[A preliminary study of piglet intraperitoneal bleeding model and electrical impedance tomography monitoring].
Department of Urology, Tangdu Hospital, Fourth Military Medical University, Xi'an 710038, China.Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi 03/2009; 26(1):10-3.
Piglets having each a body weight of 20-30 kg and an abdominal perimeter like human's were used in the experiment. Being guided by ultrasound, we stabbed the piglet's abdomen, placed a catheter on the liver's lower margin, then injected the anticoagulated blood through the catheter by electrical infusion pump with constant speed respectively, and monitored the whole process by EIT. We observed the image change, using Ultrasound and CT to examine the area of blood injection after the end of monitoring,and we dissected to check the result of observations. The results reveal: (1) Ultrasound, CT and dissection are all able to find out a large amount of blood in piglet's abdominal cavity; (2) The pixel value of EIT target area decreases with the increase of blood, and the change in impedance image can be obviously observed. Therefore, this animal model is suitable for simulating intraperitoneal bleeding, and the speed of bleeding therein can be controlled. We can get a limpid image when EIT is used for monitoring the intraperitoneal bleeding simulated by this animal model.
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ABSTRACT: Many regions of China have abundant straw resources for industrial utilization. Although there has been an emerging trend of using straw resources for bioenergy in China, there is little study of the dynamics of straw utilization in industry. This study develops an agent-based model to simulate the dynamics of industrial utilization of redundant straw in a virtual area of 10,000 square kilometers. The dynamics of three typical industrial straw utilization technologies applied in enterprise are simulated: bioethanol, power generation, and paper making. Four scenarios are established to compare changes in the total scale and proportion of enterprise caused by collection technologies and subsidy to bioethanol. The results show that the final industrial consumption of straw is approximately 60% in the basic scenario, whereas the highest proportion is almost 90% in the other scenarios. The largest share of straw is consumed by power generation in scenarios with low bioethanol subsidies and is close to bioethanol in scenarios with high bioethanol subsidies. The industrial structure varies due to changes in collection technologies and bioethanol subsidies in the scenario analysis. The industrialization of bioethanol is also determined by technological maturity time. Some policy implications to improve industrial straw utilization are discussed based on the results.
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