Chronic migraine(CM)is a prevalent and highly debilitating neurological disorder.Functional magnetic resonance imaging(fMRI)studies have demonstrated associations between abnormal brain region activation and CM,yet th...Chronic migraine(CM)is a prevalent and highly debilitating neurological disorder.Functional magnetic resonance imaging(fMRI)studies have demonstrated associations between abnormal brain region activation and CM,yet the underlying complex neural circuitry mechanisms remain unclear.The spinal trigeminal nucleus caudalis(Sp5C)serves as the primary central hub for orofacial nociceptive input,receiving trigeminal pain signals and projecting to higher-order centers such as the thalamus.Therefore,we sought to investigate whether the Sp5C region and its associated circuits were involved in CM pathogenesis.In this study,we established a CM mouse model through repeated intraperitoneal injections of nitroglycerin(NTG).Using a combination of in vivo fiber photometry and in vitro c-Fos immunohistochemistry,we found a marked periorbital and plantar mechanical allodynia in CM mice,accompanied by increased glutamatergic neuronal activity in Sp5C.Chemogenetic manipulation of Sp5C glutamatergic neurons(Sp5CV^(glut2))bidirectionally modulated migraine-like behaviors and induced pain-related affective states,as evidenced by conditioned place preference/aversion(CPP/CPA)paradigms.Anterograde viral tracing revealed dense projections from Sp5C^(Vglut2)to the subthalamic nucleus(STN),which was activated in CM mice.Optogenetic activation of the Sp5C-STN pathway similarly produced migraine-like behaviors and pain-related aversive memory in mice.Altogether,we revealed a critical role of the Sp5CVglut2-STN circuit in the development and modulation of CM.Our findings provide novel mechanistic insights into the central mechanisms underlying CM,establishing potential theoretical foundations for clinical diagnosis and therapeutic development.展开更多
After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the tim...After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the timing of interventions,combined with the limitations of current methods.To address these challenges,various techniques have been developed to aid in the repair and reconstruction of neural circuits at different stages of injury.Notably,neuromodulation has garnered considerable attention for its potential to enhance nerve regeneration,provide neuroprotection,restore neurons,and regulate the neural reorganization of circuits within the cerebral cortex and corticospinal tract.To improve the effectiveness of these interventions,the implementation of multitarget early interventional neuromodulation strategies,such as electrical and magnetic stimulation,is recommended to enhance functional recovery across different phases of nerve injury.This review concisely outlines the challenges encountered following spinal cord injury,synthesizes existing neurostimulation techniques while emphasizing neuroprotection,repair,and regeneration of impaired connections,and advocates for multi-targeted,task-oriented,and timely interventions.展开更多
Replicating the chaotic characteristics inherent in nonlinear dynamical systems via machine learning(ML)is a key challenge in this rapidly advancing interdisciplinary field.In this work,we explore the potential of var...Replicating the chaotic characteristics inherent in nonlinear dynamical systems via machine learning(ML)is a key challenge in this rapidly advancing interdisciplinary field.In this work,we explore the potential of variational quantum circuits(VQC)for learning the stochastic properties of classical nonlinear dynamical systems.Specifically,we focus on the one-and two-dimensional logistic maps,which,while simple,remain under-explored in the context of learning dynamical characteristics.Our findings reveal that,even for such simple dynamical systems,accurately replicating longterm characteristics is hindered by a pronounced sensitivity to overfitting.While increasing the parameter complexity of the ML model typically enhances short-term prediction accuracy,it also leads to a degradation in the model’s ability to replicate long-term characteristics,primarily due to the detrimental effects of overfitting on generalization power.By comparing the VQC with two widely recognized classical ML techniques,which are long short-term memory(LSTM)networks for timeseries processing and reservoir computing,we demonstrate that VQC outperforms these methods in terms of replicating long-term characteristics.Our results suggest that for the ML of dynamics,it is demanded to develop more compact and efficient models(such as VQC)rather than more complicated and large-scale ones.展开更多
The output voltages for the capacitive elements of a neural circuit model can be mapped into dimensionless capacitive variables,which present firing patterns similar to the membrane potentials detected in biological n...The output voltages for the capacitive elements of a neural circuit model can be mapped into dimensionless capacitive variables,which present firing patterns similar to the membrane potentials detected in biological neurons.The inclusion of a memcapacitor also en‐ables consideration of membrane deformation effects,enhancing the model’s capacity to simulate neuronal behavior across varying physio‐logical and environmental conditions.In this study,a capacitor and a memcapacitor are connected through a linear resistor in parallel with other electric components in different branch circuits composed of an inductor and a nonlinear resistor.The electrical activities in a neuron with a double-layer membrane and two capacitive variables are discussed in detail after converting the nonlinear equations for the neural circuit into a theoretical neuron model.A dimensionless neuron model and its corresponding energy function are derived.The field energy function for the neural circuit is converted into an equivalent Hamilton energy function and further validated via the Helmholtz theorem.Furthermore,the average value of energy serves as an indicator for predicting stochastic resonance,as supported by analyzing the distribu‐tion of the coefficient of variation.The neuronal firing patterns are shown to be energy-dependent.An adaptive control strategy is proposed to regulate mode transitions in electrical activities of the neuron.An analog equivalent circuit is constructed to experimentally verify the nu‐merical results,thereby supporting the reliability of the proposed neuron model.展开更多
Point-of-care diagnostics and inline quantitative phase imaging(QPI)drive the demand for portable,ultra-miniaturized,and robust optical imaging and metrology systems.We propose and demonstrate a wavefront sensor integ...Point-of-care diagnostics and inline quantitative phase imaging(QPI)drive the demand for portable,ultra-miniaturized,and robust optical imaging and metrology systems.We propose and demonstrate a wavefront sensor integrated into a photonic integrated circuit,enabling single-shot optical phase retrieval.We implemented an integrated wavefront sensor array with a spatial resolution of 17μm and a numerical aperture of 0.1.Furthermore,we experimentally demonstrated the reconstruction of wavefronts defined by Zernike polynomials,specifically the first 14 terms(Z_(1)to Z_(14)),achieving an average root mean square error below 0.07.This advancement paves the way for fully integrated,portable,and robust optical imaging systems,facilitating integrated wavefront sensors in demanding applications such as point-of-care diagnostics,endoscopy,in situ QPI,and inline surface profile measurement.展开更多
The modeling and dynamical analysis of discrete chaotic systems is a vital research field,and various chaotic maps have been developed using mathematical and control-theoretic approaches.However,physical circuit desig...The modeling and dynamical analysis of discrete chaotic systems is a vital research field,and various chaotic maps have been developed using mathematical and control-theoretic approaches.However,physical circuit design of mathematically defined discrete chaotic systems and the computation of their energy functions remain challenging and open problems.In this study,a two-dimensional(2D)chaotic map is constructed using an open-loop modulation coupling method,and its dynamical characteristics are analyzed using bifurcation diagrams.Lyapunov exponents(LEs)and spectral entropy(SE)complexity are also inspected under different parameter configurations.Furthermore,the proposed chaotic map is expressed using two distinct physical memristive circuits:one is composed of a magnetic flux-controlled memristor,a nonlinear resistor,and a capacitor;the other utilizes a charge-controlled memristor,a nonlinear resistor,and an inductor.Moreover,two energy functions are derived from the two memristor-coupled circuits for the proposed chaotic map.The results demonstrate that the mathematical model of the discrete chaotic system can be effectively expressed through these two nonlinear circuits.Our study offers a theoretical foundation and viable methodology for the physical circuit representation of discrete chaotic systems and determination of their energy functions.展开更多
Epilepsy,a common neurological disorder,is characterized by recurrent seizures that can lead to cognitive,psychological,and neurobiological consequences.The pathogenesis of epilepsy involves neuronal dysfunction at th...Epilepsy,a common neurological disorder,is characterized by recurrent seizures that can lead to cognitive,psychological,and neurobiological consequences.The pathogenesis of epilepsy involves neuronal dysfunction at the molecular,cellular,and neural circuit levels.Abnormal molecular signaling pathways or dysfunction of specific cell types can lead to epilepsy by disrupting the normal functioning of neural circuits.The continuous emergence of new technologies and the rapid advancement of existing ones have facilitated the discovery and comprehensive understanding of the neural circuit mechanisms underlying epilepsy.Therefore,this review aims to investigate the current understanding of the neural circuit mechanisms in epilepsy based on various technologies,including electroencephalography,magnetic resonance imaging,optogenetics,chemogenetics,deep brain stimulation,and brain-computer interfaces.Additionally,this review discusses these mechanisms from three perspectives:structural,synaptic,and transmitter circuits.The findings reveal that the neural circuit mechanisms of epilepsy encompass information transmission among different structures,interactions within the same structure,and the maintenance of homeostasis at the cellular,synaptic,and neurotransmitter levels.These findings offer new insights for investigating the pathophysiological mechanisms of epilepsy and enhancing its clinical diagnosis and treatment.展开更多
Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after inju...Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after injury,which limits the ability to observe long-term behavioral recovery.Here,we used a severe stroke rat model with 150 minutes of ischemia,which produced severe behavioral deficiencies that persisted at 12 weeks,to study the therapeutic effect of neural stem cells on neural restoration in chronic stroke.Our study showed that stroke model rats treated with human neural stem cells had long-term sustained recovery of motor function,reduced infarction volume,long-term human neural stem cell survival,and improved local inflammatory environment and angiogenesis.We also demonstrated that transplanted human neural stem cells differentiated into mature neurons in vivo,formed stable functional synaptic connections with host neurons,and exhibited the electrophysiological properties of functional mature neurons,indicating that they replaced the damaged host neurons.The findings showed that human fetal-derived neural stem cells had long-term effects for neurological recovery in a model of severe stroke,which suggests that human neural stem cells-based therapy may be effective for repairing damaged neural circuits in stroke patients.展开更多
To address the issues of high costs and low component utilization caused by the independent configuration of hybrid DC circuit breakers(HCBs)and DC power flow controllers(DCPFCs)at each port in existing DC distributio...To address the issues of high costs and low component utilization caused by the independent configuration of hybrid DC circuit breakers(HCBs)and DC power flow controllers(DCPFCs)at each port in existing DC distribution networks,this paper adopts a component sharing mechanism to propose a composite multi-port hybrid DC circuit breaker(CM-HCB)with DC power flow and fault current limitation abilities,as well as reduced component costs.The proposed CM-HCB topology enables the sharing of the main breaker branch(MB)and the energy dissipation branch,while the load commutation switches(LCSs)in the main branch are reused as power flow control components,enabling flexible regulation of power flow in multiple lines.Meanwhile,by reconstructing the current path during the fault process,the proposed CM-HCB can utilize the internal coupled inductor to limit the current rise rate at the initial stage of the fault,significantly reducing the requirement for breaking current.A detailed study on the topological structure,steady-state power flow regulation mechanism,transient fault isolation mechanism,control strategy and characteristic analysis of the proposed CM-HCB is presented.Then,a Matlab/Simulink-based meshed three-terminal DC grid simulation platform with the proposed CM-HCB is built.The results indicate that the proposed CM-HCB can not only achieve flexible power flow control during steady-state operation,but also obtain current rise limitation and fault isolation abilities under short-circuit fault conditions,verifying its correctness and effectiveness.Finally,a comparative economic analysis is conducted between the proposed CM-HCB and the other two existing solutions,confirming that its component sharing mechanism can significantly reduce the number of components,lower system costs,and improve component utilization.展开更多
针对具有非最小相位特性的单电感双输出Buck-Boost变换器(SIDO Buck-Boost)输出两支路存在严重的交叉影响、控制困难以及系统暂态性能差等问题,提出一种基于扩张状态观测器(extended state observer,ESO)的主路微分平坦控制(differentia...针对具有非最小相位特性的单电感双输出Buck-Boost变换器(SIDO Buck-Boost)输出两支路存在严重的交叉影响、控制困难以及系统暂态性能差等问题,提出一种基于扩张状态观测器(extended state observer,ESO)的主路微分平坦控制(differential flatness based control,DFBC)和支路改进双闭环自抗扰控制(active disturbance rejection controller,ADRC)的控制策略.首先,根据主路微分平坦理论,在主路控制中设计微分平坦控制器,并对微分平坦系统进行误差反馈;设计ESO对主路的扰动项进行观测,将观测后的状态量反馈到微分平坦控制器中.其次,针对支路存在耦合以及右半平面零点的问题,设计改进型双闭环ADRC进行系统解耦,其中,电流内环选取基于模型补偿和前馈补偿的ADRC,电压外环选取普通ADRC,然后,利用Lyapunov理论证明系统的稳定性.最后,在Matlab/Simulink平台中搭建了仿真模型,并基于HIL搭建了实验平台.仿真及实验结果表明:所提控制策略减小了输出两支路之间的交叉影响,解决了非最小相位系统控制困难的问题,提高了系统的暂态响应性能.展开更多
Depressive disorder is a chronic,recurring,and potentially life-endangering neuropsychiatric disease.According to a report by the World Health Organization,the global population suffering from depression is experienci...Depressive disorder is a chronic,recurring,and potentially life-endangering neuropsychiatric disease.According to a report by the World Health Organization,the global population suffering from depression is experiencing a significant annual increase.Despite its prevalence and considerable impact on people,little is known about its pathogenesis.One major reason is the scarcity of reliable animal models due to the absence of consensus on the pathology and etiology of depression.Furthermore,the neural circuit mechanism of depression induced by various factors is particularly complex.Considering the variability in depressive behavior patterns and neurobiological mechanisms among different animal models of depression,a comparison between the neural circuits of depression induced by various factors is essential for its treatment.In this review,we mainly summarize the most widely used behavioral animal models and neural circuits under different triggers of depression,aiming to provide a theoretical basis for depression prevention.展开更多
基金supported by the National Natural Science Foundation of China(No.32571336 and 32271048)Research Funds of Centre for Leading Medicine and Advanced Technologies of IHM(No.2025IHM01100)。
文摘Chronic migraine(CM)is a prevalent and highly debilitating neurological disorder.Functional magnetic resonance imaging(fMRI)studies have demonstrated associations between abnormal brain region activation and CM,yet the underlying complex neural circuitry mechanisms remain unclear.The spinal trigeminal nucleus caudalis(Sp5C)serves as the primary central hub for orofacial nociceptive input,receiving trigeminal pain signals and projecting to higher-order centers such as the thalamus.Therefore,we sought to investigate whether the Sp5C region and its associated circuits were involved in CM pathogenesis.In this study,we established a CM mouse model through repeated intraperitoneal injections of nitroglycerin(NTG).Using a combination of in vivo fiber photometry and in vitro c-Fos immunohistochemistry,we found a marked periorbital and plantar mechanical allodynia in CM mice,accompanied by increased glutamatergic neuronal activity in Sp5C.Chemogenetic manipulation of Sp5C glutamatergic neurons(Sp5CV^(glut2))bidirectionally modulated migraine-like behaviors and induced pain-related affective states,as evidenced by conditioned place preference/aversion(CPP/CPA)paradigms.Anterograde viral tracing revealed dense projections from Sp5C^(Vglut2)to the subthalamic nucleus(STN),which was activated in CM mice.Optogenetic activation of the Sp5C-STN pathway similarly produced migraine-like behaviors and pain-related aversive memory in mice.Altogether,we revealed a critical role of the Sp5CVglut2-STN circuit in the development and modulation of CM.Our findings provide novel mechanistic insights into the central mechanisms underlying CM,establishing potential theoretical foundations for clinical diagnosis and therapeutic development.
基金supported by the National Key Research and Development Program of China,No.2023YFC3603705(to DX)the National Natural Science Foundation of China,No.82302866(to YZ).
文摘After spinal cord injury,impairment of the sensorimotor circuit can lead to dysfunction in the motor,sensory,proprioceptive,and autonomic nervous systems.Functional recovery is often hindered by constraints on the timing of interventions,combined with the limitations of current methods.To address these challenges,various techniques have been developed to aid in the repair and reconstruction of neural circuits at different stages of injury.Notably,neuromodulation has garnered considerable attention for its potential to enhance nerve regeneration,provide neuroprotection,restore neurons,and regulate the neural reorganization of circuits within the cerebral cortex and corticospinal tract.To improve the effectiveness of these interventions,the implementation of multitarget early interventional neuromodulation strategies,such as electrical and magnetic stimulation,is recommended to enhance functional recovery across different phases of nerve injury.This review concisely outlines the challenges encountered following spinal cord injury,synthesizes existing neurostimulation techniques while emphasizing neuroprotection,repair,and regeneration of impaired connections,and advocates for multi-targeted,task-oriented,and timely interventions.
基金Project supported in part by Beijing Natural Science Foundation(Grant No.1232025)Peng Huanwu Visiting Pro-fessor Program,and Academy for Multidisciplinary Studies,Capital Normal University.
文摘Replicating the chaotic characteristics inherent in nonlinear dynamical systems via machine learning(ML)is a key challenge in this rapidly advancing interdisciplinary field.In this work,we explore the potential of variational quantum circuits(VQC)for learning the stochastic properties of classical nonlinear dynamical systems.Specifically,we focus on the one-and two-dimensional logistic maps,which,while simple,remain under-explored in the context of learning dynamical characteristics.Our findings reveal that,even for such simple dynamical systems,accurately replicating longterm characteristics is hindered by a pronounced sensitivity to overfitting.While increasing the parameter complexity of the ML model typically enhances short-term prediction accuracy,it also leads to a degradation in the model’s ability to replicate long-term characteristics,primarily due to the detrimental effects of overfitting on generalization power.By comparing the VQC with two widely recognized classical ML techniques,which are long short-term memory(LSTM)networks for timeseries processing and reservoir computing,we demonstrate that VQC outperforms these methods in terms of replicating long-term characteristics.Our results suggest that for the ML of dynamics,it is demanded to develop more compact and efficient models(such as VQC)rather than more complicated and large-scale ones.
基金supported by the National Natural Science Foundation of China(No.12072139).
文摘The output voltages for the capacitive elements of a neural circuit model can be mapped into dimensionless capacitive variables,which present firing patterns similar to the membrane potentials detected in biological neurons.The inclusion of a memcapacitor also en‐ables consideration of membrane deformation effects,enhancing the model’s capacity to simulate neuronal behavior across varying physio‐logical and environmental conditions.In this study,a capacitor and a memcapacitor are connected through a linear resistor in parallel with other electric components in different branch circuits composed of an inductor and a nonlinear resistor.The electrical activities in a neuron with a double-layer membrane and two capacitive variables are discussed in detail after converting the nonlinear equations for the neural circuit into a theoretical neuron model.A dimensionless neuron model and its corresponding energy function are derived.The field energy function for the neural circuit is converted into an equivalent Hamilton energy function and further validated via the Helmholtz theorem.Furthermore,the average value of energy serves as an indicator for predicting stochastic resonance,as supported by analyzing the distribu‐tion of the coefficient of variation.The neuronal firing patterns are shown to be energy-dependent.An adaptive control strategy is proposed to regulate mode transitions in electrical activities of the neuron.An analog equivalent circuit is constructed to experimentally verify the nu‐merical results,thereby supporting the reliability of the proposed neuron model.
基金supported by the National Natural Science Foundation of China(Grant Nos.52175509 and 52450158)the National Key Research and Development Program of China(Grant No.2023YFF1500900)+2 种基金the Shenzhen Fundamental Research Program(Grant No.JCYJ20220818100412027)the Guangdong-Hong Kong Technology Cooperation Funding Scheme Category C Platform(Grant No.SGDX20230116093543005)the Innovation Project of Optics Valley Laboratory(Grant No.OVL2023PY003)。
文摘Point-of-care diagnostics and inline quantitative phase imaging(QPI)drive the demand for portable,ultra-miniaturized,and robust optical imaging and metrology systems.We propose and demonstrate a wavefront sensor integrated into a photonic integrated circuit,enabling single-shot optical phase retrieval.We implemented an integrated wavefront sensor array with a spatial resolution of 17μm and a numerical aperture of 0.1.Furthermore,we experimentally demonstrated the reconstruction of wavefronts defined by Zernike polynomials,specifically the first 14 terms(Z_(1)to Z_(14)),achieving an average root mean square error below 0.07.This advancement paves the way for fully integrated,portable,and robust optical imaging systems,facilitating integrated wavefront sensors in demanding applications such as point-of-care diagnostics,endoscopy,in situ QPI,and inline surface profile measurement.
基金supported by the National Natural Science Foundation of China(No.62301416).
文摘The modeling and dynamical analysis of discrete chaotic systems is a vital research field,and various chaotic maps have been developed using mathematical and control-theoretic approaches.However,physical circuit design of mathematically defined discrete chaotic systems and the computation of their energy functions remain challenging and open problems.In this study,a two-dimensional(2D)chaotic map is constructed using an open-loop modulation coupling method,and its dynamical characteristics are analyzed using bifurcation diagrams.Lyapunov exponents(LEs)and spectral entropy(SE)complexity are also inspected under different parameter configurations.Furthermore,the proposed chaotic map is expressed using two distinct physical memristive circuits:one is composed of a magnetic flux-controlled memristor,a nonlinear resistor,and a capacitor;the other utilizes a charge-controlled memristor,a nonlinear resistor,and an inductor.Moreover,two energy functions are derived from the two memristor-coupled circuits for the proposed chaotic map.The results demonstrate that the mathematical model of the discrete chaotic system can be effectively expressed through these two nonlinear circuits.Our study offers a theoretical foundation and viable methodology for the physical circuit representation of discrete chaotic systems and determination of their energy functions.
基金supported by Basic Research Programs of Science and Technology Commission Foundation of Shanxi Province,No.20210302123486(to WJ).
文摘Epilepsy,a common neurological disorder,is characterized by recurrent seizures that can lead to cognitive,psychological,and neurobiological consequences.The pathogenesis of epilepsy involves neuronal dysfunction at the molecular,cellular,and neural circuit levels.Abnormal molecular signaling pathways or dysfunction of specific cell types can lead to epilepsy by disrupting the normal functioning of neural circuits.The continuous emergence of new technologies and the rapid advancement of existing ones have facilitated the discovery and comprehensive understanding of the neural circuit mechanisms underlying epilepsy.Therefore,this review aims to investigate the current understanding of the neural circuit mechanisms in epilepsy based on various technologies,including electroencephalography,magnetic resonance imaging,optogenetics,chemogenetics,deep brain stimulation,and brain-computer interfaces.Additionally,this review discusses these mechanisms from three perspectives:structural,synaptic,and transmitter circuits.The findings reveal that the neural circuit mechanisms of epilepsy encompass information transmission among different structures,interactions within the same structure,and the maintenance of homeostasis at the cellular,synaptic,and neurotransmitter levels.These findings offer new insights for investigating the pathophysiological mechanisms of epilepsy and enhancing its clinical diagnosis and treatment.
文摘Exogenous neural stem cell transplantation has become one of the most promising treatment methods for chronic stroke.Recent studies have shown that most ischemia-reperfusion model rats recover spontaneously after injury,which limits the ability to observe long-term behavioral recovery.Here,we used a severe stroke rat model with 150 minutes of ischemia,which produced severe behavioral deficiencies that persisted at 12 weeks,to study the therapeutic effect of neural stem cells on neural restoration in chronic stroke.Our study showed that stroke model rats treated with human neural stem cells had long-term sustained recovery of motor function,reduced infarction volume,long-term human neural stem cell survival,and improved local inflammatory environment and angiogenesis.We also demonstrated that transplanted human neural stem cells differentiated into mature neurons in vivo,formed stable functional synaptic connections with host neurons,and exhibited the electrophysiological properties of functional mature neurons,indicating that they replaced the damaged host neurons.The findings showed that human fetal-derived neural stem cells had long-term effects for neurological recovery in a model of severe stroke,which suggests that human neural stem cells-based therapy may be effective for repairing damaged neural circuits in stroke patients.
基金funded by Youth Talent Growth Project of Guizhou Provincial Department of Education(No.Qianjiaoji[2024]21)National Natural Science Foundation of China(No.62461008 and No.52507211)Guizhou Provincial Key Technology R&D Program(No.[2024]General 049).
文摘To address the issues of high costs and low component utilization caused by the independent configuration of hybrid DC circuit breakers(HCBs)and DC power flow controllers(DCPFCs)at each port in existing DC distribution networks,this paper adopts a component sharing mechanism to propose a composite multi-port hybrid DC circuit breaker(CM-HCB)with DC power flow and fault current limitation abilities,as well as reduced component costs.The proposed CM-HCB topology enables the sharing of the main breaker branch(MB)and the energy dissipation branch,while the load commutation switches(LCSs)in the main branch are reused as power flow control components,enabling flexible regulation of power flow in multiple lines.Meanwhile,by reconstructing the current path during the fault process,the proposed CM-HCB can utilize the internal coupled inductor to limit the current rise rate at the initial stage of the fault,significantly reducing the requirement for breaking current.A detailed study on the topological structure,steady-state power flow regulation mechanism,transient fault isolation mechanism,control strategy and characteristic analysis of the proposed CM-HCB is presented.Then,a Matlab/Simulink-based meshed three-terminal DC grid simulation platform with the proposed CM-HCB is built.The results indicate that the proposed CM-HCB can not only achieve flexible power flow control during steady-state operation,but also obtain current rise limitation and fault isolation abilities under short-circuit fault conditions,verifying its correctness and effectiveness.Finally,a comparative economic analysis is conducted between the proposed CM-HCB and the other two existing solutions,confirming that its component sharing mechanism can significantly reduce the number of components,lower system costs,and improve component utilization.
文摘针对具有非最小相位特性的单电感双输出Buck-Boost变换器(SIDO Buck-Boost)输出两支路存在严重的交叉影响、控制困难以及系统暂态性能差等问题,提出一种基于扩张状态观测器(extended state observer,ESO)的主路微分平坦控制(differential flatness based control,DFBC)和支路改进双闭环自抗扰控制(active disturbance rejection controller,ADRC)的控制策略.首先,根据主路微分平坦理论,在主路控制中设计微分平坦控制器,并对微分平坦系统进行误差反馈;设计ESO对主路的扰动项进行观测,将观测后的状态量反馈到微分平坦控制器中.其次,针对支路存在耦合以及右半平面零点的问题,设计改进型双闭环ADRC进行系统解耦,其中,电流内环选取基于模型补偿和前馈补偿的ADRC,电压外环选取普通ADRC,然后,利用Lyapunov理论证明系统的稳定性.最后,在Matlab/Simulink平台中搭建了仿真模型,并基于HIL搭建了实验平台.仿真及实验结果表明:所提控制策略减小了输出两支路之间的交叉影响,解决了非最小相位系统控制困难的问题,提高了系统的暂态响应性能.
基金supported by the Brain&Behavior Research Foundation(30233).
文摘Depressive disorder is a chronic,recurring,and potentially life-endangering neuropsychiatric disease.According to a report by the World Health Organization,the global population suffering from depression is experiencing a significant annual increase.Despite its prevalence and considerable impact on people,little is known about its pathogenesis.One major reason is the scarcity of reliable animal models due to the absence of consensus on the pathology and etiology of depression.Furthermore,the neural circuit mechanism of depression induced by various factors is particularly complex.Considering the variability in depressive behavior patterns and neurobiological mechanisms among different animal models of depression,a comparison between the neural circuits of depression induced by various factors is essential for its treatment.In this review,we mainly summarize the most widely used behavioral animal models and neural circuits under different triggers of depression,aiming to provide a theoretical basis for depression prevention.
