Data Matrix(DM)codes have been widely used in industrial production.The reading of DM code usually includes positioning and decoding.Accurate positioning is a prerequisite for successful decoding.Traditional image pro...Data Matrix(DM)codes have been widely used in industrial production.The reading of DM code usually includes positioning and decoding.Accurate positioning is a prerequisite for successful decoding.Traditional image processing methods have poor adaptability to pollution and complex backgrounds.Although deep learning-based methods can automatically extract features,the bounding boxes cannot entirely fit the contour of the code.Further image processing methods are required for precise positioning,which will reduce efficiency.Because of the above problems,a CenterNet-based DM code key point detection network is proposed,which can directly obtain the four key points of the DM code.Compared with the existing methods,the degree of fitness is higher,which is conducive to direct decoding.To further improve the positioning accuracy,an enhanced loss function is designed,including DM code key point heatmap loss,standard DM code projection loss,and polygon Intersection-over-Union(IoU)loss,which is beneficial for the network to learn the spatial geometric characteristics of DM code.The experiment is carried out on the self-made DM code key point detection dataset,including pollution,complex background,small objects,etc.,which uses the Average Precision(AP)of the common object detection metric as the evaluation metric.AP reaches 95.80%,and Frames Per Second(FPS)gets 88.12 on the test set of the proposed dataset,which can achieve real-time performance in practical applications.展开更多
非编码RNA(non-coding RNA,ncRNA)为一类不编码蛋白的RNA分子,是机体重要的生物调控因子,在转录及转录后水平调控基因表达,影响糖尿病血管病变的发展过程。ncRNA按其片段大小主要分为微RNA(microRNA,miRNA)、长链非编码RNA(long non cod...非编码RNA(non-coding RNA,ncRNA)为一类不编码蛋白的RNA分子,是机体重要的生物调控因子,在转录及转录后水平调控基因表达,影响糖尿病血管病变的发展过程。ncRNA按其片段大小主要分为微RNA(microRNA,miRNA)、长链非编码RNA(long non coding RNA,lncRNA)及环状RNA(circular RNA,circRNA)。miRNA可在转录后水平调控靶基因表达,并有成为临床诊断标志物的潜能。lncRNA影响多种分子信号通路,其在糖尿病血管病变中的作用逐渐受到关注。circRNA具有显著的基因调节功能,可与miRNA竞争结合位点,参与调控糖尿病血管病变。该文回顾目前有关ncRNA与糖尿病血管病变的研究,探讨ncRNA与糖尿病微血管及大血管病变间的关系,为糖尿病血管病变的诊断和治疗提供新思路。展开更多
We investigate the joint effects of phase decoherence, Dzyaloshinskii Moriya （DM） interaction and inhomogeneity of the external magnetic field （b） on dense coding in a two-qubit anisotropic Heisenberg XYZ spin cha...We investigate the joint effects of phase decoherence, Dzyaloshinskii Moriya （DM） interaction and inhomogeneity of the external magnetic field （b） on dense coding in a two-qubit anisotropic Heisenberg XYZ spin chain. Analytical expressions are obtained for the dense coding capacity. It is found that valid dense coding is always possible with this model when the system is initially prepared in the maximum entangled state. Moreover, optimal dense coding can be implemented for this initial state as long as the mean spin-spin coupling constant J＋ of the XY plane is larger than b and the DM interaction despite the intrinsic decoherence. Non-maximal entangled initial states are found to be undesirable for dense coding with this model.展开更多
基金funded by the Youth Project of National Natural Science Foundation of China(52002031)the General Project of Shaanxi Province Science and Technology Development Planned Project(2023-JC-YB-600)+1 种基金Postgraduate Education and Teaching Research University-Level Project of Central University Project(300103131033)the Transportation Research Project of Shaanxi Transport Department(23-108 K).
文摘Data Matrix(DM)codes have been widely used in industrial production.The reading of DM code usually includes positioning and decoding.Accurate positioning is a prerequisite for successful decoding.Traditional image processing methods have poor adaptability to pollution and complex backgrounds.Although deep learning-based methods can automatically extract features,the bounding boxes cannot entirely fit the contour of the code.Further image processing methods are required for precise positioning,which will reduce efficiency.Because of the above problems,a CenterNet-based DM code key point detection network is proposed,which can directly obtain the four key points of the DM code.Compared with the existing methods,the degree of fitness is higher,which is conducive to direct decoding.To further improve the positioning accuracy,an enhanced loss function is designed,including DM code key point heatmap loss,standard DM code projection loss,and polygon Intersection-over-Union(IoU)loss,which is beneficial for the network to learn the spatial geometric characteristics of DM code.The experiment is carried out on the self-made DM code key point detection dataset,including pollution,complex background,small objects,etc.,which uses the Average Precision(AP)of the common object detection metric as the evaluation metric.AP reaches 95.80%,and Frames Per Second(FPS)gets 88.12 on the test set of the proposed dataset,which can achieve real-time performance in practical applications.
基金Project supported by the National Natural Science Foundation of China (Grant No. 10064004)the Priority Subjects Program for Theoretical Physics of Xinjiang Normal University (XJNU),Chinathe Science and Technology Innovative Foundation for Graduate Students of XJNU,China (Grant No. 20101203)
文摘We investigate the joint effects of phase decoherence, Dzyaloshinskii Moriya （DM） interaction and inhomogeneity of the external magnetic field （b） on dense coding in a two-qubit anisotropic Heisenberg XYZ spin chain. Analytical expressions are obtained for the dense coding capacity. It is found that valid dense coding is always possible with this model when the system is initially prepared in the maximum entangled state. Moreover, optimal dense coding can be implemented for this initial state as long as the mean spin-spin coupling constant J＋ of the XY plane is larger than b and the DM interaction despite the intrinsic decoherence. Non-maximal entangled initial states are found to be undesirable for dense coding with this model.
