Study of dynamic plastic buckling of cylindrical shell impacted by sudden constant load

  &nbsp

一种基于模糊成像机理的QR码图像快速盲复原方法.

A fast blind restoration method of QR code images was proposed based on a blurred imaging mechanism. On the basis of the research on the centroid invariance of the blurred imaging diffuse light spots, the circular finder pattern is designed. When the image is blurred, the centroid of the pattern and the position of the QR code symbol can be quickly detected by methods such as connected components. Moreover, combined with step edge characteristics, gradient and intensity characteristics, edge detection technology, and optical imaging mechanism, the defocus radius of the blurred QR code image can be quickly and accurately estimated. Furthermore, the Wiener filter is applied to restore the QR code image quickly and effectively. Compared with the other algorithms, the proposed method has improved deblurring results in both structural similarity and peak signal-to-noise ratio, especially in the recovery speed. The average recovery time is 0.329 2 s. Experimental results show that this method can estimate the defocus radius with high accuracy and can quickly realize the blind restoration of QR code images. It has the advantages of rapidity and robustness, which are convenient for embedded hardware implementation and suitable for barcode identification-related industrial Internet of Things application scenarios

STEM teaching for the Internet of Things maker course: a teaching model based on the iterative loop.

As the key technology for 5G applications in the future, the Internet of Things (IoT) is developing rapidly, and the demand for the cultivation of engineering talents in the IoT is also expanding. The rise of maker education has brought new teaching inspiration for cultivating innovative technical talents in the IoT. In the IoT maker course, teaching problems include the lack of adequate teaching models, emphasis on products but less emphasis on theory, and letting students imitate practice. Focusing on these problems, this paper proposes a new Science, Technology, Engineering, and Mathematics (STEM) teaching model called Propose, Guide, Design, Comment, Implement, Display and Evaluate (PGDCIDE) for the IoT maker course. The PGDCIDE teaching model is based on STEM teaching and Kolodner's design-based scientific inquiry learning cycle model, and realizes the combination of "theory, practice, and innovation." Finally, this paper designs the IoT maker course to practice the PGDCIDE model. The practical results indicate that students significantly improved their emotional level, knowledge level, and innovation level after studying the course. Therefore, the PGDCIDE teaching model proposed in this paper can improve the effectiveness of the IoT maker course teaching and is conducive to the cultivation of students' sustainable ability in engineering education. It has reference significance for the application of maker courses in engineering education practice

Fast restoration for out-of-focus blurred images of QR code with edge prior information via image sensing.

Out-of-focus blurring of the QR code is very common in mobile Internet systems, which often causes failure of authentication as a result of a misreading of the information hence adversely affects the operation of the system. To tackle this difficulty, this work firstly introduced an edge prior information, which is the average distance between the center point and the edge of the clear QR code images in the same batch. It is motivated by the theoretical analysis and the practical observation of the theory of CMOS image sensing, optics information, blur invariants, and the invariance of the center of the diffuse light spots. After obtaining the edge prior information, combining the iterative image and the center point of the binary image, the proposed method can accurately estimate the parameter of the out-of-focus blur kernel. Furthermore, we obtain the sharp image by Wiener filter, a non-blind image deblurring algorithm. By this, it avoids excessive redundant calculations. Experimental results validate that the proposed method has great practical utility in terms of deblurring quality, robustness, and computational efficiency, which is suitable for barcode application systems, e.g., warehouse, logistics, and automated production

Rewritable and sustainable 2D barcode for traceability application in smart IoT based fault-tolerant mechanism.

With the development of the Internet of Things (IoT) technology, two-dimensional (2D) barcodes are widely used in smart IoT applications as a perception portal. In industries with many circulations and testing links like traceability, since the existing 2D barcode cannot be changed once it is printed, it can only be replaced with more expensive radio frequency identification (RFID) labels or new 2D barcodes, causing a waste of human resources and costs. For better circulation efficiency and resource utilization, we propose a new design of the rewritable and sustainable 2D barcode based on the fault-tolerance mechanism. The ability to add new information in the 2D barcode can be achieved through data encryption and the insertion of a rewritable layer. It means the message of 2D barcodes could be changed, and increases the flexibility and liquidity of the 2D barcode application. Besides, the encoding and decoding method of the proposed 2D barcode is presented. Experimental results have illustrated the superiority of rewritable and sustainable 2D barcodes in the traceability of herbal medicine compared with the conventional 2D barcodes, and demonstrated the feasibility of the design. The findings show the potential for significant application in the field of traceability in smart IoT, as well as in the manufacturing industry and logistics

A novel molecular pathway of lipid accumulation in human hepatocytes caused by PFOA and PFOS

Exposed to ubiquitously perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) has been associated with non-alcoholic fatty liver disease (NAFLD), yet the underlying molecular mechanism remains elusive. The extrapolation of empirical studies correlating per- and polyfluoroalkyl substance (PFAS) exposure with NAFLD occurrence to real-life exposure was hindered by the limited availability of mechanistic data at environmentally relevant concentrations. Herein, a novel pathway mediating hepatocyte lipid accumulation by PFOA and PFOS at human-relevant dose (&lt;10 μM) was identified by integrating CRISPR-Cas9 genome screening, concentration-dependent transcriptional assay in HepG2 cell and epidemiological data mining. 1) At genetic level, nudt7 showed the highest enriched potency among 569 NAFLD-related genes, and the transcription of nudt7 was significantly downregulated by PFOA and PFOS exposure (&lt;7 μM). 2) At molecular pathway, upon exposure to ≤10-4 μM PFOA and PFOS, the downregulation of nudt7 transcriptional expression triggered the reduction of Ace-CoA hydrolase activity. 3) At cellular level, increased lipids were measured in HepG2 cells with PFOA and PFOS (&lt;2 μM). Overall, we identified a novel mechanism mediated by transcriptional downregulation of nudt7 gene in hepatocellular lipid increase treated with PFOA and PFOS, which could potentially explain the NAFLD occurrence associated with exposure to PFASs in humans.</p

TSegFormer: 3D Tooth Segmentation in Intraoral Scans with Geometry Guided Transformer

Optical Intraoral Scanners (IOS) are widely used in digital dentistry to provide detailed 3D information of dental crowns and the gingiva. Accurate 3D tooth segmentation in IOSs is critical for various dental applications, while previous methods are error-prone at complicated boundaries and exhibit unsatisfactory results across patients. In this paper, we propose TSegFormer which captures both local and global dependencies among different teeth and the gingiva in the IOS point clouds with a multi-task 3D transformer architecture. Moreover, we design a geometry-guided loss based on a novel point curvature to refine boundaries in an end-to-end manner, avoiding time-consuming post-processing to reach clinically applicable segmentation. In addition, we create a dataset with 16,000 IOSs, the largest ever IOS dataset to the best of our knowledge. The experimental results demonstrate that our TSegFormer consistently surpasses existing state-of-the-art baselines. The superiority of TSegFormer is corroborated by extensive analysis, visualizations and real-world clinical applicability tests. Our code is available at https://github.com/huiminxiong/TSegFormer.Comment: MICCAI 2023, STAR(Student Travel) award. 11 pages, 3 figures, 5 tables. arXiv admin note: text overlap with arXiv:2210.1662

Physicochemical properties and in vitro bioaccessibility of lutein loaded emulsions stabilized by corn fiber gums

Lutein is a natural colorant and functional ingredient with many health-promoting bioactivities. However, its use in functional foods is limited due to its low water-solubility and chemical instability. The objectives of this study were to investigate the physicochemical properties and in vitro bioaccessibilities of lutein loaded emulsions stabilized by corn fiber gums (CFG1 and CFG2). The physicochemical properties and stabilities of the emulsions were evaluated by droplet size and distribution, ζ-potential, viscosity, visual observation of phase separation, and lutein retention during storage. The lutein bioaccessibilities of the emulsions were measured after digestion in a simulated gastrointestinal tract (SGT). The results showed that CFG2 had better emulsifying capacity and stability than CFG1. Compared to lutein dispersed in corn oil, the chemical stability and in vitro bioaccessibility of lutein in the emulsions were significantly increased through emulsification. These results suggest that corn fiber gum is a promising natural emulsifier, which has potential to fabricate emulsions for delivering lutein or other lipophilic bioactive compounds in functional foods