Ensuring food safety is paramount worldwide.Developing effective detection methods to ensure food safety can be challenging owing to trace hazards,long detection time,and resource-poor sites,in addition to the matrix ...Ensuring food safety is paramount worldwide.Developing effective detection methods to ensure food safety can be challenging owing to trace hazards,long detection time,and resource-poor sites,in addition to the matrix effects of food.Personal glucose meter(PGM),a classic point-of-care testing device,possesses unique application advantages,demonstrating promise in food safety.Currently,many studies have used PGM-based biosensors and signal amplification technologies to achieve sensitive and specific detection of food hazards.Signal amplification technologies have the potential to greatly improve the analytical performance and integration of PGMs with biosensors,which is crucial for solving the challenges associated with the use of PGMs for food safety analysis.This review introduces the basic detection principle of a PGM-based sensing strategy,which consists of three key factors:target recognition,signal transduction,and signal output.Representative studies of existing PGM-based sensing strategies combined with various signal amplification technologies(nanomaterial-loaded multienzyme labeling,nucleic acid reaction,DNAzyme catalysis,responsive nanomaterial encapsulation,and others)in the field of food safety detection are reviewed.Future perspectives and potential opportunities and challenges associated with PGMs in the field of food safety are discussed.Despite the need for complex sample preparation and the lack of standardization in the field,using PGMs in combination with signal amplification technology shows promise as a rapid and cost-effective method for food safety hazard analysis.展开更多
AIM:To establish the more feasible and sensitive assessment approach to the detection of adefovir (ADV) resistance-associated hepatitis B virus (HBV) quasispecies.METHODS: Based on the characteristics of rtA181V/T and...AIM:To establish the more feasible and sensitive assessment approach to the detection of adefovir (ADV) resistance-associated hepatitis B virus (HBV) quasispecies.METHODS: Based on the characteristics of rtA181V/T and rtN236T mutations, a new approach based on real-time fluorescent quantitative polymerase chain reaction (RT-PCR) was established for the detection of ADV-resistant HBV quasispecies, total HBV DNA, rtA181 and rtN236 mutations in blood samples from 32 chronic hepatitis B (CHB) patients with unsatisfactory curative effect on ADV and compared with routine HBV DNA sequencing.RESULTS: Both the sensitivity and specificity of this new detection approach to ADV-resistant HBV quasispecies were 100%, which were much higher than those of direct HBV DNA sequencing. The approach was able to detect 0.1% of mutated strains in a total plasmid population. Among the 32 clinical patients, single rtA181 and rtN236T mutation and double rtA181T and rtN236T mutations were detected in 20 and 8, respectively, while ADV-resistant mutations in 6 (including, rtA181V/T mutation alone in 5 patients) and no associated mutations in 26.CONCLUSION: This new approach is more feasible and efficient to detect ADV-resistant mutants of HBV and ADV-resistant mutations before and during ADV treatment with a specificity of 100% and a sensitivity of 100%.展开更多
Objective To research a protein chip method which can simultaneously quantitative detectβ‐Lactoglobulin(β‐L) and Lactoferrin(Lf) at one time.Methods Protein chip printer was used to print both anti‐β‐L antibodi...Objective To research a protein chip method which can simultaneously quantitative detectβ‐Lactoglobulin(β‐L) and Lactoferrin(Lf) at one time.Methods Protein chip printer was used to print both anti‐β‐L antibodies and anti‐Lf antibodies on each block of protein chip. And then an improved sandwich detection method was applied while the other two detecting antibodies for the two antigens were added in the block after they were mixed. The detection conditions of the quantitative detection for simultaneous measurement of β‐L and Lf with protein chip were optimized and evaluated. Based on these detected conditions, two standard curves of the two proteins were simultaneously established on one protein chip. Finally, the new detection method was evaluated by using the analysis of precision and accuracy.Results By comparison experiment, mouse monoclonal antibodies of the two antigens were chosen as the printing probe. The concentrations of β‐L and Lf probes were 0.5 mg/m L and 0.5 mg/m L,respectively, while the titers of detection antibodies both of β‐L and Lf were 1:2,000. Intra‐ and inter‐assay variability was between 4.88% and 38.33% for all tests. The regression coefficients of protein chip comparing with ELISA for β‐L and Lf were better than 0.734, and both of the two regression coefficients were statistically significant(r = 0.734, t = 2.644, P = 0.038; and r = 0.774, t = 2.998, P =0.024).Conclusion A protein chip method of simultaneously quantitative detection for β‐L and Lf has been established and this method is worthy in further application.展开更多
Objective To establish a method for quantitative detection of the sulfate glycosaminoglycans ( GAG) content in extracellular matrix of in vitro cultured chondrocytes so as to evaluate the biological characteristics of...Objective To establish a method for quantitative detection of the sulfate glycosaminoglycans ( GAG) content in extracellular matrix of in vitro cultured chondrocytes so as to evaluate the biological characteristics of epiphyseal, articular and rib chondrocytes. Methods Sulfate GAG content in extracellular matrix of three chondrocytes was measured by the modified dimethylmethylene blue (DMB) method. The changes of the toluidine blue (TB) stain of chondrocytes were observed by light microscope. Results Primary chondrocytes had the highest content of sulfate GAG in the extracellular matrix, ie, epiphyseal chondrocytes reached ( 70. 12 ± 7. 72 )μg/cm2, articular chondrocytes (92.00 ± 10.15) μg/cm2 and rib chondrocytes (80.61 ± 11. 40) μg/cm2, respectively. On the third pasage chondrocytes, epiphyceal chondrocytes decreased to (53.27 ± 9. 50 ) μg/cm2, articular chondrocytes to (63.88 ± 11.92) μg/cm2 and rib chondrocytes to (58.94 ±8.21) μg/cm2, respectively. The change of TB in every passage展开更多
Objective Shellfish are recognized as important vehicles of norovirus-associated gastroenteritis. The present study aimed to monitor norovirus contamination in oysters along the farm-to-fork continuum in Guangxi, a ma...Objective Shellfish are recognized as important vehicles of norovirus-associated gastroenteritis. The present study aimed to monitor norovirus contamination in oysters along the farm-to-fork continuum in Guangxi, a major oyster production area in Southwestern China. Methods Oyster samples were collected monthly from farms, markets, and restaurants, from January to December 2016. Norovirus was detected and quantified by one-step reverse transcription-droplet digital polymerase chain reaction(RT-ddPCR). Results A total of 480 oyster samples were collected and tested for norovirus genogroups I and II. Norovirus was detected in 20.7% of samples, with genogroup II predominating. No significant difference was observed in norovirus prevalence among different sampling sites. The norovirus levels varied widely, with a geometric mean of 19,300 copies/g in digestive glands. Both norovirus prevalence and viral loads showed obvious seasonality, with a strong winter bias. Conclusion This study provides a systematic analysis of norovirus contamination ‘from the farm to the fork' in Guangxi. RT-ddPCR can be a useful tool for detection and quantification of low amounts of norovirus in the presence of inhibitors found particularly in foodstuffs. This approach will contribute to the development of strategies for controlling and reducing the risk of human illness resulting from shellfish consumption.展开更多
Objective:To develop the rapid and efficient quantitative detection tool for nervous necrosis virus isolated from sevenband grouper Hyporhodus septemfasciatus.Methods:The viral genes of the NNV(SGYeosu08) isolated fro...Objective:To develop the rapid and efficient quantitative detection tool for nervous necrosis virus isolated from sevenband grouper Hyporhodus septemfasciatus.Methods:The viral genes of the NNV(SGYeosu08) isolated from sevenband grouper were phylogenetically analyzed.In addition,novel quantitative PCR primers based on the genomic sequence of SGYeosu08 isolate were designed and compared it with the conventional bio-assay method(TCID_(50)) using in vitro and in vivo samples.Results:The phylogenetic analysis of viral genes demonstrated the relationship of SGYeosu08 with members of red-spotted grouper nervous necrosis virus(RGNNV).The qNNV_Rl primer set(R1_F and R1_R) and the qNNV_R2 primer set(R2_F and R2_R) revealed 93%primer efficiency(regression:y=-0.2861 x + 9.9401,R^2= 0.9976)and the revealed 108%primer efficiency(regression:y=-0.3172 x + 10.0611,R^2= 0.9982),respectively.Its comparison with viral infectivity calculated by TCID_(50) method showed similar kinetic pattern at in vitro and NNV challenged fish(in vivo) samples.Conclusions:Result show that this method is rapid and efficient to diagnose NNV infection compare to traditional bioassay method(TCID_(50)).展开更多
The differences in intracellular and extracellular protein expressions between human prostate cancer lines LNCap and DU145 were examined.The proteins of the two cell lines were ex-tracted and condensed by using protei...The differences in intracellular and extracellular protein expressions between human prostate cancer lines LNCap and DU145 were examined.The proteins of the two cell lines were ex-tracted and condensed by using protein extraction kits.And the intracellular and extracellular proteins were quantitatively detected on a micro-plate reader by using bicinchoninic acid(BCA) method.The proteins in cell culture fluid were qualitatively assayed by SELDI-TOF-MS.The results showed that the intracellular protein contents of LNCap cells were extremely higher than those of DU145 cells.After serum-free culture,both intracellular and extracellular protein contents of LNCap and DU145 were decreased to some extent.And the intracellular proteins were decreased by 5% in LNCap and by 36% in DU145 respectively,while the extracellular proteins were decreased by 89% in LNCap and 96% in DU145 respectively.SELDI assay revealed that there were 5 marker proteins in LNCap and 6 in DU145.Although both LNCap and DU145 cell lines originated from human prostate cancer,they had some differences in protein expression.展开更多
We isolated 4 Norwalk-like viruses (NLVs) contaminated oysters from 33 Chinese oysters collected from local commer- cial sources of Shandong Province. After amplification of the RNA-dependent RNA polymerase (RdRp) reg...We isolated 4 Norwalk-like viruses (NLVs) contaminated oysters from 33 Chinese oysters collected from local commer- cial sources of Shandong Province. After amplification of the RNA-dependent RNA polymerase (RdRp) region of NLVs genomes with RT-PCR, the open reading frame 1 (ORF1) of the RdRp was sequenced and subjected to multiple-sequence alignment. The re- sults showed that NLVs in the four isolates belong to genogroup II. The sequence comparison showed that the similarity between four Chinese oyster isolates were higher than 99.0%, which indicated that NLVs prevalent in close areas have high homogeneity in genome sequences. In addition, the most conserved sequences between diverse NLVs were used to design primers and TaqMan probes, then the real-time quantitative PCR assay was performed. According to the standard curve of GII NLVs, the original amounts (copies) of NLVs in positive patient’s fecal isolate, positive Japanese oyster isolate, and the Chinese oyster isolate were 8.9×108, 1.25×108 and 4.7×101 respectively. The detecting limit of NLVs was 1×101 copies. This study will be helpful for routine diagnosis of NLVs pathogens in foods and thus for avoiding food poisoning in the future.展开更多
Artificial immune detection can be used to detect network intrusions in an adaptive approach and proper matching methods can improve the accuracy of immune detection methods.This paper proposes an artificial immune de...Artificial immune detection can be used to detect network intrusions in an adaptive approach and proper matching methods can improve the accuracy of immune detection methods.This paper proposes an artificial immune detection model for network intrusion data based on a quantitative matching method.The proposed model defines the detection process by using network data and decimal values to express features and artificial immune mechanisms are simulated to define immune elements.Then,to improve the accuracy of similarity calculation,a quantitative matching method is proposed.The model uses mathematical methods to train and evolve immune elements,increasing the diversity of immune recognition and allowing for the successful detection of unknown intrusions.The proposed model’s objective is to accurately identify known intrusions and expand the identification of unknown intrusions through signature detection and immune detection,overcoming the disadvantages of traditional methods.The experiment results show that the proposed model can detect intrusions effectively.It has a detection rate of more than 99.6%on average and a false alarm rate of 0.0264%.It outperforms existing immune intrusion detection methods in terms of comprehensive detection performance.展开更多
An aldehyde-reactive probe based on 2-amino benzamidoxime(ABAO)framework was introduced,which can selectively label aldehydes in DNA through intramolecular ring closure under mild aqueous solutions.We screened ABAO de...An aldehyde-reactive probe based on 2-amino benzamidoxime(ABAO)framework was introduced,which can selectively label aldehydes in DNA through intramolecular ring closure under mild aqueous solutions.We screened ABAO derivatives that can undergo a cyclization with the formylated nucleobases to generate a fluorescence nucleoside,and of these derivatives 5–methoxy-ABAO(PMA)emerged as the optimal choice.PMA can sensitively and selectively react with 5f U,5f C and AP to form fluorogenic dihydroquinazoline derivatives,which also can quantify DNA damages induced byγ-irradiation.PMA-initiated labeling strategy provides great convenience for qualitative and quantitative detection of aldehydes in DNA.展开更多
Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSP...Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.展开更多
Under the influence of air humidity,dust,aerosols,etc.,in real scenes,haze presents an uneven state.In this way,the image quality and contrast will decrease.In this case,It is difficult to detect the target in the ima...Under the influence of air humidity,dust,aerosols,etc.,in real scenes,haze presents an uneven state.In this way,the image quality and contrast will decrease.In this case,It is difficult to detect the target in the image by the universal detection network.Thus,a dual subnet based on multi-task collaborative training(DSMCT)is proposed in this paper.Firstly,in the training phase,the Gated Context Aggregation Network(GCANet)is used as the supervisory network of YOLOX to promote the extraction of clean information in foggy scenes.In the test phase,only the YOLOX branch needs to be activated to ensure the detection speed of the model.Secondly,the deformable convolution module is used to improve GCANet to enhance the model’s ability to capture details of non-homogeneous fog.Finally,the Coordinate Attention mechanism is introduced into the Vision Transformer and the backbone network of YOLOX is redesigned.In this way,the feature extraction ability of the network for deep-level information can be enhanced.The experimental results on artificial fog data set FOG_VOC and real fog data set RTTS show that the map value of DSMCT reached 86.56%and 62.39%,respectively,which was 2.27%and 4.41%higher than the current most advanced detection model.The DSMCT network has high practicality and effectiveness for target detection in real foggy scenes.展开更多
Urban underground pipelines are an important infrastructure in cities,and timely investigation of problems in underground pipelines can help ensure the normal operation of cities.Owing to the growing demand for defect...Urban underground pipelines are an important infrastructure in cities,and timely investigation of problems in underground pipelines can help ensure the normal operation of cities.Owing to the growing demand for defect detection in urban underground pipelines,this study developed an improved defect detection method for urban underground pipelines based on fully convolutional one-stage object detector(FCOS),called spatial pyramid pooling-fast(SPPF)feature fusion and dual detection heads based on FCOS(SDH-FCOS)model.This study improved the feature fusion component of the model network based on FCOS,introduced an SPPF network structure behind the last output feature layer of the backbone network,fused the local and global features,added a top-down path to accelerate the circulation of shallowinformation,and enriched the semantic information acquired by shallow features.The ability of the model to detect objects with multiple morphologies was strengthened by introducing dual detection heads.The experimental results using an open dataset of underground pipes show that the proposed SDH-FCOS model can recognize underground pipe defects more accurately;the average accuracy was improved by 2.7% compared with the original FCOS model,reducing the leakage rate to a large extent and achieving real-time detection.Also,our model achieved a good trade-off between accuracy and speed compared with other mainstream methods.This proved the effectiveness of the proposed model.展开更多
The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment pro...The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-interest and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization interests can effectively complete the task formation.展开更多
Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ ...Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.展开更多
Background: Nowadays, emergence of Carbapenemase-Producing Enterobacterales (CPE) throughout the world has become a public health problem, especially in countries with limited resources. In recent years, CPE of type O...Background: Nowadays, emergence of Carbapenemase-Producing Enterobacterales (CPE) throughout the world has become a public health problem, especially in countries with limited resources. In recent years, CPE of type OXA-48 (Ambler class D) have been identified in Dakar. The aim of this study was to evaluate the phenotypic detection of OXA-48 CPE using a temocillin disc (30 μg). Methodology: A retrospective study was carried out at Medical Biology Laboratory of Pasteur Institute in Dakar on Ertapenem-Resistant Enterobacterales (ERE) strains isolated from 2015 to 2017. These strains were then tested with a 30 μg temocillin disc. Any strain resistant to temocillin (inhibition diameter Results: Forty-one ERE isolated during the study period were tested, of which 34 (82.9%) were OXA-48 based on phenotypic detection using temocillin disc and confirmed by PCR (100%). OXA-48 CPE strains detected were composed of Klebsiella pneumoniae (n = 14;41.2%), Enterobacter cloacae (n = 8;23.5%), Escherichia coli (n = 7, 20.5%), Citrobacter freundii (n = 3;8.8%), Cronobacter sakazakii (n = 1;3%) and Morganella morganii (n = 1;3%). Conclusion: Temocillin resistance has a good positive predictive value for detecting OXA-48 CPE by phenotypic method, confirmed by PCR. Temocillin is therefore a good marker for detection of OXA-48 CPE except Hafnia alvei.展开更多
In recent years,frequent network attacks have highlighted the importance of efficient detection methods for ensuring cyberspace security.This paper presents a novel intrusion detection system consisting of a data prep...In recent years,frequent network attacks have highlighted the importance of efficient detection methods for ensuring cyberspace security.This paper presents a novel intrusion detection system consisting of a data prepro-cessing stage and a deep learning model for accurately identifying network attacks.We have proposed four deep neural network models,which are constructed using architectures such as Convolutional Neural Networks(CNN),Bi-directional Long Short-Term Memory(BiLSTM),Bidirectional Gate Recurrent Unit(BiGRU),and Attention mechanism.These models have been evaluated for their detection performance on the NSL-KDD dataset.To enhance the compatibility between the data and the models,we apply various preprocessing techniques and employ the particle swarm optimization algorithm to perform feature selection on the NSL-KDD dataset,resulting in an optimized feature subset.Moreover,we address class imbalance in the dataset using focal loss.Finally,we employ the BO-TPE algorithm to optimize the hyperparameters of the four models,maximizing their detection performance.The test results demonstrate that the proposed model is capable of extracting the spatiotemporal features of network traffic data effectively.In binary and multiclass experiments,it achieved accuracy rates of 0.999158 and 0.999091,respectively,surpassing other state-of-the-art methods.展开更多
The data analysis of blasting sites has always been the research goal of relevant researchers.The rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection ...The data analysis of blasting sites has always been the research goal of relevant researchers.The rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of blasting.Serverless Computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine learning.In this paper,we design a distributedmachine learning training application based on the AWS Lambda platform.Based on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively realized.It also encrypts the data set,effectively reducing the risk of data leakage.We rent a cloud server and a Lambda,and then we conduct experiments to evaluate our applications.Our results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.展开更多
The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology...The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.展开更多
This paper presents a new finite element model updating method for estimating structural parameters and detecting structural damage location and severity based on the structural responses(output-only data).The method ...This paper presents a new finite element model updating method for estimating structural parameters and detecting structural damage location and severity based on the structural responses(output-only data).The method uses the sensitivity relation of transmissibility data through a least-squares algorithm and appropriate normalization of the extracted equations.The proposed transmissibility-based sensitivity equation produces a more significant number of equations than the sensitivity equations based on the frequency response function(FRF),which can estimate the structural parameters with higher accuracy.The abilities of the proposed method are assessed by using numerical data of a two-story two-bay frame model and a plate structure model.In evaluating different damage cases,the number,location,and stiffness reduction of the damaged elements and the severity of the simulated damage have been accurately identified.The reliability and stability of the presented method against measurement and modeling errors are examined using error-contaminated data.The parameter estimation results prove the method’s capabilities as an accurate model updating algorithm.展开更多
基金supported by the Natural Science Foundation of Shandong Province(Grant No.:ZR2020QC250)China Agriculture Research System(Grant No.:CARS-38)+1 种基金Modern Agricultural Technology Industry System of Shandong Province(Grant No.:SDAIT10-10)Key Technology Research and Development Program of Shandong(Grant Nos.:2021CXGC010809 and 2021TZXD012).
文摘Ensuring food safety is paramount worldwide.Developing effective detection methods to ensure food safety can be challenging owing to trace hazards,long detection time,and resource-poor sites,in addition to the matrix effects of food.Personal glucose meter(PGM),a classic point-of-care testing device,possesses unique application advantages,demonstrating promise in food safety.Currently,many studies have used PGM-based biosensors and signal amplification technologies to achieve sensitive and specific detection of food hazards.Signal amplification technologies have the potential to greatly improve the analytical performance and integration of PGMs with biosensors,which is crucial for solving the challenges associated with the use of PGMs for food safety analysis.This review introduces the basic detection principle of a PGM-based sensing strategy,which consists of three key factors:target recognition,signal transduction,and signal output.Representative studies of existing PGM-based sensing strategies combined with various signal amplification technologies(nanomaterial-loaded multienzyme labeling,nucleic acid reaction,DNAzyme catalysis,responsive nanomaterial encapsulation,and others)in the field of food safety detection are reviewed.Future perspectives and potential opportunities and challenges associated with PGMs in the field of food safety are discussed.Despite the need for complex sample preparation and the lack of standardization in the field,using PGMs in combination with signal amplification technology shows promise as a rapid and cost-effective method for food safety hazard analysis.
基金Supported by The fund from Health Project of Jiangsu Province,No.H200711the AIDS,Hepatitis B and Other Infectious Diseases Prevention Program,No.2009ZX10004-712
文摘AIM:To establish the more feasible and sensitive assessment approach to the detection of adefovir (ADV) resistance-associated hepatitis B virus (HBV) quasispecies.METHODS: Based on the characteristics of rtA181V/T and rtN236T mutations, a new approach based on real-time fluorescent quantitative polymerase chain reaction (RT-PCR) was established for the detection of ADV-resistant HBV quasispecies, total HBV DNA, rtA181 and rtN236 mutations in blood samples from 32 chronic hepatitis B (CHB) patients with unsatisfactory curative effect on ADV and compared with routine HBV DNA sequencing.RESULTS: Both the sensitivity and specificity of this new detection approach to ADV-resistant HBV quasispecies were 100%, which were much higher than those of direct HBV DNA sequencing. The approach was able to detect 0.1% of mutated strains in a total plasmid population. Among the 32 clinical patients, single rtA181 and rtN236T mutation and double rtA181T and rtN236T mutations were detected in 20 and 8, respectively, while ADV-resistant mutations in 6 (including, rtA181V/T mutation alone in 5 patients) and no associated mutations in 26.CONCLUSION: This new approach is more feasible and efficient to detect ADV-resistant mutants of HBV and ADV-resistant mutations before and during ADV treatment with a specificity of 100% and a sensitivity of 100%.
基金Sponsored by the Young Scholar Scientific Research Foundation of China CDC[2015A202]:The establishment of testing platform of quantitatively detecting main protein of cow milk by using protein chip technique
文摘Objective To research a protein chip method which can simultaneously quantitative detectβ‐Lactoglobulin(β‐L) and Lactoferrin(Lf) at one time.Methods Protein chip printer was used to print both anti‐β‐L antibodies and anti‐Lf antibodies on each block of protein chip. And then an improved sandwich detection method was applied while the other two detecting antibodies for the two antigens were added in the block after they were mixed. The detection conditions of the quantitative detection for simultaneous measurement of β‐L and Lf with protein chip were optimized and evaluated. Based on these detected conditions, two standard curves of the two proteins were simultaneously established on one protein chip. Finally, the new detection method was evaluated by using the analysis of precision and accuracy.Results By comparison experiment, mouse monoclonal antibodies of the two antigens were chosen as the printing probe. The concentrations of β‐L and Lf probes were 0.5 mg/m L and 0.5 mg/m L,respectively, while the titers of detection antibodies both of β‐L and Lf were 1:2,000. Intra‐ and inter‐assay variability was between 4.88% and 38.33% for all tests. The regression coefficients of protein chip comparing with ELISA for β‐L and Lf were better than 0.734, and both of the two regression coefficients were statistically significant(r = 0.734, t = 2.644, P = 0.038; and r = 0.774, t = 2.998, P =0.024).Conclusion A protein chip method of simultaneously quantitative detection for β‐L and Lf has been established and this method is worthy in further application.
文摘Objective To establish a method for quantitative detection of the sulfate glycosaminoglycans ( GAG) content in extracellular matrix of in vitro cultured chondrocytes so as to evaluate the biological characteristics of epiphyseal, articular and rib chondrocytes. Methods Sulfate GAG content in extracellular matrix of three chondrocytes was measured by the modified dimethylmethylene blue (DMB) method. The changes of the toluidine blue (TB) stain of chondrocytes were observed by light microscope. Results Primary chondrocytes had the highest content of sulfate GAG in the extracellular matrix, ie, epiphyseal chondrocytes reached ( 70. 12 ± 7. 72 )μg/cm2, articular chondrocytes (92.00 ± 10.15) μg/cm2 and rib chondrocytes (80.61 ± 11. 40) μg/cm2, respectively. On the third pasage chondrocytes, epiphyceal chondrocytes decreased to (53.27 ± 9. 50 ) μg/cm2, articular chondrocytes to (63.88 ± 11.92) μg/cm2 and rib chondrocytes to (58.94 ±8.21) μg/cm2, respectively. The change of TB in every passage
文摘Objective Shellfish are recognized as important vehicles of norovirus-associated gastroenteritis. The present study aimed to monitor norovirus contamination in oysters along the farm-to-fork continuum in Guangxi, a major oyster production area in Southwestern China. Methods Oyster samples were collected monthly from farms, markets, and restaurants, from January to December 2016. Norovirus was detected and quantified by one-step reverse transcription-droplet digital polymerase chain reaction(RT-ddPCR). Results A total of 480 oyster samples were collected and tested for norovirus genogroups I and II. Norovirus was detected in 20.7% of samples, with genogroup II predominating. No significant difference was observed in norovirus prevalence among different sampling sites. The norovirus levels varied widely, with a geometric mean of 19,300 copies/g in digestive glands. Both norovirus prevalence and viral loads showed obvious seasonality, with a strong winter bias. Conclusion This study provides a systematic analysis of norovirus contamination ‘from the farm to the fork' in Guangxi. RT-ddPCR can be a useful tool for detection and quantification of low amounts of norovirus in the presence of inhibitors found particularly in foodstuffs. This approach will contribute to the development of strategies for controlling and reducing the risk of human illness resulting from shellfish consumption.
基金a part of the project titled'Production of diagnostic antibodies for viral diseases in aquatic animals'(Project No.20150259)funded by the Ministry of Oceans and Fisheries,Korea
文摘Objective:To develop the rapid and efficient quantitative detection tool for nervous necrosis virus isolated from sevenband grouper Hyporhodus septemfasciatus.Methods:The viral genes of the NNV(SGYeosu08) isolated from sevenband grouper were phylogenetically analyzed.In addition,novel quantitative PCR primers based on the genomic sequence of SGYeosu08 isolate were designed and compared it with the conventional bio-assay method(TCID_(50)) using in vitro and in vivo samples.Results:The phylogenetic analysis of viral genes demonstrated the relationship of SGYeosu08 with members of red-spotted grouper nervous necrosis virus(RGNNV).The qNNV_Rl primer set(R1_F and R1_R) and the qNNV_R2 primer set(R2_F and R2_R) revealed 93%primer efficiency(regression:y=-0.2861 x + 9.9401,R^2= 0.9976)and the revealed 108%primer efficiency(regression:y=-0.3172 x + 10.0611,R^2= 0.9982),respectively.Its comparison with viral infectivity calculated by TCID_(50) method showed similar kinetic pattern at in vitro and NNV challenged fish(in vivo) samples.Conclusions:Result show that this method is rapid and efficient to diagnose NNV infection compare to traditional bioassay method(TCID_(50)).
文摘The differences in intracellular and extracellular protein expressions between human prostate cancer lines LNCap and DU145 were examined.The proteins of the two cell lines were ex-tracted and condensed by using protein extraction kits.And the intracellular and extracellular proteins were quantitatively detected on a micro-plate reader by using bicinchoninic acid(BCA) method.The proteins in cell culture fluid were qualitatively assayed by SELDI-TOF-MS.The results showed that the intracellular protein contents of LNCap cells were extremely higher than those of DU145 cells.After serum-free culture,both intracellular and extracellular protein contents of LNCap and DU145 were decreased to some extent.And the intracellular proteins were decreased by 5% in LNCap and by 36% in DU145 respectively,while the extracellular proteins were decreased by 89% in LNCap and 96% in DU145 respectively.SELDI assay revealed that there were 5 marker proteins in LNCap and 6 in DU145.Although both LNCap and DU145 cell lines originated from human prostate cancer,they had some differences in protein expression.
文摘We isolated 4 Norwalk-like viruses (NLVs) contaminated oysters from 33 Chinese oysters collected from local commer- cial sources of Shandong Province. After amplification of the RNA-dependent RNA polymerase (RdRp) region of NLVs genomes with RT-PCR, the open reading frame 1 (ORF1) of the RdRp was sequenced and subjected to multiple-sequence alignment. The re- sults showed that NLVs in the four isolates belong to genogroup II. The sequence comparison showed that the similarity between four Chinese oyster isolates were higher than 99.0%, which indicated that NLVs prevalent in close areas have high homogeneity in genome sequences. In addition, the most conserved sequences between diverse NLVs were used to design primers and TaqMan probes, then the real-time quantitative PCR assay was performed. According to the standard curve of GII NLVs, the original amounts (copies) of NLVs in positive patient’s fecal isolate, positive Japanese oyster isolate, and the Chinese oyster isolate were 8.9×108, 1.25×108 and 4.7×101 respectively. The detecting limit of NLVs was 1×101 copies. This study will be helpful for routine diagnosis of NLVs pathogens in foods and thus for avoiding food poisoning in the future.
基金This research was funded by the Scientific Research Project of Leshan Normal University(No.2022SSDX002)the Scientific Plan Project of Leshan(No.22NZD012).
文摘Artificial immune detection can be used to detect network intrusions in an adaptive approach and proper matching methods can improve the accuracy of immune detection methods.This paper proposes an artificial immune detection model for network intrusion data based on a quantitative matching method.The proposed model defines the detection process by using network data and decimal values to express features and artificial immune mechanisms are simulated to define immune elements.Then,to improve the accuracy of similarity calculation,a quantitative matching method is proposed.The model uses mathematical methods to train and evolve immune elements,increasing the diversity of immune recognition and allowing for the successful detection of unknown intrusions.The proposed model’s objective is to accurately identify known intrusions and expand the identification of unknown intrusions through signature detection and immune detection,overcoming the disadvantages of traditional methods.The experiment results show that the proposed model can detect intrusions effectively.It has a detection rate of more than 99.6%on average and a false alarm rate of 0.0264%.It outperforms existing immune intrusion detection methods in terms of comprehensive detection performance.
基金financially supported by National Natural Science Foundation of China(Nos.22077088 and 21877082)Foundation from Science and Technology Department of Sichuan Province(Nos.2020JDJQ0017,2021YFH0132)。
文摘An aldehyde-reactive probe based on 2-amino benzamidoxime(ABAO)framework was introduced,which can selectively label aldehydes in DNA through intramolecular ring closure under mild aqueous solutions.We screened ABAO derivatives that can undergo a cyclization with the formylated nucleobases to generate a fluorescence nucleoside,and of these derivatives 5–methoxy-ABAO(PMA)emerged as the optimal choice.PMA can sensitively and selectively react with 5f U,5f C and AP to form fluorogenic dihydroquinazoline derivatives,which also can quantify DNA damages induced byγ-irradiation.PMA-initiated labeling strategy provides great convenience for qualitative and quantitative detection of aldehydes in DNA.
基金supported by the Scientific and Innovative Action Plan of Shanghai(21N31900800)Shanghai Rising-Star Program(23QB1403500)+4 种基金the Shanghai Sailing Program(20YF1443000)Shanghai Science and Technology Commission,the Belt and Road Project(20310750500)Talent Project of SAAS(2023-2025)Runup Plan of SAAS(ZP22211)the SAAS Program for Excellent Research Team(2022(B-16))。
文摘Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.
基金This work was jointly supported by the Special Fund for Transformation and Upgrade of Jiangsu Industry and Information Industry-Key Core Technologies(Equipment)Key Industrialization Projects in 2022(No.CMHI-2022-RDG-004):“Key Technology Research for Development of Intelligent Wind Power Operation and Maintenance Mothership in Deep Sea”.
文摘Under the influence of air humidity,dust,aerosols,etc.,in real scenes,haze presents an uneven state.In this way,the image quality and contrast will decrease.In this case,It is difficult to detect the target in the image by the universal detection network.Thus,a dual subnet based on multi-task collaborative training(DSMCT)is proposed in this paper.Firstly,in the training phase,the Gated Context Aggregation Network(GCANet)is used as the supervisory network of YOLOX to promote the extraction of clean information in foggy scenes.In the test phase,only the YOLOX branch needs to be activated to ensure the detection speed of the model.Secondly,the deformable convolution module is used to improve GCANet to enhance the model’s ability to capture details of non-homogeneous fog.Finally,the Coordinate Attention mechanism is introduced into the Vision Transformer and the backbone network of YOLOX is redesigned.In this way,the feature extraction ability of the network for deep-level information can be enhanced.The experimental results on artificial fog data set FOG_VOC and real fog data set RTTS show that the map value of DSMCT reached 86.56%and 62.39%,respectively,which was 2.27%and 4.41%higher than the current most advanced detection model.The DSMCT network has high practicality and effectiveness for target detection in real foggy scenes.
基金supported by the National Natural Science Foundation of China under Grant No.61976226the Research and Academic Team of South-CentralMinzu University under Grant No.KTZ20050.
文摘Urban underground pipelines are an important infrastructure in cities,and timely investigation of problems in underground pipelines can help ensure the normal operation of cities.Owing to the growing demand for defect detection in urban underground pipelines,this study developed an improved defect detection method for urban underground pipelines based on fully convolutional one-stage object detector(FCOS),called spatial pyramid pooling-fast(SPPF)feature fusion and dual detection heads based on FCOS(SDH-FCOS)model.This study improved the feature fusion component of the model network based on FCOS,introduced an SPPF network structure behind the last output feature layer of the backbone network,fused the local and global features,added a top-down path to accelerate the circulation of shallowinformation,and enriched the semantic information acquired by shallow features.The ability of the model to detect objects with multiple morphologies was strengthened by introducing dual detection heads.The experimental results using an open dataset of underground pipes show that the proposed SDH-FCOS model can recognize underground pipe defects more accurately;the average accuracy was improved by 2.7% compared with the original FCOS model,reducing the leakage rate to a large extent and achieving real-time detection.Also,our model achieved a good trade-off between accuracy and speed compared with other mainstream methods.This proved the effectiveness of the proposed model.
基金supported by the Basic Scientific Research Business Expenses of Central Universities(3072022QBZ0806)。
文摘The formation control of multiple unmanned aerial vehicles(multi-UAVs)has always been a research hotspot.Based on the straight line trajectory,a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption.In order to avoid the collision between UAVs in the formation process,the concept of safety ball is introduced,and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs.Based on the idea of game theory,a method of UAV motion form setting based on the maximization of interests is proposed,including the maximization of self-interest and the maximization of formation interest is proposed,so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance.Finally,through simulation verification,the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length,and the UAV motion selection method based on the maximization interests can effectively complete the task formation.
基金the financial support provided by the National Natural Science Foundation of China(Grant No.11872013).
文摘Copper-based azide(Cu(N_(3))2 or CuN_(3),CA)chips synthesized by in-situ azide reaction and utilized in miniaturized explosive systems has become a hot research topic in recent years.However,the advantages of in-situ synthesis method,including small size and low dosage,bring about difficulties in quantitative analysis and differences in ignition capabilities of CA chips.The aim of present work is to develop a simplified quantitative analysis method for accurate and safe analysis of components in CA chips to evaluate and investigate the corresponding ignition ability.In this work,Cu(N_(3))2 and CuN_(3)components in CA chips were separated through dissolution and distillation by utilizing the difference in solubility and corresponding content was obtained by measuring N_(3)-concentration through spectrophotometry.The spectrophotometry method was optimized by studying influencing factors and the recovery rate of different separation methods was studied,ensuring the accuracy and reproducibility of test results.The optimized method is linear in range from 1.0-25.0 mg/L,with a correlation coefficient R^(2)=0.9998,which meets the requirements of CA chips with a milligram-level content test.Compared with the existing ICP method,component analysis results of CA chips obtained by spectrophotometry are closer to real component content in samples and have satisfactory accuracy.Moreover,as its application in miniaturized explosive systems,the ignition ability of CA chips with different component contents for direct ink writing CL-20 and the corresponding mechanism was studied.This study provided a basis and idea for the design and performance evaluation of CA chips in miniaturized explosive systems.
文摘Background: Nowadays, emergence of Carbapenemase-Producing Enterobacterales (CPE) throughout the world has become a public health problem, especially in countries with limited resources. In recent years, CPE of type OXA-48 (Ambler class D) have been identified in Dakar. The aim of this study was to evaluate the phenotypic detection of OXA-48 CPE using a temocillin disc (30 μg). Methodology: A retrospective study was carried out at Medical Biology Laboratory of Pasteur Institute in Dakar on Ertapenem-Resistant Enterobacterales (ERE) strains isolated from 2015 to 2017. These strains were then tested with a 30 μg temocillin disc. Any strain resistant to temocillin (inhibition diameter Results: Forty-one ERE isolated during the study period were tested, of which 34 (82.9%) were OXA-48 based on phenotypic detection using temocillin disc and confirmed by PCR (100%). OXA-48 CPE strains detected were composed of Klebsiella pneumoniae (n = 14;41.2%), Enterobacter cloacae (n = 8;23.5%), Escherichia coli (n = 7, 20.5%), Citrobacter freundii (n = 3;8.8%), Cronobacter sakazakii (n = 1;3%) and Morganella morganii (n = 1;3%). Conclusion: Temocillin resistance has a good positive predictive value for detecting OXA-48 CPE by phenotypic method, confirmed by PCR. Temocillin is therefore a good marker for detection of OXA-48 CPE except Hafnia alvei.
文摘In recent years,frequent network attacks have highlighted the importance of efficient detection methods for ensuring cyberspace security.This paper presents a novel intrusion detection system consisting of a data prepro-cessing stage and a deep learning model for accurately identifying network attacks.We have proposed four deep neural network models,which are constructed using architectures such as Convolutional Neural Networks(CNN),Bi-directional Long Short-Term Memory(BiLSTM),Bidirectional Gate Recurrent Unit(BiGRU),and Attention mechanism.These models have been evaluated for their detection performance on the NSL-KDD dataset.To enhance the compatibility between the data and the models,we apply various preprocessing techniques and employ the particle swarm optimization algorithm to perform feature selection on the NSL-KDD dataset,resulting in an optimized feature subset.Moreover,we address class imbalance in the dataset using focal loss.Finally,we employ the BO-TPE algorithm to optimize the hyperparameters of the four models,maximizing their detection performance.The test results demonstrate that the proposed model is capable of extracting the spatiotemporal features of network traffic data effectively.In binary and multiclass experiments,it achieved accuracy rates of 0.999158 and 0.999091,respectively,surpassing other state-of-the-art methods.
文摘The data analysis of blasting sites has always been the research goal of relevant researchers.The rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of blasting.Serverless Computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine learning.In this paper,we design a distributedmachine learning training application based on the AWS Lambda platform.Based on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively realized.It also encrypts the data set,effectively reducing the risk of data leakage.We rent a cloud server and a Lambda,and then we conduct experiments to evaluate our applications.Our results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.
基金supported by the Stable-Support Scientific Project of the China Research Institute of Radio-wave Propagation(Grant No.A13XXXXWXX)the National Natural Science Foundation of China(Grant Nos.42174210,4207202,and 42188101)the Strategic Pioneer Program on Space Science,Chinese Academy of Sciences(Grant No.XDA15014800)。
文摘The Solar wind Magnetosphere Ionosphere Link Explorer(SMILE)satellite is a small magnetosphere–ionosphere link explorer developed cooperatively between China and Europe.It pioneers the use of X-ray imaging technology to perform large-scale imaging of the Earth’s magnetosheath and polar cusp regions.It uses a high-precision ultraviolet imager to image the overall configuration of the aurora and monitor changes in the source of solar wind in real time,using in situ detection instruments to improve human understanding of the relationship between solar activity and changes in the Earth’s magnetic field.The SMILE satellite is scheduled to launch in 2025.The European Incoherent Scatter Sciences Association(EISCAT)-3D radar is a new generation of European incoherent scatter radar constructed by EISCAT and is the most advanced ground-based ionospheric experimental device in the high-latitude polar region.It has multibeam and multidirectional quasi-real-time three-dimensional(3D)imaging capabilities,continuous monitoring and operation capabilities,and multiple-baseline interferometry capabilities.Joint detection by the SMILE satellite and the EISCAT-3D radar is of great significance for revealing the coupling process of the solar wind–magnetosphere–ionosphere.Therefore,we performed an analysis of the joint detection capability of the SMILE satellite and EISCAT-3D,analyzed the period during which the two can perform joint detection,and defined the key scientific problems that can be solved by joint detection.In addition,we developed Web-based software to search for and visualize the joint detection period of the SMILE satellite and EISCAT-3D radar,which lays the foundation for subsequent joint detection experiments and scientific research.
文摘This paper presents a new finite element model updating method for estimating structural parameters and detecting structural damage location and severity based on the structural responses(output-only data).The method uses the sensitivity relation of transmissibility data through a least-squares algorithm and appropriate normalization of the extracted equations.The proposed transmissibility-based sensitivity equation produces a more significant number of equations than the sensitivity equations based on the frequency response function(FRF),which can estimate the structural parameters with higher accuracy.The abilities of the proposed method are assessed by using numerical data of a two-story two-bay frame model and a plate structure model.In evaluating different damage cases,the number,location,and stiffness reduction of the damaged elements and the severity of the simulated damage have been accurately identified.The reliability and stability of the presented method against measurement and modeling errors are examined using error-contaminated data.The parameter estimation results prove the method’s capabilities as an accurate model updating algorithm.
