Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is...Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.展开更多
As air descends the intake shaft, its infrastructure, lining and the strata will emit heat during the night when the intake air is cool and, on the contrary, will absorb heat during the day when the temperature of the...As air descends the intake shaft, its infrastructure, lining and the strata will emit heat during the night when the intake air is cool and, on the contrary, will absorb heat during the day when the temperature of the air becomes greater than that of the strata. This cyclic phenomenon, also known as the "thermal damping effect" will continue throughout the year reducing the effect of surface air temperature variation. The objective of this paper is to quantify the thermal damping effect in vertical underground airways. A nonlinear autoregressive time series with external input(NARX) algorithm was used as a novel method to predict the dry-bulb temperature(Td) at the bottom of intake shafts as a function of surface air temperature. Analyses demonstrated that the artificial neural network(ANN) model could accurately predict the temperature at the bottom of a shaft. Furthermore, an attempt was made to quantify typical "damping coefficient" for both production and ventilation shafts through simple linear regression models. Comparisons between the collected climatic data and the regression-based predictions show that a simple linear regression model provides an acceptable accuracy when predicting the Tdat the bottom of intake shafts.展开更多
In this paper, a novel design procedure is proposed for synthesizing high-capacity auto-associative memories based on complex-valued neural networks with real-imaginary-type activation functions and constant delays. S...In this paper, a novel design procedure is proposed for synthesizing high-capacity auto-associative memories based on complex-valued neural networks with real-imaginary-type activation functions and constant delays. Stability criteria dependent on external inputs of neural networks are derived. The designed networks can retrieve the stored patterns by external inputs rather than initial conditions. The derivation can memorize the desired patterns with lower-dimensional neural networks than real-valued neural networks, and eliminate spurious equilibria of complex-valued neural networks. One numerical example is provided to show the effectiveness and superiority of the presented results.展开更多
Neuronal networks in the brain exhibit the modular （clustered） property, i.e., they are composed of certain subnetworks with differential internal and external connectivity. We investigate bursting synchronization i...Neuronal networks in the brain exhibit the modular （clustered） property, i.e., they are composed of certain subnetworks with differential internal and external connectivity. We investigate bursting synchronization in a clustered neuronal network. A transition to mutual-phase synchronization takes place on the bursting time scale of coupled neurons, while on the spiking time scale, they behave asynchronously. This synchronization transition can be induced by the variations of inter- and intra coupling strengths, as well as the probability of random links between different subnetworks. Considering that some pathological conditions are related with the synchronization of bursting neurons in the brain, we analyze the control of bursting synchronization by using a time-periodic external signal in the clustered neuronal network, Simulation results show a frequency locking tongue in the driving parameter plane, where bursting synchronization is maintained, even in the presence of external driving. Hence, effective synchronization suppression can be realized with the driving parameters outside the frequency locking region.展开更多
目的利用网络药理学分子对接及动物实验探究三妙解毒液外治臁疮的作用机制。方法通过TCMSP数据库筛选三妙解毒液的有效成分及作用靶点;利用Gene Card、OMIM、Pharm Gkb、Drug Bank数据库检索臁疮的疾病靶点,并与三妙解毒液药物靶点取交...目的利用网络药理学分子对接及动物实验探究三妙解毒液外治臁疮的作用机制。方法通过TCMSP数据库筛选三妙解毒液的有效成分及作用靶点;利用Gene Card、OMIM、Pharm Gkb、Drug Bank数据库检索臁疮的疾病靶点,并与三妙解毒液药物靶点取交集;构建三妙解毒液有效成分-作用靶点及蛋白质-蛋白质相互作用网络,通过Cytoscape软件筛选核心靶点基因;通过DAVID数据库进行基因本体(GO)功能富集分析及京都基因与基因组百科全书(KEGG)通路富集分析,微生信平台对结果进行可视化,并构建药物有效成分-臁疮-靶点-通路网络图;利用Auto Dock Tools、Vina及Pymol对药物有效成分与核心靶点进行分子对接。SPF级雄性SD大鼠48只,分为空白组(8只)和造模组(40只)。造模组通过结扎左髂总静脉+局部皮肤全层切除的方法构建臁疮大鼠模型,造模成功后将其分为三妙解毒液低剂量组(0.5 g/ml)、三妙解毒液中剂量组(1.0 g/ml)、三妙解毒液高剂量组(2.0 g/ml)、阳性对照组(牛碱性成纤维细胞生长因子外用溶液)、模型组,每组8只。将无菌纱布修剪成方块,各组分别给予相关药物或0.9%氯化钠注射液溻渍于溃疡创面。RT-q PCR法检测各组AKT1、TP53、MAPK1 m RNA表达水平。结果共检索到三妙解毒液中有效成分367个,潜在作用靶点316个;涉及臁疮靶点2931个,两者共同靶点224个。有效成分包括槲皮素、芹菜素、葛根素等,核心靶点包括AKT1、TP53、MAPK1等。GO富集分析得到生物过程907项、细胞组成113项、分子功能177项。KEGG通路富集分析得到179条信号通路,主要涉及PI3K/Akt、MAPK信号通路等。分子对接结果显示,槲皮素、芹菜素、葛根素可与AKT1、TP53、MAPK1有效结合。动物实验结果显示,模型组AKT1、TP53、MAPK1 m RNA表达低于空白组(P<0.05);三妙解毒液低、中、高剂量组AKT1、TP53、MAPK1 m RNA表达高于模型组(P<0.05);三妙解毒液中剂量组AKT1、TP53、MAPK1m RNA表达高于三妙解毒液低剂量组(P<0.05);三妙解毒液高剂量组AKT1、TP53、MAPK1 m RNA表达低于三妙解毒液中剂量组(P<0.05)。结论三妙解毒液可能通过槲皮素、芹菜素、葛根素等核心活性成分,作用于AKT1、MAPK1、TP53等核心靶点,通过PI3K/Akt、MAPK等信号通路干预臁疮创面的修复。展开更多
基金supported by the National Key R&D Program of China(Grant No.2018YFC0809300)the National Natural Science Foundation of China(Grant No.51806247)+2 种基金the Key Technology Project of Petro China Co Ltd.(Grant No.ZLZX2020-05)the Foundation of Sinopec(Grant No.320034)the Science Foundation of China University of Petroleum,Beijing(Grant No.2462020YXZZ052)
文摘Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.
基金funded by National Institute for Occupational Safety and Health (NIOSH) (No. 2014-N-15795, 2014)
文摘As air descends the intake shaft, its infrastructure, lining and the strata will emit heat during the night when the intake air is cool and, on the contrary, will absorb heat during the day when the temperature of the air becomes greater than that of the strata. This cyclic phenomenon, also known as the "thermal damping effect" will continue throughout the year reducing the effect of surface air temperature variation. The objective of this paper is to quantify the thermal damping effect in vertical underground airways. A nonlinear autoregressive time series with external input(NARX) algorithm was used as a novel method to predict the dry-bulb temperature(Td) at the bottom of intake shafts as a function of surface air temperature. Analyses demonstrated that the artificial neural network(ANN) model could accurately predict the temperature at the bottom of a shaft. Furthermore, an attempt was made to quantify typical "damping coefficient" for both production and ventilation shafts through simple linear regression models. Comparisons between the collected climatic data and the regression-based predictions show that a simple linear regression model provides an acceptable accuracy when predicting the Tdat the bottom of intake shafts.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61503338,61573316,61374152,and 11302195)the Natural Science Foundation of Zhejiang Province,China(Grant No.LQ15F030005)
文摘In this paper, a novel design procedure is proposed for synthesizing high-capacity auto-associative memories based on complex-valued neural networks with real-imaginary-type activation functions and constant delays. Stability criteria dependent on external inputs of neural networks are derived. The designed networks can retrieve the stored patterns by external inputs rather than initial conditions. The derivation can memorize the desired patterns with lower-dimensional neural networks than real-valued neural networks, and eliminate spurious equilibria of complex-valued neural networks. One numerical example is provided to show the effectiveness and superiority of the presented results.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 61072012, 61104032, and 61172009)the Natural Science Foundation of Tianjin Municipality, China (Grant No. 12JCZDJC21100)the Young Scientists Fund of the National Natural Science Foundation of China (GrantNos. 60901035 and 50907044)
文摘Neuronal networks in the brain exhibit the modular （clustered） property, i.e., they are composed of certain subnetworks with differential internal and external connectivity. We investigate bursting synchronization in a clustered neuronal network. A transition to mutual-phase synchronization takes place on the bursting time scale of coupled neurons, while on the spiking time scale, they behave asynchronously. This synchronization transition can be induced by the variations of inter- and intra coupling strengths, as well as the probability of random links between different subnetworks. Considering that some pathological conditions are related with the synchronization of bursting neurons in the brain, we analyze the control of bursting synchronization by using a time-periodic external signal in the clustered neuronal network, Simulation results show a frequency locking tongue in the driving parameter plane, where bursting synchronization is maintained, even in the presence of external driving. Hence, effective synchronization suppression can be realized with the driving parameters outside the frequency locking region.
文摘目的利用网络药理学分子对接及动物实验探究三妙解毒液外治臁疮的作用机制。方法通过TCMSP数据库筛选三妙解毒液的有效成分及作用靶点;利用Gene Card、OMIM、Pharm Gkb、Drug Bank数据库检索臁疮的疾病靶点,并与三妙解毒液药物靶点取交集;构建三妙解毒液有效成分-作用靶点及蛋白质-蛋白质相互作用网络,通过Cytoscape软件筛选核心靶点基因;通过DAVID数据库进行基因本体(GO)功能富集分析及京都基因与基因组百科全书(KEGG)通路富集分析,微生信平台对结果进行可视化,并构建药物有效成分-臁疮-靶点-通路网络图;利用Auto Dock Tools、Vina及Pymol对药物有效成分与核心靶点进行分子对接。SPF级雄性SD大鼠48只,分为空白组(8只)和造模组(40只)。造模组通过结扎左髂总静脉+局部皮肤全层切除的方法构建臁疮大鼠模型,造模成功后将其分为三妙解毒液低剂量组(0.5 g/ml)、三妙解毒液中剂量组(1.0 g/ml)、三妙解毒液高剂量组(2.0 g/ml)、阳性对照组(牛碱性成纤维细胞生长因子外用溶液)、模型组,每组8只。将无菌纱布修剪成方块,各组分别给予相关药物或0.9%氯化钠注射液溻渍于溃疡创面。RT-q PCR法检测各组AKT1、TP53、MAPK1 m RNA表达水平。结果共检索到三妙解毒液中有效成分367个,潜在作用靶点316个;涉及臁疮靶点2931个,两者共同靶点224个。有效成分包括槲皮素、芹菜素、葛根素等,核心靶点包括AKT1、TP53、MAPK1等。GO富集分析得到生物过程907项、细胞组成113项、分子功能177项。KEGG通路富集分析得到179条信号通路,主要涉及PI3K/Akt、MAPK信号通路等。分子对接结果显示,槲皮素、芹菜素、葛根素可与AKT1、TP53、MAPK1有效结合。动物实验结果显示,模型组AKT1、TP53、MAPK1 m RNA表达低于空白组(P<0.05);三妙解毒液低、中、高剂量组AKT1、TP53、MAPK1 m RNA表达高于模型组(P<0.05);三妙解毒液中剂量组AKT1、TP53、MAPK1m RNA表达高于三妙解毒液低剂量组(P<0.05);三妙解毒液高剂量组AKT1、TP53、MAPK1 m RNA表达低于三妙解毒液中剂量组(P<0.05)。结论三妙解毒液可能通过槲皮素、芹菜素、葛根素等核心活性成分,作用于AKT1、MAPK1、TP53等核心靶点,通过PI3K/Akt、MAPK等信号通路干预臁疮创面的修复。
