Objective:to explore the changes of the F-wave in the posterior tibial nerve of rabbits after different levels of lumbar spinal cord ischaemic injury and its correlation with motor function and the extent of lumbar sp...Objective:to explore the changes of the F-wave in the posterior tibial nerve of rabbits after different levels of lumbar spinal cord ischaemic injury and its correlation with motor function and the extent of lumbar spinal cord pathological damage.Methods:thirty New Zealand rabbits were randomly divided into 6 groups.The control group(n=5)was used to exclude the influence of anaesthesia and surgery on the F-wave.Different levels of lumbar arteries were ligated in the five experimental groups(n=5).The F-wave was recorded to observe the changes in the acute phase of spinal cord ischaemia.The correlation between the changes of the F-wave in the acute reversible phase and the motor function of the spinal cord was analysed.Motor functions were assessed after surgery and 2 d after vascular ligation.The specimens were taken 2 d after ligation for histopathologic observation.Results:the results for the control group indicated that anaesthesia and surgery did not affect the F-wave results.There was no statistically significant difference in the F-wave amplitudes and latency before and after ligation in the 1 and 2 level ligation groups.The F-wave changed immediately after ligation in the 3,4 and 5 ligation groups.The latency of the F-wave gradually extended,the amplitude of the F-wave gradually reduced.The amplitude variations of the F-wave were positively correlated with the motor function 2 d after ligation,there was a statistically significant difference.With the increase in the number of vascular ligation,the degree of destruction of the motor neurons in the anterior horn of the spinal cord in the pathological specimens increased.Conclusion:the F-waves in the posterior tibial nerve of rabbits were found to be sensitive to the lumbar spinal cord ischaemic injury and specific to predict motor function.展开更多
The standard design technology co-optimization(DTCO)involves frequent interactions between circuit design and process manufacturing,which requires several months.To assist designers in establishing a bridge between de...The standard design technology co-optimization(DTCO)involves frequent interactions between circuit design and process manufacturing,which requires several months.To assist designers in establishing a bridge between device parameters and circuit metrics efficiently,and provide guidance for parameter optimization in the early stages of circuit design.In this paper,we propose an efficient machine learning(ML)-enhanced DTCO framework.This framework achieves the co-optimization of device parameters and circuit metrics.We select the gate metal work function(WF)as the parameter to validate the effectiveness of our framework.And the ridge regression approach is used to bypass TCAD simulation,compact model extraction and cell library characterization.We reduces time consumption by at least 92%compared to traditional DTCO framework,while ensuring that errors of delay,internal power consumption and leakage power below 4 ps,0.035mJ,and 0.4μW,respectively.By adjusting the WF,we achieved a better balance between circuit delay and power consumption.This work contributes to designers exploring a broader design space and achieving a efficient DTCO flow.展开更多
基金This work was supported by the funds from the Medical and Health Science and Technology Development Project of Shandong Province,China(grant nos.2015WS0375 and 2019WS125)Scientific and Technological Project of Henan Province,China(grant nos.192102310114 and 192102310110).
文摘Objective:to explore the changes of the F-wave in the posterior tibial nerve of rabbits after different levels of lumbar spinal cord ischaemic injury and its correlation with motor function and the extent of lumbar spinal cord pathological damage.Methods:thirty New Zealand rabbits were randomly divided into 6 groups.The control group(n=5)was used to exclude the influence of anaesthesia and surgery on the F-wave.Different levels of lumbar arteries were ligated in the five experimental groups(n=5).The F-wave was recorded to observe the changes in the acute phase of spinal cord ischaemia.The correlation between the changes of the F-wave in the acute reversible phase and the motor function of the spinal cord was analysed.Motor functions were assessed after surgery and 2 d after vascular ligation.The specimens were taken 2 d after ligation for histopathologic observation.Results:the results for the control group indicated that anaesthesia and surgery did not affect the F-wave results.There was no statistically significant difference in the F-wave amplitudes and latency before and after ligation in the 1 and 2 level ligation groups.The F-wave changed immediately after ligation in the 3,4 and 5 ligation groups.The latency of the F-wave gradually extended,the amplitude of the F-wave gradually reduced.The amplitude variations of the F-wave were positively correlated with the motor function 2 d after ligation,there was a statistically significant difference.With the increase in the number of vascular ligation,the degree of destruction of the motor neurons in the anterior horn of the spinal cord in the pathological specimens increased.Conclusion:the F-waves in the posterior tibial nerve of rabbits were found to be sensitive to the lumbar spinal cord ischaemic injury and specific to predict motor function.
基金supported by the Cooperation Project between Xidian University and Shenzhen Fuxin Technology Company Ltd.(Electronic Design Automation Technology Innovation Center Project in Guangdong-Hong Kong Macao Greater Bay Area)well as by the Project of Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory(6142806230302).
文摘The standard design technology co-optimization(DTCO)involves frequent interactions between circuit design and process manufacturing,which requires several months.To assist designers in establishing a bridge between device parameters and circuit metrics efficiently,and provide guidance for parameter optimization in the early stages of circuit design.In this paper,we propose an efficient machine learning(ML)-enhanced DTCO framework.This framework achieves the co-optimization of device parameters and circuit metrics.We select the gate metal work function(WF)as the parameter to validate the effectiveness of our framework.And the ridge regression approach is used to bypass TCAD simulation,compact model extraction and cell library characterization.We reduces time consumption by at least 92%compared to traditional DTCO framework,while ensuring that errors of delay,internal power consumption and leakage power below 4 ps,0.035mJ,and 0.4μW,respectively.By adjusting the WF,we achieved a better balance between circuit delay and power consumption.This work contributes to designers exploring a broader design space and achieving a efficient DTCO flow.
