A novel adaptive subspace ensemble slow feature regression model was developed for soft sensing application.Compared to traditional single models and random subspace models,the proposed method is improved in three asp...A novel adaptive subspace ensemble slow feature regression model was developed for soft sensing application.Compared to traditional single models and random subspace models,the proposed method is improved in three aspects.Firstly,sub-datasets are constructed through slow feature directions and variables in each subdatasets are selected according to the output related importance index.Then,an adaptive slow feature regression is presented for sub-models.Finally,a Bayesian inference strategy based on a slow feature analysis process that monitors statistics is developed for probabilistic combination.Two industrial examples were used to evaluate the proposed method.展开更多
Kernel-based slow feature analysis(SFA)methods have been successfully applied in the industrial process fault detection field.However,kernel-based SFA methods have high computational complexity as dealing with nonline...Kernel-based slow feature analysis(SFA)methods have been successfully applied in the industrial process fault detection field.However,kernel-based SFA methods have high computational complexity as dealing with nonlinearity,leading to delays in detecting time-varying data features.Additionally,the uncertain kernel function and kernel parameters limit the ability of the extracted features to express process characteristics,resulting in poor fault detection performance.To alleviate the above problems,a novel randomized auto-regressive dynamic slow feature analysis(RRDSFA)method is proposed to simultaneously monitor the operating point deviations and process dynamic faults,enabling real-time monitoring of data features in industrial processes.Firstly,the proposed Random Fourier mappingbased method achieves more effective nonlinear transformation,contrasting with the current kernelbased RDSFA algorithm that may lead to significant computational complexity.Secondly,a randomized RDSFA model is developed to extract nonlinear dynamic slow features.Furthermore,a Bayesian inference-based overall fault monitoring model including all RRDSFA sub-models is developed to overcome the randomness of random Fourier mapping.Finally,the superiority and effectiveness of the proposed monitoring method are demonstrated through a numerical case and a simulation of continuous stirred tank reactor.展开更多
Two long-term slow slip events(SSEs) in Lower Cook Inlet, Alaska, were identified by Li SS et al.(2016). The earlier SSE lasted at least 9 years with M_(w) ~7.8 and had an average slip rate of ~82 mm/year. The latter ...Two long-term slow slip events(SSEs) in Lower Cook Inlet, Alaska, were identified by Li SS et al.(2016). The earlier SSE lasted at least 9 years with M_(w) ~7.8 and had an average slip rate of ~82 mm/year. The latter SSE, occurring in a similar area, lasted approximately 2 years with M_(w) ~7.2 and an average slip rate of ~91 mm/year. To test whether these SSEs triggered earthquakes near the slow slip area, we calculated the Coulomb stressing rate changes on receiver faults by using two fault geometry definitions: nodal planes of focal mechanism solutions of past earthquakes, and optimally oriented fault planes. Regions in the shallow slab(30–60 km) that experienced a significant increase in the Coulomb stressing rate due to slip by the SSEs showed an increase in seismicity rates during SSE periods. No correlation was found in the volumes that underwent a significant increase in the Coulomb stressing rate during the SSE within the crust and the intermediate slab. We modeled variations in seismicity rates by using a combination of the Coulomb stress transfer model and the framework of rate-and-state friction. Our model indicated that the SSEs increased the Coulomb stress changes on adjacent faults,thereby increasing the seismicity rates even though the ratio of the SSE stressing rate to the background stressing rate was small. Each long-term SSE in Alaska brought the megathrust updip of the SSE areas closer to failure by up to 0.1–0.15 MPa. The volumes of significant Coulomb stress changes caused by the Upper and Lower Cook Inlet SSEs did not overlap.展开更多
This paper studies the process of mutual neutralization of Si^＋ and H^- ions in slow collisions within the multichannel Landau-Zener model. All important ionic-covalent couplings in this collision system are included...This paper studies the process of mutual neutralization of Si^＋ and H^- ions in slow collisions within the multichannel Landau-Zener model. All important ionic-covalent couplings in this collision system are included in the collision dynamics. The cross sections for population of specific final states of product Si atom are calculated in the CM energy range 0.05 e∨/u-5 ke∨/u. Both singlet and triplet states are considered. At collision energies below -10 e∨/u, the most populated singlet state is Si（3p4p, ^1S0）, while for energies above -150e∨/u it is the Si（3p, 4p, ^1P1） state. In the case of triplet states, the mixed 3p4p（^3S1 ＋^3P0） states are the most populated in the entire collision energy range investigated. The total cross section exhibits a broad maximum around 200 300e∨/u and for ECM ≤ 10e∨/u it monotonically increases with decreasing the collision energy, reaching a value of 8 × 10^-13 cm^2 at ECM = 0.05 e∨/u. The ion-pair formation process in Si（3p^2 ^3PJ）＋H（1s） collisions has also been considered and its cross section in the considered energy range is very small （smaller than 10^-20 cm^2 in the energy region below 1 ke∨/u）.展开更多
The dynamics of soil organic carbon(SOC)was analyzed by using laboratory incubation and double exponential model that mineralizable SOC was separated into active carbon pools and slow carbon pools in forest soils deri...The dynamics of soil organic carbon(SOC)was analyzed by using laboratory incubation and double exponential model that mineralizable SOC was separated into active carbon pools and slow carbon pools in forest soils derived from Changbai and Qilian Mountain areas.By analyzing and fitting the CO2 evolved rates with SOC mineralization,the results showed that active carbon pools accounted tor 1.0%to 8.5%of SOC with an average of mean resistant times(MRTs)for 24 days,and slow carbon pools accounted for 91%to 99%of SOC with an average of MRTs for 179 years.The sizes and MRTs of slow carbon pools showed that SOC in Qilian Mountain sites was more difficult to decompose than that in Changbai Mountain sites.By analyzing the effects of temperature,soil clay content and elevation on SOC mineralization,results indicated that mineralization of SOC was directly related to temperature and that content of accumulated SOC and size of slow carbon pools from Changbai Mountain and Qilian Mountain sites increased linearly with increasing clay content,respectively,which showed temperature and clay content could make greater effect on mineralization of SOC.展开更多
Purpose: BupredermTM-Buprenorphine transdermal delivery system (BTDS) was developed for the treatment of post-operative and chronic pains. This study examined the relationship between the plasma concentration of bupre...Purpose: BupredermTM-Buprenorphine transdermal delivery system (BTDS) was developed for the treatment of post-operative and chronic pains. This study examined the relationship between the plasma concentration of buprenorphine and its analgesic effect (tail flick test) in order to assess the usefulness of pharmacokinetic-pharmacodynamic (PK-PD) modeling in describing this relationship. Methods: After patch application, plasma concentrations of bu- prenorphine in mice were measured for 72 hours with a validated LC/MS/MS system, and the analgesic effects were assessed by tail flick test for the period of 24 hours. A modified two- compartment open model was used to explain the PK properties of BTDS, and the PD model was characterized by slow receptor binding. Results: The peak buprenorphine level in plasma was achieved at 1-24 h and the effective therapeutic drug concentration was maintained for 72 hours. BupredermTM induced prolongation of tail-flick latency in a dose and time dependent manner. Maximum analgesic effect was attained at 3-6 h and was maintained for 24 h after patch application. Counter-clockwise hysteresis between the plasma concentration and the analgesic efficacy of BTDS was observed after BupredermTM application, indicating there was a delay between plasma concentrations and the effect observed. From the developed PK-PD model, Kd values (0.69-0.82 nM) that were derived from the pharmacodynamic parameters (Kon and Koff) are similar to the reported values (Kd = 0.76 ± 0.14 nM). Good agreement between the predicted and observed values was noted for the rate of change in analgesic effect data (R2 = 0.822, 0.852 and 0.774 for 0.24, 0.8 and 2.4 mg/patch, respectively). Conclusions: The established PK- PD model successfully described the relationship between plasma concentration of buprenorphine and its analgesic efficacy measured by the tail flick test. Our model might be useful in estimation and prediction of onset, magnitude and time course of concentration and pharmacological effects of BTDS and will be useful to simulate PK-PD profiles with clinical regimens.展开更多
The Shanghai Advanced Proton Therapy facility employs third-integer slow extraction. In order to achieve accurate treatment, high-quality spill is needed. Therefore,parameters that may affect slow extraction should be...The Shanghai Advanced Proton Therapy facility employs third-integer slow extraction. In order to achieve accurate treatment, high-quality spill is needed. Therefore,parameters that may affect slow extraction should be investigated by simulation. A computer model of the synchrotron operation slow extraction was constructed with MATLAB~. By simulating the motion of the circulating protons, we could quantify the influence of machine and initial beam parameters on properties of the extracted beam, such as ripple, uniformity, stability, on-and off-time of the spill and spill width in the synchrotron.Suitable design parameters including the horizontal tunes,power supply ripple, longitudinal RF cavity voltage, RFKO and the chromaticities were determined.展开更多
The similarities and differences in inherent mechanism and characteristic frequency between the onedimensional(1D)poroelastic model and the layered White model were investigated.This investigation was conducted under ...The similarities and differences in inherent mechanism and characteristic frequency between the onedimensional(1D)poroelastic model and the layered White model were investigated.This investigation was conducted under the assumption that the rock was homogenous and isotropic at the mesoscopic scale.For the inherent mechanism,both models resulted from quasi-static flow in a slow P-wave diffusion mode,and the differences between them originated from saturated fluids and boundary conditions.On the other hand,for the characteristic frequencies of the models,the characteristic frequency of the 1D poroelastic model was first modified because the elastic constant and formula for calculating it were misused and then compared to that of the layered White model.Both of them moved towards higher frequencies with increasing permeability and decreasing viscosity and diffusion length.The differences between them were due to the diffusion length.The diffusion length for the 1D poroelastic model was determined by the sample length,whereas that for the layered White model was determined by the length of the representative elementary volume(REV).Subsequently,a numerical example was presented to demonstrate the similarities and differences between the models.Finally,published experimental data were interpreted using the 1D poroelastic model combined with the Cole-Cole model.The prediction of the combined model was in good agreement with the experimental data,thereby validating the effectiveness of the 1D poroelastic model.Furthermore,the modified characteristic frequency in our study was much closer to the experimental data than the previous prediction,validating the effectiveness of our modification of the characteristic frequency of the 1D poroelastic model.The investigation provided insight into the internal relationship between wave-induced fluid flow(WIFF)models at macroscopic and mesoscopic scales and can aid in a better understanding of the elastic modulus dispersion and attenuation caused by the WIFF at different scales.展开更多
The effects of both the switching frequency and the leakage inductance on the slow-scale stability in a voltage controlled flyback converter are investigated in this paper. Firstly, the system description and its math...The effects of both the switching frequency and the leakage inductance on the slow-scale stability in a voltage controlled flyback converter are investigated in this paper. Firstly, the system description and its mathematical model are presented. Then, the improved averaged model, which covers both the switching frequency and the leakage inductance, is established, and the effects of these two parameters on the slow-scale stability in the system are analyzed. It is found that the occurrence of Hopf bifurcation in the system is the main reason for losing its slow-scale stability and both the switching frequency and the leakage inductance have an important effect on this slow-scale stability. Finally, the effectiveness of the improved averaged model and that of the corresponding theoretical analysis are confirmed by the simulation results and the experimental results.展开更多
In this paper we propose an Ising model on an infinite ladder lattice, which is made of two infinite Ising spin chains with interactions. It is essentially a quasi-one-dimessional Ising model because the length of the...In this paper we propose an Ising model on an infinite ladder lattice, which is made of two infinite Ising spin chains with interactions. It is essentially a quasi-one-dimessional Ising model because the length of the ladder lattice is infinite, while its width is finite. We investigate the phase transition and dynamic behavior of Ising model on this quasi-one-dimessional system. We use the generalized transfer matrix method to investigate the phase transition of the system. It is found that there is no nonzero temperature phase transition in this system. At the same time, we are interested in Glauber dynamics. Based on that, we obtain the time evolution of the local spin magnetization by exactly solving a set of master equations.展开更多
Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons...Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon as a slow leaky integrator, which captures almost all-known neural behaviors. The model controls the switching of axonal firing dynamics between passive conduction mode and persistent firing mode. The interplay between the axonal integrated potential and its multiple thresholds in axon precisely determines the persistent firing dynamics of neurons. We also present a persistent firing polychronous spiking network which exhibits asynchronous dynamics indicating that this computationally efficient model is not only bio-plausible, but also suitable for large scale spiking network simulations. The implications of this network and the analog circuit design for exploring the relationship between working memory and persistent firing enable developing a spiking network-based memory and bio-inspired computer systems.展开更多
基金the support from the National Natural Science Foundation of China(No.21676086).
文摘A novel adaptive subspace ensemble slow feature regression model was developed for soft sensing application.Compared to traditional single models and random subspace models,the proposed method is improved in three aspects.Firstly,sub-datasets are constructed through slow feature directions and variables in each subdatasets are selected according to the output related importance index.Then,an adaptive slow feature regression is presented for sub-models.Finally,a Bayesian inference strategy based on a slow feature analysis process that monitors statistics is developed for probabilistic combination.Two industrial examples were used to evaluate the proposed method.
基金supported by the Program of National Natural Science Foundation of China(U23A20329,62163036)Youth Academic and Technical Leaders Reserve Talent Training project(202105AC160094)Industrial Innovation Talent Special Project of Xingdian Talent Support Program(XDYC-CYCX-2022-0010).
文摘Kernel-based slow feature analysis(SFA)methods have been successfully applied in the industrial process fault detection field.However,kernel-based SFA methods have high computational complexity as dealing with nonlinearity,leading to delays in detecting time-varying data features.Additionally,the uncertain kernel function and kernel parameters limit the ability of the extracted features to express process characteristics,resulting in poor fault detection performance.To alleviate the above problems,a novel randomized auto-regressive dynamic slow feature analysis(RRDSFA)method is proposed to simultaneously monitor the operating point deviations and process dynamic faults,enabling real-time monitoring of data features in industrial processes.Firstly,the proposed Random Fourier mappingbased method achieves more effective nonlinear transformation,contrasting with the current kernelbased RDSFA algorithm that may lead to significant computational complexity.Secondly,a randomized RDSFA model is developed to extract nonlinear dynamic slow features.Furthermore,a Bayesian inference-based overall fault monitoring model including all RRDSFA sub-models is developed to overcome the randomness of random Fourier mapping.Finally,the superiority and effectiveness of the proposed monitoring method are demonstrated through a numerical case and a simulation of continuous stirred tank reactor.
基金supported by the National Natural Science Foundation of China (Grant No. 42104001)。
文摘Two long-term slow slip events(SSEs) in Lower Cook Inlet, Alaska, were identified by Li SS et al.(2016). The earlier SSE lasted at least 9 years with M_(w) ~7.8 and had an average slip rate of ~82 mm/year. The latter SSE, occurring in a similar area, lasted approximately 2 years with M_(w) ~7.2 and an average slip rate of ~91 mm/year. To test whether these SSEs triggered earthquakes near the slow slip area, we calculated the Coulomb stressing rate changes on receiver faults by using two fault geometry definitions: nodal planes of focal mechanism solutions of past earthquakes, and optimally oriented fault planes. Regions in the shallow slab(30–60 km) that experienced a significant increase in the Coulomb stressing rate due to slip by the SSEs showed an increase in seismicity rates during SSE periods. No correlation was found in the volumes that underwent a significant increase in the Coulomb stressing rate during the SSE within the crust and the intermediate slab. We modeled variations in seismicity rates by using a combination of the Coulomb stress transfer model and the framework of rate-and-state friction. Our model indicated that the SSEs increased the Coulomb stress changes on adjacent faults,thereby increasing the seismicity rates even though the ratio of the SSE stressing rate to the background stressing rate was small. Each long-term SSE in Alaska brought the megathrust updip of the SSE areas closer to failure by up to 0.1–0.15 MPa. The volumes of significant Coulomb stress changes caused by the Upper and Lower Cook Inlet SSEs did not overlap.
基金Project supported by the National Natural Science Foundation of China （Grant Nos 10574018 and 10574020）.
文摘This paper studies the process of mutual neutralization of Si^＋ and H^- ions in slow collisions within the multichannel Landau-Zener model. All important ionic-covalent couplings in this collision system are included in the collision dynamics. The cross sections for population of specific final states of product Si atom are calculated in the CM energy range 0.05 e∨/u-5 ke∨/u. Both singlet and triplet states are considered. At collision energies below -10 e∨/u, the most populated singlet state is Si（3p4p, ^1S0）, while for energies above -150e∨/u it is the Si（3p, 4p, ^1P1） state. In the case of triplet states, the mixed 3p4p（^3S1 ＋^3P0） states are the most populated in the entire collision energy range investigated. The total cross section exhibits a broad maximum around 200 300e∨/u and for ECM ≤ 10e∨/u it monotonically increases with decreasing the collision energy, reaching a value of 8 × 10^-13 cm^2 at ECM = 0.05 e∨/u. The ion-pair formation process in Si（3p^2 ^3PJ）＋H（1s） collisions has also been considered and its cross section in the considered energy range is very small （smaller than 10^-20 cm^2 in the energy region below 1 ke∨/u）.
基金The research was funded by National Natural Science Foundation(40231016)and Canadian International Development Agency(CIDA).
文摘The dynamics of soil organic carbon(SOC)was analyzed by using laboratory incubation and double exponential model that mineralizable SOC was separated into active carbon pools and slow carbon pools in forest soils derived from Changbai and Qilian Mountain areas.By analyzing and fitting the CO2 evolved rates with SOC mineralization,the results showed that active carbon pools accounted tor 1.0%to 8.5%of SOC with an average of mean resistant times(MRTs)for 24 days,and slow carbon pools accounted for 91%to 99%of SOC with an average of MRTs for 179 years.The sizes and MRTs of slow carbon pools showed that SOC in Qilian Mountain sites was more difficult to decompose than that in Changbai Mountain sites.By analyzing the effects of temperature,soil clay content and elevation on SOC mineralization,results indicated that mineralization of SOC was directly related to temperature and that content of accumulated SOC and size of slow carbon pools from Changbai Mountain and Qilian Mountain sites increased linearly with increasing clay content,respectively,which showed temperature and clay content could make greater effect on mineralization of SOC.
文摘Purpose: BupredermTM-Buprenorphine transdermal delivery system (BTDS) was developed for the treatment of post-operative and chronic pains. This study examined the relationship between the plasma concentration of buprenorphine and its analgesic effect (tail flick test) in order to assess the usefulness of pharmacokinetic-pharmacodynamic (PK-PD) modeling in describing this relationship. Methods: After patch application, plasma concentrations of bu- prenorphine in mice were measured for 72 hours with a validated LC/MS/MS system, and the analgesic effects were assessed by tail flick test for the period of 24 hours. A modified two- compartment open model was used to explain the PK properties of BTDS, and the PD model was characterized by slow receptor binding. Results: The peak buprenorphine level in plasma was achieved at 1-24 h and the effective therapeutic drug concentration was maintained for 72 hours. BupredermTM induced prolongation of tail-flick latency in a dose and time dependent manner. Maximum analgesic effect was attained at 3-6 h and was maintained for 24 h after patch application. Counter-clockwise hysteresis between the plasma concentration and the analgesic efficacy of BTDS was observed after BupredermTM application, indicating there was a delay between plasma concentrations and the effect observed. From the developed PK-PD model, Kd values (0.69-0.82 nM) that were derived from the pharmacodynamic parameters (Kon and Koff) are similar to the reported values (Kd = 0.76 ± 0.14 nM). Good agreement between the predicted and observed values was noted for the rate of change in analgesic effect data (R2 = 0.822, 0.852 and 0.774 for 0.24, 0.8 and 2.4 mg/patch, respectively). Conclusions: The established PK- PD model successfully described the relationship between plasma concentration of buprenorphine and its analgesic efficacy measured by the tail flick test. Our model might be useful in estimation and prediction of onset, magnitude and time course of concentration and pharmacological effects of BTDS and will be useful to simulate PK-PD profiles with clinical regimens.
基金supported by the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.20150210)
文摘The Shanghai Advanced Proton Therapy facility employs third-integer slow extraction. In order to achieve accurate treatment, high-quality spill is needed. Therefore,parameters that may affect slow extraction should be investigated by simulation. A computer model of the synchrotron operation slow extraction was constructed with MATLAB~. By simulating the motion of the circulating protons, we could quantify the influence of machine and initial beam parameters on properties of the extracted beam, such as ripple, uniformity, stability, on-and off-time of the spill and spill width in the synchrotron.Suitable design parameters including the horizontal tunes,power supply ripple, longitudinal RF cavity voltage, RFKO and the chromaticities were determined.
基金supported by the National Natural Science Foundation of China (42030810,42104115)。
文摘The similarities and differences in inherent mechanism and characteristic frequency between the onedimensional(1D)poroelastic model and the layered White model were investigated.This investigation was conducted under the assumption that the rock was homogenous and isotropic at the mesoscopic scale.For the inherent mechanism,both models resulted from quasi-static flow in a slow P-wave diffusion mode,and the differences between them originated from saturated fluids and boundary conditions.On the other hand,for the characteristic frequencies of the models,the characteristic frequency of the 1D poroelastic model was first modified because the elastic constant and formula for calculating it were misused and then compared to that of the layered White model.Both of them moved towards higher frequencies with increasing permeability and decreasing viscosity and diffusion length.The differences between them were due to the diffusion length.The diffusion length for the 1D poroelastic model was determined by the sample length,whereas that for the layered White model was determined by the length of the representative elementary volume(REV).Subsequently,a numerical example was presented to demonstrate the similarities and differences between the models.Finally,published experimental data were interpreted using the 1D poroelastic model combined with the Cole-Cole model.The prediction of the combined model was in good agreement with the experimental data,thereby validating the effectiveness of the 1D poroelastic model.Furthermore,the modified characteristic frequency in our study was much closer to the experimental data than the previous prediction,validating the effectiveness of our modification of the characteristic frequency of the 1D poroelastic model.The investigation provided insight into the internal relationship between wave-induced fluid flow(WIFF)models at macroscopic and mesoscopic scales and can aid in a better understanding of the elastic modulus dispersion and attenuation caused by the WIFF at different scales.
基金Project supported by the National Natural Science Foundation of China(Grant No.51007068)the Specialized Research Fund for the Doctoral Program of Higher Education,China(Grant No.20100201120028)+2 种基金the Natural Science Basic Research Plan in Shaanxi Province,China(Grant No.2012JQ7026)the Fundamental Research Funds for the Central Universities,China(Grant No.2012jdgz09)the Fund from the State Key Laboratory of Electrical Insulation and Power Equipment,China(Grant No.EIPE12303)
文摘The effects of both the switching frequency and the leakage inductance on the slow-scale stability in a voltage controlled flyback converter are investigated in this paper. Firstly, the system description and its mathematical model are presented. Then, the improved averaged model, which covers both the switching frequency and the leakage inductance, is established, and the effects of these two parameters on the slow-scale stability in the system are analyzed. It is found that the occurrence of Hopf bifurcation in the system is the main reason for losing its slow-scale stability and both the switching frequency and the leakage inductance have an important effect on this slow-scale stability. Finally, the effectiveness of the improved averaged model and that of the corresponding theoretical analysis are confirmed by the simulation results and the experimental results.
文摘In this paper we propose an Ising model on an infinite ladder lattice, which is made of two infinite Ising spin chains with interactions. It is essentially a quasi-one-dimessional Ising model because the length of the ladder lattice is infinite, while its width is finite. We investigate the phase transition and dynamic behavior of Ising model on this quasi-one-dimessional system. We use the generalized transfer matrix method to investigate the phase transition of the system. It is found that there is no nonzero temperature phase transition in this system. At the same time, we are interested in Glauber dynamics. Based on that, we obtain the time evolution of the local spin magnetization by exactly solving a set of master equations.
文摘Neurons are believed to be the brain computational engines of the brain. A recent discovery in neurophysiology reveals that interneurons can slowly integrate spiking, share the output across a coupled network of axons and respond with persistent firing even in the absence of input to the soma or dendrites, which has not been understood and could be very important for exploring the mechanism of human cognition. The conventional models are incapable of simulating the important newly-discovered phenomenon of persistent firing induced by axonal slow integration. In this paper, we propose a computationally efficient model of neurons through modeling the axon as a slow leaky integrator, which captures almost all-known neural behaviors. The model controls the switching of axonal firing dynamics between passive conduction mode and persistent firing mode. The interplay between the axonal integrated potential and its multiple thresholds in axon precisely determines the persistent firing dynamics of neurons. We also present a persistent firing polychronous spiking network which exhibits asynchronous dynamics indicating that this computationally efficient model is not only bio-plausible, but also suitable for large scale spiking network simulations. The implications of this network and the analog circuit design for exploring the relationship between working memory and persistent firing enable developing a spiking network-based memory and bio-inspired computer systems.
