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
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
This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide...This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.展开更多
Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While suc...Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While such a computing paradigm can only employ a single photonic device as the nonlinear node for data processing,the performance highly relies on the fading memory provided by the delay feedback loop(FL),which sets a restriction on the extensibility of physical implementation,especially for highly integrated chips.Here,we present a simplified photonic scheme for more flexible parameter configurations leveraging the designed quasi-convolution coding(QC),which completely gets rid of the dependence on FL.Unlike delay-based TDRC,encoded data in QC-based RC(QRC)enables temporal feature extraction,facilitating augmented memory capabilities.Thus,our proposed QRC is enabled to deal with time-related tasks or sequential data without the implementation of FL.Furthermore,we can implement this hardware with a low-power,easily integrable vertical-cavity surface-emitting laser for high-performance parallel processing.We illustrate the concept validation through simulation and experimental comparison of QRC and TDRC,wherein the simpler-structured QRC outperforms across various benchmark tasks.Our results may underscore an auspicious solution for the hardware implementation of deep neural networks.展开更多
Background:Over the past few decades,a threefold increase in obesity and type 2 diabetes(T2D)has placed a heavy burden on the health-care system and society.Previous studies have shown correlations between obesity,T2D...Background:Over the past few decades,a threefold increase in obesity and type 2 diabetes(T2D)has placed a heavy burden on the health-care system and society.Previous studies have shown correlations between obesity,T2D,and neurodegenera-tive diseases,including dementia.It is imperative to further understand the relation-ship between obesity,T2D,and cognitive deficits.Methods:This investigation tested and evaluated the cognitive impact of obesity and T2D induced by high-fat diet(HFD)and the effect of the host genetic background on the severity of cognitive decline caused by obesity and T2D in collaborative cross(CC)mice.The CC mice are a genetically diverse panel derived from eight inbred strains.Results:Our findings demonstrated significant variations in the recorded phenotypes across different CC lines compared to the reference mouse line,C57BL/6J.CC037 line exhibited a substantial increase in body weight on HFD,whereas line CC005 ex-hibited differing responses based on sex.Glucose tolerance tests revealed significant variations,with some lines like CC005 showing a marked increase in area under the curve(AUC)values on HFD.Organ weights,including brain,spleen,liver,and kidney,varied significantly among the lines and sexes in response to HFD.Behavioral tests using the Morris water maze indicated that cognitive performance was differentially affected by diet and genetic background.Conclusions:Our study establishes a foundation for future quantitative trait loci map-ping using CC lines and identifying genes underlying the comorbidity of Alzheimer's disease(AD),caused by obesity and T2D.The genetic components may offer new tools for early prediction and prevention.展开更多
Real-time prediction and precise control of sinter quality are pivotal for energy saving,cost reduction,quality improvement and efficiency enhancement in the ironmaking process.To advance,the accuracy and comprehensiv...Real-time prediction and precise control of sinter quality are pivotal for energy saving,cost reduction,quality improvement and efficiency enhancement in the ironmaking process.To advance,the accuracy and comprehensiveness of sinter quality prediction,an intelligent flare monitoring system for sintering machine tails that combines hybrid neural networks integrating convolutional neural network with long short-term memory(CNN-LSTM)networks was proposed.The system utilized a high-temperature thermal imager for image acquisition at the sintering machine tail and employed a zone-triggered method to accurately capture dynamic feature images under challenging conditions of high-temperature,high dust,and occlusion.The feature images were then segmented through a triple-iteration multi-thresholding approach based on the maximum between-class variance method to minimize detail loss during the segmentation process.Leveraging the advantages of CNN and LSTM networks in capturing temporal and spatial information,a comprehensive model for sinter quality prediction was constructed,with inputs including the proportion of combustion layer,porosity rate,temperature distribution,and image features obtained from the convolutional neural network,and outputs comprising quality indicators such as underburning index,uniformity index,and FeO content of the sinter.The accuracy is notably increased,achieving a 95.8%hit rate within an error margin of±1.0.After the system is applied,the average qualified rate of FeO content increases from 87.24%to 89.99%,representing an improvement of 2.75%.The average monthly solid fuel consumption is reduced from 49.75 to 46.44 kg/t,leading to a 6.65%reduction and underscoring significant energy saving and cost reduction effects.展开更多
This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as o...This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as other transformer-based models including Token to Token ViT,ViT withoutmemory,and Parallel ViT.Leveraging awidely-used steel surface defect dataset,the research applies data augmentation and t-distributed stochastic neighbor embedding(t-SNE)to enhance feature extraction and understanding.These techniques mitigated overfitting,stabilized training,and improved generalization capabilities.The LMViT model achieved a test accuracy of 97.22%,significantly outperforming ResNet18(88.89%)and ResNet50(88.90%),aswell as the Token to TokenViT(88.46%),ViT without memory(87.18),and Parallel ViT(91.03%).Furthermore,LMViT exhibited superior training and validation performance,attaining a validation accuracy of 98.2%compared to 91.0%for ResNet 18,96.0%for ResNet50,and 89.12%,87.51%,and 91.21%for Token to Token ViT,ViT without memory,and Parallel ViT,respectively.The findings highlight the LMViT’s ability to capture long-range dependencies in images,an areawhere CNNs struggle due to their reliance on local receptive fields and hierarchical feature extraction.The additional transformer-based models also demonstrate improved performance in capturing complex features over CNNs,with LMViT excelling particularly at detecting subtle and complex defects,which is critical for maintaining product quality and operational efficiency in industrial applications.For instance,the LMViT model successfully identified fine scratches and minor surface irregularities that CNNs often misclassify.This study not only demonstrates LMViT’s potential for real-world defect detection but also underscores the promise of other transformer-based architectures like Token to Token ViT,ViT without memory,and Parallel ViT in industrial scenarios where complex spatial relationships are key.Future research may focus on enhancing LMViT’s computational efficiency for deployment in real-time quality control systems.展开更多
N6-methyladenosine(m^(6)A), the most prevalent and conserved RNA modification in eukaryotic cells, profoundly influences virtually all aspects of mRNA metabolism. mRNA plays crucial roles in neural stem cell genesis a...N6-methyladenosine(m^(6)A), the most prevalent and conserved RNA modification in eukaryotic cells, profoundly influences virtually all aspects of mRNA metabolism. mRNA plays crucial roles in neural stem cell genesis and neural regeneration, where it is highly concentrated and actively involved in these processes. Changes in m^(6)A modification levels and the expression levels of related enzymatic proteins can lead to neurological dysfunction and contribute to the development of neurological diseases. Furthermore, the proliferation and differentiation of neural stem cells, as well as nerve regeneration, are intimately linked to memory function and neurodegenerative diseases. This paper presents a comprehensive review of the roles of m^(6)A in neural stem cell proliferation, differentiation, and self-renewal, as well as its implications in memory and neurodegenerative diseases. m^(6)A has demonstrated divergent effects on the proliferation and differentiation of neural stem cells. These observed contradictions may arise from the time-specific nature of m^(6)A and its differential impact on neural stem cells across various stages of development. Similarly, the diverse effects of m^(6)A on distinct types of memory could be attributed to the involvement of specific brain regions in memory formation and recall. Inconsistencies in m^(6)A levels across different models of neurodegenerative disease, particularly Alzheimer's disease and Parkinson's disease, suggest that these disparities are linked to variations in the affected brain regions. Notably, the opposing changes in m^(6)A levels observed in Parkinson's disease models exposed to manganese compared to normal Parkinson's disease models further underscore the complexity of m^(6)A's role in neurodegenerative processes. The roles of m^(6)A in neural stem cell proliferation, differentiation, and self-renewal, and its implications in memory and neurodegenerative diseases, appear contradictory. These inconsistencies may be attributed to the timespecific nature of m^(6)A and its varying effects on distinct brain regions and in different environments.展开更多
Cerebral ischemia is a major health risk that requires preventive approaches in addition to drug therapy.Physical exercise enhances neurogenesis and synaptogenesis,and has been widely used for functional rehabilitatio...Cerebral ischemia is a major health risk that requires preventive approaches in addition to drug therapy.Physical exercise enhances neurogenesis and synaptogenesis,and has been widely used for functional rehabilitation after stroke.In this study,we determined whether exercise training before disease onset can alleviate the severity of cerebral ischemia.We also examined the role of exercise-induced circulating factors in these effects.Adult mice were subjected to 14 days of treadmill exercise training before surgery for middle cerebral artery occlusion.We found that this exercise pre-conditioning strategy effectively attenuated brain infarct area,inhibited gliogenesis,protected synaptic proteins,and improved novel object and spatial memory function.Further analysis showed that circulating adiponectin plays a critical role in these preventive effects of exercise.Agonist activation of adiponectin receptors by Adipo Ron mimicked the effects of exercise,while inhibiting receptor activation abolished the exercise effects.In summary,our results suggest a crucial role of circulating adiponectin in the effects of exercise pre-conditioning in protecting against cerebral ischemia and supporting the health benefits of exercise.展开更多
Postoperative cognitive dysfunction is a seve re complication of the central nervous system that occurs after anesthesia and surgery,and has received attention for its high incidence and effect on the quality of life ...Postoperative cognitive dysfunction is a seve re complication of the central nervous system that occurs after anesthesia and surgery,and has received attention for its high incidence and effect on the quality of life of patients.To date,there are no viable treatment options for postoperative cognitive dysfunction.The identification of postoperative cognitive dysfunction hub genes could provide new research directions and therapeutic targets for future research.To identify the signaling mechanisms contributing to postoperative cognitive dysfunction,we first conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the Gene Expression Omnibus GSE95426 dataset,which consists of mRNAs and long non-coding RNAs differentially expressed in mouse hippocampus3 days after tibial fracture.The dataset was enriched in genes associated with the biological process"regulation of immune cells,"of which Chill was identified as a hub gene.Therefore,we investigated the contribution of chitinase-3-like protein 1 protein expression changes to postoperative cognitive dysfunction in the mouse model of tibial fractu re surgery.Mice were intraperitoneally injected with vehicle or recombinant chitinase-3-like protein 124 hours post-surgery,and the injection groups were compared with untreated control mice for learning and memory capacities using the Y-maze and fear conditioning tests.In addition,protein expression levels of proinflammatory factors(interleukin-1βand inducible nitric oxide synthase),M2-type macrophage markers(CD206 and arginase-1),and cognition-related proteins(brain-derived neurotropic factor and phosphorylated NMDA receptor subunit NR2B)were measured in hippocampus by western blotting.Treatment with recombinant chitinase-3-like protein 1 prevented surgery-induced cognitive impairment,downregulated interleukin-1βand nducible nitric oxide synthase expression,and upregulated CD206,arginase-1,pNR2B,and brain-derived neurotropic factor expression compared with vehicle treatment.Intraperitoneal administration of the specific ERK inhibitor PD98059 diminished the effects of recombinant chitinase-3-like protein 1.Collectively,our findings suggest that recombinant chitinase-3-like protein 1 ameliorates surgery-induced cognitive decline by attenuating neuroinflammation via M2 microglial polarization in the hippocampus.Therefore,recombinant chitinase-3-like protein1 may have therapeutic potential fo r postoperative cognitive dysfunction.展开更多
The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because o...The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution framework.However,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale DPFSPs.As a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the mini-malmakespan.InMLIGA,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous solutions.In addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory mechanism.Meanwhile,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom rules.At last,a discrete adaptive learning rate is employed to enhance the stability of the memory and learningmechanisms.Complete ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large extent.Furthermore,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale DPFSPs.This indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.展开更多
Hippocampal neuronal loss causes cognitive dysfunction in Alzheimer’s disease.Adult hippocampal neurogenesis is reduced in patients with Alzheimer’s disease.Exercise stimulates adult hippocampal neurogenesis in rode...Hippocampal neuronal loss causes cognitive dysfunction in Alzheimer’s disease.Adult hippocampal neurogenesis is reduced in patients with Alzheimer’s disease.Exercise stimulates adult hippocampal neurogenesis in rodents and improves memory and slows cognitive decline in patients with Alzheimer’s disease.However,the molecular pathways for exercise-induced adult hippocampal neurogenesis and improved cognition in Alzheimer’s disease are poorly understood.Recently,regulator of G protein signaling 6(RGS6)was identified as the mediator of voluntary running-induced adult hippocampal neurogenesis in mice.Here,we generated novel RGS6fl/fl;APP_(SWE) mice and used retroviral approaches to examine the impact of RGS6 deletion from dentate gyrus neuronal progenitor cells on voluntary running-induced adult hippocampal neurogenesis and cognition in an amyloid-based Alzheimer’s disease mouse model.We found that voluntary running in APP_(SWE) mice restored their hippocampal cognitive impairments to that of control mice.This cognitive rescue was abolished by RGS6 deletion in dentate gyrus neuronal progenitor cells,which also abolished running-mediated increases in adult hippocampal neurogenesis.Adult hippocampal neurogenesis was reduced in sedentary APP_(SWE) mice versus control mice,with basal adult hippocampal neurogenesis reduced by RGS6 deletion in dentate gyrus neural precursor cells.RGS6 was expressed in neurons within the dentate gyrus of patients with Alzheimer’s disease with significant loss of these RGS6-expressing neurons.Thus,RGS6 mediated voluntary running-induced rescue of impaired cognition and adult hippocampal neurogenesis in APP_(SWE) mice,identifying RGS6 in dentate gyrus neural precursor cells as a possible therapeutic target in Alzheimer’s disease.展开更多
(TiZrHf)_(50)Ni_(30)Cu_(20-x)Co_(x)(x=2,4,6,at%)high-entropy high-temperature shape memory alloys were fabricated by watercooled copper crucible in a magnetic levitation vacuum melting furnace,and the effects of Co co...(TiZrHf)_(50)Ni_(30)Cu_(20-x)Co_(x)(x=2,4,6,at%)high-entropy high-temperature shape memory alloys were fabricated by watercooled copper crucible in a magnetic levitation vacuum melting furnace,and the effects of Co content on microstructure and mechanical properties were investigated.The results indicate that the grain size of the alloy decreases with increasing the Co content.In the as-cast state,the alloy consists primarily of the B19′phase,with a trace of B2 phase.The fracture morphology is predominantly composed of the B19′phase,whereas the B2 phase is nearly absent.Increasing the Co content or reducing the sample dimensions(d)markedly enhance the compressive strength and ductility of the alloy.When d=2 mm,the(TiZrHf)_(50)Ni_(30)Cu_(14)Co_(6) alloy demonstrates the optimal mechanical properties,achieving a compressive strength of 2142.39±1.8 MPa and a plasticity of 17.31±0.3%.The compressive cyclic test shows that with increasing the compressive strain,the residual strain of the(TiZrHf)_(50)Ni_(30)Cu_(14)Co_(6) alloy increases while the recovery ability declines.The superelastic recovery capability of the alloy is continuously enhanced.The superelastic recovery rate increases from 1.36%to 2.12%,the residual strain rate rises from 1.79%to 5.52%,the elastic recovery rate ascends from 3.86%to 7.36%,while the total recovery rate declines from 74.48%to 63.20%.展开更多
The memory behavior in liquid crystals(LCs)that is characterized by low cost,large area,high speed,and high-density memory has evolved from a mere scientific curiosity to a technology that is being applied in a variet...The memory behavior in liquid crystals(LCs)that is characterized by low cost,large area,high speed,and high-density memory has evolved from a mere scientific curiosity to a technology that is being applied in a variety of commodities.In this study,we utilized molybdenum disulfide(MoS_(2))nanoflakes as the vip in a homotropic LCs host to modulate the overall memory effect of the hybrid.It was found that the MoS₂nanoflakes within the LCs host formed agglomerates,which in turn resulted in an accelerated response of the hybrids to the external electric field.However,this process also resulted in a slight decrease in the threshold voltage.Additionally,it was observed that MoS₂nanoflakes in a LCs host tend to align homeotropically under an external electric field,thereby accelerating the refreshment of the memory behavior.The incorporation of a mass fraction of 0.1%2μm MoS₂nanoflakes into the LCs host was found to significantly reduce the refreshing memory behavior in the hybrid to 94.0 s under an external voltage of 5 V.These findings illustrate the efficacy of regulating the rate of memory behavior for a variety of potential applications.展开更多
As a typical in-memory computing hardware design, nonvolatile ternary content-addressable memories(TCAMs) enable the logic operation and data storage for high throughout in parallel big data processing. However,TCAM c...As a typical in-memory computing hardware design, nonvolatile ternary content-addressable memories(TCAMs) enable the logic operation and data storage for high throughout in parallel big data processing. However,TCAM cells based on conventional silicon-based devices suffer from structural complexity and large footprintlimitations. Here, we demonstrate an ultrafast nonvolatile TCAM cell based on the MoTe2/hBN/multilayergraphene (MLG) van der Waals heterostructure using a top-gated partial floating-gate field-effect transistor(PFGFET) architecture. Based on its ambipolar transport properties, the carrier type in the source/drain andcentral channel regions of the MoTe2 channel can be efficiently tuned by the control gate and top gate, respectively,enabling the reconfigurable operation of the device in either memory or FET mode. When working inthe memory mode, it achieves an ultrafast 60 ns programming/erase speed with a current on-off ratio of ∼105,excellent retention capability, and robust endurance. When serving as a reconfigurable transistor, unipolar p-typeand n-type FETs are obtained by adopting ultrafast 60 ns control-gate voltage pulses with different polarities.The monolithic integration of memory and logic within a single device enables the content-addressable memory(CAM) functionality. Finally, by integrating two PFGFETs in parallel, a TCAM cell with a high current ratioof ∼10^(5) between the match and mismatch states is achieved without requiring additional peripheral circuitry.These results provide a promising route for the design of high-performance TCAM devices for future in-memorycomputing applications.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.
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.
基金supported by the National Natural Science Foundation of China(61973105,62373137)。
文摘This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution algorithm.To provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical data.Sufficient conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack matrices.Subsequently,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect.Finally,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.
基金National Natural Science Foundation of China(62171305,62405206,62004135,62001317,62111530301)Natural Science Foundation of Jiangsu Province(BK20240778,BK20241917)+3 种基金State Key Laboratory of Advanced Optical Communication Systems and Networks,China(2023GZKF08)China Postdoctoral Science Foundation(2024M752314)Postdoctoral Fellowship Program of CPSF(GZC20231883)Innovative and Entrepreneurial Talent Program of Jiangsu Province(JSSCRC2021527).
文摘Photonic platforms are gradually emerging as a promising option to encounter the ever-growing demand for artificial intelligence,among which photonic time-delay reservoir computing(TDRC)is widely anticipated.While such a computing paradigm can only employ a single photonic device as the nonlinear node for data processing,the performance highly relies on the fading memory provided by the delay feedback loop(FL),which sets a restriction on the extensibility of physical implementation,especially for highly integrated chips.Here,we present a simplified photonic scheme for more flexible parameter configurations leveraging the designed quasi-convolution coding(QC),which completely gets rid of the dependence on FL.Unlike delay-based TDRC,encoded data in QC-based RC(QRC)enables temporal feature extraction,facilitating augmented memory capabilities.Thus,our proposed QRC is enabled to deal with time-related tasks or sequential data without the implementation of FL.Furthermore,we can implement this hardware with a low-power,easily integrable vertical-cavity surface-emitting laser for high-performance parallel processing.We illustrate the concept validation through simulation and experimental comparison of QRC and TDRC,wherein the simpler-structured QRC outperforms across various benchmark tasks.Our results may underscore an auspicious solution for the hardware implementation of deep neural networks.
文摘Background:Over the past few decades,a threefold increase in obesity and type 2 diabetes(T2D)has placed a heavy burden on the health-care system and society.Previous studies have shown correlations between obesity,T2D,and neurodegenera-tive diseases,including dementia.It is imperative to further understand the relation-ship between obesity,T2D,and cognitive deficits.Methods:This investigation tested and evaluated the cognitive impact of obesity and T2D induced by high-fat diet(HFD)and the effect of the host genetic background on the severity of cognitive decline caused by obesity and T2D in collaborative cross(CC)mice.The CC mice are a genetically diverse panel derived from eight inbred strains.Results:Our findings demonstrated significant variations in the recorded phenotypes across different CC lines compared to the reference mouse line,C57BL/6J.CC037 line exhibited a substantial increase in body weight on HFD,whereas line CC005 ex-hibited differing responses based on sex.Glucose tolerance tests revealed significant variations,with some lines like CC005 showing a marked increase in area under the curve(AUC)values on HFD.Organ weights,including brain,spleen,liver,and kidney,varied significantly among the lines and sexes in response to HFD.Behavioral tests using the Morris water maze indicated that cognitive performance was differentially affected by diet and genetic background.Conclusions:Our study establishes a foundation for future quantitative trait loci map-ping using CC lines and identifying genes underlying the comorbidity of Alzheimer's disease(AD),caused by obesity and T2D.The genetic components may offer new tools for early prediction and prevention.
基金founded by the Open Project Program of Anhui Province Key Laboratory of Metallurgical Engineering and Resources Recycling(Anhui University of Technology)(No.SKF21-06)Research Fund for Young Teachers of Anhui University of Technology in 2020(No.QZ202001).
文摘Real-time prediction and precise control of sinter quality are pivotal for energy saving,cost reduction,quality improvement and efficiency enhancement in the ironmaking process.To advance,the accuracy and comprehensiveness of sinter quality prediction,an intelligent flare monitoring system for sintering machine tails that combines hybrid neural networks integrating convolutional neural network with long short-term memory(CNN-LSTM)networks was proposed.The system utilized a high-temperature thermal imager for image acquisition at the sintering machine tail and employed a zone-triggered method to accurately capture dynamic feature images under challenging conditions of high-temperature,high dust,and occlusion.The feature images were then segmented through a triple-iteration multi-thresholding approach based on the maximum between-class variance method to minimize detail loss during the segmentation process.Leveraging the advantages of CNN and LSTM networks in capturing temporal and spatial information,a comprehensive model for sinter quality prediction was constructed,with inputs including the proportion of combustion layer,porosity rate,temperature distribution,and image features obtained from the convolutional neural network,and outputs comprising quality indicators such as underburning index,uniformity index,and FeO content of the sinter.The accuracy is notably increased,achieving a 95.8%hit rate within an error margin of±1.0.After the system is applied,the average qualified rate of FeO content increases from 87.24%to 89.99%,representing an improvement of 2.75%.The average monthly solid fuel consumption is reduced from 49.75 to 46.44 kg/t,leading to a 6.65%reduction and underscoring significant energy saving and cost reduction effects.
基金funded by Woosong University Academic Research 2024.
文摘This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as other transformer-based models including Token to Token ViT,ViT withoutmemory,and Parallel ViT.Leveraging awidely-used steel surface defect dataset,the research applies data augmentation and t-distributed stochastic neighbor embedding(t-SNE)to enhance feature extraction and understanding.These techniques mitigated overfitting,stabilized training,and improved generalization capabilities.The LMViT model achieved a test accuracy of 97.22%,significantly outperforming ResNet18(88.89%)and ResNet50(88.90%),aswell as the Token to TokenViT(88.46%),ViT without memory(87.18),and Parallel ViT(91.03%).Furthermore,LMViT exhibited superior training and validation performance,attaining a validation accuracy of 98.2%compared to 91.0%for ResNet 18,96.0%for ResNet50,and 89.12%,87.51%,and 91.21%for Token to Token ViT,ViT without memory,and Parallel ViT,respectively.The findings highlight the LMViT’s ability to capture long-range dependencies in images,an areawhere CNNs struggle due to their reliance on local receptive fields and hierarchical feature extraction.The additional transformer-based models also demonstrate improved performance in capturing complex features over CNNs,with LMViT excelling particularly at detecting subtle and complex defects,which is critical for maintaining product quality and operational efficiency in industrial applications.For instance,the LMViT model successfully identified fine scratches and minor surface irregularities that CNNs often misclassify.This study not only demonstrates LMViT’s potential for real-world defect detection but also underscores the promise of other transformer-based architectures like Token to Token ViT,ViT without memory,and Parallel ViT in industrial scenarios where complex spatial relationships are key.Future research may focus on enhancing LMViT’s computational efficiency for deployment in real-time quality control systems.
基金supported by the Natural Science Foundation of Heilongjiang Province of China,Outstanding Youth Foundation,No.YQ2022H003 (to DW)。
文摘N6-methyladenosine(m^(6)A), the most prevalent and conserved RNA modification in eukaryotic cells, profoundly influences virtually all aspects of mRNA metabolism. mRNA plays crucial roles in neural stem cell genesis and neural regeneration, where it is highly concentrated and actively involved in these processes. Changes in m^(6)A modification levels and the expression levels of related enzymatic proteins can lead to neurological dysfunction and contribute to the development of neurological diseases. Furthermore, the proliferation and differentiation of neural stem cells, as well as nerve regeneration, are intimately linked to memory function and neurodegenerative diseases. This paper presents a comprehensive review of the roles of m^(6)A in neural stem cell proliferation, differentiation, and self-renewal, as well as its implications in memory and neurodegenerative diseases. m^(6)A has demonstrated divergent effects on the proliferation and differentiation of neural stem cells. These observed contradictions may arise from the time-specific nature of m^(6)A and its differential impact on neural stem cells across various stages of development. Similarly, the diverse effects of m^(6)A on distinct types of memory could be attributed to the involvement of specific brain regions in memory formation and recall. Inconsistencies in m^(6)A levels across different models of neurodegenerative disease, particularly Alzheimer's disease and Parkinson's disease, suggest that these disparities are linked to variations in the affected brain regions. Notably, the opposing changes in m^(6)A levels observed in Parkinson's disease models exposed to manganese compared to normal Parkinson's disease models further underscore the complexity of m^(6)A's role in neurodegenerative processes. The roles of m^(6)A in neural stem cell proliferation, differentiation, and self-renewal, and its implications in memory and neurodegenerative diseases, appear contradictory. These inconsistencies may be attributed to the timespecific nature of m^(6)A and its varying effects on distinct brain regions and in different environments.
基金supported by STI2030-Major Projects,No.2022ZD0207600(to LZ)the National Natural Science Foundation of China,Nos.32070955(to LZ),U22A20301(to KFS)+3 种基金the Natural Science Foundation of Guangdong Province,No.2021A1515012197(to HO)Guangzhou Core Medical Disciplines Project,No.2021-2023(to HO)Key Research and Development Plan of Ningxia Hui Automomous Region,No.2022BEG01004(to KFS)Science and Technology Program of Guangzhou,China,No.202007030012(to KFS and LZ)。
文摘Cerebral ischemia is a major health risk that requires preventive approaches in addition to drug therapy.Physical exercise enhances neurogenesis and synaptogenesis,and has been widely used for functional rehabilitation after stroke.In this study,we determined whether exercise training before disease onset can alleviate the severity of cerebral ischemia.We also examined the role of exercise-induced circulating factors in these effects.Adult mice were subjected to 14 days of treadmill exercise training before surgery for middle cerebral artery occlusion.We found that this exercise pre-conditioning strategy effectively attenuated brain infarct area,inhibited gliogenesis,protected synaptic proteins,and improved novel object and spatial memory function.Further analysis showed that circulating adiponectin plays a critical role in these preventive effects of exercise.Agonist activation of adiponectin receptors by Adipo Ron mimicked the effects of exercise,while inhibiting receptor activation abolished the exercise effects.In summary,our results suggest a crucial role of circulating adiponectin in the effects of exercise pre-conditioning in protecting against cerebral ischemia and supporting the health benefits of exercise.
基金supported by the National Natural Science Foundation of China,Nos.81730033,82171193(to XG)the Key Talent Project for Strengthening Health during the 13^(th)Five-Year Plan Period,No.ZDRCA2016069(to XG)+1 种基金the National Key R&D Program of China,No.2018YFC2001901(to XG)Jiangsu Provincial Medical Key Discipline,No.ZDXK202232(to XG)。
文摘Postoperative cognitive dysfunction is a seve re complication of the central nervous system that occurs after anesthesia and surgery,and has received attention for its high incidence and effect on the quality of life of patients.To date,there are no viable treatment options for postoperative cognitive dysfunction.The identification of postoperative cognitive dysfunction hub genes could provide new research directions and therapeutic targets for future research.To identify the signaling mechanisms contributing to postoperative cognitive dysfunction,we first conducted Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses of the Gene Expression Omnibus GSE95426 dataset,which consists of mRNAs and long non-coding RNAs differentially expressed in mouse hippocampus3 days after tibial fracture.The dataset was enriched in genes associated with the biological process"regulation of immune cells,"of which Chill was identified as a hub gene.Therefore,we investigated the contribution of chitinase-3-like protein 1 protein expression changes to postoperative cognitive dysfunction in the mouse model of tibial fractu re surgery.Mice were intraperitoneally injected with vehicle or recombinant chitinase-3-like protein 124 hours post-surgery,and the injection groups were compared with untreated control mice for learning and memory capacities using the Y-maze and fear conditioning tests.In addition,protein expression levels of proinflammatory factors(interleukin-1βand inducible nitric oxide synthase),M2-type macrophage markers(CD206 and arginase-1),and cognition-related proteins(brain-derived neurotropic factor and phosphorylated NMDA receptor subunit NR2B)were measured in hippocampus by western blotting.Treatment with recombinant chitinase-3-like protein 1 prevented surgery-induced cognitive impairment,downregulated interleukin-1βand nducible nitric oxide synthase expression,and upregulated CD206,arginase-1,pNR2B,and brain-derived neurotropic factor expression compared with vehicle treatment.Intraperitoneal administration of the specific ERK inhibitor PD98059 diminished the effects of recombinant chitinase-3-like protein 1.Collectively,our findings suggest that recombinant chitinase-3-like protein 1 ameliorates surgery-induced cognitive decline by attenuating neuroinflammation via M2 microglial polarization in the hippocampus.Therefore,recombinant chitinase-3-like protein1 may have therapeutic potential fo r postoperative cognitive dysfunction.
基金supported in part by the National Key Research and Development Program of China under Grant No.2021YFF0901300in part by the National Natural Science Foundation of China under Grant Nos.62173076 and 72271048.
文摘The distributed permutation flow shop scheduling problem(DPFSP)has received increasing attention in recent years.The iterated greedy algorithm(IGA)serves as a powerful optimizer for addressing such a problem because of its straightforward,single-solution evolution framework.However,a potential draw-back of IGA is the lack of utilization of historical information,which could lead to an imbalance between exploration and exploitation,especially in large-scale DPFSPs.As a consequence,this paper develops an IGA with memory and learning mechanisms(MLIGA)to efficiently solve the DPFSP targeted at the mini-malmakespan.InMLIGA,we incorporate a memory mechanism to make a more informed selection of the initial solution at each stage of the search,by extending,reconstructing,and reinforcing the information from previous solutions.In addition,we design a twolayer cooperative reinforcement learning approach to intelligently determine the key parameters of IGA and the operations of the memory mechanism.Meanwhile,to ensure that the experience generated by each perturbation operator is fully learned and to reduce the prior parameters of MLIGA,a probability curve-based acceptance criterion is proposed by combining a cube root function with custom rules.At last,a discrete adaptive learning rate is employed to enhance the stability of the memory and learningmechanisms.Complete ablation experiments are utilized to verify the effectiveness of the memory mechanism,and the results show that this mechanism is capable of improving the performance of IGA to a large extent.Furthermore,through comparative experiments involving MLIGA and five state-of-the-art algorithms on 720 benchmarks,we have discovered that MLI-GA demonstrates significant potential for solving large-scale DPFSPs.This indicates that MLIGA is well-suited for real-world distributed flow shop scheduling.
基金supported by the National Institutes of Health,Nos.AA025919,AA025919-03S1,and AA025919-05S1(all to RAF).
文摘Hippocampal neuronal loss causes cognitive dysfunction in Alzheimer’s disease.Adult hippocampal neurogenesis is reduced in patients with Alzheimer’s disease.Exercise stimulates adult hippocampal neurogenesis in rodents and improves memory and slows cognitive decline in patients with Alzheimer’s disease.However,the molecular pathways for exercise-induced adult hippocampal neurogenesis and improved cognition in Alzheimer’s disease are poorly understood.Recently,regulator of G protein signaling 6(RGS6)was identified as the mediator of voluntary running-induced adult hippocampal neurogenesis in mice.Here,we generated novel RGS6fl/fl;APP_(SWE) mice and used retroviral approaches to examine the impact of RGS6 deletion from dentate gyrus neuronal progenitor cells on voluntary running-induced adult hippocampal neurogenesis and cognition in an amyloid-based Alzheimer’s disease mouse model.We found that voluntary running in APP_(SWE) mice restored their hippocampal cognitive impairments to that of control mice.This cognitive rescue was abolished by RGS6 deletion in dentate gyrus neuronal progenitor cells,which also abolished running-mediated increases in adult hippocampal neurogenesis.Adult hippocampal neurogenesis was reduced in sedentary APP_(SWE) mice versus control mice,with basal adult hippocampal neurogenesis reduced by RGS6 deletion in dentate gyrus neural precursor cells.RGS6 was expressed in neurons within the dentate gyrus of patients with Alzheimer’s disease with significant loss of these RGS6-expressing neurons.Thus,RGS6 mediated voluntary running-induced rescue of impaired cognition and adult hippocampal neurogenesis in APP_(SWE) mice,identifying RGS6 in dentate gyrus neural precursor cells as a possible therapeutic target in Alzheimer’s disease.
基金National Natural Science Foundation of China(12404230,52061027)Science and Technology Program Project of Gansu Province(22YF7GA155)+1 种基金Lanzhou Youth Science and Technology Talent Innovation Project(2023-QN-91)Zhejiang Provincial Natural Science Foundation of China(LY23E010002)。
文摘(TiZrHf)_(50)Ni_(30)Cu_(20-x)Co_(x)(x=2,4,6,at%)high-entropy high-temperature shape memory alloys were fabricated by watercooled copper crucible in a magnetic levitation vacuum melting furnace,and the effects of Co content on microstructure and mechanical properties were investigated.The results indicate that the grain size of the alloy decreases with increasing the Co content.In the as-cast state,the alloy consists primarily of the B19′phase,with a trace of B2 phase.The fracture morphology is predominantly composed of the B19′phase,whereas the B2 phase is nearly absent.Increasing the Co content or reducing the sample dimensions(d)markedly enhance the compressive strength and ductility of the alloy.When d=2 mm,the(TiZrHf)_(50)Ni_(30)Cu_(14)Co_(6) alloy demonstrates the optimal mechanical properties,achieving a compressive strength of 2142.39±1.8 MPa and a plasticity of 17.31±0.3%.The compressive cyclic test shows that with increasing the compressive strain,the residual strain of the(TiZrHf)_(50)Ni_(30)Cu_(14)Co_(6) alloy increases while the recovery ability declines.The superelastic recovery capability of the alloy is continuously enhanced.The superelastic recovery rate increases from 1.36%to 2.12%,the residual strain rate rises from 1.79%to 5.52%,the elastic recovery rate ascends from 3.86%to 7.36%,while the total recovery rate declines from 74.48%to 63.20%.
文摘The memory behavior in liquid crystals(LCs)that is characterized by low cost,large area,high speed,and high-density memory has evolved from a mere scientific curiosity to a technology that is being applied in a variety of commodities.In this study,we utilized molybdenum disulfide(MoS_(2))nanoflakes as the vip in a homotropic LCs host to modulate the overall memory effect of the hybrid.It was found that the MoS₂nanoflakes within the LCs host formed agglomerates,which in turn resulted in an accelerated response of the hybrids to the external electric field.However,this process also resulted in a slight decrease in the threshold voltage.Additionally,it was observed that MoS₂nanoflakes in a LCs host tend to align homeotropically under an external electric field,thereby accelerating the refreshment of the memory behavior.The incorporation of a mass fraction of 0.1%2μm MoS₂nanoflakes into the LCs host was found to significantly reduce the refreshing memory behavior in the hybrid to 94.0 s under an external voltage of 5 V.These findings illustrate the efficacy of regulating the rate of memory behavior for a variety of potential applications.
基金supported by the National Key Research&Development Projects of China(Grant No.2022YFA1204100)National Natural Science Foundation of China(Grant No.62488201)+1 种基金CAS Project for Young Scientists in Basic Research(YSBR-003)the Innovation Program of Quantum Science and Technology(2021ZD0302700)。
文摘As a typical in-memory computing hardware design, nonvolatile ternary content-addressable memories(TCAMs) enable the logic operation and data storage for high throughout in parallel big data processing. However,TCAM cells based on conventional silicon-based devices suffer from structural complexity and large footprintlimitations. Here, we demonstrate an ultrafast nonvolatile TCAM cell based on the MoTe2/hBN/multilayergraphene (MLG) van der Waals heterostructure using a top-gated partial floating-gate field-effect transistor(PFGFET) architecture. Based on its ambipolar transport properties, the carrier type in the source/drain andcentral channel regions of the MoTe2 channel can be efficiently tuned by the control gate and top gate, respectively,enabling the reconfigurable operation of the device in either memory or FET mode. When working inthe memory mode, it achieves an ultrafast 60 ns programming/erase speed with a current on-off ratio of ∼105,excellent retention capability, and robust endurance. When serving as a reconfigurable transistor, unipolar p-typeand n-type FETs are obtained by adopting ultrafast 60 ns control-gate voltage pulses with different polarities.The monolithic integration of memory and logic within a single device enables the content-addressable memory(CAM) functionality. Finally, by integrating two PFGFETs in parallel, a TCAM cell with a high current ratioof ∼10^(5) between the match and mismatch states is achieved without requiring additional peripheral circuitry.These results provide a promising route for the design of high-performance TCAM devices for future in-memorycomputing applications.
