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In order to solve the problem of small data sets and small detected targets in image detection of wind turbine blades. In this paper, we propose an improved YOLOX-X model. Firstly, we use a variety of data set enhancement methods to solve the problem of small data sets. Secondly, an improved Mixup image enhancement method is proposed to enrich the image background. Then, the attention mechanisms of ECAnet and CBAM are introduced to improve the attention of important features. Furthermore, the IOU_LOSS loss function in the original model is replaced with CIOU_LOSS in this paper to improve the positioning accuracy of small target. Last but not least, the overall network uses the Adam optimizer to accelerate network training and recognition. The effectiveness of algorithm is evaluated on a data sets captured by a UAV in a wind farm. Compared with the original YOLOX-X model, our algorithm improves mAP by 4.55%. In addition, compared with other types of YOLO series networks, it is proved that our model is superior to other algorithms. &nbsp

Changhao Dong,1,2 Rui Xian,1,2 Guangxiang Wang,2,3 Lihong Cui1,2 1Department of Gastroenterology, School of Medicine, South China University of Technology, Guangzhou, People’s Republic of China; 2Department of Gastroenterology, The Sixth Medical Center of PLA General Hospital of Beijing, Beijing, People’s Republic of China; 3The Second School of Clinical Medicine, Southern Medical University, Guangzhou, People’s Republic of ChinaCorrespondence: Lihong Cui, Department of Gastroenterology, the Sixth Medical Center of PLA General Hospital of Beijing, No. 6 Fucheng Road, Haidian Distract, Beijing, 100048, People’s Republic of China, Tel +86-10-66957541, Email cuilhkeyan@163.comPurpose: There is probably a high prevalence of small intestinal bacterial overgrowth (SIBO) in patients with gallbladder polyps (GBPs). To date, no study has evaluated the occurrence of SIBO in patients with GBPs. The aim of this study was to investigate the prevalence of SIBO in patients with GBPs and explore the possible association between these two conditions.Patients and Methods: The hydrogen-methane breath test was used to diagnose SIBO, and patients were divided into GBPs and control groups based on whether GBPs were found under ultrasound. Clinical and paraclinical factors were compared between the two groups.Results: A total of 297 subjects were included in this study. The prevalence of SIBO was significantly higher in the GBPs group than in the control group (50.0% vs.30.8%, p< 0.01). Multivariate logistic regression analysis showed that male (OR=2.26, 95% CI=1.12– 4.57, p=0.023), SIBO (OR=3.21, 95% CI=1.69– 6.11, p< 0.001), fatty liver (OR=2.91, 95% CI= 1.50– 5.64, p=0.002) and BMI (OR=1.13, 95% CI=1.01– 1.26, p=0.035) were independently associated with GBPs. And by subgroup analysis, we found that the association between SIBO and GBPs was stronger in females than in males (p for interaction< 0.001). In addition, SIBO (OR=5.11, 95% CI=1.42– 18.36, p=0.012) and fasting glucose (OR=3.04, 95% CI=1.27– 7.28, p=0.013) were found to be associated with solitary polyps.Conclusion: SIBO was highly prevalent in patients with GBPs, and this association seemed to be stronger among females.Keywords: gut microbiota, bacterial overgrowth, breath test, gallbladder polyps