Subjects: Nursing >> Nursing submitted time 2023-04-24
Abstract： Objective To investigate the effect of Traditional Chinese Medicine (TCM)characteristic nursing combined with Liuzijue Qigong on rehabilitation of cardiac function in patients with chronic heart failure (CHF). Methods A total of 80 CHF patients were randomly divided into the study group and control group, with 40 cases in each group. All patients received routine drug therapy during hospitalization. Patients in the control group were give routine care including work-rest schedule, dietary guidance, psychological care and daily care. Patients in the study group were given TCM characteristic nursing combined with Liuzijue Qigong in addition to routine care. The Minnesota Living with Heart Failure Questionnaire (MLHFQ) was used to measure the patient quality of life, and outcomes of left ventricular ejection fractions (LVEF) and 6-minute walking test were measured and compared between two groups. Results Longer 6MWD and higher LEVF were reported in both groups at three months of intervention, and patients in the study group achieved better outcomes of 6MWD and higher LEVF compared with those in the control group（P＜0.01）. The score of MLHFQ decreased in both groups at three months of intervention, and score of MLHFQ in the study group was lower than that in the control group (P＜0.01). Conclusion The TCM characteristic nursing combined with Liuzijue Qigong is potentially effective to improve the rehabilitation of cardiac function and long-term quality of life in CHF patients.
Peer Review Status:
Awaiting Review
Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-28 Cooperative journals: 《中国科学院院刊》
Abstract： The Tibetan Plateau is the source zone of major rivers, which provide water resources for more than 2 billion people downstream. Compared with runoff, riverine sediment load is considered as a more sensitive variable in response to climate and land surface process changes, and also as an important index to quantify regional land degradation and soil resource changes. In this study, 8 major rivers originated in the Tibetan Plateau, including Yerqiang River, Shule River, Heihe River, Yarlung Tsangpo River, Nujiang River, Yellow River, Yangtze River, and Lancang River, were selected to study the variation of sediment load in the source zone or upper reaches. Firstly, the general amount and spatial variation of runoff and sediment load of these rivers were explored. Secondly, the changes of riverine sediment load in recent decades (1960–2017) were analyzed, with the spatial and temporal variations of sediment load compared to climate (temperature, precipitation) and land surface process (glacier, frozen soil, vegetation cover) factors. Thirdly, the uncertainty of sediment load variation associated with interaction of multi-factors was discussed. Finally, the significant impacts of sediment load variation on the ecological environment and the safety of hydropower projects was pointed out with typical cases. Nowadays, the scarcity of hydrometeorological data is a major challenge to understand the variation of riverine sediment load from the Tibetan Plateau and assess the impacts. It is urgent to strengthen observation and modeling studies to reveal the complex mechanism of sediment transport changes, so as to provide scientific basis for the sustainable utilization of water and soil resources on the Tibetan Plateau and the downstream water resources management, so as to serve the national ecological security.
Subjects: Computer Science >> Integration Theory of Computer Science submitted time 2018-11-29 Cooperative journals: 《计算机应用研究》
Abstract： Convolutional neural network's high computational complexity often obstructs its widespread adhibition in real-time and low-power applications. The existing software implementation solution cannot meet the demands of the convolutional neural network for computing performance and power consumption. The traditional FPGA-oriented convolutional neural network construction method has problems such as complicated process, long cycle and small optimization space. For these problems, according to the characteristics of convolutional neural network calculation pattern, this paper proposed a design and scheduling mechanism of convolutional neural network accelerator for cloud FPGAs. By using for reference the design which based HLS technology, imported the cyclic cutting parameters and rearranged the convolution layer circularly. Then constructed the network in a modular way, and extended parameters to further optimize the accelerator processing process. Summarized the scheduling scheme by analyzing the characteristics of system tasks and resources, and optimized its design from two aspects of control and data flow. In comparison with other existing work, the proposed design provided a solution with flexibility, low energy consumption, high energy efficiency and performance. The design also discussed the efficient universal scheduling scheme of the accelerator. Experimental results show that compared with the CPU implementation, this design achieves 8.84 times speedup of AlexNet, while the power consumption of Cifar implementation is only 24.96% of it. Compared with the CPU+GPU to achieve 6.90 times speedup of Cifar, although the performance of large-scale network is inferior to the GPU, but the minimum power consumption is only 14.98%. This design achieves the maximum acceleration of 6.29 times in comparison with the existing research results. Compared to the accelerators generated for large platforms, even if it only has comparable performance but with a lower clock frequency.
Subjects: Library Science，Information Science >> Library Science submitted time 2016-01-25
Abstract：通过调研国际主要机构的战略规划，归纳出Data Curation 在管理、资源建设、技术基础设施方面存在的主要挑战。针对这些挑战，从战略规划、数据评估与遴选政策、关键技术、审计和认证四方面全面回顾了国际Data Curation 研究、实践的发展情况。分析图书馆在大数据科研环境下可能参与科研数据保管的领域，为图书馆在Data Curation活动中谋求发展机会。
Peer Review Status:Awaiting Review
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