This study was designed to explore the mediating role of serum 25-hydroxyvitamin D (25(OH) D) in Triglyceride–glucose (TyG) index and hypertension (HTN). Study participants were selected from the 2001 to 2018 National Health and Nutrition Examination Survey. Firstly, we estimated the association between TyG index and serum 25(OH)D with HTN using a weighted multivariable logistic regression model and restricted cubic spline. Secondly, we used a generalised additive model to investigate the correlation between TyG index and serum 25(OH)D. Lastly, serum 25(OH)D was investigated as a mediator in the association between TyG index and HTN. There were 14 099 subjects in total. TyG index was positively and linearly associated with HTN risk, while serum 25(OH)D had a U-shaped relationship with the prevalence of HTN. When the serum 25(OH)D levels were lower than 57·464 mmol/l, the prevalence of HTN decreased with the increase of serum 25(OH)D levels. When serum 25(OH)D levels rise above 57·464 mmol/l, the risk of HTN increases rapidly. Based on the U-shaped curve, serum 25(OH)D concentrations were divided into two groups: < 57·464 and ≥57·464 mmol/l. According to the mediation analysis, when serum 25(OH)D levels reached < 57·464 mmol/l, the positive association between the TyG index and incident HTN was increased by 25(OH)D. When serum 25(OH)D levels reached ≥ 57·464 mmol/l, the negative association between the TyG index and incident HTN was increased by 25(OH)D. There was a mediation effect between the TyG index and HTN, which was mediated by 25(OH)D. Therefore, we found that the association between serum 25(OH)D levels and TyG index may influence the prevalence of HTN.

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.

In behavioral, biomedical, and psychological studies, structural equation models (SEMs) have been widely used for assessing relationships between latent variables. Regression-type structural models based on parametric functions are often used for such purposes. In many applications, however, parametric SEMs are not adequate to capture subtle patterns in the functions over the entire range of the predictor variable. A different but equally important limitation of traditional parametric SEMs is that they are not designed to handle mixed data types—continuous, count, ordered, and unordered categorical. This paper develops a generalized semiparametric SEM that is able to handle mixed data types and to simultaneously model different functional relationships among latent variables. A structural equation of the proposed SEM is formulated using a series of unspecified smooth functions. The Bayesian P-splines approach and Markov chain Monte Carlo methods are developed to estimate the smooth functions and the unknown parameters. Moreover, we examine the relative benefits of semiparametric modeling over parametric modeling using a Bayesian model-comparison statistic, called the complete deviance information criterion (DIC). The performance of the developed methodology is evaluated using a simulation study. To illustrate the method, we used a data set derived from the National Longitudinal Survey of Youth.

One species-general life history (LH) principle posits that challenging childhood environments are coupled with a fast or faster LH strategy and associated behaviors, while secure and stable childhood environments foster behaviors conducive to a slow or slower LH strategy. This coupling between environments and LH strategies is based on the assumption that individuals’ internal traits and states are independent of their external surroundings. In reality, individuals respond to external environmental conditions in alignment with their intrinsic vitality, encompassing both physical and mental states. The present study investigated attachment as an internal mental state, examining its role in mediating and moderating the association between external environmental adversity and fast LH strategies. A sample of 1169 adolescents (51% girls) from 9 countries was tracked over 10 years, starting from age 8. The results confirm both mediation and moderation and, for moderation, secure attachment nullified and insecure attachment maintained the environment-LH coupling. These findings suggest that attachment could act as an internal regulator, disrupting the contingent coupling between environmental adversity and a faster pace of life, consequently decelerating human LH.

A negative pressure wall-climbing robot is a special robot for climbing vertical walls, which is widely used in construction, petrochemicals, nuclear energy, shipbuilding, and other industries. The mobility and adhesion of the wheel-track wall-climbing robot with steering-straight mode are significantly decreased on the cylindrical wall, especially during steering. The reason is that the suction chamber may separate from the wall and the required driving force for movement increases, during steering. In this paper, a negative pressure wall-climbing robot with omnidirectional movement mode is developed. By introducing a compliant adjusting suction mechanism and omni-belt wheels, an omnidirectional movement mode is formed instead of the steering-straight mode, and the performances of adhesion and mobility are improved. We establish the safety adhesion model for the robot on a cylindrical wall and obtain the safety adhesion forces. We designed and manufactured an experimental prototype based on the analysis. Experiments showed that the robot has the ability of full maneuverability in cylindrical walls.

Previous studies have revealed an association between dietary factors and atopic dermatitis (AD). To explore whether there was a causal relationship between diet and AD, we performed Mendelian randomisation (MR) analysis. The dataset of twenty-one dietary factors was obtained from UK Biobank. The dataset for AD was obtained from the publicly available FinnGen consortium. The main research method was the inverse-variance weighting method, which was supplemented by MR‒Egger, weighted median and weighted mode. In addition, sensitivity analysis was performed to ensure the accuracy of the results. The study revealed that beef intake (OR = 0·351; 95 % CI 0·145, 0·847; P = 0·020) and white bread intake (OR = 0·141; 95 % CI 0·030, 0·656; P = 0·012) may be protective factors against AD. There were no causal relationships between AD and any other dietary intake factors. Sensitivity analysis showed that our results were reliable, and no heterogeneity or pleiotropy was found. Therefore, we believe that beef intake may be associated with a reduced risk of AD. Although white bread was significant in the IVW analysis, there was large uncertainty in the results given the wide 95 % CI. Other factors were not associated with AD in this study.

We design a scheme for laser-inertial odometry and mapping with bundle adjustment (BA-LIOM), which can greatly mitigate the problem of undesired ground warping due to sparsity of laser scans and significantly reduce odometry drift. Specifically, an Inertial measurement unit (IMU)-assisted adaptive voxel map initialization algorithm is proposed and elaborately integrated with the existing framework LIO-SAM, allowing for accurate registration in the beginning of the localization and mapping process. In addition, to accommodate to fast-moving and structure-less scenarios, we design a tightly coupled odometry, which jointly optimizes both the IMU preintegration constraints and scan matching with adaptive voxel maps. The voxels (edge and plane, respectively) are updated with BA optimization. And then the accurate mapping result is obtained by performing local BA. The proposed BA-LIOM is thoroughly assessed using datasets collected from multiple platforms over a variety of environments. Experimental results show the superiority of BA-LIOM over the state-of-the-art methods in robustness and precision, especially for large-scale scenarios. BA-LIOM improves the accuracy of localization by $61\%$ and $73\%$ on the buildings and lawn datasets, respectively, and has a $29\%$ accuracy improvement over LIO-SAM on the KITTI datasets. A supplementary video can be accessed at https://youtu.be/5l4ZFhTc2sw.

Clay–organic interaction is an important natural process that underpins soil ecosystem services. This process can also be tailored to produce clay–organic nanocomposites for industrial and environmental applications. The organic moiety of the nanocomposites, typically represented by a toxic surfactant, could be replaced by hydrochar formed from biomolecules (e.g. glucose) via hydrothermal carbonization. The effect of montmorillonite (Mnt) and glucose dosage on hydrochar formation, however, has not been clarified. In addition, the mechanisms by which Mnt-hydrochar nanocomposites (CMnt) can detoxify and remove carcinogenic Cr(VI) from aqueous solution are not well understood. In the current study, research milestones in terms of clay–organic interactions are summarized, following which the synthesis and characterization of CMnt for Cr(VI) adsorption are outlined. Briefly, 1 g of Mnt was reacted with 75 mL of glucose solution (0.1, 0.2, 0.3, 0.4, 0.5, and 0.6 mol L−1) by hydrothermal carbonization at 200°C for 16 h. The resultant CMnt samples were analyzed for chemical composition, functional groups, morphological features, and Cr(VI) adsorptive properties. Mnt promoted the conversion of glucose to hydrochars, the particle size of which (~80 nm) was appreciably smaller than that formed in the absence of Mnt (control). Furthermore, the hydrochars in CMnt had an aromatic structure with low hydrogen substitution and high stability (C/H atomic ratio 0.34–0.99). The weakened OH (from hydrochar) and Si–O–Si stretching peaks in the Fourier-transform infrared (FTIR) spectra of CMnt are indicative of chemical bonding between Mnt and hydrochar. The CMnt samples were effective at removing toxic Cr(VI) from acidic aqueous solutions. Several processes were involved, including direct reduction of Cr(VI) to Cr(III), complexation of Cr(III) with carboxyl and phenolic groups of hydrochar, electrostatic attraction between Cr(VI) and positively charged CMnt at pH 2 followed by indirect reduction of Cr(VI) to Cr(III), and Cr(III) precipitation.

High-intensity vortex beams with tunable topological charges and low coherence are highly demanded in applications such as inertial confinement fusion (ICF) and optical communication. However, traditional optical vortices featuring nonuniform intensity distributions are dramatically restricted in application scenarios that require a high-intensity vortex beam owing to their ineffective amplification resulting from the intensity-dependent nonlinear effect. Here, a low-coherence perfect vortex beam (PVB) with a topological charge as high as 140 is realized based on the super-pixel wavefront-shaping technique. More importantly, a globally adaptive feedback algorithm (GAFA) is proposed to efficiently suppress the original intensity fluctuation and achieve a flat-top PVB with dramatically reduced beam speckle contrast. The GAFA-based flat-top PVB generation method can pave the way for high-intensity vortex beam generation, which is crucial for potential applications in ICF, laser processing, optical communication and optical trapping.

We explored the transmission mechanisms of corporate fraud and its punishments within social network communities. Using fraud triangle theory and trust triangle theory, we hypothesize four transmitting channels of how fraud commission and detection are affected by peers’ fraud and punishment. Based on Chinese listed corporations from 2008 to 2018, we first construct and detect interlocked social network communities with a community-detecting algorithm, and then examine hypotheses using a bivariate probit model with partial observability. Our findings indicate that peer-concealing and -hinting effects exist within social network communities. The peer-concealing effect decreases the likelihood of being detected when committing fraud, for those with more and closer fraudulent peers. The peer-hinting effect increases the likelihood of being detected when committing fraud, for those with more and closer punished peers. There is no evidence to support peer-contagion and vicarious-punishment effects. Thus, an improved understanding of the transmission mechanism of corporate fraud commission and detection within communities is provided to prevent and detect corporate fraud. In addition, stakeholders and regulators should be aware of the deviant subculture and social distancing in social network communities.

Parametric interaction allows both forward and backward energy transfers among the three interacting waves. The back-conversion effect is usually detrimental when unidirectional energy transfer is desired. In this theoretical work, we manifest that the back-conversion effect underpins the direct generation of the picosecond pulse train without the need for a laser resonator. The research scenario is an optical parametric amplification (OPA) that consists of a second-order nonlinear medium, a quasi-continuous pump laser and a sinusoidal amplitude-modulated seed signal. The back-conversion of OPA can transfer the modulation peaks (valleys) of the incident signal into output valleys (peaks), which inherently induces spectral sidebands. The generation of each sideband is naturally accompanied with a phase shift of ±π. In the regime of full-back-conversion, the amount and amplitude of the sidebands reach the maximum simultaneously, and their phase constitutes an arithmetic sequence, leading to the production of a picosecond pulse train. The generated picosecond pulse train can have an ultrahigh repetition rate of 40 GHz or higher, which may facilitate ultrafast applications with ultrahigh speed.

We conducted three experiments to investigate the effects of physical and psychological pains on intertemporal choices. In Experiments 1 and 2, physical pain was induced by the self-created Shiatsu sheet treading method (SSTM) and the classical cold pressor task (CPT), respectively. In Experiment 3, psychological pain was induced by the video induction method. All types of pain increased preference for smaller immediate rewards. Theoretical implications and practical implications are discussed.

Excavation at Mogou, a Bronze Age cemetery containing over 1700 burials and 6000 individuals, has revealed a diverse range of multiple burials. Building on this dataset, the Mogou Multidisciplinary Investigation Project aims to explore connections between kinship, burial space and social organisation in Bronze Age north-west China.

In strong-field physics experiments with ultraintense lasers, a single-shot cross-correlator (SSCC) is essential for fast optimization of the pulse contrast and meaningful comparison with theory for each pulse shot. To simultaneously characterize an ultrashort pulse and its long pedestal, the SSCC device must have both a high resolution and a large temporal window. However, the resolution and window in all kinds of single-shot measurement contradict each other in principle. Here we propose and demonstrate a novel SSCC device with two separate measurement channels: channel-1 for the large-window pedestal measurement has a moderate resolution but a large window, while channel-2 for the ultrashort pulse measurement has a small window but a high resolution; this allows the accurate characterization of the pulse contrast in a single shot. A two-channel SSCC device with a 200-fs resolution and 114-ps window has been developed and tested for its application in ultraintense lasers at 800 nm.

Collision avoidance is critical in multirobot systems. Most of the current methods for collision avoidance either require high computation costs (e.g., velocity obstacles and mathematical optimization) or cannot always provide safety guarantees (e.g., learning-based methods). Moreover, they cannot deal with uncertain sensing data and linguistic requirements (e.g., the speed of a robot should not be large when it is near to other robots). Hence, to guarantee real-time collision avoidance and deal with linguistic requirements, a distributed and hybrid motion planning method, named Fuzzy-VO, is proposed for multirobot systems. It contains two basic components: fuzzy rules, which can deal with linguistic requirements and compute motion efficiently, and velocity obstacles (VOs), which can generate collision-free motion effectively. The Fuzzy-VO applies an intruder selection method to mitigate the exponential increase of the number of fuzzy rules. In detail, at any time instant, a robot checks the robots that it may collide with and retrieves the most dangerous robot in each sector based on the predicted collision time; then, the robot generates its velocity in real-time via fuzzy inference and VO-based fine-tuning. At each time instant, a robot only needs to retrieve its neighbors’ current positions and velocities, so the method is fully distributed. Extensive simulations with a different number of robots are carried out to compare the performance of Fuzzy-VO with the conventional fuzzy rule method and the VO-based method from different aspects. The results show that: Compared with the conventional fuzzy rule method, the average success rate of the proposed method can be increased by 306.5%; compared with the VO-based method, the average one-step decision time is reduced by 740.9%.