As a kind of relatively clean fossil energy,natural gas will face severe uncertainties in the background of carbon neutrality.Reviewing the medium-and long-term development trend of natural gas consumption is the prer...As a kind of relatively clean fossil energy,natural gas will face severe uncertainties in the background of carbon neutrality.Reviewing the medium-and long-term development trend of natural gas consumption is the prerequisite to better understanding the status of natural gas and ensure the sustainable development of natural gas industry.In this paper,a multi-model comparison framework is established on the basis of 8 representative integrated assessment models(CE3METL,DNE21+,IPAC,AIM/CGE,IMAGE,REMIND,WITCH and POLES).Then,the medium-and long-term evolution trend of China's total primary energy consumption and natural gas consumption in different scenarios of climate policy is discussed.In addition,comparative analysis is conducted on key time nodes such as 2030,2045 and 2060.And the following research results are obtained.Firstly,the prediction results of most models indicate that China's total primary energy consumption in 2060 will be lower than the level in 2019 except for the scenario of national determined contribution(NDC).Secondly,by 2060,the carbon neutrality goal year,the cross-model average level of natural gas consumption under the NDC,2.0℃,and 1.5℃ scenarios will be 6943×10^(8)m^(3),4342×10^(8)m^(3)and 2502×10^(8)m^(3),respectively.Thirdly,under the 1.5℃scenario,the decrease of total primary energy consumption shall begin in 2020,which means that faster technological progress and more effective combination of“nudge”policies are needed.Fourthly,under the temperature control goal of 2.0℃,natural gas consumption will account for about 13.6% of China's primary energy consumption in 2060,and this proportion will drop to 9% under the stricter 1.5℃ scenario.In conclusion,the multi-model comparison results can present different development paths of China's total primary energy consumption and natural gas consumption and its proportion during 2020-2060 more comprehensively,so as to provide support for formulating the medium-and long-term policies and strategies of natural gas industry under the challenge of climate change.展开更多
OBJECTIVE:To develop an automated system for identifying and classifying constitution types in Traditional Chinese Medicine(TCM)by leveraging multi-model fusion algorithms.METHODS:A condensed version of a physical inf...OBJECTIVE:To develop an automated system for identifying and classifying constitution types in Traditional Chinese Medicine(TCM)by leveraging multi-model fusion algorithms.METHODS:A condensed version of a physical information collection form was designed to facilitate efficient data acquisition.The collected data were analyzed using a multi-model fusion approach,which integrated several machine learning techniques.These included support vector machines,Naive Bayes,decision trees,random forests,logistic regression,multilayer perceptrons,K-nearest neighbors,gradient boosting,adaptive ensemble learning,and recurrent neural networks.A soft voting strategy was used to combine the predictive outputs of each model,enabling the selection of the most effective model combination.RESULTS:The classification models demonstrated consistent and robust performance across most TCM constitution types when enhanced by the multi-model fusion strategy.In particular,high levels of accuracy,precision,recall,and F1-score were achieved for constitution types such as Yang deficiency,Qi deficiency,and Qi stagnation.However,the classification performance for the Yin deficiency constitution was relatively lower,indicating the need for further refinement and optimization in future research.CONCLUSION:This study introduces a novel,automated method for classifying TCM constitution types through the application of multi-model fusion algorithms.The approach simplifies the complex task of constitution identification while offering a practical and theoretical framework for the intelligent diagnosis of TCM body types.The findings have the potential to enhance personalized health management and support clinical decision-making in TCM diagnosis and treatment.展开更多
[Objectives]This study was conducted to achieve rapid and accurate detection of protein content in rice with a particle size of 1.0 mm.[Methods]A multi-model fusion strategy was proposed on the basis of Stacking ensem...[Objectives]This study was conducted to achieve rapid and accurate detection of protein content in rice with a particle size of 1.0 mm.[Methods]A multi-model fusion strategy was proposed on the basis of Stacking ensemble learning.A base learner pool was constructed,containing Partial Least Squares(PLS),Support Vector Machine(SVM),Deep Extreme Learning Machine(DELM),Random Forest(RF),Gradient Boosting Decision Tree(GBDT),and Multilayer Perceptron(MLP).PLS,DELM,and Linear Regression(LR)were used as meta-learner candidates.Employing integer coding technology,systematic dynamic combinations of base learners and meta-learners were generated,resulting in a total of 40 non-repetitive fusion models.The optimal combination was selected through a comprehensive evaluation based on multiple assessment indicators.[Results]The combination"PLS-DELM-MLP-LR"(code 1367)achieved coefficients of determination of 0.9732 and 0.9780 on the validation set and independent test set,respectively,with relative root mean square errors of 2.35%and 2.36%,and residual predictive deviations of 6.1075 and 6.7479,respectively.[Conclusions]The Stacking fusion model significantly enhances the predictive accuracy and robustness of spectral quantitative analysis,providing an efficient and feasible solution for modeling complex agricultural product spectral data.展开更多
China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the qua...China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the quantitative measurement ability of the PMR is critical.China operates more than 250 weather radars over the mainland.Consistency of the spaceborne radar with ground-based radars will enhance precipitation measurement ability,especially over oceans and mountains where observations are sparse.Additionally,the spaceborne radar can be used to evaluate the spatial and temporal homogeneity of the ground-based radar network.This paper focuses on comparing the PMR onboard the FY-3G satellite with S-band China New Generation Weather Radars(CINRADs).A comparison algorithm between the PMR and CINRADs has been developed,incorporating detailed quality control,attenuation correction,data optimization,spatiotemporal matching,non-uniform beam filling constraint,uniformity constraint,and frequency correction.The matched data in typical months of four seasons were selected to carry out the comparison.The data consistency between the PMR and CINRADs was analyzed.The correlation coefficient is 0.87,the deviation is 0.89 dB,and the standard deviation is 2.50 dB,based on 98226 matching samples.The results show the radar reflectivity of the PMR is quite comparable to that of the CINRADs,demonstrating that the PMR data quality is satisfactory and can be used to verify and correct data consistency among multiple ground-based radars.This work also paves the way for data fusion and joint application of satellite and ground radars in the future.展开更多
Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi...Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi-firmware comparison method based on evolutionary algorithms and trusted base points.We first model the multi-firmware comparison as a multi-sequence matching problem.Then,we propose an adaptation function and a population generation method based on trusted base points.Finally,we apply an evolutionary algorithm to find the optimal result.At the same time,we design the similarity of matching results as an evaluation metric to measure the effect of multi-firmware comparison.The experiments show that the proposed method outperforms Bindiff and the string-based method.Precisely,the similarity between the matching results of the proposed method and Bindiff matching results is 61%,and the similarity between the matching results of the proposed method and the string-based method is 62.8%.By sampling and manual verification,the accuracy of the matching results of the proposed method can be about 66.4%.展开更多
Intelligent Automation&Soft Computing has retracted the article titled“Line Trace Effective Comparison AlgorithmBased onWavelet Domain DTW”[1],Intell Automat Soft Comput.2019;25(2):359–366 at the request of the...Intelligent Automation&Soft Computing has retracted the article titled“Line Trace Effective Comparison AlgorithmBased onWavelet Domain DTW”[1],Intell Automat Soft Comput.2019;25(2):359–366 at the request of the authors.DOI:10.31209/2019.100000097 URL:https://www.techscience.com/iasc/v25n2/39663 The article duplicates significant parts of a paper published in Journal of Intelligent&Fuzzy Systems[2].展开更多
In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceana...In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceanatmosphere models,which exhibit varying levels of complexity.This nonlinear approach demonstrated extraordinary superiority and effectiveness in constructing ENSO MME.Subsequently,we employed the leave-one-out crossvalidation and the moving base methods to further validate the robustness of the neural network model in the formulation of ENSO MME.In conclusion,the neural network algorithm outperforms the conventional approach of assigning a uniform weight to all models.This is evidenced by an enhancement in correlation coefficients and reduction in prediction errors,which have the potential to provide a more accurate ENSO forecast.展开更多
Previous bidirectional quantum private comparison(BQPC)protocols cannot meet the requirements in some special application scenarios,where only one party needs to obtain the comparison results without a third party(TP)...Previous bidirectional quantum private comparison(BQPC)protocols cannot meet the requirements in some special application scenarios,where only one party needs to obtain the comparison results without a third party(TP),such as scenarios for authority surveys or healthcare data sharing.In addition to this,the BQPC protocol has the potential of information leakage in multiple comparisons.Therefore,we design a new unidirectional quantum private comparison(UQPC)protocol based on quantum private query(QPQ)protocols with ideal database security and zero failure probability(IDS-ZF),for the reason that they have excellent unidirectionality and security.Concretely,we design a UQPC protocol based on Wei et al.’s work[IEEE Transactions on Computers 672(2017)]and it includes an authentication process to increase the resistance to outside attacks.Moreover,we generalize the protocol and propose a general model that can transform a QPQ protocol with or without the IDS-ZF property into a secure UQPC protocol.Finally,our study shows that protocols using our model are secure,practical,and have the IDS-ZF property.展开更多
Given that the citrus psyllid is the primary vector of citrus Huanglongbing(HLB),there is an urgent need to control this pest to mitigate the spread of the disease.This paper reviews the current research on two predom...Given that the citrus psyllid is the primary vector of citrus Huanglongbing(HLB),there is an urgent need to control this pest to mitigate the spread of the disease.This paper reviews the current research on two predominant control strategies:chemical control and biological control agents,in managing the citrus psyllid.It emphasizes the mechanisms of action,efficacy,and application advancements of these control methods.Finally,the paper analyzes the principal challenges associated with the sustainable management of citrus psyllids and offers perspectives for future research.展开更多
BACKGROUND Endoscopic retrograde cholangiopancreatography(ERCP)is an essential diagnostic and therapeutic procedure for pancreatobiliary disorders.However,few large-scale studies from South Asia have examined long-ter...BACKGROUND Endoscopic retrograde cholangiopancreatography(ERCP)is an essential diagnostic and therapeutic procedure for pancreatobiliary disorders.However,few large-scale studies from South Asia have examined long-term ERCP outcomes,particularly using established quality benchmarks.AIM To evaluate ERCP indications,success rates,complications,and quality performance at a high-volume tertiary care center in Pakistan over a 17-year period.METHODS This retrospective study analyzed 13215 ERCP procedures performed between 2006 and 2023.Data included demographics,indications,cannulation rates,complications,and pediatric cases.Findings were assessed against American Society of Gastroenterology/European Society of Gastrointestinal Endoscopy quality indicators.RESULTS Biliary ERCP accounted for 93.1%of procedures;choledocholithiasis was the most common indication(40%).Cannulation success was 93.9%for biliary and 94.2%for pancreatic ERCP.Pediatric ERCP comprised 4%of cases,mostly for stones and chronic pancreatitis.Bleeding(1.7%)and post-ERCP pancreatitis(2.3%)were the most frequent complications.Performance met or exceeded most American Society of Benchmarks.CONCLUSION This study offers insight into nearly two decades of ERCP practice within a public sector hospital.Our experience echoes the quality and efficiency of ERCP not previously available in Pakistan.As healthcare systems in resourcelimited sectors expand,our findings serve as a reference point.Continued training and quality improvement studies can further enhance ERCP effectiveness in the region and beyond.展开更多
The NEutron Detector Array(NEDA)is designed to be coupled to gamma-ray spectrometers to enhance the sensitivity of the setup by enabling reaction channel selection through counting of the evaporated neutrons.This arti...The NEutron Detector Array(NEDA)is designed to be coupled to gamma-ray spectrometers to enhance the sensitivity of the setup by enabling reaction channel selection through counting of the evaporated neutrons.This article presents the implementation of a double trigger condition system for NEDA,which improves the acquisition of neutrons and reduces the number of gamma rays acquired.Two independent triggers are generated in the double trigger condition system:one based on charge comparison(CC)and the other on time-of-flight(TOF).These triggers can be combined using OR and AND logic,offering four distinct trigger modes.The developed firmware is added to the previous one in the Virtex 6 field programmable gate array(FPGA)present in the system,which also includes signal processing,baseline correction,and various trigger logic blocks.The performance of the trigger system is evaluated using data from the E703 experiment performed at GANIL.The four trigger modes are applied to the same data,and a subsequent offline analysis is performed.It is shown that most of the detected neutrons are preserved with the AND mode,and the total number of gamma rays is significantly reduced.Compared with the CC trigger mode,the OR trigger mode allows increasing the selection of neutrons.In addition,it is demonstrated that if the OR mode is selected,the online CC trigger threshold can be raised without losing neutrons.展开更多
Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the co...Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the complex and time-consuming nature of traditional sequential laboratory extraction methods for determining the forms of HMs in tailings,a rapid and precise identification approach is urgently required.To address this issue,a general empirical prediction method for HM occurrence was developed using machine learning(ML).The compositional information of the tailings,properties of the HMs,and sequential extraction steps were used as inputs to calculate the percentages of the seven forms of HMs.After the models were tuned and compared,extreme gradient boosting,gradient boosting decision tree,and categorical boosting methods were found to be the top three performing ML models,with the coefficient of determination(R^(2))values on the testing set exceeding 0.859.Feature importance analysis for these three optimal models indicated that electronegativity was the most important factor affecting the occurrence of HMs,with an average feature importance of 0.4522.The subsequent use of stacking as a model integration method enabled the ability of the ML models to predict HM occurrence forms to be further improved,and resulting in an increase of R^(2) to 0.879.Overall,this study developed a robust technique for predicting the occurrence forms in tailings and provides an important reference for the environmental assessment and recycling of tailings.展开更多
Driven by rapid technological advancements and economic growth,mineral extraction and metal refining have increased dramatically,generating huge volumes of tailings and mine waste(TMWs).Investigating the morphological...Driven by rapid technological advancements and economic growth,mineral extraction and metal refining have increased dramatically,generating huge volumes of tailings and mine waste(TMWs).Investigating the morphological fractions of heavy metals and metalloids(HMMs)in TMWs is key to evaluating their leaching potential into the environment;however,traditional experiments are time-consuming and labor-intensive.In this study,10 machine learning(ML)algorithms were used and compared for rapidly predicting the morphological fractions of HMMs in TMWs.A dataset comprising 2376 data points was used,with mineral composition,elemental properties,and total concentration used as inputs and concentration of morphological fraction used as output.After grid search optimization,the extra tree model performed the best,achieving coefficient of determination(R2)of 0.946 and 0.942 on the validation and test sets,respectively.Electronegativity was found to have the greatest impact on the morphological fraction.The models’performance was enhanced by applying an ensemble method to the top three optimal ML models,including gradient boosting decision tree,extra trees and categorical boosting.Overall,the proposed framework can accurately predict the concentrations of different morphological fractions of HMMs in TMWs.This approach can minimize detection time,aid in the safe management and recovery of TMWs.展开更多
To address the installation challenges of a 2-m ring Gregorian telescope system,and similar optical systems with a small width-to-radius ratio,we propose a detection method combining local interferometry with a compar...To address the installation challenges of a 2-m ring Gregorian telescope system,and similar optical systems with a small width-to-radius ratio,we propose a detection method combining local interferometry with a comparison model.This method enhances the precision of system calibration by establishing a dataset that delineates the relationship between secondary mirror misalignment and wavefront aberration,subsequently inferring the misalignment from interferometric detection results during the calibration process.For the 2-m ring telescope,we develop a detection model using five local sub-apertures,enabling a root-mean-square detection accuracy of 0:0225λ(λ=632:8 nm)for full-aperture wavefront aberration.The calibration results for the 2-m Ring Solar Telescope system indicate that the root-mean-square value of sub-aperture wavefront aberration reaches 0.104λ,and the root-mean-square value of spliced full-aperture measurement yields reaches 0.112λ.This method offers a novel approach for calibrating small width-toradius ratio telescope systems and can be applied to the calibration of other irregular-aperture optical systems.展开更多
Background:Platform algorithms driving content presentation are profoundly shaping the experience of younger users.While prior research has examined anxiety stemming from young adults’social media usage,the link betw...Background:Platform algorithms driving content presentation are profoundly shaping the experience of younger users.While prior research has examined anxiety stemming from young adults’social media usage,the link between upward social comparison and anxiety remains unclear.This study aims to investigate the mediating role of upward social comparison in this relationship and determine the moderating role of psychological resilience.Methods:A cross-sectional survey was conducted among 562 young Chinese adults aged 18–35(53%female).Data were collected via an online questionnaire employing validated measurement instruments,including scales for social media usage patterns,upward comparator behaviour(INCOM),anxiety levels(GAD-7),and psychological resilience(RSA).Correlation analysis,mediation analysis,and moderation analysis were conducted using SPSS 29.0.Results:As predicted,the results indicate that upward social comparison mediates the relationship between both active(β=−0.11,95%CI=[−0.15,−0.08])and passive(β=0.11,95%CI=[0.07,0.15])social media use and anxiety.Furthermore,psychological resilience(β_(low)=0.10,95%CI=[0.06,0.14];β_(high)=0.05,95%CI=[0.01,0.09])moderated the indirect effect of passive social media use on anxiety through upward social comparison.Conclusion:The findings indicate that upward social comparison significantly influences the anxiety experienced by young social media users,with psychological resilience playing a crucial moderating role.These results offer valuable insights for optimizing content recommendation algorithms on social media platforms to better support young adults’mental health.展开更多
基于国际比较的地方空间规划的范围和工具研究An International Comparison of the Scope and Instruments of Local Spatial Planning源自:The TownPlanning Review,2024,95(2):197-217作者:MaciejJNowak,StefanieDühr,Sergio Pe&...基于国际比较的地方空间规划的范围和工具研究An International Comparison of the Scope and Instruments of Local Spatial Planning源自:The TownPlanning Review,2024,95(2):197-217作者:MaciejJNowak,StefanieDühr,Sergio Peña,et al.推荐:申明锐,南京大学建筑与城市规划学院。shenmingr@nju.edu.cn.展开更多
基金Project supported by“Research on the Coupling and Cooperative Control of Energy and Water in China’s Oil and Gas Development”(No.71673297)“Research on the Multiple Uncertainty Mechanism of Energy-Economy-Environment Integration Model and Emission Reduction Policies”(No.71874177)sponsored by the National Natural Science Foundation of China.
文摘As a kind of relatively clean fossil energy,natural gas will face severe uncertainties in the background of carbon neutrality.Reviewing the medium-and long-term development trend of natural gas consumption is the prerequisite to better understanding the status of natural gas and ensure the sustainable development of natural gas industry.In this paper,a multi-model comparison framework is established on the basis of 8 representative integrated assessment models(CE3METL,DNE21+,IPAC,AIM/CGE,IMAGE,REMIND,WITCH and POLES).Then,the medium-and long-term evolution trend of China's total primary energy consumption and natural gas consumption in different scenarios of climate policy is discussed.In addition,comparative analysis is conducted on key time nodes such as 2030,2045 and 2060.And the following research results are obtained.Firstly,the prediction results of most models indicate that China's total primary energy consumption in 2060 will be lower than the level in 2019 except for the scenario of national determined contribution(NDC).Secondly,by 2060,the carbon neutrality goal year,the cross-model average level of natural gas consumption under the NDC,2.0℃,and 1.5℃ scenarios will be 6943×10^(8)m^(3),4342×10^(8)m^(3)and 2502×10^(8)m^(3),respectively.Thirdly,under the 1.5℃scenario,the decrease of total primary energy consumption shall begin in 2020,which means that faster technological progress and more effective combination of“nudge”policies are needed.Fourthly,under the temperature control goal of 2.0℃,natural gas consumption will account for about 13.6% of China's primary energy consumption in 2060,and this proportion will drop to 9% under the stricter 1.5℃ scenario.In conclusion,the multi-model comparison results can present different development paths of China's total primary energy consumption and natural gas consumption and its proportion during 2020-2060 more comprehensively,so as to provide support for formulating the medium-and long-term policies and strategies of natural gas industry under the challenge of climate change.
基金Supported by Traditional Chinese Medicine Standardization Project of National Administration of Traditional Chinese Medicine:Research on the Physical Characteristics and Pre-disease Health Management of the Elderly in Hubei Province(No.GZY-FJS-2022-046)。
文摘OBJECTIVE:To develop an automated system for identifying and classifying constitution types in Traditional Chinese Medicine(TCM)by leveraging multi-model fusion algorithms.METHODS:A condensed version of a physical information collection form was designed to facilitate efficient data acquisition.The collected data were analyzed using a multi-model fusion approach,which integrated several machine learning techniques.These included support vector machines,Naive Bayes,decision trees,random forests,logistic regression,multilayer perceptrons,K-nearest neighbors,gradient boosting,adaptive ensemble learning,and recurrent neural networks.A soft voting strategy was used to combine the predictive outputs of each model,enabling the selection of the most effective model combination.RESULTS:The classification models demonstrated consistent and robust performance across most TCM constitution types when enhanced by the multi-model fusion strategy.In particular,high levels of accuracy,precision,recall,and F1-score were achieved for constitution types such as Yang deficiency,Qi deficiency,and Qi stagnation.However,the classification performance for the Yin deficiency constitution was relatively lower,indicating the need for further refinement and optimization in future research.CONCLUSION:This study introduces a novel,automated method for classifying TCM constitution types through the application of multi-model fusion algorithms.The approach simplifies the complex task of constitution identification while offering a practical and theoretical framework for the intelligent diagnosis of TCM body types.The findings have the potential to enhance personalized health management and support clinical decision-making in TCM diagnosis and treatment.
文摘[Objectives]This study was conducted to achieve rapid and accurate detection of protein content in rice with a particle size of 1.0 mm.[Methods]A multi-model fusion strategy was proposed on the basis of Stacking ensemble learning.A base learner pool was constructed,containing Partial Least Squares(PLS),Support Vector Machine(SVM),Deep Extreme Learning Machine(DELM),Random Forest(RF),Gradient Boosting Decision Tree(GBDT),and Multilayer Perceptron(MLP).PLS,DELM,and Linear Regression(LR)were used as meta-learner candidates.Employing integer coding technology,systematic dynamic combinations of base learners and meta-learners were generated,resulting in a total of 40 non-repetitive fusion models.The optimal combination was selected through a comprehensive evaluation based on multiple assessment indicators.[Results]The combination"PLS-DELM-MLP-LR"(code 1367)achieved coefficients of determination of 0.9732 and 0.9780 on the validation set and independent test set,respectively,with relative root mean square errors of 2.35%and 2.36%,and residual predictive deviations of 6.1075 and 6.7479,respectively.[Conclusions]The Stacking fusion model significantly enhances the predictive accuracy and robustness of spectral quantitative analysis,providing an efficient and feasible solution for modeling complex agricultural product spectral data.
基金jointly supported by the National Natural Science Foundation of China(Grant U2442214)the China Meteorological Administration Youth Innovation Team(Grant No.CMA2024QN10)+1 种基金the National Defense Science and Technology Bureau’s 14th Five-Year Civil Aerospace Preresearch Project(Grant Nos.D030303 and D040204)the International Space Water Cycle Observation Constellation Program(Grant No.183311KYSB20200015).
文摘China launched its first spaceborne Precipitation Measurement Radar(PMR)on the FY-3G satellite in April 2023.To achieve the scientific goal of measuring the three-dimensional precipitation structure,evaluating the quantitative measurement ability of the PMR is critical.China operates more than 250 weather radars over the mainland.Consistency of the spaceborne radar with ground-based radars will enhance precipitation measurement ability,especially over oceans and mountains where observations are sparse.Additionally,the spaceborne radar can be used to evaluate the spatial and temporal homogeneity of the ground-based radar network.This paper focuses on comparing the PMR onboard the FY-3G satellite with S-band China New Generation Weather Radars(CINRADs).A comparison algorithm between the PMR and CINRADs has been developed,incorporating detailed quality control,attenuation correction,data optimization,spatiotemporal matching,non-uniform beam filling constraint,uniformity constraint,and frequency correction.The matched data in typical months of four seasons were selected to carry out the comparison.The data consistency between the PMR and CINRADs was analyzed.The correlation coefficient is 0.87,the deviation is 0.89 dB,and the standard deviation is 2.50 dB,based on 98226 matching samples.The results show the radar reflectivity of the PMR is quite comparable to that of the CINRADs,demonstrating that the PMR data quality is satisfactory and can be used to verify and correct data consistency among multiple ground-based radars.This work also paves the way for data fusion and joint application of satellite and ground radars in the future.
文摘Multi-firmware comparison techniques can improve efficiency when auditing firmwares in bulk.How-ever,the problem of matching functions between multiple firmwares has not been studied before.This paper proposes a multi-firmware comparison method based on evolutionary algorithms and trusted base points.We first model the multi-firmware comparison as a multi-sequence matching problem.Then,we propose an adaptation function and a population generation method based on trusted base points.Finally,we apply an evolutionary algorithm to find the optimal result.At the same time,we design the similarity of matching results as an evaluation metric to measure the effect of multi-firmware comparison.The experiments show that the proposed method outperforms Bindiff and the string-based method.Precisely,the similarity between the matching results of the proposed method and Bindiff matching results is 61%,and the similarity between the matching results of the proposed method and the string-based method is 62.8%.By sampling and manual verification,the accuracy of the matching results of the proposed method can be about 66.4%.
文摘Intelligent Automation&Soft Computing has retracted the article titled“Line Trace Effective Comparison AlgorithmBased onWavelet Domain DTW”[1],Intell Automat Soft Comput.2019;25(2):359–366 at the request of the authors.DOI:10.31209/2019.100000097 URL:https://www.techscience.com/iasc/v25n2/39663 The article duplicates significant parts of a paper published in Journal of Intelligent&Fuzzy Systems[2].
基金The fund from Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)under contract No.SML2021SP310the National Natural Science Foundation of China under contract Nos 42227901 and 42475061the Key R&D Program of Zhejiang Province under contract No.2024C03257.
文摘In this study,we conducted an experiment to construct multi-model ensemble(MME)predictions for the El Niño-Southern Oscillation(ENSO)using a neural network,based on hindcast data released from five coupled oceanatmosphere models,which exhibit varying levels of complexity.This nonlinear approach demonstrated extraordinary superiority and effectiveness in constructing ENSO MME.Subsequently,we employed the leave-one-out crossvalidation and the moving base methods to further validate the robustness of the neural network model in the formulation of ENSO MME.In conclusion,the neural network algorithm outperforms the conventional approach of assigning a uniform weight to all models.This is evidenced by an enhancement in correlation coefficients and reduction in prediction errors,which have the potential to provide a more accurate ENSO forecast.
基金supported by the National Key Research and Development Program of China(Grant Nos.2024YFB2906504 and 2024YFB2906500)the National Natural Science Foundation of China(Grant Nos.62401067 and 62272051)the 111 Project(Grant No.B21049).
文摘Previous bidirectional quantum private comparison(BQPC)protocols cannot meet the requirements in some special application scenarios,where only one party needs to obtain the comparison results without a third party(TP),such as scenarios for authority surveys or healthcare data sharing.In addition to this,the BQPC protocol has the potential of information leakage in multiple comparisons.Therefore,we design a new unidirectional quantum private comparison(UQPC)protocol based on quantum private query(QPQ)protocols with ideal database security and zero failure probability(IDS-ZF),for the reason that they have excellent unidirectionality and security.Concretely,we design a UQPC protocol based on Wei et al.’s work[IEEE Transactions on Computers 672(2017)]and it includes an authentication process to increase the resistance to outside attacks.Moreover,we generalize the protocol and propose a general model that can transform a QPQ protocol with or without the IDS-ZF property into a secure UQPC protocol.Finally,our study shows that protocols using our model are secure,practical,and have the IDS-ZF property.
基金Supported by National Undergraduate Training Programs for Innovation and Entrepreneurship(202510580009)Special Project for Promoting the Coordinated Development of Urban and Rural Areas and Regions by Introducing Scientific and Technological Achievements of Guangdong Province into Counties and Towns(2025B0202010051)Project of High-quality Development in Hundred Counties,Thousands Towns and Ten Thousand Villages of Guangdong Provincial Department of Science and Technology:Key Dispatch Project for Rural Science and Technology Commissioners(KTP20240704).
文摘Given that the citrus psyllid is the primary vector of citrus Huanglongbing(HLB),there is an urgent need to control this pest to mitigate the spread of the disease.This paper reviews the current research on two predominant control strategies:chemical control and biological control agents,in managing the citrus psyllid.It emphasizes the mechanisms of action,efficacy,and application advancements of these control methods.Finally,the paper analyzes the principal challenges associated with the sustainable management of citrus psyllids and offers perspectives for future research.
文摘BACKGROUND Endoscopic retrograde cholangiopancreatography(ERCP)is an essential diagnostic and therapeutic procedure for pancreatobiliary disorders.However,few large-scale studies from South Asia have examined long-term ERCP outcomes,particularly using established quality benchmarks.AIM To evaluate ERCP indications,success rates,complications,and quality performance at a high-volume tertiary care center in Pakistan over a 17-year period.METHODS This retrospective study analyzed 13215 ERCP procedures performed between 2006 and 2023.Data included demographics,indications,cannulation rates,complications,and pediatric cases.Findings were assessed against American Society of Gastroenterology/European Society of Gastrointestinal Endoscopy quality indicators.RESULTS Biliary ERCP accounted for 93.1%of procedures;choledocholithiasis was the most common indication(40%).Cannulation success was 93.9%for biliary and 94.2%for pancreatic ERCP.Pediatric ERCP comprised 4%of cases,mostly for stones and chronic pancreatitis.Bleeding(1.7%)and post-ERCP pancreatitis(2.3%)were the most frequent complications.Performance met or exceeded most American Society of Benchmarks.CONCLUSION This study offers insight into nearly two decades of ERCP practice within a public sector hospital.Our experience echoes the quality and efficiency of ERCP not previously available in Pakistan.As healthcare systems in resourcelimited sectors expand,our findings serve as a reference point.Continued training and quality improvement studies can further enhance ERCP effectiveness in the region and beyond.
基金supported by MICIU MCIN/AEI/10.13039/501100011033Spain with Grant PID2020-118265GB-C42,-C44,PRTR-C17.I01Generalitat Valenciana,Spain with Grant CIPROM/2022/54,ASFAE/2022/031,CIAPOS/2021/114 and by the EU NextGenerationEU,ESF funds.This work was also supported by the National Science Centre(NCN),Poland(Grant No.2020/39/D/ST2/00466).
文摘The NEutron Detector Array(NEDA)is designed to be coupled to gamma-ray spectrometers to enhance the sensitivity of the setup by enabling reaction channel selection through counting of the evaporated neutrons.This article presents the implementation of a double trigger condition system for NEDA,which improves the acquisition of neutrons and reduces the number of gamma rays acquired.Two independent triggers are generated in the double trigger condition system:one based on charge comparison(CC)and the other on time-of-flight(TOF).These triggers can be combined using OR and AND logic,offering four distinct trigger modes.The developed firmware is added to the previous one in the Virtex 6 field programmable gate array(FPGA)present in the system,which also includes signal processing,baseline correction,and various trigger logic blocks.The performance of the trigger system is evaluated using data from the E703 experiment performed at GANIL.The four trigger modes are applied to the same data,and a subsequent offline analysis is performed.It is shown that most of the detected neutrons are preserved with the AND mode,and the total number of gamma rays is significantly reduced.Compared with the CC trigger mode,the OR trigger mode allows increasing the selection of neutrons.In addition,it is demonstrated that if the OR mode is selected,the online CC trigger threshold can be raised without losing neutrons.
基金financially supported by the Natural Science Foundation of Hunan Province,China(No.2024JJ2074)the National Natural Science Foundation of China(No.22376221)the Young Elite Scientists Sponsorship Program by CAST,China(No.2023QNRC001).
文摘Tailings produced by mining and ore smelting are a major source of soil pollution.Understanding the speciation of heavy metals(HMs)in tailings is essential for soil remediation and sustainable development.Given the complex and time-consuming nature of traditional sequential laboratory extraction methods for determining the forms of HMs in tailings,a rapid and precise identification approach is urgently required.To address this issue,a general empirical prediction method for HM occurrence was developed using machine learning(ML).The compositional information of the tailings,properties of the HMs,and sequential extraction steps were used as inputs to calculate the percentages of the seven forms of HMs.After the models were tuned and compared,extreme gradient boosting,gradient boosting decision tree,and categorical boosting methods were found to be the top three performing ML models,with the coefficient of determination(R^(2))values on the testing set exceeding 0.859.Feature importance analysis for these three optimal models indicated that electronegativity was the most important factor affecting the occurrence of HMs,with an average feature importance of 0.4522.The subsequent use of stacking as a model integration method enabled the ability of the ML models to predict HM occurrence forms to be further improved,and resulting in an increase of R^(2) to 0.879.Overall,this study developed a robust technique for predicting the occurrence forms in tailings and provides an important reference for the environmental assessment and recycling of tailings.
基金Project(2024JJ2074) supported by the Natural Science Foundation of Hunan Province,ChinaProject(22376221) supported by the National Natural Science Foundation of ChinaProject(2023QNRC001) supported by the Young Elite Scientists Sponsorship Program by CAST,China。
文摘Driven by rapid technological advancements and economic growth,mineral extraction and metal refining have increased dramatically,generating huge volumes of tailings and mine waste(TMWs).Investigating the morphological fractions of heavy metals and metalloids(HMMs)in TMWs is key to evaluating their leaching potential into the environment;however,traditional experiments are time-consuming and labor-intensive.In this study,10 machine learning(ML)algorithms were used and compared for rapidly predicting the morphological fractions of HMMs in TMWs.A dataset comprising 2376 data points was used,with mineral composition,elemental properties,and total concentration used as inputs and concentration of morphological fraction used as output.After grid search optimization,the extra tree model performed the best,achieving coefficient of determination(R2)of 0.946 and 0.942 on the validation and test sets,respectively.Electronegativity was found to have the greatest impact on the morphological fraction.The models’performance was enhanced by applying an ensemble method to the top three optimal ML models,including gradient boosting decision tree,extra trees and categorical boosting.Overall,the proposed framework can accurately predict the concentrations of different morphological fractions of HMMs in TMWs.This approach can minimize detection time,aid in the safe management and recovery of TMWs.
基金supported by the Jiangsu Provincial Key Research and Development Program(BE2022072)the National Natural Science Foundation of China(12141304)the Natural Science Foundation of Jiangsu Province(BK20231134).
文摘To address the installation challenges of a 2-m ring Gregorian telescope system,and similar optical systems with a small width-to-radius ratio,we propose a detection method combining local interferometry with a comparison model.This method enhances the precision of system calibration by establishing a dataset that delineates the relationship between secondary mirror misalignment and wavefront aberration,subsequently inferring the misalignment from interferometric detection results during the calibration process.For the 2-m ring telescope,we develop a detection model using five local sub-apertures,enabling a root-mean-square detection accuracy of 0:0225λ(λ=632:8 nm)for full-aperture wavefront aberration.The calibration results for the 2-m Ring Solar Telescope system indicate that the root-mean-square value of sub-aperture wavefront aberration reaches 0.104λ,and the root-mean-square value of spliced full-aperture measurement yields reaches 0.112λ.This method offers a novel approach for calibrating small width-toradius ratio telescope systems and can be applied to the calibration of other irregular-aperture optical systems.
文摘Background:Platform algorithms driving content presentation are profoundly shaping the experience of younger users.While prior research has examined anxiety stemming from young adults’social media usage,the link between upward social comparison and anxiety remains unclear.This study aims to investigate the mediating role of upward social comparison in this relationship and determine the moderating role of psychological resilience.Methods:A cross-sectional survey was conducted among 562 young Chinese adults aged 18–35(53%female).Data were collected via an online questionnaire employing validated measurement instruments,including scales for social media usage patterns,upward comparator behaviour(INCOM),anxiety levels(GAD-7),and psychological resilience(RSA).Correlation analysis,mediation analysis,and moderation analysis were conducted using SPSS 29.0.Results:As predicted,the results indicate that upward social comparison mediates the relationship between both active(β=−0.11,95%CI=[−0.15,−0.08])and passive(β=0.11,95%CI=[0.07,0.15])social media use and anxiety.Furthermore,psychological resilience(β_(low)=0.10,95%CI=[0.06,0.14];β_(high)=0.05,95%CI=[0.01,0.09])moderated the indirect effect of passive social media use on anxiety through upward social comparison.Conclusion:The findings indicate that upward social comparison significantly influences the anxiety experienced by young social media users,with psychological resilience playing a crucial moderating role.These results offer valuable insights for optimizing content recommendation algorithms on social media platforms to better support young adults’mental health.
文摘基于国际比较的地方空间规划的范围和工具研究An International Comparison of the Scope and Instruments of Local Spatial Planning源自:The TownPlanning Review,2024,95(2):197-217作者:MaciejJNowak,StefanieDühr,Sergio Peña,et al.推荐:申明锐,南京大学建筑与城市规划学院。shenmingr@nju.edu.cn.
