Fluorescence microscopy enables the visualization of cellular morphology,molecular distribution,ion distribution,and their dynamic behaviors during biological processes.Enhancing the signal-to-noise ratio(SNR)in fluor...Fluorescence microscopy enables the visualization of cellular morphology,molecular distribution,ion distribution,and their dynamic behaviors during biological processes.Enhancing the signal-to-noise ratio(SNR)in fluorescence imaging improves the quantification accuracy and spatial resolution;however,achieving high SNR at fast image acquisition rates,which is often required to observe cellular dynamics,still remains a challenge.In this study,we developed a technique to rapidly freeze biological cells in milliseconds during optical microscopy observation.Compared to chemical fixation,rapid freezing provides rapid immobilization of samples while more effectively preserving the morphology and conditions of cells.This technique combines the advantages of both live-cell and cryofixation microscopy,i.e.,temporal dynamics and high SNR snapshots of selected moments,and is demonstrated by fluorescence and Raman microscopy with high spatial resolution and quantification under low temperature conditions.Furthermore,we also demonstrated that intracellular calcium dynamics can be frozen rapidly and visualized using fluorescent ion indicators,suggesting that ion distribution and conformation of the probe molecules can be fixed both spatially and temporally.These results confirmed that our technique can time-deterministically suspend and visualize cellular dynamics while preserving molecular and ionic states,indicating the potential to provide detailed insights into sample dynamics with improved spatial resolution and temporal accuracy in observations.展开更多
In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its s...In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.展开更多
The M?ller algorithm is a self-stabilizing minor component analysis algorithm.This research document involves the study of the convergence and dynamic characteristics of the M?ller algorithm using the deterministic di...The M?ller algorithm is a self-stabilizing minor component analysis algorithm.This research document involves the study of the convergence and dynamic characteristics of the M?ller algorithm using the deterministic discrete time(DDT)methodology.Unlike other analysis methodologies,the DDT methodology is capable of serving the distinct time characteristic and having no constraint conditions.Through analyzing the dynamic characteristics of the weight vector,several convergence conditions are drawn,which are beneficial for its application.The performing computer simulations and real applications demonstrate the correctness of the analysis’s conclusions.展开更多
基金supported by JST-CREST and JST COI-NEXT program under Grant number JPMJCR1925 and JPMJPF2009supported by JST SPRING under Grant number JPMJSP2138,Deutsche Forschungsgemeinschaft SFB1278(TP C04)+1 种基金the Leibniz Association(Leibniz Science Campus,InfectoOptics,HotAim 2.0)supported by Janelia Research Campus,Howard Hughes Medical Institute.
文摘Fluorescence microscopy enables the visualization of cellular morphology,molecular distribution,ion distribution,and their dynamic behaviors during biological processes.Enhancing the signal-to-noise ratio(SNR)in fluorescence imaging improves the quantification accuracy and spatial resolution;however,achieving high SNR at fast image acquisition rates,which is often required to observe cellular dynamics,still remains a challenge.In this study,we developed a technique to rapidly freeze biological cells in milliseconds during optical microscopy observation.Compared to chemical fixation,rapid freezing provides rapid immobilization of samples while more effectively preserving the morphology and conditions of cells.This technique combines the advantages of both live-cell and cryofixation microscopy,i.e.,temporal dynamics and high SNR snapshots of selected moments,and is demonstrated by fluorescence and Raman microscopy with high spatial resolution and quantification under low temperature conditions.Furthermore,we also demonstrated that intracellular calcium dynamics can be frozen rapidly and visualized using fluorescent ion indicators,suggesting that ion distribution and conformation of the probe molecules can be fixed both spatially and temporally.These results confirmed that our technique can time-deterministically suspend and visualize cellular dynamics while preserving molecular and ionic states,indicating the potential to provide detailed insights into sample dynamics with improved spatial resolution and temporal accuracy in observations.
基金This project is supported by Key Science-Technology Project of Shanghai City Tenth Five-Year-Plan, China (No.031111002)Specialized Research Fund for the Doctoral Program of Higher Education, China (No.20040247033)Municipal Key Basic Research Program of Shanghai, China (No.05JC14060)
文摘In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.
基金supported by the National Natural Science Foundation of China(61903375,61673387,61374120)Shaanxi Province Natural Science Foundation(2016JM6015)。
文摘The M?ller algorithm is a self-stabilizing minor component analysis algorithm.This research document involves the study of the convergence and dynamic characteristics of the M?ller algorithm using the deterministic discrete time(DDT)methodology.Unlike other analysis methodologies,the DDT methodology is capable of serving the distinct time characteristic and having no constraint conditions.Through analyzing the dynamic characteristics of the weight vector,several convergence conditions are drawn,which are beneficial for its application.The performing computer simulations and real applications demonstrate the correctness of the analysis’s conclusions.
