Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base ...Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.展开更多
Statistical and contextual information are typically used to detect moving regions in image sequences for a fixed camera.In this paper,we propose a fast and stable linear discriminant approach based on Gaussian Single...Statistical and contextual information are typically used to detect moving regions in image sequences for a fixed camera.In this paper,we propose a fast and stable linear discriminant approach based on Gaussian Single Model(GSM)and Markov Random Field(MRF).The performance of GSM is analyzed first,and then two main improvements corresponding to the drawbacks of GSM are proposed:the latest filtered data based update scheme of the background model and the linear classification judgment rule based on spatial-temporal feature specified by MRF.Experimental results show that the proposed method runs more rapidly and accurately when compared with other methods.展开更多
Functional near-infrared spectroscopy(fNIRS)is a neuroimaging technology which is suitable for psychiatric patients.Several fNIRS studies have found abnormal brain activations during cognitive tasks in elderly depress...Functional near-infrared spectroscopy(fNIRS)is a neuroimaging technology which is suitable for psychiatric patients.Several fNIRS studies have found abnormal brain activations during cognitive tasks in elderly depression.In this paper,we proposed a discriminative model of multivariate pattern classification based on fNIRS signals to distinguish elderly depressed patients from healthy controls.This model used the brain activation patterns during a verbal fluency task as features of classification.Then Pseudo-Fisher Linear Discriminant Analysis was performed on the feature space to generate discriminative model.Using leave-one-out(LOO)cross-validation,our results showed a correct classification rate of 88%.The discriminative model showed its ability to identify people with elderly depression and suggested that fNIRS may be an efficient clinical tool for diagnosis of depression.This study may provide the first step for the development of neuroimaging biomarkers based on fNIRS in psychiatric disorders.展开更多
基金Under the National Key R&D Program Key Project(No.2021YFC3201201)National Natural Science Foundation of China(No.52360032)+2 种基金Basic Scientific Research Business Fee Project of Colleges And Universities Directly Under the Inner Mongolia Autonomous Region(No.JBYYWF2022001)Development Plan of Innovation Team of Colleges And Universities in Inner Mongolia Autonomous Region(No.NMGIRT2313)the Innovation Team of‘Grassland Talents’。
文摘Clarifying the mechanisms through which coal mining affects groundwater storage(GWS)variations is crucial for water resource conservation and sustainable development.The Ordos Mining Region in China,a key energy base in China with significant strategic importance,has undergone intensive coal mining activities that have substantially disrupted regional groundwater circulation.This study integrated data from the Gravity Recovery and Climate Experiment Satellite(GRACE)and Famine Early Warning Systems Network(FEWS NET)Land Data Assimilation System(FLDAS)models,combined with weighted downscaling methodology and water balance principles,to reconstruct high-resolution(0.01°)terrestrial water storage(TWS)and GWS changes in the Ordos Mining Region,China from April 2002 to December 2021.The accuracy of GWS variations were validated through pumping test measurements.Subsequently,Geodetector analysis was implemented to quantify the contributions of natural and anthropogenic factors to groundwater storage dynamics.Key findings include:1)TWS in the study area showed a fluctuating but overall decreasing trend,with a total reduction of 8901.11 mm during study period.The most significant annual decrease occurred in 2021,reaching 1696.77 mm.2)GWS exhibited an accelerated decline,with an average annual change rate of 44.35 mm/yr,totaling a decrease of 887.05 mm.The lowest annual groundwater storage level was recorded in 2020,reaching 185.69 mm.3)Precipitation(PRE)contributed the most to GWS variation(q=0.52),followed by coal mining water consumption(MWS)(q=0.41).The interaction between PRE and MWS exhibited a nonlinear enhancement effect on GWS changes(0.54).The synergistic effect of natural hydrological factors has a great influence on the change of GWS,but coal mining water consumption will continue to reduce GWS.These findings provide critical references for the management and regulation of groundwater resource in mining regions.
基金Project (No. 10577017) supported by the National Natural Science Foundation of China
文摘Statistical and contextual information are typically used to detect moving regions in image sequences for a fixed camera.In this paper,we propose a fast and stable linear discriminant approach based on Gaussian Single Model(GSM)and Markov Random Field(MRF).The performance of GSM is analyzed first,and then two main improvements corresponding to the drawbacks of GSM are proposed:the latest filtered data based update scheme of the background model and the linear classification judgment rule based on spatial-temporal feature specified by MRF.Experimental results show that the proposed method runs more rapidly and accurately when compared with other methods.
文摘Functional near-infrared spectroscopy(fNIRS)is a neuroimaging technology which is suitable for psychiatric patients.Several fNIRS studies have found abnormal brain activations during cognitive tasks in elderly depression.In this paper,we proposed a discriminative model of multivariate pattern classification based on fNIRS signals to distinguish elderly depressed patients from healthy controls.This model used the brain activation patterns during a verbal fluency task as features of classification.Then Pseudo-Fisher Linear Discriminant Analysis was performed on the feature space to generate discriminative model.Using leave-one-out(LOO)cross-validation,our results showed a correct classification rate of 88%.The discriminative model showed its ability to identify people with elderly depression and suggested that fNIRS may be an efficient clinical tool for diagnosis of depression.This study may provide the first step for the development of neuroimaging biomarkers based on fNIRS in psychiatric disorders.
