The main purpose of this paper is to investigate the singularities of solutions to the single Tricomi equation with derivative term and combined memory term.In addition,the blow-up of the solution to the weakly couple...The main purpose of this paper is to investigate the singularities of solutions to the single Tricomi equation with derivative term and combined memory term.In addition,the blow-up of the solution to the weakly coupled system with memory term is also considered,where one is a power nonlinear term and the other is a derivative nonlinear term.Upper bound lifespan estimates of solution are obtained in the sub-critical by utilizing the test function method and iteration technique.The innovation of this paper focuses on the lifespan estimates of the solutions,which extends the well-known Strauss and Glassey conjectures.展开更多
T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection met...T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection methods face challenges owing to surface oxide scales,and conventional high-precision magnetic sensors are ineffective at high temperatures.To overcome these limitations,a small coil sensor was employed to measure the residual magnetism strength in oscillation traces,using metal magnetic memory and electromagnetic induction methods,which can carry out detection without an external excitation source.Using this technology,the proposed scheme successfully detects defects at high tempe-ratures(up to 670℃)without a cooling device.The key findings include the ability to detect both surface and near-surface defects,such as cracks and oscillation marks,with an enhanced signal-to-noise ratio(SNR)of 7.2 dB after signal processing.The method’s practicality was validated in a steel mill environment,where testing on casting slabs effectively detected defects,providing a foundation for improving industrial quality control.The proposed detection scheme offers a significant advancement in nondestructive testing(NDT)for high-temperature applications,contributing to more efficient and accurate monitoring of ferromagnetic material integrity.展开更多
Aerobic exercise facilitates synaptic plasticity,thereby improving cognitive functions such as learning and memory.The 5-hydroxytryptamine system has been indicated in these processes.5-Hydroxytryptamine type 3 recept...Aerobic exercise facilitates synaptic plasticity,thereby improving cognitive functions such as learning and memory.The 5-hydroxytryptamine system has been indicated in these processes.5-Hydroxytryptamine type 3 receptors are necessary for exercise-induced hippocampal neurogenesis.Some antipsychotic drugs with 5-hydroxytryptamine type 3 receptor antagonistic properties may impede the amelioration of cognitive impairment and hippocampal plasticity induced by exercise.However,the mechanisms underlying the facilitation of synaptic plasticity by aerobic exercise have not yet been elucidated.In this study,we found that 5-hydroxytryptamine type 3 receptors played an important role in aerobic exercise-mediated improvement of hippocampal-dependent spatial and exploratory memory in mice.While 5-hydroxytryptamine type 3 receptors did not affect baseline neurogenesis in the hippocampal dentate gyrus,5-hydroxytryptamine type 3 receptors were required for aerobic exercise-induced neurogenesis and astrocyte proliferation in this region.In addition,5-hydroxytryptamine type 3 receptors were crucial for maintaining long-term potentiation in the CA1,dentate gyrus,and CA3 regions of the hippocampus.The long-term potentiation changes induced by aerobic exercise in sub-regions of the hippocampus were heterogeneous:5-hydroxytryptamine type 3 receptors were essential for aerobic exercise to enhance long-term potentiation in the CA3,but not the CA1 or dentate gyrus,regions of the hippocampus.Furthermore,aerobic exercise up-regulated 5-hydroxytryptamine type 3 receptor expression and increased brain-derived neurotrophic factor release in the hippocampus in a 5-hydroxytryptamine type 3 receptor-dependent manner.These results suggest that aerobic exercise increases hippocampal dentate gyrus neurogenesis and astrocyte proliferation via the up-regulation of 5-hydroxytryptamine type 3 receptors,leading to more brain-derived neurotrophic factor production and release from these cells,which results in long-term potentiation facilitation in the hippocampal CA3 region and help improve memory.Our findings provide insight into the mechanisms by which physical activity enhances memory and may have implications for improving memory through modulating 5-hydroxytryptamine type 3 receptor.展开更多
Aging is a physiological and complex process produced by accumulative age-dependent cellular damage,which significantly impacts brain regions like the hippocampus,an essential region involved in memory and learning.A ...Aging is a physiological and complex process produced by accumulative age-dependent cellular damage,which significantly impacts brain regions like the hippocampus,an essential region involved in memory and learning.A crucial factor contributing to this decline is the dysfunction of mitochondria,particularly those located at synapses.Synaptic mitochondria are specialized organelles that produce the energy required for synaptic transmission but are also important for calcium homeostasis at these sites.In contrast,non-synaptic mitochondria primarily involve cellular metabolism and long-term energy supply.Both pools of mitochondria differ in their form,proteome,functionality,and cellular role.The proper functioning of synaptic mitochondria depends on processes such as mitochondrial dynamics,transport,and quality control.However,synaptic mitochondria are particularly vulnerable to age-associated damage,characterized by oxidative stress,impaired energy production,and calcium dysregulation.These changes compromise synaptic transmission,reducing synaptic activity and cognitive decline during aging.In the context of neurodegenerative diseases such as Alzheimer’s,Parkinson’s,and Huntington’s,the decline of synaptic mitochondrial function is even more pronounced.These diseases are marked by pathological protein accumulation,disrupted mitochondrial dynamics,and heightened oxidative stress,accelerating synaptic dysfunction and neuronal loss.Due to their specialized role and location,synaptic mitochondria are among the first organelles to exhibit dysfunction,underscoring their critical role in disease progression.This review delves into the main differences at structural and functional levels between synaptic and non-synaptic mitochondria,emphasizing the vulnerability of synaptic mitochondria to the aging process and neurodegeneration.These approaches highlight the potential of targeting synaptic mitochondria to mitigate age-associated cognitive impairment and synaptic degeneration.This review emphasizes the distinct vulnerabilities of hippocampal synaptic mitochondria,highlighting their essential role in sustaining brain function throughout life and their promise as therapeutic targets for safeguarding the cognitive capacities of people of advanced age.展开更多
Your hometown is often a special place.It can be big or small.And it usually has an important place in your life and heart.You may not live there anymore.But you remember it well.Maybe you have warm feelings for your ...Your hometown is often a special place.It can be big or small.And it usually has an important place in your life and heart.You may not live there anymore.But you remember it well.Maybe you have warm feelings for your school,your friends and your neighbors there.You remember special places and fun times.There may be interesting museums or great sports teams in your hometown.You can tell people about them.展开更多
Near-infrared(NIR)light-responsive shape memory polymers(SMPs)show great promise for biomedical applications,but conventional photothermal agents suffer from high cost,complex preparation,or poor biocompatibility,whil...Near-infrared(NIR)light-responsive shape memory polymers(SMPs)show great promise for biomedical applications,but conventional photothermal agents suffer from high cost,complex preparation,or poor biocompatibility,while lignin-based alternatives exhibit insufficient photothermal conversion efficiency.Herein,we developed a novel strategy to enhance photothermal performance of lignin through sequential demethylation modification and Fe^(3+)complexation for constructing NIR light responsive SMPs.Dealkaline lignin(DL)was first demethylated using iodocyclohexane to produce demethylated lignin(DDL)with increased catechol content,which was then incorporated into polycaprolactone-based polyurethane synthesis followed by Fe^(3+)complexation.Results showed that DDL-Fe^(3+)complexes have significantly enhanced photothermal conversion performance,and the resulting PU-DDL+Fe^(3+)polyurethane with 0.5 wt%DDL content demonstrated a temperature increases of 39.8℃under 0.33 W·cm-2808 nm NIR irradiation.This excellent photothermal performance enables the shape-fixed PU-DDL+Fe^(3+)polyurethane to rapidly recover to its initial shape under NIR light irradiation.Additionally,PU-DDL+Fe^(3+)polyurethane exhibits good mechanical properties and biocompatibility,demonstrating significant biomedical application potential.展开更多
Alzheimer's disease is the primary cause of dementia and imposes a significant socioeconomic burden globally.Physical exercise,as an effective strategy for improving general health,has been largely reported for it...Alzheimer's disease is the primary cause of dementia and imposes a significant socioeconomic burden globally.Physical exercise,as an effective strategy for improving general health,has been largely reported for its effectiveness in slowing neurodegeneration and increasing brain functional plasticity,particularly in aging brains.However,the underlying mechanisms of exercise in cognitive aging remain largely unclear.Adiponectin,a cell-secreted protein hormone,has recently been found to regulate synaptic plasticity and mediate the antidepressant effects of physical exercise.Studies on the neuroprotective effects of adiponectin have revealed potential innovative treatments for Alzheimer's disease.Here,we reviewed the functions of adiponectin and its receptor in the brains of human and animal models of cognitive impairment.We summarized the role of adiponectin in Alzheimer's disease,focusing on its impact on energy metabolism,insulin resistance,and inflammation.We also discuss how exercise increases adiponectin secretion and its potential benefits for learning and memory.Finally,we highlight the latest research on chemical compounds that mimic exerciseenhanced secretion of adiponectin and its receptor in Alzheimer's disease.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
The overgeneralization of fear is associated with psychiatric disorders and cognitive decline.Recent studies have shown that engram cells in the dorsal dentate gyrus are integrated into functionally heterogeneous ense...The overgeneralization of fear is associated with psychiatric disorders and cognitive decline.Recent studies have shown that engram cells in the dorsal dentate gyrus are integrated into functionally heterogeneous ensembles that are involved in contextual fear memory generalization and discrimination.However,the intracellular signals that promote fear generalization remain to be fully elucidated.In this study,we labeled and manipulated the c-Fos+and Npas4+ensembles in the dorsal dentate gyrus that are activated by contextual fear conditioning using a robust activity marking system.The results showed that increasing the excitability of Fos-dependent robust activity marking by overexpressing NaChBac or decreasing the excitability of Npas4-dependent robust activity marking by overexpressing Kir2.1 promoted fear memory generalization.Furthermore,CRISPR-mediated downregulation of the autophagy-related Atg5 or Atg7 genes in dorsal dentate gyrus neurons inhibited activation of c-Fos,but not Npas4.Knockdown of Atg5 or Atg7 in the Fos-dependent robust activity marking or Npas4-dependent robust activity marking ensemble led to an increase in neuronal excitability and a decrease in spine density in both ensembles.However,Atg7 knockdown in the Fos-dependent robust activity marking ensemble promoted memory generalization,while knockdown of Atg5 or Atg7 in the Npas4-dependent robust activity marking ensemble increased anxiety levels.These results contribute to our understanding of how the varying plasticity of memory engrams is involved in regulating fear memory generalization and anxiety.展开更多
Aiming at the problem of potential information noise introduced during the generation of ghost feature maps in GhostNet,this paper proposes a novel lightweight neural network model called ResghostNet.This model constr...Aiming at the problem of potential information noise introduced during the generation of ghost feature maps in GhostNet,this paper proposes a novel lightweight neural network model called ResghostNet.This model constructs the Resghost Module by combining residual connections and Adaptive-SE Blocks,which enhances the quality of generated feature maps through direct propagation of original input information and selection of important channels before cheap operations.Specifically,ResghostNet introduces residual connections on the basis of the Ghost Module to optimize the information flow,and designs a weight self-attention mechanism combined with SE blocks to enhance feature expression capabilities in cheap operations.Experimental results on the ImageNet dataset show that,compared to GhostNet,ResghostNet achieves higher accuracy while reducing the number of parameters by 52%.Although the computational complexity increases,by optimizing the usage strategy of GPU cachememory,themodel’s inference speed becomes faster.The ResghostNet is optimized in terms of classification accuracy and the number of model parameters,and shows great potential in edge computing devices.展开更多
Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning...Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning to mitigate accuracy degradation in 24-h forecasting.Initially,an optimized DB-SCAN(Density-Based Spatial Clustering of Applications with Noise)algorithm clusters wind fields based on wind direction,probability density,and spectral features,enhancing physical interpretability and reducing training complexity.Subsequently,a ResNet(Residual Network)extracts multi-scale patterns from decomposed wind signals,while transfer learning adapts the backbone network across clusters,cutting training time by over 90%.Finally,a CBAM(Convolutional Block Attention Module)attention mechanism is employed to prioritize features for LSTM-based prediction.Tested on the 2015 Jena wind speed dataset,the model demonstrates superior accuracy and robustness compared to state-of-the-art baselines.Key innovations include:(a)Physics-informed clustering for interpretable wind regime classification;(b)Transfer learning with deep feature extraction,preserving accuracy while minimizing training time;and(c)On the 2016 Jena wind speed dataset,the model achieves MAPE(Mean Absolute Percentage Error)values of 16.82%and 18.02%for the Weibull-shaped and Gaussian-shaped wind speed clusters,respectively,demonstrating the model’s robust generalization capacity.This framework offers an efficient and effective solution for long-term wind forecasting.展开更多
This study aimed to systematically regulate the performance of 4D printing composites by investigating the synergistic effects of dicumyl peroxide(DCP)and maleic anhydride-grafted polyethylene(MAH-g-PE)on a poly(lacti...This study aimed to systematically regulate the performance of 4D printing composites by investigating the synergistic effects of dicumyl peroxide(DCP)and maleic anhydride-grafted polyethylene(MAH-g-PE)on a poly(lactic acid)/thermoplastic polyurethane(PLA/TPU)matrix.Specifically,using a 70 wt%/30 wt%PLA/TPU matrix and an L_(9)(3^(2))orthogonal design,composites were evaluated via morphology,shape memory,mechanical tests,and multi-criteria analysis.Moderate DCP enhanced crosslinking,improving storage modulus and thermal stability,while excessive DCP caused brittleness.Furthermore,MAH-g-PE effectively improved interfacial compatibility,and its synergy with DCP was dosage-dependent.Consequently,Sample 5 achieved optimal performance,exhibiting uniform fracture morphology,a shape fixation rate of98.8%with the fastest recovery,and balanced strength-ductility.Multi-criteria analysis identified elongation at break and recovery time as the top contributing factors,with consistent rankings validated by Spearman analysis(ρ=0.833,p<0.01).In summary,adjusting DCP and MAH-g-PE contents effectively modulates the crosslinking structure and interfacial properties of PLA/TPU composites,providing a viable strategy for developing high-performance,tunable 4D printing materials.展开更多
Recent studies have indicated that stroke can lead to neuronal iron overload and lipid peroxidation.Lycium barbarum glycopeptide,which has a low molecular weight and potent antioxidant properties,may mitigate ferropto...Recent studies have indicated that stroke can lead to neuronal iron overload and lipid peroxidation.Lycium barbarum glycopeptide,which has a low molecular weight and potent antioxidant properties,may mitigate ferroptosis in stroke.We hypothesized that Lycium barbarum glycopeptide can effectively mitigate iron overload within ischemic neurons due to its robust antioxidant properties.The aims of this study were to investigate the effects of Lycium barbarum glycopeptide on ferroptotic damage following brain ischemia and explore the underlying mechanisms.A rat model of middle cerebral artery occlusion was established using the intraluminal filament method,and the rats were treated with Lycium barbarum glycopeptide for 7 consecutive days,beginning 24 hours after ischemia.Liproxstatin-1,a ferroptosis inhibitor,and Erastin,a ferroptosis activator,were used as controls.We found that treatment with Lycium barbarum glycopeptide resulted in significant reductions in infarct volume(as detected by triphenyltetrazolium chloride staining staining and magnetic resonance imaging)and neuronal death(as measured by Nissl staining),as well as improvements in sensory and motor functions in rats subjected to middle cerebral artery occlusion.Furthermore,treatment with Lycium barbarum glycopeptide alleviated anxiety and depression-like behaviors and improved memory.Additionally,Lycium barbarum glycopeptide effectively reduced the iron ion content in the ischemic penumbra of the cortex.Moreover,treatment with Lycium barbarum glycopeptide downregulated the expression of ferroptotic and oxidant proteins such as transferrin receptor 1,divalent metal transporter 1,and Acyl-CoA synthetase long-chain family member 4 and upregulated the expression of anti-ferroptotic and antioxidant proteins such as ferroportin 1,solute carrier family 7 member 11,glutathione,and glutathione peroxidase 4.However,these beneficial effects were reversed when ferroptosis was induced with the activator Erastin.Therefore,the positive effects of Lycium barbarum glycopeptide in ischemic stroke are likely mediated through activation of the anti-ferroptotic pathway and the antioxidative System Xc-glutathione-glutathione peroxidase 4 pathway.Overall,our findings highlight the potential use of Lycium barbarum glycopeptide as a neuroprotective agent targeting both ferroptosis and oxidation to decrease ischemic brain damage.展开更多
GABA_(A) receptors containingα5-subunits(GABA_(A)R-α5)cluster at both extrasynaptic and synaptic locations,interacting with the scaffold proteins radixin and gephyrin,respectively,and the re-localization of GABA_(A...GABA_(A) receptors containingα5-subunits(GABA_(A)R-α5)cluster at both extrasynaptic and synaptic locations,interacting with the scaffold proteins radixin and gephyrin,respectively,and the re-localization of GABA_(A)R-α5 influences GABAergic transmission.Here,we found that when early spatial memory deficits occurred in aged mice at 24 h after sevoflurane anesthesia,there was a re-localization of GABA_(A)R-α5 that enhanced tonic inhibition and reduced the decay kinetics of miniature inhibitory postsynaptic currents in the hippocampal CA1 region.Mechanistically,increased phosphorylation of radixin at threonine 564(Thr564)mediates the re-localization of GABA_(A)R-α5.Acute treatment with the selective extrasynaptic GABA_(A)R-α5 antagonist S44819 restored the GABA_(A)R-α5-mediated inhibitory currents by reversing radixin phosphorylation-dependent GABA_(A)R-α5 re-localization,then improved the sevoflurane-induced spatial memory impairment in aged mice.Our results suggest that the localization of GABA_(A)R-α5 altered by sevoflurane is linked to unbalanced GABAergic transmission,which induces early memory impairment in aged mice.Modulating the GABA_(A)R-α5 localization might be a novel strategy to improve memory after sevoflurane exposure.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
Recognizing human interactions in RGB videos is a critical task in computer vision,with applications in video surveillance.Existing deep learning-based architectures have achieved strong results,but are computationall...Recognizing human interactions in RGB videos is a critical task in computer vision,with applications in video surveillance.Existing deep learning-based architectures have achieved strong results,but are computationally intensive,sensitive to video resolution changes and often fail in crowded scenes.We propose a novel hybrid system that is computationally efficient,robust to degraded video quality and able to filter out irrelevant individuals,making it suitable for real-life use.The system leverages multi-modal handcrafted features for interaction representation and a deep learning classifier for capturing complex dependencies.Using Mask R-CNN and YOLO11-Pose,we extract grayscale silhouettes and keypoint coordinates of interacting individuals,while filtering out irrelevant individuals using a proposed algorithm.From these,we extract silhouette-based features(local ternary pattern and histogram of optical flow)and keypoint-based features(distances,angles and velocities)that capture distinct spatial and temporal information.A Bidirectional Long Short-Term Memory network(BiLSTM)then classifies the interactions.Extensive experiments on the UT Interaction,SBU Kinect Interaction and the ISR-UOL 3D social activity datasets demonstrate that our system achieves competitive accuracy.They also validate the effectiveness of the chosen features and classifier,along with the proposed system’s computational efficiency and robustness to occlusion.展开更多
Shrublands and grasslands,which constitute approximately 70%of Australia’s vegetation,play a critical role in global wildfire-prone regions.To advance the understanding of grass fire spread,a three-dimensional,physic...Shrublands and grasslands,which constitute approximately 70%of Australia’s vegetation,play a critical role in global wildfire-prone regions.To advance the understanding of grass fire spread,a three-dimensional,physicsbased fire model provides valuable insights into fire dynamics.However,such models are computationally intensive and time-consuming.To address these challenges,we constructed an extensive numerical database comprising 64,000 high-fidelity wildfire simulation cases and implemented a Long Short-Term Memory neural network architecture.The model demonstrates strong predictive performance,achieving a coefficient of determination(R2)of 0.96 on training data,indicating excellent agreement with the physics-based simulation outputs.By utilizing coordinates from five reference points to predict fire front movement,this approach offers a novel method for analysing fire dynamics in homogeneous fuel beds with an average deviation of less than 2.5%.Combining the strengths of physics-based modelling and deep learning,our research enhances fire spread prediction accuracy of over 95%while significantly reducing computational demands.Future efforts will focus on refining the model,expanding the dataset,and incorporating additional variables to improve predictive capabilities and operational applicability.展开更多
Accurate and reliable power system data are fundamental for critical operations such as gridmonitoring,fault diagnosis,and load forecasting,underpinned by increasing intelligentization and digitalization.However,data ...Accurate and reliable power system data are fundamental for critical operations such as gridmonitoring,fault diagnosis,and load forecasting,underpinned by increasing intelligentization and digitalization.However,data loss and anomalies frequently compromise data integrity in practical settings,significantly impacting system operational efficiency and security.Most existing data recovery methods require complete datasets for training,leading to substantial data and computational demands and limited generalization.To address these limitations,this study proposes a missing data imputation model based on an improved Generative Adversarial Network(BAC-GAN).Within the BAC-GAN framework,the generator utilizes Bidirectional Long Short-Term Memory(BiLSTM)networks and Multi-Head Attention mechanisms to capture temporal dependencies and complex relationships within power system data.The discriminator employs a Convolutional Neural Network(CNN)architecture to integrate local features with global structures,effectivelymitigating the generation of implausible imputations.Experimental results on two public datasets demonstrate that the BAC-GAN model achieves superior data recovery accuracy compared to five state-of-the-art and classical benchmarkmethods,with an average improvement of 17.7%in reconstruction accuracy.The proposedmethod significantly enhances the accuracy of grid fault diagnosis and provides reliable data support for the stable operation of smart grids,showing great potential for practical applications in power systems.展开更多
基金Supported by National Natural Science Foundation of China Under Grant(12401647)Supported by Fundamental Research Program of Shanxi Province(202203021212336)+2 种基金Taiyuan Institute of Technology Scientific Research Initial Funding(2023KJ057,2024KJ007,2024LJ005)Supported by Scientific and Technologial Innovation Programs of Higher Education Institutions in Shanxi(2024L358)Youth Program of Taiyuan University(24TYQN10)。
文摘The main purpose of this paper is to investigate the singularities of solutions to the single Tricomi equation with derivative term and combined memory term.In addition,the blow-up of the solution to the weakly coupled system with memory term is also considered,where one is a power nonlinear term and the other is a derivative nonlinear term.Upper bound lifespan estimates of solution are obtained in the sub-critical by utilizing the test function method and iteration technique.The innovation of this paper focuses on the lifespan estimates of the solutions,which extends the well-known Strauss and Glassey conjectures.
文摘T he residual stray magnetic fields present in ferromagnetic casting slabs were investigated in this work,which result from the magnetic fields generated during the steel casting process.Existing optical detection methods face challenges owing to surface oxide scales,and conventional high-precision magnetic sensors are ineffective at high temperatures.To overcome these limitations,a small coil sensor was employed to measure the residual magnetism strength in oscillation traces,using metal magnetic memory and electromagnetic induction methods,which can carry out detection without an external excitation source.Using this technology,the proposed scheme successfully detects defects at high tempe-ratures(up to 670℃)without a cooling device.The key findings include the ability to detect both surface and near-surface defects,such as cracks and oscillation marks,with an enhanced signal-to-noise ratio(SNR)of 7.2 dB after signal processing.The method’s practicality was validated in a steel mill environment,where testing on casting slabs effectively detected defects,providing a foundation for improving industrial quality control.The proposed detection scheme offers a significant advancement in nondestructive testing(NDT)for high-temperature applications,contributing to more efficient and accurate monitoring of ferromagnetic material integrity.
基金supported by the National Natural Science Foundation of China,Nos.31972914,31771175(both to YH).
文摘Aerobic exercise facilitates synaptic plasticity,thereby improving cognitive functions such as learning and memory.The 5-hydroxytryptamine system has been indicated in these processes.5-Hydroxytryptamine type 3 receptors are necessary for exercise-induced hippocampal neurogenesis.Some antipsychotic drugs with 5-hydroxytryptamine type 3 receptor antagonistic properties may impede the amelioration of cognitive impairment and hippocampal plasticity induced by exercise.However,the mechanisms underlying the facilitation of synaptic plasticity by aerobic exercise have not yet been elucidated.In this study,we found that 5-hydroxytryptamine type 3 receptors played an important role in aerobic exercise-mediated improvement of hippocampal-dependent spatial and exploratory memory in mice.While 5-hydroxytryptamine type 3 receptors did not affect baseline neurogenesis in the hippocampal dentate gyrus,5-hydroxytryptamine type 3 receptors were required for aerobic exercise-induced neurogenesis and astrocyte proliferation in this region.In addition,5-hydroxytryptamine type 3 receptors were crucial for maintaining long-term potentiation in the CA1,dentate gyrus,and CA3 regions of the hippocampus.The long-term potentiation changes induced by aerobic exercise in sub-regions of the hippocampus were heterogeneous:5-hydroxytryptamine type 3 receptors were essential for aerobic exercise to enhance long-term potentiation in the CA3,but not the CA1 or dentate gyrus,regions of the hippocampus.Furthermore,aerobic exercise up-regulated 5-hydroxytryptamine type 3 receptor expression and increased brain-derived neurotrophic factor release in the hippocampus in a 5-hydroxytryptamine type 3 receptor-dependent manner.These results suggest that aerobic exercise increases hippocampal dentate gyrus neurogenesis and astrocyte proliferation via the up-regulation of 5-hydroxytryptamine type 3 receptors,leading to more brain-derived neurotrophic factor production and release from these cells,which results in long-term potentiation facilitation in the hippocampal CA3 region and help improve memory.Our findings provide insight into the mechanisms by which physical activity enhances memory and may have implications for improving memory through modulating 5-hydroxytryptamine type 3 receptor.
基金supported by ANID FONDECYT No.1221178Centro Ciencia&Vida,FB210008,Financiamiento Basal para Centros Científicos y Tecnológicos de Excelencia de ANID to CTR.
文摘Aging is a physiological and complex process produced by accumulative age-dependent cellular damage,which significantly impacts brain regions like the hippocampus,an essential region involved in memory and learning.A crucial factor contributing to this decline is the dysfunction of mitochondria,particularly those located at synapses.Synaptic mitochondria are specialized organelles that produce the energy required for synaptic transmission but are also important for calcium homeostasis at these sites.In contrast,non-synaptic mitochondria primarily involve cellular metabolism and long-term energy supply.Both pools of mitochondria differ in their form,proteome,functionality,and cellular role.The proper functioning of synaptic mitochondria depends on processes such as mitochondrial dynamics,transport,and quality control.However,synaptic mitochondria are particularly vulnerable to age-associated damage,characterized by oxidative stress,impaired energy production,and calcium dysregulation.These changes compromise synaptic transmission,reducing synaptic activity and cognitive decline during aging.In the context of neurodegenerative diseases such as Alzheimer’s,Parkinson’s,and Huntington’s,the decline of synaptic mitochondrial function is even more pronounced.These diseases are marked by pathological protein accumulation,disrupted mitochondrial dynamics,and heightened oxidative stress,accelerating synaptic dysfunction and neuronal loss.Due to their specialized role and location,synaptic mitochondria are among the first organelles to exhibit dysfunction,underscoring their critical role in disease progression.This review delves into the main differences at structural and functional levels between synaptic and non-synaptic mitochondria,emphasizing the vulnerability of synaptic mitochondria to the aging process and neurodegeneration.These approaches highlight the potential of targeting synaptic mitochondria to mitigate age-associated cognitive impairment and synaptic degeneration.This review emphasizes the distinct vulnerabilities of hippocampal synaptic mitochondria,highlighting their essential role in sustaining brain function throughout life and their promise as therapeutic targets for safeguarding the cognitive capacities of people of advanced age.
文摘Your hometown is often a special place.It can be big or small.And it usually has an important place in your life and heart.You may not live there anymore.But you remember it well.Maybe you have warm feelings for your school,your friends and your neighbors there.You remember special places and fun times.There may be interesting museums or great sports teams in your hometown.You can tell people about them.
基金supported by the National Natural Science Foundation of China(Nos.51603005,52403186 and 52573150)Fujian Provincial Natural Science Foundation of China(No.2024J011447)+1 种基金Natural Science Foundation of Xiamen,China(No.3502Z20227305)the Postdoctoral Fellowship Program of CPSF(No.GZC20240095)。
文摘Near-infrared(NIR)light-responsive shape memory polymers(SMPs)show great promise for biomedical applications,but conventional photothermal agents suffer from high cost,complex preparation,or poor biocompatibility,while lignin-based alternatives exhibit insufficient photothermal conversion efficiency.Herein,we developed a novel strategy to enhance photothermal performance of lignin through sequential demethylation modification and Fe^(3+)complexation for constructing NIR light responsive SMPs.Dealkaline lignin(DL)was first demethylated using iodocyclohexane to produce demethylated lignin(DDL)with increased catechol content,which was then incorporated into polycaprolactone-based polyurethane synthesis followed by Fe^(3+)complexation.Results showed that DDL-Fe^(3+)complexes have significantly enhanced photothermal conversion performance,and the resulting PU-DDL+Fe^(3+)polyurethane with 0.5 wt%DDL content demonstrated a temperature increases of 39.8℃under 0.33 W·cm-2808 nm NIR irradiation.This excellent photothermal performance enables the shape-fixed PU-DDL+Fe^(3+)polyurethane to rapidly recover to its initial shape under NIR light irradiation.Additionally,PU-DDL+Fe^(3+)polyurethane exhibits good mechanical properties and biocompatibility,demonstrating significant biomedical application potential.
基金supported by the National Natural Science Foundation of China,No.82072529(to HWHT)Key Laboratory of Guangdong Higher Education Institutes,No.2021KSYS009(to HWHT)the China Postdoctoral Science Foundation,No.2022M720907(to HHG)。
文摘Alzheimer's disease is the primary cause of dementia and imposes a significant socioeconomic burden globally.Physical exercise,as an effective strategy for improving general health,has been largely reported for its effectiveness in slowing neurodegeneration and increasing brain functional plasticity,particularly in aging brains.However,the underlying mechanisms of exercise in cognitive aging remain largely unclear.Adiponectin,a cell-secreted protein hormone,has recently been found to regulate synaptic plasticity and mediate the antidepressant effects of physical exercise.Studies on the neuroprotective effects of adiponectin have revealed potential innovative treatments for Alzheimer's disease.Here,we reviewed the functions of adiponectin and its receptor in the brains of human and animal models of cognitive impairment.We summarized the role of adiponectin in Alzheimer's disease,focusing on its impact on energy metabolism,insulin resistance,and inflammation.We also discuss how exercise increases adiponectin secretion and its potential benefits for learning and memory.Finally,we highlight the latest research on chemical compounds that mimic exerciseenhanced secretion of adiponectin and its receptor in Alzheimer's disease.
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the STI2030-Major Projects,Nos.2021ZD0203500(to FW),2021ZD0202100(to XL)the National Natural Science Foundation of China,Nos.32222033(to FW),32330041(to LM)and 82021002(to LM),32171041(to XL)and 32450102(to XL)CAMS Innovation Fund for Medical Sciences,No.2021-I2M-5-009(to LM and XL).
文摘The overgeneralization of fear is associated with psychiatric disorders and cognitive decline.Recent studies have shown that engram cells in the dorsal dentate gyrus are integrated into functionally heterogeneous ensembles that are involved in contextual fear memory generalization and discrimination.However,the intracellular signals that promote fear generalization remain to be fully elucidated.In this study,we labeled and manipulated the c-Fos+and Npas4+ensembles in the dorsal dentate gyrus that are activated by contextual fear conditioning using a robust activity marking system.The results showed that increasing the excitability of Fos-dependent robust activity marking by overexpressing NaChBac or decreasing the excitability of Npas4-dependent robust activity marking by overexpressing Kir2.1 promoted fear memory generalization.Furthermore,CRISPR-mediated downregulation of the autophagy-related Atg5 or Atg7 genes in dorsal dentate gyrus neurons inhibited activation of c-Fos,but not Npas4.Knockdown of Atg5 or Atg7 in the Fos-dependent robust activity marking or Npas4-dependent robust activity marking ensemble led to an increase in neuronal excitability and a decrease in spine density in both ensembles.However,Atg7 knockdown in the Fos-dependent robust activity marking ensemble promoted memory generalization,while knockdown of Atg5 or Atg7 in the Npas4-dependent robust activity marking ensemble increased anxiety levels.These results contribute to our understanding of how the varying plasticity of memory engrams is involved in regulating fear memory generalization and anxiety.
基金funded by Science and Technology Innovation Project grant No.ZZKY20222304.
文摘Aiming at the problem of potential information noise introduced during the generation of ghost feature maps in GhostNet,this paper proposes a novel lightweight neural network model called ResghostNet.This model constructs the Resghost Module by combining residual connections and Adaptive-SE Blocks,which enhances the quality of generated feature maps through direct propagation of original input information and selection of important channels before cheap operations.Specifically,ResghostNet introduces residual connections on the basis of the Ghost Module to optimize the information flow,and designs a weight self-attention mechanism combined with SE blocks to enhance feature expression capabilities in cheap operations.Experimental results on the ImageNet dataset show that,compared to GhostNet,ResghostNet achieves higher accuracy while reducing the number of parameters by 52%.Although the computational complexity increases,by optimizing the usage strategy of GPU cachememory,themodel’s inference speed becomes faster.The ResghostNet is optimized in terms of classification accuracy and the number of model parameters,and shows great potential in edge computing devices.
基金funded by Science and Technology Research and Development Program Project of China Railway Group Limited(No.2023-Major-02)National Natural Science Foundation of China(Grant No.52378200)Sichuan Science and Technology Program(Grant No.2024NSFSC0017).
文摘Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning to mitigate accuracy degradation in 24-h forecasting.Initially,an optimized DB-SCAN(Density-Based Spatial Clustering of Applications with Noise)algorithm clusters wind fields based on wind direction,probability density,and spectral features,enhancing physical interpretability and reducing training complexity.Subsequently,a ResNet(Residual Network)extracts multi-scale patterns from decomposed wind signals,while transfer learning adapts the backbone network across clusters,cutting training time by over 90%.Finally,a CBAM(Convolutional Block Attention Module)attention mechanism is employed to prioritize features for LSTM-based prediction.Tested on the 2015 Jena wind speed dataset,the model demonstrates superior accuracy and robustness compared to state-of-the-art baselines.Key innovations include:(a)Physics-informed clustering for interpretable wind regime classification;(b)Transfer learning with deep feature extraction,preserving accuracy while minimizing training time;and(c)On the 2016 Jena wind speed dataset,the model achieves MAPE(Mean Absolute Percentage Error)values of 16.82%and 18.02%for the Weibull-shaped and Gaussian-shaped wind speed clusters,respectively,demonstrating the model’s robust generalization capacity.This framework offers an efficient and effective solution for long-term wind forecasting.
基金supported by the National Natural Science Foundation of China(No.51905543)。
文摘This study aimed to systematically regulate the performance of 4D printing composites by investigating the synergistic effects of dicumyl peroxide(DCP)and maleic anhydride-grafted polyethylene(MAH-g-PE)on a poly(lactic acid)/thermoplastic polyurethane(PLA/TPU)matrix.Specifically,using a 70 wt%/30 wt%PLA/TPU matrix and an L_(9)(3^(2))orthogonal design,composites were evaluated via morphology,shape memory,mechanical tests,and multi-criteria analysis.Moderate DCP enhanced crosslinking,improving storage modulus and thermal stability,while excessive DCP caused brittleness.Furthermore,MAH-g-PE effectively improved interfacial compatibility,and its synergy with DCP was dosage-dependent.Consequently,Sample 5 achieved optimal performance,exhibiting uniform fracture morphology,a shape fixation rate of98.8%with the fastest recovery,and balanced strength-ductility.Multi-criteria analysis identified elongation at break and recovery time as the top contributing factors,with consistent rankings validated by Spearman analysis(ρ=0.833,p<0.01).In summary,adjusting DCP and MAH-g-PE contents effectively modulates the crosslinking structure and interfacial properties of PLA/TPU composites,providing a viable strategy for developing high-performance,tunable 4D printing materials.
基金National Nature Science Foundation of China,No.30971530(to YR)The National 111 Project,No.B14036(to KFS)Key Basic Study and Functional Product Research of Wolfberry Grant of Ningxia Hui Autonomous Region(to KFS).
文摘Recent studies have indicated that stroke can lead to neuronal iron overload and lipid peroxidation.Lycium barbarum glycopeptide,which has a low molecular weight and potent antioxidant properties,may mitigate ferroptosis in stroke.We hypothesized that Lycium barbarum glycopeptide can effectively mitigate iron overload within ischemic neurons due to its robust antioxidant properties.The aims of this study were to investigate the effects of Lycium barbarum glycopeptide on ferroptotic damage following brain ischemia and explore the underlying mechanisms.A rat model of middle cerebral artery occlusion was established using the intraluminal filament method,and the rats were treated with Lycium barbarum glycopeptide for 7 consecutive days,beginning 24 hours after ischemia.Liproxstatin-1,a ferroptosis inhibitor,and Erastin,a ferroptosis activator,were used as controls.We found that treatment with Lycium barbarum glycopeptide resulted in significant reductions in infarct volume(as detected by triphenyltetrazolium chloride staining staining and magnetic resonance imaging)and neuronal death(as measured by Nissl staining),as well as improvements in sensory and motor functions in rats subjected to middle cerebral artery occlusion.Furthermore,treatment with Lycium barbarum glycopeptide alleviated anxiety and depression-like behaviors and improved memory.Additionally,Lycium barbarum glycopeptide effectively reduced the iron ion content in the ischemic penumbra of the cortex.Moreover,treatment with Lycium barbarum glycopeptide downregulated the expression of ferroptotic and oxidant proteins such as transferrin receptor 1,divalent metal transporter 1,and Acyl-CoA synthetase long-chain family member 4 and upregulated the expression of anti-ferroptotic and antioxidant proteins such as ferroportin 1,solute carrier family 7 member 11,glutathione,and glutathione peroxidase 4.However,these beneficial effects were reversed when ferroptosis was induced with the activator Erastin.Therefore,the positive effects of Lycium barbarum glycopeptide in ischemic stroke are likely mediated through activation of the anti-ferroptotic pathway and the antioxidative System Xc-glutathione-glutathione peroxidase 4 pathway.Overall,our findings highlight the potential use of Lycium barbarum glycopeptide as a neuroprotective agent targeting both ferroptosis and oxidation to decrease ischemic brain damage.
基金supported by the Tianjin Scientific Research Start-up Foundation for Talent Introduction(2021-1-10)the 14th Five-Year Plan Peak Discipline Support Plan of Tianjin Medical University Cancer Institute and Hospital(7-2-13)+3 种基金National Natural Science Foundation of China(82171221),Beijing Bethune Charitable Foundation(YXJL-2024-0778-0030)Beijing Science and Technology Innovation Medical Development Foundation(KC2024-JF-0069)Tianjin Medical University Postgraduate Education Reform Research Program(TMUYY02)Tianjin Key Medical Discipline(Specialty)Construction(TJYXZDXK-009A).
文摘GABA_(A) receptors containingα5-subunits(GABA_(A)R-α5)cluster at both extrasynaptic and synaptic locations,interacting with the scaffold proteins radixin and gephyrin,respectively,and the re-localization of GABA_(A)R-α5 influences GABAergic transmission.Here,we found that when early spatial memory deficits occurred in aged mice at 24 h after sevoflurane anesthesia,there was a re-localization of GABA_(A)R-α5 that enhanced tonic inhibition and reduced the decay kinetics of miniature inhibitory postsynaptic currents in the hippocampal CA1 region.Mechanistically,increased phosphorylation of radixin at threonine 564(Thr564)mediates the re-localization of GABA_(A)R-α5.Acute treatment with the selective extrasynaptic GABA_(A)R-α5 antagonist S44819 restored the GABA_(A)R-α5-mediated inhibitory currents by reversing radixin phosphorylation-dependent GABA_(A)R-α5 re-localization,then improved the sevoflurane-induced spatial memory impairment in aged mice.Our results suggest that the localization of GABA_(A)R-α5 altered by sevoflurane is linked to unbalanced GABAergic transmission,which induces early memory impairment in aged mice.Modulating the GABA_(A)R-α5 localization might be a novel strategy to improve memory after sevoflurane exposure.
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 and funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2025R410),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Recognizing human interactions in RGB videos is a critical task in computer vision,with applications in video surveillance.Existing deep learning-based architectures have achieved strong results,but are computationally intensive,sensitive to video resolution changes and often fail in crowded scenes.We propose a novel hybrid system that is computationally efficient,robust to degraded video quality and able to filter out irrelevant individuals,making it suitable for real-life use.The system leverages multi-modal handcrafted features for interaction representation and a deep learning classifier for capturing complex dependencies.Using Mask R-CNN and YOLO11-Pose,we extract grayscale silhouettes and keypoint coordinates of interacting individuals,while filtering out irrelevant individuals using a proposed algorithm.From these,we extract silhouette-based features(local ternary pattern and histogram of optical flow)and keypoint-based features(distances,angles and velocities)that capture distinct spatial and temporal information.A Bidirectional Long Short-Term Memory network(BiLSTM)then classifies the interactions.Extensive experiments on the UT Interaction,SBU Kinect Interaction and the ISR-UOL 3D social activity datasets demonstrate that our system achieves competitive accuracy.They also validate the effectiveness of the chosen features and classifier,along with the proposed system’s computational efficiency and robustness to occlusion.
基金funded by the National Natural Science Foundation of China(NSFC No.52322610)Hong Kong Research Grants Council Theme-based Research Scheme(T22-505/19-N)Furthermore,this research was undertaken with the assistance of computational resources from the National Computational Infrastructure(NCI Australia),an NCRISenabled capability supported by the Australian Government.
文摘Shrublands and grasslands,which constitute approximately 70%of Australia’s vegetation,play a critical role in global wildfire-prone regions.To advance the understanding of grass fire spread,a three-dimensional,physicsbased fire model provides valuable insights into fire dynamics.However,such models are computationally intensive and time-consuming.To address these challenges,we constructed an extensive numerical database comprising 64,000 high-fidelity wildfire simulation cases and implemented a Long Short-Term Memory neural network architecture.The model demonstrates strong predictive performance,achieving a coefficient of determination(R2)of 0.96 on training data,indicating excellent agreement with the physics-based simulation outputs.By utilizing coordinates from five reference points to predict fire front movement,this approach offers a novel method for analysing fire dynamics in homogeneous fuel beds with an average deviation of less than 2.5%.Combining the strengths of physics-based modelling and deep learning,our research enhances fire spread prediction accuracy of over 95%while significantly reducing computational demands.Future efforts will focus on refining the model,expanding the dataset,and incorporating additional variables to improve predictive capabilities and operational applicability.
基金supported by the National Natural Science Foundation of China(No.51977113)the Science and Technology Project of State Grid Zhejiang Electric Power Co.,Ltd.(No.5211JX240001).
文摘Accurate and reliable power system data are fundamental for critical operations such as gridmonitoring,fault diagnosis,and load forecasting,underpinned by increasing intelligentization and digitalization.However,data loss and anomalies frequently compromise data integrity in practical settings,significantly impacting system operational efficiency and security.Most existing data recovery methods require complete datasets for training,leading to substantial data and computational demands and limited generalization.To address these limitations,this study proposes a missing data imputation model based on an improved Generative Adversarial Network(BAC-GAN).Within the BAC-GAN framework,the generator utilizes Bidirectional Long Short-Term Memory(BiLSTM)networks and Multi-Head Attention mechanisms to capture temporal dependencies and complex relationships within power system data.The discriminator employs a Convolutional Neural Network(CNN)architecture to integrate local features with global structures,effectivelymitigating the generation of implausible imputations.Experimental results on two public datasets demonstrate that the BAC-GAN model achieves superior data recovery accuracy compared to five state-of-the-art and classical benchmarkmethods,with an average improvement of 17.7%in reconstruction accuracy.The proposedmethod significantly enhances the accuracy of grid fault diagnosis and provides reliable data support for the stable operation of smart grids,showing great potential for practical applications in power systems.
