Rotory high temperature superconducting(HTS)flux pumps can consistently generate a DC voltage by rotating magnets over superconducting tapes,and thus energize the circuit if a closed loop is formed.The voltage output ...Rotory high temperature superconducting(HTS)flux pumps can consistently generate a DC voltage by rotating magnets over superconducting tapes,and thus energize the circuit if a closed loop is formed.The voltage output is a crucial factor to reflect the performance of such an HTS flux pump,which is determined by a set of design specifications,and some of them have been investigated extensively in the current literature.However,no work has been done yet to study the HTS dynamo output voltage by efficiently integrating all the design parameters together.In this paper,a well‐trained deep‐learning neuron network(DNN)with back‐propagation algorithms has been put forward and validated.The proposed DNN is capable of quantifying the output voltage of an HTS dynamo instantly with an overall accuracy of approximately 98%with respect to the simulated values with all design parameters explicitly specified.The model possesses a powerful ability to characterize the output behavior of HTS dynamos by considering multiple design parameters,e.g.,airgap,superconductor tape width,operating frequency,remanent flux density,rotor radius,and permanent magnet width,which have covered all the typical design considerations.The output characteristics of an HTS dynamo against each of the design parameters have been successfully demonstrated using this model.Compared to conventional time‐consuming finite element method(FEM)based numerical models,the proposed DNN model has the advantages of automatic learning,fast computation,as well as strong programmability.Therefore the DNN model can greatly facilitate the design and optimization process for HTS dynamos.An executable application has been developed accordingly based on the DNN model,which is believed to provide a useful tool for learners and designers of HTS dynamos.展开更多
Theophylline(TP)is a very well established orally or intravenously delivered antiasthma drug with many beneficial effects.This study aims to improve asthma treatment by creating a dry powder inhalable(DPI)formulation ...Theophylline(TP)is a very well established orally or intravenously delivered antiasthma drug with many beneficial effects.This study aims to improve asthma treatment by creating a dry powder inhalable(DPI)formulation of TP to be delivered directly to the lung,avoiding the side effects associated with conventional oral delivery.The DPI TP formulation was investigated for its physico-chemical characteristics using scanning electron microscopy,laser diffraction,thermal analysis and dynamic vapour sorption.Furthermore,aerosol performance was assessed using the Multi Stage Liquid Impinger(MSLI).In addition,a Calu-3 cell transport assay was conducted in vitro using a modified ACI to study the impact of the DPI formulation on lung epithelial cells.Results showed DPI TP to be physico-chemically stable and of an aerodynamic size suitable for lung delivery.The aerosolisation performance analysis showed the TP DPI formulation to have a fine particle fraction of 29.70±2.59%(P<0.05)for the TP formulation containing 1.0%(w/w)sodium stearate,the most efficient for aerosolisation.Regarding the deposition of TP DPI on Calu-3 cells using the modified ACI,results demonstrated that 56.14±7.62%of the total TP deposited(13.07±1.69μg)was transported across the Calu-3 monolayer over 180 min following deposition,while 37.05±12.62%of the deposited TP was retained in the cells.This could be due to the presence of sodium stearate in the current formulation that increased its lipophilicity.A DPI formulation of TP was developed that was shown to be suitable for inhalation.展开更多
文摘Rotory high temperature superconducting(HTS)flux pumps can consistently generate a DC voltage by rotating magnets over superconducting tapes,and thus energize the circuit if a closed loop is formed.The voltage output is a crucial factor to reflect the performance of such an HTS flux pump,which is determined by a set of design specifications,and some of them have been investigated extensively in the current literature.However,no work has been done yet to study the HTS dynamo output voltage by efficiently integrating all the design parameters together.In this paper,a well‐trained deep‐learning neuron network(DNN)with back‐propagation algorithms has been put forward and validated.The proposed DNN is capable of quantifying the output voltage of an HTS dynamo instantly with an overall accuracy of approximately 98%with respect to the simulated values with all design parameters explicitly specified.The model possesses a powerful ability to characterize the output behavior of HTS dynamos by considering multiple design parameters,e.g.,airgap,superconductor tape width,operating frequency,remanent flux density,rotor radius,and permanent magnet width,which have covered all the typical design considerations.The output characteristics of an HTS dynamo against each of the design parameters have been successfully demonstrated using this model.Compared to conventional time‐consuming finite element method(FEM)based numerical models,the proposed DNN model has the advantages of automatic learning,fast computation,as well as strong programmability.Therefore the DNN model can greatly facilitate the design and optimization process for HTS dynamos.An executable application has been developed accordingly based on the DNN model,which is believed to provide a useful tool for learners and designers of HTS dynamos.
基金Professor Young is the recipient of an Australian Research Council Future Fellowship(project number FT110100996)Associate Professor Traini is the recipient of an Australian Research Council Future Fellowship(project number FT12010063).
文摘Theophylline(TP)is a very well established orally or intravenously delivered antiasthma drug with many beneficial effects.This study aims to improve asthma treatment by creating a dry powder inhalable(DPI)formulation of TP to be delivered directly to the lung,avoiding the side effects associated with conventional oral delivery.The DPI TP formulation was investigated for its physico-chemical characteristics using scanning electron microscopy,laser diffraction,thermal analysis and dynamic vapour sorption.Furthermore,aerosol performance was assessed using the Multi Stage Liquid Impinger(MSLI).In addition,a Calu-3 cell transport assay was conducted in vitro using a modified ACI to study the impact of the DPI formulation on lung epithelial cells.Results showed DPI TP to be physico-chemically stable and of an aerodynamic size suitable for lung delivery.The aerosolisation performance analysis showed the TP DPI formulation to have a fine particle fraction of 29.70±2.59%(P<0.05)for the TP formulation containing 1.0%(w/w)sodium stearate,the most efficient for aerosolisation.Regarding the deposition of TP DPI on Calu-3 cells using the modified ACI,results demonstrated that 56.14±7.62%of the total TP deposited(13.07±1.69μg)was transported across the Calu-3 monolayer over 180 min following deposition,while 37.05±12.62%of the deposited TP was retained in the cells.This could be due to the presence of sodium stearate in the current formulation that increased its lipophilicity.A DPI formulation of TP was developed that was shown to be suitable for inhalation.
