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Hibernation, a survival strategy in mammals for extreme climates, induces physiological phenomena such as ischemia–reperfusion and metabolic shifts that hold great potential for advancements in modern medicine. Despite this, the molecular mechanisms underpinning hibernation remain largely unclear. This study used RNA‐seq and Iso‐seq techniques to investigate the changes in liver transcriptome expression of Rhinolophus pusillus during hibernation and active periods, as well as under different microhabitat temperatures. We identified 11 457 differentially expressed genes during hibernation and active periods, of which 395 showed significant differential expression. Genes associated with fatty acid catabolism were significantly upregulated during hibernation, whereas genes related to carbohydrate metabolism and glycogen synthesis were downregulated. Conversely, immune‐related genes displayed differential expression patterns: genes tied to innate immunity were significantly upregulated, while those linked to adaptive immunity and inflammatory response were downregulated. The analysis of transcriptomic data obtained from different microhabitat temperatures revealed that R. pusillus exhibited an upregulation of genes associated with lipid metabolism in lower microhabitat temperature. This upregulation facilitated an enhanced utilization rate of triglyceride, ultimately resulting in increased energy provision for the organism. Additionally, R. pusillus upregulated gluconeogenesis‐related genes regardless of the microhabitat temperature, demonstrating the importance of maintaining blood glucose levels during hibernation. Our transcriptomic data reveal that these changes in liver gene expression optimize energy allocation during hibernation, suggesting that liver tissue adaptively responds to the inherent stress of its function during hibernation. This study sheds light on the role of differential gene expression in promoting more efficient energy allocation during hibernation. It contributes to our understanding of how liver tissue adapts to the stressors associated with this state. [ABSTRACT FROM AUTHOR]

As an important data source of complex product design and manufacturing, 3D assembly model has accumulated a large number of 3D assembly models in various manufacturing industries under the background of widely used digital design technology. In order to make better use of reusable common structure information about 3D assembly model, reduce repetitive labor, and shorten product development cycles, a common structure mining method of 3D assembly models was proposed. Firstly, based on the attribute neighbourhood diagram of individual parts of the 3D assembly model, the information of the assembly feature attributes is maintained and the nonassembly feature attributes are simplified to form an attributed assembly feature neighbourhood diagram; then, based on the assembly relationship between the parts of the 3D assembly model, the attributed assembly feature neighbourhood diagrams of the parts are combined to form a 3D assembly model attribute neighbourhood diagram. Secondly, the common structure of the 3D assembly model is extracted by the frequent subgraph mining algorithm. Finally, a set of fixture models is used to verify the results, which show that this 3D assembly model common structure mining method can accurately and effectively explore the common structure information of the product and has good results. [ABSTRACT FROM AUTHOR]

3D model retrieval is increasingly becoming a hot topic in today's research. The existing model retrieval methods are limited to the retrieval between similar models, while the matching retrieval for models with assembly relationships is neglected. They cannot realize the prediction of the virtual assembly and make the assemblers to spend extensive time detecting when there are assembly errors in the model. This work proposes a 3D assembly model retrieval method for multiassembly interface, which can retrieve the parts or subassemblies that can be assembled with the input model. In this work, a method for the reuse of the 3D assembly mode is also provided. The method here involves a series of steps, which includes an attribute adjacency graph to express the 3D assembly models, followed by the definition of a conjugated subgraph, and the serialization of the vertices of the graph for the Atlas of the assembly model. Finally, the frequent subgraph mining method is improved, and the 3D assembly model that satisfies the multiassembly interface is extracted. The article claims through the obtained results that this method not only allows the performance of the 3D assembly model retrieval of multiassembly interfaces but also the extraction of the 3D model required by designers, improving, at the same time, the product design efficiency. [ABSTRACT FROM AUTHOR]

Dynamic epigenetic changes during hibernation occur in some hibernating rodents, but these changes are poorly understood in hibernating bats. Populations of the greater horseshoe bat (Rhinolophus ferrumequinum) in north China hibernate and provide an opportunity to study how epigenetic markers and modifiers differ in the active and torpid states of a chiropteran. We used fluorescence-labeled methylation-sensitive amplified polymorphism (F-MSAP) and qRT-PCR techniques to determine changes in the global DNA methylation levels and mRNA expression levels of methylation-related proteins. These included DNA methyltransferase (DNMTs), methyl-CpG-binding proteins (MBPs, including MBDs, UHRFs, and zinc-finger protein family) in active and torpid R. ferrumequinum. In the torpid state, both the relative global methylation and the relative mRNA expression levels of some DNMTs and MBPs, including dnmt3b and zbtb4 , increased significantly compared to the expression levels of these in the active state. These changes may involve methylation or assist in regulation of a particular subset of genes according to hibernation status. This indicates that epigenetic mechanisms may exist and facilitate the hibernation process of R. ferrumequinum. [Display omitted] • The global DNA methylation level increased in torpid state. • Some MBPs showed higher mRNA expression levels in hibernation. • Epigenetic marker and modifiers may facilitate the hibernation of the great horseshoe bats. [ABSTRACT FROM AUTHOR]

• Develop an electromechanical model to couple vehicle-track and traction drive systems. • Wheel polygon wear evolution analysis is performed including effects of interharmonic. • The pulsating torque with specific interharmonic excites the wheelset resonance at 70 km/h. The formation and development of wheel polygon wear (WPW) present significant challenges to the safety of railway vehicle operations. It is widely accepted that WPW occurs due to the mechanical vibration within the wheel-rail system. The output torque produced by the traction motor acts as the primary power source for the vehicle's movement. The pulsating torque, resulting from interharmonics can directly impact the wheelset's dynamic behavior, contributing to the occurrence of WPW. However, the precise mechanism by which interharmonics affect WPW remains incompletely understood. Therefore, this paper aims to establish the link between interharmonics originating from the electric traction drive system and the wheelset vibration. A comprehensive WPW evolution model that incorporates an electromechanical coupling model and a wheel wear calculation model is developed. This model allows to elucidate the intricate mechanism by which interharmonics impact WPW. The analysis indicates that when the locomotive is running at 70 km/h, the pulsating torque generated by the | 5 f − 7 f 0 | interharmonic can excite the 1st-order bending mode of the wheelset. This excitation triggers wheelset resonance, which ultimately leads to the development of 20th-order WPW. [ABSTRACT FROM AUTHOR]

The pantograph–catenary system (PCS) vibration causes the pantograph–catenary contact force (PCCF) to fluctuate, deteriorating current collection quality and damaging the electrical equipment. The active pantograph is one of the most promising methods for suppressing PCS coupling vibration and improving the current collection quality of high-speed trains. This paper first summarizes the research progress of five critical links in the active pantograph, including PCS modeling, control algorithm, hardware support, and HIL test verification. Then, the impact of the PCS model on numerical simulation accuracy and calculation time, the pros and cons of different control algorithms, and the execution mechanism selection are discussed. Finally, the active pantograph's future development trend and research direction are prospected, such as model optimization, algorithm design, and signal correction. The analysis results show that establishing the PCS model should consider the representation of system dynamics and calculation efficiency. Control targets need to reflect the current collection quality comprehensively, and the measurement system needs to minimize the effect of locomotive disturbances on the observation results. The actuator structure needs to execute the control commands efficiently and quickly without affecting the operation of the raising mechanism. These factors, together with the real-time control algorithm, determine the practical effectiveness of the active pantograph. [ABSTRACT FROM AUTHOR]

To reduce exposure to risky and challenging driving situations and prolong mobility and independence, older drivers self-regulate their driving behavior. But self-regulation can be challenging because it depends on drivers’ ability to assess their limitations. Studies using self-reports, survey data, and hazard and risk perception tests have shown that driving behavior feedback can help older drivers assess their limitations and adjust their driving behavior. But only limited work has been conducted in developing feedback technology interventions tailored to meet the information needs of older drivers, and the impact these interventions have in helping older drivers self-monitor their driving behavior and risk outcomes. The vehicles of 33 drivers 65 years and older were instrumented with OBD2 devices. Older drivers were provided access to customized web-based Trip Diaries that delivered post-trip feedback of the routes driven, low-risk route alternatives, and frequency of their risky driving behaviors. Data were recorded over four months, with baseline driving behavior collected for one month. Generalized linear mixed effects regression models assessed the effects of post-trip feedback on the route risk and driving behaviors of older drivers. Results showed that post-trip feedback reduced the estimated route risk of older drivers by 2.9% per week, and reduced their speeding frequency on average by 0.9% per week. Overall, the Trip Diary feedback reduced the expected crash rate from 1 in 6172 trips to 1 in 7173 trips, and the expected speeding frequency from 46% to 39%. Thus providing older drivers with tailored feedback of their driving behavior and crash risk could help them appropriately self-regulate their driving behavior, and improve their crash risk outcomes. [ABSTRACT FROM AUTHOR]