Article
Green & Sustainable Science & Technology
Zhuyuan Li, Xiaolong Wang, Run Zheng, Sanggyun Na, Chang Liu
Summary: This study analyzes the operational efficiency and total factor productivity of 32 container terminal companies in China. The research reveals the existence of efficiency gaps and resource waste in some container terminals, while highlighting the higher operational efficiency of terminals in the Bohai Rim, Pearl River Delta, and Yangtze River Delta regions. Furthermore, the study finds that most container terminal companies have imperfect management practices and decision making.
Article
Economics
Xiang Chen, Yong Chen, Wenli Huang, Xuping Zhang
Summary: China's rapid economic development and increasing GDP over the past forty years has led to serious environmental problems. This research proposes a new model of the green Malmquist productivity index by combining green total factor productivity (GTFP) with the characteristics of the Malmquist and Luenberger indices. The empirical study finds that GTFP in China is increasing but at a decreasing rate, primarily due to a slowdown in technical progress. Additionally, significant differences are observed among the eastern, central, and western regions of China.
Article
Energy & Fuels
Zile Zheng
Summary: This paper analyzes the energy efficiency of 23 cities by evaluating Total Factor Energy Efficiency (TFEE). The results show significant differences in TFEE changes among regions, with cities like Harbin, Shanghai, and Changsha showing an upward trend while Chengdu, Chongqing, and others have minor changes. Inadequate resource allocation and lack of technological innovation are the main reasons for the decline in Total Factor Productivity (TFP).
Article
Agronomy
Xiao Wang, Jiaojiao Li, Jia Li, Yu Chen, Jinming Shi, Jianxu Liu, Songsak Sriboonchitta
Summary: Ensuring sustainable levels of rice yield is an important concern. To improve rice production, it is essential to increase factor inputs and productivity. This study utilizes the DEA-Malmquist index to analyze rice productivity and its determinants in China, finding that overall efficiency has fluctuated upward with technological progress being the primary driver. Distribution patterns reveal lower efficiency from east to west, influenced by resource endowment, production conditions, socioeconomic development, and political systems. The study offers ideas for structural adjustments and regional divisions in China's rice industry, providing a theoretical foundation for evidence-based policies.
Article
Green & Sustainable Science & Technology
Ying Ye, Shiping Yan, Shaoying Zhu
Summary: The TFP in the Pan-PRD region shows uneven development in terms of time, space, industry, and city dimensions, especially in the uneven development of city TFP. It is necessary to accelerate regional collaborative innovation, cultivate advantageous industrial clusters, create an advantageous industrial ecosystem, and achieve sustainable development in the Pan-PRD region.
Article
Green & Sustainable Science & Technology
Wuzhao Xue, Hua Li, Rizwan Ali, Ramiz Ur Rehman, Gonzalo Fernandez-Sanchez
Summary: This study evaluates the efficiency of scientific research output of universities under the Ministry of Education in China from 2010 to 2017 using a three-stage DEA model and the Malmquist index method. The results show an overall increase in efficiency, with scale optimization being the primary internal factor promoting efficiency and technological progress having a minimal impact.
Article
Biodiversity Conservation
Yufeng Chen, Rui Zhang, Jiafeng Miao
Summary: By using the meta-frontier super SBM model and the global Malmquist-Luenberger index, this paper explores the marine ecological efficiency and technology gaps among coastal regions in China. The findings reveal that China's coastal regions still have ineffective marine ecological efficiency, significant regional technological heterogeneity, and technological progress as the primary factor affecting marine ecological efficiency.
ECOLOGICAL INDICATORS
(2023)
Article
Green & Sustainable Science & Technology
Liting Gao, Qianhui Gao, Marcin Lorenc
Summary: Because rice is one of China's staple foods, studying the total factor productivity (TFP) of rice is of great importance for China's food security. This paper comparatively analyzes the production efficiency of the rice industry in China and Japan, and its trends and changes. The results show that rice TFP in Japan is higher than that in China, and technological progress is the main driver of the difference in rice TFP between the two countries.
Article
Economics
Wei Wei, Ying Han, Mohammad Zoynul Abedin, Jingjing Ma, Shanglei Chai
Summary: By using DEA-BCC and DEA-Malmquist models, this study examines the regional disparities of technical efficiency and total factor productivity in the Chinese power industry. The results indicate a development pattern of emphasizing market over environment, but some progress has been made in green technology and environmental regulations. However, the lack of long-term incentives hinders the continuous development of the power market reform.
Article
Energy & Fuels
Wasi Ul Hassan Shah, Gang Hao, Hong Yan, Rizwana Yasmeen, Yan Jie
Summary: Energy efficiency and emission reduction are important global concerns in the 21st century due to rapid economic and infrastructure growth. This study examines the energy efficiency of Chinese provinces and finds that there has been progress in the transition from energy security policy to energy efficiency with emission reduction policy. However, more efforts are needed to achieve the energy efficiency targets, especially in the central and western regions where there is a significant technological gap compared to the eastern coastal region.
Article
Green & Sustainable Science & Technology
Guangdi Zhang, Yaojun Ye, Mengya Sun
Summary: The digital economy is a new economic form that has become a crucial driver of economic development in various countries. This study used a three-stage DEA model and the Malmquist index to quantify and analyze the efficiency of China's digital economy from 2013 to 2020, both statically and dynamically. The findings revealed significant improvements in scale efficiency, integrated technical efficiency, and pure technical efficiency after excluding external environmental factors, indicating the unique influence of these factors on the digital economy's efficiency. The efficiency of the digital economy varied across regions, with the eastern region performing the best and the central region the worst. Technological advancement was identified as the primary driver of the positive growth trend in the efficiency of the digital economy. Overall, there is ample room for growth in China's digital economy, and each province and city should leverage their own capabilities to accelerate digital construction.
Article
Mathematics
Fenfen Li, Bo Dai, Qifan Wu
Summary: This study proposes a method for resource management and optimization in the industrial sector of China, analyzing the total factor productivity changes and consistency of sustainable development. The results show poor performance of the system and pollution treatment process, while the industrial production process remains stable in ranking. System performance is closely related to regionalism.
Article
Geography
Maria Bonaventura Forleo, Vincenzo Giaccio, Luigi Mastronardi, Luca Romagnoli
Summary: The study found that there is much potential for improvement in the efficiency of diversified Italian farms, even considering the variability in efficiency scores among farms and over time. Factors such as farm location and size were found to be related to the efficiency performances of these farms. Additionally, technological change supported farm performances and addressed instances of low managerial efficiency during the investigated period.
JOURNAL OF RURAL STUDIES
(2021)
Article
Public, Environmental & Occupational Health
Zhiting Chen, Wenzhong Zhu, Hainuo Feng, Houwei Luo
Summary: COVID-19 has had a significant impact on the global business environment, corporations, and individuals. This article focuses on the social responsibility efficiency of 17 sample enterprises in the food industry in China and explores the impact of the pandemic on their CSR performance. The results indicate that COVID-19 has promoted the social responsibility efficiency of these enterprises, although most of them still fall below the industry average.
FRONTIERS IN PUBLIC HEALTH
(2022)
Article
Environmental Sciences
Murnira Othman, Mohd Talib Latif, Nor Diana Abdul Halim
Summary: Air pollutants have a significant impact on humans and the environment. This study analyzed the influence of air pollutant concentrations on the environmental performance of 15 states in Malaysia and found that air pollutants play a crucial role in achieving good environmental performance.
ENVIRONMENTAL RESEARCH LETTERS
(2023)
Review
Orthopedics
Limin Wu, Yifan Li, Haibo Si, Yi Zeng, Mingyang Li, Yuan Liu, Bin Shen
Summary: This study evaluated the efficacy of various radiofrequency ablation treatments for knee osteoarthritis and determined the optimal modality and treatment guidance. The results showed that radiofrequency ablation is effective in improving knee pain and function, with cooled bipolar radiofrequency ablation being the most effective modality.
ARTHROSCOPY-THE JOURNAL OF ARTHROSCOPIC AND RELATED SURGERY
(2022)
Article
Engineering, Multidisciplinary
Chaoqun Duan, Yifan Li, Huayan Pu, Jun Luo
Summary: A novel multi-attribute Bayesian control chart is proposed in this paper to predict failures of hidden-state systems by jointly considering two performance measures of system operation. The fault prediction scheme integrates system availability and cost objectives to monitor and predict impending risks using a computational algorithm developed in a semi-Markov decision process framework, demonstrating the effectiveness and superiority of the approach.
APPLIED MATHEMATICAL MODELLING
(2022)
Article
Nanoscience & Nanotechnology
Tao Zhang, Qian Cheng, Yifan Li, Zhiguo Hu, Jinbang Ma, Yixin Yao, Yuxuan Zhang, Yan Zuo, Qian Feng, Yachao Zhang, Hong Zhou, Jing Ning, Chunfu Zhang, Jincheng Zhang, Yue Hao
Summary: In this study, beta-Ga2O3 films were deposited on (-201) homo-substrates using MOCVD method. It was found that the Ga source flow rate significantly influenced the surface morphology, and a relatively flat surface was obtained with appropriate TEGa and O-2 flow rates. The substrate morphology can be greatly improved by cleaning and thermal annealing, which promotes the surface flatness of the epilayer. Insertion of a buffer layer and optimization of growth conditions also contribute to achieving a higher surface flatness.
SCRIPTA MATERIALIA
(2022)
Article
Materials Science, Multidisciplinary
Xue Liang Li, Shaozhuan Huang, Dong Yan, Jian Zhang, Daliang Fang, Yew Von Lim, Ye Wang, Tian Chen Li, Yifan Li, Lu Guo, Hui Ying Yang
Summary: In this study, a 3D lithiophilic rGO-Ag-S-CNT composite with interlayer-bridged structure was proposed to guide uniform and stable Li plating/stripping. The composite exhibited lower overpotential, higher Coulombic efficiency, and superior long cycling performance compared to other anode materials.
ENERGY & ENVIRONMENTAL MATERIALS
(2023)
Article
Chemistry, Multidisciplinary
Zhipeng Yu, Yifan Li, Vlad Martin-Diaconescu, Laura Simonelli, Jonathan Ruiz Esquius, Isilda Amorim, Ana Araujo, Lijian Meng, Joaquim Luis Faria, Lifeng Liu
Summary: This paper reports the fabrication of a self-supported nickel-iron phosphosulfide nanotube array electrode which exhibits outstanding activity and durability for hydrogen and oxygen evolution reactions. It also shows good catalytic performance for urea oxidation reaction and can efficiently catalyze urea-mediated alkaline-saline water electrolysis.
ADVANCED FUNCTIONAL MATERIALS
(2022)
Article
Neurosciences
Xin Tan, Jinjian Wu, Xiaomeng Ma, Shangyu Kang, Xiaomei Yue, Yawen Rao, Yifan Li, Haoming Huang, Yuna Chen, Wenjiao Lyu, Chunhong Qin, Mingrui Li, Yue Feng, Yi Liang, Shijun Qiu
Summary: This study utilized a convolutional neural network to construct a model for classifying T2DM patients into cognitive impairment and non-cognitive impairment groups based on T1-weighted structural MRI. The results showed that the model could accurately identify T2DM-related cognitive decline, providing clinicians with a tool for analyzing and predicting cognitive impairment in patients.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Engineering, Industrial
Yifan Li, Chunjie Wu, Wendong Li, Fugee Tsung
Summary: This article proposes a nonparametric CUSUM charting scheme to monitor passenger flow in urban rapid transit systems. By using a minimum distance criterion and kernel density estimation, this method is able to detect shifts of all sizes sensitively and performs well in practical applications.
Article
Ophthalmology
He-Yan Li, Qiong Yang, Li Dong, Rui-Heng Zhang, Wen-Da Zhou, Hao-Tian Wu, Yi-Fan Li, Wen-Bin Wei
Summary: This study examined the relationship between stroke and ocular diseases, including visual impairment, and found significant associations between visual impairment and major ocular diseases with stroke. The associations were particularly strong for mild visual impairment, moderate/severe visual impairment, and any ocular disease.
Article
Engineering, Electrical & Electronic
Yuequan Wang, Xiaolin Zhou, Yaoyang Wu, Han Wang, Yifan Li, Pengfei Tian, Sirui Xiu
Summary: This paper proposes an iterative photon counting nonorthogonal multiple access-multiple-input-multiple-output (NOMA-MIMO) system based on optical intelligent reflecting surface (IRS). The channel fading coefficient matrix of the NOMA-MIMO system is constructed by analyzing the geometric and misalignment losses under turbulence effect in the optical IRS-based atmospheric channel. A novel iterative parallel interference cancellation algorithm based on logarithmic likelihood ratio is developed for signal detection at the receiver. The reliability of the proposed system is proved through simulation of bit error rate (BER), with a BER performance of 2 x 10-5 at -165 dBJ per bit for the scenario of 3x5 MIMO system. Additionally, the numerical results indicate that the proposed system has a rapid convergence performance in the external information transfer process.
MICROWAVE AND OPTICAL TECHNOLOGY LETTERS
(2023)
Article
Clinical Neurology
Haoming Huang, Xiaomeng Ma, Xiaomei Yue, Shangyu Kang, Yifan Li, Yawen Rao, Yue Feng, Jinjian Wu, Wenjie Long, Yuna Chen, Wenjiao Lyu, Xin Tan, Shijun Qiu
Summary: The white matter of the brain in patients with type 2 diabetes mellitus is susceptible to neurodegenerative processes, resulting in microstructural lesions. Specifically, abnormalities were found in specific portions of the right superior longitudinal fasciculus, right arcuate fasciculus, left anterior thalamic radiation, and forceps major. These abnormalities may be associated with insulin and glucose status as well as blood pressure.
CLINICAL NEURORADIOLOGY
(2023)
Article
Behavioral Sciences
Haoming Huang, Xiaomeng Ma, Xiaomei Yue, Shangyu Kang, Yawen Rao, Wenjie Long, Yi Liang, Yifan Li, Yuna Chen, Wenjiao Lyu, Jinjian Wu, Xin Tan, Shijun Qiu
Summary: This study used diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI) to investigate the microstructural alterations in the gray matter (GM) of type 2 diabetes mellitus (T2DM) patients. The results showed widespread GM neuritic density loss in T2DM patients, which occurred before measurable macrostructural alterations. The cortical intracellular volume fraction (ICVF) values provided valuable diagnostic information regarding the early GM microstructural alterations in T2DM. The support vector machine model achieved a high accuracy of 74% in classifying T2DM versus healthy controls (HCs).
BRAIN AND BEHAVIOR
(2022)
Article
Chemistry, Multidisciplinary
Ruru Chen, Jian Zhao, Yifan Li, Yi Cui, Ying-Rui Lu, Sung-Fu Hung, Shifu Wang, Weijue Wang, Guodong Huo, Yang Zhao, Wei Liu, Junhu Wang, Hai Xiao, Xuning Li, Yanqiang Huang, Bin Liu
Summary: By using experimental and theoretical methods, the metastable state of single-atom Sn in copper oxide was tracked and identified, providing a theoretical basis for the highly selective CO2 electroreduction to CO.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Chemistry, Multidisciplinary
Shunqin Luo, Hui Song, Fumihiko Ichihara, Mitsutake Oshikiri, Wenning Lu, Dai-Ming Tang, Sijie Li, Yunxiang Li, Yifan Li, Philo Davin, Tetsuya Kako, Huiwen Lin, Jinhua Ye
Summary: In this study, a light activation strategy was demonstrated to regulate the dynamic restructuring of Cu active sites in a TiO2-supported Cu catalyst during low-temperature methanol steam reforming. The thermally deactivated Cu/TiO2 underwent structural restoration from Cu2O to metallic Cu under illumination, leading to significantly enhanced activity and stability. The optimized Cu/TiO2 exhibited a high H-2 production rate under low-intensity solar irradiation, outperforming conventional photocatalytic and thermocatalytic processes. The results suggest the feasibility of real-time functionalization of catalysts through the strong light-matter-reactant interaction.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Chemistry, Multidisciplinary
Ruru Chen, Jian Zhao, Yifan Li, Yi Cui, Ying-Rui Lu, Sung-Fu Hung, Shifu Wang, Weijue Wang, Guodong Huo, Yang Zhao, Wei Liu, Junhu Wang, Hai Xiao, Xuning Li, Yanqiang Huang, Bin Liu
Summary: By using experimental and theoretical approaches, this study successfully tracked and identified the metastable state of single-atom Sn in copper oxide, providing fundamental insights for the highly selective electroreduction of CO2 to produce CO.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY
(2023)
Article
Computer Science, Artificial Intelligence
Likun Xia, Yuan Feng, Ziheng Guo, Jinhong Ding, Yanlei Li, Yifan Li, Ming Ma, Guoxi Gan, Yehan Xu, Jingyu Luo, Zhiping Shi, Yong Guan
Summary: This study proposes an early detection framework based on EEG data for reducing the risk of mental stress-related diseases. The framework, called MuLHiTA, utilizes a multibranch LSTM and hierarchical temporal attention approach to effectively identify mental stress levels. Experimental results demonstrate that MuLHiTA outperforms state-of-the-art algorithms, showcasing its viability for early detection of mental stress.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
