In this paper,we propose a new biased estimator of the regression parameters,the generalized ridge and principal correlation estimator.We present its some properties and prove that it is superior to LSE(least squares ...In this paper,we propose a new biased estimator of the regression parameters,the generalized ridge and principal correlation estimator.We present its some properties and prove that it is superior to LSE(least squares estimator),principal correlation estimator,ridge and principal correlation estimator under MSE(mean squares error) and PMC(Pitman closeness) criterion,respectively.展开更多
<span style="font-family:""><span style="font-family:Verdana;">Flood is a natural process generated by the interaction of various driving fac</span><span style="font-...<span style="font-family:""><span style="font-family:Verdana;">Flood is a natural process generated by the interaction of various driving fac</span><span style="font-family:Verdana;">tors. Flood peak flows, flood frequency at different return periods, and potential driving forces are analyzed in this study. The peak flow of six gauging stations, with a catchment area ranging from 169 -</span></span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">124,108 km</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> and sufficient observed streamflow data, was selected to develop threshold (3</span><sup><span style="font-family:Verdana;">rd</span></sup><span style="font-family:Verdana;"> quartile) magnitude and frequency (POTF) that occurred over ten years of records. Sixteen Potential climatic, watershed and human driving factors of floods in the study area were identified and analyzed with GIS, Pearson’s correlation, and Principal Correlation Analysis (PCA) to select the most influential factors. Eight of them (MAR, DA, BE, VS, sand, forest AGR, PD) are identified as the most significant variables in the flood formation of the basin. Moreover, mean annual rainfall (MAR), drainage area (DA), and lack of forest cover are explored as the principal driving factors for flood peak discharge in Wabi-Shebele River Basin. Fi</span></span><span style="font-family:""><span style="font-family:Verdana;">nally, the study resulted in regression equations that helped plan and design different infrastructure works in the basin as ungauged catchment empirical</span><span><span style="font-family:Verdana;"> equations to compute Q</span><sub><span style="font-family:Verdana;">MPF</span></sub><span style="font-family:Verdana;">, Q</span><sub><span style="font-family:Verdana;">5</span></sub><span style="font-family:Verdana;">, Q</span><sub><span style="font-family:Verdana;">10</span></sub><span style="font-family:Verdana;">, Q</span><sub><span style="font-family:Verdana;">50</span></sub><span style="font-family:Verdana;">, and Q</span><sub><span style="font-family:Verdana;">100</span></sub><span style="font-family:Verdana;"> using influential climate, watershed, and human driving factors. The results of these empirical equations are </span></span><span style="font-family:Verdana;">also statistically accepted with a high significance correlation (R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> > 0.9).展开更多
In this paper, a novel criterion is proposed to determine the retained principal components (PCs) that capture the dominant variability of online monitored data. The variations of PCs were calculated according to thei...In this paper, a novel criterion is proposed to determine the retained principal components (PCs) that capture the dominant variability of online monitored data. The variations of PCs were calculated according to their mean and covariance changes between the modeling sample and the online monitored data. The retained PCs containing dominant variations were selected and defined as correlative PCs (CPCs). The new Hotelling's T2 statistic based on CPCs was then employed to monitor the process. Case studies on the simulated continuous stirred tank reactor and the well-known Tennessee Eastman process demonstrated the feasibility and effectiveness of the CPCs-based fault detection methods.展开更多
Background Schizophrenia is considered to be a disorder of dysconnectivity characterized by abnormal functional integration between distinct brain regions.Different brain connection abnormalities were found to be corr...Background Schizophrenia is considered to be a disorder of dysconnectivity characterized by abnormal functional integration between distinct brain regions.Different brain connection abnormalities were found to be correlated with various clinical manifestations,but whether a common deficit in functional connectivity(FC)in relation to both clinical symptoms and cognitive impairments could present in first-episode patients who have never received any medication remains elusive.Objective To find a core deficit in the brain connectome that is related to both psychopathological and cognitive manifestations.Methods A total of 75 patients with first-episode schizophrenia and 51 healthy control participants underwent scanning of the brain and clinical ratings of behaviors.A principal component analysis was performed on the clinical ratings of symptom and cognition.Partial correlation analyses were conducted between the main psychopathological components and resting-state FC that were found abnormal in schizophrenia patients.Results Using the principal component analysis,the first principal component(PC1)explained 37%of the total variance of seven clinical features.The ratings of GAF and BACS contributed negatively to PC1,while those of PANSS,HAMD,and HAMA contributed positively.The FCs positively correlated with PC1 mainly included connections related to the insula,precuneus gyrus,and some frontal brain regions.FCs negatively correlated with PC1 mainly included connections between the left middle cingulate cortex and superior and middle occipital regions.Conclusion In conclusion,we found a linked pattern of FC associated with both psychopathological and cognitive manifestations in drug-na¨ıve first-episode schizophrenia characterized as the dysconnection related to the frontal and visual cortex,which may represent a core deficit of brain FC in patients with schizophrenia.展开更多
基金Foundation item： the National Natural Science Foundation of China （Nos. 60736047 10671007+2 种基金 60772036） the Foundation of Beijing Jiaotong University （Nos. 2006XM037 2007XM046）.
文摘In this paper,we propose a new biased estimator of the regression parameters,the generalized ridge and principal correlation estimator.We present its some properties and prove that it is superior to LSE(least squares estimator),principal correlation estimator,ridge and principal correlation estimator under MSE(mean squares error) and PMC(Pitman closeness) criterion,respectively.
文摘<span style="font-family:""><span style="font-family:Verdana;">Flood is a natural process generated by the interaction of various driving fac</span><span style="font-family:Verdana;">tors. Flood peak flows, flood frequency at different return periods, and potential driving forces are analyzed in this study. The peak flow of six gauging stations, with a catchment area ranging from 169 -</span></span><span style="font-family:""> </span><span style="font-family:""><span style="font-family:Verdana;">124,108 km</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> and sufficient observed streamflow data, was selected to develop threshold (3</span><sup><span style="font-family:Verdana;">rd</span></sup><span style="font-family:Verdana;"> quartile) magnitude and frequency (POTF) that occurred over ten years of records. Sixteen Potential climatic, watershed and human driving factors of floods in the study area were identified and analyzed with GIS, Pearson’s correlation, and Principal Correlation Analysis (PCA) to select the most influential factors. Eight of them (MAR, DA, BE, VS, sand, forest AGR, PD) are identified as the most significant variables in the flood formation of the basin. Moreover, mean annual rainfall (MAR), drainage area (DA), and lack of forest cover are explored as the principal driving factors for flood peak discharge in Wabi-Shebele River Basin. Fi</span></span><span style="font-family:""><span style="font-family:Verdana;">nally, the study resulted in regression equations that helped plan and design different infrastructure works in the basin as ungauged catchment empirical</span><span><span style="font-family:Verdana;"> equations to compute Q</span><sub><span style="font-family:Verdana;">MPF</span></sub><span style="font-family:Verdana;">, Q</span><sub><span style="font-family:Verdana;">5</span></sub><span style="font-family:Verdana;">, Q</span><sub><span style="font-family:Verdana;">10</span></sub><span style="font-family:Verdana;">, Q</span><sub><span style="font-family:Verdana;">50</span></sub><span style="font-family:Verdana;">, and Q</span><sub><span style="font-family:Verdana;">100</span></sub><span style="font-family:Verdana;"> using influential climate, watershed, and human driving factors. The results of these empirical equations are </span></span><span style="font-family:Verdana;">also statistically accepted with a high significance correlation (R</span><sup><span style="font-family:Verdana;">2</span></sup><span style="font-family:Verdana;"> > 0.9).
基金supported by the National Basic Research Program of China (973 Program) (No. 2013CB733600)the National Natural Science Foundation of China (No. 21176073)+1 种基金the Program for New Century Excellent Talents in University (No. NCET-09-0346)the Fundamental Research Funds for the Central Universities, China
文摘In this paper, a novel criterion is proposed to determine the retained principal components (PCs) that capture the dominant variability of online monitored data. The variations of PCs were calculated according to their mean and covariance changes between the modeling sample and the online monitored data. The retained PCs containing dominant variations were selected and defined as correlative PCs (CPCs). The new Hotelling's T2 statistic based on CPCs was then employed to monitor the process. Case studies on the simulated continuous stirred tank reactor and the well-known Tennessee Eastman process demonstrated the feasibility and effectiveness of the CPCs-based fault detection methods.
基金This study was supported by the National Natural Science Foundation of China(Grant Nos.8212018014,82071908,81761128023,and 82101998)Sichuan Science and Technology Program(Grant Nos.2021JDTD0002 and 2020YJ0018)+4 种基金Post-Doctor Research Project,West China Hospital,Sichuan University(Grant No.2020HXBH005)the Fundamental Research Funds for the Central Universities(Grant No.2020SCU12053)Miaozi Project in Science and Technology Innovation Program of Sichuan Province(Grant No.2021028)1.3.5 Project for Disciplines of Excellence,West China Hospital,Sichuan University(Project Nos.ZYYC08001 and ZYJC18020)Dr Lui acknowledges the support from Humboldt Foundation Friedrich Wilhelm Bessel Research Award and Chang Jiang Scholars(Program No.T2019069).
文摘Background Schizophrenia is considered to be a disorder of dysconnectivity characterized by abnormal functional integration between distinct brain regions.Different brain connection abnormalities were found to be correlated with various clinical manifestations,but whether a common deficit in functional connectivity(FC)in relation to both clinical symptoms and cognitive impairments could present in first-episode patients who have never received any medication remains elusive.Objective To find a core deficit in the brain connectome that is related to both psychopathological and cognitive manifestations.Methods A total of 75 patients with first-episode schizophrenia and 51 healthy control participants underwent scanning of the brain and clinical ratings of behaviors.A principal component analysis was performed on the clinical ratings of symptom and cognition.Partial correlation analyses were conducted between the main psychopathological components and resting-state FC that were found abnormal in schizophrenia patients.Results Using the principal component analysis,the first principal component(PC1)explained 37%of the total variance of seven clinical features.The ratings of GAF and BACS contributed negatively to PC1,while those of PANSS,HAMD,and HAMA contributed positively.The FCs positively correlated with PC1 mainly included connections related to the insula,precuneus gyrus,and some frontal brain regions.FCs negatively correlated with PC1 mainly included connections between the left middle cingulate cortex and superior and middle occipital regions.Conclusion In conclusion,we found a linked pattern of FC associated with both psychopathological and cognitive manifestations in drug-na¨ıve first-episode schizophrenia characterized as the dysconnection related to the frontal and visual cortex,which may represent a core deficit of brain FC in patients with schizophrenia.
