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According to the National New Urbanization Plan (2014), China's national urbanization rate will reach approximately 60% in 2020. Throughout the rapid process of urbanization, China's energy consumption will expand at an unprecedented rate. In 2012, total energy consumption in China was 3 . 411 × 10 9 tons of coal equivalent (tce); energy shortage is becoming increasingly serious. In this study, two future urbanization scenarios in China were simulated based on linear and logistic growth models. These models were used to quantitatively predict the long-term (2020–2030) energy consumption of urban and rural residents in three economic sectors: transport, construction, and residential. The annual area of newly paved roads in Chinese cities was positively correlated with energy consumption by the transport sector, and the annual increase in newly built floor space in buildings was positive correlated with energy consumption by the construction sector. If the urbanization level of China is in accordance with the new urbanization plan (the logistic growth model), which proposes a lower urbanization speed, the energy consumption growth by the three sectors will be significantly reduced compared with the linear growth model. Energy consumption growth by the transport, construction, and residential sectors will decrease by 7 . 26 × 10 7 tce, 1 . 28 × 10 7 tce, and 5 . 45 × 10 6 tce by 2020. [ABSTRACT FROM AUTHOR]

Managing over-temperature alarms in cold chain logistics (CCL) is crucial for temperature monitoring systems. However, existing research in this area primarily focuses on improving identification accuracy while overlooking the associated cost implications. This study addresses this gap by proposing a cost-effective over-temperature alarm system using an artificial neural network (ANN) model that integrates multi-source data (MSD). This article demonstrates that utilizing ANN and MSD leads to significantly improved recognition accuracy compared to using single-source data while keeping the cost increase to a minimum. The paper found recognition accuracy to be 97.4% with three feature values and 98.6% with six feature values. Sensitivity analyses reveal that factors such as the initial food temperature, cumulative open time, data acquisition interval, and algorithm significantly impact the recognition accuracy of the over-temperature alarm system. The location of sensors, however, has a slight effect. Furthermore, the choice of the number of feature values and the granularity of the data influences the cost of temperature management and recognition accuracy. This study provides valuable insights into the factors influencing recognition accuracy, aiding in designing cost-effective over-temperature alarm systems for food supply chain management. [Display omitted] • A cost-effective over-temperature alert system is developed utilizing artificial neural networks. • The model achieves over 98% accuracy in cold chain logistics unstable environmental temperatures. • By selecting algorithms and features, the system can reduce sensor quantity while maintaining accuracy. [ABSTRACT FROM AUTHOR]

The goal of the work is to investigate the lubrication mechanism of MoS 2 nano sheet. Polyisobutyleneamine Succinimide (PIBS) provides the steric repulsion to disperse nanoparticles in oil due to its long carbon chain. In the present study, the tribological behavior of nano-MoS 2 sheet mixed with different percentages of PIBS was explored. The dispersed state and the mode of nano-MoS 2 sheet entering the contact point were studied. Ball-on-disk results illustrated that the COF of nano-MoS 2 in paraffin oil with free of PIBS was 26.2% compared with those containing 3 wt% PIBS, and the reduction of wear depth reached 41.9%. The nano-MoS 2 sheets with 3 wt% PIBS were in discrete state in paraffin oil, which moved with side flow and could not enter the contact area to cause poor lubrication. Aggregation of particles took place in the case of low PIBS concentration and without PIBS, it entered the contact area and formed well-distributed MoS 2 tribofilm to reduce friction and wear. [ABSTRACT FROM AUTHOR]