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Net embodied petroleum importers face greater petroleum security risks in international trade due to their high foreign dependence. Therefore, paying better attention to the national flows and drivers of embodied petroleum consumption can effectively serve net embodied petroleum importers to avoid petroleum security risks and formulate environmental protection policy. This study utilized the multi-regional input-output model to determine the top five embodied petroleum net importers (i.e., the USA, Japan, Germany, the UK, and France) under the economic globalization, and traced the flows of embodied petroleum consumption through international trade. Combined with the logarithmic mean Divisia index method, this study also deeply investigated the drivers of changes embodied petroleum in net imports. The results show that from the perspective of international trade, the USA was not only the largest importer but also the largest exporter of embodied petroleum. Among the trade flows of embodied petroleum, the largest trade flow was from China to the USA, which indicated that China was the world factory and the USA was the consumer power. The embodied petroleum trade markets of Germany, the UK, and France was mainly distributed in EuropeEurasia resulted from European economic integration. The largest contributor to the decrease of embodied petroleum imports in the top 4 net importers was the petroleum intensity effect. Meanwhile, the import dependence effect was the largest contributor to the increase of France's embodied petroleum net imports. In order to further avoid the risk of petroleum security, it is an effective path worth exploring to construct the diversified petroleum product import strategy and improve energy efficiency.

Objective: At present, intramural block anesthesia is mostly used clinically for vaginal delivery, but it is unclear whether intraocular block anesthesia has an effect on postpartum pelvic floor muscles and immune function after vaginal delivery. Therefore, this study investigated the effect of intraspinal block anesthesia on vaginal delivery parturients and its effect on postpartum pelvic floor muscle strength and immune function.Patients and Methods:A total of 182 parturients with vaginal delivery were selected as the study subjects. They were admitted in our hospital from March 2015 to January 2017. Among them, 92 parturients receiving intraspinal block anesthesia were enrolled in the study group and 90 parturients without intraspinal block anesthesia in the control group. The pelvic floor muscle damage and muscle strength recovery in the two groups were measured 3 months after delivery. The peripheral blood T lymphocyte subsets of parturients at different time points in the two groups was detected to investigate the effect of intraspinal block anesthesia on pelvic floor muscle strength and immune function after vaginal delivery. Results: The pain degree during delivery in the study group was significantly lower than that in the control group (p

Geological disaster rescue presents features such as multi-stage, multi-sector, multi-subject, and multi-target. However, due to the shortage of professional rescue technicians, it is necessary to consider the matching, fairness, and efficiency of rescue tasks and rescue subjects. This study takes "disaster scenario-rescue task-rescue subject-demand prediction-subject deployment" as the main line in major geological disasters such as landslides and mudslides. By collecting data on 87 rescue operations in China from 2004 to 2019, we screened 18 representative cases of rescue operations and sorted out different types of rescue force function positioning, divisions of responsibility, and collaboration modes, summarizing them into five major rescue tasks and five major rescue subjects. A rescue subject demand prediction model was developed based on different scenarios according to the influence of rescue tasks on the demand of rescue subjects. Considering the urgency of the rescue tasks, a rescue subject deployment model based on different tasks and the NSGA-II algorithm can be built up. We tested the Zhejiang Yongjia weir breach rescue operation case (2019) in China for empirical analysis to verify the effectiveness and practicality of the model and algorithm.

In recent years, supply chain finance (SCF) is exploited to solve the financing difficulties of small- and medium-sized enterprises (SMEs). SME credit risk assessment is a critical part in the SCF system. The diffusion of SME credit risk may cause serious consequences, leading the whole supply chain finance system unstable and insecure. Compared with traditional credit risk assessment models, the supply chain relationship, credit condition of SME, and core enterprises should all be considered to rate SME credit risk in SCF. Traditional methods mix all indicators from different index systems. They cannot give a quantitative result on how these index systems work. Furthermore, traditional credit risk assessment models are heavily dependent on the number of annotated SME data. However, it is implausible to accumulate enough credit risky SMEs in advance. In this paper, we propose an adaptive heterogenous multiview graph learning method to tackle the small sample size problem for SMEs’ credit risk forecasting. Three graphs are constructed by using indicators from supply chain operation, SME financial indicator, and nonfinancial indicator individually. All the graphs are integrated in an adaptive manner, providing a quantitative explanation on how the three parts cooperate. The experimental analysis shows that the proposed method has good performance for determining whether SME is risky or nonrisky in SCF. From the perspective of SCF, SME financing ability is still the main factor to determine the credit risk of SME.

Throughout the digitization of the petrochemical industry, the Beidou technology-based disaster monitoring, evaluation, and early warning network system has supported emergency decision making for oil and gas accidents. Many problems arise throughout the emergency decision-making process during oil–gas accidents, such as the limited time for decision making, high complexity, and inadequate emergency plans. Targeting these issues, we propose the construction of a case library using a Bayesian network. This way, when a new accident occurs, its similarity and deviation indexes could be matched against those of historical cases registered in the database. As such, the candidate cases are adjusted using a case combination and pruning method, yielding the final qualified case model. A case verification of the “11.22” Sinopec Oil pipeline leak and explosion in Qingdao reveals that the proposed method only requires an oil and gas accident database to be built in advance, eliminating the need for sampling data to make decisions, and reducing the search space. Using the proposed case-based reasoning, historical data and experience regarding oil and gas emergency decisions can be activated and reused, which would greatly improve the modeling efficiency of the Bayesian network.

Achieving "Responsible Consumption and Production" is one of the 17 sustainable development goals set by the United Nations. Controlling overcapacity is an important guarantee in order to achieve this goal. There are many types and large quantities of raw materials in the construction industry, which easily leads to overcapacity. Studying the problems related to overcapacity in the construction industry helps to understand the formation mechanism of overcapacity in related industries. This puts forward targeted countermeasures and suggestions for the capacity resolution to achieve green and sustainable development. Based on this, this paper uses the construction industry capacity utilization data of the Shandong Province in China from 2005 to 2017. It also uses the production function method to construct a construction industry overcapacity calculation model to estimate the construction industry capacity utilization and overcapacity rate in Shandong Province. The DEA method was used to construct an extraction model of influencing factors for overcapacity. The results show that the capacity utilization ratio for Shandong Province from 2005 to 2016 was 81.98%. There was no overcapacity as a whole, but there were large fluctuations in capacity utilization for some time periods. Suggestions for optimization countermeasures were also proposed.

Surfactant flooding is considered as one of the efficient chemical enhanced oil recovery techniques in recent decades as it has the potential ability to alter the wettability and reduce the interfacial tension of water-oil. Addition of surfactants has caused a dramatic decrease in the interfacial of water-oil. Thereby, the capillary number has increased and has caused to enhance oil mobilization in the porous media. In this paper, a cationic surfactant of Cetyl trimethyl ammonium bromide and an anionic surfactant of linear alkylbenzene sulfonic acid were used to consider their effect on the interfacial tension and oil recovery factor. According to the results of this study, the anionic surfactant of linear alkylbenzene sulfonic acid has the highest recovery factor of 70%, and cationic surfactant of Cetyl trimethyl ammonium bromide has the second-highest oil recovery factor of about 55%. Therefore, the addition of surfactants due to its beneficial impact on the interface adsorption between oil and water would be an essential point on the oil recovery enhancement as it can increase the oil recovery factor. Moreover, the critical micelle concentration value is about 300 ppm and 250 ppm for anionic and cationic surfactants respectively where the two crosslines meet each other and anionic has the highest interfacial tension rather than cationic which has caused to have more oil recovery factor.

Paying attention to the national flows and drivers of embodied petroleum consumption in net petroleum importers are important for petroleum safety risk aversion and environmental protection policy formulation. This study utilized the multi-regional input-output model to determine the top five embodied petroleum net importers (i.e. the United States, Japan, Germany, the United Kingdom and France) under the economic globalization, and traced the flows of embodied petroleum consumption through international trade. Combined with the Logarithmic Mean Divisia Index method, this study also deeply investigated the drivers of changes embodied petroleum in net imports. From the perspective of international trade, the United States was not only the largest importer but also the largest exporter of embodied petroleum. Among the trade flows of embodied petroleum, the largest trade flow was from China to the United States, which indicated that China was the world factory and the United States was the consumer power. The embodied petroleum trade markets of Germany, the United Kingdom and France was mainly distributed in Europe & Eurasia resulted from European economic integration. The largest contributor to the decrease of embodied petroleum imports in top 4 net importers was the petroleum intensity effect. Meanwhile, the import dependence effect was the largest contributor to the increase of France’s embodied petroleum net imports. In order to further avoid the risk of petroleum security, constructing the diversified petroleum product import strategy is an extremely effective path. Moreover, improving energy efficiency is another way to solve the contradiction between petroleum supply and demand.

The production enterprise’s capacity overinvestment and governmental supervision failure often lead to overcapacity. The article builds an evolutionary game model between supervision agencies and p...

Achieving "Responsible Consumption and Production" is one of the 17 sustainable development goals set by the United Nations. Controlling overcapacity is an important guarantee in order to achieve this goal. There are many types and large quantities of raw materials in the construction industry, which easily leads to overcapacity. Studying the problems related to overcapacity in the construction industry helps to understand the formation mechanism of overcapacity in related industries. This puts forward targeted countermeasures and suggestions for the capacity resolution to achieve green and sustainable development. Based on this, this paper uses the construction industry capacity utilization data of the Shandong Province in China from 2005 to 2017. It also uses the production function method to construct a construction industry overcapacity calculation model to estimate the construction industry capacity utilization and overcapacity rate in Shandong Province. The DEA method was used to construct an extraction model of influencing factors for overcapacity. The results show that the capacity utilization ratio for Shandong Province from 2005 to 2016 was 81.98%. There was no overcapacity as a whole, but there were large fluctuations in capacity utilization for some time periods. Suggestions for optimization countermeasures were also proposed.

The investment in shale gas green and efficient development in China faces many uncertain factors that affect the investment decision-making of enterprises, which contributes to China's low-carbon energy transformation and national energy security. Based on the characteristics of China's shale gas resource development and considering the uncertainties in the aspects of market, technology and environment, this paper proposes a real option model to evaluate investment decision-making of China’s shale gas development and uses the Least Square Monte Carlo simulation to solve the investment values and optimal investment timings of shale gas low, moderate, high and ultrahigh productivities under four combination scenarios of financial subsidy and/or carbon emission trading. The results show that the current investment environment in China is not suitable for immediate investment in shale gas development projects. Investors can invest immediately when the initial average daily production reaches at least 30 × 104 m3. And financial subsidy and carbon emission trading help advance the optimal investment timings. According to a sensitivity analysis, appropriate increases in financial subsidy, shale gas price, absolute value of the drift rate of drilling and completion cost and environmental external benefit coefficient are found to improve the investment value and advance the optimal investment timing, while drilling and completion cost and production decline rate have the opposite effect. Therefore, to stimulate the investment, the government and enterprises should adopt some measures such as addressing key problems on technology and equipment, flexibly adjusting subsidy policies and driving forward the carbon emission trading market.

In the economic growth process when China joined in WTO, internationalized operation has become an inevitable issue. Under the new normal economic condition, including the cut offtariffs on imported goods, businesses in China have realized the importance of enhancing the overall brand image, quality of products and services, and the international compatibility. Businesses of China need to develop creative and high-value-added products, and shall be able to rapidly change to satisfy market requirements to distinguish themselves from other products. It is the way of creating a new pattern of upgrading. It is the market-orientated development that is a primary condition for enterprises to adapt to the rapidly changing environment, keeping growth and attracting customers, acquiring competitive advantages, and creating excellent value for customers. It reveals the fact that in the future, businesses must change the focus from product to market needs. It is the marketorientation which could generate the competitive strength to resist competitors. The research involves in total 45 international enterprises, which are distributed with the questionnaires. There are totally 124 and 107 copies of questionnaires retrieved from manufacturing industry and service industry, with valid retrieval rates of 54% and 46%, respectively. The research results show that: 1. there is positive effect of market orientation on breakthrough innovation, 2. there is positive effect of breakthrough innovation on organizational performance, and 3. there is positive effect of market orientation on organizational performance. Based upon the results, some suggestions are proposed in this study, expecting to help international enterprises develop market orientation, enhance breakthrough innovation, and improve organizational performance.

This paper takes Shandong Province as an example to forecast the CO2 emission from 2017 to 2030 by system dynamics under four designed scenarios. The results indicate that despite the coal consumption, CO2 emission and the CO2 emission intensity of low intensity scenario and medium intensity scenario both decrease compared to the results of current scenario. However, neither the coal consumption peak year nor the CO2 emission peak year is before 2030. We find that with the high intensity scenario, the CO2 emission would peak on 2027 and the coal consumption would peak on 2021. Besides, the CO2 emission intensity of 2030 is reduce by almost 80% of 2005 level. Finally, conclusions and policy implications are concluded based on the simulations results.

Measures programming is an important way for improving the effect of measures of oil fields. Based on the theory of fuzzy chance-constrained goal programming, a fuzzy chance-constrained goal programming model is put forward for measures programming of Oilfield, which uses the increasing production and cost as objectives. The process of its hybrid intelligent algorithm including fuzzy simulation, genetic algorithm and neural network is provided, and the sensitivity analysis on uncertain factors to determine the influence on the optimal result can also be carried on. Finally, an example is given to illustrate the validity of the model and approach.

Enterprise performance evaluation is an important means of enterprise management, which can diagnose the whole development status of enterprise. Data envelopment analysis (DEA) is one of the most frequently used evaluation methods and support vector machine (SVM) is a novel method of data mining, which can be used for prediction and regression. Based on DEA and SVM, the paper proposes a method for evaluating and predicting enterprise performance. First, DEA method is used to evaluate DEA efficiency of all the oil refining enterprises performance. Then the input/output data and results of some decision making units (DMUs) are selected as the learning examples to train the SVM network and the others are used as the test examples to test the network. If the SVM network is testified well, a synthetic evaluation formula can be given to predict the DEA efficiency of a new DMU. A real example testifies the efficiency, practicability and intellectual ability of this method.

Measures programming is an important way for improving the effect of measures of oil fields, which can extend the stable production age limit of oil fields, reduce the mining difficulty and improve oil-producing speed and final recovery ratio. Based on the theory of stochastic chance-constrained goal programming, a stochastic chance-constrained goal programming model is put forward for measures programming of oil fields, which considers the per increasing production and per increasing cost of measures as stochastic variables, uses the increasing production and increasing cost as objectives and the total work load and work load of each measure as constraints. At the same time, the process of its hybrid intelligent algorithm including stochastic simulation, genetic algorithm and neural network is also provided. Finally, the real example, i .e. measures programming of DX Oilfield testifies the efficiency, practicability and intellectual ability of the model and its solution algorithm, which provides a new decision basis for the incremental measures program of oil fields.