Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automaticall...Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.展开更多
Background:Plant phenomics has made significant progress recently,with new demand to move from external characterization to internal exploration through data combination.Hyperspectral and metabolomic data,with cause-a...Background:Plant phenomics has made significant progress recently,with new demand to move from external characterization to internal exploration through data combination.Hyperspectral and metabolomic data,with cause-and-effect relationship,are given priority for integration.However,few efficient integrating methods are available.Results:Here,we showed the way to explore hyperspectral data through combining with upper-level metabolomic data and perform higher-level-data-guided dimension reduction in target-trait-oriented manner to obtain high analysis efficiency.To verify its feasibility,two-stage pipeline combining hyperspectral and metabolic data was designed to discriminate salt-tolerant phenotype for Medicago truncatula mutants.Centered on salt tolerance,data are combined through constructing metabolite-based spectral indices outlining tolerance-related metabolic changes in primary screening,and models converting hyperspectral data to metabolite content for detailed characterizing in secondary screening.Target phenotype could be discriminated after five-day salt-treatment,much earlier than phenotypic difference appearance.20 mutants with salt-tolerant phenotype were successfully identified from about 1000 mutants,almost tripled that of unintegrated analysis.Accuracy rate,confirmed with salt-tolerance analysis for experimental verification,reached 90%,which can be optimized to 100%theoretically utilizing results from hierarchical-clustering-assisted Principal Component Analysis.Conclusions:Mutant-screening pipeline provided here is a practical example for targeted data integration and data mining under the guide of upper-layer omic data.Targeted combination of phenomic and metabolomic data provides the ability for accurate phenotype discrimination and prediction from both external and internal aspects,providing a powerful tool for phenotype selection in new-generation crop breeding.展开更多
To investigate the effects of temperature and moisture content(MC) on acoustic wave velocity(AWV)in wood,the relationships between wood temperature,MC,and AWV were theoretically analyzed.According to the theoretical p...To investigate the effects of temperature and moisture content(MC) on acoustic wave velocity(AWV)in wood,the relationships between wood temperature,MC,and AWV were theoretically analyzed.According to the theoretical propagation characteristics of the acoustic waves in the wood mixture and the differences in velocity among various media(including ice,water,pure wood or oven-dried wood),theoretical relationships of temperature,MC,and AWV were established,assuming that the samples in question were composed of a simple mixture of wood and water or of wood and ice.Using the theoretical model,the phase transition of AWV in green wood near the freezing point(as derived from previous experimental results) was plausibly described.By comparative analysis between theoretical and experimental models for American red pine(Pinus resinosa) samples,it was established that the theoretically predicted AWV values matched the experiment results when the temperature of the wood was below the freezing point of water,with an averageprediction error of 1.66%.The theoretically predicted AWV increased quickly in green wood as temperature decreased and changed suddenly near 0 °C,consistent with the experimental observations.The prediction error of the model was relatively large when the temperature of the wood was above the freezing point,probably due to an overestimation of the effect of the liquid water content on the acoustic velocity and the limited variables of the model.The high correlation between the predicted and measured acoustic velocity values in frozen wood samples revealed the mechanisms of temperature,MC,and water status and how these affected the wood(particularly its acoustic velocity below freezing point of water).This result also verified the reliability of a previous experimental model used to adjust for the effect of temperature during field testing of trees.展开更多
The rheological behavior of a soft interlayer is critical to understanding slope stability, which is closely related to the water content of the soft interlayer. This study used the soft interlayer of the Permian Maok...The rheological behavior of a soft interlayer is critical to understanding slope stability, which is closely related to the water content of the soft interlayer. This study used the soft interlayer of the Permian Maokou Formation in Southwest China as an example to perform ring shear creep tests with different water content amounts. The effect of water content on the creep properties of the soft interlayer was analyzed, and a new shear rheological model was established. This research produced several findings. First, the ring shear creep deformation of the soft interlayer samples varied with the water content and the maximum instantaneous shear strain increment occurred near the saturated water content. As the water content increased, the cumulative creep increment of the samples increased. Second, the water content significantly affected the long-term strength of the soft interlayer, which decreased with the increase of water content, exhibiting a negative linear correlation. Third, a constitutive equation for the new rheological model was derived, and through fitting of the ring shear creep test data, the validity and applicability of the constitutive equation were proven. This study has developed an important foundation for studying the long-term deformation characteristics of a soft interlayer with varying water content.展开更多
Seventeen models participating in the Coupled Model Intercomparison Project phase 5（CMIP5） activity are compared on their historical simulation of the South China Sea（SCS） ocean heat content（OHC） in the upper 30...Seventeen models participating in the Coupled Model Intercomparison Project phase 5（CMIP5） activity are compared on their historical simulation of the South China Sea（SCS） ocean heat content（OHC） in the upper 300 m. Ishii＇s temperature data, based on the World Ocean Database 2005（WOD05） and World Ocean Atlas 2005（WOA05）, is used to assess the model performance by comparing the spatial patterns of seasonal OHC anomaly（OHCa） climatology, OHC climatology, monthly OHCa climatology, and interannual variability of OHCa. The spatial patterns in Ishii＇s data set show that the seasonal SCS OHCa climatology, both in winter and summer, is strongly affected by the wind stress and the current circulations in the SCS and its neighboring areas. However, the CMIP5 models present rather different spatial patterns and only a few models properly capture the dominant features in Ishii＇s pattern. Among them, GFDL-ESM2 G is of the best performance. The SCS OHC climatology in the upper 300 m varies greatly in different models. Most of them are much greater than those calculated from Ishii＇s data. However, the monthly OHCa climatology in each of the 17 CMIP5 models yields similar variation and magnitude as that in Ishii＇s. As for the interannual variability, the standard deviations of the OHCa time series in most of the models are somewhat larger than those in Ishii＇s. The correlation between the interannual time series of Ishii＇s OHCa and that from each of the 17 models is not satisfactory. Among them, BCC-CSM1.1 has the highest correlation to Ishii＇s, with a coefficient of about 0.6.展开更多
Forest fire occurrence is closely relative with fuel water content. There are a lot of research about dead fuels. but forest fuels consist of both dead fuels and living fuels. Each large fire occurrence has a good rel...Forest fire occurrence is closely relative with fuel water content. There are a lot of research about dead fuels. but forest fuels consist of both dead fuels and living fuels. Each large fire occurrence has a good relationship with living fuels. Especially living fuels can influence the production and development of big forest fire, so, we selected Tahe, in Daxingan Mountains, as observation site. According to actual data,we can establish a set of models of different living fuel water content variation with linear -regression method.展开更多
In order to explore the effects of moisture content and plasticity index on Duncan-Chang model parameters?K,n,?C?and?Rf,?we selected 8 groups of soft soil with water content of 69.1%?-?94.3% and plasticity index of 32...In order to explore the effects of moisture content and plasticity index on Duncan-Chang model parameters?K,n,?C?and?Rf,?we selected 8 groups of soft soil with water content of 69.1%?-?94.3% and plasticity index of 32.2?-?54.1 for triaxial unconsolidated undrained shear test. The results show that?Cuu,?K?and?n?values all showed a downward trend, and?Rf?variation was not obvious with the increase of moisture content. The variation rule of each parameter is not obvious with the increase of plasticity index. When moisture content is constant,?Cuu?and?n?values do not change much,?K?increases with the increase of plasticity index within the range of 70%?-?80% moisture content, and does not change much with the increase of plasticity index when moisture content is greater than 80%,?Rf?has no obvious rule.?When the plasticity index is constant,?Cuu,?Kand?n?decrease with the increase of moisture content,?Rf?has no obvious rule. The maximum value of?Cuu?is 20.18?kPa, the minimum is 3.72?kPa, and the maximum to minimum ratio is 5.42. The maximum value of?K?is 0.517, the minimum is 0.022, and the maximum to minimum ratio is 23.5. The maximum value of?n?is 1.198, the minimum is 0.150, and the maximum to minimum ratio is 7.99. The maximum value of?Rf?is 0.872, the minimum is 0.679, and the maximum to minimum ratio is 1.28.展开更多
文摘Slope units are divided according to the real topography and have clear geological characteristics,making them ideal units for evaluating the susceptibility to geological disasters.Based on the results of automatically and manually corrected hydrological slope unit division,the Longhua District,Shenzhen City,Guangdong Province,was selected as the study area.A total of 15 influencing factors,namely Fluctuation,slope,slope aspect,curvature,topographic witness index(TWI),stream power index(SPI),topographic roughness index(TRI),annual average rainfall,distance to water system,engineering rock group,distance to fault,land use,normalized difference vegetation index(NDVI),nighttime light,and distance to road,were selected as evaluation indicators.The information volume model(IV)and random points were used to select non-geological disaster units,and then the random forest model(RF)was used to evaluate the susceptibility to geological disasters.The automatic slope unit and the hydrological slope unit were compared and analyzed in the random forest and information volume random forest models.The results show that the area under the curve(AUC)values of the automatic slope unit evaluation results are 0.931 for the IV-RF model and 0.716 for the RF model,which are 0.6%(IV-RF model)and 1.9%(RF model)higher than those for the hydrological slope unit.Based on a comparison of the evaluation methods based on the two types of slope units,the hydrological slope unit evaluation method based on manual correction is highly subjective,is complicated to operate,and has a low evaluation accuracy,whereas the evaluation method based on automatic slope unit division is efficient and accurate,is suitable for large-scale efficient geological disaster evaluation,and can better deal with the problem of geological disaster susceptibility evaluation.
基金supported by the Strategic Priority Research Program of Chinese Academy of Sciences(XDA26030102)the CAS-CSIRO Project(063GJHZ2022047MI)the CAS Special Research Assistant(SRA)Program(Y973RG1001).
文摘Background:Plant phenomics has made significant progress recently,with new demand to move from external characterization to internal exploration through data combination.Hyperspectral and metabolomic data,with cause-and-effect relationship,are given priority for integration.However,few efficient integrating methods are available.Results:Here,we showed the way to explore hyperspectral data through combining with upper-level metabolomic data and perform higher-level-data-guided dimension reduction in target-trait-oriented manner to obtain high analysis efficiency.To verify its feasibility,two-stage pipeline combining hyperspectral and metabolic data was designed to discriminate salt-tolerant phenotype for Medicago truncatula mutants.Centered on salt tolerance,data are combined through constructing metabolite-based spectral indices outlining tolerance-related metabolic changes in primary screening,and models converting hyperspectral data to metabolite content for detailed characterizing in secondary screening.Target phenotype could be discriminated after five-day salt-treatment,much earlier than phenotypic difference appearance.20 mutants with salt-tolerant phenotype were successfully identified from about 1000 mutants,almost tripled that of unintegrated analysis.Accuracy rate,confirmed with salt-tolerance analysis for experimental verification,reached 90%,which can be optimized to 100%theoretically utilizing results from hierarchical-clustering-assisted Principal Component Analysis.Conclusions:Mutant-screening pipeline provided here is a practical example for targeted data integration and data mining under the guide of upper-layer omic data.Targeted combination of phenomic and metabolomic data provides the ability for accurate phenotype discrimination and prediction from both external and internal aspects,providing a powerful tool for phenotype selection in new-generation crop breeding.
基金funded by the National Natural Science Foundation of China(Grant Nos.31600453 and 31570547)Fundamental Research Funds for the Central Universities(Grant No.2572017EB02)Natural Science Foundation of Heilongjiang Province,China(Grant No.C201403)
文摘To investigate the effects of temperature and moisture content(MC) on acoustic wave velocity(AWV)in wood,the relationships between wood temperature,MC,and AWV were theoretically analyzed.According to the theoretical propagation characteristics of the acoustic waves in the wood mixture and the differences in velocity among various media(including ice,water,pure wood or oven-dried wood),theoretical relationships of temperature,MC,and AWV were established,assuming that the samples in question were composed of a simple mixture of wood and water or of wood and ice.Using the theoretical model,the phase transition of AWV in green wood near the freezing point(as derived from previous experimental results) was plausibly described.By comparative analysis between theoretical and experimental models for American red pine(Pinus resinosa) samples,it was established that the theoretically predicted AWV values matched the experiment results when the temperature of the wood was below the freezing point of water,with an averageprediction error of 1.66%.The theoretically predicted AWV increased quickly in green wood as temperature decreased and changed suddenly near 0 °C,consistent with the experimental observations.The prediction error of the model was relatively large when the temperature of the wood was above the freezing point,probably due to an overestimation of the effect of the liquid water content on the acoustic velocity and the limited variables of the model.The high correlation between the predicted and measured acoustic velocity values in frozen wood samples revealed the mechanisms of temperature,MC,and water status and how these affected the wood(particularly its acoustic velocity below freezing point of water).This result also verified the reliability of a previous experimental model used to adjust for the effect of temperature during field testing of trees.
基金supported by the National Natural Science Foundation of China(Grant No.41521001)the Natural Science Foundation of Hubei Province(Grant No.2018CFB385)
文摘The rheological behavior of a soft interlayer is critical to understanding slope stability, which is closely related to the water content of the soft interlayer. This study used the soft interlayer of the Permian Maokou Formation in Southwest China as an example to perform ring shear creep tests with different water content amounts. The effect of water content on the creep properties of the soft interlayer was analyzed, and a new shear rheological model was established. This research produced several findings. First, the ring shear creep deformation of the soft interlayer samples varied with the water content and the maximum instantaneous shear strain increment occurred near the saturated water content. As the water content increased, the cumulative creep increment of the samples increased. Second, the water content significantly affected the long-term strength of the soft interlayer, which decreased with the increase of water content, exhibiting a negative linear correlation. Third, a constitutive equation for the new rheological model was derived, and through fitting of the ring shear creep test data, the validity and applicability of the constitutive equation were proven. This study has developed an important foundation for studying the long-term deformation characteristics of a soft interlayer with varying water content.
基金The National Basic Research Program(973 Program)of China under contract No.2011CB403502the Major National Scientific Research Projects of China under contract No.2012CB957803+2 种基金the National Natural Science Foundation of China under contract Nos 41006018 and 41476024the Foundation for Outstanding Young and Middle-aged Scientists in Shandong Province of China under contract No.BS2011HZ019the UNESCO-IOC/WESTPAC Project"Response of marine hazards to climate change in the Western Pacific"
文摘Seventeen models participating in the Coupled Model Intercomparison Project phase 5（CMIP5） activity are compared on their historical simulation of the South China Sea（SCS） ocean heat content（OHC） in the upper 300 m. Ishii＇s temperature data, based on the World Ocean Database 2005（WOD05） and World Ocean Atlas 2005（WOA05）, is used to assess the model performance by comparing the spatial patterns of seasonal OHC anomaly（OHCa） climatology, OHC climatology, monthly OHCa climatology, and interannual variability of OHCa. The spatial patterns in Ishii＇s data set show that the seasonal SCS OHCa climatology, both in winter and summer, is strongly affected by the wind stress and the current circulations in the SCS and its neighboring areas. However, the CMIP5 models present rather different spatial patterns and only a few models properly capture the dominant features in Ishii＇s pattern. Among them, GFDL-ESM2 G is of the best performance. The SCS OHC climatology in the upper 300 m varies greatly in different models. Most of them are much greater than those calculated from Ishii＇s data. However, the monthly OHCa climatology in each of the 17 CMIP5 models yields similar variation and magnitude as that in Ishii＇s. As for the interannual variability, the standard deviations of the OHCa time series in most of the models are somewhat larger than those in Ishii＇s. The correlation between the interannual time series of Ishii＇s OHCa and that from each of the 17 models is not satisfactory. Among them, BCC-CSM1.1 has the highest correlation to Ishii＇s, with a coefficient of about 0.6.
文摘Forest fire occurrence is closely relative with fuel water content. There are a lot of research about dead fuels. but forest fuels consist of both dead fuels and living fuels. Each large fire occurrence has a good relationship with living fuels. Especially living fuels can influence the production and development of big forest fire, so, we selected Tahe, in Daxingan Mountains, as observation site. According to actual data,we can establish a set of models of different living fuel water content variation with linear -regression method.
文摘In order to explore the effects of moisture content and plasticity index on Duncan-Chang model parameters?K,n,?C?and?Rf,?we selected 8 groups of soft soil with water content of 69.1%?-?94.3% and plasticity index of 32.2?-?54.1 for triaxial unconsolidated undrained shear test. The results show that?Cuu,?K?and?n?values all showed a downward trend, and?Rf?variation was not obvious with the increase of moisture content. The variation rule of each parameter is not obvious with the increase of plasticity index. When moisture content is constant,?Cuu?and?n?values do not change much,?K?increases with the increase of plasticity index within the range of 70%?-?80% moisture content, and does not change much with the increase of plasticity index when moisture content is greater than 80%,?Rf?has no obvious rule.?When the plasticity index is constant,?Cuu,?Kand?n?decrease with the increase of moisture content,?Rf?has no obvious rule. The maximum value of?Cuu?is 20.18?kPa, the minimum is 3.72?kPa, and the maximum to minimum ratio is 5.42. The maximum value of?K?is 0.517, the minimum is 0.022, and the maximum to minimum ratio is 23.5. The maximum value of?n?is 1.198, the minimum is 0.150, and the maximum to minimum ratio is 7.99. The maximum value of?Rf?is 0.872, the minimum is 0.679, and the maximum to minimum ratio is 1.28.
