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
Loss of synapse and functional connectivity in brain circuits is associated with aging and neurodegeneration,however,few molecular mechanisms are known to intrinsically promote synaptogenesis or enhance synapse functi...Loss of synapse and functional connectivity in brain circuits is associated with aging and neurodegeneration,however,few molecular mechanisms are known to intrinsically promote synaptogenesis or enhance synapse function.We have previously shown that MET receptor tyrosine kinase in the developing cortical circuits promotes dendritic growth and dendritic spine morphogenesis.To investigate whether enhancing MET in adult cortex has synapse regenerating potential,we created a knockin mouse line,in which the human MET gene expression and signaling can be turned on in adult(10–12 months)cortical neurons through doxycycline-containing chow.We found that similar to the developing brain,turning on MET signaling in the adult cortex activates small GTPases and increases spine density in prefrontal projection neurons.These findings are further corroborated by increased synaptic activity and transient generation of immature silent synapses.Prolonged MET signaling resulted in an increasedα-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/N-methyl-Daspartate(AMPA/NMDA)receptor current ratio,indicative of enhanced synaptic function and connectivity.Our data reveal that enhancing MET signaling could be an interventional approach to promote synaptogenesis and preserve functional connectivity in the adult brain.These findings may have implications for regenerative therapy in aging and neurodegeneration conditions.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
The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language proc...The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language processing,image recognition,and real-time decisionmaking.However,these models demand immense computational power and are often centralized,relying on cloud-based architectures with inherent limitations in latency,privacy,and energy efficiency.To address these challenges and bring AI closer to real-world applications,such as wearable health monitoring,robotics,and immersive virtual environments,innovative hardware solutions are urgently needed.This work introduces a near-sensor edge computing(NSEC)system,built on a bilayer AlN/Si waveguide platform,to provide real-time,energy-efficient AI capabilities at the edge.Leveraging the electro-optic properties of AlN microring resonators for photonic feature extraction,coupled with Si-based thermo-optic Mach-Zehnder interferometers for neural network computations,the system represents a transformative approach to AI hardware design.Demonstrated through multimodal gesture and gait analysis,the NSEC system achieves high classification accuracies of 96.77%for gestures and 98.31%for gaits,ultra-low latency(<10 ns),and minimal energy consumption(<0.34 pJ).This groundbreaking system bridges the gap between AI models and real-world applications,enabling efficient,privacy-preserving AI solutions for healthcare,robotics,and next-generation human-machine interfaces,marking a pivotal advancement in edge computing and AI deployment.展开更多
为了改善Buck-Boost矩阵变换器(Buck-Boost Matrix Converter,BBMC)逆变的电能质量和解决抗干扰性能不足的问题,提出一种改进线性自抗扰控制技术(Linear Active Disturbance Rejection Control,LADRC),并将其应用于电压外环控制策略中....为了改善Buck-Boost矩阵变换器(Buck-Boost Matrix Converter,BBMC)逆变的电能质量和解决抗干扰性能不足的问题,提出一种改进线性自抗扰控制技术(Linear Active Disturbance Rejection Control,LADRC),并将其应用于电压外环控制策略中.该控制技术在线性扩张状态观测器(Linear Expanded State Observer,LESO)中引入了电容电压微分与观测值的偏差信号,提高了观测精度,为了进一步提高系统动态性能,在线性状态误差反馈控制律(Linear State Error Feedback,LSEF)中引入模糊自适应系数.利用MATLAB/Simulink仿真试验平台分别对文中所提及策略的稳态和动态性能采用对照试验方法,仿真结果表明:无论是从稳态运行还是从系统参考信号和负载突变时的动态响应速度,文中改进型LADRC控制效果均显著优于传统LADRC控制器.展开更多
In this paper,we propose an RLC equivalent circuit model theory which can accurately predict the spectral response and resonance characteristics of metamaterial absorption structures,extend its design,and characterize...In this paper,we propose an RLC equivalent circuit model theory which can accurately predict the spectral response and resonance characteristics of metamaterial absorption structures,extend its design,and characterize the parameters of the model in detail.By employing this model,we conducted computations to characterize the response wavelength and bandwidth of variously sized metamaterial absorbers.A comparative analysis with Finite Difference Time Domain(FDTD)simulations demonstrated a remarkable level of consistency in the results.The designed absorbers were fabricated using micro-nano fabrication processes,and were experimentally tested to demonstrate absorption rates exceeding 90%at a wavelength of 9.28μm.The predicted results are then compared with test results.The comparison reveals good consistency in two aspects of the resonance responses,thereby confirming the rationality and accuracy of this model.展开更多
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 NIH/NIMH grant R01MH111619(to SQ),R21AG078700(to SQ)Institute of Mental Health Research(IMHR,Level 1 funding,to SQ and DF)institution startup fund from The University of Arizona(to SQ)。
文摘Loss of synapse and functional connectivity in brain circuits is associated with aging and neurodegeneration,however,few molecular mechanisms are known to intrinsically promote synaptogenesis or enhance synapse function.We have previously shown that MET receptor tyrosine kinase in the developing cortical circuits promotes dendritic growth and dendritic spine morphogenesis.To investigate whether enhancing MET in adult cortex has synapse regenerating potential,we created a knockin mouse line,in which the human MET gene expression and signaling can be turned on in adult(10–12 months)cortical neurons through doxycycline-containing chow.We found that similar to the developing brain,turning on MET signaling in the adult cortex activates small GTPases and increases spine density in prefrontal projection neurons.These findings are further corroborated by increased synaptic activity and transient generation of immature silent synapses.Prolonged MET signaling resulted in an increasedα-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid/N-methyl-Daspartate(AMPA/NMDA)receptor current ratio,indicative of enhanced synaptic function and connectivity.Our data reveal that enhancing MET signaling could be an interventional approach to promote synaptogenesis and preserve functional connectivity in the adult brain.These findings may have implications for regenerative therapy in aging and neurodegeneration conditions.
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.
基金the National Research Foundation(NRF)Singapore mid-sized center grant(NRF-MSG-2023-0002)FrontierCRP grant(NRF-F-CRP-2024-0006)+2 种基金A*STAR Singapore MTC RIE2025 project(M24W1NS005)IAF-PP project(M23M5a0069)Ministry of Education(MOE)Singapore Tier 2 project(MOE-T2EP50220-0014).
文摘The rise of large-scale artificial intelligence(AI)models,such as ChatGPT,Deep-Seek,and autonomous vehicle systems,has significantly advanced the boundaries of AI,enabling highly complex tasks in natural language processing,image recognition,and real-time decisionmaking.However,these models demand immense computational power and are often centralized,relying on cloud-based architectures with inherent limitations in latency,privacy,and energy efficiency.To address these challenges and bring AI closer to real-world applications,such as wearable health monitoring,robotics,and immersive virtual environments,innovative hardware solutions are urgently needed.This work introduces a near-sensor edge computing(NSEC)system,built on a bilayer AlN/Si waveguide platform,to provide real-time,energy-efficient AI capabilities at the edge.Leveraging the electro-optic properties of AlN microring resonators for photonic feature extraction,coupled with Si-based thermo-optic Mach-Zehnder interferometers for neural network computations,the system represents a transformative approach to AI hardware design.Demonstrated through multimodal gesture and gait analysis,the NSEC system achieves high classification accuracies of 96.77%for gestures and 98.31%for gaits,ultra-low latency(<10 ns),and minimal energy consumption(<0.34 pJ).This groundbreaking system bridges the gap between AI models and real-world applications,enabling efficient,privacy-preserving AI solutions for healthcare,robotics,and next-generation human-machine interfaces,marking a pivotal advancement in edge computing and AI deployment.
文摘为了改善Buck-Boost矩阵变换器(Buck-Boost Matrix Converter,BBMC)逆变的电能质量和解决抗干扰性能不足的问题,提出一种改进线性自抗扰控制技术(Linear Active Disturbance Rejection Control,LADRC),并将其应用于电压外环控制策略中.该控制技术在线性扩张状态观测器(Linear Expanded State Observer,LESO)中引入了电容电压微分与观测值的偏差信号,提高了观测精度,为了进一步提高系统动态性能,在线性状态误差反馈控制律(Linear State Error Feedback,LSEF)中引入模糊自适应系数.利用MATLAB/Simulink仿真试验平台分别对文中所提及策略的稳态和动态性能采用对照试验方法,仿真结果表明:无论是从稳态运行还是从系统参考信号和负载突变时的动态响应速度,文中改进型LADRC控制效果均显著优于传统LADRC控制器.
基金Supported by the National Natural Science Foundation of China(62174092)the Open Fund of State Key Laboratory of Infrared Physics(SITP-NLIST-ZD-2023-04)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0580000)。
文摘In this paper,we propose an RLC equivalent circuit model theory which can accurately predict the spectral response and resonance characteristics of metamaterial absorption structures,extend its design,and characterize the parameters of the model in detail.By employing this model,we conducted computations to characterize the response wavelength and bandwidth of variously sized metamaterial absorbers.A comparative analysis with Finite Difference Time Domain(FDTD)simulations demonstrated a remarkable level of consistency in the results.The designed absorbers were fabricated using micro-nano fabrication processes,and were experimentally tested to demonstrate absorption rates exceeding 90%at a wavelength of 9.28μm.The predicted results are then compared with test results.The comparison reveals good consistency in two aspects of the resonance responses,thereby confirming the rationality and accuracy of this model.
