Objective To investigate the desensitization of acetylcholine (ACh) on the inhibition effects of blood pressure (BP) in anesthe tized canine and build a model for studying desensitization in vivo. Methods Through ...Objective To investigate the desensitization of acetylcholine (ACh) on the inhibition effects of blood pressure (BP) in anesthe tized canine and build a model for studying desensitization in vivo. Methods Through changing the intervals (120, 100, 80, 60, 40, 20 seconds) of twice ACh administration (each was 15μg·kg -1,i.v.), the desensitization on the effect of systemic blood pressure of the first ACh in jection towards the subsequent ACh administration was observed. Results When ACh administration intervals were 40, 60, 80 , 100 seconds, the percentages of desensitization of ACh on systemic blood press ure were significantly increased (P<0.05). However, as the intervals were 20 and 120 seconds, the effects of twice ACh administration had no significant dif ference (P>0.05). Conclusion The results indicated that ACh contents in blo od might influence the action of next ACh administration. To some extent, the hi gher the concentration of ACh in blood, the bigger the ratio of desensitization of exogenous ACh is. In addition, this method of twice drug administration could be used as a model of studying desensitization in vivo.展开更多
Ground fi ssure is a geological hazard that poses a great threat to human life and,property and the environment.Therefore,it is necessary to detect shallow underground fi ssures eff ectively.In this paper,a time-frequ...Ground fi ssure is a geological hazard that poses a great threat to human life and,property and the environment.Therefore,it is necessary to detect shallow underground fi ssures eff ectively.In this paper,a time-frequency analysis of Rayleigh waves based on the wavelet transform is proposed to detect shallow underground fi ssures.The arrival time of the directed Rayleigh waves and the diff racted Rayleigh waves from the underground fi ssure is extracted from the time-frequency spectrum of any two traces.Furthermore,the locations of the underground fissures are calculated according to the time difference relation.Four sets of fracture models and one set of fi eld data were used to test the eff ectiveness of the wavelet transform of Rayleigh waves.Moreover,the detection results of the actual data are compared with that of the high-density electrical method to further prove its detection eff ect.The fi eld investigation shows that using the wavelet transform of Rayleigh waves to detect shallow underground fi ssures is feasible and eff ective.展开更多
Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological b...Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological background in the study area,dip-steering cube operation and median filtering of seismic data were performed using fast Fourier transform to improve the continuity of seismic events and eliminate random noise.A total of 200 stratigraphic continuous sample training points and 500 discontinuous training points were obtained from the processed seismic data.Thereafter,a variety of attributes(coherence,curvature,amplitude,frequency,etc.)were extracted as the input for the multilayer perceptron neural network training.During the training period,the training results were traced by normalized root mean square error(RMSE)and misclassifi cation.The training results showed a downward trend during the training period.The misclassifi cation curve was stable at 0.3,and the normalized RMSE curve was stable at 0.68.When the value of the normalized RMSE curve reached the minimum,the training was terminated,and the training results were extended to the whole data volume to obtain the attribute cube of intelligent ground fi ssure detection.The characteristics of ground fi ssures were analyzed and identifi ed from the sections and slices.A total of 11 ground fissures were finally interpreted.The interpretation results showed that the dip angles were 60°-85°,the fault throws were 0-43 m,and the extension lengths were 300-1,100 m in the whole area.The strike of 73%of the ground fi ssures was consistent with the direction of the regional tectonic settings.Specifi cally,four ground fi ssures coincided with the surface disclosed,and the verifi cation rate reached 100%.In conclusion,the intelligent ground fi ssure detection attribute based on the dip-steering cube is eff ective in predicting the spatial distribution of ground fi ssures.展开更多
文摘Objective To investigate the desensitization of acetylcholine (ACh) on the inhibition effects of blood pressure (BP) in anesthe tized canine and build a model for studying desensitization in vivo. Methods Through changing the intervals (120, 100, 80, 60, 40, 20 seconds) of twice ACh administration (each was 15μg·kg -1,i.v.), the desensitization on the effect of systemic blood pressure of the first ACh in jection towards the subsequent ACh administration was observed. Results When ACh administration intervals were 40, 60, 80 , 100 seconds, the percentages of desensitization of ACh on systemic blood press ure were significantly increased (P<0.05). However, as the intervals were 20 and 120 seconds, the effects of twice ACh administration had no significant dif ference (P>0.05). Conclusion The results indicated that ACh contents in blo od might influence the action of next ACh administration. To some extent, the hi gher the concentration of ACh in blood, the bigger the ratio of desensitization of exogenous ACh is. In addition, this method of twice drug administration could be used as a model of studying desensitization in vivo.
基金supported by the National Natural Science Foundation of China (Grant Nos. 41874123,41004043)fundamental research funds for the central universities (Grant Nos. 300102268401,300102268402)。
文摘Ground fi ssure is a geological hazard that poses a great threat to human life and,property and the environment.Therefore,it is necessary to detect shallow underground fi ssures eff ectively.In this paper,a time-frequency analysis of Rayleigh waves based on the wavelet transform is proposed to detect shallow underground fi ssures.The arrival time of the directed Rayleigh waves and the diff racted Rayleigh waves from the underground fi ssure is extracted from the time-frequency spectrum of any two traces.Furthermore,the locations of the underground fissures are calculated according to the time difference relation.Four sets of fracture models and one set of fi eld data were used to test the eff ectiveness of the wavelet transform of Rayleigh waves.Moreover,the detection results of the actual data are compared with that of the high-density electrical method to further prove its detection eff ect.The fi eld investigation shows that using the wavelet transform of Rayleigh waves to detect shallow underground fi ssures is feasible and eff ective.
基金The study was supported by Open Fund of State Key Laboratory of Coal Resources and Safe Mining(Grant No.SKLCRSM19ZZ02)the National Natural Science Foundation of China(No.41702173)。
文摘Taking a study area in Jinzhong Basin in Qixian County,Shanxi Province,as an example,this work performs an intelligent interpretation of ground fissures.On the basis of a complete analysis of the regional geological background in the study area,dip-steering cube operation and median filtering of seismic data were performed using fast Fourier transform to improve the continuity of seismic events and eliminate random noise.A total of 200 stratigraphic continuous sample training points and 500 discontinuous training points were obtained from the processed seismic data.Thereafter,a variety of attributes(coherence,curvature,amplitude,frequency,etc.)were extracted as the input for the multilayer perceptron neural network training.During the training period,the training results were traced by normalized root mean square error(RMSE)and misclassifi cation.The training results showed a downward trend during the training period.The misclassifi cation curve was stable at 0.3,and the normalized RMSE curve was stable at 0.68.When the value of the normalized RMSE curve reached the minimum,the training was terminated,and the training results were extended to the whole data volume to obtain the attribute cube of intelligent ground fi ssure detection.The characteristics of ground fi ssures were analyzed and identifi ed from the sections and slices.A total of 11 ground fissures were finally interpreted.The interpretation results showed that the dip angles were 60°-85°,the fault throws were 0-43 m,and the extension lengths were 300-1,100 m in the whole area.The strike of 73%of the ground fi ssures was consistent with the direction of the regional tectonic settings.Specifi cally,four ground fi ssures coincided with the surface disclosed,and the verifi cation rate reached 100%.In conclusion,the intelligent ground fi ssure detection attribute based on the dip-steering cube is eff ective in predicting the spatial distribution of ground fi ssures.
