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INTRODUCTION: Photovoltaic power generation, as a rapidly developing new energy technology, is increasingly receiving attention from countries around the world. However, the efficiency of photovoltaic power generation systems is influenced by various factors. Local shadows have become one of the bottlenecks restricting the development of photovoltaic systems. OBJECTIVES: The research aims to improve the maximum power tracking performance of photovoltaic systems under local shadow conditions. METHODS: A maximum power tracking system based on ant colony optimization fuzzy algorithm is proposed. Research can effectively solve local optimal problems caused by local shadows through ant colony algorithm. Combining fuzzy algorithms can not only improve the tracking accuracy of the maximum power tracking system, but also enhance the adaptability to complex environments. RESULTS: In the simulation experiment results, the error between the ant colony optimization fuzzy algorithm and the actual maximum power in four local shadow environments was 0.21W, 0.55W, 0.27W, and 0.98W, respectively. Both stability and accuracy were superior to ant colony algorithm, fuzzy algorithm, and perturbation observation method. CONCLUSION: Research has confirmed the potential value of ant colony optimization fuzzy algorithm in maximum power tracking of photovoltaic power generation, providing a new solution for the operation and management of photovoltaic power plants.

How to extract discriminative features from redundant video information is a key issue for video pedestrian re-identification. Factors such as occlusion, perspective, and posture changes in complex environments pose severe challenges to pedestrian re-identification based on local methods. In this paper, a posture-guided multi-scale structural relationship learning pedestrian re-identification method is proposed. The purpose is to analyze the video sequence of pedestrians based on the reference pose and the pose alignment model, and extract the sample frame with the highest image quality and the most complete spatial information in the reference pose. The method based on posture guidance can more accurately eliminate the interference of background, occlusion and perspective factors. To further explore the potential relationship between local regions, this paper calculates the relationship matrix between the local regions based on the relationship model to further calculate the relationship weight, and the graph convolutional network based on the relationship weight learns the structural relationship feature of multi-scale regions. The input of the graph convolutional network is a local region divided by a multi-scale method, and the output is a pose-guided multi-scale structural relationship feature. The experimental results on three public datasets show that the proposed method performs favorably against state-of-the-art methods.

When a large amount of heat is produced during the operation of a MRF (magnetorheological fluid) testing device, the temperature of the device will increase, which will in turn affect the characteristics of the MRF. Exploring the temperature field characteristics of the MRF yield stress testing device is necessary to improve the accuracy of the device. In this study, first, the yield stress testing device is designed, and then its temperature field model, including enameled wire and assembly gap, is established. Second, simulation software is used to simulate the temperature field change. Finally, a test platform is developed to test the simulation results, especially for two factors, namely, thermal conductivity of the coil winding and assembly gap, which demonstrate considerable influence. Comprehensive thermal conductivity and assembly clearance are determined, and the optimum temperature field of the device for measuring yield stress is resulted.

Magnetorheological fluids (MRFs) have a wide range of applications in automotive and other industrial fields. As one of the main performance parameters of MRFs, static yield stress is the demarcation point of solid-liquid performance conversion. Therefore, yield stress is important to the study of MRFs. In this work, a new type of MRF testing device was designed. Three types of material blocks, namely, steel, copper, and aluminum, were tested to determine wall slippage using MRF-122E and MRF-132D. The results indicate that the best pulling blocks were the 1-mm copper rectangular channel and the 2-mm aluminum triangle channel. Identity distance was also tested, and the result indicated that the 1-mm copper pulling block and identity distance of 5-mm curve were nearest to the Lord Corporation yield curve with a maximum relative error within 5 %. [ABSTRACT FROM AUTHOR]

Background The right to health of children has been a general concern of the society. The rate of systematic health management for children is a core indicator effectively reflecting the monitoring and management of children's physical growth and psycho-behavioral development. Most of the studies on systematic health management for children use an empirical design, mainly focusing on explorations of management models, while few have made in-depth analysis of the national status from temporal and geographical perspectives. Objective To analyze the temporal changes and regional differences in terms of the rate of systematic health management of children under three years old from 2010 to 2019, providing valuable evidence for the consolidation and improvement of the health management level in this group, and for promoting health level in children. Methods In November 2021, data about health management of children under three years old in China during 2011—2020 were extracted from 10 volumes of China Health Statistics Yearbook published annually from 2011 to 2020. A descriptive analysis was used to conduct temporal and geographical analysis of the systematic health management for children. Results As a whole, the national health management rate for children under three years old showed a continuous upward trend increased from 81.5% in 2010 to 91.9% in 2019, with a 12.8% increase. The annual rate of systematic health management of the children during the period was greater than 90.0% in Beijing, Inner Mongolia Autonomous Region, Liaoning Province, Shanghai, Jiangsu Province, Zhejiang Province, Shandong Province, Guangdong Province and Shaanxi Province, but was relatively low in the Tibet Autonomous Region (71.9% in 2019) , indicating that there was still a certain gap between the local level and policy goals in this region. The analysis from temporal changes and regional differences as well as regional perspective revealed the following findings: the rate of systematic health management for children under three years during 2010—2019 was higher than the national level in 13 (41.9%) out of 31 regions in China, lower than the national level in 7 regions (22.6%) , and moved around the national level in 11 regions (35.5%) . The systematic health management rate of children under 3 years old varied greatly between regions during 2010—2012, but the inter-regional differences gradually narrowed after 2015. The rate of systematic health management for children under 3 years old was the highest in northeast China, followed by eastern China, western China and central China. In 2019, there was still large differences in the rate of systematic health management for these children among regions in western China. Conclusion China has achieved remarkable results in systematic health management for children under 3 years old. More attention should be given to the regions in western China, especially the Tibet Autonomous Region during the improvement of the management for these children. To further improve and consolidate the health management level of children, it is suggested to make efforts to improve the equity and accessibility of essential medical services, narrow the inter-regional differences between health resource allocation and public health services, learn and apply relevant good management methods from advanced regions, make full use of big data and internet techniques, and strengthen the construction of community pediatric health management team.