With advancements in industrial robot technology and the ongoing enhancements in control system performance, the demand for precise robot motion is increasing. Generally, an increased number of interpolation points enhances the precision of robot movement, but excessive points can lead to jittering and out-of-step issues. This paper investigates the relationship between the number of motion interpolation points and the response times of the control system and the robot’s terminal velocity, based on the theoretical calculation and experimental analysis of the limit interpolation points for the control system of a self-developed 6-DOF (Six Degree of Freedom) robot. The method for calculating limit interpolation points is refined using the least squares method, and equations are derived for different control system response time and robot’s terminal velocity reaction times. The validity of the prediction curves is verified through experimental analysis.

The greatest challenge in pressure reconstruction from the measured velocity fields is that the error of material acceleration is significantly contaminated due to error propagation. Particularly for flows with moving boundaries, accurate boundary velocities are difficult to obtain due to error propagation, and a complex boundary processing technique is needed to treat the moving boundaries. The present work proposes a machine-learning-based method to determine the pressure for incompressible flows with moving boundaries. The proposed network consists of two neural networks: one network, named the boundary network, is used to track the Lagrangian boundary points; the other physics-informed neural network, named the flow network, is adopted to approximate the flow fields. These two networks are coupled by imposing boundary conditions. We further propose a new dynamic weight strategy for the loss terms to guarantee convergence and stability. The performance of the proposed method is validated by two examples: the flow over an oscillating cylinder and the flow around a swimming fish. The proposed method can accurately determine the pressure fields and boundary motion from synthetic particle image velocimetry (PIV) flow fields. Moreover, this method can also predict the boundary and pressure at a given instant without supervised data. Finally, this method was applied to reconstruct the pressure from the two-dimensional and three-dimensional PIV velocities of the left ventricle. All of the results indicate that the proposed method can accurately reconstruct the pressure fields for flows with moving boundaries and is a novel method for surface pressure estimation.

Researchers would often like to leverage data from a collection of sources (e.g., meta-analyses of randomized trials, multi-center trials, pooled analyses of observational cohorts) to estimate causal effects in a target population of interest. However, because different data sources typically represent different underlying populations, traditional meta-analytic methods may not produce causally interpretable estimates that apply to any reasonable target population. In this article, we present the CausalMetaR R package, which implements robust and efficient methods to estimate causal effects in a given internal or external target population using multi-source data. The package includes estimators of average and subgroup treatment effects for the entire target population. To produce efficient and robust estimates of causal effects, the package implements doubly robust and non-parametric efficient estimators and supports using flexible data-adaptive (e.g., machine learning techniques) methods and cross-fitting techniques to estimate the nuisance models (e.g., the treatment model, the outcome model). We briefly review the methods, describe the key features of the package, and demonstrate how to use the package through an example. The package aims to facilitate causal analyses in the context of meta-analysis.

Although both butterflies and dragonflies are four-winged insects, their wing geometries and kinematics differ significantly. Butterflies have a much narrower gap between their forewing and hindwing than dragonflies. While previous research has extensively investigated the forewing–hindwing interactions in dragonfly flight, this work focuses on their interactions in butterfly flight. The interactions are studied based on numerical simulations of the Navier–Stokes equations around a butterfly-inspired flapping wing with an adjustable slot, representing the narrow gap between the forewing and hindwing. The slot is controlled by a dihedral angle between the forewing and hindwing. The lift coefficients of wings with different slot sizes and locations are investigated in detail. The results show that the forewing–hindwing interactions can significantly enhance the lift if the slot is properly configured. When the slot is configured by elevating the forewing at a 10-degree dihedral angle relative to the hindwing during flapping flight, the wing generates over 20 % more lift than the model without a slot. The streamwise ram effect and tip-vortex capture are shown to be responsible for the lift enhancement by using a lift decomposition formula. The streamwise ram effect reduces the streamwise velocity beneath the forewing, decreasing the negative vortex lift associated with spanwise vorticity. The tip-vortex capture enhances the positive vortex lift associated with streamwise vorticity when the hindwing captures the tip vortex shedding from the forewing.

Psychogenic pseudosyncope is one of the primary causes of transient loss of consciousness in children and adolescents, essentially classified as a conversion disorder that significantly impacts patients’ quality of life. Clinically, psychogenic pseudosyncope shares certain similarities with vasovagal syncope in terms of pre-syncope symptoms and triggers, making it sometimes difficult to differentiate and easily misdiagnosed. Therefore, placing emphasis upon the characteristics of psychogenic pseudosyncope is crucial for early identification and treatment, which holds significant importance for the mental and psychological health of children and adolescents. In the present review, we aimed to address psychogenic pseudosyncope with clinical features, diagnosis, and treatment.

With the advent of web-based technology, online testing is becoming a mainstream mode in large-scale educational assessments. Most online tests are administered continuously in a testing window, which may post test security problems because examinees who take the test earlier may share information with those who take the test later. Researchers have proposed various statistical indices to assess the test security, and one most often used index is the average test-overlap rate, which was further generalized to the item pooling index (Chang & Zhang, 2002, 2003). These indices, however, are all defined as the means (that is, the expected proportion of common items among examinees) and they were originally proposed for computerized adaptive testing (CAT). Recently, multistage testing (MST) has become a popular alternative to CAT. The unique features of MST make it important to report not only the mean, but also the standard deviation (SD) of test overlap rate, as we advocate in this paper. The standard deviation of test overlap rate adds important information to the test security profile, because for the same mean, a large SD reflects that certain groups of examinees share more common items than other groups. In this study, we analytically derived the lower bounds of the SD under MST, with the results under CAT as a benchmark. It is shown that when the mean overlap rate is the same between MST and CAT, the SD of test overlap tends to be larger in MST. A simulation study was conducted to provide empirical evidence. We also compared the security of MST under the single-pool versus the multiple-pool designs; both analytical and simulation studies show that the non-overlapping multiple-pool design will slightly increase the security risk.

CEOs who develop strong clan values as a result of exposure to clan culture in early life wish to bring honor to their clan, motivating them to engage in increased CSR activities. We propose that the influence of CEOs' clan values on CSR is subject to contextual boundaries. Specifically, we predict that the positive relationship between CEOs' clan values and CSR results primarily in an improved level of institutional CSR and varies with CEOs' personal attributes such as overseas experience and hometown identity. An analysis of a longitudinal sample of Chinese publicly listed firms for 2010–2019 provides strong support for our predictions. The implications for upper echelons theory and CSR research are discussed.

The presence of dispersed-phase droplets can result in a notable increase in a system's drag. However, our understanding of the mechanism underlying this phenomenon remains limited. In this study, we use three-dimensional direct numerical simulations with a modified multi-marker volume-of-fluid method to investigate liquid–liquid two-phase turbulence in a Taylor–Couette geometry. The dispersed phase has the same density and viscosity as the continuous phase. The Reynolds number $Re\equiv r_i\omega _i d/\nu$ is fixed at 5200, the volume fraction of the dispersed phase is up to $40\,\%$, and the Weber number $We\equiv \rho u^2_\tau d/\sigma$ is approximately 8. It is found that the increase in the system's drag originates from the contribution of interfacial tension. Specifically, droplets experience significant deformation and stretching in the streamwise direction due to shear near the inner cylinder. Consequently, the rear end of the droplets lags behind the fore head. This causes opposing interfacial tension effects on the fore head and rear end of the droplets. For the fore head of the droplets, the effect of interfacial tension appears to act against the flow direction. For the rear end, the effect appears to act in the flow direction. The increase in the system's drag is attributed primarily to the effect of interfacial tension on the fore head of the droplets which leads to the hindering effect of the droplets on the surrounding continuous phase. This hindering effect disrupts the formation of high-speed streaks, favouring the formation of low-speed ones, which are generally associated with higher viscous stress and drag of the system. This study provides new insights into the mechanism of drag enhancement reported in our previous experiments.

Remote center-of-motion (RCM) manipulators are a key issue in minimally invasive surgeries (MIS). The existing RCM parallel mechanisms (PMs) can only generate RCM motion based on the invariant RCM. To provide mobility for RCM, this paper designed a new family of RCM PMs with movable RCM that features a double-stage topological structure. Drawing mainly on configuration evolution and Lie-group, a general approach is proposed to design double-stage PMs with movable RCM. Feasible limbs for 2R1T RCM motion are enumerated and used to construct the secondary PM. Type synthesis of the primary PMs that realize movable RCM is accomplished based on the method presented. Different connection styles between the two stages that ensure the geometrical conditions of RCM motion are designed. Using different connection styles, double-stage PMs with movable RCM are constructed. These new RCM PMs can realize precise positioning of RCM by taking advantage of the primary PMs, which indicates their potential application prospects in MIS.

We investigate the coupling effects of the two-phase interface, viscosity ratio and density ratio of the dispersed phase to the continuous phase on the flow statistics in two-phase Taylor–Couette turbulence at a system Reynolds number of $6\times 10^3$ and a system Weber number of 10 using interface-resolved three-dimensional direct numerical simulations with the volume-of-fluid method. Our study focuses on four different scenarios: neutral droplets, low-viscosity droplets, light droplets and low-viscosity light droplets. We find that neutral droplets and low-viscosity droplets primarily contribute to drag enhancement through the two-phase interface, whereas light droplets reduce the system's drag by explicitly reducing Reynolds stress due to the density dependence of Reynolds stress. In addition, low-viscosity light droplets contribute to greater drag reduction by further reducing momentum transport near the inner cylinder and implicitly reducing Reynolds stress. While interfacial tension enhances turbulent kinetic energy (TKE) transport, drag enhancement is not strongly correlated with TKE transport for both neutral droplets and low-viscosity droplets. Light droplets primarily reduce the production term by diminishing Reynolds stress, whereas the density contrast between the phases boosts TKE transport near the inner wall. Therefore, the reduction in the dissipation rate is predominantly attributed to decreased turbulence production, causing drag reduction. For low-viscosity light droplets, the production term diminishes further, primarily due to their greater reduction in Reynolds stress, while reduced viscosity weakens the density difference's contribution to TKE transport near the inner cylinder, resulting in a more pronounced reduction in the dissipation rate and consequently stronger drag reduction. Our findings provide new insights into the physics of turbulence modulation by the dispersed phase in two-phase turbulence systems.

Foodborne diseases are ongoing and significant public health concerns. This study analysed data obtained from the Foodborne Outbreaks Surveillance System of Wenzhou to comprehensively summarise the characteristics of foodborne outbreaks from 2012 to 2022. A total of 198 outbreaks were reported, resulting in 2,216 cases, 208 hospitalisations, and eight deaths over 11 years. The findings suggested that foodborne outbreaks were more prevalent in the third quarter, with most cases occurring in households (30.8%). Outbreaks were primarily associated with aquatic products (17.7%) as sources of contamination. The primary transmission pathways were accidental ingestion (20.2%) and multi-pathway transmission (12.1%). Microbiological aetiologies (46.0%), including Vibrio parahaemolyticus, Salmonella ssp., and Staphylococcus aureus, were identified as the main causes of foodborne outbreaks. Furthermore, mushroom toxins (75.0%), poisonous animals (12.5%), and poisonous plants (12.5%) were responsible for deaths from accidental ingestion. This study identified crucial settings and aetiologies that require the attention of both individuals and governments, thereby enabling the development of effective preventive measures to mitigate foodborne outbreaks, particularly in coastal cities.

The delay-shift of the pre-pulse may mislead the determination of its origination and cause problems for the temporal contrast improvement of high-peak-power lasers, especially when the corresponding post-pulse is beyond the time window of the measurement device. In this work, an empirical formula is proposed to predict the delay-shift of pre-pulses for the first time. The empirical formula shows that the delay-shift is proportional to the square of the post-pulse’s initial delay, and also the ratio of the third-order dispersion to the group delay dispersion’s square, which intuitively reveals the main cause for the delay-shift and may provide a convenient routing for identifying the real sources of pre-pulses in both chirped-pulse amplification (CPA) and optical parametric chirped-pulse amplification (OPCPA) systems. The empirical formula agrees well with the experimental results both in the CPA and the OPCPA systems. Besides, a numerical simulation is also carried out to further verify the empirical formula.