In materials science,a significant correlation often exists between material input parameters and their corresponding performance attributes.Nevertheless,the inherent challenges associated with small data obscure thes...In materials science,a significant correlation often exists between material input parameters and their corresponding performance attributes.Nevertheless,the inherent challenges associated with small data obscure these statistical correlations,impeding machine learning models from effectively capturing the underlying patterns,thereby hampering efficient optimization of material properties.This work presents a novel active learning framework that integrates generative adversarial networks(GAN)with a directionally constrained expected absolute improvement(EAI)acquisition function to accelerate the discovery of ultra-high temperature ceramics(UHTCs)using small data.The framework employs GAN for data augmentation,symbolic regression for feature weight derivation,and a self-developed EAI function that incorporates input feature importance weighting to quantify bidirectional deviations from zero ablation rate.Through only two iterations,this framework successfully identified the optimal composition of HfB_(2)-3.52SiC-5.23TaSi_(2),which exhibits robust near-zero ablation rates under plasma ablation at 2500℃ for 200 s,demonstrating superior sampling efficiency compared to conventional active learning approaches.Microstructural analysis reveals that the exceptional performance stems from the formation of a highly viscous HfO_(2)-SiO_(2)-Ta_(2)O_(5)-HfSiO_(4)-Hf_(3)(BO_(3))_(4) oxide layer,which provides effective oxygen barrier protection.This work demonstrates an efficient and universal approach for rapid materials discovery using small data.展开更多
Optimal scale selection is the key step of the slope segmentation. Taking three geomorphological units in different parts of the loess as test areas and 5 m-resolution DEMs as original test date, this paper employed t...Optimal scale selection is the key step of the slope segmentation. Taking three geomorphological units in different parts of the loess as test areas and 5 m-resolution DEMs as original test date, this paper employed the changed ROC-LV (Lucian, 2010) in judging the optimal scales in the slope segmentation process. The experiment results showed that this method is effective in determining the optimal scale in the slope segmentation. The results also showed that the slope segmentation of the different geomorphological units require different optimal scales because the landform complexity is varied. The three test areas require the same scale which could distinguish the small gully because all the test areas have many gullies of the same size, however, when come to distinguish the basins, since the complexity of the three areas is different, the test areas require different scales.展开更多
The Loess Plateau is densely covered by numerous types of gullies which represent different soil erosion intensities.Therefore,research on topographic variation features of the loess gullies is of great significance t...The Loess Plateau is densely covered by numerous types of gullies which represent different soil erosion intensities.Therefore,research on topographic variation features of the loess gullies is of great significance to environmental protection and ecological management.Using a5 m digital elevation model and data from a national geographic database,this paper studies different topographical areas of the Loess Plateau,including Shenmu,Suide,Yanchuan,Ganquan,Yijun,and Chunhua,to derive representative gully terrain profile data of the sampled areas.First,the profile data are standardized in MATLAB and then decomposed using the ensemble empirical mode decomposition method.Then,a significance test is performed on the results;the test confidence is 95% to 99%.The most reliable decomposition component is then used to calculate the relief period and size of the gullies.The results showed that relief periods of the Chunhua,Shenmu,Yijun,Yuanchuan,Ganquan,and Suide gullies are 1110.14 m,1096.85 m,1002.49 m,523.48 m,498.12 m,and 270.83 m,respectively.In terms of gully size,the loess landforms are sorted as loess fragmented tableland,aeolian and dune,loess tableland,loess ridge,loess hill and loess ridge,and loess hill,in descending order.Taken together,the gully terrain features of the sample areas and the results of the study are approximately consistent with the actual terrain profiles.Thus,we conclude that ensemble empirical mode decomposition is a reliable method for the study of the relief and topography of loess gullies.展开更多
Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this app...Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this approach can be used to judge whether the spatial pattern of the objective is regular,random or aggregated in space.The lacunarity analysis,however,cannot afford many quantitative information.Therefore,this study proposed the lacunarity variation index(LVI)to reflect the rates of variation of lacunarity with the resolution.In comparison with lacunarity analysis,the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data.The experiment showed that different slope types in the Loess Plateau display aggregated patterns,and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data.This study can improve the spatial pattern analysis and scale detecting methods,as well as provide a new method for landscape and vegetation community pattern analyses.Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this approach can be used to judge whether the spatial pattern of the objective is regular,random or aggregated in space.The lacunarity analysis,however,cannot afford many quantitative information.Therefore,this study proposed the lacunarity variation index(LVI)to reflect the rates of variation of lacunarity with the resolution.In comparison with lacunarity analysis,the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data.The experiment showed that different slope types in the Loess Plateau display aggregated patterns,and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data.This study can improve the spatial pattern analysis and scale detecting methods,as well as provide a new method for landscape and vegetation community pattern analyses.展开更多
The EX 16+22Y system is a polymerase chain reaction(PCR)-based amplification kit that enables typing of 15 autosomal short tandem repeat(STR)loci(i.e„D3S1358,D13S317,D7S820,D16S539,TPOX,TH01,D2S133&CSF1PO,D19S433,...The EX 16+22Y system is a polymerase chain reaction(PCR)-based amplification kit that enables typing of 15 autosomal short tandem repeat(STR)loci(i.e„D3S1358,D13S317,D7S820,D16S539,TPOX,TH01,D2S133&CSF1PO,D19S433,vWA,D18S51,D21S11,D8S1179,D5S81&and FGA)and 22 widely used Y chromosome STR(Y-STR)loci(DYS391,DYS527a/b,DYS635,DYS458,DYS456,DYS385a/b,DYS43&DYS44&DYS437,DYS19,DYS576,DYS533,DYS393,DYS389I/n,DYS439,DYS392,Y_GATA_H4,DYS390,and DYS481)which contains 20 core Y-STR recommended by the Ministry of Public Security and amelogenin.This multiplex system was designed for the simultaneous analysis of amelogenin-Y allele mutation,single-source searches,kinship(including familial searching),mixture profiles,international data sharing,and other forensic applications.In this study,the multiplex system was validated for sensitivity of detection,species specificity,DNA mixtures,stability,sizing precision,stutter,reproducibility,and PCR-based conditions according to the Scientific Working Group on DNA Analysis Methods developmental validation guidelines and Chinese criteria for the human fluorescent STR multiplex PCR reagent.The results show that the EX16+22Y system is a robust and reliable amplification kit which can be used for human identification testing.展开更多
A simulated loess watershed, where the loess material and relief properly represent the true loess surface, is adopted to investigate the variation in slope spectrum with loess watershed evolution. The evolution of th...A simulated loess watershed, where the loess material and relief properly represent the true loess surface, is adopted to investigate the variation in slope spectrum with loess watershed evolution. The evolution of the simulated loess watershed was driven by the exogenetic force of artificial rainfall. For a period of three months, twenty artificial rainfall events with different intensities and durations were carried out. In the process, nine DEM data sets, each with 10mm grid resolution, were established by the method of close-range photogrammetry. The slope spectra were then extracted from these DEMs. Subsequent series of carefully designed quantitative analyses indicated a strong relationship between the slope spectrum and the evolution of the simulated loess watershed. Quantitative indices of the slope spectrum varied regularly following the evolution of the simulated loess watershed. Mean slope, slope spectrum information entropy （H）, terrain driving force （Td）, Mean patch area （AREA_MN）, Contagion Index （CONTAG）, and Patch Cohesion Index （COHESION） kept increasing following the evolution of the simulated watershed, while skewness （S）, Perimeter-Area Fractal Dimension （PAFRAC）, and Interspersion and Juxtaposition Index （IJl） represented an opposite trend. All the indices changed actively in the early and active development periods, but slowly in the stable development periods. These experimental results indicate that the time series of slope spectra was able to effectively depict the slope distribution of the simulated loess watershed, thus presenting a potential method for model- ing loess landforms.展开更多
Gully morphology is an important part of loess landform research.Along with gully development,the variation of its cross section is the most significant,and it can intuitively reflect the characteristics of the latera...Gully morphology is an important part of loess landform research.Along with gully development,the variation of its cross section is the most significant,and it can intuitively reflect the characteristics of the lateral widening of the gully slope.Therefore,in-depth research of the variation of the cross-sectional morphology of the gully is helpful to understanding the development process of the loess gully.Based on the DEMs(Digital Elevation Model)of nine periods of an indoor simulated loess small watershed,this paper studies the evolution model of a complete branch ditch in the watershed using the digital terrain analysis theory and method.Results show that with the development of the gully,the average gradient of the gully slope continuously decreases,and the slope morphology is mostly a concave slope along the slope direction.The degree of downward concave first increases and then gradually tends to be gentle.The gully erosion mode is gradually transformed from downward cutting erosion to lateral erosion.The more mature the gully development,the lower the depth of gully bottom cutting is compared with the width of gully widening.Furthermore,the surface cutting depth tends to be stable and the slope is stable.Then,the transformation law of the slope morphology of the gully cross section with the development of the gully is studied,and the prediction model of the transformation of the slope morphology of the gully cross section is established by using the Markov chain.The Markov model can better reflect the dynamic change of the slope morphology of the gully cross section,which is of great significance to revealing the external performance and internal mechanism of the gully morphology.展开更多
基金supported by the Natural Science Foundation of China[grant numbers 52302093]Natural Science Foundation of Jiangxi Province[grant numbers 20224BAB204021].
文摘In materials science,a significant correlation often exists between material input parameters and their corresponding performance attributes.Nevertheless,the inherent challenges associated with small data obscure these statistical correlations,impeding machine learning models from effectively capturing the underlying patterns,thereby hampering efficient optimization of material properties.This work presents a novel active learning framework that integrates generative adversarial networks(GAN)with a directionally constrained expected absolute improvement(EAI)acquisition function to accelerate the discovery of ultra-high temperature ceramics(UHTCs)using small data.The framework employs GAN for data augmentation,symbolic regression for feature weight derivation,and a self-developed EAI function that incorporates input feature importance weighting to quantify bidirectional deviations from zero ablation rate.Through only two iterations,this framework successfully identified the optimal composition of HfB_(2)-3.52SiC-5.23TaSi_(2),which exhibits robust near-zero ablation rates under plasma ablation at 2500℃ for 200 s,demonstrating superior sampling efficiency compared to conventional active learning approaches.Microstructural analysis reveals that the exceptional performance stems from the formation of a highly viscous HfO_(2)-SiO_(2)-Ta_(2)O_(5)-HfSiO_(4)-Hf_(3)(BO_(3))_(4) oxide layer,which provides effective oxygen barrier protection.This work demonstrates an efficient and universal approach for rapid materials discovery using small data.
文摘Optimal scale selection is the key step of the slope segmentation. Taking three geomorphological units in different parts of the loess as test areas and 5 m-resolution DEMs as original test date, this paper employed the changed ROC-LV (Lucian, 2010) in judging the optimal scales in the slope segmentation process. The experiment results showed that this method is effective in determining the optimal scale in the slope segmentation. The results also showed that the slope segmentation of the different geomorphological units require different optimal scales because the landform complexity is varied. The three test areas require the same scale which could distinguish the small gully because all the test areas have many gullies of the same size, however, when come to distinguish the basins, since the complexity of the three areas is different, the test areas require different scales.
基金the National Natural Science Foundation of China (Grant Nos.41471316,41671389,and 41501487)the Natural Science Foundation of Jiangsu Province (No.BK20161118).
文摘The Loess Plateau is densely covered by numerous types of gullies which represent different soil erosion intensities.Therefore,research on topographic variation features of the loess gullies is of great significance to environmental protection and ecological management.Using a5 m digital elevation model and data from a national geographic database,this paper studies different topographical areas of the Loess Plateau,including Shenmu,Suide,Yanchuan,Ganquan,Yijun,and Chunhua,to derive representative gully terrain profile data of the sampled areas.First,the profile data are standardized in MATLAB and then decomposed using the ensemble empirical mode decomposition method.Then,a significance test is performed on the results;the test confidence is 95% to 99%.The most reliable decomposition component is then used to calculate the relief period and size of the gullies.The results showed that relief periods of the Chunhua,Shenmu,Yijun,Yuanchuan,Ganquan,and Suide gullies are 1110.14 m,1096.85 m,1002.49 m,523.48 m,498.12 m,and 270.83 m,respectively.In terms of gully size,the loess landforms are sorted as loess fragmented tableland,aeolian and dune,loess tableland,loess ridge,loess hill and loess ridge,and loess hill,in descending order.Taken together,the gully terrain features of the sample areas and the results of the study are approximately consistent with the actual terrain profiles.Thus,we conclude that ensemble empirical mode decomposition is a reliable method for the study of the relief and topography of loess gullies.
基金supported by the National Natural Science Foundation of China(Grant Nos.41930102,41571383,41771415,41801321,and 41701450).
文摘Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this approach can be used to judge whether the spatial pattern of the objective is regular,random or aggregated in space.The lacunarity analysis,however,cannot afford many quantitative information.Therefore,this study proposed the lacunarity variation index(LVI)to reflect the rates of variation of lacunarity with the resolution.In comparison with lacunarity analysis,the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data.The experiment showed that different slope types in the Loess Plateau display aggregated patterns,and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data.This study can improve the spatial pattern analysis and scale detecting methods,as well as provide a new method for landscape and vegetation community pattern analyses.Lacunarity analysis is frequently used in multiscale and spatial pattern studies.However,the explanation for the lacunarity analysis results is limited mainly at a qualitative description level.In other words,this approach can be used to judge whether the spatial pattern of the objective is regular,random or aggregated in space.The lacunarity analysis,however,cannot afford many quantitative information.Therefore,this study proposed the lacunarity variation index(LVI)to reflect the rates of variation of lacunarity with the resolution.In comparison with lacunarity analysis,the simulated experiments show that the LVI analysis can distinguish the basic spatial pattern of the geography objects more clearly and detect the scale of aggregated data.The experiment showed that different slope types in the Loess Plateau display aggregated patterns,and the characteristic scales of these patterns were detected using the slope pattern in the Loess Plateau as the research data.This study can improve the spatial pattern analysis and scale detecting methods,as well as provide a new method for landscape and vegetation community pattern analyses.
文摘The EX 16+22Y system is a polymerase chain reaction(PCR)-based amplification kit that enables typing of 15 autosomal short tandem repeat(STR)loci(i.e„D3S1358,D13S317,D7S820,D16S539,TPOX,TH01,D2S133&CSF1PO,D19S433,vWA,D18S51,D21S11,D8S1179,D5S81&and FGA)and 22 widely used Y chromosome STR(Y-STR)loci(DYS391,DYS527a/b,DYS635,DYS458,DYS456,DYS385a/b,DYS43&DYS44&DYS437,DYS19,DYS576,DYS533,DYS393,DYS389I/n,DYS439,DYS392,Y_GATA_H4,DYS390,and DYS481)which contains 20 core Y-STR recommended by the Ministry of Public Security and amelogenin.This multiplex system was designed for the simultaneous analysis of amelogenin-Y allele mutation,single-source searches,kinship(including familial searching),mixture profiles,international data sharing,and other forensic applications.In this study,the multiplex system was validated for sensitivity of detection,species specificity,DNA mixtures,stability,sizing precision,stutter,reproducibility,and PCR-based conditions according to the Scientific Working Group on DNA Analysis Methods developmental validation guidelines and Chinese criteria for the human fluorescent STR multiplex PCR reagent.The results show that the EX16+22Y system is a robust and reliable amplification kit which can be used for human identification testing.
基金We are grateful for the financial support from the National Natural Science Foundation of China （Grant Nos. 41171299 and 41271438）, the Priority Academic Program Development of Jiangsu Higher Education Institutions （164320H116） and the foundation of State Key Laboratory of Soil Erosion and Dryland Fanning on the Loess Plateau （10501-1217, K318009902-13）. We are also grateful to Dr. Josef Strobl for his constructive critique of the manuscript. The constructive criticisms and suggestions from anonymous reviewers are also gratefully acknowledged.
文摘A simulated loess watershed, where the loess material and relief properly represent the true loess surface, is adopted to investigate the variation in slope spectrum with loess watershed evolution. The evolution of the simulated loess watershed was driven by the exogenetic force of artificial rainfall. For a period of three months, twenty artificial rainfall events with different intensities and durations were carried out. In the process, nine DEM data sets, each with 10mm grid resolution, were established by the method of close-range photogrammetry. The slope spectra were then extracted from these DEMs. Subsequent series of carefully designed quantitative analyses indicated a strong relationship between the slope spectrum and the evolution of the simulated loess watershed. Quantitative indices of the slope spectrum varied regularly following the evolution of the simulated loess watershed. Mean slope, slope spectrum information entropy （H）, terrain driving force （Td）, Mean patch area （AREA_MN）, Contagion Index （CONTAG）, and Patch Cohesion Index （COHESION） kept increasing following the evolution of the simulated watershed, while skewness （S）, Perimeter-Area Fractal Dimension （PAFRAC）, and Interspersion and Juxtaposition Index （IJl） represented an opposite trend. All the indices changed actively in the early and active development periods, but slowly in the stable development periods. These experimental results indicate that the time series of slope spectra was able to effectively depict the slope distribution of the simulated loess watershed, thus presenting a potential method for model- ing loess landforms.
基金support from the National Natural Science Foundation of China(Grant Nos.41930102 and 41571383).
文摘Gully morphology is an important part of loess landform research.Along with gully development,the variation of its cross section is the most significant,and it can intuitively reflect the characteristics of the lateral widening of the gully slope.Therefore,in-depth research of the variation of the cross-sectional morphology of the gully is helpful to understanding the development process of the loess gully.Based on the DEMs(Digital Elevation Model)of nine periods of an indoor simulated loess small watershed,this paper studies the evolution model of a complete branch ditch in the watershed using the digital terrain analysis theory and method.Results show that with the development of the gully,the average gradient of the gully slope continuously decreases,and the slope morphology is mostly a concave slope along the slope direction.The degree of downward concave first increases and then gradually tends to be gentle.The gully erosion mode is gradually transformed from downward cutting erosion to lateral erosion.The more mature the gully development,the lower the depth of gully bottom cutting is compared with the width of gully widening.Furthermore,the surface cutting depth tends to be stable and the slope is stable.Then,the transformation law of the slope morphology of the gully cross section with the development of the gully is studied,and the prediction model of the transformation of the slope morphology of the gully cross section is established by using the Markov chain.The Markov model can better reflect the dynamic change of the slope morphology of the gully cross section,which is of great significance to revealing the external performance and internal mechanism of the gully morphology.
