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To solve the problems of low teaching programming efficiency and poor flexibility in robot welding of complex box girder structures, a method of seam trajectory recognition based on laser scanning displacement sensing was proposed for automated guidance of a welding torch in the skip welding of a spatially intermittent welding seam. Firstly, a laser scanning displacement sensing system for measuring angles adaptively is developed to detect corner features of complex structures. Secondly, a weld trajectory recognition algorithm based on Euclidean distance discrimination is proposed. The algorithm extracts the shape features by constructing the characteristic triangle of the weld trajectory, and then processes the set of shape features by discrete Fourier analysis to solve the feature vector used to describe the shape. Finally, based on the Euclidean distance between the feature vector of the test sample and the class matching library, the class to which the sample belongs is identified to distinguish the weld trajectory. The experimental results show that the classification accuracy rate of four typical spatial discontinuous welds in complex box girder structure is 100%. The overall processing time for weld trajectory detection and classification does not exceed 65 ms. Based on this method, the field test was completed in the folding special container production line. The results show that the system proposed in this paper can accurately identify discontinuous welds during high-speed metal active gas arc welding (MAG) welding with a welding speed of 1.2 m/min, and guide the welding torch to automatically complete the skip welding, which greatly improves the welding manufacturing efficiency and quality stability in the processing of complex box girder components. This method does not require a time-consuming pre-welding teaching programming and visual inspection system calibration, and provides a new technical approach for highly efficient and flexible welding manufacturing of discontinuous welding seams of complex structures, which is expected to be applied to the welding manufacturing of core components in heavy and large industries such as port cranes, large logistics transportation equipment, and rail transit.

We propose piezoelectric energy harvester (PEH) with double-cantilever-beam (DCB) undergoing coupled bending-torsion vibrations by combining width-splitting method and asymmetric mass, in order that more ambient energy could be harvested from environmental vibration with multiple-frequency excitation. The geometrical dimensions are optimized for PEHDCB, when the maximum of output peak voltages U p-max and resonance frequency difference (Δ f 0 ) between the first and second modes are chosen as optimization objectives based on orthogonal test method. The energy harvesting efficiency is evaluated by the proportion of half-power bandwidth and quality factor, and the experimental and simulation results are compared to verify reliability. The U p-max1 and P p-max1 are increased 25.2% and 57.3% for PEHDCB under the multi-frequency excitation, when the split-width method is applied into PEH with single-cantilever-beam (SCB) undergoing coupled bending-torsion vibrations. The deviations of U p-max1 and f 0 are at the ranges of 4.9–14.2% and 2.2–2.5% for PEHDCB under the different mass ratios, and the measurement reliability is acceptable considering incomplete clamping, damping and inevitable assembly effects. The energy harvesting efficiency of PEHDCB presented is much higher than that of the conventional PEHSCB from environmental vibration with multiple-frequency excitation.

Studies on triaxial contact stresses and asphalt pavement rutting are of great significance for traffic safety and the durability of the asphalt pavement. Our new approach considers more evaluating indicators by investigating compressive creep, vertical, and longitudinal permanent deformation to analyse asphalt pavement rutting under triaxial contact stress during typical driving conditions. For this purpose, firstly sophisticated three-dimensional finite element models encompassing the truck-bus tire and asphalt pavement temperature are developed. Secondly, a comparative analysis was conducted by collating the predicted deformations obtained through finite element analysis with the deformations measured in laboratory experiments using specialized sensors. Finally, the rutting analysis process under triaxial contact stresses during typical driving conditions is established. The results show asphalt pavement exhibits different temperature gradient changes between daytime and nighttime during the summer season. The longitudinal contact stress under braking condition has a significant impact on the longitudinal permanent deformation and compressive creep of asphalt pavement, especially, the longitudinal permanent deformation of the feature points in the middle layer exhibits the most pronounced sensitivity to this contact stress. In addition, the maximal compressive creep is observed at the top of the middle layer, although the characteristic positions for the maximum values of positive and negative creep differ. The proposed new method is beneficial for improving the accuracy and comprehensiveness of asphalt pavement rutting analysis.

Droplet transfer frequency is a decisive factor in welding quality and efficiency in gas tungsten arc welding (GTAW). However, there still needs to be a monitoring method for droplet transfer frequency with high precision and good real-time performance. Therefore, a real-time monitoring method for droplet transfer frequency in wire-filled GTAW using arc sensing is proposed in this paper. An arc signal acquisition system is developed, and the wavelet filtering method filters out noise from the arc signal. An arc signal segmentation method—based on the OTSU algorithm and a feature extraction method for droplet transition based on density-based spatial clustering of applications with noise (DBSCAN)—is proposed to extract the feature signal of the droplet transition. A new conception of droplet transition uniformity is proposed, and it can be used to monitor the weld bead width uniformity. Numerous experiments for monitoring droplet transfer frequency in real time are conducted with typical welding parameters. This method enables the real-time observation of droplet transfer frequency, and the result shows that the average monitoring error is less than 0.05 Hz.

Objective Tuberculosis (TB) remains a leading global cause of death attributable to a single infectious agent. However, studies examining the TB burden in The Group of Twenty(G20) countries are limited. This study sought to analyze temporal trends in TB burden and identify key risk factors across G20 nations from 1990 to 2021, while projecting the risk factors-attributable disease burden through 2035 using advanced modeling techniques. Methods Data were obtained from the Global Burden of Disease (GBD) 2021 database. Disease burden was assessed using the disability-adjusted life years (DALYs) and the age-standardized DALYs rates (ASDR), characterizing temporal trends, regional variations, age-specific patterns, and sex disparities in TB burden across G20 countries. Joinpoint regression analysis identified periods with significant temporal changes in country-specific TB ASDR attributable to different risk factors (1990–2021). Health inequality analysis was performed to assess inequalities in TB burden attributable to risk factors relative to the socio-demographic index (SDI). Decomposition analysis was performed to investigate the drivers of changes in TB burden across G20 countries. Additionally, trends in the population attributable fractions (PAF) and summary exposure values (SEV) were analyzed for each risk factor. Finally, Bayesian age-period-cohort (BAPC) modeling was used to project DALYs and ASDR for TB related to six risk factors across the G20 countries from 2022 to 2035. Results From 1990 to 2021, overall TB DALYs in G20 countries decreased by 50% (95% UI: 36% – 56%). In 2021, India recorded the highest DALYs, followed by Indonesia, while South Africa exhibited the highest ASDR, with Indonesia and India ranking second and third, respectively. Smoking constituted the leading risk factor for TB ASDR in 2021, followed by high alcohol use. Over the past three decades, the PAF of TB DALYs attributable to each risk factor varied significantly across age and gender groups. Health inequality analysis revealed narrowed absolute disparities but widespread exacerbation of relative inequalities in TB burden related to risk factrs across G20 nations. Decomposition analysis demonstrated divergent proportional contributions of drivers–aging, population growth, and epidemiological changes–to the risk-attributable TB burden across G20 countries. BAPC model projections indicated persistently high TB burdens in India, Indonesia, China, and South Africa throgh 2035. Trends in TB DALYs and ASDR attributable to risk factors across G20 countries were heterogeneous: while most nations showed declining smoking-attributable burdens relative to 2021 levels, other risk factors contributed to increased burdens to varying degrees in numerous countries. Conclusion Despite declining TB burden across G20 nations, substantial heterogeneity persists. Smoking and high alcohol use remained the dominant risk factors contributing to TB burden, while comorbidities like diabetes and obesity warrant continued focus. The implementation of interventions specifically targeting these risk factors, combined with enhanced collaborative frameworks within the G20, is essential to further mitigate TB burden and disparities.

Three-dimensional (3D) zigzag-line welding seams are found extensively in the manufacturing of marine engineering equipment, heavy lifting equipment, and logistics transportation equipment. Currently, due to the large amount of calculation and poor real-time performance of 3D welding seam detection algorithms, real-time tracking of 3D zigzag-line welding seams is still a challenge especially in high-speed welding. For the abovementioned problems, we proposed a method for the extraction of the pose information of 3D zigzag-line welding seams based on laser displacement sensing and density-based clustering point cloud segmentation during robotic welding. after thee point cloud data of the 3D zigzag-line welding seams was obtained online by the laser displacement sensor, it was segmented using theρ-Approximate DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. In the experiment, high-speed welding was performed on typical low-carbon steel 3D zigzag-line welding seams using gas metal arc welding. The results showed that when the welding velocity was 1000 mm/min, the proposed method obtained a welding seam position detection error of less than 0.35 mm, a welding seam attitude estimation error of less than two degrees, and the running time of the main algorithm was within 120 ms. Thus, the online extraction of the pose information of 3D zigzag-line welding seams was achieved and the requirements of welding seam tracking were met.

Background Depressive symptoms are common public health concern among undergraduate students. With the widespread use of smartphones, the association between smartphone usage duration and depressive symptoms has received extensive attention. Meanwhile, academic and life stress play key roles in the development of depressive symptoms. Objective To explore the independent and interactive effects of pre-sleep smartphone use duration and negative life events (NLEs; e.g., exam failure, romantic relationship breakdown) on depressive symptoms among undergraduate students. Methods From October to November 2022, a cluster sampling survey was conducted at a university in Shaanxi Province, China. A total of 21,227 undergraduates were included in the final analysis. Depressive symptoms were assessed using the Self-Rating Depression Scale (SDS). Consistent with the standard psychometric convention for this scale, the presence of depressive symptoms was determined using a binary cut-off, with a total SDS score ≥ 50 indicating clinically significant depressive symptoms. The results do not reflect a clinical diagnosis of depression. Binary logistic regression models were used to examine the effects of pre-sleep smartphone use duration and negative life events on depressive symptoms. Restricted cubic spline (RCS) regression was applied to assess dose–response relationships, and Relative Excess Risk due to Interaction (RERI) and Attributable Proportion due to Interaction (AP) were used to characterize their interaction effect. Results The prevalence of depressive symptoms among participants was 15.6%, and 54.8% reported experiencing NLEs. Prolonged pre-sleep smartphone use and more NLEs were significantly associated with an increased risk of depressive symptoms in a dose-response manner. Compared with the 0–30 min/day group, the fully adjusted ORs were 1.436(95%CI: 1.254–1.644) for 31–60 min/day, 1.917༈95%CI༚1.697–2.166༉ for 61–120 min/day, and 3.005༈95%CI༚2.654–3.042༉for > 120 min/day. The highest risk was observed in the group with > 120 min/day use and more than one NLE (OR = 10.830, 95%CI: 8.786–13.365) versus the reference group (0–30 min/day use and no NLEs). RERI/AP values for one NLE combined with 31–60, 61–120, > 120 min/day use were 0.359/0.119, 0.770/0.203, 0.143/0.023; for more than one NLE, the corresponding values were 0.171/0.044, -0.106/-0.191, 1.085/0.100. Conclusions Both pre-sleep smartphone use and NLEs are significantly associated with depressive symptoms among undergraduate students in a dose-response manner, and exert a synergistic effect on depressive symptoms.

Purpose To evaluate the relationship between vertebral bone marrow fat, blood flow perfusion, and IVD biochemical components in postmenopausal women using quantitative MRI. Materials and methods Postmenopausal women were categorized into three groups based on QCT: normal BMD ( n =  34), osteopenia ( n =  27), and osteoporosis ( n =  24). Lumbar vertebral bone marrow fat fraction (FF) was quantified using a 6-echo-based Dixon sequence. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provided quantitative parameters for bone marrow blood perfusion ( K trans , K ep , V e ). T2 mapping imaging assessed lumbar disc degeneration, yielding T2 values for the nucleus pulposus (NP), anterior annulus fibrosus (AAF), and posterior annulus fibrosus (PAF). We analyzed Spearman correlation coefficients and identified independent factors influencing disc T2 values through multiple linear regression analysis. Results Significant differences were found in FF, K trans , K ep , and V e values across groups ( p <  0.001 , p <  0.001 , p <  0.001 , p =  0.025). FF showed a strong inverse correlation with adjacent NP T2 values at L1 ( r =  -0.760, adjusted p <  0.001), and moderate at L2 and L3 ( r =  -0.613, adjusted p <  0.001; r =  -0.455, adjusted p <  0.001). Positive correlations were found between K trans and adjacent NP T2 values at all levels ( r =  0.715 to 0.314, adjusted p <  0.01 to < 0.001). A multivariate linear regression analysis revealed that FF and K trans values were independent predictors of adjacent NP T2 values at L1 to L4 levels. Conclusion Both vertebral bone marrow FF and K trans are independent predictors of intervertebral disc health, as reflected by nucleus pulposus T2 values. Notably, these relationships exhibit a distinct craniocaudal gradient, with stronger vertebral-disc coupling in the upper lumbar spine. Multiparametric quantitative MRI provides deeper insights into early disc degeneration pathways beyond single-parameter assessments.

Objectives Gastric cancer (GC) ranks as the fifth most common malignancy and the fifth leading cause of cancer-related deaths globally. Early-onset GC (EOGC), accounting for approximately 10% of all GC cases, remains understudied regarding disease burden trends across the 11 BRICS nations. Leveraging the Global Burden of Disease (GBD) 2021 database, this study analyzes the incidence, burden trends, and attributable risk factors of EOGC in the 11 BRICS countries (2025 expansion) and projects its epidemiological trajectory from 2022 to 2035. Methods Data were obtained from the GBD 2021 database. We assessed the EOGC incidence and burden in the 11 BRICS countries (2025 expansion) using both absolute numbers and age-standardized rates (ASRs). Joinpoint regression analysis was used to identify significant temporal trends in ASRs from 1990 to 2021. Health inequality analysis revealed health inequality patterns in EOGC burden associated with the socio-demographic index (SDI). Decomposition analysis was performed to identify key drivers of EOGC burden variations across the 11 BRICS nations. Additionally, we analyzed trends in population attributable fractions (PAFs) and summary exposure values (SEVs) for relevant risk factors, projected EOGC incidence and burden for 2022–2035 using the BAPC model, and evaluated the sensitivity of each indicator’s prediction results using the mean absolute difference (MAD) following secondary prediction with the Nordpred model. Results From 1990 to 2021, the 11 BRICS countries experienced an 11.87% decline in absolute EOGC cases and a 33.75% reduction in disability-adjusted life years (DALYs). In 2021, China and India exhibited the highest absolute burden, while the United Arab Emirates (UAE) had the lowest. The ASRs were highest in China and Russia and lowest in the UAE. A male predominance in EOGC burden was observed, except in Ethiopia, the UAE, and Saudi Arabia. Joinpoint regression revealed declining trends in age-standardized incidence rates (ASIR) and age-standardized DALY rates (ASDR) across all nations except Egypt (average annual percentage changes [AAPC] ASIR = 0.40, 95% confidence interval [CI]: 0.26–0.50; AAPC ASDR = 0.10, 95% CI: − 0.02–0.20). Ethiopia demonstrated the most substantial ASIR reduction, while the Russian Federation indicated the most significant ASDR decline. Transient increases (annual percentage change [APC] > 0, 95% CI excluding 0) occurred in South Africa (1990–2004) and Saudi Arabia (2003–2008). Health inequality analysis indicated persistent relative inequalities concentrated in high-SDI countries (concentration index > 0, 95% CI excluding 0), though absolute inequalities were non-significant (95% CI of slope index including 0). Decomposition analysis identified population growth and aging as primary drivers of increasing burden, except in China and Russia (population growth) and Ethiopia (aging). Epidemiological changes correlated with burden reduction, except in Egypt. Risk factor analysis indicated declining smoking-attributable PAFs in most countries, with increases in Indonesia and Iran. The Russian Federation (15.52%, 95% uncertainty interval [UI]: 0.18.49–12.52%) and China (14.13%, 95% UI: 20.11–9.97%) exhibited the highest smoking PAFs, with notable SEV increases in the Russian Federation (11.95%) and Egypt (9.13%). High-sodium diet PAFs remained stable, peaking in India (11.57%, 95% UI: 0–57.36%) and Ethiopia (11.49%, 95% UI: 0–65.27%), with significant SEV rises in India (6.32%) and Egypt (2.60%). Projections suggest overall EOGC burden reduction across the 11 BRICS nations, though South Africa’s ASDR is predicted to rise to the second highest by 2035. Conclusion While the overall EOGC burden has declined across the 11 BRICS nations (2025 expansion), member states face distinct epidemiological challenges. Higher-SDI nations and Males bore heavier burdens. Smoking and high-sodium diets were key modifiable risks. By 2035, China and India will face the highest burdens, while South Africa’s ASDR will rise. We recommend enhanced regional collaboration —including shared best practices, joint prevention strategies, and harmonized data collection—to address these persistent public health concerns, strengthen future surveillance, and improve comparative analyses.

Objectives Congenital birth defects (CBDs) rank among the top five causes of death in children under the age of five. Despite their significant impact, studies on the burden of CBDs in G20 countries remain limited. This study sought to examine the temporal trends in the disease burden and mortality rates of CBDs across G20 countries from 1990 to 2021, identify potential risk factors contributing to these trends, and project the disease burden and mortality rates for the period 2022–2040. Method Data for this study were obtained from the Global Burden of Disease (GBD) 2021 and GBD 2019 databases. We analyzed trends in disability-adjusted life years (DALYs) and mortality rates for CBDs in G20 countries using absolute numbers, all-age rates, age-standardized rates (ASR), annual percent change (APC), and average annual percent change (AAPC). Joinpoint regression analysis was conducted to identify significant periods of change in ASR. Spearman correlation analysis with locally weighted regression, supplemented by 10,000 bootstrap iterations for robustness validation was used to examine the associations between the socio-demographic index (SDI), healthcare access and quality (HAQ) index, Summary exposure value (SEV) of risk factor exposure, and ASR. Decomposition analysis was performed to investigate the driving factors behind changes in CBDs. Finally, a Bayesian age-period-cohort (BAPC) model was applied to project DALYs and mortality rates for the period 2022–2040. Results From 1990 to 2021, the total DALYs and the number of deaths in G20 countries decreased by 59.77% (95% UI: 68.14–35.22%) and 63.81% (95% UI: 38.72–71.64%), respectively, with a more pronounced reduction observed in males compared to females. In 2021, India recorded the highest DALYs and deaths, followed by China and Indonesia. Mexico reported the highest age-standardized DALY rate (ASDR) and age-standardized mortality rate (ASMR), followed by Turkey, with Argentina ranking third for ASDR and Brazil third for ASMR. Congenital heart anomalies (CHAs) remained the leading cause of ASDR and ASMR among CBDs in 2021, with digestive congenital anomalies (DCAs) ranking second. Joinpoint regression analysis indicated that the most significant changes in ASDR in G20 countries occurred between 1995 and 2021 (APC = -2.58, 95% CI: -2.61 to -2.55), while the most pronounced changes in ASMR were observed between 2019 and 2021 (APC = -3.75, 95% CI: -4.75 to -2.86). The periods of significant change in ASR varied across countries. Spearman correlation analysis revealed that countries with higher SDI and HAQ index exhibited lower ASR ( p  < 0.01, 95% BCa CI excluded zero ). Eleven level-3 risk factors showed a positive correlation with ASDR ( p  < 0.05, 95% BCa CI excluded zero ), with the highest absolute correlation coefficients observed for occupational noise, unsafe sanitation, and vitamin A deficiency. Decomposition analysis showed that changes in aging and epidemiological patterns contributed to reductions of -26.19% and − 54.21% in DALYs, respectively, while population growth led to a 20.64% increase in DALYs. The driving factors for DALY changes varied across countries. The BAPC model predicted a declining trend in DALYs, deaths, and ASR of CBDs across all G20 countries in the future. Conclusion Although the burden of CBDs has declined in G20 countries, significant disparities persist between nations. To effectively reduce these gaps, enhanced international cooperation, increased investment in healthcare resources, and the implementation of more robust preventive measures are essential to effectively reduce the gap in the CBD burden across these countries.