X-rays are widely used in the non-destructive testing(NDT)of electrical equipment.Radio frequency(RF)electron linear accelerators can generate MeV high-energy X-rays with strong penetrating ability;however,the system ...X-rays are widely used in the non-destructive testing(NDT)of electrical equipment.Radio frequency(RF)electron linear accelerators can generate MeV high-energy X-rays with strong penetrating ability;however,the system generally has a large scale,which is not suitable for on-site testing.Compared with the S-band(S-linac)at the same stage of beam energy,the accelerator working in the X-band(X-linac)can compress the facility scale by over 2/3 in the longitudinal direction,which is convenient for the on-site NDT of electrical equipment.To address the beam quality and design complexity simultaneously,the non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ),which is a multi-objective genetic algorithm(MOGA),was developed to optimize the cavity chain design of the X-linac.Additionally,the designs of the focusing coils,electron gun,and RF couplers,which are other key components of the X-linac,were introduced in this context.In particular,the focusing coil distributions were optimized using a genetic algorithm.Furthermore,after designing such key components,PARMELA software was adopted to perform beam dynamics calculations with the optimized accelerating fields and magnetic fields.The results show that the beam performance was obtained with a capture ratio of more than 90%,an energy spread of less than 10%,and an average energy of approximately 3 MeV.The design and simulation results indicate that the proposed NSGAⅡ-based approach is feasible for X-linac accelerator design.Furthermore,it can be generalized as a universal technique for industrial electron linear accelerators provided that specific optimization objectives and constraints are set according to different application scenarios and requirements.展开更多
The rapid progress in the construction of heavy-haul and high-speed railways has led to a surge in rail defects and unforeseen failures.Addressing this issue necessitates the implementation of more sophisticated rail ...The rapid progress in the construction of heavy-haul and high-speed railways has led to a surge in rail defects and unforeseen failures.Addressing this issue necessitates the implementation of more sophisticated rail inspection methods,specifically involving real-time,precise detection,and assessment of rail defects.Current applications fail to address the evolving requirements,prompting the need for advancements.This paper provides a summary of various types of rail defects and outlines both traditional and innovative non-destructive inspection techniques,examining their fundamental features,benefits,drawbacks,and practical suitability for railway track inspection.It also explores potential enhancements to equipment and software.The comprehensive review draws upon pertinent international research and review papers.Furthermore,the paper introduces a fusion of inspection methods aimed at enhancing the overall reliability of defect detection.展开更多
In high-risk industrial environments like nuclear power plants,precise defect identification and localization are essential for maintaining production stability and safety.However,the complexity of such a harsh enviro...In high-risk industrial environments like nuclear power plants,precise defect identification and localization are essential for maintaining production stability and safety.However,the complexity of such a harsh environment leads to significant variations in the shape and size of the defects.To address this challenge,we propose the multivariate time series segmentation network(MSSN),which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates.To tackle the classification difficulty caused by structural signal variance,MSSN employs logarithmic normalization to adjust instance distributions.Furthermore,it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences.Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95%localization and demonstrates the capture capability on the synthetic dataset.In a nuclear plant's heat transfer tube dataset,it captures 90%of defect instances with75%middle localization F1 score.展开更多
Objective This study describes acceptance and attitudes towards genetic cancer testing among German primary care patients.Design Cross-sectional survey.Setting Primary care.Participant Systematically recruited patient...Objective This study describes acceptance and attitudes towards genetic cancer testing among German primary care patients.Design Cross-sectional survey.Setting Primary care.Participant Systematically recruited patients aged≥18 years from six general practices in Mecklenburg-Western Pomerania participated in an anonymous self-administered survey on familial cancer prevention(n=479 and 67.0%participation rate).Those with complete data were analysed(n=424;mean age 53.7,SD 16.6 years;men 34.4%).Linear regression analyses were used to examine potential disparities in general acceptance of genetic testing and attitudes towards genetic cancer testing according to sociodemographics and familial cancer knowledge.Result General acceptance of genetic testing was high,particularly among younger,higher-educated individuals and those with a family history of cancer and higher familial cancer knowledge.For example,83.3%either agreed or strongly agreed that it should be available to anybody.The most important benefits of genetic cancer testing were to guide check-up frequency(81.4%),to inform medical decision-making(80.2%)and to understand children’s risk(75.2%).The most important concerns included the potential burden on the family(44.6%)and the belief that cancer cannot be prevented(39.2%).More favourable attitudes were found among younger,higher-educated individuals,those with a personal history of cancer and those with fewer children or no partner.For example,higher age was linked to lower benefit(regression coefficient(RC)−0.01,95%CI−0.01 to−0.001)and higher concern ratings(RC 0.01,95%CI 0.002 to 0.01).About a third(34.7%)rated not wanting to know about genetic alterations that increase their cancer risk as a(very)important reason against testing.Information avoidance was higher among older individuals(RC 0.02,95%CI 0.01 to 0.02),women(RC 0.40,95%CI 0.11 to 0.69),those with lower education(RC−0.64,95%CI−0.91 to−0.36)and those with more children(RC 0.21,95%CI 0.09 to 0.33).Conclusion Acceptance of genetic testing was high,but barriers remain,particularly among older adults,women,the less educated and those with more children.Targeted educational efforts to improve health literacy,emphasise the preventive potential of genetic testing and emotional support through genetic counselling are essential to overcome these barriers and promote informed decision-making.展开更多
In the current social environment,the importance of energy conservation and emission reduction is increasing day by day for both the country and its people.Electronic and electrical products,as important items for peo...In the current social environment,the importance of energy conservation and emission reduction is increasing day by day for both the country and its people.Electronic and electrical products,as important items for people’s production and life,require high attention from industry insiders in terms of their energy efficiency testing.Relying on energy efficiency testing can achieve the goal of energy conservation and emission reduction,and related quality control technologies will also inject new momentum into the green development of the industry.This article will discuss the practical strategies of quality control technology for energy efficiency testing of electronic and electrical products based on the significance of such testing,hoping to provide some help.展开更多
Traditional spectrophotometers have a large volume and slow scanning speed,which limits their applicability for rapid on-site detection.Herein,a micro-spectrophotometer(named ATOM)is fabricated,and its performance is ...Traditional spectrophotometers have a large volume and slow scanning speed,which limits their applicability for rapid on-site detection.Herein,a micro-spectrophotometer(named ATOM)is fabricated,and its performance is verified in water quality testing.An M-type Czerny-Turner light path structure,a broadband light emitting diode(LED)light source,and a linear charge-coupled device(CCD)photodetector were adopted in ATOM.The performance of ATOM was validated through iron content determination by using o-phenanthroline spectrophotometry.The experiment results showed that the linear correlation coefficient of determination R^(2) was 0.9997 for mass concentrations ranging from 0 to 2.0μg/mL.The relative standard deviation was 0.37%,and the relative error compared to a commercial large-scale spectrophotometer was below 1.4%.The dimensions of ATOM are 75 mm×60 mm×25 mm,with hardware costs of approximately 1000 CNY.ATOM features compact size,low cost,rapid measurement,high integration and high precision,making it suitable for portable on-site rapid detection.展开更多
This study aims to construct a virtual twin testing framework for the safety of the intended functionality of intelligent connected vehicles to address the safety requirements of intelligent driving and transportation...This study aims to construct a virtual twin testing framework for the safety of the intended functionality of intelligent connected vehicles to address the safety requirements of intelligent driving and transportation systems.The research methods include the construction of a theoretical model of safety for intelligent connected vehicles based on the concept of virtual twins,the correlation study between key concepts and functional safety,and the application research of virtual twin technology in the safety testing of intelligent connected vehicles.The results reveal that the virtual twin testing framework can effectively enhance the functional safety of intelligent connected vehicles,reduce development costs,and shorten the product launch cycle.The conclusion suggests that this framework provides strong support for the healthy development of the intelligent connected vehicle industry and has a positive impact on the safety and efficiency of intelligent transportation systems.展开更多
Test case prioritization and ranking play a crucial role in software testing by improving fault detection efficiency and ensuring software reliability.While prioritization selects the most relevant test cases for opti...Test case prioritization and ranking play a crucial role in software testing by improving fault detection efficiency and ensuring software reliability.While prioritization selects the most relevant test cases for optimal coverage,ranking further refines their execution order to detect critical faults earlier.This study investigates machine learning techniques to enhance both prioritization and ranking,contributing to more effective and efficient testing processes.We first employ advanced feature engineering alongside ensemble models,including Gradient Boosted,Support Vector Machines,Random Forests,and Naive Bayes classifiers to optimize test case prioritization,achieving an accuracy score of 0.98847 and significantly improving the Average Percentage of Fault Detection(APFD).Subsequently,we introduce a deep Q-learning framework combined with a Genetic Algorithm(GA)to refine test case ranking within priority levels.This approach achieves a rank accuracy of 0.9172,demonstrating robust performance despite the increasing computational demands of specialized variation operators.Our findings highlight the effectiveness of stacked ensemble learning and reinforcement learning in optimizing test case prioritization and ranking.This integrated approach improves testing efficiency,reduces late-stage defects,and improves overall software stability.The study provides valuable information for AI-driven testing frameworks,paving the way for more intelligent and adaptive software quality assurance methodologies.展开更多
T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection met...T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection methods face challenges owing to surface oxide scales,and conventional high-precision magnetic sensors are ineffective at high temperatures.To overcome these limitations,a small coil sensor was employed to measure the residual magnetism strength in oscillation traces,using metal magnetic memory and electromagnetic induction methods,which can carry out detection without an external excitation source.Using this technology,the proposed scheme successfully detects defects at high tempe-ratures(up to 670℃)without a cooling device.The key findings include the ability to detect both surface and near-surface defects,such as cracks and oscillation marks,with an enhanced signal-to-noise ratio(SNR)of 7.2 dB after signal processing.The method’s practicality was validated in a steel mill environment,where testing on casting slabs effectively detected defects,providing a foundation for improving industrial quality control.The proposed detection scheme offers a significant advancement in nondestructive testing(NDT)for high-temperature applications,contributing to more efficient and accurate monitoring of ferromagnetic material integrity.展开更多
In this study,a novel colorimetric detection method for tryptophan is developed using Au@MnO_(2)NPs based on their redox reaction.Tryptophan etches the outer MnO_(2)NPs shell and forms a stable protective layer outsid...In this study,a novel colorimetric detection method for tryptophan is developed using Au@MnO_(2)NPs based on their redox reaction.Tryptophan etches the outer MnO_(2)NPs shell and forms a stable protective layer outside the released AuNPs core in situ,accompanied by a noticeable color change from brown to pink.According to the absorbance ratio of 545 nm and 580 nm(A_(545)/A_(580)),a rapid(within 1 min),accurate,and specific detection method for tryptophan is constructed amidst other common amino acids.Coupling with a smartphone application,integrated Au@MnO_(2)NPs-based portable test strips can be used for the point-of-care testing(POCT)of tryptophan.展开更多
Members of the British Textile Machinery Association(BTMA)can look back on 2025 as a year marked by notable technological advances and continued progress in global trade,despite an uncertain and volatile market.“Our ...Members of the British Textile Machinery Association(BTMA)can look back on 2025 as a year marked by notable technological advances and continued progress in global trade,despite an uncertain and volatile market.“Our members have been very active over the past 12 months and this has resulted in new technologies for the production of technical fibres and fabrics,the introduction of AI and machine learning into process control systems and significant advances in materials testing,”says BTMA CEO Jason Kent.“There’s real excitement about what can be achieved in 2026 as we look ahead to upcoming exhibitions such as JEC Composites in Paris in March and Techtextil in Frankfurt in April.”展开更多
At present,there is currently a lack of unified standard methods for the determination of antimony content in groundwater in China.The precision and trueness of related detection technologies have not yet been systema...At present,there is currently a lack of unified standard methods for the determination of antimony content in groundwater in China.The precision and trueness of related detection technologies have not yet been systematically and quantitatively evaluated,which limits the effective implementation of environmental monitoring.In response to this key technical gap,this study aimed to establish a standardized method for determining antimony in groundwater using Hydride Generation–Atomic Fluorescence Spectrometry(HG-AFS).Ten laboratories participated in inter-laboratory collaborative tests,and the statistical analysis of the test data was carried out in strict accordance with the technical specifications of GB/T 6379.2—2004 and GB/T 6379.4—2006.The consistency and outliers of the data were tested by Mandel's h and k statistics,the Grubbs test and the Cochran test,and the outliers were removed to optimize the data,thereby significantly improving the reliability and accuracy.Based on the optimized data,parameters such as the repeatability limit(r),reproducibility limit(R),and method bias value(δ)were determined,and the trueness of the method was statistically evaluated.At the same time,precision-function relationships were established,and all results met the requirements.The results show that the lower the antimony content,the lower the repeatability limit(r)and reproducibility limit(R),indicating that the measurement error mainly originates from the detection limit of the method and instrument sensitivity.Therefore,improving the instrument sensitivity and reducing the detection limit are the keys to controlling the analytical error and improving precision.This study provides reliable data support and a solid technical foundation for the establishment and evaluation of standardized methods for the determination of antimony content in groundwater.展开更多
With the rapid development of Internet technology,REST APIs(Representational State Transfer Application Programming Interfaces)have become the primary communication standard in modern microservice architectures,raisin...With the rapid development of Internet technology,REST APIs(Representational State Transfer Application Programming Interfaces)have become the primary communication standard in modern microservice architectures,raising increasing concerns about their security.Existing fuzz testing methods include random or dictionary-based input generation,which often fail to ensure both syntactic and semantic correctness,and OpenAPIbased approaches,which offer better accuracy but typically lack detailed descriptions of endpoints,parameters,or data formats.To address these issues,this paper proposes the APIDocX fuzz testing framework.It introduces a crawler tailored for dynamic web pages that automatically simulates user interactions to trigger APIs,capturing and extracting parameter information from communication packets.A multi-endpoint parameter adaptation method based on improved Jaccard similarity is then used to generalize these parameters to other potential API endpoints,filling in gaps in OpenAPI specifications.Experimental results demonstrate that the extracted parameters can be generalized with 79.61%accuracy.Fuzz testing using the enriched OpenAPI documents leads to improvements in test coverage,the number of valid test cases generated,and fault detection capabilities.This approach offers an effective enhancement to automated REST API security testing.展开更多
Cemented paste backfill(CPB)is a technology that achieves safe mining by filling the goaf with waste rocks,tailings,and other materials.It is an inevitable choice to deal with the development of deep and highly diffic...Cemented paste backfill(CPB)is a technology that achieves safe mining by filling the goaf with waste rocks,tailings,and other materials.It is an inevitable choice to deal with the development of deep and highly difficult mines and meet the requirements of environmental protection and safety regulations.It promotes the development of a circular economy in mines through the development of lowgrade resources and the resource utilization of waste,and extends the service life of mines.The mass concentration of solid content(abbreviated as“concentration”)is a critical parameter for CPB.However,discrepancies often arise between the on-site measurements and the pre-designed values due to factors such as groundwater inflow and segregation within the goaf,which cannot be evaluated after the solidification of CPB.This paper innovatively provides an in-situ non-destructive approach to identify the real concentration of CPB after curing for certain days using hyperspectral imaging(HSI)technology.Initially,the spectral variation patterns under different concentration conditions were investigated through hyperspectral scanning experiments on CPB samples.The results demonstrate that as the CPB concentration increases from 61wt%to 73wt%,the overall spectral reflectance gradually increases,with two distinct absorption peaks observed at 1407 and 1917 nm.Notably,the reflectance at 1407 nm exhibited a strong linear relationship with the concentration.Subsequently,the K-nearest neighbors(KNN)and support vector machine(SVM)algorithms were employed to classify and identify different concentrations.The study revealed that,with the KNN algorithm,the highest accuracy was achieved when K(number of nearest neighbors)was 1,although this resulted in overfitting.When K=3,the model displayed the optimal balance between accuracy and stability,with an accuracy of 95.03%.In the SVM algorithm,the highest accuracy of 98.24%was attained with parameters C(regularization parameter)=200 and Gamma(kernel coefficient)=10.A comparative analysis of precision,accuracy,and recall further highlighted that the SVM provided superior stability and precision for identifying CPB concentration.Thus,HSI technology offers an effective solution for the in-situ,non-destructive monitoring of CPB concentration,presenting a promising approach for optimizing and controlling CPB characteristic parameters.展开更多
Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of...Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of conducting full-scale fall experiments on robots or their surrogates remain somewhat limited.This paper proposes a method for optimizing the thickness of Expandable Polyethylene(EPE),which is used as back protection for the Chubao humanoid robot,based on small-scale impact test data to predict full-scale behavior.The optimal thickness is defined as a balance between compact design and protective effectiveness.An equivalent impact model characterized by four parameters:contact area S,mass m,fall height h,and cushioning material thickness d is introduced to describe impact conditions.The relationship between the peak impact acceleration ap and material thickness d,which forms the core of the method and gives rise to the name AP-D,is analyzed through their plotted curves.After introducing three characteristic parameters and two correction fac-tors,the relationship among the aforementioned variables is derived.Subsequently,both the optimal thickness do and its corresponding peak impact acceleration aop are predicted via nonlinear and linear regression models.Finally,the accuracy and effectiveness of the theoretically derived optimal thickness are validated on both a dummy and the actual robot.With the cushioning material applied,the peak chest acceleration is reduced to 41.57g for the dummy and 32.08g for the robot.展开更多
Human fungal infections represent a rapidly emerging global health threat,especially threatening immunocompromised populations,highlighting the urgent need for accurate and timely diagnostic approaches to reduce morbi...Human fungal infections represent a rapidly emerging global health threat,especially threatening immunocompromised populations,highlighting the urgent need for accurate and timely diagnostic approaches to reduce morbidity and mortality.This review synthesizes recent advances in diagnostic methodologies,including serological assays,point-of-care diagnostics,polymerase chain reaction(PCR)-based and sequencing technologies,as well as artificial intelligence(AI)-and machine learning(ML)-powered tools.Emerging diagnostic approaches have demonstrated notable improvements in detection accuracy,turnaround time,and antifungal resistance profiling capabilities,especially for drug-resistant strains.Nevertheless,substantial challenges persist in terms of standardization,scalability,cost-effectiveness,and implementation,particularly in resource-constrained settings.Future efforts should be directed toward the continuous innovation of rapid,sensitive,and multiplex diagnostic platforms for the simultaneous detection of fungi,bacteria,and viruses.Such advances may accelerate result acquisition,enhance diagnostic accuracy,support the development of more targeted therapeutic strategies,and ultimately improve clinical outcomes for patients.展开更多
Clustered regularly interspaced short palindromic repeats(CRISPR)systems have achieved significant advancements in precise molecular diagnosis.However,their applications in whole blood detection remain challenging due...Clustered regularly interspaced short palindromic repeats(CRISPR)systems have achieved significant advancements in precise molecular diagnosis.However,their applications in whole blood detection remain challenging due to signal interference from blood autofluorescence.Here,we proposed a universal and accessible bioluminescent CRISPR/Cas(bioLUCas)platform for direct detection of disease biomarkers in whole blood.By employing a specially designed cpHNLucMB reporter,the bioLUCas system converts CRISPR/Cas12a trans-cleavage activity into a ratiometric bioluminescent signal,producing a distinct emission color change.Compared to conventional CRISPR/Cas12a-based sensors,this platform eliminates the need for external light excitation,effectively bypassing blood autofluorescence and offering high sensitivity.Additionally,the visual signal of bioLUCas system allows user-friendly readout methods,such as smartphone.The platform successfully facilitated point-of-care test(POCT)for myeloperoxidase(MPO)in clinical acute myelogenous leukemia(AML)blood samples and hepatitis C virus(HCV)RNA in synthetic blood samples.This work may advance CRISPR/Cas technology for accessible whole-blood disease diagnostics.展开更多
Fluidic Thrust Vectoring(FTV)is used for the yaw attitude control of tailless flying wing,which can significantly improve stealth performance,maneuverability and lateral/heading maneuverability.The FTV control scheme ...Fluidic Thrust Vectoring(FTV)is used for the yaw attitude control of tailless flying wing,which can significantly improve stealth performance,maneuverability and lateral/heading maneuverability.The FTV control scheme of co-directional secondary flow was designed based on a 30 kgf thrust turbojet engine,an equivalent rudder deflection control variable of Mass Flow Combination(MFC)was proposed,and a control model was established to form a FTV control system scheme,which was integrated with the flight control system of a 100 kg tailless flying wing with medium aspect ratio to achieve closed-loop control of the yaw attitude based on FTV.The heading stability augmentation and maneuvering control characteristics and time response characteristics of tailless flying wing by FTV were quantitatively studied through virtual flight test in a wind tunnel at a wind speed of 35 m/s.The results show that the control strategy based on MFC achieves bidirectional continuous and stable control of thrust vector angle in a range of±11°,and the thrust vector angle varies monotonically with MFC;the co-directional FTV realizes bidirectional continuous and stable control of the yaw attitude of tailless flying wing,without longitudinal/lateral coupling moment.The increment of the maximum yawing moment coefficient is 0.0029,the maximum yaw rate is 7.55(°)/s,and the response time of the yaw rate of the vectoring nozzle actuated by the secondary flow is about 0.06 s,which satisfies the heading stability augmentation and maneuvering control response requirements of the aircraft with statically unstable heading,and provides new control means for the heading rudderless attitude control of tailless flying wing.展开更多
基金supported by the National Natural Science Foundation of China(Nos.12341501 and 12575164)。
文摘X-rays are widely used in the non-destructive testing(NDT)of electrical equipment.Radio frequency(RF)electron linear accelerators can generate MeV high-energy X-rays with strong penetrating ability;however,the system generally has a large scale,which is not suitable for on-site testing.Compared with the S-band(S-linac)at the same stage of beam energy,the accelerator working in the X-band(X-linac)can compress the facility scale by over 2/3 in the longitudinal direction,which is convenient for the on-site NDT of electrical equipment.To address the beam quality and design complexity simultaneously,the non-dominated sorting genetic algorithmⅡ(NSGA-Ⅱ),which is a multi-objective genetic algorithm(MOGA),was developed to optimize the cavity chain design of the X-linac.Additionally,the designs of the focusing coils,electron gun,and RF couplers,which are other key components of the X-linac,were introduced in this context.In particular,the focusing coil distributions were optimized using a genetic algorithm.Furthermore,after designing such key components,PARMELA software was adopted to perform beam dynamics calculations with the optimized accelerating fields and magnetic fields.The results show that the beam performance was obtained with a capture ratio of more than 90%,an energy spread of less than 10%,and an average energy of approximately 3 MeV.The design and simulation results indicate that the proposed NSGAⅡ-based approach is feasible for X-linac accelerator design.Furthermore,it can be generalized as a universal technique for industrial electron linear accelerators provided that specific optimization objectives and constraints are set according to different application scenarios and requirements.
文摘The rapid progress in the construction of heavy-haul and high-speed railways has led to a surge in rail defects and unforeseen failures.Addressing this issue necessitates the implementation of more sophisticated rail inspection methods,specifically involving real-time,precise detection,and assessment of rail defects.Current applications fail to address the evolving requirements,prompting the need for advancements.This paper provides a summary of various types of rail defects and outlines both traditional and innovative non-destructive inspection techniques,examining their fundamental features,benefits,drawbacks,and practical suitability for railway track inspection.It also explores potential enhancements to equipment and software.The comprehensive review draws upon pertinent international research and review papers.Furthermore,the paper introduces a fusion of inspection methods aimed at enhancing the overall reliability of defect detection.
基金supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China(2024ZD0608100)the National Natural Science Foundation of China(62332017,U22A2022)
文摘In high-risk industrial environments like nuclear power plants,precise defect identification and localization are essential for maintaining production stability and safety.However,the complexity of such a harsh environment leads to significant variations in the shape and size of the defects.To address this challenge,we propose the multivariate time series segmentation network(MSSN),which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates.To tackle the classification difficulty caused by structural signal variance,MSSN employs logarithmic normalization to adjust instance distributions.Furthermore,it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences.Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95%localization and demonstrates the capture capability on the synthetic dataset.In a nuclear plant's heat transfer tube dataset,it captures 90%of defect instances with75%middle localization F1 score.
基金supported by the research networks Community Medicine,Molecular Medicine,GANI_MED and Digital Health Lab of the University Medicine Greifswald(grant number FOVB-2024-04).
文摘Objective This study describes acceptance and attitudes towards genetic cancer testing among German primary care patients.Design Cross-sectional survey.Setting Primary care.Participant Systematically recruited patients aged≥18 years from six general practices in Mecklenburg-Western Pomerania participated in an anonymous self-administered survey on familial cancer prevention(n=479 and 67.0%participation rate).Those with complete data were analysed(n=424;mean age 53.7,SD 16.6 years;men 34.4%).Linear regression analyses were used to examine potential disparities in general acceptance of genetic testing and attitudes towards genetic cancer testing according to sociodemographics and familial cancer knowledge.Result General acceptance of genetic testing was high,particularly among younger,higher-educated individuals and those with a family history of cancer and higher familial cancer knowledge.For example,83.3%either agreed or strongly agreed that it should be available to anybody.The most important benefits of genetic cancer testing were to guide check-up frequency(81.4%),to inform medical decision-making(80.2%)and to understand children’s risk(75.2%).The most important concerns included the potential burden on the family(44.6%)and the belief that cancer cannot be prevented(39.2%).More favourable attitudes were found among younger,higher-educated individuals,those with a personal history of cancer and those with fewer children or no partner.For example,higher age was linked to lower benefit(regression coefficient(RC)−0.01,95%CI−0.01 to−0.001)and higher concern ratings(RC 0.01,95%CI 0.002 to 0.01).About a third(34.7%)rated not wanting to know about genetic alterations that increase their cancer risk as a(very)important reason against testing.Information avoidance was higher among older individuals(RC 0.02,95%CI 0.01 to 0.02),women(RC 0.40,95%CI 0.11 to 0.69),those with lower education(RC−0.64,95%CI−0.91 to−0.36)and those with more children(RC 0.21,95%CI 0.09 to 0.33).Conclusion Acceptance of genetic testing was high,but barriers remain,particularly among older adults,women,the less educated and those with more children.Targeted educational efforts to improve health literacy,emphasise the preventive potential of genetic testing and emotional support through genetic counselling are essential to overcome these barriers and promote informed decision-making.
文摘In the current social environment,the importance of energy conservation and emission reduction is increasing day by day for both the country and its people.Electronic and electrical products,as important items for people’s production and life,require high attention from industry insiders in terms of their energy efficiency testing.Relying on energy efficiency testing can achieve the goal of energy conservation and emission reduction,and related quality control technologies will also inject new momentum into the green development of the industry.This article will discuss the practical strategies of quality control technology for energy efficiency testing of electronic and electrical products based on the significance of such testing,hoping to provide some help.
基金National Natural Science Foundation of China(No.62375048)Natural Science Foundation of Shanghai,China(No.22ZR1402600。
文摘Traditional spectrophotometers have a large volume and slow scanning speed,which limits their applicability for rapid on-site detection.Herein,a micro-spectrophotometer(named ATOM)is fabricated,and its performance is verified in water quality testing.An M-type Czerny-Turner light path structure,a broadband light emitting diode(LED)light source,and a linear charge-coupled device(CCD)photodetector were adopted in ATOM.The performance of ATOM was validated through iron content determination by using o-phenanthroline spectrophotometry.The experiment results showed that the linear correlation coefficient of determination R^(2) was 0.9997 for mass concentrations ranging from 0 to 2.0μg/mL.The relative standard deviation was 0.37%,and the relative error compared to a commercial large-scale spectrophotometer was below 1.4%.The dimensions of ATOM are 75 mm×60 mm×25 mm,with hardware costs of approximately 1000 CNY.ATOM features compact size,low cost,rapid measurement,high integration and high precision,making it suitable for portable on-site rapid detection.
文摘This study aims to construct a virtual twin testing framework for the safety of the intended functionality of intelligent connected vehicles to address the safety requirements of intelligent driving and transportation systems.The research methods include the construction of a theoretical model of safety for intelligent connected vehicles based on the concept of virtual twins,the correlation study between key concepts and functional safety,and the application research of virtual twin technology in the safety testing of intelligent connected vehicles.The results reveal that the virtual twin testing framework can effectively enhance the functional safety of intelligent connected vehicles,reduce development costs,and shorten the product launch cycle.The conclusion suggests that this framework provides strong support for the healthy development of the intelligent connected vehicle industry and has a positive impact on the safety and efficiency of intelligent transportation systems.
文摘Test case prioritization and ranking play a crucial role in software testing by improving fault detection efficiency and ensuring software reliability.While prioritization selects the most relevant test cases for optimal coverage,ranking further refines their execution order to detect critical faults earlier.This study investigates machine learning techniques to enhance both prioritization and ranking,contributing to more effective and efficient testing processes.We first employ advanced feature engineering alongside ensemble models,including Gradient Boosted,Support Vector Machines,Random Forests,and Naive Bayes classifiers to optimize test case prioritization,achieving an accuracy score of 0.98847 and significantly improving the Average Percentage of Fault Detection(APFD).Subsequently,we introduce a deep Q-learning framework combined with a Genetic Algorithm(GA)to refine test case ranking within priority levels.This approach achieves a rank accuracy of 0.9172,demonstrating robust performance despite the increasing computational demands of specialized variation operators.Our findings highlight the effectiveness of stacked ensemble learning and reinforcement learning in optimizing test case prioritization and ranking.This integrated approach improves testing efficiency,reduces late-stage defects,and improves overall software stability.The study provides valuable information for AI-driven testing frameworks,paving the way for more intelligent and adaptive software quality assurance methodologies.
文摘T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection methods face challenges owing to surface oxide scales,and conventional high-precision magnetic sensors are ineffective at high temperatures.To overcome these limitations,a small coil sensor was employed to measure the residual magnetism strength in oscillation traces,using metal magnetic memory and electromagnetic induction methods,which can carry out detection without an external excitation source.Using this technology,the proposed scheme successfully detects defects at high tempe-ratures(up to 670℃)without a cooling device.The key findings include the ability to detect both surface and near-surface defects,such as cracks and oscillation marks,with an enhanced signal-to-noise ratio(SNR)of 7.2 dB after signal processing.The method’s practicality was validated in a steel mill environment,where testing on casting slabs effectively detected defects,providing a foundation for improving industrial quality control.The proposed detection scheme offers a significant advancement in nondestructive testing(NDT)for high-temperature applications,contributing to more efficient and accurate monitoring of ferromagnetic material integrity.
基金College student innovation training program of Guangzhou University,202311078018the National Key Research and Development Program of China,2022YFE0201800+2 种基金Fundamental Research Funds for the Central Universities,24xkjc025Tertiary Education Scientific research project of Guangzhou Municipal Education Bureau,2024312227Guangzhou University Instrument and Equipment Open Sharing Fund,Year 2024。
文摘In this study,a novel colorimetric detection method for tryptophan is developed using Au@MnO_(2)NPs based on their redox reaction.Tryptophan etches the outer MnO_(2)NPs shell and forms a stable protective layer outside the released AuNPs core in situ,accompanied by a noticeable color change from brown to pink.According to the absorbance ratio of 545 nm and 580 nm(A_(545)/A_(580)),a rapid(within 1 min),accurate,and specific detection method for tryptophan is constructed amidst other common amino acids.Coupling with a smartphone application,integrated Au@MnO_(2)NPs-based portable test strips can be used for the point-of-care testing(POCT)of tryptophan.
文摘Members of the British Textile Machinery Association(BTMA)can look back on 2025 as a year marked by notable technological advances and continued progress in global trade,despite an uncertain and volatile market.“Our members have been very active over the past 12 months and this has resulted in new technologies for the production of technical fibres and fabrics,the introduction of AI and machine learning into process control systems and significant advances in materials testing,”says BTMA CEO Jason Kent.“There’s real excitement about what can be achieved in 2026 as we look ahead to upcoming exhibitions such as JEC Composites in Paris in March and Techtextil in Frankfurt in April.”
基金supported by the National Natural Science Foundation of China(Project No.42307555).
文摘At present,there is currently a lack of unified standard methods for the determination of antimony content in groundwater in China.The precision and trueness of related detection technologies have not yet been systematically and quantitatively evaluated,which limits the effective implementation of environmental monitoring.In response to this key technical gap,this study aimed to establish a standardized method for determining antimony in groundwater using Hydride Generation–Atomic Fluorescence Spectrometry(HG-AFS).Ten laboratories participated in inter-laboratory collaborative tests,and the statistical analysis of the test data was carried out in strict accordance with the technical specifications of GB/T 6379.2—2004 and GB/T 6379.4—2006.The consistency and outliers of the data were tested by Mandel's h and k statistics,the Grubbs test and the Cochran test,and the outliers were removed to optimize the data,thereby significantly improving the reliability and accuracy.Based on the optimized data,parameters such as the repeatability limit(r),reproducibility limit(R),and method bias value(δ)were determined,and the trueness of the method was statistically evaluated.At the same time,precision-function relationships were established,and all results met the requirements.The results show that the lower the antimony content,the lower the repeatability limit(r)and reproducibility limit(R),indicating that the measurement error mainly originates from the detection limit of the method and instrument sensitivity.Therefore,improving the instrument sensitivity and reducing the detection limit are the keys to controlling the analytical error and improving precision.This study provides reliable data support and a solid technical foundation for the establishment and evaluation of standardized methods for the determination of antimony content in groundwater.
基金supported by the Open Foundation of Key Laboratory of Cyberspace Security,Ministry of Education of China(KLCS20240211)。
文摘With the rapid development of Internet technology,REST APIs(Representational State Transfer Application Programming Interfaces)have become the primary communication standard in modern microservice architectures,raising increasing concerns about their security.Existing fuzz testing methods include random or dictionary-based input generation,which often fail to ensure both syntactic and semantic correctness,and OpenAPIbased approaches,which offer better accuracy but typically lack detailed descriptions of endpoints,parameters,or data formats.To address these issues,this paper proposes the APIDocX fuzz testing framework.It introduces a crawler tailored for dynamic web pages that automatically simulates user interactions to trigger APIs,capturing and extracting parameter information from communication packets.A multi-endpoint parameter adaptation method based on improved Jaccard similarity is then used to generalize these parameters to other potential API endpoints,filling in gaps in OpenAPI specifications.Experimental results demonstrate that the extracted parameters can be generalized with 79.61%accuracy.Fuzz testing using the enriched OpenAPI documents leads to improvements in test coverage,the number of valid test cases generated,and fault detection capabilities.This approach offers an effective enhancement to automated REST API security testing.
基金funded by the National Natural Science Foundation of China(Nos.52474165 and 52522404)。
文摘Cemented paste backfill(CPB)is a technology that achieves safe mining by filling the goaf with waste rocks,tailings,and other materials.It is an inevitable choice to deal with the development of deep and highly difficult mines and meet the requirements of environmental protection and safety regulations.It promotes the development of a circular economy in mines through the development of lowgrade resources and the resource utilization of waste,and extends the service life of mines.The mass concentration of solid content(abbreviated as“concentration”)is a critical parameter for CPB.However,discrepancies often arise between the on-site measurements and the pre-designed values due to factors such as groundwater inflow and segregation within the goaf,which cannot be evaluated after the solidification of CPB.This paper innovatively provides an in-situ non-destructive approach to identify the real concentration of CPB after curing for certain days using hyperspectral imaging(HSI)technology.Initially,the spectral variation patterns under different concentration conditions were investigated through hyperspectral scanning experiments on CPB samples.The results demonstrate that as the CPB concentration increases from 61wt%to 73wt%,the overall spectral reflectance gradually increases,with two distinct absorption peaks observed at 1407 and 1917 nm.Notably,the reflectance at 1407 nm exhibited a strong linear relationship with the concentration.Subsequently,the K-nearest neighbors(KNN)and support vector machine(SVM)algorithms were employed to classify and identify different concentrations.The study revealed that,with the KNN algorithm,the highest accuracy was achieved when K(number of nearest neighbors)was 1,although this resulted in overfitting.When K=3,the model displayed the optimal balance between accuracy and stability,with an accuracy of 95.03%.In the SVM algorithm,the highest accuracy of 98.24%was attained with parameters C(regularization parameter)=200 and Gamma(kernel coefficient)=10.A comparative analysis of precision,accuracy,and recall further highlighted that the SVM provided superior stability and precision for identifying CPB concentration.Thus,HSI technology offers an effective solution for the in-situ,non-destructive monitoring of CPB concentration,presenting a promising approach for optimizing and controlling CPB characteristic parameters.
基金Natural Science Foundation of Beijing Municipality under Grant L243004the National Natural Science Foundation of China under Grant 62403060.
文摘Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots.Despite notable progress in fall protection hardware,the theoretical foundation for modeling and the feasibility of conducting full-scale fall experiments on robots or their surrogates remain somewhat limited.This paper proposes a method for optimizing the thickness of Expandable Polyethylene(EPE),which is used as back protection for the Chubao humanoid robot,based on small-scale impact test data to predict full-scale behavior.The optimal thickness is defined as a balance between compact design and protective effectiveness.An equivalent impact model characterized by four parameters:contact area S,mass m,fall height h,and cushioning material thickness d is introduced to describe impact conditions.The relationship between the peak impact acceleration ap and material thickness d,which forms the core of the method and gives rise to the name AP-D,is analyzed through their plotted curves.After introducing three characteristic parameters and two correction fac-tors,the relationship among the aforementioned variables is derived.Subsequently,both the optimal thickness do and its corresponding peak impact acceleration aop are predicted via nonlinear and linear regression models.Finally,the accuracy and effectiveness of the theoretically derived optimal thickness are validated on both a dummy and the actual robot.With the cushioning material applied,the peak chest acceleration is reduced to 41.57g for the dummy and 32.08g for the robot.
基金supported by the MOST Key R&D Program of China(grant number 2022YFC2303500 to X.H.)the National Natural Science Foundation of China(grant numbers 32570236,32170195,and 32311530119 to C.C.and 32470200 to X.H.)+1 种基金Shanghai Science and Technology Innovation Action Plan 2023“Basic Research Project”(grant number 23JC1404200 to C.C.)the Foundation of State Key Laboratory of Pathogen and Biosecurity(grant number SKLPBS2236 to C.C.).
文摘Human fungal infections represent a rapidly emerging global health threat,especially threatening immunocompromised populations,highlighting the urgent need for accurate and timely diagnostic approaches to reduce morbidity and mortality.This review synthesizes recent advances in diagnostic methodologies,including serological assays,point-of-care diagnostics,polymerase chain reaction(PCR)-based and sequencing technologies,as well as artificial intelligence(AI)-and machine learning(ML)-powered tools.Emerging diagnostic approaches have demonstrated notable improvements in detection accuracy,turnaround time,and antifungal resistance profiling capabilities,especially for drug-resistant strains.Nevertheless,substantial challenges persist in terms of standardization,scalability,cost-effectiveness,and implementation,particularly in resource-constrained settings.Future efforts should be directed toward the continuous innovation of rapid,sensitive,and multiplex diagnostic platforms for the simultaneous detection of fungi,bacteria,and viruses.Such advances may accelerate result acquisition,enhance diagnostic accuracy,support the development of more targeted therapeutic strategies,and ultimately improve clinical outcomes for patients.
基金supported by the National Natural Science Foundation of China(22474032,22104032)to Mengyi Xiong and(22234003,21890744)to Xiao-Bing Zhangthe Natural Science Foundation of Shanxi Province(202303021221139)to Xuhua Zhao+1 种基金the China Postdoctoral Science Foundation(2024M761887)to Xuhua Zhaothe Innovation and Entrepreneurship Training Program for College Students(20161469)。
文摘Clustered regularly interspaced short palindromic repeats(CRISPR)systems have achieved significant advancements in precise molecular diagnosis.However,their applications in whole blood detection remain challenging due to signal interference from blood autofluorescence.Here,we proposed a universal and accessible bioluminescent CRISPR/Cas(bioLUCas)platform for direct detection of disease biomarkers in whole blood.By employing a specially designed cpHNLucMB reporter,the bioLUCas system converts CRISPR/Cas12a trans-cleavage activity into a ratiometric bioluminescent signal,producing a distinct emission color change.Compared to conventional CRISPR/Cas12a-based sensors,this platform eliminates the need for external light excitation,effectively bypassing blood autofluorescence and offering high sensitivity.Additionally,the visual signal of bioLUCas system allows user-friendly readout methods,such as smartphone.The platform successfully facilitated point-of-care test(POCT)for myeloperoxidase(MPO)in clinical acute myelogenous leukemia(AML)blood samples and hepatitis C virus(HCV)RNA in synthetic blood samples.This work may advance CRISPR/Cas technology for accessible whole-blood disease diagnostics.
文摘Fluidic Thrust Vectoring(FTV)is used for the yaw attitude control of tailless flying wing,which can significantly improve stealth performance,maneuverability and lateral/heading maneuverability.The FTV control scheme of co-directional secondary flow was designed based on a 30 kgf thrust turbojet engine,an equivalent rudder deflection control variable of Mass Flow Combination(MFC)was proposed,and a control model was established to form a FTV control system scheme,which was integrated with the flight control system of a 100 kg tailless flying wing with medium aspect ratio to achieve closed-loop control of the yaw attitude based on FTV.The heading stability augmentation and maneuvering control characteristics and time response characteristics of tailless flying wing by FTV were quantitatively studied through virtual flight test in a wind tunnel at a wind speed of 35 m/s.The results show that the control strategy based on MFC achieves bidirectional continuous and stable control of thrust vector angle in a range of±11°,and the thrust vector angle varies monotonically with MFC;the co-directional FTV realizes bidirectional continuous and stable control of the yaw attitude of tailless flying wing,without longitudinal/lateral coupling moment.The increment of the maximum yawing moment coefficient is 0.0029,the maximum yaw rate is 7.55(°)/s,and the response time of the yaw rate of the vectoring nozzle actuated by the secondary flow is about 0.06 s,which satisfies the heading stability augmentation and maneuvering control response requirements of the aircraft with statically unstable heading,and provides new control means for the heading rudderless attitude control of tailless flying wing.
