The nervous system processes a vast amount of information,performing computations that underlie perception,cognition,and behavior.During development,neuronal guidance genes,which encode extracellular cues,their recept...The nervous system processes a vast amount of information,performing computations that underlie perception,cognition,and behavior.During development,neuronal guidance genes,which encode extracellular cues,their receptors,and downstream signal transducers,organize neural wiring to generate the complex architecture of the nervous system.It is now evident that many of these neuroguidance cues and their receptors are active during development and are also expressed in the adult nervous system.This suggests that neuronal guidance pathways are critical not only for neural wiring but also for ongoing function and maintenance of the mature nervous system.Supporting this view,these pathways continue to regulate synaptic connectivity,plasticity,and remodeling,and overall brain homeostasis throughout adulthood.Genetic and transcriptomic analyses have further revealed many neuronal guidance genes to be associated with a wide range of neurodegenerative and neuropsychiatric disorders.Although the precise mechanisms by which aberrant neuronal guidance signaling drives the pathogenesis of these diseases remain to be clarified,emerging evidence points to several common themes,including dysfunction in neurons,microglia,astrocytes,and endothelial cells,along with dysregulation of neuron-microglia-astrocyte,neuroimmune,and neurovascular interactions.In this review,we explore recent advances in understanding the molecular and cellular mechanisms by which aberrant neuronal guidance signaling contributes to disease pathogenesis through altered cell-cell interactions.For instance,recent studies have unveiled two distinct semaphorin-plexin signaling pathways that affect microglial activation and neuroinflammation.We discuss the challenges ahead,along with the therapeutic potentials of targeting neuronal guidance pathways for treating neurodegenerative diseases.Particular focus is placed on how neuronal guidance mechanisms control neuron-glia and neuroimmune interactions and modulate microglial function under physiological and pathological conditions.Specifically,we examine the crosstalk between neuronal guidance signaling and TREM2,a master regulator of microglial function,in the context of pathogenic protein aggregates.It is well-established that age is a major risk factor for neurodegeneration.Future research should address how aging and neuronal guidance signaling interact to influence an individual’s susceptibility to various late-onset neurological diseases and how the progression of these diseases could be therapeutically blocked by targeting neuronal guidance pathways.展开更多
Phosphatase and tensin homolog deleted on chromosome 10(PTEN)messenger RNA(mRNA)delivery has fueled a great hope for tumor immunotherapy via augmenting the immune sensitivity in many human cancers.However,therapeutic ...Phosphatase and tensin homolog deleted on chromosome 10(PTEN)messenger RNA(mRNA)delivery has fueled a great hope for tumor immunotherapy via augmenting the immune sensitivity in many human cancers.However,therapeutic efficacy and clinical translation are limited by inadequate mRNA expression,insufficient immune stimulation and stringent storage requirements.Herein,inspired by the intrinsic properties of metal ions and exosomes,we developed a biomimetic delivery system(Mn-NP@PM)with superior stability for precise colorectal cancer immunotherapy.This platform employs adjuvant-metal-ion chelation for PTEN mRNA loading and PD-L1 antibodies(αPD-L1)-modified monocyte-macrophage membrane coating for mRNA protection and tumor targeting.Mn^(2+) was specifically selected due to its capacity for reversible mRNA binding through weak non-electrostatic interactions,facilitating efficient release,while simultaneously activating the stimulator of interferon genes(STING)pathway.Importantly,Mn-NP@PM exhibited membrane fusion for immediate cytosolic mRNA delivery,bypassing endo-lysosomal escape,optimizing transportation efficiency.Clinical-data-driven analyses further demonstrated that Mn-NP@PM-mediated PTEN restoration significantly increased T-cell infiltration and strengthened antitumor immunity in humanized patient derived xenograft(PDX)models.Collectively,this biomimetic,metal-ion-chelating,membrane-coated mRNA delivery system represents a versatile and clinically translatable strategy for personalized cancer immunotherapy.展开更多
Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model...Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.展开更多
Lip language provides a silent,intuitive,and efficient mode of communication,offering a promising solution for individuals with speech impairments.Its articulation relies on complex movements of the jaw and the muscle...Lip language provides a silent,intuitive,and efficient mode of communication,offering a promising solution for individuals with speech impairments.Its articulation relies on complex movements of the jaw and the muscles surrounding it.However,the accurate and real-time acquisition and decoding of these movements into reliable silent speech signals remains a significant challenge.In this work,we propose a real-time silent speech recognition system,which integrates a triboelectric nanogenerator-based flexible pressure sensor(FPS)with a deep learning framework.The FPS employs a porous pyramid-structured silicone film as the negative triboelectric layer,enabling highly sensitive pressure detection in the low-force regime(1 V N^(-1) for 0-10 N and 4.6 V N^(-1) for 10-24 N).This allows it to precisely capture jaw movements during speech and convert them into electrical signals.To decode the signals,we proposed a convolutional neural networklong short-term memory(CNN-LSTM)hybrid network,combining CNN and LSTM model to extract both local spatial features and temporal dynamics.The model achieved 95.83%classification accuracy in 30 categories of daily words.Furthermore,the decoded silent speech signals can be directly translated into executable commands for contactless and precise control of the smartphone.The system can also be connected to AR glasses,offering a novel human-machine interaction approach with promising potential in AR/VR applications.展开更多
Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating In...Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.展开更多
针对跟踪复杂机动目标过程中由于目标运动状态发生变化导致的跟踪误差较大的问题,提出一种自适应交互多模型无迹卡尔曼滤波(interacting multiple model unscented Kalman filter,IMM-UKF)算法,使用模型概率后验信息和模型似然函数自适...针对跟踪复杂机动目标过程中由于目标运动状态发生变化导致的跟踪误差较大的问题,提出一种自适应交互多模型无迹卡尔曼滤波(interacting multiple model unscented Kalman filter,IMM-UKF)算法,使用模型概率后验信息和模型似然函数自适应修正马尔可夫转移概率矩阵(transition probability matrix,TPM)。设计模型概率校正方法和模型转移加速方法,两种方法分别作用于模型稳定阶段和模型转移阶段,提高模型概率准确度和模型转移响应速度,减小状态估计误差。最后,通过两种场景下的实验验证所提算法在目标具有复杂运动状态下的性能,并与传统方法进行对比分析,在目标做机动运动时,位置精度和速度精度分别提高了15%和26%,验证了算法的有效性和可行性。展开更多
The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first i...The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.展开更多
Immersive services are the typical emerging services in current IMT-2020 network.With the development of network evolution,real-time interactive applications emerge one after another.This article provides an overview ...Immersive services are the typical emerging services in current IMT-2020 network.With the development of network evolution,real-time interactive applications emerge one after another.This article provides an overview on immersive services which focus on real-time interaction.The scenarios,framework,requirements,key technologies,and issues of interactive immersive service are presented.展开更多
English immersion in the mainland of China has started in Xi＇an since the late 1990s, and extended into other cities in the mainland of China. This study reported the findings of the students＇ interactive peer learn...English immersion in the mainland of China has started in Xi＇an since the late 1990s, and extended into other cities in the mainland of China. This study reported the findings of the students＇ interactive peer learning model in the immersion programs, such as peer prompting and waiting; non-verbal expressions; correcting errors and modulating speaking volume; translation; attending to the peer interlocutor＇ s needs; and reciprocating peer assistance.展开更多
In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operati...In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.展开更多
基金supported by JSPS(KAKENHI:21K06205,23K06937,24K23419)AMED(to JYK,SaY,TM,SiY,YT,and NH)JYW had long been supported by the NIH.
文摘The nervous system processes a vast amount of information,performing computations that underlie perception,cognition,and behavior.During development,neuronal guidance genes,which encode extracellular cues,their receptors,and downstream signal transducers,organize neural wiring to generate the complex architecture of the nervous system.It is now evident that many of these neuroguidance cues and their receptors are active during development and are also expressed in the adult nervous system.This suggests that neuronal guidance pathways are critical not only for neural wiring but also for ongoing function and maintenance of the mature nervous system.Supporting this view,these pathways continue to regulate synaptic connectivity,plasticity,and remodeling,and overall brain homeostasis throughout adulthood.Genetic and transcriptomic analyses have further revealed many neuronal guidance genes to be associated with a wide range of neurodegenerative and neuropsychiatric disorders.Although the precise mechanisms by which aberrant neuronal guidance signaling drives the pathogenesis of these diseases remain to be clarified,emerging evidence points to several common themes,including dysfunction in neurons,microglia,astrocytes,and endothelial cells,along with dysregulation of neuron-microglia-astrocyte,neuroimmune,and neurovascular interactions.In this review,we explore recent advances in understanding the molecular and cellular mechanisms by which aberrant neuronal guidance signaling contributes to disease pathogenesis through altered cell-cell interactions.For instance,recent studies have unveiled two distinct semaphorin-plexin signaling pathways that affect microglial activation and neuroinflammation.We discuss the challenges ahead,along with the therapeutic potentials of targeting neuronal guidance pathways for treating neurodegenerative diseases.Particular focus is placed on how neuronal guidance mechanisms control neuron-glia and neuroimmune interactions and modulate microglial function under physiological and pathological conditions.Specifically,we examine the crosstalk between neuronal guidance signaling and TREM2,a master regulator of microglial function,in the context of pathogenic protein aggregates.It is well-established that age is a major risk factor for neurodegeneration.Future research should address how aging and neuronal guidance signaling interact to influence an individual’s susceptibility to various late-onset neurological diseases and how the progression of these diseases could be therapeutically blocked by targeting neuronal guidance pathways.
基金supported by the Basic Science Center Project of the National Natural Science Foundation of China(22388101)New Cornerstone Science Foundation(NCI202318)+6 种基金the National Natural Science Foundation of China(32171398 and T242200557)the National Key R&D Program of China(2023YFA1610200 and 2022YFA1603701)Beijing Nova Program(20220484060,20230484426,and 20240484661)Beijing Natural Science Foundation(F251001)Chinese Academy of Sciences Project for Young Scientists in Basic Research(YSBR-036)the One Hundred Talents Program of Chinese Academy of Sciences(E3G551R1ZX)Chinese Academy of Medical Sciences(CAMS)and Innovation Fund for Medical Sciences(CIFMS2019-I2M-5-018).
文摘Phosphatase and tensin homolog deleted on chromosome 10(PTEN)messenger RNA(mRNA)delivery has fueled a great hope for tumor immunotherapy via augmenting the immune sensitivity in many human cancers.However,therapeutic efficacy and clinical translation are limited by inadequate mRNA expression,insufficient immune stimulation and stringent storage requirements.Herein,inspired by the intrinsic properties of metal ions and exosomes,we developed a biomimetic delivery system(Mn-NP@PM)with superior stability for precise colorectal cancer immunotherapy.This platform employs adjuvant-metal-ion chelation for PTEN mRNA loading and PD-L1 antibodies(αPD-L1)-modified monocyte-macrophage membrane coating for mRNA protection and tumor targeting.Mn^(2+) was specifically selected due to its capacity for reversible mRNA binding through weak non-electrostatic interactions,facilitating efficient release,while simultaneously activating the stimulator of interferon genes(STING)pathway.Importantly,Mn-NP@PM exhibited membrane fusion for immediate cytosolic mRNA delivery,bypassing endo-lysosomal escape,optimizing transportation efficiency.Clinical-data-driven analyses further demonstrated that Mn-NP@PM-mediated PTEN restoration significantly increased T-cell infiltration and strengthened antitumor immunity in humanized patient derived xenograft(PDX)models.Collectively,this biomimetic,metal-ion-chelating,membrane-coated mRNA delivery system represents a versatile and clinically translatable strategy for personalized cancer immunotherapy.
文摘Aiming at the problems of lagging curriculum,weak practice,and single evaluation in the cultivation of HarmonyOS Development talents,this study constructs a“teacher-machine-student”ternary interactive teaching model based on the Congyou platform.Through the building block curriculum system,the HarmonyOS technology stack is decoupled into dynamic capability units,and a multi-disciplinary cross-case library is jointly built with Huawei,which significantly improves the synchronization of teaching content and industrial technology.This paper innovatively designs an AI collaborative teaching system,which employs knowledge graphs to plan learning paths,utilizes virtual equipment clusters to simulate development environments,and establishes a“diagnosis-feedback-enhancement”closed loop through AI-based review,thereby effectively improving students’development efficiency and code reuse rate.A three-dimensional evaluation model integrating task outcomes,process performance,and innovation is constructed,incorporating indicators such as code standardization and an innovation index to strengthen the cultivation of engineering thinking and innovative ability.Furthermore,a data-driven support platform is built to generate student competency profiles,open up the“credit-competency-certification”pathway,promote the transformation of course achievements into contributions to the Huawei ecosystem,and significantly shorten the job adaptation cycle for graduates.The research results provide a replicable paradigm for the cultivation of domestic operating system talents.
基金supported by the Natural Science Foundation of Fujian Province under Grant No.2024J010016Fujian Province Young and Middle aged Teacher Education Research Project No.JAT241317the Mindu Innovation Laboratory Project under Grant No.2020ZZ113.
文摘Lip language provides a silent,intuitive,and efficient mode of communication,offering a promising solution for individuals with speech impairments.Its articulation relies on complex movements of the jaw and the muscles surrounding it.However,the accurate and real-time acquisition and decoding of these movements into reliable silent speech signals remains a significant challenge.In this work,we propose a real-time silent speech recognition system,which integrates a triboelectric nanogenerator-based flexible pressure sensor(FPS)with a deep learning framework.The FPS employs a porous pyramid-structured silicone film as the negative triboelectric layer,enabling highly sensitive pressure detection in the low-force regime(1 V N^(-1) for 0-10 N and 4.6 V N^(-1) for 10-24 N).This allows it to precisely capture jaw movements during speech and convert them into electrical signals.To decode the signals,we proposed a convolutional neural networklong short-term memory(CNN-LSTM)hybrid network,combining CNN and LSTM model to extract both local spatial features and temporal dynamics.The model achieved 95.83%classification accuracy in 30 categories of daily words.Furthermore,the decoded silent speech signals can be directly translated into executable commands for contactless and precise control of the smartphone.The system can also be connected to AR glasses,offering a novel human-machine interaction approach with promising potential in AR/VR applications.
文摘Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.
文摘针对跟踪复杂机动目标过程中由于目标运动状态发生变化导致的跟踪误差较大的问题,提出一种自适应交互多模型无迹卡尔曼滤波(interacting multiple model unscented Kalman filter,IMM-UKF)算法,使用模型概率后验信息和模型似然函数自适应修正马尔可夫转移概率矩阵(transition probability matrix,TPM)。设计模型概率校正方法和模型转移加速方法,两种方法分别作用于模型稳定阶段和模型转移阶段,提高模型概率准确度和模型转移响应速度,减小状态估计误差。最后,通过两种场景下的实验验证所提算法在目标具有复杂运动状态下的性能,并与传统方法进行对比分析,在目标做机动运动时,位置精度和速度精度分别提高了15%和26%,验证了算法的有效性和可行性。
基金supported by the National Natural Science Foundation of China,Nos.82104560(to CL),U21A20400(to QW)the Natural Science Foundation of Beijing,No.7232279(to XW)the Project of Beijing University of Chinese Medicine,No.2022-JYB-JBZR-004(to XW)。
文摘The primary mechanism of secondary injury after cerebral ischemia may be the brain inflammation that emerges after an ischemic stroke,which promotes neuronal death and inhibits nerve tissue regeneration.As the first immune cells to be activated after an ischemic stroke,microglia play an important immunomodulatory role in the progression of the condition.After an ischemic stroke,peripheral blood immune cells(mainly T cells)are recruited to the central nervous system by chemokines secreted by immune cells in the brain,where they interact with central nervous system cells(mainly microglia)to trigger a secondary neuroimmune response.This review summarizes the interactions between T cells and microglia in the immune-inflammatory processes of ischemic stroke.We found that,during ischemic stroke,T cells and microglia demonstrate a more pronounced synergistic effect.Th1,Th17,and M1 microglia can co-secrete proinflammatory factors,such as interferon-γ,tumor necrosis factor-α,and interleukin-1β,to promote neuroinflammation and exacerbate brain injury.Th2,Treg,and M2 microglia jointly secrete anti-inflammatory factors,such as interleukin-4,interleukin-10,and transforming growth factor-β,to inhibit the progression of neuroinflammation,as well as growth factors such as brain-derived neurotrophic factor to promote nerve regeneration and repair brain injury.Immune interactions between microglia and T cells influence the direction of the subsequent neuroinflammation,which in turn determines the prognosis of ischemic stroke patients.Clinical trials have been conducted on the ways to modulate the interactions between T cells and microglia toward anti-inflammatory communication using the immunosuppressant fingolimod or overdosing with Treg cells to promote neural tissue repair and reduce the damage caused by ischemic stroke.However,such studies have been relatively infrequent,and clinical experience is still insufficient.In summary,in ischemic stroke,T cell subsets and activated microglia act synergistically to regulate inflammatory progression,mainly by secreting inflammatory factors.In the future,a key research direction for ischemic stroke treatment could be rooted in the enhancement of anti-inflammatory factor secretion by promoting the generation of Th2 and Treg cells,along with the activation of M2-type microglia.These approaches may alleviate neuroinflammation and facilitate the repair of neural tissues.
文摘Immersive services are the typical emerging services in current IMT-2020 network.With the development of network evolution,real-time interactive applications emerge one after another.This article provides an overview on immersive services which focus on real-time interaction.The scenarios,framework,requirements,key technologies,and issues of interactive immersive service are presented.
文摘English immersion in the mainland of China has started in Xi＇an since the late 1990s, and extended into other cities in the mainland of China. This study reported the findings of the students＇ interactive peer learning model in the immersion programs, such as peer prompting and waiting; non-verbal expressions; correcting errors and modulating speaking volume; translation; attending to the peer interlocutor＇ s needs; and reciprocating peer assistance.
基金the Talent Fund of Beijing Jiaotong University(Grant No.2024XKRC055).
文摘In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.
