In this paper, we propose a new soft multi-phase segmentation model where it is assumed that the pixel intensities are distributed as a Gaussian mixture. The model is formulated as a minimization problem through the u...In this paper, we propose a new soft multi-phase segmentation model where it is assumed that the pixel intensities are distributed as a Gaussian mixture. The model is formulated as a minimization problem through the use of the maximum likelihood estimator and phase-transition theory. The mixture coefficients, which are estimated using a spatially varying mean and variance procedure, are used for image segmentation. The experimental results indicate the effectiveness of the method.展开更多
Sesbania rostrata,an annual tropical legume,has been found to be tolerant to heavy metals,with an unknown mechanism.It is a promising candidate species for revegetation at mine tailings.In this study,sequential extrac...Sesbania rostrata,an annual tropical legume,has been found to be tolerant to heavy metals,with an unknown mechanism.It is a promising candidate species for revegetation at mine tailings.In this study,sequential extractions with five buffers and strong acids were used to extract various chemical forms of cadmium and copper in S.rostrata,with or without Cd or Cu treatments,so that the mechanisms of tolerance and detoxification could be inferred.Both metals had low transition rates from roots to the aboveground of S.rostrata.The transition ratio of Cd(4.00%)was higher than that of Cu(1.46%).The proportion of NaCl extracted Cd(mostly in proteinbinding forms)increased drastically in Cd treated plants from being undetectable in untreated plants.This suggests that Cd induced biochemical processes producing proteinlike phytochelatins that served as a major mechanism for the high Cd tolerance of S.rostrata.The case for Cu was quite different,indicating that the mechanism for metal tolerance in S.rostrata is metal-specific.The proportion of water-insoluble Cu(e.g.oxalate and phosphate)in roots increased significantly with Cu treatment,which partially explains the tolerance of S.rostrata to Cu.However,how S.rostrata copes with the high biotic activity of inorganic salts of Cu,which increased in all parts of the plant under Cu stress,is a question for future studies.Sesbania rostrata is among the very few N-fixing plants tolerant to heavy metals.This study provides evidence for the detoxification mechanism of metals in Sesbania rostrata.展开更多
Forecasting 3-dimensional skeleton-based human poses from the historical sequence is a classic task,which shows enormous potential in robotics,computer vision,and graphics.Currently,the state-of-theart methods resort ...Forecasting 3-dimensional skeleton-based human poses from the historical sequence is a classic task,which shows enormous potential in robotics,computer vision,and graphics.Currently,the state-of-theart methods resort to graph convolutional networks(GCNs)to access the relationships of human joint pairs to formulate this problem.However,human action involves complex interactions among multiple joints,which presents a higher-order correlation overstepping the pairwise(2-order)connection of GCNs.Moreover,joints are typically activated by the parent joint,rather than driving their parent joints,whereas in existing methods,this specific direction of information transmission is ignored.In this work,we propose a novel hybrid directed hypergraph convolution network(H-DHGCN)to model the high-order relationships of the human skeleton with directionality.Specifically,our H-DHGCN mainly involves 2 core components.One is the static directed hypergraph,which is pre-defined according to the human body structure,to effectively leverage the natural relations of human joints.The second is dynamic directed hypergraph(D-DHG).D-DHG is learnable and can be constructed adaptively,to learn the unique characteristics of the motion sequence.In contrast to the typical GCNs,our method brings a richer and more refined topological representation of skeleton data.On several large-scale benchmarks,experimental results show that the proposed model consistently surpasses the latest techniques.展开更多
文摘In this paper, we propose a new soft multi-phase segmentation model where it is assumed that the pixel intensities are distributed as a Gaussian mixture. The model is formulated as a minimization problem through the use of the maximum likelihood estimator and phase-transition theory. The mixture coefficients, which are estimated using a spatially varying mean and variance procedure, are used for image segmentation. The experimental results indicate the effectiveness of the method.
基金This research project was funded by the National Natural Science Foundation of China(Grant No.30070126)the Science Foundation of Guangdong Province(No.980293).
文摘Sesbania rostrata,an annual tropical legume,has been found to be tolerant to heavy metals,with an unknown mechanism.It is a promising candidate species for revegetation at mine tailings.In this study,sequential extractions with five buffers and strong acids were used to extract various chemical forms of cadmium and copper in S.rostrata,with or without Cd or Cu treatments,so that the mechanisms of tolerance and detoxification could be inferred.Both metals had low transition rates from roots to the aboveground of S.rostrata.The transition ratio of Cd(4.00%)was higher than that of Cu(1.46%).The proportion of NaCl extracted Cd(mostly in proteinbinding forms)increased drastically in Cd treated plants from being undetectable in untreated plants.This suggests that Cd induced biochemical processes producing proteinlike phytochelatins that served as a major mechanism for the high Cd tolerance of S.rostrata.The case for Cu was quite different,indicating that the mechanism for metal tolerance in S.rostrata is metal-specific.The proportion of water-insoluble Cu(e.g.oxalate and phosphate)in roots increased significantly with Cu treatment,which partially explains the tolerance of S.rostrata to Cu.However,how S.rostrata copes with the high biotic activity of inorganic salts of Cu,which increased in all parts of the plant under Cu stress,is a question for future studies.Sesbania rostrata is among the very few N-fixing plants tolerant to heavy metals.This study provides evidence for the detoxification mechanism of metals in Sesbania rostrata.
基金supported in part by the National Natural Science Foundation of China(62306141)in part by the Jiangsu Funding Program for Excellent Postdoctoral Talent(2022ZB269)+2 种基金in part by the Natural Science Foundation of Jiangsu Province(BK20220939)in part by the China Postdoctoral Science Foundation(2022M721629)in part by Research Project of University Natural Science Fund of Jiangsu Province(22KJB520002).
文摘Forecasting 3-dimensional skeleton-based human poses from the historical sequence is a classic task,which shows enormous potential in robotics,computer vision,and graphics.Currently,the state-of-theart methods resort to graph convolutional networks(GCNs)to access the relationships of human joint pairs to formulate this problem.However,human action involves complex interactions among multiple joints,which presents a higher-order correlation overstepping the pairwise(2-order)connection of GCNs.Moreover,joints are typically activated by the parent joint,rather than driving their parent joints,whereas in existing methods,this specific direction of information transmission is ignored.In this work,we propose a novel hybrid directed hypergraph convolution network(H-DHGCN)to model the high-order relationships of the human skeleton with directionality.Specifically,our H-DHGCN mainly involves 2 core components.One is the static directed hypergraph,which is pre-defined according to the human body structure,to effectively leverage the natural relations of human joints.The second is dynamic directed hypergraph(D-DHG).D-DHG is learnable and can be constructed adaptively,to learn the unique characteristics of the motion sequence.In contrast to the typical GCNs,our method brings a richer and more refined topological representation of skeleton data.On several large-scale benchmarks,experimental results show that the proposed model consistently surpasses the latest techniques.
