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Fatigue crack damage is a primary pavement failure; however, it is an extreme challenge to predict the fatigue damage under high-cycle loading. This paper develops a time–strain superposition principle based on the free volume theory, with a proposed damage density master curve model, to predict high-cycle fatigue damage using multiple low-cycle damage curves. This principle was validated through controlled-strain fatigue experiments, including destructive time-sweep fatigue tests on asphalt binders and repeated direct tension fatigue tests on asphalt mixtures. To address the time and resource-intensive nature of fatigue tests and simulations under high-cycle loading, this study presents an efficient numerical predication of the high-cycle fatigue damage using a viscoelastic damage model and low-cycle simulation results. The results demonstrate the feasibility of predicting high-cycle fatigue damage by employing low-cycle damage results using the time–strain shift model. This offers a potential solution to the computational and experimental prediction of the high-cycle fatigue damage in the viscoelastic bituminous materials. Practical Applications: The deterioration of asphalt pavements performance caused by high-cycle fatigue cracking has been a research focus in the pavement field. However, challenges such as long time for fatigue tests, high material costs, lengthy finite element simulation times, and inaccurate results have been encountered. This study develops a damage density prediction model, which generates damage data under low-cycle through finite element simulation based on bituminous material parameters, to predict the trend of high-cycle fatigue damage density development under reference strains. This approach enables rapid simulation and high-cycle damage prediction for different bituminous materials, significantly saving time for testing and simulation, and assisting practitioners in quickly assessing material fatigue performance. Additionally, after finding the maximum tensile strain of each bituminous layer, users can analyze the damage rate of different bituminous material layers of structures using the predictive model developed in this study, to assist with road maintenance. [ABSTRACT FROM AUTHOR]

The amygdala is an established site for fear memory formation, and clinical studies suggest involvement of hormone signaling cascades in development of trauma-related disorders. While an association of thyroid hormone (TH) status and mood disorders is established, the related brain-based mechanisms and the role of TH in anxiety disorders are unknown. Here we examine the role that TH receptor (TR, a nuclear transcriptional repressor when unbound and a transcriptional activator when bound to TH) may have in mediating the initial formation of fear memories in the amygdala. We identified mRNA levels of TR and other TH pathway regulatory genes, including thyrotropin-releasing hormone (Trh), transthyretin (Ttr), thyrotropin-releasing hormone receptor (Trhr), type 2 iodothyronine deiodinase (Dio2), mediator complex subunit 12 (Med12/Trap230) and retinoid X receptor gamma (Rxrg) to be altered in the amygdala following Pavlovian fear conditioning. Using TH agonist and antagonist infusion into the amygdala, we demonstrated that this pathway is both necessary and sufficient for fear memory consolidation. Inhibition of TH signaling with the TR antagonist 1-850 decreased fear memory consolidation; while activation of TR with T3 (triiodothyronine) resulted in increased memory formation. Using a systemic hypothyroid mouse model, we found that intra-amygdala infusions of T3 were sufficient to rescue deficits in fear memory. Finally, we demonstrated that T3 was sufficient to activate TR-specific gene pathways in the amygdala. These findings on the role of activity-dependent TR modulation support a model in which local TH is a critical regulator of fear memory-related plasticity in the amygdala., Competing Interests: Competing interests: KJR has performed scientific consultation for Acer, Bionomics, and Jazz Pharma; serves on Scientific Advisory Boards for Sage, Boehringer Ingelheim, Senseye, Brain and Behavior Research Foundation, and the Brain Research Foundation, and he has received sponsored research support from Alto Neuroscience. The remaining authors declare no conflict of interest, financial or otherwise. Ethics approval and consent to participate: All studies involving mouse subjects received approval from the McLean Institutional Animal Care and Use Committee (IACUC)., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)