The implementation of multiple pathogen testing is essential for a rapid response to future outbreaks and for reducing disease transmission.This study introduces a 96-channel microfluidic chip,fabricated through a mol...The implementation of multiple pathogen testing is essential for a rapid response to future outbreaks and for reducing disease transmission.This study introduces a 96-channel microfluidic chip,fabricated through a molding process,which enables the batch detection of pathogens.It explores the rapid lysis and elution processes of pathogens within the microfluidic chips to ensure that nucleic acid extraction,elution,and amplification are completed entirely within the chip.This chip can extract nucleic acids from samples in just 10 min,achieving an extraction efficiency comparable to that of traditional in-tube methods.An oil phase is pre-loaded into the chip to effectively prevent aerosol contamination.This approach allows for the simultaneous detection of 21 common respiratory pathogens,with a detection limit of 10 copies per reaction.Furthermore,applications involving clinical samples demonstrate significant practicality.Compared to many traditional in-tube pathogen detection methods and molecular biology technologies that utilize microfluidic chips,this detection chip not only enables simultaneous detection of multiple pathogens but also demonstrates high sensitivity.展开更多
The performance and price of copper-based micro linear products are determined by the diameter uniformity.How to accurately detect the wire diameter of long-length copper based micro linear products without cutting or...The performance and price of copper-based micro linear products are determined by the diameter uniformity.How to accurately detect the wire diameter of long-length copper based micro linear products without cutting or damage has always been a technical concern for production enterprises.Herein,a novel approach was developed for nondestructive detection of the average diameter at any given segment of a long copper wire by assessing the adsorption capacity of arginine on its surface.The amount of adsorbent on the surface of the copper wire exhibits a positive correlation with the area,which can be detected by extractive electrospray ionization mass spectrometry(EESI-MS)after online elution with ammonia.The experimental results demonstrated that the analysis can be completed within 15 min,with a good linear relationship between copper wires with different diameters and the adsorption capacity of arginine.The linear correlation coefficient R2was 0.995,the relative standard deviation was 1.10%-2.81%,and the detection limit reached 2.5μm(length of segment=4 cm),showing potential applications for facile measurement of the average diameter of various metal wires.展开更多
Modern intrusion detection systems(MIDS)face persistent challenges in coping with the rapid evolution of cyber threats,high-volume network traffic,and imbalanced datasets.Traditional models often lack the robustness a...Modern intrusion detection systems(MIDS)face persistent challenges in coping with the rapid evolution of cyber threats,high-volume network traffic,and imbalanced datasets.Traditional models often lack the robustness and explainability required to detect novel and sophisticated attacks effectively.This study introduces an advanced,explainable machine learning framework for multi-class IDS using the KDD99 and IDS datasets,which reflects real-world network behavior through a blend of normal and diverse attack classes.The methodology begins with sophisticated data preprocessing,incorporating both RobustScaler and QuantileTransformer to address outliers and skewed feature distributions,ensuring standardized and model-ready inputs.Critical dimensionality reduction is achieved via the Harris Hawks Optimization(HHO)algorithm—a nature-inspired metaheuristic modeled on hawks’hunting strategies.HHO efficiently identifies the most informative features by optimizing a fitness function based on classification performance.Following feature selection,the SMOTE is applied to the training data to resolve class imbalance by synthetically augmenting underrepresented attack types.The stacked architecture is then employed,combining the strengths of XGBoost,SVM,and RF as base learners.This layered approach improves prediction robustness and generalization by balancing bias and variance across diverse classifiers.The model was evaluated using standard classification metrics:precision,recall,F1-score,and overall accuracy.The best overall performance was recorded with an accuracy of 99.44%for UNSW-NB15,demonstrating the model’s effectiveness.After balancing,the model demonstrated a clear improvement in detecting the attacks.We tested the model on four datasets to show the effectiveness of the proposed approach and performed the ablation study to check the effect of each parameter.Also,the proposed model is computationaly efficient.To support transparency and trust in decision-making,explainable AI(XAI)techniques are incorporated that provides both global and local insight into feature contributions,and offers intuitive visualizations for individual predictions.This makes it suitable for practical deployment in cybersecurity environments that demand both precision and accountability.展开更多
Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water re...Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water resource management and flood control.However,current investigations on their spatio-temporal patterns remain limited,largely because of the lack of systematic detection indices that are specifically designed for precipitation events,which constrains event-scale research.In this study,we defined a set of precipitation event detection indices(PEDI)that consists of five conventional and fourteen extreme indices to characterize precipitation events from the perspectives of intensity,duration,and frequency.Applications of the PEDI revealed the spatial patterns of hourly precipitation events in China and its first-and second-order river basins from 2008 to 2017.Both conventional and extreme precipitation events displayed spatial distribution patterns that gradually decreased in intensity,duration,and frequency from southeast to northwest China.Compared with those in northwest China,the average values of most PEDIs in southeast China were usually 2-10 times greater for first-order river basins and 3-15 times greater for second-order basins.The PEDI could serve as a reference method for investigating precipitation events at global,regional,and basin scales.展开更多
In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At prese...In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At present, research on residual stress at home and abroad mainly focuses on the optimization of traditional detection technology, stress control of manufacturing process and service performance evaluation, among which research on residual stress detection methods mainly focuses on the improvement of the accuracy, sensitivity, reliability and other performance of existing detection methods, but it still faces many challenges such as extremely small detection range, low efficiency, large error and limited application range.展开更多
The current study examines damage detection in fluid-conveying pipes supported on a Pasternak foundation.This study proposes a novel method that uses the matching pursuit(MP)algorithm for damage detection.The governin...The current study examines damage detection in fluid-conveying pipes supported on a Pasternak foundation.This study proposes a novel method that uses the matching pursuit(MP)algorithm for damage detection.The governing equations of motion for the pipe are derived using Hamilton’s principle.The finite element method,combined with the Galerkin approach,is employed to obtain the mass,damping,and stiffness matrices.To identify damage locations through pipe mode-shape decomposition,an index called the“matching pursuit residual”is introduced as a novel contribution of this study.The proposed method facilitates damage detection at various levels and locations under different boundary conditions.The findings demonstrate that the MP residual damage index can accurately localize damage in the pipes.Furthermore,the results of the numerical and experimental tests showcase the efficiency of the proposed method,highlighting that the MP signal approximation algorithm effectively detects damage in structures.展开更多
Legume foods are not only trendy but also rich in nutrients and offer unique health benefits.Nevertheless,allergies to soy and other legumes have emerged as critical issues in food safety,presenting significant challe...Legume foods are not only trendy but also rich in nutrients and offer unique health benefits.Nevertheless,allergies to soy and other legumes have emerged as critical issues in food safety,presenting significant challenges to the food processing industry and impacting consumer health.The complexity of legume allergens,coupled with inadequate allergen identification methods and the absence of robust detection and evaluation systems,complicates the management of these allergens.Here,we provide a comprehensive and critical review,mentioning various aspects related to legume allergies,including the types of legume allergens,the mechanisms behind these allergies,and the immunoglobulin E(Ig E)-binding epitopes involved,summarizing and discussing the detection techniques and the impact of different processing techniques on sensitization to legume proteins.Furthermore,this paper provides an overview of research advances in diagnostic and therapeutic strategies for legume allergens and discusses current challenges and prospects for studying legume allergens.展开更多
Near-Earth Asteroids posed a threat to human civilization,making their monitoring crucial.As the demand for asteroid detection technology increased,precise detection of these celestial bodies became an urgent task to ...Near-Earth Asteroids posed a threat to human civilization,making their monitoring crucial.As the demand for asteroid detection technology increased,precise detection of these celestial bodies became an urgent task to understand their characteristics and assess potential impact risks.To improve asteroid detection accuracy and efficiency,we proposed an advanced image processing method and a deep learning network for automatic asteroid detection.Specifically,we aligned star clusters and overlaid images to exploit asteroid motion rates,transforming them into object-like trajectories and improving the signal-to-noise ratio.This approach created the Asteroid Trajectory Image Data set under various conditions.We modified CenterNet2 network to develop AstroCenterNet by integrating Multi-channel Histogram Truncation for feature enhancement,using the SimAM attention mechanism to expand contextual information and suppress noise,and refining Feature Pyramid Network to improve low-level feature detection.Our results demonstrated a detection accuracy of 98.4%,a recall of 97.6%,a mean Average Precision of 94.01%,a false alarm rate of 1.6%,and a processing speed of approximately 17.86 frames per second,indicating that our method achieves high precision and efficiency.展开更多
Current damage detection methods based on model updating and sensitivity Jacobian matrixes show a low convergence ratio and computational efficiency for online calculations.The aim of this paper is to construct a real...Current damage detection methods based on model updating and sensitivity Jacobian matrixes show a low convergence ratio and computational efficiency for online calculations.The aim of this paper is to construct a real-time automated damage detection method by developing a theory-assisted adaptive mutiagent twin delayed deep deterministic(TA2-MATD3)policy gradient algorithm.First,the theoretical framework of reinforcement-learning-driven damage detection is established.To address the disadvantages of traditional mutiagent twin delayed deep deterministic(MATD3)method,the theory-assisted mechanism and the adaptive experience playback mechanism are introduced.Moreover,a historical residential house built in 1889 was taken as an example,using its 12-month structural health monitoring data.TA2-MATD3 was compared with existing damage detection methods in terms of the convergence ratio,online computing efficiency,and damage detection accuracy.The results show that the computational efficiency of TA2-MATD3 is approximately 117–160 times that of the traditional methods.The convergence ratio of damage detection on the training set is approximately 97%,and that on the test set is in the range of 86.2%–91.9%.In addition,the main apparent damages found in the field survey were identified by TA2-MATD3.The results indicate that the proposed method can significantly improve the online computing efficiency and damage detection accuracy.This research can provide novel perspectives for the use of reinforcement learning methods to conduct damage detection in online structural health monitoring.展开更多
BACKGROUND Helicobacter pylori(H.pylori),a globally prevalent pathogen,is exhibiting increasing rates of antimicrobial resistance.However,clinical implementation of pre-treatment susceptibility testing remains limited...BACKGROUND Helicobacter pylori(H.pylori),a globally prevalent pathogen,is exhibiting increasing rates of antimicrobial resistance.However,clinical implementation of pre-treatment susceptibility testing remains limited due to the organism’s fastidious growth requirements and prolonged culture time.AIM To propose a novel detection method utilizing antibiotic-supplemented media to inhibit susceptible strains,while resistant isolates were identified through urease-mediated hydrolysis of urea,inducing a phenol red color change for visual confirmation.METHODS Colombia agar was supplemented with urea,phenol red,and nickel chloride,and the final pH was adjusted to 7.35.Antibiotic-selective media were prepared by incorporating amoxicillin(0.5μg/mL),clarithromycin(2μg/mL),metronidazole(8μg/mL),or levofloxacin(2μg/mL)into separate batches.Gastric antral biopsies were homogenized and inoculated at 1.0×105 CFU onto the media,and then incubated under microaerobic conditions at 37°C for 28-36 hours.Resistance was determined based on a color change from yellow to pink,and the results were validated via broth microdilution according to Clinical and Laboratory Standards Institute guidelines.RESULTS After 28-36 hours of incubation,the drug-resistant H.pylori isolates induced a light red color change in the medium.Conversely,susceptible strains(H.pylori 26695 and G27)produced no visible color change.Compared with the conventional 11-day protocol,the novel method significantly reduced detection time.Among 201 clinical isolates,182 were successfully evaluated using the new method,resulting in a 90.5%detection rate.This was consistent with the 95.5%agreement rate observed when compared with microdilution-based susceptibility testing.The success rate of the novel approach was significantly higher than that of the comparative method(P<0.01).The accuracy of the new method was comparable to that of the dilution method.CONCLUSION The novel detection method can rapidly detect H.pylori drug resistance within 28-36 hours.With its operational simplicity and high diagnostic performance,it holds strong potential for clinical application in the management of H.pylori antimicrobial resistance.展开更多
Reservoirs with a group of vertical fractures in a vertical transversely isotropic(VTI)background are considered as orthorhombic(ORT)medium.However,fracture detection in ORT medium using seismic inversion methods rema...Reservoirs with a group of vertical fractures in a vertical transversely isotropic(VTI)background are considered as orthorhombic(ORT)medium.However,fracture detection in ORT medium using seismic inversion methods remains challenging,as it requires the estimation of more than eight parameters.Assuming the reservoir to be a weakly anisotropic ORT medium with small contrasts in the background elastic parameters,a new azimuthal elastic impedance equation was first derived using parameter combinations and mathematical approximations.This equation exhibited almost the same accuracy as the original equation and contained only six model parameters:the compression modulus,anisotropic shear modulus,anisotropic compression modulus,density,normal fracture weakness,and tangential fracture weakness.Subsequently,a stepwise inversion method using second-order derivatives of the elastic impedance was developed to estimate these parameters.Moreover,the Thomsen anisotropy parameter,epsilon,was estimated from the inversion results using the ratio of the anisotropic compression modulus to the compression modulus.Synthetic examples with moderate noise and field data examples confirm the feasibility and effectiveness of the inversion method.The proposed method exhibited accuracy similar to that of previous inversion strategies and could predict richer vertical fracture information.Ultimately,the method was applied to a three-dimensional work area,and the predictions were consistent with logging and geological a priori information,confirming the effectiveness of this method.Summarily,the proposed stepwise inversion method can alleviate the uncertainty of multi-parameter inversion in ORT medium,thereby improving the reliability of fracture detection.展开更多
With the gradual penetration of the internet of things(IoT)into all areas of life,the scale of IoT devices shows an explosive growth trend.The era of internet of everything is coming,and the important position of IoT ...With the gradual penetration of the internet of things(IoT)into all areas of life,the scale of IoT devices shows an explosive growth trend.The era of internet of everything is coming,and the important position of IoT security is becoming increasingly prominent.Due to the large number types of IoT devices,there may be different security vulnerabilities,and unknown attack forms and virus samples are appear.In other words,large number of IoT devices,large data volumes,and various attack forms pose a big challenge of malicious traffic identification.To solve these problems,this paper proposes a concept drift detection and adaptation(CDDA)method for IoT security framework.The AI model performance is evaluated by verifying the effectiveness of IoT traffic for data drift detection,so as to select the best AI model.The experimental test are given to confirm that the feasibility of the framework and the adaptive method in practice,and the effect on the performance of IoT traffic identification is also verified.展开更多
Wheat quality detection is essential to ensure the safety ofwheat circulation and storage.The traditional wheat quality detection methods mainly include artificial sensory evaluation and physicochemical index analysis...Wheat quality detection is essential to ensure the safety ofwheat circulation and storage.The traditional wheat quality detection methods mainly include artificial sensory evaluation and physicochemical index analysis,which are difficult to meet the requirements for high accuracy and efficiency in modern wheat quality detection due to the disadvantages of subjectivity,destruction of sample integrity and low efficiency.With the rapid development of optical technology,various optical-based methods,using near-infrared spectroscopy technology,hyperspectral imaging technology and terahertz,etc.,have been proposed for wheat quality detection.These methods have the characteristics of nondestructiveness and high efficiency which make them popular in wheat quality detection in recent years.In this paper,various state-of-the-art optical-based techniques of wheat quality detection are analyzed and summarized in detail.Firstly,the principle and process of common optical non-destructive detection methods for wheat quality are introduced.Then,the optical techniques used in these detection methods are divided into seven categories,and the comparison of these technologies and their advantages and disadvantages are further discussed.It shows that terahertz technology is regarded as the most promising wheat quality detection method compared with other optical detection technologies,because it can not only detect most types of wheat deterioration,but also has higher accuracy and efficiency.Finally,the research of optical technology in wheat quality detection is prospected.The future research of optical technology-based wheat quality detection mainly includes the construction of wheat quality optical detection standardization database,the fusion of multiple optical detection technologies and multiple quality index information,the improvement of the anti-interference of optical technology and the industrialization of optical inspection technology for wheat quality.These studies are of great significance to improve the detection technology of wheat and ensure the storage safety of wheat in the future.展开更多
Optoelectronic terahertz generation and detection play a key role in the applications of non-destructive testing,which involves different areas such as physics,biological,material science,imaging,explosions detection,...Optoelectronic terahertz generation and detection play a key role in the applications of non-destructive testing,which involves different areas such as physics,biological,material science,imaging,explosions detection,astronomy applications,semiconductor technology and superconductiong electronics. In this article,we present a reviewof the principle and performance of typical terahertz sources,detectors and non-destructive testing applications. On this basis,the newdevelopment and trends of terahertz radiation detectors are also discussed.展开更多
This article takes the actual construction project of a certain concrete bridge project as an example to analyze the application of acoustic non-destructive testing technology in its detection.It includes an overview ...This article takes the actual construction project of a certain concrete bridge project as an example to analyze the application of acoustic non-destructive testing technology in its detection.It includes an overview of a certain bridge construction project studied and acoustic non-destructive testing technology and the application of acoustic non-destructive testing technology in actual testing.This analysis hopes to provide some guidelines for acoustic non-destructive testing of modern concrete bridge projects.展开更多
Within the roadway advanced detection methods, DC resistivity method has an extensive application because of its simple principle and operation. Numerical simulation of the effect of focusing current on advanced detec...Within the roadway advanced detection methods, DC resistivity method has an extensive application because of its simple principle and operation. Numerical simulation of the effect of focusing current on advanced detection was carried out using a three-dimensional finite element method （FEM）, meanwhile the electric-field distribution of the point source and nine-point power source were calculated and analyzed with the same electric charges. The results show that the nine-point power source array has a very good ability to focus, and the DC focus method can be used to predict the aquifer abnormality body precisely. By comparing the FEM modelling results with physical simulation results from soil sink, it is shown that the accuracy of forward simulation meets the requirement and the artificial disturbance from roadway has no impact on the DC focus method.展开更多
We present a non-destructive method (NDM) to identify minute quantities of high atomic number (<em>Z</em>) elements in containers such as passenger baggage, goods carrying transport trucks, and environment...We present a non-destructive method (NDM) to identify minute quantities of high atomic number (<em>Z</em>) elements in containers such as passenger baggage, goods carrying transport trucks, and environmental samples. This method relies on the fact that photon attenuation varies with its energy and properties of the absorbing medium. Low-energy gamma-ray intensity loss is sensitive to the atomic number of the absorbing medium, while that of higher-energies vary with the density of the medium. To verify the usefulness of this feature for NDM, we carried out simultaneous measurements of intensities of multiple gamma rays of energies 81 to 1408 keV emitted by sources<sup> 133</sup>Ba (half-life = 10.55 y) and <sup>152</sup>Eu (half-life = 13.52 y). By this arrangement, we could detect minute quantities of lead and copper in a bulk medium from energy dependent gamma-ray attenuations. It seems that this method will offer a reliable, low-cost, low-maintenance alternative to X-ray or accelerator-based techniques for the NDM of high-Z materials such as mercury, lead, uranium, and transuranic elements etc.展开更多
Multi-source information fusion （MSIF） is imported into structural damage diagnosis methods to improve the validity of damage detection. After the introduction of the basic theory, the function model, classification...Multi-source information fusion （MSIF） is imported into structural damage diagnosis methods to improve the validity of damage detection. After the introduction of the basic theory, the function model, classifications and mathematical methods of MSIF, a structural damage detection method based on MSIF is presented, which is to fuse two or more damage character vectors from different structural damage diagnosis methods on the character-level. In an experiment of concrete plates, modal information is measured and analyzed. The structural damage detection method based on MSIF is taken to localize cracks of concrete plates and it is proved to be effective. Results of damage detection by the method based on MSIF are compared with those from the modal strain energy method and the flexibility method. Damage, which can hardly be detected by using the single damage identification method, can be diagnosed by the damage detection method based on the character-level MSIF technique. Meanwhile multi-location damage can be identified by the method based on MSIF. This method is sensitive to structural damage and different mathematical methods for MSIF have different preconditions and applicabilities for diversified structures. How to choose mathematical methods for MSIF should be discussed in detail in health monitoring systems of actual structures.展开更多
A reverse-transcription loop-mediated isothermal amplification （RT-LAMP） method was established for the detection of wheat streak mosaic virus （WSMV）. Ac-cording to the conservative regions of the genes that encod...A reverse-transcription loop-mediated isothermal amplification （RT-LAMP） method was established for the detection of wheat streak mosaic virus （WSMV）. Ac-cording to the conservative regions of the genes that encode the coat protein of WSMV, 2 pairs of primers were designed. Final y, the 1st pair of primers was select-ed through the specificity test. The sensitivity test showed the sensitivity of RT-LAMP method was 10 times higher than that of RT-PCR. In addition, the amplifica-tion of target gene could be judged visual y from the presence of fluorescence （cal-cein） in the final reaction system. The RT-LAMP method, established in this study, was rapid, easy, specific and sensitive. Moreover, it did not require sophisticated equip-ment. The RT-LAMP was suitable for the rapid detection of WSMV.展开更多
基金supported by grants from the National Key Research and Development Program of China(Nos.2023YFA0915200,2023YFA0915204)the Equipment Research and Development Projects of the Chinese Academy of Sciences(No.PTYQ2024YZ0010)+3 种基金the Science and Technology Commission of Shanghai Municipality Project(No.XTCX-KJ-2024-038)the Natural Science Foundation of Hebei Province of China(No.H2024206249)the Postdoctoral Fellowship Program of CPSF(No.GZC20232838)Science and Technology Commission of Shanghai Municipality(No.22S31901700).
文摘The implementation of multiple pathogen testing is essential for a rapid response to future outbreaks and for reducing disease transmission.This study introduces a 96-channel microfluidic chip,fabricated through a molding process,which enables the batch detection of pathogens.It explores the rapid lysis and elution processes of pathogens within the microfluidic chips to ensure that nucleic acid extraction,elution,and amplification are completed entirely within the chip.This chip can extract nucleic acids from samples in just 10 min,achieving an extraction efficiency comparable to that of traditional in-tube methods.An oil phase is pre-loaded into the chip to effectively prevent aerosol contamination.This approach allows for the simultaneous detection of 21 common respiratory pathogens,with a detection limit of 10 copies per reaction.Furthermore,applications involving clinical samples demonstrate significant practicality.Compared to many traditional in-tube pathogen detection methods and molecular biology technologies that utilize microfluidic chips,this detection chip not only enables simultaneous detection of multiple pathogens but also demonstrates high sensitivity.
基金supported by the National Natural Science Foundation of China(No.22422402)National Key Research and Development Program of China(No.2022YFF0705300)Key Research and Development Program of Jiangxi Province(No.20232BBG70004)。
文摘The performance and price of copper-based micro linear products are determined by the diameter uniformity.How to accurately detect the wire diameter of long-length copper based micro linear products without cutting or damage has always been a technical concern for production enterprises.Herein,a novel approach was developed for nondestructive detection of the average diameter at any given segment of a long copper wire by assessing the adsorption capacity of arginine on its surface.The amount of adsorbent on the surface of the copper wire exhibits a positive correlation with the area,which can be detected by extractive electrospray ionization mass spectrometry(EESI-MS)after online elution with ammonia.The experimental results demonstrated that the analysis can be completed within 15 min,with a good linear relationship between copper wires with different diameters and the adsorption capacity of arginine.The linear correlation coefficient R2was 0.995,the relative standard deviation was 1.10%-2.81%,and the detection limit reached 2.5μm(length of segment=4 cm),showing potential applications for facile measurement of the average diameter of various metal wires.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R104)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Modern intrusion detection systems(MIDS)face persistent challenges in coping with the rapid evolution of cyber threats,high-volume network traffic,and imbalanced datasets.Traditional models often lack the robustness and explainability required to detect novel and sophisticated attacks effectively.This study introduces an advanced,explainable machine learning framework for multi-class IDS using the KDD99 and IDS datasets,which reflects real-world network behavior through a blend of normal and diverse attack classes.The methodology begins with sophisticated data preprocessing,incorporating both RobustScaler and QuantileTransformer to address outliers and skewed feature distributions,ensuring standardized and model-ready inputs.Critical dimensionality reduction is achieved via the Harris Hawks Optimization(HHO)algorithm—a nature-inspired metaheuristic modeled on hawks’hunting strategies.HHO efficiently identifies the most informative features by optimizing a fitness function based on classification performance.Following feature selection,the SMOTE is applied to the training data to resolve class imbalance by synthetically augmenting underrepresented attack types.The stacked architecture is then employed,combining the strengths of XGBoost,SVM,and RF as base learners.This layered approach improves prediction robustness and generalization by balancing bias and variance across diverse classifiers.The model was evaluated using standard classification metrics:precision,recall,F1-score,and overall accuracy.The best overall performance was recorded with an accuracy of 99.44%for UNSW-NB15,demonstrating the model’s effectiveness.After balancing,the model demonstrated a clear improvement in detecting the attacks.We tested the model on four datasets to show the effectiveness of the proposed approach and performed the ablation study to check the effect of each parameter.Also,the proposed model is computationaly efficient.To support transparency and trust in decision-making,explainable AI(XAI)techniques are incorporated that provides both global and local insight into feature contributions,and offers intuitive visualizations for individual predictions.This makes it suitable for practical deployment in cybersecurity environments that demand both precision and accountability.
基金National Key Research and Development Program of China,No.2023YFC3206605,No.2021YFC3201102National Natural Science Foundation of China,No.41971035。
文摘Precipitation events,which follow a life cycle of initiation,development,and decay,represent the fundamental form of precipitation.Comprehensive and accurate detection of these events is crucial for effective water resource management and flood control.However,current investigations on their spatio-temporal patterns remain limited,largely because of the lack of systematic detection indices that are specifically designed for precipitation events,which constrains event-scale research.In this study,we defined a set of precipitation event detection indices(PEDI)that consists of five conventional and fourteen extreme indices to characterize precipitation events from the perspectives of intensity,duration,and frequency.Applications of the PEDI revealed the spatial patterns of hourly precipitation events in China and its first-and second-order river basins from 2008 to 2017.Both conventional and extreme precipitation events displayed spatial distribution patterns that gradually decreased in intensity,duration,and frequency from southeast to northwest China.Compared with those in northwest China,the average values of most PEDIs in southeast China were usually 2-10 times greater for first-order river basins and 3-15 times greater for second-order basins.The PEDI could serve as a reference method for investigating precipitation events at global,regional,and basin scales.
文摘In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At present, research on residual stress at home and abroad mainly focuses on the optimization of traditional detection technology, stress control of manufacturing process and service performance evaluation, among which research on residual stress detection methods mainly focuses on the improvement of the accuracy, sensitivity, reliability and other performance of existing detection methods, but it still faces many challenges such as extremely small detection range, low efficiency, large error and limited application range.
文摘The current study examines damage detection in fluid-conveying pipes supported on a Pasternak foundation.This study proposes a novel method that uses the matching pursuit(MP)algorithm for damage detection.The governing equations of motion for the pipe are derived using Hamilton’s principle.The finite element method,combined with the Galerkin approach,is employed to obtain the mass,damping,and stiffness matrices.To identify damage locations through pipe mode-shape decomposition,an index called the“matching pursuit residual”is introduced as a novel contribution of this study.The proposed method facilitates damage detection at various levels and locations under different boundary conditions.The findings demonstrate that the MP residual damage index can accurately localize damage in the pipes.Furthermore,the results of the numerical and experimental tests showcase the efficiency of the proposed method,highlighting that the MP signal approximation algorithm effectively detects damage in structures.
基金financially supported by National Natural Science Foundation of China(32460627 and 32272359)the Special Research Fund of Natural Science(Special Post)of Guizhou University(2022)54。
文摘Legume foods are not only trendy but also rich in nutrients and offer unique health benefits.Nevertheless,allergies to soy and other legumes have emerged as critical issues in food safety,presenting significant challenges to the food processing industry and impacting consumer health.The complexity of legume allergens,coupled with inadequate allergen identification methods and the absence of robust detection and evaluation systems,complicates the management of these allergens.Here,we provide a comprehensive and critical review,mentioning various aspects related to legume allergies,including the types of legume allergens,the mechanisms behind these allergies,and the immunoglobulin E(Ig E)-binding epitopes involved,summarizing and discussing the detection techniques and the impact of different processing techniques on sensitization to legume proteins.Furthermore,this paper provides an overview of research advances in diagnostic and therapeutic strategies for legume allergens and discusses current challenges and prospects for studying legume allergens.
基金funded by the National Science and Technology Major Project(2022ZD0117401)the National Defense Science and Technology Innovation Special Zone Project Foundation of China(grant No.19-163-21-TS-001-067-01)support was provided by the Chinese Academy of Sciences(CAS)“Light of West China”Program(No.2020-XBQNXZ-016 and No.2022-XBQNXZ-016).
文摘Near-Earth Asteroids posed a threat to human civilization,making their monitoring crucial.As the demand for asteroid detection technology increased,precise detection of these celestial bodies became an urgent task to understand their characteristics and assess potential impact risks.To improve asteroid detection accuracy and efficiency,we proposed an advanced image processing method and a deep learning network for automatic asteroid detection.Specifically,we aligned star clusters and overlaid images to exploit asteroid motion rates,transforming them into object-like trajectories and improving the signal-to-noise ratio.This approach created the Asteroid Trajectory Image Data set under various conditions.We modified CenterNet2 network to develop AstroCenterNet by integrating Multi-channel Histogram Truncation for feature enhancement,using the SimAM attention mechanism to expand contextual information and suppress noise,and refining Feature Pyramid Network to improve low-level feature detection.Our results demonstrated a detection accuracy of 98.4%,a recall of 97.6%,a mean Average Precision of 94.01%,a false alarm rate of 1.6%,and a processing speed of approximately 17.86 frames per second,indicating that our method achieves high precision and efficiency.
基金supported by National Key Research and Development Program of China(2023YFF0906100)National Natural Science Foundation of China(52408008)Key Research and Development Program of Jiangsu Province(BE2022833).
文摘Current damage detection methods based on model updating and sensitivity Jacobian matrixes show a low convergence ratio and computational efficiency for online calculations.The aim of this paper is to construct a real-time automated damage detection method by developing a theory-assisted adaptive mutiagent twin delayed deep deterministic(TA2-MATD3)policy gradient algorithm.First,the theoretical framework of reinforcement-learning-driven damage detection is established.To address the disadvantages of traditional mutiagent twin delayed deep deterministic(MATD3)method,the theory-assisted mechanism and the adaptive experience playback mechanism are introduced.Moreover,a historical residential house built in 1889 was taken as an example,using its 12-month structural health monitoring data.TA2-MATD3 was compared with existing damage detection methods in terms of the convergence ratio,online computing efficiency,and damage detection accuracy.The results show that the computational efficiency of TA2-MATD3 is approximately 117–160 times that of the traditional methods.The convergence ratio of damage detection on the training set is approximately 97%,and that on the test set is in the range of 86.2%–91.9%.In addition,the main apparent damages found in the field survey were identified by TA2-MATD3.The results indicate that the proposed method can significantly improve the online computing efficiency and damage detection accuracy.This research can provide novel perspectives for the use of reinforcement learning methods to conduct damage detection in online structural health monitoring.
基金Supported by the Guangxi Science and Technology Major Projects,No.AA23073012the National Natural Science Foundation of China,No.32360035 and No.32060018。
文摘BACKGROUND Helicobacter pylori(H.pylori),a globally prevalent pathogen,is exhibiting increasing rates of antimicrobial resistance.However,clinical implementation of pre-treatment susceptibility testing remains limited due to the organism’s fastidious growth requirements and prolonged culture time.AIM To propose a novel detection method utilizing antibiotic-supplemented media to inhibit susceptible strains,while resistant isolates were identified through urease-mediated hydrolysis of urea,inducing a phenol red color change for visual confirmation.METHODS Colombia agar was supplemented with urea,phenol red,and nickel chloride,and the final pH was adjusted to 7.35.Antibiotic-selective media were prepared by incorporating amoxicillin(0.5μg/mL),clarithromycin(2μg/mL),metronidazole(8μg/mL),or levofloxacin(2μg/mL)into separate batches.Gastric antral biopsies were homogenized and inoculated at 1.0×105 CFU onto the media,and then incubated under microaerobic conditions at 37°C for 28-36 hours.Resistance was determined based on a color change from yellow to pink,and the results were validated via broth microdilution according to Clinical and Laboratory Standards Institute guidelines.RESULTS After 28-36 hours of incubation,the drug-resistant H.pylori isolates induced a light red color change in the medium.Conversely,susceptible strains(H.pylori 26695 and G27)produced no visible color change.Compared with the conventional 11-day protocol,the novel method significantly reduced detection time.Among 201 clinical isolates,182 were successfully evaluated using the new method,resulting in a 90.5%detection rate.This was consistent with the 95.5%agreement rate observed when compared with microdilution-based susceptibility testing.The success rate of the novel approach was significantly higher than that of the comparative method(P<0.01).The accuracy of the new method was comparable to that of the dilution method.CONCLUSION The novel detection method can rapidly detect H.pylori drug resistance within 28-36 hours.With its operational simplicity and high diagnostic performance,it holds strong potential for clinical application in the management of H.pylori antimicrobial resistance.
基金sponsorship of the National Natural Science Foundation of China(42430809,42274157,42030103,42404132)the Fund of State Key Laboratory of Deep Oil and Gas,China University of Petroleum(East China)(SKLDOG2024-ZYTS-02)+5 种基金the Postdoctoral Fellowship Program of CPSF(GZB20240850)the Postdoctoral Project of Qingdao(QDBSH20240102082)the Fundamental Research Funds for the Central Universities(24CX07004A,24CX06036A)the CNPC Innovation Fund(2024DQ02-0505,2024DQ02-0136)the Innovation fund project for graduate student of China University of Petroleum(East China)the Fundamental Research Funds for the Central Universities(24CX04002A).
文摘Reservoirs with a group of vertical fractures in a vertical transversely isotropic(VTI)background are considered as orthorhombic(ORT)medium.However,fracture detection in ORT medium using seismic inversion methods remains challenging,as it requires the estimation of more than eight parameters.Assuming the reservoir to be a weakly anisotropic ORT medium with small contrasts in the background elastic parameters,a new azimuthal elastic impedance equation was first derived using parameter combinations and mathematical approximations.This equation exhibited almost the same accuracy as the original equation and contained only six model parameters:the compression modulus,anisotropic shear modulus,anisotropic compression modulus,density,normal fracture weakness,and tangential fracture weakness.Subsequently,a stepwise inversion method using second-order derivatives of the elastic impedance was developed to estimate these parameters.Moreover,the Thomsen anisotropy parameter,epsilon,was estimated from the inversion results using the ratio of the anisotropic compression modulus to the compression modulus.Synthetic examples with moderate noise and field data examples confirm the feasibility and effectiveness of the inversion method.The proposed method exhibited accuracy similar to that of previous inversion strategies and could predict richer vertical fracture information.Ultimately,the method was applied to a three-dimensional work area,and the predictions were consistent with logging and geological a priori information,confirming the effectiveness of this method.Summarily,the proposed stepwise inversion method can alleviate the uncertainty of multi-parameter inversion in ORT medium,thereby improving the reliability of fracture detection.
基金supported by 2023 Teaching Research Project of the Education Department of Anhui Province:Exploration of Optimizing Teaching Strategies for Embedded Courses in the Context of“New Engineering”(Project No.2023jyxm0460)2024 High-quality Course on Ideological and Political Education Integrated into Curriculum at Anhui University of Engineering:“Data Structures and Algorithms”(Project No.2024szyzk40)Industry-University-Research Cooperation Project of Anhui University of Engineering:“Online detection of surface quality defects in high-speed wire rod”(Project No.HX-2024-11-003).
文摘With the gradual penetration of the internet of things(IoT)into all areas of life,the scale of IoT devices shows an explosive growth trend.The era of internet of everything is coming,and the important position of IoT security is becoming increasingly prominent.Due to the large number types of IoT devices,there may be different security vulnerabilities,and unknown attack forms and virus samples are appear.In other words,large number of IoT devices,large data volumes,and various attack forms pose a big challenge of malicious traffic identification.To solve these problems,this paper proposes a concept drift detection and adaptation(CDDA)method for IoT security framework.The AI model performance is evaluated by verifying the effectiveness of IoT traffic for data drift detection,so as to select the best AI model.The experimental test are given to confirm that the feasibility of the framework and the adaptive method in practice,and the effect on the performance of IoT traffic identification is also verified.
基金supported by the scientific and technological key project in Henan Province (No.212102210148)Open fund of Key Laboratory of Grain Information Processing and Control (No.KFJJ-2018-101)
文摘Wheat quality detection is essential to ensure the safety ofwheat circulation and storage.The traditional wheat quality detection methods mainly include artificial sensory evaluation and physicochemical index analysis,which are difficult to meet the requirements for high accuracy and efficiency in modern wheat quality detection due to the disadvantages of subjectivity,destruction of sample integrity and low efficiency.With the rapid development of optical technology,various optical-based methods,using near-infrared spectroscopy technology,hyperspectral imaging technology and terahertz,etc.,have been proposed for wheat quality detection.These methods have the characteristics of nondestructiveness and high efficiency which make them popular in wheat quality detection in recent years.In this paper,various state-of-the-art optical-based techniques of wheat quality detection are analyzed and summarized in detail.Firstly,the principle and process of common optical non-destructive detection methods for wheat quality are introduced.Then,the optical techniques used in these detection methods are divided into seven categories,and the comparison of these technologies and their advantages and disadvantages are further discussed.It shows that terahertz technology is regarded as the most promising wheat quality detection method compared with other optical detection technologies,because it can not only detect most types of wheat deterioration,but also has higher accuracy and efficiency.Finally,the research of optical technology in wheat quality detection is prospected.The future research of optical technology-based wheat quality detection mainly includes the construction of wheat quality optical detection standardization database,the fusion of multiple optical detection technologies and multiple quality index information,the improvement of the anti-interference of optical technology and the industrialization of optical inspection technology for wheat quality.These studies are of great significance to improve the detection technology of wheat and ensure the storage safety of wheat in the future.
基金supported by the Cooperative Innovation Center of Terahertz Science , the National Basic Research Program of China (Grant No. 2014CB339800)the National Natural Science Foundation of China (Grant Nos. 61138001, 61420106006)+1 种基金the Program for Changjiang Scholars and Innovative Research Team in University (grant No. IRT13033)the Major National Development Project of Scientific Instruments and Equipment of China (Grant No. 2011YQ150021)
文摘Optoelectronic terahertz generation and detection play a key role in the applications of non-destructive testing,which involves different areas such as physics,biological,material science,imaging,explosions detection,astronomy applications,semiconductor technology and superconductiong electronics. In this article,we present a reviewof the principle and performance of typical terahertz sources,detectors and non-destructive testing applications. On this basis,the newdevelopment and trends of terahertz radiation detectors are also discussed.
文摘This article takes the actual construction project of a certain concrete bridge project as an example to analyze the application of acoustic non-destructive testing technology in its detection.It includes an overview of a certain bridge construction project studied and acoustic non-destructive testing technology and the application of acoustic non-destructive testing technology in actual testing.This analysis hopes to provide some guidelines for acoustic non-destructive testing of modern concrete bridge projects.
基金Project(41174103)supported by the National Natural Science Foundation of ChinaProject(20110162130008)supported by the PhD Program Foundation of Ministry of Education of ChinaProject(2011BAB04B08)supported by the National Key Technology R&D Program during the 12th Five-Year Plan of China
文摘Within the roadway advanced detection methods, DC resistivity method has an extensive application because of its simple principle and operation. Numerical simulation of the effect of focusing current on advanced detection was carried out using a three-dimensional finite element method （FEM）, meanwhile the electric-field distribution of the point source and nine-point power source were calculated and analyzed with the same electric charges. The results show that the nine-point power source array has a very good ability to focus, and the DC focus method can be used to predict the aquifer abnormality body precisely. By comparing the FEM modelling results with physical simulation results from soil sink, it is shown that the accuracy of forward simulation meets the requirement and the artificial disturbance from roadway has no impact on the DC focus method.
文摘We present a non-destructive method (NDM) to identify minute quantities of high atomic number (<em>Z</em>) elements in containers such as passenger baggage, goods carrying transport trucks, and environmental samples. This method relies on the fact that photon attenuation varies with its energy and properties of the absorbing medium. Low-energy gamma-ray intensity loss is sensitive to the atomic number of the absorbing medium, while that of higher-energies vary with the density of the medium. To verify the usefulness of this feature for NDM, we carried out simultaneous measurements of intensities of multiple gamma rays of energies 81 to 1408 keV emitted by sources<sup> 133</sup>Ba (half-life = 10.55 y) and <sup>152</sup>Eu (half-life = 13.52 y). By this arrangement, we could detect minute quantities of lead and copper in a bulk medium from energy dependent gamma-ray attenuations. It seems that this method will offer a reliable, low-cost, low-maintenance alternative to X-ray or accelerator-based techniques for the NDM of high-Z materials such as mercury, lead, uranium, and transuranic elements etc.
基金The National High Technology Research and Develop-ment Program of China(863Program)(No.2006AA04Z416)the Na-tional Science Fund for Distinguished Young Scholars(No.50725828)the Excellent Dissertation Program for Doctoral Degree of Southeast University(No.0705)
文摘Multi-source information fusion （MSIF） is imported into structural damage diagnosis methods to improve the validity of damage detection. After the introduction of the basic theory, the function model, classifications and mathematical methods of MSIF, a structural damage detection method based on MSIF is presented, which is to fuse two or more damage character vectors from different structural damage diagnosis methods on the character-level. In an experiment of concrete plates, modal information is measured and analyzed. The structural damage detection method based on MSIF is taken to localize cracks of concrete plates and it is proved to be effective. Results of damage detection by the method based on MSIF are compared with those from the modal strain energy method and the flexibility method. Damage, which can hardly be detected by using the single damage identification method, can be diagnosed by the damage detection method based on the character-level MSIF technique. Meanwhile multi-location damage can be identified by the method based on MSIF. This method is sensitive to structural damage and different mathematical methods for MSIF have different preconditions and applicabilities for diversified structures. How to choose mathematical methods for MSIF should be discussed in detail in health monitoring systems of actual structures.
文摘A reverse-transcription loop-mediated isothermal amplification （RT-LAMP） method was established for the detection of wheat streak mosaic virus （WSMV）. Ac-cording to the conservative regions of the genes that encode the coat protein of WSMV, 2 pairs of primers were designed. Final y, the 1st pair of primers was select-ed through the specificity test. The sensitivity test showed the sensitivity of RT-LAMP method was 10 times higher than that of RT-PCR. In addition, the amplifica-tion of target gene could be judged visual y from the presence of fluorescence （cal-cein） in the final reaction system. The RT-LAMP method, established in this study, was rapid, easy, specific and sensitive. Moreover, it did not require sophisticated equip-ment. The RT-LAMP was suitable for the rapid detection of WSMV.
