromatography(UHPLC)and High-Resolution Mass Spectrometry(HRMS),the detection and quantification of plant-derived are made more accurate in forensic contexts.Real-world case studies are presented to demonstrate the critical role of plant toxins in forensic outcomes and legal proceedings.The challenges,potential,and future prospects of integrating phytochemical fingerprinting of plant toxins into forensic science were discussed.This review aims to illuminate phytochemical fingerprinting of plant toxins as a promising tool to enhance the precision and depth of forensic analyses,offering new insights into the complex stories embedded in plant toxins.
基金supported by the Modern Agro-industry Technology Research System(CARS-45-KXJ19)the Agricultural Science and Technology Innovation Program from the Ministry of Agriculture of the People’s Republic of China(CAAS-ASTIP-2019-IAR)。
文摘Terpenoids,as crucial plant secondary metabolites in honey,possess various bioactivities.This study aimed at investigating terpenoids of longan,litchi,and schefflera honey.Our results reveal that these three species of honey are characterized by abundant terpenoids,with eight terpenoids and one phenylpropanoid identified.Callunene,3,4,5-trimethoxyphenylpropanal,schefflerin(4-2'-(3',4'-dihydroxy-5'-methylfuran)-3,5,5-trimethyl-2-cyclohexenone)or abscisic acids may be as the characteristic components of longan,litchi,or schefflera honey.Abscisic acids were the most abundant components,average contents reached up to 53.67,96.89 and 21.11 mg/kg,respectively,and the content ranges in three types of honey were 13.75-85.40,19.93-177.31,14.69-28.38 mg/kg,respectively.To our knowledge,the presence of schefflerin,(6R,9S)-vomifoliol,and 3,4,5-trimethoxyphenylpropanal in honey is a novel finding.We distinguish Thailand from Chinese mainland and Taiwan longan honeys,based on the ratio of abscisic acid and callunene content.Overall,our proposal to combine terpenoids with standard fingerprints seems to provide a novel and reliable solution for evaluating the authenticity of commercial honey.
基金supported by the National Natural Science Foundation of China(No.51827803)the Fundamental Research Funds for the Central Universities,111 Center(No.B20001)Institutional Research Fund from Sichuan University(No.2021SCUNL201).
文摘Generally,gaining fundamental insights into chain processes during the combustion of flame-retardant polymers relies on the qualitative and quantitative characterization of key chain carriers.However,polymer combustion processes based on conventional solid-fuel combustion strategies,due to the high coupling of pyrolysis,combustion,soot formation and oxidation,exhibit relatively high complexity and poor flame stability,and lead to a huge obstacle to the use of optical diagnostics.Herein,a spatial-confinement combustion strategy,which can produce a special staged flame with multi-jets secondary wave,is devised to provide a highly decoupled combustion environment.Glowing soot particles are therefore decoupled from main chemiluminescence region and confined to the flame tip to provide a well-controlled,opticalthin test environment for combustion diagnostic.Based on this strategy,a multi-nozzle-separation(MNS)burner is designed and fabricated,and the combustion processes associated with four model compounds,PVC,PS,PP/TBBA blends and PP/RP blends are investigated by spontaneous spectral diagnosis,and the chemiluminescence fingerprint of key diatomic/triatomic intermediates(such as OH,CH,C_(2),ClO,Br_(2),and PHO)are clearly observed.This encouraging result means that the strategy of spatial-confinement combustion we proposed shows promising prospect in many subjects associated with combustion chain regulation,such as efficient design of flame retardants.
文摘With the rapid development of Internet of things technology,the efficiency of data transmission between devices has been significantly improved.However,the open network environment also poses serious security risks.This paper proposes an innovative fingerprint template protection scheme,which generates key streams through an improved fourdimensional superchaotic system(4CSCS),uses the space-filling property of Hilbert curves to achieve pixel scrambling,and introduces dynamic DNA encoding to improve encryption.Experimental results show that this scheme has a large key space 2^(528),encrypts image information entropy of more than 7.9970,and shows excellent performance in defending against statistical attacks and differential attacks.Compared with existing methods,this scheme has significant advantages in terms of encryption performance and security,and provides a reliable protection mechanism for fingerprint authentication systems in the Internet of things environment.
基金supported by the National Natural Science Foundation of China under Grant Nos.62071496,62061008the Research and Innovation Project of Graduate of Central South University under Grant No.2023ZZTS0168.
文摘A device is defined as a memristor if it exhibits a pinched hysteresis loop in the current–voltage plane,and the loop area shrinks with increasing driven frequency until it gets a single-valued curve.However,the explaination of the underlying mechanism for these fingerprints is still limited.In this paper,we propose the differential form of the memristor function,and we disclose the dynamical mechanism of the memristor according to the differential form.The symmetry of the curve is only determined by the driven signal,and the shrinking loop area results from the shrinking area enclosed by driven signal and the time coordinate axis.Significantly,we find the condition for the phase transition of a memristor,and the resistance switches between the positive resistance,local zero resistance,and local negative resistance.This phase transition is confirmed in the HP memristor.These results advance the understanding of the dynamics mechanism and phase transition of a memristor.
基金supported by the National Natural Science Foundation of China(Nos.62002100,61902237)Key Research and Promotion Projects of Henan Province(Nos.232102240023,232102210063,222102210040).
文摘Fingerprint features,as unique and stable biometric identifiers,are crucial for identity verification.However,traditional centralized methods of processing these sensitive data linked to personal identity pose significant privacy risks,potentially leading to user data leakage.Federated Learning allows multiple clients to collaboratively train and optimize models without sharing raw data,effectively addressing privacy and security concerns.However,variations in fingerprint data due to factors such as region,ethnicity,sensor quality,and environmental conditions result in significant heterogeneity across clients.This heterogeneity adversely impacts the generalization ability of the global model,limiting its performance across diverse distributions.To address these challenges,we propose an Adaptive Federated Fingerprint Recognition algorithm(AFFR)based on Federated Learning.The algorithm incorporates a generalization adjustment mechanism that evaluates the generalization gap between the local models and the global model,adaptively adjusting aggregation weights to mitigate the impact of heterogeneity caused by differences in data quality and feature characteristics.Additionally,a noise mechanism is embedded in client-side training to reduce the risk of fingerprint data leakage arising from weight disclosures during model updates.Experiments conducted on three public datasets demonstrate that AFFR significantly enhances model accuracy while ensuring robust privacy protection,showcasing its strong application potential and competitiveness in heterogeneous data environments.
基金This research is a phased achievement of The National Social Science Fund of China(23BGL272).
文摘Fraudulent website is an important car-rier tool for telecom fraud.At present,criminals can use artificial intelligence generative content technol-ogy to quickly generate fraudulent website templates and build fraudulent websites in batches.Accurate identification of fraudulent website will effectively re-duce the risk of public victimization.Therefore,this study developed a fraudulent website template iden-tification method based on DOM structure extraction of website fingerprint features,which solves the prob-lems of single-dimension identification,low accuracy,and the insufficient generalization ability of current fraudulent website templates.This method uses an im-proved SimHash algorithm to traverse the DOM tree of a webpage,extract website node features,calcu-late the weight of each node,and obtain the finger-print feature vector of the website through dimension-ality reduction.Finally,the random forest algorithm is used to optimize the training features for the best combination of parameters.This method automati-cally extracts fingerprint features from websites and identifies website template ownership based on these features.An experimental analysis showed that this method achieves a classification accuracy of 89.8%and demonstrates superior recognition.
