Traditional mediation analysis assumes that a study population is homogeneous and the mediation effect is constant over time, which may not hold in some applications. Motivated by smoking cessation data, we propose a latent class dynamic mediation model that explicitly accounts for the fact that the study population may consist of different subgroups and the mediation effect may vary over time. We use a proportional odds model to accommodate the subject heterogeneities and identify latent subgroups. Conditional on the subgroups, we employ a Bayesian hierarchical nonparametric time-varying coefficient model to capture the time-varying mediation process, while allowing each subgroup to have its individual dynamic mediation process. A simulation study shows that the proposed method has good performance in estimating the mediation effect. We illustrate the proposed methodology by applying it to analyze smoking cessation data.

A social network comprises both actors and the social connections among them. Such connections reflect the dependence among social actors, which is essential for individuals’ mental health and social development. In this article, we propose a mediation model with a social network as a mediator to investigate the potential mediation role of a social network. In the model, the dependence among actors is accounted for by a few mutually orthogonal latent dimensions which form a social space. The individuals’ positions in such a latent social space are directly involved in the mediation process between an independent and dependent variable. After showing that all the latent dimensions are equivalent in terms of their relationship to the social network and the meaning of each dimension is arbitrary, we propose to measure the whole mediation effect of a network. Although individuals’ positions in the latent space are not unique, we rigorously articulate that the proposed network mediation effect is still well defined. We use a Bayesian estimation method to estimate the model and evaluate its performance through an extensive simulation study under representative conditions. The usefulness of the network mediation model is demonstrated through an application to a college friendship network.

The paper clarifies the relationship among several information matrices for the maximum likelihood estimates (MLEs) of item parameters. It shows that the process of calculating the observed information matrix also generates a related matrix that is the middle piece of a sandwich-type covariance matrix. Monte Carlo results indicate that standard errors (SEs) based on the observed information matrix are robust to many, but not all, conditions of model/distribution misspecifications. SEs based on the sandwich-type covariance matrix perform most consistently across conditions. Results also suggest that SEs based on other matrices are either not consistent or perform not as robust as those based on the sandwich-type covariance matrix or the observed information matrix.

In this paper we propose an upward correction to the standard error (SE) estimation of \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$\hat{\theta}_{\mathrm{ML}}$\end{document}, the maximum likelihood (ML) estimate of the latent trait in item response theory (IRT). More specifically, the upward correction is provided for the SE of \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$\hat{\theta}_{\mathrm{ML}}$\end{document} when item parameter estimates obtained from an independent pretest sample are used in IRT scoring. When item parameter estimates are employed, the resulting latent trait estimate is called pseudo maximum likelihood (PML) estimate. Traditionally, the SE of \documentclass[12pt]{minimal}\usepackage{amsmath}\usepackage{wasysym}\usepackage{amsfonts}\usepackage{amssymb}\usepackage{amsbsy}\usepackage{mathrsfs}\usepackage{upgreek}\setlength{\oddsidemargin}{-69pt}\begin{document}$\hat{\theta}_{\mathrm{ML}}$\end{document} is obtained on the basis of test information only, as if the item parameters are known. The upward correction takes into account the error that is carried over from the estimation of item parameters, in addition to the error in latent trait recovery itself. Our simulation study shows that both types of SE estimates are very good when θ is in the middle range of the latent trait distribution, but the upward-corrected SEs are more accurate than the traditional ones when θ takes more extreme values.

This paper studies changes of standard errors (SE) of the normal-distribution-based maximum likelihood estimates (MLE) for confirmatory factor models as model parameters vary. Using logical analysis, simplified formulas and numerical verification, monotonic relationships between SEs and factor loadings as well as unique variances are found. Conditions under which monotonic relationships do not exist are also identified. Such functional relationships allow researchers to better understand the problem when significant factor loading estimates are expected but not obtained, and vice versa. What will affect the likelihood for Heywood cases (negative unique variance estimates) is also explicit through these relationships. Empirical findings in the literature are discussed using the obtained results.

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.

In mammals, the skin acts as a barrier to prevent harmful environmental stimuli from entering the circulation. CYP450s are involved in drug biotransformation, exogenous and endogenous substrate metabolism, and maintaining the normal physiological function of the skin, as well as facilitating homeostasis of the internal environment. The expression pattern of CYP450s in the skin is tissue-specific and thus differs from the liver and other organs. The development of skin topical medications, and knowledge of the toxicity and side effects of these medications require a detailed understanding of the expression and function of skin-specific CYP450s. Thus, we summarized the expression of CYP450s in the skin, their function in endogenous metabolic physiology, aberrant CYP450 expression in skin diseases and the influence of environmental variables and medications. This information will serve as a crucial foundation for future studies on the skin, as well as for the design and development of new drugs for skin diseases including topical medications.

With the advantages of short duration and extreme brightness, laser proton accelerators (LPAs) show great potential in many fields for industrial, medical, and research applications. However, the quality of current laser-driven proton beams, such as the broad energy spread and large divergence angle, is still a challenge. We use numerical simulations to study the propagation of such proton bunches in the plasma. Results show the bunch will excite the wakefield and modulate itself. Although a small number of particles at the head of the bunch cannot be manipulated by the wakefield, the total energy spread is reduced. Moreover, while reducing the longitudinal energy spread, the wakefield will also pinch the beam in the transverse direction. The space charge effect of the bunch is completely offset by the wakefield, and the transverse momentum of the bunch decreases as the bunch transports in the plasma. For laser-driven ion beams, our study provides a novel idea about the optimization of these beams.

Integrating the literature on talent management and teams, and drawing upon the signaling theory as the overarching framework, we investigated the moderated indirect effects of talent inducements on employee creativity via employee work engagement in teams. Empirical data from matched leader-members indicated that team talent inducement was positively related to member work engagement, which was then positively associated with team and member creativity. In addition, individual learning and performance-approach goal orientation positively moderated this indirect relationship, whereas individual performance-avoidance goal orientation negatively moderated this indirect relationship. Together, these results illuminate a cross-level influence process of team talent inducements on creativity and individual goal orientations as boundary conditions.

Suppose you need to complete a task of 5 steps, each of which has equal difficulty and pass rate. You somehow have a privilege that can ensure you pass one of the steps, but you need to decide which step to be privileged before you start the task. Which step do you want to privilege? Mathematically speaking, the effect of each step on the final outcome is identical, and so there seems to be no prima facie reason for a preference. Five studies were conducted to explore this issue. In Study 1, participants could place the privilege on any of steps 1–5. Participants were most inclined to privilege step 5. In Study 2, participants needed to pay some money to purchase the privilege for steps 1–5, respectively. Participants would pay most money for step 5. Study 3 directly reminded participants that the probability of success of the whole task is mathematically the same, no matter on which step the privilege is placed, but most of the participants still prefer to privilege the final step. Study 4 supposed that the outcomes of all steps were not announced until all steps were finished, and asked how painful participants would feel if they passed all steps but one. People thought they would feel most painful when they failed at the final step. In Study 5, an implicit association test showed that people associated the first step with easy and the final step with hard. These results demonstrated the phenomenon of the final step effect and suggested that both anticipated painfulness and stereotype may play a role in this phenomenon.

Objectives: Medical devices and the hospital environment can be contaminated easily by multidrug-resistant bacteria. The effectiveness of cleaning practices is often suboptimal because environmental cleaning in hospitals is complex and depends on human factors, the physical and chemical characteristics of environment, and the viability of the microorganisms. Ultraviolet-C (UV-C) lamps can be used to reduce the spread of microorganisms. We evaluated the effectiveness of an ultraviolet-C (UV-C) device on terminal room cleaning and disinfection. Methods: The study was conducted at an ICU of a medical center in Taiwan. We performed a 3-stage evaluation for the effectiveness of UV-C radiation, including pre–UV-C radiation, UV-C radiation, and a bleaching procedure. The 3 stages of evaluation were implemented in the ICU rooms from which a patient had been discharged or transferred. We collected the data from adenosine triphosphate (ATP) bioluminescence testing, colonized strains, and their corresponding colony counts by sampling from the environmental surfaces and air. We tested 8 high-touch surfaces, including 2 sides of bed rails, headboards, footboards, bedside tables, monitors, pumping devices, IV stands, and oxygen flow meters. Results: In total, 1,696 environmental surfaces and 72 air samples were analyzed. The levels of ATP bioluminescence and colony counts of isolated bacteria decreased significantly after UV-C radiation and bleaching disinfection for both the environmental and air samples (P < .001). Resistant bacteria (vancomycin-resistant Enterococcus, VRE) were commonly isolated on the hard-to-clean surfaces of monitors, oxygen flow meters, and IV pumps. However, they were also eradicated (P < .001). Conclusions: UV-C can significantly reduce environmental contamination by multidrug-resistant microorganisms. UV-C is an effective device to assist staff in cleaning the hospital environment.

Evidence of couples’ BMI and its influence on birth weight is limited and contradictory. Therefore, this study aims to assess the association between couple’s preconception BMI and the risk of small for gestational age (SGA)/large for gestational age (LGA) infant, among over 4·7 million couples in a retrospective cohort study based on the National Free Pre-pregnancy Checkups Project between 1 December 2013 and 30 November 2016 in China. Among the live births, 256 718 (5·44 %) SGA events and 506 495 (10·73 %) LGA events were documented, respectively. After adjusting for confounders, underweight men had significantly higher risk (OR 1·17 (95 % CI 1·15, 1·19)) of SGA infants compared with men with normal BMI, while a significant and increased risk of LGA infants was obtained for overweight and obese men (OR 1·08 (95 % CI 1·06, 1·09); OR 1·19 (95 % CI 1·17, 1·20)), respectively. The restricted cubic spline result revealed a non-linear decreasing dose–response relationship of paternal BMI (less than 22·64) with SGA. Meanwhile, a non-linear increasing dose–response relationship of paternal BMI (more than 22·92) with LGA infants was observed. Moreover, similar results about the association between maternal preconception BMI and SGA/LGA infants were obtained. Abnormal preconception BMI in either women or men were associated with increased risk of SGA/LGA infants, respectively. Overall, couple’s abnormal weight before pregnancy may be an important preventable risk factor for SGA/LGA infants.

A 1178 J near diffraction limited 527 nm laser is realized in a complete closed-loop adaptive optics (AO) controlled off-axis multi-pass amplification laser system. Generated from a fiber laser and amplified by the pre-amplifier and the main amplifier, a 1053 nm laser beam with the energy of 1900 J is obtained and converted into a 527 nm laser beam by a KDP crystal with 62% conversion efficiency, 1178 J and beam quality of 7.93 times the diffraction limit (DL). By using a complete closed-loop AO configuration, the static and dynamic wavefront distortions of the laser system are measured and compensated. After correction, the diameter of the circle enclosing 80% energy is improved remarkably from 7.93DL to 1.29DL. The focal spot is highly concentrated and the 1178 J, 527 nm near diffraction limited laser is achieved.

We investigated the effects of botulinum toxin on gait in Parkinson’s disease (PD) patients with foot dystonia. Six patients underwent onabotulinum toxin A injection and were assessed by Burke–Fahn–Marsden Dystonia Rating Scale (BFMDRS), visual analog scale (VAS) of pain, Timed Up and Go (TUG), Berg Balance Test (BBT), and 3D gait analysis at baseline, 1 month, and 3 months. BFMDRS (p = 0.002), VAS (p = 0.024), TUG (p = 0.028), and BBT (p = 0.034) were improved. Foot pressures at Toe 1 (p = 0.028) and Midfoot (p = 0.018) were reduced, indicating botulinum toxin’s effects in alleviating the dystonia severity and pain and improving foot pressures during walking in PD.