A soft-measuring approach is presented to measure the flux of liquid zinc with high temperature andcausticity. By constructing mathematical model based on neural networks, weighing the mass of liquid zinc, the fluxof ...A soft-measuring approach is presented to measure the flux of liquid zinc with high temperature andcausticity. By constructing mathematical model based on neural networks, weighing the mass of liquid zinc, the fluxof liquid zinc is acquired indirectly, the measuring on line and flux control are realized. Simulation results and indus-trial practice demonstrate that the relative error between the estimated flux value and practical measured flux value islower than 1.5%, meeting the need of industrial process.展开更多
In order to interpret the magnetic flux leakage (MFL) testing data quantitatively and size the defects accurately, some defect profiles inversion methods from the MFL signals are studied on the basis of the neural net...In order to interpret the magnetic flux leakage (MFL) testing data quantitatively and size the defects accurately, some defect profiles inversion methods from the MFL signals are studied on the basis of the neural network.Because the wavelet ba- sis function neural network (WBFNN) has good accuracy in the forward calculation and the radial basis function neural network (RBFNN) has reliable precision in the inversion modeling respectively,a new neural network scheme combining WBFNN and RBFNN is presented to solve the nonlinear inversion problem for the MFL data and reconstruct the defect shapes.And such details as the choice of wavelet basis function,the initialization of the weight value and the input normalization are analyzed,the train- ing and testing algorithm for the network are also studied.The inversion results demonstrate that the proposed network scheme has good reliability to interpret the MFL data for some defects.展开更多
In this paper, an artificial neural network method that can predict the chemical composition of deposited weld metal by CO 2 Shielded Flux Cored Wire Surfacing was studied. It is found that artificial neural networ...In this paper, an artificial neural network method that can predict the chemical composition of deposited weld metal by CO 2 Shielded Flux Cored Wire Surfacing was studied. It is found that artificial neural network is a good approach on studying welding metallurgy processes that cannot be described by conventional mathematical methods. In the same time we explored a new way to study the no equilibrium welding metallurgy processes.展开更多
We introduce a thermal flux-diffusing model for complex networks. Based on this model, we propose a physical method to detect the communities in the complex networks. The method allows us to obtain the temperature dis...We introduce a thermal flux-diffusing model for complex networks. Based on this model, we propose a physical method to detect the communities in the complex networks. The method allows us to obtain the temperature distribution of nodes in time that scales linearly with the network size. Then, the local community enclosing a given node can be easily detected for the reason that the dense connections in the local communities lead to the temperatures of nodes in the same community being close to each other. The community structure of a network can be recursively detected by randomly choosing the nodes outside the detected local communities. In the experiments, we apply our method to a set of benchmarking networks with known pre-determined community structures. The experiment results show that our method has higher accuracy and precision than most existing globe methods and is better than the other existing local methods in the selection of the initial node. Finally. several real-world networks are investigated.展开更多
Limited-heating is one of the heating statuses which can meet the reliability requirement of those uninterrupted heat-users under the accidental status of heat-supply network.It requires the network to be provided wit...Limited-heating is one of the heating statuses which can meet the reliability requirement of those uninterrupted heat-users under the accidental status of heat-supply network.It requires the network to be provided with both ability of spare-structure and spare-transportation,and the later one is depended on the limited-flux coefficient.This paper investigates the relationship between the limited-flux coefficient and limited-heating coefficient of indirect connection system.The optimal value of the limited-flux coefficient is presented as well.展开更多
The rapid development of 5G mobile communication and portable traffic detection technologies enhances highway transportation systems in detail and at a vehicle level. Besides the advantage of no disturbance to the reg...The rapid development of 5G mobile communication and portable traffic detection technologies enhances highway transportation systems in detail and at a vehicle level. Besides the advantage of no disturbance to the regular traffic operation, these ubiquitous sensing technologies have the potential for unprecedented data collection at any temporal and spatial position. While as a typical distributed parameter system, the freeway traffic dynamics are determined by the current system states and the boundary traffic demand-supply. Using the three-step extended Kalman filtering, this paper simultaneously estimates the real-time traffic state and the boundary flux of freeway traffic with the distributed speed detector networks organized at any location of interest. In order to assess the effectiveness of the proposed approach, a freeway segment from Interstate 80 East (I-80E) in Alameda, Emeryville, and Northern California is selected. Experimental results show that the proposed method has the potential of using only speed detecting data to monitor the state of urban freeway transportation systems without access to the traditional measurement data, such as the boundary flows.展开更多
Constraint-based models such as flux balance analysis （FBA） are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution an...Constraint-based models such as flux balance analysis （FBA） are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term‘noise＇, and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.展开更多
OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs...OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs such role to calculate the sensitivity of flux change upon that of enzymes under the framework of ordinary differential equation(ODE)models,which are restricted in small-scale networks and require explicit kinetic parameters.The constraint-based models,like flux balance analysis(FBA),lack of the room of performing MCA because they are parameters-free.In this study,we developed a hyper-cube shrink algorithm(HCSA)to incorporate the enzymatic properties to the FBA model by introducing a pair of parameters for each reaction.Our algorithm was able to handle not only prediction of knockout strains but also strains with an adjustment of expression level of certain enzymes.RESULTS We first showed the concept by applying HCSA to a simplest three-nodes network.Then we show the HCSA possesses Michaelis-Menten like behaviors characterized by steady state of ODE.We obtained good prediction of a synthetic network in Saccharomyces cerevisiae producing voilacein and analogues.Finally we showed its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast.CONCLUSION We have developed an algorithm the impact on fluxes when certain enzymes were inhibited or activated.It provides us a powerful tool to evaluate the consequences of enzyme inhibitor or activator.展开更多
In this paper, we study the optimization of network traffic by considering the effects of node buffer ability and capacity. Two node buffer settings are considered. The node capacity is considered to be proportional t...In this paper, we study the optimization of network traffic by considering the effects of node buffer ability and capacity. Two node buffer settings are considered. The node capacity is considered to be proportional to its buffer ability. The node effects on network traffic systems are studied with the shortest path protocol and an extension of the optimal routing [Phys. Rev. E 74 046106 （2006）]. In the diagrams of flux-density relationships, it is shown that a nodes buffer ability and capacity have profound effects on the network traffic.展开更多
Artificial neural networks (ANNs) are applied successfully to analyze the critical heat flux (CHF) experimental data from some round tubes in this paper. A set of software adopting artificial neural network method for...Artificial neural networks (ANNs) are applied successfully to analyze the critical heat flux (CHF) experimental data from some round tubes in this paper. A set of software adopting artificial neural network method for predicting CHF in round tube and a set of CHF database are gotten. Comparing with common CHF correlations and CHF look-up table, ANN method has stronger ability of allow-wrong and nice robustness. The CHF predicting software adopting artificial neural network technology can improve the predicting accuracy in a wider parameter range,and is easier to update and to use. The artificial neural nefwork method used in this paper can be applied to some similar physical problems.展开更多
Wet deposition was collected in Mexico City (MC), Metropolitan Area of Monterrey (MAM) and El Chico National Park (ECNP), during 2009 and 2010. pH, conductivity, Cl-, , Na+, K+, Ca2+ and Mg2+ were determined. In MC, s...Wet deposition was collected in Mexico City (MC), Metropolitan Area of Monterrey (MAM) and El Chico National Park (ECNP), during 2009 and 2010. pH, conductivity, Cl-, , Na+, K+, Ca2+ and Mg2+ were determined. In MC, sulphate levels were greater than nitrate levels, and NH4 had mixed sources (vehicular emissions and agriculture activities). MAM had markedly alkaline atmospheric deposition, Na+ and Cl-levels were unexpectedly high, especially during hurricane “Alex”. Low pH values were found in ECNP and nitrate concentrations were high, suggesting the influence of a local source (forest fires). Deposition fluxes (Kg.ha-1yr-1) for N-NO3, N-NH4 and S-SO4 were 1.36, 2.74 and 4.84 for MAM;7.27, 0.57 and 4.32 for ECNP;and 5.97, 4.96 and 6.78 for MC, respectively. Nitrogen deposition fluxes in ECNP were high considering that this site is a natural reserve.展开更多
Prediction of radon flux from the fractured zone of a propagating cave mine is basically associated with uncertainty and complexity. For instance, there is restricted access to these zones for field measure- ments, an...Prediction of radon flux from the fractured zone of a propagating cave mine is basically associated with uncertainty and complexity. For instance, there is restricted access to these zones for field measure- ments, and it is quite difficult to replicate the complex nature of both natural and induced fractures in these zones in laboratory studies. Hence, a technique for predicting radon flux from a fractured rock using a discrete fracture network （DFN） model is developed to address these difficulties. This model quantifies the contribution of fractures to the total radon flux, and estimates the fracture density from a measured radon flux considering the effects of advection, diffusion, as well as radon generation and decay. Radon generation and decay are classified as reaction processes. Therefore, the equation solved is termed as the advection-diffusion-reaction equation （ADRE）. Peclet number （Pe）, a conventional dimensionless parameter that indicates the ratio of mass transport by advection to diffusion, is used to classify the transport regimes. The results show that the proposed model effectively predicts radon flux from a fractured rock. An increase in fracture density for a rock sample with uniformly distributed radon generation rate can elevate radon flux significantly compared with another rock sample with an equivalent increase in radon generation rate. In addition to Pe, two other independent dimensionless parameters （derived for radon transport through fractures） significantly affect radon dimensionless flux. Findings provide insight into radon transport through fractured rocks and can be used to improve radon control measures for proactive mitigation.展开更多
The shortcomings of traditional methods to find the shortest path are revealed, and a strategy of finding the self- organizing shortest path based on thermal flux diffusion on complex networks is presented. In our met...The shortcomings of traditional methods to find the shortest path are revealed, and a strategy of finding the self- organizing shortest path based on thermal flux diffusion on complex networks is presented. In our method, the shortest paths between the source node and the other nodes are found to be self-organized by comparing node temperatures. The computation complexity of the method scales linearly with the number of edges on underlying networks. The effects of the method on several networks, including a regular network proposed by Ravasz and Barabasi which is called the RB network, a real network, a random network proposed by Ravasz and Barabasi which is called the ER network and a scale-free network, are also demonstrated. Analytic and simulation results show that the method has a higher accuracy and lower computational complexity than the conventional methods.展开更多
Based on the gene-protein-reaction (GPR) model of S. cerevisiae_iND750 and the method of constraint-based analysis, we first calculated the metabolic flux distribution of S. cere-visiae_iND750. Then we calculated the ...Based on the gene-protein-reaction (GPR) model of S. cerevisiae_iND750 and the method of constraint-based analysis, we first calculated the metabolic flux distribution of S. cere-visiae_iND750. Then we calculated the deletion impact of 438 calculable genes, one by one, on the metabolic flux redistribution of S. cere-visiae_iND750. Next we analyzed the correlation between v (describing deletion impact of one gene) and d (connection degree of one gene) and the correlation between v and Vgene (flux sum controlled by one gene), and found that both of them were not of linear relation. Furthermore, we sought out 38 important genes that most greatly affected the metabolic flux distribution, and determined their functional subsystems. We also found that many of these key genes were related to many but not several subsystems. Because the in silico model of S. cere-visiae_iND750 has been tested by many ex-periments, thus is credible, we can conclude that the result we obtained has biological sig-nificance.展开更多
基金Project (201AA411040) supported by National Plan and Development Committee.
文摘A soft-measuring approach is presented to measure the flux of liquid zinc with high temperature andcausticity. By constructing mathematical model based on neural networks, weighing the mass of liquid zinc, the fluxof liquid zinc is acquired indirectly, the measuring on line and flux control are realized. Simulation results and indus-trial practice demonstrate that the relative error between the estimated flux value and practical measured flux value islower than 1.5%, meeting the need of industrial process.
基金Funded by National Natural Science Foundation of China(50305017)the Youth Chengguang Project of Science and Technology of Wuhan City of China(20045006071-27).
文摘In order to interpret the magnetic flux leakage (MFL) testing data quantitatively and size the defects accurately, some defect profiles inversion methods from the MFL signals are studied on the basis of the neural network.Because the wavelet ba- sis function neural network (WBFNN) has good accuracy in the forward calculation and the radial basis function neural network (RBFNN) has reliable precision in the inversion modeling respectively,a new neural network scheme combining WBFNN and RBFNN is presented to solve the nonlinear inversion problem for the MFL data and reconstruct the defect shapes.And such details as the choice of wavelet basis function,the initialization of the weight value and the input normalization are analyzed,the train- ing and testing algorithm for the network are also studied.The inversion results demonstrate that the proposed network scheme has good reliability to interpret the MFL data for some defects.
文摘In this paper, an artificial neural network method that can predict the chemical composition of deposited weld metal by CO 2 Shielded Flux Cored Wire Surfacing was studied. It is found that artificial neural network is a good approach on studying welding metallurgy processes that cannot be described by conventional mathematical methods. In the same time we explored a new way to study the no equilibrium welding metallurgy processes.
基金Project supported by the National Natural Science Foundation of China (Grant No. 60672095)the Fundamental Research Funds for the Central Universities,China (Grant No. KYZ201300)the Youth Sci-Tech Innovation Fund of Nanjing Agricultural University, China (Grant No. KJ2010024)
文摘We introduce a thermal flux-diffusing model for complex networks. Based on this model, we propose a physical method to detect the communities in the complex networks. The method allows us to obtain the temperature distribution of nodes in time that scales linearly with the network size. Then, the local community enclosing a given node can be easily detected for the reason that the dense connections in the local communities lead to the temperatures of nodes in the same community being close to each other. The community structure of a network can be recursively detected by randomly choosing the nodes outside the detected local communities. In the experiments, we apply our method to a set of benchmarking networks with known pre-determined community structures. The experiment results show that our method has higher accuracy and precision than most existing globe methods and is better than the other existing local methods in the selection of the initial node. Finally. several real-world networks are investigated.
基金Sponsored by the National Natural Science Foundation of China(Grant No.50378029)the National Key Technologies R&D Program of China during the 11th Five-Year Plan Period(Grant No.2006BAJ16B03)
文摘Limited-heating is one of the heating statuses which can meet the reliability requirement of those uninterrupted heat-users under the accidental status of heat-supply network.It requires the network to be provided with both ability of spare-structure and spare-transportation,and the later one is depended on the limited-flux coefficient.This paper investigates the relationship between the limited-flux coefficient and limited-heating coefficient of indirect connection system.The optimal value of the limited-flux coefficient is presented as well.
文摘The rapid development of 5G mobile communication and portable traffic detection technologies enhances highway transportation systems in detail and at a vehicle level. Besides the advantage of no disturbance to the regular traffic operation, these ubiquitous sensing technologies have the potential for unprecedented data collection at any temporal and spatial position. While as a typical distributed parameter system, the freeway traffic dynamics are determined by the current system states and the boundary traffic demand-supply. Using the three-step extended Kalman filtering, this paper simultaneously estimates the real-time traffic state and the boundary flux of freeway traffic with the distributed speed detector networks organized at any location of interest. In order to assess the effectiveness of the proposed approach, a freeway segment from Interstate 80 East (I-80E) in Alameda, Emeryville, and Northern California is selected. Experimental results show that the proposed method has the potential of using only speed detecting data to monitor the state of urban freeway transportation systems without access to the traditional measurement data, such as the boundary flows.
基金Project supported by the National Natural Science Foundation of China (Grant No 10721403)the MOST of China (Grant No2009CB918500)the National Basic Research Program of China (Grant Nos 2006CB910706 and 2007CB814800)
文摘Constraint-based models such as flux balance analysis （FBA） are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term‘noise＇, and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.
基金The project supported by 985 Startup Funding in PKU
文摘OBJECTIVE One of the long-expected goals of genome-scale metabolic modeling is to evaluate the influence of the perturbed enzymes to the yield of an expected end product.METHDOS Metabolic control analysis(MCA)performs such role to calculate the sensitivity of flux change upon that of enzymes under the framework of ordinary differential equation(ODE)models,which are restricted in small-scale networks and require explicit kinetic parameters.The constraint-based models,like flux balance analysis(FBA),lack of the room of performing MCA because they are parameters-free.In this study,we developed a hyper-cube shrink algorithm(HCSA)to incorporate the enzymatic properties to the FBA model by introducing a pair of parameters for each reaction.Our algorithm was able to handle not only prediction of knockout strains but also strains with an adjustment of expression level of certain enzymes.RESULTS We first showed the concept by applying HCSA to a simplest three-nodes network.Then we show the HCSA possesses Michaelis-Menten like behaviors characterized by steady state of ODE.We obtained good prediction of a synthetic network in Saccharomyces cerevisiae producing voilacein and analogues.Finally we showed its capability of predicting the flux distribution in genome-scale networks by applying it to sporulation in yeast.CONCLUSION We have developed an algorithm the impact on fluxes when certain enzymes were inhibited or activated.It provides us a powerful tool to evaluate the consequences of enzyme inhibitor or activator.
基金Project supported by the National Natural Science Foundation of China (Grant Nos. 71171185, 71001001, and 71071044)the Doctoral Program of the Ministry of Education, China (Grant No. 20110111120023)PhD Program Foundation of Hefei University of Technology, China (Grant No. 2011HGBZ1302)
文摘In this paper, we study the optimization of network traffic by considering the effects of node buffer ability and capacity. Two node buffer settings are considered. The node capacity is considered to be proportional to its buffer ability. The node effects on network traffic systems are studied with the shortest path protocol and an extension of the optimal routing [Phys. Rev. E 74 046106 （2006）]. In the diagrams of flux-density relationships, it is shown that a nodes buffer ability and capacity have profound effects on the network traffic.
文摘Artificial neural networks (ANNs) are applied successfully to analyze the critical heat flux (CHF) experimental data from some round tubes in this paper. A set of software adopting artificial neural network method for predicting CHF in round tube and a set of CHF database are gotten. Comparing with common CHF correlations and CHF look-up table, ANN method has stronger ability of allow-wrong and nice robustness. The CHF predicting software adopting artificial neural network technology can improve the predicting accuracy in a wider parameter range,and is easier to update and to use. The artificial neural nefwork method used in this paper can be applied to some similar physical problems.
文摘Wet deposition was collected in Mexico City (MC), Metropolitan Area of Monterrey (MAM) and El Chico National Park (ECNP), during 2009 and 2010. pH, conductivity, Cl-, , Na+, K+, Ca2+ and Mg2+ were determined. In MC, sulphate levels were greater than nitrate levels, and NH4 had mixed sources (vehicular emissions and agriculture activities). MAM had markedly alkaline atmospheric deposition, Na+ and Cl-levels were unexpectedly high, especially during hurricane “Alex”. Low pH values were found in ECNP and nitrate concentrations were high, suggesting the influence of a local source (forest fires). Deposition fluxes (Kg.ha-1yr-1) for N-NO3, N-NH4 and S-SO4 were 1.36, 2.74 and 4.84 for MAM;7.27, 0.57 and 4.32 for ECNP;and 5.97, 4.96 and 6.78 for MC, respectively. Nitrogen deposition fluxes in ECNP were high considering that this site is a natural reserve.
基金the financial support from the National Institute for Occupational Safety and Health(NIOSH)(200-2014-59613)for conducting this research
文摘Prediction of radon flux from the fractured zone of a propagating cave mine is basically associated with uncertainty and complexity. For instance, there is restricted access to these zones for field measure- ments, and it is quite difficult to replicate the complex nature of both natural and induced fractures in these zones in laboratory studies. Hence, a technique for predicting radon flux from a fractured rock using a discrete fracture network （DFN） model is developed to address these difficulties. This model quantifies the contribution of fractures to the total radon flux, and estimates the fracture density from a measured radon flux considering the effects of advection, diffusion, as well as radon generation and decay. Radon generation and decay are classified as reaction processes. Therefore, the equation solved is termed as the advection-diffusion-reaction equation （ADRE）. Peclet number （Pe）, a conventional dimensionless parameter that indicates the ratio of mass transport by advection to diffusion, is used to classify the transport regimes. The results show that the proposed model effectively predicts radon flux from a fractured rock. An increase in fracture density for a rock sample with uniformly distributed radon generation rate can elevate radon flux significantly compared with another rock sample with an equivalent increase in radon generation rate. In addition to Pe, two other independent dimensionless parameters （derived for radon transport through fractures） significantly affect radon dimensionless flux. Findings provide insight into radon transport through fractured rocks and can be used to improve radon control measures for proactive mitigation.
基金supported by the National Natural Science Foundation of China (Grant No 60672095)the National High-Tech Research and Development Program of China (Grant No 2007AA11Z210)+3 种基金the Doctoral Fund of Ministry of Education of China (Grant No 20070286004)the Natural Science Foundation of Jiangsu Province,China (Grant No BK2008281)the Science and Technology Program of Southeast University,China (Grant No KJ2009351)the Excellent Young Teachers Program of Southeast University,China (Grant No BG2007428)
文摘The shortcomings of traditional methods to find the shortest path are revealed, and a strategy of finding the self- organizing shortest path based on thermal flux diffusion on complex networks is presented. In our method, the shortest paths between the source node and the other nodes are found to be self-organized by comparing node temperatures. The computation complexity of the method scales linearly with the number of edges on underlying networks. The effects of the method on several networks, including a regular network proposed by Ravasz and Barabasi which is called the RB network, a real network, a random network proposed by Ravasz and Barabasi which is called the ER network and a scale-free network, are also demonstrated. Analytic and simulation results show that the method has a higher accuracy and lower computational complexity than the conventional methods.
文摘Based on the gene-protein-reaction (GPR) model of S. cerevisiae_iND750 and the method of constraint-based analysis, we first calculated the metabolic flux distribution of S. cere-visiae_iND750. Then we calculated the deletion impact of 438 calculable genes, one by one, on the metabolic flux redistribution of S. cere-visiae_iND750. Next we analyzed the correlation between v (describing deletion impact of one gene) and d (connection degree of one gene) and the correlation between v and Vgene (flux sum controlled by one gene), and found that both of them were not of linear relation. Furthermore, we sought out 38 important genes that most greatly affected the metabolic flux distribution, and determined their functional subsystems. We also found that many of these key genes were related to many but not several subsystems. Because the in silico model of S. cere-visiae_iND750 has been tested by many ex-periments, thus is credible, we can conclude that the result we obtained has biological sig-nificance.
