As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The ...As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.展开更多
A novel strategy was developed to fabricate FeNx-doped carbon quantum dots(Fe-N-CQDs)to detect Cu^(2+) ions selectively as a fluorescence probe.The Fe-N-CQDs were synthesized by an efficient electrolysis of a carbon c...A novel strategy was developed to fabricate FeNx-doped carbon quantum dots(Fe-N-CQDs)to detect Cu^(2+) ions selectively as a fluorescence probe.The Fe-N-CQDs were synthesized by an efficient electrolysis of a carbon cloth electrode,which was coated with monoatomic ironanchored nitrogen-doped carbon(Fe-N-C).The obtained Fe-N-CQDs emitted blue fluorescence and possessed a quantum yield(QY)of 7.5%.An extremely wide linear relationship between the Cu^(2+) concentration and the fluorescence intensity was obtained in the range from 100 nmol L^(-1) to 1000 nmol L^(-1)(R^(2)=0.997),and the detection limit was calculated as 59 nmol L^(-1).Moreover,the Fe-N-CQDs demonstrated wide range pH compatibility between 2 and 13 due to the coordination between pyridine nitrogen and Fe^(3+),which dramatically reduced the affection of the protonation and deprotonation process between H^(+) and Fe-N-CQDs.It is notable that the Fe-N-CQDs exhibited a rapid response in Cu^(2+) detection,where stable quenching can be completed in 7 s.The mechanism of excellent selective detection of Cu^(2+) was revealed by energy level simulation that the LUMO level of Fe-N-CQDs(-4.37 eV)was close to the redox potential of Cu^(2+),thus facilitating the electron transport from Fe-N-CQDs to Cu^(2+).展开更多
Dry powder inhalers(DPIs) had been widely used in lung diseases on account of direct pulmonary delivery, good drug stability and satisfactory patient compliance. However, an indistinct understanding of pulmonary deliv...Dry powder inhalers(DPIs) had been widely used in lung diseases on account of direct pulmonary delivery, good drug stability and satisfactory patient compliance. However, an indistinct understanding of pulmonary delivery processes(PDPs) hindered the development of DPIs. Most current evaluation methods explored the PDPs with over-simplified models, leading to uncompleted investigations of the whole or partial PDPs. In the present research, an innovative modular process analysis platform(MPAP) was applied to investigate the detailed mechanisms of each PDP of DPIs with different carrier particle sizes(CPS). The MPAP was composed of a laser particle size analyzer, an inhaler device,an artificial throat and a pre-separator, to investigate the fluidization and dispersion, transportation,detachment and deposition process of DPIs. The release profiles of drug, drug aggregation and carrier were monitored in real-time. The influence of CPS on PDPs and corresponding mechanisms were explored. The powder properties of the carriers were investigated by the optical profiler and Freeman Technology four powder rheometer. The next generation impactor was employed to explore the aerosolization performance of DPIs. The novel MPAP was successfully applied in exploring the comprehensive mechanism of PDPs, which had enormous potential to be used to investigate and develop DPIs.展开更多
基金supported by the Meteorological Soft Science Project(Grant No.2023ZZXM29)the Natural Science Fund Project of Tianjin,China(Grant No.21JCYBJC00740)the Key Research and Development-Social Development Program of Jiangsu Province,China(Grant No.BE2021685).
文摘As the risks associated with air turbulence are intensified by climate change and the growth of the aviation industry,it has become imperative to monitor and mitigate these threats to ensure civil aviation safety.The eddy dissipation rate(EDR)has been established as the standard metric for quantifying turbulence in civil aviation.This study aims to explore a universally applicable symbolic classification approach based on genetic programming to detect turbulence anomalies using quick access recorder(QAR)data.The detection of atmospheric turbulence is approached as an anomaly detection problem.Comparative evaluations demonstrate that this approach performs on par with direct EDR calculation methods in identifying turbulence events.Moreover,comparisons with alternative machine learning techniques indicate that the proposed technique is the optimal methodology currently available.In summary,the use of symbolic classification via genetic programming enables accurate turbulence detection from QAR data,comparable to that with established EDR approaches and surpassing that achieved with machine learning algorithms.This finding highlights the potential of integrating symbolic classifiers into turbulence monitoring systems to enhance civil aviation safety amidst rising environmental and operational hazards.
基金the National Natural Science Foundation of China(Nos.21776302 and 21776308)the Science Foundation of China University of Petroleum,Beijing(No.2462020YXZZ033).
文摘A novel strategy was developed to fabricate FeNx-doped carbon quantum dots(Fe-N-CQDs)to detect Cu^(2+) ions selectively as a fluorescence probe.The Fe-N-CQDs were synthesized by an efficient electrolysis of a carbon cloth electrode,which was coated with monoatomic ironanchored nitrogen-doped carbon(Fe-N-C).The obtained Fe-N-CQDs emitted blue fluorescence and possessed a quantum yield(QY)of 7.5%.An extremely wide linear relationship between the Cu^(2+) concentration and the fluorescence intensity was obtained in the range from 100 nmol L^(-1) to 1000 nmol L^(-1)(R^(2)=0.997),and the detection limit was calculated as 59 nmol L^(-1).Moreover,the Fe-N-CQDs demonstrated wide range pH compatibility between 2 and 13 due to the coordination between pyridine nitrogen and Fe^(3+),which dramatically reduced the affection of the protonation and deprotonation process between H^(+) and Fe-N-CQDs.It is notable that the Fe-N-CQDs exhibited a rapid response in Cu^(2+) detection,where stable quenching can be completed in 7 s.The mechanism of excellent selective detection of Cu^(2+) was revealed by energy level simulation that the LUMO level of Fe-N-CQDs(-4.37 eV)was close to the redox potential of Cu^(2+),thus facilitating the electron transport from Fe-N-CQDs to Cu^(2+).
基金funded by the Fundamental Research Funds for the Central Universities(Nos.21620434 and 2162014,China)the National Natural Science Foundation of China(Nos.81673375 and 81703431)+1 种基金the Science and Technology Foundation Guangzhou(No.201509030006,China)the National Students Innovation Training Program of China(No.201901390,China)。
文摘Dry powder inhalers(DPIs) had been widely used in lung diseases on account of direct pulmonary delivery, good drug stability and satisfactory patient compliance. However, an indistinct understanding of pulmonary delivery processes(PDPs) hindered the development of DPIs. Most current evaluation methods explored the PDPs with over-simplified models, leading to uncompleted investigations of the whole or partial PDPs. In the present research, an innovative modular process analysis platform(MPAP) was applied to investigate the detailed mechanisms of each PDP of DPIs with different carrier particle sizes(CPS). The MPAP was composed of a laser particle size analyzer, an inhaler device,an artificial throat and a pre-separator, to investigate the fluidization and dispersion, transportation,detachment and deposition process of DPIs. The release profiles of drug, drug aggregation and carrier were monitored in real-time. The influence of CPS on PDPs and corresponding mechanisms were explored. The powder properties of the carriers were investigated by the optical profiler and Freeman Technology four powder rheometer. The next generation impactor was employed to explore the aerosolization performance of DPIs. The novel MPAP was successfully applied in exploring the comprehensive mechanism of PDPs, which had enormous potential to be used to investigate and develop DPIs.
