Surface defect detection of ceramic disc based on improved YOLOv5s.

Addressing the challenges in detecting surface defects on ceramic disks, such as difficulty in detecting small defects, variations in defect sizes, and inaccurate defect localization, we propose an enhanced YOLOv5s algorithm. Firstly, we improve the anchor frame structure of the YOLOv5s model to enhance its generalization ability, enabling robust defect detection for objects of varying sizes. Secondly, we introduce the ECA attention mechanism to improve the model's accuracy in detecting small targets. Under identical experimental conditions, our enhanced YOLOv5s algorithm demonstrates significant improvements, with precision, F1 scores, and mAP values increasing by 3.1 %, 3 %, and 4.5 % respectively. Moreover, the accuracy in detecting crack, damage, slag, and spot defects increases by 0.2 %, 4.7 %, 5.4 %, and 1.9 % respectively. Notably, the detection speed improves from 232 frames/s to 256 frames/s. Comparative analysis with other algorithms reveals superior performance over YOLOv3 and YOLOv4 models, showcasing enhanced capability in identifying small target defects and achieving real-time detection.

Meta-analysis study of small extracellular vesicle nursing application therapies for healing of wounds and skin regeneration.

We designed and performed this meta-analysis to investigate the impact of the application of extracellular small vesicle therapies on regeneration of skin and wound healing. The findings of this study were computed using fixed or random effect models. The mean differences (MDs), and odds ratio (ORs) with their 95% confidence intervals (CIs) were calculated. In this study, 43 publications were included, encompassing 530 animals with artificial wounds. Small extracellular vesicle therapy had a significant greater rate of wound closure (MD, 24.0; 95% CI, 19.98-28.02, P < 0.001), lower scar width (MD, -191.33; 95%CI, -292.26--90.4, P < 0.001), and higher blood vessel density (MD,36.11; 95%CI, 19.02-53.20, P < 0.001) compared to placebo. Our data revealed that small extracellular vesicle therapy had a significantly higher regeneration of skin and healing of wounds based on the results of wound closure rate, lower scar width, and higher blood vessel density compared to placebo. Future studies with larger sample size are needed.

Surface Defect Detection of Bearing Rings Based on an Improved YOLOv5 Network.

Considering the characteristics of complex texture backgrounds, uneven brightness, varying defect sizes, and multiple defect types of the bearing surface images, a surface defect detection method for bearing rings is proposed based on improved YOLOv5. First, replacing the C3 module in the backbone network with a C2f module can effectively reduce the number of network parameters and computational complexity, thereby improving the speed and accuracy of the backbone network. Second, adding the SPD module into the backbone and neck networks enhances their ability to process low-resolution and small-object images. Next, replacing the nearest-neighbor upsampling with the lightweight and universal CARAFE operator fully utilizes feature semantic information, enriches contextual information, and reduces information loss during transmission, thereby effectively improving the model's diversity and robustness. Finally, we constructed a dataset of bearing ring surface images collected from industrial sites and conducted numerous experiments based on this dataset. Experimental results show that the mean average precision (mAP) of the network is 97.3%, especially for dents and black spot defects, improved by 2.2% and 3.9%, respectively, and that the detection speed can reach 100 frames per second (FPS). Compared with mainstream surface defect detection algorithms, the proposed method shows significant improvements in both accuracy and detection time and can meet the requirements of industrial defect detection.

A New Real-Time Pinch Detection Algorithm Based on Model Reference Kalman Prediction and SRMS for Electric Adjustable Desk.

This paper presents a new algorithm based on model reference Kalman torque prediction algorithm combined with the sliding root mean square (SRMS). It is necessary to improve the accuracy and reliability of the pinch detection for avoiding collision with the height adjustable desk and accidents on users. Motors need to regulate their position and speed during the operation using different voltage by PWM (Pulse Width Modulation) to meet the requirement of position synchronization. It causes much noise and coupling information in the current sampling signal. Firstly, to analyze the working principle of an electric height adjustable desk control system, a system model is established with consideration of the DC (Direct Current) motor characteristics and the coupling of the system. Secondly, to precisely identify the load situation, a new model reference Kalman perdition method is proposed. The load torque signal is selected as a pinch state variable of the filter by comparing the current signal. Thirdly, to meet the need of the different loads of the electric table, the sliding root means square (SRMS) of the torque is proposed to be the criterion for threshold detection. Finally, to verify the effectiveness of the algorithm, the experiments are carried out in the actual system. Experimental results show that the algorithm proposed in this paper can detect the pinched state accurately under different load conditions.

Consensus via event-triggered strategy of nonlinear multi-agent systems with Markovian switching topologies.

The consensus problem via event-triggered strategy of nonlinear multi-agent systems (MASs) with Markovian switching topologies is addressed in this paper. To simplify information transmission, a distributed event-triggered mechanism (ETM) is designed. By combining the Markovian switching topologies and ETM, an appropriate consensus control protocol is presented. Considering the impact of delay on systems stability, the system model is transformed by the delay system approach. By choosing a Lyapunov-Krasovskii function and applying linear matrix inequalities technique, sufficient conditions are obtained to ensure the consensus stability with H∞ norm bound of the MASs. A numerical simulation is given to confirm the effectiveness of the designed method.

MR Lymphangiography for Focal Disruption of the Thoracic Duct in Chylothorax of an Infant: a Case Report and Literature Review.

Chylothorax is a rare cause of pleural effusion in children, and it is usually difficult to identify the location of chyle leakage due to the small size of the thoracic duct in children. Herein we report an infant case with chylothorax whose leakage of the thoracic duct was successfully located by magnetic resonance lymphangiography (MRL) using pre-contrast MR cholangiopancreatography (MRCP) and gadodiamide-enhanced spectral presaturation inversion recovery (SPIR) T1-weighted imaging, which demonstrate the imaging method is easy and effective for detecting the focal disruption of the thoracic duct in children with chylothorax and younger than 8 months old.