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We present a satellite attitude control system design using low-cost hardware and software for a 1U CubeSat. The attitude control system architecture is a crucial subsystem for any satellite mission since precise pointing is often required to meet mission objectives. The accuracy and precision requirements are even more challenging for small satellites where limited volume, mass, and power are available for the attitude control system hardware. In this proposed embedded attitude control system design for a 1U CubeSat, pointing is obtained through a two-stage approach involving coarse and fine control modes. Fine control is achieved through the use of three reaction wheels or three magnetorquers and one reaction wheel along the pitch axis. Significant design work has been conducted to realize the proposed architecture. In this paper, we present an overview of the embedded attitude control system design; the verification results from numerical simulation studies to demonstrate the performance of a CubeSat-class nanosatellite; and a series of air-bearing verification tests on nanosatellite attitude control system hardware that compares the performance of the proposed nonlinear controller with a proportional-integral-derivative controller.

Background:This study aimed to identify key genes associated with acute myocardial infarction (AMI) by reanalyzing microarray data.Methods:Three gene expression profile datasets GSE66360, GSE34198, and GSE48060 were downloaded from GEO database. After data preprocessing, genes without heterogeneity across different platforms were subjected to differential expression analysis between the AMI group and the control group using metaDE package. P < .05 was used as the cutoff for a differentially expressed gene (DEG). The expression data matrices of DEGs were imported in ReactomeFIViz to construct a gene functional interaction (FI) network. Then, DEGs in each module were subjected to pathway enrichment analysis using DAVID. MiRNAs and transcription factors predicted to regulate target DEGs were identified. Quantitative real-time polymerase chain reaction (RT-PCR) was applied to verify the expression of genes.Result:A total of 913 upregulated genes and 1060 downregulated genes were identified in the AMI group. A FI network consists of 21 modules and DEGs in 12 modules were significantly enriched in pathways. The transcription factor-miRNA-gene network contains 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p. RT-PCR validations showed that expression levels of FOXO3 and MYBL2 were significantly increased in AMI, and expression levels of hsa-miR-21–5p and hsa-miR-30c-5p were obviously decreased in AMI.Conclusion:A total of 41 DEGs, such as SOCS3, VAPA, and COL5A2, are speculated to have roles in the pathogenesis of AMI; 2 transcription factors FOXO3 and MYBL2, and 2 miRNAs hsa-miR-21-5p and hsa-miR-30c-5p may be involved in the regulation of the expression of these DEGs.