BackgroundEpidemiological data on the prevalence of headache in nursing staff in Mainland China are lacking. We therefore performed a study to assess the prevalence of headache, and factors associated with headaches, in nursing staff in three hospitals in North China.MethodsStratified random cluster sampling was used to select 1102 nurses from various departments in three hospitals. A structured questionnaire was used to collect epidemiological data, headache characteristics and associated factors.ResultsThe response rate was 93.0%. Among nursing staff, the 1-year prevalence of primary headache disorders was 45.3%, of migraine 14.8% (migraine with aura 3.4%, migraine without aura 11.4%), of tension-type headache (TTH) 26.2%, of chronic daily headache (CDH) 2.7%. Multivariate analysis showed that seniority (≥5 years) was a risk factor for migraine (OR 2.280), obesity (BMI ≥ 25) was a risk factor for TTH and CDH (OR 1.684 and 3.184), and age (≥40 years) was a risk factor for CDH (OR 8.455). Nurses working in internal medicine were more likely to suffer CDH than those in other departments. Working a greater number of night shifts was also associated with increased prevalence of headache.ConclusionThe prevalence of primary headache disorders in nurses is higher than that in the general population in China, and occupational factors may play an important role. Therefore, the prevalence of headache in nurses should be a focus of attention, and coping strategies should be provided. Such measures could contribute to improving patient care.

No abstract

No abstract

Multi-tier shuttle warehousing systems are increasingly popular because of their high flexibility and robustness. These systems consist of a multi-tier shuttle sub-system that controls horizontal movement and a lift sub-system that manages vertical movement. The combination of shuttles and lifts undertakes inbound/outbound tasks instead of the stacker crane in conventional automated storage and retrieval systems. Scheduling different devices to reduce expected cycle time is an important concern. Thus, we propose a time sequence mathematical model of task operation on the basis of the movement characteristics of shuttles and lifts. The task scheduling problem between shuttles and lifts is converted into an assembly line parallel job problem by analysing the mathematical model, which generates the scheduling task queue model in the specified time window. In addition, a Pareto optimal based on an elitist non-dominated sorting genetic algorithm is adopted to solve the multi-objective optimisation function in the task scheduling problem. Finally, we illustrate the findings of the study through a practical example. Results show that the optimisation scheduling solution can reduce the total lift idle time and the total shuttle waiting time. Furthermore, it can improve warehousing efficiency and lower operation costs.

Traditional fisheye views for exploring large graphs introduce substantial distortions that often lead to a decreased readability of paths and other interesting structures. To overcome these problems, we propose a framework for structure-aware fisheye views. Using edge orientations as constraints for graph layout optimization allows us not only to reduce spatial and temporal distortions during fisheye zooms, but also to improve the readability of the graph structure. Furthermore, the framework enables us to optimize fisheye lenses towards specific tasks and design a family of new lenses: polyfocal, cluster, and path lenses. A GPU implementation lets us process large graphs with up to 15,000 nodes at interactive rates. A comprehensive evaluation, a user study, and two case studies demonstrate that our structure-aware fisheye views improve layout readability and user performance.