Developing efficient neural network(NN)computing systems is crucial in the era of artificial intelligence(AI).Traditional von Neumann architectures have both the issues of"memory wall"and"power wall&quo...Developing efficient neural network(NN)computing systems is crucial in the era of artificial intelligence(AI).Traditional von Neumann architectures have both the issues of"memory wall"and"power wall",limiting the data transfer between memory and processing units[1,2].Compute-in-memory(CIM)technologies,particularly analogue CIM with memristor crossbars,are promising because of their high energy efficiency,computational parallelism,and integration density for NN computations[3].In practical applications,analogue CIM excels in tasks like speech recognition and image classification,revealing its unique advantages.For instance,it efficiently processes vast amounts of audio data in speech recognition,achieving high accuracy with minimal power consumption.In image classification,the high parallelism of analogue CIM significantly speeds up feature extraction and reduces processing time.With the boosting development of AI applications,the demands for computational accuracy and task complexity are rising continually.However,analogue CIM systems are limited in handling complex regression tasks with needs of precise floating-point(FP)calculations.They are primarily suited for the classification tasks with low data precision and a limited dynamic range[4].展开更多
This essay will reexamine research on the relationship between human memory and addiction. This paper will review several studies that discussed how memory systems in the human brain are involved in the acquisition of...This essay will reexamine research on the relationship between human memory and addiction. This paper will review several studies that discussed how memory systems in the human brain are involved in the acquisition of behavior that is learned and is associated with the development of drug addiction and drug relapse. Additional information reveals that when individuals make the transition from recreational drug or impulsive use to compulsive drug abuse, which may result in a neuroanatomical change in areas of the brain from cognitive control guided by the hippocampus/dorsomedial striatum towards conditioned control of behavior managed by the dorsolateral striatum (DLS) [1]. This review also looked at studies that involved experiments with humans and lower animals, which suggested that the hippocampus mediates a cognitive/spatial type of memory, while the dorsal striatum manages stimulus-response (S-R) habit memory, and the amygdala governs the classical conditioning form of learning and stimulus-affective-associative relationships [1]. Overall, these studies utilize the hypothesis of the memory systems view of addiction, and the involvement of learning and memory in the context of drug addiction, which was proposed by them [2]. This theory has been proposed in response to drug addiction research and includes alcohol, amphetamine, and cocaine [1]. The research also explains how stress and anxiety can play a role in how strong emotional excitement can lead to dependent habit memory in rodents and humans [1]. .展开更多
A fault-tolerant spaceborne mass memory architecture is presented based on entirely commercial-off-theshelf components.The highly modularized and scalable memory kernel supports the hierarchical design and is well sui...A fault-tolerant spaceborne mass memory architecture is presented based on entirely commercial-off-theshelf components.The highly modularized and scalable memory kernel supports the hierarchical design and is well suited to redundancy structure.Error correcting code(ECC) and periodical scrubbing are used to deal with bit errors induced by single event upset.For 8-bit wide devices, the parallel Reed Solomon(10, 8) can perform coder/decoder calculations in one clock cycle, achieving a data rate of several Gb/...展开更多
The diffusion behavior driven by bounded noise under the influence of a coupled harmonic potential is investigated in a two-dimensional coupled-damped model. With the help of the Laplace analysis we obtain exact descr...The diffusion behavior driven by bounded noise under the influence of a coupled harmonic potential is investigated in a two-dimensional coupled-damped model. With the help of the Laplace analysis we obtain exact descriptions for a particle’s two-time dynamics which is subjected to a coupled harmonic potential and a coupled damping. The time lag is used to describe the velocity autocorrelation function and mean square displacement of the diffusing particle. The diffusion behavior for the time lag is also discussed with respect to the coupled items and the amplitude of bounded noise.展开更多
BACKGROUND Cognitive impairment is a major cause of disability in patients who have suffered from a stroke,and cognitive rehabilitation interventions show promise for improving memory.AIM To examine the effectiveness ...BACKGROUND Cognitive impairment is a major cause of disability in patients who have suffered from a stroke,and cognitive rehabilitation interventions show promise for improving memory.AIM To examine the effectiveness of virtual reality(VR)and non-VR(NVR)cognitive rehabilitation techniques for improving memory in patients after stroke.METHODS An extensive and thorough search was executed across five pertinent electronic databases:Cumulative Index to Nursing and Allied Health Literature;MEDLINE(PubMed);Scopus;ProQuest Central;and Google Scholar.This systematic review was conducted following the preferred reporting items for systematic reviews and meta-analyses guideline.Studies that recruited participants who experienced a stroke,utilized cognitive rehabilitation interventions,and published in the last 10 years were included in the review.RESULTS Thirty studies met the inclusion criteria.VR interventions significantly improved memory and cognitive function(mean difference:4.2±1.3,P<0.05),whereas NVR(including cognitive training,music,and exercise)moderately improved memory.Compared with traditional methods,technology-driven VR approaches were particularly beneficial for enhancing daily cognitive tasks.CONCLUSION VR and NVR reality interventions are beneficial for post-stroke cognitive recovery,with VR providing enhanced immersive experiences.Both approaches hold transformative potential for post-stroke rehabilitation.展开更多
BACKGROUND Working memory serves as a fundamental cognitive function that substantially impacts performance in various cognitive tasks.Extensive neurophysiological research has established that theta oscillations(4-8 ...BACKGROUND Working memory serves as a fundamental cognitive function that substantially impacts performance in various cognitive tasks.Extensive neurophysiological research has established that theta oscillations(4-8 Hz)play an essential role in supporting working memory operations.Theta-band transcranial alternating current stimulation(tACS)offers a potential mechanism for working memory enhancement through direct modulation of these fundamental neural oscillations.Nevertheless,current empirical evidence shows substantial variability in the observed effects of theta-tACS across studies.AIM To conduct a systematic review and meta-analysis evaluating the effects of thetatACS on working memory performance in healthy adults.METHODS A systematic literature search was performed on PubMed,EMBASE,and Web of Science up to March 10,2025.Effect sizes were computed using Hedges’g with 95%confidence intervals(CIs),with separate meta-analyses for all included studies and for distinct working memory paradigms[n-back and delayed matchto-sample(DMTS)tasks]to examine potential task-specific effects.Subgroup analyses and meta-regression were performed to evaluate the influence of key moderating variables.RESULTS The systematic review included 21 studies(67 effect sizes).Initial meta-analysis showed theta-tACS moderately improved working memory(Hedges’g=0.405,95%CI:0.212-0.598).However,this effect became nonsignificant after correcting for publication bias(trim-and-fill adjusted Hedges’g=0.082,95%CI:-0.052 to 0.217).Task-specific analyses revealed significant benefits in n-back tasks(Hedges’g=0.463,95%CI:0.193-0.733)but not in DMTS tasks(Hedges’g=0.257,95%CI:-0.186 to 0.553).Moderator analyses showed that performance in n-back tasks was influenced by stimulation frequency(P=0.001),concurrent status(P=0.014),task modality(P=0.005),and duration(P=0.013),whereas only the region of targeted stimulation(P=0.012)moderated DMTS tasks.CONCLUSION Theta-tACS enhances working memory in healthy adults,with effects modulated by the task type and protocol parameters,offering dual implications for cognitive enhancement and clinical interventions.展开更多
After billions of years of evolution,biological intelligence has converged on unrivalled energy efficiency and environmental adaptability.The human brain,for instance,is highly efficient in information transmission,co...After billions of years of evolution,biological intelligence has converged on unrivalled energy efficiency and environmental adaptability.The human brain,for instance,is highly efficient in information transmission,consuming only about 20 W onaverage in a resting state[1,2].A key to this efficiency is that biological signal transduction and processing rely significantly on multi-ions as the signal carriers.Inspired by this paradigm.展开更多
The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and e...The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and existence of uniform attractor under some suitable assumptions on the nonlinear term g(u),the nonlinear damping f(u_(t))and the external force h(x,t).Specifically,the asymptotic compactness of the semigroup is verified by the energy reconstruction method.展开更多
Early life stress correlates with a higher prevalence of neurological disorders,including autism,attention-deficit/hyperactivity disorder,schizophrenia,depression,and Parkinson's disease.These conditions,primarily...Early life stress correlates with a higher prevalence of neurological disorders,including autism,attention-deficit/hyperactivity disorder,schizophrenia,depression,and Parkinson's disease.These conditions,primarily involving abnormal development and damage of the dopaminergic system,pose significant public health challenges.Microglia,as the primary immune cells in the brain,are crucial in regulating neuronal circuit development and survival.From the embryonic stage to adulthood,microglia exhibit stage-specific gene expression profiles,transcriptome characteristics,and functional phenotypes,enhancing the susceptibility to early life stress.However,the role of microglia in mediating dopaminergic system disorders under early life stress conditions remains poorly understood.This review presents an up-to-date overview of preclinical studies elucidating the impact of early life stress on microglia,leading to dopaminergic system disorders,along with the underlying mechanisms and therapeutic potential for neurodegenerative and neurodevelopmental conditions.Impaired microglial activity damages dopaminergic neurons by diminishing neurotrophic support(e.g.,insulin-like growth factor-1)and hinders dopaminergic axon growth through defective phagocytosis and synaptic pruning.Furthermore,blunted microglial immunoreactivity suppresses striatal dopaminergic circuit development and reduces neuronal transmission.Furthermore,inflammation and oxidative stress induced by activated microglia can directly damage dopaminergic neurons,inhibiting dopamine synthesis,reuptake,and receptor activity.Enhanced microglial phagocytosis inhibits dopamine axon extension.These long-lasting effects of microglial perturbations may be driven by early life stress–induced epigenetic reprogramming of microglia.Indirectly,early life stress may influence microglial function through various pathways,such as astrocytic activation,the hypothalamic–pituitary–adrenal axis,the gut–brain axis,and maternal immune signaling.Finally,various therapeutic strategies and molecular mechanisms for targeting microglia to restore the dopaminergic system were summarized and discussed.These strategies include classical antidepressants and antipsychotics,antibiotics and anti-inflammatory agents,and herbal-derived medicine.Further investigations combining pharmacological interventions and genetic strategies are essential to elucidate the causal role of microglial phenotypic and functional perturbations in the dopaminergic system disrupted by early life stress.展开更多
The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,th...The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.展开更多
Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability...Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability of the triazine ring structure within cyanate ester(CE)crosslinked networks after molding posed significant challenges for both recycling,repairing,and degradation of resin.To address these obstacles,dynamic thiocyanate ester(TCE)bonds and photocurable group were incorporated into CE,obtaining the recyclable and 3D printable CE covalent adaptable networks(CANs),denoted as PTCE1.5.This material exhibits a Young's modulus of 810 MPa and a tensile strength of 50.8 MPa.Notably,damaged printed PTCE1.5 objects can be readily repaired through reprinting and interface rejoining by thermal treatment.Leveraging the solid-state plasticity,PTCE1.5 also demonstrated attractive shape memory ability and permanent shape reconfigurability,enabling its reconfigurable 4D printing.The printed PTCE1.5 hinges and a main body were assembled into a deployable and retractable satellite model,validating its potential application as a controllable component in the aerospace field.Moreover,printed PTCE1.5 can be fully degraded into thiol-modified intermediate products.Overall,this material not only enriches the application range of CE resin,but also provides a reliable approach to addressing environmental issue.展开更多
Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous...Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.展开更多
As the scaling of applications increases, the demand of main memory capacity increases in order to serve large working set. It is difficult for DRAM （dynamic random access memory） based memory system to satisfy the ...As the scaling of applications increases, the demand of main memory capacity increases in order to serve large working set. It is difficult for DRAM （dynamic random access memory） based memory system to satisfy the memory capacity requirement due to its limited scalability and high energy consumption. Compared to DRAM, PCM （phase change memory） has better scalability, lower energy leakage, and non-volatility. PCM memory systems have become a hot topic of academic and industrial research. However, PCM technology has the following three drawbacks： long write latency, limited write endurance, and high write energy, which raises challenges to its adoption in practice. This paper surveys architectural research work to optimize PCM memory systems. First, this paper introduces the background of PCM. Then, it surveys research efforts on PCM memory systems in performance optimization, lifetime improving, and energy saving in detail, respectively. This paper also compares and summarizes these techniques from multiple dimensions. Finally, it concludes these optimization techniques and discusses possible research directions of PCM memory systems in future.展开更多
The decades-old synchronous memory bus interface has restricted many innovations in the memory system, which is facing various challenges （or walls） in the era of multi-core and big data. In this paper, we argue tha...The decades-old synchronous memory bus interface has restricted many innovations in the memory system, which is facing various challenges （or walls） in the era of multi-core and big data. In this paper, we argue that a message- based interface should be adopted to replace the traditional bus-based interface in the memory system. A novel message interface based memory system called MIMS is proposed. The key innovation of MIMS is that processors communicate with the memory system through a universal and flexible message packet interface. Each message packet is allowed to encapsulate multiple memory requests （or commands） and additional semantic information. The memory system is more intelligent and active by equipping with a local buffer scheduler, which is responsible for processing packets, scheduling memory requests, preparing responses, and executing specific commands with the help of semantic information. Under the MIMS framework, many previous innovations on memory architecture as well as new optimization opportunities such as address compression and continuous requests combination can be naturally incorporated. The experimental results on a 16-core cycle-detailed simulation system show that： with accurate granularity message, MIMS can improve system performance by 53.21% and reduce energy delay product （EDP） by 55.90%. Furthermore, it can improve effective bandwidth utilization by 62.42% and reduce memory access latency by 51% on average.展开更多
Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memor...Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.展开更多
Biologically inspired neuromorphic sensory memory systems based on memristor have received a lot of attention in the booming artificial intelligence industry due to significant potential to effectively process multi-s...Biologically inspired neuromorphic sensory memory systems based on memristor have received a lot of attention in the booming artificial intelligence industry due to significant potential to effectively process multi-sensory signals from complex external environments.However,many memristors have significant switching parameters disperse,which is a great challenge for using memristors in bionic neuromorphic sensory memory systems.Herein,a stable ferroelectric memristor based on the Pd/BaTiO_(3):Eu2O_(3)/La0.67Sr0.33MnO_(3)grown on Silicon structure with SrTiO_(3)as buffer layer is presented.The device possesses low coercive field voltage(-1.3-2.1 V)and robust endurance characteristic(~10^(10)cycles)through optimizing the growth temperature.More importantly,an ultra-stable artificial multimodal sensory memory system with visual and tactile functions was reported for the first time by combining a pressure sensor,a photosensitive sensor,and a robotic arm.Utilizing the above system,the sensitivity value of the system is expressed by the conductance of the memristor to realize the gradual change of external stimulus,and multi signals inputs at the same time to this system have faithfully achieved sensory adaptation to multimodal sensors.This work paves the way for future development of memristor-based perception systems in efficient multisensory neural robots.展开更多
The appearance and wide use of memory hardware bring significant changes to the conventional vertical memory hierarchy that fails to handle contentions for shared hardware resources and expensive data movements.To dea...The appearance and wide use of memory hardware bring significant changes to the conventional vertical memory hierarchy that fails to handle contentions for shared hardware resources and expensive data movements.To deal with these problems,existing schemes have to rely on inefficient scheduling strategies that also cause extra temporal,spatial and bandwidth overheads.Based on the insights that the shared hardware resources trend to be uniformly and hierarchically offered to the requests for co-located applications in memory systems,we present an efficient abstraction of memory hierarchies,called Label,which is used to establish the connection between the application layer and underlying hardware layer.Based on labels,our paper proposes LaMem,a labeled,resource-isolated and cross-tiered memory system by leveraging the way-based partitioning technique for shared resources to guarantee QoS demands of applications,while supporting fast and low-overhead cache repartitioning technique.Besides,we customize LaMem for the learned index that fundamentally replaces storage structures with computation models as a case study to verify the applicability of LaMem.Experimental results demonstrate the efficiency and efficacy of LaMem.展开更多
Phase change memory （PCM） is a promising technology for future memory thanks to its better scalability and lower leakage power than DRAM （dynamic random-access memory）. However, adopting PCM as main memory needs t...Phase change memory （PCM） is a promising technology for future memory thanks to its better scalability and lower leakage power than DRAM （dynamic random-access memory）. However, adopting PCM as main memory needs to overcome its write issues, such as long write latency and high write power. In this paper, we propose two techniques to improve the performance and energy-efficiency of PCM memory systems. First, we propose a victim cache technique utilizing the existing buffer in the memory controller to reduce PCM memory accesses. The key idea is reorganizing the buffer into a victim cache structure （RBC） to provide additional hits for the LLC （last level cache）. Second, we propose a chip parallelism-aware replacement policy （CPAR） for the victim cache to further improve performance. Instead of evicting one cache line once, CPAR evicts multiple cache lines that access different PCM chips. CPAR can reduce the frequent victim cache eviction and improve the write parallelism of PCM chips. The evaluation results show that, compared with the baseline, RBC can improve PCM memory system performance by up to 9.4% and 5.4% on average. Combing CPAR with RBC （RBC＋CPAR） can improve performance by up to 19.0% and 12.1% on average. Moreover, RBC and RBC＋CPAR can reduce memory energy consumption by 8.3% and 6.6% on average, respectively.展开更多
Page migration has long been adopted in hybrid memory systems comprising dynamic random access memory(DRAM)and non-volatile memories(NVMs),to improve the system performance and energy efficiency.However,page migration...Page migration has long been adopted in hybrid memory systems comprising dynamic random access memory(DRAM)and non-volatile memories(NVMs),to improve the system performance and energy efficiency.However,page migration introduces some side effects,such as more translation lookaside buffer(TLB)misses,breaking memory contiguity,and extra memory accesses due to page table updating.In this paper,we propose superpagefriendly page table called SuperPT to reduce the performance overhead of serving TLB misses.By leveraging a virtual hashed page table and a hybrid DRAM allocator,SuperPT performs address translations in a flexible and efficient way while still remaining the contiguity within the migrated pages.展开更多
OBJECTIVE: To investigate the effects of combined acupuncture and eugenol on learning-memory ability and the antioxidation system of the hippocampus in Alzheimer disease (AD) rats. METHODS: Sixty Sprague Dawley rats, ...OBJECTIVE: To investigate the effects of combined acupuncture and eugenol on learning-memory ability and the antioxidation system of the hippocampus in Alzheimer disease (AD) rats. METHODS: Sixty Sprague Dawley rats, weighing (300±10) g, were randomly divided with 10 rats per group into a normal control group, AD model group, AD with cut olfactory nerve group, Xiu three-needle group, eugenol group, and combined acupuncture and eugenol group. The AD model was established by injection of amyloid β1-40 (Aβ 1-40). Morris maze tests were conducted for evaluating the learning-memory ability. Content of malo- ndialdehyde (MDA) and activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in the hippocampus were detected. RESULTS: The average escape latency and the mean swimming distance in the normal control group, the Xiu three-needle group, the eugenol group, and the combined acupuncture and euge-nol group were significantly shorter than those in the AD model group (all P<0.01). The combined acupuncture and eugenol group had shorter escape latency and mean swimming distance than those in the Xiu three-needle group and the eugenol group. There were no significant differences between the Xiu three-needle group and the eugenol group and between the AD group and the AD with cut olfactory nerve group (P>0.05). Compared with the normal control group, the MDA content in the hippocampus significantly increased (P<0.05) and GSH-Px and SOD activities significantly decreased in the AD model group (P<0.01). Compared with the AD model group, significantly decreased (P< 0.01) and SOD and GSH-Px activities significantly increased in the Xiu three-needle group, eugenol group, and combined acupuncture and eugenol group (P<0.05). Compared with the Xiu three-needle group and eugenol group, the MDA content significantly decreased (P<0.05) and SOD and GSH-Px activities increased (P<0.05) in the combined acupuncture and eugenol group. There were no significant differences among the three indices between the Xiu three-needle group and the eugenol group and between the AD model group and the AD with cut olfactory nerve group (P>0.05). CONCLUSION: Both Xiu three-needle and eugenol can increase learning-memory ability, decrease MDA content, and increase SOD and GSH-Px activities in the hippocampus in AD rats. The combination of acupuncture with eugenol has stronger effects, and the effects depend on the olfactory pathway.展开更多
文摘Developing efficient neural network(NN)computing systems is crucial in the era of artificial intelligence(AI).Traditional von Neumann architectures have both the issues of"memory wall"and"power wall",limiting the data transfer between memory and processing units[1,2].Compute-in-memory(CIM)technologies,particularly analogue CIM with memristor crossbars,are promising because of their high energy efficiency,computational parallelism,and integration density for NN computations[3].In practical applications,analogue CIM excels in tasks like speech recognition and image classification,revealing its unique advantages.For instance,it efficiently processes vast amounts of audio data in speech recognition,achieving high accuracy with minimal power consumption.In image classification,the high parallelism of analogue CIM significantly speeds up feature extraction and reduces processing time.With the boosting development of AI applications,the demands for computational accuracy and task complexity are rising continually.However,analogue CIM systems are limited in handling complex regression tasks with needs of precise floating-point(FP)calculations.They are primarily suited for the classification tasks with low data precision and a limited dynamic range[4].
文摘This essay will reexamine research on the relationship between human memory and addiction. This paper will review several studies that discussed how memory systems in the human brain are involved in the acquisition of behavior that is learned and is associated with the development of drug addiction and drug relapse. Additional information reveals that when individuals make the transition from recreational drug or impulsive use to compulsive drug abuse, which may result in a neuroanatomical change in areas of the brain from cognitive control guided by the hippocampus/dorsomedial striatum towards conditioned control of behavior managed by the dorsolateral striatum (DLS) [1]. This review also looked at studies that involved experiments with humans and lower animals, which suggested that the hippocampus mediates a cognitive/spatial type of memory, while the dorsal striatum manages stimulus-response (S-R) habit memory, and the amygdala governs the classical conditioning form of learning and stimulus-affective-associative relationships [1]. Overall, these studies utilize the hypothesis of the memory systems view of addiction, and the involvement of learning and memory in the context of drug addiction, which was proposed by them [2]. This theory has been proposed in response to drug addiction research and includes alcohol, amphetamine, and cocaine [1]. The research also explains how stress and anxiety can play a role in how strong emotional excitement can lead to dependent habit memory in rodents and humans [1]. .
基金Supported by Innovative Program of Chinese Academy of Sciences (No. KGCY-SYW-407-02)Grand International Cooperation Foundation of Shanghai Science and Technology Commission (No. 052207046)
文摘A fault-tolerant spaceborne mass memory architecture is presented based on entirely commercial-off-theshelf components.The highly modularized and scalable memory kernel supports the hierarchical design and is well suited to redundancy structure.Error correcting code(ECC) and periodical scrubbing are used to deal with bit errors induced by single event upset.For 8-bit wide devices, the parallel Reed Solomon(10, 8) can perform coder/decoder calculations in one clock cycle, achieving a data rate of several Gb/...
基金supported by the National Natural Science Foundation of China(11101333 and 11302172)the Natural Science Foundation of Shaanxi(2011GQ1018)the Northwestern Polytechnical University Foundation for Fundamental Research(JC201152)
文摘The diffusion behavior driven by bounded noise under the influence of a coupled harmonic potential is investigated in a two-dimensional coupled-damped model. With the help of the Laplace analysis we obtain exact descriptions for a particle’s two-time dynamics which is subjected to a coupled harmonic potential and a coupled damping. The time lag is used to describe the velocity autocorrelation function and mean square displacement of the diffusing particle. The diffusion behavior for the time lag is also discussed with respect to the coupled items and the amplitude of bounded noise.
文摘BACKGROUND Cognitive impairment is a major cause of disability in patients who have suffered from a stroke,and cognitive rehabilitation interventions show promise for improving memory.AIM To examine the effectiveness of virtual reality(VR)and non-VR(NVR)cognitive rehabilitation techniques for improving memory in patients after stroke.METHODS An extensive and thorough search was executed across five pertinent electronic databases:Cumulative Index to Nursing and Allied Health Literature;MEDLINE(PubMed);Scopus;ProQuest Central;and Google Scholar.This systematic review was conducted following the preferred reporting items for systematic reviews and meta-analyses guideline.Studies that recruited participants who experienced a stroke,utilized cognitive rehabilitation interventions,and published in the last 10 years were included in the review.RESULTS Thirty studies met the inclusion criteria.VR interventions significantly improved memory and cognitive function(mean difference:4.2±1.3,P<0.05),whereas NVR(including cognitive training,music,and exercise)moderately improved memory.Compared with traditional methods,technology-driven VR approaches were particularly beneficial for enhancing daily cognitive tasks.CONCLUSION VR and NVR reality interventions are beneficial for post-stroke cognitive recovery,with VR providing enhanced immersive experiences.Both approaches hold transformative potential for post-stroke rehabilitation.
基金Supported by Shanghai Municipal Health Commission’s Special Clinical Research Project for the Hygiene Industry,No.20244Y0041Youth Initiation Fund of Naval Medical University,No.2023QN028 and No.2023QN030。
文摘BACKGROUND Working memory serves as a fundamental cognitive function that substantially impacts performance in various cognitive tasks.Extensive neurophysiological research has established that theta oscillations(4-8 Hz)play an essential role in supporting working memory operations.Theta-band transcranial alternating current stimulation(tACS)offers a potential mechanism for working memory enhancement through direct modulation of these fundamental neural oscillations.Nevertheless,current empirical evidence shows substantial variability in the observed effects of theta-tACS across studies.AIM To conduct a systematic review and meta-analysis evaluating the effects of thetatACS on working memory performance in healthy adults.METHODS A systematic literature search was performed on PubMed,EMBASE,and Web of Science up to March 10,2025.Effect sizes were computed using Hedges’g with 95%confidence intervals(CIs),with separate meta-analyses for all included studies and for distinct working memory paradigms[n-back and delayed matchto-sample(DMTS)tasks]to examine potential task-specific effects.Subgroup analyses and meta-regression were performed to evaluate the influence of key moderating variables.RESULTS The systematic review included 21 studies(67 effect sizes).Initial meta-analysis showed theta-tACS moderately improved working memory(Hedges’g=0.405,95%CI:0.212-0.598).However,this effect became nonsignificant after correcting for publication bias(trim-and-fill adjusted Hedges’g=0.082,95%CI:-0.052 to 0.217).Task-specific analyses revealed significant benefits in n-back tasks(Hedges’g=0.463,95%CI:0.193-0.733)but not in DMTS tasks(Hedges’g=0.257,95%CI:-0.186 to 0.553).Moderator analyses showed that performance in n-back tasks was influenced by stimulation frequency(P=0.001),concurrent status(P=0.014),task modality(P=0.005),and duration(P=0.013),whereas only the region of targeted stimulation(P=0.012)moderated DMTS tasks.CONCLUSION Theta-tACS enhances working memory in healthy adults,with effects modulated by the task type and protocol parameters,offering dual implications for cognitive enhancement and clinical interventions.
文摘After billions of years of evolution,biological intelligence has converged on unrivalled energy efficiency and environmental adaptability.The human brain,for instance,is highly efficient in information transmission,consuming only about 20 W onaverage in a resting state[1,2].A key to this efficiency is that biological signal transduction and processing rely significantly on multi-ions as the signal carriers.Inspired by this paradigm.
基金Supported by the National Natural Science Foundation of China(Grant Nos.11961059,1210502)the University Innovation Project of Gansu Province(Grant No.2023B-062)the Gansu Province Basic Research Innovation Group Project(Grant No.23JRRA684).
文摘The goal of this paper is to investigate the long-time dynamics of solutions to a Kirchhoff type suspension bridge equation with nonlinear damping and memory term.For this problem we establish the well-posedness and existence of uniform attractor under some suitable assumptions on the nonlinear term g(u),the nonlinear damping f(u_(t))and the external force h(x,t).Specifically,the asymptotic compactness of the semigroup is verified by the energy reconstruction method.
基金supported by the National Natural Science Foundation of China,Nos.82304990(to NY),81973748(to JC),82174278(to JC)the National Key R&D Program of China,No.2023YFE0209500(to JC)+4 种基金China Postdoctoral Science Foundation,No.2023M732380(to NY)Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine,No.202102010014(to JC)Huang Zhendong Research Fund for Traditional Chinese Medicine of Jinan University,No.201911(to JC)National Innovation and Entrepreneurship Training Program for Undergraduates in China,No.202310559128(to NY and QM)Innovation and Entrepreneurship Training Program for Undergraduates at Jinan University,Nos.CX24380,CX24381(both to NY and QM)。
文摘Early life stress correlates with a higher prevalence of neurological disorders,including autism,attention-deficit/hyperactivity disorder,schizophrenia,depression,and Parkinson's disease.These conditions,primarily involving abnormal development and damage of the dopaminergic system,pose significant public health challenges.Microglia,as the primary immune cells in the brain,are crucial in regulating neuronal circuit development and survival.From the embryonic stage to adulthood,microglia exhibit stage-specific gene expression profiles,transcriptome characteristics,and functional phenotypes,enhancing the susceptibility to early life stress.However,the role of microglia in mediating dopaminergic system disorders under early life stress conditions remains poorly understood.This review presents an up-to-date overview of preclinical studies elucidating the impact of early life stress on microglia,leading to dopaminergic system disorders,along with the underlying mechanisms and therapeutic potential for neurodegenerative and neurodevelopmental conditions.Impaired microglial activity damages dopaminergic neurons by diminishing neurotrophic support(e.g.,insulin-like growth factor-1)and hinders dopaminergic axon growth through defective phagocytosis and synaptic pruning.Furthermore,blunted microglial immunoreactivity suppresses striatal dopaminergic circuit development and reduces neuronal transmission.Furthermore,inflammation and oxidative stress induced by activated microglia can directly damage dopaminergic neurons,inhibiting dopamine synthesis,reuptake,and receptor activity.Enhanced microglial phagocytosis inhibits dopamine axon extension.These long-lasting effects of microglial perturbations may be driven by early life stress–induced epigenetic reprogramming of microglia.Indirectly,early life stress may influence microglial function through various pathways,such as astrocytic activation,the hypothalamic–pituitary–adrenal axis,the gut–brain axis,and maternal immune signaling.Finally,various therapeutic strategies and molecular mechanisms for targeting microglia to restore the dopaminergic system were summarized and discussed.These strategies include classical antidepressants and antipsychotics,antibiotics and anti-inflammatory agents,and herbal-derived medicine.Further investigations combining pharmacological interventions and genetic strategies are essential to elucidate the causal role of microglial phenotypic and functional perturbations in the dopaminergic system disrupted by early life stress.
基金supported by the National Natural Science Foundation of China(Grant No.62403486)。
文摘The highly dynamic nature,strong uncertainty,and coupled multiple safety constraints inherent in carrier aircraft recovery operations pose severe challenges for real-time decision-making.Addressing bolter scenarios,this study proposes an intelligent decision-making framework based on a deep long short-term memory Q-network.This framework transforms the real-time sequencing for bolter recovery problem into a partially observable Markov decision process.It employs a stacked long shortterm memory network to accurately capture the long-range temporal dependencies of bolter event chains and fuel consumption.Furthermore,it integrates a prioritized experience replay training mechanism to construct a safe and adaptive scheduling system capable of millisecond-level real-time decision-making.Experimental demonstrates that,within large-scale mass recovery scenarios,the framework achieves zero safety violations in static environments and maintains a fuel safety violation rate below 10%in dynamic scenarios,with single-step decision times at the millisecond level.The model exhibits strong generalization capability,effectively responding to unforeseen emergent situations—such as multiple bolters and fuel emergencies—without requiring retraining.This provides robust support for efficient carrier-based aircraft recovery operations.
基金supported by the National Natural Science Foundation of China(Nos.52473080,52403167 and 52173079)the Fundamental Research Funds for the Central Universities(Nos.xtr052023001 and xzy012023037)+1 种基金the Postdoctoral Research Project of Shaanxi Province(No.2024BSHSDZZ054)the Shaanxi Laboratory of Advanced Materials(No.2024ZY-JCYJ-04-12).
文摘Shape memory polymers used in 4D printing only had one permanent shape after molding,which limited their applications in requiring multiple reconstructions and multifunctional shapes.Furthermore,the inherent stability of the triazine ring structure within cyanate ester(CE)crosslinked networks after molding posed significant challenges for both recycling,repairing,and degradation of resin.To address these obstacles,dynamic thiocyanate ester(TCE)bonds and photocurable group were incorporated into CE,obtaining the recyclable and 3D printable CE covalent adaptable networks(CANs),denoted as PTCE1.5.This material exhibits a Young's modulus of 810 MPa and a tensile strength of 50.8 MPa.Notably,damaged printed PTCE1.5 objects can be readily repaired through reprinting and interface rejoining by thermal treatment.Leveraging the solid-state plasticity,PTCE1.5 also demonstrated attractive shape memory ability and permanent shape reconfigurability,enabling its reconfigurable 4D printing.The printed PTCE1.5 hinges and a main body were assembled into a deployable and retractable satellite model,validating its potential application as a controllable component in the aerospace field.Moreover,printed PTCE1.5 can be fully degraded into thiol-modified intermediate products.Overall,this material not only enriches the application range of CE resin,but also provides a reliable approach to addressing environmental issue.
基金supported by the Deanship of Research at the King Fahd University of Petroleum&Minerals,Dhahran,31261,Saudi Arabia,under Project No.EC241001.
文摘Various factors,including weak tie-lines into the electric power system(EPS)networks,can lead to low-frequency oscillations(LFOs),which are considered an instant,non-threatening situation,but slow-acting and poisonous.Considering the challenge mentioned,this article proposes a clustering-based machine learning(ML)framework to enhance the stability of EPS networks by suppressing LFOs through real-time tuning of key power system stabilizer(PSS)parameters.To validate the proposed strategy,two distinct EPS networks are selected:the single-machine infinite-bus(SMIB)with a single-stage PSS and the unified power flow controller(UPFC)coordinated SMIB with a double-stage PSS.To generate data under various loading conditions for both networks,an efficient but offline meta-heuristic algorithm,namely the grey wolf optimizer(GWO),is used,with the loading conditions as inputs and the key PSS parameters as outputs.The generated loading conditions are then clustered using the fuzzy k-means(FKM)clustering method.Finally,the group method of data handling(GMDH)and long short-term memory(LSTM)ML models are developed for clustered data to predict PSS key parameters in real time for any loading condition.A few well-known statistical performance indices(SPI)are considered for validation and robustness of the training and testing procedure of the developed FKM-GMDH and FKM-LSTM models based on the prediction of PSS parameters.The performance of the ML models is also evaluated using three stability indices(i.e.,minimum damping ratio,eigenvalues,and time-domain simulations)after optimally tuned PSS with real-time estimated parameters under changing operating conditions.Besides,the outputs of the offline(GWO-based)metaheuristic model,proposed real-time(FKM-GMDH and FKM-LSTM)machine learning models,and previously reported literature models are compared.According to the results,the proposed methodology outperforms the others in enhancing the stability of the selected EPS networks by damping out the observed unwanted LFOs under various loading conditions.
基金This work was supported by the National Basic Research 973 Program of China under Grant No. 2011CB302502, the National Natural Science Foundation of China under Grant No. 61379042, Huawei Research Program under Grant No. YB2013090048, and the Strategic Priority Research Program of Chinese Academy of Sciences under Grant No. XDA06010401.
文摘As the scaling of applications increases, the demand of main memory capacity increases in order to serve large working set. It is difficult for DRAM （dynamic random access memory） based memory system to satisfy the memory capacity requirement due to its limited scalability and high energy consumption. Compared to DRAM, PCM （phase change memory） has better scalability, lower energy leakage, and non-volatility. PCM memory systems have become a hot topic of academic and industrial research. However, PCM technology has the following three drawbacks： long write latency, limited write endurance, and high write energy, which raises challenges to its adoption in practice. This paper surveys architectural research work to optimize PCM memory systems. First, this paper introduces the background of PCM. Then, it surveys research efforts on PCM memory systems in performance optimization, lifetime improving, and energy saving in detail, respectively. This paper also compares and summarizes these techniques from multiple dimensions. Finally, it concludes these optimization techniques and discusses possible research directions of PCM memory systems in future.
基金partially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences under GrantNo.XDA06010401the National Basic Research 973 Program of China under Grant No.2011CB302502+1 种基金the National NaturalScience Foundation of China under Grant Nos.60925009,61221062,61331008the Huawei Research Program under Grant No.YBCB2011030
文摘The decades-old synchronous memory bus interface has restricted many innovations in the memory system, which is facing various challenges （or walls） in the era of multi-core and big data. In this paper, we argue that a message- based interface should be adopted to replace the traditional bus-based interface in the memory system. A novel message interface based memory system called MIMS is proposed. The key innovation of MIMS is that processors communicate with the memory system through a universal and flexible message packet interface. Each message packet is allowed to encapsulate multiple memory requests （or commands） and additional semantic information. The memory system is more intelligent and active by equipping with a local buffer scheduler, which is responsible for processing packets, scheduling memory requests, preparing responses, and executing specific commands with the help of semantic information. Under the MIMS framework, many previous innovations on memory architecture as well as new optimization opportunities such as address compression and continuous requests combination can be naturally incorporated. The experimental results on a 16-core cycle-detailed simulation system show that： with accurate granularity message, MIMS can improve system performance by 53.21% and reduce energy delay product （EDP） by 55.90%. Furthermore, it can improve effective bandwidth utilization by 62.42% and reduce memory access latency by 51% on average.
文摘Globally coupled map (GCM) model can evolve through chaotic searching into several stable periodic orbits under properly controlled parameters. This can be exploited in information processing such as associative memory and optimization. In this paper, we propose a novel covariance learning rule for multivalue patterns and apply it in memorization of gray scale images based on modified GCM model (S GCM). Analysis of retrieval results are given finally.
基金supported by the National Key R&D Plan“nano frontier”Key Special Project(grant no.2021YFA1200502)Cultivation projects of national major R&D project(grant no.92164109)+14 种基金National Natural Science Foundation of China(grant nos.61874158,62004056,and 62104058)Special Project of Strategic Leading Science and Technology of Chinese Academy of Sciences(grant no.XDB440000007)Hebei Basic Research Special Key Project(grant no.F2021201045)the Support Program for the Top Young Talents of Hebei Province(Grant no.70280011807)the Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(grant no.SLRC2019018)Interdisciplinary Research Program of Natural Science of Hebei University(DXK202101)Institute of Life Sciences and Green Development(521100311)Outstanding Young Scientific Research and Innovation Team of Hebei University(grant no.605020521001)the Natural Science Foundation of Hebei Province(F2022201054 and F2021201022)Special Support Funds for National High Level Talents(grant no.041500120001)the Advanced Talents Incubation Program of the Hebei University(521000981426,521100221071,and 521000981363)funded by Science and Technology Project of Hebei Education Department(grant nos.QN2020178 and QN2021026)Baoding Science and Technology Plan Project(2172P011 and 2272P014)Hebei Youth Fund Project(A2021201048)Post-graduate's Innovation Fund Project of Hebei Province(CXZZSS2023001).
文摘Biologically inspired neuromorphic sensory memory systems based on memristor have received a lot of attention in the booming artificial intelligence industry due to significant potential to effectively process multi-sensory signals from complex external environments.However,many memristors have significant switching parameters disperse,which is a great challenge for using memristors in bionic neuromorphic sensory memory systems.Herein,a stable ferroelectric memristor based on the Pd/BaTiO_(3):Eu2O_(3)/La0.67Sr0.33MnO_(3)grown on Silicon structure with SrTiO_(3)as buffer layer is presented.The device possesses low coercive field voltage(-1.3-2.1 V)and robust endurance characteristic(~10^(10)cycles)through optimizing the growth temperature.More importantly,an ultra-stable artificial multimodal sensory memory system with visual and tactile functions was reported for the first time by combining a pressure sensor,a photosensitive sensor,and a robotic arm.Utilizing the above system,the sensitivity value of the system is expressed by the conductance of the memristor to realize the gradual change of external stimulus,and multi signals inputs at the same time to this system have faithfully achieved sensory adaptation to multimodal sensors.This work paves the way for future development of memristor-based perception systems in efficient multisensory neural robots.
基金supported in part by National Natural Science Foundation of China(62125202).
文摘The appearance and wide use of memory hardware bring significant changes to the conventional vertical memory hierarchy that fails to handle contentions for shared hardware resources and expensive data movements.To deal with these problems,existing schemes have to rely on inefficient scheduling strategies that also cause extra temporal,spatial and bandwidth overheads.Based on the insights that the shared hardware resources trend to be uniformly and hierarchically offered to the requests for co-located applications in memory systems,we present an efficient abstraction of memory hierarchies,called Label,which is used to establish the connection between the application layer and underlying hardware layer.Based on labels,our paper proposes LaMem,a labeled,resource-isolated and cross-tiered memory system by leveraging the way-based partitioning technique for shared resources to guarantee QoS demands of applications,while supporting fast and low-overhead cache repartitioning technique.Besides,we customize LaMem for the learned index that fundamentally replaces storage structures with computation models as a case study to verify the applicability of LaMem.Experimental results demonstrate the efficiency and efficacy of LaMem.
文摘Phase change memory （PCM） is a promising technology for future memory thanks to its better scalability and lower leakage power than DRAM （dynamic random-access memory）. However, adopting PCM as main memory needs to overcome its write issues, such as long write latency and high write power. In this paper, we propose two techniques to improve the performance and energy-efficiency of PCM memory systems. First, we propose a victim cache technique utilizing the existing buffer in the memory controller to reduce PCM memory accesses. The key idea is reorganizing the buffer into a victim cache structure （RBC） to provide additional hits for the LLC （last level cache）. Second, we propose a chip parallelism-aware replacement policy （CPAR） for the victim cache to further improve performance. Instead of evicting one cache line once, CPAR evicts multiple cache lines that access different PCM chips. CPAR can reduce the frequent victim cache eviction and improve the write parallelism of PCM chips. The evaluation results show that, compared with the baseline, RBC can improve PCM memory system performance by up to 9.4% and 5.4% on average. Combing CPAR with RBC （RBC＋CPAR） can improve performance by up to 19.0% and 12.1% on average. Moreover, RBC and RBC＋CPAR can reduce memory energy consumption by 8.3% and 6.6% on average, respectively.
文摘Page migration has long been adopted in hybrid memory systems comprising dynamic random access memory(DRAM)and non-volatile memories(NVMs),to improve the system performance and energy efficiency.However,page migration introduces some side effects,such as more translation lookaside buffer(TLB)misses,breaking memory contiguity,and extra memory accesses due to page table updating.In this paper,we propose superpagefriendly page table called SuperPT to reduce the performance overhead of serving TLB misses.By leveraging a virtual hashed page table and a hybrid DRAM allocator,SuperPT performs address translations in a flexible and efficient way while still remaining the contiguity within the migrated pages.
基金Supported by a Grant from the National Natural Sciences Foundation of China(No.30973792)
文摘OBJECTIVE: To investigate the effects of combined acupuncture and eugenol on learning-memory ability and the antioxidation system of the hippocampus in Alzheimer disease (AD) rats. METHODS: Sixty Sprague Dawley rats, weighing (300±10) g, were randomly divided with 10 rats per group into a normal control group, AD model group, AD with cut olfactory nerve group, Xiu three-needle group, eugenol group, and combined acupuncture and eugenol group. The AD model was established by injection of amyloid β1-40 (Aβ 1-40). Morris maze tests were conducted for evaluating the learning-memory ability. Content of malo- ndialdehyde (MDA) and activities of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) in the hippocampus were detected. RESULTS: The average escape latency and the mean swimming distance in the normal control group, the Xiu three-needle group, the eugenol group, and the combined acupuncture and euge-nol group were significantly shorter than those in the AD model group (all P<0.01). The combined acupuncture and eugenol group had shorter escape latency and mean swimming distance than those in the Xiu three-needle group and the eugenol group. There were no significant differences between the Xiu three-needle group and the eugenol group and between the AD group and the AD with cut olfactory nerve group (P>0.05). Compared with the normal control group, the MDA content in the hippocampus significantly increased (P<0.05) and GSH-Px and SOD activities significantly decreased in the AD model group (P<0.01). Compared with the AD model group, significantly decreased (P< 0.01) and SOD and GSH-Px activities significantly increased in the Xiu three-needle group, eugenol group, and combined acupuncture and eugenol group (P<0.05). Compared with the Xiu three-needle group and eugenol group, the MDA content significantly decreased (P<0.05) and SOD and GSH-Px activities increased (P<0.05) in the combined acupuncture and eugenol group. There were no significant differences among the three indices between the Xiu three-needle group and the eugenol group and between the AD model group and the AD with cut olfactory nerve group (P>0.05). CONCLUSION: Both Xiu three-needle and eugenol can increase learning-memory ability, decrease MDA content, and increase SOD and GSH-Px activities in the hippocampus in AD rats. The combination of acupuncture with eugenol has stronger effects, and the effects depend on the olfactory pathway.
