Creep modeling of composite materials based on improved gene expression programming.

In this article, a new method for creep modeling and performance prediction of composite materials is presented. Since Findley power-law model is usually suitable for studying one-dimensional time-dependent creep of materials under low stress, an intelligent computing method is utilized to derive three temperature-related sub-functions, the creep model as a function of time and temperature is established. In order to accelerate convergence rate and improve solution accuracy, an improved gene expression programming (IGEP) algorithm is proposed by adopting the probability-based population initialization and semi-elite roulette selection strategy. Based on short-term creep data at seven temperatures, a bivariate creep model with certain physical significance is developed. At fixed temperature, the univariate creep model is acquired. R2, RMSE, MAE, RRSE statistical metrics are used to verify the validity of the developed model by comparison with viscoelastic models. Shift factor is solved by Arrhenius equation. The creep master curve is derived from time-temperature superposition model, and evaluated by Burgers, Findley and HKK models. R-square of IGEP model is above 0.98 that is better than classical models. Moreover, the model is utilized to predict creep values at t = 1000 h. Compared with experimental values, the relative errors are within 5.2%. The results show that the improved algorithm can establish effective models that accurately predict the long-term creep performance of composites.

Current status and influential factors for family health management during quarantine: A latent category analysis.

OBJECTIVE: We aimed to explore factors affecting family health management during home quarantine as well as the effects of variations in family health management (FHM) on individuals' health status. METHODS: Using stratified random sampling, 618 families in Wuhan as well as cities within its surrounding provinces were recruited and surveyed online. Latent class variables were extracted from four modules: disinfection, space layout, physical exercise, and food reserves. The analysis was conducted using the poLCA package in R software (v.4.1.0). Chi-squared tests, Fisher's exact tests, and non-parametric Kruskal-Wallis tests were used to compare groups as appropriate. RESULTS: We found an overall questionnaire reliability of 0.77 and a total omega of 0.92, indicating that the survey results were credible. The Bayesian information criterion and Akaike information criterion were used to identified four latent class variables, namely latent non-family health management (18.9%) and latent low, medium, and advanced FHM (30.93%, 29.49%, and 20.59%, respectively). Gender, household income level, body mass index, the presence of a nearby community hospital, and self-rated health status showed statistically significant differences with respect to latent FHM. Moreover, we found a statistically significant difference in emotional reactions when comparing latent advanced and low to mid-level latent FHM. Compared with latent non-family health managers, we detected statistically significant differences in individual energy levels between potential family health managers at latent low and medium levels. Additionally, we found statistically significant differences in individual energy levels between latent advanced and low level family health managers. CONCLUSIONS: We found that multiple factors, including gender, household income, and body mass index, were correlated with latent FHM during home quarantine. We conclude that FHM can meaningfully improve individuals' health. Thus, increasing social support for individuals can improve FHM as well as individuals' health during home quarantine.

Incidence Trends and Survival Prediction of Malignant Skin Cancer: A SEER-Based Study.

Purpose: This study aimed to analyze the incidence trend and further explore the risk factors influencing the survival among patients of malignant skin cancer in America. Methods: Age-adjusted incidence rates, annual percentage change (APC) of different sex and ethnicity in 1973-2015 and patient records were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate analysis and multivariate Cox regression were used to analyze risk factors influencing the survival in skin cancer patients. Survival curves and nomograms were constructed to evaluate the survival prediction by R. Results: The overall age-adjusted incidence of skin cancer increased in America from 1973 to 2005 (APC = 2.8%, 95% CI: 2.6-2.9%, P < 0.05), particularly in white patients, 66-year-old people, and males. The 3- and 5-year overall survival (OS) rates were 51.4% and 33.8%, respectively. Independent predictors for short OS include age over 65, white ethnicity, other marital status and no surgery (P < 0.05). Stage was not an independent factor of survival (P > 0.05). The nomogram with a C-index of 0.72 (95% CI: 0.71-0.73) matched an appropriate calibration curve. Conclusion: Incidence of skin cancer in America was on the rise during 1973-2015 based on SEER database. Age, ethnicity, marital status and surgical history were related with survival of malignant skin cancer. Nomograms were effective tools for predicting the survival prognosis.

Study on Factors of People's Wearing Masks Based on Two Online Surveys: Cross-Sectional Evidence from China.

(1) Background: To analyze factors of people's wearing masks based on two online surveys, and to explore whether living area factor or quarantine status could have an impact on mask-wearing. (2) Methods: Chi-square test and logistic regression analysis were used to explore the influence of different factors on people's behavior of mask-wearing in the present study. R3.6.2 was used for data cleaning, SPSS 26.0 was used to conduct corresponding statistical analysis, and a two-sided p-value less than 0.05 was considered to be statistically significant. (3) Results: According to our study, the proportion of participants who wore face masks was higher than 90.0% in both surveys. Single factor analysis showed that the proportion of people wearing face masks raised with the increase of people's education, age, and monthly income (Yuan) in both surveys. People who lived in rural areas were less likely to wear masks. Mask-wearing rate was lower in the isolated individuals than in the non-isolated ones. (4) Conclusions: Masks-wearing is one of the effective measures for COVID-19 pandemic prevention and control. After the Chinese government made wearing face masks mandatory in public places, most residents in China had developed the habit of wearing masks, contributing to the high rate of masks-wearing in China. However, people in rural areas need to raise their awareness of wearing masks. Meanwhile, the mask-wearing of the isolated individuals needs to be enhanced.

An image-based approach for quantitative assessment of uniformity in particle distribution of noise reduction material.

Under the background of noise pollution caused by railway development, noise reduction material is worthy of in-depth study. A uniform distribution of particles in the material has an important influence on sound absorption property. In this article, the relevant image processing technology is applied to get structure information to quantify the uniformity. The main contributions of this study are: (a) In the preprocessing stage, SEM cross-sectional image of material is processed by mean filter and histogram equalization. Therefore, the grayscale and the contrast between target and background are enhanced, and a low-quality image is transformed into a high-quality one. (b) In the locating stage, local details of the image are considered to discriminate each particle from the whole image. When a global threshold is combined with the local iteration threshold, an improved Otsu algorithm is designed to binarize the image. Through morphology transforming, area filtering, and hole filling, the connected domain of target can be found and particles are located. (c) In the assessing stage, area index, number index and local distance index are established for assessing the uniformity of pore distribution. The experimental results indicate that statistical analysis is consistent with human visual observation. The smaller the porosity is, the better the uniformity is. Compared with some important methods, the effectiveness and efficiency of the proposed approach could be illustrated.

Risk Factors Analysis of Bone Mineral Density Based on Lasso and Quantile Regression in America during 2015-2018.

This study aimed to explore the risk factors of bone mineral density (BMD) in American residents and further analyse the extent of effects, to provide preventive guidance for maintenance of bone health. A cross-sectional study analysis was carried out in this study, of which data validity was identified and ethics approval was exempted based on the National Health and Nutrition Examination Survey (NHANES) database. Candidates' demographics, physical examination, laboratory indicators and part of questionnaire information were collected and merged from NHANES in 2015-2016 and 2017-2018. The least absolute shrinkage selection operator (lasso) was used to select initial variables with "glmnet" package of R, quantile regression model to analyze influence factors of BMD and their effects in different sites with "qreg" code in Stata. Among 2937 candidates, 17 covariates were selected by lasso regression (λ = 0.00032) in left arm BMD, with 16 covariates in left leg BMD (λ = 0.00052) and 14 covariates in total BMD (λ = 0.00065). Quantile regression results displayed several factors with different coefficients in separate sites and quantiles: gender, age, educational status, race, high-density lipoprotein (HDL), total cholesterol (TC), lead, manganese, ethyl mercury, smoking, alcohol use and body mass index (BMI) (p < 0.05). We constructed robust regression models to conclude that some demographic characteristics, nutritional factors (especially lipid levels, heavy metals) and unhealthy behaviors affected BMD in varying degrees. Gender and race differences, Low-fat food intake and low exposure to heavy metals (mostly lead, manganese and mercury) should be considered by both clinical doctors and people. There is still no consensus on the impact of smoking and alcohol use on bone mineral density in our study.

Moderating role of job satisfaction on turnover intention and burnout among workers in primary care institutions: a cross-sectional study.

BACKGROUND: Global countries are suffering from a shortage of health professionals. Turnover intention is closely related to job satisfaction and burnout, making good use of these relationships could alleviate the crisis. Our research aims to examine the mediating role of job satisfaction in the relationship between burnout and turnover intention. METHODS: This research was conducted in Huangpi, China. The convenience sampling method and self-administereded questionnaires were used. 1370 of valid samples were collected with 97.72% effective rate. Descriptive analyses were conducted to describe social demographic factors. The structural equation model (SEM) was performed to adjust model fitting, and the mediation effect test was carried out by using the bootstrap method. Sobel-Z test was used to verify the significance of mediation effect. RESULTS: The mean age was 36.98 (SD = 9.84). The fitting indices of hypothetical model are not good. After the adjustments, χ2/df = 5.590, GFI = 0.932, AGFI = 0.901, CFI = 0.977, NFI = 0.973, IFI = 0.977, TLI = 0.970, RESEA = 0.058. The revised model fitted well, and the SEM was put up by using the bootstrap method. The mediating effect is partial, and Soble-Z test indicates that the mediation effect is significant. Burnout is negatively correlated with job satisfaction (p < 0.01) and the standardized path coefficient is - 0.41. Job satisfaction is also negatively correlated with turnover intention (p < 0.01) and the standardized path coefficient is - 0.18. Burnout is positively correlated with turnover intention (p < 0.01) and the standardized path coefficient is 0.83. CONCLUSIONS: Job satisfaction is a mediating variable that affects the relationship between burnout and turnover intention. The mediating effect was a partial mediating effect and has a low impact of 7.4%. Improving treatment and giving more promotion opportunities for workers to improve job satisfaction, conducting career planning course and paying attention to employee psychological health to reduce job burnout. The above measures may be helpful to reduce employee turnover rate and alleviating the current situation of a shortage of health personnel in China.