[Objective]With increasing energy demand and growing concerns about climate change,the rational utilization of marginal lands for cultivating biomass energy crops has emerged as a research focus in recent years.Previo...[Objective]With increasing energy demand and growing concerns about climate change,the rational utilization of marginal lands for cultivating biomass energy crops has emerged as a research focus in recent years.Previous studies have demonstrated that cultivating perennial biomass crops on marginal lands significantly impacts regional climate change and food production.However,these investigations did not fully consider the interactive feedback between plant growth and climate change,leading to slightly insufficient reliability of the result.[Methods]To address the limitations of earlier studies,the coupled model CWRF-BioCro was employed to comprehensively consider the interactive feedback between plant growth and climate change,and to analyze changes in regional precipitation patterns and their physical mechanisms under two scenarios in the United States:cultivation of perennial biomass crops on marginal lands and maintenance of existing vegetation cover.[Results]The result showed that after cultivating perennial biomass crops on marginal lands,the regional total average daily precipitation increased by 6.33 mm/day(0.01%),with most of the increase occurring during spring,summer,and autumn in the central and western regions and during autumn and winter in the eastern region.This was primarily due to the significant enhancement of water vapor transport and latent heat flux in the region.The regional maximum daily precipitation decreased by 2.1 mm(4.39%),mainly in the central and eastern regions,Resulting from a significant decrease in sensible heat flux in these regions.Meanwhile,the frequency of precipitation events with an average daily precipitation greater than 50 mm/d decreased in the central and eastern regions,with the most pronounced reduction of 31 days(0.24%)observed in events in the range of 50.0~99.9 mm/day.[Conclusion]In summary,planting perennial biomass crops on marginal lands can increase regional precipitation and reduce extreme precipitation.These findings highlight the critical role of biophysical feedback mechanisms in regulating regional climate and provide a scientific foundation for developing climate-adaptive land management strategies.展开更多
[Objective]China is one of the countries most severely affected by heavy rainfall from tropical cyclones,incurring annual economic losses amounting to hundreds of billions of yuan.Understanding the variation character...[Objective]China is one of the countries most severely affected by heavy rainfall from tropical cyclones,incurring annual economic losses amounting to hundreds of billions of yuan.Understanding the variation characteristics of these events is crucial for flood prevention and disaster mitigation efforts.[Methods]Based on hourly rainfall data from 1185 meteorological stations in China and the best track dataset of tropical cyclones,heavy rainfall events were defined using an absolute threshold method.Linear regression was employed to analyze the characteristics of hourly-scale heavy rainfall events induced by landfalling tropical cyclones in China from 1980 to 2020.The analysis focused on the spatiotemporal distribution of these events and the interannual variation trends in frequency,intensity,and duration of events with different durations(short-duration:1~6 h,medium-duration:7~12 h,and long-duration:>12 h).[Results](1)Heavy rainfall events induced by landfalling tropical cyclones mainly occurred in Hainan Island and the southeastern coastal areas of China,with their intensity weakening toward inland and northern areas.The overall intensity of such events showed an increasing trend.The duration of heavy rainfall events tended to decrease from south to north and from coastal to inland areas,with Hainan exhibiting the longest duration(6.22 h/a).Areas with increasing trends in event frequency,intensity,and duration were mainly located along the southern coast,the lower reaches of the Yangtze River,and Shandong Province.(2)In rainfall events induced by landfalling tropical cyclones with different durations,long-duration events accounted for the highest proportion(39.75%)and showed an increasing trend in frequency along with short-duration events.The rainfall intensity of both types was increasing,but the duration of long-duration events continued to rise,while that of short-and medium-duration events was decreasing.[Conclusion]From 1980 to 2020,the intensity of heavy rainfall events induced by landfalling tropical cyclones has increased,and event durations have been prolonged,exerting profound impacts on the socioeconomic development and ecological security in some regions of China.The increasing frequency,intensity,and duration of long-duration heavy rainfall events pose significant challenges for disaster prevention in both coastal and inland areas of the country.展开更多
Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic ev...Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic events for providing accurate information of rockmass.The accurate identification of microseismic events and blasts determines the timeliness and accuracy of early warning of microseismic monitoring technology.An image identification model based on Convolutional Neural Network(CNN)is established in this paper for the seismic waveforms of microseismic events and blasts.Firstly,the training set,test set,and validation set are collected,which are composed of 5250,1500,and 750 seismic waveforms of microseismic events and blasts,respectively.The classified data sets are preprocessed and input into the constructed CNN in CPU mode for training.Results show that the accuracies of microseismic events and blasts are 99.46%and 99.33%in the test set,respectively.The accuracies of microseismic events and blasts are 100%and 98.13%in the validation set,respectively.The proposed method gives superior performance when compared with existed methods.The accuracies of models using logistic regression and artificial neural network(ANN)based on the same data set are 54.43%and 67.9%in the test set,respectively.Then,the ROC curves of the three models are obtained and compared,which show that the CNN gives an absolute advantage in this classification model when the original seismic waveform are used in training the model.It not only decreases the influence of individual differences in experience,but also removes the errors induced by source and waveform parameters.It is proved that the established discriminant method improves the efficiency and accuracy of microseismic data processing for monitoring rock instability and seismicity.展开更多
Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-de...Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.展开更多
Objective The utility of non-obstructive coronary artery diseases(NOCAD) in cardiovascular events (CVE) among Chinese patients has less been evaluated. Our objective was to investigate the prognostic value of NOCAD in...Objective The utility of non-obstructive coronary artery diseases(NOCAD) in cardiovascular events (CVE) among Chinese patients has less been evaluated. Our objective was to investigate the prognostic value of NOCAD in patients with angina-like chest pain detected by coronary angiography (CAG) in a large Chinese cohort study.展开更多
Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor do...Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor domains and sparse representation is proposed in this paper,i.e.UKGE-MS.Specifically,UKGE-MS can improve the existing text mining technology's ability of understanding and discovering high-dimensional unmarked information,and solves the problems of traditional unsupervised feature selection methods,which only focus on selecting features from a global perspective and ignoring the impact of local connection of samples.Firstly,considering the influence of local information of samples in feature correlation evaluation,a feature clustering algorithm based on average neighborhood mutual information is proposed,and the feature clusters with certain event correlation are obtained;Secondly,an unsupervised feature selection method based on the high-order correlation of multi-dimensional statistical data is designed by combining the dimension reduction advantage of local linear embedding algorithm and the feature selection ability of sparse representation,so as to enhance the generalization ability of the selected feature items.Finally,the events knowledge graph is constructed by means of sparse representation and l1 norm.Extensive experiments are carried out on five real datasets and synthetic datasets,and the UKGE-MS are compared with five corresponding algorithms.The experimental results show that UKGE-MS is better than the traditional method in event clustering and feature selection,and has some advantages over other methods in text event recognition and discovery.展开更多
In order to get prepared for the coming extreme pollution events and minimize their harmful impacts, the first and most important step is to predict their possible intensity in the future. Firstly, the generalized Par...In order to get prepared for the coming extreme pollution events and minimize their harmful impacts, the first and most important step is to predict their possible intensity in the future. Firstly, the generalized Pareto distribution （GPD） in extreme value theory was used to fit the extreme pollution concentrations of three main pollutants： PM10, NO2 and SO：, from 2005 to 2010 in Changsha, China. Secondly, the prediction results were compared with actual data by a scatter plot. Four statistical indicators： EMA （mean absolute error）, ERMS （root mean square error）, IA （index of agreement） and R2 （coefficient of determination） were used to evaluate the goodness-of-fit as well. Thirdly, the return levels corresponding to different return periods were calculated by the fitted distributions. The fitting results show that the distribution of PM10 and SO2 belongs to exponential distribution with a short tail while that of the NOe belongs to beta distribution with a bounded tail. The scatter plot and four statistical indicators suggest that GPD agrees well with the actual data. Therefore, the fitted distribution is reliable to predict the return levels corresponding to different return periods. The predicted return levels suggest that the intensity of coming pollution events for PM10 and SO2 will be even worse in the future, which means people have to get enough preparation for them.展开更多
Objective To investigate the correlation between gene polymorphisms and the occurrence of adverse clinical events following dual antiplatelet therapy in patients with symptomatic intracranial atherosclerotic stenosis....Objective To investigate the correlation between gene polymorphisms and the occurrence of adverse clinical events following dual antiplatelet therapy in patients with symptomatic intracranial atherosclerotic stenosis.Methods A total of 195 patients were enrolled and categorized into 32 cases(those with clinical adverse events)and 163 controls(without events).Genotyping of 20 single nucleotide polymorphism(SNP)from 17 genes was executed.To address the imbalance in sample size between cases(n=32)and controls(n=163),weighted Logistic regression analysis was performed using frequency weights based on the reciprocal of group proportions.Weights were calculated to account for the unequal case-control ratio and improve the stability and reliability of regression estimates.Results The ITGA2 rs1126643(C807T)and rs1062535(G873A)polymorphisms were significantly correlated with adverse clinical events.Specifically,the mutant frequency of allele C(ITGA2 rs1126643)and allele G(ITGA2 rs1062535)was significantly higher in cases compared to controls(OR=2.97,95%CI:1.702-5.172,P=0.0001;OR=3.27,95%CI:1.762-6.066,P=0.0002,respectively).Other genotypes showed no significant differences between the groups.Conclusion The ITGA2 C807T and G873A polymorphisms are associated with an increased risk of recurrent ischemic events in Chinese patients with symptomatic intracranial atherosclerotic stenosis after stenting.Detection of these variants may help identify individuals at high risk of recurrent ischemic events in this specific population.展开更多
一、环保纪录片的里程碑关于环保的纪录片多是欧美发达国家拍摄的,例如:《可爱的动物(Animals Are Beautiful People)》(1974,南非)、《野鸟世界(The Life of Birds)》(1998,英国)、《地球公民(Earthlings)》(2005,美国)、《地球脉动(Pl...一、环保纪录片的里程碑关于环保的纪录片多是欧美发达国家拍摄的,例如:《可爱的动物(Animals Are Beautiful People)》(1974,南非)、《野鸟世界(The Life of Birds)》(1998,英国)、《地球公民(Earthlings)》(2005,美国)、《地球脉动(Planet Earth)》(2006,英国)、《难以忽视的真相(An Inconvenient Truth)》(2006,美国)、《危险中的星球(Planet in Peril)》(2007,美国)、《自然界大事件(Nature’s Great Events)》(2009,英国)、《人类星球(Human Planet)》(2011,英国)、《家园(Home)》(2011,展开更多
Our study area covered the Eastern Himalayan Syntaxis (EHS) and its southern extension (Hengduan Mountain or western Sichuan and Yunnan (WSY)) which is located at the orthogonal and oblique collisional front between I...Our study area covered the Eastern Himalayan Syntaxis (EHS) and its southern extension (Hengduan Mountain or western Sichuan and Yunnan (WSY)) which is located at the orthogonal and oblique collisional front between Indian and Asian continents during Cenozoic.Based on geometric and kinematic mapping of the major boundary or regional faults (Dongjug—Mainling(1), Anigiao(2) and Jali(3), Guyu(4) faults in EHS, Ailaoshan—Red River(5), Lancangjiang(6), Gaoligong(7), Binlangjiang(8) and Magok(9) faults in WSY) (see Fig.1), especially on abundant geochronological dating of the mylonitic rocks along these faults, and coupled with magmato\|metamorphic sequences of this region, we try to deal with the temporal and spatial relationships of collisional process to answer questions such as: (1) when did collision start ? (2) is thrusting as a initial and dominant deformation mode to absorb the crustal shortening after suturing, or earlier thrusting usually followed by large\|scale strike\|slip faults? (3) are the two structural patterns coeval at times, or do they occur alternatively during deformation history? (4) are the collisional and associate uplift processes a continuous one or periodic? Insight into such questions is crucial for better understanding of the continental deformation and testing the models available or constraining a new one.展开更多
文摘[Objective]With increasing energy demand and growing concerns about climate change,the rational utilization of marginal lands for cultivating biomass energy crops has emerged as a research focus in recent years.Previous studies have demonstrated that cultivating perennial biomass crops on marginal lands significantly impacts regional climate change and food production.However,these investigations did not fully consider the interactive feedback between plant growth and climate change,leading to slightly insufficient reliability of the result.[Methods]To address the limitations of earlier studies,the coupled model CWRF-BioCro was employed to comprehensively consider the interactive feedback between plant growth and climate change,and to analyze changes in regional precipitation patterns and their physical mechanisms under two scenarios in the United States:cultivation of perennial biomass crops on marginal lands and maintenance of existing vegetation cover.[Results]The result showed that after cultivating perennial biomass crops on marginal lands,the regional total average daily precipitation increased by 6.33 mm/day(0.01%),with most of the increase occurring during spring,summer,and autumn in the central and western regions and during autumn and winter in the eastern region.This was primarily due to the significant enhancement of water vapor transport and latent heat flux in the region.The regional maximum daily precipitation decreased by 2.1 mm(4.39%),mainly in the central and eastern regions,Resulting from a significant decrease in sensible heat flux in these regions.Meanwhile,the frequency of precipitation events with an average daily precipitation greater than 50 mm/d decreased in the central and eastern regions,with the most pronounced reduction of 31 days(0.24%)observed in events in the range of 50.0~99.9 mm/day.[Conclusion]In summary,planting perennial biomass crops on marginal lands can increase regional precipitation and reduce extreme precipitation.These findings highlight the critical role of biophysical feedback mechanisms in regulating regional climate and provide a scientific foundation for developing climate-adaptive land management strategies.
文摘[Objective]China is one of the countries most severely affected by heavy rainfall from tropical cyclones,incurring annual economic losses amounting to hundreds of billions of yuan.Understanding the variation characteristics of these events is crucial for flood prevention and disaster mitigation efforts.[Methods]Based on hourly rainfall data from 1185 meteorological stations in China and the best track dataset of tropical cyclones,heavy rainfall events were defined using an absolute threshold method.Linear regression was employed to analyze the characteristics of hourly-scale heavy rainfall events induced by landfalling tropical cyclones in China from 1980 to 2020.The analysis focused on the spatiotemporal distribution of these events and the interannual variation trends in frequency,intensity,and duration of events with different durations(short-duration:1~6 h,medium-duration:7~12 h,and long-duration:>12 h).[Results](1)Heavy rainfall events induced by landfalling tropical cyclones mainly occurred in Hainan Island and the southeastern coastal areas of China,with their intensity weakening toward inland and northern areas.The overall intensity of such events showed an increasing trend.The duration of heavy rainfall events tended to decrease from south to north and from coastal to inland areas,with Hainan exhibiting the longest duration(6.22 h/a).Areas with increasing trends in event frequency,intensity,and duration were mainly located along the southern coast,the lower reaches of the Yangtze River,and Shandong Province.(2)In rainfall events induced by landfalling tropical cyclones with different durations,long-duration events accounted for the highest proportion(39.75%)and showed an increasing trend in frequency along with short-duration events.The rainfall intensity of both types was increasing,but the duration of long-duration events continued to rise,while that of short-and medium-duration events was decreasing.[Conclusion]From 1980 to 2020,the intensity of heavy rainfall events induced by landfalling tropical cyclones has increased,and event durations have been prolonged,exerting profound impacts on the socioeconomic development and ecological security in some regions of China.The increasing frequency,intensity,and duration of long-duration heavy rainfall events pose significant challenges for disaster prevention in both coastal and inland areas of the country.
基金Projects(51822407,51774327,51664016)supported by the National Natural Science Foundation of China。
文摘Microseismic monitoring system is one of the effective methods for deep mining geo-stress monitoring.The principle of microseismic monitoring system is to analyze the mechanical parameters contained in microseismic events for providing accurate information of rockmass.The accurate identification of microseismic events and blasts determines the timeliness and accuracy of early warning of microseismic monitoring technology.An image identification model based on Convolutional Neural Network(CNN)is established in this paper for the seismic waveforms of microseismic events and blasts.Firstly,the training set,test set,and validation set are collected,which are composed of 5250,1500,and 750 seismic waveforms of microseismic events and blasts,respectively.The classified data sets are preprocessed and input into the constructed CNN in CPU mode for training.Results show that the accuracies of microseismic events and blasts are 99.46%and 99.33%in the test set,respectively.The accuracies of microseismic events and blasts are 100%and 98.13%in the validation set,respectively.The proposed method gives superior performance when compared with existed methods.The accuracies of models using logistic regression and artificial neural network(ANN)based on the same data set are 54.43%and 67.9%in the test set,respectively.Then,the ROC curves of the three models are obtained and compared,which show that the CNN gives an absolute advantage in this classification model when the original seismic waveform are used in training the model.It not only decreases the influence of individual differences in experience,but also removes the errors induced by source and waveform parameters.It is proved that the established discriminant method improves the efficiency and accuracy of microseismic data processing for monitoring rock instability and seismicity.
基金Projects(41601424,41171351)supported by the National Natural Science Foundation of ChinaProject(2012CB719906)supported by the National Basic Research Program of China(973 Program)+2 种基金Project(14JJ1007)supported by the Hunan Natural Science Fund for Distinguished Young Scholars,ChinaProject(2017M610486)supported by the China Postdoctoral Science FoundationProjects(2017YFB0503700,2017YFB0503601)supported by the National Key Research and Development Foundation of China
文摘Climate sequences can be applied to defining sensitive climate zones, and then the mining of spatio-temporal teleconnection patterns is useful for learning from the past and preparing for the future. However, scale-dependency in this kind of pattern is still not well handled by existing work. Therefore, in this study, the multi-scale regionalization is embedded into the spatio-temporal teleconnection pattern mining between anomalous sea and land climatic events. A modified scale-space clustering algorithm is first developed to group climate sequences into multi-scale climate zones. Then, scale variance analysis method is employed to identify climate zones at characteristic scales, indicating the main characteristics of geographical phenomena. Finally, by using the climate zones identified at characteristic scales, a time association rule mining algorithm based on sliding time windows is employed to discover spatio-temporal teleconnection patterns. Experiments on sea surface temperature, sea level pressure, land precipitation and land temperature datasets show that many patterns obtained by the multi-scale approach are coincident with prior knowledge, indicating that this method is effective and reasonable. In addition, some unknown teleconnection patterns discovered from the multi-scale approach can be further used to guide the prediction of land climate.
文摘Objective The utility of non-obstructive coronary artery diseases(NOCAD) in cardiovascular events (CVE) among Chinese patients has less been evaluated. Our objective was to investigate the prognostic value of NOCAD in patients with angina-like chest pain detected by coronary angiography (CAG) in a large Chinese cohort study.
基金This study was funded by the International Science and Technology Cooperation Program of the Science and Technology Department of Shaanxi Province,China(No.2021KW-16)the Science and Technology Project in Xi’an(No.2019218114GXRC017CG018-GXYD17.11),Thesis work was supported by the special fund construction project of Key Disciplines in Ordinary Colleges and Universities in Shaanxi Province,the authors would like to thank the anonymous reviewers for their helpful comments and suggestions.
文摘Text event mining,as an indispensable method of text mining processing,has attracted the extensive attention of researchers.A modeling method for knowledge graph of events based on mutual information among neighbor domains and sparse representation is proposed in this paper,i.e.UKGE-MS.Specifically,UKGE-MS can improve the existing text mining technology's ability of understanding and discovering high-dimensional unmarked information,and solves the problems of traditional unsupervised feature selection methods,which only focus on selecting features from a global perspective and ignoring the impact of local connection of samples.Firstly,considering the influence of local information of samples in feature correlation evaluation,a feature clustering algorithm based on average neighborhood mutual information is proposed,and the feature clusters with certain event correlation are obtained;Secondly,an unsupervised feature selection method based on the high-order correlation of multi-dimensional statistical data is designed by combining the dimension reduction advantage of local linear embedding algorithm and the feature selection ability of sparse representation,so as to enhance the generalization ability of the selected feature items.Finally,the events knowledge graph is constructed by means of sparse representation and l1 norm.Extensive experiments are carried out on five real datasets and synthetic datasets,and the UKGE-MS are compared with five corresponding algorithms.The experimental results show that UKGE-MS is better than the traditional method in event clustering and feature selection,and has some advantages over other methods in text event recognition and discovery.
基金Project(51178466) supported by the National Natural Science Foundation of ChinaProject(200545) supported by the Foundation for the Author of National Excellent Doctoral Dissertation of China+1 种基金Project(2011JQ006) supported by the Fundamental Research Funds of the Central Universities of ChinaProject(2008BAJ12B03) supported by the National Key Program of Scientific and Technical Supporting Programs of China
文摘In order to get prepared for the coming extreme pollution events and minimize their harmful impacts, the first and most important step is to predict their possible intensity in the future. Firstly, the generalized Pareto distribution （GPD） in extreme value theory was used to fit the extreme pollution concentrations of three main pollutants： PM10, NO2 and SO：, from 2005 to 2010 in Changsha, China. Secondly, the prediction results were compared with actual data by a scatter plot. Four statistical indicators： EMA （mean absolute error）, ERMS （root mean square error）, IA （index of agreement） and R2 （coefficient of determination） were used to evaluate the goodness-of-fit as well. Thirdly, the return levels corresponding to different return periods were calculated by the fitted distributions. The fitting results show that the distribution of PM10 and SO2 belongs to exponential distribution with a short tail while that of the NOe belongs to beta distribution with a bounded tail. The scatter plot and four statistical indicators suggest that GPD agrees well with the actual data. Therefore, the fitted distribution is reliable to predict the return levels corresponding to different return periods. The predicted return levels suggest that the intensity of coming pollution events for PM10 and SO2 will be even worse in the future, which means people have to get enough preparation for them.
文摘Objective To investigate the correlation between gene polymorphisms and the occurrence of adverse clinical events following dual antiplatelet therapy in patients with symptomatic intracranial atherosclerotic stenosis.Methods A total of 195 patients were enrolled and categorized into 32 cases(those with clinical adverse events)and 163 controls(without events).Genotyping of 20 single nucleotide polymorphism(SNP)from 17 genes was executed.To address the imbalance in sample size between cases(n=32)and controls(n=163),weighted Logistic regression analysis was performed using frequency weights based on the reciprocal of group proportions.Weights were calculated to account for the unequal case-control ratio and improve the stability and reliability of regression estimates.Results The ITGA2 rs1126643(C807T)and rs1062535(G873A)polymorphisms were significantly correlated with adverse clinical events.Specifically,the mutant frequency of allele C(ITGA2 rs1126643)and allele G(ITGA2 rs1062535)was significantly higher in cases compared to controls(OR=2.97,95%CI:1.702-5.172,P=0.0001;OR=3.27,95%CI:1.762-6.066,P=0.0002,respectively).Other genotypes showed no significant differences between the groups.Conclusion The ITGA2 C807T and G873A polymorphisms are associated with an increased risk of recurrent ischemic events in Chinese patients with symptomatic intracranial atherosclerotic stenosis after stenting.Detection of these variants may help identify individuals at high risk of recurrent ischemic events in this specific population.
文摘一、环保纪录片的里程碑关于环保的纪录片多是欧美发达国家拍摄的,例如:《可爱的动物(Animals Are Beautiful People)》(1974,南非)、《野鸟世界(The Life of Birds)》(1998,英国)、《地球公民(Earthlings)》(2005,美国)、《地球脉动(Planet Earth)》(2006,英国)、《难以忽视的真相(An Inconvenient Truth)》(2006,美国)、《危险中的星球(Planet in Peril)》(2007,美国)、《自然界大事件(Nature’s Great Events)》(2009,英国)、《人类星球(Human Planet)》(2011,英国)、《家园(Home)》(2011,
文摘Our study area covered the Eastern Himalayan Syntaxis (EHS) and its southern extension (Hengduan Mountain or western Sichuan and Yunnan (WSY)) which is located at the orthogonal and oblique collisional front between Indian and Asian continents during Cenozoic.Based on geometric and kinematic mapping of the major boundary or regional faults (Dongjug—Mainling(1), Anigiao(2) and Jali(3), Guyu(4) faults in EHS, Ailaoshan—Red River(5), Lancangjiang(6), Gaoligong(7), Binlangjiang(8) and Magok(9) faults in WSY) (see Fig.1), especially on abundant geochronological dating of the mylonitic rocks along these faults, and coupled with magmato\|metamorphic sequences of this region, we try to deal with the temporal and spatial relationships of collisional process to answer questions such as: (1) when did collision start ? (2) is thrusting as a initial and dominant deformation mode to absorb the crustal shortening after suturing, or earlier thrusting usually followed by large\|scale strike\|slip faults? (3) are the two structural patterns coeval at times, or do they occur alternatively during deformation history? (4) are the collisional and associate uplift processes a continuous one or periodic? Insight into such questions is crucial for better understanding of the continental deformation and testing the models available or constraining a new one.
