The pmrA gene, a yeast PMR1 homologue, was isolated from Aspergillus niger. Sequence analysis of the pmrA cDNA and the genomic DNA revealed that two introns exist in the coding region, and that an open reading frame in the cDNA encodes a polypeptide of 1056 amino acids containing all the conserved regions present in P-type Ca2+-ATPases. The predicted pmrA protein exhibited a high degree of sequence similarity to the Pmr1 proteins from yeasts and mammalians (50-59% identity). The expression of the pmrA cDNA partially restored the growth defect of Yarrowia lipolytica pmr1 null mutant on EGTA-containing medium. This indicates that the A. niger pmrA gene encodes a functional homologue of the yeast P-type Ca2+-ATPase involved in the secretory pathway. An A. niger pmrA null mutant exhibited growth retardation on EGTA-containing medium and the growth defect was overcome by adding Ca2+ or Mn2+ into the medium. This suggests an involvement of the pmrA protein in Ca2+ and Mn2+ homeostasis in A. niger.
In autonomous driving, using a variety of sensors to recognize preceding vehicles at middle and long distances is helpful for improving driving performance and developing various functions. However, if only LiDAR or cameras are used in the recognition stage, it is difficult to obtain the necessary data due to the limitations of each sensor. In this paper, we proposed a method of converting the vision-tracked data into bird’s eye-view (BEV) coordinates using an equation that projects LiDAR points onto an image and a method of fusion between LiDAR and vision-tracked data. Thus, the proposed method was effective through the results of detecting the closest in-path vehicle (CIPV) in various situations. In addition, even when experimenting with the EuroNCAP autonomous emergency braking (AEB) test protocol using the result of fusion, AEB performance was improved through improved cognitive performance than when using only LiDAR. In the experimental results, the performance of the proposed method was proven through actual vehicle tests in various scenarios. Consequently, it was convincing that the proposed sensor fusion method significantly improved the adaptive cruise control (ACC) function in autonomous maneuvering. We expect that this improvement in perception performance will contribute to improving the overall stability of ACC.
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