In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by re...In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.展开更多
BACKGROUND Patients with acute-on-chronic liver failure(ACLF)experience severe immune dysfunction.Liver transplantation(LT)significantly improves survival outcomes.However,the characteristics of peripheral blood lymph...BACKGROUND Patients with acute-on-chronic liver failure(ACLF)experience severe immune dysfunction.Liver transplantation(LT)significantly improves survival outcomes.However,the characteristics of peripheral blood lymphocyte subsets(PBLSs)in this patient population are not well defined,and the dynamics of immune reconstitution post-LT are insufficiently understood.AIM To characterize PBLSs in patients with ACLF prior to LT and to evaluate PBLS reconstitution after LT.METHODS Clinical data from patients undergoing LT in the Transplantation Center,The Third Xiangya Hospital from January 2022 to December 2023 were analyzed retrospectively.Our cohort comprised 44 patients with ACLF,16 patients with acute decompensation of cirrhosis,and 23 patients with compensated cirrhosis.Twenty healthy volunteers were included as controls.PBLSs were evaluated across all groups.The relationship between PBLSs and post-LT prognosis was assessed,and dynamic changes in PBLSs among patients with ACLF were analyzed at different time points.RESULTS Patients with ACLF exhibited a marked reduction in PBLSs compared with healthy volunteers.Natural killer(NK)cell counts were further reduced in patients with ACLF when compared with patients with compensated cirrhosis.PBLSs did not correlate with the etiology or severity of ACLF or with established liver failure scores.Following LT,a rapid restoration of NK cells and B cells was observed in patients with ACLF.However,the cluster of differentiation(CD)3+T cell and CD4+T cell counts decreased 14 days post-LT and subsequently returned to preoperative levels by day 21.CONCLUSION Patients with ACLF exhibited markedly reduced PBLSs,with decreased NK cells potentially linked to progression from compensated cirrhosis to liver failure.NK and B cell were rapidly restored after LT.展开更多
In modal logic,topological semantics is an intuitive and natural special case of neighbourhood semantics.This paper stems from the observation that the satisfaction relation of topological semantics applies to subset ...In modal logic,topological semantics is an intuitive and natural special case of neighbourhood semantics.This paper stems from the observation that the satisfaction relation of topological semantics applies to subset spaces which are more general than topological spaces.The minimal modal logic which is strongly sound and complete with respect to the class of subset spaces is found.Soundness and completeness results of some famous modal logics(e.g.S4,S5 and Tr)with respect to various important classes of subset spaces(eg intersection structures and complete fields of sets)are also proved.In the meantime,some known results,e.g.the soundness and completeness of Tr with respect to the class of discrete topological spaces,are proved directly using some modifications of the method of canonical mode1,without a detour via neighbourhood semantics or relational semantics.展开更多
The stratospheric airship is affected by harsh conditions in the stratosphere environment.To ensure the safety of the airship,it is necessary to detect the material state of the airship envelope.Since digital image co...The stratospheric airship is affected by harsh conditions in the stratosphere environment.To ensure the safety of the airship,it is necessary to detect the material state of the airship envelope.Since digital image correlation possesses non-contact strain measurement ability,this paper explores the infuence of different shapes of the subset on measurement accuracy.Through the results,it is found that increasing the aspect ratio of subsets can improve the strain accuracy measured in the c-direction,and reducing the aspect ratio can improve the strain accuracy measured in the y-direction.This trend becomes more obvious as the strain increases.Based on this discovery,a subset adaptive algorithm is proposed.The feasibility of the algorithm is verified by experiments,and the precision of strain measurement can be effectively improved by adjusting the threshold value.Therefore,the algorithm can be utilized to increase the measurement accuracy in the larger strain direction without changing the size of the subset.展开更多
There are some limitations when we apply conventional methods to analyze the massive amounts of seismic data acquired with high-density spatial sampling since processors usually obtain the properties of raw data from ...There are some limitations when we apply conventional methods to analyze the massive amounts of seismic data acquired with high-density spatial sampling since processors usually obtain the properties of raw data from common shot gathers or other datasets located at certain points or along lines. We propose a novel method in this paper to observe seismic data on time slices from spatial subsets. The composition of a spatial subset and the unique character of orthogonal or oblique subsets are described and pre-stack subsets are shown by 3D visualization. In seismic data processing, spatial subsets can be used for the following aspects： （1） to check the trace distribution uniformity and regularity; （2） to observe the main features of ground-roll and linear noise; （3） to find abnormal traces from slices of datasets; and （4） to QC the results of pre-stack noise attenuation. The field data application shows that seismic data analysis in spatial subsets is an effective method that may lead to a better discrimination among various wavefields and help us obtain more information.展开更多
A new method that uses a modified ordered subsets （MOS） algorithm to improve the convergence rate of space-alternating generalized expectation-maximization （SAGE） algorithm for positron emission tomography （PET）...A new method that uses a modified ordered subsets （MOS） algorithm to improve the convergence rate of space-alternating generalized expectation-maximization （SAGE） algorithm for positron emission tomography （PET） image reconstruction is proposed.In the MOS-SAGE algorithm,the number of projections and the access order of the subsets are modified in order to improve the quality of the reconstructed images and accelerate the convergence speed.The number of projections in a subset increases as follows：2,4,8,16,32 and 64.This sequence means that the high frequency component is recovered first and the low frequency component is recovered in the succeeding iteration steps.In addition,the neighboring subsets are separated as much as possible so that the correlation of projections can be decreased and the convergences can be speeded up.The application of the proposed method to simulated and real images shows that the MOS-SAGE algorithm has better performance than the SAGE algorithm and the OSEM algorithm in convergence and image quality.展开更多
Objective: To study the expression of Fas and Bcl-2proteins on T lymphocyte subsets in the peripheralblood of relapsing patients with condyloma acuminatum(CA) and healthy controls. Methods: Flow cytometry (permeabizat...Objective: To study the expression of Fas and Bcl-2proteins on T lymphocyte subsets in the peripheralblood of relapsing patients with condyloma acuminatum(CA) and healthy controls. Methods: Flow cytometry (permeabization andstaining procedure with conjugated antibodies) wasused. Results: We observed that the expression of Fasprotein on CD4^+ T lymphocyte subset of CA patientswas significantly higher than that of healthy controls(P<0.01). Conclusions: Increased expression of Fas proteinon CD4^+ T lymphocyte subset may be a cause of de-creased percentage of CD4^+ T lymphocyte subset. Thisinduces the increased ratio of CD4^+/CD8^+.展开更多
The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is pr...The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is proposed and applied to model and forecast power load. Numerical example verifies that desirable accuracy of short term load forecasting can be achieved by using the SSTAR model.展开更多
文摘In this study,we examine the problem of sliced inverse regression(SIR),a widely used method for sufficient dimension reduction(SDR).It was designed to find reduced-dimensional versions of multivariate predictors by replacing them with a minimally adequate collection of their linear combinations without loss of information.Recently,regularization methods have been proposed in SIR to incorporate a sparse structure of predictors for better interpretability.However,existing methods consider convex relaxation to bypass the sparsity constraint,which may not lead to the best subset,and particularly tends to include irrelevant variables when predictors are correlated.In this study,we approach sparse SIR as a nonconvex optimization problem and directly tackle the sparsity constraint by establishing the optimal conditions and iteratively solving them by means of the splicing technique.Without employing convex relaxation on the sparsity constraint and the orthogonal constraint,our algorithm exhibits superior empirical merits,as evidenced by extensive numerical studies.Computationally,our algorithm is much faster than the relaxed approach for the natural sparse SIR estimator.Statistically,our algorithm surpasses existing methods in terms of accuracy for central subspace estimation and best subset selection and sustains high performance even with correlated predictors.
基金Supported by the National Natural Science Foundation of China,No.82300857.
文摘BACKGROUND Patients with acute-on-chronic liver failure(ACLF)experience severe immune dysfunction.Liver transplantation(LT)significantly improves survival outcomes.However,the characteristics of peripheral blood lymphocyte subsets(PBLSs)in this patient population are not well defined,and the dynamics of immune reconstitution post-LT are insufficiently understood.AIM To characterize PBLSs in patients with ACLF prior to LT and to evaluate PBLS reconstitution after LT.METHODS Clinical data from patients undergoing LT in the Transplantation Center,The Third Xiangya Hospital from January 2022 to December 2023 were analyzed retrospectively.Our cohort comprised 44 patients with ACLF,16 patients with acute decompensation of cirrhosis,and 23 patients with compensated cirrhosis.Twenty healthy volunteers were included as controls.PBLSs were evaluated across all groups.The relationship between PBLSs and post-LT prognosis was assessed,and dynamic changes in PBLSs among patients with ACLF were analyzed at different time points.RESULTS Patients with ACLF exhibited a marked reduction in PBLSs compared with healthy volunteers.Natural killer(NK)cell counts were further reduced in patients with ACLF when compared with patients with compensated cirrhosis.PBLSs did not correlate with the etiology or severity of ACLF or with established liver failure scores.Following LT,a rapid restoration of NK cells and B cells was observed in patients with ACLF.However,the cluster of differentiation(CD)3+T cell and CD4+T cell counts decreased 14 days post-LT and subsequently returned to preoperative levels by day 21.CONCLUSION Patients with ACLF exhibited markedly reduced PBLSs,with decreased NK cells potentially linked to progression from compensated cirrhosis to liver failure.NK and B cell were rapidly restored after LT.
基金supported by the National Social Science Fund of China(No.20CZX048)。
文摘In modal logic,topological semantics is an intuitive and natural special case of neighbourhood semantics.This paper stems from the observation that the satisfaction relation of topological semantics applies to subset spaces which are more general than topological spaces.The minimal modal logic which is strongly sound and complete with respect to the class of subset spaces is found.Soundness and completeness results of some famous modal logics(e.g.S4,S5 and Tr)with respect to various important classes of subset spaces(eg intersection structures and complete fields of sets)are also proved.In the meantime,some known results,e.g.the soundness and completeness of Tr with respect to the class of discrete topological spaces,are proved directly using some modifications of the method of canonical mode1,without a detour via neighbourhood semantics or relational semantics.
文摘The stratospheric airship is affected by harsh conditions in the stratosphere environment.To ensure the safety of the airship,it is necessary to detect the material state of the airship envelope.Since digital image correlation possesses non-contact strain measurement ability,this paper explores the infuence of different shapes of the subset on measurement accuracy.Through the results,it is found that increasing the aspect ratio of subsets can improve the strain accuracy measured in the c-direction,and reducing the aspect ratio can improve the strain accuracy measured in the y-direction.This trend becomes more obvious as the strain increases.Based on this discovery,a subset adaptive algorithm is proposed.The feasibility of the algorithm is verified by experiments,and the precision of strain measurement can be effectively improved by adjusting the threshold value.Therefore,the algorithm can be utilized to increase the measurement accuracy in the larger strain direction without changing the size of the subset.
文摘There are some limitations when we apply conventional methods to analyze the massive amounts of seismic data acquired with high-density spatial sampling since processors usually obtain the properties of raw data from common shot gathers or other datasets located at certain points or along lines. We propose a novel method in this paper to observe seismic data on time slices from spatial subsets. The composition of a spatial subset and the unique character of orthogonal or oblique subsets are described and pre-stack subsets are shown by 3D visualization. In seismic data processing, spatial subsets can be used for the following aspects： （1） to check the trace distribution uniformity and regularity; （2） to observe the main features of ground-roll and linear noise; （3） to find abnormal traces from slices of datasets; and （4） to QC the results of pre-stack noise attenuation. The field data application shows that seismic data analysis in spatial subsets is an effective method that may lead to a better discrimination among various wavefields and help us obtain more information.
基金The National Basic Research Program of China (973Program) (No.2003CB716102).
文摘A new method that uses a modified ordered subsets （MOS） algorithm to improve the convergence rate of space-alternating generalized expectation-maximization （SAGE） algorithm for positron emission tomography （PET） image reconstruction is proposed.In the MOS-SAGE algorithm,the number of projections and the access order of the subsets are modified in order to improve the quality of the reconstructed images and accelerate the convergence speed.The number of projections in a subset increases as follows：2,4,8,16,32 and 64.This sequence means that the high frequency component is recovered first and the low frequency component is recovered in the succeeding iteration steps.In addition,the neighboring subsets are separated as much as possible so that the correlation of projections can be decreased and the convergences can be speeded up.The application of the proposed method to simulated and real images shows that the MOS-SAGE algorithm has better performance than the SAGE algorithm and the OSEM algorithm in convergence and image quality.
文摘Objective: To study the expression of Fas and Bcl-2proteins on T lymphocyte subsets in the peripheralblood of relapsing patients with condyloma acuminatum(CA) and healthy controls. Methods: Flow cytometry (permeabization andstaining procedure with conjugated antibodies) wasused. Results: We observed that the expression of Fasprotein on CD4^+ T lymphocyte subset of CA patientswas significantly higher than that of healthy controls(P<0.01). Conclusions: Increased expression of Fas proteinon CD4^+ T lymphocyte subset may be a cause of de-creased percentage of CD4^+ T lymphocyte subset. Thisinduces the increased ratio of CD4^+/CD8^+.
文摘The subset threshold auto regressive (SSTAR) model, which is capable of reproducing the limit cycle behavior of nonlinear time series, is introduced. The algorithm for fitting the sampled data with SSTAR model is proposed and applied to model and forecast power load. Numerical example verifies that desirable accuracy of short term load forecasting can be achieved by using the SSTAR model.
