The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving ...The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving reliability, an approach for assessing the effect of driving erroneous actions on the dynamic performance of the driver vehicle system is presented. The analysis of driving erroneous actions in the driver vehicle system has been performed to show that the reliability during perception with variety widely could result in the incidents and/or accidents in traffic system.展开更多
Objective:Chronic fatigue syndrome(CFS)is a prevalent symptom of post-coronavirus disease 2019(COVID-19)and is associated with unclear disease mechanisms.The herbal medicine Qingjin Yiqi granules(QJYQ)constitute a cli...Objective:Chronic fatigue syndrome(CFS)is a prevalent symptom of post-coronavirus disease 2019(COVID-19)and is associated with unclear disease mechanisms.The herbal medicine Qingjin Yiqi granules(QJYQ)constitute a clinically approved formula for treating post-COVID-19;however,its potential as a drug target for treating CFS remains largely unknown.This study aimed to identify novel causal factors for CFS and elucidate the potential targets and pharmacological mechanisms of action of QJYQ in treating CFS.Methods:This prospective cohort analysis included 4,212 adults aged≥65 years who were followed up for 7 years with 435 incident CFS cases.Causal modeling and multivariate logistic regression analysis were performed to identify the potential causal determinants of CFS.A proteome-wide,two-sample Mendelian randomization(MR)analysis was employed to explore the proteins associated with the identified causal factors of CFS,which may serve as potential drug targets.Furthermore,we performed a virtual screening analysis to assess the binding affinity between the bioactive compounds in QJYQ and CFS-associated proteins.Results:Among 4,212 participants(47.5%men)with a median age of 69 years(interquartile range:69–70 years)enrolled in 2004,435 developed CFS by 2011.Causal graph analysis with multivariate logistic regression identified frequent cough(odds ratio:1.74,95%confidence interval[CI]:1.15–2.63)and insomnia(odds ratio:2.59,95%CI:1.77–3.79)as novel causal factors of CFS.Proteome-wide MR analysis revealed that the upregulation of endothelial cell-selective adhesion molecule(ESAM)was causally linked to both chronic cough(odds ratio:1.019,95%CI:1.012–1.026,P=2.75 e^(−05))and insomnia(odds ratio:1.015,95%CI:1.008–1.022,P=4.40 e^(−08))in CFS.The major bioactive compounds of QJYQ,ginsenoside Rb2(docking score:−6.03)and RG4(docking score:−6.15),bound to ESAM with high affinity based on virtual screening.Conclusions:Our integrated analytical framework combining epidemiological,genetic,and in silico data provides a novel strategy for elucidating complex disease mechanisms,such as CFS,and informing models of action of traditional Chinese medicines,such as QJYQ.Further validation in animal models is warranted to confirm the potential pharmacological effects of QJYQ on ESAM and as a treatment for CFS.展开更多
Handling uncertainty is a key aspect of production management.This paper employs a Bayesian network(BN)approach to improve uncertainty analysis in production decisionmaking by identifying common causal factors that ma...Handling uncertainty is a key aspect of production management.This paper employs a Bayesian network(BN)approach to improve uncertainty analysis in production decisionmaking by identifying common causal factors that may affect one or more components of an integrated supply chain problem.A Bayesian network approach with learning and analytical features is proposed,allowing production managers to make risk-based decisions as well as conduct various scenarios and what-if analyses.Additionally,this approach provides managers with the possibility of updating their knowledge about uncertain factors in the light of new data.The proposed model is applied to a vaccine manufacturing and distributing chain,revealing that the company will fail to gain a profit unless it reduces costs,enhances staff quality,or acquires more customers with higher demand.展开更多
Objective: This study aims to examine the causal relationship between inflammatory factors and the probability of developing vascular dementia (VD) using Mendelian Randomization (MR) and Chinese herbal medicine predic...Objective: This study aims to examine the causal relationship between inflammatory factors and the probability of developing vascular dementia (VD) using Mendelian Randomization (MR) and Chinese herbal medicine prediction method, and to screen potential Chinese herbal medicines for the prevention and treatment of VD. Methods: Single nucleotide polymorphisms (SNPs) that exhibit a strong association with vascular dementia (VD) were identified as instrumental variables from the summary statistics of genome-wide association studies (GWAS). The primary analytical method employed was inverse variance weighting (IVW), while auxiliary analyses included the MR-Egger method, weighted median method, simple model, and weighted model. A two-way Mendelian randomization analysis was conducted to assess the causal relationship between inflammatory factors and the risk of VD, thereby identifying the key inflammatory factors involved. The MR-Egger intercept test and Cochran’s Q test were employed to assess the horizontal polymorphism and heterogeneity of instrumental variables. A sensitivity analysis was conducted by excluding one method at a time. Ultimately, based on key inflammatory factors, predictions for the prevention and treatment using traditional Chinese medicine were made, along with the screening of homologous herbal remedies. Results: Based on the results of the forward MR, the probability of developing VD was elevated when the inflammatory factors CXCL10 and CXCL5 were expressed at higher levels, whereas the probability of developing VD decreased as the expression levels of IL-13 and IL-20RA increased. These findings were supported by the assessment of pleiotropy, heterogeneity, and sensitivity. The results of the reverse MR analysis showed that there was no causal relationship between VD, as an exposure dataset, and these four inflammatory factors. According to the key inflammatory factors, 37 Chinese herbal medicines such as Siraitia grosvenorii were selected. Their characteristics including four natures, five flavors, channel tropism and treatment efficiency were cold, warm, neutral, pungent, sweet, bitter, lung meridian, spleen meridian, liver meridian, kidney meridian and clearing heat. Among them, Siraitia grosvenorii, Poria with hostwood, Perilla frutescens, and Radix Platycodi were all medicine and food homologous Chinese herbal medicines. Conclusions: The increase of CXCL10 and CXCL5 expression levels can increase the risk of VD, and the increase of IL-13 and IL-20 RA expression levels can reduce the risk of VD. Siraitia grosvenorii and other Chinese herbal medicines might be potential sources of therapeutic drugs for the treatment of VD. Medicine and food homologous Chinese herbal medicines, such as Siraitia grosvenorii, Poria with hostwood, Perilla frutescens, and Radix Platycodi, may help the elderly population with corresponding Traditional Chinese Medicine (TCM) constitutions to prevent VD.展开更多
探讨瓶装液化石油气(LPG)事故关键致因,对加强事故防治意义重大。首先,基于中国内地“十三五”至今100起典型事故,运用系统理论事故模型与过程分析方法(System-Theoretical Accident Model and Processes,STAMP)建立包含12项系统组件的...探讨瓶装液化石油气(LPG)事故关键致因,对加强事故防治意义重大。首先,基于中国内地“十三五”至今100起典型事故,运用系统理论事故模型与过程分析方法(System-Theoretical Accident Model and Processes,STAMP)建立包含12项系统组件的安全控制结构,并结合事故调查报告与各组件安全控制行为,辨识人、机、环、管4个维度的19项典型事故致因;其次,采用N-K模型测度风险耦合水平,同时构建事故致因关联网络,并通过中心度与可达性分析探讨风险作用机理;最后,以风险耦合值改进节点中心度辨识关键致因,并通过凝聚子群挖掘确定核心诱因。结果表明:瓶装LPG事故的发生概率与风险耦合水平成正比,“人-机-环-管”四因素风险耦合值最高;人员和机器因素对事故影响最大;A_(2)、D_(2)、D_(4)、D_(5)、D_(6)为事故关键致因,除违规用气和操作行为A_(2)外,均为来自瓶装LPG经营企业或用户的组织缺欠;安全主体责任未贯彻落实D2和用户与供气管理存在缺陷D4在关键致因中的地位更加突出,作为核心诱因必须加强其管控和约束。各级政府和有关部门应深化对瓶装LPG经营企业与用户的监管力度,在督促上述两类单位贯彻落实安全主体责任和完善安全管理制度的基础上,确保经营企业做好对用户的供气管理、入户安检与用气指导,从源头深处遏制风险涌现并阻断其耦合,提升系统本质安全水平。展开更多
Understanding the spatial heterogeneity of debris-flow-prone areas holds significant implications for regional risk management, particularly in seismically active regions with geological faults. Despite the significan...Understanding the spatial heterogeneity of debris-flow-prone areas holds significant implications for regional risk management, particularly in seismically active regions with geological faults. Despite the significance of this knowledge, a comprehensive quantification of the influence of regional topographical and geological factors on the spatial heterogeneity of debris-flow-prone areas has been lacking. This study selected the Hengduan Mountains, an earthquake-prone region characterized by diverse surface conditions and complex landforms, as a representative study area. An improved units zoning and objective factors identification methodology was employed in earthquake and fault analysis to assess the impact of seismic activity and geological factors on spatial heterogeneity of debrisflow prone areas. Results showed that the application of GIS technology with hydrodynamic intensity and geographical units analysis can effectively analyze debris-flow prone areas. Meanwhile, earthquake and fault zones obviously increase the density of debrisflow prone catchments and make them unevenly distributed. The number of debris-flow prone areas shows a nonlinear variation with the gradual increase of geomorphic factor value. Specifically, the area with 1000 m-2500 m elevation difference, 25°-30° average slope, and 0.13-0.15 land use index is the most favorable conditions for debris-flow occurrence;The average annual rainfall from 600 to 1150 mm and landslides gradient from 16° to 35° are the main causal factors to trigger debris flow. Our study sheds light on the quantification of spatial heterogeneity in debris flow-prone areas in earthquake-prone regions, which can offer crucial support for post-debris flow risk management strategies.展开更多
针对国省干线人因交通事故的异质性特点,提出一种事故链式因果推断方法,实现交通事故因果机制辨识与交互效应量化的同步解析。首先,采集新疆11条国省干线近年交通事故信息构建数据集,利用K-prototype聚类算法将事故严重程度分为3类;其次...针对国省干线人因交通事故的异质性特点,提出一种事故链式因果推断方法,实现交通事故因果机制辨识与交互效应量化的同步解析。首先,采集新疆11条国省干线近年交通事故信息构建数据集,利用K-prototype聚类算法将事故严重程度分为3类;其次,基于结构因果模型、因果森林及SHAP(SHapley Additive exPlanation)算法构建链式因果推断模型,推理出事故关键致因链、多维诱因交互效应及事故类别概率预测值,解析“场景组合-人为要素-事故类别”的链式传导特征及异质性特点;最后,基于SHAP值分析多维要素贡献度,并结合因果效应强度划分行为致因类别,辨识出事故关键人为致因,提出具有针对性的事故防控策略。结果表明:本文所提方法的加权平均F1得分与宏平均AUC(Area Under Curve)值分别为0.86与0.82,相对高于常用的机器学习算法,且克服了传统关联模型难以实现多因素交互作用机制刻画与效应量化的局限,适宜人因事故异质机理解构分析;由致因链分析可知,人为要素为事故主要致因,天气和时段等环境要素对事故后果均有显著影响,恶劣环境与危险行为的综合作用对事故程度升级具有非线性影响作用;超速行驶、疲劳驾驶、跟车过近与观察不周为核心行为致因,营运类车辆出现上述行为后事故严重程度相对较高,严重型事故占比超过50%,应重点进行事故监测与防控。展开更多
文摘The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving reliability, an approach for assessing the effect of driving erroneous actions on the dynamic performance of the driver vehicle system is presented. The analysis of driving erroneous actions in the driver vehicle system has been performed to show that the reliability during perception with variety widely could result in the incidents and/or accidents in traffic system.
基金supported by an internal fund from Macao Polytechnic University(RP/FCSD-02/2022).
文摘Objective:Chronic fatigue syndrome(CFS)is a prevalent symptom of post-coronavirus disease 2019(COVID-19)and is associated with unclear disease mechanisms.The herbal medicine Qingjin Yiqi granules(QJYQ)constitute a clinically approved formula for treating post-COVID-19;however,its potential as a drug target for treating CFS remains largely unknown.This study aimed to identify novel causal factors for CFS and elucidate the potential targets and pharmacological mechanisms of action of QJYQ in treating CFS.Methods:This prospective cohort analysis included 4,212 adults aged≥65 years who were followed up for 7 years with 435 incident CFS cases.Causal modeling and multivariate logistic regression analysis were performed to identify the potential causal determinants of CFS.A proteome-wide,two-sample Mendelian randomization(MR)analysis was employed to explore the proteins associated with the identified causal factors of CFS,which may serve as potential drug targets.Furthermore,we performed a virtual screening analysis to assess the binding affinity between the bioactive compounds in QJYQ and CFS-associated proteins.Results:Among 4,212 participants(47.5%men)with a median age of 69 years(interquartile range:69–70 years)enrolled in 2004,435 developed CFS by 2011.Causal graph analysis with multivariate logistic regression identified frequent cough(odds ratio:1.74,95%confidence interval[CI]:1.15–2.63)and insomnia(odds ratio:2.59,95%CI:1.77–3.79)as novel causal factors of CFS.Proteome-wide MR analysis revealed that the upregulation of endothelial cell-selective adhesion molecule(ESAM)was causally linked to both chronic cough(odds ratio:1.019,95%CI:1.012–1.026,P=2.75 e^(−05))and insomnia(odds ratio:1.015,95%CI:1.008–1.022,P=4.40 e^(−08))in CFS.The major bioactive compounds of QJYQ,ginsenoside Rb2(docking score:−6.03)and RG4(docking score:−6.15),bound to ESAM with high affinity based on virtual screening.Conclusions:Our integrated analytical framework combining epidemiological,genetic,and in silico data provides a novel strategy for elucidating complex disease mechanisms,such as CFS,and informing models of action of traditional Chinese medicines,such as QJYQ.Further validation in animal models is warranted to confirm the potential pharmacological effects of QJYQ on ESAM and as a treatment for CFS.
文摘Handling uncertainty is a key aspect of production management.This paper employs a Bayesian network(BN)approach to improve uncertainty analysis in production decisionmaking by identifying common causal factors that may affect one or more components of an integrated supply chain problem.A Bayesian network approach with learning and analytical features is proposed,allowing production managers to make risk-based decisions as well as conduct various scenarios and what-if analyses.Additionally,this approach provides managers with the possibility of updating their knowledge about uncertain factors in the light of new data.The proposed model is applied to a vaccine manufacturing and distributing chain,revealing that the company will fail to gain a profit unless it reduces costs,enhances staff quality,or acquires more customers with higher demand.
文摘Objective: This study aims to examine the causal relationship between inflammatory factors and the probability of developing vascular dementia (VD) using Mendelian Randomization (MR) and Chinese herbal medicine prediction method, and to screen potential Chinese herbal medicines for the prevention and treatment of VD. Methods: Single nucleotide polymorphisms (SNPs) that exhibit a strong association with vascular dementia (VD) were identified as instrumental variables from the summary statistics of genome-wide association studies (GWAS). The primary analytical method employed was inverse variance weighting (IVW), while auxiliary analyses included the MR-Egger method, weighted median method, simple model, and weighted model. A two-way Mendelian randomization analysis was conducted to assess the causal relationship between inflammatory factors and the risk of VD, thereby identifying the key inflammatory factors involved. The MR-Egger intercept test and Cochran’s Q test were employed to assess the horizontal polymorphism and heterogeneity of instrumental variables. A sensitivity analysis was conducted by excluding one method at a time. Ultimately, based on key inflammatory factors, predictions for the prevention and treatment using traditional Chinese medicine were made, along with the screening of homologous herbal remedies. Results: Based on the results of the forward MR, the probability of developing VD was elevated when the inflammatory factors CXCL10 and CXCL5 were expressed at higher levels, whereas the probability of developing VD decreased as the expression levels of IL-13 and IL-20RA increased. These findings were supported by the assessment of pleiotropy, heterogeneity, and sensitivity. The results of the reverse MR analysis showed that there was no causal relationship between VD, as an exposure dataset, and these four inflammatory factors. According to the key inflammatory factors, 37 Chinese herbal medicines such as Siraitia grosvenorii were selected. Their characteristics including four natures, five flavors, channel tropism and treatment efficiency were cold, warm, neutral, pungent, sweet, bitter, lung meridian, spleen meridian, liver meridian, kidney meridian and clearing heat. Among them, Siraitia grosvenorii, Poria with hostwood, Perilla frutescens, and Radix Platycodi were all medicine and food homologous Chinese herbal medicines. Conclusions: The increase of CXCL10 and CXCL5 expression levels can increase the risk of VD, and the increase of IL-13 and IL-20 RA expression levels can reduce the risk of VD. Siraitia grosvenorii and other Chinese herbal medicines might be potential sources of therapeutic drugs for the treatment of VD. Medicine and food homologous Chinese herbal medicines, such as Siraitia grosvenorii, Poria with hostwood, Perilla frutescens, and Radix Platycodi, may help the elderly population with corresponding Traditional Chinese Medicine (TCM) constitutions to prevent VD.
文摘探讨瓶装液化石油气(LPG)事故关键致因,对加强事故防治意义重大。首先,基于中国内地“十三五”至今100起典型事故,运用系统理论事故模型与过程分析方法(System-Theoretical Accident Model and Processes,STAMP)建立包含12项系统组件的安全控制结构,并结合事故调查报告与各组件安全控制行为,辨识人、机、环、管4个维度的19项典型事故致因;其次,采用N-K模型测度风险耦合水平,同时构建事故致因关联网络,并通过中心度与可达性分析探讨风险作用机理;最后,以风险耦合值改进节点中心度辨识关键致因,并通过凝聚子群挖掘确定核心诱因。结果表明:瓶装LPG事故的发生概率与风险耦合水平成正比,“人-机-环-管”四因素风险耦合值最高;人员和机器因素对事故影响最大;A_(2)、D_(2)、D_(4)、D_(5)、D_(6)为事故关键致因,除违规用气和操作行为A_(2)外,均为来自瓶装LPG经营企业或用户的组织缺欠;安全主体责任未贯彻落实D2和用户与供气管理存在缺陷D4在关键致因中的地位更加突出,作为核心诱因必须加强其管控和约束。各级政府和有关部门应深化对瓶装LPG经营企业与用户的监管力度,在督促上述两类单位贯彻落实安全主体责任和完善安全管理制度的基础上,确保经营企业做好对用户的供气管理、入户安检与用气指导,从源头深处遏制风险涌现并阻断其耦合,提升系统本质安全水平。
基金supported by the Hubei Provincial Engineering Research Center of Slope Habitat Construction Technique Using Cement-based Materials Open Research Program (Grant No. 2022SNJ112022SNJ12)+4 种基金National Natural Science Foundation of China (Grant No. 42371014)Hubei Key Laboratory of Disaster Prevention and Mitigation (China Three Gorges University) Open Research Program (Grant No. 2022KJZ122023KJZ19)CRSRI Open Research Program (Grant No. CKWV2021888/KY)the Key Laboratory of Mountain Hazards and Earth Surface Processes, Chinese Academy of Sciences (Grant No. KLMHESP20-0)。
文摘Understanding the spatial heterogeneity of debris-flow-prone areas holds significant implications for regional risk management, particularly in seismically active regions with geological faults. Despite the significance of this knowledge, a comprehensive quantification of the influence of regional topographical and geological factors on the spatial heterogeneity of debris-flow-prone areas has been lacking. This study selected the Hengduan Mountains, an earthquake-prone region characterized by diverse surface conditions and complex landforms, as a representative study area. An improved units zoning and objective factors identification methodology was employed in earthquake and fault analysis to assess the impact of seismic activity and geological factors on spatial heterogeneity of debrisflow prone areas. Results showed that the application of GIS technology with hydrodynamic intensity and geographical units analysis can effectively analyze debris-flow prone areas. Meanwhile, earthquake and fault zones obviously increase the density of debrisflow prone catchments and make them unevenly distributed. The number of debris-flow prone areas shows a nonlinear variation with the gradual increase of geomorphic factor value. Specifically, the area with 1000 m-2500 m elevation difference, 25°-30° average slope, and 0.13-0.15 land use index is the most favorable conditions for debris-flow occurrence;The average annual rainfall from 600 to 1150 mm and landslides gradient from 16° to 35° are the main causal factors to trigger debris flow. Our study sheds light on the quantification of spatial heterogeneity in debris flow-prone areas in earthquake-prone regions, which can offer crucial support for post-debris flow risk management strategies.
文摘针对国省干线人因交通事故的异质性特点,提出一种事故链式因果推断方法,实现交通事故因果机制辨识与交互效应量化的同步解析。首先,采集新疆11条国省干线近年交通事故信息构建数据集,利用K-prototype聚类算法将事故严重程度分为3类;其次,基于结构因果模型、因果森林及SHAP(SHapley Additive exPlanation)算法构建链式因果推断模型,推理出事故关键致因链、多维诱因交互效应及事故类别概率预测值,解析“场景组合-人为要素-事故类别”的链式传导特征及异质性特点;最后,基于SHAP值分析多维要素贡献度,并结合因果效应强度划分行为致因类别,辨识出事故关键人为致因,提出具有针对性的事故防控策略。结果表明:本文所提方法的加权平均F1得分与宏平均AUC(Area Under Curve)值分别为0.86与0.82,相对高于常用的机器学习算法,且克服了传统关联模型难以实现多因素交互作用机制刻画与效应量化的局限,适宜人因事故异质机理解构分析;由致因链分析可知,人为要素为事故主要致因,天气和时段等环境要素对事故后果均有显著影响,恶劣环境与危险行为的综合作用对事故程度升级具有非线性影响作用;超速行驶、疲劳驾驶、跟车过近与观察不周为核心行为致因,营运类车辆出现上述行为后事故严重程度相对较高,严重型事故占比超过50%,应重点进行事故监测与防控。
