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关键词： Snow mechanics   Modified Cam-Clay   Finite strain plasticity   Damage   Healing   Snow traction  

摘要： Reliable prediction of mechanical interactions with hard-packed snow requires constitutive models that capture coupled plasticity, damage, healing, and large deformation. Current constitutive formulations for snow typically neglect either damage-induced degradation or stiffness recovery (healing), particularly under finite-strain conditions relevant to high-speed interactions such as tire-snow contact. While continuum damage-healing models exist for materials such as concrete, asphalt, and polymers, their direct application to snow is hindered by snow's distinct rapid mechanical degradation and healing behaviour. In this contribution, a finite-strain constitutive model is proposed for hard-packed snow, incorporating both damage and healing effects. The elastic response is described by a Neo-Hookean constitutive law, while plastic deformation is governed by a cohesive extension of Modified Cam-Clay plasticity augmented with exponential hardening. Damage evolution is driven by deviatoric plastic deformation, whereas healing is activated by compressive volumetric plastic deformation. The finite element method (FEM) is used, and mesh objectivity is maintained through a non-local regularization approach. Model parameters are calibrated using numerical triaxial and uniaxial tests. Predictive capability is demonstrated through a blade-cutting simulation using a B-spline material point method (MPM) combined with a level-set contact algorithm. The proposed model successfully captures the interplay between shear-induced damage and compression-induced healing, providing a consistent framework for predictive assessment and optimization of winter tire performance.

关键词： Snow mechanics   Modified Cam-Clay   Finite strain plasticity   Damage   Healing   Snow traction  

摘要： Reliable prediction of mechanical interactions with hard-packed snow requires constitutive models that capture coupled plasticity, damage, healing, and large deformation. Current constitutive formulations for snow typically neglect either damage-induced degradation or stiffness recovery (healing), particularly under finite-strain conditions relevant to high-speed interactions such as tire-snow contact. While continuum damage-healing models exist for materials such as concrete, asphalt, and polymers, their direct application to snow is hindered by snow’s distinct rapid mechanical degradation and healing behaviour. In this contribution, a finite-strain constitutive model is proposed for hard-packed snow, incorporating both damage and healing effects. The elastic response is described by a Neo-Hookean constitutive law, while plastic deformation is governed by a cohesive extension of Modified Cam-Clay plasticity augmented with exponential hardening. Damage evolution is driven by deviatoric plastic deformation, whereas healing is activated by compressive volumetric plastic deformation. The finite element method (FEM) is used, and mesh objectivity is maintained through a non-local regularization approach. Model parameters are calibrated using numerical triaxial and uniaxial tests. Predictive capability is demonstrated through a blade-cutting simulation using a B-spline material point method (MPM) combined with a level-set contact algorithm. The proposed model successfully captures the interplay between shear-induced damage and compression-induced healing, providing a consistent framework for predictive assessment and optimization of winter tire performance.

关键词： Distribution timing   Leakage failure   Tolerance stack-up   Valve distribution system  

摘要： Low-speed high-torque water hydraulic motor (LHTWHM) is a key actuator in water hydraulic systems, and leakage in the distribution system can markedly degrade overall motor performance. Experiments and numerical simulations were combined to clarify the leakage failure mechanism in a cam-driven valve distribution system, where the root cause arises from the disorder of distribution timing at the system level. First, the sealing performance of all distribution valves was experimentally examined. Next, the distribution timing of the valve distribution system was analyzed, and the influence of tolerance stack-up along the dimensional chain under permissible manufacturing tolerances was analyzed. The results indicate that tolerance stack-up along the dimensional chain can disrupt the intended distribution timing, thereby creating unintended communication between the high-pressure inlet and the low-pressure outlet within the distribution valve and ultimately causing internal leakage failure. At a residual valve opening of 0.06 mm and a working pressure of 2.7 MPa, the leakage flow rate is approximately 1.22 L/min. The leakage flow rate exhibits an approximately linear increase with the investigated small opening range. A tolerance stack-up along the dimensional chain on the order of tens of micrometers is sufficient to trigger severe internal leakage, whereas targeted dimensional correction of the tappet within the assembly dimensional chain can effectively mitigate this leakage. Furthermore, prior to assembly, residual valve opening can be estimated by integrating machining accuracy inspection with an evaluation of tolerance stack-up along the dimensional chain, providing an actionable route for preventing and rectify this leakage failure mode.

关键词： 3D point cloud   Bolt-loosening monitoring   Occluded-point-removal   PointNet deep learning   Stereo vision   Visibility filters  

摘要： This study presents a novel approach for bolt loosening monitoring in steel structures by integrating stereo vision, CAD-assisted PointNet deep learning, and geometric feature extraction. The 3D point clouds of girder connections under various loosening scenarios are reconstructed by stereo vision system to enable robustness to obstacles and independence from GPS. The bolt feature extraction is performed in two stages: (i) bolt segmentation and (ii) estimation of bolt head angle and loosening length using both geometric and deep learning approaches. In the geometric approach, hexagon fitting and density histogram are proposed to estimate bolt head angles and loosening lengths. In the deep learning approach, a procedure integrating computer-aided design (CAD)-based and visibility filter techniques is developed to simulate stereo-vision effects and generate a diverse and well-labeled databank for training. The PointNet segmentation model separates bolts from other structural elements, while the PointNet classification models estimate bolt features. To enhance model performance, advanced 3D point cloud processing techniques such as representative orientation alignment, K-means clustering, and best-fitting rectangle are developed. Experimental validation on bolt connections demonstrates that the geometric approach is straightforward and efficient, while the deep learning approach achieves higher overall accuracy.

关键词： Oncolytic newcastle disease virus   Pyrimidinosome   Pyrimidine synthesis   GOT1   CAD   NAD+/NADH  

摘要： Oncolytic viruses selectively infect and kill tumor cells, but the metabolic adaptations that support their replication remain incompletely understood. Here, using oncolytic Newcastle disease virus (NDV) as a model, we identify glutamic-oxaloacetic transaminase 1 (GOT1) as a key metabolic enzyme required for efficient viral replication through its dual role in de novo pyrimidine synthesis. In NDV-infected tumor cells, GOT1 promotes aspartate production through the malate-aspartate shuttle to support pyrimidine biosynthesis, while also maintaining NAD⁺/NADH homeostasis to activate the mTOR-S6K-CAD signaling axis and further enhance pyrimidine synthesis. These GOT1-dependent metabolic and signaling adaptations sustain pyrimidine biosynthesis and viral replication. In addition, NDV infection promotes pyrimidinosome assembly, and GOT1 functions as a pyrimidinosome-associated component. Together, these findings reveal a mechanism by which oncolytic NDV rewires host pyrimidine metabolism to support its replication and provide a rationale for metabolic modulation of oncolytic virotherapy.

关键词： AD   Alzheimer’s disease   AHI   Apnea, hypopnea index   ALAN   Artificial light at night   BMI   Body mass index   BZD   benzodiazepine hypnotics   CAD   Coronary artery disease   CBT-I   Cognitive behavioral therapy for insomnia   CI   Confidence interval   COMISA   Comorbid insomnia and sleep apnea   COPD   Chronic obstructive pulmonary disease   CPAP   Continuous positive airway pressure   CREB   cAMP response element-binding protein   CVA   Cerebrovascular accident   CVD   Cardiovascular disease   CVDs   Cardiovascular diseases   DB   Decibel   DORAs   Dual orexin receptor antagonists   EEG   Electroencephalography   EPSPs   Excitatory postsynaptic potentials   FDA   U.S. Food and Drug Administration   HF   Heart failure   HR   Hazard ratio   HRT   Hormone replacement therapy   HTN   Hypertension   IL-6   Interleukin-6   LLSHF   Late-Life Sleep Health Framework   Lnight   Nighttime equivalent continuous sound level noise metric   LTP   Long-term potentiation   MADs   Mandibular advancement devices   MI   Myocardial infarction   MR   Mendelian randomization   MrOS   Osteoporotic Fractures in Men study   MSLT   Multiple Sleep Latency Test   N1   NREM sleep stage 1   N2   NREM sleep stage 2   N3   NREM sleep stage 3 slow-wave sleep   NREM, Non   rapid eye movement sleep   NREM1, Non   rapid eye movement sleep stage 1   NREM2, Non   rapid eye movement sleep stage 2   O-GlcNAc   O-linked β-N-acetylglucosamine   OGA   O-GlcNAcase   OGT   O-GlcNAc transferase   OR   Odds ratio   OSA   Obstructive sleep apnea   OSAS   Obstructive sleep apnea syndrome   PAP   Positive airway pressure   PLMD   Periodic limb movement disorder   PLMI   Periodic limb movement index   R   Coefficient of determination   RBD   REM sleep behavior disorder   RDI   Respiratory disturbance index   REM   Rapid eye movement sleep   RLS   Restless legs syndrome   ROS   Reactive oxygen species   RR   Relative risk   RSTLS   Sleep restlessness   SCN   Suprachiasmatic nucleus   SD   Standard deviation   SDB   Sleep-disordered breathing   SE   Sleep efficiency   SIRT1   Sirtuin 1   SOL   Sleep-onset latency   SWA   Slow-wave activity   SWS   Slow-wave sleep   TIA   Transient ischemic attack   TNF-α   Tumor necrosis factor alpha   TST   Total sleep time   UK   United Kingdom   WASO   Wake after sleep onset   WHO   World Heal  

摘要： Population aging accelerates globally, increasing sleep-related complaints among older adults. These disorders substantially impact cognitive function, physical health, and quality of life. This narrative review examines age-related changes in sleep architecture, alterations in circadian rhythm, common sleep disorders, and modifiable behavioral factors in older populations. We searched PubMed, Web of Science, and Google Scholar through December 2025 for studies involving adults aged ≥ 65 years focusing on sleep patterns, architecture, circadian rhythms, and disorders. Normal aging involves reduced slow-wave and REM sleep, decreased sleep efficiency, increased fragmentation, and circadian amplitude dampening. However, pathological sleep disorders affect substantial proportions: insomnia (20–40%), obstructive sleep apnea (>30%), restless legs syndrome, and REM sleep behavior disorder. Chronic sleep disturbances are associated with elevated risks of cognitive decline, cardiovascular disease, falls, frailty, and mortality. Evidence supports cognitive-behavioral therapy as a first-line insomnia treatment. Emerging dual orexin receptor antagonists show promise with favorable safety profiles. Continuous positive airway pressure remains the standard of care for obstructive sleep apnea, though adherence challenges persist. Sleep may represent a modifiable healthy aging determinant. Distinguishing normal age-related changes from pathological disorders can enable appropriate management. Future priorities include longitudinal studies in the oldest-old, investigations of circadian mechanisms, implementation of behavioral interventions, and equity-focused research across diverse populations.

关键词： Hypertrophic cardiomyopathy   Coronary microvascular dysfunction   Magnetic resonance imaging   Machine learning   Radiomics   HCM   Hypertrophic cardiomyopathy   CMD   Coronary microvascular dysfunction   CMR   Cardiac magnetic resonance   IMR   Microcirculatory resistance index   FFR   Fractional flow reserve   ECG   Electrocardiograms   AUC   Area under curve   ROC   Receive operating characteristic   CFVR   Coronary flow velocity reserve   MPR   Myocardial perfusion reserve   MPRI   Myocardial perfusion reserve index   TR   Epetition time   TE   Echo time   FOV   Field of view   RF   Random forest   CAD   Coronary artery disease   EF   Ejection fraction   EDV   End-diastolic volume   EDVI   End-diastolic volume index   ESV   End-systolic volume   ESVI   End-systolic volume index   SV   Stroke volume   SVI   Stroke volume index   CO   Cardiac output   CI   Cardiac index   LVM   Left ventricular mass   LVMI   Left ventricular mass index   MIVS   Maximum interventricular septum thickness   MWT   Maximum wall thickness   ROI   Region of interest   ICC   Intraclass correlation coefficient   ROC   Receiver operating characteristic   DCA   Decision curve analysis   AUC   Area under the curve   ML   Machine learning   SVM   Support vector machine   CCTA   Coronary computed tomography angiography   ECV   Extracellular volume fraction  

摘要： In hypertrophic cardiomyopathy (HCM), detection of coronary microcirculatory dysfunction (CMD) usually relies on contrast-enhanced cardiac magnetic resonance (CMR). This study sought to develop a practical non-contrast radiomics model to identify CMD, minimizing reliance on contrast agents.

关键词： CAM   Complementary therapies   Educational models   Rank-sum test   Self-perception  

摘要： Graduate trainees are poised to shape the future of integrative medicine as incoming providers, policy informants, and consumers. Identifying both personal and professional factors underlying trainees’ familiarity with and perceptions of traditional complementary and integrative medicine (TCIM) is critical for advancing holistic, evidence-based care. Prior studies have explored TCIM beliefs among specific trainee populations (e.g., medical students) and compared perceptions between cohorts of clinical and academic trainees. Little is known about how self-identified training orientation (i.e., science vs. practice) relates to TCIM perceptions across disciplines. The present study aims to clarify whether objective (i.e., training program focus) and subjective (i.e., self-identified training orientation) aspects of professional training differentially inform familiarity with and perceptions of TCIM among the next generation of healthcare stakeholders.

关键词： Tropical cyclones   Post-tropical cyclones   Extreme rainfall   Climate change   Storyline analysis  

摘要： Tropical and post-tropical cyclones (TCs and PTCs) can produce severe hazards, making it critical to robustly assess how their characteristics may change under future climate warming. This study examines ten 2022–2024 North Atlantic storms using storyline ensemble simulations with the variable-resolution Community Atmosphere Model (CAM) at 14 km and 28 km, and the Advanced Research Weather Research and Forecasting (WRF) model at 14 km resolution over the North Atlantic. Future warming scenarios of +2 K, +3 K, and +4 K in global mean surface temperature relative to preindustrial levels are considered. Across all model configurations, climate warming leads to a robust increase in storm intensity and inner-core rainfall, along with a consistent delay in extratropical transition completion. Differences in mean and extreme inner-core 3-hourly rainfall rates among model configurations are statistically not significant, suggesting that the projected changes are robust across models with different resolutions and physical designs. When treating the experiments using different configurations as a multi-model ensemble, the mean inner-core 3-hourly rainfall rate increases by 3.8 ± 1.0% K⁻¹, and the 95th, 99th, and 99.9th percentiles of rainfall rate increase by 3.2 ± 1.1% K⁻¹, 6.1 ± 0.9% K⁻¹, and 7.8 ± 0.7% K⁻¹, respectively, relative to present-day conditions. During the post-tropical phase, the mean and extreme rainfall increase at a higher rate than when calculated across both TC and PTC phases, underscoring the importance of assessing future PTC hazards under a warming climate.

关键词： Coronary computed tomography angiography   Plaque burden   Coronary Artery Disease-Reporting and Data System   Method agreement   Segment involvement score  

摘要： To assess the agreement of the three methods of coronary plaque burden assessment approved by the Coronary Artery Disease-Reporting and Data System classification (CAD-RADS 2.0): coronary artery calcium (CAC) testing, segment involvement score (SIS), and visual estimate.