Sporadic E(Es)layers in the ionosphere are characterized by intense plasma irregularities in the E region at altitudes of 90-130 km.Because they can significantly influence radio communications and navigation systems,...Sporadic E(Es)layers in the ionosphere are characterized by intense plasma irregularities in the E region at altitudes of 90-130 km.Because they can significantly influence radio communications and navigation systems,accurate forecasting of Es layers is crucial for ensuring the precision and dependability of navigation satellite systems.In this study,we present Es predictions made by an empirical model and by a deep learning model,and analyze their differences comprehensively by comparing the model predictions to satellite RO measurements and ground-based ionosonde observations.The deep learning model exhibited significantly better performance,as indicated by its high coefficient of correlation(r=0.87)with RO observations and predictions,than did the empirical model(r=0.53).This study highlights the importance of integrating artificial intelligence technology into ionosphere modelling generally,and into predicting Es layer occurrences and characteristics,in particular.展开更多
The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precisio...The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.展开更多
The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into ...The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into the first four stages,and a summative evaluation table is designed for the fifth,enabling students to self-evaluate and reflect.Elementary school English picture book teaching is used as an example to demonstrate the optimized model's application.展开更多
To solve the problem of false edges in a flat region of l_(1)norm total variational TV model,an edge extractor based on non-local idea is proposed in this paper.The new edge extractor can effectively suppress the infl...To solve the problem of false edges in a flat region of l_(1)norm total variational TV model,an edge extractor based on non-local idea is proposed in this paper.The new edge extractor can effectively suppress the influence of noise and extract the edge information of the image.The new edge extractor is used as the adaptive function and the weighting function of the l_(p) norm variational model to control the noise reduction ability of the model,and a new model 1 is obtained.Considering that the new model 1 only uses the gradient mode as the image feature operator,which is insufficient to express the image texture information,a new level set curvature gradient variational model 2 combined with the edge extractor is proposed.The new model 2 uses the idea of minimum curvature of the level set of clear images to obtain noise reduction images.By coupling new model 1 and new model 2 to smooth the noise and protect more textures,a new Non-local level set denoising model(NLSDM)for image noise reduction is obtained.The experimental results show that compared with the noise reduction model,the new model has significantly improved the peak signal-to-noise ratio and structural similarity,and the effect of noise reduction and edge preservation is better.展开更多
[Objective] The aim was to build an optimal leaf area measurement model of E. urophylla and E. grandis×E.urophylla. [Method] The correlation between leaf area and leaf＇s eigenvalue of E. urophylla and E. grandis...[Objective] The aim was to build an optimal leaf area measurement model of E. urophylla and E. grandis×E.urophylla. [Method] The correlation between leaf area and leaf＇s eigenvalue of E. urophylla and E. grandis×E.urophylla were studied. [Result] There was certain difference in leaf characteristics values between the 2 species. The leaf areas of E. urophylla and E. grandis×E.urophylla both had significant correlation with leaf length,leaf width,leaf perimeter,leaf length × leaf width,the ratio of leaf length to leaf width,shape factor,etc.,so the factors could be constructed into a regression model with leaf area. Among them,the best 2 models for leaf area calculation which were built by leaf length × leaf width of E. urophylla and E. grandis×E.urophylla both had relatively high accuracy and practical applications. [Conclusion] The research provides a simple and effective leaf area measurement method for studies on the 2 tree species.展开更多
Hot carrier effects of p MOSFETs with different oxide thicknesses are studied in low gate voltage range.All electrical parameters follow a power law relationship with stress time,but degradation slope is dependent ...Hot carrier effects of p MOSFETs with different oxide thicknesses are studied in low gate voltage range.All electrical parameters follow a power law relationship with stress time,but degradation slope is dependent on gate voltage.For the devices with thicker oxides,saturated drain current degradation has a close relationship with the product of gate current and electron fluence.For small dimensional devices,saturated drain current degradation has a close relationship with the electron fluence.This degradation model is valid for p MOSFETs with 0 25μm channel length and different gate oxide thicknesses.展开更多
AIM:To develop models to predict hepatitis B e antigen(HBe Ag)seroconversion in response to interferon(IFN)-αtreatment in chronic hepatitis B patients.METHODS:We enrolled 147 treatment-nave HBe Agpositive chronic h...AIM:To develop models to predict hepatitis B e antigen(HBe Ag)seroconversion in response to interferon(IFN)-αtreatment in chronic hepatitis B patients.METHODS:We enrolled 147 treatment-nave HBe Agpositive chronic hepatitis B patients in China and analyzed variables after initiating IFN-α1b treatment.Patients were tested for serum alanine aminotransferase(ALT),hepatitis B virus-DNA,hepatitis B surface antigen(HBs Ag),antibody to hepatitis B surface antigen,HBe Ag,antibody to hepatitis B e antigen(anti-HBe),and antibody to hepatitis B core antigen(anti-HBc)at baseline and 12 wk,24 wk,and 52 wk after initiating treatment.We performed univariate analysis to identify response predictors among the variables.Multivariate models to predict treatment response were constructed at baseline,12 wk,and 24 wk.RESULTS:At baseline,the 3 factors correlating most with HBe Ag seroconversion were serum ALT level>4×the upper limit of normal(ULN),HBe Ag≤500 S/CO,and anti-HBc>11.4 S/CO.At 12 wk,the 3 factors most associated with HBe Ag seroconversion were HBe Ag level≤250 S/CO,decline in HBe Ag>1 log10 S/CO,and anti-HBc>11.8 S/CO.At 24 wk,the 3 factors most associated with HBe Ag seroconversion were HBe Ag level≤5 S/CO,anti-HBc>11.4 S/CO,and decline in HBe Ag>2 log10 S/CO.Each variable was assigned a score of1,a score of 0 was given if patients did not have any of the 3 variables.The 3 factors most strongly correlating with HBe Ag seroconversion at each time point were used to build models to predict the outcome after IFN-αtreatment.When the score was 3,the response rates at the 3 time points were 57.7%,83.3%,and 84.0%,respectively.When the score was 0,the response rates were 2.9%,0.0%,and 2.1%,respectively.CONCLUSION:Models with good negative and positive predictive values were developed to calculate the probability of response to IFN-αtherapy.展开更多
Chaos game representation （CGR） is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their ...Chaos game representation （CGR） is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their positions in a continuous space. This distribution of positions has two features： one is unique, and the other is source sequence that can be recovered from the coordinates so that the distance between positions may serve as a measure of similarity between the corresponding sequences. A CGR-walk model is proposed based on CGR coordinates for the DNA sequences. The CGR coordinates are converted into a time series, and a long-memory ARFIMA （p, d, q） model, where ARFIMA stands for autoregressive fractionally integrated moving average, is introduced into the DNA sequence analysis. This model is applied to simulating real CGR-walk sequence data of ten genomic sequences. Remarkably long-range correlations are uncovered in the data, and the results from these models are reasonably fitted with those from the ARFIMA （p, d, q） model.展开更多
基金supported by the Project of Stable Support for Youth Team in Basic Research Field,CAS(grant No.YSBR-018)the National Natural Science Foundation of China(grant Nos.42188101,42130204)+4 种基金the B-type Strategic Priority Program of CAS(grant no.XDB41000000)the National Natural Science Foundation of China(NSFC)Distinguished Overseas Young Talents Program,Innovation Program for Quantum Science and Technology(2021ZD0300301)the Open Research Project of Large Research Infrastructures of CAS-“Study on the interaction between low/mid-latitude atmosphere and ionosphere based on the Chinese Meridian Project”.The project was supported also by the National Key Laboratory of Deep Space Exploration(Grant No.NKLDSE2023A002)the Open Fund of Anhui Provincial Key Laboratory of Intelligent Underground Detection(Grant No.APKLIUD23KF01)the China National Space Administration(CNSA)pre-research Project on Civil Aerospace Technologies No.D010305,D010301.
文摘Sporadic E(Es)layers in the ionosphere are characterized by intense plasma irregularities in the E region at altitudes of 90-130 km.Because they can significantly influence radio communications and navigation systems,accurate forecasting of Es layers is crucial for ensuring the precision and dependability of navigation satellite systems.In this study,we present Es predictions made by an empirical model and by a deep learning model,and analyze their differences comprehensively by comparing the model predictions to satellite RO measurements and ground-based ionosonde observations.The deep learning model exhibited significantly better performance,as indicated by its high coefficient of correlation(r=0.87)with RO observations and predictions,than did the empirical model(r=0.53).This study highlights the importance of integrating artificial intelligence technology into ionosphere modelling generally,and into predicting Es layer occurrences and characteristics,in particular.
基金Supported by the National Key Research and Development Program of China(2022YFB3904803)。
文摘The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.
基金This paper is funded by Project Information:2023 Guangdong Undergraduate Colleges and Universities Teaching Quality and Teaching Reform Project Construction Project,Project Name:Action Research on Whole-area Nurturing of English Reading Teaching in Universities,Secondary and Primary Schools under the Perspective of Discipline Nurturing.Project serial number:895.
文摘The 5E model includes Engagement,Exploration,Explanation,Elaboration,and Evaluation,with“Evaluation”at the end,conflicting with teaching learning-evaluation consistency.Thus,formative levaluation is integrated into the first four stages,and a summative evaluation table is designed for the fifth,enabling students to self-evaluate and reflect.Elementary school English picture book teaching is used as an example to demonstrate the optimized model's application.
基金funded by National Nature Science Foundation of China,grant number 61302188.
文摘To solve the problem of false edges in a flat region of l_(1)norm total variational TV model,an edge extractor based on non-local idea is proposed in this paper.The new edge extractor can effectively suppress the influence of noise and extract the edge information of the image.The new edge extractor is used as the adaptive function and the weighting function of the l_(p) norm variational model to control the noise reduction ability of the model,and a new model 1 is obtained.Considering that the new model 1 only uses the gradient mode as the image feature operator,which is insufficient to express the image texture information,a new level set curvature gradient variational model 2 combined with the edge extractor is proposed.The new model 2 uses the idea of minimum curvature of the level set of clear images to obtain noise reduction images.By coupling new model 1 and new model 2 to smooth the noise and protect more textures,a new Non-local level set denoising model(NLSDM)for image noise reduction is obtained.The experimental results show that compared with the noise reduction model,the new model has significantly improved the peak signal-to-noise ratio and structural similarity,and the effect of noise reduction and edge preservation is better.
基金Supported by Key Science and Technology Project of Forestry in Guangxi Province for the Eleventh Five-year Plan ([2009] No.8)~~
文摘[Objective] The aim was to build an optimal leaf area measurement model of E. urophylla and E. grandis×E.urophylla. [Method] The correlation between leaf area and leaf＇s eigenvalue of E. urophylla and E. grandis×E.urophylla were studied. [Result] There was certain difference in leaf characteristics values between the 2 species. The leaf areas of E. urophylla and E. grandis×E.urophylla both had significant correlation with leaf length,leaf width,leaf perimeter,leaf length × leaf width,the ratio of leaf length to leaf width,shape factor,etc.,so the factors could be constructed into a regression model with leaf area. Among them,the best 2 models for leaf area calculation which were built by leaf length × leaf width of E. urophylla and E. grandis×E.urophylla both had relatively high accuracy and practical applications. [Conclusion] The research provides a simple and effective leaf area measurement method for studies on the 2 tree species.
文摘Hot carrier effects of p MOSFETs with different oxide thicknesses are studied in low gate voltage range.All electrical parameters follow a power law relationship with stress time,but degradation slope is dependent on gate voltage.For the devices with thicker oxides,saturated drain current degradation has a close relationship with the product of gate current and electron fluence.For small dimensional devices,saturated drain current degradation has a close relationship with the electron fluence.This degradation model is valid for p MOSFETs with 0 25μm channel length and different gate oxide thicknesses.
基金Supported by Specialized Research Fund for the Doctoral Program of Higher Education of China,No.20093420120005National Science Foundation of China,No.30771907
文摘AIM:To develop models to predict hepatitis B e antigen(HBe Ag)seroconversion in response to interferon(IFN)-αtreatment in chronic hepatitis B patients.METHODS:We enrolled 147 treatment-nave HBe Agpositive chronic hepatitis B patients in China and analyzed variables after initiating IFN-α1b treatment.Patients were tested for serum alanine aminotransferase(ALT),hepatitis B virus-DNA,hepatitis B surface antigen(HBs Ag),antibody to hepatitis B surface antigen,HBe Ag,antibody to hepatitis B e antigen(anti-HBe),and antibody to hepatitis B core antigen(anti-HBc)at baseline and 12 wk,24 wk,and 52 wk after initiating treatment.We performed univariate analysis to identify response predictors among the variables.Multivariate models to predict treatment response were constructed at baseline,12 wk,and 24 wk.RESULTS:At baseline,the 3 factors correlating most with HBe Ag seroconversion were serum ALT level>4×the upper limit of normal(ULN),HBe Ag≤500 S/CO,and anti-HBc>11.4 S/CO.At 12 wk,the 3 factors most associated with HBe Ag seroconversion were HBe Ag level≤250 S/CO,decline in HBe Ag>1 log10 S/CO,and anti-HBc>11.8 S/CO.At 24 wk,the 3 factors most associated with HBe Ag seroconversion were HBe Ag level≤5 S/CO,anti-HBc>11.4 S/CO,and decline in HBe Ag>2 log10 S/CO.Each variable was assigned a score of1,a score of 0 was given if patients did not have any of the 3 variables.The 3 factors most strongly correlating with HBe Ag seroconversion at each time point were used to build models to predict the outcome after IFN-αtreatment.When the score was 3,the response rates at the 3 time points were 57.7%,83.3%,and 84.0%,respectively.When the score was 0,the response rates were 2.9%,0.0%,and 2.1%,respectively.CONCLUSION:Models with good negative and positive predictive values were developed to calculate the probability of response to IFN-αtherapy.
基金Project supported by the National Natural Science Foundation of China (Grant No 60575038)the Natural Science Foundation of Jiangnan University,China (Grant No 20070365)
文摘Chaos game representation （CGR） is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to determine the coordinates of their positions in a continuous space. This distribution of positions has two features： one is unique, and the other is source sequence that can be recovered from the coordinates so that the distance between positions may serve as a measure of similarity between the corresponding sequences. A CGR-walk model is proposed based on CGR coordinates for the DNA sequences. The CGR coordinates are converted into a time series, and a long-memory ARFIMA （p, d, q） model, where ARFIMA stands for autoregressive fractionally integrated moving average, is introduced into the DNA sequence analysis. This model is applied to simulating real CGR-walk sequence data of ten genomic sequences. Remarkably long-range correlations are uncovered in the data, and the results from these models are reasonably fitted with those from the ARFIMA （p, d, q） model.
