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学者姓名：谢启伟
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Abstract ：
Environmental regulations can effectively mitigate environmental degradation, yet their impact on energy efficiency remains unclear. This study contributes to the existing literature by examining how the Environmental Protection Tax Law (EPTL) drives energy efficiency and demonstrating its environmental and economic dividends. Empirical evidence from a dataset of 271 Chinese prefecture-level cities from 2011 to 2020 reveals that EPTL significantly enhances energy efficiency by 3.8%, and it has a positive spatial spillover effect. The underlying mechanisms are improvements in environmental governance and economic development. Heterogeneity analysis highlights a particularly prominent positive impact in the eastern and western regions. Our study confirms the effectiveness of EPTL in promoting energy efficiency and supports the double dividend hypothesis, providing policymakers with insights for formulating differentiated policies.
Keyword ：
Environmental Protection Tax Law Environmental Protection Tax Law Double dividend Double dividend Energy efficiency Energy efficiency Environmental governance Environmental governance Spatial spillover effect Spatial spillover effect Economic development Economic development
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| GB/T 7714 | Jin, Xi , Wang, Lizheng , Xie, Qiwei et al. Taxing for a Green Future: How China's Environmental Protection Tax Law Drives Energy Efficiency [J]. | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH , 2024 , 18 (2) . |
| MLA | Jin, Xi et al. "Taxing for a Green Future: How China's Environmental Protection Tax Law Drives Energy Efficiency" . | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH 18 . 2 (2024) . |
| APA | Jin, Xi , Wang, Lizheng , Xie, Qiwei , Li, Yongjun , Liang, Liang . Taxing for a Green Future: How China's Environmental Protection Tax Law Drives Energy Efficiency . | INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH , 2024 , 18 (2) . |
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The efficiency of green credit in commercial banks is important for promoting green economic development. But seldom studies have investigated the efficiency evaluation of banking green credit activities. To fill this gap, this paper proposes a model for assessing the efficiency of green credit and further investigates the factors that potentially affect the efficiencies. The evaluation model for green credit efficiency is built through a multi-period leader-follower framework by innovatively considering green credit as an inherent input-output indicator with preference. The results demonstrate that the green credit efficiency of the Chinese commercial banks in the profit earning stage generally surpasses that in the deposit conversion stage. Throughout the multi-period analysis, the majority of banks, especially those that are state-owned, have improved their deposit conversion efficiency from 2017 to 2021. The efficiency in the profit earning stage for all banks significantly declined due to the impact of COVID-19. Bank size, asset quality, and macroeconomic conditions have significant influences on green credit efficiency. However, their influences vary heterogeneously across different stages and types of banks.
Keyword ：
Green credit Green credit Preference Preference Commercial banks Commercial banks Efficiency evaluation Efficiency evaluation Multi-period leader-follower model Multi-period leader-follower model
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| GB/T 7714 | Li, Jingyu , Guo, Xiangyuan , Xie, Qiwei et al. Green credit efficiency of commercial banks in China: Evidence from a multi-period leader-follower model with preference [J]. | INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS , 2024 , 96 . |
| MLA | Li, Jingyu et al. "Green credit efficiency of commercial banks in China: Evidence from a multi-period leader-follower model with preference" . | INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS 96 (2024) . |
| APA | Li, Jingyu , Guo, Xiangyuan , Xie, Qiwei , Sun, Xiaolei . Green credit efficiency of commercial banks in China: Evidence from a multi-period leader-follower model with preference . | INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS , 2024 , 96 . |
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Synapses are fundamental components of how neurons communicate with each other and have attracted widespread attention from neuroscientists. Due to the rapid development of electron microscopy (EM) technology, imaging synapses at nanometer scale has become possible. However, the automation and efficacy of the synapse detection algorithm have not yet met expectations. The most popular approach involves a two-step process in which binary segmentation masks are first obtained and then connected components are used to produce reconstruction results. In this paper, an intelligent system to detect and segment synapses from serial section EM images is proposed. Specifically, a novel 3D instance segmentation network that can predict the synapses end-to-end is presented. The network can exploit and summarize features consistent with the biological structures of synapses, which is similar to the process of manual annotation. A block-wise inference strategy that adapts well to large-scale EM images is then introduced. Finally, two public datasets are used to evaluate our method. Experimental results demonstrate the superiority of the proposed approach, thus enabling computer-assisted analysis of synapses for neuroscientists.
Keyword ：
Electron microscopy Electron microscopy Instance segmentation Instance segmentation Connectomics Connectomics Deep learning Deep learning Synapse Synapse
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| GB/T 7714 | Liu, Jing , Hong, Bei , Xiao, Chi et al. A novel 3D instance segmentation network for synapse reconstruction from serial electron microscopy images [J]. | EXPERT SYSTEMS WITH APPLICATIONS , 2024 , 255 . |
| MLA | Liu, Jing et al. "A novel 3D instance segmentation network for synapse reconstruction from serial electron microscopy images" . | EXPERT SYSTEMS WITH APPLICATIONS 255 (2024) . |
| APA | Liu, Jing , Hong, Bei , Xiao, Chi , Zhai, Hao , Shen, Lijun , Xie, Qiwei et al. A novel 3D instance segmentation network for synapse reconstruction from serial electron microscopy images . | EXPERT SYSTEMS WITH APPLICATIONS , 2024 , 255 . |
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Current research on commercial bank credit risk mainly focuses on the risk of loans and advances without considering the treasury operations and off-balance-sheet credit business that also carry credit risk. Ignoring the correlation between diverse risk factors results in the biased integration of credit risk. In this work, we aggregate the credit risk of commercial banks based on three risk factors using a vine copula. Our empirical results show that banks that are not global systemically important banks are confronted with higher credit risk than global systemically important banks. In addition, the risk of loans-and-advances business is positively correlated with treasury operations risk and negatively correlated with off-balance-sheet credit business. While the risk of loans-and-advances business is significant, the risks of treasury operations and off-balance-sheet credit business still play an indispensable role in (and contain vital information about) credit risk. In addition, banking as a system can achieve lower credit risk, but this effect is weakened under the extreme lower-tail risk.
Keyword ：
commercial banks commercial banks risk integration risk integration credit risk credit risk risk dependency risk dependency vine copula vine copula
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| GB/T 7714 | Xie, Qiwei , Cheng, Lu , Li, Jingyu et al. The impact of treasury operations and off-balance-sheet credit business on commercial bank credit risk [J]. | JOURNAL OF RISK , 2023 , 25 (5) : 23-50 . |
| MLA | Xie, Qiwei et al. "The impact of treasury operations and off-balance-sheet credit business on commercial bank credit risk" . | JOURNAL OF RISK 25 . 5 (2023) : 23-50 . |
| APA | Xie, Qiwei , Cheng, Lu , Li, Jingyu , Zheng, Xiaolong . The impact of treasury operations and off-balance-sheet credit business on commercial bank credit risk . | JOURNAL OF RISK , 2023 , 25 (5) , 23-50 . |
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Currently, most state-of-the-art pipelines for 3D micro-connectomic reconstruction deal with neuron over-segmentation, agglomeration and subcellular compartment (nuclei, mitochondria, synapses, etc.) detection separately. Inspired by the proofreading consensus of experts, we established a paradigm to acquire priori knowledge of cellular characteristics and ultrastructures, as well as determine the connectivity of neural circuits simultaneously. Following this novel paradigm, we were keen to bring the Intra- and Inter-Cellular Awareness back when Tracking and Segmenting neurons in connectomics. Our proposed method (II-CATS) utilizes few-shot learning techniques to encode the internal neurite representation and its learnable components, which could significantly impact neuron tracings. We further go beyond the original expected run length (ERL) metric by focusing on biological constraints (bERL) or spanning from the nucleus to spines (nERL). With the evaluation of these metrics, we perform typical experiments on multiple electron microscopy datasets on diverse animals and scales. In particular, our proposed method is naturally suitable for tracking neurons that have been identified by staining.
Keyword ：
connectomics connectomics neuron segmentation neuron segmentation neuron tracking neuron tracking few-shot learning few-shot learning
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| GB/T 7714 | Zhai, Hao , Liu, Jing , Hong, Bei et al. Intra- and Inter-Cellular Awareness for 3D Neuron Tracking and Segmentation in Large-Scale Connectomics [J]. | MEDICAL IMAGING WITH DEEP LEARNING, VOL 227 , 2023 , 227 : 1691-1712 . |
| MLA | Zhai, Hao et al. "Intra- and Inter-Cellular Awareness for 3D Neuron Tracking and Segmentation in Large-Scale Connectomics" . | MEDICAL IMAGING WITH DEEP LEARNING, VOL 227 227 (2023) : 1691-1712 . |
| APA | Zhai, Hao , Liu, Jing , Hong, Bei , Liu, Jiazheng , Xie, Qiwei , Han, Hua . Intra- and Inter-Cellular Awareness for 3D Neuron Tracking and Segmentation in Large-Scale Connectomics . | MEDICAL IMAGING WITH DEEP LEARNING, VOL 227 , 2023 , 227 , 1691-1712 . |
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Abstract ：
The structural information detection of road conditions, which is adopted for improving driving comfort, patrol inspection, road maintenance, and accident rescue. In order to improve the trustworthiness of road condition detection, a real-time artificial intelligence road detection system based on binocular vision sensors is investigated in this article. The system is deployed on the low-power edge computing platform, which can upload the processing results to the cloud through the Internet-of-Things devices. The authors use binocular disparity information and image-based lightweight deep segmentation network to enhance the detection robustness and accuracy in the industrial Internet-of-Things application scenarios. Considering the small training dataset, a special data labeling regularization and training strategy have also been proposed for training this network. In addition, we employ multiframes feature matching and measurement data filtering to enhance the measurement accuracy. The experimental results demonstrate that our monocular-binocular fusion framework is robust and efficient.
Keyword ：
monocular-binocular fusion framework monocular-binocular fusion framework Task analysis Task analysis Cameras Cameras trustworthy road condition detection trustworthy road condition detection deep learning deep learning Image segmentation Image segmentation Deep learning Deep learning Field programmable gate arrays Field programmable gate arrays Computational modeling Computational modeling Binocular vision Binocular vision Roads Roads
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| GB/T 7714 | Xie, Qiwei , Hu, Xiyuan , Ren, Lei et al. A Binocular Vision Application in IoT: Realtime Trustworthy Road Condition Detection System in Passable Area [J]. | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS , 2023 , 19 (1) : 973-983 . |
| MLA | Xie, Qiwei et al. "A Binocular Vision Application in IoT: Realtime Trustworthy Road Condition Detection System in Passable Area" . | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 19 . 1 (2023) : 973-983 . |
| APA | Xie, Qiwei , Hu, Xiyuan , Ren, Lei , Qi, Lianyong , Sun, Zhao . A Binocular Vision Application in IoT: Realtime Trustworthy Road Condition Detection System in Passable Area . | IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS , 2023 , 19 (1) , 973-983 . |
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The insurance industry plays a crucial role of the national financial system, and the operating efficiency of insurance companies has always been a significant subject of academic research. This study proposes a multiperiod DEA model to dynamically evaluate the operating efficiency of insurance companies, which not only overcomes the defect of the traditional DEA method ignoring the internal structure of decision-making units, but also extends the limitation of the leader-follower model in evaluating single-period efficiency. By analyzing the efficiency of seven listed insurance companies in China from 2009 to 2018, the following conclusions are drawn. The multiperiod DEA model demonstrates advantages over the leader-follower model. The profitability of insurance companies during the first five years is higher compared with the last five years. There is a significant correlation between premium financing efficiency and overall efficiency. Throughout both periods, the loss ratio, loss reserve ratio, and consumer price index (CPI) are always positively correlated with the efficiency of the insurer, while the gearing ratio is negatively related to the efficiency of the insurer. The correlation among gross domestic product (GDP), total insurance value, tradable financial assets, and corporate efficiency varies over time.
Keyword ：
insurance companies insurance companies multiple periods multiple periods DEA DEA leader-follower model leader-follower model
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| GB/T 7714 | Xie, Qiwei , Zhao, Mengfan , Li, Rong et al. Efficiency Evaluation of Insurance Companies From Multiperiod Perspective [J]. | IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS , 2023 , 11 (2) : 2656-2674 . |
| MLA | Xie, Qiwei et al. "Efficiency Evaluation of Insurance Companies From Multiperiod Perspective" . | IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 11 . 2 (2023) : 2656-2674 . |
| APA | Xie, Qiwei , Zhao, Mengfan , Li, Rong , Li, Wen , Zheng, Xiaolong , Li, Yongjun et al. Efficiency Evaluation of Insurance Companies From Multiperiod Perspective . | IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS , 2023 , 11 (2) , 2656-2674 . |
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This paper studies the carbon price fluctuation in China through the adaptive Fourier decomposition (AFD). Apart from the transient time-frequency distribution of the original AFD model, we also reconstruct the mono-components of this model to obtain the components in different time-frequency scales. Our empirical results based on the carbon price in Hubei Province demonstrate that there are three periods when the price fluctuates dramatically, mainly affected by the governmental policies about carbon emission and the development of clean energies, as well as the outbreak of COVID-19. Furthermore, the fluctuations of the price in the three identified periods are reflected in different scales. The comparison of the decomposition results and those of EMD and VIVID shows that the AFD performs best in absorbing the price's useful information extracted through all these methods. (C) 2021 The Authors. Published by Elsevier B.V.
Keyword ：
adaptive Fourier decomposition adaptive Fourier decomposition time-frequency domain time-frequency domain Carbon price Carbon price
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| GB/T 7714 | Li, Jingyu , Liu, Ranran , Xie, Qiwei . The price fluctuation in Chinese carbon emission trading market: New evidence from adaptive Fourier decomposition [J]. | 8TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2020 & 2021): DEVELOPING GLOBAL DIGITAL ECONOMY AFTER COVID-19 , 2022 , 199 : 1095-1102 . |
| MLA | Li, Jingyu et al. "The price fluctuation in Chinese carbon emission trading market: New evidence from adaptive Fourier decomposition" . | 8TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2020 & 2021): DEVELOPING GLOBAL DIGITAL ECONOMY AFTER COVID-19 199 (2022) : 1095-1102 . |
| APA | Li, Jingyu , Liu, Ranran , Xie, Qiwei . The price fluctuation in Chinese carbon emission trading market: New evidence from adaptive Fourier decomposition . | 8TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT (ITQM 2020 & 2021): DEVELOPING GLOBAL DIGITAL ECONOMY AFTER COVID-19 , 2022 , 199 , 1095-1102 . |
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PurposeThis study aims to systematically reveal the complex interaction between uncertainty and the international commodity market (CRB).Design/methodology/approachA composite uncertainty index and five categorical uncertainty indices, together with wavelet analysis and detrended cross-correlation analysis, were used. First, in the time-frequency domain, the coherency and lead-lag relationship between uncertainty and the commodity markets were investigated. Furthermore, the transmission direction of the cross-correlation over different lag periods and asymmetry in this cross-correlation under different trends were identified.FindingsFirst, there is significant coherency between uncertainties and CRB mainly in the short and medium terms, with natural disaster and public health uncertainties tending to lead CRB. Second, uncertainty impacts CRB more markedly over shorter lag periods, whereas the impact of CRB on uncertainty gradually increases with longer lag periods. Third, the cross-correlation is asymmetric and multifractal under different trends. Finally, from the perspective of lag periods and trends, the interaction of uncertainty with the Chinese commodity market is significantly different from its interaction with CRB.Originality/valueFirst, this study comprehensively constructs a composite uncertainty index based on five types of uncertainty. Second, this study provides a scientific perspective on examining the core and diverse interactions between uncertainty and CRB, as achieved by investigating the interactions of CRB with five categorical and composite uncertainties. Third, this study provides a new research framework to enable multiscale analysis of the complex interaction between uncertainty and the commodity markets.
Keyword ：
Wavelet analysis Wavelet analysis DCCA methods DCCA methods International commodity market International commodity market Uncertainty Uncertainty
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| GB/T 7714 | Liu, Chao , Zhang, Wei , Xie, Qiwei et al. Multiscale analysis of the complex interaction between uncertainty and the international commodity market [J]. | INTERNATIONAL JOURNAL OF EMERGING MARKETS , 2022 . |
| MLA | Liu, Chao et al. "Multiscale analysis of the complex interaction between uncertainty and the international commodity market" . | INTERNATIONAL JOURNAL OF EMERGING MARKETS (2022) . |
| APA | Liu, Chao , Zhang, Wei , Xie, Qiwei , Wang, Chao . Multiscale analysis of the complex interaction between uncertainty and the international commodity market . | INTERNATIONAL JOURNAL OF EMERGING MARKETS , 2022 . |
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Abstract ：
Carbon trading is a vital market mechanism to achieve carbon emission reduction. The accurate prediction of the carbon price is conducive to the effective management and decision-making of the carbon trading market. However, existing research on carbon price forecasting has ignored the impacts of multiple factors on the carbon price, especially climate change. This study proposes a text-based framework for carbon price prediction that considers the impact of climate change. Textual online news is innovatively employed to construct a climate-related variable. The information is combined with other variables affecting the carbon price to forecast the carbon price, using a long short-term memory network and random forest model. The results demonstrate that the prediction accuracy of the carbon price in the Hubei and Guangdong carbon markets is enhanced by adding the textual variable that measures climate change. (c) 2022 Economic Society of Australia, Queensland. Published by Elsevier B.V. All rights reserved.
Keyword ：
Climate change Climate change Long short-term memory (LSTM) Long short-term memory (LSTM) Random forest (RF) Random forest (RF) Text mining Text mining Carbon price prediction Carbon price prediction
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| GB/T 7714 | Xie, Qiwei , Hao, Jingjing , Li, Jingyu et al. Carbon price prediction considering climate change: A text-based framework [J]. | ECONOMIC ANALYSIS AND POLICY , 2022 , 74 : 382-401 . |
| MLA | Xie, Qiwei et al. "Carbon price prediction considering climate change: A text-based framework" . | ECONOMIC ANALYSIS AND POLICY 74 (2022) : 382-401 . |
| APA | Xie, Qiwei , Hao, Jingjing , Li, Jingyu , Zheng, Xiaolong . Carbon price prediction considering climate change: A text-based framework . | ECONOMIC ANALYSIS AND POLICY , 2022 , 74 , 382-401 . |
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