This article shows a side segment of efforts toward finding ways to successfully commercialize a high tech product in Iran. During last decades, sanctions against importing petrochemical most used and needed utilities...This article shows a side segment of efforts toward finding ways to successfully commercialize a high tech product in Iran. During last decades, sanctions against importing petrochemical most used and needed utilities caused difficulties for Iranian petrochemical production chain. Inconveniences provoked Iranian specialists to achieve technical knowledge toward finding new ways of local producing. Attempting（s） had been encompassed to complete the whole chain of production and consumption inside of the country. Concepts implicate that during recent years, Iranian specialists have taken special steps toward localizing needed catalysts as an example of important commodities. Considerable amount of analyses have been made by Iranian petrochemical community probing the problems and obstacles associated with successful producing and what it really takes for a successful commercialization. Thematic analysis has been implicated as the research method to evaluate concepts represented as interviewees＇ analyzed declarations. Themes are analyzed toward mapping a successful merging with parties involved along with focusing on national commercializing streamline. Findings show that the idea of executing venture capital agencies as a new sector in the sequence of Iranian governmental and private petrochemical network has been appraised. Also, evaluating network management between parties involved and ways of policy making by the expert individuals are considered as the foremost factors to converse. Benchmarking feels as a necessary aspect as well to consider in the merging process. It has been concluded vital for Iranian companies to assess their own efficiency with accepted international standards, while on the other hand, they can take benchmark as a coming out opportunity when they commercialize in new intact market cooperating with renowned foreign companies.展开更多
Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CN...Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFE main performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resumé, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.展开更多
Objective To explore the pharmacodynamic material basis and mechanism of action of volatile oil from Chuanxiong(Chuanxiong Rhizoma)-Suhexiang(Styrax)-Bingpian(Borneolum)(hereinafter referred to as C-S-B volatile oil)i...Objective To explore the pharmacodynamic material basis and mechanism of action of volatile oil from Chuanxiong(Chuanxiong Rhizoma)-Suhexiang(Styrax)-Bingpian(Borneolum)(hereinafter referred to as C-S-B volatile oil)in treating angina pectoris based on network pharmacology and to detect its protective effects against rat myocardial damage.Methods Gas chromatography-mass spectrometry(GC-MS)was used to determine the constituents of volatile oils from Chuanxiong(Chuanxiong Rhizoma),Suhexiang(Styrax),and Bingpian(Borneolum),and the targets of the three main constituents were found predicted and screened using the PharmMapper server,and Gene Cards and Coo LGe N databases.The STRING database and Cytoscape software were used to draw the protein-protein interaction(PPI)network,RStudio software was used to analyze Gene Ontology(GO)and Kyoto Encyclopedia of Genome and Genome(KEGG)pathways,and Cytoscape software was used to construct the component-target-pathwaydisease network.The rat model of myocardial injury was established by intraperitoneal injection of a large dose of isoprenaline hydrochloride.After continuous intervention with C-S-B volatile oil for 14 d,the ejection fraction(EF)and short axis shortening rate(FS)of the left ventricle were detected.The indices of myocardial damage were detected after hematoxylin-eosin(HE)staining.Results Fifteen volatile oil components from the C-S-B formula were identified.There are 470 targets of these volatile oil components and 401 angina-related genes.There are 28 core targets,including CHRM4,ADRA1 A,FGFR1,CHRM2,CYP2 A6,CHRM5,CHRM1,CHRM3,HDAC2,and MPO,etc..The results of the KEGG analysis indicated that the C-S-B formula probably interferes with the following pathways:neuroactive ligand-receptor interactions,calcium signaling,cytochrome P450 metabolism of heteropoietin,among others.The results of animal experiments showed that the C-S-B formula essential oil could significantly improve the following myocardial indices in rats with myocardial injury:EF,FS,left ventricular end-systolic diameter(LVIDs),left ventricular end-diastolic diameter(LVIDd),and stroke volume(SV),and all the differences were statistically significant(P<0.01).Conclusion The mechanism of action of volatile oil components in the C-S-B formula in treating angina pectoris was analyzed using multi-component,multi-target and multi-pathway systems,which has laid a foundation for further revealing its mechanism of action.Animal experiments have shown that the volatile oil of the C-S-B formula can improve EF,FS,and other indices of myocardial damage in a rat model,thus relieving myocardial damage caused by heart hyperactivity,improving cardiac function,and protecting against myocardial damage.展开更多
The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-obje...The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.展开更多
In order to predict and improve the performance of natural gas/diesel dual fuel engine (DFE), a combustion rate model based on forward neural network was built to study the combustion process of the DFE. The effect ...In order to predict and improve the performance of natural gas/diesel dual fuel engine (DFE), a combustion rate model based on forward neural network was built to study the combustion process of the DFE. The effect of the operatin g parameters on combustion rate was also studied by means of this model. The stu dy showed that the predicted results were good agreement with the experimental d a ta. It was proved that the developed combustion rate model could be used to succ essfully predict and optimize the combustion process of dual fuel engine.展开更多
文摘This article shows a side segment of efforts toward finding ways to successfully commercialize a high tech product in Iran. During last decades, sanctions against importing petrochemical most used and needed utilities caused difficulties for Iranian petrochemical production chain. Inconveniences provoked Iranian specialists to achieve technical knowledge toward finding new ways of local producing. Attempting（s） had been encompassed to complete the whole chain of production and consumption inside of the country. Concepts implicate that during recent years, Iranian specialists have taken special steps toward localizing needed catalysts as an example of important commodities. Considerable amount of analyses have been made by Iranian petrochemical community probing the problems and obstacles associated with successful producing and what it really takes for a successful commercialization. Thematic analysis has been implicated as the research method to evaluate concepts represented as interviewees＇ analyzed declarations. Themes are analyzed toward mapping a successful merging with parties involved along with focusing on national commercializing streamline. Findings show that the idea of executing venture capital agencies as a new sector in the sequence of Iranian governmental and private petrochemical network has been appraised. Also, evaluating network management between parties involved and ways of policy making by the expert individuals are considered as the foremost factors to converse. Benchmarking feels as a necessary aspect as well to consider in the merging process. It has been concluded vital for Iranian companies to assess their own efficiency with accepted international standards, while on the other hand, they can take benchmark as a coming out opportunity when they commercialize in new intact market cooperating with renowned foreign companies.
文摘Great efforts have been made to resolve the serious environmental pollution and inevitable declining of energy resources. A review of Chinese fuel reserves and engine technology showed that compressed natural gas (CNG)/diesel dual fuel engine (DFE) was one of the best solutions for the above problems at present. In order to study and improve the emission performance of CNG/diesel DFE, an emission model for DFE based on radial basis function (RBF) neural network was developed which was a black-box input-output training data model not require priori knowledge. The RBF centers and the connected weights could be selected automatically according to the distribution of the training data in input-output space and the given approximating error. Studies showed that the predicted results accorded well with the experimental data over a large range of operating conditions from low load to high load. The developed emissions model based on the RBF neural network could be used to successfully predict and optimize the emissions performance of DFE. And the effect of the DFE main performance parameters, such as rotation speed, load, pilot quantity and injection timing, were also predicted by means of this model. In resumé, an emission prediction model for CNG/diesel DFE based on RBF neural network was built for analyzing the effect of the main performance parameters on the CO, NOx emissions of DFE. The predicted results agreed quite well with the traditional emissions model, which indicated that the model had certain application value, although it still has some limitations, because of its high dependence on the quantity of the experimental sample data.
基金funding support from the Major Science and Technology Research and Development Special Project of Jiangxi Science and Technology Department(No.20194ABC28009)National Key Research and Development Plan(No.2018YFC1706404)。
文摘Objective To explore the pharmacodynamic material basis and mechanism of action of volatile oil from Chuanxiong(Chuanxiong Rhizoma)-Suhexiang(Styrax)-Bingpian(Borneolum)(hereinafter referred to as C-S-B volatile oil)in treating angina pectoris based on network pharmacology and to detect its protective effects against rat myocardial damage.Methods Gas chromatography-mass spectrometry(GC-MS)was used to determine the constituents of volatile oils from Chuanxiong(Chuanxiong Rhizoma),Suhexiang(Styrax),and Bingpian(Borneolum),and the targets of the three main constituents were found predicted and screened using the PharmMapper server,and Gene Cards and Coo LGe N databases.The STRING database and Cytoscape software were used to draw the protein-protein interaction(PPI)network,RStudio software was used to analyze Gene Ontology(GO)and Kyoto Encyclopedia of Genome and Genome(KEGG)pathways,and Cytoscape software was used to construct the component-target-pathwaydisease network.The rat model of myocardial injury was established by intraperitoneal injection of a large dose of isoprenaline hydrochloride.After continuous intervention with C-S-B volatile oil for 14 d,the ejection fraction(EF)and short axis shortening rate(FS)of the left ventricle were detected.The indices of myocardial damage were detected after hematoxylin-eosin(HE)staining.Results Fifteen volatile oil components from the C-S-B formula were identified.There are 470 targets of these volatile oil components and 401 angina-related genes.There are 28 core targets,including CHRM4,ADRA1 A,FGFR1,CHRM2,CYP2 A6,CHRM5,CHRM1,CHRM3,HDAC2,and MPO,etc..The results of the KEGG analysis indicated that the C-S-B formula probably interferes with the following pathways:neuroactive ligand-receptor interactions,calcium signaling,cytochrome P450 metabolism of heteropoietin,among others.The results of animal experiments showed that the C-S-B formula essential oil could significantly improve the following myocardial indices in rats with myocardial injury:EF,FS,left ventricular end-systolic diameter(LVIDs),left ventricular end-diastolic diameter(LVIDd),and stroke volume(SV),and all the differences were statistically significant(P<0.01).Conclusion The mechanism of action of volatile oil components in the C-S-B formula in treating angina pectoris was analyzed using multi-component,multi-target and multi-pathway systems,which has laid a foundation for further revealing its mechanism of action.Animal experiments have shown that the volatile oil of the C-S-B formula can improve EF,FS,and other indices of myocardial damage in a rat model,thus relieving myocardial damage caused by heart hyperactivity,improving cardiac function,and protecting against myocardial damage.
基金Supported by the National High Technology Research and Development Program of China （2008AA042902, 2009AA04Z162）, the Program of Introducing Talents of Discipline to University （B07031） and the National Natural Science Foundation of China （21106129）.
文摘The demand of hydrogen in oil refinery is increasing as market forces and environmental legislation, so hydrogen network management is becoming increasingly important in refineries. Most studies focused on single-objective optimization problem for the hydrogen network, but few account for the multi-objective optimization problem. This paper presents a novel approach for modeling and multi-objective optimization for hydrogen network in refineries. An improved multi-objective optimization model is proposed based on the concept of superstructure. The optimization includes minimization of operating cost and minimization of investment cost of equipment. The proposed methodology for the multi-objective optimization of hydrogen network takes into account flow rate constraints, pressure constraints, purity constraints, impurity constraints, payback period, etc. The method considers all the feasible connections and subjects this to mixed-integer nonlinear programming （MINLP）. A deterministic optimization method is applied to solve this multi-objective optimization problem. Finally, a real case study is intro-duced to illustrate the applicability of the approach.
文摘In order to predict and improve the performance of natural gas/diesel dual fuel engine (DFE), a combustion rate model based on forward neural network was built to study the combustion process of the DFE. The effect of the operatin g parameters on combustion rate was also studied by means of this model. The stu dy showed that the predicted results were good agreement with the experimental d a ta. It was proved that the developed combustion rate model could be used to succ essfully predict and optimize the combustion process of dual fuel engine.
