The association between smoking and family health with the mediation role of personality among Chinese people: nationwide cross-sectional study.

BACKGROUND: There may be unexplored interactions between family health, personality, and smoking that could help provide new perspectives on tobacco control. OBJECTIVE: To examine the relationship between the health of one's family and their smoking habits, as well as investigate the potential influence of personality on this relationship. METHODS: For this cross-sectional investigation, a national survey conducted in China in 2022 recruited a total of 21,916 individuals. The Family Health Scale was utilized to assess the health of the family. The 10-item Big Five Inventory scale was utilized to assess the Big five personality traits. The relationship between big five personality, family health, and smoking were investigated using binary and linear logistic regression. The indirect effects mediated by Big five personality were analyzed using mediation analysis with Sobel tests, and the indirect effects were composited using the Karlson-Holm-Breen method. RESULTS: The overall prevalence of smoking in the study population was 14.87%, 26.19% for males and 3.54% for females. Urban and rural smoking prevalence was 13.81% and 16.10% respectively. Binary logistic regression analysis revealed a significant negative relationship between smoking and family health (odds ratio 0.964, 95% CI 0.959, 0.970, P < 0.001) with covariates controlled. The Karlson-Holm-Breen composition facilitated the connection between extraversion (47.81%) and nervousness (52.19%). CONCLUSIONS: Preventive interventions for smoking behavior should prioritize family health and the Big five personality as significant areas to focus on. According to this study, in addition to implementing various interventions for different personalities, family health should be strengthened to reduce smoking behavior.

Investigation on blind tip reconstruction errors caused by sample features.

Precision measurements of a nanoscale sample surface using an atomic force microscope (AFM) require a precise quantitative knowledge of the 3D tip shape. Blind tip reconstruction (BTR), established by Villarrubia, gives an outer bound with larger errors if the tip characterizer is not appropriate. In order to explore the errors of BTR, a series of simulation experiments based on a conical model were carried out. The results show that, to reconstruct the tip precisely, the cone angle of the tip characterizer must be smaller than that of the tip. Furthermore, the errors decrease as a function of the tip cone angle and increase linearly with the sample radius of curvature, irrespective of the tip radius of curvature. In particular, for sharp (20 nm radius) and blunt (80 nm radius) tips, the radius of curvature of the tip characterizer must be smaller than 5 nm. Based on these simulation results, a local error model of BTR was established. The maximum deviation between the errors derived from the model and the simulated experiments is 1.22 nm. Compared with the lateral resolution used in the above simulated experiments (4 nm/pixel), it is valid to ignore the deviations and consider the local error model of BTR is indeed in quantitative agreement with the simulation results. Finally, two simulated ideal structures are proposed here, together with their corresponding real samples. The simulation results show they are suitable for BTR.

The Association Between Personality Traits and Health-Related Quality of Life and the Mediating Role of Smoking: Nationwide Cross-Sectional Study.

Background: There are positive and negative correlations in different directions between smoking, personality traits, and health-related quality of life (HRQOL), where smoking may mask the pathway between personality traits and HRQOL. Understanding the masking pathway of smoking between personality traits and HRQOL can elucidate the mechanisms of smoking's psychosocial effects and provide new ideas for developing tobacco control strategies. Objective: The purpose of this study was to investigate the correlation between Big Five personality traits and HRQOL and whether smoking mediates the relationship between them. Methods: This was a cross-sectional study using data from 21,916 respondents from the 2022 Psychology and Behavior Investigation of Chinese Residents survey. Linear regression models were used to analyze the correlations between smoking, Big Five personality traits, and HRQOL while controlling for potential confounders. The mediating role of smoking on the association between Big Five Personality traits and HRQOL was analyzed using the Sobel-Goodman mediation test. Results: Extraversion (ß=.001; P=.04), agreeableness (ß=.003; P<.001), and neuroticism (ß=.003; P<.001) were positively correlated with HRQOL, whereas openness was negatively correlated with HRQOL (ß=-.001; P=.003). Smoking was associated with a decrease in HRQOL and mediated the positive effect of HRQOL on extraversion (z=-2.482; P=.004), agreeableness (z=-2.264; P=.02), and neuroticism (z=-3.230; P=.001). Subgroup analyses further showed that smoking mediated the effect of neuroticism on HRQOL in the population with chronic illnesses (z=-2.724; P=.006), and in the population without chronic illnesses, smoking contributed to the effect of HRQOL on extraversion (z=-2.299; P=.02), agreeableness (z=-2.382; P=.02), and neuroticism (z=-2.213; P=.03). Conclusions: This study provided evidence that there is a correlation between personality traits and HRQOL. It also found that smoking plays a role in mediating the connection between personality traits and HRQOL. The development of future tobacco control strategies should consider the unique traits of each individual's personality, highlighting the significance of extraversion, agreeableness, and neuroticism.

A rate adaptive control method for Improving the imaging speed of atomic force microscopy.

A simple rate adaptive control method is proposed to improve the imaging speed of the atomic force microscope (AFM) in the paper. Conventionally, the probe implemented on the AFM scans the sample surface at a constant rate, resulting in low time efficiency. Numerous attempts have been made to realize high-speed AFMs, while little efforts are put into changing the constant-rate scanning. Here we report a rate adaptive control method based on variable-rate scanning. The method automatically sets the imaging speed for the x scanner through the analysis of the tracking errors in the z direction at each scanning point, thus improving the dynamic tracking performance of the z scanner. The development and functioning of the rate adaptive method are demonstrated, as well as how the approach significantly achieves faster scans and a higher resolution AFM imaging.