Rapid Initiation of Antiretroviral Therapy With Coformulated Bictegravir, Emtricitabine, and Tenofovir Alafenamide Versus Efavirenz, Lamivudine, and Tenofovir Disoproxil Fumarate in HIV-Positive Men Who Have Sex With Men in China: Week 48 Results of the Multicenter, Randomized Clinical Trial.

BACKGROUND: Most international treatment guidelines recommend rapid initiation of antiretroviral therapy (ART) for people newly diagnosed with human immunodeficiency virus (HIV)-1 infection, but experiences with rapid ART initiation remain limited in China. We aimed to evaluate the efficacy and safety of efavirenz (400 mg) plus lamivudine and tenofovir disoproxil fumarate (EFV + 3TC + TDF) versus coformulated bictegravir, emtricitabine, and tenofovir alafenamide (BIC/FTC/TAF) in rapid ART initiation among men who have sex with men (MSM) who have been diagnosed with HIV. METHODS: This multicenter, open-label, randomized clinical trial enrolled MSM aged ≥18 years to start ART within 14 days of confirmed HIV diagnosis. The participants were randomly assigned in a 1:1 ratio to receive EFV (400 mg) + 3TC + TDF or BIC/FTC/TAF. The primary end point was viral suppression (<50 copies/mL) at 48 weeks per US Food and Drug Administration Snapshot analysis. RESULTS: Between March 2021 and July 2022, 300 participants were enrolled; 154 were assigned to receive EFV + 3TC + TDF (EFV group) and 146 BIC/FTC/TAF (BIC group). At week 48, 118 (79.2%) and 140 (95.9%) participants in the EFV and BIC group, respectively, were retained in care with viral suppression, and 24 (16.1%) and 1 (0.7%) participant in the EFV and BIC group (P < .001), respectively, discontinued treatment because of adverse effects, death, or lost to follow-up. The median increase of CD4 count was 181 and 223 cells/µL (P = .020), respectively, for the EFV and BIC group, at week 48. The overall incidence of adverse effects was significantly higher for the EFV group (65.8% vs 37.7%, P < .001). CONCLUSIONS: BIC/FTC/TAF was more efficacious and safer than EFV (400 mg) + 3TC + TDF for rapid ART initiation among HIV-positive MSM in China.

The prevalence and risk factors of work related musculoskeletal disorders among electronics manufacturing workers: a cross-sectional analytical study in China.

OBJECTIVES: To describe the prevalence of self-reported musculoskeletal disorders among workers in the electronics manufacturing industry and to investigate the relations between work-related musculoskeletal disorders (WMSDs) and work-related variables. METHODS: An interview-based questionnaire survey was carried out in thirty electronics manufacturing factories in China in 2018. The prevalence of WMSDs was estimated using the modified Nordic Musculoskeletal Questionnaire (NMQ). A multivariate logistic regression model was applied to evaluate the effects of risk factors on WMSDs on multiple body parts. RESULTS: The 12-month prevalence of WMSDs among participants was 40.6%, and the common body sites affected were the neck (26.8%), shoulder (22.8%), upper back (14.9%), and lower back (14.8%). The results of logistic regression showed that female adults, > 5 job tenure and work-related factors (including awkward posture, lifting or carrying weights, excessive repetition, prolonged sitting, monotonous work and working under conditions of cold or temperature variations) led to a higher risk of WMSDs on most body parts. Upper back, wrist/hand and elbow pain levels were significantly higher for workers with vibration. However, more frequently, physical exercise was a protective factor against WMSDs on most body parts except the upper back, leg and knee. CONCLUSIONS: The study indicates a high prevalence of musculoskeletal pain among the electronics manufacturing industry in China. Different personal and work factors are related to the occurrence of WMSD on different body parts. Preventive measures should be implemented based on the characteristics of WMSD in the electronic manufacturing industry. Furthermore, the training and intervention guidance of ergonomic hazards in the workplace need to be strengthened by understanding the impact of bad posture, avoiding long-term sitting posture and increasing physical activities.

The association between adverse ergonomic factors and work-related musculoskeletal symptoms among medical staff in China: a cross-sectional study.

We investigated the prevalence of work-related musculoskeletal symptoms (WMSs) among medical staff and evaluated the associations of different levels of adverse ergonomic factors with WMSs. A total of 6099 Chinese medical staff were asked to complete a self-reported questionnaire to assess the prevalence and risk factors of WMSs from June 2018 to December 2020. A prevalence rate of 57.5% was observed for WMSs among overall medical staffs, which mainly affected the neck (41.7%) and shoulder (33.5%). 'Keeping sitting for long hours very frequently' (OR = 1.26, 95% CI: 1.04, 1.53) was positively associated with WMSs in doctors, while 'keeping sitting for long hours occasionally' (OR = 0.91, 95% CI: 0.85, 0.97) was identified as a protective factor of WMSs in nurses. The associations of adverse ergonomic factors, organisational factors, and environmental factors with WMSs were different among medical staff in different positions.Practitioner summary: We conducted a multi-city study concerning the risk factors of WMSs by carrying out a face-to-face one-to-multiple questionnaire survey among medical staff in China. As a risk factor of WMSs in medical staff, adverse ergonomic factors should be paid more attention by the standard setting department and policy makers.Abbreviations: WMSDs: work-related musculoskeletal disorders; WMSs: work-related musculoskeletal symptoms; MSDs: musculoskeletal disorders; NMQ: Nordic Musculoskeletal Questionnaires; DMQ: Dutch Musculoskeletal Questionnaires; NIOSH: National Institute for Occupational Safety and Health; ORs: odds ratios.

Prevalence and risk factors analysis for low back pain among occupational groups in key industries of China.

BACKGROUND: With the acceleration of industrialization and population aging, low back pain (LBP) has become the leading cause of life loss years caused by disability. Thus, it places a huge economic burden on society and is a global public health problem that needs urgent solution. This study aimed to conduct an epidemiological investigation and research on a large sample of workers in key industries in different regions of China, determine the incidence and distribution characteristics of LBP, explore the epidemic law, and provide a reference basis for alleviating global public health problems caused by LBP. METHODS: We adopted a modified epidemiological cross-sectional survey method and a stratified cluster sampling method. All on-duty workers who fulfill the inclusion criteria are taken as the research participants from the representative enterprises in key industries across seven regions: north, east, central, south, southwest, northwest, and northeast China. The Chinese version of the musculoskeletal disease questionnaire, modified by a standardized Nordic questionnaire, was used to collect information, and 57,501 valid questionnaires were received. Descriptive statistics were used, and multivariate logistic regression analysis (p < 0.05) was performed to explore the association between musculoskeletal disorders and potential risk factors. RESULTS: LBP annual incidence among workers in China's key industries is 16.4%. There was a significant difference in LBP incidence among occupational groups across different industries (p < 0.05). The multivariate regression model showed the following as risk factors for LBP: frequent repetitive movements with the trunk, working in the same positions at a high pace, trunk position, frequently turning around with your trunk, often working overtime, lifting heavy loads (i.e., more than 20 kg), education level, staff shortage, working age (years), cigarette smoking, use of vibration tools at work, body mass index, lifting heavy loads (i.e., more than 5 kg), and age (years). Physical exercise, often standing at work, and absolute resting time were protective factors. CONCLUSION: LBP incidence among key industries and workers in China is high. Thus, it is urgent to take relevant measures according to the individual, occupational, and psychosocial factors of LBP to reduce the adverse impact of LBP on workers' health.

Shoulder work-related musculoskeletal disorders and related factors of workers in 15 industries of China: a cross-sectional study.

BACKGROUND: Changes in modern industrial production practices can easily lead to shoulder work-related musculoskeletal disorders (WMSD). The current reports on shoulder WMSD are limited to some industries are less well studied, and the sample size is usually small. This study aimed to describe the prevalence and severity of shoulder WMSD in a large sample of Chinese workers from 15 industries, analyze the possible correlations with sociodemographic and work-related variables, and compare the differences between industries. METHODS: A cross-sectional study was conducted among a sample of 55,749 participants from 252 enterprises in 15 industries throughout China. A Chinese version of the musculoskeletal disease questionnaire was used to collect the demographic factors, shoulder symptoms in past 12 months, and work-related factors including posture-related factors, repetition, vibration, work organization, job control, and environmental factors as independent variables. Descriptive statistics were used, and the binary logistic regression analysis was performed to explore the association between shoulder WMSD and potential demographic and work-related factors. RESULTS: Nearly 35.5% of participants reported shoulder pain and discomfort in the previous 12 months. Biopharmaceutical manufacturing (56.2%), medical services (54.4%), and aviation services (50.1%) were the three industries with the highest prevalence of shoulder WMSD. The pain score of aviation services workers was the highest. The related factors for shoulder WMSD varied among the different industries. CONCLUSION: Our study found a relatively high prevalence of shoulder WMSD in China. There were large differences in the prevalence of shoulder WMSD among industries, and the related factors were particular to each industry. Such information is useful to help occupational health practitioners and policymakers conduct preventive programs to reduce shoulder disorders in these working populations.

Comparative effectiveness and tolerability of esomeprazole and omeprazole in gastro-esophageal reflux disease: A systematic review and meta-analysis.

This study aims to evaluate the effectiveness and tolerability of esomeprazole and omeprazole in patients with gastroesophageal reflux disease (GERD). Electronic searches on PubMed, EMBASE, the Cochrane Library, and ClinicalTrials.gov databases were carried out for reports up to February 28, 2015. Ten eligible studies from 8 articles were found that enrolled a total of 10,286 patients for meta-analysis. These results revealed a significant difference between esomeprazole vs. omeprazole (RR=1.06, 95% CI [1.01, 1.10], I2=72%, p=0.01) by subgroup according to dosage by random effects model, and a significant difference between esomeprazole 40 mg vs. omeprazole 20 mg (RR=1.07, 95% CI [1.004, 1.14], I2=78%, p=0.04) based on healing rate as determined by endoscopy, using a random effects model. A significant difference between esomeprazole 20 mg and omeprazole 40 mg (RR=0.68, 95% CI [0.47, 0.97], I2=not applicable, p=0.03) was also found in comparing relief of symptoms by random effects model. There were no significant differences in outcomes between other subgroups, including tolerability. Based on these results, a high dose of esomeprazole is recommended for GERD treatment and control in adults.

GPC2 as a diagnostic and prognostic marker regulated progression of colorectal cancer.

BACKGROUND AND STUDY AIMS: Glypican 2 (GPC2) is a member of the glypican gene family and is expressed in multiple kinds of cancer. However, the function and mechanism of GPC2 in colorectal cancer remains unclear. In this study, we aimed to identify the role of GPC2 on tumor cell proliferation and survival in colorectal cancer. PATIENTS AND METHODS: Ten pairs of colon cancer and matched normal colon tissues were collected in this research. GEPIA was used to analysis the GPC2 gene expression profile in TGCA data base. RT-qPCR and western blot assay were performed to determine the mRNA and protein expressions. CCK-8, Flow cytometry and colon formation assay were applied to evaluate cell viability. IHC staining was performed to evaluate the protein expression in tissues. The function of GPC2 in vivo was verified by an animal model of colon cancer. RESULTS: Through the bioinformatics analysis and qRT-PCR validation, we found that GPC2 was upregulated in the colon cancer tissues and cells. GPC2 knockdown suppressed cell proliferation in vitro and in vivo was confirmed by the results of CCK-8, colony formation assays, and tumor xenograft models. Moreover, by the analysis of flow cytometry assay and gain-or-loss function experiments, we discovered that CEP164 was highly associated with the expression state of GPC2, and mediated G2/M-phase arrest in GPC2-downregulated tumor cells. CONCLUSION: GPC2 might be a novel oncogenic gene in colorectal cancer, suggesting that it could be a considerable marker for the diagnosis and prognosis of colorectal cancer.

Small target detection algorithm based on multi-branch stacking and new sampling transition module.

Aiming at the problem that the SSD algorithm does not fully extract the feature information contained in each feature layer, as well as the feature information is easily lost during the sampling process, which makes the feature expression ineffective and leads to insufficient performance in small target detection. In this paper, AMT-SSD is proposed, a small target detection algorithm that incorporates the multi-branch stacking and new sampling transition module of the attention mechanism. In this algorithm, the composite attention mechanism is utilized to improve the correlation of features of the samples to be detected in terms of spatial and channels, and the efficiency of the algorithm; secondly, multi-branch stacking module is used to extract multi-size features for each feature layer, and different sizes of convolution kernels are utilized in parallel to fully extract their features and improve the expression of features; meanwhile, during the sampling process, the problem of missing features is solved by applying inverse subpixel convolution in the new sampling transition module. Experimentally, the AMT-SSD algorithm achieves 84.6% and 53.4% mAP metrics on the PASCAL VOC dataset and MS COCO dataset, respectively. This indicates that the AMT-SSD algorithm can effectively extract feature information that is beneficial to detection samples, and also performs well in reducing feature loss, which is effective for the algorithm to improve the algorithm on small targets.

Research on multi-object detection technology for road scenes based on SDG-YOLOv5.

To resolve the challenges of low detection accuracy and inadequate real-time performance in road scene detection, this article introduces the enhanced algorithm SDG-YOLOv5. The algorithm incorporates the SIoU Loss function to accurately predict the angle loss of bounding boxes, ensuring their directionality during regression and improving both regression accuracy and convergence speed. A novel lightweight decoupled heads (DHs) approach is employed to separate the classification and regression tasks, thereby avoiding conflicts between their focus areas. Moreover, the Global Attention Mechanism Group Convolution (GAMGC), a lightweight strategy, is utilized to enhance the network's capability to process additional contextual information, thereby improving the detection of small targets. Extensive experimental analysis on datasets from Udacity Self Driving Car, BDD100K, and KITTI demonstrates that the proposed algorithm achieves improvements in mAP@.5 of 2.2%, 3.4%, and 1.0% over the original YOLOv5, with a detection speed of 30.3 FPS. These results illustrate that the SDG-YOLOv5 algorithm effectively addresses both detection accuracy and real-time performance in road scene detection.

Unleashing the power of AI in detecting metal surface defects: an optimized YOLOv7-tiny model approach.

The detection of surface defects on metal products during the production process is crucial for ensuring high-quality products. These defects also lead to significant losses in the high-tech industry. To address the issues of slow detection speed and low accuracy in traditional metal surface defect detection, an improved algorithm based on the YOLOv7-tiny model is proposed. Firstly, to enhance the feature extraction and fusion capabilities of the model, the depth aware convolution module (DAC) is introduced to replace all ELAN-T modules in the network. Secondly, the AWFP-Add module is added after the Concat module in the network's Head section to strengthen the network's ability to adaptively distinguish the importance of different features. Finally, in order to expedite model convergence and alleviate the problem of imbalanced positive and negative samples in the study, a new loss function called Focal-SIoU is used to replace the original model's CIoU loss function. To validate the effectiveness of the proposed model, two industrial metal surface defect datasets, GC10-DET and NEU-DET, were employed in our experiments. Experimental results demonstrate that the improved algorithm achieved detection frame rates exceeding 100 fps on both datasets. Furthermore, the enhanced model achieved an mAP of 81% on the GC10-DET dataset and 80.1% on the NEU-DET dataset. Compared to the original YOLOv7-tiny algorithm, this represents an increase in mAP of nearly 11% and 9.2%, respectively. Moreover, when compared to other novel algorithms, our improved model demonstrated enhanced detection accuracy and significantly improved detection speed. These results collectively indicate that our proposed enhanced model effectively fulfills the industry's demand for rapid and efficient detection and recognition of metal surface defects.

Reconstructed SqueezeNext with C-CBAM for offline handwritten Chinese character recognition.

Background: Handwritten Chinese character recognition (HCCR) is a difficult problem in character recognition. Chinese characters are diverse and many of them are very similar. The HCCR model consumes a large number of computational resources during runtime, making it difficult to deploy to resource-limited development platforms. Methods: In order to reduce the computational consumption and improve the operational efficiency of such models, an improved lightweight HCCR model is proposed in this article. We reconstructed the basic modules of the SqueezeNext network so that the model would be compatible with the introduced attention module and model compression techniques. The proposed Cross-stage Convolutional Block Attention Module (C-CBAM) redeploys the Spatial Attention Module (SAM) and the Channel Attention Module (CAM) according to the feature map characteristics of the deep and shallow layers of the model, targeting enhanced information interaction between the deep and shallow layers. The reformulated intra-stage convolutional kernel importance assessment criterion integrates the normalization nature of the weights and allows for structured pruning in equal proportions for each stage of the model. The quantization aware training is able to map the 32-bit floating-point weights in the pruned model to 8-bit fixed-point weights with minor loss. Results: Pruning with the new convolutional kernel importance evaluation criterion proposed in this article can achieve a pruning rate of 50.79% with little impact on the accuracy rate. The various optimization methods can compress the model to 1.06 MB and achieve an accuracy of 97.36% on the CASIA-HWDB dataset. Compared with the initial model, the volume is reduced by 87.15%, and the accuracy is improved by 1.71%. The model proposed in this article greatly reduces the running time and storage requirements of the model while maintaining accuracy.

Epidemiological study of work-related musculoskeletal disorders and related risk factors among automobile maintenance workers.

BACKGROUND: The automotive industry is labor-intensive, and workers are involved in highly repetitive tasks, long hours, and medium to low workloads, resulting in work-related musculoskeletal disorders (WMSDs), which have become a major health concern for workers in this industry. China is a major automotive country with tens of thousands of auto repair workers, but their conditions of WMSDs have been poorly reported. OBJECTIVE: This work aimed to analyze the current prevalence of WMSDs and their associated risk factors among automobile maintenance workers. METHODS: A total of 539 respondents from 50 automotive repair and maintenance companies in China were selected to investigate the prevalence of WMSDs via the modified Nordic Musculoskeletal Disorders Questionnaire. Chi-square test and logistic regression models were applied to analyze their associated risk factors. RESULTS: The total prevalence of WMSDs among 539 workers was 32.8%. The top three body parts for prevalence were the lower back (17.1%), neck (16.3%), and shoulders (14.5%). The highest prevalence of WMSDs was found in the neck (23.6%) and lower back (14.3%) for sheet metal workers and mechanics, respectively, whereas painters had the highest prevalence of WMSDs in the lower back and feet (both at 15.4%). Logistic regression analysis showed that females were at higher risk of WMSDs than males (OR 5.027, [95% CI] [1.278-19.772], p < 0.05). Workers subjected to uncomfortable positions were at increased risk of WMSDs (OR 1.79, [95% CI] [1.333-2.410], p < 0.01). CONCLUSION: The prevalence of WMSDs is high among automotive maintenance workers, with the highest prevalence in the lower back (17.1%). Uncomfortable working postures and frequent repetitive movements with lower limbs and ankles at work may be important risk factors.

Associations of modern initial antiretroviral therapy regimens with all-cause mortality in people living with HIV in resource-limited settings: a retrospective multicenter cohort study in China.

Despite the proven virological advantages, there remains some controversy regarding whether first-line integrase strand transfer inhibitors (INSTIs)-based antiretroviral therapy (ART) contributes to reducing mortality of people living with HIV (PLHIV) in clinical practice. Here we report a retrospective study comparing all-cause mortality among PLHIV in China who were on different initial ART regimens (nevirapine, efavirenz, dolutegravir, lopinavir, and others [including darunavir, raltegravie, elvitegravir and rilpivirine]) between 2017 and 2019. A total of 41,018 individuals were included across China, representing 21.3% of newly reported HIV/AIDS cases collectively in the country during this period. Only the differences in all-cause mortality of PLHIV between the efavirenz group and the nevirapine group, the dolutegravir group and the nevirapine group, and the lopinavir group and the nevirapine group, were observed in China. After stratifying the cause of mortality, we found that the differences in mortality between initial ART regimens were mainly observed in AIDS-related mortality.

Immediate and long-term outcomes after treat-all among people living with HIV in China: an interrupted time series analysis.

BACKGROUND: In 2003, China implemented free antiretroviral therapy (ART) for people living with HIV (PLHIV), establishing an eligibility threshold of CD4 < 200 cells/µl. Subsequently, the entry criteria were revised in 2012 (eligibility threshold: CD4 ≤ 350 cells/µl), 2014 (CD4 ≤ 500 cells/µl), and 2016 (treat-all). However, the impact of treat-all policy on HIV care and treatment indicators in China is unknown. We aimed to elucidate the immediate and long-term impact of the implementation of treat-all policy in China. METHODS: Anonymized programmatic data on ART initiation and collection in PLHIV who newly started ART were retrieved between 1 January 2015 and 31 December 2019, from two provincial and municipal Centers for Disease Control and Prevention and ten major infectious disease hospitals specialized in HIV care in China. We used Poisson and quasi-Poisson segmented regression models to estimate the immediate and long-term impact of treat-all on three key indicators: monthly proportion of 30-day ART initiation, mean CD4 counts (cells/µl) at ART initiation, and mean estimated time from infection to diagnosis (year). We built separate models according to gender, age, route of transmission and region. RESULTS: Monthly data on ART initiation and collection were available for 75,516 individuals [gender: 83.8% males; age: median 39 years, interquartile range (IQR): 28-53; region: 18.5% Northern China, 10.9% Northeastern China, 17.5% Southern China, 49.2% Southwestern China]. In the first month of treat-all, compared with the contemporaneous counterfactual, there was a significant increase in proportion of 30-day ART initiation [+ 12.6%, incidence rate ratio (IRR) = 1.126, 95% CI: 1.033-1.229; P = 0.007] and mean estimated time from infection to diagnosis (+ 7.0%, IRR = 1.070, 95% CI: 1.021-1.120; P = 0.004), while there was no significant change in mean CD4 at ART initiation (IRR = 0.990, 95% CI: 0.956-1.026; P = 0.585). By December 2019, the three outcomes were not significantly different from expected levels. In the stratified analysis, compared with the contemporaneous counterfactual, mean CD4 at ART initiation showed significant increases in Northern China (+ 3.3%, IRR = 1.033, 95% CI: 1.001-1.065; P = 0.041) and Northeastern China (+ 8.0%, IRR = 1.080, 95% CI: 1.003-1.164; P = 0.042) in the first month of treat-all; mean estimated time from infection to diagnosis showed significant increases in male (+ 5.6%, IRR = 1.056, 95% CI: 1.010-1.104; P = 0.016), female (+ 14.8%, IRR = 1.148, 95% CI: 1.062-1.240; P < 0.001), aged 26-35 (+ 5.3%, IRR = 1.053, 95% CI: 1.001-1.109; P = 0.048) and > 50 (+ 7.8%, IRR = 1.078, 95% CI: 1.000-1.161; P = 0.046), heterosexual transmission (+ 12.4%, IRR = 1.124, 95% CI: 1.042-1.213; P = 0.002) and Southwestern China (+ 12.9%, IRR = 1.129, 95% CI: 1.055-1.208; P < 0.001) in the first month of treat-all. CONCLUSIONS: The implementation of treat-all policy in China was associated with a positive effect on HIV care and treatment outcomes. To advance the work of rapid ART, efforts should be made to streamline the testing and ART initiation process, provide comprehensive support services, and address the issue of uneven distribution of medical resources.

Photonic generation of tunable microwave signal using Brillouin fiber laser.

A simple approach to generate two bands of tunable microwave signal is proposed and demonstrated. In this scheme, two single-mode fibers with optimized Brillouin frequency shift spacing have been chosen as the scattering medium in two cascaded ring cavities. Two bands of tunable microwave signal from 390 to 453 MHz and 10.863 to 11.076 GHz can be obtained through adjusting the temperature of the fiber and the pump wavelength. The tunable frequency range can be further expanded by using a temperature controller with a wider adjustment range. The generated microwave signal exhibits high stability on frequency.

[Investigation of occupational hazards of ultraviolet radiation and protective measures for workers in electric welding].

OBJECTIVE: To investigate and analyze the occupational hazards of ultraviolet radiation, protective measures and related factors for typical symptoms among workers in electric welding, and to provide basic information for revision of the occupational standards of UV. METHODS: Questionnaires and physical examinations were used in this investigation. A total of 828 workers from four vehicle manufacturers in Beijing and Guangdong Province were selected. Corresponding analyses were conducted with SPSS 16.0 statistic software. RESULTS: The top three injuries of faces and hands were burning tingling (48.7% & 41.3%), itch of skin (39% & 34.9%) and pigmentation (31.9% & 24.5%).The major injuries of eyes were ophthalmodynia (61.5%) , photophobia and tearing (61.4%), and blurred vision (50.2%). The incidences of facial and hands burning tingling, hands flushing, hands macula and papula were significantly different between the welders and auxiliary workers (P<0.05). The differences of facial and hands burning tingling, flushing, facial disesthesia and anaesthesia, symptoms and signs of eyes were significant in different working years groups (P<0.05). The top three usages of protective measures were welding masks (87.2%), gloves (84.3%) and glasses (65.9%). Except for UV cut cream, the usages of other protective equipments in the auxiliary workers were significantly lower than those in the welders (P<0.05). The logistic regression analysis showed that prolonged exposure to arc welding, using argon arc welding and CO(2) gas shielded arc welding, not wearing welding masks, and not using UV cut cream was significantly associated with the increased risk of face burning tingling, and the ORs were 3.894 (6 h to 8 h), 2.665 (4 h to 6 h), 2.052, 1.765, 1.759, 1.833, respectively; working years might be a protective factor, and the OR was 0.440, respectively. CONCLUSION: The study suggested that the UV radiation produced during welding operations not only caused harm to welders, but also to the auxiliary workers. Protection should be strengthened,for example, wearing welding masks, glasses, etc. Meanwhile automatic welding machines should be adopted by the factories to reduce the exposure time for workers.

Enhanced You Only Look Once X for surface defect detection of strip steel.

Using deep learning-based methods to detect surface defects in strip steel can reduce the impact of human factors and lower costs while maintaining accuracy and efficiency. However, the main disadvantages of this method is the inability to tradeoff accuracy and efficiency. In addition, the low proportion of valid information and the lack of distinctive features result in a high rate of missed detection of small objects. In this paper, we propose a lightweight YOLOX surface defect detection network and introduce the Multi-scale Feature Fusion Attention Module (MFFAM). Lightweight CSP structures are used to optimize the backbone of the original network. MFFAM uses different scales of receptive fields for feature maps of different resolutions, after which features are fused and passed into the spatial and channel attention modules in parallel. Experimental results show that lightweight CSP structures can improve the detection frame rate without compromising accuracy. MFFAM can significantly improve the detection accuracy of small objects. Compared with the initial YOLOX, the mAP and FPS were 81.21% and 82.87Hz, respectively, which was an improvement of 4.29% and 12.72Hz. Compared with existing methods, the proposed model has superior performance and practicality, verifying the effectiveness of the optimization method.

Research on Small Target Detection Technology Based on the MPH-SSD Algorithm.

To address the problems of less semantic information and low measurement accuracy when the SSD (single shot multibox detector) algorithm detects small targets, an MPH-SSD (multiscale pyramid hybrid SSD) algorithm that integrates the attention mechanism and multiscale double pyramid feature enhancement is proposed in this paper. In this algorithm, firstly, the SSD algorithm is used to extract the feature map of small targets, and the shallow feature enhancement module is added to expand the receptive field of the shallow feature layer so as to enrich the semantic information in the feature layer for small targets and improve the expression ability of shallow features. The processed shallow feature layer and deep feature layer are fused at multiple scales, and the semantic information and location information are fused together to obtain a feature map with rich information. Secondly, the cascaded double pyramid structure is used to transfer from the deep layer to the shallow layer so that the context information between different feature layers can be effectively transferred and the feature information can be further strengthened. The hybrid attention mechanism can retain more context information in the network, adaptively adjust the feature map after addition and fusion, and reduce the background interference. The experimental analysis of MPH-SSD algorithm on Pascal VOC and MS COCO datasets shows that the map of this algorithm is 87.7% and 51.1%, respectively. The results show that the MPH-SSD algorithm can make better use of the feature information in the shallow feature layer in the process of small target detection and has better detection performance for small targets.

Bearing fault diagnosis based on particle swarm optimization fusion convolutional neural network.

Bearings are the most basic and important mechanical parts. The stable and safe operation of the equipment requires bearing fault diagnosis in advance. So, bearing fault diagnosis is an important technology. However, the feature extraction quality of the traditional convolutional neural network bearing fault diagnosis is not high and the recognition accuracy will decline under different working conditions. In response to these questions, a bearing fault model based on particle swarm optimization (PSO) fusion convolution neural network is proposed in this paper. The model first adaptively adjusts the hyperparameters of the model through PSO, then introduces residual connections to prevent the gradient from disappearing, uses global average pooling to replace the fully connected layer to reduce the training parameters of the model, and finally adds a dropout layer to prevent network overfitting. The experimental results show that the model is under four conditions, two of which can achieve 100% recognition, and the other two can also achieve more than 98% accuracy. And compared with the traditional diagnosis method, the model has higher accuracy under variable working conditions. This research has important research significance and economic value in the field of the intelligent machinery industry.

Incidence and Risk Factors of the Upper-Limb Musculoskeletal Disorders Among Occupational Groups in Key Industries - China, 2018-2021.

What is already known about this topic?: The burden of illness and economic losses due to upper-limb work-related musculoskeletal disorders (UL-WMSDs) is high; thus, they have become a major global public health problem. At present, the epidemiological characteristics of UL-WMSDs in China's occupational population are still unknown. What is added by this report?: The incidence of UL-WMSDs among key occupational groups in China is 22.5%, with distinct occupational characteristics. What are the implications for public health practice?: This study has primarily determined the occurrence and potential risk factors of UL-WMSDs in key industries in China and provided data support for recommending prevention and control of the occurrence of such diseases in key industries in China, and in facilitating the addition into the China's List of Legal Occupational Diseases.