This study aims to explore the relationships between electricity consumption and per capita GDP, urbanization rate, and the proportion of tertiary industry in China during 2005-2018. The results demonstrate that electricity consumption and its determinants are cointegrated. Then fully modified ordinary least square (FMOLS) and fixed effect with varying coefficients and intercept techniques are used to explore the relationships. The empirical results show that all three factors positively affect electricity consumption, per capita GDP has exerted positive impacts on electricity consumption in the 28 provinces, urbanization rate also contributes a positive influence on electricity consumption in 29 provinces, while the positive effect of the proportion of tertiary industry emerges only in 10 provinces. Meanwhile, the urbanization rate makes the most considerable contribution to electricity consumption, while the proportion of the tertiary industry is the least essential determinant. The panel causality results reveal that per capita GDP and urbanization rate cause electricity consumption in the short run and per capita GDP and electricity consumption Granger cause each other in the long run. Finally, we propose policy implications including enhancing the security and reliability of power supply and optimizing the structure of electricity consumption in different industries in China.
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http://dx.doi.org/10.1007/s11356-021-16261-8 | DOI Listing |
Sci Rep
December 2024
Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, 55905, USA.
Alcohol use disorder (AUD) is a chronic relapsing brain disorder characterized by an impaired ability to stop or control alcohol consumption despite adverse social, occupational, or health consequences. AUD affects nearly one-third of adults at some point during their lives, with an associated cost of approximately $249 billion annually in the U.S.
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December 2024
Information Construction and Management Center, Nanyang Institute of Technology, Nanyang, 473004, Henan, China.
Given the increasingly severe environmental challenges, distributed green manufacturing has garnered significant academic and industrial interest. This paper addresses the distributed two-stage flexible job shop scheduling problem (DTFJSP) under time-of-use (TOU) electricity pricing, with the objective of minimizing both makespan and total energy consumption costs (TEC). To tackle the problem, a hybrid memetic algorithm (HMA) is proposed.
View Article and Find Full Text PDFNanomaterials (Basel)
December 2024
State Key Laboratory of Wide Bandgap Semiconductor Devices and Integrated Technology, National Engineering Research Center of Wide Band-Gap Semiconductor, School of Microelectronics, Xidian University, Xi'an 710071, China.
This study systematically investigates the effects of anode metals (Ti/Au and Ni/Au) with different work functions on the electrical and temperature characteristics of β-GaO-based Schottky barrier diodes (SBDs), junction barrier Schottky diodes (JBSDs) and P-N diodes (PNDs), utilizing Silvaco TCAD simulation software, device fabrication and comparative analysis. From the perspective of transport characteristics, it is observed that the SBD exhibits a lower turn-on voltage and a higher current density. Notably, the V of the Ti/Au anode SBD is merely 0.
View Article and Find Full Text PDFJ Funct Morphol Kinesiol
November 2024
Department of Kinesiology, University of Georgia, Athens, GA 30602, USA.
: Previous studies have shown that neuromuscular electrical stimulation (NMES), while expensive, can provide some of the health benefits of exercise to people who cannot exercise their legs normally. The aim of this study was to quantify the increases in muscle metabolism in four muscles of the legs of able-bodied individuals with NMES. : Healthy college-aged students were tested.
View Article and Find Full Text PDFJ Imaging
November 2024
Engineering Sciences Laboratory, National School of Applied Sciences of Kenitra, Ibn Tofail University, Kenitra 14000, Morocco.
The evolution of maritime surveillance is significantly marked by the incorporation of Artificial Intelligence and machine learning into Unmanned Surface Vehicles (USVs). This paper presents an AI approach for detecting and tracking unmanned surface vehicles, specifically leveraging an enhanced version of YOLOv8, fine-tuned for maritime surveillance needs. Deployed on the NVIDIA Jetson TX2 platform, the system features an innovative architecture and perception module optimized for real-time operations and energy efficiency.
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