Mechanically durable transparent electrodes are essential for achieving long-term stability in flexible optoelectronic devices.Furthermore,they are crucial for applications in the fields of energy,display,healthcare,a...Mechanically durable transparent electrodes are essential for achieving long-term stability in flexible optoelectronic devices.Furthermore,they are crucial for applications in the fields of energy,display,healthcare,and soft robotics.Conducting meshes represent a promising alternative to traditional,brittle,metal oxide conductors due to their high electrical conductivity,optical transparency,and enhanced mechanical flexibility.In this paper,we present a simple method for fabricating an ultra-transparent conducting metal oxide mesh electrode using selfcracking-assisted templates.Using this method,we produced an electrode with ultra-transparency(97.39%),high conductance(Rs=21.24Ωsq^(−1)),elevated work function(5.16 eV),and good mechanical stability.We also evaluated the effectiveness of the fabricated electrodes by integrating them into organic photovoltaics,organic light-emitting diodes,and flexible transparent memristor devices for neuromorphic computing,resulting in exceptional device performance.In addition,the unique porous structure of the vanadium-doped indium zinc oxide mesh electrodes provided excellent flexibility,rendering them a promising option for application in flexible optoelectronics.展开更多
Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devi...Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.展开更多
This paper deals with a semilinear parabolic problem involving variable coefficients and nonlinear memory boundary conditions.We give the blow-up criteria for all nonnegative nontrivial solutions,which rely on the beh...This paper deals with a semilinear parabolic problem involving variable coefficients and nonlinear memory boundary conditions.We give the blow-up criteria for all nonnegative nontrivial solutions,which rely on the behavior of the coefficients when time variable tends to positive infinity.Moreover,the global existence of solutions are discussed for non-positive exponents.展开更多
Aging is an inevitable biological phenomenon that involves a multitude of physiological alterations.Dietary interventions are being considered as potential strategies for delaying age-related dysfunction.Unsaponifiabl...Aging is an inevitable biological phenomenon that involves a multitude of physiological alterations.Dietary interventions are being considered as potential strategies for delaying age-related dysfunction.Unsaponifiable matter(USM),a composition of highly active ingredients found in walnut oil,has demonstrated antioxidant effects.This study aims to explore the neuroprotective effects of USM on d-galactose-treated C57BL/6 mice and elucidate its underlying mechanism,which was validated in PC12 cells treated with d-galactose.The results of behavioral tests demonstrated that USM significantly improved cognitive deficits associated with aging.The morphological analysis demonstrated that USM effectively alleviated hippocampal neuronal damage,synaptic impairment,and mitochondrial dysfunction induced by d-galactose.Furthermore,USM significantly increases the antioxidant enzymes activity while reducing the malondialdehyde and reactive oxygen species levels.The results suggest that USM can mitigate age-related symptoms caused by d-galactose by activating the nuclear factor erythroid-2-related factor 2 signaling pathway,which enhances the expression of antioxidant enzymes,restore redox balance,and improves synaptic and mitochondrial functions.This has a positive on improving cognition and memory disorders in elderly mice.展开更多
This paper proposes a concurrent neural network model to mitigate non-linear distortion in power amplifiers using a basis function generation approach.The model is designed using polynomial expansion and comprises a f...This paper proposes a concurrent neural network model to mitigate non-linear distortion in power amplifiers using a basis function generation approach.The model is designed using polynomial expansion and comprises a feedforward neural network(FNN)and a convolutional neural network(CNN).The proposed model takes the basic elements that form the bases as input,defined by the generalized memory polynomial(GMP)and dynamic deviation reduction(DDR)models.The FNN generates the basis function and its output represents the basis values,while the CNN generates weights for the corresponding bases.Through the concurrent training of FNN and CNN,the hidden layer coefficients are updated,and the complex multiplication of their outputs yields the trained in-phase/quadrature(I/Q)signals.The proposed model was trained and tested using 300 MHz and 400 MHz broadband data in an orthogonal frequency division multiplexing(OFDM)communication system.The results show that the model achieves an adjacent channel power ratio(ACPR)of less than-48 d B within a 100 MHz integral bandwidth for both the training and test datasets.展开更多
In this work,we propose a comprehensive theoretical framework for the multilevel NAND(NOT AND logic)flash memory,built upon the modified Student’s t distribution where the distortion of the threshold voltage caused b...In this work,we propose a comprehensive theoretical framework for the multilevel NAND(NOT AND logic)flash memory,built upon the modified Student’s t distribution where the distortion of the threshold voltage caused by the random telegraph noise,cell-to-cell interference and data retention noise are jointly considered.Based on the superposition modulation,we build a non-orthogonal multiuser communication model where a linear mapping is conducted between the verify voltages and binary antipodal symbols.Aimed at improving the storage efficiency,we propose an unequal amplitude mapping(UAM)solution by optimizing the weighting coefficients of verify voltages to intelligently adjust the width of each state.Moreover,the uniform storage efficiency region and sum storage efficiency of different labelings with various decoding schemes are discussed.Simulation results validate the effectiveness of our proposed UAM solution where an up to 20.9%storage efficiency gain can be achieved compared to the current used benchmark scheme.In addition,analytical and simulation results also demonstrate that the successive cancellation decoding outperforms other decoding schemes for all labelings.展开更多
Background:Episodic memory loss is a prominent clinical manifestation of Alzheimer’s disease(AD),which is closely related to tau pathology and hippocampal impairment.Due to the heterogeneity of brain neurons,the spec...Background:Episodic memory loss is a prominent clinical manifestation of Alzheimer’s disease(AD),which is closely related to tau pathology and hippocampal impairment.Due to the heterogeneity of brain neurons,the specific roles of different brain neurons in terms of their sensitivity to tau accumulation and their contribution to AD-like social memory loss remain unclear.Therefore,further investigation is necessary.Methods:We investigated the effects of AD-like tau pathology by Tandem mass tag proteomic and phosphoproteomic analysis,social behavioural tests,hippocampal electrophysiology,immunofluorescence staining and in vivo optical fibre recording of GCaMP6f and iGABASnFR.Additionally,we utilized optogenetics and administered ursolic acid(UA)via oral gavage to examine the effects of these agents on social memory in mice.Results:The results of proteomic and phosphoproteomic analyses revealed the characteristics of ventral hippocampal CA1(vCA1)under both physiological conditions and AD-like tau pathology.As tau progressively accumulated,vCA1,especially its excitatory and parvalbumin(PV)neurons,were fully filled with mislocated and phosphorylated tau(p-Tau).This finding was not observed for dorsal hippocampal CA1(dCA1).The overexpression of human tau(hTau)in excitatory and PV neurons mimicked AD-like tau accumulation,significantly inhibited neuronal excitability and suppressed distinct discrimination-associated firings of these neurons within vCA1.Photoactivating excitatory and PV neurons in vCA1 at specific rhythms and time windows efficiently ameliorated tau-impaired social memory.Notably,1 month of UA administration efficiently decreased tau accumulation via autophagy in a transcription factor EB(TFEB)-dependent manner and restored the vCA1 microcircuit to ameliorate tau-impaired social memory.Conclusion:This study elucidated distinct protein and phosphoprotein networks between dCA1 and vCA1 and highlighted the susceptibility of the vCA1 microcircuit to AD-like tau accumulation.Notably,our novel findings regarding the efficacy of UA in reducing tau load and targeting the vCA1 microcircuit may provide a promising strategy for treating AD in the future.展开更多
Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex asso...Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex associative learning behaviors is still nascent.Here,an optoelec-tronic memristor based on Ag/TiO_(2) Nanowires:ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors.Effective implementation of synaptic behaviors,including long and short-term plasticity,and learning-forgetting-relearning behaviors,were achieved in the device through the application of light and electrical stimuli.Leveraging the optoelectronic co-modulated characteristics,a simulation of neuromorphic computing was conducted,resulting in a handwriting digit recognition accuracy of 88.9%.Furthermore,a 3×7 memristor array was constructed,confirming its application in artificial visual memory.Most importantly,complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli,respectively.After training through associative pairs,reflexes could be triggered solely using light stimuli.Comprehen-sively,under specific optoelectronic signal applications,the four features of classical conditioning,namely acquisition,extinction,recovery,and generalization,were elegantly emulated.This work provides an optoelectronic memristor with associative behavior capabilities,offering a pathway for advancing brain-machine interfaces,autonomous robots,and machine self-learning in the future.展开更多
It is still challenging to fully integrate computing in memory chip as edge learning devices.In recent work published on Science,a fully-integrated chip based on neuromorphic memristors was developed for edge learning...It is still challenging to fully integrate computing in memory chip as edge learning devices.In recent work published on Science,a fully-integrated chip based on neuromorphic memristors was developed for edge learning as artificial neural networks with functionality of synapses,dendrites,and somas.A crossbar-array memristor chip facilitated edge learning including hardware realization,learning algorithm,and cycle-parallel sign-and threshold-based learning(STELLAR)scheme.The motion control and demonstration platforms were executed to improve the edge learning ability for adapting to new scenarios.展开更多
Ferroelectrics have great potential in the field of nonvolatile memory due to programmable polarization states by external electric field in nonvolatile manner.However,complementary metal oxide semiconductor compatibi...Ferroelectrics have great potential in the field of nonvolatile memory due to programmable polarization states by external electric field in nonvolatile manner.However,complementary metal oxide semiconductor compatibility and uniformity of ferroelectric performance after size scaling have always been two thorny issues hindering practical application of ferroelectric memory devices.The emerging ferroelectricity of wurtzite structure nitride offers opportunities to circumvent the dilemma.This review covers the mechanism of ferroelectricity and domain dynamics in ferroelectric AlScN films.The performance optimization of AlScN films grown by different techniques is summarized and their applications for memories and emerging in-memory computing are illustrated.Finally,the challenges and perspectives regarding the commercial avenue of ferroelectric AlScN are discussed.展开更多
Two-dimensional(2D)transition metal dichalcogenides(TMDs)allow for atomic-scale manipulation,challenging the conventional limitations of semiconductor materials.This capability may overcome the short-channel effect,sp...Two-dimensional(2D)transition metal dichalcogenides(TMDs)allow for atomic-scale manipulation,challenging the conventional limitations of semiconductor materials.This capability may overcome the short-channel effect,sparking significant advancements in electronic devices that utilize 2D TMDs.Exploring the dimension and performance limits of transistors based on 2D TMDs has gained substantial importance.This review provides a comprehensive investigation into these limits of the single 2D-TMD transistor.It delves into the impacts of miniaturization,including the reduction of channel length,gate length,source/drain contact length,and dielectric thickness on transistor operation and performance.In addition,this review provides a detailed analysis of performance parameters such as source/drain contact resistance,subthreshold swing,hysteresis loop,carrier mobility,on/off ratio,and the development of p-type and single logic transistors.This review details the two logical expressions of the single 2D-TMD logic transistor,including current and voltage.It also emphasizes the role of 2D TMD-based transistors as memory devices,focusing on enhancing memory operation speed,endurance,data retention,and extinction ratio,as well as reducing energy consumption in memory devices functioning as artificial synapses.This review demonstrates the two calculating methods for dynamic energy consumption of 2D synaptic devices.This review not only summarizes the current state of the art in this field but also highlights potential future research directions and applications.It underscores the anticipated challenges,opportunities,and potential solutions in navigating the dimension and performance boundaries of 2D transistors.展开更多
Charge trapping devices incorporating 2D materials and high-κdielectrics have emerged as promising candidates for compact,multifunctional memory devices compatible with silicon-based manufacturing processes.However,t...Charge trapping devices incorporating 2D materials and high-κdielectrics have emerged as promising candidates for compact,multifunctional memory devices compatible with silicon-based manufacturing processes.However,traditional charge trapping devices encounter bottlenecks including complex device structure and low operation speed.Here,we demonstrate an ultrafast reconfigurable direct charge trapping device utilizing only a 30 nm-thick Al_(2)O_(3)trapping layer with a MoS_(2)channel,where charge traps reside within the Al_(2)O_(3)bulk confirmed by transfer curves with different gatevoltage sweeping rates and photoluminescence(PL)spectra.The direct charging tapping device shows exceptional memory performance in both three-terminal and two-terminal operation modes characterized by ultrafast three-terminal operation speed(~300 ns),an extremely low OFF current of 10^(-14)A,a high ON/OFF current ratio of up to 10^(7),and stable retention and endurance properties.Furthermore,the device with a simple symmetrical structure exhibits VDpolarity-dependent reverse rectification behavior in the high resistance state(HRS),with a rectification ratio of 10^(5).Additionally,utilizing the synergistic modulation of the conductance of the MoS_(2)channel by V_(D)and V_(G),it achieves gate-tunable reverse rectifier and ternary logic capabilities.展开更多
Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimen...Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.展开更多
Skyrmions, with their vortex-like structures and inherent topological protection, play a pivotal role in developing innovative low-power memory and logic devices. The efficient generation and control of skyrmions in g...Skyrmions, with their vortex-like structures and inherent topological protection, play a pivotal role in developing innovative low-power memory and logic devices. The efficient generation and control of skyrmions in geometrically confined systems are crucial for the development of skyrmion-based spintronic devices. In this study, we focus on investigating the non-reciprocal transport behavior of skyrmions and their interactions with boundaries of various shapes. The shape of the notch structure in the nanotrack significantly affects the dynamic behavior of magnetic skyrmions. Through micromagnetic simulation, the non-reciprocal transport properties of skyrmions in nanowires with different notch structures are investigated in this work.展开更多
In energy-dispersive X-ray fluorescence spectroscopy,the estimation of the pulse amplitude determines the accuracy of the spectrum measurement.The error generated by the amplitude estimation of the pulse output distor...In energy-dispersive X-ray fluorescence spectroscopy,the estimation of the pulse amplitude determines the accuracy of the spectrum measurement.The error generated by the amplitude estimation of the pulse output distorted by the measurement system leads to false peaks in the measured spectrum.To eliminate these false peaks and achieve an accurate estimation of the distorted pulse amplitude,a composite neural network model is proposed,which embeds long and short-term memory(LSTM)into the UNet structure.The UNet network realizes the fusion of pulse sequence features and the LSTM model realizes pulse amplitude estimation.The model is trained using simulated pulse datasets with different amplitudes and distortion times.For the pulse height estimation,the average relative error of the trained model on the test set was approximately 0.64%,which is 27.37% lower than that of the traditional trapezoidal shaping algorithm.Offline processing of a standard iron source further validated the pulse height estimation performance of the UNet-LSTM model.After estimating the amplitude of the distorted pulses using the model,the false peak area was reduced by approximately 91% over the full spectrum and was corrected to the characteristic peak region of interest(ROI).The corrected peak area accounted for approximately 1.32%of the characteristic peak ROI area.The results indicate that the model can accurately estimate the height of distorted pulses and has substantial corrective effects on false peaks.展开更多
A notable portion of cachelines in real-world workloads exhibits inner non-uniform access behaviors.However,modern cache management rarely considers this fine-grained feature,which impacts the effective cache capacity...A notable portion of cachelines in real-world workloads exhibits inner non-uniform access behaviors.However,modern cache management rarely considers this fine-grained feature,which impacts the effective cache capacity of contemporary high-performance spacecraft processors.To harness these non-uniform access behaviors,an efficient cache replacement framework featuring an auxiliary cache specifically designed to retain evicted hot data was proposed.This framework reconstructs the cache replacement policy,facilitating data migration between the main cache and the auxiliary cache.Unlike traditional cacheline-granularity policies,the approach excels at identifying and evicting infrequently used data,thereby optimizing cache utilization.The evaluation shows impressive performance improvement,especially on workloads with irregular access patterns.Benefiting from fine granularity,the proposal achieves superior storage efficiency compared with commonly used cache management schemes,providing a potential optimization opportunity for modern resource-constrained processors,such as spacecraft processors.Furthermore,the framework complements existing modern cache replacement policies and can be seamlessly integrated with minimal modifications,enhancing their overall efficacy.展开更多
To mitigate the impact of noise and inter-ference on multi-level-cell(MLC)flash memory with the use of low-density parity-check(LDPC)codes,we propose a dynamic write-voltage design scheme con-sidering the asymmetric p...To mitigate the impact of noise and inter-ference on multi-level-cell(MLC)flash memory with the use of low-density parity-check(LDPC)codes,we propose a dynamic write-voltage design scheme con-sidering the asymmetric property of raw bit error rate(RBER),which can obtain the optimal write voltage by minimizing a cost function.In order to further improve the decoding performance of flash memory,we put forward a low-complexity entropy-based read-voltage optimization scheme,which derives the read voltages by searching for the optimal entropy value via a log-likelihood ratio(LLR)-aware cost function.Simulation results demonstrate the superiority of our proposed dynamic write-voltage design scheme and read-voltage optimization scheme with respect to the existing counterparts.展开更多
A significant obstacle impeding the advancement of the time fractional Schrodinger equation lies in the challenge of determining its precise mathematical formulation.In order to address this,we undertake an exploratio...A significant obstacle impeding the advancement of the time fractional Schrodinger equation lies in the challenge of determining its precise mathematical formulation.In order to address this,we undertake an exploration of the time fractional Schrodinger equation within the context of a non-Markovian environment.By leveraging a two-level atom as an illustrative case,we find that the choice to raise i to the order of the time derivative is inappropriate.In contrast to the conventional approach used to depict the dynamic evolution of quantum states in a non-Markovian environment,the time fractional Schrodinger equation,when devoid of fractional-order operations on the imaginary unit i,emerges as a more intuitively comprehensible framework in physics and offers greater simplicity in computational aspects.Meanwhile,we also prove that it is meaningless to study the memory of time fractional Schrodinger equation with time derivative 1<α≤2.It should be noted that we have not yet constructed an open system that can be fully described by the time fractional Schrodinger equation.This will be the focus of future research.Our study might provide a new perspective on the role of time fractional Schrodinger equation.展开更多
基金supported by a National Research Foundation of Korea(NRF)grant(No.2016R1A3B 1908249)funded by the Korean government.
文摘Mechanically durable transparent electrodes are essential for achieving long-term stability in flexible optoelectronic devices.Furthermore,they are crucial for applications in the fields of energy,display,healthcare,and soft robotics.Conducting meshes represent a promising alternative to traditional,brittle,metal oxide conductors due to their high electrical conductivity,optical transparency,and enhanced mechanical flexibility.In this paper,we present a simple method for fabricating an ultra-transparent conducting metal oxide mesh electrode using selfcracking-assisted templates.Using this method,we produced an electrode with ultra-transparency(97.39%),high conductance(Rs=21.24Ωsq^(−1)),elevated work function(5.16 eV),and good mechanical stability.We also evaluated the effectiveness of the fabricated electrodes by integrating them into organic photovoltaics,organic light-emitting diodes,and flexible transparent memristor devices for neuromorphic computing,resulting in exceptional device performance.In addition,the unique porous structure of the vanadium-doped indium zinc oxide mesh electrodes provided excellent flexibility,rendering them a promising option for application in flexible optoelectronics.
文摘Load forecasting is of great significance to the development of new power systems.With the advancement of smart grids,the integration and distribution of distributed renewable energy sources and power electronics devices have made power load data increasingly complex and volatile.This places higher demands on the prediction and analysis of power loads.In order to improve the prediction accuracy of short-term power load,a CNN-BiLSTMTPA short-term power prediction model based on the Improved Whale Optimization Algorithm(IWOA)with mixed strategies was proposed.Firstly,the model combined the Convolutional Neural Network(CNN)with the Bidirectional Long Short-Term Memory Network(BiLSTM)to fully extract the spatio-temporal characteristics of the load data itself.Then,the Temporal Pattern Attention(TPA)mechanism was introduced into the CNN-BiLSTM model to automatically assign corresponding weights to the hidden states of the BiLSTM.This allowed the model to differentiate the importance of load sequences at different time intervals.At the same time,in order to solve the problem of the difficulties of selecting the parameters of the temporal model,and the poor global search ability of the whale algorithm,which is easy to fall into the local optimization,the whale algorithm(IWOA)was optimized by using the hybrid strategy of Tent chaos mapping and Levy flight strategy,so as to better search the parameters of the model.In this experiment,the real load data of a region in Zhejiang was taken as an example to analyze,and the prediction accuracy(R2)of the proposed method reached 98.83%.Compared with the prediction models such as BP,WOA-CNN-BiLSTM,SSA-CNN-BiLSTM,CNN-BiGRU-Attention,etc.,the experimental results showed that the model proposed in this study has a higher prediction accuracy.
基金Supported by Shandong Provincial Natural Science Foundation(Grant Nos.ZR2021MA003 and ZR2020MA020).
文摘This paper deals with a semilinear parabolic problem involving variable coefficients and nonlinear memory boundary conditions.We give the blow-up criteria for all nonnegative nontrivial solutions,which rely on the behavior of the coefficients when time variable tends to positive infinity.Moreover,the global existence of solutions are discussed for non-positive exponents.
基金supported by the National Key Research and Development Program(2022YFD1600402)Hebei Provincial Major Science and Technology Achievement Transformation Project(21287101Z)Hebei Provincial Innovation and Entrepreneurship Team Project(215A7102D)。
文摘Aging is an inevitable biological phenomenon that involves a multitude of physiological alterations.Dietary interventions are being considered as potential strategies for delaying age-related dysfunction.Unsaponifiable matter(USM),a composition of highly active ingredients found in walnut oil,has demonstrated antioxidant effects.This study aims to explore the neuroprotective effects of USM on d-galactose-treated C57BL/6 mice and elucidate its underlying mechanism,which was validated in PC12 cells treated with d-galactose.The results of behavioral tests demonstrated that USM significantly improved cognitive deficits associated with aging.The morphological analysis demonstrated that USM effectively alleviated hippocampal neuronal damage,synaptic impairment,and mitochondrial dysfunction induced by d-galactose.Furthermore,USM significantly increases the antioxidant enzymes activity while reducing the malondialdehyde and reactive oxygen species levels.The results suggest that USM can mitigate age-related symptoms caused by d-galactose by activating the nuclear factor erythroid-2-related factor 2 signaling pathway,which enhances the expression of antioxidant enzymes,restore redox balance,and improves synaptic and mitochondrial functions.This has a positive on improving cognition and memory disorders in elderly mice.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.HC-CN-20220722010。
文摘This paper proposes a concurrent neural network model to mitigate non-linear distortion in power amplifiers using a basis function generation approach.The model is designed using polynomial expansion and comprises a feedforward neural network(FNN)and a convolutional neural network(CNN).The proposed model takes the basic elements that form the bases as input,defined by the generalized memory polynomial(GMP)and dynamic deviation reduction(DDR)models.The FNN generates the basis function and its output represents the basis values,while the CNN generates weights for the corresponding bases.Through the concurrent training of FNN and CNN,the hidden layer coefficients are updated,and the complex multiplication of their outputs yields the trained in-phase/quadrature(I/Q)signals.The proposed model was trained and tested using 300 MHz and 400 MHz broadband data in an orthogonal frequency division multiplexing(OFDM)communication system.The results show that the model achieves an adjacent channel power ratio(ACPR)of less than-48 d B within a 100 MHz integral bandwidth for both the training and test datasets.
基金supported by Key Project of Sichuan Provincial Natural Science Foundation(No.2022NSFSC0043).
文摘In this work,we propose a comprehensive theoretical framework for the multilevel NAND(NOT AND logic)flash memory,built upon the modified Student’s t distribution where the distortion of the threshold voltage caused by the random telegraph noise,cell-to-cell interference and data retention noise are jointly considered.Based on the superposition modulation,we build a non-orthogonal multiuser communication model where a linear mapping is conducted between the verify voltages and binary antipodal symbols.Aimed at improving the storage efficiency,we propose an unequal amplitude mapping(UAM)solution by optimizing the weighting coefficients of verify voltages to intelligently adjust the width of each state.Moreover,the uniform storage efficiency region and sum storage efficiency of different labelings with various decoding schemes are discussed.Simulation results validate the effectiveness of our proposed UAM solution where an up to 20.9%storage efficiency gain can be achieved compared to the current used benchmark scheme.In addition,analytical and simulation results also demonstrate that the successive cancellation decoding outperforms other decoding schemes for all labelings.
基金supported in part by the National Natural Science Foundation of China(91949205,82071219,82001134,31730035,81721005,and 82201584)the Hubei Provincial Key S&T Program(2018ACA142)the Guangdong Provincial Key S&T Program(2018B030336001).
文摘Background:Episodic memory loss is a prominent clinical manifestation of Alzheimer’s disease(AD),which is closely related to tau pathology and hippocampal impairment.Due to the heterogeneity of brain neurons,the specific roles of different brain neurons in terms of their sensitivity to tau accumulation and their contribution to AD-like social memory loss remain unclear.Therefore,further investigation is necessary.Methods:We investigated the effects of AD-like tau pathology by Tandem mass tag proteomic and phosphoproteomic analysis,social behavioural tests,hippocampal electrophysiology,immunofluorescence staining and in vivo optical fibre recording of GCaMP6f and iGABASnFR.Additionally,we utilized optogenetics and administered ursolic acid(UA)via oral gavage to examine the effects of these agents on social memory in mice.Results:The results of proteomic and phosphoproteomic analyses revealed the characteristics of ventral hippocampal CA1(vCA1)under both physiological conditions and AD-like tau pathology.As tau progressively accumulated,vCA1,especially its excitatory and parvalbumin(PV)neurons,were fully filled with mislocated and phosphorylated tau(p-Tau).This finding was not observed for dorsal hippocampal CA1(dCA1).The overexpression of human tau(hTau)in excitatory and PV neurons mimicked AD-like tau accumulation,significantly inhibited neuronal excitability and suppressed distinct discrimination-associated firings of these neurons within vCA1.Photoactivating excitatory and PV neurons in vCA1 at specific rhythms and time windows efficiently ameliorated tau-impaired social memory.Notably,1 month of UA administration efficiently decreased tau accumulation via autophagy in a transcription factor EB(TFEB)-dependent manner and restored the vCA1 microcircuit to ameliorate tau-impaired social memory.Conclusion:This study elucidated distinct protein and phosphoprotein networks between dCA1 and vCA1 and highlighted the susceptibility of the vCA1 microcircuit to AD-like tau accumulation.Notably,our novel findings regarding the efficacy of UA in reducing tau load and targeting the vCA1 microcircuit may provide a promising strategy for treating AD in the future.
基金This work was supported by the Jinan City-University Integrated Development Strategy Project under Grant(JNSX2023017)National Research Foundation of Korea(NRF)grant funded by the Korea government(MIST)(RS-2023-00302751)+1 种基金by the National Research Foundation of Korea(NRF)funded by the Ministry of Education under Grants 2018R1A6A1A03025242 and 2018R1D1A1A09083353by Qilu Young Scholar Program of Shandong University.
文摘Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex associative learning behaviors is still nascent.Here,an optoelec-tronic memristor based on Ag/TiO_(2) Nanowires:ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors.Effective implementation of synaptic behaviors,including long and short-term plasticity,and learning-forgetting-relearning behaviors,were achieved in the device through the application of light and electrical stimuli.Leveraging the optoelectronic co-modulated characteristics,a simulation of neuromorphic computing was conducted,resulting in a handwriting digit recognition accuracy of 88.9%.Furthermore,a 3×7 memristor array was constructed,confirming its application in artificial visual memory.Most importantly,complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli,respectively.After training through associative pairs,reflexes could be triggered solely using light stimuli.Comprehen-sively,under specific optoelectronic signal applications,the four features of classical conditioning,namely acquisition,extinction,recovery,and generalization,were elegantly emulated.This work provides an optoelectronic memristor with associative behavior capabilities,offering a pathway for advancing brain-machine interfaces,autonomous robots,and machine self-learning in the future.
基金funding support from the National Natural Science Foundation of China(52172205).
文摘It is still challenging to fully integrate computing in memory chip as edge learning devices.In recent work published on Science,a fully-integrated chip based on neuromorphic memristors was developed for edge learning as artificial neural networks with functionality of synapses,dendrites,and somas.A crossbar-array memristor chip facilitated edge learning including hardware realization,learning algorithm,and cycle-parallel sign-and threshold-based learning(STELLAR)scheme.The motion control and demonstration platforms were executed to improve the edge learning ability for adapting to new scenarios.
基金fundings of National Natural Science Foundation of China(No.T2222025,62174053 and 61804055)National Key Research and Development program of China(No.2021YFA1200700)+1 种基金Shanghai Science and Technology Innovation Action Plan(No.21JC1402000 and 21520714100)the Fundamental Research Funds for the Central Universities.
文摘Ferroelectrics have great potential in the field of nonvolatile memory due to programmable polarization states by external electric field in nonvolatile manner.However,complementary metal oxide semiconductor compatibility and uniformity of ferroelectric performance after size scaling have always been two thorny issues hindering practical application of ferroelectric memory devices.The emerging ferroelectricity of wurtzite structure nitride offers opportunities to circumvent the dilemma.This review covers the mechanism of ferroelectricity and domain dynamics in ferroelectric AlScN films.The performance optimization of AlScN films grown by different techniques is summarized and their applications for memories and emerging in-memory computing are illustrated.Finally,the challenges and perspectives regarding the commercial avenue of ferroelectric AlScN are discussed.
基金supported by the National Key R&D Plan of China(Grant 2021YFB3600703)the National Natural Science Foundation(Grant 62204137)of China for Youth,the Open Research Fund Program of Beijing National Research Centre for Information Science and Technology(BR2023KF02009)+1 种基金the National Natural Science Foundation of china(U20A20168,61874065,and 51861145202)the Research Fund from Tsinghua University Initiative Scientific Research Program,the Center for Flexible Electronics Technology of Tsinghua University,and a grant from the Guoqiang Institute,Tsinghua University.
文摘Two-dimensional(2D)transition metal dichalcogenides(TMDs)allow for atomic-scale manipulation,challenging the conventional limitations of semiconductor materials.This capability may overcome the short-channel effect,sparking significant advancements in electronic devices that utilize 2D TMDs.Exploring the dimension and performance limits of transistors based on 2D TMDs has gained substantial importance.This review provides a comprehensive investigation into these limits of the single 2D-TMD transistor.It delves into the impacts of miniaturization,including the reduction of channel length,gate length,source/drain contact length,and dielectric thickness on transistor operation and performance.In addition,this review provides a detailed analysis of performance parameters such as source/drain contact resistance,subthreshold swing,hysteresis loop,carrier mobility,on/off ratio,and the development of p-type and single logic transistors.This review details the two logical expressions of the single 2D-TMD logic transistor,including current and voltage.It also emphasizes the role of 2D TMD-based transistors as memory devices,focusing on enhancing memory operation speed,endurance,data retention,and extinction ratio,as well as reducing energy consumption in memory devices functioning as artificial synapses.This review demonstrates the two calculating methods for dynamic energy consumption of 2D synaptic devices.This review not only summarizes the current state of the art in this field but also highlights potential future research directions and applications.It underscores the anticipated challenges,opportunities,and potential solutions in navigating the dimension and performance boundaries of 2D transistors.
基金supported by the National Key Research&Development Project of China(Grant No.2022YFA1204100)the National Natural Science Foundation of China(Grant No.62488201)+1 种基金CAS Project for Young Scientists in Basic Research(Grant No.YSBR-003)the Innovation Program of Quantum Science and Technology(Grant No.2021ZD0302700)。
文摘Charge trapping devices incorporating 2D materials and high-κdielectrics have emerged as promising candidates for compact,multifunctional memory devices compatible with silicon-based manufacturing processes.However,traditional charge trapping devices encounter bottlenecks including complex device structure and low operation speed.Here,we demonstrate an ultrafast reconfigurable direct charge trapping device utilizing only a 30 nm-thick Al_(2)O_(3)trapping layer with a MoS_(2)channel,where charge traps reside within the Al_(2)O_(3)bulk confirmed by transfer curves with different gatevoltage sweeping rates and photoluminescence(PL)spectra.The direct charging tapping device shows exceptional memory performance in both three-terminal and two-terminal operation modes characterized by ultrafast three-terminal operation speed(~300 ns),an extremely low OFF current of 10^(-14)A,a high ON/OFF current ratio of up to 10^(7),and stable retention and endurance properties.Furthermore,the device with a simple symmetrical structure exhibits VDpolarity-dependent reverse rectification behavior in the high resistance state(HRS),with a rectification ratio of 10^(5).Additionally,utilizing the synergistic modulation of the conductance of the MoS_(2)channel by V_(D)and V_(G),it achieves gate-tunable reverse rectifier and ternary logic capabilities.
基金M.Zhu acknowledges support by the National Outstanding Youth Program(62322411)the Hundred Talents Program(Chinese Academy of Sciences)+1 种基金the Shanghai Rising-Star Program(21QA1410800)The financial support was provided by the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB44010200).
文摘Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.
基金Project supported by the Key-Area Research and Development Program of Guangdong Province,China(Grant No.2021B0101300003)the Guangdong Basic and Applied Basic Research Foundation,China(Grant Nos.2022A1515110863 and 2023A1515010837)+5 种基金the National Key Research and Development Program of China(Grant No.2016YFA0300803)the National Natural Science Foundation of China(Grant Nos.12304136,61427812,11774160,12241403,51771127,52171188,and 52111530143)the Natural Science Foundation of Jiangsu Province,China(Grant Nos.BK20192006 and BK20200307)the Fundamental Research Funds for the Central Universities,China(Grant No.021014380113)International Exchanges 2020 Cost Share(NSFC),China(Grant No.IECNSFC201296)the Project for Maiden Voyage of Guangzhou Basic and Applied Basic Research Scheme,China(Grant No.2024A04J4186)。
文摘Skyrmions, with their vortex-like structures and inherent topological protection, play a pivotal role in developing innovative low-power memory and logic devices. The efficient generation and control of skyrmions in geometrically confined systems are crucial for the development of skyrmion-based spintronic devices. In this study, we focus on investigating the non-reciprocal transport behavior of skyrmions and their interactions with boundaries of various shapes. The shape of the notch structure in the nanotrack significantly affects the dynamic behavior of magnetic skyrmions. Through micromagnetic simulation, the non-reciprocal transport properties of skyrmions in nanowires with different notch structures are investigated in this work.
基金supported by the Open Project of Guangxi Key Laboratory of Nuclear Physics and Nuclear Technology(No.NLK2022-05)the Central Government Guidance Funds for Local Scientific and Technological Development,China(No.Guike ZY22096024)+5 种基金the Sichuan Natural Science Youth Fund Project(No.2023NSFSC1366)Key R&D Projects of Sichuan Provincial Department of Science and Technology(No.2023YFG0287)the Open Research Fund of National Engineering Research Center for Agro-Ecological Big Data Analysis&Application,Anhui University(No.AE202209)the National Natural Science Youth Foundation of China(No.12305214)the Vanadium and Titanium Resource Comprehensive Utilization Key Laboratory of Sichuan Province(No.2023FTSZ03)the Key Laboratory of Interior Layout optimization and Security,Institutions of Higher Education of Sichuan Province(No.2023SNKJ-01)。
文摘In energy-dispersive X-ray fluorescence spectroscopy,the estimation of the pulse amplitude determines the accuracy of the spectrum measurement.The error generated by the amplitude estimation of the pulse output distorted by the measurement system leads to false peaks in the measured spectrum.To eliminate these false peaks and achieve an accurate estimation of the distorted pulse amplitude,a composite neural network model is proposed,which embeds long and short-term memory(LSTM)into the UNet structure.The UNet network realizes the fusion of pulse sequence features and the LSTM model realizes pulse amplitude estimation.The model is trained using simulated pulse datasets with different amplitudes and distortion times.For the pulse height estimation,the average relative error of the trained model on the test set was approximately 0.64%,which is 27.37% lower than that of the traditional trapezoidal shaping algorithm.Offline processing of a standard iron source further validated the pulse height estimation performance of the UNet-LSTM model.After estimating the amplitude of the distorted pulses using the model,the false peak area was reduced by approximately 91% over the full spectrum and was corrected to the characteristic peak region of interest(ROI).The corrected peak area accounted for approximately 1.32%of the characteristic peak ROI area.The results indicate that the model can accurately estimate the height of distorted pulses and has substantial corrective effects on false peaks.
文摘A notable portion of cachelines in real-world workloads exhibits inner non-uniform access behaviors.However,modern cache management rarely considers this fine-grained feature,which impacts the effective cache capacity of contemporary high-performance spacecraft processors.To harness these non-uniform access behaviors,an efficient cache replacement framework featuring an auxiliary cache specifically designed to retain evicted hot data was proposed.This framework reconstructs the cache replacement policy,facilitating data migration between the main cache and the auxiliary cache.Unlike traditional cacheline-granularity policies,the approach excels at identifying and evicting infrequently used data,thereby optimizing cache utilization.The evaluation shows impressive performance improvement,especially on workloads with irregular access patterns.Benefiting from fine granularity,the proposal achieves superior storage efficiency compared with commonly used cache management schemes,providing a potential optimization opportunity for modern resource-constrained processors,such as spacecraft processors.Furthermore,the framework complements existing modern cache replacement policies and can be seamlessly integrated with minimal modifications,enhancing their overall efficacy.
基金supported in part by the NSF of China under Grants 62322106,62071131,U2001203,61871136the Guangdong Basic and Applied Basic Research Foundation under Grant 2022B1515020086+1 种基金the International Collaborative Research Program of Guangdong Science and Technology Department under Grant 2022A0505050070the Industrial R&D Project of Haoyang Electronic Co.,Ltd.under Grant 2022440002001494.
文摘To mitigate the impact of noise and inter-ference on multi-level-cell(MLC)flash memory with the use of low-density parity-check(LDPC)codes,we propose a dynamic write-voltage design scheme con-sidering the asymmetric property of raw bit error rate(RBER),which can obtain the optimal write voltage by minimizing a cost function.In order to further improve the decoding performance of flash memory,we put forward a low-complexity entropy-based read-voltage optimization scheme,which derives the read voltages by searching for the optimal entropy value via a log-likelihood ratio(LLR)-aware cost function.Simulation results demonstrate the superiority of our proposed dynamic write-voltage design scheme and read-voltage optimization scheme with respect to the existing counterparts.
基金Project supported by the National Natural Science Foun dation of China(Grant No.11274398).
文摘A significant obstacle impeding the advancement of the time fractional Schrodinger equation lies in the challenge of determining its precise mathematical formulation.In order to address this,we undertake an exploration of the time fractional Schrodinger equation within the context of a non-Markovian environment.By leveraging a two-level atom as an illustrative case,we find that the choice to raise i to the order of the time derivative is inappropriate.In contrast to the conventional approach used to depict the dynamic evolution of quantum states in a non-Markovian environment,the time fractional Schrodinger equation,when devoid of fractional-order operations on the imaginary unit i,emerges as a more intuitively comprehensible framework in physics and offers greater simplicity in computational aspects.Meanwhile,we also prove that it is meaningless to study the memory of time fractional Schrodinger equation with time derivative 1<α≤2.It should be noted that we have not yet constructed an open system that can be fully described by the time fractional Schrodinger equation.This will be the focus of future research.Our study might provide a new perspective on the role of time fractional Schrodinger equation.
