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This study aims to investigate the adverse effects of near-fault ground motions on the long-term development of high-speed railways. In this paper, the ground motions are analyzed based on the Train–Track–Bridge Coupling Braking System (TTBCBS) which has been validated during earthquakes. The effects of earthquakes on the whole system are discussed in depth, focusing on the random nature of earthquakes, the impulsive character of near-fault earthquakes and the effects of different initial speeds on the system behavior. The results show that under random earthquakes, the probability of train derailment gradually increases with the increase of peak ground acceleration (PGA) of earthquakes. When the PGA exceeds 0.2 g, the train is highly susceptible to derailment and the bridge itself may incur damage. When analyzing the nature of pulses of near-fault ground motions, it was found that the responses induced by class B and class C pulses are significantly similar. Meanwhile, the calculated values of derailment coefficients are basically the same when the PGA of class A pulse wave is at 0 g and 0.1 g. This suggests that train braking somewhat mitigates the response induced by near-fault ground motions. Furthermore, the value of improved spectral intensity (SI) for the running safety during earthquakes indicates that the increase in seismic intensity is detrimental to the system. In terms of the effect of train initial speeds on the system during earthquakes, it is observed that the system response reaches the lowest point when the train speed is 250 km/h, which is more favorable to the smooth deceleration of the train. When the train speed is 400 km/h, the system response reaches its maximum value. These research findings provide crucial insights and guidance for seismic safety design and management of high-speed railways. [ABSTRACT FROM AUTHOR]

Highlights Composite structures are frequently exposed to varying hygrothermal environments, which can lead to the deterioration of their mechanical properties. This study explores the effects of hygrothermal aging on the mechanical behaviors of twill‐woven carbon fiber composite laminates, with a particular focus on laminates with flame‐retardant epoxy resin (CF_FR)—a relatively underexplored area. The findings reveal several key insights: (1) CF_FR exhibit more pronounced aging damage compared to those with general epoxy resin (CF_G), primarily due to higher moisture absorption, which results in increased surface swelling and internal delamination. (2) Hygrothermal aging enhances the impact resistance of both types of laminates by increasing peak force, particularly at higher temperatures, thereby reducing impact‐induced damage. (3) CF_FR suffers greater reductions in compressive and compression after impact (CAI) strength following aging, with CAI strength decreasing by 36.3% for flame‐retardant laminates and 14.8% for CF_G after immersion at 70°C. (4) Significant local buckling is observed in the swollen regions of CF_FR under compressive loading, indicating an heightened vulnerability to structural instability after aging. These findings offer valuable insights into the performance of composite materials under prolonged moisture exposure, particularly in safety‐critical applications where both flame retardancy and mechanical integrity are crucial. More aging damage is captured from laminates with flame‐retardant epoxy resin Aging temperatures alleviate LVI induced damage and improve the peak force Compressive and CAI strength are affected after prolonged aging conditions CAI strength of CF_FR decreases by 36.3% after exposure to the 70°C water bath Significant local buckling is observed in CF_FR under compressive loading [ABSTRACT FROM AUTHOR]

Background: Steroid hormones (SH) during pregnancy are associated with the development of gestational diabetes mellitus (GDM). Early and mid-Down syndrome screening is used to assess the risk of Down syndrome in the fetus. It is unclear whether changes in SH during this period can be used as an early predictor of GDM., Methods: This study was a multicenter, longitudinal cohort study. GDM is diagnosed by an oral glucose tolerance test (OGTT) between 24 and 28 weeks of gestation. We measured SH levels at early and mid-Down syndrome screening, respectively. Based on the SH changes, logistic regression analysis was used to construct a prediction model for GDM. Finally, evaluated the model's predictive performance by creating a receiver operating characteristic curve (ROC) and performing external validation., Results: This study enrolled 193 pregnant women (discovery cohort, n = 157; validation cohort, n = 36). SH changes occur dynamically after pregnancy. At early Down syndrome screening, only cortisol (F) (p < 0.05, 95 % CI 4780.95-46083.68) was elevated in GDM. At mid-Down syndrome screening, free testosterone (FT) (p < 0.01, 95 % CI 0.10-0.55) and estradiol (E2) (p < 0.05, 95 % CI 203.55-1784.78) were also significantly elevated. There were significant differences in the rates of change in E2 (Fold change (FC) = 1.3425, p = 0.0072), albumin (ALB) (FC=1.5759, p = 0.0117), and dihydrotestosterone (DHT) (FC=-2.1234, p = 0.0165) between GDM and no-GDM. Stepwise logistic regression analysis resulted in the best predictive model, including six variables (Δweight, ΔF, Δcortisone (E), ΔE2, Δprogesterone (P), ΔDHT). The area under the curve for this model was 0.791, and for the external validation cohort, it was 0.799., Conclusions: A GDM prediction model can be constructed using SH measures during early and mid-Down syndrome screening., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)