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risk assessment of oil and gas investment environment in countries along the Belt and Road Initiative

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Petroleum Science 2024年第2期21卷 1429-1443页

作者： Bao-Jun Tang Chang-Jing Ji Yu-Xian Zheng Kang-Ning Liu Yi-Fei Ma Jun-Yu Chen Center for Energy and Environmental Policy Research Beijing Institute of TechnologyBeijing100081China School of Management and Economics Beijing Institute of TechnologyBeijing100081China Collaborative Innovation Center of Electric Vehicles in Beijing BeijingChina Sustainable Development Research Institute for Economy and Society of Beijing BeijingChina Institute of Carbon Neutrality ShanghaiTech UniversityShanghai201210China

With the implementation of the Belt and Road Initiative, China is deepening its cooperation in oil and gas resources with countries along the Initiative. In order to better mitigate risks and enhance the safety of investments, it is of significant importance to research the oil and gas investment environment in these countries for China's overseas investment macro-layout. This paper proposes an indicator system including 27 indicators from 6 dimensions. On this basis, game theory models combined with global entropy method and analytic hierarchy process are applied to determine the combined weights, and the TOPSIS-GRA model is utilized to assess the risks of oil and gas investment in 76 countries along the Initiative from 2014 to 2021. Finally, the GM(1,1) model is employed to predict risk values for 2022-2025. In conclusion, oil and gas resources and political factors have the greatest impact on investment environment risk, and 12 countries with greater investment potential are selected through cluster analysis in conjunction with the predicted results. The research findings may provide scientific decisionmaking recommendations for the Chinese government and oil enterprises to strengthen oil and gas investment cooperation with countries along the Belt and Road Initiative.

关键词： Belt and Road Initiative Oil and Gas Investment risk assessment

Migration mechanism and risk assessment of perand polyfluoroalkyl substances in the Ya'Er Lake oxidation pond area,China

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Journal of Environmental Sciences 2024年第2期136卷 301-312页

作者： Chang Li Huifang Zhong Jing Wu Lingyi Meng Yingjun Wang Chunyang Liao Yawei Wang Yujian He University of Chinese Academy of Sciences Beijing 100049China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China Institute of Biomedical and Health Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China China National Environmental Monitoring Centre Beijing 100012China Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances Institute of Environment and HealthJianghan UniversityWuhan 430056China

The migration mechanisms,sources,and environmental risks of 29 legacy and emerging perfluorinated and polyfluoroalkyl species present in an oxidation pond(Ya'Er Lake)were investigated for treating sewage based on the analysis of their occurrence and distribution.The concentration of per-and polyfluoroalkyl substances(PFAS)in pond area was between0.30 and 63.2 ng/g dw(dry weight),with the overall average concentration of 8.00 ng/g dw.Notably,the PFAS concentrations in the surface sediments near the sewage outlet in Pond-1(50.2 ng/g dw)and Pond-5(average 15.1 ng/g dw)were 1–2 orders of magnitude higher than those in other areas.In general,the legacy PFAS,i.e.,perfluorooctane sulfonic acid was considered to be the major pollutant in the polluted area,on average,accounting for 73.0%of the total concentration of PFAS pollutants.By evaluating the regional distribution of different PFAS homologs,the short-chain PFAS pollutants with lower K_(ow)were found to migrate farther in both horizontal and vertical directions.The sewage outlets in Pond-1 and Pond-5are the main pollution sources in polluted area and the emerging PFAS pollutants in Pond-5have replaced the legacy PFAS pollutants as the main pollutants.Based on positive matrix factorization analysis,three main industrial sources of PFAS pollutants in the study area were identified:protective coating,fire-fighting,and food packaging sources.Moreover,the environmental risk assessment results showed that most study areas exhibited medium environmental risk(0.01≤risk quotient(RQ)risks in this area need further attention.

关键词： Perfluoroalkyl substances Distribution Migration mechanism risk assessment

A risk assessment method considering risk attributes and work safety informational needs and its application

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Chinese Journal of Chemical Engineering 2024年第4期68卷 253-262页

作者： Cong Luo Yunsheng Zhao Ke Xu School of Political Science and Public Administration Shandong UniversityQingdao 266200China Faculty of Engineering China University of GeosciencesWuhan 430074China Department of Emergency Management of Hubei Province Wuhan 430064China

The technological revolution has spawned a new generation of industrial systems,but it has also put forward higher requirements for safety management accuracy,timeliness,and systematicness.risk assessment needs to evolve to address the existing and future challenges by considering the new demands and advancements in safety management.The study aims to propose a systematic and comprehensive risk assessment method to meet the needs of process system safety management.The methodology first incorporates possibility,severity,and dynamicity(PSD)to structure the“51X”evaluation indicator system,including the inherent,management,and disturbance risk factors.Subsequently,the four-tier(risk point-unit-enterprise-region)risk assessment(RA)mathematical model has been established to consider supervision needs.And in conclusion,the application of the PSD-RA method in ammonia refrigeration workshop cases and safety risk monitoring systems is presented to illustrate the feasibility and effectiveness of the proposed PSD-RA method in safety management.The findings show that the PSD-RA method can be well integrated with the needs of safety work informatization,which is also helpful for implementing the enterprise's safety work responsibility and the government's safety supervision responsibility.

关键词： risk assessment Safey “51X”evaluation indicator system Four-tier risk assessment model risk attributes Process system

IoT Smart Devices risk assessment Model Using Fuzzy Logic and PSO

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Computers, Materials & Continua 2024年第2期78卷 2245-2267页

作者： Ashraf S.Mashaleh Noor Farizah Binti Ibrahim Mohammad Alauthman Mohammad Almseidin Amjad Gawanmeh School of Computer Sciences Universiti Sains MalaysiaPenangMalaysia Department Computer Center Al-Balqa Applied UniversitySaltJordan Department of Information Security Faculty of Information TechnologyUniversity of PetraAmmanJordan Department of Computer Science Tafila Technical UniversityTafilaJordan College of Engineering and IT University of DubaiDubaiUnited Arab Emirates

Increasing Internet of Things(IoT)device connectivity makes botnet attacks more dangerous,carrying catastrophic hazards.As IoT botnets evolve,their dynamic and multifaceted nature hampers conventional detection methods.This paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization(PSO)to address the risks associated with IoT botnets.Fuzzy logic addresses IoT threat uncertainties and ambiguities methodically.Fuzzy component settings are optimized using PSO to improve accuracy.The methodology allows for more complex thinking by transitioning from binary to continuous assessment.Instead of expert inputs,PSO data-driven tunes rules and membership functions.This study presents a complete IoT botnet risk assessment system.The methodology helps security teams allocate resources by categorizing threats as high,medium,or low severity.This study shows how CICIoT2023 can assess cyber risks.Our research has implications beyond detection,as it provides a proactive approach to risk management and promotes the development of more secure IoT environments.

关键词： IoT botnet detection risk assessment fuzzy logic particle swarm optimization(PSO) cybersecurity interconnected devices

Trends and hotspots in gastrointestinal neoplasms risk assessment: A bibliometric analysis from 1984 to 2022

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World Journal of Gastrointestinal Oncology 2024年第6期16卷 2842-2861页

作者： Qiang-Qiang Fu Le Ma Xiao-Min Niu Hua-Xin Zhao Xu-Hua Ge Hua Jin De-Hua Yu Sen Yang Department of General Practice Yangpu HospitalSchool of MedicineTongji UniversityShanghai 200090China Shanghai General Practice and Community Health Development Research Center Shanghai 200090China Department of Shanghai Lung Cancer Center Shanghai Chest HospitalShanghai Jiao Tong University School of MedicineShanghai 200030China Department of Oncology Shanghai Tenth People’s HospitalTongji University School of MedicineShanghai 200090China

BACKGROUND Gastrointestinal neoplasm(GN)significantly impact the global cancer burden and mortality,necessitating early detection and treatment.Understanding the evolution and current state of research in this field is vital.AIM To conducts a comprehensive bibliometric analysis of publications from 1984 to 2022 to elucidate the trends and hotspots in the GN risk assessment research,focusing on key contributors,institutions,and thematic evolution.METHODS This study conducted a bibliometric analysis of data from the Web of Science Core Collection database using the"bibliometrix"R package,VOSviewer,and CiteSpace.The analysis focused on the distribution of publications,contributions by institutions and countries,and trends in keywords.The methods included data synthesis,network analysis,and visualization of international collaboration networks.RESULTS This analysis of 1371 articles on GN risk assessment revealed a notable evolution in terms of research focus and collaboration.It highlights the United States'critical role in advancing this field,with significant contributions from institutions such as Brigham and Women's Hospital and the National Cancer Institute.The last five years,substantial advancements have been made,representing nearly 45%of the examined literature.Publication rates have dramatically increased,from 20 articles in 2002 to 112 in 2022,reflecting intensified research efforts.This study underscores a growing trend toward interdisciplinary and international collaboration,with the Journal of Clinical Oncology standing out as a key publication outlet.This shift toward more comprehensive and collaborative research methods marks a significant step in addressing GN risks.CONCLUSION This study underscores advancements in GN risk assessment through genetic analyses and machine learning and reveals significant geographical disparities in research emphasis.This calls for enhanced global collaboration and integration of artificial intelligence to improve cancer prevention and treatment accuracy,ultimately enha

关键词： Gastrointestinal neoplasms Bibliometric analysis risk assessment Network analysis Research trends

Machine Learning-Based Decision-Making Mechanism for risk assessment of Cardiovascular Disease

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工程与科学中的计算机建模(英文) 2024年第1期138卷 691-718页

作者： Cheng Wang Haoran Zhu Congjun Rao School of Mathematics and Statistics Hubei University of EducationWuhan430205China School of Science Wuhan University of TechnologyWuhan430070China

Cardiovascular disease(CVD)has gradually become one of the main causes of harm to the life and health of residents.Exploring the influencing factors and risk assessment methods of CVD has become a general trend.In this paper,a machine learning-based decision-making mechanism for risk assessment of CVD is designed.In this mechanism,the logistics regression analysismethod and factor analysismodel are used to select age,obesity degree,blood pressure,blood fat,blood sugar,smoking status,drinking status,and exercise status as the main pathogenic factors of CVD,and an index systemof risk assessment for CVD is established.Then,a two-stage model combining K-means cluster analysis and random forest(RF)is proposed to evaluate and predict the risk of CVD,and the predicted results are compared with the methods of Bayesian discrimination,K-means cluster analysis and RF.The results show that thepredictioneffect of theproposedtwo-stagemodel is better than that of the comparedmethods.Moreover,several suggestions for the government,the medical industry and the public are provided based on the research results.

关键词： CVD influencing factors risk assessment machine learning two-stage model

An Innovative Deep Architecture for Flight Safety risk assessment Based on Time Series Data

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2549-2569页

作者： Hong Sun Fangquan Yang Peiwen Zhang Yang Jiao Yunxiang Zhao Civil Aviation Flight Technology and Flight Safety Research Base Civil Aviation Flight University of ChinaGuanghan618307China Airport Academy Civil Aviation Flight University of ChinaGuanghan618307China School of Economics and Management Civil Aviation Flight University of ChinaGuanghan618307China China Academy of Civil Aviation Science and Technology Beijing101300China Flight Training Standards Branch Civil Aviation Flight University of ChinaGuanghan618307China

With the development of the integration of aviation safety and artificial intelligence,research on the combination of risk assessment and artificial intelligence is particularly important in the field of risk management,but searching for an efficient and accurate risk assessment algorithm has become a challenge for the civil aviation industry.Therefore,an improved risk assessment algorithm(PS-AE-LSTM)based on long short-term memory network(LSTM)with autoencoder(AE)is proposed for the various supervised deep learning algorithms in flight safety that cannot adequately address the problem of the quality on risk level labels.Firstly,based on the normal distribution characteristics of flight data,a probability severity(PS)model is established to enhance the quality of risk assessment labels.Secondly,autoencoder is introduced to reconstruct the flight parameter data to improve the data quality.Finally,utilizing the time-series nature of flight data,a long and short-termmemory network is used to classify the risk level and improve the accuracy of risk assessment.Thus,a risk assessment experimentwas conducted to analyze a fleet landing phase dataset using the PS-AE-LSTMalgorithm to assess the risk level associated with aircraft hard landing events.The results show that the proposed algorithm achieves an accuracy of 86.45%compared with seven baseline models and has excellent risk assessment capability.

关键词： Safety engineering risk assessment time series data autoencoder LSTM

risk assessment of high-speed railway CTC system based on improved game theory and cloud model

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Railway Sciences 2024年第3期3卷 388-410页

作者： Yanhao Sun Tao Zhang Shuxin Ding Zhiming Yuan Shengliang Yang Signal and Communication Research Institute China Academy of Railway Sciences Corporation LimitedBeijingChina Traffic Management Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail TransitBeijingChina Signal and Telecommunication Department China Railway Chengdu Group Company LimitedChengduChina Postgraduate Department China Academy of Railway SciencesBeijingChina

Purpose-In order to solve the problem of inaccurate calculation of index weights,subjectivity and uncertainty of index assessment in the risk assessment process,this study aims to propose a scientific and reasonable centralized traffic control(CTC)system risk assessment method.Design/methodologylapproach-First,system-theoretic process analysis(STPA)is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis.Then,to enhance the accuracy of weight calculation,the fuzzy analytical hierarchy process(FAHP),fuzzy decision-making trial and evaluation laboratory(FDEMATEL)and entropy weight method are employed to calculate the subjective weight,relative weight and objective weight of each index.These three types of weights are combined using game theory to obtain the combined weight for each index.To reduce subjectivity and uncertainty in the assessment process,the backward cloud generator method is utilized to obtain the numerical character(NC)of the cloud model for each index.The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system.This cloud model is used to obtain the CTC system's comprehensive risk assessment.The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud.Finally,this process yields the risk assessment results for the CTC system.Findings-The cloud model can handle the subjectivity and fuzziness in the risk assessment process well.The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.Originality/value-This study provides a cloud model-based method for risk assessment of CTC systems,which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment,achieving effective risk assessment of CTC systems.It can provide a reference and theoretical basis for risk management of the CTC

关键词： High-speed railway Centralized traffic control risk assessment Game theory Cloud model Paper type Research paper

Comprehensive risk assessment of Sea Level Rise and Tropical Cyclones in Dongzhaigang Mangroves,China

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Chinese Geographical Science 2024年第4期34卷 631-646页

作者： DING Ruyi CAI Rongshuo YAN Xiuhua LI Cuihua WANG Cui NIE Xinyu Third Institute of Oceanography Ministry of Natural ResourcesXiamen 361005China

Mangroves play a pivotal role in tropical and subtropical coastal ecosystem,yet they are highly vulnerable to the effects of climate change,particularly the accelerated global sea level rise(SLR)and stronger tropical cyclones(TCs).However,there is a lack of research addressing future simultaneous combined impacts of the slow-onset of SLR and rapid-onset of TCs on China's mangroves.In order to develop a comprehensive risk assessment method considering the superimposed effects of these two factors and analyze risk for mangroves in Dongzhaigang,Hainan Island,China,we used observational and climate model data to assess the risks to mangroves under low,intermediate,and very high greenhouse gas(GHG)emission scenarios(such as SSP1-2.6,SSP2-4.5,and SSP5-8.5)in 2030,2050,and 2100,and compiled a risk assessment scheme for mangroves in Dongzhaigang,China.The results showed that the combined risks from SLR and TCs will continue to rise;however,SLRs will increase in intensity,and TCs will decrease.The comprehensive risk of the Dongzhaigang mangroves posed by climate change will remain low under SSP1-2.6 and SSP2-4.5 scenarios by 2030,but it will increase substantially by 2100.While under SSP5-8.5 scenario,the risks to mangroves in Dongzhaigang are projected to increase considerably by 2050,and approximately 68.8%of mangroves will be at very high risk by 2100.The risk to the Dongzhaigang mangroves is not only influenced by the hazards but also closely linked to their exposure and vulnerability.We therefore propose climate resilience developmental responses for mangroves to address the effects of climate change.This study for the combined impact of TCs and SLR on mangroves in Dongzhaigang,China can enrich the method system of mangrove risk assessment and provide references for scientific management.

关键词： mangrove climate change risk assessment combined hazards sea level rise(SLR) tropical cyclones(TCs) resilience development Dongzhaigang China