Geographical origin identification of winter jujube(Ziziphus jujuba Dongzao')by using multi-element fingerprinting with chemometrics

Winter jujube(Ziziphus jujuba'Dongzao')is greatly appreciated by consumers for its excellent quality,but brand infringement frequently occurs in the market.Here,we first determined a total of 38 elements in 167 winter jujube samples from the main winter jujube producing areas of China by inductively coupled plasma mass spectrometer(ICP-MS).As a result,16 elements(Mg,K,Mn,Cu,Zn,Mo,Ba,Be,As,Se,Cd,Sb,Ce,Er,Tl,and Pb)exhibited significant differences in samples from different producing areas.Supervised linear discriminant analysis(LDA)and orthogonal projection to latent structures discriminant analysis(OPLS-DA)showed better performance in identifying the origin of samples than unsupervised principal component analysis(PCA).LDA and OPLS-DA had a mean identification accuracy of 87.84 and 94.64%in the testing set,respectively.By using the multilayer perceptron(MLP)and C5.0,the prediction accuracy of the models could reach 96.36 and 91.06%,respectively.Based on the above four chemometric methods,Cd,Tl,Mo and Se were selected as the main variables and principal markers for the origin identification of winter jujube.Overall,this study demonstrates that it is practical and precise to identify the origin of winter jujube through multi-element fingerprint analysis with chemometrics,and may also provide reference for establishing the origin traceability system of other fruits.

A UWB/IMU-Assisted Fingerprinting Localization Framework with Low Human Efforts

With the rapid development of smart phone,the location-based services(LBS)have received great attention in the past decades.Owing to the widespread use of WiFi and Bluetooth devices,Received Signal Strength Indication(RSSI)fingerprintbased localization method has obtained much development in both academia and industries.In this work,we introduce an efficient way to reduce the labor-intensive site survey process,which uses an UWB/IMU-assisted fingerprint construction(UAFC)and localization framework based on the principle of Automatic radio map generation scheme(ARMGS)is proposed to replace the traditional manual measurement.To be specific,UWB devices are employed to estimate the coordinates when the collector is moved in a reference point(RP).An anchor self-localization method is investigated to further reduce manual measurement work in a wide and complex environment,which is also a grueling,time-consuming process that is lead to artificial errors.Moreover,the measurements of IMU are incorporated into the UWB localization algorithm and improve the label accuracy in fingerprint.In addition,the weighted k-nearest neighbor(WKNN)algorithm is applied to online localization phase.Finally,filed experiments are carried out and the results confirm the effectiveness of the proposed approach.

CMAES-WFD:Adversarial Website Fingerprinting Defense Based on Covariance Matrix Adaptation Evolution Strategy

Website fingerprinting,also known asWF,is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination,even when using the Tor anonymity network.While advanced attacks based on deep neural network(DNN)can performfeature engineering and attain accuracy rates of over 98%,research has demonstrated thatDNNis vulnerable to adversarial samples.As a result,many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success.However,these methods suffer from high bandwidth overhead or require access to the target model,which is unrealistic.This paper proposes CMAES-WFD,a black-box WF defense based on adversarial samples.The process of generating adversarial examples is transformed into a constrained optimization problem solved by utilizing the Covariance Matrix Adaptation Evolution Strategy(CMAES)optimization algorithm.Perturbations are injected into the local parts of the original traffic to control bandwidth overhead.According to the experiment results,CMAES-WFD was able to significantly decrease the accuracy of Deep Fingerprinting(DF)and VarCnn to below 8.3%and the bandwidth overhead to a maximum of only 14.6%and 20.5%,respectively.Specially,for Automated Website Fingerprinting(AWF)with simple structure,CMAES-WFD reduced the classification accuracy to only 6.7%and the bandwidth overhead to less than 7.4%.Moreover,it was demonstrated that CMAES-WFD was robust against adversarial training to a certain extent.

Certis: Cloud Asset Management & Threat Evaluation Using Behavioral Fingerprinting at Application Layer

This paper introduces Certis, a powerful framework that addresses the challenges of cloud asset tracking, management, and threat detection in modern cybersecurity landscapes. It enhances asset identification and anomaly detection through SSL certificate parsing, cloud service provider integration, and advanced fingerprinting techniques like JARM at the application layer. Current work will focus on cross-layer malicious behavior identification to further enhance its capabilities, including minimizing false positives through AI-based learning techniques. Certis promises to offer a powerful solution for organizations seeking proactive cybersecurity defenses in the face of evolving threats.

Improving Optimal Fingerprinting Methods Requires a Viewpoint beyond Statistical Science

While being successful in the detection and attribution of climate change,the optimal fingerprinting method(OFM)may have some limitations from a physics-and-dynamics-based viewpoint.Here,an analysis is made on the linearity,noninteraction,and stationary-variability assumptions adopted by OFM.It is suggested that furthering OFM needs a viewpoint beyond statistical science,and the method should be combined with theoretical tools in the dynamics and physics of the Earth system,so as to be applied for the detection and attribution of nonlinear climate change including tipping elements within the Earth system.

The significance of metabolic fingerprinting in carcinogenesis

Carcinogenesis describes the process through which normal cells transform into malignant cells(cancer).There were an estimated 18.1 million new cases of cancer(all cancers combined excluding non-melanoma skin cancer)worldwide in 2020:8.8 million(48%)in females and 9.3 million(52%)in males,giving a male:female ratio of 10:9.5.It may be initiated by the action of biological,physical,or chemical agents that cause a non-lethal,permanent,DNA error on the cell with a consequence of altered cell metabolism.This altered cell metabolism include the Warburg effect,altered lipid and amino acid metabolism and production of various metabolites.It also results in unique metabolic dependencies that,in some cases,can be targeted with precision medicine and nutrition,including drugs that selectively target metabolic enzymes.Metabolic fingerprinting has been applied to the study of carcinogenesis and is particularly helpful in early diagnosis,staging and choice of treatment,thus improving health outcomes.This technology could therefore be harnessed effectively while combining with other omics technologies.

Plastid Inheritance in Sweet Potato as Revealed by DNA Restriction Fingerprinting

The inheritance of chloroplast DNA (cpDNA) in sweet potato (Ipomoea batatas Lain.) was analyzed using DNA restriction fingerprinting. The cpDNA fingerprints of hybrids from reciprocal crosses between Xushu18 and AB78-1 were found to be identical to those of their female parents, which reveals that cpDNA of sweet potato is maternally inherited in this intervarietal crossing. This maternal cpDNA transmission pattern does not accord with the putative one based on former cytological studies. The plastid inheritance in Convolvulaceae has been briefly reviewed in this study, and the utility of DNA restriction fingerprinting analysis in the study of plastid inheritance is also discussed.

WEIGHTED ALGORITHM FOR FINGERPRINTING RELATIONAL DATABASES

The necessity and the feasibility of introducing attribute weight into digital fingerprinting system are given. The weighted algorithm for fingerprinting relational databases of traitor tracing is proposed. Higher weights are assigned to more significant attributes, so important attributes are more frequently fingerprinted than other ones. Finally, the robustness of the proposed algorithm, such as performance against collusion attacks, is analyzed. Experimental results prove the superiority of the algorithm.

A Molecular Approach to Identification of the Chinese Drug“pu Gong Ying”(Herba Taraxaci)and Six Adulterants byDNA Fingerprinting Using Random Primed PolymeraseChain Resaction(PCR)

DNA fingerprinting among members of the Chinese drug Pu Gong Ying(Taraxacum mongolicum Hand,-Mazz.)and six adulterants of Tu Gong Ying were demonstrated with random-primed polymerase chain reaction(PCR)including arbitrarily primed polymerase chain reaction(AP-PCR)and random amplified polymorphic DNA(RAPD).Distinctive,reproducible genomic fingerprints from DNA from 7 species belonged to Compositae were generated with two long(20 and 24 mer)and one short(10 mer)randomly chosen primers.The Pu Gong Ying can be differentiated from six species of Tu Gong Ying according to the banding pattems of their amplified DNA on agarose gels.The results showed that AP-PCR and RAPD methods can be used for identifying Chinese drugs.Moreover,the Similarity Indexes of the genomic DNA fingerprints showed that Pu Gong Ying and its adulterants are unrelated.Therefore,AP-PCR and RAPD methods can be used for identifying Chinese drugs.

SSR fingerprinting of 203 sweetpotato (Ipomoea batatas (L.) Lam.) varieties

Simple sequence repeat （SSR） markers have been shown to be a powerful tool for varieties identification in plants. How- ever, SSR fingerprinting of sweetpotato varieties has been a little reported. In this study, a total of 1 294 SSIR primer pairs, including 1 215 genomic-SSR and 79 expressed sequence tag （EST）-SSR primer pairs, were screened with sweetpotato varieties Zhengshu 20 and Luoxushu 8 and their 2 F1 individuals randomly sampled, and 273 and 38 of them generated polymorphic bands, respectively. Four genomic-SSR and 3 EST-SSR primer pairs, which showed good polymorphism, were selected to amplify 203 sweetpotato varieties and gave a total of 172 bands, 85 （49.42%） of which were polymorphic. All of the 203 sweetpotato varieties showed unique fingerprint patterns, indicating the utility of SSR markers in variety iden- tification of this crop. Polymorphism information content （PIC） ranged from 0.5824 to 0.9322 with an average of 0.8176. SSR-based genetic distances varied from 0.0118 to 0.6353 with an average of 0.3100 among these varieties. Thus, these sweetpotato varieties exhibited high levels of genetic similarity and had distinct fingerprint profiles. The SSR fingerprints of the 203 sweetpotato varieties have been successfully constructed. The highly polymorphic SSR primer pairs developed in this study have the potential to be used as core primer pairs for variety identification, genetic diversity assessment and linkage map construction in sweetpotato and other plants.

Identification of Porphyra lines using computerized DNA fingerprinting

RAPD (Randomly Amplified Polymorphic DNA) analysis was performed with filaments of 15 Porphyra lines representing four important groups (P. yezoensis, P. haitanensis, P. katadai var. Hemiphylla and P. digospermatangia). Eight stable and repeatable RAPD bands amplified with two primers, OPN-02 and OPJ-18, were selected for the construction of DNA fingerprinting. The RAPD results were scored based on the presence or absence of each of the 8 bands and then converted to computer language expressed with two digitals, 1 and 0, which represented the presence (numbered as 1) or absence (numbered as 0) of each band, respectively. Based on these results, a model DNA fingerprint and a computerized DNA fingerprint were constructed. In the constructed DNA fingerprint, each Porphyra line has its unique fingerprinting pattern and can be easily distinguished from each other. Later, a software, named as PhGI, was designed based on this DNA fingerprinting. It can be used in practical Porphyra line identification.

Authentication of Cassia seeds on the basis of two-wavelength HPLC fingerprinting with the use of chemometrics

High performance liquid chromatographic(HPLC) fingerprints of Cassia seed,a traditional Chinese medicine(TCM),were developed by means of the chromatograms at two wavelengths of 238 and 282 nm.Then,the two data sets were combined into one matrix.The application of principal component analysis(PCA) for this data matrix showed that the samples were clustered into four groups in accordance with the plant sources and preparation procedures.Furthermore,partial least squares(PLS),back propagation artificial neural...

AFLP Fingerprinting and Genetic Diversity of Main Sweetpotato Varieties in China

AFLP fingerprinting of the 98 main sweetpotato varieties planted in China has been constructed. Using 17 AFLP primer combinations which were selected from 1 208 primer combinations and generated the most amounts of polymorphic bands, AFLP analysis of the 98 main sweetpotato varieties gave a total of 410 clear polymorphic bands with an average of 24.12 polymorphic bands per primer combination. Each one of the 98 sweetpotato varieties could be clearly distinguished by EcoR I-cta/Mse I-ggc primer combination which generated the most polymorphic bands. AFLP-based genetic distance ranged from 0.0546 to 0.5709 with an average of 0.3799. The dendrogram based on AFLP markers indicated that sweetpotato varieties coming from the same regions or having same parents were clustered in the same groups. Analysis of molecular variance （AMOVA） revealed greater variations within regions （94.08%） than among regions （5.92%）. Thus, the genetic variations mainly existed within regions, while the variations among regions were very low in the tested sweetpotato varieties. Significant genetic variations existed between ＂Northern＂ and ＂Southern＂ sweetpotato varieties when Yangtze River was used as the dividing line.

Quantification of total phenol,flavonoid content and pharmacognostical evaluation including HPTLC fingerprinting for the standardization of Piper nigrum Linn fruits

Objective:To carry out the physicochemical and phytochemical standardization with high performance thin layer chromatography fingerprinting of Piper nigrum L.(P.nigrum)fruits in order to ascertain the standard pharmacognostical parameters of this king of spices.Methods:Many standardization parameters like extractive values,total ash value,water soluble ash value and acid insoluble ash,moisture content,loss on drying and pH values of P.nigrum L.fruits were analyzed.The method of Harborne was adopted for the preliminary phytochemicals screening.Analysis of total phenolic and flavonoid contents,pesticides residues,aflatoxin and heavy metals were also performed.CAMAG-high performance thin layer chromatography system was used for fingerprinting of methanolic extract of P.nigrum L.fruits.Results:The results of phytochemicals testing indicated the presence of carbohydrates,phenolic compounds,flavonoids,alkaloids,proteins,saponins,lipids,sterols and tannins in various solvent extracts.Total phenolic and flavonoid contents in methanolic extract were found to be 1.728 1 mg/g and 1.087 ug/g,respectively.Heavy metals concentrations were found to be within standard limits.Aflatoxins and pesticides residues were absent.Conclusions:The outcome of this study might prove beneficial in herbal industries for identification,purification and standardization of P.nigrum L.fruits.

Chromatographic fingerprinting and quantitative analysis for the quality evaluation of Xinkeshu tablet

A simple, sensitive and accurate method based on high performance liquid chromato- graphy （HPLC） with diode array detector （DAD） was developed and validated for systematic quality evaluation of one type of traditional Chinese medicine preparations named Xinkeshu （XKS） tablet. In this study, the chromatographic fingerprints of XKS tablet were developed first, 23 peaks were selected as the common peaks to evaluate the similarities among different batches of XKS samples, which were manufactured in a long time span of three years. Additionally, simultaneous quantification of six markers in XKS tablet, including Danshensu, Protocatechuic aldehyde, Puerarin, Daidzin, Salvianolic acid B and Daidzein, was performed. The validation results showed that the developed method was specific, accurate, precise and robust. The preliminary explanation on why a close similarity between fingerprints did not exactly mean similar contents of chemical components in samples was given. The contribution of each chromatographic peak to similarity was also evaluated. The developed method offers an efficient, reliable and practical approach for systematic quality evaluation of XKS tablet.

Bohai crude oil identification by gas chromatogram fingerprinting quantitative analysis coupled with cluster analysis

By gas chromatogram, six crude oils fingerprinting distributed in four oilfields and four oil platforms were analyzed and the corre- sponding normal paraffin hydrocarbon （ including pristane and phytane） concentration was obtained by the internal standard methed. The normal paraffin hydrocarbon distribution patterns of six crude oils were built and compared. The cluster analysis on the normal paraffin hydrocarbon concentration was conducted for classification and some ratios of oils were used for oils comparison. The results indicated： there was a clear difference within different crude oils in different oil fields and a small difference between the crude oils in the same oil platform. The normal paraffin hydrocarbon distribution pattern and ratios, as well as the cluster analysis on the nomad paraffin hydrocarbon concentration can have a better differentiation result for the crude oils with small difference than the original gas chromatogram.

Fingerprinting 146 Chinese chestnut(Castanea mollissima Blume)accessions and selecting a core collection using SSR markers

Chinese chestnut is an important nut tree around the world.Although the types of Chinese chestnut resources are abundant,resource utilization and protection of chestnut accessions are still very limited.Here,we fingerprinted and determined the genetic relationships and core collections of Chinese chestnuts using 18 fluorescently labeled SSR markers generated from 146 chestnut accessions.Our analyses showed that these markers from the tested accessions are highly polymorphic,with an average allele number(N_(a))and polymorphic information content(PIC)of 8.100 and 0.622 per locus,respectively.Using these strongly distinguishing markers,we successfully constructed unique fingerprints for 146 chestnut accessions and selected seven of the SSR markers as core markers to rapidly distinguish different accessions.Our exploration of the genetic relationships among the five cultivar groups indicated that Chinese chestnut accessions are divided into three regional type groups:group I(North China(NC)and Northwest China(NWC)cultivar groups),group II(middle and lower reaches of the Yangtze River(MLY)cultivar group)and group III(Southeast China(SEC)and Southwest China(SWC)cultivar groups).Finally,we selected 45 core collection members which represent the most genetic diversity of Chinese chestnut accessions.This study provides valuable information for identifying chestnut accessions and understanding the phylogenetic relationships among cultivar groups,which can serve as the basis for efficient breeding in the future.

A preliminary study on fingerprinting approach in marine sediment dynamics with the rare earth elements

Locating the quantitized natural sediment fingerprints is an important work for marine sediment dynamics study.The total of 146 sediment samples were collected from the Shelf of the East China Sea and five rivers,including Huanghe （Yellow）,Changjiang （Yangtze）,Qiantang,Ou and Min River.The sediment grain size and the contents of rare earth elements （REEs） were measured with laser particle size analyzer and ICP-MS technology.The results show that absolute REE content （ΣREE） and the concentration ratio of light REEs to heavy REEs （L/HREE） are different in the sediments among those rivers.There are higher REE contents in being less than 2 m and 2–31 μm fractions in the Changjiang Estuary surface sediments.The REE contents of bulk sediment are dominated by the corresponding values of those leading size-fractions.REE of sediment is higher close to the estuaries and declines seaward on the inner shelf of the East China Sea （ECS）.The L/HREE ratio has a tendency of increase southward from 28 ？ N.Hydrodynamic conditions plays a predominate role on spacial distributions of the surficial sediment’s REE parameters.In some situations,the currents tend to remove the coarser light grains from initial populations,as well as the deposit of the finer heavy mineral grains.In other situations,the currents will change the ratio of sediment constituents,such as ratio between silts and clays in the sediments.As a result,the various values of REE or L/HREE ratio in different bulk sediments are more affected by the change of size-fractions than source location.Under the long-term stable hydrodynamic environment,i.e.,the East China Sea Shelf,new sediment transport model based on the size and density gradation concept may help to understand the spatial distribution patterns of REE parameters.

Science Letters:Serum protein fingerprinting coupled with artificial neural network distinguishes glioma from healthy population or brain benign tumor

To screen and evaluate protein biomarkers for the detection of gliomas (Astrocytoma grade Ⅰ-Ⅳ) from healthy individuals and gliomas from brain benign tumors by using surface enhanced laser desorption/ionization time of flight mass spectrometry (SELDI-TOF-MS) coupled with an artificial neural network (ANN) algorithm. SELDI-TOF-MS protein fingerprinting of serum from 105 brain tumor patients and healthy individuals, included 28 patients with glioma (Astrocytoma Ⅰ-Ⅳ), 37 patients with brain benign tumor, and 40 age-matched healthy individuals. Two thirds of the total samples of every compared pair as training set were used to set up discriminating patterns, and one third of total samples of every compared pair as test set were used to cross-validate; simultaneously, discriminate-cluster analysis derived SPSS 10.0 software was used to compare Astrocytoma grade Ⅰ-Ⅱ with grade Ⅲ-Ⅳ ones. An accuracy of 95.7%, sensitivity of 88.9%, specificity of 100%, positive predictive value of 90% and negative predictive value of 100% were obtained in a blinded test set comparing gliomas patients with healthy individuals; an accuracy of 86.4%, sensitivity of 88.9%, specificity of 84.6%, positive predictive value of 90% and negative predictive value of 85.7% were obtained when patient's gliomas was compared with benign brain tumor. Total accuracy of 85.7%, accuracy of grade Ⅰ-Ⅱ Astrocytoma was 86.7%, accuracy ofⅢ-Ⅳ Astrocytoma was 84.6% were obtained when grade Ⅰ-Ⅱ Astrocytoma was compared with grade Ⅲ-Ⅳ ones (discriminant analysis). SELDI-TOF-MS combined with bioinformatics tools, could greatly facilitate the discovery of better biomarkers. The high sensitivity and specificity achieved by the use of selected biomarkers showed great potential application for the discrimination of gliomas patients from healthy individuals and glioma from brain benign tumors.

Comparison of DUS testing and SNP fingerprinting for variety identification in cucumber

Variety identification plays an important role in protecting the intellectual property of varieties,ensuring seed quality,and encouraging breeding innovation.Currently,morphological evaluation in the field,such as distinctness,uniformity,and stability(DUS)testing,and DNA fingerprinting in the laboratory using molecular markers are two dominant methods used for variety identification.Few studies have compared the results of these approaches,and the relationship between the two methods is obscure.In this study,134 dominant cucumber varieties were evaluated using 50 DUS testing traits and genotyped by 40 single nucleotide polymorphisms(SNPs).The 40 SNPs were developed in our previous study and arewell suited for variety identification.In the DUS testing,significant positive or negative correlations among 50 DUS traits were observed,and 20 core traits,including 15 fruit traits,were further selected to increase field inspection efficiency.This suggested that fruit shape plays an important role in variety identification.The ratio of fruit length/diameter was themost important trait,explaining 9.2%of the phenotypic variation.In the DNA fingerprinting test,the 40 SNPs were highly polymorphic and could distinguish all of the 134 cucumber varieties,and 14 core SNPs were selected to improve the identification rate.Interestingly,the population structure analysis of 134 cucumber varieties by phenotypic data in the DUS test was in accordance with the genotypic data from the DNA fingerprinting,indicating that all varieties could be divided into the same four subgroups:European type,North China type,South China type,and hybrids of the North China and South China types.Moreover,linear correlativity of distinguishment for each pair of varieties was observed between the DUS test and the DNA fingerprinting.These results indicated that these two methods have good application in future research,especially for the scaled-up analysis of hundreds of varieties.