With the application of Distributed Acoustic Sensors(DAS)across various infrastructures,it will play a pivotal role in shaping smart cities in the future.However,the current single-source detection and identification ...With the application of Distributed Acoustic Sensors(DAS)across various infrastructures,it will play a pivotal role in shaping smart cities in the future.However,the current single-source detection and identification technology might struggle to meet the high precision needs in the intricate environmental conditions of mixed multi-source interference.We propose a new deep neural network-based multi-source signal separation method for DAS and accomplish the separation performance of this method under practical applications.In addition,a new evaluation metric for the separation method is proposed in conjunction with the separation and identification of DAS mixed signals.For mixed signals with different source numbers,the recognizable rate of separated signals can reach 98.33%on average.This study provides a promising solution to the multi-source mixed interference problem faced by DAS in complex environments.展开更多
Objective:Pulmonary hypertension is a crucial factor affecting the recovery after Glenn procedure.This study explores the effects of intravenous treprostinil on hemodynamic status and hospital postoperative recovery u...Objective:Pulmonary hypertension is a crucial factor affecting the recovery after Glenn procedure.This study explores the effects of intravenous treprostinil on hemodynamic status and hospital postoperative recovery under different administration strategies.Methods:We retrospectively included pediatric patients admitted to Fuwai Hospital from 2019 to 2022 who underwent the Glenn procedure and had intraoperative measurements of mean pulmonary artery pressure(mPAP)>15 mmHg postoperatively.Patients with non-anatomical single ventricle physiology undergoing the Glenn procedure and those requiring postoperative extracorporeal membrane oxygenation were excluded.Due to the standardized use of treprostinil in our center starting in 2021,patients from 2019–2020 were included in Group 1,and patients from 2021–2022 were included in Group 2.The changes in hemodynamic data before and after medication for both groups of patients,as well as the differences in postoperative recovery,were compared.Results:Twenty-eight patients were eventually enrolled in the study.Group 1 consisted of 14 cases,with a maintenance dose of 11±2 ng/(kg·min)1 to 2 days postoperatively.Group 2 also consisted of 14 cases,with a maintenance dose of 26±7 ng/(kg·min)1 day postoperatively.After a 24-h observation period,the mPAP decreased from 17±3 to 13±3 mmHg(p<0.001)in the first group and decreased from 18±3 to 13±3 mmHg(p<0.001)in the second group.The vasoactive-inotropic score in the first group decreased from 9(6,17)to 6(4,9)(p=0.001)and decreased from 12(6,23)to 10(3,15)(p=0.002)in the second group.Group 2 patients had a shorter postoperative hospital stay than Group 1,with durations of 18(11,22)days and 29(19,47)days,respectively(p=0.021).No severe adverse reactions occurred in all patients.Conclusion:Intravenous infusion of treprostinil in high-risk patients after the Glenn procedure can decrease pulmonary artery pressure,reduce vasoactive-inotropic score,and demonstrate satisfactory drug tolerance without severe adverse reactions.Standardized use of treprostinil facilitates postoperative recovery and shortens postoperative length of stay.展开更多
Distributed acoustic sensing(DAS)technology is a fiber-optic based distributed sensing technology.It achieves real-time monitoring of acoustic signals by detecting weak disturbances along the fiber.It has advantages s...Distributed acoustic sensing(DAS)technology is a fiber-optic based distributed sensing technology.It achieves real-time monitoring of acoustic signals by detecting weak disturbances along the fiber.It has advantages such as long measurement distance,high spatial resolution and large dynamic range.Artificial intelligence(AI)has great application potential in DAS technology,including data augmentation,preprocessing and classification and recognition of acoustic events.By introducing AI algorithms,DAS system can process massive data more automatically and intelligently.Through data analysis and prediction,AI-enabled DAS technology has wide applications in fields such as transportation,energy and security due to its accuracy of monitoring data and reliability of intelligent decision-making.In the future,the continuous advancement of AI technology will bring greater breakthroughs and innovations for the engineering application of DAS technology,play a more important role in various fields,and promote the innovation and development of the industry.展开更多
文摘With the application of Distributed Acoustic Sensors(DAS)across various infrastructures,it will play a pivotal role in shaping smart cities in the future.However,the current single-source detection and identification technology might struggle to meet the high precision needs in the intricate environmental conditions of mixed multi-source interference.We propose a new deep neural network-based multi-source signal separation method for DAS and accomplish the separation performance of this method under practical applications.In addition,a new evaluation metric for the separation method is proposed in conjunction with the separation and identification of DAS mixed signals.For mixed signals with different source numbers,the recognizable rate of separated signals can reach 98.33%on average.This study provides a promising solution to the multi-source mixed interference problem faced by DAS in complex environments.
基金supported by the Clinical Research Foundation of the National Health Commission of the People’s Republic of China(grant numbers:2022-GSP-GG-32,2022-GSP-QN-13 and 2023-GSP-QN-5).
文摘Objective:Pulmonary hypertension is a crucial factor affecting the recovery after Glenn procedure.This study explores the effects of intravenous treprostinil on hemodynamic status and hospital postoperative recovery under different administration strategies.Methods:We retrospectively included pediatric patients admitted to Fuwai Hospital from 2019 to 2022 who underwent the Glenn procedure and had intraoperative measurements of mean pulmonary artery pressure(mPAP)>15 mmHg postoperatively.Patients with non-anatomical single ventricle physiology undergoing the Glenn procedure and those requiring postoperative extracorporeal membrane oxygenation were excluded.Due to the standardized use of treprostinil in our center starting in 2021,patients from 2019–2020 were included in Group 1,and patients from 2021–2022 were included in Group 2.The changes in hemodynamic data before and after medication for both groups of patients,as well as the differences in postoperative recovery,were compared.Results:Twenty-eight patients were eventually enrolled in the study.Group 1 consisted of 14 cases,with a maintenance dose of 11±2 ng/(kg·min)1 to 2 days postoperatively.Group 2 also consisted of 14 cases,with a maintenance dose of 26±7 ng/(kg·min)1 day postoperatively.After a 24-h observation period,the mPAP decreased from 17±3 to 13±3 mmHg(p<0.001)in the first group and decreased from 18±3 to 13±3 mmHg(p<0.001)in the second group.The vasoactive-inotropic score in the first group decreased from 9(6,17)to 6(4,9)(p=0.001)and decreased from 12(6,23)to 10(3,15)(p=0.002)in the second group.Group 2 patients had a shorter postoperative hospital stay than Group 1,with durations of 18(11,22)days and 29(19,47)days,respectively(p=0.021).No severe adverse reactions occurred in all patients.Conclusion:Intravenous infusion of treprostinil in high-risk patients after the Glenn procedure can decrease pulmonary artery pressure,reduce vasoactive-inotropic score,and demonstrate satisfactory drug tolerance without severe adverse reactions.Standardized use of treprostinil facilitates postoperative recovery and shortens postoperative length of stay.
基金supported in part by Department of Natural Resources of Guangdong Province,grant number GDNRC[2022]No.22Science,Technology and Innovation Commission of Shenzhen Municipality,grant number 20220815121807001+1 种基金Intelligent Laser Basic Research Laboratory,grant number PCL2021A14-B1.Key Basic Research Scheme of Shenzhen Natural Science Foundation(JCYJ20200109142010888)Hong Kong Research Grants Council(RGC)under General Research Fund 15224521.
文摘Distributed acoustic sensing(DAS)technology is a fiber-optic based distributed sensing technology.It achieves real-time monitoring of acoustic signals by detecting weak disturbances along the fiber.It has advantages such as long measurement distance,high spatial resolution and large dynamic range.Artificial intelligence(AI)has great application potential in DAS technology,including data augmentation,preprocessing and classification and recognition of acoustic events.By introducing AI algorithms,DAS system can process massive data more automatically and intelligently.Through data analysis and prediction,AI-enabled DAS technology has wide applications in fields such as transportation,energy and security due to its accuracy of monitoring data and reliability of intelligent decision-making.In the future,the continuous advancement of AI technology will bring greater breakthroughs and innovations for the engineering application of DAS technology,play a more important role in various fields,and promote the innovation and development of the industry.
