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Could the EU carbon border adjustment mechanism promote climate mitigation?An economy-wide analysis

Advances in Climate Change Research 2024年第3期15卷 557-571页

作者： Kun ZHANG Yun-Fei YAO Xiang-Yan QIAN Yu-Fei ZHANG Qiao-Mei LIANG Yi-Ming WEI College of economics and management Beijing University of TechnologyBeijing 100124China Center for Energy and Environmental Policy Research Beijing Institute of TechnologyBeijing 100081China school of management and economics Beijing Institute of TechnologyBeijing 100081China beijing Key Laboratory of Energy economics and Environmental management Beijing 100081China Sinopec Research institute of Petroleum Engineering SinopecBeijing 100101China College of economics and management Nanjing Agricultural UniversityNanjing 210095China

Due to concerns about carbon leakage and sectoral competitiveness,the European Union(EU)proposed implementing the carbon border adjustment mechanism(CBAM).The effectiveness and potential negative consequences of CBAM have aroused extensive *** the perspective of the economy-wide analysis,this study uses a global computable general equilibrium model to explore the rationality of CBAM from the aspects of socioeconomic impact and the effects of promoting climate ***,the potential alternative mechanism of CBAM is *** results show that CBAM can reduce the EU's gross domestic product(GDP)loss;however,the GDP loss in all other regions ***,CBAM raises household welfare losses in most regions,including the ***,although CBAM can reduce the marginal abatement cost in eight regions,it comes at the cost of greater economic ***,the economic and household welfare cost of raising emissions reduction targets in regions like the USA and Japan is substantially higher than the impact of passively accepting the CBAM;therefore,CBAM's ability to drive ambitious emission reduction initiatives may be ***,for the potential alternative mechanism,from the perspective of reducing economic cost and household welfare losses,the EU could implement domestic tax cuts in the short-term and promote global unified carbon pricing in the long-term.

关键词： Border adjustment mechanism Computable general equilibrium model Carbon price Climate policy Global carbon pricing

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Influence mechanism of government subsidy on the green transformation of coal company in China

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International Journal of Mining Science and technology 2024年第7期34卷 1033-1040页

作者： Xiaolei Li Changsong Wu school of management China University of Mining and Technology-BeijingBeijing 100083China school of economics and management China University of Mining and TechnologyXuzhou 221116China

The optimization of government subsidies to enhance the efficiency of coal companies’green transformation constitutes a critical component in the pursuit of global *** investigate the influence mechanism of government subsidies on the green transformation using data from the listed coal companies in China from 2007 to *** to our findings and hypothesis testing,previous government subsidies did not have a significant direct impact on coal companies’green ***,government subsidies can help coal companies transition to greener practices by promoting innovative green ***,we confirmed an indirect route:that government subsidies enable the adoption of low-carbon initiatives,which in turn could facilitate the transition of coal companies towards green *** addition,we discovered that the coal company’s digitization will improve this indirect ***,we propose increasing the effectiveness of government subsidies in facilitating coal companies’transition to green practices by focusing on technological advancements and enhancing company digitalization.

关键词： Government subsidy Green transformation Coal company Digitalization Innovation

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Robust reinforcement learning with UUB guarantee for safe motion control of autonomous robots

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Science China(Technological Sciences) 2024年第1期67卷 172-182页

作者： ZHANG RuiXian HAN YiNing SU Man LIN ZeFeng LI HaoWei ZHANG LiXian school of Astronautics Harbin Institute of TechnologyHarbin 150001China school of management Harbin Institute of TechnologyHarbin 150001China beijing institute of Tracking and Telecommunication technology Beijing 100094China

This paper addresses the issue of safety in reinforcement learning(RL)with disturbances and its application in the safety-constrained motion control of autonomous *** tackle this problem,a robust Lyapunov value function(rLVF)is *** rLVF is obtained by introducing a data-based LVF under the worst-case disturbance of the observed *** the rLVF,a uniformly ultimate boundedness criterion is *** criterion is desired to ensure that the cost function,which serves as a safety criterion,ultimately converges to a range via the policy to be ***,to mitigate the drastic variation of the rLVF caused by differences in states,a smoothing regularization of the rLVF is *** train policies with safety guarantees under the worst disturbances of the observed states,an off-policy robust RL algorithm is *** proposed algorithm is applied to motion control tasks of an autonomous vehicle and a cartpole,which involve external disturbances and variations of the model parameters,*** experimental results demonstrate the effectiveness of the theoretical findings and the advantages of the proposed algorithm in terms of robustness and safety.

关键词： motion control reinforcement learning robustness stability

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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

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Recent advances and perspectives in MXene-based cathodes for aqueous zinc-ion batteries

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International Journal of Minerals,Metallurgy and Materials 2024年第7期31卷 1752-1765页

作者： Aiduo Wu Tianhao Wang Long Zhang Chen Chen Qiaomin Li Xuanhui Qu Yongchang Liu beijing Advanced Innovation Center for Materials Genome Engineering Institute for Advanced Materials and TechnologyState Key Laboratory for Advanced Metals and MaterialsUniversity of Science and Technology BeijingBeijing 100083China school of Materials Science and Engineering University of Science and Technology BeijingBeijing 100083China school of economics and management University of Science and Technology BeijingBeijing 100083China

Aqueous zinc-ion batteries(AZIBs)show great potential for applications in grid-scale energy storage,given their intrinsic safety,cost effectiveness,environmental friendliness,and impressive electrochemical ***,strong electrostatic interactions exist between zinc ions and host materials,and they hinder the development of advanced cathode materials for efficient,rapid,and stable Zn-ion *** and their derivatives possess a large interlayer spacing,excellent hydrophilicity,outstanding electronic conductivity,and high redox *** materials are considered“rising star”cathode candidates for *** comprehensive review discusses recent advances in MXenes as AZIB cathodes from the perspectives of crystal structure,Zn-storage mechanism,surface modification,interlayer engineering,and conductive network design to elucidate the correlations among their composition,structure,and electrochemical *** work also outlines the remaining challenges faced by MXenes for aqueous Zn-ion storage,such as the urgent need for improved toxic preparation methods,exploration of potential novel MXene cathodes,and suppression of layered MXene restacking upon cycling,and introduces the prospects of MXene-based cathode materials for high-performance AZIBs.

关键词： aqueous zinc-ion batteries MXenes terminal groups interlayer engineering conductive network design

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Performance evaluation of seven multi-label classification methods on real-world patent and publication datasets

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Journal of Data and Information Science 2024年第2期9卷 81-103页

作者： Shuo Xu Yuefu Zhang Xin An Sainan Pi College of economics and management Beijing University of TechnologyBeijing 100124China school of economics&management Beijing Forestry UniversityBeijing 100083China

Purpose:Many science,technology and innovation(STI)resources are attached with several different *** assign automatically the resulting labels to an interested instance,many approaches with good performance on the benchmark datasets have been proposed for multi-label classification task in the ***,several open-source tools implementing these approaches have also been ***,the characteristics of real-world multi-label patent and publication datasets are not completely in line with those of benchmark ***,the main purpose of this paper is to evaluate comprehensively seven multi-label classification methods on real-world *** limitations:Three real-world datasets differ in the following aspects:statement,data quality,and ***,open-source tools designed for multi-label classification also have intrinsic differences in their approaches for data processing and feature selection,which in turn impacts the performance of a multi-label classification *** the near future,we will enhance experimental precision and reinforce the validity of conclusions by employing more rigorous control over variables through introducing expanded parameter *** implications:The observed Macro F1 and Micro F1 scores on real-world datasets typically fall short of those achieved on benchmark datasets,underscoring the complexity of real-world multi-label classification *** leveraging deep learning techniques offer promising solutions by accommodating the hierarchical relationships and interdependencies among *** ongoing enhancements in deep learning algorithms and large-scale models,it is expected that the efficacy of multi-label classification tasks will be significantly improved,reaching a level of practical utility in the foreseeable ***/value:(1)Seven multi-label classification methods are comprehensively compared on three real-world datasets.(2)The TextCNN and

关键词： Multi-label classification Real-World datasets Hierarchical structure Classification system Label correlation Machine learning

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Spatial impact of digital finance on carbon productivity

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Geoscience Frontiers 2024年第3期15卷 358-372页

作者： Huaping Sun Tingting Chen Christoph Nedopil Wang school of Finance and economics Jiangsu UniversityZhenjiangChina school of economics and management University of Science and Technology BeijingBeijingChina Fanhai International school of Finance Fudan UniversityShanghaiChina

Low carbon productivity has been identified as a key direction for China’s future *** an important driving force for economic growth,the question of whether digital finance that is reliant on digital technology can support the development of a low-carbon urban economy remains *** on the carbon productivity measured by panel data from 201 cities for the period 2011-2020,this study applies the spatial Dubin model and threshold regression model to explore the impact of digital finance on carbon productivity,yielding the following key ***,the spatial distribution heterogeneity of carbon productivity in China’s eastern region is higher than that in the western region,and both productivity and digital finance are characterized by high(low)-high(low)dotted spatial ***,digital finance can significantly improve carbon productivity via two transmission channels:the human capital and marketization *** the same time,digital finance exerts a spatial spillover effect on carbon productivity,and rising local digital finance levels will increase carbon productivity in neighboring *** analysis indicates that the spillover effect of digital finance in urban agglomerations and eastern regions is more ***,fixed-asset investment has a positive nonlinear moderating effect on digital finance,thus improving carbon *** the per capita investment in fixed assets does not exceed 682.73 yuan,digital finance exerts only a limit pulling effect on carbon productivity;when it is higher than this value,the pulling effect is intensified.

关键词： Digital finance Carbon productivity Spatial spillover effect Fixed-asset investment Spatial heterogeneity

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A comprehensive framework for predicting public opinion by tracking multi-informational dynamics

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Frontiers of Computer Science 2024年第4期18卷 197-199页

作者： Mingtao SUN Yan WEI Shan JIANG Guozhu JIA school of economics and management Beihang UniversityBeijing 100191China school of Software Beihang UniversityBeijing 100191China school of economics Wuhan University of TechnologyWuhan 430070China

1 Introduction In the digital landscape,trivial rumors can spark significant online reactions[1].Accurate prediction of public opinion is important for crisis management,misinformation mitigation,and fostering public ***,existing methods often fail to thoroughly investigate multiple informational factors and their timely interactions[2-4],thereby limiting their efficacy in analysing public opinion.

关键词： thereby thoroughly limiting

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De-biased knowledge distillation framework based on knowledge infusion and label de-biasing techniques

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Journal of Electronic Science and technology 2024年第3期22卷 57-68页

作者： Yan Li Tai-Kang Tian Meng-Yu Zhuang Yu-Ting Sun school of economics and management University of Electronic Science and Technology of ChinaChengdu611731China school of economics and management Beijing University of Posts and TelecommunicationBeijing100876China school of Electrical Engineering and Computer Science The University of QueenslandBrisbane4072Australia

Knowledge distillation,as a pivotal technique in the field of model compression,has been widely applied across various ***,the problem of student model performance being limited due to inherent biases in the teacher model during the distillation process still *** address the inherent biases in knowledge distillation,we propose a de-biased knowledge distillation framework tailored for binary classification *** the pre-trained teacher model,biases in the soft labels are mitigated through knowledge infusion and label de-biasing *** on this,a de-biased distillation loss is introduced,allowing the de-biased labels to replace the soft labels as the fitting target for the student *** approach enables the student model to learn from the corrected model information,achieving high-performance deployment on lightweight student *** conducted on multiple real-world datasets demonstrate that deep learning models compressed under the de-biased knowledge distillation framework significantly outperform traditional response-based and feature-based knowledge distillation models across various evaluation metrics,highlighting the effectiveness and superiority of the de-biased knowledge distillation framework in model compression.

关键词： De-biasing Deep learning Knowledge distillation Model compression

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Community-Level Practice Checklists for Health Protection During Cold Spells in China

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China CDC weekly 2024年第5期6卷 83-87页

作者： Jing Shang Mengzhen Zhao Zhao Liu Xiya Zhang Shiguang Miao Ishaq D.Sulaymon Wenjia Cai institute of Urban Meteorology CMABeijingChina school of management and economics Beijing Institute of TechnologyBeijingChina school of Airport economics and management Beijing Institute of Economics and ManagementBeijingChina Department of Earth System Science Tsinghua UniversityBeijingChina Sand and Dust Storm Warning Regional Center National Center for MeteorologyJeddahSaudi Arabia Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment TechnologySchool of Environmental Science and EngineeringNanjing University of Information Science and TechnologyNanjing CityJiangsu ProvinceChina

Communities play a crucial role in protecting the health of vulnerable populations such as the elderly,low-income groups,and high-risk individuals during cold ***,current strategies for responding to cold spells primarily consist of programmatic policies that lack practicality,specificity,and detailed implementation guidelines for community ***,this study aims to identify and analyze the challenges faced by communities in responding to cold spells,review international experiences,and develop a set of practical checklists for community-level health *** checklists will assist community workers and volunteers in effectively preparing for,responding to,and recovering from cold spells.

关键词： preparing income primarily

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