In this paper,a dynamic linear detecting method,that the non-linear coefficient NL% was led and the non-linearity of data were estimated continuously and dynamically and determined when NL% exceeded reference value (...In this paper,a dynamic linear detecting method,that the non-linear coefficient NL% was led and the non-linearity of data were estimated continuously and dynamically and determined when NL% exceeded reference value (5%),was used for data processing and could solve the problem caused by the phenomenon of substrate depleting occurred following the redox reaction in portable blood sugar analyzer.By contrast to the conventional end-point method,the dynamic linear detecting method is based on multipoint data collecting.Experiments of measuring the calibration glucose solution with 8 various concentrations from 50 mg/dl to 400 mg/dl were carried out with the analyzer developed by our group.The linear regression curve,whose correlation for the data was 0.9995 and the residual was 2.8080,were obtained.The obtained correlation,residual, and the computation workload are all fit for the portable blood sugar analyzer.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
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
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
In order to eliminate the subjectivity of wheeze diagnosis and improve the accuracy of objective detecting methods,this paper introduces a wheeze detecting method based on spectrogram entropy analysis.This algorithm m...In order to eliminate the subjectivity of wheeze diagnosis and improve the accuracy of objective detecting methods,this paper introduces a wheeze detecting method based on spectrogram entropy analysis.This algorithm mainly comprises three steps which are preprocessing,features extracting and wheeze detecting based on support vector machine(SVM).Herein,the preprocessing consists of the short-time Fourier transform(STFT) decomposition and detrending.The features are extracted from the entropy of spectrograms.The step of detrending makes the difference of the features between wheeze and normal lung sounds more obvious.Moreover,compared with the method whose decision is based on the empirical threshold,there is no uncertain detecting result any more.Results of two testing experiments show that the detecting accuracy(AC) are 97.1%and 95.7%,respectively,which proves that the proposed method could be an efficient way to detect wheeze.展开更多
The low frequency line components of the radiated noise from an underwater target usually have both high spectrum level and sustained stability. This feature could be used to increase the detection performance of conv...The low frequency line components of the radiated noise from an underwater target usually have both high spectrum level and sustained stability. This feature could be used to increase the detection performance of conventional broadband energy integration method. The required spectrum level is theoretically discussed when the detection performance of the known line detection is better than that of broadband energy integration method. Under the condition of the target can be detected in line spectrum band, the relationship between the line spectrum level and signal to noise ratio （SNR） is also discussed. This paper proposes a line spectrum target detection method that a matrix using DC jump to fluctuations ratios of sub-band spatial spectrum and beam space output is constructed. This matrix acts as a filter that the line spectrum target with certain frequency and azimuth is passed at most. By fusing with the other sub band results, the conventional detection performance can be improved. At the same time, the applicable condition and detection performance are analyzed in the paper. The simulation and the sea trial data processing results show that the algorithm can effectively extract weak goal line spectrum target under the condition of multi-interference. The algorithm doesn＇t need multi-frame statistics and the detection performance is closer to the optimal line spectrum method.展开更多
A new detecting method for the conditions of existence of the Hopf bifurcation is given in terms of the coefficients of the characteristic polynomial at the equilibrium by using the Hopf bifurcation theory and matrix ...A new detecting method for the conditions of existence of the Hopf bifurcation is given in terms of the coefficients of the characteristic polynomial at the equilibrium by using the Hopf bifurcation theory and matrix theory. The method is available and important for the study of the existence of the Hopf bifurcation for higher differential equations which often occur in biological models, chemical models, epidemiological models, and models of AIDS.展开更多
The breaking of wind-generated waves is an important phenomenon in the ocean, having close relation to many aspects of the ocean, such as air-sea interaction, ocean wave dynamics, oceanic remote sensing and ocean engi...The breaking of wind-generated waves is an important phenomenon in the ocean, having close relation to many aspects of the ocean, such as air-sea interaction, ocean wave dynamics, oceanic remote sensing and ocean engineering. The first problem encountered in both its theoretical study and practical measurement is how to detect the breaking of waves.展开更多
Network traffic anomalies refer to the traffic changed abnormally and obviously.Local events such as temporary network congestion,Distributed Denial of Service(DDoS)attack and large-scale scan,or global events such as...Network traffic anomalies refer to the traffic changed abnormally and obviously.Local events such as temporary network congestion,Distributed Denial of Service(DDoS)attack and large-scale scan,or global events such as abnormal network routing,can cause network anomalies.Network anomaly detection and analysis are very important to Computer Security Incident Response Teams(CSIRT).But wide-scale traffic anomaly detection requires extracting anomalous modes from large amounts of high-dimensional noise-rich data,and interpreting the modes;so,it is very difficult.This paper proposes a general method based on Principle Component Analysis(PCA)to analyze network anomalies.This method divides the traffic matrix into normal and anomalous subspaces,maps traffic vectors into the normal subspace,gets the distance from detected vector to average normal vector,and detects anomalies based on that distance.展开更多
As a new type of environmental pollutants,microplastics have gradually attracted people's attention.A large number of plastics discharged into the environment by human beings are constantly aging and breaking,and ...As a new type of environmental pollutants,microplastics have gradually attracted people's attention.A large number of plastics discharged into the environment by human beings are constantly aging and breaking,and finally become microplastics.Microplastics can adsorb pollutants in the environment,and their components have certain toxicity,which can cause different degrees of harm to organisms.Due to the structural characteristics of microplastic particles,such as small particle size,large specific surface area,and their distribution in different environmental media,it is very difficult to accurately detect microplastics.Reliable collection and detection methods are the key to the study of environmental behavior of microplastics.In this study,the collection and detection methods of microplastics in the environment were reviewed,and the development direction of microplastics detection technology in the future was prospected.This study has a certain reference value for the related research and the prevention and treatment of micro-plastic pollution.展开更多
To rapidly obtain high-quality genomic DNA from Chenopodium quinoa Willd, the genomic DAN in different tissues （leaves, stems and roots） of Chenopodi- um quinoa Willd was extracted by modified CTAB method, SDS metho...To rapidly obtain high-quality genomic DNA from Chenopodium quinoa Willd, the genomic DAN in different tissues （leaves, stems and roots） of Chenopodi- um quinoa Willd was extracted by modified CTAB method, SDS method and high- salt Iow-pH method, respectively. The quality and yield of extracted DNA was deter- mined using agarose gel electrophoresis and UV spectrophotometry. At the same time, the PCR-SSR and SSCP molecular detection was also performed. The results showed that the gel test strips, without obvious decomposition, of all the extraction methods were relatively obvious; the genomic DNA yield extracted by modified CTAB method was highest, followed by that by SDS method, and the genomic DNA extracted by high-salt Iow-pH method was lowest： the genomic DNA yields extracted by different methods from Chenopodium quinoa Wiltd leaves were all high- er than those from roots and stems; the quality of Chenopodium quinoa Willd ge- nomic DNA extracted by modified CTAB method and high-salt Iow-pH method was better, and polyphenols, polysaccharides and other impurities were removed more completely. The PCR-SSR and SSCP detection results showed that the genomic DNA extracted by different methods from different tissues of Chenopodium quinoa Willd all could be better amplified, and high-quality strips could be obtained. So the Chenopodium quinoa Willd genomic DNA extracted by the three methods all can be used for subsequent molecular biology research.展开更多
Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time perfor...Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.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
Lithium-plating-type defects in lithium-ion batteries pose severe safety risks due to their potential to trigger thermal runaway.To prevent defective batteries from entering the market,developing in-line detection met...Lithium-plating-type defects in lithium-ion batteries pose severe safety risks due to their potential to trigger thermal runaway.To prevent defective batteries from entering the market,developing in-line detection methods during manufacturing is critical yet challenging.This study introduces a deep learning-based method for detecting lithium-plating-type defects using formation and capacity grading data,enabling accurate identification of defective batteries without additional equipment.First,lithiumplating-type defect batteries with various types and area ratios are fabricated.Formation and capacity grading data from 154 batteries(48 defective,106 normal)are collected to construct a dataset.Subsequently,a dual-task deep learning model is then developed,where the reconstruction task learns latent representations from the features,while the classification task identifies the defective batteries.Shapley value analysis further quantifies feature importance,revealing that defective batteries exhibit reduced coulombic efficiency(attributed to irreversible lithium loss)and elevated open-circuit voltage/K-values(linked to self-equalization effects).These findings align with the electrochemical mechanisms of lithium plating,enhancing the model's interpretability.Validated on statistically robust samples shows that the framework achieves a recall of 97.14%for defective batteries and an overall accuracy of 97.42%.This deep learning-driven solution provides a scalable and cost-effective quality control strategy for battery manufacturing.展开更多
In heavy-duty long-distance transmission scenarios,steel wire ropes are widely used due to their unique advantages,and their safety is very important,which has also led to the rapid development of non-destructive test...In heavy-duty long-distance transmission scenarios,steel wire ropes are widely used due to their unique advantages,and their safety is very important,which has also led to the rapid development of non-destructive testing technology for steel wire ropes.The non-destructive testing technology for steel wire ropes is influenced by various factors such as its own structure and external working environment,and the testing process is relatively complex.Multiple testing methods and related types of sensors have also emerged.The electromagnetic detection method is currently the most effective method,but it also has its limitations in development and has not yet fully achieved the expected detection goals.In order to completely replace manual inspection work with the development of non-destructive testing technology for steel wire ropes,more in-depth research and long-term accumulation are still needed.展开更多
An example of using ultrasonic method to detect the compactness of complicated concrete-filled steel tube in certain high-rise building was discussed in this study.Because of the particularity of the complicated concr...An example of using ultrasonic method to detect the compactness of complicated concrete-filled steel tube in certain high-rise building was discussed in this study.Because of the particularity of the complicated concrete-filled steel tubular column,the plane detection method and embedded sounding pipe method were adopted in the process of effectively detecting the column.According to the results of the plane detection method and embedded sounding pipe method,the cementing status of steel tube and concrete can be concluded,which cannot be judged by the hammering method in the rectangular steel tube-reinforced concrete.展开更多
Simultaneous localization and mapping(SLAM) technology is a research hotspot in the field of intelligent mobile robot, and many researchers have developed many classic systems in the past few decades. However, most of...Simultaneous localization and mapping(SLAM) technology is a research hotspot in the field of intelligent mobile robot, and many researchers have developed many classic systems in the past few decades. However, most of the existing SLAM methods assume that the environment of the robot is static, which results in the performance of the system being greatly reduced in the dynamic environment. To solve this problem, a new dynamic object detection method based on point cloud motion analysis is proposed and incorporated into ORB-SLAM2. First, the method is regarded as a preprocessing stage, detecting moving objects in the scene, and then removing the moving objects to enhance the performance of the SLAM system. Experiments performed on a public RGB-D dataset show that the motion cancellation method proposed in this paper can effectively improve the performance of ORB-SLAM2 in a highly dynamic environment.展开更多
Avian influenza （AI）, caused by the influenza A virus, has been a global concern for public health. AI outbreaks not only impact the poultry production, but also give rise to a risk in food safety caused by viral co...Avian influenza （AI）, caused by the influenza A virus, has been a global concern for public health. AI outbreaks not only impact the poultry production, but also give rise to a risk in food safety caused by viral contamination of poultry products in the food supply chain. Distinctions in AI outbreak between strains H5N1 and H7N9 indicate that early detection of the AI virus in poultry is crucial for the effective warning and control of AI to ensure food safety. Therefore, the establishment of a poultry surveillance system for food safety by early detection is urgent and critical. In this article, methods to detect AI virus, including current methods recommended by the World Health Organization （WHO） and the World Organisation for Animal Health （Office International des Epizooties, OIE） and novel techniques not commonly used or commercialized are reviewed and evaluated for feasibility of use in the poultry surveillance system. Conventional methods usually applied for the purpose of AI diagnosis face some practical challenges to establishing a comprehensive poultry surveillance program in the poultry supply chain. Diverse development of new technologies can meet the specific requirements of AI virus detection in various stages or scenarios throughout the poultry supply chain where onsite, rapid and ultrasensitive methods are emphasized. Systematic approaches or integrated methods ought to be employed according to the application scenarios at every stage of the poultry supply chain to prevent AI outbreaks.展开更多
Real-time liquefaction monitoring and warning techniques are new ways to mitigate liquefaction hazard. A key point is to establish a reverse liquefaction detection method based on seismic records. However, the existin...Real-time liquefaction monitoring and warning techniques are new ways to mitigate liquefaction hazard. A key point is to establish a reverse liquefaction detection method based on seismic records. However, the existing methods are quite limited and the reliability requires verification. On Feb. 22, 2011 an earthquake of magnitude 6.3 struck at New Zealand＇s South Island. Remarkable liquefaction phenomena were reported, which provide an opportunity to verify the existing liquefaction detection methods. 27 acceleration records within 50 km to the epicenter were selected to perform a blind detection by using the existing methods, including Miyajima method, Suzuki method, Kostadinov-Yamazaki method and Yuan-Sun method. The blind detection results indicate that Yuan-Sun method gives correct results for seven confirmed sites, and Suzuki method and Yuan-Sun method yield correct detection for a reported non-liquefied site. Four methods including the Yuan-Sun method give identical detection for four sites and three methods also including the Yuan-Sun method give identical detection for ten sites. Besides, there are five sites, for which the four methods give opposite detection.展开更多
Surface irradiance measurements with high temporal resolution can be used to detect clear skies,which is a critical step for further study,such as aerosol and cloud radiative effects.Twenty-one clear-sky detection(CSD...Surface irradiance measurements with high temporal resolution can be used to detect clear skies,which is a critical step for further study,such as aerosol and cloud radiative effects.Twenty-one clear-sky detection(CSD)methods are assessed based on five years of 1-min surface irradiance data at Xianghe—a heavily polluted station on the North China Plain.Total-sky imager(TSI)discrimination results corrected by manual checks are used as the benchmark for the evaluation.The performance heavily relies on the criteria adopted by the CSD methods.Those with higher cloudy-sky detection accuracy rates produce lower clear-sky accuracy rates,and vice versa.A general tendency in common among all CSD methods is the detection accuracy deteriorates when aerosol loading increases.Nearly all criteria adopted in CSD methods are too strict to detect clear skies under polluted conditions,which is more severe if clear-sky irradiance is not properly estimated.The mean true positive rate(CSD method correctly detects clear sky)decreases from 45%for aerosol optical depth(AOD)≤0.2%to 6%for AOD>0.5.The results clearly indicate that CSD methods in a highly polluted region still need further improvements.展开更多
文摘In this paper,a dynamic linear detecting method,that the non-linear coefficient NL% was led and the non-linearity of data were estimated continuously and dynamically and determined when NL% exceeded reference value (5%),was used for data processing and could solve the problem caused by the phenomenon of substrate depleting occurred following the redox reaction in portable blood sugar analyzer.By contrast to the conventional end-point method,the dynamic linear detecting method is based on multipoint data collecting.Experiments of measuring the calibration glucose solution with 8 various concentrations from 50 mg/dl to 400 mg/dl were carried out with the analyzer developed by our group.The linear regression curve,whose correlation for the data was 0.9995 and the residual was 2.8080,were obtained.The obtained correlation,residual, and the computation workload are all fit for the portable blood sugar analyzer.
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.
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.
文摘In order to eliminate the subjectivity of wheeze diagnosis and improve the accuracy of objective detecting methods,this paper introduces a wheeze detecting method based on spectrogram entropy analysis.This algorithm mainly comprises three steps which are preprocessing,features extracting and wheeze detecting based on support vector machine(SVM).Herein,the preprocessing consists of the short-time Fourier transform(STFT) decomposition and detrending.The features are extracted from the entropy of spectrograms.The step of detrending makes the difference of the features between wheeze and normal lung sounds more obvious.Moreover,compared with the method whose decision is based on the empirical threshold,there is no uncertain detecting result any more.Results of two testing experiments show that the detecting accuracy(AC) are 97.1%and 95.7%,respectively,which proves that the proposed method could be an efficient way to detect wheeze.
文摘The low frequency line components of the radiated noise from an underwater target usually have both high spectrum level and sustained stability. This feature could be used to increase the detection performance of conventional broadband energy integration method. The required spectrum level is theoretically discussed when the detection performance of the known line detection is better than that of broadband energy integration method. Under the condition of the target can be detected in line spectrum band, the relationship between the line spectrum level and signal to noise ratio （SNR） is also discussed. This paper proposes a line spectrum target detection method that a matrix using DC jump to fluctuations ratios of sub-band spatial spectrum and beam space output is constructed. This matrix acts as a filter that the line spectrum target with certain frequency and azimuth is passed at most. By fusing with the other sub band results, the conventional detection performance can be improved. At the same time, the applicable condition and detection performance are analyzed in the paper. The simulation and the sea trial data processing results show that the algorithm can effectively extract weak goal line spectrum target under the condition of multi-interference. The algorithm doesn＇t need multi-frame statistics and the detection performance is closer to the optimal line spectrum method.
文摘A new detecting method for the conditions of existence of the Hopf bifurcation is given in terms of the coefficients of the characteristic polynomial at the equilibrium by using the Hopf bifurcation theory and matrix theory. The method is available and important for the study of the existence of the Hopf bifurcation for higher differential equations which often occur in biological models, chemical models, epidemiological models, and models of AIDS.
文摘The breaking of wind-generated waves is an important phenomenon in the ocean, having close relation to many aspects of the ocean, such as air-sea interaction, ocean wave dynamics, oceanic remote sensing and ocean engineering. The first problem encountered in both its theoretical study and practical measurement is how to detect the breaking of waves.
基金This work was funded by the High-tech Research and Development Program of China (863 Program) under Grant 2006II01Z451.
文摘Network traffic anomalies refer to the traffic changed abnormally and obviously.Local events such as temporary network congestion,Distributed Denial of Service(DDoS)attack and large-scale scan,or global events such as abnormal network routing,can cause network anomalies.Network anomaly detection and analysis are very important to Computer Security Incident Response Teams(CSIRT).But wide-scale traffic anomaly detection requires extracting anomalous modes from large amounts of high-dimensional noise-rich data,and interpreting the modes;so,it is very difficult.This paper proposes a general method based on Principle Component Analysis(PCA)to analyze network anomalies.This method divides the traffic matrix into normal and anomalous subspaces,maps traffic vectors into the normal subspace,gets the distance from detected vector to average normal vector,and detects anomalies based on that distance.
基金Supported by Project of National Center of Technology Innovation for Dairy"Study on the Key Technologies of Microplastics Detection for New Pollutants in Dairy Ingredient Water"(2023-KFKT-24).
文摘As a new type of environmental pollutants,microplastics have gradually attracted people's attention.A large number of plastics discharged into the environment by human beings are constantly aging and breaking,and finally become microplastics.Microplastics can adsorb pollutants in the environment,and their components have certain toxicity,which can cause different degrees of harm to organisms.Due to the structural characteristics of microplastic particles,such as small particle size,large specific surface area,and their distribution in different environmental media,it is very difficult to accurately detect microplastics.Reliable collection and detection methods are the key to the study of environmental behavior of microplastics.In this study,the collection and detection methods of microplastics in the environment were reviewed,and the development direction of microplastics detection technology in the future was prospected.This study has a certain reference value for the related research and the prevention and treatment of micro-plastic pollution.
基金Supported by National Natural Science Foundation of China(31301372)Key Project of Science and Technology Plan of Zhejiang Province(2011C12030)Innovation Training Project of Zhejiang Agriculture and Forestry University(201301004)~~
文摘To rapidly obtain high-quality genomic DNA from Chenopodium quinoa Willd, the genomic DAN in different tissues （leaves, stems and roots） of Chenopodi- um quinoa Willd was extracted by modified CTAB method, SDS method and high- salt Iow-pH method, respectively. The quality and yield of extracted DNA was deter- mined using agarose gel electrophoresis and UV spectrophotometry. At the same time, the PCR-SSR and SSCP molecular detection was also performed. The results showed that the gel test strips, without obvious decomposition, of all the extraction methods were relatively obvious; the genomic DNA yield extracted by modified CTAB method was highest, followed by that by SDS method, and the genomic DNA extracted by high-salt Iow-pH method was lowest： the genomic DNA yields extracted by different methods from Chenopodium quinoa Wiltd leaves were all high- er than those from roots and stems; the quality of Chenopodium quinoa Willd ge- nomic DNA extracted by modified CTAB method and high-salt Iow-pH method was better, and polyphenols, polysaccharides and other impurities were removed more completely. The PCR-SSR and SSCP detection results showed that the genomic DNA extracted by different methods from different tissues of Chenopodium quinoa Willd all could be better amplified, and high-quality strips could be obtained. So the Chenopodium quinoa Willd genomic DNA extracted by the three methods all can be used for subsequent molecular biology research.
基金supported by the National Key Research and Development Project of China(No.2023YFB3709605)the National Natural Science Foundation of China(No.62073193)the National College Student Innovation Training Program(No.202310422122)。
文摘Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.
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.
基金supported by the National Natural Science Foundation of China(NSFC,52277223 and 51977131)the Shanghai Pujiang Programme(23PJD062)。
文摘Lithium-plating-type defects in lithium-ion batteries pose severe safety risks due to their potential to trigger thermal runaway.To prevent defective batteries from entering the market,developing in-line detection methods during manufacturing is critical yet challenging.This study introduces a deep learning-based method for detecting lithium-plating-type defects using formation and capacity grading data,enabling accurate identification of defective batteries without additional equipment.First,lithiumplating-type defect batteries with various types and area ratios are fabricated.Formation and capacity grading data from 154 batteries(48 defective,106 normal)are collected to construct a dataset.Subsequently,a dual-task deep learning model is then developed,where the reconstruction task learns latent representations from the features,while the classification task identifies the defective batteries.Shapley value analysis further quantifies feature importance,revealing that defective batteries exhibit reduced coulombic efficiency(attributed to irreversible lithium loss)and elevated open-circuit voltage/K-values(linked to self-equalization effects).These findings align with the electrochemical mechanisms of lithium plating,enhancing the model's interpretability.Validated on statistically robust samples shows that the framework achieves a recall of 97.14%for defective batteries and an overall accuracy of 97.42%.This deep learning-driven solution provides a scalable and cost-effective quality control strategy for battery manufacturing.
文摘In heavy-duty long-distance transmission scenarios,steel wire ropes are widely used due to their unique advantages,and their safety is very important,which has also led to the rapid development of non-destructive testing technology for steel wire ropes.The non-destructive testing technology for steel wire ropes is influenced by various factors such as its own structure and external working environment,and the testing process is relatively complex.Multiple testing methods and related types of sensors have also emerged.The electromagnetic detection method is currently the most effective method,but it also has its limitations in development and has not yet fully achieved the expected detection goals.In order to completely replace manual inspection work with the development of non-destructive testing technology for steel wire ropes,more in-depth research and long-term accumulation are still needed.
文摘An example of using ultrasonic method to detect the compactness of complicated concrete-filled steel tube in certain high-rise building was discussed in this study.Because of the particularity of the complicated concrete-filled steel tubular column,the plane detection method and embedded sounding pipe method were adopted in the process of effectively detecting the column.According to the results of the plane detection method and embedded sounding pipe method,the cementing status of steel tube and concrete can be concluded,which cannot be judged by the hammering method in the rectangular steel tube-reinforced concrete.
基金supported by the National Natural Science Foundation of China (No.61876167)the Natural Science Foundation of Zhejiang Province (No.LY20F030017)。
文摘Simultaneous localization and mapping(SLAM) technology is a research hotspot in the field of intelligent mobile robot, and many researchers have developed many classic systems in the past few decades. However, most of the existing SLAM methods assume that the environment of the robot is static, which results in the performance of the system being greatly reduced in the dynamic environment. To solve this problem, a new dynamic object detection method based on point cloud motion analysis is proposed and incorporated into ORB-SLAM2. First, the method is regarded as a preprocessing stage, detecting moving objects in the scene, and then removing the moving objects to enhance the performance of the SLAM system. Experiments performed on a public RGB-D dataset show that the motion cancellation method proposed in this paper can effectively improve the performance of ORB-SLAM2 in a highly dynamic environment.
基金supported by the National Natural Science Foundation of China (21405008)the Shenzhen Municipal Government Subsidies for Postdoctoral Research+1 种基金the Special Fund for Sino-US Joint Research Center for Food Safety in Northwest A&F University, China (A200021501)the Start-up Funds for Talents in Northwest A&F University, China (Z111021403)
文摘Avian influenza （AI）, caused by the influenza A virus, has been a global concern for public health. AI outbreaks not only impact the poultry production, but also give rise to a risk in food safety caused by viral contamination of poultry products in the food supply chain. Distinctions in AI outbreak between strains H5N1 and H7N9 indicate that early detection of the AI virus in poultry is crucial for the effective warning and control of AI to ensure food safety. Therefore, the establishment of a poultry surveillance system for food safety by early detection is urgent and critical. In this article, methods to detect AI virus, including current methods recommended by the World Health Organization （WHO） and the World Organisation for Animal Health （Office International des Epizooties, OIE） and novel techniques not commonly used or commercialized are reviewed and evaluated for feasibility of use in the poultry surveillance system. Conventional methods usually applied for the purpose of AI diagnosis face some practical challenges to establishing a comprehensive poultry surveillance program in the poultry supply chain. Diverse development of new technologies can meet the specific requirements of AI virus detection in various stages or scenarios throughout the poultry supply chain where onsite, rapid and ultrasensitive methods are emphasized. Systematic approaches or integrated methods ought to be employed according to the application scenarios at every stage of the poultry supply chain to prevent AI outbreaks.
基金National Natural Science Foundation of China Under Grant No.50078165
文摘Real-time liquefaction monitoring and warning techniques are new ways to mitigate liquefaction hazard. A key point is to establish a reverse liquefaction detection method based on seismic records. However, the existing methods are quite limited and the reliability requires verification. On Feb. 22, 2011 an earthquake of magnitude 6.3 struck at New Zealand＇s South Island. Remarkable liquefaction phenomena were reported, which provide an opportunity to verify the existing liquefaction detection methods. 27 acceleration records within 50 km to the epicenter were selected to perform a blind detection by using the existing methods, including Miyajima method, Suzuki method, Kostadinov-Yamazaki method and Yuan-Sun method. The blind detection results indicate that Yuan-Sun method gives correct results for seven confirmed sites, and Suzuki method and Yuan-Sun method yield correct detection for a reported non-liquefied site. Four methods including the Yuan-Sun method give identical detection for four sites and three methods also including the Yuan-Sun method give identical detection for ten sites. Besides, there are five sites, for which the four methods give opposite detection.
基金supported by the National Key R&D Program of China grant number 2017YFA0603504the Strategic Priority Research Program of the Chinese Academy of Sciences grant number XDA17010101the National Natural Science Foundation of Chinagrant number 41875183。
文摘Surface irradiance measurements with high temporal resolution can be used to detect clear skies,which is a critical step for further study,such as aerosol and cloud radiative effects.Twenty-one clear-sky detection(CSD)methods are assessed based on five years of 1-min surface irradiance data at Xianghe—a heavily polluted station on the North China Plain.Total-sky imager(TSI)discrimination results corrected by manual checks are used as the benchmark for the evaluation.The performance heavily relies on the criteria adopted by the CSD methods.Those with higher cloudy-sky detection accuracy rates produce lower clear-sky accuracy rates,and vice versa.A general tendency in common among all CSD methods is the detection accuracy deteriorates when aerosol loading increases.Nearly all criteria adopted in CSD methods are too strict to detect clear skies under polluted conditions,which is more severe if clear-sky irradiance is not properly estimated.The mean true positive rate(CSD method correctly detects clear sky)decreases from 45%for aerosol optical depth(AOD)≤0.2%to 6%for AOD>0.5.The results clearly indicate that CSD methods in a highly polluted region still need further improvements.
