For direct wave energy conversion in a two dimensional(2D) way, this paper proposes a planar, direct-drive generator based on switched reluctance principle. The proposed machine has the merit of a simple and robust st...For direct wave energy conversion in a two dimensional(2D) way, this paper proposes a planar, direct-drive generator based on switched reluctance principle. The proposed machine has the merit of a simple and robust structure and it is very suitable for the operation under hostile environment in the ocean. This paper first presents the design and construction of the generator. Then, performance prediction of the generator based on three dimensional(3D) time-stepping finite element methods(FEM) and power generation investigation from co-simulation are carried out. Next, preliminary generation current waveforms are inspected by the regulation of turn-on and turn-off positions based on FEM and verified by experimental results. Last, the voltage output waveform of any one axis of motion is also presented.展开更多
In this work, a series of Cu2O-Ag/ZnO, Cu2O/ZnO and Ag/ZnO nanocomposites with various compositions were prepared via a hydrothermal method followed by chemical modification, and their antibacterial performance was in...In this work, a series of Cu2O-Ag/ZnO, Cu2O/ZnO and Ag/ZnO nanocomposites with various compositions were prepared via a hydrothermal method followed by chemical modification, and their antibacterial performance was investigated in detail. X-ray powder diffraction, scanning electron microscopy and transmission electron microscopy results confirmed that 31 nm Cu20 and 30 nm Ag nanoparticles are well-dispersed on 202 nm ZnO grains to form a Cu2O/ZnO and Ag/ZnO heterojunction, respectively. The bi-heterojuction structure in the Cu20-Ag/ZnO provided a synergistic effect on antibacterial activity, and the(Cu2O)0.04Ag0.06ZnO0.9nanocomposites showed the highest antimicrobial activity of all samples with minimum inhibitory concentration and minimum bactericidal concentration against Escherichia coli and Staphylococcus aureus as low to 31.25 μg/mL, 250μg/mL, 125μg/mL and 500μg/mL, respectively. This is the first report of the antibacterial activities of Cu2O and Ag co-modified ZnO nanocomposites.展开更多
The issue of unoccupied or abandoned homesteads(courtyards)in China emerges given the increasing aging population,rapid urbanization and massive rural-urban migration.From the aspect of rural vitalization,land-use pla...The issue of unoccupied or abandoned homesteads(courtyards)in China emerges given the increasing aging population,rapid urbanization and massive rural-urban migration.From the aspect of rural vitalization,land-use planning,and policy making,determining the number of unoccupied courtyards is important.Field and questionnaire-based surveys were currently the main approaches,but these traditional methods were often expensive and laborious.A new workflow is explored using deep learning and machine learning algorithms on unmanned aerial vehicle(UAV)images.Initially,features of the built environment were extracted using deep learning to evaluate the courtyard management,including extracting complete or collapsed farmhouses by Alexnet,detecting solar water heaters by YOLOv5s,calculating green looking ratio(GLR)by FCN.Their precisions exceeded 98%.Then,seven machine learning algorithms(Adaboost,binomial logistic regression,neural network,random forest,support vector machine,decision trees,and XGBoost algorithms)were applied to identify the rural courtyards’utilization status.The Adaboost algorithm showed the best performance with the comprehensive consideration of most metrics(Accuracy:0.933,Precision:0.932,Recall:0.984,F1-score:0.957).Results showed that identifying the courtyards’utilization statuses based on the courtyard built environment is feasible.It is transferable and cost-effective for large-scale village surveys,and may contribute to the intensive and sustainable approach to rural land use.展开更多
文摘For direct wave energy conversion in a two dimensional(2D) way, this paper proposes a planar, direct-drive generator based on switched reluctance principle. The proposed machine has the merit of a simple and robust structure and it is very suitable for the operation under hostile environment in the ocean. This paper first presents the design and construction of the generator. Then, performance prediction of the generator based on three dimensional(3D) time-stepping finite element methods(FEM) and power generation investigation from co-simulation are carried out. Next, preliminary generation current waveforms are inspected by the regulation of turn-on and turn-off positions based on FEM and verified by experimental results. Last, the voltage output waveform of any one axis of motion is also presented.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.51677120 and 51207093)the Shenzhen Government Fund(Grant Nos.JCYJ20160422102919963)the Shenzhen Key Laboratory of Special Functional Materials(Grant Nos.T201502)
文摘In this work, a series of Cu2O-Ag/ZnO, Cu2O/ZnO and Ag/ZnO nanocomposites with various compositions were prepared via a hydrothermal method followed by chemical modification, and their antibacterial performance was investigated in detail. X-ray powder diffraction, scanning electron microscopy and transmission electron microscopy results confirmed that 31 nm Cu20 and 30 nm Ag nanoparticles are well-dispersed on 202 nm ZnO grains to form a Cu2O/ZnO and Ag/ZnO heterojunction, respectively. The bi-heterojuction structure in the Cu20-Ag/ZnO provided a synergistic effect on antibacterial activity, and the(Cu2O)0.04Ag0.06ZnO0.9nanocomposites showed the highest antimicrobial activity of all samples with minimum inhibitory concentration and minimum bactericidal concentration against Escherichia coli and Staphylococcus aureus as low to 31.25 μg/mL, 250μg/mL, 125μg/mL and 500μg/mL, respectively. This is the first report of the antibacterial activities of Cu2O and Ag co-modified ZnO nanocomposites.
基金the project“National Key Research and Development Program of China,No.2018YFD1100803”.
文摘The issue of unoccupied or abandoned homesteads(courtyards)in China emerges given the increasing aging population,rapid urbanization and massive rural-urban migration.From the aspect of rural vitalization,land-use planning,and policy making,determining the number of unoccupied courtyards is important.Field and questionnaire-based surveys were currently the main approaches,but these traditional methods were often expensive and laborious.A new workflow is explored using deep learning and machine learning algorithms on unmanned aerial vehicle(UAV)images.Initially,features of the built environment were extracted using deep learning to evaluate the courtyard management,including extracting complete or collapsed farmhouses by Alexnet,detecting solar water heaters by YOLOv5s,calculating green looking ratio(GLR)by FCN.Their precisions exceeded 98%.Then,seven machine learning algorithms(Adaboost,binomial logistic regression,neural network,random forest,support vector machine,decision trees,and XGBoost algorithms)were applied to identify the rural courtyards’utilization status.The Adaboost algorithm showed the best performance with the comprehensive consideration of most metrics(Accuracy:0.933,Precision:0.932,Recall:0.984,F1-score:0.957).Results showed that identifying the courtyards’utilization statuses based on the courtyard built environment is feasible.It is transferable and cost-effective for large-scale village surveys,and may contribute to the intensive and sustainable approach to rural land use.
