Aim: To observe the rats’ learning and memory acquisition ability disturbance induced by BI-D1870. Methods: Male SD rats were randomly divided into control group, solvent control group and BI-D1870 group. The rats in...Aim: To observe the rats’ learning and memory acquisition ability disturbance induced by BI-D1870. Methods: Male SD rats were randomly divided into control group, solvent control group and BI-D1870 group. The rats in the control group were intraperitoneally injected with saline, while those in the solvent control group were intraperitoneally injected with DMSO + sulfobutyl-β-cyclodextrin solvent, and those in the BI-D1870 group were intraperitoneally injected with BI-D1870. All the rats’ appearance and behavior were daily observed, and body weight was recorded on the day 15, 30, 45, 60, 75 and 82 of BI-D1870 injected. Morris water maze was used to screen the rats’ learning and memory acquisition ability on the day 22 - 25, 52 - 55, and 82 - 85 of training by BI-D1870 treated. The successful rates of the rats’ memory impairment were respectively calculated for three times screening. Results: During the whole experiment, there was no obvious difference in appearance and fur color in all rats. The rats’ agitation began to appear on the day 10th of BI-D1870 given. The agitation rats’ number and rats’ body weight gradually increased along with BI-D1870 treated (P P Conclusion: Intraperitoneal injection of BI-D1870 can induce the rats’ learning and memory acquisition ability disorder.展开更多
为实现柔性直流(voltage sourced converter-high voltage direct current,VSC-HVDC)换流阀冷却系统入阀水温的智能预测,文中提出一种基于随机森林(random forest,RF)和双向长短时记忆(bi-directional long short-term memory,BiLSTM)...为实现柔性直流(voltage sourced converter-high voltage direct current,VSC-HVDC)换流阀冷却系统入阀水温的智能预测,文中提出一种基于随机森林(random forest,RF)和双向长短时记忆(bi-directional long short-term memory,BiLSTM)网络混合的柔直换流阀冷却系统入阀水温的预测模型,并以此为基础对柔直换流站阀冷系统的冷却能力进行评估。首先,采用RF算法对由阀冷系统监测变量组成的高维特征集进行重要性分析,筛选出影响入阀水温的重要特征,与历史入阀水温构成输入特征向量。然后,将特征向量输入到BiLSTM预测模型,对模型进行训练并实现对入阀水温的准确预测和冷却能力定量评估。最后,以广东电网某柔直换流站为实例对所提方法进行分析,验证了所提出的基于RF-BiLSTM的混合模型预测精度优于BiLSTM模型、RF模型、支持向量机(support vector machine,SVM)模型和自回归滑动平均模型(auto-regressive and moving average,ARMA)模型,并且实现了冷却能力的定量评估。结果表明该换流站冷却裕量达98%,存在过度冷却、能源浪费的问题,与换流站现场运行情况相符,验证了文中所提方法的有效性和准确性。展开更多
文摘Aim: To observe the rats’ learning and memory acquisition ability disturbance induced by BI-D1870. Methods: Male SD rats were randomly divided into control group, solvent control group and BI-D1870 group. The rats in the control group were intraperitoneally injected with saline, while those in the solvent control group were intraperitoneally injected with DMSO + sulfobutyl-β-cyclodextrin solvent, and those in the BI-D1870 group were intraperitoneally injected with BI-D1870. All the rats’ appearance and behavior were daily observed, and body weight was recorded on the day 15, 30, 45, 60, 75 and 82 of BI-D1870 injected. Morris water maze was used to screen the rats’ learning and memory acquisition ability on the day 22 - 25, 52 - 55, and 82 - 85 of training by BI-D1870 treated. The successful rates of the rats’ memory impairment were respectively calculated for three times screening. Results: During the whole experiment, there was no obvious difference in appearance and fur color in all rats. The rats’ agitation began to appear on the day 10th of BI-D1870 given. The agitation rats’ number and rats’ body weight gradually increased along with BI-D1870 treated (P P Conclusion: Intraperitoneal injection of BI-D1870 can induce the rats’ learning and memory acquisition ability disorder.
文摘为实现柔性直流(voltage sourced converter-high voltage direct current,VSC-HVDC)换流阀冷却系统入阀水温的智能预测,文中提出一种基于随机森林(random forest,RF)和双向长短时记忆(bi-directional long short-term memory,BiLSTM)网络混合的柔直换流阀冷却系统入阀水温的预测模型,并以此为基础对柔直换流站阀冷系统的冷却能力进行评估。首先,采用RF算法对由阀冷系统监测变量组成的高维特征集进行重要性分析,筛选出影响入阀水温的重要特征,与历史入阀水温构成输入特征向量。然后,将特征向量输入到BiLSTM预测模型,对模型进行训练并实现对入阀水温的准确预测和冷却能力定量评估。最后,以广东电网某柔直换流站为实例对所提方法进行分析,验证了所提出的基于RF-BiLSTM的混合模型预测精度优于BiLSTM模型、RF模型、支持向量机(support vector machine,SVM)模型和自回归滑动平均模型(auto-regressive and moving average,ARMA)模型,并且实现了冷却能力的定量评估。结果表明该换流站冷却裕量达98%,存在过度冷却、能源浪费的问题,与换流站现场运行情况相符,验证了文中所提方法的有效性和准确性。
