A5101686928- Evacuation and Crowd Dynamics
- Fire dynamics and safety research
- Air Quality and Health Impacts
- Birth, Development, and Health
- Education, Safety, and Science Studies
- BIM and Construction Integration
- Pregnancy and preeclampsia studies
- Fire effects on ecosystems
- Advanced Manufacturing and Logistics Optimization
- Extraction and Separation Processes
- Vehicle Routing Optimization Methods
- Transportation Planning and Optimization
- Health, Environment, Cognitive Aging
- Fatty Acid Research and Health
- Urban Green Space and Health
- Noise Effects and Management
- Reservoir Engineering and Simulation Methods
- Maritime Ports and Logistics
- Traffic Prediction and Management Techniques
- Oil and Gas Production Techniques
- Traffic control and management
- Innovation in Digital Healthcare Systems
- Disaster Management and Resilience
- Cultural and Historical Studies
- Flame retardant materials and properties
Fujian Medical University
2024-2025
Union Hospital
2024-2025
University of Maryland, College Park
2023-2025
University of Florida
2021
The impacts of early-life tobacco smoke exposure, including exposure during pregnancy and the initiation smoking childhood adolescence, on cognitive decline risk dementia in later life have not been investigated. We used data from UK Biobank (UKB) to assess utero age at which was initiated. Cox proportional-hazards regression models were employed gauge relationships between both adulthood. adjusted for potential confounding factors, age, gender, race, household income, alcohol consumption...
Abstract Introduction Stroke is a life-threatening condition that causes major medical burden globally. The currently used methods for the prevention or prediction of stroke have certain limitations. Exposure to tobacco in early life, including smoking during adolescence and maternal pregnancy, can affect adolescent development lead several negative outcomes. However, association between early-life exposure not known. Methods In this prospective cohort study, analyses involving pregnancy age...
AbstractTraffic shockwaves demonstrate the formation and spreading of traffic fluctuation on roads. Existing methods mainly detect their propagation by estimating density flow, which presents weaknesses in applications when data is only partially or locally collected. This paper proposed a four-step data-driven approach that integrates machine learning with features to estimate speeds using partial vehicle trajectory data. Specifically, we first denoise speed derived from Fast Fourier...