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Aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders:progress of experimental models based on disease pathogenesis
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作者 Li Xu Huiming Xu Changyong Tang 《Neural Regeneration Research》 SCIE CAS 2025年第2期354-365,共12页
Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism rem... Neuromyelitis optica spectrum disorders are neuroinflammatory demyelinating disorders that lead to permanent visual loss and motor dysfunction.To date,no effective treatment exists as the exact causative mechanism remains unknown.Therefore,experimental models of neuromyelitis optica spectrum disorders are essential for exploring its pathogenesis and in screening for therapeutic targets.Since most patients with neuromyelitis optica spectrum disorders are seropositive for IgG autoantibodies against aquaporin-4,which is highly expressed on the membrane of astrocyte endfeet,most current experimental models are based on aquaporin-4-IgG that initially targets astrocytes.These experimental models have successfully simulated many pathological features of neuromyelitis optica spectrum disorders,such as aquaporin-4 loss,astrocytopathy,granulocyte and macrophage infiltration,complement activation,demyelination,and neuronal loss;however,they do not fully capture the pathological process of human neuromyelitis optica spectrum disorders.In this review,we summarize the currently known pathogenic mechanisms and the development of associated experimental models in vitro,ex vivo,and in vivo for neuromyelitis optica spectrum disorders,suggest potential pathogenic mechanisms for further investigation,and provide guidance on experimental model choices.In addition,this review summarizes the latest information on pathologies and therapies for neuromyelitis optica spectrum disorders based on experimental models of aquaporin-4-IgG-seropositive neuromyelitis optica spectrum disorders,offering further therapeutic targets and a theoretical basis for clinical trials. 展开更多
关键词 AQUAPORIN-4 experimental model neuromyelitis optica spectrum disorder PATHOGENESIS
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Exploiting fly models to investigate rare human neurological disorders
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作者 Tomomi Tanaka Hyung-Lok Chung 《Neural Regeneration Research》 SCIE CAS 2025年第1期21-28,共8页
Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein functio... Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases. 展开更多
关键词 ACOX1 Drosophila melanogaster GLIA lipid metabolism model organisms NEUROINFLAMMATION neurologic disorders NEURON rare disease VLCFA
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A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis
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作者 Xiao Liang Xingping Quan +6 位作者 Xiaorui Geng Yujing Huang Yonghua Zhao Lei Xi Zhen Yuan Ping Wang Bin Liu 《Neural Regeneration Research》 SCIE CAS 2025年第7期2029-2037,共9页
To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these me... To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral cortex.However,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly age-related.In this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed laser.We observed the molding process in mice of different ages and presented age-dependent vascular embolism differentiation.Moreover,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a stroke.Our imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes. 展开更多
关键词 AGE-DEPENDENT cerebral cortex ischemic stroke mouse model optical coherence tomography angiography photoacoustic microscopy PHOTOTHROMBOSIS vascular imaging
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Reduced mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor contributes to neurodegeneration in a model of spinal and bulbar muscular atrophy pathology
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作者 Yiyang Qin Wenzhen Zhu +6 位作者 Tingting Guo Yiran Zhang Tingting Xing Peng Yin Shihua Li Xiao-Jiang Li Su Yang 《Neural Regeneration Research》 SCIE CAS 2025年第9期2655-2666,共12页
Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen r... Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy patients.These aggregates alter protein-protein interactions and compromise transcriptional activity.In this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic factor.Overexpressio n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor aggregation.Conversely.knocking down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor aggregation.Our findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy. 展开更多
关键词 androgen receptor mesencephalic astrocyte-derived neurotrophic factor mouse model NEURODEGENERATION neuronal loss neurotrophic factor polyglutamine disease protein misfolding spinal and bulbar muscular atrophy transcription factor
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基于SSA-BP神经网络的车-轨-桥系统随机振动分析
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作者 何旭辉 赵永帅 蔡陈之 《铁道科学与工程学报》 EI CAS CSCD 北大核心 2024年第8期3225-3236,共12页
轨道及桥梁结构参数随机性对车-轨-桥耦合系统的振动影响不能忽略。基于代理模型研究轨道-桥梁间3层弹簧刚度和弹簧阻尼以及桥梁刚度和阻尼的随机性对竖向车-轨-桥耦合系统动力响应的影响。首先,基于经典的车-轨-桥耦合系统力学模型(没... 轨道及桥梁结构参数随机性对车-轨-桥耦合系统的振动影响不能忽略。基于代理模型研究轨道-桥梁间3层弹簧刚度和弹簧阻尼以及桥梁刚度和阻尼的随机性对竖向车-轨-桥耦合系统动力响应的影响。首先,基于经典的车-轨-桥耦合系统力学模型(没有考虑桥墩),采用Monte-Carlo生成2 000个样本集,作为代理模型的训练集。然后,对比SSA-BP(麻雀优化BP算法)与传统BP神经网络、GA-BP神经网络(遗传优化BP算法)对车辆和桥梁响应的预测精度,同时探讨样本数量以及Levenberg-Marquardt和Bayesian Regulation训练算法对SSA-BP神经网络预测精度的影响。最后,假定各随机参数概率分布规律服从高斯型正态分布,所有随机参数变异系数均分为0.05、0.10、0.15、0.20、0.25等5个级别,采用所提出的SSA-BP神经网络研究轨道及桥梁的刚度和阻尼变化对车辆和桥梁响应极值的影响。结果表明:与经典的车-轨-桥耦合系统力学模型相比,所提出的代理模型具有更高的计算效率;SSA-BP模型对车辆和桥梁响应的预测精度高于GA-BP模型,GA-BP模型的预测精度高于传统的BP模型;SSA-BP模型采用Levenberg-Marquardt训练算法对车辆和桥梁响应的预测精度优于Bayesian Regulation训练算法的预测精度;道砟和桥梁之间弹簧刚度的随机变化对桥梁随机振动响应尤为明显;钢轨和轨枕之间弹簧刚度的随机性对车体响应的影响不可忽视,而桥梁刚度和阻尼随机性对车体的影响可不考虑。研究成果可为车轨桥系统随机振动响应预测进一步研究提供依据和参考。 展开更多
关键词 桥梁工程 车轨桥系统 ssa-bp 随机振动 代理模型
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基于天气状态模式识别的SSA-BP神经网络光伏电厂功率及碳减排量预测
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作者 胡浔惠 丁伟 +3 位作者 曹敬 陈时熠 李梦阳 姚钦才 《可再生能源》 CAS CSCD 北大核心 2024年第7期877-885,共9页
文章提出了一种基于天气状态模式识别并结合SSA-BP(Sparrow Search Algorithm-Back Propagation)预测光伏出力的方法。首先,在分析辐照度、温度、风速等参数变化规律基础上,基于高斯混合模型,针对专业天气类型开展分类,获得类晴、类雨... 文章提出了一种基于天气状态模式识别并结合SSA-BP(Sparrow Search Algorithm-Back Propagation)预测光伏出力的方法。首先,在分析辐照度、温度、风速等参数变化规律基础上,基于高斯混合模型,针对专业天气类型开展分类,获得类晴、类雨和类阴3种典型的广义天气;然后,将数据作为SSA-BP神经网络输入,对光伏电厂出力分类进行预测;最后,结合碳核算方法学对光伏发电项目碳减排量进行核算。结果表明:利用分类识别和改进的SSA-BP神经网络,在3种天气类型预测中平均相对误差分别为0.195,0.243,0.310;SSA-BP与其他模型相比,平均相对误差降低了17.8%~66.7%。此外,预测CO_(2)减排量与实际核算值相对误差为3.37%,亦表现出良好预测效果。 展开更多
关键词 光伏发电 模式识别 ssa-bp神经网络 功率预测 天气状态
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采用STAMP-24Model的多组织事故分析
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作者 曾明荣 秦永莹 +2 位作者 刘小航 栗婧 尚长岭 《安全与环境学报》 CAS CSCD 北大核心 2024年第7期2741-2750,共10页
安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事... 安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。 展开更多
关键词 安全工程 系统理论事故建模与过程模型(STAMP) 24model 多组织事故 原因分析
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基于改进24Model-ISM-SNA建筑工人不安全行为关联路径研究
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作者 赵平 刘钰 +1 位作者 靳丽艳 王佳慧 《工业安全与环保》 2024年第7期37-40,共4页
建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险... 建筑施工现场环境复杂,为有效控制不安全行为发生,基于行为安全“2-4”模型对360份具有代表性的建筑安全事故调查报告进行分析,提取出22个不安全行为的主要影响因素。利用灰色关联分析方法(GRA)改进的集成ISM-SNA模型,将不安全行为风险因素划分为表层、过渡层与深层,然后对风险因素进行可视化分析、中心度分析及凝聚子群分析,揭示了各致因因素间的关联关系和传导路径。结果表明,建筑工人不安全行为影响因素可划分成7级3阶的多级递阶结构,安全意识、现场监管、外部环境是建筑工人不安全行为的关键影响因素,同时现场监管和隐患排查到位能有效降低不安全行为的发生。 展开更多
关键词 建筑工人 不安全行为 24model 解释结构模型(ISM) 社会网络分析(SNA)
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基于24Model的地铁内涝事故原因分析与评估
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作者 张江石 胡馨月 +3 位作者 侯轩 李泳暾 李梓萌 高进东 《安全与环境工程》 CAS CSCD 北大核心 2024年第6期111-117,共7页
为降低地铁内涝事故灾害风险,基于事故致因“2-4”模型,分析了地铁内涝事故致灾因子,采用层次分析法构建了地铁内涝事故原因分析指标体系,确定了各风险因子的权重,并利用模糊综合评价法对地铁内涝事故进行了定量评估,识别出关键的影响... 为降低地铁内涝事故灾害风险,基于事故致因“2-4”模型,分析了地铁内涝事故致灾因子,采用层次分析法构建了地铁内涝事故原因分析指标体系,确定了各风险因子的权重,并利用模糊综合评价法对地铁内涝事故进行了定量评估,识别出关键的影响因素。结果表明:地铁内涝事故一级指标中不安全动作与物态因素最重要,其中影响最大的指标包括擅自更改建筑设计、未按照要求检查水位情况、未及时排水、出入口不符合防汛标准等因素;习惯性不安全行为的权重位居第二,表明该指标因素较为重要,同时安全管理体系得分位居第二,表明该指标因素较易发生。对关键指标采取防范措施,可有效降低风险,从而减少地铁内涝事故的发生。 展开更多
关键词 安全工程 地铁内涝 24model 层次分析法 模糊综合评价法
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基于24Model-D-ISM的地铁站火灾疏散影响因素研究
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作者 孙世梅 张家严 《中国安全科学学报》 CAS CSCD 北大核心 2024年第4期153-159,共7页
为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾... 为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。 展开更多
关键词 “2-4”模型(24model) 决策试验与评价实验法(DEMATEL) 解释结构模型(ISM) 地铁站 火灾疏散 影响因素
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基于SSA-BP近似模型的湿式制动器带排转矩参数CSO智能优化
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作者 李杰 王帅 +1 位作者 兰海 王志勇 《机械传动》 北大核心 2024年第7期128-136,共9页
针对湿式制动器在非制动工况下功率损失的工程问题,考虑摩擦副间隙内部的润滑油对摩擦副带排转矩的影响,运用麻雀搜索算法-反向传播(Sparrow Search Algorithm-Back Propagation,SSABP)神经网络的强大非线性拟合能力,以制动器空载工况... 针对湿式制动器在非制动工况下功率损失的工程问题,考虑摩擦副间隙内部的润滑油对摩擦副带排转矩的影响,运用麻雀搜索算法-反向传播(Sparrow Search Algorithm-Back Propagation,SSABP)神经网络的强大非线性拟合能力,以制动器空载工况为输入量、带排转矩为输出量,建立了湿式制动器近似模型;与传统的BP模型对比,该模型预测精度明显提高,更能满足实际工程的需要;同时,为获取最小带排转矩,采用鸡群优化(Chicken Swarm Optimization,CSO)智能算法对工况参数进行搜索寻优,得到湿式制动器的最佳工况。经试验测试验证,与优化前相比,优化后摩擦副间的带排转矩和功率损失有着明显降低。研究为湿式制动器结构的进一步优化提供了理论基础和工程实践经验。 展开更多
关键词 湿式制动器 带排转矩 ssa-bp模型 CSO算法 近似模型
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基于SSA-BP的爆破振动峰值速度预测研究
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作者 李攀云 高文学 +3 位作者 张小军 何茂林 葛晨雨 王林 《爆破》 CSCD 北大核心 2024年第3期205-211,共7页
为了精准预测爆破振动峰值速度(PPV),有效降低爆破振动的危害,以星光一号露天矿山爆破工程为依托,选取爆心距、堵塞长度、最小抵抗线、炸药单耗、最大单孔装药量、总延期时间、最大单响药量等7个影响因素作为输入变量,采用灰色关联分析... 为了精准预测爆破振动峰值速度(PPV),有效降低爆破振动的危害,以星光一号露天矿山爆破工程为依托,选取爆心距、堵塞长度、最小抵抗线、炸药单耗、最大单孔装药量、总延期时间、最大单响药量等7个影响因素作为输入变量,采用灰色关联分析法评估各因素与PPV之间的相关性,构建麻雀搜索算法(SSA)优化BP神经网络的爆破峰值振速预测模型,对三向峰值振动速度进行预测,并与BP神经网络模型预测结果进行对比分析,得到SSA-BP神经网络模型预测结果的平均误差分别为6.08%、7.34%、1.91%,BP神经网络模型预测结果的平均误差分别为22.19%、54.01%、25.29%。研究结果表明:SSA-BP神经网络模型全面考虑了多种爆破设计参数对振动峰值速度的影响;麻雀搜索优化算法有效解决了传统BP神经网络模型容易陷入局部最优的问题,预测结果更精确,与振速监测值吻合度更高、误差更小;并且极大地缩短了样本数据的学习训练时间,加快BP神经网络预测模型的收敛速度,可为类似露天爆破工程质点峰值振速的预测提供借鉴。 展开更多
关键词 爆破振动 露天矿山 质点峰值振速预测 BP神经网络 ssa-bp神经网络模型
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24Model与LCM原因因素定义对比研究 被引量:2
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作者 袁晨辉 傅贵 +1 位作者 吴治蓉 赵金坤 《中国安全科学学报》 CAS CSCD 北大核心 2024年第1期27-34,共8页
为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分... 为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。 展开更多
关键词 “2-4”模型(24model) 损失致因模型(LCM) 事故致因模型 原因因素定义 对比研究
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Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area 被引量:1
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作者 GUO Junqi XI Wenfei +4 位作者 YANG Zhiquan SHI Zhengtao HUANG Guangcai YANG Zhengrong YANG Dongqing 《Journal of Mountain Science》 SCIE CSCD 2024年第3期952-972,共21页
Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calcu... Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions. 展开更多
关键词 Baihetan SBAS-InSAR ssa-bp Landslide hazard susceptibility evaluation
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基于HSS-MCC融合模型及SSA-BP神经网络开展深基坑超大变形预测研究
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作者 倪小东 张宇科 +3 位作者 焉磊 王东兴 徐硕 王媛 《湖南大学学报(自然科学版)》 EI CAS CSCD 北大核心 2024年第9期35-45,共11页
软土环境下深基坑开挖变形特性研究中,多采用硬化类弹塑性模型进行分析,如HSS模型和MCC模型.南京河漫滩软土地区,深基坑开挖时局部常发生较大变形,部分土体变形状态介于小应变与大应变之间,单一模型无法准确预测土体变形特征.同时,BP神... 软土环境下深基坑开挖变形特性研究中,多采用硬化类弹塑性模型进行分析,如HSS模型和MCC模型.南京河漫滩软土地区,深基坑开挖时局部常发生较大变形,部分土体变形状态介于小应变与大应变之间,单一模型无法准确预测土体变形特征.同时,BP神经网络在基坑变形预测中得到广泛应用,但在训练过程中,权阈值易陷入局部最优解,影响预测的准确性.据此,依托南京地区典型软土深基坑工程,采用Midas中的HSS模型与MCC模型进行分析,比对两种模型的桩体变形量差异,并基于最小二乘准则对两模型进行线性融合,融合模型可对后续区段监测数据进行校准及补充.通过融合麻雀搜索算法对BP神经网络进行优化,在其训练过程中快速收敛,得到全局最优的权阈值,依托狭长基坑已开挖区段监测数据学习训练,进而依据后续区段浅部开挖揭露深部变形特征,预测结果与实测值吻合度较高.研究结果对软土地区深基坑大变形的预测研究具有重要参考价值. 展开更多
关键词 深基坑 大变形 HSS模型 MCC模型 BP神经网络 麻雀搜索算法
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基于SSA-BP神经网络的重力式矿浆浓度检测算法
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作者 陈永春 黄宋魏 +2 位作者 和丽芳 高徐辉 钟婷婷 《化工自动化及仪表》 CAS 2024年第6期1010-1016,1027,共8页
为了克服现有矿浆浓度检测技术的不足,提高矿浆浓度检测技术在复杂选矿环境中的精度和适应性,在对现有矿浆浓度检测技术进行分析的基础上,提出重力式矿浆浓度检测方法,利用麻雀搜索算法(SSA)改进BP神经网络算法优化关键参数,进行了系统... 为了克服现有矿浆浓度检测技术的不足,提高矿浆浓度检测技术在复杂选矿环境中的精度和适应性,在对现有矿浆浓度检测技术进行分析的基础上,提出重力式矿浆浓度检测方法,利用麻雀搜索算法(SSA)改进BP神经网络算法优化关键参数,进行了系统设计、算法研究和应用测试,结果表明:算法具有检测精度高、适应性强、稳定性好等优点。 展开更多
关键词 ssa-bp神经网络 矿浆浓度 参数校正 重力式
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基于SSA-BP算法的超高温陶瓷裂纹长度预测
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作者 王一宁 刘宝良 +1 位作者 刘洋 李长青 《广东石油化工学院学报》 2024年第4期104-107,共4页
超高温陶瓷构件在航天航空中的运用往往会出现检测方面的困难,在构件产生裂纹后会在一定范围内失效。针对使用传统的BP神经网络预测超高温陶瓷构件的裂纹长度存在的对连接权值和阈值具有较强依赖性导致收敛速度较慢、易陷入局部最优和... 超高温陶瓷构件在航天航空中的运用往往会出现检测方面的困难,在构件产生裂纹后会在一定范围内失效。针对使用传统的BP神经网络预测超高温陶瓷构件的裂纹长度存在的对连接权值和阈值具有较强依赖性导致收敛速度较慢、易陷入局部最优和稳定性差等问题,提出一种基于麻雀搜索算法SSA优化的BP神经网络关于裂纹长度的预测方法。以ABAQUS有限元分析软件得出的超高温陶瓷裂纹长度相关参数构成的基础数据集作为模型的输入。利用SSA优化BP神经网络的初始权值与阈值得到了更好的拟合结果。结果表明利用SSA-BP神经网络进行预测的可行性。 展开更多
关键词 超高温陶瓷 裂纹长度预测 ssa-bp 数值模拟
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Anisotropic time-dependent behaviors of shale under direct shearing and associated empirical creep models 被引量:3
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作者 Yachen Xie Michael Z.Hou +1 位作者 Hejuan Liu Cunbao Li 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2024年第4期1262-1279,共18页
Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,... Understanding the anisotropic creep behaviors of shale under direct shearing is a challenging issue.In this context,we conducted shear-creep and steady-creep tests on shale with five bedding orientations (i.e.0°,30°,45°,60°,and 90°),under multiple levels of direct shearing for the first time.The results show that the anisotropic creep of shale exhibits a significant stress-dependent behavior.Under a low shear stress,the creep compliance of shale increases linearly with the logarithm of time at all bedding orientations,and the increase depends on the bedding orientation and creep time.Under high shear stress conditions,the creep compliance of shale is minimal when the bedding orientation is 0°,and the steady-creep rate of shale increases significantly with increasing bedding orientations of 30°,45°,60°,and 90°.The stress-strain values corresponding to the inception of the accelerated creep stage show an increasing and then decreasing trend with the bedding orientation.A semilogarithmic model that could reflect the stress dependence of the steady-creep rate while considering the hardening and damage process is proposed.The model minimizes the deviation of the calculated steady-state creep rate from the observed value and reveals the behavior of the bedding orientation's influence on the steady-creep rate.The applicability of the five classical empirical creep models is quantitatively evaluated.It shows that the logarithmic model can well explain the experimental creep strain and creep rate,and it can accurately predict long-term shear creep deformation.Based on an improved logarithmic model,the variations in creep parameters with shear stress and bedding orientations are discussed.With abovementioned findings,a mathematical method for constructing an anisotropic shear creep model of shale is proposed,which can characterize the nonlinear dependence of the anisotropic shear creep behavior of shale on the bedding orientation. 展开更多
关键词 Rock anisotropy Direct shear creep Creep compliance Steady-creep rate Empirical model Creep constitutive model
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Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence 被引量:1
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作者 Jiazhen ZHAO Shengping HE +2 位作者 Ke FAN Huijun WANG Fei LI 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2024年第8期1465-1482,共18页
Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Ar... Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained). 展开更多
关键词 wintertime newly formed Arctic sea ice model democracy model weighting scheme model performance model independence
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基于SSA-BP神经网络模型的全球入海径流量未来变化趋势
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作者 赵鹏 姜彤 +1 位作者 苏布达 高妙妮 《气候变化研究进展》 CSCD 北大核心 2024年第2期182-192,共11页
入海径流是水循环的重要环节,探究气候变化背景下全球入海径流量的时空变化特征,可为水资源合理利用提供依据。基于全球376条外流河逐月流量、ERA5-LAND再分析资料和10个全球气候模式,构建基于SSA-BP神经网络的降水径流关系模型,分析全... 入海径流是水循环的重要环节,探究气候变化背景下全球入海径流量的时空变化特征,可为水资源合理利用提供依据。基于全球376条外流河逐月流量、ERA5-LAND再分析资料和10个全球气候模式,构建基于SSA-BP神经网络的降水径流关系模型,分析全球入海径流量在历史时期(1961—2020年)和未来(2021—2100年)3种情景(SSP1-2.6、SSP3-7.0和SSP5-8.5)下的时空变化特征。研究发现:(1)全球尺度上,1961—2020年,多年平均入海年径流量为37423 km^(3)。2021—2100年,全球入海年径流量在未来3种情景下均呈增加趋势,SSP1-2.6情景下趋势显著。与基准期相比,21世纪末期增幅最大。(2)洲际尺度上,历史时期,非洲入海径流量呈显著减少趋势,北美洲呈显著增加趋势。2021—2100年,亚洲、北美洲在3种情景下呈增加趋势,大洋洲呈减少趋势,其余各大洲情景间差异明显。(3)纬向分布上,历史时期,南北半球低纬度变化趋势不显著;北半球中纬度呈弱减少趋势,南半球中纬度呈显著减少趋势;北半球高纬度呈显著增加趋势。2021—2100年,从低到高排放情景,入海径流在北半球低纬度的增加趋势和在南半球低纬度的减少趋势愈发显著;北半球中高纬由低排放情景的显著增加转变为中高排放情景的显著减少;南半球中纬度在低排放情景下呈显著增加趋势,在中高排放情景下趋势不显著。 展开更多
关键词 入海径流量 趋势预估 ssa-bp模型 全球
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