IE University

Hepatitis B virus (HBV) infection remains a public health concern in China, especially among middle-aged and older adults. Accurate prediction models can assist in early detection and targeted interventions. However, predicting HBV infection using population-level data is challenging due to its relatively low prevalence, which creates highly imbalanced datasets that undermine the performance of traditional predictive models. This study aimed to develop a machine learning model to predict HBV infection using an ensemble approach designed to handle class imbalance. Our study conducted a cross-sectional analysis of participants aged 45 and above from the China Health and Retirement Longitudinal Study 2011. To address the class imbalance in HBV infection, the synthetic minority oversampling technique (SMOTE) was employed. We developed machine learning models, including logistic regression (LR), support vector machine (SVM), random forest (RF), gradient boosting machine (GBM), adaptive boosting classifier (AdaBoost), extreme gradient boosting (XGBoost), and stacking ensemble model (SEM), to predict HBV infection and identify predictors. Model performance was evaluated using area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (AP), accuracy, sensitivity, specificity, precision, F1 score, and Brier score. Shapley additive explanation (SHAP) analysis was applied to interpret each predictor’s individual contribution and direction to the model’s output. In the final analysis, 8,954 participants were included, among whom 0.64% self-reported HBV infection, confirming highly imbalanced data. The SEM model achieved balanced performance (AUC: 87.93%, AP: 18.85%, F1: 15.66%, Brier score: 0.03). Machine learning models also identified several new important predictors, including birth season, depression, and knee height. An ensemble machine learning model incorporating techniques to manage data imbalance can accurately predict HBV infection in Chinese middle-aged and older adults. The novel predictors we identified offer new insights into HBV risk in ageing populations and support the development of more targeted prevention strategies.

The efficient propulsion of flexible swimmers in unsteady flow is a fundamental problem in fluid–structure interaction (FSI), governed by the physical trade-off between maximizing propulsive efficiency and maintaining hydrodynamic stability. This study integrates high-fidelity computational fluid dynamics simulations with high-resolution kinematic tracking to quantify the response mechanisms of four biological prototypes with distinct geometric characteristics in a controlled Kármán vortex street. Our results reveal a morphology-driven spectrum of interaction modes comprising three distinct physical regimes: Vortex synchronization (efficiency-optimization), low-vorticity navigation (stability-prioritization), and hydrodynamic instability (physical failure). In the synchronization regime, we quantify a characteristic non-linear saturation in tail-beat frequency. This kinematic signature is consistent with a flow-induced resonance state, where phase-locking maximizes momentum extraction from the environment. In contrast, laterally compressed bluff-body prototypes are highly susceptible to destabilizing yawing moments, necessitating a spatial avoidance strategy to mitigate the risk of biomechanical failure. This work quantifies how geometric constraints dictate the physical boundary conditions for the FSI mechanism, providing a critical mechanical framework for the multi-mode adaptive control of bio-inspired vehicles in complex turbulent environments.

ABSTRACT Apologies are widely regarded as a crucial step in reconciliation, yet they are not always offered voluntarily. When transgressors do not apologize, victims may demand an apology to restore their sense of power. In this research, across four studies (total N = 869) we investigate how transgressors react when faced with a solicited apology. We propose that being explicitly asked to apologize decreases transgressors' feelings of power and increases transgressors' anger towards victims, ultimately leading to increased avoidance of victims. The pilot study and Study 1, utilizing a micro‐narrative approach, suggested that while victims feel better after soliciting an apology, transgressors feel worse and seek to avoid the victim. In Study 2, using an experimental design, we found support for our full proposed model—transgressors have increased intentions to avoid the victim after being asked to apologize, mediated by the feeling of less power, but more anger. Study 3 replicated the significant serial mediation, this time using a dictator game design in which the real‐time behavioral reactions of participants were examined. In Study 4, we tested whether transgression responsibility represents a boundary condition for the proposed serial mediation process. Together, these findings challenge the prevailing assumptions about the positive role of apologies and reveal a paradox: soliciting apologies may undermine the very reconciliation it aims to achieve, particularly when responsibility is ambiguous, contested, or not fully acknowledged by the transgressor.

Aluminum alloy tube–concrete composite columns have received increasing attention owing to their high strength-to-weight ratio and superior corrosion resistance compared with conventional steel–concrete composite columns. In this study, a refined finite element model is established to investigate the axial compression behavior of aluminum alloy tube–concrete long columns. The results indicate that the axial bearing capacity and deformation characteristics are strongly governed by the confinement effect provided by the aluminum alloy tube, which varies significantly with different cross-sectional configurations. Circular and square aluminum alloy tubes exhibit distinct confinement mechanisms, leading to different stress distributions and damage evolution patterns in the core concrete. Enhanced confinement effectively improves the utilization of concrete strength and delays local buckling of the aluminum alloy tube, thereby contributing to an increase in axial bearing capacity. Furthermore, parametric analyses clarify the combined influence of material properties and geometric parameters on the confinement efficiency and overall axial compression performance of the composite columns.