Nursing intervention treatment of patients with syncope

总结了门诊换药室患者发生晕厥的护理干预措施，包括心理干预、疼痛干预、体位干预等。认为护理人员必须了解晕厥发生的原因和机理，认真评估病情，掌握病史，以便有针对性地采取护理干预措施，有效防止晕厥的发生，这对保障患者安全、提高护理服务质量有着积极的意义。The nursing intervention measures of syncope in outpatient dressing room were summarized, including psychological intervention, pain intervention, postural intervention and so on. Nurses should realize the causes and mechanisms of syncope, assess the condition carefully, and master the history of the disease, so that targeted nursing intervention measures could be taken, to ensure patient safety and improve the quality of nursing servic

Projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks

We study projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks. We relax some limitations of previous work, where projective-anticipating and projective-lag synchronization can be achieved only on two coupled chaotic systems. In this paper, we can realize projective-anticipating and projective-lag synchronization on complex dynamical networks composed by a large number of interconnected components. At the same time, although previous work studied projective synchronization on complex dynamical networks, the dynamics of the nodes are coupled partially linear chaotic systems. In this paper, the dynamics of the nodes of the complex networks are time-delayed chaotic systems without the limitation of the partial-linearity. Based on the Lyapunov stability theory, we suggest a generic method to achieve the projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random dynamical networks and find both the existence and sufficient stability conditions. The validity of the proposed method is demonstrated and verified by examining specific examples using Ikeda and Mackey-Glass systems on Erdos-Renyi networks.Comment: 14 pages, 6 figure

Emergence, Evolution and Scaling of Online Social Networks

This work was partially supported by AFOSR under Grant No. FA9550-10-1-0083, NSF under Grant No. CDI-1026710, NSF of China under Grants Nos. 61473060 and 11275003, and NBRPC under Grant No. 2010CB731403. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD