Reduction of satellite flywheel microvibration using rubber shock absorbers

Microvibration of flywheels strongly affects the imaging quality of space cameras. A passive vibration method is used in this study to reduce the effect of microvibration. A rubber shock absorber was designed and installed on a satellite. The angular displacement of the second mirror was measured via a fiber optic gyroscopic method. The measured data were imported into MATLAB and analyzed by different methods. The data was plotted as a root-mean-square graph of angular displacement at different speeds along the x-axis, a waterfall plot of the attenuation of force in the x direction, the vibration spectrum between the frequency and displacement amplitude, and the time domain response of the inverse Fourier transform of the spectrum. The results show that the microvibration of the flywheel causes significant vibration of the imaging system, and that adding a rubber shock absorber can reduce the vibration. The proposed method is a new attempt to analyze microvibration, and can be applied to the engineering design of flywheels

Reduction of satellite flywheel microvibration using rubber shock absorbers

Microvibration of flywheels strongly affects the imaging quality of space cameras. A passive vibration method is used in this study to reduce the effect of microvibration. A rubber shock absorber was designed and installed on a satellite. The angular displacement of the second mirror was measured via a fiber optic gyroscopic method. The measured data were imported into MATLAB and analyzed by different methods. The data was plotted as a root-mean-square graph of angular displacement at different speeds along the x-axis, a waterfall plot of the attenuation of force in the x direction, the vibration spectrum between the frequency and displacement amplitude, and the time domain response of the inverse Fourier transform of the spectrum. The results show that the microvibration of the flywheel causes significant vibration of the imaging system, and that adding a rubber shock absorber can reduce the vibration. The proposed method is a new attempt to analyze microvibration, and can be applied to the engineering design of flywheels

Research on the Spatial Distribution Pattern and Influencing Factors of China’s Antipoverty (Pro-Poor Tourism) on GIS

Eliminating poverty is the common mission of all mankind, and it is also an important task faced by many countries. Pro-poor tourism villages are an active attempt by China to use rural tourism to escape poverty. This paper aims to provide theoretical support for consolidating the results of poverty alleviation and achieving comprehensive poverty alleviation and to provide a scientific basis for policy formulation by using GIS spatial analysis to study the spatial distribution characteristics and influencing factors of 22,651 pro-poor tourism villages in China. The findings revealed that the spatial distribution of pro-poor tourism villages is roughly divided by the Hu line. Pro-poor tourism villages show an uneven agglomeration pattern and present a spatial pattern of dense southeast and sparse northwest with six high-density core areas, among which some cities in the southwest are H-H agglomeration areas. Specifically, topography, annual rainfall, endowment of tourism resources, location transportation, and policy orientation are important factors affecting the spatial distribution of pro-poor tourism villages

Ground infrastructure monitoring in coastal areas using time-series inSAR technology: the case study of Pudong International Airport, Shanghai

Shanghai Pudong International Airport (PDIA), with its east side built along the coast with weak geological conditions, is prone to uneven foundation settlement due to the consolidation and compression of soil and erosion of coastal tides, affecting the safe operation of the airport. Therefore, it is crucial to conduct dynamic subsidence monitoring within the airport, especially in the runway area. 29 scenes of ascending track Sentinel-1A radar images from August 2016 to June 2018 are selected to perform surface deformation inversion based on PS-InSAR and improved SBAS-InSAR for PDIA and its around coastal area. Through cross-validation, the reliability of the time-series InSAR technique for dynamic monitoring of surface deformation of coastal zone infrastructures is confirmed. The results show severely uneven settlement. By combining the monitoring results with the local geological and hydrological dataset, the driving factors of differential deformation of the infrastructures are analyzed, including stratigraphic geological conditions, ground loadings, foundation treatment methods, water erosion, and groundwater level changes. Finally, the time-series deformation characteristics and the causes of PDIA's runway are emphasized based on the PS deformation results. This case provides a reference for the safety management of critical infrastructure in coastal areas using advanced InSAR technique

Deep Reinforcement Learning-Based Joint Optimization Control of Indoor Temperature and Relative Humidity in Office Buildings

Indoor temperature and relative humidity control in office buildings is crucial, which can affect thermal comfort, work efficiency, and even health of the occupants. In China, fan coil units (FCUs) are widely used as air-conditioning equipment in office buildings. Currently, conventional FCU control methods often ignore the impact of indoor relative humidity on building occupants by focusing only on indoor temperature as a single control object. This study used FCUs with a fresh-air system in an office building in Beijing as the research object and proposed a deep reinforcement learning (RL) control algorithm to adjust the air supply volume for the FCUs. To improve the joint control satisfaction rate of indoor temperature and relative humidity, the proposed RL algorithm adopted the deep Q-network algorithm. To train the RL algorithm, a detailed simulation environment model was established in the Transient System Simulation Tool (TRNSYS), including a building model and FCUs with a fresh-air system model. The simulation environment model can interact with the RL agent in real time through a self-developed TRNSYS–Python co-simulation platform. The RL algorithm was trained, tested, and evaluated based on the simulation environment model. The results indicate that compared with the traditional on/off and rule-based controllers, the RL algorithm proposed in this study can increase the joint control satisfaction rate of indoor temperature and relative humidity by 12.66% and 9.5%, respectively. This study provides preliminary direction for a deep reinforcement learning control strategy for indoor temperature and relative humidity in office building heating, ventilation, and air-conditioning (HVAC) systems

Identification of dysregulated genes in rheumatoid arthritis based on bioinformatics analysis

Background Rheumatoid arthritis (RA) is a chronic auto-inflammatory disorder of joints. The present study aimed to identify the key genes in RA for better understanding the underlying mechanisms of RA. Methods The integrated analysis of expression profiling was conducted to identify differentially expressed genes (DEGs) in RA. Moreover, functional annotation, protein–protein interaction (PPI) network and transcription factor (TF) regulatory network construction were applied for exploring the potential biological roles of DEGs in RA. In addition, the expression level of identified candidate DEGs was preliminarily detected in peripheral blood cells of RA patients in the GSE17755 dataset. Quantitative real-time polymerase chain reaction (qRT-PCR) was conducted to validate the expression levels of identified DEGs in RA. Results A total of 378 DEGs, including 202 up- and 176 down-regulated genes, were identified in synovial tissues of RA patients compared with healthy controls. DEGs were significantly enriched in axon guidance, RNA transport and MAPK signaling pathway. RBFOX2, LCK and SERBP1 were the hub proteins in the PPI network. In the TF-target gene network, RBFOX2, POU6F1, WIPF1 and PFKFB3 had the high connectivity with TFs. The expression status of 11 candidate DEGs was detected in GSE17755, the expression levels of MAT2A and NSA2 were significantly down-regulated and CD47 had the up-regulated tendency in peripheral blood cells of patients with RA compared with healthy individuals. qRT-PCR results of MAT2A, NSA2, CD47 were compatible with our bioinformatics analyses. Discussion Our study might provide valuable information for exploring the pathogenesis mechanism of RA and identifying the potential biomarkers for RA diagnosis