Explore the vast range of titles available.

Combined the phase field model with the wavelet dummy node-virtual crack closure technique (WDN-VCCT) used for stress intensity factors (SIFs) calculation. Calculated the node displacement using an improved brittle fracture phase field method, established the relationship between node displacement and node force using WDN-VCCT, and calculated the SIFs at the crack tip. The correctness and accuracy of the proposed method were verified through functional gradient material (FGM) tensile experiment. The influence of crack inclination angle, crack position and gradient index on mechanical response, and SIFs values at the crack tip was discussed. This study provides important computational tools for estimating the service life of FGMs and important references for structural optimization design methods.

Background Ovarian cancer (OC) is the seventh most common malignancy worldwide and the most lethal gynaecological malignancy. We aimed to explore global geographical patterns and temporal trends from 1973 to 2015 for 41 countries in OC incidence and especially to analyse the birth cohort effect to gain further insight into the underlying causal factors of OC and identify countries with increasing risk of OC. Methods OC data were drawn from the Cancer Incidence in Five Continents databases and online databases published by governments. The joinpoint regression model was applied to detect changes in OC trends. The age–period–cohort model was applied to explore age and birth cohort effects. Results The age-standardized rate of OC incidence ranged from 3.0 to 11.4 per 100,000 women worldwide in 2012. The highest age-standardized rate was observed in Central and Eastern Europe, with 11.4 per 100,000 women in 2012. For the most recent 10-year period, the increasing trends were mainly observed in Central and South America, Asia and Central and Eastern Europe. The largest significant increase was observed in Brazil, with an average annual percentage change of 4.4%. For recent birth cohorts, cohort-specific increases in risk were pronounced in Estonia, Finland, Iceland, Lithuania, the United Kingdom, Germany, the Netherlands, Italy, Malta, Slovenia, Bulgaria, Russia, Australia, New Zealand, Brazil, Costa Rica, Ecuador, India, Japan, the Philippines and Thailand. Conclusions Disparities in the incidence and risk of OC persist worldwide. The increased risk of birth cohort in OC incidence was observed for most countries in Asia, Central and Eastern Europe, and Central and South America. The reason for the increasing OC risk for recent birth cohorts in these countries should be investigated with further epidemiology studies.

In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue. Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011-2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China. The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics.

Predicting the specific magnitude and the temporal peak of the epidemic of individual local outbreaks is critical for infectious disease control. Previous studies have indicated that significant differences in spatial transmission and epidemic magnitude of dengue were influenced by multiple factors, such as mosquito population density, climatic conditions, and population movement patterns. However, there is a lack of studies that combine the above factors to explain their complex nonlinear relationships in dengue transmission and generate accurate predictions. Therefore, to study the complex spatial diffusion of dengue, this research combined the above factors and developed a network model for spatiotemporal transmission prediction of dengue fever using metapopulation networks based on human mobility. For improving the prediction accuracy of the epidemic model, the ensemble adjusted Kalman filter (EAKF), a data assimilation algorithm, was used to iteratively assimilate the observed case data and adjust the model and parameters. Our study demonstrated that the metapopulation network-EAKF system provided accurate predictions for city-level dengue transmission trajectories in retrospective forecasts of 12 cities in Guangdong province, China. Specifically, the system accurately predicts local dengue outbreak magnitude and the temporal peak of the epidemic up to 10 wk in advance. In addition, the system predicted the peak time, peak intensity, and total number of dengue cases more accurately than isolated city-specific forecasts. The general metapopulation assimilation framework presented in our study provides a methodological foundation for establishing an accurate system with finer temporal and spatial resolution for retrospectively forecasting the magnitude and temporal peak of dengue fever outbreaks. These forecasts based on the proposed method can be interoperated to better support intervention decisions and inform the public of potential risks of disease transmission.

China has experienced successive waves of dengue epidemics over the past decade. Nationwide data on 95,339 dengue cases, 89 surveillance sites for mosquito density and population mobility between 337 cities during 2013-20 were extracted. Weekly dengue time series including time trends and harmonic terms were fitted using seasonal regression models, and the amplitude and peak timing of the annual and semiannual cycles were estimated. A data-driven model-inference approach was used to simulate the epidemic at city-scale and estimate time-evolving epidemiological parameters. We found that the geographical distribution of dengue cases was expanding, and the main imported areas as well as external sources of imported cases changed. Dengue cases were predominantly concentrated in southern China and it exhibited an annual peak of activity, typically peaking in September. The annual amplitude of dengue epidemic varied with latitude ( F  = 19.62, P  = 0.0001), mainly characterizing by large in southern cities and small in northern cities. The effective reproduction number R eff across cities is commonly greater than 1 in several specific months from July to November, further confirming the seasonal fluctuations and spatial heterogeneity of dengue epidemics. The results of this national study help to better informing interventions for future dengue epidemics in China. The geographical distribution of dengue in China has been expanding this century. Here, the authors report the spatiotemporal distribution of dengue in China using surveillance data from 2013–2020 and combine it with mosquito abundance and human mobility data to simulate transmission at the city scale.

Stress intensity factors (SIFs) are important parameters for evaluating structural reliability. This work combines CT in situ uniaxial compression experiment to study the main crack propagation trajectories of the reactive powder concrete (RPC) specimens. The three-dimensional (3D) displacement fields of RPC specimens with 3D surface cracks were analyzed using a 3D digital image correlation (3D-DIC) method. The 3D-DIC method was used to calculate the 3D surface crack SIFs of RPC specimens at different inclination angles, and the influence of crack inclination angles on SIFs was analyzed. The study found that the distribution pattern of SIFs calculated by the 3D-DIC method is consistent with the results obtained by the numerical method.

ObjectiveTo investigate the relationship between job satisfaction, work stress, work–family conflict and turnover intention, and explore factors associated with turnover intention, among physicians in Guangdong Province, China.MethodsFrom August to October 2013, physicians completed questionnaires and scales with regard to their job satisfaction, work stress, work–family conflict, and turnover intention. Binary logistic regression and structural equation modelling (SEM) were used in data analysis.ResultsA total of 3963 physicians were approached, with 3563 completing the questionnaire. The mean score of the overall perception of turnover intention of physicians who worked in Guangdong was 2.71 on a scale ranging from 1 to 6. Hours worked per week, working in an urban/rural area, type of institution, and age significantly impacted on turnover intention. Turnover intention was directly and negatively related to job satisfaction, and it was directly, indirectly and positively related to work stress and work–family conflict.ConclusionJob satisfaction, work stress, work–family conflict, hours worked per week, working in an urban/rural area, types of institution and age are influencing factors of turnover intention. Reducing working hours, raising salary, providing more opportunities for career development and training, supporting and encouraging physicians by senior managers could potentially contribute to the reduction in turnover intention.

We aimed to estimate the non-accidental and cause-specific mortality burden attributed to diurnal temperature range (DTR) and the relative contributions of low, high, and extremely low and extremely high DTR in Yunnan, southwest China. Furthermore, we explored the possible effect modification of the DTR–mortality association by season, sex, age, ethnicity, marital status, and occupation. A standard time-series quasi-Poisson regression model combined with a distributed lag nonlinear model was used to derive estimates of city-specific DTR–mortality associations, then random effects meta-analysis was used to pool the estimated city-specific overall cumulative DTR–mortality association, estimating empirical confidence intervals (eCIs). The overall fraction of non-accidental mortality caused by DTR was 11.00% (95% eCI 3.40–17.28): high DTR accounted for most of burden (total estimate 10.03%, 95% eCI 2.59–16.32). The estimated mortality risk attributable to DTR was significantly associated with cardiovascular and respiratory mortality, with attributable fractions of 13.61% (95% eCI 3.91–21.13) and 14.32% (95% eCI 0.47–21.44), respectively. The estimated risk attributable to DTR was slightly greater for males, people ≥75 years old, married people, and non-farmers than their corresponding categories. Most of the DTR-related mortality burden was attributable to high DTR, and the mortality risk attributable to DTR might be modified by specific causes, sex, age, marital status, and occupation.

Background Cervical cancer (CC), primarily caused by human papillomavirus (HPV) infection, remains a significant global health concern. We aimed to comprehensively investigate the epidemiological status of HPV in China. Methods Data from 2,728,321 women undergoing routine cervical examinations at 2127 medical institutions nationwide from January 2017 to June 2023 were analyzed. HPV genotype testing was conducted using HPV DNA typing kits. Results The overall HPV prevalence was 17.70%, with 13.12% classified as high-risk HPV (HR-HPV) and 4.58% as low-risk HPV (LR-HPV). Notably, HPV52 emerged as the most common carcinogenic type, followed by HPV58 and HPV16. Age-specific prevalence revealed a bimodal distribution, with peaks observed in women under 21 and over 61 years of age. Geographically, the south (19.48%) exhibited the highest infection rate, while the northwest (12.36%) had the lowest. Furthermore, HPV infection rates were higher during winter and spring. Although HPV infection rates have remained stable overall over the past 7 years, the infection rate in 2023 (14.76%) has declined relative to 2017 (16.17%) ( P  < 0.05). Conclusions This study provides comprehensive insight into HPV epidemiology in China and guidance for future vaccine development and cervical cancer prevention strategies.

Antiretroviral treatment (ART) and pre-exposure prophylaxis (PrEP) for HIV-serodiscordant couples, effectively reduce mortality, transmission events and influence quality of life at the expense of increased costs. We aimed to evaluate health economics of antiretroviral-based strategies for HIV-serodiscordant couples in the China context. A deterministic model of HIV evolution and transmission within a cohort of serodiscordant couples was parameterized using the real-world database of Zhoukou city and published literature. We evaluated the mid-ART (a historical strategy, initiating ART with CD4 < 500 cells/mm 3 ), early-ART (the current strategy, offering ART regardless of CD4 cell counts) and a hypothetical strategy (early-ART combined short-term daily PrEP) versus the late-ART (the baseline strategy, initiating ART with CD4 < 350 cells/mm 3 ) offered by 2008 national guidelines. We estimated the incremental cost-effectiveness ratios (ICER) and incremental cost-utility ratios (ICUR) from a societal perspective, derived by clinical benefits and HIV-caused life quality respectively, and portrayed their changes over a 0–30 year’s timeframe. The model projections indicated that the antiretroviral-based interventions were more likely to obtain clinical benefits but difficult to improve quality of life, and cumulative ICER and ICUR were generally decreasing without achieving cost-saving. Scale-up access to ART for the HIV-positive among serodiscordant couples was easily fallen within the range of paying for incremental life-years and quality adjusted life years by the societal willingness. The hypothetical strategy had the potential to prevent most seroconversion events within marriages but required enormous upfront costs, thus it took a long time to reach established thresholds. The current strategy of early-ART is the most cost-effective. Clarifying the obstacles of high cost of PrEP and improving life quality for HIV-serodiscordant couples have emerged as an urgent requisition.